CT_Opioid_Overdose_Deaths.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Opioid Overdoses in connecticut from 2012 to June 2017"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### By Driss Guessous Last Updated (2018-02-27)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Goal of this project was to explore a dataset from the DATA.Gov site entitle 'Accidental Drug Related Deaths 2012- June 2017' which can be found at [Data](https://catalog.data.gov/dataset/accidental-drug-related-deaths-january-2012-sept-2015)\n",
    "\n",
    "The only other external source for data was a CT government website containg a list of cities by county which can be found [here](http://www.ct.gov/ecd/cwp/view.asp?a=1106&q=250994)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A large amount of missing data regarding the County of Death and the County or Residence were missing. I created a few functions to create new columns using the death location data, which had no missing data, and the residence city data. I used value_counts function to determine which cities had multiple hits that were not in the list of cities then I manually looked them up to determine which county they were in."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Summary of Results:\n",
    "\n",
    "### Clustering Analysis:\n",
    "* The clustering did not show clear groups with particular features.  More work refining the Models paramaters could be done discern possible clusterings.  Alternatively there may not be distinct clusters based upon the features of this dataset\n",
    "\n",
    "SARIMAX(deaths_per_year.Value, trend='n', order=(1,1,2), seasonal_order=(1,1,1,12))\n",
    "### Time Series Analyis:\n",
    "* After refining a SARIMA Model of with ARIMA params of (1,1,2) and a seasonal order coresponding to 12 Months to account for any seasonal variability (i.e. The Hot Summer or Colder Winters can have an effect on Opiod use and therefore OverDoses)\n",
    "* Clear upward trend was scene in the monthly death counts and the model forecasted a continuation in this non stationary trend. Seen Below:\n",
    "![Graph](death_forecast.png)\n",
    "\n",
    "\n",
    "#### Mean Age  =  42\n",
    "\n",
    "#### Gender = 27% Female, 73% Male\n",
    "* Roughly a 50-50 split between Men and Women\n",
    "\n",
    "#### Race= 79% White, 8% Black\n",
    "* 80% of population is White\n",
    "* 11% of population is Black\n",
    "\n",
    "#### Death County = 29% Hartford, 16% Fairfield, 27% New Haven\n",
    "* Fairfield has the highest population of 26% of population but only 16% of deaths\n",
    "* Hartfield has 24% of population but accounts for 30% of deaths. \n",
    "* New Haven has 24& of population and 27% of death\n",
    "* The other counties match the census data in # of Deaths and Percentage of Population\n",
    "\n",
    "###  Census Data from the [Census Bureau](https://www.census.gov/quickfacts/CT) \n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Manipulation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#importing relavant libaries \n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import datetime as dt\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#importing CT opiod overdose deaths data\n",
    "data = pd.read_csv('data/drug_deaths.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# creating a list of the drug columns who are coded as Y or N\n",
    "drugs_list = ['Heroin', 'Cocaine', 'Fentanyl', 'Oxycodone',\n",
    "       'Oxymorphone', 'EtOH', 'Hydrocodone', 'Benzodiazepine', 'Methadone',\n",
    "       'Amphet', 'Tramad', 'Morphine (not heroin)', 'Other', 'Any Opioid',]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def clean_drug_columns(entry):\n",
    "# turning the Y into 1 and N into 0 so that it will work with machine learing algorithim \n",
    "    if pd.isnull(entry):\n",
    "        return 0\n",
    "    elif entry == 'Y':\n",
    "        return 1\n",
    "\n",
    "def clean_all_drugs(drugs):\n",
    "# applying the Y to 1 N to 0 schema to all columns     \n",
    "    for drug in drugs:\n",
    "        data[drug] = data[drug].apply(clean_drug_columns)    \n",
    "    \n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fill_missing_drugs(drugs):\n",
    "#creating function to run through all the drugs and fill the NAN values with 0     \n",
    "    for drug in drugs:\n",
    "        data[drug] = data[drug].fillna(0)\n",
    "clean_all_drugs(drugs_list)\n",
    "data.Other = data.Other.fillna(0)\n",
    "fill_missing_drugs(drugs_list)        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#This list was created using http://www.ct.gov/ecd/cwp/view.asp?a=1106&q=250994 the CT gov website showing cities by county, used to clean up data\n",
    "Fairfield = 'Bethel, Bridgeport, Brookfield, Danbury, Darien, Easton, Fairfield, Greenwich, Monroe, New Canaan, New Fairfield, Newtown, Norwalk,  Shelton, Sherman, Stamford, Stratford, Redding, Ridgefield, Trumbull, Weston, Westport, Wilton'\n",
    "Hartford = 'Avon, Berlin, Bloomfield, Bristol, Burlington, Canton, East Granby, East, Hartford, , East Windsor, Enfield, Farmington, Glastonbury, Granby, Hartford, Hartland, Manchester, Marlborough, New Britain, Newington, Plainville, Rocky  Hill, Simsbury, Southington, South Windsor, Suffield, West Hartford, Wethersfield, Windsor, Windsor Locks, East Hartford, S Glastonbury'\n",
    "Litchfield = 'Barkhamsted, Oakville, Winsted, Bethlehem, Bridgewater, Canaan, Colebrook, Cornwall, Goshen, Harwinton, Kent, Litchfield, Morris, New Hartford, New Milford, Norfolk, North Canaan, Plymouth, Roxbury, Salisbury, Sharon, Thomaston, Torrington, Warren, Washington, Watertown, Winchester, Woodbury'\n",
    "Middlesex = 'Chester, Clinton, Cromwell, Deep River, Durham, East Haddam, East Hampton, Essex, Haddam, Killingworth, Middlefield, Middletown, Old Saybrook, Portland, Westbrook'\n",
    "New_Haven = 'Ansonia, W Haven, E Haven, Beacon Falls, Bethany, Branford, Cheshire, Derby, East Haven, Guilford, Hamden, Madison, Meriden, Middlebury, Milford, Naugatuck, New Haven, North Branford, North Haven, Orange, Oxford, Prospect, Seymour, Southbury, Wallingford, Waterbury, West Haven, Wolcott, Woodbridge'\n",
    "New_London = 'Bozrah, Oakdale, Mystic, Uncasville, Colchester, East Lyme, Franklin, Griswold, Groton, Lebanon, Ledyard, Lisbon, Lyme, Montville, New London, North Stonington, Norwich, Old Lyme, Preston, Salem, Sprague, Stonington, Voluntown, Waterford'\n",
    "Tolland = 'Andover, Bolton, Columbia, Coventry, Ellington, Hebron, Mansfield, Somers, Stafford, Tolland, Union, Vernon, Willington'\n",
    "Windham = 'Ashford, East Woodstock, Willimantic, Brooklyn, Canterbury, Chaplin, Eastford, Hampton, Killingly, Plainfield, Pomfret, Putnam, Scotland, Sterling, Thompson, Windham, Woodstock'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#creating dictionary between the cities and the county name\n",
    "counties_list = {'Fairfield':Fairfield,'Windham':Windham,'Tolland':Tolland,\n",
    "                 'New London':New_London,'New Haven':New_Haven,'Middlesex':Middlesex,\n",
    "                 'Litchfield':Litchfield,'Hartford':Hartford}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def clean_counties_list(county):\n",
    "# function used to turn the raw long strings in the imported data to individual city entries \n",
    "    county = [x.strip() for x in county.split(',')]\n",
    "    return county\n",
    "for key,value in counties_list.items():\n",
    "        counties_list[key] = clean_counties_list(value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#running through the Residence city column and using this to create new column where the counties are based off of this data \n",
    "for index, row in data.iterrows():\n",
    "    if pd.notnull(row['Residence City']) and pd.notnull(row['Residence County']):\n",
    "        data.loc[index,'New_Res_Counties'] = row['Residence County'].lower().title()\n",
    "        \n",
    "    elif pd.isnull(row['Residence City']) and pd.isnull(row['Residence County']):\n",
    "        data.loc[index,'New_Res_Counties'] = 'Unknown'\n",
    "        \n",
    "    elif pd.notnull(row['Residence City']) and pd.isnull(row['Residence County']):\n",
    "        for key,value in counties_list.items():\n",
    "            if (row['Residence City'].lower().title()) in value:\n",
    "                data.loc[index,'New_Res_Counties'] = key\n",
    "    else:\n",
    "        data.loc[index,'New_Res_Counties'] = row['Residence County'].lower().title()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def clean_up_res_counties(value):\n",
    "#function to fix the new counties list with either the counties or unknown... \n",
    "#can clean up by adding more cities to the cities list\n",
    "    if value not in list(counties_list.keys()):\n",
    "        return 'Unknown'\n",
    "    else:\n",
    "        return value\n",
    "        \n",
    "data.New_Res_Counties = data.New_Res_Counties.apply(clean_up_res_counties)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#turning data string in to datetime values and creating a years column for other feature also a month column \n",
    "data.Date= pd.to_datetime(data.Date)\n",
    "data['Years'] = data.Date.apply(lambda x: x.year)\n",
    "data['Months'] = data.Date.apply(lambda x: x.month)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#filling in the nan values with unkonwns for most attributes dealing with death description\n",
    "data.MannerofDeath = data.MannerofDeath.fillna('Unknown')\n",
    "data.AmendedMannerofDeath = data.AmendedMannerofDeath.fillna('0')\n",
    "data.DescriptionofInjury = data.DescriptionofInjury.fillna('None')\n",
    "data.InjuryPlace = data.InjuryPlace.fillna('Unknown')\n",
    "data.ImmediateCauseA = data.ImmediateCauseA.fillna('Unknown')\n",
    "data.Location = data.Location.fillna('Unknown')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Using the death location to create Death City column \n",
    "data['New_Death_City'] = data['DeathLoc']\n",
    "data['New_Death_City']= data['New_Death_City'].apply(lambda x: x.split(',')[0].lower().title())\n",
    "#Checked which city was null and used Lat Log to calculate which city it was in \n",
    "data.loc[data['Death City'].isnull(),['New_Death_City']] = 'Middletown'\n",
    "data.loc[data.New_Death_City == '06340',['New_Death_City']]='Groton'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creating a new column called New_Death_Counties which contains a cleaned up version of death counties \n",
    "for index, row in data.iterrows():\n",
    "    if pd.isnull(row['Death County']):\n",
    "        for key,value in counties_list.items():\n",
    "            if (row['New_Death_City'].lower().title()) in value:\n",
    "                data.loc[index,'New_Death_Counties'] = key\n",
    "    else:\n",
    "        data.loc[index,'New_Death_Counties'] = row['Death County'].lower().title()            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Updating the residence state information so that they are either CT or other \n",
    "for index, row in data.iterrows():\n",
    "    if row.New_Res_Counties in counties_list.keys():\n",
    "         data.loc[index,'New_Res_State'] = 'CT'\n",
    "    else:\n",
    "         data.loc[index,'New_Res_State'] = row['Residence State']\n",
    "#filling all NAN values with unknown \n",
    "data['New_Res_State'].fillna('Unknown',inplace=True)        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#fillin in nan values with Race unknown, Sex: Male cause they are by far the mode of the data, \n",
    "#Age with mean, Date with unknown, and years with unknown and unknown residence city with unknown \n",
    "data.Race.fillna('Unknown',inplace=True)\n",
    "data.Sex.fillna('Male',inplace=True)\n",
    "data.Age.fillna(data.Age.mean(),inplace=True)\n",
    "data.Years.fillna('Unknown',inplace=True)\n",
    "data.loc[data.New_Death_Counties =='Usa',['New_Death_Counties']] = 'Hartford'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating dummy vairables for the Sex column in the dataframe\n",
    "def clean_gender(sex):\n",
    "    if sex == 'Male':\n",
    "        return 0\n",
    "    else:\n",
    "        return 1\n",
    "data.Sex = data.Sex.apply(clean_gender)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#There were ionly 3 values that didnt fit into Residence or Other so I decided to add them to Other\n",
    "def clean_location(loc):\n",
    "    if (loc == 'Unknown' or loc =='Hospice'  or loc == 'Convalescent Home'):\n",
    "        return 'Other'\n",
    "    else:\n",
    "        return loc\n",
    "data.Location = data.Location.apply(clean_location)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Re ordering the data columns to make more logical groups \n",
    "cols = ['CaseNumber',\n",
    " 'Date',\n",
    " 'Years',\n",
    " 'Months',\n",
    " 'Sex',\n",
    " 'Race',\n",
    " 'Age',\n",
    " 'Residence City',\n",
    " 'Residence State',\n",
    " 'Residence County',\n",
    " 'Death City',\n",
    " 'Death State',\n",
    " 'Death County',\n",
    " 'New_Res_Counties',\n",
    " 'New_Res_State',\n",
    " 'New_Death_Counties',\n",
    " 'New_Death_City',\n",
    " 'Location',\n",
    " 'DescriptionofInjury',\n",
    " 'InjuryPlace',\n",
    " 'ImmediateCauseA',\n",
    " 'Heroin',\n",
    " 'Cocaine',\n",
    " 'Fentanyl',\n",
    " 'Oxycodone',\n",
    " 'Oxymorphone',\n",
    " 'EtOH',\n",
    " 'Hydrocodone',\n",
    " 'Benzodiazepine',\n",
    " 'Methadone',\n",
    " 'Amphet',\n",
    " 'Tramad',\n",
    " 'Morphine (not heroin)',\n",
    " 'Other',\n",
    " 'Any Opioid',\n",
    " 'MannerofDeath',\n",
    " 'AmendedMannerofDeath',\n",
    " 'DeathLoc',]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# copying data\n",
    "new_data = data[cols].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# dropping features that are un important to learning \n",
    "new_data.drop(['CaseNumber','Residence City','Residence County','Residence State','New_Res_State','Death City','Death County','Death State','DeathLoc','InjuryPlace','ImmediateCauseA','DescriptionofInjury','AmendedMannerofDeath','MannerofDeath'],axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Sort the index by date to make them in chronological order \n",
    "new_data = new_data.sort_values('Date')\n",
    "new_data = new_data[:-2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#The index used was arbitrary so I changed the date to be the index so the deaths were in chronological order \n",
    "new_data.set_index('Date',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "#These are categorical variables \n",
    "dummy_cols = ['Race','New_Res_Counties','New_Death_Counties','Location']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_data = pd.get_dummies(new_data,columns = dummy_cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#FOR NOW DROP DEATH CITIES BUT COME BACK SEE EFFECT\n",
    "new_data = new_data.drop('New_Death_City',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "compare_dat = new_data.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = StandardScaler()\n",
    "new_data = scaler.fit_transform(new_data)\n",
    "new_data = pd.DataFrame(new_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "pca = PCA(n_components=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_data['x'] = pca.fit_transform(new_data)[:,0]\n",
    "new_data['y'] = pca.fit_transform(new_data)[:,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "cluster = KMeans(n_clusters=8)\n",
    "new_data['Cluster'] = cluster.fit_predict(new_data[new_data.columns[:-2]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x10a83eef0>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10a83eba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "sns.set(style='ticks')\n",
    "\n",
    "fg = sns.FacetGrid(data=new_data, hue='Cluster',size=10,aspect=1.5)\n",
    "fg.map(plt.scatter, 'x', 'y').add_legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "compare_dat['Cluster'] = new_data.iloc[:,-1].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "mean_ages = pd.pivot_table(compare_dat,index='Cluster',aggfunc='mean').Age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Amphet</th>\n",
       "      <th>Any Opioid</th>\n",
       "      <th>Benzodiazepine</th>\n",
       "      <th>Cocaine</th>\n",
       "      <th>EtOH</th>\n",
       "      <th>Fentanyl</th>\n",
       "      <th>Heroin</th>\n",
       "      <th>Hydrocodone</th>\n",
       "      <th>Location_Hospital</th>\n",
       "      <th>...</th>\n",
       "      <th>Race_Chinese</th>\n",
       "      <th>Race_Hawaiian</th>\n",
       "      <th>Race_Hispanic, Black</th>\n",
       "      <th>Race_Hispanic, White</th>\n",
       "      <th>Race_Native American, Other</th>\n",
       "      <th>Race_Other</th>\n",
       "      <th>Race_Unknown</th>\n",
       "      <th>Race_White</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Tramad</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cluster</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>42.787257</td>\n",
       "      <td>0.021598</td>\n",
       "      <td>0.194384</td>\n",
       "      <td>0.289417</td>\n",
       "      <td>0.315335</td>\n",
       "      <td>0.195464</td>\n",
       "      <td>0.254860</td>\n",
       "      <td>0.494600</td>\n",
       "      <td>0.018359</td>\n",
       "      <td>0.326134</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001080</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003240</td>\n",
       "      <td>0.085313</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001080</td>\n",
       "      <td>0.003240</td>\n",
       "      <td>0.799136</td>\n",
       "      <td>0.277538</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>49.121622</td>\n",
       "      <td>0.027027</td>\n",
       "      <td>0.229730</td>\n",
       "      <td>0.351351</td>\n",
       "      <td>0.108108</td>\n",
       "      <td>0.256757</td>\n",
       "      <td>0.162162</td>\n",
       "      <td>0.337838</td>\n",
       "      <td>0.040541</td>\n",
       "      <td>0.364865</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.027027</td>\n",
       "      <td>0.108108</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.756757</td>\n",
       "      <td>0.324324</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>40.648647</td>\n",
       "      <td>0.016216</td>\n",
       "      <td>0.216216</td>\n",
       "      <td>0.270270</td>\n",
       "      <td>0.248649</td>\n",
       "      <td>0.183784</td>\n",
       "      <td>0.324324</td>\n",
       "      <td>0.502703</td>\n",
       "      <td>0.027027</td>\n",
       "      <td>0.243243</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.032432</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.010811</td>\n",
       "      <td>0.908108</td>\n",
       "      <td>0.194595</td>\n",
       "      <td>0.027027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>41.436782</td>\n",
       "      <td>0.022989</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>0.195402</td>\n",
       "      <td>0.252874</td>\n",
       "      <td>0.201149</td>\n",
       "      <td>0.295977</td>\n",
       "      <td>0.574713</td>\n",
       "      <td>0.045977</td>\n",
       "      <td>0.362069</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002874</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.074713</td>\n",
       "      <td>0.002874</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.873563</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>40.138340</td>\n",
       "      <td>0.027668</td>\n",
       "      <td>0.201581</td>\n",
       "      <td>0.213439</td>\n",
       "      <td>0.197628</td>\n",
       "      <td>0.213439</td>\n",
       "      <td>0.359684</td>\n",
       "      <td>0.529644</td>\n",
       "      <td>0.023715</td>\n",
       "      <td>0.284585</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003953</td>\n",
       "      <td>0.059289</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.007905</td>\n",
       "      <td>0.901186</td>\n",
       "      <td>0.320158</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>40.851913</td>\n",
       "      <td>0.031614</td>\n",
       "      <td>0.164725</td>\n",
       "      <td>0.279534</td>\n",
       "      <td>0.301165</td>\n",
       "      <td>0.262895</td>\n",
       "      <td>0.314476</td>\n",
       "      <td>0.514143</td>\n",
       "      <td>0.024958</td>\n",
       "      <td>0.397671</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003328</td>\n",
       "      <td>0.124792</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.004992</td>\n",
       "      <td>0.008319</td>\n",
       "      <td>0.745424</td>\n",
       "      <td>0.291181</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>40.243590</td>\n",
       "      <td>0.017094</td>\n",
       "      <td>0.226496</td>\n",
       "      <td>0.196581</td>\n",
       "      <td>0.179487</td>\n",
       "      <td>0.192308</td>\n",
       "      <td>0.230769</td>\n",
       "      <td>0.598291</td>\n",
       "      <td>0.029915</td>\n",
       "      <td>0.350427</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.012821</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.008547</td>\n",
       "      <td>0.965812</td>\n",
       "      <td>0.290598</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>42.807292</td>\n",
       "      <td>0.018750</td>\n",
       "      <td>0.193750</td>\n",
       "      <td>0.201042</td>\n",
       "      <td>0.296875</td>\n",
       "      <td>0.209375</td>\n",
       "      <td>0.371875</td>\n",
       "      <td>0.575000</td>\n",
       "      <td>0.029167</td>\n",
       "      <td>0.293750</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001042</td>\n",
       "      <td>0.003125</td>\n",
       "      <td>0.177083</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002083</td>\n",
       "      <td>0.009375</td>\n",
       "      <td>0.710417</td>\n",
       "      <td>0.252083</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 48 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Age    Amphet  Any Opioid  Benzodiazepine   Cocaine      EtOH  \\\n",
       "Cluster                                                                        \n",
       "0        42.787257  0.021598    0.194384        0.289417  0.315335  0.195464   \n",
       "1        49.121622  0.027027    0.229730        0.351351  0.108108  0.256757   \n",
       "2        40.648647  0.016216    0.216216        0.270270  0.248649  0.183784   \n",
       "3        41.436782  0.022989    0.166667        0.195402  0.252874  0.201149   \n",
       "4        40.138340  0.027668    0.201581        0.213439  0.197628  0.213439   \n",
       "5        40.851913  0.031614    0.164725        0.279534  0.301165  0.262895   \n",
       "6        40.243590  0.017094    0.226496        0.196581  0.179487  0.192308   \n",
       "7        42.807292  0.018750    0.193750        0.201042  0.296875  0.209375   \n",
       "\n",
       "         Fentanyl    Heroin  Hydrocodone  Location_Hospital    ...     \\\n",
       "Cluster                                                        ...      \n",
       "0        0.254860  0.494600     0.018359           0.326134    ...      \n",
       "1        0.162162  0.337838     0.040541           0.364865    ...      \n",
       "2        0.324324  0.502703     0.027027           0.243243    ...      \n",
       "3        0.295977  0.574713     0.045977           0.362069    ...      \n",
       "4        0.359684  0.529644     0.023715           0.284585    ...      \n",
       "5        0.314476  0.514143     0.024958           0.397671    ...      \n",
       "6        0.230769  0.598291     0.029915           0.350427    ...      \n",
       "7        0.371875  0.575000     0.029167           0.293750    ...      \n",
       "\n",
       "         Race_Chinese  Race_Hawaiian  Race_Hispanic, Black  \\\n",
       "Cluster                                                      \n",
       "0            0.001080       0.000000              0.003240   \n",
       "1            0.000000       0.000000              0.027027   \n",
       "2            0.000000       0.000000              0.000000   \n",
       "3            0.002874       0.000000              0.000000   \n",
       "4            0.000000       0.000000              0.003953   \n",
       "5            0.000000       0.000000              0.003328   \n",
       "6            0.000000       0.000000              0.000000   \n",
