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perfect-postcode/price_model.ipynb
Andras Schmelczer c38d654ac7 Fmt
2026-03-15 21:22:28 +00:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "5c1271a9",
"metadata": {},
"source": [
"# Price Model\n",
"\n",
"Aim: estimate current prices of a property, given historical data\n",
"Assumptions:\n",
"- parallel trends\n",
"- only heterogenious effects exist between Postcodes "
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "b4bc1a1e",
"metadata": {},
"outputs": [],
"source": [
"import polars as pl\n",
"import pandas as pd\n",
"\n",
"import random\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"\n",
"pd.set_option(\"display.max_columns\", None)\n",
"pd.set_option(\"display.max_colwidth\", 60)"
]
},
{
"cell_type": "markdown",
"id": "6b103e9e",
"metadata": {},
"source": [
"# PARAMETERS"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "c30127d3",
"metadata": {},
"outputs": [],
"source": [
"param_import_path = \"/bulk/wide-2.parquet\"\n",
"\n",
"param_lookback = 3"
]
},
{
"cell_type": "markdown",
"id": "f3268e1d",
"metadata": {},
"source": [
"# EXPLORE"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "c27367e0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"shape: (1, 1)\n",
"┌──────────┐\n",
"│ len │\n",
"│ --- │\n",
"│ u32 │\n",
"╞══════════╡\n",
"│ 12718926 │\n",
"└──────────┘\n"
]
},
{
"data": {
"text/html": [
"<div><style>\n",
".dataframe > thead > tr,\n",
".dataframe > tbody > tr {\n",
" text-align: right;\n",
" white-space: pre-wrap;\n",
"}\n",
"</style>\n",
"<small>shape: (5, 54)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>Address per Property Register</th><th>Postcode</th><th>historical_prices</th><th>Leashold/Freehold</th><th>Last known price</th><th>Address per EPC</th><th>Current energy rating</th><th>Potential energy rating</th><th>Property type</th><th>Total floor area (sqm)</th><th>Rooms (including bedrooms &amp; bathrooms)</th><th>Approximate construction age</th><th>lat</th><th>lon</th><th>public_transport_easy_minutes</th><th>public_transport_quick_minutes</th><th>cycling_minutes</th><th>Index of Multiple Deprivation (IMD) Score</th><th>Income Score (rate)</th><th>Employment Score (rate)</th><th>Education, Skills and Training Score</th><th>Health Deprivation and Disability Score</th><th>Crime Score</th><th>Living Environment Score</th><th>Indoors Sub-domain Score</th><th>Outdoors Sub-domain Score</th><th>% Asian</th><th>% Black</th><th>% Mixed</th><th>% White</th><th>% Other</th><th>Possession of weapons (avg/yr)</th><th>Public order (avg/yr)</th><th>Criminal damage and arson (avg/yr)</th><th>Anti-social behaviour (avg/yr)</th><th>Robbery (avg/yr)</th><th>Violence and sexual offences (avg/yr)</th><th>Other theft (avg/yr)</th><th>Other crime (avg/yr)</th><th>Burglary (avg/yr)</th><th>Bicycle theft (avg/yr)</th><th>Drugs (avg/yr)</th><th>Vehicle crime (avg/yr)</th><th>Shoplifting (avg/yr)</th><th>Theft from the person (avg/yr)</th><th>Restaurants within 2km</th><th>Groceries within 2km</th><th>Parks within 2km</th><th>Public transport within 2km</th><th>Good+ primary schools within 2km</th><th>Good+ secondary schools within 2km</th><th>Max available download speed (Mbps)</th><th>Property type/built form</th><th>Price per sqm</th></tr><tr><td>str</td><td>str</td><td>list[struct[2]]</td><td>str</td><td>i64</td><td>str</td><td>str</td><td>str</td><td>str</td><td>f64</td><td>i64</td><td>u16</td><td>f64</td><td>f64</td><td>i64</td><td>i64</td><td>i64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>f64</td><td>i32</td><td>i32</td><td>i32</td><td>i32</td><td>i32</td><td>i32</td><td>u16</td><td>str</td><td>i32</td></tr></thead><tbody><tr><td>&quot; 20 FORESTERS DRIVE&quot;</td><td>&quot;E17 3PG&quot;</td><td>[{2018,685000}]</td><td>&quot;Freehold&quot;</td><td>685000</td><td>&quot;20, Foresters Drive&quot;</td><td>&quot;E&quot;</td><td>&quot;B&quot;</td><td>&quot;House&quot;</td><td>147.0</td><td>5</td><td>1930</td><td>51.583423</td><td>0.00242</td><td>70</td><td>33</td><td>32</td><td>33.406</td><td>0.442</td><td>0.191</td><td>19.015</td><td>0.188</td><td>0.543</td><td>32.45</td><td>-0.078</td><td>1.645</td><td>19.9</td><td>15.0</td><td>6.5</td><td>52.8</td><td>5.8</td><td>null</td><td>13.7</td><td>9.2</td><td>77.5</td><td>4.7</td><td>47.2</td><td>15.0</td><td>2.5</td><td>8.5</td><td>5.0</td><td>8.0</td><td>19.3</td><td>2.5</td><td>6.7</td><td>88</td><td>43</td><td>0</td><td>142</td><td>15</td><td>5</td><td>1000</td><td>&quot;Semi-Detached&quot;</td><td>4660</td></tr><tr><td>&quot; 12 PENTLE DRIVE&quot;</td><td>&quot;SA69 9BW&quot;</td><td>[{2014,160000}]</td><td>&quot;Freehold&quot;</td><td>160000</td><td>&quot;12, Pentle Drive, Pentlepoir&quot;</td><td>&quot;E&quot;</td><td>&quot;C&quot;</td><td>&quot;Bungalow&quot;</td><td>79.0</td><td>4</td><td>1967</td><td>51.722784</td><td>-4.72585</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>2.0</td><td>2.5</td><td>4.3</td><td>2.0</td><td>1.0</td><td>18.5</td><td>5.0</td><td>1.5</td><td>2.3</td><td>null</td><td>2.0</td><td>null</td><td>1.0</td><td>null</td><td>0</td><td>0</td><td>0</td><td>2</td><td>0</td><td>0</td><td>30</td><td>&quot;Semi-Detached&quot;</td><td>2025</td></tr><tr><td>&quot; 107 BRAMPTON CLOSE&quot;</td><td>&quot;SS17 7NR&quot;</td><td>[{2018,337500}]</td><td>&quot;Freehold&quot;</td><td>337500</td><td>&quot;107, Brampton Close, Corringha…</td><td>&quot;D&quot;</td><td>&quot;B&quot;</td><td>&quot;House&quot;</td><td>97.0</td><td>6</td><td>1967</td><td>51.531787</td><td>0.452354</td><td>87</td><td>78</td><td>123</td><td>14.436</td><td>0.162</td><td>0.086</td><td>23.035</td><td>-0.796</td><td>-0.174</td><td>17.084</td><td>-0.088</td><td>0.186</td><td>6.9</td><td>11.9</td><td>3.0</td><td>76.7</td><td>1.5</td><td>2.0</td><td>10.7</td><td>8.5</td><td>7.0</td><td>1.3</td><td>23.5</td><td>10.5</td><td>4.0</td><td>2.0</td><td>1.0</td><td>6.5</td><td>12.2</td><td>2.2</td><td>null</td><td>13</td><td>5</td><td>0</td><td>0</td><td>5</td><td>0</td><td>1000</td><td>&quot;Semi-Detached&quot;</td><td>3479</td></tr><tr><td>&quot; 5 CRAIGMORE COURT&quot;</td><td>&quot;PO37 6HH&quot;</td><td>[{1995,50000}, {2000,82000}, … {2012,167000}]</td><td>&quot;Leasehold&quot;</td><td>167000</td><td>&quot;5, Craigmore Court&quot;</td><td>&quot;E&quot;</td><td>&quot;C&quot;</td><td>&quot;Flat&quot;</td><td>77.43</td><td>3</td><td>1967</td><td>50.637558</td><td>-1.171078</td><td>null</td><td>null</td><td>null</td><td>31.108</td><td>0.331</td><td>0.225</td><td>34.047</td><td>0.997</td><td>-0.058</td><td>12.917</td><td>-0.095</td><td>-0.372</td><td>1.2</td><td>0.3</td><td>1.2</td><td>97.0</td><td>0.3</td><td>1.0</td><td>8.0</td><td>5.3</td><td>5.0</td><td>null</td><td>33.2</td><td>9.0</td><td>2.5</td><td>3.0</td><td>1.0</td><td>1.7</td><td>3.0</td><td>1.0</td><td>1.5</td><td>28</td><td>9</td><td>0</td><td>9</td><td>3</td><td>0</td><td>1000</td><td>&quot;Flats/Maisonettes/NO DATA!&quot;</td><td>2157</td></tr><tr><td>&quot; 72 ERW SALUSBURY&quot;</td><td>&quot;LL16 3HN&quot;</td><td>[{1999,50000}, {2012,159000}]</td><td>&quot;Freehold&quot;</td><td>159000</td><td>&quot;72, Erw Salusbury&quot;</td><td>&quot;D&quot;</td><td>&quot;B&quot;</td><td>&quot;Bungalow&quot;</td><td>122.0</td><td>5</td><td>1967</td><td>53.186254</td><td>-3.399275</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>null</td><td>1.0</td><td>3.3</td><td>8.3</td><td>null</td><td>15.0</td><td>4.3</td><td>2.5</td><td>1.0</td><td>1.0</td><td>2.0</td><td>1.0</td><td>1.0</td><td>null</td><td>13</td><td>8</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1000</td><td>&quot;Detached&quot;</td><td>1303</td></tr></tbody></table></div>"
],
"text/plain": [
"shape: (5, 54)\n",
"┌───────────┬──────────┬───────────┬───────────┬───┬───────────┬───────────┬───────────┬───────────┐\n",
"│ Address ┆ Postcode ┆ historica ┆ Leashold/ ┆ … ┆ Good+ ┆ Max ┆ Property ┆ Price per │\n",
"│ per ┆ --- ┆ l_prices ┆ Freehold ┆ ┆ secondary ┆ available ┆ type/buil ┆ sqm │\n",
"│ Property ┆ str ┆ --- ┆ --- ┆ ┆ schools ┆ download ┆ t form ┆ --- │\n",
"│ Register ┆ ┆ list[stru ┆ str ┆ ┆ within… ┆ speed (… ┆ --- ┆ i32 │\n",
"│ --- ┆ ┆ ct[2]] ┆ ┆ ┆ --- ┆ --- ┆ str ┆ │\n",
"│ str ┆ ┆ ┆ ┆ ┆ i32 ┆ u16 ┆ ┆ │\n",
"╞═══════════╪══════════╪═══════════╪═══════════╪═══╪═══════════╪═══════════╪═══════════╪═══════════╡\n",
"│ 20 ┆ E17 3PG ┆ [{2018,68 ┆ Freehold ┆ … ┆ 5 ┆ 1000 ┆ Semi-Deta ┆ 4660 │\n",
"│ FORESTERS ┆ ┆ 5000}] ┆ ┆ ┆ ┆ ┆ ched ┆ │\n",
"│ DRIVE ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n",
"│ 12 PENTLE ┆ SA69 9BW ┆ [{2014,16 ┆ Freehold ┆ … ┆ 0 ┆ 30 ┆ Semi-Deta ┆ 2025 │\n",
"│ DRIVE ┆ ┆ 0000}] ┆ ┆ ┆ ┆ ┆ ched ┆ │\n",
"│ 107 ┆ SS17 7NR ┆ [{2018,33 ┆ Freehold ┆ … ┆ 0 ┆ 1000 ┆ Semi-Deta ┆ 3479 │\n",
"│ BRAMPTON ┆ ┆ 7500}] ┆ ┆ ┆ ┆ ┆ ched ┆ │\n",
"│ CLOSE ┆ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │\n",
"│ 5 ┆ PO37 6HH ┆ [{1995,50 ┆ Leasehold ┆ … ┆ 0 ┆ 1000 ┆ Flats/Mai ┆ 2157 │\n",
"│ CRAIGMORE ┆ ┆ 000}, {20 ┆ ┆ ┆ ┆ ┆ sonettes/ ┆ │\n",
"│ COURT ┆ ┆ 00,82000} ┆ ┆ ┆ ┆ ┆ NO DATA! ┆ │\n",
"│ ┆ ┆ , …… ┆ ┆ ┆ ┆ ┆ ┆ │\n",
"│ 72 ERW ┆ LL16 3HN ┆ [{1999,50 ┆ Freehold ┆ … ┆ 0 ┆ 1000 ┆ Detached ┆ 1303 │\n",
"│ SALUSBURY ┆ ┆ 000}, {20 ┆ ┆ ┆ ┆ ┆ ┆ │\n",
"│ ┆ ┆ 12,159000 ┆ ┆ ┆ ┆ ┆ ┆ │\n",
"│ ┆ ┆ }] ┆ ┆ ┆ ┆ ┆ ┆ │\n",
"└───────────┴──────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴───────────┘"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data = pl.scan_parquet(param_import_path).unique(subset=[\"Postcode\", \"Address per EPC\"])\n",
"data = data.filter(pl.col(\"Total floor area (sqm)\") > 10)\n",
"\n",
"# print(data.collect_schema()) # column names and types\n",
"print(data.select(pl.len()).collect()) # row count\n",
"data.head().collect()\n",
"\n",
"# data.head(2).collect().select(pl.col('historical_prices').map_elements(repr, return_dtype=pl.String).alias('historical_prices_str'), pl.exclude('historical_prices')).transpose()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "f63522b7",
"metadata": {},
"outputs": [],
"source": [
"columns_required = [\n",
" # absolute neccesity\n",
" \"Postcode\",\n",
" \"Address per EPC\",\n",
" \"historical_prices\",\n",
" \"Price per sqm\",\n",
" # faily fixed attributes\n",
" \"Property type\", # or 'epc_property_type' or 'built_form'\n",
" \"Leashold/Freehold\",\n",
" \"Total floor area (sqm)\",\n",
" \"Rooms (including bedrooms & bathrooms)\",\n",
" \"Approximate construction age\",\n",
" # latest\n",
" # 'date_of_transfer'\n",
" \"Last known price\",\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "b5af8a79",
"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>Postcode</th>\n",
" <th>Address per EPC</th>\n",
" <th>historical_prices</th>\n",
" <th>Price per sqm</th>\n",
" <th>Property type</th>\n",
" <th>Leashold/Freehold</th>\n",
" <th>Total floor area (sqm)</th>\n",
" <th>Rooms (including bedrooms &amp; bathrooms)</th>\n",
" <th>Approximate construction age</th>\n",
" <th>year</th>\n",
" <th>price</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>M5 4ZF</td>\n",
" <td>Apartment 1708 Block B, 4, Hulme Street</td>\n",
" <td>{'year': 2022, 'price': 425670}</td>\n",
" <td>4434.062500</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>96.00</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2022</td>\n",
" <td>425670</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>M6 8AQ</td>\n",
" <td>29, Lancaster Road</td>\n",
" <td>{'year': 2015, 'price': 280000}</td>\n",
" <td>1937.984496</td>\n",
" <td>House</td>\n",
" <td>Freehold</td>\n",
" <td>144.48</td>\n",
" <td>7.0</td>\n",
" <td>1930.0</td>\n",
" <td>2015</td>\n",
" <td>280000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>SS16 5UT</td>\n",
" <td>49, Kingswood Road</td>\n",
" <td>{'year': 2020, 'price': 275000}</td>\n",
" <td>2925.531915</td>\n",
" <td>House</td>\n",
" <td>Freehold</td>\n",
" <td>94.00</td>\n",
" <td>4.0</td>\n",
" <td>1967.0</td>\n",
" <td>2020</td>\n",
" <td>275000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>CM8 2DY</td>\n",
" <td>23, Collingwood Road</td>\n",
" <td>{'year': 2015, 'price': 415000}</td>\n",
" <td>2748.344371</td>\n",
" <td>House</td>\n",
" <td>Freehold</td>\n",
" <td>151.00</td>\n",
" <td>8.0</td>\n",
" <td>1930.0</td>\n",
" <td>2015</td>\n",
" <td>415000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>SW15 1RH</td>\n",
" <td>2c, Chelverton Road</td>\n",
" <td>{'year': 1997, 'price': 87000}</td>\n",
" <td>1897.905759</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>45.84</td>\n",
" <td>2.0</td>\n",
" <td>1900.0</td>\n",
" <td>1997</td>\n",
" <td>87000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>198437</th>\n",
" <td>PE11 3TD</td>\n",
" <td>93, Starlode Drove, West Pinchbeck</td>\n",
" <td>{'year': 2021, 'price': 325000}</td>\n",
" <td>2876.106195</td>\n",
" <td>Bungalow</td>\n",
" <td>Freehold</td>\n",
" <td>113.00</td>\n",
" <td>5.0</td>\n",
" <td>1983.0</td>\n",
" <td>2021</td>\n",
" <td>325000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>198438</th>\n",
" <td>NG31 8XB</td>\n",
" <td>8, Penrhyn Way</td>\n",
" <td>{'year': 2018, 'price': 229995}</td>\n",
" <td>1742.386364</td>\n",
" <td>House</td>\n",
" <td>Freehold</td>\n",
" <td>132.00</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2018</td>\n",
" <td>229995</td>\n",
" </tr>\n",
" <tr>\n",
" <th>198439</th>\n",
" <td>BD6 3QJ</td>\n",
" <td>163, Wibsey Park Avenue</td>\n",
" <td>{'year': 2002, 'price': 72500}</td>\n",
" <td>557.949823</td>\n",
" <td>House</td>\n",
" <td>Freehold</td>\n",
" <td>129.94</td>\n",
" <td>5.0</td>\n",
" <td>1930.0</td>\n",
" <td>2002</td>\n",
" <td>72500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>198439</th>\n",
" <td>BD6 3QJ</td>\n",
" <td>163, Wibsey Park Avenue</td>\n",
" <td>{'year': 2004, 'price': 125000}</td>\n",
" <td>961.982453</td>\n",
" <td>House</td>\n",
" <td>Freehold</td>\n",
" <td>129.94</td>\n",
" <td>5.0</td>\n",
" <td>1930.0</td>\n",
" <td>2004</td>\n",
" <td>125000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>198439</th>\n",
" <td>BD6 3QJ</td>\n",
" <td>163, Wibsey Park Avenue</td>\n",
" <td>{'year': 2012, 'price': 162000}</td>\n",
" <td>1246.729260</td>\n",
" <td>House</td>\n",
" <td>Freehold</td>\n",
" <td>129.94</td>\n",
" <td>5.0</td>\n",
" <td>1930.0</td>\n",
" <td>2012</td>\n",
" <td>162000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>395821 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" Postcode Address per EPC \\\n",
"0 M5 4ZF Apartment 1708 Block B, 4, Hulme Street \n",
"1 M6 8AQ 29, Lancaster Road \n",
"2 SS16 5UT 49, Kingswood Road \n",
"3 CM8 2DY 23, Collingwood Road \n",
"4 SW15 1RH 2c, Chelverton Road \n",
"... ... ... \n",
"198437 PE11 3TD 93, Starlode Drove, West Pinchbeck \n",
"198438 NG31 8XB 8, Penrhyn Way \n",
"198439 BD6 3QJ 163, Wibsey Park Avenue \n",
"198439 BD6 3QJ 163, Wibsey Park Avenue \n",
"198439 BD6 3QJ 163, Wibsey Park Avenue \n",
"\n",
" historical_prices Price per sqm Property type \\\n",
"0 {'year': 2022, 'price': 425670} 4434.062500 Flat \n",
"1 {'year': 2015, 'price': 280000} 1937.984496 House \n",
"2 {'year': 2020, 'price': 275000} 2925.531915 House \n",
"3 {'year': 2015, 'price': 415000} 2748.344371 House \n",
"4 {'year': 1997, 'price': 87000} 1897.905759 Flat \n",
"... ... ... ... \n",
"198437 {'year': 2021, 'price': 325000} 2876.106195 Bungalow \n",
"198438 {'year': 2018, 'price': 229995} 1742.386364 House \n",
"198439 {'year': 2002, 'price': 72500} 557.949823 House \n",
"198439 {'year': 2004, 'price': 125000} 961.982453 House \n",
"198439 {'year': 2012, 'price': 162000} 1246.729260 House \n",
"\n",
" Leashold/Freehold Total floor area (sqm) \\\n",
"0 Leasehold 96.00 \n",
"1 Freehold 144.48 \n",
"2 Freehold 94.00 \n",
"3 Freehold 151.00 \n",
"4 Leasehold 45.84 \n",
"... ... ... \n",
"198437 Freehold 113.00 \n",
"198438 Freehold 132.00 \n",
"198439 Freehold 129.94 \n",
"198439 Freehold 129.94 \n",
"198439 Freehold 129.94 \n",
"\n",
" Rooms (including bedrooms & bathrooms) Approximate construction age \\\n",
"0 NaN NaN \n",
"1 7.0 1930.0 \n",
"2 4.0 1967.0 \n",
"3 8.0 1930.0 \n",
"4 2.0 1900.0 \n",
"... ... ... \n",
"198437 5.0 1983.0 \n",
"198438 NaN NaN \n",
"198439 5.0 1930.0 \n",
"198439 5.0 1930.0 \n",
"198439 5.0 1930.0 \n",
"\n",
" year price \n",
"0 2022 425670 \n",
"1 2015 280000 \n",
"2 2020 275000 \n",
"3 2015 415000 \n",
"4 1997 87000 \n",
"... ... ... \n",
"198437 2021 325000 \n",
"198438 2018 229995 \n",
"198439 2002 72500 \n",
"198439 2004 125000 \n",
"198439 2012 162000 \n",
"\n",
"[395821 rows x 11 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# temp_Postcodes = [\"LE5 4ED\", \"E14 9GU\", \"YO8 9PW\", \"SW1P 3AN\", \"BH3 7DX\", \"E14 2DG\"]\n",
"temp_Postcodes = data.select(\"Postcode\").collect().sample(10000)[\"Postcode\"].to_list()\n",
"data_small = (\n",
" data.filter(pl.col(\"Postcode\").is_in(temp_Postcodes))\n",
" .select(columns_required)\n",
" .collect()\n",
" .to_pandas()\n",
")\n",
"data_small = data_small.explode(\"historical_prices\")\n",
"data_small[\"year\"] = data_small[\"historical_prices\"].apply(lambda x: x[\"year\"])\n",
"data_small[\"price\"] = data_small[\"historical_prices\"].apply(lambda x: x[\"price\"])\n",
"data_small[\"Price per sqm\"] = data_small[\"price\"] / data_small[\"Total floor area (sqm)\"]\n",
"data_small = data_small.drop(columns=[\"Last known price\"])\n",
"data_small"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "3692ab7b",
"metadata": {},
"outputs": [],
"source": [
"# data_small[\n",
"# (data_small['Postcode'] == 'E14 2DG')\n",
"# & data_small['epc_address'].str.contains('76')\n",
"# ]"
]
},
{
"cell_type": "markdown",
"id": "ed6b63af",
"metadata": {},
"source": [
"# Calculate $PC\\_AVG_t$"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "64e1890e",
"metadata": {},
"outputs": [],
"source": [
"# pc_avg_simple = data_small.groupby(['Postcode', 'year'])['Price per sqm'].mean().reset_index().sort_values(by=['Postcode', 'year'], ascending=False)\n",
"# temp_df = pc_avg_simple[pc_avg_simple['Postcode'] == data_small['Postcode'].iloc[0]]\n",
"# print(data_small['Postcode'].iloc[0])\n",
"# temp_df.plot.line(x='year', y='Price per sqm')\n",
"# display(pc_avg_simple)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "ba841c10",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"rolling periods (relative): [-3, -2, -1, 0]\n"
]
},
{
"data": {
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"<div>\n",
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Postcode</th>\n",
" <th>year</th>\n",
" <th>ppsqm_sum</th>\n",
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" <tr>\n",
" <th>161608</th>\n",
" <td>YO8 9SL</td>\n",
" <td>2024</td>\n",
" <td>3722.560976</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>161607</th>\n",
" <td>YO8 9SL</td>\n",
" <td>2023</td>\n",
" <td>2804.878049</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>161606</th>\n",
" <td>YO8 9SL</td>\n",
" <td>2020</td>\n",
" <td>2546.698113</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>161605</th>\n",
" <td>YO8 9SL</td>\n",
" <td>2019</td>\n",
" <td>19767.575710</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>161604</th>\n",
" <td>YO8 9QL</td>\n",
" <td>2025</td>\n",
" <td>13427.078408</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>AL1 4HJ</td>\n",
" <td>2011</td>\n",
" <td>5704.124521</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>AL1 4HJ</td>\n",
" <td>2010</td>\n",
" <td>5257.510730</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>AL1 4HJ</td>\n",
" <td>2004</td>\n",
" <td>3468.208092</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>AL1 4HJ</td>\n",
" <td>2003</td>\n",
" <td>3535.031847</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>AL1 4HJ</td>\n",
" <td>1999</td>\n",
" <td>2261.146497</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>161609 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" Postcode year ppsqm_sum ppsqm_count\n",
"161608 YO8 9SL 2024 3722.560976 2\n",
"161607 YO8 9SL 2023 2804.878049 1\n",
"161606 YO8 9SL 2020 2546.698113 1\n",
"161605 YO8 9SL 2019 19767.575710 8\n",
"161604 YO8 9QL 2025 13427.078408 4\n",
"... ... ... ... ...\n",
"4 AL1 4HJ 2011 5704.124521 1\n",
"3 AL1 4HJ 2010 5257.510730 1\n",
"2 AL1 4HJ 2004 3468.208092 1\n",
"1 AL1 4HJ 2003 3535.031847 1\n",
"0 AL1 4HJ 1999 2261.146497 1\n",
"\n",
"[161609 rows x 4 columns]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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" <th>ppsqm_sum</th>\n",
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" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>161608</th>\n",
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" <th>161606</th>\n",
" <td>YO8 9SL</td>\n",
" <td>2017</td>\n",
" <td>2546.698113</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>161605</th>\n",
" <td>YO8 9SL</td>\n",
" <td>2016</td>\n",
" <td>19767.575710</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>161604</th>\n",
" <td>YO8 9QL</td>\n",
" <td>2022</td>\n",
" <td>13427.078408</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
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" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>AL1 4HJ</td>\n",
" <td>2011</td>\n",
" <td>5704.124521</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>AL1 4HJ</td>\n",
" <td>2010</td>\n",
" <td>5257.510730</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
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" <td>3468.208092</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>AL1 4HJ</td>\n",
" <td>2003</td>\n",
" <td>3535.031847</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>AL1 4HJ</td>\n",
" <td>1999</td>\n",
" <td>2261.146497</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>646436 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" Postcode year ppsqm_sum ppsqm_count\n",
"161608 YO8 9SL 2021 3722.560976 2\n",
"161607 YO8 9SL 2020 2804.878049 1\n",
"161606 YO8 9SL 2017 2546.698113 1\n",
"161605 YO8 9SL 2016 19767.575710 8\n",
"161604 YO8 9QL 2022 13427.078408 4\n",
"... ... ... ... ...\n",
"4 AL1 4HJ 2011 5704.124521 1\n",
"3 AL1 4HJ 2010 5257.510730 1\n",
"2 AL1 4HJ 2004 3468.208092 1\n",
"1 AL1 4HJ 2003 3535.031847 1\n",
"0 AL1 4HJ 1999 2261.146497 1\n",
"\n",
"[646436 rows x 4 columns]"
]
},
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"output_type": "display_data"
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{
"data": {
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" <th>Price per sqm PC AVG</th>\n",
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" <th>264550</th>\n",
" <td>YO8 9SL</td>\n",
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" <td>1861.280488</td>\n",
" </tr>\n",
" <tr>\n",
" <th>264549</th>\n",
" <td>YO8 9SL</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>264548</th>\n",
" <td>YO8 9SL</td>\n",
" <td>2022</td>\n",
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" <tr>\n",
" <th>264547</th>\n",
" <td>YO8 9SL</td>\n",
" <td>2021</td>\n",
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" <tr>\n",
" <th>264546</th>\n",
" <td>YO8 9SL</td>\n",
" <td>2020</td>\n",
" <td>2675.788081</td>\n",
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" <tr>\n",
" <th>...</th>\n",
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" <tr>\n",
" <th>3</th>\n",
" <td>AL1 4HJ</td>\n",
" <td>1999</td>\n",
" <td>2261.146497</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>AL1 4HJ</td>\n",
" <td>1998</td>\n",
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" <tr>\n",
" <th>1</th>\n",
" <td>AL1 4HJ</td>\n",
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" <td>1996</td>\n",
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"</div>"
],
"text/plain": [
" Postcode year Price per sqm PC AVG\n",
"264550 YO8 9SL 2024 1861.280488\n",
"264549 YO8 9SL 2023 2175.813008\n",
"264548 YO8 9SL 2022 2175.813008\n",
"264547 YO8 9SL 2021 2175.813008\n",
"264546 YO8 9SL 2020 2675.788081\n",
"... ... ... ...\n",
"4 AL1 4HJ 2000 3535.031847\n",
"3 AL1 4HJ 1999 2261.146497\n",
"2 AL1 4HJ 1998 2261.146497\n",
"1 AL1 4HJ 1997 2261.146497\n",
"0 AL1 4HJ 1996 2261.146497\n",
"\n",
"[264551 rows x 3 columns]"
]
},
"metadata": {},
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},
{
"name": "stdout",
"output_type": "stream",
"text": [
"M5 4ZF\n"
]
},
{
"data": {
"text/plain": [
"<Axes: xlabel='year'>"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from typing import Any\n",
"from pandas.core.frame import DataFrame\n",
"\n",
"print(f\"rolling periods (relative): {[i for i in range(-param_lookback, 1)]}\")\n",
"\n",
"# Rolling average (±2 year), weighted by number of sales per year\n",
"pc_avg_raw = (\n",
" data_small.groupby([\"Postcode\", \"year\"])\n",
" .agg(ppsqm_sum=(\"Price per sqm\", \"sum\"), ppsqm_count=(\"Price per sqm\", \"count\"))\n",
" .reset_index()\n",
" .sort_values(by=[\"Postcode\", \"year\"], ascending=False)\n",
")\n",
"\n",
"display(pc_avg_raw)\n",
"\n",
"# Each year's totals contribute to year-1, year, and year+1\n",
"pc_avg_expanded = pd.concat(\n",
" [\n",
" pc_avg_raw.assign(year=pc_avg_raw[\"year\"] + offset)\n",
" for offset in range(-param_lookback, 1) #\n",
" ]\n",
")\n",
"\n",
"display(pc_avg_expanded)\n",
"\n",
"# Sum counts and sums, then divide to get weighted mean\n",
"pc_avg_complex = (\n",
" pc_avg_expanded.groupby([\"Postcode\", \"year\"])\n",
" .agg(ppsqm_sum=(\"ppsqm_sum\", \"sum\"), ppsqm_count=(\"ppsqm_count\", \"sum\"))\n",
" .reset_index()\n",
")\n",
"pc_avg_complex[\"Price per sqm PC AVG\"] = (\n",
" pc_avg_complex[\"ppsqm_sum\"] / pc_avg_complex[\"ppsqm_count\"]\n",
")\n",
"pc_avg_complex: Any | DataFrame = pc_avg_complex[\n",
" [\"Postcode\", \"year\", \"Price per sqm PC AVG\"]\n",
"].sort_values(by=[\"Postcode\", \"year\"], ascending=False)\n",
"display(pc_avg_complex)\n",
"\n",
"temp_df = pc_avg_complex[pc_avg_complex[\"Postcode\"] == data_small[\"Postcode\"].iloc[0]]\n",
"print(data_small[\"Postcode\"].iloc[0])\n",
"temp_df.plot.line(x=\"year\", y=\"Price per sqm PC AVG\")"
]
},
{
"cell_type": "markdown",
"id": "e3beccbc",
"metadata": {},
"source": [
"# Calculate $C_x$"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "112da774",
"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>Postcode</th>\n",
" <th>Address per EPC</th>\n",
" <th>Price per sqm</th>\n",
" <th>Price per sqm PC AVG</th>\n",
" <th>c</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>M5 4ZF</td>\n",
" <td>Apartment 1708 Block B, 4, Hulme Street</td>\n",
" <td>4434.062500</td>\n",
" <td>3952.139814</td>\n",
" <td>1.121940</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>M6 8AQ</td>\n",
" <td>29, Lancaster Road</td>\n",
" <td>1937.984496</td>\n",
" <td>2265.288544</td>\n",
" <td>0.855513</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>SS16 5UT</td>\n",
" <td>49, Kingswood Road</td>\n",
" <td>2925.531915</td>\n",
" <td>2832.343786</td>\n",
" <td>1.032901</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>CM8 2DY</td>\n",
" <td>23, Collingwood Road</td>\n",
" <td>2748.344371</td>\n",
" <td>3542.927966</td>\n",
" <td>0.775727</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>SW15 1RH</td>\n",
" <td>2c, Chelverton Road</td>\n",
" <td>1897.905759</td>\n",
" <td>3307.169627</td>\n",
" <td>0.573876</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>395816</th>\n",
" <td>PE11 3TD</td>\n",
" <td>93, Starlode Drove, West Pinchbeck</td>\n",
" <td>2876.106195</td>\n",
" <td>2344.646504</td>\n",
" <td>1.226669</td>\n",
" </tr>\n",
" <tr>\n",
" <th>395817</th>\n",
" <td>NG31 8XB</td>\n",
" <td>8, Penrhyn Way</td>\n",
" <td>1742.386364</td>\n",
" <td>1947.845614</td>\n",
" <td>0.894520</td>\n",
" </tr>\n",
" <tr>\n",
" <th>395818</th>\n",
" <td>BD6 3QJ</td>\n",
" <td>163, Wibsey Park Avenue</td>\n",
" <td>557.949823</td>\n",
" <td>954.919954</td>\n",
" <td>0.584290</td>\n",
" </tr>\n",
" <tr>\n",
" <th>395819</th>\n",
" <td>BD6 3QJ</td>\n",
" <td>163, Wibsey Park Avenue</td>\n",
" <td>961.982453</td>\n",
" <td>961.982453</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>395820</th>\n",
" <td>BD6 3QJ</td>\n",
" <td>163, Wibsey Park Avenue</td>\n",
" <td>1246.729260</td>\n",
" <td>1441.546448</td>\n",
" <td>0.864855</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>395821 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" Postcode Address per EPC Price per sqm \\\n",
"0 M5 4ZF Apartment 1708 Block B, 4, Hulme Street 4434.062500 \n",
"1 M6 8AQ 29, Lancaster Road 1937.984496 \n",
"2 SS16 5UT 49, Kingswood Road 2925.531915 \n",
"3 CM8 2DY 23, Collingwood Road 2748.344371 \n",
"4 SW15 1RH 2c, Chelverton Road 1897.905759 \n",
"... ... ... ... \n",
"395816 PE11 3TD 93, Starlode Drove, West Pinchbeck 2876.106195 \n",
"395817 NG31 8XB 8, Penrhyn Way 1742.386364 \n",
"395818 BD6 3QJ 163, Wibsey Park Avenue 557.949823 \n",
"395819 BD6 3QJ 163, Wibsey Park Avenue 961.982453 \n",
"395820 BD6 3QJ 163, Wibsey Park Avenue 1246.729260 \n",
"\n",
" Price per sqm PC AVG c \n",
"0 3952.139814 1.121940 \n",
"1 2265.288544 0.855513 \n",
"2 2832.343786 1.032901 \n",
"3 3542.927966 0.775727 \n",
"4 3307.169627 0.573876 \n",
"... ... ... \n",
"395816 2344.646504 1.226669 \n",
"395817 1947.845614 0.894520 \n",
"395818 954.919954 0.584290 \n",
"395819 961.982453 1.000000 \n",
"395820 1441.546448 0.864855 \n",
"\n",
"[395821 rows x 5 columns]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_small = data_small.merge(\n",
" pc_avg_complex, on=[\"Postcode\", \"year\"], suffixes=(\"\", \" pc_avg_complex\")\n",
")\n",
"data_small[\"c\"] = data_small[\"Price per sqm\"] / data_small[\"Price per sqm PC AVG\"]\n",
"data_small[\n",
" [\"Postcode\", \"Address per EPC\", \"Price per sqm\", \"Price per sqm PC AVG\", \"c\"]\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "12b1d00a",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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" 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></th>\n",
" <th>n_sales</th>\n",
" <th>year_min</th>\n",
" <th>year_max</th>\n",
" <th>c_mean</th>\n",
" <th>c_std</th>\n",
" <th>c_cv</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Postcode</th>\n",
" <th>Address per EPC</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>SS0 9AA</th>\n",
" <th>Pineflow, 55a Shakespeare Drive</th>\n",
" <td>3</td>\n",
" <td>1996</td>\n",
" <td>1997</td>\n",
" <td>3.960179</td>\n",
" <td>6.498855</td>\n",
" <td>1.641051</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SS0 9UU</th>\n",
" <th>94 SOUTHBOURNE GROVE, WESTCLIFF-ON-SEA</th>\n",
" <td>2</td>\n",
" <td>1996</td>\n",
" <td>1996</td>\n",
" <td>0.265513</td>\n",
" <td>0.365610</td>\n",
" <td>1.376993</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SW2 1ER</th>\n",
" <th>70a Saltoun Road</th>\n",
" <td>2</td>\n",
" <td>2001</td>\n",
" <td>2002</td>\n",
" <td>0.749516</td>\n",
" <td>1.030029</td>\n",
" <td>1.374259</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SW2 3DF</th>\n",
