cv19_daily.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Covid-19 Dashboard\n",
    "---\n",
    "\n",
    "Analysis of Covid-19 cases based on data reported on the European CDC website. The data is updated once daily and can differ from other sources because the reporting times for each country is different. E.g. the UK figures are a day late.\n",
    "\n",
    "\n",
    "Quick link to the [Dashboard](#dashboard)\n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "**Modification history:**\n",
    "- New ECDC file format supported\n",
    "- Generic chart() function\n",
    "- Metrics for cumulatives cases/deaths per million of population\n",
    "- 3-day moving averages computed to smoothen fluctuations in daily cases/deaths\n",
    "- Fatality7 metric computed on moving average stats instead of cumulative ones\n",
    "- rpt_daily_stats() modified. Added a filter which defaults to only include countries when cum_deaths > 100\n",
    "- Excel date format is a bit flaky about day-first vs. month-first - dates now generated using other fields\n",
    "- Added consolidation at continent level\n",
    "- Use dataframe styles for output; removed rounding\n",
    "\n",
    "---\n",
    "\n",
    "Chandranath Gunjal, 2020 (github.com/cdragun)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code <a id='code_section'></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import IPython.display as ipd\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline\n",
    "sns.set(style='whitegrid', context='notebook', palette='muted')\n",
    "\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.precision', 10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fetch file and data cleaning\n",
    "\n",
    "def fetch_ECDC_file(url1, url2):\n",
    "    \"\"\"Fetch file from ECDC website. Returns requests.response\"\"\"    \n",
    "    # format can be .xlsx or .xls - try both\n",
    "    r = requests.get(url1, allow_redirects=True)\n",
    "    if r.ok:\n",
    "        return r\n",
    "\n",
    "    r = requests.get(url2, allow_redirects=True)\n",
    "    return r\n",
    "\n",
    "\n",
    "def load_data(asof, local_csv, url1, url2):\n",
    "    \"\"\"Read local csv or fetch from ECDC website\"\"\"\n",
    "    try:\n",
    "        # read local\n",
    "        df = pd.read_csv(local_csv, parse_dates=[0], na_filter=False, index_col=False)\n",
    "\n",
    "    except:\n",
    "        # fetch data\n",
    "        response = fetch_ECDC_file(url1, url2)\n",
    "        if not response.ok:\n",
    "            response.raise_for_status()\n",
    "\n",
    "        # load into data frame using the response\n",
    "        df = cleanse_ECDC_data(pd.read_excel(response.content, parse_dates=[0], na_filter=False))\n",
    "\n",
    "        # save locally\n",
    "        df.to_csv(local_csv, index=False)\n",
    "    return df\n",
    "\n",
    "\n",
    "def fix_missing_numeric(df, col, fillval=0):\n",
    "    \"\"\"Fill blanks and NAs with zeroes\"\"\"\n",
    "    m = df[col].eq('')\n",
    "    df.loc[m, col] = fillval\n",
    "    df[col] = df[col].fillna(fillval)\n",
    "    return\n",
    "    \n",
    "    \n",
    "def cleanse_ECDC_data(df):\n",
    "    \"\"\"Cleanse and reformat ECDC data\"\"\"\n",
    "    # work on a copy\n",
    "    ndf = df.copy()\n",
    "    \n",
    "    # rename columns\n",
    "    rv = {'countriesandterritories': 'country', 'popdata2019': 'population',\n",
    "          'continentexp': 'continent', 'popdata2018': 'population'}\n",
    "    c = [rv[k] if k in rv else k for k in (i.lower() for i in ndf.columns)]\n",
    "    ndf.columns = c\n",
    "    \n",
    "    ndf['date'] = pd.to_datetime({'year': ndf['year'], 'month': ndf['month'], 'day': ndf['day']})\n",
    "    needed_cols = ['date', 'country', 'geoid', 'cases', 'deaths', 'population', 'continent']\n",
    "    ndf = pd.DataFrame(ndf, columns=needed_cols)\n",
    "\n",
    "    # correct data for known issues\n",
    "    fix_missing_numeric(ndf, 'population', 0)\n",
    "    fix_missing_numeric(ndf, 'cases', 0)\n",
    "    fix_missing_numeric(ndf, 'deaths', 0)\n",
    "   \n",
    "    # sort by country and date\n",
    "    ndf.sort_values(by=['geoid', 'date'], ascending=[True, True],\n",
    "                    axis=0, inplace=True, ignore_index=True)\n",
    "    \n",
    "    # append global totals\n",
    "    ndf = ndf.append(compute_global_totals(ndf, 'W_'), ignore_index=True)\n",
    "\n",
    "    # append cumulative counts\n",
    "    ndf['cum_cases'] = ndf.groupby(['geoid'])['cases'].cumsum()\n",
    "    ndf['cum_deaths'] = ndf.groupby(['geoid'])['deaths'].cumsum()\n",
    "    return ndf\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Statistics / computations\n",
    "\n",
    "def lookup_country(df, x):\n",
    "    \"\"\"Lookup a country name or geoid. Empty string prints full list\"\"\"\n",
    "    x, n = x.upper(), len(x)\n",
    "    all_names = dict(sorted(zip(df['geoid'], df['country'])))\n",
    "\n",
    "    # simple search - either matches geoid or beginning of country name\n",
    "    subset = {g:c for g,c in all_names.items() if x == g or x == c.upper()[:n]}\n",
    "    \n",
    "    # display\n",
    "    for i, (g,c) in enumerate(subset.items(), 1):\n",
    "        print('{: <26}'.format((g + ': ' + c)[:24]), end='')\n",
    "        if i % 3 == 0: print()\n",
    "    print()\n",
    "    return\n",
    "\n",
    "\n",
    "def compute_global_totals(df, prefix):\n",
    "    \"\"\"Return dataframe with by-continent and world-wide statistics\"\"\"\n",
    "    if df['geoid'].str.startswith(prefix).any():\n",
    "        raise ValueError('duplicate error: world stats already exist in dataframe')\n",
    "        \n",
    "    # consolidate by continent. Geoid = prefix + first two letters of continent name\n",
    "    cc = df.groupby(['continent', 'date'], as_index=False).sum()\n",
    "    cc['country'] = cc['continent']\n",
    "    cc['geoid'] = prefix + cc['continent'].str[:2].str.upper()\n",
    "   \n",
    "    # worldwide numbers\n",
    "    ww = df.groupby(['date'], as_index=False).sum()\n",
    "    ww['country'] = 'World'\n",
    "    ww['continent'] = 'World'\n",
    "    ww['geoid'] = prefix + 'WW'\n",
    "    return pd.concat([cc, ww])\n",
    "\n",
    "\n",
    "def compute_fatality_ratio(df, lag, new_col, num_col='cum_deaths', denom_col='cum_cases'):\n",
    "    \"\"\"Compute fatality ratio with a given lag. Creates a new column in given df\"\"\"                    \n",
    "    def shifted_fr(x):\n",
    "        x[new_col] = (x[num_col] / x[denom_col].shift(lag)).fillna(0).replace(np.inf, 0)\n",
    "        return x\n",
    "        \n",
    "    df[new_col] = df.groupby(['geoid']).apply(shifted_fr)[new_col]\n",
    "    return\n",
    "\n",
    "\n",
    "def compute_timeline(df, threshold, col, new_col):\n",
    "    \"\"\"Count days from when a variable crossed a given threshold. Creates a new column in df\"\"\"\n",
    "    df[new_col] = 0\n",
    "    df.loc[df[col] >= threshold, new_col] = 1\n",
    "    df[new_col] = df.groupby(['geoid'])[new_col].cumsum()\n",
    "    return\n",
    "\n",
    "\n",
    "def compute_growth_rate(df, lag, col, new_col, dbl_col):\n",
    "    \"\"\"Compute average growth rate of a variable. Creates new columns in df\"\"\"\n",
    "    def growth_rate(x):\n",
    "        x[new_col] = (x[col] / x[col].shift(lag)).pow(1.0/lag).sub(1).\\\n",
    "                        fillna(0).replace(np.inf, 0)\n",
    "        return x\n",
    "    \n",
    "    df[new_col] = df.groupby(['geoid']).apply(growth_rate)[new_col]\n",
    "    df[dbl_col] = (np.log(2) / np.log(df[new_col].add(1))).\\\n",
    "                        fillna(0).replace(np.inf, 0)\n",
    "    return\n",
    "\n",
    "\n",
    "def compute_percapita_stat(df, col, new_col, base=1e6):\n",
    "    \"\"\"Rebase statistic to per unit of population\"\"\"\n",
    "    df[new_col] = df[col].div(df['population']).mul(base).\\\n",
    "                        fillna(0).replace(np.inf, 0)\n",
    "    return\n",
    "\n",
    "\n",
    "def compute_ma(df, window, col, new_col):\n",
    "    \"\"\"Compute moving average of a given column\"\"\"\n",
    "    df[new_col] = df.groupby(['geoid'])[col].apply(lambda s: s.rolling(window).mean()).\\\n",
    "                        fillna(0)\n",
    "    return\n",
    "\n",
    "\n",
    "def compute_stats(df, threshold=100, avg_period=3, lag=7):\n",
    "    \"\"\"Run all computations\"\"\"\n",
    "    # Create a timeline - first day when cum_cases exceeded a threshold\n",
    "    compute_timeline(df, threshold, 'cum_cases', 'timeline')\n",
    "\n",
    "    # compute fatality ratios - both unlagged and lagged\n",
    "    compute_fatality_ratio(df, 0, 'fatality0')\n",
    "\n",
    "    # compute n-day growth rates and doubling times\n",
    "    compute_growth_rate(df, avg_period, 'cum_cases', 'gr_cases', 'dbl_cases')\n",
    "    compute_growth_rate(df, avg_period, 'cum_deaths', 'gr_deaths', 'dbl_deaths')\n",
    "    \n",
    "    # compute cum cases/deaths per million of population\n",
    "    compute_percapita_stat(df, 'cum_cases', 'pm_cases', 1e6)\n",
    "    compute_percapita_stat(df, 'cum_deaths', 'pm_deaths', 1e6)\n",
    "    \n",
    "    # moving average of daily cases / deaths\n",
    "    compute_ma(df, avg_period, 'cases', 'ma_cases')\n",
    "    compute_ma(df, avg_period, 'deaths', 'ma_deaths')\n",
    "    compute_fatality_ratio(df, lag, 'fatality7', 'ma_deaths', 'ma_cases')\n",
    "\n",
    "    # sort out column order\n",
    "    df = pd.DataFrame(df, columns=['date', 'country', 'geoid', 'timeline',\n",
    "                                   'continent', 'population',\n",
    "                                   'cases', 'deaths', 'ma_cases', 'ma_deaths',\n",
    "                                   'cum_cases', 'cum_deaths', 'pm_cases', 'pm_deaths',\n",
    "                                   'fatality0','fatality7',\n",
    "                                   'gr_cases', 'dbl_cases', 'gr_deaths', 'dbl_deaths'])\n",
    "    return df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reports\n",
    "\n",
    "nice_names = {'date': 'Date', 'country': 'Country', 'geoid': 'GeoId',\n",
    "              'cases': 'Daily Cases', 'deaths': 'Daily Deaths',\n",
    "              'population': 'Population',\n",
    "              'cum_cases': 'Cum. Cases', 'cum_deaths': 'Cum. Deaths', \n",
    "              'timeline': 'Timeline',\n",
    "              'fatality0': 'Fatality (spot)',   'fatality7': 'Fatality (lagged)',\n",
    "              'gr_cases': 'Growth Rate Cases', 'gr_deaths': 'Growth Rate Deaths',\n",
    "              'pm_cases': 'Cases (per mil.)',  'pm_deaths': 'Deaths (per mil.)',\n",
    "              'ma_cases': 'MA Daily Cases',    'ma_deaths': 'MA Daily Deaths',\n",
    "              'dbl_cases': 'Doubling Time Cases', 'dbl_deaths': 'Doubling Time Deaths'\n",
    "             }\n",
    "\n",
    "\n",
    "fmt_style = {'date': lambda d: d.strftime('%Y-%m-%d'), 'cases': '{:,.0f}', 'deaths': '{:,.0f}',\n",
    "              'population': '{:,.0f}',\n",
    "              'cum_cases': '{:,.0f}', 'cum_deaths': '{:,.0f}', \n",
    "              'fatality0': '{:.2%}',  'fatality7': '{:.2%}',\n",
    "              'gr_cases': '{:.2%}',   'gr_deaths': '{:.2%}',\n",
    "              'pm_cases': '{:,.0f}',  'pm_deaths': '{:,.0f}',\n",
    "              'ma_cases': '{:,.0f}',  'ma_deaths': '{:,.0f}',\n",
    "              'dbl_cases': '{:,.0f}', 'dbl_deaths': '{:,.0f}',\n",
    "             }\n",
    "\n",
    "def make_nice_names(names):\n",
    "    \"\"\"Return nice names for given list\"\"\"\n",
    "    return [nice_names[c] if c in nice_names else c.capitalize() for c in names]\n",
    "\n",
    "\n",
    "def spruce(df, show_cols=[], hide_cols=[], show_nice_names=False):\n",
    "    \"\"\"Spruce up index & columns for displaying a dataframe\"\"\"\n",
    "    # choose columns to show\n",
    "    all_cols = show_cols if len(show_cols) > 0 else list(df.columns)\n",
    "    for c in hide_cols:\n",
    "        if c in all_cols:\n",
    "            all_cols.remove(c)\n",
    "    \n",
    "    y = pd.DataFrame(df, columns=all_cols)\n",
    " \n",
    "    # pretty up index and columns names\n",
    "    y.index = np.arange(1, len(df) + 1)\n",
    "    if show_nice_names: y.columns = make_nice_names(all_cols)\n",
    "    return y\n",
    "\n",
    "\n",
    "def stylise(df, show_nice_names=False):\n",
    "    \"\"\"Apply styles to dataframe\"\"\"\n",
    "    return df.style.format({nice_names[c]:f for c,f in fmt_style.items()}\n",
    "                                if show_nice_names else fmt_style)\n",
    "    \n",
    "    \n",
    "def rpt_show(df, caption, asof=None, sortby=None, count=0,\n",
    "             hide_cols=['population'], show_nice_names=False):\n",
    "    \"\"\"Show part of a dataframe\"\"\"\n",
    "    if count == 0: count = len(df)\n",
    "\n",
    "    y = df\n",
    "    if asof is not None: y = y[y.date == asof]\n",
    "    if sortby is not None: y = y.sort_values([sortby], ascending=False)\n",
    "    \n",
    "    # show report \n",
    "    print('\\n', caption, '\\n')\n",
    "    y = spruce(y.head(count), hide_cols=hide_cols, show_nice_names=show_nice_names)\n",
    "    ipd.display(stylise(y, show_nice_names=show_nice_names))\n",
    "    return\n",
    "\n",
    "\n",
    "def rpt_daily_stats(df, asof, variables, filter_col='cum_deaths', threshold=100,\n",
    "                    sort_ascending=False, count=10, show_nice_names=False):\n",
    "    \"\"\"Daily stats report\"\"\"\n",
    "    main_cols = ['country', 'geoid']\n",
    "    \n",
    "    sections = []\n",
    "    for i, v in enumerate(variables, 1):\n",
    "        x = df[(df[filter_col] > threshold) & (df['date'] == asof) &\n",
    "                      (~ df['geoid'].str.startswith('W_'))]\\\n",
    "                   .sort_values([v], ascending=sort_ascending)\\\n",
    "                   .head(count)\n",
    "        \n",
    "        x = spruce(x, main_cols + [v])\n",
    "        x.columns = [c + str(i) for c in main_cols] + [v]\n",
    "        sections.append(x)\n",
    "    y = pd.concat(sections, axis=1)\n",
    "    if show_nice_names: y.columns = make_nice_names(y.columns)\n",
    "\n",
    "    print('\\n', 'Daily statistics for ' + asof, '\\n')\n",
    "    ipd.display(stylise(y, show_nice_names=show_nice_names))\n",
    "    return\n",
    "\n",
    "\n",
    "def rpt_history(df_all, geoid, history=7, show_nice_names=False):\n",
    "    \"\"\"Show n-day history for given geoid\"\"\"\n",
    "    \n",
    "    # show history\n",
    "    df = df_all[(df_all.geoid == geoid) & (df_all.timeline > 0)]\n",
    "    if len(df) < 2:\n",
    "        print(\"Insufficient data for requested country\")\n",
    "        return\n",
    "    \n",
    "    caption = '{} ({}), pop. {:,}: Last {} days. Timeline: Day-{}'.\\\n",
    "               format(df['country'].iloc[0], geoid, df['population'].max(),\n",
    "                      history, df['timeline'].max())\n",
    "    rpt_show(df.tail(history)[::-1], caption, hide_cols=['country', 'geoid',\n",
    "                                                         'population', 'continent'],\n",
    "            show_nice_names=show_nice_names)\n",
    "    return\n",
    "\n",
    "\n",
    "def rpt_country(df_all, geoid, history=7, show_nice_names=False):\n",
    "    \"\"\"Summary report for given country\"\"\"\n",
    "    \n",
    "    # show history\n",
    "    rpt_history(df_all, geoid, history, show_nice_names=show_nice_names)\n",
    "\n",
    "    # show charts\n",
    "    df = df_all[(df_all.geoid == geoid) & (df_all.timeline > 0)]\n",
    "    if len(df) < 2:\n",
    "        print(\"Insufficient data for requested country\")\n",
    "        return None\n",
    "  \n",
    "    plt.figure(1, figsize=(18, 21))\n",
    "    ax = plt.subplot(321)\n",
    "    df.plot(ax=ax, x='timeline', y=['cum_cases'], marker='.')\n",
    "\n",
    "    ax = plt.subplot(322)\n",
    "    df.plot(ax=ax, x='timeline', y=['cum_deaths'], marker='.')\n",
    "\n",
    "    ax = plt.subplot(323)\n",
    "    # df.plot(ax=ax, x='timeline', y=['cases', 'ma_cases', 'gr_cases'],\n",
    "    #        secondary_y='gr_cases', marker='.')\n",
    "    df.plot(ax=ax, x='timeline', y='cases', kind='line')\n",
    "    # df.plot(ax=ax, x='timeline', y='ma_cases', kind='line')\n",
    "    df.plot(ax=ax, x='timeline', y='gr_cases', secondary_y='gr_cases', kind='line', marker='.')\n",
    "    \n",
    "    ax = plt.subplot(324)\n",
    "    # df.plot(ax=ax, x='timeline', y=['deaths', 'ma_deaths', 'gr_deaths'],\n",
    "    #        secondary_y='gr_deaths', marker='.')\n",
    "    df.plot(ax=ax, x='timeline', y='deaths', kind='line')\n",
    "    # df.plot(ax=ax, x='timeline', y='ma_deaths', kind='line')\n",
    "    df.plot(ax=ax, x='timeline', y='gr_deaths', secondary_y='gr_deaths', kind='line', marker='.')\n",
    "\n",
    "    ax = plt.subplot(325)\n",
    "    df.plot(ax=ax, x='timeline', y=['fatality0', 'fatality7'], marker='.')\n",
    "\n",
    "    ax = plt.subplot(326)\n",
    "    df.plot(ax=ax, x='timeline', y=['dbl_cases', 'dbl_deaths'], marker='.')\n",
    "\n",
    "    plt.show()\n",
    "    return\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# charts\n",
    "def chart(df, title, *, geoid, x, y, log_scale=None, filter_timeline=False,\n",
    "          figsize=(16,8), **kwargs):\n",
    "    \"\"\"Generic charting routine\n",
    "    \n",
    "    geoid:           a single geoid or a list\n",
    "    x:               x-axis column\n",
    "    y:               y-axis column(s)\n",
    "    log_scale:       scale axis on a log scale; valid values are None, x, y or both\n",
    "    filter_timeline: additionally filter data for timeline > 0\n",
    "    \n",
    "    Note that both geoid and y cannot be lists.\n",
    "    \"\"\"\n",
    "    # check parameters\n",
    "    if np.isscalar(geoid):\n",
    "        geoid = [geoid]\n",
    "    if np.isscalar(y):\n",
    "        y = [y]\n",
    "    assert len(geoid) == 1 or len(y) == 1, 'Both geoid and y cannot be arraylike'\n",
    "    \n",
    "    # log graph?\n",
    "    p_logx = log_scale == 'x'\n",
    "    p_logy = log_scale == 'y'\n",
    "    p_loglog = log_scale == 'both'\n",
    "\n",
    "    # filter data\n",
    "    mask = df['geoid'].isin(geoid)\n",
    "    if x == 'timeline' or filter_timeline:\n",
    "        mask &= df['timeline'] > 0\n",
    "\n",
    "    needed_cols = [x] + y\n",
    "    cnames = dict(zip(df['geoid'], df['country']))   # TODO: Refactor\n",
    "\n",
    "    # create the chart\n",
    "    plt.figure(1, figsize=figsize)\n",
    "    ax = plt.subplot(111)\n",
    "    for g in geoid:\n",
    "        lbl = y if len(geoid) == 1 else [cnames.get(g, g)]\n",
    "        \n",
    "        data = pd.DataFrame(df[mask & (df['geoid'] == g)], columns=needed_cols)\n",
    "        data.plot(ax=ax, x=x, y=y, label=lbl, logx=p_logx, logy=p_logy, loglog=p_loglog, **kwargs)\n",
    "\n",
    "    plt.title(title)\n",
    "    plt.show()\n",
    "    return\n",
    "\n",
    "\n",
    "def timeline_chart(df, title, *, geoid, y, log_scale=None, **kwargs):\n",
    "    \"\"\"Chart variable for given countries\"\"\"\n",
    "    chart(df, title, geoid=geoid, x='timeline', y=y, log_scale=log_scale, **kwargs)\n",
    "    return\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dashboard <a id='dashboard'></a>\n",
    "\n",
    "- Update asof to today's date and load data\n",
    "- This will fetch the data from the ECDC website and save a clean (dated) version in the local directory\n",
    "- Subsequent loads will read the local version if it exists.\n",
    "\n",
    "\n",
    "Click here to go to the [Code section](#code_section)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# general parameters\n",
    "# ------------------\n",
    "# asof date\n",
    "asof = '2020-12-14'\n",
    "\n",
    "# Day0 for each country is determined when cum_cases >= threshold\n",
    "timeline_threshold = 100\n",
    "\n",
    "# Period over which to compute the average growth rate\n",
    "avg_period = 3\n",
    "\n",
    "# subsets of interest\n",
    "home = 'UK'\n",
    "world = 'W_WW'\n",
    "monitor = ['W_WW', 'US', 'BR', 'UK', 'IT', 'ES', 'DE', 'FR', 'CH', 'SE',\n",
    "           'CN', 'JP', 'KR', 'RU', 'IN']\n",
    "continents = ['W_WW', 'W_AS', 'W_EU', 'W_AM', 'W_AF', 'W_OC', 'W_OT']\n",
    "\n",