       "7            0.000000       0.001042              0.003125   \n",
       "\n",
       "         Race_Hispanic, White  Race_Native American, Other  Race_Other  \\\n",
       "Cluster                                                                  \n",
       "0                    0.085313                     0.000000    0.001080   \n",
       "1                    0.108108                     0.000000    0.000000   \n",
       "2                    0.032432                     0.000000    0.000000   \n",
       "3                    0.074713                     0.002874    0.000000   \n",
       "4                    0.059289                     0.000000    0.000000   \n",
       "5                    0.124792                     0.000000    0.004992   \n",
       "6                    0.012821                     0.000000    0.000000   \n",
       "7                    0.177083                     0.000000    0.002083   \n",
       "\n",
       "         Race_Unknown  Race_White       Sex    Tramad  \n",
       "Cluster                                                \n",
       "0            0.003240    0.799136  0.277538  0.000000  \n",
       "1            0.000000    0.756757  0.324324  1.000000  \n",
       "2            0.010811    0.908108  0.194595  0.027027  \n",
       "3            0.000000    0.873563  0.250000  0.000000  \n",
       "4            0.007905    0.901186  0.320158  0.000000  \n",
       "5            0.008319    0.745424  0.291181  0.000000  \n",
       "6            0.008547    0.965812  0.290598  0.000000  \n",
       "7            0.009375    0.710417  0.252083  0.000000  \n",
       "\n",
       "[8 rows x 48 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.pivot_table(compare_dat,index='Cluster',aggfunc='mean')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## This section is all the time series analysis that is done on the total death number per month \n",
    "\n",
    "* This is starts by using a groupby function to join the year and month data and then using the size() to get the total elements in the each month set. \n",
    "\n",
    "* I then use a OLS Regression to find general linear regression and different stats to describe it\n",
    "\n",
    "* Then I created an autocorelation plot to try and determine if the data is truly random or if there is a relationship (possibly period)\n",
    "\n",
    "* Using a seasonal decompose function built into the statsmodel with a frequency of 12 to see if there is a monthly preiodicity that shows a relationship between number of deaths and the month of year\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/statsmodels/compat/pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.\n",
      "  from pandas.core import datetools\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                      y   R-squared:                       0.874\n",
      "Model:                            OLS   Adj. R-squared:                  0.870\n",
      "Method:                 Least Squares   F-statistic:                     221.7\n",
      "Date:                Tue, 27 Feb 2018   Prob (F-statistic):           1.69e-29\n",
      "Time:                        11:08:07   Log-Likelihood:                -293.39\n",
      "No. Observations:                  66   AIC:                             590.8\n",
      "Df Residuals:                      64   BIC:                             595.2\n",
      "Df Model:                           2                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "x1             0.0262      0.003      9.896      0.000       0.021       0.031\n",
      "x2             0.2472      0.749      0.330      0.742      -1.249       1.743\n",
      "==============================================================================\n",
      "Omnibus:                        6.857   Durbin-Watson:                   0.238\n",
      "Prob(Omnibus):                  0.032   Jarque-Bera (JB):                4.536\n",
      "Skew:                           0.485   Prob(JB):                        0.104\n",
      "Kurtosis:                       2.159   Cond. No.                         585.\n",
      "==============================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fbb0588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Creating a table extract deaths per month data\n",
    "table = compare_dat.groupby(['Years','Months']).size().plot(kind='line')\n",
    "\n",
    "x = list(compare_dat.groupby(['Years','Months']).size().index)\n",
    "y = (compare_dat.groupby(['Years','Months']).size().values)\n",
    "\n",
    "#Running a simple Logisitc Regression\n",
    "import statsmodels.api as sm\n",
    "model = sm.OLS(y, x)\n",
    "results = model.fit()\n",
    "print(results.summary())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creating a DF to hold the deaths per year values\n",
    "deaths_per_year = pd.DataFrame(y,x,columns=['Value'])\n",
    "deaths_per_year.index.names=['Date']\n",
    "deaths_per_year.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10acf6f98>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10acefe80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.plotting import autocorrelation_plot\n",
    "plt.figure()\n",
    "autocorrelation_plot(deaths_per_year['Value'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/statsmodels/regression/linear_model.py:1127: RuntimeWarning: invalid value encountered in sqrt\n",
      "  return rho, np.sqrt(sigmasq)\n"
     ]
    }
   ],
   "source": [
    "from statsmodels.tsa.stattools import pacf\n",
    "partialacf = pacf(deaths_per_year.Value[2:])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "deaths_per_year.Date=deaths_per_year.Date.apply(lambda x:'-'.join((str(x[0])[:-2],str(x[1])[:-2])) + ('-01'))\n",
    "deaths_per_year.Date = pd.to_datetime(deaths_per_year['Date'],format='%Y-%m-%d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "deaths_per_year.set_index(deaths_per_year.Date,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x109856978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10acf6828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statsmodels.tsa.seasonal import seasonal_decompose\n",
    "decompostiton = seasonal_decompose(deaths_per_year.Value,freq=12,model = 'additive')\n",
    "fig = plt.figure()\n",
    "fig = decompostiton.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "#This code was got from http://www.seanabu.com/2016/03/22/time-series-seasonal-ARIMA-model-in-python/ and slightly modified by me \n",
    "from statsmodels.tsa.stattools import adfuller\n",
    "def test_stationarity(timeseries):\n",
    "\n",
    "    #Determing rolling statistics\n",
    "    rolmean = timeseries.rolling(window=12,center=False).mean()\n",
    "    rolstd = timeseries.rolling(window=12,center=False).std()\n",
    "\n",
    "    #Plot rolling statistics:\n",
    "    fig = plt.figure(figsize=(12, 8))\n",
    "    orig = plt.plot(timeseries, color='blue',label='Original')\n",
    "    mean = plt.plot(rolmean, color='red', label='Rolling Mean')\n",
    "    std = plt.plot(rolstd, color='black', label = 'Rolling Std')\n",
    "    plt.legend(loc='best')\n",
    "    plt.title('Rolling Mean & Standard Deviation')\n",
    "    plt.show()\n",
    "    \n",
    "    #Perform Dickey-Fuller test:\n",
    "    print ('Results of Dickey-Fuller Test:')\n",
    "    dftest = adfuller(timeseries, autolag='AIC')\n",
    "    dfoutput = pd.Series(dftest[0:4], index=['Test Statistic','p-value','#Lags Used','Number of Observations Used'])\n",
    "    for key,value in dftest[4].items():\n",
    "        dfoutput['Critical Value ({})'.format(key)] = value\n",
    "    print (dfoutput )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fdcbfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results of Dickey-Fuller Test:\n",
      "Test Statistic                  0.210942\n",
      "p-value                         0.972869\n",
      "#Lags Used                      5.000000\n",
      "Number of Observations Used    60.000000\n",
      "Critical Value (1%)            -3.544369\n",
      "Critical Value (5%)            -2.911073\n",
      "Critical Value (10%)           -2.593190\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "test_stationarity(deaths_per_year.Value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CQ9eXK1eOgwcP0q9fPwYMGMC+ffsAuH37Np9++imbNm3Cy8uLfv36PXTfCxcusHTpUry9vXn++ee5efMm586dY+DAgTRp0oQ//viDefPmKUCLiIiI5BJOGaADAtKvFueE0qVLc/To0Yeuv3DhAg0bNqRSpUpJrr906RJVqlTB29sbgAYNGjx03woVKlCwYEEAfH19iY6OxtfXl0WLFvHFF19gMpmIi4vLge9GRERERLJCkwgzoXXr1uzevTtJiF6/fj3FixfHzc0Nk8mU5PgKFSpw7tw5oqKiiI+PTzF8J78PwJw5c+jSpQsBAQE0adIEi8Vi+29GRERERLLEKSvQjuLj48PixYuZMmUKYWFhmM1mqlevzscff8yUKVMeOr548eK8+uqr9O7dm6JFixIdHY2Hh0e6FeV27doxefJkPvnkE8qUKUNoaGhOfUsiIiIikkkmSy4rb165coXWrVuzfft2ypUr5+jhZEtcXBxLlixhyJAhAPTp04fhw4fTqFEjB49MRERERLKaO1WBzkEeHh5ERkbSrVs3PD09qVu3Lg0bNnT0sEREREQkGxSgc9jIkSMZOXKko4chIiIiuUxUFERHQ5Eijh6JZJYmEYqIiIg4QPfu8OSTjh6FZIUCtIiIiIgDnD8PFy86ehSSFQrQIiIiIg4QEQFxcRAf7+iRSGYpQIuIiIg4QGSkcRkd7dhxSOYpQGfQvn37aNq0KX5+fvj5+fHiiy8ybNgwYmJiUr3PmDFj2LlzJxs2bGDmzJncvHkTf3//bI3Dz8+P9u3bJ7nuhx9+oHr16ly5ciVb5xYRERH7iYgwLhWgnU+WV+Ewm82MHz+e8+fP4+7uztSpU7FYLIwZMwaTyUS1atX44IMPcHNznYz+1FNPMWvWrISvR40axU8//US7du0ydH9fX99sB2irkydPUqNGDQC+/fZbypYta5PzioiIiH0oQDuvLAfoHTt2ALBmzRr27duXEKCHDx9OkyZNeP/999m+fTtt2rSx2WATvPMOrF9v23N27w4BARk+PCYmhpCQEIr8b+2ZadOm8fvvvwPQqVMn+vfv/9B9rly5wsiRI1m3bh2dO3emcePGBAYGYjKZWLhwIQULFuTDDz/k+PHjlCxZkqtXr7Jo0aKHFvbu2LEjmzdvpkaNGty9e5fo6GhKliwJwL1793jvvfcSdi8cP3481atXZ+XKlfzwww/ExcVRqFAh5s2bx+bNm/nll1+Iiori0qVLvPrqq7z44otZ+vGJiIhIxsXGGv3PAGm8mS25VJbLw88//zwTJ04E4Nq1a5QsWZITJ07QuHFjAJo3b87u3bttM8pcYu/evfj5+dGhQwdefPFF2rRpQ9OmTdmxYwdXrlxh3bp1rF69ms2bNxMYGJjmucLDw+nYsSMrV66kVKlS7Ny5k+3btxMWFsYXX3zBlClTCA4OTvG+rVq1YufOnVgsFr7//vskFfDFixfz1FNPsWLFCiZOnIi/vz/x8fGEhYWxbNkyVq9eTVxcHMeOHQPg/v37fPLJJyxatIh///vftvthiYiISKqs/c+gCrQzytZGKh4eHrz77rts27aNuXPnsmPHDkwmEwA+Pj7cu3cvzfvPmzeP+fPnZ/6BAwIyVS22FWsLR2hoKK+88kpCZTgoKIiGDRtiMpnw9PSkXr16BAUFpXu+mjVrAlCmTBmio6O5evUq9evXB6B48eJUrlw5xfvly5ePGjVqcOjQIbZt28asWbNYvXo1AKdPn2bv3r1s3boVgLt37+Lm5oanpycjR46kQIECXL9+nbj/vex94oknEsaQVj+3iIiI2I61fQMUoJ1RthuUp0+fzvfff8+ECROITvQMCA8Pp3Dhwmned+jQoQQGBib52L59e3aHlOOKFStGQEAA48ePJyQkhCpVqiS0b8TGxnLo0CEqVqyY7nmsLzasqlWrxuHDhwG4c+cOFy5cSPW+nTp1YtmyZRQpUgQfH5+E6ytXrsyAAQNYsWIFs2fPpnPnzpw6dYoff/yR2bNnM2HCBOLj47FYLCmOQURERHKeArRzy3KA3rRpE5988gkA3t7emEwmateuzb59+wDYuXMnDRs2tM0oc6GqVavi5+fHpEmTaNmyJeXKlaNHjx706NGDtm3bUqtWrUyfs0WLFhQrVoyePXvy3nvvkT9/fjw9PVM89plnnuHgwYN06tQpyfWvv/46W7duxc/Pj8GDB1OtWjUqVqyIt7c3L774IgMHDsTX15eQkJAsfd8iIiKSfQrQzs1ksZYiMykiIoKxY8dy69Yt4uLiePXVV6lSpQoTJkwgNjaWypUrM2nSJNzd3TN13itXrtC6dWu2b9/+0OQ5VxcUFMSpU6fo2LEjoaGhdOrUiR07duDl5eXooYmIiIgN7d8PTZoYn+/YAS1aOHQ4eVZWc2eWe6ALFCjAnDlzHrp+5cqVWT1lnlemTBlmzpzJ8uXLMZvNjB49WuFZRETEBWkSoXPL1iRCsa0CBQqwaNEiRw9DREREcphaOJyb6+xyIiIiIuIkFKCdmwK0iIiIiJ0pQDs3BWgRERERO1MPtHNTgBYRERGxM1WgnZsmEWbQvn37GD58OFWrVgWMjWLKlSvHzJkzU10pY8yYMXTo0IFbt25x7tw5+vfvz4IFC/D398/yOC5evMjkyZMxm83ExcVRu3ZtRo0ahZubGytXrqRv375Jjo+OjqZ9+/b89NNPWX5MERERsS0FaOemCnQmPPXUU6xYsYIVK1awYcMGPD09MxVMfX19sxWeAT7++GP69u3L0qVLWbZsGRcuXEjYvVEreIiIiDgHBWjn5pQV6HfeeYf169fb9Jzdu3cnICAgw8fHxMQQEhJCkSJFAJg2bVrCdt6dOnWif//+D93nypUrjBw5knXr1tG5c2caN25MYGAgJpOJhQsXUrBgQT788EOOHz9OyZIluXr1KosWLUqysPejjz7Kxo0b8fHxoW7dusyePRsPDw8WLVrEnTt38Pf355133mH06NHcvXuXChUqZPMnIyIiIramHmjnpgp0Juzduxc/Pz86dOjAiy++SJs2bWjatCk7duzgypUrrFu3jtWrV7N582YCAwPTPFd4eDgdO3Zk5cqVlCpVip07d7J9+3bCwsL44osvmDJlCsHBwQ/db8SIEdSrV4+PP/6Yp59+mrFjx3Lv3j2GDBlCkSJF8Pf3Z+PGjTz++OOsWrWKnj175tSPQ0RERLJIFWjn5pQV6ICAgExVi23lqaeeYtasWYSGhvLKK68kVIaDgoJo2LAhJpMJT09P6tWrR1BQULrnq1mzJmDsQBgdHc3Vq1epX78+AMWLF6dy5coP3Wfv3r0MGDCAAQMGEB4ezvTp01m4cCFjxoxJOObMmTM0a9YMgHr16uHh4ZT/zCIiIi5LAdq5qQKdBcWKFSMgIIDx48cTEhJClSpVEto3YmNjOXToEBUrVkz3PCaTKcnX1apV4/DhwwDcuXOHCxcuPHSfgIAAdu3aBYCPjw+VKlVKmMRosVgAqFy5csJ5/vzzT+Li4rL2jYqIiEiOSBygY2IcNw7JGpUms6hq1ar4+fkxadIk5s6dy/79++nRowexsbG0a9eOWrVqZfqcLVq0YOfOnfTs2ZOSJUuSP39+PD09kxwze/ZsJk2axEcffYSXlxflypVLmJhYpUoVRo8ezbRp0xg7diy9evWicuXKD51DREREHEs90M7NZLGWLXOJK1eu0Lp1a7Zv355k8lxeEBQUxKlTp+jYsSOhoaF06tSJHTt2pLpMnoiIiDinVq1gxw7j8379YPlyx44nr8pq7lQFOhcpU6YMM2fOZPny5ZjNZkaPHq3wLCIi4oLUA+3cFKBzkQIFCmgtZxERkTxAAdq5aRKhiIiIiJ1FRMD/tpJQgHZCCtAiIiIidhYZCcWKGZ8rQDsfBWgRERERO4uIgEKFwM1NAdoZKUCLiIiI2FlEBBQoAPnyKUA7IwVoERERETsym43NUxSgnZcCtIiIiIgdWTdRUYB2XgrQIiIiInZkXcLO2xu8vBSgnZECtIiIiIgdWQO0KtDOSwFaRERExI4UoJ2fArSIiIiIHakH2vkpQIuIiIjYkSrQzk8BWkRERMSOEk8izJfPWNbObHbsmCRzFKBFRERE7Ch5BRqMdaHFeShAi4iIiNhR8h5oUBuHs1GAFhEREbGjlCrQCtDORQFaRERExI6S90CDArSzUYAWERERsSNVoJ2fArSIiIiIHakH2vkpQIuIiIjYkSrQzk8BWkRERMSO1APt/BSgRUREROxIFWjnpwAtIiIiYkcK0M5PAVpERETEjjSJ0PkpQIuIiIjYUeIeaC8v43MFaOeiAC0iIiJiRxER4OEBnp6qQDsrBWgRERERO4qIMNo3QAHaWSlAi4iIiNhRZKQCtLNTgBYRERGxo4gIo/8ZFKCdlQK0iIiIiB2l1MIRE+O48UjmKUCLiIiI2JF6oJ2fArSIiIiIncTHQ1SUArSzU4AWERERsZOoKONSPdDOTQFaRERExE4Sb+MNCtDOSgFaRERExE4UoF2DArSIiIiInURGGpcK0M5NAVpERETETlSBdg0K0CIiIiJ2Yg3QmkTo3BSgRUREROxEFWjXoAAtIiIiYicK0K5BAVpERETETpJPInR3Nz4UoJ2LArSIiIiInSTvgQbw8lKAdjYK0CIiIiJ2kryFA4w2DgVo56IALSIikkt8/TVs3+7oUUhOyksB2myGKVPg7FlHj8T2PBw9ABERETHCRq9e8NhjcOKEo0cjOSV5DzS4boA+fBjeew9u34aZMx09GttSBVpERCQXCAw0qpN37jh6JJKTUuqBdtUAff++cRkW5thx5AQFaBERkVzg8GHjMjzcseOQnJVaC0dMjGPGk5OiooxLa5B2JQrQIiIiucChQ8alK4YNeSAv9UBb21Xu3XPsOHJClnqgY2NjGTduHFevXiUmJoYhQ4ZQtWpVxowZg8lkolq1anzwwQe4uSmfi4iIZIQ1QMfFGdVILy/HjkdyRl7qgXblCnSWAvTXX39N0aJFCQgIIDQ0lG7duvHEE08wfPhwmjRpwvvvv8/27dtp06aNrccrIiLiciyWBy0cYLRxKEC7ptR6oM1m48Pd3THjygnWAO2KFegslYjbtWvH22+/nfC1u7s7J06coHHjxgA0b96c3bt322aEIiIiLu7KFfjrrwdfu2LFTgyptXCA61WhVYFOxsfHB4D79+8zbNgwhg8fzvTp0zGZTAm338vAy4158+Yxf/78rAxBRETEZSSuPoMmErqyiAhwc0v6DkPiAJ04WDs7V+6BznKTcnBwMP369aNLly507tw5Sb9zeHg4hQsXTvccQ4cOJTAwMMnHdq0gLyIieYy1/7l6deNSAdp1RUYaIfl/NUdAFWhnlKUAfevWLV555RXeeecd/vGPfwBQs2ZN9u3bB8DOnTtp2LCh7UYpIiLiwqwV6GefNS5dMXCIISIiaf8z5I0AHR/v2LHYWpYC9OLFi7l79y4LFy7Ez88PPz8/hg8fzrx58+jRowexsbG0bdvW1mMVERFxSYcOQalSULWq8bUq0K4rIuLhNg1XDdDWFg5wved0lnqgx48fz/jx4x+6fuXKldkekIiISF4SGgoXLsALL0DBgsZ1rhY25IGICPD1TXqdqwZoawUajCp0oUKOG4utaaFmERERBzpyxLhs0AD+N0dfLRwuLC9VoBMHaFebSJilCrSIiIjYhnUCYYMGDyaWqQLtmiwWo60hr/RAJ27hcLUXhapAi4iIOJB1AmH9+mrhcHXR0UaITl6Bti5p52oB2pUr0ArQIiIiDnTokNG6UbWqWjhcXUqbqIDrVqCT90C7EgVoERERB4mKgj//hLp1jS2crQFaFWjXlJcDtCrQIiIiYhMnToDZbPQ/g1o4XJ21JzivBGj1QIuIiIjNWScQ1q9vXKqFw7VZK9B5ZRKhKtAiIiJic9YJhNYKtFo4XFt6LRwxMfYdT05TD7SIiIjY3KFDRu9z7drG145o4fjuOwgJsd/j5WV5rQc6cQuHKtAiIiKSbfHxxiYqNWpA/vzGdV5e4OFhv2rdpUvQvj1MnGifx8vr8loPtFo4RERExKbOnjUqzdb2DauCBe1Xgb5927i8ds0+j5fX5cUe6MKFjc9+PseyAAAgAElEQVTVwiEiIiLZlnwCoZWPj/0CtLVC+Ndf9nm8vC6vtXBERYGvr/G5KtAiIiKSbcknEFr5+NivWmcN0NZKtOSsvBSgrduWlyxpfK0KtIiIiGRbahVoe7ZwWHtyVYG2j7zUAx0ba4ToQoWM708VaBEREcm2w4ehYkUoVizp9T4+RqUyPj7nx6AKtH3lpR5o63Mrf37jRaEq0CKSJXv2uN4anyKSNcHBcOPGw+0bYARo69vfOc0acqKiHoQ7yTl5qYXD+vz19jaq0KpAi0im7doFTz8Ny5c7eiQikhuk1r4B9l0LOnFIVxU65+WlAK0KtIhk24ULxuWlSw4dhojkEqlNIAT7buedeJ1e9UHnvLzUA504QFsr0BaLY8dkSwrQInZw545xefeuY8chIrmDtQKdVoBWBdr15KUe6MQtHAULQlyca31/CtAidqAALSKJHT4MxYtDuXIP32bPFg5VoO0rtRYOLy/j0pUCZvIKNLhWG4cCtIgdWAO09VJE8q67d41dCBs0AJPp4dsd1cKhCnTOy6s90NYA7UoTCRWgRewgLMy4VAVaRI4cMS5TmkAIjmvhUAU651kDdP78Sa93dzc+XDVAW99VUQVaRDJFLRwiYpXWBEJwXAuHKtA5LzLS6AlO6Z2HfPlcK0AnX8YOVIEWkUxSgBYRq7SWsAOtwuHKIiIebt+wcrUArQq0iGSbWjhExOrwYSNUVK+e8u1ahcN1pRegXWmzLVfvgfZw9ABE8gJVoEUEjIB0/LjRvuGRyl9gV1qFIzY2lkuXLnH27FmCgoISPkJDQylatGjCR7FixZJ8XbRoUUqUKMHjjz9OPusMOxcQEfHw1u1WrlaBTtzCYd2W3pUq0ArQInZgDdDh4cZamKn94RQR13byJMTGpt6+AfZt4bh9+yIwBTe3YA4fNtO2bRxmsznFD4vFgre3Nz4+PhQoUIACBQo89Lm7uzsXL14kKCiIs2fPcvHiRcxmc5bH5+XlRf369WnSpEnCR5UqVTCl1ETsBCIjoWzZlG/Ll8+1VmpKXIF2+1+/gyrQIpIpiX8p3ruXegVCRFxbWhuoWNmjhSMuLo45c+awc+f7QATx8UZg/+GHpMe5u7snfJhMJiIjI7FkcDu5UqVKJQTeKlWqULVq1YTPixcvzr179wgNDSUsLCzFj+vXr/P777/zxx9/sH//fubNmwdAiRIlaNy4cZJQXcwJfqlaLEYFOvkmKlauVoFOHKCt61wrQItIhsXFJa0k3b2rAC2SV6U3gRByvoXjwIEDvPbaaxw+fBgPjxKYTIuoX78LR464c+eOOx4eRmB2c3N7qNJrsViIiooiIiKCiIgIwsPDk3weGxtL+fLlqVy5MoWsja+psLZqpCcyMpLDhw+zb9++hI+tW7eydetWADw9PenRowfDhg2jUaNGWf/B5LDYWDCb894kQm/vBxVotXCISIYl73tWH7SIc4iKMiYAP/KI7c55+LARJurWTf2YnGrhuHfvHuPHj2f+/PnEx8czYMAADh4M4OLFkpQubbzYTyvgAZhMJry9vfH29qZEiRK2HWAqvL29adq0KU2bNk24LiQkhP3797Nv3z6+/PJLVq5cycqVK2natCnDhg3jpZdewtPT0y7jy6jUNlGxcrUAbe2Bzp//wUYxrlSB1iocIjkseU+bArSIc/DzM1bKSLxSRXbExxsBunr1tENqTrRwbNq0iRo1ajB37lyqVq3Kjh07+M9//kNcXEm8vY1txcF5VuIoVaoUnTp1YuLEiZw4cYIffviBjh07smfPHnr16kWlSpWYMmUKN2/edPRQE1ifR2kF6Ph444WMK9AydiKSLdYl7KwUoEVyv9On4YsvjP+voaG2OeeFC8b50mrfgAcByxYB+vLly3Tr1o1u3bpx8+ZNPvjgA44cOUKLFi0AI+Tkzw/WYrIzrgVtMplo06YNmzdv5vTp0wwbNoy7d+/y3nvvUb58eQYNGsQR6/aPDmStQKfVAw2uU4V29WXsFKBFcpi1Al2yZNKvRST3mj37weeJl3rLjoxMIARjS2dv7+xX6/773/9Ss2ZNNm3aRPPmzTly5Aj+/v7kT7SPdGSkEXCcrQKdmmrVqjFnzhyuXLnCnDlzKF++PJ999hn169dn4cKFDh1bRlo4wHUCdOJl7FSBFpFMswbmChWMS1WgRXK327dh+fIHX9uqhSMjEwitfHyyV4E+evQogwYNwsPDg6VLl7Jjxw6eeOKJh46LijICjjNXoFNSuHBhhg0bRmBgIJs3b6ZEiRK8++67XL161WFjymsBOnEF2jqRMHkFOjQ0lD179vDZZ5+xcOFC4q0LRjsBTSIUyWHWAF2+PPzxhwK0SG73738bYadIEeP/r60C9OHDxmVGAnTBglkP0GazmcGDBxMXF8fq1atp3759qsdaWzhcpQKdnJubGx07dmT69OkMHjyYkSNHsnbtWoeMJSM90OB6ATpfPgvXrl0jf/6TnD9/kjfeOMnJk8bHjRs3ktynbdu2VKlSxQGjzTwFaJEcZu2BVgVaJPeLiYF584wA26+f8bktK9Bly4Kvb/rH+vjAtWtZe5y5c+dy4MAB+vTpk2Z4jo83wpqz90BnxMCBA/n0009Zt24dr776Ks8//7zdx5DXeqCN/zf7qVnzxYTKf0QELFpk9K1XrFiR9u3bU6NGDWrUqEHjxo2dJjyDArRIjlMLh4jzWL/eCK7Dhz+Yt2CLAB0SYpy3U6eMHZ/VFo7z588zfvx4SpQowaxZs9I81hrUnHEVjsxyc3Nj4cKFNGzYkDfffJOjR4/afYvw9Fo4rJuNuEqAvnXrD6AtwcF3efHFF/nll5rExtbg559rUL16dQqktRSNE1APtEgOS9zCAQrQIrmVxQIff2z0ag4b9qBSaItJhMeOGZf16mXs+IIFjWp4bGzGH8NisfDPf/6TiIgIZs+ejW86pe7E6/S6egUaoEGDBrzxxhucPn2ajz/+2O6Pn5d6oI8ePcqJE22AOyxfvpwvv/ySSpUmEhvbmwYNGjh9eAYFaJEclzxAaxUOkdzp11+NeQrdukGlSkawBNtUoK2tXKVKZez4rKwFvWLFCrZt20a7du3o06dPuscn3inO1SvQVhMnTqR06dJMnDiRixcv2vWx80qA/vPPP3n++ecxm2/j4/Mpffv2BYwXhZGRrrPOtQK0SA6z/uFUBVokd7N2PIwYYVxaK9C2CNCJl/TKiMwG6JCQEEaMGIGPjw+LFy9+aAvulCReJaFwYWP5PFcP0EWLFiUgIIDIyEiGDx9u18dO7zngCgH69OnTtG7dmps3b1KixCKKFXsl4TbrWtA5tUW9vSlAi+Qwa8XZ19f4BakALZL7nD0LX30FjRrB008b1zkyQFvXzc1o2Hj77be5ffs2U6ZMoWLFipkaU/78YDIZVWhXbuGw6tu3L82aNWPTpk1s2bLFbo/r6hXooKAgWrVqxfXr15kzZw5eXq+TaMlxl9tMRQFaJIfduWP8YrRWeRSgRXKfuXONHuiRI40wCbmjAp2RjSc2b97MmjVraNKkCW+++WaGx5S4hQOMPmhXr0CDsQLEggULcHd3Z+jQoUTZaqecdKQUoL/55hs++ugjYmJiEgJ0TIxdhmNTFy9epFWrVly9epWAgACGDRuWsESilattpqIALZLDwsKM9WTBuFSAFsldwsLgs8+gXDl46aUH19tyEmF6S5gll9EWjrt37zJkyBA8PT359NNPcXd3z/CYErdwgFGBvn3beCHh6urUqcPbb7/NuXPnmD59ul0eM3mAvn//Pn379mX06NE8++yz3Lt3DnC+CvSVK1do2bIlly5dYvLkyYwePRowXjQmfr6rAi0imXLnzoMAXbiwJhGK5DZLlhhBdehQ8PR8cL0tJxHmVAvHuHHjuHLlCmPHjqV27dpZGpP1+yxRAszmvPMi39/fn0cffZSpU6cSFBSU44+X/DmwatUq7t69S5UqVThw4ADTpjUA1jlVgA4ODqZVq1acP3+e999/n3HjxgHGizBVoEUkW+7cgaJFjc8LFzb+IJrNjh2TiBhiY43NUnx84NVXk96W21s4du3axcKFC6lRo0ZCcMmM5C0c1pU48kIfNEChQoX4+OOPiY6OZtiwYVhyuPSeuAJtsViYP38+Hh4e/PrrryxbtgyzOQ7owdKlrxNpq917clBISAitW7fmzJkzjBkzBn9//4TbrG0o6oEWkSyJjjb+SCWuQIPr/AIRcXZffgmXL8PAgVCsWNLbckOATq0CHR0dzeDBgwH49NNPs7QpSEoVaMgbfdBWL7/8Mq1bt2bLli189dVXOfpYiQP0r7/+yvHjx3nppZcoU6YM/fv3Z/r034G67Nz5CU2aNOHkyZM5Op7suHHjBi1btuTkyZOMHDmSKVOmJFn5JaXnuyrQIpJh1naN5AE6r7xFKpKbWTdOMZng7bcfvt2WPdC2buGYPHkyp06d4o033uBp67IhmZTXK9BgTCicP38+np6evP3220RYU24OSBygFyxYAJBk0mflyk8Ae2nadAjHjh2jYcOGLFu2LMcr45l1/fp1WrZsyZ9//smwYcOYOXPmQ8smJu+vB1WgRSQTrAE6cQsHKECL5Aa7d8OBA/D3v0PVqg/f7sge6JRaOMLDw1m/fj0vv/wyU6ZMoVy5ckyZMiXLY0oecvJiBRrgiSeeYNSoUQmT4HKK9TkQGnqNDRs2UKdOHZ599tmE2403Ebzp1Gkh69evx9PTk4EDB9KvXz/u5ZLUGRwcnFB5HjFiBLNnz05xzfGUArT1RWEu+VayTQFaJAclr0BbLxWgRRwv+cYpyeWGFo7Q0AehuVSpUrz88susX7+eypUrs3r1agpbX5VnY0yJV+GAvFWBtho/fjwVKlRgxowZ9OvXj59//pn4+HibPkZEhBGSP/3038TFxfHWW28lCZ+J14H+xz/+waFDh2jcuDErV67kySef5ODBgzYdT2Zdu3aNFi1acOrUKUaPHs1HH32U6oY9aVWg1cIhIumy7kKYvIVDK3GIONb587BxI/ztb9C8ecrHOCpAR0REsG/fF8DLzJz5IDSXLVuW9957j8OHDxMYGEizZs2yNaaU1oGGvFeBBvDx8WHlypVUrFiRFStW0LJlS6pVq8bEiRO5dOmSTR4jIgK8vWP45JNPKFKkyEPbrSffSKVSpUr8+uuvjB49mjNnztC0aVMmTZpEnAP2wr569SotWrTg9OnTvPvuu8yYMSPN3S7T6oFWBVpE0qUeaJHcae5ciI83qs+p5QB7t3DExsYydOhQfH19GTu2O7AeH5+yjBs3LiE0T5o0iXr16mVoq+70pLQONOTNCjRAs2bNOHPmDL/88gv9+/fn+vXrvP/++zz22GO0bduWtWvXZmvTlYgIMJk2cv36dQYOHIiP9W2G/0lpJ0IvLy8CAgLYtm0bpUuXZsKECTRv3pyzZ89meRyZdfnyZZ577jnOnDnDuHHjmDp1arrPP1WgRSRb1AMtkvvExMDSpfDoo/Dyy6kfZzIZAcBWkwi9vMAtlb+60dHRdO/enfnz51O6dGnefHMccIhOnQKZPHmyzUJz8jGBeqATM5lMNG/enGXLlnH9+nU+/fRTmjZtyg8//EDPnj159NFHeeuttwgMDMz0uSMjITLSmDz4xhtvPHR7Wlt5P//88xw7doyePXuyZ88e6tevz5IlS3J8guGlS5do0aIFQUFBjB8/nkmTJmXoeahJhCKSLapAi+Q+wcHGH/FWrYxQm5b8+W1XgU6t+hwREUGXLl346quvaNWqFceOHePDDycD9YmIsG1oTkyrcKStUKFCDBo0iF27dnHy5Eneffdd8uXLx4IFC3jqqae4ePFips53795RoqJ+5YUXXqBatWoP3Z5WgAYoVqwYn3/+OatXr8bT05PXXnuNv//979y4cSOz31qGXLx4kRYtWnDu3Dk++OAD/vWvf2X4RZyWsRORbEmtB1oBWsRxQkKMy1Kl0j/W29t2Adq6hXNi9+7do2PHjnz//fd06NCBzZs34+Pjk6GNVGwxJnhQJfTxMV5Q5OUKdGqeeOIJpk2bxuXLl/noo48ICwujV69exMbGZvgcERFG9fmtt95K8Xbri7n0diLs1asXR48epVWrVmzevJk6derw9ddfZ3gcGXH+/Hmee+45zp8/z4cffoi/v3+m3gHJC6tweDh6ACKuLHkLh1bhEHE8RwXo5BXosLAw2rdvz969e3nppZdYvXo1Xv9LUfnyGe0e6W3lnR3JQ47JZFShVYFOnYeHByNGjODAgQOsWbMGf3//DC19d/NmGPHxK8mfvyIdOnRI8Zj0KtCJlS9fnm3btjF37lzGjBlDly5dGDRoELNmzaKQtVciHdHR0QQHB3Pt2jWuXr3KtWvXEj62b99OcHAwEydOZPz48Rk6X2IpBWh3d+P/gKtUoBWgRXJQai0cWoVDxHEyG6Ct7yRlR2TkgxfSALdu3eKFF17g0KFD9OnTh2XLluHh8eBPsslkVOzsEaATB/sSJYwWF0mdyWRi8eLF7N+/n6lTp9KyZUuef/75NO+zdOkyIILHHnsDd3f3FI/JTIAGcHNzY/jw4bRp04a+ffuydOlS/vvf/5IvXz7c3d3T/AgNDeWvNF4peXh4MH36dP7v//4vY4NJJqXnFhh90KpAi0i61MIhkvtkNkDbahKhNUxcv36d559/nhMnTjB48GAWL16cYqjy8bFvCwcYFeg//wSz2agYSsqKFCnCmjVrePrpp/Hz8+Pw4cOULl06xWPj4+NZsmQhkI/HH38l1XNmNkBb1apVi3379jF58mS2bt1KXFwcZrM5xY/Y2FiioqLw9fWlXr16lC1blkcfffShjzJlymRpe3irlJ5bYLwoVAVaRNJlrTRbg7MCtIjjZSZAWycRWiypL3eXHovlQYC+fPkyrVu35syZMwwbNizVndzACBs5Wa1LrQJtsRi/u6yTCiVljRo1Ytq0aYwePZr+/fuzZcsW3FJYZmXbtm2cO3cG6E+xYiVTPV9WAzQYy919+OGHfPjhh5m/cw5IqYUDjAr0rVv2H09O0CRCkRx0545RRfL0NL7Ol8+YKKIALeI4ma1AWyzG0ndZZQ1EFss5mjdvzpkzZxgzZkya4RmM3x32aOFIvBKJVuLInBEjRtC+fXu+//57PvrooxSPWbBgwf8+eyvFiaRWbm7g4ZG951pukVqAtlagc3j1PbtQgBbJQXfuPGjfsCpSRAFaxJGsAdrXN/1jbbEbYXh4PPAFBw8258KFC0ycOJEpU6aku6qBtYUjp8JGZKQRcBIPQ2tBZ46bmxvLli2jTJkyjBs3jn379iW5/fz582zevJlatRoDDdMM0GAUWbJSgc5tUts4qFAhYwMjW0zMdTQFaJEcFBb2cIAuXFgBWsSRQkKMSlh6YQYeBICs9EGbzWbWrl3LM8/UBboTHR3MRx99xPjx4zO0JFjBgkZ4tkUPdkqioh4OOKpAZ16pUqVYuXIlZrOZnj17cifRLPHFixdjsVjo0sVYui69rdxdJUCnVYEG15hIqAAtkkOsfYSJZ96DEaC1CoeI44SEZKx9A7JWgTabzXz++efUqVOHnj17cvbsKaAf3bqdZOTIkRk+j3Ut6Jxq44iKejjgqAKdNa1ateK9997jwoULvPbaa1gsFiIjI1m6dCklS5akSZPuQPov2lw9QLvSdt6aRCiSQyIjIS4u5Qr0/fua5S7iCBaLEaAbNszY8dYAkJEAHRcXx5o1a5g0aRKBgYG4u7szcOBA/vGPcXTsWJVHHsncWBNvplIy9blnWWZt4UhMFeis++CDD9ixYwfr1q2jTZs2eHh48NdffzF27Fji4owfdF4J0Gm1cIAq0Bw5cgQ/Pz/A2PKxV69e9O7dmw8++ID4+HibDFDEWSVfws7KuhKHK7wCF3E2YWHGC1tbVqDj4uJYvnw5NWvWxM/Pj6CgIAYPHszp06f57LPP8PWtmuRcGWV9uzsnK9DJx6QKdNZ5eHiwevVqihUrxrBhw5g8eTJubm68/vrrREQYx+SVAJ1eC4cr/P3LcoBesmQJ48ePJ/p//9JTp05l+PDhrF69GovFwvbt2202SBFnlHwTFSstZSfiOJlZgQPSD9Bms5lmzZoxYMAALly4wD//+U/OnDnDkiVLqFy5cpL7ZjZA53QLhyrQtlehQgU+++wzIiMjOXv2LJ07d6ZChQoZfg64eoBWBRrjSTJv3ryEr0+cOEHjxo0BaN68Obt3787+6CRPuHsXnnoKvv7a0SOxreTbeFtpO28BY6mqVq3g008dPZK8JasBOrWJfD///DN79+6ldevWnD17lsWLF/PYY48lOSa7ATqnqnWOqkDPmwcdOhhtbK6oa9euDB06FDCWuQNUgf4fVaCBtm3bJtl21GKxJMwq9vHx4V4GXl7MmzeP6tWrJ/lo3bp1VockTurIEdi3DzZscPRIbEsVaEnL5cuwYwcsXuzokeQtmQ3Q6fVA//e//wXA39+fChUqpHhMVgN0TrZwxMUZAdYRFegVK2DrVrhyJecew9HmzJnDhQsXeO6554DMB2hnXyc5tZ0IVYFO6USJdt8JDw+nsDUlpGHo0KEEBgYm+VDrR95jrXRcvuzYcdhaej3QWokjb7O+gDp82DWqMc7Cli0c9+/f58svv6RSpUo888wzqZ4jN7ZwpBZwvL2Nj5ysQAcFGZcXL+bcYziayWSiYsWKCV9nJkBbLMYLHGcWFWVsCuORbKkKLWOXgpo1ayYsIL5z504aZnSKs+R5oaHG5aVLjh2HrakCLWmx/vubzXDggGPHkpfYMkBv2LCB8PBw+vXrl+a6zrmxhSOlbbytihfPuQp0WNiDcO7KATq5zPRAg/O3caS0RCK41jJ2NgvQ7777LvPmzaNHjx7ExsbStm1bW51aXJz1l+mVK87/tlViqfVAK0ALJP3337XLcePIa2wZoK3tG9bVqFKTG1s4UutRBaMPOqcq0NbqM+StAJ2ZCjQ4f4COjEz5+e5KFehsrQNdrlw51q1bB0ClSpVYuXKlTQYleYv1F3VUFNy6lbHtdZ1Bei0cCtB5W+J/f825tp+bN43L7E4ivHz5Mj/99BPPPPMMVapUSfMcztTCAUYF+uhRo40g+Vvw2aUAnfZxXl7GpbMHaFWgRewgcaXDldo4Umvh0CocAkn//ffsAS2dbx8hIWAyPVhtIj2pTSJctWoVFouFfv36pXsOZ2vhsP5srO11tqQAnfZxrlKBTi9Au0IFWgFasuSvv4wluP7X9p4tiQO0K00kdIYWjogIeOEFWLPG0SPJe6z//qVKGe9WnDzp2PHkFSEhRkDMaGU1pRYOi8XC8uXLyZcvHy+//HK658iNLRzpVaAhZ/qgz5598HleCtB5sQc6rRYOVaAlz/r5Z2MJrk2bsn8uVw/QuXkVjj17YNs2GDXKWJdY7McaoNu1My7VB20fISEZb9+AlAP0wYMHOXXqFF26dKFo8lfIKciNLRzp9UBDzvRBBwUZ7wDUqmW84+hK817SYq1A55UAndImPaAKtAjXrhmXtqhQuGqADgsz/lBYf2FY5aYK9OHDxuW1a7B6tWPHktdYX0ApQNtPXJzxOysrATpxD7R18mBG2jfA+Vo4crICHRQEZctC9erGGKyTOl1dRAR4ehofabEGaGcuaFgsxguAlAK0l5fx7o8q0JJnWQP0rVvZP9ft2w9+qbhaD3ShQuCW7H9ZbgrQhw49+HzmzLxTDcoNrP/+Tz1lvEuhiYQ5z/r7KjsV6JiYGD7//HNKlSrFCy+8kKFzOFsLR05VoKOi4OpVqFoVrEsk55U2joiI9PufwTUq0Naxp/TcshaVVIGWPMvWFejHHwd3d9eqQN+583D/Mxi/ID09Uw7QZrOZ8PBwIiMjiY6OJjY2lri4OOLj47HkQLo9dMj4ZdanD5w4YewOJvZh/fcvWhSaNjV6Q2/ccOyYXF1ml7CDhycRbt26lb/++ovevXvjmV45kaT3zY0tHPasQJ8/b7xIr1JFATo1rhCg03u+FyzoGgHaxgvUSF5x9apxmd0KtNlsBM0GDYxA4WoBunz5h683mYyK4927xmSks2fPsm3bNrZt28aOHTu4k0ZztMlkwmQy4e7uTrFixfD19aVUqVIJl4k/9/X1pXjx4kl2CU0sKsqYuNaggYnhw6uwapUnM2ZAhw62+glIWqwBulAheOYZ+O47oye9a1fHjsuVZSVAJ69AL1++HID+/ftn+BxZDdDu7kagyskWDntWoK0rcOTFAJ3ausjJuUKATuu5BcbvPFcoFihAS5bYqgJtXSu5eHGIjTUCRE6sPWpv8fFGgK5d++Hbbt26hZvbdi5c2EalSj9yMdFfkCpVqvD0009jsVgSqs7x