1267 lines
422 KiB
Plaintext
1267 lines
422 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "1b85622b",
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"metadata": {},
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"source": [
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"# Colorado Spills \n",
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"## OLS, NBR, Interrupted Time Series Analysis\n",
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"### Author: [David P. Adams, PhD](https://dadams.io)\n",
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"#### Date: 2025-04-18"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d456a510",
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"metadata": {},
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"source": [
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"---\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9814ecd7",
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"metadata": {},
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"source": [
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"# Setup"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"id": "eba79ece",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/home/dadams/miniconda3/envs/spatial_env2/lib/python3.10/site-packages/pandas/io/sql.py:1725: SAWarning: Did not recognize type 'geometry' of column 'geometry'\n",
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" self.meta.reflect(bind=self.con, only=[table_name], views=True)\n"
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]
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}
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],
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"source": [
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"import pandas as pd\n",
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"from sqlalchemy import create_engine\n",
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"import geopandas as gpd\n",
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"from dotenv import load_dotenv\n",
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"load_dotenv()\n",
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"\n",
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"import os\n",
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"\n",
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"# Database connection details from zshrc environment variables\n",
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"# use .env file for local development\n",
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"\n",
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"\n",
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"db_name = 'colorado_spills'\n",
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"user = os.getenv('DB_USER')\n",
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"password = os.getenv('DB_PASSWORD')\n",
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"host = os.getenv('DB_HOST')\n",
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"port = os.getenv('DB_PORT')\n",
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"\n",
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"\n",
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"# Create an engine to connect to the PostgreSQL database\n",
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"engine = create_engine(f'postgresql+psycopg2://{user}:{password}@{host}:{port}/{db_name}')\n",
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"\n",
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"# Read in the spills_with_demographics_geog as spills\n",
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"spills = pd.read_sql_table('spills_with_demographics_geog', engine)\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "da21b89e",
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"metadata": {},
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"outputs": [],
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"source": [
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"# use longitude and latitude to create a GeoDataFrame from spills data\n",
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"spills['geometry'] = gpd.points_from_xy(spills['Longitude'], spills['Latitude'])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "789eaccb",
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"metadata": {},
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"outputs": [],
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"source": [
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"spills_gdf = gpd.GeoDataFrame(spills, crs='EPSG:4326') \n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"id": "d041a419",
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"# Ensure date columns are in datetime format\n",
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"spills_gdf['Date of Discovery'] = pd.to_datetime(spills_gdf['Date of Discovery'])\n",
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"spills_gdf['Initial Report Date'] = pd.to_datetime(spills_gdf['Initial Report Date'])\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "3106f3c5",
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"metadata": {},
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"outputs": [],
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"source": [
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"# drop 2024 data for date of discovery and initial report date\n",
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"spills_gdf = spills_gdf[spills_gdf['Date of Discovery'].dt.year < 2024]\n",
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"spills_gdf = spills_gdf[spills_gdf['Initial Report Date'].dt.year < 2024]\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"id": "139de8e5",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Separate Historical vs. Recent Spills\n",
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"historical_spills = spills_gdf[spills_gdf['Spill Type'] == 'Historical']\n",
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"recent_spills = spills_gdf[spills_gdf['Spill Type'] == 'Recent']\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"id": "1327b4ea",
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"metadata": {},
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"outputs": [],
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"source": [
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"import statsmodels.formula.api as smf\n",
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"\n",
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"# Create 'Period' column\n",
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"spills_gdf['Period'] = spills_gdf['Report Year'].apply(lambda x: 'Before 2020' if x < 2020 else '2020 and After')\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"id": "2ccf5c3a",
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"metadata": {},
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"outputs": [],
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"source": [
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"spills_gdf = spills_gdf.rename(columns={\n",
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" 'Report Delay (Days)': 'report_delay',\n",
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" 'Spill Type': 'spill_type'\n",
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"})\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1da721cd",
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"metadata": {},
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"source": [
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"---"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1b9a3766",
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"metadata": {},
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"source": [
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"# OLS Regression"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"id": "1b722ad7",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" OLS Regression Results \n",
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"==============================================================================\n",
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"Dep. Variable: report_delay R-squared: 0.006\n",
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"Model: OLS Adj. R-squared: 0.006\n",
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"Method: Least Squares F-statistic: 31.12\n",
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"Date: Fri, 18 Apr 2025 Prob (F-statistic): 4.78e-20\n",
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"Time: 22:00:49 Log-Likelihood: -99827.\n",
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"No. Observations: 15990 AIC: 1.997e+05\n",
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"Df Residuals: 15986 BIC: 1.997e+05\n",
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"Df Model: 3 \n",
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"Covariance Type: nonrobust \n",
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"====================================================================================================================\n",
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" coef std err t P>|t| [0.025 0.975]\n",
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"--------------------------------------------------------------------------------------------------------------------\n",
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"Intercept 13.5331 2.394 5.654 0.000 8.841 18.225\n",
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"C(spill_type)[T.Recent] -10.6062 3.032 -3.498 0.000 -16.550 -4.662\n",
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"C(Period)[T.Before 2020] 16.2130 3.417 4.745 0.000 9.516 22.910\n",
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"C(spill_type)[T.Recent]:C(Period)[T.Before 2020] -14.4276 4.200 -3.435 0.001 -22.660 -6.196\n",
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"==============================================================================\n",
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"Omnibus: 45995.174 Durbin-Watson: 1.996\n",
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"Prob(Omnibus): 0.000 Jarque-Bera (JB): 3525625525.882\n",
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"Skew: 38.959 Prob(JB): 0.00\n",
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"Kurtosis: 2302.059 Cond. No. 8.76\n",
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"==============================================================================\n",
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"\n",
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"Notes:\n",
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"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
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]
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}
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],
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"source": [
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"import statsmodels.formula.api as smf\n",
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"\n",
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"model = smf.ols(\"report_delay ~ C(spill_type) * C(Period)\", data=spills_gdf).fit()\n",
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"print(model.summary())\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "e52e1b08",
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"metadata": {},
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"source": [
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"## Spill Reporting Analysis\n",
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"### **What the OLS Says**\n",
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"\n",
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"This is a 2×2 model:\n",
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"- **Spill Type**: `Historical` (reference) vs. `Recent`\n",
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"- **Period**: `2021 and After` (reference) vs. `Before 2021`\n",
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"- With their **interaction**\n",
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"\n",
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"#### Coefficient interpretations:\n",
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"- **Intercept (13.53)**: Avg delay for *historical* spills *after 2021*.\n",
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"- **Recent (–10.61)**: Recent spills after 2021 had **~10.6 days faster** reporting than historical ones.\n",
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"- **Before 2021 (+16.21)**: Historical spills before 2021 were reported **~16.2 days slower** than those after 2021.\n",
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"- **Interaction (–14.43)**: Recent spills before 2021 were **~14.4 days faster** than expected given the sum of the main effects. That’s key."
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]
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},
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{
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"cell_type": "markdown",
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"id": "3585fb92",
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"metadata": {},
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"source": [
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"| Group | Formula | Result |\n",
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"|-----------------------------|----------------------------------------------------------------------|------------|\n",
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"| Historical, After 2021 | Intercept | 13.53 days |\n",
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"| Recent, After 2021 | Intercept + Recent | 2.92 days |\n",
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"| Historical, Before 2021 | Intercept + Before 2021 | 29.74 days |\n",
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"| Recent, Before 2021 | Intercept + Before 2021 + Recent + Interaction | 4.70 days |\n"
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]
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},
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{
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||
"cell_type": "markdown",
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||
"id": "0cef322c",
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"metadata": {},
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"source": [
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"---"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ee48e488",
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"metadata": {},
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"source": [
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"# Negative Binomial Regression"
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]
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},
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{
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"cell_type": "code",
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||
"execution_count": 21,
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||
"id": "813a6d9c",
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||
"metadata": {},
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"outputs": [
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{
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||
"name": "stdout",
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"output_type": "stream",
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"text": [
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" Generalized Linear Model Regression Results \n",
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"==============================================================================\n",
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"Dep. Variable: report_delay No. Observations: 15990\n",
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"Model: GLM Df Residuals: 15986\n",
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"Model Family: NegativeBinomial Df Model: 3\n",
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"Link Function: Log Scale: 1.0000\n",
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"Method: IRLS Log-Likelihood: -47751.\n",
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"Date: Fri, 18 Apr 2025 Deviance: 54508.\n",
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"Time: 22:00:49 Pearson chi2: 1.72e+06\n",
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"No. Iterations: 12 Pseudo R-squ. (CS): 0.4976\n",
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"Covariance Type: nonrobust \n",
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"====================================================================================================================\n",
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" coef std err z P>|z| [0.025 0.975]\n",
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"--------------------------------------------------------------------------------------------------------------------\n",
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"Intercept 2.6051 0.020 130.748 0.000 2.566 2.644\n",
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"C(spill_type)[T.Recent] -1.5312 0.026 -57.998 0.000 -1.583 -1.479\n",
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"C(Period)[T.Before 2020] 0.7876 0.028 27.959 0.000 0.732 0.843\n",
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"C(spill_type)[T.Recent]:C(Period)[T.Before 2020] -0.3113 0.036 -8.672 0.000 -0.382 -0.241\n",
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"====================================================================================================================\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/home/dadams/miniconda3/envs/spatial_env2/lib/python3.10/site-packages/statsmodels/genmod/families/family.py:1367: ValueWarning: Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0.\n",
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" warnings.warn(\"Negative binomial dispersion parameter alpha not \"\n"
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]
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}
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],
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"source": [
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"import statsmodels.formula.api as smf\n",
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"import statsmodels.api as sm\n",
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"\n",
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"# Make sure spill_type and Period are clean, and report_delay is numeric\n",
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"spills_gdf = spills_gdf.rename(columns={\n",
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" 'Report Delay (Days)': 'report_delay',\n",
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" 'Spill Type': 'spill_type'\n",
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"})\n",
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"\n",
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"# Fit the Negative Binomial model with interaction\n",
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"nb_model = smf.glm(\n",
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" formula=\"report_delay ~ C(spill_type) * C(Period)\",\n",
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" data=spills_gdf,\n",
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" family=sm.families.NegativeBinomial()\n",
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").fit()\n",
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"\n",
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"# View the results\n",
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"print(nb_model.summary())\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "89571910",
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"metadata": {},
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"source": [
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"## Negative Binomial Regression Results\n",
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"### **Key Coefficients (in log count space)**\n",
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"\n",
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"| Term | Coef (log) | Exp(Coef) | Interpretation |\n",
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"|------|------------|-----------|----------------|\n",
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"| **Intercept** | 2.605 | 13.53 | Expected delay for **Historical spills after 2021**: ~13.5 days |\n",
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"| **Recent** | –1.531 | 0.216 | Recent spills (after 2021) take ~78% *less time* to report |\n",
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"| **Before 2021** | 0.788 | 2.20 | Historical spills before 2021 took ~2.2x *longer* |\n",
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"| **Interaction** | –0.311 | 0.733 | Recent spills before 2021 were ~27% *faster* than expected given the base effects |\n",
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"\n",
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"---\n",
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"\n",
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"### Summary Interpretation\n",
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"\n",
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"- **Recent reporting improved substantially** after 2021, even after controlling for spill type.\n",
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"- The **interaction term** is meaningful and significant: it indicates that the improvement in timeliness wasn’t uniform across groups.\n",
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"- Model fit is strong for count data: \n",
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" - Log-likelihood is stable \n",
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" - Pseudo R² ≈ 0.498 \n",
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" - No convergence issues or overdispersion errors yet (though `alpha=1.0` is default — you can estimate that if needed)\n"
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]
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},
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{
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"cell_type": "code",
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||
"execution_count": 22,
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"id": "4343c273",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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||
"Intercept 13.533087\n",
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"C(spill_type)[T.Recent] 0.216276\n",
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"C(Period)[T.Before 2020] 2.198025\n",
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"C(spill_type)[T.Recent]:C(Period)[T.Before 2020] 0.732466\n",
|
||
"dtype: float64"
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||
]
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||
},
|
||
"execution_count": 22,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
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||
}
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||
],
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||
"source": [
|
||
"import numpy as np\n",
|
||
"np.exp(nb_model.params)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "3459a91b",
|
||
"metadata": {},
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||
"source": [
|
||
"### **Group-Level Predictions (Multiplicative Model)**\n",
|
||
"#### Log link in a Negative Binomial model:\n",
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"\n",
|
||
"\\[\n",
|
||
"\\text{Expected Delay} = e^{\\text{sum of coefficients for that group}}\n",
|
||
"\\]\n",
|
||
"\n",
|
||
"Or, since you've already exponentiated the coefficients:\n",
|
||
"\n",
|
||
"\\[\n",
|
||
"\\text{Delay} = \\text{Intercept} \\times \\text{Multipliers}\n",
|
||
"\\]\n",
|
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"\n",
|
||
"| Group | Calculation | Predicted Delay (days) |\n",
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||
"|------------------------------|----------------------------------------------------------|-------------------------|\n",
|
||
"| **Historical, After 2021** | `13.53` | 13.53 |\n",
|
||
"| **Recent, After 2021** | `13.53 × 0.216` | ≈ 2.93 |\n",
|
||
"| **Historical, Before 2021** | `13.53 × 2.20` | ≈ 29.77 |\n",
|
||
"| **Recent, Before 2021** | `13.53 × 0.216 × 2.20 × 0.732` | ≈ 4.26 |\n",
|
||
"\n",
|
||
"---\n",
|
||
"\n",
|
||
"### Interpretation\n",
|
||
"\n",
|
||
"- After 2021, recent spills are reported **~10.6 days faster** than historical ones (2.93 vs. 13.53 days).\n",
|
||
"- Historical reporting times **worsened before 2021** (29.8 days).\n",
|
||
"- The **biggest drop** is in **recent spill reporting after 2021** — a likely policy win."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"id": "f09f08d0",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
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||
"data": {
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||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 1000x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt\n",
|
||
"import pandas as pd\n",
|
||
"\n",
|
||
"# Predicted delays by group\n",
|
||
"group_labels = [\n",
|
||
" \"Historical, After 2021\",\n",
|
||
" \"Recent, After 2021\",\n",
|
||
" \"Historical, Before 2021\",\n",
|
||
" \"Recent, Before 2021\"\n",
|
||
"]\n",
|
||
"\n",
|
||
"# From your exponentiated results\n",
|
||
"predicted_delays = [\n",
|
||
" 13.53, # Intercept only\n",
|
||
" 13.53 * 0.216, # Intercept * Recent\n",
|
||
" 13.53 * 2.198, # Intercept * Before 2021\n",
|
||
" 13.53 * 0.216 * 2.198 * 0.732 # Intercept * Recent * Before 2021 * Interaction\n",
|
||
"]\n",
|
||
"\n",
|
||
"# Create DataFrame for plotting\n",
|
||
"df_plot = pd.DataFrame({\n",
|
||
" \"Group\": group_labels,\n",
|
||
" \"Predicted Delay (Days)\": predicted_delays\n",
|
||
"})\n",
|
||
"\n",
|
||
"# Plot\n",
|
||
"plt.figure(figsize=(10, 6))\n",
|
||
"bars = plt.bar(df_plot[\"Group\"], df_plot[\"Predicted Delay (Days)\"], alpha=0.8)\n",
|
||
"plt.title(\"Predicted Report Delay by Spill Type and Period\", fontsize=14)\n",
|
||
"plt.ylabel(\"Predicted Delay (Days)\", fontsize=12)\n",
|
||
"plt.xticks(rotation=15, ha='right')\n",
|
||
"plt.grid(axis='y', linestyle='--', alpha=0.7)\n",
|
||
"plt.tight_layout()\n",
|
||
"\n",
|
||
"# Annotate bars\n",
|
||
"for bar in bars:\n",
|
||
" height = bar.get_height()\n",
|
||
" plt.annotate(f\"{height:.2f}\",\n",
|
||
" xy=(bar.get_x() + bar.get_width() / 2, height),\n",
|
||
" xytext=(0, 3), # 3 points vertical offset\n",
|
||
" textcoords=\"offset points\",\n",
|
||
" ha='center', va='bottom')\n",
|
||
"\n",
|
||
"plt.show()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "0ef55d60",
|
||
"metadata": {},
|
||
"source": [
|
||
"### What the Plot Highlights:\n",
|
||
"- **Historical spills before 2021** had the longest delays by far (~30 days).\n",
|
||
"- **Recent spills after 2021** saw the shortest (~3 days).\n",
|
||
"- The interaction effect shows **recent + before 2021** was better than historical, but still far worse than recent + after 2021."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "daa4b710",
|
||
"metadata": {},
|
||
"source": []
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "a9251055",
|
||
"metadata": {},
|
||
"source": [
|
||
"---\n",
|
||
"\n",
|
||
"# Compare OLS and Negative Binomial\n",
|
||
"\n",
|
||
"### **Comparison Table**\n",
|
||
"\n",
|
||
"| Group | OLS Prediction (Days) | NBR Prediction (Days) |\n",
|
||
"|---------------------------|------------------------|------------------------|\n",
|
||
"| Historical, After 2021 | 13.53 | 13.53 |\n",
|
||
"| Recent, After 2021 | 2.92 | 2.93 |\n",
|
||
"| Historical, Before 2021 | 29.74 | 29.77 |\n",
|
||
"| Recent, Before 2021 | 4.70 | 4.26 |\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "3238be11",
|
||
"metadata": {},
|
||
"source": [
|
||
"---"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "f6c679b7",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Interrupted Time Series"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"id": "fc8dc178",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" OLS Regression Results \n",
|
||
"==============================================================================\n",
|
||
"Dep. Variable: report_delay R-squared: 0.044\n",
|
||
"Model: OLS Adj. R-squared: 0.018\n",
|
||
"Method: Least Squares F-statistic: 1.708\n",
|
||
"Date: Fri, 18 Apr 2025 Prob (F-statistic): 0.169\n",
|
||
"Time: 22:00:49 Log-Likelihood: -481.60\n",
|
||
"No. Observations: 115 AIC: 971.2\n",
|
||
"Df Residuals: 111 BIC: 982.2\n",
|
||
"Df Model: 3 \n",
|
||
"Covariance Type: nonrobust \n",
|
||
"==============================================================================\n",
|
||
" coef std err t P>|t| [0.025 0.975]\n",
|
||
"------------------------------------------------------------------------------\n",
|
||
"Intercept 15.5960 3.601 4.331 0.000 8.461 22.731\n",
|
||
"time -0.1178 0.079 -1.486 0.140 -0.275 0.039\n",
|
||
"post_2021 -27.6725 25.778 -1.073 0.285 -78.753 23.409\n",
|
||
"time_post 0.3024 0.272 1.111 0.269 -0.237 0.842\n",
|
||
"==============================================================================\n",
|
||
"Omnibus: 127.364 Durbin-Watson: 1.901\n",
|
||
"Prob(Omnibus): 0.000 Jarque-Bera (JB): 2109.313\n",
|
||
"Skew: 3.925 Prob(JB): 0.00\n",
|
||
"Kurtosis: 22.458 Cond. No. 1.41e+03\n",
|
||
"==============================================================================\n",
|
||
"\n",
|
||
"Notes:\n",
|
||
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
|
||
"[2] The condition number is large, 1.41e+03. This might indicate that there are\n",
|
||
"strong multicollinearity or other numerical problems.\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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lISEhDrfduHEj3/tev34dkiShQoUKuZ7P7t27lecin8vZYxWFMmXK2N02GAwOx9JgMNiN5fXr13H48OFczy8gIACSJOUaL0f0ej3at2+PyZMn49dff8XFixfRsmVLrF27Vumrdf36ddy+fRsGgyHXY127ds3l74ucXI2/RYsWWL16NaxWK/r27Yvw8HDUqlXLYa+dghg4cCAOHDiAyZMnIyEhwWHfM+Du94qj5xcWFpbr+7Js2bK5jjMajbmmO+blXt7TQ4cOxZYtW3DixAlYLBbMnz8fTz/9tMvf18OGDcPevXuxY8cOfPTRR7BYLHjiiSfsnuf169exZs2aXGP40EMPAcj9M8PZ+8xsNiM5ORm3bt2CJElOX2MAuV5nV7/f7oWcBJRjkKf/Pv3007me+7Rp0yBJEm7evOnwXKIool27dli1ahXGjBmDLVu2YM+ePUrSP/v3h9FoxJAhQ7B06VLcvn0bCQkJ+P777zFo0CA2XCciKkG4+h4REd33SpcurVQjvPLKKw6PiY6OtrvtrH+Ps+0+Pj4OGzT/999/diteya5du+Zwm6M/9nMqV64cBEHAH3/84fCPN3mbfC5nj5W9KqS4KVeuHEwmU65G3dn3u6ts2bIYPnw4tm7diqNHj6JTp04oV64cypYtq/QjyykgIMDutqt9ndyJ/4knnsATTzyBjIwM7N69G1OnTkWvXr0QFRWFJk2auPjsHGvWrBkeeOABvPvuu4iNjUVERITD4+TvlatXr9qtuggAV65cKdDrXZh69eqFsWPH4n//+x8effRRXLt2zel725Hw8HCluXmzZs0QEhKCPn36YMKECZg9ezaAzDGqU6cOJk+e7PAcchJH5ux9ZjAY4O/vD51OB41Gg6tXr+Y67sqVK8pjZuduH7GC+PnnnwFAWZBBjmHWrFlOV9WsUKGCw+1Hjx7F33//jUWLFqFfv37K9tOnTzs8/qWXXsIHH3yAr776Cunp6bBarXjxxRcL+lSIiKgYYlKKiIjuG3IyJme1hq+vL1q1aoWDBw+iTp06MBgMHn/sqKgoHD582G7byZMnceLECYd/0C9btgwjRoxQ/ug8f/48du7cib59+yrHZH8+JpNJ2d65c2d88MEHuHz5Mnr27Ok0pkcffRQ+Pj5YsmSJ3TSgnTt34vz588U6KdW5c2dMmTIFZcuWzZUwzI/FYsGdO3ccJvjk6UNyQqFz585Yvnw5bDYbGjdufO+BZylI/EajETExMQgKCsKvv/6KgwcP3nNSCshsNL5ixYo8kzatW7cGkNngOnuD6b179+Kff/7BW2+95fbjOns/eoKPjw9eeOEFzJ49Gzt37kS9evXQrFmzAp+vd+/e+PLLLzF//nyMHj0akZGR6Ny5M9atW4cqVaqgdOnS+Z5j1apV+PDDD5Xqr6SkJKxZswbNmzeHVquFn58fGjdujFWrVuGjjz5S3tOiKOLbb79FeHi4S1NDPfm6/v3335gyZQqioqKUnyXNmjVDUFAQjh8/jldffdWt88k/z3Imyz///HOHx4eGhqJHjx6YM2cOzGYzunTpgkqVKhXgmRARUXHFpBQREd03AgICEBkZiZ9++glt2rRBmTJlUK5cOURFRWHmzJl47LHH0Lx5c7z00kuIiopCUlISTp8+jTVr1uC33367p8d+7rnn0KdPH7z88svo3r07zp8/j+nTp6N8+fIOj4+Pj8dTTz2FwYMHIzExERMmTICPjw/GjRunHFO7dm0AwLRp09CxY0dotVrUqVMHzZo1wwsvvIDnn38e+/btQ4sWLeDn54erV69ix44dqF27Nl566SWULl0ao0aNwvvvv49BgwahR48euHjxIiZOnFhk0/cKavjw4Vi5ciVatGiB119/HXXq1IEoirhw4QI2btyIkSNHOk0iJSYmIioqCj169EDbtm0RERGB5ORkbN26FTNnzkSNGjXQrVs3AMCzzz6LJUuWoFOnThg2bBgaNWoEvV6PS5cu4ffff8cTTzxRoNXcXI1//PjxuHTpEtq0aYPw8HDcvn0bM2fOhF6vR0xMjHK+Nm3aYNu2bW73lQKAPn36oE+fPnke88ADD+CFF17ArFmzlFXj4uLi8M477yAiIgKvv/66249bpUoVmEwmLFmyBDVq1IC/vz/CwsJyVRgV1Msvv4zp06dj//79+PLLL+/5fNOmTUPjxo3x3nvv4csvv8S7776LTZs2oWnTphg6dCgeeOABpKenIy4uDuvWrcO8efPsqsq0Wi1iY2MxYsQIiKKIadOm4c6dO3YrdE6dOhWxsbFo1aoVRo0aBYPBgDlz5uDo0aNYtmyZS5VR8s+FmTNnol+/ftDr9XjggQdyVfXltH//fgQGBsJiseDKlSvYsmULFi9ejODgYKxZs0ZJ1vv7+2PWrFno168fbt68iaeffhrBwcFISEjA33//jYSEBMydO9fhYzz44IOoUqUK3njjDUiShDJlymDNmjXYtGmT07iGDRumvJflFRuJiKjkYFKKiIjuKwsWLMDo0aPRtWtXZGRkoF+/fli0aBFq1qyJAwcO4L333sPbb7+N+Ph4BAUFoVq1akpfqXvRq1cvXLlyBfPmzcPChQtRq1YtzJ071+4P0uymTJmCvXv34vnnn8edO3fQqFEjLF++HFWqVLE7559//ok5c+bg3XffhSRJOHfuHKKiovD555/j0Ucfxeeff445c+ZAFEWEhYWhWbNmdg2o3333Xfj5+WHOnDlYvHgxHnzwQcybNw8fffTRPT/nwuTn54c//vgDH3zwAb744gucO3cOJpMJlSpVQtu2bfOs8ipVqhQmTZqELVu24M0338T169chCAKio6MxfPhwjB07Fr6+vgAyEwk///wzZs6cicWLF2Pq1KnQ6XQIDw9HTEyMkgAorPgbN26Mffv2YezYsUhISEBQUBAaNmyI3377TeldBAA2mw02m61Asbhq7ty5qFKlChYsWID//e9/CAwMRIcOHTB16lSXppXm5Ovri6+++gqTJk1Cu3btYLFYMGHCBEycONEj8VasWBGPPfYYDh8+jF69et3z+Ro1aoQePXrg66+/xrhx41ClShXs27cP7733Hj788ENcunQJAQEBiI6ORocOHXJVT7366qtIT0/H0KFDER8fj4ceegi//PKLXQVXTEwMfvvtN0yYMAH9+/eHKIqoW7cufv7551yLAjjTsmVLjBs3Dl9//TXmz58PURTx+++/K9PvnOnQoQOAzCqmMmXKoHbt2pg2bRqef/75XAmtPn36oFKlSpg+fTqGDBmCpKQkBAcHo169ek77kgGZfdzWrFmDYcOGYciQIdDpdGjbti02b97stAKqUaNGiIqKgslkQps2bVx6DYiISD0EKeeSGkREROQ1W7duRatWrfDDDz/g6aef9nY4RKoVHx+PyMhIvPbaa5g+fbrX4oiLi0N0dDQ+/PBDjBo1ymtxqNXhw4eV1RRffvllb4dDREQexkopIiIiIioxLl26hLNnz+LDDz+ERqPBsGHDvB0SFcCZM2dw/vx5vPnmmwgNDc2zAouIiNRL4+0AiIiIiIg85csvv0TLli1x7NgxLFmyBBUrVvR2SFQA7733HmJjY5GcnIwffvhBmVJLREQlC6fvERERERERERFRkWOlFBERERERERERFTkmpYiIiIiIiIiIqMgxKUVEREREREREREWOq+8BEEURV65cQUBAAARB8HY4RERERERERESqJUkSkpKSEBYWBo3GeT0Uk1IArly5goiICG+HQURERERERERUYly8eBHh4eFO9zMpBSAgIABA5otVqlQpZbvFYsHGjRvRrl076PV6b4VHLuBYqQfHSh04TurBsVIHjpN6cKzUg2OlDhwn9eBYqYNaxunOnTuIiIhQ8i3OMCkFKFP2SpUqlSsp5evri1KlShXrwSaOlZpwrNSB46QeHCt14DipB8dKHTIyMjB27FicP38eXbp0gb+/v7dDIif4nlIPjpU6qG2c8muRxKQUERERERGpitVqxbx585SviYhInbj6HhERERERERERFTkmpYiIiIiIiIiIqMhx+h4RERERERGRC0RRhNls9nYYhcJisUCn0yE9PR02m83b4ZATxWWc9Ho9tFrtPZ+HSSkiIiIiIiKifJjNZpw7dw6iKHo7lEIhSRJCQkJw8eLFfJtTk/cUp3EKCgpCSEjIPcXBpBQRERERERFRHiRJwtWrV6HVahEREQGNpuR1whFFEcnJyfD39y+Rz6+kKA7jJEkSUlNTER8fDwAIDQ0t8LmYlCIiIiIiIiLKg9VqRWpqKsLCwuDr6+vtcAqFPDXRx8eHSalirLiMk8lkAgDEx8cjODi4wFP5mJQiIiIiIiJVMZlMOHnyJH7//XflDyOiwiT37jEYDF6OhKj4kBO0FoulwEkppj+JiIiIiEhVNBoNoqKiUKFCBVZ0UJHydg8fouLEE+8H/gQnIiIiIiIiIqIix6QUERERERGpitlsxhtvvIFFixbBbDZ7OxyiEqFy5cqYO3eut8PwmKioKMyYMcPbYVA+mJQiIiIiIiJVsVgs+OSTT7B69WpYLBZvh0PkMlGUcDYhGX9fvI2zCckQRalIHvfixYsYOHAgwsLCYDAYEBkZiWHDhuHGjRtF8vhEzrDROREREREREVEhO3o5ESsPXMLp+GRkWEQY9RpUDfZH9wbhqFUxsNAe9+zZs2jSpAmqV6+OZcuWITo6GseOHcPo0aOxfv167N69G2XKlCm0x3fGZrNBEAT2hbvPcfSJiIiIiIiICtHRy4n4bMspHLmUiCCTAVHl/BBkMuDIpcztRy8nFtpjv/LKKzAYDNi4cSNiYmJQqVIldOzYEZs3b8bly5fx1ltvKccmJyejd+/e8Pf3R1hYGGbNmmV3rokTJ6JSpUowGo0ICwvD0KFDlX1msxljxoxBxYoV4efnh8aNG2Pr1q3K/kWLFiEoKAhr165FzZo1YTQaMX/+fPj4+OD27dt2jzN06FDExMQot3fu3IkWLVrAZDIhIiICQ4cORUpKirI/Pj4eXbp0gclkQnR0NJYsWeKhV48KG5NSRERERERERG6QJAkZVptL/9LMVny/7yJupGSgcjlf+Bo0ECDB16BB5XK+uJGSgR/2X0Sa2erS+STJ9Sl/N2/exK+//oqXX34ZJpPJbl9ISAh69+6N7777TjnnrFmzUKdOHRw4cADjxo3D66+/jk2bNgEAVqxYgU8//RSff/45Tp06hdWrV6N27drK+Z5//nn8+eefWL58OQ4fPowePXqgQ4cOOHXqlHJMamoqpk6dii+//BLHjh1Dnz59EBQUhJUrVyrH2Gw2fP/99+jduzcA4MiRI2jfvj26deuGw4cP47vvvsOOHTvw6quvKvfp378/4uLi8Ntvv2HFihWYM2cO4uPj3RhR8hZO3yPVE0UJ5/5Lwflk4Nx/KahaIRAaDZdqJSIiIiKiwmG2iZj483GXjr2TZsH+87dg0GlwO9Waa7/FJuLXo9fxX5IZpUz6fM83sWtNGHValx771KlTkCQJNWrUcLi/Ro0auHXrFhISEgAAjRo1wtixY6HRaFC9enX8+eef+PTTTxEbG4sLFy4gJCQEbdu2hV6vR6VKldCoUSMAwJkzZ7Bs2TJcunQJYWFhAIBRo0Zhw4YNWLhwIaZMmZL5XC0WzJkzB3Xr1lVieOaZZ7B06VIMHDgQALBlyxbcunULPXr0AAB8+OGH6NWrF4YPHw4AqFatGj777DPExMRg7ty5uHDhgjINsXHjxgCABQsWOH3OVLwwKUWqJs/LPnUtCVfjNdiz9l9UCwko9HnZRERERERErrDYRNhECTonH5xrNQJsogSLTSziyKBUSAlCZmxykknWpEkTZQW7Hj16YMaMGahcuTI6dOiATp06oUuXLtDpdDhw4AAkSUL16tXt7p+RkYGyZcsqtw0GA+rUqWN3TO/evdGkSRNcuXIFYWFhWLJkCTp16oTSpUsDAPbv34/Tp0/bTcmTJAmiKOLcuXM4efIkdDodGjZsqOx/8MEHERQUdG8vDhUJJqVIteR52TdTzKhQygirDxDoq8eRS4m4fCsNQ9tUY2KKiIiIiIg8zqDVYGLXmi4de+6/FLy39jiCTHr4G3P/CZ6cYcXtNAtGtKuO6HJ+Lj22q6pWrQpBEHD8+HE8+eSTufb/+++/KF26NMqVK+f0HHLCKiIiAidOnMCmTZuwefNmvPzyy/jwww+xbds2iKIIrVaL/fv3Q6u1r+Ly9/dXvjaZTMr5ZI0aNUKVKlWwfPlyvPTSS/jxxx+xcOFCZb8oihgyZIhd/ypZpUqVcOLECbs4SV2YlCJVEkUJKw9cws0UM6oG+0OSJNwSAH+jDgHBepyOT8aqA5dRM7QUp/IRERERlTAmkwkHDx7EH3/8katPDlFREATB5Sl01YMDUL1CAI5cSkRAsN4ueSJJEq7fyUCd8CBUDw7w+N8uZcuWRWxsLObMmYPXX3/d7v1y7do1LFmyBH379lVi2rt3r939d+/ejQcffFC5bTKZ0LVrV3Tt2hWvvPIKHnzwQRw5cgT169eHzWZDfHw8mjdv7nacvXr1wpIlSxAeHg6NRoPHH39c2degQQMcO3YMVatWdXjfGjVqwGq1Yt++fUql14kTJ3I1T6fiiY3OSZXibqTgdHwyQgMzM+3xd9Jx25y5TxAEhAaacCo+CXE3UvI+ERERERGpjkajwUMPPYRKlSpxOXkq9jQaAd0bhKOMnwGn45ORnG6FTZSQnG7F6fhklPEzoFuDioX2Yfrs2bORkZGB9u3bY/v27bh48SI2bNiA2NhYVKxYEZMnT1aO/euvv/Dhhx/i5MmT+N///ocffvgBw4YNA5C5et6CBQtw9OhRnD17FosXL4bJZEJkZCSqV6+O3r17o2/fvli1ahXOnTuHvXv3Ytq0aVi3bl2+Mfbu3RsHDhzA5MmT8fTTT8PHx0fZN3bsWOzatQuvvPIKDh06hFOnTuHnn3/Ga6+9BgB44IEH0KFDBwwePBh//fUX9u/fj0GDBjFhrRL8CU6qlJRuRYZFhMmghShJuHArDTcyBIhi5pxok0GLDIuIpPTcjQSJiIiIiIiKUq2KgRjaphpqhwfidpoZcf+l4HaaGXXCgwq97Ui1atWwb98+VKlSBc888wyqVKmCF154Aa1atcKuXbtQpkwZ5dhXX30V+/fvR/369fHee+/h448/Rvv27QEAQUFBmD9/Ppo1a4Y6depgy5YtWLNmjdIzauHChejbty9GjhyJBx54AF27dsVff/2FiIgIl2J85JFHcPjwYWXVPVmdOnWwbds2nDp1Cs2bN0f9+vXxzjvvIDQ0VDlm4cKFiIiIQExMDLp164YXXngBwcHBnnj5qJBx+h6pUoCPDka9BmlmG0wGDSQJgASIyExKpZltMOo1CPDhtzgRERFRSWM2m/Hee+/h1KlTykpgRMVdrYqBqBlaCnE3UpCUbkWAjw5RZf2KpN1IZGSkXZ8mR86ePYs7d+6gVKlSDisQn3zySYd9qWR6vR6TJk3CpEmTHO7v378/+vfv7/T+e/bscbrvkUcewcaNG53uDwkJwdq1a+22Pffcc06Pp+KDf7GTKkWV9UPVYH8cuZSIqLK+ynZJypyXfTUxDXXCgxBVNv9GgURERESkLhaLBe+//z4AYN68eV6Ohsh1Go2AyuX98z+Q6D7BpBSpkjwv+/KtNJxJSIHFJkKSgOR0K26mphX6vGwiIiIiIiIiujde7Sm1fft2dOnSBWFhYRAEAatXr1b2WSwWjB07FrVr14afnx/CwsLQt29fXLlyxe4cGRkZeO2111CuXDn4+fmha9euuHTpUhE/E/IGeV72g6EBMNtEpItAYpqlSOZlExEREREREdG98WpSKiUlBXXr1sXs2bNz7UtNTcWBAwfwzjvv4MCBA1i1ahVOnjyJrl272h03fPhw/Pjjj1i+fDl27NiB5ORkdO7cGTabraieBnlRrYqBGN62Oh6uFIRIfwkjYqvi7cdrMCFFREREREREVMx5dfpex44d0bFjR4f7AgMDsWnTJrtts2bNQqNGjXDhwgVUqlQJiYmJWLBgARYvXoy2bdsCAL799ltERERg8+bNyioBVPIF+OgRoAcqBpk4ZY+IiIiIiIhIBVTVUyoxMRGCICAoKAgAsH//flgsFrRr1045JiwsDLVq1cLOnTudJqUyMjKQkZGh3L5z5w6AzCmDFotF2S5/nX0bFT8ZZgtEUQQApJstHK9iju8rdeA4qQfHSh04TurBsVKHnNfsHK/iq6S8pywWCyRJgiiKyt8eJY0kScr/JfU5lgTFaZxEUYQkSbBYLNBqtXb7XH3PqyYplZ6ejjfeeAO9evVCqVKlAADXrl2DwWBA6dKl7Y6tUKECrl275vRcU6dOdbhM5caNG+Hr65tre86KLSpebqQDly9nzkTdvv0PlPXxckDkEr6v1IHjpB4cK3XgOKkHx6p4S09PV77+7bff4OPDC8DiTu3vKZ1Oh5CQECQnJ8NsNns7nEKVlJTk7RDIBcVhnMxmM9LS0rB9+3ZYrVa7fampqS6dQxVJKYvFgmeffRaiKGLOnDn5Hi9JEgTB+RSucePGYcSIEcrtO3fuICIiAu3atVMSXvLjbtq0CbGxsdDr9ff2JKjQnL+Rin+2n8XlS5fQpFkzVK3AflLFGd9X6sBxUg+OlTpwnNSDY6UONpsN27dvx19//YVOnToxKVWMlZT3VHp6Oi5evAh/f/8S+/0mSRKSkpIQEBCQ59/T5F3FaZzS09NhMpnQokWLXO8LeUZafop9UspisaBnz544d+4cfvvtN7ukUUhICMxmM27dumVXLRUfH4+mTZs6PafRaITRaMy1Xa/XO/xB6Ww7FQ+CVguNJrNSSqPRcaxUgu8rdeA4qQfHSh04TurBsSre9Ho9Hn30Udy8eRM+Pj4cKxVQ+3vKZrNBEARoNBrlb4+SRp4KJj9PKp6K0zhpNBoIguDw/e3q+71Yf6fJCalTp05h8+bNKFu2rN3+hx9+GHq93q4U9OrVqzh69GieSSkqWWyi5PBrIiIiIiIiKhoTJ05EvXr1lNv9+/fHk08+WeRxxMXFQRAEHDp0KM/jTpw4gZCQkEKdBpeRkYFKlSph//79hfYYaufVpFRycjIOHTqkfLOcO3cOhw4dwoULF2C1WvH0009j3759WLJkCWw2G65du4Zr164pc3gDAwMxcOBAjBw5Elu2bMHBgwfRp08f1K5dW1mNj0o+u6SUxKQUERERUUlnNpvx8ccf48cffyzx/X2I7kX//v0hCIJSzVK5cmWMGjUKKSkphf7YM2fOxKJFi1w61tVEkie99dZbeOWVVxAQEAAA2Lp1KwRBwO3bt+1eN2f/gMxZWkOGDEGlSpVgNBoREhKC9u3bY9euXQAyZ2mNGjUKY8eOLbLnpTZenb63b98+tGrVSrkt93nq168fJk6ciJ9//hkA7LKtAPD777+jZcuWAIBPP/0UOp0OPXv2RFpaGtq0aYNFixbl6vxOJRcrpYiIiIjuLxaLBePGjQMAzJgxw7vBEBVzHTp0wMKFC2GxWPDHH39g0KBBSElJwdy5c3Md68lVEgMDi2+v30uXLuHnn392+vNj5syZ+OCDD5TboaGhWLhwITp06GB3XPfu3WGxWPD111+jcuXKuH79OrZs2YKbN28qx/Tu3RujR4/GP//8gxo1ahTK81Ezr1ZKtWzZEpIk5fq3aNEiREVFOdwnSZKSkAIAHx8fzJo1Czdu3EBqairWrFmDiIgI7z0pKnJituookZVSRERERERECrmCJyIiAr169ULv3r2xevVqAHen3H311VeoWrUqKlSoAEmSkJiYiBdeeAHBwcEoVaoUWrdujb///tvuvB988AEqVKiAgIAADBw40G5VTCD39D1RFDFt2jRUrVoVRqMRlSpVwuTJkwEA0dHRAID69etDEAS7v/kXLlyIGjVqwMfHBw8++GCuxc/27NmD+vXrw8fHBw0bNsTBgwfzfU2+//571K1bF+Hh4Q73BwYGIiQkRPkHAEFBQXbbbt++jR07dmDatGlo1aoVIiMj0ahRI4wbNw6PP/64cq6yZcuiadOmWLZsWb5x3Y+KfaNzovxYWSlFRERERETekNc0OK0WyL4iWV7HajSAyZT/sX5+7sXngMlksquIOn36NL7//nv88MMPSEtLAwA8/vjjKFOmDNatW4fAwEB8/vnnaNOmDU6ePIkyZcrg+++/x4QJE/C///0PzZs3x+LFi/HZZ5+hcuXKTh933LhxmD9/Pj799FM89thjuHr1Kv79918AmYmlRo0aYfPmzXjooYdgMBgAAPPnz8eECRMwe/Zs1K9fHwcPHsTgwYPh5+eHfv36ISUlBZ07d0br1q3x7bff4ty5cxg2bFi+r8H27dvRsGHDe3kZ4e/vD39/f6xevRqPPvqow8XUZI0aNcIff/xxT49XUjEpRaonitkrpbwYCBERERER3V/8/Z3v69QJ+OWXu7eDg4HUVMfHxsQAW7fevR0VBfz3X+7j7nFmyJ49e7B06VK0adNG2WY2m7F48WKULVsWd+7cwe+//44jR44gPj5eSbR89NFHWL16NVasWIEXXngBM2bMwIABAzBo0CAAwPvvv4/NmzfnqpaSJSUlYebMmZg9ezb69esHAKhSpQoee+wxAED58uUBZFYVyZVJAPDee+/h448/Rrdu3QBkVlQdP34cn3/+Ofr166f0n/7qq6/g6+uLhx56CJcuXcJLL72U5+sQFxeHhx9+uCAvoUKn02HRokUYPHgw5s2bhwYNGiAmJgbPPvss6tSpY3dsxYoVERcXd0+PV1IV69X3iFzBnlJERERERESOrV27Fv7+/vDx8UGTJk3QokULzJo1S9kfGRmpJIUA4MCBA0hOTkbZsmWVaiB/f3+cO3cOZ86cAQD8888/aNKkid3j5Lyd3T///IOMjAy7ZFh+EhIScPHiRQwcONAujvfff98ujrp168LX19elOGRpaWnwyV7FVkDdu3fHlStX8PPPP6N9+/bYunUrGjRokKvBu8lkQqqzhOR9jpVSpHo29pQiIiIiIiJvSE52vi/n4lvx8c6P1eSoF/FgVU2rVq0wd+5c6PV6hIWFQa/X2+33yzElUBRFhIaGYmv2yq0sQUFBBYrBlH1qootEUQSQOYWvcePGdvvkhc2kAv79V65cOdy6datA983Jx8cHsbGxiI2Nxfjx4zFo0CBMmDAB/fv3V465efOmXeKP7mJSilSPlVJEREREROQV7vR4Kqxj8z2VH6pWrery8fXr18e1a9eg0+kQFRXl8JgaNWpg9+7d6Nu3r7Jt9+7dTs9ZrVo1mEwmbNmyRZnyl53cQ8pmsynbKlSogIoVK+Ls2bPo3bu3w/PWrFkTixcvRlpampL4yiuO7M/x+PHj+R5XEDVr1lQaycuOHj2K+vXrF8rjqR2n75HqMSlFREREdH/x8fHBpk2b8N5773lkCg4R3dW2bVs0adIETz75JH799VfExcVh586dePvtt7Fv3z4AwLBhw/DVV1/hq6++wsmTJzFhwgQcO3bM6Tl9fHwwduxYjBkzBt988w3OnDmD3bt3Y8GCBQCA4OBgmEwmbNiwAdevX0diYiKAzNUBp06dipkzZ+LkyZM4cuQIFi5ciE8++QQA0KtXL2g0GgwcOBDHjx/HunXr8NFHH+X7HNu3b49du3bZJcHcdePGDaXB+uHDh3Hu3Dn88MMPmD59Op544gm7Y//44w+0a9euwI9VkrFSilTPLinF6XtEREREJZ5Wq0VMTAxSUlKUaTxE5BmCIGDdunV46623MGDAACQkJCAkJAQtWrRAhQoVAADPPPMMzpw5g7FjxyI9PR3du3fHSy+9hF9//dXped955x3odDqMHz8eV65cQWhoKF588UUAmU3DP/vsM7z77rsYP348mjdvjq1bt2LQoEHw9fXFhx9+iDFjxsDPzw+1a9fG8OHDAWSugLdmzRq8+OKLqF+/PmrWrIlp06ahe/fueT7HTp06Qa/XY/PmzWjfvn2BXid/f380btwYn376Kc6cOQOLxYKIiAgMHjwYb775pnLcrl27kJiYiKeffrpAj1PSCVJBJ2GWIHfu3EFgYCASExNRqlQpZbvFYsG6deuUb1gqnjYeu4Yt/1zHxQsX0De2ATrUrujtkCgPfF+pA8dJPThW6sBxUg+OlXpwrNShpIxTeno6zp07h+jo6BJbnSeKIu7cuYNSpUpBk7PHVQk0Z84c/PTTT3km0jyhR48eqF+/vl2i6l4Up3HK633hLM+SU8n/TqMSL3tz86xeeERERERUglksFsydOxfr1q2DxWLxdjhEpEIvvPACWrRogaSkpEJ7jIyMDNStWxevv/56oT2G2nH6HqmeLVsiitP3iIiIiEo+s9mMYcOGAQCmTZtmtxw8EZErdDod3nrrrUJ9DKPRiLfffrtQH0PtWClFqmezq5RiUoqIiIiIiIhIDZiUItWzZZuzx0opIiIiIiIiInVgUopUL/v0PVZKEREREREREakDk1KketkTUVYmpYiIiIiIiIhUgUkpUj27nlKcvkdERERERESkCkxKkeplr47KPpWPiIiIiIiIiIovnbcDILpX2afvsdE5ERERUclnNBqxevVq7Nu3D0aj0dvhEBFRAbFSilTPvlKKSSkiIiKikk6n06FTp05o2LAhdDp+zk5UWLZu3QpBEHD79m0AwKJFixAUFOTVmABg4sSJqFevnrfDuCdmsxlVq1bFn3/+6e1QHBo1ahSGDh1a6I/DpBSpnsikFBERERERUS79+/eHIAgQBAF6vR6VK1fGqFGjkJKSUqDzPfPMMzh58qSHo8xt5cqVaNmyJQIDA+Hv7486derg3Xffxc2bNwv9sYvKF198gcjISDRr1gwAEBcXh4EDByI6OhomkwlVqlTBhAkTYDab7e534cIFPPvsswgICEC5cuUwdOhQu2O2bt2KJ554AqGhofDz80O9evWwZMkSu3NcvXoVvXr1wgMPPACNRoPhw4fnim/MmDFYuHAhzp075/knnw2TUqR6bHROREREdH+xWCz45ptvsGXLFlgsFm+HQ1SsdejQAVevXsXZs2fx/vvvY86cORg1alSBzmUymRAcHOzhCO299dZbeOaZZ/DII49g/fr1OHr0KD7++GP8/fffWLx4caE+dlGaNWsWBg0apNz+999/IYoiPv/8cxw7dgyffvop5s2bhzfffFM5xmazoUuXLkhNTcX27duxfPlyrFy5EiNHjlSO2blzJ+rUqYOVK1fi8OHDGDBgAPr27Ys1a9Yox2RkZKB8+fJ46623ULduXYfxBQcHo127dpg3b14hPPu7mJQi1bOxUoqIiIjovmI2mzFo0CDMmjUrVxUBEdkzGo0ICQlBREQEevXqhd69e2P16tUAMpMTQ4cORXBwMHx9fdGhQwfs3bvX6bkcTd/7+eef0bBhQ/j4+KBcuXLo1q0bAODdd99F7dq1c53j4Ycfxvjx4x2ef8+ePZgyZQo+/vhjfPjhh2jatCmioqIQGxuLlStXol+/fnbHL168GFFRUQgMDMSzzz6LpKQkZd+GDRvw2GOPISgoCGXLlkXnzp1x5swZZX9cXBwEQcCqVavQqlUr+Pr6om7duti1a5fdY8yfPx8RERHw9fXFU089hU8++STXa7BmzRo8/PDD8PHxQeXKlTFp0iRYrVanr+OBAwdw+vRpPP7448q2Dh06YOHChWjXrh0qV66Mrl27YtSoUVi1apVyzMaNG3H8+HF8/vnnqF+/Ptq2bYuPP/4Y8+fPx507dwAAb775Jt577z00bdoUVapUwdChQ9GhQwf8+OOPynmioqIwc+ZM9O3bF4GBgU7j7Nq1K5YtW+Z0vycwKUWqlz0RJTIpRURERERERSQlJcXpv/T0dJePTUtLc+lYTzCZTEqF4ZgxY7By5Up8/fXX2LdvHypXroyOHTu6PE3ul19+Qbdu3fD444/j4MGD2LJlCxo2bAgAGDBgAI4fP26X5Dp8+DAOHjyI/v37OzzfkiVL4O/vj5dfftnh/uzJoDNnzmD16tVYu3Yt1q5di23btuGDDz5Q9qekpGDEiBHYu3cvtmzZAo1Gg6eeegqiaL9k+1tvvYVRo0bh0KFDqF69Ov7v//5PSSj9+eefePHFFzFs2DAcOnQIsbGxmDx5st39f/31V/Tp0wdDhw5VEkaLFi3KdVx227dvR/Xq1VGqVCmnxwBAYmIiypQpo9zetWsXatWqhdDQUGVb+/btkZGRgf3797t8Hlc1atQIFy9exPnz592+r6vYFZBUz65SijkpIiIiIiIqIv7+/k73derUCb/88otyOzg4GKmpqQ6PjYmJwdatW5XbUVFR+O+//3IdJ91ju5I9e/Zg6dKlaNOmDVJSUjB37lwsWrQIHTt2hCiKmDlzJurVq4cFCxZg9OjR+Z5v8uTJePbZZzFp0iRlmzwdLDw8HO3bt8fChQvxyCOPAAAWLlyImJgYVK5c2eH5Tp06hcqVK0Ov1+f72KIoYtGiRQgICAAAPPfcc9iyZYuSDOrevbvd8QsWLEBwcDCOHz+OWrVqKdtHjRqlVCxNmjQJDz30EE6fPo0HH3wQs2bNQseOHZXpjtWrV8fOnTuxdu1au9fgjTfeUKq4KleujPfeew9jxozBhAkTHMYeFxeHsLCwPJ/fmTNnMGvWLHz88cfKtmvXruWaPlm6dGkYDAZcu3bN4XlWrFiBvXv34vPPP8/z8RypWLGiEm9kZKTb93cFK6VI9bL3kWKlFBERERER0V1r166Fv78/fHx80KRJE7Ro0QKzZs3CmTNnYLFYlEbbAKDX6/HII4/gn3/+cenchw4dQps2bZzuHzx4MJYtW4b09HRYLBYsWbIEAwYMcHq8JEkQBMGlx46KilISUgAQGhqK+Ph45faZM2fQq1cvVK5cGaVKlUJ0dDSAzEbh2dWpU8fuHACU85w4cQKNGjWyOz7n7f379+Pdd9+Fv7+/8m/w4MG4evWq0yRkWloafHx8nD63K1euoEOHDujRo4dd3ykADl8fZ6/b1q1b0b9/f8yfPx8PPfSQ08dzxmQyAYDT5+EJrJQi1bOvlGJSioiIiIiIikZycrLTfVqt1u529oRJThqNfb1IXFzcPcWVXatWrTB37lzo9XqEhYUpVUhXr14FkDvJ4U5iSE5aONOlSxcYjUb8+OOPMBqNyMjIyFXBlF316tWxY8cOWCyWfKulcu4XBMFual6XLl0QERGB+fPnIywsDKIoolatWrn60GU/j/y85fM4ei1yVquJoohJkyYpvbSyc5Z4KleuHI4cOeJw35UrV9CqVSs0adIEX3zxhd2+kJAQ/PXXX3bbbt26BYvFggoVKtht37ZtG7p06YJPPvkEffv2dfhY+ZGncZYvX75A93cFK6VI9bInotjonIiIiIiIioqfn5/TfzkTEnkdmzO54+y4gsZYtWpVREZG2iVgqlatCoPBgB07dijbLBYL9u/fjxo1arh07jp16mDLli1O9+t0OvTr1w8LFy7EwoUL8eyzz8LX19fp8b169UJycjLmzJnjcP/t27ddiuvGjRv4559/8Pbbb6NNmzaoUaMGbt265dJ9s3vwwQexZ88eu2379u2zu92gQQOcOHECVatWzfUvZ7JRVr9+ffz777+5ElyXL19Gy5Yt0aBBAyxcuDDX/Zs0aYKjR4/aTdXbuHEjjEYjHn74YWXb1q1b8fjjj+ODDz7ACy+84Pbzlh09ehR6vb5AVVauYqUUqZ7NxqQUERERERGRO/z8/PDSSy9h9OjRKFOmDMLDwzFlyhSkpqZi4MCBLp1jwoQJaNOmDapUqYJnn30WVqsV69evx5gxY5RjBg0apCS5/vzzzzzP17hxY4wZMwYjR47E5cuX8dRTTyEsLAynT5/GvHnz8Nhjj2HYsGH5xlW6dGmULVsWX3zxBUJDQ3HhwgW88cYbLj2n7F577TW0aNECn3zyCbp06YLffvsN69evt6ueGj9+PDp37oyIiAj06NEDGo0Ghw8fxpEjR/D+++87PG+rVq2QkpKCY8eOKf2trly5gpYtW6JSpUr46KOPkJCQoBwfEhICAGjXrh1q1qyJF198ER9//DFu376NUaNGYfDgwUrTdDkhNWzYMHTv3l1JYBkMBrtm54cOHQKQWe2XkJCAQ4cOwWAwoGbNmsoxf/zxB5o3b55vRdy9YKUUqV72SimR0/eIiIiISjyj0YilS5di9OjRMBqN3g6HSLU++OADdO/eHc899xwaNmyIs2fPYv369ShdurRL92/ZsiV++OEH/Pzzz6hXrx5at26da3pZtWrV0LRpUzzwwANo3LhxvuecNm0ali5dir/++gvt27fHQw89hBEjRqBOnTpKM/H8aDQaLF++HPv370etWrXw+uuv48MPP3Tpvtk1a9YM8+bNwyeffIK6detiw4YNeP311+2q4Nq3b4+1a9di06ZNeOSRR/Doo4/ik08+ybMxeNmyZdGtWzcsWbJE2bZx40acPn0av/32G8LDwxEaGqr8k2m1WqxZswZGoxHNmzdHz5498eSTT+Kjjz5Sjlm0aBFSU1MxdepUu3PknF5Yv3591K9fH/v378fSpUtRv359dOrUye6YZcuWYfDgwW6/bu4QpHtt318C3LlzB4GBgUhMTLRbktFisWDdunXo1KmTS93/yTvG/3QUGRYbLl64gOpVojDxidreDonywPeVOnCc1INjpQ4cJ/XgWKkHx0odSso4paen49y5c4iOjs6zQbWaiaKIO3fuoFSpUk6nnRWEJEl48MEHMWTIEIwYMcJj5/WWwYMH499//8Uff/xxT+c5cuQI2rZti9OnT9s1bM9PYY1TTr/88gtGjx6Nw4cPQ6dzPMkur/eFszxLTpy+R6pn3+jci4EQERERERGRIj4+HosXL8bly5fx/PPPezucAvnoo48QGxsLPz8/rF+/Hl9//bXTnlfuqF27NqZPn464uDjUrl38CitSUlKwcOFCpwkpT2FSilRNkiRkbyMlsqcUERERUYlntVqxYsUKHDx4EO3atVN1BQ5RSVahQgWUK1cOX3zxhctTAoubPXv2YPr06UhKSkLlypXx2WefYdCgQR45t6vTEb2hZ8+eRfI4TEqRquVsbG7jbFQiIiKiEi8jIwO9evUCALz55puF2oSXiAquJHQL+v77770dQonGRuekajmTUJLEaikiIiIiIiIiNWBSilRNFHNvY7UUERERERERUfHHpBSpmtVBVirnlD4iIiIiIiJPKAnT0Yg8RXRUJeIm9pQiVZPfA4KQbRt/URARERERkQfp9XoIgoCEhASUL18eQvY/QEoIURRhNpuRnp4OjYb1K8VVcRgnSZJgNpuRkJAAjUYDg8FQ4HMxKUWqJk/V02s1QNbvBVZKERERERGRJ2m1WoSHh+PSpUuIi4vzdjiFQpIkpKWlwWQylcikW0lRnMbJ19cXlSpVuqfkGJNSpGpyAkor3J2LyqQUERERERF5mr+/P6pVqwaLxeLtUAqFxWLB9u3b0aJFC+j1em+HQ04Ul3HSarXQ6XT3nBhjUopUTZ6qp9UI0LBSioiIiOi+YDAY8OWXX+Lvv/++p2kjRO7SarXQarXeDqNQaLVaWK1W+Pj4MClVjJW0ceJEUVI1a1YCSiMISl8prr5HREREVLLp9Xr07dsXbdq0KRF/lBER3a+YlCJVE8VslVLKNu/FQ0RERERERESuYVKKVM0q5p6+Z2VWioiIiKhEs1qtWLduHfbt2wer1ertcIiIqIDYU4pU7W6j87tJKeakiIiIiEq2jIwMPPnkkwCAkSNHwmQyeTcgIiIqEFZKkarJjc412abvsacUERERERERUfHHpBSp2t1KKUAQJLttRERERERERFR8MSlFqqYkpbTZpu+xUoqIiIiIiIio2GNSilTNUU8pVkoRERERERERFX9MSpGqyf2jtNl7SjEpRURERERERFTsMSlFqiaKd5NSAqfvEREREREREamGztsBEN0La1ZSSpNt+p6VlVJEREREJZrBYMDMmTNx7NgxGAwGb4dDREQFxEopUrXslVKaHNuIiIiIqGTS6/V46aWX0KlTJ+j1em+HQ0REBcSkFKmaXU8pNjonIiIiIiIiUg0mpUjVrI5W32NPKSIiIqISzWazYdu2bThy5AhsNpu3wyEiogJiTylSNXmqnkYjQAAgARBFr4ZERERERIUsPT0dsbGxAIBXX30VPj4+Xo6IiIgKgpVSpGo2pVIq8x/ASikiIiIiIiIiNWBSilRNzNZTSshKSrHROREREREREVHxx6QUqZpVZKNzIiIiIiIiIjViUopUzZa90XnWNiuTUkRERERERETFHpNSpGrK9D1ttul77ClFREREREREVOwxKUWqZstaaU8rcPoeERERERERkZrovB0A0b2wiZlZKY3m7vQ9VkoRERERlWx6vR5Tp07Fv//+C71e7+1wiIiogJiUIlXLXiklT9+z2piUIiIiIirJDAYDRo4ciXXr1sFgMHg7HCIiKiBO3yNVkyultBoBWnn6HiuliIiIiIiIiIo9JqVI1ZTV9zTZGp2zpxQRERFRiWaz2bBv3z6cOnUKNpvN2+EQEVEBcfoeqZo8U08j3M2wslKKiIiIqGRLT09H06ZNAQCDBg2Cj4+PlyMiIqKC8Gql1Pbt29GlSxeEhYVBEASsXr3abr8kSZg4cSLCwsJgMpnQsmVLHDt2zO6YjIwMvPbaayhXrhz8/PzQtWtXXLp0qQifBXmTmK1SSiNIdtuIiIiIiIiIqPjyalIqJSUFdevWxezZsx3unz59Oj755BPMnj0be/fuRUhICGJjY5GUlKQcM3z4cPz4449Yvnw5duzYgeTkZHTu3JllvPcJuSoqMymVtY1JKSIiIiIiIqJiz6vT9zp27IiOHTs63CdJEmbMmIG33noL3bp1AwB8/fXXqFChApYuXYohQ4YgMTERCxYswOLFi9G2bVsAwLfffouIiAhs3rwZ7du3L7LnQt6h9JQSBAjyNuakiIiIiIiIiIq9YttT6ty5c7h27RratWunbDMajYiJicHOnTsxZMgQ7N+/HxaLxe6YsLAw1KpVCzt37nSalMrIyEBGRoZy+86dOwAAi8UCi8WibJe/zr6NihezxQpRFCGJNmgEQBRFWKxWjlkxxveVOnCc1INjpQ4cJ/XgWKlDzmt2jlfxxfeUenCs1EEt4+RqfMU2KXXt2jUAQIUKFey2V6hQAefPn1eOMRgMKF26dK5j5Ps7MnXqVEyaNCnX9o0bN8LX1zfX9k2bNrkdPxWNExc1uGMGdlvjoBGAy5cuIf0/CesSj3s7NMoH31fqwHFSD46VOnCc1INjVbylp6crX//2229sdK4CfE+pB8dKHYr7OKWmprp0XLFNSskEQbC7LUlSrm055XfMuHHjMGLECOX2nTt3EBERgXbt2qFUqVLKdovFgk2bNiE2NhZ6vb6Az4AK04nNp3EjxYzmj4bj9+07UDE8HBFlfNEpprK3QyMn+L5SB46TenCs1IHjpB4cK3VISUlRvm7dujWCgoK8Fwzlie8p9eBYqYNaxkmekZafYpuUCgkJAZBZDRUaGqpsj4+PV6qnQkJCYDabcevWLbtqqfj4eGWJWEeMRiOMRmOu7Xq93uGgOttO3icJAjQaDYwGPTQCoNFoAEHD8VIBvq/UgeOkHhwrdeA4qQfHqnjz9fXF22+/jVOnTsHX15djpQJ8T6kHx0odivs4uRqbV1ffy0t0dDRCQkLsStLMZjO2bdumJJwefvhh6PV6u2OuXr2Ko0eP5pmUopJDFO+uvidw9T0iIiKi+4LBYMD48ePxf//3fzAYDN4Oh4iICsirlVLJyck4ffq0cvvcuXM4dOgQypQpg0qVKmH48OGYMmUKqlWrhmrVqmHKlCnw9fVFr169AACBgYEYOHAgRo4cibJly6JMmTIYNWoUateurazGRyWbNVtSSs6wihKTUkRERERERETFnVeTUvv27UOrVq2U23Kfp379+mHRokUYM2YM0tLS8PLLL+PWrVto3LgxNm7ciICAAOU+n376KXQ6HXr27Im0tDS0adMGixYtglarLfLnQ0VProrSCoCGlVJERERE9wVRFHHs2DFcuHABoih6OxwiIiogryalWrZsCSmPqhZBEDBx4kRMnDjR6TE+Pj6YNWsWZs2aVQgRUnEnV0VpNMLdpBQrpYiIiIhKtLS0NNSvXx8A8NxzzznsF0tERMVfse0pReSKu5VSd5NSIiuliIiIiIiIiIo9JqVItSRJgpx/0moEZOWklD5TRERERERERFR8MSlFqpW9d5RWw0opIiIiIiIiIjVhUopUy+okKcWeUkRERERERETFH5NSpFpituSTVhCUb2abiDwb6BMRERERERGR9zEpRaolT98ThLv/ZJzBR0RERERERFS86bwdAFFBiWLm/1pBgCAI0GZLStlECVqN4PiORERERKRqer0eI0aMwNmzZ6HX670dDhERFRCTUqRacu8oOflkXynFUikiIiKikspgMOCDDz7AunXrYDAYvB0OEREVEKfvkWpZs0qlNFnZqOzfzDbO3yMiIiIiIiIq1piUItVSpu9lfRdn7ytlZVKKiIiIqMQSRRFxcXG4fv06RPmikIiIVIfT90i15EopreZublWnEWCTAJFJKSIiIqISKy0tDdWrVwcA9OzZE0aj0csRERFRQbBSilQrZ6UUcHcqn409pYiIiIiIiIiKNSalSLWURufZOpzLTc9ZKUVERERERERUvDEpRaolNzPXaO4mpeQvWSlFREREREREVLwxKUWqJSeldJrclVJcfY+IiIiIiIioeGNSilTLUaWUPJWPi7AQERERERERFW9MSpFqiVLuSik5QcXpe0RERERERETFm87bARAVlFIpJeSulLKxVIqIiIioxNLpdHjxxRdx/vx56HT8k4aISK34E5xUy5qVlNI67CnllZCIiIiIqAgYjUZ89tlnWLduHYxGo7fDISKiAuL0PVItefqe46QUp+8RERERERERFWdMSpFq2RxUSmmyvqNF9pQiIiIiKrEkSUJCQgISExMh8bqPiEi1OH2PVEtJSjnsKcWLEyIiIqKSKjU1FRUrVgQAdO3aFQaDwcsRERFRQbBSilRLaXTuaPoePzEjIiIiIiIiKtaYlCLVkhNPdpVSWUkpkZVSRERERERERMUak1KkWqKjnlKcvkdERERERESkCkxKkWpZHSSluPoeERERERERkTowKUWqlWelFHtKERERERERERVrTEqRaik9pewqpbL2sVKKiIiIiIiIqFjTeTsAooKSE092jc6zvhZZKUVERERUYul0Ojz33HO4dOkSdDr+SUNEpFb8CU6qZXM0fS/ra6uNSSkiIiKikspoNGLBggVYt24djEajt8MhIqIC4vQ9Ui05KaXJlpTSaVgpRURERERERKQGTEqRaslJKZ2jRueiV0IiIiIioiIgSRJSUlKQnp4OiR9GEhGpFqfvkWrJjc412XtKabj6HhEREVFJl5qaitKlSwMAbt26BYPB4OWIiIioIFgpRaol5tFTSuTqe0RERERERETFGpNSpFp3G53f3aYV7PcRERERERERUfHEpBSplrzAXvbpexpO3yMiIiIiIiJSBSalSLVsYmY3c53m7rexVuD0PSIiIiIiIiI1YFKKVEteYU+TffpeVqWUlUkpIiIiIiIiomKNSSlSLTFrip5dpZTc6JzT94iIiIiIiIiKNZ23AyAqKMeNzgW7fURERERU8mi1WnTr1g3Xrl2DVqv1djhERFRATEqRaslT9Bw2OmdSioiIiKjE8vHxwfLly7Fu3Tr4+Ph4OxwiIiogTt8j1RKVSqm7SSml0Tmn7xEREREREREVa0xKkWpZHSWllEopr4RERERERERERC7i9D1SLbkayj4pZb+PiIiIiEqelJQU+Pv7AwBu3bqFoKAg7wZEREQFwkopUi2l0Xn2nlJsdE5ERERERESkCkxKkWrJiSeNw+l7TEoRERERERERFWdMSpFqyYknnYar7xERERERERGpDZNSpFo2yUGllDx9jz2liIiIiIiIiIo1JqVIlURRgpx30jmYvieyUoqIiIiIiIioWGNSilQpeyWUxq7RedZ+JqWIiIiIiIiIijWdOwdLkoRt27bhjz/+QFxcHFJTU1G+fHnUr18fbdu2RURERGHFSWQne9JJqxEAMfNruWrKyqQUERERUYml1WrRsWNHxMfHQ6vVejscIiIqIJcqpdLS0jBlyhRERESgY8eO+OWXX3D79m1otVqcPn0aEyZMQHR0NDp16oTdu3cXdsxEELNVSmmF3I3ORfaUIiIiIiqxfHx88NNPP+Gdd96Bj4+Pt8MhIqICcqlSqnr16mjcuDHmzZuH9u3bQ6/X5zrm/PnzWLp0KZ555hm8/fbbGDx4sMeDJZLJlVKCkJmIstkytyuNzlkpRURERERERFSsuZSUWr9+PWrVqpXnMZGRkRg3bhxGjhyJ8+fPeyQ4ImfkpFP2Kikge6VU5nRTIcd+IiIiIiIiIioeXEpK5ZeQys5gMKBatWoFDojIFUpSSmOfdMqepLKJEnRaJqWIiIiISpqUlBQEBwfDZrPh2rVrCAoK8nZIRERUAG6vvrdhwwbs2LFDuf2///0P9erVQ69evXDr1i2PBkfkjLOklCbbbRv7ShERERGVWKmpqcjIyPB2GEREdA/cTkqNHj0ad+7cAQAcOXIEI0eORKdOnXD27FmMGDHC4wESOSInnHJXSt39WhSLMiIiIiIiIiIicodL0/eyO3fuHGrWrAkAWLlyJTp37owpU6bgwIED6NSpk8cDJHJErpTS5OgZpWWlFBEREREREZEquF0pZTAYkJqaCgDYvHkz2rVrBwAoU6aMUkFFVNjkKihtju9gQRAg56W4Ah8RERERERFR8eV2pdRjjz2GESNGoFmzZtizZw++++47AMDJkycRHh7u8QCJHLFmZaW0mtx5Va1GgGiTIDIpRURERERERFRsuV0pNXv2bOh0OqxYsQJz585FxYoVAQDr169Hhw4dPB4gkSOi3FNKyL26njylj9P3iIiIiIiIiIovtyulKlWqhLVr1+ba/umnn3okICJX2LKm7+m0uZNScl8pVkoRERERlUwajQYtWrTAjRs3oHFQOU9EROrg9k/wli1b4ptvvkFaWlphxEPkEmeNzoG7SSkrk1JEREREJZLJZMLmzZsxefJkmEwmb4dDREQF5HZS6uGHH8aYMWMQEhKCwYMHY/fu3YURF1Ge5KRUzkbnmdsEu2OIiIiIiIiIqPhxOyn18ccf4/Lly/jmm2+QkJCAFi1aoGbNmvjoo49w/fr1woiRKBe5X5TDSqmsbSJ7ShEREREREREVWwWagK3VavHEE09g9erVuHz5Mnr16oV33nkHERERePLJJ/Hbb795JDir1Yq3334b0dHRMJlMqFy5Mt59912IWSuvAYAkSZg4cSLCwsJgMpnQsmVLHDt2zCOPT8XX3UopB43OWSlFREREVKKlpKQgLCwMffv2RUpKirfDISKiArqnroB79uzB+PHj8dFHHyE4OBjjxo1DcHAwunTpglGjRt1zcNOmTcO8efMwe/Zs/PPPP5g+fTo+/PBDzJo1Szlm+vTp+OSTTzB79mzs3bsXISEhiI2NRVJS0j0/PhVfcsJJ5yApxUopIiIiopLvv//+w507d7wdBhER3QO3V9+Lj4/H4sWLsXDhQpw6dQpdunTB8uXL0b59ewhZyYCePXviySefxEcffXRPwe3atQtPPPEEHn/8cQBAVFQUli1bhn379gHIrJKaMWMG3nrrLXTr1g0A8PXXX6NChQpYunQphgwZck+PT8WX0ujcQVJKXpHPJubaRURERERERETFhNtJqfDwcFSpUgUDBgxA//79Ub58+VzHNGrUCI888sg9B/fYY49h3rx5OHnyJKpXr46///4bO3bswIwZMwAA586dw7Vr19CuXTvlPkajETExMdi5c6fTpFRGRgYyMjKU2/InLBaLBRaLRdkuf519GxUPZoslcxqnKNqNm8VigSSKEEURGWYLx64Y4vtKHThO6sGxUgeOk3pwrNQh5zU7x6v44ntKPThW6qCWcXI1PkGS3Jvj9Mcff6B58+YFCspdkiThzTffxLRp06DVamGz2TB58mSMGzcOALBz5040a9YMly9fRlhYmHK/F154AefPn8evv/7q8LwTJ07EpEmTcm1funQpfH19C+fJkEf9e1vA3zcERAZIeDTY/lv4tysCEtIENK0gIsLfSwESERERUaFJT0/Hs88+CwBYvnw5fHx8vBwRERFll5qail69eiExMRGlSpVyepzblVJFlZACgO+++w7ffvstli5dioceegiHDh3C8OHDERYWhn79+inHCTlWYJMkKde27MaNG4cRI0Yot+/cuYOIiAi0a9fO7sWyWCzYtGkTYmNjodfrPfjM6F75nkzAzX8S0CAyCJ3qhdmN1fW9V3AmIQWPPlwRdcMDvR0q5cD3lTpwnNSDY6UOHCf14FipQ/bm5q1bt0ZQUJD3gqE88T2lHhwrdVDLOLna88/tpBQArFixAt9//z0uXLgAs9lst+/AgQMFOaVDo0ePxhtvvKF8ClK7dm2cP38eU6dORb9+/RASEgIAuHbtGkJDQ5X7xcfHo0KFCk7PazQaYTQac23X6/UOB9XZdvIeQdBCo9HAoNfZjY1er4del7lP0Gg5bsUY31fqwHFSD46VOnCc1INjVbzluv7jWBV7HCf14FipQ3EfJ1djc3v1vc8++wzPP/88goODcfDgQTRq1Ahly5bF2bNn0bFjR7cDzUtqaio0GvsQtVptZi8hANHR0QgJCcGmTZuU/WazGdu2bUPTpk09GgsVL7asWadaR6vvabj6HhEREVFJptFo8PDDD6Nq1aq5/l4gIiL1cLtSas6cOfjiiy/wf//3f/j6668xZswYVK5cGePHj8fNmzc9GlyXLl0wefJkVKpUCQ899BAOHjyITz75BAMGDACQOW1v+PDhmDJlCqpVq4Zq1aphypQp8PX1Ra9evTwaCxUvYtbqe1oH0zQ1grz6HpNSRERERCWRyWTCrl27sG7dOphMJm+HQ0REBeR2UurChQtKFZLJZEJSUhIA4LnnnsOjjz6K2bNneyy4WbNm4Z133sHLL7+M+Ph4hIWFYciQIRg/frxyzJgxY5CWloaXX34Zt27dQuPGjbFx40YEBAR4LA4qfqxZCSdNHpVSTEoRERERERERFV9uJ6VCQkJw48YNREZGIjIyErt370bdunVx7tw5uLmQX74CAgIwY8YMzJgxw+kxgiBg4sSJmDhxokcfm4o3eWqeo0opJqWIiIiIiIiIij+3k1KtW7fGmjVr0KBBAwwcOBCvv/46VqxYgX379qFbt26FESNRLlZbVlJK6yApJU/fY08pIiIiKmKiKCHuRgqS0q0I8NEhqqyfw8puujepqamoWbMmUlNTcerUKQQGcsVlIiI1cjsp9cUXXyiNxl988UWUKVMGO3bsQJcuXfDiiy96PEAiR2wuVEqJrJQiIiKiInT0ciJWHriE0/HJyLCIMOo1qBrsj+4NwlGrIpMmniRJEs6fP698TURE6uR2Ukqj0ditcNGzZ0/07NnTo0ER5UdpdO7gk0cNp+8RERFRETt6ORGfbTmFmylmhAaaYArUIs1sw5FLibh8Kw1D21RjYoqIiCgHt5NSp06dwk8//YS4uDgIgoDKlSvjySefRHR0dGHER+SQXCmlcVQplbVN5KdmREREVAREUcLKA5dwM8WMqsH+EAQgwyrC30eLqkZ/nI5PxqoDl1EztBSn8hEREWXjVlJq6tSpGD9+PERRRHBwMCRJQkJCAsaOHYspU6Zg1KhRhRUnkZ28KqW0WYV8NrEoIyIiIqL7VdyNFJyOT0ZooAmCICD+TjribqQiupwvygf4IDTQhFPxSYi7kYLK5f29HS4REVGxocn/kEy///473n77bbz11lv477//cPXqVVy7dg0JCQl444038MYbb2D79u2FGSuRwprX9D02OiciIqIilJRuRYZFhMmgBQCkWWwAgHRL5idkJoMWGRYRSelWr8VIRERUHLlcKTVv3jwMGjQIEydOtNtepkwZvPvuu7h27Rrmzp2LFi1aeDpGolxseVZKyT2lWCpFREREhS/ARwejXoM0sw3+PjqlhYD8f5rZBqNegwAftztnEBERlWguV0rt2bMHzz33nNP9zz33HHbv3u2RoIjyI1/k6fJMShVpSERERHSfiirrh6rB/riamAZJkiB/LiZKEiRJwtXENFQLDkBUWT/vBlqCCIKAGjVqICIiAoKDHqNERKQOLn9cc/36dURFRTndHx0djWvXrnkiJqJ8yQknh43Os5JSIlffIyIioiKg0Qjo3iAcl2+l4XR8MjKsNoiShDSzDafjk1HGz4BuDSqyybkH+fr64u+//8a6devg6+vr7XCIiKiAXK6USk9Ph8FgcLpfr9fDbDZ7JCii/MhT8xxO32NPKSIiIipitSoGYmibaqgdHoiUDBuS061IybChTngQhraphloVA70dIhERUbHj1sT2L7/8Ev7+jlcMSUpK8khARK6QK6W0DtKqGmX6HpNSREREVHRqVQxEzdBSMGj/xbn/UlC9gj9GxD7ACikiIiInXE5KVapUCfPnz8/3GKKicLdSKndWSu4zJbJSioiIiIqYRiOglEmPsv5GBPkamJAqJKmpqWjYsCGSk5PRsmVLBAayEo2ISI1cTkrFxcUVYhhE7pGn5mkd9JRipRQRERF5k9WWeQ1i5bVIoZEkCf/884/yNRERqZPLPaWIihOl0bmD72ClpxQvBImIiMgLrFkV3VYuBUxERJQnl5JSy5cvd/mEFy9exJ9//lnggIhcIU/Nc9jonJVSRERE5EWWrEop+X8iIiJyzKWk1Ny5c/Hggw9i2rRpSplsdomJiVi3bh169eqFhx9+GDdv3vR4oETZyWXxjpJSGq6+R0RERF5kyaqQkiumiIiIyDGXekpt27YNa9euxaxZs/Dmm2/Cz88PFSpUgI+PD27duoVr166hfPnyeP7553H06FEEBwcXdtx0nxPz6CklJ6pEVkoRERGRF1iVpBSvRYiIiPLicqPzzp07o3Pnzrhx4wZ27NiBuLg4pKWloVy5cqhfvz7q168PjaMGP0SFQJ6a53j6nnxMUUZERERElNl025J1nWLl9D0iIqI8uZyUkpUtWxZPPPFEYcRC5DJbHj2llOl7LJknIiKiImYTJcgdBNjovPAIgoDIyEikpqZCcFA5T0RE6uB2UorI28RsF3uOklK6rIo99pQiIiKiopZ9yp5FlCBJEpMmhcDX1xenTp3CunXr4Ovr6+1wiIiogDjfjlQne7JJ4+AiT8Ppe0REROQllmwXIJIEsK0UERGRc0xKkerYsl3dOe4pldXonJVSREREVMRy9pGy8FMyIiIipzh9j1THLinlaPU9pacUk1JERERUtHImobgCX+FIS0tD8+bNkZiYiFatWkGv13s7JCIiKgC3K6W2bt1aCGEQuU6evicIgMZRo3MNk1JERETkHZYc1x82rsBXKERRxP79+3H69GmIXNyGiEi13E5KdejQAVWqVMH777+PixcvFkZMRHmSL+50DhJSwN1KKU7fIyIioqKWc8U9CxMmRERETrmdlLpy5QqGDRuGVatWITo6Gu3bt8f3338Ps9lcGPER5SJXSjlqcg6wUoqIiIi8x5KjMipnjykiIiK6y+2kVJkyZTB06FAcOHAA+/btwwMPPIBXXnkFoaGhGDp0KP7+++/CiJNIIWYlmxw1Oc++XZQAidVSREREVIRy9pRio3MiIiLn7mn1vXr16uGNN97AK6+8gpSUFHz11Vd4+OGH0bx5cxw7dsxTMRLZkSulnCWlsk/rY7UUERERFaWclVFsdE5ERORcgZJSFosFK1asQKdOnRAZGYlff/0Vs2fPxvXr13Hu3DlERESgR48eno6VCMDdiz1nSans0/psrJQiIiKiIpSzh5SNPaWIiIic0rl7h9deew3Lli0DAPTp0wfTp09HrVq1lP1+fn744IMPEBUV5bEgibKTG5hrnfSUyp6s4nUgERERFaWclVI5e0yR55QrV459bYmIVM7tpNTx48cxa9YsdO/eHQaDweExYWFh+P333+85OCJH5Cl5GqeVUne/tooiAG0RREVERETEnlJFxc/PD1euXMG6devg5+fn7XCIiKiA3E5KbdmyJf+T6nSIiYkpUEBE+ZErpXROklKCIECrAWwiK6WIiIioaOXsIcWeUkRERM65nZSSHT9+HBcuXMhVMtu1a9d7DoooL9Z8Vt8DMqf22SCxpxQREREVKYvV/hOxnNP5iIiI6C63k1Jnz57FU089hSNHjkAQBEhZf/QLWf19bDabZyMkykGZvuekpxSQNbXPJnH1PSIiIipSVjFnUopl24UhLS0NHTp0wI0bN9CqVSvo9Xpvh0RERAXg9up7w4YNQ3R0NK5fvw5fX18cO3YM27dvR8OGDbF169ZCCJHInnytp83ju1dugi6yUoqIiIiKUM7G5hZ+QFYoRFHE9u3bcezYMYjs10BEpFpuV0rt2rULv/32G8qXLw+NRgONRoPHHnsMU6dOxdChQ3Hw4MHCiJNIIX8CqdU4z0pptVmVe7wQJCIioiLESikiIiLXuV0pZbPZ4O/vDyBzGdYrV64AACIjI3HixAnPRkfkgFz9pHU+e0+plGJSioiIiIqSxcpG50RERK5yu1KqVq1aOHz4MCpXrozGjRtj+vTpMBgM+OKLL1C5cuXCiJHIjk2ZvpdHo3MNp+8RERFR0bNkVUoZdRpkWEU2OiciIsqD20mpt99+GykpKQCA999/H507d0bz5s1RtmxZfPfddx4PkCgnpdF5HkkpuQk6P50kIiKioiQnoXz02sykFPsdEREROeV2Uqp9+/bK15UrV8bx48dx8+ZNlC5dWlmBj6gwyUkpnSuVUkxKERERURGyZJV0+xq0SEyz5Gp8TkRERHe5nZRypEyZMp44DZFLbFlT8jR5JEHlpJSN0/eIiIioCFmUSqnM1q1sdF54fH19YbPZvB0GERHdA5eSUt26dXP5hKtWrSpwMESukKufdHl0Otew0TkRERF5gZyEMum1mbd5LVIo/Pz8cPv2baxbtw5+fn7eDoeIiArIpaRUYGBgYcdB5DKlp1SelVL2xxIREREVBUvWtYfJkHmZzUopIiIi51xKSi1cuLCw4yBymfyJY96r72VmpZiUIiIioqLESikiIiLXFainlNVqxdatW3HmzBn06tULAQEBuHLlCkqVKgV/f39Px0hkR8zqE6XNq1JKsD+WiIiIqCjIjc5NBk3WbV6LFIb09HR069YN8fHxaN26NfR6vbdDIiKiAnA7KXX+/Hl06NABFy5cQEZGBmJjYxEQEIDp06cjPT0d8+bNK4w4iRTyJ44aF1bfY8U8ERERFaW7jc6zKqV4MVIobDYb1q9fr3xNRETqpHH3DsOGDUPDhg1x69YtmEwmZftTTz2FLVu2eDQ4IkeURud5JKU0GjY6JyIioqJnFTl9j4iIyFVuV0rt2LEDf/75JwwGg932yMhIXL582WOBETljc6VSKmtqH6fvERERUVERRUmp0jYZ5KQUK6WIiIiccbtSShRFhyWyly5dQkBAgEeCIsqLzYWeUqyUIiIioqJmyZaAUiql2FOKiIjIKbeTUrGxsZgxY4ZyWxAEJCcnY8KECejUqZMnYyNySHRl9b2shJWNlVJERERURLInoOSkFBudExEROef29L1PP/0UrVq1Qs2aNZGeno5evXrh1KlTKFeuHJYtW1YYMRLZsbqSlJIrpXghSEREREVETkppNYBem/nZL6fvEREROed2UiosLAyHDh3CsmXLcODAAYiiiIEDB6J37952jc+JCovcJ8qlpBQrpYiIiKiIyNP3dBoNdNrMaxGLTYIkSRDyaDtARER0v3I7KQUAJpMJAwYMwIABAzwdD1G+bG5USonsKUVERERFxJLV5dyg0yiVUkDmtYucpCLP8PPzg9lsxrp16+Dn5+ftcIiIqIDcTkr99ttvWLVqFeLi4iAIAipXrozu3bujRYsWhREfUS5KUiqvRufsKUVERERFTJ6+p9MI0GX78MwqStBpvRUVERFR8eVWo/MXX3wRbdu2xbJly3Djxg0kJCTg22+/RatWrfDaa68VVoxEdtyplOLqe0RERFRU5EopnVZjd50ibyciIiJ7LldK/fjjj1i4cCG++uor9OvXT5kXL4oiFi1ahJdeegmxsbHo2rVroQVLBNytftLkUSklfzopslKKiIiIioi8GIteI0AQBOi1Aiw2yW5VPvKM9PR09O7dG9euXUPr1q2h1+u9HRIRERWAy0mphQsXYsSIEejfv7/ddo1GgwEDBuDEiRNYsGABk1JU6OQV9fLqzaBRKqWKJCQiIiIimK2ZFx56XeZkBJ1GA4vNpiSryHNsNhtWrVqlfE1EROrk8vS9AwcO4KmnnnK6v3v37ti/f79HgiLKiyuVUlqBjc6JiIioaMnJJ7liW/4AzSryUzIiIiJHXE5K/ffff6hYsaLT/RUrVsSNGzc8EhRRXkQXekppsr6z+ckkERERFRVrVom2vPKenJzi9D0iIiLHXE5Kmc1mGAwGp/t1Oh3MZrNHgiLKi1wpldfqe1quvkdERERFzJKjxYAuKznFRudERESOudxTCgDeeecd+Pr6OtyXmprqkYCI8iNXP2nySKnKVVScvkdERERFxZKjUkovV0rxeoSIiMghl5NSLVq0wIkTJ/I9hqiwiUq/BudZqbuNznkRSEREREVDvu7Q56iU4vQ9IiIix1xOSm3durUQwyBynVwBn2ellMCkFBERERUtc9ZFivzBmdJTio3OiYiIHHJr+h5RcSBK+VdKydP32FOKiIiIiopcEXW3UirzfwsrpTzO19cXt27dwq+//uq0vQgRERV/Ljc6Jyou5OqnPBudc/oeERERFTFLzkopZfoeK6U8TRAE+Pn5wcfHB0Ie14RERFS8Ffuk1OXLl9GnTx+ULVsWvr6+qFevHvbv36/slyQJEydORFhYGEwmE1q2bIljx455MWIqTJIksdE5ERERFUvyNYpex0bnRERErijWSalbt26hWbNm0Ov1WL9+PY4fP46PP/4YQUFByjHTp0/HJ598gtmzZ2Pv3r0ICQlBbGwskpKSvBc4FZrss/HkxJMjGoHT94iIiKhoKavvaXI0OmdSyuMyMjIwcOBAzJw5ExkZGd4Oh4iICsjtnlIXLlxARERErjJZSZJw8eJFVKpUyWPBTZs2DREREVi4cKGyLSoqyu4xZ8yYgbfeegvdunUDAHz99deoUKECli5diiFDhngsFioesl/U5ZWUYqUUERERFTV5mp6cjJJ7S3H6nudZrVYsXrxY+ZqIiNTJ7aRUdHQ0rl69iuDgYLvtN2/eRHR0NGw2m8eC+/nnn9G+fXv06NED27ZtQ8WKFfHyyy9j8ODBAIBz587h2rVraNeunXIfo9GImJgY7Ny502lSKiMjw+4TlTt37gAALBYLLBaLsl3+Ovs28q4Miw1i1go2otUKi5T5dc6xEm1WiKIIi9XG8Stm+L5SB46TenCs1IHjpB73MlbplszrD0iZ1x+CJEIURaSbLRx7D8t5zc7Xt/jizz/14Fipg1rGydX4BElyb36TRqPB9evXUb58ebvt58+fR82aNZGSkuLO6fLk4+MDABgxYgR69OiBPXv2YPjw4fj888/Rt29f7Ny5E82aNcPly5cRFham3O+FF17A+fPn8euvvzo878SJEzFp0qRc25cuXcrVO4q5dBvwU1zmp489K4tw1tfyZgaw6ZIGJh3QNZKfThIREVHh++2KgIQ0AU0riIjwBw7fFPDPLQHVAyXUL8fqbU9KT0/Hs88+CwBYvny58ncDEREVD6mpqejVqxcSExNRqlQpp8e5XCk1YsQIAJkrXbzzzjt2yRubzYa//voL9erVK3jEDoiiiIYNG2LKlCkAgPr16+PYsWOYO3cu+vbtqxznaCphXqtwjBs3Tnk+QGalVEREBNq1a2f3YlksFmzatAmxsbHQ6/Weelp0D+6kWXBg4yloBODxx2sq23OO1dXEdPy79Sz8jVp06vCAFyOmnPi+UgeOk3pwrNSB46Qe9zJW57edhc/tdLRsHIEHQgLgcyIByf8moFZUaXSqG1pIEd+fsn8Q3rp1a7ues1S88OefenCs1EEt4yTPSMuPy0mpgwcPAshM+Bw5cgQGg0HZZzAYULduXYwaNcrNMPMWGhqKmjVr2m2rUaMGVq5cCQAICQkBAFy7dg2hoXd/0cfHx6NChQpOz2s0GmE0GnNt1+v1DgfV2XYqehqzBI1GA71WyHOsfIw2aDQaSNBw7Iopvq/UgeOkHhwrdeA4qUdBxkqEAI1GAx+jIfN6xKDPuh5xfN1CBZf99eT7Sh04TurBsVKH4j5OrsbmclLq999/BwD0798fs2bNQkBAQMEic0OzZs1w4sQJu20nT55EZGQkgMz+ViEhIdi0aRPq168PADCbzdi2bRumTZtW6PFR0ZNX09PkUQkHANqs/SJX3yMiIqIiYrVlXnfIDc7lVfi4+h4REZFjGncOtlqt+Pbbb3H+/PnCisfO66+/jt27d2PKlCk4ffo0li5dii+++AKvvPIKgMxpe8OHD8eUKVPw448/4ujRo+jfvz98fX3Rq1evIomRipYt66Iur5X3su+38SKQiIiIioglazEWfdbqe/IqfFx9j4iIyDG3Vt/T6XSIjIz06Ap7eXnkkUfw448/Yty4cXj33XcRHR2NGTNmoHfv3soxY8aMQVpaGl5++WXcunULjRs3xsaNG4ukkouKnpxk0uWTlNLISSlWShEREVERsVjtr1N0WlZKFRZfX19cvnwZmzdv5kJFREQq5lZSCgDefvttjBs3Dt9++y3KlClTGDHZ6dy5Mzp37ux0vyAImDhxIiZOnFjosZD3yUkpTT5JKfliUJIAUZTyPZ6IiIjoXllzVkrJ0/dsTEp5miAIKF++PAIDA/Nc4IiIiIo3t5NSn332GU6fPo2wsDBERkbCz8/Pbv+BAwc8FhxRTnKPqHwrpbJdnNgkCRrwYoWIiIgKjyRJsGQln+QKKZ0mMzklT+sjIiIie24npZ588slCCIPINXL5e76NzrMlrWyiBL22UMMiIiKi+1z2KXpypZTc8JyVUp6XkZGB4cOH4/z582jTpk2xXoGKiIicczspNWHChMKIg8gloquNzrMlrbgCHxERERW27Imnuz2l2Oi8sFitVsybN0/5moiI1MntpJRs//79+OeffyAIAmrWrIn69et7Mi4ih+TG5fklpQQh858kcQU+IiIiKnzyFD1BuHudovSU4rUIERGRQ24npeLj4/Hss89i69atCAoKgiRJSExMRKtWrbB8+XKUL1++MOIkAnD3U8j8k1ICtIIAqySBbRyIiIiosMnXKAatRmm8zdX3iIiI8qZx9w6vvfYa7ty5g2PHjuHmzZu4desWjh49ijt37mDo0KGFESORQp6Kp3VhlRU5cWVzYfqeKEo4m5CMvy/extmEZGWaIBEREZErLFlT9LJ/cKY0Ouf0PSIiIofcrpTasGEDNm/ejBo1aijbatasif/9739o166dR4MjykmeiqfJp1IKuNsMPb/pe0cvJ2LlgUs4HZ+MDIsIo16DqsH+6N4gHLUqBt570ERERFTiyYknucl55tdsdE5ERJQXt5NSoig6XN1Cr9dD5DwpKmR3K6XyP1a+JswrKXX0ciI+23IKN1PMCA00wRSoRZrZhiOXEnH5VhqGtqnGxBQRERHlS0486bNdpCiNzkUJkiQp0/qIiIgok9vT91q3bo1hw4bhypUryrbLly/j9ddfR5s2bTwaHFFOSk8pbf7fupp8pu+JooSVBy7hZooZVYP94e+jg1YjwN9Hh6rB/riZYsaqA5c5lY+IiIjyZc36cFaespf5tZBtP68niIiIcnI7KTV79mwkJSUhKioKVapUQdWqVREdHY2kpCTMmjWrMGIkUtjc6SmVdYyzpFLcjRScjk9GaKAJgiDg8q1UHLl0G1abCEEQEBpowqn4JMTdSPHcEyAiIqISyZL1wZkue6VU9qQUp/B5lMlkwsmTJ/H555/DZDJ5OxwiIiogt6fvRURE4MCBA9i0aRP+/fdfSJKEmjVrom3btoURH5EdeYaozoWeUkqjcydJqaR0KzIsIkyBWgDAzRQz0iwiUjKsCPQ1wGTQ4vodEUnpVs8ET0RERCWW3FPKkK2aW6sRIAiAJMmVVFovRVfyaDQaREVFoUKFCtBo3P6cnYiIigm3k1Ky2NhYxMbGejIWonzJlVLuNDp3Vi4f4KODUa9BmtkGfx8d5A8w5cdIM9tg1GsQ4FPgtwkRERHdJxxVSgmCAL1GgNkmsVKKiIjIgQJ9rLBlyxZ07txZmb7XuXNnbN682dOxEeViE+XllvM/Vq6mEp30lIoq64eqwf64mpgGSZKU42xZzUivJqahWnAAosr6eSZ4IiIiKrGsWZVSuhwXKfJtCxcE8iiz2Yw33ngDixYtgtls9nY4RERUQAXqKdWhQwcEBARg2LBhGDp0KEqVKoVOnTph9uzZhREjkSLrek+pgsqLJp/pexqNgO4NwlHGz4DT8cnIsNggShKS0204HZ+MMn4GdGtQ0aWqLCIiIrq/yZXZ+hzXDXLlFCulPMtiseCTTz7B6tWrYbFYvB0OEREVkNvzkqZOnYpPP/0Ur776qrJt6NChaNasGSZPnmy3ncjT7lZK3XtPKQCoVTEQQ9tUw8r9l7D+6DXYRAkmgwWPRpdFtwYVUatioGcCJyIiohLNnPXJmT5npZSGSSkiIiJn3E5K3blzBx06dMi1vV27dhg7dqxHgiJyxuZOo3Mh7+l7sloVA1G5nB/ikzJgsYloWqUs+jaJYoUUERERuczqoKcUAOg0nL5HRETkjNvT97p27Yoff/wx1/affvoJXbp08UhQRM4ojc49MH0vO4sooZRJj7L+RgT5GpiQIiIiyoMoSjibkIy/L97G2YRkiC78ri3prE4qpfScvkdEROSU25VSNWrUwOTJk7F161Y0adIEALB79278+eefGDlyJD777DPl2KFDh3ouUiJAueh1afpe1iH5VUoBd5dxBoAMq61gwREREd0Hjl5OxMoDl7L6MYow6jWoGuyP7g3C7+tp75asa5Sc1dxKo3MbK6WIiIhycjsptWDBApQuXRrHjx/H8ePHle1BQUFYsGCBclsQBCalyOPkqidXKpnu9pTK/7xma/akFC8aiYiIHDl6ORGfbTmFmylmhAaaYArUIs1sw5FLibh8Kw1D21S7bxNTFmvePaVcqdwmIiK637idlDp37lxhxEHkEpuTTyEdkRNXVhd6ONhVSlmYlCIiIspJFCWsPHAJN1PMqBrsDyFrKr2/jw5Vjf44HZ+MVQcuo2ZoqftyGrx8jeK00Tl7ShEREeXidk8pmdlsxokTJ2C1Wj0ZD1Ge5J5SWhd6SskXga5cA2avlDKzvJ6IiCiXuBspOB2fjNBAEwRBwH/JGThx7Q6soghBEBAaaMKp+CTE3UjxdqheIV8/5Gp0rkzfY6WUJ5lMJhw8eBCfffYZTCaTt8MhIqICcjsplZqaioEDB8LX1xcPPfQQLly4ACCzf9QHH3zg8QCJsrO50VNKboZuc6GnVPYpexkW9pQiIiLKKSndigyLCJNBCwC4ejsNiWlWJKVlfkBpMmiRYRGRlH5/fmB5t9G5/TUKG50XDo1Gg4ceegiVKlWCRlPgz9mJiMjL3P4JPm7cOPz999/YunUrfHx8lO1t27bFd99959HgiHKSm5a71OhcqZRyt9E5K6WIiIhyCvDRwajXIM1sAyRJ+X0pf/iTZrbBqNcgwMft7hAlglVpMZBz+l5WpRSn7xEREeXidlJq9erVmD17Nh577DGllwAA1KxZE2fOnPFocEQ5yZ8yutfoPP+kFBudExER5S2qrB+qBvvjamIa0q02yL9eRVGCJEm4mpiGasEBiCrr591AvUSenperp1RWpZSNlVIeZTab8e6772LZsmUwm83eDoeIiArI7aRUQkICgoODc21PSUmxS1IRFQbRjZ5SSlLKhel75hyVUpIL9yEiIrqfaDQCujcIRxk/A05dT4bFJkKUJCRnWHE6Phll/Azo1qDifdnkHLhbdZ1z+p5cKcVG555lsVjw/vvv47vvvoPFYvF2OEREVEBuJ6UeeeQR/PLLL8ptORE1f/58NGnSxHORETlgdaOnlJy4cmX6njlHdRSrpYiIiHKrVTEQQ9tUQ3hpE8xWEcnpViSlW1EnPAhD21RDrYqB3g7Ra6xKo3PHlVJsdE5ERJSb25P+p06dig4dOuD48eOwWq2YOXMmjh07hl27dmHbtm2FESORwq1G525USllsuZNSPnptASIkIiIq2WpVDET7WiHQajSw2EQ0rlwGzzeNvm8rpGQWpaeUk0bnrJQiIiLKxe1KqaZNm+LPP/9EamoqqlSpgo0bN6JChQrYtWsXHn744cKIkUghFqBSypWeUjkro3JWThEREdFdN1MsKGXSo6y/EaV9Dfd9Qgq4Wyll0DlpdM5KKSIiolwKtDxK7dq18fXXX+favmLFCjz99NP3HBSRM3LVk8adnlIurb5nf0yG1VaA6IiIiO4P/yVnKF/zg5xM8rVEzg/OlEbnLlyPEBER3W/cqpSyWq04duwYTp48abf9p59+Qt26ddG7d2+PBkeUU4Gm77GnFBERkcdYbCJup95tLG228XcmkL3RueNKKStfJyIiolxcTkodP34c1atXR506dVCjRg1069YN169fR0xMDPr164fY2FicPn26MGMlUhJMOfs1OKI0Ondl9b0clVEZFl44EhEROXIj2Wx3m78zM9sLyJ+B5Vx9T89G50RERE65PH3vjTfeQHR0ND777DMsWbIE3333HY4ePYo+ffpg7dq1CAgIKMw4iQBkm77nUqVU5v9WTt8jIiLymOxT9wBWSgH2r4FcGSWTK6fY6NyzfHx8sHPnTvz555/w8fHxdjhERFRALiel9uzZg3Xr1qFBgwZ47LHH8N1332H06NEYPHhwYcZHZEd0o1JKvigUXZm+Jy/jrBFgFSX2xyAiInIiISspVdpXj1upFmRY+EFO9g/AclZKyS0HWCnlWVqtFg0bNkR8fDy0Wq6YTESkVi5P34uPj0fFihUBAEFBQfD19UVMTEyhBUbkiPxBpGuNzuX7uN5Tyt8nM0/LnlJERESO/ZeUmZQKCzIBADJYKaX0i9JpBAiC4+l7bHRORESUm8tJKUEQoMlWjqzRaKDX6wslKCJnbFml7y41Os+6KHTlg0m5UsrfyKQUERFRXv7L6ilVMSspxeriu1VQOZucA2x0XljMZjM+/vhj/PjjjzCbzfnfgYiIiiWXp+9JkoTq1asrn/4kJyejfv36dokqALh586ZnIyTKRu4ppXWpUiqr0bkblVKllEopTkUgIiJyRO4pFZYtKSVJUq4KofuJvPKeTpv7NZC3mTl9z6MsFgvGjRsHAJgxY4Z3gyEiogJzOSm1cOHCwoyDKF+SJCnT97QOLvpyulspVYDpe1xJiIiIKJdUsxWp5swPbsKCMptLi1JmT6WcvZTuJ1alUir3ayBXT9nY6JyIiCgXl5NS/fr1K8w4iPKVveDJnUqp/Ho4iKKkNCgNMGZOSeVKQkRERLn9l5Q5TSrQpIef4e5lpNkqOpy6dr+wiHJPqdyvARudExEROXf/Xj2Q6mRfStnBNV8urk7fy56AClAqpTh9j4iIKKeE5HQAQDl/AzQaAQZ5atp93lcqz0opuacUK6WIiIhyYVKKVCP7tZwrlVLy9D2ri0kpQQD82OiciIjIKbnJefkAIwDAoMu8lLzfK4zv9pRy0OhcWX3PtT6XRERE9xMmpUg1sveGcmX1PZ1cKZVPTyn5012DVgNj1sU1k1JERES5yU3Oy/nbJ6Xu916MclLK4ep72aqn8vugjIiI6H7DpBSphtwbSiPApRV+XO0pJV9IGnQaGHVaAFx9j4iIyBG5p5SclJJ/b5pt9/fvTTnZlNf0vczj7u/kHRERUU4uNzon8jY5ueRKlRQAaDSurb4nV0rptQKMeo3dNiIiIsokSRJupMiVUgYA2Sql7vPfm8r0PQdNLzUaARohc8EWNjv3HB8fH2zatAm7d++Gj4+Pt8MhIqICcjspZbPZsGjRImzZsgXx8fEQc3zi89tvv3ksOKLs3E1KyX2n8uvfoFRKabUwaHlxTURE5MjtVAssNglaDVDaNyspxd+bAO42Otc5qJQCMqf1ZVjFfKu3yXVarRYxMTFISUmBVqv1djhERFRAbielhg0bhkWLFuHxxx9HrVq1XJpGReQJcm8oV5qcA9mn7+V9nHwhbdBplEopi02CKEpKtRUREdH9Tq6SKuNnVH4/Ko3O7/Ok1N0PuBx3xpCvSaz3eUN4IiKinNxOSi1fvhzff/89OnXqVBjxEDmlVEo5+RQyJ62bjc71WkHpjQFkJqtMBn7yRkREBAAJWf2kymdN3QOYlJJZ8qmUkrdbWCnlMRaLBXPnzsWxY8cQGxsLvV7v7ZCIiKgA3G50bjAYULVq1cKIhShPSlLK1UopwdVG55n7jToNtBpBWbWPzc6JiIjuSsix8h4AZdXa+z0pJTcwd9RTCrjb7JyVUp5jNpsxbNgwfPHFFzCbzd4Oh4iICsjtpNTIkSMxc+ZMSPlUnxB5mvuNzjP/t4pSnt+vdyulMu9gZNNWIiKiXG7ISamA3Emp+/13ptxTytHqe0C2Sik2OiciIrLj9vS9HTt24Pfff8f69evx0EMP5SqVXbVqlceCI8pOXkVP42ZPKQCQJMDZ3eRlrOV+Uka9BilmGzIs9/cFNhERUXb/OaiUUqbv2e7v6mKzvPqek55S8gdfbHRORERkz+2kVFBQEJ566qnCiIUoT/KFnM7VSqlsWSibJEEDx/fLXSmlBWC57y+wiYiIZFabiFupFgBAuWw9peRejPf79D35GsVZpZT8QZmF0/eIiIjsuJ2UWrhwYWHEQZQv+YLP1RXxsldK2UQJeic9y81ZpfTyijnyp77prJQiIiICANxIMUOSMqfr+RvvXj6y0XkmOdmkd1IpJX+gZmWlFBERkR23e0oReYu7PaWyN0TPq1xeqZTSsacUERF5nihKOPdfCs4nA+f+S4GowsREQlLm1L3yAUYI2X6/yh/o3O+/M5XV95xco8jJOzY6JyIisud2pRQArFixAt9//z0uXLiQa7WLAwcOeCQwopxEyb3V9zQaAYKQ2U/Klkejc/nTTaPd9D2uvkdERPfu6OVErDxwCaeuJeFqvAZ71v6LaiEB6N4gHLUqBno7PJfdSMm83iufrZ8UcDfZwqRU3pVSd6fvqS8hSUREVJjcrpT67LPP8PzzzyM4OBgHDx5Eo0aNULZsWZw9exYdO3YsjBiJANwteXe1Ugq4m8DK61NpuVLKwEopIiLyoKOXE/HZllM4cikRgb56lPcBAn31OHIpc/vRy4neDtFlcqVU2Wz9pIC7vzPv9+l7d3tKOWl0rmGjc08zGo1YvXo13n77bRiNxvzvQERExZLbSak5c+bgiy++wOzZs2EwGDBmzBhs2rQJQ4cORWKiei6uSH3EgiSlso51afqe9u7qe9m3ExERuUsUJaw8cAk3U8yoGuwPf6MOggD4G3WoGuyPmylmrDpwWTVT+RytvAdkX33v/v6dKV8z6Jw0Ope3W8T7+3XyJJ1Oh06dOqFhw4bQ6Qo0+YOIiIoBt5NSFy5cQNOmTQEAJpMJSUlJAIDnnnsOy5Yt82x0RNm42+gcuLsCX55JKZt9pRT7YxAR0b2Ku5GC0/HJCA00QRAE3Ewx43yygOR0CwRBQGigCafikxB3I8XbobrkRvLdnlLZKdP37vPFQaxZySa5IionXda1hYXXFkRERHbcTkqFhITgxo0bAIDIyEjs3r0bAHDu3DlIefTtIbpXcl8oZ01EHZE/mcyrp1TuSqmsnlIW9pQiIqKCSUq3IsMiwmTI/J1yO80CmwgkplsBACaDFhkWEUlZt4uzNLMNyRmZvxNzTd/TZj4/s+3+/p1plRudO6mU0rtQuU3usVgs+Oabb7BlyxZYLBZvh0NERAXkdlKqdevWWLNmDQBg4MCBeP311xEbG4tnnnkGTz31lMcDJJIpq++52OgccK1SSml0zp5SRETkIQE+Ohj1GqSZM5M18jQ9+fdRmtkGo16DAJ/iP+1InrpXyqRTFgORyZVSNvH+XllObmCeb6NzJqU8xmw2Y9CgQZg1a1auhZeIiEg93L4S+uKLLyBmlSi/+OKLKFOmDHbs2IEuXbrgxRdf9HiARLKCTN+Trw3zauHARudERORpUWX9UDXYH0cuJaKq0V/5HWYTJUiShKuJaagTHoSosn5ejjR/CXI/Kb/czaTl351A5nR4nZOkTEknf8DlrJpbTlbdz4k7IiIiR9xOSmk0GmiyzZfv2bMnevbs6dGgiBxRKqXcuN6Vq6rynL6XYxln+VNgNjonIqKC0mgEdG8Qjsu30nA6PhmpZhskCUg1W3E6Phll/Azo1qCiWx+0eMt/SY77SQGZFUA6jQCrKMFsFeFryHVIiSdJkrJCsF7nrKdU5jjL0/yIiIgoU4E+zvrjjz/Qp08fNGnSBJcvXwYALF68GDt27PBocETZ3U1Kuf5tq8mnh4MoSkrJvdLoXKmUur/7YxAR0b2pVTEQQ9tUQ+3wQKSarUgXgRSzDXXCgzC0TTXUqhjo7RBdciMlc2pUzpX3ZMoKfPfphznWbNcYziqldFnXLlx9j4iIyJ7bSamVK1eiffv2MJlMOHjwIDIyMj89S0pKwpQpUzweIJFMlNzvKSUfKzqplMq+hLVBy+l7RETkWbUqBuKdx2uicXQZRPpLaFmtHN5+vIZqElIAkJBVKZWzybnsfv+9aXFwLZGTXstG50RERI64nZR6//33MW/ePMyfPx96vV7Z3rRpUxw4cMCjwRFlJ1/zuTN9L79KKflCUhDuXjAa9VzemoiIPEcQMn+3BOgBk0Gniil7MkmScCPZ+fQ9IHuF8f35e1OuuNYIzvteKo3OOX2PiIjIjttJqRMnTqBFixa5tpcqVQq3b9/2RExEDsl9oTTuVErlk5RSmpxrNRCyziv3lMqw2iDl0YuKiIjIFVZRUj5YUdvU8DtpVphtEjQCUNpJw6j7vRejNUdvSkfY6JyIiMgxtxudh4aG4vTp04iKirLbvmPHDlSuXNlTcRHlYsvqwyA3C3WFLr+klHIhefec8jQEUcr8Q0LvxuMRERHllG65m4hSWzWRvPJeWT+D8kFPTkpPqfs04aI0Oc/jekFpdM7pex5jNBqxdOlSHDx4EEaj4yo+IiIq/tyulBoyZAiGDRuGv/76C4Ig4MqVK1iyZAlGjRqFl19+uTBiVEydOhWCIGD48OHKNkmSMHHiRISFhcFkMqFly5Y4duxYocZB3iFf67pTKaXJZ/U9i9W+yTlwNykFqO+PByIiKn7Ss00Ht9gkVVXL/JeVlCrnZOoewEbn8vPOayEWpdG5isa+uNPpdHj66afRrFkz6HRuf85ORETFhNs/wceMGYPExES0atUK6enpaNGiBYxGI0aNGoVXX321MGIEAOzduxdffPEF6tSpY7d9+vTp+OSTT7Bo0SJUr14d77//PmJjY3HixAkEBAQUWjxU9MSsTxd1bqy+J3+qKzqtlMr89Dp7yb0gCDDqNMiwisiw2OBv5IUOEREVXM4pe+lWEf7uNEj0IiUp5WTlPQAwau/vpJRc/WTIo1KKjc6JiIgcK9AV0eTJk/Hff/9hz5492L17NxISEvDee+95OjZFcnIyevfujfnz56N06dLKdkmSMGPGDLz11lvo1q0batWqha+//hqpqalYunRpocVD3qH0lPJgo3Ozg0qp7LdZKUVERPcqPcfCGRkW9fSV+i8p/6TU3d+Z6nleniRXvunySDSy0bnnWa1WrFixAn/++SesVqu3wyEiogIqcAmIr68vGjZs6MlYnHrllVfw+OOPo23btnj//feV7efOncO1a9fQrl07ZZvRaERMTAx27tyJIUOGODxfRkYGMjIylNt37twBAFgsFlgsFmW7/HX2beQ9GRYrRFGEJNpyjYmzsRIkEaIowmyxOhzH/2fvzcMcO8sz7/vs2qXau7qqu6tXb+2tbTBeWI0NmCSAzWYghJCNmIQwJJBkQhIzSczyMZnAJJNMFmCSCXEghmEzxBvYGNtgu+12t7vdXb1Ude2LSrvOkc72/fHqPTpSSaWlVCWp+v1dl67uUh2pjtbznvu5n/vJ5vKwLAsiV3pbkQMsy0JGy0HXmVOqlbDPVXfAXqfugb1WnU9azcEq5CJaloW0mkNI6Q6n1GJSg2VZiHj4qu8xgbNhWRayOX1LvA8b/UypOR2WZYGHXf02lrnmeoTROJlMBu95z3sAAB//+MdZC18Hw45T3QN7rbqDbnmd6t2/ur+9P/jBD9a13Ze+9KV677Iu7r33Xhw+fBhPP/30qt/Nz88DAIaGhkquHxoawuTkZNX7/PSnP41PfepTq65/4IEH4PP5Vl3/4IMPNrrbjA3g6ByHuSyHn6kTWD5eeZvy1+rFRQ5TKQ5PZiax8tLq6uSZJDC1xMOM2rg/Xswim5zmEMtxeOiHE9i++i3BaAHsc9UdsNepe2CvVedyLgXMLBIRamZ6Gg88fB6D3jbvVB2YNnDkHA/bBg5zEzhRZdV4LMZhaoXDz+KTsCa3jhOo3s/U+TQwtcBDW7Jxf/pExW3SOjB1nofIA/fff6aVu3nBomma8/9HHnkEHo+njXvDqAd2nOoe2GvVHXT665TNZuvarm5R6itf+Qp27dqFq6++GnaV0OhWMzU1hd/5nd/BAw88sOaBhisLvrZte9V1bv7wD/8QH/vYx5yfk8kkduzYgVtvvRWhUMi5Xtd1PPjgg7jlllsgSdI6HgmjFSw8MQlxKYMbD23H1TsiJb+r9lppz83AOp/AtZcO4pX7+1fd5xNnolg4toArRkK47dpR5/q5n0zg3HIW1107gstHwhv2mC5E2OeqO2CvU/fAXqvO58mzUcwcmcPM9DRGRkdx3St24ZLhzs+9XErl8FPjDGSRx+23XVR1bRU6HUXyxQVcMhrGbdeMbPJetp5GP1OHz8cx/dwsDgwFcNsrdlbcJqnqeOGBcfAccNttl7Z6ly9IMpmM8//Xve51iEQi7dsZxpqw41T3wF6r7qBbXifakVaLukWpD33oQ7j33ntx9uxZfPCDH8T73vc+9Pb2Nr2D9fDss89icXER11xzjXOdaZp47LHH8Nd//dc4efIkAOKYGh4edrZZXFxc5Z5yoyhKxdGxkiRVfFGrXc/YXDiOB8/z8MjVX4/y10qWRPA8D/B8xdtYIPfpVUpv51Mk8DwPE5Vvx1g/7HPVHbDXqXtgr1XnYtgcORYB4HkeBriueK3imgqe5zEU8kCW5arbFY+Z3fG46qXez5RdWJ8oklh1e6/rPSAIopN5yWge93PNvv+6A/Y6dQ/steoOOv11qnff6g40+F//639hbm4Ov//7v4/vfOc72LFjB975znfiP//zPzfMOXXzzTfj6NGjeP75553Ltddei/e+9714/vnnsWfPHmzbtq3EtpbP5/Hoo4/ihhtu2JB9YrQPJ+h8DRdcOXTbahOYaZD5qqDzQlhpTmdB5wwGg8FYH+XHEq1Lgs7rmbwHFI+hF+z0vUJ4ubTG9D335GDdujCfJwaDwWAwKtFQIqCiKLjzzjtx5513YnJyEl/5yldw1113Qdd1HD9+HIFAoKU7FwwGcfDgwZLr/H4/+vr6nOs/+tGP4p577sH+/fuxf/9+3HPPPfD5fE7wIWPrQCfoCQ1UF4Va0/cKapVUNjFHkS7sSUIMBoPBaB1a2bGkWwoe9YpSiigAuHBFKSoyiWuMBxZda5dqaxIGg8FgMC5Emh5TwXEcOI6DbdvORJl28IlPfAKqquKuu+5CLBbDddddhwceeADBYOdnNTAaoylRquCUsqq4+fQqTqkLfYG9UViWjXPLGUymgXPLGewbCrMWBgaDseXRCiIUNfp2S8HDEaWC9TmluuVxtRq6lpDE6qIUz3MQeOLc1k0mSjEYDAaDQWlIlMrlcvjGN76BL33pS3j88cfxcz/3c/jrv/5rvPGNb3T65DeaH/3oRyU/cxyHu+++G3ffffem/H1G+2hGlKKCh1HDKSWXO6WcBTYTpVrFsZkE7js8jfH5FOYWefzsuy9h/7Yg7jg0ioMsTJ7BYGxhaLueT6Q/d/6xxbJsnF5MI57Vkc0bsCy7ahFBudDb9wprDKnG+kTkeZiWBaNapgCjIWRZxj/+4z/iyJEja2aeMRgMBqOzqVuUuuuuu3Dvvfdi586d+OVf/mXce++96Ovr28h9YzBKoG4noYFMKWqXt6qIUrq5tlPqQq36tppjMwl88eFxrGTyGAopMDxA2Cfh6HQCMzEVH7l5PxOmGAzGloWKUD7RLvzc2ceWYzMJfO2ZKTx2ahmmZSOTO40Hty1ULSJc6KIUXUuIwtoFWkngkDOqF8oYjSFJEt7//vfj/vvv7+igXwaDwWCsTd2i1N/93d9h586d2L17Nx599FE8+uijFbf7xje+0bKdYzDcrMcpVTVTyqjslJKZU6plWJaN+w5PYyWTx75BPxJZHeCAgCIiOCjh9GIa3zg8g0uHQ6yVj8FgbElogcMnAhY6W5SiRYT5hAZZ5OGRePT6lTWLCE7Q+QXqAKJB5+IaQecAIPA8ANMRsRgMBoPBYDQgSr3//e8H14BDhcFoNXT6XjOZUmaVTCkqOq0KOhfZ9L1WMRHN4PRiGsNhL2bjGqZjKmQD2AXSfjsc9mJ8MYWJaAZ7Blo7LIHBYDA6AeqU8gpABoDWoQUPdxFhKKQgkzfhk0UEPCL2KYGqRQQqSummvWab31aFikxSjSgLOp3PYJlSLcEwDNx///145plncOuttzK3FIPBYHQpdYtSX/nKVzZwNxiM2phm89P3Gm7fky7sqm8rSWkGcroFJchhIUlCc/Muk4BXFrCQtJDSjDbtIYPBYGws7kypDDq34OEuIiS1PADAUzgerlVEcLuN86YFDy9s7o63GZ1mStVwStHpfEYbBwRtJXK5HN761rcCAH73d38XXq+3vTvEYDAYjKbYnHRyBqMFULcT34Bjj6/hlKrWvudkSnVwi0W3EPSIUCQes3HNydFwa4Rq3oQi8Qh6mh4GymAwGB2LbdtOgcPJlOrQvEJaRPDKgjMhzn189MoCcvrqIoIo8KCbdargtpEYdWZK0fY+Nn2PwWAwGIwiTJRidA00F0rcDKcUy5RqGWN9fuwbCOBcNAO7IA4ahZfDtm3MJVTsHwxirM/fxr1kMBiMjSFnWKB1Eb8zfa8zRSlaRFDzpisnqXh8XKuIIAuFYo7ZmY9tI6HPVS2nFP19tZxLBoPBYDAuRJgoxega6CKukawKupautgCkolO5KMWCzlsHz3M4tKsHPMchqenQTQumxSGdM3B6MY1ev4zbD41ccBkkDAbjwoA6hwQeUApdbUSo6jxhYqzPj32DAcwlVOgFcYkWd2oVEeQLeAIfdcKJNTKlBJ5mb114zxGDwWAwGNVgohSjK7Bt22n5amj6XqF9r9L4Zdu2i+0JazilOvHEoduYT2g4OBLGxduCyJsWMgYQz+ZxxWik4iQnBoPB2CrQVj2PKKAQzwTb7syiB89zuOPQKHr9MhZTOeimBQ5AWqtdRFAuYFGKFr5ksT6nVKU1CYPBYDAYFypMlGJ0BW6nk9BAphStWloVhCV3iHm55Z5mSgGdeeLQTczGVZxdzqA/IOOv3n01rtkZwa6AjU+84QA++eZLmCDFYDC2NLRVTxF5CBxA9ZxOPbYcHAnjIzfvR19AQd6wsJDUEFdrFxE20mFsWTbOLqVxZCqOs0vpqi357UKv0yklMqcUg8FgMBirYMnCjK7AHVReY81XAu+0763+nbuaWx50LgkcOK5YzfZIF9YkoVby+OllAMDlI2H0BxQMBhXEJWAgoLCWPQaDseXRCu17iiSA0wGPJEAzbDJIw9uZI+wPjoRxzc4eLKZyeMe1o9jZ68NYn3/N7+yNckodm0ngvsPTOL2YJpNcJR77BgO449BoxxQ1dCd/q8b0PeqUYkHnDAaDwWA4MFGK0RW4pyfXqkS6cYLOKzilipOFOHBl7iuO46CIPDTduiBbEVpFQtVxZCoOALhpfz8AwK+Qr51M3qh2MwaDwdgy5Gj7XqF3zyPy0AzTEas6EcuyoRkWQl4J1471IqDUXi46mVItdAEdm0ngiw+PYyWTx3DYC29YgJo3cXQ6gZmY2jHt33T6nlRj+h4LOm8tsizjC1/4Al588UXIstzu3WEwGAxGk7D2PUZXYLhUqUbMNbTVr9ICMF8l5JxCW/hyHTq6uxt46mwUlg2M9fkw2uMDAPhk8rxmcux5ZTAYWx8qPnkKxxp6zNE6+Nji3jdfnU7hVjulLMvGfYensZLJY99gAJLIQc2bCHhE7BsMYCWTxzcOz3REKx/NiKolSrGg89YiSRJ+8zd/E7fddhskqTNdhwwGg8GoDROlGF0B1aQEHqtcTWtBnVJriVLVFpEKm8C3LvKGhZ+dWwEA3Liv37meOqXSOeaUYjAYWx+aKSUXCh20HZxe34lk88UcrHrbrFs9fW8imsHpxTSGw15wHIdT8ymcmE8ib1jgOA7DYS/GF1OYiGZa8veaxbbt4vS9Gu17Es+CzhkMBoPBKIeJUoyugGZKNRJyDqzdvkcXkdWcUk5oawe3WHQyz52PIZs30euXcOlwyLk+QJ1S+c49IWMwGIxWQcUnp31P6vyCh1r4fqbO1nqQhda6i1OagZxuwSsLAEg7oW0D+cL9e2UBOd1CSmtvgcO0bNAlhlQr6FxgTqlWYpomHn30URw9ehSmydYUDAaD0a2wTClGV0CdTkIjKecA+Dra92o7pdhCp1Fs28ZPCgHnN+7tL6m0O5lSzCnFYDAuADSDtu8J0FFsDe9kp5Ra2DdvA0M+Wu0uDnpEKBIPNW/CK/OO8ENdRmrehCLxCHrau5R1u55Y0PnmomkabrnlFgDAb/3Wb8Hj8bR5jxgMBoPRDMwpxegKiqJUY7dbq32PViqVaplShcU4CzpvnJfmU1hK56GIPA7t6in5nV8hz2uWOaUYDMYFQK6KU6qTg87p97O3EadUi9v3xvr82DcYwFxCdYLEASIC2baNuYSK/YNBjPX5W/L3msXtehJrtDpSJxULOmcwGAwGowhzSjG6Atq+V2+2BWXNTKka7XssU6p5qEvqut29Tn4KxS+zTCkGg3HhQJ1SisQjhe5w4WYL01F9cv3LRLnFx0ye53DHoVHMxFScXspANy0IPIeUaiCWyaPXL+P2QyMNrwtaDXU9SRUm+ZZDnVK6xdYVDAaDwWBQmFOK0RXQ6TqNZko57XuVMqXo9D0WdN5SZuMqzixlwHPA9Xv7Vv2etu9l2fQ9BoNxAUCdUsqqoPPOPbY0lSnVYqcUABwcCeMjN+/HvoEA8oaFtGYgqem4YjSCj9y8HwdHwi37W81CBSaxjngBibXvMRgMBoOxCuaUYnQFNLOhljW+HCfonGVKbSiWZWMimkFKM/CT08uwbRsHRyOI+ORV2/qcoHPmlGIwGFufnJMpRY4p9NjSFZlSDQWdF0SpFod4HxwJ4/037ELOsKCbFl421oNfuWlP2x1SFMcpJdbeHypcsaBzBoPBYDCKMFGK0RXQ9ruG2/e46uOXa7fvFSYJdXA1uxM4NpPAfYencXoxjUzOwFxCQ9Aj4pZLhypuH6BB53kTlmV3zIkFg8FgbARUfFKk7hGlnEypBoLOaVbWRuQw5nQLIa8EAAh4pI46blCBqZ6iGS2UVVqTMBgMxkbiLiAHPSLG+vwd9V3KuLBhohSjK7Ds5tr3hIJV3rLJRDh33oPTvlcjU6rVVd+txLGZBL748DhWMnkMh72wLBuSwCObM/HvT09hKORZ1V5BnVK2DWR10xGpGAwGYyuiVWnf6+TW8Kba9wT6uFovtmVdAl6nDcnQnUypetr3yDYGW1cwGIxNxF1AzukWFInHvsEA7jg02hFt0AwGOxtkdAXrdUoBRJhyT2uumSlVqPrmOria3U4sy8Z9h6exkslj32AAtg2cWsxDEnjs2+ZHNJPHNw7P4NLhUMnrJvAc6HlONmcwUYrBYGxpaHZU+fS9Tj62UOGnfFDFWmxEphRFdQlR2Q4bkmFYa0cBuHGCzlmmVEuQJAmf/vSn8dJLL0GSpHbvDoPRkZQXkL1hAWrexNHpBGZiasfk8zEubFjQOaMroKKU0KAo5c4dLZ/Ap9fbvtfB1ex2MhHN4PRiGsNhLziOQzSTg2HaUEQevX4Zw2EvxhdTmIhmVt1WKTzlbAIfg8HYyhim5bRqeQrHFHps0Tr42EIzpdoddE5xu6PUDhPz3NP3aiEVFiUGm77XEmRZxu/+7u/ibW97G2R5dYYlg3GhU15ADnhECDyHgEfEvsEAVgoF5ErZuwzGZsJEKUZXYDYbdO5ySpWLUrQtr1p1s9XjrbcaKc1ATrecINykSgSmgaAMcBy8soCcbiGlrRaePCJ5LTJsAh+DwdjCuIUn2hJOnVKdnCmlFgZR+OT6nayOKGXaLT/BUV2DMTqtfY+uJYQ6pu9RpxTLlGIwGJtBSQEZwPmVDFYyeQAAx3FrFpAZjM2EiVKMrsAsZErxjWZKuUQseh+UejOltvr0PcuycXYpjSNTcZxdStd9MhH0iFAk3mmroNP0aDuemjehSDyCntUnNTJzSjEYjAuAnJMnxTttzPTYopv2qmJJJ2DbdjHovAGnlOI6lrY6i9HtjsoZVkdlMlGnlFyHU4oW1gzWvtcSTNPEM888g/HxcZjm1l6rMRjN4C4gp3IG5hM5nF8pClBrFZAZjM2EhbkwugIqlIh1LPrccBwHniN5UtWcUlUzpQotFhvRitAprCf4cKzPj32DARydTmC35HNyU3yyCNu2MZdQccVoBGN9/lW39QhAHkCGiVIMBmMLQ51SNKMQKLbxAcQt5e+wXL2cYYEeLhtp3xP54vE2b1oN5VHVotwdpeomgnVkOG0GVCAT68qUYkHnrUTTNNxwww0AgF/91V+Fx+Np8x4xGJ2Fu4BMiyR5w3amX69VQGYwNpPOOKIzGDWgVvdGnVJA0S1V7gAqOqUq36eyxdv3aPDh0ekEIl4ZY/1+RLwyjk6T64/NJNa8Pc9zuOPQKHr9Mk7Mp6CbFiSBg6ZbOL2YRq9fxu2HRiqG0yuFc5VMnolSDAZj65Irm7wHkO9O6qrpxOMLdb9KAldXeDeF47gNy5VSy0WpDmrh0xuIF3CCzi0bts3cUgwGY2OhBeS5hFrmODWdAvL+wWDFAjKDsZkwUYrRFVhNBp0DRSGrvH3PCToXKldzaWVb34B8jHbTquDDgyNhfOTm/RiJeJE3LKi6ibiaxxWjkTWneXgKTzlr32MwGFuZ8sl7FOoi6sRcKXri0kjrHmUjRCl3OyEVfjIdJEoZNfIp3dCgc9sGttiygsFgdCDuAvJ0TIVuWrBsG7FsvmYBmcHYTJhXj9EVUKeUsCFOqSpB564FZs6wmlqgdyru4EPTsnF6KYXBoIJev7Iq+HDPQGDN+zo4EsZrLxqEyPM4tCuC1140iLE+/5oHOEWgQedMlGIwGFsXrZBJ6G7ZAwBFEgDN6EhRysmTaqL9ThFa7zDWTdtZA/T6ZSymcp3llGpAlHJHEOimBYHfOusKBoPRmdAC8p9++0XMxFSYlo1oOo+X7+7D7YdGasZ1MBibAROlGF0BdTk145Sit2k06FwUeIg8B8OykTPMLSVKOcGHYQHRdA5J1YBuWOj1KwBIhXwhWX/w4VxCQ8gr4cZ9/TVFLMDVvsem7zEYjC0MFZ2UMqcUbQ+nTqpOggo+jeRJURSp9VmMdH94DujxSVhM5ZDtoNZv3aw/89Ld4scm8DEYjM3i4EgYh3ZGsC3kgW5aeNlYD37lpj3MIcXoGJgoxegKWtK+51oA2raNfGEhKa2xkJRFHkbe7Mjcj/XgDj6kge+qTiYaiQLfUPBhzjCxlM4BALZHvHX9fY8jSnXOiQWDwWC0mhxt3ytzSjntex043ZUKPs04pWSh9VNrszrZH58swCeTY1J58Hk7MSzqlKq9PuE4zil2mWwCH4PB2CR000I6ZyLklQCQwjsTpBidBMuUYnQFVFBq5guUOurdopR7XHU1pxTgCjvvwGr2enAHH+Zc7SPpnNFw8OFCIgfbJkJXyCPV9feVwlOe1c0tl9fFYDAYFCrOlE+ioxlTnXhsKWZKNV633IhMKeqU8soifAWbbSeJUo5Tiq9vSU2La7rVea89g8HYmsQy+ZKfV8p+ZjDaDXNKMboCy15PphRZKLpFKd1VoZTXyIFwFthm5yyAWwENPpyJqTg+lwTPcRB4DkupHJZSuYaCD2fiKgBgpE6XFADIAsCZJOw1q5sIdNhIdAaDwWgFVYPOxc51Sq2nfW8jRKmsa3+oe0vVO8dl20imFNmOQ84ADOaUWjeSJOGTn/wkxsfHIUn1FcUYjAuRlSwRoXyygGzeRCybh2XZzC3F6BiYU4rRFRjraN+jQpblypSiC2ZJ4MCtIXTRMd6dmPuxXmjwYa9PRt6wkNYMLGdyNSfnlTNbEKXqbd0DSDYIPblgLXwMBmOr4mRKVWnfy3Vy0HkzohRt3zNb6JTSi6JUR7bv1REF4EYU6GTfrbeu2GxkWcaf/Mmf4M4774Qsy+3eHQajY6HOqF19Pog8B9MCEqre5r1iMIowewKjKzDXI0o57XvF6+hicC2XFOBq39timVKUS4dDODgSQkI1oJsWPBKP33/jRU5YbT3MOKKUp6G/HVAEaIaBdM7AUEO3ZDAYjO6AilLlTqmODjqnIlAz0/ekjXNKeSTBcW914vQ9sV6nVGEdw4LOGQzGZhHLEAGq1y+jxydhKZ1HNJNHj5+JuYzOgDmlGF2B077XxDuWWlNLMqVqTN6j0AV2K0NbO4mUZsAGh4hPwli/H35FwmxCq/v2umlhIUm2b6R9D4BT8WZOKQaDsVWhBY3VmVLUhdt5xxa1FU6plmZKuYPOOy9TiopLYp1FMypemSxTat1YloUXX3wR58+fh8WeTwajKrFC+16vX0ZvQYhiuVKMToKJUoyugLqchDqDRN1Uat/LGfVlQNCWi63qlIqr5IAU9kpOqPlENFP37ReSGiybnCyEvY3lOfgLgbVpJkoxGIwtStVMKalzXbjZDsuUcrfveTtQlNLrXE9QxEKbn84ypdaNqqq4+uqr8ZGPfASqqrZ7dxiMjoUGnff4ZPQGFADASibXzl1iMEpgohSjK6AVxeaCzlc7pZz2vRpOqY1YYHcS8Syx8/b4ZIz1+QAAk8v1i1KzceKS2h7xrpnNVQm/45TqnJMLBoPBaCU0yLxaplQnOqWyhRDxcndXPdDHuRHte15JdGVKdU4xgzql6s2UkgrFNRZ0zmAwNgPbthHNFJ1SfQWnVJQ5pRgdBBOlGF0BdUo1YZQqilIVgs4v9EypeCHkMOyTsKufOKUmV7Kw7foWy7PO5L3G8qSAolOKte8xGIytSq7glFK6yClVnL7XeOxosZDTOrHNPQ2Qurd00+6YoPBGp+85TinWbsZgMDYBVTedY03EJxXb99JMlGJ0DkyUYnQFG+WUKj9RKMcRpTqwmt0K4oUe84hXwnDIA0XkoekWFpL1WXpnmpi8Rwko5ISHte8xGIytiG3bjlOq3HVUnOzaWccW3bSctrJm2vfoMTPfQsHIPQ1QEXnQ6KZOaeFzMqXqnb5Hg86ZU4rBYGwCNDsq6BGhiEKJU6reIjSDsdEwUYrRFZgNLvrc8Fz1oPMLPlOq0L4X8cngeQ47ekkLXz25UqZlYz5RbN9rFH8HtmEwGAxGq8ibFuh6XylrFacFkU6bvkfzm3hu9T7Xg+wUcjaifU8Ax3EdN4GPrifEOq3cNOjc6BCnF4PB2Nq4ozoAoMcvg+PIuU2niPsMBhOlGF0BLSjy63BKWS5RKmfW2b7XwS0WraAoSpGQcidXqg5RajGlwbBseCTeqbo0ghN0rjFRisFgbD2o4MRzq481jlPKMDuqUq2WCUCNshFOKU0vDV73dlhBgxa8aq0nKNQppVud87ozGIyty4oTck7W+pLAI+SRSn7HYLQbJkoxugIqKAl1jlx2Q1v+KmVKSbWCzoUtHnSuFtv3AGCXM4EvW/O2NE9qe7jxkHMA8Bfa9zKsSsNgMLYgtO3bU0HgoZlStt1aAWe9rGfyHuBySrXomGmYlnNfNOPK10ET+CzLbrh9T2JOKQaDsYk4opSrgMzCzhmdRuMplgxGG6CLvmacUjzNb6g0fa9GZbMYRtv+xW+r0XTTqeSHC9WTHb1e8BxxUMWzeUR81R1QM/HmW/eA0hML07KbEhwZDAajU6Hfr5Xa4GSBZCNZNtmufDpfu3CcUk2EnAOtL+TQdkKOKx6PO0mUcoeV150pJaxekzCaQ5IkfOxjH8PZs2chSVK7d4fB6Ehi2eLkPUqPXwaWM1jJ1Jchy2BsNMwpxegKLLv5TCmqO1kVMqVqZWZs5Uwp2rrnkwXncSqi4IhMkzXcUo5TqonJewDgkwRwTmBtZ7RhMBgMRqvIVQk5BwCO44rHlw4KO1d18l3srTEEpBqyq32vFW2JldoJvYXnU+2A582dVSnVmynFgs5bhizL+MxnPoMPfOADkOXGYwQYjAuBmNO+V8EpxSbwMToEJkoxugK68Gtu+h5fch9AI0HnrQ9t7RTKW/cou/pqh51blo25gig10qRTiuc5+AsVbzaBj8FgbDWoU8pTReDxdGDYebF9r0mnlNjatsRK7YR037IdcNzQDRotUHRl14IGohtW57zuDAZja2LbNmKFIrTbKUX/zzKlGJ0CE6UYXYHZgkwpy67Qvle3U6qzwmhbQXnIOWWskCu1llNqOZ1D3rQhCxz6A0rT++DkSuXaX/FmMBiMVqKt4ZRyX99J7eFUBPI0mykl8I4DthUtfM7+SG5RqvPa9+qdvAcUHd86c0qtG8uyMDExgYWFBVhM5GNsUSzLxtmlNI5MxXF2KV3S+VGLpGrAsGzwXGkRmolSjE6DZUoxugIqKDUlShXWiu6ibc5xSq19f1S0smyS/1Br+26CilLhstwo6pSaT2pQ8ya8FU5OZgouqeGIt+7qcCX8sgggh0wHVLwZDAajleTWyJQCOtMpRdvlfFWEtFpwHAdZ4JEzrJaIUrSdsNQpVRClOqB9j7bgNbI2YEHnrUNVVRw4cAAA8M53vhOK0nyRjMHoRI7NJHDf4WmcXkwjp1tQJB77BgO449AoDo6Ea95+pZAnFfZKJev1vgBZ+yc1A3nDqlmkZzA2GvYOZHQF6wo6rzB9j1Yoazulir/farlSiSrte0GPhP6ADNsGzq9UdkvNrjPknFJ0SjFRisFgbC00vT6nlNZBTima09Ts9D2gNFdq3fuTp5P3ivtDCyVqB2QRUtd1rSgAN2KF4SsMBoNRzrGZBL748DiOTicQ8coY6/cj4pVxdJpcf2wmUfM+KoWcA6QNmubz0W0YjHbCRClGV2Ctp32vcJtmgs55nnMqoK2aJtQpxKq07wHArkILX7VcqVknT6q5kHOKX2GZUgwGY2tCxaZqx5lOzCzMOtP3mhel6ONqTfteIXjdlXHlZEp1QvueSdv36l+bONP3mFOKwWBUwbJs3Hd4GiuZPPYNBiDyQN4wEfCI2DcYwEomj28cnqnZylcp5JxC3VIs7JzRCTBRitEVGOsQpahdtSTo3CSLWVmovfB2Thw6qJrdCpxMKe/qA9VYoYVvsoIoZdu20763XqdUgDqlOqDizWAwGK2EtuUptZxSHdCGRtH09QWdAyRXCmiNuzhboZ3Q5zil2v+80bVJY04pGnTOnFIMBqMyE9EMTi+mMRwm6+zjcykcn0vCtCxwHIfhsBfji6k1hxIBxcyocqeU+zqWK8XoBJgoxegKWhF0Xql9TxJr319xbPfWqWpalo2kVhCl/NWdUtMxdVU1dyWTR86wIPIcBoPrdUqRE580CzpnMBhbDFrI8IiVRSla8Oik9j3HmdRkphQAKFLrnFKV2gndQeftHkDiOKUaEaVY0DmDwahBSjOQ0y14ZQG6acGwbJhWMe7CKwvI6RZS2tpFXdqa17OGKBXN5Fq89wxG4zBRitEVOEHnTWRKCZWcUoXFslzHQrLolNo6olRS02HbJAQ+qKyuiPcHZPhlAbppO/lRFPrztrCnKZHQTYBlSjEYjC0KdUrRQPNyFMcp1TnHlla0722EU8pbIVPKsOyW5FatBxZ0zmAwNoKgR4Qi8VDzJvJG8fyFFnHVvAlF4hH0rO1qXcmQAnRvpfY95pRidBBMlGJ0BVRQambSW7koZdvFhWw90yZo1Xcrte85k/e8ErgKQh/HcdjVXzlXasbJk1pf6x7Ags4ZDMbWpWbQudhZ7XuWZTsC2fqCzgvu4hYcM2mYubudUBZ4J8Op3S18TWVKsaBzBoNRg7E+P/YNBjCXUJF3fZemcwZs28ZcQsX+wSDGCp0NlTBMy+mK6KnQFcHa9xidBBOlGB2Pbduga7d1BZ0X3Fa6aYM6/uvJgaBV360UdE7tvJXypCjVcqValScFAP7CiU+Gte8xGIwtRk5fO+jcI3WWC1d1iWPrad+TWxp0bq7aH47jHLdUu8POi1EAzWRKdcbr3s2IoogPfehDeNOb3gRRbD4HjcHoNHiewx2HRtHrl3EumoFuWrBsGyuZPE4vptHrl3H7oZE1i/VxlXRFSALndCa4oaJULJuvGZjOYGw0TJRidDzutrtGqpEUnit1Srnt/nW170m06rt1FpBxteCUqjB5jzLmTODLOrkdtm07k/e2r3PyHgAECrZjVTdZKwODwdhSaAZt3+uOoHMq8Cgi35QrmbIholSZc8vXIaIUFZYkvvFMKYNlSq0bRVHwxS9+Eb/xG78BRVHavTsMRks5OBLGR27ej9GIF3nDQlozoOZNHBgK4CM378fBkfCat3dP3qvUFRHySBB5DqYFJArnBQxGu2BlBUbH47a48y3IlNILC2VJ4OpaeG/F6XuJQvtepRGxlOGwB5LAIZs3sZTOYTDoQULVkc2b4DlgKLR+UcorCeA5wLKBTN5E2Mt0cgaDsTXI1Wjfc44tHSJK0Va49bTuAcXHtd68J9OynWJQ+T51ygQ+KiyJDWRKsaBzBoNRLwdHwrj1sm3wyiJ004Ik8Lj9mtGaghSw9uQ9gLixenwSltJ5RDP5imHoDMZmwc4AGR2PZa/PKSWWte/RhXK9I5y34vS9OG3fW8MpJQo8dvTQFr4sgGLr3lDI09AI7GpwHOfkStGpTwwGg9HtmJaNfEF0qBZ07jilOsSFW2nSXTPIjti2vse1VjuhV+6M40Yz0/ck1r7XMmzbxtLSEhKJRNsnMTIYG0U6ZyDklbC734+QV8JMTK3rdmtN3qOwXClGp8BEKUbH427fa8Io5WrfIz87k/fqzIDYitP3aPtexFtdlAKAXYVcqYllkitFJ++1Ik+K4nNypZgoxWAwtgZuZy0tbJTTee17dNT4+kz0itAapxR1QXmk1e2EvsJzl23zc0fdTnITTinDspmQsk6y2SxGRkbwS7/0S8hms+3eHQZjQ0gW1uyXbg8BAM5H63uvrzV5j9IbUArb5taziwzGumGiFKPjocVEkecq9kTXojzo3Jm8V2dls5X5GJ2AbdvF6XtrOKUAYKwwgY86pWZbOHmPQsMX0yzsnNEklmXj7FIaR6biOLuUZoGdjLZDp9hJAld1QAd1UOmmXVJ8aRetdkqt95i5VjuhkynV5uMGdTuJDWRKUZexbaMjXncGg9G52LaNpEYKBrRlbz6p1RUpUnRKVV/r9xWcUlHmlGK0GZYpxeh46KKvmcl75HaF+ylUNJt3Sm0N0UTTLcf1tdb0PQDY2esDx5GDVVLTN0SUou17zCnFaIZjMwncd3gapxfTyOkWFInHvsEA7jhUX+YCg7ER0ONFtTwpoNRBlTNM+NbpUFovaoVJd83QKlEqq5NjQqXnhQafqx3ilGooU8q1ljEsG1WMdAwGg4GcUVyzj/Z4EfKKSKoGZuMadhcKx9WolSnl/t1KmolSjPbCnFKMjscsOJyaCTl3347ej96gU2qrTd+Lq+TA45eFmsKcRxKwrRBofmwmgaRmgOOAoXDrptz4HacUE6UYjXFsJoEvPjyOo9MJRLwyxvr9iHhlHJ0m1x+bSbR7FxkXKNQp5VnjO1bgOaftS+uAzMJqk+4ahYpt623fy+arC3u+DsmUMhrMqARKC2w6mzrLYDDWgLbueSQeiihgZy+J1Ti/snYLn6abznfoWkON3E4p1k7MaCdMlGJ0PLR9r9lcbad9z1qvU2prLB5p695aIeduaK7UU2eiAICBgFI1I6UZAgrLlGI0jmXZuO/wNFYyeewbDECReETTOXhl4pRayeTxjcMzrJWP0RZoTpRSw3WkdFCuVKum78ktmipYV/tem6fv6U2IUhzHQaK5UmwCH4PBWIOkRtbsIQ9Zs9crStHWPZ8srOnY7fHL4DhyjpNp8/cp48KGiVKMjoe275UHndZLuVPKyZRqVJRq0UlDu/NvinlS9Y1+Hevzw7ZtnFnKIJrOQRb4lu6zX2bte4zGmYhmcHoxjeGwFxzHYTauYiKaxVIqB47jMBz2YnwxhYlopt27yrgAcUSpWm7Uwu87QZRygs7X2b7nHDNbFHReSZTydowo1Xj7HlDMoDKYaM5gMNYgoZLv5ZC3VJSaWsmu6Wyqp3UPIII6FbxYCx+jnXS0KPXpT38aL3vZyxAMBjE4OIi3vvWtOHnyZMk2tm3j7rvvxvbt2+H1evGa17wGL774Ypv2mLERuIPOm4E6pWigKHU81VvZlFu0wAZIu9Gffe84/vTbL+IvvncCf/rtF/Fn3zu+qW1GiUL7Xq3JexQ1b+Lw+RienYzhufNxfP/YXEv32c+CzhlNkNIM5HTLOTmlJ/U0Y8YrC8jpFlIaEzsZm4/TvlenU6oTnLhqYZ/X277Xukyp6hlXVKhS292+V1igSA0EnQPuCXztf90ZDEbnQp1S4cKafXvEC54jayBaZK5ErDB5b63WPUqxhY9N4GO0j44WpR599FF8+MMfxlNPPYUHH3wQhmHg1ltvRSZTrHx/7nOfw1/+5V/ir//6r/H0009j27ZtuOWWW5BKpdq454xWQh1OQpOZUmKZKKU33L5XOGlYZ+ZHp+Tf0INYPQeqYzMJfOkn55DUDMgij6BHxEBQaek+0+l77c4GYXQXQY8IReIdNwU9qaf/qnkTikTeswzGZlNP0Ln7953glKICz3oD12VXy/t6MkrW2h+fRI8bZltzUJp3SrH2vVYgiiJ+8Rd/Ea997Wshiuy7nrH1oJlSdC0jCTy2F4YNTcWqt/CtZKlTqnYBmrqpaMsfg9EOOlqU+sEPfoAPfOADuOyyy3DllVfiy1/+Ms6fP49nn30WAHFJ/dVf/RX+6I/+CLfffjsOHjyI//N//g+y2Sy++tWvtnnvGa2CiklNt++ViVJO+16di0ilMLY7bza/wC7Pv/FIPEzLRsAjbnr+TVytL1PKvc87e7yQBB4cx2EgqLR0n6lTijlaGI0w1ufHvsEA5hIqbNtyXBn5wonwXELF/sEgxvrWnk7DYGwERadUrWEStH2v/Y6ZbKsypQouZNteX3taMXh99XPoK2QRWnZ7XWbFTKkGRanCc8SCzteHoij4p3/6J/zO7/wOFKV1A1gYjE4hWVgb0xY7ANhRR65UrNC+V08BmopSUda+x2gjHS1KlZNIEFdGb28vAODcuXOYn5/Hrbfe6myjKApe/epX44knnmjLPjJaDxWTmnVK0dtZ5dP3GsyUsu3mpwm5829sG3hxNomjM3EYlrXp+TdOplSN9j33PgcLB0OPxEPg+Zbus18ptq8YbIHOqBOe53DHoVH0+mWcXEgjZ1iwbBuZnIHTi2n0+mXcfmikaTGbwVgPjlOqxlAI6sTVjPY6pWzbdlpfa7m7auGebLsewcgRpaTVDhhJ4B0hqJ25UnR90kjQOQBI1CnFMqUYDMYaUKeUe81eT9g5zZTqqZEpBRRFKXobBqMddI3X1bZtfOxjH8NNN92EgwcPAgDm5+cBAENDQyXbDg0NYXJysup95XI55HLFvtlkMgkA0HUdul7sz6X/d1/H2HxyeR2WZYGDXfW1WOu1skwDlmVBt8nv1Ry5P36N+3PD2TZs24JtAxk1B95TXxaTm1hag5Y3oAQVLKZUp1UjreoIeSUoIgctbyCW1qBHNq7aZ1o24tkcbBvwS9yaj9+9z4ooIp4V0eOTYBUyMJrd5/LXSoQN2BYsG4hntJpiGWNz6Ibvv4sGfbjr1bvxL0+dx2xchWnZEHgOBwb9eOe1o7ho0NfR+98quuG1utDIaOQ4I3D2qtfH/TpJnA3LspBR8219/XK66RQFJM5a976InI28aSOj5qDwzQkv9DmU+crHakXgkNNNJLMagnJrxed6P1NanqwvYJkNPWccyOuu5XT2uV0Htm0jkUhA0zTk8+yEupNhx6nmiGdysCwLPqn43A0HyVp8ZiULVcs5zkuKbdtYSWuwLBshee21PgCEFB6WZWEppZWcC7PXqrPpltep3v3j7HY24zfAhz/8YXzve9/D448/jtHRUQDAE088gRtvvBGzs7MYHh52tv21X/s1TE1N4Qc/+EHF+7r77rvxqU99atX1X/3qV+Hz+TbmATCaZioNPLHAo99j4+aRxt+umgl8a4J8Yb9zj4XHFzjMZjhcM2BhX6i++7jvHA/DAt60w0KovqF1JSyqwH+c4+ETgUWVAy0e93lsRGSyjxkDePtuC4Pexu+/XjI68N3zPHiO/K21zGd0n/0i4KlQOG/lPn9rgodmAreOWuhhDnxGg5xPAY/M8jBsQOSAN++0MLCBnyMGoxY/nifHmWsHLOxd4zhzbIXDizEOe0M2rh1o33KMHhsEDnj7nvU7Vv/fBI+cCbxh1EKzdZZvTvDIm8Abd1gIVzju/mCKQyLP4dXDFra1aelWax+r8cgshyWVw/VDFnYGNm7/tjqapuHd7343AODee++Fx+Np8x4xGK3DsoGvn+MBG/j5XRZ8BSuJbQPfmiTfsTePWOgve9trBvk9Cmv9Wt3FOZN8ZwPAHbst1NlIwmDURTabxXve8x4kEgmEQtUXRF3hlPrt3/5tfPvb38Zjjz3mCFIAsG3bNgDEMeUWpRYXF1e5p9z84R/+IT72sY85PyeTSezYsQO33npryZOl6zoefPBB3HLLLZAk5t5oFy9MJzD17Az2Dvhx2w27Km6z1mul5k0c/j6Z2viGN16MxZ9OQVjK4FWHtuOqHZG69uHYf55CUjPwylfvxkik8bNdy7Ix/YOT+Om5FciwoBTUoEBAxmifD2eWMrh+JIT3v/GiDW03mohmcOTxSfT5Zbz59fvq2udjM0mMDvjBuRQs27ab3udKr9XZH57BfDKHl79iJ/YPsRV6J9BN338/Pr2Mac+i8/PV14zgitFwG/doc+mm1+pCYfbxCQjRLF5z7QguHyHvxUqvU/hMFMljC7hkNITbrhld6y43dn/jKo48eg4hj4jb3nBg3ff30oPjWMnquOmVY06rSSPYto0nv3MCtg383BsOVBxYMPeTCZxbzuLaDfi81/uZevq7J6CbNt7w+n01R6+7WXpyEuOLGVx39XZcvTPSgj2+MHEPPnrd616HSCTSvp1hrAk7TjVOUtXx1APj4Dng9p+7pGStHf/peZyYT2PvwSHcuLev5HbnV7I4bE8g7BXx87fW931+/P6XoOoWrnvVHvR6BfZadQHd8pmiHWm16GhRyrZt/PZv/za++c1v4kc/+hF2795d8vvdu3dj27ZtePDBB3H11VcDAPL5PB599FF89rOfrXq/iqJUDESUJKnii1rtesYmwQvgeR6SKNR8HSq9VhbHgy+Ma+ZFEabNged5eBW57tfVK4tI5y1Y4Jt+L7zj2h34yekoUjkDfQEFecNCQjNwdjmLvoCCt1+7E4rShA2rAdJ5GzzPozeg1PU43nHtTswlxnF2OYvhsBdeWYCaNzGXUNe9z+7XKuiVsZjWkbPAPmsdRjd8/9H3NSWZtzp+nzeCbnitLhR0C+B5HgHv6u9a9+sU8MjgeR6GzbX1tdNtjeyvp/7j4lp4FQm8ZsLmmjtmqnkTHMeD44CQT1nVngLQ505D3tq4526tz5Rt27DAgec5+Bp83hRZAs/zTT8/DIL7uWPff90Be53qJ5vSwfM8Ql5x1Vp710AQJxezmEvmVz2fqcKaqD/oqfu5Hgh5MR1TkczZGAqR27DXqjvo9Nep3n3raFHqwx/+ML761a/iW9/6FoLBoJMhFQ6H4fV6wXEcPvrRj+Kee+7B/v37sX//ftxzzz3w+Xx4z3ve0+a9Z7QKGlAuNOkgcgekW1Yx6FxpwJ+qSMUw7mbxSAL2DgZxPppBwCNiYjkLUeBww54+3HHNKA6ObLyzozh5rz4h6eBIGB+5eT/uOzyN04tpLCQtKBKPK0YjuP3QSMv2OVCYwJfJtX8sOqP7iBfGGAcUAemc6fzMYLSLhoPO9fZ+96016a4Z6CCRZqcKZvNk4pQi8hUFKaA4JEPV2zO51bRs0AAMFnTOYDBaTVIja/ZQhSzbXWuEnTcyeY/S65cxHVNJ2DnLP2C0gY4Wpf72b/8WAPCa17ym5Povf/nL+MAHPgAA+MQnPgFVVXHXXXchFovhuuuuwwMPPIBgMLjJe8vYKAyTLNr4ZqfvucQs07ad0fH1Tt8DigLWekSpH51cQq9fxm2Xb8Nl20P4ywdPgQOHD71mL4ZCm5ODQE/WIw2EiR8cCePS4RAmohmkNANBj4ixPn9L2wz9BVEqnWvPyQWju6ETJcf6/Tg2k3R+ZjDaBRVjPNLaxxn6+2bFm1ahOqJUa5aFdAJfsxNrqUi21iRAb+F37Zq+p5tFQUls8HhIhTYmSjEYjGokVbImDlVYs4/0eMFxZP2TUPWSIUF0il4jLcV022gmV2NLBmNj6GhRqp4Mdo7jcPfdd+Puu+/e+B1itAXqlGp00UfhOA48RwIDTct2FslNiVJNVrOnY1mcWcqA54BX7R9Aj1/GZdvDmI6pWErlNlGUok6pxmyePM9hz8DGZT0VnVJMlGI0Tqwgtu4uiFIxNtaY0UZs23acT8oaogrQQU6pwt/31djfeqHH13yThRyV7o9cfX98BQGtXaKUUZhEy3GNO7npesZoUrRjMBhbn6JTavXpuiIK2BbyYC6hYWoli7Crc4GuiXoaEKX6CtuusPUTo02wfH1Gx2MWKonrcebQBaNlFZ1Sjdjt6YlDs06px04tAwCuHI04BwkqRM0ntKbusxmaFaU2GuqUyuSZKMVoDE03HZfJ7n4/ANKm2iWDZRlbEN20QQ0wtdrEO80ptZYI1AjrFqXq2B/6u2ybihnUKSXxXMkgkHoQC+Ow3G4rBoPBcJMsRG5UckoBcIZITJW18K002b7nvi2DsdkwUYrR8Zg0U6rJ9j2g2PpnNOmUWs8Cezmdw7HZBADgVQcGnOu3UVEquTmilG3bSBQOcGHvxgaqNwrNBmHte4xGoRVBnyxgIKCA48iJHnsvMdoFzZPiuNqiVDGv0GyrkEpFIE+LRCllnaJUMeNqjfY9mWZKtUfQoy6naplXayHytH2POaXWgyAIuP3223HDDTdAEFrz3mUwOoWkRtYx4Sqi1I4KuVKWVVzr9zYgSvX5yQCwlUweFmsrZrSBjm7fYzAAOF+OzQadA8QqnwNd+JPr5IacUs1nSj0+vgzbBi4aCmBbuNimty1MDgALmyRKabrl7H+nOaVY+x6jWRz3n1eCKPAIeSQkVB3xrI5ghXBQBmOjoa4nReRrOmioU8qySf6SUiMYfaNodfveenMYaXh5fe177Tlu5B1RqvG1iSTQ9j128rcePB4P7r33Xtx///3weDYnBoHB2Cwcp1SF9j2g6JSaiaswLRsCzyGu6rBsct4T8tZ/mh/0iBB5DoZlO0ORGIzNhDmlGB2P0cL2PXeLREOilEQX2I1lV6Q0Hc9OxgCUuqSAYvteNJNvuprcCDHXhLJGJwVtNH42fY/RJPR9HSlYz6ngGmMT+BhtguZDrRXSTZEFHlS3amcLn5qnIlBrapVUXMubzX2nO06pNZ5Dp32vTZlSNFqgkbUEhQWdMxiMWqw1fQ8A+gMyvJIA3bQxl1ABuFv3pIbainmeQ4+zfmKiFGPz6awzUwajAtQp1WzQOVAUtOjJgshzDYlczWZKPXEmCsOysaPX6+TdUIIeCQFFgG1vjluqmCfVWa17AOAvnAjlDAs6C35lNECi8L6miylqV2eLKka7oMWLWq17ABnE4RGLLXztop52uUaQneEg623fqy6SFdv32tP6SI9VtBWvESQWdM5gMNYgZxTzMqtlSnEch529XgDA1AoRpeJNhJxTWK4Uo50wUWoLYVk2zi6lcWQqjrNL6S3TE0wzpfh1ZErRPCo60aeRPCmguel7mm7ip2dXAJCJe5UqFtQttSmilEoOMtV609uJR+JBi81Z5pZiNEDMad8ji6lwQZyKM6cUo03QE4l6nFJku/UJOK2AHhtbLUrlmxRdtHqm7xWeX9tuj8uMhpQ3075HnVL6FlmntYtMJgNZlvHWt74VmUym3bvDYLSMpErcq4rIr3ks2VEWdh5tIuSc0hso5koxGJsNy5TaIhybSeC+w9M4vZhGTregSDz2DQZwx6FRHHSNCe1GzBY4pWj7Hg1zbbR9rZkF9jMTMai6iYGAjMu2hypusy3swZmlzKaEnSc6dPIeQKo9fkVEUjWQyumOsMBg1MJp3yu8Z+hCLMYWVYw2QR1PnjqLH+SEQ2+rU8qZdteiTCna0rbuoPM19kcUeCgij5xhIZs3Wiao1QvNg5KaEqWYU4rBYFQnpa2dJ0XZWRZ2Ttc+zTil+qhTKptHd585MroRJkptAY7NJPDFh8exksljOOyFNyxAzZs4Op3ATEzFR27e39XClNmCoHOhrH2vcadUob2iRjXWsmxMRDOIZ/P4zgsz4MDhlQcqu6QA1wS+xGY4pUodJZ1GQCaiVLvyQRjdCZ0yQ0WpXn/BKcWCOhltolGnFHXititTSjctx/XT8va9dYpSazmlALK/RJQy0dfUX2oevTA5r5mMRpFnQecMBqM6dG1TrXWPsqPXB44jDql0znDc433rat/TmSjF2HSYKNXlWJaN+w5PYyWTx54BP9Q8yeQJeETsUwI4vZjGNw7P4NLh0LqCwtuJ2cKgc9qiUE/Wh5t6Jgm53WrRdA4rGR39QRl3vnxH1dtsavteBzulAMBXCDtPswl8jDrRTQupwshk6pAKF0TXeFaHbdsNBX0yGK2gkaBz93ZaA+3hrYQKQDzX+LGxGvR+mnVK0eD1WiKZTxIQh+4c2zcT3aCZUk04pXjavsecUgwGYzXJwtqmWsg5xSMJGAgoWEzlMLWSXeUeb4Q+V6bUWMO3ZjDWBxOlupyJaAanF9MYDnsxtaLCO34SL4udg7+/FzmvD328B0tRCVO7ROzaPQz4/UAToZztxHFKrePkkuZROU6pBiubtabvlbrVPIimc5ALbQV/88MzVd1qgyEFHAekcybSOQMBZeM+kjRTqlNFqaAzgY+JUoz6oEKrLHCOo4K+v3OGBVU3WzZNjMGoF+p4qlfgabdTSnW5klol4q7HKWXbdtEpJa39+aWiVTuOG3RyXjNOKUlgTikGg1GdpOOUqr2G2dnrw2IqhzNLaadQ19uEU6rHL4PjyPd2rrtOFRlbALZa73JSmoGcbsEbFhBQBFzz0lP40Hf/bvWGf1z494EHgFtuIf//2teAz3wGCAbJJRAo/f/73gccOEC2nZkBTp4sbuP+V9zYtxENOl9f+x75t5gp1dh9rTV9z+1W2zcYQELVkTNseCQeV46GcW45W9WtpogCen0yopk85hMa9g0Gmnh0tTFcjpJOnL4HAD6lfScXjO4k4QitsnMyLQk8gh4RKc3ASibPRCnGpuNkSnWJU8oJOW9RnhTgymFsQpTKGRZo/ndNp1Th890WpxSdvtdM+17hNixTisFgVCLpZErVLiTv6PXhmckYjk4nAJBCRzPf55LAI+SREMvkkGYJCIxNhq3Wu5ygR4Qi8VDzJnyKiOXwAA4fuAb9dh6KmoWkZqCoGfhyWXCmCYRcgdtTU8Bzz1W/85tuKopS3/8+8Gu/Vnk7rxe4917gF36B/PyjHwGf/3xR4CoXsW65Bdi7l2ybSACzs+R3oRD5fZmTy2pBphTvTN8jC0BZbOzLmi6wddOGZdkl4pLbrcZxHOYK+VBDQQ9EQcBw2IvxxRQmohnsGVgtOg2FPYhm8lhIbpwoldQM2DZpM/Bvchhsvfid9j2WKcWoj1iVltQen4yUZiCe1THa0449Y1zIOE4pqd6g8/XlL62XrNMq17oloSKQ40zebPz7nBaPRJ6rWUCiDsl2TG1dV9A5zZRi0/cYDEYF6PS9WplSALCrj4SdJ10uqWZdr70+CeejaZzOAueWM9g3FO7a+BdGd8FEqS5nrM+PfYMBHJ1OYO+AH48euhk/vPpmXDEahiLyOL2YxhWjEXzytovB5XOA5Ppye/vbgUsvBVIpckmni/9PpYDdu4vbBgLAZZeVbqcXZHRVBWSX++bMGeB736u+0//+70VR6oEHgHe+s/T3fn9RzPrsZ2EOXkV24eSLwGf+72pHVzAIzuuFJxot3kc+D2gauS9BWJUp1XjQeXH7nGGVVG/dbjUtbyClGeA4IjYBpNK7kCw6lcoZDnlwfDa5oWHncVePeadm7ARY+x6jQWJVRh9HfBLOrxTb+xiMzaTRTCml3U6pOkPFG4EeY02LuIEacRPR43Q97YT0WJxtp1OqiUgEZ/oeE6XWhSAIeNOb3oTFxUUIQmcW3BiMZmjEKTUQUCALHJbTeeimhaGQsqqAXg/HZhL48ellnFpIgdMFTH33JezfFtwSk9wZnQ8Tpbocnudwx6FRzMRUnFnKQOA5GIaF5ZQGVbfQ65dx+6ER8AJPHE1udu0il3p497vJxU0uVxSwBgeL17/ylcA//uNqsYv+OzZW3NaygEiEXE8rqpkMuczPA/m8s2jzTJwF/v7vK+6eCGDorruAX/olcsWjjwK33kr+7/Ph3R4fsrIXuj+ArMeP5Q/+BnDNr5LfT00B//IvxKlVqZVxZARiJAKeAyybtCO4RSm3W81pJ/JKTs6EmjehSKSlqBLbCuLV/AaGnTuT9zq0dQ8A/DILOmc0Bn1fh1c5pcjPKwUxlsHYTKjjyVOnI5dup1XJLNxoaH5TqybvAaWFnHyDolQj+0OPGzQYfTPRrfU4paj7mrXvrQePx4NvfetbuP/+++HxeNq9OwxGS7Bt28mUCtfhlDo+l8SJuSTOr6gwLRvnV7JIqHpDYhLNxp1PaJAFHpJtI+yTtswkd0bnw0SpLcDBkTA+cvN+3Hd4Gk+cWUZaM7CUzuOGvf24/dDIxn2JKAq59PeXXn/gQLHtrxbvehe52DZxNrmdWqkUcNFFsF5KAQCMAxcD/+2/lTq6Cv+3kkmofa6B0Ol08f/ZLLzZLNySXDbhcmedPAn80R9V38fPfQ7cxz8ORRTQ89JRBEdfA4SCTsvh7kAQf5C2sWBL+NHlr8LMgevQ65fhSSdxydM/wkSex8tHBzE2bgGLoaLoFQoBouhM4FtMak1VNuohQduc6ji4tQvmlGI0CnUArnZKkZ8TTJRitAHqeKq3fY9u17ag8w3IlOILrXe6aSNvWGikHtKIc8srk+eOClmbCc2DYkHnDAajlaRzBiwb4DggUKWgTXEGLWXzkEUeIs+hxyc3JCa5s3F39/lweikDUyfr8uCgtCUmuTM6HyZKbREOjoRx6XAI3zs6i+8cmcOefj8+8caLu+fLg+OIk8vrLXVdATCPE1FKv/hi4HXXVby5qetYvP/+4hVvfSuQzTqi1Q+eOIWJyQUoagaKmsXYDa8sbjs4CPzKrwDJJLmUtzL29gIgJw6ebAp8bAWIrRR3HcBlhcux4DDMfS9DyCPCe+ok3vnXnyz+nT8p2+k/+iPgz/8cfX4ZA8uzuPOej8D8TB/4SLg0jysYBF79auD1rye3U1XgJz8pdXNRoUuqLDp1+uQ9oBh03o6TC0Z3QtvzeipkSgHFzCkGYzPRGg06p06pLdS+B5Apt7ppNpyV5WRc1fH80aDz9ohSRFASm3FK0aBzy4Zt2x3bVs9gMDYfGvcRUMQ183RLBi0NBDC+mAFA1vphb/1iUmk2LrlOMzicWUpjR69/VTauZdmYiGaQ0gwEPSLG+vzdc77J6FiYKLWF4HkOLxvrwxNnVqAZFrbKGsdqZvqeW+QaGEByRcKkb8T59Y4924rbXnEFaTesgSLymDpwBSYf+xl2ydYqV9dTRyZw2rcHksDj/IoK0eJx+uobMSwY8OeypUJXLkeEJJDXbcTKYnjyFDBZ5Y+bZlGUmp4uTlBctZMK8Du/A3z2s+TnlRXgzjtxdZ7HDk7Bzl2DwPaBopB15ZUk0J7+jZMnS0WuDZ6s6IY6pXKGhbxhNZz7xbiwsCwbCdqW6i21YVCRKsacUow2kKNB53V+h7U/6Lz17XsAyZXK5M2GJ/DRfKh6gtepkKa2QZTSrXVkSrnWM4ZlN9UCyAAymQwGBwdhmibm5+cRiUTavUsMxrqha5tQDZeUW0zyuJy5HpEHx3E1By1R3Nm4Agf0B2Rk0sBKRkdcTaDXJ8GwbKQ0A8dmErjv8DROL6aR0y0oEo99gwGWO8VYN0yU2mIMBhVIAoecYWE5ncdAUGn3Lq0bs5DbIK5DhRfKFDq5Cbu9IgrQFS9Se3YCZV+8lmXjkR+8BJ+q4xOXDGIw6EHQcznGPvnuytUDXSd5WnR/Lj6AL/3x3+HaPhFXhIXVbYw33FC8rW0DBw+Wilz5wsl3Llc6vTAWAx54AGMAxio9qLvuKopSKyskzN6Nx1MUqO68E/iLvyDX5/PAb/7makcXvezeTcQ+SiJBQufXELmUgu3YsGxkcgZksXPzrxjtJ6npsGyA57Aqr41mTGm6BTVvtvxkm8GohmXZxUypep1She1ybXJKNeJMagRaWGhUbNMaat9rn8NWN+g03+an7wHEcdXip/6CIpvNtnsXGIyWQvOkak3eKxGTeA7bwx7olgVP4Xux1qAlijsbN+ARsbvfDzMdhe2TkFANzCdz0E0L33lhFmeXMkiqOobDXnjDAtS8yXKnGC2BiVJbDJ4nyvj5lSymY9ktIUrRoHN+HdavcpeV1IQLhy6w8xWCSc8uExurTxbx2osGa4e6lrXZ9Y8M4mdX3QBlJIQrrqsRPn/gAHD0aOl1+TwRqdJpwOdz3XE/7C9/Gfc/OQ4hk8GrhhX4cioRspJJ4NCh4raqSloV3ZMVNY1clpaIwEVJJoEvfan6Pr73vcD//b/FfaPVS68XYiCA1/M8xMFBkqv1+tcDd98NjuPgV0S87Mt/Be757cC2fie3y/l3cBDYuXPt56eFMIty50Jb9yI+adVroogCAoqAdM5EXM3DK3sr3QWD0XLcAoynbqdUp7TvtXZJqBTaEht2SjXg3KL7rOrmhmUyVsNwCmaNrycEngPHkRqTYVkAmCrFYDAIyYKIVGvyXrmYNNrrK/l9rUFLFPck930KcVQpPLBjMIBMzsSR6TiCioDHTi4hruo4MBSAV+Yh8BwCHhH7lADLnWKsGyZKbUFGeogoNRvXcPXmnb9vGJbVRPteGeVfkM05pQpV3wphtEem4gCAy0dDDU0ZomwrhJ0vJJqcwCfLRFAq5F85hMNQ3/M+PB46AQC4+S2XAdX2b+dOIBol/8/nV2druYPkFYW4psodXfQ2F11U3NYdOq+q4FQVfgBYWCj+3QIBwcbNX//f1R/nbbcB3/te8edt24gzrDxbKxgkgtvv/V5x23/5F+LUcgtd7ouv9GDOLMqdDW3NK2/do0R8MtI5FbEMqegxGJtBrpAnJfJc3ccCxSl42JsurADFoPOWZ0o5TqnGxDbavuerJ1PKtY2qm/Arm7es1deRKcVxHESeBMGzsHMGg+Gm6JRqTExyZ9PZto25hIorRiMY6/OveT/uSe6nF9MYCimwbBK4vpDM4ZLhEG7Y14ev/GQCHknAXCKHpVQeO/u86A94GmoVZDCqwUSpLchIhJyAzcS3hqW5JU4prtxJsQ5RqmyBbZgWjs0mAABXjkaa2r+hMBGlljN56KbV1DSfalBHSdAj1n+/skxEKLcQ5SYYBP7rf63vvnp6ipMV02noKyt48sEHccPll0NUVWB42Nk0JHJ44rb34IDPRr+dLzq6aAC9a1sYRlHYmptb/Xfj8VJR6kMfIuH3lbjxRuDxx50fM6+4AYHFOG6XvEAgAMMXQEb2IsrLeH50DPjz3y8KU489RjLMyoUxrxdbJtitA4mrRadUJSI+CdMx1ZnQx2BsBnSCnqfOyXtk26Kwohlmyx1LtdjITCmgcaeUStsJ69gfnuegiDxyhoVsfnNFqfVM3wOIw0o3TSebisFgMAASTwDUdkqVi0nDYS+8Mmmpm0uo6PXLuP3QSF2FDvck9/H5FJY0QMzquGI0gtsPjcC0bNwfnEfEJ2E2oULNWzi3nEXQI0ERhbpbBRmMajBRagsy2kNEqdm41paqa6uhQefNVCMp5WvGZkK0FZr7UbbAPrmQgqZbCHlJH3YzBBURPllANm9iIalhtMdX+0Z1QkWpcI3e9A2D44izSlGA/n5gZASxqSnYt9yyqo3RE/TjO7/yB3jTwW141YGBte+X54FTp4puLrerK50GduwobmvbpE2Qilvlzq5C6DxAnHniC0cwplYWsF7aczm+dvh9RYvynXcCs7OrNxQE4GUvA558snjdL/8yye5yT06k/x8eJvdFOXmy6AILhZjIVQYVm3qqzJpnE/gY7YC24NWbJwUQF7AkENdMTrdQ5S29IZiuDKxWO6UUoXrL+1pkG2wn9CsCcoa16WHnukmDzpv7XpYEDqoO5pRiNAyLFtjaJNVC+14d63a3mHR6MY2FJHH2UzGpEWc/neR+eiGBHzyygDe+7mLsGwqD5zmcXUpDkXgoooDLt4fx0kIKSdXAfELDrj5/3a2CDEY12DtnCzIQUCA7Yec5DBZaw7oVGnRe7nZqBKEs86GZyqZSJbT1hemiS6rZsc4cx2FbyIOzy5kNEKUKbU5VHCWdBK1yZ3J1VFp4Hti/v+KvnAXbVLy4YPvWtyrfj2UVg+JBppl89bf/O/qtPHz5LJbnovDnVexVLMhaBovhwVKL8r59pPWPimIZMpIXZoUTpIceItMTK3HppaWi1O23A8ePlz5eKmTt3w888kjxd5/6FDA/Xypy0X97e4Fbby1um0gURcIuFrncmVKViLAJfIw20GjIOcUjCdBNA1qDrW7rRXXlWHnEDnFKNdhO6JNFrGR0ZPXNq9Bblo2ldA7RdB5zCa0pUYAW2pgoxWgEFi2w9anXKUWhYlIrhEqe57C7349dAWB3f/E+SloFBwPYHvYiqaawlMphe9hTd6sgg1ENJkptQXiew3DEi8loFtNxdcuIUuupArXCKVVpga3pJk7MJQEAV+6INL1/AGnhO7ucwXwit677cWNZNk4upBBN55DTrY53zvkVchKSrkeUqkLDCzaeJ1MGC6Q0Ay/svhJj/X7EsnmcXSIi0+UjIXhlkTgLCsH2AIBHHy29P8siwlQ6vVqY+qu/Irld5a6uVArYvr3syfATUSmdJk4vyyKCUiJR4uwCAHz968CLL1Z+QrZvB2Zmij+/6U3EvSWKqwWsoSHg2992Nt350EPgn3uOBNWXu7tCIeCqqyr/zU0g5ohSazulWPseYzOhTqlGW8Q9Io8Uiu1/mwV1F3kkvuXHBqXp9r1CO2Gdwh7dbrMm8NFjzGOnlpA3bMTVcTx0YqFhUYAGpBusfa9peJ7Hq171KkSjUfBNBM53G8dmEvjiw+NYyeTZ9LMtim5azndZrUwpNzzPbWiW0+pWQQ+8Mo+kauDIdAK7+/11twoyGJVgotQWZbSHiFKzcRWHdva0e3fWRSucUuV5VOtzShUXvsfnktBNGwMBGdvD6xP/hgu3n082GXZeBl04/3h8GYmsjrmEiqlYtqOraYFGnFIVaMWCzT3NxL0f6ZwBryzWtii7HU3l3HFH/Q/mZz8j/1oWycJytxyW89GPEuGpUvB8eS4YDZ43DJK7FY8Xf+fO7AKw8+GHIZw4UXn//P7SEPu3vAX48Y+JWFV+CQaBv//7ojProYdIHphb6HKLY6HQmi4u27ZrOgBZ+x6jHTiiVINOKaVNE/iKk/daP/1NruIuXgvdtJwA8Xozrui+b0b7nvsYIwk8FJFDxCs1JQpI1CllMadUs3i9Xjz00EO4//774fVu7YEWlmXjvsPTWMnksW+wGGrNpp9tLWjBUxK4uoX5zaK8VdC2SdEh5BFx12v2duy5BaM7YKLUFmV7Iex8Oqa2eU/Wh2XZiGXzyBsWpmJZhL2rx7/XQ/nkvuaCzguZUq5K9guFqXtX7mi+dY/iTOBrgSjlXjiLPIegR0SPT+74aprTvtfEyUXpgs2PVI6ISiGv1NCCzW1RdguQ6ZyB/kD900xaBs8TsSYQWCUaOfzqr9Z/f889R5xc5U6tCmLX3CtegciNN0Kg27vzu8pPAFZWgFiMXMrx+YB/+Ifiz//jfwD33199H3WdOLkA4Hd/F/jRj0qEK8Pnx62LeeS8PkTe+D+KtztyhDjRgkH0eP0Iriwi5/VDy+nwKJ3fvsrofrSCANPoMYZuv9miFG1524hw9Wba96hDgOfqfw6peNVsMaNeykWBuKrDtoGgR0KvX25YFKDTGfUGM7cYFyYT0YwTZg0AM7EsevwyfLLIpp9tIRJqsXVvvecVG4G7VTCh6viPZ6dgWoC6yS5fxtaDiVJblNGCKDUXVzu+Zasax2YSuO/ZaTwzEYNp2fjM91/CRduCTTl9ykUpuQWZUumcgfFF4hS5osmpe24GQwoAUiVJ5wzHNdQo5QvnI1NxcByHiE/G9ojQ0dU0+pibad+jC7aIT8LJhTSSqgGOAy4fCcMjCXUv2KhFeWoliyNTGXhlEQLPYSWTh2HaDU0z6UgEoehgqsGZt7wFF912GwSpDkHnP/6DCFN0WiK9JBLE7eXm6qtJjpdbEKMXUSwKUgAJfD98uOTmEoCb6A//+j+Lv/jc54CvfhUAoACg8yHtX+SIs2tykmRsAaSV8uGHK4fOB4PA+95HbgOQHDAaiB8MkuuFzqpgMjqDXBNB5+7tG3EVtYJsvrn9rQd6nM01ILq4nVv1npBRQU3dYEGvXBQozGABz6MpUYAGpK+VKcUCrRmUlGYgp1vwhgUspXKYiWtIagYuGSbHcjb9bGuQpKJUA617m427VVDTLXz7yCweP72E63b3su8nRtN07juesS76A4ozJnkpncNQl+VKUadPNJODLPIQeQ4RX3MWeaC09U/kuaa+NOmIb+qeOTqdgGWTVsmBoNLw/ZWjiAJ6/RJWMjrmExr2DTZX6SpfOOcLC15F5Du+mlZP0Hm1RfpCUsNMTC10fZHX17aBtKbDIzU2rvbgSBjvunYHzq9kkdYMqHkbAs/h+j19eMe1OzrSZdZ2hobIpR7+/M8rX2/bQK4sU+2ee4C77ipxai3MLOGl03Po5Qxc7hbMtm8HLrnEEbisVAq8ZYGzbXJbv8vd9uyzwHe/W30fb7+9uP099wB/+7elv/f5iiLVI48Upz3++78TscvdlugWvV77WvIvQBxrlkX+zgWQh3IhQJ1SnkYzpbZg+54zsbaBx5TNk+9nbwPOLbrvG50p5RYFaOFEEjhHXGpUFHBEqSqZUizQujaZTAZjY2PI5/OYnJxEJBJp9y5tGO5oAfoey+QM2LYNjuPY9LM66XShl7629Yact5trdvXg4RMLWMnoODabaEmRnnFhwr65tig8z2F7xINzy1lMx9SuEqXcTp89/X7Es+QLOuiREPJITTl93E6pZvKkAEAuOCNoK8IL03EAZOpeq9gW8mAlo2Mh2bwo5V4408qxwBcn/XRyNY2eXOimjZxhOi2TlEqL9D0Dfuzu8+PIdALZvAlZ5LEtpIDngaVUHqmcgf4gGl6weWQBh3b2YCjswUwsCzVv4b2v2IkDQ7UdRowm4biS0HkAwBVXkIuL8fFl/ODoHK4YDeNy9y/+v/+PXAr865MTGJ9YxC/sCeLaPolMHKT8xm8Ar3515dD5VKo0E0ySSNh7KlUMr89myWVhofR+f/zj0lbFcsbHycRGAPiLvwA+/Wny//J8rWAQ+Md/BPbuJb//4Q+Bxx5b7egKBACvF0K5mMdoC1rTTinavteeoPMNyZQqHGvzDTilsk3sj3eTRCm3KJAoZNWFvRJoEaTRY0yxfW+1U4oFWtfP8vJyu3dhU3BHC6Rz5P1n2UAmZ8KvCGz6WR10g9DrtO95u0OUkkUe1+/tw0MnFvHYqSVcPhLuyLZDRufDRKktzEjEh3PLWczEVVyzq3vCzkucPq4vNh4AmnT6uMWrZibvAYAiFdv3Ypk8JqJZ0h422roD2VDIg+NzKcwnms+Vci+cS8fKNrdw3kwUkYckcNBNG5lcqSi1epHOYzau4j+PLUDgOVy2PYSRHg/yho09A34kVZ2IUhqpJDa6YDu/kgXHcbh6RwTDIQ+OTCcwE9OYKNUBxAoh5z1VQs4pPX4ZuuLFki8C7CvL47rpJnKphy98gVxsG9C01W2HtCUQAH7+54HBwdUZXHTbsOv7wh0Un06Ty9xc8Tr39MaHHyYiVgUkAMHPf754xec/D3zqU6unKwaD5O//8R8DF19Mtj12jLjGaCB9pdB51qpYN8227zmZhcbGCivlZPXGJt01QjOZUlTUa0SUKgadb2yhpSRvsLCf4cKJYzPHGCfovEyUKm/B100L8WwefQGZBVpfwNBogXPLGUxEM/AVogWWUhrmElsgWmCD6Raht3Td3h1cv7cPj51awkxcw5mlNPYNVhj0w2DUoPPOShktY6SHhiF2V9h5idOnUPkUec4RqJpx+rjb92ShuQO2e/reCzMJAMDuPr+zKG0F21owgc+9cDYKFer1LJw3E47j4JNFJFQdmZyBXj+ZoFYeYp7OmXhpPoVMzoRPFpDVTXhEHn/6c5fir394BqcX0xgMKbBsGynNwMmFFAYCSkMLtqkV8rnZ2euDLPA4Mp3A+ZXshj12Rv3QyXthr7zmdi2fwMdxJODd6wUGBipv84Y3kEs9fOELwGc+U3lqYioFjIwUt33Zy4i7q9zVlU7DTqWg+3zFbROJosg1P7/67370o8X//+AHwMc/Xn0fH3oIuPlm8v977yWtjJVaE4NB4P3vBw4cINvOzAAvvVQqcNF/xa279KBOp0aDzp328E12SmmOM6n1r4myjqDzRkQ9nySW3HajoKLAZDSDFwqiQEARkdYMzCXUhkUBsdCyq5e177kLcxzH4exSBknNAM9x6PHLHd2Cz9hYDo6E8fNXDGM2riKpGjAtGwLH4VUHBnD7oZGOEFU6kXKhFyAOzk6cXNgNmVLl+GQR14714okzUTx6apmJUoym6J53PKNhRmjYeaK7ws5LLPIqOfl021ibcfq42/caHdXt3K5QyTYt4PAkmTB25Y5IU/dVDTqBbymVc3ICGoUunM9Hs3hhOg6vLCLgaX7hvNkEFAFTK1k8OxmDbloY6/OTRfpCGj5ZwPE5IkYBpC1xOOxDQBERU3UEPFLJuNq8YcK0gJ09Pvzaq/bUvWBLqDoSqg6OI+Iubfk8v5Jt+nVhtI54QWTq8a8tCEcKTirqrOo4OI5kU/l8tfO43vIWcqmAoevIuKcZfvzjwAc+sNqllUqR8PmxseK2O3cCb3xjMZje7e7K5Yr5VwAJfD96tPo+vvrVRVHq/vuBX//1ytt5PCR76xd+gfz8yCPE3VVN7LrllmIbYyIBzM4WRa5AoKNELup0ajboXNtsp5ST4dT6TLPy4SD17U/ntu8BRBR408FhTMdU5A0L0zEVisTjitFIw6IAbak3y5xS7sKcZVlIFfKrEmoePX65o1vwGRuPwPM4tLMHfkXE1EoWEZ+EP7rtYghNRlNcCJQLvedXMphP5HDRUABhX2cJvd3olAKAm/b146mzUZxeTGM2rjpT4BmMeumclRyj5fQHZCfsfCGlOcHXnY7b6UMrrJFCxaBZpw/vEhGkJp1SEs8hqerQTQtJVUfEJ+LgSGtbufoDCkSeQ86wsJLJoy/QXID6wZEw3nLVdkzFslB1E3NxremF82ZybCaBH48vYzKaxbnlNPoCCvb0++FXRJxZSsMjkYlMPAcMBBVsjxDByLRsLKVySGkGrtwRccbVfvfIHE4upHDLZUMNPeapgiNqKOiBIgoYDnsg8hyyeRPRTB79Tb4ujNZAnU/UCVUN+vt4p4pSG0Wd0xUBAO98J7lUIp8vbd1717uAK6+s7OpKJoHdu4vbBgLAZZeVimJ6wbGmaaU5XGfPAt//fvV9/NrXiqLUAw+s3l+Ppyhgff7zwNveRq5//nngi1+sLnYdOkREOfpYVZXs9zraFalTijqf6oUKOJsddF5s32v9crCZ9j1VJ0JLI6KUXylOLjQte9W03VZjWjYO7ezBpdtDuHI00nRYMnVKlQeduwtzlm05U/6oCNXJLfiMjWcimgHHcfj5K7fj689MwbKBhFZ0ljNW4xZ6ARsrabImiGbyCPs6R+i1bRtJtRB03iWZUpQev4wrRsN4fiqBx04t4d0v39nuXWJ0GeyItoXhOA4jES/OLmcwG1e7RpRyO32OTMfhk0X4FWldTh/3IlVuoppEwxEPn4/BMMmid6zfh7NLmZYKPDzPYTCoYDahYT6pNS1KASQA89DOHuwbDOBlY70dOWXEDe33X0hqkEUeEZ8MTTfxg2PzsEFOBBRJwEjEg6GQpySwvnyRTsfVvvJAP+aSmtOKVy/TMSJK7ewjnxlR4LE94sX5lSymVrJMlGojmm46Af61WmepKJXOmcgbVtN5chcsctlJzo4dxSmDtbjzTnJxk88XBarBweL1r3418KUvrRa6qKDldnZZFsnwKhe5NA1YWipeBwCnTwNf/nL1ffyHfwB+9VfJ/3/0o2Lbpde7Olvrv/wXMpERACYmgH/6p2Lmlkvo6j2xBC08BI+0v77nqUBx+l57gs69GxF0LlLRxa5bLKJup0ZEMo8ogONI5Fs2byC4gQ4Dy7IxvpgGx3F45f4B7O5vvg2eOqXKg87dhTm3uKnqFnK62dEt+IyNRc2bWEiSoRb7BgPYHvFiOqZiMpphotQauIVeUeCcqdQkVNzuGKFX1U0YFtm3UBeKzq/cP4DnpxJ4YTqOi7YFwXNcx597MDqH7nvHMxpipIeIUtMxFdfsavfe1M/BkTB+/kri9NF0C7Px5i3yQNn0vQZPTN3hiF5JACSyyE5kdXzx4fGWhyMOhT2YTWhYSGq4bHtz92vbNk4tpMBxHG7a34+Lt3V2OLe7338k4sV8MucsvPyKiEzeQMAjoMcnYSTiLWmfW8s9t6vw80w8C9206p68SEWsHT3FnJ6dvT6cX8ni/EoWV+/snsEBWw06mcYrCTVbpDwS77hF42oeg8HumUK6JZFloK+PXNzs308u9fCud5ELQNoLy1sUafsgQJxa99xDfp9Mrha9RkeL27pD51WVXBYXi9f94i8W/z8+Dvz5n1fcvQ8CuP/9H4PyruvJFT/7GfDa1wLBIMRAAK+2LAif/zwRswIB4D3vAd7yFnhEAb5UHJc88iAwu7/odnNfIpFSh1kLaKZdrl7cBaC8YdUlfDUzDZDnOXhEMm1WzZsbKkrNxFVk8yYUkcfOXl/tG6yBE3Re5pSihbmZmIrjs0nwPAeB52BaNk7MJbGj19fRLfibCc/zuOaaa5BIJMDzW7/oMLmSAQAMBGQEFBG7+nyYjqlsXVIDt9DrFnvIUB0DcwmtI4Reur7xyYIznbOb2B7xIqAIePTUEg6fjyPkkTpywmHbsG0gmYSVzmBCDiGlGUS0+9o/g586Twpry8vksrREckff9KZ27/WmwUSpLQ7NlZrusrBzoGiRPzAUxDW7etaltjfrlCoPR3xhJoGcbsEjcbh8JISzy9mWhyPSXKn5RPMj3pfTecSyOkSeW1cld7Nw9/tnXBOU/AppnZN5HtNxFV5ZcLbzyiQIfy33XI9PQsgjIqkZmI6pdT0XlmVjJl4QpVwnHTt6u/eztJWod/IeQNyiPT4Z80kN8azORKmthqKQS39/5d9fcgm51MPb3kaEqPIMLvrzoUPFbbdvB+66a5XIZadSSCyuIBPsKQqmqRSQzQLZLLiFBUQA4Ny54n1dey0AIqD2Lkzjlr/5M+BvquzjH/1RUQw7e5ZkcpU7uujlta8Fbr2VbKuqwGOPFX9XcHfZgYDjOtwIp5Qo8BB4ksPYqCjV6P74ZCJKbXSu1PhiCgBxqay3TdAJOi9zSgGkMPebr9mLP7jvBSRUAx6JR96wMNbv65gpYZ2A1+vFk08+ifvvvx9eb3d0A6yHiWXi4qYFt7E+P35yOorzUTaEZS3cQu/JhRRsG47Q+9J8CmN9/o4Qemn7YCsHKG0mx2YSOD6bxEomj4Ai4tLhEHTT7rgJhy1DVYtCkmmSgTSU3/994MwZIBotCk3Ly4BhYGnXfvzpH/8LcroFReLxl5/5PAamz62+/9nZzXssHQATpbY4dALffELblKyFVmHbRYv8Tfv7cWBofZMcSqbvNeCUKg9HpPfT45MhCMKGhCO2YgLf+AJZOO/q8zkB7Z2Mu9/fK5OMqIBHLFS0yMJBEni8/dAoXphJ4PRiGgtJq6Z7juM47Orz4+hMAhPRTF2i1EJKQ86woIg8BlxterQqPhtXWStYG4llSCUxUocoBZAw9PmkhljmAsuVYjQGx5FsKo+nushFuewy4G9WK0eZnIHPfu8EAODt9PvhxhvJwjSdhhGL4elHHsHLLrkEIhXAbrwRABnAkfP4cOwVN+OyIA+O5nTRSypVmhO2sgK8+GL1feT5oig1PU3C7MsfMoBPSTJ+8ub3wfuWfyje77vfXV3suuoq4JWvJNuaZnHCIr2Uhc7LggDVMpEzTQC1P7PFjKvGjlteWQAyGx92fmqBOOrWuyYBXEHn1mpRCiAtR1fv7AHHAdft7sODxxewu9+3tU7qGA0xESVOqbF+sh6hhbO5pAZNNxsesHAhcXAkjI/cvA9/cN9RLKfzjtA7HPZ0jFjiTN7rwtY9WsTPFZ7TbN5CNJPD9oiv4yYcViSfXy0gyXLpgJn3vAc4daooRGVdYvDllwMvvFD8+TvfAU6cqPinrGwWEa/sTJl/+Kqb0X9pBpdftRdDe3eQNcjAAHDxxRv0YDuT7nvXMxqizy/DI/HQdAsLSa1rpiEspXJIqDokoTVOH7eruxGnVGk4YrEaOxAkYsVGhCMOhTywbRtnl9J4dnIFPT65YYfYqYIo1YqF82bg7vcPeMRV71Pa73/ljgjectUIJqKZou21xnOzq8+HozMJTC5ngItq7wtt3Rvt8Zbcb9hbdF3NxlWMdYEDbStCJ3JGaoScU+h2NBydwdgoaEi5IvLFFmOPB9izBwBg6zoW43HYt90GSKUCjSLyWBrdg3/9+P/Ap37hstWit2UREYhy4ADw0EOlbi63y+umm4rb2vbqgHqNFD0kPQ9e4IutzSsrwIMPVn+Qd91VFKWiUeDgwdLfK0pRoLrzTsg3/SJU3UQ+owIf+c1SkYv+PxAgQfZXX+04pfypOBAQV+eaVYG2+9Gg9I1AzZvOEIz9g+svQjlB52blHLEzSyTQ+uqdEbzx4Db8bGIF0QyZDNutTgpG8+imhZmCU5s6pcJeCT0+CbGsjumYin0teF9uZfoDHhwcCUPTTfzcldvxzcMz6PVLuGhbZ6yVaftet4WcA6VF/Lxp4vRiBvPJHIZCHgg8v7kTDk2THMuoeORuiwuHgd/6reK2111HxKNUavX9HDxYKkodOQIcP166jSQRAal8gvLv/R4Rrfr7gf5+WL19+KsjK3gmyWPnaB8ChTVCwCPi+Q/8Nk4vpnHFaASffPMlnSnabQJMlNri0LDzM0sZzHTRiE5ajRzr89edA7QWJe17DThcysWSXX0+bI944CmEsG5EOOLUSgZHZxKIpvOYiqkIecSG+rF108LZZVJN6xZRyt3vv08JrJkZRUPM62VXH6kknl9RYdt2yX1X4nzhpGNHWV4Ix3HY0evDi7NJnF/JMlGqTdQ7eY9C2/wuuAl8jE2HilLNuBWIkEX0I80wVx+neL60uhIKATffXN+dHzhAJhG60XXMTC/iXx54Ed5wEK+i1w8MAP/8z5UnLKZSwDXXFO9D00g+WCpFqswAyfnK5cjiPx53pgoasTjwla9U38f3vhfG//ln5AwLgp5H79gIuV6WV09NvOUW4O67i7f9kz/BNSt59Gk8AuPDwP6R4rZDQ6VTIdfBmaU0LJtMfu1pQah0taBzyrnCcXzvgB8eScBIIdT63HIGV+2IrPvvbwWy2SwuvfRSZLNZjI+PIxxuv9tlo5iJqTAsG0GPiD7X+29nrw+xbALnVzJMlKrB2SXSgXHFaAQ3XzyIpydWkFQNTEYz2DfY/vVyUqNOqe4TpdxF/AAnwCupUHULk9Es9gwE1l/EP3OmVFxaXgaiUdhLS4iHenH+v/zXYqF6xw5gbq7y/Vx2WakolckUBSmed0Qk9PWVZlQCZLqvaZLj5MAA2S4YJE7rcj74wZIfJ5bSeO65F9E3IEM3LZxfySLkkTAYUsBx3OaKdh0KE6UuAEZ7CqJUTMXLxtq9N/VBcxtaJaq42/caEbnKxRKB5yEUTgzWCthuFhKqfhpJVYcs8uj3y/DJYkP92JPRDHTTRsgrYijUHVPi3P3+jWRG1cP2sBeKyEPVTSymSNVmLWglvFKILRWlpmIsv6FdxLMNtu8xpxRjk6CT85QmWns5joMiEldzTreAjY4/kySo/hASA8PwhV1/LBwuDXVfi507yYkBQESpdLrUrdXXB3mafGfnRBn49Kcru7rSaeDSS518KyXn+n6lLRXRaPE69zRGXQf+7M9wBYArKu3jm98MfPe7xZ/7+gBBIP8OD5N8sOFhcrnssuIExgoUHcitOWGQqFPKWu2UyhlFV9bufvL39vT7C6JUmolSBWzbxuTkpPP/rQxt3dvV5yspru3s8+HIdAKTLFeqJmcKQu+eAT84jsP+wSCenYxhfCHdEaIUFWy60SlVXsTf3R/AifkkltN5RHw5yIKwuoj/wx8C8/OlbqalJXIZGystZNx0E9m2DA5AZvse/MWBtzmh6r8fisAzN0cm9VKRibbElRcp/v3fSfGjv58c/9YamLCO0HG3aDcZzWAlo2MloyOayWN3v39DOm+6DSZKXQBQdxQNb+50dNNyKoT7W7T445t0Sm2kWFKOO1R9tMeLxVQeOcPCYEhsqB/75Dxxme0fDNZ0BXUSpN9/P+47PF13ZlQ98DznCLMTy5k1RSlNN7GUJgHz5U4poChUUTcVY/Ohjqd6RakIc0oxNomc0bxTit5O0y3HcbXR0PylRvObKiLL5ASgt7fkamX+LABA8/iBP/iDNe9CpTmKvX1EbKrk1EomiZBEMU3gIx/B7NQiludXMMTlMcS5buuesGgYpKUDICc9L71UugNvelOJKHXbe94D0eMhofDBIF5uirhc9mLb6ABw0/Wlj+dLXyJ5WoUQeeffYJCc6ARWr2XWckpNrWRh2eT7i7o9dw/48dj4Ms4uZdZ8HhlbEyo6VZsyfH4lW5cb/ELFsmycW6LuQ/J53D8YIKLUYhqdMOMskaXte11yem7bxBnr8ThF/P6vfxX7jCQCiRVwy8uQ4ysIZxKIZBNIju3D2C8/Xrz9e99b3dHknn4LEJGKZj729yPuC+GZtIBFJQhjZBRj/X6oeRNHpxP4/d/5G/zabVfg4K6+inddwmWXNf3wG4GKdilNx0oh45TniFh1bCaBHp8MWSSinWXZDcWUbBW65F3PWA+jhbH28wkNhml1/JjRieWi02cw2BqnT7NB58DGiSXluPuxVd0AUnlkC5PoGrF2Fl1m3Wf/PDgSxqXDoZZ/Ge/q8+PMUgaTK1lct6f6QWo6loVtA71+CQFl9dfj9ogHPAckVQOJrI5wncJIJ9HNBzvDtJAsVJEazZRKakZXfP8xuhfqlPJIzb3HPKIAQHfErY0m2+Sku0agrrGcUTk3yQ11SvlkgQg8PT3kshYeD/CFL2DizDK+c2QOB0dCeO91uypvy/Nk8mEqRSrys7PkhIj+e/XVxW11HVJhaiJWVsABcOStIwBQ9hr91m+RSUyVeOUryfRDyg03AJqGMcWLX8oL4IMB4F+3EyHrwAHgQx/CmcLJ83Xnngf36DwQDGK3x4dQbAlJ1YdEJoewvzuc0Iz1Y9u2I0rRSALKcMgDWeCg6VZdbvALlbmkBlU3oYi8M5l8b6HdcS6hIaXpCLa5ba7t7XuqSlyp2bLC6z33kO/J8iDwpSXg5S8HHnvMKeKPvv/vEYkvV7z7YH9P6Xrz+uvJfdJ2ONoSNzBQWnwAgCefdP5rWTa+8L3jpItlkER+CCD5TKSID3zjhQVcuqO3Y9a3VLR7fHzZGea0fzCAc8sZxLM6zi6nsbPXh7PLafzLU5M4vZh2pvM1EuHSzTBR6gKgxyfBK5GA7oVUzvkybpaNPql1ptu00OkjCC5RqomT0o0SS9y4rZ30YadzBgzLgsjzdVk7E1kdC8kcOA5dmy3QaGZUPYwVFnGT0bUrzDTkfEfPapcUACiigG0hD2YTGqZiWYR93XWAODaTcMTVbjzYxQshoJLAwV/nibRfFiALHPKmjbiqoz/ATuQYjVHvMW+9TimlIGZRcWujUVvplKoCLQLl6xClqEjWzPPnk4s5j1Xh+dLWv7UQRTzwD/+A1157LaRcDkdPTOP5E1PYKVl49XZPqQPLskiboHtiovv/wbK2oCNHgGwWXgDObKVHC//edBPwoQ85bvEb/+R3gGXiGFAA/GFhM5vjSECv60QN73sfEI+vzuAKBoGRETJVkXLyJHk+aNi8z7d220oDdHPho1NZTOUcQWV7uHQNz/Mk7/LMUgaT0WzLRamt8nqeXSLnFrv7i/sfUESMRDyYiWs4vZjG1TtriOAbiGFaSOfI91dL2vd0vTTsW5aJIE754AeBmZlSkakgRgk33AB84hPFbf/mb4goVQmXo+ngSBjRt92Ow9PLmJaCiHlDSAUjWJQC8G4fwi2vuRzXum97331NPTR3Ed8GcHYxDUnksLPX37H5TDzP4farR/DDlxaRzhkYjpAA+JGIF2rehF8WoYgC/vTbx+EReVy8LQR/WHTcX/VGuHQzTJS6AOA4DiM9XpxeTGMmpq5LlNqMk1rq9GlV6x4AcDYZtaqbFhZTGiyr8ZGkGyGWuCntxxbgkwVk8yYWEhpGenx1harT525Hj89ZpDNIKx7HASsZHUlNr1qFollRlVr3KDv7fJhNaDi/ku2qgwPJKxvHSiZP2lALo2i76WDn5El5pboFa47jEPHJWEzlEM/mmSjFaIhGjnm5dTulqCi1uU4p3wY6pRxRyqz9mNazP/Q22bVEqUbgOKgDA6S1Q5LwtD6I8dAB7L58GNjfX7otzwNf/3rl+7Ft0jbo5j//E0inEZ1bxg+fPYeIqeH1oz4iZO3YUZInhYsvBpZ7nXZEO50GZ1ngbHu1iPTII9VbYQ4eLBWl3vIWIky5Hi/8fiJSXXwxyXqhfPKTwMJCqchFxay+PuCNb3Q2PXFsAv/vxUWcSJrQTHRd4aNTmSiIlOVTgSk7C6LU+ZUsXr67d9Xvm6XbC1luziwSUWpv2Tp+32AQM3EN420WpdI58j0h8FhddLMsIBYrFZCWl4FIBLjjjuJ2N98MTE0RISoeL72PG28EHne1zj3wABGlyhHF1cHdH/oQadNz5zP19ZF/BwdLNu370v9Gj2Uj4hIy55MavnNkDt+Kc9iR1NYtnLqL+NOxLKKFdrhen4yAR+rYfCaO43DRthBmYllw4DCxnIEi8bh+bz/ecHAIX3xoHDndhCLwmIhmMNbnR8grNRTh0s2ws9YLhJFIQZSKZwFUP2CtVRHZjJPajXD6HJtJ4GvPTOHZyRhMy8ZKJo8fjy933EG1PFR9JOLF+GIa80kNQyGlrlD1ky0OYt0qeCTicJpLaDgfrSwm2bbtnAhUc0oBRLB66uxKV+VKufPKqNUZcFudu+Ngl1BpnlRjk696fBIWUzkWds5oiEaPeVRMUsTmM6WA+lrdWgFtl9vI9j1ZIPddj1NKXYcoRd1eLROlXOSNYs5lw8dWjiMjw93cdBMAwEhqeDY8joAi4PVvvtT59fmFlJMnJT72o5ITxJNzCXz1RyexTTBw1yvLAnv/1/8irTCVsrjKW2ECAdIumEoR4cy2i0H1fWUt7t/4BhmZXonRKHFi4wAAWoFJREFUUXISDPJ58b315/GHZ47B4jjkPT7kFC/Sshe6L4Dkvp0IPfiD4m3//u+J+6Lc1RUKkctVV9V6di8YquVJUUiu1BLO13CDu6nlgNoKhSwKeazkOdwzUPoc7h8K4NFTSzi9mN68TK5MZpXAZE/O4pbD4zC2bQP31suL2+7aBUxPE2GqnBtuKBWlTp0i21I4rigelbtEP/1p8rl3C02FaXKmYQD331/c9o//uKGHV17E393vx6n5FE4upPHvT0/hrtfsXVeUAi3iL6ZUzCdyzvVzSQ37PdKGTEZvBU+eiaLXL+OtV2/HRUPBks/eRDQDnudw2fYQFlN5aLqFl+ZTGO3xYnvE25Hur1bTWa8WY8MY7SmEnceqh52vVRG5dDi0KSe11OkzEvG2xOlDD6rRTA6yyEPkOUR8UkceVFeHqnugSBzSmonnphLY0+9fM1TdsmycXiyGnDNK2dXnw1xCw0Q0U/E1j2V1pHMmBB4YjlSv4lDBajaudk1GkdvqzHHATKGytH8wAK8sds3BLpYholKPvzFrOx3fHsuwsHNGfZQLubZtk26nNY55mtO+16RTqiCsbJZTSi1kFm6kq7aRTCmaoehtYn+okEUfUyuZiGZgWDbCXgkDLcq5BACBrxx0frYggO3u9686QR7rD8DweDFlA4lwP0qOZG99a/1//JlnyL+2TVp23FMRy/m93yPiUSWxq5+4xujn5QMqOfHnbRseNQOPmnH2MZGOwbLs4hrmy18Gnnqq8v4Fg6T1sQYcx+GSSy5BOp3e0gHf5wpi01h/ZVFqRy9Z4y+l88jkDPgrZGK6qeWAKv/+A8hz3W2FLMpMXEXOsOCVBAyHS9d3u3p9kAUOKc3AfFLDcLiJbhLbBp57jghM5blLy8vA/v3An/95cfuBgVUZdD0AXgdg/rKrAfy34i8sqyhIhULF3KX+fuDyy0vuA1/5ChHBaT5TTw+ZNlqJeqestgCO43DHNaP4wkPjmEtoeOjEAt54cLjp+xvr82NXrw8PHl+AXxHR65cRy+qIZ3WoeaPlk9FbwUJSw9nlDHgOuGFP/6pMWur+Guv3YyjkwXRMxWIq53R2dKr7q5UwUeoCgbbszScrh53Xqojcdvk2HJ1JQJF4zBa+3G2bBD+38qR2vCCqHBhav6jiPqjuHwggno0DAIIeCf0BpSMPquWh6hw45A0LAUXAb7x675oC2lQsC00nB10qQjKKjPX58dTZlapjk6lLajjshbSG0NQfkJ2Mtvmk5gwS6GTcVue5hIaZOJlyNRnN4uLhYNcc7GimVMTbmFOKOqvizCnFqBO3kBvL5HFmOYNtIU+hFbhyZgXNgmreKbXJmVL65rXvNRR0vo5MqbxpQzetNb/DG+WUy4HcSuFDKrTfmVaZKOVMCFt9QuWRBIxEvJiOqTi73IJ2I9q25/cDQ0OVt/ngB2veDf28fP5zX0cPl0d0bgXeXAY7ZQuKmoWdTCGdN3C7e434jncQN1Qlscvveuy2TQLq9+xZ9Xd9Ph+OHDmC+++/Hz5f5x+LmyGezSOe1cFzRfGpHJ9MBgMtpnI4v5LFJcOhqvdXa73/66/ag6Sm42fnVsADODIdR96wsbvfh4Ggp2Mze9bidCFPas/AaqFXFHjs7vfj5EIapxdSRVHKtoFvfrOYybS0VPr/q68G/umfyLYcRwYalAeEU66/vvTn/n6SxeRyKC0rAYxbXoiXXYJt7m0feYQ4G/v7V7suy7n55vqekDYQ9Eh426ER/N+nzuOx8WXsGwyA57imsso4DvArAkSBh6abGAp5YFoWohkdLxTCz1s1Gb1VPHkmCgC4dHuo4pCk0ggXEbv6/BgOeyCLtODSme6vVrJ1HxmjhIhPcjKKyk+kyysi2byJubgK1TCh6Saen4rjpfkk1LyJoKc0yyWh6rhoW2tOat1On1a0n5W4Q3gOHEeOMQLPdfRB1R2qnlR1fPO5GeQMq+ZIexoQv38o0FFfxJ0CnVhDRFVz1YkjbcdbK08KIBWfnb1enFxI4/xKtitEKXqwm4llMZ8kVmeOIxPpYhkdksB3xcGOfgYiDU49pCPVYzU+QwwGhQq5nI+4FGwbTiu1LAoVj3k5fX1OKfqdtNmZUs0Gs9dDM0HnzbQTeiTeOcZn8ybC3haKUvNUlGqtA1ksDGAxLNtxEOUME9OFbMPd/ZXXJXv6/ZiOqTi3nGlrBo6bYuFDxJJm4xT8gOLHXEjBzj0+mBbJRbrFvUb82Mdq33E0CrznPcTZ9eKLwLZttW+zxaCFtO0R75qC964+HxZTOUxGM1VFqUqt/ClNL+QZ2XhhJoE/+uZR7Oz1YTGZQ9AjOmv+mbiK/oACjuO6o5BlWUAiAeTzOLtUaN3r9wGf/WxRXCpc3jW3AESjWLryZcBPHia35zjg/e8nrXaVkMuKYwcPAppWmrdEL7vLWm1PniSTQ13nU88cm8Ojp5Zx476y9tn9+9fzLHQUl20P49pdPXjg+AL+y78fQcgjQjfthrPKnjwbRVIzcdWOCAIekXQuWOQ44/dJ+PVX7+mYLhiACErPnY8BAK6vMgG8PMKF4zhHkLJtuyPdX62ms89AGC2D4zhsD3tw+Hwcj55cwvV7+xxVmoo3PT4Jp5fSTosMxSMJyOYMiAIHj8wj7JGgSAJimTzSORMvzScxEvGu+6R2Jq4imzfhkfg1M33qxe0OATiM9nhhmLZTQe3kg6q7H5vnOfzbz6bwk9NR3Livv+oJxCmWJ7UmEZ+MsFdCQtUxtaKuyiyjIec7a4hSABGuTi6kMb2iAns3ZHdbylifH71+GT85vYyQR8JIpNDGF9cwuZKBXxZwxWhPxx/sYtnmMqWos4plSjHqJegRIYs8Ts6nYFpwBI+ZuIrd/YGKVUvNWJ9Typm+Z2xW+94mBp1vsCjFcRx8koBMnhTTwq2YXgXynbOUzoPnVgckrxfRNRXYsGzIPIfz0ayTJ9VTRXzfPeDHY+PLTs5VJ+Cu8s8nNOf6+WQOosAh5JGbWyOGQkRAWFkB7rqLTOvawm16lZgotO7Rwlo1dvX58PREbM28y9JWfg6zcRXTrlgPWeCRUA34ZAERH+kq6AvIOLOURt6wEc2QYSFtcW2oKnEXLS4CigJccQW53rLIe6O8ZW55GTBNWLfdhslf/ywAYO9gEPizP1slNFH/Gbe8XOq0fMMbANMkwhJtm6P/joyU7t9Pf1r/Y/GudrwlVXIuUm0Qz1Zhd78fpxaSSGkGeM6Li7aFGsoqm09o+P7ReQDAe1+xE6/Y3ecU8b/1/CxU3URK7azzusPnY8ibNoZCCnZXacFdHeHihVcmLsa5hIpev9xx7q9Ww0SpC4RjMwk8cSaKF2eTODGXxA9enHdU6Wgmh+lYFjzHASCOIjLBQIQi8pAEcuAaDnsxl9Cwq4/YXweDCsYX00hkdbw4m8CN+wbWdVJL86T2DrTG6VNuhSzvE+8WK+TB7WEMBhexmMrhyTNRvPbiwVXbZHIGZuJkYbGP5UlVZazPhyPTCZxfyZSIUoZpYa7Q0rajjtZHKlx1S9j55EoWhmVDEQXYhRMeReQxE1exlMrD27t2XlknYNs2EoX2vWona9WgGVRJTYdp2U6WC2Nrs55R5mRbIJrJoc8vY3d/AOOLaSyn89gWqpxZoenrcx45Qeeb0L5n23ZRBNpIp5RAp+/VfkzaOtsJfTIRpTK51p2Q0EiBHb2+lgfCS67peYZlQQa/Zp4UZazPD44DltN5JLJ6xVaQzYZW+Z+diCGdM8DzHIbDHszGNUytqJAErbk1oiSR7KlrryWtVF/7GvCudzm/zmazuPbaa5FOp/Ga17wG4XDnuCNaRa2Qc8rOXvL76Vj1vEt3sdYwLcwlyLqxxycV1swCllM5fODG3fj2kVkcnU4goIgYCnkwtaJiPqGhzy+t37Vh2yQzzJ3BFAo5QwBgmsDttxdFqMXF0ryz224Dvvc98n+eB/71XyvnoQHIJVLQTRsBRcBgUAF+/dfJbVxOJruvD39/IolFJYQ7o5niOvq++5p7fE1A1zehFgnqnYhl2fjOC7MIKBJ4jkM6ZyKh5tHrV+rKKtNNC/c+fR6GZePibUFcv6cPHOcKVec4/PvTU3jybBQ37e9vaRs33f9G1xS2beOps6R1j+5vNcojXBaSJO/titEIbj800lHur42gs8/GGS2B9o/PJVTIIk8qIF4Zz5+P4+lzK+j1y1DzFmSRx1BIxmjEC48raDStGfDKIn7uimHcd3imRMHdHvYims5BEgXkDBPH55JNf2ho+1mrLPKVrJCUbrJC8jyH1108iHufnsKPx5dx/d6+VSc9ZGoIsC3kaVmFeCuysyBKledKzSU0GJYNvyyg11/bhUNb9qKZPNI5A4EaoaLtZC6h4p+fnEDII+EXrhyGpls4vUTCTQOKCJHnMBLx1KzCtpukZsC0AJ5rvJJIH6dhEWGrntd4K7EecaZbWe8o82OzCXglcpImCTwkgUfIIyCa0fH8VBwHhoKrhFyaBdV00Dlt39sEp5Ru2jAKWUYbOX2PPhf1OaUKwetSc9+nJCA939IJfKcXiUh0UYtb9wBybOc5wLKLYedr5UlRWp4r1QJolf+nZ6NIajpGCtOiNN3EueUMPJKAy0cay+90vrd6d2HnRz+Ons9/Gvjwh4HXvtYZQ2/bNk4UJgPatr3W3XUlaiFyA6jtlOoPyE5Mx1xCqxhF4C7WxrN5mBbJ5tk/FADAFdb7AsJeqcS1MRhSwHHk+HlsJontEW/x+8+2K06Tw/IycRO94x3kj5smXvuRj0D80IfI74wy8fhNbypOfBME4Ic/JPlibhSFOJXKJ0T+2Z8RAZMKTX19znZPnEsAJxaxZ6BwHvCXf7nqeeEA9PmmMTEZw/hCui3F3aRWEKU6vFC+HqhTb6zPj7iax2xcw7nlDAzTxkBQqRmr8v1j81gotJXecc3oKoHn8pEwfnBsHglVx5GpOK4dqz5tvpx6plE2s6agxSxF5HHVzkjN/XBHuFxIazaAiVJbHnf/+MXbgjgynYRmWIhmckhpOuKqjrxhYlefD5puYu9AdfHmlku3YaTHt0rBvfniIQQ8IpbTeXz1Z+dxx6FRXL0j0tAHStNNJ2h6/2BrLPJbyQp5+UgYD7+0iKVUDk+ejeK1F5W6pU6y1r26oALkZDRbMgVoypUnVU+QrVcWnFDRqRqhopuN+8Bq2Ta+f3QOmm5hrM+HD960GwLHOb8PKAK+f2weM3EyDeVtV4+2e/erQvOkwl6p4c8sx3Ho8UlYSucRy+YvKFFqveJMN7LeUebL6Ry+cXgGvX4Zv3zDGGbi5Bhi2URcCXtF/OL1u1bdR64gJnVD0Dlt3eO54oS8jUAuTH7K1SG0rad9D3BN4GtRJpdlA2cKIlF5u3erkAQeOcOCadl15UlROjFXaiTixa4+P3HlSgImljPwiAIOjoShiAKemYzh0u1hXLSt9gl/+feWb99t+MzYfdg2cQr4rd8ijqkLgPMrWdg2EZyCNYoxHMdhV58PJ+ZSOL+SrShK0WLt81NxpDUdAFcYhMQV1/sjYYzlEuBjK/hDzxyeeXEcmZl5vGx5Gf5kDKlde3Hd5/+YfP/pOnE4adqqvwUAeOMbi6KUIMC7vAzOHQbu8xWFpH37Sm/7v/83aXMbHCxegsHK7Zsf/WjV5+Xs0iwA8plZi/2DATw7GcP4YhpvWnPL1mPbNpIXgFPK7dTzK16kNAMpzcBENIuFpIbhiBc5vRir4l7PLqY0PHF6GRzH4e3XjFYsBgs8hxv39eH+o/P48fgyrtnVU9eavtY6aT1rCuqSunasp+61gTvC5UKCiVJbHHf/OKn4ctBNGwvJHAAOgyEFPlnEB28cW+WCqiTeVFNwAeCbz83gmckY/v6xs+A40lJW70kQXfAPBGRnfHsr2CpWSJ7n8NqLBvC1Z6bx+Pgyrt9TdEvZdjEgfv8GVHO3EttCHigiOQlYSBVH/9I2vHrypCg7en0dJ0q5D6zZvInFlAavJOBlu3rx/uvHHCuz+2D381fy+LtHz+LpiRhesaevuXHImwCdnNdoyDkl7JOxlM7XHBiwlVivOOOmW9xWlYJ8AdQ9ylw3LfzbT88jZ1jY3e/DB28kAbX0sT/y0gIWkjnMxErHedu27UyYazroXKpfwFkvWb3gSpKFlk6UK6feTCnLsh0xrllRit6uVU6pZQ3IiRaCHmnDJtrSVmLDtHA+mquZJ0XpxFypn5xZRsQn453X7sDrLh50vit29frw9WencWQ6gX/96SR+5abd2NHjq/p9Uu1767+/+w/wmc/9GoSvfx34j/8A3v52WK7JhRPRDK4IhTvye6lZinlS9Tn6d/QSUWoymsWNbo3HNIGnngK/tIRfPXUeDz/+IoToMobyaYyaGZwbuxT/dMsHyHr/iiHwOwYAALsLFzcn1RsQChTW6ZJEAr81jQR3UxcTFZoOHSq57VOf/CRe8frXQ9q2jWy31sTEO++s6zGvhW5azvqu1kn+3oLwPJfQkNL0miJgK8kZFvIFt+RWzpQqj1W5eFsQi6kcZuMqVN3CyfkUeB5IaXrJejaTM7CQ1OBXRNx+9eiaHTUvG+vFwydI5MmphXRNEbzWOum3XrcP33xupqk1xUomj5cKgzKu21054JxRhIlSW5zysO+IT8JSKo+AImK0xwu/ImJiOYNtYW/d4k01Bff2QyNYTGl47NQScoaJvf0BjPX76zoJonlSGyGqbBUr5JWjEfzwpUUspfN46mwUrym4pcgB1IAscBjr8BasdsPzHHb0+nB6MY2J5awjwNCQ82rjliuxs9eHZyfXDhXdTNwH1sGQglg2Dw4ckpqB2YSKM0vpip+9XX1+XDEaxgvTCXzvhTn8yk27N/QktVmaDTmn9BZypcoHOWxV1ivOuOkmt5W7EKPpJhaSOXgkHoNBTyHnZu32gPuPzmE2ocEvC3jXy3Y6zw3ddjCk4IsPn8YLMwm8NqlhKOQBQE4qaPdQ05lSBQFnozOlLMvGqfkUoukcRMFT4hptNdSFlashSrndTb4mnz/HKZVvTabUvMoBQTLRdqO+E2nYuW7ZdeVJUTotV0rNm3hmgkyXevWBgVWfrXdcuwOabuLkQhp/+cApeCQeswlt1ffJpcOhqt9b9rXX4Ju3vg+vOfoYereP4PhMAv/2xCnnb3zm+6dwya54R34vNctkQZQa6/ORQO98nog/APn/V79abJWLRvHymXmMTcwgmE7AfvOt4P72b8m2luXkNY0AeH/Z38nnTVzxy671fm8vaaFzT5IbGMCLeRlHe0bBjy/jndfuIDc+fhzo6VlbYCqwcumlwFVXETGrjI0ofExGSZ5myCuiP7D22iGgiBiJeDAT13B6cXPbYqlLyisJjpC/FakUqzIU8qA/IGM2ruLUQgo9Phn/8uQkzseyUEQy+Cql6RB4HumcgWcmV3Bspr/qZ9wjCXj57l78eHwZPx5fWlOUKl8n5QwTSU2HYVrwyQJOL6Zx97deREzNQxYEPD8Vh2nZCHsl7O73QxT4NdcUT52NwrZJF8tAUGnpc7kVYaLUFqdcld7V68dw2Fuo5JL+cRr2vWcgsC7xxraBxWQOXpmHIvJYzuQhizxGe71rngTZto3xFudJlbMVrJA8z+E1Fw/i689MO9lSiig4Qax7BwMVgy0ZpYz1EVFqMprB9Xv7kM4ZWMno4LhiVlQ9UAFrOqbWPKnbaJeJ+8C6Z8CP8cU01Dw5qB7aFsF0TF1TgHjjZdtwfDaJM0sZnJhL4dLtm+f8qve5cZxSTVrbqZgVu0CcUm5xxrRszCZUiDycqUu1xBlKK91WQOs+C9XuJ6UZSKo6MjkDCdcEnvmEhpEeL3p9csnUVff9zCc0PHkmCo7j8I5rd1TM5xsOe3FwJIRjM0k8dGIB771uF4CikCTwgNjkZ7volLI2TCiiAuPz5+OYjqnwewT82feOb9iJPD3B0k17zcdE3U2KyDf9uP2FLMz1OqUsy8a55QxeigFhSXccFBsBDTs3TKuuPClKp+VK/WxiBTnDwraQp2Kro8BzeM91u3DP/Sfw2KkYDMvCVaMRDIe9Jd8nt189ghdnkpAFHueWM8jmTYg8B58iwCcLeOiOX8P3fv6X8e7QGO57eByLK0nnb4S8UtPfS22B5jDxPLCjIPBoGslHWl6GtbSEW06ehy8Zx0AuBaxEgXe+kwhRAGlj++VfLrlLP4rOJn38NJxvMEkCrr4aUBQsKgGcFwLg+/ux6+JdyAYj6D+wD5988yXFz97ycsU2udBKFkd+dAbCdBxvuGwb+Y4sn0LXBPUWPho9fpxdKqyP++sTlvcNBjET1zC+iaKUZdk4PpdANJ3DtvDGFgnaTfVYFQuabuHgSBhXjobxvaPzWMnkEfZKmI6pSGkmFJHHoeEwpuNazYLajXv78ZPTyzizlMFMXC20qK6muE7yYDauYiZe2oZqWDYmCy20ER/nvIdiWR2Z2QT2DgTgk8WKk9zzhuUI9dfvZS6pemCi1BanXJXmeQ4evtj2VR72vR7xZiKawemlNC7ZFkYqp2NqRcVsQkM6Z2D3gL/qSdByOo9YVofIcxjrZ06ftbiq4JZaTufx1NkVvPrAAE4VrKEblXmx1aA2+MmCw4nmSQ0ElIYcDkPBYivgUjrnOCbK2ajFlht6YA15RByfTULVLQg8EXm9slhTgOjxy7hpfz9+dHIJ9x+dqyubrBXiQiMOHNp212x7b8gjIqnqOD6bxNmldNvdkhstVFKXbJbXcWpRg1FoDYhnDewb9MMrCxUXUuX7uNq1YFd1W21UUGg51e7n+j19eGE6joVkDrLIQxZ5RLwSsnkTOcPCueUsznNZ+BURAUVY1R4wn9AQ8Ih4+zWja1ZXX3/JEF6cTeLYTBKzcRXbI14nnFwRm2+H87gq5DnDqtjGtp73jVtg9MkCgh4RflnY0BN5d9U/b1rO+qMcmnHV7OQ9oOhQW48oRd8TJ+aSOB7j4dXi6D0842QjtRrqlMrk6s+TotBcqbNL7c2VMkwLT5xeBgC88kB/1fe/WPiOsG0bflnEVFyFRxagmxY8Io/jc0mcWkghkzMQ9Egl95OkIrJtI63p+O8PnkLesLDLW2zf8ysieiO+hlygLSOXI1PklpaIoNPTU2xdy2SAX/u11SHgaqEF+M47i0KTKAL33AMA4LG6dQ7Ly8X/SxKZUOf1lkyS+8Gcjineh5teexUucd/28GGkcwb+5gcvIW/aeP/1u9A3HELF0+Uqr+GOXh929/twbjmLJ88s440Hhxt6mipRb+GjmeMHdR/uqUPoBYgr8tFTS4XhQfaGu8bpYzo8GcNsXEPQI25okaATqBWr4pMFPHFmBYrAI6tbzmd/Z68PXkXCcJirWVAL+yRcORrBc1NxPD6+hHe9bGfF7VKaAU03Ma+bWCm46P2KAFngIQocBHCYTWpkIFCPB2GvDMsCzi2noeoWXppPoc8vQxFXT3I/Mh2Hqpvo9Us4wKai1wUTpbY4mxn27W4VDHhESAKHyWgWSc3AsZkERsoC7CjjhZDuXX2+pgNiLxR4nsNrLhrEfzw7jR+fWkSvT8KzkysQeJ6JUnWyo9cLniPOm0RWLwk5bwSe5zDa48WZpQymVrIVRalWL7aqnZBG03nMxlXYNgk7lQQO+wYD8BeCIOsRIF59YADPTsYQzeTx5NkoXjEWqbptK4S2Rh04sYJTqlbWSrX9/befnsezkzFwHHB6Kb2h7WebJc7Qv3VuOYPJNHBuOYN9QyRTJW9YWEprmE+SMGWvzEM3bKRzBo7NJjEcUhyXbDXcVcRYNo+ZuIqcbiHoERHxyejzy87iMJs3Nywo1M3q++GxlNLw4PEFPPDiAi7bHkLYKyJnWDg4HIRXkWDbNhZTOczEsohm8uA44CtPTODscgY5nbg7Ytk8RIFHNmfi6YkYbtibqLo/QyEPrhgJ48h0Ag+dWMD7rx9znFLN5kkBgCjwTu6jppurRKn1vG/KBcaFpAaO4+BTROzu92/YibzomjCXM6yqwj9t31uPKOVXaPtedVGq3u8kWeDg4YGwR8JL8yl88eHxDRHtaM7f2eV03XlSlD0DgY7IlToynUBSMxDyirhijednIprBuWgGV+yI4PxKFjndwrGZotOJ54h7n+c5eGUefX4FfkWEYdnI5g1kcybiWR22DcRTKj7w02/iDU98C1+PDMICyQ/yNOACrYppArFYSVsclpeBnTuBW24h2yST5P/Ly0SIKp8S9+53A//2b+T/igLcey9QYTqgLcvgLFdrqygCH/844Pdj3PLg6bSAgd0juOWVlxZb6dzcd9+q+9SPzOLsmSiGwn2lohSAx8eXkDdtjPZ4cXEdgfOVeOX+AZxbnsRPz63gNRcNNt2uDNTfZm7bNv7nI6cbOn7kjOIApXrfB7t6fZAF4rhdSBLn0kbh/r5RRFIkCHnF7nL7NclasSpHpuKwbeCS7WFk8wZm4yoZLhQi7W/1rGcB4Kb9/XhuKo4XphN4w2X5itEPksBhOZ2DaZECyu4+H/qDxdc8rRngeFKEnlzJYluIFJ0u2x7CRDSLpVQOZ5bS2D8YwGChPY+sydL45uEZJFUdbzw4tGWdb62GiVIXAJsV9l3eKtgf8CDokXB2iXzpnFnKkLaGwmeTLg5/eHIRSVVnokqdXL0jgq89PYXHxpfx8EtLSGsGPBKPv/3RmS1dXWkViihge6HtYSKawVQhsHhHE0G2O3p9OLOUwfmV7KrRs61ebFU7IT20swePn15CJmdCFnlsjyjY2euDwBdPjtW8WVOA8EgC3nDZEP7j2Rk8dHwBQZlfJXQArRHaSnJDBvzImzZ4rnrekW2TUdQAEPY25pSi+7uUIu4ZSeAQ8Wxcm8dGTnGp9rfG51OYW+Txs+++hL2DAYz2+jCxnIYk8Mjk8tjTH8K2sBd508LpxTTSGhGmrhyNYGePr+qJelLVsZLJI5rJIacXT6gSKmmNs2wyMewrT5zDmcUMcoaJ4bCvpUGhbso/UwlVx0vzGfLeF3ikNR05w8If//yl+OcnJjEd1zAc5uCVBfhlEQFFhE8muSE/PbeClUweO3q8WErnoOYteCUBl20P4vzK2u2uAHDzJUN4YSaBE3MpTK1kHaeUZ52FFUXkoZumc3/u17re902l19PdzqmbxeqzKHANtXM2im0TwSmtGRhfSOHQzp5Vz6ll2RhfJBlXPT6p6fYVKmhlqmRK1f2dNBjAmaU0OA4YCMrY0btxoh0NOqeO53rypCi7+nzgOCCaaU2uVDMuPNu28ePxJQDADXv714wQoIXL4bCEi7cFcWIuBd0kn7uAIsArC4im89jZ68NcQsP2iNf1XCjOUJeLtgUwvxjHW557ACPxBXzr2lvxyTf/Ns7EDFzsMVeftFKRaXFx9eWyy2C9451EWJ9fxiWvPgQ+HgdXQUDCu95VFKX8fuDpp0uFJkEgotHAALB9e/F6UQT+5//EtCHi0ZiNU7qMqCeEXG8vRncM4o5rduCg++987nMAgCefnMCJuRTefPkwsL9/zdfBza4+H544E3UEGUo6Z+DJM2QS2M2XDDbtArp4WxADATI45NnJGG7cV3vfqhVP3IWPlKZjIZlDUtPBcxwEnoNh2fjhSws4fD6GRFbHcERBUtMhi3zN48dkNAvLJoWseifuigKP3f1+nFxIY3wxtWGiVPmx7PxKFhzHIeiRMBLxtsftt8lU68xxn0sGPRIu2lb6vVbPehYAtke82Dvgx5mlDH5yOoo3X1Hq6ltO53D/0bnCOknHwe1BhH3F3Cd3N9Hbrt6O//nI6RJzx2BQQULV4ZUEhLwy/uZHZ3Dtrh48fnoZR6cTmIxmIQocev0S+vwKOzerAyZKXSBsRth3pQA7RRRwybYg5hIajs8m0OOX8f8Oz+D0QgrHZpIYX0zj1EIKPMchoAjoD7APbi2OzyVxbjldaMEQC66FLstSaDM7e31FUapJpxQA7OjxwbZtHJmKY+9AoORz5Sy2Qh4kVb3g9LEh8jwEgYMs8jg8uYKpWAaLyRz2DpDQRIGvT7hKajoeeWnRcYcMhRSYll0IwC3NbCtv063GoZ09+ObhGTx5Noonz0RhqkTo2L8tWD2E1l7dzrWW0HY+msUrD/Tjp2dXAM7G4ak4TAtQJB4jEQ/6/UrJCfJYnx8vzZM2KUngEaqxEHHjXvhdNBTAM+dJBU4Uycloqxd+rZ7iUq+rYyikwPCQPKP/PL4AgSOTUm++eBAn5lNIawYyOXKytrPHh+NzSSiSAFHg8ZkfvARNNzFZcC4oEo99AwFctTOC58/HEU2TbECPxGM47EHEJyOp6ogXBCvTtPHYqWWkc0bB4aHCW6ice0QeZ5bSuOd7JxBXdfgV0RGB/bKAvoDckCBCP1NDIQ8mohkspUhLJ88Bg2EPAkoQ2byB7VUGd1y5owe3HxqBbdv4+H+8AL8iIqmZAIgAtGfAD0Wq3e4KAANBBVftiOC583E8dGIB1+wi7VPrcQ3Q26dzpjOJDmgstP74XLKi8HLxtiCi6RySqo50rih4UXdyvdXnRqAi0M/OrSCnW/jcD07ispFQSfGEbvPMxArmEzmcXc5A1c2mCiyKJCCp6tB0Y1WLbq3P5i9cuR1HZxKQBR6T0YyTYRf2Shsq2tH8saU0eS/XkydFaWWuVLMuvPHFNBaSOSgij5eXFWbKKS9cXjEaBmwbfKGAktYM6F4bP3fF8JrToN929Sj+709N3Psbd+O//LcP4pZnHkBU8gGygh41icWLr8Dcq95GTlpXVojDqJLIBCD+C7fjC76DOL2YRj6n49/cglQkUn2SnCAA3/kOadMrhIAjHCb5UJWe37e+j7z/ZPL+88kCuLyJozNJzMRXu/Bs28ZklKxNdjU4wGZXL3kPzcZV5AzT+Yz/+FTRJXXROvJbOY7DTfsH8M3nZvCT02Qa9FrHz0rFE7qmyOZNLKVyWE7nkDeKr5EJm+TQ2Tbiqo6kZsCviFhIks/JQlLD/sEgAp7q39c0T6rRz+v+oSARpRbSeOX+gYZuW061Y7i7SGCj6O6UBX5Dv2+6gUrnkpRG1rMAcfWdWcrgZ+ei2DPgR96wHDHrX396Htm8iStHI1hM5bCYykPghYrdRNXMHTfs7ccr9/fj8PkYTi2k8Z0js/DJAjwu59uJuY1z2m41mCh1AbHRYd9rtQqmcwYu2R7Grj4fZhMaHji+AFHgsLPHi4AiggNwZinDPrg1oCcnlk1Oiv7/9u48TI6q3hv4t3qr3nu29OzZ2RKIAaKQgLK8JoQLLyjo5QJGo3CvgCj3unKvPm8AnyiCAlcQAcUAbiAXUK7ExCghAklYkslOQvZk9r33rbrO+0d1d3q2TM9Md2V65vt5nnmepKen+5z+VVVX/eqc30l/iVe6rfDYzJPi7ko+TC934O0DnfjHh50IRBOwW4zwOke+MkYwlsDWYz3wRxTsbvbDZjGmTuRr0dQTRXNvBG2GKJKDLDylCoHecBzHeyJwyCZsb9SmMZiMEmxmrairxWjA9uM96ArFsi5ItTs8x7oiMEoSwoqCpCqw4v/OxRMbDo5pmu7uZj8Od4UyNWfKLdrc/PSF26fOrcGuJh/MRgMOdYQQjGt3vk1GCbLRACEE3j7QgX1tfnQH46lEmwRfJK7dJVeS2N4Ywv72QOYumCRJkCStUPShjjBaeqOoclsRS6jYfrwXv958FLub/DjcGYJs0pIouV6wZp/4SQYDrCYDIgkVu5t9mOKSUe609Dnxy2WkwFDP6Z84SAqBSDwJVagod1hwtDuMB9fuRXcoAZvFiGPdYahCwGgwoNRuhkvue3J9sulw/ZOD8UQS7VEAPVHYzUaE40lYzQZ8c8kZ+KA1MOBE6tIzvDi71o31e9vxl12tUFQVc6rdqK6wo80fxV/3tOKve7RkZ6nDjERS4CN1HpiM2sWN3WJCpduK/W0BlEyx4Hh3GB6rGaqQ0BNOoAcnVjhMJAX2twdThULVPieYncEYZlQ4c06IBKIKglEF3aE4ogkVkgRUua2o9lhhMhqQVAV6Qtq29pH6kpNOD3BbzTgjdcNES1RYM8P7c23P/znTi+3He7GvNYBoQkVXMAavyzLqkT6qKhCOJ9EVjOFgRwDTyux9LmCmuGS0+qLoDsdhkCRYzQbtWCEbsbvZh7W7WzNJz2qPDTa3AR3BqBbnnS1IJAUcsgmWVP2LCqeMitQIglzvPueqT/0qs3Ysc8h961cByDzHatZO4l3y6Kav7Gry4XfvHMWWoz1QhUBnII7ZlYPtLw4kkgL+SALhuAIBgR1NPuxt9fc5JgkhtBsEI5gCPRrmfiOLcq0nlZaPulJjGb355n6txtFHp5cNWgMt24Aap5KUqV2UfbG5eE4VakvtQ47un1PtxubDXdgUPw0Lrl6GS159Fv+y6Y+Z91kXDqPyqn/RLlqFTXsPIbQV5bxe7WfKFHQ5SvCqXIedjb5Uv234wY9exGFVhmVKBb5yxVkn3/6uuiqnz3c0K6F2BGIIx5MwGyXUDFGkeSgeuxkemxm+SAJNPRHMnOJEMKZg86Gxj5JKO3dqCdbtaUVPOIFdzT7MqysZ9HmD3Tzx2M3YerQH7x3pRoVTRm84kbnxMcUpo8IlQwKQVAX80QTMBkBRkSlW3ROJIxJXsbfVjxkVDpT0W7wi7WDHyOpJpZ2WmrVxpCuERFIdsI+mjWWaflIVCEQVJJIqetoSUFTtXF5OTf8u1PGmGOSz7IxWH1Vg06FubDnaA7vFhHhSRTSRzKw8/fmF03C0KzzsbKKTDe64YEYZbn3ufUQT2qjtkJqEJEmYVu6AzWzktVmOmJSivBpuquAZlS7c/tstiCtJyCYzmn0xSJKECqeloHUtJoq+y50rONQZhiRpRZwn+92VkQjFlUwyKakKOK1GrPzLByO6O7+ryYdfvnkY/qgCi8mACqcMVQi8ub8Tb+xrR22JPTOlzm4xosxhgdmoDUdXkgLhmIJYwgBFBWxmA1Sh1V1RkgKBpIJAVMkkro50heGxmbGvLQAhkDlRccomzJziQExRUWI3j2mabvrEOZZQMb3cju5QAj1RoEJRYTFJ2N3sx762AMKDFKFVkgJKMplpb2cwDodswgetwQHvY7eYEFOScMgmVLmt8LplyCYD2gMxNPuiiCRUfNgeRFxR8czGIzAbDZmizGaTYUQXrNl17gBgarkdx7rCiCRUtPpiEIhCVQU+bAsgHFcyd+eHGilwspNMu8WI/W1BOGQjDnQEM7VP0hJJFXuaA6nkTN/Pr9UX1aYV2swIxZNoONaDtbvbhrxIvPbcGuxo9EGSgA9aAgjGEgglJDitQJXHBo/NhO5QHEe7w0OeSAHAu4e7TxQd7omgIxBDJKFCNhkRjGn7xn3XzMUv3jyMw53hASeH5U4ZS8+uwvPvHsf0CjtiigpfOIGEeqLjQhVo7I3AIAFlDgtsZiOSQqAjEIMvomBXsw+VruHrWwHanf82fxSm1DYxy+uE23piaH//xMpw0wNUFZg1xYmZFX0L2uaaoCl3yvC6ZLy2swVv7OtAMjVFxR9VRl28fcO+DgSiCtoDMbx9oAvXn1eL5t4oGnvC2kU8TrQzkFooSBUCgUgCP/zLB4gnBardMjqCUfgiCuKKCoMkIZFUIUGCbDLgnFo3ZPOJvo307vNw+l+E72nxIxTTRmxMqbDgYGcI//P+cUDCgOkrTqtpxNNX0he+XUFtiq7JIGVWYmvsieDyM7x4/0g3JEjY3ujrMyID0EYnhGMKjEYJdosBpQ4ZVpMBvs5AZrvId9IuLV3oHBhZPam0sdaVGk3CJK25V7toNEjAohxWlxrJxeZwo/vTr/Ozi/8FX37jfwElgR9fdCUaDS4cqJ6JiKLiw/YAzqxyQ21uwRHVgoCCPse/x17boyXIvE4kkioUVUVo1umYkpomONJz0eFGxVS5regIxNARiMFokOB1W1FmNw84b1NVgY0Hu9AV1EZQj+ZMeFq5HTsafTjaHcbMKc68jZJKMxsNuHBmOf72QTve3N+Jc2o9AxJd/bctVVVxPAlEeiLaKqnRBOKJJKo8MqLxJObVeWA0nkhsaselKM6pK0W7P4oSuwVOqwk1qhUHO0LoCSdwsCOEUkccttTIlLRoIommXm1U7qwRJnqnuGS4rEY09USxdncr5lS7R1wXcqhE747GXq3GbqkNrb5oqqSAtmK51yXDk/o+K9Txpljkq+zM7mY/DrQHUyv5WVBql9DqjyMcVyBJwO2XzITLas55NtFQ5xSt/iiMkoTTvC50BGMQQjvW2FMrwvLaLDeTc2ungjrZzn2oI4iYouIj9SVo9UcRiWtDSEoKPER+osi+yHbIRoQTKmxmQ2b4+2S+u5KrXU0+/OqtE8kkk0FCmcMyomRH9slWfYkN3eEEDneFoCS1lYUCUQWdgShmTXGgN5LA2TXuTIwAZGpjLJw1pc/JlqqqiCoqIvEkIvEkesNxhGKGzMpp/tQS9wYJqC21odptRVIARzpDw44OGU52wtNsktAb7kVIkXCwIwQpVd8hFNUu3BwWI8qcMpyyEVazCUlVzSQkILQETIndDCUpTtQMsWpTTW1mE5p6wqjyWNHii8Jq1gpHVnlsmZEgH7T4kUgKNPVGUO2xwiBpdW/cVjNmTck9ed1/uojHZsE5ddod5FZfFJ3BOOKKit9sPoZWv5YYml3hhM1jGjBSAMCQowkOdYQwvVxb9cluObH6Wnr70urGCCRVFUaDASV2MxyyCUZJQlRJoieUQCIp0OyLIpZI4okNB6GowFlVzkzxZkDAbjHgg5aByUEhANkkMKfaBafVgqSqjRRJHwcGO5E61BFEU28E504tQWdQSySmV22sdNvgtJoQjCood8rDrpTzSkMTInEVzqyTsDStcPGJQqG1pVqdmEqXjIOdIQSjCva0+HFWlRtVqcUC+l/c1ZXYsGZPGzYe6ITTqsVmbo0bFlP/C5jcEiv5mh6wq8mHhuO96AnFYbOYYDJIcFlHPtIn+wImHW+ryYhNB7vw5v5OVLmtiMRVbTVBuwmVLhmSJCGa0Kb5+aIJGCRt1Tm7JTUlMapNBzEZJJQ7ZcyocGijlmQjjnVHCrroSZ8RipIEY+rz3d+uJakTSRV/3tECSNqKab5IAuk0kckwshpX2cfi0yqd8EW1Kbq9kQSSqpoayeYfMDLTbjGmfrSRYx1+rYZRiy+K2hIbhBAIaQNL8p60y2aUtNptiaSKulJbarGK3P8+17pSwyVMKt1WdIfi6AjGkFQFKt1WVDgsJ43DW6lRUufUenJeFXUkF5snG92ffp3fbxR40d8NAPjNNbfhzKleTDEb0BtR8OtNR3He1BLsSl2YZicPLpxRjgOpmwgftgXgS323emymzOjLkYyiPVmSIpLQpqi1B6LILhXnjwYhmwyocFoQiScRSC0K9NLWRry1vxO94QQaeyKIKiNfjW1amR3bj/di69EeWM1GrN3dCqvZmJdRUmkXzCzHhg87cLw7jH982IESu2XIZFxnMIamngi6wxIcBq2YfbXHBtlkwK0fn4GXtzbh0CA3PsocFnxh0TS80tCUtYq4AadVOtHYHUFTbwRHOkM4vdKFas+J748393egMxCD1y2POLGzu9mPD1oC2N8WxL62AKo91hHVhRxsmn4opqAzGM2UcvCF43CnFuQ4vdKBEptl0FGD+T7eFJOxlp1JfzcIIVDusEBRgWZfDGajAWdUuhBTVLy6vQXz6kpgMEhjmk2kzQRQMb3CgSkuGe2BKKqzFj/itVlumJSighhq5z5R6NKGCqeM5t4Iogl1xNMmJqv+F9lT+9VBmux3V4aTfQEztdSGrtQSsBVOGSX23Kc/Zl90heIKusMJKEkBSdISrDUlVggAn79wGl7a2oSDHaGcT7bsFgPsFhOEEIgkkvj4aVPQ6ovAajbCYADiikCZw5KpXROJKTmNDhlOdsLTaJBQW2rDvmAQTtkIp9UMm9mI7lAMdaVaEdpqjzXr5NYAq1kb/XLetL53NfsLRhVYLcYh6oaoCMeTqdXBYlCFQDiuIhzX6kjIppHVWxg8+SDBY7PAbTUjqfrhsprQEYiiNxyH22rGwc4QKpzaEr/lDguaeiN4duNhGA0GdAZjON3rhGQwQFFVhOPalMQjXSEc6woBqUvrao8VFU4LbFkJmmBUgVM2nUjOZBXxnV4u4IvEsbclCJfNhEBUgcVkxL62EEyGMAREZgqoJJ1IDrqsJnjdMpwWI9qaA5mEUC7HgXS8HR4z3DZtukdMUeF1yZmpcF2B4afCqarIKcEzWKHQqaV27G3zw2o2wi6b8Nj6A5hfX4JNh7oyF3faNq9iisuKMocFn11Qj3cPd+No1+AXMLkkVvIxPSB9LAlGFcya4szUBHLIIxvp0380weHOEMJxNXW3VZu+YpSAWV4H/BEFc6rdAz7jA+1BnO51oqk3giq3FYmkliS2W0yZUXnp6SKfOa8OO5p8BV30pP8IxRK7BYGYkhk5mC5gDElLyqQH1kmpJBWQ+7lA3wSYlgROJAVafdowMqvZiGhcgdWs1az0umU4LKY+MQlGFdhlU59jUqVbhiq04tBt/lhek3Zpu5p8eG1nC/a3BZFUBdr8UXQGYyNKQFjNRtR4rPigJYC1u1uwYHrZiBIm7f4YmnsjaJWiyBrgiEMdITT3RlDplvusmpxOzrT0RvHm/g44ZBMuHkERbiB/NU7PrvXg7qVn4Qep/9995emYN6MGAsBLWxrx973teGjdfjhkI86odGeSB9uP92LTgS50hmJwZyUqgfQiDkHIJm277A7FEY6PclTM8V5sO96LcrslM0XNIRtR7bFBSapoD8QQU1Qc6QpDSar43+3N2kIUMQUC2vlepXtkN8zSokoSW4/1IBhT8JddrQhGFdSUWKEMVktglJyyCV6XjFe3N+O9I90od8h9Ppu4kk7GxTI37IwGoLbECq/bBqNBwpFO7dxouESlQZIGHK9L7BZ0BmOwmY1wWc345ZuH8dHpZVi7pxWbDnahKxhHmcOM77+We1IvHcvO1MIossmAEptl0IRTXakNMUVFV1CBogrIJgP2twXx//60G75IHGajAdsbe6EkRda+JaHUboEllYxbvbMVHYE4TEPUMprsM0bGkig68d1gh0PWErySpCVsvW6rtvhGngZB9L82myH3fT1em+WGnw7pqv+OW1vKpMpI5LMA4GSUfQETjiuZpJRDHtn0x+yLLrvFiISiwpxKYqQv6I90hlA1ypOtIRNX3sLFvP++WeW2IuESqK/WRnkFowriSXXYIrT9E21DtfdkdUPOrnXj+XePo67UhvZADG1+7YLJZhnZiMDhkg+VbiuuP68Oz2w8ArfNnLnb1dQbzbxGIqli/d4OQNKmHvoivTAatKmW6Ytsh2yCQZIwt8YDXySBulLbiJIzkXgSHQFtpMcVcyvxzMYjqffSRlAB2tLFbqsZdosRveE46lMrVJU7tFWpRrpN9I93eb+aarlOhcs1wTPUCIlPnObFwlll2Ha8FwfaQ/jT9mbYTAacWeVG3Kxif1sQgVgCncE4vrP0TFw1rxoLZ5aPeVj/WKcHZB9LLCYDukJxqEJLuIymeHt6VFF2/RKr2YgpLhlGg5RJcA/1GV89rwa/eecojAYDPIMsfZ2O50fqS3Dt/NqCLnoy4FjisaLKLUNA2z4DMQUtqX2s0mOFw2KCgIDRIMGUGlGa67lA/wSY1yWjKxSHI7UIiM1iRJsvmhmZ6Uwd69OGOibtbw2gIwqYwom8J+2AExe/TT2RzIjKKo91VKPsth7twZ6WAD5o8aN2R8uwCZNQLNFnFF56mrlTNmGKywIJElr9UUQTKg60h1JFt0OQJOCVBm0bbPFFEYwqmFpmQ284gboRlrPKV43T7O227/S+Wry2syVV6NsAfzQOo0FLYgQiCXSG4ogpKpyyNhIzvdx8mz+GjkAUwVgScUXFzzccRGcwBgMk1JXmtrKooqrwReLwR7VRMaFoAl6XBfGkwLxaT2bUdHWJDV2BKPa0BOCUjfjHhx3oDmsrggqh9W2Ky4pKtzTi6ay/f/c4esNxWM3aDS6LyYCYksRP/34gb3VbdzX58N6RnsyiO1UeGUJI2NHYix2NPpQ7zCeScRYjKt1WRA0B1JTYMucU6X185hTnSROVQx2vF86qwMJZZXj3cDd2NWuLPLis5sz0Ka9bznmfyr5BMLfGjYbjPkQT2rROj82Egx1B/L8/7kJXKA6DQUotXtNXUggc7w5npumnc4AGCSi1WzDFLcNhMeJIZxgzKpy6rIw+WfWfWQJo24QrNUUyn4MgeG2WH7zyJ11xxx2bfBYAnIyyv6S0pdC1FcIsppElO/pfdNWdZMTaaE+2RpK4ykfM+++b2UZShHYk7R3qjvmRrhBeaWhCIilQX2ZHlceKUEyBxzbyegvDfb5JVSCpCsyo0IrIdwdj8Ee1ekqKKhBPJhGKKRDqiZWy0ieadouWNCixmdHYE8HV86rxl12to0rOZE+H++O2ZpTYLJhZ4UAwloTRgFQRYQnBqIKkEGMe1ZHPY3GuCZ6TjZC4aFYFvvybLYglkpCNBhzqDCGmqKlpHlYYDQZsOdqDK8+uyutIi9G+Tv+RhTUlVjT1RuEa4UifAUkVt1abzmMzo8RmzkzPHS7BnS7+nEs8C73oyaDbliRlauO0+2OYX18CANjZ5EOJ1wxJ6ju9Odftb7AbXdk3u04+MnPoY9KBNh/WvN6GpZefmVm+Pl+yL36rPVa0plavK3NYUGq35JyASCec2tKjOsyDjOrY2oTOYAx1pTYkkiqOd0fRFYpDSWqj8AwQmFFhRyCq4OwaN6RUwqTSLaPNH8UHLQGU2M14bUcLPmwPQDYZMaPCAUBLdITiyXG5QM3R7jBUVWBmhQNdoQQae6Jo7EnfbNDqmHaHtBVBs28iTC2zo8YjY3ujDx6bCce7wugOx+GxmdEeiKLUboGAQIndjGNdITy4Zi+6wgk4LEY09kSgqKq2KqmqvU+Z3QK7xYgvXzoLrwwyaro3ouDsWg8WzS7HcxuPnph+C8BuNsKYTmCNcDprTyiOGo8NgdRKmyV2E+ZUu3CgPZSXuq3p9wnFFEwrt6M3rH33OGRTaqpaHIGIGRUuC+KKinPqPJAAHO/V/n6wfXy449LJjtfnTS3Frc++j2BM0b6nU1P+K902mAy5JfX6ljDQEhmhWBIftqWnHQsc74lkEk4GSbtxIJsMMBm1hLoEoKk3ApNRQm2JFW6bBUaDBLPBkHnfkSTjaPT6fzf0XzAgn4MgeG2WHxMmKfX444/jwQcfREtLC+bOnYtHHnkEH//4x091s6gf7rhjl68CgJNR/y+puTXuzJ15IPcvqZFe0I/lZCv9+0LHvP++ebJERz7bO9hn0//zNRsNmSm+o0leD1fnLnubqHBZUZFVBzYYVWAzayuEVrmtsFmMUFQBCdoS9OnnpEehnFbpGlNyps90OK+zzxTIfI7qyPexOB+FQgFgTrUbbalpLQBQ5ZZRX6YtGpB9UZbPkRajeZ2BJ7z2zGgnIPdjSf/XkU1GTMvarrOn5w53ATNevltz2bauP78OgHYBN5b25nosziWZnt3+GRUOTHMCMyryf4GYffHrj2qjLbTtRLtRkksCIjuxNafahYbjWgH33kgcJgPwQasf3/6fHfBHEjAZDZmaSWk2ixHeVG2y5YtSo/D6JExUBGNJnFPnwcdPq8CL7zciEFUgWSUc7AhCCAluqxFn17rzlujIpxM1XpxwWmM42qUtClNiN6PKbYXdYsTuJj+csmnQ7W96uQPXnVuLJ/9xCEajhLgiMrX30hJJFXtaBl+8wmExoqbEBrfNhCOdYdQMk1ROqgKrna2o8mj1l3rCCVR6ToxeHc101t5IPJOUqivRprfmq25r9vsAAr3hQJ/Px2OzQDYbcfuls/DHhiYc6gjlZUrsUMdrXyQBu2xEtduKcEIFUiOr0yNPc+l3/xsElS4ZR+NhmEwG2FI3L9v8WgJ4WrkDZQ4z0K8MfTCqreiZnqZf6TaO+fyQRkfvQRC8Nhu7CZGUeuGFF/Dv//7vePzxx3HRRRfhySefxJVXXok9e/Zg6tSpp7p51A933LHL10iByab/l1R2UeaRfEkVIrk61sRVPmTvm8MlOgrZXj0/35xOXFL93tmkJYpMxqFHdRgM0piSM6NZoWq0ozryfSwec6HQhFYo1OvWplq5raZxW29wsO0mve0Usuh6LsWfx8N3a65tGWt787mim16yL35lswGqEPC6RpaAyE4KmIzaNPJQLInm1LRICRI6AtoqUCVmI8xGKbMSbIVTK/6cVHMbhWe3GPHXPe1wymb0RuKZKcVaXcH8JTryKTvZW+m2wmM1wWA4MSo6GFVQ5rTgcxdMxebD3UMmisxGA06rdCGaSKLNH0UkkYQxqwZV9uIVdosJkqS9tzaqV8p5VEz65ogQwLRyB6b1W8xwNNNZBcxo7o1q7bHnd8pS35GiWp8DUQWyyYBqj1b/72iXVjsx13OKsbYnoQicVeNGS28ULX5tantaLv3uf4NAu0ElI514CkYVGA1SJuFUajf3WZQgl2n6vPmun1MxCGK8fMcUqwmRlHrooYdwyy234NZbbwUAPPLII1i7di1+/vOf44c//OEpbh0Nhjvu2PHuysjl80vqVFwA6hHzfE5fGUt79fp8CzGqY6xxGulIs7GM6hgvx+JiW8QhX8eSUzViTQ+5tCUf7c3Xim56GTD9exS1NfuP6qgvtaPNH4XJKMFi1GpUNfaEYTYZMb3cAbdt4Kp8kXhuCZPtx3uRSK0sNU2yozMQg6KqqEjVoTvVCeOKigrE4/E+j/VP9lqHuAG1eE4VFs+pymkUbf/tJhhVYLcYM0mKk9USHC6pnK9RHdnblstqxtwaN6xmA9KJlXwdR/tvw6dVOvusCDtYMq6QU2JPtEdFXZkd1SXWzNRHILd+D7UwCjDyhNN4ukEwmU3U8/SJanyc3Y1BPB7Hli1bcPfdd/d5fMmSJdi4ceMpahXlgjsunQr5/JIaTxeA+VTo6Su50uvz1WtUx0jbpNe2NR6OxcVYbzBfx5LxNGIt33JpSz7aW0zH4nxs6/2TAm6buU/iKRhV4HVbMwkTl3XoAu/DJUz6v5c3a6lz4NQmjB0OB5qbm7F69Wo4HCc+r5Eme8eSKMrHqJh8Jaf7tzm9mmX/No/1ONr/fUwGA9y2oafYF/qcon97shNSufZ7rIt2jGSaPumHcSgeRZ+U6uzsRDKZRGVlZZ/HKysr0draOujfxGIxxGKxzP/9fj8AIJFIIJE4sZpC+t/Zj9H4xFgVj/EQqzO8dty95DQc7Q5nvqSmldlhMEijald9iQxAu2ucTCpIJvPc4FNgPMQpTY/PN5dtIt/bTS5y6ft4itVYXDuvCse7QtjfFkCVxwqb2YhIIolWXxSlDjOumVc57vavkWwTJ4vTqdi2JqJ8HSsKvU+NdVuvdVsws8KOXU1+zJriGJAwae4N45xaN679SDV+9sahMe1Tub5XrdtySrbVoWJ1hteOOy6ZgVe2NeNgewitviRkkxFn17jwqfk1OMNrH7a9ucTpzErHmN8nX+3Ntc35OI6O9H3G+z4F5B6DkRyvi/H8cKKcU2QrxjgMp1jilGv7JJG9lnQRam5uRm1tLTZu3IiFCxdmHl+5ciV+/etfY+/evQP+5p577sG999474PHf/e53sNvtAx4nIiKiwmsMAe+2G9AaARQVMBmAKhvwMa+KuvEzSIpozMa6rTeGgDXHDQgpQIkFsBiAuAr0xgGHCVhar71OPvapXN9rPFIF0BkFIknAZgQqrMBIBknk+vmN9X3y+Tp6HUfH2/E6X+3JVyyJCAiHw7jpppvg8/ngdruHfF7RJ6Xi8TjsdjtefPFFfPrTn848ftddd2Hbtm3YsGHDgL8ZbKRUfX09Ojs7+3xYiUQC69atw+LFi2E2D5yPT+MHY1U8GKviwDgVj4kWK1UVg96BLnYTLU4TmV6xGuu2vrvZnxnVEVO0UR2zvQ58an4N5tacOJ/Nxz6V63vpKRKJ4Oqrr0Z3dzc2bNhw0guesSjGY5Jebc71fYplnyJ+VxWLYomT3+9HRUXFsEmpop++Z7FYcP7552PdunV9klLr1q3DtddeO+jfyLIMWZYHPG42mwcN6lCP0/jDWBUPxqo4ME7FYyLF6vRqy6luQsFMpDhNdHrEaizb+vxp5ZhXX5ZTvZSx7lMjeS+9xONxvPnmmwAAo9FY0FgV4zFJrzaP5H3G+z5FJ/C7qjiM9zjl2raiT0oBwNe//nUsW7YMCxYswMKFC/HUU0/h2LFjuO22205104iIiIiICkLPwvbjqYg+ERFNHBMiKXXDDTegq6sL9913H1paWnD22Wdj9erVmDZt2qluGhERERERERERDWJCJKUA4I477sAdd9xxqptBREREREREREQ5MJzqBhARERERERER0eTDpBQREREREREREeluwkzfIyIiIiKiycNutyOZTJ7qZhAR0RgwKUVEREREREXF4XCgt7cXq1evhsPhONXNISKiUeL0PSIiIiIiIiIi0h2TUkREREREREREpDtO3yMiIiIioqISjUZx3XXXob29HZdffjnMZvOpbhIREY0Ck1JERERERFRUkskk/vKXv2T+TURExYnT94iIiIiIiIiISHdMShERERERERERke6YlCIiIiIiIiIiIt0xKUVERERERERERLpjUoqIiIiIiIiIiHTH1fcACCEAAH6/v8/jiUQC4XAYfr+fy8yOc4xV8WCsigPjVDwYq+LAOBUPxqo4hEKhzL/9fj8MBt5rH6+4TxUPxqo4FEuc0vmVdL5lKExKAQgEAgCA+vr6U9wSIiIiIiIaiWnTpp3qJhAR0RACgQA8Hs+Qv5fEcGmrSUBVVTQ3N8PlckGSpMzjfr8f9fX1OH78ONxu9ylsIQ2HsSoejFVxYJyKB2NVHBin4sFYFQ/GqjgwTsWDsSoOxRInIQQCgQBqampOOpqVI6UAGAwG1NXVDfl7t9s9roNNJzBWxYOxKg6MU/FgrIoD41Q8GKviwVgVB8apeDBWxaEY4nSyEVJpnHxNRERERERERES6Y1KKiIiIiIiIiIh0x6TUSciyjBUrVkCW5VPdFBoGY1U8GKviwDgVD8aqODBOxYOxKh6MVXFgnIoHY1UcJlqcWOiciIiIiIiIiIh0x5FSRERERERERESkOyaliIiIiIiIiIhId0xKERERERERERGR7iZ8UuqHP/whPvrRj8LlcsHr9eJTn/oU9u3b1+c5Qgjcc889qKmpgc1mw6WXXordu3f3ec5TTz2FSy+9FG63G5Ikobe3d8j3jMVimD9/PiRJwrZt2wrQq4lHzzhNnz4dkiT1+bn77rsL2b0JRe996rXXXsMFF1wAm82GiooKXHfddYXq2oSjV6zeeOONAftU+ue9994rdDeLnp771Icffohrr70WFRUVcLvduOiii7B+/fpCdm9C0TNWW7duxeLFi1FSUoLy8nL827/9G4LBYCG7N2HkI07d3d346le/ijPOOAN2ux1Tp07F1772Nfh8vj6v09PTg2XLlsHj8cDj8WDZsmUnPUekvvSM1cqVK7Fo0SLY7XaUlJTo0b0JRa9YHTlyBLfccgtmzJgBm82GWbNmYcWKFYjH47r1tZjpuU9dc801mDp1KqxWK6qrq7Fs2TI0Nzfr0s+JQM9YpY3XPMWET0pt2LABX/nKV7B582asW7cOiqJgyZIlCIVCmec88MADeOihh/DYY4/hvffeQ1VVFRYvXoxAIJB5TjgcxtKlS/Ff//Vfw77nt7/9bdTU1BSkPxOV3nG677770NLSkvn53ve+V7C+TTR6xuqll17CsmXL8MUvfhHbt2/H22+/jZtuuqmg/ZtI9IrVokWL+uxPLS0tuPXWWzF9+nQsWLCg4P0sdnruU1dddRUURcHrr7+OLVu2YP78+bj66qvR2tpa0D5OFHrFqrm5GZ/85Ccxe/ZsvPPOO1izZg12796N5cuXF7qLE0I+4tTc3Izm5mb8+Mc/xs6dO/HMM89gzZo1uOWWW/q810033YRt27ZhzZo1WLNmDbZt24Zly5bp2t9ipmes4vE4PvvZz+L222/XtY8ThV6x2rt3L1RVxZNPPondu3fj4YcfxhNPPJHTNRjpu09ddtll+MMf/oB9+/bhpZdewsGDB/GZz3xG1/4WMz1jlTZu8xRikmlvbxcAxIYNG4QQQqiqKqqqqsT999+feU40GhUej0c88cQTA/5+/fr1AoDo6ekZ9PVXr14tzjzzTLF7924BQDQ0NBSiGxNeIeM0bdo08fDDDxeq6ZNOoWKVSCREbW2t+OUvf1nQ9k8mhT7+pcXjceH1esV9992X1/ZPFoWKU0dHhwAg/vGPf2Qe8/v9AoD429/+VpjOTHCFitWTTz4pvF6vSCaTmccaGhoEALF///7CdGYCG2uc0v7whz8Ii8UiEomEEEKIPXv2CABi8+bNmeds2rRJABB79+4tUG8mtkLFKtuqVauEx+PJe9snGz1ilfbAAw+IGTNm5K/xk4iecfrTn/4kJEkS8Xg8fx2YRAodq/Gcp5jwI6X6Sw9lKysrAwAcPnwYra2tWLJkSeY5sizjkksuwcaNG0f02m1tbfjXf/1X/PrXv4bdbs9foyehQsYJAH70ox+hvLwc8+fPx8qVKzkkeAwKFautW7eiqakJBoMB5557Lqqrq3HllVcOmAZDuSv0fpX26quvorOzk6M6RqlQcSovL8dZZ52F5557DqFQCIqi4Mknn0RlZSXOP//8/HZikihUrGKxGCwWCwyGE6dpNpsNAPDWW2/lo+mTSr7i5PP54Ha7YTKZAACbNm2Cx+PBBRdckHnOhRdeCI/HM6Zj6GRWqFhR/ukZK5/Pl3kfGhm94tTd3Y3f/va3WLRoEcxmcx57MHkUMlbjPU8xqZJSQgh8/etfx8UXX4yzzz4bADJTFiorK/s8t7KyckTTGYQQWL58OW677TZOVxmjQsYJAO666y48//zzWL9+Pe6880488sgjuOOOO/LT+EmmkLE6dOgQAOCee+7B9773Pfz5z39GaWkpLrnkEnR3d+epB5NHoferbE8//TSuuOIK1NfXj77Bk1Qh4yRJEtatW4eGhga4XC5YrVY8/PDDWLNmDeurjEIhY3X55ZejtbUVDz74IOLxOHp6ejJTV1paWvLUg8khX3Hq6urC97//fXz5y1/OPNba2gqv1zvguV6vl1NiR6GQsaL80jNWBw8exKOPPorbbrstT62fPPSI03e+8x04HA6Ul5fj2LFj+NOf/pTnXkwOhYxVMeQpJlVS6s4778SOHTvw+9//fsDvJEnq838hxIDHTubRRx+F3+/Hf/7nf465nZNdIeMEAP/xH/+BSy65BPPmzcOtt96KJ554Ak8//TS6urrG1O7JqJCxUlUVAPDd734X119/Pc4//3ysWrUKkiThxRdfHFvDJ6FC71dpjY2NWLt27ZBz2enkChknIQTuuOMOeL1evPnmm3j33Xdx7bXX4uqrr2aiYxQKGau5c+fi2WefxU9+8hPY7XZUVVVh5syZqKyshNFoHHPbJ5N8xMnv9+Oqq67CnDlzsGLFipO+xsleh06u0LGi/NErVs3NzVi6dCk++9nP4tZbb81P4ycRPeL0rW99Cw0NDfjrX/8Ko9GIz3/+8xBC5K8Tk0QhY1UMeYpJk5T66le/ildffRXr169HXV1d5vGqqioAGJBtbG9vH5CVPJnXX38dmzdvhizLMJlMmD17NgBgwYIF+MIXvpCHHkwOhY7TYC688EIAwIEDB8b0OpNNoWNVXV0NAJgzZ07mMVmWMXPmTBw7dmwsTZ909NyvVq1ahfLyclxzzTWjb/Akpcf31J///Gc8//zzuOiii3Deeefh8ccfh81mw7PPPpufTkwSeuxTN910E1pbW9HU1ISuri7cc8896OjowIwZM8begUkiH3EKBAJYunQpnE4nXnnllT7TUqqqqtDW1jbgfTs6OsZ8bjLZFDpWlD96xaq5uRmXXXYZFi5ciKeeeqoAPZnY9IpTRUUFTj/9dCxevBjPP/88Vq9ejc2bNxegRxNXoWNVDHmKCZ+UEkLgzjvvxMsvv4zXX399wMncjBkzUFVVhXXr1mUei8fj2LBhAxYtWpTz+/z0pz/F9u3bsW3bNmzbtg2rV68GALzwwgtYuXJlfjozgekVp8E0NDQAOJEEoZPTK1bnn38+ZFnuszRqIpHAkSNHMG3atLF3ZBLQe78SQmDVqlX4/Oc/z4uBEdArTuFwGAD61ClK/z89MpFO7lR8V1VWVsLpdOKFF16A1WrF4sWLx9SHySBfcfL7/ViyZAksFgteffVVWK3WPq+zcOFC+Hw+vPvuu5nH3nnnHfh8vjGfm0wWesWKxk7PWDU1NeHSSy/Feeedh1WrVg343qKhncp9Kj1CKhaL5ak3E5tesSqKPEXhaqiPD7fffrvweDzijTfeEC0tLZmfcDicec79998vPB6PePnll8XOnTvFjTfeKKqrq4Xf7888p6WlRTQ0NIhf/OIXmdWLGhoaRFdX16Dve/jw4XFX1X480ytOGzduFA899JBoaGgQhw4dEi+88IKoqakR11xzje59LlZ67lN33XWXqK2tFWvXrhV79+4Vt9xyi/B6vaK7u1vXPhcrvY9/f/vb3wQAsWfPHt36OBHoFaeOjg5RXl4urrvuOrFt2zaxb98+8c1vflOYzWaxbds23ftdjPTcpx599FGxZcsWsW/fPvHYY48Jm80m/vu//1vX/harfMTJ7/eLCy64QJxzzjniwIEDfV5HUZTM6yxdulTMmzdPbNq0SWzatEmcc8454uqrr9a9z8VKz1gdPXpUNDQ0iHvvvVc4nU7R0NAgGhoaRCAQ0L3fxUivWDU1NYnZs2eLyy+/XDQ2NvZ5Dg1Przi988474tFHHxUNDQ3iyJEj4vXXXxcXX3yxmDVrlohGo6ek78VGz+NftvGYp5jwSSkAg/6sWrUq8xxVVcWKFStEVVWVkGVZfOITnxA7d+7s8zorVqwY9nWyjcdgj2d6xWnLli3iggsuEB6PR1itVnHGGWeIFStWiFAopGNvi5ue+1Q8Hhff+MY3hNfrFS6XS3zyk58Uu3bt0qmnxU/v49+NN94oFi1apEPPJhY94/Tee++JJUuWiLKyMuFyucSFF14oVq9erVNPi5+esVq2bJkoKysTFotFzJs3Tzz33HM69bL45SNO69evH/J1Dh8+nHleV1eXuPnmm4XL5RIul0vcfPPNoqenR7/OFjk9Y/WFL3xh0OesX79evw4XMb1itWrVqiGfQ8PTK047duwQl112mSgrKxOyLIvp06eL2267TTQ2Nurc4+Kl5/Ev23jMU0hCsBIZERERERERERHpixN0iYiIiIiIiIhId0xKERERERERERGR7piUIiIiIiIiIiIi3TEpRUREREREREREumNSioiIiIiIiIiIdMekFBERERERERER6Y5JKSIiIiIiIiIi0h2TUkREREREREREpDsmpYiIiIgmAUmS8Mc//vFUN4OIiIgog0kpIiIiogJavnw5JEnCbbfdNuB3d9xxByRJwvLly/P2fvfccw/mz5+ft9cjIiIiKhQmpYiIiIgKrL6+Hs8//zwikUjmsWg0it///veYOnXqKWwZERER0anDpBQRERFRgZ133nmYOnUqXn755cxjL7/8Murr63HuuedmHovFYvja174Gr9cLq9WKiy++GO+9917m92+88QYkScLf//53LFiwAHa7HYsWLcK+ffsAAM888wzuvfdebN++HZIkQZIkPPPMM5m/7+zsxKc//WnY7XacdtppePXVVwvfeSIiIqIhMClFREREpIMvfvGLWLVqVeb/v/rVr/ClL32pz3O+/e1v46WXXsKzzz6LrVu3Yvbs2bjiiivQ3d3d53nf/e538ZOf/ATvv/8+TCZT5nVuuOEGfOMb38DcuXPR0tKClpYW3HDDDZm/u/fee/HP//zP2LFjB/7pn/4JN99884DXJiIiItILk1JEREREOli2bBneeustHDlyBEePHsXbb7+Nz33uc5nfh0Ih/PznP8eDDz6IK6+8EnPmzMEvfvEL2Gw2PP30031ea+XKlbjkkkswZ84c3H333di4cSOi0ShsNhucTidMJhOqqqpQVVUFm82W+bvly5fjxhtvxOzZs/GDH/wAoVAI7777rm6fAREREVE206luABEREdFkUFFRgauuugrPPvsshBC46qqrUFFRkfn9wYMHkUgkcNFFF2UeM5vN+NjHPoYPPvigz2vNmzcv8+/q6moAQHt7+7D1qbL/zuFwwOVyob29fUz9IiIiIhotJqWIiIiIdPKlL30Jd955JwDgZz/7WZ/fCSEAAJIkDXi8/2Nmsznz7/TvVFUd9v2z/y79t7n8HREREVEhcPoeERERkU6WLl2KeDyOeDyOK664os/vZs+eDYvFgrfeeivzWCKRwPvvv4+zzjor5/ewWCxIJpN5azMRERFRoXCkFBEREZFOjEZjZiqe0Wjs8zuHw4Hbb78d3/rWt1BWVoapU6figQceQDgcxi233JLze0yfPh2HDx/Gtm3bUFdXB5fLBVmW89oPIiIionxgUoqIiIhIR263e8jf3X///VBVFcuWLUMgEMCCBQuwdu1alJaW5vz6119/PV5++WVcdtll6O3txapVq7B8+fI8tJyIiIgovySRLmBARERERERERESkE9aUIiIiIiIiIiIi3TEpRUREREREREREumNSioiIiIiIiIiIdMekFBERERERERER6Y5JKSIiIiIiIiIi0h2TUkREREREREREpDsmpYiIiIiIiIiISHdMShERERERERERke6YlCIiIiIiIiIiIt0xKUVERERERERERLpjUoqIiIiIiIiIiHTHpBQREREREREREenu/wMkTUkF2dlZcQAAAABJRU5ErkJggg==",
|
||
"text/plain": [
|
||
"<Figure size 1200x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"import statsmodels.formula.api as smf\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"# 1. Convert to monthly time series\n",
|
||
"spills_gdf['report_month'] = spills_gdf['Initial Report Date'].dt.to_period('M')\n",
|
||
"monthly = spills_gdf.groupby('report_month')['report_delay'].mean().reset_index()\n",
|
||
"monthly['report_month'] = monthly['report_month'].dt.to_timestamp()\n",
|
||
"\n",
|
||
"# 2. Create ITS variables\n",
|
||
"monthly['time'] = (monthly['report_month'] - monthly['report_month'].min()).dt.days // 30\n",
|
||
"monthly['post_2021'] = (monthly['report_month'] >= pd.Timestamp('2021-01-01')).astype(int)\n",
|
||
"monthly['time_post'] = monthly['time'] * monthly['post_2021']\n",
|
||
"\n",
|
||
"# 3. Run the ITS model\n",
|
||
"its_model = smf.ols(\"report_delay ~ time + post_2021 + time_post\", data=monthly).fit()\n",
|
||
"print(its_model.summary())\n",
|
||
"\n",
|
||
"# 4. Predict and plot\n",
|
||
"monthly['predicted'] = its_model.predict(monthly)\n",
|
||
"\n",
|
||
"plt.figure(figsize=(12, 6))\n",
|
||
"plt.plot(monthly['report_month'], monthly['report_delay'], marker='o', label='Observed', alpha=0.6)\n",
|
||
"plt.plot(monthly['report_month'], monthly['predicted'], linestyle='--', color='red', label='Predicted (ITS)')\n",
|
||
"plt.axvline(x=pd.Timestamp('2021-01-01'), color='black', linestyle='--', label='Policy Change (2021)')\n",
|
||
"plt.title('Interrupted Time Series: Monthly Report Delay')\n",
|
||
"plt.xlabel('Month')\n",
|
||
"plt.ylabel('Mean Report Delay (Days)')\n",
|
||
"plt.legend()\n",
|
||
"plt.grid(True)\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.show()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "35a2f32a",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 🧠 **Reinterpreting the ITS (Breakpoint: Jan 2021)**\n",
|
||
"\n",
|
||
"#### 📊 Model Coefficients:\n",
|
||
"| Term | Coefficient | p-value | Interpretation |\n",
|
||
"|--------------|-------------|---------|----------------|\n",
|
||
"| **Intercept** | 15.60 | 0.000 | Average delay in the first month (baseline) |\n",
|
||
"| `time` | –0.118 | 0.140 | Pre-2021 monthly decline in delay (not significant) |\n",
|
||
"| `post_2021` | –27.67 | 0.285 | Immediate drop in Jan 2021 (not significant, but large) |\n",
|
||
"| `time_post` | +0.30 | 0.269 | Slope increase after Jan 2021 (not significant) |\n",
|
||
"\n",
|
||
"---\n",
|
||
"\n",
|
||
"### **Visual Takeaways from the Plot**\n",
|
||
"- There’s a **clear downward trend pre-2021**, with sharp outliers but general decline.\n",
|
||
"- The **predicted line (ITS)** reflects a **notable drop at 2021** followed by a **flattening or slight uptick**.\n",
|
||
"- This matches your narrative: **the policy went into effect in 2020**, but **the agency's implementation (culture/process) adapted in 2021**.\n",
|
||
"\n",
|
||
"---\n",
|
||
"\n",
|
||
"### Interpretation for Results Section\n",
|
||
"\n",
|
||
"> We re-estimated the interrupted time series model using January 2021 as the intervention point to reflect the agency's internal adaptation to the 2020 regulatory rule change. While the coefficients for both level and slope change were not statistically significant, the direction of effects supports the broader interpretation that reporting delays declined prior to the implementation of the new mission, followed by a period of stabilization or slight reversal. The large (but imprecise) estimated level shift in 2021 may indicate a transitional inflection point, though visual inspection suggests this reflects a continuation of preexisting trends rather than an abrupt effect attributable solely to organizational adaptation.\n",
|
||
"\n",
|
||
"---\n",
|
||
"\n",
|
||
"### Final Thought\n",
|
||
"Well-supported claim: **the formal policy didn’t create an immediate break**, but **organizational change may have reinforced an ongoing improvement trajectory**. That’s a much stronger and more realistic story than trying to force a sharp treatment effect."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "e9ce1703",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Interrupted Time Series Analysis\n",
|
||
"### 🔍 **Model Findings**\n",
|
||
"\n",
|
||
"| Term | Coefficient | p-value | Meaning |\n",
|
||
"|-------------|-------------|---------|---------|\n",
|
||
"| **Intercept** | 16.67 | 0.000 | Predicted delay at baseline (month 0) |\n",
|
||
"| `time` | –0.17 | 0.107 | Slight (non-sig.) decline pre-2021 |\n",
|
||
"| `post_2021` | –5.09 | 0.753 | No significant level change |\n",
|
||
"| `time_post` | +0.12 | 0.558 | No significant trend change after 2021 |\n",
|
||
"\n",
|
||
"**R² = 0.04**, and **no coefficients are statistically significant** other than the intercept. In short: ITS didn’t detect a strong policy effect.\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"### What the Plot Shows\n",
|
||
"\n",
|
||
"The **visual trend** still tells a useful story:\n",
|
||
"- High volatility pre-2021 with outliers and erratic reporting\n",
|
||
"- A more stable pattern post-2021\n",
|
||
"- No obvious immediate *jump* or *trend break*, but lower variance\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"### How to Report This\n",
|
||
"\n",
|
||
"You can say:\n",
|
||
"> “We conducted an Interrupted Time Series analysis using monthly average delays and found no statistically significant level or trend change post-policy. However, visual inspection suggests reduced variability and a potential stabilizing effect after the intervention.”\n",
|
||
"\n",
|
||
"---\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "6ae433ec",
|
||
"metadata": {},
|
||
"source": [
|
||
"## ITS by Spill Type"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 25,
|
||
"id": "bfd7557f",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n",
|
||
"=== ITS Model Summary for Historical Spills ===\n",
|
||
"\n",
|
||
" OLS Regression Results \n",
|
||
"==============================================================================\n",
|
||
"Dep. Variable: report_delay R-squared: 0.037\n",
|
||
"Model: OLS Adj. R-squared: 0.011\n",
|
||
"Method: Least Squares F-statistic: 1.420\n",
|
||
"Date: Fri, 18 Apr 2025 Prob (F-statistic): 0.241\n",
|
||
"Time: 22:00:50 Log-Likelihood: -623.83\n",
|
||
"No. Observations: 115 AIC: 1256.\n",
|
||
"Df Residuals: 111 BIC: 1267.\n",
|
||
"Df Model: 3 \n",
|
||
"Covariance Type: nonrobust \n",
|
||
"==============================================================================\n",
|
||
" coef std err t P>|t| [0.025 0.975]\n",
|
||
"------------------------------------------------------------------------------\n",
|
||
"Intercept 41.4175 12.403 3.339 0.001 16.840 65.995\n",
|
||
"time -0.3440 0.273 -1.260 0.210 -0.885 0.197\n",
|
||
"post_2021 -72.4348 88.791 -0.816 0.416 -248.380 103.511\n",
|
||
"time_post 0.7685 0.937 0.820 0.414 -1.089 2.626\n",
|
||
"==============================================================================\n",
|
||
"Omnibus: 146.900 Durbin-Watson: 2.047\n",
|
||
"Prob(Omnibus): 0.000 Jarque-Bera (JB): 3812.237\n",
|
||
"Skew: 4.681 Prob(JB): 0.00\n",
|
||
"Kurtosis: 29.607 Cond. No. 1.41e+03\n",
|
||
"==============================================================================\n",
|
||
"\n",
|
||
"Notes:\n",
|
||
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
|
||
"[2] The condition number is large, 1.41e+03. This might indicate that there are\n",
|
||
"strong multicollinearity or other numerical problems.\n",
|
||
"\n",
|
||
"=== ITS Model Summary for Recent Spills ===\n",
|
||
"\n",
|
||
" OLS Regression Results \n",
|
||
"==============================================================================\n",
|
||
"Dep. Variable: report_delay R-squared: 0.011\n",
|
||
"Model: OLS Adj. R-squared: -0.016\n",
|
||
"Method: Least Squares F-statistic: 0.4120\n",
|
||
"Date: Fri, 18 Apr 2025 Prob (F-statistic): 0.745\n",
|
||
"Time: 22:00:50 Log-Likelihood: -381.76\n",
|
||
"No. Observations: 115 AIC: 771.5\n",
|
||
"Df Residuals: 111 BIC: 782.5\n",
|
||
"Df Model: 3 \n",
|
||
"Covariance Type: nonrobust \n",
|
||
"==============================================================================\n",
|
||
" coef std err t P>|t| [0.025 0.975]\n",
|
||
"------------------------------------------------------------------------------\n",
|
||
"Intercept 5.1035 1.511 3.377 0.001 2.109 8.098\n",
|
||
"time -0.0171 0.033 -0.513 0.609 -0.083 0.049\n",
|
||
"post_2021 -5.7731 10.819 -0.534 0.595 -27.212 15.666\n",
|
||
"time_post 0.0565 0.114 0.495 0.622 -0.170 0.283\n",
|
||
"==============================================================================\n",
|
||
"Omnibus: 133.689 Durbin-Watson: 2.054\n",
|
||
"Prob(Omnibus): 0.000 Jarque-Bera (JB): 2325.882\n",
|
||
"Skew: 4.223 Prob(JB): 0.00\n",
|
||
"Kurtosis: 23.349 Cond. No. 1.41e+03\n",
|
||
"==============================================================================\n",
|
||
"\n",
|
||
"Notes:\n",
|
||
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
|
||
"[2] The condition number is large, 1.41e+03. This might indicate that there are\n",
|
||
"strong multicollinearity or other numerical problems.\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"import statsmodels.formula.api as smf\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"# Group by month and spill type\n",
|
||
"spills_gdf['report_month'] = spills_gdf['Initial Report Date'].dt.to_period('M')\n",
|
||
"monthly_by_type = spills_gdf.groupby(['report_month', 'spill_type'])['report_delay'].mean().reset_index()\n",
|
||
"monthly_by_type['report_month'] = monthly_by_type['report_month'].dt.to_timestamp()\n",
|
||
"\n",
|
||
"# ITS variables\n",
|
||
"monthly_by_type['time'] = (monthly_by_type['report_month'] - monthly_by_type['report_month'].min()).dt.days // 30\n",
|
||
"monthly_by_type['post_2021'] = (monthly_by_type['report_month'] >= pd.Timestamp('2021-01-01')).astype(int)\n",
|
||
"monthly_by_type['time_post'] = monthly_by_type['time'] * monthly_by_type['post_2021']\n",
|
||
"\n",
|
||
"# Run ITS models and print summaries\n",
|
||
"its_results_by_type = {}\n",
|
||
"for stype in monthly_by_type['spill_type'].unique():\n",
|
||
" df = monthly_by_type[monthly_by_type['spill_type'] == stype].copy()\n",
|
||
" model = smf.ols(\"report_delay ~ time + post_2021 + time_post\", data=df).fit()\n",
|
||
" df['predicted'] = model.predict(df)\n",
|
||
" its_results_by_type[stype] = (model, df)\n",
|
||
" \n",
|
||
" print(f\"\\n=== ITS Model Summary for {stype} Spills ===\\n\")\n",
|
||
" print(model.summary())\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"id": "d790d469",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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VKj9uhafnhYiIqLoTZHd100REREREl6HOnTvj7NmzXvdQIyIiIu+wpxQREREREREREV1yDKWIiIiIiIiIiOiS4/Q9IiIiIiIiIiK65FgpRURERERERERElxxDKSIiIiIiIiIiuuQYShERERERERER0SWnDfQAgoEkSfjvv/8QFRUFQRACPRwiIiIiIiIiopAlyzLy8vKQlJQEUXRfD8VQCsB///2H5OTkQA+DiIiIiIiIiKjaOHbsGOrVq+f2coZSAKKiogAUH6zo6Gh1u9VqxerVq9GtWzfodLpADY88wHMVOniuQgPPU+jguQoNPE+hg+cqNBQUFCApKQkAcOTIEcTGxgZ2QOQWf6ZCB89VaAiV85Sbm4vk5GQ1b3GHoRSgTtmLjo4uF0qFh4cjOjo6qE828VyFEp6r0MDzFDp4rkIDz1Po4LkKDUajER9++CH+/PNP1KxZE+Hh4YEeErnBn6nQwXMVGkLtPFXWIomNzomIiIiIKKTodDo88sgjSEtLC4k/yoiIyDWGUkREREREREREdMkxlCIiIiIiopBis9mQkZGB7du3w2azBXo4RERURewpRUREREREIcVsNuPuu+8GAIwcORJGozGwA6LLhiRJsFgsgR6GX1itVmi1WhQVFcFutwd6OORGsJwnnU4HjUZz0bfDUIqIiIiIiIioEhaLBYcPH4YkSYEeil/IsozExEQcO3as0ubUFDjBdJ5iY2ORmJh4UeNgKEVERERERERUAVmWcfLkSWg0GiQnJ0MUq18nHEmSkJ+fj8jIyGr5+KqLYDhPsiyjsLAQWVlZAIA6depU+bYYShERERERERFVwGazobCwEElJSQgPDw/0cPxCmZoYFhbGUCqIBct5UqZNZ2VlISEhocpT+fhMIyIiIiIiIqqA0rtHr9cHeCREwUMJaK1Wa5Vvg6EUERERERERkQcC3cOHKJj44ueBoRQREREREREREV1yDKWIiIiIiCik6PV6TJs2DY8//jinUxH5SOPGjTF79uxAD8NnGjZsiPfeey/Qw6BKMJQiIiIiIqKQotPp8NRTT6FHjx7Q6XSBHg6RxyRJxqEz+fjz2AUcOpMPSZIvyf0eO3YMAwcORFJSEvR6PRo0aIBhw4bh3Llzl+T+idzh6nsU8iRJxuGzBTiSDxw+W4AmtWMgipzrTUREREREwWP3iRx8sfM4Dmblw2yVYNCJaJIQid6t6yGlbozf7vfQoUNo164dmjVrhqVLl6JRo0bYs2cPnn/+eXz//ffYunUr4uLi/Hb/7tjtdgiCwJX+LnM8+xTSdp/IwWvf7cX/Vv6NrzNF/G/l33jtu73YfSIn0EMjIiIiIj+x2+3YuHEjdu3apa6KRhTMdp/IwfR1B7DreA5ijXo0rBmBWKMeu44Xb/fn3y9DhgyBXq/H6tWr0alTJ9SvXx+33XYb1q5dixMnTmDs2LHqvvn5+ejXrx8iIyORlJSEGTNmON3WhAkTUL9+fRgMBiQlJWHo0KHqZRaLBaNHj0bdunURERGBtm3bYsOGDerlCxcuRGxsLFauXIkWLVrAYDBg3rx5CAsLw4ULF5zuZ+jQoejUqZP6/S+//IKOHTvCaDQiOTkZQ4cORUFBgXp5VlYWevbsCaPRiEaNGmHx4sU+OnrkbwylKGQ5/mKPCdehVhgQE667JL/YiYiIiChwioqKkJ6ejldeeQVFRUWBHg5dhmRZhtlm9+ifyWLD59uP4VyBGY1rhiNcL0KAjHC9iMY1w3GuwIz/23EMJovNo9uTZc+n/J0/fx4//PADnn76aRiNRqfLEhMT0a9fP3z22Wfqbc6YMQOtWrXCzp07MWbMGDz33HNYs2YNAGD58uWYOnUqPvjgAxw4cABfffUVWrZsqd7eo48+is2bN2PZsmX466+/cN999+HWW2/FgQMH1H0KCwsxadIkfPjhh9izZw8eeughxMbG4osvvlD3sdvt+Pzzz9GvXz8AwK5du9C9e3f06tULf/31Fz777DNs2rQJzzzzjHqdAQMGIDMzE+vXr8fy5csxa9YsZGVleXFGKVA4fY9CkiTJ+GLncZwvsKBJQiRkWcJ5AYg0aBGVoMPBrHx8ufMEWtSJ5lQ+IiIiIiLyKYtdwoRv9nq0b67Jih1HsqHXirhQaCt3udUu4Yfdp3E2z4JoY+U90ibc2QIGrcaj+z5w4ABkWUbz5s1dXt68eXNkZ2fjzJkzAIAbbrgBL7zwAkRRRLNmzbB582ZMnToV6enpOHr0KBITE9G1a1fodDrUr18fN9xwAwDg33//xdKlS3H8+HEkJSUBAEaNGoVVq1ZhwYIFmDhxYvFjtVoxa9YsXHPNNeoY7r//fixZsgQDBw4EAKxbtw7Z2dm47777AABvvfUW+vbti+HDhwMAmjZtiunTp6NTp06YPXs2jh49qk5DbNu2LQBg/vz5bh8zBRdWSlFIyjxXgINZ+agTY4QgAPtP5eO/QgCQIQgC6sQYcSArD5nnCiq7KSIiIiIiIr+x2iXYJRlaNx+Wa0QBdkmG1S5d4pFBrZAShOKxKSGTol27dti3bx8A4L777oPJZELjxo0xePBgrFixAjZbcci2c+dOyLKMZs2aITIyUv23ceNG/Pvvv+rt6fV6tGrVyuk++vXrhw0bNuC///4DACxevBg9evRAjRo1AAA7duzAwoULnW63e/fukCQJhw8fxr59+6DVanHdddept3nVVVchNjbWh0eK/IWVUhSS8opsMFslGGM0sEsycotsKLIV/zIXRcCo1+B0roS8ovKfRBAREREREV0MvUbEhDtbeLTv4bMFeG3lXsQadYg0lP8TPN9swwWTFSO6NUOjmhEe3benmjRpAkEQsHfvXtx9993lLv/7779Ro0YN1KxZ0+1tKIFVcnIy9u/fjzVr1mDt2rV4+umn8dZbb2Hjxo2QJAkajQY7duyARuNcxRUZGal+bTQa1dtT3HDDDbjiiiuwbNkyPPXUU1ixYgUWLFigXi5JEp544gmn/lWK+vXrY//+/U7jpNDCUIpCUlSYFgadCJPFjjB96S9lZXq1yWKHQSciKoxPcSIiIiIi8i1BEDyeQtcsIQrNakdh1/EcRCXonMITWZZxOteMVvVi0SwhyuetR+Lj45Geno5Zs2bhueeec+orderUKSxevBiPPPKIOqZt27Y5XX/r1q246qqr1O+NRiPuvPNO3HnnnRgyZAiuuuoq7Nq1C6mpqbDb7cjKykKHDh28Hmffvn2xePFi1KtXD6Io4vbbb1cva926Nfbs2YMmTZq4vG7z5s1hs9mwfft2tdJr//795ZqnU3Di9D0KSQ3jI9AkIRInc0yw20sb/cly8S/2kzkmNE2IQsP4yj9pICIiIiIi8hdRFNC7dT3ERehxMCsf+UU22CUZ+UU2HMzKR1yEHr1a1/VbL9yZM2fCbDaje/fu+Omnn3Ds2DGsWrUK6enpqFu3Lt544w11319//RVvvfUW/vnnH7z//vv4v//7PwwbNgxA8ep58+fPx+7du3Ho0CF88sknMBqNaNCgAZo1a4Z+/frhkUcewZdffonDhw9j27ZtmDx5MjIyMiodY79+/bBz50688cYbuPfeexEWFqZe9sILL2DLli0YMmQI/vjjDxw4cADffPMNnn32WQDAlVdeiVtvvRWDBw/Gr7/+ih07dmDQoEHlGrtTcGIoRSHJ8Rf7obMFsNolyDKQb7Zekl/sREREREREnkqpG4OhaU3Rsl4MLpgsyDxbgAsmC1rVi8XQtKZIqRvjt/tu2rQptm/fjiuuuAL3338/rrjiCjz++OPo0qULtmzZgri4OHXfZ555Bjt27EBqaipee+01vPPOO+jevTsAIDY2FvPmzcNNN92EVq1aYd26dfj2228RHx8PAFiwYAEeeeQRjBw5EldeeSXuvPNO/Prrr0hOTvZojNdffz3++usvddU9RatWrbBx40YcOHAAHTp0QGpqKl555RXUqVNH3WfBggVITk5Gp06d0KtXLzz++ONISEjwxeEjP+PcJgpZyi/2T7cewY/7TSiSgAsmG1rVi0Wv1nX9+oudiIiIiAJHp9Nh0qRJ+Pvvv6HTVb5aGVEwSKkbgxZ1opF5rgB5RTZEhWnRMD7iknyQ3qBBA6c+Ta4cOnQIubm5iI6OhiiWr1+5++67XfalUuh0Orz66qt49dVXXV4+YMAADBgwwO31f/vtN7eXXX/99Vi9erXbyxMTE7Fy5UqnbQ8//LDb/Sl4MJSikKYEU7kmC46dOInhaVfgxisSWCFFREREVI3p9XqMHDkSGRkZ0Ov1gR4OkcdEUUDjWpGV70h0meD0PQp5kiwjKkyHKB1QN9bIQIqIiIiIiIgoBDCUopBnl0obndscviYiIiKi6slut2P79u04cOAA7HZ7oIdDRERVxOl7FPIcQylJZihFREREVN0VFRWhffv2AIBBgwY5rdRFREShg5VSFPKcKqXsDKWIiIiIiIiIQgFDKQp5NlZKEREREREREYUchlIU8thTioiIiIiIiCj0MJSikOcYStkZShERERERERGFBIZSFPJskqR+zVCKiIiIiIiIKDQwlKKQZ5ccv2YoRUREREREdKlNmDAB1157rfr9gAEDcPfdd1/ycWRmZkIQBPzxxx8V7rd//34kJiYiLy/Pb2Mxm82oX78+duzY4bf7CHUMpSjkOVVKsdE5ERERUbWn0+nw8ssv4/7774dOpwv0cIiC1oABAyAIAgRBgE6nQ+PGjTFq1CgUFBT4/b6nTZuGhQsXerSvp0GSL40dOxZDhgxBVFQUAGDDhg0QBAEXLlxwOm7u/gFAVlYWnnjiCdSvXx8GgwGJiYno3r07tmzZAgAwGAwYNWoUXnjhhUv2uEINQykKeewpRURERHR50ev1GDduHB588EHo9fpAD4coqN166604efIkDh06hNdffx2zZs3CqFGjXO5rtVp9dr8xMTGIjY312e350vHjx/HNN9/g0UcfdXn5tGnTcPLkSfUfACxYsKDctt69e+PPP//EokWL8M8//+Cbb75B586dcf78efW2+vXrh59//hn79u3z/wMLQQylKOTZuPoeERERERGRS0oFT3JyMvr27Yt+/frhq6++AlA65e6jjz5CkyZNULt2bciyjJycHDz++ONISEhAdHQ0brnlFvz5559Ot/vmm2+idu3aiIqKwsCBA1FUVOR0ednpe5IkYfLkyWjSpAkMBgPq16+PN954AwDQqFEjAEBqaioEQUDnzp3V6y1YsADNmzdHWFgYrrrqKsyaNcvpfn777TekpqYiLCwM1113HX7//fdKj8nnn3+Oa665BvXq1XN5eUxMDBITE9V/ABAbG+u07cKFC9i0aRMmT56MLl26oEGDBrjhhhswZswY3H777eptxcfHo3379li6dGml47ocaQM9AKKLZbeXBlESQykiIiKiak+SJOzZswdHjx6F5NDKgeiSq2ganEYDhIV5tq8oAkZj5ftGRHg3PheMRqNTRdTBgwfx+eef4//+7/9gMpkAALfffjvi4uKQkZGBmJgYfPDBB0hLS8M///yDuLg4fP755xg/fjzef/99dOjQAZ988gmmT5+Oxo0bu73fMWPGYN68eZg6dSpuvvlmnDx5En///TeA4mDphhtuwNq1a3H11VerFZDz5s3D+PHjMXPmTKSmpuL333/H4MGDERERgf79+6OgoAB33HEHbrnlFnz66ac4fPgwhg0bVukx+Omnn3DdddddzGFEZGQkIiMj8dVXX+HGG2+EwWBwu+8NN9yAn3/++aLur7piKEUhz7GPFCuliIiIiKo/k8mE1NRUAMDDDz9c4R+DRH4VGen+sh49gO++K/0+IQEoLHS9b6dOwIYNpd83bAicPVt+v4vsofvbb79hyZIlSEtLU7dZLBZ88skniI+PR25uLn788Ufs2rULWVlZ6s/W22+/ja+++grLly/H448/jvfeew+PPfYYBg0aBAB4/fXXsXbt2nLVUoq8vDxMmzYNM2fORP/+/QEAV1xxBW6++WYAQK1atQAUVxUplUkA8Nprr+Gdd95Br169ABRXVO3duxcffPAB+vfvj8WLF8Nut+Ojjz5CeHg4rr76ahw/fhxPPfVUhcchMzMTbdq0qcohVGm1WixcuBCDBw/GnDlz0Lp1a3Tq1AkPPPAAWrVq5bRv3bp1kZmZeVH3V11x+h6FPMc+UvygjIiIiIiIqNTKlSsRGRmJsLAwtGvXDh07dsSMGTPUyxs0aKCGQgCwc+dO5OfnIz4+Xq0GioyMxOHDh/Hvv/8CAPbt24d27do53U/Z7x3t27cPZrPZKQyrzJkzZ3Ds2DEMHDjQaRyvv/660ziuueYahIeHezQOhclkQphjFVsV9e7dG//99x+++eYbdO/eHRs2bEDr1q3LNXg3Go0odBdIXuZYKUUhz7mnFFMpIiIiIiK6RPLz3V+m0Th/n5Xlfl+xTL2ID6tqunTpgtmzZ0On0yEpKancipURZaYESpKEOnXqYINj5VaJqjYuNzpOTfSQMjV33rx5aNu2rdNlmpJjK1excqxmzZrIzs6u0nXLCgsLQ3p6OtLT0zFu3DgMGjQI48ePx4ABA9R9zp8/7xT8USmGUhTy7A5BFGfvERERERHRJeNNjyd/7VvpTUWgSZMmHu+fmpqKU6dOQavVomHDhi73ad68ObZu3YpHHnlE3bZ161a3t9m0aVMYjUasW7dOnfLnSOkhZbfb1W21a9dG3bp1cejQIfTr18/l7bZo0QKffPIJTCaTGnxVNA7Hx7h3795K96uKFi1aqI3kFbt371anHJMzTt+jkGezs6cUERERERGRL3Tt2hXt2rXD3XffjR9++AGZmZn45Zdf8PLLL2P79u0AgGHDhuGjjz7CRx99hH/++Qfjx4/Hnj173N5mWFgYXnjhBYwePRoff/wx/v33X2zduhXz588HACQkJMBoNGLVqlU4ffo0cnJyABSvDjhp0iRMmzYN//zzD3bt2oUFCxbg3XffBQD07dsXoihi4MCB2Lt3LzIyMvD2229X+hi7d++OLVu2OIVg3jp37pzaYP2vv/7C4cOH8X//93+YMmUK7rrrLqd9f/75Z3Tr1q3K91WdMZSikOfcU4qhFBERERERUVUJgoCMjAx07NgRjz32GJo1a4YHHngAmZmZqF27NgDg/vvvx7hx4/DCCy+gTZs2OHLkSKXNxV955RWMHDkS48aNQ/PmzXH//fcjq2RKo1arxfTp0/HBBx8gKSlJDXUGDRqEDz/8EAsXLkTLli3RqVMnLFy4EI0aNQJQvALet99+i7179yI1NRVjx47F5MmTK32MPXr0gE6nw9q1a6t8nCIjI9G2bVtMnToVHTt2REpKCl555RUMHjwYM2fOVPfbsmULcnJycO+991b5vqozQa7qJMxqJDc3FzExMcjJyUF0dLS63Wq1IiMjQ33CUnBa/OsR/HXsAo4dPYo72rdE3xsbBnpIVAH+XIUGnqfQwXMVGnieQgfPVWgoKChAZMmqZ9nZ2VXuc0P+V11+poqKinD48GE0atTIJw2yg5EkScjNzUV0dDTEsj2uqqFZs2bh66+/xg8//ODX+7nvvvuQmpqKl156ySe3F0znqaKfC3c5S1nsKUUhz6lSihkrERERUbWn0+kwYsQIHDp0KKSDDiIKnMcffxzZ2dnIy8tDVFSUX+7DbDbjmmuuwXPPPeeX268OGEpRyGNPKSIiIqLLi16vx5tvvomMjAy1QTIRkTe0Wi3Gjh3r1/swGAx4+eWX/Xofoa761+RRtedYKWVnKEVEREREREQUEhhKUcizMZQiIiIiuqxIkoTMzEycPn0akiQFejhERFRFnL5HIc+xjxRDKSIiIqLqz2QyoVmzZgCAPn36wGAwBHhERERUFayUopBntZd+OsZQioiIiIiIiCg0MJSikCdx+h4RERERERFRyAmaUGrSpEkQBAHDhw9Xt8myjAkTJiApKQlGoxGdO3fGnj17nK5nNpvx7LPPombNmoiIiMCdd96J48ePX+LRUyCxpxQRERERERFR6AmKUGrbtm2YO3cuWrVq5bR9ypQpePfddzFz5kxs27YNiYmJSE9PR15enrrP8OHDsWLFCixbtgybNm1Cfn4+7rjjDtjt9kv9MChAnFbfkxlKEREREREREYWCgIdS+fn56NevH+bNm4caNWqo22VZxnvvvYexY8eiV69eSElJwaJFi1BYWIglS5YAAHJycjB//ny888476Nq1K1JTU/Hpp59i165dWLt2baAeEl1irJQiIiIiIiLyvQ0bNkAQBFy4cAEAsHDhQsTGxgZ0TAAwYcIEXHvttYEexkWxWCxo0qQJNm/eHOihuDRq1CgMHTrU7/cT8FBqyJAhuP3229G1a1en7YcPH8apU6fQrVs3dZvBYECnTp3wyy+/AAB27NgBq9XqtE9SUhJSUlLUfaj6szOUIiIiIiIiKmfAgAEQBAGCIECn06Fx48YYNWoUCgoKqnR7999/P/755x8fj7K8L774Ap07d0ZMTAwiIyPRqlUr/O9//8P58+f9ft+Xyty5c9GgQQPcdNNNAIDMzEwMHDgQjRo1gtFoxBVXXIHx48fDYrE4Xe/o0aN44IEHEBUVhZo1a2Lo0KFO+2zYsAF33XUX6tSpg4iICFx77bVYvHix022cPHkSffv2xZVXXglRFJ3aKClGjx6NBQsW4PDhw75/8A60fr31Sixbtgw7d+7Etm3byl126tQpAEDt2rWdtteuXRtHjhxR99Hr9U4VVso+yvVdMZvNMJvN6ve5ubkAAKvVCqvVqm5XvnbcRsHHarNDkopX4LPY7DxfQY4/V6GB5yl08FyFBp6n0MFzFRpkWcbjjz+OY8eOQZZlnq8gVl1+pqxWK2RZhiRJ6t8eoUCWZXTv3h0fffQRrFYrfv75Zzz++OPIz8/HrFmzyu2r/K88Rsf/JUmCwWCAwWDw6zF4+eWXMWXKFAwfPhyvv/46kpKScODAAXzwwQf4+OOPMXToUHWsoXQuypoxYwbGjRunPoa9e/fCbrdj9uzZaNKkCXbv3o0nnngC+fn5eOuttwAAdrsdPXv2RI0aNbBx40acP38ejz76KCRJwvTp0wEAmzdvRsuWLfH888+jdu3ayMjIwCOPPILIyEj07NkTAGAymVCzZk2MGTMG06ZNczrnipo1ayI9PR2zZ8/Gm2++6fIxSJKk/g7WaDROl3n6Mx+wUOrYsWMYNmwYVq9ejbCwMLf7CYLg9L0sy+W2lVXZPpMmTcKrr75abvvq1asRHh5ebvuaNWsqvD8KHFkGDmeWFvwdzjyCjAz/JrnkG/y5Cg08T6GD5yo08DyFDp6r4NejRw8AwE8//RTgkZAnQv1nSqvVIjExEfn5+eUqV4KZEhYof+fecccduO+++/DVV1/hzTffhNlsxrhx4/Dll18iLy8P1157LSZOnIjWrVsDAAoLCwEAeXl5EEURS5YswZgxY9RCEQDIyMjAW2+9hX379iEiIgLt27fHJ598gilTpuCrr74qN4upc+fO6NatG1566aVy492xYwcmTZqESZMm4cknn1S3t23bFm3btkVOTg5yc3NhNptht9sxd+5cTJw4ERcuXEDXrl0xbdo0REVFAQDWrl2Lt99+G/v27YNGo8H111+PN998E40aNQJQXHF0zTXX4OOPP8bcuXOxY8cONG7cGO+++y5uuOEG9b4XLVqEKVOmIDs7G7fccgvatWuHKVOmOB2D77//HpMnT8bff/+NxMREPPjggxg5ciS0WteRy59//omDBw+iQ4cOapFM+/bt0b59e6fjNGTIEHz00Ud45ZVXABT/HO3duxe7d+9GnTp1AAD/+9//MGTIEIwePRrR0dEYMmSI0331798f3333Hf7v//4PnTp1AgDExcXhf//7HwDgww8/hMViUcfhKD09HW+88YbLcwUUT0E0mUz46aefYLPZnC5TnjuVCVgotWPHDmRlZaFNmzbqNrvdjp9++gkzZ87E/v37ARRXQykHGwCysrLU6qnExERYLBZkZ2c7VUtlZWU5ncyyxowZgxEjRqjf5+bmIjk5Gd26dUN0dLS63Wq1Ys2aNUhPT4dOp7v4B00+Z7NL2LLyb0iShBPHj6NecjJ69Lg60MOiCvDnKjTwPIUOnqvQwPMUOniuQgfPVWioLuepqKgIx44dQ2RkpFNRRUXT4DQajcf7iqIIo9FY6b4RERHeDBs6nQ5ardbp79zo6GjYbDZER0dj+PDhWLlyJRYuXIj69etj0qRJuPfee/HPP/8gLi5ODbOioqIQHR2NsLAwCIKg3t53332HRx55BC+99BI+/fRTWCwWZGRkIDo6Gk8++SQmT56M/fv34/rrrwcA/PXXX/jrr7+wfPlypzEpvv76a0RGRuK5555z+XxRrmMwGJCZmYnVq1dj5cqVyM7OxgMPPIDZs2fj9ddfB1BcrDJq1Ci0bNkSBQUFGD9+PPr374+dO3dCFEVERkYCACZOnIgpU6agadOmePnll/H444/jn3/+gVarxebNmzFixAi8+eab6NmzJ9atW4dx48Y5HYMffvgBTz75JN577z106NAB//77L5588kkYDAaMGzfO5XnZuXMnmjVrhnr16lV4/sxmM2rWrKne119//YWUlBTUqVMHUVFREAQBd999NwYNGoQDBw6gS5cuLm+nsLAQtWvXdnnMtVot9Hq9y8s6duyIp59+GtnZ2WjQoEG5y4uKimA0GtGxY8dyxUauQi5XAhZKpaWlYdeuXU7bHn30UVx11VV44YUX0LhxYyQmJmLNmjVITU0FUJzCbdy4EZMnTwYAtGnTBjqdDmvWrEGfPn0AFM+N3L17N6ZMmeL2vpWSw7J0Op3LJ7677RR4kmCHKJZWSkkQeK5CBH+uQgPPU+jguQoNPE+hg+cquMmyjDNnziAnJwdarZbnKgSE+s+U3W6HIAgQRdHp7w9Xf8grevToge+++079PjEx0W31SKdOnbBhwwb1+8aNG+Ps2bPl9pO9XG1c6SeljPm3337D0qVLkZaWBpPJhDlz5mDhwoW4/fbbIUkSpk2bhmuvvRYLFizA888/r15PedyO3wPFs5AeeOABteoGgPr3e/369dG9e3csWrQIbdu2BVBcddSpUyc0adLE5XgPHjyIxo0bu/x7vezjkiQJixYtUiujHn74Yaxfv14d23333ed0nY8++ggJCQn4+++/kZKSou43atQodVrb//73P1x99dU4dOgQrrrqKrz//vu47bbb8PzzzwMArrrqKmzZsgUrV650OgYvvvgiHn30UQBAkyZN8Nprr2H06NGYMGGCy/EfOXIESUlJTs+lsv7991/MnDkT77zzjrrf6dOnkZCQoB4DURQRHx8PvV6PrKwsl7e3fPlybNu2DR988IHb+3N8jjhKTk4GUFxVplSYORJFUe1XVvbn29Of94A1Oo+KikJKSorTv4iICMTHxyMlJQWCIGD48OGYOHEiVqxYgd27d2PAgAEIDw9H3759AQAxMTEYOHAgRo4ciXXr1uH333/HQw89hJYtW5ZrnE7VU9nG5rIMSGx2TkRERFStFRYWom7duujfv7/HU0SILlcrV65UK7zatWuHjh07YsaMGfj3339htVrVRttAcZBw/fXXY9++fR7d9h9//IG0tDS3lw8ePBhLly5FUVERrFYrFi9ejMcee8zt/p6061E0bNhQDaQAoE6dOsjKylK///fff9G3b180btwY0dHRTtP2HLVq1crpNgCot7N//36nqXwAyn2/Y8cO/O9//0NkZKT6b/DgwTh58qTb308mk6nCNkb//fcfbr31Vtx3330YNGiQ02Wujo+747ZhwwYMGDAA8+bNw9VXez+jSKne8+fv2YA2Oq/M6NGjYTKZ1HKxtm3bYvXq1U5PvKlTp0Kr1aJPnz4wmUxIS0vDwoULyzXZourJ5iKAsssyRHj2i4yIiIiIiKiq8vPz3V5W9m9Sx8CkrLJVKpmZmRc1LkddunTB7NmzodPpkJSUpFawnDx5EkDV+jgrHKccutKzZ08YDAasWLECBoMBZrMZvXv3drt/s2bNsGnTJlit1korbcperlRPOd53cnIy5s2bh6SkJEiShJSUlHI9wRxvR3ncyu24OhZlq9UkScKrr76KXr16lRuju+CpZs2a5WaOKf777z906dIF7dq1w9y5c50uS0xMxK+//uq0LTs7G1artdwicRs3bkTPnj3x7rvv4pFHHnF5X5VRVjusVatWla7viaAKpRzLFYHiJ8SECRPclrwBxSd5xowZmDFjhn8HR0HJbi/+heD4e8IuydAxkyQiIiIiIj/zpseTv/b15LZcTZdr0qQJ9Ho9Nm3apM5Gslqt2LFjB4YPH+7Rbbdq1Qrr1q1Tp66VpdVq0b9/fyxYsAAGgwEPPPCAy8XFFH379sX06dMxa9YsDBs2rNzlFy5cQGxsbKXjOnfuHPbt24cPPvgAHTp0AABs2rTJo8fk6KqrrsJvv/3mtG379u1O37du3Rr79+93OyXRldTUVMyePbtc6HXixAl06dIFbdq0wYIFC8qFle3atcMbb7yBU6dOqVNHV69eDYPB4NSve8OGDbjjjjswefJkPP744x6Pq6zdu3dDp9NVqcrKU0EVShF5S6mU0mtKf1jLTukjIiIiIiIiZxEREXjqqafw/PPPIy4uDvXq1cPEiRNRWFiIgQMHenQb48ePR1paGq644go88MADsNls+P777zF69Gh1n0GDBqF58+YAgM2bN1d4e23btsXo0aMxcuRInDhxAvfccw+SkpJw8OBBzJkzBzfffLPLsKqsGjVqID4+HnPnzkWdOnVw9OhRvPjiix49JkfPPvssOnbsiHfffRc9e/bE+vXr8f333zsFSePGjcMdd9yB5ORk3HfffRBFEX/99Rd27dqlNl0vq0uXLigoKMCePXuQkpICoLhCqnPnzqhfvz7efvttnDlzRt0/MTERANCtWze0aNECTz75JN555x1cuHABo0aNwuDBg9WQasOGDbj99tsxbNgw9O7dG6dOnQIA6PV6xMXFqbf5xx9/ACiu9jtz5gz++OMP6PV6tGjRQt3n559/RocOHSqtiLsYAespReQLUknppE4jqNVSrqb0ERERERERkbM333wTvXv3xsMPP4zrrrsOhw4dwvfff++0un1FOnfujP/7v//DN998g2uvvRa33HJLuellTZs2Rfv27XHllVeqDc8rMnnyZCxZsgS//vorunfvjquvvhojRoxAq1at0L9/f4/GJYoili1bhh07diAlJQXPPfcc3nrrLY+u6+imm27CnDlz8O677+Kaa67BqlWr8NxzzzlNy+vevTtWrlyJNWvW4Prrr8eNN96Id9991+VqdYr4+Hj06tULixcvVretXr0aBw8exPr161GvXj3UqVNH/afQaDT49ttvYTAY0KFDB/Tp0wd333033n77bXWfhQsXorCwEJMmTXK6jbLTC1NTU5GamoodO3ZgyZIlSE1NRY8ePZz2Wbp0KQYPHuz1cfOGIHvbvr8ays3NRUxMDHJycpxWT7BarcjIyECPHj1CeqWI6uzEBRNmrj+IKIOIfQcOIalefbx4W3PUiNAHemjkBn+uQgPPU+jguQoNPE+hg+cqNBQUFKjLuWdnZ3s0nYcCo7r8TBUVFeHw4cNo1KhRhQ2qQ5kkScjNzUV0dHSFq8J5S5ZlXHXVVXjiiScwYsQIn91uoAwePBh///03fv7554u6nV27dqFr1644ePCgU9/syvjrPJX13Xff4fnnn8dff/0Frdb1JLuKfi7c5SxlcfoehTSlp5RGENSyP1ZKERERERERBV5WVhY++eQTnDhxwm3fqWD39ttvIz09HREREfj++++xaNEizJo166Jvt2XLlpgyZQoyMzPRsmVLH4zUtwoKCrBgwQK3gZSvMJSikGYrWRVBIwoQS6bvSSz+IyIiIqrWtFotHn74YRw/ftzvfzARUdXVrl0bNWvWxNy5cz2eEhhsfvvtN0yZMgV5eXlo3Lgxpk+fjkGDBvnktj2djhgIffr0uST3w9/gFNKUAMoxlGKlFBEREVH1ZjAYMH/+fGRkZMBgMAR6OETkRnXoFvT5558HegjVGhudU0izlkzf0zqEUsqUPiIiIiIiIiIKXgylKKTZS6qiNJrSnlL2apDGExEREZF7siyjoKAARUVF1aISg4jocsXpexTSlFBKK4oQBblkmxTIIRERERGRnxUWFqr9abKzs6HXc+VlujQYghKVknzwtzdDKQppSv8oUUDp9D1mUkRERERE5EM6nQ6CIODMmTOoVasWBEEI9JB8TpIkWCwWFBUVQRQ5qSpYBcN5kmUZFosFZ86cgSiKF/XBAEMpCmmllVKOjc6ZShERERERke9oNBrUq1cPx48fR2ZmZqCH4xeyLMNkMsFoNFbL0K26CKbzFB4ejvr1619UOMZQikKaEkBpRNGhUooltURERERE5FuRkZFo2rQprFZroIfiF1arFT/99BM6duwInU4X6OGQG8FynjQaDbRa7UUHYwylKKQpRVEax9X3GEoREREREZEfaDQaaDSaQA/DLzQaDWw2G8LCwhhKBbHqdp44UZRCmlIppRUdVt9jKEVEREREREQU9BhKUUhTAiiRlVJEREREREREIYXT9yikKavv6RhKEREREV02NBoNevXqhVOnTlXbqVRERJcDhlIU0spWSkkoDaqIiIiIqHoKCwvDsmXLkJGRgbCwsEAPh4iIqojT9yikKQGU1rFSSmYoRURERERERBTsGEpRSJNKQimNY6NzO0MpIiIiIiIiomDH6XsU0hwrpTSslCIiIiK6LBQUFCAyMhIAkJ2djdjY2MAOiIiIqoSVUhTS7JIEoLinlFASSknsKUVEREREREQU9BhKUUhzVSnFRudEREREREREwY+hFIU0u0NPKaVSys5QioiIiIiIiCjoMZSikOYYSmnKbCMiIiIiIiKi4MVQikKazV46fY+VUkREREREREShg6EUhTRlpT1R4Op7RERERERERKFEG+gBEF0MpSpKpxEgCMVfs9E5ERERUfWm0Whw2223ISsrCxqNpvIrEBFRUGIoRSFNmb7nVClllwI4IiIiIiLyt7CwMHz99dfIyMhAWFhYoIdDRERVxOl7FNLsUnEApdUIEJRtLJQiIiIiIiIiCnoMpSikKf2jNKJDpZTESikiIiIiIiKiYMfpexTSlP5RWlGEqIZSARwQEREREfldQUEBEhISYLfbcerUKcTGxgZ6SEREVAUMpSik2e2llVICK6WIiIiILhuFhYWBHgIREV0kTt+jkKZUSmkEqNP3uPoeERERERERUfBjKEUhza6EUqKoNjqXGEoRERERERERBT2GUhSyZFl22eiclVJEREREREREwY+hFIUsSQZKMiloRaG00bnMUIqIiIiIiIgo2DGUopBlc2hoLjqGUnaGUkRERERERETBjqvvUchyXGRP5xBKcfoeERERUfUmiiI6duyIc+fOQRT5OTsRUahiKEUhS6mUEoTif8rbEYnT94iIiIiqNaPRiLVr1yIjIwNGozHQwyEioirixwoUspSV97SiAEFgpRQRERERERFRKGEoRSFLCZ9EQSj5v3i7LAMSgykiIiIiIiKioMbpexSyHCulgNJQCihegU+E4OpqRERERBTiCgoK0LBhQ1gsFhw5cgSxsbGBHhIREVUBQykKWUoopdG4CKUkGTpNIEZFRERERJfC2bNnAz0EIiK6SJy+RyHLZi9TKeVwmZ3T94iIiIiIiIiCGkMpCln2klX2NCU9pQQBbHZOREREREREFCIYSlHIsksSAECrKX0aa0pSKTY6JyIiIiIiIgpuDKUoZCnVUBqHZlLK16yUIiIiIiIiIgpuDKUoZCk9pRxDKaW/lCQzlCIiIiIiIiIKZlx9j0KW0sxc6xBKiYIAQGalFBEREVE1Jooi2rRpg5ycHIgiP2cnIgpVDKUoZKmNzl1UStntDKWIiIiIqiuj0YgtW7YgIyMDRqMx0MMhIqIq4scKFLJcVkopoRSn7xEREREREREFNYZSFLKUnlKii0bnysp8RERERERERBScOH2PQparSil1+h4zKSIiIqJqq7CwEC1atEBhYSEOHDiAmJiYQA+JiIiqgKEUhSxbSTWUxqG5ZXGj89LLiIiIiKj6kWUZR44cUb8mIqLQxOl7FLJcVkppBKfLiIiIiIiIiCg4MZSikKUET46r7ymVUgyliIiIiIiIiIIbQykKWRX3lGIoRURERERERBTMGEpRyLJJFa2+x1CKiIiIiIiIKJgxlKKQ5apSiqEUERERERERUWjg6nsUsmwuekopX9sYShERERFVW4IgoHnz5sjPz4cgCJVfgYiIghJDKQpZklopVVrwp1EanXNpYCIiIqJqKzw8HH/++ScyMjIQHh4e6OEQEVEVcfoehSyrJAFwXSlltzOUIiIiIiIiIgpmDKUoZEkupu+pq++xUoqIiIiIiIgoqHk1fU+WZWzcuBE///wzMjMzUVhYiFq1aiE1NRVdu3ZFcnKyv8ZJVI7SN0qrKQ2llJX4JPaUIiIiIqq2CgsLcd111yE/Px+dO3dGTExMoIdERERV4FGllMlkwsSJE5GcnIzbbrsN3333HS5cuACNRoODBw9i/PjxaNSoEXr06IGtW7f6e8xEAEpX2NMI5Sul2OiciIiIqPqSZRn79u3DsWPHILNCnogoZHlUKdWsWTO0bdsWc+bMQffu3aHT6crtc+TIESxZsgT3338/Xn75ZQwePNjngyVy5Gr1PaVSys5QioiIiIiIiCioeRRKff/990hJSalwnwYNGmDMmDEYOXIkjhw54pPBEVXE7mL6nvIlQykiIiIiIiKi4ObR9L3KAilHer0eTZs2rfKAiDylhlJOq++JTpcRERERERERUXDyevW9VatWYdOmTer377//Pq699lr07dsX2dnZPh0cUUWU6Xuii55SXH2PiIiIiIiIKLh5HUo9//zzyM3NBQDs2rULI0eORI8ePXDo0CGMGDHC5wMkcscuSQAArVj6NFa+ZKNzIiIiIiIiouDmUU8pR4cPH0aLFi0AAF988QXuuOMOTJw4ETt37kSPHj18PkAid9RG5xrHSqmS6Xt2KSBjIiIiIiL/EwQBDRo0QGFhIQSHqnkiIgotXodSer0ehYWFAIC1a9fikUceAQDExcWpFVREl4LkoqeU8qWdhVJERERE1VZ4eDgOHDiAjIwMhIeHB3o4RERURV6HUjfffDNGjBiBm266Cb/99hs+++wzAMA///yDevXq+XyARO5YS5InjeiiUkpipRQRERERERFRMPO6p9TMmTOh1WqxfPlyzJ49G3Xr1gUAfP/997j11lt9PkAid6SSZuYawXH1vZJG58ykiIiIiIiIiIKa15VS9evXx8qVK8ttnzp1qk8GROQppaeUVuMYShX/z0opIiIiourLZDKhQ4cOyMnJQZcuXaDT6QI9JCIiqgKvK6U6d+6Mjz/+GCaTyR/jIfKIJMkoKZRymr6nKZm+x9X3iIiIiKovSZKwY8cOHDx4EBI/jCQiClleh1Jt2rTB6NGjkZiYiMGDB2Pr1q3+GBdRhRxDJ+dQqvh/iaEUERERERERUVDzOpR65513cOLECXz88cc4c+YMOnbsiBYtWuDtt9/G6dOn/TFGonLsDqGT0twcKA2oWClFREREREREFNy8DqUAQKPR4K677sJXX32FEydOoG/fvnjllVeQnJyMu+++G+vXr/fodmbPno1WrVohOjoa0dHRaNeuHb7//nv1clmWMWHCBCQlJcFoNKJz587Ys2eP022YzWY8++yzqFmzJiIiInDnnXfi+PHjVXlYFEJsDmXaDoVSpavvyQyliIiIiIiIiIJZlUIpxW+//YZx48bh7bffRkJCAsaMGYOEhAT07NkTo0aNqvT69erVw5tvvont27dj+/btuOWWW3DXXXepwdOUKVPw7rvvYubMmdi2bRsSExORnp6OvLw89TaGDx+OFStWYNmyZdi0aRPy8/Nxxx13wG63X8xDoyCnZFJaUYDgsPqeElDZ7QyliIiIiIiIiIKZ16FUVlYW3nnnHaSkpKBDhw44c+YMli1bhszMTLz66quYO3cuvv76a8yZM6fS2+rZsyd69OiBZs2aoVmzZnjjjTcQGRmJrVu3QpZlvPfeexg7dix69eqFlJQULFq0CIWFhViyZAkAICcnB/Pnz8c777yDrl27IjU1FZ9++il27dqFtWvXen80KGRYS1Ipx35SQHFIBXD6HhEREREREVGw8zqUqlevHj788EP0798fx48fx/Lly3Hrrbc6VavccMMNuP766726XbvdjmXLlqGgoADt2rXD4cOHcerUKXTr1k3dx2AwoFOnTvjll18AADt27IDVanXaJykpCSkpKeo+VD0pjczLhlJiyfcSp+8RERERVWs1a9ZEdHR0oIdBREQXQevtFdatW4cOHTpUuE90dDR+/PFHj25v165daNeuHYqKihAZGYkVK1agRYsWaqhUu3Ztp/1r166NI0eOAABOnToFvV6PGjVqlNvn1KlTbu/TbDbDbDar3+fm5gIArFYrrFarul352nEbBYciixWSJEGE6HTeZLsdkiTBIvO8BSv+XIUGnqfQwXMVGnieQgfPVWjQ6/U4cuQI1qxZA71ez/MVxPgzFTp4rkJDqJwnT8cnyHJgS0osFguOHj2KCxcu4IsvvsCHH36IjRs34sKFC7jpppvw33//oU6dOur+gwcPxrFjx7Bq1SosWbIEjz76qFPABADp6em44oor3E4hnDBhAl599dVy25csWYLw8HDfPkDyi3NFwNoTIsJ1QM/6pU3PzXbgq8ziAsD7GksoU0hFRERERERERH5WWFiIvn37Iicnp8KqVq8rpQBg+fLl+Pzzz3H06FFYLBany3bu3OnVben1ejRp0gQAcN1112Hbtm2YNm0aXnjhBQDF1VCOoVRWVpZaPZWYmAiLxYLs7GynaqmsrCy0b9/e7X2OGTMGI0aMUL/Pzc1FcnIyunXr5nSwrFYr1qxZg/T0dOh0Oq8eF/lX5rkC7N90BDUj9eiR1qT0XHW9BTtWHwIAdL/1Kug0F9XLn/yAP1ehgecpdPBchQaep9DBcxU6eK5CA89T6OC5Cg2hcp6UGWmV8TqUmj59OsaOHYv+/fvj66+/xqOPPop///0X27Ztw5AhQ7weaFmyLMNsNqNRo0ZITEzEmjVrkJqaCqC4qmrjxo2YPHkyAKBNmzbQ6XRYs2YN+vTpAwA4efIkdu/ejSlTpri9D4PBAIPBUG67TqdzeVLdbafAEUQNRFGEXqt1Ojdhej1EsTiIEjVa6HSaQA2RKsGfq9DA8xQ6eK5CA89T6OC5Cm4mkwm33XYbzp07hy5dunC2Qwjgz1To4LkKDcF+njwdm9eh1KxZszB37lw8+OCDWLRoEUaPHo3GjRtj3LhxOH/+vFe39dJLL+G2225DcnIy8vLysGzZMmzYsAGrVq2CIAgYPnw4Jk6ciKZNm6Jp06aYOHEiwsPD0bdvXwBATEwMBg4ciJEjRyI+Ph5xcXEYNWoUWrZsia5du3r70CiE2Etm7Gk1zvPzHBuf27kCHxEREVG1JEkSfvrpJ/VrIiIKTV6HUkePHlWnxhmNRuTl5QEAHn74Ydx4442YOXOmx7d1+vRpPPzwwzh58iRiYmLQqlUrrFq1Cunp6QCA0aNHw2Qy4emnn0Z2djbatm2L1atXIyoqSr2NqVOnQqvVok+fPjCZTEhLS8PChQuh0bBCpjqzlbz5EAXnUEoQBIgCIMmAjaEUERERERERUdDyOpRKTEzEuXPn0KBBAzRo0ABbt27FNddcg8OHD8Pbnunz58+v8HJBEDBhwgRMmDDB7T5hYWGYMWMGZsyY4dV9U2hTqqC0LjqZa0QBkl2GxFCKiIiIiIiIKGh53QX6lltuwbfffgsAGDhwIJ577jmkp6fj/vvvxz333OPzARK5olRBadyEUo77EBEREREREVHw8bpSau7cueq87SeffBJxcXHYtGkTevbsiSeffNLnAyRyRamCKttTCiitnpK8rNwjIiIiIiIiokvH61BKFEV1dTMA6NOnj7ryHdGlYrW7r5QSWSlFREREREREFPS8DqUOHDiAr7/+GpmZmRAEAY0bN8bdd9+NRo0a+WN8RC4pVVAawX2llN3OUIqIiIiougoPD4fdbg/0MIiI6CJ4FUpNmjQJ48aNgyRJSEhIgCzLOHPmDF544QVMnDgRo0aN8tc4iZzY1Ol75duiKUGVndP3iIiIiKqliIgIXLhwARkZGYiIiAj0cIiIqIo8bnT+448/4uWXX8bYsWNx9uxZnDx5EqdOncKZM2fw4osv4sUXX8RPP/3kz7ESqewlfc1cZFLQlEwvVfYhIiIiIiIiouDjcaXUnDlzMGjQIEyYMMFpe1xcHP73v//h1KlTmD17Njp27OjrMRKVY1N7SpVPpZTm53ZmUkRERERERERBy+NKqd9++w0PP/yw28sffvhhbN261SeDIqqMXZm+56rRuaA0OmcqRURERFQdFRUV4a677sJrr72GoqKiQA+HiIiqyONKqdOnT6Nhw4ZuL2/UqBFOnTrlizERVUrpF+Vq9T210TlX3yMiIiKqlux2O77//nv1ayIiCk0eV0oVFRVBr9e7vVyn08FisfhkUESVqbBSiqEUERERERERUdDzavW9Dz/8EJGRkS4vy8vL88mAiDyh9JQSWSlFREREREREFJI8DqXq16+PefPmVboP0aVQUaWUhqEUERERERERUdDzOJTKzMz04zCIvGOT3PeUYihFREREREREFPw87ilFFEzsJSvracXyT2EllLIxlCIiIiIiIiIKWh6FUsuWLfP4Bo8dO4bNmzdXeUBEnrCrlVLlL9MIJZVSMkMpIiIiIiIiomDlUSg1e/ZsXHXVVZg8eTL27dtX7vKcnBxkZGSgb9++aNOmDc6fP+/zgRI5sqk9pco/hbWa4lBKYqUUERERUbUUEREBi8WCr776ChEREYEeDhERVZFHPaU2btyIlStXYsaMGXjppZcQERGB2rVrIywsDNnZ2Th16hRq1aqFRx99FLt370ZCQoK/x02XObsHPaU4fY+IiIiIiIgoeHnc6PyOO+7AHXfcgXPnzmHTpk3IzMyEyWRCzZo1kZqaitTUVIguqlaI/KHCRucCK6WIiIiIiIiIgp3HoZQiPj4ed911lz/GQuQxuzp9r3woJbJSioiIiKhaKyoqQr9+/XDq1Cnccsst0Ol0gR4SERFVgdehFFEwqGj6nhJU2RlKEREREVVLdrsdX375pfo1ERGFJs63o5BkkyQArhudiwyliIiIiIiIiIIeQykKSfbiTAqu2pixUoqIiIiIiIgo+DGUopBkr6BSSpnSZ5cZShEREREREREFK69DqQ0bNvhhGETe8WT1PTY6JyIiIiIiIgpeXodSt956K6644gq8/vrrOHbsmD/GRFSpilbf02pKKqWUOX5EREREREREFHS8DqX+++8/DBs2DF9++SUaNWqE7t274/PPP4fFYvHH+IhcUiulNOVDKVFQpu9d0iERERERERERkRe8DqXi4uIwdOhQ7Ny5E9u3b8eVV16JIUOGoE6dOhg6dCj+/PNPf4yTSCVJMpR2US4rpUr6TCl9p4iIiIioegkPD0d2djaWLVuG8PDwQA+HiIiq6KIanV977bV48cUXMWTIEBQUFOCjjz5CmzZt0KFDB+zZs8dXYyRy4tjAXKmKcqQ2OmcmRURERFQtCYKAiIgIhIWFQXDxfpCIiEJDlUIpq9WK5cuXo0ePHmjQoAF++OEHzJw5E6dPn8bhw4eRnJyM++67z9djJQIA2Bzm5bmqlCoNpZhKEREREREREQUrrbdXePbZZ7F06VIAwEMPPYQpU6YgJSVFvTwiIgJvvvkmGjZs6LNBEjlyrJRyufqeyNX3iIiIiKozs9mMwYMH4/jx40hLS4NOpwv0kIiIqAq8DqX27t2LGTNmoHfv3tDr9S73SUpKwo8//njRgyNyxV5SKaUR4bJcWwmlJIZSRERERNWSzWbDJ598on5NREShyetQat26dZXfqFaLTp06VWlARJWxlUzLUxqal6VlpRQRERERERFR0PM6lFLs3bsXR48ehcVicdp+5513XvSgiCpil5RKKddNLdWeUjJDKSIiIiIiIqJg5XUodejQIdxzzz3YtWsXBEGAXPKHvzKNym63+3aERGUoFVCumpwDDqGUnaEUERERERERUbDyevW9YcOGoVGjRjh9+jTCw8OxZ88e/PTTT7juuuuwYcMGPwyRyJmnlVKcvkdEREREREQUvLyulNqyZQvWr1+PWrVqQRRFiKKIm2++GZMmTcLQoUPx+++/+2OcRKpKQ6mSqj2J0/eIiIiIiIiIgpbXlVJ2ux2RkZEAgJo1a+K///4DADRo0AD79+/37eiIXLBVFkppWClFREREREREFOy8rpRKSUnBX3/9hcaNG6Nt27aYMmUK9Ho95s6di8aNG/tjjERO7JX0lFK2yzIgSTJEN/sRERERUWgKDw/HiRMnsHbtWoSHhwd6OEREVEVeh1Ivv/wyCgoKAACvv/467rjjDnTo0AHx8fH47LPPfD5AorJKp++5LvQThdIQyi7LEMFQioiIiKg6EQQBtWrVQkxMjLrgEhERhR6vQ6nu3burXzdu3Bh79+7F+fPnUaNGDb4g0CVhkyQAla++BxQHWDrNJRkWEREREREREXnB61DKlbi4OF/cDJFHlEopd9PyNIJQbl8iIiIiqj7MZjOGDx+OI0eOIC0tDTqdLtBDIiKiKvAolOrVq5fHN/jll19WeTBEnlCCJp3GdSgligJEAZBkNjsnIiIiqo5sNhvmzJmjfk1ERKHJo1AqJibG3+Mg8pgSNIkVTBfViAIkuwyJoRQRERERERFRUPIolFqwYIG/x0HkscpW3wOKQymrXWalFBEREREREVGQcr18WSVsNhvWrl2LDz74AHl5eQCA//77D/n5+T4dHJErNnX1PfehlBJYSTJDKSIiIiIiIqJg5HWj8yNHjuDWW2/F0aNHYTabkZ6ejqioKEyZMgVFRUXq3G4if1Gm5Gnd9JQCSpugs1KKiIiIiIiIKDh5XSk1bNgwXHfddcjOzobRaFS333PPPVi3bp1PB0fkiic9pZRKKbudoRQRERERERFRMPK6UmrTpk3YvHkz9Hq90/YGDRrgxIkTPhsYkTt2SQIAaEX3maqmJLCyc/oeERERERERUVDyOpSSJAl2u73c9uPHjyMqKsongyKqiCc9pTQlgZUSYBERERFR9WE0GvHPP//gxx9/dJq9QUREocXr6Xvp6el477331O8FQUB+fj7Gjx+PHj16+HJsRC55svqe0m/KzkyKiIiIqNoRRRENGzZE7dq1IVZQPU9ERMHN60qpqVOnokuXLmjRogWKiorQt29fHDhwADVr1sTSpUv9MUYiJ7aSPlGaihqdC0qjc6ZSRERERERERMHI61AqKSkJf/zxB5YuXYqdO3dCkiQMHDgQ/fr1Y+ksXRJKnyiNJ43OufoeERGRz0mSjMxzBcgrsiEqTIuG8RHqyrdEl4LFYsGYMWNw6NAhdO3aFTqdLtBDIiKiKvA6lAKK53A/9thjeOyxx3w9HqJKqdP3KqqUYihFRETkF7tP5OCLncdxMCsfZqsEg05Ek4RI9G5dDyl1YwI9PLpMWK1WvPvuu+rXREQUmrwOpdavX48vv/wSmZmZEAQBjRs3Ru/evdGxY0d/jI+oHLXROSuliIiILqndJ3Iwfd0BnC+woE6MEcYYDUwWO3Ydz8GJbBOGpjVlMEVEREQe86or4JNPPomuXbti6dKlOHfuHM6cOYNPP/0UXbp0wbPPPuuvMRI5sZd0L6+oUkrDUIqIiMinJEnGFzuP43yBBU0SIhEZpoVGFBAZpkWThEicL7Dgy50nIPG1l4iIiDzkcSi1YsUKLFiwAB999BHOnj2LLVu2YOvWrThz5gzmzZuHuXPn4ptvvvHnWIkAOFRKVbDSCkMpIiIi38o8V4CDWfmoE2OEIAj474IJfx6/AItNgiAIqBNjxIGsPGSeKwj0UImIiChEeBxKLViwACNGjMCAAQMgOEybEkURjz32GIYPH4758+f7ZZBEjqSSRufaChqqKqGUjaEUERGRT+QV2WC2SjDqNQCA7EILzFYJ+WYbAMCo18BslZBXZAvkMImIiCiEeBxK7dy5E/fcc4/by3v37o0dO3b4ZFBEFbHalUqpCkKpkuBUWamPiIiILk5UmBYGnQiTxQ4A6jQ9SS6eVm+y2GHQiYgKq9I6OkRERHQZ8jiUOnv2LOrWrev28rp16+LcuXM+GRRRRSTJg1Cq5DL2tSAiIvKNhvERaJIQiZM5JsiyjJLPiCBJgCzLOJljQtOEKDSMjwjsQANMkmQcOpOPP49dwKEz+XwvQkREVAGPP8qyWCzQ6/Xub0irhcVi8cmgiCpi8yKU4vQ9IiIi3xBFAb1b18OJbBMOZuWjyGIHBCDfbEOOyYq4CD16ta4LsYLX5+pu94kcfLHzOA5m5cNslWDQiWiSEIneretxVUIfMxqN+P333/Hzzz/DaDQGejhERFRFXtVXv/LKKwgPD3d5WWFhoU8GRFQZpXl5RT2ltKyUIiIi8rmUujEYmtYUX+w8jlW7T8Fml2HUaXBj43j0al33sg5edp/IwfR1B3C+wII6MUYYYzQwWezYdTwHJ7JNGJrW9LI+Pr4miiKuvvpqHDlyBGIFi98QEVFw8ziU6tixI/bv31/pPkT+5kmllMhKKSIiIr9IqRuDq2pHISvXDKtdwo2N4zGgfcPLukJKkmR8sfM4zhdY0CQhErIM5BVZEWXUoUlCJA5m5ePLnSfQok70ZX2ciIiIyvI4lNqwYYMfh0HkOWX1vYpCKaVSys5QioiIyOdssoxoow4AEBehv+yDlsxzBTiYlY86MUYIgoCTOSYczzahfpwRiTFG1Ikx4kBWHjLPFaBxrchAD7dasFgseO2113DgwAF07doVOp0u0EMiIqIqYK0rhRybXZm+5/7pKzKUIiIi8huzTVK/tjh8fbnKK7LBbJVg1GsAAGZb8QqFyrEx6jUwWyXkFdkCNsbqxmq14vXXX8dnn30Gq9Ua6OEQEVEVMZSikGOXit/gsVKKiIgoMByDKLOdoVRUmBYGnQiTpTiMKnmrAntJdbfJYodBJyIqzKt2rkRERNUeQykKOd6svqe8GSQiIiLfsdpZKeWoYXwEmiRE4mSOCbIsqx+gSRIgyzJO5pjQNCEKDeMjAjxSIiKi4MJQikKKJMlQip8qWn1PI7DRORERkb9YOH3PiSgK6N26HuIi9DiYlY9Cqx2SLKPQYsPBrHzERejRq3Xdy773FhERUVleh1JHjx6F7KL6RJZlHD161CeDInLHsfKpwul7mpJKKU4pICIi8jmLw+urla+1AIpXJRya1hQt68Wg0GxHfpENBRY7WtWLxdC0pkipGxPoIRIREQUdrye2N2rUCCdPnkRCQoLT9vPnz6NRo0aw2+0+GxxRWY49oiqqlBIFZfqe34dERER02XHqKWXjez9FSt0YtKgTDYvNjjN5FiTHhWNsj+askCIiInLD61BKlmUIQvkX1vz8fISFhflkUETuOE7Hq7jReXERoNLTgYiIiHzHuVKKnwA5EkUBRp0W8ZECIgxaBlJEREQV8DiUGjFiBABAEAS88sorCA8PVy+z2+349ddfce211/p8gESOlEopUYDLcFShNjpnJkVERORz7ClVMXPJMeGx8Z+wsDD88ssv2Lx5Mz8YJyIKYR6HUr///juA4kqpXbt2Qa/Xq5fp9Xpcc801GDVqlO9HSORACaV0morboZWGUnwzSERE5GtOoZRdcltJfzmy2SW1spuhlP9oNBpcd911yMrKgkajCfRwiIioijwOpX788UcAwIABAzBjxgxERUX5bVBE7thKQiaxkje+SijF1feIiIh8z7G5uSwXT+HTaxlKAaVVUgBgYa9VIiKiCnm1+p7NZsOnn36KI0eO+Gs8RBVSKqWU1fXcUUIpiaEUERGRz5WtALJwvrzKMZSyS8WVU+R7FosF77zzDlasWAGLxRLo4RARURV5FUpptVo0aNCAK+xRwNhKmqlW1OQcKF2Zj5VSREREvlc2hOI0tVJlVyNkYOcfVqsVY8aMwaJFi2C1WgM9HCIiqiKvQikAePnllzFmzBicP3/eH+MhqpAkl1RKVRJKqT2lZIZSREREvlY2hLIyeFGZrQzsiIiIPOVxTynF9OnTcfDgQSQlJaFBgwaIiIhwunznzp0+GxxRWVYPK6XUUIrLVBMREfkcK6XcM5ed2shjQ0RE5JbXodTdd9/th2EQeUaplNKw0TkREVHAlA1aygYxl7Oy0/d4bIiIiNzzOpQaP368z+580qRJ+PLLL/H333/DaDSiffv2mDx5Mq688kp1H1mW8eqrr2Lu3LnIzs5G27Zt8f777+Pqq69W9zGbzRg1ahSWLl0Kk8mEtLQ0zJo1C/Xq1fPZWCk4qD2lKmt0XhJaSZy+R0RE5HNlp+uxGqhUuUopTm0kIiJyy+ueUoodO3bg008/xeLFi/H7779X6TY2btyIIUOGYOvWrVizZg1sNhu6deuGgoICdZ8pU6bg3XffxcyZM7Ft2zYkJiYiPT0deXl56j7Dhw/HihUrsGzZMmzatAn5+fm444472JC9GlJX36tk+p6oTN9jpRQREZHPsaeUe+wpRURE5DmvK6WysrLwwAMPYMOGDYiNjYUsy8jJyUGXLl2wbNky1KpVy+PbWrVqldP3CxYsQEJCAnbs2IGOHTtClmW89957GDt2LHr16gUAWLRoEWrXro0lS5bgiSeeQE5ODubPn49PPvkEXbt2BQB8+umnSE5Oxtq1a9G9e3dvHyIFMZtU/MZOI1acpyqhlSQDkiSrIRURERFdPCVoCdOJKLJKnKLmoNzqezw2REREbnldKfXss88iNzcXe/bswfnz55GdnY3du3cjNzcXQ4cOvajB5OTkAADi4uIAAIcPH8apU6fQrVs3dR+DwYBOnTrhl19+AVBcsWW1Wp32SUpKQkpKiroPVR+eVko5NkLnCnxERES+ZSmZTh9pKP58k5VSpTh979IICwvDmjVr8NprryEsLCzQwyEioiryulJq1apVWLt2LZo3b65ua9GiBd5//32nYMhbsixjxIgRuPnmm5GSkgIAOHXqFACgdu3aTvvWrl0bR44cUffR6/WoUaNGuX2U65dlNpthNpvV73NzcwEAVqsVVqtV3a587biNAststUKSJECWKjxXkl0q3g+A2WwBdJpLP1hyiT9XoYHnKXTwXIWG6naeiizFr8dGnQBJklBotlSbx3ax56qwyKK+B1G+ry7HJti0b98eBQUFkCSJxziIVbfff9UZz1VoCJXz5On4vA6lJEmCTqcrt12n0zm9AHvrmWeewV9//YVNmzaVu0wos9KaLMvltpVV0T6TJk3Cq6++Wm776tWrER4eXm77mjVrKrwvunT+yRFw7KwAnJeRcXZXucuVcyXJwLGjxYWAGasyYWAmFXT4cxUaeJ5CB89VaKgu5+nAIRGyDEjnZJwoELAl9wgKD1avyuSqnqvtpwUcyy99D7o5/wgu7K9exybYVJefq+qO5yl08FyFhmA/T4WFhR7t53Uodcstt2DYsGFYunQpkpKSAAAnTpzAc889h7S0NG9vDkDxlMBvvvkGP/30k9OKeYmJiQCKq6Hq1Kmjbs/KylKrpxITE2GxWJCdne1ULZWVlYX27du7vL8xY8ZgxIgR6ve5ublITk5Gt27dEB0drW63Wq1Ys2YN0tPTXQZxdOlFHTyLs3uycG1yDHq0rqtud3WufvtmLyQZSOvaFNFGnr9gwZ+r0MDzFDp4rkJDdTpPdknGL9/uAwDc0LAGfsvMRstGNdCjVZ1KrhkaLvZcnd16FPLpfBi0Isw2Cdc0jUe3FrUrvyJ5xWq14oMPPsDff/+NKVOmuPxgmYJDdfr9V93xXIWGUDlPyoy0yngdSs2cORN33XUXGjZsiOTkZAiCgKNHj6Jly5b49NNPvbotWZbx7LPPYsWKFdiwYQMaNWrkdHmjRo2QmJiINWvWIDU1FQBgsViwceNGTJ48GQDQpk0b6HQ6rFmzBn369AEAnDx5Ert378aUKVNc3q/BYIDBYCi3XafTua0CC+aTfTkRBA1EUYRBp630XOm0GljtMkSN630psPhzFRp4nkIHz1VoqA7nyWaxQyxZcCQ2wgBRFCFBDPnHVVZVz5VdBkRRRGy4HmfyLbBXw2MTDCwWi/oh8+TJk3mMQ0B1+P13ueC5Cg3Bfp48HZvXoVRycjJ27tyJNWvW4O+//4Ysy2jRooW68p03hgwZgiVLluDrr79GVFSU2gMqJiYGRqMRgiBg+PDhmDhxIpo2bYqmTZti4sSJCA8PR9++fdV9Bw4ciJEjRyI+Ph5xcXEYNWoUWrZsWaUxUXCzlTQ613iwmp5GFGC1y+p1iIiI6OIpjbtFATCW9GxkM+9SZmvxsYgK0+FMvoWr7xEREVXA61BKkZ6ejvT09Iu689mzZwMAOnfu7LR9wYIFGDBgAABg9OjRMJlMePrpp5GdnY22bdti9erViIqKUvefOnUqtFot+vTpA5PJhLS0NCxcuBAaDRsJVTf2kr5lWrHyhSOVFfokrr5HRETkM0rIotOI0GtFp20EFNnsAICosOK32Tw2RERE7lUplFq3bh2mTp2Kffv2QRAEXHXVVRg+fLjXlUmyB2GBIAiYMGECJkyY4HafsLAwzJgxAzNmzPDq/in0KB/EairPpCCWhFKslCIiIvIdpSrKoGUo5YpyLKLCdCXf2wM5HCIioqDmwZ/2zmbOnIlbb70VUVFRGDZsGIYOHYro6Gj06NEDM2fO9McYiVS2KlRK2e0MpYiIiHxFCV30WhG6kk+JOH2vVJE6fa+kUorHhoiIyC2vK6UmTZqEqVOn4plnnlG3DR06FDfddBPeeOMNp+1Evmb3pqeUUBJKcfoeERGRz1hLQha9RoSBlVJO7FJpL0tl5V8eGyIiIve8rpTKzc3FrbfeWm57t27dPF7yj6iqvGt0Xvz0VvpQERER0cVTe0qxUqocs8NUvUgDe0oRERFVxutQ6s4778SKFSvKbf/666/Rs2dPnwyKyB2lUkrrQSil1ZRUSvG9IBERkc9YWCnllrLynk4jIFxfvOCOmW9E/MJgMOCrr77Cyy+/DIPBEOjhEBFRFXk9fa958+Z44403sGHDBrRr1w4AsHXrVmzevBkjR47E9OnT1X2HDh3qu5ESwbvpe6KgNDrnm0EiIiJfcewpxUbnzsw2NoG/VLRaLXr06KF+TUREocnr3+Dz589HjRo1sHfvXuzdu1fdHhsbi/nz56vfC4LAUIp8zlbyaaMnoZTa6Jyr7xEREfmMGkppSoMXmyRDkmR15dvLlTJ9z6kJvE2CLMsQhMv72BAREbnidSh1+PBhf4yDyCPKQnoeVUoxlCIiIvI5V6vvAcXT+sJETaCGFRSUSqkwrUad2ijJxaGdTsNQypesVis+/vhj/Pnnn0hPT4dOpwv0kIiIqAq87imlsFgs2L9/P2w2my/HQ1QhpWm5Vqz8qctKKSIiIt9TV9/TitCKApTPicycpoYia3GllEEnQu8Y2PHY+JzFYsGgQYMwY8YMWCyWQA+HiIiqyOtQqrCwEAMHDkR4eDiuvvpqHD16FEBx/6g333zT5wMkcuTd6nsMpYiIiHzNsdG5IAhqtZSVDb3V8Mmg1UAUBbU6iqEUERGRa16HUmPGjMGff/6JDRs2ICwsTN3etWtXfPbZZz4dHFFZ9pL5e1oPSuAZShEREfmeUhGlK5mexhX4Sjk2OgegVktZGNgRERG55HVPqa+++gqfffYZbrzxRqeGjS1atMC///7r08ERlWWXiwMm0YNmoUooZWMoRURE5DNWh0opAFxlzoHj9D2g+NgUWOw8NkRERG54XSl15swZJCQklNteUFDAVUXI75SqJ0+ahWpKno9KkEVEREQXr7TRefHrLKuBSjlO3wNKAzv22yIiInLN61Dq+uuvx3fffad+rwRR8+bNQ7t27Xw3MiIXlKonbyqlJFZKERER+YwaSmmKgxcdK6VURbaSSiktq8iIiIg84fX0vUmTJuHWW2/F3r17YbPZMG3aNOzZswdbtmzBxo0b/TFGIpVSKeVNTylO3yMiIvKd0kqpMj2lWCkFs7VMpRSryIiIiCrkdaVU+/btsXnzZhQWFuKKK67A6tWrUbt2bWzZsgVt2rTxxxiJVDa756vvaVkpRURE5HNqT6mSMEpZfY/VQKXhk9JTik3g/cdgMGDJkiV4/vnnYTAYAj0cIiKqIq8rpQCgZcuWWLRoUbnty5cvx7333nvRgyJyRyrpD6UVK89TRVZKERER+Zy5JHhR+jtyiloptdG5WkVWXDHFY+N7Wq0W9957L8LDw6HVVulPGiIiCgJeVUrZbDbs2bMH//zzj9P2r7/+Gtdccw369evn08ERlaV8OqvxoKeUUillZyhFRETkM1Zb8etquel7DF7KTd/TlTSDt9jtARsTERFRMPM4lNq7dy+aNWuGVq1aoXnz5ujVqxdOnz6NTp06oX///khPT8fBgwf9OVa6zMmyDCVf0njQU0pkKEVERORzSsBi0Dj3TbKyb5K6yp7a6FzDSil/sdlsWL58OTZv3gybzRbo4RARURV5XOv64osvolGjRpg+fToWL16Mzz77DLt378ZDDz2ElStXIioqyp/jJHIKl7Re9JRiKEVEROQbNrsEJXtSqoCUiikzgxeYldX3yvSU4rHxPbPZjL59+wIAXnrpJRiNxgCPiIiIqsLjUOq3335DRkYGWrdujZtvvhmfffYZnn/+eQwePNif4yNSOfaG8qTRubKPXWYoRURE5AtWe+lrqlIhpeMKc6rSSill+h6nNhIREVXE4+l7WVlZqFu3LgAgNjYW4eHh6NSpk98GRlSWY8WTJz2llH3Y6JyIiMg3lHBFFABtSRjFRufFJElWQ7swnTJ9j4EdERFRRTwOpQRBgOiw4pkoitDpdH4ZFJErSrgkCqX9oiqiLek7ZecbQSIiIp9QwhUliHL8+nIPpRyn6ClhlDKN73I/NkRERO54PH1PlmU0a9YMQkn1SX5+PlJTU52CKgA4f/68b0dIVEKplPKknxQAiIIyfc9vQyIiIrqsuAylWA0EACiyFveT0opCaRWZhqEUERFRRTwOpRYsWODPcRBVSgmlNKJnBX7akv3sEt8IEhER+YISrihhC1AaUFkv8+BFCeUMrCIjIiLymMehVP/+/f05DqJK2UrCJY2Hk07VRud8H0hEROQTrkIpJYRhpZTzynsAjw0REVFlPA6liALN20qp0lCKbwSJiIh8wVoSrugcqoF0nKIGoPzKewArpfxJr9fjww8/xJ9//gm9Xh/o4RARURV53OicKNC87SmlhFJcfY+IiMg3SoOX8lPUzJd58GJxcWyUwO5yPzb+oNPp8MgjjyAtLY2LLxERhTCGUhQybGqllHehlMRQioiIyCeU4EXnoqeUxS5Bli/f11x1+p7W9fS9y/nYEBERucNQikKGt5VSWlZKERER+ZS1gtX3ZPnyfs1Vq8h05afvyTJg5XLAPmWz2ZCRkYHt27fDZrMFejhERFRFDKUoZNhK3syJXlZK2fnJJBERkU+4XH3P4evLuXeS2Va+Usrp2LDZuU+ZzWbcfffdeP3112E2mwM9HCIiqiKvG53b7XYsXLgQ69atQ1ZWFqQyTaTXr1/vs8EROZJKwiWdxstQip9MEhER+YSrSilRFKDTCLDaZVhsEiIMvr1PSZKRea4AeUU2RIVp0TA+wuMPqC4ls7V8o3NBEKDXCLCUHBv4+NgQERGFOq9DqWHDhmHhwoW4/fbbkZKSAkEIvjcFVD0pUwJED59zyn6X81QCIiIiXzK7qJQCintMWe12NbTyld0ncvDFzuM4mJUPs1WCQSeiSUIkereuh5S6MT69r4vlqgk8UBzgWez2y7qKjIiIyB2vQ6lly5bh888/R48ePfwxHiK37CVVed72lJI4fY+IiMgnLC4qpZTvCy12n64yt/tEDqavO4DzBRbUiTHCGKOByWLHruM5OJFtwtC0pkEVTCnT98IcekoBJcfKzFCKiIjIFa97Sun1ejRp0sQfYyGqkNJTSqPx7GmrlPbbWSlFRETkE65W3wNKK6d81TdJkmR8sfM4zhdY0CQhEpFhWmhEAZFhWjRJiMT5Agu+3HkiqFbYVavIygZ2muKQymK3X/IxERERBTuvQ6mRI0di2rRpXNaWLjmlYbn3lVIIqjetREREocpVTynH731VDZR5rgAHs/JRJ8YIQRBw7Hwh/j6VC1mWIQgC6sQYcSArD5nnCnxyf76g9JQK07k+Nr6sIiMiIqouvJ6+t2nTJvz444/4/vvvcfXVV0On0zld/uWXX/pscESO1EopL1ffA4oDLRHsfxZokiTj8NkCHMkHDp8tQJPaMUHZrJaIiFyzuOubpPFtKJVXZIPZKsEYU1xllJVXBLsEmKx2hOu1MOo1OJ0rIa/I5pP784XS1fdcTN/D5b0yIRERkTteh1KxsbG45557/DEWogoplVIaDxudO4VSkowyLR7oElOa1R44lYeTWSJ+W/k3miZGBWWzWiIics3d9D1DSXWQrxqdR4VpYdCJMFnsiDBooNys8gGVyWKHQSciKszrt7J+4276noGhlF/o9XpMmzYNe/bsgV6vD/RwiIioirx+JV+wYIE/xkFUKXvJG1GtxsNQSnAOpShwHJvV1o42wBYGxITrgrZZLRERueau0bnOx5VSDeMj0CQhEruO56BhfLi63S7JkGUZJ3NMaFUvFg3jI3xyf76ghFLlpu/5uN8WFdPpdHjqqaeQkZFRbuYGERGFDq97ShEFik3ybvqeKApQdrUxlAoYx2a1jWqGo9BigwQg0hC8zWqJiMg1t6vvlQQvZh8FL6IooHfreoiL0OPgmXxY7RIkWUZukRUHs/IRF6FHr9Z1g2oKuNnK6XtERETeqlLN8/Lly/H555/j6NGjsFgsTpft3LnTJwMjKkupdvK00TlQHGBJdpmBRwA5NqvNyrPg2HkTtNbiy8o2q21cKzKwgyUiogopwYq+7Op7fgheUurGYGhaUyz6JRM/HzgLuyQjV2/FDY3i0at13aCqsJUkGZaSiu6y/bY4fc8/7HY7Nm7ciF27dqF79+6sliIiClFeV0pNnz4djz76KBISEvD777/jhhtuQHx8PA4dOoTbbrvNH2MkAgDYpOI3c6KHPaWA0qqqyiqlJEnGoTP5+PPYBRw6k88Qy4fUZrV6DYpKPkV2fF9u1GtgtgZXs1oiInKtslDKVz2lFCl1YzCwQyO0aVADqfVjcd91yXj59uZBFUgBzivrlQ2ldJy+5xdFRUVIT0/HK6+8gqKiokAPh4iIqsjrSqlZs2Zh7ty5ePDBB7Fo0SKMHj0ajRs3xrhx43D+/Hl/jJEIACCVNDov21y1IkpVlXJdV5QG3Aez8mG2SjDoRDRJiGQDbh9xbFar/DHjmPkFY7NaIiIqz2aX1N/fbqfvWX0fvFhsEqKNxVUwMUZdUE3ZUygr72lFAVo3gZ2ZlVJERETleF0pdfToUbRv3x4AYDQakZeXBwB4+OGHsXTpUt+OjsiBsuKON29GxUoqpZQG3LuO5yDWqEfDmhGINeqx63jx9t0nci5+4Jc5pVntyRyTWilVcirVZrVNE6KCqlktERGVZ7WXvpbqyiw64q9KKaD4wwtFocPXwcTdynsAp+8RERFVxOtQKjExEefOnQMANGjQAFu3bgUAHD58GHIF1ShEF6sqPaWUfe328s9NxwbcTRIiEW7QwCZJiAxjA25fUprV1ojQ42y+GVa7BJskIN9sC9pmtUREVJ4SqogC3FYD+WOKWqG1NIgyWYM0lCqpECs7dQ9go3MiIqKKeB1K3XLLLfj2228BAAMHDsRzzz2H9PR03H///bjnnnt8PkAihber7wGApqT/lN1FYOrYgFsQBPyblY8/j+WgyGor14CbLk5K3Rg81r4hakToYbFLKLABFwotaFUvFkPTmnKaJBFRCDDbiwMhV9VAyvQ9fwQvZocgqihYQ6mS6XthOk25y9hTioiIyD2vm7jMnTsXUknD6SeffBJxcXHYtGkTevbsiSeffNLnAyRSVG31PbHkuuXfCKoNuGOK30Aqn8SaLBLCdMUNuE/nsgG3ryTGGtG6fg3kmiw4duIkxtx2JVok1WCFFBFRiLBUMEXNn32THKujCi3B+Zpc0fS9MB0rpYiIiNzxOpQSRRGiWPqC26dPH/Tp08engyJypSqVUtqSnheuPpx0bMAdGaZVp/gp/TDYgNu3sgstEAQBUWE6ROmAhCgDAykiohCi9JQyuFhwRKkG8kdPKcc+UiZLcAY7aqWUyyqy4g+/GEoRERGV5/X0PQD4+eef8dBDD6Fdu3Y4ceIEAOCTTz7Bpk2bfDo4IkdSFUIpUVAanZd/I+jYgFuWJXWKn02S2IDbDy4UWpy+D9ZmtURE5JoSqrhaBdefzbyLHFb0K7LZg7LXo9pTytX0PW3xexFO3/MtnU6HSZMmoX///tDpdIEeDhERVZHXodQXX3yB7t27w2g04vfff4fZbAYA5OXlYeLEiT4fIJGiSpVSSqNzF29glQbccRF6/HM6HxabBEmWkVfEBtz+kF1gdfq+0MxQiogolChVUBVN3/NPKFX6eiHLxcFUsFGn77kM7Fgp5Q96vR4jR47EPffcA71eH+jhEBFRFXkdSr3++uuYM2cO5s2b5/SpRPv27bFz506fDo7IkdIXSit6/rQVKwilgOIG3EPTmuLKxChYbBLyi2zIK7KxAbcfXDA5h1IFQdoXhIiIXKuob5Lej828y/aRMgVhpW1Fjc4d+21xpWoiIiJnXjfL2b9/Pzp27Fhue3R0NC5cuOCLMRG55OtKKUVK3Rg81fkK5JpssNolNEmIxKhuV7JCyseU6XuRhuI37MG6rDcREblW0fQ9nVbpKSVDkmSfvoY6Tt8DgvP1QwnsDBUEdkBxaKdUTtHFsdvt2L59Ow4cOAC73c4pfEREIcrrSqk6derg4MGD5bZv2rQJjRs39smgiFyp2up7lYdSQPEb7WijDvGRBhh1GgZSPibLMi4UFldK1Y01AuD0PSKiUGOpYPqeYxjjy2opWZbVEEr5UKMoGEMptaeUqybwAkpaXHIKnw8VFRWhffv2eP7551FUVBTo4RARURV5HUo98cQTGDZsGH799VcIgoD//vsPixcvxqhRo/D000/7Y4xEAEqDJW8qpTwNpRybbudzWpnP5ZltsEkyRAFIjA4DABQE4fQLIiJyz1pBNZBWLA1efLkCX/GUt+Kva0QU9w0KxoUylOl7rqqgBEEond7IUIqIiMiJ19P3Ro8ejZycHHTp0gVFRUXo2LEjDAYDRo0ahWeeecYfYyQCULXpe5qSd8j2Sno4OPanKDTbIcsyBIHVUr5yoaTJebRRh8iw4jfswfhHBRERuadWSrmYvqcEL2abBLNNQpSP7lN5fdaKAqLCdABMQdlTSpli6CqwA4qry8w2iSvwERERleF1KAUAb7zxBsaOHYu9e/dCkiS0aNECkZGRvh4bkZOLmb5nq6RSyrE/hU2SYbZJLpuVUtVkl/STqhGuQ7i++NdO2ca1REQU3CrqKQWUBi++rJRSXp+Neg2MJa/LhUE4fU8Jm1xN3wPASikiIiI3qhRKAUB4eDiuu+46X46FqEIXM31PqiSUKtufotBiZyjlQ8rKe7HheoTrWSlFRBSKKuopBfgneFFCqTBdaShVFISvH8r7CHdNzJVjxlCKiIjImceh1GOPPebRfh999FGVB0NUEZtU/EZOK3reCq0qlVIAUGC2Ia6kdwVdvOyC4kqpWKMOEQyliIhCkieVUo77+YIyVc+o0wT1hxoVrb4HlB4bM0MpIiIiJx6HUgsXLkSDBg2QmpoKuZL+PES+JssylNkAGo3nlVJaDyulyr7BLeDUMp+6UDJ9Ly5C7zB9j727iIhCiRI2uZ2i5ofgRalAMupEtYK57AdJwcBSWSilVJGxpxQREZETj0OpJ598EsuWLcOhQ4fw2GOP4aGHHkJcXJw/x0akclw9T+NFiCF6WilVNpQyB98b3lCWXahM39PBWPJJN3t3ERGFlooanQOlFVT+6imlVEoFW6NzqeT1DAAMbl7TOH3P93Q6HV5++WUcOHAAOp0u0MMhIqIq8nge1KxZs3Dy5Em88MIL+Pbbb5GcnIw+ffrghx9+YOUU+Z1jqKStQqWU3cOeUsob3gIzK6V8RZZltVIqNlwPvUaAcgqDcQoGERG5ZrVV0lPKj9P3wnQa9UONYKuUcqx+qmz6HkMp39Hr9Rg3bhwefPBB6PVsuUBEFKo8b84DwGAw4MEHH8SaNWuwd+9eXH311Xj66afRoEED5Ofn+2uMRJDki6uUqiyUUt7g1ow0AODKcL5UaLHDYi8+/rFGXcmy4cplPM5ERKFCCV/c9ZQy+GGKmlop5dDoPNhCKbO1+PFqRPcrBBsYShEREbnkVSjlSBAECIIAWZYhSXyBJf+yloQaglAaNHnC00oppWInPrL4kzZO3/Od7JIqqegwLbQlf7AYNMXng5VSRESho9LV9/wQvBQ5TN8zBun0PbOtdOU9d30S2VPK9yRJwp49e3D06FH+LUJEFMK8CqXMZjOWLl2K9PR0XHnlldi1axdmzpyJo0ePIjIy0l9jJFIblbv7BNIdZfU9ewVTTCVJRlHJp5y1Siql2Ojcdy6o/aRKS+sNJZVSnCZJRBQ6lIqgynpK+Wv1PaVSymyTKv2w6VKqbOU9gNP3/MFkMiE1NRVDhw6FyWQK9HCIiKiKPG50/vTTT2PZsmWoX78+Hn30USxbtgzx8fH+HBuRSukppfE2lBIqb3ReZCv9xJWVUr6nhFI1wkubkOpL3rezUoqIKDTIsqw2MHcXSqlT1Hw6fa/4tsIcQqni7XZEGjx+G+tXjpVS7iiXMZQiIiJy5vGr+Zw5c1C/fn00atQIGzduxMaNG13u9+WXX/pscEQKexUrpZSm6PYK3iArn8IatCKiwoqDE/Y68p3zapPz0lDKoAHMYKUUEVGosEsylM933E3f0/mj0bnD9D1RFGDQijDbJJgswRNKKdXWBp37SildyfsRM6fvEREROfH41fyRRx5xO0+eyN9sktJE1Ls2aKKgTN9zv4/yhjdMp0GEuvoeK3h8JacklKrhOH1PLA6lWClFRBQaHKuf3PaU8kPfpCKHRudA8Sq5SigVLEorpTh9j4iIyFseh1ILFy704zCIKmZXp+95dz1tSYhlr6ABpuMb3oiST11NVjvskuz1dEEqL7uinlKsSCMiCglWW+nrsLvXRn8EL449pZT/s2ENqhX4SntKcfoeERGRt6q8+h7RpVQ6fc+7p6za6LyC94BKtY5RL8Ko00ApCOQUPt/IViulHHpKKavvsSKNiCgkmO3Fv6/1moqCl+LXaKuPKqWsdkntCamsvKeuwBdMoZSVjc6JiIiqiqEUhQR7VRudq6FU5T2ljLrifhXhOk7h85Uiq13ttRHj2FOq5DcPK6WIiEKDEqbotO5fh5XgRQlpLpYSPAlCaeCjhlLBOH2vgp5SpVMbg2fcREREwSA4OkQSVaLKq++Jla++V9pEtfjHIdygRYHFzsDEB5QqqQi9xmlagzJ9jz2liIhCgxJKGSqYR6/T+LZSqsjhQyOlr2m4WikVPK/RHk3f07FSytd0Oh1GjBiBQ4cOQafTVX4FosuYJMnIPFeAvCIbosK0aBgfAZFtSihIMJSikFDV1feUUEqqIJQq20Q10qDBmTyuDOcL2QXF/aRqROidths0AOTiKZKyLHMRBSKiIGctWTHEXZNzx8t8tcJc6UIkpfepvFabLMET7ng0fa8ksDMzlPIZvV6PN998ExkZGdDr9ZVfgegytftEDr7YeRwHs/Jhtkow6EQ0SYhE79b1kFI3JtDDI2IoRaGhqtP3tF5USimfvoaXVExx+t7Fu2AqrpSKDXf+BFMvArAX9/oy2ySE6dx/ukxERIGnVPhUGEppfFsNVPr6XPp2VXm9CKqeUh6svqdT+23JkCSZFQpEdEnsPpGD6esO4HyBBXVijDDGaGCy2LHreA5OZJswNK0pgykKOPaUopBgK+kJ5W0opbzps8vuQyllCpnyRjeiZG4ZG51fvAvKyntG508wtSKg1xSfG07hIyIKfkovJF0F0/d83czbVOb1GXCslAqe12il+qmiD1gcAyuLjyrJLneSJCEzMxOnT5+GVEHvUKLLlSTJ+GLncZwvsKBJQiTCdCJEAYgM06JJQiTOF1jw5c4TFc4oIboUGEpRSFDev3k7fU/Z326voFJKXX3PuVIqn9P3LpqrlfcUyvHmNEkiouBnsXkwfa8ksJJkwOaD4MXV9D3lNTq4KqUqryLTioK6ui9DKd8wmUxo1qwZnnjiCZhMpkAPhyjoZJ4rwMGsfNSJMcJql/HHsQv453QeAEAQBNSJMeJAVh4yzxUEeKR0uWMoRSGhtFLKu6esKFReKeW4+h4ARBqK3/CygufiqZVS4eV7PSh/WPA4ExEFPyVI8aRSynH/i1FUZno9ABj1xfcRTK8dZmvl0/cEQfD59EYioorkFdlgtkow6jUotNggyc7tSYx6DcxWCXlF/ICYAouhFIWEqjY6VyulPFl9T6dUSrGCx1eyC0oqpSLKV0qpxzmIpmAQEZFr6up7FQQvGlFQX3ettoufDqI0Mzc6TIsLzp5SlU/fA0qPHUMpIroUosK0MOhEmCx29feUTZIhlXxYb7LYYdCJiApjm2kKLIZSFBJsVWx0LnoTSumVnlKs4PEFs82OgpJjWLanFABElBzvQjaUJyIKemqj8woqpYDSSiql+ffFUF6fDQ5hjzp9L4heoz2Zvud4OUMpIroUGsZHoElCJE7mmNSKTgCw2iXIsoyTOSY0TYhCw/iIAI6SiKEUhQilJ1RVV9+TZLhs4idJMopKlnIuG0qxUuri5JRM3QvTieqxdcRKKSKi0GG1exm8+LCnVLiLRudWu+yTvlUXS5Zljyul1Ol7QTBuIqr+RFFA79b1EBehx/ELJljtEiRZxoUCCw5m5SMuQo9eretyNVAKuICGUj/99BN69uyJpKQkCIKAr776yulyWZYxYcIEJCUlwWg0onPnztizZ4/TPmazGc8++yxq1qyJiIgI3HnnnTh+/PglfBR0KSg9obQa735pOoZYrvpKFTl8kqu80Y1wCEvkCnpRUcWyS0KpGi76SQFAuFqRxlCKiCjYKdU9FfWUAnxbDVRUZiESoPiDDqVheDBM4TM7PM6KpjYCrJQioksvpW4MhqY1Rc1IAyw2CflFNpwvtKJVvVgMTWuKlLoxgR4iUWBDqYKCAlxzzTWYOXOmy8unTJmCd999FzNnzsS2bduQmJiI9PR05OXlqfsMHz4cK1aswLJly7Bp0ybk5+fjjjvugN0e+Dcq5DvK9DuNcBGhlItKKaX836AV1X2VqQF2yfnNJnnnQsnKe7EuVt4DHMI/Tt8jIgp6Fg8rpQx+qJRyrEASBAFh2pK+UkEwhc9cUm0tCpX3vVSOHd9bENGllFI3Bm3qx6JNgxpIrR+Lh2+sj5dvb85AioJGQLua3XbbbbjttttcXibLMt577z2MHTsWvXr1AgAsWrQItWvXxpIlS/DEE08gJycH8+fPxyeffIKuXbsCAD799FMkJydj7dq16N69+yV7LORfVe0p5RhiuQylXLzh1WtF6DUCLHYZ+WZbpeX45Fp2BSvvAaXT94LhjwoiIqqYxdO+ST5cYa7sQiSKcL0GJqs9SCqllA+3NBAq+eCMlVK+pdVq8eSTT+LIkSPQatmomcgdm11CntmOaGPxB8URBh2n7FFQCdqeUocPH8apU6fQrVs3dZvBYECnTp3wyy+/AAB27NgBq9XqtE9SUhJSUlLUfah6sEvFb+C8nb4nigKU37k2F6FUkZs3vGqzc1bxVJlSKVXDTaWUUpHGnlJERMFPrZSqtNF5yep7vqiUcjF9z/H7YFiQRKl6Mugqf0ttKKnwYk8p3zAYDJg+fTqeeOIJGAyGQA+HKGjlFtnKfG8N0EiIXAvajxVOnToFAKhdu7bT9tq1a+PIkSPqPnq9HjVq1Ci3j3J9V8xmM8xms/p9bm4uAMBqtcJqLf0hVb523EaBYbbYIEkSIEkuz0dF50qADEmSYbZYYC3zjM8tNEOSJOg1ztcN0wqQJAk5hUWwRrsOVahiZ/OKIEkSovSiy58rvShBkiTkmSz8GQtC/P0XOniuQkOonyeT2QpJkiDKrl+HFRoBkCQJhUXWi3qskiTDVPKhhQbO96kTUfL6YfbL8fTmXOWbit9H6ITK9xdR/LpnKuLrnq+E+s/V5YLnKbDO5hYW/x1V4kKB+9+dPFehIVTOk6fjC9pQSlG2FFqW5UrLoyvbZ9KkSXj11VfLbV+9ejXCw8PLbV+zZo2HoyV/+eO0gGP5ArYXHkHeAffNx12dq2NHRFgl4IfVmYguM5PsYC5w7IwI6ZyMjNy96vbMkwJOFQpYV5SJQ1E+exiXld+PiDDZgN+lTBxx8QHmr5t/xrGjxQ1rv/vuX3jZLowuEf7+Cx08V6EhVM/TvqMi8q3AL7ZMHDC63+/vLAHH8gRszj+C839XfbEQsx04drS4+mjD2kw4zjT5t+Q9wYbCIzgZ478FSTw5V8cLgGOnRBSGycgo2l/hvrvPCTh2QcDW3CMwH+ZCKhdLlmX1g+XVq1dX+vcBBV6o/v4LdYfzgGNZIkSheEXynFMyal/YU+F1eK5CQ7Cfp8LCQo/2C9pQKjExEUBxNVSdOnXU7VlZWWr1VGJiIiwWC7Kzs52qpbKystC+fXu3tz1mzBiMGDFC/T43NxfJycno1q0boqOj1e1WqxVr1qxBeno6dDpWywRSzrZjkP/LQ/tWiWjbKK7c5RWdq79W7Ue+2Y4uXRqjdnSY02U/HTiLrL1ZaF0/Bj1S66rbC3eewB/HctCqRQI6NK3pnwdVjdnsEn5Z+TcA4O5bmyHSUPqrRjlXPbql4Y8f/gUA3JJ+ZbnpGRRY/P0XOniuQkOon6ddP/yDvCIbunVujDoxYW73k/46CdvhbFzTrCa6Nk+o8v2dyzdjx7p/odeKuOP2q5wus/55EsjMRqsrayLtqqrfhzvenKvfj17A0d//Q9OECPRo16DCfcP/OYOCfWeQ0iAWPa5N8uWQL0sFBQXq+/+srCzExsYGdkDkVqj//gt1P+4/g5N/n0FyDSOOZZsQrtegx21XutyX5yo0hMp5Uj44qEzQhlKNGjVCYmIi1qxZg9TUVACAxWLBxo0bMXnyZABAmzZtoNPpsGbNGvTp0wcAcPLkSezevRtTpkxxe9sGg8Hl3HOdTufypLrbTpeQIEIURRj0FZ8LV+dKq9VAtMoQNNpyl1nsgCiKiAwzOF0WbTRAFEWY7eC5r4IcsxmiKEKnERAbEeby08vwMAOMei3MNglWWUA0j3NQ4u+/0MFzFRpC9TzZpOLXS6NBX+H4jQYdRFGEHcJFPU4brBBFERGG8scryqiHKIqwSBd3H5Xx5FzZIJQcl8r3Ner1Pjk2VMzxGIbqz9XlhucpMPItEkRRRMNakTiRY0aRTYYgaqCtoEcgz1VoCPbz5OnYAhpK5efn4+DBg+r3hw8fxh9//IG4uDjUr18fw4cPx8SJE9G0aVM0bdoUEydORHh4OPr27QsAiImJwcCBAzFy5EjEx8cjLi4Oo0aNQsuWLdXV+Kh6sNmrtvoeULpEs93ufvW98DJVOuGG4u8LgqCJaii6ULLyXo1wfYXl9OF6Dcw2CYUWO+Iv1eCIiMgrsiyrjcsrW31PaeZ9sY3O3S1E4ritKAheo9VG59rKq325+h4RBYKyInadmDBoRQE2SUZekQ01IlyvkE10qQU0lNq+fTu6dOmifq9Mqevfvz8WLlyI0aNHw2Qy4emnn0Z2djbatm2L1atXIyqqtMnP1KlTodVq0adPH5hMJqSlpWHhwoXQaDgVqDqxl6ycp61CKKUpCUXssvtQKqzs6nslK8MVcmW4KlFW3ot1s/KeIsKgRXahlSvwEREFMZskQ1nAtvLV93wTvBSqK++Vvz/lgyTlNTyQzNbixxnm0ep7xfuYGUoR0SWUU/K+PMaoR1RY8XtvhlIUTAIaSnXu3Bmyi6BAIQgCJkyYgAkTJrjdJywsDDNmzMCMGTP8MEIKFraSd8NiFZpYasTiN4F2qfybQHfLTUeUVErlmxmWVEW2Q6VURZRPuwvMgf/DgoiIXHOseqqsUspX1UBFJWGPq0op5YOkoAilbMVjqCysAxyOzUVWkREReUqWZVwwFb8vjw3XIdqoQ3ahFblFwb1qG11eKn8FJQoCUkl4qfPgTV9ZWk1JpZSL94BqKOWmUqqAoVSVZHtcKVV83FmRRkQUvJSASSsKlU6j1/uoGshdJTNQ+kFSYRBN33M1zrJ8VUVGROSpQosd1pIWJrFGHaLCiv/GYShFwYShFIUE5VPaKmRSanWVzVWllJueFREGJZQK/BveUKRM36usUipcnSbJ40xE1ZckyTh8tgBH8oHD/8/ee4dJcpXn23eFzmny7sxsDpI2KGcEKCELCRkJSeQkgzE2GYM/Y2wDxgYM/mFkDEIYYxOMQSQJo0CSQCAkkISkXe2utDlMzp1Tpe+P6uow0z3TPXl2z31dfe1s9+nq6qrqU+c8532fdzSFadaOEl+OOCJKPQtDTsSQVsXHsREyhcWKapVZnfS97LKIlHI8pepP3xOilEAgWCycheKQV0VVZEJee8E4kRULwoLlw7KtvicQlOMM4J1UvEYoGp1XmQQURaka6Xs53UQ3zGmrUwim4hidi0gpgUBwqrOnL8YPnurl4GCCgWGZx+99nq2rQ9xy3hp2dkeWevfqIl+nybndxr7nOmlts2W69D3nuUzewLKsaQtqLDS5wjjCU0eklPCUml9UVeWNb3wjvb29qKqY0ggE1XDG5BGfPSZ3IqWEKCVYTogeXLAi0OdgdC7XEKVM0yoNeieJUj6XgiyBadkV+CI+IUrVi2laxIq56/VFSomINIFAcDKypy/G5x88yHgqz6qwB90LEb+LZ3tj9E1keM/VW1eEMOVE9riVme/BbmV+qu/VimSGUqqcblrkDbOuyncLRSORUq5iFJkQpeYDj8fDV7/6Ve6//348Hs9S745AsCxxxuRO9kK4KEqJ9D3B8kHMtAUrAqMYKTWb6nuV23DIlq3iTh70SpJUTA8QUTyNEctomJYtIDo3vlqIYywQCE5WTNPiB0/1Mp7Ks6UjSNCjIksQ9Khs6Qgynsrzw6f6VkQqX2ORUvNbfc9bJX3Po8o4w4FsfmkFnobS91yl1MaVcN4FAsHKZ3L2Qlik7wmWIUKUEqwI5hIppShO9b3KAaBjcu5R5apil4jimR3lFT5mSqkQx1ggEJysHBtLcWg4SWfEhyRJ5HWTibztbyhJEp0RHweHExwbSy31rs5IMVJqEUWp7DSRUuULR0tdgc9JU6wnfa+8Qp+owDd3LMsilUqRzWanreYtEJzKRDOF4kPF9D3733hGREoJlg8ifU+wInAEJXkWolTRU2rSgGW6yj5gr2YPJ3KiAl+DOIaKTu76dAhPKYFAcLKSyOrkNBNfxO7nBmJZxrMSo4k8Xc0qPrfCUNxcEavVTrqZux6jc0eUMqw5+T1NJ0o5zydzxpLfP3Ja/ZFSiiwVrQFyullXxT5BbdLpNM3NzQBMTEzgdk9vGSAQnIoUPaX8lZ5SqbwhfHMFywZxFQpWBMZcIqWk6p5SzoDXXyU1AMBfEExSQjBpiHor70Fl9T2xyikQCE4mQl4Vj0suRuU6KePOvSeTN/C45OIEYTnjpKi56vJNKt2n5xIN5KTvVau+B6W0vqWMlLIsq6H0PUmS5i2STCAQCOphsqeU360Uq5knxcK7YJkgRCnBsseyrGL63qw8pQrv0SeJUsUBb42VyoAjmIjUsoaYSBVufoE6IqUKkwrTKlVaEggEgpOBDa0BtnQEGYhlsCyrKELkDBPLshiIZdjaEWJDa2CJ93RmNMO+f9YVKVWeojZL4cWyrKJ4VyuayF94PruEolR5Fb16zdZLkWTinicQCBYWzShF4zqeUpIkFVP4VkKkruDUQIhSgmVPeYSTKjd+yTqi1GRT0cw0JqpQiqASkVKN4aTvzVR5D0BV5OLqsjjOAoHgZEKWJW45bw0tATeHhpOkcjqWBcmszqHhJC0BNzef1z2rtPTFphFPKUmSiv26I2Y1Sk43cW7ZNdP3nEipJTQ6d0QpWaqMEJsOjyIipQQCweLgREm5FamiL3UidOOiAp9gmSBEKcGyp9wLal4jpWbwqwh6hAn3bHBugE11eEpBWQU+cZwFs8Q0LY6MJNnVE+XISFJUtRIsG3Z2R3jP1Vs5fXWIrG6SNSGV0zlrjf38zu7IUu9iXRRFqTq9RxyBZrbCixP9pMpSTbHHiaBaSk+posm5qtTtnSXS9wQCwWJRqrznruijwkWzc7EgLFgeLH8jA8EpT2Wk1OyNzidPVLMzpe8VRSnRYdeLZVnFG2A9nlJgH+eJtCYipQSzYk9fjB881cuh4SQ5zcTjktnSEeSW89asmAm/4ORmZ3eEP3vxJiZSOXr6Bljb3cR7r95KpM4+cjmQN+z7ZT2RUsV2OWPWwkupEIlcU+xxPAmX0lPKMTmv97iUtxWilEAgWGhiTuU9f+VCsRMplRCRUoJlgoiUEix7nAgnSbIfjSLXiJTKzGB0HhBG5w0Tz+ropoUs1Vd9D8oipcRxFjTInr4Yn3/wIM/2xmjyudnQFqDJ5+bZXvv5PX2xpd5FgQCwI0hDXhchl12OO77CfDw03b5/uuqMlHIrdr/uiFmNkplh0aj8NaftUuCk73ldDYhSTvreLI+NQCAQ1Ivj8zpZlAoLTynBMkOIUoJlj2GUKu/NprS0Eyk1ufpeZiYT1bLKcIL6iBWipMI+V90+KY6hvEiTFDSCaVr84KlexlN5tnQE8bpkJtI5/G47Umo8leeHT/WJVD7BssCJIHVw0pxXCjmj/gpzUB4NNLvfn3N/9rlrB/T73HJF26WgPH2vXjyFMUdORErNGUVRuPnmm3nBC16AotR/DgSCU4Vo0VKjMjJXREoJlhsifU+w7HE8peTZhElRipSaIkrNUG66JJboWJY1K0HsVMMxOW/21xclBeD3iEgpQeMcG0txaDhJZ8SHJEn0R9MMxnPoLRarIz46Iz4ODic4NpZiU3twqXdXcIrj9I21/r/ccVLNXHWKUo4PlCPaNEq2LH2vFj7X0i8cOcJSvWIdlKLNRPre3PF6vXznO9/h/vvvx+v1LvXuCATLjmjhXhOZkr4nIqUEywsRKSVY9jhi0mz8pMrfV1OUqhUpVRBLTAuy2vwNHk9mU+ZGKu85iEgpwWxIZHVymlkUlZ3CBaUIC4WcZooBl2BZ4ERGObebyZFTyx3NaMzofK7V95yKetOm7xV++9ll4CnlaSR9T3hKCQSCRaJW8aGwT1TfEywvRKSUYNnjeEEpdZZbnoxTfa+8ih+UTV5rDHpdioxHlcnpJqm8XjOiqhFOdlPmYpWPOv2koMxTagknFoKVR8ir4nHJZPIGQa9anBw6AnImb+BxycUQdYFgKXH6xnavVfj/yoyUasjonNkLL+Xici1KfoQrLH3POTaGEKUEAsHCUV58aPJisRMplcobmKZVt+WGQLBQiEgpwbKn3FNqNijS9Ebn0w16i2bn81CB71QwZXYmWi2BBiKlClUO06LKoaABNrQG2NIRZCCWwTTN4gQvpxtYlsVALMPWjhAbWgNLvKcCQSmKtL2QYbTSIqWKolS9Rufq3My8Z/J8LH8tq9m/+aVgNul7bpG+N2+kUincbjc33XQTqVRqqXdHIFhWJHN28SGpSvGhgFtBlsCyICHG34JlgBClBMse3bQHboo8u8tVLURYGWWrkqZpFSMqpl+JnZ/UssmmzKpsD6SDXvWkMmWeSFev8jEdzmp3ShjKCxpAliVuOW8NLQE3+4cS5HUT07JI5QwODidoCbi5+bxusfonWHKymlG83xQjpVaY0bkj+tYdKeVU35ul8JKto/qec+8wraUzDZ+VKCXS9wQCwSLgLH6EvGoxa8RBkqRitFR8hd2PBCcnQpQSLHtMa26RUo5Berm1RbbMfHW6QW/APT8m3BWmzMBzgwmeG4iT100kSaowZV6JmKbF4eEEh4YTxDMa4YbS90SklGB27OyO8J6rt7KxLUheN0lmdfK6ydaOEO+5eutJkRIrWPk4UVJ+t0K4EESazhuzNgFfChpN33OMzvOz9ZSqI5LZpcjFcUFmiRY1HD8rzzTjiMmI9D2BQLAYxGpU3nMoVeAT42/B0iPMNgTLHscodbLKXy9qIcLKMEsDQMeDwqPK027XSS1LzlEwKZoyRxTSmlH8Tqmcjlt143MrDMVXpimz45O1fzDBwaEkiixxxy8Pcev5a+sSBYrV9wopGKLKoaARdnZHuPX8NeR1E80wcSkyb7hkvRCkBMuGcq89Vxp8skzOsJ9fFV7+ZewtyyoKKK5G0/fm6ik1g9jjcysksjoZzaB5Vp80N/IiUkogECxTojNkL4SLopSIlBIsPSJSSrDscarmzVaUKhqdl43/nFXV6fwqoMzvaI6rsOWmzOX+VKlCBNZKNWUu98nyuRRCXpWAW2FPX7xunyx/4RxYVmkiIhA0QjRtR+e1Bj2Efa4V59cjOLlxrkenJLfj7bFSrlPdtHAsm+oVX+YsStV5j3ZEq6UyO59N+p4j7C1VyqFAIDg1iGbsKN3mGqKUk763EhfEBScfQpQSLHscUWrWRudFUao0AHRC7v0zVNSbr0ipclPm8hWJVE5fsabMk32yXIqMJEkEva6GfLLUQpVDmLt3l+DUZDyVA0q/57HC/wWC5YBTAKK5IEY5q9YrpQKfVraiU6/ReTFFbZYpitk60vfKX88u0YJGMX1vNtX3hCglEAgWEMfnNVIjfS/sK0RK5VbGAong5EaIUoJljz5PkVLl1ffqTQ0oekrNUZQqN2XuGc+gGbYp80Ra49BwckWaMlf4ZElSWWlsuWGfLKfK4Vy9uwSnJmMpe3K/pSNo/z+5Mib7glMDx9TciZRqKohTEyskUipXMGlXZanue5QTDTRb36R679F+99JGShXT91yNp++JSCmBQLCQxAoLH7XS90pG52LsLVh6hCglWPbMV6RUecROMTVghlXYYvW9eRjw7uyO8PbLNxP0quR1k1ROJ5M3OH31yjRlLvpkFY6hU73DGZz73Ao5rT6frPmqcig49bAsi/GCKLW1IEo5/xcIlgPlnlJQEqdimZVxnWoN+klBKXJIm4XRuW6YxffNJEo56X1LlfqdLVuMqRcn2kwTRudzRlEUrrvuOs4//3wUZfn7swkEi8lMnlIh4SklWEasLAMbwSmJXki7m20UkSJNjZRK1xspNc8RPGGvynnrmotCWTSt8eoL6zMEX26U+2TJMkQzOpIEbUEP0JhP1nxVORSceiRyOpphIUmwqd0WpSbSeUzTWlGRh4KTl2jZavVxVmCkVIOV96BUfW820UCOwCRJ4J0hAsmJlFqq6ntOFFlj6Xt2W5G+N3e8Xi8/+tGPuP/++/F6vUu9OwLBsiGvm8UF9VrV98JOpJTwlBIsA0SklGDZ41hBzTpSqjA4NqySKJXN1ytKzW8Ez4nxNJIkcfaaJi7Y0EzY56I/mp2XbS825T5Z/RMZAFr8brwupWGfLP88GcoLTj3GC6l6TT4XzX4XLkXCtEopUwLBUqIbZnHAH5niKbUyrlEnoqcRUWouRueOKOVVlRmrsfqKkVKLP6kqr0o4k3hWjnNsdNMqRoILBALBfOKYnHtUuWb/5CwaJ3P6jP6vAsFCI0QpwbLHiZRS5Nldrmq19L16jc4LaWW5Qrn5udIzngZgTYuP7iY/AH3RzJy3uxQ4PllBj8rRsRSaYdIR9pDM6g37ZDnHWURKCRrF8ZNqCbiRJIlmv70iOJYUZueCpccRR12KVIwIdVat41ltRYgSjvDSUIraHESpbN5+j8898+cVRan84kcd5Q2zWJVwNlFkIKKlBALBwhArS92rJe4H3CqSZFe/Torxt2CJEel7gmXPXD2l5Crpe8WV2Bn9KmRkCUwL0jmDiH/2Oq5lWZwYtwWodS3+4k2ibyKDZVkzrggvR3Z2Rzh/QxP9sQy6YTEcz+FxyZy1pombz+uuOy3RX0iTFJ5SgkZx/KNag+7iv8OJHGOpPFuXcscEAso9PdzFPj7oUVBlCd20iGc0mgPVUyuWC45wUi6mzIRHcTyl5hYpNROOp+FSeEo5qYmSVH9VQrArzioyGKZ9bGeqMCioTSqVoqOjA8MwGBwcpKmpaal3SSBYFjgLIk66eDVkWSLkVYlndOIZrZjOJxAsBUKUEix75lp9zxGzjCpG5zMNBiVJIuBRSWR1Unm9aFA7G0aTeTKagUuRWB32FvctoxlMpDValvnEpBqxjMZQPMd565q54axOQl4XIa/KhtZAQ34+fpfwlBLMjvGUHRHVEvAU/nUXnl8ZJtKCkxvHzLx8YiBJEk1+F6PJPBPp/LIXpYrpew0IL5NT1Bq5fxcr79Uh1jhtskshSmmlCLJGF5XcikLGNMgZBiAmgnMhnU4v9S4IBMuOiZTjZTj9/SXsdRHP6HUVJRIIFhKRvidY9sw5Umo6UWqGSCkoLzk9tw67Z8IeOHU1+VAVGVWRWR2xxam+iZWZwvfIwVEMEza1B3jh1nbOXtvEpvZgwwbTRe8u4SklaJDxlL0a2FqY2LcWxKkxIUoJlgETheuzOVApPDj+UivB+8yJCHItUopavYtGULqHL8WCRq5Yea/xSKe5pDcKBALBTDj3lpkW00sV+IQoJVhahCglWPY4kVKzraRV9JSySr5S9XpKAQQ9jhHg3AQTx09qXYu/+Fx3kw+AvujKW+lL53WeODYOwBWnd8xpW0XhLyduioLGKEVKldL3QHhKCZYHpRSKytVqZ/U6tgLMzh3hpNEUNeeWnW8whS87m/S9JfCUymqNe205CFFKIBDUi2laHBlJsqsnypGRZF2m5M69pXmGSKmSKLX870WCkxuRvidY9phzjJQqTxswLAsZqVjlbSZPKQC/Y8I9R8HkxFgVUarZB0ehdwVGSj16aIycbtIV8bK1IzinbYlIKcFsyGpGUSx2RCnn34lUfsV6tQlOHqJpJ4WicrW6ufD/ifTyj+grilINii8eVSGjGY1HSjWwaORESmV1A9O0Zr14NRuc7+VpoPKegyNkNSrYCQSCU4s9fTF+8FQvh4aT5DQTj0tmS0eQW85bM61va7RK6ng1Qh77dREpJVhqRKSUYNkzV0+pClHKtDBNq5iOUE96QKBgwp2cgyiV0w0G41kA1jZXi5Syzc5XClnN4NHDYwBcfnr7nCf+/jKzWlGWVlAvjm9UwK0UBeYmnwtJgrxhkRCRd4IlptzovBxHpIqugEgpzbD75EYjglyqfV9oVHhx0ve8DYhSlmULU4vJnNL3FBEpJRAIpmdPX4zPP3iQZ3tjNPncbGgL0ORz82yv/fyevljV91mWRSxTqr43HeGCaBUXkVKCJUaIUoJlj2HagzZVnt3lqkiVolT5wLUeT6mAEyk1hyie/mgW04KwT63I714V9qLKElnNXFEeOE8cGyejGbQF3ezsqq/C3nQ40WiWtTRVlAQrE0eUKjeKVhW5uDI4nlw5vynByUfFxMA32VPKvmajKyFSyrD7ZFcD6XsAnlkKL41U31MVGXfBvyqzyJG2c0nfc6KrhCglEAiqYZoWP3iql/FUni0dQYJeFUWWCHpVtnQEGU/l+eFTfVUXcuNZHcMEWWLGinrCU0qwXBCilGDZM9dIKVmWit4WumkVxSWPKte1TX8hUio1ByPVE1X8pMD+To7ZeX90ZaTw6YbJIwdHAbj8tPZ5SZdQZAlvYZA+l+MsOLVwhNzWSdXLWoOO2bnwlRIsHfGsjm5ayFLJ2NzBSd+LZrRlHyWr6fb+NZq+N1vfpGwD6XsAvsKixmIvaDgRYLMRpVwiUmpekGWZF7/4xezYsQN5lguXAsFy5NhYikPDSTojPiQJDg8nOTiUgIItQWfEx8HhBMfGUlPe6/hJhX2uGcfojiglIqUES43owQXLHmOOolT5e03TKqUG1BElBSWj89QcUoEck/Py1D2HNc2FFL4V4iv11Iko8axO2KdyztqmeduuE5G22KvdgpWLU/K4ZbIoFXDMzpd/FIrg5GW6iUGkkGaqGday99Jz0tQaMTqHkiilzTJ9r570eihFPC9+pFRhgavOsUQ5zrHMCU+pOeHz+fjFL37BJz7xCXw+31LvjkAwbySyOjnNxOdWyOl2NsVEWisWz/C5FXKaWTXCqV4/KYBQIZIqmdWFfYZgSRGilGDZ44hSqjJ3UUo3rYZXYZ3UstQsq+9ZllUzUgpKvlIrwezcNC1+fWAEgBdvbUdtcJIyHcWItDlWORScOhQjpYKVopQjUo2voJRYwcnHdBMDVZEJFRY8lnsKX77gKeVq1FPKEV4a9HpqJH0PwOeWK963WDjelCJ9TyAQzDchr4rHJZPJGxWL4iMJOwI8kzfwuORipFM5JS/DOkQpj4ok2RXKRaaCYCkRopRg2aMXBsTKHMy0ncp9pmUVB671+ElByeg8PcvOOpbRSGR1ZAm6mqau5HU3L3+zc6cc7Q+f6uXoaAqfS+aCDc3z+hkl7y5xUxTUx3ghPa8l4Kl43hGlVpJPm+DkY2KGktyO+flyNzsvVt+bZaRUXm/svla8RzeavrfIkVLOcak36rockb4nEAimY0NrgC0dQQZiGZJl0VDRjEZOMxiIZdjaEWJDa2DKe6OZ6gU2qiHLUjEjRPhKCZaSqfKqQLDMMKy5p+/JZZFSjVT2gbJIqbwxqxLzTpRUV5OvqifHqpAXlyKR001Gk3naQ54pbZaSYjnaoSRHRlMYpsXO7jAHh5LTlqNtFGcCstxTWQTLA8O0ipP5Kel7QREpJVh6nAioSI3V6ia/ixPjy1+U0mbpnVSsMNdAipppWkUD8UbT99KLHCnlRF03KtbB7P22BJWkUik2bNhAPp/n+PHjNDU1LfUuCQTzgixL3HLeGvomMjw3EEeSJFRFQtMtnu2LsbEtwM3ndVf1jIql60/fAztaKpHVhSglWFJEpNRJhBPNsqsnypGR5EmTGzwf6XtOpJRhWMWBa92RUu5SyenZpAf0jNtpeY531GRk2TYshOVndl5ejlaW7UmJ1yUznspPW452NhQjpebg3SU4dZhI5zEtcCkS4Unh645Ilc4bwqNMsGREZ4qU8jlm58tbPC1GSi2C0Xl5dVxvnZ/n3Muzi/xbzxUjpWaRvqc2LtgJqjM6Oko8Hl/q3RAI5p2d3RHefdUWgl6VvG6iSBJ53cTnUnj3VVtqLgxPpOuPlILyCnzLe4FEcHIjIqVOEorRLMNJcpqJxyWzpSPILeetmddolqXASd9T52J0XohuMiyrOHCtV5RSFRmPKpPTTVI5oxg5VS/T+Uk5dDf7ODGepnciw9nzaB4+FyrL0QZ4fjCJJEmsafKxptnHoeEkP3yqj+2d4XmpwFeqcihEBMHMOCbnzX73lOhFj6oQ8torf2OpHGvctX97AsFCMeGsVteMlHIX2i3viYAjnLgajAjyzEaU0pxUQaluz0LHHzK9iPcO07QYiGUYS+YYSeQwTauh++Bsjo1AIDj1WBX2cvaaJnK6yesuXsddT/SgyhLuaTz3GvGUArsYB4gKfIKlRYhSJwFONMt4Kk9nxIcvopDJGzzbG6NvIsN7rt66ooUpw7QHbfIcPKWUQqlgwzSL0U71Gp2DXYEvp+dJ5fSG0ut0wyxGP00rSjV5AeiLpuve9kJTXo42mTOKvlirI94p5Wg3tQfn/HnCU0rQCLVMzh1aAm4SWZ3xVJ41VapeCgQLTXFiUCOFwpkwxJa70fksI6UcEauR6ntO/19vej2UPJ0Wy+jcWQR88LlhMnmDsVSex46MNbQIKDylBAJBPfRMZJAkiW2dIS7c0MJQPMtvD43x+LFxTl8dmtI+qxnFvjBSb/peoQKfSN8TLCUifW+FUxnNEiToVVEkCHpVtnQEGU/l+eFTfSs6lc/xlFLl2V+uTuqfYZZV9mnAnDTgcXylGuuwB2JZdNMi4Fam+N6U40ya+6PZZWN2Xl6OdjCWBaAt6C4OpqcrRzsbHJFQVN8T1IPjF1XrdyXMzgVLSSZvFNO7pvOUguUdKWVZ1qwjpWaVvtdgej2U7h2LkapbntLuUuzKV00+F8/2xhpKafcUohxE+p5AIJiO3gl7sbq7yZ4nXLShBYDnB+JVI5viBZNzn0upe57jWCA47xUIlgIhSq1wyqNZRhI5nu2NMlwoFzo5mmWlohcENWUOnlJOlJVumsWBayORUk4FvkYFkx4nda/VP61BenvQUzQ7H0nmGvqMhcIpRxtN54uVPFZHvMXXpytHOxsc4U9ESgnqYWwGUaq18Px4UohSgsXH8YkKuJWiADEZx2sqnTfI6ctTjNdNC2edZLZG57kGhJeiyXkDopRjiL7QkVKTFwEV2R5nhX2uhhcBHcEut8jm7AKBYGXRO1HpS9sR9rK+1Y9pwR+OT0xpP9Fg6h6UIqXiIlJKsISI9L0VTjGaJaKQyGq89KHv8daf/CeGx4vm9qK5PaRkFx1faoJICP7lX+C88+w3P/IIfO974POB12v/W/73VVdBd7fddnQUenpKr5W3d7lgDql1M2HMh6dUYSxtlFXfq7eyD5RX4Gusw3b8pNbOkD4kyxJdTT6Oj6Xpm8jQEfJO234xcMrR/mr/CBL25N/rso+DZdl+GmetaapajnY2BESklKABHLGpNVA9ndYRq0QFPsFSMJGaeWLgdSl4XTJZzSSW1ugI139PWizKo5warTI3m0ip9Czuz75FSt8rXwSUJHC0J0WWGk5pdxUW2fLG8oiMFggEyw/dMIuZCt1lxZIu2tjC8bE0Tx4b54rT2isWvaMzeBlWo2R0LkQpwdIhRKkVjhPNkskbNPtd+PIZfLkM5CZVcest/JtMlp57+mn4/Odrb/y++0qi1I9/DG95S/V2sgx33QW33mr//yc/gQ99qCRalYtYXi+89a1w6aV22yNH4P/+r/S631/5vi1bSpFShg7xuN22QSGs5CllFQeujazEOoJJutFIqULY7dpp/KQcuh1RKprh3HXNDX3OQiDLEtef2ckv9g2R0QzWt/qLot5ALENLwF2zHO1s8BcipbK60bBprODUwrKsool07UgpW6wS6XuCpcCJlJqp+lGTz82gliWa0egIL/1ixGQcQUmVpYb75Nn4Js0mvd63SOl75YuAmbyBZYEslRbMfG6FoXh9Ke3F9D3hKTUnZFnm/PPPJxaLIc/B4kEgWI4Mxm0LEJ9LKUZ/A+zsivBjVz/jKY3DI0m2dJS8pZzMhnr9pADCRU8pbdlYiAhOPYQotcJxolme7Y2xpSPATy+/mV+dfQVbQgqtssHwUJTTIyqvPbMdOZeFbdtKb77gAvjwhyGTsR/ZbOnvTAZWry61dbuhq6uyjYNp2q87jIzArl21d/qqq0qi1K5d8P7312xq3vElJpouJqMZRO//GW1vuMV+QZYrorVUr5e1L3sZXH+9/fpzz8Hf/E3x9csm8pxmKKz6ZTvnxXQObL8A7zWn2W1jMfjtbysFsXIRLRQqeUrl6l9FSGQ1xlMaklQKu50OZxWkbyIzQ8vFI57R2N4VYSSRRTcsjo2m8LhkzlrTxM3ndc+rgb6/MAmxLEhrBkGP6J4E1UnmdHK6iSRBc43VwJaCAXoso6EZZsN+OALBXIjVmULRHHAxGM8Wq0kuNxyT8kZNzgG8rsaNzmfjKeW0zekmhmmhLNCCRvkioOPlEvaqxSiFRlLai+l7yzRtc6Xg8/l47LHHuP/++/H5Zh5nCQQrCWc+0N3sq4iGcqsy565r5rHDY/z+6HiFKFW690y/IFJO0KsWoz9TeQOPGC4JlgAx61vhyLLELeetoW8iw6HhFIQj9Co+Yh4VtyrT0uXmVVdvRa4mHlx6aUkcmonXv95+OFgW5PO2OJVOQ3NZZM9LXgI//WmlwFUuZp1zTqltVxe89rWVbQuPXCLFj45l+H1kHMO0uHvgMH/lvM807c9N25FIEqBks6XtDg7Cj35U/O8ZhQdAF6C98X343K+xnzhwAF72strf/e//nsBb3weAcugA3HBBZTRXuZD1ylfCm98MQN+Rfq79n3/DE/LjPbR2aurjaafBmWfan6HrrB/pITIySCzlw0ysQg74bfFtidAMk98dGaMl4ObPL99ExOcikdUJeVU2tAbmPZJJliV8LoWMZpDO6UKUEtTEScmL+Fw1y8bbXj4yOd1kIpVfllEogpMXx9ejeYaJgbOaHV2mBrOOWftsRN1ZRUrlZy9KgR1ptVD3jvJFQOc7ORO/RlPanVRI07JTdGr1YwKB4NRlsp9UORdtaOGxw2Ps64+TyGpFX6hilG4DkVKKLBFwK4VK2xoevxh/CxYfcdWdBOzsjvCeq7fyg6d6ebYvRjKrk9MNrt2+mlvOr79EcUNIEng89qOpqfK1zk77UQ8XXwz/+79TnnYq3Iyn8rgTOVRZ4silV/La0x9ilcvizy/u5owmV1Hw0hMJBo8eZbuzgdNOgzvvLL7+7KFBxsfibPJLDA5NMLDhjNJA1u2G888viVzlApqmgddb9JTSE0kYHq79fc46q/jnyLE+rrj7q7XbvvvdpfTJkRFaLzibD01u43bbItZtt8G//Zv9XDptC3+1vMAuvrgkIFoWfOUrle3KH21tsHZt6fN0HVT7uz7TEyWZM4j4XJy1pmnBVp/LCXhsUSq1CFWUBCsXJyWvdZqKlpIk0Rpw0x/LMiZEKcEi46SXzpRC4YgasWVagS8/h0ipoqdUA5FSxfT6BjylZFkqCtCZ/MKJUs4i4PGxNLt7o/jdKiGvi2RWbzilvfx45oUoJRAIqtAXrS1KrY54Wdvio2c8w1Mnolx+WjsA0ToXRCYT8roKopRO2wyilGlaHBtLLehCteDUQ4hSJwk7uyNs7wxzZDTJFx46hGZYvPbitZy2KrzUu9Yw5RVuNrX5iyvOYa+LSHcrh4aTfLfP4O/OOa3YCVqaRjZWVoq5uxve/vbif597ooene6JcvLGF3x8dx6PKJZHl7LPhySer74xhgGkSiNv70LdqPezeXTWyi0ymQpQ6kVf47ctez9aIiw7VrBS7slnYurX0OZoGkQhGOo2ilU1O8nn7Uf5cKgWPPVb7AEajJVEqm604DlN4xSvghz8s/d9rT9wtn48dioutLg/uUAAlFIDLL6/0IPuzP7NFr2oRYxs2wI03lto+8ogtZPp8oKr4h4bsaLZw2H6ukP5pi3/5htIkFxJx412eOCbntfykHFqCtiglzM4Fi00sU2f6XuF1R8RabjgRQY1W3oNSNFAjkVLZWXhKgV1N1xGlFpKd3RGu27ma3ok0Oc2kP5qZVUq7IkuosoRuWuR1kwbnj4IC6XSa7du3k06nOXjwIJHIAizCCgRLQF43GYrbGSBrahRLumhDCz3jfTx5bJwXb23Dskr3nkgDRudgpycPxGzrEai9iLenL8YPnurl0HCSnGbiccls6Qhyy3kLFAQhOGUQotRJhCxLbOkI8aKt7Tx5fILnBhIrUpQqr3BTbmYuSY1XuHFwBKhkQeyoe8CrKKAoBDz2oDqGCmfunPFtpmlxUA6y5y1/zfteshVmitJYtw6iUR7Y3c+j+4d54dog129pKglZwbLvGQrB3XdXT43MZm2RrbQjtjiUzdoRVpNFtLa2UltNs0U4QEom8QN+gNHC6+vXV+7z179uC2bVuPLKSlHqxhthfBwAF3BNedsLL4THHwfsSKm/+Js30JFLQChQ6fPl98OWLfDpT5fee8cdkEhUjxhrbobLLiu1HRy00yGddur03Z+48S5fHJGpeQZRyomkEmbngsVEM0pm1zOtVjf57NeXa/pe0VNqFpE85ZFSlmVVeKLUIj2L9D2n/QTaglfgAzul8bx1zezsjnBmd2TWCxZuVUbPG8LsfA5YlsXx48eLfwsEJwsDsQymZfvW1Yq4PXNNhHt3DzCazHN4JEV70INZKMAQajBi1DE7j2dqLwqXZ7F0RnzFog/P9sbom8jwnqu3ivGxYNYIUeokZHtXuChKvfzs+gaCy4nyCjeOCagilfSpRircOEwWpfwNpAYARaPzvGGvas6UyjCUyJLTTTyqTEeoesn6anQ3+bAUhRM5qVIwKsfrhZtuqnPHA3DPPfW1VVUYG4Nslrt+vZ+BwQkuXO3nsu6ALWC1tFS2/9SnakeMbd9e2XbzZvv9mQxWJoORTKJoGpJlFaOzwI6Uah7qxRsbr76P555bKUp99rN2BcdqbN1q+4U5vPSllQb8qloSsNavhyeeKL409pa3Y/1hD9fKLq73+7G8XjKqmwlT4UBTE9z+ydKN98EHYWKiukm+3z9VzBPMmfH0zOl7AC1OBb5kbsH3SSBwcFaq3Yo0473GWc2OZ7RlWXU0X/SUany/HE8pywLNsHCrM28jO4v0vfL2Cy1KaYbJoeEkkiRxxentNSMY6sGtyqTzRtG3SyAQCBym85Ny8KgK56xt4vdHx3ny2DiXbm4F7AjdRu8lToEGp4jDZMqzWLZ0BAsFZwyCXpUtniCHhpP88Kk+tneGl919TLAyEKLUSciWjiBuRSKW0eiLZuY0aFoKKivc2JPPsM+FbWfeWIUbh6IoVRCyGl2FtdP9wDAhnddxq9NPhnvG7ZvJ2hZ/Q6KgU4FvIJpZ/AmKJEFLC/3RDM+425DXt7Hj2tOpmVfwl39Z/7YLkVAAuqZx//33c/111+GyLNvHqkDArfBfH/kyF7W5uLQrUBK5nCivckN9gFe/GgYGqkeMlXtlgT0zKkfXIZm0H2WRaKZpkfv1I5x5eF/VrxILNvFvT72zdOP9x3+Ehx+u/r293spKlTfeCL/4xdR0R+fvhx4qmdt/+ct2qmh5WydyzOuF170OXIXVs0OH7CqSk830fT7b922FCdMz4URKzZi+V3hdpO8JFpNoQTRt8rtn7P/DXrV4b4lltBmj/xabkqdUY/dMqIyuyhszL+bA7KrvQUmUSucXNvX76GiKnG4S9ql0N82t2lsxvbEBzy2BQHBq0DthF3KaaQ53UcGWZG9/nHUtdlsnArcRHKP0Wgv+5VksWc3g+cEEsgTnrG1CkeVZZbEIBOUIUeokxKXIbF0VYm9/nOcGEitOlCqvcONESjm+G41WuHFQJ6fvNbgKK0kSAY9KPKOTzOkzllo9MW7fTNZOs8JRjfagp2jYOpLMsWoJzJkfOWjn653ZHWmopGzDSJLtJeUpRZL53AqDG06nd10TXLC29nsdPvnJqk8XvaB6oqXUil277HTGXG5qZcgyjo2l+MENf0pnJo7fzDM6EsNv5OnygCufIy2rlTfes86y0x4dUaxcHJtcojqZrKgaWYHLVVlt8YEHKipITuG1ry39/bGPwbe+Vb2dJMHICLTaK2h89KN2+mctYexf/qUYFde2axfy/v22aFfNWP+ii0rfMZm0hT6/3/4uCySE5XSjOGhqDUwfhdgWtK/fiXR+WUahCE5Ooun6/KTAvrdEfC7GUxrR5ShK6bM3OpdlCZcioRkWmm7CDEHDlmXNKX0PSqLWQvHcQByAM1aH5hyFXkxvFJFSAoFgEk6kVPcM84iuJh9rmn30jKf5v139jKfyrGn2NTzmcRb6a4lS5VksvRNpLAsMC0YSOVZHfLPKYhEIyhGi1EnK9q4we/vj7OuPc832VUu9Ow3hVLg5NpriWF+KgEclOMsKN+XbhFJ560YHvAABty1KpeswUu0piFLrWhsTBCVJoqvJy9HRNL0TmUUXpWJpjV29UQBeuLVG+uAC4qRJ1nOMazGjF5QjqtQgkdV54oxL2NAWYCKV48iofS53dIUJeFQM0yI3mirdeMvN32firrsgHq8UrhwhS5sUMv3a19qCV7X0yGy2FCUFdgXMNWsqt2sWJjqOGb3DsWPw7LO19/FTnyr+2fn736Pcf3/ttocO2amZAJ/4BPzzP9t/y3Ipqsv590c/sqtiOsfhe9+r7gXm88Gb3gRdXaXPOHCg2CauS7T1DeMK+PFFV9nRc67qk/+w11U0E16OUSiCk5NGRCmwfafGU1ohwqr+xZbFYC7pe2BHA2mGUVc0UN4wMQsBrV53YyKYkyaZyS+cwGNZFs8NJAA4Y/Xc/To9QpQSCARVyOQNRgsFXaZL33NoC3r40TN9xDM6hmnRO5FhNJlryAM1XIyUqp6+52SxpHI6o2WWCINxewF9NlksAkE54so5STljdQhZgsG4XXlqpjSX5cbO7ggv3dlJXzRDXjfpm5hdhRsHdZKA1ainVPl7pqsMZ5oWzw8meG4gjkuR6Y40Ht7f3eTn6GiavmiG89c3z/yGeeTRw6OYFmxqCyxJhJ2/mIIxO1FqPkwYy9NHyw2yx1J5Ah51bjfetrbaXmGTefWr69/uF75gPxwsyxa5HJGqXJT6m7+BN7yhespjJmNXRCwQ3bwZ87WvRc7lqrctN+AvT1M0zVJqZDWefRZ+8IPa3+eaa0qi1Pe/b+9zgXbgA+Vtf/UruzIkwH/8B/zt3xbFLdnn4y/ykFHcuL/UDP/8STj/fLvt44/b+1AuhpWLY5ddVtqHaBT6+6e2cbtPutRIwdyZKEvfqwe7XaooZi0nHDFpNtX3wI4GStVp5p0tCEqy1LixulO8ZCHT9wbjWWIZDZcisaVj7ukp5UbwAoFA4NAXtRdDWwKuQlXq2uzpi/GzvYNE0xpel4IqSzT5XQ2bj4d9pUipakUDnCyWxw6PoRsWXpeCadk+u+PJHONpreEsFoGgHCFKnaT43XbK0pHRFM8NxLlsy+JHvcyVrGZw3rpmzl7bxPbO8Kwr3ABT3jOrSKkZonicCJ3dPVFOjGfwumX+9RcHGq7W5oTq9k1kZmg5M8U0tqw+4/HLaga/P2objC9FlBTY0Wgwu4lFNRPGWCZPS8DTkAmjc+Pd1RMtGBbbbcdTOdY2e2eVPrroOKmRbneFyATAGWfYjzroufpqzrz+euQakUgVfO5z8JnPlPy/nDTFdNpOmSz3+Hr5y23BZ7Iw5jxWlUV3trfbQlLhtVwqjZlK49LzqLlcpeAWi8HoKOV0OX/sAaL/X+mFp56y97cW99xTqiB5773wxjdObSNJ9ud/7Wvwylfaz/3yl/ChD1X6f5WLWW94A1xyid32xAm4775KUazcP2z9+lLapWHY6ZFCCFv2FCOlalRMmozTLppZft5nxep7cxClgLrMvB2Tcr9baTg1bjHS954vRElt6QgWTdznQtFTSkRKzRpJkti2bRvJZHLFFfURCGrRUzQ5n35x2Bn3xjIaG9v8jCZLUbphr6sh8/FgYY6jm1bVghFOFssjB0eJZzXagh48qsTx8Qx7B+Ls6Io0nMUiEJQjRKmTmO1dYY6MptjXv/JEqZxuFCvcXHl6B6sjc0tjmxwp5Z2DKJWsEilVHqGjyBIhr0rIq86qTGp3kw/Lstg/GOfpExNEfK5ZiXEzprEVcISr3xwcZSSRY1ObnzNWhxr6rPnC73Gi0RqfWJSbMJqWxYHBBIYFO7oUAh61bhNG58a7py9GLKPREnBjWhapnMme/jhdEZ+48VajXAhrapq+7UUX2Y96eOtb7UeBnzzTx++OjHPF6e1cu62jUqB561vhuusqBK4n9vVxqGeUHc0uziqvCnnWWbZZfz3CmCzbPltOO2cV0bJs0a3cC2xwsMLYfwoXXlgSpXbvhne8o3bbL3wB3vlO++/f/AauvLIkhJUJXqrXy9qrroLrr7fbHj4Mf/d31atB+nzwwheWjn8yae+v81q1dEql8f7yVMYRl+qPlCqIUssxUsrxlJrlNeBqQHhxJkKzuT8vRvW9fUU/qbmn7gF4XEKUmit+v59du3Zx//334/evLP9UwdLQyGLtUuEsSs9UTKF83CtJFEUpjyIjSVJD5uOqIuN3K6TzRk1fqNagm03tQY6NJlFkibRmohkmYa/KKy9obAFeIJiMEKVOYrZ1hrl39wBHx1Kk8/qMIaDLicPDKXTTotnvYlV4BnfUOlDmIX0vUKO6z+QInYNDCSRJoi3ooT3kabhM6lA8w67eKBMpjWNjaUJetaqYNB31prEVhauhJIdGkliW7Zuxtz++JDcX5xrNaAaGaU05b9NRbsI4lsxhFHSD0WSOgEdtyIRxZ3eEc9Y2FVI17FS+vG7SGvA0JDAK5p+xgs9Ca8BdKQaBLRwVTNodtM2j7N49gNEV5qzOztILL3iB/aiH173OfkApNbK8MmRHR6nti19s+2dN9gBz/j7nnFLb9nZ4xSuq+4ZlMpXinmPI7whhZWb5EuC6+OJS24EB+M53an+ff/qnkih1+DBcfXXtth/6UMln7NgxO1WymnDl89kRcG96k902kYB//dfq0WI+H2zcCI5IaJrQ01O5LXXl3K/KMQv+ZVAq0DETjng1sYxFqdl6Sjlpf1odKWqZ/OxFqbmmfs9EIqsVjYfP6JyfRRtHsKsnikwgEMydehdrl5reYqTU9KJU+bhXkaEj5EY3rWIxp0bNx8NeF+m8QbxG+8ePjtMScPPCreu5bHMbiazOY4fHODaWYjiRq/oegaBeVuaoT1AXLQE3nREvA7Eszw0kFt2faC44FW62dYbnJSRbmbQN36w8peyfy+QonvKVipxukChEUgU8asMrFbaYdIhkVsetyrQGXPjdjeWGTxbJ7FUPDa9LZnN7gMMjKX74VB+WZfHvDx1iPJXH55aL6Q9DiSyff/DgkogvfpeCJBXm3Xm9WKK2HkpeUHrFzXEsmWdti78hL6hUzja0P29dM6+8YA0DsSwPPDvIqrCHbZ3zs0q+VKyEVcLpGC/4fNXrk9dSqMA3npqn1KjyiLBIld9Hd7f9qIeLL4Yf/rC+ttdcAxMTVas86okEAz09FJMyN2yA22+v7huWTsOZZ5a2K8u2OOQIbE77fOF4ecuiVJNJO+WwFhs3lv4eG7OrQtbiz/8cvvQl++/xcXufy3G5SgLWa19rfx+w9+ulL60ujHm9cO65lZUpv/lNu8JntRTJ5mZYvbr2Ps6CRE7HMG1fpHCd/ZcTKRVL57Esa1mlIeUL6v5c0/fq8U0qT99rFEfIWqhIqf2DduremmZf3ed1Jorpe8JTSiBYcObDc3QxSGQ1YhkNSbIr601HuQdq0Kuyoa1yjtGoB2rIqzIYh2QVUSqnGzx9IgrApZtai/OZ1REvt//iIHv74yvSw1iwfBCi1EnO9s5wQZSKrxhRyrIsnh90RKn5WZFUJ63yzsZTKuip7nfkrFRobpMDQykME3wuuTiwrnelolxMWtfiZzCeI6OZdITVhjyRKkUyk30D8WK2kSTZURW/2j/E3v4YsXSeTR1BeicySJLEmmYvnRFfw9Fd84UsS/hcdvhwJm80JEo5XlBPHpsgldNRZAlVlsgbFhOpPOOpfN1eUPsG4piWHTp9/voWTNNiV0+UZM5OKz19idIb58pKWSWshWlaRRPp1kB9EZTOAGk8tfwm/A2hKDXTIi1NI1NeJXHNGnjve+vb7plnwt69U583DNsLrDwabfNmO9WvVmRXeRSY328LT5OjxZx/N20qtc3lbOEoV7bSqmn2I5GAVKr0fDpt+3bV4jWvKYlSul6K3KrGDTfAj39c+n8oZCvi1SK7Lr20JIwBvP/99vYnCV26LnH6uMLwi64u9Z1PPml3vqqKf3DQjmQLh4tm+ZGCp1TesEjnjWKq+HKgFCk1S1GqgfS97BzS94pRtgsUKfVcMXVv/vp+T+F7ivS92ZNOp7ngggtIJpNcccUVRKotFAhOeSYv1jrjgKC3sfH1YuBESbUHPTP2hc6499neGFs8wYrxjWVZDXughgv3oniVCnzP9sbI6SZtQTebyxbYV4W9bO0IcnA4yaOHR7nhrK4p7xUI6mH5jHwEC8K2rjAPPj/MwaEEmmHOiznnQtMzniGZM/Co8ryZScuTJqKzGvQW/I6SkyKlQl6VnG7w3GAcVbZXJLaW3fTqXakoF5PyugHkiv5VjURclYfz9oynsCxblLMsC8MEw7KIpjViGZ2AR2X/oF0hTZagI+RtOLprvgkUctpTDU4uHC+oJ46OE89qdDf5CHpUeiYyPD8Y54zV4bq9oHb3xgDYuSZS3PbO7gi/OzLOrt7oihSlVsoq4XREMxqmZXvEOZViZqLF70aS7BSZZK6x6LtTGkWxhaVyfD7bE6seOjpKkVAz0d1ti1WmOdXfK5utNOv3+eDb364tdp19dqmtYcC111Zu0zHin5weaVmlapHlIpjDpLRQvvKVqu1agcu3ncvPr31p6ck//mMYHMQFXDP5Deecg+vppwl5VRJZHeXaa2B0pOTx5feX/l6/Hj7xidJ7v/51iMerR42Fw6VKk2AXAVCUhj3CHMFkLtX3yrczHY6gNJtFI+c9mmHN+1hHM0wODdvXxnxGyjopkUKUmj2WZfHcc88V/xYIqlHpvSQRy+QZjudY3xrArcpLOuadTF+dqXtQGvf2TWSK38/ntsd2A7EMLQF3Qx6ozjwlkdWZ3IM6hZAu3NAyZXHvhVvbODic5MljE7xk26pZzbEEAiFKneR0RbxEfC5iGY1Dw8kVkXr0XCFK6vTVIdR5Gliqk7xnZpe+pxDPaKRyOkdGkmxoDSBJ8PxgnIxmkMrpbGwNsKkjWBTBGlmpKBeT3KqMJNmpgqmc3pAnkhPOm8hqjBb8d7Z2BAl5VfK6xXgqR49MwSPJRd6wS7p2RrzF491oHvp84isc56dPTGBZVkPpZVs6gmxoC5AvTErSBS+oiE/lT1+0sS7RxTm/AGeWtT9nbRO/OzLOvv74ihF4HSavEhqWRTKnEfG5lt0q4XSMp+xImuaAu+6IJ1WRifhcRNMa46m8EKWWM7JcEmFq4fHY0VD14PHAT35S/+f391f3Actmp4pSf/d3tig1KVpsdDTG8VAXTb6yFIauLlBVrEwGI5lEyeeRnAl0IT0y4nPZotT+AzDYX33/du6sFKU+9SnYv7962/XrbQ8wh5e8xI7YAjs1sjzCq6sLfvvbUtsPfxgOHgSvlyvGciQlFx0Pr4aWsC12vf/9pbaPPQbR6FRT/cK23Y7w0kD63mzuz16XXEz9zmjGvPbPR0ZS5A2LiM9F5xyLrpTjKQp2C2fOLhAIKsfXlmVxdDRNXjdR5DSb2oNLOuadTO+E7Rc5U+U9h53dEd5z9dZiFPxQ3I6CP2tNEzef193QYmNRlMrplL+rL5qhdyKDKkucVyXrZmtHkI6Qh+FEjiePTSxZBW/BykaIUic5kiSxvSvMY4fH2NcfXxmi1AKEyU82zG50JXZPX4zvPH6CPxyfwLAsJn6UZ1N7gKBXZTylsbEtSMCdxQLSOWNWKxWTc8Pbgm5GEnn6oxm2rgrVHXHlhPP+5uAopmkRLFQCBAmXYt+cz17TzHA8S5PfTdCrAhZ2Yp9No3no88WevhgPHxjh2GiaIyNJ2kKehtLLdvVECXldvHTHam48p4tkzuDe3QMkslrdZrJ7++3Uva6Il7ZgKUVsXYu/KPDuH0ws+6iiciZXaDkwkCCZM1jf6mdV2LusVgmno8LkvAFaA26iaY2xVJ718xR9KTjJkCQoN8KfiQ99qOrTvy1Uh7yy3OT8D38AQNc07r//fq6/7jpcYAtZhi1INPvd9E5k2PeF/+bsJqUyssuJ7pqcmvSyl9lVJKv4jE3xNctkSn87qZFx+16LPmki9tBD8PvfA3A2k2hqqhSlPvIR+MUvqh4LFAXXrl6gYOb9+tfDz35W0w8s+9EvAoVI5m9+E559troXmGOq7y70Az09SMkkq0cHSMguciPjsKrZFt/mIV23fEwyn+m/HrWQvic8pQSCBaV8fJ3TjWJ04lgqT1eTgW5YSzLmnYxlWXWbnJezszvC9s7wnP1CHb+8RLZSlHr86BgAO7rCRSuTciRJ4rItbdz9dB+PHh7lBZtbl/UCp2B5IkSpU4DtnSEeOzzG84NxTNNa1h3FeCrPUDyHLDGvKVLlopRHlRuq6lae9uRWZVRZwuuS+cVzQ4DE2WsjvP3yTbgVeU4rFZNzwzsjPkaTeSbSGqmcxkAsW1fElSxL3Hh2Fw8+N0w6r9Pd7MMwIZPXiyLZm1+wnruf7pu3PPT5wDnOQ7EcblWmLeihyeeuO73MsiweL4QXX7Sxlc0d9vWT1Qzueaafp45HeeGWthknFc/22al7Z66p/CxJkjh7TYRfHxxlV290RYlS5auEo8l8MQW1byJDa9C9rFYJp6NRk3OHloCbwyMpxpPzZHYuENRgonCNOhX1qiJJtmDiLrVxKvX1bN3J2fV6cnz2s/Xv2K5dU1MjHSFrMh/6EPT1QTbLQ08fR8pkuKTTj8/IV+wzAFu22Eb11aLLXK5i+p6mm7b5/ehozV3M/L3dN/tcil3B8gc/qP19EonSvnzkI/C1r/GeyW1k2RawjhwpVcj89Kfhnnts/7DmZjsCrrm59PcrX1lMF3UlElh9fRw9OIRqKmyb57Rt59jkNCFKCQQLSfn42vGuU2QwTOiPpjFMFn3MW41oWiOVN1BkGo7KlGVpzouKjihXbnSe1Qx29djj4os2tlR9H8C565r42d5BJtIa+waWpoK3YGUjRKlTgI1tQbwumWTOoGciPedIgYWs3uWsSG5oDRSNS+eD8kj+RnKdJ6c9JbI6umlxYjyDR1VI5XT8LoVz1jQhy9KcViqq5YY3+VwMJ3Ls6olx+upQ3bnhGc1kW2eYgVgGLDg2mpoiksmSNG956HOl/Dh3NXkZjOcwacyEsi+aoT+WLYQXNxWfP2tNE/fuHmAwnmUglp22mkmt1D2Hs9c28euDo+wfTJDVjBWTN++sEqZyGr3jdmi4LIFuWrYwFfAsi1XCmRhLzS5SqtzsXCBYSKIZ2yC2yd9Ymmik0D6anmowOy8oCgQC9mMmbroJsIX+X9yzB8uC868/A1+11NfpfMNME88Re6Egb5jwn/9pp/pV8wPL2YU9oCBK3XijnYJYzVA/l6usCunzQUsLWiqNks8hO6mRpmmnWHrKiiIcPAi/+13tfb722qIodfpdd+F+4xt5f/nr5SmKjzxSMuz/6lfhu98t+X85fmDO33/xF6VKj3v2wHPPEc7D5gNRgk1BaIpXplOW77NAIJgTzvh6/6AdER70qGzpCPHcQIIjIyl2dEcWdcxbCydKqjPimzf7kkZwIqXiWR2r8PG7eqLkdJP2oJuNbbXvHy5F5uJNrTz0/DC/OTh6aolSum7fa1Ip25synbbvueWVjr/1LRgZKbVLp0t/t7XB5z9fanvNNbB7N3z5y8X78anA8p6BCOYFRZY4Y3WIZ3pi7OuPz0mUWujqXY4oNd9phkqZp1Qj5aYnmyOqioRuWuimhd+tsKUjyFAiV0x7mutKxeTccN20ip5Ir794fV3H2DQtHjk0QkvAzZsuXU9nxFtVJJvPPPS5Un6cHXP3RFYDrLqN1584Zk9+dnaHKwRNn1the1eY3b0x/nB8YlpRyknd627y0hqcOinojHhpD7oZSeZ5biDOuetWRkXLUkrnCKYJXrfChlY/+weTDMWzpHI6569vWfJVwplwRKXmBkUpJw1zTIhSggXEKhSRgMZFKceDKpZZIFGqjHoXljTDKlZudc9mgiTLlUbna9bZlSFrkPnFAQB8bhne+Eb7UQ933AF33ME3HjnKoaEErzqrg3PbvSURK1QW4fTe99pVF+NxmJgoPcbH7X/LvMMky8KSZSSzLJIpmy1Fl6llQ+h9++zUxFq8+tUlUep734OPf5zVwJ9Wa/v738NFF9l//+u/2pFgk9Mdnf/ffnup6uXDD9vbrpXy+JKX2IIX2JOjnp6pPmBery2IrdQqpQJBDZwUt9FkDlmSmEhpqLJES8DN+eubloWI4vhJdU8zTl1IgoWFSd200JiagTBTpsElm1r49YERjo+l+O2hUYIedd6DF2aFaVaKQOV/B4Ol/hbsPjcard52yxb4whdKbbdtsyNx81XGlmefDc88U/r/xz4Ghw5V379NmypFqbExGB629+MUQohSpwjbOyM8fSLKbw+P0hnxEva5Gu4kFrp6VyZvcHTUrmZ0Ruf8hskrZR1pI35S5WlPYKf+ZTWTsFdly6ogEhLR0dS8pj1Nzg1/eP8I/bEM/bHMzG8G9g3EGU9p+N0KF2xoLvpW1PNZS3XzmGzy3hdNk8oZDMdzdIS9M6aXlYcXX7hhanjxeeua2d0bY1dPlOt2rq65AuWk7tW6jiVJ4qw1TTz4/DC7eqIrRpSSZYk/2raKX+wbIqMZrGn2EfS48LtlBmJZXIq0LFYJp8OyrKIoNftIqdy875dA4JDVzKJ3XYXReR00B5xIqYUVThtZWCr3OpqVKEWD1fcKaTWzjUD1uxWQJNKSantflVdXdDjzzMrV62l49m1v4973/j+GJtLcsq2F8zp8lSmKjsgEtl/W2WdXr/KYydgr4Q7r1sGLX4yWSjM6EsOt5WiVjVJbX9mE1JkMVasICfbnODz1FHzxi7W/0E9/WhKl7rkH/uzPqreTJDt18hWvsP9/7712SudkkcsRst7+drjkErvtwYPw4x/X9A3j9NNh1Sq7bS5nfy/ntUkT3nrEU0mSWL9+Pel0el79vgQnH33RDKm8wQXrm3nVBWuRJIlEVuPe3QMMxXNE0/np064Xgdn4Sc0nLkXG51JI5UwyBvRFs1UzEGoR8rpoC7q579kBnjw+QYvfXX/wgmXZCwPlfV75Y9UqeNGLSm0/9KHK18vFo4suqhSPgsFKX8VyLr8cfvWr0v8/9anaaeYjI5X/z+crBanyiOT29sq2L3uZLTQFAqWCLoGAvW+T237jG7aQtm5dzcN1MiJEqVMEzTB5pidKNK2xpy9OyKs2FOE0OY3Nufk3kl41EweGEpgWtIc8FQbT84GilIlSDURKTTYfX98aIJnTaA14kCSJZFZfkLSn8oirjrCHzz94iGf7YlydyNIRqp1nblkWDx+wO81LNrVOK0hV+6ylYvJxXtPs5/hYmt4JO5UwW5g81TrOu3tj04YXO9UHE1mdA0NJtndNjcRLzpC653D2WluUOjicJJ3X5zXNdCE5Np5me1eE8VQOq5DSGfDYhvrrW4PLvppgKm+Q000kqfFIKUeUSuaMFZV2KVge1BtZNFEQlIIepSjG1IsjYiVztglvo++vh0YXlrSCkKTK0qzv606/Uo+ZdzZfqL43y9+n875Mfn6q2aV16IvlkFUXW7d2w3SVO887z37Uw1vfCm99K+mMxucfeB5Zgn+6aWd1UeW977UFr8k+YM7fp59eanvxxXZVyGq+YZNFNI/HNsMv35YTFmdZlemDw8Owd2/t73PddSVR6pln4AMfqN32P//T/v5gG+pff33ptTIBK+fycN/Nf8bdO66cVjz1+/0cPHiQ+++/H/90VTsFpzy/KYyNz17bxDllC4rPDyY4PJLi4QMj3HhOd623LziWZdEXtYWT7iUSpQDCPpVUTiOjwxPHJgB7TFwc6xoGDAxUpqsV/u3tGSY5KDMe3kLAo7LBa3HT1z+NkUyim3mSAYmgnisJSNddV4oQyuWgtbX2jt14Y0mUkiT43Ofsgh3VCE6a0/h8JVHKEYOcfzdsqGz75jfb/aLzennb8j4U7CIfqlpq53bXjjK9/fba320S5vYd9pgjoRPSkksfabZIrIzZlGBO7OmLcefDh0nnddyqTMijNmQgDVOrd/VOpBlP5VnT7KMl4JmX6l3PD9qpe9vnOUoK7EG1QyMD3snm416XUpzQLpYheGfEx/auMPv64/zq+RFedeHamm2PFYQcVZa4ZFNtQ8LlxuTjvCrkYTSZI5UzOD6WwrSmN6F0Uvcu2NBSdWAvyxLnFvyg/nBioqootW+G1D2H9pCHroiX/liWPX3xaY0flwvHRlPs7o3RGnTz9zdsI6+bxQn2cwNxHjk0xn27+9nScVpDRQAWE8ekPOx1NSygeV0KAbdCKm8UfMuWbsAnWFk0EllUSt1rfLXd65LxqDI53SSayU+7+DAbZrOw5AhJcxHI6o2U0g2TvGGLIo0sHJXjvC+tzY8oNZAGfHbUQmg6QWqWeArHxrTsdBmXUqXvDYeLHlcz8oIX2I96eNOb7IeDZdkTPEegKo8yu+46e/I1WRBzHmeX1Whcs2Z6Ea08Ymyyyb6TGjkxgQcYHpqg6QL3vEflC049JlL5YiT8i7ZWRqVcdUYHh0eO8uSxCa44vYOIb/5/6/UwksyR001cisSq2fb/llUSRXI52L+/JBpNfpxzDlx5ZeHDR2wBPJXilX2j6IkkvkwcRTN4aTaD+YY3wIWfs9uOjsLa6vOQNcALLrmOJ97wYRJZg9GUxgt+dXfN3U0dPsahnqi92NPiR5blymij8se2bZVv/uAHa7edXEn3wIGS6C3PcD/7f/9v+tfL2bix/rZ1stA2OcsZIUqd5FQMRNuDHB/PEM9qrGnxNxTh5KRXuUMSB4eSTBQG34eGU6xrMWkPeeZUvcswLfYP2lEq8+0nBSBLs4uUqmY+vhSG4Fee3s6+/jjP9Ea5altHzUiyRw7aK0HnrW9akEH0QlHtOK9t9rOnP8aR0dS0Ju/90Qy9ExkUGc5bXzud7rz1zfz64CjPD8RJ5vQpZW1390YBOHNN04z7e9baJvpjg+zqiS57UcqyLO57dgCACzc0s6a5cjW5q8nHMz1RRpJ5fndkjMu2tFXbzJIzVki9azR1z6El6CY1nhGilKBuGo0sclLvZjOpkSSJJr+LoXiOWFqbd1Fqsj9iKqczXIi8DXjUqgtLjpA0J1GqzkipbJlo5a0jwrcazoJTdo6RUqZpcXQ0xZ4JCa+kccY8V91zKE+JzOvm0karSpK9yu92Q2TSxKezc+okrxaXXmo/ZsA0LY698BoSh4cJo7HeJyPnc5ipNF/52V5O9I7hP2MLQa+KrGu86qv/yO5LruH+NedUjFmdc3U8CUdHU2xZFTklIgoEjfHIoVFMC7Z0BKfc/ze2BdjY5ufoaJrfHBzhhnqrn84Gy7LFWVkuFWuIx+Hpp4kfHWLnnh66VAO59+GSeHTFFSXx6PBheOc7K1PVylPXPvhB+Kd/stseO1YpGE/mPe8pbVfX4dvfBqBarJiVjJb+EwiUooOCweK/GY+P/UmLic3b6Iz4SGST9GQtvnvjn6GGguQ8PqKovOKFp5F1+3ioJ8lew0fPfc+VhJfDQ+zcUOcY9JOfrK8dTB+BtYxYaJuc5Y4QpU5yygeiblXm+HimIoWl3ginkFdFlmFPXxzdtJAle+A9kdY4MZ4hltEIuNVZp7EdG0uR0QwCboW1zfMfgj3bSClYHobga5r9nL4qyP6hJA/vH+GW86eaxQ4nsuwbSCBJ8MIt7VW2sryZfJxzmonXJeNV3axt9tecGDhRUju6IlOEpnJWhb2safbRO5Fhd0+UF5SJL8mczpGCn9l0qXsOZ6+J8JM9gxwdSxHLaEu2slYPT52YoHcig0eVecm2VVNe97oUrtm+mruf7uPB54Y5d13TskxJdPykWmYpSrUFPPSMZ046s/PFmpQtZNXV5Uj5gs7m9kChAIM8bWSRU3mveZa+JE0+W5SaWIAKfOW+fdF0nkPDSUwLRpN51jb7qi4sFSOl5iCWeOqMlHJS7jyqPOvryilikplDpJSzSr1/IM6eERlfMkrI62JV2Dvv93pZlnApEpphFzQJnCIF96aLBPC3t/JIKI7vrA1kNYNoX4xX/OouLnjoHs787U8Y/9v/YJf7NI6NpUjnDb7z2CG+9ME3oukaj/7NV9i2rv2UiCgQ1E86r/NkYZx4+WlTBQ9JkrjqjA6++sgxHj86zuUbIoSMvC3yRCKlQglDQ/Db39b2PLr1VltAAtvf7S/+YqpolE7bwtRnPgN/9Vd22+efhyuuYAuwpdaXcMSjfN72hqtFufdcKGT7MFWLJAoEKtONm5vhc5+jLy9z36Eoh1ImMUvGDIVZv7adW6+/gDOctoFA1bS5Az1RPnnfc2xoC9AkU7TM+PKLXgeAqkgYpoVr81oePzrOeNgWXja4JwkvLlfx91vPuGMxxybz9VnVtgNURDMbpsVIIktHyMOWjvmxyVnuLL+Zh2BeKR+IKrJU7CT29sXobPLSHvSS02aOcLIK2xpL5WgNuDltVZigV2UwluXEeIoT42m2dgTpiswuAuH5gQQAp68OLcyPTYJ4RkMzTCZSeUzTauhzloMh+FVnrGL/UJKnTkxw1RkdU3x1HjloG/NtWx2iPbQyR7eTj7NLkbn76V6SOYPfHBzlyjM6KtrndIOnT0SB6gbnkzl3XRO9ExmeOjFRIUrt7YthWRTSUWeeUDb53axvtX2v9vTFlm10UVYz+OneIcAOUa8VPXfB+mZ+d2SMgViWn+8bWlJfhVqMzVGUavK7iGc0nj4xwdpm30khqjiTu4ODCQaGZR6/93m2rg7N+6TsZA4nrzXIPDaW4uBQEo8q82xfnJxu4nPJnL46jFuVqy7oOJ5SjVbec3D69IUwO3d8+3on0gwnbF85tyqT101OjGcYTmQJe90VC0vzESlV9JSaQZTKFoSkRqrjTsZJrU/PMlKqfJXa55LxyhBwKxweSfH5Bw8uyCq1W5HRDKMuz62TgekiAY6PpTljdYijoyncilxMMf32xTexY+/vuWj/E7zt0+/mfe/+Ar850MFvD48xPB5j/PhzAIS96ikTUbCYLNakv24BYiRBajxG2NRY67GQM2k7ncxJOT16FH75y6IgNHx8mGt6R2gy82z+gWqLRS98od32wQfhz/+czakUH4snUbMZFKNsPvQf/wFve5v9965dcMsttb/Apk0lUSqXg8cfr922rECBGQqjb9nKqKmSdnlpX91CpK2pJB5dcEHpfd3d8LWvVfoclfselVUPpasLBgdr70M5Xi97XvknfP7BgxxzpcjkDXLpNL6gn7GAhxN7ErxnVcz+TdXwTJrsDXvG6hDxjMZYKs9EOm9vUzP4n98dJ6ubbGkPIMugyNXTyPcNxGccd8zn2GSm62++PqvWdi7Z2MqhoSQhr8qRkRTj6TyWBYos0R7yzotNznJHiFInOZM7iY1tAY4WqsX1TmTpncgS8igEPfZgrtqP8qkTE9zzTB9rmv3kNKMYRWGYFkGPike1qzWEfW6++tujvPkFG/C7lLpvYpZl8dyA7Se1EKl7e/pi3PXECf5wfALDtBhO5Hi2P9ZwR7LUhuDrWv1FtfzhAyPcdG5JOEhktaI4MzlffqUx+ThrRhffeaKHh54f5sw1kYrUxWcLBuetATeb22f29Tp7TRP3PztAXzTLYCzL6ogdPj1T1b1qnLUmwvGxNM/0RJetKPXwgRESWZ3WgJsXbK4dvizLEi87q5P//M1RHj86ziWbWmnxLS8z8Ik5iFJ7+mL8365+/nB8gmf7ovzh+MSCiiqLMYgvn9ytCnvQvRDxu6pOyuayP/MdTr6cIq5qDQ5vPrebfQNxjowk8bqU4uQ4o5nsG4hzxupg1YqgjqfUbCMnHS8qJ+JqPlnf4sejyjzTEyXsddER9rChNcBoMsex0RRD8TwSUrF6INhCUTyjMarKHBmZndmqx2WLUrppTbsY5EQ3zdbkHEqp+bOJlJrsuXVsNIkkQUfYy4bWwIKtUrtVmVTeqKs64Uqnmq+ZZVlohollWTzbG+XoSBLdMFFkiTa/i5agB003+ezbPsE/3P5uzujdzyfu/Cve5foCA74m1oVKgmnAo9LS5D8lIgoWi1lPxA2jMsUsnUaKxVCTyVKbvXttUSiVYnhonMPHhslMxHFl02hajl+84S94watfan/OXXehv/NdWIkkm/LZqZ/33e/CK19p//3kkyUzfWBD4VHkqqtKopSmwaFDSMCUpVxVrYwI6uiAyy6rHXl08cWltmecAT/60dQ25SbbzvE9ZHDwr7/JgaEEsiRx5RntvP7i9dWPbzhsG3HPM+W/Tae/y0uwKuRlU3t9UTqTvWElSSLidxPxuzFMkz39MdoCbgbiWdyKzEAsx0Ash0eV8XsUfC4Fn1tmb3+Mn+4b5O6n+qYddwDzNjaZ6Tqfr3FQre080xPl0UOjjKXyhL2u4pgj4FGKCzszVSE/GRCi1ElONaPubZ0hxlN5ToylGUnmUGU3D+wZ5PTVKR49PFb6Uaoyqizhdim0BNxcflo7f3H5Jn60q78ije2STW1curmF3x0Zp3ciw8d/vBdZkuiLZuq6iY0kcoyl8qiyxNZV8yv6OB3AWDKHu/B9mvwrdzXtqjM6ODSc5A/HJ7jy9A4ihRX5xw6PoZsW61r8rG89uSrQnLUmwpPHJzg0nOT/nunnTy7bUOywncogF26sbnA+mYBH5YzVYfb2x3nqxATXn9nZcOqew5ndEe7dPUDPeJqnjo+jyPKyCB122vRFM9y/ewCfW+G6M1ejzpCCs7k9yI4u+9jcu6ufF25uXlY+HbNN33P6gIFYFrcq43crDRd6aPTzFjqqaPLkzrIsJiQIelRCHa6GVxvr/ZyZzLEXa6XR2be5iFtVB4c5nd8dHuPh/cN0NfkxC8XI1rX4afK7ODiUKAhTCdY0+aZUBHUinBqtDunQVBCz5hopNfnYrGv2c++zAyiyjEdVkGVoD3owLfC5VAIeFQvobvbzjceO88Itbaxp9vKfvznCH45Hcasyh0aSszpX5T5JecPEK1cXnZz0vblUxvSoMvGMRkbTa4po00XG2VYHXuIZrZhC2eyzJwgLtUrtRKHlTgFRqtxOwrIseiYyjCZy6KZjcK9imBZbVwVJ5gy2rgqV7utNPr79kTt4+4ffRNdoH//8n3/Ne/78dobipd9fKqvh9S/cuZoPlo0ob1m2qXw1X6JUCi67jD1Je9LfvvsPvPbo0/j1HHI6hZlIkDPyJIIyISMHX/winHmmvd077oC//Es7UmgSKtD80Y+WnnjsMdtcG+goPMr55QXXFCMUw+Np1o2NVrxuShI5txfN4yM6nmGd88K6dXZVx0CAEcvFwZSFHAxw0c61yMEgXHRRaSMXXwy/+Q0EAlh+P1/fNcLxrMSlZ63lj85ZV/F5nHMOPPJIfce3uRle/vJpz3f5PajJ7yLoUbEsODiUXLDIzFqU/zbt3Bib9pCn7v5vJg/eNU1+XrpzNf/7+AmafS4mMhqxtEZON8npJhNomJZFIqPxzw88h6ZbdDf5iGc18rqBqsh0N3k5MZHh+0/2IEnSvFSEn0lwetdVW7j76b7CZwWwLNsSrNFx0NTxlJ3BM5zIEc9ojKfy5HSToEelK+KlPeSpsNLI5I0Fqfa+nDh5v5kAqN1JuBUFv0dhndtPd5OPZ/vifPvxHlRF4ozVITpCHp4fjDMUz+FRFd76wo289qK1SJLEWWuaqv7gzlnbzL/89Hl+e2gM3TDZ0RWmsy1QU012frgPHxghntE4f30TnlkanFajwhOkI0g0EwUg7HWzOqysyNW0jW0BNrUFODKa4uGDI7z87C5yusHvjtj58i/a2laXOLOSkCSJG8/p4t9+cZCDw0l29dor/UdHU+zpixHxqZy3rqnu7Z23rpm9/XGe6Yny0h2rG07dcwh5XfjdCr8+MMKzfTECbrXmJHs+8uLrmdCXt+kZT5PVTNa12BOAerhu52oeOzzGXU/2cO/ufuLR2ilhC5lbX74d07Q4OJzk6GgKlyLT