    "# load and compute data\n",
    "# ---------------------\n",
    "# ECDC website - caveat, the file's name format changes once in a while\n",
    "site = 'https://www.ecdc.europa.eu/sites/default/files/documents/'\n",
    "url1 = site + 'COVID-19-geographic-disbtribution-worldwide-' + asof + '.xlsx'\n",
    "url2 = site + 'COVID-19-geographic-disbtribution-worldwide-' + asof + '.xls'\n",
    "\n",
    "# Local filename - the cleaned data is saved here. If this file exists, the routine\n",
    "# will load it instead of hitting the ECDC website\n",
    "local_csv = 'ecdc_' + asof.replace('-', '') + '.csv'\n",
    "df = load_data(asof, local_csv, url1, url2)\n",
    "df = compute_stats(df, timeline_threshold, avg_period)\n",
    "\n",
    "# data subsets \n",
    "df_world = df[df['geoid'] == world]\n",
    "df_home  = df[df['geoid'] == home]\n",
    "df_mon   = df[df['geoid'].isin(monitor)]\n",
    "df_continents = df[df['geoid'].isin(continents)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# export computed dataframe if needed\n",
    "# df.to_csv('cvdb_' + asof.replace('-', '') + '.csv')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Description of column names\n",
    "---\n",
    "- *geoid:* Geographic ID. WW has been included for World statistics\n",
    "- *timeline:* Day-1 is the first day that cum_cases for a country exceeds a certain threshold (defined by timeline_threshold; see above)\n",
    "\n",
    "\n",
    "- *cases:* Cases reported on the given date\n",
    "- *cum_cases:* Cumulative cases up to the given date\n",
    "- *deaths:* Deaths reported on the given date\n",
    "- *cum_deaths:* Cumulative deaths up to the given date\n",
    "\n",
    "\n",
    "- *fatality0:* Spot fatality rate (%age) based on cumulative statistics. FR0 = cum_deaths(t) / cum_cases(t)\n",
    "- *fatality7:* Lagged fatality rate based on moving average statistics. FR7 = ma_deaths(t) / ma_cases(t-7)\n",
    "\n",
    "\n",
    "- *gr_cases:* The growth rate (%age) in cases reported. This is a 3-day compounded moving average to smoothen the data\n",
    "- *gr_deaths:* The growth rate (%age) in deaths reported. Computed similar to gr_cases\n",
    "- *dbl_cases:* Days for cumulative cases reported to double in number. Implied from the growth rate; therefore lagging because of the averaging period used\n",
    "- *dbl_deaths:* Days for cumulative deaths reported to double in number\n",
    "\n",
    "\n",
    "- *pm_cases:* Total cases per million of population\n",
    "- *pm_deaths:* Total deaths per million of population\n",
    "- *ma_cases:* 3-day moving average of daily cases reported\n",
    "- *ma_deaths:* 3-day moving average of daily deaths reported\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monitor\n",
    "\n",
    "Statistics for countries in the monitor list "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Statistics by continent for: 2020-12-14 \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Country</th>        <th class=\"col_heading level0 col1\" >Timeline</th>        <th class=\"col_heading level0 col2\" >Daily Cases</th>        <th class=\"col_heading level0 col3\" >Daily Deaths</th>        <th class=\"col_heading level0 col4\" >MA Daily Cases</th>        <th class=\"col_heading level0 col5\" >MA Daily Deaths</th>        <th class=\"col_heading level0 col6\" >Cum. Cases</th>        <th class=\"col_heading level0 col7\" >Cum. Deaths</th>        <th class=\"col_heading level0 col8\" >Cases (per mil.)</th>        <th class=\"col_heading level0 col9\" >Deaths (per mil.)</th>        <th class=\"col_heading level0 col10\" >Fatality (spot)</th>        <th class=\"col_heading level0 col11\" >Fatality (lagged)</th>        <th class=\"col_heading level0 col12\" >Growth Rate Cases</th>        <th class=\"col_heading level0 col13\" >Doubling Time Cases</th>        <th class=\"col_heading level0 col14\" >Growth Rate Deaths</th>        <th class=\"col_heading level0 col15\" >Doubling Time Deaths</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col0\" class=\"data row0 col0\" >World</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col1\" class=\"data row0 col1\" >331</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col2\" class=\"data row0 col2\" >540,659</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col3\" class=\"data row0 col3\" >7,085</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col4\" class=\"data row0 col4\" >608,073</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col5\" class=\"data row0 col5\" >9,898</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col6\" class=\"data row0 col6\" >71,503,614</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col7\" class=\"data row0 col7\" >1,612,833</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col8\" class=\"data row0 col8\" >9,380</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col9\" class=\"data row0 col9\" >212</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col10\" class=\"data row0 col10\" >2.26%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col11\" class=\"data row0 col11\" >1.59%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col12\" class=\"data row0 col12\" >0.87%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col13\" class=\"data row0 col13\" >80</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col14\" class=\"data row0 col14\" >0.62%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row0_col15\" class=\"data row0 col15\" >112</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col0\" class=\"data row1 col0\" >America</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col1\" class=\"data row1 col1\" >289</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col2\" class=\"data row1 col2\" >250,922</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col3\" class=\"data row1 col3\" >2,433</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col4\" class=\"data row1 col4\" >298,430</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col5\" class=\"data row1 col5\" >4,036</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col6\" class=\"data row1 col6\" >30,887,593</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col7\" class=\"data row1 col7\" >785,420</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col8\" class=\"data row1 col8\" >30,473</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col9\" class=\"data row1 col9\" >775</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col10\" class=\"data row1 col10\" >2.54%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col11\" class=\"data row1 col11\" >1.40%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col12\" class=\"data row1 col12\" >0.99%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col13\" class=\"data row1 col13\" >71</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col14\" class=\"data row1 col14\" >0.52%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row1_col15\" class=\"data row1 col15\" >134</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col0\" class=\"data row2 col0\" >Europe</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col1\" class=\"data row2 col1\" >296</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col2\" class=\"data row2 col2\" >208,571</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col3\" class=\"data row2 col3\" >3,277</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col4\" class=\"data row2 col4\" >221,859</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col5\" class=\"data row2 col5\" >4,399</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col6\" class=\"data row2 col6\" >21,400,012</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col7\" class=\"data row2 col7\" >479,789</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col8\" class=\"data row2 col8\" >26,707</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col9\" class=\"data row2 col9\" >599</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col10\" class=\"data row2 col10\" >2.24%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col11\" class=\"data row2 col11\" >1.86%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col12\" class=\"data row2 col12\" >1.06%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col13\" class=\"data row2 col13\" >66</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col14\" class=\"data row2 col14\" >0.93%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row2_col15\" class=\"data row2 col15\" >75</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col0\" class=\"data row3 col0\" >Asia</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col1\" class=\"data row3 col1\" >331</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col2\" class=\"data row3 col2\" >64,995</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col3\" class=\"data row3 col3\" >1,027</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col4\" class=\"data row3 col4\" >69,856</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col5\" class=\"data row3 col5\" >1,106</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col6\" class=\"data row3 col6\" >16,782,046</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col7\" class=\"data row3 col7\" >290,129</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col8\" class=\"data row3 col8\" >3,763</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col9\" class=\"data row3 col9\" >65</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col10\" class=\"data row3 col10\" >1.73%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col11\" class=\"data row3 col11\" >1.37%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col12\" class=\"data row3 col12\" >0.42%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col13\" class=\"data row3 col13\" >165</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col14\" class=\"data row3 col14\" >0.38%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row3_col15\" class=\"data row3 col15\" >181</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col0\" class=\"data row4 col0\" >Africa</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col1\" class=\"data row4 col1\" >279</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col2\" class=\"data row4 col2\" >16,142</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col3\" class=\"data row4 col3\" >347</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col4\" class=\"data row4 col4\" >17,856</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col5\" class=\"data row4 col5\" >356</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col6\" class=\"data row4 col6\" >2,379,827</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col7\" class=\"data row4 col7\" >56,334</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col8\" class=\"data row4 col8\" >1,821</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col9\" class=\"data row4 col9\" >43</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col10\" class=\"data row4 col10\" >2.37%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col11\" class=\"data row4 col11\" >2.27%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col12\" class=\"data row4 col12\" >0.76%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col13\" class=\"data row4 col13\" >91</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col14\" class=\"data row4 col14\" >0.64%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row4_col15\" class=\"data row4 col15\" >109</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col0\" class=\"data row5 col0\" >Oceania</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col1\" class=\"data row5 col1\" >280</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col2\" class=\"data row5 col2\" >29</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col3\" class=\"data row5 col3\" >1</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col4\" class=\"data row5 col4\" >72</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col5\" class=\"data row5 col5\" >1</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col6\" class=\"data row5 col6\" >53,440</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col7\" class=\"data row5 col7\" >1,154</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col8\" class=\"data row5 col8\" >1,289</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col9\" class=\"data row5 col9\" >28</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col10\" class=\"data row5 col10\" >2.16%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col11\" class=\"data row5 col11\" >0.81%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col12\" class=\"data row5 col12\" >0.13%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col13\" class=\"data row5 col13\" >516</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col14\" class=\"data row5 col14\" >0.12%</td>\n",
       "                        <td id=\"T_18cda3f0_5c37_11eb_beaf_3af9d3d753e3row5_col15\" class=\"data row5 col15\" >599</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f7f695d84d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rpt_show(df_continents, 'Statistics by continent for: ' + asof, asof, 'cum_deaths',\n",
    "         hide_cols=['population', 'date', 'geoid', 'continent'], show_nice_names=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Statistics by country for: 2020-12-14 \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >country</th>        <th class=\"col_heading level0 col1\" >timeline</th>        <th class=\"col_heading level0 col2\" >cases</th>        <th class=\"col_heading level0 col3\" >deaths</th>        <th class=\"col_heading level0 col4\" >ma_cases</th>        <th class=\"col_heading level0 col5\" >ma_deaths</th>        <th class=\"col_heading level0 col6\" >cum_cases</th>        <th class=\"col_heading level0 col7\" >cum_deaths</th>        <th class=\"col_heading level0 col8\" >pm_cases</th>        <th class=\"col_heading level0 col9\" >pm_deaths</th>        <th class=\"col_heading level0 col10\" >fatality0</th>        <th class=\"col_heading level0 col11\" >fatality7</th>        <th class=\"col_heading level0 col12\" >gr_cases</th>        <th class=\"col_heading level0 col13\" >dbl_cases</th>        <th class=\"col_heading level0 col14\" >gr_deaths</th>        <th class=\"col_heading level0 col15\" >dbl_deaths</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col0\" class=\"data row0 col0\" >World</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col1\" class=\"data row0 col1\" >331</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col2\" class=\"data row0 col2\" >540,659</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col3\" class=\"data row0 col3\" >7,085</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col4\" class=\"data row0 col4\" >608,073</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col5\" class=\"data row0 col5\" >9,898</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col6\" class=\"data row0 col6\" >71,503,614</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col7\" class=\"data row0 col7\" >1,612,833</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col8\" class=\"data row0 col8\" >9,380</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col9\" class=\"data row0 col9\" >212</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col10\" class=\"data row0 col10\" >2.26%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col11\" class=\"data row0 col11\" >1.59%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col12\" class=\"data row0 col12\" >0.87%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col13\" class=\"data row0 col13\" >80</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col14\" class=\"data row0 col14\" >0.62%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row0_col15\" class=\"data row0 col15\" >112</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col0\" class=\"data row1 col0\" >United_States_of_America</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col1\" class=\"data row1 col1\" >287</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col2\" class=\"data row1 col2\" >189,723</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col3\" class=\"data row1 col3\" >1,340</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col4\" class=\"data row1 col4\" >213,458</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col5\" class=\"data row1 col5\" >2,333</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col6\" class=\"data row1 col6\" >16,256,754</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col7\" class=\"data row1 col7\" >299,177</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col8\" class=\"data row1 col8\" >49,403</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col9\" class=\"data row1 col9\" >909</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col10\" class=\"data row1 col10\" >1.84%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col11\" class=\"data row1 col11\" >1.13%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col12\" class=\"data row1 col12\" >1.35%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col13\" class=\"data row1 col13\" >52</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col14\" class=\"data row1 col14\" >0.79%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row1_col15\" class=\"data row1 col15\" >88</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col0\" class=\"data row2 col0\" >Brazil</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col1\" class=\"data row2 col1\" >275</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col2\" class=\"data row2 col2\" >21,825</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col3\" class=\"data row2 col3\" >279</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col4\" class=\"data row2 col4\" >40,051</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col5\" class=\"data row2 col5\" >546</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col6\" class=\"data row2 col6\" >6,901,952</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col7\" class=\"data row2 col7\" >181,402</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col8\" class=\"data row2 col8\" >32,703</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col9\" class=\"data row2 col9\" >860</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col10\" class=\"data row2 col10\" >2.63%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col11\" class=\"data row2 col11\" >1.41%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col12\" class=\"data row2 col12\" >0.59%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col13\" class=\"data row2 col13\" >118</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col14\" class=\"data row2 col14\" >0.30%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row2_col15\" class=\"data row2 col15\" >229</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col0\" class=\"data row3 col0\" >India</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col1\" class=\"data row3 col1\" >273</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col2\" class=\"data row3 col2\" >27,071</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col3\" class=\"data row3 col3\" >336</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col4\" class=\"data row3 col4\" >29,110</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col5\" class=\"data row3 col5\" >390</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col6\" class=\"data row3 col6\" >9,884,100</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col7\" class=\"data row3 col7\" >143,355</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col8\" class=\"data row3 col8\" >7,234</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col9\" class=\"data row3 col9\" >105</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col10\" class=\"data row3 col10\" >1.45%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col11\" class=\"data row3 col11\" >1.11%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col12\" class=\"data row3 col12\" >0.30%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col13\" class=\"data row3 col13\" >234</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col14\" class=\"data row3 col14\" >0.27%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row3_col15\" class=\"data row3 col15\" >254</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col0\" class=\"data row4 col0\" >Italy</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col1\" class=\"data row4 col1\" >295</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col2\" class=\"data row4 col2\" >17,937</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col3\" class=\"data