8fEPfW42m7l9+zbBwcGcOHEiW2P94w/o2LEUjz02gF9+GcyBA9Vo1Chbp5QMuHvXqEh5eMDTTxvX7dqlAJ2Tshug//rrLzZv3kydOnWoV69ehs+R1QANRrXOVVbhyMsBOiICihVL/7i8EKALFky6GouzcvKYIo6SOEBbLEZVNSusFY5ixYzJBbt2QXBwypVbZ3L/vvFzsbZwREREMG3aNL799lsOHTqU0I5x924x/vGPf9CmTRvatGlDpUqVMv1YsbGx3Lp1i5s3bxISEkJISEjC56Ghoam2fvz5J+zcCU8/HcHJk99w4cIMYAYdOz7Hxx8P5qWXXsI7K3/xJUPu3n3QD9+kiVFtzOpEwvh4eP11aNYM0tkUL0/LTgtHVBSsXbuW2NjYdLfuTi4y0vj3zWDHRxI+PvZv4cipCrQ1NCUO0K407yUtztTCcesWDB4MH34ImXidmCC9F4yFChmTJGNiHmwc44wUoCXTwsMfrCAQF2cEgeRLtWWU9Rd08eIPqh6XLzt/gE68hJ3FYuGVV15h7dq1eHl50aJFC86fb8OFC89z48bf8PR0z9ZjeXp6UjPe81sAACAASURBVKZMGcqUKZOp+w0ZYgToefOgZs0oNmzYyD//+Sk3b/6En98vDB06lL59+zJ48OBMVdvSYrFY+Omnn9i0aRMxGZhmbq22x8XFJblM/Hn58uVp1aoVrVq1wteJtrFM/P/Gxwfq14fff099A4K07NkDS5bAsWMK0GnJSoB2czP+yEdGGqtvuLm50bt370w9bkbfvk+Jj0/OrFTh6Ap0kSJGJTIvVKDNZiMQO0uAXrcOvvrKaK3Myq/+jFSgwSg0WZ9rzkgBWjItODjp17du2SZAW/9TXbr04C1tZ5V4G++ZM2eydu1annnmGb777jsKFixI585w4YLxRywrVSlbOHTIaB+oVQvy5ctP7969MJl60bv3Wf72t8+4du0/zJ8/n/nz59OoUSMGDRpE165dKV26dKYf686dOyxfvpyFCxcSGBho8+/l3//+NwB169aldevWtG7dmubNm1Mo+RqCucjdu0lfKD79tBGgf//d6InOjPXrjcsLF2w2PJeUlQANRvgNDQ3k9Ol9tG3blkcffTRT989OgC5Y0Jh8Z2tphRwvL+Nxc6IHunjxB+/MVayYNwJ0WtX+5HJDgP7lF+Myq733GemBtp5fAVryFGv7htWtW0ZFISsSB2hrLnOFiYTWCvTt29tYvHgMZcuW5YsvvqDg/14lJN7O2/o2vj2ZzXD0qDU8P7i+e3cYO7YqJ09OISjoQ/bv38Knn37Kli1bOHDgAEOGDKFx48Z07tyZzp07U6dOnTTfyj527BgLFixg5cqVhIeH4+XllVDVfuSRR9Idp8lkwsPDA3d39xQv3dzcOHHiBNu3b2f79u389ttvHD16lFmzZuHh4UHjxo0TAnWjRo0okJESkB3ExhqhKvG//TPPGO8G7N6duQAdHw9ffGF8fv169sKaq8tOgL5501j7OTOTB62yW4GOijL+z7pn782qJNILdcWL27YCbTYbLwQaNHhwXcWKxuo/jvo9aC8Z3cYbHB+gLRZjozTI+koZ6T23XGUzFQVoyTTrChzlysGVK9n7JZs4QFurca4ToM/x1Vc98PDw4Msvv0wSGB29FvTp08Yf9fr1k17v4QEjRsDw4bBkiSfvv9+FLl26cPXqVdasWcM333zDb7/9xr59+xg/fjwVKlSgU6dOdO7cmRYtWpA/f35iYmLYuHEjCxYs4NdffwWgQoUKvPfeewwaNIhSmU0v6WjcuDGNGzdm7NixREZGsnv37oRAvXfvXnbv3s3EiRNxc3OjVq1aPPnkkzRs2JCGDRtSt25dh/R5W/9wFCpkISoqmvDwcCpWDAfus3lzOA0b3ic8PJz7943LqKgoihYtSokSJZJ8FC5cmL17TQn/J8F4B6d6dbt/S04hJMR4x6dQIQs7dvxM5cqVqWhtxk1D/vzx3Ly5gkKFCtGlS5dMP25kZMYmkKUk8VJ2tgyZabVwgNEHfeaM7R7vyhXjhWPiYkuFCsblxYtQp47tHiu3caYAHRj44IVmVivQ6T23XGU7bwVoyTRrBbpePeOXYnaWsnPVAH3jRjjQlcjIUJYuXUqTJk2S3O7o7bytOxAmrgZZDRpkTB6ZNw9GjzZ+6ZctW5ZRo0YxatQoQkND+e677/jmm2/YunUrCxcuZOHChfj4+PDcc8/xxx9/cP36dQDatGnDm2++SadOnXC3ZfksFd7e3gkVZ4CwsDB++eUXduzYwcGDBzl06BDHjh1j2bJlALi7u1O7dm0aNmzIk08+SefOnSlXrlyOj/Py5VBgAd9/Pw9v76QNrjt3QqtWGTuPh4cHXl7FgRIUKlSCe/fKMG5ceZo1K0/58sZHhQoVKFWqVKrLGeYlISFQrNhp2rV7i23btlGwYEHmz5+f7qRAi+UXzObLdO/+SpbexYiMhEx2fSRIvJmKLQN0RirQ9+/bbqJX4v5nq8QrcShAGxwdoK3VZ8h+BTq9Fg5VoCXPsQboOnXg229tV4EuWdL4D+fss7ItFgsLFrwCHKNNmzd45ZVXHjrG0RVo6w6EySvQYPzBHjIEpkyB5cuNzxMrVqwYvXr1olevXsTGxrJ7926++eYbvvnmG7Zs2UKRIkV4++23GTJkCNUdXAotWrQoXbp0Sagams1mTp06xcGDB/n99985ePAghw8f5siRIyxdupQJEyZw5MgRypYtmyPjCQ4OZtasWSxcuBi4h8VSlDZt2lCwYEF8fHzYs6cgQUE+vPVWQSpU8Em4Pl++fISFhfHXX3899HHgwF+YTCHcvx8IxLNhA2zYkPRxPT09KVeuHOXLl+fRRx/FYrEQHR1NTEwM0dHRKX5erVo1evbsSbdu3SiS1UkOuUhERARXrkwhLi6AbdtiaN68OYcOHWLAgAF8//33LFq0KNXv8969zG3dnVx2WzjA9itxpBdyEq/EkYFuq3QlXoHDKq8sZZeZZQwdHaCt/c+QcwFaFWjJs6wBum5d49JWFWiTyahCO3sFOiAggD/+WAc8y9Chs1I8xtEB2lqBTilAAwwdCh99ZHy89lrqvZeenp4899xzPPfcc8ycOZPLly9TvHhxfKx/9XMZd3d3atWqRa1atRJ6WePi4jh58iSff/45U6dOpU+fPmzfvt2mFfNz584REBDAf/7zH6KjoylRogzh4e8zdOg/CQh4MNFx3jwYNgyefBIGDEj/vHv2GJMP+/eHAQPMtGwZQr//Z++6w6Oo3u7Z9JCEIoRikIQuIEVsCEj5FFAQpCpFUbGiFAuKBX8qig1FEFRERBEUFDs2UBBQiiBdhNBJICG0FCAJKXu/P05udrPZ3Sk7my2Z8zzLkt27M7M7M/eee+5533dkCvr2TUVqatlHSkoK/vzzT6dpDS0WCyIjIxEREYHIyEiEhoZi2bJlWLZsGR588EH06dMHw4YNQ58+fQIyteHSpUsxduw4FBYeRlRUfSxcOB0DBw7EoUOHMGLECCxatAjr16/HZ599ho4OEcznz59HVtZXABLRufN1mvddVMSHpwTaaLKhtMxun4nDCAKtpEAHMwJFgZb+57p1gcxMzy0cwe6BNtf0TGhGWhrJbqtW/NsoBRoggT550nYDBhqWL1+Op59+GrGxCQC+Qq1aztc+fUmghaAC3aiR6+wpdesCI0dy0PvuO/XbvuSSS/yWPLtCWFgYWrdujSlTpmDgwIFYvXo1pkyZYsi2d+7ciREjRqBZs2aYPXs2EhISMHv2bMydexDABMTHl80SIoMH161Tt32ZfWPIEKBx41AA9VBQcA0GDx6MRx99FNOmTcOSJUuwYcMGpKWlIT8/H0ePHkVaWhpOnz6Nc+fOoaCgAMXFxcjLy0N2djZOnDiB9PR07Nu3Dy+99BIaNWqEb775BkOGDEGdOnVw5513YtmyZSgqKjLkN/ImDh06hH79+qFfv344duwogCfRv/9uDBo0CBaLBY0aNcKaNWvw3HPPISUlBV26dMHkyZNRXFxcuo1vv/0WVus5ACNRXKx9yPSkiApQ1sJhJJQsHEbngjYJtDoCLe0yviDQ+/YxELlrV5JcbyvQgU6gTQXahGakpTGKXaoSnijQmZkM6pGcSwaVHD0KNG3q2XFWNA4cOIChQ4ciPDwcPXp8g2+/reOSoNpn4ahoHDvGc9ali/t2jz8OzJ0LTJ0KDByov1hOoMBisWDu3Ln4559/8OKLL6Jbt27oovQjucD27dvx3HPPYenSpQCYXu+pp57CkCFDEBYWhsWL2c7R09qmDe8FNQVVZPaNatWAHj24ShAW5j6VXUREhGp7SpMmTTBp0iQ8++yz2LFjBxYtWoRFixbh008/xaeffor4+HgMGjQIDRo0QEREBCIiIhAeHu70/2FhYYqFR+Li4pCUlIQ6dep47Ne+cOECpk6diilTpiA/Px9du3bFgw++h2HDWsLx64eHh2Py5Mm44YYbMGLECDz//PP4/fffsXDhQjRo0ACffvppScs7kJ+v3Q/sKYH2lYXD6FzQBw7wN7BPV1+vHvt/k0Db4EsFWvqfu3UDNm6smDR2gQyTQJvQBCFIwC691JgO9swZRqfLsdU+kDCQCPS5c+fQv39/ZGZmYt68eVi+/GoArhVeXyrQ7gII7dG8OdCvHxPq//UXq9wFO2rUqIFFixahS5cuGD58OLZv346aUopTiTVr1qB37944f/48OnXqhKeffhq9e/cuQyDleXck0GFhrEq4ciUnl+4yN2zcyPtk5EgbqWvQwPhc0BaLBW3btkXbtm3xyiuvYP369Vi0aBG+/PJLzJ4929idAYiKikJiYiIaNmyIpKQkNGzYsPT/SUlJsFgsOHfuHM6ePVv6bP//nJwcfPLJJ9i3bx/q1KmDuXPnYvjw4fjpJ/7+rpLAdOnSBTt27MD999+Pr776Cm3btsVLL72E33//HTVrXovTp5uWSz2oBkYRaG9YOOSkyxmMVKCFIIFu3LjsRDwkhH1+sBPoQPFAS/9z167A++/rPy9K39dUoE1USmRn8+ZISGDHW7265x5oe34SiJk4hBC4++678e+//+Lhhx/G3XffXbq0LgsGOMKXWTjcBRA64oknSKCnTq0cBBoAOnbsiMmTJ+PZZ5/FqFGj8N1336ku27x69Wr07t0bhYWF+PLLLzFkyBCn7VwRaO6fBHr9eqB3b9f7srdvSCQl8bPeygUdEhKCTp06oVOnTpg+fTo2btyInJwcFBYWoqCgoPRh/3dhYSEKCwsVt52VlYVDhw7h0KFDOHz4sEcFd0JCQjBu3DhMnjy5NDBQTQ7oGjVq4Msvv8S8efMwbtw4jB07FgDQpMlInD6tz1rmzxYOd8dkpAJ96hTJkrN6AYmJwB9/6KvAGSgIBAVa+p9r16ZAFhvLSZsQ2lcfTQXahAknkAGEMiVTzZr6O1ghSKDtleZAItAFBQXYvXs3FixYgK+++grXXXcd3n6bQYPZ2VR3XHWYgaBAA/TkduwILF0K/Pcf0LKld4/NXzBx4kSsXLkSP/zwA2bNmlVKpNxh1apV6NOnDwoLC/HVV1+hX79+Ltu6I9DSB712rWsCLQTtG1Wr0r4hkZTE54rIBR0WFlYu4M5I5OTk4PDhwzh8+HApsT5y5AgsFgvi4uIQGxtb5tn+/82aNUNjB7amtoiKxWLBPffcg86dO2P48OE4duwYLr30Vvz9t28ItLcsHHl57gmrkQq0M/+zhPRBHz0KNGni+b78EXoIdEGB947HGQ4c4Pg+ZAgJc1wci98oTbScwfRAmzDhBI4EulYtYMsWfbPUs2d5g9qX8pQeaH9LZZeRkYHt27djx44d2L59O7Zv347du3eXBlLVr18fS5YsQXhJXe6sLNo3XP0mviTQW7cC8fHq89I+8QQwYAAzcnz0kXePzV8QGhqKBQsWoG3btpgwYQI6d+6My93MOOzJ89dff42+ffu63b5ceXBGoDt04HXjLpBw40beI3fcUbaSpCTQR44EfjGVqlWrok2bNmgj0/14CK1VCJs3b45//vkHBQUFeOop/si+JNBGq3VKiq+RCrSzFHYS9oGEJoH2nQJt738GyqaaM5pAmwq0CZc4eBB4+23g9dfV3TCBBGcKdGEhb4S4ONefcwbHDByA/yjQ+fn5WLJkCT7//HNs3boVGRkZZd6vUqUKrrjiilJvaP/+/VFH1iIHCZK71Lm+ItBZWSyn26OH+glPv35As2bAwoXAyy+XDQIKZtSrVw/z589H7969cdttt2HLli2lpdjt8ccff6BPnz4oKipSRZ4B9wp09erMcPP337y3SuZkZeDMvgHYCLTRPuhggJ4y3jK9nyQQkhhogT9bOJxczqWoaAU6mH3QkkD7swfa3v8MlE01Fx+vbVtmGjsTujF7NjBrFvDjj74+EuPhTIEG9PmgnRHouDgST18R6AMHDuDJJ59E/fr1MXLkSPz666+IiopC3759MWnSJCxZsgR79+5FTk4ONmzYgA8++AAPPfQQLnaQc7OzXfufAc7Mw8MrnkBv385nNfYNiZAQYPx4LikuWuSd4/JX3HTTTZgwYQL27duHMWPGlHt/5cqV6NOnD4qLi/HNN9+oIs+AewIN0MaRl2c7X/awt2/07Fn2PZNAu4Yk0FrJAGBT0oJJgVaycMgAViMU6MpOoOU14K9p7KT/uVYtm03PE5uFkgItf4dAV6BNAu0F7NnD5//+8+1xeAPOFGhAXyfrjEADtHE4s3BYrVbs3bsX6enphuagLS4uxtKlS3HTTTehadOmmDp1KiwWCyZOnIiDBw/i8OHD+OGHH/DSSy9h8ODBaNq0qdsiG0VF7BjcKdAWCwlQRRNoLQGE9hgyhJ5uqXxWJkyZMgVXXXUV5s+fjwULFpS+vmLFilLy/O233+Lmm29WvU153l2t2khrsbN0dps2kWz061fWvgGYBNodTpzg762HyMrPBJMHWsnbGhbGPswoBTo01EaW7VEZCLQWC0dICMWViiTQhw7Rg961q21l0hObhRKBDgkhQQ90Bdq0cHgBMng8GAn0sWN8lrlUjVagAdo4du4sb4OYP39+aVlsi8WC+Ph41K1bt8yjTp06qFu3LuLj41GjRo3SR7Vq1cqR3oyMDHz00Uf44IMPkFLC2Dt16oTRo0dj8ODBiHRkJyohyZFS9eOqVSs+C4eWAEJ7xMfTG7diBSc30qteGRAREYHFixejXbt2GD16NDp06IAjR46gb9++sFqt+Pbbb9HbXboMJ8jJIfl1dYnZBxKOH1/2PVf2DYATW6Vc0JUVJ05os2/Yw5cE2hsWDiHUZb246CLjFOjEROd2pPr1+WwSaBsiIyuWQDv6nwHPFGg117xJoE2UQ2EhPdAAsGuXb4/FG0hL4wAtibMnCnRmJp+dEWiANg57EtqzZ0889thjOHr0KI4fP47jx4/j8OHD2LFjh+K+LBYLqlatWkqoY2Ji8Pfff6OwsBAxMTF48MEHMXr0aEMCliQpdmfhAEigDx3yeHeasHUrO3E9ObaHDCGB/uor4LHHjD82f0ajRo0wZ84cDBs2DDfffDNSUlIghMD333+PG2+8UfP2cnLc5xNu1Ihkb+3asgG6QpBAx8WVt28AVPm8kQs60GG1ssLpVVfp+7w/KNBGLndLcqZEoGvW9HwcO3cOyMgomy3GHpGRjKuoDARa7TVQ0QTa0f8MGKNAu9OgPKl06C8wCbTBOHiQS/gAsHev6yCgQEVaGjs7WSjMCAXasViEfSaOyy6zvZ6QkIC33nqr3HZyc3ORkZFRSqrT09Nx6tQpZGZmOn0kJycjNzcXrVq1wujRo3HHHXegqtbqCG4gCbQaBfrsWQ7uHhZeU4ULF7gqcuWVJFpaMWAA8NBDJHCVjUADwNChQ/H777/jo48+QmRkJL7//nv06tVL17aUCLTFQhX62295H8hl7n/+IdEYMcI1+ZG5oIM5r65WZGWxX/ZUgfZFEKE3LBxKZbwlLrqIx+9JXnEpKDnzP0skJvLaLi7W1zf5O7R4oAHfKNA1azJ4WcKTQL/8fPIed+cyNtZmCQ1UmATaYEj7hsXCDnvfvuDJnWu1AunpQPv2tte84YHWmomjSpUqpdXK1KKwsLA05ZzRyMrisxoCLQQHRq0ZTPRg1y5ek1rtGxK1a3OJb+VKnht5nioTZsyYgRo1auDmm29GV3u5RiNycgC7pC1O0bEjCfS6dTYC7c6+IWGfC7pZM92HGFTQk4HDHr4MIoyO5nhiJIGWx6RGgQbYV6usAF8O7lLYSSQmAhs2cHyRlo5ggj9bOA4fZl8xYEBZIcc+jZ1WqMkdHRfHa7qiBCRvIEAP238hCXTnznwOJh/06dNU1O0TTnjLAw14NxOHt8gzoF6Blu9XVCCh3gBCe0ji9tVXnh9PICImJgZTp071iDwXF3NQUlr0sPdBA2XtG+6EbzOQsDw8JdC+tHBYLFShjbRwKAV5SRiRC9pdBg6JYA8kzM2lGqt22NFLoFetYr5+IbR9BijrfwY8U6CVMrwA3kvPWJEwCbTBkAR6wAA+B5MP2jEDB+AfCrS/QYsHGqg4Aq03gNAeAwdSLaiM2TiMgiRCSgS6fXsOpJJAb95MUty3r/vBSZIRk0DbcPIknwORQAMk0L6wcBiRC9ok0CTQVaqoz72vl0C//DIwYYK2glfO/M+A5wq0EoEOhmIqJoE2GMnJJBiyim8wKdCOGTgAWwerV4G2WMortXIJz9+qEaqFFgsHUHGZOLZupQpi7yvXitq12dGuXx+4ExxfQ22WlshI+tV37KAKpMa+AZgKtDMYpUD7wgMNkMz4wsJhKtDGQKuHXC+BloH5jz5q854rYdUqxiG1bl32dU890GoV6EAOJDQJtMFITgYaNmQUfVxc8CvQERH8nnoJdPXq5QMNIiPpDw1UgqYliBCoGAXaamVRjksv9WwgB2wE7uuvPT+uygilIir26NSJ5+7vv0mgY2MBpaQfJoEuj0C2cADes3BUlAJdt64tGNIZgp1ASwVaLSSB1mLFADj2WCy8Vu66i3YxdzhyhP1Ely7lfcieprFT44EGTAXaRAkyM7lU2Lw5L+KWLW2ZOIIBzgg0QB+0XguHo31D4pJLmNjdatW+XV/DHy0cBw6wo/LEviFh2jg8gxYCLQuqzJzJlIf9+ikrO2Yu6PII5CBCwKZAayVUrlBRHuiCApI0d+ozYCPQgbrqqAStBFpWI9TKHbKzKZIMGgT8+Scwfbr79tK+4eh/BjxPY6fWwmEq0CYA2PzPzZvzuVUr3gAyCjnQ4Y5AnzqlvXN3R6AbNOAMXHoXAwn+qEAbEUAoUacOFYt16zjJMaENegj0Dz/wWcm+AZA8X3KJSaDtEQwKdHExCakR0JOFQw+OHKEIokSg4+JoIzAVaELmT9Zi4xCC9sHq1YH332c//cwzwL//uv6MK/8zoF+Btlp5naq1cJgKtAkA5Qm0TF8XLDYOVwS6Zk3e6DJVjxrk5XGW6k6BBgLTxqHWA12RWTiMCCC0h2nj0A8tBDo+3lb0JjbWffYNeyQlMSWYHs9uMOLECa4KSkKoFf5AoAHjyIaWPNCAfgVajf9ZIjGRBNoold1fIIQ+DzSgjUDn5TFNabVq7Dc+/JBEduRI1xOvVavY3ln9sKgo2iu1XnNqry1TgTZRBs4UaCB4AgnT0nhTOVoT9KSyc1WFUMKbBLqwEJgxA9i40fhtA8GvQAO0cVgswWXj+PVXYOlS7+9HC4EGbOns+vZVPwjb54I2QQJdq5b+Ih1GBBF6UtTG6JRfWoMI9SrQWgn0+fOe+a39EfKa8bYC7Tju9O0LjBrFvv+ll8q3T01loGGXLs7vC4tFX7VAtfYgM4jQRBkEuwJ97BgzcDim4tGTys5VFUIJbxHokydZAvmRR4Dnnzd22xLZ2ewAlTqQiszCsW0bbTGuJixaUbcuO961a23ZWQIdo0YBgwcDx497dz9aCfTNN/P57rvV78MMJCyLEyf02zcAzz3QUVHqU5g5g9HVCNWSnOrVedwVpUADwWfj0FpEBbARaC2WHWcrn2+/zd/11VcZiGwPd/YNidhY/Qq0mcbOhCYkJ/OiqFuXf19yCS/AYFCgi4qAjIzy9g1AnwLtKge0hH05b6OwdStw1VW2xPHesodkZSmrz0DFKdDHj/NhlH1DIphsHNnZtDwUFDBgz9v7AtQT6EGDOPHr0UP9PkwCbUNhIfsbXQQ6Lw9ISystgqGXQHua+cZXFo7QUJJoTxXoJk2U28o+3yTQninQ9ivEVasC8+fTlzxyZFmbpbsAQglTgXYPk0AbhOJiBgvKDByALRNHcnLgZ+LIyKCXyxmB9kSBrigLx6JFXAo/coTLWS1aeE85zc72LwIt/c9G2TckBg0KHhvHvn22/7//vndVEa0KNGCbpKqFSaBtkBN7XQT6tttoQk9NRXS07wi0rywcAPt3TxToqlXVec+DVYHW44E3wsIh0bUrV1z37gWeesr2+qpVPDfuxgU9CrTa72sq0CZKceQIL3Zp35CQmTjkTDxQ4SqAEPCOAl23LrMJeEqgi4uBiROB4cO5vR9+ACZNYrGWrCxtgY9qkZ2tnMIOqLggQul/NlqBrlsXuO462jjk9RGokAQ6MZH+fC2VvLRCD4HWCpNA26A7A8eqVTTF5+YCb73lUwLtLQuHmuO66CL211qD+6xWemwbN1ZnXwlWAl3RCrQz8WbKFIpGM2cCK1ZQPNq/n/23u7iAuDheK0VF6o/DVKBNaMaePXx2JNDB4oN2R6C9oUCHhtJv7YmFIzMT6N0beOMNoFkzBg327cv3ZDVFo1XoCxfYgahRoKOiSOorikAbrUADtHEIEfg2jr17+fzqqyQV06Z5b9WoIgi0mQvaBl0EWgjg6af5/xo1gA8/xMURp3QHEfqrhUOtAl1QoJ28p6fzu6vxPwMmgbaHHgItPdDOxJvoaGDBAvYJd91lS4vpzv8M6CO5pgfahGY4BhBKBEsmjopWoAHaONLTtc1+JXbtot95+XKS6L//ZoJ5CW8RaLUZOACqMlWrVoyFo0YNm8fQSASLjUMS6I4dGUyYkuK971QRBNrMBW2DJNDx8Ro+9MMPwIYNvMCffx7IzcU9uTMrpYVDbyYOLQGEAM9PdLRJoAHjFWgAuOIKrr4ePUpLB+De/wzoI7laLRymAm2ilEDbkzQgeBRoSTQl8bSHNxRogATAatVuD/jlF+Caa9iBP/ssx0LHWbk/EGiAJMqbWTjOnqU94fLLPcsC4Ar16gGdOwN//cXJjpHYswf4/ntjt+kKe/dy0LrkEuCxx1hpcepU7+SkzckhwfUkrZkaeJILevly4J9/DD8kj7F4MSsyaoFmBbq4mBUoQkKAl18G7r0XqFkTt2fNREiuNrnMauXvH8gWDj39O6CdQFssnOQHK4H2lQfaHs88A1x5JVcU4uKUbX3eVKDNQiomSpGczA5AFj2QaNAgODJxqLFweEOBBrTZOIQAHnyQY+CXX3L8c+bx8jaBVuOBBryvQO/YwWdvOEkn+AAAIABJREFU2DckvGXjeOIJoH9/7/urhSCBbtKEnKlRIwqP27bRL2g0cnJ43r0xobGH9EFrjSPIy6PV6Y47DD8kj7BzJzBsGEmAFmgm0AsXssO++24qIjExwLhxqFacidtz52jatxai6g6+tHBUlAIN0MZx+rRxEwV/gFRkK8rC4Y5Ah4fTylGlCtO5hoW536YeBVrttRUezu9pKtAmkJxMsuzYUVosNO8nJ+uzIvgLJImpV6/8e1FR7OCNzAMN2CwHWghAcjIJd79+7sse+5MCnZPjvepb3gogtIe3bBwHD/LZWwVvJE6e5Dlo1sz22hNP8HnqVOP3Jwm0t6E3kHDzZipUe/ZomxR7G3/+yefNm7V9ThOBvnAB+N//OLLbJ4ofMwZ5oTF4VLyFovPqWY2uKoRnz5ZjLL7OwgHoV6DVpLCTkD7oYCoA5Ms0ds5w6aVclfzkE+Vt6rFZaLnmY2NNAl3pkZPDpVJH/7NEq1YckAI5E0daGgd92ZE7olYt7ZUIY2OBiAjXbfSkslu+nM89e7pv5y0CrbaMt0S1aiTP3lJcvBlAKHHxxUwR+Oefxtk4hLANops2GbNNV5D+Z3sCfdVVDLBZvhzYvt3Y/fk7gV6/3vb/deuMOhrPsXYtn/ft0zboaiLQs2fzwhszxtYBAcBFF+HXxAeQgDQUfbJQ9b41E+hVq7gEUrcu8NBDpUuXvs7CAehToCMinNv+XCEYAwn9xQNtj4svdj2W20OPzULL6kZcnGnhqPSQA7ArAh0MPui0NOf2DQmtuULPnHGvPgP6CPSyZXxWItC1a3P5yh8UaMB7No5t29gZO3rzjYa0cXzzjTHby862daze9uLK+9fRfvXkk3x+803j9iWESaD1wv5YpDVJDU6cIJFT/M3PnqXnq2pVWwYOO/za4jEUIBxhb79Bj5gKqCbQQgDvvcdqOVlZlBHff5/qyw03oM767xCCYsPIRkUp0A0baiufLgn0sX25DOL88suKKdXqRRjigT56lEt8bgIasrNt5beNgh4FWguBNhVoEy4zcEgEeiaOCxfYeboj0LVqsaNQG6V+5oxyWWmt1QgvXKCA06JFWfHIGUJCaEfxBw804B0CXVgI/Psv0Lq1stdNEVYrmaYLr8mgQXw2ysZhP2n65x/vWVwA5wo0ANx0E+/dxYuNW1I+f57fRe0EyxPoIdBCkEDXqsV7RKq+vkZaGr+HXLGSKytqIMt4K3rOp03jMtoTTzit/JF3UQI+xUiEHdgLfPutqn2rItAFBQzcePhhqgorVvDLfv010L07sGIFEsYMwAE0RvdNb+ivamIHSXIkUXMHPQp0Zibbq/I/Z2RQ+Xj9dfT8ZBj+QwvcPT4OuPZaFrK57DKbMhKA0OuBjkIeEtctAnr14mB4661Aly4uFaWsLBLeEE9ZndXKicuNNyIxjbNpbyvQ3uzfvQmTQBsAJQId6Aq09D+7W4rTolIUFpIwKhHoiy7iwKNWgV63jiReSX2WSEig5cBqVddeDbRaOCSB9obIsns3x2aP/c/5+WTIzZsDHTowzYlDj5eQQBvHmjUsG+4p7M/5mTM2P7Q34IpAWyzAhAmMXZg+3Zh9VUQKOwk9uaBTUnj+unYF2rShfaagwGuHqBpSfb71Vj7rIdBucfIklxpq17bl+HJAdDTwBp6EsFiA115TNeorEugTJ4DrrwfmzKHPatMmkqSwMGDgQGDlSmDnTly46wHE4ySGb5/IKlD33GMrMaoD+fkkaWrIlh4F2m0AYU4OMGsW84tefDHtKjfeCDz1FGqvWIyLkYbk+M7A+PFMiXP8ON+/996KUaMNZnOaLBxCABs24Mq5DyId9XDjp8PpI+vQARgwgNfHFVcAf/xR7qNqC3i5xYoVwNVXc+KybBk6fHw/QlDsVQ90UZE2q4o/wSTQBkCJQDdoQA+brxXonBzgiy+0D4juMnBIaMkFLUmmEoG2WKgkqyXQ0v/cq5e69gkJvHmlR9II+JOFw5AAwqws/qDffcf11Y0bOfBdey3w669lBhsjbRxS8ZXH7k0f9L59PA/OSNbw4bzuP/zQdt16gook0HpyQUv7RocOnBBduABs2eLZcZw44Xk6QqmEjxpF4qeWO54/TwKjSKBfeYVS2HPPuTSHRkcD+9AM2dcPYiTj778r7t8tmdi6lTnF/vqLM4O//rJ5GOxx2WUImTMb9XEU7zWZxo5r3jzeHDNmKB6Dq+NSm0ZRjwLtlEDv2QOMHcvjHzuWE/GwMKZ8+d//gG++QdHeg6gZkoX7mq7mrPWtt7gE1a4dy4N6W41+4w2gTh2nBFUvVBHotDTg9deptl17LRJ//QDnEYO11z1FJWTdOq5IvPsu5f0ePfjb2PW/2dkerGxt2ULl6YYbeG0PGwYMHIiqR/7FXfjEqwo0ELg+aJNAG4DkZN4crhTakBDaCvbs8V0mjk2bgPbtgaFDabXTAjUEWotKoSaFncQll5CUqym5vWwZl3i7dFFuC3gnkNBfLBzFxSR9AAPidCE9nVLkmjVkx8nJZC4DBrAyzU03sfLIsmWAEBg4kB/77TfPj19OmuQ2vUWgrVYS6GbNnC/xR0RQCDt3jvFlnqIiCTRAG0damnqFZ8MGPl97LU8t4LkPeuJEpiP0JJvK2rVMe9WhAy1J//6rrlKkqgDCI0fYKSYlAfff77KZJMEpw5/if157TXH/Lgn0F19whnL0KOssL15sixR0gvBwIDeiBj6t+SiXTH76iV/qmWe4DY3Qkpu6WjX6mHUp0EnFLIfesycHwVmzuMGXX+aFmZLCRP0vvggMGICwpg2RUN9SNoiwbVtePC+8YFOj77vP+E5zyxb+nidPktQb5F9S9EC/8AIHuqeeYpLz227Djjd+RQOk4Neur9oCWCwWBpauXs1zP2ECB/Rz52C16iTQBw5QJbjiCnbcPXuSQH/+OfDOO7BGRmMy/ocLZ9RHr2r1QAOB64M2CbSHkNbQZs3cL4fJTBzeXIp2BquVK5MdO9o6tdWrtW3DaAVaC4GWPmilMeLECQo6nTu7HYfKwJsEWksWDsD4sWDaNPb/gwezb9SMfft40ezYwU570SJKf23bUmLeupWsaMMGDmidOqH+f8sRGyM0F7pwBkmgb7mF95W3CHRqKsmlYwChPR54gErJjBmeLzVWNIHWmhZs/XqStfbtye8Az3iEEBQaAboR9CA3l5fbFVeQhLRrx750927lz6oi0C+8wA2+9JLbtECSEJxKvIIK4MqVirOCcgTaaiVJGzqU6uv33/NvFUnBY2JKsnCEhHAV6LXX+OPInIsakJ+vXoG2WGjN1qJAp/+XicfwFnqOacqcor/9RmVjyRKSxGefdZ4TFbxm09IcJkjh4UwruGkT+6C5c6lGy2VHT1FQwLzfxcWMHr5wgQKBATk03XqgT5zg6kfdugwaTU8HFi9G7nW9YEWo8/6mY0eS/c6d6VXu0AG52/dBCA0WjowMrgJcein7dkmgly3jzQ8ACQnIvPsxJCANHda/rfn7lpkw5Oc7tcaYCnQlx9GjvGBc2TckfOGDzshgP/vEEyS4v/1G+9y6ddpsXloUaKMJtNpMHHI1Va3/GfAOgZbL/GoJkjcU6J07WbK1Th32yZoLdmzeTPZ0+DDJxaxZ5UPp27VjINWWLSTS69fDcmMvrBGd0Xzfjx4by1NTedzNm1O42rJFdeIDTSj1PzcVtKn8/HO5NtWqUZg8fhz47DPP9ucLBRpQZ+PIzydRbdeOg1+DBrzntfYX9ti5k/0QoH3iLrFpE1fupCIubT1qfNCKBHrXLuDTTylrDxvmdluSEOTlwZalQ0GFLkMmTp7kjPDVV+lt2LCBSqdKxMQ4EI0772TJ1cWLNf+4ZSwcVis7irlz+WM7We5TzLIklaQvvgDuuw9TFyXgLUxA+Onj9C5v28ZjHDyYZNgNEhO5OaeiSbt2JLXPP0+y2auXMWr0a69RLLj3XlopPv+cs5VevbQZ7p3ArYXj4485U3jqKQaSlqSmUkxjV7cuJ3DjxgG7dqFK1ytxM5a6Fm5OnmR//eijJMgXX8x+PTGR52zjRto3HFDwyJM4gXj02v66aq9jOQV67VoO9ldeyWOwGxsCvZy3SaA9hJL/WaKiM3EsW8YgoGXLSKJ37OD90akT7wMtOam1KNDesHAAygRa2uIU/c/5+QzYadMG3ZY8jFAUGa5AV6miOEaUwuggwoICVpArKOB4KM+LaqxYAXTrxpnQ++9zoHLHwC+/3Eakb7kFl+euwxe5fVHcuCllcJ3G4ZQUTgAiImhBOX9eneKoFXv3Ao1wAA9804vWlD59nHqcHnmEguGbb3o2N/BnAr1lC8fya6/l3xYL+4vjx7WXz5awt6v+9Zc+C5u0kEhFXOY0V+ODViTQkybxhL7yimK+tTIEuls3Blt9+63bCzMvDwhBMdps+ICDxI8/Ur3euNGmqqhEbKxDHuiQEGDmTJ6osWM1/bhlLByTJ3OV6b77+J3i4qhM3nor7SU//ogWMSk4c1pwIlVUxJnR/Pm8Mbp04SyzeXMq63Pn4oSlDl6uNhWWo0fpJWvbVvWxKeaCjojgxH7TJg5yc+fyWW/y6J07aSlJSLDlrBwyhBOr7Gyer3//1bdtuCHQVivHoujocmU/JYF2G68UHs5lsQULgMJCLEU/DE9+nts9dozK8ujRJB+1a9MPN306J42dOrGf272b59nF8nnsxVXxIp5HdNE52mxUoAyBzsqiRUTOzgcO5LWweDFQXBzwFg4IP0Nqaqpo1qyZSE1N9fWhqMLMmUIAQnz2mft2Bw+y3bBh3j2eCxeEmDCB+woPF2LaNCGKi23vz5jB9+bPV7/N7t35mfx81222bGGbsWOVtzd9Ott+/bVy22XL2PbFF123sVqFqFtXiNq1y37XMsjOFuL119mQgpoQgPgO/cS9I3KVD0QlGjcW4uKLnbyxf78QQ4YIMWcOT1IJNm7koTz+uDH7f/ZZbu+ee3R8+MsvhYiI4OOrr3Tt/9Wh28SHuEcUR0bxQKpUEeKBB4TYuVP1NoqLeQhXX82/332Xm5o3T9chucaFC2Jpx1dELkqOtWdPXkQAbxwHjBzJt5Yu1b9LLde+EVi1ivt75hnltm++ybaLFtlee/ttvvbpp/r2f8MN/Hz//nz++2/t2+jTh59NT+ffZ88KYbEI0bWr8mdfeYWf/flnJ2+uX883O3ViJ6KADz9k8wULSl749lu+cNddLj+zaMI/4m9cxXZxcbwACguVD9wJrriCt1M53HMPt//OO6q3FRYmxLXXCiF+/JGfTUoS4oMPhBgzRoguXYSoVq1MPykAcQbVRVGrNkJERZV9LyREiJYthbj9diGmTRP5y1eLEBSJbt10fU0xZw43+8knKhpfuCDEU0/xAy1aCHH6tLadFRbyhwWE+Omn8u9/9BHfq11biN27tW27BJ0783otd4ktX+7y+tm/n2/dfbe6fWyZt1UcQEN+qFatsucnJkaIHj2EeOklIVavFiIvT/WxFxcLEYYCkRLdVIjQUCH27FH8jLzXz5y2cswDhHj+eSH++0+IO+7gdgAhmjUTy0Z8IsJQoHe4MQx6eadJoD3EmDG8Fv75x3274mJ2fm3beu9Y9u8X4qqSvrpJE+fH9M8/fP/++9Vvt3lz3pPukJLC7Q4frry9559n25Urldv+9x/b3nuv6zY7drDNiBFO3szIIHuQA0JsrBBPPCFEcrIo6s7RfUf1zkKcOaN8MCpQsyb78TI4fFiIBg1sHVpSEkfjggKxZw9fuu8+z/e9fj3HsqQkzhc04d132cvHxak7MS4gSdiP809xwpKYaPve3bqROSoQiOPH2XzQIP4tJxmjR+s+rPL46y8hWrUSAhDpqCPOz1vMEW73biHq1eMOX321zEfkddali/7dTp7Mbfz2m4fHrxKHD6u/LwcNYtvDh22vyd/+wQe17/v8eSEiI9nnLVrE7bz+urZtFBcLcdFFQjRqVPb15s15Syvx3kcecdE/5+WR2QBC/PmnqmNZsIDN58yxO7gWLchGU1LKNj5zRoiHHhJWi0UIQBztOlyItDRV+3GFLl24/3IiQUYGf4zq1YU4cUJxO4WFJf1lh/38TFQUFRB7WK28EH74QYiXXhJ/Jw4We9CME+PLLydpf/dddjrnz5f56K5dHkzihTrRpBwee4wfuu46TQRRvPoqPzdypOs2773HNhdfLMS+fRoOinA58Rk8mNtdv77cW6mp6u9bITgPqoHTIrlVfyHi44W4+WYh3niDM9aCAs3HbI+YGCEeb/g1D2jAAMX2vXqx6YX35vI/nTuX7fP37+eAHh4uBCAOIkmsHTnbvULnZZgE2kfo0YPXSE6OctsrruCAUlRk/HF89hm5DyDEnXe6Pp6CAt7Ml12mfttxcUK0aeO+zfnzNhFPCWPHsu22bcptz55l2169XLeRpK2MSnbokBAPP2xTS+LjhZgypSxRzs8XX4ffxvcvu0yIY8eUD8gNrFaOpR062L2YmsrRHxBi0iQhxo/nRVBCpDPfnCvCUCBuu82jXYtz54Ro2pQceNWqkheTk4WYO5cjvruHPCG1a5cfSDXiq6+4qbffLnmhqEiI774T4vrrbUS6QQOOji6O5+Azc8S9mCMWXz9HiKVLRf75IhEeLsSVV3p0aERmJhXxkmP5rOoDokmtzLJt9u0T4pJL2OaFF8qwtBtv5MsbNujbvVwd0qPE6kFhIQWfjh2V2yYkcIHGnpQWFAgRHS1E69ba9/3rr/yuTzxB7ggI0bu3tm3ICfQdd5R9/baS2/bgQfefHz6c7crw2/Xrhbj0Ur7Rr5/qY5HX9owZdi9+8glfHD+ef1utXN6LjxcCECdqXSq6Y4VYsUL1blyid2/u6uxZJ2/KpUV3SkMJzp0TIhrnxYG4Nqql3kcfZdNNm5SP84cf2PaVV5TbOoMUFUaNUtc+I0OIFb8V2y6KwYPdLEXa4b//uNRVt66ycj1tmq3vsp9hqkCLFk4EqPR0DhZt2jidBZ44UVZEUMJnn7H97NmaDk0V6tQRollTKzsRFRPOrl2FaI7dwlqlCidoR444b3jkiNh74xiRh5LxMCGBkxUVq0FGwyTQPkKDBi6W7J1ALgHv3Wvc/nNz2WdKcXXhQuXPdO9OopWZqdw2J4fbvvFG5bbR0ZwkKGHECCeDmhvUqOFE1bWDnMSkHbMKsW4dfTJymSgxUYhZs8qpJBKtWxWL2eFjbG2Tk9UdlBPISUTpb5WeLkSzZrYlLIljx4QYN66USB9AQzHtso88Ugoefpi7eW70SX7fq68utwTr9tGokS51xRGbNpXlE2Wwaxdl5JgYbcfWuLGYkviBiA3L0y9SWK1CLF7M0QAQolUrUbBqrQgJoUBSDocOCdGwZEn06adLO3Wpjo0bp+8w7r+fn9e5GqwLSUnKfZRcQXImMHXtyv4iK0vbfiXp+v13/t2sGSfjWhwM0jbx/ntWIb7/XohbbhFi4kQxY9IJAShbYaSFJC9P8J8nn+QyjTyJ586pPpaffuLHXnvN7sULFzjZqlJFiD/+oAIK8O/XXhPPTLggAHZLnkKuhh8/7uTNwkKKABaLIss9ecIqFmCEpqWFl15i82XLlNtK288XX6jadDnk5vLzN9yg3PbCBSHatWP7fzfn82IFuPTgDkVFVDoAWnHUQKrVjRpRGFGJxETyhDKQ3qJ333X6mexsvn3zzer2IW1u9vYro9CkCRflxNq13EmHDm5J7nVX5YltlrZsu2SJ223//LMQdZEmNnR+nPcM4NEYrBcmgfYBzp3j+f6//1PX/rXXtN2vStizh8oQwE5ELf+ZNImfceoLdEBysno14JJL2Fko4aabuE21Y1ebNpwcOLtnc3OFqBqRJybV/9jmZZOK8oIFiqSUy01WkT+pZG29Vi11MosTSJXtttsEJYSWLfnCxInOD/7oUWEdM9Y2A2/UiEZfjUT69x/zxCAsESti+wlrWBi3FRLCLzd7NmdV7h6LFmn3DrrAyZPc/S23uGmUlcWO1cXx/HL7QjEcC8XfYxeQcUZECAGINNQVKePeUO9PsVo5W5071zbLiori4HXhgrLSlZJCWR8gG7RaS8/xkCFafxli6FB+3sPFDk3o1o37dDf5+OILtnnjjfLvPfMM3/v1V237bdWKk2q5on7ffepVTIlRdxaJwfhS5DZrU2ZSVRgVI17FRPHq4yfdfr5NGyGqVhVcMpCqc6NG9IJqxMqVtkWJMpDqr3z071+qUo4bx5e2btW8u3K46y5ua/9+Fw3++IMNrrnGrQJ7ZvI7QgBiX81rVC+bSxfD558rt5W2xs2bVW3aKWrX5q2nBBnzAQjx3HOCK4wl1izx1luuP/jWW2wzdKi2A5P+w2bNbKZ8BcTH89IrRXExJ+dVqriclebnczc9eqg7LMnHf/lFXXstaNeOE18hhM3n5YYYL6g1nm1U+BL//JNNn3lGcPBYs8aYg9YIk0D7AFu38uSr9WYuXcr2U6Z4vu/PPyeplPvXYvv6+Wd+btIk5bayT1bTtl07HpMSrrmGnEjtSo0MIiqnmKekiAO3PS1OoJaNNPbvL8SKFao3PmoUP7pnjyDZDAnhl9BhUpXLzY+MPG2TRcaPVzyWltWOis8uGlNKFEV4OAf57t05aj7/PIn1ihUcPS9c4Db//FPk33m/yLRUt40i7dpxcPDQb6kXVisFZk+8/o8/zq9SapNISxM7bnxC5KDkgq9enSNnRkbZDxYXM1jx3Xc5i5FeZvm44YYy7EMuNZdRFB2Rlsblj5IbrSC/WABCd4CU22V4x+9y9ChVn88/p6w3Zw4DPZcvJwvdt4+DjsKESxIvdytf0ivsbPyScWb/+5/y95M4etRhNUbYlpmnTlWxgcJCIRYsEPsjSHqtISFcutqyRYh33hFFdXhuc0NjGER20jmRTqqbJz6obqc6jx2rSXW2h4w5nDjR4Y1z5yjzN2pULhBNThpUxF4pQhLT7dvdNJI2ho8/dv7+X38Ja1iYOI7aYsJQ9WPs4sXc7KxZym2lQKJ1xcIeV13FBTp3TgwZ85GYyInapZeWdLUpKVxyAXjgjti7lxPp+HiX141LWK28AAB6wVWIHTExbFoK6W1yo0pZrWyiNt5CHpIRKx2OuO46uyDIvXtpPWncuEwwfClKOovk0BYuV33tITmUmuQD3oRJoH0A2alMn66u/YEDbK82MMAZcnNty8Bxcc77ByVkZvLz3bsrt124sGQJ9X3ltnK5VEnUaNqUtjO1ePBBu4HDaiWrHzSo1KZxCheJQ7dN1OxNE4KqBSBsHsWvvyaRDQ/X/OOuXy9EVWSJI3Wvsi2PqiDypUt8qalkMtdcUy5bSJmHxVImSv4oLhZrOz3BKDc/QKtWPDy9kEvV9irtjh1CVMcZ8XX7l0v9pSIqit6VadM4capZs+zvVLeuELfeylF/585y50J65xUzYmRk2JZ67rlH1KxeJFq21PfdykXkb9lCsvPCCwy5/7//IxErCbBR/YiJoYfwrrvKeQ5feIFNli93fVwdOnBczHWSkOb0aX7++uvVf8958/iZUi+8sJFqt8vSFy7Qt1ESN1CAMPFrwqjy7D8vT0yqOkMcDymZJMXG0mpz6lRpk+L1f4tdaGFTnUuDA/RBDvZO7Tv5+U7Z3u238zOubKBaoIokpaZS2axduzyDTU8Xol49YQ0NFV3xh3j4YfX7/u037ltNYF/TprwVPYGMr3Ml8jrGfAwcyPalyX62b+cAGRFR9rwXF9tsNl9+qe/grFaa8gF2IgpNQ0KY6KUUAwbwswqBEBERHArUQI6Ru3apa68FckJUOumXMznHrC9paULUqiXyESFurKciwElozzbiLejlnWFGpsSzWq144YUXkJycjIiICLz88stIlEkdgxBqc0BLJCUx5aPeXND79jE95fbtTKW4ZIn7CmquUL06U0P+/TdTeoa5uQrU5ICWsC/n7a79mTPM8asWshph5rrdwO23MW8nALRrh+dOjsWsU8OQ/kk0oLKylj3KFVMZOJDJa2+5hYUVTp4EHn5YVTWSc8fP4Wf0RoPjm4C77gLefVfV56pWLclzXb8+8LZdxaf8fL5x5Ej5R3o6jrTth3vWjMS5K7vjr1WhgKF3s34kJTHVaFaWhspYdkhNZYrTunVtr7VoARRUqYHnC57FwMOPAvPmMWfru+/aGiUmMul5ly4sQd6kidvfv7SISjOFA6pdG/jjD1bp+egjzI0rwOgT86DnB8/J4fm2pB0DHn+cRQwcUacO82snJtoe9eoxoWxWlutHejrwySfM/zpuHIt91KihmAv6wgXmgJYFVBxx0UX8/TdssOsvcnNZRe/HH/kbV6/OXMAlzznzq6MnquGWutWBPdWAuDgkWCzomATsXQUUpzqkXbZaub3XX+cFEBGBQzeNRvdfnsSo+5PQy7Gfi4rCls7jkPTzfTg55UPEznyVBUpmzuR3Ly6GZepUtIQVPzUcgz47XlNfotQFyuSBdoRM3OsAl6W8dUAevtuqbfXrs8rfs88yV7LsTwoLme83PR2p49/E6hndcJWGY5I5+5WqERYX8zqTxW70wj4XtH0/IPHUUxwPH3+ct3p6OgukLlnCAoVo04Y5um+6iYWe/vqLg9577wF//sl+fvBgfQdnsfB3/fln5sm/9VZbwQIHFBTw0i7NAZ2WxtLl7doxwb0bREaqr3wq0+1rLuWtAvbVAmNjAfzvf8wB/uKLwMiR3KnVyv+fOoUXYt/B4Wrq8n6beaDtsGzZMjGxZH1r69at4kEduY8CSYGWEd5KkeD2aN+ewpnWTByLF9ssG/ff71wp0gKpYiul35NLu2p8izKQzd0SY3GxcB245QIyfdSv939NZe6224T4809x7KhVAO4zdChB2mocMpZRbpIBZw0aMAJ03jzXJ/v8eXG8ZTcuX10xTNMJ7tSJv4mW4OP0dKo8UVGeW2mOAAAgAElEQVQVG5CmBvI60Ov7TEjgirgjOnfm71S6Al9QQC/eggW6Vh+6daOCpfpeysykJASILWgnir/5TnPEeJPEAvFi9bdsN/PVV9OasXw5Aw48ubGLipgBQmYQqVFDiLfeEquX59t8hk6wbh2bjxnjetP33iuEBcVi7wcrKRfJlD9GP6Kj2ekcPSqefJIvySBER0j/6/Llgr/b9OllVm4u1G8ouuIPTSk73eHIEW769tvVf0a1ZUcFZCIIxRia/HwusYeGCvHvv3xtfIkvdcgQsXoV+001tjwJmQ5R6bsfOsR2ntY7kLZyZ4GIMn1yy5Y26+LZs+wLywWbyyXU+vVpuI2JYV5Ep5GYGiFzRLtJlXHmDJuUxoTIaEwVS7q1arkPnreH1rgiLZBpxsssAk2Zwheffpp/v/566fJSXKxVtGunbtvlAu99BL9QoDdv3ozrrrsOANCuXTv860H1nkBAcjJniVIhVYNWraj2HDpEgUwJBQUs9vT++1QgPvuMhX08RceOLIK0bh1wxRWu2+lVoF0hJ4eTVTVVCCXk5H5NrYHoZVea6bf5fFasPugGLst5t2vHH+fpp1ky9dNP+QAoj3TrZnvUrQv07486/63CVxiEC2M/RTOFqmb2kBP43Fx1IpkQLC19+jQLUV16qepdVQjsFU9ZNU4tCgt5zXXuXP69q66ikLRlC3DddaBMrVdFAhWsBg00qIPVqwPLl2N1q4dw3dHPETKwP6W2F15gSWal1Ya//sJ3Rx9Cq+KdvAHmzAHuucdlFTDNCA2lCnTrrVRip0wBHn8cHevPxDBMwZFDQ+Gs+OyGDXyWFQjLYfdujElfgOewEA0eKCkJ2qABq98NG0ZJPTubMlh2Ng5uycJbz2fj+vZZGHh9yeslsumhw8D69UD7y51ct02aAGPGlJYNXLeOP8011zg/LPuKhD16RAPjx/PG+PBD4NQpbOz4JFbfFIvrXFUh1Ah5nchKa2rgDQW6TDVCZ4iMZMW5vn2pxt9zDzuKFi2Ajz5C/npep1EaVuzUKtCywm3jxuq37QyuqhFmZgJ3381VkAULbN8hNpZi87ffcvVLVv7FiBGsCf7UU1yZEgL44AOXS6Dnz3OBs0MHFQd5111cCfv6a+CXX3gADpBVCKOjQXl+7lyeSBWDuBYFOjubt7/TcuEeQqrEZVY+HnmEav7bb7NE97PPcpVs3jzkJ1hUX1vR0bzHTQVaCPHMM8+IVXZ+o65du4pCjVWXAkWBtlopImnJpyyELRPOd9+pay9T9LZubUwgisS+fdyuUv5hqfqpOY3vvKNsLZMVGd0U73L5GUf1Y9gwvi5FFj3IyOA23OaHl8FpM2fSbOfota1aVQhA7GtxswjHBc2V6mRmBrVxfxs22DzsatKdVjSWLCnvf1ULd4U/Pv+c77kLrlcLmV9cbZS7Pe6/X4gW2CWybhpKCRvg0tIPPzhXpDMymJy95Hr5vvY92oOX9OD0aSEef1xYS4JTd8e0dyrnSs/5wYOCN/qpU1TDZ8wok9kmG3FiZaNR9JS6ufCkOOUshECmy1NKv5yfzyCyMsFXDpD+SVdqp7wONRTocwt5zfTpo/4zHTpw0cwISDFVda5fKX+HhnLFoGQA+f577feR1crv4c6Tm5Jiy56pJluHO0i/uaNPW3rKJ08u/xnZP9hnDC09+Iceshnw3awa3X03m6nO271jB3/fRo2crh7JcXbUKGGL3leRq1sIbjIhQd1htGxJYd0bkFm7yiWukYEOAPvB338XRUX8U0uQddWqynUmvA29vNMg6YOIjY3FebvpsdVqRZgbg+3MmTPRvHnzMo/rr7/eyEPyGtLTOSNT63+WkDNjNT7oFSsoJLVoQdVG677coXFjCj1r17pvl5bGybo7n7SEGgVaKhg1aqg7ToAqscVS4hMugdUK/PYblfGWLdVvyxG1alHILKdA2yMkhMa6MWOoNpw4AezYQVVnwAAgIgLo2xcL+y1BISI0+9CqVuVzdra69hs38nnUKOPESyOh5Ll1h1Q7gdMR0jK4aZOeoyqL/fv5rCeGID4e2I2W2DZxEeWq224Dtm4F+vUDrr4a+OknDivFxVw6at4cmD8f1jbtcC3W4f32c3nheRsXXQS8+SYsycn4LmYELj2/BbjhBuD664E77qBCed11mPxtaxwNuQRJbeJ4M9SqxWMeP57ybu/eEIsWo1XNDNxV9BFNp24uvOXLeb/ecEP59y65BGjUCFizhj+PK2zdSvWtUyfXbRo25L2zbZvz90+c4HNtgxRoqao59UC7QF6eMeozYFMCFRVoienT2TcVF9OzWjKAyOPXokBbLLycXCnQv/8OtG/PvumOO4BBg9Rv2xmcKdBffw0sXMhb7Omny3