" <th>Flat D, 108 Christchurch Road</th>\n",
" <td>2</td>\n",
" <td>2006</td>\n",
" <td>2014</td>\n",
" <td>0.915386</td>\n",
" <td>1.249392</td>\n",
" <td>1.364880</td>\n",
" </tr>\n",
" <tr>\n",
" <th>PL6 8DY</th>\n",
" <th>43 Bluebell Street</th>\n",
" <td>2</td>\n",
" <td>2016</td>\n",
" <td>2019</td>\n",
" <td>0.561477</td>\n",
" <td>0.764020</td>\n",
" <td>1.360732</td>\n",
" </tr>\n",
" <tr>\n",
" <th>WN6 0US</th>\n",
" <th>1, Meadowacre, Standish</th>\n",
" <td>2</td>\n",
" <td>2015</td>\n",
" <td>2021</td>\n",
" <td>0.515135</td>\n",
" <td>0.697189</td>\n",
" <td>1.353411</td>\n",
" </tr>\n",
" <tr>\n",
" <th>L24 9LL</th>\n",
" <th>59 Addenbrooke Drive, Speke</th>\n",
" <td>2</td>\n",
" <td>2013</td>\n",
" <td>2020</td>\n",
" <td>0.465642</td>\n",
" <td>0.623893</td>\n",
" <td>1.339855</td>\n",
" </tr>\n",
" <tr>\n",
" <th>N10 3NR</th>\n",
" <th>Flat 2, 6 Queens Avenue</th>\n",
" <td>2</td>\n",
" <td>1997</td>\n",
" <td>2002</td>\n",
" <td>0.372452</td>\n",
" <td>0.494968</td>\n",
" <td>1.328944</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SW11 3HB</th>\n",
" <th>Flat 3 Beaufort House, 30, Winders Road</th>\n",
" <td>2</td>\n",
" <td>1996</td>\n",
" <td>2018</td>\n",
" <td>0.510002</td>\n",
" <td>0.653344</td>\n",
" <td>1.281063</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CR3 5QE</th>\n",
" <th>36 Banstead Road</th>\n",
" <td>2</td>\n",
" <td>2002</td>\n",
" <td>2023</td>\n",
" <td>0.418259</td>\n",
" <td>0.534478</td>\n",
" <td>1.277862</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SW5 9BH</th>\n",
" <th>FLAT 51, WETHERBY MANSIONS, EARL'S COURT SQUARE</th>\n",
" <td>2</td>\n",
" <td>1995</td>\n",
" <td>2022</td>\n",
" <td>0.536443</td>\n",
" <td>0.682598</td>\n",
" <td>1.272453</td>\n",
" </tr>\n",
" <tr>\n",
" <th>WD3 5LH</th>\n",
" <th>Flat 7 Sheraton House, Lower Road, Chorleywood</th>\n",
" <td>2</td>\n",
" <td>1995</td>\n",
" <td>1996</td>\n",
" <td>0.442410</td>\n",
" <td>0.552779</td>\n",
" <td>1.249472</td>\n",
" </tr>\n",
" <tr>\n",
" <th>KT13 8XF</th>\n",
" <th>27 Fortescue Road</th>\n",
" <td>2</td>\n",
" <td>2007</td>\n",
" <td>2024</td>\n",
" <td>0.481300</td>\n",
" <td>0.600319</td>\n",
" <td>1.247285</td>\n",
" </tr>\n",
" <tr>\n",
" <th>N7 6RY</th>\n",
" <th>Flat 4, 102 Tollington Way, Islington</th>\n",
" <td>2</td>\n",
" <td>2001</td>\n",
" <td>2003</td>\n",
" <td>0.959964</td>\n",
" <td>1.180041</td>\n",
" <td>1.229256</td>\n",
" </tr>\n",
" <tr>\n",
" <th>RH4 1AY</th>\n",
" <th>76, High Street</th>\n",
" <td>2</td>\n",
" <td>2004</td>\n",
" <td>2012</td>\n",
" <td>0.411008</td>\n",
" <td>0.496243</td>\n",
" <td>1.207382</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CA28 6TJ</th>\n",
" <th>2, The Crest</th>\n",
" <td>2</td>\n",
" <td>2005</td>\n",
" <td>2013</td>\n",
" <td>0.509162</td>\n",
" <td>0.593252</td>\n",
" <td>1.165152</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W1U 3DR</th>\n",
" <th>20 Jacobs Well Mews</th>\n",
" <td>3</td>\n",
" <td>2003</td>\n",
" <td>2022</td>\n",
" <td>0.426429</td>\n",
" <td>0.496747</td>\n",
" <td>1.164898</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SG6 4DL</th>\n",
" <th>20, Icknield Green</th>\n",
" <td>2</td>\n",
" <td>2016</td>\n",
" <td>2016</td>\n",
" <td>0.546056</td>\n",
" <td>0.632503</td>\n",
" <td>1.158312</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SO51 6DA</th>\n",
" <th>Lukes Barn, Maurys Lane, West Wellow</th>\n",
" <td>2</td>\n",
" <td>1995</td>\n",
" <td>2012</td>\n",
" <td>0.606841</td>\n",
" <td>0.697969</td>\n",
" <td>1.150169</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NR27 0DJ</th>\n",
" <th>139 Kings Chalet Park, Overstrand Road</th>\n",
" <td>2</td>\n",
" <td>1996</td>\n",
" <td>2023</td>\n",
" <td>0.415552</td>\n",
" <td>0.477604</td>\n",
" <td>1.149325</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" n_sales year_min \\\n",
"Postcode Address per EPC \n",
"SS0 9AA Pineflow, 55a Shakespeare Drive 3 1996 \n",
"SS0 9UU 94 SOUTHBOURNE GROVE, WESTCLIFF-ON-SEA 2 1996 \n",
"SW2 1ER 70a Saltoun Road 2 2001 \n",
"SW2 3DF Flat D, 108 Christchurch Road 2 2006 \n",
"PL6 8DY 43 Bluebell Street 2 2016 \n",
"WN6 0US 1, Meadowacre, Standish 2 2015 \n",
"L24 9LL 59 Addenbrooke Drive, Speke 2 2013 \n",
"N10 3NR Flat 2, 6 Queens Avenue 2 1997 \n",
"SW11 3HB Flat 3 Beaufort House, 30, Winders Road 2 1996 \n",
"CR3 5QE 36 Banstead Road 2 2002 \n",
"SW5 9BH FLAT 51, WETHERBY MANSIONS, EARL'S COURT SQUARE 2 1995 \n",
"WD3 5LH Flat 7 Sheraton House, Lower Road, Chorleywood 2 1995 \n",
"KT13 8XF 27 Fortescue Road 2 2007 \n",
"N7 6RY Flat 4, 102 Tollington Way, Islington 2 2001 \n",
"RH4 1AY 76, High Street 2 2004 \n",
"CA28 6TJ 2, The Crest 2 2005 \n",
"W1U 3DR 20 Jacobs Well Mews 3 2003 \n",
"SG6 4DL 20, Icknield Green 2 2016 \n",
"SO51 6DA Lukes Barn, Maurys Lane, West Wellow 2 1995 \n",
"NR27 0DJ 139 Kings Chalet Park, Overstrand Road 2 1996 \n",
"\n",
" year_max c_mean \\\n",
"Postcode Address per EPC \n",
"SS0 9AA Pineflow, 55a Shakespeare Drive 1997 3.960179 \n",
"SS0 9UU 94 SOUTHBOURNE GROVE, WESTCLIFF-ON-SEA 1996 0.265513 \n",
"SW2 1ER 70a Saltoun Road 2002 0.749516 \n",
"SW2 3DF Flat D, 108 Christchurch Road 2014 0.915386 \n",
"PL6 8DY 43 Bluebell Street 2019 0.561477 \n",
"WN6 0US 1, Meadowacre, Standish 2021 0.515135 \n",
"L24 9LL 59 Addenbrooke Drive, Speke 2020 0.465642 \n",
"N10 3NR Flat 2, 6 Queens Avenue 2002 0.372452 \n",
"SW11 3HB Flat 3 Beaufort House, 30, Winders Road 2018 0.510002 \n",
"CR3 5QE 36 Banstead Road 2023 0.418259 \n",
"SW5 9BH FLAT 51, WETHERBY MANSIONS, EARL'S COURT SQUARE 2022 0.536443 \n",
"WD3 5LH Flat 7 Sheraton House, Lower Road, Chorleywood 1996 0.442410 \n",
"KT13 8XF 27 Fortescue Road 2024 0.481300 \n",
"N7 6RY Flat 4, 102 Tollington Way, Islington 2003 0.959964 \n",
"RH4 1AY 76, High Street 2012 0.411008 \n",
"CA28 6TJ 2, The Crest 2013 0.509162 \n",
"W1U 3DR 20 Jacobs Well Mews 2022 0.426429 \n",
"SG6 4DL 20, Icknield Green 2016 0.546056 \n",
"SO51 6DA Lukes Barn, Maurys Lane, West Wellow 2012 0.606841 \n",
"NR27 0DJ 139 Kings Chalet Park, Overstrand Road 2023 0.415552 \n",
"\n",
" c_std c_cv \n",
"Postcode Address per EPC \n",
"SS0 9AA Pineflow, 55a Shakespeare Drive 6.498855 1.641051 \n",
"SS0 9UU 94 SOUTHBOURNE GROVE, WESTCLIFF-ON-SEA 0.365610 1.376993 \n",
"SW2 1ER 70a Saltoun Road 1.030029 1.374259 \n",
"SW2 3DF Flat D, 108 Christchurch Road 1.249392 1.364880 \n",
"PL6 8DY 43 Bluebell Street 0.764020 1.360732 \n",
"WN6 0US 1, Meadowacre, Standish 0.697189 1.353411 \n",
"L24 9LL 59 Addenbrooke Drive, Speke 0.623893 1.339855 \n",
"N10 3NR Flat 2, 6 Queens Avenue 0.494968 1.328944 \n",
"SW11 3HB Flat 3 Beaufort House, 30, Winders Road 0.653344 1.281063 \n",
"CR3 5QE 36 Banstead Road 0.534478 1.277862 \n",
"SW5 9BH FLAT 51, WETHERBY MANSIONS, EARL'S COURT SQUARE 0.682598 1.272453 \n",
"WD3 5LH Flat 7 Sheraton House, Lower Road, Chorleywood 0.552779 1.249472 \n",
"KT13 8XF 27 Fortescue Road 0.600319 1.247285 \n",
"N7 6RY Flat 4, 102 Tollington Way, Islington 1.180041 1.229256 \n",
"RH4 1AY 76, High Street 0.496243 1.207382 \n",
"CA28 6TJ 2, The Crest 0.593252 1.165152 \n",
"W1U 3DR 20 Jacobs Well Mews 0.496747 1.164898 \n",
"SG6 4DL 20, Icknield Green 0.632503 1.158312 \n",
"SO51 6DA Lukes Barn, Maurys Lane, West Wellow 0.697969 1.150169 \n",
"NR27 0DJ 139 Kings Chalet Park, Overstrand Road 0.477604 1.149325 "
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# 1. Coefficient of Variation (std/mean) per property, filtered to 3+ sales\n",
"c_stats = (\n",
" data_small.groupby([\"Postcode\", \"Address per EPC\"])\n",
" .agg(\n",
" n_sales=(\"c\", \"count\"),\n",
" year_min=(\"year\", \"min\"),\n",
" year_max=(\"year\", \"max\"),\n",
" c_mean=(\"c\", \"mean\"),\n",
" c_std=(\"c\", \"std\"),\n",
" )\n",
" .dropna()\n",
")\n",
"c_stats[\"c_cv\"] = c_stats[\"c_std\"] / c_stats[\"c_mean\"]\n",
"# c_stats_3plus = c_stats[c_stats['n_sales'] >= 3]\n",
"# print(f\"Properties with 3+ sales: {len(c_stats_3plus)} / {len(c_stats)}\")\n",
"c_stats.sort_values(\"c_cv\", ascending=False).head(20)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "3e05ec4d",
"metadata": {},
"outputs": [
{
"data": {
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" <th></th>\n",
" <th></th>\n",
" <th>n_sales</th>\n",
" <th>year_min</th>\n",
" <th>year_max</th>\n",
" <th>c_mean</th>\n",
" <th>c_std</th>\n",
" <th>c_cv</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Postcode</th>\n",
" <th>Address per EPC</th>\n",
" <th></th>\n",
" <th></th>\n",
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" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>M4 1LA</th>\n",
" <th>Flat 316 Smithfield Buildings, 44, Tib Street</th>\n",
" <td>5</td>\n",
" <td>1997</td>\n",
" <td>2021</td>\n",
" <td>1.130153</td>\n",
" <td>0.130248</td>\n",
" <td>0.115248</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" n_sales year_min \\\n",
"Postcode Address per EPC \n",
"M4 1LA Flat 316 Smithfield Buildings, 44, Tib Street 5 1997 \n",
"\n",
" year_max c_mean \\\n",
"Postcode Address per EPC \n",
"M4 1LA Flat 316 Smithfield Buildings, 44, Tib Street 2021 1.130153 \n",
"\n",
" c_std c_cv \n",
"Postcode Address per EPC \n",
"M4 1LA Flat 316 Smithfield Buildings, 44, Tib Street 0.130248 0.115248 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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" <tbody>\n",
" <tr>\n",
" <th>132613</th>\n",
" <td>M4 1LA</td>\n",
" <td>1994</td>\n",
" <td>1194.925154</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132614</th>\n",
" <td>M4 1LA</td>\n",
" <td>1995</td>\n",
" <td>1286.241248</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132615</th>\n",
" <td>M4 1LA</td>\n",
" <td>1996</td>\n",
" <td>1327.996791</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132616</th>\n",
" <td>M4 1LA</td>\n",
" <td>1997</td>\n",
" <td>1345.611429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132617</th>\n",
" <td>M4 1LA</td>\n",
" <td>1998</td>\n",
" <td>1526.929223</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132618</th>\n",
" <td>M4 1LA</td>\n",
" <td>1999</td>\n",
" <td>1779.166943</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132619</th>\n",
" <td>M4 1LA</td>\n",
" <td>2000</td>\n",
" <td>1901.008928</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132620</th>\n",
" <td>M4 1LA</td>\n",
" <td>2001</td>\n",
" <td>1992.811006</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132621</th>\n",
" <td>M4 1LA</td>\n",
" <td>2002</td>\n",
" <td>2146.132342</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132622</th>\n",
" <td>M4 1LA</td>\n",
" <td>2003</td>\n",
" <td>2301.921624</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132623</th>\n",
" <td>M4 1LA</td>\n",
" <td>2004</td>\n",
" <td>2558.301387</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132624</th>\n",
" <td>M4 1LA</td>\n",
" <td>2005</td>\n",
" <td>2632.014683</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132625</th>\n",
" <td>M4 1LA</td>\n",
" <td>2006</td>\n",
" <td>2651.830756</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132626</th>\n",
" <td>M4 1LA</td>\n",
" <td>2007</td>\n",
" <td>2762.468670</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132627</th>\n",
" <td>M4 1LA</td>\n",
" <td>2008</td>\n",
" <td>2429.151977</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132628</th>\n",
" <td>M4 1LA</td>\n",
" <td>2009</td>\n",
" <td>2393.004123</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132629</th>\n",
" <td>M4 1LA</td>\n",
" <td>2010</td>\n",
" <td>2386.781694</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132630</th>\n",
" <td>M4 1LA</td>\n",
" <td>2011</td>\n",
" <td>2484.917175</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132631</th>\n",
" <td>M4 1LA</td>\n",
" <td>2012</td>\n",
" <td>2637.198527</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132632</th>\n",
" <td>M4 1LA</td>\n",
" <td>2013</td>\n",
" <td>2775.333931</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132633</th>\n",
" <td>M4 1LA</td>\n",
" <td>2014</td>\n",
" <td>2938.922880</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132634</th>\n",
" <td>M4 1LA</td>\n",
" <td>2015</td>\n",
" <td>3153.721022</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132635</th>\n",
" <td>M4 1LA</td>\n",
" <td>2016</td>\n",
" <td>3258.098184</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132636</th>\n",
" <td>M4 1LA</td>\n",
" <td>2017</td>\n",
" <td>3450.349098</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132637</th>\n",
" <td>M4 1LA</td>\n",
" <td>2018</td>\n",
" <td>3600.062667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132638</th>\n",
" <td>M4 1LA</td>\n",
" <td>2019</td>\n",
" <td>3643.365916</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132639</th>\n",
" <td>M4 1LA</td>\n",
" <td>2020</td>\n",
" <td>3708.378707</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132640</th>\n",
" <td>M4 1LA</td>\n",
" <td>2021</td>\n",
" <td>3695.106191</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132641</th>\n",
" <td>M4 1LA</td>\n",
" <td>2022</td>\n",
" <td>3785.347967</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132642</th>\n",
" <td>M4 1LA</td>\n",
" <td>2023</td>\n",
" <td>3725.247226</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132643</th>\n",
" <td>M4 1LA</td>\n",
" <td>2024</td>\n",
" <td>3598.084741</td>\n",
" </tr>\n",
" <tr>\n",
" <th>132644</th>\n",
" <td>M4 1LA</td>\n",
" <td>2025</td>\n",
" <td>4032.779104</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Postcode year Price per sqm PC AVG\n",
"132613 M4 1LA 1994 1194.925154\n",
"132614 M4 1LA 1995 1286.241248\n",
"132615 M4 1LA 1996 1327.996791\n",
"132616 M4 1LA 1997 1345.611429\n",
"132617 M4 1LA 1998 1526.929223\n",
"132618 M4 1LA 1999 1779.166943\n",
"132619 M4 1LA 2000 1901.008928\n",
"132620 M4 1LA 2001 1992.811006\n",
"132621 M4 1LA 2002 2146.132342\n",
"132622 M4 1LA 2003 2301.921624\n",
"132623 M4 1LA 2004 2558.301387\n",
"132624 M4 1LA 2005 2632.014683\n",
"132625 M4 1LA 2006 2651.830756\n",
"132626 M4 1LA 2007 2762.468670\n",
"132627 M4 1LA 2008 2429.151977\n",
"132628 M4 1LA 2009 2393.004123\n",
"132629 M4 1LA 2010 2386.781694\n",
"132630 M4 1LA 2011 2484.917175\n",
"132631 M4 1LA 2012 2637.198527\n",
"132632 M4 1LA 2013 2775.333931\n",
"132633 M4 1LA 2014 2938.922880\n",
"132634 M4 1LA 2015 3153.721022\n",
"132635 M4 1LA 2016 3258.098184\n",
"132636 M4 1LA 2017 3450.349098\n",
"132637 M4 1LA 2018 3600.062667\n",
"132638 M4 1LA 2019 3643.365916\n",
"132639 M4 1LA 2020 3708.378707\n",
"132640 M4 1LA 2021 3695.106191\n",
"132641 M4 1LA 2022 3785.347967\n",
"132642 M4 1LA 2023 3725.247226\n",
"132643 M4 1LA 2024 3598.084741\n",
"132644 M4 1LA 2025 4032.779104"
]
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" <th></th>\n",
" <th>Postcode</th>\n",
" <th>Address per EPC</th>\n",
" <th>historical_prices</th>\n",
" <th>Price per sqm</th>\n",
" <th>Property type</th>\n",
" <th>Leashold/Freehold</th>\n",
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" <th>c</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>637</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 324, Smithfield Buildings, 44 Tib Street</td>\n",
" <td>{'year': 1997, 'price': 160000}</td>\n",
" <td>1649.484536</td>\n",
" <td>Maisonette</td>\n",
" <td>Leasehold</td>\n",
" <td>97.00</td>\n",
" <td>5.0</td>\n",
" <td>1996.0</td>\n",
" <td>1997</td>\n",
" <td>160000</td>\n",
" <td>1345.611429</td>\n",
" <td>1.225825</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2931</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 323 Smithfield Buildings, 44, Tib Street</td>\n",
" <td>{'year': 1997, 'price': 62000}</td>\n",
" <td>1550.000000</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>40.00</td>\n",
" <td>1.0</td>\n",
" <td>1996.0</td>\n",
" <td>1997</td>\n",
" <td>62000</td>\n",
" <td>1345.611429</td>\n",
" <td>1.151893</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60080</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 404 Smithfield Buildings, 44, Tib Street</td>\n",
" <td>{'year': 1997, 'price': 95000}</td>\n",
" <td>1301.369863</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>73.00</td>\n",
" <td>4.0</td>\n",
" <td>1996.0</td>\n",
" <td>1997</td>\n",
" <td>95000</td>\n",
" <td>1345.611429</td>\n",
" <td>0.967122</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75436</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 201, Smithfield Buildings, 44 Tib Street</td>\n",
" <td>{'year': 1997, 'price': 63000}</td>\n",
" <td>900.000000</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>70.00</td>\n",
" <td>2.0</td>\n",
" <td>1900.0</td>\n",
" <td>1997</td>\n",
" <td>63000</td>\n",
" <td>1345.611429</td>\n",
" <td>0.668841</td>\n",
" </tr>\n",
" <tr>\n",
" <th>74698</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 206 Smithfield Buildings, 44, Tib Street</td>\n",
" <td>{'year': 1997, 'price': 68950}</td>\n",
" <td>1231.250000</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>56.00</td>\n",
" <td>2.0</td>\n",
" <td>1996.0</td>\n",
" <td>1997</td>\n",
" <td>68950</td>\n",
" <td>1345.611429</td>\n",
" <td>0.915012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>279239</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 120, Smithfield Buildings, 44 Tib Street</td>\n",
" <td>{'year': 2024, 'price': 285000}</td>\n",
" <td>2938.144330</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>97.00</td>\n",
" <td>3.0</td>\n",
" <td>1996.0</td>\n",
" <td>2024</td>\n",
" <td>285000</td>\n",
" <td>3598.084741</td>\n",
" <td>0.816586</td>\n",
" </tr>\n",
" <tr>\n",
" <th>293530</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 221 Smithfield Buildings, 44, Tib Street</td>\n",
" <td>{'year': 2024, 'price': 295000}</td>\n",
" <td>3041.237113</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>97.00</td>\n",
" <td>2.0</td>\n",
" <td>1900.0</td>\n",
" <td>2024</td>\n",
" <td>295000</td>\n",
" <td>3598.084741</td>\n",
" <td>0.845238</td>\n",
" </tr>\n",
" <tr>\n",
" <th>212197</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 304 Smithfield Buildings, 44, Tib Street</td>\n",
" <td>{'year': 2025, 'price': 291500}</td>\n",
" <td>4272.940487</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>68.22</td>\n",
" <td>2.0</td>\n",
" <td>1996.0</td>\n",
" <td>2025</td>\n",
" <td>291500</td>\n",
" <td>4032.779104</td>\n",
" <td>1.059552</td>\n",
" </tr>\n",
" <tr>\n",
" <th>209539</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 321, Smithfield Buildings, 44 Tib Street</td>\n",
" <td>{'year': 2025, 'price': 290000}</td>\n",
" <td>3222.222222</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>90.00</td>\n",
" <td>2.0</td>\n",
" <td>1996.0</td>\n",
" <td>2025</td>\n",
" <td>290000</td>\n",
" <td>4032.779104</td>\n",
" <td>0.799008</td>\n",
" </tr>\n",
" <tr>\n",
" <th>82391</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 307, Smithfield Buildings, 44 Tib Street</td>\n",
" <td>{'year': 2025, 'price': 290000}</td>\n",
" <td>4603.174603</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>63.00</td>\n",
" <td>1.0</td>\n",
" <td>1900.0</td>\n",
" <td>2025</td>\n",
" <td>290000</td>\n",
" <td>4032.779104</td>\n",
" <td>1.141440</td>\n",
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"text/plain": [
" Postcode Address per EPC \\\n",
"637 M4 1LA Flat 324, Smithfield Buildings, 44 Tib Street \n",
"2931 M4 1LA Flat 323 Smithfield Buildings, 44, Tib Street \n",
"60080 M4 1LA Flat 404 Smithfield Buildings, 44, Tib Street \n",
"75436 M4 1LA Flat 201, Smithfield Buildings, 44 Tib Street \n",
"74698 M4 1LA Flat 206 Smithfield Buildings, 44, Tib Street \n",
"... ... ... \n",
"279239 M4 1LA Flat 120, Smithfield Buildings, 44 Tib Street \n",
"293530 M4 1LA Flat 221 Smithfield Buildings, 44, Tib Street \n",
"212197 M4 1LA Flat 304 Smithfield Buildings, 44, Tib Street \n",
"209539 M4 1LA Flat 321, Smithfield Buildings, 44 Tib Street \n",
"82391 M4 1LA Flat 307, Smithfield Buildings, 44 Tib Street \n",
"\n",
" historical_prices Price per sqm Property type \\\n",
"637 {'year': 1997, 'price': 160000} 1649.484536 Maisonette \n",
"2931 {'year': 1997, 'price': 62000} 1550.000000 Flat \n",
"60080 {'year': 1997, 'price': 95000} 1301.369863 Flat \n",
"75436 {'year': 1997, 'price': 63000} 900.000000 Flat \n",
"74698 {'year': 1997, 'price': 68950} 1231.250000 Flat \n",
"... ... ... ... \n",
"279239 {'year': 2024, 'price': 285000} 2938.144330 Flat \n",
"293530 {'year': 2024, 'price': 295000} 3041.237113 Flat \n",
"212197 {'year': 2025, 'price': 291500} 4272.940487 Flat \n",
"209539 {'year': 2025, 'price': 290000} 3222.222222 Flat \n",
"82391 {'year': 2025, 'price': 290000} 4603.174603 Flat \n",
"\n",
" Leashold/Freehold Total floor area (sqm) \\\n",
"637 Leasehold 97.00 \n",
"2931 Leasehold 40.00 \n",
"60080 Leasehold 73.00 \n",
"75436 Leasehold 70.00 \n",
"74698 Leasehold 56.00 \n",
"... ... ... \n",
"279239 Leasehold 97.00 \n",
"293530 Leasehold 97.00 \n",
"212197 Leasehold 68.22 \n",
"209539 Leasehold 90.00 \n",
"82391 Leasehold 63.00 \n",
"\n",
" Rooms (including bedrooms & bathrooms) Approximate construction age \\\n",
"637 5.0 1996.0 \n",
"2931 1.0 1996.0 \n",
"60080 4.0 1996.0 \n",
"75436 2.0 1900.0 \n",
"74698 2.0 1996.0 \n",
"... ... ... \n",
"279239 3.0 1996.0 \n",
"293530 2.0 1900.0 \n",
"212197 2.0 1996.0 \n",
"209539 2.0 1996.0 \n",
"82391 1.0 1900.0 \n",
"\n",
" year price Price per sqm PC AVG c \n",
"637 1997 160000 1345.611429 1.225825 \n",
"2931 1997 62000 1345.611429 1.151893 \n",
"60080 1997 95000 1345.611429 0.967122 \n",
"75436 1997 63000 1345.611429 0.668841 \n",
"74698 1997 68950 1345.611429 0.915012 \n",
"... ... ... ... ... \n",
"279239 2024 285000 3598.084741 0.816586 \n",
"293530 2024 295000 3598.084741 0.845238 \n",
"212197 2025 291500 4032.779104 1.059552 \n",
"209539 2025 290000 4032.779104 0.799008 \n",
"82391 2025 290000 4032.779104 1.141440 \n",
"\n",
"[267 rows x 13 columns]"
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" <tr>\n",
" <th>151664</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 316 Smithfield Buildings, 44, Tib Street</td>\n",
" <td>{'year': 1997, 'price': 80500}</td>\n",
" <td>1319.672131</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>61.0</td>\n",
" <td>2.0</td>\n",
" <td>1996.0</td>\n",
" <td>1997</td>\n",
" <td>80500</td>\n",
" <td>1345.611429</td>\n",
" <td>0.980723</td>\n",
" </tr>\n",
" <tr>\n",
" <th>151665</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 316 Smithfield Buildings, 44, Tib Street</td>\n",
" <td>{'year': 1999, 'price': 129000}</td>\n",
" <td>2114.754098</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>61.0</td>\n",
" <td>2.0</td>\n",
" <td>1996.0</td>\n",
" <td>1999</td>\n",
" <td>129000</td>\n",
" <td>1779.166943</td>\n",
" <td>1.188620</td>\n",
" </tr>\n",
" <tr>\n",
" <th>151666</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 316 Smithfield Buildings, 44, Tib Street</td>\n",
" <td>{'year': 2001, 'price': 155000}</td>\n",
" <td>2540.983607</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>61.0</td>\n",
" <td>2.0</td>\n",
" <td>1996.0</td>\n",
" <td>2001</td>\n",
" <td>155000</td>\n",
" <td>1992.811006</td>\n",
" <td>1.275075</td>\n",
" </tr>\n",
" <tr>\n",
" <th>151667</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 316 Smithfield Buildings, 44, Tib Street</td>\n",
" <td>{'year': 2014, 'price': 180000}</td>\n",
" <td>2950.819672</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>61.0</td>\n",
" <td>2.0</td>\n",
" <td>1996.0</td>\n",
" <td>2014</td>\n",
" <td>180000</td>\n",
" <td>2938.922880</td>\n",
" <td>1.004048</td>\n",
" </tr>\n",
" <tr>\n",
" <th>151668</th>\n",
" <td>M4 1LA</td>\n",
" <td>Flat 316 Smithfield Buildings, 44, Tib Street</td>\n",
" <td>{'year': 2021, 'price': 271000}</td>\n",
" <td>4442.622951</td>\n",
" <td>Flat</td>\n",
" <td>Leasehold</td>\n",
" <td>61.0</td>\n",
" <td>2.0</td>\n",
" <td>1996.0</td>\n",
" <td>2021</td>\n",
" <td>271000</td>\n",
" <td>3695.106191</td>\n",
" <td>1.202299</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Postcode Address per EPC \\\n",
"151664 M4 1LA Flat 316 Smithfield Buildings, 44, Tib Street \n",
"151665 M4 1LA Flat 316 Smithfield Buildings, 44, Tib Street \n",
"151666 M4 1LA Flat 316 Smithfield Buildings, 44, Tib Street \n",
"151667 M4 1LA Flat 316 Smithfield Buildings, 44, Tib Street \n",
"151668 M4 1LA Flat 316 Smithfield Buildings, 44, Tib Street \n",
"\n",
" historical_prices Price per sqm Property type \\\n",
"151664 {'year': 1997, 'price': 80500} 1319.672131 Flat \n",
"151665 {'year': 1999, 'price': 129000} 2114.754098 Flat \n",
"151666 {'year': 2001, 'price': 155000} 2540.983607 Flat \n",
"151667 {'year': 2014, 'price': 180000} 2950.819672 Flat \n",
"151668 {'year': 2021, 'price': 271000} 4442.622951 Flat \n",
"\n",
" Leashold/Freehold Total floor area (sqm) \\\n",
"151664 Leasehold 61.0 \n",
"151665 Leasehold 61.0 \n",
"151666 Leasehold 61.0 \n",
"151667 Leasehold 61.0 \n",
"151668 Leasehold 61.0 \n",
"\n",
" Rooms (including bedrooms & bathrooms) Approximate construction age \\\n",
"151664 2.0 1996.0 \n",
"151665 2.0 1996.0 \n",
"151666 2.0 1996.0 \n",
"151667 2.0 1996.0 \n",
"151668 2.0 1996.0 \n",
"\n",
" year price Price per sqm PC AVG c \n",
"151664 1997 80500 1345.611429 0.980723 \n",
"151665 1999 129000 1779.166943 1.188620 \n",
"151666 2001 155000 1992.811006 1.275075 \n",
"151667 2014 180000 2938.922880 1.004048 \n",
"151668 2021 271000 3695.106191 1.202299 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"random_c = c_stats.sample(1)\n",
"display(random_c)\n",
"\n",
"# pc avg trend\n",
"temp_pc_avg = pc_avg_complex[\n",
" pc_avg_complex[\"Postcode\"] == random_c.index[0][0]\n",
"].sort_values(by=\"year\")\n",
"display(temp_pc_avg)\n",
"\n",
"# c for specific address\n",
"temp_postcode = data_small[\n",
" (data_small[\"Postcode\"] == random_c.index[0][0])\n",
" # & (data_small['Address per EPC'] == random_c.index[0][1])\n",
"].sort_values(by=\"year\")\n",
"display(temp_postcode)\n",
"\n",
"temp_address = data_small[\n",
" (data_small[\"Postcode\"] == random_c.index[0][0])\n",
" & (data_small[\"Address per EPC\"] == random_c.index[0][1])\n",
"].sort_values(by=\"year\")\n",
"display(temp_address)\n",
"\n",
"# plot\n",
"\n",
"fig, ax1 = plt.subplots()\n",
"\n",
"temp_pc_avg.plot.line(x=\"year\", y=\"Price per sqm PC AVG\", ax=ax1, color=\"black\")\n",
"temp_address.plot.line(x=\"year\", y=\"Price per sqm\", ax=ax1, color=\"green\")\n",
"\n",
"ax2 = ax1.twinx()\n",
"ax2.set_ylim(0, 3)\n",
"\n",
"for property in temp_postcode[\"Address per EPC\"].unique():\n",
" property_data = temp_postcode[temp_postcode[\"Address per EPC\"] == property]\n",
" property_data.plot.line(x=\"year\", y=\"c\", ax=ax2, color=\"orange\", style=\":\")\n",
"\n",
"temp_address.plot.line(x=\"year\", y=\"c\", ax=ax2, color=\"red\", style=\":\")\n",
"\n",
"ax1.set_ylabel(\"Price per sqm\")\n",
"ax2.set_ylabel(\"c\")\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "b0b74a2e",
"metadata": {},
"source": [
"## investigation: is it constant over time?"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "7ljy1kmdcwn",
"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></th>\n",
" <th>n_sales</th>\n",
" <th>year_min</th>\n",
" <th>year_max</th>\n",
" <th>c_mean</th>\n",
" <th>c_std</th>\n",
" <th>c_cv</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Postcode</th>\n",
" <th>Address per EPC</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>SS0 9AA</th>\n",
" <th>Pineflow, 55a Shakespeare Drive</th>\n",
" <td>3</td>\n",
" <td>1996</td>\n",
" <td>1997</td>\n",
" <td>3.960179</td>\n",
" <td>6.498855</td>\n",
" <td>1.641051</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SS0 9UU</th>\n",
" <th>94 SOUTHBOURNE GROVE, WESTCLIFF-ON-SEA</th>\n",
" <td>2</td>\n",
" <td>1996</td>\n",
" <td>1996</td>\n",
" <td>0.265513</td>\n",
" <td>0.365610</td>\n",
" <td>1.376993</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SW2 1ER</th>\n",
" <th>70a Saltoun Road</th>\n",
" <td>2</td>\n",
" <td>2001</td>\n",
" <td>2002</td>\n",
" <td>0.749516</td>\n",
" <td>1.030029</td>\n",
" <td>1.374259</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SW2 3DF</th>\n",
" <th>Flat D, 108 Christchurch Road</th>\n",
" <td>2</td>\n",
" <td>2006</td>\n",
" <td>2014</td>\n",
" <td>0.915386</td>\n",
" <td>1.249392</td>\n",
" <td>1.364880</td>\n",
" </tr>\n",
" <tr>\n",
" <th>PL6 8DY</th>\n",
" <th>43 Bluebell Street</th>\n",
" <td>2</td>\n",
" <td>2016</td>\n",
" <td>2019</td>\n",
" <td>0.561477</td>\n",
" <td>0.764020</td>\n",
" <td>1.360732</td>\n",
" </tr>\n",
" <tr>\n",
" <th>WN6 0US</th>\n",
" <th>1, Meadowacre, Standish</th>\n",
" <td>2</td>\n",
" <td>2015</td>\n",
" <td>2021</td>\n",
" <td>0.515135</td>\n",
" <td>0.697189</td>\n",
" <td>1.353411</td>\n",
" </tr>\n",
" <tr>\n",
" <th>L24 9LL</th>\n",
" <th>59 Addenbrooke Drive, Speke</th>\n",
" <td>2</td>\n",
" <td>2013</td>\n",
" <td>2020</td>\n",
" <td>0.465642</td>\n",
" <td>0.623893</td>\n",
" <td>1.339855</td>\n",
" </tr>\n",
" <tr>\n",
" <th>N10 3NR</th>\n",
" <th>Flat 2, 6 Queens Avenue</th>\n",
" <td>2</td>\n",
" <td>1997</td>\n",
" <td>2002</td>\n",
" <td>0.372452</td>\n",
" <td>0.494968</td>\n",
" <td>1.328944</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SW11 3HB</th>\n",
" <th>Flat 3 Beaufort House, 30, Winders Road</th>\n",
" <td>2</td>\n",
" <td>1996</td>\n",
" <td>2018</td>\n",
" <td>0.510002</td>\n",
" <td>0.653344</td>\n",
" <td>1.281063</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CR3 5QE</th>\n",
" <th>36 Banstead Road</th>\n",
" <td>2</td>\n",
" <td>2002</td>\n",
" <td>2023</td>\n",
" <td>0.418259</td>\n",
" <td>0.534478</td>\n",
" <td>1.277862</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SW5 9BH</th>\n",
" <th>FLAT 51, WETHERBY MANSIONS, EARL'S COURT SQUARE</th>\n",
" <td>2</td>\n",
" <td>1995</td>\n",
" <td>2022</td>\n",
" <td>0.536443</td>\n",
" <td>0.682598</td>\n",
" <td>1.272453</td>\n",
" </tr>\n",
" <tr>\n",
" <th>WD3 5LH</th>\n",
" <th>Flat 7 Sheraton House, Lower Road, Chorleywood</th>\n",
" <td>2</td>\n",
" <td>1995</td>\n",
" <td>1996</td>\n",
" <td>0.442410</td>\n",
" <td>0.552779</td>\n",
" <td>1.249472</td>\n",
" </tr>\n",
" <tr>\n",
" <th>KT13 8XF</th>\n",
" <th>27 Fortescue Road</th>\n",
" <td>2</td>\n",
" <td>2007</td>\n",
" <td>2024</td>\n",
" <td>0.481300</td>\n",
" <td>0.600319</td>\n",
" <td>1.247285</td>\n",
" </tr>\n",
" <tr>\n",
" <th>N7 6RY</th>\n",
" <th>Flat 4, 102 Tollington Way, Islington</th>\n",
" <td>2</td>\n",
" <td>2001</td>\n",
" <td>2003</td>\n",
" <td>0.959964</td>\n",
" <td>1.180041</td>\n",
" <td>1.229256</td>\n",
" </tr>\n",
" <tr>\n",
" <th>RH4 1AY</th>\n",
" <th>76, High Street</th>\n",
" <td>2</td>\n",
" <td>2004</td>\n",
" <td>2012</td>\n",
" <td>0.411008</td>\n",
" <td>0.496243</td>\n",
" <td>1.207382</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CA28 6TJ</th>\n",