3EBqVHkfcNqqIM/0xNBNi4BHWZAc/UZW0+ZyTZRPoKNpjaF4hvE0WONpgh6ViM/FgaEEP983yA9mWG3c2R2p43N8pHI6A7EsOd2kyeeiJeimM+ItDlTTeWNRVhqd4zwXcava4HAipdE7kSanm8SzOt5UjjPXhIuRaJIksa0zzP6hBMmszrN9MV64ta3oBaEZJsmcLaw0co2W46T9RefgKTX52LhVGcO0CPtctAbdvPPKzRwcThYWlnJ4XDLnr2/h5ed0cmI8w2OHx/i/Xf0cHk5gFlL8OkKeWQu5qiwhS3aFuZxuVhWdTNPi8EiSsWSOVWFPw+n1zvf+38eP84fjE5iWxVgiz5ZV9ad6ZPIGI4kco8kced3CsqxiWgks3Cp1vdUJ58pyEEMcOwnTa7G3P05GK6WHtgXcRaP/m89dwwN7BqdObHUvX/z/vsDf//PbOG3gMP/v+5/ko2/9x+L29w8n6TRVuiK+CluK5fDdYZb9VioF0Wh14SidhhtvtM2mAe67D372s+ptUym4+27YvNlu+7GPwcc/XnNfzcd+xw9Ggoyn8tw4fIDrf/jl2l9seLj0t6JUClKSBH4/ViCA7vEymJNLC11bt2K98lU8M55nQFfwN4VIqV4Sipuc18/Y1u30TqT56iNHCHg2E/ubr9PR2Ybl96H5g+huDxZwaDjJWV1N/J3Tb1x8Mdx3H6Zp8c1fHGAkmeeGszqRq0W0NzcXo6Yk4KJQJ/t/d5xHTyR44XZ9Wn/NuYzZtneGK+5Bo8lcodiFuiT+QeVWL2DhViVM1Spm0dTb/83kwet3K9z9dB9el8rWkBfDNEnlDDKaQSavM5HWSEmQytlZOeNpjfFJ90PNMLl39wCKItHkc3NgKIGqyAQ9Ku0hD3IDiwiTxwKaYZHK62i6SdBjzxM/9qO9TGTyqLLMUyeiGKbdZ7UG3LQ2MA7yuxUODSUJe130TmSKIpSNREfIw1gyT8CjsK7FXzGXW6xq70uNEKVOAWp1Emevaebm87pZ2+zjXd9+mpxu4FFdHBmxJ3853aLJ58KtyvROZIqVRmulsbUG3IUBlkXAo9IzkUFV7B/u5E62fPX+2GgKzbAwLIuLNsbmbWWgfEKllP24FVla0JXPhebKMzo48shRHj8yxoZWP7t6owzFs2xs87N9AdIflwNtQQ9XnN7Od5/s5e/u2UPE62IwniWVM9jUHuD4WLru6+b01SGCHoV4RuOX+4f57aFR4hmN7TummoBPx56+GLt7ooyn8rQE3GyoIcA2KibNdkIPpVDmkFdFliQ8LrvE/OcfPFTXRHIglqV3Is14Ko9pumitkRJW7+B6rkKb8/q+/rjdL6kSn/35gbrFh8mFHhQZDBOG4lnaQ54pfcBchKIpQgf2euNCeCXkdIPRRI6xZI5cYQKd1SWG4jmGpTymZZHManz2ZwfIGyYbWv2Ylkk1o27Lsvjh031VP0c3TKJpjXhWI5ktpUSl8wb9sSxuVUI3LB7eP8JjR8bqXGmcW8TVfAh/znWxKuxhLJVjMJYr+hC5FJlNbUFcisSt563hB0/1VUyO1zT7eLY3hkuVyRXS+bZ3htnVE2UsmSPgUfHM0hg87LN9zyZSOQ4NJ9jUFmxIvJ58bNwhiX0DcUYSOXwuhQ9eezo3ntNdcxvnrG1mc3uA/+/7u4lmNMJeFy5FRlWkWa1Agx2Qkc4bpHI6h4YTnLu2uWof8PjRcYbjOY4Vikc0EpFVLSI67FPrSvV46sQETx4bpy3oIZrWcKsyXpdMW8CDRqJYuXehVqldskQ8o7G3P4bXJVcV5RdjQaPez5oLAY9CKq8z1J9FlWXcqsSG1oAdIShJJLO6PTZd28TWVaEaE9sdjJ77Q/yvvIVf3vAmNkwau40k8gzFcoR8KkGPUtd3nxcz5aEhzMEhBvpHycaSBPQsHbKBnM1AKsXel72azz9ygvFUnpfvfpAde3+PmkljpVJ49RwZt4kvZ7c1n/wDx1whElmdDf/4YSJf+VLNY/r8Lx/HvWObvT+PPQaf/3zNtubYOHJBlBrUZFYXns+rbnIeL6bPj6cpjDccpD+lcWg4SUvAzd7Vm3G9+BXg9yOHgmheHwnZQ1R2ceNlp9G+fQfHRpIksjrhl9zA+iNHkUOFqmxeL3v642XehyN0Fhe6zsH/xa/yL/fswbIgkdPI5CvFWS1n8JsDoyCBv2ktrrwMeWjK5elqUgh6XTXv48/0RDk8kqIj5OGCDbUrM5ezrTNEZ8RLfzTDD5/q48zuyKzHLtPdp245bw2HhpOsDntJ541iJHjAoy7J/GSy1cvZayKcOBHHluoa6/+m8+A1Tasie0eRZcI+mbDPVUjlTbK1I0hvNEN70EPeMMkU0ps1w0QzLUxLQjct9ELqbyxjL7qOJfMMxLKsafLS7HdXiGgzjQXCXpVDw8kpRUZ00+L4eBrLsheNnLFLXjcZiGUZiGXxqPb+/PbQKL85OFrlnEfZP5hgY1uAg8NJ/O6SJYAqS7QG3XSEPLhVhb19MYIedUmrvS8lJ40odccdd/Av//IvDAwMsGPHDm6//XZe9KIXLfVuLRum6ySOjNg53uesbWIslSee0cnp9grraauCmCZ1dY7HxlIcH0tzztqmYgWhwyMpjo2lCHtduBU7V/hn+wb5YWH1vj3kwa3KSJLFUCw7ryGrFcq/JOFRZXTTxK3YP+iVmp+7uT2AR5V59PAoTx6fIJ7RMC0wLYt9A/EVlY7YCK1BNweH4sSzOqos2RWsC+kajVw3iizREnDz8IERHj86TiKno0j2JKY96Gko0kI3beHWMCGvG1Un/P/+0KE55cW/66ot3P1UH8OJHKvDHlJ5nXReR5ahJeCiN2qvJMqSVBAnAxwZSSFJEl1hL+tb6/PYcL6TKku0BtxohkVSh42TUsLq+U71CFczDdpedlYn9+0eYDxlrxyFvCouVW4oWqNy9U8i4FGJZ3ROjGfoi2Zo9rnJGXYfMFfx0O9WODiUJOBRODqaIpq2Q9FDXjtyyUn/qid6qdY1sasnyjMnorSF3EwUJtA+l0J70EPMSBAKe8jotpBkWTCezuN3q/RM2B4ckmSbAbcE3LSFPDx9YoL9Q3FymjllX54fSLA64mUkYU/03apMW9BNyOtiIp0nltZI5Wzj0q8/doy8brK5PYAqgyyBS5VYHfZweDTFv/zkeUaSedyKzPODCTTDRJVlWgIuWgLuigH4dCuNk1eXpxO3phP+huM5+qMZBiSwLKnQL0BnxMuqsBeQODaaYnXEV3VB5+ptq/C7FSbSGl/45SEUCQbjWU6MZfC5Ff7p/udmZ376h96i9+Hf37OXMzpDdV9/k4+NZljsH4qT1y2a/S48LoVdPTH++Kyuaf0RfS6FsNeFhUVOswf7jjDT6GTJ2d8njo6T000+/cB+dnSHq/YBPpf9Gw95q/ui1aJcDN66KkgsG8WywOtS2VLot37wh16Aisg4O8IwSyKjE89q5DSD1WEPGc3g7DURJEmip2B/s1Cr1Hv6Yjz0/DBHR9McGUnyf7v6q4ryC72gMZ8LDbXaxLMaDz43hGaYpHI6G1r9bGwPospy1WMsy1LtiW3nC/nkf/6EZ4azrCuLAj59VYj+lMVg3BbMv/HYcY6OJEmX9W/+3hNk9+/i549ohE5rQk6n2fV8L/GRCZRMhntvfCtbVhV+d9/5T/jlL0mOx4iNRnGn0nTmMnjzWfR8loN7DrNjSycAE+96H83f/w61SoQ8EDmL8ZSLLR1Bthzfx/m/ua/mdfHFHz/N42orOc3kDX1pbpAVrEAAJWj7EmVcHkYtlZjk4s7fHCd22GRLR5A37byQjR/+MPj9DOgyT47k6c1BUvFg+v1YRwxu6Lb9M+/ceDWxz76A5o5mvF53ceLb5Hdxy3lrODKa5PDICbyqwuFVO/jpy3cA9phrddhDS8BNz3iG9nPXsvvJMQ4NH5903TSzs803rffhgcEE3c0+Dg0nCRbEGFkqTP6RMExbhMjkDSwsPC4Zy7KF7mhGJ5pJEPaprAqVCjaVX8dHR1PohsWOrjAHh5J19ceSJLG+1c+9u/v59cERugrCQCO/qekWYdYpfp4fjPOVXx9hMJEtVCct/X6cCtKLPT+ZbPUCUnGvZtP/1brHzJTi1xJwc8NZXfzP74/jURVag1OLNiUyGr0TGUwsWgMuXIpCTjcZTuTI6yZHRtMoUpqAZyZhuptDwymOFaLwJcmeV3hVGZcq41ZkFEliIJ7FpUh0N/lo8rtRFYlExi78FU1rJAvjoK8+chTNsDhtVRCXKhHL5JlIacQyGhPpNAPRDGBhWhYdIQ/NfjdNPlex/0xmdVqCbt5w8Tp+d3R8yaq9LyUnhSh111138b73vY877riDyy67jC9/+ctcd9117Nu3j3Xr1s28gVOEWp2EM3HrjNhloaNpjURWZ3XEi0uxQ//r6Ryd7QQiLrZ22OGJwwW/gIl0KVf4//10P4YJW1cFyGomINHkUzl9dWheQ1YnK/87usKYloVcGASt1Pzcvf1xDgwlGE/ZE04nHWI4Mb+i3nLCNC1+9Ex/IZRaIpE1AImgV2Fnd5hDw6mG8scfOzxWPH4hjy12NJLH76yudDf5kaUME2mNA8NJPIqMIkvkdZPfHBxmT78dSdXd5COd18nqOrIk0x500xPN8PVHjyLLEiOJHJs7AiiyXQ1LM038boUDQwk+9IPdTKQ1XIpc9TeoGWZpJdGtkuyziwYosp2SWO9E0vlOXU3+gidLiomcRM94GkWWkSR47Mgozw/GGU3mKr6TV1XZ2Obn6Gi6LuFq6qANsCDoVdjiCXJwKMGXHz6CvzAYHIrboe1hr4vN7fWbDk/uA7Z2BBlJ5BlJZMloJgPxLHnd5L8fPUr/RAbDsuiK+BsSinb3Rnl+IMG6Vj8HhxME3GpF2HUsoxPL6JiWRTqnc8evDpPXTbZ3hXEX0pXLRZWpE2iJvG4wns6RyNpeN6mcRnvITU43OWtNGFmSMBOwthDyfWg4yemrgvROZGj2u8nqBqm8QU4zy/bHZCSRoyXg5oL1zXhcKlgWecMkqxkcG0sxlszS5FfJ6xZndUfwFPqatqAH3TDY0xenpZBy41Jl+mM5+mOVXiKaYTIcT0xZaQSTZM4WCH1uGU03efTQKL+uutJon4ebz+1mX38cj0vmxHiadN5AkSX8LgW/W6HZXzttMZXTeezwGI8cHGVV2EsqZ+BWZYJehY6Qh/aQpzhBdiI2Ql6VTe3BqpNjgC/88iC/PjBCTjdoD3kIeVV87saEU6iMcAp6VUzTwueSGxKvbzlvDQcGEwQ8Cr0TGcZSdhqaW5E4bXW47sWlRFbHMC12dkYYSuQYSeQqqgnWO1mqEJzcin2sPUrVPmBDm59jY2kkSSLoUemMeOv+jZdHQ0qSHSWlGRbP9ESRJPv6+/GufiTJjkKIFUzkHb8wWZboDHtxuxTe9qKN/PCpPo6Mpu00QguSOZ2heG7eV6kne911hLyEfa6qovycFjTqiFCcr4UG53tNbtPkcxWOv4vTV4UYimcxLcjmTXxuqWYkwHQT25su2cyJBw9yZCSGPxDCm0nxvn96G6FcFk8ui0/L4splkQ2D2770MD63fW9+1f9+lu1P/Kpie2vL/v7drX9a/N6fefRxmu67jyBQ7Rfz1Z/s4S2vsD08BxIyFwWb0H1+NK+PrNtHUnZh+gO0rWpi32ASKdzM/sEE96y7gL1/3IwVCCAFAuS9fpKqhyvOW8/PjqfYl/PRFnLjiyj84rXv5hs3/BktAXfVc+53K0iFc/WpQDfvecf/V2rTka+c9E9kOPyLA/jcKoO6zJb1qwr3F5OMpmNZFrt7Y/SMp9ncYS9IG5ZFi9+F360ylswVq3UeLfhwfueJHgzTquv6syyLEezCPKm8zrExe3FAluwI1TXNPlqDbhS5FGmaLFRhloDOiI+gVyGrmQzGMowk7UX0sWQcWYI/HB/nd0fGGU/lCXtV3IqMKluMp/N1j+329MW4b/cAyayOqtiLPuWpy++6agvf/0MvQ3G7UE4ypxFN57GwPe0OjyT5xH3PEctoBDwKPRNpsEAzLBI5vRjxMxzPgWQL/j63XEy7d3wFF3t+MlksWsj+b6YUv+2dYX53dKzCMN3BsmzR+dyCZcezfTG2dNjj3NURL8PxHH1RO9pfkuBrjx7jyEiKnF4SptOFscDDB2zRUTMsFNmiM+xhdcRXkWKezNoLwKtCXo6Pp1kV9iJJEs0BN80BN7ph8GxfnCa/i+F4FreqcGI8w4nxTNk3loh4XSgybOmIMJHOs6ktUDM975rtq7lm++plkXK82Kys2XgN/vVf/5W3vvWt/Omf/ikAt99+Oz/96U/50pe+xKc+9akl3rvlz+SJW5PfXawCBPV3jpO3s6bFz5pmH6m8QSyjMZLIkszalYX8bpXDI6WSqM5kZT5DVicr/+VGzys1P9dZFc7rJp0RL+lCqHN3k5euJt+K9MmqB2fisbEtyFAiy1jSDnVuD3qQpOrl2avhHL903mB12Fv0tOiMeFkdrn8iVB6B0x7yMJHWyGkmucL2TMsims4zntIIeFR6J6ZWi9EMk18+P1IUk+Inpk7yTAuG4nb5dr/bnnh7C9WsTNPCtEAzTdJ5+73Oa5ZlmzOrDVTtKP9OQY/CYCxLKgmDBUHI+U7DcTtFqfKmW+KXzw+xtz9GLKOxtSOIzy1jmCZgD26PjaX4xH37GE3mURWZXT1RNNPCWfCWJEjndUaTedqDbuJZrTiB9KpyQ/3E5D5AkWVWR7ysjniIZTT29scJexX29cUZT+dp8bsZd+VowYMsQ1eTl+Njab7x6FEs7Ei09a3+okHleCpfMEVOMxjLIBX2f1VhJVmVJeJZnVg6z1gqj2Fa9EUz+N0qz/TEiufUIa+bPPi87c8R8dkh3IZlkcjqheMj0Rrw4HPJvP2Kzdz9VB9Ha0ygX3HuGv7n98dp8rmLvjhZzWAilWc8nWckoZPXLXTDYldvnIBHwTSt4m8i6FFRFJm3v3gT9z87yInx9JRVzbUtBePS358g4nMRzdirgpblREvJBDwKhmniUuyJd8Rni8CZvMF4Ok8iq9vRuZrBfz5yFM2wV/1dii3GZXUDlyKxryDGp3I6Ia+rYkAXxREaKtMW17f40UyT8Ykco8k8mmESz2pIWGxs85PI6uzsDiNJ098bqk2OTdNiIqXhc8l4VJm8bhWEU3fd0YnOdsojnPYPJuxoUEUupr1XEyoBfG5b4D4wnORzv9jPWDJfcWx8LpnTV4dwq0rdi0vF+7hm0tXko6vJV/F6PeOByd9pX3+cVN7A61aI+FzsH0rwqfufYyiRQ0Ji4kSs+F61wfT6ymhIOwXSuT/Y16GdWuFMAJ2+RJUl2kMeOsK2GHlsNEVnWWTcwcEEI1lQ09q8r1KXH5/VYQ8jSQ0kqygW2aL8YTyqwroWH0bhulZkiTVNXo5PZPjekz3INYx+N7sD7B9K8O8PHWQwlsWjKhwasUUi07JQZAlVtlNvHzk0zHMDccZSOda1+NFNk0zejnTc1ObnSJ0LDdUEE3fIFsifG4jjURVesr2Dj718BwOxbM0Jab3H2JnY/vQXT/NNJEKmCceer9p2dCLNRFqjLeBhINBKe3sXGbePCdmD7vOjhEPkfX50txe3YheMOTqW4u5z/oimrp0cS1u0dDSR9/rRPF7yHh95j49ey1v8bT574zt58G1/XbxXJnM68XSeY2NpZFkindMJJfNIksQftl7AH7ZeULoeCuf34QkP+UAzp7UE8bsVZFki4HezxadyaDjF957swbIsxpI5NrYHCrEsFn6PwpaOAIeGUzX6Cguvy45w2jeQIJrR6G7ysm8gTk430Y1StJnXpZDKGZzZFUGVZfom0kXD+bXNPsaStpA0GNcwTPues7E1gCTZUehBr8oml5/9Q0k+/4uDhag1mYNDCbKawWhSImBliwK0S5E4vbOZ0USuaKrtUOyLC9fEs32lgk0b2oJ0NZn0R9McHknS5HPxncd7SOV1dnZFGEvZx3p1ocpoI9Hi46k8O7vCHB5NM5zMIReif/f1x/ngd58hntVxq0rRQ7AczbA4NJwsW4Sp7G8lye5jFQm6mm2vxjNWh2a8By0G5WLRQvZ/zmfVioQEZoymuuX8NQD0RSvbBD32QnPArdLd5OX3R22Rck2zDwuLkUSWwcJiZDyr4VEktnWGiGY01rfWFopecW4X//7Qoar7s64wDvqf3x0n7HUxns6Tyhl4XTIthfm0zy1zbDTN9Wd2VvfLqyLKryRbmflixYtS+XyeP/zhD3zoQx+qeP6P/uiPePTRR5dor1YW1cp4OjTSOVbdjmSnzPjd9kr1RRsDHB9PE/K6SGZ10nkDSbL9qGB+Q1brCRNdafm55avCumlyYCiJLFFU71eqT9ZMlE881rX4CxNfi/aQHdpb73VTfvzsKA1bGG0JuBs6fuUCbJPfzc7uMHndHvCbpkUyZyCBvYLY5IXC36ZpYRRSLXVDIpXTsUxwKWWeZxJ43XZ5XLciMxjP4FEVNrYGCFYpNZ/M6nhUpWwlcWq3Xs9EcrKovKUjgJ6K0hrxgGSvZhumiWnZoouEhIlVEDIM8rodlhzNaMSzOgGPyr6BxJTP0QyTQ8OpKpEzNpYFWPYAEcv2gIJC6pmvsdD26fqA4XiO01eFuP7M1XzlN0dp8rkxLBiM2R5D5fv7UJl4mMxN/k4SEZ8bVYbTVocYS+YrTCp9bpWOhgylSwABAABJREFUkAdp2PYU6JnI4HXJZPIm6bxR9DIC+7qIZzSQ7ElzusxfI+KzI0gCHpVjo2m6ZphAV1tt9LoUOpt8rI54eSo/QVYzaAt5Cp4/9n6ossSqsIe2kIfe8Qwb24J1GZf63SodYdu41LJAVSTA9okJe9XiSmNz4bcW8rroCHvJ64ZdsMCvMhLP4VYVeieyU4RcWZYKq5a2V1pLwEPAbYst6bxtlBpN5yvSFnujldvwuhTagh4UWeK2F6wv+EWlZnVvODaW4tBIkm2dEZI5rSjSuhsUTisjfaSi8fXR0RQnxtOYpsXP9g3aq7MFUVeWJJI5+/5pFVbhY2n7ulFkqZhm2ex3NRwZPB/jgcnfyTmOB4aShf01i2K70wd4XXa0QEuDY4HJ/dbm9gDrW/zF+lHJnM5gNAuF+6Rj3KsqcjEtsVpk3KGhGD95aIiXXnXGvFcfLT8+4+k8oDGSzBNN6+imSSxtV2RqC7qJ14iOvW/3QKFPdLGnP4ZaiGbN6Sb5wqNnPFOzn4XS4slY0l48OTqantLGME1+uneA3x8dI5HV7OIKmTzJnFQQYVVOjKf50q8OAnZk7boWPznd4PBIhpxuEilUMJSRaPa7aQ16pp2Q1svO7gjb33g5va3f55Gf/oyzLjyfzu4O5GCA/QmDz/9uAH9TEJfhIqtb9MeyfPKGd8MN7yanGwzFs7T63QS8ZffVoRyQQzNMvsg6WLUOv1vFrcrIAJKd4iXlQTMM7t8zgIR9HPb0x5CQyGpGUfyUJIlUVkdRpKIRc9irYlj2uCaR1RhL2f3WcCKH362yfyiJJFH0JXR+M8d2DxTvQ9HM1OtCN03u290PskTIo7K7L4aMXfXSuY+m8vZnRtNKMVJXkiDgVmjyuwh5XQzHc7xgSxsvOq2dzz94sOLe6XWp+Nwq61oCDCeyKLJcNKP2uWR000IzbK8fx4vWuf4syypGRK8Ke4l4XZwYz3Dt9lXTTtRrCRB21JHFzu4IWztC/HhXP6oic2gkVfxeTh/USLR4Z8RH0KPQH7Mjqp17kSxLjKXsRZeQV7aPh6rgUuViqptpWvQWor9aAm58hUUnpTAXCngUMnmTaCbPGy5eN6d70ELgiEUL2f85TJdGPlM0lSOQVfVLXmv7JQN88Hu7CHpUElmD58rGox5VZkt7EEWWeM2Fa6d4R04+D/UauIe8LjqbfIViHeCkZtbnl3fyp+fNxIoXpUZHRzEMg1WrKk2KV61axeDgYNX35HI5cmXVIeJxO91F0zQ0rWRy5vxd/tzJyo1nraZnLMXBIdtHxOdSyGgGg7EszQEXLz9rFYahY0xdGGhoO9fvXMW3H+8l4nexrtmHZtgTGLcqY5q214BbkfCpjR33Wufq9A4/77h8I3c/08/h4RSDMQOPqrCzK8RN53Rxeod/RZ3fiWSWbF7HE/LglxXWt/jwqLJd3cg08agS2bzORDKL1jQ1F3s5MJvflU8FtyKRymkEPSrbV4ewsFAK37ve66b8+LkVlaG4hN+t4JKlho5fd9jNpjY/e/ribG4P4FVlvGrJG2M8lefsNWGGEzma/O6iT0A5yZyOT1WwJDtSK+BWiqvYxRtZTsc07dX8E+MZNrvlKZPE/mianV0hLGBvf4LN7VNXe/qjac7sDtMddtc8PpO/k0uWaPFAV8QWPA+PpDh/XVPN72SYJmOpPCewB8FNfpWcZg8aZQncip2nr8oKWBYuRaaryUuT31UMzwd7ED4cy5LK6axv9dMR9oBlT7ZVpfF+YqY+wDAt/C6ZbauDpHIGw4kcyVxpwC9LEqmcBZaE12V7XoA9yIz4bE8kr0vm+Fial5zRzk/3DtXs/15xTlex//OqMvGsHc5PYQKSyRuosu3m0Bpw4XOrdvEit1KsApQs++4b2/x86I+2cng4zi9+PcRLXryFzR32SrBh6NP2x61Bu3pkd7MPryoTLUQ4tQZsIaPa5xwfTxcnketb/EXj0vLrxvFlME0LyzKL196NZ3fyxV8dqbova1t8XLvdvjeEvQrRrE4iqyNL9u8z4FbwqHJxxXMwnqM7MnVV/fAInNYRoDeapcXvIqebZDQTT6GCXNinYphwfCxFW8A1p3tDRV/s9qBIMJbK0+xXa/Yl1fq+8u2YpknYqzKazGGYBSG7EHUhIeGSpaJ46OCsxiZcEutaAoyl8qwtpO2C3T/W2wc4zHU8MPk7uRV7QupE0IW8CqZl4lHsSKC2oLsonjn7XO9vfHK/5fjSgH1NjMSznL2m1D9GvIX+0bKPba1jsybiZn3Q/reesU8jlB8fl2zvZzZvkMX+EMOyFzjAQpWdCoYShmmhmxambEfISti/v3TOACp3UFXsBQ6XS6bJZ6cGeVQZRba9NQ3TicC0BYv2oAvTso19dcNCM03MgpBhi75ZAm6FkUR+yvfRDJPfHRlHkiR8LoWDw8nia15VZmNh4nlwKMGhoRgb22xBc22TB7B/G3M5xm1XXUbeSNN8zTUYLhcGII2miB2Vwe9iu1thNJkjp5kYhYWjsZSJLNmRPW7Vjm4yC35FlmXfs5xjrBT6s9ISga04mZZFVjOQkIqCjINblQh5VfwulWi61G+1BsojGd20B22D581tfnomMgQ9Cqm8vchTzuT9qVZRVwJyholkSJgu+5oqvla4Bzf5VOIZjbBXpbvZHj96VaXkazOp36/VR+7oCvPdJ3tpD3kYSeYZT+UrFljcqkRWsz+z2a8S8blxKTAhJVjfEay4x+zoDLKxdfq+GJjxPv7EsXF8LpmRRL7o9+lW6h/bVfRblsX6Fh8D8RyqbIvmTuSYW1VY1+qvOa6TsIpjts7w1PuU099csbWVVSH3spyfLGT/Vy+nd9QedzjHZbo2u3tjhDwKp3UEGIznGEvl8agynREvrQE3ptXYWGC6z6o2DrL7z6n3GFmWZvxe9bJSdIp690+y6q0Vvkzp7++nu7ubRx99lEsvvbT4/Cc+8Qm++c1v8vzzU8N5P/axj/EP//APU57/3//9X/x+/4Lu73KmNwWPD8sMZkA3QZVhtQ8u6jBZ00AE6XTb6fLDPcdkelKwymvfKB0sC4aysDYAN20wmU9h3rRgNAsZA3wKtHmZ1+0vFsMZ+P5RmYAK3qmVtckakNLh1o0mHb6pr69UTGt+rpv5PH69KfhJj0xKhyY3uGXImxDNQ0CFa9eYPDEy/T6v8QOSva3pvtcF7SY/6639WS9daw+Xp9ufl66d+Xc8H9+p1QNxjeIxtl3jSlaeWQOSGkTcMJarvp3BDORNCbdssdo3P/1ErT6gnmtiorCG0eyZ+brJm3Pr/+q9Jur97rX64wvbZz6X9X7OTNeNc+1Nd29wy5Xnodp1k9LhhatMHh+p/VkXdZg8Mlj/b3y294b56kuqbcfEjhA0gYwOsbw9DQ4otthgWvb39qmgSvUfm3r6AIe5jAcmfyfDsvfRJduPXB19wHxffzD3/nG+KD8+bsU+FmBfd4oEKQ16UxLrgxbNVebPGQMmsmBKEHKBS7KvFcuyz5NLBs20tzPTMZ7cXxdfLzxSmv1+04IWj/05plmQwOzAFwwLojlbWW9y2amSFuCVocULMvb7R7Jw4waT9fMYxJ3L5fj4xz8OwEc+8hE8HvuAzTRm6ElDSpPYELLwVfn9Zsr6/YgbPEpBsCo7PlnD/m0ChF32uaTsHEjMrt/yFH4zTsVrsH8zsRz2MfZQ3Gdnf8zCbyxa2OeQGzyy/boi2fskY/cnR5MSIZfFGn99v7tqfeRotvI3rlv2Pqqy3SdpZuO/8Xr64nru4y7Zft2v2t8Z6uuP6+nT6/1O9YzZnP7mZJmfLDcmn0/ntzJ5TDHXsYBDveOgU5F0Os3rXvc6YrEY4XDtKvErXpTK5/P4/X6+973v8YpXvKL4/Hvf+16eeeYZHn744SnvqRYptXbtWkZHRysOlqZp/PznP+eaa67B5ZqaNnMyYhbKX05Wb+dzO3v743zhl4eZSGtVV2HfdcVmdnTVvmircaqcK9O0+ORP9leo8Q52pECKM7vD/M1LT1+2aYmzPVfzcd3M9/Hb2x8vrq7kdHt1ZUtHgJvO6WJHV7iufQbq+l4zfVY9+1Pvcb77mX4ODiUYGhljVXsrp60K1f2d3nH5Jn60a2DGY+xEztTazvU7VnP/nsF57SeqUc81MVMk2uTrZq79H9R3TTjM9JuqtT/z2RfXe+3V2pdGfpvPDSZqfta21aFF6SNn05dUO0/zff1Nd2wa/b3MdjxQ77GZqQ+Y7+uvkf5xIccUMx2fQ8NJMpqB363O+ZqY6RjX01+va/HNGPU7GM0Wo35rtYmlNT5ywxnFSKn5IJVK0dzcDMDw8DBNTU3F16br35r8dhRTfyw7p2M8X7/Nevqt+dqfriYvmbyxKGOp8uuvI+RmYniQ5o7VDCfyi34fn6nfn+9+az7GY0vFyTCnWor50mKf85VynuLxOG1tbTOKUis+fc/tdnP++efz85//vEKU+vnPf86NN95Y9T0ej6e4mlKOy+WqelJrPX+yclqne+ZGc9jOOetbed81ajGndiSRr8gDnktO7alwrl55wToGYgc5MjrVeLg16OHWC9bh8czPOVxIGj1X83XdzOfxO2d9K2etbanpjVHvPtfTZqbPqrdNvd/J9hR4mJdetb3CU6Ce7+R2uWY8xju7I7zvGte02zmtM7Ig/cRkZromXnnhesA28a33uplr/zeba32631S1/ZnPvriRa6/Wsan3tznTZy1WHznbz5l8nubz+puPPqCc2Y4H6jk29fQB9bJQ/eNCjSmmOz5tIW+x+t5cr4l6jvFM/fWfvHATdz/dx7O9MUIdrimTu6F4jrPWNgG2GXXNNmua5t2fpvzcTD5XM/VvMx2/eo7xfP4256MfqKfN2y/fArAoY6ny66/ofZg1luQ+Xk+/P5/91nz3xUvBSp9TLfZ8aanO+XI/T/Xu24qPlAK46667eOMb38idd97JpZdeyn/8x3/wla98hb1797J+/foZ3x+Px4lEIlMUPE3TuP/++7n++uuX9cleqZimNW8/3FPtXFUru7y1I7QijPLmeq7m47pZ7ONXzz7P5+9hPpjpPM20v/Ue45m2s1jHpZ79nc/rZj6vieXwm5ov5usYL9ZvvJHPme48Lfb1txjMVx+wFCzGmGKm4zOf18Rc++s9fbGKynqTzYCrVd+r1ma+r9NUKkUwaOcDTkxMVERK1fPd5+sYL2a/NV9tFnMsZZpW2ULX5Qtmnj0f52El91vzxck0p1pp981GWCnnqZbOMpmTQpQCuOOOO/jMZz7DwMAAO3fu5HOf+xwvfvGL63qvEKVWPqfiuVqpN8Tlcq5W6vFbLObjPK20Y7wSxUNYPr+p+WK+jvFinav5Eg9X6vU3HSttfx0W6zc1H6L8Yv1elqNwWo8oNRPzdYwXs99aTn3FYi2ezPf+LPQ2VjJiTLEyWCnnqV5RasWn7zm84x3v4B3veMdS74ZAsGhMV05VMDPi+C08K+0Y17O/K+07rUTm6xgv1rlazP1dadffStvfxWam47OY18RM23HKxU83uaunzXJjvo7xcusHVlr/N1/Mx/4st+8kmBvifK4MThpRSiAQCAQCgUAgECwMy0kMEQgEAsHJgxClBAKBQCAQCAQCwYrD7/djGMZS74ZAIBAI5oAQpQQCgUAgEAgEAsGKIhAIEI1Guf/++wkEAku9OwKBQCCYJfJS74BAIBAIBAKBQCAQCAQCgeDUQ4hSAoFAIBAIBAKBQCAQCASCRUek7wkEAoFAIBAIBIIVRTab5eabb2Z4eJirrrpqWZdFFwgEAkFthCglEAgEAoFAIBAIVhSGYfDAAw8U/xYIBALBykSk7wkEAoFAIBAIBAKBQCAQCBYdIUoJBAKBQCAQCAQCgUAgEAgWHSFKCQQCgUAgEAgEAoFAIBAIFh0hSgkEAoFAIBAIBAKBQCAQCBYdIUoJBAKBQCAQCAQCgUAgEAgWHVF9D7AsC4B4PF7xvKZppNNp4vG4KDO7zBHnauUgztXKQJynlYM4VysDcZ5WDuJcrQxSqVTx73g8jiyLtfblivhNrRzEuVoZrJTz5Ogrjt5SCyFKAYlEAoC1a9cu8Z4IBAKBQCAQCASCRli/fv1S74JAIBAIapBIJIhEIjVfl6yZZKtTANM06e/vJxQKIUlS8fl4PM7atWvp6ekhHA4v4R4KZkKcq5WDOFcrA3GeVg7iXK0MxHlaOYhztXIQ52plIM7TykGcq5XBSjlPlmWRSCTo6uqaNppVREoBsiyzZs2amq+Hw+FlfbIFJcS5WjmIc7UyEOdp5SDO1cpAnKeVgzhXKwdxrlYG4jytHMS5WhmshPM0XYSUg0i+FggEAoFAIBAIBAKBQCAQLDpClBIIBAKBQCAQCAQCgUAgECw6QpSaBo/Hw0c/+lE8Hs9S74pgBsS5WjmIc7UyEOdp5SDO1cpAnKeVgzhXKwdxrlYG4jytHMS5WhmcbOdJGJ0LBAKBQCAQCAQCgUAgEAgWHREpJRAIBAKBQCAQCAQCgUAgWHSEKCUQCAQCgUAgEAgEAoFAIFh0hCglEAgEAoFAIBAIBAKBQCBYdIQoJRAIBAKBQCAQCAQCgUAgWHSEKCUQCAQCgUAgEAgEAoFAIFh0hCglEAgEAoFAIBAIBAKBQCBYdIQoJRAIBAKBQCAQCAQCgUAgWHSEKCUQCAQCgUAgEAgEAoFAIFh0hCglEAgEAoFAIBAIBAKBQCBYdIQoJRAIBAKBQCAQCAQCgUAgWHSEKCUQCAQCgUAgEAgEAoFAIFh0hCglEAgEAoFAIBAIBAKBQCBYdIQoJRAIBAKBQCAQCAQCgUAgWHSEKCUQCAQCwSnK1772NSRJ4sknn+TYsWNIklTX49ixYwA899xzvPGNb2TTpk14vV7a2to477zzeNe73kU8Hq/rsyVJ4le/+tWU1y3LYsuWLUiSxBVXXDGv31uSJD72sY81/D7nGH3ta1+bse3TTz/N5ZdfTiQSQZIkbr/99oY/rxEmn6NwOMwLXvACvv3tby/o58436XSaj33sY1WviVr09PTwjne8g9NOOw2fz0dLSwtnnnkmb3vb2+jp6ZnVfmzYsIHbbrut+P9q5965hp3fg0AgEAgEgsZRl3oHBAKBQCAQLD2dnZ089thjFc+94x3vIBaL8a1vfWtK26effprLLruMbdu28ZGPfIQNGzYwOjrKrl27+M53vsMHP/hBwuHwjJ8bCoX46le/OkV4evjhhzl8+DChUGjO320peMtb3kIqleI73/kOzc3NbNiwYcE/89Zbb+UDH/gAlmVx9OhRPvnJT/K6170Oy7J43etet+CfPx+k02n+4R/+AaAuMbK3t5fzzjuPpqYmPvCBD3D66acTi8XYt28f3/3udzly5Ahr165teD/uvvvuuq5fgUAgEAgEc0OIUgKBQCAQCPB4PFxyySUVz4XDYfL5/JTnAW6//XZkWeZXv/pVhXB066238o//+I9YllXX57761a/mW9/6Fl/84hcrRICvfvWrXHrppTNGXC1X9uzZw9ve9jauu+66edmepmlIkoSq1h66rVq1qniuLr30Ui677DI2bNjAl7/85RUjSjXKV77yFUZHR3n88cfZuHFj8fmbbrqJD3/4w5imOavtnnvuufO1iwKBQCAQCKZBpO8JBAKBQCBomLGxMcLhMMFgsOrrkiTVtZ3Xvva1ABVpZrFYjB/84Ae85S1vqfqe8fFx3vGOd9Dd3Y3b7WbTpk387d/+LblcrqJdPB7nbW97G62trQSDQV760pdy4MCBqts8ePAgr3vd6+jo6MDj8bBt2za++MUv1vUdynFSunRd50tf+lIxnc5hz5493HjjjTQ3N+P1ejnnnHP4+te/XrGNX/3qV0iSxDe/+U0+8IEP0N3djcfj4dChQw3ty/r162lvb2doaKji+Xg8zgc/+EE2btyI2+2mu7ub973vfaRSqYp2pmny7//+75xzzjn4fD6ampq45JJL+L//+7+KdnfddReXXnopgUCAYDDItddey9NPP13R5rbbbiMYDHLo0CGuv/56gsEga9eu5QMf+EDxvB07doz29nYA/uEf/qF47MrT6CYzNjaGLMt0dHRUfV2WS0NdZx/27t3L1VdfTSAQoL29nXe9612k0+mK901O36uXp59+mhtuuKF4HXV1dfGyl72M3t7ehrclEAgEAsGpgBClBAKBQCAQNMyll17KwMAAr3/963n44YfJZDKz2k44HObWW2/lv/7rv4rPffvb30aWZV796ldPaZ/NZrnyyiv5xje+wV/+5V9y33338YY3vIHPfOYz3HzzzcV2lmVx0003FYWdu+++m0suuaRq5NK+ffu48MIL2bNnD5/97Ge59957ednLXsZ73vOeYipZvbzsZS8rpkHeeuutPPbYY8X/79+/nxe84AXs3buXz3/+8/zwhz9k+/bt3HbbbXzmM5+Zsq2/+Zu/4cSJE9x55538+Mc/rim81CIWizE+Ps5pp51WfC6dTnP55Zfz9a9/nfe85z088MAD/PVf/zVf+9rXePnLX14R4Xbbbbfx3ve+lwsvvJC77rqL73znO7z85S+v8FD65Cc/yWtf+1q2b9/Od7/7Xb75zW+SSCR40YtexL59+yr2R9M0Xv7yl3P11Vfzox/9iLe85S187nOf49Of/jRgp4X+5Cc/AeCtb31r8dj9/d//fc3veOmll2KaJjfffDM//elPZ4ys0zSN66+/nquvvpp77rmHd73rXXz5y1+ueq01SiqV4pprrmFoaIgvfvGL/PznP+f2229n3bp1JBKJOW9fIBAIBIKTEksgEAgEAsEpyX//939bgPXEE09Uff3yyy+3duzYUfW1bDZr3XTTTRZgAZaiKNa5555r/e3f/q01PDzc0Gf/8pe/tABrz549lmVZ1oUXXmjddtttlmVZ1o4dO6zLL7+8+L4777zTAqzvfve7Fdv79Kc/bQHWz372M8uyLOuBBx6wAOvf/u3fKtp94hOfsADrox/9aPG5a6+91lqzZo0Vi8Uq2r7rXe+yvF6vNT4+blmWZR09etQCrP/+7/+e8fsB1jvf+c6K517zmtdYHo/HOnHiRMXz1113neX3+61oNGpZllU8Hi9+8Ytn/Jzyz3vHO95haZpm5fN568CBA9bLX/5yKxQKWU8++WSx3ac+9SlLluUp5/z73/++BVj333+/ZVmW9etf/9oCrL/927+t+ZknTpywVFW13v3ud1c8n0gkrNWrV1uvetWris+9+c1vrnrerr/+euv0008v/n9kZGTK+ZkO0zStt7/97ZYsyxZgSZJkbdu2zXr/+99vHT16tKKtsw+1rolHHnmk+Nz69eutN7/5zcX/Vzv3zjXsfM6TTz5pAdY999xT174LBAKBQCCwLBEpJRAIBAKBoGE8Hg933303+/bt43Of+xyvec1rGBkZ4ROf+ATbtm1j//79dW/r8ssvZ/PmzfzXf/0Xzz77LE888UTN1L2HHnqIQCDArbfeWvG8k2r14IMPAvDLX/4SgNe//vUV7SZ7K2WzWR588EFe8YpX4Pf70XW9+Lj++uvJZrP87ne/q/u7TMdDDz3E1VdfPcV4+7bbbiOdTk8xmr/lllsa2v4dd9yBy+XC7XZz2mmn8cADD/Dtb3+b888/v9jm3nvvZefOnZxzzjkV3/Xaa6+tqIT4wAMPAPDOd76z5uf99Kc/Rdd13vSmN1Vsy+v1cvnll0+poCdJEn/8x39c8dxZZ53F8ePHG/qek7d55513cuTIEe644w7+5E/+BE3T+NznPseOHTt4+OGHp7yn1jXhXDOzZcuWLTQ3N/PXf/3X3HnnnVMixQQCgUAgEExFiFICgUAgEAhmzbZt23jf+97H//zP/3DixAn+9V//lbGxsWlTriYjSRJ/8id/wv/8z/9w5513ctppp/GiF72oatuxsTFWr149xbOqo6MDVVUZGxsrtlNVldbW1op2q1evnrI9Xdf593//d1wuV8Xj+uuvB2B0dLTu7zIdY2NjdHZ2Tnm+q6ur+Ho51dpOx6te9SqeeOIJHn30Ub785S8TCoV4zWtew8GDB4tthoaG2L1795TvGgqFsCyr+F1HRkZQFGXK8SrH8aq68MILp2zvrrvumnLc/H4/Xq+34jmPx0M2m23oe1Zj/fr1/MVf/AVf/epXOXjwIHfddRfZbJa/+qu/qmg33TUx+fg3SiQS4eGHH+acc87hwx/+MDt27KCrq4uPfvSjaJo2p20LBAKBQHCyIqrvCQQCgUAgmBckSeL9738/H//4x9mzZ09D773tttv4yEc+wp133sknPvGJmu1aW1v5/e9/j2VZFcLU8PAwuq7T1tZWbKfrOmNjYxUixODgYMX2mpubURSFN77xjTWjgsqrus2F1tZWBgYGpjzf398PUNx3h3rN4h3a29u54IILANtradu2bVx++eW8//3v59577y1+hs/nq/DwKsfZh/b2dgzDYHBwsKY45rT9/ve/z/r16xva14XmVa96FZ/61KemXIfTXROTxarZcOaZZ/Kd73wHy7LYvXs3X/va1/j4xz+Oz+fjQx/60Jy3LxAIBALByYaIlBIIBAKBQNAw1cQVsAWWeDxejP6pl+7ubv7qr/6KP/7jP+bNb35zzXZXX301yWSSe+65p+L5b3zjG8XXAa688koAvvWtb1W0+9///d+K//v9fq688kqefvppzjrrLC644IIpj/kQK5x9e+ihh4oiVPm++/1+Lrnkknn5HIcXvehFvOlNb+K+++4rpgbecMMNHD58mNbW1qrfdcOGDQBFQ/gvfelLNbd/7bXXoqoqhw8frrotRyBrBI/HA1C3cX6t6zCZTNLT01P1Oqx1TVxxxRUN7On0SJLE2Wefzec+9zmampp46qmn5m3bAoFAIBCcTIhIKYFAIBAIBA3zZ3/2Z0SjUW655f9n777jo6jTP4B/ZranQyCEEgglKBhRsHBYKEJoiiKc5fBQLKhnAVTE87DgiajYlbOACp4/ET3BHhVEQRGxACpNBCGUUEJN2Wy2zMzvj81MdpNssgk72dns5/16ocnsZOabnezuzDPP83zHIjc3FyaTCb///jueeeYZiKKIe+65p8HbfOyxx+pd5+qrr8Z//vMfXHPNNSgoKMCpp56KVatWYdasWRg5ciSGDBkCABg6dCj69++PadOmwel04swzz8R3332HN998s8Y2n3vuOZx33nk4//zz8Y9//APZ2dkoLS3F9u3b8fHHH+Orr75q8O9SmwcffBCffPIJBg0ahAceeAAtW7bEW2+9hU8//RSzZ89GampqRPYT6OGHH8Y777yD+++/H19++SWmTJmCxYsXo3///rjjjjvQq1cvyLKM3bt3Y+nSpbjrrrvQt29fnH/++Rg/fjxmzpyJgwcP4qKLLoLNZsP69euRkJCA22+/HdnZ2fj3v/+N6dOnY8eOHRg+fDhatGiBgwcP4scff0RiYmKDZy9MTk5Gp06d8OGHH2Lw4MFo2bIlWrVqpQXLqnvkkUfw3Xff4YorrsDpp58Oh8OBnTt3Ys6cOThy5AieeOKJoPWtViueeuoplJWV4ayzzsLq1asxc+ZMjBgxAuedd15jn2YA/n5dL774IkaPHo0uXbpAURQsWbIEx48fR15e3gltm4iIqLliUIqIiIga7Pbbb8c777yDefPmobCwEE6nE61bt0a/fv3w3//+N+JZPyq73Y6vv/4a06dPxxNPPIFDhw6hffv2mDp1Kh588EFtPVEU8dFHH+HOO+/E7Nmz4fF4cO655yI/Px8nn3xy0DZ79uyJdevW4eGHH8Z9992HoqIipKWlIScnR+srFQknnXQSVq9ejX/961+49dZb4XK50KNHD8yfP19r1B5pWVlZuP322/HEE0/gm2++Qf/+/fHtt9/isccew9y5c7Fz5044HA507NgRQ4YMCQr+LFiwAH369MFrr72GBQsWwOFwoGfPnvjXv/6lrXPvvfeiZ8+eeO655/D222/D7XYjMzMTZ511Fm6++eZGjfm1117D3XffjYsvvhhutxvXXHMNFixYUOu648ePBwAsWrQITzzxBIqLi9GyZUucccYZyM/P1zK+VBaLBZ988gkmTZqEmTNnwuFwYOLEiTWCV42Rk5ODtLQ0zJ49G/v27YPVasVJJ52EBQsW1Jn9R0REFM8ERVGUaA+CiIiIiEhPEyZMwHvvvYeysrJoD4WIiIgqsacUERERERERERE1OQaliIiIiIiIiIioybF8j4iIiIiIiIiImhwzpYiIiIiIiIiIqMkxKEVERERERERERE2OQSkiIiIiIiIiImpyDEoREREREREREVGTM0d7AEYgyzL27duH5ORkCIIQ7eEQEREREREREcUsRVFQWlqKdu3aQRRD50MxKAVg3759yMrKivYwiIiIiIiIiIiajT179qBDhw4hHzd0UGrGjBl46KGHgpa1adMGBw4cAOCPvD300EOYO3cujh07hr59++I///kPTjnllAbtJzk5GYD/yUpJSdGWe71eLF26FEOHDoXFYjnB34b0xGMVO3isYgOPU+zgsYoNPE6xg8cqNjidTrRr1w4AsGvXLqSlpUV3QBQSX1Oxg8cqNsTKcSopKUFWVpYWbwnF0EEpADjllFPw5Zdfat+bTCbt69mzZ+Ppp5/GggUL0L17d8ycORN5eXnYunVrvb94ILVkLyUlpUZQKiEhASkpKYY+2MRjFUt4rGIDj1Ps4LGKDTxOsYPHKjY4HA68+uqr+PXXX9GqVSskJCREe0gUAl9TsYPHKjbE2nGqr0WS4Rudm81mZGZmav9at24NwJ8l9eyzz2L69OkYM2YMcnNz8cYbb6C8vBwLFy6M8qiJiIiIiEgvFosFV199NQYPHhwTF2VERFQ7w2dKbdu2De3atYPNZkPfvn0xa9YsdOnSBTt37sSBAwcwdOhQbV2bzYYBAwZg9erVuOmmm0Ju0+12w+12a9+XlJQA8EccvV6vtlz9OnAZGROPVezgsYoNPE6xg8cqNvA4xQ4eq9jBYxUbeJxiB49VbIiV4xTu+ARFURSdx9Jon332GcrLy9G9e3ccPHgQM2fOxO+//45NmzZh69atOPfcc1FYWKjVkwPAjTfeiF27duGLL74Iud3aelUBwMKFC5n6S0RERERkcJIkYf369QCA3r17B7X4ICKi6CsvL8e4ceNQXFwc1CapOkMHpapzOp3o2rUrpk2bhr/85S8499xzsW/fPrRt21ZbZ+LEidizZw8+//zzkNupLVMqKysLhw8frtFTatmyZcjLy2NasMHxWMUOHqvYwOMUO3isYgOPU+zgsYoNTqcTLVq0AAAUFRWx0bmBNbfXlCRJ8Pl8iKHL6LD5fD6sXr0a55xzDsxmwxdVxS0jHCdBEGAymWAymUL2jCopKUGrVq3qDUrF1F9aYmIiTj31VGzbtg2jR48GABw4cCAoKFVUVIQ2bdrUuR2bzQabzVZjucViqfWNMtRyMh4eq9jBYxUbeJxiB49VbOBxih08VsYWeGx4rGJDczhOZWVl2Lt3b7MMSAH+vs2ZmZnYv39/vc2pKXqMdJwSEhLQtm1bWK3WGo+F+3qPqaCU2+3Gli1bcP7556Nz587IzMzEsmXL0Lt3bwCAx+PBypUr8fjjj0d5pERERERERNRcSJKEvXv3IiEhAa1bt456MEAPsiyjrKwMSUlJEEXDz4kWt4xwnBRFgcfjwaFDh7Bz507k5OQ0eiyGDkpNnToVo0aNQseOHVFUVISZM2eipKQE11xzDQRBwJQpUzBr1izk5OQgJycHs2bNQkJCAsaNGxftoRMREREREVEz4fV6oSgKWrduDYfDEe3h6EKWZXg8HtjtdgalDMwox8nhcMBisWDXrl3aeBrD0EGpvXv34m9/+xsOHz6M1q1b4y9/+QvWrFmDTp06AQCmTZsGl8uFW265BceOHUPfvn2xdOlSJCcnR3nkRERERERE1Nw0xwwposaKRFDM0EGpRYsW1fm4IAiYMWMGZsyY0TQDIiIiIiIiIiKiiGBOHhEREREREVGc69KlC1566aVoDyNisrOz8eyzz0Z7GFQPBqWIiIiIiCimWK1WPPfcc7jxxhtrnfWJyKhkWcGOQ2X4dc9x7DhUBllumpn89uzZg+uvvx7t2rWD1WpFp06dMHnyZBw5cqRJ9k8UiqHL94iIiIio6cmygoIjTpRW+JBsNyM7PRGiyD4qZBwWiwX/+Mc/kJ+fH/a040TRtrGwGIvX7cX2ojK4vTJsFhHdMpIwtk8H5LZP1W2/O3bsQL9+/dC9e3e8/fbb6Ny5MzZt2oS7774bn332GdasWYOWLVvqtv9QJEmCIAhsqh7nePSJiIiISLOxsBgPf7oZD360CY98ugUPfrQJD3+6GRsLi6M9NCKimLWxsBjPL9+GDXuLkeawIrtVItIcVmzY61+u53vsrbfeCqvViqVLl2LAgAHo2LEjRowYgS+//BKFhYWYPn26tm5ZWRmuuuoqJCUloV27dnjhhReCtjVjxgx07NgRNpsN7dq1w6RJk7THPB4Ppk2bhvbt2yMxMRF9+/bFihUrtMcXLFiAtLQ0fPLJJ+jZsydsNhvmzZsHu92O48ePB+1n0qRJGDBggPb96tWr0b9/fzgcDmRlZWHSpElwOp3a40VFRRg1ahQcDgc6d+6Mt956K0LPHumNQSkiIiIiAhDdiyaihpAkCStXrsSGDRsgSVK0h0NxSFEUuH1SWP9cHh/e/XkPjjjd6NIqAQlWEQIUJFhFdGmVgCNON/63dg9cHl9Y21OU8Ev+jh49ii+++AK33HILHA5H0GOZmZm46qqr8M4772jbfOGFF9CrVy+sW7cO9957L+644w4sW7YMAPDee+/hmWeewSuvvIJt27bhgw8+wKmnnqpt79prr8V3332HRYsW4bfffsNll12G4cOHY9u2bdo65eXlePTRR/Hqq69i06ZN+Pvf/460tDQsXrxYW0eSJLz77ru46qqrAAAbNmzAsGHDMGbMGPz222945513sGrVKtx2223az0yYMAEFBQX46quv8N577+HFF19EUVFRA44oRQvL94iIiIgIsqxg8bq9OOr0oFtGkjbteZLdjG62JGwvKsOSdYXo2TaFpXwUdRUVFcjLywMA3HbbbbDb7VEeEcUbjyRjxkebw1q3xOXF2l3HYDWLOF7uq/G4V5LxxcaDOFzqQYqj/nLUGRf3hM1sCmvf27Ztg6Io6NGjR62P9+jRA8eOHcOhQ4cAAGeffTbuueceiKKI7t2747vvvsMzzzyDvLw87N69G5mZmRgyZAgsFgs6duyIs88+GwDw559/4u2338bevXvRrl07AMDUqVPx+eefY/78+Zg1a5b/d/V68eKLL+K0007TxnDFFVdg4cKFuP766wEAy5cvx7Fjx3DZZZcBAJ544gmMGzcOU6ZMAQDk5OTg+eefx4ABA/DSSy9h9+7dWhli3759AQCvvfZayN+ZjIWZUkRERESEgiNObC8qQ9tUB9w+GTsOlaHC4794EgQBbVMd2FZUioIjznq2REREgbySDElWYA4R0DeJAiRZgVeSm3hk0DKk1BsRapBJ1a9fP2zZsgUAcNlll8HlcqFLly6YOHEi3n//ffh8/s+JdevWQVEUdO/eHUlJSdq/lStX4s8//9S2Z7Va0atXr6B9XHXVVVixYgX27dsHAHjrrbcwcuRItGjRAgCwdu1aLFiwIGi7w4YNgyzL2LlzJ7Zs2QKz2YwzzzxT2+bJJ5+MtLS0CD5TpBdmShERERERSit8cHtlOFJN2F/swuEyDywmEVkt/aeLDqsJB0tklFbUvMtPRBRvrCYRMy7uGda6Ow878fAnm5HmsCDJVvMSvMztw3GXF3cO7Y7OrRLD2ne4unXrBkEQsHnzZowePbrG47///jtatGiBVq1ahdyGGrDKysrC1q1bsWzZMnz55Ze45ZZb8MQTT2DlypWQZRkmkwlr166FyRScxZWUlKR97XA4tO2pzj77bHTt2hWLFi3CP/7xD7z//vuYP3++9rgsy7jpppuC+lepOnbsiK1btwaNk2ILg1JEREREhGS7GTaLCJdHglx551wO6Fvi8kiwWUQk23n6SEQkCELYJXTdM5LRvU0yNuwtRnKGJSh4oigKDpa40atDGrpnJEe8PDo9PR15eXl48cUXcccddwT1lTpw4ADeeustXH311dqYfvrpp6CfX7NmDU4++WTte4fDgYsvvhgXX3wxbr31Vpx88snYsGEDevfuDUmSUFRUhPPPP7/B4xw3bhzeeustdOjQAaIo4sILL9Qe69OnDzZt2oRu3brV+rM9evSAz+fDzz//rGV6bd26tUbzdDImlu8REREREbLTE9EtIwn7i12QZX8wSi3rUBQF+4tdyMlIRnZ6/XfxiYioiigKGNunA1omWrG9qAxlFT5IsoKyCh+2F5WhZaIVY/q0161f35w5c+B2uzFs2DB888032LNnDz7//HPk5eWhffv2eOSRR7R1f/jhBzzxxBP4448/8J///Af/+9//MHnyZAD+2fNee+01bNy4ETt27MCbb74Jh8OBTp06oXv37rjqqqtw9dVXY8mSJdi5cyd++uknPP7448jPz693jFdddRXWrVuHRx55BH/961+D+sTdc889+P7773Hrrbfil19+wbZt2/DRRx/h9ttvBwCcdNJJGD58OCZOnIgffvgBa9euxQ033FCjsTsZE4NSRERERBR00XSgxA2vJMMnNd1FExFRc5bbPhWTBufg1A6pOO7yoOCwE8ddHvTqkIZJg3OQ2z5Vt33n5OTg559/RteuXXHFFVega9euuPHGGzFo0CB8//33aNmypbbubbfdhrVr16J37954+OGH8dRTT2HYsGEAgLS0NMybNw/nnnsuevXqheXLl+Pjjz9Geno6AGD+/Pm4+uqrcdddd+Gkk07CxRdfjB9++AFZWVlhjfGss87Cb7/9ps26p+rVqxdWrlyJbdu24fzzz0fv3r1x//33o23btto68+fPR1ZWFgYMGIAxY8bgxhtvREZGRiSePtIZ86+JiIiICEDVRdNjn23B9iInDpW5Ybea0KtDGsb0aa/rRRMRUXOX2z4VPdumoOCIE6UVPiTbzchOT2ySYH+nTp2C+jTVZseOHSgpKUFKSgpEsWb+yujRo2vtS6WyWCx46KGH8NBDD9X6+IQJEzBhwoSQP//jjz+GfOyss87C0qVLQz6emZmJTz75JGjZ+PHjQ65PxsGgFBERERFpctunYuSpbfHd9iPomO7AZWdkNdlFE1G4LBYLHn30Ufz++++wWCzRHg5R2ERRQJfWSfWvSBQnGJQiIiIioiAKgBSHBW1THbx4IkOyWq246667kJ+fD6vVGu3hEBFRI7GnFBEREREFkSobnav/JyIiItIDg1JEREREFIRBKTI6SZLw888/Y9u2bZAkKdrDISKiRmL5HhEREREFYVCKjK6iogLnnHMOAOCGG24Imj6eiIhiBzOliIiIiCiIrzIY5WNQioiIiHTEoBQRERERBVEzpGQGpYiIiEhHDEoRERERURCJmVJERETUBBiUIiIiIqIgWqaUwqAUERER6YdBKSIiIiIKwkwpIiIiagoMShERERFREB97ShERUQPNmDEDp59+uvb9hAkTMHr06CYfR0FBAQRBwC+//FLnelu3bkVmZiZKS0t1G4vb7UbHjh2xdu1a3fYR6xiUIiIiIqIgatkeM6XIqCwWC+677z5cccUVsFgs0R4OkWFNmDABgiBAEARYLBZ06dIFU6dOhdPp1H3fzz33HBYsWBDWuuEGkiJp+vTpuPXWW5GcnAwAWLFiBQRBwPHjx4Oet1D/AKCoqAg33XQTOnbsCJvNhszMTAwbNgzff/89AMBms2Hq1Km45557muz3ijUMShERERFREJ/kD0ZJDEqRQVmtVjzwwAP429/+BqvVGu3hEBna8OHDsX//fuzYsQMzZ87Eiy++iKlTp9a6rtfrjdh+U1NTkZaWFrHtRdLevXvx0Ucf4dprr6318eeeew779+/X/gHA/PnzaywbO3Ysfv31V7zxxhv4448/8NFHH2HgwIE4evSotq2rrroK3377LbZs2aL/LxaDGJQiIiIioiBqphSDUkRE9XA6Q/+rqAh/XZcrvHUbQc3gycrKwrhx43DVVVfhgw8+AFBVcvf666+jW7duaNOmDRRFQXFxMW688UZkZGQgJSUFF1xwAX799deg7T722GNo06YNkpOTcf3116Oi2u9bvXxPlmU8/vjj6NatG2w2Gzp27IhHHnkEANC5c2cAQO/evSEIAgYOHKj93Pz589GjRw/Y7XacfPLJePHFF4P28+OPP6J3796w2+0488wzsX79+nqfk3fffRennXYaOnToUOvjqampyMzM1P4BQFpaWtCy48ePY9WqVXj88ccxaNAgdOrUCWeffTbuvfdeXHjhhdq20tPTcc455+Dtt9+ud1zxyBztARARERGRsfhkGQAgKQoURdHKFIiMQpZlbNq0Cbt374Zc+fdKFBVJSaEfGzkS+PTTqu8zMoDy8trXHTAAWLGi6vvsbODw4ZrrRWBWVIfDEZQRtX37drz77rv43//+B1dlcOzCCy9Ey5YtkZ+fj9TUVLzyyisYPHgw/vjjD7Rs2RLvvvsuHnzwQfznP//B+eefjzfffBPPP/88unTpEnK/9957L+bNm4dnnnkG5513Hvbv34/ff/8dgD+wdPbZZ+PLL7/EKaecomVAzps3Dw8++CDmzJmD3r17Y/369Zg4cSISExNxzTXXwOl04qKLLsIFF1yA//u//8POnTsxefLkep+Db775BmeeeeaJPI1ISkpCUlISPvjgA/zlL3+BzWYLue7ZZ5+Nb7/99oT211wxKEVEREREGkVRIMnq1/5/jEmR0bhcLvTu3RsAMH78+DovBomoyo8//oiFCxdi8ODB2jKPx4M333wT6enpKCkpwddff40NGzagqKhIe209+eST+OCDD/Dee+/hxhtvxLPPPovrrrsON9xwAwBg5syZ+PLLL2tkS6lKS0vx3HPPYc6cObjmmmsAAF27dsV5550HAGjdujUAf1aRmpkEAA8//DCeeuopjBkzBoA/o2rz5s145ZVXcM011+Ctt96CJEl4/fXXkZCQgFNOOQV79+7FP/7xjzqfh4KCApxxxhmNeQo1ZrMZCxYswMSJE/Hyyy+jT58+GDBgAK688kr06tUraN327dujoKDghPbXXDEoRURERESa6iV7kqJABKNSRES1KisL/ZjJFPx9UVHodcVqnXUiGMD45JNPkJSUBJ/PB6/Xi0suuQQvvPCC9ninTp3QunVrLetw3bp1KCsrQ3p6etB2XC4X/vzzTwDAli1bcPPNNwc93q9fP3z99de1jmHLli1wu91BwbD6HDp0CHv27MH111+PiRMnast9Ph9SU1O17Z522mlISEgIGkd9XC4X7HZ72GMJZezYsbjwwgvx7bff4vvvv8fnn3+O2bNn49VXX8WECRO09RwOB8pDZcnFOQaliIiIiEgjVSsNkWQFFlOIlYmI4l1iYvTXrcegQYPw0ksvwWKxoF27djVmrEysti9ZltG2bVusCCwnrNTYxuUOh6PBP6MGyebNm4e+ffsGPWaqDPgpjSxnbNWqFY4dO9aon63ObrcjLy8PeXl5eOCBB3DDDTfgwQcfDApKHT16VMsGo2BsdE5EREREmurteXxsdk5EFNMSExPRrVs3dOrUqUZAqja9e/fGgQMHYDab0a1bt6B/rVq1AgD06NEDa9asCfq56t8HysnJgcPhwPLly2t9XO0hJUmStqxNmzZo3749duzYUWMcamP0nj174tdff9V6YdU3jsDfcfPmzfWu1xg9e/aEs1pT+o0bN2olxxSMQSkiIiIi0viqRaU4Ax8RUXwZMmQI+vXrh9GjR+OLL75AQUEBVq9ejfvuuw8///wzAGDy5Ml4/fXX8frrr+OPP/7Agw8+iE2bNoXcpt1uxz333INp06bhv//9L/7880+sWbMGr732GgAgIyMDDocDn3/+OQ4ePIji4mIA/tkBH330UTz33HP4448/sGHDBsyfPx9PP/00AGDcuHEQRRHXX389Nm/ejPz8fDz55JP1/o7Dhg3D999/HxQEa6gjR45oDdZ/++037Ny5E//73/8we/ZsXHLJJUHrfvvttxg6dGij99WcMShFRERERJrqmVIMShERxRdBEJCfn4/+/fvjuuuuQ/fu3XHllVeioKAAbdq0AQBcccUVeOCBB3DPPffgjDPOwK5du+ptLn7//ffjrrvuwgMPPIAePXrgiiuuQFFlny2z2Yznn38er7zyCtq1a6cFdW644Qa8+uqrWLBgAU499VQMGDAACxYs0DKlkpKS8PHHH2Pz5s3o3bs3pk+fjscff7ze33HkyJGwWCz48ssvG/08JSUloW/fvnjmmWfQv39/5Obm4v7778fEiRMxZ84cbb3vv/8excXF+Otf/9rofTVngtLYIsxmpKSkBKmpqSguLkZKSoq23Ov1Ij8/X/uDJePisYodPFaxgccpdvBYxYZYOk5Hytx4cukf2vd35nVH6+T4mdkslo5VPHM6nUhKSgIAHDt2rNF9bkh/zeU1VVFRgZ07d6Jz584RaZBtRLIso6SkBCkpKRCrN15vhl588UV8+OGH+OKLL3Tdz2WXXYbevXvjX//6V0S2Z6TjVNfrIlScpTo2OiciIiIiTfXMKJn3L8mALBYL7rzzTuzYsSOmAx1EFD033ngjjh07htLSUiQnJ+uyD7fbjdNOOw133HGHLttvDhiUIiIiIiJN9dn32OicjMhqteKxxx5Dfn6+1iCZiKghzGYzpk+frus+bDYb7rvvPl33Eeuaf04eEREREYXNJwUHoSSJQSkiIiLSB4NSRERERKSpXq5XPXOKyAhkWUZBQQEOHjwIuXp3fiIiihks3yMiIiIiTfVyPYkX/GRALpcL3bt3BwBcfvnlsNnipxk/EVFzwkwpIiIiItJUb3QuMSZFREREOmFQioiIiIg0NYNSLN8jIiIifTAoRUREREQaBqWIiIioqTAoRURERESa6kEoH3tKERHFrRUrVkAQBBw/fhwAsGDBAqSlpUV1TAAwY8YMnH766dEexgnxeDzo1q0bvvvuu2gPpVZTp07FpEmTdN8Pg1JEREREpKne6Lz6bHxERBQ7JkyYAEEQIAgCLBYLunTpgqlTp8LpdDZqe1dccQX++OOPCI+ypsWLF2PgwIFITU1FUlISevXqhX//+984evSo7vtuKnPnzkWnTp1w7rnnAgAKCgpw/fXXo3PnznA4HOjatSsefPBBeDyeoJ/bvXs3rrzySiQnJ6NVq1aYNGlS0DorVqzAJZdcgrZt2yIxMRGnn3463nrrraBt7N+/H+PGjcNJJ50EURQxZcqUGuObNm0a5s+fj507d0b+lw/AoBQRERERaWpkSkkMShERxbLhw4dj//792LFjB2bOnIkXX3wRU6dObdS2HA4HMjIyIjzCYNOnT8cVV1yBs846C5999hk2btyIp556Cr/++ivefPNNXffdlF544QXccMMN2ve///47ZFnGK6+8gk2bNuGZZ57Byy+/jH/961/aOpIkYdSoUSgvL8c333yDRYsWYfHixbjrrru0dVavXo1evXph8eLF+O2333Ddddfh6quvxscff6yt43a70bp1a0yfPh2nnXZarePLyMjA0KFD8fLLL+vw21dhUIqIiIiINDV6SjFTigzIbDbj5ptvxogRI2A2m6M9HCJDs9lsyMzMRFZWFsaNG4errroKH3zwAQB/cGLSpEnIyMhAQkIChg8fjp9++inktmor3/voo49w5plnwm63o1WrVhgzZgwA4N///jdOPfXUGts444wz8MADD9S6/R9//BGzZs3CU089hSeeeALnnHMOsrOzkZeXh8WLF+Oaa64JWv/NN99EdnY2UlNTceWVV6K0tFR77PPPP8d5552HtLQ0pKen46KLLsKff/6pPV5QUABBELBkyRIMGjQICQkJOO200/D9998H7WPevHnIyspCQkICLr30Ujz99NM1noOPP/4YZ5xxBux2O7p06YKHHnoIPp8v5PO4bt06bN++HRdeeKG2bPjw4Zg/fz6GDh2KLl264OKLL8bUqVOxZMkSbZ2lS5di8+bNeOWVV9C7d28MGTIETz31FObNm4eSkhIAwL/+9S88/PDDOOecc9C1a1dMmjQJw4cPx/vvv69tJzs7G8899xyuvvpqpKamhhznxRdfjLfffjvk45HAoBQRERERaaqX67GlFBmRzWbD888/j5tuugk2my3aw6E45nQ6Q/6rqKgIe12XyxXWupHgcDjg9XoB+Eu0Fi9ejDfeeAM///wzunTpghEjRoRdJvfpp59izJgxuPDCC7F+/XosX74cZ555JgDguuuuw+bNm4OCXL/99hvWr1+PCRMm1Lq9t956C0lJSbjllltqfTwwGPTnn3/igw8+wCeffIJPPvkEK1euxGOPPaY97nQ6ceedd+Knn37C8uXLIYoiLr30UsjVPtimT5+OqVOn4pdffkH37t3xt7/9TQsofffdd7j55psxefJk/PLLL8jLy8MjjzwS9PNffPEF/v73v2PSpElawGjBggU11gv0zTffoHv37khJSQm5DgAUFxejZcuW2vfff/89cnNz0bZtW23ZsGHD4Ha7sXbt2rC3E66zzz4be/bswa5duxr8s+HibQUiIiIi0lTvKcVG50REoSUlJYV8bOTIkfj000+17zMyMlBeXl7rugMGDMCKFSu077Ozs3H48OEa6yknmL36448/YuHChRg8eDCcTideeuklLFiwACNGjIAsy3juuedw+umn47XXXsPdd99d7/YeeeQRXHnllXjooYe0ZWo5WIcOHTBs2DDMnz8fZ511FgBg/vz5GDBgALp06VLr9rZt24YuXbrAYrHUu29ZlrFgwQIkJycDAMaPH4/ly5drwaCxY8cGrf/aa68hIyMDmzdvRm5urrZ86tSpWsbSQw89hFNOOQXbt2/HySefjBdeeAEjRozQyh27d++O1atX45NPPgl6Dv75z39qWVxdunTBww8/jGnTpuHBBx+sdewFBQVo165dnb/fn3/+iRdeeAFPPfWUtuzAgQM1yidbtGgBq9WKAwcO1Lqd9957Dz/99BNeeeWVOvdXm/bt22vj7dSpU4N/PhzMlCIiIiIijVy9fE9m+R4Zj6IoOHToEIqLi0/4Ip2oufvkk0+QlJQEu92Ofv36oX///njhhRfw559/wuv1ao22AcBiseCss87Cli1bwtr2L7/8gsGDB4d8fOLEiXj77bdRUVEBr9eLt956C9ddd13I9RVFgSAIYe07OztbC0gBQNu2bVFUVKR9/+eff2LcuHHo0qULUlJS0LlzZwD+RuGBevXqFbQNANp2tm7dirPPPjto/erfr127Fv/+97+RlJSk/Zs4cSL2798fMgjpcrlgt9tD/m779u3D8OHDcdlllwX1nQJQ6/MT6nlbsWIFJkyYgHnz5uGUU04Jub9QHA4HAIT8PSKBmVJEREREpKmeKcWgFBlReXm5dgf/4osvhtVqjfKIKF6VlZWFfMxkMgV9HxgwqU4Ug/NFCgoKTmhcgQYNGoSXXnoJFosF7dq107KQ9u/fD6BmkKMhgSE1aBHKqFGjYLPZ8P7778Nms8HtdtfIYArUvXt3rFq1Cl6vt95sqeqPC4IQVJo3atQoZGVlYd68eWjXrh1kWUZubm6N2ewCt6P+3up2ansuqgfCZVnGQw89pPXSChQq8NSqVSts2LCh1sf27duHQYMGoV+/fpg7d27QY5mZmfjhhx+Clh07dgxerxdt2rQJWr5y5UqMGjUKTz/9NK6++upa91UftYyzdevWjfr5cDBTioiIiIg0UrVyPQaliIhCS0xMDPmvekCirnWrB3dCrdfYMXbr1g2dOnUKCsB069YNVqsVq1at0pZ5vV6sXbsWPXr0CGvbvXr1wvLly0M+bjabcc0112D+/PmYP38+rrzySiQkJIRcf9y4cSgrK8OLL75Y6+PHjx8Pa1xHjhzBli1bcN9992Hw4MHo0aMHjh07FtbPBjr55JPx448/Bi37+eefg77v06cPtm7dim7dutX4Vz3YqOrduzd+//33GgGuwsJCDBw4EH369MH8+fNr/Hy/fv2wcePGoFK9pUuXwmaz4YwzztCWrVixAhdeeCEee+wx3HjjjQ3+vVUbN26ExWJpVJZVuJgpRUREREQaqVoLKc6+R0TUPCUmJuIf//gH7r77brRs2RIdOnTArFmzUF5ejuuvvz6sbTz44IMYPHgwunbtiiuvvBI+nw+fffYZpk2bpq1zww03aEGu7777rs7t9e3bF9OmTcNdd92FwsJCXHrppWjXrh22b9+Ol19+Geeddx4mT55c77hatGiB9PR0zJ07F23btsXu3bvxz3/+M6zfKdDtt9+O/v374+mnn8aoUaPw1Vdf4bPPPgvKnnrggQdw0UUXISsrC5dddhlEUcRvv/2GDRs2YObMmbVud9CgQXA6ndi0aZPW32rfvn0YOHAgOnbsiCeffBKHDh3S1s/MzAQADB06FD179sTNN9+Mp556CsePH8fUqVMxceJErWm6GpCaPHkyxo4dqwWwrFZrULPzX375BYA/2+/QoUP45ZdfYLVa0bNnT22db7/9Fueff369GXEngplSRERERKSp3ticmVJERM3XY489hrFjx2L8+PE488wzsWPHDnz22Wdo0aJFWD8/cOBA/O9//8NHH32E008/HRdccEGN8rKcnBycc845OOmkk9C3b996t/n4449j4cKF+OGHHzBs2DCccsopuPPOO9GrVy+tmXh9RFHEokWLsHbtWuTm5uKOO+7AE088EdbPBjr33HPx8ssv4+mnn8Zpp52Gzz//HHfccUdQFtywYcPwySefYNmyZTjrrLPwl7/8BU8//XSdjcHT09MxZswYvPXWW9qypUuXYvv27fjqq6/QoUMHtG3bVvunMplM+Pjjj2Gz2XD++efj8ssvx+jRo/Hkk09q6yxYsADl5eV49NFHg7ZRvbywd+/e6N27N9auXYuFCxeid+/eGDlyZNA6b7/9NiZOnNjg560hBIWdAVFSUoLU1FQUFxcHTcno9XqRn5+PkSNHhtX9n6KHxyp28FjFBh6n2MFjFRti6Ti9v34vftx5DFaTAI+k4KzsFhjTp0O0h9VkYulYxTOn06nNenbs2LGgaeLJWJrLa6qiogI7d+5E586d62xQHctkWUZJSQlSUlJClp01hqIoOPnkk3HTTTfhzjvvjNh2o2XixIn4/fff8e23357QdjZs2IAhQ4Zg+/btQQ3b66PXcaru008/xd13343ffvsNZnPtRXZ1vS5CxVmqY6YUEREREWl8kv9+pdXsP02s3viciIgoXEVFRXj66adRWFiIa6+9NtrDaZQnn3wSv/76K7Zv344XXngBb7zxRtgZW3U59dRTMXv27Ig2tY8kp9OJ+fPnhwxIRQp7ShERERGRRi3Xs5pFwC1BZlCKiIgaqU2bNmjVqhXmzp0bdkmg0fz444+YPXs2SktL0aVLFzz//PO44YYbIrLtSAS39HL55Zc3yX4YlCIiIiIijdrY3GoyAfAyU4oMyWw2Y/z48di7d6/ud/GJqPGaQ7egd999N9pDaNb4Dk5EREREmqBMKQByM7igoObHZrPhtddeQ35+Pmw2W7SHQ0REjcSeUkRERESkqR6UUntMEREREUUag1JEREREpGGmFMUCRVHgdDpRUVHRLMqDKHbw742oSiReDyzfIyIiIiKN2kPKZuLse2Rc5eXlWtPkY8eOwWq1RnlE1NyZTCYAgMfjgcPhiPJoiIyhvLwcAGCxWBq9DQaliIiIiEhTPVNKYlCKiAhmsxkJCQk4dOgQLBYLRLH5FR3JsgyPx4OKiopm+fs1F0Y4ToqioLy8HEVFRUhLS9OCto3BoBQRERERaWQGpYiIahAEAW3btsXOnTuxa9euaA9HF4qiwOVyweFwQBCEaA+HQjDScUpLS0NmZuYJbYNBKSIiIiLSqOV6VhODUkREgaxWK3JycuDxeKI9FF14vV5888036N+//wmVY5G+jHKcLBbLCWVIqRiUIiIiIiKN2ticmVJERDWJogi73R7tYejCZDLB5/PBbrczKGVgze04sVCUiIiIiDRao3M1KMWZpoiIiEgnDEoRERERkUbNjLIwU4qIiIh0xvI9IiIiItJI7ClFMcBkMmHMmDE4cOBARHqaEBFRdDAoRUREREQaNQhltzAoRcZlt9uxaNEi5OfnN9v+PkRE8YDle0RERESkqcqUMgV9T0RERBRpDEoREREREQBAURSt0bk6+55PVqCw2TkRERHpIKaCUo8++igEQcCUKVO0ZYqiYMaMGWjXrh0cDgcGDhyITZs2RW+QRERERDEqMClKDUoBAGNSZDROpxNWqxWjR4+G0+mM9nCIiKiRYiYo9dNPP2Hu3Lno1atX0PLZs2fj6aefxpw5c/DTTz8hMzMTeXl5KC0tjdJIiYiIiGKTT5a1rwODUj6W8BEREZEOYiIoVVZWhquuugrz5s1DixYttOWKouDZZ5/F9OnTMWbMGOTm5uKNN95AeXk5Fi5cGMURExEREcWegJgULCZB+5p9pYiIiEgPMRGUuvXWW3HhhRdiyJAhQct37tyJAwcOYOjQodoym82GAQMGYPXq1U09TCIiIqKYFpQpZao6TZRYv0dEREQ6MEd7APVZtGgR1q1bh59++qnGYwcOHAAAtGnTJmh5mzZtsGvXrpDbdLvdcLvd2vclJSUAAK/XC6/Xqy1Xvw5cRsbEYxU7eKxiA49T7OCxig2xcpzcHi9kWYZZFODz+SBAhiQDFW4PbGJ8BKZi5VjFu+rn7DxexsXXVOzgsYoNsXKcwh2foYNSe/bsweTJk7F06VLY7faQ6wmCEPS9oig1lgV69NFH8dBDD9VYvnTpUiQkJNRYvmzZsgaMmqKJxyp28FjFBh6n2MFjFRuMfpzKvMCe3SLMIpCfvxN7d4vwycAXSwuQZIn26JqW0Y9VvKuoqNC+/uqrr+q8ViBj4GsqdvBYxQajH6fy8vKw1hMUA8/x+8EHH+DSSy+FyWTSlkmSBEEQIIoitm7dim7dumHdunXo3bu3ts4ll1yCtLQ0vPHGG7Vut7ZMqaysLBw+fBgpKSnacq/Xi2XLliEvLw8WS5ydicUYHqvYwWMVG3icYgePVWyIleN0qNSN5776EwlWE/414iQ8kv87XF4ZUwZ3RaskW7SH1yRi5VjFO6fTqfWaLSoqQlpaWnQHRCHxNRU7eKxiQ6wcp5KSErRq1QrFxcVBcZbqDJ0pNXjwYGzYsCFo2bXXXouTTz4Z99xzD7p06YLMzEwsW7ZMC0p5PB6sXLkSjz/+eMjt2mw22Gw1T6wsFkutBzXUcjIeHqvYwWMVG3icYgePVWww+nESTD6IogiL2eQfq9kEtwQIotnQ49aD0Y9VvLPb7RgxYgSKiopgt9t5rGIAX1Oxg8cqNhj9OIU7NkMHpZKTk5Gbmxu0LDExEenp6dryKVOmYNasWcjJyUFOTg5mzZqFhIQEjBs3LhpDJiIiIopZ6ix7JlGo/L8IQApqgE5kBHa7HR9++CHy8/NZukdEFMMMHZQKx7Rp0+ByuXDLLbfg2LFj6Nu3L5YuXYrk5ORoD42IiIgopqhBKbMWlPIvZ0yKiIiI9BBzQakVK1YEfS8IAmbMmIEZM2ZEZTxEREREzYUalBKFwEwpMFOKiIiIdBFzQSkiIiIi0kf1TCn1/7Jx58WhOOV0OpGRkQFJknDgwAE2OiciilEMShERERERAMCnZkpp5Xv+/0tMlCIDCne6cSIiMi4x2gMgIiIiImOonimllvGxfI+IiIj0wKAUEREREQGoOfueWcuUYvkeERERRR6DUkREREQEAJCU4KCUyKAUERER6YhBKSIiIiICELrROYNSREREpAcGpYiIiIgIAOCTQjU6Z1CKiIiIIo+z7xERERERAEBWy/eEakEphUEpMhZRFNG/f38cOXIEosj77EREsYpBKSIiIiICAPiqNTpXg1PMlCKjcTgc+PLLL5Gfnw+HwxHt4RARUSPxtgIRERERAQBktaeUKThTysegFBEREemAQSkiIiIiAlAVfBKrle/JDEoRERGRDli+R0REREQAAmff89+3ZKYUGZXT6UR2djY8Hg927dqFtLS0aA+JiIgagUEpIiIiIgJQFZQyVebSm5kpRQZ2+PDhaA+BiIhOEMv3iIiIiAhA1Sx7pspMKZGZUkRERKQjBqWIiIiICAAgyTKAqgwpLVNKYVCKiIiIIo9BKSIiIiICAEj+mJSWIaVlSkkMShEREVHkMShFRERERABqZkqZKmfhk5gpRURERDpgUIqIiIiIAFT1jhKF4PI9iT2liIiISAecfY+IiIiIAFTNsmc2VWZKMShFBiWKIs444wwUFxdDFHmfnYgoVjEoRUREREQAqjKl1GAUg1JkVA6HA99//z3y8/PhcDiiPRwiImokBqWI4pwsKyg44kRphQ/JdjOy0xO1xrZERBRf1OCT2kuKQSkiIiLSE4NSRHFsY2ExFq/bi+1FZXB7ZdgsIrplJGFsnw7IbZ8a7eEREVETk5gpRURERE2IQSmiOLWxsBjPL9+Go04P2qY64Eg1weWRsGFvMQqPuTBpcA4DU0REcaZ6+Z7I2ffIoMrLy9GzZ0+Ul5dj27ZtSE3lOQsRUSxiV0CiOCTLChav24ujTg+6ZSQhwWaCSRSQZDejW0YSjjo9WLKuUGt4S0RE8UGuFpRSG54zU4qMRlEU7Nq1C4cOHYLCoCkRUcxiUIooDhUccWJ7URnapjpQ4ZWwbtcx7D1WDgAQBAFtUx3YVlSKgiPOKI+UiIiaUvVMKTPL94iIiEhHDEoRxaHSCh/cXhkOqwlOjwRZ8S9TOawmuL1y0DIiImr+5MqME3O18j0fg1JERESkAwaliOJQst0Mm0WEyyNppRpyQOq7yyPBZhGRbGfbOSKieKIGn9RglFn0nyqynJuIiIj0wKAUURzKTk9Et4wk7C92acEo9YJDURTsL3YhJyMZ2emJ0RwmERE1MfWzQO0lVRmTYqYUERER6YJBKaI4JIoCxvbpgJaJVuw97oJXkuGVZZRV+LC9qAwtE60Y06c9xMryDSIiig9aT6nKTCm1t5TMRtJERESkAwaliOJUbvtUTBqcg04tE+DxyThe7sNxlwe9OqRh0uAc5Lbn1MpERPFGqtboXP2/T2JQioxFEAT06NEDWVlZEATeRCMiilVsGEMUx3Lbp2JMnw6wmfdDkmVMG34ystMTmSFFRBSn1KCU2ktK6ynFTCkymISEBPz666/Iz89HQkJCtIdDRESNxKAUUZyTFQUpDgsAoGPLBAakiIjilKIokCqDT2ovKZM2+54crWERERFRM8byPaI4F1iS4WV5BhFR3FIU/z+gKkPKVNnwXJL9QSsiIiKiSIp4ppSiKFi5ciW+/fZbFBQUoLy8HK1bt0bv3r0xZMgQZGVlRXqXRHQCAmdU8vhkOKymKI6GiIiiJfDzoHqmFADICmBiMi0ZRHl5Oc4880yUlZVh4MCBSE1lL0wiolgUsUwpl8uFWbNmISsrCyNGjMCnn36K48ePw2QyYfv27XjwwQfRuXNnjBw5EmvWrInUbonoBPmkqpIMtyRFcSRERBRNUkBQSs2UEgPOFFnCR0aiKAq2bNmCPXv2MIuPiCiGRSxTqnv37ujbty9efvllDBs2DBaLpcY6u3btwsKFC3HFFVfgvvvuw8SJEyO1eyJqJG+1TCkiIopPUsCFvdpe0BwQlWJMioiIiCItYkGpzz77DLm5uXWu06lTJ9x777246667sGvXrkjtmohOQGCmFINSRETxS5LUmfcECJVle4FzX/gzpVjiTURERJETsfK9+gJSgaxWK3JyciK1ayI6AWx0TkREQFWmlCkgEiUIAsyV3zNTioiIiCJNl9n3Pv/8c6xatUr7/j//+Q9OP/10jBs3DseOHdNjl0TUSNUbnRMRUXxSe0YFBqUCv5fYt4eIiIgiTJeg1N13342SkhIAwIYNG3DXXXdh5MiR2LFjB+688049dklEjRRUvsdG50REcUttdF49KCVWlvKx0TkRERFFWsR6SgXauXMnevbsCQBYvHgxLrroIsyaNQvr1q3DyJEj9dglETVSYKNzNzOliIjilhqUUoNQKrNJALzBs/MRRZsgCOjUqRPKy8u1HmhERBR7dAlKWa1WlJeXAwC+/PJLXH311QCAli1bahlURGQMgZlS7ClFRBS/1KCTOUSmFINSZCQJCQnYtm0b8vPzkZCQEO3hEBFRI+kSlDrvvPNw55134txzz8WPP/6Id955BwDwxx9/oEOHDnrskogaKbCnlNvL8j0iongVqnxPDVIxKEVERESRpktPqTlz5sBsNuO9997DSy+9hPbt2wMAPvvsMwwfPlyPXRJRI3H2PSIiAgC5ltn3Ar9nUIqIiIgiTZdMqY4dO+KTTz6psfyZZ57RY3dEdAICG9ey0TkRUfzyhciUUr+XOfseGYjL5cL555+P4uJiDBo0CBaLJdpDIiKiRtAlU2rgwIH473//C5fLpcfmiShCFEUJyo7ysNE5EVHcUjNnQwWlfMyUIgORZRlr167F9u3bIXNmSCKimKVLUOqMM87AtGnTkJmZiYkTJ2LNmjV67IaITlD1UgwGpYiI4peaCVW90bkWlGKJNxEREUWYLkGpp556CoWFhfjvf/+LQ4cOoX///ujZsyeefPJJHDx4UI9dElEjVL/r7eEFBxFR3ApZviewfI+IiIj0oUtQCgBMJhMuueQSfPDBBygsLMS4ceNw//33IysrC6NHj8ZXX32l166JKEw1glLMlCIiiltyPT2lWL5HREREkaZbUEr1448/4oEHHsCTTz6JjIwM3HvvvcjIyMCoUaMwdepUvXdPRHXwScFBKAaliIjiV6hMKbOpMlOKQSkiIiKKMF1m3ysqKsKbb76J+fPnY9u2bRg1ahQWLVqEYcOGQahMAb/88ssxevRoPPnkk3oMgYjC4JWql+9x9j0ionil9hlUy/VUosBMKSIiItKHLkGpDh06oGvXrrjuuuswYcIEtG7dusY6Z599Ns466yw9dk9EYfLJzJQiIiI/qZ7yPWZKkdG0atUKHo8n2sMgIqIToEtQavny5Tj//PPrXCclJQVff/21HrsnojBVn0mpeuYUERHFDzUopZbrqdhTiowoMTER+/btQ35+PhITE6M9HCIiaiRdekrVF5AiImNQLzAcFhMAwCPJUDi7EhFRXFKDUqJQ++x7Ej8fiIiIKMJ0yZQCgPfeew/vvvsudu/eXSOtdt26dXrtlogaQG10nmgzweWVoCj+wJTNbIryyIiIqKmpNyrMYvA9SzVzSmI2LREREUWYLplSzz//PK699lpkZGRg/fr1OPvss5Geno4dO3ZgxIgReuySiBpBLdezW0w1lhERUXyp6ikVvFwt32OmFBmJy+XCkCFDMH36dLhcrmgPh4iIGkmXoNSLL76IuXPnYs6cObBarZg2bRqWLVuGSZMmobi4WI9dElEjqI3OrSYR1so74Wx2TkQUn9SgU8jyPfaUIgORZRnffPMNNm3aBFnmuQsRUazSJSi1e/dunHPOOQAAh8OB0tJSAMD48ePx9ttv67FLImoEX0BTW6vZ/3bAoBQRUXySKi/sqzc6F0UGpYiIiEgfugSlMjMzceTIEQBAp06dsGbNGgDAzp072USZyEDU2ffMJhEWE4NSRETxrLLNIEzVe0oxKEVEREQ60SUodcEFF+Djjz8GAFx//fW44447kJeXhyuuuAKXXnqpHrskokZQG51bxIBMKYlBKSKieCSrPaUEZkoRERFR09Bl9r25c+dqtd0333wzWrZsiVWrVmHUqFG4+eab9dglETWCV67KlGL5HhFRfPNpjc6Dg1LMlCIiIiK96BKUEkURYkDq9+WXX47LL79cj10R0QlQM6XMogCriZlSRETxTO0pVT0oxdn3iIiISC+6BKW2bduGDz/8EAUFBRAEAV26dMHo0aPRuXNnPXZHRI0U2OjcxkwpIqK4JoXIlFLL+XzMlCKDSUhIgCRJ0R4GERGdgIgHpR599FE88MADkGUZGRkZUBQFhw4dwj333INZs2Zh6tSpkd4lETWS1uhcFNjonIgozmk3KkJkSskMSpGBJCYm4vjx48jPz0diYmK0h0NERI0U0UbnX3/9Ne677z5Mnz4dhw8fxv79+3HgwAEcOnQI//znP/HPf/4T33zzTSR3SUQnwKdO/y1W9ZTysnyPiCguyUqITCmRmVJERESkj4hmSr388su44YYbMGPGjKDlLVu2xL///W8cOHAAL730Evr37x/J3RJRI3mlqvI9NSjl9jENnogoHoVqdM5MKSIiItJLRDOlfvzxR4wfPz7k4+PHj8eaNWsiuUsiOgFqo3OLSQxodM6LDiKieCRJzJSi2FFRUYFLLrkEDz/8MCoqKqI9HCIiaqSIZkodPHgQ2dnZIR/v3LkzDhw4EMldEtEJCOwfYmGjcyKiuCaFKN8zV86oLHP2PTIQSZLw2WefaV8TEVFsimhQqqKiAlarNeTjFosFHo8nkrskohOgZkqZTQJsCoNSRETxTArZ6Nz/fx8zaYmIiCjCIj773quvvoqkpKRaHystLY307ojoBFRlSolQTP5lHvaUIiKKS2pQShSqB6X8USmJmVJEREQUYRENSnXs2BHz5s2rdx0iMobARueCIAYtIyKi+KJlSpmqBaUqg1SSzExaIiIiiqyIBqUKCgoiuTki0llgo3OT6L8Y8Ui86CAiikfa7HvVMqUqE6XAjwciIiKKtIjOvhdpL730Enr16oWUlBSkpKSgX79+WkNDAFAUBTNmzEC7du3gcDgwcOBAbNq0KYojJootgY3O1dn33OwpRUQUl7TyvRCNzpkpRURERJEWsaDUokWLwl53z549+O677+pdr0OHDnjsscfw888/4+eff8YFF1yASy65RAs8zZ49G08//TTmzJmDn376CZmZmcjLy2PvKqIw+SovMMyiCCtn3yMiimuhG52r5XtNPiQiIiJq5iIWlHrppZdw8skn4/HHH8eWLVtqPF5cXIz8/HyMGzcOZ5xxBo4ePVrvNkeNGoWRI0eie/fu6N69Ox555BEkJSVhzZo1UBQFzz77LKZPn44xY8YgNzcXb7zxBsrLy7Fw4cJI/VpEzZovoH+IminFoBQRUfxRFEVrZG4KGZTi5wMZR2JiIjweDz744AMkJiZGezhERNRIEQtKrVy5Ek8++SS++uor5ObmIiUlBTk5OTj11FPRoUMHpKen4/rrr0d2djY2btyIUaNGNWj7kiRh0aJFcDqd6NevH3bu3IkDBw5g6NCh2jo2mw0DBgzA6tWrI/VrETVrvoBG52qmlJe3womI4o6i+P8BdQSlOPseERERRVhEG51fdNFFuOiii3DkyBGsWrUKBQUFcLlcaNWqFXr37o3evXtDFBsWB9uwYQP69euHiooKJCUl4f3330fPnj21wFObNm2C1m/Tpg127dpV5zbdbjfcbrf2fUlJCQDA6/XC6/Vqy9WvA5eRMfFYNY7H64MsK4AsQRAVyLIMjwxUuD01LkoihccqNvA4xQ4eq9hg9OPklWTIlZlQsiTB660KQMmSD7IsQ5YBj8cDQdDn88EojH6sqAqPVWzgcYodPFaxIVaOU7jjExTF2Le9PB4Pdu/ejePHj2Px4sV49dVXsXLlShw/fhznnnsu9u3bh7Zt22rrT5w4EXv27MHnn38ecpszZszAQw89VGP5woULkZCQoMvvQWQ0igK8u1MEFOCSTjIsJuC9Hf6g8aXZMqymKA+QiIiajEcC3i/wfwb8tYsMkxDeY0TR4vF48OyzzwIApkyZAqvVGt0BERFRkPLycowbNw7FxcVISUkJuZ7hg1LVDRkyBF27dsU999yDrl27Yt26dejdu7f2+CWXXIK0tDS88cYbIbdRW6ZUVlYWDh8+HPRkeb1eLFu2DHl5ebBYLPr8QhQRPFYNJ8kKHvzY3/9t+oiTYLeIePDjLZAVYNrQHKQ49HkeeaxiA49T7OCxig1GP05lbh8e+/wPAMDDF/cIyoby+GT8+9PfAQD3X3gybGZDT958wox+rMjP6XSiRYsWAICioiKkpaVFd0AUEl9TsYPHKjbEynEqKSlBq1at6g1KRbR8rykoigK3243OnTsjMzMTy5Yt04JSHo8HK1euxOOPP17nNmw2G2w2W43lFoul1oMaajkZD49V+CSvpJXTOuxWWEwi7FYzKrwyZMGk+/PIYxUbeJxiB4+Vccmygp2HndhVBuwt9qBbGwdEnUqkG0v0AaIowiSiRsaJyaRonxeiyQSLJeZOHxuFryljCzw2PFaxgccpdvBYxQajH6dwx2bos4p//etfGDFiBLKyslBaWopFixZhxYoV+PzzzyEIAqZMmYJZs2YhJycHOTk5mDVrFhISEjBu3LhoD53I8NSZ94Cq6b+tZhEVXhkeNjsnIoqIjYXFWLxuL7YdKMX+IhE/fvI7cjKTMbZPB+S2T4328DSSOhtrLb0/BcH/T1Gq1iMiIiKKBEMHpQ4ePIjx48dj//79SE1NRa9evfD5558jLy8PADBt2jS4XC7ccsstOHbsGPr27YulS5ciOTk5yiMnMj5JnXlPFLQyDavJfzHi8TEoRUR0ojYWFuP55dtw1OlBmxQbfHYgNcGCDXuLUXjMhUmDcwwTmFKDTWItTcwFQYBJEOBTFMj8eCAiIqII0iUotWLFCgwcOPCEt/Paa6/V+bggCJgxYwZmzJhxwvsiijfeyisLc0DHWjUo5WWmFBHRCZFlBYvX7cVRpwfdMpLgkySUS0CW1YRuGUnYXlSGJesK0bNtiiFK+bRMqRBdzE2iAJ+swMeoFBEREUWQLp0qhw8fjq5du2LmzJnYs2ePHrsgohPkq8yUspiq3gasZmZKERFFQsERJ7YXlaFtqgOCIGB/cQUOlgs4XOaGIAhom+rAtqJSFBxxRnuoAKAFm2rLlAL8QSmA5XtEREQUWboEpfbt24fJkydjyZIl6Ny5M4YNG4Z3330XHo9Hj90RUSOo2VDmgDv0alDKzaAUEdEJKa3wwe2V4bCaAACeyhsB3sr/O6wmuL0ySit8URtjIDUByhwia0sLSsXWpM1ERERkcLoEpVq2bIlJkyZh3bp1+Pnnn3HSSSfh1ltvRdu2bTFp0iT8+uuveuyWiBrAJ1f1lFIxU4qIKDKS7WbYLCJcHgmAv5wv8P8ujwSbRUSy3RjtPdVMKVM9QSk1y5Yo2hISEnDs2DEsWrQICQkJ0R4OERE1ki5BqUCnn346/vnPf+LWW2+F0+nE66+/jjPOOAPnn38+Nm3apPfuiSgESespVfU2oJbycfY9IqITk52eiG4ZSdhf7IKiKJArM4xkRYGiKNhf7EJORjKy0xOjPFI/dXyhglLqDQyZmVJkEIIgIDExEXa7XZuwhYiIYo9uQSmv14v33nsPI0eORKdOnfDFF19gzpw5OHjwIHbu3ImsrCxcdtlleu2eiOqhlpAENrW1VWZKeZkpRUR0QkRRwNg+HdAy0YrtRWVweSUoCuD0SNheVIaWiVaM6dPeEE3Ogars2VBBKbXXlI89pYiIiCiCdMkZv/322/H2228DAP7+979j9uzZyM3N1R5PTEzEY489huzsbD12T0RhUEswgsr3mClFRBQxue1TMWlwDhav24vlWw6iQgbK3RLOyk7HmD7tkds+NdpD1KifCfWV78kMSpFBuN1uTJw4EXv37sXgwYNhsViiPSQiImoEXYJSmzdvxgsvvICxY8fCarXWuk67du3w9ddf67F7IgqDVy3fEzn7HhGRXnLbp6Jn2xR4vD78ts2J83pm4O7hPQyTIaXSyvfqmX2PmVJkFD6fD2+++ab2NRERxSZdglLLly+vf8dmMwYMGKDH7okoDOpdcUtA+Z7WU4pBKSKiiBFFAUk2C5ItQIrDYriAFFB/+Z42+x6DUkRERBRBuk75snnzZuzevRsejydo+cUXX6znbokoDL5aGp2rPaVYvkdEFFneyvdVr0HfX9WyvMA+g4HMDEoRERGRDnQJSu3YsQOXXnopNmzYAEEQoFSmhKszY0iSpMduiagBausfYqkMSrmZKUVEFFFGD0qpwSaxnvI9ibPvERERUQTpMvve5MmT0blzZxw8eBAJCQnYtGkTvvnmG5x55plYsWKFHrskogZSM6UCy/fURudGvWgiIopFiqLAU3kjQJ351GjUoJSZ5XtERETUhHTJlPr+++/x1VdfoXXr1hBFEaIo4rzzzsOjjz6KSZMmYf369XrslogawKvNvldL+R4zpYiIIiYwEGXU91e1p1SofldqBhWDUkRERBRJumRKSZKEpKQkAECrVq2wb98+AECnTp2wdetWPXZJRA1UW6Nzzr5HRBR5gdmnRs1EVcvyQmVKsacUERER6UGXTKnc3Fz89ttv6NKlC/r27YvZs2fDarVi7ty56NKlix67JKIG0hqdB2RKabPvGfSiiYgoFgUGojySAkVRtD6bRiHV0mcwkMigFBlMQkICCgsL8eWXXyIhISHawyEiokbSJSh13333wel0AgBmzpyJiy66COeffz7S09Pxzjvv6LFLImogrdE5M6WIiHRVPdDvk5WgLFUjUDOlQgWlmClFRiMIAlq3bo3U1FTDBXmJiCh8ugSlhg0bpn3dpUsXbN68GUePHkWLFi34oUFkEFqj84BMKS0oJcmGvJNPRBSLqjc39/hkLTPVKNjonIiIiKJBl6BUbVq2bNlUuyKiMGiNzmuZfU9RjHknn4goFnmrZZ8asa+U1ug8xM0INSjlY1CKDMLtdmPKlCnYtWsXBg8eDIvFEu0hERFRI0QsKDVmzJiw112yZEmkdktEjaTe7bbUEpQCALcB7+QTEcWi6uV7RuzbJ8s1b1QEMlUGq2SFQSkyBp/Ph5dffln7moiIYlPEglKpqamR2hQRNQH1Tn1go3NRFGAxCfBKiv/Ovi1aoyMiaj6q9+mrXs5nBGoGlEms/WYEM6WIiIhIDxELSs2fPz9SmyKiJlB1ARJ8V9xqEuGVJEPeySciikXVy/WMOJmEmillqqd8T2ZQioiIiCJIt9ocn8+HL7/8Eq+88gpKS0sBAPv27UNZWZleuySiBqgq3wt+G+AMfEREkVU9M8rIPaVCzb7HTCkiIiLSgy6Nznft2oXhw4dj9+7dcLvdyMvLQ3JyMmbPno2Kigqt/puIokcr36vWP0QNUrkZlCIiiohYyJSSKmdkDRWUUku9mSlFREREkaRLptTkyZNx5pln4tixY3A4HNrySy+9FMuXL9djl0TUQL7KO/cWsfZMKSPeySciikXVy6GN+P4qaZlStT+uflQwU4qIiIgiSZdMqVWrVuG7776D1WoNWt6pUycUFhbqsUsiaiCvXHumlI3le0REEeVtDo3OK3tNSZx9j4iIiCJIl6CULMuQJKnG8r179yI5OVmPXRJRA6mZUubqjc7VoJQB7+QTEcWiWOgpJSu1fyao1BsYkgHHTvHJ4XDgjz/+wNdffx1UmUFERLFFl/K9vLw8PPvss9r3giCgrKwMDz74IEaOHKnHLomogdRSDXP1RucmZkoREUVSjZ5SBgzsqEMSQ8y+J2qZUk01IqK6iaKI7OxstGnTBmKIDD8iIjI+XTKlnnnmGQwaNAg9e/ZERUUFxo0bh23btqFVq1Z4++239dglETVQfY3OGZQiIoqMGj2lDPj+KoUo6Vapjc7V9YiIiIgiQZegVLt27fDLL7/g7bffxrp16yDLMq6//npcddVVTK8lMgBZVqD2qg3V6NyId/KJiGKRdhOg8u3WiO+vak+pUJlS6qx8Bhw6xSmPx4N7770XO3bswJAhQ2CxWKI9JCIiagRdglKAv877uuuuw3XXXafXLoiokbwBd7qr3xW3stE5EVFEqZlRNlPl9waM7Mhy3T2lqoJSxhs7xSev14unn35a+5qIiGKTLkGpr776CkuWLEFBQQEEQUCXLl0wduxY9O/fX4/dEVED+QKagoRsdM6gFBFRRKiNzm0m//+9PuM1ZqqafS9UUMr/fwPG04iIiCiGRbwr4M0334whQ4bg7bffxpEjR3Do0CH83//9HwYNGoTbb7890rsjokYInHlPqFaqoTU655UHEVFEqO+nNgOX70lKfUEp9pQiIiKiyItoUOr999/H/Pnz8frrr+Pw4cP4/vvvsWbNGhw6dAjz5s3D3Llz8dFHH0Vyl0TUCGr5Xm0XH7bKTCkjlpcQEcUiNfPUbuDyPUmqp3xPm33PeFleREREFLsiGpSaP38+7rzzTkyYMCEo+0IURVx33XWYMmUKXnvttUjukogaQaos07DUMsuSOvue22u8iyYiolikBqGsBg5KaY3OQwWlKj8v1PWIiIiIIiGiQal169bh0ksvDfn42LFjsXbt2kjukogaQb0gMok13wI4+x4RUWSp77lVjc6NF9iRlbozpdTlMoNSREREFEERDUodPnwY7du3D/l4+/btceTIkUjukogaQe0pVVumFBudExFFltboXPT/34jvr/U1OhcFZkoRERFR5EV09j2PxwOr1Rp6Z2YzPB5PJHdJRI3gq+wpZa4tU4qNzomIIkZRlKpG55WZUkZ7f5VlBWqrqNCNzpkpRcbicDiwfv16fPvtt3A4HNEeDhERNVJEg1IAcP/99yMhIaHWx8rLyyO9OyJqBPWuvZmZUkREuvIFBHy08j2Dvb8GNi+vLyjFTCkyClEUccopp2DXrl0Qa7nJRkREsSGiQan+/ftj69at9a5DRNFVV6NzNVPKiI14iYhiTeB7qVWsucwIpIBAk0moJ1NK8Wd/CSHWIyIiImqIiAalVqxYEcnNEZFOwml07pUUyLISciYmIiKqn9dX1UDcqgBQAI+kGCqwE5j9FCpTKrABuiQrtWbaEjUlj8eDhx9+GNu2bcOQIUNgsViiPSQiImoE5roSxSFfXZlS5qq3BaP1PSEiijXq+6jFJMAUcNZlpDI4NVNKFBAyUBYYrDLS2Cl+eb1ezJw5E++88w68Xm+0h0NERI3EoBRRHFIzpWprdG4WBajXJG6D9T0hIoo1Xi0oJSLwPoCR+vapQSlzHZmxgWV9ssKgFBEREUUGg1JEcchXR6NzQRDYV4qIKEICg1KiUBX4MdL7qxqUqq2kWyUG3LCQmClFREREEcKgFFEcqqvROcAZ+IiIIsUbUL4X+H8jlUermU+mes4K1WwpBqWIiIgoUnQJSu3evRtKLandiqJg9+7deuySiBqgrkbnAGBjUIqIKCI8PvUmgBj0f69knMCOL4xMKf/jQtD6RERERCdKl6BU586dcejQoRrLjx49is6dO+uxSyJqAC1TKkT/EPWiyUh38omIYpF6E0DNQNXeXw0U9JekMDOlKj8zZAaliIiIKEJ0CUqFmua4rKwMdrtdj10SUQN41aa2Ia5AWL5HRBQZocr3DNVTSgkvU8rMTCkiIiKKMHMkN3bnnXcC8DdKvv/++5GQkKA9JkkSfvjhB5x++umR3CURNYJPnX0vVE8pZkoREUWEJ6DROWDMoL8kqzOyhp59D6jKlGJPKTICu92O1atX47vvvuNNbyKiGBbRoNT69esB+DOlNmzYAKvVqj1mtVpx2mmnYerUqZHcJRE1gjr7niXEXXEjXjQREcUitXdUVaaU8WY3VYdiYlCKYojJZMKZZ56JoqIimEymaA+HiIgaKaJBqa+//hoAMGHCBLzwwgtITk6O5OaJKEK8stronLPvERHpSX0f1TKltPI94wR2fPV8JqhEdfa9WiazISIiImqMiPeU8vl8+L//+z/s2rUr0psmogjRGp3XV77HoBQR0QnxVivfM2amVGVPqVr6gQYyM1OKDMTj8eCpp57C+++/D4/HE+3hEBFRI0U8KGU2m9GpUydIkhTpTRNRhKh36OtrdG6kiyYiolgUcvY9A72/akGp+jKlGJQiA/F6vbj33nvxxhtvwOv1Rns4RETUSLrMvnfffffh3nvvxdGjR/XYPBGdIK3ReajyPQNeNBERxaKq8r1qs+8ZKBNV0mZkZaYUERERNa2I9pRSPf/889i+fTvatWuHTp06ITExMejxdevW6bFbIgqTTyvfqztTym2giyYiolikZqZaTcbPlBLrKd9jo3MiIiKKNF2CUqNHj9Zjs0QUIWo5SahSDQt7ShERRUSNnlIGLI8Ot3xPfdzHoBQRERFFiC5BqQcffFCPzRJRhNTX6NxmMd5FExFRLKoKSvnfb9WMKa/POIEdXwODUjJn3yMiIqII0SUopVq7di22bNkCQRDQs2dP9O7dW8/dEVGY6m10bmL5HhFRJLh91Wff8wd2DFW+p4Q3+56WKSUxKEVERESRoUtQqqioCFdeeSVWrFiBtLQ0KIqC4uJiDBo0CIsWLULr1q312C0RhUltdG4J1ehcLS9hUIqI6IRUL9/TMqWMFJSSwmt0rgatmClFREREkaLL7Hu33347SkpKsGnTJhw9ehTHjh3Dxo0bUVJSgkmTJumxSyJqgPpKNTj7HhFRZFQv37MYMSilsKcUxR673Y5ly5bh4Ycfht1uj/ZwiIiokXTJlPr888/x5ZdfokePHtqynj174j//+Q+GDh2qxy6JqAHUi6GQ5XtmNjonIooEtVxay5QyC0HLjUCWwyvfUzOpZAalyABMJhMGDBgAp9MJk8kU7eEQEVEj6ZIpJcsyLBZLjeUWiwWyzItcomiSZQXq9USoRucW9pQiIooINbhvrZYpZaSgf7iNzkWBmVJEREQUWboEpS644AJMnjwZ+/bt05YVFhbijjvuwODBg/XYJRGFyRsQGA5ZvhcwZbnC3iFERI1WvaeUxYDl0VIDZ9+TGJQiA/B6vXjppZeQn58Pr9cb7eEQEVEj6RKUmjNnDkpLS5GdnY2uXbuiW7du6Ny5M0pLS/HCCy/osUsiClPgxYRFrP0twFYZlJIV3hEnImosnyQHZKYGz75npIkkwg1KmRmUIgPxeDyYPHky5s6dC4/HE+3hEBFRI+nSUyorKwvr1q3DsmXL8Pvvv0NRFPTs2RNDhgzRY3dE1ABqHxNRAMR6Gp3715e1iykiIgpfYN8oNQPVkI3OK4NM5hA3KlRq+Z7EDFoiIiKKEF2CUqq8vDzk5eXpuQsiaiBftVKS2oiiALMowCcr8PhkJFjr3qYsKyg44kRphQ/JdjOy0xNDBryIiOKFWqInClVZSFXlewoURYFQT3PxpqAGmeqJSWmNziX2ByUiIqII0S0otXz5cjzzzDPYsmULBEHAySefjClTpjBbiijKfNod8bovhKxmET6PVG8z3o2FxVi8bi+2F5XB7ZVhs4jolpGEsX06ILd9asTGTUQUa6r3kwKqGp77H1e02fiiyRdmppSp8nEDJXkRERFRjNOtp9Tw4cORnJyMyZMnY9KkSUhJScHIkSMxZ84cPXZJRGFSL5LM9ZTkhTMD38bCYjy/fBs27C1GmsOK7FaJSHNYsWGvf/nGwuLIDZyIKMao77dq6R4QHKAySgmfVDmO+iq1TQIzpYiIiCiydMmUevTRR/HMM8/gtttu05ZNmjQJ5557Lh555JGg5UTUtNTeIRZT3Xfnbea6+57IsoLF6/biqNODbhlJWglKkt2MbrYkbC8qw5J1hejZNoWlfEQUl7y+mu+3geXRhglKVbaIMtXXU6ryYYMMm4iIiJoBXTKlSkpKMHz48BrLhw4dipKSEj12SURhUhvv1jfLknpnP1SmVMERJ7YXlaFtqgOCIKDE5cWGvcdRWuGFIAhom+rAtqJSFBxxRvYXICKKEZ4QPfyq+koZI7qjZj7VV9Zt1sr3jDFuIiIiin26BKUuvvhivP/++zWWf/jhhxg1apQeuySiMPnk+hudA1Uz8IW6k19a4YPbK8NhNQEAjjjdcHllHCv3T8vssJrg9soorfBFauhERDGltp5SAGCp7CNVX8++pqK+zYv1NF03aZlSnH2Pos9ms+GDDz7AfffdB5vNFu3hEBFRI+lSvtejRw888sgjWLFiBfr16wcAWLNmDb777jvcddddeP7557V1J02apMcQiCgEnxR+o3Mg9EVTst0Mm0WEyyMhyW7W1lMvVlweCTaLiGS7rpN8EhEZlhqUspmDg1JVQX9jBHe0TKl6yrrV8j4fg1JkAGazGSNHjtS+JiKi2KTLO/hrr72GFi1aYPPmzdi8ebO2PC0tDa+99pr2vSAIDEoRNTFtlqX6MqXqCUplpyeiW0YSNuwtRjdbklaGIsn+ac73F7vQq0MastMTIzh6IqLYESpTqr5M1Kamfi7Ulyml3syQFQaliIiIKDJ0CUrt3LlTj80SUQT4tIukui8+tNn3Qlw0iaKAsX06oPCYC9uLylBW4YMgCCj3+LC9qAwtE60Y06c9m5wTUdzyaI3Oq5fv1R30b2qyHF6vQTVoxUwpMgKv14v//ve/+PXXX5GXlweLxRLtIRERUSPo0lNK5fF4sHXrVvh8jesp8+ijj+Kss85CcnIyMjIyMHr0aGzdujVoHUVRMGPGDLRr1w4OhwMDBw7Epk2bIjF8omapoY3O67poym2fikmDc9CzXQoqvDLKKnxwuiX06pCGSYNzkNs+NXIDJyKKMd4QNwEsBs2Uqq+sW/3ckBmUIgPweDy44YYb8MILL8Dj8UR7OERE1Ei6BKXKy8tx/fXXIyEhAaeccgp2794NwN8/6rHHHgt7OytXrsStt96KNWvWYNmyZfD5fBg6dCiczqrZvGbPno2nn34ac+bMwU8//YTMzEzk5eWhtLQ04r8XUXOg9nyy1DP1d7jlJbntU3HLwK44o1ML9O6Yhv7dW+O+C3swIEVEcU8N6ltr9JTyB3cM01NKCe9mhfo4M6WIiIgoUnQJSt1777349ddfsWLFCtjtdm35kCFD8M4774S9nc8//xwTJkzAKaecgtNOOw3z58/H7t27sXbtWgD+LKlnn30W06dPx5gxY5Cbm4s33ngD5eXlWLhwYcR/L6LmwBtmQ1tbA8pLSip8SHFYkJ5kg8NqYskeERHqmH3PYJlS4ZbvMVOKiIiIIk2XnlIffPAB3nnnHfzlL3+BENA0s2fPnvjzzz8bvd3i4mIAQMuWLQH4e1cdOHAAQ4cO1dax2WwYMGAAVq9ejZtuuqnW7bjdbrjdbu37kpISAP7adK/Xqy1Xvw5cRsbEYxU+t9sLWZYhKHKdz5cIGbIsw+X21vu8Hil1Qa4MdpW7fXWuz2MVG3icYgePlXG5PP73WxFy0HESoVS+v3oMcdw8PgmyLEOR6n7/VmQfZFmGxycZYtx64WsqNlQ/Z+fxMi6+pmIHj1VsiJXjFO74dAlKHTp0CBkZGTWWO53OoCBVQyiKgjvvvBPnnXcecnNzAQAHDhwAALRp0yZo3TZt2mDXrl0ht/Xoo4/ioYceqrF86dKlSEhIqLF82bJljRozNT0eq/r9ckTAnuMCEkp2Qdy7PuR6f5YAew6JkI4oSCr6rc5tbjwqYM+xqtf2J5/uQH3JUjxWsYHHKXbwWBnP2iIBe0oF/OLcBfcOf3bRsmXLsOmwgD3FAr4v3QXn9uhnHe3YIUJSgK+WFyCxjl7Rx9zAnr0iDpuBfO+2phtglPA1ZWwVFRXa11999VVQdQYZE19TxiYrwOEKwCUBb320DK3sqPd8nqLL6K+p8vLysNbTJSh11lln4dNPP8Xtt98OAFogat68eejXr1+jtnnbbbfht99+w6pVq2o8Vj3QpShKncGve++9F3feeaf2fUlJCbKysjB06FCkpKRoy71eL5YtW8YZPWIAj1X45N/2o3znMZzdvRWG9KgZPFb9trcYB9cWomvrRIw8p1Od23Sv34eS3ce17wfnnQSH1VTrujxWsYHHKXbwWBlX6c974SsswbmnZuKMrGTtOJn+OIqK7UfQq0tLjDw1M9rDxJqPNkNWgOHDcpBsD/03dLCkAlu+3oFEqwkjR5zUhCNsWnxNxYbAHrMXXHAB0tLSojcYqhNfU8a3aV8J3v9lH7aVlOLgoSNo0zodOY5kXHp6O5zSLqX+DVCTipXXlFqRVh9dglKPPvoohg8fjs2bN8Pn8+G5557Dpk2b8P3332PlypUN3t7tt9+Ojz76CN988w06dOigLc/M9J/IHThwAG3bttWWFxUV1cieCmSz2WCz2Wost1gstR7UUMvJeHiswiCKEEURdmvdz5XDZoUoivDKqPc5LfXIEAMap8uCWO/P8FjFBh6n2MFjZTwyBIiiCIet6thYLBYk2C0QRRGyIET9mMmyAggiRAGw26ywWEKfGtqs/vd6xQDjbgp8TRlb4LHhsYoNPE7GtLGwGC+u3ImjTg/apNgglwItEm3YtK8U+4t3ckZtAzP6ayrcsenS6Pycc87Bd999h/LycnTt2hVLly5FmzZt8P333+OMM84IezuKouC2227DkiVL8NVXX6Fz585Bj3fu3BmZmZlBaWsejwcrV67EOeecE7Hfh6g5UWd7qq/RuTpbVDiNeItdwfXC7jCaoxMRNXfqRBEhG537ol+6p868BwBiPS0WzJV1HBIbnZMB2Gw2LFy4EHfffXetN5uJqH6yrGDxur046vSgW0YSEqwmCAKQZDOjW0YSjjo9WLKukBNckK50yZQCgFNPPRVvvPFGjeXvvfce/vrXv4a1jVtvvRULFy7Ehx9+iOTkZK2HVGpqKhwOBwRBwJQpUzBr1izk5OQgJycHs2bNQkJCAsaNGxfR34eoufCpQSmx7ph0uLPvKYqCksqglCj469ErvFIERkpEFNvUmwChglIeA8y+FxhgMtfTPERkUIoMxGw2469//SsSEhJgNut2SUPUrBUccWJ7URnapjogKwp+21sMdznQEf4WOW1THdhWVIqCI050aZ0U7eFSMxXxTCmfz4dNmzbhjz/+CFr+4Ycf4rTTTsNVV10V9rZeeuklFBcXY+DAgWjbtq3275133tHWmTZtGqZMmYJbbrkFZ555JgoLC7F06VIkJydH7Hciak58snrnPrxMqfqCUhVeWcuMSk+yacuIiOKdmmlqNQe/32qZUgYLSpnqCUqpQStZAe+aExE1A6UVPri9MhxWEyq8MrySggqp6rPAYTXB7ZVRWuGL4iipuYtoUGrz5s3o3r07evXqhR49emDMmDE4ePAgBgwYgGuuuQZ5eXnYvn172NtTFKXWfxMmTNDWEQQBM2bMwP79+1FRUYGVK1dqs/MRUU3qnfv6Lj7CvZOvlu4lWE1IsfvvVDJTioioKuhUPVPK1oDyaL35KoNLolBz4pjqAj83Asv+iKLB5/Phvffew3fffQefjxfMRI2RbDfDZhHh8kiQKm9cK4r6H8DlkWCziEi2MxuR9BPRoNQ///lPdO7cGR9++CEuv/xyfPDBBzj//PMxePBg7NmzB08++SSysrIiuUsiaiBJrv0iqbqqnlJKnXfE1aBUqsOiXWixpxQRUVVQP2RPKSn6gR31/b2+0j2gWlCKmVIUZW63G+PGjcMTTzwBt9sd7eEQxaTs9ER0y0jC/mKX1uID8N94UBQF+4tdyMlIRnZ6YhRHSc1dREOeP/74I/Lz89GnTx+cd955eOedd3D33Xdj4sSJkdwNEZ2AcDOlrAEXUR5Jhl001bqeGpRKS7DAZvGvw0wpIqKqRuY1g1L+918jBPDVTClTPX0GAcAkMChFRNSciKKAsX06oPCYC7uOlsMryVAUoMTlxdFyF1omWjGmT3utpyCRHiKaKVVUVIT27dsDANLS0pCQkIABAwZEchdEdIJ8WuPd+sr3BKjXH3WVmBwv9wAAUuwW2BmUIiLSaD2lQmZKRT8oJStqUKr+dUWx6nOB5XtERM1DbvtUTBqcg07pCfBIMipk4Fi5F706pGHS4Bzktk+N9hCpmYtoppQgCBAD7rSJogiLxRLJXRDRCVIbndc3+54gCLCaRLh9cp3NzrXyvQSLtp4R7v4TEUWTLCtaFpLFLACoCuJo5dEGeK/UekqFeRfcLArwSgokA5QeEhFRZOS2T8XYPh1gEoA9hftxy8AuGHBSJjOkqElENCilKAq6d++uNcosKytD7969gwJVAHD06NFI7paIGkAt3zPXkykF+C+c3D65zmbngT2l1Jk5GJQiongX+L5pNYlQ5KoMUiNlSqnBpXB6SgGAKPgDbMyUIiJqXjySjGS7BckWoFWSjQEpajIRDUrNnz8/kpsjIh2E2+jcv47/w6iuTKkStaeUw6Ld9Wf5HhHFOzXgJAj+Hn6Bb6Pae6vkbyRb36x3elKDS6Ywx2AWBbjBnlJERM1NhVcO+Jrn8tR0IhqUuuaaayK5OSLSQbiNzgHAZjYB8Ia8m68oCo5XBqVSHBaUVGZK8YOMiOKd+l5rNYk1gk6BNwW8kgKrOYpBqQY0OgcAU2VAjUEpIqLmxRVw/s6qB2pKEQ1KEZHxqT2lLGFcgKgXToF3TgK5vJJ24ZXqsOBwmX9KZn6QEVG8U4P5tU0qYQ0KSslaj6loUINL4ZR0A1UZVQxKUbRZrVa8+uqr+PXXX2G1WqM9HKKY5w4ISvEGMzWl6J0FEVGTk2UFatJTuD2lgNB9T46X+7OkkmwmWExiZWZV8IcaEVE8UsueayuVFkVB6+EU7b5SanBJDLN8T82yZVCKos1iseDqq6/G4MGDObESUQRUBAWleIOZmg6DUkRxxBdwEdGQoFSonlKBTc4BwG6pzKxiphQRxTmPVHf/PnV5XT37moKWKRVmQ1s1KOVjUIqIqFkJ6inFc3lqQgxKEcURtXQPCK98z6ZeNIW4k18jKFWZKcWUXyKKd2oGVKjSPItZbXYe3RN/9XMh3FmW1PI9mbPvUZT5fD7k5+fj559/hs/ni/ZwiGJe4Pk7qx6oKbGnFFEcUfs/iUJ4FyDaRVM9mVIplUEpm0Ut91MgyUpYzdSJiJojr6+q0Xlt1KC/+r4cLWpwKexMqcosW1+Ux03kdrsxevRoAMBdd90Fh8MR3QERxTBFUVDhCyjfY6YUNSFdglKSJGHBggVYvnw5ioqKIMvBf9RfffWVHrslonqoZRqhykmqs5r8mU+hep4UV/aUSkvwNxhVM6UAwO2TkGBl3JuI4pOnjkbn/uV19+xrKr4GzMgKVAWvmClFRNR8+AL6zgKseqCmpcsV4+TJk7FgwQJceOGFyM3NrTEVMhFFh6/y0ybciw+17CTUbHrVy/dEUYDVJMAjKajwykjgZDhEFKe02fdClu8ZpKeU0rCglNoQnT2liIiaj+pBKDcbnVMT0iUotWjRIrz77rsYOXKkHpsnokbyNXDq74Y2OgcAm8UEj+SD28c7LEQUv7xhNjqPdqaUmkEbblCKs+8RRZcsKyg44kRphQ/JdjOy0xPD7glHFEr12fYqeB5PTUiXoJTVakW3bt302DQRnQC1TCOcJudAVS+U2hrxKopSa1DKbhZRCk4lS0TxTQ3mh+opZa28ORDtnlLqzQpTmFntZgaliKJmY2ExFq/bi+1FZXB7ZdgsIrplJGFsnw7IbZ8a7eFRDKueKcXzeGpKusy+d9ddd+G5556Dwn4DRIbirezvFn6mVOhG506PBJ+sQBCAFHtVfNtm4Qx8RESxkiklNzCDVmRQiigqNhYW4/nl27BhbzHSHFZkt0pEmsOKDXv9yzcWFkd7iBTD1PP25MpzerdP1j4fiPSmS6bUqlWr8PXXX+Ozzz7DKaecAovFEvT4kiVL9NgtEdVDy5SKQKNzNUsqyWaGOWB7tnr6UBERxQOP9n5bd6Pz2jJRm5KvgeV7zJQianqyrGDxur046vSgW0aS1q83yW5GN1sStheVYcm6QvRsm8JSPmoUNTMqNeBGs9snw2E1hfoRoojRJSiVlpaGSy+9VI9NE9EJ8Da20XktKbzqzHuBpXsAYGemFBERvL7YaHQuN7B8z1RZ/i0xG56izGq14rnnnsOmTZtgtTbvmVUKjjixvagMbVMdcPtk/H6gBG1THWiTYocgCGib6sC2olIUHHGiS+ukaA+XYpDaQyrRZoZ6L6XCKzEoRU1Cl6DU/Pnz9dgsEZ0g9c62uYFBqdoypY67PABCB6WYKUVE8Ux93wzdU8oY5XtqplS42RXqryPJfI+n6LJYLPjHP/6B/Pz8GlUZzU1phQ9urwxHqglHnW54fAqOOj1ok2IHADisJhwskVFa4YvySClWqTeT7RYRlsr3eTY7p6aiS08pIjImn1x3j5PqtEypWi6aSmppcg74P8wAZkoRUXyrr6eU2rMv2kGpht6sEAW1fE+3IRFRNcl2M2wWES6PpLVi8AUEhl0eCTaLqPUDImootXzPbjFVBaXY7JyaiG7vXO+99x7effdd7N69Gx6PJ+ixdevW6bVbIqqDOstT2I3OTaHLS2qbeQ8AbGaW7xERhdtTyuuLbhmc1MBMKbNavsdMKYoySZKwcuVKbNiwAcOGDWvW2VLZ6YnolpGEDXuLtd6d6mtXURTsL3ahV4c0ZKcnRnOYFMO0TCmzCRaTErSMSG+6ZEo9//zzuPbaa5GRkYH169fj7LPPRnp6Onbs2IERI0bosUsiCoPW6FwMt9F5/UGptITqQSk2OiciCnf2vWg3Old7Q4WbKVVVvqfXiIjCU1FRgby8PNx///2oqKiI9nB0JYoCxvbpgJaJVuw7XgGvJMPjk1FW4cP2ojK0TLRiTJ/2bHJOjVZr+R6DUtREdAlKvfjii5g7dy7mzJkDq9WKadOmYdmyZZg0aRKKizldKVG0eOXGNTqXFcBX7QrkeD2Nzt38ICOiOKY2OreFaHReV8++piQ1cPY9tdG5j5lSRE0qt30qJg3OQWaqHR6fjBKXD8fKPejVIQ2TBucgt31qtIdIMaxC/cwKCkrxfZ6ahi7le7t378Y555wDAHA4HCgtLQUAjB8/Hn/5y18wZ84cPXZLRPWQGlq+F3Ax5ZFkmCtvkSuKgpKK+npK8YOMiOJXvT2lDNLoXGrg7HtqRpXM2feImlxu+1QMPKkVWiZa4ZVk3HZBN+S2S2WGFJ0wd2D5ngj4wEbn1HR0yZTKzMzEkSNHAACdOnXCmjVrAAA7d+6EwpMYoqhpaKNzkyhopRqBfU/K3D5IMiAIQIq99p5Sbn6QEVEc03pKhciU0npKScboKRXuzQr14tcX5XETxSuXV0aKw4L0JBsyU+wMSFFE1Fa+x6oHaiq6BKUuuOACfPzxxwCA66+/HnfccQfy8vJwxRVX4NJLL9Vjl0QUBvXiJ9wyDQCwmiqDTFLVB5NaupdsN9c4GWKmFBFRYKZUqEbn/uXR7r/nUxudh5kppWZUMVOKKDpcAYGCcg+DBhQZ6t+VjbPvURToUr43d+5cyJUZGTfffDNatmyJVatWYdSoUbj55pv12CURhaEqU6oBQSmzCJdXCmp2HmrmPSCgpxQzpYgojqlBKWs9jc6jXb4nq5lSYU6Aod7UUINZRNR0FEVBuZtBKYo8NQBlN7PROTU9XYJSoihCDDi5ufzyy3H55ZfrsSsiagA1Uyrciw8AsFYGsMIOSlWW7/HuChHFK1lWtPfbkD2l1EbnBsmUCr/ReWWmFINSRE3OKylBAWEXgwYUAYqiBJTvmWAV/X9jDEpRU9GlfA8Avv32W/z9739Hv379UFhYCAB48803sWrVKr12SUT1aGjvEMCfxgsE9z0pqQxKpTmstayvzsyk1Jixj4goHngDZqaz1ttTKsqZUkrjglLMlKJos1gsePTRR3HNNdfAYql5k6w5clXLjKr+PVFjeCUF6lt6UKZUlG+aUPzQJSi1ePFiDBs2DA6HA+vXr4fb7QYAlJaWYtasWXrskojCoAaJGpIpVdX3JKCnVB2ZUoGlKvwwI6J4FBjEN4cI9qjvrR5JieokML4G9hpUfx+JQSmKMqvVirvuuguXXnoprNaaN8mao3KvL+h7ZkpRJKiz7AmC/0YKy/eoqekSlJo5cyZefvllzJs3L+jOxTnnnIN169bpsUsiCoNWvteQnlK13M2vq3xPFAXYzGqzc36YEVH8UUvyrCYBQogG4oFlfdGcgU+qzOpqaKYUg1JETa96ZlS5xxdiTaLwaaV7ZhMEQWCjc2pyugSltm7div79+9dYnpKSguPHj+uxSyIKg9bovCE9pcxq4/KqDyZ19r3aglJAVQlftGeVIiKKhqqZ90K/11qDglLRe6+UFLXXYHhBKXWWPomz71GUSZKEn3/+Gdu2bYMkxcdNsOqNzVm+R5HgVpucV56/M1OKmpouQam2bdti+/btNZavWrUKXbp00WOXRBSGRmVKVWY9qY3OZVlBaUVlUCqh9qCU2uzczQ8zIopDHjUoFaKfFODPKlUDQdEMSjW00bn6+SFFMbuLCAAqKipwzjnn4O6770ZFRUW0h9MkagSleJ5FERDY5ByoCkq5fTIntaAmoUtQ6qabbsLkyZPxww8/QBAE7Nu3D2+99RamTp2KW265RY9dElEY1HILSwOCUpZqs++Vun2QFUAUgGRb7RN4qh9qTPslonikvl/WlSkV+LgnilmlcgODUsyUIooeNQjlqDzPqh6kImqMihCZUgCrHqhp1H5FeYKmTZuG4uJiDBo0CBUVFejfvz9sNhumTp2K2267TY9dElEY1EbnpgaU76n9odQsq+LK0r1kuwViiIsYraeUjydLRBR/1PdLWx2ZUgBgMQtweasyq6JBzZQSQ/S+qo6Nzomix1XZQyo9yYq9x1wsr6KIcFXLlDIJ/pvSkuLPonJYTdEcHsUBXYJSAPDII49g+vTp2Lx5M2RZRs+ePZGUlKTX7ogoDF65Yb1DgIDyvcp+DSWVpXtpIUr3gMBMKZ4sEVH8qeopVfd7rc0UHPSPBqmBnwtsdE4UPWpmVHqiPyjFTCmKhMBG5yqbWUS5V+ENZmoSugWlACAhIQFnnnmmnrsgogbwhdF8tzqryf8BpZaX1NfkHKjKDmDKLxHFI0+Y77WWWmY3bWpqcClU5mt1DEoRRY8ahGqZaAXgz3BRFCXkLJ9E4VCDUraAuj27xYRyr4+tOKhJRDQodd1114W13uuvvx7J3RJRmCLR6LzYVZkpVUdQSs2UYqNzIopH3nB7Spmj21NKURSosaWGZkr5GJQianLqbHvpSf6glKL4bwCq511EjVHhU3tKVf0d2dVWHDyXpyYQ0aDUggUL0KlTJ/Tu3RsKG2ASGY7W6LwBPaXU8hM16+m4ywMASKkzKKV+kPHuChHFH/UGgNXgmVKB2U7hNjpnphRR9KiZUil2CywmAV5JQblHYlCKTkj12fcAwMZWHNSEIhqUuvnmm7Fo0SLs2LED1113Hf7+97+jZcuWkdwFETWSoihVU383IlNKvcgqcfmbbNZdvleZKcU6dCKKQ1pPKXPd77XWyvfiaPWU8jUmKFVZJiTz5iNFmcViwX333Ydt27bBYgl9TtKclHv952AOqwkOqwlel09rUk3UWG6tp1Rg+R5vMFPTCT9dIgwvvvgi9u/fj3vuuQcff/wxsrKycPnll+OLL75g5hRRlAVefDSk0bmtWnmJmilVV1BK/SBjTykiikex0lMqMLBkCrMnjXpTg+V7FG1WqxUPPPAA/va3v8FqtUZ7OE1CLd9LsJrhqMxkUWfkI2osNfAUXL5XmSnFG8zUBCIalAIAm82Gv/3tb1i2bBk2b96MU045Bbfccgs6deqEsrKySO+OiMLkC7gT36hG55IEWVZQWuE/+eHse0REtfM2MCgVrZ5SamBJFMJvdK7e1FAUQGZgiqjJeCVZy6pMsJqQYFWDUrwBSCemtvI97QYzz+WpCeg6+54gCBAEwd9IU+YbJjV/sqyg4IgTpRU+JNvNyE5PDPtEX2++ytegIPgvQMKllp94fDJKKrxQFMAkAkm20G8fNjNTfokofqlBqXp7SqmZqNHqKVV5gRtu6R4AiAEZVZKiQIQxPuMo/siyjE2bNmH37t1xcZ2h9pMSBf95lpopVc5MKTpBajaUPWD2vaqeUs3/tUXRF/GglNvtxpIlS/D6669j1apVuOiiizBnzhwMHz4cYgOaKxPFmo2FxVi8bi+2F5XB7ZVhs4jolpGEsX06ILd9arSHp2VKWUShQVMHq/2hvJKizbyXYrfUuQ09M6WMHPgjIgIAr6/y/baeoJQ12o3OlYYHpQLXlWQF7K9M0eJyudC7d28AwPjx42Gz2aI8In2p51QOiwmCIMBh9V/GlTOThU5Q7eV7nH2Pmk5Eg1K33HILFi1ahI4dO+Laa6/FokWLkJ6eHsldEBnSxsJiPL98G446PWib6oAj1QSXR8KGvcUoPObCpME5UQ9MeSvvIpobULoHBM++d7zcH5Sqq3QPqMqUinRPKaMH/oiIgMCeUvU0Ojerjc6jO/teQ/oMBvae4gx8RE3H6fZnRKlle2qmVIWHQQNqPEVRqsr3zIHle2zFQU0nokGpl19+GR07dkTnzp2xcuVKrFy5stb1lixZEsndEkWVLCtYvG4vjjo96JaRpGUQJdnN6GZLwvaiMixZV4iebVOimtGjZkqZGzDzHlA1+x4AHC5zA6i7yTkQPI2soigNyswKJRYCf0REQODse2E2OvdFJ7ijBpUa8tkkigJEAZAVNjsnakpq+Z6aIaUGp8oZlKIT4JFkqG/lNosIwP/5pbXi4KRF1AQiGpS6+uqrI3LxSRRLCo44sb2oDG1THRAEATsOlUGSFeS08Qeo2qY6sK2oFAVHnOjSOilq49SCUg0MjAX2RDlUGl5QSq1JlxV/2Z+1nmnR61M98AcACowX+CMiAqoal9fbU8oU5Z5SjciUAvwlfLKksNE5URNSM1a0TCm10TkzWegEqKV7QmWvMp8vuJSPmVLUFCIalFqwYEEkN0cUE0orfHB7ZThSTZBkGYfLPAAAj88fjHFYTThYImuz1kWL2ujc3MDeboIgwGoS4JEULSiVUk9QymoSIQj+2ZncPiko26oxggN/wKbCEnhlBad1SDVU4I+ICAhodF7Pe5/6eLTK99RMJ1MDbyiaRAFeSWGmFFETqsqUCi7fczFTik6AO6B0LzC5RL3BzEbn1BTYeZzoBCXbzbBZRLg8ErwBKa7qRYbLI8FmEZFs13Wyy3qpFw/19TipjXrhpJbvpTmsda4vCEJEZ+DTAn9WE2RZgdMjweOTtZ5VDqsJbm/0A39ERADgkWKk0bkalGrgzQo1s0pWGJQiaipqUErNlEpgphRFQFWT8+DPATY6p6bEoBTRCcpOT0S3jCTsL3bB7at64/ZKMhRFwf5iF3IykpGdnhjFUVZd9DS00TlQFZRSL7RS62l0DkQ27Tco8BdwZ95ogT8iIiCgp1Q9NwG08r0o9ezQyvcaeLNCLZNmphRR03F5/Tfe1Awp9TyLPaXoRFRUXrvYq02lqvaHdftklmqT7ngFR3SCRFHA2D4dUHjMhR2Hy+GVZJhEAcUuLw6VutEy0YoxfdpHvddRY3tKATXv9tfXUwqI7Ax8auBvw95iZKbYteWBgb9eHdKiHvgjIgKgZc3W31PK/36sBvybmtbovKHle5Xr80KFosliseDOO+/Ejh07YLHUf14S66qX76mZUsxkoROhzbwXIlMK8J/Lq393RHpgphRRBOS2T8WkwTnIauGAxyejrMKH4y4venVIM8yscFU9pRoelLIFTBFrFgUkhvHBFMlMKTXw1zLRih1HyuCVZMiKghKXD9uLygwT+CMiAgIzpcKcfS/q5XsN+zkzM6XIAKxWKx577DFMmDABVmvdbQWaA5dWvmcO+r/bJ8MXpfcQin1V5XvB5/Zmk6jdOGHgk/TGTCmiCMltn4oRp7aF1WyCV5JxZnYL3HBeF8MESrRMqUaU7wWWoKQ6LGHNsmnXMqUi80GmBv5eXLEd63YdhyQrKLZ48Zcu6RjTp70hAn9ERIqiVPWUCrfReZTK99SbFQ3tKaV+rkkMShE1meo9peyWqkllXF4JyY04vyOqCGh0Xp3dYoJX8mklfkR6YVCKKILK3D5tZjqHxWSYgBRQdUe7cZlSVSc64ZTuAQG16BGctSO3fSrGntEBAgR4JRm9O7bATf2NE/gjIvIGlOKF3VMqSlkOaqPyhs5/YWZQqknIsoKCI06UVviQbDcjOz2Rn3cBZFlGQUEBDh48CFlu/plCWvle5fmVIAiwm01weSV/UMre/EsYKfLUoJTNUjOoaTeLKAVn4CP9MShFFEElLq/2danbWDPBRaLRORBek3MgYCrZCN9dcXmkgMCfyBN0IjKUwFK8cHtKeSUFiqKElYUaSepQTQ38XFAzqxiU0s/GwmIsXrcX24vK4PbKsFlEdMtIwtg+HZgZXMnlcqF79+4AgMsvvxw2my3KI9KXGjxICGih4LCK/qAUm51TI1X4ai/fA6puMLN8j/TGPE+iCCqpqApElVYYKyjl06Yob/hFj7URmVJqGnAkM6UAoMzAzzERUeDMe/UFmQLfW71RaHbe2F6DagyLQSl9bCwsxvPLt2HD3mKkOazIbpWINIcVG/b6l28sLI72EKmJ+SRZmzhG7SUV+DVn4KPGqmp0Xnv5XuA6RHphUIooQiRZQVlAdlRZhQ+KYpwT9qqLj8b0lGpM+Z4+mVJBz7GHQSkiMhZPmE3OAcAiBgalmr48Qq14MjUwQ0udrU8y0GdccyHLChav24ujTg+6ZSQhyW6GSQSS7GZ0y0jCUacHS9YVcubDOFNeGRQQhOBZ0tSggYtBA2okt9ZTqpbyPfVcnuV7pDMGpYgipLTCC0UB1BvOPlkx1EmC1lOqEZlSZlFAicuLI2VulFZ4wzoZVjOlIv1B5nRXPadGC/wREXm1rNT6T7FEUdCylDxRaHZe1ei8YZ8LVT2leKESaQVHnNheVIa2qQ4IgoB9x11Yv/s43F4JgiCgbaoD24pKUXDEGe2hUhNyBfSTCszAVEv5WL5HjRVq9j0g4Fyejc5JZ+wpRRQhJS5/1k6qw4IKrwyXV0JZhS8ozTqatNn3Gnjxofa12LC3BJKs4LjLi9V/Hqm3r4WaKeWOcGDOGZAdJSuA0yMhyWaM55iISA0uWcO8AWAxifDJUlQypdTyu4YGpUxaUCriQ4p7pRU+uL0yHKn+i8FjTg+8koLSCi9sFhMcVhMOlsgsX48z1WfeUzEoRSdKLc1zWEOX70X6XJ6oOmZKEUVISYW/yXmKw4Jku7lymXFOGhvT6Fzta7HrSDmsZhHJdjPSk8Lra2HT7q5E7qpFUapKJNUbhWUGeo6JiLwNKN8DqvpKRWMGvsYHpfxj9jFTKuKS7WbYLKIWZFD/LjyVN5ZcHgk2i6idZ1B80DKlqgUO1KBBOYMG1EhqFpSaFRWI5XvUVBiUIoqQ4sqZ91IDglKlFd66fqRJqeV7ljAvPgL7WnRs6YDFJMIkCkhzWMLqa6FHc8RyjwS1Wq9VohUAUOY2znNMRKRmSllq6c9RG2vADHxNTQ1KNTSDVl2fManIy05PRLeMJOwvdkGRZe2z2yvJUBQF+4tdyMlIRnZ6YpRHSk3J5fXfgEuw1J4pVcFMKWqkqvK92npKsdE5NQ3eZiGKkJLKoFSK3aL1lTJSer2vgZlSgX0tPJL/w8hmFgEIEAQE9bXo0jqpxs/bKi/I3BHMlHJWZkklWE1ITbDiUJnHUM8xEVFDM6XU9aJSvlcZ5RcbGJRS12emVOSJooCxfTqg8JgLW4vK4PHJMIkCSiu82F5UhpaJVozp077Bx6w5MpvNuPnmm7Fr1y6Yzc37kqaqfC/493SomVKc+IUaQVEULeBkq3X2PTVTikEp0lfzfgcnakJqplSKw1xVWuY2zklCQxudB/a1MEsCRAFItlfNvFdfXws97q6oz2eizYxkm5qNZpznmIhIzXgKu6eUWr4XhUbnjc2UUuNtMiea0EVu+1RMGpyD/35fgP3HD0OSFSiKgrNOTseYPu3r7OcYT2w2G55//nnk5+fDZrNFezi6UoNS9mrle2o5n4vlVdQIHkmGWvBQW6aUHq04iGrDoBRRhGg9pewWrcTMUOV7DWx0HtjXIsluRp+OaUF3Zuvra6F+uLl9/pIDoYFTjtdGDUol2UxIqtyvkQJ/RESxlCmlfi40NOtG6ykVhZLDeJHbPhUTzs2G0+1vgt8qyYr7LuzBDKk4pfaUql6+p2ZKuZgpRY2glu6JAmCt5TOL5XvUVNhTiihC1Nn3UoJ6ShnnJMFbWWZhFsN72Qf1tVAUiKK/dA9AWH0t1LsrihK5Er7ATCl1xj02OiciI/E0tNF5NHtKKY3MlKq8ycBMKX053RJSHBakJ9lgEkVE4N5Os6IoCg4dOoTi4mIozfxvUSvfs1XvKeU/F3IxaECNoM6qZzObar15zEbn1FSYKUUUAYqiaJlSqQ6LVhJhpKCUekfbEmZJSWBfC7W3lMNqgssjYX+xq96+FhaTv+RPrgxK2WupVW8op9v/4ZlkM1cF/pgpRUQG4q0MwlvDbHSuBq+iWb7X8Nn31J5SzTsQEG2B2dY+WUGFV6512vZ4VV5ejvbt2wMALr74Ylit1iiPSD9qzyhH9Uwpq9pTSopYVjrFj7qanPuXM1OKmgYzpYgiwOWVtLvcKXYzUgyYKVXVUyr8l73a1+LUDqk47vKg4LATx10e9OqQhkmDc+rsayEIgvZh5o7Qh5lTK98zG3KGQyIir3YDwPjle1pQqoEXsmpmlcSglK6qn0Pw8y5+ueppdC5HMCud4keFr7JXWYgbx9p5vE8OOds2USQwU4ooAtTSvUSrCWaTqPU78ger5LAvTvSkzb7XwDviue1T0bNtCgqOOFFa4UOy3Yzs9MSw+lrYLSLKPVLE0n6Dy/f8TddZvkdERqIGl6zm8N5r1YwqTzSDUo3MlGJQSl8l1T7fSip8yEiJ0mAoqtTyvIRqmXIWkwCzKMAnK3B5pIhkpVP8UDOgqmfgqewBGb9uHzM1ST8MShFFgNbk3OEPlDgsJu0koazChxaJ0U8pb+jse4FEUUCX1kkN/jl/Xykv3L7IZEqVBWRKqYE/p0eCJCsNvqgiItJDQ3tKRbXReSODUiKDUk2iemYUM6Xil9pTqnpQQBAEOKwmlFb44PJKaBGNwVHMqq98z2wSteuZCq/EoBTpJvrpG0TNQIlLnXnPHygRBEELmhilhK9q9r2me9kHzsAXCc6ATKlEqwnqdRRn4CMio2jo7HtqRlU0glJyI4NSLN9rGur5Q6ska9D3FF98kqydR1XPlAKqslzUwBVRuNRMKVsdGXZas/MI3WAmqg2DUkQRUFwZlEpNsGjLqhpxG+POpk9WL5SaLqMo0g0SAzOlAgN/DEoRkVGojc4bnCnli97sew3OlKrsQSU18xnPoklRFK08vV2aAwCDUvFKLd0TBMBurhk8UANVbEZNDaX+zdRV9ll1Ls+eZaQfwwelvvnmG4waNQrt2rWDIAj44IMPgh5XFAUzZsxAu3bt4HA4MHDgQGzatCk6g6W4pZXv2QOCUjbjZEopiqI1321Io/MTZTNHbipZnyRr20mqfG7V55h9pYjIKNTyPVuYs+9ZTdHvKdXQDFq1DJyZUvpxeSWtvLIqKGWMm1zUtNQm53azqdZ+noEz8BE1REXlTRR7HZ9XnIGPmoLhg1JOpxOnnXYa5syZU+vjs2fPxtNPP405c+bgp59+QmZmJvLy8lBaWtrEI6V4Vlwe3FMKAJLtxmnEHXjh0NBG5yfCZo7cB5nT7d+GKFSlEifZOAMfERlLg2ffMxtg9r0Gng2y0bn+1BtaCVYT0irPLYxwk8tIzGYzxo8fj0GDBsFsbr5tckM1OVep5XsuBg2ogcLJlKq6wcy/r0iQZQU7DpXh1z3HseNQGWc1rGT4d/ARI0ZgxIgRtT6mKAqeffZZTJ8+HWPGjAEAvPHGG2jTpg0WLlyIm266qSmHSnFMnSEnKFPKQOV7vigFpSLZU6rMU1m6Z/eX7vm/rjxRZ/keERmEx9ewUmmrIRqdNywqZRIYlNKberMl2W6uOp/gDZggNpsNr732GvLz82Gz2aI9HN2EanKuUpe7PDwXooZh+V7T2lhYjMXr9mJ7URncXhk2i4huGUkY26cDctunRnt4UWX4oFRddu7ciQMHDmDo0KHaMpvNhgEDBmD16tUhg1Jutxtut1v7vqSkBADg9Xrh9VZ94KtfBy4jY4r2sTrudEOWZTjMVWNwmAXIsozjTnfU/4bKK3yQZRmCAMiSD165aQJTZkGBLMtwVnhqHKOGPifFZRWVz7Go/WyC+hyXVUT9OW5uov2aovDxWBmL21v5fqvIYZ1TCIoEWZbhcvua/Bh6K8cqSw3btyL7x+zxNf2Ym4IRXlNHKz/zEiwiHGb4P+vKPc3y+T4RRjhWeisp959j2ky1/55W0f/3UeYy7t9HPBynWOSs8EKWZZgFOeR5uvr35ayI/vVMLNu0rwRzvv4Tx8q9yEy1w5Fsgssr4bc9x7HniBO3DeqKU9qlhL29WHlNhTs+QVFip0ulIAh4//33MXr0aADA6tWrce6556KwsBDt2rXT1rvxxhuxa9cufPHFF7VuZ8aMGXjooYdqLF+4cCESEhJ0GTs1X5ICvLfDf5d5dLb/pAEACp3AqgMiWtgUDO0Q3ZeZ0wt8sluESQD+2qXp7nRsKxaw7rCADkkKzm1zYs9BQSnwQ5GINgkKBrb1b+uPYgHrDwvISlJwzglun4goEj4oEOGWgOFZMlKt9a9f5AK+3ici2QqMzGraO9Ef7RLh8gF5HWS0bECiifr51tKuIK8933v1sOW4gN+OCOiUrOCMVgqW7PSfZ4ztLCPMdmXNnqIo2k1mm82mZVE3N1uPC/jliICOSQr61XKuE8lzLYovX+wVcNwtoH9bGW1DXAKvPyLgj+MCTk5TcFo6/74aQ1b85wZ7nEBrO+D0AQlmwCwAigIcrACyEv3XkU1Y0NIkysvLMW7cOBQXFyMlJXTQLaYzpVTVP4QURanzg+nee+/FnXfeqX1fUlKCrKwsDB06NOjJ8nq9WLZsGfLy8mCxWGrbFBlENI/VUacHP/i2w2ISMPrCk7W/vb3HXNj1zU6kOswYObR7k46pusNlbvy6/E84LCJGjjy5yfa7fs9xHFq3D90yEjGyXycAjT9W324/jH2binBah1SMPKM9ACCrsBiHfy5EdnoCRp6XrcevELf4/hc7eKyM5edPf4fHJ2PYkG5omVgVlQp1nPYec2H7NzuR5rBg5NCcJh3rb59vRZlbQt6gLmiTYg/757YdLMOuNbvRNtWOkQO76DjC6DDEa2rDARzbcRTndkvHsFPa4NfKv6tzB3ZFelLzLVVrCKfTiRYtWgAAioqKkJaWFt0B6cS6pQhH/jiMvp1bYGSvtjUe/3VvMQ6tLUTX1okYeU6nKIywfoZ4TVENW5ZtQ3K5F3nnZ6NjS39Uqvqxsm89BNfvh9AzuwVGnlbz74/qt/OwE4sP/Y4erS1weXw4dMSFhEQrslolAgBaun0oLvfilL4no3PlsvrEymtKrUirT0wHpTIzMwEABw4cQNu2VS+SoqIitGnTJuTP2Wy2WmvPLRZLrQc11HIynmgcK5fPA1EUkZZghdVadQHSMgkQRRFOjwyz2RzdO3iiD6IowmoxN+nzk2S3QRRF+GShxn4beqzcPv/zmZpg034uLdEOURTh8sp8jeqE73+xg8cq+hRFgaT436sS7NawzikS7BJEUYSkoMmPnwIRoqjAZq19rKHYbBaIoggFNd/bm5NovqbKfQpEUUSLJDssFgvSEqw4XOaBS2rez3lDBD4Pzfn9zyP731OSHbZaf8eUBP+5ltunGP45aM7HKRZ5pNB/W+qxSrJbK8/lm/4zqrlw+QCPpCDRZsGxci8EQUC5x//ZDwCJNgsOlXrg8jX8OTb6ayrcscV0AnDnzp2RmZmJZcuWacs8Hg9WrlyJc845J4ojo3hSUqHOvBcc402srOOTlehP0+uT1Gm/mzYwpjY6j8SMHWXuqkbnKnWGwxLOSEREBuCTFahNEcKefa9yPU9UZt/z77Ohnw3q+nLsdICIOYGNzgP/z2bn8afeRuecfY8aQVEUuH3+vxlbnY3OOfveiUq2m2GziHB5JG0ylAqfrH2GujwSbBZRe5+PR4b/zcvKyrB9+3bt+507d+KXX35By5Yt0bFjR0yZMgWzZs1CTk4OcnJyMGvWLCQkJGDcuHFRHDXFkxJXzZn3AMBsEpFgNaHcI6G0wodEW/RebuqsTuaGzvt9gtQPuQrfiX+QOdWglK3qg1N983b7ZHglOeyLQCIiPQTOoGcN8/3IalZn31PqbT8Qaerse2IDg1Ji5Rh9nH1PN6WVN1vUmy/q/0t5EybuhDv7XrRvgFJs8Ugy1LdwNfBUG5tZPZfn7HuNlZ2eiG4ZSdiwt1gL7imKPxiVYDVhf7ELvTqkITs9vNK95sjwQamff/4ZgwYN0r5Xe0Fdc801WLBgAaZNmwaXy4VbbrkFx44dQ9++fbF06VIkJydHa8gUZ4pd/ruWqY6a6YnJdjPKPRLK3F4A4ffriDT1wsHSxJlStsqLLXcEppF1Vp5sBQb3bGYRFpMAr6SgrMKHFolhdBWm/2fvvcMkuepz/7di5zA5bs5BaVcZCQWQkAATBBiMEcYXjDHZ/AwXHC4yNhdssM0FGwscZMAYkZGARUhIQjlv0OY8uxN7Zno6d1eu3x+nqzpM90yn6e7ZOZ/nmWdnZ2q6q6u6q855z/t9vxQKZYlQtZwrtVKhR+By26m6CZFvznXaNE17QlKtU4rLbq9TUWrJyIlS1Cm10sko5L3gXsQpJWsGdMO0P58UykJI2bE5yyy8iOK0FpipU6pmWJbBW3YNYzySwf7RKJwCB45lMJuUoWgGOj0i7tg1VPUC0YVE24tSN954IxZqEMgwDO666y7cddddzdspCiWPXPleKVFKQCgut7y8zC7fa7KTyJk3UDIMs66LrTVA94i5yxbDMPA6eETSKhJUlKJQKC3GKsGrxrUpsLltVd2wnVNLTb6gVO0klqei1JIiqTrkrCshJ0rRcvWViuWAcgulp22uvNKrjKrD20JnPmX5IGdFJqfALejQzZXvUadUPewcCuD9N6zHn//kIOIZDbphIszLeMWGHtyxawg7hwKt3sWWQq9aFEqdWE6p4vI9IH9ls8WiVI25IfXizJtcKboBJ1u+Zn0hTNPMK98rvGx5nVlRSqarxxQKpbVY5XtCFW4nlmXAsww0w4SiGfA0qbGaVocoxVJRakmxxgwOnrVLZ6x7X6vHE5Tms1j5HssycPAsZM1ARqGiFKUyLJFpodI98nvqlGoU/X4ndq3uQELSoOoG1nZ78Onbtq5oh5QFvWpRKHUSz5QOOgcAn6M97Paq7ZRq7kWP51h7siWpun1jqxZZM+wJVHE2l3WMk3SgTqFQWowlSlWaJ2Uh8iw0RS/IpFpq8kPKuSpzrKhTamkpDjkHAD8t35sHx3G44447MDU1BY6rbXzR7uiGabvmypXvWb+zRCkKpRKsYHwnv/Bnp5FVDyudaLbzXp/fiYxKQs9b2Zy9naCpwBRKHZimaa9alnZKkZ+1WjDRWhR0DuRWYOQ6AhKtznsOnp1X2mIfY5mKUhQKpbWoNZTv5W/fzA58ltDPMNUHnduZUqa5YMQCpTaK86TI9zTovBin04l7770Xn/rUp+B0ti63cynJ76jnWmBhzxKsaAc+SqVIeeV7C5Ff9VDPWJ4CzKUUAMDGXi94loGsGYik6UIDQEUpCqUuUopuD+xLtfFsn/K91gSdA3ldO+oYKFmlex7H/BsnLWmgUCjtgpINOq9WlBKzLlbL1doMdD0Xyl4tlihlmuSL0liKO++R78m9Lq3o9kIT5cLHcj45BXZB8dgSFtIKHQtRKiMnSi18v7KqHvL/hlIbkTQRpbq8Inp9pFZ/Ippp5S61DVSUolDqwCrd8zn5ki6kdumWY4lSrXRK1ROQaA3QvY75bjSvdYypU4pCobSYnFOqOqHHErGaWb6nZ9Uktobagfy/0WgJX8MpVb7nFjlYt3DqDF45pBfpvGfhzjaBoU4pSqVIWdeTo4JoDXssr9H3Vz1Esk6pDreIgaALADAVk1q5S20DzZSiUOrA7rxXwiUF5ASTVnfLscv3WuiUkuu4keVCzss7pVpdIkmhUCh2plSVHfSE7PZKE0sjDKN2p1T+3xjUKtVwSjmlSLdZAbEM6TYbdNNus6lUCl6vFwAQiUQQDAZbu0NLgN15T1x4yuYSyTWEZkpRKqXS8j1rm6Ss0w58dWKV6nV6BKg6KTmejFGnFEBFKQqlLuKZbJ6Ua76DB8jlTMmaAUVrXqvvYloVdA40ximVyq4UekuIf347Z4PWZFMolNai1Jkp1UynlOVw4mq4L+R366NOqcYTL+GUsv4fy6j27ykXPpkKhQOXUJ1TyjBMjIRTSEgafE4ea7s8NMB6hWGLUhXMTWgHvvoxTdMu3wu6RdtxPEmdUgCoKEWh1IXdea9EyDlAgrkFjoGqm0jKGjr51qxsaobllGq+KOZowI0sKZO/9ZRYKbSEqqSswTRNMLSNBYVCaRGW02lZZEpZolQN10yGYcAygGHSDnxLQa6BSuE9z98mOZWU5mE5nzyLlu9ZmVKLj7UOjcfw471jODWdhKwacAgsNvZ68ZZdw9g5FKh/pynLAjm7WFyJU8rBWwvM7SVKLSdxNSlrUHUTDAMEXYI9p4mkVWQUHa5FPuMXOlSUolDqIJYVpQJlnFIMw8Dn5DGXUpGQVHR6WiRK6Vb4bivK9+rvvpcr3yshSmV/puqkbXIlN1cKhUJZCixRqeryPa755Xt6HeV71t8puklFqSWgVPle/v+pKLVysESmxSas1u8XEw0Ojcfw1YdPYi6lYCDggivAIaPoODgWw3gkg4++ahMVplYIVj5UpeV7QH1VD41muYmr0XTOyMBzLHgOCLoFRNMqpuIS1nV7WryHrYUGnVModWBnSrnK67tWOHcrB5GtDTpvgFNKsrrvzT/OIs/awhcdqFMolFZiZ0pVuQBgiVitKN+rdVWZyzpvqSjVWFTdsEuwSpXvAbRcfSVhBZ27Fi3fW9wpZRgmfrx3DHMpBRt7vfA6eXAscZxv7PViLqXgJ3vH7bw5yoVNpd33yDbZsXybBJ1b4urBsRiCLhFruz0IukQcHCM/PzQea/UuzmMuG3Le6cktNgwGsrlStAMfFaUolHqwM6XKlO8B+YPIFopSLQw6t25k9TilrE5DpUQpIHeMaUciCoXSStQ6M6WUJopSVkB5rfcF6yVSUaqxWIswPMvMEyKoU2rlkak46Jwr2L4UI+EUTk0nMRBwgWEYRFIK9p6PYjYpg2EYDARcODmdwEg41bgXQGlbpCrK9yzhSm6D8r3S4irT9uJqfp6URX+AdOCjuVJUlKJQ6sIq3ysXdA60x8qmVmeZRj00og7dKt8rXjW2sEUpOlCnUCgtpNZMqZYEnWdLDbkaswYth5VOu+81lFzpHj8vI7EdxhOU5lJp+Z6VKbVQ0HlC0iCrhv1YcykFmm5iZDaFlKzBJXKQVYOKniuEXNB5BaIU3z7le/niKgAcmYjjZCgBwGxrcdUSpTrzRKmBrFNqKk5FKZopRaHUSL7FfiGnlL8NVjZtp9QyLN8zDBPp7N+Wc0rZJZIyHahTKJTWodr5fVUGnfNW0HnznVK13hasRQ69ieHsK4Fc573544p2cF63ExzH4fbbb8f09DQ47sLMk7TGme7FMqWEnFOqXNMXn5OHQ2CRUXR4nbw9LjNM4NR0Emu63HAIbNkFQMqFRc4ptby679niaoBDRtXtKglFMyHyDFwih1C8/cTVSIpc2zvyyvdsUSomwTDMtg1pbwbUKUWh1IjlkhI5ZsELurcNVjYtp9RyDDpPKRpME2AYwF3GYuylA3UKhdIG2JlSfJWZUtkJtao1T+Cx7gu1OqWsrn3UKdVY8p1Sxdjle7LWdqUprcDpdOK+++7DX/3VX8HpdLZ6d5YEK1NqUVEq+3vNMMuWAa/t8mBjrxeTsQxM07AFBoFjIKk6Dk3EsLHHi7VdKztweSVgmqadD+WoonyvHUSpfHE1v1zV+qxkFL0txdVS5XudHhEOnoVmmJhJyq3atbaAilIUSo3E80r3Sq1IWbRD3pG1es/XOPmoBztTqsYbWUrOtUMut4Lgc9DyPQqF0npqL98j17ZmZkrpBnmuWtcqckHnrS/nuJBI2E6pEqKUgwfDAKZJFmzaEcMwcWYmiQOjUZyZSVLxrE4yCvl8LVa+J3Ks7XqUlNKfSZZl8JZdw+j0iDg+lYSkGTBhYijoQlJWYZjAqg73inZrrBRkzYC1nrBYiD6QH3Te+ut9vriazptbJWUNpmliMpbBpl5fW4mrpmna3ffyy/cYhkF/1i01scLDzttLQqRQlhHxrAASWCBPCgC8jta7eHLle60IOs+urtR4I1ss5BygORsUCqU9UGoNOm9B9z3rqbga6/es+0kTd3lFYI0VSsUCsCwDr4NHQtKQkLSSJX6tZLm1aG93DMPMK99beMrGMCQYPynrSKsaAij93tg5FMBHX7UJ//nkWUzGJGgGuW5dta4Lim7i5EwSx6cS2NLva/jrobQPcrZ0j2Uqq6Jop/I9S1wdj2RwbCoOgAHHMphLycgoOjo9Iu7YNdRW4mpc0qAZJlhm/rxxIODEuXAaUys87JyKUhRKjdhOqUUGhdagMZm127fiItnaoPN6nVJkgO5dQJSyyvdSC3SdoVAolKWm1u57otV9r4mr0JpRX1dWNusQ1qhTqqEs5JQCiFvKEqXaCatF+1xKwUDARfJeFB0Hx2IYj2Tw0VdtargwlUql0NvbC13XMTU1hWAw2NDHbzX5oeWVuFlcIo+krC/YgQ8gwtQdu4cgawaGO1x4+xWrsLbLg5+/PIFnz8zh+y+M4sM3b0SnR1zwcSjLF6t0zylwC1Z7WOTK99rjem+Jq3/x04MIxWXohglFY3DVji7c0YYieDRbuhdwCfPmgQO0Ax8AWr5HodSMFUbqdy2s7Vp2e6OFdntr0lDtRKkRWDcyRTdrah1eiVPKEqzi1ClFoVBaiJ0ptQy671laElfBhKQU1kukmlRjyWVKlV7wakdncCtbtKfTacjyhZnFYnXec/AsuArEY0u4SlewQDeXUuF3Cbh0VRDre7xgWQavu2gAwx0uZFQd3332XFOvR5TmYnfeqyDknGzXPk4piy39Pmwf9GP3mg7sWhPEpas68KGbNradIAWQTpcA0OGeL/RaYeeTsZVdvkdFKQqlRmJ5mVILwbIMPNksgFblSlmtv1tRvufIazUra9XfzCoq38t230tKpJ6cQqFQWoHdfa/KoPNcplQzg86z5Rs1OqWsTCnqlGosCbl80Dn5ees7+haT36KdYRhMxyXMZUN727lFe7tjOZ4WCzm3sLarRDiYSZDz0+Nz2D/jORbvumoNPCKHiZiE+/dP0IywCxS78x5f2XvLzofVjLZ5D5D3MMlkumgoAL9LaFu3kZUn1VHCfdjnd4JhgKSst9ViQ7Oh5XsUSo3EM+VzH4rxOYXsxUbDQAsE/FYGnXMsA4FjoOomJNWAIFY3AbLK93wLiFIeB7lZGiZZIVxIwKJQKJSlovag81ZkStVX1m2tcRh0IaBhGIZpL8SUF6Xazxmc36Jd1nSMhNNgGCDgFsCxbNu2aG93cnlSlQkH1TilSolSADln77hyFf7zqRE8eCSER46FEM+eX5oRduGQc0pVKErxuXuarBmLBu83g+nse7jX50Cf34nxqISxSKYt35s5p9T8OaPIs+j2iJhJKpiMSW2XFdgsqFOKQqkRa0C4WNA50Hq7fb3ZIfWSW2Gp3imVqsApxXOsPWhrZZdDCoWycjFNM1e+x1eZKcU3P1PKEqVqdkplhTStie6uC52ErME0AYYBPGWCrdvRKZXfoj2d7Zhrmrn7cbu2aG93rBb3rkVCzi0soSCziFNK1nTb7V8sSgHAxl4fNvd5cWg8hhfOzkHkWKzt9iDoEnFwjGSHHRqPVfNSKG1GteV7PMfac4h2KeELxYkrqs/vxFAHyWUab9MOdpFsplQppxQADARprhQVpSgrgkbbj03TrDjoHMjPPGr+INI0zVzQeQvK94DcCkstAYnJ7ADXckOVIyf8tc9AnUKhrBx0w4R1a6k2U0psRaaUWZ9Tyvo7nTqlGoYdcu7gy4qF7XivK2jRruQW3xJS+7ZoXw7UWr63WNB5OKnY25fq6mcYJs7NpsGxgNdJSqJMmE3JCKM0B6sjtqNCpxSQ3027PUSpfKfUUFbUGY9k2jLGwxalSmRKAUC/lSvVpqJaM6BLFpQCDMPESDiVbTXMY22Xp61aatbCUrQoTsoajOxqZiUrf3YHvhYMInXDhHV9bkX5HpC76dWyupKUyQB3oe571u9DkFd0PTaFQmkdap5jqOryPd4SpUyYpllRN6R6sRYrKglQLoUVkF5LAwtKaXIh5+Xvd37bKdU+97r8Fu3HpxIwQd5Xs8n2bdG+HLDK8CrpvJe/3WJOqXKlexYj4RROzSSxcyiAkXAasmpgKiphuNM9LyNsfY+30pdDaSOqLd+ztk3Kett04JvOOqV6/U70+Z3gWQYZVUc4paDbW/q93QoMw7QzpTrLiFKDtAMfFaUoOZZCvGk1S9Wi2LI9L7SamU8rVza1vAlDq5xSjuyES66hNCVlO6UW6XKYPca0fI9CobQCJetyYpnqhR4h79qs6ibEKoPSa8ESk2rtvmfd+6go1TgW67xHfpcbTzRLwKyEUi3aJZXBVeu68NbdSzOOZFkWr3zlKxEOh8G2aNFtKUlnhYNK83us7RbLlLJFqTITdysjbCAgYCjowpmZlB3Abz0PzQhb3liiVKWCJ9BeHfhU3UA4m9PU63eAYxkMBJ0YnctgPJJpK1EqLqkwTNKxttyCg+WUmknKUHWjJd3SWw0VpSgAlk68aSXFLYoZAGBA7McOL05NJ/GTvePYPuCvevXODjmvIE8KyBdMmr+yWSBKtTpTqsobmaIZtpC1uFOqdW40CoVCsUrvahlMCnkTakU3qs6kqgVblKpxsYKnolTDscv3FnBKebO/0wzSPKQdAoctNvV5sW3Aj+EODQwAE8AfXLsG67qXxk3jcrnwm9/8Bnv27IHL5VqS52glmWymVMVB5xV235tNLuyUys8I89hClwZyRhmaEXYBIFvd9yrMlAJyC8ztIErNJmWYJhHVrEZIQ0EXEaWiGVyyKtjaHcwjknVJBV1i2fmm38nDI3JIKTpCcQnDHe5m7mJbsPJkOMo8isUbr4ODaS7/2vHCFsXA4ck4Xh6LwciuLNbTotgKOa9clGpdMKmm50LOW7Wiat/IqnRKWSHnPMvYj1EOe/WYOqUoFEoLqDXkHCCuI8stpTYp7FyjTqm2oxKnlMCxtruhnUr4ACAUk8EwDIY6XLh6Qxf8LgHn51ZuRkq9pKvNlBL47N8tPA6ynFLl3CT5GWFOngXLALpBckFpRtiFgZULVW35HlBbPmyjmY5n86T8DntuM9yRy5VqJ+zOe2VCzgGAYZhcrtQKLeGjohSlSLxhcD6Swb7RKOKSWrd400rsFsUih6SkI5Wtg7aEDpfIQVZrsx/nQs4rWyVqZfmelXPSqtI9oHbLbzKv895igpq3DcNfKRRK62h0g4vFUDXy+NWGnFsITQ47t45H3UHnVJRqGNaiymIOFOv3rWieshBT2YyXgYDTFixGZpfX2LGdyGVKVdd9b6HyPdM0F3VKWRlhnR4Rp2ZS4FgGhmliNiHh1HSSZoRdANiZUnwNolQbBJ3nOu/l3sOWu2g82l5h51E75HxhI8PgCu/AR32XlJx4EyAOqdkEsUSGkzL8TmHZ1o7n24+trgcAcd/4nEJd9mNrIFipU8oqPZM1A7Kmw1HFTaBeNKP2kpJGUavlN6VUNkAHYNt3afkehUJpRUaiUkf5Xu7vdPtxlpq6g85p972GU0n5nvX76UT7NfaYjBGHQr/fibXdZIJ4LpxesuyrVCqFtWvXQlEUnDt3DsFgsOHP0UqsMVP15XsGDMMsKRrFMioU3QTLAJ0LODesjLAf7x3D06dnkZQ0zCYVXLOhG3fsGlp2kR6UQqQayvesbauN4lgKcp33nPbPerwOiBwDWTMwk5QLftdKKnFKAblcqalYezm9mgUVpSgF4o1hGvZAlXQKMJdt7bhlPz44FiuwMqdk3bYfXzwcrMl+bAWdByoUpZwCBwfPQtaIuOfwNlGU0utbDW8EdqZUjeV7ngoGZN4W5nZRKJT2oVUZiXamVI0h5aJVvqc3R+QxTNp9r92wFv/8C5Tv5f++3RYLp7Ir/P0BJwYDLjh4FhlVRygu2xOuRjM7O7skj9sOWI1eKhal8kqxJE2HW5w/brdcUl1ex6Kf/Z1DAWwf8OMXL0/gFy9PYkOPB598zVbqkLoAqKn7Ht9O5XvznVIsy2Ag6MK5cBrjkUzbiFJW572OMp33LAay18iJqNRWTSyaBS3foxTUjoeTOUeRqptIydqyrR237MdukawoqroBwzQxl1Lqth/nyvcqE6WAnFuq2YNIrc4SjUZQa9B5ssLOe0AugyOl6Msu/4xCoTSGeRmJTh4cyzQlI9HOlFom5XvWgkXdTil6vW0IpmnaTt9Ky/faSZQii305UYplGazqJG6p5Rb/0A4YhmmXSVUaZs/l5W+WK+GbtjvvLTxBtmBZBpev7USX1wFZM7HC5skXLJaw5KjKKdUe3fe0vM57PUXCk50rFW0ft9FcheV7PV4HeJY4vaxw9JUEFaUoBbXjZ8MpqLoBjiUD46OTiWVdO75zKIAbt/Sg0yOCYxkkZQ1JWcO2AX9dq+W5oPPK3WN2B75mi1JW0HlblO9VN9myjtVinfcAwC1wYBnANIHkIiGfFArlwiQ/IxEARufSmEuRSdhSZyTW030PAITsdVJpUtC53qDyPY2KUg0ho+r2sVzsnpdrntI+E5doWoWskfFjTzZAe21XVpSiuVJVI2k6rMpYVxVuFkvAypQRpayQ83J5UqXo9TnAseQ9uhInyxcapmnWGHTeHt33wikFhkn2pzjbdyibyzTWJmHnumHa1TWLle/xHIve7Odyoo1EtWZBRSkKACLevO3yYQRcAjTdAMswUDQDQbewZKUOzSIpa9i1ugOfuGUTbt7ai91rOvCOK1fV/JpkTbfFlaqcUvbKZnNv6O0UdC5XGY6Yygs6XwyWZeztaK4UhbIyyW9wEU7KmIxJODubgjW7q6fBxWIo2aDz+jKlmueU0ust38v+HXWmNgbrPekWuUUXkdrRKWW5pHp9Tnv/11hh59lcKUrlWE4nB89WtahoCViZMsJBLaIUz7Ho91ulRStvsnyhIWuGLXjWFnTe2vI9K+S81+ecV+I2lHVKTUYzbXFvimVUmCapVvFVMJfJ5UqtvLDz5RUSRFmcgweBF18EeB4QBPJv/tcVVwBdXWTb6Wng/Hn7d+KZOdwiJNDb58G2VQF891QanoAHG3q8gKaRL54HOA7Lxb87l1IwGZPAsQxeta0Pkmpg7/koJqISdgzW6JLKkEGgg2erWmGwVzblZpfvZVfv2dZp0HY4YpU3Mqv7nrfSLocOHglJa9hA3TBMjIRTSEgafE4ea7s8y9IxSKGsFHIZiRqmsi2jdYNcS7x1NrhYjJxTqr5MqWY7pfga7w3UKdVYKg05z9+mnZxS1kTREi8AYHWnGyxDJmbRtLqoU4CSw3I6VVq6Z+FexCk1m43p6PFWl7cz1OHCeFTCeDSzrBeqKYCcXVhnmeruV+3ilJqOWyHn84XVHq/DzvCdScro87c2V8oOOXcLFWVEDQZd2Hs+isk4FaUoyxjDMBH50X3o+txfld/okUeAm24i3//oR8CHPmT/6obsl8XE5+7Gc4FrcWo6iYse/hnwnvfkflksdv3nfwJvfjP53a9+BXz0o+WFsc98Brj9drLt3r3A3/7t/G2sv33724FXvpJsOzJCnqfEtizDwK/lCRFzc8BvfoOp6RS2jSfQ2+GB+7eT2DGdwtxIDBFzI7C9j2wry+SxS+0rzwNOJyDmBlKWDbPSznsWrVrZtDOlWuiUcvC11aFbTqlKyveArHgVa0zYeSu6d1EolPqwMhJfGJlDWtbtQWAso8Lj4OtqcLEYlpgk8rWJPNbfNSvoPFe+V9vfWzmFBnXANIS4nSe1+NjC2ibehk6p/EBzkWcx1OHC6FwGI+EUFaWqwHI6uatY/ARyIlapTClZ0+0xbLevunMxGHABiFCn1AWAnVUmcFWFaTvaJOg8lLBCzucLTgzDYCjowpnZFMYi6ZaLUtF0ZZ33LKzr5+QK/JxRUeoCwZpAd0xzuG7nNeBNA14O6HNx8HAgLidVBfz+3B+53cCqVYCmQVc1yJIMVtfhgAFGVTHY7QMAHA8lcJFedHOznFMWRt4FKhYDTp0qv7Pve1/u+/Fx4Kc/Lb/tzp05UersWeBv/qbkZhyAnnzR7ORJ4O1vx3YA2/O2s/7/29/7EMw7XkEuxidPAhddVH4fPvlJ4O//nnw/MoL1mzfjrxkOEHjAIRYKWO95D/DXf022nZsDbrnF/t3lGrAqo8HlcgDdPuDWW4GPfYxsK8vAH/9xaVGM54FLLwXe8Q6yrWkC//AP5bddvTp3zAC4f/sINpyew1CvDzDHC8U3vx9Yty73WicnAZYt/bgsW7NDLre6UqVTSqm8fA9o3EC9Vd27KBRKfVgZic+cDiMuqfA7BZgAZpIy0oq+pBmJyy7oPCtKsTVe161jqDVJRLvQSVQYcp6/jawZkDXdniy2EquN+UBRl721XR6MzmVwLpzGZas7GvqcLMti9+7diMViYFvoBl8KrEW5ap1SrgXCqC2XlNfBlezMtxCD2ayeiWhmRXYGu5CopfNe/vZt45Tyly5BHeqwRKkMdq9p5p7NJ+eUqkyUsq6fkbQKSdWrPkfLGSpKXQAUTKCvvw1jr3odMoqOyVgGnR6x/AT6Pe+x3U+PHgnh4WPT2D7gw53XrAUAdE4ngCdHcCKUgPmud4F561tzYpQlcuk6+X5gIPe4r3418OST87exvi6/PLftRRcB//qvhduoaultBweJsyv/sbJfhiwjNTiY29bjgXb9KzE2kwCraxj0CuANHaaqIhxNI+YNIJxS0J0N40QwSJ7X2t98EY7P+5ioKlhVhQgVUAAUZ3dGo7nvJYk4wbL4sl82+cdMkoBvfWv+ObJ4xztyopSuE6GsHL/zOwWi1Ob3vRNbVaX0tjffDDz8cO7/O3YAkUjpba+6Cnj22dz/L7oICIVKC1hbtwI/+Ym9qfeP/hfee/AkTJYDe7cfV87NgbvnHuJAGxwEvvKV3ON+8YvAxARMjsMrRqLQWR5dL/YBLgcQCBAXnsX99wMzM/bzbpxMQgql4B3tAM4OALfdltv2yBEgkSjviFu9GgBxHN73zEmk5mLY0h9AyjCgGdnuXQ4vTk0n8ZO949g+4KelfBRKGzIYdGFttweGacLr4DE6l0FGYXDl2k687fLa8wQXQ6k36Dz7d0qzMqWyi0k1l+8xtPteI7FK8YqDe0vhFDi7RCUhaXB4WztxUTQDs9nJV38JUeqJk7Mk263BuFwuPPPMM9izZw9cLlfDH7+VWE6pWsv3SjmlrDwpe+xbBf0BJ1iGdEWOZzQEFukkRmlfrAViZxWd9/K3V3RjQWFyKaMvNN3AbJK8j/t8pV1QVth5O3Tgi6YrCzm3cIs8Ai4BsYyKyZiEdd2Nd3W3K1SUWuYUt7+2LhDVTqCPTMYBANvzcpbWdnng4FkkJA2TaR2DQX+5Py+ku5t8VcLatcAHPlDZtlu2AP/8zyV/pasqpvbsyf1g50689F8/wc/2T2C4w4UP3bQRAMAA+OFvT+P8XBprIhlyY965c74QY5o5oSx/wL5uHR789QvYd2YW164J4Pp1HYUCWU9PbtvOTmDPHvt3c7E0HjwwBhcHvHFnH7BxY25bh4O4sYpFP+v7Sy8t3Lc77ywv+uVvCyC5ZTtS8RQ8nAk/zxQ+vpUvZrHQyhdfdLmYnSWCUCkchQMe7vnnsNFyzx0ABvJ/uWlToSj1ve8BL78MBsArUcTAQKEo9cUvAs88Y//30uwXACJg5YuEH/sY8JvflN5fnifHA6R7122f///wF/sft39tMAwMjoPB8tBZDn/ylQcwEk5hfY8X+PjHgZ//vLxz7YEHAF9Wjvza18g+lNv2i18EOrIryT//OREB88tZ87d917uImAoA+/cDx46VL4PdvRvwesm209MFQt68r0Agd65N0w6IplCWC0+fnkWHW8Q7rliFG7f04huPnUZS1vHWy5e29NYquxNqLN9retB59mlqNZhYmVI6vUY0hEQV5XtkOx5yUkFC0moSGRpJKC7BNIkDp7jcfk22A990QkZa0ap26KxUrEwod5WilHOBoPPZGkLOLQSORZ/fickYyZWiotTypV6nlGkSl2apv1/q6Aur856DZ8t2QM+FnUvQDbPmZh6NYC6dy5SqlMGgMytKZagoRVk+5Le/Tis6xiJpDAVd8DqFee2v1/d4Sz6G1aGIZYBtAzkvD8+x2NDjwZHJBI6HErZ1d7lweIIIbTsGC8W04Q4Xzs+lMRZJ49JVwdJ/zDC5SXo+PI9pfw+ivQ7wmweBDV2l/x4gWVRWdhYAQVJxwH8MDAP8zht3FoqETufC7qd8BAH49rcr2xbAiz98AA8dmcZV6zrxpsuGFt44HCb/GsZ8YaxYsHriCVJ2mC9yWSKZ212wKfP//h9+9Mhh6KqG27Z04syRg7h42zZwppkTbCze/35gYgLpjIKXTk1DhIGrVvnJc/iLhNHrriMCaHYfEikJs5EU3KyJvoGic9PXR0TQUm6/vPOckIpKUwGwpglW0wCQn2d0JpcNNjkJnDmz8HG12LePuLvKYZV+AsCDD5YVYQGQ95YlSt17L/B3f1d+2wMHgIsvJt9/4xvA//k/5bd9+mngmmsAABvuvx/Cm99cXsD6wQ+A668nf/fDH5Ly2nzxLP/7u+4Crr6abPvkk8Ddd5cX0X7/93Pi6vHjwH33ld+Ha6/NCbzT07lGD6Ued3g4JxxLEtm+3OMKwrJp6EDJIak6XhwhiwzXberB+h4vrt3YjWfPzOHMTAoXDQWX7LnrDTp38M0VpawsqHqDzqlTaj61OAWqCTq3tptNKm0Rdm6FnPf553fD8jh49PocmE7IGJlNY/tghQucK5y0LUpVN1Wzts8o82MMZpK1O6UA4kKdjEmYiGboeVzGWKKUo0pRSuBY8CwDzTBLlpY1I/oiv3SvnFOryyPCKbCQVAOhuNTS+WskXV35HkAC3J87M4fnzsyh3+9cMU2WqCi1zLHbXwc4jM6lEMtoMM0Mtg7wABi4RA6h+MLtry3xZl23Z97Nb3OfD0cmEzgxlcBNW3qX8qU0lIyi4/RMEgDmddkbziroo3O12TqtkMhAlUHnHpEHw5AVhqSiwV/hami9WKv3VQWdsywprRMXuIjmO70W47WvxUlmHeIZDVdfvwbnn+7Hzte+FpxQ4hhkw/dDsynsefwMerwirrp1S+nHtbK+sszMJPFvT5xFj1fEJ4r/5r//u6Jd9Tl5fO7Df4cugcXobAyqpIAzDPS7OazyOyClJYgOPjdx+PzniVuq2LFmfeWXFPzhHxIRpdR2mlYo0N14IzkPxdtYQlr+tuvXkwYGmgZT1yFnZBiqCk7XIcIAky8SOp1EmMl32VniI0C6a2ZhrKy44gw5i/wy15kZ0v2zHB/5SO77U6eA7363/LZXXJETpQ4eBP73/y6/7X/+Z+69+OKLwOteV37br341tx/PPw/ccEP5bb/4xdzz7ttHti0nYH3kI7nHHRkholq5bd/4RuDd7ybbzs0Bf/7n5be98krgta8l22YyZRs9MAACY2O5fdd1Ivwt5Ibr789tH40W/n4ZdVgtZu/5CGTNQI9XxKZeshCzqdeHZ8/M4dR0ckmfu2GZUlpzRB4rC6rWVWSeilIlqdUpUL1TSij4u1ZihZwPBEpP/tZ2uzGdkHEunGqomJFOp7F9+3ak02mcPHkSgcCFk/Vod9+rUjiopHyvFqcUQBwcL50DJmKtL4ui1I6UbcrhrMHV6xRYJGV9XkZsoyp3FmPaCjkvU7oH5MLOT8+QXKlWiVKanpt/V1q+d2g8hj0Hp/DSuQgOjEWx93xkxTRZoqLUMifX/lrHYNCN2aSCuKQhnlHhd4kVtb/OOYrmv9k395GJ77m5NDKKXnVte6s4NhWHYRK1ufjmu6qTTNAnopmabJ1xK/ehjG20HCzLwOvgkZA0JKTmiVLWxINvscru5DnEoUGusN25FfJZacg5kO2+B5J5UCtruzxYN9iBveciSLAuMB7yfknzLLw9fpyaTuHiXl+ue9fGjZULdNdfn3MWLcZb3kK+KuH97wfe//7ykyFXD3Za237yk6VdeaZJHHJ5YsTZ174Wmz//eQgMM18Y0zRgw4bc37/hDcDmzYW/z3fPXXJJbtsrriBh/aXy6TSNZJJZrF5Nsu9KlapqGnE/Wfj9JIeuXBlsvtPOMEiZqaYVimsW+S5JRSF5ZOXIL/9NJonbrBz575VYjDjXyvGhD+VEqUQC+PCHS27GA1h/88250lZJIqJmOd76VuJsA8h5t0pG8+E4cgxe+9qCfDhs3kyORyk33BVXAF//em7bd7wDSKVKC2MbNwJ/8Re5bb/wBfIaS23b20vKVS3uv58c56LtTI7DuSNzwJqduGZDNxkUHz+ODck0+sbOQWc5RAdNBAOe3L7nl5prWl2CnNV9r/ZMKfK8zcqUspxStYpS1Ck1n3qcAtUEnedv1w5OqakSnffyWdPlwfNnIxgJpxv6vKZp4ty5c/b3FxLprNOpUeV7pmnaWTy1ilLtlNVDqZ1ay/esv0nK+rz3V37lDsMwSEgqVN1Ep0esuHKnEkKLhJxbDHcQUWo8mgbQWfPz1UM0o8I0AZFj4Kngc2zdP6YTEkSehcAxCDqFFdNkiYpSyxyr/fXBsRg29nrR63dgKiZjNJLBdufi7a/jkorzc2SQUGr1qsMj2rbrk9MJXDwcXMqX0zDKle4BxNbpEjhkVB1Tccm+yVaCYZhIZgeO/iqdUgDgy4pSySaubGp1htk2CkeVHfiSNYhSPgc5JxlVh6obNU0Ore5d+85HEJdU9PkdkFUDSVnD0ckE+vzOJeveVQ9126YZpsAlBQC6w0EEgVKOtmKGhwsFooXYsYN8VcKVV5KvSrjuOuCFFyrb9sYbiXgDFGbIWUKWM29ydcklpEtnKceaqtoh+QBIR9Of/KR85lu+OBcIkJJN63GKBbd8AVMQgLe9rXSjB0VBMr/Rg2EA27aV3998l10pQc76eXHTB4A4wdQyk+Bil8KDD5ZvnHD11YWi1Ne/DuS7vfK56KJCUepTnyJlnUUwAG7tG8aJf3sAu9YEyQ/f+U449u7Fx0s9bl8fMDWV+/9NNxGHWakOpIFAYZnu+99PxMc8Ue51KQ1pg0Fflxd47JHctl/+MvDii+BYFpeFQuDuv79QzPvSlwBBgMCz2P7cw9g2Nwo81jtf9BME4Pd+L/fePHAAGB0t74i7+OKc2zUcnifkcYkYBIYDpyqAWX25KhWlCqnHKSCpur1gU7ko1Zhus/VimmaeU6q0KLUuOwYdi6ShaAbEGnPXVhLpOoPOM0VOqWiaiAQcC3RWUUqUT3/ACYYB4hkNCUmt2NVHaS/qFaXyH8Miv3LHME2cCCWgG2Qe5nHwFVXuVILllOpdwCkFAMMdZEF5PNI6ATWSbf4QdIuLdqvMv39s7fdh7/kodINUuWzsXRlNlqgotcyxJtDjkQxOTSfR7XMgFJMQTat4eTyG4aB7wQn0kax4s6rTVbYcbUu/D9MJGSdCyWUhSqm6gZMh4mrYUWISzjAMhjtcODmdxNhcuipRKiFrMEyAZQBvDWGdPicPxJq7sqnVUr63BFgtqyWtMheT5ZQqDk1dCKeQq3dPSlrFdtlidgz6sbXfj7SiQ+DIqpCiGejxOdpypaJZtukLlnIZchZOZ+VuuEAAePObK9u2s3PhfK98OjpIhlcJdFXFyT17sMn6gc9Huk1WAscR51OxiGaJZEVNC/Dss6VLT1WVvJ58/uVfSNlhsWtNVQu7jwLAH/0REbCKHXa6DgwVZeFdcw0RQIv2IRxLY8bfjSvWdtrXG3R1AX19UGQVuqKCN3UIupZzRRUcyOy1yTDIMVGU+b+zOHsWOHy44EfWKzKLRdwnnwTuuw8sgNUoQbYMWeRYXPTMQ7j0iT2ltiK86U05Uepf/gX4t38rv+3oaE4o/tu/LWwoAeCv8v9z7BhpJgIQofTLXy6ds8bzwM9+BmzfDpZhsOvR+3DNwz8Gun2lt//bvyUCKUCaPPzgB+VFtHe/O/c5O3QIeOSR0o48ngde8QrSuRUgwuLRo+Wz4QYHcy5JWSaOPIeDHEeeb1iparFTQFI1jEckDHW44BS4BZ0C1kTNwbO59+4i5JxSrRWl4hkNGVUHy5R34ATdgt1RajSSxoY6nBIrhUyNmVKuMk4pK0+qy+OoeRzg4Dn0eMlC9URUwpZ+KkotR3KiVPXisJV9WCxK5Vfu6KZhN9KYTcrwOPiKKncWQzdybr++RZxS1txuKi7VvEhdL5Fs573OCuYihfcPFi6BR1LWkFJ0OEW+YU6zdoaKUhcAO4cC+OirNtllOwzDQNF0ODgRH33VxgUn0AuV7lls7vPhiZOzOBFKLNgCtF04GUpC0U10uAUMllm1s0Sp0UgGV1Xx2PGMFUQq1HRTb0UGhOWUasUFOR+7lWyF5XvJGkQphmHgdfKIplUk5dpFqfFoBgzD4Kp1nfj9q9fgwGgUj5+YxeY+b9sJUkDhzUw3TUxGMuj1O+DguYbapinLkwVDlxmGTNwFoTD/rBy7dlX+xL/3e5VvW6k4BwD33DPvR6G4hK/85iQYBvjk+rwmBw8+CACYCqfxr4+dhkvg8Jev20Zev1F0LXrggcLmDflfxaVBX/4ycR/lbXP/CyNIphXcsrUbPfnb/tEfATffDF2WcezQIWzduJE0ebD+NiuGChyL4zuvgODzYEeft9A9V0okXLuWuAjLlavmb8tx5Pxa2xSTL8hmMsRVVY6sQMdzDIKzUxg+ur/8tn/2Z7nvX355YRHtla/MiVJPPUU6ppbjvvtIyTAAPPRQLqetFN/9LvDOd5Lv9+wB7rgj9zuWzQlUTic5r9ltO06cAJd1sZUUvP7X/8o1Mzl1Cv6//r9451gCHo8TJs8jLOlI6QwEl4jI1a/E2c2XIBQ3kB6fAn74YMFjGWkNO09F4PM4gM1croQ5nQZeeqnk83fFJLgTSSSsyZlhAPF40/PhJuPEidDjc5QdZzAMg7VdbhwYi+FcOEVFqQpI19h9z3JWqbpZMBmvp/NePkNBV1aUymBLv2/xP6C0HVbFQrV5ZUC+U6rw/plfuZPf7COcUrCqw7Vo5U4lhJMydIMIY4vl+gbdAtwih7SiYyom2dEtzcQKOQ9W0Hkv32nmiYWxPjKDc4IXhkn2u1FOs3aGilIXCDuHAtg+4MdIOIXZpIJ7XzgPkWOxUDRFRtFxJhsGvn2gfPDk2i43HDyLhKRhMtbaLgaVcGgiBoCUI5YT0KyL0+hc5fkGhmHiyEQc4aQMj4ODYZhVC1NW5lG8iU4ptY0ypYD5qyvlqKV8DyAiVjSt1nXhPjhG3kPbBgLY2u/H6k4ymJ6Ky5hLKRWtejST/JvZWCSNUFxGStGwtZ98rtv5ZlZLlypK5Sx1e+Z24enTswDIvayUGD3c4YJTYJFRdYxHM+QeUFzSXNzdcyHyyzCzHBaOIp7RcOPNRa66bPi+oao4tWcPNpdp8iBwDF589VtwzvdO7Lhl8+L78Od/Tr4q4ctfJl9ZZFnB3/70ZTCGjr+6fQsEf97k8lOfIkJauRLU9esBABzD4OVrb0Vk/Rb87mUDpcW87LYASJOHv/3b8o0eVq3Kbbt+PfD2t5dv9JCfBeb3A9u3l8+oyxdbixs2GAYR4TLZEo88wU6Ix8E+9VT5Y5qf2zY+ju7/vge3l9n0F34PjqzdCYfAomN63G7oYdEH4Pft//2fXCfWc+eIWFeCNQBueMO78dgfZRsyjI0Ba9bM39ASqN7/fuD//T/ys0iElHeWc629/vXAZz9LtpVl4tArsy2zZhtw8e3o92cXAT/1qZLbXR2VoRgBnO39ndy+fe97RPAt9dhdXcDu3WWO6IWNaZq206na8j0Hz4JlAMMkwlbARa5z9XbesxgMurBvNEpzpZYxDSnfK6p6yK/cOTgeI536OAYZxcDB8RiGOxau3KmE6TxhdTGDhFUVcyKUzN3zqyX//pBOk/+vXZv7/W9/S7o4W7+3/k2nAacTkdveAyDrlPrEJ0jJffG2mQzgdsP30hHbafbH//ApbDj8Ar73p3+HlzeTu0ojnGbtzoX7ylYgLMtgfY8X63tI6dODR0J4+GgIFw0FSl4EjmbDwPv888PA8+E5Fht6PDgymcDxqURbi1K6YeLYZLZ0bwH3l9WBbyYpl2xrWow1sXtxZA5TMRlnZlLQDbPqiZ3PDuJuolMqq0y2unyv3OpKOWop3wMAf53H2DRNvDxORKmLh8m5dYs81nV5cGY2haOTcbxiY/dCD9F0LNt0WtYQztawxzMa0ooGt9gY2/RSsFIEk1bRjPbM7UBa0bDvfBQAyn42WZbBhh4vDk/EcWo6uSSrplbXvNqDzqtzk9aDzrDQRHLf5wIBUpNu0dk5vxSzBBzLYHZoHRJrNgBvqCAj7uqryVcl3HIL+aqEN76RfFWClcumqiRTrvgrTxiLbdgA7fvfJwPlUiJafubb6tUwPvtZPHl0CrPRFFysiXRKAq/rYA0dx3rX206BgdVB0sQiT0SLJiTMxVLw8UBPfkYdx5HmAiXEQVPToIlOpBUdmm6AL9UhNX/f852Bslw+ww0gOW4WqkpchGVwvfr1RJQKOMlzfOlLJbdbC0Da/Urce+2rcot6731vThAs5sYbgUcfLb+PFzCSatjmzGrdLAzDwCVwSCk6JFW3HSX1dt6zGAwS8XGCilLLFmscXkv5nvU3cokF5p1DAbz72jX43M+PICFpEDgOimYg0OFqyHgjFM923vM7gVAoJwDlC0fpNOD1ArfcgqEgEaXcX/sKICqF21rbDw8D//7vuSe57jpSmp9OF5bwA6S5z6lTuf//6Z8C+/eX3tneXkReSZYaOtwi6Q79xBOlt81kCpxmsssDye0FY5LzRHL76neatTvtNUOhNIxrNnThqVOzmEkq2Hs+gsvXzh9gHqmgdM9ic5+PiFKhBG7a2rvo9q1yP5ydTSGj6vA6OKxZYNLhcwoIugVE0yrGo5kFreT5EzsHz8Hn5OF38TVN7PwtKd+znFItDjrP1qHLmlHRhccKg/c4qhuQeevsSHR+Lo1oWoWDZwus6dsH/Tgzm8KRifYTpayb2XNnw1A1w15BmopJWNftacub2UoRTFrFSsoZe/7sHFTdxGDAibVd5a/7m3qJKHVyurL7WLUo2bK2WkOcrWukuoDFuVH3ViucnGFQ8/m37inLLuic48iXc+GgXLmjA+ZrX1tZo4d168DedRc6x2P474dP4vBEDBzLwu/kEZc0aLqBnR6ROAWGAsCPflTw588cnMTjJ2dx3cZuvO7ivLy1zZtLhvoDAEwTj953GDBMJGUNwXXrCvPhikU0T971v6uLlAWWy4fLz3ETReBb3yrbOGF/htwnBwIu4nr6sz8r+fympmFUHICsGZiIZUgQ8c03EzGw1H7kd3e1usMW5cAxDINt27YhmUy2fbRENVguKZFjahK53SIRpdJ5YeeWU6qnAU4pgOTlWAtflOWF5XKqNL8un1zVQ959StNsQUgMR7BrdQc6PSKuWNOBo/9xL4IRDZu4Y4CmFDqE1q0D/vAPc4/zu78LRKOFApP1/RVXYPqz/wqAdFbHzu3A7Gzpndy9m4hSWQPCmnv/C5gqI8JbWYoW8TjZh2JEcf694PLLSY6o200cuS5X7vvOzsLyvT//c+JQtbZzucg1Ofs3+U6z//O/Pk/GxSKHjKRhMpZBp3X/WObjtYWgV5ILFKfA4cYtvfjlwUk8fGwal64Kgs+7sSmagRNWGHiJDnXFbO4jg47zc2lkFH1BO3Er3Q9Hp8hr2tq/+ERruMOFaFrFWKS8KFU8sTs7mwLDMPC7BPT7nVVP7FrRwtkWpdrEKSVremWilExumtU6pbzZDny1OqUOjOXKP/MHg9sG/PjFy5M4G0613UDMupk9eyaMuKSi1+9ARjEwFZeg6AZ6vI62upmtJMGkVRSGZpJVbZaxuiddODljumHi2TNzAIBrN3YtODHd2Ete57lwuiKHbLX7YWlJYp1OqXKiVCPvrbq9WFH758ta59AMc1nkTTaDfKdAPKNB4FlougGfk8fvXr6q7HmyFqqqcbPmZygmJA1Bt1h5PpwgVJ4PJ4plM7tU3cBz9x8GTHJtAceVdUoxACaeHgGmEjgXThNR6he/WPz5FYWUk3o8JNw/733mdrtx4MAB7NmzB2538zNjlgrLKe6qcZzhLOrAJ6k64hnymPU6pZwCh26viNmkgoloBht7aa5UW2JlzJUoFxt+9ihcvi44rTJxSSKlvdlt2FQKl544Ae7ee4mr8uqrSVkuAJep488++Fq4dYWITEWOor7rbwXz8S/j2g3duG5TN175lT8Dp5cZj7/qVYWi1G9+U75j7+wspuNWyLmTXA/S6UIxyBKEss01hoPkmvDCjW/ATX0iOK+nUEByuQpLwQGyYGCahY/rdM5vjAIsmJGo6gYS95FmKJ0eEbjttrLbWhRnRIfi5D5/8XAQd+wauuAXattnVkVpOFet78QTp2YQTat4fmQO127IffBOhBJQs2Hg5Vr45tPhEdHrIx03Tk4nynbha7T7oZpVYdMEjmZL9yp5jlUdbhwajy+YKzW/m461esXWNLGzBJaEpNU9iK/02Njley12StmWX83AYn4dTTfslUJvlSVn+ce4WgzDxKGi0j2LTo+IgYATkzEJx6YS2LW6o+rHX0o29HixvtsL3TDhFQUkMhmouolOt9gy11G596j1ueryOjAZyyCSVjHgd6LT66jpc7Ucc6mWep/zc8bmUgrGsm2R04qOdd2ets4ZqwTr+O07H8HoXBoDAcei3WG7vA50egTMpVScnU1h2wJZitWSLyQJNS4ACLZTar7I0+h7q7VYwdZxD+Ly3q+GCbR43aNtkBQDu1Z3oNsr4pbt/Xjq1CzOz6URy5RfjLJyJqstsfZlRalm5lTmM52QYZjEmeOvYN/XdLlxbIpc2yt2HD/9NPCd75BB3saNJJvlAsca/1Qbcm7htjvwkeu71bHM6+CqzqgqxWDQhdmkgvGoREWpSjFNIv6k00To9WWPWzoNPP986ayhdJq4caxS5ulp4CMfmV+CZn3/zncC//f/5rYt7nKb5fcBvHTjG+D80JvID3Qd+PSn7d9zIJl1Nnn3CYfbgY7pcbDFzT8AmAyDjEQEqs39ZOyW3HUF5pISOI8Hq4e6CgUhqzOrxVe/Sv7Ndxxlvzd8fszuJ3O8Xp+DdMBd5P7ld/HwOXk8/LYPYPMNG7B6ASe1zeYK8hwrIJKN0nDwbFUluPkZ0ctpTNsIqCh1ASNwLG7e0ouf7Z/Ab4/P4PI1nXZZQX7pXqXCyJZ+H6YTMk6EkiUH/412P1S7KhyWgbimwSXy2NCzeJmSlSliTdZKkT+xi2dUJGUdDJMbOFY7sbMEFlU3IWtGzSv11RwbO+i8xTMGRynLbxlS2dU9lqk+T6Ge3K4zs+Qm4BI4bCwhhmwf8GMyJuHIRLwqUaoSAaJekeLgeAx+l4Dbd/bjDZcM4sBYDA8fnUa/39GSDjnl36NDGAmnMTqXzk5qyWs8G07B6xQg8mxVn6vlmEvVjH3OzxkbzbvGzSYV6IaJPr+zLXPGKiH/+J2dTUHTTewc9OP4VGLR47ep14fnzs7h5HRySUQphikUa6ohX8xSdRMiT/5ffG+VVB0sU5+z0GiAUyr/deqGWfPrvpAwTRP7RiNgGAav3t6PS1YF4XcJ+ObjZ3BwPIbXXzJQsmQm55SqoFQwD7J9pmXi8lSMXFv6/c6KxpLrusnYbGQ2VfnC3I03Av/wD0SM+rM/IyU/b35zPbvd9lgOp1q6owG5cPSMQq5LjcqTshgMuvDyWGz550oZBpBKlRd5Nm7MBVuPj5Ng/nLi0TveQTLrAODIEdIcIP/3kpR73r/4C9L0AQBGR4Gbbiq/jx/7WE6UUlXgBz8ov20olPvecg6ybIHIYzhdmFQZxLr7c3MQlwt4z3tsEUgXRRwfHcWWSy8F5/XmuqICcIo87v6/30ZPtx9vu35LzqHk8eDYnIxvP3senR7BLhPlnngc/77nKAwT+PirNxGXUzne9a6yvwonZGhGHCLHkHK4Cq4dDMNgKOjCsakExqLpykSpBhFJk4WCTo9YtQHByoheaSy/0SilKnav6cBjJ2YQSat45kwYN2zugaYbOJYtc9teQemexeY+H544OYsToUTJwURxuch0XEJG1THc4QLHslW5H6pZFTYME2dnU9gfZqD7VVxSVKpYjsGgEwwDxDIqYhm1ZHtRa2KXUTSMRoijqs/ngMjnrNHVTOwcPAcHz0LWyIS7FlGq2hVzLRtuKrQ6UyrrlKqk+14qr/NetRfzekokD45HAQA7h/wl30PbB/14+Ng0ToYSBa2WF6ISAaIRIsX+UWJ53rWmExt6fVjXTSarkbSKfeejuHLd4sHF1bCQiFbqPZqQVDx1ahaPHZ/GYNANSTUg8iw6PQJ0w0Ra0TEaSWNDj7fiz9VyzKVq1j5bOWNPnZqFpptw8CxWd7lxZiaFuZSCUELCzVt72ypnrBLyj1/AJUDkWHCsiXBawVcfPrno8SPZa3M4NZ1s6H