/m5pup2i5Z4uTg33mHnuVFi1yuFB09SlUbAN54Q+WBtm4NPPoocPAg8Mor5d6WCnSVKqDyDQAPPKBq01oVaG/4nwEXCjTA1a7Wrfn/iROB668vXZ3Rcs3HxSn4+v0Yhg6/7du3x5o1awAA27ZtQzOF6JyxY8ciOTm5zGPFihVGHpLXoDWAUEKSvV273LfLyuIKkVyq8jD+pRwsFto4jh4tS0ztIQSJpbQ5KEFyglOnXLeRHbAWC0dEBEm8/XFu28b99OypKk7PJUJCSMLdEmhnH2rdmsuj33zDQMMffsCpcxyR9BLonBx17Tdv5nP79tr2U1EwgkA7i8lp3JgTLyMItOoAQieIj+fzyZPgjHjxYk6obr0V+OcfjuTXXMN14Ice4mxvxgyc/HkTNuDa0vNdYUhKwoyrFqI9NsPa/XpakhYuBH78EWLtWtQuOobQqHBYmjYFunfnpPCuu0jAjh0DfvoJlqG3oX2naKSksM9whbNnOSm/8krbhNoRXbuyf5OxwM4gJ/YdO7puExLCYOrkZBtRsYfRBDosjA9fEWjVFg6Jpk2B774joxwwoPRlSXK0EGiA59NRHLFayRt79SKJe+89cvWICG3bdkT16iRWkkAfP07eGRXF7TsTdOLi6KL47z8nAlVoKN+UbNAJZsxgkGzVqowj37FD5cE+/zw7rNdftxGDEsjrsm7xMQbctm/Pm0MFIiK0EWg9AdtqIIMIy9ksQkM5q3n7bWDyZAD6rq3Y2MC1cBhKoHv06IGIiAgMHToUr776Kp52Nk0MEugl0GozcYwfz4Hquefce5Q9gVR3XKnQmZm8gdX4nwFtCrQWAg2wf0pNZYcNUOUCPPM/SyQksIN2p4ipgVSQvU2gt2yhomHkioSRqFmTg70eAp2SwmdnBNpi4dhz4ICyF1MJhhFoicsuY0aNnTuZKmfTJpLpESOAPXuAceOQk8tRv8IJNNjvbEV7HPzgN/6AR44A2dn4enERauIM5v/vIC+slSs5Kfz4Y3ZCdl5R2V+sW+d6P6tWkYT07Om6TbdutrauIPskdwo0QAu61eqc7BhNoAH23b4m0JrUuptuKhcnoEclBNhnZ2ba+uCsLPLyZ5/lGLFmDTB6tGeChoTFQhX6yJGyMR+vv+4+5mPIED6XU6EVkJ1NgbhePRJ0gEl+VCE2luy7sJATZiFK35IEuuPujzjAqFSfAfUKdFERr4kKV6ABTtIeeYQrV9BHoE0FWm4sJASTJ0/G4sWL8cUXX6Cxp5EEfgy9BDo0lB3A7t2uCds33zBe7aqrnC9VGQWp7rgaELUEEALeU6ABLukXFtoGxWXLXC8Ta0VCAs9FRoZn25EEWqsSIDs+NQQ6L4+Tr3btHNKA+REsFhI2oy0cgM3GIVV4vdi3j896CLQkZPJaLIPLLgO+/JKkeccOKr316gGwnV9fEWgAOHzEQg9FgwZA1apY/zeHADVBU0r9BWCb2Loj0F278nn1aufvC8F9JCS4zA5WCvtAQkd4i0BrDSL0mYXDBfRYOABOjIUgcd6xg/fiDz8A//d/nHupCrzTgMRE3jNvvw0sXcr9jBnj/jN9+7qwcSjggw+ogo4bxwymrVrR7eFqdbYc+vcH+vThBHTRotKX8/KAEBTjiq1zeQKHDVN9TJGRTCJgx8edQvYr3iLQLhVoJ9ATNBsby88VFWk/Nl/DDx2UgQG9BBrgzZmf75xgZGTYlqo+/bR0YucVXHEFb1JXCrRWAu1tBRpgh3buHI+5fXtjrKQuM3FoRFYWyaPscNRCiwK9cyfJvr/aNySSkmyJGbTAnYUDMM4HvXcvl4H1pKl3qkA7onlzmz+wBH5BoA+XfX39ek7E1KwqX3kl+yN3cRPLl3NAdJnRA7bU1mvW2NRMexw8yH6wUydlNVPmG966tfx7J07Q5qG1r3EHf1CgPSXQnijQADBrFsny/v1MbrFsme2eMBLy3nziCd4zH3+sHPMhbRy7dlGkUoOCAgrIsbHAgw/ympswgYRu+nSVB2uxMGApOhp47LHSji83F7gJv6BqdipXozQMDjK1uF3iKafQK9yohZZczXoVaMDz69oXMAm0TiQnU9nQc9G68kELQfJ86hTw2mveT08WGclBcft250soWgl0TAy36Q0F2p5Ar15NNdoI+wZgHIHOzmZnoDWwTwuB3rKFz4FAoIHyaaiUkJJCe4qrIFMjCXTjxuqCYx2hikA7gb8RaFlApW1bdTEWUVGcdG/d6nywO3yYv+v//Z/yxL9bN/YFzjKdSoXbnf9ZomVL7suVAl2zprErNVFR6gm0EH5g4XACTzzQAC2/4eG0V7/6qr57SA0kgbZaGQOoNl2sVhvH559zrLvvPtt4Pnw4x705czSIAA0bApMmcfY3aRIAEuj7MYfva7BvANoJtLcVaDXXnV4PNBCYPmiTQOvAhQscLPR6UGUmDkcCPX8+i3F1784UqxWBjh2paMrMDvbQSqAtFueBJvbwxMIBkGAtW8b/u1sm1gIjCbSeTkxLFg5pXfCWL94o6A0kTE3lZMmV8njxxUy77QmBPn2a16Ee+wZgW/UIdAK9bRv7MndqsSM6dWJ/4ez3V2PfkJA2Dmc+aLX+Z4CBVq1a0VLguAR84oSx9g1AmwJdWEjyFywWDlkR8LLLaO+/5RbPjkMJsk5C//5M+KAWWmwcQtDrHBpKK69ERARDAM6dsyXPUIUJE6h8vfce8M8/sBxNRR/8hNONrtRcnlESaCUftDerEAL6FGitWTiAwPRBmwRaB/bvZ8eol0BLBdo+kPDIEfqv4uLULVUZBXeBhJJAq83CAZBceFuBXr6caoyWgd8djCTQelYktCrQkZFMbejP0EOgc3NJbt0pTRYLVehjx5hKUg88CSAEOLhWr+7CA+0GcoLkCwKdkECSYH8+1q/nsxbvqrv+QktgrwwkdOaDXreOqxBt1VUDxuWXc+CW5xWgapeZ6R0CrdYDbWQRFfvt+MrCMWoU8NFHLLyjJ/2jVvTty8r08+drC0yMiwNuvJGrG3v2uG/7yy8UsoYNK9/vPPAAtzVjhvpsGIiIIHkWAnjwQTRbNQehsCLlJm3qM6CeQPuTAq1ncmYq0JUM0v+s12LRsCEvMKlAW62srnT2LJeq9Pgy9UKSUGeBQZJQqlWgASrQOTmul53OnOHkQCuJkAT6r7/4+3fv7nmqJAkjCLTV6rkCrUSgCwrogW7TxrveeCOgh0DL9GhKgWOe2jg8CSCUiI8PLAU6LIy/q/35UKxA6ASuAgmLipgLuGFDdVXokpJ4PKtXl/VBZ2WR+Fx9tfprXAYS2vug5STeGwS6sFBdxh6jCXRICCcWnip1ehXoGjVIoo1OqeoK4eHAnXfqu1/U2jhkvucJE8q/V60as3+kp9PmoRrduwO33w5s3oyrV76KHMQhs+dQDRsgtBLoCk9j5wSeeKBNAl1J4EkAIVA+E8fMmcAff3BJ7M47jTtONahdm2rC+vXlA3rS0tiJucrn6gxyedtVmrHMTHbEWhV2WcxFWk2M8j8DtgmCJwT63DmKDnoItNosHLt2cfD2d/8zoI9Au0thZw9PCbRUKj1R0eLjqZY7C4JzBV8SaIAT87Q024C8fj2/R6NG6rdRpw4J8rp1Zb/7pk0cyNXmZbdYqEKfPl12JW7DBt5HauwbEs4CCb2RgQPQVkzFaAINUK0zSoHWSqADCWpsHJs2cQLXs6fr1Y5HHuG48+ab2u51vPkmUL06QqzFWIjbEVnTdf5pV/AXBdptGjsHeEKgTQtHJYGnBBqwZeL49VdGMsfHM2DBiByaWtGpE29Cx9zUaWkkl1qOSZJtVzaOM2e0VSGUCA0F6te3/W2U/xngAHfRRZ4RaE9UALUKdKAEEAK8DqpU0UaglVLYSciMEZ4SaE8V6OJiTgjVwtcEOimJ5DQ1lfd2SgrtG1r7nI4dqRTbL4/rycvuzAetJYBQQpIf+0BCbxFoSYZ9RaBjYnxn4QgkVK3Ka3HnznK1TUoxdSqfn3jC9Xbq12dA4X//sZChatSpA7zzDnKq1ME7GMdKhBrhLx7oiAg+vJnGDjAV6EqDPXuozDZsqH8b0gc9fDg7tA8+ML6zVws5WNn7Gq1WLl1psW8ANgXaWSChECTQetNKSWUyMdF4D15CgmcE2pNOrEoVKvJKBDpQAggBfbmglVLYSdSqxXtv0yblHKnOsHcvf3Ot17Y93OaCdgF/INAAz4ke+4aEMx/0smWc5Hbvrn47znzQcptajqtqVariW7farodgJtC+snAEGtzZOA4eZBG9du1Y2d4dpL1DEm7VuOMOTBhxHMm4VNc14C8WDoAk11Sgy8Mk0BohBGe0elNgSchMHDk5jDC2q7Ra4XBWYezkSSpsegm0MwU6L4+dgacEulcv45X6hATOgPXOgj1ZRrNYSAKUsnBs2cJr7rLLtO/DF0hK4sRCbRootRYOgDaOM2eAQ4e0HZMQ9EA3a+bZNaQnlZ0/EWgZQKiHQDv6oLOygL//ZvVyLYN4o0a871av5nkpKuJ2WrbUvkp1+eW8HqSP3tsEWk0gob9bOIJZgQZo44iIcE6gp02jSPTkk8r9QOvWDEpcs8Z5tip3kNeANxVob1s4AJJcb3mgTQW6EuHkSQ4YnpZRliTokksY5etLXHopBz57RUlPBg7AfTEVvRk4JKRX00j7hoSngYSedmJVq7pXoIuKmK/7sstsHau/Q2suaLUKNKDfB52Wxmwfnq5geEKgY7XbIQ2BI4EOCVFXQMURrVrxOpf9xcqVJCNa70vpgz55kvEgO3aQHGrxP0s4BhIGswJdWKicG9gd8vN57r2Vv9lfUK0axZYdO8pmaDl1Cpg3jyuZUqVWgrR5aFWhZSnvQLZwAOyzvGXhMBXoSgQj/M8AFeyPP6YH2ptLL2oQEkJV6cABWzlrPRk4APcKtKcEeuxYYPZs76j1RhFovedSiUDv2cOBLxD8zxJaAwlTU3ltqIny10ugjfA/A/oJdGys70qwy/Oxdy/z+LZpo4/Mh4RQud63j0RV5mXXE9hrX9ZbS/5nRzgGEgZzECHgmQqdl8fv4Yt4m4qGMxvHu+/yN3j0UfWTiO7d2fd+8w3HSbWoCAJdUQq0WUilPEwCrRFGEWgAuOsumxfa13BcltVaREXCmwp07drMzemNHNmeEmhPVYBq1UiwXHl6A8n/LKGFQMvgNjXqM8DBzGIhEdQCowi0Xg+0r+wbAAOiQkM5addaQMUR9v3FsmWcOOpRs6UPetUqfQGEEpJAy0DCYFagAc8IdH5+8Ns3JPr1K2vjyM1lKfIaNYB77lG/HYuFKrTVSvuHWkgCrcdvroVAR0Z619MeG8uVD6VjMT3QJtzCSALtT3AMDNJLoL2pQHsT/mDhKC52PTAHUgYOCS0EOiuLHahaAh0Xx2Iymzery8kr4WsF2pcEOiyMJFoqPVoKqDhC9hfz59Oic/31+iwBTZoA9erZFOj4eFsFOi2oW5dk2V6Bjoy0Dc5GIRgItFSgKwOqVaO1aPt2rpjMn8+xafRo7asvgwezT5s3T/19L39rPaKPFgLtTfUZUE9y9fjrTQW6EiFYCfTVV1Od8mcF2pvwBwsH4NrGsWULO+E2bfRt3xfQQqDVprCzx5VXskN3labKGXxNoL090ClBnhPAMwVa9hfffce/9eZllz7ojAxeAx076rMWWCxUoY8cYWpBWcbbaJuCPwQRAp6pdfn5lYdAAzYbx+LFwFtvUZEeO1b7dsLCgMce4+/37rvqPpObq8++AdgKhanxQFcUgVYiuXoyvJgKdCVCcjIJoFRagwVVqnAA2ryZHYReAh0XxxR/lU2B9tTCIQm0s0wcViuVtRYt9HfGvkCtWupzQWsJIJTQ44Pet4/Xn6fXoFYCfeECH75UoAEbga5ZU5/SKxEbW7b4RI8e+rclfdCAPv+zhAwk3LbNRqCNRjAo0JXJwgHQxhEeDrz2Gv3Ld97JFQs9GDWKfcesWTZ7hjt4QqD9SYFWO3EzPdAmXKKwkPkjg019lujUidHdmzeTQFepon3At1g4ODtToGXRCT2FVLyNWrU445dpsLTCCAsH4FyB3rePA2Yg2TcAbbmgtaSwk9BKoIuKOIB6qj4DvFaqVVPvgZaDg78QaD0FVBwhvcrNmpVVtrXCnkDr8T9LSB/0X3+RvHqDQPs6iNC0cGhH9eq0ceTm8pp//HH924qJAR56iOPbJ58ot8/N1X/+1RDoCxdIWr2diECtAq2HQIeG8jcyCXQQQwimsCkqYtq3YIR9QZVjx6jK6hlka9UKPAXaYqHa7ksPNOCcQAdiAKGE2lzQehTotm2pLC1bpqzSACTyRUXGEGiAKrRaBdrXOaAlZCpIT+wbEp0789nTtJLNm1MRjIjw7BqXBFpmBQlGBdpTC4cQlc/CAdhsHP36eS6AjRlDcvv668rnIS/Puwp0RWTgANRfd3qvebVZPvwNJoFWgZwcBhA8+ywDXh57zNdH5B3I5dPVq6ms6a3UVrMmCVNRUdnX/ZlAAwywysgof9xqkJ3NmbSaFGzOIDtAZwQ6EAMIJdTmgtbjgY6KAu69F9i/H/jf/5TbG+V/loiP50TRalVu6y8EesgQ4KWXgIcf9nxbAwYAU6YAzzzj2XYsFgZ3ff65Z8SuSRPef7LKojcJtK880J4q0IWFJNGVycIBAMOG8bo3ouZCnTrkACkpwFNPuW9rhIXDXc7viiLQ3lSgAfV5pv0NJoFWwK5dXCr+5hsuNW7ZEjiV4LQiIYHJ5X//nX/rJdDSHy4Js4T82x8tHAC/v9UKHD+u/bMykEPvsrg7BVoSaOnxDCSoDSRMTeVvp7VwzxtvUFWdOpVL9+4gCbRRZeBr12YGEDWVFv2FQEdHA5MmGbPkGxFB8lyvnufb6tkTGDTIs22EhHBVQmZlCUYF2lMCXVnKeDsiIoLXfWKiMdt7/nmmoH33XaZgdIbCQooxFaFAe9vCodanLAm01mJfpgIdhFi0iNHme/cCEyaQWOoNPggUdOxom/F6okAD5X3QZ87Yggz9EZ4EEnoayOGKQAtBAt2smfEpuSoCagl0SgrvLa3XRmws8Omn/P+dd7rvhPft47ORCjSgzgftLwQ62GE/yQxGD7SnFo7KUsbb24iMZCG0kBAGFjqb0MggQ296oCtagVZj4dBTpCc2ltt2VQfBX2ESaCcoKADGjweGD+cNsmQJFa5gL30KlI2C91SBdvRBnznjv/YNwHMC7YkK4CoLx8GDfC0Q/c+AOgJttTJ4U4t9wx6dOgFPPsnfasIE1+2kAu1J9gl7aMnEIc+rSaC9C+mDBkwF2hkqqwLtDVx9NYurHDoEPP10+fflb+1NBboiyngD2hRoPddWXBzHATX3lT/BJNAOSEtj2c533mHasE2b6H+uLLCPgveGAh2MBLqoiLNnbyjQgex/BtR5oE+c4HKnlgBCR7z4ItC6NfDBB8Avvzhvs3cvz7Ge8tXOoIVAmwp0xcAk0O6h16NqwjleeIFJBWbOZOyQPTwp4w0EpgKtl0AHaio7k0DbYfVqEpV164DbbgM2bgzejBuu0Lq17WLW6keVcKZAFxTw5gtGAi3JkUmgy0NNLmg9KewcERlJK0d4OEv0Ovrv8/K4H6PsG4CNoJkE2n/QqhWDeYHgDCI0LRz+hagom5XjnnvKTmwqkkD7Uxo7vQo0EHg+aJNAl+DoUeCGG6iaTp9O/7NRSlUgISzMVuLXSAVa5oAORgJthArgKguHJND2ylogQU0uaD0p7JyhXTsq0enp5bNMHDjAZ6MCCAHTA+2PiIpicBdgOz9GQqsCbbHYKsoZAdPC4X/o0IG5pQ8cYKYuiWDyQGtJY6fn+5oKdICjZk2mplm1iv5no0vABhKmTGHVJpkzViucKdD+nsIOsE0Y9BJoIzzQ9gRaBhA2bOi/mUvUIDGREyhnVRYBfSnsXOGJJ5jjePFiPiSMTmEHmBYOf8W0acDs2dozAaiB1iDC6GhjxxLTwuGfePFF5pd+5x3gzz/5WjB5oCtKgTYJdIAiOpqJ0T0pJRssuPpqYOJE/R2/VKDtCbQ/VyGUiIwk+ddKoI3oxGJi+Hvbk8zUVP6GgRpAKKHkgzZKgQa4gjJ/Pgethx6ylaQ3CXTlwQ03AA884J1ta1WgjbZKmBYO/0R0NCsTWizMypGbG1wWDi2lvE0LhwkTHkAq0PYWjkBQoAHaOI4d05ZOx4hlNIuF5MpegQ50/7OEUiYOIzzQ9mjalFlzMjNZaEUI7xJo08JReRAeTo+1rwh0RAQniaaFw//QoQNXsffvZ87pYAoirFKFY5Q7hbioiA/TwmHChAeoVo2DTKBZOAAS6PPnnRc0cQWjOrHKSqBTU0lM6tQxbp+jRwM9ejAjx4cfkkCHhNAOYxQiI3nOtCjQgZjL20RZREerDyL0htIbE+O5hcNUoL2DyZM5SZ8+HfjtN76m97eWOfHVWDi8PTG3WJSrBXpiDzIVaBMmSmCx0MYRqAo0oM3GYdQyWrVqlZdA169PgmsULBZg3jyek8ceA3bsIHk2MqALoAqtlkBHR/tvESET6hEd7TsFGrAVndAD07lzxJcAACAASURBVAPtXURHMysHwJSagH4F2mLhJF1Jga5SpWL6FaVqgZ5cW6YCbcKEHWrVClwFGtBGoI0K5JAKtLSPbNlCW4M3sglUJNwR6IICZs0wyr5hj/r1gVmzqNadPWusfUMiPp7XudXqvl1OjmnfCBZERfmWQHuiQJsWDu+jY0fg0Udtf+sl0IA6Au1t/7OEWgVazzVvKtAmTNihZk16UIuL+XcwE2gjLRxFReyI0tP5CHT1GSDJjI52TqDT0jhh8AaBBlhNVBZCMjKFnUTt2jxnchLlCjk53vcpmqgYqFGgi4s5OfQWgTaDCP0bL71k6288IdAREcoEuqL6FSUF2pPJmalAmzBhh1q1SIxk9o3KQKA9VQLsy3kHi30DcJ8L2sgUdq72PXs2szLcd5/x21ebicNUoIMHajzQ3iSqsbEMUNMS6CxhKtAVgypVgCVLGMTcubP+7bhToIXgxL0iCXRurk0Uc4TpgTZhwiA4FlMJZgJtpIUDINkKJgINkEA7ywVtZAo7V6hZkyT6ssuM37YaAl1UxIHHJNDBATUKtDeqEErExJA8qbGROML0QFcc2rZlALPM3a0H7gh0Xh77loq0cACu7UOmB9qECYPgWEzlzBneWP6+dOhrCwdQlkAHeg5oCVe5oI1OYVfRUEOg5aBgEujgQFQU7RmulDjA+wQa0KfWmRaOwII7Al1RKewklIqdeHLNm4VUTJiwgzMF2t/VZ4DHGBmpnUBHRHiu6tiX8968GahbF6hXz7Nt+gtcBRJ628LhbdSuzWd3uaDNHNDBBUkQ3Nk4vEmglZRAdzAtHIGFyEhO1pyhoqoQSigVUzFCgTYtHCZMoLwCnZnp31UIJSwWWzEVtTAqEloSrAMHSCyDxb4BKBPoYFagTQIdXFBTjbAiFGg9BNpUoAMLgaRAe0KgIyNZIMhUoE2YQFkF2molgQ4EBRoggc7IAAoL1bU3KpBDEqzVq/lcGQh0SgoJQUX5+IyGSaArH3ytQBth4TAV6MCAVKCdBYxWVBlvCSWV2JNr3mJRzvLhjzAJtAmvwF6Bzs5mBxBIBFoI4Phx5bYyhZmRBPqPP/hcGQh0airVZ4uloo/IGKgh0HKgMwl0cMDXCrRp4ag8kOW8ndk4gkmBBpTzTPsjTAJtwiuwV6ADJQOHhJZAwm++4RLbNdd4vl9JsNLS+BwsAYSA81zQubm8NgLV/wzYCLTpga48kATBtHCY8DYkgXZm4/CVB9pbBNpUoE2YKIG9Ah3MBPrtt/k8bpzn+7UnWDVrBq4v2Bmc5YIOdP8zwMEiLs60cFQm+FqB9sTCIY9LEjMT/g13BNpXCrQ3gggBU4E2YaIU1asDISHBrUCvXw9s2AD07WtMmWj7jrB9+8C1NbiCzAUtCWWgp7CTiI83CXRlgq8JtCcWjvx8IDwcCA019phMeAdqCHRFeaC9mcZObr+gwHXWEX+ESaBNeAUhISTMwaxAS/X50UeN2a89wQom/7OEYy7oQE9hJyEJtKvKcCaBDi74SxChXgJt2jcCB/5o4fCmAu1u+/4Ik0Cb8Bpq1gxeBfrwYeDrr4F27YBu3YzZrz3BCib/s4RjIGEwWDgA5oKWwaTOYBLo4IKvFWhPLRxmAGHgwB8tHN70QAMmgTZhAgB90KdP24qpBAqBvvhiPrsj0DNnMj3fo48aZ7WIibFtKxgV6MREPksCHUwWDsC1jcMk0MEFXwcRemrhMAl04MCfLBzeTGNnv/1A8kGbBNqE11CzJknmoUP8OxAKqQCsKhgf75pAnz0LzJ3LSoFDhxq335AQzsKrVQMaNTJuu/6CYFWgTQJdueAvCrRp4Qh+KBFomT+5IlBRCnQgEegwXx+AieCFzMSxdy+fA0WBBoD69YE9e+hrdVSY580jKXrySZJtI/HII2WV6GCCMwJdsyZQpYqvjsgYyHLeJoGuHPAXD7ReC0fdusYejwnvQckDHRdH4aUi4G0PdL9+wI4dwKWX6vu8L2ASaBNeg8wFHYgEOiEB2LqVnZS9cl5cDMyYwU7igQeM3++LLxq/TX9B7dr83Q4f5sQkNRVo2tTXR+U5lHJB5+RwomWmDgsO+FqB9tTCYSrQgQMlBbqi/M+AssXC02u+c2fg11/1fdZXMC0cJrwG+1zQoaGBpcC5CiT8/ntaUu680/b9TKiDfS7ozEwSgEC3bwDqLBwVOdCZ8C7UEOjc3LJtjYReC0dxMVOEmR7owIFc4XRFoCvK/wwAYWG8drxl4QhEmATahNcgFWiAKm4g2RJcEehp0/j8yCMVezzBgqQkZmX57z/+XVkIdCBNHk24h6+DCKXlSauFQ5KwykRwAh2uFGirteIVaMB9tUCTQJswYSDsFdpAsm8Azgn0pk3A2rXATTcFlk/LnyB90H/+yedAzwENqPNAmwQ6eOBrC0doKLerVYE2y3gHHlwR6HPnaIPzBYF2p0BbLMbHBfkzTAJtwmuwV6CDgUDLwimPPVbxxxMskAR6zRo+B5MC7cwDbbVywDEJdPDA10GEAG0cWgm0PKbKpBAGOlwR6IpOYScRG+s+jV1UVGCtNHsKk0Cb8BqCSYFOTQW+/BJo3Rq4/nrfHVegQxLodev4HAwEOiqKA4szBVoONiaBDh74WoEGSKC1Wjgq4xJ7oEMSaMfy1hVdREVCKtDOqq5WxhzjJoE24TUEE4GeNYtBOI88Urlm2EZDEmiZ2i0YLByArZy3I8wUdsEHtR7oiAjvpRiLjTUtHJUBrhToii7jLREby1U1Z6sv/9/e3cfIVdV/HP/M7s7uTne7rdDpFsMPY0UItjyk1pZIpZGiGESMgQ1E60PAKLjZIloesoLdrlu0JhsTQEmIBgk1mELCP0aDxD8khbZBY0lagUSr0pY+LJbS3W23szu9vz+Od2d2OrM7986duefe+34lm+lOO8sZzm3nM9/5nnMI0ECAihcORi1AL1xoXmgOHTKVniefNL2uX/5y2COLNjdAS+bacE99jLrFi02ALq3MEKDjp9oKdD2DKi0cyTBXC0cYFWipfB90va95GxGgUTfNzYU9lKNyCqErlTJV6EOHpF//2rzj/853ePGplbsXtCRdcIGUToc7nqBks9LkZOGFzUWAjh9bAvSZM9LUVPWPoQIdPTb2QEvl24eoQAMBcxcSRq0CLZkAfeyYWTzY1ibdfXfYI4o+dy9oKR79z65KW9m5L3QE6PhIp01rxlyLCOsZVP0cpkIPdPTY1sIxWwWaAA0EzO2DjmqAlqT9+6X16wvblaE2boCOS/+zVDlAU4GOn1TKhOOwK9CStwBNC0f02NbCMdtphEk85ZIAjbqKegXaxcEpwYljBbrSXtAE6Hhqbw83QM/2UXoltHBEj20B2q1Al153k5NmkX3S3pwRoFFXcahAf/az0vLl4Y4lTuIYoCvtBU2AjqfZKtCOQwUawbCtB7pSC0dS24MI0Kirm26SVq2Sli0LeyTerVsnXXKJtHlz2COJlxtvNCc53nBD2CMJDi0cyZLJVO6BdsOObQE6qSEnymzrga70yUdSr62WsAeAeLvlFvMVRcuXS2+9FfYo4ufyy6U33gh7FMEiQCdLJlP56PZ6H6Ii0cKRFLa2cJRWoBtxzduICjQA1Ige6GSZrYWjEWGCFo5kmC1ANzcXroNGoQI9EwEaAGpED3SytLebUHP27Lm/Z2uATmrIibLZWjgWLGj8qbj0QM9UU4B+6aWX9P3vf3/6+z179qinp0e33367Hn/88ZoHBwBRkMmYUEMFOhnccFyuD9oN0PPm1e+/TwtHMsxWgW50+4ZU+bqjhcOjoaEhDQ8P62zRW/BNmzZpeHhYzz77rF5//XXt27cvkEECgO2y2fIBuqUleS8scVdNgLatAk0LR/S0/G+Vmi0Bmgr0TL4D9IoVKzQwMDD9/djYmHK5nC666CKlUimtWbNGO3fuDGKMAGC9xYtNgHacwn0nT5rqc6M/akV9zXact60Bmgp09KRSpgpdHKCnpkwFuNFb2EmVD1JJaoCecxeO5557Tk8//fSM+x555BHdeOON2r179/R9Y2Nj6nT/70rq6OjQgQMHZv3Zjz32GK0eAGIhm5VyOROa3eqQG6ARL25QCCtAu+Hp+PHqH0MFOppKA7TbFhZmBZpFhMacAbqnp0c9PT1z/qDOzk6NF70dHh8fV9ccrxx9fX3q6+ubcd/Bgwe1bt26Of97AGCT4q3sigN0nI4shxF2BXrJEnN79Gj1j0lqyIm60gAd1hZ27lhaWtjGzhXYLhydnZ1Kp9N6++235TiOduzYoZUrVwb14wHAaqV7QTsOFei4CjtAZ7Pm4/3Dh6t/DC0c0dTWZj7ZcoV1CqFkrrnOTirQrkAPUtm8ebM2btyofD6vNWvW6MorrwzyxwOAtUr3gj51ymxzRoCOn7AXEba0mOvtyJHqH0MLRzS1tc18oxbWKYSu+fPpgXbVFKBXr16t1atXT39/1VVXafv27TUPCgCipnQvaLawi6+wK9CSaePYv7/6Pz8xYSqIra31GxOC19ZWCM1SuC0ckqlAl+42RAsHAMC30hYOAnR8hb2IUDIBenS0+p04JibMuNkRJlps6oGWqEAXI0ADQABKA7T7QkeAjh9bKtBS9W0cp08nL+DEQaUAHUYPtGQq0GfOSJOThfsI0AAA30p7oKlAx1fYPdCSdMEF5rbaAD0xkbyP2OOgrc2EVffMOht6oKWZCwmTukCVAA0AAaAHOjmoQKNR3OO83Z04wm7hKHeYSlIXqBKgASAA8+aZLyrQ8WdTgK52Kzu3BxrR4gZot40j7AA9WwU6adcXARoAAuIe5y0RoOPMhkWEtHAkQ2mAdls4wuyBlmZWoAnQAICaZLMmQLuHqEgE6DiyqQJdTYB2HFo4oioKFWi2sQMA1CSbNS90o6ME6DizYRGhlwA9NWUWoRGgo6dcgG5tDW8u3QBNBZoADQCBKd7KjgAdXzZUoOfPN/+Nanqgk7pLQhyUC9BhtW9IhRYOeqAJ0AAQmOKt7AjQ8TVXgG5ultLp+o4hlTJ90NVUoJO6S0IclOuBDqt9QypfgT59Wmpqqv81bxsCNAAEpFwFOswXO9THXIsIG1XpXbJEOnq0sEdwJUmtEMaBe/R6cQU6zH9TKlWgk3jKJQEaAAJSvBf0yZPmBaWjI9wxIXhzVaAbGaDzeendd2f/c7RwRFdxBTqXM3NpWwU6qVskEqABICClFeiuruRVZZJgrkWEjQqq1W5lRwtHdBUH6LCP8ZYqb2OXxDdnBGgACEhpDzT9z/HU2mreGNlQgZbmDtBUoKOrOECHfYy3VHkbuyS+OSNAA0BAylWgET+plAkMUQnQVKCjq/go77D3gJYqV6CTeG0RoAEgIKU90ATo+Mpk7AnQc21lxyLC6LKthaPSUd5JvLYI0AAQkI4OE54OHJAmJwnQcZbJnNsDPTVlvmzrgaaFI7psa+FwF0W7FWj3lMskXlsEaAAI0OLF0v795tcE6PgqV4Fu9JHGtHDEX7kKdJgBuqnJhGi3Aj05aUJ0Eq8tAjQABCibLVT8CNDxZUOAXrzY9GPTwhFftgVoybRxuBXoJF9bLWEPAADixO2DlgjQcVZuEWGjA3Q6LS1aRAtHnBUHaPf6CrMHWjILCd0KdKOveZtQgQaAABGgk8HtgXacwn1hhIklS2jhiDPbeqAlKtAuAjQABMjdC1oiQMeZG5LdI5al8AL0+++X3xHERQU6umxs4ejslMbHzRHyBGgAQCCoQCdDueO8wwrQ0uxVaCrQ0WVjgJ4/33zycuoUARoAEBACdDLYEqCr2couySEn6mxs4Sg+TIUeaABAIAjQyeCG0bADdDUVaFo4oqu0Aj1vnlk8Gqbiw1SS/OaMAA0AAaIHOhlsqUBXcxohLRzRVRqgw64+S4UAPTpKgAYABIQKdDK4Ibn4NEJaOBC00gAd9hZ2UqGFY2yMFg4AQECKA7QN1SLUh20VaFo44qm11dy6PdA2/JtCBdogQANAgDo6Ci8mVKDjK0o90LRwRJdbgT5xQpqasiNAF1egCdAAgECkUoU+aPeFBvFjSwV6wQITsmbrgU5yyIk6N0AfPWpubQjQ5SrQSfx0g6O8ASBgl15qbpubwx0H6seWHuhUyvRBz9XC0dJivhAtLS1mjo8dM9/b1gN99qz5dRLfnPHXCQAC9pvfzAxWiB9bKtCSaeP4619NmGkq87ny6dPJDDhxkEqZKvTx4+Z72yrQbpEgidcXARoAAla8kBDxZFuAnpw0IWvRonN/f2IimR+xx0VbW+ENuQ0BuvggFTc4JzFA0wMNAIBHtiwilObeyo4KdLS5fdCSHS0cxQepsI0dAAComm0VaKlygJ6YIEBHWXGAtqECzTZ2BgEaAACPbFlEKFUXoJNYIYwL2wI029gZBGgAADyysQJdaSs7WjiizdYAPTpKCwcAAPBgtgDd6LA6Ww+045hT7AjQ0WVbD3Rrq/miAg0AADyptIiwvd1sPdZIs7VwnDljbpNYIYwL2yrQkumDpgcaAAB4UqkCHUZQ7e42t+VaODjGO/psDNCdnVSgCdAAAHhUaRFhGAG6tVU6//zyFegkH7UcF26ATqWkrq5wx+JyK9CnT5vDVNLpsEfUeARoAAA8sqkCLZk2jnIBmgp09LkBev788idNhqGzsxCgk3ptWTIVAABEhxtqbArQ771X6Hl2Jfkj9rhwrzVb2jckE+anpqSTJ5N7bRGgAQDwKJUywcGmAC2dW4WmhSP6bA3QkjQyktxriwANAIAPmUwhoDpOuAeWVNrKjhaO6GttNbc2bGHncveCpgINAAA8yWQKATXsSu9cFeikhpw4sLkCLSX32iJAAwDgQ3GADvtEtkqnEYYd7FE7GwO0W4GWknttEaABAPChuAc67ABNC0d82RigqUAToAEA8MXGCjSLCOPHDdA29kBLBGgAAOCBu4jQcaRTpwr3haFSgKYCHX1UoO1EgAYAwIdMxoTnXC78CvQHPmB2a6jUA53UkBMHNgZoeqAJ0AAA+FJ8GmHYATqVKn8aIS0c0ece353NhjuOYlSgpZawBwAAQBS5wcGGAC2ZAL1nj6mKp1KFsUnJDTlxcNttZj4///mwR1JAgKYCDQCALzZVoCUToHM5c6S3ixaO6Ovqkr75TbvmkBYOAjQAAL64wWFiwo4AXW4rO1o4UA9UoAnQAAD4YmMFWpoZoGnhQD2wjR0BGgAAX6IQoGnhQD0UV6CT+ukGARoAAB9sW0TotnAUb2VHCwfqIZORmv6XIJP65owADQCAD7b1QNPCgUZJpQptHEm9tgjQAAD4EKUWDirQCBoBGgAAeGZbgO7uNrfFLRzuuNzT7ICguH3QSX1zRoAGAMAH23qg29vNkd6lFei2tsLBKkBQ3ABNBRoAAFTNtgq0dO5x3hMT4Y8J8UQLhw+jo6O66667tH79et12223629/+Jknas2ePenp6dPvtt+vxxx8PdKAAANjEtkWEkgnQ//2vOZFQMuNKasBBfdHC4cNTTz2lq6++Wtu2bdOPf/xjDQ4OSpI2bdqk4eFhPfvss3r99de1b9++QAcLAIAtbKxAu1vZHT1qbicmCNCoj6RXoFv8POgb3/iGWltbJUn5fF5tbW0aGxtTLpfTRRddJElas2aNdu7cqWXLlgU3WgAALGFjgC7eieP//s8E6EWLwh0T4mnhQnPb0RHuOMIyZ4B+7rnn9PTTT8+475FHHtEVV1yhkZER3Xffferv79fY2Jg6i8527Ojo0IEDB2b92Y899hitHgCASCpdRNjSYr7CVLqVHS0cqJfeXumDH5QuuyzskYRjzr/qPT096unpOef+t956S9/73vd0//33a9WqVRobG9P4+Pj074+Pj6urq2vWn93X16e+vr4Z9x08eFDr1q2rdvwAAISitAIddvVZKgRodys7FhGiXpYtM19J5asH+h//+IfuueceDQ8Pa+3atZKkzs5OpdNpvf3223IcRzt27NDKlSsDHSwAALYoXUQ4b16445EKPdBHjkhTU+aLCjQQPF8fNg0PDyuXy2nLli2STHh+4okntHnzZm3cuFH5fF5r1qzRlVdeGehgAQCwhc0V6CNHCqcQEqCB4PkK0E888UTZ+6+66ipt3769pgEBABAFpQE6mw13PNLMFg6O8Qbqh4NUAADwwT0e26YK9HnnSem0qUC7O4NQgQaCR4AGAMCHpiYTom0K0E1NUnc3LRxAvRGgAQDwKZORRkels2ftCNBS4ThvW/amBuKIAA0AgE+ZjHT8eOHXNliyxFSf3dMIqUADwSNAAwDgU3u7fQHa3cruX/8ytwRoIHgEaAAAfMpkpMnJwq9t4O7E4QZoW8YFxAkBGgAAn4rDqS1BtTRAU4EGgkeABgDAJxsDtNvC8e9/m1tbxgXECQEaAACfbAzQVKCB+iNAAwDgU3E4tS1AHztmbgnQQPAI0AAA+GRzBdply7iAOCFAAwDgk40BOpORFiwofE8FGggeARoAAJ9sDNDSzCo0ARoIHgEaAACfohCgbRoXEBcEaAAAfLJxEaFU2MpOogIN1AMBGgAAn6hAA8lEgAYAwKcoBGgq0EDwCNAAAPhEgAaSiQANAIBPtgbo4h5om8YFxAUBGgAAn2xdREgFGqgvAjQAAD7ZWoF2A3RTk9TSEu5YgDjirxUAAD7ZGqAXLZKam031OZUKezRA/BCgAQDwydYA3dQkdXdLZ86EPRIgngjQAAD45PYXp1JSa2u4YynV1yedOhX2KIB4IkADAOCTW3XOZOxrlXjwwbBHAMQXiwgBAPCpOEADSA4CNAAAPhGggWQiQAMA4BMBGkgmAjQAAD65iwgJ0ECyEKABAPCJCjSQTOzCAQCAT01N0i23SCtWhD0SAI1EgAYAoAbPPx/2CAA0Gi0cAAAAgAcEaAAAAMADAjQAAADgAQEaAAAA8IAADQAAAHhAgAYAAAA8IEADAAAAHhCgAQAAAA8I0AAAAIAHBGgAAADAAwI0AAAA4AEBGgAAAPCAAA0AAAB4QIAGAAAAPCBAAwAAAB4QoAEAAAAPCNAAAACABy1hD6BUPp+XJB05ciTkkQAAACDO3Lzp5s9qWRegR0ZGJElf+cpXQh4JAAAAkmBkZEQf+tCHqv7zKcdxnDqOx7OJiQnt3btX2WxWzc3Ngf3cdevW6U9/+lNgPw/hYB7jgXmMD+YyHpjHeGAevcvn8xoZGdHy5cvV3t5e9eOsq0C3t7dr5cqVdfnZF154YV1+LhqLeYwH5jE+mMt4YB7jgXn0zkvl2cUiQgAAAMADAjQAAADgAQEaAAAA8KB5YGBgIOxBNMrq1avDHgICwDzGA/MYH8xlPDCP8cA8NoZ1u3AAAAAANqOFAwAAAPCAAA0AAAB4QIAGAAAAPCBAAwAAAB4QoAEAAAAPrDvK24vJyUn19/fr0KFDyuVyuvvuu3XxxRfrwQcfVCqV0kc/+lFt2rRJTU3mfcJ//vMf9fb26ne/+50k6Z133lF/f7/y+bwcx9Hg4KCWLl0a5lNKpFrncWRkRBs3btTk5KSy2ax+8pOfKJPJhPmUEqvWuXS99tpr2rhxo/785z+H8TQSr9Z5PHHihG644QZdcsklkqTrr79eX//610N7PklV6zyeOnVKAwMDOnjwoCYnJ/Xwww/riiuuCPMpJVKt87hlyxa9+eabkszrZVdXl7Zv3x7a84kNJ8Kef/55Z2hoyHEcxzl+/Lizdu1a59vf/raza9cux3Ec5+GHH3b++Mc/Oo7jOC+88ILzpS99yfnkJz85/fj777/feemllxzHcZyXX37Z6e3tbfAzgOPUPo9DQ0POCy+84DiO4zz66KPOU0891dgngGm1zqXjOM4777zj3HXXXefcj8apdR5feeUVZ3BwsPEDxwy1zuOjjz7qPPnkk47jOM4bb7wx/e8sGiuIf1cdx3FyuZxz6623Om+++WbjBh9jkW7h+NznPqd77rln+vvm5mbt27dPq1atkiRde+21evXVVyVJCxYs0LZt22Y8/oEHHtDatWslSfl8Xm1tbQ0aOYrVOo/9/f26+eabdfbsWR0+fFjnn39+4waPGWqdyzNnzmjTpk1K0PlOVqp1Hvfu3at9+/Zp/fr12rBhg44dO9a4wWNarfO4Y8cOpdNp3XnnnfrFL36hT33qU40bPKbVOo+ubdu26ZprrtGll15a/0EnQKQDdEdHhzo7OzU2NqYNGzbou9/9rhzHUSqVmv790dFRSdKnP/1pzZs3b8bjzzvvPKXTae3fv19bt25Vb29vw58Dap/HVCqlfD6vm266Sbt379aKFSsa/hxg1DqXg4ODuuOOO9Td3d3wsaOg1nlcunSpNmzYoG3btun666/X0NBQw58Dap/H9957TydPntSvfvUrXXfdddq6dWvDnwNqn0dJyuVy+u1vf6s777yzoWOPs0gHaEk6fPiwvva1r+mLX/yivvCFL0z3AEnS+Pi4urq6Zn38rl271Nvbq5/+9Kf0P4eo1nlMp9P6/e9/rx/96Ed64IEH6j1czMLvXB49elR/+ctf9POf/1xf/epX9f777+vee+9t1LBRopa/k1dfffX0ccKf+cxn9Pe//73u40V5tczjwoULdd1110kywWzv3r11Hy/Kq/U1cufOnfrEJz6h+fPn13uoiRHpAP3uu+/qjjvu0H333adbb71VkvSxj31Mu3fvliS9/PLLWrlyZcXH79q1S1u2bNEvf/lLXX755Q0ZM85V6zwODAxo165dksw7cfddORqvlrns7u7Wiy++qGeeeUbPPPOMFixYoJ/97GcNGzsKav07+dBDD+nFF1+UZF64ly1bVv9B4xy1zuPHP/7x6YW8r732mi6++OL6DxrnqHUeJenVV1/VtddeW/exJknKcRwn7EH4NTQ0pD/84Q8zKsc/+MEPNDQ0pMnJSS1dulRDQ0Nqbm6e/v1rrrlGr7zyiiTp5ptvVi6XUzablSR9EMUWRAAAAL1JREFU+MMf1uDgYGOfBGqex3/+85/TPbNNTU364Q9/qI985CMNfQ4wap3LYpXuR/3VOo8HDhxQf3+/JCmTyWhoaEiLFy9u7JNAzfN44sQJPfTQQxoZGVFLS4u2bt2qCy+8sOHPI+mC+Hf1W9/6lu69915ddtllDR17nEU6QAMAAACNFukWDgAAAKDRCNAAAACABwRoAAAAwAMCNAAAAOABARoAAADwgAANAAAAeECABgAAADwgQAMAAAAe/D8Arwd032MgvwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c173b7c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results of Dickey-Fuller Test:\n",
      "Test Statistic                 -5.331122\n",
      "p-value                         0.000005\n",
      "#Lags Used                      4.000000\n",
      "Number of Observations Used    60.000000\n",
      "Critical Value (1%)            -3.544369\n",
      "Critical Value (5%)            -2.911073\n",
      "Critical Value (10%)           -2.593190\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "deaths_per_year['first_difference'] = deaths_per_year.Value - deaths_per_year.Value.shift(1)\n",
    "test_stationarity(deaths_per_year.first_difference.dropna(inplace=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c174a3c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results of Dickey-Fuller Test:\n",
      "Test Statistic                 -2.748103\n",
      "p-value                         0.066078\n",
      "#Lags Used                     11.000000\n",
      "Number of Observations Used    42.000000\n",
      "Critical Value (1%)            -3.596636\n",
      "Critical Value (5%)            -2.933297\n",
      "Critical Value (10%)           -2.604991\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "deaths_per_year['seasonal_difference'] = deaths_per_year.Value - deaths_per_year.Value.shift(12)\n",
    "test_stationarity(deaths_per_year.seasonal_difference.dropna(inplace=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c175ed320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results of Dickey-Fuller Test:\n",
      "Test Statistic                 -1.778716\n",
      "p-value                         0.391079\n",
      "#Lags Used                     11.000000\n",
      "Number of Observations Used    41.000000\n",
      "Critical Value (1%)            -3.600983\n",
      "Critical Value (5%)            -2.935135\n",
      "Critical Value (10%)           -2.605963\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "deaths_per_year['seasonal_first_difference'] = deaths_per_year.first_difference - deaths_per_year.first_difference.shift(12)\n",
    "test_stationarity(deaths_per_year.seasonal_first_difference.dropna(inplace=False))    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'residual = decompostiton.resid\\nresidual.dropna(inplace=False)\\ntest_stationarity(residual)'"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"residual = decompostiton.resid\n",
    "residual.dropna(inplace=False)\n",