" <th>2, The Crest</th>\n",
" <td>2</td>\n",
" <td>2005</td>\n",
" <td>2013</td>\n",
" <td>0.509162</td>\n",
" <td>0.593252</td>\n",
" <td>1.165152</td>\n",
" </tr>\n",
" <tr>\n",
" <th>W1U 3DR</th>\n",
" <th>20 Jacobs Well Mews</th>\n",
" <td>3</td>\n",
" <td>2003</td>\n",
" <td>2022</td>\n",
" <td>0.426429</td>\n",
" <td>0.496747</td>\n",
" <td>1.164898</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SG6 4DL</th>\n",
" <th>20, Icknield Green</th>\n",
" <td>2</td>\n",
" <td>2016</td>\n",
" <td>2016</td>\n",
" <td>0.546056</td>\n",
" <td>0.632503</td>\n",
" <td>1.158312</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SO51 6DA</th>\n",
" <th>Lukes Barn, Maurys Lane, West Wellow</th>\n",
" <td>2</td>\n",
" <td>1995</td>\n",
" <td>2012</td>\n",
" <td>0.606841</td>\n",
" <td>0.697969</td>\n",
" <td>1.150169</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NR27 0DJ</th>\n",
" <th>139 Kings Chalet Park, Overstrand Road</th>\n",
" <td>2</td>\n",
" <td>1996</td>\n",
" <td>2023</td>\n",
" <td>0.415552</td>\n",
" <td>0.477604</td>\n",
" <td>1.149325</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" n_sales year_min \\\n",
"Postcode Address per EPC \n",
"SS0 9AA Pineflow, 55a Shakespeare Drive 3 1996 \n",
"SS0 9UU 94 SOUTHBOURNE GROVE, WESTCLIFF-ON-SEA 2 1996 \n",
"SW2 1ER 70a Saltoun Road 2 2001 \n",
"SW2 3DF Flat D, 108 Christchurch Road 2 2006 \n",
"PL6 8DY 43 Bluebell Street 2 2016 \n",
"WN6 0US 1, Meadowacre, Standish 2 2015 \n",
"L24 9LL 59 Addenbrooke Drive, Speke 2 2013 \n",
"N10 3NR Flat 2, 6 Queens Avenue 2 1997 \n",
"SW11 3HB Flat 3 Beaufort House, 30, Winders Road 2 1996 \n",
"CR3 5QE 36 Banstead Road 2 2002 \n",
"SW5 9BH FLAT 51, WETHERBY MANSIONS, EARL'S COURT SQUARE 2 1995 \n",
"WD3 5LH Flat 7 Sheraton House, Lower Road, Chorleywood 2 1995 \n",
"KT13 8XF 27 Fortescue Road 2 2007 \n",
"N7 6RY Flat 4, 102 Tollington Way, Islington 2 2001 \n",
"RH4 1AY 76, High Street 2 2004 \n",
"CA28 6TJ 2, The Crest 2 2005 \n",
"W1U 3DR 20 Jacobs Well Mews 3 2003 \n",
"SG6 4DL 20, Icknield Green 2 2016 \n",
"SO51 6DA Lukes Barn, Maurys Lane, West Wellow 2 1995 \n",
"NR27 0DJ 139 Kings Chalet Park, Overstrand Road 2 1996 \n",
"\n",
" year_max c_mean \\\n",
"Postcode Address per EPC \n",
"SS0 9AA Pineflow, 55a Shakespeare Drive 1997 3.960179 \n",
"SS0 9UU 94 SOUTHBOURNE GROVE, WESTCLIFF-ON-SEA 1996 0.265513 \n",
"SW2 1ER 70a Saltoun Road 2002 0.749516 \n",
"SW2 3DF Flat D, 108 Christchurch Road 2014 0.915386 \n",
"PL6 8DY 43 Bluebell Street 2019 0.561477 \n",
"WN6 0US 1, Meadowacre, Standish 2021 0.515135 \n",
"L24 9LL 59 Addenbrooke Drive, Speke 2020 0.465642 \n",
"N10 3NR Flat 2, 6 Queens Avenue 2002 0.372452 \n",
"SW11 3HB Flat 3 Beaufort House, 30, Winders Road 2018 0.510002 \n",
"CR3 5QE 36 Banstead Road 2023 0.418259 \n",
"SW5 9BH FLAT 51, WETHERBY MANSIONS, EARL'S COURT SQUARE 2022 0.536443 \n",
"WD3 5LH Flat 7 Sheraton House, Lower Road, Chorleywood 1996 0.442410 \n",
"KT13 8XF 27 Fortescue Road 2024 0.481300 \n",
"N7 6RY Flat 4, 102 Tollington Way, Islington 2003 0.959964 \n",
"RH4 1AY 76, High Street 2012 0.411008 \n",
"CA28 6TJ 2, The Crest 2013 0.509162 \n",
"W1U 3DR 20 Jacobs Well Mews 2022 0.426429 \n",
"SG6 4DL 20, Icknield Green 2016 0.546056 \n",
"SO51 6DA Lukes Barn, Maurys Lane, West Wellow 2012 0.606841 \n",
"NR27 0DJ 139 Kings Chalet Park, Overstrand Road 2023 0.415552 \n",
"\n",
" c_std c_cv \n",
"Postcode Address per EPC \n",
"SS0 9AA Pineflow, 55a Shakespeare Drive 6.498855 1.641051 \n",
"SS0 9UU 94 SOUTHBOURNE GROVE, WESTCLIFF-ON-SEA 0.365610 1.376993 \n",
"SW2 1ER 70a Saltoun Road 1.030029 1.374259 \n",
"SW2 3DF Flat D, 108 Christchurch Road 1.249392 1.364880 \n",
"PL6 8DY 43 Bluebell Street 0.764020 1.360732 \n",
"WN6 0US 1, Meadowacre, Standish 0.697189 1.353411 \n",
"L24 9LL 59 Addenbrooke Drive, Speke 0.623893 1.339855 \n",
"N10 3NR Flat 2, 6 Queens Avenue 0.494968 1.328944 \n",
"SW11 3HB Flat 3 Beaufort House, 30, Winders Road 0.653344 1.281063 \n",
"CR3 5QE 36 Banstead Road 0.534478 1.277862 \n",
"SW5 9BH FLAT 51, WETHERBY MANSIONS, EARL'S COURT SQUARE 0.682598 1.272453 \n",
"WD3 5LH Flat 7 Sheraton House, Lower Road, Chorleywood 0.552779 1.249472 \n",
"KT13 8XF 27 Fortescue Road 0.600319 1.247285 \n",
"N7 6RY Flat 4, 102 Tollington Way, Islington 1.180041 1.229256 \n",
"RH4 1AY 76, High Street 0.496243 1.207382 \n",
"CA28 6TJ 2, The Crest 0.593252 1.165152 \n",
"W1U 3DR 20 Jacobs Well Mews 0.496747 1.164898 \n",
"SG6 4DL 20, Icknield Green 0.632503 1.158312 \n",
"SO51 6DA Lukes Barn, Maurys Lane, West Wellow 0.697969 1.150169 \n",
"NR27 0DJ 139 Kings Chalet Park, Overstrand Road 0.477604 1.149325 "
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# 1. Coefficient of Variation (std/mean) per property, filtered to 3+ sales\n",
"c_stats = (\n",
" data_small.groupby([\"Postcode\", \"Address per EPC\"])\n",
" .agg(\n",
" n_sales=(\"c\", \"count\"),\n",
" year_min=(\"year\", \"min\"),\n",
" year_max=(\"year\", \"max\"),\n",
" c_mean=(\"c\", \"mean\"),\n",
" c_std=(\"c\", \"std\"),\n",
" )\n",
" .dropna()\n",
")\n",
"c_stats[\"c_cv\"] = c_stats[\"c_std\"] / c_stats[\"c_mean\"]\n",
"# c_stats_3plus = c_stats[c_stats['n_sales'] >= 3]\n",
"# print(f\"Properties with 3+ sales: {len(c_stats_3plus)} / {len(c_stats)}\")\n",
"c_stats.sort_values(\"c_cv\", ascending=False).head(20)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "qe21ukn7u5n",
"metadata": {},
"outputs": [
{
"data": {
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",
"text/plain": [
"<Figure size 1200x400 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"46.4% of properties have CV < 0.1\n",
"79.6% of properties have CV < 0.2\n",
"92.0% of properties have CV < 0.3\n"
]
}
],
"source": [
"# 2. Histogram of std and CV across all properties (3+ sales)\n",
"import matplotlib.pyplot as plt\n",
"\n",
"fig, axes = plt.subplots(1, 2, figsize=(12, 4))\n",
"\n",
"axes[0].hist(c_stats[\"c_std\"], bins=100, edgecolor=\"black\")\n",
"axes[0].set_xlabel(\"Std of c\")\n",
"axes[0].set_ylabel(\"Number of properties\")\n",
"axes[0].set_title(\"Distribution of c stability (std)\")\n",
"axes[0].axvline(\n",
" x=c_stats[\"c_std\"].median(),\n",
" color=\"red\",\n",
" linestyle=\"--\",\n",
" label=f\"Median ({c_stats['c_std'].median()}) threshold\",\n",
")\n",
"axes[0].legend()\n",
"\n",
"axes[1].hist(c_stats[\"c_cv\"], bins=100, edgecolor=\"black\")\n",
"axes[1].set_xlabel(\"CV of c (std/mean)\")\n",
"axes[1].set_ylabel(\"Number of properties\")\n",
"axes[1].set_title(\"Distribution of c stability (CV)\")\n",
"axes[1].axvline(\n",
" x=c_stats[\"c_cv\"].median(),\n",
" color=\"red\",\n",
" linestyle=\"--\",\n",
" label=f\"Median ({c_stats['c_cv'].median()}) threshold\",\n",
")\n",
"axes[1].legend()\n",
"\n",
"plt.tight_layout()\n",
"plt.show()\n",
"\n",
"# output text\n",
"pct_stable = (c_stats[\"c_cv\"] < 0.1).mean() * 100\n",
"print(f\"{pct_stable:.1f}% of properties have CV < 0.1\")\n",
"\n",
"pct_stable = (c_stats[\"c_cv\"] < 0.2).mean() * 100\n",
"print(f\"{pct_stable:.1f}% of properties have CV < 0.2\")\n",
"\n",
"pct_stable = (c_stats[\"c_cv\"] < 0.3).mean() * 100\n",
"print(f\"{pct_stable:.1f}% of properties have CV < 0.3\")"
]
},
{
"cell_type": "markdown",
"id": "567b53f1",
"metadata": {},
"source": [
"So about half are very stable. Now investigate - of the unstable c values, was it stable for a period, then a sudden change but is at a new stable value afterwards? If so, then could suggest an underlying attribute has materially changed (e.g. renovation)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "129dbfd2",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Postcode Address per EPC \n",
"SS0 9AA Pineflow, 55a Shakespeare Drive 1.641051\n",
"SS0 9UU 94 SOUTHBOURNE GROVE, WESTCLIFF-ON-SEA 1.376993\n",
"SW2 1ER 70a Saltoun Road 1.374259\n",
"SW2 3DF Flat D, 108 Christchurch Road 1.364880\n",
"PL6 8DY 43 Bluebell Street 1.360732\n",
"WN6 0US 1, Meadowacre, Standish 1.353411\n",
"L24 9LL 59 Addenbrooke Drive, Speke 1.339855\n",
"N10 3NR Flat 2, 6 Queens Avenue 1.328944\n",
"SW11 3HB Flat 3 Beaufort House, 30, Winders Road 1.281063\n",
"CR3 5QE 36 Banstead Road 1.277862\n",
"SW5 9BH FLAT 51, WETHERBY MANSIONS, EARL'S COURT SQUARE 1.272453\n",
"WD3 5LH Flat 7 Sheraton House, Lower Road, Chorleywood 1.249472\n",
"KT13 8XF 27 Fortescue Road 1.247285\n",
"N7 6RY Flat 4, 102 Tollington Way, Islington 1.229256\n",
"RH4 1AY 76, High Street 1.207382\n",
"CA28 6TJ 2, The Crest 1.165152\n",
"W1U 3DR 20 Jacobs Well Mews 1.164898\n",
"SG6 4DL 20, Icknield Green 1.158312\n",
"SO51 6DA Lukes Barn, Maurys Lane, West Wellow 1.150169\n",
"NR27 0DJ 139 Kings Chalet Park, Overstrand Road 1.149325\n",
"Name: c_cv, dtype: float64"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"3\n",
"SW2 3DF\n",
"Flat D, 108 Christchurch Road\n"
]
},
{
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" <th></th>\n",
" <th>Postcode</th>\n",
" <th>year</th>\n",
" <th>Price per sqm PC AVG</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>229787</th>\n",
" <td>SW2 3DF</td>\n",
" <td>1992</td>\n",
" <td>1211.205828</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229788</th>\n",
" <td>SW2 3DF</td>\n",
" <td>1993</td>\n",
" <td>859.426128</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229789</th>\n",
" <td>SW2 3DF</td>\n",
" <td>1994</td>\n",
" <td>1012.719731</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229790</th>\n",
" <td>SW2 3DF</td>\n",
" <td>1995</td>\n",
" <td>986.462940</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229791</th>\n",
" <td>SW2 3DF</td>\n",
" <td>1996</td>\n",
" <td>1050.105052</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229792</th>\n",
" <td>SW2 3DF</td>\n",
" <td>1997</td>\n",
" <td>1231.052659</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229793</th>\n",
" <td>SW2 3DF</td>\n",
" <td>1998</td>\n",
" <td>1459.428040</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229794</th>\n",
" <td>SW2 3DF</td>\n",
" <td>1999</td>\n",
" <td>1717.824419</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229795</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2000</td>\n",
" <td>2015.268874</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229796</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2001</td>\n",
" <td>2294.071930</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229797</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2002</td>\n",
" <td>2970.672857</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229798</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2003</td>\n",
" <td>3276.062592</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229799</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2004</td>\n",
" <td>3491.190047</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229800</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2005</td>\n",
" <td>3802.847099</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229801</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2006</td>\n",
" <td>3609.831360</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229802</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2007</td>\n",
" <td>3489.470558</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229803</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2008</td>\n",
" <td>3373.234697</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229804</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2009</td>\n",
" <td>3676.732944</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229805</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2010</td>\n",
" <td>3918.815428</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229806</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2011</td>\n",
" <td>4721.461812</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229807</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2012</td>\n",
" <td>5121.047171</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229808</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2013</td>\n",
" <td>5629.903491</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229809</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2014</td>\n",
" <td>6100.588039</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229810</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2015</td>\n",
" <td>6343.983693</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229811</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2016</td>\n",
" <td>6595.750392</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229812</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2017</td>\n",
" <td>6553.915908</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229813</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2018</td>\n",
" <td>7038.672750</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229814</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2019</td>\n",
" <td>7006.037364</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229815</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2020</td>\n",
" <td>6824.060025</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229816</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2021</td>\n",
" <td>7172.611001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229817</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2022</td>\n",
" <td>7159.720050</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229818</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2023</td>\n",
" <td>7303.259037</td>\n",
" </tr>\n",
" <tr>\n",
" <th>229819</th>\n",
" <td>SW2 3DF</td>\n",
" <td>2024</td>\n",
" <td>8276.355759</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Postcode year Price per sqm PC AVG\n",
"229787 SW2 3DF 1992 1211.205828\n",
"229788 SW2 3DF 1993 859.426128\n",
"229789 SW2 3DF 1994 1012.719731\n",
"229790 SW2 3DF 1995 986.462940\n",
"229791 SW2 3DF 1996 1050.105052\n",
"229792 SW2 3DF 1997 1231.052659\n",
"229793 SW2 3DF 1998 1459.428040\n",
"229794 SW2 3DF 1999 1717.824419\n",
"229795 SW2 3DF 2000 2015.268874\n",
"229796 SW2 3DF 2001 2294.071930\n",
"229797 SW2 3DF 2002 2970.672857\n",
"229798 SW2 3DF 2003 3276.062592\n",
"229799 SW2 3DF 2004 3491.190047\n",
"229800 SW2 3DF 2005 3802.847099\n",
"229801 SW2 3DF 2006 3609.831360\n",
"229802 SW2 3DF 2007 3489.470558\n",
"229803 SW2 3DF 2008 3373.234697\n",
"229804 SW2 3DF 2009 3676.732944\n",
"229805 SW2 3DF 2010 3918.815428\n",
"229806 SW2 3DF 2011 4721.461812\n",
"229807 SW2 3DF 2012 5121.047171\n",
"229808 SW2 3DF 2013 5629.903491\n",
"229809 SW2 3DF 2014 6100.588039\n",
"229810 SW2 3DF 2015 6343.983693\n",
"229811 SW2 3DF 2016 6595.750392\n",
"229812 SW2 3DF 2017 6553.915908\n",
"229813 SW2 3DF 2018 7038.672750\n",
"229814 SW2 3DF 2019 7006.037364\n",
"229815 SW2 3DF 2020 6824.060025\n",
"229816 SW2 3DF 2021 7172.611001\n",
"229817 SW2 3DF 2022 7159.720050\n",
"229818 SW2 3DF 2023 7303.259037\n",
"229819 SW2 3DF 2024 8276.355759"
]
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" <tr>\n",
" <th>328924</th>\n",
" <td>KT13 8XF</td>\n",
" <td>33 Fortescue Road</td>\n",
" <td>{'year': 1996, 'price': 112000}</td>\n",
" <td>1244.444444</td>\n",
" <td>Bungalow</td>\n",
" <td>Freehold</td>\n",
" <td>90.0</td>\n",
" <td>3.0</td>\n",
" <td>1950.0</td>\n",
" <td>1996</td>\n",
" <td>112000</td>\n",
" <td>1965.247585</td>\n",
" <td>0.633225</td>\n",
" </tr>\n",
" <tr>\n",
" <th>328925</th>\n",
" <td>KT13 8XF</td>\n",
" <td>33 Fortescue Road</td>\n",
" <td>{'year': 1999, 'price': 170000}</td>\n",
" <td>1888.888889</td>\n",
" <td>Bungalow</td>\n",
" <td>Freehold</td>\n",
" <td>90.0</td>\n",
" <td>3.0</td>\n",
" <td>1950.0</td>\n",
" <td>1999</td>\n",
" <td>170000</td>\n",
" <td>2805.203443</td>\n",
" <td>0.673352</td>\n",
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" <th>328926</th>\n",
" <td>KT13 8XF</td>\n",
" <td>33 Fortescue Road</td>\n",
" <td>{'year': 2003, 'price': 325000}</td>\n",
" <td>3611.111111</td>\n",
" <td>Bungalow</td>\n",
" <td>Freehold</td>\n",
" <td>90.0</td>\n",
" <td>3.0</td>\n",
" <td>1950.0</td>\n",
" <td>2003</td>\n",
" <td>325000</td>\n",
" <td>3934.841426</td>\n",
" <td>0.917727</td>\n",
" </tr>\n",
" <tr>\n",
" <th>328927</th>\n",
" <td>KT13 8XF</td>\n",
" <td>33 Fortescue Road</td>\n",
" <td>{'year': 2007, 'price': 470000}</td>\n",
" <td>5222.222222</td>\n",
" <td>Bungalow</td>\n",
" <td>Freehold</td>\n",
" <td>90.0</td>\n",
" <td>3.0</td>\n",
" <td>1950.0</td>\n",
" <td>2007</td>\n",
" <td>470000</td>\n",
" <td>3946.702433</td>\n",
" <td>1.323186</td>\n",
" </tr>\n",
" <tr>\n",
" <th>328928</th>\n",
" <td>KT13 8XF</td>\n",
" <td>33 Fortescue Road</td>\n",
" <td>{'year': 2023, 'price': 807500}</td>\n",
" <td>8972.222222</td>\n",
" <td>Bungalow</td>\n",
" <td>Freehold</td>\n",
" <td>90.0</td>\n",
" <td>3.0</td>\n",
" <td>1950.0</td>\n",
" <td>2023</td>\n",
" <td>807500</td>\n",
" <td>8816.246845</td>\n",
" <td>1.017692</td>\n",
" </tr>\n",
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"text/plain": [
" Postcode Address per EPC historical_prices \\\n",
"328924 KT13 8XF 33 Fortescue Road {'year': 1996, 'price': 112000} \n",
"328925 KT13 8XF 33 Fortescue Road {'year': 1999, 'price': 170000} \n",
"328926 KT13 8XF 33 Fortescue Road {'year': 2003, 'price': 325000} \n",
"328927 KT13 8XF 33 Fortescue Road {'year': 2007, 'price': 470000} \n",
"328928 KT13 8XF 33 Fortescue Road {'year': 2023, 'price': 807500} \n",
"\n",
" Price per sqm Property type Leashold/Freehold Total floor area (sqm) \\\n",
"328924 1244.444444 Bungalow Freehold 90.0 \n",
"328925 1888.888889 Bungalow Freehold 90.0 \n",
"328926 3611.111111 Bungalow Freehold 90.0 \n",
"328927 5222.222222 Bungalow Freehold 90.0 \n",
"328928 8972.222222 Bungalow Freehold 90.0 \n",
"\n",
" Rooms (including bedrooms & bathrooms) Approximate construction age \\\n",
"328924 3.0 1950.0 \n",
"328925 3.0 1950.0 \n",
"328926 3.0 1950.0 \n",
"328927 3.0 1950.0 \n",
"328928 3.0 1950.0 \n",
"\n",
" year price Price per sqm PC AVG c \n",
"328924 1996 112000 1965.247585 0.633225 \n",
"328925 1999 170000 2805.203443 0.673352 \n",
"328926 2003 325000 3934.841426 0.917727 \n",
"328927 2007 470000 3946.702433 1.323186 \n",
"328928 2023 807500 8816.246845 1.017692 "
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" <th>332499</th>\n",
" <td>SW2 3DF</td>\n",
" <td>Flat D, 108 Christchurch Road</td>\n",
" <td>{'year': 2006, 'price': 500000}</td>\n",
" <td>6493.506494</td>\n",
" <td>Flat</td>\n",
" <td>Freehold</td>\n",
" <td>77.0</td>\n",
" <td>4.0</td>\n",
" <td>1900.0</td>\n",
" <td>2006</td>\n",
" <td>500000</td>\n",
" <td>3609.831360</td>\n",
" <td>1.798839</td>\n",
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" <th>332500</th>\n",
" <td>SW2 3DF</td>\n",
" <td>Flat D, 108 Christchurch Road</td>\n",
" <td>{'year': 2014, 'price': 15000}</td>\n",
" <td>194.805195</td>\n",
" <td>Flat</td>\n",
" <td>Freehold</td>\n",
" <td>77.0</td>\n",
" <td>4.0</td>\n",
" <td>1900.0</td>\n",
" <td>2014</td>\n",
" <td>15000</td>\n",
" <td>6100.588039</td>\n",
" <td>0.031932</td>\n",
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" Postcode Address per EPC \\\n",
"332499 SW2 3DF Flat D, 108 Christchurch Road \n",
"332500 SW2 3DF Flat D, 108 Christchurch Road \n",
"\n",
" historical_prices Price per sqm Property type \\\n",
"332499 {'year': 2006, 'price': 500000} 6493.506494 Flat \n",
"332500 {'year': 2014, 'price': 15000} 194.805195 Flat \n",
"\n",
" Leashold/Freehold Total floor area (sqm) \\\n",
"332499 Freehold 77.0 \n",
"332500 Freehold 77.0 \n",
"\n",
" Rooms (including bedrooms & bathrooms) Approximate construction age \\\n",
"332499 4.0 1900.0 \n",
"332500 4.0 1900.0 \n",
"\n",
" year price Price per sqm PC AVG c \n",
"332499 2006 500000 3609.831360 1.798839 \n",
"332500 2014 15000 6100.588039 0.031932 "
]
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evMnOnTtfO7jA0tKSgQMHcvnyZY4fP86YMWPo06cPDg4OAHz77bfMnj2bxYsXc+PGDby9vVm7di0///xzpuJft24dq1ev5urVq9y5c4f169djZWVFxYoVqV69Op06deKzzz7jzJkzXLhwgaFDh5qsw+8vv/yCTqejSZMmbN++nZs3b+Lr68vixYtxc3NLdx8vLy8uXrzI0KFDqVOnjtHWr18/fv/9d8Nt6NatW+Pi4sKAAQOoUaMGzZs3NzrWl19+iZubG23btmXRokVcvHgRf39/9u/fz969e9MuwZcYDVG34Flwjnw/JEnK35IHioG8JZvdZHJXiGm1WoYPH87EiRP5448/uH37NqdPn37t8isv2r59O40bN6Zfv37UqlWLiRMnotPpAKVl79ixY9y4cYNWrVrh6urKtGnTKFu27CuP6eLiQu/evenSpQsdOnSgXr16LFu2zPD60KFDWbVqFWvXrqVu3bq0adOGdevWZbrlzs7OjpUrV9KiRQvq1avHwYMH2bVrFyVLlgSUEaNly5alTZs29O7dm+HDh6c7ajg3VK5cmYsXL/LOO+8wfvx46tSpQ/v27Tl06BDLly9Pd5/Vq1dTq1Ytw4jX1Hr16kVYWBh79uwBlBbnwYMH8/TpUwYPHpymfvIHgUmTJrF27VpatmxJzZo1GTt2LC1atGDHjh3GO1z/GXZVxex6+hMkS5JUuP35558kJiZSt25dateubepwChSVeJOe2oVEcHAwFSpUICgoiPLlyxu9FhERQUBAAC4uLvlyYl+9Xs/s2bNZuXIl9+/fx9HRkREjRjB58mSjenFxcfj7+xta+3LSjBkz2LFjB15eXjl6nqyqVKkSY8eOZezYsaYOJW/zWwqXvyKp/IfcLD4+V353JEnKP9q2bcvhw4f54Ycf0rznZJdXvX8XZCZtudPpdEydOhVnZ2esrKyoUqUK33//vdHIQCEE06ZNw9HRESsrK9q1a8fNmzeNjvPkyRP69++Pra0tdnZ2DBkyxNDpPtmVK1do1aoVlpaWVKhQgblz5+bKNeZ1arWaKVOmcPfuXRISEggICMixPzKpkKnmDn2iSWq41NSRSJKUx4SEhHDkyBEAPvzwQxNHU/CYNLn78ccfWb58OUuXLsXX15cff/yRuXPnGi1jNHfuXBYvXsyKFSs4c+YMNjY2dOzYkbi4OEOd/v37c+3aNQ4cOMDu3bv5999/jdY+jYyMpEOHDlSsWJELFy4wb948ZsyYwW+//Zar1ytJhYrsHC1J0kts3rwZIQRubm5ZGggnvYYJ59gTXbt2FYMHDzYq6927t+jfv78QQlnOyMHBQcybN8/wenh4uNBqtWLjxo1CCCF8fHwEoEwa/NzevXuFSqUS9+7dE0IIsWzZMlG8eHERHx9vqDNp0iRRvXr1DMVZUJcfywy5hJSUVfJ3R5KkFzVp0kQAYvHixTl6HjmJsQk0b96cQ4cOGabRuHz5MidOnKBz584A+Pv7ExoaSrt27Qz7FCtWjKZNm+Lp6QmAp6cndnZ2RpPVtmvXDrVabVgc3dPTk9atWxtNvdGxY0f8/Px4+vRpmrji4+OJjIw0bFFRUdl/8ZJU0MU/hjPDMD83yNSRSJKUh9y+fZuzZ8+iVqvp06ePqcMpkEw6ifFXX31FZGQkNWrUQKPRoNPpmDVrFv379wcgNDQUSJnxP5m9vb3htdDQ0DSjF83MzChRooRRnRebfZOPGRoaSvHixY1emz17Nt9++202XaUkFWK3V6EBKPm1qSORJCmP2LRpEwDvvvtumvd3KXuYtOVuy5YteHh4sGHDBsOiwfPnz0+z+Htumzx5MhEREYbNx8fHpPFIUr5kbgf1viex/gJUclC+JEnPpZ64WMoZJm25mzBhAl999ZVhpEzdunUJCAhg9uzZDBw40DBh7YMHDwzLHCU/b9CgAaDM6B8WFmZ03KSkJJ48eWLY38HBgQcPHhjVSX6eXCe15BUbkr1uPVBJktKh1kCdb9DFxSFesY6wJEmFh7e3N9euXcPCwoLevXubOpwCy6Qtd8+ePUuzdqlGozGsv+ns7IyDg4PRCgqRkZGcOXPGMCO/m5sb4eHhRktEHT58GL1eb1hL083NjX///ZfExERDnQMHDlC9evU0t2QlSZIkScoZGzZsAKBLly7Y2dmZNpgCzKTJXffu3Zk1axb//PMPd+/e5a+//uLnn3+mV69egDJj/tixY5k5cyZ///033t7eDBgwgLJly9KzZ08AatasSadOnRg2bBhnz57l5MmTjB49mg8//NCwCsJHH32EhYUFQ4YM4dq1a2zevJlFixYxbtw4U126JBUOCeGoom+jTpKt35JU2AkhDP3t5C3ZHGbKobqRkZHiiy++EE5OTsLS0lJUrlxZTJkyxWjKEr1eL6ZOnSrs7e2FVqsVbdu2FX5+fkbHefz4sejXr58oUqSIsLW1FZ9++qmIiooyqnP58mXRsmVLodVqRbly5cScOXMyHKecCsV4OouKFSuKBQsWmDokKT841F4ID0TwiTlyKhRJKuROnTolAFGkSJFce88srFOhmLTPXdGiRVm4cCELFy58aR2VSsV3333Hd99999I6JUqUMDT1vky9evU4fvx4VkMtkPz9/Xn8+DGgfJ8tLCwoWbIkjo6OqF4xAe25c+ewsbHJrTCl/MyiBMKsCCqR+Pq6kiQVaMkDKXr06JEvl+vMT0ya3EmmZ2tri7OzM3q9noiICAIDA1GpVEYDWJKJ5yMeS5cundthZovExETMzc1NHUbh0mID8fEJRPj7U8LUsUiSZDJJSUls2bIFkLdkc4NJ+9xJecOCBQuoXbs2FSpU4L333mPOnDmA0rJ369YtQkJCuH79Ovfv3wegUqVKRq2t4eHhfPbZZ9jb22NpaUmdOnXYvXu34fUTJ07QqlUrrKysqFChAmPGjCEmJual8cyYMYMGDRrw66+/UqFCBaytrenTpw8RERFG9VatWkXNmjWxtLSkRo0aLFu2zPDa3bt3UalUbN68mTZt2mBpaYmHh0eacwkhmDFjBk5OTmi1WsqWLcuYMWMMr4eFhdG9e3esrKxwdnbGw8MjzfWrVCp+/fVXunXrhrW1NTVr1sTT05Nbt27x9ttvY2NjQ/Pmzbl9+3bGfiAFiUr+i5EkCY4ePcqDBw8oUaIE7du3N3U4BZ5sucsBQgj0Qg9JzxMYjXXKOpu6BBCJoDIDTcp0Kyl1rVLeEPWJoE8AlQY0lq+vqzZHrVK/8pbqi+bPn8+2bdtYsGABLVu25Ny5c4YVQ0AZnazRaKhUqVKakc0Aer2ezp07ExUVxfr166lSpQo+Pj5oNBpAmYm8U6dOzJw5kzVr1vDw4UNGjx7N6NGjWbt27UvjunXrFlu2bGHXrl1ERkYyZMgQRo0aZUjQPDw8mDZtGkuXLsXV1ZVLly4xbNgwbGxsGDhwoOE4X331FT/99BOurq5YWlqmOc/27dtZsGABmzZtonbt2oSGhnL58mXD64MGDeL+/fscOXIEc3NzxowZk2bqHYDvv/+en3/+mZ9//plJkybx0UcfUblyZSZPnoyTkxODBw9m9OjR7N27NwM/FUmSpIIl+Zbsf/7zH6PVoqQcYuI+f/lCZgdUJOmSxLl754TwQAgPxCX//4lz986Jc/fOieBTI4XwQIQd7mEoO3fvnEjaaCmEB+LyrZ2GsoDTXwrhgXh0oKNR3YQtdkJ4ILxvbDKU+Z/7WjmOLinD13XlyhVhYWEhVq5cKfR6vYiIiBDnz58XgYGBQggh7ty5I7y8vIROp3vpgIr9+/cLtVqdZpBLsiFDhojhw4cblR0/flyo1eqXdrCfPn260Gg0Ijg42FC2d+9eoVarRUhIiBBCiCpVqogNGzYY7ff9998LNzc3IYQQ/v7+AhALFy585ffgp59+EtWqVRMJCQlpXvPz8xOAOHv2rKHM19dXAEYDSgDxzTffGJ57enoKQKxevdpQtnHjRmFpafnKWAqkR+dE4slPxYPDY+SACkkqpOLi4kSxYsUEII4ePZqr5y6sAyrkPZNC7Pbt2yQkJGBvb8/Fixe5efMmJUqUMEwhA2BlZZVui10yLy8vypcvT7Vq1dJ9/fLly6xbt44iRYoYto4dO6LX6/F/xcS2Tk5OlCtXzvDczc0NvV6Pn58fMTEx3L59myFDhhgdd+bMmWlufaZeczg9H3zwAbGxsVSuXJlhw4bx119/kZSUBICvry9mZmY0atTIUL9GjRrpzs1Ur149w+Pk5XTq1q1rVBYXF1f4JsSOvYfZ3bUUjThq6kgkSTKRvXv3EhERQbly5WjVqpWpwykU5G3ZHKBWqXF1cEX3H6WPWN3Ut2VL/4Su0RxKqMwokfq2bO8H6IDaqW+1lqmDznUGdioNrqlvy/YIQAfUfKFuhee3ZTMqeRWOqlWr4uzsjIWFRZpbuq9K7EBJ/l4lOjqazz77zKgfWzInJ6cMx/riMQFWrlxpmKg6WfLt4GSvG9VboUIF/Pz8OHjwIAcOHGDUqFHMmzePY8eOZSqm1AM1kr+H6ZUlT9BdaBSrQ2Kt6TyJsaGkqWORJMkkkm/J9u3b97XvKVL2kMldDlCpVGhUGrCwTfui2gpIJyFKt64GSNtP7OV1M8fZ2RlLS0tOnDhBjRo1Mr0/KC1WwcHB3LhxI93Wu4YNG+Lj44OLi0umjhsYGMj9+/cNrYinT59GrVZTvXp17O3tKVu2LHfu3KF///5Zijs1KysrunfvTvfu3XF3d6dGjRp4e3tTo0YNkpKSuHDhAo0bNwbAz8+P8PDwNz5noVG0CroaXxHp7y+TO0kqhKKjo9m1axcgR8nmJpncFWJarZbhw4czceJELCwsaNGiBQ8fPuTatWsMGTIkQ8do06YNrVu35v333+fnn3/GxcWF69evo1Kp6NSpE5MmTaJZs2aMHj2aoUOHYmNjg4+PDwcOHGDp0qUvPa6lpSUDBw5k/vz5REZGMmbMGPr06WNYC/jbb79lzJgxFCtWjE6dOhEfH8/58+d5+vRpplYeWbduHTqdjqZNm2Jtbc369euxsrKiYsWKlCxZkk6dOvHZZ5+xfPlyzMzMGDt27GtbKyVJkiTFzp07iY2NxcXFxaiLi5SzZPtoIefu7s748eOZNm0aNWvWpG/fvumOBn2V7du307hxY/r160etWrWYOHEiOp0OUFr2jh07xo0bN2jVqhWurq5MmzbNqF9felxcXOjduzddunShQ4cO1KtXz2iqk6FDh7Jq1SrWrl1L3bp1adOmDevWrcPZ2TlTsdvZ2bFy5UpatGhBvXr1OHjwILt27aJkSaWdae3atZQtW5Y2bdrQu3dvhg8fTpkyZTJ1jkIv4Qnm8QHKiG5JkgqV5Fuy/fr1y9RMDtKbUQnxfGZa6aWCg4OpUKECQUFBlC9f3ui1iIgIAgICcHFxKdAzbsfFxeHv72+4lZuTZsyYwY4dO/Dy8srR82RVpUqVGDt2LGPHjjV1KPmC2GSFSh9HfEdftCWzdvtfkqT85/Hjxzg4OJCUlISPjw81a9bM9Rhe9f5dkMmWO0mScpZFcXRqG0iKNnUkkiTlom3btpGUlESDBg1MktgVZrLPnSRJOSq+0w38A4JwLpa5W+aSJOVvqW/JSrlLJndSnjNjxgxmzJhh6jBe6u7du6YOIX9Ry38zklTY3Lt3j3///ReADz/80MTRFD7ytqwkSZIkSdlq8+bNCCFo0aJFluc0lbJOJneSJOUodfB2HAKnob63w9ShSJKUS+QtWdOSyZ0kSTlK9eQcxR9vQ/3krKlDkSQpF9y8eZPz58+j0Wj44IMPTB1OoSSTuzdkZqb0Jyp0y0pJUgbFl3yHMMcxULazqUORJCkXJLfatWvXLt/NC7p8+XLq1auHra0ttra2uLm5sXfv3lfus3XrVmrUqIGlpSV169Zlz549uRTty8mezm9Io9GgVqtJSkoiKSmpwK6bp9frEUIQHx9v6lCkfESv1xMqamNeuQGasrLfjSQVdEKIfH1Ltnz58syZM4eqVasihOD333+nR48eXLp0idq1a6epf+rUKfr168fs2bPp1q0bGzZsoGfPnly8eJE6deqY4AoUchLjDHjVJIjJk/uWK1fOaKH4giY+Pp7AwEBDMitJGaVWq3F2dsbCwsLUoUiSlMO8vLxwdXVFq9USFhaGrW06a6HnouyYxLhEiRLMmzcv3WU5+/btS0xMDLt37zaUNWvWjAYNGrBixYosx/2mZMtdNrGwsECr1VJQc2UhBGZmZpQrVw6tVmvqcKR8xMLcDHVSBMTEgI1svZOkgiy51a5r164mT+xSi4qKIjIy0vBcq9W+9r1Mp9OxdetWYmJicHNzS7eOp6dnmvXMO3bsyI4dO9445jchk7tspFKpCuzaeWq1GpVKhVarzfHlx6QC5skF2PcWWJeHnkGmjkaSpByi1+vZtGkTkPduydaqVcvo+fTp0186n6q3tzdubm7ExcVRpEgR/vrrrzT7JwsNDcXe3t6ozN7entDQ0GyJO6tkcidJUs6yKK581SeaNg5JknJEfHw8W7duZcmSJQQGBlK0aFG6du1q6rCM+Pj4UK5cOcPzV7XaVa9eHS8vLyIiIti2bRsDBw7k2LFjL03w8iLZeaqQ0+v1zJ07FxcXF7RaLU5OTsyaNcvUYUkFiU0l+DABepv2k6wkSdkrODiYb775hgoVKvDJJ59w9uxZLCwsmDNnDlZWVqYOz0jRokUNI2BtbW1fmdxZWFjg4uJCo0aNmD17NvXr12fRokXp1nVwcODBgwdGZQ8ePMDBwSFb488s2XKXk5JilK8aa0i+XatLAJEIKjPQaNOpawWq5zm3PhH0CaDSgMby9XXVmR/QMXnyZFauXMmCBQto2bIlISEhXL9+PdPHkaSXUqlTfk8lScrXhBAcP36cJUuW8Ndff6HT6QAoV64cI0eOZNiwYflu+pPX0ev1L50pws3NjUOHDjF27FhD2YEDB17aRy+3yOQuJ20ponztHQaWpZXHvvPgyjdQZSg0XZlSd3sZ0D2D9/yhSCWl7MYvcPFLqPgRtPBIqbuzEsQ/gi5Xwe750Ow768BlWKbCi4qKYtGiRSxdupSBAwcCUKVKFVq2bJnpS5UkSZIKrpiYGDw8PFi6dCne3t6G8jZt2vD555/To0cPw7yv+dnkyZPp3LkzTk5OREVFsWHDBo4ePcr+/fsBGDBgAOXKlWP27NkAfPHFF7Rp04affvqJrl27smnTJs6fP89vv/1mysuQyV1h5uvrS3x8PG3btjV1KFJB5zMPovygxjgoln/6rUhSYXf79m2WLVvGmjVrCA8PB8Da2ppPPvkEd3d36tata9oAs1lYWBgDBgwgJCSEYsWKUa9ePfbv30/79u0BCAwMNJoOrHnz5mzYsIFvvvmGr7/+mqpVq7Jjxw6TznEHcp67DMnIPHfOzs5pR5Hm8duy3t7e1KtXjzt37uDs7PzKuq+8Tkl6nf1N4fFZaL0Tyr9n6mgkqVC4cOECU6ZMITo6Gmtra6ysrLC2tjZsr3qekJDA77//zp49ewxTfFWpUgV3d3cGDRpE8eLFTXx1GZMd89zlR7LlLieZ2aQt01gA6Uzmml5dtXn6CdvL6mZS1apVsbKy4tChQwwdOjTT+0tShlUZAuXeg6LVTB2JJBUKly5dol27dobWtjfRuXNnRo8eTadOneQk9vmETO4KMUtLSyZNmsTEiROxsLCgRYsWPHz4kGvXrqU7E7ckZZnLcFNHIEmFhre3N+3btyc8PJzmzZszbtw4YmNjefbsmeFr8pb6eerHCQkJtGrVCnd3d6pWrWrqS5IySSZ3hdzUqVMxMzNj2rRp3L9/H0dHR0aMGGHaoJJiUgaj9IlOv6VSkiRJSuP69eu0a9eOx48f07hxY/bs2UOxYsVMHZaUy0zavlqpUiXDqg6pN3d3d0Dp5+Xu7k7JkiUpUqQI77//fpr5ZAIDA+natSvW1taUKVOGCRMmkJSUZFTn6NGjNGzYEK1Wi4uLC+vWrcutS8zz1Go1U6ZM4e7duyQkJBAQEMDkyZNNHZZU0Oh1EP8Y4h6aOhJJKrBu3rzJu+++S1hYGA0aNGD//v0ysSukTJrcnTt3jpCQEMN24MABAD744AMAvvzyS3bt2sXWrVs5duwY9+/fp3fv3ob9dTodXbt2JSEhgVOnTvH777+zbt06pk2bZqjj7+9P165deeedd/Dy8mLs2LEMHTrUMKxZyoM01sr0Mb3DlMdS/ndjCWwvBRfGmDoSSXpjcXFxXLx4kYCAgJfOf5bb/P39effddwkJCaFOnTocOHAg3wx6kLKfSW/Lli5d2uj5nDlzqFKlCm3atCEiIoLVq1ezYcMG3n33XQDWrl1LzZo1OX36NM2aNeN///sfPj4+HDx4EHt7exo0aMD333/PpEmTmDFjBhYWFqxYsQJnZ2d++uknAGrWrMmJEydYsGABHTt2zPVrljJApUqZF1AqGCxKKF+Tnpk2Dkl6Q3q9nvfee8/QGAFQvHhxHB0dcXR0xMHBwehr6sfFihXLkfXHAwMDeffddwkODqZGjRocPHiQUqVKZft5pPwjz/S5S0hIYP369YwbNw6VSsWFCxdITEykXbt2hjo1atTAyckJT09PmjVrhqenJ3Xr1jVatLdjx46MHDmSa9eu4erqiqenp9Exkuuknk36RfHx8UafxqKiorLvQiWpMKr4IVTql6VR3ZKUlyxatIgDBw6g0WjQaDQkJCTw9OlTnj59io+Pzyv3tbS0pGLFiowePZrhw4djYZHOzAmZdP/+fd59913u3r2Li4sLhw4dSrOQvVT45JnkbseOHYSHhzNo0CAAQkNDsbCwwM7Ozqievb09oaGhhjov/hInP39dncjISGJjY9Nd/2727Nl8++232XFZUlboEpSVPABqTng+fYyUr8mfoVQAXL161dAn+ZdffmH48OE8ffrU0LUoNDTU6GvqxxEREcTFxeHn58fnn3/OggULmDlzJn379s3y9CIPHjygbdu23L59m0qVKnH48GHKli2bnZcs5VN5JrlbvXo1nTt3zhO/mJMnT2bcuHGG5/fu3aNWLTmrfq4RicoSbQA1xpLuvICSJEm5KD4+nv79+xMfH0+3bt0YPnw4KpWKEiVKUKJECWrXrv3K/WNjYwkNDWXfvn1899133Llzh48++oh58+Yxe/ZsOnTokKlbto8ePaJdu3Zcv36dChUqcPjwYSpUqPCmlykVEHliNsKAgAAOHjxoNJGug4MDCQkJaSZgfPDgAQ4ODoY6L46eTX7+ujq2trbpttoBaLVabG1tDVvRokXf6PqkTFKZKWvvVhmqPJbyv6RncGkinBmqjJyVpHxm6tSpXLlyhdKlS7Nq1apM952zsrLC2dmZkSNHcuvWLWbOnImtrS2XLl2iU6dOtGvXjnPnzmXoWE+ePKF9+/ZcvXoVR0dHDh8+/NpVhqTCJU8kd2vXrqVMmTJ07drVUNaoUSPMzc05dOiQoczPz4/AwEDc3NwAcHNzw9vbm7CwMEOdAwcOYGtra2hpc3NzMzpGcp3kY0h5kEYLTVcqW+ol2qT8S2Wm3Gq/vRoSI0wdjSRlyrFjx5g/fz4AK1eufOM+bTY2NkyZMoXbt28zbtw4LCwsOHz4ME2aNKFPnz7cuHHjpftGRETQsWNHvLy8KFOmDIcPH8bFxeWN4pEKIGFiOp1OODk5iUmTJqV5bcSIEcLJyUkcPnxYnD9/Xri5uQk3NzfD60lJSaJOnTqiQ4cOwsvLS+zbt0+ULl1aTJ482VDnzp07wtraWkyYMEH4+vqKX375RWg0GrFv374MxxgUFCQAERQUlOa12NhY4ePjI2JjYzN55flLYblOKQddmiSE90whEiJMHYkkZVh4eLhwcnISgBgyZEiOnOPu3bti4MCBQqVSCUBoNBrx2Wefifv37xvVi4yMFG5ubgIQJUuWFN7e3jkST0Hyqvfvgszkyd3+/fsFIPz8/NK8FhsbK0aNGiWKFy8urK2tRa9evURISIhRnbt374rOnTsLKysrUapUKTF+/HiRmJhoVOfIkSOiQYMGwsLCQlSuXFmsXbs2UzHK5K7wXKckSVJqH3/8sQBE5cqVRWRkZI6e68qVK6Jbt24CEICwtrYWX3/9tQgPDxfR0dGidevWAhB2dnbi4sWLORpLQVFYkzuVEEKYps0w/wgODqZChQoEBQVRvnx5o9fi4uLw9/fH2dkZS0tLE0WY83L1OpNiYHsZ5fH7YXL5MUmSTGLLli2G0awnTpzIte48x48fZ9KkSXh6egJQokQJKlWqxMWLF7G1teXgwYM0btw4V2LJ7171/l2Q5Yk+d5KUhu6ZskkFR/ISZInRpo5Ekl7r3r17hnW2v/7661ztp92qVStOnjzJX3/9Rc2aNXny5AkXL17ExsaGvXv3ysROei2Z3El5j8YK3vNXNk36I5qlfOhkH2UJMv/fTR2JJL2SXq9n0KBBPH36lLfeestoScvcolKp6NmzJ1euXGH16tV069aN/fv307x581yPRcp/ZHJXyOn1eubOnYuLiwtarRYnJydmzZpl2qBUaihSSdlU8le0wEhegixRrvgi5W1Llizh4MGDWFlZsX79eszNTbeyipmZGYMHD2bXrl20aNHCZHFI+YucRCwnJcUoXzXWynqpoKy+IBKVqSFST/NhqGuVktDoE0GfACoNaCxfXzcLSztNnjyZlStXsmDBAlq2bElISAjXr1/P9HEk6bUaLYLGy+QSZFKedu3aNSZNmgTA/PnzqV69uokjkqTMk80iOWlLEWWLf5RS5jtPKTs/2rju9jJKeUxgStmNX5Sy00OM6+6spJRH+KaU3VmX6fCioqJYtGgRc+fOZeDAgVSpUoWWLVsaTSZtEvpEuL5Q2fSJpo1Fyj5m1jKxk/K0hIQEPv74Y+Lj4+ncuTMjR440dUiSlCWy5a4Q8/X1JT4+nrZt25o6FGP6BLj4pfLYZZhMCCRJyhXTpk3Dy8uLkiVLsnr16kyvQiFJeYVM7nJSn+ejAjXWKWU1Jyjrpb64rNb7z1fZSD2AoJq7ktyoNMZ1e9xNW7fyoEyH97Ll10xOpYGKH6U8lgqGSD9lhQqLElD7K1NHI0lG/v33X+bOnQsoq1A4OjqaOCJJyjp5WzYnmdkoW+pPfxoLpezFZbUMdVP9SNTmz+taZqxuJlWtWhUrK6s0y7OZnMYSWngo24vXLuVfz+4p3RLu/tfUkUiSkYiICAYMGIAQgk8//ZRevXqZOiRJeiOy5a4Qs7S0ZNKkSUycOBELCwtatGjBw4cPuXbtGkOGDHn9ASQpM4pWgRrjwaaiqSORJCNjxowhICAAZ2dnFi1aZOpwJOmNyeSukJs6dSpmZmZMmzaN+/fv4+joaJi4U5KylU1FaDjf1FFIBcyzZ8+YNm0ap0+fpnz58lSqVIlKlSpRsWJFw1dra+uX7r9t2zb++OMP1Go1//3vfylatGguRi9JOUMmd4WcWq1mypQpTJkyxdShpEiKUUYEg9K/UC4/JklSOnx8fOjTpw/Xrl17Zb3SpUsbJXvJCaCdnR2fffYZAF999ZWcR04qMGRyJ+VNqaePkQoOvQ4Sw8HcVo6ClrJMCMG6detwd3cnNjYWe3t7vvvuO6KjowkICODu3buGLTIykocPH/Lw4UPOnz+f7vEaNmzI9OnTc/kqJCnnyOROyns0VtDlaspjqeDYUQ7iHkDny1C8nqmjkfKh6OhoRo0axX//qwzMadeuHevXr8fe3j7d+uHh4UYJX/Lj5K9arRYPDw8sLCxy8zIkKUfJ5E7Ke1RqsKtt6iiknGBRXEnuEsPTfTlJn8TWa1vx8PZge5/taM206daTCqfLly/Tp08fbty4gVqt5vvvv+err75CrX75xA92dnbY2dlRv379XIxUkkxLJneSJOWeDp5KH8qX3JIVQjDhwATuRd1jy7UtfFL/k1wOUMqLhBD8+uuvjB07lvj4eMqVK8fGjRtp1aqVqUOTpDxJznMn5T36RLi1Utnk8mMFi4XdK/vamWvMGdV4FACLzixCCJFLgUl5VUREBB9++CEjR44kPj6erl274uXlJRM7SXoFmdxJeY8+Ac4OVzZ9gqmjkXLZsIbD0Gq0XAi5wOng06YORzKh8+fP07BhQ7Zs2YKZmRnz58/n77//plSpUqYOTZLyNJncSXmPSgPleyibXH6sYAk9CJcmQtCfL61S2qY0H9VVlp9bfHZxbkUm5SFCCBYtWkTz5s25c+cOFStW5MSJE4wfP/6V/eskSVLIvxIp79FYQusdyiaXHytYHp5SliAL+d8rq41pOgaAbT7buBd5Lzcik/KIJ0+e0KtXL8aOHUtiYiK9e/fm0qVLNG3a1NShSVK+IZM7SZJyT+kWyhJkjh1eWa2BQwNaV2xNkj6J5eeX51Jwkql5enri6urKzp07sbCwYMmSJWzbto3ixYubOjRJyldkcidJUu5xaKssQVah92urjmmitN79euFX4pLicjoyyYR0Oh0zZ86kVatWBAYG4uLigqenJ6NHj0alUpk6PEnKd2RyJ+U9Sc+U5cd2VlIeS4VSjxo9qGBbgUfPHrHp6iZThyPlkMDAQN555x2mTp2KTqejX79+XLhwgYYNG5o6NEnKt2RyJ+VBAmIClA05FUaBo9dBwtPXVjNTm+He2B2AxWcWy2lRCqCtW7dSv359jh8/TpEiRfjjjz/w8PDA1tbW1KFJUr4mk7tCTq/XM3fuXFxcXNBqtTg5OTFr1izTBqW2hI5nlU0tB1QUKFG3YJOZ0iqbAcMaDcPKzIpLoZc4EXgiZ2OTck10dDRDhgyhT58+hIeH06RJE7y8vPjkk0/kbVhJygYyuctJSTHKlrrFQZeglOniX1JXn1KmT3xeNy5jdbNg8uTJzJkzh6lTp+Lj48OGDRteukZjrlFroGRjZVPLqVAKFHM75WtiJOiTXlu9hFUJPq73MSCnRSkokm+5rlmzBpVKxddff82JEyeoUqWKqUOTpAJDJnc5aUsRZYt/lFLmO08pOz/auO72Mkp5TGBK2Y1flLLTQ4zr7qyklEf4ppTdWZfp8KKioli0aBFz585l4MCBVKlShZYtWzJ06NBMH0uSMkRbAnqHwYcJoM7Y6oefN/kcgL98/yIwIvA1taW8Sq/XM2/ePNzc3Lh58ybly5fn8OHDzJo1C3Pzl69aIkm5afbs2TRu3JiiRYtSpkwZevbsiZ+f3yv3WbduHSqVymiztDTtXSeZ3BVivr6+xMfH07ZtW1OHYkyfBP4eypaB1h0pH1GpwbL0K5cge1Fd+7q8U+kddELH8nNyWpT86P79+3To0IGJEyca5q67fPkyb7/9tqlDkyQjx44dw93dndOnT3PgwAESExPp0KEDMTExr9zP1taWkJAQwxYQEJBLEacvYx+dpazpE6181VinlNWcADXGguqFb/37Yc/rWqWUVXMHl2FpV2nocTdt3cqDMh2elZXV6yuZgj4ePJVbcVTomeEWHqngGtN0DEfuHuG3i78xrc00rMzz6O+ulMbOnTsZMmQIjx8/xtramkWLFjFkyBDZt07Kk/bt22f0fN26dZQpU4YLFy7QunXrl+6nUqlwcHDI6fAyTLbc5SQzG2VL/U9MY6GUabQvqZvqR6I2f17XMmN1M6lq1apYWVlx6NChTO+bs9Tg0E7Z5K9owXNnHVyaAE+vZHiX7tW6U8muEk9in+Dh7ZFzsUnZ5tmzZ4waNYqePXvy+PFjXF1duXDhAkOHDpWJnZRvREREAFCiRIlX1ouOjqZixYpUqFCBHj16cO3atdwI76XkO2chZmlpyaRJk5g4cSJ//PEHt2/f5vTp06xevdq0gZlZwbsHlM1MttAUOHc9wHc+hGc8udOoNYxurPRTldOi5H1XrlyhcePGLF+u3EYfP348np6e1KhRw8SRSYVVVFQUkZGRhi0+Pv61++j1esaOHUuLFi2oU6fOS+tVr16dNWvWsHPnTtavX49er6d58+YEBwdn5yVkirzfVchNnToVMzMzpk2bxv3793F0dGTEiBGmDksqyCr0Brv6YFs9U7sNdh3MtKPT8A7z5ljAMd6u9HbOxCe9kevXr9O8eXNiYmJwcHDgjz/+oH379qYOSyrkatWqZfR8+vTpzJgx45X7uLu7c/XqVU6cePU0TG5ubri5uRmeN2/enJo1a/Lrr7/y/fffZznmN2Hylrt79+7x8ccfU7JkSaysrKhbty7nz583vC6EYNq0aTg6OmJlZUW7du24efOm0TGePHlC//79sbW1xc7OjiFDhhAdHW1U58qVK7Rq1QpLS0sqVKjA3Llzc+X68jq1Ws2UKVO4e/cuCQkJBAQEMHnyZFOHJRVkVUcqS5CVbJyp3YpbFWdAvQGA0non5T3x8fH069ePmJgYWrRowZUrV2RiJ+UJPj4+REREGLbXvc+NHj2a3bt3c+TIEcqXL5+pc5mbm+Pq6sqtW7feJOQ3YtLk7unTp7Ro0QJzc3P27t2Lj48PP/30k9Ei0XPnzmXx4sWsWLGCM2fOYGNjQ8eOHYmLS5n7rX///ly7do0DBw6we/du/v33X4YPH254PTIykg4dOlCxYkUuXLjAvHnzmDFjBr/99luuXq+UQUnP4J/ayiaXH5NS+bypMi3KTr+d3A2/a9pgpDS+/vprvLy8KFmyJFu2bKF06dKmDkmSAChatCi2traGTavVpltPCMHo0aP566+/OHz4MM7Ozpk+l06nw9vbG0dHxzcNO+uECU2aNEm0bNnypa/r9Xrh4OAg5s2bZygLDw8XWq1WbNy4UQghhI+PjwDEuXPnDHX27t0rVCqVuHfvnhBCiGXLlonixYuL+Ph4o3NXr149Q3EGBQUJQAQFBaV5LTY2Vvj4+IjY2NgMHSu/ytXrTIwWwgNlS4zO+fNJuU+XKERCVJZ2bf9He8EMxP/t/79sDkp6E3v37hUo6wWKv//+29ThSJIQ4tXv3+kZOXKkKFasmDh69KgICQkxbM+ePTPU+eSTT8RXX31leP7tt9+K/fv3i9u3b4sLFy6IDz/8UFhaWopr165l+/VklElb7v7++2/eeustPvjgA8qUKYOrqysrV640vO7v709oaCjt2rUzlBUrVoymTZvi6ekJgKenJ3Z2drz11luGOu3atUOtVnPmzBlDndatW2NhYWGo07FjR/z8/Hj6NO0al/Hx8UYdL6OiorL92qVXUFtC2yPKJpcfK3ju/AGbzOFk3yztPqbpGABWXVpFTMKr556ScseDBw8YOHAgoPRT6t69u4kjkqSsWb58OREREbz99ts4Ojoats2bNxvqBAYGEhISYnj+9OlThg0bRs2aNenSpQuRkZGcOnUqTT+/3GTSARV37txh+fLljBs3jq+//ppz584xZswYLCwsGDhwIKGhoQBplsOyt7c3vBYaGkqZMmWMXjczM6NEiRJGdV5sWk0+ZmhoqNFtYFBmqP7222+z70KlzFFrwP5tU0ch5RTzosrXhLQfrDKiS9UuVClehdtPb7P+yno+e+uzbAxOyiwhBJ9++ilhYWHUqVOHefPmmTokScoykYGR+EePHjV6vmDBAhYsWJBDEWWNSVvu9Ho9DRs25IcffsDV1ZXhw4czbNgwVqxYYcqwmDx5slHHSx8fH5PGI0kFimMnZQmydseytLtapWZ0k+fTopyV06KY2uLFi9m7dy9arZaNGzfm3cnRJakQMWly5+jomKbZsmbNmgQGKutHJs/2/ODBA6M6Dx48MLzm4OBAWFiY0etJSUk8efLEqE56x0h9jtS0Wq1Rx8uiRYtm9RKlrNAnQdAOZZPLjxU8ZlaZXoLsRZ82+JQiFkXweejDYf/D2RiclBmXL19m4sSJAPz000+vnAtMkqTcY9LkrkWLFmkW5L1x4wYVK1YEwNnZGQcHB6MVFCIjIzlz5oxhThk3NzfCw8O5cOGCoc7hw4fR6/U0bdrUUOfff/8lMTHRUOfAgQNUr149zS1ZKQ/Qx8PxXsqmf/1Ek1LhU8yyGIPqDwJg0ZlFpg2mkHr27Bn9+vUjISGB7t27M2rUKFOHJEnScyZN7r788ktOnz7NDz/8wK1bt9iwYQO//fYb7u7ugLJW29ixY5k5cyZ///033t7eDBgwgLJly9KzZ09Aaenr1KkTw4YN4+zZs5w8eZLRo0fz4YcfUrZsWQA++ugjLCwsGDJkCNeuXWPz5s0sWrSIcePGmerSpVdSQ6nmymb6qRil7Cb0cO0HZQmyN5jqJvnW7O4bu7n95HZ2RSdl0Pjx4/H19cXR0ZE1a9bIJcUkKS8x2Tjd53bt2iXq1KkjtFqtqFGjhvjtt9+MXtfr9WLq1KnC3t5eaLVa0bZtW+Hn52dU5/Hjx6Jfv36iSJEiwtbWVnz66aciKsp4moXLly+Lli1bCq1WK8qVKyfmzJmT4RjlVCiF5zqlXKDXC7FRq0x1E333jQ7VaX0nwQzEl/u+zKbgpIz4888/DdOeHDhwwNThSNJLZXYqlIJCJYTsjfw6wcHBVKhQgaCgoDQzVcfFxeHv74+zszOWlgV32o7Ccp1SLrkwFlRmUHMCWNm/tvrL7L25ly4bumCrteXeuHsUsSiSfTFK6QoODqZ+/fo8efKECRMmyNV+pDztVe/fBZm85yVJUu5rtFBZguwNEjuAji4dqVayGpHxkfxx+Y/siU16KZ1Ox4ABA3jy5AmNGjVi5syZpg5JkqR0yOROynuSYmFfY2VLijV1NFIeplap+byJsiTZ4jOL0Qu9iSMq2ObOncuRI0ewsbFhw4YNRhPDS5KUd8jkrpDT6/XMnTsXFxcXtFotTk5OzJo1y9RRwZPzyoZ8sy6w9Emge/PR0APrD6SoRVH8Hvtx4PaBbAhMSs+ZM2eYOnUqAEuWLKFatWomjkiSpJeRyV1OSopRttTdGnUJStmLb2qGuqmSGX3i87pxGaubBZMnT2bOnDlMnToVHx8fNmzYkGZFkFyn1kKb3cqmTn9xZymfOztSWYLs+pvP6l5UW5TBroMBZVJjKftFRUXx0UcfodPp6Nu3L4MGDTJ1SJIkvYJM7nLSliLKFv8opcx3nlJ2frRx3e1llPKYwJSyG78oZaeHGNfdWUkpj/BNKbuzLtPhRUVFsWjRIubOncvAgQOpUqUKLVu2ZOjQoZk+VrZSm0G5rsqmNukKeVJOMbNWviY8yZbDjW4yGhUq9tzcw83HN7PlmFIKd3d37ty5g5OTEytWrJDTnkhSHieTu0LM19eX+Ph42rZta+pQpMKm9hTo/RDq/5Ath3Mp4UKXql0AWHp2abYcU1J4eHjw3//+F7VazYYNG7CzszN1SJIkvYZsFslJfaKVrxrrlLKaE6DGWGUaiNTef76EmibVuozV3MFlGKg0xnV73E1bt/KgTIeXZ9eA1OvgwfMlpezfBbXm1fWl/EdbItsP+UXTL/jn5j+s9VrL9+9+j63WNtvPUdjcuXOHkSNHAjBt2jRatGhh4ogkScoI2XKXk8xslC31LQyNhVKm0b6kbqofidr8eV3LjNXNpKpVq2JlZWW0vFueoI+DIx2UTR/3+vqSBLSr3I6apWoSlRDFOq91pg4n30tKSqJ///5ERUXRokULpkyZYuqQJEnKIJncFWKWlpZMmjSJiRMn8scff3D79m1Onz7N6tWrTRyZGuzqK5v8FS2YngUrS5D5/pRth1SpVIZpUZacXSKnRXlD8+bN4/Tp0xQrVgwPDw/MzOSNHknKL+Q7ZyE3depUxo8fz7Rp06hZsyZ9+/YlLCzMtEGZWUEXL2Uzy6O3jqU3ExsKl6eA38JsPewn9T+hmLYYt57cYt+tfdl67MLk6tWrzJgxA4DFixdTsWJF0wYkSVKmyOSukFOr1UyZMoW7d++SkJBAQEAAkydPNnVYUkFnXQ4qDwbnQdl62CIWRRjiqowuX3xGTouSFUlJSXz66ackJCTQrVs3PvnkE1OHJElSJsnkTpKk3GflCM1WQ/3vs/3QydOi7L+9n+uPrmf78Qu6efPmcf78eezs7Pj111/ltCeSlA/J5E7Ke5Ji4eDbyiaXH5Myybm4M+9Vfw+AJWeWmDia/OXatWuG27GLFi2ibNmypg1IkqQskcmdlAfpIeyYssnlxwo2fZIy9U02G9N0DAC/X/6d8LjwbD9+QZSUlMSgQYPk7VhJKgBkciflPWottNyibHL5sYJrr6uyBNkjz2w/9DuV3qF26drEJMaw9tLabD9+QTR//nx5O1aSCgiZ3El5j9oMnD5QNrn8WMGltlC+JjzN9kOrVCpD693Sc0vR5UDrYEFy7do1pk+fDsjbsZJUEMjkTpIk02j1p7IEWdkuOXL4j+t9THHL4tx5eoc9N/fkyDkKgtSjY7t27Spvx0pSASCTOynv0evg4Ullky0uBZd1ObAslWPLy1mbWzOs4TAAFp1ZlCPnKAjmz5/PuXPnsLOz47fffpO3YyWpAJDJnZT36OPgQEtlk8uPSW9gVONRqFVqDvkf4lrYNVOHk+f4+PgYbscuXLhQ3o6VpAJCJndSHqSCIi7KhmxFKLAen1OWIAv6M8dOUdGuIj1r9ASUJcmkFKlHx3bt2pUBAwaYOiRJkrLJGyV30dHRREZGGm2S9MbMrOG9m8pmZm3qaKSc8vCksgRZ4LYcPc2YJsrAij8u/8HT2OwfvJFf/fTTT5w7d45ixYrJ0bGSVMBkOrnz9/ena9eu2NjYUKxYMYoXL07x4sWxs7OjePHiORGjJEkFUfEGUGUI2L+bo6dpXbE19e3rE5sUy+pLq3P0XPmFj48P06ZNA5TRseXKlTNxRJIkZadMzzPx8ccfI4RgzZo12Nvby097kiRljf3bypbDkqdFGfL3EJaeXcrYZmMxK8RT7Lw4OlbejpWkgifT/+EuX77MhQsXqF69ek7EI+UyvV7P/Pnz+e233wgKCsLe3p7PPvuMKVOmmC4oXRwcf1953Go7aCxNF4tUIPSr04+JByYSEBHALr9d9KrZy9QhmcxPP/3E2bNn5e1YSSrAMn1btnHjxgQFBeVELAVPUoyyCZFSpktQynTxL6mbarktfeLzunEZq5sFkydPZs6cOUydOhUfHx82bNiAvb19lo6VbYQO7u9RNiGnQinw9Ek5fgorcyuGNxoOwOKzi3P8fHlV6tuxCxculLdjJamAynTL3apVqxgxYgT37t2jTp06mJubG71er169bAsu39tSRPnaOwwsSyuPfefBlW+gylBoujKl7vYyoHsG7/lDkUpK2Y1f4OKXUPEjaOGRUndnJYh/BF2ugl1tpezOOnAZlqnwoqKiWLRoEUuXLmXgwIEAVKlShZYtW2b6UrOV2gKarU15LBVMcWHwtwvoYuDDRFDl7OD9kW+NZO7JuRy9e5QrD65Qz75w/a9KfTu2S5cuhr95SZIKnkwndw8fPuT27dt8+umnhjKVSoUQApVKhU4nW1ryC19fX+Lj42nbtq2pQzGmNofKg0wdhZTTzG0hKUp5nBgBFjk7IKtCsQq8X+t9tlzbwpIzS1j53srX71SA/Pzzz4bbsXKyYkkq2DKd3A0ePBhXV1c2btwoB1S8Tp9o5asm1XQeNSdAjbGgeuFb/37Y87pWKWXV3JXWONULM/j3uJu2bhaSISsrq9dXkqScorGEbjdAWwLM7XLllGOajGHLtS2s917P7HazKWVdKlfOa2q+vr7ydqwkFSKZTu4CAgL4+++/cXFxyYl4ChYzm7RlGgsgnVuN6dVVmytbRutmUtWqVbGysuLQoUMMHTo00/vnGL0OIryVx8Xq5tjyVFIeYFs1V0/XvEJzGjo25GLIRVZdXMVXLb/K1fObQvLt2Pj4eHk7VpIKiUx3cnn33Xe5fPlyTsQi5TJLS0smTZrExIkT+eOPP7h9+zanT59m9WoTzwWmj4O9rsomlx+TspFKpTJMavzLuV9IyoXBHKY2fvx4zpw5I2/HSlIhkumWu+7du/Pll1/i7e1N3bp10wyoeO+997ItOCnnTZ06FTMzM6ZNm8b9+/dxdHRkxIgRJo5KBVZlUx5LBVfw3xDuDeW6KpMa54K+dfoy4cAEgiOD2XF9B/+p9Z9cOa8pLFu2jMWLldHBq1evlrdjJamwEJmkUqleuqnV6kwda/r06QIw2qpXr254PTY2VowaNUqUKFFC2NjYiN69e4vQ0FCjYwQEBIguXboIKysrUbp0afF///d/IjEx0ajOkSNHhKurq7CwsBBVqlQRa9euzVScQUFBAhBBQUFpXouNjRU+Pj4iNjY2U8fMbwrLdUq57FgvITwQ4sayXD3tN4e+EcxAtFrTKlfPm5v27t0rNBqNAMQPP/xg6nAkySRe9f5dkGX6tqxer3/plpWRsrVr1yYkJMSwnThxwvDal19+ya5du9i6dSvHjh3j/v379O7d2/C6Tqeja9euJCQkcOrUKX7//XfWrVtn6DgMKculvfPOO3h5eTF27FiGDh3K/v37Mx2rJEnZzKGdsgRZ0Wq5etqRjUdipjbjeOBxLoVcytVz54arV6/Sp08fdDodAwcO5KuvCn7fQkmSUjFlZjl9+nRRv379dF8LDw8X5ubmYuvWrYYyX19fAQhPT08hhBB79uwRarXaqDVv+fLlwtbWVsTHxwshhJg4caKoXbu20bH79u0rOnbsmOE4Zctd4blOqfDot62fYAZi0I5Bpg4lW4WGhoqKFSsKQLRu3drwv1CSCqPMttz98MMP4q233hJFihQRpUuXFj169BDXr19/7X5btmwR1atXF1qtVtSpU0f8888/bxr6G8l0n7vk/hsZMWbMmNfWuXnzJmXLlsXS0hI3Nzdmz56Nk5MTFy5cIDExkXbt2hnq1qhRAycnJzw9PWnWrBmenp7UrVvXaEWFjh07MnLkSK5du4arqyuenp5Gx0iuM3bs2JfGFB8fT3x8ygoSUVFRGb5mKRvo4uDUJ8rj5v+Vy49JOWJM0zFsvLqRDd4b+LHdj5SxKWPqkN5YbGwsPXv2JCAgABcXF/78808sLORE4JKUUceOHcPd3Z3GjRuTlJTE119/TYcOHfDx8cHGJp2ZKoBTp07Rr18/Zs+eTbdu3diwYQM9e/bk4sWL1KlTJ5evQJHp5G7BggU8fPiQZ8+eYWdnB0B4eDjW1taULl3aUE+lUr02uWvatCnr1q2jevXqhISE8O2339KqVSuuXr1KaGgoFhYWhnMks7e3JzQ0FIDQ0NA0S2UlP39dncjISGJjY9Od62327Nl8++23r/9mSDlD6CBo2/PH60waipRLhD7HV6h4UdNyTWlctjHn7p9j5YWVTGltwvWUs4EQgsGDB3P69GmKFy/OP//8Q8mSJU0dliTlK/v27TN6vm7dOsqUKcOFCxdo3bp1uvssWrSITp06MWHCBAC+//57Dhw4wNKlS1mxYkWOx5yeTP83nTVrFg0aNMDX15cnT57w5MkTfH19adiwITNnzsTf3x9/f3/u3Lnz2mN17tyZDz74gHr16tGxY0f27NlDeHg4W7ZsydLFZJfJkycTERFh2Hx8fEwaT6GjtoC3liqbXH6sYLv3D2yxhYNv5/qpVSoVY5oqH0CXnV9Goi5r6zPnFTNmzGDTpk2YmZmxfft2qlXL3X6MklQQRUREAFCiRImX1nnZHUJPT88cje1VMp3cTZ06lSVLllC9enVDWfXq1VmwYAHffPPNGwVjZ2dHtWrVuHXrFg4ODiQkJBAeHm5U58GDBzg4OADg4ODAgwcP0rye/Nqr6tja2r50hQatVoutra1hK1q06Btdl5RJanNldY5q7lmanFnKRzSWyhJkCU9Mcvo+tfvgUMSB+1H32e673SQxZAcPDw++++47AH799VfeeecdE0ckSXlLVFQUkZGRhi1116uX0ev1jB07lhYtWrzy9urL7hAm30E0hUwndyEhISQlpZ34U6fTpUmiMis6Oprbt2/j6OhIo0aNMDc359ChQ4bX/fz8CAwMxM3NDQA3Nze8vb0JCwsz1Dlw4AC2trbUqlXLUCf1MZLrJB9DkiQTKtVMWYKs3b8mOb2FxoIRjZR5HRefyXh/4rzk5MmTDB48GICJEycaHkuSlKJWrVoUK1bMsM2ePfu1+7i7u3P16lU2bdqUCxFmr0wnd23btuWzzz7j4sWLhrILFy4wcuTINM2Sr/N///d/HDt2jLt373Lq1Cl69eqFRqOhX79+FCtWjCFDhjBu3DiOHDnChQsX+PTTT3Fzc6NZs2YAdOjQgVq1avHJJ59w+fJl9u/fzzfffIO7uztarRaAESNGcOfOHSZOnMj169dZtmwZW7Zs4csvv8zspUu5Regh8qayCb2po5FykpmNsgSZ9uW3PHLaZ299hrnaHM9gT87dO2eyOLLizp079OzZk4SEBHr16pWhNyxJKox8fHyMultNnjz5lfVHjx7N7t27OXLkCOXLl39l3ZfdIUy+g2gSmR1eGxYWJjp37ixUKpWwsLAQFhYWQq1Wi86dO4sHDx5k6lh9+/YVjo6OwsLCQpQrV0707dtX3Lp1y/B68iTGxYsXF9bW1qJXr14iJCTE6Bh3794VnTt3FlZWVqJUqVJi/Pjx6U5i3KBBA2FhYSEqV64sJzHOgly9zsRoZWJbD5THkpTDPv7zY8EMxCd/fmLqUDLs6dOnokaNGgIQDRs2FNHR8m9Fkl6U2alQ9Hq9cHd3F2XLlhU3btzI0D59+vQR3bp1Mypzc3MTn332WabjzS4qIYTISlJ48+ZNfH19AWWKkoLceTc4OJgKFSoQFBSUJoOPi4vD398fZ2dnLC0L7pQduXqdSTHw1/NlknrdU1p3pILr1m8Q9xCqjQKL4iYJ4dy9czRZ1QRztTmBXwbiUMSEn7gzIDExkS5dunDw4EHKlSvH2bNnKVu27Ot3lKRC5lXv3+kZNWoUGzZsYOfOnUZjC4oVK2bopz9gwADKlStnaCk/deoUbdq0Yc6cOXTt2pVNmzbxww8/mHQqlCzPPVC1alXee+89unbtyrNnz3j69Gl2xiUVZmY28EG4ssnEruC7/A1c+QaeBZsshMblGuNW3o1EfSK/nv/VZHFkhBCCzz//nIMHD2JjY8OuXbtkYidJ2WT58uVERETw9ttv4+joaNg2b95sqBMYGEhISIjhefPmzdmwYQO//fYb9evXZ9u2bezYscNkiR1kYZ67sWPHUrduXYYMGYJOp6NNmzacOnUKa2trdu/ezdtvv50DYUqSVGA59QF9nMkT+TFNx+AZ7Mny88uZ3GoyFpq8OQ3PwoUL+fXXX1GpVGzcuBFXV1dThyRJBUZGbmYePXo0TdkHH3zABx98kAMRZU2mW+62bdtG/fr1Adi1axd37tzh+vXrfPnll0yZkr8nAS2M9Ho9c+fOxcXFBa1Wi5OTE7NmzTJ1WFJh0ngpNF0FRSqbNIz3a75P2aJleRDzgK3Xtpo0lpfZtWsX48ePB2D+/Pl0797dxBFJkpQXZTq5e/TokWEEyJ49e+jTpw/VqlVj8ODBeHt7Z3uA+VpSjLKl/iSgS1DKdPEvqZtqdKg+8XnduIzVzYLJkyczZ84cpk6dio+PDxs2bEgzX0+u08WD5yBle/H7JEk5xFxjzsi3RgKw+Gzemxblxo0b9OvXDyEEw4cPlyP+JUl6qUwnd/b29vj4+KDT6di3bx/t27cH4NmzZ2g0mmwPMF/bUkTZ4h+llPnOU8rOjzauu72MUh4TmFJ24xel7PQQ47o7KynlEb4pZXfWZTq8qKgoFi1axNy5cxk4cCBVqlShZcuWDB06NNPHylYiCfx/VzaRdk5FqYDK2tiubDW80XAsNBacvXeWM8FnTB2OkXnz5hETE0ObNm1YunQpKpXK1CFJkpRHZTq5+/TTT+nTpw916tRBpVIZ5rY7c+YMNWrUyPYApZzj6+tLfHw8bdu2NXUoxlTm0GCusqnkChUF3pUZyhJkl03fraOMTRk+qvsRAIvOLDJxNCmePHmCh4cHoKxbaW4u/y4kSXq5TA+omDFjBnXq1CEoKIgPPvjAMFmwRqPhq6++yvYA87U+0cpXjXVKWc0JUGMsqF741r//fJUNTaol0aq5g8swUL3QItrjbtq6lQdlOryXLb9mchoLqDXB1FFIuUWlMukSZC/6vMnnrPNax1afrczvMJ+yRU0/EnXt2rXExsZSr149WrZsaepwJEnK4zKd3AH85z//SVM2cODANw6mwElv9J/GAkhnFF56ddXm6a+t+rK6mVS1alWsrKw4dOiQ6W/FSoWXywio+BFYljF1JAA0dGxIS6eWnAg8wYrzK/june9MGo9Op2PZsmWAMmu+vB0rSdLrZHmeOyn/s7S0ZNKkSUycOJE//viD27dvc/r0aVavXm3awIQent1TNrn8WMFnZa8sQWZRzNSRGIxpMgaAFedXEJ9k2kE9+/bt486dO9jZ2dG/f3+TxiJJUv6QpZY7qeCYOnUqZmZmTJs2jfv37+Po6MiIESNMG5QuFnY8n0m8T7TJ5z+TCp+eNXpS3rY8wZHBbL62mQH1B5gslqVLlwIwZMgQrK2tX1NbkiRJttwVemq1milTpnD37l0SEhIICAh47YLKuUJllrZfolQwxT+Gm8vBb6mpIzEw15jj3tgdUAZWZHGVxjd28+ZN9u3bh0qlYuTIkSaJQZKk/CdTyV1SUhJ//PEHDx48yKl4JElpqeuXqGyy1a7gi38M50YpS5DlIUMbDsXSzJKLIRc5FXTKJDEk97Xr0qULVapUMUkMkiTlP5lK7szMzBgxYgRxcXGvryxJkpQRlqWhfC9w+iBPzHWXrJR1KfrXVfq4mWJS4+joaNauXQsoAykkSZIyKtO3ZZs0aYKXl1cOhCJJUqFkURxa/wlNVyrTouQhnzf5HIDtPtsJjgzO1XOvX7+eiIgIXFxc6NChQ66eW5Kk/C3TnZpGjRrFuHHjCAoKolGjRtjYGN82q1evXrYFJxVSuni4OE553PBn0GhNG49UaNV3qE+bim04FnCM5eeWM6tt7qy7LIQwDKRwd3dHrZbdoyVJyrhMJ3cffvghAGPGjDGUqVQqhBCoVCp0Ol32RScVTiIJbip9jXCdC8jkrlCJCAP3LtDwLRi3wtTR8EXTLzgWcIxfL/zKN62/wco85yf/PnbsGNeuXcPa2ppBgwbl+PkkSSpYMp3c+fv750QckpRCZQ51pqc8lgq+o90g7F9ouRmWrwGPC7DzIgz8BkqWN2lo3at3p2KxigREBLDx6kYGuw7O8XMmt9p98skn2NnZ5fj5JEkqWDKd3FWsWDEn4pCkFBoLqDfD1FFIuUkXpyxBFv8Epv4Xjp6AYSNMntgBmKnNcG/szsSDE1l8ZjGfNvg0R1eJCAoKYseOHYAcSCFJUtZkqSPHf//7X1q0aEHZsmUJCAgAYOHChezcuTNbg5MkqZBosgK63YAKvcDCEo6HwIDppo7KYEjDIViZWXH5wWWOBx7P0XP9+uuv6HQ63n77berUqZOj55IkqWDKdHK3fPlyxo0bR5cuXQgPDzf0sbOzs2PhwoXZHZ9UGAkBCeHKloemxpByUFEXZQkys3RWYIgIUzYTKmFVgk/qfQLA4jM5Ny1KfHw8v/32GyBb7SRJyrpMJ3dLlixh5cqVTJkyBY1GYyh/66238Pb2ztbgpEJK9wy2FVc23TNTRyOZ0p8LoVo5GNnJ1JEwpqkyiOyv638REB6QI+fYunUrDx8+pHz58vTo0SNHziFJUsGX6eTO398fV1fXNOVarZaYmJhsCUqSpEIm4rqyBFnw38blcTEQlgSHvSHykWlie652mdq0dW6LXuhZdm5ZjpwjeSDFiBEjMDOTy+9JkpQ1mU7unJ2d053EeN++fdSsWTM7YpIKO401fJigbBq5UHqh8PCEsgTZrZXG5R9NgZ9Hgm8Q2JYyTWypJLferby4kmeJ2duqfO7cOc6cOYOFhQXDhg3L1mNLklS4ZDq5GzduHO7u7mzevBkhBGfPnmXWrFlMnjyZiRMn5kSMUg7S6/XMnTsXFxcXtFotTk5OzJqVOxO1vpRKBWpzZctjKxZIOcS2OlToDaVbpH3ty2VQ3CH3Y0pH16pdcbZz5mncUzyueGTrsZNb7fr06UOZMmWy9diSJOVds2fPZs2aNWnK16xZw48//pilY2Y6uRs6dCg//vgj33zzDc+ePeOjjz5i+fLlLFq0yDDBsfRcUoyypR4UoEtQynTxL6mrTynTJz6vG5exulkwefJk5syZw9SpU/Hx8WHDhg3Y29tn6ViSlGVlWkGr7VD7q1fX85gJF/fnTkzp0Kg1jG6iDHRYfHYxIpsG/Dx8+JBNmzYBciCFJBU2v/76KzVq1EhTXrt2bVasyNpE7lmaCqV///7cvHmT6OhoQkNDCQ4OZsiQIVkKoEDbUkTZ4lP1FfKdp5Sdf+Ef+PYySnlMYErZjV+UstMvfG93VlLKI3xTyu6sy3R4UVFRLFq0iLlz5zJw4ECqVKlCy5YtGTp0aKaPla10CXBpgrLpEkwbi5R3TOwOH0+FT/uCXv/6+jlksOtgbMxtuBp2laN3j2bLMVetWkVCQgKNGzemadOm2XJMSZLyh9DQUBwdHdOUly5dmpCQkCwdM8sLFoaFhXHhwgX8/Px4+PBhVg8jmZCvry/x8fG0bdvW1KEYE4ngO1/ZRNZaJKUCaMAEsALqVIF4042itrO0Y2D9gQAsOrPojY+XlJTE8uXLAdlqJ0mFUYUKFTh58mSa8pMnT1K2bNksHTPTw7GioqIYNWoUGzduRP/807NGo6Fv37788ssvFCtWLEuBFEh9opWvqQcF1JwANcaC6oVv/fvP5/HSpFq3spo7uAwDlca4bo+7aetWHpTp8Kyscn6NzCxRmUPN/0t5LBV8ujjYVR0SnkKve2BeNG2dOq3h1g0oWzX343vB6CajWXZ+GX/7/Y3/U3+ciztn+Vi7du0iKCiIUqVK0adPn2yMUpKk/GDYsGGMHTuWxMRE3n33XQAOHTrExIkTGT9+fJaOmaU+d2fOnOGff/4hPDyc8PBwdu/ezfnz5/nss8+yFESBZWajbKkHBWgslDKN9iV1U/1I1ObP61pmrG4mVa1aFSsrKw4dOpTpfXOUxgJc5ymbxsLU0Ui5Qa2FuFBlCbKEpy+vlwcSO4CapWvSoUoHBIJfzv3yRsdKHkgxbNgwLC0tX1NbkqSCZsKECQwZMoRRo0ZRuXJlKleuzOeff86YMWOYPHlylo6pEpnsEWxjY8P+/ftp2bKlUfnx48fp1KlTgZzrLjg4mAoVKhAUFET58sZrXcbFxeHv74+zs3O+/Mf87bffsmjRIhYuXEiLFi14+PAh165dS9OHMr9fp5QPPLkI5rZgU/H1H1YCr8HQrvBhfxhsmtHd/9z4h24bu1FMW4zgccEUsSiS6WP4+PhQu3Zt1Go1/v7+ODk55UCkklR4ver9O6+Jjo7G19cXKysrqlatilarff1OL5HplruSJUume+u1WLFiFC9ePMuBzJkzB5VKxdixYw1lcXFxuLu7U7JkSYoUKcL777/PgwcPjPYLDAyka9euWFtbU6ZMGSZMmEBSUpJRnaNHj9KwYUO0Wi0uLi6sW7cuy3EWNFOnTmX8+PFMmzaNmjVr0rdvX8LCTLvUE0Ioo3/1iXL5scKkRENlGbKMtELPGgkHAuCrH03W/65z1c64lHAhIj6C9VfWZ+kYv/yitPr16NFDJnaSVMgVKVKExo0bU6dOnTdK7CALyd0333zDuHHjCA0NNZSFhoYyYcIEpk6dmqUgzp07x6+//kq9evWMyr/88kt27drF1q1bOXbsGPfv36d3796G13U6HV27diUhIYFTp07x+++/s27dOqZNm2ao4+/vT9euXXnnnXfw8vJi7NixDB06lP37TTedQl6iVquZMmUKd+/eJSEhgYCAgCw3A2cb3TPYZKFscvkxKT3z/oRWjuCxGrSmmeharVLzeZPPAWW92cxOixIREcHvv/8OyIEUkiRlM5FJDRo0EEWKFBHm5uaiSpUqokqVKsLc3FwUKVJEuLq6Gm0ZERUVJapWrSoOHDgg2rRpI7744gshhBDh4eHC3NxcbN261VDX19dXAMLT01MIIcSePXuEWq0WoaGhhjrLly8Xtra2Ij4+XgghxMSJE0Xt2rWNztm3b1/RsWPHDF9zUFCQAERQUFCa12JjY4WPj4+IjY3N8PHyo1y9zsRoITxQtsTonD+flDc8+FcIv1+EeHzR1JFkWERchCjyQxHBDMT/bv0vU/suWrRIAKJWrVpCr9fnUISSVLi96v27IMv0aNmePXtma3Lp7u5O165dadeuHTNnzjSUX7hwgcTERNq1a2coq1GjBk5OTnh6etKsWTM8PT2pW7eu0aS7HTt2ZOTIkVy7dg1XV1c8PT2NjpFcJ/Xt3xfFx8cTH58yyXBUVFQ2XKmUYRpr+M/TlMdS4XB7Nfj/Dg3mQIm061e/UuA1KFUBrG1zJraXsNXa8mmDT1lydgmLzy6mfZX2GdpPr9cbbsmOHj0alVyJRZKkbJTp5G769OnZdvJNmzZx8eJFzp07l+a10NBQLCwssLOzMyq3t7c33BIODQ1Ns5pC8vPX1YmMjCQ2Njbd6UBmz57Nt99+m+Xrkt6QSgUWdqaOQsptJZsoo2WLVMncfr98CV8tggFvwy+HcyS0VxndZDRLzi7hnxv/cOvJLVxKuLx2n4MHD3Ljxg1sbW355JNPciFKSZIKkyxPYvymgoKC+OKLL/Dw8Mhzoy8nT55MRESEYfPx8TF1SJJU8FUbpSxB5vSfzO2n10G0gMNnITH3VzSpVrIaXap2UaZFOZuxaVGSpz8ZNGgQRYpkfpStJEnSq5gsubtw4QJhYWE0bNgQMzMzzMzMOHbsGIsXL8bMzAx7e3sSEhIIDw832u/Bgwc4OCiLiDs4OKQZPZv8/HV1bG1tXzqJr1arxdbW1rAVLZrOhKpSztElwJUZyiaXH5Nex30hLB0LXmFgbpp5Ecc0GQPAGq81RMW/uhvHrVu32L17NwCjRo3K8dgkSSp8TJbctW3bFm9vb7y8vAzbW2+9Rf/+/Q2Pzc3NjSbY9fPzIzAwEDc3NwDc3Nzw9vY2mrrjwIED2NraUqtWLUOdFyfpPXDggOEYUh4kEuHqt8omlx+TXketBvcFJhs1C9C+Snuql6xOZHwkv1/+/aX1kucIFULQoUMHqlevnotR5hNy+iNJemMmS+6KFi1KnTp1jDYbGxtKlixJnTp1KFasGEOGDGHcuHEcOXKECxcu8Omnn+Lm5kazZs0A6NChA7Vq1eKTTz7h8uXL7N+/n2+++QZ3d3fDHDEjRozgzp07TJw4kevXr7Ns2TK2bNnCl19+aapLl15HZQZVRynbi8u0SQXXw1OwoyL8r0XWj6HXw7xhcOt89sWVAamnRVlydgl6oTd6PS4uji+//JJOnTrx4MEDatWqZRhQIT0n9HCgFWyxhhMfGr/26DRE+ilzX0oZF3IArr/5+sdS/pPl5C4hIQE/P780EwZnpwULFtCtWzfef/99WrdujYODA3/++afhdY1Gw+7du9FoNLi5ufHxxx8zYMAAvvvuO0MdZ2dn/vnnHw4cOED9+vX56aefWLVqFR07dsyxuKU3pNFC41+U7cVl2qSCS20OzwLhWVDWj/FJY5i4Cj59L/viyqAB9Qdgq7XlxuMb/O/2/wzlPj4+NG3alIULFwLKrdjz58/j4vL6gReFikoNDX9WlqJTvfDWdOID2F0DnlxIKXtyCXx+hNDcH0STJwVsgaNd4e6mlLLirhB6wHQxSaaT2blTYmJixODBg4VGoxEajUbcvn1bCCHE6NGjxezZs7N7qpY8Qc5zV3iuUzKhxGghHp4RIvJW1o9xYpsQVggxrrMQSYnZF1sGfbnvS8EMROf1nYVerxe//PKLsLS0FIAoVaqU2LVrV67HlK/o9UJE3Tb+HdAlCbGngRCbrIWIDUsp95mvzIV54kPjYxzrKcSJj4SIDkx1jATl2AVFTJAQd/4QQq9LKfOa8vz78ZFx3WchuRtbHlNY57nLdMvd5MmTuXz5MkePHjUa5dquXTs2b96cfVmnJEn5lhCCZcuW8cUXXxAUlMGWODMbKNUEimZyKpTUWrwPAQHw0x7Q5P4tfffG7qhQsffWXt794F3c3d2Ji4ujY8eOeHt7061bt1yPKV9IilW+qlRQpLLx74BaA50vQZ9o0JZKKbetAZX6g/07KWW6eAjeCQEbQJ1qcM2NpbC1KFz8P+PzPjgGUbeVEdd5Werb/Pok2F0LPAfAU6+Ucqf/gOt8qP218b5WDrkSYkHy77//0r17d8qWLYtKpWLHjh2vrH/06FFUKlWaLfVKXrkt08ndjh07WLp0KS1btjSaeLN27drcvn07W4OTCqmkGNhormxJMaaORsokvV7PF198gbu7O4sXL6Z69epMnz6dmJhc+lmWNt0arVVKVKFJ8SYAHH12FAsLCxYsWMCePXsMI/ilFzw+Bzud4OaKV9dTqZQtWbmu0Hw9uAw3rtdyK7jOA8syKWVRt5X/JanXLdYlwOF3YZcLxKdaTzv0MPj+BI/OZv2assvjc/C/5nAkVTcitRk4vPt8XsjolPLiDaDmeLCrnethFjQxMTHUr18/0/1i/fz8CAkJMWxlypR5/U45JNPJ3cOHD9MNOCYmRs6yLmUfkaRsUr6SkJDAJ598wpIlS1CpVNSvX5/Y2Fi+++47qlWrxn//+1/0ev3LDxD0F9xYBnEP3zwYr0PQqCTsXPLmx8qA5EETZxadAUDdUM2hk4cYO3YsarXJxq7lfTd+gfhH8PDkmx9LowWn96Hm/xkngg1/hm5+UM09pSzhMRStDtqSYJkq8Q7eAZf+D4JT+nejT4QDrcFzoPEHTl1C9o3ujbyhDH54dCalzNwOHnlC2DFISrXOdsvt0PEMlGmdPeeWjHTu3JmZM2fSq1evTO1XpkwZHBwcDJsp/+4zfea33nqLf/75x/A8OaFbtWqVnF4kH9Lr9cydOxcXFxe0Wi1OTk7MmjXLtEFprKBnsLJp0p+LUMp7YmJi6NGjBxs2bMDMzAwPDw8uXbrE1q1bqVSpEvfv32fAgAE0a9aMU6dOpX+QSxPgvDtE3XjzgL4fAxefwPhJyijaHGQ0aOIOFE8qjt5cz4WkC6/dt9BrugoaLYEGP+bcOTQWYFsNrMunlFk5Qjcf6P3QOBEs2Ric+kLJZillMYHw8DgEbjH+n+Q1EbbZge/PKWV6ndL6FxPw6sQv1nj+Va7/DBfHwt0NKWVFXcDtv9DtBpilmupHrcnIVUu5rEGDBjg6OtK+fXtOnsyGDytvINOdUn744Qc6d+6Mj48PSUlJLFq0CB8fH06dOsWxY8dyIsb8K/kTnsY65Z+HLkGZu01lZjwS1FDXKmWkmD4R9Amg0oDG8vV1U99yyKDJkyezcuVKFixYQMuWLQkJCeH69euZPk62UqnBupxpY5Ay5cmTJ3Tr1g1PT0+srKz4888/6dSpEwD/+c9/6NatG4sWLWLWrFmcO3eOFi1a0LdvX3788UcqVqyYciCH9hBfH8yyYdWGZbsh8h2Yv0aZCy8HCCFYvnw548ePJy4ujlKlSrF27VruOdxjxD8jWHJ2CZ83/Rz1i6M/pRRqM6g+2nTnf/GOk/MnypaathS02AQJT41H8kbdgsRI48TrWSAcbquM+u37DHh+/KC/lITP/h2lv1z4FehxF2ye//6X7QrR/lCikXFszh9n15UWalFRUURGRhqea7Vaw5Rpb8rR0ZEVK1bw1ltvER8fz6pVq3j77bc5c+YMDRs2zJZzZFpWRmHcunVLDB06VDRu3FjUrFlT9O/fX1y5ciV7h3rkIVkeLeuBsqUe4eU9Uyk7PdS47iZrpTzKP6XMd0H6o5+2lVLKn15NKbv5W6avKzIyUmi1WrFy5crX1pWjZaWXCQ4OFrVr1xaAKF68uDh16tRL64aEhIihQ4cKlUolAGFpaSmmTJkioqKicjHi7PHo0SPRrVs3AQhAdOzYUYSEKCMTo+Ojhd0cO8EMxC4/OUI2XU+88v8I1sRnQoRfM/4f/+SSEH9XE+Kf+kJE3xXi8nQhLk8V4uh7yv/tG8uE2O8mhIdK+b99oLUQZ0YYHzcpPhcvomBLfv9+cZs+fXqG9gfEX3/9lenztm7dWnz88ceZ3i+7ZOnjZJUqVVi5ciVnz57Fx8eH9evXU7du3WxJNqXc4+vrS3x8PG3btjV1KMZ0CeAzT9nk8mN52s2bN2nZsiXXrl2jbNmyHD9+/JXdMxwcHFi5ciUXL17k7bffJi4ujlmzZlG1alXWrVv36v54b+rqv9m29qy/vz/Nmzdn9+7d6Q6asLGwYajrUAAWn1mcLecsUKJuwf4mcLCV0vKVX5lZQbFaYFlauQUb4QPa0tDdTxnhGxuirLRzYymUeRsq/EeZe67pKnj/ERSpAmH/woMX5uo72Re2lYCAVDNQJEYpo3uf3cvVSywofHx8jNaMnzx5co6er0mTJty6dStHz/FKmc0G//nnH7Fv37405fv27RN79uzJlowzr8lyy11itLKl/nSaFK+UJcW9pG6qeYt0Cc/rxmasbiZduXJFAOLOnTuvrZurLXeJ0SmtnonROX8+KUsuXrwoypQpIwBRtWpV4e/vn6n99Xq9+Ouvv0SVKlUMn6YbNmwojh07lv3Bft1bCHOE+OY/b3yoixcvCgcHBwGIChUqCC8vr3Tr+T/1F+pv1YIZiGth1974vAVKwDblbsWhDvm/9S7Z6aHK/6wr36aU6RKFOPmJ0kL34v98IYR4FirEnfVC+HsYl++uoxzrXqr31NAjStlOF+O6t9YIcX2J8V0fyeBN57kjiy137dq1E7169crSObNDplvuvvrqK3S6tHMCCSH46quv3ijRLHDMbJQtdZ8OjYVS9uLKC4a6qX4kavPndS0zVjeTqlatipWVVZq1d01OZQbOA5VNLj+WJx09epQ2bdoQFhaGq6srJ06coFKlSpk6hkqlomfPnly7do358+dja2uLW8mLVPJqw47pVdm3b1/2rYBjZg6JwLGTbzS44uDBg7Rp04bQ0FDq1q2Lp6cn9evXT7duJbtKvFddWSlj6dmlWT5ngeT0vtK61WRF2j5veZ0+CS58CXvqQ0J4SnnJxsr/6tQtkWozaP4HuAxLf7UdK3tw7g+VPjIu73gaulyB0i1TynSxSkufbQ3jun4L4cLnSqthssfn4FBbuDLNuK68E5Ih0dHRhjXvQWmp9/LyIjAwEFD6qg8YMMBQf+HChezcuZNbt25x9epVxo4dy+HDh3F3d0/v8Lkjs9mgpaVlup/Q/f39hbW1dTbkm3lPQV6hYsaMGaJ48eLi999/F7du3RKenp5i1apVaerl9+uUss9ff/0ltFqtAESbNm1EREREthz3wYMHYuv3bkJ4INaPUlrySpcuLUaPHi08PT2F/k1aeJIShVj9tRA63evrvoSHh4cwNzcXgHj77bfF06dPX7vPEf8jghkI61nW4mns6+tLeYwuUYiwk0IEv9Bv8u9qSita0I6UssSYtHdZcsKLfweXpymrckSlugNza40S36H2xnX3uAqxrbQQD/5NKXsWKkTYCSFiH+RczCaUlZa7I0eOpNtPb+DAgUIIIQYOHCjatGljqP/jjz+KKlWqCEtLS1GiRAnx9ttvi8OHD2fzlWROppM7e3t7cejQoTTlBw4cEKVLl86WoPKagpzc6XQ6MXPmTFGxYkVhbm4unJycxA8//JCmXn6/Til7rFmzRqjVagGInj17Zv/vQ0ywuH12o5gybpAoXbq00T/WKlWqiKlTp4rr169n7zkzYP78+YY4+vTpI+Li0rnFlg69Xi/qLqsrmIGYf3J+DkeZDwTtFCLCz9RRvJxeb9zFJXj381uhlY3r+W8UImCrEPFPczW8DIvyF+L278ZJqV4vxBZb5XrCU3UTuL1OKTvY1vgYvj8LcWO58WCRfKiwLj+W6eRu+PDhom7duuLWrZS1/27evCnq1asnhgwZkq3B5RUFObnLqMJyndLLzZ0715DgDB48WCQm5uzarQkJCWLPnj2if//+wtra2ijRa9Sokfj555/F/fv3lcrRAUIc72O8nqj3TCF8flJaJlKLixFi4ntC3H/9GrY6nU6MGzfOcN4vvvhC6DLZ+rfywkrBDESlhZVEki4pU/sWKLEPhNhSTIiN5kI8PG3qaNK6NleIP8sJ4bc0pSwhUojtDkIc/0AZGZvfJUQoo3lTj8a9tVqIHRWFODsypUyvV35WL87KELRD6Sfpu9D4uOn1J8wjZHKXQeHh4aJZs2bCzMxMVKpUSVSqVEmYmZmJd955J0O3KfIjmdyZYEDFlmLKJgdUmJxerxcTJkwwJDgTJ058s1ukWRAdHS08PDxEly5dhEajMcSiVqtFu3btxN0/GipvRIc7KTskxaW0UoSdSHUxOiHerSAECNGt6ivPGRcXJ/r162c419y5c7N03TEJMaLEjyUEMxA7fHe8foeCKjpQiCNdhNjTUAhTJrm6JCGC/xHiwnjjJOfqLOX35d/exvULyoCP10l9nboEIc5/IcSRbsrt5mSXp6c/ldfWEkoSHJnqA1OUv5LExz3OwaBfr7Amd5nurV6sWDFOnTrFgQMHuHz5MlZWVtSrV4/WreUyKFI2SowwdQQSEBERwejRo1m/fj0Ac+fOZcKECTl3wsRouLcLdM+gyhBDsY2NDR999BEfffQRDx8+ZMuWLXh4eODp6cnBgwfp7AvLPlWx46Ce1k//pHP7NljVmwVhR6BUqqlZrs2GDio4r4J33n1pGJGRkfTq1YvDhw9jZmbG2rVr+fjjrE0ma21uzbCGw/jx5I8sPruYHjV6ZOk4+Z5NBXj7H0iIyN0VFvRJEPcgZWJ0lQpOD4L4h1C+B5RppZRX/AhKNDYexJBcvzBIfZ1qc2i0MG2din3BxkkZ2JEsIRwSniiPLe1Tyv3/AO/pUHkwNFudUn5lhvKzqNgPzLNhsnIpfabOLvMD2XKXy9ep1wkRcUPZ9FnvAC+9me3btwtHR0dDC9maNWty/qTP7istAxvUGfrZ3759W3z//feiRo0aRrdtixYtKj7++GOxe/duER+fqnVmz/MWPq9Ut5USnwkRedPw9P79+6J+/foCEEWKFBH79+9/48sKCA8Qmm81ghkI7wfeb3w8KYNCDil3APY2Ni6/ME6I08OEeFpwJ9/PVfFPhHh8wbjs6iwh/iovxNXZqeqFp0xzlRCZUn5jhRDHcmbakMLacqcS4vWrHi9evJjhw4djaWnJ4sWvnpBzzJgxb55x5jHBwcFUqFCBoKAgypcvb/RaXFwc/v7+ODs7Y2lp+ZIj5H+F5ToluHfvHqNHj2bHjh0AVKtWjd9++402bdrk/Ml18XC0M1gUh+YeaacBelFCBFgUQwiBl5cXGzduZNOmTQQFBRmqFC9enPfff58PP/yQNk1rYBayG5w+AG0JpcLdLXCqL5TviZ/9HDp16sTdu3cpU6YMe/fuzbblgz7Y+gHbfLYxrOEwfuv+W7YcM18I3AqRflBjvDLpb065v09Z+7XC+1Cuq1L27B7sKK8sH9YjMGfPL6VPiJRWwbhHyqTO8Y+gxcaUOqc/hUee0C37l7581ft3gZaRDLBSpUri0aNHhscv25ydnXMuDTUh2XJXeK6zMNPpdOKXX34RRYsWFYAwMzMT33zzTd79mT84rvSru77YqFin04mTJ0+Kzz//XNjb2xu16JUpU0a4u7uL48ePKwMj9q0SorK5ED+oxL3dH4uSJUsKQLi4VBFhJ6YJEe6bbeH+e/dfwQyE1Uwr8SjmUbYdN09LjFYGKXigLKeYnce9v9+4n9iF8c/7g70wsO+Jl2n7+Emv9/i88YTN2Ui23EkvJVvucvk69Ylw63nLhsvwLE3QLGXOtWvXGDZsGJ6engA0a9aMlStXUqdOHdMFpde9um/W6cFwZ63SN6/pqnSr6HQ6/v33XzZt2sS2bdt48uSJ4bXy5cvjXTocu0vRJNQvSrXQRAIexNG4cWP2bppLydPvKIu/v/8oW/oGCSFo+FtDvEK9+LHdj0xsMfGNj5nnCQEBm+DWCnhn/+tbYjNCnwjbSymTBXf1gWI1lfKHpyD4LyjXA8q0fPUxpEKjsLbcZWqFisTERKpUqYKvr29OxSNJoE+A86OVTS9nVM9JcXFxTJ06FVdXVzw9PSlatChLly7lxIkTpk3s4h/DP7Xg1ioQL1lRoukqaLISGsx96WE0Gg3vvPMOv/76K6GhoezZs4cBAwZQtGhRgoODeed2NL7Vod6tKAIexNG5c2cOHz5MSTtbcOwM5bobJ3YXxikdwrOwvqdKpWJME6Xbyi/nfiFJn02rb+RlKhVU6gftjmUtsXt6Gf7tDSf7pZSpzaFkE7B2gthUP4fSzcF1nkzsJIlMJnfm5ubExcXlVCySpFBplAW2K/xHeSzliGPHjlG/fn1mzpxJYmIi7733Hj4+Pri7u6PRmPj7fmMpRN1QllYSaZc7BJTl91yGpvSdew1zc3M6d+7M77//TlhYGH/++SfVO/elUaAVfjEwaNAgdu7cSZEiRaBEQ3hnD7TcknKAxEi4uUzpM5SQ0gKILl5pocqAfnX7Ucq6FIERgfzt93eG9sm39C/5ub1MXBjc3QThV1PKVGqlNS54p/J9TtbqT+hxFxzaZUuoklTQZHptWXd3d3788cfsW/NRkl6ksYRWW5UtO27j5IbQQ3BuFNz5w7jc/7/KlnoNyriHSovEi60/udRD4unTpwwbNoy3336bGzdu4OjoyPbt29mxY0feuW1Rewo0XAhNfk25LS8EJMYoHfQzmzi8wNLSkl69erFp0ybCwsK4fPkya9aswfziXuO1Z1NPD6Eyh6YrweUzKJaqVfPKVNhdAwI2v/68ZpZ81ugzABadWfRG15CnhR6EvfUh9PDL6+heaCjwmgSn+il/L8mK1VFa49oeNe6eYV608ExRIklZkOnk7ty5c/z55584OTnRsWNHevfubbRJUqH05CLcXA4PDhmXX/gCPAdAbGhKWdB22NsAzn9uXHdnJdhspRwr2b09sL8ZXHphbrkr0+HCWIi+k1IW7Q+310DIAeO6EdchwheRGMPmzZupWbMmq1YpfdQ+++wzfHx86N27N6q89GapNoMaX0DpFillARthpxOc6ANH2mdbMlykSBHq1auH6tNm4NYDlnyefkUzK3D+JO1i9/d2K62MqVuZEyKUn2M6MY58ayQalYZ/A/7FK9QrW64hz7n6PURcU1rcXqRPVBa132pn/Hfh0B6KNwDrVB8wVCqo+X9QqonSiidJUoZkehJjOzs73n///ZyIRZLyDyHgWZAyoSco/X3qTIPi9Y3rObRXWu0s7FLK1ObKZJ/aksZ1dc+U1gy1NqUs9h48PgOWZYzr+v8BMXeh4odQpLJS9ugMnBkC9u+AY/uUuif7QLg304+68f1KZcDEiO7l+eXDENRlroNdqthOD1ESlQZzUhKrSD/wWwJFKilvtMnu7VFuT5ZpnfJ9SIpREk6zokr97CKEEkPCE+X7U7ZL9rfcFC2qjKk945m5/TqeVhK8sp1TyoK2wZmhSp+9Nsa3X8vZluM/tf7D5mubWXJmCat7rKbAafUX+MyBykPg5gql72z159Nkqc0h4Sno4+HhcWVaGlAmta30keliloy9+H9LylcyndytXbs2J+KQpBRJz2BXVeVx95tgZm3aeNLjPR38FkOr7eDQVkmEUrcyJWuZzq26KkOMVl8w6HpNuXarsilljh2h9U5lnq7Uqn+h9FGyrpBSZllGSXrsjBPMBGHNs1gN/zviibm5OVOmTOHrj6uiPtMfJZtJ5elFeOoFiVEpZdF34OYvUNzVOLnzmaO8ObfcmpLcPbkEB1tB0arQ/UZK3aPd4cFh5bZm8ht4pB94DlJWLkjdt+3WSojwAac+UPr56hKJkVB5ENhWhbrfpbTuPPFSWsxsnMCiWNrvaWbM3QHvrILeYzO3n7lt2qQkLgw0VlCyaUqZ0IP3t1C2K2OafM7ma5vx8Pbgx/Y/Usr6hZ9vfhT/WOluUKSS8oHDdS48OArnRiofZqp9npKQv/WL8uGmaNWU/fNSy3FhoksA72nw9Iry/yx5LsC4MJnc5WMZTu70ej3z5s3j77//JiEhgbZt2zJ9+nSsrOSkkPmZXq9n/vz5/PbbbwQFBWFvb89nn33GlClTTBiVgNj7KY/zGl0CPDiiLJEWczf7jvti6xwoSUty4pRajbFpyxzeVbZUbt26RccxD7lzR0fp0qU5efIfGjdurLQQOgYBL7yhNlqk9Aks7ppSVqQy1JkK2hfiK9lY6RNpVS5VoVCuQ1vauG5StNIymfrWZfwTeHxaWRoqteC/4f5uKFY7Jbl7FgTnRijHdXver1EIONoF4kKUCXIbzlfKYwJgVzWwKAG9Q1KOe202hOxT+swlJ2OJUeA1WfkA0eDHlMTu0RmIuqW0xNo9718n9ErSqbGCIs6vvk1Ye7LSUpV6ROwjT7j6HfgtxK3XA94q+xbn759n5YWVTG41+eXHymuEHqJuKsl5+fdSys+PgYANUH8W1P5aKSvlprRel2mttNQl96FN/rlKuSvsBNxZDbY1oNYkpUxtDrdXKcl5xDUo+ZZSbm5rujilN5bh5G7WrFnMmDGDdu3aYWVlxaJFiwgLC2PNmjU5GV/+lhSjfNVYp3wq1SWASASVGWi06dS1SnnT0CcqtzNUGuOBBS+rm4X54CZPnszKlStZsGABLVu2JCQkhOvXs3+W8ExRW0LnSymP8xqNBbx7QElCKvYxdTQvdeHCBbp06UJYWBjOzs7s37+fqlWft5RoLI37NiUrk84a0bbVod53acsb/pTO/q2g94O05a22Ka1vqVsgbasrt+9e/L2t2Afsaiv9r0BpzfSaBKVapKwPCkrCl/BUeWxRPKU86Znyd/PiNDoRPhD2L5R7npDok+DcaLj7hzJYwjXVlCpXfoFf/gv/NwHcnpcnRsKeusrjvvHK7wEoyeGNJUqCWe/blGMf7qD8jbb+SxkAYGYDpVtDYjiq0P2MaTKGATsGUP3G9+gTj6Iu3wMqf5qq5eShchvaoiRYmqhlLzFSadExt4Xi9ZSyhKfKABKADyJSkoDkhD5oB9ScqPSb1Gjh3f/letgScHWmMvdfo0VKizcofzN31kGp5inJnUoFtb9J+z/ByiHXQ5ayUUZnO3ZxcRErVqwwPD9w4ICwsLBQZnkv4LK8QkXyGnqxYSll3jOfz6I+1LjuJmulPMo/pcx3gVJ24iPjuttKKeVPr6aU3fwt09cVGRkptFqtWLly5WvryhUqhBBJ8a+vk0fs379f2NjYCEC4urqKkJAQU4eUdV5fK7/vOysLoUs0fi3ukRBBO43LnlwSIipAiKjbxuWPzwtxe50QEddTypLXmj3UwbhuTa0QIETfyillsQ+E2FZaWRUj9coI50Y/X6/2m5SyhMiUv//EZynll75Sys5/IeIS40Ttn0qJpPWk+l/x4Pn+EUJ4f5/+igvbSgqxxU6I6LspZXc3C3GgjRBXf3jhezdFiEuThHgWmlIWcUMI/w1ChJ1KKdPrhQg5KMSN5ULER6WUX56mxOD5qfFx/64mxL6mQkTeSim7Ouf5/6sPhZSLnl4VwnOwEGfdjcv3NVN+Hv4bU8qi7wpxeboQwf/kaoimVFhXqMhwy11gYCBdunQxPG/Xrh0qlYr79+/nnekTpEzx9fUlPj6etm3bmjqUvC/uERxsCTXGKatm5GEeHh4MGjSIpKQk2rZty59//omtbT6+xVJ1FET4Kq1a6hf+ZWlLGt8ajL4L/2uu3DJuvSOl/FmwMro46ib0DE4pbzAHEGD//G9AnwSB22DiRPhqNvQcllLXsgy8H5Y2vnrfQ40vlUEkydRaZS42Xaxxq3uZNsptzdIt0Zpp6dNgOH0u/sBiBy3lHJoqrXsAlybC3Q1Ky59Zqp+dEErLmdCD2iKlPMYfwo4pt4tTu7HkeX/FwWBlr5Td/wcufgll3oZ2R1LqHm6vfC/MiykTD4PS9QAVPDxpfNwSb0F8mHJ9ycp2hPDLKS2uyXTxxncppKy7sQzu71W6ZTg8/53VPYM7a5SW07eWpNwlqjYaEj+BUqn6fdpUhHozcjtqyQQynNwlJSWlWXbK3NycxMTEbA+qwOgTrXzVpBoQUHOC8oepeuFbn/ymoUnVh7GaO7gMSzuRb4+7aetWHpTp8PJsf0l9Itz1UB5X6p83lh+7vUrpY3RtjhJT8pvwm0gIV940LYoro22TPbmg3JKzq5tyGzIhQhm8oLE0nrj10VllRG3x+lCkMj///DPTp4ynZ0No1rwlo+f8g1b7/I310WllupTirlDs+W21pBgI+hNQg3P/lOM+9ITI61DCNeXNWhenjNIFqDI0pUvAw1PKIIziril9qfQ6ZRAGKH3ckt/cH55S4ijewLh/oM88QA9V3VNWhHjoqQzCKF4fWv+Zqu6PSizVPk+ZwPjRabj3j5LEoVK6aiZEpNyutbRXfn7xj+DJeSjVTClPPapYCDjVX1l8vuF0uPMYrDOQFFvYpe14rrGACr3S1i3bSdmeG9Z4NBVPzuPP2/Gcf/dnGpnZKHE8OAJJUcqSXY4dlMqxD5Rby91vKt07UvdrLN8TbJyNB9iAktRF+xuXJU+fk3oaHZVK+X+iizNeEcS2BiCgWC3jYzw8Ac8CjZO78GvKdDVxYVAr1dJqB1pBbDC02Kzctgelr6MuVrkGOZAirdgQuDIN4h8af0h55Kn0Ry3VLCW5K1Zb6RNrVw/lF//59zP137NU6GQ4uRNCMGjQoJQ3CpSli0aMGIGNTcob3Z9//pne7oVTegmAxgKwSFueXl21efqJzcvqZlLVqlWxsrLi0KFDDB06NNP75xh9Apz+VHns9EHeSO6S+6eU75E9iR1AyP/gZF+lz9L7T1LWUb38jdLxv9k6qDxQKYu+Dce6K4MXeqVqefL9EYL+RN9oKRNX+vPTTz9RzRG2fgHC/CqqVH+v3FgGd/+rTAqbnNzFP1Hm4VNbGL8Z+P+hrAdad4Zx37ezygS8VB6cktwFbYfrPyv9rJKTO5GkzPEH4DwwJbkL2afMgVbV3Ti5u/yVklQ4D0hJ7kL/B94zlA8u5bql1L06S0l8KvVPSe4en4NrM8GhAzRZBRdGKUtWdfRUWuPCjkOLjUqykrrfXmoqlTLiOXiH0qk8dWKnSwJNpicXeC3Hoo70qd0HD28Plpxdwrqe65Q4ulxRJsa2fyelcsBGpcWt3HvQ5oX542yclWQp7qFx+cMTSjLr/DHYVlPKqgyFwM3KEl6p9YlOm2hV6q98mFC/0PLWeJnSglikCtzfpyQbxWoqH16Tp+YBJVGN9FUG1KTubxm8Ezw/gbJd4e3dKeWPziijxa3LF56kL2Cz0kpboVfKh3S1VvlACc8/pDwfCe78iTICO/Xfjpl1+n1ipUItw/+tBg4cmKbs448/ztZgpNxlaWnJpEmTmDhxIhYWFrRo0YKHDx9y7do1hgxJZ6qO3KLSKFN6JD/OC1QqqP1V9h7z0Wnlq9oiJbEDsKmstIJZpFpWy8wGSjROO6LWtgb6km4s/m0zP/18HIAv/28yovRJVC8udm9XG+zfVdbkTKaxUhKiFxNouzrKG2/qqSrUFkpy+yK7+lDhfaWlMZlKDU59n+9nZly3Un/ltmlqzoMAfUprdEwQ+M5X6pdsbly3yhClhSm5I3+0v5I4VHVXliOzdFBuRcbchRvLlcTCayJUGQZNf0sbf2rVxyjXaFMxpez3aTDlR9i7H+q+/er9s2BM0zF4eHuw8epGfmz3I/ZF7JVkuFwX44r6BKUlslQzZaLqolXAqjxcGg9FXODiWLByhF73U/Yp8dbz1rVUo