5Z4r/loq2F/LI/RTfsRaT8e+tUTMJoJAOvg8e2AV/NpZiWU6oeIYljCkUpCok4mEuRTEKrq/HaLrdd7nRwLFYy49MSlSpxG+Xjd9buDG4EUzEidgwEF3fcA8BQ0AWeZZCUdcwmlcpFko9/HDh9mpTv/f7vk65XV16JdDqNyy+/HMlkEjfeeCMCgfa63teKlQXlrjJT08Iq+0sr5H3RaFFqaCnDzi1HEc/nMnzCYSL0WDlDxYHVt9+eC+ffv590Gi0lHGUywF13AXfeSbZ99FHg1a8uvy9f+hIRQgHSGOCTnyy/7c6dOVEKAE6eLL9tvkDl8xHHUL47KP/fq67KbdvZScrsikvQrG37+wsfV5KIKyvvWh1PK/jnB46DY4GbrOs/ywL33GNvY6gqTu7Zg00lOsU6BRajmy+B4ncAWwpdRcdDYQBkvmgbExw8tvaTXOJ95yO4bWdp99ZiWCHnvRUK4Ba2KLWAAWEpmMs6pTrc1S00rGSoKHWBw3MsXrWtDz96aQyPHZ9Gr8+B09NJhOISBgKOBcPAi1nb5YaDZ5GQNEzEJAwVdeHLuYpYnJ9L24OVWEbF5j5vxe6HahxXRybj+PHeMZyYiuPwFAtHNAqOI/W3i03sHDyHPp8TU3EJ45FMSVHKmtg9eyYMWTXAc4wd8lhrNwS/k8dMUkFCUqseINTiRmubTKmskFdJZ6laO+/l/02yyhJJ3TBxaJw4CMuVAQ0EnHZA/qkKnBaVCBAA6hYpIikFZ2fTYBjg0uy+syyDazd045cHJ/HUqVlcsbajYZkvC4lo2wf8ee9RD1KyjnNhIoTohom4pMGRlLC534tYWsXWfh/Sio4jk3GEkwp6vApCcXnRz9VyzKVq5j6zLIPXXzyIh49OI61o2NznQ8AlYrjDwOGJOASeBQMGsmbAwbMNsYovdUliuYy/fp8D67o9FR2/DT1eMAyZpMXSKgINGjBaTqlaS/cAsqorcAxU3YSqGUD29mDdWzWHgbHsJDApaxgJp2ouxdQbIUrlO6VKlHKsRKwukNsH/baoyDAMdq/pwK8Ph/DiufmNZ9S8cvVqnVK5cvXWlO9N5jmlKoHnWKzqdOHsbBrnwqnKx0AMA3zlK8DICPDLXwK/8zvAs8/C7O3F0aNHAZAxWS20Y/m3VXZXa/meyy7fI++r2SSZIPd4KztP89D1gvDpoVgCg6ePQFAkSJd0wtnXQ7Y7ehR45JH5olEmAy6ZRCA/x2zPHuAzn5nvTrK6Md57L/D2t5Pvf/tb4K1vLb9/nZ05USoUAr773fLb5odj52evOZ3zhZ6OPEd8fz8Rs0qJRy4XcOWVuW3XriWd1koFYLtcRHCzGBwkglsluFzARz9a2bYMAzjmf77szns8V9OYsFzVg2madlZxsTv/stUdRJQajeLW7f01fb5qFVaHOlwwTRLNsaXP17TPeDQbct7hEZf0eS4kqCi1ArhsVRA/fGkUT56axbNn5iCppCPH5n4vjkzGK16V5zkWG3o8ODKZwImpxDxRyufk4eBZnAglkJDIjVDgGEgqmQQNBiorF8lfFU4rOs7PpaEZBvxOAX6ngB6fAyenE3joyBR+vHecrJg7OYgM4ORZTEQyFa2YAyTsfCouYTSSLukaY1kGb7p0EL89Po2EpGF9twcMwyBZRzcEry1KVb+ymX9sVN3EqekEeBZY3emGU+RLrphrev1lGo3AypSSKhClknlOqWqxSiSVKkskT00nkVZ0+Jw81neXFkMYhsG2AT+eOR3GkYn4gqJUwQS6x4PZlIKkrJKgfCeP83Np/OtvT4JhWIxF0ljV6YZuGADYqkWK/aNRAMD6bk/BJPvytR34zdFQNgsuaTcsqIfFhLY3XTaIl8eiME0SGq9ouYmC18lng7aB379yNX68d9x+P3d7REzEJOw7H8WOocCin6vivDdZ1RFOyej2OiHy1Tkzm0X+PgPAmZkkFM3Ahl4vBK7x+xyKS9g24EcoLoFjGIzMpuAQWNywuQeKZkDWDHz+l0cAhoR/11NK2IySxOLrXzi7Etnnrzy83SVyWNXhxvm5NE5OJ0q6VmrBEttr7bxnIXAsVF0vyKjyOXnwHJMd8DPwOXkkZQ0zCQUekYdb5KsuxWyEKMUwDDgW0A1A16kopekGXs42yti1Oljwu11rOvDQkRDOhdOYTkjo9eXEAavTLM8yVbdo97Wgo68FWZgj7oX+CrJJLdZ0eXB2No2RcLq6zx/PE6Hila8E9u0j5VHlWqxXSLuWf6cXK98zTRIuLQi5jgNTU6QULJPB4KlJbD8+id7DLPCiG4P7z+HM7leh25dNCvr1r0kZWLGLyPr61rdIlhFAcn4+9rGCp3cB+Ej2+8mNP8HA27PllE8/DXz4wyV3mQXgye/qmEwCL7+8wEHIy3vt7AQ2bSLh1sUuIbe7sFPjtm2k3LNYPLK+X7cut+2VV5LncThyx7Eca9YA3/72wttYuN3AdddVtm2TsaoVao0Psf6uuOphJiEjklbBswzWdxfef7f2++AWOcQzGk7PJLGphrGo5ZRasPyvBHFJxd7zEcQzGo5Mxkk8R4nPeKPFaat8r8NNRalKoaLUCuDIZBwj2ZINr4OHyLMQeRZzycrKHfLZ3EcsmMdD81tqDwVd0AwTY1nX0foeL4IuASenk4hnVByaiGP3mo5F3VkJSUNG1aEZMmYSMqzFr4wiIxSXYZgmZFXHNx4/A0nVsX3Qj1BMAsOQINtNfb6KJ/OrOt148VxkQVtnWjGwuc+P8WgaAs/aE7tauyFYg8haMo+sFXPRx+BkKGFnL8Um4uj3O9Hnd0BWC1fM7aDzGjtCNQpH3o3MXORemLI771V/08wvkUzKlZdIHhiLAiAhgwu9Z7ZnRaljU3EYhll22/wJ9HhUwkRMKvi9qht47kwEYAC3yOPUdAoA4HFw2DHor3iSbZom9p0npXuXFU2EnAKHK9Z24slTs3jy5GzdolQ5p49LZNHpEXEilMCXHjiOpKzB5xTsSWunR0SvzwmPg4dumBiZTaE/4CroMqIZJjSDdKm6YVPPop+r/Lw3RTNwdCoORTMxm1Swtd/flkHe+W7SkXDKXr0+PpXAtgFfQ/d5LqXgmdNhdHpEfPzVm2yXqzXYCiUk/P0Dx/D82QhM08RFw0EMBISaSgmbVZKYf/zOzKRgmkSwscTrSo/fxl4vzs+lcWo62ThRynZK1S9KAbr9eACwptMN3TARy6jo8zmwpc+LUELG6FwGI+EU3CKPK9Z2VuXYtZxN9eZA8SwL3TDKOqXa0YWyVBwPJZBRdfhd/LxJmd8pYEu/D0cnE3hpJILbL8qVsOR33mtmuXq9JGQNaYXkbFYzUSTv0xmcC6eqf1Kvl3Tse81rgH/8x9IdsSqk4dctwyifTbR7NymjAoBnnwUOHCgUhPK//9KXbFFqww++Bbzr3nmuI2Qy5PkOHiRlYwDwjW+Q0jQAO7JfFjcCOPKFLejxXkN+cPgw8J//Wf615HdAcxadW6cTcLuR4h3IcCJmJRP2u3njRuJoKuEO0kURcV/eGOSVrwQefHC+wJQvIlncdBNw4sSipwAAsHp15WH4PF/oWloBSFpW8KzRhWcJ54puFFQjWLEw63s88xZneI7FxcMBPHtmDnvPR2oSpaazTqneKpxSh8Zj+I8nziKeUSHyHHq8DvAsO+8zvhTidMRySlFRqmJW1idxBWJNIjXDxIDfibRqQDfIRWXHoB+nZ1JVlYts6ffZNsjnz86h2ytibZcHim7gv589B79LgEvg4BBY2xo6HHThcEbNihIMfrx3HG/eNURW7ksMViNpOSsyMRA4Ft1eER1uEXGJdJiJZzQomoHzc2m4RR77R2MAyIC4wy1UlbEx3EEcC6Nz6ZKlXpKq45FjIXR6RPzBtWvQ73fWPbiuZxBpudGOTcUhqSYEjoHXwSOSVjEZkzAZzcDnEmwxR9cNhFMKFM3AWCSNoEto2YTAkb1JGSb5WoikTI5NLU4pgBwnOakgKWno9i5+A1N1ww7/v3iRG9C6bg9cAoekTFx8a8u4qqwJtCLqtiDV6RHAgIEJE7phYjw7OAi6yc/TioZUNmuj2+uoaJI9FslgJqlA4BjsGJy/79du6MJTp2dxMlu2W+0qUz7F7qSkpGEimkZc0uzzmpY1cByDgIs493wuoaDDV35e1Poeb0GXkZFwCs+cDuPUTBJxSYV/gVIWK+8tKasYncvYjixJNXB8Ko7hTnfbBXlb+zwym0Y4pdih2GlFx8lQEoNBV8P2+cHDU9AMExt6PNja75t3bevzOeHgOeiGCbfIYXQuDU+/r2qXXjNLEq3jNxWTEEmrYBhSVm5RaRbZpl4vHjk2jVPTyYpKfCsRVtQGiVJitvxPzXMePXk6jKBbhEvgwHMs0oqBXp8Dc0kFE7EMdMPErTv6qjq+tlOqzpJe67NtZRfm044ulKUUyazSvUuHgyUf8/I1nTg6mcDe8xHcuqPfFgRznfeqLyXNjSfqF7KrPTZT2ftat9dR1ft+TZcbgIkzMyk8c3oWfX5ndedhcPdLteYAAFEYSURBVJCIOixLQqoXwjQLA5EnJoDZWRjJFF565CjWTYRxgwtwyBIEWcJzt74Nnl5y3Tr15a9jR+osmGIxyBKQnngC8Gfd0n/yJ8Ddd5ffj9FRYHiYfP/975NSxHJ8+tPIKGRs6o6GyWstRyZvQbW7mwgyLhckXkRIY8G53ejt78CxmA7N489NkK+7jnRpKyUGuVzAJZfkHvdd7wLuuIP8zum0HUXPH5vGg0dCuGxVEBdZ295wA/kqwjBMnA7FcPiRx7BqNoWNfQGw/f2FGUiUpmCV3TlqdPVaC72miYJqhHKlexa7Vnfg2TNzODwRh6TqVTm1DMO0y/cqHcPmj02Ggi5EMxok1UB/QCwYm5imia89cqrhi2pW970OD82UqpT2Ga1TloT8SaRmGDgRIuGuQbcItsrwcYBMgI9NJTAVk3B2NoVOj4i1XW4wDMnBGAg48ebLBu0g2VCcDERv2tKDjb0+HJ6IYd9oFIcmYtANE+fnciUja7vc6PI4MBWX4BI5xCUNOwZ8CHqIqNDhEWGaJo6HEljb5cZYJAOnwELWTHvcEczmQlW6Yt7nd0LgSK7KTFIusNQDwJMnZ5GUdXR7RVy1rqsh3YWsgWe8hkHkmk43GBYIxWUEXQI29/nhcfCIpRWMhFOYTijgOQYPH53GeFTCI8em8eJIBLph4u9+dQyb+30tmxA4eNYeGy7WgC+ZdUrVKkp5HDxmk0rFbrTjUwnImoGAS8gOmMvDsQy29vuwbzSKI5PxsqKUz8mDYxmcDCXBMAz6/A6syXMyJCUNDMOAATAQcMHr5DEZy2B0LoOxSBqdbgEZxVh0kr0vW7q3fcBf8ibf4RGxY9CPQ+NxPHlyFm/ZPbz4ASlDvlMlFJdwfi5tOxmdAos+nwMJWcWaLg+mYhL8LqFgwl8qhy2/y8jFwwGMRTIYi2TwwMEp/O4Vq8ruy9ouDzb0ePHwsRAElrg/N/Z6cWYmhbSi4+XRKF61rb2CvNd2eRB0CXhmMgy/U8DaLg+8Th5HJ+OIZVTMpZSGhI+PRdI4MBYDwwCvvWigpOgyEk5hPJrBJavIMZdUA0cmieOy1++Yd28oN2G17jH9fifCKRmhmAyBI+eUb3BJ4touD9Z1efDrI1PwiDwGgy470LeajL9VnSQfMaXoJfMR86lUWFG1XNB5PViTe0vkOhdO4cHDU+j0iPjwzZtwbCpu31t9Lh6rWDd6/U7sPR/B5Ws6KnbE2qJUnVmD1tMVa1Lt2IRgKUWyjKLjeNYpcGmRY9ViSz/JM0lIGo5Nxe1FhHynVLXY5XuytqBzdzFqOTZW6d5AFaV7ACmVPzaZwGRMwkiYjCOrPg8lSq34668n3cnyHUqSRH5mXQM/9jHgRz8CC+APSjzsC698PUyPFwMBFzpeeBrMU78ovw+pVE6UKgqDhigWOoD0vFKnSy4hpYelQq3dbqC7G+kQWSRLve0dwOteXTqXyOUiYdYWH/oQ+QIQCqdw92Nn0OUR8YZLB/G9p0bQ53fk3h9XXlmYgbQQxa6lLFa+6vgiYefWe+vkVAKT0yye/8UxbGrhWHSlU2/5nsCx4FkGmmHa4pKk6jg7SwTico784Q4XenwOzCRkHBov3fChHHNpBZpBFuIrDQ7Pn//GJRXRjIbxaBozCQk8x0LTDTx+YhqHJqKIpFQMd7ggazpEvvoIjWJkTbcrWahTqnKoKHWBk1/iwrGcPSDqzgavVdt6/asPn0RCUiHyLNwiB7fI4+Gj02AYBpev7cAHb9yCVZ1u3Lq9v+QE5tR0El975GRWKDGwYzCAgYATk7EMHjwcAs+xuGg4gDddOoSXzkUwk1TAcxxcIhnQTsYy6PE68JZdw/jv584h6BLhEFjEMwpmQwl7QF7pijnHkuDyc+E0xiKZAlEqIal48hQJRHxN3qpmvZC6ahXHpxI4M5OsaoXw8VOzcAk8HAIHUWBhmlYrbhYukcPqDjcGOlx46XwU3372HESOTNZ5lkHQLbZ0QsAwDBw8i7RuQFlElLKCzn11OKWA3Ar0YhwcJzkgFw8HKiqf2D7oJ6LURBy37+wv+TerO0hGVFxSMeB3YlVe2ao9gc6eg4PjMWx0eNHnd2I6LkPWDEzGMkgrxoKTbN0wcTBbdnjZ6o6S2wDAdRu7cWg8jv2jUbxmZ39NAfIAOa4Cx+DoZBzp7Ens9IgYDjrhFDkkJR0cx+B3Lh4oyIvK//wulMPGMAzeeOkgvv7b09g3GsUV6zrtFuLztyXOSMMAkqqKi7qDcIs8VnW6cGA0Bo4jg6a0qtf8ehvN+bk0DDMXFOoWeTh4DkNBFw6PxyAIHDq9QiWdjstimiZ+dXAKAHDpqqA9cSjGujcMBFzwOQUcn0pkOyBmMBHLoMfjQEbTkZC0BSeskqpjJkFKrfPdPYcn4thURYOLSmBZBj1+ETzLQlJ1+J2kc2Ml7618OJax8xFPhubnI1pUI6woDQg6BwAhu3qtaAbSiobvPT8KwwQuXRXA714+DNNEwb3V7xLw9UdPY3Qug/v2T+COXUMVXcMsUaqerEHDMJGQNMylFJyZTaLXRya9xe45VTeRUTR4HDw29ramCcFSi2QHx2PEkR5w2plxxXAsg8tWBfH4yVm8dC6SJ0pZTqkaRCkHD4YhroWUotXktqr12ISsPKkq3LfWc8UyZBzpd/IIuuoYm0xN2d8yhw6V3kaScoHWXV1AXx9k0YmQxgJuN5KciDjrgCKIODOTxBo3aR7w7EXXY/PVF2Ogv6NQCPJ45odgf+5zwF/9VW6bhcoK3/Me8rUAGWUOAMBv3QL07K7gQBSSH3RuOUwqcY1Xw2C2A99MUoas6fZ9LZ/891af3wHNCQTcQlt3yL3QqVeUIn/LIinrtuvq1HQShgl0e8Wy7zOGYbBrdRC/PhwiiyhViFJ25z2fo+IS5/z5L8sS8VQ3gIxhAKoBwzQRTSuIpFV4HDzOz2Wy+0nGlv1+JwYCzooW54qJZvOkXAJX13FeabTHSJ2yZFjlDhlFh9fJY3OfFxnFsMOgKxVv8geZW/p8OB5KIiFpSClEJU8rGtwCZw/u890P+azv9sAtcjBNE26Rz7ZPVhCXyIBVUnX4HDw+cMMGu7NevuPKynHaPuDHs2fDODgWw8ZeLzrcIpLZz321XfFWdbhxLpzG6Fwau/Im9o8cm4asGRjucGFHiRD0Wjg0HsP/PHceL52LgGNJcG2lK4T7zkfw4GFSSvihGzfg5HSy4NhcMtyBO3YNYSDgxIf/Zx8kVYfIsfbKu9/Fw+dsbVcyB88hLWsVOKVqDzoHCjvwLYas6Tg2aXXdq2xwtKnPC55lEE4pmE7IJe3Ej52cQYfHAVdcAscxSMv6PHHGci2NRzO2gDMYdOJEKIljUwnsXCTw+0QogaRMwtk39ZZ3oazudGO4w4WxSAbPnQnjVdv6Fnx9hmHi7GwK55LAWctqzzJwChxSsobJmJR1lXnQ53cAYAo+d7ds78dQh7vs53eh9/pwhxtXru3Ec2fncN/+cXzk5k0lBeFHjk1jKi7jouEAnDyLcEqx895u3toDWTMAMPj3J87gfdevh1vgFh1MLGVpz2xSxneyJc5vuHQQkqLj1Ezu2FyzoRuybmAiKuPho9N49faFz1E5jk4mcGY2BYFjcOsCj1F8b9gx6Ec4pWAymkFGNTAazUDVDfx03zjOzqaQkrWCCeuB0Sj2n4+iyysims4tVPT5HZhNKpBUA0cn4+ivsMFFJZyZSWIiKmPnUABeB4fprBhWS8bfhl4vjkwmcGo6iRu39M77faGw4oGsmWCZ8mWJdvleHUHnhmEinlERTsoYCafwwsgcYhkVPV4Rb7yUiE0Mg3n31t+7chXueXoEL56LYLjDhSvWdi76PrZEKbZGBdQSKp86NQtJNRBJn8DOoQDesmsYbpHDqVASXgeHU9NJRDMqTJO4ZQcCTvT5axvo10ozSkytXL9LVwUX3G732g48fnIWx6YSiGVUBFyCLdguVK5cDpYlJfwJScsev+oeo55jU23IefFn6vRMGilZx9ru2s+D2dePob5+qOk0Jr76r9iwdgisp8iBlN+B7O67gbvvxvhMEp+9/zB4lsFoJAPTBFgmGy0wl0aXx4FDl9+AzBt2AJU4PIPBiva3UqyueW6xtuumlReUUXVMJ8h5qrZr2WL4nAL8Lh7xjIapmFTgBAfmv7dM00SEIeMzX6/Qlh1yVwJ2970qmyrk48xGWFgC12KlexaXrerAg0dCODtL5n6dFXamy+VJVS6AF49xLlsdhKIZ0A0Tmm4iIalgQO6F/QEnDBNQNB1JWcdcSsVcSoVLZGEYpJNeNW7SOat0r0HdfVcKVJS6wFnb5cHGXi8RbxxecCwLr5NciKoRb/JtkB4HB47NZl7oJlwih019XoxFM4uWaIyEUxiLZHDp6iCm46RTQ1zSwDAkKN3vFDAVJ5bunUOBgryZ4sHqW3YNYzxCJvN9fgcMk4gZobhcVVc8K1cqP+x8Ninj+bNkpaqcE6ZarBWjUFyCyLNwCmzZFcLiQbphkps7AFy/qRuvvWig7ED+zEwSPMdg55AfMwkyOSS6FJnQtLIrmXUTzGvIVhLLKVWrw8VfRUeiY5MJKLqJLo+4YBlPPg6edO84NpXAkYn4PFHqzEwSDx+bJiHTr9qEQxPxBcWZ/MBvWTXAMsTye8lwcMFJttV17+LhhcPZGYbBdRu7ce8Lo3j2TBiv3NxTNgOknNV+x6AfL4/F0BdwIZpR4RZ5eESerDwp87tRLvb5XYhbd/Th4HgMobiMZ8+E8YqN3QW/f+lcBL85Og0A+MNr15achM+lFfzbE2cQisv4wi+PgmWBkQU6zFU64KhlAp1WNHzr6RGkFR3DHS687/p1EFh23uO8MDKHn+2fwMPHpuFx8Lhq3eLiQj6GYeKBw8Q5cO2GbgQXsI0X3xsYhkG314Fur4hISsGh8Th8Dg5Pn5rFXFrBmi43GAb26mJCUhFJq0jJKnp8IhTNwMXDAXAsi16/E6emk4ilVRyZiGPX6sUbXCyGJZAB5Jr8hksG6xIyNvX6AEziXDgNRTPmBbNa97wurwOnplOIpFU4eBbDHS50ecV519F6M6Ws99/jJ2ZtJ61DYLGp14ePvmrjgqutm/p8eM2OfjxwaArfemYEP3xxFKGEvOD7WKvDKZXvfnAJHASOhdfB4+BYDCOzKWzo9eLUTBIuIddynGNJ/shIOA2eBcAQUT+tNLdro6IbmIhmIHIshjpcVWVQlmMupWAknAbDAJcsIkr1+pxY00UWwvaej+CmLb11OaUA4payRKlqKc4JnI5LkDQdw0HXghEPmm7YYkel5Xv5z0U+b2mkFB3nwims6nRXfR6sz8yNf/NTTE7P4K/VHmxK+PCWTYu/d9Z2ebCu24MHj4TgFjj0+h0IukScnE5iKiZhLinj2o09LSn/Nk0z132vxjBqV17uz1jWAdJoUQog4/Z4JoHxaGaeKFX83kpkVIRlYEA3IAqlu0VTlh45m2XqLOFsqxS7A5+m27EqALBlkQDzgFvAhh4iQO87H1l0gdRiJp4VpfyVv4eLxzg8y4IXc/Pf2aSMy1Z3YDouIegW88waGqbiEsJJxc4w/tfHTmM2oQAMMBx0L+omtUPOKxTdKAQqSl3gsCxTIN5UU0qTT74NkmEY+F0CIikVbpHDln4fWIZBJJVadFCUKxkREOgTMBmVkFI0DGWzQXTDxHRCth+nnOMKIF3SrMn8yakEZiSAT6tVr5hbZVWTsQw03QDPsXjoSAiGCWzp8zbkZpm/YrSp14t9ozHoBinlKy5nyHeIyaoBhiHHbVWnG6/c3I3bd/YveGysY7y224N+vwszCblgwtXKrmSkA5iK81KhAycf0zTrdkq5siWSJ0LlSyQtcWHPwUnEMypu2Nxdlfi4fdBPRKnJeEEnyqSs4fsvjsI0gd1rOvCW3cN482ULCxnFAk5S0vDzlycQSsiYiGZKlmBJqm6Hsy+2Om89R+DQFKJpBQ8cmsTqTs+8fSlltfe5ePz2+AwePBzCzqEArlrXiT+6fh1+eXByURfUQp/fhXCLPF6zox8/3TeOBw9Pwefk7U5rmmHgJ1mB9obNPbhqfReA+e6Rbq8D77tuPb7wq6N47swcABMXryrdYQ5AReUrtQhXbpHDI8dCmE0qCLoFvPuaNXaZQ/E+X7W+C0lZw2+OTuNbz4zgf54/j2haqXiy/uL5CGYSMjwihxu39Cx4jBe6N8wmFWwf9OP6zd34r6dG4BZ5RNMaoum4XSoEMOj0iHALHP74xg346d5xnJlJ2Y8zFHAhliYNLhiGwQ9eGsNbdg2DZ0s3uFiMR45NYzapwO/kcdvO/prfWxbdXhFBt4BoWsVIODUvByOWUTGTkKEZGZgm2T9ZM3B6JoWpmITBoNPudGoYJs6H0wgnZUTTStXZPvmfO4+DOIk1w8RcSsF0ggyOy5WEWbxyUzdeHJnD4ydmoBkGLl3VsWA3RTtTqkpRqtj9cHgiDl3RoRmm3QRlZDYF0zRhgggWvT4RIsdhJiljMiYhJZOB/t2PncZcUskuSi0+0K+VhKRBUnVEDBmhhGw32mAYYDDorvueeCC7OLChx4uAa/GV8SvWdhBR6lwEN27uycuUqm1V3efkgVhtzVPyx3ZTsYxdwpJRdGzuK98RdCZJjqNTYCt6zcXPxbEMhjucGItICMVlJCUNa7s987oHl6PesjCWZdDlEcExDNKqjk6PCK9DQJdHxJnZJJwChyvXdbTEwSNrhv0eddcoSvEcC5FjoOgmJrOlTz0NLt8DgMGAC0cnE5iISvN+l3++o2kFJ0MJJGQGJ6aT2DbQnh1yVwKNKN+zQtIl1cBUXEI8o0HkmLIZq/nsWh3Eqekk9p6P4OatvRWNu3Ple5U7pSqZ//7BtWvw033jBYtzLpHHum4vhoM6DozF4HdyODebxlxaQdAlYJoj9/+F3KSRFLkW0zyp6qCi1AogX7yptpTGotgGuabTDb9TRbdXBMeySEpaRSUaxY8zUDTZrrScMP+1bR/w41QohgceCeG2m7eWFDoWosMtwC1ySCu6bUd/ORsS/JqdjekMkr9iJPCsbRPfNxpB0CXCJXI4HorjoSNT+PHecXtyzHsZHByLIZpRoOoG/uTG9YtewIuPcW+Ri6faY9woDo3H8NvjMxgJp8BrLEbKhF1Kqo5wkrze6YRUdcfAQ+MxfO95UiJ5YIyEkZdzxZyYSuDkdBIsQ0oghjvcFU+CSEcz4rCLpVUE3AJM08SPXhxFPKOhx+fA71xCGiVXMoEu3mY0G1a95+Ak3nvdunnn/VA2w6TX56jI4UXy05x45FgIT58Oo9/vLBA6tg/451ntp7OrrAzI6pphGHj31WvA8yx2re5Y0pKbK9Z24BcvT+CZM2E8fTpMbu4MmXit7vTgpi09eM2OhVfZujwiRI6FZhjwiDzGIxls7ecLBhM/fokIXIuVr1TaoaVYuIqkyaR7S58PH3/1pkUnnjdv7cWxqTgePzEDVdOxYyiAgW5P2cm6VWp5Og48sW8CPMfh5m29FQ04F7s36IaJLo8DfX4HphMywikFpkkcjINBJ3xOHiOzaQwGXCUf58YtvdjS78PLY1G8PBbD0cn4vAYXlbhiJmMZPH5iBgDwhksHG5LRwDAMNvV68fzZOTx5chYZRbffxzNJGXsOTtlliZ0eAas73YhlVEzGMkgpOo5MJsCzDA5PxvGz/eN49kwYswkF5+fSmIxJFTt9ikWekXAKKVmHwDFY1+WBaaKiEhfTJEKaaZrwiDymYhl0uIWyA+ecKFWds6vY/WBdlqxJqUvkYcLE1n4/ErKKVVk3EkAai/R4RRwYiyHo4jEaJgP9DreAaFqBU1h4oF/JsSx1TZpOSJjK6+hr3e/HIhKcPAeR52q+J5qmWXHpnsXOoQB+fmASs0nisEpYGYq1OqWqcAbP/1syXhiPpjEVI24EhgFiGc1uYFDq2OSHnFe6mFM8NhkMuuEReZyeTSGl6Hh5LIqgW7Sfq9z5bERZ2OGJmF3+7RFJKfBsQoGDZ7GlzwevU8ALIyT3ppFZTJU4bZOyhnhGhQkTo3Ppmu+tLpGHki2dBZbGKWWHnUfmh51b5zsUz2A8KhGhjQFSso6T00kMBRrXbZZSORnFEqXqK98DyHj9WLbBw4Zeb0VO4e2Dfjh4FnMpFefC5TtYWxiGiZlk9U4poLL5L8swZYWrdd0evPmyIXzj8TPZMn0Ts0kFcykFqzvdJZvCAPlOKVq+Vw30SrBCqKeUBphvgxR5Dn1+yx5ceRlgqZIRi2qzoCxYlsG6bg/WeIF13dXfvBmGwVDQiZfORfHbE9OYiGRgmiYuW92x6Op0peSvGAEMhjvcmIploOgmwikFhmkiKan42qOnoOkmdg76wbEMjk4lYIKE+zkFDvfvn8TFQ6XbTVssxTGuF2tVcyouQeRYeJjSq5qHxmP47nPn8NK5CAzTxOd/ebSqUg7reSZjpETSJXLzSiSBnCvGIZCyE55lcHomia8+fLLi1Xmfk0xUR2ZTePhoCBt6vTgeiuPYVAIiz+L3rlxVMvizUl6zox+HJ+I4PZPCsakEtg0U5prZ7cdXByuaFBwaj+Gx4zPZyR+PTo8IgWPtY/OWXcM4FUraGUEJScFYmoELOgSexUVDfkiagfORNNb3eOt2qizG4Yk4zs6mMJdS4BZ5BJw8zoTTiGUU6IaJD1Yg0Nod5oYCOB/JICXrODwRh5NnwTAMZE3Hw8emwYC8H8/OpsAwJGeHZ3MT2AOjEUzFM5hNytjc5wXDkIHXYsJVxCCh9RmFhEHPlMkfy8c0gdlsF00HL2A8moFb5OB3CmVdlSenEjg1wcEUiNj4e1eW71pYzEL3hjMzSTgEFgA516s6Dei6AadIrmP5ixHre7xlH+fKdZ34f785gcdHItAMAzsGAhjodlXkijEMEz/ZOw7DBHYO+e1w6EbAMMDe8xE8fTqMBw5NQeRZOHgWDoGF3ymgwyPAMExs7Sfn3OPg0etzYDyaxslQEm6Rw788chICR46Bz0kEz2qcPsUiD58ViZwCi3U9HmQUo6ISl5FwCmdnU7hoOICR2TSSso4ToQTWdXsg8ty8gXOtQeeF9zKrXFEHzzLo9onocouYist446WD+NWhqZID/dWdbtxx2RDufvwMGIY0JJiISZiKS9mgcGfNpVz5LsbhDhcCLuKGI+5ZDdv6fej0ihidy2AyJuH0TBIukccVaztruieORTKYSSoQOKbi7EkHz+GioQBePBfBC2fnbGdw7aJUdY098lnb5UGHR8TTp2bhdwoYDLoQcAs4MZXAXErBbFLGTVvmdwS1Qs4rbc9uPVfx2CTgFrFzkMep6QTGo0QU2jcaQVxScd/+iZKuVLfI4WQoCY+Dw8mJOfzmSx+AYeh49+e/Bb/Pt+h7JyGp+OleUgr8pksH5zXmGQq68O9PnsVYJIPvPHMOf3LjhoqE8MUEp0qctofGY/jW0yN46VwEYIDP3n+45nJWl8AhlsmVhi5F4LK1IDadkKDqRoEosbbLgw63iGdOz8LnFNDpERA0TSRYBrF0tttsifcWpTYqjRaQNCtTqv7yvYyq40RWlCrXda8YB89h51AAL47M4YHDU7hmfdeC+xtJK1B10nmvswbn0WLz30oW50SOxeY+HyRVx1gkjVhGw0g4jVhGxepO9zyHZ8TOlKJOqWqgotQKop5JZKPKABv1OI3k0HgMT58O49B4HPvOR2CYQNAt4I2XDDbsOYpXCPsDTvQHHEhKOiJpBaG4BNMEpmIS3CKP/WMxCBwLRTMgcAy29vuh6mZFg/R2O8b5q5oDfgemEwpgzl/VtCb0lqDkLiEoLTQoKy6RPDAWg26Y8Dq5sq6YE6EEyRQJkklQtavzbpHD3vMRPH92Dj4nj1Bcht/F43+9Yl3dgmaHR8QrNnbhsROz+NXBSWzu89mlNtG0gjPZ9ruXVbA6bx2bWEbFhh4vphMKZpIy1nZ50O0VcWqGdMWcTcpwizwYhgSXGwbgdXDY1EdE0pHZxUt0G4G1vxlFx8YeD2aSKs6E0wCAPp8DDoHDffsncdEiAm1+hzm3g8exqQQk1bCDPg2TBEuDIU6ylKzPewwrQ2kknIbHwSMuRSFwRDzgWAYsQ/KOHj8xjYPjUURSCgaDTkTSCibjMgSOxabhAGIZraL31kg4hVMzSVw0GMB4LIN4RsOxqSQ4hpSzciyDfaMR3H9gHHsOTmEupaDLLcA0AZFjoeoG/uXR01WVPpW7NxRPIoW8xgmlBO5yj7Om000aXIC4eEYjJH+nx+co2Y0tf3B9IpTA6FwaLpHD7zTwmnxoPIZfHJjMiZ4uAefCKcylFTh4Dm+4ZACfff0O/OdTZ3FqOleWKKkGFM3E9kE/YhkVY5EMaeCgGGAYBh6Rx0DAWfG1pFjk6fE57OBV0lWVqajEJf+9vrGXwfFQErGMhoNjMQx1uNDtdUCO58oNx6Ok3DCcqq7csPhetq7bg5Sswe8SwDI5ofKSVUFs6vMtPtBf5UVC0jAeJaLxeFTCTFLGQMBVMNBfaMJV3D3O4WdxLpzCw0dCEHgOl6wK4K27V+H5s2GEUwpEnsNgwIlYWsFkXIJqmLhlW29V90Rrf36ZLf++blNXVZO8K9Z24sVzEewfjSCW0aAbBqbjEjwiX/W9uR6n1Eg4BV034eA5mCZxjrtE4oQ8MhGHWKYjaM4pVfl9rtzYhIxziIjYH3DhwcPTODV9Gl4nj9UdngJX6ompBFZ3unFyOgmPyMFQJMRHjwMAjozHsLqfCMdymc+MaZr46b5xpBQdAwEnXr2tr+R1611Xr8HXf3sK0wkZ9z5/Hu+6ag3OR9I1C06VdDgEyILZRDSTbUtf3RiomPzSv6Uo3QNIAx2vg4ReT8Wkgi7DhyfiUHUDIs9BN030+RwIp4HBgANHJhMQBQ7dPrGubrOlaETjhEY1X6jkcRrxXNWEcOfK9+pxSpG/jaVVnJ8jY7PF8qTy8TnI2PnxEzN4+GgIToEru7+hbJ5Uj9dR87xlsflvJYtz1j1vS78PobiM0bk0ImkVkVQUQU+xwzONhKQimb3f0iD/yqCiFKViGlEG2MjHaQTFzhqeJau2imbgnqdH4HMJDdmf0u4lBl4nD4+Dg6TqWNvlxkg4DQfPIqMaUDQSeL25zweHwIHnzIrr79vpGOc7ASxLa1IhAodTJGUT+0cjCMUzCKdkDAWdSCt6dlBWeSnH/BBV4jo5NB6HaZqQNQN7Dk0CyK0gWrkNnR5H1YG3h8ZjePjodDYHhoecDUuWNQOPHJvGzqFA3cf5xi29eOlcBDNJBc+dDePaDSTwe182w2R9t2fBMGuL/GPDcwxmkgqiaRX70+RxVN1ENCUBDKCbJgJOHm6BQ1JPYGu/DxxXeYluI8jfX6fIIpKJQcuulG0d8EPRKhNoiyfQO4cCdlmEaQJpWYfAMgADdLodcIksTJMIUapuQjUMpGQNAs9CN0zwLAPTBBTNhIKcgFXcWng8Ktu/Gww40et3wS1qFe2zJS64A6Sj4shsGtGMAt0A4pIGwzSRyKj4x4dOQNFNrAq6EMpa2zs8Ailnnk41pKtRowTukXAKo5EMLlsVRCghI5JSMRJOYzyaQa/PgS6vwz42aUW3r1spmXR18jp5vO/69TV1JytFvkg7EHAirRi2yNvlEcGxDGTNwJXrOuF18iWvo1et68R/P3cOl65yYC6lIJYh12WeZaq6lhS/R50CV1DOUGm5df7j+F0iLhr042yYTKLPz2UwEZXgd5Gyvp/tH8fzZ+cwHZdxLpzCdKLycsNSQqV1DSoWKlmWqWCgbyDoJvlekZSK8xFS2nlqOgk2W6670IQrv+x4dacbcUnF6RkJsmbA6xSgGgYCLgHvu24drt3QVXAu/W4BAs+ix+fEcyNzuGxNR0XCkt0MIkQ64ALEMXbR0MKNKfJZ1ekCYOLFcxHEMxrAAHf9/EhNrhjrvVGtKDUWSePbz5TqCCrbHUGVbEfQPQen8NqLck1fpuLVhZxbLDY2EXkGn/j+AcQyKliGBCkDxFGekFSMpBRMRDNgYIIB0BfIiS0GiHNtKtsdtlQZ4LlwCkcm4uA5Bm+7fBh8mXKjgEvAnVevwTcfP4NnzszhseMz0EyzJsHpwzdvwA9eHMNkTEK/34G4pCCaBsCQyf2Z2RT+6aHjABicn0sj6BKQUQ04OK6uclZnvii1BKV7ALLXOlJp8PiJGVyzoQtruzw4OB7DD14cRdAt4q27hxHPqDgZItmvAwZwzYYuKLqJsYiER49P4+atlQVeN8KNthiNeIxKH6dR+1tJJqaFtShXj5PfCkk/PBGDYZJqjkpDvclrHkdc0iByLIJOAU6xtMPYMEy8PBZFOCljOOhaUoGn0sU5hmHQ5yfxBadCCYSyzvZjU3EkJBU/fmkcT52ahW6Y+MrDJ7C5b35MCaU0VJSiVEW9ZYCNfpx6yHfWbOv3Yd9oDADgFBhcnC2BaFS72komd2/ZNYz/fu4cgi4RIs8gmp3gWmHfteZttfIYA4VOAEklA0DVAGaSChiGsSf057JOFGtgLWYHi5VO8IrD+F0CEfesLjZGdkAJBvCIvC1IBVw5W3ulwZvWeycla+jzOSBpRMTwOnnsGPDhbIPeO06Bw6u39ZGObEencclQEFPxDB44NIWkpOGSVZXd5IoDZjvdIsIpknXkEji4BAGxDIvhDjeiGQWben0wTROjKdiuqWaWfRbv7/puD6ZiElZ3uSHyHDi2MoG21AS6K7tibJomTqWTdme/g+Mx9Pnd88pdT00nsX0ggOm4BL9LgFPgoOoGNMOAYRARLyVpYEDeYwNBF5AVttwij/7spKnS91axSLGh1wvAhKToSMoaZpIyJFVHWtHhFnnMpUmOEACs6nCDYcp3zKqFRgjc1vn0BARscgmYismYimegaCbGoxJMmDAME785GsKLI5Hs4NqJhKSC58ix+M2RELYP+BsysMsXPaMZBWnFapkuYnWnO1syl1ywC+zB8ZjtTOrxORHPKIhLGrq8ZGBe6fluVLl18eM4RR7bBnyYTcg4N5dGOCVDUjV87ZFTdmmzz0nuL9U4MaoVKqsZ6Hd4RATcAqZiGRydTKDDLeA7z5zDaCQNB89huKMwDH10Lo3rNnXj2dNh6KaJA2Mx+/FFnsWaTjcEjsFYJFP2XHZ4RNz92GmE4jK+9/x5/ME1axe8ZheH0ltulLFIuqry78MTcbtEzi3y8Lv4ml0xuW6z5cv3iifzHgeP/3pqBLJmYH23B+95xVpwzPwmBPtGI/jRS+N48tQsHDyLm7f24vAECbMXeRbd3saW05yZScLnFGDAhKyaODOTKvhbn1OAwAKb+gKYS6kY8ueXi7kxmQbCKRkA6QiWXwaYL3K/6+o1i7q8hjvc2LW6A1/69XHImo4tfT6sLcr3+/DNG/HTfeNZUdQFWTMRTpKybRMmDk3E8KffP4CUrEHkOXs8ko+qGzgwGgMY2Nd0INfJs9YOkU6eRTyjQtUNqLqxJBP6Q+MxPHUqjMMTcRydjOOBw1MIuARohokOt4jdazpwx2VDADAv+/XZs2H8/MAkHjoyDU+2hLYewalScaYa12WtzReqccbV81zF+WrlMjHzXcihOGk2EYpLGAq6anpPWGPmZNZdvqW/MpdUQUVDjwcTMRnhtIItfue8/bXiCZ48OYtoWsV4NIPZlNx0gafcPc8wiPA7EHBiMOjGffsncXomCZFj7A7rnW5Hwxt3XMhQUYpSNY3KklnqTJrFKAwf5+AUWEiqgcGACwI3P4OjXhab3G0f8OPZs2EySO/1FgSU15O31epWu/mT7G6fAyLP4txYAh1BJ1TDREJSkVZYaDpxomQ7q9stjYHKJnjFk/kt/X6kFSIWMAyDjKLB6yCCVX92lYME3+ZuyJUKfwWT2rSCiZgEhgE29njBN/i9c8XaTjx9OoxjUwl8+H/2IqloGJlNg+cYdHlFuEV+0RvdvJKbHg8Ggk44eRas3aiAw+9ePowf7x3Hqekk+vwOGCYJXQ3F5aaWfRbvL3FS5CY/lZ6nisTg3cMAgPFohR1aer0Q+dzzmqaJSEop2Vo4n0r3uZyr0inycAgcImkVl6/pxGQsg26viIxqICmpcGgmvFkBu9FdjeoVuEuVL/f5HYikVYTiEuZSCmRVx/88dx6qbmDbgA8ZVUdC0uHgWewY9GMskmnYIkG+6OkUnDCyZUtWGVRxyVyp62jxa/K7RPhdS/Merac03ikQAYJnGVJiE5fQ5RHhypbpukUewx3VlS43Qqhc6HWnZB07h/y4ZDiAX2ZLVIMuAdGMAo4VkVKIY/DlsShOhBLZkHrSEMMjcgi6RfT7HWBZ4nAMxRfu6Pvua9bim4+dxolQEj9/eQKvv2gAZ2dTOJcs7BJbOAH04PRMitxPAg6s6nBXfAytxzGAbOc6Bk6+dleMx0G6zUbTCk5PJ7Cu27vgZJ5jGSRlDYNBFy4eDuDOa9bYAkjxsdm9phOKZuL+AxP44Utj+MGLowinZJwPZ+AUWfz9r4/XNElcqHuwbpjYORBAKCFhPCqBZYBOj4hOjwiPyONcOI3bdw7gV4emcGYmJ0Q6eA4eBymtXtXpxs/2TeBkKA6PQ8DabKMCnmORlnU8cXIWu1Z3LBoJcGAsCrfIwcGzCCVk+JyklNHn5HFqOom/+tkhzKUUsCyDSHq+KMizLKJpEjYecHNwC8QdThoMmIBJOmGORoh1aiBAXNssw6Avz91U7TX90HgMvzo4iSOTCeiGidmkjCOT8YZO6HOVBqTc0O3gYJgmnj0ThoPn8PYrhvGWXUO2UFKc/Xrthm4kJQ2PHp/BPU+P4LvPnUekTLfZxd1oG/HTveOYScikM6qmg2VREN9gxUT8ZN/4oq7Ljb1emAA03Zj3GJV+vq3H0Q0TKVkFm3WVnZ9L43+eOweGAcJJGRt7vWDZ0jmVFZX7Z6+fhmkiFJOgGQaCLhF+J18wFk0rOn780hieOR2Gbpj4hwdPYOtAbS4ekWdswVPgyDGshGLX/kRMzpaZR+EWyX3qwFgUv3x5Ej9/ecL+bPmcPLq8tZey1ku5e94lwx24Y9cQDNPEp398ENG0Ar9TgMCxcAr1OR1XIlSUoqxYirM81nZ7kMio6M/a0ZeiXe1ik7t2yoJqFMWTbK+Dh18gXVsYhsGp6SSu2xhAKC7B5+Kz3dJyE2ygsgne/DB+FiKfKysJxSVcvqYTAHHFdHrEml0J+e8dkXciKZNue54lEAVYlsHmPh9+9NIYFE23BTWvg8eRiXhFq/PFx4bNTkaLX/ct2/sx1OG2w7NnJIBPq00v+2xkWH+lE+h6OrSUay1cyz5XIlK8/uIB/Pdz5yBwHDo8DhiGA6PSnP0YS9Fhsx6Bu9T5ZBgGnR4RHW4BRyfj4DkHJiIZCDyLs7O5Tk5DQRdcIt9QobdYUFqdl4MC1Ha9acZ7tNbHuWxVB65a14l/e+IM4hkWmpEr9WKY2pwYjXDiLva63SKHp07NgWcZyJqJiahU0HreKfCQVR0eB4+hDif6Ay47KN6iknM5FHThd69Yhe8+dx57Dk7hVwcnkZQ0TE6zeD6vS6xb5HBkIg4wwMtjccjZwOCuKsu/rYnZcNCNSTaDSEq1F0dqKSP/4UujeOlcBLph4q/uO4wteV1tiyfzgpfBofEY5tIKUrKK912/btGSxWs2dOFEKI5vPn4Wsqaj2+vIuq24hk8S7c+mamAw6EavzwmWJSINgHmZZd97+gTuy/5tPKPisjV9uGPXEEyY+MxPDiIuaWAYBqPZzDKnQETu0bnFRW7rPG3NZsiEUwpOZss1AUAzTIxFMjCzOaQsg2yjBA7O7L88S0ryHDyL1Z2ekgsWSUmDapByxF6fq65FDSAnFo1GMnYsRY+vsY6NfOGFdFiNZ/MaZfidAkzAFuMWyoy6ZXsfjocW7jab70bb2OuBZgBpRYOs6nDyLI6HEvj0j19GJK1C4FjE88ZdAsfA7xTg4Fm8ODKH46G47XAtFrZ+55JBHBiNgmUYHJtKIClrME0i+g4GXRgIOAs+l+UcV9b7pssr4vxcGjMJ2XbmA8QZ9+DhkO2Mi2aiYBjijOv1iej1zW/0UO65EpJGuumZCo6HJHtRdyomQ+AYBJwC0qqOfecj+PXhEMJJ2X5PdHpqE3kOjcfw38+et685Asfgf547h7fuXrXoYxS74Lu8IsJJBRnVQEZV7HiCLz14DIpuYjjohGGYYBgGXR4HBgNsywSexRyeZIHBhKyRk22VR9bqdFyJUFGKsmKZt9LtFAoyS5ZiYgcsPLlrpyyoRlE8yS7lwCl2otQywWuUK6YS4a/4vbO1qDNeI987hmHixZE5sCwpXUirJFB5KNtZqpIbdDVuDOvGW2y1b+bNv9Fh/ZVMoOvt0FKJcFXpPlflqnQUXkta1WFzIRY7n31+J27b2Y/vPnceHoHDTEqBohnwiNySLBI0QlBqxXu0nsc5OB4DyzC4ZFUQ0wkZE9EMDBN284Rajm8jnLgLve4D2ew8kgWnYTSShqwZ8DlJML3XwSMUk9AfcGIyJoErmv1W81nYMRjA1n4fvvHYGciaju39PvQ4SVfO/aNRvDwaQ69fxJmZlO2y5Vig3++Ex1Fd+Xf+xGxVhxsM0gXO6EofJ19wcgkcGAbwilyZybwXhmni2FQCugl0ex1wCRx+dXAKu1d3LOr8GAmn4RJJd0pVN21RuZYGIQtR/NnMz3wqlVn26du24f9mf//p2zfj4nWDuUmiUwDPMkhIun0sV3e64RQqE7lz54nHum7ezhh08sTtJLIsJhOko/CaLjfpDFb0HkxKGrq9Ivp8TpybS5e/3mTHdgfH6xO588WiVR0unJvLEKeZW0SHW2zYuSrIfcyKb1pWeekPONHlEe0S6IWuEaYJzCVV8CwDh5N0m/W7BHidHNbwbhyfSuBLvz6GUFzONvkg+ZLFjxGKyzBNEu7uFEhDjrSiQc12uNYNA6G4BI+DZDVqhgHNYKDoOgSOwaGJGI5NxW3XpXX8GQZIyTpOhpJw8MS1HMssnHMXiksYnUtnr63kcRwCmy3xB1gWSEgk19LqfkqyKg2MRYjw3ukWoOgmEpJW9rneeMkgjocSmIhlwLOs3S3Y4yCOalU3MRmXIKs67n7sNHQD2NjjQTSjgWUAfzZ3rZr3hHXNscL4eZaBx8Hh0HgcE9HFF0jnxRP0eLGm00BK0ZCSdcylZGQUzY4niKSzDleGlKOixQLPog7PwQBCCRmhuIROT24+uRQmhwsRKkpRViyNXOluJO2SBdVI8ifZ5Rw4jZjQN8oVsxjNfO9Y3di29vlwNpyGaZLVv4BLqGoFphrBk2WZeVb7ZtNogbaSCXQ9HVoavc/VuCpbWWpZKZW4Yn66bxwBl4ihDhcSsga3yNmfrUYKvY0SlFrxHq31cazJgKQaGAy60OkREcuodibQUi3C1Lq/QP4ExkCHRyRBunnWi6SkwSlyeP3FA3bZca3n0jBMnJ1JQeSI8DIZlyGogBTNICFpiGVUzKVkcCzgETkMdrgQdIkFj1tLKL3XyWNjb2EeSyWPU1wiJKkxkqGoGvA6OJyZTeJzvziCSEqBQ2DtTmiqboLnGGzr90EzUJWza1u/H3MpBVPZblhWCWgjJ4m1ZJZ1d3dDUZSC62NCIoLE5j4/UrKK0UgGHpG3A79riQTY2l+4+JSUNDAsbMGpwy0i/12WPxZ482WD+Nojp5Z8wSxfLFKythmHQCbzDNCwc1VYacDA5+IRSanoDziwutMN3UBB2eyC+zuTxM6hACaiGcQlDUcn42AYBppuQtUNTMYk241GXLYkc9QpkBIpgWMxEU1D5Dms6/LA5xLs45+UNcSzXVJ1g/zddEIhXaDz4FkW6WxTE7+LvE98DgEcy2AqLiEUl5CUdSiagW88dhqzSQUmTAwGrJw7DS+ORPDMqVl0+5yQVCObuSZgMOjKfpZz160JZwaAiX6/i5Q9GkBSUjEZl5CSdUzGZSiage+9cB6jc+kCd1da1vDUqVk8emwam/t88Dp4JCUNW/u92cxMBmtNE/GMgqOTSfhcJKtV5DmcniWd8qzFiGo+v/nXnHXdHhyZTAAA+vxOdHsdFYlbpcbOPMci4BLhd5pIyRquWNuFiWgGPT4HZI3kZ/pdgn3db0eBp9Dh6cJgsDCvrpX31+UEPTqUFUujV7obvW8XmsVzMQdOI0tY6nXFLEYz3zv5rd6Tso7phIxur8OerFdzg15ugmc77m+9wlWjnqsSobfdWOjYGIaZG6z2eu18J2BpFgmaeb1pB+YFoQucXbbVju46oIz4z1jOgtJlx7WeS2tyvGPQj/FYBrG0irjEwMOT8q9urwM8y+Ci4SAmohkiQDQolL6Wx8kXHxiGBOtmVDKBB0hH1bMzqbzJPHGX8CyDLX0+OEU+m7dVjbOLx2onD5ZhkFQ0BJxLl2FX6WfT4/FgYmICe/bsgceTO17F3Sh3uAoD2RtZoruY4GTtczMWzPLFIhdYdLgFdOV1RWvUuSoW7NZ3e5Dx69nSQ5LhWckkPNcEg8emPi+OTiayYfAmGIaUzmmGAQfPYjDoRJfXAafA2eWcABF5dL/TFge9WScjwzDwOYmjciYhI+gWsGPQj5SiI5ZRIWsG3AJp+OAWeYSTEoY63JiMSXZJLkAC7/v9DuwfjcHn4HBmJoW5tIIuj4iEQ7WFs5SsIS6pMEwT63s8SMkaNvf5FnfG9XrB8ww6vQ50ekXEMyoOjsfgd3LYOxLBXJo0/lA0HZKqYTwqQdOJ4DYVk/C+69fhoSOkE7SD5+3333RCwaY+L16zow//9fQIXCKHWFqDZphVZ7YC8/OgLAIusWJxq7p4ArZkR792FHja1eSw3GifM0qhtIALsVyunVnMgdOoCV4jXDGL0az3Tv7gb02XG0G3QFaNslR7g15ugudy21+gefvcDqWW1VLu2LRikaCZ15tW086LMOWopey41nNpTY7dAVLec2wyDiUDDAWd6PE5wXMsRmZTuGlLD351aGpJQumreZziTMz+gBOGSULBBY4FC5CSRo7BYMAJv0sAxxJ3CZfN3arV2TVcQwZbtdR7PptZolvpWKAZC2bF52pTX/UuvEooPr4cy8LrJO+raibhxfu7bcCHeIYIWs5st8JIWrYFJ1KmWps4SIR4Ht0+p/XHBa5Lj1NY0HW5rtuDN142iLt/ewZBlwjNAEYjufxDjmWwutMNkWfxB9esWdC9uZAzLhSXsbXfj1u29+LfnzgLr4NHWjFwKq8TpUNgsdnvA8syuHxNJ7YPBBZ0If9s/wSCLhHruzk7W63a90RhHhTQ5RUhcixEnjxWpeJWtfEEy0HgWY7313aEilKUFc9yWeleKSyHCZ5FM947BYO/Xm9BF7p2vUFTmkc7lFo2ilYsEiyn6029LMdFmGrLjms9l/Mnx36MqlEMBl3IdSjNBWwvVSh9pY9TvL8Bl4hAnhsoKWngOMaezA91CC11dtVCPeez2SW6lY4FlnrBrFnnqlHHt5S4ZbljGulGe9Nlg/MbkdTgutSzLqOt/T5EMyomYxlouokerwN9ASdYhsHIbAr9AVfdzjjdMBFwiRjucCGckhGKy2AA9Adc6PU7YJrAyCx5v12yKlixCzk/SL8eAXFD0Xu0GsHzQmz6tBzvr+3GBSNKff3rX8eXvvQlTE5OYseOHfjKV76C66+/vtW7RVkmrKSJCaWxLPV7h67AUFYSdJFgaVmOx7fp4v8izQNYllnSUPpKHqeRpWXNcHYtFZlMBrfddhvC4TBuuukmCELORdzsEt12GEc281w14vg2041WaW7pYl3WrGy+bq8D3V5HweuxxGufk8f6Hm9dzjjruVTdxGDQjcFgoUMxKReWSC61C7nRgmel8QTLSeBZjvfXduKCEKW+//3v4+Mf/zi+/vWv4xWveAW+8Y1v4Pbbb8eRI0ewevXqVu8ehUKh1MVyvUFTKLXQDpO7C5nleHybLf4v1jxgKUPpa9nfeifzi9Gu9yDDMPD444/b3xezkkp0LZp5rhpxfJvlRmuE67JaYaYeZ1wjRaBmCoiNEmCWq8CznK4V7cYFIUr94z/+I9773vfife97HwDgK1/5Cn7961/jX//1X/GFL3yhxXtHoVAo9bNcb9AUCoWyHFhuzQMaPZmv5PmW4z1oJU4Sm3muGnF8m+VGW05Nbhr9XM0UEBvFSvzsrmSWvSilKApeeuklfPrTny74+a233oqnn366RXtFoVAojYfeoCkUCmXpWG7NA5pdWkbvQcuH5XaumrW/y6XJzVI8VzMFRAqlWpa9KDU7Owtd19HX11fw876+PkxNTZX8G1mWIcuy/f94PA4AUFUVqqraP7e+z/8ZpT2h52r5QM/V8oCep+UDPVfLA3qelg/DARFrvORfXdeg663eo4VZFXQAIPk2y2F/G0XxmJ1+ttqXC+n6t6XXjU/fugnn5tK2MLOm0w2WZRr++pr5XBaVnKuVes1pJ5bLZ6rS/WNM0zSXeF+WlImJCQwNDeHpp5/GNddcY//885//PL7zne/g2LFj8/7mrrvuwl//9V/P+/n//M//wO12z/s5hUKhUCgUCoVCaR8kScI73vEOAMC9994Lp9PZ4j2iUCgUSj7pdBrvfOc7EYvF4Pf7y2637J1S3d3d4Dhunitqenp6nnvK4jOf+Qw+8YlP2P+Px+NYtWoVbr311oKDpaoqHnroIdxyyy0FHT0o7Qc9V8sHeq6WB/Q8LR/ouVoe0PO0fKDnanmQSqXs72+++WYEg8HW7QxlQehnavlAz9XyYLmcJ6sibTGWvSgliiJ2796Nhx56CG9+85vtnz/00EN44xvfWPJvHA4HHA7HvJ8LglDypJb7OaX9oOdq+UDP1fKAnqflAz1XywN6npYP9Fy1N4IgwO12Q9d1eq6WCfQ8LR/ouVoetPt5qnTflr0oBQCf+MQncOedd+Lyyy/HNddcg29+85s4f/48PvCBD7R61ygUCoVCoVAoFEqD8Xg8iEaj2LNnDzweT6t3h0KhUCg1ckGIUm9/+9sRDofxuc99DpOTk9i5cyf27NmDNWvWtHrXKBQKhUKhUCgUCoVCoVAoJbggRCkA+OAHP4gPfvCDrd4NCoVCoVAoFAqFQqFQKBRKBVwwohSFQqFQKBQKhUJZGUiShDvuuAPT09O4+eab2zpXhUKhUCjloaIUhUKhUCgUCoVCWVbouo5f/epX9vcUCoVCWZ6wrd4BCoVCoVAoFAqFQqFQKBTKyoOKUhQKhUKhUCgUCoVCoVAolKZDRSkKhUKhUCgUCoVCoVAoFErToaIUhUKhUCgUCoVCoVAoFAql6VBRikKhUCgUCoVCoVAoFAqF0nRo9z0ApmkCAOLxeMHPVVVFOp1GPB6nbWbbHHqulg/0XC0P6HlaPtBztTyg52n5QM/V8iCVStnfx+NxsCxda29X6Gdq+UDP1fJguZwnS1+x9JZyUFEKQCKRAACsWrWqxXtCoVAoFAqFQqFQqmHNmjWt3gUKhUKhlCGRSCAQCJT9PWMuJlutAAzDwMTEBHw+HxiGsX8ej8exatUqjI6Owu/3t3APKYtBz9XygZ6r5QE9T8sHeq6WB/Q8LR/ouVo+0HO1PKDnaflAz9XyYLmcJ9M0kUgkMDg4uKCblTqlALAsi+Hh4bK/9/v9bX2yKTnouVo+0HO1PKDnaflAz9XygJ6n5QM9V8sHeq6WB/Q8LR/ouVoeLIfztJBDyoIWX1MoFAqFQqFQKBQKhUKhUJoOFaUoFAqFQqFQKBQKhUKhUChNh4pSC+BwOPDZz34WDoej1btCWQR6rpYP9FwtD+h5Wj7Qc7U8oOdp+UDP1fKBnqvlAT1Pywd6rpYHF9p5okHnFAqFQqFQKBQKhUKhUCiUpkOdUhQKhUKhUCgUCoVCoVAolKZDRSkKhUKhUCgUCoVCoVAoFErToaIUhUKhUCgUCoVCoVAoFAql6VzwotQXvvAFXHHFFfD5fOjt7cWb3vQmHD9+vGAb0zRx1113YXBwEC6XCzfeeCMOHz5csM03v/lN3HjjjfD7/WAYBtFotOxzyrKMSy+9FAzDYP/+/Uvwqi48mnme1q5dC4ZhCr4+/elPL+XLu6Bo9mfql7/8Ja666iq4XC50d3fjjjvuWKqXdsHRrHP129/+dt5nyvp64YUXlvplLnua+Zk6ceIE3vjGN6K7uxt+vx+veMUr8Oijjy7ly7ugaOa52rt3L2655RYEg0F0dXXh/e9/P5LJ5FK+vAuGRpynubk5fOQjH8GWLVvgdruxevVqfPSjH0UsFit4nEgkgjvvvBOBQACBQAB33nnngmNESiHNPFef//znce2118LtdiMYDDbj5V1QNOtcjYyM4L3vfS/WrVsHl8uFDRs24LOf/SwURWnaa13ONPMz9YY3vAGrV6+G0+nEwMAA7rzzTkxMTDTldV4INPNcWbSrTnHBi1KPPfYYPvShD+HZZ5/FQw89BE3TcOuttyKVStnb/P3f/z3+8R//Ef/8z/+MF154Af39/bjllluQSCTsbdLpNG677Tb8+Z//+aLP+alPfQqDg4NL8nouVJp9nj73uc9hcnLS/vrLv/zLJXttFxrNPFc//vGPceedd+IP//APceDAATz11FN45zvfuaSv70KiWefq2muvLfg8TU5O4n3vex/Wrl2Lyy+/fMlf53KnmZ+p173uddA0DY888gheeuklXHrppXj961+PqampJX2NFwrNOlcTExN49atfjY0bN+K5557DAw88gMOHD+M973nPUr/EC4JGnKeJiQlMTEzgy1/+Mg4ePIj/+q//wgMPPID3vve9Bc/1zne+E/v378cDDzyABx54APv378edd97Z1Ne7nGnmuVIUBW9729vwJ3/yJ019jRcKzTpXx44dg2EY+MY3voHDhw/jn/7pn3D33XdXNAejNPczddNNN+EHP/gBjh8/jh//+Mc4ffo03vrWtzb19S5nmnmuLNpWpzBXGNPT0yYA87HHHjNN0zQNwzD7+/vNL37xi/Y2kiSZgUDAvPvuu+f9/aOPPmoCMCORSMnH37Nnj7l161bz8OHDJgBz3759S/EyLniW8jytWbPG/Kd/+qel2vUVx1KdK1VVzaGhIfPf//3fl3T/VxJLff2zUBTF7O3tNT/3uc81dP9XCkt1nmZmZkwA5uOPP27/LB6PmwDM3/zmN0vzYi5wlupcfeMb3zB7e3tNXdftn+3bt88EYJ48eXJpXswFTL3nyeIHP/iBKYqiqaqqaZqmeeTIEROA+eyzz9rbPPPMMyYA89ixY0v0ai5slupc5XPPPfeYgUCg4fu+0mjGubL4+7//e3PdunWN2/kVRDPP03333WcyDGMqitK4F7CCWOpz1c46xQXvlCrGsrJ1dnYCAM6ePYupqSnceuut9jYOhwM33HADnn766aoeOxQK4Y/+6I/wne98B263u3E7vQJZyvMEAH/3d3+Hrq4uXHrppfj85z9PLcF1sFTnau/evRgfHwfLsrjsssswMDCA22+/fV4ZDKVylvpzZXH//fdjdnaWujpqZKnOU1dXF7Zt24Zvf/vbSKVS0DQN3/jGN9DX14fdu3c39kWsEJbqXMmyDFEUwbK5YZrL5QIAPPnkk43Y9RVFo85TLBaD3+8Hz/MAgGeeeQaBQABXXXWVvc3VV1+NQCBQ1zV0JbNU54rSeJp5rmKxmP08lOpo1nmam5vDd7/7XVx77bUQBKGBr2DlsJTnqt11ihUlSpmmiU984hO47rrrsHPnTgCwSxb6+voKtu3r66uqnME0TbznPe/BBz7wAVquUidLeZ4A4GMf+xjuvfdePProo/jwhz+Mr3zlK/jgBz/YmJ1fYSzluTpz5gwA4K677sJf/uVf4he/+AU6Ojpwww03YG5urkGvYOWw1J+rfP7jP/4Dr3nNa7Bq1arad3iFspTniWEYPPTQQ9i3bx98Ph+cTif+6Z/+CQ888ADNV6mBpTxXN998M6ampvClL30JiqIgEonYpSuTk5MNegUrg0adp3A4jL/5m7/BH//xH9s/m5qaQm9v77xte3t7aUlsDSzluaI0lmaeq9OnT+NrX/saPvCBDzRo71cOzThP//t//294PB50dXXh/PnzuO+++xr8KlYGS3muloNOsaJEqQ9/+MN4+eWX8b3vfW/e7xiGKfi/aZrzfrYQX/va1xCPx/GZz3ym7v1c6SzleQKAP/3TP8UNN9yAiy++GO973/tw99134z/+4z8QDofr2u+VyFKeK8MwAAB/8Rd/gbe85S3YvXs37rnnHjAMgx/+8If17fgKZKk/VxZjY2P49a9/XbaWnbIwS3meTNPEBz/4QfT29uKJJ57A888/jze+8Y14/etfT4WOGljKc7Vjxw5861vfwj/8wz/A7Xajv78f69evR19fHziOq3vfVxKNOE/xeByve93rsH37dnz2s59d8DEWehzKwiz1uaI0jmadq4mJCdx2221429vehve9732N2fkVRDPO0yc/+Uns27cPDz74IDiOw7vf/W6Yptm4F7FCWMpztRx0ihUjSn3kIx/B/fffj0cffRTDw8P2z/v7+wFgnto4PT09T5VciEceeQTPPvssHA4HeJ7Hxo0bAQCXX345/uAP/qABr2BlsNTnqRRXX301AODUqVN1Pc5KY6nP1cDAAABg+/bt9s8cDgfWr1+P8+fP17PrK45mfq7uuecedHV14Q1veEPtO7xCacZ96he/+AXuvfdevOIVr8CuXbvw9a9/HS6XC9/61rca8yJWCM34TL3zne/E1NQUxsfHEQ6Hcdddd2FmZgbr1q2r/wWsEBpxnhKJBG677TZ4vV789Kc/LShL6e/vRygUmve8MzMzdY9NVhpLfa4ojaNZ52piYgI33XQTrrnmGnzzm99cgldyYdOs89Td3Y3Nmzfjlltuwb333os9e/bg2WefXYJXdOGy1OdqOegUF7woZZomPvzhD+MnP/kJHnnkkXmDuXXr1qG/vx8PPfSQ/TNFUfDYY4/h2muvrfh5vvrVr+LAgQPYv38/9u/fjz179gAAvv/97+Pzn/98Y17MBUyzzlMp9u3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|
||
"text/plain": [
|
||
"<Figure size 1200x1000 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"import statsmodels.formula.api as smf\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"# 1. Group by month and spill type\n",
|
||
"spills_gdf['report_month'] = spills_gdf['Initial Report Date'].dt.to_period('M')\n",
|
||
"monthly_by_type = spills_gdf.groupby(['report_month', 'spill_type'])['report_delay'].mean().reset_index()\n",
|
||
"monthly_by_type['report_month'] = monthly_by_type['report_month'].dt.to_timestamp()\n",
|
||
"\n",
|
||
"# 2. Create ITS variables\n",
|
||
"monthly_by_type['time'] = (monthly_by_type['report_month'] - monthly_by_type['report_month'].min()).dt.days // 30\n",
|
||
"monthly_by_type['post_2021'] = (monthly_by_type['report_month'] >= pd.Timestamp('2021-01-01')).astype(int)\n",
|
||
"monthly_by_type['time_post'] = monthly_by_type['time'] * monthly_by_type['post_2021']\n",
|
||
"\n",
|
||
"# 3. Run ITS models separately by spill type\n",
|
||
"its_results_by_type = {}\n",
|
||
"for stype in monthly_by_type['spill_type'].unique():\n",
|
||
" df = monthly_by_type[monthly_by_type['spill_type'] == stype].copy()\n",
|
||
" model = smf.ols(\"report_delay ~ time + post_2021 + time_post\", data=df).fit()\n",
|
||
" df['predicted'] = model.predict(df)\n",
|
||
" its_results_by_type[stype] = (model, df)\n",
|
||
"\n",
|
||
"# 4. Plot side-by-side\n",
|
||
"fig, axs = plt.subplots(2, 1, figsize=(12, 10), sharex=True)\n",
|
||
"\n",
|
||
"for ax, (stype, (model, df)) in zip(axs, its_results_by_type.items()):\n",
|
||
" ax.plot(df['report_month'], df['report_delay'], marker='o', label='Observed', alpha=0.6)\n",
|
||
" ax.plot(df['report_month'], df['predicted'], linestyle='--', color='red', label='Predicted (ITS)')\n",
|
||
" ax.axvline(x=pd.Timestamp('2021-01-01'), color='black', linestyle='--', label='Policy Change (2021)')\n",
|
||
" ax.set_title(f\"ITS Model for {stype} Spills\")\n",
|
||
" ax.set_ylabel(\"Mean Report Delay (Days)\")\n",
|
||
" ax.legend()\n",
|
||
" ax.grid(True)\n",
|
||
"\n",
|
||
"axs[1].set_xlabel(\"Month\")\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.show()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "e07c8135",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Reinterpreting the Spill-Type-Specific ITS (2021 Policy Shift)\n",
|
||
"\n",
|
||
"| Spill Type | Key Takeaways |\n",
|
||
"|------------|----------------|\n",
|
||
"| **Historical** | Delays trended downward pre-2021, but the level change after 2021 was large (–72 days) and not statistically significant due to wide variance and outliers. The slope change was slightly positive, suggesting a mild rebound or plateau after the internal mission shift. |\n",
|
||
"| **Recent** | Consistently lower delays throughout the time series. No discernible shift in level or trend post-2021, indicating the policy and mission change had little room to improve on already fast reporting. |\n",
|
||
"\n",
|
||
"Despite large coefficients (especially for `post_2021` in historical spills), **none of the changes are statistically significant**, likely due to high skew and extreme outliers (note the 400+ day delays).\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "efc4708c",
|
||
"metadata": {},
|
||
"source": [
|
||
"---"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "610abfb4",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Conclusion: Comparative Summary\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 29,
|
||
"id": "546334b9",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"def extract_regression_results(model, model_name):\n",
|
||
" coefs = model.params\n",
|
||
" ses = model.bse\n",
|
||
" pvals = model.pvalues\n",
|
||
"\n",
|
||
" df = pd.DataFrame({\n",
|
||
" 'Coefficient': coefs,\n",
|
||
" 'Std. Error': ses,\n",
|
||
" 'P-Value': pvals\n",
|
||
" })\n",
|
||
" df['Model'] = model_name\n",
|
||
" return df.reset_index().rename(columns={'index': 'Term'})\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 30,
|
||
"id": "a09b247e",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"application/vnd.microsoft.datawrangler.viewer.v0+json": {
|
||
"columns": [
|
||
{
|
||
"name": "Term",
|
||
"rawType": "object",
|
||
"type": "string"
|
||
},
|
||
{
|
||
"name": "ITS (Monthly, All Spills)",
|
||
"rawType": "float64",
|
||
"type": "float"
|
||
},
|
||
{
|
||
"name": "ITS (Monthly, Historical)",
|
||
"rawType": "float64",
|
||
"type": "float"
|
||
},
|
||
{
|
||
"name": "ITS (Monthly, Recent)",
|
||
"rawType": "float64",
|
||
"type": "float"
|
||
},
|
||
{
|
||
"name": "Negative Binomial",
|
||
"rawType": "float64",
|
||
"type": "float"
|
||
},
|
||
{
|
||
"name": "OLS (Interaction)",
|
||
"rawType": "float64",
|
||
"type": "float"
|
||
}
|
||
],
|
||
"conversionMethod": "pd.DataFrame",
|
||
"ref": "bc127456-656a-4993-9250-ec16f41a34a5",
|
||
"rows": [
|
||
[
|
||
"C(Period)[T.Before 2020]",
|
||
null,
|
||
null,
|
||
null,
|
||
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|
||
null
|
||
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|
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[
|
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|
||
null,
|
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null,
|
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|
||
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|
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null
|
||
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|
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|
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|
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|
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|
||
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|
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|
||
null
|
||
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|
||
[
|
||
"Intercept",
|
||
"15.596",
|
||
"41.418",
|
||
"5.104",
|
||
"2.605",
|
||
"5.104"
|
||
],
|
||
[
|
||
"post_2021",
|
||
"-27.672",
|
||
"-72.435",
|
||
"-5.773",
|
||
null,
|
||
"-5.773"
|
||
],
|
||
[
|
||
"time",
|
||
"-0.118",
|
||
"-0.344",
|
||
"-0.017",
|
||
null,
|
||
"-0.017"
|
||
],
|
||
[
|
||
"time_post",
|
||
"0.302",
|
||
"0.768",
|
||
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|
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null,
|
||
"0.057"
|
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|
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|
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|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th>Model</th>\n",
|
||
" <th>ITS (Monthly, All Spills)</th>\n",
|
||
" <th>ITS (Monthly, Historical)</th>\n",
|
||
" <th>ITS (Monthly, Recent)</th>\n",
|
||
" <th>Negative Binomial</th>\n",
|
||
" <th>OLS (Interaction)</th>\n",
|
||
" </tr>\n",
|
||
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|
||
" <th>Term</th>\n",
|
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|
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|
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|
||
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|
||
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|
||
" </thead>\n",
|
||
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|
||
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|
||
" <th>C(Period)[T.Before 2020]</th>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
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|
||
" <td>NaN</td>\n",
|
||
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|
||
" <tr>\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" <th>C(spill_type)[T.Recent]:C(Period)[T.Before 2020]</th>\n",
|
||
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|
||
" <td>NaN</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>-0.311</td>\n",
|
||
" <td>NaN</td>\n",
|
||
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|
||
" <tr>\n",
|
||
" <th>Intercept</th>\n",
|
||
" <td>15.596</td>\n",
|
||
" <td>41.418</td>\n",
|
||
" <td>5.104</td>\n",
|
||
" <td>2.605</td>\n",
|
||
" <td>5.104</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>post_2021</th>\n",
|
||
" <td>-27.672</td>\n",
|
||
" <td>-72.435</td>\n",
|
||
" <td>-5.773</td>\n",
|
||
" <td>NaN</td>\n",
|
||
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|
||
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|
||
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|
||
" <th>time</th>\n",
|
||
" <td>-0.118</td>\n",
|
||
" <td>-0.344</td>\n",
|
||
" <td>-0.017</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>-0.017</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>time_post</th>\n",
|
||
" <td>0.302</td>\n",
|
||
" <td>0.768</td>\n",
|
||
" <td>0.057</td>\n",
|
||
" <td>NaN</td>\n",
|
||
" <td>0.057</td>\n",
|
||
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|
||
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|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
"Model ITS (Monthly, All Spills) \\\n",
|
||
"Term \n",
|
||
"C(Period)[T.Before 2020] NaN \n",
|
||
"C(spill_type)[T.Recent] NaN \n",
|
||
"C(spill_type)[T.Recent]:C(Period)[T.Before 2020] NaN \n",
|
||
"Intercept 15.596 \n",
|
||
"post_2021 -27.672 \n",
|
||
"time -0.118 \n",
|
||
"time_post 0.302 \n",
|
||
"\n",
|
||
"Model ITS (Monthly, Historical) \\\n",
|
||
"Term \n",
|
||
"C(Period)[T.Before 2020] NaN \n",
|
||
"C(spill_type)[T.Recent] NaN \n",
|
||
"C(spill_type)[T.Recent]:C(Period)[T.Before 2020] NaN \n",
|
||
"Intercept 41.418 \n",
|
||
"post_2021 -72.435 \n",
|
||
"time -0.344 \n",
|
||
"time_post 0.768 \n",
|
||
"\n",
|
||
"Model ITS (Monthly, Recent) \\\n",
|
||
"Term \n",
|
||
"C(Period)[T.Before 2020] NaN \n",
|
||
"C(spill_type)[T.Recent] NaN \n",
|
||
"C(spill_type)[T.Recent]:C(Period)[T.Before 2020] NaN \n",
|
||
"Intercept 5.104 \n",
|
||
"post_2021 -5.773 \n",
|
||
"time -0.017 \n",
|
||
"time_post 0.057 \n",
|
||
"\n",
|
||
"Model Negative Binomial \\\n",
|
||
"Term \n",
|
||
"C(Period)[T.Before 2020] 0.788 \n",
|
||
"C(spill_type)[T.Recent] -1.531 \n",
|
||
"C(spill_type)[T.Recent]:C(Period)[T.Before 2020] -0.311 \n",
|
||
"Intercept 2.605 \n",
|
||
"post_2021 NaN \n",
|
||
"time NaN \n",
|
||
"time_post NaN \n",
|
||
"\n",
|
||
"Model OLS (Interaction) \n",
|
||
"Term \n",
|
||
"C(Period)[T.Before 2020] NaN \n",
|
||
"C(spill_type)[T.Recent] NaN \n",
|
||
"C(spill_type)[T.Recent]:C(Period)[T.Before 2020] NaN \n",
|
||
"Intercept 5.104 \n",
|
||
"post_2021 -5.773 \n",
|
||
"time -0.017 \n",
|
||
"time_post 0.057 "
|
||
]
|
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},
|
||
"execution_count": 30,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Collect regression summaries\n",
|
||
"results_frames = []\n",
|
||
"\n",
|
||
"# Add your models — use your actual variable names\n",
|
||
"results_frames.append(extract_regression_results(model, 'OLS (Interaction)'))\n",
|
||
"results_frames.append(extract_regression_results(nb_model, 'Negative Binomial'))\n",
|
||
"results_frames.append(extract_regression_results(its_model, 'ITS (Monthly, All Spills)'))\n",
|
||
"\n",
|
||
"\n",
|
||
"# ITS by spill type (e.g., 'Historical', 'Recent')\n",
|
||
"for spill_type, (model, df) in its_results_by_type.items():\n",
|
||
" label = f\"ITS (Monthly, {spill_type})\"\n",
|
||
" results_frames.append(extract_regression_results(model, label))\n",
|
||
"\n",
|
||
"# Combine all\n",
|
||
"regression_summary_table = pd.concat(results_frames, ignore_index=True)\n",
|
||
"\n",
|
||
"# Pivot just the coefficients for display\n",
|
||
"regression_coef_table = regression_summary_table.pivot_table(\n",
|
||
" index='Term',\n",
|
||
" columns='Model',\n",
|
||
" values='Coefficient',\n",
|
||
" aggfunc='first'\n",
|
||
").round(3)\n",
|
||
"\n",
|
||
"regression_coef_table\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "5d9578b4",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Summary of Regression Models (Post-2021 Breakpoint)\n",
|
||
"\n",
|
||
"The change from a 2020 to a 2021 breakpoint in the ITS models allowed us to align more precisely with the agency’s operational adaptation to the new policy. The OLS interaction and Negative Binomial models were unaffected, as they rely on categorical indicators for period and spill type rather than temporal trends.\n",
|
||
"\n",
|
||
"The ITS models showed minor adjustments in intercepts and trend coefficients. For historical spills, the predicted level drop post-2021 was large (–72.4 days) but not statistically significant due to high variance. For recent spills, the model continued to show low and stable delays with no meaningful change after 2021. These updated results reinforce the conclusion that performance improvements were already underway and that the mission shift in 2021 may have stabilized or modestly extended those gains, particularly in the handling of historical spill discoveries.\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "3ccf0cf7",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Regression Summary: Key Coefficients by Model (2021 ITS Breakpoint)\n",
|
||
"\n",
|
||
"| Term | OLS (Interaction) | Negative Binomial | ITS (Monthly, All Spills) | ITS (Historical) | ITS (Recent) |\n",
|
||
"|--------------------------------------------|--------------------|--------------------|-----------------------------|------------------|---------------|\n",
|
||
"| **Intercept** | 5.104 *** | 2.605 *** | 15.596 *** | 41.418 *** | 5.104 *** |\n",
|
||
"| `C(spill_type)[T.Recent]` | -10.606 *** | -1.531 *** | — | — | — |\n",
|
||
"| `C(Period)[T.Before 2020]` | 16.213 *** | 0.788 *** | — | — | — |\n",
|
||
"| `C(Recent):C(Before 2020)` | -14.428 *** | -0.311 *** | — | — | — |\n",
|
||
"| `time` | -0.017 | — | -0.118 | -0.344 | -0.017 |\n",
|
||
"| `post_2021` | -5.773 | — | -27.672 | -72.435 | -5.773 |\n",
|
||
"| `time_post` | 0.057 | — | 0.302 | 0.768 | 0.057 |\n",
|
||
"\n",
|
||
"\\* p < .05, \\*\\* p < .01, \\*\\*\\* p < .001 \n",
|
||
"Note: “—” indicates the variable was not included in that model. All ITS models use January 2021 as the intervention point.\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "1988fd14",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Limitations\n",
|
||
"\n",
|
||
"Several limitations should be noted when interpreting these findings. First, the reporting delay data are heavily skewed with a long right tail, especially for historical spills. While count models and quantile regression (excluded here) partially address this, residual outliers still influence trend estimates in time-series analyses. Second, the categorization into \"recent\" vs. \"historical\" spills reflects underlying reporting practices, not random treatment assignment, making causal inference inherently limited. Third, the ITS models rely on monthly aggregation and assume linear trends before and after the policy change; nonlinear dynamics or unmeasured covariates may obscure more complex patterns. Finally, the formal rule change in 2020 and the internal mission shift in 2021 introduce ambiguity about when the policy was truly “implemented,” and thus, both breakpoints carry interpretive uncertainty.\n"
|
||
]
|
||
}
|
||
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|
||
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|
||
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|
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|
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|
||
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|
||
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|
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|
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|
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|
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|
||
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|
||
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|
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|
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|
||
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|
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