    "test_stationarity(residual)\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that there are minimal to no seasonal effects because the most stationary timeseries resulted in the first difference and did not result from either the seasonal or the seasonal coupled with the first difference "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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N6tut9fja26q5neq11nk/m4NwJOlyWqycdhfRSJaCdElJidxut3/a6XTK6/XK5XJp586devXVV/X444/riSeeaPQ6c3JylJuba6UcAEAL8xmmDMOQz2fKZ1T9M2QYZrV5hj8k1uWUOcSsfbPmOmqGpVMFper3PeXm6gpcJybMBoKX/zGEKgCyGKTdbrdKS0v904ZhyOU6vqoVK1Zo//79uv322/XVV18pOjpaZ511VoO905mZmcrMzAyYV1RUpNTUVCslAkCbd6qfjat6+wzDlOH/X8f/N8zjy0zzRDg+ftustjwgJJ/4R3AEgNosBemUlBS99dZbGjJkiAoKCtSvXz//sgceeMB/OycnR127dmWIB4Cw4/UZ8lT6ZBjWE6Spk+G0vuBac9nxsFvjp+fqKwUAhARLQTotLU0bNmxQenq6TNPUnDlztHDhQiUkJNCDDCDkGYYpj9cnr9eQx2uo0ns8NHt9J2/bfWAQACD0WQrSUVFRysrKCpiXmJhY6341h2oAQGvxGabKK7wq93hVUelTZeWJkOz1yecjJQMAgmcpSANAKKn0+lRW4VN5hVdlHq/KK7zyVBp2lwUAaOMI0gDChmmaqvD4ToRln8o9XpVVeOlhBgDYgiANRLhTnWbMP11joWEGnhGi6qC4uuYHLq99Htmm1FHhOR6cGbsMAAgVBGmEvOrhzOc7eVaDqrMcNJSr6ruYQeNraNr8U66nRpKseVGC6ld4qrpgg6rdrn6O3YCzOpgnLyIQMK+u+SeWAQCA4BCkYQvTNFXu8ansxMFgXq/hP89t1flrDUP+CzwAAACEGoI0WpxhmP6xrGUVJ8e2EpABAEA4I0ijWfl8hso8J86ecOJfRaWPoQSwxaHici1ft0tf7j+qhO7xGjW4rzp3jLW7LABAG0GQRp1qXW2t2pjk40MvdGL5ycsIc8oxhJrl63Zp9zfFkqTd3xRr+bpd+tnwi22uCgDQVhCkw0j1ywdXv+0LmF/tDAlSwKWIq09XHax2fPrk7ar10YOMtuDL/UfrnQYAIBgE6RBSUlapIyUVqvD46gzKhFugaRK6x/t7pKumAQBoLlF2FxDpjpVX6pvvSrV99yF98dURHTpSrtKyyuNjiz0+VXqPD50gRANNN2pwXx39dpdMw6feZ3TUqMF97S4JANCG0CNtg3KPV0dKPP7eZwAto3PHWO1663FJ0ty3P7a5GgBAW0OQbiWVXp++P3o8PJdVeO0uBwAAAEEiSLcgr8/QkZIKHSnxqLS8kuEZAAAAbQhBugWUVXi1/9AxHT3mITwDAAC0UQTpFlBW4dXRUo/dZQAAAKAFcdYOAAAAwAJLPdKGYWjmzJnasWOHYmJiNHv2bPXq1cu//LnnntPq1aslSddee60mTZrUPNUCAAAAIcJSj/SaNWvk8XiUl5enqVOnKjs7279s7969WrVqlZYuXaq8vDy9++672r59e7MVDAAAAIQCSz3SGzdu1MCBAyVJycnJKiws9C/r0aOH/vznP8vpdEqSvF6v2rVr1wylAgAAAKHDUpAuKSmR2+32TzudTnm9XrlcLkVHR6tz584yTVOPPPKILrzwQvXp06fBdebk5Cg3N9dKOQhjh4rLtXzdLn25/6gSusdr1OC+6twx1u6ygLDF3xQAtB5LQzvcbrdKS0v904ZhyOU6mckrKip0//33q7S0VDNmzGjUOjMzM7Vjx46Af2vXrrVSHproUHG5/rRiq379x/f0pxVbdai4vNW2vXzdLu3+pliGYWr3N8Vavm5Xq20baIv4mwKA1mMpSKekpCg/P1+SVFBQoH79+vmXmaapX/ziFzrvvPOUlZXlH+KB0GXnB++X+4/WOw2gafibAoDWY2loR1pamjZs2KD09HSZpqk5c+Zo4cKFSkhIkGEY+vDDD+XxeLR+/XpJ0n333acBAwY0a+FoPnZ+8CZ0j9fub4oDpgFYx98UALQeS0E6KipKWVlZAfMSExP9t7du3RpcVWhVdn7wjhrcVzP+sFTurueoz1mna9Tgvq22bTQe427DB39TANB6uLIhbP3g7dwxVrveelySNPftj1ttu2iaquE/kvzDf342/GKbq0Jd+JsCgNZDkAYfvGgQ424BAKiNIN1G8NM7WhLjbgEAqM3SWTsQejjlFVrSqMF9dfTbXTINn3qf0ZFxtwAAiB7pNoOf3tGSGP4DAEBtBOk2gp/ewwfDcAAAbVWkfcYxtKON4Kf38MEwHABoXXZewTfSRNpnHD3SbQQ/vYcPhuEAoSPSes/sZGdbcwrP1hNpn3H0SAOtrOawG4bhINLZ2VsYab1ndrKzrSMt3Nkp0j7jCNJAK2MYDhCIgBUZ7GzrSAt3doq0zziGdgCtjGE4aEikDTewO2DZcaB2pL3Gkr0Hxdt5Bd9IE2mfcfRIA2hRHOTTdJE23MDO3kK7es8i7TWW7O2prAp3m16cop8Nv7jNf2lB66FHGkCL4iCfpgvH4QbB9LDa2VtoV+9ZOL7GwYq0nkpEBoI0gBYViYEhWOF4XvhgvjBFYsAKx9cY4SMShw7ZhaEdQBMxVKFpOMin6cLxYB2+MDVNOL7GCB+ROHTILvRIA03EUIWm4SCfpgvHHlp6WJvGzteY3srWY1db88W29dAjDTQRb1BNE64H+fDLQ9PQw9p6gt036a1sPXa1Nb8Eth7LQdowDE2fPl1jx45VRkaG9uzZE7B82bJlGjFihMaMGaO33nor6EKBUMEbVGQgbDRNuH5hCkfB7pt0BrSeYNo6mC9MfLFtPZaD9Jo1a+TxeJSXl6epU6cqOzvbv+zAgQNatGiRli5dqmeffVa///3v5fF4mqVgwG68QUUGwgZCVbD7Jp0BrSeYtg7mCxNfbFuPwzRN08oD586dq6SkJA0dOlSSNHDgQK1fv16StHbtWr3zzjvKysqSJN1zzz266667lJSU1KRtFBUVKTU1VZfdMlOx7i5WyrSkqKhIktSzZ09LjzcMU17DUrMGZf++ryVJ3Xuc2aqPDZad27Yq2Joj7TmH4/519JhHPt/Jv2On06H4DjHNWlt9wrG9w7FmO7dt177pM0wdKS6VI8ollytKHWKj5YxyNKkGqyLtdQ6mrb8/WlFrXqf4do3edji3dbQrSq2zRwYqLzmoj/4+U2vXrm10BrR8sGFJSYncbrd/2ul0yuv1yuVyqaSkRPHxJ791xcXFqaSkpN715eTkKDc312o5zcpqgK7y9ddfyVTrf5gE88cSzGOD/YOxa9t2tXWwjw/H5xxse9lRd4fYaB0rr5TPZ8rpdKhDbHSTHm/n34Vd+1ek7SN2bTfYfdMZ5VDnTu6G73gK4djWdm07mLZ2Oh21vjA1RTj/TTkUfBZrLZaDtNvtVmlpqX/aMAy5XK46l5WWlgYE67pkZmYqMzMzYF5Vj/S8SQPDpkElKaFXL/l8pv7PwpHYN/4oRZIsPdYudtV8qLhcM/5QKHfXc9TJ3a7JR0OHY1tLwdUdic/ZLuFYs0Td4bJdO0ViW9uxbbvPrmLn6xztitLru3e36nalE7nz7017jOUx0ikpKcrPz5ckFRQUqF+/fv5lSUlJ2rhxoyoqKnT06FF99tlnAcuB5rB83S7F/6CvHFFODgYDALQpnTvG6mfDL9bsu65inHMIs9wjnZaWpg0bNig9PV2maWrOnDlauHChEhISlJqaqoyMDN16660yTVP33nuv2rVr/LgeoDGCPRq673WT5e56jv60YivnUQUAAE1mOUhHRUX5DyaskpiY6L89ZswYjRkzxnplQAOCuQBEVW+2xEVVAACANVyQBWFr1OC+6n1GR0VFOZp8GrpIPLVZVS/8gNELuMAI2hT2bQB24RLhCFtV48esiMTLGdMLj7aKfRtoXgx/bDx6pBGRgunNDleR2AuPyMC+3fbxq0Pr4mD+xqNHGhEpmN7scBWJvfCIDOzbbR+/OrQuvpw2Hj3SQISIxF54RAb27dZjV88wwa51cRn5xqNHGogQkdgLj8jAvt167OoZ5leH1jVqcN9aF4NB3QjSAACgUezqGSbYtS6+nDYeQRoIIxxJDcBOdvUM2xnseN9FfRgjDYQRjqQGYKdIHI/O+27rqfrS0v+W3+vBJ97VvoOldpfUIHqkgTDCATcA7BSJP/nzvtt6qo/B3/b5QS1YuknZ91xjc1X1o0caCCMcSQ2EDs5tHBl43209Nb+kbN99yKZKGo8gDYSRSPxZFQhV/OQfGXjfbT01v6Sc37uzTZU0HkM7gDASiT+rAqGKn/wjA++7rafq7Cx79x/V+b07a0r6ALtLahBBGgAACzi3MdC8qr60nN/7dEW7nHaX0ygM7QghjLcDgPDBT/4A6JEOIXZdMQoA0HT85A+AHukQwng7AACA8GGpR7q8vFzTpk3TwYMHFRcXp3nz5qlz58AjK+fNm6ePP/5YXq9XY8eO1ZgxY5ql4LaM8XZA28CV0AAgMljqkV6yZIn69eunv/3tbxo+fLiefPLJgOX/+te/9OWXXyovL09LlizRM888oyNHjjRLwW0Z4+2AtoHTogFAZLDUI71x40ZNnDhRkjRo0KBaQXrAgAG64IIL/NM+n08uF8OxG8J4O6BtYJgWAESGBtPtiy++qOeffz5gXpcuXRQff3zYQVxcnI4eDfyQaNeundq1a6fKyko9+OCDGjt2rOLi4urdTk5OjnJzc5taPwCEHIZpAUBkaDBIjx49WqNHjw6YN2nSJJWWlkqSSktL1bFjx1qPO3LkiCZPnqzLL79cd911V4OFZGZmKjMzM2BeUVGRUlNTG3wsAISSqosKfLn/qBK6x4fNMC3GdgNA01gab5GSkqJ33nlHSUlJys/P16WXXhqwvLy8XHfccYd+8pOf6KabbmqWQgEgXITrMC1OwQkATWPpYMNx48Zp165dGjdunPLy8jRp0iRJ0iOPPKItW7Zo6dKl2rt3r1588UVlZGQoIyNDe/fubdbCAQDNi7HdANA0lnqk27dvr8cff7zW/AceeECSlJSUpDvuuCOowgAArYux3QDQNFyQpQU45JDDYXcVANA0nIITAJqGc9K1AIdDcjmjdH7v03X4aIWOlFSovMJnd1kAUK9wHdsNAHYhSLegaJdTPzi9g35wegeVe7z6/kSo9lQadpcGAACAIBGkW0lsjEs9urjUo0ucjpVX6vuSCh056pHXR6gGAAAIRwRpG3SIjVaH2Gid0cVUadmJUF3ikWGYdpcGAACARiJI28jhcMjdIUbuDjE6s6upo8c8OlJSoYpKnwzDlGFIhmkSsAEAAEIQQTpEREU5dJq7nU5zt6tzuc84HqirgnVdt6vuIx0P4KYpGYYp0zRlSjJNyTzxmOPTJ+5jmjKrQrtpSuR2AACABhGkw4QzyiFnVOucU88wToRy05TPZ8gwq+YZ/p5yn2H4g7zD4ZBkyul0yOcjhQMAgMhAkEYtUVEORVWF9mhng/d3OR2SHLqwTxdVen06Vu5Vucen8gqvyiq8qvRyQCUAAGh7CNJoVtEup05zO3VatXlen6GyE6G6rMKr8govpwAEAABhjyCNFudyRim+Q4ziO8T45/l8hsqq9Vp7fUatsd7Hx3fbWDgAAEA9CNKwhdMZJXf7KLnbR9d7P7NGsK4ZtI+P027ats2GjqY8xeKGMr1pIfVXHdxZ/eDPqnWZJzZatez4/JP3M1X7/qZR93wOIAUAoPkRpBGUfQdL1WdQpuK69NGDT7yrKekD1KNLXLOt3+FwHB+D3fBQbdTjZPiWanbz18zYtb8PmAHLqs4IU3UGGKPqdrX5PqPafaqdQaauuk5VR/UZDofD0hcVAABaEkEaQVmwdJPc3c6VJG37/KAWLN2k7Huusbkq1ORwOOTwn/Sldc7+0pz8B7Se00XlFV6Ve6rG2/tU7vEyBAgAYAuCNIKyffeheqeBYFX/1ePhpzbU+tXDNE1VeHwq85wM1mUVXk7FCABocQRpBOX83p217fODAdNAc2roVw+Hw6HYdi7FtnNJ8ScfV+n1qazi+AGtFZU+VXoNVXqP/08PNgCgORCkEZQp6QO0YOkmbd99SOf37qwp6QPsLgltjNVfPaJdTkW7nOoYF1NrWfVQXek15Km6XXl82uvj9IwAgIZZCtLl5eWaNm2aDh48qLiZbsXpAAAgAElEQVS4OM2bN0+dO9fuiSwrK1N6erqmTp2qQYMGBV0sQk+PLnGMiUaLaolfPaJdUYp2RZ1yuWGYqvQZqqz0yVfHQZKNVXVwZuBZZqoOxjT9Vw2tuczwHxkKAAhlloL0kiVL1K9fP2VmZmr16tV68skn9etf/7rW/bKysk5cPhoArLHjV4+oKIfaRTnVrhFX9mwp1c9yEpCp6znTSfUhK4ZpyqwjoJt1hHej2hlYqpb5DEO+E48j1ANA3SwF6Y0bN2rixImSpEGDBunJJ5+sdZ9nn31WAwYM4JRVAIISqb96REWdqhOi9Tsnjp+73ZDPZ/rDtc84fhGlk/MM/2kPpaadV736Xf3nTPfPqPrPrHXfOu9f43F1baP6+k61zprbB4C6NBikX3zxRT3//PMB87p06aL4+ONH9cTFxeno0aMBy99//33t2bNHWVlZ+vjjjxtVSE5OjnJzcxtbNwCglTijHHJGORUdwUfVBFww6eTMExdMOj63aiiPqv6XZJgn71f1K0PN+1RbXd23a30rqPNmqwo4B3yNLzvV/6t+Mamaj6/9Zan2ugPWb9ZoiZrbrWM71ddXfXtVF7WquX7//fgChUZq8G1x9OjRGj16dMC8SZMmqbS0VJJUWlqqjh07Bixfvny5vvrqK2VkZOjzzz/Xtm3b1K1bN11wwQWn3E5mZqYyMzMD5hUVFSk1NbXRTwYAgJYQeC52/1w7SkErCbii7IkbNb84+b8s1HUV2mqPaXhbzV9//dtr+gZP+eWu5hfMGus/+UXlxOOqjRar+UWranlUGA0LttS/kJKSonfeeUdJSUnKz8/XpZdeGrD8//7v//y3H3zwQQ0ZMqTeEA0AABBKqo7xCueLWaHlnfqw9XqMGzdOu3bt0rhx45SXl6dJkyZJkh555BFt2bKlWQsMN1UXj+h/y+/14BPvat/BUrtLAgAAQAtwmCF8NGDV0I61a9eqZ8+edpfTKA8+8W7AqbouOqdLRB4oBQAAEE6s5E5LPdI4NS6ZDQAAEBkI0s2s5sUiuGQ2AABA20SQbmZT0gfoonO6yBnl0EXndOGS2QAAAG1UBJ8VtGVE6sUjAAAAIg090gAAAIAFBGkAAADAAoI0AAAAYAFBGgAAALAgpA829Pl8kqR9+/bZXAkAAADasqq8WZU/GyOkg/SBAwckSePHj7e5EgAAAESCAwcOqFevXo26b0hfIry8vFyFhYXq1q2bnE5nq2676hKRaBzaq+los6ahvZqG9moa2qtpaK+mob2axq728vl8OnDggPr376/Y2NhGPSake6RjY2N12WWX2bb9xl5nHcfRXk1HmzUN7dU0tFfT0F5NQ3s1De3VNHa1V2N7oqtwsCEAAABgAUEaAAAAsIAgDQAAAFjgnDlz5ky7iwhVV1xxhd0lhBXaq+los6ahvZqG9moa2qtpaK+mob2aJlzaK6TP2gEAAACEKoZ2AAAAABYQpAEAAAALCNIAAACABQRpAAAAwAKCNAAAAGBBSF8i3A6GYWjmzJnasWOHYmJiNHv27CZfLjLSDB8+XPHx8ZKOX9Jz7ty5NlcUmjZv3qxHH31UixYt0p49e/Tggw/K4XCob9++mjFjhqKi+F5bXfX22rZtm37+85+rd+/ekqRx48ZpyJAh9hYYIiorK/WrX/1KX331lTwej+6++26de+657F/1qKvNevTowT52Cj6fT7/+9a/1xRdfyOl0au7cuTJNk33sFOpqr6NHj7J/NeDgwYMaMWKE/vKXv8jlcoXN/kWQrmHNmjXyeDzKy8tTQUGBsrOz9dRTT9ldVsiqqKiQJC1atMjmSkLbM888o1WrVql9+/aSpLlz52rKlCm64oorNH36dK1du1ZpaWk2Vxk6arbXf/7zH/3kJz/RnXfeaXNloWfVqlXq1KmT5s+fr8OHD+uWW27R+eefz/5Vj7ra7J577mEfO4W33npLkrR06VJ98MEH/iDNPla3utpr8ODB7F/1qKys1PTp0xUbGyspvD4jQzPe22jjxo0aOHCgJCk5OVmFhYU2VxTatm/frrKyMt1555267bbbVFBQYHdJISkhIUE5OTn+6W3btunyyy+XJA0aNEjvvfeeXaWFpJrtVVhYqLffflvjx4/Xr371K5WUlNhYXWi58cYb9ctf/tI/7XQ62b8aUFebsY+d2n/9139p1qxZkqSvv/5aXbt2ZR+rR13txf5Vv3nz5ik9PV0/+MEPJIXXZyRBuoaSkhK53W7/tNPplNfrtbGi0BYbG6sJEybo2Wef1W9/+1vdf//9tFcdbrjhBrlcJ38AMk1TDodDkhQXF6ejR4/aVVpIqtleSUlJeuCBB7R48WKdffbZeuKJJ2ysLrTExcXJ7XarpKREkydP1pQpU9i/GlBXm7GP1c/lcul///d/NWvWLN1www3sYw2o2V7sX6f28ssvq3Pnzv5OTCm8PiMJ0jW43W6Vlpb6pw3DCPhAR6A+ffropptuksPhUJ8+fdSpUycdOHDA7rJCXvWxXqWlperYsaON1YS+tLQ09e/f33/7P//5j80VhZZvvvlGt912m26++WYNGzaM/asRarYZ+1jD5s2bp9dff12/+c1v/MP6JPaxU6neXtdccw371ym89NJLeu+995SRkaFPPvlE//u//6tDhw75l4f6/kWQriElJUX5+fmSpIKCAvXr18/mikLb8uXLlZ2dLUnav3+/SkpK1K1bN5urCn0XXnihPvjgA0lSfn6+LrvsMpsrCm0TJkzQli1bJEnvv/++LrroIpsrCh3fffed7rzzTk2bNk2jRo2SxP7VkLrajH3s1FasWKE//vGPkqT27dvL4XCof//+7GOnUFd7TZo0if3rFBYvXqwXXnhBixYt0gUXXKB58+Zp0KBBYbN/OUzTNO0uIpRUnbVj586dMk1Tc+bMUWJiot1lhSyPx6OHHnpIX3/9tRwOh+6//36lpKTYXVZIKioq0n333adly5bpiy++0G9+8xtVVlbqnHPO0ezZs+V0Ou0uMaRUb69t27Zp1qxZio6OVteuXTVr1qyAIViRbPbs2frHP/6hc845xz/v4Ycf1uzZs9m/TqGuNpsyZYrmz5/PPlaHY8eO6aGHHtJ3330nr9ern/70p0pMTOQ97BTqaq8zzjiD97BGyMjI0MyZMxUVFRU2+xdBGgAAALCAoR0AAACABQRpAAAAwAKCNAAAAGABQRoAAACwgCANIGIUFRXpggsu0M033+z/d9NNN2n58uVNXtfbb7+txx57TJK0du1azZ49u8FtDxgwoN77jBgxQkOGDFFjjwE/evSobrvttsYV3IrOO++8gPPA1qWp7QcAoYgrjQCIKLGxsVq5cqV/ev/+/frxj3+s/v376/zzz2/0erZu3aojR45IklJTU5WamhpUXZs3b5bH41F0dLTWr1+vQYMGNfiYI0eOaOvWrUFt1y7N3X4AYAeCNICI1r17d/Xq1Uu7d+9WQkKCZs6cqT179uj7779XXFycHn30UZ1zzjnKyMjQaaedps8//1xDhgzR0qVL5fP5FB8fr169eun111/XH//4RxUUFGj+/PnyeDw6cOCArrrqKs2ZM6fBOpYsWaIf/ehHOv300/X888/7g3RRUZGGDRumTZs21Zp+6KGHVF5erptvvlkvv/yyNm3apEceeURlZWWKjo7WlClT/Ov54x//qL///e9yuVzq1auXsrOzFR8fryeeeEKrV6+W0+lUnz599Jvf/EbdunULeL7jxo3TG2+8ETA9fPhw/e53v9POnTtVWVmpK6+8Ug888EDAlWCPHTtWZ3sePXr0lO23b98+zZw5U1999ZVM09Tw4cM1ceJEFRUV6Y477tC1116rzZs3q7i4WNOmTVNaWloL7BUA0DgM7QAQ0TZt2qQvv/xSl1xyifLz89WxY0fl5eXp9ddfV//+/bV48WL/fTt27KjXXntNkyZNUnp6uoYMGaJ77703YH1//etfNXnyZL344otavXq11q1bp8LCwnpr+P777/Xaa6/ppptu0k033aR//etf+vTTTxusfe7cuf4e9uLiYk2ePFkPP/ywXnnlFc2bN0/Tpk3T3r17tXbtWr388svKy8vTq6++qp49e+qFF17QSy+9pPXr12v58uV65ZVX1LdvXz344IO1nm9GRkat6Tlz5uiiiy7Syy+/rBUrVujw4cNauHBhQH2nas9LLrnklO13//3364orrtArr7yiJUuWaNWqVVq9erUkae/evbrmmmu0fPlyTZ06tVFfUACgJdEjDSCiVPXgSpLP59Ppp5+u+fPn64wzztAZZ5yhs88+W4sWLdKePXv04YcfBoxrbsxlarOzs5Wfn6+nn35an3/+uSoqKnTs2DF16tTplI95+eWXde6556pfv36SpKuuukp//etflZWV1ejntWXLFiUkJOiSSy6RJPXt21cpKSn68MMP9cknn+jGG2/UaaedJkl66KGHJEm//OUvNWLECHXo0EGSdNttt+npp5+Wx+Op8/lWn3777be1detW//jy8vLyWjXdeOON9bZnTceOHdPHH3+sv/zlL5Kk+Ph4jRgxQvn5+brkkksUHR2ta6+9VtLxy6B///33jW4fAGgJBGkAEaXmGOnq/va3v2nZsmUaP368hg0bpk6dOqmoqMi/vCpw1ud//ud/dN5552ngwIH67//+b23evLnegwdN09TSpUt15MgRDR48WJJUVlamDz/8UPfee68cDkfA4ysrK+tcj8/nk8PhqLVur9crp9MZsKy4uFjFxcUyDCNgvmEY8nq9p3y+1acNw9Bjjz2mxMRE/zprbr+h9qzJMIxabVW9pujoaEVFHf8htea2AMAODO0AgBPeffdd3XLLLRo9erT69OmjdevWyefz1Xlfp9MZEDql42Fy69atuv/++3X99ddr3759+vLLL2UYxim3uWHDBh08eFBr1qzRunXrtG7dOq1fv17dunVTXl6eOnbsqMrKSv9Qj6phDpLkcrnk8/lkmqaSk5P1+eefa8uWLZKkXbt26d///rcuv/xyXXXVVXrzzTdVUlIiScrJydFzzz2ngQMH6qWXXtKxY8ckSYsWLdL/+3//TzExMQ221TXXXKPnnntOpmnK4/Ho7rvv1gsvvNDo9qyr/dxuty655BL/cJqjR49qxYoVuuqqqxqsBwDsQI80AJxw5513avr06f7hCsnJydq5c2ed9/3hD3+o+++/X7NmzdJFF10k6fgY4p/97Ge65ZZb1KFDB3Xv3l0pKSnas2ePzj777DrXs2TJEo0ZM0bx8fH+eS6XS3fddZcef/xxTZgwQdOmTdNPf/pTde7cWTfeeKP/ft26dVNSUpKGDh2qxYsX67HHHtOsWbNUXl4uh8OhuXPnqk+fPurTp48+/fRTjRs3TpJ07rnnatasWerQoYO++eYbjR49WoZhqFevXnr00Ucb1VYPP/ywfve732nYsGGqrKzUVVddpYkTJza6PetqP0l69NFHlZWVpZdfflkej0fDhg3TiBEj9NVXXzWqLgBoTQ6zsScsBQAAAODH0A4AAADAAoI0AAAAYAFBGgAAALCAIA0AAABYENJn7SgvL1dhYaG6desmp9NpdzkAAABoo3w+nw4cOKD+/fsrNja2UY8J6SBdWFio8ePH210GAAAAIsTixYsbdSVbKcSDdLdu3SQdf0I9evSwuRoAAAC0Vfv27dP48eP9+bMxQjpIVw3n6NGjh3r27GlzNQAAAGjrmjKcmIMNAQAAAAsI0gAAAIAFBGkAAADAgqCC9ObNm5WRkVFr/rp16zRy5EiNHTtWy5YtC2YTAAAAQEiyfLDhM888o1WrVql9+/YB8ysrKzV37lwtX75c7du317hx43Tdddc16QhIO+07WKoFSzdp++5DOr93Z01JH6AeXeLsLgsAAAAhxnKPdEJCgnJycmrN/+yzz5SQkKDTTjtNMTExuvTSS/XRRx8FVWRrWrB0k7Z9flA+w9S2zw9qwdJNdpcEAACAEGS5R/qGG25QUVFRrfklJSWKj4/3T8fFxamkpKTB9eXk5Cg3N9dqOc1m++5D9U4DAAAAUgscbOh2u1VaWuqfLi0tDQjWp5KZmakdO3YE/Fu7dm1zl9eg83t3rncaAAAAkFogSCcmJmrPnj36/vvv5fF49NFHH2nAgAHNvZkWMyV9gEoOfCrT8Omic7poSnr41A4AAIDW02xXNnzllVd07NgxjR07Vg8++KAmTJgg0zQ1cuRIde/evbk20+J6dInTF/nHx36/unu3vcUAAAAgZAUVpHv27Ok/vd2wYcP88wcPHqzBgwcHVxkAAAAQwrggCwAAAGABQRoAAACwgCANAAAAWECQBgAAACwgSAMAAAAWEKQBAAAACwjSAAAAgAUEaQAAAMACgjQAAABgAUEaAAAAsIAgDQAAAFhAkAYAAAAsIEgDAAAAFhCkAQAAAAsI0gAAAIAFBGkAAADAAoI0AAAAYIGlIG0YhqZPn66xY8cqIyNDe/bsCVj+7LPPasSIERo5cqTefPPNZikUAAAACCUuKw9as2aNPB6P8vLyVFBQoOzsbD311FOSpOLiYi1atEhvvPGGysrKNHz4cKWlpTVr0QAAAIDdLPVIb9y4UQMHDpQkJScnq7Cw0L+sffv2OvPMM1VWVqaysjI5HI7mqRQAAAAIIZZ6pEtKSuR2u/3TTqdTXq9XLtfx1Z1xxhkaOnSofD6f7rrrrkatMycnR7m5uVbKAQAAAFqdpSDtdrtVWlrqnzYMwx+i8/Pz9e2332rt2rWSpAkTJiglJUVJSUn1rjMzM1OZmZkB84qKipSammqlRAAAAKBFWRrakZKSovz8fElSQUGB+vXr51922mmnKTY2VjExMWrXrp3i4+NVXFzcPNUCAAAAIcJSj3RaWpo2bNig9PR0maapOXPmaOHChUpISFBqaqree+89jRkzRlFRUUpJSdHVV1/d3HUDAAAAtrIUpKOiopSVlRUwLzEx0X978uTJmjx5cnCVAQAAACGMC7IAAAAAFhCkAQAAAAsI0gAAAIAFBGkAAADAAoI0AAAAYAFBGgAAALCAIA0AAABYQJAGAAAALCBIAwAAABYQpAEAAAALCNIAAACABQRpAAAAwAKCNAAAAGABQRoAAACwgCANAAAAWECQBgAAACwgSAMAAAAWuKw8yDAMzZw5Uzt27FBMTIxmz56tXr16+Ze/8847euKJJyRJF154oWbMmCGHw9E8FQMAAAAhwFKP9Jo1a+TxeJSXl6epU6cqOzvbv6ykpETz58/X008/rWXLlumss87S4cOHm61gAAAAIBRYCtIbN27UwIEDJUnJyckqLCz0L9u0aZP69eunefPm6dZbb1XXrl3VuXPn5qkWAAAACBGWhnaUlJTI7Xb7p51Op7xer1wulw4fPqwPPvhAK1asUIcOHTR+/HglJyerT58+9a4zJydHubm5VsoBAAAAWp2lHmm3263S0lL/tGEYcrmOZ/JOnTrp4osvVrdu3RQXF6fLLrtMn3zySYPrzMzM1I4dOwL+rV271kp5AAAAQIuzFKRTUlKUn58vSSooKFC/fv38y/r376+dO3fq0KFD8nq92rx5s84999zmqRYAAAAIEZaGdqSlpWnDhg1KT0+XaZqaM2eOFi5cqISEBKWmpmrq1KmaOHGiJOnGG28MCNoAAABAW2ApSEdFRSkrKytgXmJiov/20KFDNXTo0OAqAwAAAEIYF2QBAAAALCBIAwAAABYQpAEAAAALCNIAAACABQRpAAAAwAKCNAAAAGABQRoAAACwgCANAAAAWECQBgAAACwgSAMAAAAWEKQBAAAACwjSAAAAgAUEaQAAAMACgjQAAABgAUEaAAAAsIAgDQAAAFhAkAYAAAAssBSkDcPQ9OnTNXbsWGVkZGjPnj113mfixIlasmRJ0EUCAAAAocZSkF6zZo08Ho/y8vI0depUZWdn17rPggULdOTIkaALBAAAAEKRpSC9ceNGDRw4UJKUnJyswsLCgOX//Oc/5XA4NGjQoOArBAAAAEKQy8qDSkpK5Ha7/dNOp1Ner1cul0s7d+7Uq6++qscff1xPPPFEo9eZk5Oj3NxcK+UAAAAArc5SkHa73SotLfVPG4Yhl+v4qlasWKH9+/fr9ttv11dffaXo6GidddZZDfZOZ2ZmKjMzM2BeUVGRUlNTrZQIAAAAtChLQTolJUVvvfWWhgwZooKCAvXr18+/7IEHHvDfzsnJUdeuXRniAQAAgDbHUpBOS0vThg0blJ6eLtM0NWfOHC1cuFAJCQn0IAMAACAiWArSUVFRysrKCpiXmJhY6341h2oAAAAAbQUXZAEAAAAsIEgDAAAAFhCkAQAAAAsI0gAAAIAFBGkAAADAAoI0AAAAYAFBGgAAALCAIA0AAABYQJAGAAAALCBIAwAAABYQpAEAAAALCNIAAACABS67CwAAwC77DpZqwdJN2r77kM7v3VlT0geoR5c4u8sCECbokQYARKwFSzdp2+cH5TNMbfv8oBYs3WR3SQDCCD3SLWTrp9/ZXQIAoAGf7D5Ua5r3b8BeF5/b1e4SGo0gDaBFHSou1/J1u/Tl/qNK6B6vUYP7qnPHWLvLAiRJCd3jtfub4oBpAGgshnYAaFHL1+3S7m+KZRimdn9TrOXrdtldEuA3anBfHf12l0zDp95ndNSowX3tLglAGLHUI20YhmbOnKkdO3YoJiZGs2fPVq9evfzLn3vuOa1evVqSdO2112rSpEnNUy2AsPPl/qP1TgN26twxVrveelySNPftj22uBkC4sdQjvWbNGnk8HuXl5Wnq1KnKzs72L9u7d69WrVqlpUuXKi8vT++++662b9/ebAUDCC81fyrnp3MAQFthKUhv3LhRAwcOlCQlJyersLDQv6xHjx7685//LKfTqaioKHm9XrVr1655qgUQdvjpHADQVlka2lFSUiK32+2fdjqd8nq9crlcio6OVufOnWWaph555BFdeOGF6tOnT4PrzMnJUW5urpVyAIQwfjoHALRVloK02+1WaWmpf9owDLlcJ1dVUVGhX/3qV4qLi9OMGTMatc7MzExlZmYGzCsqKlJqaqqVEgEAAIAWZWloR0pKivLz8yVJBQUF6tevn3+ZaZr6xS9+ofPOO09ZWVlyOp3NUykAAAAQQiz1SKelpWnDhg1KT0+XaZqaM2eOFi5cqISEBBmGoQ8//FAej0fr16+XJN13330aMGBAsxYOAAAA2MlSkI6KilJWVlbAvMTERP/trVu3BlcVAAAAEOK4IAsAAABgAZcIBwAALe5QcbmWr9ulL/cfVUL3eI0a3FedO8baXRYQFHqkAQBAi1u+bpd2f1MswzC1+5tiLV+3y+6SgKARpAEAQIv7cv/ReqeBcESQBgAALS6he3y900A4Yow0GLcGABHErvf8UYP7asYflsrd9Rz1Oet0jRrct8W3CbQ0eqTBuDUAiCB2ved37hirXW89rk0vTtHPhl9Mhw3aBII0GLcGABGE93yg+RCkwbg1AIggvOcDzYcgDY0a3FdHv90l0/Cp9xkdGbeGNuNQcbn+tGKrfv3H9/SnFVt1qLjc7pIA2/GeDzQfDjaEf9yaJM19+2ObqwGaT9VYUEn+saA/G36xzVUB9uI9Hy0p0k5gQJAGwkikvUEFK1zHgvI6oz7sHwhlkdaBwdAOIIxwhpWmCdexoLzOqA/7B0JZMB0YVcPxhk9bpQefeFf7DpY2d3nNjiANhJFw7WG1S7iOBeV1Rn3YPxDKgunAqPqS6DNMbfv8oBYs3dTc5TU7gjQQRsK1h9Uu4XreWl5n1If9A6EsmA6Mml8Kt+8+1NzlNTuCNNDKgjmTRLj2sKJp7Hqdw/UsJ+Fat1W8DyCUBdOBUfNL4fm9Ozd3ec3O8sGGhmFo5syZ2rFjh2JiYjR79mz16tXLv3zZsmVaunSpXC6X7r77bl133XXNUjAQ7oI5EMOuo+05uKl12fU6h+tBQuFat1WcdQNtVfXLyPc/9weakj7A7pIaZDlIr1mzRh6PR3l5eSooKFB2draeeuopSdKBAwe0aNEivfTSS6qoqNCtt96qq6++WjExMc1WOBCuwnF8Y6QFlUgVjvumFL51o/XQGRAeqr4kRrui9Oru3XaX0yiWh3Zs3LhRAwcOlCQlJyersLDQv2zLli0aMGCAYmJiFB8fr4SEBG3fvj34aoE2IBzHNxJUIkM47ptS+NaNxgt2+I5dZzqJtGFHkchhmqZp5YEPP/ywrr/+el177bWSpB/96Edas2aNXC6XVq5cqZ07d2ratGmSpAceeEDDhw/XVVdd1aRtFBUVKTU1VZfdMlOx7i5WyrSkqKhIktSzZ0/L6/B4jeYqp1Xs3/e1JKl7jzNtrqTt8xmmjhSXyhHlkssVpQ6x0XJGORr9eDteq6PHPPL5Tr5VOJ0OxXdo/C9Mdu5f4bpv21F3sPumXcLxbypYwdZs13O2ut1g34O+P1pRa16n+HZNqsGKYOsOV8HsX/v3fS2HgstgVpWXHNRHf5+ptWvXNnr7lod2uN1ulZaePL+fYRhyuVx1ListLVV8fP09BDk5OcrNzbVaTrMK9sUrKiqSKes7kGx4bDBvpna+oYfjY51RDnXu5G7y46rY8Vp1iI3WsfJK+XymnE6HOsRGN+nxwX5Yh+O+HezfhR11B7tv8jfVeo8N9m/K6uOD/dJiebs+s97phjidjlqBtimsvlbB1m3ne5Bd+2f3HmcqxhU+58Kw3CP9+uuv66233lJ2drYKCgqUm5urP//5z5KOj5G+8847tXz5cnk8Ho0ePVorV65Uu3ZN+/ZX1SPdlG8GoaB3796q9Br6p4WDQG78UYoktfpjgxHsdu16zuHY1sGi7tbbrp1tTXu1nkh7zn9asdV/vIQk9T6jY6scLxHsdoMdI231tQq2bjv3Lzv3z4vP7drq25Ss5U7LPdJpaWnasGGD0tPTZZqm5syZo/6Xw08AAA4WSURBVIULFyohIUGpqanKyMjQrbfeKtM0de+99zY5RAOAnQ4Vl6vvdZPl7nqO/rRia9gcnBSudUeacH2d7DpeYtTgvrWCcFN07hhrywHSwdaN0Gc5SEdFRSkrKytgXmJiov/2mDFjNGbMGOuVASEqXD8A0TTL1+1S/A+Of+iF05lKwrXuSBOur1NC9/iAHtbWOrDTriAsBfeeb2fdaB3hMwgFbVLVG9SA0QvC5ojmqg9AR5SzVY/+RusK1zOVhGvdkSZcX6dRg/uq9xkdFRXliJiLwYTje344fraGK4I0bBWOb1Dh+gGIpgnXU6qFa92RJlxfp6oe1tl3XdXkq9aFq3B8zw/Hz9ZwRZCGrcLxDSpcPwDRNOHa8xaudUcaXqfwEY7v+eH42RquLI+RBpqDXePtgsHBI5EhXMc22lU3xw40TbjuX5HIrvf8YP6mwvGzNVwRpGGrcAylfAACtYXrwXPB4MtDZLDrPT+Yv6lgP1vZtxuPIA1bEUqBtiGYn5LD9UM7Er88oPUE8zcV7Gcr+3bjMUYaABC0YMaRhuuBUYxDRUuyc2w2+3bjEaQBAEEL5uC5cP3QDseD0BA+7DwglX278RjaAQAIWjA/JYfrgVHheIwHwoedQx/ZtxuPIA1EiHAdhxqOaOumCdcPbY7xQFvFvt14BGkgQnDwSOuhrZuGD20A4Yox0kCECNdxqOGItgaAyECQBiIEB4+0HtoaACIDQRqIEFySuPXQ1gAQGRgjDUQIxqG2HtoaACIDPdIAAACABQRphK2qU4wNGL1Af1qxVYeKy1vlsQAAAJLFIF1e/v/bu7+YqO40jOPPMFghA8QwYGxiW0ElWFhS0OiNcGFrbExasUoEDcZiSNsIOttYRVstFSKi7cYUtds1NjFUAbGN8aYxKWkljdQLKmXBak38U9RqEBoDUymIsxe7sA4Of+YMcg76/SQmnjMznpc3b5hnjmd+p0v5+flauXKlcnNz1d7e/shzSktLtWLFCi1btkzHjh0LuFBgoEBuKzxeb0kMAACsw1CQrqioUFxcnI4ePar09HQdOHDA6/Eff/xRv/32m6qqqlRRUaGDBw/q7t27o1Iw0CeQJcZYngwAAATKUJCur69XamqqJCktLU11dXVejycnJ2vnzp392729vQoO5nuNGF2BLDHG8mQAACBQw6bb6upqHT582Guf0+lUePh/g4fD4VBHh/fZvIkTJ2rixInq6elRQUGBVqxYIYfDMYplA4HdVni83pIYAABYx7BBOiMjQxkZGV778vLy5Ha7JUlut1sRERGPvO7u3btav3695s6dq7feemvYQsrKyrRv376R1g0EtMQYy5MBAIBAGbq0IyUlRadPn5Yk1dbWavbs2V6Pd3V1ac2aNVq2bJnWrVs3on8zPz9fFy9e9PpTU1NjpDwAAADgsTMUpLOysnTp0iVlZWWpqqpKeXl5kqTdu3ersbFRlZWVamlpUXV1tbKzs5Wdna2WlpZRLRzWwDJyAADgaWXoG4ChoaH69NNPH9m/adMmSVJSUpLWrFkTUGEYH/qWkZPUv4wcl0xgNPV9WAuLitW/TvxbyxfMVGREiNllAQDADVkQGJaRw+PGmt8AAKtiTbrHZEJwkP42I8rQ6yT5/dpbbW7FLdgghzNGR05dkCszWVOcj3+llFnTItV8uc1r28jPDQymZcCHs5bbHcwYAMASOCP9hNhbeU5h0TNkC7Kr+XKb9laeG5PjujKTlRDrlD3IpoRYp1yZyWNyXDw94qdFDrkNAIBZOCP9hLhwtX3I7cdlitOhXevmj8mx8HRyZSZrb+U5XbjarvhpkXxYAwBYBkH6CRE/4BILztrhScGHNQCAVXFpxxOCSywAAADGFmeknxCctQMAABhbnJEGAAAADCBIAwAAAAYQpAEAAAADCNIAAACAAQRpAAAAwACCNAAAAGAAQRoAAAAwgCANAAAAGECQBgAAAAwgSAMAAAAGGArSXV1dys/P18qVK5Wbm6v29nafz7t3756WLFmi2tragIoEAAAArMZQkK6oqFBcXJyOHj2q9PR0HThwwOfzduzYIZvNFlCBAAAAgBUZCtL19fVKTU2VJKWlpamuru6R5xw6dEjJycmKj48PrEIAAADAgoKHe0J1dbUOHz7stc/pdCo8PFyS5HA41NHR4fV4XV2drl27ph07duinn34aUSFlZWXat2/fSOsGAAAATDVskM7IyFBGRobXvry8PLndbkmS2+1WRESE1+PHjx/XjRs3lJ2drcuXL6u5uVnR0dGaNWvWoMfJz89Xfn6+177r16/r5ZdfHvEPAwAAAIyVYYO0LykpKTp9+rSSkpJUW1ur2bNnez3+ySef9P+9oKBAixcvHjJEAwAAAOONoWuks7KydOnSJWVlZamqqkp5eXmSpN27d6uxsXFUCxxvbrW5FZOWr8Sl/1DB/h90q81tdkkAAAB4DGwej8djdhGD6bu0o6amRlOnTjW7nBEp2P+Dmi+39W8nxDq1a938Eb32VptbWX//pxzOGCXOmCxXZrKmOB2Pq1QAAAD8j5HcyQ1ZRtmFq+1Dbg9lb+U5hUXPkC3IrubLbdpbeW60ywMAAMAoIUiPsvhpkUNuDyWQEA4AAICxRZAeZa7MZCXEOmUPsikh1ilXZvKIXxtICAcAAMDYMrRqBwY3xekY8TXRA7kyk7W38pwuXG1X/LRIv0I4AAAAxhZB2kICCeEAAAAYW1zaAQAAABhAkAYAAAAMIEgDAAAABhCkAQAAAAMs/WXD3t5eSdKtW7dMrgQAAABPsr682Zc/R8LSQbq1tVWStGrVKpMrAQAAwNOgtbVVL7zwwoiea/N4PJ7HXI9hXV1dampqUnR0tOx2+5geu+9e6xgZ+uU/euYf+uUf+uUf+uUf+uUf+uUfs/rV29ur1tZWJSYmKiQkZESvsfQZ6ZCQEM2ZM8e040+dOtW0Y49H9Mt/9Mw/9Ms/9Ms/9Ms/9Ms/9Ms/ZvVrpGei+/BlQwAAAMAAgjQAAABgAEEaAAAAMMBeWFhYaHYRVjVv3jyzSxhX6Jf/6Jl/6Jd/6Jd/6Jd/6Jd/6Jd/xku/LL1qBwAAAGBVXNoBAAAAGECQBgAAAAwgSAMAAAAGEKQBAAAAAwjSAAAAgAGWvkW4GR48eKDCwkJdvHhRzzzzjIqLi/2+XeTTJj09XeHh4ZL+e0vPkpISkyuypp9//lkff/yxysvLde3aNRUUFMhms2nmzJn68MMPFRTE59qHPdyv5uZmvf3225o2bZokKSsrS4sXLza3QIvo6enR1q1bdePGDXV3d+udd97RjBkzmK8h+OrZlClTmLFB9Pb26oMPPtCVK1dkt9tVUlIij8fDjA3CV786OjqYr2G0tbXpjTfe0BdffKHg4OBxM18E6QG+/fZbdXd3q6qqSg0NDdq1a5c+++wzs8uyrL/++kuSVF5ebnIl1nbw4EGdPHlSoaGhkqSSkhK5XC7NmzdP27dvV01NjRYuXGhyldYxsF/nz5/Xm2++qZycHJMrs56TJ09q0qRJ2rNnj/744w8tXbpU8fHxzNcQfPVs3bp1zNggvvvuO0lSZWWlzp492x+kmTHffPVrwYIFzNcQenp6tH37doWEhEgaX++R1oz3Jqqvr1dqaqok6aWXXlJTU5PJFVnbhQsXdO/ePeXk5Gj16tVqaGgwuyRLev7551VWVta/3dzcrLlz50qS0tLSdObMGbNKs6SB/WpqatL333+vVatWaevWrers7DSxOmt59dVXtWHDhv5tu93OfA3DV8+YscG98sorKioqkiTdvHlTUVFRzNgQfPWL+RpaaWmpMjMzNXnyZEnj6z2SID1AZ2enwsLC+rftdrvu379vYkXWFhISorVr1+rQoUP66KOPtHHjRvrlw6JFixQc/P//APJ4PLLZbJIkh8Ohjo4Os0qzpIH9SkpK0qZNm3TkyBE999xz2r9/v4nVWYvD4VBYWJg6Ozu1fv16uVwu5msYvnrGjA0tODhYmzdvVlFRkRYtWsSMDWNgv5ivwX399deKjIzsP4kpja/3SIL0AGFhYXK73f3bDx488HpDh7eYmBi9/vrrstlsiomJ0aRJk9Ta2mp2WZb38LVebrdbERERJlZjfQsXLlRiYmL/38+fP29yRdby+++/a/Xq1VqyZIlee+015msEBvaMGRteaWmpTp06pW3btvVf1icxY4N5uF/z589nvgbx1Vdf6cyZM8rOztYvv/yizZs3q729vf9xq88XQXqAlJQU1dbWSpIaGhoUFxdnckXWdvz4ce3atUuSdPv2bXV2dio6OtrkqqzvxRdf1NmzZyVJtbW1mjNnjskVWdvatWvV2NgoSaqrq1NCQoLJFVnHnTt3lJOTo/fee0/Lly+XxHwNx1fPmLHBnThxQp9//rkkKTQ0VDabTYmJiczYIHz1Ky8vj/kaxJEjR/Tll1+qvLxcs2bNUmlpqdLS0sbNfNk8Ho/H7CKspG/Vjl9//VUej0c7d+7U9OnTzS7Lsrq7u7VlyxbdvHlTNptNGzduVEpKitllWdL169f17rvv6tixY7py5Yq2bdumnp4excbGqri4WHa73ewSLeXhfjU3N6uoqEgTJkxQVFSUioqKvC7BepoVFxfrm2++UWxsbP++999/X8XFxczXIHz1zOVyac+ePcyYD3/++ae2bNmiO3fu6P79+8rNzdX06dP5HTYIX/169tln+R02AtnZ2SosLFRQUNC4mS+CNAAAAGAAl3YAAAAABhCkAQAAAAMI0gAAAIABBGkAAADAAII0AAAAYABBGgAAADCAIA0AAAAYQJAGAAAADPgPeg2+QrWVZMsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c17645a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12,8))\n",
    "ax1=fig.add_subplot(211)\n",
    "fig=sm.graphics.tsa.plot_acf(deaths_per_year.first_difference.iloc[1:],lags=40,ax=ax1)\n",
    "ax2=fig.add_subplot(212)\n",
    "fig=sm.graphics.tsa.plot_pacf(deaths_per_year.first_difference.iloc[1:],lags=40,ax=ax2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c17777828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12,8))\n",
    "ax1=fig.add_subplot(211)\n",
    "fig=sm.graphics.tsa.plot_acf(deaths_per_year.seasonal_difference.iloc[13:],lags=40,ax=ax1)\n",
    "ax2=fig.add_subplot(212)\n",
    "fig=sm.graphics.tsa.plot_pacf(deaths_per_year.seasonal_difference.iloc[13:],lags=40,ax=ax2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/statsmodels/tsa/kalmanf/kalmanfilter.py:646: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  if issubdtype(paramsdtype, float):\n",
      "/anaconda3/lib/python3.6/site-packages/statsmodels/tsa/kalmanf/kalmanfilter.py:650: FutureWarning: Conversion of the second argument of issubdtype from `complex` to `np.complexfloating` is deprecated. In future, it will be treated as `np.complex128 == np.dtype(complex).type`.\n",
      "  elif issubdtype(paramsdtype, complex):\n",
      "/anaconda3/lib/python3.6/site-packages/statsmodels/base/model.py:473: HessianInversionWarning: Inverting hessian failed, no bse or cov_params available\n",
      "  'available', HessianInversionWarning)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>ARIMA Model Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>      <td>D.Value</td>     <th>  No. Observations:  </th>    <td>65</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>          <td>ARIMA(1, 1, 2)</td>  <th>  Log Likelihood     </th> <td>-225.444</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>css-mle</td>     <th>  S.D. of innovations</th>   <td>7.610</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>          <td>Tue, 27 Feb 2018</td> <th>  AIC                </th>  <td>460.889</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>              <td>11:08:09</td>     <th>  BIC                </th>  <td>471.761</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sample:</th>           <td>02-01-2012</td>    <th>  HQIC               </th>  <td>465.179</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th></th>                 <td>- 06-01-2017</td>   <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "        <td></td>           <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>const</th>         <td>    1.0108</td> <td>    0.101</td> <td>    9.983</td> <td> 0.000</td> <td>    0.812</td> <td>    1.209</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L1.D.Value</th> <td>    0.9318</td> <td>    0.129</td> <td>    7.204</td> <td> 0.000</td> <td>    0.678</td> <td>    1.185</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L1.D.Value</th> <td>   -1.7975</td> <td>    0.163</td> <td>  -11.022</td> <td> 0.000</td> <td>   -2.117</td> <td>   -1.478</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L2.D.Value</th> <td>    0.7975</td> <td>    0.160</td> <td>    4.973</td> <td> 0.000</td> <td>    0.483</td> <td>    1.112</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<caption>Roots</caption>\n",
       "<tr>\n",
       "    <td></td>   <th>           Real</th> <th>         Imaginary</th> <th>         Modulus</th> <th>        Frequency</th>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>AR.1</th>               1.0732                    +0.0000j                    1.0732                    0.0000     \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MA.1</th>               1.0000                    +0.0000j                    1.0000                    0.0000     \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MA.2</th>               1.2539                    +0.0000j                    1.2539                    0.0000     \n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                             ARIMA Model Results                              \n",
       "==============================================================================\n",
       "Dep. Variable:                D.Value   No. Observations:                   65\n",
       "Model:                 ARIMA(1, 1, 2)   Log Likelihood                -225.444\n",
       "Method:                       css-mle   S.D. of innovations              7.610\n",
       "Date:                Tue, 27 Feb 2018   AIC                            460.889\n",
       "Time:                        11:08:09   BIC                            471.761\n",
       "Sample:                    02-01-2012   HQIC                           465.179\n",
       "                         - 06-01-2017                                         \n",
       "=================================================================================\n",
       "                    coef    std err          z      P>|z|      [0.025      0.975]\n",