87t6qY/6CW9ZMq8qLK9qFxX5Wv0XTjeS7kl3emc8aCU5GP2DFJagYu6pJTH3gdUxi2NQsDRzkrS2NkrZc7ICF/ldnrxBumPHM8vdHHKB57wq9D2UMrt+sjrcO9v5WebnNxpS0D92crPOPXfpmOHlJZcSXoVU3b4W7Zsmahbt64oWrSoKFq0qGjWrJnYs2eP4fXY2FgxatQoUaJECWFjYyN69+4tQkNDjY4REBAgunTpIqysrETp0qXF//3f/4nERONO10eOHBGurq7CwsJCVKlSRaxduzZTcWZ5QEU+oNPpxMyZM0XFihWFubm5cHJyEj/88EOaevn9OrPk9u9CXBgnhC4pZ46v1wvx4LgQD0+nlCU+UwYOnP9C6ZT/GlFRUaJDhw4CEGZmZuKPP/7ImVhz27W5Smfw/7UQQv+KQVs+85R6pwYYlz86l3KMHZWF2KAR4taqzMfx7KEQ9ayVwRVdXTK/fwY1XdlUMAPx3dHvUgp1SUpn+cC/UpUlCPHvf5Trujpb6RjvgRDb7YXYWkKIA28bD+BIPfAjJzw+L8SumkIcfCfz50qMUQbEJEuIVI61UWt8DZenPx/UMdh4/2tzlIEkqevmFff/J8SxnkJc+TalTK9XfkYeCPH4Qkr54wtCXF+kfC+lbFdYB1SYNLn7+++/xT///CNu3Lgh/Pz8xNdffy3Mzc3F1avKKNARI0aIChUqiEOHDonz58+LZs2aiebNmxv2T0pKEnXq1BHt2rUTly5dEnv27BGlSpUSkydPNtS5c+eOsLa2FuPGjRM+Pj5iyZIlQqPRiH379mU4zoKc3GVUYblOg+hAITZaKP+I7+RiwuS/4XlCUvG1SeWDBw/EW2+9JQBhbW0t9u7dmzsx5pbAv4xHhCfFKyNjY4JTysJOCuGhUt5IX0wubq5URpbeWqOMkE2dJD7xMk6q05MUp4ym/Qkh+lQQIuLhG1/Sy2y59Jto8yOi7cJSIj55VHZs2PNRtCrjRP/aj0L8XVUZTf/0ihBnhgtxearx9R9qryRD0YE5FrOBLsF4NO4bH++FEdHXFwuxx1WI60tSyuIep4wwTv29CdimjEh+cDz74nmdC+OF2N9cGYWc7M76lA8nqd38TYi7m5T4pVwhk7s8onjx4mLVqlX/z951h0dRft2zJZvee09IIYTeCYRepQsidiyoKIKKCiIqVrCAiAJi74ggKgpI7x1CTwgkJJDee9vN7s73x5lhZpOAoLTf597n2QcYZmenv+c999xzhbKyMsHGxkZYuXLlxf87ffq0AEDYt2+fIAiCsG7dOkGtVluweZ988ong4uIi6PV8QU6fPl1o2bKlxW+MHz9eGDx48BXvkxXc/XeO0yLOLycjdDnm6FqH2SQI2X8JQsYqxTIzrTqOzbo4KJw7d06IjIwUAAheXl7CgQMHbtw+3qzYcTsHzJNvycvMZkuw1zD0ZZYgOXeLIGwbLgh/xhI0nfvm8r+Z+J4grPKxBJn/JsxmgoALKy2sdYxHaffy+RIIy04sk9f/szmBQ2Wa5TYuF5XneJ6WaQShVgFIa/P/p+x8LhvV2bRn2T7Scvme+0RW8215maFSELYOEYTDzzYGjlcTxQmCsHNMY2ua9V34m+d/lpdVXSD4vpEg0xpNxn8V3N0ynZhNJhOWL1+O6upqxMXFISEhAfX19RgwQK4MjImJQUhICPbtY+/Hffv2oXXr1vD19b24zuDBg1FRUYHExMSL6yi3Ia0jbaOp0Ov1qKiouPiprKy85LrW+H8coeOBuG9vbMNylZrVlMFj5GVF+1lckDwfUKlw5MgRxMXFITU1FWFhYdizZw+6dOly6W3+L0XWH4CxllquxLnUKUkRNJJVr0prEZXq0gUSAIXoSj3jiZdZbSiYafnhP+TS3wWA2BeAYUnUK0qx7ccrOxZjNauDC3ZbLt/QGdg9jlorMTQeHVCmcUOpGfjo4EfyusNOA4P2WFqc/F2hgUMo0H8r0H6+pflxwjPArz7A+Z+ubP8vF+k/ABdWUCfXVJj0//43LhcOAUC3rxoXlgSNBKKeALx7yssqklnIc2GZpf7z6AvA5j6sspaCCXhWxW/qCeRtlv/PXM/K8mxFAQjAQqLuP8qVwAC1gTHPAD7x//ZIrWGNfxTXvvzrKuPkyZOIi4tDXV0dnJyc8NtvvyE2NhbHjh2DTqeDm7KpOQBfX1/k5eUBAPLy8iyAnfT/0v9dbp2KigrU1tY2aQcyd+5cvP7669fqEK3xvxKmOlZyxs6UKzZvhfDsxP6t1ReQmV+Fvn37oqKiAt8/641Rd94D51DPm72H1yYK9wI7R7E4wKynm75zpKKx/D1A2H2Nve6uJrp+xRZgHT/kv+186GGo1tDfzqcXO2cow1Y8v2YzMDAY2JoDfH8OuO9VeZ3qC+yr6tVdBlQZvwD7H6S33YDtXKZSsdrRUCJ3mgGA4DHQe8Tj5Q9DYDDtx8Hsg+gS2OWfVYyqNayyVVbaCmZa7NSXWwLFqvP0pvMfbAmaLxf6YiBhKgsfVBogZKzl/+dsAI4+TwsP54ir3/9/EyHj5PtFCodgoMtncscScz0BXe4GoOwkn/szH7LrTNkJYHNv2lfV5QLFB1ktbCil5Uj7+Sz0EAT52jQ8/v9iGMqBvE2s8g0acbP3xhoAbjpz17x5cxw7dgwHDhzAE088gQkTJiApKemm7tPMmTNRXl5+8XOz98caNygOPQkkzgF2jrw0I3EzQm0DhNwBtHgOc+fORUVFBYb0boN7O5fAOW2Oog/v/2CY64GsP4GEaQQ79gFkQMIn0FhYpwCuGt3lgV1N9t//nmsM0GMZQZ1UeXz8JeD3UNq8rGtj6f+mjPpSwK6Ab82d31j+384xBKaFO+Vl7m15PPYBluv2Xc/KUmV/VZUKvk6+uKvVXQCAjw58hGsaKjUw/DQwcLelBUr6t8DO0fT3u9LQOADNnwY8u9Ffr2H4D2Lv3qzVjf/vZoS9L/1C1bbApl7A9hGs8LX1BTouBooPkKGrr2Blbn05K9XjfuCEAuA5+tWH1eN+/QnsDOVc36zwehUEWgbpSyz3IW8r235VX5CXmY30+/tfDEGgl6UUGSvJRifOuXn7ZA2LuOnMnU6nQ2QkS+Q7duyIQ4cOYeHChRg/fjwMBgPKysos2Lv8/Hz4+bHnnZ+fHw4ePGixvfz8/Iv/J/0pLVOu4+LickkTX1tbWws/v4qKin93kNb434jIx+g91/LlW9JjKyMjA198Qe+rWa/Pgyo4m75gSguSs0tEv7j7ZW+sWzmM1RwUzHqg2QNMgUpdEq7mGpQnA+s7AoEj2Lj+Shkjk4HsjLGSjJpjqOzTVpsHlB4FnKO5PVtP4Pm7gB4/ADG1ltvx7AwIJstlbm2B25sAnJc5rqldpuK7499hReIKvD/wffg7+1/ZcVxJqNT08VOG1pmeclK/XQCorwIOTQKCbqf3WkNZgtYeaD2bxrlNSRZUKqDlzGu331cbxmpg/8NAeSLQfweQvZosZk0mjcADRzG979UVaP4koBJ4jdW2nFj0/pNdQXzFPstV59lf11TLdLAUe+8BctYBLrHAcMqAkLuBdi4uMbRzkfwdT73OvsY9fpZtdspOAus7AK6tgGEn5e0WH+YkxjmaHna3Wpx8HUj9HOj0kSwfCRCP2SfektW0xk2Lmw7uGobZbIZer0fHjh1hY2ODLVu2YOxY0t5nzpxBRkYG4uI4442Li8Pbb7+NgoIC+PhwFr5p0ya4uLggNjb24jrr1q2z+I1NmzZd3IY1rHExvLoBI1OvPD11LUIwX7Gmb+7cuaivr0e/fv0Q31vsrKDsTGIycBCpK6Df2a2WLqrNpzGroQToMJ/LdG70rVPbAjZu/xyQ5m5gG6aMn8mI9PpF/r+/2hOw9P6DRrsAu19krAA8OgCDDgDp39Arz9aTg2vlWeDsInYEaDkLaPsWvxe/BCjZwBSdsq1W508aD2j/YIDrGNAR3YO7Y2/mXnya8Cle6/PaVW/jqqLFNGrDlF0pctayQ0zRAUvtp9lkqV9U3rcmA5D2JRDxmOU61ztSlgJp3wK+fYDYF8m6qrScpNWXAbvvAAq2A55xQKuXgW7fEtRVXQCOz6AXYvcf5O1tH8rUbN8N8rKK09yWa0vAVTGRqkzhn0pzZsl7sSIZKDkis7NOEWTzDOXyutVi55CGPoJHphGEdv+RDCgAVGfwmri2unFpT0EgQC7YSR2jdD8bytgVJ3eDfH84BJIZtsYtEzcV3M2cORO33XYbQkJCUFlZiWXLlmH79u3YsGEDXF1d8cgjj2DatGnw8PCAi4sLpkyZgri4OHTrxtZBgwYNQmxsLO6//3689957yMvLw8svv4zJkydfZN4mTZqERYsWYfr06Xj44YexdetWrFixAmvXrr3crlnjvxKF+8hcOIpmqjcS2NXkUN/T6mUybZcBeRkZGfjyyy8BALNnz77EWmag5SvssKDst5q9jn1AQ8aTdblZUZfPgga1jsescxfTOwaaIDuFcb2078i2xL7Y2Oz4UhHzNA2QjzzTuMCiMpVGxmobDrClR5mGO/Mhf9dvEJkqqAiKa3OYljOIqbWUJWQqAocC3b6WWwVumAR8ugKY+SjQ+V0uq83jwG7v31i7d4XxdNensTdzL5YeXoqZ8TNhq73OfVlVast7z60t0OJ5dkORBnRBAP5oxhRkj58B356W2zjyLM9T/g4gfvmV/W7DiU3hXur5fHoR5JtN7K6R/j3ToQU7gOL9QP9twMHHqCE01gAQmLI/vww4/CS/32kRgXpdAVC0Fyjex+vf7AH+VuU5tsxrqEzSuROgSfo8gKbfIeO4DxpFd6FOiwh0lL103dsxXV1xRp5IAIBLCyDta6BgKxAl9isOHgO0mEFwp+xCYetBwKg0EC8+RPmAZxdLcHf4acBYAcQ8R+Nx4N8xZ8rvGqvJhpsNTEVL93PkoyxE8u39z37DGjckbiq4KygowAMPPIDc3Fy4urqiTZs22LBhAwYOJCuxYMECqNVqjB07Fnq9HoMHD8aSJUsufl+j0WDNmjV44oknEBcXB0dHR0yYMAFvvCG3YgkPD8fatWvx7LPPYuHChQgKCsIXX3yBwYMH3/DjtcYtFuXJnKlr7YH+2+X2TDcqkj8AqlLJPoTff9lVlaxdr169ml5JYwc0f4ofZZx6nanHukJWf96IKDrI6l7XWKbwAMC9DbtEeHeX21mdX0Y27/yPwKgMFiMkf0CRPwD0XHXlvxn1GDtUqNRi26tksjADdnKgcghmMUXiHKYhY2eQjbH3ZUrJ1psgEAAChgP5WzjYe3QEUj8FDAp5Rr0BePBTIA+AzXvA/B4E1HlbgH33UYTfb5O8/oZuTAvG/yKzOSVHuF3XVkDzKRdXHePpizEeXthSlo+VSStxX5sb3AnINYYt6pRReoy9ZAEye24tmTqvySSIco7iNZW6Skhx6EmC5Y4fyxOotG+AQ0+wC03PVbJmbc/d/I2OHxF4O0fzuUhZTP1lfTl7rpadYoGDVJDi0QnotJjPMkDAJ7XSE8zsN6wvtAT9np2BPusbd3zpv60xMHJrCcSvaHyemuoUobHjurU5PD9SVF8gYFOm7o01wOn3AAgETFKE3ce0ca1CTmTvz9Z8Tg3kBpmryKJFPi4vy1rNyUrgSMuOLJWp7N7SVLFY0UHgxCyy5/E/E9AdfY4sqF8vEUSL4RrbuNewNW65uKngTmIiLhV2dnZYvHgxFi9efMl1QkNDG6VdG0afPn1w9OjRf7SP1vh/HFp7snY2zo0brt+IaDuHL3G/fjKDYTZx4FJYWFy4cOHis/Laa69d3W+YTdRO1ZfLfWoBVnZWprDV1rXo3SsIHEillFxNBtOeDkGW2qyG7b8ChwNRTwKOYfIxx68gS9H1c3k9Qyn1YcqCirpiDujt3pGXX7SjEIANXamlG3pCtqRwb88B0jUWaDdX3lZTKSWzkftdXw5ETiIg2TaUx9RhHvBIF+Cnw0Cf1tQcARzcXWLY61UZtTn8KM91+Wkg9TMCFwW40yY8hVWeRRhQCyw8sBD3tr4Xqpy/gD138fj6KLIOJ18nWxg9WWZu6grJ9Nj7Me0shSAwda0vIhCz95P/L/Vz8Tgfl9OEmb9Sw+kjssvxvxB0pSxhT+PhZ8nY5W1m+tCsJ9OmjOw1BIAtXya40heRuTXVka3aNRbI/hPo+RuBoZ0vr3NVGtdxa8v7R+cB5G8FWr9BqyC1LYF08FjAV7y2UU8Q2LR6Wf59lRpo9VLja2uqYypX04AVvRTjVV/J8+wcKa+T9QfBlU8fIELshW02AKvFFml3lHByABCc6Yt4bFKY9UCL55hytfWWl+dt4n1h6w0EiT2VPToBFdP4d2ONrMXrMB+oOMt7TorKFLLkxgbFGlv687nsv42TGOcoAGqg7BigsuF1VOtoD9N7Nf9tqgGipwAe7Zs+L9a4ZeOW09xZwxo3LBxDWT1oNtycdKVG15hJO/cZcOwloMMHFwcMibXr378/evbs2cSGLhNqDXvixs6wHLhOv0+2LHoKhdH/Js59xe21eAGIeJjLAofz36F3AbhMikjnCnRuMHlziQZ6/mK5bP9D7CHb9i0yPd69gG2DgdIjwLaBZER8+gADtnF9lZoMoaHcknUIuYOfKwkJMOrcAXMKU4JQARAIjN7YB7yiB2wUvYFDxjatdRywgwBVOQi7tQZav964X6pTMxiNtahABg7nHMb+rP2IM5ZysNYXMX3p2VW2byk/RfARcgcQPJos7Y7hgMYRcAwCBuwmcN7Slzo6cx3Q7GGg25dAeRL9BDNWEmwEjSa4K9hF8JS/hbpIlYppxOAxBC/GSmrGqs/ze55dyU65tuI2iw+S/Wz9Gq+XvhhY4czzdttRYGQ6z+uhSfz/8iRqIgFeL6dQsqp2PoDbG0DSuwSB5aeB5s8Ce+8icxequJaxM66skKMiBdjaD3DvQK2kvb/8bORtZvW2Vzcg7G4uM+mBlaKWbmyRbI1TfgpI/473mgTuNHYEqGobpmwlcBdwG5k7JbOpc2/MkAJMAdt6WzKDlSms6i1PArp9Iy8vOUztm1Mzma2MfIyFM0otn7me1x0Azi4GMn+h7MHWmwxd8Dig/Tzg1FvU++0cw2va5m2y0Nb4nwsruLPGfysEM/U2LqKe5VaqKBUEDtb1ZRdTThcuXMBXX30F4HJauyuIhoyEc3MOnOEPyMtq85h+8x90+SIPQzl1SdI26/KZAr3wswzuNHaNm8gro76y6Yb0UpjqyC4aSsjeFOzkd47OoMC956+sit15O82m87c2Zl/7rr/09q82vLowvZu5iqneFi8AajVQfoiDIDSAoQ44t4SgsPlUS/2SUzhQJQCFu8n8ucYyTe0STTB/YCLQaQkBf+/V0J6ej/U1r2JJcT0+OvgR4kZ9AXicBta2ADb1AMYUAHbeLIZIXwZc+BHQ2hHcaewIXMpOUPtVX05wZyjhAK9kD6vOA+d/oOVMwJ1yuvz4S9zX6KlA4DAuK9pLVse1FTD8DKtCVRogbAL/r81bTDkfeY6p9WYPiZY2vckmmmqYVlXrZH1lm7eAdu9aXjutA1ml+kqCj+JDZJaCxwDNnwF0Tpw0SNuSQrpnTQYeo3TuC/ewwMK9Hat/a7OA2gKg5g8g+w9LwFZ8CDj7EXVsErjT2JI5NBsIUqV1ffsD7TRM2yvj9tzGz5tHB0sW9XLhN6AxoHIIInNaX2a57ZKjrLoVFHYs+kJgcy9eJ5+eBH8D9wBDjvCezN8OlBwiaLf1pEbQowNZRL+BlEmkLOa7ssN8mSU89zWQ9hUQejcQ/aT8e0om0Rq3TFjBnTWuPOorgLNLgYjb5XL+/7U4MZtasO4/WFYC3gqhUgF9N9JJP5QDy9y5cxHqUY8OXXpcPWt3uWj9Chk95UCf+hlwcjYHzh6X6GJw4FGCgb6b5FRn+ANkP670fBprWMHq04sMpbGGDJxLC1qOpH3LQTZlMQe10ZlMARbsILOisedArvMAbs8HbF3+3bloGIJAcK1SAVpHLjPVUZzv3l42QK46z1SX2QwcDAB+zgVeNQFuAI7PIpi5s1YW4acsJcMZM02uFlZpgTML+Pe27wAar4u/5yHUwE8DvJ70C+YNnIdA1xiK+9VauXNHxCNc5toc8Bavh19/4LYEmglrbHltAKDfZqayHYNl3ZVLc7JHOg8ZmAPUuxmraCi9ayzQ6lUyaYKYqq7JJKA31hJ4lSaQrQWYknaKFAsIdgAjzxGIDj/DStCVrkDXL6inc44g47f7DgK8jh+yoObgo4BHZwKsw08BUAGjMgEHf4K3yEkEn/oieZ/NJuA3Py4bUyin+Qt2UWsZPoHgzrcv0OdPYPd4gqW6fKZL63JZsBA7g4BHGaMzZQAjmOW0pldXeR19CdlZG1f5t80m3tuCiduWAGjFWaDqHN+jkn5NEKhBFUycsEgp4+JDZGvdWlqywqfeYtFG5KO89lVpQMZvnOgIJt6/BbvI+uVuJFOf+xfQ9Wsyp5JXn3Mknz2AE462cwiqq89ToydFSQLPudJOx1zP62nrBQw9KR935Tmyu06Rt5Yh/H8orODuPx5msxnz5s3DZ599hszMTPj6+uLxxx/HrFmzLFcUBIK79A8B9zAZ3JnrOUD9L/gamY180ZpqLS0JbqVQay4WV5C1+xLbXgK6NT/CdNG1tEFoqLVTazkwBYq/IQhAWSJgLGfnBZWKg7upjmyABO4cAi0tWS4V5nqK4S8s50Bk1pP5OfIM04Lt3mOaOnk+2Qgbd3qImQwcNELGcp99enPgX9Ocv91vq+w/ZjaRuTBWW3rd5e9gkYZnN7JwANmkfRO4H/23yOsemkSg2+ZNWb9lrCEAAagvU9vIthvmOuDPLCAfwM5AYObDQOKb4vcqAY3I9DiGkoW0U3TMUWtptaJ1sKzEbPYgEHAb1v7xJIzmA1h6eCne7PcmMFphgiuF/0B+GkZAg6IxpXGzFM4RrIxtGN1EPfT+RwhkqtNpXDw6i9fRKQwYkkCQYijhuXBrx+80f4ppzSPPWho4u0TzfJgNllXpNTnU99kHAVDz2glGgsfDTwEqHQATwZexHFjbksxxfQUnFgG3AUnvkaGTqlzrcllosPde7m/wHbxnAOCPSAKrZg8DXZbyWuZuZJofauAeRdHDpt40po56UpYP1OUDv4nHdbdZfvedfJ2sX8uXyCoDvDc2iPfbndUyQEz7BkiaSyay4wL59/aJxTMBtwEaUYeXu5FV5hETLRm9xLmcQMQ8x+PZ3Fs+L0G38/6V7Fr8+suTCOcIeZ/zt9HQ2SkSGCmua+NEJs+7B9nz/C28d5tPIYh0jqROUDCKWlsj2WFjJVCUymt+5iOeixbPy6lns5GTG+dIpv+vhdbXGpcMK7i7niFVc2kc5IfJZCCFrtJainkvrmuvENfX82Wl0li+DC+17j94WGbOnInPP/8cCxYsQHx8PHJzc5GcnNz0yjZuTEUotSBpXwOn3iYbEfP0Vf/+DQ21Fui1Gsj569ZokWM2klGIekJmVxQxZ84cONsa4ebqCo26/vqLmlu+xMFGpRVtEDqL/U8Fsj5+/WndEP0U036Xi7oiAmlbb3m/9cU0bVWpgX5bAJiZmvXoRC2VjRO7THh0InPU+nWyFXVFwOlPWZCQ+ilZicgnOLBUZ3Lwi3iQv1F9HvgzkozbnVXy/pz/ETj3OQc8Cdyp1GQyAF4LSWMneZXVKyYANi6ijsmVz6TahoUwvX6nTvKlYiDFFZj9DXBsKtBjJVNiNm7yNqIn89MwJA89ZTgEAg6BuK/LC/j9wh34NOFTzOo1C3baG2jVA7CoxbcvrS80Og7c0rvMIYifpsKzEzBwF9nNzN8JaL3jgN5reB/sGgskPMvUedqX1OcZSglA1LYEjueXEbCVnyJgUevkSZnaHgi5DfASK4/Tv+d64Q8STNh6sPdteSIAFVnXimQyYmYjv6Mvkt+ZFyd7DTrTVJ3jn7W54n8LvFelEMz8rqmOle9qHaAv4/5WpXFzDsF8pgQzNY/6Yt737h14nWvz2PtW68y0qErNd/6Fn/n7Ns5k0z27kOU8PJX74BVH1k/rRGZPZcPnLfIxTmK0DiyA0TozXT/kMH/71NvAgUf4vEt9hmtzgZXuHJPG5BGYV6ZQI1qRTPDX+w+mtDV27I8MFXCPGbijlBXJyQuAsx9zsqLWNrZzqclkul9tC4xX6GDPLqF2MOxevmOscU3CCu6uZ6wQ6WhJHwNw5iLNwpTVgKt8OAsbmS7rUc4u5kMWeg/Q40d53dVhfDENPSU3NE/7xrKc/gqisrISCxcuxKJFizBhAispIyIiEB8f33hllYqDb+fF1PZIkb2WFVgmhWO/2cSKL9++javRbkYoNSFq7a0B7AARGL9JUfaIcxbmr5LWzmgESjv9AbT2tBxI078nm3atenfWV1Cs7SWlo3QcIFUaAk+fPlzsGmP5PbMZqEjiDD/gNuq8BDPTp0lzxYGmK1/eofcw/WPvB0CgV5nWkdWssdO5vV3jKPbu+LF8b9eX85nROBJkGUq5n8Yq4Pz3ZGgA3ncZK/l3ldbSdNezC49RWdBg48pesxKYk6LVbBYCaBQ6IrWWxTcNI2AwP1LGPHkB09YXlgMdFlIE7x0HRE26osvQMEbFjEKwSzAyKzKx/NRyPNjuwX+0nSsOQQAgWGoufXrynAsmsjwdFvB9Vpkq6wcFM8Fa/hamP6OfYpFSxkrg2HTae3jHEajYOHOg1xcCyR8S3GmdgM6fkl21DyQIChnPe0elBqAiW6yx4/VSa+mnd/J14MjzcurPzof3YNo3LFRxCGHKuS6Pn913EExrnaiVy/qT95ZnV2DIMUAQmb+N3WlkHfYA9XfNHhFbbN0pGxm7tua+be1Prap7ewJ/r65AwW5gxzAyz4YSrmvjxOKFwj0EVjHPkgmrOMOCIZcYy6rtc1/yPRr7Iv0VNXY02M4WC0+cQuViqOIDJA1aPC/fa+WnmRbXecjbtPXkea9MIdCL+5bH1HwqO8WYbHkPSF1vnKMJ7pyjmO49+gLgN4T7Ij1jiXN5TTQOLOzQuQEt3qL0QGmODQBh98upfSly17NYxrOzFdxdw7CCu/9wnD59Gnq9Hv37/4sHqsdyvoDcFaxS0R6KrR3DgJFpNzdlW1cIbIwj8G0x/dZKH7u2JEALGWfp6m8yYM6cOTAajRgwYADiezbwtStP5swbamDYKaY5rjbM9QTkNi4EZhu7kXXo8BEF8E5hQNcv2dkh+QMg4Wmg3Rx6s6nUTLtk/wl0+Rw4PJlAq8fPwJ7xHJw7fsiBwdaHTGnmLxwMBu4maKxMJbOhtIYACCQdgixZaFsvToZsXGmFkfEzzWjd2zGFLfkTnvsMOD6T9+KQBMtrHTmRH2WotXKVozL+jUYoaDRw9gsgIQlweJ9M4oVlZFmkSklBIFCysHUpYHWlnbdcYWmshrZgN+a1Gojxe7/CRwc+woS2E6DK30pGyruHLOY3lAIn3wAgyJpAgKxI9hqyIlI1paGU4MVsAEakyAPt0ReA0/OpOQsYxn021XEyCZAVK9pHEGCsBQxFcrW1Sk1Aqy8gmAu/n+DOOYrASfJnq83nZDB4LJC6lIbSIXfx/sldD4yrAH62Y2rcoxMnBR0+4Dk7Nh3w6kGQbqziPXzmY8BQTEPhkLs4oSzaR9AfNFpOY1emAlv6Eey0n0dmEeC/y05QW+ahqGQ1lBL8BI2kZQoAZP7GP/WFANRAmzd4j6m0/Lh3oIbRNVbuk6yx59+lya9LDKtvs/+i32Lcd/ye/20EnKub0dKm9x+cLBUfBJLe4XMa8Qi3GfUEGdF278j7GzGRWRVvxcTcIZDPpKaBE0DLlzjpcmrGidaAHQRcw5NliY3kL2ms4b2qsSNDHnIn77t+Csb7zAJei5HpQHtxnzJWARd+4jUIF1PNTuFA9+/QKCInMWXufQ01xdawgrvrGlJaSMkAtHiBFW6qBqdecr1XPojRkwlKVBrLdUedb7zulWieGsSleuteVWjtLbshAHL7K5/elgPssZlkboLH3DiRrZTaSP2ML8WGLM3NDO/uBDvK2W3xIRi3DocmjULxJitkTTWARxceiwTsqjNpLqt1lgdxADg6nULo1q/LfR9TP+Pg6dqS4NC1JYFTfRVw4EE2TBeMHPRs3AlOHIKowznwCODbj7Nzs4E6G+8eYgcIWw5e9gEEBm3n0Ecv4xd+P/UzArMBu8mqDNzb+Hp0+sjSmqUmm+BQyXJLgMy9jeV37QP4O83EwgCTKGmQgLOxmukjtY3cPxYQOyMUEoRI3m/VmdSB6dws/QHPfMxq3YhHZGBVnsQKUTsfoO3HwCvZwEkAH7gAga5MtW3swWc/eBTwVwfu6+1Z8nYPPclK3E6L5UrEmmxg+xDcoXWBvdYeR/OOYk/mHsRnfw+kf8sqU2kfjLVMwak0luCuPImpZ2WnD5VGTLeDg7LGlt+vKwIgMP29pQ+rLevFd5jWiWymYCR4PvocmVSlnKD1q2Sj7QM56OeLoKHPOqbFkz9iQQXMZEedIsi6lifK+stuX1HfVZnC58KzG5knWx8AKk4c+21lal1tw5R/3mYgbzvQS2RtIRCslR7ldXQM5nMS+RivdckRGdz59gNavyne/4oK7u7LAVM131clRzmRCLiNWZizi2kMXnEawGhg8MGmJ423ZxPIVWfw+AAWkgB8F9q6E/y6tSQzd/gpahulCv6YZ3lu0r9nOtMhmECp8xJe1/0PEwh2/UKuaC49zv11juSzFXpn4/2qOkfGXDJ1VqmY0m2qo4qyCjZwmPw7UpgNfLdUplha+hTu5v3sECKDO8EMrGvDgpu4bznJA+hbGDi08W9b41+FFdxdz5Aq7ZSh0QHQNV7e1Lpqm6Z1dJda9yojKioK9vb22LJlCyZOnPj3X7jSCLmDAK6+Ul5Wm0uvKgjUKkng7ip6q/6jaP4UB3efvrcGsKuvJJuj0nCGr1Lx7+e+5Gy8PBHa+gJ0iQBsfTsivupZYE8U0GOZvI2Dj5PRiP9FXlZ2kia7TpGW4K7kCNMpEY/w3+nfiq22IDIgNRwE280Dyk+KOjlPYNcdTJHFfSdqmLw5GNsFEEB2/Aho/wEHxcJ9BPTOEUwrVZxlqvn4S+w6EXYXQVLmKq7vHCH60MUR8OWs5eREEvuva0fw0ewhem6VJ9K+Qa0VOxgoUrbZa4DDU5h2jf+ZgnO1LQeR8lNA56UcMFu+zPOwcxRB3OD98jk6Mo1prV6r5YlKZQoLPVxbWoK7rNVMPXrHy8CqXmSdHMMABxcg2Bs4Uw7kVAA+5RT3m6qB5HkiKyfIg70UNi48N8pnQesEuLWF2sYF97WJwedHPsdHBz5CfLt+ZNSUg7GNC9N3ap2lBUvYvQQyyhZZhXuByCdZhCFNMrN+Y39dz25k7bL/JECozQWqz7G63CkU6P492TeXGFZqOoXL21VqCsuTCRBVGnYlSV1KAAEx7VsjVkD/5stzETGR10Uw8d7K28RJg1SBbTaKqfhqwLOj/A706kFwpzD9hrGKKViA3ogXWws6EOjaerCbCcBCnLMfkqXz6yffVyUH+Jzp3MniDdjJ9PSOEcwG9F4jA53ig0zFu7WxlMZkr2Oq1Dtetk8x1nL/Ih7hR5qcqTRktwGaNkvRYQEANT0WlQ4FVed5zza8j448yyKJuB/k90DFGbKyrrG8H3aP5351FxllO19LFrmpMBl4nFIRlRRah6a9BcPuJdjz6CQvq77AZ7kyxfJdfGwmwX/sDAsz75sZO3fuxPvvv4+EhATk5ubit99+w+jRoy/7ne3bt2PatGlITExEcHAwXn75ZTz44IM3ZH+bCiu4+w+HnZ0dZsyYgenTp0On06FHjx4oLCxEYmIiHnnkkX+3cZXa0kNOpaGdQlWapXbs4CQ+8G3euLZ6C+UAF/XEtdtuU1FyhLNrxzDLopJtQwi6lC2ncjcwreUdT8G5FCmfACUJyG/+Kd7+bjX+SDBjzU/3AQXPckDLXst2TSqVqG9pwLrmip5u+gK5OKC+ggOOT28OlNWZHFs1DoD/YCDue4LEzb3JtiiZpBOvcGCrr6KO548o6jzry6iBcwgEkt5nqkzqw1p9gUzChi5cx62dbNlRlcYBPaC1JYA5+QbZG78BMrgzFHPQKj5Me43yJPq42fkTKEk9XwGRGTkv31PSoC/5n535iJrA+gqmAm3cGk+OJH2R0nfP3p8i9obeeeH38dq5tpKXOTWjsazUburz9UBJLhDkwd91CAM2x5MxSZ5PUBxwGxnN4LG8pt2+4kcZDgHA0GMAgCn5J/H5kc/x6+lfkTloPoIbavhsnCw7bgAE2Rkrya4rmf2TszlQ+/eXWU3naAIQe1+yPb79CABKT/J6BI1SnBtfmWkx14sdVXwI8tN/INAxVvBca+xYqZr7l3h/tCGIdgiiT2Cv1WQxHUPl5zVgCD/KUGuBQXvRKFrPpl5TyX67xPJ4bFwtTYM9OxFAuLW13IZ7B4I7jT2tQ3x6ysbXNu5MqVac5vLS42R5lUCr/BRwdhGLQpTgLmEK7/uBe8jSAwTNe8bz76F3y5O2Aw8TZEU9yV7HAFB6gt1AXFtYdnbJWc8ijK5fyVpuY63cxcXO17LVWuU5/m5NFtnXwGGirdVivou6/8gKcIDp66R3CN6lKmqTAfjNn8/diJQrk4F4dpLZUSns/NgdozbXEkyWJ/EdcD0n+VcZ1dXVaNu2LR5++GGMGTPmb9dPT0/HsGHDMGnSJPz4448XCRN/f/+b1urUCu7+4/HKK69Aq9Xi1VdfRU5ODvz9/TFp0j8Tf1827HyANq9ZLhPMbHKvL4RFF4O6An5cW/4zjdy5r2lf0PlTS3uJ6xVVaUyJefe0BHd1hUxxGUrlZToPngtl30mAg7xnN3z6wwZ8vMGMgQMHolX8fUBxJCvadgxnWqnLp/TCU2r0AKZwajLFjhCC2Gj8VSBvPQsZHENZ/VpyGIh5AejwHr9XKVYDmmotK64FM/dbYj1qc5gO1nnKoF0CUG6tmXL0FKtQ7f04UPb4STaLtg8gK+TWIJUaPJZAUOcmL+v8KZCzjmng8Alkl/K30WTVZLBkrHz7AIP2y9/PXkeA228jJxT5O4CTr1Jn5BAEjCsViwYUoUz5SuHaommvv6bkD3ZeluyefwQ/yhh6AthzD5C9Gkh6GygXRf8RjzZuydZEtPZtjb5hfbHt/DYsObQEc3vPspQ2HJvJ9HW7uXIrNEMJ9VAOQQprDiO1WY5h1DKajQR6xmqmHC/6sCXRJy/tS1p/mOt5fydMIWAPGkXGNX8r4BDKc+7akno3KerLgHrwfhhyhPenS4xlkZUEev5pqFSNDXRt3YHBBziJUT7/Pr34aRj9NvJe/zOKf47KoHQm6kmmVO285Pur568ERo5h8vfd2pIZVlaGAiKzq2bRVLt3KSOQJjsANZZSlJ/mefZVZDUqz7I63Duez7cUx2eRYe+9VgbZhbto5eLWhtWuUuy5m5Ok6Kl8PjV2rBhPnEO9oVQwBQC5m/g59yUBb4vnOXmqyyPrV3mWTOg/0fgCnGRI+kVldP+ex38LeafedtttuO222654/aVLlyI8PBzz588HALRo0QK7d+/GggULrODOGjcn1Go1Zs2a1djX7kaESg3cdoSzSuVLN/07phHCH6A242qiNg84/CRfol49Govor0e4tmRKrOHLvdtXBEnKl6FfP2BMfuNttJyJ9PR0vLmIxQGzZ8/moBI4nC9njR3FyYAlsMv8nS9pxwi+HN070gJC8stS28mMWK340jdVy9+XtGcOwZap/eZTOIhJBqsDd3IgcGkhD86RjxHsaOwtB9HhCiudE7M5oIfeRTuGhtFpoeW/zSbaLXT8UJ7dt33L0qpEGbaeipRXDVPTNRnUJUU9QY1b0EjLScLxlwhm2rwuFy9cr0j4C/jgZeC7A0Cv3zgwh4wjE6vSsMVX6THLtKmxllpGQeCAb+cN2Ljh7Zg4rCzbhudz34V57TKoR19gmrhgJ3WVZcfJgnvFMX1oqGCrLtcYbuvoC2QOY19kClv6rU09+PcunxGQOEVwQpG6FHCOES17XuckBmoAZuox9YX8nqGU94qNO8FJdYaowzrL7UnyA0ljdT0iYyXPp5TGVU4WmorafJ4rv37i+u68t6vSxCrgQN7TLg2ATMO0JCCzVGYTfSGl1G78CmDHKFa3escT3DV7gM9CXQFbw0nR4yeeRzcFI+zSgkxbQ7sZjw4EtPYKv0RTHY9f20DLXJlKixadm5ymrcnkO9a1FTBekdZNeodgPXgc4NeXy0qPAxu78v1we64M/vc/wvuu3Vy5nV91Ju9v1xZX1gZOCp2bnNn4H419+/ZhwIABFssGDx6MZ5555ubsEKzgzho3OxyCGqdN9cXUTUlMEMCX17EXgUCxeu1SFL69H5uQZ66ydNy/nuHaonFKDLBMCTUMs5GzYIegi31tpQrZe0fHo0eUSW511OY1DpLHZzGNOXAXkLGCerO8zRxkdZ5Mn9m4sWIQAKCmiapg5D+jJzP90UxxXrzigHHljfWIDRmqhi2WAHG/L1OUU3yYrAUEVrQ2tY2GkfA0O1NkrwN6/Spf57/TBAEEp82nsMNFuIJJUwK7mhwCHHM9vdv+jZC7roBdCex8ZOBiKKW9BgB4DQX6DgMqBSAoHri9BVNxHu05oJ35gHrA3XcCHT5ksYkgEKRmraJ9RvlJVouG3oW4c3PQxQvQqASYazL5TORtobdY+ASg9wsc+FVaCtoBYPBeOQ0tgXIp5WgyUP/kEEp7o8NPySbAtj7UhGkcaUYLgeAh9G6m9EuOsTrZWMmCBP8BPAcS0L6RUbgH2HMX92/g3sbpwIZRkgBs6Er2/PYc+bz0+FnUn2ku//2moq4AWNOC52Nsicy+NXuI7wFl0ZlGZwnsgKb32a2lDBSV0RTTHDQSuKteftYvrvsl35un3uB90foVTujaziGgVR6re3sAAp8hH7Fy1ayX7WeU79yaDIJGkwIc1uWxStk7/urA3Q2KyspKVFRUXPy3ra0tbG2vjVVXXl4efH19LZb5+vqioqICtbW116Z48SrDCu6scetFu7lMoylTtXmbgTMLCdpGXZCXK7V1UjSl2bmR0XCfcjcyZebTi+2PADIda6IpMg+7B+l+s/HNN98AAJbek08dXJu3gVYvcX0bZxY+AHTjT3ybaVLnaP7p2pLA1rcPQdSQBL7MUz6hnhFgu7H6Sku9nkZ3/VLXbq3J4NRmXRmwA6i7TP0MKNhO64oeP1syFJcLtY3o8zUV0CqOafddZKOaT6WOrc9ftO2oPAOkZAJRj5PJ0zoyXVW0n2bOEqtTepz6SVtPVhdLcfBxygo6L+U2ALKj+ydw4LzjAeCp0cCWXUB7V6ZhoeX94NsH6PYdsHME2ZUdiipEL5FJ07nzYzZQS+XRCTlVxRidkg4b95bYp7aFyq8/B1/f/nJHCsFMnafWQS6wqMmi7c7YIoLC1C+ouSo7BrSfzzZf69rKbJxaR3uR2lym5LVOPP727/PeDr8PsPMUK087yOn3mxGe3WjRoXGwtGQCeOylxwi6pOyAWztRlxbM45N8RaUuJ38XFSliP14PWYZh603ALpipz5Oqk4NHN81YX4+Qql6V4daa+5K3UX4GnZo1Db46zGu8zKcnML7WUtMomNkHWV9gma2wD+T9YXeFz+sNjtjYWIt/z549G6+99trN2ZkbEFZwZ41bMxo2lZcsLhyCLGeQm3uybVG7d+SX9I0IfTEF6zo3MncAAcKGLkxPjMm/yMihYBc1eaY6Gdzp3DlgGyuBnL/w0fcmGI1GPHZnNzg56YFSkMmRwJ17W1EILpBJMdUQBPTbIDMz1ZlkDKT2QQDQ5RPL/U6YSuaiyxdyp4brFRpbMgUNQzCL/llGy/RZ0X4CUjtfAsKyUyyWOLuI7Jiyku7wFILdtu/IqbL8bdQdubQAhh6Xl2WIKUhbL6DFswSQWkf6HzqEMSW6914CrppsFqcEjgAggjuVlqxEQ1ZE50amVALyZiMHfP/BBEO7xwM9zgNvZAN5G4CKfkzbJc8nIyKl0BzDmXoVVEDJQQCCyP44E3zYehKoDTkEp9pSJC8IQk3+Key4sAN9wkZZFjsYylnE4xJD1qfoIBnexDfJbN1ZxbTpwUcJCrXOvJfs/VlsULBTbC0nMjdO4WSKfvPn/Rs6XgYul2NnBLEiWKXl715Pf0m1hsVBKnVjRj/9e4Jtj47s0CCtP/TklaeJ64p4L0vvpPJTZMKco2Rwp1Kxi4tD8JWxzNcrzCYg61cy+X79uF9tXmf1quQH+U9CpaYE4OQbLNDq+AGABoDeIaDpVna3SCQlJSEwUC40uVasHQD4+fkhP99SbpOfnw8XF5ebwtoBFFBYwxpXFvUVdOAvT/77da91uLdjv8s2r8vLKlOZksn8xTKtWJUmenb9w1AK7s1GuuDvf5j6JCmSPwQ2dWc1phQaBw6cxkqmLaTw7cu+nI4hHGgBvnRHnAV0XoC+AOmHWDU3f1wZB2c7f1pD6EvIsujcWTk59DjF2W3epEO/svLz0JM0Qc1a3fRx6Uuobyw7iUZtlpoKYw2PpybHcnn2GqY+lee4+BBwaDJw+gPg/HIOMgDbTK2JZYpWisxVwEpnYIeYqspeS3H5oSeBnSNFp/oBNJs1lAKJbwFpDSpJy07w2tflysvUOqZbpfZ8gKh16kg9mBL823qT7TFW0MC56hxBTeRj1J4pDVWdI4DbjrFww1jL82c20ZtsXClTU6u8gaPPk2Xsu556q+w/gfKjQG0Gu6LEzgD8xpAV9B/MIoc2b7IKdPB+oOULIuByIHBUaYB991Pon78DAOBu744H2jwAFYDf97/FFl1mI/cr81davWzuydQ2AKR+QmCndSTgq8unBs5vIBDxOCchUv/cFs9R1ykYeT0lFkjnxolV5ONNaxRNek4YKs7KywQj8LM9sNyGhRVSJL3Hc3XsRcttrO8E/NWRWjgpMlYB20cAyQ10mQnPAJt6AUdnyMtKjwInXgeOvsh9ubhvtTynDiFyMUNNNguLSo9bbrfiLN9tyud8/0TgVx+CRCn8+lM3GfuiJaPlFH5zgR3AAprdd7KKXfke+zfATgrBxEKO3HX/fls3IZydneHi4nLxcy3BXVxcHLZs2WKxbNOmTYiLu3laQitzZ40rj/pKIP1TwKuV3IaqroAVl56db/yLzakZMOgAU0vKWfixFznQdV7CwfpKI/VzArmg0UDnRVym0gCn59GbKvZF+SXpHMEBQ8kwqlQc2E16apJUWq7n148z3y19WWUXOJzr2/sBIXfgXMIqGOoLMXpYPzg5lQNlKoI4rROwOoQWJFpnIEy0UFBWZgJkEctPUz9lrCRzBQDnvmIlarOHOEDbejCFeHoeNVleXble6XGC19osoP92mYk8/yNbhAWOoGO+FIenUis2cK/sL1aVRtsGxzCybZmraH1TkcI0ldK+RCMCUlMN9Wm7bqe42zmG5yzmGTmFVnEWiJrcmJVt9SoBoXQMANmZ0ZmWgFdtA9wmAksJhNgHkOFr+RKZrqLdQOxM3sNS3+S6AiDlUwIhn55kTgUzWwqaatl5RfJ409jyGinBjUrN+0/nKTKRVcALo4BfdgInzwHeouGrBKwAFgMMihD97lQEOlXpQG2B2KfUBPj1w7TWo2BIWYq5xi3A3i1ij9IAAmmAxyexgr79+NyGjCPrJkW/jfI9UnGa3mo2LjwHgom/ayiWi3E6i2CxvpKttby7yyzZsZkEFVK3CoAg++K5UKQK6yt4riTdH0AQchGQKQBJ5VkgZw33QRB4/tUapu1NtawQrT7P4pCifUCiKD+ouSBXOp+cTVDX+jW5P3fueuDARMB/GNB3jby/m3oy1Thgl8wG11dwn5LmyubSNi60dTnyLNP9vr25PG8ri7nc21tWWh96isfS+nW5cKAqHUhZyvtaqTmuSOHvOQQ27WfaMEx1tCuSnsPwCZx4BgwTDaqvoeTCbwDQ7VtOTP6fR1VVFVJTUy/+Oz09HceOHYOHhwdCQkIwc+ZMZGdn47vvvgMATJo0CYsWLcL06dPx8MMPY+vWrVixYgXWrl17sw7BCu6scYUhCLTACBxlWdmauYqMi/8QoO9flutf71ZfKjVTi8r0oiBQ9ySYLPU35cmsWgsec5lSfhULDqrSFItUtCFQ6yyBXLMHaTFSeoRMVdhdXO7dA9g5hqawbecQEKpUBAd2AWTkSk8C7vRWS/N8Dl9t/Azdo4EBU18GOrchkMzbQrbKKZLMzN67gLoc9nE0lAKj0uUqurSvWQkZeg8Q940MQI++QFBlrme6RKUmECw+wDRci+e4ra0DCJQEo6XxtNaRhS3KVFfpcQ489n7y4FObD5x8jeyY/23cb7/+ZI3avEFgqbRA8R/I9KDGniyYrReZWTtfoN3blv1yXaJloK2MpjwRpX6XRQcJyiQbF4CD6fpO1K9FPCp2LfmURq55m/hvpf/ZqbdYqGAfBIzOEPVMak4oarJ5j0ngLmg0i3+cGtxXyqIUQxnw2y4g3wh89Bzw5ko0irytrHINvYu6UzsfDqhpX9EHzW8g4NcPUec/wZe+QI4RyNMFItxUQ8ARNIpgss0bss9Z+P38NBW1OUzTG6tZVNH8KVZrBo2iV5y+lPeiVFFtNgK/+hJYjUiVr5NHe6aOlV13NPYs1DHXW4KU5lN5fA0ZwL4bee9Jtixhd9PX0c6HTPFKZ+q5op4gsM9cRfYt63c+8y4tAP+hnLQ4i/d/xVl6q9l6WXpunvkITFop2WsVwSzAjIAE7nx7A5kr5QmTFPUVIvBTLiunYbCuQVFJ4R5OQP0GyeCu4ixw+j3ec0pwd/Ax6k27/yS/U0qPA3vvI/PaU3HfHHmeQNenL9BHZOttXNhOzM7n2mtpbVxY7fsfiMOHD6Nv374X/z1t2jQAwIQJE/DNN98gNzcXGRlydiY8PBxr167Fs88+i4ULFyIoKAhffPHFTbNBAazgzhpXGioV2YD27wI6O3m5sZovai+FX5W5HlgTQ3fyLkuvv91Ew/0cuFN0pg+Tl1/4iTqZon20pADIBOiLOVg5hpD56bQYsPGgtYJLDAXJbd4AKtOYdlRpmHJTqSg+3yi+rGsygdgX+HeP9gR3x18im2HjxHMQ8TBTjOc+Azp9DACYM3cuPh1rhkYNwPQh8PsmGoXWZBB0hNxD0JP9B1OF5tcJwqrSCTA8OlLnZe9PEOXVTT5m/yGsqj02g+AqYAjBZ4cPZQBYkSICdzea60pWDLX5BJJ2Pqw+liL1Mw6gLV+W23/ZOMntrNq/Q1NZpzAK9l1bNG5rpOy84t4WGHyIg3TCVALVUelXxlo0FXmbmcr0iuM5du/Aa5W7iWO52UhWrv08aoecI1jMUHEG8IqndQogp/BsPS0nKYP28TlQLrPzkRmuS4WjG/DJB8D5M8BTC+mBmLeJ+9PsAaa4T88jm5n2FQFj0Ai2zwNYverSnJ0JcjiJ+rkSeCO3GllOzeEIAL1+v7pzVbSfz69KS2uMwOG8br1+p1fk2hgCrD4i+6DWkmGtzaEWUAJ3oXcDYfdZnhPJbFsQCILq8nnPSefqzCJ6/jV7hCDGfyAnVX9EEKSH3sXUuXsHgnVjNVB1ga21qs/LHnHePfg8HJlGLVyfDUCAyL5WptAexqNjEx5qZlZ7SqHWcgIkmC3tTqKeoKyitoATIeld1vkTIP1HsocSc+fdkzKAslO8RpLfYMidBHdpXwCxoibNIQiImdb4vtHYk7lVvjNr83hsDdtQFuwgU1+8j/erxk62LrEPBm5LkE2Oj05n8UuLF+TCG30x3w92vrKFDECQrba9MR6ht2j06dMHQkM/TEVIxW8Nv3P06NHruFdXF1ZwZ41/Fy2ep5eWsg1O8SG+qA1llma9Gas4ePkP/vvBUBkmA9OA5npLH6j8HUwpKZuy1xWIeh6Bmigpyk+JJf1u8rKKs8DaFgBUwJ21BBin3pA7IcTOBNq1BvY/BBQdEHtJQjT8NVB3JVmQVJyRt9tyFnDiVf7dWC3bIjgEcnAUq8nS0tLwzTffooMJuH3MWPjrs7ntnHUcVO39yUJ4dSVbZB/AKliNLZDyGbVUkrFxU7YvXT+jqD5/B895bT5Td4ZS2WvPqwtf7Oc+Z/Wo1oEDcuZKnjOAg7PEfLi1EU1wFYNlXT6rMx1DOThJKVSpFVXDqDjLcy5VWDoGc5susWTcdo4mWOz+E323MlcB0U/J7v+GcjJcUJNtsvfnb+duAM6KqdCifbS76L2OeqnMFbLNR9lRMkOJc3k/urVlpd+Bh4D0PjzGDh+wAtapGcFF0R7RtsZFHhzTvgNgFjtfiKxuZSrZSIdg2d4ifwcnFy27AkPfASoS2cnh9Hv8XZ+efGZy/xKrYjuQMTPpmUqtyWRKz6U59WuBwyHUZGNxURHK69Lww/Hv8XjHiZeXRdTmUifpHM3fs/NmRwWvHmxtVXKIXUm6i9oyF1F2oTTaBYAB2xubBku/m7dF7PDQS640rj4P/NGMYGF8LdOvtdkEO3mb2TC+MBg49TaZULe2PHemWmDbILF7zRwuL0sCvDPJuDqG87sREzlRkGQZRgWb5hxJ6yRDCZC+DAi/h8s7fsTWaFXpBGLSO8VvEHB4MlOoElBWqYF9D3C/labBgpFgzbWVnFq38+Jx1pdR3ypF4FCRhVcUILi1BDrMb3yd+jahZ/PsDMSv5Psz8V2gpag1DB5LIObejs+Lezt6WKq0QG0mZSBSdXfxITKCUhtCgHKaQ0/y2VGCu30TODlVVoFXZ3Bya+9PsJu3mbKD4kOc5Hp0kN8JggBa51gl/TczrODOGv8+1BpArXjhe3QCBu4mIFGpgczfCIzOL6dvV7evOcs9+hxNdjsvlv2x9j/Mwbz9fNmAuOocsDaWDNUdxfLvnPuClgTt35fBndlA9kdtYwnu7Pw4u3UMIUjM30ZrFSlU4AvbOZoDNCBrdDJ+4WBr4y6azao44z34OFMiLZ6XU1cnXuXLdVgiByCNHdkZlQaImsSPIADZ61Dyx2RoVCaszhmEJ0f8wgFEpZENbZVAVkqzSWyJuZYDiU8feR1jLasd/QbwmmgdqSuLnSkzKZWiLmzbYHpgOQYzpViTJaerM1awGtUhiO2hlCxa1OPyCx8gYNwygOCv99q/73FckwVs6c/z2fULIETUiWnt2RWh8iyBRU0WJww1GbJhbnUGtYV2vmRMAKCQhQZwiuIgWnoEaD6N1cmCiam7Cz9wHY/OtKVwa0f2MetXLg9/CDDnih51v/FTdoyDm86dDNuJl1kdWZkigv45NEw21fAa2DhzQD/2Iu/f0Lt5fMUHRdbkEEGJZ2d+L3cPkO4ERGUDh5/mQO/engx4zhpg7z3Uk7Z6maAn/UcW8Pj2A/SFUJWdwqIW9yA4Kw0tU56AkD0XqrB7OLEo2MHOBJ5dqZXU2ou9fsXqVvtAYOQ5ThLav08QZaziJEmK8z8Q+DV/itYtUhu2YzM4QSpNIPs4Jp+GtuWJBDc56yhF0BdxouQSC0DFe6i+jBOl8lNAh4XUb3l0pH4t9y8e/9BjnBhWnydzZ+cLnH4fqC8lC+ffnxpMfRGZxqDbqd/r+StbGZ54lYy9ZyeCYXM9r3VlqgzufHsDzs05manOUDxnZoIkVYNh0SHEEqwB1NrFTGvMCHZaxPvOMURe5t4WGJnS9PMgCJYTQIBFMmUneA+5tyVwLTkCZCznpKv5FLGn64sEbBk/k5V3b0fgddsR9lZW6lzbvMHzrOwIonUkqNM1qBqWCmCURWq1ebwvHUJYKFSXx5ZlZxeLQHCJnF6uTCXr6xAMjDovb+PsEj6foffI4N9Yy2PQuVtmHazxr8MK7qxx7UOjY7pEirSv+UIIGCp6cvUjG5S1mkzFKrFyMX452Yr6CqYbpNA6ckBp2LLLs7OlJgjgi6rtHH5HqfuLeZbaI4cQsgI7RhAItp9PgKOx5aDU9m1g21ACi6CRTNN0XsJUVPQUmbWor+Qg4BKtmM0LQPIHfFmH3i1boaR+yZRj+P0c8M31qNs1AZ18irBoAtD2wee43pV6wQEclFu+xApdKTJ/ZWcK755MTUshnQOtPdPOh6cQSEov78iJlp08bFw5QDZ7SLZUuVTU5ZItqFc1DewMpRyYfPvJPlxmPQeQnPVMY9n78vd8ehNABY0BivaSFYh5DggZT1B7YCKBVuelZDL0JcDRaTzf1Re4nmtLDnL+AwgMHMN5PwpmDsYSy6TWEjiaxOscOIw+dEX7ybJkrQbavMX7wrUl4NqGYECloSYtf7vYH9WO93RNFo8ncxW37xRBoLClL6+RrRegthe7ebQGZu0FcquAee5AMy+ymLcd4XfXbOF6mb/SNqXHcgBSVaaKqcraHHTv8gbycpYBEKCqySCAa/UKJ0PGSiB/C1tJNX+KQvuTb/Ja1eUDf0ZT12fjzmfIuTkrTrcPB3r/SRa06pxoiLyDz4bWmc+xxp7PEECQlbmS2wgYSSbZs6tY5JPI8zXqgqx/dG/HSVblWaD1q2Twde68NrkbWR1bksD7Kv4XVn3W5QOOzYDqNFHH+RZ7otbmkJXN28iJXO5GMndZf1Au4RjKCt+8TTz/+x9iZXb798l01+bwnvwjipPLvn+xoMjOm51Vctezyr2XOAmoKwS2DuL17v2HzLylfk4mK3S8zIDpSzj5U2kI+DJ/JWCz9eZ7y6sbtXhb+vFeGZ4kPzPp3/O31XbypDX0ThZ1aB0t07NSv+TKVD4DjqHUB/bbRgPxvfcB3X8QrW0UFeAA2cOeqxo/s3038f5RK6pJHUP57lJpCbyN1QRvLs05KXBQgFxDKZ+3hmnNvM0Egh4dZXBXkwlsH8p30bjyxvtijX8cVnBnjesffgP5Eg+7X9anGMqZTsxZzwfe3o/L271DwfTR55gSinmWs+BxpY2323wqP8rQOlj6b5UeJ4OgtgN6/CgvD7uHL6+gkTJjJaXWGqZGmhKkt3iO+6Z0aBfMQMzzTDspG3fXZBBIilWDSz79Aqd+K8LC+4FH+wFoqwCnad8CSe+ypY9kPgywz6fOjS97iVFsqGWsL+cyZbGBIFCv5zeI4C76SV6PyhRLkXnq56ywcwggCzAsyVJDVZnKWXrr2ZbedO7taBFiruegX50hsxbmeuC3AA7mkgDf3hdoO5etjgQj8HuwbHY8YDu/V54M7BhKbVvsDLl6V+MggxGJPfTsCKzvwrSzZxcyA+e+YtpVAqbNn2ncv9h/kFwZK0Xko9SOBY3mQHnoCQK0wJEc7Mx6IGY6z/+pt2QWdHUoAWnGcjJV3t15jh3DOHC7teYAKzGgfRYDob8DFfmA33SgWwNbkOGned32P8hzVHKYE5bQu8F0lxbQF8HFzhvz3e/BncU/ItpWBZvY6bz/i/ZLF5/a0foyTgTC7iX7VZXOezLpPTLJAM/1uS/5HX0hLhYb2AcALi05aZLuaY0Dr1fgCN5vPn3JjlWnAp0WcLJVfpasWtZvPI99xKrUbl8BfzanVUvYPXwvOAQQ7CR/wCbyMIsTObPoB+nI+/bYi3yG7ANFttSFzCkgV6aXHiXwEIy8/2JfkLWwO0fz2Mx66kIB+g5WpfIc6dzl91NlClnXOoU1i7GaQFEyAc/8nSxkyTF2FHFrTUnHtkE8b9L90Wkx78ncv0RWXcfjtXHje6E2hxMg6X61D+CfZz7kvejRjhOMHj8zRbyph+zZF/kowWDGz3w3OIZy4qKxBQq2cnJztaHWNG7fZu9rmdKVoqnOPB4d2KpMujZSNJvA//NUMHSCmYxtw1S/Nf51WMGdNa5/KM1npdC5cpYf+ZhY3Wrkcsdg6tdy1nKmF6sY+IoOipWnHS7dIqiugAOjsqtB5q8ckKUuBIBlyvafhkots3MA96nNa5brmAxMqQEw+vTHlCeewNKlS2GjAe4ZFIa4tqHQSC9zgCCq4jRZAikEAdg1hi9LZZVixiqyooHDmBKJfpKMRFkiBfq2nmS/do6mVmbUBbJrLlGWHQVKElilp3UERp5nek15XACQ8CzTMnV5tHmoyeX2NToxbfg9tToBt1GAb9Jz4HJrw33J+p1sWF0+e89GPgIceAwQ6gnIivcBQaJFjFMzgjXnaLn9UckRCvABiuql8OjIRumScDxnHT8eHeWq7sqUptP6ad8SDJSdYCqw0xKyPm4tyVKVneI9k/4DIBiA7su5/3+14/f9h9Lzy2zg4OTejgUCpUeBLb1pvzFSTPGb6lhE4NKcA/wPmwCdLRCguA7KUKmArl+R7Q65k+c98V0yg34D2CHCtx9esM2Egw5QQ4CQ8AxU1ZmWBSyFO/mJfIzaurITYiVsAZk1rTihqU5npXPIWIKXyMdoWJvxE4G+awtabrR5k9q8wl0yaOrzBwshypPEKuJmgGMggR1AMC7Fydf5W05RZAEzfwWg5vPu1oZg2CkcqM4Cjr1EJqz1m5ywtBAZ7pRPmcrTOLJ9mEotsugt+F5xCAFaTIMFmAeotWvzpgyeAP7WgF2NixVavEAwLfVWBsj+xX0vb/fc57zXIp9kgY53T04QjVVkpILGsOhIpeIzWnWO967E7rlEA12/ptbzwESZuW07hyxyfTnlAR7t+Nw6BPN5aJgi9orj7yqrdF2aA3E/XHl3l2sZaq08WVdG0ChLw22AllrScVvjmoYV3P3Hw2w2Y968efjss8+QmZkJX19fPP7445g1a9aN24mGLwJbb6DL5xzQlCDj1Ot8mXb4gKwZIJqIqvgCPfEaiwxaTJdnlG5taPrrN9AyhXk9Q6pcAwh+/AfClLUOr85+DUu/S4RKpcKbb89Fj+enQ6VSAcdf5ou/xfNydZ6xigJmhyAyT25tyAjmbaH/XPAYtlXKWcvzZTZxth12L01sTbUEI2XHyHS4NKc1imdXsiUlRwgENQ4A1ARDdv6WImhTPZkOtZYMaU0G0Go221SVnQA6fMSKzqpzYhsigYP7sRepk2r5MgsaDj7OymGpoEFfyH3o8inZEhtnMotS5G4goDEb5HPp0YFsTeEeGchJofx3s4ep+VT2JdYX8bjsfAh2BYHAIvVT7otKy8lF1mpWMgNkVSTtkWsrnv+KM8Cp2VzmFUeW2b0t07jnf+S1a/4Ur5utFyt0qy8A7d4TbUemsCCj65eAazSgEQj47Hw46JlNvN+3DWZhgsaO4M5Ux8H9rKgRTf+GnzH5cCpPoIuHGdCpwWcmYAiZanMdwVvIOOrAYp7lvlUk0djZpyfTffXlLCRQa+XCnNgZrIyuSmOaDaAuzCuOz1LDNl/t3uH+S+2oJGBvrAb6b5XXk4Cebx+ytxS7yv8/cDcZ+w2dOFE7/R5b6DV/Gmj7Jq/dYbFQJ+QOscuJB5D0PnD8RRZYdPlUZhm3D+M7ousXMqNcdIDbdGvL+1eqji3cy/NsrKVezbsHryPAiWXyfDJj7d/jMv/BLNxJXUIrF68unMx1+ZwdQKrTgV5i2jN6MlnUyrMyCJOqxtW2lgyhvS9TvqYa6kSl8GgPjExv3Fmj/btoFLYeQPi9jZdfqxAETg4E0+V7aFvjpoUV3F3PkJzyNQ5yistkIFuh0soNqy3WtZcHWHO9mM7TyGDhcuv+nZi9iZg5cyY+//xzLFiwAPHx8cjNzUVycvJVb+eahq2HpQZMCp0H0zW+fTnQZv5K0HLoSc6yvbrxRd7Qp05KwVzvMBmoEUr/nlVq9v4AgETbB3H7jE1IOZeIoR3t8f7MuxA7dob8vbxNTAGF3UuQ5RBA1jJlCVM9LWcCg/dx3S39WAziHM3BzTGYBRuHJ5MxCRrFFJupjgAgdz0Hm/LTbFQvpcoA4PgsACoCUK/eZObO/0gGKm8rcO5TVllqHDm7jnySFXbVGfz+2UXAETEtfnseUzH2fhxoBTO1OZt6cEBTaQgMA4dzG8dnESAoB6ayk0y7HX9JrtQ11dHUGOAAKhgub5MSMlYu0gAI5lI+AaKmEERt6MJBuyaXwC5gKNNEyfMJ7PwGUcNl48p9zdtI1kgJ7FQaMjiGYnrhaZ3EanEVUJxA4OgcQ3Pkoj0EPjtH87sae2DPONrUhD9AwJeiAQ6YgHsBDD5AUGOu4+fCMmr9OnzA94iphmDA1ovsVtRkmE7Ph05twswSHV4ePB2Onm0IQBKmEsR1+5K/7RhOMO3QhmDHJZrvDN8+QMePG3cxGLSfjKRyUuTXv2mPwZBxlv/Wucst4CpTeQ1sXMlm+fSiBlMwMuV7dhFg48iJR+oXTN/120LGtPggULCN16Htm/yOayxZxI4LZWmBsVqe6FVfIPhwCuNzJBVZ1ZcDUU8yhXziFU4WDj3B+73PGnZH0RfLhTN9N/IePjyZhS4FO2RQu+du6m6dIlksU18OlJ7gZEvrxMmJ5LdXksD9avUaoFYzxSqFcyTvHUOJpdWKdM8rQ2N3Y1ssXi6SP2BHlqDRsrWUNW6psIK76xkrxAqoMQUyu3D6fVbeRUxkz0YpVvnwxT0yXX6Azy6mC3roPZZ6sdVhZCOGnmIKCSCNL1lFXGFUVlZi4cKFWLRoESZMmAAAiIiIQHx8/N988yZF9+/JDqjUTI2VnaDupy6fL8fAEazOcgxl1ZxLDPVSykq06xlqG4IJQwlw/iegxTSsXr0a9913H6qqqjCoaxDWTs0CDN8BVa/IJrgxzxFEKV/6juHUHto2YKkCR1L87hzJGbN7W6bDQsbRC02tI5itzuRgYKoli5G3md/XFzL1VZfPwaf0CGA0ADYOZKuM1UyvVqfLv6nSMB14/CX+u+vXBBxnPpbX2XMnzVMBsj8pn5Cp0NgBEIC4bwGoWGCgdaEhs/8QppLXdyF4snXnwBwwnKlpwURt24Xloj/ffGDnOB5v+ASCEZ/e/O6hJxR+fe9RK3d8luhlKB5zr9XUXxbuIWDtvIQ6Q8cQPj+CEXBtzX1yEu079EXUANZmkQFVqQnQjkxjUYWxiscV9xOtMfZvYkquJpO/odaSLRPqxfMvMjTFh8iq1XkDbxcC9QCiAQS9zXfDsRmyZqmukPout7ZMXwsmsrjnPgeCb4fK3h9/7XsZcz2qUbJ1MBxjnmClOkDbl/XdeDwZP3GZrQ9TtSlLCGQiHyXjWJtL25byU7wXffvI1zftOzKZnnG8b+28eN7zt7G1nEOQLEnIXkOrntIEpqbtfAkGtC7sGKGxB8bXEGAW7gHymrP3bm0BWVCNLZ/d8HuZ+s36neTe2SWc/AzcTb3d/ocoQWjxAgsLoh4HMlfz/ejVnZOarl/yup6eR6bJtTUr5yMeJXCVKjVrsmlYrXEkU2vjzmenrpATZ507waStL0Fd3hbeV4P2USYC8B46/hLv3z5/yudu93iy2wN28bmr2cDJ/f4JZEE7LBANqN1Z8VubS72txIhVpHBC5hRuCaLLTvL+dmrWuBf39Q6f3ny21bob+7vWuOKwgrv/cJw+fRp6vR79+zcxE79VwlDKKr/iA8DAXbLWLvQuamciH2M6U+vMl7U2lMzHqTe53pgCGdxVZ4raFLdrs28lCUxddfyY7JdKxUo8YxUE3wGY+/Yb+GnpbNTrgf79emPZilVA4iPc7/oKDij6YjJwKjVf6uVJHHydI9hH16QH8ndyELJxZsWuVPGZ+A6Q+DbPQfwKLjObCAwEM/VIInuI8iSKrl1b8zwCNMjdI4r0278LbNxJuwzphW0fyI4Xvv1pByOFewcg4kGC6d3jCXwkMFFfRYa1JpODas/fyLTY+RIMGqv48exGQb3ZSIApiGllG1fajLg0J5umc+O1l+waqs6TVTn1Fpmt/tuYxitPlFORBx9nalZKddn6EgyUnqK4/eBE7lvyhxS6t3mLA2R1GpD+NXBmPlPU8T+T+ZS8DAGChposFqnYB7E601gJ7Lub/6914b1orCQ4MJnZ+zj0bnrdAYBdIFCXTaY0IBYYUQiU2QP9enG7jmEE77Y+1Ncdf5HtvQYfpu9fzl9kQ1Np1aJuNwcu57cCJX/Coz6PAGrALmr/yhOBkgP8ADy/fn3JdktRV8T07I4Rck9kOx+CnJjnaLxdfFgGqB0/JgDL2cBCAoDsXotprEbd/6Ccgq/NIyPn2lKsntWSjf0zms+pSs1n3CmC94XGUU67+vYH+m8mGNx7L//PJKZ5ffvy+Ss7yYmFZzey206hBOXlp4B1LVn5Gzic90LxIQIqtzZkFQ3lLJY69BTwexCrkqUWbYV7yTo7hrOlncqG6dLtw9gtJupJAk2XFpyI/NWO92izh+VuLLvHc4LjFM5nqXg/pREA7xFTnZguf4bX4/wyThD1RQSstfnAuta8Vw2l1PSFjKOMI/07sRtPFtBnHavO/2rPlLKxnOe8/xb2ek77SuzS4cF0u0dHekCaDXyPOjVjAdK5L/nxjier7BjC52brQD6n8StkkqIqjfujlD8AwJ57eY06LZZT4zkbuA9e3WQ5DUALIEMpgeytwkj+PworuLuecaeoL1GmNVq8wIe5oZfS2AJxXYXGLHoyZ9UNxb6Sd5ByXWWroysMe3v7v1/pRofJQLG31FpLY08/O2MlX85SL9GWMy2rYpUhmAj4arIs9VjHZwEXfqTHVvOnFOsLZJoyfwVazeLAAVCXtu8BCrSVFbR77xfTPXq+nDy78oW5MQ6w90fNgJN46dGRmNp6Laa9BdjZAKYOd0Dj6UmwU3mWHTzU9vSrcwyn8P7oDOD89xzUIx9jGkpfSHG+FCHjmbYFCMKMVdRzSaFSAaH3EgAq75sLywGogKjHFCdK1Dt5duOA6Cr6fUWJA3/o3fz9gl3UPgWPo+3FiZlA7zWsCm3+FNPQYfdzANjUg78rFch4dgNsxdSZtJ9qWw4UjsE897beHOhD7yGwU6mosQoey3SaSU8xuaGUbHfBLlZTA8C5bziAAnI/0/IzTPu5tuY9oC8kY7bvLmBUBhC/ikArUwSsaV/yvgq9i6w6QCuOnaOpMQsYRtBVfppssbGKXnehd3EArxRlDG4dgOhJBJbrOwAwsyDIWCvqJMdxoA8dz8INtQ1B8EN17MlalQaURREIlJ3g9QgaRaCitScrlLeRhRaVqayi1RcD6zuhs2cchiXaYaZrHdp6BMP52ExxIqADTs/nPkr2Qr79RVPuM2QHk94WTcLr+P86T16P+v3s01q0j9vRuIjyEoHguiaD19IpkgUDWX/SigcQO7ms4nOxvgOvgWtLsTgmQfSSFAg2XWLFDidmMnYVyXz+JY2cYxj3uSoVgLf83mv7DiuDz30mP+f+Q4C76ghISo7IE5XYGZQa5K6Xv69z5f5J9iIWpruCfBzSuwiQ7T08OgERD/Hv1eIyja2cAgf4PECgzUv0ZN6fqV/yWghggZP0m8YapnbDHqAG0CWa6+sLAWjIVEt6RkMJ7xvHZmQhbVzFfsDn5N+WOqzU5YoehL4EuBGPcOJXKhYxnHiZ0o+wuym3KNrHP0+/z9Z8YXeToRaMMmAHmK7O22RZnAIwLV1fTp2pFFWp9M4UzJbgLvMXvhNaTIM1rn1Ywd31jKa0QRodgCao7KbWVbZpupJ1rzKioqJgb2+PLVu2YOLEJjRuNzpy/gL23EPhsCTC1thRs2QfwJfQlYS9Pxm0hlGbxReMZK0BUCeTMIWsXnW6ZWrbVMcXo6mO3yvcTb2QoZTC9ZC7CKK84kTxfy1M+nJMHt8By9afwdT3ARutFoARmpTFBHKxL8igy1zLP53C+JK3ceFEQF9ArVX4AxyAnJpxsA0cDtnvDBws28wh8yfFhZ8JEL17WnYBUesACOwOIZkke8ezos41loCx/2amnJQpno0P0nMOIGOmtiV7JWlIY2fwA3AQKD8lD6h+AwnsTAa+8KUBx6znIFtXSMF4XR6Xn/mAINK9A3twnv2Yg1ddnlzokPkLBzeJpTv/LSsvq1J4rgwlAIwcLEPvIoA8PZ8WIBpHYMdIDoZecWRjdB5AzkbAuBIIf5DXoC6PVa9pX/J8+Q6g9sshWNa9Fe0lSKnJ4n45BAOmSl6n7D9Z8OLTHzgxS+xooqcRb9vlZKZSlwJRT1Gb1Xo27/OtIoPucwd7OEc8LBt1O0cRENm48pwceNji1taZDZgS3gbxdQeRU1cM57pMav66fcvUrAS26ysIHINGkuGVrpW+hIbEK93IUvrfRvZQZSezU949RWuaWIJjyWg64iFaqiQvBHu2mnl+g0eROZKKVlq8wGtekkBNokpFhrbXr0DKUt6XORv5HEZMBHx6yOfWJZosUbs58kHXZgOGIlqESBYmdQUsvHJrA/TbJK+b9i0Z4F6/kw0F+Bwff5nH03+zvO755Uxb9/6T5wHg/XT0BQLOOyrkQq/MX4HczdRgBorV3mYjffhyN1KjF07JC3I3MtXd9i163SmNjtu9SwNqW0+5YMJcDww9wb8r332xL5IhtPeX2TGzkelqk57blUBj5OM8hsoUAALPi1pLtq/yHMGc5EEYejf39+xHfJ9JvqI9lokFW4pCjoBhvA+dmlkWkHVcyHvCTlGl69OLbK+yZzRA2YmxsjFAtMY1iZsK7ubOnYtff/0VycnJsLe3R/fu3fHuu++ieXO5lL+urg7PPfccli9fDr1ej8GDB2PJkiXw9ZVvnoyMDDzxxBPYtm0bnJycMGHCBMydOxdarXx427dvx7Rp05CYmIjg4GC8/PLLePDBB2/k4d5yYWdnhxkzZmD69OnQ6XTo0aMHCgsLkZiYiEceeeT6/rihnLM811gZbEjtlSrOWr4wop+81FauLvpv5QstazWZh77rOfss2EmQEf2UbL58/ie+dPpuBFQ6Or6XJ1Jj03EhhfiFe0QTXn8g6T1U2LaFQ+1xfH13MQ6fdkNxqw/QLH44Ux3HZ4rCajAFdY8AbIrnDL7N21zeeRFtY9a1JosjmAjQ+m1hirK+0rJ92snZHLBcomVrE+eopoF+t68IXOwUlckOAY0r6pTAzmTgwKq2Z/oq6nG+tGuyyVz69mO6N3EOUyu+fdgerfoCwZfaBtjYQwSHWuCeeqD6HL0HD4oMYosZQKvXeU3KRDah9LDMLEjAD+D5l1z3XVsShNh6s2oYoB7MpxfF+Sde5bq2Xiz0UGnI8O0R027NHgDuNnBQ3HYbkL+ZoKzb1wRyhjI5lWgoJgNZkiCnJg1lHIhNVWQt6wqBvPW8p4v2cSBs8yaQUAZAzd/P20wGUEqrZ6wEUhaxyCXuW0CvA36qB079ArzvyZR4eRKZKwmct3mT7c88OpFFMtdTqhAzDe2qC7F670Gcr6/BpKBI2Nac570ZMZHXLOdPbuPCT0ybtXyZx1x2nPt++GnqvHTeTLcWOgNhRgI7l+YEiNsGUatoNuDiROPo85RBBI/hMocQAsLfAsXKUBW/K5h4fgDAzpOTJaGeaTtjDc9T8X76wXnHizY49jz2lE/IaLZ6hcegsWNVdeYqMpwSuKsvF4s33Czbe+VvZSrTqZkM7ozV1B2qbcicSlG4k9uw81UANj3XBWhKLF3Dwr00VrZxoj0NwIlg1u/8e20eAYyNE++rVBHEKoEdwJRvQ9sStU3TE1rHkMbfV2stjeOlcI7kRzINlkLqe6vMYLjG8BM82nLdhsUyALXeLs2BnaN4bkekEmg2m9DEuq2bPg5lpxtrXPO4qeBux44dmDx5Mjp37gyj0YiXXnoJgwYNQlJSEhwdyU49++yzWLt2LVauXAlXV1c89dRTGDNmDPbs2QMAMJlMGDZsGPz8/LB3717k5ubigQcegI2NDebM4SwvPT0dw4YNw6RJk/Djjz9eZKr8/f0xePDgm3b8t0K88sor0Gq1ePXVV5GTkwN/f39MmjTp+v/w0RcoCI96ku3HAL54Bx/i7PFSPnb/NhxDCZRqcwgoQsYR0NgHcrBO/YxppgMTOfAMOw381ZaDmcaR4uawTkyHXVjGQSv4dhgT58NFZUBWGaBS2+Cv1T8jqKVo7xE0ikBR8sySWK+BuzkQKNNBF1aS1XBrLfuV1eWzohDgQNdVZLG848niahUFI+7tgTtrGvcZVXqfXWlodOwaovQHBJjeTv+WeqyqVJ7H+goWLLi34yd/O4snLoaRdhKxLwM7bpOPRecmuvcf4fV3CGVari5XPFd2QO/fWdm4WRzAtY7UV5n0wK++MuAqPQrkriUbaedPcKcvAo1/VWR+3NqScapMJSDL3yb6o3kwtVedIfZh/ZJdKTot5rGY65iicmzGiuC6fIJrx2YE5bW53N4hUS9mKKEx9PBkHo9ULWvrSZZG58kJBkAAaeMMDE8Bng8HSgTgYDHQaztbTLV8kSnPI88SEDWfAgw5xO9eWMEJkXc8/MLD8PmJLVifshYXwgfjg7s+IgD0H0gtZP5WAkyX5jzvnmLl8IGJZMFyNzJlKBnfGisJCFu/xvRnwS6CrYRnyDjaePB5SvuC7KRknuwczfNRmyOn4v0HE2gWbOf92v1Hptx1HkzZpX1Ff7ewe5kidwqTmczR2dwHrTNtds5+RFPmkDtl4PBnNFnVPmtYla2xIwOXu54TsaDRPC7POGottQ5c1mo2gbd03e0DyErZ+rBowKTnfaq247qA5fPqNxCAimnSI88RUKrUZKVqMlksIVX0+vTm8qvpRPNvwlRHUK9zb2yfci1CreXzZarjcySBW2vcEnFTwd369est/v3NN9/Ax8cHCQkJ6NWrF8rLy/Hll19i2bJl6NePM4+vv/4aLVq0wP79+9GtWzds3LgRSUlJ2Lx5M3x9fdGuXTu8+eabmDFjBl577TXodDosXboU4eHhmD+fM7kWLVpg9+7dWLBgwX8e3KnVasyaNev6+doJAqt+M39h6kJKAQTfzoHKqQFVLzVbvxZRX0nWrPiQXG2s1jINZq5nhwKdG/VtANNKp96k7ketBezDOBDa+XIGHnAbcOQZ4NDj1Am1fRsm1zaY+eo86E8YkFUCCIEj8O13P8LZWcGAuTTngKbUSJaf5qxXMMtGtwA9yMpP8kUpgUCX5gRt1efJlkkR8wy1eymL5X6y1wMUN5QB2PkwZRM8lukpfQlf7mtbAoMPcnBzDOMgX50harlUNLDNFbWLGif2EU2cQysJgBq53r+zUETqg+rVhUwVIHukucSK7KSak4O0r8gwCgLF3KZaMnCHnuR3do8jG+Xbi4O6oZgsTtJcAsqL1jminswpkmycSk1WsCqFf8Y8R/ChLyI7efo9gjUbF35cmpONyN9O/VOrVzioOgQB/XcBNvZMi6m0tPeAib8TMIQ/7x0CfPwGkPkTEFNtmdoS6rlNGxfei5I3ZPJ8MkIRjwGdPsbUrlNRmbUWH5QthvDLj1B1mMffEEys4jw8hayjsYJgafhpwKMLkP0bn4XopykLqM4EYCTD3no2LXhM1fL+nP+Bf96eQ21b2REyfF2/AYJHkp2tPANUXSAj1fUr3itt54hdIc5xuwBBsFlPkCYxZTU5YvW4QIZZWveAKJvQOLAIBGBBSGWKeG/6y1W7CdM4CbH3o7Qj+HYCkc2iG0DoXfK6J2azklqabAYO4/KfbHjuRmfK6577ipOt4DHs/Wvjwr6/UHPS1/49FkMBLPjI2C+aV/eTGbTS42JXjUjZEkvZLvHvQrlubT7T92aD/LsAsGsci3a6fCq/46SoTOU7yDlSlqlUZ9Jj0VgFjM64sv3osID3jUuLv13VGjc21H+/yo2L8vJyAICHB2cZCQkJqK+vx4ABAy6uExMTg5CQEOzbtw8AsG/fPrRu3doiTTt48GBUVFQgMTHx4jrKbUjrSNtoGHq9HhUVFRc/lZWV1+4g/2uhUrFKs2CHnKoAKHwennR9xbSmOvrOXVjGAUiKyMcocG5YNevZCYicxHSkqZYz7L330Nn+rjqCK0MJ/682GzWhT2HSjMWIKH4fWSVAq0Ev4pdPX4Rz6QbL7e69H1gdQi2cFLZeHJCq0ii4lyJiIhD3nexiD3A/bzsC3FEiD2iAaMVRTRZJCeqSF3LAVHa5uJbR/j2mOr26cYBS2VCHVnmGA8rO24E/wlk44hxNM+WY55luAwBoOeA4RzAlKIVXHNk9375iWlfHdfY+AJQlyROD2lzgZwdgSx+gw/tkRMuOM0VaX06gkPkL07vGCjKL+VtYHFN6lCytBFg9OhH0aBwJdoLHMC3V/Ttqss59Tq+4Pn8RQNcVAL/60Cj6jjJgyEFuJ+sPtvPy7MKij54rRd818LfSvwaOTmfFsEoF9NvK3qn+Q6g1Pb+cQGD0BGDafgLLXaPl9nY+vamJKj3K35FCGlTPfQbUl2Ngs4EY4s53oaq+jN0cfnFlS7ut/VgEYawgcPTswu1l/wZAzZRspw+psfIfyO06RQC77mAVcMePKVGwD6TO0SuO5yNg8MXWerDzAqCS7w3BQEsShwAySG5tWdR0RPHcRz5KAHXydd7TgKgB3caiidIT8rqdlwLjKlmkIIWNC6uD+260fA6CRpIl9R8iLxPMPI9BoywnWzbOnJAoAbW5XtQqCpbrlp3geZP0lt5xlHSoNASTJsXznLuJEoSUT2ERWwcA61qJhSVinPuCYHL3eDKtOevJzO4YBWzqRUueQ09RF3n8JeDwVD7nxkoWRiTPB84upX6xrpCTCo0977mN3fncSJH0Ln39pGIkgO+ZitNkHOurcEXh3Z3P35WCUmvcsLhlCirMZjOeeeYZ9OjRA61asWovLy8POp0Obm5uFuv6+voiLy/v4jpKYCf9v/R/l1unoqICtbW1japG586di9dffx3WuEYhVT4G3y4vu9YvA30J0zz6Irk7hZ03NV0OgXL/2IZRfYGp2MjHOVB1+YQsVHUmWyyd+4Iv/ODRwICdF13sS8vL8fPMVogWMvF4f2Bs/0h43f408Js/B2b73dSl2LiwQlKltWwbZOvFwcs5ytKguqE2pmEoU0Jh95DtqFdMPgQzu3Toi0ULErGKsK4IgNmyyOJqovQkcGYh2QHHUAIdjS2tISQdnMqWae4jz8jfq0hke6X4lUDy+zwPalvg6DTAuRkQPZUWEPUVtPzwjqdVy13iALm+E7VuoePl8+QUARRm8RgLdjOVG9Wa59cxnANWwQ6yiw7BTIXp3FmgUZXGFGTcD2RijZVkMHLWcLvdvqFPW9p38mBo50vt37EXuT3pPOsLOegKRt5jhXvYTcRUy+4X0c/SCFpK90JgatS9A9lD11j6r53/gdrBpDncv/AH+WcNgJXvAne9SuCXvQbU7ynugSoRHHh0AU68AlXxIbSNGA3kfYpSswqu3vFQlxwiIJFajbV+jc+F1o59ZgOGUifX6WOmXp3CmfaMeoITpD138n7tuYqAYdftPFcD94jtANtyGzpXAtikudSJ9l3PtKCyhZeNs1is0YCxLz3G9LUEiAEykjtHkrWWWlSpNcDh53g+W7/GFK5Gx2etPJnPrTQJ8O1j6dUHkLntsazx/d3ieX6UodISwJtq5Ylg/naCJZ27Za/VTh8T9JpqLAsPnMJpGeTRkWybvoj3jdT5QuvIyVj2nyL7bASg4v22/Tb+v8aRbKqkc6wvBzJ/42QqYCj7ITd7mOfw8BPcrltroOOHBLe/iGnhXeOAQbv5d9dYbjfpHXYq8e3La9PxI5pHH5sJdP5YPo4zH/F5CH9AZvpq85lmt/W2fG/VZPM62nlbvtuscUPjlgF3kydPxqlTp7B79+6bvSuYOXMmpk2TZ4bZ2dmIjY29zDescdlQVnNeaVxNigJghd3R58n2xDwnMgignUiT2zfzNzbFcwae+A4AM+0JJCsUxxBqbyrP0FqhzzrAvz9SU1OxecEoTOpZht8SbJDldDuCYnoTBLi0oG5n+1AChyFHWN3WerZloYNK1XjgudpQqRu3/jHpWYVZtMfSgyr1U87umz8DdFygOA/igCOBQLORlizZf5JVDRnPgW3/BLIVUpQeB2KeFoGdBoAJaPsGEDGBfnG5G1m8kbtW7p4yLBFY21pMnVYTnDV7gJ+CXcD+hwkecjeJ1bV6VhoGjQagIhjz7EqWpDKFA+3mnjwP4yo4EKZ8SpDv0VFMo95NneSO4fz/vhs5cLq1Zto242dWKUZPJTjRF5Gt1Thw4Kw8C3h2JIuS/i3NbwFeY5VGBlcScKqvJMOr0gG1mRzsqzPY+aJgGwszDj1BbZtXPCta7YM4+Ti7iAxWyWGgEMDrKqBmNhDoAIQ35/3kFMGq03Nf8by6tiLT3Ho2wXHZSfTrOBEvn7ZDmr4OD3XsioHDxIIIQymfD62j/Gw5hbMXMMDBP/MXpjBjZxBMnv+OXSViZ/A7fgNE1q8zj01iQH3iWQhVtI8gpPQo2buGwn+fnvw0jB4/EZhJxVUA7xmPTpbm3gCBe8UZy84zhXvo0+feAbhNLFwym5iGrsvj+ZGeleSFBI7Rk8k8XSpUKt4TRp0MqL26E8i7xlpWeQpmaiOlyF7DQi3/wUDvP7is8hzwZyTvrTur5GtQeYbMctAYoO1cVklrnXmPGmt5XoLHUYfY4gUCuQ2d+d3AEUx3d/uSzGfpUU7gags4+dLYcv2MFXL3C4CWJKmf8jwqLZMcAoGSg4CmQVFW+necZHn3lMFd2Qlgz11k5wNH8F6KngzsvY+gT+kbWHSA70SXGGDQHnm7x18WJQ/PNt35xBr/OG4JcPfUU09hzZo12LlzJ4KCZE8hPz8/GAwGlJWVWbB3+fn58PPzu7jOwYMHLbaXn59/8f+kP6VlynVcXFya9HqztbWFra3txX9XVFT8uwO0xtXH4cn0tlK2kpKirpBu8DbOtGAAOJiHP0CBuNbh0ts99zUr4ZzCaVIbNZkv1tp8skebejL12f59gi+fXsAKZw5kVeexP6kYI0aMQJegMng7OqLbmNcQ2EMx4x+exJnrlr5ArYmDgFTckPQ+U5PRT1mmXa9laO1lbZAyyk/zTxsXeVnJcWB9ewAqglrHIFa2nvmA/3/oCc7ii8SXsWQDAhXByZHn2QHAPoiMm0nP9lEtX+Ixn3qTbIYkTHeNJZBQ21LonrGSs36vLhzw41fQCidrtNydIXYmB6wTr/DfkY+x8lClIvun0jLtZigDkhdwwKrJYgox7G5+R6UmSNM6iR1dRLBg40RmQedBewqAKVLXVgSZ8Sv4O0X7ma7y6UMRf9i9AATq0ACg8ycEWqVHOXilfSmDy7zNBAimaoKe5lPEtm8giFPryITaeomFISpWJnv1AgI+AYqqgJ0vAMYhrES2FatMDzxCADCuXKG9ygHUNrALGIbayFT8tP8DlCR8jYEx6+hb5tNH7n966k3uW//NBGiCwImJjbvozwYOutlrOHB7dZHP2e05DTzhxHCJBnr+KvvHXU1IhTjK8B/EjzLqq5gJqMmWfRkBsr8ae8v7O38rK1kB9kaWIu1rpvGL9gKj0uXlJ98kAI58jFWjFSl8D9VXEZBUJJNB7f6jDFBrspnyrC8H7iiVr0XOX6yuNdXyfveJF21LVHw2NnQj8x7zNJk39w7sR5v1K9PUGlvaoJx8g4U7dbnMGgQM4bsr6gn22U56j5Mex1A+KzoPtp27sAwIETMl3b609N+Tot9WThgkNhrghLDHcsuqfIC6Te+eloyrjTOfbUFgSti9A8GdSiP6IirGVmMVJ4L15ZbbLdrP92/YPY33zxr/Km4quBMEAVOmTMFvv/2G7du3Izw83OL/O3bsCBsbG2zZsgVjx3KQP3PmDDIyMhAXFwcAiIuLw9tvv42CggL4+DDltGnTJri4uFxk2+Li4rBu3TqLbW/atOniNqxxC0b7eUyD+Q+0fGEDbP1zbDoH4IiJMniK+9ZyveJDZFyCR1OEv2MY7RMACroFM2f/LV/k4Jz2DfUxZYnyNlRqpnlt3LB2ywHccc+jqKurQ35oR/R4fs3FCYRFOAQCI86SmVJWreas44w2RKGbM5SzIMC337VpwG2q43FUpZGBkQZhKT2SuZopaJWGnRwg8LM6mFo/rTP1bhp7+rIVKWbZQw5z+2UnRZ81FXVKmatYcWkoJigrOwn4D2DK2SueerPSo2zSLhUPJL1DQ163VgSkbq25H5IhMHea508ymdV5yE3XdR4EK3Y+BOkA74uaLLIl3opnO+NnaqyaPSwvy/ydH58+lrrPoy+werXjh/JArS8ioPLoxOOSQmJCbL3lSUjZKZ4zlxjAuxswrpSDX+FuDvTu7ZiiTv+WLblcYmjRU3FG1IapOEACwLdtgJP30xZT5wF4dODy6kxxB8xM40l6t/yttDnp8CEmd5mMBfsX4GD6BpRvHQHX/HUsHhl5jozY+e8pScjfxurQjd3IZvXfwcITgCl2QeC5U4YS2J37kmyk1Abx72QFTUVdERk/lQYIHCovP/w0l7d/T2a5i/eTcXVtJQNygJMXUy3ZpMpUMqESG23nw/MshWcXFi45BMsVpVoHpscrz/K3js/k8pIjAEzA+o7UGKYs4eSlcA9Z1uCxclePfRMIRsPvE+1WVGRjzy5in16PDsD4OurdTr4qpnBdaUDv3Z2ArHAfsMqL18mpGYGe2Uipxbkv5een8xLg92CaTNcVEtxpdDwm52i54OZyIZmhWywLktk2ZcQ83XiZVzdgwHZOjI+/SKYbkD0DJcNngOduWFLjbbR8kcDOq9vf7681ripuKribPHkyli1bhtWrV8PZ2fmiRs7V1RX29vZwdXXFI488gmnTpsHDwwMuLi6YMmUK4uLi0K0bb4ZBgwYhNjYW999/P9577z3k5eXh5ZdfxuTJky+yb5MmTcKiRYswffp0PPzww9i6dStWrFiBtWvX3rRjt8bfhNaBs/8Dj3HmGzqOlXT1FeyzaOdHa8YS7scAANc8SURBVAJJo3PuKxr4hj8ge7clvsOZ8PkfgNuOMZ2k0vLlrtKS5YkSNSpqG7J6bm2ADvPk/Uj7DriwHHsveGLE42shCAKGDRuG1U+VQHN0GFMukoeavoRprYDbOCDZikBkY3cChI4fccAMGEoB/bEZTJflbSIQGnGWbYGqLzBN5dGVjE/eFuDwk4B3L26j9AirMPc/TM1U1BN8Uddk0b5D0t04N6dthEsM0zIAUH4cWBvLGbSP0qoELDjw6ExQU18qLlQDMAMtX+H3HEKZNhJMBHbJ8wlaAQIQUw2NZXeN5TWKfZ7edg6hBM2OwQTr4fcTtB19gTYfnp147uN/AU69TSF+m7d5fnLW8bwpB52Ep5lu67hQXubeluC5vpIsgpTaP7+MgC16iryu2oZgVN+g6MSjI0GbUivk1oZMYMMUY+81BMEanWLdVo0bqatUlqlIOx/AfT77BKu1/L57a6b9KxTgNqoLUNafA3Xcd/Jy5wj5uJWpfoN4zez90My9GUY2H4ms86sJ7ACed2Mt2WP3DkDr10UzZxUrhEuPieBGBHcuzYHWr+CSkfIJgZZjOFuj6VzkyUx1Jj3tNPaW3md77mFatetXchV02XFq61xjLcFdRTIrqasvKM6dL9OhysIHgJXJJ19lalhiolxbsTo3cxULXvQFrDTu8inthEwGFnakLCZg8+lLuxbXlnLxl0dn7oNDEO8D7x5k4CX7Hc8urBC/sAJInkfQnPg2q5CDb+dv1+URPA/cQxAXPIbHlPYlmVGpu1D/rcDvISxo0BcT3Nn783qUjWQqXBlx3/P6K4Fr8OjGPnXXO+x9WZ3eMJSyGq2DpXm8FH4DGi+zxjWJmwruPvmElHmfPn0sln/99dcXDYYXLFgAtVqNsWPHWpgYS6HRaLBmzRo88cQTiIuLg6OjIyZMmIA33njj4jrh4eFYu3Ytnn32WSxcuBBBQUH44osv/vM2KLdcFO6jdk6i6Av3kHUBOEMNHM4XsgRUIh4We1OWMX1iquMAEXa3rBEBOGAJRhrAtnmTBRSJb8tMmSBw1l0sVk9L7BAAc3Um1EX7cPoQV3v88cexaNEiaH51Y6WqWc/9TpjK9GRtFgf4qvMEhs7NmN4xFJHRK9rPVIpTM874HQIBt/YU+Sc8w1lwXT6w+27AUEjw2lpMF2X/QT3gkWfI8hirAJipf8vbxOP0k9JYavZQBSicVmnlLgVmUbTt05s6MKcopmfq8kSdjj1ZEI0jmQWf3vKLueYCU0U9fxW1YfsAaGiG2nIWT1JNFgctrSPZj4jH2CViXSt2CNA6Egzb+TJ9U5sNJO8U25aZOFhKA1n6D2w15jfAEtxVpnLw1xfIy/yHEMjZ+5G53BhHJqXZI/SCc1CAM5+ewNBTsrBdiobsL0BQpzR7lULyL/unIRnvSpH5Cyslm08lc+gSzS4Lpjrgy1nA7q3ANwc44CvTjFL0/YvAVmxtOLXrVDyWthqfVmjwUPRA6Dot4iRj11g+N10+lScg7d8FuiyVTaxNBq6rc5NlDhUpfK50bkCL56gDOz2f1/xXT4JdyUKk8izT+i4tLMGdoYTpY6U5tX0gQZTUXkuKli9RwiAxlgAZ3tuzKe7f/whTxoZisrL+A8iAnn6fhSrRk/lslCQAoZVyat+rB4trfPvw+dPYA2c/BeqLxXvQzArf/G1k0zRO3Meox/lZ6c77CeAkwLMzZQc5f7GAyKBIPd6eAyzX8dmrSCa4c2spFzTUKe5fgM+Qxp5MnBR+A5oGQf9Ws2uN/9dx09Oyfxd2dnZYvHgxFi9efMl1QkNDG6VdG0afPn1w9OjRy65jjZsYdUWswqvL58Dd+lXOcG29WMnY7EEOIhWnORAobUx0blyvrlAUX6uAs0sIRAKGcyartuWgaKxmKsWlOWe8lefYmuj891yn0yL+ue8hGNX2eOnzFJw5BlwoAv5YOA7Dow9DlSSCG8EktoISq+Z8+3I/7XzFLhizubzLZxzknJoxraMvpN6l3Tz+3SGILdAqUwhgTr8nghbx+fDsLDebz1jBY3Ruzu4FAK0ibN1YAWnrzXSnzlVsNt6L7vsae6YMM1cA+bt57C1n0ivPWMXG6QB9q9xaMx12cBLF3rZitad9AFO29n5iRelXBH5ji/j7AFPhG7tz3ZGp7FJQm8NBuCqF10hdLgLVfhSWm+pon1J1joyG5GcHMMUUehctNJTReTEHYWUqO2CI3KP53Jc8t9UXgO4/yOucnk8GK+h2OZV4q0TxQbDfqpu8TKUCjm4DHnuHt8PID4Exz1x6G4oOI311evwWZI891bVYbD8Iz2p0FLZ79xKrN428d858SDax3Tvydjb1IHjv/afsPVebBSS+xXu5hVi0NPQ4rVKq0yxZUMdQFsI09LFs9x7Q9m0yhVK4xsiWMoLA7dRkU+8qsT/p31NuEDiCmrvtw5jqT/uK/+/RETBUkBlWaclMX1jJSYpXd5oNR0/hM7BPnDyWn6K9UOyLwCoR5AomfjdyIt8X5YlkFpWTiKHHyHILJplB9Ikn2567gZo45fWLepKTDSVA0zqQlW9oLnz6fT4HA3bKle0561ks5tvPspNG3lYyd+7tLDvL3KyozWUxVNi918+E3hpXHLdEQYU1rEEXdR+CO8lU1rMzB/royXIPxfpypkmcImTtj6GUVZUtX+JLM2Up1wsYRvNiGxdq6paL6bM7Sti/FiALlfgm01TBY8j67RgFIX8LtAB+Xg3kltvg66+/xoiOhcCRlQQcbd5Q7LsrZ+CxL8htdspO0BtMqCcQS/+OKUP3dmTZUpbIKaeev9Kaw601AZvGjtYWPvEEolVpQF0OB/2ivTz2Th/y+zUZgKkCqKkg6xY9ib0+q9JYUVe4k/tbXw7sVhSn1GWzdZlPTxYaaF14HA6h3E5tPoGd1oXHlrGcf7afT41aVTpwYTlTbOc+57ED/C3ByOtWX8U0lr6EQLLX70z97ZtAe4uWM+X+yf03E3hr7IE9d7NYo/MnFPJ7/dT4fvHpdfn7Kex+nneJrQRYPXnqTZ4L9/ZyRXVtrmzxcjOj/fvsKassRqg6DzTzBu7uANjZAgMfsPxOSQJToB4dOTlwbcF/n3wVKqjQWlsLD0eg16GP8UzBR1BVnxfTzGLRTEUyCwxcYizBna0XWax6RTFZXT6vj3e8vEzrSF8/ldaSBXWObJyeBgD3Npc/B2YDu44AZHCrLzDNWptDTWF9JVk3lZaAX2NLpuwv8XmOeJRGvkGjxEKHMoJSrQOB0fmfyObVl3CyJaWR41cAyR8Btu4yYAscxue1+jwnYFI4hgIDdjRxbK35aRidFjZeFnYPK78btgr07MrzqCxyqE4nyGxo53RgIv9vwC6+KwBKOE69xedDaWhccoQFUU7hsmnytQyziSbmhlIysErNqzVuSljBnTVuTtRkUycX+Rg1G2oN2ZhjM+S+h7vv5Au902K5v6xPL9oy+PYXBbsCsL4zZ7suMRQz1+aJKcr+cjGGBCLM9QQdkhjeMYRC+aDRQKtZgLkeNXoztCZg5X5Ao3PGhg2r0bdvXwIm52hZe2Uo5+AxIlXsganlPhfsAtq8xYbovv3IUp37nNokGycK4N3bcV9sfalDMteRBbTzFfvq2rN7g8pGTHUJHEjry3isxlqg+/cEfEeeJXg01YrtyBx5fAEjmP5KmEq2xD6AbJffAA4gdj7UCiW9R2PbVi8Du0bxNwt30o8s9kVgiyJ9KGkUncJpy3DqdQ5+UuhcgdFZolWIioOmMtQ6itm1TpbVjoBsq1FxmkUZxsp/dm8B1LH5xFsuM9cxnVl8kOBOipSl7E4Q/RT9ym50KG1/fOKZ3qtKI0uVMJUs6dOTgcLtwNGHCZKlOPgEQb6kDeuwgPdW7gbAOQr6Tktw/5rpuF2TjipTMJwBXgOpd7Nzc94bypQ1QE87jZ1l8UTeZt5j1Rcs91kJfJRhrqd2zM5H3k7hXqY73dvKjGDuFtrPmOuAkWniM1ALbO5LditiotgNYjYroo0i4ByeTAY+7Rtg/0NimzAdGTd7fx5X3mZOmmzEFHrY3TyvZr0lQ3qp1KdDoDyxvJZh4yJPMJUhddJRRtDtZDobsnPOkTyvyv2rOMNJZEOD9l13EAgO3C33oC3YyWIPr+5k8KWoSuP50nlcuR2VWkNJSNU5SxNna9y0sII7a9yc2D2Oqb/6cjIWkuh80F55HYdQal2U4nYbF3q1XawGUwHNHiKLJJmHht5FJqOhUeqYfOpclAL4Zg/KgmYAh48cx0NTTyDUGcisDcAfGzagVaCR/mmV59iUPnAoBdo7R7HdkVormr5OYtqxLo96N7UtO1uYjUwL1Vey2q/lLJqvnniZOj1zHX9creVApC/k8dn5U+ztHAncnsf06LnPCNxUajIPANO+Xb+SUyGmOrIsHeYDa6KB0gS+rKU+n6ZaFnxUpQN7xouDoi3F38UHeE4Biu19elLLlruey/I2s+oVIBiKfrKxMbJysKnJYVpLAuxurSgE9xtwaUPlTkvI/DW0xvi3oXW0ZFylqCsgS6VM/epL2FLKpw8nF1eTZjLWsrBE0rMBBCAVZ6kTlRiYnPUENa4tadwsxcnXCEDtfAlA1FrAqzOQuojM1tnFwNnfgdvWECSp1HJ7OsHI7XX7GnAIgq3fANzTfBsmlq9Eam0pnMfkWlZSOgTw3m10rhwaL+v4MdPygSPAHLF4n2StBjJWUZYQ8RCX1eYDv4m/M7aI5yJ7HXWlVSk0AJbA3Z47ZSNsfTEnB+d/BPY/yONXaThpsnEBQu+h3CL4dtlnLmQ8P9oGtlbRT8qTQmXYOAFwarz8Vg17v6arX/ttbLwsYAitWho+Wzo3wOBK0CtF2UlqX81GS3C3pT/vJSUQLNxH6YpnV0sNpb6E7xa1hr9rTcfeMmEFd9a4/lGdyYrVFs/LaYiIiZzZn13E2V73Hyx7mOZtoYWG1kn2uhIEvvDP/wgMPiCnr1q8wBSfxA44R/JlqJy95m9nytM7Xk4NnVnENJ1TODB4P7b88RUO/vQ4lj1qROtgoDziMbi2asX0TpFYbKG2pSGqYxj/baoF6srExvFFZBJsPTk423rKBSB5myjsDxopGoHGEpy5tgTabeKxG6u571KqaF1bMb3rRHYT4Mt2z90sNgm9m7/j1ZXATzLBPfsxtzdWTFd7x5MtkSJzFRmUpHc4cPr2Bbr/xN/dOVrsotBJrpTss44mzr59ZSsGQE5rXipKT7CoQa0luylZU/ydp1VDxu16R5dPCHahYCkko1yomVqvPM9zW3yA6S2//izMKU/i/Sfp9zJ/p3bUq7ulWWvKUn7Xq6sM7jT2TGM1FNX79CEbZufHNmht3yKw6bsRKCoH7h8PFJiB7RuZEgUI6DstkgdXxYRlaOtH8P26lThfX4UxlcVoaecrMzLmeoIzfRFTmtL3Uz8Hzn7CZ6PXKi5TaznZSFksA7biQyxeKNzNZ1sCd+skPaOKx2jryd+oSiEo81ak1b3jWVTT6lU+V2otJwODD5JRtHHi9bD15j3Z0MKjIaj7L4dTM3nSpwypw4cyfHqz6rqhHEGSMtgrJmklCayOrsu3BHfrO7CAatA+uQiq5AiflYbVvda4oWEFd9czjNX8U+Mgv0xNBg4WKq2l9uHiuvYySDHXc6au0liyV5dat6F+4wrCbDZj3rx5+Oyzz5CZmQlfX188/vjjmDVr1lVvq+kfMAEbuxL8uMTILciaPUTQsu9+6nrUDXQgvn1FINYOgADkbOALQ/rkbmD6s2AnGTMJAJaeAP5qy4FxTC6XCQLb52T9Jqat2rBReNI7gNkAwVCM+fPm4acl05HwlgC9UQ1B6whXF2dqnsqTua8enWjZYTZRtxM4ggOxdzzd4wUj7VVUamBclTzo+PbjMQSNsPQMG3muifNVz9/U2NFDqiSBA9y2IWQFoyZRf2Pnw1Rs6lLaQJQcofWElH4ym9gD1TmKXlnJC8hMefcQvbAieN4FE+1jbMU0dfxKarck7SAg9kLddPUt49xaEexq7DjAS+DuVgh9CQX1Ki0rGKWU15HnCKhbvQr0+oPPX85fwK4xZDJrc5iW7LMeyPyVgM1vINlKnZsskJdsSaQIHkvbDGX607MTu3bYNmBZ2r9r+W9JBuA/EKg7ASSagToAh44BQYNZLaqykcG2qY6FI/oioP37CAgZjN89xiAm71c029weaPE0j6/sBPdp9zhxH+/gNqrO85jLjvKT+hnlE+vFyZRjON9Btp70lyvcTcCqBO32QXzuev4qg1mfeJpeuzSXGSEA6L268fUxGyzBQb/NYnW1dci6ZuHWip+GMTqT45TyXHt25ntGabsiCHwnCSYCb4Bym7ytrPwevP/67r81LhvWJ+V6xgqR+h9TIA9sp99nOi5iojzrBoBVPkzljEwnUACYfjnyLFMRSi3G6jC+uIeekhmDtG84iF9lzJw5E59//jkWLFiA+Ph45ObmIjk5+e+/eKWh1lAzUtTgQa/JpEYo7D4KuaUXyd4HgOzVQIePWP2ZsojVs9uHELAN3M2m4R4dyGBl/UYdngTuJMBsKJWrazd0AaDmfkiMW00GYDbAZBeMdzf7Y9YnL8DJDtiRHY34wfdD1folgrTiI2L1pkCrCJfm/H7Fabbosg+UTXAFgYOgY7ilkF+yUFCGsYZGtjXZtGeRgNPhqTJga/MG05fGWtl82acv0O596rDMeg7IGicygwBtHqrOk8ncfz8BTNEB6tzUNpyldxYrzzvMZ5pNmiwABCe2XRtfx78DdoJABujCMpEF1PD89d0givOvEhj+k6jJJtjXOsmpY4DtkEqOMFXpJR5bwQ4CNs9uwOB98rqFe5k6j3pSnogU7BYnaDb0pivYSXAS+RjXKU/kJCV6MgtO7ihrbLwtFZwoQ+to2XdViupMstn2/vL9Zqxm9bK+GPjoJSC6PRB/BwtPkueTFW//PtdVafmOAZhytfPGMx0n4uj6X2GPehjKTkP3ezAAFRlIrRNBnnTPFu7ic2UrMnweEsgSJ5KdF8uA06M9ZRLubS3bRw053BiIXYpVahhnFtH+pvsy2Rz63+jezOKEUKWW90kQ5Oda6yzfn8ZqPm8aOzF9K65bm8N17QMsC7kMpfy+cuJSngzAzImVNOGuK+A2dO6WTFnxYZ5393byBL4mh23tbL0s74+CnQTuXnHyZKQ6k7IHWx+5iwjAybCxinYpkjyg+gIZfztfy2uVtZqTHf/BMitalysaa4vvVa+u8rMjhUrFDin6QnmCcnYJeyQrW51Z46aE+u9Xscb/16isrMTChQvx3nvvYcKECYiIiEB8fDwmTpzY9BcMpcCJV6k9u6ofSqXxrlR5JwjU2JyeR4Na5YtRqOd6hhK23cndwJePWxt+nCNk36vwCdRDKV9UGauoabs9ly8f+wC+sE01LECQDD4jJyE1cD56vgHM+uQgdDod1i26C72alUJjKJRf4B7tOSAIRkvH9aBRQIcPqaFSRqvZfKFqFZqes0uYYk1SMjIqGsAmvm3J8jiGUANnrFGsa6amrt8mtghTa4HCHTRarS9jSstsYIGCrQdQmURrivAHmTYuPyW3yMr+k/uR9QcHlNIjwOZ49uBsKgQBWG4HLLflLF2KqjRWvkr7Xl/OKtiMlWwcL4WdN4FwwS6yt1LUV1G/l6+oOhQEanuyVlMPCNBb7dQc4NBTXC7F1kHAz068H6WOIsWHqGFLeIaG1Mp9rTjNqtAi0XLDPoAidXMdWV1zPZfHzuD9U3yIDARAIHdnFQc6Ox/qQm2ceO09u9F6BgJTqRodi0qOTgd+C+a+GGs5iCdMY//W9O/Fc1ABrO8CrHSjWbd0fs4sZPu6XWPZpB4gs33+BxoQRyYD7cRnQOcGQMVG8iff5LLEuQQWLi0IbMtOIl5ViKnuwEk9kFdymt+x9+W9YaziPbf7TgJZ52gWLPkN4uQlWays7fkLn6uMX4B17Wh74daavYrd2gBrYoFtorZSAlH7HwH+iOBzKUXZKeC3IGB9J1jE/keAVd48RrOBhUgVKcAKF5r7KuPARN6TyQvkZTVZwDKVXBUvxeGngJ9t+axJYSgFVroAK10tJ2InZgO/erPARgqzgVZBvwdTNytF8gIe28nXLH9vXStWjiqfl7SvWdHbcN0t/ShduNh1BGSEN/duvO7u8cC2wbKbAMBJ3Y4RLGyyOObJwO47RGmBGEX7gb33sppWGSdeYceZ8kR5WdlJZiH+LtRaTkKkdH7AYPZp7rz0779rjesaVubuesadVfxToxAnt3iB4lVVg1Mv+XMp+/FFTyYbp2zsDACjzjdeV6GxudI4ffo09Ho9+vfv//crm418sWWsAEIGNS5WuFw4BjMVqFJzQD8xm2Aj5rnGwt+2c+mcbx/A38jfTo2HoaxxVZ5S/yVF5VnOTvXF1FLp3IDhZ+X2PAAEsxmf/nIUTz89EwaDAeHh4Vi5ciU6uh0DDiwnyyWFSsUCADsfecZdk0UwYCjh36X0kakW+F1kGO4okWev9eVMgZUrquO09vSD0rmTVZAiZprYpF0El4eeBM59QauWyMeBs3dTmB48DshcyfPZ/Bm+8MPuJmsYPJaz7LKTFMb7D+Js/9SbAAS2dVOpgTvKxUpXFfXxeZtFD0FXeX8yfyND2DAOPMaekHE/sCOIzo3eYMkfUK/VSmSODGUEjvlbWfgR+ShT2qfnU6Bt6wWMFQfBv9rxPAFMn8c8w2txQpQIpH0NjBdZRmM1KylPvUng49aS18erO+1iDjws67/avSf3nbX1FO1VutKvbIUTu11EPEKWJXg0dYxJczkh8OvHe0AQZDYs8nGe15wN/P2SBCD0XhrpGkqB30PlSt/0H3ksGSuAMyIQMZSKjKsDveQgsJo65hkOlI6hZKnLE3mOm08hkA8YRmYx61e2bSpJALa/ApT6ABHnyLgB/P/KFD5zeRuB3E1QnXwNJmhQZTahtT4NgnsHqIYc4nURBHYKKTvOTMGg/bSmyd1IMCGBHym9WpXKdZWTElMtAbQEkqWozeW9qax8NtdzQgKzvEwwE+zqi8gghd3HwqjKFH63YS9bSbJiNqJRNPRPlVg55fJLMckXlyvXVfN9rVJZLlfbchLXUFJi68n9sujQ4Mxra+Nqua5TGN+rSpZT507GVioYkcK1Jd9DSomOnY9oAB1tua5HJ/H3FBW2dn5im8N2lut69+K9orSysfMjm3u14dPr722KrHFDwgrurmcoCwSk0OjAZpFXsK5k33Gl615l2NtfhRBZpeGLJPwBzuqlyPiFLFPoXZZVqMro+gX/NJuAtS34wk77mjP+hiGlpAEWHwSNpEg9/Vu+RJtPvXSVJcDUXFUqUKVI/7hEXfxrVXkxipZF4cL6UqgFYOTIkfjmm2/g7u4OVLoRrCh1JWYjTYWrz9N6oSCBM2WPjhx4wx+Q03daB74U1TYsrpDAXfAdfKFKKTYplOa6ANOpCVP5m/E/M5VYcZYDWfEBvsCNNWzN5dubL1HnSDKFUmcAZdj7y2mV2jwxtaTiRMBQRvapzRvUDia9x6KJNm8CkZOovTLVgYOZmtocqRq5PEluk1WXzz8L95GRsXElmJdiQ1cCbodgeWCrPk9gp7G3TDtJA5FThHyNnaOAoDEEQcoOBl0/p+awaL+cavdoz+KPPXfLgEylotar8iwAM9ksKVRasc+vynIC5dGe11VKR5qNnDB4diVTJaX+c9ezj6xbO55/O2/e45IJs28/tppTqXj9vXsS2OZvIVhza03tW/V5MmS2XiwkSvmE92DMM/IxJ86haW/0VBY5OAQDu1cD0wFoCoB1LwPh4mAcNVnWsWrtCCKNlVC5tcHjuRloU16GJyOHo7tKLdt/1ExhR4mSw+xa4jeA+9xrdWNA0u59AjulgbRrK6D/NssJJ8DUv+EVy8mgS3MxbavjuT31Ju+p9vOA1q/xvpW0i45hnJw1rMJsP592Q8qiKTt/VpU3BG7t53HSqNQ427gBd9ZwXeVEu927nAwot6G2Ae5uAFoBWie1akKbPCa/8bJLVe4OPdF4Wfi9cgtFZUg9W5UROFyuOlZG/PLGy3x7A75bGi/vvKjxMk9RX2yN/9mwgrv/cERFRcHe3h5btmy5dCpWCpWKM8aWLykq7UzAsZkEU6baxrqyhqHWAH3X82Xebu7l11VG0ChqioLHXh7YAQSDpurGzc4BJCUl4bvXB+CdUaV4aiDgE/82nnl+JlTS8WSsAI6/xIFdakOl1jJFqC9kl4byU0yF1uWx+tW3r+WPjM5qPBC5RFkATABkXdJ/5EDdfApn72uak40AqKnbew8H6G7fkIn06Snqhj4gKLoaHZvWgYO+StXYy82zM1lRW2+CvJos6gtLEpjasfNjb17p93aNEZkXyKl2fRFZIo/O1EVKYedD9qbzUrlvqEssGWznaLJ9UvT8leBA6yT/lmusXK2pDNdYS9NdKXSuQN91jZdHPNw4ha6xJYhWhiCQ9XCJlfWsggnYNojXJu57WU8nWYL4D5atXgQTu484NxPZahVBetYfBIFO4WRIffvIXRZiniWrZ6zkRKHiNLcTO0Per8DhBFPh98lM8cBpgO88wFYLuPQFgvpxeWSDZ9lYDQxPhlpti+G2n2Hu7rnIPr0T27qIx1u4h8yljQtBrgT47Hz4PDUMryYYHZ1r0+2wmuonKvWNBphST5rLCUzUJEuJBcAJY8NnB2i6UlutkavKG/5ew1Cpmq6ybcgQWuPqor6Csh2NPTuPWOOmhRXc/YfDzs4OM2bMwPTp06HT6dCjRw8UFhYiMTERjzzyyN9vQKjngHn+Rw46UpQncVbe0FEdoKC6qSbTlwuVShaL/100n8JPg/jxxx/x2GOPoa62BpVVbpgy9Wk8O7iBv5djKMXGmgaDQfwKshcuzTnA2rhx0Gtq0GjK5yn9e1qptHiBg3t1JnDqbYrWveL4u4lzResBgWySTx96l7m2JHhoyufqakJjL4Pv8mQOqO3eZ7N3jR1Z1KBR1HoV7mGaTF/E8+HZmccQPJoAwDmajEvkJCD2eW7TvS01iMrWSwDQf3vTYLf9e4338e+A+/UIY61YjS6yzqmfAYcm0cBZAokaW5EdUcsN46vSmP51DJWBHUBvvJIEtu2Sig7qK9kj2TkaGHFGZhTd2hBMVIqTI40dr3m/TYB9MDVWHh1Z3NGUP5+DB7BlPxAcC9hcgjUHyPSLrPETnZ7Ae3vew/bz23Hu9GeIOPcR+6EO3AuEjPt35/KfhFtL2nHYuDYGdtb43wuNPd8BDaVE1rjxIVjjbyMzM1MAIGRmZjb6v9raWiEpKUmora29CXv278NkMglvvfWWEBoaKtjY2AghISHCnDlzGq132eM0my3/vW2oIPyoEoSUz/jv8z8LQsmxa7fTdcWCoC+9olVra2uFxx9/XADzi0L//v2F/Pz8a7cvgiAI+hL+WZMjCMkfCULSPMv//6urIPwIQUj/SRDqq/j/P0IQltkIQuo3gpC+jP/+s+W13S9l1OTyN35UCcKG7vz7cgdBSJovr2M2C0LuJkEwGeVlJpMgHHyK6x9+9vrt382IXeME4ScbQchez3/XFfHaLNMIwpZB8no77xCEn50FIetPeVnedp6TP6Ist7l9hCD8pBOEtO/lZbX5gnD6A0HI+K3p/TCbBaEsURAq0+VlpSfla2TUy8sLDwhC8RFBMJv+yRELgiAI41aME8bOg1D/o0oQVroLwnInQTj37T/e3lWFsVYQjrwgCNWN36XWsMb1iMuN3/+fw8rc/cdDrVZj1qxZ/87XTpkeNBlADZOamqOSBNpEqDRM10mVrv80sv4ADjzCFG2XJiqyTs+nPq/ZQ0jTjcK4ceNw5MgR2GiBF2e+jNmzX4NGcw1mlUX7WQFqrAaS5wF9/iLzkjCV2im3dtRgFe9nUYBXHNmTLf0o2PfuxVRY6J1kbbp8Sn3WdQsV7QrUGgr8995N9inzF9nKRaVq3IJJpSJDZeNqqYf8XwlzPa/VqTdZGNBfrIA99hKLdcz1rBgOGMwChqPPA47NgH4bFNswMGVakyUvc46kV2NDdrrHctF/UvFM2Pkw9XqpUKkaW6LYevM6GUottawnZjGt23mJ3ArObOLn7QlAbg6wdIfltqozgZw1vC9DxuHprk/jrrMrUWQU4O7fHbbdvvj3zPCVxsFJfD6LD1KjdyMscqxhjf9gWMGdNa5taHRAnzUsbHAIpH+Sbz8K2neMYhPt4DH/fPs6N6YLi/YypdZQN5O9Fig7iYJj36DDpNdRXl4OT09P7P58NGLs1gKFfVkBeaVhrKUAvvIcEPO0vPzsIqajnSII8CRNnEdHiuC3DWABgp2PXCl44lWaLNv6sJKz2QMEWMdfYXpPWQ1csFMUrXeQCxTMJqYF1bZXNyie+5ppWH0RwZ1XF2DIMVpNhNxx+e+qVHSfV3qE3QohCKxmVRYXnfuahQpaR6a2g0czHb65t7yOvoRi/fJE6ijbvMH+uQCvgUenxoCt/fv8KJu5OwQC3b5qvF9Nper/Sdj7WraEAnjMNq7UJCo7PORuAL4aD7xWxSYb9/1CDzwpKk6z6tqtLRAyDt2Du8PHuwM6ZR7BlPB4zLhRwA5gFXXhbp5zK7CzhjWuW1jVo9a4PiGZjtp6AD1Xi0agWezt+m/CpxfQey0wJKFJQbTJgXYlv28+gfLycsTFxeHokQTEqLdSvF6Tcelt12Sz+rdwr2KDtayOPfIMK0yl8BtAjVLr14G2c8i0bOpFptI5itWO9eWsKu20iNozQzF91Tovla1rqjNp/Jv1m+W+JM6VW4FJUX4S+Nmen8rUKz9nFUmsUIZZtl3RObMiT1lBeKnQ6G4esMvfQTPvcoU9TfFhWpj82dzSoy77D34u/ESvMICAWW3LSsr+22X/wZhn2I0j/AEZZDiGAkMOAT1+stwHl2h+bnabK5WKXnN3lDYwt90BRFQBQ9yAl8YCXcUiiIRpQOoXYru0QayWLjoIlUqFqV2mItsILD68BEbJTqQy1fIevxZhKJf9AgEC5+HJTdsYWcMa1rhmcQtNxa3x/za0OmB4Ej3TJGsOgANP3kZWBUrVc1cSgU2nLxMTE/HaawdRUwikFQDPPvss3nnnHeh0OsDnIL3Ewu5r8rvcn89pBho+gS2pAIJTP9G81lhN5tBYzY/Khi2Xzi8DNvekgN4xnOBu+GkCDzs/Cu41OlaD6ostGTqncNo6SG74UrjEiN5+Cmd+qTI1aLQlu2Qoky0h0n8kq9jta7laLeoJwCGU517pe3WzoiaLjKVTM/lclCfTm06lBQbulNc98yHZuLZzOEFwa8lrYqoBamvoUefdg/dPyDiypfXlMiPpGA6Mr23MEjWscv5fioZAu82brNy9zUXum1yTwwpclRoYW8zCGH0hkDAFGLQf41uNxwubXkBmRSZ+T/4ddxgOs1K67Rx66F2LqMkGNvditfSQBLly9lZigK1hjf+nYX3KrHFjQmNHk10pBIFatYozbJl1NeBOuY0LP8HoEYf5n6zAq6++CoPBAHd3d3z++ecYO3asvK6dF1tyXS48u4hp1QZpuX4b6C+ndaAr//kfgQvLae7b4jmxLY/AdOvAvYBGfKyaT7Xcjr1fY22TY4iseVNGUx6A3vFs96MMQxnwZyTgN5g6rIwV1PmlLgU6fsh1nJqxmvngJIKchszUtQhBoEWMSmvZGknSuilTmIdFU95Oi2jUDZBBLNpHls0k2sFodDzmmmxa1OSspW7TIYTeZydeoaecZE4bdo9lf1Pgv5H60+jo5acMsxnwfwpwqCPw77yYoKrtHEClgp3WDo93fBxv7XoLHx34CHf0nghAEBneaxT2/pQtCCbLFnfWsIY1rntY07LWuDmhUgE9VrA/p9J/rHAfGa/6qr/fxrHpwN57sevDjnjxxRdhMBgw6e5eSNm+AGMHiGkrQ/nlt6GMwKE0V5W6KwBM065tTW83gO210r+lAW2792hf4hzJtkxDDsrA7nqESk0rEhsXWpVk/QFsGUA2sOw4U44tngPavg3ENgCypjracWSs+Hf7oC9h70+LVmoA9twF/OJBY2EpBCPZ0vPLLLsDOEey9ZfSeNs+EOi5iiznL27sLwzweLr/AEBF0CcIBCkuUTRq7bPGarbaMI5uArrGAtN+ADqLLaRsnAmwFZOLJzo/Aa1ai10Zu3DMNgYYlgh0+/Lf/XZdEbWhAO/X7j/QI9F6jazxPxaLFy9GWFgY7Ozs0LVrVxw8ePCS637zzTdQqVQWHzs7u0uufyPCCu6scfPCvQ2rRJWpwsQ5TLUdv3z1rslkwne7gIpaYPORUri6OuPrr7/GkikR8Dz1INtN6UuAP8LZ81TZE/JSYTaxt2ZFCoHEmlhg9zgaFxfslDtxRE8lKxb7gmyaeiNF6QAAFduIlSYALWbwPKo11CTGvkh2UV8ir27jTD+xDh823pSxlpWjmb9bLj/2InuApnwiL6uvYGrvxKuWgM1OPA/6InmZfQA7DnRaZNlirf37ZOAKdgOb4rkdjY6FNvYB1DkWH5bXd44CxpURPP8XmLh/G1obILUSSC4DDjdh6CxGgHMAxsXS2+6jw0sbV+xebeRtZl/V0woPQzsfyy4S1rDG/0D8/PPPmDZtGmbPno0jR46gbdu2GDx4MAoKCi75HRcXF+Tm5l78XLhw4QbuceOwgjtr3FoROJyWIVK6DqBmp+TIxX+mpqaiT58+mPD0PARPAQ7XDsLJk4l48MEHoao+z5Wq0pnGM5SywX1TLduk0Jew0nJzH2rnUhaLDeDdmWaMnQHcns20rF8/Vvx697geR990CAILCw5PJWMHEOTETgdaTKc5sXJ/MlcBR58D1rVmdS7A428+lWzZtqHAeUV7In0BzYv3jLcEbMYadqKoVhSh2AcQhEVOsuw52+ZNtnNqPVteprHlv93bASdnAxcU3SBsXFj4ULjHssglZhowLMmyg4lKJXeFsMbfR+s+wOIXgWP7gS5NtKZSxNSulA4sO7kMhdVij9/6KqD6HwxM1ZlsR5exonGPWWtY438oPvjgAzz66KN46KGHEBsbi6VLl8LBwQFffdVEhbwYKpUKfn5+Fz++vk10S7mBYdXcWePWiqjHmapVMjTJHwCn50GIeQ6L9oRixowZqK2thZOTE+Z98AEmTpwotxALHA4YStjrM/x+9hI1GyzbCglmwKSXqx8rTlPMr3Gk1YRa9BXr9hULInQNemve6DDVADtHkjULHEFrGbVGrrjNXkd2zW8AiyZsvVmQUZEMbOgMjK8Te62aWXWa+5covL+L37fzZ/cEh0Bqo6TijugpPIdOij69Gh3Tpw1D50pgWHqC2rmwe+XtFOwgIxs4Eggdz2Vae7ZBcwynVlEKZQ9Sa/zzmHhl7f26BnZF54DOOJRzCJ8lfIZZzdoA+x4AvLoBff/6+w1I3TYA8X4UgNC7/1Gva2tY41YIg8GAhIQEzJwpS1vUajUGDBiAffv2XfJ7VVVVCA0NhdlsRocOHTBnzhy0bNnyRuxyk2Fl7qxx60XD1JuxGoJKi5c+3IipU6eitrYWg/r3xqljB/Hoo48S2FWeA7aPoMXC0GOyR5hnJ7nyFaBe7LcAIHm+vMyzGwFTzDPAyDS5NZZL85sD7EqPs2dv+g9MT2od2YIq7H5g773ASmeZwQPoc3b6fdk2xbcPMOQo/27jwkKHslPAcluCvq5fAqGKwgONjm2x+m+1rNp1iWLrMVvPpvfTUMreoFKoVMCO4WzfVXJIXu7bjwN/6F2W34+aRPPgm20x8v89DvwB/NFEc3iQbZDYuyWHl6DeOYrVxlXn/l73emEFsLU/J0rcGPWz1utpjVswKisrUVFRcfGj1+ubXK+oqAgmk6kR8+br64u8vLwmv9O8eXN89dVXWL16NX744QeYzWZ0794dWVlZTa5/I8LK3Fnjlg5BEPDZkbaY/5YOqdkn4eDggPfeew9PDNJCfawnYHyV6cZjL9KF36xnL1iVlr5eOWuBiImyrk+jY+oof6tcOKHWAP23XMudZhVnfSXgECAvLz0OlJ0kaJSavxtKgT13c5+GJLAy9K928ndaTCdAbSc2V19uC0AQ+76KjJdffw6s3j3l72ntyNhJPnaHJrPA4dgM4M4r0B82OiYz+8lK3RJyNwLbBrOwZOgJeT3/QUyJQwHQPdpffT9ha1ybWP4OcN9MwE0DnB0DeAQ0WuXOlnfihU0vIKcyB79mHsf4Qfto5txUn2QpDOXA4SdZzJPySWPDZWtY4xaL2FhLTens2bPx2muvXZNtx8XFIS4u7uK/u3fvjhYtWuDTTz/Fm2++eU1+42rDCu6scctGZmYmHnnkEWzatAkA0LNnT3z99deIiIigbkxfTMABAB3msSK0w3zg5GssKFBpCJocw4Dg27le0O1MMyqBUMOozqAXm0MgjW0BArUzCyn2b/u2vG7yAlaDRjwst4MylAKrRLbrLoOcojr/A3B6HhDznAzu6grIvAEEbI7BQMBw7rdKa5kSVdsQANr7s5WUFEEj+WkYSoPirl+S0bPzv/RxXyqOvQikfMpCiMiJXOYm+qmZDSw+kUBf1y+ufvvWuH4xdCLg9QrQzAOoKGkS3Ok0OkzqOAmv7XgNHx38COMf3vP329W5At2+YWu36Keu/X5bwxrXOJKSkhAYKPuG2to2beDu5eUFjUaD/Px8i+X5+fnw87uywjkbGxu0b98eqalXYTZ/jcOalr3JUV9fD6PReLN345YKvV6PhQsXolWrVti0aRPs7OywYMECbN++ncAOAHr/CXRfRlBTngQkPAtUngG2DQPOLiFQ8u5FHZrWCUj9DNh9FwcjvwEEPtWZwCofYJWX5Q6cegvY1ANI/15eZjbQVy1xjgwoATJtJYdpyiuFxBKq1GTwpHCJBfwGyj56xYeANS3YQaDXakArfq/3alaGDt5LDaIyPNqzMld1lY+u1p5axqARl17HUA4ceAzY0E22swAAqJna/T/27j2+rYO+//9bF0vnOCG9UJK6pW4Uy2lSLr1Rss4aGzO02xhLt3xpxy64IAcMySArxP56TGYwvAZlYNxvwjo89gu3DMLyhXDZGMWl8AUa0pS2tI7ctLXTtLXTONAmilvJF53fH8e2JOxgS7Ei6ej1fDzOQ87Hn3PyOXKavnPO0Tm/zLgVgHmxtOGE/bSBzGeforQsu0g68JD042Fp5avP2Pae171HVe4q/fTpn+rg0NQnlS1r6ijs1NeP/0v2p5gv/WPpqo9zU2KUhZe97GVatmzZzHKmcOfz+XTdddeptzd9NieVSqm3tzfr6NxvMjk5qUceeUQ1NXn8Y3qREO4KafpJBpmfQJwcs2uTSY2Njemxxx7T448/rsnkqanejGupUuNTvYkzbPfXevOQSqUUjUYVDAbl9/tVW1urzs7O+Vc8WxOj0okD9n3tpkxOTupHX9qsf/ubFdr9f7bo1KlT+q3f+i317d+nLWu/Kvc9jfY+nzhgP0rsma9L36q3nyc79G37BqyjT9jPX5VHCn1V+v27pZo328Hk6FelFzJOIXpM+679yV9mhxnzEvuIWeYnbKuW2ad3r/hb+/TmtFW32UGzbmO65q6SbhmV/nzC/sTttLp3Sr//PftaM8m+YfLSOvuZtBdclb5WKdfglo8X+uwQmxlgvUvtT7D+8mf2I8umBTfaRwyv/0z2Ns50LR5KS+2rJPdv/jN18dKLdeur7Q+73PmzO+2j1/99lf2BnIkX7SeF3P8++36GC7kHJVDGbr/9dvX09Ojzn/+8YrGY3vve92p0dFTvfOc7JUnveMc7sj5w8bGPfUzf+973NDAwoJ///Of6q7/6Kz311FNqbm4u1i4Q7gpqz1J7ybz3V2y7XTu4WRMTExofH9fo6KhcX7/YrmfeduLwTru2P5y93X0r7frJWLo2sCuvEdvb27Vt2zZFIhEdOnRIu3fvXvyPcP/4z+15B7+Urp16TPreOunHb5NlWfr2t7+ta665RscP7tSm3zupN12zTHfddZd+/OMfa9WqVfZTF3510D6t+b119pMPpo90SdLre6Q3fFN65Qb7BrnLf+20a+2t9j3eam5K13wX2NeLrT+SHahe+w/SnzwprfnbdM1dJa3rka77lP20jWnnv3rq9i2rs38/b/X892Rzue0Pf7zxu+nTv4UQf0Ia+IIdYqeduM8+EjmQcS2c2yNd88/S73zdPpU9bWlAuvBajtCUuxdPSS2/K31w7sf3vf/19gcrvvLoV3Qs5bFD3GTC/ofUqnfa9xtcvcn+sw042K233qp//ud/VkdHh66++mo99NBD+u53vzvz/8ajR49qeHh4pv/555/Xxo0btXbtWv3RH/2RTp06pZ/+9KezrvM7l/jbuoiqq6u1evVqPfbYY7Kmju6lUqlzlrjj8bi6u7u1Y8cONTU1SZLq6uoUCoXmWTNH1oR9pG762aiSfWPT6lrFJ5bqj97wBv34xz+WJN17qamVa69W5JMfkTH2lHTvm6VXdUhv+MbU0xnOl7wfn3qk0r/YgSszmJ3ptGPNm+0lk9tjfyDgXIs/aR8xW3K5fTRvMU2M2v9AmH6OpyT96GbpZJ8d2i672a4tf4P96dUVv5+9/q+fBoZzfLlT+tcf2X/rv/tn0hXrsr59/aXX64ZX3qD7nrlPn/3559QR2mPfmmb66PMfPcopeFSMzZs3a/Pmua8nvffee7N+3dXVpa6uOR4ZWUSEu0K6Zer0hSfjX7prt9qfLHPZb/2SJUtUX1+vR1LfVyqV0rLnJrRqaUput9v+V3Jwo/3BgEzrj0xtN+OWA9P3PMtBLBZTMplUY2Njzuvm5NpPSVd/Iv0UA0mPHnlRf/fvV+lb3/qWJMkwDL3//e9XW1ubLrzwQrvpJ2+XnvuBfauSq//JrlmWfa1Xuf1PJvN+YM/dIz36UfvTrhOnpSv+Jv9tWhPpD2yc+Jl9rWD1K9N/RiQ7wFUty7732LLVhXnGLEpX+A5p3/+V3vJWqf76OVvev+79uu+Z+/QvB/9F/zv0v+XL/O+s3P6bAyoYp2ULybvEXjJPz3l8di3jk4wve9nLtGr1a2R5qvXCyVMaHBy0j+S5q6Z6jTNsN+PHl8dNQ03zHN2PakmtfQSgaqmeeuop3XbbbXrta1+rb33rW/J4PNq4caMef/xxfeITn0gHO8m+ju3aT9sBd5rL9Zv/J3P6iDTyU/u1FDzRI/33NdIz30jXLvsz6eXr7E/KPnnmO57/Rn13SF+vkQ5n3L/svCslWfajvjKfqfu6O6Ubf2rf2BmVy+2Wvv249N5PnfEavA1rN+iSl12iY6eP6Wt9XzvHAwJYLIS7ErFs2TIFg0G5XC49//zzOnLkyMyp2kKpr6+XaZpZnwoqlJGREf3t3/6tVq9erc9//vOyLEsbNmzQo48+qs9+9rN65StfOXuli39fWvMB+5qvhTq8wz56lfk81HPpxWezf33qMfvxZ0f3pGv+l9u3kbjiA9LKv9BvNJmwHzv2PzfYz4Cd4bJvl3Jif7pU9TLp5melm58u/lM1UPpGX5CGn8wqVXmq9N7X2bf0ufPAnUUYCsBiKGq4+9GPfqS3vvWtuuSSS+RyufSNb3wj6/uWZamjo0M1NTUyTVNvetOb9Pjjj2f1/OpXv9Jf/uVfatmyZTr//PMVDod1+nT2p7l+8Ytf6Hd+53dkGIYuu+wyRaNRlaLzzjvP/vCApF/+8pc6evRoQQOeYRhqa2tTa2urvvCFL+jJJ5/U/v379bnPfW5Rtm9Zlo4ePaqPfexjqqur06c//WmNjY3p93//93XgwAH953/+p9asWbMov9cM/0X2ByrO9Sc5rZT9bNpvvNK+Ncu0undJr/+s9Lpfe0LAeWuk6z4tXbk1XYs/aX9g5MmM99/tl45+beoDJQ+k6yv/QnrzT6QbPp+9XXNh92FChfv+F6QrVkhv/91Z33r3de+Wz+PTgWcP6GfP/KwIwwE4W0UNd6Ojo7rqqqu0c+fOOb8fjUZ155136q677tLPfvYzLVmyRDfddJMSifStQf7yL/9SfX19uvvuu/Xtb39bP/rRj/Tud7975vunTp3SjTfeqMsvv1wPPPCAtm/frn/4h3/QZz/72YLvXz4uuOCCmYA3MjKip59+uqABLxKJ6IMf/KA6Ojq0du1a3XrrrTp+/HjO2xkfH9cjjzyiL37xi/rgBz+oxsZGXXTRRbr88sv1kY98RPF4XNdcc43+53/+R9///vd1/fVzX/Nz1l71v6U/eVy6srUw25/20jH7ma7TXO6pT++67E+iTjvvSvu08q+HzReftUPbSxmPs/nVQenBrfZ9+ma265Je+4/Sb//H1GnXKUtq7ceq/fope2Ah/IY0PCY9PCwN/iLrW8uXLNdfvMY+oszRO6BMWSVCkvX1r3995tepVMq6+OKLre3bt8/UXnjhBcvv91v/8R//YVmWZR06dMiSZN1///0zPf/93/9tuVwu69lnn7Usy7I+85nPWBdccIGVTCZnetra2qwrrrhiwbM9/fTTliTr6aefnvW9l156yTp06JD10ksvLXh7CzEyMmLdf//91v333289/fTTViqVOuttjo2NWc8++6z1xBNPWEeOHLGeeeYZ69ixY9aJEyesF154wTp9+rSVSCSsiYmJWb9f5n6+8MIL1o9+9CPrzjvvtN71rndZ1157reXz+SxJsxav12tdd9111le+8hVrcnLyrPehJJx63LK+7LKsrxiWNXYqXX8hZlkvDs3un0ha1sn+7Nr//LZlfVmW9eTn07XRpy3rh+st69A/F2RsIMtnWy3r2MCc33pg6AFL/yDL+zGv9eypZ8/xYMDi+U3//3aykv207ODgoI4dO6Y3velNM7XzzjtP69at03333ac///M/13333afzzz9fr3vd62Z63vSmN8ntdutnP/