row4 col3\" >484</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col4\" class=\"data row4 col4\" >18,855</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col5\" class=\"data row4 col5\" >631</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col6\" class=\"data row4 col6\" >1,843,712</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col7\" class=\"data row4 col7\" >64,520</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col8\" class=\"data row4 col8\" >30,545</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col9\" class=\"data row4 col9\" >1,069</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col10\" class=\"data row4 col10\" >3.50%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col11\" class=\"data row4 col11\" >2.96%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col12\" class=\"data row4 col12\" >1.04%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col13\" class=\"data row4 col13\" >67</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col14\" class=\"data row4 col14\" >1.00%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row4_col15\" class=\"data row4 col15\" >70</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col0\" class=\"data row5 col0\" >United_Kingdom</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col1\" class=\"data row5 col1\" >286</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col2\" class=\"data row5 col2\" >18,447</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col3\" class=\"data row5 col3\" >144</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col4\" class=\"data row5 col4\" >20,540</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col5\" class=\"data row5 col5\" >363</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col6\" class=\"data row5 col6\" >1,849,403</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col7\" class=\"data row5 col7\" >64,170</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col8\" class=\"data row5 col8\" >27,749</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col9\" class=\"data row5 col9\" >963</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col10\" class=\"data row5 col10\" >3.47%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col11\" class=\"data row5 col11\" >2.22%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col12\" class=\"data row5 col12\" >1.14%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col13\" class=\"data row5 col13\" >61</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col14\" class=\"data row5 col14\" >0.57%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row5_col15\" class=\"data row5 col15\" >122</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row6\" class=\"row_heading level0 row6\" >7</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col0\" class=\"data row6 col0\" >France</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col1\" class=\"data row6 col1\" >289</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col2\" class=\"data row6 col2\" >11,533</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col3\" class=\"data row6 col3\" >150</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col4\" class=\"data row6 col4\" >12,962</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col5\" class=\"data row6 col5\" >324</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col6\" class=\"data row6 col6\" >2,376,852</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col7\" class=\"data row6 col7\" >57,911</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col8\" class=\"data row6 col8\" >35,469</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col9\" class=\"data row6 col9\" >864</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col10\" class=\"data row6 col10\" >2.44%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col11\" class=\"data row6 col11\" >2.76%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col12\" class=\"data row6 col12\" >0.55%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col13\" class=\"data row6 col13\" >126</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col14\" class=\"data row6 col14\" >0.57%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row6_col15\" class=\"data row6 col15\" >123</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row7\" class=\"row_heading level0 row7\" >8</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col0\" class=\"data row7 col0\" >Russia</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col1\" class=\"data row7 col1\" >272</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col2\" class=\"data row7 col2\" >28,080</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col3\" class=\"data row7 col3\" >488</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col4\" class=\"data row7 col4\" >28,267</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col5\" class=\"data row7 col5\" >554</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col6\" class=\"data row7 col6\" >2,653,928</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col7\" class=\"data row7 col7\" >46,941</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col8\" class=\"data row7 col8\" >18,194</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col9\" class=\"data row7 col9\" >322</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col10\" class=\"data row7 col10\" >1.77%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col11\" class=\"data row7 col11\" >1.95%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col12\" class=\"data row7 col12\" >1.09%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col13\" class=\"data row7 col13\" >64</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col14\" class=\"data row7 col14\" >1.21%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row7_col15\" class=\"data row7 col15\" >58</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row8\" class=\"row_heading level0 row8\" >9</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col0\" class=\"data row8 col0\" >Germany</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col1\" class=\"data row8 col1\" >289</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col2\" class=\"data row8 col2\" >16,362</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col3\" class=\"data row8 col3\" >188</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col4\" class=\"data row8 col4\" >21,667</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col5\" class=\"data row8 col5\" >335</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col6\" class=\"data row8 col6\" >1,337,078</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col7\" class=\"data row8 col7\" >21,975</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col8\" class=\"data row8 col8\" >16,106</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col9\" class=\"data row8 col9\" >265</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col10\" class=\"data row8 col10\" >1.64%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col11\" class=\"data row8 col11\" >1.88%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col12\" class=\"data row8 col12\" >1.68%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col13\" class=\"data row8 col13\" >42</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col14\" class=\"data row8 col14\" >1.57%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row8_col15\" class=\"data row8 col15\" >44</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row9\" class=\"row_heading level0 row9\" >10</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col0\" class=\"data row9 col0\" >Sweden</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col1\" class=\"data row9 col1\" >283</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col2\" class=\"data row9 col2\" >0</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col3\" class=\"data row9 col3\" >0</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col4\" class=\"data row9 col4\" >0</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col5\" class=\"data row9 col5\" >0</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col6\" class=\"data row9 col6\" >320,098</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col7\" class=\"data row9 col7\" >7,514</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col8\" class=\"data row9 col8\" >31,290</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col9\" class=\"data row9 col9\" >734</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col10\" class=\"data row9 col10\" >2.35%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col11\" class=\"data row9 col11\" >0.00%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col12\" class=\"data row9 col12\" >0.00%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col13\" class=\"data row9 col13\" >0</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col14\" class=\"data row9 col14\" >0.00%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row9_col15\" class=\"data row9 col15\" >0</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row10\" class=\"row_heading level0 row10\" >11</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col0\" class=\"data row10 col0\" >Switzerland</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col1\" class=\"data row10 col1\" >283</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col2\" class=\"data row10 col2\" >0</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col3\" class=\"data row10 col3\" >0</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col4\" class=\"data row10 col4\" >1,704</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col5\" class=\"data row10 col5\" >35</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col6\" class=\"data row10 col6\" >372,329</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col7\" class=\"data row10 col7\" >5,378</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col8\" class=\"data row10 col8\" >43,575</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col9\" class=\"data row10 col9\" >629</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col10\" class=\"data row10 col10\" >1.44%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col11\" class=\"data row10 col11\" >2.40%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col12\" class=\"data row10 col12\" >0.46%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col13\" class=\"data row10 col13\" >150</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col14\" class=\"data row10 col14\" >0.66%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row10_col15\" class=\"data row10 col15\" >105</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row11\" class=\"row_heading level0 row11\" >12</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col0\" class=\"data row11 col0\" >China</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col1\" class=\"data row11 col1\" >331</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col2\" class=\"data row11 col2\" >12</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col3\" class=\"data row11 col3\" >0</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col4\" class=\"data row11 col4\" >16</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col5\" class=\"data row11 col5\" >0</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col6\" class=\"data row11 col6\" >92,021</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col7\" class=\"data row11 col7\" >4,739</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col8\" class=\"data row11 col8\" >64</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col9\" class=\"data row11 col9\" >3</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col10\" class=\"data row11 col10\" >5.15%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col11\" class=\"data row11 col11\" >0.00%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col12\" class=\"data row11 col12\" >0.02%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col13\" class=\"data row11 col13\" >3,904</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col14\" class=\"data row11 col14\" >0.00%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row11_col15\" class=\"data row11 col15\" >0</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row12\" class=\"row_heading level0 row12\" >13</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col0\" class=\"data row12 col0\" >Japan</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col1\" class=\"data row12 col1\" >297</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col2\" class=\"data row12 col2\" >2,366</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col3\" class=\"data row12 col3\" >23</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col4\" class=\"data row12 col4\" >2,704</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col5\" class=\"data row12 col5\" >28</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col6\" class=\"data row12 col6\" >179,653</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col7\" class=\"data row12 col7\" >2,585</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col8\" class=\"data row12 col8\" >1,416</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col9\" class=\"data row12 col9\" >20</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col10\" class=\"data row12 col10\" >1.44%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col11\" class=\"data row12 col11\" >1.21%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col12\" class=\"data row12 col12\" >1.55%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col13\" class=\"data row12 col13\" >45</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col14\" class=\"data row12 col14\" >1.09%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row12_col15\" class=\"data row12 col15\" >64</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3level0_row13\" class=\"row_heading level0 row13\" >14</th>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col0\" class=\"data row13 col0\" >South_Korea</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col1\" class=\"data row13 col1\" >298</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col2\" class=\"data row13 col2\" >718</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col3\" class=\"data row13 col3\" >7</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col4\" class=\"data row13 col4\" >899</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col5\" class=\"data row13 col5\" >5</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col6\" class=\"data row13 col6\" >43,484</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col7\" class=\"data row13 col7\" >587</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col8\" class=\"data row13 col8\" >849</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col9\" class=\"data row13 col9\" >11</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col10\" class=\"data row13 col10\" >1.35%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col11\" class=\"data row13 col11\" >0.82%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col12\" class=\"data row13 col12\" >2.16%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col13\" class=\"data row13 col13\" >32</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col14\" class=\"data row13 col14\" >0.87%</td>\n",
       "                        <td id=\"T_18cfff2e_5c37_11eb_beaf_3af9d3d753e3row13_col15\" class=\"data row13 col15\" >80</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f7f65865250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rpt_show(df_mon, 'Statistics by country for: ' + asof, asof, 'cum_deaths',\n",
    "         hide_cols=['population', 'date', 'geoid', 'continent'], show_nice_names=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Country Report\n",
    "\n",
    "Show recent history and charts for a given country (or the world 'WW')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# find country - empty string prints full list\n",
    "# lookup_country(df, 'Taiwan')\n",
    "# rpt_history(df, 'UK', history=60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " United_Kingdom (UK), pop. 66,647,112: Last 7 days. Timeline: Day-286 \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >date</th>        <th class=\"col_heading level0 col1\" >timeline</th>        <th class=\"col_heading level0 col2\" >cases</th>        <th class=\"col_heading level0 col3\" >deaths</th>        <th class=\"col_heading level0 col4\" >ma_cases</th>        <th class=\"col_heading level0 col5\" >ma_deaths</th>        <th class=\"col_heading level0 col6\" >cum_cases</th>        <th class=\"col_heading level0 col7\" >cum_deaths</th>        <th class=\"col_heading level0 col8\" >pm_cases</th>        <th class=\"col_heading level0 col9\" >pm_deaths</th>        <th class=\"col_heading level0 col10\" >fatality0</th>        <th class=\"col_heading level0 col11\" >fatality7</th>        <th class=\"col_heading level0 col12\" >gr_cases</th>        <th class=\"col_heading level0 col13\" >dbl_cases</th>        <th class=\"col_heading level0 col14\" >gr_deaths</th>        <th class=\"col_heading level0 col15\" >dbl_deaths</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col0\" class=\"data row0 col0\" >2020-12-14</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col1\" class=\"data row0 col1\" >286</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col2\" class=\"data row0 col2\" >18,447</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col3\" class=\"data row0 col3\" >144</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col4\" class=\"data row0 col4\" >20,540</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col5\" class=\"data row0 col5\" >363</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col6\" class=\"data row0 col6\" >1,849,403</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col7\" class=\"data row0 col7\" >64,170</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col8\" class=\"data row0 col8\" >27,749</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col9\" class=\"data row0 col9\" >963</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col10\" class=\"data row0 col10\" >3.47%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col11\" class=\"data row0 col11\" >2.22%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col12\" class=\"data row0 col12\" >1.14%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col13\" class=\"data row0 col13\" >61</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col14\" class=\"data row0 col14\" >0.57%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row0_col15\" class=\"data row0 col15\" >122</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col0\" class=\"data row1 col0\" >2020-12-13</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col1\" class=\"data row1 col1\" >285</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col2\" class=\"data row1 col2\" >21,501</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col3\" class=\"data row1 col3\" >520</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col4\" class=\"data row1 col4\" >21,379</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col5\" class=\"data row1 col5\" >487</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col6\" class=\"data row1 col6\" >1,830,956</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col7\" class=\"data row1 col7\" >64,026</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col8\" class=\"data row1 col8\" >27,472</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col9\" class=\"data row1 col9\" >961</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col10\" class=\"data row1 col10\" >3.50%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col11\" class=\"data row1 col11\" >3.13%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col12\" class=\"data row1 col12\" >1.20%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col13\" class=\"data row1 col13\" >58</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col14\" class=\"data row1 col14\" >0.77%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row1_col15\" class=\"data row1 col15\" >90</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col0\" class=\"data row2 col0\" >2020-12-12</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col1\" class=\"data row2 col1\" >284</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col2\" class=\"data row2 col2\" >21,672</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col3\" class=\"data row2 col3\" >424</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col4\" class=\"data row2 col4\" >19,738</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col5\" class=\"data