       "---------------------------------------------------------------------------------\n",
       "const             1.0108      0.101      9.983      0.000       0.812       1.209\n",
       "ar.L1.D.Value     0.9318      0.129      7.204      0.000       0.678       1.185\n",
       "ma.L1.D.Value    -1.7975      0.163    -11.022      0.000      -2.117      -1.478\n",
       "ma.L2.D.Value     0.7975      0.160      4.973      0.000       0.483       1.112\n",
       "                                    Roots                                    \n",
       "=============================================================================\n",
       "                 Real           Imaginary           Modulus         Frequency\n",
       "-----------------------------------------------------------------------------\n",
       "AR.1            1.0732           +0.0000j            1.0732            0.0000\n",
       "MA.1            1.0000           +0.0000j            1.0000            0.0000\n",
       "MA.2            1.2539           +0.0000j            1.2539            0.0000\n",
       "-----------------------------------------------------------------------------\n",
       "\"\"\""
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from statsmodels.tsa.arima_model import ARIMA\n",
    "deaths_per_year.Value = deaths_per_year.Value.astype(float)\n",
    "arima = ARIMA(deaths_per_year.Value,(1,1,2))\n",
    "results = arima.fit()\n",
    "results.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/statsmodels/tsa/kalmanf/kalmanfilter.py:646: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  if issubdtype(paramsdtype, float):\n",
      "/anaconda3/lib/python3.6/site-packages/statsmodels/tsa/kalmanf/kalmanfilter.py:650: FutureWarning: Conversion of the second argument of issubdtype from `complex` to `np.complexfloating` is deprecated. In future, it will be treated as `np.complex128 == np.dtype(complex).type`.\n",
      "  elif issubdtype(paramsdtype, complex):\n",
      "/anaconda3/lib/python3.6/site-packages/statsmodels/tsa/kalmanf/kalmanfilter.py:577: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  if issubdtype(paramsdtype, float):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'RSS: 3854.7203249499853')"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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iwGAwYhpeIPAqYgGxVjDGRIDBYMQ0gesKx1pcgIkAg8GIaZSuIICJAIPBYMQUrkBLIMbSRJkIMBiMmMbl9vr9zSwBBoPBiCHcHv9Bn2UHMRgMRgwR6A7yelmdAIPBYMQMUmBYo6bDoYdnlgCDwWDEDC4PjQnEmbQAWEyAwWAwYgrJEjAbmAgwGAxGzOESA8PMEmAwGIwYRHYHGZkIMBgMRswhuYPijDoATAQYDAYjppBSRM1GDQDAy+oEGAxGLHPibH1MzYbdckxAtASi1DaipMqCmgZHVF4rEkwEGAyGzIETVXhwxVZ8u6+4oy8lakhtI6IdE3jstR147r19UXmtSGha8ySPx4NHHnkEpaWlcLvduOeee9CnTx8sXrwYHMehb9++WLZsGVQqpjEMRmfiWFEdAKD2FzBDjRY+d1B0RaDB6oZWq47Ka0WiVSKwbt06JCUl4e9//zvq6+tx7bXXon///li4cCHGjBmDpUuXYvPmzZg6dWpbXy+DwWhHTpU2AgCc7tjxi8t1AlEUAUFcyMbh8jZ/cDvTqqn6FVdcgQceeED+W61W48iRIxg9ejQAYMKECdixY0fbXCGDwYgaRWVUBBzujh+cooUcE4iiCEhxB+cvQARaZQmYzWYAgNVqxf3334+FCxfi2WefBcdx8n6LxdLseVauXImXX365NZfAYDDaGIvdjap66gYKXGjl10xwnUD7v3dpNTOnm4cgEKhUXLu/Zjha7bQvLy/HTTfdhFmzZmHGjBl+/n+bzYaEhIRmz7FgwQIUFBT4/WzevLm1l8RgMM4DyQoA8ItwU0QLl5uHWsXBoKdz4mhYAsolLZ0dbHW1SgRqampw66234uGHH8Zvf/tbAMDAgQOxa9cuAMDWrVsxcuTItrtKBoPR7hSW+kQgtiwBHnqdGlq5i2gU3EEKoelowW2VCLz22mtoamrCq6++ivnz52P+/PlYuHAhVq5cieuvvx4ejwfTpk1r62tlMBjtyCmFCHT07DSauD089Fo1tBpRBKJgCSjXMOhoEWhVTGDJkiVYsmRJ0PbVq1ef9wUxGIyOoai0EQYdTVl0umLIEnCLloAoAt5oBIYVq5l19GfNEvkZDAZcHh7FVVbkZifCqNfElCXg8vDQadXQaKLnDnJ7fzmWABMBBoOBsxVNEASC3OwEGPSaVtUJrNlyEht2FLXD1bUvLrfkDqJWUDQsAWVguKPTcZkIMBgAsHIl8NprHX0VHYYUFO6VkwSDTt0qS+DTLSfx6bc/t/WltSuCQOD2CtDr1FCrOKhUXHSyg5SBYWcnjAkwGL86HnsM0GiAu+/u6CvpECQR6J2TCIOOWgKEELn2pyW4vQKI3d1el9guSG4Zvdi+QatRRaVOwC8mwCwBRkchCAT1FmdHX0bHY7MBjY1AbS19jEEKSxuhUnHonhUPg04ttzVoKYQQuD08bE4v+Ch14WwLpFRYvRgQ16pVUbIEWEyA8Qvg233FuPkvG3G2oqmjL6VjKSvz/X7qVMddRwfBCwRF5U3onhkPnVYtF005ziFrRSkYVoenza+xvZBSNXV+lkCUYwId7A5iIhDDFFdaQAhQWm3r6EvpWEpLfb/HoAiU11jhcvPIzaZV/tKs+FzcFG6PgPu+eQW/37oKTbbO4xKSLQGlCEQjO0jhDnJ0cGEeiwnEMNKMzeHqPDO3dkEpAj93rsBmW6AMCgOAUUeHhXOpGnZ7eEw4vg02vRk19s5zP0kzctkdpFHBFoWZuYe5gxi/BOzizW5zxE5OeEhi3BJQBoUB34B4LoOT2+mGyeNEoqMJFpur7S+ynZDcQT5LQB2limFlsRgTAUYHYXPSGZudWQK+32NYBCR3kKEVloC3li5Go+M9sNfUt/EVth+B7iBNlGICzBJg/CKwSe6gDg5MdTiSCJhMMecOIoSgsKwRGSkmeY1do/7cYwLeWt/A7y6vaNuLbEdcge4gtSoqC837xQSYCDA6CrtkCTARoDUCo0bR352dP22W54UWDeJ1TU40Wt2yKwgA9KIlcC49bYR6nwjwFVXncKUdizvIHaSCQNDuaa7uX1ADOSYCMYwUC4h5ESgrA7p0Afr2BQgBijpf64NAXlmTj1uf+MZvsAlFURlND87N9omAoRXZQUKdTwSEqupzudQOJbBOQBOlTqLKOgFWLMboMOwsJgAIAhWBnBygd2+6rZO7hCrr7Ni85ywsdjcszVTwniptAAA/S0CqEziX/kFEUWTHVXciEQisE4jSmgJSxbBOo+pwdywTgRjFywvylzymLYHqasDrpSLQpw/d1smDw19sL4RA6O9K33MofEHh87MEUN8g/6qqq2n58zqYUHUCQPQsgYQ4PXMHMToG5cAvWQQxiRQUVloCnVgE7E4Pvt51Rv67WXdQaRPiTTqkJRnkbVJ20Dl1Em3wiYC2vq7lz+tgQtUJAFEQAVGcE+N0cIh9mjoKJgIxinLgj2lLQBKB7OxfhTto0+6zsDu98qDmjpDpQghBRZ0NXTPi/BrFtcYS4Jp87iB9Y+cRgVB1AkD7LzYvWwImndzJtKNgIhCjKPu7MBEAtQQSEoD09E5rCfACwbpthdBpVJh0YTcAkd1Bbq8AQnyDvoQcEziH7CBVo88SMDV1vjoBXYA7yMu378zc4xGg1ahgNEifdcd9B5kIxChKS8Dh8nSoOdqhKEUAoNbA6dM0TtDJ2HW4HJV1dlw2qjvSEql7xxXBHeQOCIpKtMYSUDX5mhDGWRujUnDVFgTVCcjuoPa1BKTVzIxysz4mAowoo2wV4eVJp/nStjlSB1GlCHg8QHFxx11TK/n8e2rBzLyklzywR4oJBObIS7SmYlhjoe4gu86IREcjrJ1kXYFgd1B0YgIeLw+dRiX3aWIiwIg6gcFgW6wGh0NZAkCncwmdOFuPY6frMHJAJrqJLaEB/8VLAglMj5QwtKJ3kNpqgQAOdanZSHA0oamziIBcJ0AHYzlFtN2zgwRotWrZHcREgBF1pJYRZqMWQAy3jigtBRITAbOZ/t1J00TXilbArAm9AAB6Lf1qR3YHibnqWv9hQK1WQaNWnZMloLU2wa43wpmcCqPHCVtd51ijItASiFqxmIdaAoZWVGe3NUwEYhSpXW56khFADAeHS0tpZpBEJ8wQqq53YPvBMvTskoChfdMB+LJcImUHhYsJALR/0LnEBHRWC2x6M7zJqQAAR0l5i5/bkbjcPFQcoFHT7ChfdlD7p4iymACjQ5HcQWmSCMRi1bDDAdTX+1xBQKd0Bx04UQVBIJg2toec6tmSmEDgLFiJXqc5p8VOdDYqAiSdipCnvLLFz+1I3F4eep1a/tzk7KBoxQT0kuut475/TARiFJvDg4tO/ohFf7wCGY2VsWkJBMYDACAjA4iL61Qi0GCl/fu7pJnlbdLA3prsIIDGBVwttQR4HnqHFTa9GaoMKgJ8RecQAZebh17rW1tLDgzz7eee4QUCL09ES0B0xzJ3ECPa2JweTD28GQZrI/pUnorNquFQIsBx1Bo4dYo2k+sESCKQGKeXt0l+/kiBYbeHx03b3kWfTf8N2mfQa1peMSymh9r0Zmi7ZAHoPE3kXB4eOkWdRDSygzwK8TXozz0I39YwEYhRXE12XFB8CACQZG+ITUsgMD1UondvwGYDKjvHbLbRQjNxkvxEoAWWgMON6/Z8ij6frgraRy0BHoLQAiEUm8fZ9GYYu3YBAHA1nUQE3LwcRAeiIwJSdbBWo5JjAh3ZSZSJQIySXnAABi+dQSbZG2NTBEJZAkCnyxBqlC0BnbytJTEBvoEO3obqYLGTawWa6T0EQO4bZNObYe5ORUBV2zmayLk8vF9MJBopolIh2tx//BFdlz4MoGOz885LBPLz8zF//nwAwJkzZzB37lzceOONWLZsGQQhRouPOgm9Du+Sf6eWAHMHyXSyDKEGqwtmg0bObAF87qBIbSOk9s+6xnoaJFdwTlXDogg4DGaYu9FMK10naCJHCIHbw8s1AkB0UkRdHh4cEdDj0E6Ytn8HAHB0RkvgX//6F5YsWQKXi85Cnn76aSxcuBDvv/8+CCHYvHlzm11krHDoVA1+Lmlo/sA2IO/EPghiRkSivRH2Dm5n2yEomscdLarF8TPiwNXJMoQarS6/eADgCwxHShGFot+P7BoTOaf8dVEEnOZ4qLMyAQC6hpaLQGm1FbuPRn9JSo/YO0mvVdN7YehQpPzwrbyv3V7XI8DodkBFBKhFseyUMYHu3btj5cqV8t9HjhzB6NGjAQATJkzAjh07mj3HypUrkZeX5/czefLk1l5Sp+fpVXuw4sP97f9C1dXoWf4zCnsNAVGrkWRviM1isdJSQK0GMjPx/Ps/Yfnbu2kPpU7kDhIEgkabO0gEWuIOIo0W3x8lJX77WmMJuEzxQFISvCo1TJaWN5F7a91hPPXvXWiyRbfK2FcxrQLefx84eBAJO7cDaN/eQW4vj3inFQDANTZCJfCds1hs2rRp0Gh8ZhQhRM61NZvNsFgs4Z4qs2DBAhQUFPj9xKoF4fEKsNjdqKyztXszN+9XX0MFgsILLgJJz0CSrSE220aUlgJZWYBajSarC/UWF8prbUDXroBW2yncQVaHB4JA/OIBgC/AGckdpGz/LFtFIufUSVQUAbc5HuA42M2JMFtbbtGWVFkhEKCyztbi57QFvgVlNMDatQAAjYNeQ3uuLOb2CIhz+sbHRJe1c1oCQSdS+U5ls9mQkJDQVqeOCawOOgtyuHi5mre94DduBACUDrsYXGYGkhwxGBhWLCvJC0ROhzxWVEetg9zcTmEJNIZIDwUAnab57CDOomjt0AaWgMccDwCwJyQj3t7YoqAyzwuoqrMDAKrqHc0c3bZIVlKisxEQPRcauygC7Zkd5PFZAgCQxtt/HSIwcOBA7NpFg41bt27FyJEj2+rUnZ5DP9fg7mc2oaYh/E1utftm4pGOO28IgWbzJjQYE2HNGwQuMxMmtwNey/nNwo6frsNtT32Dn4ujE9MICc8D//oXUNcCf3RNDe0WmpPj9wU8dloRF6it9Vsx65eIVCOQFCACKhUHrUYV0R2kUopAgCWgP5fVxcQAsyeOioArMRlxLjusDdZIzwIAVDc4wItpqNX19uZfqw2RRKpv/g9yTYjaTq+5PSuGPV4BcQoRSP21iMCiRYuwcuVKXH/99fB4PJg2bVpbnbrTs/dYJUqrbSg4E95PqlwQvF2/DEePQl1RjgM9hsJk0gGZNJCnqa06r9PuOFSOqjo73v/6eFtcZetYswa4805gyZLmj1XUCCgzo2QR6CRxgXCWAEDjApFmtGpr+JiA1M7gXCwBbxxdp9gj9g+ylzQf7K2o9U0+om0JSO6gXnu+k7epomEJeHk/EUjx2DpUBDTNHxKerl274uOPPwYA5ObmYvXq1W1yUb826pqcABCxva5ypa92tQS+/hoAsL/HMHQxammbBAC681wcvEhcsHzP0UqcrWhC96wOcAd+8QV9/PBD4IUXAIMh/LGKzCBlUPxshQVWuxtxygyhCy9spws+fxotVAQyLTUAyaUVzyJ6rSqiS0ZtVczUz8MSIPUN4ADwCVQEvClUBJwl5cDwvIjPLa/1TXgkt1C0cLl56D0uZB/YAQwYABQVQSV+Ju0bE+ARr4gJJLltbGWxXzuyCNhcYY9RLsJRHQURONBjGMwGrWwJ6M8jr5sQglOljVCp6AAkLW4SVXge2LCB/l5fD6xfH/l4RY2AFA9Ri9d//Ex9yDRRnhew7UBpu686dS40WN24+MQOjL56DPC///nt02rUEd1BGlvz2UEt6R8kNFALV4iPoxvSaP8gd3nzlkB5jc8SqI62JeDlMeRsPjQuJzBzJhAfD5Xt/N1BTrcXP+SXhU3wcHsEv5hAkssCt1cA347CEwkmAlGgtpGKgMUWPgPHoogJtJsIOJ3A99/D0jsPdXEpMBs1sggkWOsjDhiRqGlwwmJ3Y8ygLOSkm/HtvmLUNkb3C409e6gPf9w4+vd//hP5eKUIiB0c+/dMASC6hCR3kCJD6KsfT+Nv7+7Ft/v8B8yOpNHqwpQjYkbd3r1++3TayCKgFQc80rUrUFHht6Smb8WrFtwT9Q2w64zQGqhLihOtS29F8y5GyR0Ub9KhKtoxATePsad5KHA7AAAgAElEQVR20z9mzQLi48HZzt8dtGbLSTzzzh4cLQo9sXJ7eZgVIpDgor+fS9fWtoSJQBRoiSWgjAm0mzto+3bA4UDlhXSgNCksgfPpH1RURl1Bvbsm4ppL+8DLE6zfVtg219xSpFnwQw8BI0cCX31FB7ZwKEVAXGpzRF4GOI4GuZGbC5hMwJYtNJMIwLZ8Gkcoq24+4BktXBVVGH7mAP2j0P8zp+6g8IOZTgyCcgMHUktK0StJr2+5JYCGBth0JjktVZNFRYC0oIlceY0NBp0afbsnwerwRLVy3eVwY1ThHrhS0oAxY2j3WDG1/XxE4OBJ6lptsIT+vgdaAvEO+podVavDRKCdsTs9ctBHOdsPxGr3IMVahwRHU/uJgOgKOjPkIgDiqmLirI1WDbfuC3hKjAf0yk7EZSO7ISlOj69+PB3dVhRffklz+ydPBm6+mQ5q770X/vgQlkB6shHdM+NRcLYeXo0WmDuXLjr/9deoa3LiaFEtAKAyyr7rSHTbsQkaQZxBFhX57aOBYT6sW0In5sSjf3/6qIgLGM4hJsA1NsKmN8tpqZoudGKB6sgiQAhBRa0NWalmZCSb6FOi6BIy5e9Dsr0RdZdOBVQqaglYrVBzrS8Wc7q8OHGWusfCBXs9ASmiZjvN0uqoJnJMBNoZyQoAmrEEbC787cNFeOzLv6OmwdGy7o3nytdfA3o9TvcZCgB+MYG2sAR65SRCp1Vj+vhc2JxefL3rTNtcd3OUlwM//QRceikQH08Hb62WuoTCFd6VltJj4+Pl923Sa9C/Zwpcbp6+p7vuose+8QZ2HCyTTxVtt0UkBu3ZRH9JSAiyBHRaNQgBvGF8zXqHFQ6dEejRg27wE4EWtjgWBHCWJtgMZrlfkTGHNpFTN5Ns0GB1wenm0SXNjIxkurhRND/btK3fAAAsk6+gG+LjAUFAHPG0OjB8/EydnPIa7rNze2mxGB9HYygmW2PE49sbJgLtjFIEIsUESGUVMpuq0busAILHK6f+tRkVFUB+PjBhApoE+gU3GTSAuBJUkq31rSNOlTYiKU6PlASajXPlxbnQ69RYu7Uw7ADUpnz5JX286ir6mJoKTJ8OHDoEHDgQ+jlioRjgW1rTZNBiYK4iLjByJDB8OLBuHfK/PwiOE33XdVGOd4QTsspK5J06gKLuA+i1lpXRuI+Ir2AsjAg4bXDqTb4GeorgsNxFtDlLwGoFJwjUEhBbVUjtpLX1tRGfWlFDB/ysVDPSRUsgmmmimds3wanRw3nJRLpBHJTjBFer3UGHTvnec7iZvdvDI85lg5CSBiQlwWgVRYC5g36d1DW2zBIwnqGzOK3HjYymqrYPDm/bRh+nTJHdNGajFtBq4U5IQpKjsVWtI6x2N6rq7MjNTpDbhiSYdZg6ujtqGhzYdqC0mTO0AZIIXH21b9vvf08fQwWInU4aRBbXFpbcQUaDxhccLqqj6ZZ33gnwPHps+AQDeqagd06iOIONwheWEGD8eGDKFDkuoYT/eA1URMDR0VNpDAOg7isRXyfR0AO50WmD02imbTKAkJZAs+9T0UZaigmYcjIhgIO+IXL/oHIxKNwl1SRbAlErGDtxAonFhdjfYxh0CWJWUzwtdovnWy8Ch0/5rJ9IlkC80wKSnAykpkJvEUWAuYOix4mz9ai3OJs/sA1QWgI2pzfszDix1OfP7VZb3PZxgeNiEdeQIbA5fO4PAHCnpCHJ1jp3UFEZ9Wf2ykn02z5rQm+oOOCzb39u315IbjfwzTc0m6dfP9/2K6+kVs5779FjlAQsJuOQLQENuqSakRSnp8FhALjxRniNJlx+8BuMG5yJjJQo+q63bAF++IE+vvNO0G7hgw8ggMPZ8dOAXr3oRkVcoLkmckaXHS6DOaQloNOqwXEtiAmIImDVm+XOpWqtBlZTPIzNNJGTMoM6JCYg9gra1Xu0b3lNUQTiWikCTjeNBxibWS2Mt9mg97p9ItDUABDC3EHRotHqwqKXt+HNzw9H5fVqm5xQCTxGO+gXzBKmYCyl3Oc/71ZX0vaWwIkT9LFfP9icHhj1aqjFBTS8aelIcFrgtJ77LEwOCgeIQFaqGeOG5uB0eVPYVLk2Yft2mtEhuYIktFrgxhtpewipfkAiYB0BX0xAC47jMCA3BTWNTuqfTkjATyMmI8NSjYnVR5CRQmesUQkOv/IKfdRogMWL5fYM0nvQ7NyBozkDoe7RzWcJKOIC+kgi4HJBy3vhNppli0hpCahUHPRadYstAbve7LeegdWcBLMlcssNqUagS5oZyQkGqFVc9GICa9dC4FTY02sk9Dp/ETB7Xa2qEyg4Uw8vTzCsH022CDeoa8T/I5eSAqSmQuVxw+BxdljBWMyJwNlKC7w8iVrf/tpGJ36z5zM89s8/YFDJkZDtcgWBIL2qWP67e3tYAgUFgE4H9OgBu9ND00Ol1xeLe/hWrAurDAoHctnIbgCAHw6WBe1rM6TUUKUrSCKcSyhIBKg7yGSgllH/HtQldPx0HeqbnPgg91IAQMLqVciUfdftPFgVF9PZ6rBhwOOP0/TNJ57w7f/kE3CEYFveONpBVLIEFCLgswSCBzRvHZ2lu81x9L7IyAhRMKZpvouowh2kUyzTaE9IhtlhAfGGH9jKa21QqzikJxmhVnFITTJGJyZQWgrs2IGyvkPQZEr0rSwmxgTMXkersoMOia6gUQNoskU4EVCLbjIuNZXGrwDEOy3MEogWpZUWTDi+FeoTBa0ujjoX6hqdmHTsewDAgLLjsIQQAbvTg5z6UjiNcSA6HbrVtrElQAi1BPr0AdRq2BweGg+QEDOESCvW1C0sbYRBp0aXtLigfUP7piPOqMUP+WXtk+0E0HiAyQRMmBC8b9gwYMgQ2k7iuKKnUaAIuLzQqDnZpy0Hh4vqsONgGX7O6IOGvMHAF18g20UHvXZvcfD66zQO8Ic/AA8+SGf6K1b43seHH4KoVNjR92LaPC6kO4i+n1CtIzyiCHhM4v+ta1f6uShcdwZ9CywBxfrCOsUyja7EFKhA4CoPXzBWUWtDRopJtkgzko2otzjbtW8PAOCNNwBCcPDiKwEgyBIweVt3DYdP1YLjgJGiCIQTUE0TvYdUaSmyCCQ4LC0rzGsHYk4EEle9gYe/fAF3bX4dpVEo+jGcPI5udXSGlVtdFNISsDTakdVYifquuUBeHrrVFaOmLQeZ6mr6Ze3XD4QQ2Jxemh4qwomrQamqzq2JnNvD42ylBT27JMgtF5RoNSqMHdwFdU1O36pdbUlhIR0Up0wJ3yforrtot9ABA2icYP164OxZuk/hDjKKriCAFr1pNSocPV2H7aIVo77nbkAQ0PUL2iurXd1BLhfthpqcTNNdDQbaC8nrBRYupMHfXbtQPXwsGsxJtHlcWhpgNoexBEKIQK0oAmL7Z+Tk0CUm631+fINOc04xAZ3GN5xITeRsxaGtQLvTg0arG11SzfK2jGQTCGnn3lluNxWBxET8NGIKAATFBEweJzy8EDKWtWn3GSxftTtIHF0eHgVn6tErJxFJ8XqoVFzYmb1WDASrUlKYJRB1vv8eY976OwBgYOkxlBS275J2hBAM2rdF/rtXVVHImICz4CQ0Ag9Lt1xwAwbA6HGCP1scdFyrUcQDXG4egkBk1wcAqLOyAACqmnNwB5WV4WxxHQSBhHQFSYwbSv3NP+S3g0tIcgUFxgOU3HMPXTVq3DhaRTxzJvDSS3Sf6At3OD1+n4dWo0afrkk4XdaII4W1GNAzBfG33QzEx8O4+j/QcUL7uoM++wyoqgJuuYVaOQBtazB1KrBxI3D77QCAkxddDkBsI81x1BooKpJn81KKaKhZrbeeDkS8JAIhMoT0OnXzFcN+7iCfJcCLg5urNPR3rKJWSg81ydvSo1Er8N//0nTpW26BVUUX4pHFS8rb9zhBCOR8fyXf/1SKHw+V450vj/ltP3GmHl5ewOBeaeA4DkadOrwIiIv5+LmDHBZWLNbuFBcD110HAuCnHsOgFbzwbmrfVcysdjcuOr4dHq0etoFDkF1fBltNcCxCOEZNfGePXsDAgQCAhLM/t12OfUBQGICfJaATi3u0tc10Ej16lPqlhw0DcnKQes2VMLlsEUVgaN90mI1a/HCwHVxCgfUBoeA4Opvevp3WDNx1F50xd+lCVxUDdQcpRQCgLiGB0PF03NBsOkDMmweuuBiX1hxtm1qBb78N8sMD8AWE77nH/328+CJd8GbzZkCjwaGhNFYht5HOzQWamuT1FPQR3EFCPb0P+XiFJQD4XY9Rp4GXJ5FdI2FEgEhN5MpCuxjl9NA0f0sAaOc0UemzvfdeuDw89Dq1bAFKloDRTf+3od639P1Zv60Q+Sd8kyYpHnBBbzqoG/WasCJgEOsCkJJCfyBaAqxOoB1xOIDZs4Hqarw56TZsuvwmAEDCti3NPPH8sOzej+51JSgePg7uMWOhAoHm2JHgAwsKAADe3n1lEehWU+xXYxCJilqbX1/2IJQi4FDUCIhou9IZsb4ujCXw2mvUnTJoELB0KRWDAQOQfGgfnlyzDH3M4QcJ6hLKQm2jM+J6CudMbS1NnRwyBOjWTd58/Exd+G6MQ4fS91JeTt+DRgNBoKl5ykA54GsmBwDjhojZM9dfDwAYUXrk/GsF9u4FLrsMGDEC2LfPtz0/n6aFXnGFr4mdxMCBwIIF9PfLL0clqAtMXloyIC4QyR3EN9CBSIiLbAkAzfQPClEnAABchphsEKZ/U0WNLz1Uwlc13E7uoEOHaL3M5ZcDffvSVtIK4ZJEwOCJIAIOD3QaFVQqDi9+tF/+PknxgEG9qAgY9Jqw94feKi7mE+AOsjN3UDtBCJ1R7d0L6w2/wxdDroTp0nGw64zoduDHdn1pbs0aAEDF5KuhGj4cAGAqOBp0nPbUSXqp/fLoYAuga11xi4LDW/YW496/bcHj/9oZ/iCFCNgVOfESajEmYGgIUeHpctGBp6gIuPZaYPVqGmM4dAh7xlyJvpU/I3f+byL2iRk/lM4ytx9sw8KxVauof/fmm+VNR4tq8fBL2/DuhmPhnwfQL3tSEgCa200IgiyBAT1ToFZxGNAzBWlJdHDCqFGAWo1eZ+n/8Lxy2v/9b/pYXQ1MnEhn94BvpnrffaGf9/jj1B30+ONotLqg06hgFOs9AtNEtRFEQBAHbxIvrvsgWQIKEZDOGzEuIIuAyW9AVYvJBkKYOFMkS6Dd3EEBn63Lw/tZL5I7yOiSRCD4fdudXqQnm3D9lH6oaXDgjc8Pwe3hcfxMHXK7JCLORAXZqNeEndkbbCFEgLmD2pFXX6UpgqNG4fCDfwU4Dl26JKOw/0hk1JXBfaygfV6XEMR/uRYutQ7OqVdAN3IEACDp5+ABynC6EAI4qPP6An37QlCr0b2ZDCGeF/Dm2sP4xwc/weMVUFFrC+9uOXGC9pbJyPC5g0JkB5maQszUjx6lAcnf/576qufNAxITwXMq/H3i3dg2dgZU+QfoQBZm1ie5hHa0VZaQINDsGb3elwYKmqkEAF/uOC3P0JpDMtlNen9LIDFOj6fuGYeH5ikWlDGbgSFDkFl0DBre0/rByukEPviAuqQ+/JCK2VVXAW++SYvbevakQexQJCbSoPGoUWi0upAYr/e5MwLSRCV3kDuUO0fM6iHSWuCSJaBwB+lb0j9IrhMw+VkC2mx6T3HVoV2M5SEsAUls26VgrLGRTmB69JDTid3hLIFm3EFmowZzpvRDn66J2LK3GO98eQwer4DBoisIoCIQbo0AoyQCYrEYACS5O26x+V+3CJSU0PS69HTg009R0kQ/5JyMOFSPpf7Ups/WNX8em43mbN95J52FrV0L2JsZAI4cQdzpn7EvdwSSuqTBMHwIvCo10s4Ei058cSGqEjMQl5wA6PVwde9Jq4bDDDJNNjeWvvEj1m49hW6ZcejfIxm8QEL3G+J52hO/Xz+A40K6g2AywakzIs4SIoMnP58+Dh3qt7mi1gaHh2DPH5YCDzxAxeLSS6mbJgCtRoUxg7JQ0+iUOyyeF1u2ACdPUvdMis9tI2V7OVxebNx5ukWnCmUZSQzqlSpXCMtcdBHUHjd6VRW1Pk103To6eM6fT9/DV19RQbvjDnpf3XMP9f1HgBCCBqvbf1nJc3AHkSbavlgWgRCWQIv6BzU2wqM3wKvW+s2qDdliskGYJnIVtTakJBj8BmGdVo3keH37WAL/+Q/9Ht99t/zZSjEBGVEEdKIlEBiTc3t4eLwCTAYtNGoV/nTjhdBqVFi7lS48NLh3mnysZEWFWiPAZA8hAi4rKxZrF558kroznnkG6NYNpVV0kMhJj4N3ylQAALfx69DPdTqp//iqq+g/6ppr6Azsrbfo72lp9PHtt/0rOSU++QQAsL3fOKQkGsAZDChL744upYV0YJZoaICxsQ6lyTmIM9GBWcjrj3iXFdai4Awhi92NP734PQ7+XIMxg7Lw3P0T0K97MgDf4jV+FBfTz0BsqWBTNEtTYo1PRkKoCs+DB+ljgAgUlohFYl2TgH/8g+aznzghv+9AxotZQttbkCXkdnmwbc59OLlxR+gDXnuNPt59t9/msmo6u9Tr1Fi3rbBFud62gEKxZrmItuHuX348bJro+m2FWP1VBJfUqlX0UbJiJk0Cvv+eWmRxccCtt8qHfvRNAT7//uegUzjdPNwe3n+B+Z496aNoCUiDcqjAMCfes6pEMagvdlT1ayLXknWGGxrgMsX7vR4AmHKoCIRqIufxCqhpcPi5giTSk41t30WXEOoR0OmA224TNxEqAiHcQXqnXb5OJYFJFd0y43Hz1QPl/VI8APAJaCiXkMlhhVurB4xGal3qdEhwMkug7fn5Zzpg9+sH3EQDwaXVVqhUHO1VMnQAilO6InH3D3SQDOT22+mMbMMGIC8PeOQR4McfgZ07gT//mX7h1q6lX9ihQ30zZoDedB9/DI9Wjz29RsrdNctz+kDvcfqtViX560uSsxEv+hO1FwwGAKgKgq2GHQfLUFlnx1UX98Qjvx8Nk0GL1ER6/pCreSniAQBglyyBgEHPnpiCBEcjPO4AN4r0vi64wG9zobJSmOPktEX89FPwNQAY1i8DZoOmRVlCxes24ZJPXkXyrfNC9/35/HP6mY8d67ertNqKpHg9rhjbE7WNTmzd3/wKYJIlYDxXESgrCBnAFASC9zcex8ebTvitG+13/Rs30kVMxPgPANqt9OhRGrxMozNKp8uL978uwIdfFwTlrEtWX4JZ59toMtGMJ8kS0EgN5ILFkLPQ2SiXqMjskgrGRFq0pkBDA5zGOL/XA4D4JDMs+riQTeSq6u0QiCI9dOtWuZdPerIJXp60bW+vzZtp8sWcOXLXXC9PIAjEXwR0OkCngy6MCEj3itKKnjG+F8YPzcalw7v6/S+k+ylQQHmetpF2mEULjOOA1FTEOZpYsVib8/jj1Jf9xBO09wqAkiorslKo77JbVjx+6jkcGpeDZmMo2bWL+maHD6eFOfn5wFNP0UFnzBhg+XL6hS0oAB5+GDhzBrj4YkAMBOPIEeD4cRwbMBpeoxnx4gy/ugcdiIX9+32vJQ705SnZsgmpHUJFwHgqWAT2F9AA7MwJveU1fVMSqS+1tinEFydABHwzX39LwJGUCo3Aw1GuCPASQt97796yqSxRqFhIBgDNXNHrw4qAVqPCmMFdUNPgwIniyC4h91E6i04rOw08/7z/zn//m1pSd9/tt6i6x8ujut6OnPQ4zJzQCyoVh8++a755ncMZOiYQll69QNLTkVdxIqQ7qLTaiuSSQvQtO4ETobKhVq+mMQ1FLEMmJcU3mwdwsrgBgkCL+wKtjgZRBPwsAYAGh8+cAXg+ojtIJYlAcpJvY04OTS91UHFrtpMoIUBDAxyiCGiVloBegyZTQsgmclI8oI+7jmbtXXopTTooL/cFh9siBZcQ2lzw/vvp34pgu2Qd+bmDACA+HjpXGEvAEWw1qlQcFt00Cg/97kK/Y8Otx0A7iFrhNCu+T6mpiLM3iUkK7dhsMQy/ThE4dIgWCA0bBvz2twCoH91idyMng96wyfF6HOs3kh7/1Ve+5xIC/PGP9PcXX/QtuBGKfv1Q++hf4PrwYzogXXcdTaH86CMAwA+SK0gcrBr7UNPRvVcxUIoiUJvVUx7UOTFNNPGs/4LtvEBw4GQ1MpKNyFaY0j5LoAUiIN7IcUb/Qc+dTGefrhKFu6asjPr4hwzxO5YQgsLSRmQkG+VsCGi19LhDh4Jn7yItLRwjJ2i2FM+pQP76V18VLM/Tak8xZ19JRS2dXWan0Y6UE4bn4GyFBfuOR66CDuwb1CwcB+6ii5DRVA1XiIK+gtO1WPr5k3j2oz+jZt1X/jsJoa4gvR64/npU1NoiulqOnva5UiTRlWgUly5MDBSBXr3o5KekJGIDOZXVCp5TQZOgGIwC0kRlSyDcDNVmA3geDgO9F/WK3kEqFQdrXBJdMCWgDXZ1cSVu2vYurrr9alq8lZBAP5vDh30tpRvOMy6wbRtNVrj8cuDYMRrPGzNG3i19Jn6WAADExUHroK8d2ETO5vCgS305eh+JkIknInXoDRIBpxtxLhtccQoLLDUVRocVHM83v35DO/DrFIHHHqM31VNP0WXjAL94AABwHIemkRfDpdGBbFB8WT/+mLp9Zs8O3Y9GhBcIPtpUgFuf/AZ/t3Wnz8nNpZbH8uUgBgO+yx6G1ARfOwNHfzq4k/2KhU5EEWjq2tO3rX9/CByHzKqzfoPEz8X1sDk8GJ6X4csIASK7gySXUt++APwXUFHiSaEi4C5TZPiECQofLapDg9WF3l2T/LZjxAgqAEdC1EIAGN4vHSaDBnuORq7U1p6m7ox3x/0OnNNJ4w2E0OKw4mLgd78LskykoLD0/509kebYf/ZtsD9diZSb3WIRAGSXUPaJg0H+9rotPyCrsRIagce4v97vv+Tj7t10QLrmGlRBj3ue3YJVXwSnDEscP+2bRQeKQIOVCm1SvM5vuzJNNFIDOY21CQ6dEXqd4n0HFIw1GxOQMoMMceA4QKP2H04c8clQC4JfKwps345Lb5iM6/Z8Cj49nWZHvf463XfkiCJNtJWWQFERrbGYMIG6ma6+mlqnr7/uZzlKg20oS0ArLrsZuLqY3enFLVtXYeIjd/j3ogqB5A4KFAFPDU2+CBQBAIjroLjAr08Edu2i/sVx4/zS7EqraTZE1wxfo7Ps7mk4nDMI3OFDvlWZFi2ivsG//S3sS9Q2OrD09R1YveE4BHF2zg8cRL/kkyYBggDP1GmwawxyPAAAdFkZqI5Pg+bwQXkbKSiAQ2sAn5XtewGTCZb07KBuoj8VVCO9qQq3LLlRtjYAIFVyB4WzBLKy6GwLiuCW0X/Q84q+Ur6s3LcxRFDY4fJixYf7wXF0zQA/LhRNYmXxkwKtRo3umfGoqLWHLMmXMJechkutw2ejrkHFsLE0LvPZZ2EDwoBv8fdsUQRysxMxvF86Dp2qwckI7if7ubqDAEVwuCDIJZT89RcAgJ8GjYfZ1ggyc6a8eLkyILzveBW8vIA9x0JX1AoCwbHTdXIh2KlAS8AawRIA/EUgRL67xmaFXWfy6/wZ1hIINzuV+gYZaBtp5cQEAJyJNGGBSLUCjY3A3LnQN9XjvYtugDP/MM2OGkzdnzhy5PxbR/zhDzTmMnkysGMHbR4o1ugocYWzBOLjoXHYAUKC6gRsTg9SbGIGnfS/DIPPigqICdRQ686dECwCCR3UP+jXJwKPPkofly/3U/6SAEsAALpnxmN/T/EG2biRZrmcOUN9iL0DBjiR3UcrsOC57+TsnHFDs8U1aZtoQG/jRuDdd1H6+LMAfLN0gAbxCtNzoa2qpL1hBAE4eRJlydmIM/vP6Kw9eiPZ3oD60z7Xyf6CKvx2z2cwnzhGsxxEV49eq0acURtsCTid9P0oFluxO71Qcb6bVEJIpz3QhYrIlsDbXxxBea0Nsyf28cuGAEAtASBsXAAAMlJM4AUSvhqaEKRUFqMyOQuEU+GT3/yRivK991IxGDs2yDIBgFIxMyg73ecmmz2peWtAcge1ODAMACNHQlCpkVde4DdY2R1uDN7/LVx6I3Yufg7/G3oluMOHaSqo3U5rA7KzgalTsb+ADoxVdfaQsYXiKgtsDg9G5GUgNdEgt+yWaFYEiorkQG2o7CCt3Qq7zuhfLBVoCTQXE5A6iOpMfkFhCamJnNw/6MEHgZISbJg0D+svm4/4NNGS7NePxu0OHz6/xWWqquj3b+RIYNMmWaxDIVVB60K4g1S8F1reEyIw7PEtEP+f/1C3WxiMYdxBfC0VEW+8wopWFIwxEThftm2jmQDTpgW5cmR3gcIS6J4Vj32SCLz7LhWOtDSfkCjweAX8a+0hPPHWLjjdXtw9ewgevWW03Dv8mLQSlVYL/O53qDZQpVdaAvEmHYrSRXM9Px8oLgbndKIkOUfODJJfr19/AIDjAF38xubwoOJYEaYe2UJn9TYb7YkjZjalJhqCLYFTp6gbRSECNocHRoNWjj9IqDKpCEC5pkB+PnW7iMHKn45XYcOO0+iRFY95V/QP+owweDB9/2EsAQDITGmmKrS6GgaXHXUZ3ZCebMRuTwLI4sX0Cy5Vf4egrMYKjoNfV8qhfdPRKzsROw6WhW2r4WiNO8hshq3vAPSpPIXqSl9abcnG7ejSWInSMZPQr18X/GvibagZMZZaplOn0kHzppvAg0P+Sd/nfLgwOJdeWtlsQG4qeuUkorbR6VcHEjEwDAS4gwJEgBBo7TbYFauBATj3mICyg6g2eCjhU6mL0VFaTuNub70FMnQo3hk6C10UjeOg09F79MgRmA0amA2aoPvD6fJi5ccHcPDnCE0OP/qIxo3mzw9/jIjkIgvlDgJo/6BAEbA6PIh3iFZdRQUVnDD4RMD/sxNq6P/aE8IS6KhOor8uEeB5Gsh99tmgXaXVVpgNGr8vTbfMeJSkdO83yuMAACAASURBVEVjahZt5mW1An/5i9xSQKKyzo5FL2/Duq2F6JYZh+cfmICrx+XKq1ABChEQkQbklABLoCi9J/3jwAHZX1+anC3XCEioBon5x0epf/3gz9WYvm89tF438PTTNDX1p59kwUpNNMLu9PrfRFJQOC9P3mRzeoLSQwFAlUWbyKmqRdPd4aDXN2QIwHGw2t1Y8dF+aNScWCQTophJr6dCkJ9P2zeHQJrphcuxdx2hmUHWnB7o2y0JDVYXqu9+gL6HzEwafA9BWbUV6ckmv5kdx3GYMro7BOIbVAMJFyNpDs+o0dDxHngVQX6v6KLzXDsbA3NTwKs1+OC2J6hVuUOsebj5Zpw4S5fy7N+DuksOnwrOpZdWYxvYM0XOwFLGBXyWQEBMICeHCnFREVQqDhq1Cp7AmIDdDpXAh7cERBHQN2cJiCLQpDUFz6gBCGKqK19wkhbCaTRoWPkaHETtVykMgN43FgtQXIz0ZBOq6+1+mTL//uIIvt51Bqs3RPDFr15NC8HEHk+RiOQOAgCjJ3hNAYfNBbPLBj5FtIDffjvs+cNZAkS0BPjE0JZAs62724E2FQFBELB06VJcf/31mD9/Ps6cOdP8k9qSiRNpSmeAu4DnBZTX2JCTEefnt0xJMMBs0uFgb9GNMXAgzSJQ8OOhcjzwwnc4WdyAy0Z2wwsPXIrcbJ+KS2vSBoqA5O7wswTMOhRmiDM1hQiUKWoEJAxDqZ9Ue4Iec3h/Ea7K/xLe1DTaYvill+jA+PzzwFdfhQ4OB2QGAbROINSApxYrPDU1oggcOULdVeJn+dpnh1DX5MTcy/tH7BqKCy+k1smx0MVSGc1YAtaD9HmuHrno240OkiernTTwfuAALbAJwO70oK7JhZwQxUfS59IYYh0H6bmAL5ujpWjHjwMAGH/aQzcQgswtX8Kp0SNj7rXokmZGYpwO++sEWiGckEBTIfv3x0+iK+iaiX1gNmrlDpRKjp+ug9mgQbfMePnz9hcBN8wGTbAYq9V0IqRoHRHkDvJbCEYxBKSl0Vm56A6Sewc1YwlYNMaQkwKVGGdKXvF3es4lS1CSTV10QYVigwbRRzE47HDxcp2FZIECdLIVth5m926aDSS2QYlEpMAwENoS8NbUQgUCz0UX07qZdevo8qUhCBdUJ2KQnE9O9m1UxgQ6oJNom4rApk2b4Ha78dFHH+HBBx/EM88805anbzWV9XZ4eYKuGf4ZJRzHoXtmPL7oPQEkMxN4+WW5psDjpb15lq/aDY9XwAPXD8Mf546AIWCw4DgO/Xsmo6bB4efHlBaYV4pAglmHysRMuIxmPxEoSckJsgQSRg0DAMSfof7spA/+gziXHaqFC32Vhh98QL+0N9+MbIG6u/xcQgEiIAgEdpfXv2WEiD49BR61Bto6cVaqCApvO1CK7/eXIK9HMn4zqU/Qc/1oJi4gd4oMYwl4jvuymfp2o7Olk2fraYm92Po5kLIaKR4QvLqZ5DMP2VIDvhhJ0GDQDKbLqLsx5RiNm5CDB5FaVYJD/ccgOTOF3hc9UlBd70BNdi5tc7F+PQBg/4kqqFQchvVNx6DcVFTU2v3unQaLC2U1NuT1TIFKxYUUgQarKzgeINGrF3WfWa3QadXB7qAmWiPg0Bn9Z8IqFY1ZyO6gc7EEgocSqTGh2m6j6dqPPCJ3D+0SyhIA/NJEq+rsfhbotLE0XTvkcqXvvQcA8M69Uf7uRcLlCR8TAEKLgNSiW5WeTidiHo/8uoGEswQ48RwkSSECUjtphwWODmgi16YisG/fPlxyySUAgGHDhuHw4egs5t4coYLCEt2z4nG0S3+c3X+CZvaI/PPTfKzdegpdM+LwwgMTMGV0+HqBAT2pkh9T5HVLN6JfYNikA+FUqOzah6aYHaCpomUhYgKG9FTUxqcipbQIZaW1uGzbGrgMJqjuu9d30PDh1PVVVYUJK5cBhASLgEolBwsdLtox0xzCEjAZdWgwJkJfL85sxKAwGTIEb649BL1OjT/NHSEvBRiWZjKE0ptxB+EkrRHQDchDHzEF9WRx5PWgfZlBwZaA5C5ptIa2BBwuL4wGbVBmS3Oo+/RGkzkJ3QrpPW555wMAQPlE39oGA3r6lqlERgYQHw+r3Y2TZ+uR1z0ZZqMWF/Sh944yLiBZldLzM1NMMBs0cpW2IBA0RRIBKS5w+jS0oURAtgRCuHG6dqWttr1eOX00bO66KAKNGqO8gI0SXRexk6haA7z9NmrtXmz48TSAEIKtsATSFS2llRbovGn9wXEh6kwIoa4gsxlvojduf+oblFRZQl+ziEuKCYRzB7kd8PAB71t05WjSUmmaskZDixdDFHjJIhAws1eJloCQFGwJxDubOn9MwGq1Ii7O989Vq9XwRoigr1y5Enl5eX4/kydPbstLAqCoEcgIFoFumfSffrbCd9PsPlKBb3afRa+cRLyw8FL06JIQ8fzyl13hEqprdMKoV/u5XkxiQLa4S2/qatmxA47UDDh0xiARAICarJ5IaaxG/bMvItVWj9LZ8+iMWMkDDwBTpyLjx29x8ckfg91BubnUWoCiWtgY7Pow6TVoMCfB2FDrqxTmOFRl90JdkwujB2aFnGkHccEF1CURxhLQN9MkTHe6EC61DvF9e8Js1CInPQ4/lzREbDUhWQKhRL55S8BzbkFhCY5Dae/BSGusgutMMdT//RQujQ7aGQoRkOJFiqU180/WQCDAiP40ED+4F/WbK+MCxwNEgOM45OYkorSaNhmz2N0QCJAUH8ESAIDCQui1quAuopIlEND5EwCNCwgCUFkJrUYFjZoLPzsVxcSiCx0Y1vXohu/zLsHeBUtxKL4rFv7je5wsbsCE4Tnye5Pp3Zvep0eOyBOFddtO+VmgyQkGDMxNDXYJ7dwJFBbCefVMfHWwGh6vgM+/9y+0DKQ5d5AhRExA3SBZAmm0/cSMGdRiVnYAEPE1kAsQAXmRecX7l0WgY5rItakIxMXFwWbzZWEIggCNJvwXbMGCBSgoKPD72Sz1VW9DpMygrqEsAUkEKqkINFpdWPnxAWg1KvzpxhG+Xu0R6NMtERq1yl8Empx+riCAVlHGm7Q4lSbO1AhBQ05PAMEVvADQ0J2mqfZ543l4VBrE/fnh4BfnOOCVV0B0Otz+3VtoqhCvoaGBugQC0kMBIC6kJaBFozERWreLBsjz84G+ffFzA31On64R4gBKjEY6qztwwL9RnoKMFBOq6x3BtQKEIK7sLMqTspCWQmf1fbsnwe70oqwm/HrQgYViSsyi8IZa2xmgn8m5xgMk6gbRzDLnq6/DXPQz9vUcgT4Dusr7+3RNovdFkW+A33+CxgOG96P+8tycRJgMGr+4wLHTdVCpOLkxIEDbcxACnK5oCp8eKh+sSBONYAm4DOZgCyigpbRep2nWEghcVUwiPt6A565+EP/OvAhLXtsBi82NO64ZjIfmXRiUnQaNhvZSOnoUGYn0fR0+VRtkgY4fmg1CgB0HFfUsq1cDAL4fOBG8QKBRc9iytzhi/yHJHRSqYhiglkBgxbBGFAFp0MYtt9DHEAFiyYoKnNmrxEXmkawQAaU7qLOLwIgRI7B161YAwIEDB9BPMQB1JCVVYvpgiMBh9yxJBJpACMEra/LRYHVh/pUD0CMrsgUgodWo0bdbEorKqDnn8QposLqQkhAcxEww61CQ3F3+uyaT/h4YEwAAZ2/6+eldDuwaMQUZg/uGvoC+feFa+CDSrbUY+N6rdJvoVglMDwXogB+IUbQEANBVrxoagCFDcKqE3rS9c5KCnhOWESNoXnyIBngAkJkcplagqgo6hw3lSV3k3vJ9W+ASKqu2QqPm5BmkEpWKQ6JZJ6dUKiGEiEtLnltmkITrwlEAgLiXXwQA7Oo/zi9pQKdVo0/XRBSWNcHpon1h9hdUIc6oRR8x6K1WcRiYm4ryGhtqGx3weHmcLG5AbnaC3wREGReQXFtBmUESyjRRDRUBv540oiXgNoWw7AIyhAw6dbMxAZveFNIdJFm3pdU2JMXp8NQ94zDzkt7hXW+DBgF2O7KafGmgt1w90M8CvXhINnUJSXEBtxv46CMIGZl425GFlAQ9fj99EDxeAV9sLwp8BRlJ2ILES1psPkRMQCsN4FL78iuvpHGq996jNTkK1CoOep06aGavaWwAz6mgTlZMqjQaCAmJHba6WJuKwNSpU6HT6XDDDTfg6aefxp///Oe2PH2rKa22IiM5dBpbSoIBZoMGZyss+O6nEvx4qBz/396ZR0lR3v3+W1W9r9M9O8wwMCCLCIgiEB1BBYN64hp5EzWaXH018SIqObgcggFxMDHncnwjRnNNvB6PvInBJCY5iYnxeBINCsa8EQUUERCZgWFmYLbel+q6fzxV1dXd1XvNTE338/lH6enpeZ7q7vo9v+37m9tei2vSu2HzMGeqF4mEgEPHB+UTSLonAJAvxqeOZgiipvmpuhb58XQEUWUyAQZdt6nXx0uYHvkeet0NWPz6L4i4nUplUFIKN/Pky7EM/E7x5PnGG+S/CxbInarthXoCQN68QNYKIVFd9XRDi1yjLlcIZTECgiDgRH8ATbV2cOmnSxG3w4wRFSMQifJIJITSwkEAuCWLyRc6GECUM2Jw2coM6YQ502rJ56JrECf6/egbDGHBzPqUtc4Tdej3HTmDw13DiPOJjHCJ0ghk7RGQn5z0BMxGDgmBqGbKiEYgZlcxAmmegMVkyFkdJFgsiBlMMKqEg7wuM2rdFsyfUYf/WndJZnNhOmJy2HXsEFoaHFgytwlXXjgt7TVJSOjjz8+QvNvrrwNnzuDIxVciEBPwlY52rFraBpfdhNfe+TzryTpfn4AllmoEBEGA2Scm5iVPwGAgPQmDg6RSKA21OcPG4SH4LQ4YjamfOcHrhSvkm/jhIJZlsWXLFrz88sv41a9+helZum7HkkAohiFfRDUfAJB4a2ujEydPB/B/f/sRrGYO9399YdYbSjak+O/BYwPJyiB3phFw2U2IcCYkZpLa/ZMecvJSCwcZFi5A0GjBP2Z1oP3SC3L+fdZhx6+uXgMuwZPWeekUnlYeCmSviQ+6xBuPaAQE0RNo8NpUjVRW8lUIedWTw4JouAJiiAwApk12gWUZUiGkwkggikAophoKknDZTQiE45kdoHKjWGmeQN2kOhwT+z7+PXUhps1uzXjOnKnEiH3y+YCsALtwZkPKc6SJVPuPnJaLC9KNQEuDEwaOxdETw7JByxoO8njIBLKjR+Wbc0pISAwHxezOzN+VyitFqQeLObcnkBDHU2aEVUA85Oe/dzm23n0RPCoHogzE5DDz8cf4yQOXYcO3FmeGjUBmPpOQ0Ek5FLSj9nxYzRyuvHAaLCYDvnLRNPhDMbzxT/Uy9ax9AnI4KJwyVCYS5eEIinnDWoUxk0JCP/1pRoLYajJkNIsZfcPwmx2Zf7e2Vhw2X9hEPC2prGYxFXLlAySmNLlkyd7/vHZeZiNLAcxuI1/aj48NqPYISEg30/D5ZF7tEW8rbBaDatWNp7UJ3779WWy/8j7Mm1GX8fN0uhdfin+2X0Aa3557jjyoEg5SKxEFgHCN+DfEE/zgtNkY9kcLzwdILFhAqpKyeAKNWWbJSqM+o1Pb5ccsJgPampw4emI4Y9ITkBwkkytpLd0sRwKp3kDRCqJpNHpt+KSZdE6/e9aXMHuqJ+M5sxVFA3I+YFZ9ynOmT3bDajaIRkBKCqeemo0GFlOanPiiZ0SWDM/qCQDEG1BIR6ToB4meAK9mBMTaftkImAyIxHj1xPzQEHix8zUjwSySt5pMiaJMlGUZVQMAABfObwbDAO/vOQT84Q8ITJ2Of9tbsGrpVPkwddVF02Aycvj9W0dURzxKshGF9gkEwjG4wuJEMKURmDMHWLmSfOc2bkx5qQxPQBBg8g3BZ3FkeE5MXS1MfAy8T72zfTSpeCPQnaMySELKCyya04jLF0/J+rxc1DjNmFRnx6fHBnBarFyoVTEC0uCJ7u8+AuzejS6TJynHnEa9x4ohuwczZjQWdFqtdVvw3CV3QLBYgN5ewGJJuvdIThVTKxEFgIjUCSkIQE0NPgO5ZkXlAwDSwzB7NqmaSGR+ARu86r0CsYPEE2BmpuY+zmr1IBpPoKs3s+wvmRTObrizlYnKA2VKTAx7XBb8fukNeOmiW/CPWR2Y1ebNfI7TguY6Ow4eG8C+w6fR0uCQu6YlOI7F2dO8ONEfwIef9aOuxiqXSSqZPtmNaDwhdxNnzQkAJC8QDMITIqf+FCVR0RPgnSpGoEH0UvqJ12IxcRAEdekJDA2BFz0BtZxA0UydSgbjZFGhlai1crhxaB9u2P4gEA7jzVnLwXEsrrk4GXlwO8xYeUEr+gZDqtPs8ncMpxmBUAwOSTfIm/Y+/+IXwIwZRHbmmWfkhyUvSs7HBIPg4nH4LY6M68WK3dXsoHpn+2hS8UYgV+WIxGWLWvH1y2fh/q8vLLpeXMnsqV4EwnF8eIhUemQLBwHAkNEGXHAB/MGoPHQmnQaPDXd/dT7uvPacgv5+rduK3pomnPnf95MHzjpLltIGFCdflRJRAOBrFSfUBQtw5CQ5+Uwv1hMASF7A708mqBVk6xVgDn+GiMEE67RUQyw1jR06npkXkKqGCvEE0stEQyVKRkhwLANmSht2LlkNb51L1fMDSGgnEI4jHOWxcFaD6nOkvEAowmeWT4pIeQGphDRrOAiQ9Z68g0SlVHkTF4bJ+5pwqBgBj4eU+MpGIIuSaDgMxGKIS0ZAJRxUNCxLuvYPHlQXZ/v0U2D9eqClBbc9/wgWHN+H42ctwK/aL8HFCydnGM7rls8Ay0B1uJBcIlpgs1gwHIcz5EPMapNLrmXq64k2UkMDCcW++ip5DbMBgqDosxAbxXwWZ2ZJrehdSGWoY0nlGwHRE2jJ4Qk4bSbccsXs3F+qAjhbzAtIsgC1OYyALxhFLM4jHOXhtGY/0V114bRM3f4sSH/v8E13EU11caymRD5PgK9XGIH583FEmiOcSyYiGznyAqq9AoIA87HP0eNOlodKyJ3DKpLQkpGfpFL5JeEWr3m6dEQwUl44CEh6NbNVvAAJ5U1dKg1NR8oLpD9fiVR5xCcEsIx6MYGMOAzJO0AUPJXSEQmxqifhUql+Y1lyQxKNQFb9IPE1Yg7JCGh0K5k7l8iOHEmr89+3j4QZt20DEgmE7r4Ha277MdZc/ShGrC55foSS5jo7vjRvEo6eGMZHn6XKO0ieUbbqIOIJJK8ZCQf5EHVlhvwAkD6HP/2JeDI33wy8846sLiCHhEQj4LfYMz0n0QgYh3NP3RsNKtoIJBICvjg1AquZy3pK0xLpyyvFrtWSYdIXdyQQhT8oTvnK4gkUi6wfFBaI7PL69Sk/z5cTQH0deEb8SCxYgMPdQ6h1W+BxlnDtCqgQSukV6OuDIRTASc8k1Neknujaml0wGlh8puYJ9AdgMeV+f+WcgD89JyDNEijDCIhezay2LDcHJD8XBo6RT/zpTG+pgVXUm8luBJI3bZfDnDVmDkA2Au4zxAgoReSEkRHEWAM4FR0mAOREK+YEZP2gdE9ANAJR0QioCgqWgqJzOIVHHiHG4amngBMnYH1mO+yLSJ/Gwpn1KaW5SiQ58d/8LdUjjcTiMBnYzGtoNkMwGGCJhlOGykjhoLg7+/uMRYvIiNlYDLj6atSLswfkhjHZCDgzq6lEI2Aazt0dPxpUrBEYCUTx6PN70N3nx5yptWWFeQqlpcEp32AdVqNqxYTLLiUpybhLIM+Jrghqc80ahnK+sPpNz2qzYMRKTkIj02djYCQsSzcUzbnnkka2LBVCGb0CYtjoZE1zhhEwiDHzoyeH8U/FVLJEQsDJ0wFMqnfkfH8lI5DeK1CqgqiSs6d5YTSwcgewGq2NTkyqs2PJ3OYM7SkJA0dmMDd4bSk3eyU2i1HudcmZFAbkcJDrNGmqSonpj5CpYiZjFuNXX09u8rFYdv0gyQiIvQZmrTwBRXJY5p//JHLcF15Iwi1msvcvL2kDyzL42uWzVF6IMHOKB/Nn1OGDQ/3YvS+ZG4hEefUQFsOAcThgS+sYDo0EYI2FU4Xf1LjiCjLRcHAQs/aSnilZOkKUjPCp5AQkI2D2USOgCYe7hrDuyb/j3wf7cP7showh0KMFyzLyKU4tHwAALkfSE/CNlieQZWBLMBQjTSxZ4rc2swFDNg8ElsVnblK6Or2UUBBA3OqZM4kRUNFWyegVEI3AKU+z6rW789p5MHAstu/cK8f2zwyHEY3xOfM9QDIEl941LIWDihook8aKC6bg5c6rMsQJlbAsg6cfuDTv5/D+ry3ETx+6LGdFjRSay5kUBmRPwNlPbnwRRWiDGR4WdYOy/B0pLHj6dFI/KL1XIM0IjKonIFXdbN2aMihqxQWt+OVjV+btP/jODfNhNLB45jcfyZ+BSIzPLhrodGYkhuO9JDwmpCeF1fjqVwEALR8TLziclhPwWxyZBkg0AvbgSMZEs9Gm4ozA63u+wINP/wP9QyHc/OVZ+P4dSzU7aReCVCaYLTwhrcUXjCqGvmuzPulvqkrtguQE7NbsYmk2iwEvXnwrPn90Gw6fITfaQvMRqpx3HqlEUZnHmtErIDaK+Sa1ZTRcASQkdOuVszHki+CZ33wIQRByCscpyZ8YLt0IMAxTUFLUaOBU96WE49i8N9PpshHI4wnU1AAuF+x9xAgoPQHG50PQZMt6GFCWiUohqgz9INEIhGzE+GV9rWJpbSUHCMkT+PvfSd/K5ZcTqXgFDMMU5MW1Njpxyyry2fnZ7/YBINcj65qdTlijqZ4AL0pGM7V5Gt4Akh+YPBlN+98HBCEzJ2B1wsClfQdTpotRI1Ay7+3vwdOv7IXZyOH7dyzFTatm546bjgJni/XdaklhgMTjWSY9HKSNJ2AycnDaTFk9gUAoljUpDJBww/9MOx/Hr/yqnBQuqTJIQprxLDb0KEnvFUgcIp5AvL0947kS1y6fgbOnefHuRz1469/dOCFVBtXl9gQcVqIflK1EtJycwFgjxb7zhoMAYOpU2E6dBAQhaQR4Hqzfh6CagqiEokzUnK06SCwzDUuegFbhIIYh3sChQ0QSQpry19lZ1stet3w6Zk6pwd//3Y09+3sQiebwBBwOWNK0gxLibGCplDPvHi65BJahAbQOdGcYgbDNlXkQEz2M8ZgzXFFGoK3ZhasvbseT65Zj0Zz8gyVGg7Pba3HTl2dlDmEX4VgGdqsJvqAyHKSdp6I6ZlIkGI5lLQ8FkifiYCSOI91DqHGYy0uo33gj6Vx94YWMkr/0XoHEoUNEhXNKZtetBMcyZKaDicNPX92Hjw6T01muHgGAhGNcdlOGJ6BFTmCsOXdmPf5j5UxceeHU/E9ua4Mh6Icj7E/2CfiJ4SRD5vN4Av39ck4gks0TsBAjoEmfgMQ555DPy49/TCayXXstsHhxWS/JcSzu//p5JCz06w8Riub2BIx8DAmFHpA0B8BQX4ARAGSvZV7XvgwjEHWq5HyU08WoESidplo77rqutI5freBYBjevmp21WgEgMWpSHaStJwAQIxCKxOWeAAmeTyAc5fN6AgDQeyaIvsEQ2lvc5SXUrVaiu97TA7z2WsqPUnoFBAHskcMkKezN/d411dpxxzXnIBCKybryhUhcu+2mUSkRHWsMHItbr5yTMwchI+YFGnz9SU9APMEHC8kJ9PfLfQIZIQrRCAQlI6CVJwAk8wIbN5JT9WOPafKyrY1O3LxqNgZ9ESQSQnYjKJaJcuFkCbPUxGVsKtIIdO9P3tTFxHDYoRJidTjAGwzjMme4oozARMFlN8EXjMlJKi1zFnKFUJo3IPcIZCsPRbIcUJI1LrkySMmdd5L//uxnKQ+n9Ar09oINEPXQ9MogNVYtbcP5YjWOy24q6Pq5HWYEQrGMBiAg2RBVcYgVQg3Dfck+AVEyotCcQD5PIGgmRluTZjEJyQhEo8BNN5EZFRpx/fLpct9JrsQwABiCSQkHg2QEGrJXgaUwfTqijc04p+tAUg9I9ATiav0ZDIOoyzMuctLUCIwDLrsJiYQgJ0W1qg4CoD5rGIXp5Eg/S8pHl5EPkFiwgNRPv/aaLE8sIfcKHEqWh9YVYAQYhsG9X1uIGoc5RXM/F2r6QaFwHFazYczzRmOG7An0JcNBkieQKxykyAlk7RhWyEgD2bWDSkIqE+U44NFHtXtdkLDQfV9fCLOJQ6M3U3ocgNw1bFQYAeMIuW5soeEghkFo6UWoCQ3DdFhU9B0YQNBkBWdRz+fE3DVwhv3UCFQD0slVkjzQOicAqHgCUqNYAeEgqX+rrMogJXfeSTSE0oZvSL0CwX0fAwB6PJMKMgIAqYR69uEVePibudVVJdwqZaKBUqeKTRQkT2CkP1l2KHkCuRLDynCQNDA9/cYkDZk3kRupZtVBANHov+kmYMsWosmjMW1NLvy/jV/Gf16TRY5F8gRCQVluQq7fL6REVCTeQeZQ136whzwwMICAxSGL+mU8v8YDeySAUFB9Ct5oQY3AOCDVrfcNBGEycpp+gbKFg4IFhIOUcwYcVqM88LtsbrqJiMo9/3yKoJxUJho+QEpIT9Y0FRQOUq6x0GvnUikTDYbjlW0EJE9ANRxkzX7tvF4iH5HLEzh9GjCbEWLJZ1mzPgGA5AF+8QtgwwbtXjMNl92UvR9DIR0hzWGw+NNmCRSAIOYFGve9T/49OAif2ZH1WiVqvGAhgD99RvXnowU1AuOAUzQCCUHbpDCQPRwkdcvmqoRRqmlOLzcprMTpBL72NeDYMUAxPlQyMoLYKNZX21K2flM20pVEBUFAKBKDzTxxKoOKpq4OCatVTAynhoPISMgsX39JP0iRE8joGD5xAmhpQZSXNHgq6FaSIiInDh4KDCPBsKT/okBMs2fitKOWNI1Fo2B8PtItnOVaCaKBkXoSxooKeucmDpInAKgPkymHZMNYqifwt//pApAUuVODeYVFBQAAGMZJREFU41g5WaZJUliJSoJY8gSMnx9FxGAGN7l51OLz6Q1jsXgCcV4oq1tY9zAMEq1tqB9RVAcpPIGcydyGBjEcpOIJRKNEqrylJbsQ20QmbaZAKBInQ+DtzhRV3nxYLUbsaz0Hdt8gKXWFpCCa5VqJRoA5M7ZKotQIjAPKahYt8wEAMTBGA5uiH9Td58P7H/didpsnbyJVapwqeoZAPpYsIVUfv/udrFDZaEqg49NdcHQdRU9NE2rzlIeWQ7qSaDCPomqlILRNgSvsgyDe/JMlovbcobT6emBwEGaQm3yKJ9DTQ6RAWlpk45Itzj0hkUdMkuligXCM1O87iiuUMBpYHJgiVjb99rcAsiiIirB1YqhpgIaDKh6lJ6B1OIhhGHhdFgwowkF/+MdRAERfPR9SjLysTmH1hRFvIBYD1q0DbrgBk+e246E//R8YoxF80LagqHxAsaR7AhOxR6AUGDEvYBPlIwr2BMTkMDtwBiYjl+oJiPOHJSPAsUxxE8T0jhgOkobNB4JROMM+RF3FH4wOTz+X/I84Y0BVQVREqjziBsbWE6jsb4BOSTUC2usa1botOHhsADyfQCAcx5vvd6HBY8XSc5ry/m5znQORWGJ0Gu5uvRV46CHgv/8bAMDMno1XGxbizbYl+KKuDavHwAiMpHkCFR0OAsC2k0Htjl6xPFfhCeSM4ysqhKxmLrU6SGkEoonKygcAGeGg8OkhGBJ8bhnpLIw0tWDAVQeveM18FpX5wiK2SUTlwBEaKXHhpVHZ3wCdkpITGBUjYEVCAAZ9Efztf7oQjfG4+uLpBZ3W1t9yPmLxxOjE5r1e4MUXiWLo9dcDc+finR+/jS/EIfKj6QlI+kFDPuIJyOJxlZwYBsCKZaKOfiIpXVROAJD1g7J5ArFDvLaVQXogLRwU6SPhy7wy0ipYLUYcmDIPF+//GwDiCWQLnZmbiRFY3Di2n8kKM+ETA4fVKCviah0OApIVQr0DQfxx1+ewmg348pLCZifbrUbUOEenQgcAqRLauFHuCm1QNOzUe7I072gAyzJw2Uxys1i5Q+YnDGI4SJorUFDHMJChH5TSMawwApFYorKSwkDGiMl4LxmwI3gK7xGQsJoM+HDyXPnfqrMEJOQRk2M7XYwagXGA41g5ITk6ngAxAr9/+wgGRsK4fMkU3YqkKXsRCm0UKxWXwySXiAYj5ctITwhET8BzRjQCw8OImczgOUNBOQH09cFqMqRqByk9gRhfWUlhICMcxPeJJZtF9AhIWM2pRsBvdmRXXJ08mehtWUZ/CqKSCv8G6BeX3QR/KDY6noCL3Ex37+sBywBXd2SXZx5vlK37o20EahxmHD/lQ5xPKGSk9WkcNaOpCTHOCI84cB4jIwhbCtD7UYaDJnGI8wnE+QSZidDdDRgMQEMDovEE3I4K8wTkZrEw6RMoRkY6DYuZwyl3ExKTW8Ce6IbPmj0nAJeLSGgXqk+kERVmwicOUsNYriHzpaKczLV0XvO4qqrmQwoHWc1cSsfyaKCcMCaFgyo9MQyWxWBNPbyDJKSB4WGEzHYYOAZcrryPipKonBfo7ianVpZFNMZXXmLYaoXAsrInwIjicVxD8UbAajYADIPI5auQMJlxxlGbO4fS0gKYxm4IFkCNwLgh3ZC0FI+TUA60uW6Z9torWiINaq+rsY36HGhlmWioWsJBAAa9TagJDAKhEJkvnEs3SEJFPygSjROd/54eoKUFgiAgFk9UXmKYYRC32pJGYEBSEC3RCADo3/gY/rXzDfisLt0ZTX2tpoqYVOeAgWNlrR8tqXVbYLMYMGeqVx53qVcavDbYLAa0NRWgj18msoicPzohB8qUynCtWBp85AgQCuUWj5PweklvR19fqifQ2wvwPMkHiLLcmorH6QTe5oBFnDPMDREjYG4qPkwjGYGgwYyRZpKk13QAjwaUdQx644038Je//AXbtm0DAOzduxdbt24Fx3Ho6OjAPffco8kiK5GbV83CqqVto1KJYzRwePL+5XDaTaN+ui4Xs5HDf627ZFQ8onTc4rUeDkSS1UETaLRkqfjqmgEAiQ8/BIsCykMBIuNcV5fiCYQiceBEaqMYoLGMtE7g7XZY/aeJpzNMFETNzaUbgVA4jqio5Ko3T6Dkb0BnZyd27dqFOXPmyI9t2rQJ27dvR2trK+666y4cOHAAc+fOzfEq1YvNYhzVU2gh07b0QnPd2OQs3HZiBIb8EYUnUPlGYKR+EgCA30uMgN9og7mQG1F9PXDqlOwJRKJ8aqNYvAJ1g0R4mx3WaBdifAKmEdEINNYX/TpJ7aW4rLOkt/BZySbpvPPOw+bNm+V/+/1+RKNRTJkyBQzDoKOjA7t379ZijRSKJrgcmeEgaxV4AsHGyeR/PtoHAPAbC/AEAGIEBgZgZcnNKxSJZ0hGAPo72WpBwu6AmY8iHo7A4h9GjDOAcRR/sJI9gUhcnumgt/BZ3m/AK6+8ghdffDHlsccffxxXXXUV3nvvPfkxv98Ph+Ii2e12dHV15Xzt7du34+mnny52zRRKSdRIieFAFMFIDGYTV1maN1kINhEjwO6XjIClsLi0mBz2xMgEPH8wqm4EdHay1QLBIeao/H7Y/MMI2FyoKSG0alXMaJZmOmTtExgn8hqB1atXY/Xq1XlfyOFwIBBIjmMLBAJwqc3SVLB27VqsXbs25bHu7m6sWLEi79+jUIpFqsgaFsNB1ZAPAIBoYxN4hgV3kugHBUx5FEQlxHr1uqgPAJEhUQsH6e2mpgWCnYQohREf7CEfRmrqUYqurlSCHIrEEZNkt3WWQ9FsNQ6HA0ajEcePH4cgCNi1axcWLVqk1ctTKGXjtJnAMmKJaKVPFVNgspD6dImCEsOA7Al4I0RqYmAkTIwAywJNTbInoLfwhhYIYsOYMDQMWziASJEy0hLyUJ6IMjGsr+ul6bfg0Ucfxfr168HzPDo6OrBgwQItX55CKQuWZeC0E+mIYDiGOq3GZ+oco4FFn6sBDT4ihJZzqpgS0Qi4AsMAaoj4Xnc30NwMGAzyyVZviU5NEI0AurrAQihJRhpIzQnodQBPWUZgyZIlWLJkifzvc889Fzt37ix7URTKaOF2mNE/GEI0nqiacJDZyKHPVQ+IatIhkxXuIjwBh38IQA2GhoNkrOR55wGAfLItqNJogiElgY3dxwEAUXeJRkAZDuIlo6mv66Wv1VAoo4zbbpa7he0aj/bUKybJCIgE8k0VkxBzAtzAGTisRkR7eslQoJYWANBtyaMWMJKc9CliOfma4hVEAWViWJkT0Nf1okaAUlVIZaJAdZSHApIRSDY6FZsTQH8/PC4LDD2iKyEZAZ02P2kB4yZFLXZxIpvgLa3zPiUcpNPrpa/VUCijjFsx0KdqEsNpRiBkshWVE0BfHzxOM6z9ohJpmiegtxi3FrCiJyBLcHuLl5EGALOJA8MQyY1kX4W+rld1fAsoFBGpVwCoDt0ggJw8U8NBeQbKSNTWEv2g/n54nBbY/eIAdNkIVG6fACd6AnXDRH2VqSvNCDAMA4vJgFA4DrOJA8sgt3rrOECNAKWqcCmNQBWFg/qdSSMQNloKO41yHDEE/f3wuMxw+VKNgNQBW4l9AlwNMQLeAJnyxTUULxkhYTVzCEXjYFnAaOR0p+dVHd8CCkXE7ai+cJDZyCFuMCJU2wBjOIgEyxUekqivB3p74XFa4PGLE7bknICoIlqJnoArVdXWWF+8jLSE1WxAIByHgWN16TVVx7eAQhGRROQAMgS8GpDi/59edyvcfBhAEQ1e9fXAJ5/Aa+PglTyBSUSQLqpTGQQtMNSkNoeZmkr3BCxmA84Mh2ExcbpLCgPUCFCqjGr0BKTT597r/hfqPTbgtx8VbgQk6Qg+AK//DEKeOljFyVdRnZY8agGTJnljKWGWgITVbEA4yiMS5WVFVj2hP7NEoYwi7irNCQAkfFO08qcsHeFDre8MfJ7kzbCSVUShEMMMmqywu0uXO5du/L5gVJfXSn8rolBGEYfNBCkvV03VQQC5aRddpigagZruYzDzUQy6k7FxvWrhaII9edP3WRxlfVakw0acF2DU4bWiRoBSVXAsI6uJVk04SPIEYkk542KNgPXjjwAApxVCdLEK7hMAyyJkItpSfqurLKkHq+JzpjcFUYAaAUoV4hKTw9XSMWyWjUBCjuMXmxNg9u4FAPRYkp2zskHR4Y1NCyJmYgSC9tyS+PlQ5gH0mD+pzHePQslBndsCA8dWTThIOsVGUsJBxeUE8MEHAIBukxuCIACAPGhejyEOLZCMQNhRmnichPKwoUevqTqOQhSKgjuvm4czwyHdqTmOFmYNwkHoJZIRvTYvAuE4EZSLV7YnEDXbyH9dpc0SkLCak9daj+W01AhQqo7WRidaG535n1ghcBwLjmVSEsNF9QkoOOOow+BImBiBGA+jgdVdB6xWRCySEdDQE9ChwdTfiigUiuaYjJxYIlpkMlfSDxI54/Bi0EcazqKxhC5valoRE40A7ylNRlrCovNwUOW+gxQKRcZs5EorETUYAC+5CUbdHkSNZgyORAAQ7SA93tS0ImYlZaKJMo2A3nMC1AhQKFWA0cjKOQGWAQxcESEcMSQUa2oGANkTiMQSFZsUBpJGQPCUNktAwmqi4SAKhTLOmAwcKREVT+9FxfHFMlFhMhGOS/EEdHhT04qwm9z8hUmTy3qdlD4BHRpNmhimUKoAs5HDwEgY0VgJIRzRE2CntAKAIidQ2eGgD666BW8xjZg3d15Zr6MMB+mxIk1/K6JQKJpjMrKIxXlEYomSjYBp6hQAwKCPeAKVnhiOe7zYfdaXYLeWd1ZOaRbTodGs3HeQQqHImIwc4ryAcCQOc7G16qIRMLRNgd1iwOBIGDyfAJ8QdHlT0wqj2N1bblMhlY2gUCjjjnSz9odixd+4V64E2tqAZcvgcVkw6IvIA2Uq2wiQ26PdWqYRMCWvkR6vF80JUChVgCQTkSjl9L5sGXDsGADA4+xBd58foUgcgD5j3FrR1uSC1cxhcr0j/5NzwHEsTAYW0XhCl9pB1AhQKFWA8sZfcLewCh4nEd/rGwyW/Vp6Z9XSNqy4oBUGrnxDZzEbEI1HdSkbob8VUSgUzVHerMsJSXhcFgBA7xliBCrZEwCgiQEAkhVCegwHVfY7SKFQAKTefMqZbpXuCejxpqZHZCOgQ6OpvxVRKBTNUd58yvMEiBHoHaBGoBj07AmUlBPw+Xx44IEH4Pf7EYvF8PDDD2PhwoXYu3cvtm7dCo7j0NHRgXvuuUfr9VIolBLQKidQ4xTDQZIR0OHJVo9IRkCP4bOSVvTCCy9g6dKl2LFjB37wgx9gy5YtAIBNmzZh27Zt+OUvf4kPP/wQBw4c0HSxFAqlNEwa5QS8rjQjoMOTrR6xiDMF9JhIL8kT+Na3vgWTicxp5XkeZrMZfr8f0WgUU6aQrsKOjg7s3r0bc+fOzfo627dvx9NPP13KEigUShEo8wDlnN6lnEC/nBPQ38lWj7Q2OGE196FGvH56Iq8ReOWVV/Diiy+mPPb4449j/vz56O/vxwMPPIANGzbA7/fD4UjW09rtdnR1deV87bVr12Lt2rUpj3V3d2PFihXF7IFCoeTBrFE4yGkzgWMZxHkyYtKow7p3PXLLFbNxw6UzdDnSNK8RWL16NVavXp3x+Kefforvfve7ePDBB7F48WL4/X4EAgH554FAAC5XeQOaKRSKNihv1uWEcFiWQY3TjDPDRESuaAmKKoVhGF0aAKDEnMDhw4dx3333Ydu2bVi+fDkAwOFwwGg04vjx4xAEAbt27cKiRYs0XSyFQikNrfoEgGRICKCeQCVQUk5g27ZtiEaj2Lp1KwBiAJ599lk8+uijWL9+PXieR0dHBxYsWKDpYikUSmmk5ATKNAKkQmg443UpE5OSjMCzzz6r+vi5556LnTt3lrUgCoWiPaklouXduJWeAK0OmvhQM06hVAEmjXICQLJMNP11KRMTagQolCpAy3BQSk6AhoMmPPQdpFCqAK06hgGgRuEJ6LH5iVIc1AhQKFWAWSMBOQDwOpNGQI8yCJTioO8ghVIFaCUbASRF5LR4Lcr4Q40AhVIFKE//ZYeDlNVBNDE84aFGgEKpArT0BCwmA2wWSRqZ3kImOvQdpFCqAAPHgmUZANqEcKQKIRoOmvjQGcMUSpVgNrIIRXhNTu9tzS6EIjw40bBQJi7UCFAoVYLJyBEjoEEc/97/WIhonAfDUCMw0aFGgEKpEowGDkZDMixUDnarEXboUxWTUhw0J0ChVAlmI0tj+JQMqCdAoVQJV3xpGvyh6Hgvg6IzqBGgUKqE65ZPH+8lUHQIDQdRKBRKFUONAIVCoVQx1AhQKBRKFUONAIVCoVQx1AhQKBRKFUONAIVCoVQx1AhQKBRKFaO7PgGe5wEAp06dGueVUCgUysRBumdK99BC0Z0R6O/vBwDccsst47wSCoVCmXj09/ejra2t4OczgiAIo7ieogmHw9i/fz/q6+vBcfl1TlasWIE333xzDFY2ftA9VgZ0j5WBXvfI8zz6+/txzjnnwGKx5P8FEd15AhaLBYsWLSrqd1paWkZpNfqB7rEyoHusDPS6x2I8AAmaGKZQKJQqhhoBCoVCqWKoEaBQKJQqhtu8efPm8V5EuSxZsmS8lzDq0D1WBnSPlUEl7VF31UEUCoVCGTtoOIhCoVCqGGoEKBQKpYqhRoBCoVCqGGoEKBQKpYqhRoBCoVCqGGoEKBQKpYrRnXYQAMRiMWzYsAEnTpxANBrF3XffjRkzZuDhhx8GwzA466yzsGnTJrAssWFffPEF1qxZgz/+8Y8AgJMnT2LDhg3geR6CIGDLli1ob28fzy1lUO4e+/v7sX79esRiMdTX1+OHP/whrFbreG4pg3L3KPH+++9j/fr1eOutt8ZjGzkpd49DQ0NYtWoVZs6cCQBYuXIlvvnNb47bftQod4/BYBCbN29Gd3c3YrEYHnnkEcyfP388t5RBuXvcunUrDh48CIB8N10uF3bu3Dlu+ykKQYf8+te/Fjo7OwVBEISBgQFh+fLlwre//W1hz549giAIwiOPPCL89a9/FQRBEF599VXh+uuvFy688EL59x988EHhjTfeEARBEN5++21hzZo1Y7yD/JS7x87OTuHVV18VBEEQnnrqKeGFF14Y2w0UQLl7FARBOHnypPCd73wn43G9UO4e33nnHWHLli1jv/AiKHePTz31lPDcc88JgiAIn3zyify51RNafFYFQRCi0ahw4403CgcPHhy7xZeJLsNBV1xxBe677z753xzH4cCBA1i8eDEAYNmyZXj33XcBAG63Gzt27Ej5/YceegjLly8HQORVzWbzGK28cMrd44YNG3DNNdcgkUigp6cHtbW1Y7f4Ail3j5FIBJs2bYKem9rL3eP+/ftx4MABfOMb38C9996Lvr6+sVt8gZS7x127dsFoNOKOO+7AM888g4svvnjsFl8g5e5RYseOHbjoooswa9as0V+0RujSCNjtdjgcDvj9ftx77724//77IQgCGIaRf+7z+QAAl156KWw2W8rve71eGI1GHD16FE888QTWrFkz5nvIR7l7ZBgGPM/jK1/5Ct577z2cd955Y76HfJS7xy1btuD2229HY2PjmK+9UMrdY3t7O+69917s2LEDK1euRGdn55jvIR/l7nFwcBAjIyN4/vnncdlll+GJJ54Y8z3ko9w9AkA0GsXLL7+MO+64Y0zXXi66NAIA0NPTg9tuuw3XXnstrr76ajkWBwCBQAAulyvn7+/Zswdr1qzBj370I93lAyTK3aPRaMRrr72Gxx57DA899NBoL7ckSt1jb28v/vWvf+EnP/kJbr31VgwPD2PdunVjteyiKOd9XLp0qaxDc/nll+Pjjz8e9fWWQjl7rKmpwWWXXQaA3ED3798/6usthXK/j7t378YFF1wAp9M52kvVFF0agdOnT+P222/HAw88gBtvvBEAcPbZZ+O9994DALz99ts5B8/s2bMHW7duxc9//nPMmzdvTNZcLOXucfPmzdizZw8AckqRTix6opw9NjY24vXXX8dLL72El156CW63G08++eSYrb1Qyn0fN27ciNdffx0AuYnMnTt39BddJOXu8fzzz5eT+u+//z5mzJgx+osuknL3CADvvvsuli1bNupr1RpdCsh1dnbiz3/+c8oJ/nvf+x46OzsRi8XQ3t6Ozs7OlPGTF110Ed555x0AwDXXXINoNIr6+noAwLRp07Bly5ax3UQeyt3jkSNH5Fg5y7L4/ve/j+nTp4/pHvJR7h6VZHt8vCl3j11dXdiwYQMAwGq1orOzEw0NDWO7iTyUu8ehoSFs3LgR/f39MBgMeOKJJ3Q3mUuLz+pdd92FdevWYc6cOWO69nLRpRGgUCgUytigy3AQhUKhUMYGagQoFAqliqFGgEKhUKoYagQoFAqliqFGgEKhUKoYagQoFAqliqFGgEKhUKqY/w/U30mozczvoAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c1769ab70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results_AR = arima.fit(disp=-1)  \n",
    "plt.plot(deaths_per_year.first_difference)\n",
    "plt.plot(results_AR.fittedvalues, color='red')\n",
    "plt.title('RSS: {}'.format(sum(((results_AR.fittedvalues-deaths_per_year.first_difference).dropna(inplace=False)**2))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/statsmodels/tsa/kalmanf/kalmanfilter.py:577: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  if issubdtype(paramsdtype, float):\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c1769a9e8>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c17384550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "deaths_per_year['forecast'] = results.predict(start = 55, end= 66, dynamic= True)  \n",
    "deaths_per_year[['first_difference', 'forecast']].plot(figsize=(12, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c17674630>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c1779ba20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "deaths_per_year['Trend'] = decompostiton.trend\n",
    "deaths_per_year[['Value','Trend']].plot(figsize=(12,8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/statsmodels/base/model.py:496: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  \"Check mle_retvals\", ConvergenceWarning)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Statespace Model Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>                <td>Value</td>             <th>  No. Observations:  </th>    <td>66</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>           <td>SARIMAX(1, 1, 2)x(1, 1, 1, 12)</td> <th>  Log Likelihood     </th> <td>-193.725</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>                   <td>Tue, 27 Feb 2018</td>        <th>  AIC                </th>  <td>399.449</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                       <td>11:08:11</td>            <th>  BIC                </th>  <td>412.587</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sample:</th>                    <td>01-01-2012</td>           <th>  HQIC               </th>  <td>404.641</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th></th>                          <td>- 06-01-2017</td>          <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>               <td>opg</td>              <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>        <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L1</th>    <td>   -0.9999</td> <td>    0.089</td> <td>  -11.250</td> <td> 0.000</td> <td>   -1.174</td> <td>   -0.826</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L1</th>    <td>    0.1413</td> <td>    0.353</td> <td>    0.400</td> <td> 0.689</td> <td>   -0.551</td> <td>    0.834</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L2</th>    <td>   -0.7212</td> <td>    0.427</td> <td>   -1.690</td> <td> 0.091</td> <td>   -1.558</td> <td>    0.115</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.S.L12</th> <td>   -0.1759</td> <td>    0.456</td> <td>   -0.386</td> <td> 0.700</td> <td>   -1.070</td> <td>    0.718</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.S.L12</th> <td>   -0.9714</td> <td>    9.831</td> <td>   -0.099</td> <td> 0.921</td> <td>  -20.239</td> <td>   18.296</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>sigma2</th>   <td>   58.9491</td> <td>  539.804</td> <td>    0.109</td> <td> 0.913</td> <td> -999.047</td> <td> 1116.946</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Ljung-Box (Q):</th>          <td>45.51</td> <th>  Jarque-Bera (JB):  </th> <td>5.27</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Q):</th>                <td>0.25</td>  <th>  Prob(JB):          </th> <td>0.07</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Heteroskedasticity (H):</th> <td>1.89</td>  <th>  Skew:              </th> <td>-0.03</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(H) (two-sided):</th>    <td>0.19</td>  <th>  Kurtosis:          </th> <td>4.54</td> \n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                                 Statespace Model Results                                 \n",
       "==========================================================================================\n",
       "Dep. Variable:                              Value   No. Observations:                   66\n",
       "Model:             SARIMAX(1, 1, 2)x(1, 1, 1, 12)   Log Likelihood                -193.725\n",
       "Date:                            Tue, 27 Feb 2018   AIC                            399.449\n",
       "Time:                                    11:08:11   BIC                            412.587\n",
       "Sample:                                01-01-2012   HQIC                           404.641\n",
       "                                     - 06-01-2017                                         \n",
       "Covariance Type:                              opg                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "ar.L1         -0.9999      0.089    -11.250      0.000      -1.174      -0.826\n",
       "ma.L1          0.1413      0.353      0.400      0.689      -0.551       0.834\n",
       "ma.L2         -0.7212      0.427     -1.690      0.091      -1.558       0.115\n",
       "ar.S.L12      -0.1759      0.456     -0.386      0.700      -1.070       0.718\n",
       "ma.S.L12      -0.9714      9.831     -0.099      0.921     -20.239      18.296\n",
       "sigma2        58.9491    539.804      0.109      0.913    -999.047    1116.946\n",
       "===================================================================================\n",
       "Ljung-Box (Q):                       45.51   Jarque-Bera (JB):                 5.27\n",
       "Prob(Q):                              0.25   Prob(JB):                         0.07\n",
       "Heteroskedasticity (H):               1.89   Skew:                            -0.03\n",
       "Prob(H) (two-sided):                  0.19   Kurtosis:                         4.54\n",
       "===================================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
       "\"\"\""
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mod = sm.tsa.statespace.SARIMAX(deaths_per_year.Value, trend='n', order=(1,1,2), seasonal_order=(1,1,1,12))\n",
    "seasonal_results = mod.fit()\n",
    "seasonal_results.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c1767f710>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fd840f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "deaths_per_year['forecast_seasonal'] = seasonal_results.predict(start = 55, end= 66, dynamic= True)  \n",
    "deaths_per_year[['Value', 'forecast_seasonal']].plot(figsize=(12, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "import dateutil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "start = datetime.datetime.strptime(\"2017-06-01\", \"%Y-%m-%d\")\n",
    "date_list = [start + dateutil.relativedelta.relativedelta(months=x) for x in range(0,12)]\n",
    "future = pd.DataFrame(index=date_list, columns= deaths_per_year.columns)\n",
    "deaths_per_year = pd.concat([deaths_per_year, future])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Value</th>\n",
       "      <th>first_difference</th>\n",
       "      <th>seasonal_difference</th>\n",
       "      <th>seasonal_first_difference</th>\n",
       "      <th>forecast</th>\n",
       "      <th>Trend</th>\n",
       "      <th>forecast_seasonal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2012-01-01</th>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>31.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-02-01</th>\n",
       "      <td>2012-02-01</td>\n",
       "      <td>27.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-03-01</th>\n",
       "      <td>2012-03-01</td>\n",
       "      <td>24.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-04-01</th>\n",
       "      <td>2012-04-01</td>\n",
       "      <td>30.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-05-01</th>\n",
       "      <td>2012-05-01</td>\n",
       "      <td>28.0</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-06-01</th>\n",
       "      <td>2012-06-01</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-07-01</th>\n",
       "      <td>2012-07-01</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.750000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-08-01</th>\n",
       "      <td>2012-08-01</td>\n",
       "      <td>31.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>30.375000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-09-01</th>\n",
       "      <td>2012-09-01</td>\n",
       "      <td>27.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>31.583333</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-01</th>\n",
       "      <td>2012-10-01</td>\n",
       "      <td>36.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.458333</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-11-01</th>\n",
       "      <td>2012-11-01</td>\n",
       "      <td>27.0</td>\n",
       "      <td>-9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>32.541667</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-01</th>\n",
       "      <td>2012-12-01</td>\n",
       "      <td>37.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33.166667</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>35.0</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.166667</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-02-01</th>\n",
       "      <td>2013-02-01</td>\n",
       "      <td>38.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.750000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-03-01</th>\n",
       "      <td>2013-03-01</td>\n",
       "      <td>42.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.500000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-04-01</th>\n",
       "      <td>2013-04-01</td>\n",
       "      <td>33.0</td>\n",
       "      <td>-9.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-15.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.500000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-05-01</th>\n",
       "      <td>2013-05-01</td>\n",
       "      <td>27.0</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>38.125000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-06-01</th>\n",
       "      <td>2013-06-01</td>\n",
       "      <td>44.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40.041667</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>2013-07-01</td>\n",
       "      <td>37.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>41.333333</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-08-01</th>\n",