uZ/vRP/1T33Xef3vCGN8jnS1+Ef9NNN+kTn/iEnn/+eV1wwQX6dclkMuuhwvF4Hs/iPEsXXXSRUqmUjh49qmPHjsntduuSS2Y/OmghXnrpJT333HP65S9/ueCjgC6XS16vd2ZxuVwaGRnRu9/97pnblvy6l73sZbr66quzliuvvFKGUcZHl5K/kp7+v/Y93qY/kby0zv60adX59vNrq66w6+dNnWJOTaafy3kyZn+gwlttf8p3+kMw1VPXGD7SIa16R7r2hm+cg50CJG38xBm/dW3NtQrVhvTjoz/WXQfv0sfe+LFzOBiAs1Wy4e7YMft01a/fUHfFihUz3zt27JiWL1+e9X2v16sLL7wwqycQCMzaxvT35gp3d9xxhz760Y8uzo6cheXLl8uyLD399NMaGhqS2+1e8LPtLMvS6dOndezYMZ08mf7k5JIlS3TBBRcolUrN3ER5YmJCk5OTM7+2LEuWZWl8fFzj4+knX7z44ot6+umnJUmXXXbZrCC3cuVK+xYuxfTk5+wwdtn/Wpx7yB27Wzqw0X5iRaDJPk3qctlPbMh8goVkn06NRaXAbfaNkCX7UWMut728NGw/r1aSVr3L/pCFb/afP+Cc++YOyVgi3Zj+b+b9r3//TLj78O98WH7v3I9rAlB6SjbcFVN7e7tuv/32mV8/++yzRbvT9IoVK5RKpfTss8/qmWeekdvtnhVoM1mWpeeff17Hjh3Tiy++OFM///zzdfHFF2vJkiVy/YYnJ1iWNRP8MpeXXnpJk5OT2rVrl17zmtfo5S8v0UdPnYxJQ/8lnXfm52ie0bPfkR6/S1r59vSnWC/9Y/s+e6/8E/sRbx6f/eGJR//RvuXKG74h+adv32JJo09lX3PnrpLeelgyL82+Jc6KN0p/dpynPqD4ut4r3X6X9Eqf9NgGqXqZJOnmNTfrlcteqWdOPaOv9n1V77jqHUUeFMBClez/WaaPUD333HNZD9997rnndPXVV8/0/PrF/xMTE/rVr341s/7FF1+s5557Lqtn+tdnOgrm9/uzHip86tSpOfvOlZqaGqVSKQ0PD+vo0aNyuVx6xStekdUzOTmpEydO6LnnntPY2Jgk+9TqRRddpBUrViz41KjL5ZLH45HH48l6DxKJhOLxuK666qrSPs16+a32I8HyCXe/esB+Rq01mQ53Y89Lgb+ybyQ9fX89l1t6+utS/LB9K5JLpx7n9MqbpWVrpJe/Pnu71XPc5sXjkzyvmF0HzrW/aJX+8bPSdauk5Isz4a7KU6VN129Se2+77vzZnfrr1/71b/yHIYDSUbL3uQsEArr44ouz7sF26tQp/exnP9MNN9wgSbrhhhv0wgsv6IEH0reIuOeee5RKpbRu3bqZnh/96EdZpxfvvvtuXXHFFXOeki1Vl1xyyczp5Keeekq//KX9nNCxsTE988wz+sUvfqGnn35aY2Nj8nq9uuSSS/Ta175Wl19+eWmHscX28uvta+Ne/rp5W2ep+QOp9s+lNemjtnrhUengZin2yezeV7VL6/7dfubqtOpLpYsb7fvNAeViRUDqH5C+EZMuyP4Hb/O1zTK8hh4YfkD3PXPfGTYAoNQUNdydPn1aDz30kB566CFJ9ocoHnrooZmjU1u2bNHHP/5xffOb39Qjjzyid7zjHbrkkkt08803S5LWrl2rP/iDP9DGjRt14MAB/eQnP9HmzZv153/+5zMfPviLv/gL+Xw+hcNh9fX16atf/aq6u7uzTruWA5fLpVe+8pUzR+wGBwf1xBNP6JFHHtGxY8c0OTkpwzB0+eWX67Wvfa0uueQSVVXl/tSKipGalOJPZNce+Yh09CvSqVi6dtFvSRffaB+9s1Lp+qrb7Gv68r2v3OkB6dFO6Yl/y299YDEtv3zO8kXVF+kvX/OXkqTun3Wfy4kAnIWinpY9ePCg3vjGN878ejpwNTU1adeuXWptbdXo6Kje/e5364UXXlAoFNJ3v/vdrCNRX/7yl7V582Y1NjbK7XZrw4YNuvPO9L2ZzjvvPH3ve9/Tpk2bdN111+miiy5SR0dH1r3wyoXL5VJtba0sy9KJEyf0wgsvSLI/pbpixQqdd955nDZ58VkpOSL5l0vVGZ8utlLpT6q++Kz07TX2NXRvO5U+3fqKBvuauYxHw8l3vvT7/7P4c8afkH7x99IFV0vB5sXfPpCP409J7/4D6ZqrpY/Yzx7+m9f/jT734Oe099BePXPqGb1y2RyXGQAoKS5roffGqGDPPPOMLrvsMj399NOzHpOVSCQ0ODioQCBwzk5/WpalZ599VuPj41q+fLmWLFky/0pnqRj7mZeff0jq/6S0tlW65hPS4Jekvo9Ll7xFunbq1KplSf/3FdLkmHTTgfQtTCwr+0MPhfRCn/RYt1R9mfSayLn5PYH5fPyvpMiXJVPSU09Jr6iVJP3ert/TD5/6of4u9HfqbOws7oxADn7T/7+drGSvucOZTZ+iDQQC5yTYlZWqZZJZk33d26nH7E+2Tpu+lcn/ej4d7Kbr58r5r5LWfZZgh9LS9u/SH6yS/uPOmWAnSR9Y9wFJ0r8+8K96afylM60NoESU7Kdlgby8psNeptXcKP3ut+zbmWRaMvc1RkBFq/JJ//3krPJbr3irLj/vcj118il95dGv6J3XLMI9JAEUDEfu4GzGcvtedcZFxZ4EKD/Hn5JGjsrr9mrT9Zsk2R+s4GoeoLQR7gAAs+3ulK5YJTXfKEkKXxuW6TX18HMP6/8d/X9FHg7Ab0K4K6SJUXvJ/Ffu5Jhdm0yeoTfjdhup8anexMJ685BKpRSNRhUMBuX3+1VbW6vOTi6YBire0vOkF1LSzwelk8d1oXmh/vq1fy1JuvNnd86zMoBiItwV0p6l9pI8ka7Fttu1g5uze/cut+ujR9O1wzvt2v5wdu++lXb9ZMb92AZ25TVie3u7tm3bpkgkokOHDmn37t2znucLoAL9yWbpc38n9T8nnWc/8vD9694vSfp6/9d19OTR37Q2gCIi3FWweDyu7u5uRaNRNTU1qa6uTqFQSM3N3HcNgKR3dUpLzp/55auWv0qNgUalrJQ+c/9nijcXgN+I+9wtQN73uZsYtV891enbbEyOSda45PJm3yx3ptdM32w3NS6lxqaea2rM3+vO7YkUBw4c0Lp16zQwMKBAIPAbe8vmPncAFl8qJf3rh6TXNuibF1Vp/VfW6wLjAj1z+zOqrqou9nTAGXGfOyw+7xJ7ybx/msdn1zKDXVZvxo/EXTXVayysN0emaea8DoAKtPWPpfd1SeEmvWXlmxU4P6DnE8/ry7/4crEnAzAHwl0Fq6+vl2ma6u3tLfYoAErZ+z4uLXNJv3edPKlJbX69fc3wnQfu5LYoQAki3FUwwzDU1tam1tZWfeELX9CTTz6p/fv363Of+1yxRwNQSuqulY4MSXf9UDKX6l3XvEtLqpbo0eOP6t4j9xZ7OgC/hnBX4SKRiD74wQ+qo6NDa9eu1a233qrjx48XeywApeaCi2e+PN+3TE2vmbotygFuiwKUGsJdhXO73frwhz+sI0eOaGxsTE899ZTa29uLPRaAUvXYz6TfuUT/GItLkvb179Pg84NFHgpAJsIdAGDhPhORfvqcLox+RX98+e/LkqWd9+8s9lQAMhDuAAALt+3/Sm8JSt/aq5bfvl2S9G8//zedHjtd5MEATCPcAQAWzlwqfftx6Yb1+sP6P1TwwqBOJk/qS7/4UrEnAzCFcAcAyIvb5dbHL32rLhy3nzfLbVGA0kC4AwDk51MtuuUvu/TdA27FTsTUO8g9M4FSQLgDAOTnglfIlZBe/YxXvkmp+2fdxZ4IgAh3AIB8vfMfpS9+VE/f+6DGPNJ3Dn9HT/zqiWJPBVQ8wh0AIH9/1aHVy6/UHwb/0L4tygFuiwIUG+EOAHDWPnDde/XVX0iP3ftZxZPxYo8DVDTCHQDgrN34DxHd8n+lL3zzRX3hwV3FHgeoaIQ7AMBZc7Vtl3WeS9+/Utpx4E6lrFSxRwIqFuEOAHD2rnmzTg88pfe8bpn6n39C33vye8WeCKhYhLtCmhi1l8wbe06O2bXJ5Bl6M/61mxqf6k0srDcPqVRK0WhUwWBQfr9ftbW16uzszGtbACrbyy68TO+6+l2S7JsaA+Vq586dWrlypQzD0Lp163TgwIHf2P+1r31Na9askWEYes1rXqP/+q//OkeTzo1wV0h7ltpL8kS6Fttu1w5uzu7du9yujx5N1w7vtGv7w9m9+1ba9ZOxdG1gV14jtre3a9u2bYpEIjp06JB2796tFStW5LUtANj8+s1yyaX/fuK/9eSvniz2OEDOvvrVr+r222/XRz7yEf385z/XVVddpZtuuknHjx+fs/+nP/2p3v72tyscDuvBBx/UzTffrJtvvlmPPvroOZ48jXBXweLxuLq7uxWNRtXU1KS6ujqFQiE1NzcXezQAZaruwjr9U+M/6QdNP9CqC1YVexwgZ5/61Ke0ceNGvfOd79SVV16pu+66S9XV1fr3f//3Ofu7u7v1B3/wB9q6davWrl2rf/zHf9S1116rHTt2nOPJ07xF+50rwS2n7VdPdbq2dqu0Zovk+rW3fsPUvwg8Zrq2epMU3Ci5PNm964/M7l11W87jxWIxJZNJNTY25rwuAJzJ/w7972KPAORlbGxMDzzwgNrb22dqbrdbb3rTm3TffffNuc59992n22+/Pat200036Rvf+EYhR/2NCHeF5F0yu+bxSfItrNddZS8L7c2RaZrzNwEAUObi8bhOnTo182u/3y+/3z+r78SJE5qcnJx1edKKFSvU398/57aPHTs2Z/+xY8cWYfL8VNRp2VwvkHS6+vp6maap3l4e9g0AcK4rr7xS55133sxyxx13FHukgqqYI3fTF0jeddddWrdunT796U/rpptu0mOPPably5cXe7yiMAxDbW1tam1tlc/nU0NDg0ZGRtTX16dwODz/BgAAKAOHDh3SpZdeOvPruY7aSdJFF10kj8ej5557Lqv+3HPP6eKLL55znYsvvjin/nOhYo7c5XqBZKWIRCL64Ac/qI6ODq1du1a33nrrGT8RBABAOXrZy16mZcuWzSxnCnc+n0/XXXdd1hmtVCql3t5e3XDDDXOuc8MNN8w6A3b33Xefsf9cqIgjd7leIJlMJpVMpu9DF4879zmJbrdbH/7wh/XhD3+42KMAAFB0t99+u5qamvS6171Or3/96/XpT39ao6Ojeuc73ylJesc73qFLL7105tTuBz7wAf3u7/6uPvnJT+otb3mLvvKVr+jgwYP67Gc/W7R9qIhwl+sFknfccYc++tGPnqvxAABAibj11ls1MjKijo4OHTt2TFdffbW++93vzmSIo0ePyu1On/j87d/+be3evVt///d/r7/7u79TfX29vvGNb+jVr351sXahMsJdrtrb27M+1vzss8/qyiuvLOJEAADgXNm8ebM2b9485/fuvffeWbW3ve1tetvb3lbgqRauIsJdrhdI/vpHpDM/Pg0AAFDKKuIDFflcIAkAAFCOKuLInTT/BZIAAABOUDHhbr4LJAEAAJygYsKd9JsvkAQAAHCCirjmDgAAoFJU1JG7fKVSKUnS8PDwrO9NTExoYmJCY2NjWfe9cZqxsTFNTEzo2LFj8nr5YwMAKH3T/9+e/v94peD/0gswfQuV17/+9bO+d/nll+uuu+7KeqKFU504cUItLS166qmnij0KAAAL9txzz6m2trbYY5wzLsuyrGIPUeomJib04IMPasWKFbOOzk1MTCgej+vyyy+XYRhFmrDwXnzxRe3fv1+XXXaZzjvvvGKPU1Li8biuvPJKHTp0SC972cuKPU7J4H05M96bufG+zI335czme29SqZSee+45XXPNNRV11qly9vQseL1eXX/99XN+L5FI6KWXXpLP55PP5zvHk5074+PjkuxHtl100UVFnqa0TN/k+tJLL9WyZcuKPE3p4H05M96bufG+zI335cwW8t5U0hG7ac69SKwUTIzaS+bB0ckxuzaZPENvxnUBqfGp3sTCevOQSqUUjUYVDAbl9/tVW1urzs7OvLYFAACKj3BXSHuW2kvyRLoW227XDv7aLVn2Lrfro0fTtcM77dr+cHbvvpV2/WQsXRvYldeI7e3t2rZtmyKRiA4dOqTdu3dz7z8AAMoYp2UrWDweV3d3t3bs2KGmpiZJUl1dnUKh0Kxel8ul8847z9GnnvPl9/v1kY98JOt5xOB9+U14b+bG+zI33pcz472ZGx+oOEuJREKDg4MKBAKzP1AxMWq/eqoll8v+enJMssYll1fy+OfoNSXX1AHV1LiUGpNcHsljzN/rrspp9gMHDmjdunUaGBhQIBDIfz8BAEDJ4MhdIXmXzK55fJLmOPo1V6+7au7AdqbeHJmmmfM6AACgtHHNXQWrr6+XaZrq7e0t9igAAGCRcOSughmGoba2NrW2tsrn86mhoUEjIyPq6+tTOByefwMAAKDkEO4qXCQSkdfrVUdHh4aGhlRTU6OWlpZijwUAAPLEadkKEo/H9fjjj+vhhx/WwYMH9fzzz8vtduvDH/6wjhw5otHRUd177736oz/6I/385z/X4cOHlUhk32Pv6NGj+tM//VO94hWv0LJly3TLLbfMPJ5t2sqVK+VyubKWbdu2nctdzckdd9yh66+/Xi972cu0fPly3XzzzXrssceyehKJhDZt2qSXv/zlWrp0qTZs2DBrv48ePaq3vOUtqq6u1vLly7V161ZNTExk9dx777269tpr5ff7FQwGtWvXrkLv3lk5V+/NvffeO+vPjMvl0rFjx87JfuZqsd6X97///bruuuvk9/t19dVXz/l7/eIXv9Dv/M7vyDAMXXbZZYpGo4XarbN2rt6XI0eOzPnnZf/+/YXcvbOyGO/Nww8/rLe//e267LLLZJqm1q5dq+7u7lm/Vzn9PXOu3pdy+zvmbBHuKkgqlVJ1dfWcd+u2LEtPPPGEksmkgsGgrrzySvn9fh0+fFiTk5Mz64fDYblcLt1zzz36yU9+orGxMb31rW+d9VDmj33sYxoeHp5Z/uZv/uac7GM+fvjDH2rTpk3av3+/7r77bo2Pj+vGG2/U6OjoTM/f/u3f6lvf+pa+9rWv6Yc//KGGhob0Z3/2ZzPfn5yc1Fve8haNjY3ppz/9qT7/+c9r165d6ujomOkZHBzUW97yFr3xjW/UQw89pC1btqi5uVn/8z//c073Nxfn6r2Z9thjj2X9uVm+fPk52c9cLcb7Mu1d73qXbr311jl/n1OnTunGG2/U5ZdfrgceeEDbt2/XP/zDP+izn/1swfbtbJyr92Xa97///aw/L9ddd92i79NiWYz35oEHHtDy5cv1pS99SX19ffrwhz+s9vZ27dixY6an3P6eOVfvy7Ry+TvmrFk4Ky+99JJ16NAh66WXXir2KDm5//77rV/96lczv37ppZes+++/33rxxRdnaqlUynrwwQet48ePWy+99JL1wAMPWIFAwDp58uRMzwsvvGC5XC7r7rvvnqldfvnlVldX1znZj0I4fvy4Jcn64Q9/aFmWvY9VVVXW1772tZmeWCxmSbLuu+8+y7Is67/+678st9ttHTt2bKbnX/7lX6xly5ZZyWTSsizLam1ttV71qldl/V633nqrddNNNxV6lxZNod6bH/zgB5Yk6/nnnz93O7OI8nlfMn3kIx+xrrrqqln1z3zmM9YFF1ww8z5ZlmW1tbVZV1xxxeLvRAEU6n0ZHBy0JFkPPvhgoUYvuLN9b6a9733vs974xjfO/Lrc/54p1PtS7n/H5Iojd5CkmSNvrun78U197Xa7dfr0aUn20T2Xy5V1s0jDMOR2u/XjH/84a3vbtm3Ty1/+cl1zzTXavn37rNOTpezkyZOSpAsvvFCS/a/C8fFxvelNb5rpWbNmjWpra3XfffdJku677z695jWvyXq6x0033aRTp06pr69vpidzG9M909soB4V6b6ZdffXVqqmp0Zvf/Gb95Cc/KfTuLJp83peFuO+++/SGN7wh6+bhN910kx577DE9//zzizR94RTqfZn2J3/yJ1q+fLlCoZC++c1vLs7Q58hivTcnT56c2YZU/n/PFOp9mVauf8fkinAHSXZI8/l8evbZZzUxMaFUKqXh4WGNjY1pfNx+bq3f75dpmmpra9OLL76o0dFRfehDH9Lk5KSGh4dntvX+979fX/nKV/SDH/xA73nPe/RP//RPam1tLdau5SSVSmnLli1qaGjQq1/9aknSsWPH5PP5dP7552f1rlixYuZ6jWPHjs16bNv0r+frOXXqlF566aVC7M6iKuR7U1NTo7vuukt79+7V3r17ddlll+n3fu/39POf/7zAe3X28n1fFmIh712pKuT7snTpUn3yk5/U1772NX3nO99RKBTSzTffXDYBb7Hem5/+9Kf66le/qne/+90ztXL+e6aQ70s5/x2TDz4tC0mS2+1WXV2djhw5ooceekiStGzZMp133nmyph5i4vF49OlPf1rvec97dOedd8rtduvtb3+7rr32Wrnd6X8n3H777TNfv/a1r5XP59N73vMe3XHHHSX/iJhNmzbp0UcfnXUkEoV9b6644gpdccUVM7/+7d/+bT355JPq6urSF7/4xUX//RYTf2bmVsj35aKLLsr6e+b666/X0NCQtm/frj/5kz9Z9N9vsS3Ge/Poo49q/fr1+shHPqIbb7xxEacrnkK+L+X8d0w+OHKHGUuWLNGrXvUqXX311brqqqu0evVqTUxMZAWyUCikJ598UsePH9eJEyf0xS9+Uc8++6xWrVp1xu2uW7dOExMTOnLkyDnYi/xt3rxZ3/72t/WDH/xAr3zlK2fqF198scbGxvTCCy9k9T/33HO6+OKLZ3p+/RN/07+er2fZsmUl/7SQQr83c3n961+vJ554YpH2oDDO5n1ZiHzfu2Ir9Psyl3Xr1pX8nxdpcd6bQ4cOqbGxUe9+97v193//91nfK9e/Zwr9vsylHP6OyRfhDrN4vV5VVVUpkUhodHR01uFwyf6X8/nnn6977rlHx48f/43/Wn7ooYfkdrtL9lNJlmVp8+bN+vrXv6577rln1nN2r7vuOlVVVWU9yeOxxx7T0aNHdcMNN0iSbrjhBj3yyCM6fvz4TM/dd9+tZcuW6corr5zp+fWngdx9990z2yhF5+q9mctDDz2kmpqaRd6jxbEY78tC3HDDDfrRj340c2mEZL93V1xxhS644IKz35FFdq7el7mU8p8XafHem76+Pr3xjW9UU1OTOjs7Z/0+5fb3zLl6X+ZS6n9mzkrxPsvhDOX0admJiQlrdHTUGh0dte6//37r2LFj1ujoqJVIJCzLsqxf/vKX1qlTp6xEImE9//zz1sMPP2w9/vjjlmWl9/PLX/6ydd9991lPPPGE9cUvftG68MILrdtvv33m9/jpT39qdXV1WQ899JD15JNPWl/60pesV7ziFdY73vGOouzzQrz3ve+1zjvvPOvee++1hoeHZ5bMTw63tLRYtbW11j333GMdPHjQuuGGG6wbbrhh5vsTExPWq1/9auvGG2+0HnroIeu73/2u9YpXvMJqb2+f6RkYGLCqq6utrVu3WrFYzNq5c6fl8Xis7373u+d0f3Nxrt6brq4u6xvf+Ib1+OOPW4888oj1gQ98wHK73db3v//9c7q/C7UY74tlWdbjjz9uPfjgg9Z73vMea/Xq1daDDz5oPfjggzOfjn3hhResFStWWH/9139tPfroo9ZXvvIVq7q62vrXf/3Xc7q/C3Wu3pddu3ZZu3fvtmKxmBWLxazOzk7L7XZb//7v/35O9zcXi/HePPLII9YrXvEK66/+6q+ytnH8+PGZnnL7e+ZcvS/l9nfM2SLcnaVyCnenTp2y7r///lnLwMCAZVmWdezYMevhhx+2Dh48aD388MPWM888Y01OTlqWld7Pj3/849aKFSusqqoqq76+3vrkJz9ppVKpmd/jgQcesNatW2edd955lmEY1tq1a61/+qd/mgmQpUjSnMv/9//9fzM9L730kvW+973PuuCCC6zq6mrrT//0T63h4eGs7Rw5csT6wz/8Q8s0Teuiiy6yPvjBD1rj4+NZPT/4wQ+sq6++2vL5fNaqVauyfo9SdK7em0984hNWXV2dZRiGdeGFF1q/93u/Z91zzz3najdztljvy+/+7u/OuZ3BwcGZnocfftgKhUKW3++3Lr30Umvbtm3naC9zd67el127dllr1661qqurrWXLllmvf/3rs26VUYoW4735yEc+Muc2Lr/88qzfq5z+njlX70u5/R1ztlyWNXW1PPKSSCQ0ODioQCAgwzCKPU7BVMp+AgBQ7rjmDgAAwEEIdxUulUopGo0qGAzK7/ertrZ2wRejAgCA0sN97gppYurZeJ5qafrJD5NjkjUuubySxz9Hrym5pjJ3alxKjUkuj+Qx5u91V+U8Ynt7u3p6etTV1aVQKKTh4WH19/fnvB0AAFAaOHJXSHuW2kvyRLoW227XDm7O7t273K6PHk3XDu+0a/vD2b37Vtr1k7F0bWBXzuPF43F1d3crGo2qqalJdXV1CoVCam5uznlbAACgNBDuKlgsFlMymVRjY2OxRwEAAIuE07KFdMtp+9VTna6t3Sqt2WKfls20YeoGr56MO4iv3iQFN9qnZTOtPzK7d9VtOY9XyncrBwAA+eHIXSF5l9jL9PV2kuTx2TWP/wy9GT8Sd9VUr7Gw3hzV19fLNM1ZdzMHAADliyN3FcwwDLW1tam1tVU+n08NDQ0aGRlRX1+fwuHw/BsAAAAlh3BX4SKRiLxerzo6OjQ0NKSamhq1tLQUeywAAJAnnlBxlirlyQ2Vsp8AAJQ7rrkDgDxNTk4qlUoVewwAyEK4A+AIX/jCF/Tyl79cyWQyq37zzTfrr//6ryVJ+/bt07XXXivDMLRq1Sp99KMf1cTExEzvpz71Kb3mNa/RkiVLdNlll+l973ufTp8+PfP9Xbt26fzzz9c3v/lNXXnllfL7/Tp69KgAoJQQ7gA4wtve9jZNTk7qm9/85kzt+PHj+s53vqN3vetd+n//7//pHe94hz7wgQ/o0KFD+td//Vft2rUr63F7brdbd955p/r6+vT5z39e99xzj1pbW7N+nxdffFGf+MQn9G//9m/q6+vT8uXLz9k+AsBCcM3dWaqUa9EqZT9R3t73vvfpyJEj+q//+i9J9pG4nTt36oknntCb3/xmNTY2qr29fab/S1/6klpbWzU0NDTn9v7zP/9TLS0tOnHCfsrMrl279M53vlMPPfSQrrrqqsLvEADkgU/LAnCMjRs36vrrr9ezzz6rSy+9VLt27dJtt90ml8ulhx9+WD/5yU+yjtRNTk4qkUjoxRdfVHV1tb7//e/rjjvuUH9/v06dOqWJiYms70uSz+fTa1/72mLtIgDMi3AHwDGuueYaXXXVVfrCF76gG2+8UX19ffrOd74jSTp9+rQ++tGP6s/+7M9mrWcYho4cOaI//uM/1nvf+151dnbqwgsv1I9//GOFw2GNjY3NhDvTNOXKvDE5AJQYwh0AR2lubtanP/1pPfvss3rTm96kyy67TJJ07bXX6rHHHlMwGJxzvQceeECpVEqf/OQn5XbblyPv2bPnnM0NAIuFcAfAUf7iL/5CH/rQh9TT06MvfOELM/WOjg798R//sWpra/W//tf/ktvt1sMPP6xHH31UH//4xxUMBjU+Pq7/83/+j9761rfqJz/5ie66664i7gkA5IdPywJwlPPOO08bNmzQ0qVLdfPNN8/Ub7rpJn3729/W9773PV1//fX6rd/6LXV1denyyy+XJF111VX61Kc+pU984hN69atfrS9/+cu64447irQXAJA/Pi17lirlU6SVsp9whsbGRr3qVa/SnXfeWexRAOCc47QsAMd4/vnnde+99+ree+/VZz7zmWKPAwBFQbgD4BjXXHONnn/+eX3iE5/QFVdcUexxAKAouOauwqVSKUWjUQWDQfn9ftXW1mbdBwwoJ0eOHNHJkyf1oQ99qNijAEDRcOSukCZG7VdPtTR9X6zJMckal1xeyeOfo9eUXFOZOzUupcYkl0fyGPP3uqtyHrG9vV09PT3q6upSKBTS8PCw+vv7c94OAAAoDRy5K6Q9S+0leSJdi223awc3Z/fuXW7XRzMeQn54p13bH87u3bfSrp+MpWsDu3IeLx6Pq7u7W9FoVE1NTaqrq1MoFFJzc3PO2wIAAKWBcFfBYrGYksmkGhsbiz0KAABYJJyWLaRbTtuvnup0be1Wac0W+7Rspg3Hp3rNdG31Jim40T4tm2n9kdm9q27LeTzTNOdvAgAAZYUjd4XkXWIvmc+h9PjsWub1dlm9GT8Sd9VUr7Gw3hzV19fLNE319vbmvC4AAChNHLmrYIZhqK2tTa2trfL5fGpoaNDIyIj6+voUDofn3wAAACg5hLsKF4lE5PV61dHRoaGhIdXU1KilpaXYYwEAgDzx+LGzVCmP5aqU/QQAoNxxzR0AAICDEO4AAAAchHAHAADgIIQ7AAAAByHcAQAAOAjhDgAAwEEIdwAAAA5CuAMAAHAQwh0AAICDEO4AAAAchHAHAADgIIQ7AAAAByHcVbhUKqVoNKpgMCi/36/a2lp1dnYWeywAAJAnb7EHcLSJUfvVUy25XPbXk2OSNS65vJLHP0evKbmmMndqXEqNSS6P5DHm73VX5Txie3u7enp61NXVpVAopOHhYfX39+e8HQAAUBo4cldIe5baS/JEuhbbbtcObs7u3bvcro8eTdcO77Rr+8PZvftW2vWTsXRtYFfO48XjcXV3dysajaqpqUl1dXUKhUJqbm7OeVsAAKA0EO4qWCwWUzKZVGNjY7FHAQAAi4TTsoV0y2n71VOdrq3dKq3ZYp+WzbTh+FSvma6t3iQFN9qnZTOtPzK7d9VtOY9nmub8TQAAoKxw5K6QvEvsZfp6O0ny+Oxa5vV2Wb0ZPxJ31VSvsbDeHNXX18s0TfX29ua8LgAAKE0cuatghmGora1Nra2t8vl8amho0MjIiPr6+hQOh+ffAAAAKDmEuwoXiUTk9XrV0dGhoaEh1dTUqKWlpdhjAQCAPLksy7KKPUQ5SyQSGhwcVCAQkGEY869QpiplPwEAKHdccwcAAOAghDsAAAAHIdwBAAA4COEOAADAQQh3AAAADkK4AwAAcBDCHQAAgIMQ7gAAAByEcAcAAOAghDsAAAAHIdwBAAA4COEOAADAQQh3FS6VSikajSoYDMrv96u2tladnZ3FHgsAAOTJW+wBHG1i1H71VEsul/315JhkjUsur+Txz9FrSq6pzJ0al1JjkssjeYz5e91VOY/Y3t6unp4edXV1KRQKaXh4WP39/TlvBwAAlAaO3BXSnqX2kjyRrsW227WDm7N79y6366NH07XDO+3a/nB2776Vdv1kLF0b2JXzePF4XN3d3YpGo2pqalJdXZ1CoZCam5tz3hYAACgNhLsKFovFlEwm1djYWOxRAADAIuG0bCHdctp+9VSna2u3Smu22KdlM204PtVrpmurN0nBjfZp2Uzrj8zuXXVbzuOZpjl/EwAAKCscuSsk7xJ7mb7eTpI8PruWeb1dVm/Gj8RdNdVrLKw3R/X19TJNU729vTmvCwAAShNH7iqYYRhqa2tTa2urfD6fGhoaNDIyor6+PoXD4fk3AAAASg7hrsJFIhF5vV51dHRoaGhINTU1amlpKfZYAAAgTy7LsqxiD1HOEomEBgcHFQgEZBjG/CuUqUrZTwAAyh3X3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMJdhUulUopGowoGg/L7/aqtrVVnZ2exxwIAAHnyFnsAR5sYtV891ZLLZX89OSZZ45LLK3n8c/Sakmsqc6fGpdSY5PJIHmP+XndVziO2t7erp6dHXV1dCoVCGh4eVn9/f87bAQAApYEjd4W0Z6m9JE+ka7Htdu3g5uzevcvt+ujRdO3wTru2P5zdu2+lXT8ZS9cGduU8XjweV3d3t6LRqJqamlRXV6dQKKTm5uactwUAAEoD4a6CxWIxJZNJNTY2FnsUAACwSDgtW0i3nLZfPdXp2tqt0pot9mnZTBuOT/Wa6drqTVJwo31aNtP6I7N7V92W83imac7fBAAAygpH7grJu8Repq+3kySPz65lXm+X1ZvxI3FXTfUaC+vNUX19vUzTVG9vb87rAgCA0sSRuwpmGIba2trU2toqn8+nhoYGjYyMqK+vT+FweP4NAACAkkO4q3CRSERer1cdHR0aGhpSTU2NWlpaij0WAADIk8uyLKvYQ5SzRCKhwcFBBQIBGYYx/wplqlL2EwCAcsc1dwAAAA5CuAMAAHAQwh0AAICDEO4AAAAchHAHAADgIIQ7AAAAByHcAQAAOAjhDgAAwEEIdwAAAA5CuAMAAHAQwh0AAICDEO4AAAAchHBX4VKplKLRqILBoPx+v2pra9XZ2VnssQAAQJ68xR7A0SZG7VdPteRy2V9PjknWuOTySh7/HL2m5JrK3KlxKTUmuTySx5i/112V84jt7e3q6elRV1eXQqGQhoeH1d/fn/N2AABAaeDIXSHtWWovyRPpWmy7XTu4Obt373K7Pno0XTu8067tD2f37ltp10/G0rWBXTmPF4/H1d3drWg0qqamJtXV1SkUCqm5uTnnbQEAgNJAuKtgsVhMyWRSjY2NxR4FAAAsEk7LFtItp+1XT3W6tnartGaLfVo204bjU71murZ6kxTcaJ+WzbT+yOzeVbflPJ5pmvM3AQCAssKRu0LyLrGX6evtJMnjs2uZ19tl9Wb8SNxVU73GwnpzVF9fL9M01dvbm/O6AACgNHHkroIZhqG2tja1trbK5/OpoaFBIyMj6uvrUzgcnn8DAACg5BDuKlwkEpHX61VHR4eGhoZUU1OjlpaWYo8FAADy5LIsyyr2EOUskUhocHBQgUBAhmHMv0KZqpT9BACg3HHNHQAAgIMQ7gAAAByEcAcAAOAghDsAAAAHIdwBAAA4COEOAADAQQh3AAAADkK4AwAAcBDCHQAAgIMQ7gAAAByEcAcAAOAghDsAAAAHIdxVuFQqpWg0qmAwKL/fr9raWnV2dhZ7LAAAkCdvsQdwtIlR+9VTLblc9teTY5I1Lrm8ksc/R68puaYyd2pcSo1JLo/kMebvdVflPGJ7e7t6enrU1dWlUCik4eFh9ff357wdAABQGjhyV0h7ltpL8kS6Fttu1w5uzu7du9yujx5N1w7vtGv7w9m9+1ba9ZOxdG1gV87jxeNxdXd3KxqNqqmpSXV1dQqFQmpubs55WwAAoDQQ7ipYLBZTMplUY2NjsUcBAACLhNOyhXTLafvVU52urd0qrdlin5bNtOH4VK+Zrq3eJAU32qdlM60/Mrt31W05j2ea5vxNAACgrHDkrpC8S+xl+no7SfL47Frm9XZZvRk/EnfVVK+xsN4c1dfXyzRN9fb25rwuAAAoTRy5q2CGYaitrU2tra3y+XxqaGjQyMiI+vr6FA6H598AAAAoOYS7CheJROT1etXR0aGhoSHV1NSopaWl2GMBAIA8uSzLsoo9RDlLJBIaHBxUIBCQYRjzr1CmKmU/AQAod1xzBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcVLpVKKRqNKhgMyu/3q7a2Vp2dncUeCwAA5Mlb7AEcbWLUfvVUSy6X/fXkmGSNSy6v5PHP0WtKrqnMnRqXUmOSyyN5jPl73VU5j9je3q6enh51dXUpFAppeHhY/f39OW8HAACUBo7cFdKepfaSPJGuxbbbtYObs3v3Lrfro0fTtcM77dr+cHbvvpV2/WQsXRvYlfN48Xhc3d3dikajampqUl1dnUKhkJqbm3PeFgAAKA2EuwoWi8WUTCbV2NhY7FEAAMAi4bRsId1y2n71VKdra7dKa7bYp2UzbTg+1Wuma6s3ScGN9mnZTOuPzO5ddVvO45mmOX8TAAAoKxy5KyTvEnuZvt5Okjw+u5Z5vV1Wb8aPxF011WssrDdH9fX1Mk1Tvb29Oa8LAABKE0fuKphhGGpra1Nra6t8Pp8aGho0MjKivr4+hcPh+TcAAABKDuGuwkUiEXm9XnV0dGhoaEg1NTVqaWkp9lgAACBPLsuyrGIPUc4SiYQGBwcVCARkGMb8K5SpStlPAADKHdfcAQAAOAjhDgAAwEEIdwAAAA5CuAMAAHAQwh0AAICDEO4AAAAchHAHAADgIIQ7AAAAByHcAQAAOAjhDgAAwEEIdwAAAA5CuAMAAHAQwl2FS6VSikajCgaD8vv9qq2tVWdnZ7HHAgAAefIWewBHmxi1Xz3Vkstlfz05Jlnjkssrefxz9JqSaypzp8al1Jjk8kgeY/5ed1XOI7a3t6unp0ddXV0KhUIaHh5Wf39/ztsBAAClgSN3hbRnqb0kT6Rrse127eDm7N69y+366NF07fBOu7Y/nN27b6VdPxlL1wZ25TxePB5Xd3e3otGompqaVFdXp1AopObm5py3BQAASgPhroLFYjElk0k1NjYWexQAALBIOC1bSLectl891ena2q3Smi32adlMG45P9Zrp2upNUnCjfVo20/ojs3tX3ZbzeKZpzt8EAADKCkfuCsm7xF6mr7eTJI/PrmVeb5fVm/EjcVdN9RoL681RfX29TNNUb29vzusCAIDSxJG7CmYYhtra2tTa2iqfz6eGhgaNjIyor69P4XB4/g0AAICSQ7ircJFIRF6vVx0dHRoaGlJNTY1aWlqKPRYAAMiTy7Isq9hDlLNEIqHBwUEFAgEZhjH/CmWqUvYTAIByxzV3AAAADkK4AwAAcBDCHQAAgIMQ7gAAAByEcAcAAOAghDsAAAAHIdwBAAA4COEOAADAQQh3AAAADkK4AwAAcBDCHQAAgIMQ7gAAAByEcFfhUqmUotGogsGg/H6/amtr1dnZWeyxAABAnrzFHsDRJkbtV0+15HLZX0+OSda45PJKHv8cvabkmsrcqXEpNSa5PJLHmL/XXZXziO3t7erp6VFXV5dCoZCGh4fV39+f83YAAEBp4MhdIe1Zai/JE+labLtdO7g5u3fvcrs+ejRdO7zTru0PZ/fuW2nXT8bStYFdOY8Xj8fV3d2taDSqpqYm1dXVKRQKqbm5OedtAQCA0kC4q2CxWEzJZFKNjY3FHgUAACwSTssW0i2n7VdPdbq2dqu0Zot9WjbThuNTvWa6tnqTFNxon5bNtP7I7N5Vt+U8nmma8zcBAICywpG7QvIusZfp6+0kyeOza5nX22X1ZvxI3FVTvcbCenNUX18v0zTV29ub87oAAKA0ceSughmGoba2NrW2tsrn86mhoUEjIyPq6+tTOByefwMAAKDkEO4qXCQSkdfrVUdHh4aGhlRTU6OWlpZijwUAAPLksizLKvYQ5SyRSGhwcFCBQECGYcy/QpmqlP0EAKDccc0dAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3FW4VCqlaDSqYDAov9+v2tpadXZ2FnssAACQJ2+xB3C0iVH71VMtuVz215NjkjUuubySxz9Hrym5pjJ3alxKjUkuj+Qx5u91V+U8Ynt7u3p6etTV1aVQKKTh4WH19/fnvB0AAFAaOHJXSHuW2kvyRLoW227XDm7O7t273K6PHk3XDu+0a/vD2b37Vtr1k7F0bWBXzuPF43F1d3crGo2qqalJdXV1CoVCam5uznlbAACgNBDuKlgsFlMymVRjY2OxRwEAAIuE07KFdMtp+9VTna6t3Sqt2WKfls204fhUr5murd4kBTfap2UzrT8yu3fVbTmPZ5rm/E0AAKCscOSukLxL7GX6ejtJ8vjsWub1dlm9GT8Sd9VUr7Gw3hzV19fLNE319vbmvC4AAChNHLmrYIZhqK2tTa2trfL5fGpoaNDIyIj6+voUDofn3wAAACg5hLsKF4lE5PV61dHRoaGhIdXU1KilpaXYYwEAgDy5LMuyij1EOUskEhocHFQgEJBhGPOvUKYqZT8BACh3XHMHAADgIIQ7AAAAByHcAQAAOAjhDgAAwEEIdwAAAA5CuAMAAHAQwh0AAICDEO4AAAAchHAHAADgIIQ7AAAAByHcAQAAOAjhDgAAwEEIdxUulUopGo0qGAzK7/ertrZWnZ2dxR4LAADkyVvsARxtYtR+9VRLLpf99eSYZI1LLq/k8c/Ra0quqcydGpdSY5LLI3mM+XvdVTmP2N7erp6eHnV1dSkUCml4eFj9/f05bwcAAJQGjtwV0p6l9pI8ka7Fttu1g5uze/cut+ujR9O1wzvt2v5wdu++lXb9ZCxdG9iV83jxeFzd3d2KRqNqampSXV2dQqGQmpubc94WAAAoDYS7ChaLxZRMJtXY2FjsUQAAwCLhtGwh3XLafvVUp2trt0prttinZTNtOD7Va6ZrqzdJwY32adlM64/M7l11W87jmaY5fxMAACgrHLkrJO8Se5m+3k6SPD67lnm9XVZvxo/EXTXVayysN0f19fUyTVO9vb05rwsAAEoTR+4qmGEYamtrU2trq3w+nxoaGjQyMqK+vj6Fw+H5NwAAAEoO4a7CRSIReb1edXR0aGhoSDU1NWppaSn2WAAAIE8uy7KsYg9RzhKJhAYHBxUIBGQYxvwrlKlK2U8AAMod19wBAAA4COEOAADAQQh3AAAADkK4AwAAcBDCHQAAgIMQ7gAAAByEcAcAAOAghDsAAAAHIdwBAAA4COEOAADAQQh3AAAADkK4AwAAcBDCXYVLpVKKRqMKBoPy+/2qra1VZ2dnsccCAAB58hZ7AEebGLVfPdWSy2V/PTkmWeOSyyt5/HP0mpJrKnOnxqXUmOTySB5j/l53Vc4jtre3q6enR11dXQqFQhoeHlZ/f3/O2wEAAKWBI3eFtGepvSRPpGux7Xbt4Obs3r3L7fro0XTt8E67tj+c3btvpV0/GUvXBnblPF48Hld3d7ei0aiamppUV1enUCik5ubmnLcFAABKA+GugsViMSWTSTU2NhZ7FAAAsEg4LVtIt5y2Xz3V6drardKaLfZp2Uwbjk/1muna6k1ScKN9WjbT+iOze1fdlvN4pmnO3wQAAMoKR+4KybvEXqavt5Mkj8+uZV5vl9Wb8SNxV031GgvrzVF9fb1M01Rvb2/O6wIAgNLEkbsKZhiG2tra1NraKp/Pp4aGBo2MjKivr0/hcHj+DQAAgJJDuKtwkUhEXq9XHR0dGhoaUk1NjVpaWoo9FgAAyJPLsiyr2EOUs0QiocHBQQUCARmGMf8KZapS9hMAgHLHNXcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwV0gTo/ZiWena5Jhdm0yeoTeVrqXGp3oTC+vNQyqVUjQaVTAYlN/vV21trTo7O/PaFgAAKD7CXSHtWWovyRPpWmy7XTu4Obt373K7Pno0XTu8067tD2f37ltp10/G0rWBXXmN2N7erm3btikSiejQoUPavXu3VqxYkde2AABA8XmLPQCKJx6Pq7u7Wzt27FBTU5Mkqa6uTqFQqMiTAQCAfLksK/OcIXKVSCQ0ODioQCAgwzCyvzkxar96qiWXy/56ckyyxiWXV/L45+g1JdfUAdXUuJQak1weyWPM3+uuymn2AwcOaN26dRoYGFAgEMh/PwEAQMngyF0heZfMrnl8knwL63VXzR3YztSbI9M0c14HAACUNq65q2D19fUyTVO9vb3FHgUAACwSjtxVMMMw1NbWptbWVvl8PjU0NGhkZER9fX0Kh8PzbwAAAJQcwl2Fi0Qi8nq96ujo0NDQkGpqatTS0lLssQAAQJ74QMVZqpQPGlTKfgIAUO645g4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuCmli1F4sK12bHLNrk8kz9KbStdT4VG9iYb15SKVSikajCgaD8vv9qq2tVWdnZ17bAgAAxUe4K6Q9S+0leSJdi223awc3Z/fuXW7XR4+ma4d32rX94ezefSvt+slYujawK68R29vbtW3bNkUiER06dEi7d+/WihUr8toWAAAoPm+xB0DxxONxdXd3a8eOHWpqapIk1dXVKRQKFXkyAACQL5dlZZ4zRK4SiYQGBwcVCARkGEb2NydG7VdPteRy2V9PjknWuOTySh7/HL2m5Jo6oJoal1JjkssjeYz5e91VOc1+4MABrVu3TgMDAwoEAvnvJwAAKBkcuSsk75LZNY9Pkm9hve6quQPbmXpzZJpmzusAAIDSxjV3Fay+vl6maaq3t7fYowAAgEXCkbsKZhiG2tra1NraKp/Pp4aGBo2MjKivr0/hcHj+DQAAgJJDuKtwkUhEXq9XHR0dGhoaUk1NjVpaWoo9FgAAyBMfqDhLlfJBg0rZTwAAyh3X3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMJdIU2M2otlpWuTY3ZtMnmG3lS6lhqf6k0srDcPqVRK0WhUwWBQfr9ftbW16uzszGtbAACg+Ah3hbRnqb0kT6Rrse127eDm7N69y+366NF07fBOu7Y/nN27b6VdPxlL1wZ25TVie3u7tm3bpkgkokOHDmn37t1asWJFXtsCAADF5y32ACieeDyu7u5u7dixQ01NTZKkuro6hUKhIk8GAADy5bKszHOGyFUikdDg4KACgYAMw8j+5sSo/eqpllwu++vJMckal1xeyeOfo9eUXFMHVFPjUmpMcnkkjzF/r7sqp9kPHDigdevWaWBgQIFAIP/9BAAAJYMjd4XkXTK75vFJ8i2s1101d2A7U2+OTNPMeR0AAFDauOaugtXX18s0TfX29hZ7FAAAsEg4clfBDMNQW1ubWltb5fP51NDQoJGREfX19SkcDs+/AQAAUHIIdxUuEonI6/Wqo6NDQ0NDqqmpUUtLS7HHAgAAeeIDFWepUj5oUCn7CQBAueOaOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgrpIlRe7GsdG1yzK5NJs/Qm0rXUuNTvYmF9eYhlUopGo0qGAzK7/ertrZWnZ2deW0LAAAUH+GukPYstZfkiXQttt2uHdyc3bt3uV0fPZquHd5p1/aHs3v3rbTrJ2Pp2sCuvEZsb2/Xtm3bFIlEdOjQIe3evVsrVqzIa1sAAKD4vMUeAMUTj8fV3d2tHTt2qKmpSZJUV1enUChU5MkAAEC+XJaVec4QuUokEhocHFQgEJBhGNnfnBi1Xz3Vkstlfz05Jlnjkssrefxz9JqSa+qAampcSo1JLo/kMebvdVflNPuBAwe0bt06DQwMKBAI5L+fAACgZHDkrpC8S2bXPD5JvoX1uqvmDmxn6s2RaZo5rwMAAEob19xVsPr6epmmqd7e3mKPAgAAFglH7iqYYRhqa2tTa2urfD6fGhoaNDIyor6+PoXD4fk3AAAASg7hrsJFIhF5vV51dHRoaGhINTU1amlpKfZYAAAgT3yg4ixVygcNKmU/AQAod1xzBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHeFNDFqL5aVrk2O2bXJ5Bl6U+laanyqN7Gw3jykUilFo1EFg0H5/X7V1taqs7Mzr20BAIDiI9wV0p6l9pI8ka7Fttu1g5uze/cut+ujR9O1wzvt2v5wdu++lXb9ZCxdG9iV14jt7e3atm2bIpGIDh06pN27d2vFihV5bQsAABSft9gDoHji8bi6u7u1Y8cONTU1SZLq6uoUCoWKPBkAAMiXy7IyzxkiV4lEQoODgwoEAjIMI/ubE6P2q6dacrnsryfHJGtccnklj3+OXlNyTR1QTY1LqTHJ5ZE8xvy97qqcZj9w4IDWrVungYEBBQKB/PcTAACUDI7cFZJ3yeyaxyfJt7Bed9Xcge1MvTkyTTPndQAAQGnjmrsKVl9fL9M01dvbW+xRAADAIuHIXQUzDENtbW1qbW2Vz+dTQ0ODRkZG1NfXp3A4PP8GAABAySHcVbhIJCKv16uOjg4NDQ2ppqZGLS0txR4LAADkiQ9UnKVK+aBBpewnAADljmvuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4a6QJkbtxbLStckxuzaZPENvKl1LjU/1JhbWm4dUKqVoNKpgMCi/36/a2lp1dnbmtS0AAFB8hLtC2rPUXpIn0rXYdrt2cHN2797ldn30aLp2eKdd2x/O7t230q6fjKVrA7vyGrG9vV3btm1TJBLRoUOHtHv3bq1YsSKvbQEAgOLzFnsAFE88Hld3d7d27NihpqYmSVJdXZ1CoVCRJwMAAPlyWVbmOUPkKpFIaHBwUIFAQIZhZH9zYtR+9VRLLpf99eSYZI1LLq/k8c/Ra0quqQOqqXEpNSa5PJLHmL/XXZXT7AcOHNC6des0MDCgQCCQ/34CAICSwZG7QvIumV3z+CT5Ftbrrpo7sJ2pN0emaea8DgAAKG1cc1fB6uvrZZqment7iz0KAABYJBy5q2CGYaitrU2tra3y+XxqaGjQyMiI+vr6FA6H598AAAAoOYS7CheJROT1etXR0aGhoSHV1NSopaWl2GMBAIA88YGKs1QpHzSolP0EAKDccc0dAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEuwqXSqUUjUYVDAbl9/tVW1urzs7OYo8FAADy5C32AI42MWq/eqoll8v+enJMssYll1fy+OfoNSXXVOZOjUupMcnlkTzG/L3uqpxHbG9vV09Pj7q6uhQKhTQ8PKz+/v6ctwMAAEoDR+4Kac9Se0meSNdi2+3awc3ZvXuX2/XRo+na4Z12bX84u3ffSrt+MpauDezKebx4PK7u7m5Fo1E1NTWprq5OoVBIzc3NOW8LAACUBsJdBYvFYkomk2psbCz2KAAAYJFwWraQbjltv3qq07W1W6U1W+zTspk2HJ/qNdO11Zuk4Eb7tGym9Udm9666LefxTNOcvwkAAJQVjtwVkneJvUxfbydJHp9dy7zeLqs340firprqNRbWm6P6+nqZpqne3t6c1wUAAKWJI3cVzDAMtbW1qbW1VT6fTw0NDRoZGVFfX5/C4fD8GwAAACWHcFfhIpGIvF6vOjo6NDQ0pJqaGrW0tBR7LAAAkCeXZVlWsYcoZ4lEQoODgwoEAjIMY/4VylSl7CcAAOWOa+4AAAAchHAHAADgIIQ7AAAAByHcAQAAOAjhDgAAwEEIdwAAAA5CuAMAAHAQwh0AAICDEO4AAAAchHAHAADgIIQ7AAAAByHcAQAAOAjhrsKlUilFo1EFg0H5/X7V1taqs7Oz2GMBAIA8eYs9gKNNjNqvnmrJ5bK/nhyTrHHJ5ZU8/jl6Tck1lblT41JqTHJ5JI8xf6+7KucR29vb1dPTo66uLoVCIQ0PD6u/vz/n7QAAgNLAkbtC2rPUXpIn0rXYdrt2cHN2797ldn30aLp2eKdd2x/O7t230q6fjKVrA7tyHi8ej6u7u1vRaFRNTU2qq6tTKBRSc3NzztsCAAClgXBXwWKxmJLJpBobG4s9CgAAWCScli2kW07br57qdG3tVmnNFvu0bKYNx6d6zXRt9SYpuNE+LZtp/ZHZvatuy3k80zTnbwIAAGWFI3eF5F1iL9PX20mSx2fXMq+3y+rN+JG4q6Z6jYX15qi+vl6maaq3tzfndQEAQGniyF0FMwxDbW1tam1tlc/nU0NDg0ZGRtTX16dwODz/BgAAQMkh3FW4SCQir9erjo4ODQ0NqaamRi0tLcUeCwAA5MllWZZV7CHKWSKR0ODgoAKBgAzDmH+FMlUp+wkAQLnjmjsAAAAHIdwBAAA4COEOAADAQQh3AAAADkK4AwAAcBDCHQAAgIMQ7gAAAByEcAcAAOAghDsAAAAHIdwBAAA4COEOAADAQQh3AAAADkK4q3CpVErRaFTBYFB+v1+1tbXq7Ows9lgAACBP3mIP4GgTo/arp1pyueyvJ8cka1xyeSWPf45eU3JNZe7UuJQak1weyWPM3+uuynnE9vZ29fT0qKurS6FQSMPDw+rv7895OwAAoDRw5K6Q9iy1l+SJdC223a4d3Jzdu3e5XR89mq4d3mnX9oeze/ettOsnY+nawK6cx4vH4+ru7lY0GlVTU5Pq6uoUCoXU3Nyc87YAAEBpINxVsFgspmQyqcbGxmKPAgAAFgmnZQvpltP2q6c6XVu7VVqzxT4tm2nD8aleM11bvUkKbrRPy2Zaf2R276rbch7PNM35mwAAQFnhyF0heZfYy/T1dpLk8dm1zOvtsnozfiTuqqleY2G9Oaqvr5dpmurt7c15XQAAUJo4clfBDMNQW1ubWltb5fP51NDQoJGREfX19SkcDs+/AQAAUHIIdxUuEonI6/Wqo6NDQ0NDqqmpUUtLS7HHAgAAeXJZlmUVe4hylkgkNDg4qEAgIMMw5l+hTFXKfgIAUO645g4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuKlwqlVI0GlUwGJTf71dtba06OzuLPRYAAMiTt9gDONrEqP3qqZZcLvvryTHJGpdcXsnjn6PXlFxTmTs1LqXGJJdH8hjz97qrch6xvb1dPT096urqUigU0vDwsPr7+3PeDgAAKA0cuSukPUvtJXkiXYttt2sHN2f37l1u10ePpmuHd9q1/eHs3n0r7frJWLo2sCvn8eLxuLq7uxWNRtXU1KS6ujqFQiE1NzfnvC0AAFAaCHcVLBaLKZlMqrGxsdijAACARcJp2UK65bT96qlO19ZuldZssU/LZtpwfKrXTNdWb5KCG+3TspnWH5ndu+q2nMczTXP+JgAAUFY4cldI3iX2Mn29nSR5fHYt83q7rN6MH4m7aqrXWFhvjurr62Wapnp7e3NeFwAAlCaO3FUwwzDU1tam1tZW+Xw+NTQ0aGRkRH19fQqHw/NvAAAAlBzCXYWLRCLyer3q6OjQ0NCQampq1NLSUuyxAABAnlyWZVnFHqKcJRIJDQ4OKhAIyDCM+VcoU5WynwAAlDuuuQMAAHAQwh0AAICDEO4AAAAchHAHAADgIIQ7AAAAByHcAQAAOAjhDgAAwEEIdwAAAA5CuAMAAHAQwh0AAICDEO4AAAAchHAHAADgIIS7CpdKpRSNRhUMBuX3+1VbW6vOzs5ijwUAAPLkLfYAjjYxar96qiWXy/56ckyyxiWXV/L45+g1JddU5k6NS6kxyeWRPMb8ve6qnEdsb29XT0+Purq6FAqFNDw8rP7+/py3AwAASgNH7gppz1J7SZ5I12Lb7drBzdm9e5fb9dGj6drhnXZtfzi7d99Ku34ylq4N7Mp5vHg8ru7ubkWjUTU1Namurk6hUEjNzc05bwsAAJQGwl0Fi8ViSiaTamxsLPYoAABgkXBatpBuOW2/eqrTtbVbpTVb7NOymTYcn+o107XVm6TgRvu0bKb1R2b3rrot5/FM05y/CQAAlBWO3BWSd4m9TF9vJ0ken13LvN4uqzfjR+Kumuo1Ftabo/r6epmmqd7e3pzXBQAApYkjdxXMMAy1tbWptbVVPp9PDQ0NGhkZUV9fn8Lh8PwbAAAAJYdwV+EikYi8Xq86Ojo0NDSkmpoatbS0FHssAACQJ5dlWVaxhyhniURCg4ODCgQCMgxj/hXKVKXsJwAA5Y5r7gAAAByEcAcAAOAghDsAAAAHIdwBAAA4COEOAADAQQh3AAAADkK4AwAAcBDCHQAAgIMQ7gAAAByEcAcAAOAghDsAAAAHIdwBAAA4COGuwqVSKUWjUQWDQfn9ftXW1qqzs7PYYwEAgDx5iz2Ao02M2q+easnlsr+eHJOsccnllTz+OXpNyTWVuVPjUmpMcnkkjzF/r7sq5xHb29vV09Ojrq4uhUIhDQ8Pq7+/P+ftAACA0sCRu0Las9RekifStdh2u3Zwc3bv3uV2ffRounZ4p13bH87u3bfSrp+MpWsDu3IeLx6Pq7u7W9FoVE1NTaqrq1MoFFJzc3PO2wIAAKWBcFfBYrGYksmkGhsbiz0KAABYJJyWLaRbTtuvnup0be1Wac0W+7Rspg3Hp3rNdG31Jim40T4tm2n9kdm9q27LeTzTNOdvAgAAZYUjd4XkXWIv09fbSZLHZ9cyr7fL6s34kbirpnqNhfXmqL6+XqZpqre3N+d1AQBAaeLIXQUzDENtbW1qbW2Vz+dTQ0ODRkZG1NfXp3A4PP8GAABAySHcVbhIJCKv16uOjg4NDQ2ppqZGLS0txR4LAADkyWVZllXsIcpZIpHQ4OCgAoGADMOYf4UyVSn7CQBAueOaOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrircKlUStFoVMFgUH6/X7W1ters7Cz2WAAAIE/eYg/gaBOj9qunWnK57K8nxyRrXHJ5JY9/jl5Tck1l7tS4lBqTXB7JY8zf667KecT29nb19PSoq6tLoVBIw8PD6u/vz3k7AACgNHDkrpD2LLWX5Il0Lbbdrh3cnN27d7ldHz2arh3eadf2h7N796206ydj6drArpzHi8fj6u7uVjQaVVNTk+rq6hQKhdTc3JzztgAAQGkg3FWwWCymZDKpxsbGYo8CAAAWCadlC+mW0/arpzpdW7tVWrPFPi2bacPxqV4zXVu9SQputE/LZlp/ZHbvqttyHs80zfmbAABAWeHIXSF5l9jL9PV2kuTx2bXM6+2yejN+JO6qqV5jYb05qq+vl2ma6u3tzXldAABQmjhyV8EMw1BbW5taW1vl8/nU0NCgkZER9fX1KRwOz78BAABQcgh3FS4Sicjr9aqjo0NDQ0OqqalRS0tLsccCAAB5clmWZRV7iHKWSCQ0ODioQCAgwzDmX6FMVcp+AgBQ7rjmDgAAwEEIdwAAAA5CuAMAAHAQwh0AAICDEO4AAAAchHAHAADgIIQ7AAAAByHcAQAAOAjhDgAAwEEIdwAAAA5CuAMAAHAQwh0AAICDEO4qXCqVUjQaVTAYlN/vV21trTo7O4s9FgAAyJO32AM42sSo/eqpllwu++vJMckal1xeyeOfo9eUXFOZOzUupcYkl0fyGPP3uqtyHrG9vV09PT3q6upSKBTS8PCw+vv7c94OAAAoDRy5K6Q9S+0leSJdi223awc3Z/fuXW7XR4+ma4d32rX94ezefSvt+slYujawK+fx4vG4uru7FY1G1dTUpLq6OoVCITU3N+e8LQAAUBoIdxUsFospmUyqsbGx2KMAAIBFwmnZQrrltP3qqU7X1m6V1myxT8tm2nB8qtdM11ZvkoIb7dOymdYfmd276racxzNNc/4mAABQVjhyV0jeJfYyfb2dJHl8di3zerus3owfibtqqtdYWG+O6uvrZZqment7c14XAACUJo7cVTDDMNTW1qbW1lb5fD41NDRoZGREfX19CofD828AAACUHMJdhYtEIvJ6vero6NDQ0JBqamrU0tJS7LEAAECeXJZlWcUeopwlEgkNDg4qEAjIMIz5VyhTlbKfAACUO665AwAAcBDCHQAAgIMQ7gAAAByEcAcAAOAghDsAAAAHIdwBAAA4COEOAADAQQh3AAAADkK4AwAAcBDCHQAAgIMQ7gAAAByEcAcAAOAghLsKl0qlFI1GFQwG5ff7VVtbq87OzmKPBQAA8uQt9gCONjFqv3qqJZfL/npyTLLGJZdX8vjn6DUl11TmTo1LqTHJ5ZE8xvy97qqcR2xvb1dPT4+6uroUCoU0PDys/v7+nLcDAABKA0fuCmnPUntJnkjXYtvt2sHN2b17l9v10aPp2uGddm1/OLt330q7fjKWrg3synm8eDyu7u5uRaNRNTU1qa6uTqFQSM3NzTlvCwAAlAbCXQWLxWJKJpNqbGws9igAAGCRcFq2kG45bb96qtO1tVulNVvs07KZNhyf6jXTtdWbpOBG+7RspvVHZveuui3n8UzTnL8JAACUFY7cFZJ3ib1MX28nSR6fXcu83i6rN+NH4q6a6jUW1puj+vp6maap3t7enNcFAACliSN3FcwwDLW1tam1tVU+n08NDQ0aGRlRX1+fwuHw/BsAAAAlh3BX4SKRiLxerzo6OjQ0NKSamhq1tLQUeywAAJAnl2VZVrGHKGeJREKDg4MKBAIyDGP+FcpUpewnAADljmvuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4a7CpVIpRaNRBYNB+f1+1dbWqrOzs9hjAQCAPHmLPYCjTYzar55qyeWyv54ck6xxyeWVPP45ek3JNZW5U+NSakxyeSSPMX+vuyrnEdvb29XT06Ouri6FQiENDw+rv78/5+0AAIDSwJG7Qtqz1F6SJ9K12Ha7dnBzdu/e5XZ99Gi6dninXdsfzu7dt9Kun4ylawO7ch4vHo+ru7tb0WhUTU1NqqurUygUUnNzc87bAgAApYFwV8FisZiSyaQaGxuLPQoAAFgknJYtpFtO26+e6nRt7VZpzRb7tGymDcenes10bfUmKbjRPi2baf2R2b2rbst5PNM0528CAABlhSN3heRdYi/T19tJksdn1zKvt8vqzfiRuKumeo2F9eaovr5epmmqt7c353UBAEBp4shdBTMMQ21tbWptbZXP51NDQ4NGRkbU19encDg8/wYAAEDJIdxVuEgkIq/Xq46ODg0NDammpkYtLS3FHgsAAOTJZVmWVewhylkikdDg4KACgYAMw5h/hTJVKfsJAEC545o7AAAAByHcAQAAOAjhDgAAwEEIdwAAAA5CuAMAAHAQwh0AAICDEO4AAAAchHAHAADgIIQ7AAAAByHcAQAAOAjhDgAAwEEIdwAAAA5CuKtwqVRK0WhUwWBQfr9ftbW16uzsLPZYAAAgT95iD+BoE6P2q6dacrnsryfHJGtccnklj3+OXlNyTWXu1LiUGpNcHsljzN/rrsp5xPb2dvX09Kirq0uhUEjDw8Pq7+/PeTsAAKA0cOSukPYstZfkiXQttt2uHdyc3bt3uV0fPZquHd5p1/aHs3v3rbTrJ2Pp2sCunMeLx+Pq7u5WNBpVU1OT6urqFAqF1NzcnPO2AABAaSDcVbBYLKZkMqnGxsZijwIAABYJp2UL6ZbT9qunOl1bu1Vas8U+LZtpw/GpXjNdW71JCm60T8tmWn9kdu+q23IezzTN+ZsAAEBZ4chdIXmX2Mv09XaS5PHZtczr7bJ6M34k7qqpXmNhvTmqr6+XaZrq7e3NeV0AAFCaOHJXwQzDUFtbm1pbW+Xz+dTQ0KCRkRH19fUpHA7PvwEAAFByCHcVLhKJyOv1qqOjQ0NDQ6qpqVFLS0uxxwIAAHlyWZZlFXuIcpZIJDQ4OKhAICDDMOZfoUxVyn4CAFDuuOYOAADAQQh3AAAADkK4AwAAcBDCHQAAgIMQ7gAAAByEcAcAAOAghDsAAAAHIdwBAAA4COEOAADAQQh3AAAADkK4AwAAcBDCHQAAgIMQ7ipcKpVSNBpVMBiU3+9XbW2tOjs7iz0WAADIk7fYAzjaxKj96qmWXC7768kxyRqXXF7J45+j15RcU5k7NS6lxiSXR/IY8/e6q3Iesb29XT09Perq6lIoFNLw8LD6+/tz3g4AACgNHLkrpD1L7SV5Il2LbbdrBzdn9+5dbtdHj6Zrh3fatf3h7N59K+36yVi6NrAr5/Hi8bi6u7sVjUbV1NSkuro6hUIhNTc357wtAABQGgh3FSwWiymZTKqxsbHYowAAgEXCadlCuuW0/eqpTtfWbpXWbLFPy2bacHyq10zXVm+Sghvt07KZ1h+Z3bvqtpzHM01z/iYAAFBWOHJXSN4l9jJ9vZ0keXx2LfN6u6zejB+Ju2qq11hYb47q6+tlmqZ6e3tzXhcAAJQmjtxVMMMw1NbWptbWVvl8PjU0NGhkZER9fX0Kh8PzbwAAAJQcwl2Fi0Qi8nq96ujo0NDQkGpqatTS0lLssQAAQJ5clmVZxR6inCUSCQ0ODioQCMgwjPlXKFOVsp8AAJQ7rrkDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEu0KaGLUXy0rXJsfs2mTyDL2pdC01PtWbWFhvHlKplKLRqILBoPx+v2pra9XZ2ZnXtgAAQPER7gppz1J7SZ5I12Lb7drBzdm9e5fb9dGj6drhnXZtfzi7d99Ku34ylq4N7MprxPb2dm3btk2RSESHDh3S7t27tWLFiry2BQAAis9b7AFQPPF4XN3d3dqxY4eampokSXV1dQqFQkWeDAAA5MtlWZnnDJGrRCKhwcFBBQIBGYaR/c2JUfvVUy25XPbXk2OSNS65vJLHP0evKbmmDqimxqXUmOTySB5j/l53VU6zHzhwQOvWrdPAwIACgUD++wkAAEoGR+4Kybtkds3jk+RbWK+7au7AdqbeHJmmmfM6AACgtHHNXQWrr6+XaZrq7e0t9igAAGCRcOSughmGoba2NrW2tsrn86mhoUEjIyPq6+tTOByefwMAAKDkEO4qXCQSkdfrVUdHh4aGhlRTU6OWlpZijwUAAPLEByrOUqV80KBS9hMAgHLHNXcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwV0gTo/ZiWena5Jhdm0yeoTeVrqXGp3oTC+vNQyqVUjQaVTAYlN/vV21trTo7O/PaFgAAKD7CXSHtWWovyRPpWmy7XTu4Obt373K7Pno0XTu8067tD2f37ltp10/G0rWBXXmN2N7erm3btikSiejQoUPavXu3VqxYkde2AABA8XmLPQCKJx6Pq7u7Wzt27FBTU5Mkqa6uTqFQqMiTAQCAfLksK/OcIXKVSCQ0ODioQCAgwzCyvzkxar96qiWXy/56ckyyxiWXV/L45+g1JdfUAdXUuJQak1weyWPM3+uuymn2AwcOaN26dRoYGFAgEMh/PwEAQMngyF0heZfMrnl8knwL63VXzR3YztSbI9M0c14HAACUNq65q2D19fUyTVO9vb3FHgUAACwSjtxVMMMw1NbWptbWVvl8PjU0NGhkZER9fX0Kh8PzbwAAAJQcwl2Fi0Qi8nq96ujo0NDQkGpqatTS0lLssQAAQJ74QMVZqpQPGlTKfgIAUO645g4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuCmli1F4sK12bHLNrk8kz9KbStdT4VG9iYb15SKVSikajCgaD8vv9qq2tVWdnZ17bAgAAxUe4K6Q9S+0leSJdi223awc3Z/fuXW7XR4+ma4d32rX94ezefSvt+slYujawK68R29vbtW3bNkUiER06dEi7d+/WihUr8toWAAAoPm+xB0DxxONxdXd3a8eOHWpqapIk1dXVKRQKFXkyAACQL5dlZZ4zRK4SiYQGBwcVCARkGEb2NydG7VdPteRy2V9PjknWuOTySh7/HL2m5Jo6oJoal1JjkssjeYz5e91VOc1+4MABrVu3TgMDAwoEAvnvJwAAKBkcuSsk75LZNY9Pkm9hve6quQPbmXpzZJpmzusAAIDSxjV3Fay+vl6maaq3t7fYowAAgEXCkbsKZhiG2tra1NraKp/Pp4aGBo2MjKivr0/hcHj+DQAAgJJDuKtwkUhEXq9XHR0dGhoaUk1NjVpaWoo9FgAAyBMfqDhLlfJBg0rZTwAAyh3X3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMJdIU2M2otlpWuTY3ZtMnmG3lS6lhqf6k0srDcPqVRK0WhUwWBQfr9ftbW16uzszGtbAACg+Ah3hbRnqb0kT6Rrse127eDm7N69y+366NF07fBOu7Y/nN27b6VdPxlL1wZ25TVie3u7tm3bpkgkokOHDmn37t1asWJFXtsCAADF5y32ACieeDyu7u5u7dixQ01NTZKkuro6hUKhIk8GAADy5bKszHOGyFUikdDg4KACgYAMw8j+5sSo/eqpllwu++vJMckal1xeyeOfo9eUXFMHVFPjUmpMcnkkjzF/r7sqp9kPHDigdevWaWBgQIFAIP/9BAAAJYMjd4XkXTK75vFJ8i2s1101d2A7U2+OTNPMeR0AAFDauOaugtXX18s0TfX29hZ7FAAAsEg4clfBDMNQW1ubWltb5fP51NDQoJGREfX19SkcDs+/AQAAUHIIdxUuEonI6/Wqo6NDQ0NDqqmpUUtLS7HHAgAAeeIDFWepUj5oUCn7CQBAueOaOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgrpIlRe7GsdG1yzK5NJs/Qm0rXUuNTvYmF9eYhlUopGo0qGAzK7/ertrZWnZ2deW0LAAAUH+GukPYstZfkiXQttt2uHdyc3bt3uV0fPZquHd5p1/aHs3v3rbTrJ2Pp2sCuvEZsb2/Xtm3bFIlEdOjQIe3evVsrVqzIa1sAAKD4vMUeAMUTj8fV3d2tHTt2qKmpSZJUV1enUChU5MkAAEC+XJaVec4QuUokEhocHFQgEJBhGNnfnBi1Xz3Vkstlfz05Jlnjkssrefxz9JqSa+qAampcSo1JLo/kMebvdVflNPuBAwe0bt06DQwMKBAI5L+fAACgZHDkrpC8S2bXPD5JvoX1uqvmDmxn6s2RaZo5rwMAAEob19xVsPr6epmmqd7e3mKPAgAAFglH7iqYYRhqa2tTa2urfD6fGhoaNDIyor6+PoXD4fk3AAAASg7hrsJFIhF5vV51dHRoaGhINTU1amlpKfZYAAAgT3yg4ixVygcNKmU/AQAod1xzBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4a7CpVIpRaNRBYNB+f1+1dbWqrOzs9hjAQCAPHmLPYCjTYzar55qyeWyv54ck6xxyeWVPP45ek3JNZW5U+NSakxyeSSPMX+vuyrnEdvb29XT06Ouri6FQiENDw+rv78/5+0AAIDSwJG7Qtqz1F6SJ9K12Ha7dnBzdu/e5XZ99Gi6dninXdsfzu7dt9Kun4ylawO7ch4vHo+ru7tb0WhUTU1NqqurUygUUnNzc87bAgAApYFwV8FisZiSyaQaGxuLPQoAAFgknJYtpFtO26+e6nRt7VZpzRb7tGymDcenes10bfUmKbjRPi2baf2R2b2rbst5PNM0528CAABlhSN3heRdYi/T19tJksdn1zKvt8vqzfiRuKumeo2F9eaovr5epmmqt7c353UBAEBp4shdBTMMQ21tbWptbZXP51NDQ4NGRkbU19encDg8/wYAAEDJIdxVuEgkIq/Xq46ODg0NDammpkYtLS3FHgsAAOTJZVmWVewhylkikdDg4KACgYAMw5h/hTJVKfsJAEC545o7AAAAByHcAQAAOAjhDgAAwEEIdwAAAA5CuAMAAHAQwh0AAICDEO4AAAAchHAHAADgIIQ7AAAAByHcAQAAOAjhDgAAwEEIdwAAAA5CuKtwqVRK0WhUwWBQfr9ftbW16uzsLPZYAAAgT95iD+BoE6P2q6dacrnsryfHJGtccnklj3+OXlNyTWXu1LiUGpNcHsljzN/rrsp5xPb2dvX09Kirq0uhUEjDw8Pq7+/PeTsAAKA0cOSukPYstZfkiXQttt2uHdyc3bt3uV0fPZquHd5p1/aHs3v3rbTrJ2Pp2sCunMeLx+Pq7u5WNBpVU1OT6urqFAqF1NzcnPO2AABAaSDcVbBYLKZkMqnGxsZijwIAABYJp2UL6ZbT9qunOl1bu1Vas8U+LZtpw/GpXjNdW71JCm60T8tmWn9kdu+q23IezzTN+ZsAAEBZ4chdIXmX2Mv09XaS5PHZtczr7bJ6M34k7qqpXmNhvTmqr6+XaZrq7e3NeV0AAFCaOHJXwQzDUFtbm1pbW+Xz+dTQ0KCRkRH19fUpHA7PvwEAAFByCHcVLhKJyOv1qqOjQ0NDQ6qpqVFLS0uxxwIAAHlyWZZlFXuIcpZIJDQ4OKhAICDDMOZfoUxVyn4CAFDuuOYOAADAQQh3AAAADkK4AwAAcBDCHQAAgIMQ7gAAAByEcAcAAOAghDsAAAAHIdwBAAA4COEOAADAQQh3AAAADkK4AwAAcBDCHQAAgIMQ7ipcKpVSNBpVMBiU3+9XbW2tOjs7iz0WAADIk7fYAzjaxKj96qmWXC7768kxyRqXXF7J45+j15RcU5k7NS6lxiSXR/IY8/e6q3Iesb29XT09Perq6lIoFNLw8LD6+/tz3g4AACgNHLkrpD1L7SV5Il2LbbdrBzdn9+5dbtdHj6Zrh3fatf3h7N59K+36yVi6NrAr5/Hi8bi6u7sVjUbV1NSkuro6hUIhNTc357wtAABQGgh3FSwWiymZTKqxsbHYowAAgEXCadlCuuW0/eqpTtfWbpXWbLFPy2bacHyq10zXVm+Sghvt07KZ1h+Z3bvqtpzHM01z/iYAAFBWOHJXSN4l9jJ9vZ0keXx2LfN6u6zejB+Ju2qq11hYb47q6+tlmqZ6e3tzXhcAAJQmjtxVMMMw1NbWptbWVvl8PjU0NGhkZER9fX0Kh8PzbwAAAJQcwl2Fi0Qi8nq96ujo0NDQkGpqatTS0lLssQAAQJ5clmVZxR6inCUSCQ0ODioQCMgwjPlXKFOVsp8AAJQ7rrkDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEuwqXSqUUjUYVDAbl9/tVW1urzs7OYo8FAADy5C32AI42MWq/eqoll8v+enJMssYll1fy+OfoNSXXVOZOjUupMcnlkTzG/L3uqpxHbG9vV09Pj7q6uhQKhTQ8PKz+/v6ctwMAAEoDR+4Kac9Se0meSNdi2+3awc3ZvXuX2/XRo+na4Z12bX84u3ffSrt+MpauDezKebx4PK7u7m5Fo1E1NTWprq5OoVBIzc3NOW8LAACUBsJdBYvFYkomk2psbCz2KAAAYJFwWraQbjltv3qq07W1W6U1W+zTspk2HJ/qNdO11Zuk4Eb7tGym9Udm9666LefxTNOcvwkAAJQVjtwVkneJvUxfbydJHp9dy7zeLqs340firprqNRbWm6P6+nqZpqne3t6c1wUAAKWJI3cVzDAMtbW1qbW1VT6fTw0NDRoZGVFfX5/C4fD8GwAAACWHcFfhIpGIvF6vOjo6NDQ0pJqaGrW0tBR7LAAAkCeXZVlWsYcoZ4lEQoODgwoEAjIMY/4VylSl7CcAAOWOa+4AAAAchHAHAADgIIQ7AAAAByHcAQAAOAjhDgAAwEEIdwAAAA5CuAMAAHAQwh0AAICDEO4AAAAchHAHAADgIIQ7AAAAByHcAQAAOAjhrsKlUilFo1EFg0H5/X7V1taqs7Oz2GMBAIA8eYs9gKNNjNqvnmrJ5bK/nhyTrHHJ5ZU8/jl6Tck1lblT41JqTHJ5JI8xf6+7KucR29vb1dPTo66uLoVCIQ0PD6u/vz/n7QAAgNLAkbtC2rPUXpIn0rXYdrt2cHN2797ldn30aLp2eKdd2x/O7t230q6fjKVrA7tyHi8ej6u7u1vRaFRNTU2qq6tTKBRSc3NzztsCAAClgXBXwWKxmJLJpBobG4s9CgAAWCScli2kW07br57qdG3tVmnNFvu0bKYNx6d6zXRt9SYpuNE+LZtp/ZHZvatuy3k80zTnbwIAAGWFI3eF5F1iL9PX20mSx2fXMq+3y+rN+JG4q6Z6jYX15qi+vl6maaq3tzfndQEAQGniyF0FMwxDbW1tam1tlc/nU0NDg0ZGRtTX16dwODz/BgAAQMkh3FW4SCQir9erjo4ODQ0NqaamRi0tLcUeCwAA5MllWZZV7CHKWSKR0ODgoAKBgAzDmH+FMlUp+wkAQLnjmjsAAAAHIdwBAAA4COEOAADAQQh3AAAADkK4AwAAcBDCHQAAgIMQ7gAAAByEcAcAAOAghDsAAAAHIdwBAAA4COEOAADAQQh3AAAADkK4q3CpVErRaFTBYFB+v1+1tbXq7Ows9lgAACBP3mIP4GgTo/arp1pyueyvJ8cka1xyeSWPf45eU3JNZe7UuJQak1weyWPM3+uuynnE9vZ29fT0qKurS6FQSMPDw+rv7895OwAAoDRw5K6Q9iy1l+SJdC223a4d3Jzdu3e5XR89mq4d3mnX9oeze/ettOsnY+nawK6cx4vH4+ru7lY0GlVTU5Pq6uoUCoXU3Nyc87YAAEBpINxVsFgspmQyqcbGxmKPAgAAFgmnZQvpltP2q6c6XVu7VVqzxT4tm2nD8aleM11bvUkKbrRPy2Zaf2R276rbch7PNM35mwAAQFnhyF0heZfYy/T1dpLk8dm1zOvtsnozfiTuqqleY2G9Oaqvr5dpmurt7c15XQAAUJo4clfBDMNQW1ubWltb5fP51NDQoJGREfX19SkcDs+/AQAAUHIIdxUuEonI6/Wqo6NDQ0NDqqmpUUtLS7HHAgAAeXJZlmUVe4hylkgkNDg4qEAgIMMw5l+hTFXKfgIAUO645g4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuAAAAHIRwBwAA4CCEOwAAAAch3AEAADgI4Q4AAMBBCHcAAAAOQrgDAABwEMIdAACAgxDuKlwqlVI0GlUwGJTf71dtba06OzuLPRYAAMiTt9gDONrEqP3qqZZcLvvryTHJGpdcXsnjn6PXlFxTmTs1LqXGJJdH8hjz97qrch6xvb1dPT096urqUigU0vDwsPr7+3PeDgAAKA0cuSukPUvtJXkiXYttt2sHN2f37l1u10ePpmuHd9q1/eHs3n0r7frJWLo2sCvn8eLxuLq7uxWNRtXU1KS6ujqFQiE1NzfnvC0AAFAaCHcVLBaLKZlMqrGxsdijAACARcJp2UK65bT96qlO19ZuldZssU/LZtpwfKrXTNdWb5KCG+3TspnWH5ndu+q2nMczTXP+JgAAUFY4cldI3iX2Mn29nSR5fHYt83q7rN6MH4m7aqrXWFhvjurr62Wapnp7e3NeFwAAlCaO3FUwwzDU1tam1tZW+Xw+NTQ0aGRkRH19fQqHw/NvAAAAlBzCXYWLRCLyer3q6OjQ0NCQampq1NLSUuyxAABAnlyWZVnFHqKcJRIJDQ4OKhAIyDCM+VcoU5WynwAAlDuuuQMAAHAQwh0AAICDEO4AAAAchHAHAADgIIQ7AAAAByHcAQAAOAjhDgAAwEEIdwAAAA5CuAMAAHAQwh0AAICDEO4AAAAchHAHAADgIIS7CpdKpRSNRhUMBuX3+1VbW6vOzs5ijwUAAPLkLfYAjjYxar96qiWXy/56ckyyxiWXV/L45+g1JddU5k6NS6kxyeWRPMb8ve6qnEdsb29XT0+Purq6FAqFNDw8rP7+/py3AwAASgNH7gppz1J7SZ5I12Lb7drBzdm9e5fb9dGj6drhnXZtfzi7d99Ku34ylq4N7Mp5vHg8ru7ubkWjUTU1Namurk6hUEjNzc05bwsAAJQGwl0Fi8ViSiaTamxsLPYoAABgkXBatpBuOW2/eqrTtbVbpTVb7NOymTYcn+o107XVm6TgRvu0bKb1R2b3rrot5/FM05y/CQAAlBWO3BWSd4m9TF9vJ0ken13LvN4uqzfjR+Kumuo1Ftabo/r6epmmqd7e3pzXBQAApYkjdxXMMAy1tbWptbVVPp9PDQ0NGhkZUV9fn8Lh8PwbAAAAJYdwV+EikYi8Xq86Ojo0NDSkmpoatbS0FHssAACQJ5dlWVaxhyhniURCg4ODCgQCMgxj/hXKVKXsJwAA5Y5r7gAAAByEcAcAAOAghDsAAAAHIdwBAAA4COEOAADAQQh3AAAADkK4AwAAcBDCHQAAgIMQ7gAAAByEcAcAAOAghDsAAAAHIdwBAAA4COGuwqVSKUWjUQWDQfn9ftXW1qqzs7PYYwEAgDx5iz2Ao02M2q+easnlsr+eHJOs8f+/vTv2USr/9z/+OnPOwDmjxVbupSEiYLS57RbQzR9gYWKLCWNCooWNEAroJtlgMSFZq2mstjCx8A+gNxu7G5aJxWAsmBuxuAbnG5hx4BafMcDV/eHhKz/gw/ORnBzy9n0+eROaVz7nM7uS40lu9Du9geRcZu7huTQ8kxxXcv3ZvVvboUcsl8s6PDzUwcGBstmsTk5OdHR0FHodAACwGti5W6QXV801+DiutZ6a2ptH070vr5n66ftx7e0zU3udn+59dd3UP7XGtePnocfr9Xqq1+uq1WrK5XJKJpPKZrPa29sLvRYAAFgNhLsN1mq1NBgMtLu7u+xRAADAT8Jr2UW699nc3Z1x7fYT6dZj81p20t0Pl73BuHbzoZR6YF7LTrrz7tveG/dDjxcEwewmAACwVti5WyTvirm+nreTJDdiapPn7aZ6J36Sre3LXv/HekNKp9MKgkCNRiP0swAAYDWxc7fBfN9XqVRSsVhUJBJRJpNRt9tVs9lUPp+fvQAAAFg5hLsNV6lU5HmeqtWqOp2OYrGYCoXCsscCAABzckaj0WjZQ6yzfr+vdrutRCIh3/dnP7CmNuV7AgCw7jhzBwAAYBHCHQAAgEUIdwAAABYh3AEAAFiEcAcAAGARwh0AAIBFCHcAAAAWIdwBAABYhHAHAABgEcIdAACARQh3AAAAFiHcAQAAWIRwt+GGw6FqtZpSqZSi0aji8bj29/eXPRYAAJiTt+wBrPbl1NzdHclxzOeLM2l0Ljme5Ea/0xtIzmXmHp5LwzPJcSXXn927tR16xHK5rMPDQx0cHCibzerk5ERHR0eh1wEAAKuBnbtFenHVXIOP41rrqam9eTTd+/KaqZ++H9fePjO11/np3lfXTf1Ta1w7fh56vF6vp3q9rlqtplwup2QyqWw2q729vdBrAQCA1UC422CtVkuDwUC7u7vLHgUAAPwkvJZdpHufzd3dGdduP5FuPTavZSfd/XDZG4xrNx9KqQfmteykO+++7b1xP/R4QRDMbgIAAGuFnbtF8q6Y6+t5O0lyI6Y2ed5uqnfiJ9navuz1f6w3pHQ6rSAI1Gg0Qj8LAABWEzt3G8z3fZVKJRWLRUUiEWUyGXW7XTWbTeXz+dkLAACAlUO423CVSkWe56lararT6SgWi6lQKCx7LAAAMCdnNBqNlj3EOuv3+2q320okEvJ9f/YDa2pTvicAAOuOM3cAAAAWIdwBAABYhHAHAABgEcIdAACARQh3AAAAFiHcAQAAWIRwBwAAYBHCHQAAgEUIdwAAABYh3AEAAFiEcAcAAGARwh0AAIBFCHcbbjgcqlarKZVKKRqNKh6Pa39/f9ljAQCAOXnLHsBqX07N3d2RHMd8vjiTRueS40lu9Du9geRcZu7huTQ8kxxXcv3ZvVvboUcsl8s6PDzUwcGBstmsTk5OdHR0FHodAACwGti5W6QXV801+DiutZ6a2ptH070vr5n66ftx7e0zU3udn+59dd3UP7XGtePnocfr9Xqq1+uq1WrK5XJKJpPKZrPa29sLvRYAAFgNhLsN1mq1NBgMtLu7u+xRAADAT8Jr2UW699nc3Z1x7fYT6dZj81p20t0Pl73BuHbzoZR6YF7LTrrz7tveG/dDjxcEwewmAACwVti5WyTvirm+nreTJDdiapPn7aZ6J36Sre3LXv/HekNKp9MKgkCNRiP0swAAYDWxc7fBfN9XqVRSsVhUJBJRJpNRt9tVs9lUPp+fvQAAAFg5hLsNV6lU5HmeqtWqOp2OYrGYCoXCsscCAABzckaj0WjZQ6yzfr+vdrutRCIh3/dnP7CmNuV7AgCw7jhzBwAAYBHCHQAAgEUIdwAAABYh3AEAAFiEcAcAAGARwh0AAIBFCHcAAAAWIdwBAABYhHAHAABgEcIdAACARQh3AAAAFiHcAQAAWIRwt+GGw6FqtZpSqZSi0aji8bj29/eXPRYAAJiTt+wBrPbl1NzdHclxzOeLM2l0Ljme5Ea/0xtIzmXmHp5LwzPJcSXXn927tR16xHK5rMPDQx0cHCibzerk5ERHR0eh1wEAAKuBnbtFenHVXIOP41rrqam9eTTd+/KaqZ++H9fePjO11/np3lfXTf1Ta1w7fh56vF6vp3q9rlqtplwup2QyqWw2q729vdBrAQCA1UC422CtVkuDwUC7u7vLHgUAAPwkvJZdpHufzd3dGdduP5FuPTavZSfd/XDZG4xrNx9KqQfmteykO+++7b1xP/R4QRDMbgIAAGuFnbtF8q6Y6+t5O0lyI6Y2ed5uqnfiJ9navuz1f6w3pHQ6rSAI1Gg0Qj8LAABWEzt3G8z3fZVKJRWLRUUiEWUyGXW7XTWbTeXz+dkLAACAlUO423CVSkWe56lararT6SgWi6lQKCx7LAAAMCdnNBqNlj3EOuv3+2q320okEvJ9f/YDa2pTvicAAOuOM3cAAAAWIdwBAABYhHAHAABgEcIdAACARQh3AAAAFiHcAQAAWIRwBwAAYBHCHQAAgEUIdwAAABYh3AEAAFiEcAcAAGARwh0AAIBFCHcbbjgcqlarKZVKKRqNKh6Pa39/f9ljAQCAOXnLHsBqX07N3d2RHMd8vjiTRueS40lu9Du9geRcZu7huTQ8kxxXcv3ZvVvboUcsl8s6PDzUwcGBstmsTk5OdHR0FHodAACwGti5W6QXV801+DiutZ6a2ptH070vr5n66ftx7e0zU3udn+59dd3UP7XGtePnocfr9Xqq1+uq1WrK5XJKJpPKZrPa29sLvRYAAFgNhLsN1mq1NBgMtLu7u+xRAADAT8Jr2UW699nc3Z1x7fYT6dZj81p20t0Pl73BuHbzoZR6YF7LTrrz7tveG/dDjxcEwewmAACwVti5WyTvirm+nreTJDdiapPn7aZ6J36Sre3LXv/HekNKp9MKgkCNRiP0swAAYDWxc7fBfN9XqVRSsVhUJBJRJpNRt9tVs9lUPp+fvQAAAFg5hLsNV6lU5HmeqtWqOp2OYrGYCoXCsscCAABzckaj0WjZQ6yzfr+vdrutRCIh3/dnP7CmNuV7AgCw7jhzBwAAYBHCHQAAgEUIdwAAABYh3AEAAFiEcAcAAGARwh0AAIBFCHcAAAAWIdwBAABYhHAHAABgEcIdAACARQh3AAAAFiHcAQAAWIRwt0hfTs01Go1rF2emdjH4h97huDY8v+zt/1jvHIbDoWq1mlKplKLRqOLxuPb39+daCwAALB/hbpFeXDXX4OO41npqam8eTfe+vGbqp+/HtbfPTO11frr31XVT/9Qa146fzzViuVzW77//rkqlor///lt//vmnfv3117nWAgAAy+ctewAsT6/XU71e1x9//KFcLidJSiaTymazS54MAADMyxmNJt8ZIqx+v692u61EIiHf96f/8cupubs7kuOYzxdn0uhccjzJjX6nN5Ccyw3V4bk0PJMcV3L92b1b26Fm/+uvv/Tbb7/p+PhYiURi/u8JAABWBjt3i+Rd+bbmRiRFfqx3a/v7ge2fekMKgiD0MwAAYLVx5m6DpdNpBUGgRqOx7FEAAMBPws7dBvN9X6VSScViUZFIRJlMRt1uV81mU/l8fvYCAABg5RDuNlylUpHneapWq+p0OorFYioUCsseCwAAzIk/qPg3bcofGmzK9wQAYN1x5g4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoQ7AAAAixDuAAAALEK4AwAAsAjhDgAAwCKEOwAAAIsQ7gAAACxCuAMAALAI4W6RvpyaazQa1y7OTO1i8A+9w3FteH7Z2/+x3jkMh0PVajWlUilFo1HF43Ht7+/PtRYAAFg+wt0ivbhqrsHHca311NTePJrufXnN1E/fj2tvn5na6/x076vrpv6pNa4dP59rxHK5rN9//12VSkV///23/vzzT/36669zrQUAAJbPW/YAWJ5er6d6va4//vhDuVxOkpRMJpXNZpc8GQAAmJczGk2+M0RY/X5f7XZbiURCvu9P/+OXU3N3dyTHMZ8vzqTRueR4khv9Tm8gOZcbqsNzaXgmOa7k+rN7t7ZDzf7XX3/pt99+0/HxsRKJxPzfEwAArAx27hbJu/JtzY1IivxY79b29wPbP/WGFARB6GcAAMBq48zdBkun0wqCQI1GY9mjAACAn4Sduw3m+75KpZKKxaIikYgymYy63a6azaby+fzsBQAAwMoh3G24SqUiz/NUrVbV6XQUi8VUKBSWPRYAAJgTf1Dxb9qUPzTYlO8JAMC648wdAACARQh3AAAAFiHcAQAAWIRwBwAAYBHCHQAAgEUIdwAAABYh3AEAAFiEcAcAAGARwh0AAIBFCHcAAAAWIdwBAABYhHAHAABgEcLdIn05NddoNK5dnJnaxeAfeofj2vD8srf/Y71zGA6HqtVqSqVSikajisfj2t/fn2stAACwfIS7RXpx1VyDj+Na66mpvXk03fvymqmfvh/X3j4ztdf56d5X1039U2tcO34+14jlclm///67KpWK/v77b/3555/69ddf51oLAAAsn7fsAbA8vV5P9Xpdf/zxh3K5nCQpmUwqm80ueTIAADAvZzSafGeIsPr9vtrtthKJhHzfn/7HL6fm7u5IjmM+X5xJo3PJ8SQ3+p3eQHIuN1SH59LwTHJcyfVn925th5r9r7/+0m+//abj42MlEon5vycAAFgZ7Nwtknfl25obkRT5sd6t7e8Htn/qDSkIgtDPAACA1caZuw2WTqcVBIEajcayRwEAAD8JO3cbzPd9lUolFYtFRSIRZTIZdbtdNZtN5fP52QsAAICVQ7jbcJVKRZ7nqVqtqtPpKBaLqVAoLHssAAAwJ/6g4t+0KX9osCnfEwCAdceZOwAAAIsQ7gAAACxCuAMAALAI4Q4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoQ7AAAAixDuAAAALEK4AwAAsAjhDgAAwCKEu0X6cmqu0WhcuzgztYvBP/QOx7Xh+WVv/8d65zAcDlWr1ZRKpRSNRhWPx7W/vz/XWgAAYPkId4v04qq5Bh/HtdZTU3vzaLr35TVTP30/rr19Zmqv89O9r66b+qfWuHb8fK4Ry+Wyfv/9d1UqFf3999/6888/9euvv861FgAAWD5v2QNgeXq9nur1uv744w/lcjlJUjKZVDabXfJkAABgXs5oNPnOEGH1+321220lEgn5vj/9j19Ozd3dkRzHfL44k0bnkuNJbvQ7vYHkXG6oDs+l4ZnkuJLrz+7d2g41+19//aXffvtNx8fHSiQS839PAACwMti5WyTvyrc1NyIp8mO9W9vfD2z/1BtSEAShnwEAAKuNM3cbLJ1OKwgCNRqNZY8CAAB+EnbuNpjv+yqVSioWi4pEIspkMup2u2o2m8rn87MXAAAAK4dwt+EqlYo8z1O1WlWn01EsFlOhUFj2WAAAYE78QcW/aVP+0GBTvicAAOuOM3cAAAAWIdwBAABYhHAHAABgEcIdAACARQh3AAAAFiHcAQAAWIRwBwAAYBHCHQAAgEUIdwAAABYh3AEAAFiEcAcAAGARwh0AAIBFCHeL9OXUXKPRuHZxZmoXg3/oHY5rw/PL3v6P9c5hOByqVqsplUopGo0qHo9rf39/rrUAAMDyEe4W6cVVcw0+jmutp6b25tF078trpn76flx7+8zUXuene19dN/VPrXHt+PlcI5bLZf3++++qVCr6+++/9eeff+rXX3+day0AALB83rIHwPL0ej3V63X98ccfyuVykqRkMqlsNrvkyQAAwLyc0WjynSHC6vf7arfbSiQS8n1/+h+/nJq7uyM5jvl8cSaNziXHk9zod3oDybncUB2eS8MzyXEl15/du7Udava//vpLv/32m46Pj5VIJOb/ngAAYGWwc7dI3pVva25EUuTHere2vx/Y/qk3pCAIQj8DAABWG2fuNlg6nVYQBGo0GsseBQAA/CTs3G0w3/dVKpVULBYViUSUyWTU7XbVbDaVz+dnLwAAAFYO4W7DVSoVeZ6narWqTqejWCymQqGw7LEAAMCc+IOKf9Om/KHBpnxPAADWHWfuAAAALEK4AwAAsAjhDgAAwCKEOwAAAIsQ7gAAACxCuAMAALAI4Q4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoS7DTccDlWr1ZRKpRSNRhWPx7W/v7/ssQAAwJy8ZQ9gtS+n5u7uSI5jPl+cSaNzyfEkN/qd3kByLjP38FwankmOK7n+7N6t7dAjlstlHR4e6uDgQNlsVicnJzo6Ogq9DgAAWA3s3C3Si6vmGnwc11pPTe3No+nel9dM/fT9uPb2mam9zk/3vrpu6p9a49rx89Dj9Xo91et11Wo15XI5JZNJZbNZ7e3thV4LAACsBsLdBmu1WhoMBtrd3V32KAAA4Cfhtewi3fts7u7OuHb7iXTrsXktO+nuh8veYFy7+VBKPTCvZSfdefdt7437occLgmB2EwAAWCvs3C2Sd8VcX8/bSZIbMbXJ83ZTvRM/ydb2Za//Y70hpdNpBUGgRqMR+lkAALCa2LnbYL7vq1QqqVgsKhKJKJPJqNvtqtlsKp/Pz14AAACsHMLdhqtUKvI8T9VqVZ1OR7FYTIVCYdljAQCAOTmj0Wi07CHWWb/fV7vdViKRkO/7sx9YU5vyPQEAWHecuQMAALAI4Q4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoQ7AAAAixDuAAAALEK4AwAAsAjhDgAAwCKEOwAAAIsQ7gAAACxCuNtww+FQtVpNqVRK0WhU8Xhc+/v7yx4LAADMyVv2AFb7cmru7o7kOObzxZk0OpccT3Kj3+kNJOcycw/PpeGZ5LiS68/u3doOPWK5XNbh4aEODg6UzWZ1cnKio6Oj0OsAAIDVwM7dIr24aq7Bx3Gt9dTU3jya7n15zdRP349rb5+Z2uv8dO+r66b+qTWuHT8PPV6v11O9XletVlMul1MymVQ2m9Xe3l7otQAAwGog3G2wVqulwWCg3d3dZY8CAAB+El7LLtK9z+bu7oxrt59Itx6b17KT7n647A3GtZsPpdQD81p20p133/beuB96vCAIZjcBAIC1ws7dInlXzPX1vJ0kuRFTmzxvN9U78ZNsbV/2+j/WG1I6nVYQBGo0GqGfBQAAq4mduw3m+75KpZKKxaIikYgymYy63a6azaby+fzsBQAAwMoh3G24SqUiz/NUrVbV6XQUi8VUKBSWPRYAAJiTMxqNRsseYp31+321220lEgn5vj/7gTW1Kd8TAIB1x5k7AAAAixDuAAAALEK4AwAAsAjhDgAAwCKEOwAAAIsQ7gAAACxCuAMAALAI4Q4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoS7DTccDlWr1ZRKpRSNRhWPx7W/v7/ssQAAwJy8ZQ9gtS+n5u7uSI5jPl+cSaNzyfEkN/qd3kByLjP38FwankmOK7n+7N6t7dAjlstlHR4e6uDgQNlsVicnJzo6Ogq9DgAAWA3s3C3Si6vmGnwc11pPTe3No+nel9dM/fT9uPb2mam9zk/3vrpu6p9a49rx89Dj9Xo91et11Wo15XI5JZNJZbNZ7e3thV4LAACsBsLdBmu1WhoMBtrd3V32KAAA4Cfhtewi3fts7u7OuHb7iXTrsXktO+nuh8veYFy7+VBKPTCvZSfdefdt7437occLgmB2EwAAWCvs3C2Sd8VcX8/bSZIbMbXJ83ZTvRM/ydb2Za//Y70hpdNpBUGgRqMR+lkAALCa2LnbYL7vq1QqqVgsKhKJKJPJqNvtqtlsKp/Pz14AAACsHMLdhqtUKvI8T9VqVZ1OR7FYTIVCYdljAQCAOTmj0Wi07CHWWb/fV7vdViKRkO/7sx9YU5vyPQEAWHecuQMAALAI4Q4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoQ7AAAAixDuAAAALEK4AwAAsAjhDgAAwCKEOwAAAIsQ7gAAACxCuNtww+FQtVpNqVRK0WhU8Xhc+/v7yx4LAADMyVv2AFb7cmru7o7kOObzxZk0OpccT3Kj3+kNJOcycw/PpeGZ5LiS68/u3doOPWK5XNbh4aEODg6UzWZ1cnKio6Oj0OsAAIDVwM7dIr24aq7Bx3Gt9dTU3jya7n15zdRP349rb5+Z2uv8dO+r66b+qTWuHT8PPV6v11O9XletVlMul1MymVQ2m9Xe3l7otQAAwGog3G2wVqulwWCg3d3dZY8CAAB+El7LLtK9z+bu7oxrt59Itx6b17KT7n647A3GtZsPpdQD81p20p133/beuB96vCAIZjcBAIC1ws7dInlXzPX1vJ0kuRFTmzxvN9U78ZNsbV/2+j/WG1I6nVYQBGo0GqGfBQAAq4mduw3m+75KpZKKxaIikYgymYy63a6azaby+fzsBQAAwMoh3G24SqUiz/NUrVbV6XQUi8VUKBSWPRYAAJiTMxqNRsseYp31+321220lEgn5vj/7gTW1Kd8TAIB1x5k7AAAAixDuAAAALEK4AwAAsAjhDgAAwCKEOwAAAIsQ7gAAACxCuAMAALAI4Q4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoS7DTccDlWr1ZRKpRSNRhWPx7W/v7/ssQAAwJy8ZQ9gtS+n5u7uSI5jPl+cSaNzyfEkN/qd3kByLjP38FwankmOK7n+7N6t7dAjlstlHR4e6uDgQNlsVicnJzo6Ogq9DgAAWA3s3C3Si6vmGnwc11pPTe3No+nel9dM/fT9uPb2mam9zk/3vrpu6p9a49rx89Dj9Xo91et11Wo15XI5JZNJZbNZ7e3thV4LAACsBsLdBmu1WhoMBtrd3V32KAAA4Cfhtewi3fts7u7OuHb7iXTrsXktO+nuh8veYFy7+VBKPTCvZSfdefdt7437occLgmB2EwAAWCvs3C2Sd8VcX8/bSZIbMbXJ83ZTvRM/ydb2Za//Y70hpdNpBUGgRqMR+lkAALCa2LnbYL7vq1QqqVgsKhKJKJPJqNvtqtlsKp/Pz14AAACsHMLdhqtUKvI8T9VqVZ1OR7FYTIVCYdljAQCAOTmj0Wi07CHWWb/fV7vdViKRkO/7sx9YU5vyPQEAWHecuQMAALAI4Q4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoQ7AAAAixDuAAAALEK4AwAAsAjhDgAAwCKEOwAAAIsQ7gAAACxCuNtww+FQtVpNqVRK0WhU8Xhc+/v7yx4LAADMyVv2AFb7cmru7o7kOObzxZk0OpccT3Kj3+kNJOcycw/PpeGZ5LiS68/u3doOPWK5XNbh4aEODg6UzWZ1cnKio6Oj0OsAAIDVwM7dIr24aq7Bx3Gt9dTU3jya7n15zdRP349rb5+Z2uv8dO+r66b+qTWuHT8PPV6v11O9XletVlMul1MymVQ2m9Xe3l7otQAAwGog3G2wVqulwWCg3d3dZY8CAAB+El7LLtK9z+bu7oxrt59Itx6b17KT7n647A3GtZsPpdQD81p20p133/beuB96vCAIZjcBAIC1ws7dInlXzPX1vJ0kuRFTmzxvN9U78ZNsbV/2+j/WG1I6nVYQBGo0GqGfBQAAq4mduw3m+75KpZKKxaIikYgymYy63a6azaby+fzsBQAAwMoh3G24SqUiz/NUrVbV6XQUi8VUKBSWPRYAAJiTMxqNRsseYp31+321220lEgn5vj/7gTW1Kd8TAIB1x5k7AAAAixDuAAAALEK4AwAAsAjhDgAAwCKEOwAAAIsQ7gAAACxCuAMAALAI4Q4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoS7DTccDlWr1ZRKpRSNRhWPx7W/v7/ssQAAwJy8ZQ9gtS+n5u7uSI5jPl+cSaNzyfEkN/qd3kByLjP38FwankmOK7n+7N6t7dAjlstlHR4e6uDgQNlsVicnJzo6Ogq9DgAAWA3s3C3Si6vmGnwc11pPTe3No+nel9dM/fT9uPb2mam9zk/3vrpu6p9a49rx89Dj9Xo91et11Wo15XI5JZNJZbNZ7e3thV4LAACsBsLdBmu1WhoMBtrd3V32KAAA4Cfhtewi3fts7u7OuHb7iXTrsXktO+nuh8veYFy7+VBKPTCvZSfdefdt7437occLgmB2EwAAWCvs3C2Sd8VcX8/bSZIbMbXJ83ZTvRM/ydb2Za//Y70hpdNpBUGgRqMR+lkAALCa2LnbYL7vq1QqqVgsKhKJKJPJqNvtqtlsKp/Pz14AAACsHMLdhqtUKvI8T9VqVZ1OR7FYTIVCYdljAQCAOTmj0Wi07CHWWb/fV7vdViKRkO/7sx9YU5vyPQEAWHecuQMAALAI4Q4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoQ7AAAAixDuAAAALEK4AwAAsAjhDgAAwCKEOwAAAIsQ7gAAACxCuNtww+FQtVpNqVRK0WhU8Xhc+/v7yx4LAADMyVv2AFb7cmru7o7kOObzxZk0OpccT3Kj3+kNJOcycw/PpeGZ5LiS68/u3doOPWK5XNbh4aEODg6UzWZ1cnKio6Oj0OsAAIDVwM7dIr24aq7Bx3Gt9dTU3jya7n15zdRP349rb5+Z2uv8dO+r66b+qTWuHT8PPV6v11O9XletVlMul1MymVQ2m9Xe3l7otQAAwGog3G2wVqulwWCg3d3dZY8CAAB+El7LLtK9z+bu7oxrt59Itx6b17KT7n647A3GtZsPpdQD81p20p133/beuB96vCAIZjcBAIC1ws7dInlXzPX1vJ0kuRFTmzxvN9U78ZNsbV/2+j/WG1I6nVYQBGo0GqGfBQAAq4mduw3m+75KpZKKxaIikYgymYy63a6azaby+fzsBQAAwMoh3G24SqUiz/NUrVbV6XQUi8VUKBSWPRYAAJiTMxqNRsseYp31+321220lEgn5vj/7gTW1Kd8TAIB1x5k7AAAAixDuAAAALEK4AwAAsAjhDgAAwCKEOwAAAIsQ7gAAACxCuAMAALAI4Q4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoS7DTccDlWr1ZRKpRSNRhWPx7W/v7/ssQAAwJy8ZQ9gtS+n5u7uSI5jPl+cSaNzyfEkN/qd3kByLjP38FwankmOK7n+7N6t7dAjlstlHR4e6uDgQNlsVicnJzo6Ogq9DgAAWA3s3C3Si6vmGnwc11pPTe3No+nel9dM/fT9uPb2mam9zk/3vrpu6p9a49rx89Dj9Xo91et11Wo15XI5JZNJZbNZ7e3thV4LAACsBsLdBmu1WhoMBtrd3V32KAAA4Cfhtewi3fts7u7OuHb7iXTrsXktO+nuh8veYFy7+VBKPTCvZSfdefdt7437occLgmB2EwAAWCvs3C2Sd8VcX8/bSZIbMbXJ83ZTvRM/ydb2Za//Y70hpdNpBUGgRqMR+lkAALCa2LnbYL7vq1QqqVgsKhKJKJPJqNvtqtlsKp/Pz14AAACsHMLdhqtUKvI8T9VqVZ1OR7FYTIVCYdljAQCAOTmj0Wi07CHWWb/fV7vdViKRkO/7sx9YU5vyPQEAWHecuQMAALAI4Q4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoQ7AAAAixDuAAAALEK4AwAAsAjhDgAAwCKEOwAAAIsQ7gAAACxCuNtww+FQtVpNqVRK0WhU8Xhc+/v7yx4LAADMyVv2AFb7cmru7o7kOObzxZk0OpccT3Kj3+kNJOcycw/PpeGZ5LiS68/u3doOPWK5XNbh4aEODg6UzWZ1cnKio6Oj0OsAAIDVwM7dIr24aq7Bx3Gt9dTU3jya7n15zdRP349rb5+Z2uv8dO+r66b+qTWuHT8PPV6v11O9XletVlMul1MymVQ2m9Xe3l7otQAAwGog3G2wVqulwWCg3d3dZY8CAAB+El7LLtK9z+bu7oxrt59Itx6b17KT7n647A3GtZsPpdQD81p20p133/beuB96vCAIZjcBAIC1ws7dInlXzPX1vJ0kuRFTmzxvN9U78ZNsbV/2+j/WG1I6nVYQBGo0GqGfBQAAq4mduw3m+75KpZKKxaIikYgymYy63a6azaby+fzsBQAAwMoh3G24SqUiz/NUrVbV6XQUi8VUKBSWPRYAAJiTMxqNRsseYp31+321220lEgn5vj/7gTW1Kd8TAIB1x5k7AAAAixDuAAAALEK4AwAAsAjhDgAAwCKEOwAAAIsQ7gAAACxCuAMAALAI4Q4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoS7DTccDlWr1ZRKpRSNRhWPx7W/v7/ssQAAwJy8ZQ9gtS+n5u7uSI5jPl+cSaNzyfEkN/qd3kByLjP38FwankmOK7n+7N6t7dAjlstlHR4e6uDgQNlsVicnJzo6Ogq9DgAAWA3s3C3Si6vmGnwc11pPTe3No+nel9dM/fT9uPb2mam9zk/3vrpu6p9a49rx89Dj9Xo91et11Wo15XI5JZNJZbNZ7e3thV4LAACsBsLdBmu1WhoMBtrd3V32KAAA4Cfhtewi3fts7u7OuHb7iXTrsXktO+nuh8veYFy7+VBKPTCvZSfdefdt7437occLgmB2EwAAWCvs3C2Sd8VcX8/bSZIbMbXJ83ZTvRM/ydb2Za//Y70hpdNpBUGgRqMR+lkAALCa2LnbYL7vq1QqqVgsKhKJKJPJqNvtqtlsKp/Pz14AAACsHMLdhqtUKvI8T9VqVZ1OR7FYTIVCYdljAQCAOTmj0Wi07CHWWb/fV7vdViKRkO/7sx9YU5vyPQEAWHecuQMAALAI4Q4AAMAihDsAAACLEO4AAAAsQrgDAACwCOEOAADAIoQ7AAAAixDuAAAALEK4AwAAsAjhDgAAwCKEOwAAAIsQ7gAAACxCuNtww+FQtVpNqVRK0WhU8Xhc+/v7yx4LAADMyVv2AFY7PTX3nR3JccznszPp/FzyPCka/bY3CKSty8x9fm76XVfy/dm929uhRyyXyzo8PNTBwYGy2axOTk50dHQUeh0AALAa2LlbpKtXzfXx47j29KmpPXo03Xvtmqm/fz+uPXtmavn8dO/166beao1rz5+HHq/X66ler6tWqymXyymZTCqbzWpvby/0WgAAYDUQ7jZYq9XSYDDQ7u7uskcBAAA/iTMajUbLHmKd9ft9tdttJRIJ+ZOvTqWVfy37X//1X/rP//xPHR8fK5FIzP89AQDAymDnbpGuXDHX12AnSZGIqU0Gu8nerYmfZHvb1P5vmPqn3pDS6bSCIFCj0Qj9LAAAWE38QcUG831fpVJJxWJRkUhEmUxG3W5XzWZT+f97zg8AAKwFwt2Gq1Qq8jxP1WpVnU5HsVhMhUJh2WMBAIA5cebu37QpZ9E25XsCALDuOHMHAABgEcIdAACARQh3AAAAFiHcAQAAWIRw95PY/ncptn8/AABsQbj7N21f/seD//Wvfy15ksX6+v225/iPJQMAgP9/+O/c/Ztc19Uvv/yiDx8+SJJ2dnbkTP4fKdbcaDTSv/71L3348EG//PKLXNdd9kgAAOD/gf/O3U8wGo303//93/qf//mfZY+yML/88ov+4z/+w6rgCgCAjQh3P9HFxYXOz8+XPcZPt729zY4dAABrgnAHAABgEf6gAgAAwCKEOwAAAIsQ7gAAACxCuAMAALAI4Q4AAMAihDsAAACLEO4AAAAs8r8dqfPOcfvwngAAAABJRU5ErkJggg==",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"unstable_c = c_stats.sort_values(\"c_cv\", ascending=False)[\"c_cv\"][:20]\n",
"display(unstable_c)\n",
"\n",
"unstable_c_specific = random.randint(0, 20)\n",
"print(unstable_c_specific)\n",
"print(unstable_c.index[unstable_c_specific][0])\n",
"print(unstable_c.index[unstable_c_specific][1])\n",
"\n",
"# pc avg trend\n",
"temp_pc_avg = pc_avg_complex[\n",
" pc_avg_complex[\"Postcode\"] == unstable_c.index[unstable_c_specific][0]\n",
"].sort_values(by=\"year\")\n",
"display(temp_pc_avg)\n",
"\n",
"# c for specific postcode\n",
"temp_postcode = data_small[\n",
" (data_small[\"Postcode\"] == unstable_c.index[unstable_c_specific][0])\n",
" # & (data_small['Address per EPC'] == unstable_c.index[unstable_c_specific][1])\n",
"].sort_values(by=\"year\")\n",
"display(temp_address)\n",
"\n",
"# c for specific address\n",
"temp_address = data_small[\n",
" (data_small[\"Postcode\"] == unstable_c.index[unstable_c_specific][0])\n",
" & (data_small[\"Address per EPC\"] == unstable_c.index[unstable_c_specific][1])\n",
"].sort_values(by=\"year\")\n",
"display(temp_address)\n",
"\n",
"# plot\n",
"\n",
"fig, ax1 = plt.subplots()\n",
"\n",
"temp_pc_avg.plot.line(x=\"year\", y=\"Price per sqm PC AVG\", ax=ax1, color=\"black\")\n",
"temp_address.plot.line(x=\"year\", y=\"Price per sqm\", ax=ax1, color=\"green\")\n",
"\n",
"ax2 = ax1.twinx()\n",
"\n",
"for property in temp_postcode[\"Address per EPC\"].unique():\n",
" property_data = temp_postcode[temp_postcode[\"Address per EPC\"] == property]\n",
" property_data.plot.line(x=\"year\", y=\"c\", ax=ax2, color=\"orange\", style=\":\")\n",
"temp_address.plot.line(x=\"year\", y=\"c\", ax=ax2, color=\"red\", style=\":\")\n",
"\n",
"ax1.set_ylabel(\"Price per sqm\")\n",
"ax2.set_ylabel(\"c\")\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "8f38e273",
"metadata": {},
"source": [
"# Predict latest"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "6f3acea0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Postcode: CR0 4JQ\n",
"Address: 1, Kemble Road\n"
]
}
],
"source": [
"# select random address\n",
"one_property = data_small.sample(1)[[\"Postcode\", \"Address per EPC\"]].iloc[0]\n",
"postcode = one_property[\"Postcode\"]\n",
"address = one_property[\"Address per EPC\"]\n",
"print(f\"Postcode: {postcode}\")\n",
"print(f\"Address: {address}\")"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "4ac06bd6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Latest year of data: 2010\n",
"\n",
"data_small.shape = (395821, 13)\n",
"data_small_train.shape = (395820, 13)\n",
"data_small_test.shape = (1, 13)\n"
]
},
{
"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>Postcode</th>\n",
" <th>Address per EPC</th>\n",
" <th>historical_prices</th>\n",
" <th>Price per sqm</th>\n",
" <th>Property type</th>\n",
" <th>Leashold/Freehold</th>\n",
" <th>Total floor area (sqm)</th>\n",
" <th>Rooms (including bedrooms &amp; bathrooms)</th>\n",
" <th>Approximate construction age</th>\n",
" <th>year</th>\n",
" <th>price</th>\n",
" <th>Price per sqm PC AVG</th>\n",
" <th>c</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>38025</th>\n",
" <td>CR0 4JQ</td>\n",
" <td>1, Kemble Road</td>\n",
" <td>{'year': 2010, 'price': 372000}</td>\n",
" <td>2439.344262</td>\n",
" <td>House</td>\n",
" <td>Freehold</td>\n",
" <td>152.5</td>\n",
" <td>8.0</td>\n",
" <td>1900.0</td>\n",
" <td>2010</td>\n",
" <td>372000</td>\n",
" <td>2154.45474</td>\n",
" <td>1.132233</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Postcode Address per EPC historical_prices \\\n",
"38025 CR0 4JQ 1, Kemble Road {'year': 2010, 'price': 372000} \n",
"\n",
" Price per sqm Property type Leashold/Freehold Total floor area (sqm) \\\n",
"38025 2439.344262 House Freehold 152.5 \n",
"\n",
" Rooms (including bedrooms & bathrooms) Approximate construction age \\\n",
"38025 8.0 1900.0 \n",
"\n",
" year price Price per sqm PC AVG c \n",
"38025 2010 372000 2154.45474 1.132233 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"property_data = data_small[\n",
" (data_small[\"Postcode\"] == postcode) & (data_small[\"Address per EPC\"] == address)\n",
"]\n",
"latest_year = property_data[\"year\"].max()\n",
"print(f\"Latest year of data: {latest_year}\")\n",
"\n",
"# Get only the latest year's data for this property (this is what we want to predict)\n",
"data_small_test = property_data[property_data[\"year\"] == latest_year]\n",
"\n",
"# Remove only the latest year's data from training (keep historical data for this property)\n",
"data_small_train = data_small.drop(data_small_test.index)\n",
"\n",
"print()\n",
"print(f\"data_small.shape = {data_small.shape}\")\n",
"print(f\"data_small_train.shape = {data_small_train.shape}\")\n",
"print(f\"data_small_test.shape = {data_small_test.shape}\")\n",
"display(data_small_test)\n",
"data_small.shape[0] == data_small_test.shape[0] + data_small_train.shape[0]"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "fd1ba4ee",
"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>Postcode</th>\n",
" <th>Address per EPC</th>\n",
" <th>historical_prices</th>\n",
" <th>Price per sqm</th>\n",
" <th>Property type</th>\n",
" <th>Leashold/Freehold</th>\n",
" <th>Total floor area (sqm)</th>\n",
" <th>Rooms (including bedrooms &amp; bathrooms)</th>\n",
" <th>Approximate construction age</th>\n",
" <th>year</th>\n",
" <th>price</th>\n",
" <th>Price per sqm PC AVG</th>\n",
" <th>c</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>38023</th>\n",
" <td>CR0 4JQ</td>\n",
" <td>1, Kemble Road</td>\n",
" <td>{'year': 1995, 'price': 58000}</td>\n",
" <td>380.327869</td>\n",
" <td>House</td>\n",
" <td>Freehold</td>\n",
" <td>152.5</td>\n",
" <td>8.0</td>\n",
" <td>1900.0</td>\n",
" <td>1995</td>\n",
" <td>58000</td>\n",
" <td>600.241588</td>\n",
" <td>0.633625</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38024</th>\n",
" <td>CR0 4JQ</td>\n",
" <td>1, Kemble Road</td>\n",
" <td>{'year': 1998, 'price': 163000}</td>\n",
" <td>1068.852459</td>\n",
" <td>House</td>\n",
" <td>Freehold</td>\n",
" <td>152.5</td>\n",
" <td>8.0</td>\n",
" <td>1900.0</td>\n",
" <td>1998</td>\n",
" <td>163000</td>\n",
" <td>1221.920537</td>\n",
" <td>0.874732</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Postcode Address per EPC historical_prices \\\n",
"38023 CR0 4JQ 1, Kemble Road {'year': 1995, 'price': 58000} \n",
"38024 CR0 4JQ 1, Kemble Road {'year': 1998, 'price': 163000} \n",
"\n",
" Price per sqm Property type Leashold/Freehold Total floor area (sqm) \\\n",
"38023 380.327869 House Freehold 152.5 \n",
"38024 1068.852459 House Freehold 152.5 \n",
"\n",
" Rooms (including bedrooms & bathrooms) Approximate construction age \\\n",
"38023 8.0 1900.0 \n",
"38024 8.0 1900.0 \n",
"\n",
" year price Price per sqm PC AVG c \n",
"38023 1995 58000 600.241588 0.633625 \n",
"38024 1998 163000 1221.920537 0.874732 "
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# get latest c in data_small_train\n",
"\n",
"latest_train_address = data_small_train[\n",
" (data_small_train[\"Postcode\"] == postcode)\n",
" & (data_small_train[\"Address per EPC\"] == address)\n",
"].sort_values(by=\"year\")\n",
"\n",
"latest_train_address"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "65c69be9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Latest c in training data: 0.875\n",
"Latest price per sqm in training data: 1221.92\n"
]
}
],
"source": [
"latest_train_c = latest_train_address[\"c\"].iloc[-1]\n",
"latest_train_pc_avg = latest_train_address[\"Price per sqm PC AVG\"].iloc[-1]\n",
"print(f\"Latest c in training data: {latest_train_c:.3f}\")\n",
"print(f\"Latest price per sqm in training data: {latest_train_pc_avg:.2f}\")"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "861f4737",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"np.float64(163000.0)"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"latest_train_c * latest_train_pc_avg * data_small_test[\"Total floor area (sqm)\"].iloc[0]"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "1f6e866a",
"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>Postcode</th>\n",
" <th>Address per EPC</th>\n",
" <th>historical_prices</th>\n",
" <th>Price per sqm</th>\n",
" <th>Property type</th>\n",
" <th>Leashold/Freehold</th>\n",
" <th>Total floor area (sqm)</th>\n",
" <th>Rooms (including bedrooms &amp; bathrooms)</th>\n",
" <th>Approximate construction age</th>\n",
" <th>year</th>\n",
" <th>price</th>\n",
" <th>Price per sqm PC AVG</th>\n",
" <th>c</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>38025</th>\n",
" <td>CR0 4JQ</td>\n",
" <td>1, Kemble Road</td>\n",
" <td>{'year': 2010, 'price': 372000}</td>\n",
" <td>2439.344262</td>\n",
" <td>House</td>\n",
" <td>Freehold</td>\n",
" <td>152.5</td>\n",
" <td>8.0</td>\n",
" <td>1900.0</td>\n",
" <td>2010</td>\n",
" <td>372000</td>\n",
" <td>2154.45474</td>\n",
" <td>1.132233</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Postcode Address per EPC historical_prices \\\n",
"38025 CR0 4JQ 1, Kemble Road {'year': 2010, 'price': 372000} \n",
"\n",
" Price per sqm Property type Leashold/Freehold Total floor area (sqm) \\\n",
"38025 2439.344262 House Freehold 152.5 \n",
"\n",
" Rooms (including bedrooms & bathrooms) Approximate construction age \\\n",
"38025 8.0 1900.0 \n",
"\n",
" year price Price per sqm PC AVG c \n",
"38025 2010 372000 2154.45474 1.132233 "
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data_small_test"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "property-map",
"language": "python",
"name": "python3"
},
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"version": 3
},
"file_extension": ".py",
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},
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