       "      <td>2013-08-01</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.333333</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-09-01</th>\n",
       "      <td>2013-09-01</td>\n",
       "      <td>39.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.041667</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-10-01</th>\n",
       "      <td>2013-10-01</td>\n",
       "      <td>48.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.625000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-11-01</th>\n",
       "      <td>2013-11-01</td>\n",
       "      <td>54.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44.791667</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-01</th>\n",
       "      <td>2013-12-01</td>\n",
       "      <td>56.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.708333</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-01</th>\n",
       "      <td>2014-01-01</td>\n",
       "      <td>47.0</td>\n",
       "      <td>-9.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.625000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-02-01</th>\n",
       "      <td>2014-02-01</td>\n",
       "      <td>50.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.625000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-03-01</th>\n",
       "      <td>2014-03-01</td>\n",
       "      <td>47.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46.125000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-01</th>\n",
       "      <td>2014-04-01</td>\n",
       "      <td>42.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46.666667</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-01</th>\n",
       "      <td>2014-05-01</td>\n",
       "      <td>46.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46.791667</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-06-01</th>\n",
       "      <td>2014-06-01</td>\n",
       "      <td>47.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-16.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>46.583333</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>70.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>70.833333</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02-01</th>\n",
       "      <td>2016-02-01</td>\n",
       "      <td>69.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>71.875000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-01</th>\n",
       "      <td>2016-03-01</td>\n",
       "      <td>69.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>73.250000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04-01</th>\n",
       "      <td>2016-04-01</td>\n",
       "      <td>79.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>72.833333</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-01</th>\n",
       "      <td>2016-05-01</td>\n",
       "      <td>78.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>73.041667</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-01</th>\n",
       "      <td>2016-06-01</td>\n",
       "      <td>79.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>-11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>75.208333</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-07-01</th>\n",
       "      <td>2016-07-01</td>\n",
       "      <td>76.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-18.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>77.083333</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-08-01</th>\n",
       "      <td>2016-08-01</td>\n",
       "      <td>76.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1.829033</td>\n",
       "      <td>78.583333</td>\n",
       "      <td>72.551325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-09-01</th>\n",
       "      <td>2016-09-01</td>\n",
       "      <td>73.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>-17.0</td>\n",
       "      <td>1.010259</td>\n",
       "      <td>80.583333</td>\n",
       "      <td>77.329130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-10-01</th>\n",
       "      <td>2016-10-01</td>\n",
       "      <td>68.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>-18.0</td>\n",
       "      <td>-26.0</td>\n",
       "      <td>1.010297</td>\n",
       "      <td>81.666667</td>\n",
       "      <td>84.567971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-01</th>\n",
       "      <td>2016-11-01</td>\n",
       "      <td>99.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>1.010333</td>\n",
       "      <td>82.416667</td>\n",
       "      <td>84.686482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-01</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>81.0</td>\n",
       "      <td>-18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.010366</td>\n",
       "      <td>83.750000</td>\n",
       "      <td>84.185082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-01</th>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>86.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>-13.0</td>\n",
       "      <td>1.010397</td>\n",
       "      <td>NaN</td>\n",
       "      <td>85.158805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-02-01</th>\n",
       "      <td>2017-02-01</td>\n",
       "      <td>89.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.010426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>83.555837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-01</th>\n",
       "      <td>2017-03-01</td>\n",
       "      <td>97.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.010453</td>\n",
       "      <td>NaN</td>\n",
       "      <td>85.103071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-01</th>\n",
       "      <td>2017-04-01</td>\n",
       "      <td>77.0</td>\n",
       "      <td>-20.0</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>-30.0</td>\n",
       "      <td>1.010478</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81.351968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-01</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>98.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1.010501</td>\n",
       "      <td>NaN</td>\n",
       "      <td>82.017485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-06-01</th>\n",
       "      <td>2017-06-01</td>\n",
       "      <td>91.0</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>1.010523</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86.957273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-06-01</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-01</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-01</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-01</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-01</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-01</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-01</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-01</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-01</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-04-01</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-01</th>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>78 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Date  Value  first_difference  seasonal_difference  \\\n",
       "2012-01-01 2012-01-01   31.0               NaN                  NaN   \n",
       "2012-02-01 2012-02-01   27.0              -4.0                  NaN   \n",
       "2012-03-01 2012-03-01   24.0              -3.0                  NaN   \n",
       "2012-04-01 2012-04-01   30.0               6.0                  NaN   \n",
       "2012-05-01 2012-05-01   28.0              -2.0                  NaN   \n",
       "2012-06-01 2012-06-01   28.0               0.0                  NaN   \n",
       "2012-07-01 2012-07-01   29.0               1.0                  NaN   \n",
       "2012-08-01 2012-08-01   31.0               2.0                  NaN   \n",
       "2012-09-01 2012-09-01   27.0              -4.0                  NaN   \n",
       "2012-10-01 2012-10-01   36.0               9.0                  NaN   \n",
       "2012-11-01 2012-11-01   27.0              -9.0                  NaN   \n",
       "2012-12-01 2012-12-01   37.0              10.0                  NaN   \n",
       "2013-01-01 2013-01-01   35.0              -2.0                  4.0   \n",
       "2013-02-01 2013-02-01   38.0               3.0                 11.0   \n",
       "2013-03-01 2013-03-01   42.0               4.0                 18.0   \n",
       "2013-04-01 2013-04-01   33.0              -9.0                  3.0   \n",
       "2013-05-01 2013-05-01   27.0              -6.0                 -1.0   \n",
       "2013-06-01 2013-06-01   44.0              17.0                 16.0   \n",
       "2013-07-01 2013-07-01   37.0              -7.0                  8.0   \n",
       "2013-08-01 2013-08-01   37.0               0.0                  6.0   \n",
       "2013-09-01 2013-09-01   39.0               2.0                 12.0   \n",
       "2013-10-01 2013-10-01   48.0               9.0                 12.0   \n",
       "2013-11-01 2013-11-01   54.0               6.0                 27.0   \n",
       "2013-12-01 2013-12-01   56.0               2.0                 19.0   \n",
       "2014-01-01 2014-01-01   47.0              -9.0                 12.0   \n",
       "2014-02-01 2014-02-01   50.0               3.0                 12.0   \n",
       "2014-03-01 2014-03-01   47.0              -3.0                  5.0   \n",
       "2014-04-01 2014-04-01   42.0              -5.0                  9.0   \n",
       "2014-05-01 2014-05-01   46.0               4.0                 19.0   \n",
       "2014-06-01 2014-06-01   47.0               1.0                  3.0   \n",
       "...               ...    ...               ...                  ...   \n",
       "2016-01-01 2016-01-01   70.0              18.0                 19.0   \n",
       "2016-02-01 2016-02-01   69.0              -1.0                 16.0   \n",
       "2016-03-01 2016-03-01   69.0               0.0                 19.0   \n",
       "2016-04-01 2016-04-01   79.0              10.0                 26.0   \n",
       "2016-05-01 2016-05-01   78.0              -1.0                 29.0   \n",
       "2016-06-01 2016-06-01   79.0               1.0                 18.0   \n",
       "2016-07-01 2016-07-01   76.0              -3.0                  0.0   \n",
       "2016-08-01 2016-08-01   76.0               0.0                 25.0   \n",
       "2016-09-01 2016-09-01   73.0              -3.0                  8.0   \n",
       "2016-10-01 2016-10-01   68.0              -5.0                -18.0   \n",
       "2016-11-01 2016-11-01   99.0              31.0                 23.0   \n",
       "2016-12-01 2016-12-01   81.0             -18.0                 29.0   \n",
       "2017-01-01 2017-01-01   86.0               5.0                 16.0   \n",
       "2017-02-01 2017-02-01   89.0               3.0                 20.0   \n",
       "2017-03-01 2017-03-01   97.0               8.0                 28.0   \n",
       "2017-04-01 2017-04-01   77.0             -20.0                 -2.0   \n",
       "2017-05-01 2017-05-01   98.0              21.0                 20.0   \n",
       "2017-06-01 2017-06-01   91.0              -7.0                 12.0   \n",
       "2017-06-01        NaT    NaN               NaN                  NaN   \n",
       "2017-07-01        NaT    NaN               NaN                  NaN   \n",
       "2017-08-01        NaT    NaN               NaN                  NaN   \n",
       "2017-09-01        NaT    NaN               NaN                  NaN   \n",
       "2017-10-01        NaT    NaN               NaN                  NaN   \n",
       "2017-11-01        NaT    NaN               NaN                  NaN   \n",
       "2017-12-01        NaT    NaN               NaN                  NaN   \n",
       "2018-01-01        NaT    NaN               NaN                  NaN   \n",
       "2018-02-01        NaT    NaN               NaN                  NaN   \n",
       "2018-03-01        NaT    NaN               NaN                  NaN   \n",
       "2018-04-01        NaT    NaN               NaN                  NaN   \n",
       "2018-05-01        NaT    NaN               NaN                  NaN   \n",
       "\n",
       "            seasonal_first_difference  forecast      Trend  forecast_seasonal  \n",
       "2012-01-01                        NaN       NaN        NaN                NaN  \n",
       "2012-02-01                        NaN       NaN        NaN                NaN  \n",
       "2012-03-01                        NaN       NaN        NaN                NaN  \n",
       "2012-04-01                        NaN       NaN        NaN                NaN  \n",
       "2012-05-01                        NaN       NaN        NaN                NaN  \n",
       "2012-06-01                        NaN       NaN        NaN                NaN  \n",
       "2012-07-01                        NaN       NaN  29.750000                NaN  \n",
       "2012-08-01                        NaN       NaN  30.375000                NaN  \n",
       "2012-09-01                        NaN       NaN  31.583333                NaN  \n",
       "2012-10-01                        NaN       NaN  32.458333                NaN  \n",
       "2012-11-01                        NaN       NaN  32.541667                NaN  \n",
       "2012-12-01                        NaN       NaN  33.166667                NaN  \n",
       "2013-01-01                        NaN       NaN  34.166667                NaN  \n",
       "2013-02-01                        7.0       NaN  34.750000                NaN  \n",
       "2013-03-01                        7.0       NaN  35.500000                NaN  \n",
       "2013-04-01                      -15.0       NaN  36.500000                NaN  \n",
       "2013-05-01                       -4.0       NaN  38.125000                NaN  \n",
       "2013-06-01                       17.0       NaN  40.041667                NaN  \n",
       "2013-07-01                       -8.0       NaN  41.333333                NaN  \n",
       "2013-08-01                       -2.0       NaN  42.333333                NaN  \n",
       "2013-09-01                        6.0       NaN  43.041667                NaN  \n",
       "2013-10-01                        0.0       NaN  43.625000                NaN  \n",
       "2013-11-01                       15.0       NaN  44.791667                NaN  \n",
       "2013-12-01                       -8.0       NaN  45.708333                NaN  \n",
       "2014-01-01                       -7.0       NaN  45.625000                NaN  \n",
       "2014-02-01                        0.0       NaN  45.625000                NaN  \n",
       "2014-03-01                       -7.0       NaN  46.125000                NaN  \n",
       "2014-04-01                        4.0       NaN  46.666667                NaN  \n",
       "2014-05-01                       10.0       NaN  46.791667                NaN  \n",
       "2014-06-01                      -16.0       NaN  46.583333                NaN  \n",
       "...                               ...       ...        ...                ...  \n",
       "2016-01-01                       21.0       NaN  70.833333                NaN  \n",
       "2016-02-01                       -3.0       NaN  71.875000                NaN  \n",
       "2016-03-01                        3.0       NaN  73.250000                NaN  \n",
       "2016-04-01                        7.0       NaN  72.833333                NaN  \n",
       "2016-05-01                        3.0       NaN  73.041667                NaN  \n",
       "2016-06-01                      -11.0       NaN  75.208333                NaN  \n",
       "2016-07-01                      -18.0       NaN  77.083333                NaN  \n",
       "2016-08-01                       25.0  1.829033  78.583333          72.551325  \n",
       "2016-09-01                      -17.0  1.010259  80.583333          77.329130  \n",
       "2016-10-01                      -26.0  1.010297  81.666667          84.567971  \n",
       "2016-11-01                       41.0  1.010333  82.416667          84.686482  \n",
       "2016-12-01                        6.0  1.010366  83.750000          84.185082  \n",
       "2017-01-01                      -13.0  1.010397        NaN          85.158805  \n",
       "2017-02-01                        4.0  1.010426        NaN          83.555837  \n",
       "2017-03-01                        8.0  1.010453        NaN          85.103071  \n",
       "2017-04-01                      -30.0  1.010478        NaN          81.351968  \n",
       "2017-05-01                       22.0  1.010501        NaN          82.017485  \n",
       "2017-06-01                       -8.0  1.010523        NaN          86.957273  \n",
       "2017-06-01                        NaN       NaN        NaN                NaN  \n",
       "2017-07-01                        NaN       NaN        NaN                NaN  \n",
       "2017-08-01                        NaN       NaN        NaN                NaN  \n",
       "2017-09-01                        NaN       NaN        NaN                NaN  \n",
       "2017-10-01                        NaN       NaN        NaN                NaN  \n",
       "2017-11-01                        NaN       NaN        NaN                NaN  \n",
       "2017-12-01                        NaN       NaN        NaN                NaN  \n",
       "2018-01-01                        NaN       NaN        NaN                NaN  \n",
       "2018-02-01                        NaN       NaN        NaN                NaN  \n",
       "2018-03-01                        NaN       NaN        NaN                NaN  \n",
       "2018-04-01                        NaN       NaN        NaN                NaN  \n",
       "2018-05-01                        NaN       NaN        NaN                NaN  \n",
       "\n",
       "[78 rows x 8 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deaths_per_year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10fc67128>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fe47f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "deaths_per_year['forecast_seasonal'] = seasonal_results.predict(start = 55, end= 66, dynamic= True)  \n",
    "deaths_per_year[['Value', 'forecast_seasonal']].plot(figsize=(12, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "deaths_per_year=deaths_per_year[~deaths_per_year.index.duplicated(keep='first')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fc67a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c173f7080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12, 8))\n",
    "deaths_per_year['Forecast'] = seasonal_results.predict(start = 65, end= 77, dynamic= True)  \n",
    "deaths_per_year[['Value', 'Forecast']].plot(figsize=(12, 8),grid=1)\n",
    "plt.title('Actual and Forecasted Deaths per Month')\n",
    "plt.savefig('death_forecast.png')\n",
    "plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importing Ployly libraries\n",
    "import plotly.plotly as py\n",
    "import plotly.graph_objs as go"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "trace_actual = go.Scatter(\n",
    "    x = deaths_per_year.index,\n",
    "    y = deaths_per_year['Value'],\n",
    "    name = 'Actual Deaths'\n",
    "    \n",
    ")\n",
    "trace_predicted = go.Scatter(\n",
    "    x = deaths_per_year.index,\n",
    "    y = deaths_per_year['Forecast'],\n",
    "    name ='Predicted Deaths'\n",
    ")\n",
    "\n",
    "# creating the actual and predicted scatter plot traces "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~drissguessous/2.embed\" height=\"525px\" width=\"100%\"></iframe>"
      ],
      "text/plain": [
       "<plotly.tools.PlotlyDisplay object>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ploting dot using plotly's interactive scatter plots \n",
    "data1=[trace_actual,trace_predicted]\n",
    "\n",
    "layout = dict(title = 'Opioid Deaths per Month in Connecticut',\n",
    "              xaxis = dict(title = 'Month'),\n",
    "              yaxis = dict(title = 'Number of Deaths'),\n",
    "              )\n",
    "\n",
    "fig = dict(data=data1, layout=layout)\n",
    "py.iplot(fig, filename='forecast')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "# using counter to tally deaths per county and using pivot tables to generate important statistics \n",
    "from collections import Counter\n",
    "county_death_numbers = dict(Counter(data.New_Death_Counties).most_common(8))\n",
    "county_mean_age = dict(pd.pivot_table(data,index='New_Death_Counties',aggfunc='mean').Age)\n",
    "county_sex_percentage = dict(pd.pivot_table(data,index='New_Death_Counties',aggfunc='mean').Sex)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# creating scaling constnat for the cholorpleth map \n",
    "death_scaling = [value for key,value in county_death_numbers.items()]\n",
    "death_scaling = sum(death_scaling)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "# importing bokeh libraries and setting up CT county workspace\n",
    "from bokeh.io import show\n",
    "from bokeh.models import (\n",
    "    ColumnDataSource,\n",
    "    HoverTool,\n",
    "    LogColorMapper\n",
    ")\n",
    "from bokeh.palettes import Reds6 as palette\n",
    "from bokeh.plotting import figure, output_file\n",
    "\n",
    "from bokeh.sampledata.us_counties import data as counties\n",
    "from bokeh.sampledata.unemployment import data as unemployment\n",
    "\n",
    "palette.reverse()\n",
    "\n",
    "counties = {\n",
    "    code: county for code, county in counties.items() if county[\"state\"] == \"ct\"\n",
    "}\n",
    "\n",
    "county_xs = [county[\"lons\"] for county in counties.values()]\n",
    "county_ys = [county[\"lats\"] for county in counties.values()]\n",
    "\n",
    "county_names = [county['name'] for county in counties.values()]\n",
    "county_rates = [county_death_numbers[county]/death_scaling for county in county_names]\n",
    "county_unemployment_rate = [unemployment[county_id] for county_id in counties]\n",
    "color_mapper = LogColorMapper(palette=palette)\n",
    "\n",
    "\n",
    "county_names = [county['name'] for county in counties.values()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "# creating properly ordered lists to use on the cholorpleth map\n",
    "cnty_mean_age=[]\n",
    "cnty_sex_male=[]\n",
    "cnty_sex_female=[]\n",
    "cnty_death_numb=[]\n",
    "for county in county_names:\n",
    "    cnty_mean_age.append(county_mean_age[county])\n",
    "    cnty_sex_female.append(county_sex_percentage[county]*100)\n",
    "    cnty_sex_male.append((1-county_sex_percentage[county])*100)\n",
    "    cnty_death_numb.append(county_death_numbers[county])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "# creating bokeh interactive cholorpleth map \n",
    "source = ColumnDataSource(data=dict(\n",
    "    x=county_xs,\n",
    "    y=county_ys,\n",
    "    name=county_names,\n",
    "    rate=county_rates,\n",
    "    unemployment_rate =county_unemployment_rate,\n",
    "    mean_age =cnty_mean_age,\n",
    "    sex_male = cnty_sex_male,\n",
    "    sex_female = cnty_sex_female,\n",
    "    cnty_death = cnty_death_numb\n",
    "    \n",
    "))\n",
    "\n",
    "TOOLS = \"pan,wheel_zoom,reset,hover,save\"\n",
    "\n",
    "\n",
    "p = figure(\n",
    "    title=\"Connecticut Opioid Deaths\", tools=TOOLS,\n",
    "    x_axis_location=None, y_axis_location=None\n",
    ")\n",
    "p.grid.grid_line_color = None\n",
    "p.patches('x', 'y', source=source,\n",
    "          fill_color={'field': 'rate', 'transform': color_mapper},\n",
    "          fill_alpha=0.8, line_color=\"black\", line_width=0.3)\n",
    "\n",
    "\n",
    "hover = p.select_one(HoverTool)\n",
    "hover.point_policy = \"follow_mouse\"\n",
    "hover.tooltips = [\n",
    "    (\"County Name\", \"@name\"),\n",
    "    (\"Total Deaths\", \"@cnty_death\"),\n",
    "    (\"Mean Age\",\"@mean_age\"),\n",
    "    (\"Percentage Male\",\"@sex_male%\"),\n",
    "    (\"Percentage Female\", \"@sex_female%\"),\n",
    "    (\"Unemployment Rate\",'@unemployment_rate%'),\n",
    "    (\"(Long, Lat)\", \"($x, $y)\"),\n",
    "    \n",
    "]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "# importingt libraries and saving generated map to a html file \n",
    "from bokeh.resources import CDN\n",
    "from bokeh.embed import file_html\n",
    "\n",
    "html = file_html(p, CDN, \"my plot\")\n",
    "html_file = open('ct_plot','w')\n",
    "html_file.write(html)\n",
    "html_file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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