row2 col5\" >491</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col6\" class=\"data row2 col6\" >1,809,455</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col7\" class=\"data row2 col7\" >63,506</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col8\" class=\"data row2 col8\" >27,150</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col9\" class=\"data row2 col9\" >953</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col10\" class=\"data row2 col10\" >3.51%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col11\" class=\"data row2 col11\" >3.11%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col12\" class=\"data row2 col12\" >1.12%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col13\" class=\"data row2 col13\" >62</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col14\" class=\"data row2 col14\" >0.79%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row2_col15\" class=\"data row2 col15\" >89</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col0\" class=\"data row3 col0\" >2020-12-11</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col1\" class=\"data row3 col1\" >283</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col2\" class=\"data row3 col2\" >20,964</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col3\" class=\"data row3 col3\" >516</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col4\" class=\"data row3 col4\" >16,608</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col5\" class=\"data row3 col5\" >549</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col6\" class=\"data row3 col6\" >1,787,783</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col7\" class=\"data row3 col7\" >63,082</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col8\" class=\"data row3 col8\" >26,825</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col9\" class=\"data row3 col9\" >947</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col10\" class=\"data row3 col10\" >3.53%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col11\" class=\"data row3 col11\" >3.71%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col12\" class=\"data row3 col12\" >0.95%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col13\" class=\"data row3 col13\" >74</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col14\" class=\"data row3 col14\" >0.89%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row3_col15\" class=\"data row3 col15\" >79</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col0\" class=\"data row4 col0\" >2020-12-10</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col1\" class=\"data row4 col1\" >282</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col2\" class=\"data row4 col2\" >16,578</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col3\" class=\"data row4 col3\" >533</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col4\" class=\"data row4 col4\" >14,526</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col5\" class=\"data row4 col5\" >440</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col6\" class=\"data row4 col6\" >1,766,819</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col7\" class=\"data row4 col7\" >62,566</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col8\" class=\"data row4 col8\" >26,510</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col9\" class=\"data row4 col9\" >939</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col10\" class=\"data row4 col10\" >3.54%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col11\" class=\"data row4 col11\" >3.15%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col12\" class=\"data row4 col12\" >0.84%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col13\" class=\"data row4 col13\" >83</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col14\" class=\"data row4 col14\" >0.71%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row4_col15\" class=\"data row4 col15\" >97</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col0\" class=\"data row5 col0\" >2020-12-09</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col1\" class=\"data row5 col1\" >281</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col2\" class=\"data row5 col2\" >12,281</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col3\" class=\"data row5 col3\" >599</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col4\" class=\"data row5 col4\" >14,757</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col5\" class=\"data row5 col5\" >340</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col6\" class=\"data row5 col6\" >1,750,241</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col7\" class=\"data row5 col7\" >62,033</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col8\" class=\"data row5 col8\" >26,261</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col9\" class=\"data row5 col9\" >931</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col10\" class=\"data row5 col10\" >3.54%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col11\" class=\"data row5 col11\" >2.69%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col12\" class=\"data row5 col12\" >0.86%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col13\" class=\"data row5 col13\" >81</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col14\" class=\"data row5 col14\" >0.55%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row5_col15\" class=\"data row5 col15\" >126</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3level0_row6\" class=\"row_heading level0 row6\" >7</th>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col0\" class=\"data row6 col0\" >2020-12-08</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col1\" class=\"data row6 col1\" >280</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col2\" class=\"data row6 col2\" >14,718</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col3\" class=\"data row6 col3\" >189</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col4\" class=\"data row6 col4\" >15,843</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col5\" class=\"data row6 col5\" >272</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col6\" class=\"data row6 col6\" >1,737,960</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col7\" class=\"data row6 col7\" >61,434</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col8\" class=\"data row6 col8\" >26,077</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col9\" class=\"data row6 col9\" >922</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col10\" class=\"data row6 col10\" >3.53%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col11\" class=\"data row6 col11\" >2.02%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col12\" class=\"data row6 col12\" >0.93%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col13\" class=\"data row6 col13\" >75</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col14\" class=\"data row6 col14\" >0.45%</td>\n",
       "                        <td id=\"T_18d450f6_5c37_11eb_beaf_3af9d3d753e3row6_col15\" class=\"data row6 col15\" >155</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f7f6ac90990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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6/vrr9eSTT/qzWQAABJTVZte0v+fI5Za+3V+uSSOp1QEAABqP1WbXik0FWr/9iPec2wj9oqQ1+S3s2L59u1JTU5Wbm1vnuj59+nj3Yy8vL9edd96p5557TpKUnZ2tlJQUjR492l9NAQAgqKzeUsh2swAAoElYbXb9fuFeOVy1dwMLM6lFLaH129azS5YsUVpammJjY097uzfeeEPXXHON4uPjJUk7duzQsmXLlJSUpKeeekpHjx71V5MAAAg4q82uT74q9h63hOrnAAAgcP79RUGdoMMcJk2+Ja5Ffdnit5kd06dP93mb0tJSLVmyRCtXrvSei4mJ0aRJk3T11Vdr9uzZev755zVr1qwz/rnZ2dln1d5TyczM9OvjhRr6xzf6yDf6yDf6yLfm0EffF0qrvw6T2zDJU/vcUL8eLh0r2KXMgkC3rnn55JNPNG/ePJWXl+vnP/+5UlNTtXHjRr344ouqrKzUqFGjvMtgrVarnnnmGdntdsXHx2vatGmyWCw6ePCgkpOTVVhYqJ49e2rmzJlq27atSkpK9NRTT+mHH35QdHS05s6dq5iYmAA/YwAAGu6b3DJ9/PUR73FLq9NRU5MWKF2xYoWGDh3qrc8hSfPnz/defuCBBzRs2LAGPWbfvn0VGRnpl/ZlZmZqwIABfnmsUET/+EYf+UYf+UYf+dYc+shqs+tv6XtV5fR8s2IySRGWMN09/OJGH2xUVlb6/cuAQPrhhx+Ulpamf/3rX+rYsaMmTpyoDRs2KC0tTYsWLVLXrl318MMPa8OGDRoyZIiSk5P1wgsvqF+/fpo6daqWLFmicePGadq0aRo3bpwSExM1f/58LViwQMnJyZo7d67i4+P15ptvKj09XdOnT9fcuXMD/bQBAGgQq82uV5ft9x6bJI24JlqP3do9cI0KIL8tYzkT69at08033+w9Li0t1d/+9jfvsWEYMpvNTdkkAAAaRVZOmTfokKT+vaL04v0XtbhvVfzho48+0s0336wuXbooPDxcc+bMUevWrdWjRw91795dFotFSUlJysjI0IEDB1RRUaF+/fpJksaOHauMjAw5HA5t3bpVI0aMqHVektavX6+kpCRJ0ujRo/XZZ5/J4XAE5LkCAHA2rDa7Ut7aK9thzzb3JpMUEd4ytpg9lSab2WEYhr755hv179/fe65NmzZ666231L9/f1111VV67733GjyzAwCAYFTlcHsvR4abdO9NXQg6zpLNZlN4eLgeeeQRHTp0SNdff70uvvjiWktNYmNjlZeXp8OHD9c6HxMTo7y8PBUXFysqKkoWi6XWeUm17mOxWBQVFaWioiJ17ty5CZ8lAABnb92XRSdmk8rzJUtLH3s0atjx4IMP6vHHH9cVV1yhoqIihYeH11pyYjabNXfuXD333HOqqKjQhRdeqJdeeqkxmwQAQKPbaSvTPz49LMmzVvbhRLaaPRcul0vbtm3TokWL1KZNGz366KNq1aqVTCaT9zaGYchkMsntdtd7vvrvmk4+rnmfsLCGTX7157Kh5lCPJtDoI9/oI9/oI9/oI9+CoY++L5TWbDGruj5YWJgU3+2IjhUcadE1wvwednzyySfeywsXLvRe7tixo/773//WuX18fLyWLVvm72YAABAwa7cVyTi+gsUwpJJyV2Ab1Mx16tRJgwcPVnS0Zyru0KFDlZGRUWvpa35+vmJjY9WlSxfl5+d7zxcUFCg2NlbR0dEqLS2Vy+WS2Wz23l7yzAopKChQly5d5HQ6Zbfb1b59+wa10V81xJpDPZpAo498o498o498o498C5Y+2vnRjzLkma1okkkjronWbcMDX6cj0EFQk9bsAAAg1O20lWmLtUSSZz/7cAtbzZ6rG264Qf/5z39UUlIil8ulzz//XCNHjlROTo5sNptcLpdWrVqlhIQExcXFKTIy0jvAWr58uRISEhQeHq74+HitXr1akpSenq6EhARJ0pAhQ5Seni5JWr16teLj4xUeHh6Q5woAQENYbXZt/fbEuKOl1+moqUl3YwEAIJRZbXb9fuE+OV1Gi97qzd+uuuoqPfDAAxo3bpwcDod+/vOf6+6779ZPf/pTPfbYY6qsrNSQIUM0cuRISdLMmTOVmpqqsrIyXX755ZowYYIkKS0tTSkpKXrttdfUtWtXzZ49W5L0xBNPKCUlRYmJiWrXrp1mzpwZsOcKAMCZqi5KWuU0ZJI08hrGHTURdgAA4CcfZRbJ6fKsXzEMKbZDBAMOP7njjjt0xx131Do3ePBgrVixos5te/furaVLl9Y5HxcXp0WLFtU53759e73++uv+aywAAE0gK6dMjhpb3DPuqI1lLAAA+IHVZtfabUXeY3MYy1cAAEDjaRURpupN7lk2WxdhBwAAfrD12xK5j484TJKGxXfg2xUAANAo1mwu0BurDkry1Opg57e6WMYCAIAfWG12SZ6gg+JgAACgMVhtdq3ZWqiPMou95wyx81t9CDsAADhHn2Ud0df7PGFHWBjfrgAAAP/zFELfK4fLqHU+zCSWsNSDZSwAAJwDq82u11bs9x4bBt+uAAAA/1u7rbBO0GEOkybfEseXLPVgZgcAAGfp5G9YTCYKhAEAAP+z2uy1lq6wxb1vhB0AAJyl7fvKTgQdkvr3itK9N3Vh0AEAAPxq/fYjtQqhj7gmWo/d2j2gbQp2hB0AAJylQ0WVkk4UJSXoAAAA/vZNbpk+y/LM6gg7PouUQui+EXYAAHAWvt5bqg+3HR94UJQUAAA0AqvNrpS39snpMli60kAUKAUAoIGsNrvmLP3Be0xRUgAA0BhWbymU8/iSWcOQYjtEEHScIWZ2AADQAFabXb9/a68cToqSAgCAxmO12fXxlzWLkjLeaAjCDgAAGiBjW+GJoEMUJQUAAI3j8+yjqt5o1iRpWHwHxhsNQNgBAMAZstrs+mjbiW9YLGaKkgIAgMZxuNhTCJ2ipGeHsAMAgDNgtdn1yrIf+IYFAAA0uszvSvSFtVR9ftJGA/ucpyt7RjHmaCAKlAIA4IOnEvpe5eYd32rW5Nlqlm9YAACAv1ltdqW9myOX29Ceg+UEHWeJsAMAAB+ycspUdVKdjhfvv4iBBwAA8Ltt35XK5fZcdrkMZeWUBbZBzRRhBwAAPhSVOLyXI8Kp0wEAABrPvkPHJHm+YGHHt7NH2AEAwGlk55Rp5aZCSZI5THo48QKCDgAA0Cg27zyqL6ylkqQwxh3nhAKlAACcgtVm18s1ipIahlRS7gpomwAAQOix2uxa91WRPtt+xHuOcce5IewAAKAe1UVJvbU6TEwlBQAA/me12ZW8cI9cNXINxh3njrADAIB61FeUlFodAADAn6w2u95YdaBW0CEx7vAHwg4AAOphqVHViqKkAADA306eRVot3My4wx8IOwAAOInVZtc7a3+URHEwAADQONZ9WVRrFunF3Vqr1wWtNfTqaMYdfkDYAQDASbZ8W+Ld314UBwMAAH5mtdm1dluR99hiNumR0XGEHH7E1rMAANRgtdm1ZVeJJCmM4mAAAKARfLWn1PvFiknSsPgOBB1+xswOAACOq7l21iRp5DXRTCUFAAB+t+fgMUmeoCMi3KSh/aMD26AQxMwOAACOq7V21iTFdogg6AAAAH618Zsj2rSzVBK1wRoTYQcAAPLM6sjYemLtrDmM5SsAAMC/rDa7Xk3f7z02qA3WaFjGAgCApI07j8p9fOc31s4CAAB/s9rs+v3CvXK4TswipTZY4/HrzI6ysjKNHj1a+/fvr3PdvHnzdMMNN2jMmDEaM2aMFi9eLEk6ePCg7rnnHo0cOVKPPvqo7Ha7P5sEAMAZ2b63TJJn4MHaWQAA4G/b95WdCDok9e8VpRfvv4gvVxqJ38KO7du36+6771Zubm6912dnZ2v27Nlavny5li9frnvuuUeSNG3aNI0bN04ZGRnq27evFixY4K8mAQBwRjK2Fmr3gXJJnh1YWDsLAAD87XBxlaQTRUnvvakL441G5LewY8mSJUpLS1NsbGy912dnZ+uNN95QUlKSnn/+eVVWVsrhcGjr1q0aMWKEJGns2LHKyMjwV5MAADgjy/6T773M2lkAAOBPVptds5d+rzXHa4NRlLRp+C3smD59uuLj4+u9zm63q0+fPkpOTtayZctUUlKiBQsWqLi4WFFRUbJYPKVDYmJilJeX568mAQDg06dfFev7w5UKM3lmdbB2FgAA+MuazQV66o09+iiz2HuOL1aaRpMUKG3btq0WLlzoPZ40aZKmTp2qcePGyWQy1brtyce+ZGdn+6WN1TIzM/36eKGG/vGNPvKNPvKNPvLNH330faG0cL1ZkmdK6dU93erfw9Cxgl3KLDjnhwcAAC1Ydk6ZXk0/IKPGOZP4YqWpNEnYcfDgQW3cuFF33HGHJMkwDFksFkVHR6u0tFQul0tms1n5+fmnXAZzKn379lVkZKRf2pmZmakBAwb45bFCEf3jG33kG33kG33km7/6KGvtIRnGYUmSIenyi+N02/Wdz/lxA62ystLvXwYAAIAz51m68kOtoCPMJI28JlpDr45mCUsT8OtuLKfSqlUr/eUvf9EPP/wgwzC0ePFiDRs2TOHh4YqPj9fq1aslSenp6UpISGiKJgEAoJxDnqKkbP0GAAD8xWqz6/dv7dWhoirvOXOYNGVMnB67rTtBRxNp1LDjwQcf1I4dOxQdHa3nn39ejz76qEaOHCnDMPTrX/9akpSWlqYlS5bo5ptv1rZt2/Sb3/ymMZsEAIAkKWtvqbZ+WyqJHVgAAID/rNlaKIfzxBazV18cpb881EujBnYKbMNaGL8vY/nkk0+8l2vW6RgxYoR315Wa4uLitGjRIn83AwCA01q+6URRDgqFAQAAf9hpK6tVjNRiZovZQGmSZSwAAASTnbYyZe2zS2IHFgAA4D+rNxd5L5skDYvvQNARIE1SoBQAgGBhtdmVsnCfHC5D5jBpRDyFwpqD8ePHq6ioyLtd/fPPPy+73a4XX3xRlZWVGjVqlJ588klJktVq1TPPPCO73a74+HhNmzZNFotFBw8eVHJysgoLC9WzZ0/NnDlTbdu2VUlJiZ566in98MMPio6O1ty5cxUTExPIpwsAaIa+yS3Tll0lkk58mTK0f3SAW9VyMbMDANCiZOWUyeHyrKM1DCm2QwRBR5AzDEO5ublavny598+ll16qqVOnasGCBVq9erWys7O1YcMGSVJycrL+8Ic/aO3atTIMQ0uWLJEkTZs2TePGjVNGRob69u2rBQsWSJLmzp2r+Ph4rVmzRnfeeaemT58esOcKAGierDa7Ut7ap9Jyl8xhnl1XXrz/IsYYAUTYAQBoUS7s3Mp7meUrzcO+ffskSZMmTdItt9yi9957T1lZWerRo4e6d+8ui8WipKQkZWRk6MCBA6qoqFC/fv0kSWPHjlVGRoYcDoe2bt3qrR9WfV6S1q9fr6SkJEnS6NGj9dlnn8nhcDT9EwUANFsfZhbKyZcpQYVlLACAFmXbd54dWBKuOF+3/jyGgUgzUFJSosGDB+vZZ5+Vw+HQhAkT9MADD9RaahIbG6u8vDwdPny41vmYmBjl5eWpuLhYUVFR3mUw1ecl1bqPxWJRVFSUioqK1Llz5zNuY3Z2tj+eqiQpMzPTb48Vqugj3+gj3+gj3+gj3zIzM/V9obR2q1meKh2GTCYpomq/MjP3B7p5LRphBwCgxdhpK9O/vyiUJG3eVaJbf05dhuagf//+6t+/v/f4jjvu0CuvvKIBAwZ4zxmGIZPJJLfbLZPJVOd89d81nXxc8z5hYQ2b/Nq3b19FRkY26D71yczMrPW8UBd95Bt95Bt95Bt95Ft1H+386EcZ8gToJpk04ppo3Ta8e4BbF3iBDstYxgIAaDHWbiuScfyyw2koK6csoO3Bmdm2bZs2bdrkPTYMQ3FxccrPz/eey8/PV2xsrLp06VLrfEFBgWJjYxUdHa3S0lK5XK5at5c8s0IKCjxbETudTtntdrVv374JnhkAoLmz2uz6wnpUkqcoaUQ4RUmDBWEHAKBFsNrs+nK3ZwkL2802L6WlpXrppZdUWVmpsrIyLVu2TL/97W+Vk5Mjm80ml8ulVatWKSEhQXFxcYqMjPR+m7R8+XIlJCQoPDxc8fHxWr16tSQpPT1dCQkJkqQhQ4YoPT1dkrR69WrFx8crPDw8IM8VANB8bN0nPfXGHu07VCGTKEoabFjGAgAIeVabXb9/a68cTkNhJs9ghO1mm48bbrhB27dv16233iq3261x48apf//+mjFjhh577DFVVlZqyJAhGjlypCRp5syZSk1NVVlZmS6//HJNmDBBkpSWlqaUlBS99tpr6tq1q2bPni1JeuKJJ5SSkqLExES1a9dOM2fODNhzBQA0D//7SZ6Wf2k+ccJEUdJgQ9gBAAh5WTllcjgN7zGDkebnN7/5jX7zm9/UOjd48GCtWLGizm179+6tpUuX1jkfFxenRYsW1Tnfvn17vf76635rKwAgtC37z2Et+ujHWufCTGLGaJBhGQsAIOT1uqC19zLLVwAAwNn6bMcRvb3m0PEjT6Frk0mafEscX6QEGWZ2AABC3hfWEknSL/qer9uuY7tZAADQcMv/m6/XVx2sccaQOcykybfEadTATgFrF+rHzA4AQEjLzi3TquPbzW75tiTArQEAAM3RTluZ3qgVdEi9Ohv6y0O9CDqCFGEHACCkrdlc6L3MdrMAAKChrDa7Zv3rBxk1zpnDpBsvczNbNIixjAUAELKsNru27/WEG2w3CwAAGspqs+v3C/fK4ToRdZjDPDU6Yi22ALYMvhB2AABCEtvNAgCAc7V2W6E36DBJ6n9xlO69qYv69GirzEzCjmDGMhYAQEhiu1kAAHAurDa7Psos9h5bzCZv0IHgR9gBAAhJl194YiDC8hUAANAQVptdr608IPfx701MkobFdyDoaEZYxgIACEn7DlZIkvr1itKEoXwLAwAAzsyazQWav+KAXG7PsckkRVhMGto/OrANQ4MQdgAAQo7VZtcbqw5Iknbm2gPcGgAA0BxYbXYt31Sgz7YfqbXzSv9eUSxfaYYIOwAAIeerPaXeaadOl2e7WQYoAADgVNZsLtC85SeWrVQzh4mgo5miZgcAIOS0jvT8ejOx3SwAAPDBarOfMuiYfEscQUczxcwOAEDI+f5wpSIsJv3q+lj179WOQQoAAKiX1WbX7Pd/qBV0sGV9aCDsAACElOycMn36dbEu69FW427qEujmAACAILX6+NIVo0bQUT2bY9TAToFrGPyCsAMAEDKsNrumvr1PDpeh7Fy7rDY738gAAIA6Vm8u0KvpB2qdu/piCpGGEmp2AABCRlZOmRwuz9czbrenMCkAAEBNO21lmre8dtBBIdLQQ9gBAAgZfS88MUChMCkAADiZ1WbXzCU/1Fq6YjJRiDQUsYwFABAycn+skCT1uyhKE4bx7QwAAPAEHFk5ZSo8WqVVm4uo0dFCEHYAAEKC1WbXgpWeKak7bfYAtwYAAASDNZsLNH/FAbncda+jRkdoI+wAAISErJwyuY8PZJwuT70OBi8AALRMVptdH24r1NptxTLquZ4aHaGPsAMAEBK6dYqUJJlEvQ4AAFqyNZsLNG/FAe+XICerXrpC0BHaCDsAACGhrMIlSRrzs05KuLI9AxgAAFoYq82utdsK9WE9sznMYdLY6zqpbWuLruwZxTihBfBr2FFWVqa77rpLr7/+urp161brunXr1unVV1+VYRjq1q2bXnzxRZ1//vlatmyZZs2apY4dO0qSrr/+ej355JP+bBYAoAX4ek+ZOrSz6KHRF8hkMgW6OQAAoAmdajZHmEkaeU20hl4dTcDRwvgt7Ni+fbtSU1OVm5tb57qysjI999xzev/999W5c2e9/PLLevXVV5Wamqrs7GylpKRo9OjR/moKAKCFMQxD274rVWz7cO36/hiDGQAAWgCrza6PMou0v6BC2TnH6p3NwU4rLZffwo4lS5YoLS1Nv/vd7+pc53A4lJaWps6dO0uSLr30Uq1cuVKStGPHDuXm5uqNN97QpZdeqmeffVbnn3++v5oFAGgB1n1ZrLJyl+zlLj399l69eP9FBB4AAISg6m1kv8+r0CdfH6n3NszmgOTHsGP69OmnvK5Dhw4aNmyYJKmiokJvvvmmxo8fL0mKiYnRpEmTdPXVV2v27Nl6/vnnNWvWLH81CwDQAqzeUihJMiQ5nOzEAgBAKPr3FwVasOKA3PVtr3IcszlQrUkLlJaWlmry5Mnq3bu3brvtNknS/Pnzvdc/8MAD3lDkTGVnZ/u1jZmZmX59vFBD//hGH/lGH/lGH/lW3UdVTmnvAbNMJkmGZ5ATUbVfmZn7A9tAAABwzqq3kN19sFx7D1ac8nbmMGlEPLM5cEKThR2HDx/W/fffr0GDBmnq1KmSPOHH+++/r/vuu0+SZ8212Wxu0OP27dtXkZGRfmljZmamBgwY4JfHCkX0j2/0kW/0kW/0kW81++idjINyuPJ1+y86qV0bKqxLUmVlpd+/DAAAoLFVL1E5r7VZ1u+PaX9BpXb9cEzGaWZyhJmkgX3O050JsS3+9z9qa5Kww+Vy6ZFHHtGoUaP0P//zP97zbdq00VtvvaX+/fvrqquu0nvvvdfgmR0AgJZrp61M/9qQL0la+UWhZlCrAwCAZsNqs2vdV0WemZlmk/79ReFpl6hUYxtZnIlGDTsefPBBPf744/rxxx+1c+dOuVwurV27VpJnRsb06dM1d+5cPffcc6qoqNCFF16ol156qTGbBAAIIZ98dcRbed1JrQ4AAIJOzUCj1wWttedQuYpLHHK4DH25u+yMwo1qLFVBQ/g97Pjkk0+8lxcuXChJuuKKK7Rr1656bx8fH69ly5b5uxkAgBZg36FySZLJJIVbTLqyZ1SAWwQAQMtVcxnKnkPlKjzq0LZvS+VqQKBxMnOYdO2l7dShXTghBxqkSQuUAgDgL5nflcj6/TFJnvW6DydewAAIAIBGcHKIUVziUId24ep1QWvtPliuyiq3JGn99iMNmqlRn+olKvZKt2SIgANnjbADANAsrdhU4L1sGFJJuSuArQEAILicHFCcvIykOqw4+ToZUs+urfXfr0368NtchYVJn2UdPecQoz41Z230uqC1Sspd1OCA3xB2AACaHcOQcn+skMkkmcQSFgBAcDhdwNCQsMHX5er79+zaWrsPHJPbLXWPjdS+gxUyDEOREWH6+MvicwwozJKOnnOfnBxo1Gw/szbQmAg7AADNzua9Jh0+4tCwAR0U1ymSb4EAAD7VDCI2ZZm08fsfzipgqD42jgcMuw+Uy+k0ZDY33gyI5oRlKAgWhB0AgGbFarPr39vDJEkbth/RjAfYbhYAQln1bh4NmQ3Rs2trfbf/mNwuQ3ExrZS1t1RZOfYaQUSYtK8okE+rGTDkmT/pUTPEONW/BctQEEwIOwAAzcrWb0tkHB+sOl1sNwsAzU19W5HWF1bstNlVcKRK39iONcJsCZPvm4SAk2dZNGQZzaas7xXTKYYQA80WYQcAoFk5UFApyUStDgAIQr6KYjpchr7aXXZOW5H6R+1ZC/50qoChMWp2nO525xpQxFpsGjCgu597B2g6hB0AgGbDarPr8x1HJRkKCzOx3WwL9Oc//1nFxcWaMWOGNm7cqBdffFGVlZUaNWqUnnzySUmS1WrVM888I7vdrvj4eE2bNk0Wi0UHDx5UcnKyCgsL1bNnT82cOVNt27ZVSUmJnnrqKf3www+Kjo7W3LlzFRMTE+BnCgS3+kINc5hJ/95SKLc70K07tTCTdPsvOil3f5531kIwBQwA/IewAwDQbHy6vVieLwNNbDfbAm3atEnLli3T9ddfr4qKCk2dOlWLFi1S165d9fDDD2vDhg0aMmSIkpOT9cILL6hfv36aOnWqlixZonHjxmnatGkaN26cEhMTNX/+fC1YsEDJycmaO3eu4uPj9eabbyo9PV3Tp0/X3LlzA/10gaBSvfTEMCSzSVq9tajJQo3q3TwkndNsiJrFMjMzf2TWAhDiCDsAAM1GUYlDkmSSoXBLGEtYWpAjR45ozpw5euSRR7Rr1y5lZWWpR48e6t7d82ElKSlJGRkZ6tWrlyoqKtSvXz9J0tixY/XKK6/ozjvv1NatWzV//nzv+XvvvVfJyclav369Fi9eLEkaPXq0nn/+eTkcDoWHhwfkuQLBoGZR0PIqt7bvs3vrJZ2r+rYiPZOAAgAagrADANAsZO0t1dZvS3VJXGv16FCmUdddzOC3BfnDH/6gJ598UocOHZIkHT58uNZSk9jYWOXl5dU5HxMTo7y8PBUXFysqKkoWi6XW+ZMfy2KxKCoqSkVFRercuXNTPT0gYE4uFpptO6bDxZXaeQ5FQX0VxSS8ANAUCDsAAEHParPrmXdy5HQZyvmxQtdfYjBQbkH+9a9/qWvXrho8eLA++OADSZLb7ZbJdKK4oGEYMplMpzxf/XdNJx/XvE9YWFiD2pidnd2g259OZmam3x4rVNFHvp2uj74vlL6ymXT0mLT7xzDVzjROVbSzbvIRZpJ+frFLFU7PfS5ob+hYlUk9Ywz9pOOPtW4bW2PFyLGCw8osOLPn0Zh4HflGH/lGHwUvwg4AQNDLyimT83jpfpfbUE5+y9gyEB6rV69Wfn6+xowZo6NHj+rYsWM6cOCAzGaz9zb5+fmKjY1Vly5dlJ+f7z1fUFCg2NhYRUdHq7S0VC6XS2az2Xt7yTMrpKCgQF26dJHT6ZTdblf79u0b1Ma+ffsqMjLynJ9rZmamBgwYcM6PE8roI99q9tHJhUQLjzq09dvSBs/aMIeZai09ae6FOHkd+UYf+UYfnV6ggyDCDgBA0OvWyfMhsnq72Z4xAd+zEE3onXfe8V7+4IMPtGXLFk2bNk3Dhw+XzWZTt27dtGrVKt1+++2Ki4tTZGSkdwC6fPlyJSQkKDw8XPHx8Vq9erWSkpKUnp6uhIQESdKQIUOUnp6uRx55RKtXr1Z8fDz1OtDsWW12LdmQp827Ss+q1sbJRUFZegKguSHsAAAEvS3flkiSru/XXkmDOulYwa4AtwiBFhkZqRkzZuixxx5TZWWlhgwZopEjR0qSZs6cqdTUVJWVlenyyy/XhAkTJElpaWlKSUnRa6+9pq5du2r27NmSpCeeeEIpKSlKTExUu3btNHPmzIA9L+BcWG12fbitUN/sC9P+oj31LDyp61TFQgk3ADR3hB0AgKD2TW6ZPtxWLEna+M1RJQ3qFOAWIZDGjh2rsWPHSpIGDx6sFStW1LlN7969tXTp0jrn4+LitGjRojrn27dvr9dff93/jQWaiNVm10dfFmnt1qLjy1NOX3OmZsBBqAEgVBF2AACC2rovi72XHU5DWTll6tUugA0CgACr3kHF7Tbkcksff1l82hocYSbp9l+c2B2FgANAS0DYAQAIasVlDkmewXq4xaQre0bpWBBU8QeAQLDa7EpeuEcu1+luZdQqKEq4AaAlIuwAAAStrL2l+nJ3mXp3b6NBl53nrfwfDFsWAkBTqp7Nkflt6SmDjjCTNLB3Ozkrj+ju4ZcScABo0Qg7AABByWqz65l3cuR0Gdp7sFwPJV7AwB1Ai2S12ZX85h653Ke+jTlMmnxLnEYN7KTMzEzeLwG0eIQdAICglJVTJqfLswjd5fbU6mDwDqCl+Sa3TDP/9UOdoOOSbq3V6wLPn5Jyl3fmGwDAg7ADABCUel3Q2nu5ulYHAIQ6q82urJwyndfarM27SrR5V2md24SbTXpkdBzhBgCcBmEHACAobd9bJkn6+eXn6fZfxDKoBxDy1mwu0PwVB065XKV6NgcFRwHAN8IOAEDQsdrsWvp5viRp63eluv0XsQFuEQA0HqvNrjVbC/VRZvEpb2MOE7M5AKABCDsAAEFn/fYjMjzlOuR0Uq8DQOiy2uxKeWuvqpzGKW8TZvIUH+V9EADOHGEHACCoWG12Ze4ukeQZ4FOvA0AoW7O1sE7QYQ6Txl7XSfZKt2SIZSsAcBYIOwAAQaPmN5wmkzTymmgG+QBCVnZOWa2lK+YwaUQ873sA4A+EHQCAoJGVU+b9htMkKbZDBAN+ACHJarNr5r++9x6bJI24JlqP3do9cI0CgBBC2AEACBptW5m9l1m+AiDUVG8re6TMqeUbC7y1iUwmKcJi0tD+0YFtIACEEMIOAEBQsNrsemPVQUmeWh0PJ17ArA4AIeN0hUj794rSvTd14T0PAPwoLNANAABA8ixhcbpOfAgoKXcFsDUA4F9rt9UtRCp56nQQdACA/zGzAwAQFLpGR0ryrFtnCQuAUGG12bVma2GtQqTVzGFsKQsAjYWwAwAQcFabXSs2Fcgk6c4hsRrU5zwG/wCavTWbCzRvxQG53SfOmSQNuqydLu3eVlf2jOK9DgAaiV+XsZSVlWn06NHav39/neusVqvGjh2rESNG6JlnnpHT6ZQkHTx4UPfcc49GjhypRx99VHa73Z9NAgAEuep17N/k2mUyiaADQEiw2uyat7xu0BERbtKdCZ31q+s7814HAI3Ib2HH9u3bdffddys3N7fe65OTk/WHP/xBa9eulWEYWrJkiSRp2rRpGjdunDIyMtS3b18tWLDAX00CADQDWTllchxfx24cPwaA5u5/P8mTu0aJjjCTNOraaL14/0WEHADQBPwWdixZskRpaWmKjY2tc92BAwdUUVGhfv36SZLGjh2rjIwMORwObd26VSNGjKh1HgDQclzZM8rzdaeo1QGg+bPa7Er9615t+67Uey7MJE0ZE6fHbutO0AEATcRvNTumT59+yusOHz6smJgY73FMTIzy8vJUXFysqKgoWSyWWucbIjs7++wafAqZmZl+fbxQQ//4Rh/5Rh/51pL6KDNXMgyLftLRrZFXunWsYJcyC87gfi2ojwA0D1abXb9fuFeOGjtLmSSNvDZaowZ2ClzDAKAFapICpW63WyaTyXtsGIZMJpP375pOPvalb9++ioyM9Es7MzMzNWDAAL88Viiif3yjj3yjj3xrSX1ktdm1/P09kqQfj5rV+9JLzuhbz5bUR2ejsrLS718GAPBt23eldYKOiHCThvaPDlyjAKCFapKwo0uXLsrPz/ceFxQUKDY2VtHR0SotLZXL5ZLZbFZ+fn69y2AAAKHpy92l3jXtTpehrJwypngDaHasNruycsq0dddRSZ6Qw2KWhg2I1tCro3lfA4AAaJKwIy4uTpGRkd5v4pYvX66EhASFh4crPj5eq1evVlJSktLT05WQkNAUTQIABBGTiXodAJqn5f/N15v/Pli7GGmY9GhSHEtXACCA/Lr17MkefPBB7dixQ5I0c+ZMvfjiixo5cqSOHTumCRMmSJLS0tK0ZMkS3Xzzzdq2bZt+85vfNGaTAABBZNt3pWoVYdLIa9ihAEDzs/7rYr2+qnbQIUmGIZWUuwLTKACApEaY2fHJJ594Ly9cuNB7uXfv3lq6dGmd28fFxWnRokX+bgYAIMht3nlUu344Jkn65KtiDbuaNe0Amo/te0v18rL9dc4zUw0AgkOTLGMBAOBkqzYXei87nNTrANB8rN5coHnpB1RzQoc5TBp7XSe1bW3RlT2jeD8DgAAj7AAABMSBgkqZTJ5CfnwLCqC5sNrsmre8dtBx9cVRuvemLgQcABBECDsAAE1u3ZdFOlRUpeuvPF8Xdm3Nt6AAmgWrza65H/wgo0bSYQ4TQQcABKFGLVAKAMDJrDa75r7/gyRp484Sgg4AzYLVZtfvF+7V94crvefMYdLkW+J4DwOAIMTMDgBAk/p6b5lcbs9lp4taHQCah4ythXK4PFM6TJL6s3QFAIIaMzsAAE0qItwkiR0LADQfVptdH2UWe48tZhNBBwAEOWZ2AACa1LZvS2UxS0Ov7qDhAzryYQFA0FufdcRbkNQkaVh8B967ACDIMbMDANBkMr8r1dd7y+R0SZ9+fSTQzQEAn6w2u7ZYj0qSwkye2WlD+0cHuFUAAF+Y2QEAaDIrNuV7Lzuc1OsAENzWbC7QvOUH5DY8QcfIa6I19Opo3rcAoBkg7AAANAnDMJT7Y4VMJs80cOp1AAhm739+WG+tPuQ9NiTFdogg6ACAZoKwAwDQJFZuKtThIw4NvbqDusVEsuUsgKBktdm19LPD2rizpNb5MJMIaAGgGaFmBwCg0Vltdr2x6oAk6bOsIwQdAIKS1WbX7xfurRN0mEzS5FvieN8CgGaEsAMA0Oi+sJbIfXwrA6fLU6sDAILNl7tL5XAZtc6Zw6THxsRp1MBOAWoVAOBsEHYAABqdLa9ckufbUWp14Gy9/PLLuvnmm5WYmKh33nlHkrRx40YlJSVp+PDhmjNnjve2VqtVY8eO1YgRI/TMM8/I6XRKkg4ePKh77rlHI0eO1KOPPiq73S5JKikp0UMPPaRRo0bpnnvuUX5+ft0GIOTtO3T8vUpSuFm6+dpo/eWhXgQdANAMEXYAABpVdk6ZNu8qleRZ8/5w4gVMBUeDbdmyRV988YVWrFih999/X4sWLdKuXbs0depULViwQKtXr1Z2drY2bNggSUpOTtYf/vAHrV27VoZhaMmSJZKkadOmady4ccrIyFDfvn21YMECSdLcuXMVHx+vNWvW6M4779T06dMD9lwRGNu+LfEuXwkLkx5NitNjt3Xn/QoAminCDgBAo1q9pdB72TCkknJXAFuD5uraa6/V3//+d1ksFhUWFsrlcqmkpEQ9evRQ9+7dZbFYlJSUpIyMDB04cEAVFRXq16+fJGns2LHKyMiQw+HQ1q1bNWLEiFrnJWn9+vVKSkqSJI0ePVqfffaZHA5HQJ4rmp7VZtfspT94j3mvAoDmj7ADANBorDa7svZ66nOEsYQF5yg8PFyvvPKKEhMTNXjwYB0+fFgxMTHe62NjY5WXl1fnfExMjPLy8lRcXKyoqChZLJZa5yXVuo/FYlFUVJSKioqa8NkhUKw2u363cK+KyzxLnVhuBwChga1nAQCNwmqz6/dv7ZXDaSjMJI28JlpDr45mSjjOyeOPP64HH3xQjzzyiHJzc2UymbzXGYYhk8kkt9td7/nqv2s6+bjmfcLCzvw7oezs7AY+k1PLzMz022OFKn/20XqrSU5XmDyVOgxdFGvoxsvcOlawS5kFfvsxTY7XkW/0kW/0kW/0UfAi7AAANIqsnDI5nCd2NYjtEEHQgbO2d+9eVVVVqU+fPmrdurWGDx+ujIwMmc1m723y8/MVGxurLl261CowWlBQoNjYWEVHR6u0tFQul0tms9l7e8kzK6SgoEBdunSR0+mU3W5X+/btz7h9ffv2VWRk5Dk/z8zMTA0YMOCcHyeU+buPNn7/g6QimSRFhIfpf267qNm/V/E68o0+8o0+8o0+Or1AB0EsYwEANIpLu7fxXmZKOM7V/v37lZqaqqqqKlVVVenjjz/WXXfdpZycHNlsNrlcLq1atUoJCQmKi4tTZGSkd5C1fPlyJSQkKDw8XPHx8Vq9erUkKT09XQkJCZKkIUOGKD09XZK0evVqxcfHKzw8PCDPFU1np61Ma7Z6liuFhVFAGQBCCTM7AACN4us9nlodA/ucp18NieUDBM7JkCFDlJWVpVtvvVVms1nDhw9XYmKioqOj9dhjj6myslJDhgzRyJEjJUkzZ85UamqqysrKdPnll2vChAmSpLS0NKWkpOi1115T165dNXv2bEnSE088oZSUFCUmJqpdu3aaOXNmwJ4rms66zGIZxyegUZQUAEILYQcAwO+sNruWbDgsSfpqT6l+NSQ2wC1CKHjsscf02GOP1To3ePBgrVixos5te/furaVLl9Y5HxcXp0WLFtU53759e73++uv+ayyahUOFlZIooAwAoYiwAwDgdx9/deLbUqfTUFZOGTM7AASVTTuPanuOXf16RanfRVG6smcU71MAEEKo2QEA8Curza6v95ZK4ttSAMFp5cZ8/XFRrgxD+ibXTtABACGImR0AAL+x2uxKeWuvqpyGTGw3CyDIWG12/XtzoT7+qth7zuli9hkAhCLCDgCA39TcbtYktpsFEDxqhrE1hZnE7DMACEEsYwEA+E3fC08EGyxfARBMsnLK6gQd5jBp8i1xhLIAEIKY2QEA8JvdB8plSLrqp1GaOLwLHyAABA17udN7OdwsDRvAMjsACGWEHQAAv7Da7Fr474Oey9/bA9waADjBarNr6ecFkjyzOR5NitOogZ0C3CoAQGNiGQsAwC+2fVcqd/V2s8cL/gFAMPj06xPbYRuGVFLuCmyDAACNjrADAOBXJrabBRBErDa7vtzNdtgA0NKwjAUAcM6sNrv+k31EbSLDdOeQWF310yjWwQMIOLbDBoCWy29hx8qVK/Xaa6/J6XRq4sSJuueee7zXWa1WpaSkeI+Liop0/vnna9WqVVq2bJlmzZqljh07SpKuv/56Pfnkk/5qFgCgkdX8MBEWJoIOAEGj5g4sbIcNAC2LX8KOvLw8zZkzRx988IEiIiJ01113aeDAgerVq5ckqU+fPlq+fLkkqby8XHfeeaeee+45SVJ2drZSUlI0evRofzQFANDEsnLK5Dj+YcIwPMd8mAAQDCIsJu9llq8AQMvil5odGzdu1KBBg9S+fXu1adNGI0aMUEZGRr23feONN3TNNdcoPj5ekrRjxw4tW7ZMSUlJeuqpp3T06FF/NAkA0ESu7Bnl+cpUfJgAEDysNrveXnNIkhQWJj2ceAFBLAC0IH6Z2XH48GHFxMR4j2NjY5WVlVXndqWlpVqyZIlWrlzpPRcTE6NJkybp6quv1uzZs/X8889r1qxZZ/yzs7Ozz63xJ8nMzPTr44Ua+sc3+sg3+si35tRH23Ikw7CoR0e3Rlzp1rGCXcosaPyf25z6CEDT+2pPqVzu4wfswAIALY5fwg632y2T6cQ0QcMwah1XW7FihYYOHeqtzyFJ8+fP915+4IEHNGzYsAb97L59+yoyMvIsWl1XZmamBgwY4JfHCkX0j2/0kW/0kW/NqY+sNrtWvL9HknToqFm9L72kSb45bU59FAiVlZV+/zIAaHaOj0XZIQoAWia/LGPp0qWL8vPzvcf5+fmKjY2tc7t169bp5ptv9h6Xlpbqb3/7m/fYMAyZzWZ/NAkA0AQ2WY/K7SnXIafLUFZOWWAbBADyBLHrMovUrnWYJgzrohfvv4glLADQwvgl7PjZz36mTZs2qaioSOXl5frwww+VkJBQ6zaGYeibb75R//79vefatGmjt956S9u3b5ckvffeew2e2QEACJzd+8sl8c0pgOBhtdn1+7f26lBRlY5VutkhCgBaKL8sY+ncubOefPJJTZgwQQ6HQ3fccYeuvPJKPfjgg3r88cd1xRVXqKioSOHh4bWWnJjNZs2dO1fPPfecKioqdOGFF+qll17yR5MAAI1s27cl+nqvZyZHmInifwCCQ1ZOmZzsEAUALZ5fwg5JSkpKUlJSUq1zCxcu9F7u2LGj/vvf/9a5X3x8vJYtW+avZgAAmsg/1x/2XjYo/gcgSHh3iDKYcQYALZnfwg4AQMuxeedR7bTZZTJ5PlPwgQJAsIhpHyHDkK7uFaV7h3ZhVgcAtFCEHQCABrHa7Hp+ca7chmQ2SyMGRGvo1dF8oAAQFJb9xzPrbOgA3pcAoCXzS4FSAEDLsXxjvtxuz2XDLcV2iOADBYCg8P5nefrgPwWSpJc/+EFWmz3ALQIABAphBwDgjFltdn2WddR7bA5j+QqA4JD5XaneWvOj97jKyXbYANCSEXYAAM7Yh5lFMo5fNkkaFt+BWR0AAi47p0x//qet1rkwkwhjAaAFo2YHAOCMfJNbpk3feGZ1hJk8RUmH9o8OcKsAtHRWm10pb+2Vy33inDlMmnxLHGEsALRghB0AAJ88Hyb2yekyZA6TRsRTlBRAcPhqT6k36DBJ6n9xlO69iV1YAKClI+wAAPi0fV+ZnC7PAhbDoCgpgOBhsZgkSSaTFGExEXQAACQRdgAAzkBxqUOS51vTcAtFSQEEj627ShRhMemm/h00jO1mAQDHUaAUAHBaVptdK78olCSFhUkPJ17AhwkAQWHbtyXKzj2mKqehT74uDnRzAABBhLADAHBan35dLOP4FiyGIZWUuwLbIAA47sNtRd7LDraaBQDUQNgBADglq82ubd+VSjqxAwtLWAAEi5JjTkm8PwEA6qJmBwCgXtXbOVY5DYWZpJHXsAMLgODhcLr13YFyDerTTr1/0lZX9ozi/QkA4EXYAQCoV1ZOmaqchveYHVgABJN/by5UeaVbfS+M0u0JsYFuDgAgyLCMBQBQvxM5B9PDAQQVq82uhf8+KEn6+0c/ymqzB7hFAIBgQ9gBAKjDarPr7x/9KEkyswMLgCCzeVeJ3McDWaeLwqQAgLoIOwAAdaz7qsj7QYIdWAAEm32HyiVJJgqTAgBOgbADAFBL1r5Sbdh+RBI7HAAIPjmHpa3fntgliplnAID6UKAUAOBltdk19e19crk9y1dGxLMDC4Dgsi33xHd1zDwDAJwKMzsAAF4ffH5YLrfnsmGwAwuA4HP0mOdvZp4BAE6HsAMAIEnKzi3Tf74p8R6bw/gQgeAxb948JSYmKjExUS+99JIkaePGjUpKStLw4cM1Z84c722tVqvGjh2rESNG6JlnnpHT6ZQkHTx4UPfcc49GjhypRx99VHa7ZwePkpISPfTQQxo1apTuuece5efnN/0TxBnJ/K5EtkKT+v20rSYM76IX77+IQBYAUC/CDgCArDa7Xl2233tskjQsvgMfIhAUNm7cqP/85z9atmyZ0tPT9c0332jVqlWaOnWqFixYoNWrVys7O1sbNmyQJCUnJ+sPf/iD1q5dK8MwtGTJEknStGnTNG7cOGVkZKhv375asGCBJGnu3LmKj4/XmjVrdOedd2r69OkBe644NavNruf+nivDMOmb74/pyp5RvEcBAE6JsAMAWjirza6Ut/bq+8OVkjy7G0SEmzS0f3SAWwZ4xMTEKCUlRREREQoPD9dFF12k3Nxc9ejRQ927d5fFYlFSUpIyMjJ04MABVVRUqF+/fpKksWPHKiMjQw6HQ1u3btWIESNqnZek9evXKykpSZI0evRoffbZZ3I4HAF5rji1rJwyOV2ebaJcbDcLAPCBAqUA0MJl5ZSpyun5AGGS1L9XlO69qQvfmCJoXHzxxd7Lubm5WrNmje69917FxMR4z8fGxiovL0+HDx+udT4mJkZ5eXkqLi5WVFSULBZLrfOSat3HYrEoKipKRUVF6ty58xm3MTs7+5yeY02ZmZl+e6xQEl4pSWZJngLKEVX7lZm5/7T3acl4HflGH/lGH/lGHwUvwg4AaOFK7E7v5YhwE0EHgtbu3bv18MMP63e/+53MZrNyc3O91xmGIZPJJLfbLZPJVOd89d81nXxc8z5hYQ2b/Nq3b19FRkY26D71yczM1IABA875cUJRzOEKLVz/rS67wK0HbrmE96nT4HXkG33kG33kG310eoEOgljGAgAt2De5ZVr2nwJJnm9KH068gA8QCEqZmZm677779P/+3//Tbbfdpi5dutQqJJqfn6/Y2Ng65wsKChQbG6vo6GiVlpbK5XLVur3kmRVSUOD5f+B0OmW329W+ffume3I4I1n7PMtWRlzp5n0KAOATYQcAtGCLP86TcfyyYUgl5a6Atgeoz6FDhzR58mTNnDlTiYmJkqSrrrpKOTk5stlscrlcWrVqlRISEhQXF6fIyEjvt0nLly9XQkKCwsPDFR8fr9WrV0uS0tPTlZCQIEkaMmSI0tPTJUmrV69WfHy8wsPDm/6J4rT+u+OI2kSGqawi0C0BADQHLGMBgBbqm9wyfbXnRIE/tppFsHr77bdVWVmpGTNmeM/dddddmjFjhh577DFVVlZqyJAhGjlypCRp5syZSk1NVVlZmS6//HJNmDBBkpSWlqaUlBS99tpr6tq1q2bPni1JeuKJJ5SSkqLExES1a9dOM2fObPonidP6ek+pvt7n2Sr4b5+b1ae3ndkdAIDTIuwAgBbqg/+cmOrPVrMIZqmpqUpNTa33uhUrVtQ517t3by1durTO+bi4OC1atKjO+fbt2+v1118/94aiUVhtdr1SY2tsp8tTWJn3KwDA6RB2AEALtPXbEm3ZVSKTPFvNhlvYahZA8KneGtu7Y5RJsoSJWWgAAJ8IOwCghbHa7Hru3Ry5DclslkYMiNbQq6P5lhRA0Fn3ZVGdrbHjux3h/QoA4BNhBwC0MEs2HJb7eFVSwy3FdojggwOAoGO12bV2W5H32GL2bI19rOBI4BoFAGg2/LYby8qVK3XzzTdr+PDhWrx4cZ3r582bpxtuuEFjxozRmDFjvLc5ePCg7rnnHo0cOVKPPvqo7Ha7v5oEADjJjn2l+sJa4j2mKCmAYLV9X5lcbs9l6goBABrKLzM78vLyNGfOHH3wwQeKiIjQXXfdpYEDB6pXr17e22RnZ2v27Nnq379/rftOmzZN48aNU2JioubPn68FCxYoOTnZH80CANRgtdk1a+kP3mM+PAAIZp3bR0jyvFdFhFNXCADQMH6Z2bFx40YNGjRI7du3V5s2bTRixAhlZGTUuk12drbeeOMNJSUl6fnnn1dlZaUcDoe2bt2qESNGSJLGjh1b534AgHNntdn1+4V7lVfskOQp8seHBwDBrLjMKUm6IyFGL95/EcEsAKBB/BJ2HD58WDExMd7j2NhY5eXleY/tdrv69Omj5ORkLVu2TCUlJVqwYIGKi4sVFRUli8UzwSQmJqbW/QAA/pGVUyaHq3aRPz48AAhmmbtL1D02UpNGXcB7FQCgwfyyjMXtdstkMnmPDcOoddy2bVstXLjQezxp0iRNnTpV48aNq3U7SXWOfcnOzj7LVtcvMzPTr48Xaugf3+gj3+gj3/zdR5VHJc9bviGLWYrvdkTHCo4os8CvP6ZJ8ToCQtf2vaXavrdMP7v8/EA3BQDQTPkl7OjSpYu2bdvmPc7Pz1dsbKz3+ODBg9q4caPuuOMOSZ4wxGKxKDo6WqWlpXK5XDKbzXXudyb69u2ryMhIfzwNZWZmasCAAX55rFBE//hGH/lGH/nWGH30We73kop1Q78OShrUqdl/S8rr6PQqKyv9/mUA0FSsNrtS38mRyy1t2lkiq83e7N+zAABNzy/LWH72s59p06ZNKioqUnl5uT788EMlJCR4r2/VqpX+8pe/6IcffpBhGFq8eLGGDRum8PBwxcfHa/Xq1ZKk9PT0WvcDAJy7HftK9eG2YknSxm+OBrg1AHB6WTllch5fdud2G8rKKQtwiwAAzZFfwo7OnTvrySef1IQJE3Trrbdq9OjRuvLKK/Xggw9qx44dio6O1vPPP69HH31UI0eOlGEY+vWvfy1JSktL05IlS3TzzTdr27Zt+s1vfuOPJgEA5PmGdHaNHVgcTj44AAhul/2kjfdyuIXtsQEAZ8cvy1gkKSkpSUlJSbXO1azTMWLECO+uKzXFxcVp0aJF/moGAOC4NZsLNG/5Abk9X5DKZOKDA4Dg992BcklS/CXtNO7GzixhAQCcFb+FHQCA4GC12fXRl0XK2Fokwzhxvn+vKN17Uxc+OAAIWlabXX9dc0iSlLWvTONu7BzgFgEAmivCDgAIIVabXSlv7VWV06h13hwmgg4AQe/rfWXe2WhOl2fZHe9bAICz4ZeaHQCA4LDyi4J6g47Jt8TxgQFA0GvfxiyJZXcAgHPHzA4AaOasNrvWfVUk248V+sZ2zHveHCaNiI/W0KujCToANAt5RxwymaS7b+is+Eva8d4FADhrhB0A0IydXIS0mknSiGui9dit3QPSLgA4G59lHVFs+3CCDgDAOWMZCwA0Q1abXa988INePUXQERFu0tD+0QFpGwCcjY3fHNGhoiodLnbo6bf3ymqzB7pJAIBmjJkdANDMnKoIqcTSFQDN15otRZIkQ5LDSXFSAMC5IewAgGbmvXU/1gk6wkzSwD7n6c6EWD4cAGiWfiyqlMnkmZ1GcVIAwLki7ACAZuLrvaVasPyAfsiv9J5jJgeAULBh+xHtL6jSz/uep4vj2ujKnlG8pwEAzglhBwAEMavNrqycMh0oqNRHmcW1rqMIKYBQYLXZ9ZclNknS1l2luv06ZqgBAM4dYQcABKk1mws0f8UBudx1r6MIKYBQkZVT5n2fc7qo1QEA8A/CDgAIMt8XSh//06b1Xx9R3RKknvocI69h6QqA0HBh51aSqNUBAPAvwg4ACALVy1X251do3ZdmSUfqvZ05TJp8S5xGDezUpO0DgMZScswlSRo9uKNuuKoDIS4AwC8IOwAggKw2u5ZsyNOWXaVy1zeNQ56AY+x1ndS2tYWifQBCzidfFatVRJiGXNme9zcAgN8QdgBAE7Pa7Fr3VZEKjzq09dv6Qg6TJJarAAh92bll+npvmSTpmb/u04v3X8T7HQDALwg7AKCJWG12fbitUB9mFp9yFoeHIXOYieUqAEJexpYi72WHk+KkAAD/IewAgEZUc+vYdV8WyzhNyBFmkm7/RScdKcrTqOsuZcAPIOTtz6+U5Hn/ozgpAMCfCDsAwI+ql6jIkEwmac2WotPO4jCHSdde2k4d2oV7l6tkZv5I0AEg5G3YXqxv9x/TwN7t1KdHW2oSAQD8irADAM5RdcBRXOLQlm9L5XKf/vZhJmlg79oBBwC0JFabXS8t+V6S9NWeMv3q+s68FwIA/IqwAwAaqGa44Takbd+WynXaGhwnsHUsAEibd5XIfTwYdrqo1QEA8D/CDgA4hZpLUi66oLW+sR3ToaJK7fr+2Glrb5yMrWMBoLZ9h8oleZb7UasDANAYCDsAtFjVxUPPa23WnkPlkiH16NxK39jsyj/i0Lc/HPOxa0pdNWtw9LqgtUrKXQQcAFDD9r2l2vptqSTPsr6HEy/gPRIA4HeEHQBCVs2ZGb0uaK09h8rlchnqdH6EMr8r1bf7GzZD41TqKzIKAKjfmhrbzRqGVFLuCmBrAAChirADQLNUX5AhQ/pJbCvttNl1+IhD3+1v+MyMM1Edbkgi4ACABjp8tEoS280CABoXYQeAoFPf8pJeF7TWd/uPqcJhSDK0YftRNUKOUcvJS1Kq20K4AQBnZ8uuEu36/piuvjhKV/40imV+AIBGQ9gBoElUz8TIzzfpsLNAew6Vq7jE4Q0Svtt/TOUOQzIMfb7jaKPMyKhPmEm6/RedZK9015klQqgBAP5jtdn1x0W5MgxpR45d997UhfdYAECjIewAcMZOnnFRM6w4eQZGldNQl+gI7T1UriOlTu0+UH48wAjT1n0HmqS9p5qZQaABNE9lZWW666679Prrr6tbt27auHGjXnzxRVVWVmrUqFF68sknJUlWq1XPPPOM7Ha74uPjNW3aNFksFh08eFDJyckqLCxUz549NXPmTLVt21YlJSV66qmn9MMPPyg6Olpz585VTExMgJ9t6MnKKZPzeJLtYrtZAEAjI+wAWphTLRGp7/JPYlvp2/3H5HC6FWYy6T/Z/phxYfLH05DkmZUxsM95uuaSdgQZQIjbvn27UlNTlZubK0mqqKjQ1KlTtWjRInXt2lUPP/ywNmzYoCFDhig5OVkvvPCC+vXrp6lTp2rJkiUaN26cpk2bpnHjxikxMVHz58/XggULlJycrLlz5yo+Pl5vvvmm0tPTNX36dM2dOzegzzcU9enexnuZWh0AgMZG2AE0U6cq0Hny5d0Hy+V0GeoSHamvd5co2+afHUjOnqEzCTzMYdLY6+pfXsKWrkDLs2TJEqWlpel3v/udJCkrK0s9evRQ9+7dJUlJSUnKyMhQr169VFFRoX79+kmSxo4dq1deeUV33nmntm7dqvnz53vP33vvvUpOTtb69eu1ePFiSdLo0aP1/PPPy+FwKDw8vOmfaAhzuj1/33R1ByVe25H3bwBAoyLsAIKErxkXP+3aWt/+cEz5Rx1yudz6xtY4O400luolJc7KIxp85U9OuwyGIAPAyaZPn17r+PDhw7WWmsTGxiovL6/O+ZiYGOXl5am4uFhRUVGyWCy1zp/8WBaLRVFRUSoqKlLnzp0b+2m1KB9mFinMJA29ugPv7wCARkfYATSy09W52H2wXA6nIZNJ+vjL4mYRXtSccXGqsOJ0S0oyMzM1YECnQD8NAM2c2+2WyXRilphhGDKZTKc8X/13TScf17xPWFhYg9qTnZ3doNufTmZmpt8eK1h8Xyht2G6WJP3hnb36dYJLP+l49o8Xin3kb/SRb/SRb/SRb/RR8CLsAPygvp1GZEhms0n/3lwotzvQLaztdDuQnO4yMy4ABIsuXbooPz/fe5yfn6/Y2Ng65wsKChQbG6vo6GiVlpbK5XLJbDZ7by95ZoUUFBSoS5cucjqdstvtat++fYPa07dvX0VGRp7z8/IEwgPO+XGCzfY1ByV5/l1cbqkqopsGDDi7mTOh2kf+RB/5Rh/5Rh/5Rh+dXqCDIL+FHStXrtRrr70mp9OpiRMn6p577ql1/bp16/Tqq6/KMAx169ZNL774os4//3wtW7ZMs2bNUseOnnj/+uuv91ZTB4LBqWZm/CS2lXZ+b1fBUYd2fX8sKHcaYQcSAKHqqquuUk5Ojmw2m7p166ZVq1bp9ttvV1xcnCIjI70D0OXLlyshIUHh4eGKj4/X6tWrlZSUpPT0dCUkJEiShgwZovT0dD3yyCNavXq14uPjqdfhZ9WTaMJMFCcFADQNv4QdeXl5mjNnjj744ANFRETorrvu0sCBA9WrVy9Jnq3innvuOb3//vvq3LmzXn75Zb366qtKTU1Vdna2UlJSNHr0aH80BThr9dXMCLeYtPKLhszMOLedRnwV5awZthBYAGjJIiMjNWPGDD322GOqrKzUkCFDNHLkSEnSzJkzlZqaqrKyMl1++eWaMGGCJCktLU0pKSl67bXX1LVrV82ePVuS9MQTTyglJUWJiYlq166dZs6cGbDnFaoOFlbpvDZm3XZdjK76KTMEAQCNzy9hx8aNGzVo0CDvlM8RI0YoIyNDU6ZMkSQ5HA6lpaV5C31deumlWrlypSRpx44dys3N1RtvvKFLL71Uzz77rM4//3x/NAuoV72hRniYVm4q8MNyk/p3GjmTOhcsEQEA3z755BPv5cGDB2vFihV1btO7d28tXbq0zvm4uDgtWrSozvn27dvr9ddf929D4ZWdU6bNu0p0da8o3XUDRV8BAE3DL2FHfRXRs7KyvMcdOnTQsGHDJEkVFRV68803NX78eEmeauiTJk3S1VdfrdmzZ+v555/XrFmz/NEswFtLozpg8F+oUVt9O40QYgAAWjqrza6pb++Tw2Uoc3eZrDY7vw8BAE3CL2HHqSqfn6y0tFSTJ09W7969ddttt0mSd797SXrggQe8ociZ8mf1cynwRVSCXXPon+8Lpa9sJpWWS98dClPtXKPm67LmLIzqy/VvhxJmkn5+sUsVTpPKKqSoVtIF7Q0dPOK5f/8ehn7Ssfj4rW2K7X7ivrHtpGMFUmaBH55ciGgOr6NAo498o4+A4JeVUyaHy/O71e02lJVTRtgBAGgSfgk7unTpom3btnmPa1Y4r3b48GHdf//9GjRokKZOnSrJE368//77uu+++yR5QhKz2dygn+2v6ucS1XR9Ceb+qZ7BUXDUoW3flp7hFq6mOpfNYaY6NTMaMjMjmPsoWNBHvtFHvtFHp1dZWen3LwOAs3FlzyiZTJJhUJgUANC0/BJ2/OxnP9Orr76qoqIitW7dWh9++KH++Mc/eq93uVx65JFHNGrUKP3P//yP93ybNm301ltvqX///rrqqqv03nvvNXhmB1qemjU3vtt/TD/kV2rn98dknFHA4VFfIVCWmwAA4F8XdIqUYUj9LorShGFd+B0LAGgyfgk7OnfurCeffFITJkyQw+HQHXfcoSuvvFIPPvigHn/8cf3444/auXOnXC6X1q5dK8kzI2P69OmaO3eunnvuOVVUVOjCCy/USy+95I8mIcRUBxxl5U598J8zr7lRXUtDkrcoKKEGAABNY9UmzxrOIVe15/cuAKBJ+SXskKSkpCQlJSXVOrdw4UJJ0hVXXKFdu3bVe7/4+HgtW7bMX81AiLHa7PrXZ3nabD3TpSknAg62ZwUAIHCsNrv+95M8SdJrKw+oR2wrficDAJqM38IOwF+89TeOOLTtuzMLOQg4AAAILtv3lXl/hzudFCcFADQtwg4EBavNro++LNKBgkrt2Gc/xZ4oJ5xcc4OAAwCA4NLxvHBJnhLgFCcFADQ1wg4ElNVm14fbCvVhZrHPGRxhJun2X3RS29YWam4AABDkiksdkqQ7h8RqUJ/z+L0NAGhShB1octXFRg8WVOqjL4tPu4sKy1MAAGieMneX6qddW+nXI7sGuikAgBaIsANNojrgKC51aOWmwtPO4iDgAACgeftqT6l25Nh1w1XtA90UAEALRdiBRrdmc4HmrThw2u1iw0zSwN4EHAAANHdWm11/+FuODEP6fMdRjR5k5/c6AKDJEXagUS1Zn6d31v542tuYw6TJt8Rp1MBOTdQqAADQWD7KLJLT5ZnC6XKzCwsAIDAIO+B3Vptda7cVKjvXrgMFVfXepno3FYqNAgAQOjyFx4u8x+YwdmEBAAQGYQf8pnr72LVbi+qtyWEySXewmwoAACHryz2lOj6pQyZJw+I78PseABAQhB04J9WFR4+UObViY8EpC4+yVAUAgNCXc6hckifoiAg3aWj/6MA2CADQYhF24Kyt2Vyg+SsOyHWawqPmMGlEfDRFRwEACHFf7i7Vf78pkSSFhUkPJ17A734AQMAQdqDBPOtxC7U2s1hGPTM52FkFAICWZ/nGfO9lw5BKyl0BbA0AoKUj7ECDrN5coPnLD7BcBQAAeBmGoe/zKmUyeZawhFsoTAoACCzCDpwRq82uf2wy6ZsDB+pcx84qAAC0bP/eXKgfi6t0Y7/2+knnVowHAAABR9iB07La7PrfT/KU+V2pDIXVui7MJI28hnocAAC0ZFabXa+t8HwZ8p/so5oxqBPjAgBAwBF2oF5Wm10rvyjQ+q+P6MSKFZP3EstVAACAJG2ylniXtzpdhrJyygg7AAABR9iBOpb9J18LVx+sp/iooTCTidkcAADAa9/B49vNmqjVAQAIHoQd8MrOLdO7aw8pO/dYvdebTNKUMczmAAAAHl/vKVXm7lJJnuWtbDcLAAgWhB0tnNVm1/Z9Zdpz4Jj++01JnetrbiPbre1hgg4AAOCVvrHAe5ntZgEAwYSwowWy2uzKyilTWblTH3xecMbbyGZmHm7CVgIAgGCWnVumHfvKZBJLWAAAwYewo4VZs7lA81cckMt96tuwywoAADgdq82up9/aJ6fLkDlMGhHPuAEAEFwIO1oIq82uVZsL9elXxTrFRA5J7LICAAB8y8opk9PlGVEYhhTbIYKgAwAQVAg7QpzVZtf/rc/T1l2lpww5zGHS2Os6qW1ri67sGcVgBQAAnFb7KM8Q0iSWrwAAghNhR4iy2uz66Msird1aVG9NDgIOAABwtjZsPyJzmHRT/w4aeU1HxhEAgKBD2BGC1mwu0LwVB+Supy4H9TgAAMDZstrs+teGPH21p0yStCHriEZe0zHArQIAoC7CjhBhtdm17qsiHSyo0va9ZfUuWQkzSVPGUI8DAAA0nNVmV8pbe1XlPDHKcDgNZeWU8QUKACDoEHY0c76Wq4SZpIG926lDu3BmcwAAgLP2UWZRraCDeh0AgGBG2NGMnW65isTOKgAA4NxVf7GSsbXIe47tZgEAwY6woxmy2uxa9UWBPvn6SL3XMwABAAD+UN/SFZOkEddE67FbuweuYQAA+EDY0UxYbXZl5ZSp8GiVVm0uknHSkhWWqwAAAH9bsamgTtAREW7S0P7RgWsUAABngLAjiFUHHPZypz74T4FcLFcBAABNwGqzK/2/+fpsx1HvOWaOAgCaE8KOIGS12fWvz/K02Vpab9HRamwjCwAA/G3N5gLNW36g1hiEpSsAgOaGsCNIVBf/OlRQqe059jrLVE7GbA4AAOBv//w0T3/78Mda51i6AgBojvwWdqxcuVKvvfaanE6nJk6cqHvuuafW9VarVc8884zsdrvi4+M1bdo0WSwWHTx4UMnJySosLFTPnj01c+ZMtW0berMUqpeknNfarD2HyiVD+mnX1tpps2t/QaV27y+Xj3xD5jBp7HWd1La1RVf2jGI2BwAAfuRrLBMK6huPXNillbJy7Np7oFyHiqpq3Z5ZpACA5sovYUdeXp7mzJmjDz74QBEREbrrrrs0cOBA9erVy3ub5ORkvfDCC+rXr5+mTp2qJUuWaNy4cZo2bZrGjRunxMREzZ8/XwsWLFBycrI/mtVg3xdKe9bneQcAxSUOdWgXrl4XtPYOCM708u6D5So86lDbVmaZTIbWbz962iUppxJmkm7/BQEHAACN6UzGMk3FarNr3VdFDRp3nMm4JTw8TCs3FZxyy/qTmUzSlDHMIgUANE9+CTs2btyoQYMGqX379pKkESNGKCMjQ1OmTJEkHThwQBUVFerXr58kaezYsXrllVd05513auvWrZo/f773/L333huQsMNqs+uvG8xyun/0feNGZg6Trr2UnVUAAGgqvsYyTeX7QuntD/acsih5U2G5LACgufNL2HH48GHFxMR4j2NjY5WVlXXK62NiYpSXl6fi4mJFRUXJYrHUOt8Q2dnZ59h6jw27THK6w44fGfKsUFU9xw29XPP41FM7wkzSpV3dimol9e9h6CcdiyVJxwoOK7PgrJ5So8jMzAx0E4IefeQbfeQbfeQbfQR/8jWW8cVf45GcfJNcbn+NO051+fTjkQE93erfw1CsxabMTNs5PJvGw/9/3+gj3+gj3+gj3+ij4OWXsMPtdstkOvFL1jCMWsenuv7k20mqc+xL3759FRkZeZYtP6FNJ7vWW3fL6ZIMndwG0zlcPnFsDjNp7HWdZK9015la2hxmcGRmZmrAgAGBbkZQo498o498o498o49Or7Ky0m8fvlsKX2MZX/w1Hvm+MFPhZpMcruozZz/uONVlxiOhjz7yjT7yjT7yjT46vUAHQX4JO7p06aJt27Z5j/Pz8xUbG1vr+vz8fO9xQUGBYmNjFR0drdLSUrlcLpnN5jr3a0p9erTVrxNcqoro5peaHSffv6TcRc0NAACClK+xTFP5SUfpzw/2apSaHYxHAAAtiV/Cjp/97Gd69dVXVVRUpNatW+vDDz/UH//4R+/1cXFxioyM9CZfy5cvV0JCgsLDwxUfH6/Vq1crKSlJ6enpSkhI8EeTzspPOkoDBnQO2M8HAACB4Wss05T69GhLGAEAwDnyS9jRuXNnPfnkk5owYYIcDofuuOMOXXnllXrwwQf1+OOP64orrtDMmTOVmpqqsrIyXX755ZowYYIkKS0tTSkpKXrttdfUtWtXzZ492x9NAgAAOGOnGssAAIDmyS9hhyQlJSUpKSmp1rmFCxd6L/fu3VtLly6tc7+4uDgtWrTIX80AAAA4K/WNZQAAQPMU5vsmAAAAAAAAzQdhBwAAAAAACCmEHQAAAAAAIKQQdgAAAAAAgJBC2AEAAAAAAEIKYQcAAAAAAAgphB0AAAAAACCkEHYAAAAAAICQYgl0A86WYRiSpKqqKr8+bmVlpV8fL9TQP77RR77RR77RR77RR6dW/bux+nclGk9jjEd4bftGH/lGH/lGH/lGH/lGH/kWqPGIyWimI6HS0lJ99913gW4GAABB65JLLlG7du0C3YyQxngEAIDTC9R4pNmGHW63W3a7XeHh4TKZTIFuDgAAQcMwDDkcDrVt21ZhYaxYbUyMRwAAqF+gxyPNNuwAAAAAAACoD1/3AAAAAACAkELYAQAAAAAAQgphBwAAAAAACCmEHQAAAAAAIKQQdgAAAAAAgJBC2AEAAAAAAEIKYQcAAAAAAAgphB2SVq5cqZtvvlnDhw/X4sWLA92coDF+/HglJiZqzJgxGjNmjLZv366NGzcqKSlJw4cP15w5cwLdxIAoKyvT6NGjtX//fkk6ZZ9YrVaNHTtWI0aM0DPPPCOn0xmoJje5k/vo6aef1vDhw72vpY8++khSy+2jefPmKTExUYmJiXrppZck8To6WX19xOuotpdfflk333yzEhMT9c4770jiddTcMR6pH+OR+jEe8Y3xyOkxHvGN8YhvQT0eMVq4H3/80bjhhhuM4uJiw263G0lJScbu3bsD3ayAc7vdxnXXXWc4HA7vufLycmPIkCHG999/bzgcDmPSpEnG+vXrA9jKpvf1118bo0ePNi6//HLjhx9+OG2fJCYmGl999ZVhGIbx9NNPG4sXLw5gy5vOyX1kGIYxevRoIy8vr85tW2If/fe//zV+9atfGZWVlUZVVZUxYcIEY+XKlbyOaqivjz788ENeRzVs3rzZuOuuuwyHw2GUl5cbN9xwg2G1WnkdNWOMR+rHeKR+jEd8YzxyeoxHfGM84luwj0da/MyOjRs3atCgQWrfvr3atGmjESNGKCMjI9DNCrh9+/ZJkiZNmqRbbrlF7733nrKystSjRw91795dFotFSUlJLa6vlixZorS0NMXGxkrSKfvkwIEDqqioUL9+/SRJY8eObTF9dXIflZeX6+DBg5o6daqSkpL0yiuvyO12t9g+iomJUUpKiiIiIhQeHq6LLrpIubm5vI5qqK+PDh48yOuohmuvvVZ///vfZbFYVFhYKJfLpZKSEl5HzRjjkfoxHqkf4xHfGI+cHuMR3xiP+Bbs4xFLoz56M3D48GHFxMR4j2NjY5WVlRXAFgWHkpISDR48WM8++6wcDocmTJigBx54oE5f5eXlBbCVTW/69Om1jut7/eTl5dU5HxMT02L66uQ+Kigo0KBBg5SWlqZ27drp4Ycf1tKlS3XxxRe3yD66+OKLvZdzc3O1Zs0a3XvvvbyOaqivjxYvXqwtW7bwOqohPDxcr7zyiv76179q5MiRvB81c4xH6sd4pH6MR3xjPHJ6jEd8YzxyZoJ5PNLiZ3a43W6ZTCbvsWEYtY5bqv79++ull15Su3btFB0drTvuuEOvvPIKfXWSU71+eF2d0L17d82fP1+xsbFq3bq1xo8frw0bNrT4Ptq9e7cmTZqk3/3ud+revTuvo3rU7KOf/vSnvI7q8fjjj2vTpk06dOiQcnNzeR01Y/w71Y/xyJlhPOIb45H6MR7xjfGIb8E6HmnxYUeXLl2Un5/vPc7Pz/dOd2vJtm3bpk2bNnmPDcNQXFwcfXWSU71+Tj5fUFDQYvvq22+/1dq1a73HhmHIYrG06D7KzMzUfffdp//3//6fbrvtNl5H9Ti5j3gd1bZ3715ZrVZJUuvWrTV8+HBt3ryZ11EzxnikfoxHzgy/R3zj90hdjEd8YzxyesE+HmnxYcfPfvYzbdq0SUVFRSovL9eHH36ohISEQDcr4EpLS/XSSy+psrJSZWVlWrZsmX77298qJydHNptNLpdLq1atavF9ddVVV9XbJ3FxcYqMjFRmZqYkafny5S22rwzD0J/+9CcdPXpUDodD//znPzVs2LAW20eHDh3S5MmTNXPmTCUmJkridXSy+vqI11Ft+/fvV2pqqqqqqlRVVaWPP/5Yd911F6+jZozxSP0Yj5wZfo/4xu+R2hiP+MZ4xLdgH4+0+JodnTt31pNPPqkJEybI4XDojjvu0JVXXhnoZgXcDTfcoO3bt+vWW2+V2+3WuHHj1L9/f82YMUOPPfaYKisrNWTIEI0cOTLQTQ2oyMjIU/bJzJkzlZqaqrKyMl1++eWaMGFCgFsbGL1799ZDDz2ku+++W06nU8OHD9fo0aMltcw+evvtt1VZWakZM2Z4z9111128jmo4VR/xOjphyJAhysrK0q233iqz2azhw4crMTFR0dHRvI6aKcYj9WM8cmYYj/jGeKQ2xiO+MR7xLdjHIybDMIxG/QkAAAAAAABNqMUvYwEAAAAAAKGFsAMAAAAAAIQUwg4AAAAAABBSCDsAAAAAAEBIIewAAAAAAAAhhbADaMEmTZqkoqIiPfjgg9qzZ49fHvPVV1/V888/L0l+fVwAABCaGI8AaAyWQDcAQOD897//lSQtXLiwUR6/sR4XAACEDsYjABoDYQfQQj399NOSpIkTJ2rPnj1asmSJjh07ptmzZ6tr167KyclR69at9dBDD2nRokXKycnR8OHDNXXqVEnSJ598otdee00Oh0OtWrXS73//e/Xv37/Wz7jxxhv18ssv69ixY5ozZ466d++u3bt3y+l0atq0aRowYICqqqo0c+ZMbd26VS6XS5dddplSU1MVFRXV5H0CAACaFuMRAI2FZSxAC/Xiiy9Kkt5991117drVe37Hjh166KGHtHz5ckVFRenNN9/UG2+8oQ8++ED/+7//q7y8POXm5mrOnDl68803lZ6erj/+8Y967LHHdOzYsVP+vKysLE2aNEnp6ekaO3as5syZI0l68803ZTab9cEHH2jFihWKjY3VzJkzG/fJAwCAoMB4BEBjYWYHgFq6deumyy67TJL0k5/8RO3atVNERISio6PVtm1bHT16VFu3btXhw4d13333ee9nMpn0/fffn/JxL7jgAvXp00eSdNlll2nZsmWSpPXr16u0tFQbN26UJDkcDnXs2LGRnh0AAGgOGI8AOFeEHQBqiYiIqHVssdR9m3C73Ro8eLDmzp3rPXfo0CHFxsbqo48+qvdxW7Vq5b1sMplkGIb3saZOnaohQ4ZIkux2uyorK8/1aQAAgGaM8QiAc8UyFqAFM5vNcjqdDb7f4MGD9d///ld79+6VJG3YsEG33HKLKioqGvxY1113nRYvXqyqqiq53W49++yzmj17doMfBwAANE+MRwA0BmZ2AC3YyJEjNX78eNnt9gbdr1evXnr++ef129/+VoZhyGKx6LXXXlPbtm0b3Ib/+Z//0Z///Gfddtttcrlc6tOnj1JSUhr8OAAAoHliPAKgMZiM6rlbAAAAAAAAIYBlLAAAAAAAIKQQdgAAAAAAgJBC2AEAAAAAAEIKYQcAAAAAAAgphB0AAAAAACCkEHYAAAAAAICQQtgBAAAAAABCCmEHAAAAAAAIKYQdAAAAAAAgpBB2AAAAAACAkELYAQAAAAAAQgphBwAAAAAACCmEHQAAAAAAIKQQdgAAAAAAgJBC2AEAAAAAAEIKYQcAAAAAAAgphB0AAAAAACCkEHYAAAAAAICQQtgBAAAAAABCCmEHAAAAAAAIKYQdAAAAAAAgpBB2AAAAAACAkELYAQAAAAAAQgphBwAAAAAACCmEHQAAAAAAIKQQdgAAAAAAgJBC2AEAAAAAAEIKYQcAAAAAAAgphB0AAAAAACCkEHYAAAAAAICQQtgBAAAAAABCCmEHAAAAAAAIKWcUdrz88su6+eablZiYqHfeeUeS9PTTT2v48OEaM2aMxowZo48++kiSZLVaNXbsWI0YMULPPPOMnE6nJOngwYO65557NHLkSD366KOy2+2SpJKSEj300EMaNWqU7rnnHuXn5zfG8wQAAAAAAC2Ez7Bjy5Yt+uKLL7RixQq9//77WrRokfbt26fs7Gy99957Wr58uZYvX65hw4ZJkpKTk/WHP/xBa9eulWEYWrJkiSRp2rRpGjdunDIyMtS3b18tWLBAkjR37lzFx8drzZo1uvPOOzV9+vRGfLoAAAAAACDUmQzDMHzdyOFwKDw8XAcOHNC4ceP0j3/8Q0lJSerfv7/y8vI0bNgwTZkyRYcOHdLEiRO1bt06SdK2bdv0yiuv6O2339bAgQO1ZcsWWSwWHTp0SPfee68+/vhj3XjjjVq8eLG6du0qp9Opa6+9Vps3b1Z4ePhp2+R0OlVYWKhWrVopLIzVOAAAVHO73aqoqFDHjh1lsVgC3ZyQxngEAID6BXo8ckY/MTw8XK+88or++te/auTIkXI6nRo0aJDS0tLUrl07Pfzww1q6dKkuvvhixcTEeO8XExOjvLw8FRcXKyoqyvsEq89L0uHDh733sVgsioqKUlFRkTp37ux9nJKSEpWUlNRqk91uV1lZ2bk9ewAAQlzN36fwv8LCQu3fvz/QzQAAIKgFYjxyxvHK448/rgcffFCPPPKINm3apPnz53uvGz9+vNLT03XRRRfJZDJ5zxuGIZPJ5P27ppOPa97n5G9G3n33Xc2bN6/WuT59+ujZZ59Vt27d1KZNmzN9GgAAhLxjx45p//79atWqVaCbEvKq+5jxCAAAtQV6POIz7Ni7d6+qqqrUp08ftW7dWsOHD9fq1avVvn17jRgxQpInoLBYLOrSpUutAqMFBQWKjY1VdHS0SktL5XK5ZDablZ+fr9jYWElSbGysCgoK1KVLFzmdTtntdrVv375WGyZOnKjbbrut1rmqqioVFxerTZs2ateu3bn2AwAAIYdlFY2vuo8ZjwAAUL9AjUd8/tT9+/crNTVVVVVVqqqq0scff6xrrrlGf/rTn3T06FE5HA7985//1LBhwxQXF6fIyEhlZmZKkpYvX66EhASFh4crPj5eq1evliSlp6crISFBkjRkyBClp6dLklavXq34+Pg69TrOO+88devWrdafmstlAAAAAAAAqvmc2TFkyBBlZWXp1ltvldls1vDhwzVlyhR16NBBd999t5xOp4YPH67Ro0dLkmbOnKnU1FSVlZXp8ssv14QJEyRJaWlpSklJ0WuvvaauXbtq9uzZkqQnnnhCKSkpSkxMVLt27TRz5sxGfLoAAAAAACDUndFuLMGotLRU3333nS655JI600YdDof279+vioqKALUO/tKqVSt169bN5+48AIATTvc7Ev5FXwPAmeEzWug61We2QP+ODMn96Pbv36927drpwgsvPGUhVAQ/wzC8Ve579uwZ6OYAAAAAOEt8RgtNwfyZLSQrl1Xv5ct/oubNZDKpY8eOpL8AAABAM8dntNAUzJ/ZQjLskE69tS2aF/4dAQAAgNDA2D40Beu/a8iGHQAAAAAAoGUi7AAAAAAAtFgpKSn64IMPGny/V155Rdu2bZMkjR8/Xps3b/Z303AOCDsAAAAAAGigrVu3yuVyBboZOIWQ3I0lmBiGoZkzZ2rdunUym8361a9+pT59+mjOnDmqqKhQSUmJnn76aQ0dOlQrV67UW2+9JbPZrG7duukvf/mLIiMj9eabb2rNmjVyuVy67rrrlJycLLvdrt/+9rcqKCiQJE2ePFk33XRTgJ8tAAAAAAQ3wzA0Y8YMrV+/XrGxsXK5XLr22muVnp6ud999V263W5dffrnS0tIUGRmp9957T8uXL1d5ebnCw8M1a9YsZWVlKTs7W6mpqZo3b54kaenSpZoxY4ZKSkr0zDPP6MYbbzzlZzw0vpAPO9Z9WaQPtxU16D5xjhz9xLFH34f30oHwU2+fMzw+WkOvjj7tY2VkZOjLL7/UypUr5XA4NG7cOHXo0EEvvPCCLrroIm3atEl/+tOfNHToUM2dO1dLlixRx44d9ec//1n79u1Tfn6+srOztXTpUplMJiUnJ2vFihVyu92Ki4vTm2++KavVqhUrVhB2AACAWpz7rXJ8v0PhP7lClm59At0cAJB0dp/RztSZfEZbu3atdu7cqVWrVqm0tFS33HKLysvL9e9//1v/93//p8jISM2aNUtvv/22JkyYoHXr1mnRokVq1aqVXn75ZS1evFjPPvus3n//fU2ZMkWXXnqpJKldu3ZatmyZPv30U82bN0833nhjvZ/x+vTh/bgphHzY0VA9K636ZekbkiSXLPrH+ZNPG3j4snXrVo0aNUoRERGKiIjQ8uXLVVlZqU8//VQZGRnavn277Ha7JOmGG27Q3XffraFDh2rEiBHq06ePVqxYoaysLI0dO1aSZ8umCy64QLfffrtmz56tvLw8XX/99Zo8efK5P3kAaOb+teGwIsPDdMvPOgW6KUDAOfdbVfre7yW3WxWWcLUb96dmH3jstNm1YmOBfvernygsLDir/wMIflu2bNHw4cMVHh6u6OhoJSQkyDAM2Ww2/fKXv5QkORwOXXbZZYqKitKsWbP073//W7m5ufr8889PGVYMHTpUktSrVy8VFxdLqv8zHppGyIcdQ6/2nezVZF+ToaqvDElSmMmlh/oXq/XPhp31z7dYLLW24tm/f7+eeOIJDRw4UAMHDtTgwYP11FNPSZJSU1O1a9cubdiwQcnJyZoyZYpcLpcmTpyoX//615KkkpISmc1mtW3bVmvWrNHnn3+uTz/9VH/961+1evVqhYVRhgVAy/Wf7CNqHWkm7AAkOb7fIbmPryV3OeX4fkezDzuyc8q0IeuInhjbTa0jzYFuDoCz1NDPaP5mMplkGIb32GKxyOVyadSoUUpNTZUk2e12uVwuHTp0SOPHj9e9996rhIQEderUSVartd7HNZvN3sevVt9nvDFjxjTis0M1PhmfxBxz4fFLJslsUfhPrjinx7vmmmv04YcfyuFwqLy8XPfff792796tJ554QgkJCfr444/lcrnkdDo1fPhwdejQQQ8//LDGjBkjq9WqQYMGafny5bLb7XI6nZo8ebLWrl2r9957T6+++qpGjRqltLQ0FRUVqays7JyfPwA0Zy635HQZvm8ItAC1xjB+GNMEA/fx/94ud2DbAaB5Gzx4sNasWaOqqiodPXpUn3/+uSTpo48+UmFhoQzD0HPPPad3331XO3bsUI8ePXTffffpiiuu0Lp167xFSc1m82kLlJ7qMx6aRsjP7Ggoc8dukiRLr2vU+me/POdvQIYNG6bs7GyNHTtWbrdbEydOlM1mU2JioiwWiwYNGqSKigpVVVXp8ccf16RJkxQZGamOHTtqxowZ6tixo3bt2qVf/vKXcrlc+sUvfqHbbrvNW6A0KSlJZrNZycnJOu+88/zRBQDQbLnchhxOPgW1NGVlZbrrrrv0+uuvq1u3bvrnP/+pRYsWyWQyqW/fvpo2bZoiIiJktVr1zDPPyG63Kz4+XtOmTZPFYtHBgweVnJyswsJC9ezZUzNnzlTbtm0D/bTOmaVbH8kSIXPHbmoz4n+a/awOSXIf/+/tchNqAjh7Q4cO1Y4dOzR69Gh16tRJF110kdq1a6cpU6Zo4sSJcrvd6tOnjx566CE5nU794x//0M033yzDMHTNNddo9+7dkqRf/OIXSktL05///Od6f47FYqn3Mx6ahsmoOX+nGSktLdV3332nSy65RO3atat1ndVqPeu1UI6921T2zzS1GjJerX9+lz+ainN0Lv+eAFqWh+bskiXMpAVPXBropgTU6X5Hhprt27crNTVVOTk5ysjIkMPh0MMPP6wPPvhAbdu2VUpKivr06aP77rtPo0eP1gsvvKB+/fpp6tSp6tu3r8aNG6eHH35Yt9xyixITEzV//nwdO3ZMycnJZ/Tzg72vi/88RhG9r1PbMWf2fILd4nU/6r2P87R46mWKbhce6OYAaADG9KGtvn/fQP+OZBnLSYzjXxkYlccC3BIAQEO5WcbS4ixZskRpaWmKjY2VJEVERCgtLU1RUVEymUy65JJLdPDgQR04cEAVFRXq16+fJGns2LHecGTr1q0aMWJErfOhwDAMyeWSYYTObKcTy1j4fw4AOD2WsZzM7ZQkGZXlAW4IAKChXG5DZB0ty/Tp02sdx8XFKS4uTpJUVFSkxYsX68UXX9Thw4cVExPjvV1MTIzy8vJUXFysqKgoWSyWWufrU1JSopKSklrnqqqq/Pl0/MtwSzJOrP0IAdUTkkPoKQEAGglhx8mqq5ZXMbMDAJobt9vgG9+zsHLlSr322mtyOp2aOHGi7rnnnlrXz5s3T++//763NtQvf/nLOrcJNnl5eXrggQd0++23a+DAgcrMzKxVHd8wDG81/prnJdU5rvbuu+9q3rx5tc5dcskleu655/zefr9wOTx/N88Vy/Xyzuwg1QQA+EDYcbLjYQfLWACg+XG5DTn4ENQgeXl5mjNnjj744ANFRETorrvu0sCBA9WrVy/vbbKzszV79mz1798/gC09c3v37tUDDzyg8ePHa9KkSZKkLl26KD8/33ubgoICxcbGKjo6WqWlpXK5XDKbzcrPz/cuiTnZxIkTddttt9U6V1VVpeLi4sZ7MufAcDmPXwidaRDu48ENoSYAwBdqdpzEIOwAgGbL5ZYcTj4ENcTGjRs1aNAgtW/fXm3atNGIESPq1KzIzs7WG2+8oaSkJD3//POqrKwMUGt9Kysr0/33368nnnjCG3RInuUtkZGRyszMlCQtX75cCQkJCg8PV3x8vFavXi1JSk9PV0JCQr2Pfd5556lbt261/tRcGhN0QjDsMKjZAQA4Q4QdJ6sOO1jGAgDNjstlUKC0hh9//FH79++v9efkmhMn17KIjY2tVbPCbrerT58+Sk5O1rJly1RSUqIFCxY02XNoqKVLl6qgoEDvvPOOxowZozFjxujll1+WJM2cOVMvvviiRo4cqWPHjmnChAmSpLS0NC1ZskQ333yztm3bpt/85jcBfAZ+5A07Quf/xImtZwPbDgBA8Gv2y1i+++67es9Xf3PTUO1+2KcYSRUlxdp9lo8B/zvbf08ALcvvEz1/857hcd9996mgoKDWuSlTpuixxx7zHrvd7nprWVRr27atFi5c6D2eNGmSpk6dqieffLIRW95wn3zyiSTPc77vvvvqvU3v3r21dOnSOufj4uK0aNGixmxeQBjVRddDaGYHy1gAAGeq2Ycd9e3Zey57OFcYh1S+U4qQSwMGDPBHE5u9jz/+WAcOHPB+A1bzfHZ2tp544olT3nf8+PGaMmWKBg4cWOv8p59+qtzcXP3617/Whx9+qMOHD+vee++t9zHYkxvAmbr1DztU6XBrxR+vULil5U5erN7X/m9/+5tat25d67rqIqPVunTpom3btnmPT65ZcfDgQW3cuFF33HGHJE8YUr1zCYIcy1gAoEmkpKTo2muv1dixYxt831deeUU/+9nPFB8ff8rPTmfC5XLpiSee0F/+8pc6v/sffPBBvfDCC+rcuXO99928ebPmzZtXb/A/fvx4LVq0SG63W4899pheeukltW3btsHtC4SWOxKsh3O/VY59ngEfy1g8qqqqtHDhQt199911rrvppptOG3ScTnZ2tsrKyiRJw4cP///svXmYFPW9/X9q62V2lhkGZgAVRVBBk5C4xEDcAMWJAYkLRjS50cQIGL83JASJaKJeTYiYxBh/mlw1LokEI6gXBzRGTYKJOkkEdBAXFodlFmaYtZdaPr8/qj7VVdXVyzBLz/J+PQ/PTFdXV1ePdnfVqXPOG1u2bMHhw4d7tK8EQRD8qi9FWUzKy8uTOia8YsdZZ52FN954A83NzYhEItiyZYursyIUCuGnP/0pPvnkEzDG8OSTT+KCCy7o75dCHA1DMcZCzg6CGHZodbWIbF0Hra4217vSJ7z11lvQdb3H2/n973+Ps88+O0noAICHH344pdCRiTfffBMAIIoiLrvsMvzqV7/q0X72J0P+0kxs+58Rf+eljOuxWCf0ht2OSwYa2h7/HgQhtR4UOPUCBKedl3HbP/vZz7B582aMGDECpaWlOPfcc/G5z30O3/jGNzBixAiEQiE88sgj/vvFGNasWYOXX34ZkiTh8ssvxzXXXIM333wTa9euRTQaRVtbG37wgx/g/PPPx/PPP4/f/OY3kCQJlZWV+OlPf4pgMIiHHnoIL774InRdx9lnn43ly5ejs7MT/+///T/b4nzjjTfivPPcr+e5557DjBkzoCgK6urqXPtcVVWFN998E3fffTf++c9/4o477oAkSTjttNPw0Ucf2crg+vXrcffdd6OtrQ233HILJkyYgD/84Q8AgHHjxuHSSy/F7Nmz8eSTT2LZsmUZ/54EQRCp4CdAqsYQDuZ4ZwYJY8aMwc0334zFixdDVVUsXLgQ06dPx3XXXYdly5Zh2rRp+NGPfoQbbrgBqqri05/+NL72ta/lereJLGB89KwxdJwd/KUMoZdEEMOSozlHiwoCpLJjIQTTuwr66xzt7rvvxquvvoqysjLouo7Pfe5zAMyi68ceewyGYeDkk0/G6tWrEQwG8cQTT2Djxo2IRCJQFAU/+9nPsG3bNuzYsQOrVq2yR5t7z53OPffclOd4zv15/PHH7ajmihUrcOTIEezduxfLly/HHXfcgd/97ncYM2YMVq9ejZqaGowZMwaCIODb3/42AKC5uRnXXXcd9u3bh2OPPRa/+MUv8JOf/AQA8JWvfAV//OMfcfbZZ+OOO+7At7/9bRQUFGT8G+eaIS92ZAuLdiZf+TAMQOqZ+eWVV15BTU0NXnjhBUQiEcyfPx/nnnsuAGD37t34zW9+g8rKypSPr66uxr/+9S88//zzUFUVixYtwkUXXYQnnngCd9xxByZNmoQ33ngDd911F84//3zcd999WLduHUaNGoV77rkHH3/8MRobG7Fjxw6sX78egiBg+fLleO6552AYBioqKvDQQw+htrYWzz33XJLY8corr+Dyyy+3bzv3+U9/+hMAQFVVfO9738P/9//9f5gyZQruuOMO1zYKCwvx7LPP4i9/+Qvuv/9+PPPMM7jiiisAAJdeeikAYMaMGVixYgWJHQRBHDWMMfsEiMbPdo+qqipUVVW5ljl7OubMmYM5c+b0924RPYViLARBDHJc52iMgUU7M4od2dDTc7TNmzfjvffewwsvvID29nZ86UtfAgB88MEHWLduHf7whz8gGAziZz/7GX77299i8eLFePnll/H4448jFArh5z//OZ588kn88Ic/xDPPPIMlS5bgxBNPBJB87nTuuef6nuM5Y/47d+5EYWGhq96hpKQEDz74IADY52d/+MMfEIlEUF1djQMHDri++w8cOIAHH3wQFRUVuOyyy7B161asWrUKjz/+OP74xz8CACRJwoknnoh//OMfOP/883v836GvGfJiR3DaeVkpe1pdLdqfWgloKgDzDZX/pf+GNGJsj55/69atuPDCCxEIBBAIBFz/U4waNSrtmwgwbU3Ox2/cuBEA8NOf/hR/+ctfUF1djXfeeQednZ0AgHPOOQdXXnklzj//fMyZMwdTp07Fc889h23bttkZsmg0ajsq7r33XtTX1+OLX/wibrzxxqTn37t3r8vy5LfPu3btwqhRozBlyhQAwMKFC3HnnXfa9/PXfPzxx6OlpcX3dVZUVGDv3r1p/xYEQRDpcF7ppRgLQQDMmjA3FGMsBokdBDGo6fY5mq4Bkoz8S5ZDrux5l19Pz9HefPNNzJ49G4qiYOTIkXb885///Cf27t2Lyy67DIB5Ufikk05CQUEBfvazn+H//u//sGfPHvz1r39N2Unod+7kd47nZM+ePSgvL3ctmz59etK2//73v+Oyyy6DIAioqKjAmWeead83ZcoUjB8/HgAwadKklOdt48aNGzTnbUNe7MgWuXIqChfdha7XHoe+9x0AAIv1vLdDFEUYKbyWoVAo837JsqsVv66uDiNHjsTVV1+N008/HaeffjrOPPNMfPe73wUArFq1Cjt37sRrr72G5cuXY8mSJdB1Hddcc41tO25ra4MkScjPz8eLL76Iv/71r/jLX/6C//3f/8WmTZsgigk3iyAIUBQl7T5LkpTyNfL7+bayfZ0EQRDdxXmlV9WGzpVsgjhqrBjL0JrGYv6k0bMEMTzg52jqvu1QJkzrFaED6Pk5miAIYA4hmRd367qOCy+8EKtWrQJgjm/XdR0HDx7E1Vdfja9+9auYOXMmRo8ejdpa/w4Sv3Mnv3O8Sy65xLU/3vLw7p63OR/vfX3ebTjPFwcyg2Mv+wm5ciqUihPt270hdpx11lnYsmUL4vE4Ojo68Oqrr3brpP6zn/0stmzZAlVVEYlE8I1vfAMffvgh9uzZg5tuugkzZ87En//8Z+i6Dk3TMHv2bIwYMQLf/OY3cckll6C2thZnnHEGNm7ciM7OTmiahhtvvBGbN2/GE088gV/+8pe48MILsXr1ajQ3N9uloZwJEyagrq4u7T4ed9xxaGtrw/vvvw8AeP755zO+LkmSoGmafbuurg4TJ07M+u9CEAThxSV2kLODIIZojIUKSgliuCFXTkX4rMt6TegAen6OduaZZ+LFF19EPB5Ha2sr/vrXvwIATj/9dLz00ks4fPgwGGO47bbb8Nhjj2H79u2YOHEirr32WkybNg0vv/yyXUoqSVLagtJU53hOJk6ciP3792f1ujdt2gTGGOrr6/Hmm29mfN3e87b9+/djwoQJGZ9rIEDODg+25RO9M5Hli1/8Iv79739j/vz5KC4uRllZmatMJhMXXHABduzYgQULFsAwDCxevBjTp0/HwoULMW/ePMiyjDPOOAPRaBTxeBzLli3D17/+dQSDQYwaNQp33303Ro0ahZ07d+Kyyy6Druv4whe+gPnz59sFpVVVVZAkCcuXL09q6T/nnHPwz3/+E7NmzUq5j4FAAD/5yU/w/e9/H6Io4thjj82oiH72s5/F97//fYwePRpXX301/vnPfyb1hRAEQXQH55VeVaMTIYJgQ3Eai/U+J7GDIIie0NNztPPPPx/bt2/HxRdfjNGjR2PSpEkAzCjIkiVLcM0118AwDEydOhXXX389NE3D73//e1x00UVgjOGzn/0sPvjgAwDAF77wBaxevRr33HOP73PJsux7judkypQpaGlpQXt7u6u3w8tll12GnTt3oqqqCqWlpRg3bhxCoRAikUjKx5x33nm45JJL8Kc//QmyLOO9995Lua8DDYGl8qcMcNrb27Fr1y5Mnjw56T9obW1tygxUJrpefhixNzcAAPK+9F0ETzmnR/v573//G3v27MH8+fOhqiouv/xy3HXXXXa/xUAnFovhyiuvxNNPP+2KszgxDANr1qzBkiVLkJeXh0ceeQT19fVYsWJF1s9z5ZVX4v7778eoUaOS7uvJf0+CIIYPrZ0arrjjXQDAmm8ej5OPGRwz4PuCdN+RRO8ykP/W8ff+is4Nd0MaewKKvnZfrnenV/jp0/vwyn9asOLKCZg1fUSud4cgiG4wkI7pB/s5mh+/+93vIIoivvrVr6Zc59VXXwVjDOeccw7a29vx5S9/Gc888wxKSkqyeo6XX34ZNTU1+P73v590n99/31x/R5Kzw4uesOigF2Isxx57LO6//3488sgjYIzhy1/+ctKb6O2338aPf/xj38c/9NBDRz0TuTcIBoO44YYb8NRTT+Gaa67xXUcURZSUlGDhwoVQFAUVFRWugtJMVFdXY86cOb5CB0EQRLY4CwupoJQgAGao/Jfc7kgvwgtK0zi+CYIgMjLYz9H8uPLKK7Fs2TJceumlCIfDvutMmjQJ3/ve93DfffcBAJYtW5a10GEYBtavX481a9b00h4n8/zzz+PXv/41NE3DNddcg6uuusp1/7vvvotbb70Vqqpi7Nix+OlPf5qUTHBCYocHZhhAIAzEI70SYykpKcFvf/vbtOvMmDHDnrIyELngggsyrnP99dfj+uuvP6rtz50796geRxAE4cQdYxk6J3cEcdToQ3Eai/mTYiwEQfSEoXCO5kVRFPz6179Ou8748ePx+9///qi2L4qiPcq2L6ivr8fatWvxpz/9CYFAAFdccQVOP/10HH/88fY6d955J5YtW4ZZs2bh7rvvxm9/+1vcfPPNqfe5z/Y2xxx1OsfQIATyAEHslYJSomcM0pQVQRA5QCdnB0G44W7VNBPTBhuMRs8SxKCGju2HJpn+ux46dAh1dXWuf21tba51tm7dijPOOAMlJSXIy8vDnDlzUF1d7VrHMAx0dnYCACKRSMaeyCHp7AiFQjh8+DBGjRrV/XGmhg5BkoBgHokdOYYxhsOHD2c1/okgCIKmsRC5ZNeuXbnehSSK9n6M0QAikS58UFOT693pFeacaP4D9qCmZk+O94YgiO7yr3/9K9e7QPQhNSm+a6699lo0NTW5li1ZsgRLly61bzc0NKC0tNS+XVZWhm3btrkes2LFCnz961/HXXfdhXA4jHXr1qXdnyEpdlRWVqKurg6NjY3dfmxxSzMUzYDABMQ//BcO5L8IddQxvb+TRFaEQiFUVlbmejcIghgEOK/00jQWor8ZiAWlUW0vIjuBUDCIz3zmM7neHQDAkQ4Nuw9F8Knjj+5v9aPHd+ON99rw7S9VoOrM0b28dwRB9CWqqqKurg7RaDTXu0L0MvyczTvQgheUPvroo0k9It6uDcMwXEYFxpjrdjQaxS233IJHH30U06dPxyOPPILvf//7eOihh1Lu15AUOxRFwbHHHntUj+3YWQCtTQDr7IAUa8eorQ+hcNFdvTrXmSAIguh9XJ0d+tCx7RPE0ZIYPTsw3g/N7Sq+//BHOHA4ho0/mg5Z6qb7Fon6EersIIjBR0/O0YjBTXl5ecYLAuXl5Xj77bft242NjSgrK7Nv79q1C8FgENOnTwcAXH755fj5z3+edptDtrPjqDF0QFcB8G9TDeq+7TndJYIgCCIzOjk7CMKNLXYMjPfDHU/sQV1jDIYBaEcpSFJBKUEQxNDkrLPOwhtvvIHm5mZEIhFs2bIFM2fOtO+fOHEiDh06hI8//hgA8Oc//xnTpk1Lu80h6ezoEYYGIZAP1tVqHhxIMpQJ6f+IBEEQRO6hGAtBeBhAzg7GGN6v60JQERFTDWhHOTqWv8/JvEUQBDG0GDNmDG6++WYsXrwYqqpi4cKFmD59Oq677josW7YM06ZNw//8z//gO9/5DhhjGDVqFO66666028xK7Pj5z3+OzZs3QxAELFy4EF/72tewdetW/M///A9isRguvPBCe+RLbW0tbrnlFnR2dmLGjBm4/fbbIcsyDhw4gOXLl+Pw4cM49thjsWbNGuTn56OtrQ3f/e538cknn2DkyJG47777XMUk/Q0zDAihfEjlJ8DoaEbB/BUUYSEIghgEOE9+aBoLQQDMyL3YEY0bkEQgrjEYBjCiWMahlrjl7JAyPj6mGhAFQJFNMzLFWAiCIIYuVVVVqKqqci17+OGH7d9nzZqFWbNmZb29jDGWN998E//4xz/w3HPP4ZlnnsHjjz+OnTt3YuXKlXjggQewadMm7NixA6+99hoAYPny5bj11luxefNmMMbshtTbb78dixYtQnV1NU455RQ88MADAID77rsPM2bMwIsvvoivfOUruPPOO7Pe+T5B1wBJgphfDDG/mIQOgiCIQQLFWAjCg+XsyOWoxx8+8jF+++JBdERMK0dJgXmdLVtnx+rHduPh/ztg3zb46FkSNAmCIIgMZBQ7Pve5z+F3v/sdZFnG4cOHoes62traMHHiRIwfPx6yLKOqqgrV1dXYv38/otEoTjvtNADAggULUF1dDVVV8dZbb2HOnDmu5QDw6quv2urNxRdfjNdffx2qqvbRy80CQ4cgSIAoJ4q9CIIgiAGPU+w42j4AghhS6NbxVA6dHYfbVHzSGLXFjhGFXOzIbp8aWuI43J44HqPODoIgCCJbsoqxKIqCX/ziF/jf//1fzJ0713cGbn19fdLy0tJS1NfXo6WlBQUFBZBl2bUccM/TlWUZBQUFaG5uxpgxY+zttLW1oa2tzbVP8Xj8KF9yBgwDkGVAkgH9KAOlBEEQRL/jcnbQVV+CSFy0MXIndhgMaOvU0R4x96U4v3vOjrjGXM4U/jvpmQRBEEQmsp7GsmzZMrzxxhs4ePAg9uzZ4zsDN9VsXO+MXABJt52PEUX3bj322GM477zzXP9uuummbHe9WzBDA0QJgigBBjk7CIIgBgtOfZpiLAQBc8IckNNpLIbB0NalJZwdVowlW2eGqhlwrkrODoIgCCJbMjo7PvroI8TjcUydOhXhcBizZ89GdXU1JClRKsVn4JaXl6OxsdFe3tTUhLKyMowcORLt7e3QdR2SJLlm5paVlaGpqQnl5eXQNA2dnZ0oKSlx7cM111yD+fPnu5bF43G0tLT05LX7Y+gQRBmQFIqxEARBDCLI2UEQbtgAiLEYjKGjy3B0digAADVLa4aqMTDHezsxjYXe4wRBEER6Mjo76urqsGrVKsTjccTjcfz5z3/GFVdcgd27d2Pv3r3QdR0vvPACZs6ciYqKCgSDQdTU1AAANm7ciJkzZ0JRFMyYMQObNm0CAGzYsMGemTtr1ixs2LABALBp0ybMmDEDiqK49qGoqAiVlZWuf302scXQAVEy/5GzgyAIYtDgHj1LHneCGAijZw3DnKhyuNUUXnhnR7ZJ4bjH2UHTWAiCIIhsyejsmDVrFrZt24Yvf/nLkCQJs2fPxrx58zBy5EgsXboUsVgMs2bNwty5cwEAa9aswapVq9DR0YGTTz4ZixcvBgCsXr0aK1aswK9//WuMHTsW9957LwDgpptuwooVKzBv3jwUFhZizZo1ffhyM8MMHRBFCJKcsH8SBEEQAx6nmYNiLAQBh9iRwxiL9dT7D8cgSwLyQ6YzOJvx0LrOoBuJCSzO7VFnB0EQBJGJrApKly5diqVLl7qWnXnmmXjuueeS1p0yZQrWr1+ftLyiogKPP/540vKSkhI8+OCD2e5v32NogGgWlFKMhSAIYvBguKaxkNhBEMwePZtLZ4f5XjzQFEdBWIIsmZ1t3vfohr834pOGGJbOr7SX8agLczk7mGu7BEEQBJGKrMSOYYWhm+WkopS4IkIQBEEMeHTr5CmoiNTZQRBAIo6b484OANjfFMOIQjml2LFjTyc+OhBxLeMOLVdBqfVSKMZCEARBZCLraSzDBWYYgCRBkBQSOwiCIAYR/OQnGBCgUYyFIBIO1ZxOYzF/dkR1FIQlSKIpdnjFCsNgSV07cet9zFwxFquglJLGBEEQRAZI7PCia4BgOTvAzA4PgiAIYsDDM/whRcx60gNBDGkGQkGpQ9ModMRYvO4rXWdJXTtxS/wwHLtPBaUEQRBEtpDY4YXHWCTZvk0QBEEMfBLODpEKSgkCAPjoWSP3MRYAKAgnYiy6V+wwEk4OTlzlMRa/glJ6jxMEQRDpIbHDi6EDkmxOYwEoykIQBDFI4Cc/IUWkglKCwECJsTjFjtQFpZrBbCcHh8danLtvx1hI7CAIgiAyQGKHBz56FqIpdtBEFoIgiMEBOTsIwoPtTmWu3ot+3QVnjCUvtdihGwyG4XZ8+BWUJmIsfbO/BEEQxNCBxA4vhgZBdDg7DBI7CIIgBgOGq7ODxA6CsGMsQE56OxhjLleGy9nhU1AKwNW341dQygwaPUsQBEFkB4kdXgzDLCcVJfM2OTsIgiAGBW5nB132JQiXOzUHzg6vHlHomMbinZjEp6vwng7Av6BUp84OgiAIIktI7HDAmGFe+XAUlNI0FoIgiMGB4ejsIGcHQcDtTs2F2OERJFwFpUZyjAVwT2mJ2zEWh7OD8W33+u4SBEEQQww51zswoODChihBEHlBqZp6fYIgCGLAwN3vwYCYdNWYIIYjbmeHDkDp1+fneoYgmCJFpoJSwHRzPFJ9ELrBcPy4MAC3TsOooJQgCILIEnJ2OLHEDoGcHQRBEIMOnZwdBOFGVwHBOtTLobOjKM88pspUUAqYMZbtuzuw7eMO+33s3HUuapLYQRAEQWSCxA4nPDAqJcQO6uwgCIIYHOgGgygCiixQZwcx7GGMmcc1coAv6Pd94HrEiePzUFaiYHSxAsk68vSKHYaeKCiNqQaiccPu7NBdMRZydhAEQRDZQTEWB7aLQ5BMdwdAYgdBEMQgQTcYJFGALAnQDfOqsmiVIRLEsIMZABgEOQCmRsEMHf39buBdG6dNKsDt1xxrLzffo15nh/lTVRliKkNMNeyyUneMxb0+QRAEQaSCnB1OrCIvQZQAkWIsBEEQgwndACRRgCL72+QJYljBO8dy6eywBAnRc7QpiUJS1ExzFJTGVAPRmGE7tJhDGDFssYPe3wRBEER6SOxwwr+VJdkRY6GCUoIgiMGAYTBIIqBYPnnq7SCGM7ycVJCtUlLW/1YI3tkhCW5PiSIJ0FN2dhiIqwYicd0xjSV5myR2EARBEJkgscOB7eIQRQhc7CBnB0EQxKDAGWMBAJUmsgwbOjo6cPHFF6Ourg4AsHXrVlRVVWH27NlYu3atvV5tbS0WLFiAOXPm4JZbboGmmYLAgQMHcNVVV2Hu3Lm44YYb0NnZmZPX0avwGK7EnR05EDust6A3TiZJyc4OW+zQTGeHbgBdUfMYzC/GYjge//d3W9EZpeM1giAIwg2JHU74PHpRBqzODkadHQRBEIMCb4xFpVD/sOCdd97BlVdeiT179gAAotEoVq5ciQceeACbNm3Cjh078NprrwEAli9fjltvvRWbN28GYwzr1q0DANx+++1YtGgRqqurccopp+CBBx7I1cvpPXg0V8llQan5nN4YiywhydnBry3FNQMxq6ujtVN3bcf5O397H+nQcMcTe/DatiO9vPcEQRDEYIfEDieO0bOCZNk+SewgCIIYFBiOaSwAdXYMF9atW4fVq1ejrKwMALBt2zZMnDgR48ePhyzLqKqqQnV1Nfbv349oNIrTTjsNALBgwQJUV1dDVVW89dZbmDNnjmv5YMeOseTS2WE9pSfFAlkSk96fvLPD6dBo6zJfgyvG4uns4L0esTiJmwRBEIQbmsbiIBFjkWxnh+32yIBWVwt133YoE6ZBrpzaR3tIEARBpIJiLMOTO++803W7oaEBpaWl9u2ysjLU19cnLS8tLUV9fT1aWlpQUFAAWZZdy/1oa2tDW1uba1k8Hu+tl9K78Is1VmcHy6Wzw6N2yGKyGMnFi45IQuxo7TRfA0szelaz4y8kdhAEQRBuSOxw4hQ7pOynsWh1tWh/YgXADEQlGYWL7iLBgyAIop/RdbMbYGSheXK3tz6KCWWhHO8V0d8YhgHBcXLNGIMgCCmX859OvLc5jz32GO6//37XssmTJ+O2227rvRfQW+jeGEvunB2ST2eHljR6NlnsaO/iMRbHNj2jZ3kcho+pJQiCIAgOiR1OXDEWPo0ls7Mj/v7WhANE16Du205iB0EQRD/DnR0nT8zHiEIZf/lPC74wrSTXu0X0M+Xl5WhsbLRvNzY2oqysLGl5U1MTysrKMHLkSLS3t0PXdUiSZK/vxzXXXIP58+e7lsXjcbS0tPTNi+kBjE+T47Fco//FDmY7O9zLZc80FsaYvXtc4ACAVh5jcew688RYuOhBHT0EQRCEF+rscKJbX7BSoqA0G7FDLOIHRQIgyVAmTOub/SMIgiBSolujZyVJwDmnjsBb77ejrZN6l4Ybp556Knbv3o29e/dC13W88MILmDlzJioqKhAMBlFTUwMA2LhxI2bOnAlFUTBjxgxs2rQJALBhwwbMnDnTd9tFRUWorKx0/XNGYwYU9ujZ3BWUcv1BSCooFVwxFqdO4XR2RGLmHc4Yi3f0rEbODoIgCCIFJHY4sCMrgmhfCclmGosQNG3S8jHTKcJCEASRIwyWsMuf+6kR0HSGv+44ktudIvqdYDCIu+++G0uXLsVFF12E4447DnPnzgUArFmzBv/zP/+DuXPnoqurC4sXLwYArF69GuvWrcNFF12Et99+G9/5zndy+Ap6B/uYRs7l6NkUnR1JYkfid6fYkdhO8u9e0YM6egiCIAgvFGNxwse0STKEbhSUGm1NAABpzHEkdBAEQeQIHmMBgOPGhjBmRADbPu7EvNNH53jPiP7glVdesX8/88wz8dxzzyWtM2XKFKxfvz5peUVFBR5//PE+3b9+x4qxCLkUO6ynFEUfscPwFzvaI8nHXdzZ4XR4eDs7KMZCEARBeCFnh5OjLCg12swMMItH+2zXCIIgBgMPbzqAZ//WmHnFPkDXE2KHIAgYXaygtYNiLMQwxZ7GkrsYC3d2SJ7ODkkUoGndd3Y4uzt0j7ODYiwEQRCEFxI7HPiOns0ixsKdHYhH+mjPCIIgBgdvvd+G/3zYnpPn1g0G0fGtVpwv26MrCWK4oTXsAQCwzlbz5wBzdjgFDmdZqa/YYW2HiyeyJIAxM8qSbvTsweZYj/afIAiCGNyQ2OHEIXYIomR2d3RD7GAqOTsIghjeqCqDqufmCqthuEdcFudLOEJiBzEM0epqEX39CQBA/N2/mAtz2NnhneSbrqC0K5a8n4kYi3lbsawiusESMRZPZ8euui58/ac7sfsQXYgiCIIYrpDY4cQxehYAIMlg2XR2tFsxlhh9oRIEMbxRdQPxHBUFOjs7AKAkX0Zbp2YXGRLEcEHdtz1xAYfbInIRY+HOjm4UlHKcZhA7xsLFDpmLHY7Rs57PnXZrbO0RirIRBEEMW0jscGI7O6zeVlHK6Oxg0U4g1mX+rpLYQRDE8CauMqg+dvL+wC/GYjCg3ccWT7h5/vnncdFFF2H27Nl48sknU6736quv4txzz+3HPSOOBmXCNNhvBn4BJ5fTWDKOnk0WOwrzEh363NnhjLHwx9mjZz2fO3yTNKWFIAhi+EJih4NEZ4f5ZxEkOSGApICXk0IQqaCUIIhhj6qzAePsKC4wT5aotyM99fX1WLt2LZ566ils2LABTz/9ND788MOk9ZqamnDPPffkYA+J7iJXTkVg+gUAgNCsr5oLjf4XO7iZRPKbxqL7d3ZwSgoSYgcXLvj2uNhhGCzl6FnDdnzQlBaCIIjhCokdTiwXhx1jEWUwa3RbKox2s69DHFFOBaUEQQx74pqRsyuphgFIkrOzwzxZIht7erZu3YozzjgDJSUlyMvLw5w5c1BdXZ203qpVq7BkyZIc7CFxNAjhAkCSIY+ZZC7IQYyFCxHezg5J9I6edd8vikBBWLJvM2a6O7izw6+zw+vs4G6QXImvBEEQRO6RM68yjOCXAayxs8jC2aHu3QYAEPJKYBz+pC/3jiAIYkCj6wyGkbsrqUmdHeTswKFDh9Da2upaVlRUhKKiIvt2Q0MDSktL7dtlZWXYtm2b6zG/+93vcNJJJ+HUU0/t2x0meo9YF4RAnlm2jhxPY/GoHYokuNwc3hhLUBERDpj7zV0g5vQV6/GyaD3OMXrW6+ygGAtBEMSwZ9CLHbt27eq1bRXt3Y3RAN7ZvgNGIB/jVR1tjQ3YWVPju37wyD6Me/NZAIC2fyfAgJoU6xIEQQwH7lgIAFpOPgv/62wA6EBNzWH3/sQ/wnD9aL722mvR1NTkWrZkyRIsXbrUvm0YBgTHyShjzHV7165d2LJlCx599FEcOnSo73ea6BVYPAIhGE7YKgZQZ4ckCa6pTVywEEVT0AgpIkKW2BGQE2IH8+vsSBVjYf6OD4IgCGL4MOjFjsmTJ6OwsLBXthXVP0FkJ3Dqpz4NMVSA1rfzkFdchAmf+Yzv+pGtHyHKnC3nDJ8+bToESemV/SEIghhMtHVquPyOd5EfErF+9bR+f/5v/GwnTqgI4/tXTARgOk0uXrUNXz1vDK46v7zf9yeXtLe3Y9euXXj00UcRDodd9zldHQBQXl6Ot99+277d2NiIsrIy+3Z1dTUaGxtx6aWXQlVVNDQ0YNGiRXjqqaf69kUQPYJ5nB0DbRqL7tPZEQ6I6IwaCCgiwkFzv4MBEV0xAwZjtltDdsVYzGVeRxkjZwdBEMSwZ9CLHb2KZ/SsIKaPsSgTpiEqiObVElEEDB0sHoUQJrGDIIjhB7eR5+rkQjeY66RKkgQUhiUcGcYxlvLy8owXBM466yz88pe/RHNzM8LhMLZs2YIf//jH9v3Lli3DsmXLAAB1dXVYvHgxCR2DABaPQAjkQeC2ihw4O7gTQ/KbxuKIrvDfQwEJnVEDQUVAOGAeiwUV88EGSwgY9uhZPV2MhX8ekbODIAhiuEIFpQ4S01isUiwpfUGpXDkV8rGfhhDMR/D0BeZCKiklCGKYolotg3GN2Sc5/YlhMEiSe1lJgTysOzuyYcyYMbj55puxePFifPnLX8bFF1+M6dOn47rrrsP27dtzvXvEUcJiXUCOYyzcvCF4nR2iAMMw37NAwgFiuzkczo6QwjtHmL2+3+jZJGeHPY2FnB0EQRDDFXJ2OPEROzIVlIrhAhh5RZDHHIcYzCspBEEQw5G46rhSqzP76mt/4S0oBcyJLDSNJTNVVVWoqqpyLXv44YeT1qusrMQrr7zSX7tF9AAWj0AcMS7HMZbUnR2A6egIiILtzuDCRtDR2eF0dnAziOIzelY3zDgM3zZfl6axEARBDF+ycnbcf//9mDdvHubNm4ef/OQnAIAf/OAHmD17Ni655BJccskleOmllwAAtbW1WLBgAebMmYNbbrkFmmYeZB44cABXXXUV5s6dixtuuAGdnZ0AgLa2Nlx//fW48MILcdVVV6GxsbEvXmd2WKNn+YGBIEqJZSlgugqIMoRAyLxNYgdBEMMU1TE/srdOMBhjiKvZXZHWDUD0ih3k7CCGKSzWZRWU5i7GYheU+nR2AImuDv4z5HR2cLEjYK7rLChNTGNhrkkuzs8girEQBEEQGcWOrVu34m9/+xueffZZbNiwAe+++y5eeukl7NixA0888QQ2btyIjRs34oILLgAALF++HLfeeis2b94MxhjWrVsHALj99tuxaNEiVFdX45RTTsEDDzwAALjvvvswY8YMvPjii/jKV76CO++8sw9fbgaYYQoX/EtZksGMDAfJhg5BkoFAnrmJeLSPd5IgCGJgojqcHb1lHf/bjlZcddd76Iymd9kBVozF861WnC8P684OYvjCOzt4jIUZOejssJ7Sr7MDgB1B4Z0dXOAIKIJL+ABM8YK/hESMBXZBKeD+3LELSnVydhAEQQxXMoodpaWlWLFiBQKBABRFwaRJk3DgwAEcOHAAK1euRFVVFX7xi1/AMAzs378f0WgUp512GgBgwYIFqK6uhqqqeOuttzBnzhzXcgB49dVXbevsxRdfjNdffx2q6u7JaGtrQ11dnetfXzhAmK4lIiwAIMrub9FUj5Eczg6VnB0EQQxPnG6O3rqaWt8SR0dUx76GhJBsjqFMPoHxi7GU5Mto79JdV38JYqjDDB1QoxCCOZ7GkqazA0iIHdyQEQ44nR2eglIDSdNYDMfoWcD9GWSkKC4lCIIghg8ZxY4TTjjBFi/27NmDF198EV/4whdwxhln4K677sK6devw9ttvY/369WhoaEBpaan92NLSUtTX16OlpQUFBQWQZdm1HIDrMbIso6CgAM3Nza59eOyxx3Deeee5/t1000298gdwYehwttsJkgxkcnboqil2KOZoP3J2EAQxXHEKHL11gsF7QOoaYwCAaNzAojvfxV+3tyatqxvw7exgDGjvyuwMIYghg3UsIgTCicKMXBSUpujskGW32MGFiVAwIXCUlSgQBGB0sTnhjrGEyOkePesUO5wxFvMnxVgIgiCGL1kXlH7wwQf45je/ie9973s47rjj8Ktf/cq+7+qrr8aGDRswadIkl3rPGIMgCPZPJ97bzseInm/Fa665BvPnz3cti8fjaGlpyXb3s8PQ7bGzAABRNp0b6dB1CI7ODprGQhDEcKUvnB385GV/kyl2NLWqaI/oONgcS1rXz9nBJzpE4jpKqJObGCaweBcAQAjmQUDuprGk6uzg71PuyrA7OxwFpVMm5OOJH5yEN95rtbblKCiVHTEWZ2eHT4yFnB0EQRDDl6wKSmtqanDttdfiv//7vzF//ny8//772Lx5s30/YwyyLKO8vNwVL2lqakJZWRlGjhyJ9vZ26FYkpLGxEWVlZQCAsrIyNDU1AQA0TUNnZydKSkpcz19UVITKykrXP6eDpLdghg4IDrFDkjI6O5jBYyzc2UFiB0EQw5N4N5wdb7zXit+/Up9xmzxvz50dLR1mzDEWTz5x0w2WdAWZT3SI+qxPEEMVFjOPRYRAOMfTWMyf3vel4ikotTs7gu5S0pGFin1xjLGEeOI3ehbwODsMXlBKYgdBEMRwJaPYcfDgQdx4441Ys2YN5s2bB8AUN+666y60trZCVVU8/fTTuOCCC1BRUYFgMIiamhoAwMaNGzFz5kwoioIZM2Zg06ZNAIANGzZg5syZAIBZs2Zhw4YNAIBNmzZhxowZUBSlL15rZpJiLErGaSzQNTPuogQBUIyFIIjhi6r5X2H148//bsGf/pq5e0m1JrF80mh+tra0m5/JMc/2mVVemOTsILGDGIY4nR25jLFwfUXyOjsssUK1OzssZwfv7JATh6f8LW0YzN6eU+wwnM4OR0kyxVgIgiCIjJ7e3/72t4jFYrj77rvtZVdccQWuv/56XHnlldA0DbNnz8bFF18MAFizZg1WrVqFjo4OnHzyyVi8eDEAYPXq1VixYgV+/etfY+zYsbj33nsBADfddBNWrFiBefPmobCwEGvWrOmL15kdSTEWCSxDQSl0zZzgIkqAEqSCUoIghi1OgSOe4QSjtUNDR1RHTDXsAkI/uEPkwOE4dIOhud10dnjH0Rr21Af3SRU5O4jhCItZYkcgnJjGkosYi6U4eJPLSaNnvQWlAafYYZWROpwdztGzmmv0rDPGQs4OgiCI4U5GsWPVqlVYtWqV731XXXVV0rIpU6Zg/fr1ScsrKirw+OOPJy0vKSnBgw8+mM2+9jlGRzNYLAKtrhZy5dSsCkr5NBYAEJSwbR0lCIIYbjivoGY6wWjpMD9bW9pV/PG1RrR1abjlqmOS1uOiiaYz1LfEE84Oj9jBrwx7R1yS2EEMR+xIbY6nsei8s8MjQnpHzxq8s8OKsQQczg4ulDDH6FnFOXrW8dZ2iqBcA8kkvBIEQRBDl6w6O4YDWl0ttD3vgEXb0f7USmh1tdbo2QwxFkOz3SBCMAyoFGMhCGJ40p2C0lZL7Ghu11C7rxN76v0/O53brGuM2c6OmOo+cTNSnFSFrPGVkRid8BDDh4Szwyl25MLZYf5MmsbiETs0b4wlkHgf2zEWhqQYi5E0jcUZYyFnB0EQxHCHxA4Ldd/2xIGArpm3JcksIE2D6ewwO0YEJUQFpQRBDFviWTo74pqBjqgZEWxuV9F4REVnxD8yqKoGykrMz9i6xpjt7PDGWPRMMRaVxA5i+MCPRYRAODH9zshdZ0fGaSy8oDSQGD3LSVtQqrsLSlWHzYOmsRAEQRAkdlgoE6YBcsC8AiLJUCZMy66g1EjEWBAIU0EpQRDDFndnR+oTjNbOxOfq/qYYOqI62iO6nbF3EtcYRhcrKM6XsbchmpjG4hU7dB5j8Rc7/Ka3EMRQxXZ2BMOOgtIcTGNh/vEy7zQWrlEU5pliR34o0Z/mV1CaGD3LoBsMQcW8HaeCUoIgCMJBxs6O4YJcORWFi+6Cum87lAnTIFdOhfpxDWCYB+CCt12LoydiLDA06K0NducHQRDEcMI1jUVPfYJxpCMhdrz/iXlSpukMcS1x0sKJawYCsojjxobw8YEImjN1dkiuxbbYQTEWYjjB4l2ApECQFLCcjp7lBaXZTWM5flwYt159DD59fKG9Lo+mGSyxPXdnB0MoICGmaq7PIBo9SxAEQZCzw4FcORXhsy5LCBWipQUZqSey8BiLVlcL/eCHYO1Nic4PgiCIYURcM+yLyHE19QmGU+zYua/L/r3DJ8qiagwBWcCkcWHsqY/arhDv9lPFWGRJgCwJiKoZJmsRxBCCxSLm2FkAAI+B9P97QLdjLO7lSdNYHM6sM08qtsUQwFNQ6jN6VteZPcXF6eJgtrODxA6CIIjhCokdaRB4PCVdlMXQIEiyf+cHQRDEMELVGPKDprXCOQLSCxc7CsOSPZUF8Bc74hqDoog4bmwYmp6wscc0f2eHtxsAMN0dNI2FGFbEu8yxs0BuYyz8fZliGovT2SEKyesBCaGEOQpKvaNnw9YUF9+C0jQuM4IgCGJoQ2JHOiw/dKqSUsaYKYSIktn5wa2iVucHQRDEcCKuGXbWXk1TCMrFjuPGhl3LfcUO1YAiCa5184JiUgdHqtGzABAmsYMYZrB4V8LZwY9NclpQ6l4ui97ODuZyczjhERidseSCUoNBNxJxNWdJMn+5cY359gERBEEQQx8SO9IhmhMAoKewfvJ4i6RArpwK+YTTASWIwkV3UWcHQRDDDlVjCCgCJDGzsyOoiBg7KuBa3hn1d3YEFBGVo4MIWKWE5SMDSQWohpGwwXshZwcx3DDamsCiHWak1nY75WL0LIMgpO7sSExj8X/vAm5jChcwEqNnTcEkIIvm547jc4ELHIwlYm4EQRDEwOb555/HRRddhNmzZ+PJJ59Muv/jjz/G1VdfjS996Uv4r//6L7S2tqbdHokdaRB4052h+q9gOT74elJRKQRRJqGDIIhhSVwzTzoCspg0GtbJkQ4NIwpkjCw0BeVRReZP/84OAwFZgCQJOKY8BAAoHxn0KSg1f/pdHSaxgxhOaHW10Ot3w2htQPtTK6Ef/MC8IyfTWJJdHUCiYFRzdHb4ubKARDTNMBIChnMai6YziCIQkEV3Qanj5cZpIgtBEMSAp76+HmvXrsVTTz2FDRs24Omnn8aHH35o388Yww033IDrrrsOzz33HKZOnYqHHnoo7TZJ7EiHVVDKUjg7GO/y4N0espJYRhAEMcxQNQOKLECRhbTOjpYOFcUFMkYWmZ+dx401RYyOiI5/fdCO2r2djm2aAgoATBpnRlnKRwSSxI5U3QCAKXZESOwghglmZ5j1/tO1RGF6DmIsusF835OSV+wwWEpnh19BqeKKsTDIkvm544qxOMQdKiklCIIY+GzduhVnnHEGSkpKkJeXhzlz5qC6utq+/91330VeXh5mzpwJAPjWt76Fq666Ku02afRsOjIVlHIRxIq7CKIM6ClcIARBEEMcLkwospgUM3FypEND2YiA7ew4pjyEt95vR2dUx4Mv7MeYkgB+/LXjAJhXZPlV3EvOKsXEMSF0RQ0Yhnmi5MzuA/6dHaGA6JoAQxBDGWXCNEQhAGCAJEMef4p5B8tNZ4dfaXBiGot5O11nh7Og1NvZoenMFkoUj7ODkbODIAhiwHDo0KGkyElRURGKiors2w0NDSgtLbVvl5WVYdu2bfbtffv2YfTo0Vi5ciVqa2tx3HHH4Yc//GHa5yWxIw3GkXoAgHZwF6RRFT4rmMKGHXeRZIAZYIYOQZT6azcJgiAGBHHNQFGebDo7rJOLaNzAvoYoJlfm2esd6dRw4vg8W+wYNyqIoCKiI6KjoSWO4nzzq0nXzfJB7uyYOCaEiWNCeOavDQCAmGpAtj5/U42eBcyC0kPk7CD6mF27duV6F2zGh0tgSAqaTv4SYo0RHAdg//46HKmp6df9+NQY4FOXADU+z3vHQgDYh5qaffj8BODzE/zX4+t2Ne2EYv3e2bjTevx+TPm8tdLJABBBTY35+XBaGXDaQvOufR9ux75efWUEQRBEd7j22mvR1NTkWrZkyRIsXbrUvm0YhqvjiTHmuq1pGt5880088cQTmDZtGu677z7cfffduPvuu1M+L4kdKdDqahH9++8BAF3/93NIJeVJXRzeGItrVC2JHQRBDDBe33YEb+9qw/9bOKFPth/XGBRZQEAWbGfHlreb8dD/7ce6W09BXlCCYTC0dmoozpcxaVwYl80qw5knFeOJl+tx4HAMMZXZfR98ZGRAcQsYQUv8iKmJ6S/pRs8GfWIs9S1x1LfEMf24gl78CxDDmcmTJ6OwsDDXuwEAaH27AFLpRJSfNx/M0HHkJWDc2LGY9JnP9Ot+PPj8frz8r2asX+2eUKcbDBffsg1fPX8MrjqvHGvW7cOOPZ149HvJnWf/+agdP/jNx/jJ9ZPQ1qXjjif24FfLJuO/H/wQF31uFP65sw2TxoWx51AE48tCWHXVMQCA/++F/djwd/PA+sHvnIiJY0J9/noJgiAIN+3t7di1axceffRRhMPuKXxOVwcAlJeX4+2337ZvNzY2oqyszL5dWlqKiRMnYto08zvl4osvxrJly9I+P3V2pEDdtz3hrzQ0KwPrwY6xWCKHxKe3kF2aIIiBx/bdHdj6bvrW6p7gjLFwO3lzuwrdSExaaY/oMAygpECGLAn42tyxKM6XURCW8PHBCAAgrjLXTx5j4QT5mElHbwcvIOUjKJ34FZSuf70Bdz61p6cvmSAGJowlRs4KjhxIP2MYzFeAlEQBsiTYnxNmFMV/G/zx5jQWc31BMEXQmGqYnR2ikFRQ6ny5KsVYCIIgckp5eTkqKytd/7xix1lnnYU33ngDzc3NiEQi2LJli93PAQCf+tSn0NzcjJ07dwIAXnnlFZx88slpn5ecHSlQJkxDVLI6OEQZyoRpySvpPMbiFjuYrsE/eUoQBJE7zDK/vtu+qhkIKKazg59c8AkrkZh5u63TFIN5VIVTEJawtz4KAIhaIgZ3h/AYC4c7PWJq4myGiykF4WRXXTggJYkdHREdHV26eTKWohiRIAYtzLBFDoGLHjno7NCZf2kwYIqYXLDMpqDUYMwWMERBQFAWTbFDZ5Ak83NBTVFQmq5DiCAIghgYjBkzBjfffDMWL14MVVWxcOFCTJ8+Hddddx2WLVuGadOm4Ve/+hVWrVqFSCSC8vJy/OQnP0m7TRI7UiBXTkXenG+ja9PPEZp1te84WWZYzg5vjCXVqFqCIIgcohuJuEdfENcYFEm0OjvM5/GKHa0pxA4eRwESjg1eKhjwOjscMRYOfx7ndjihgAhNZ65C00jcgMHMn36PIYhBDTMgiA6RUBBzMo2FMXMsrB8BR5GxbviPjQbcxhQuYIgCEFDMEdcaLyiV3MXIbmcHiR0EQRCDgaqqKlRVVbmWPfzww/bvp556KtavX5/19ijGkga54kQAgFRU5r8Cd3bYMRY+qpZiLARBDDx0a3JBX8FHz5onMeaJFXdcROLmz9Yu82dRvltgKHQ4MriIwU9QAor7q8ovxpJwdvjHWAC43B1RS3zpivqPFieIQY0zxgJYikEuYiyJaSpeAo5RsemcHZKldhhGwtkhCAKCioCY5h4963J2OLQdmsZCEAQxPCGxIx1KEADAtKjv3WkLSgmCIAYYusFgGObV1r4grjEEFMHl7Gg/CmcHj6fwExTFc8U3YDs7Eq+jI6JDEoGgklrs4IKL8/dOEjuIoYgjxgIAEESwHMRYDObf2QFYYof1Htb11J0diRhLorNDFMz3epzHWETzc8fp7HDGWMjZQRAEMTwhsSMNgmyKHVDj/ivYMRbF9ZPpFGMhCGLgwU8U+sLNzhiDasdYEnZy29nh7ezI84gdDmeHZjlQEgWlHmeH3dnhdnbkhyXXiDIOFztiDmcH35/OKF3xJYYejLEksSMXMRbDSNPZoYhZOTsEZ0Epd3aIpuPLLCg1IzABWYTq+ExwxVj6sqyIIAiCGLCQ2JEGwXZ2xPxXsGMs1kE6TWMhCGIAw4/3+yLKouo8ciJAkRJ28s6IJ8bSqSEcEJOiKYWeYtG4aiQ6O7yjZ5XkGEtHREdBiu4NvxgLH0VLzo6hzcaNGzFv3jzMmzcP99xzDwBg69atqKqqwuzZs7F27Vp73draWixYsABz5szBLbfcAk0bxN/lzEiOseRiGgtjaWMsrmksKTo7eOdHckGp6QzRLFeILAlwplVcBaUqOTsIgiCGIyR2pEMOAACY6i92pCwoJWcHQRADEM1InFj0Nqpjcoo5FYGBMZYUY2nr1FGUn9yNzWMso4rM+2Kq4dqmEy6UxDSPsyOD2BHx6ewgsWPoEolEcOedd+Lxxx/Hxo0b8fbbb+OVV17BypUr8cADD2DTpk3YsWMHXnvtNQDA8uXLceutt2Lz5s1gjGHdunU5fgU9wCt2iGJOprGkc3Y4u310A5mnsRjJBaUxzYBhjZ4VxYR7ja/PC4m5GEsQBEEML0jsSIMgyYAoAynEDng6O6iglCCIgYyuJyYf9Daqo19DkUSoGkNcM6+6AkCXo7OjOD9ZlOAjYytLQwDMPo6U01h4jCXu7uzwGzsLJDs7GGPoos6OIY+u6zAMA5FIBJqmQdM0FBQUYOLEiRg/fjxkWUZVVRWqq6uxf/9+RKNRnHbaaQCABQsWoLq6OrcvoCcw5op0CYKQG7EjjbNDcXR2aGk6OyQ7xsISMRZBQFAREbOmKkmiAEkUXEIuY0DIEkad8RaCIAhi+ECjZzMgKEEwLUVnh2caCxWUEgQxkNH70NnBOzoURUBAMacs8HGwABCNmb+3dWkoKUj+6hk3KgBRAKaMz8M7H3UgphppOjusGIvD2dER1TG6WPHdN6/YoWrMri8gsWPoUlBQgJtuugkXXnghwuEwPvvZz6KhoQGlpaX2OmVlZaivr09aXlpaivr6+qRttrW1oa2tzbUsHk9xjJBLkqaxiLmJsaRzdiiiXVhspO3ssLbFEuXKomjG27iIKkkCREGA86PNYAzBgICOKDk7CIIghiskdmRCDoCpKaaxeGIsVFBKEMRAhp/gG30hdqiJyIkiCVB15hI7eISktVPDhLJQ0uOPKQ9j3a2nYPvHHdb2DLtU0NvZYcdYnAWlkdQxlrBH7HDGWXIldjDGEFOZLcQQvc/OnTvxzDPP4C9/+QsKCwvx3e9+F3v27HE5HpjlgDAMw3e5l8ceewz333+/a9nkyZNx22239dnrOCp8prEMNGeHt7NDTtHZ4Swo5S9BFMzPmi5LRJX8YiwsEYGjzg6CIIjhCYkdGRCUYMYYi2B3dlBBKUEQA5eEs6P3t82FCUUWoCgiGEuMmQWcMRYdxT7ODsDs7eBCRlQ1oNoCivskSBIFyJKQNI0l2xhLJKY7Hpcbe/tTr9Rjw9+bcM91k3Dc2HBO9mGo87e//Q1nnnkmRo0aBcCMpvz2t7+FJCX+P2lsbERZWRnKy8vR2NhoL29qakJZWVnSNq+55hrMnz/ftSwej6OlpaWPXsXRwXwKSlkuprGwTJ0dic+kVOuJtrODQbecHTzGwl+SLJkxFudLZIxBlk0RhKaxEARBDE/oklIm0sRYbAeH6O7soIJSgiAGIn0aY/E4OwCgud2K+glmjCUaNxBTDRTn+YsSgHPSCktEY+Tkr6qAI+8f1wzEVJaxoNTX2RHJjbPjXx+0oyOiY9X/foyGIwMwBjEEmDJlCrZu3Yquri4wxvDKK6/g1FNPxe7du7F3717ouo4XXngBM2fOREVFBYLBIGpqagCYU1xmzpyZtM2ioiJUVla6/jnjLwMGvxgLchFjSePssOJuAO/sSDWNRbC2Bcc0FrfjSxTNZbqnoFQSzA4h/llCEARBDC/I2ZEBQQ6mnMYC3RtjoYJSgiAGLn0pdricHZYTo6Xd/CwcUSCjK26grcu8XewzjYVjl486R8/KySdBwYCImGrgSIdm5/hTjZ4NyCIEISFy8EksQG5iLKpm4IP9EXzmhELUfNCON95rxSVnDcAT5kHO2Wefjffeew8LFiyAoiiYNm0ali5dis9//vNYunQpYrEYZs2ahblz5wIA1qxZg1WrVqGjowMnn3wyFi9enONX0AMGSozFMMfE+hGQRdu9pRupC0r5w5lz9Kwo2MIoYDo7RFFwjZs1GIMg8LgMOTsIgiCGIyR2ZCBtjMXwxliooJQgiIELd3L3RWeHarswBDsn39JhOjtKiwOIxAy0WbEWv9GznKCjjyOumScrfln+oCzik8YYrr77PVw7pxwAkJ8ixiKKAsIBEV2WsMEjNQFZsDP//clHByJQNYbzPj0CNR+02/tD9D7XX389rr/+eteyM888E88991zSulOmTMH69ev7a9f6FsZcYocgCEBOYiwMYgoRQ5ETzg4jTWdHIsaSEGoFwT2SWransSQex/8EiqMbhCAIghheUIwlE0oQTPMXO5h39KyouJcTBEEMIPqys4MLCflByRYsGlpMsWN0iYJoTLc7PNI5O5zlo6pmQJEE36LIgCKgdl8nNJ3h7ffbzedO4ewAgNHFih0XiVpjZ0cXKznp7Kjd1wUAmH5cAWRJcHWIEESvwAwIA2EaSxadHYwxy9mRRUGpI8YSdMVY/AtKRcEUX0nsIAiCGJ6Q2JEBM8aSavSsJWrw0bMyLyilzg6CIAYefRlj6eBiR1jCcWPNaSvvfNyBoCKiMCyhK26gtdNcpygvs7MjrjLEVea6eutdj1+o3vmJKR6kKigFgLKSABqOmJ/NPM4yulhxTYzpL2r3daKsRMGoIgV5QRFdOSpJJYYwhifGIuYqxpK+swMwx8JqenYFpfboWUGwhVHAirFYo2f5OoZhukoURzcIQRAEMbwgsSMDghIANP/RszA0QJQSVx2poJQgiAGMofeh2GGJBvkhCRPKQsgLijjSoaEgLCEcEBGJGQlnR0G6glJ3Z4ei+J8AOfP6vHg0nbOjbEQADS2mcB2xYiOjihTbkdKf1O7rwkkT8wEAeUHJ3h+C6DWSCkoFc0JLP8PdFX5wIVPVWNrODruglJn/ACvG4vgMkKwYC18P4DEWwTX1hSAIghhekNiRiTQFpUzXEgIHAIhSYjlBEMQAg8dXdL33D/w7IzpEAQgHRIiigCkT8gCYbotwUEI0bpaJiqIZdUmFO8aS2tnBrwo7c/7pnB1jShS0R3REYrrt7BhVpCASN/rk75EKTWdoalUxvtR0v4SDIiJxirEQvYfpbPCIHchRjMVI39kBAHHVyBBjMX8yxmw3lygICDqKiyVJsJ+Hi7kGY3bcJRonQZEgCGI4QmJHBgQl3TQWDYKYEDsEUTIPLkjsIAhiANKXnR0dUR35Icm+CnvSBNO5YIod5lfNnvooyooDKe3qgHmFVpYE29nhN4kFSDg7Tp9SZC/L5OwAgIYjKqIxU5gZWWhGD/uzpDSmmn98Pg43LyRRjIXoZRz2B04/xliiDvEu0zQWAIhrLKuCUmYkIirJzg73iFog0RcSCogkdhAEQQxTSOzIgKAEAS1FZ4fhcXYAgKSAGSR2EAQx8OjLzo7OiOGahjLVimnkhxJix0cHujBudCDjtkKKaHZ2aMy++uuFix3nf3oEANPhEUwReQGAMSXm89a3xNEVMxAKiLYTpD/Hz3KxgztTwgExJxNhiCEMP9v3xFj6YxrLRwciWHj7Dny43+zRSTeNhQuZqmZAN5CxoNQZY0kaPSsKdgyGj59l1ujZUEBCjMQOgiCIYQmJHZmQg4Ch+0ZTmK7Z5aQcQZYBjTo7CIIYeNgxlj4qKC1wOCtOHJ8HQQAKwxLCAXP54TYNFaOCGbcVUCxnh2qkjLHkhyQUhCTMOLEIiiygICz5Tm3hJJwdcUTjBsJBEXkhLnb034lQ3BI7+IlaXlCk0bNE78KSnR3mZJa+j7H8fccR6AbsMuB001gUO7LGoOksdUGpQ8Tg0RTAPY1FsgpKAWeMBXa0jpwdBEEQw5PUlfgEAMvZAQBqLNnFoWsQvMtEhTo7CIIYkNgnAX1SUKq5nB35IQkLZ5bacRbOuNGZxY6gIiY6O1K4Na44ZwxmzxgJWRIwvjSImJr+NY0okCFLAhqOxBGJGwgFJOSHzLOo/nV2mPtpix0hiUbPEr2LFVcRnJYKoX9iLG9aY6C5gyntNBZZcK2bsqDUM3qWazjeglJbFOExFoNBlkUEAyKiKokdBEEQw5GsnB33338/5s2bh3nz5uEnP/kJAGDr1q2oqqrC7NmzsXbtWnvd2tpaLFiwAHPmzMEtt9wCTTNP/A8cOICrrroKc+fOxQ033IDOzk4AQFtbG66//npceOGFuOqqq9DY2Njbr7FHcLGDacm9Hcw3xiIDBjk7CIIYePRlZ0dn1HA5OwDg63PH4YyTihEKJr5qxmXh7AhaMZZ0BaWjixVMrjRLUM//9EicfUpx2m2KooDSYgUNLSoiMR15QdHe31zHWGgaC9Gr2M4OzzSWPo6xHG5T8dGBCACH2JHFNBb+/3+qzg7+cNvZYaknQe80Fh53MXiMBVaMhZwdBEEQw5WMYsfWrVvxt7/9Dc8++yw2bNiAd999Fy+88AJWrlyJBx54AJs2bcKOHTvw2muvAQCWL1+OW2+9FZs3bwZjDOvWrQMA3H777Vi0aBGqq6txyimn4IEHHgAA3HfffZgxYwZefPFFfOUrX8Gdd97Zhy/3KJBN67NvSalfjEWSqaCUIIgBidGHnR0dEd3l7HDCYywAUNENZ0dcM1J2djiZf3Yprp0zNuN6ZSMCqG/hzg4RhXnm5zcfSdsfJMVYQhIicaNP3DbEMIU7OJIKSvv2/7G33m+zf0+IHZk7O3ihaarODrug1HJ2iLazI7G+LAkQJR5jgfXcptASsj5P6D1GEAQx/MgodpSWlmLFihUIBAJQFAWTJk3Cnj17MHHiRIwfPx6yLKOqqgrV1dXYv38/otEoTjvtNADAggULUF1dDVVV8dZbb2HOnDmu5QDw6quvoqqqCgBw8cUX4/XXX4eqDhxnhCvG4sXwibFIMsVYCIIYkPRlZ0dnVE85+jXPcnaIIjBmROaCUruzI42z42goK1HMzo6YgXBQQlmJguPGhlD9drM95aGviXnEDl7eGqErz8RRoO75Dzo3/RJdf3kMkb8/Da2uFsxP7BD6Xux456MOFOWZnwE8rpVuGotiiRW8syZjQalhjp7lt4OOzwZJAiSHA4Svz50djAFxjd5jBEEQw42MnR0nnHCC/fuePXvw4osv4qtf/SpKS0vt5WVlZaivr0dDQ4NreWlpKerr69HS0oKCggLIsuxaDsD1GFmWUVBQgObmZowZM8beTltbG9raElcMACAe758rcWljLLpmfsM615cUcnYQBDEg6atpLJrOEI0nx1g4PMZSPiKQ0qruJKiIaOvSEFONlJ0dR0PF6CBeqmmBpjNUjA5CEAR86azRuO+ZOuzY04lpxxb02nOlgp8E2jGWoPk3i8SMtKNzCcKLVleLjt//0NHFISAqK8i/dJV12zONhfVtXKu5XUVlaRDv7e2yHUxccPCDC5k8YpLKASLaIgZcBaWKLJgvi/HOjuQYCx89y58nFKD3GEEQxHAi60tmH3zwAb7+9a/je9/7HsaPH+9qvTfHewkwDMN3Of/pJFVrPmMMoucb77HHHsN5553n+nfTTTdlu+s9Q7bEDtVHXNE1CKLiXiYpYPrAcaYQBEEApsDBL+z2dnSfd16kOlnPs07os+nrAEyxozOio7lNxejizE6QbDnzJLPXo61Ltx0VXzx1BArDEp5/o6nXnicd3NkRckxjAUDjZ4luo+7b7ikdZYCuQfvkXfOm41hK6AdnR1uXjuJ8GQFZcHV2pHJs8BgLdzWlEkK9BaX8tiAI9jbM0bPeGIspjDjFDj8YY3jqz/Wo78c4G0EQBNE/ZDWNpaamBsuWLcPKlSsxb948vPnmm64i0cbGRpSVlaG8vNy1vKmpCWVlZRg5ciTa29uh6zokSbLXB0xXSFNTE8rLy6FpGjo7O1FSUuJ6/muuuQbz5893LYvH42hpaTna1501dozFx9kBXfcvKCWxgyCIAYbTzXE0zo6PD0YwblTA98poR8Q8UU8VYwkFRAhCdn0dgOl6ONgch8GAyiwfkw0TykI4oSKMD/ZHELZOgIKKiNOnFuFfH7T32vOkI24XlHKxI+HsIIjuoEyYhii3NnAkGXLlVMSAfo+xtHdpmFyZZ3fuANY0lpSdHZbQZ4mlcsoYi/nTYCzJKRKQRcRU3XR28PV8CkqB1GJHa6eOx18+BEUW8JVZZVm/XoIgCGLgk9HZcfDgQdx4441Ys2YN5s2bBwA49dRTsXv3buzduxe6ruOFF17AzJkzUVFRgWAwiJqaGgDAxo0bMXPmTCiKghkzZmDTpk0AgA0bNmDmzJkAgFmzZmHDhg0AgE2bNmHGjBlQFLdboqioCJWVla5/zrhMn8JjLD6dHcxQfWIsVFBKEMTAw+iB2KHpDDc/8AHWveY/LYuLHamcHZIo4LtfmYAvf350Vs8XVETwXcxWIMmWc04bAQAIBRP7Om5UEM3tmn2C1pckjZ4dIM6O559/HhdddBFmz56NJ598Mun+l156CVVVVZg3bx5WrFjRb1FSIjVy5VSIIysgjhhn3j7mVBQuugty+SQAlpuDIwi9b+lywBhDW5eOwrCEgCImOjvSTGPhnR1NreYFIl4Y7IU/nDFze86XxUVDSXLEWLiDzYqx8PdaKrGDfza2ddGxG0EQxFAjo7Pjt7/9LWKxGO6++2572RVXXIG7774bS5cuRSwWw6xZszB37lwAwJo1a7Bq1Sp0dHTg5JNPxuLFiwEAq1evxooVK/DrX/8aY8eOxb333gsAuOmmm7BixQrMmzcPhYWFWLNmTV+8zqNGkFOLHdBTFJT6rUsQBJFDnONmuzt6tiOiI64xvLen0/d+O8YSTq2fn/upEVk/n3OkZG+LHV88tQSPbTmE0cUJUb18pBmVqW+JY0JZqFefz0uioNTd2dGVQ2dHfX091q5diz/96U8IBAK44oorcPrpp+P44483962rCz/60Y/w7LPPYvTo0bj55pvx7LPP4vLLL8/ZPhMWjEEqPx5GRzOksuMgV06F0W5FsjzODoa+c53GVAOqxlCUJyGkCInOjrTTWMw7GltN4aykIJXYYbo2DCuKJzleF38fSaIAyXoeLuYmxVhSiJm65Xhp76IoGUEQxFAjo9ixatUqrFq1yve+5557LmnZlClTsH79+qTlFRUVePzxx5OWl5SU4MEHH8xmX3NCuhgL03XA09khSApNYyEIYsCh6wk3h6F3z9nBnRu79ndBN1hSBp+LHakKSrsLFztKCuSU0ZijZUShgkeWT0GR4ypyuTUh5lBz34sddoxF9kxj6SNnx6FDh9Da2upaVlRUhKKiIvv21q1bccYZZ9gR0jlz5qC6uhpLliwBAOTl5eGVV16BoiiIRCI4fPiw6/FE7mCxLgjBMIRAGCzeZS203t8uZ4fYp86ONksoKMyTLWcHj7Gk7mhTrI6OhhZThCnJT31IKgiJglJXjMX6rJAl+BaUCoKQMcbC/yztERI7CIIghhpZdXYMZHbt2tWn2xfVCI4BsO/jD9Fm1Ljuq+zqQFxuw/s1ieVlbR0IdLThgxr3ugRBELnmjoX8t72oqdl7VI/9z7//lXRfnnX/4f3v4fD+Hu0iAGB6KTB9IQBodiyyr7ljIYDOD9DXTzdlhPlc/3b8He9YCIDtRk3N7l5/vmuvvRZNTe7y1SVLlmDp0qX2be8ktbKyMmzbts31GEVR8Nprr+F73/seysrKcPbZZ/f6vhLdh8UjEAJ5EIJ5YLGIucxX7BD6tLODR0CK8qSkzo5UA5hEUYAsCQlnR2E6sUNIxFiczg5LNDQ7OzwFpUZ2BaV8VC3FWAiCIIYeg17smDx5MgoLC/ts+0xTceQVoLK8DOHPfMZ1X+s/ZBSUlmG8Y3ln3SvQ4i34jGddgiCIXNLUquLqu98DAFx30Tgs+EL2vUc1u9qx6pGPAQDfubQSc2aMct3/x9ca8L/VB/Hs7af0ymjH9a834LcvHsTsGSNx86Xje7y9TDDGMH/1Dlz0uZG4/uKKPn2uXz+3H6/8uwV/XH0KANPpccmt23HtnHJc/sUxGR6dPe3t7di1axceffRRhMNh131eV0aqSWpeZs2ahX/+85+49957cdttt+FnP/tZr+0v0X2YoQNqFELQEjtsZ4d1Uu/4byiIIhjrO2dHu8PZEXR0dvDxr6kIyAK6YgwBWbBLg/0QBVOUYIzZcRUgMcJZkhIxFi5e8L4QLnbEUogduu5+DQRBEMTQIevRs8MWSTavjvgVlOoaIErJ69M0FoIgBhg9mcbSEU1c8dz1SSTp/s6oDkl0d230BL6d3u7rSIUgCCgfGcChfhg9GVMNBAOJkz9FNq9u99U0lvLy8qSCb6/Y4Z2k5pyYBgBHjhzB3/72N/t2VVUV3n///T7ZXyJ7WNx8L5oxljywWLoYi+AZU9u7cKHAdHYItrCgW70ZqQg4Imup4i6AKZgwlhyL4Z8VkpgoKNU901i4iBKJG/i/fzZhx54O17bJ2UEQBDF0IbEjA4IgAHIATPM5CNbV5IJSUabODoIgBhw9ETs6I+aJy8QxIez8JLmktCOiIz8spT1Z6Q78BKY3x85monxkAIea+0fs4H0dgPkdEw6I9vjNXHDWWWfhjTfeQHNzMyKRCLZs2WJPTANMp8fy5ctx4MABAEB1dTU+/elP52p3CY4lbvAYC79tl1D04+jZRIzF6uzQHJ0dGZwdQOpyUo5gFZSm7OwQBbsI1XDGWEQg6Iix/O+LB7H5rWbXtnnHR3uXnogAEQRBDBAYY/jhIx/jH++1Zl6ZSILEjmwQJWifvAutrta93NAByVNQKiuAQWIHQRADi56Mnu2ImJ9pJx+Tj/1NyS63zqjea+WkADCqSIYoAseO7duyUCflI0yxo69PduIaS3LAhINiTqexjBkzBjfffDMWL16ML3/5y7j44osxffp0XHfdddi+fTtGjBiBH//4x/jmN7+JL33pS9i9ezeWL1+es/0lTLiTI1WMRfBOY+mXGIvV2RF3TGPJxtmRppwU4DEWKxbj2B6fxiKKsIuTvTEWRTKFkLZODV0xI8lFxTs+NJ0hkiLqQhAEkStiKsPbu9pRu68r17syKBn0nR19jVZXC8Q6oR/chfanVpoz7CunAkgdYyFnB0EQA40ejZ6N6pAlASMLZMRUljSRpSOiI78XxY5Pn1CIR783FaXFgV7bZibKRwYQiRto7dQzXmXuCbG4kSR25IUkdPXRNJZsqaqqQlVVlWvZww8/bP9+/vnn4/zzz+/v3SLSwMUNIZhnTmNJirE43pOmNaLP9qWtS0M4IEKRRQQVEXHNEhx8pjc5sZ0dhUrKdQB3QamzAySoiJBEPp7WirFYbyVmuUAEQUBIEe2Ymve9ZjgEzvYuHXnB3p0ARRAE0RParQtOcY3E2KOBnB0ZUPdtT9zQNfdtQ0uKsQiSAmjU2UEQxMDC6eYwjiLGUhCWELZOArxTDVo7NRRnuDLbHQRB6FehAzDFDgA41JzsXOlNYpphlypy8oJin3V2EEMX5omxsFiX6UzyKSjt6xhLe5eOwjzz88HZ2eF1YnhR5OydHYwxGIYnxiKLkKWEuwNIdnYA5kSWg1ZMzftec2pA1NtBEMRAo8Mai61qFLM7GkjsyIAyYRoA65tVkq3bMO2ghg5t//vueIsoA4ZGuU+CIAYUPSoojWjID0kIBf1HOLZ2an3qhugPRhWZV5ZbOvr2ZMfX2RGUSOwgug0fNctjLGAGoMXAwJ0dHrEDfevsKMozPwN4ZwdjLMmJ4SXbzg5RFKDbMZbE9j43pQhzP2tOh7JjLLyzgzFbAAkFRLuTxxtVcYq/bZ00kYUgiIEFFzvI2XF0kNiRAblyKqQxx0IsHuOKsGj73jV/7n0H7U+tTAge3OlBvR0EQQwgdJ35/p4NHVYnhz3VwHFizhhDS8fgFzvC1sjcvhYdUnd20EkW0T3cMZY8c1msy1FQ6i7C7YsYi6oZaI9oaHM6OwIiDCNxFTJdbzEv682moNQUT9wdIJ+ZXIhvVZnjormwYU9jMRLPHQqItkjrLQN2ir/t5OwgCGKAQc6OnjG4j077CaFgJCCIttABANrebYkVrHiLXDnVLCi1lnnLSwmCIHJFjzo7IjoKwzLCtrMjcbLQFTOgaqxXYyy5IC/Ix1P2regQU5NjLGefUoIJZdE+fV5i6OGMsSDIxY5Iv8ZYnnqlHi/VNEMSBZSPyAcABC0Bg5fupnV2KFk6OwRz9/k4WT8kwV1QyjwxFk5SjMXxZ2nrItGRIIiBBYkdPWNwH532E4ISgqG6D0SlcZP5va54C0TzT8p0DWkuZhAEQfQrPRs9q6N8ZNB2PzgnhxyxYh8jBrmzg0d0nCdCNbvaUJwv4/iKvF57npiaHGOZOb2k17ZPDB/sQtJAyIyxwHJ7WCf7guj4/0wUEyJIL9LSruFwm/kZcPoU7uwwj364KCr1QmeHIAgwmDVONoXaIXpiLLrDBeJ8z3XFdau81Co0JWcHQRADGD7timIsRwfFWLJACITAVHdpnVw6EQCgnHimK94icDeHTiWlBEEMHFwFpd28wtsRNQtK+dVRZ2cHFzsGe4wlpLivRgPAgy8cwMObDvTq88R9xA6COBpYPAIEwhBEyR1jYckxFghCn4ye1RyRuELe2SFzl1QWzo5sOzvsGEsaZ4c3xsIAQUx2dhgG7Gkx5m2H2BEhZwdBEAOLDmsaCzk7jg464soCQQkBHmcHsyauBKZ83hVv4Z0dNH6WIIiBhOFydmT/OMYYOiKa2dnhE/U40snFjsEd2xNFAeGAiKijOyOuGti5r6tXr6bE1OTODoI4Gli8yxY5hGDYXpYYPdv3MRan2FFkdXbYoqglHGbq7BAE2OWmqRAFAYZhRVNSiCfc8WHYYkfC2eEUOwAg4nifOz8PaRoLQRADDSoo7Rl0xJUNShAs7hE7dLPVO6mXgxeUkrODIIgBhKuzoxsFpTHVgG4A+eFEQWnUFWMxP+sGu7MDMKMszkkNms4Q1xg+qIv0yvZ1g0HTWVJnB0EcDSzWBSFgihwJZ0ckhbOjb2Isms5QlC+hOF/GMeXmvgS8nR1p1I6JY0KYXJkHKV3WBaZgYvgUlDpJjJ41f+qeglK+Hee+meszaz8TdnGCIIiBQjt1dvSIwX902g8ISgjQVTBDhyCaVy6gmWKHXUjK15UcBaUEQRADhKPt7OBfsgVhCeFg6s6OwV5QCgB5AdH12vhV6x17OnDyMfk93n5cNbdNzg6iN2CxLrurw+7siHWB2Q6OhCrQV9NYNIOhtDiAXy45we7A4J0d3AEmpvnf/UtnjcaXzhqd8Xl4QWn6GIu7g8N0dlgxFus9V1qsoOGI6urm4X+W4nyZnB0EQQw4ulNQ2hnVIYlAyOpYI8jZkRVCIGT+4ujt4DEWSAH3yhRjIQhiAOLq7OiG2NHJxY6Qf2dHa4eGwrAEOcOV2cFAOCi5YiwqFzt2d/bK9mMkdhC9CIt32fEVd0Gp9f4UPc4O9EGMRWOQRcEWOoDENBYuKEjpcixZIohmQSljLHWMxVNQak5jMX8PWULt2FFBa9+cMRbz71JcINM0FoIgBhzdibH8+PE9uH/D/r7epUEFHXFlgaCYYgdz9nZYMRVBdosdAsVYCIIYgHCXgiQmd3YcaIrhQFPM51FARzTh7JAlAYosuDo7Wjq0IRFhAYBwUERXPNnZ8e7ezm5Ff1IRU81tUIyF6A3MGIs1KUhSzGlwMWdnRz/EWAwGWXb//xz0iKLpCkqzRRRMkdZwCBh+6wDmeokyU3dBaYUldvjFWPJDki1IEgRBDBS6E2P56GAEze10DuqExI5s4GKHo7eDWTEWyN7ODvM2OTsIghhI8KudAVlMirHcv7EOv9xQ5/s4fkUhP2ReGTVLPB0xls4hJHYERPtqNGNmv8aoIhmRmIHG1niPt0/ODqJXccZYBAFCMM81jUVwFZQKYH0RY9FNZ4cT7zSWXjB2QBQEM8ZiMPfrcuCMsXC9h5tbeIxl3GjzAlWXw9nB/yzhgAhVpUw8QRADi4SzI/3nU2dUR0dEdxVHEyR2ZIWgmFcCXM4Ou7PD39kR3/YytLra/tlBgiCIDHCBQ1GEJLGjrUtPOXKx09HZAZhRj4hn9OyQETscMRY++YFPmXFeCT5aqLOD6E3MGEuefVsIht0xln6axuKNsNmdHbHMnR3ZwgtKWTpnB4+xsMRLFT3OjnF2jCXxfuafh8GASNMOCIIYUPCJeACgZvh8OtQct9YjscMJHXFlQaKzw+nssCxCHrFDP2zmpOLbXkb7UytJ8CAIYkBgix1SsrMjGtNdPRxOOrxih8P9AAw1sSMRY+F9HcX55uvujHY/y//LDXVY/3qDfTtKYgfRSzDGwKJd0Bv2JI4zBBHawQ+gN+6zb9uIfSh2eGMsns6OdNNYskVwFJSm2h4XVXSDQbdeK191+nH5+OKpJThxfJ5r34CEsyOkiIhrzFHwShAEkVuicXMiniRmdnYcajbjyOTscENHXFmQ6OxwZNq5s8MzelZr+Nj6jQG6BnXf9v7YRYIgiLRwgSMgC0mdHZG4kVLs4I6GvKD5dREKiHZnh6oZ6IjoKMlXfB872HAKOfxgoSjPFHK6ot2/4vuP91rxnw877Ntx6uwgeglt7zYADNq+HWh/aiVi/34RxpFDMA7XIfLqo+ZKrs4OAWC9X77pF2PxdnZIvdDZIVkFpWaMJfU6AO/sMJdxt0f5yCC+f8VEFFvvZ2dBKe/s4Put0okCQRADBH7BqaRAgaaztAXzh1rMc1MSO9yQ2JEN3ejskCtPtn4TAEmGMmFaf+whQRBEWnTr2D6gJDs7InEDsZRih24Vk5pfF+GgaJ/EtHbyL+Gh4uyQEI0bMAxmHyzwkbrddXYYBsORTs0ueAUoxkL0Huqe/1i/mRdW4ju3Jpwb/M3uUAWEfoyxBGQ+erb3OjsEISFiZCoo1a2pLc5lHEkSEFQEVxGxs7MDIAs4QRADBx4xHlloHoukEzLq7RgLxfGc0BFXFnRnGosyfqr5c/IZKFx0F+TKqf2zkwRBEGlwOjucVwYYY4jGDTti4SUSM2xXB2A5Oyz3Q5NV2sm/hAc7Yet1RlUj2dkR657Y0dalwzDcIgnFWIjeQq6YYv1mXlgJTDkr4eSQJOsu7zSW/hE7BMEUFHq3s8MqKM1q9Kw5icV8XPJ6eUHJd/Qs7/WI00QWgiAGCNzZMbLIvLieLsrCnR3kTnNDR1xZIATMQqtsOjsgm+vKE6eT0EEQxIDB7uyQBfvCL2COQ2XMPGnxuxoQjRsIByX7dp6joPSjgxEAwLFjw3245/0HFzsiMQOalfUpLjBfe1c3nR1HOszviI6I09lh2eVJ7CB6iFw+CQCgTD4dhYvuQvBTF0KqnAohfwRCZy8yV/JMYwEzer2Pwk/sAMz/x/nnRG90doiOgtJUm0uMnk24NfyeOxwUPZ0dHrEjzcnEs39rRM2u9qN4BQRBEN3H6+xI59qwC0pJ7HBBR1zZ4Ofs0OKAIEIQJdeqfHKLUxghCILINYbt7HDHWKLxZOeBk66Ybtu7Abez48P9ERSGJZSVDJXODvPzPBJLjG7LC0qQxO5PY2npMNvTOyK6fYKZGD1LnR39xSuvvIIFCxbgwgsvxB133AEA2Lp1K6qqqjB79mysXbvWXre2thYLFizAnDlzcMstt0DTBvAIeev/KeX4z9kXVsS8EgjhQkgjKwBY0RWO/Xvvix2Sj9gRUBIjqlM5MbpDNgWlgiBAFPnoWf8YC2DG1ZzvZ/5xGLJjLKnf63/6WyNe+XfLUb4KgiCI7sEnsYwsTO/sYIyhnnd2UBTPBYkdWWDHWOKJglKmx5NdHQAgKQCERKcHQRDEAICXkpoFpYkvQudBv19JqensSHxVmJ0dpkDy0YEIjq8IQ+iNUP4AgMd1InHDvjKiyALyQ1K3Ozta2s0DFE1niKlusSNAzo5+4ZNPPsHq1avxwAMP4LnnnsN7772H1157DStXrsQDDzyATZs2YceOHXjttdcAAMuXL8ett96KzZs3gzGGdevW5fgVpIZx64J34gqfmey9j//ey84OXWdQMjg7fO7uNqLojLGkWU8QYDBnjMXf2dGVLsaS5kRBNxhilIcnCKKf6IyYnze8Gy2VGNvSriGuMQQVgQpKPdARVxYIkgyIstutoalJfR2A9cUqB9yTWwiCIHJMIsbidXYkvjj9Skq7YoZ9EgCYJwQxlSGmGth9KIpJ44ZGhAWAHdcxYyzm30iWBOQFpW5PY2mxYixAorfDjrHI9NXbH7z00ku46KKLUF5eDkVRsHbtWoTDYUycOBHjx4+HLMuoqqpCdXU19u/fj2g0itNOOw0AsGDBAlRXV+f2BaSD8ZyGt5fDSNznjbEAiXxHL6GmcHY4Ozt6QwwVBUC3YyyptyeJghVjSe3syAtkiLGk6ewwDOr0IAii/+Cfo7wsPVWBMnd1jBsVpBiLh6HRKtcPCIGgK8bCtLjl4vBZVwnao2kJgiAGArphXhGVJAHOYSyRLJwdo4sSn3U86vH+J13QdIYTKvL6bqf7GX6y0xXT7avViiQgLySis5sFpUc6EhGIjoiOUUUKYqoBWRJ8Tw6J3mfv3r1QFAXf+ta3cPDgQXzxi1/ECSecgNLSUnudsrIy1NfXo6GhwbW8tLQU9fX1Sdtsa2tDW1uba1k8noPvex9BQxAlwNBhR1Uczg6BiyKsd0/UdSO1s6PLjrH0/HkEQQAzzLGL6VIxiRgLv+3n7JAQaUpckOLnBSEl8+hZ3WC2aEkQBHG0vLmzDfubYph/dmna9aKqgaAi2F1fqZxnPIZcnC9j96EoGGO+wrCmM9z0q1342pyxmHFiUQ9fxeCAxI5sUUJJ01gEOUVOXQ6AaeTsIAhi4KAbDJIoQBJN6znH1dnhI3ZEYrrL2cEjLdt3dwAAjh9Czg4eY4nGDOQFubNDRF5Iyrqg9L5nPkFMNSA5TrJ4SWlMNeyxnETfo+s63n77bTz++OPIy8vDDTfcgFAo5DoA5AeEhmH4Lvfy2GOP4f7773ctmzx5Mm677bY+ex2+WGfzgifGwpjhiLg4nR29H2NhjKUsKB0zIoDafV3mbvWSs4NZ8ZR0m5MEy9mRZhpLyoLSIHd2pP4bGQaz42gEQRB+7NjTgfvWf4L7bpyMgrDku85f/tOCdz7uyCh2RGIGggERinXskCrGwo/rgoGEaOt3vBGJ6fj4YBTv7esisYNwIyghd2eHlqKzA6azg2IsBEEMJHQDltjh7uyIxNM7O7yjZ3lZ6baPO5AXFFE+0v9zcDDCYyxdcQNFjhhLfkhC45HUV+83/fMw9jVE8a2qCry3rxOHW1WcOD7PFJYc42djqmEfiBB9z+jRo3HmmWdi5MiRAIDzzz8f1dXVkKTEwWdjYyPKyspQXl6OxsZGe3lTUxPKysqStnnNNddg/vz5rmXxeBwtLf1cWmk7O5xih2R1diSLHXpbAwBA218L5dhP9cou8KiXn1PpuLFhvPrOEXO3euF/edESMViaglLA+hMwBiNNQWmep6CU9xnZzo40nRy6AcSps4MgiDTs3NeF/Yfj2FXXhU+fUOi7jm4wtHVqplstjV0tGjcQDki22JHK2cE/x7gDRNMZAj5n+fz474gjajvUoaOuLBGUkE9nR4oYixygGAtBEAMKXWeQRFhiR2K5K8bic8UyEjfsK55A4urnjj2dOOXYgl6ZtDBQSIye1T2dHWLaaSxvvd+GP/+rBYwxNB1R0RUzsHNfF8aNMqdzcWdHXGXU19GPnHPOOfjb3/6GtrY26LqOv/71r5g7dy52796NvXv3Qtd1vPDCC5g5cyYqKioQDAZRU1MDANi4cSNmzpyZtM2ioiJUVla6/jnjL/1GKveGoSfcG9a0OK2uFvF/vQgA6Pjjj6DV1fbKLtg9QL5iR8j+XeqlaSzm6Nn0BaWSIGSMseQFRcRUw95/w4r4KXLmglKDJQqHCYIg/ODT2D4+GEm5jm64L4akIho3e9MCMhdjU4kdfLS9+ZmXaiILP/5zRm2HOuTsyBLBE2NJ5+wAOTsIghhgGHaMRbBt24DbzeF1dqiaWdTJHQ9AorPDMIDTpw4tCySP60RiiWks3NnRFdVtC7vz7wGYBysdUR2NrartlInEDYwvC+GTxlgixqIZCNDY2X7j1FNPxTe+8Q0sWrQIqqri85//PK688kocd9xxWLp0KWKxGGbNmoW5c+cCANasWYNVq1aho6MDJ598MhYvXpzjV5Aa5tfL4Sko5TEcdd/2hDiia1D3bbfH1fYE/h7xEzOOHZuIt/XGsCbRGj2rG+kLSvlAGsOO+SSvwwXbaNxAfkiCwczPRv7eTOfcMDs7yNlBEERqjljT2PYciqZcJ+Gw0FCYl/p0PBI3o8QJZ4f/5w//zMvUPWQ4nne4QGJHtgSCYNGOxG1NhSCliLHIQUAlZwdBEAOHRIwFWcdYuOsj7NPZAQCfG2J5T0kU7JGZmnX5w57GEjNQ/VYzHttyEE+tPNll3edXZt7d0+naXuXooOv+WNywLaZE/7Bw4UIsXLjQtezMM8/Ec889l7TulClTsH79+v7atZ7hO3pWApjD2WGd6SsTpiEqyYCuAqIIZcK0XtkFnhH3c3aMKJBRnC+jtVPrlc4OQTSLlRnLUFDKR88aidteeMcI33/dMNdTpISz49HNB9HaqeGmBePtxzFruzR6liCIdPBpbGmdHdbnT2unhvEp1+Ixlm44OwKJGEu69VqGkdhBR11ZIshBd2eHHgdSxVgUKiglCGJgoVu5UNHT2RGNpS4o5UJI2KezY9K4MEYXpyhpHsSY5YU6dOvPokgC8kMiNJ1h++4OtHXpLoEIgD2WdocldvC/V2mxglBARAcfPauR2EH0En7jZUXRLCf19HnIlVNRcPmPAAgInPTFXnF1AA5nh4/YIQiCHWXpnc4OU2zI1NkhiQJ03VzX3A//dQBA88RYeJmfqpoxtF11Xa7H8Y9NmsZCEEQ6WixnxyeNsdSFotxh0ZledEjEWDIVlJo/g0omUcT82TqAxY7nn38eF110EWbPno0nn3wy5Xqvvvoqzj333Izbo6OuLBEC7s4OpsXNbg4/5ADFWAiCGFCY01jMExNXZ4fDbZDs7DC/PXl0BQDyQ+bvn5sytFwdnHBAtGIslrNDNp0dAPDhAfMqjffvxJ0b71liB3e8lBTKyA9JiRhLnJHYQfQO/GTeqSQIZoaD2eNlE2f6yjHTIY4eDxZ1j83tCboj6uUHj7L0zjQW09mhM5Y2FiOKvKA0cduL7eywxQ6z6yMRY2HocvT2cLj9O64atphCEAThpaVDQ2FYgqYz1DX6nw9y91mmOAkXOzIXlPLODh5jSRF3sdaLxA3fUvpcU19fj7Vr1+Kpp57Chg0b8PTTT+PDDz9MWq+pqQn33HNPVtuko65s8Rk9CymVsyNEBaUEQQwoXKNnnTGWmIH8kIigImTl7BhZpGD5ZROwIMO4tMFKOMhjLI6CUkvg2d9kHrQ4/06MMXRaotCe+ihEAfj8KcUAgNLiAArCEjqps4PobXymsQjeGIvnTF8ecxy0+t29tgtaBrFjkiV2KL0wblkQzIN0VfMfdcsRrU4i+0/go4xwZwcXawzGIEpwxFjMkwDdI3bwcweDpbaIEwQxvNF0hrYuDZ86vgBA6igLPw5rzeDsiNhiR3rHht3ZkWWMBej/iSyHDh1CXV2d619bm1uA37p1K8444wyUlJQgLy8Pc+bMQXV1ddK2Vq1ahSVLlmT1vNTZkSXJBaVqemcHxVgIghhA6Lp5kuA3ejYclKAZLKvODgA491Mj+n6Hc0Q4KJnTWLREH0FeyHz9/AQqqiaiPzHVsK/QAMCIQgWfP7kYd39jEiZXhlEQluwYC3V2DG127drVb88VbNmHCgAffPgRIkfMk/cR9fUo0XV8sm8fRgN4551tMAJ59mOK1QBGtTXi32/81bW8J9yxEID+MawhNi6KrftbDryHmgM9e565UwBM4bcOoabmkO9635oFAJ1oqjts7lv8o6R9G2nt1/7dO7B/N3BGpfnvP//5l/kY7MeUWea6NZ4H32HVv2x75989e0EEQQxZfnwpABzG7BMBsN2oqUkWma+YAWAGAOxHTc3+lNv67zkAEMXOdxusz599qKnZl7TeaIF/Pu3FHQuBtkO1SPExaX+O8c/A/uLaa69FU1OTa9mSJUuwdOlS+3ZDQ4NrwllZWRm2bdvmeszvfvc7nHTSSTj11FOzet6sxI6Ojg5cccUVePDBB1FZWYkf/OAHqKmpQTgctnf0ggsuQG1tLW655RZ0dnZixowZuP322yHLMg4cOIDly5fj8OHDOPbYY7FmzRrk5+ejra0N3/3ud/HJJ59g5MiRuO+++3Izwi0LBCUIqDEwxswmcC2eevQsTWMhCGKAkSgoFWAYsD/LojEd4YAIVRPTODskv00OSUKK2bHhncbixPl36oy6/2alxQpEUcCpk8yrOvkhCYfbzKsn1NkxtJk8eTIKCwv75bm0T0JofxM4YfJkKMd+CgAQ6axF9GOG8ZXjENkJnPqpT0EMFdiPUUeK6Ni1BZMP/wvB02b3uLvjw/1dWHr/B1h99TE446TiHm0rE3f/fi9q93Wi4YiKa2aX44pzxviu9+2fv4/ykQFcdV45lvxyF3741WNw1snufXttWwvu/v0+PPidEzFxTAj3PfMJ3t7Vhid+cDIWrN6OCz83CpvfPoxwUMLjK06yH9ce0XDZj94FADy58iSMLBx6nUUEQfSMDw90YekvP8APv3oMfrWxDp+bUuQqOuZ851cf4P26LnxhWjFWLjrGd1uMMcy7ZRuu+GIZrr6gHBet3IYrzx2DxReUJ637whtN+NVz+/H9Kybgnj/swz3XTcL04wqS1vtgfxeW3f8BAPTLZzcAtLe3Y9euXXj00Udt7YBTVOSORBuG4Zq4ZZ93W+zatQtbtmzBo48+ikOHUqg5HjIedb3zzju48sorsWfPHnvZjh078MQTT2Djxo3YuHEjLrjgAgDA8uXLceutt2Lz5s1gjGHdunUAgNtvvx2LFi1CdXU1TjnlFDzwwAMAgPvuuw8zZszAiy++iK985Su48847s9rpXGBETJuNttdUl9KNnhXkAMVYCIIYUOhWCR+3cHM3QiRuIBQUEQqIiKoG/u+fTfhHbat5H+/sCA6fE/SAIiCmemIsHrEn5hI7zL9RvuX+KC1xnwAVhBwxFpVRjIXoFViqaSyA3VQnCO73LdNNu3R820tof2oltLraHu2DlqagtLcRxYTTLBRI/XlkFjAnCkr9JrfIoqezwxo9CwCK9f6P+MRYnA4uGj9LEIQfvJx0RKGMgCxmnJ6SLsYSU81IXigoQRAEBGQhY+Ep/3xM+byOz7X+nshSXl6OyspK1z+v2FFeXo7Gxkb7dmNjI8rKyuzb1dXVaGxsxKWXXorrr78eDQ0NWLRoUdrnzXgEu27dOqxevdp+okgkggMHDmDlypWoqqrCL37xCxiGgf379yMajeK0004DACxYsADV1dVQVRVvvfUW5syZ41oOmC2qVVVVAICLL74Yr7/+OlS1f/ND2aDV1SL+n80AgI51t5kHCGljLEHA0O0DC4IgiFzDOzt4jJ9/MfKxZqGAiFjcwFN/rseLbzab96WIsQxlgor5d9Bczg7363c6O7ossePYcvNqRWmx+3uhIOwoKFXJ2UH0Ej6dHfx3+9jD01ehN3C/MgN0Deq+7T3ahUydHb2JKAi20yyd2CGJZrcH79cQ0nV2WJ+Bup7o9gjIIjqjOgwjOfPujP/FaCILQRA+2GJHgQxFERDPNI0ljeDAjzX4MZgiC2k6O8yfmQpKnYszTYLJBWeddRbeeOMNNDc3IxKJYMuWLZg5c6Z9/7Jly7B582Zs3LgRDz30EMrKyvDUU0+l3WbGGIvXbdHU1IQzzjgDq1evRmFhIb75zW9i/fr1OOGEE1wRlNLSUtTX16OlpQUFBQWQZdm1HHDncmRZRkFBAZqbmzFmjNue2NbWllRgEo/3n3NC3bc9IenrGtS97wCGlqagNGj+osUBiWpRCILIPYmCUveBfiRuYGxAREwV0d6lo7ldQ0fE/ALsGo4xloBoOztkSYAgJDs7/GIsx44NYceezqRxvPlhCZ0xHbpuliuS2EH0Cj6jZ+3JLAYXO9z/rykTpiEKAQADJBnKhGk92gW1H8UOQUiID6E07yFRMDuJbGeHz6rciaI5C0qt9QKyYF9p1Yw0zo4UJzAEQQxvWqzSz5ICBQFZzDg9JZ3gEI2bF0q4wJuNU4R/PqYqKDUck6SOtA88sWPMmDG4+eabsXjxYqiqioULF2L69Om47rrrsGzZMkyb1v3vrW6fiY8fPx6/+tWv7NtXX301NmzYgEmTJvlmbLxZG8BfaeePEX2+mR577DHcf//9rmWTJ0/Gbbfd1t3dPyqUCdMQlSRA1wBRglxh5lxTOTv4cqbGIAR7pwSMIAiiJ+iGeZCfEDvM5ZGYgVBQQihu4MP95ujUdsuJEI3pEAUgOIyiF0HFFDtUPWFt59NYxowIoL4ljqjDwt5lRX1OqMgDcBjlI93fC4VhCYwlDmgCJHYQvQEfPesXYzGsAl2P2CFXToVUOQVGy0EUXLqqx50dmUbP9ibOw8Zg2hiLeYUzMY0leR2v4GsYDKKYcHa0dZl/v+RpLE5nB4kdBEEk09KuIc+KBgdkIWXkjR+DtXfp9sUoL1GPm02RMztFgpliLDmcxpItVVVVdvKD8/DDDyetV1lZiVdeeSXj9rotdrz//vvYs2ePHUthjEGW5aSMTVNTE8rKyjBy5Ei0t7dD13VIkuTK3pSVlaGpqQnl5eXQNA2dnZ0oKSlJes5rrrkG8+fPdy2Lx+NoaWnp7u4fFXLlVOTNuRFdm36O0KyrIY05zrwjhbMDiiV20EQWgiAGCOaXKXxiLGZBaTQgosuKrXRYB/tdMXPkWSqBeihiih0MmsagWCdxsiQgqAg4bmzIFDt8OjtOm1SAH117LD59grugkpebNrer1vaHz9+S6EO4s0P0i7FYB7A+71u57DjEm/b1WOgA+jfG4jwRSB9jMUfP6rYY5PM3kPjoWfM2L28GzJMJnmNPcnY4rojGKcZCEIQPLR0aRljlxdk4MRgD2rs0lBQkn1N6o3tKGqcId54FMzk7HF8dAzHG0hd0+xITYwx33XUXWltboaoqnn76aVxwwQWoqKhAMBi0x3Rt3LgRM2fOhKIomDFjBjZt2gQA2LBhg529mTVrFjZs2AAA2LRpE2bMmAFFSf6PXVRUlFRo0t9TW+SJpm1GzCsGrAOJ1M6OkPmLSiWlBEEMDAxPjMWwrN58hrvzaml7RAdj5ija4VROCpgHCprOENcMyHLiROlrc8bi0i+YQr2f2JEXkvDZE4uSrs7kh02xg09koRgL0Sv4xFhsJwc/i/c50ReLRoNFO8HikR7vAhcD+tvZkTbGIvIYS/LjEuuYP50FpfxtG1BEtFknAHxqFUdPTJymglKCIHxpaVcxosD0EqRzYhhGItaaqrfDv7Mjg7PD7uxIL7KMLFT6vaA0V3Tb2TFlyhRcf/31uPLKK6FpGmbPno2LL74YALBmzRqsWrUKHR0dOPnkk7F48WIAwOrVq7FixQr8+te/xtixY3HvvfcCAG666SasWLEC8+bNQ2FhIdasWdOLL613EfPM0Tws0mZOYgGAFKNnydlBEMRAQ9cBKZgQOx7ZfBAHDsdhGOa0lVAscQKh6abQEYnpw6qvA4A9LaUzqrtO4i75vCmwK7KQ1NkhCKlLXAstsaO5zTyoILGD6A3sk3BHVEWwYiyJgtLk/9eEIvP/Y6OtEdLoCT3aB826wqj0i9iRnbNDFLhIYd72s4bzaSz8yqduwI6xKJLgunKq6QyKJXo6nR0x6uwgCMKHti4dlaPN7saAkr6zY2ShjIPNcbR26r7reGMsgTQFpbphirb88yqTKFI5OogdezrRHtFQGB7a/ZJZvzpnJuaqq67CVVddlbTOlClTsH79+qTlFRUVePzxx5OWl5SU4MEHH8x2F3JLIAyIMlhXmz1WNrWzw/yfnKkkdhAEMTDQrVw6P/h/b28X9jeZn1GhgIhwwC1qtEd0RKxJLcMJftW4I6L7XrEOWdNaOF1RMwYk+pUDIBFj4c4O6uwgegXf0bO8oFQFIPhGOERb7Gjqudhh9OPo2Sw7OyRRgMGYfUDv5+zg+2s4OjskR0GpE91gUBy/cyjGQhCEH5pm2IJDQBagpunsKB8ZwMHmOA42x3DqpIKkdRLjtiVre+ljMaIo2M+dKcYyc3oJ/vNRB954tw2zZ4zM/gUOQuioK0sEQYAQLoQRaQPTrDxsCmeHYDk7uChCEASRa3hnBz+o5x0SAJAXlJKulrZ36YjEhmGMxfo7dEZ13yvWoYDoKijtjOq2oOFHQdjT2SH3/YkhMQzIFGNJ0bMjOpwdPaU/OztcMZa0BaUCdIezw+/PYDs7+OhZg9mjZxWPGKk5Lrg6p7FQQSlBEH5ong6g1B0bDBWjgygISdhV1+W7Dj/W4MdhPBbzSUM0yblhWM8rS+nFDi7aTpmQh/KRAby2LdF/ubc+6oruDRWG11FsDxHyirJydoCcHQRBDDC8o2f5FQPAPHngJxCl1ujU9ohm9XkMrxgLj5l0pnJ2BMSkzo6sxA7e2THMnDJEH5FmGgszNN8ICwCIhaMACL0rdqRwNfUmokO1SBcFk8REHxEASH7uFu80FgbX6FknzhMGcnYQBJEJ3WC2eyzT6FlJFHBCZRjvf5JC7Ii5YyyKLOJgcxzf+vn7eKnGPaSDX9Din8eZilElUcAsy91xpEPFRwci+NZ972NXXc/7nAYadNTVDcRwkdnZwZvOpRQxFsUUO0CdHQRBDBD4xAGn5fwL04oxcUwIx5aH7JPwSePCAMwYRySmI2+4OTt4jCVqZCV2dEUN5IVS/43CARGCABy25tkH5OH19yT6CJYmxqJrKZ0dgiRDKBgBo62px7tgix394FYSu+HsMJgpYAApnB2eaSze0bNOnAKH4fidOjsIgvBD15ktOATSjoo1I3WTK/Owpz6KmGokuSoicfNDisdrFVnAkQ4NhgHsqY94tmd+jomWuyNTjEUSBXz+lGIYBvCfjzrQ2GpeyG/vGnqlpXTU1Q2EcBEMl7MjRYxF5gWlFGMhCGJgwK8iOLslJlfm4cHvnIjK0pD9ZXq8JXbwGEu6E4uhSDCQKChVfE7igt10doiigPyQZDs7htvfk+gjfEbPCoL1/6Ge2tkBmBNZBpuzQ3DYwv1KRzmSYH7W2ZUmPmoHj/LpjhiL5Dg5ceIUO3THOUuqHD5BEMMb3dkBpGTo2BCAE8fnwTCAP/2tEZf96F0cak5cKI/Gzf6PhFMk8fl0oCnu2V4iPiNL6YtMAfOro7TYPF9t79LRFTXs7Qw16KirGwh5RWCR9oydHX4xFq2uFpGt66DV1fb1bhIEQSRhGAySlDjQB4Di/ERHdcjj7GhuV9HaqWFkYYrPuSGKc0Z9qoLS7ogduG5obwABAABJREFUAFAQkux59nzaC0H0BObX2WEJH8zQXCJIEnIQev3HPT4e6c/ODq5vpBs7C1jODmeMxWd1yZNpN4zE9pM7OxzODtc0FoqxEASRjKYnYiyKbDosnKIph4uskyvzAAC/23IIHVEd9S2JPrWopyTe6Tw7cNidHnAWLSuSAFU30HAkjo6InrQeYAoj+aFEITtfz29fBzskdnQDHmPh8RQhY4zFVN20ulq0P7US0Vd/h/YnV6DzxftJ9CAIol/xdnYAbrHj1EkFuPQLpfj0CYVQZAEf7I/AYECFNUJtuODsA0gZY3EWlMZ05GUQO/LDkl2YGKQYC9Eb+IyeTRSUpo6xaHW10D95FyzShvanVvboWKR/xQ7zOTI5o0RBgGE4YyypR88mOjvSODtSdnakv/zZ1qnZE5gIghg+OB0WXJzwuiwYY3ah6KgiBaOKEheVnOXH0bjbXcvdpmUlCuqPxJM6hbhzV7ZEllv+92P87qWD7v1zjOVWZBFBRURHVEdnlMQOAoCQVwgwA0anVQqTqqDUmsbCnR3qvu2ApgJggK4h/u8Xe3yQQRAE0R10A67Rs4Bb7MgPSfjGReMQUEQUhCW7MGvcqBSfc0MUl9jhY5cPBbyjZ42MvSa8pBSgglKil/Dt7OAxFt33JB+wjke4UKJr5u2jRNPNK4mpnqs34U+RSeyQJCvGYr1Gv8QL/wzUnc6OFJ0dmquzI7E80zSWh/7vAO56ak/adQiCGHroRsIVysVTv8kpQOKz6JzTSnDieNPh4ez4iHjEDv75NPezo2AYQH1LIspiOEQWxYqxNB5R0dzm7uAwdPdnY0FYQmeExA7CQggXAwCM9sPm7VSdHYIISDKY5QBRJkxL/sbt4UEGQRBEd9B1Pno28VlUUiD7rlsYlnCkw/yCHNbODh8XhrOgNK4a0HSWVYyF471yTBBHhXW07BQaBDvGoqbs7FAmTAMk630viuZtH7KJ3ppRr/45jOQfW+kmsZjrCTAYSzt6llvMeTbdmbH39vSkdnakPyFo79LQ2jH0iv4IYjjTGdVxsDn98Amnw4LH4rwTWeyJKNahwX9dOA7f/coEc13HZ0ssbiDsmIg3c3oJFl9QjunHFQAA9jcl9kX3xFgicQMx1UBXzB1jcU5jAUyxw+nsMKizY3gj5hUBALRDu82fDXtSrisoQUA1FTe5ciqkipOAYH7iAESUUh5kEARB9DaJGEtiWXG+/0l6YZ55MlSUJ9m/Dxd4QSmQJsZiiR384CCj2GE5O0Sxfyz/xDCAn82LKWIs8P//TK6cioLLVgMAAtPOh1w5NWkdra4W7U+sQPTVx9D+xPcR+/eLvtsyxY6jfgXdQsg2xiLCirHwEj6/glKrs8M5elZI4ezQ/Z0dqSYscHSDej0IYqjxh7/U4/sPfZTyfrMvKNEVxC9ueD8vvIIDAASV5HW9zo4Tx+fhynPHoGK06bg96OjtMBxFy7Is2hesePGovR6PsVjHIvkhkZwdRAIhbIod+r53AACd63+c+qqHHLSdHQCAWCeU8Scjf+EqAALEEWP7eG8JgiAS2KNnHdn0VFdJC62T83GjhperA3BfOVZSFJTGNbNwrOGImcl35m39yLf+nkFZ7BfLPzEMSBNjYbqetqBUOfZTEIvHgMW6fO9X920HDMuVYOjo2vxr32OdXDg7MsZYRME1jcUvxmKPnuVih8HsPxcvEOYnKc4YC19fkYWMMRbNYBl7PQiCGFwcblPR3K4mjYjl8M+LRIzFcnZ4nGC24OD4gApYxx7Oz5ZITEfIJyZbnC8jHBSx/7DT2ZEQdxVJwJF28/gklbPDjrGEJCooJRII4ULzlyzyrqazI2atzqAfOQSxpBxiuAgQBBhN+6i3gyCIfsM7erY4X0554l2YZ540DbcIC2AeJPCDAD8XBu/ciKmGbSHN9HfiMZaB3Nfx/PPP46KLLsLs2bPx5JNPJt3/8ssv45JLLsGXvvQlfPvb30Zra2sO9pLg2NNYnA4OLnwY6UfPAoBUNhF64x7f+5Jcp4bhe6xjZtOz3OEewj+3Mr2HeEFpIsaSZvSsnjx6lgucXKDUHecJ3C0SDogZYyy6wZKs6wRBDG46Izp0I7lwlGN4HBupOjv4Z49Tk7adHZ4Yi98EKkEQUDEqiIOHE50dzhiLLAlo4c6OWHpXSUFYpoJSIoGYV+y4JQCSnDqKIgfsglIWaQPiEYglY3q1HIwgCCJb+Bchz4g6y0m98JPz4ejsEATBvsKSKsYCmC3pBw7HIAjA2JHpS1x5jGWg9nXU19dj7dq1eOqpp7BhwwY8/fTT+PDDD+37Ozo6cNttt+Ghhx7Cc889hxNPPBG//OUvc7jHhG+MxS4oTT2NhSOVHgvjcB2YljwxRK6cCihh2EJKim4PVes/Z4ddUJpx9CygM0dBqc/qgiCY69nODkeMxdo+f896px0AQDgoZXR2GJazI9UVYIIgBh+dlnDgdUtwNGuxLZ5yZ0eqzg6HsyOxbuoYi5OxowKuGIvuirEItsjh3Vfb9SZyYZfHWAzX/UMJEju6gaujQxSRd8H1vnlXAIBhQG/cC62uFsaRQ+ZDSsqtcjDrgIR6OwiC6AcSOdJEjCWd2MF7OsaNHl6TWDjBLMWO/U0xlBYr9glSKninR6Zyxb7g0KFDqKurc/1ra2tzrbN161acccYZKCkpQV5eHubMmYPq6mr7flVVsXr1aowZMwYAcOKJJ+LgQfc4O6KfMZJjLImC0mycHccAzEDXK7/xd5gyA8pJMwE5CHnSDN9jHd1g6K9Jyt2JsRiuGIu/6COJgi1kGCwRY+EFpTzK57zKybcZDogZXRu6blrVnWIJQRCDm04r6uF1S3C8IkbAp4fDXM/86ewUkkQBsiS4nB2awZJKkzn5IQlRh+hqeGIsnEjMsB0nzn10xlg6o0M7xjLom+d27drVb89V8vHrGAHzWgczDNR9uBNHjLKk9YJH9mHc4ToADK1PrMCRY2diJICdB5qhFirIP+kSjNn+DJqP/QI+ru8C6muSHh9u3oPIyGMQK5nQHy+NIIghzh0LAWA/mvfvt35vQU1Nje+6k4ut9bWPkWKVIc3yC/lvh1BTc8h13wiYf5uDe3bg/BOA809Ayr8jpxj8769lXLe3ufbaa9HU1ORatmTJEixdutS+3dDQgNLSUvt2WVkZtm3bZt8eMWIELrjgAgBANBrFQw89hKuvvrqP95xIDxc7fGIsumZGadPArDP3+Nv/h/h/tqBw0V22oMEMHdBikEZVwiifBEQ7fbeh6sx3YlFfwOMoGWMsonkiwR0VqQwusijY4gXvMwISGfuCsHl47OfsCAVEHOlMP2mFrxvXGJRBf6RNEAQAdFhRj0gmscO6pp2qsyMhirgfH/D0ARm62/3hRBIFqJ7PJ+c0FieRuGFfdDEMBlFwOjskGAxotT7TSOwYgEyePBmFhYX98lzamDy0737dPJCQZEw8cy4m+VztiGz9CFFYX7TMQJlxBBqAaWedAyEQhjH1BLRufwYVx0zCpM98xvXY2M6/o2vzbwAIgKy4DkAIgiCOhkhMx4LbduDrc8fizJOKcd29OzH/86Nx/cUVvuvXt8TxzOsNuP7iimE5PeT6tTvxSUMMV5xThmtmu8uk336/DT98dDfu/dbxuPXR3Zh1agmWfLky7fbe29uJ/37wQ5w0MQ8/+9YJfbnrNu3t7di1axceffRRhMNh131FRUWu24ZhuLoNGGO+XQft7e248cYbMWXKFMyfP79vdpzIDnv0bIoYSyDs8yDHw49wZw6zI7W22BGPmNsO5kEaPR7qrn/4bkPTWdLBel/BnRcZYyzW6Fl+vJ6Vs8NZUJqNsyMoouFI5oJSwBxPnWlaE0EQgwPu7IikiLHwLg45U2eHT4wFMN2fTheI5oimeJElAZrmFjtET3yG0xXT7c8hZ5EpkIjsJbbj+3SDGoqxdAO5cioKF92F0Kyr04oQyoRpiYMOSQZTo4ASgm7FYIRwISApMNoPJz02/s4W67fEAQhBEERP4GVaiiwkOjsKUmvdY0YE8O1LKoel0AEkTqjSxVgaWuPoiOpZlbjmMsZSXl6OyspK1z+v2FFeXo7Gxkb7dmNjI8rK3K7FhoYGLFq0CCeeeCLuvPPOftl3Ig12A6dT7Mg+xqIcc1rihrd/zJrSIgTCkEZVgnW1wuhyR58A88Be6bdpLNmNnpUsx4bd2ZHiI0ySBFuQ0Bmzt6/Yzo70nR3ZFJQCyVl9giAGJ7rOEInzHoz0zg6v6BBTGe5dvw87dncASC4y5SiyO8aiO4RYL4osuMVYltie99jFOX7W6QABEh1t3tcwlCCxo5vIlVMRPuuytG4LuXIqAp++CAAQmrUY+v5aQI3a01cEQYBYOAqsoznpsazT0XCfrgCVIAgiS/gBuyILyAtKkESgPEOp5nAmXWcHt9F/dMC8+p1NiSu/SpwLsSMbzjrrLLzxxhtobm5GJBLBli1bMHPmTPt+XdfxrW99CxdeeCFuueUWGp87EGB26NteJAjc2aFnLCiVK6dCHDUe4ohxSRdvbGdHIA/SKNO1ZDTXJW3DjLH0z/8LdkFpFjEWIDFFJdWfQRITJxxm1t1czjP2vs4OxzSWmJb+8qehJ5wdBEEMfpxFn5F4+oJSe/Ss9XnS2qnhpZoW/PtDU+zg7olMzg5z4lWWMRadpZwk59x3w+EAARKTp+z7h2DP0KCPsQxUlPEnI/7282CtDUnTV+TKqRALRiU5O1g8Ar1hNwBAHDEO+VX/jyIsBEH0GP6FqEgiivNlPHTzFBI70sAPUHydHZZg8fGBKACgIosSV34wkanINFeMGTMGN998MxYvXgxVVbFw4UJMnz4d1113HZYtW4ZDhw7hvffeg67r2Lx5MwDglFNOIYdHDrFHz/p1dhiZp7EAgDSqEnrz/qTjjESMJQxxpBl1i/7zWYQguNbVdWbbtfua7MUOc0Uu8KYS5mQpEWNxTjGYUBrCwpmlOH1qEZ74c71tSwcSAko4KELVWNJJgxN+MpNJFCEIYnDA+zqALDo7PDGW5nbVdX/Kzg5FRMxydjBmFi2nirEokuVisz6HXCO05XTODkByfC4OB2cHiR19hFg4GgAgFIywlrhH1QqFo6Af+tD1mGjNC+ZBSl4xwAwSOgiC6BV4XpR/AY7LInoxnMlmGssH+7sgCmbkJxMB2WxZDyoD1xFRVVWFqqoq17KHH34YADBt2jTs3LkzF7tFpMI3xuI4aM0QYwEAsWg01L3vJG/ajrHkwbAcqOr7W6F+9LbLBaLqrN/cSt2JsQCJzoxUKRt+cgC4pxhIkoD/unAcmttU13aAhLOD70NcYwgF/N/Tic6OoXfiQBDDEd7XAWRTUOqOsbS0m+Wfzp4gwM/ZIdhusFTuDw531WkGQ4CLHfx5rZ/hoIhIzHA5O3SDub4qvM4O6uwgskYsMsUO1nkEAKBMPdt1kCAWjoLRcdhuDNfqahF99Xfmg6MdMI7Ug+lqv+83QRBDD2dnB5EZfgLn10fAT3TaunR88dQRSUVgfgiCgAllQYzNIvJCEFmRprMD8BSXpkAsKgViXba4YW/acnYgGIb2ybuJOzw9YrqeOLjua/hLyySu8PMCXtyXztmhO0fPelbjr8uvsyPPuhIaSxNRSXR2DMEzB4IYhnQ63BFdqQpKPSIrd3Yc5uKp7SYz7/c6wxQ5EWNJ5f7gSB4Xm7Ozgx+XjCkJJO2vwdylp8kFpUNPoCWxo48Q8kcAggh1z38AAKEzLnU5NcTCUYAaA4uZI93UfdsTGVzDAMBgHGno570mCGIowkvy+qtMcLDDBQ0/Z0c4KCEgCzhtUgFuujT9FBYnv7hxMi6flTyqnCCOCsM8eHWdzLucHZlFCLFwlLmpNvdoYhZPFJQqE6YltuXpEdN0ljTisK8Quuvs0Pm0mtTr6fYhV/LEA/7e1x3nNHwaS6EldqSayAA4xA5ydhDEkMAZY0lZUKq7HRuyJEAQ0sVYPM4OR0Gp1yXihX/2cmFXN5I7O0pLFHN/PTEW55SqvODQFzsoxtJHCJIMIX8EjMa9AABppHvEo1gwEgDA2g8DoQJI5cfzRwKSDOgqjJb9kEb5j4YkCILIFlV3x1iI9KSLsciSgAduOhGlJQoCWbg6OP11BZwYJjCWFFVxuTmydXYAMNqbIJVOSGw6xgtKw5AqyyEf+xno+2tRcPntros2mtGPzg7raTI6O6y7M8VYJDGxjncUo3m/Ow5jrmf+XpRvHjo7T368WFpUWvcHQRCDB3eMJUVBqfUZwY8dBEFAQBbQ7ImxJKa2uB8fUBLlx6kEEY4zxgKYxaLeaSylPs4O3TMyXBIF5AVFdMUM0/E2BMUOuszXh4hF5lUToWAkhGCe6z6BX1Gx8rACzP+5AqdegPxLbwEA6M0H+2tXCYIYwlCMpXvYMZYUf6+K0cFuCR0E0eswI1nQcB45Z+HsEKxuMaOt0bU84ewwj1vkMceCqTFIFSe61tO0/nR2mD8zOjsE99XOVDEWSTRjLHZ23rNawtnh6Ozgzo4880poZyS1kMFPQFQaPUsQQ4JOS9wsypdSdnYYPj0biiyiwxJKMjo7FBEqd3boydtyIntiLLqBpILS4jwJQUV0OVG8MRbAjLKIIpAfkoZkZwc5O/oQsXA0dOxKcnWY95liR+zfmyAoIWh1tYAgIu+C6wElBChBxN97HfK4yVRUShBEj7DFDnIXZEU6ZwdBDAQYM5IFDaGbBaWFIwEIvpPhIMkQZNMCLRSMBAwNrKsNQn6JvZ7aj50do4sUBBUBIwrSH7YmT2PxX49fweQXMZOdHXBtB0icoPCxtJ1pnB18XXJ2EMTQgL/fRxcpKWMsmp4sYgQcF01sYSKFkKHIQvbODk+MxWAMkuS+ryAsIy8koivqLChN/rwrCJsCjiwlylOHEiR29CF8IovoI3bwKynqzq1QP3wbYlEZhPxi6A17zBXUOPQDO9H+1EpXsSlBEER3sUfPkhshK9KNniWIAQFjyR5o523vfT4IkgIhvwRGu7uzA7GI7eoAHN0eHYchOsQO3WD99h759AmF+P0tJyPsyZd7kbwxlnTODoOlLAEUBAGi6M6vG4xBFBOFftmIHXESOwhiSNAR0ZEXFJEXklLGWPw+T5wuUG+Mxfu5E1RExzSW9FE8b4zF7OxwT2PJD4vIC0ouccYcUeveVn5IQlfYgOH4TBxK0JFvH8J44aicrClp+x1j/DQVRnMdWEcL2p9aidj2PwNWrMXbfk4QBNFdvKNnifSEyNlBDHR8Yizuzo7s/t8VQvnQ9m433aV80/EIhEDYvs3FDuZxgPRvjEXIKHQA2Ts7JEmA5oixeK90AqZN3OvskETBHtXYEfE/4WGM2Xb2eBYxFsNg+J+n9mDHno6M6xIEkRs6ozoKwhLyAmLq0bPc2eH4XFR8nB12fM7z+RlQBMSyLChNH2MxvwsKwrLZx+EQZv0KmStGB1ExKmiO5E6t4Q5aSOzoI7S6WsT/XQ0AiP+72nUgAcBqOLf+/M5vY90ssYFoCSSS5Go/JwiC6C7U2dE9ggE+epb+XsQAhbHkM3nHNBYhi8M7ra4WRvMBGC0H0P7USvs4hcW7fMUOo73Z/fh+LCjNFn4Mr2oZxA7RPDmwYyw+K3JBhGNYUwz49IJUzg7DcR6UjbMjqhp4fXsr/rWrPeO6BEHkhs6ojryQhHAws7NDFv3FDj3J2eERO2TRFmEzdnZY9gz+WecsHrVjLCHJdKLEPdNYPNu88ZJK3Lr4GNvxNtQgsaOP8I6S9boz5MqpCEw7D4AA+cQzzYWCCEgygtPOQ95FSwAAoTMvowgLQRA9gsdYyKmQHbyzY6CdyBGEjaG7nRxAtwtKXccpDhcpi0UAR6m6kD/CfMoOj9jRj6Nns4UfxOsGgyCkLiiVvQWlPkfDsufAn9u/JVFAOCi6xA7dYGDMXNc5wYXn79PBT4DauobgJVWCGCJ0RnUUhCSEgyK6LPFA0xl+/5d6ROO8gNRcV3R1djhiLHxyivURkSR2WMcecY1l3dmh29tk9vNygaUgLKVwdiRvKyCLlghMYgeRJcqEaeYIWUvA8HNnKMd/FgAzx9OGChGa+VW7nyNw8jmAHACLkq2RIIieodkFpfSRnw0Vo4MIKiJKiwO53hWiF7jnnnuwYsUKAMDWrVtRVVWF2bNnY+3atfY6tbW1WLBgAebMmYNbbrkFmqblanezw2f0LLoZY1EmTEu4QRzHKd4YiyDJEPLc3R6MMWh6sh0610gOa3e6XZMkd2eHb4zFz9khJq6YcrEjphpYdNe7+Ov2VgDuk4W4mvnEgT9He9cA/3+OIIYxHREd+WHJ7MCImqpG7b5O/G7LIfznI/NcTfO5sMQ7wIBEMakdd/F2dlgiRVw1Mnd2SInPOsAdY/nMCYW48twxOKY8lKKzI32X0VCDjnz7CLlyKgoX3YXQrKtTFoxKY44DABiH66BMnIbw5y+31xMkGVL58dAOvN+v+00QxNBD1amzoztMGhfGhh9Nw+hiJde7QvSQN954A88++ywAIBqNYuXKlXjggQewadMm7NixA6+99hoAYPny5bj11luxefNmMMawbt26XO52Rpif2NHNgtKEwxQouPIO+/jDG2MBzCgLczg7dLuSbGB9pvCXrekspasDMA/qNSPRreH35+KCCMd5kpAfluzOjsOtKto6dTQcidvrceJZODv41V5ydhDEwKUzaiA/aDolYpYYcbhNBeCIkmQqKPWMnvWKrNzZEdOMzJ0d1nLnc/PPsaJ8GYsvKIckCknTWAyfGAvHFDvS/RUGJyR29CFy5VSEz0odQxFLxgDWAYXfOmLRaOgHdlFBKUEQPYI6O4jhyJEjR7B27Vp861vfAgBs27YNEydOxPjx4yHLMqqqqlBdXY39+/cjGo3itNNOAwAsWLAA1dXVvttsa2tDXV2d619jY2N/vaQETE9yb5ixFmtZFqNnAUAqnWD9nJjYdCwCIegVO0a6Ojv4SNUBF2MRsnR2iAIMnUG3oid+nR2yp6yPT2MBrOkF1tXd5nbVfk4Arsd0x9nRRs4OghiwdEZ15IdFuyg5GjfQ3Ga+Z5O6ODIUlHJBIbmzwxIwVOZwf2QXY0nl2DCdHbods9NZcoyFI4nCkBw9S2JHDhEEEWJxmfm75yqKVlcL9f2tADPQ8fsfJhWcEgRBZIstdgywExOC6EtuvfVW3HzzzSgqKgIANDQ0oLS01L6/rKwM9fX1SctLS0tRX1/vu83HHnsM5513nuvfTTfd1LcvxA8/ZweQsChkO41FsY494pHEpuNdrtGzACAUjILhmMay51AUADC+NNSNne57+MG+qrOUVy8BK6JiJMpE/U4SJElw9W84beL5IQkd1tXSlg7rhMdz1RbIztmh2zEWcnYQxEDEMBi6HJ0dANAV03HYEjrVNMWjTmeHVxTxOsrczg4kbcuJ7ezQmT0Byu8zLy8kQTcSk6H8prFwJGlodnYkz0Ql+g2trhZG0ycAgK6XHoJUeozt8FD3bQcMHu4yi8OoqJQgiKNB1Q3IkpDW1k0QQ4k//vGPGDt2LM4880z86U9/AgAYhuF6DzBmRh1SLffjmmuuwfz5813L4vE4Wlpa+uBVpIEZ/tkLUTKPHbJ0dvALLcwSOxhjQDyadAEGzADrOgJ13w4oE07BB/u7AAAnVHjWyzH8T6LrLK3ek9zZkbyOLAn2yQlgniTwc4SCkIR99abg02xZ2fnJifNkIdYtZweJHQQxEIlrDAYDQgHRFjsiMcN+7/P3sObjxnB2dnhjLF7RgZejx9XsC0o13XAUniavFw7w/dURVEToOiAG/LcpDtHODhI7cogrnuIRNJQJ0xCVFECLA6JI42cJgjhqVI1RhIUYVmzatAmNjY245JJL0Nraiq6uLuzfvx+SlBjP2tjYiLKyMpSXl7uiKE1NTSgrK/PdblFRke0U4bS3t+dA7EghyFgiR7bCJo+rcLEDahQAg+CYxqLV1SK+/RUAQMcffojCRXfhg7p8jCqSMbJoYPXaZB9jgTWNxf047zpays6OxDQW29mh+zg7shg9y58jphqIq4Z9dZcgiIEBFzEUWbRHT0diht3Zwe/nnyeyK8Zivp+DipB59KwljMSyKCjlTl1dT7099zYTU1vSxVicpcxDBfpEzSHpJrbIlVNRcOWd5vLJZ5CrgyCIo4bEDmK48cgjj+CFF17Axo0bsWzZMpx77rn4zW9+g927d2Pv3r3QdR0vvPACZs6ciYqKCgSDQdTU1AAANm7ciJkzZ+b4FWSAGRliLFke3lkxFhaznB0x07HhdHa4naYq1H3b8cGBLhxf4Y66DAS4lqXqzFfA4PCxsomMvc86Sc6OhE0835rGwhizOzvsGIuzsyOrGEvi9/YIuTsIYqDhnLLijLF4nR3+BaXmZ0ZxvpwkiiR3dpgPVDUj0dmRIn4s2TEWI20cLyhzt4hh72PqglK4PvOGCuTsyCF8You6bzuUCdOSBA1l/EkQR1YAOpVWEQRx9Kj6/8/efcfJUdePH3/NbLtecy25XHq5kBBKKEEIICW00AUBAUWxIIj6FaT9RL8K8lUEvkoTxa8oIgJKlST0jgkJkAIX0svlcr3t3W2dmd8fszO3e7flEq5u3s/HA3LZnZud29zufuY972LI2Fmx3/N4PNxxxx1cc801BAIBjj32WE455RQA7rzzTm655Ra6uro44IADuOyyy0b4aJMz9PjBDkV1YJhfDGg/dmZHKBLsiGR4hHasxVE6BWdldSTT1AlaCFQHWsUB1DYFOPbAgsH4UQaVFeDQNCPpU6BGrmDqyRqU9hk9a2Z2mF9nZzjQDfAFddq85hqt7wkPxG9Qao3tta74Rj9GZ0+Y4lGWLSPE/i4cFXiIzuxo7fPaj1vGEnmdF+a6aOsTGO27LIvOwrD2kaiMxRU1ejZZOV50HxDzsRPvM11Hz0qwY4Q5K6uTZm2oeSXonSPQ6V0IkTZCYV0yO8R+69xzz+Xcc88FYOHChTz33HP9tpk9ezZPPfXUcB/avjOM+E1IrTP8gZax9OnZEa79FIBQzTuENq0g9+LbcVZWk33ezXQ/8VPch5zOViZhGFuYMQozO6zFfsrMDoc5YrF39Gz/bVU1tkGpbvRul5NpnvB0+zQ7s0PvU4+vqr0nGNFWbvDyP//YwaM3ziHL44g5uZAmpUKMPmGtd/qUldnR3BHCF9Qj9ydrUGp+XZjjpCkynlpP1LMjKgvDFQlSpO7ZYSTcH5jlM+Y+oxuUxv850zXYMaDQf1dXF2eccQa1tbUAvPfeeyxZsoSTTz6Zu+++296upqaGc889l8WLF3PzzTcTDpsRr7q6Oi655BJOOeUUvvOd79Dd3Q2YI9y++c1vcuqpp3LJJZeMzPi2Uc6RX4re0TjShyGEGMOkjEWINGMkaEK6j8EOgmazzfDO9dYD2L3EAFzTDgXViep0s3m3GRiZPsqak0LvYj+cqkFpZFFvZXbEyxQ3R88m6NmREQl2+DU7s6Nvg9IstyNuZkddSwBfQKcrUrJiTcsCGT8rxGgUXcZSku/C41JYuaHTvt+exhJ534kOnlYUeyjIcVKQ40w9ejYqC0NP0bPDESezI37Pjsg+B1TGotgB4HSSMtixZs0aLrroIrZv3w6A3+/npptu4v777+fFF19k/fr1vPnmmwBcd911/OQnP2H58uUYhsETTzwBwM9+9jMuvvhili1bxty5c7n//vsBuOeee1iwYAFLly7lS1/6ErfddtsQ/Zhjl5pXguHvsutohRBib5llLBLsECJtJBw9G2k+sY/TWJSsgt7vj+olpigqak4helcr7V1hHCoU5Y6+covoMpZkmR2OSImKFcyIt/jvW8YSPY3FCnZ09mi0d0dS2fXeEx6ADI8at2eHddIRr+xFJrIIMbwG1EQ4KtjhcqrMmZTNR1u8UfcnLhE5/qAC/nrDHDwutd9rvt/o2chFqVCo973JmWDt5orJ7DBvixvssLNFegMtictY0nP0bMpPwyeeeIJbb73V7ky+du1aJk2axMSJE3E6nSxZsoRly5axe/du/H4/Bx10EGCmjS5btoxQKMQHH3zA4sWLY24HeOONN1iyZAkAZ5xxBm+99RahUKjfMXR2dlJbWxvz3/6SBaLmm8+73tk8wkcihBirzDIW6dkhRNowDJQ4BdrKXjco9Zi7sy6oqAooDjIWXWKXsNj7zi1G9zYTGMUTQxwxZSypt+utsY+zjSM2pTteZsfu5gCR5JCoSQvm37M8atwTKbtRYJ86fwCvZHYIMWzqWgKc+9N1bK5LfkE53CfwcODUnJgMiHAkOysc9R5hURQFp0OJlM71BjtUtf/UrOjMjt6ASPIGpal6dthlLJHAqx557Hj229GzfbMtGhsbKSkpsf9eWlpKQ0NDv9tLSkpoaGigra2NnJwcnE5nzO199+V0OsnJyaG1tZWysrKYx3zkkUe49957Y26bOXMmP/3pT/fiRx2b1Dwr2NGIo6RqhI9GCDEWhSWzQ4j0YmjxS1UimR0DHj2rqODOxAiZZSx6RyNqQSmZX/hy/13nFKM17ySYqZMxSoMd1smCP6iT5Ul8jNZJSzCcJLND7ZvZ0XsyYfXsqG0K2PdrfXp2ZHocBELBfvsNhGODHJLZIcTIaO4IoemwbY+f6eMT9yAK9Ql2zJ+aY98XnQGmaQbOOJOd+m2nx88887h6szDCSUpTrNtVZd/KWJI3KI1//GPZXjco1XU95kPUiMx6T3S7EWcWfKIPYcMwUOOEmy6//HLOOeecmNuCweDwz7UfAXZmR8f+kckihBh8obBBhnt0npwIIfZBygalA3+9K+5Mu4xF72i01x19qbnFhLZ/RKDAGLWZHaUFbsA8AUh0RRR6Twqsq53xTjwcjmQ9O8yff1eTP+b+6D8z3ardPDD6WAJWU0NdMjuEGEnWa9VqMpxI38yOGZVZ9poq063ar2V9AIEEwzASlpI4HYrZ2DikJ+zr0Xd7M9iReNvoAIr5MyfPFknHzI69/rQqLy+PKSFpamqitLS03+3Nzc2UlpZSVFSE1+tFiwwSt7YHMyukudkszwiHw3R3d1NQUNDvMfPy8qisrIz5LzqLJJ0pOYWAQvDTNwnX1oz04QghxqBQWDI7hEgnhmGAEucS4l42KAVQ3BkYgUiwo70BNb8s7nZqbhEEetCDPfaIxNEmw61SmGtex0texhKpjQ8nLmNx9rnKGT2NJStSxrKjwQx2ZHnU3galmpXZETnJCMeePFgBlnCfDI8sjyrTWIQYRtbrv6VzYMEOax3ldCgcODWHskI3LmdvxkZYN+zykr6sQImmm+8RiRqPup0qobCBnqTELnqf0dNY4o+etcbZ9paxJJ7Gsp/27Ohr/vz5bNu2jR07dqBpGi+88AKLFi1iwoQJeDweVq9eDcCzzz7LokWLcLlcLFiwgBdffBGAZ555hkWLFgFw7LHH8swzzwDw4osvsmDBAlyu0dfwaiRpdRsBg/DOdXgfu0kCHkKIvRbSDOnZIUQ60fW4AQ1lLxuUQqRJaciHEQpgdLclDHYoOcUAuALt9ojE0aiiyMzuSFbK0zfYEe9Kp8NBzOjZ6BMUt1NlXL6LxnbzJKk43xWV2WFuk+Ux/y369u3om9lhfV9hrkumsQgxjKwgRUtn8ted3dsnKpBx7TmV3HLJZJwOxX4fSdr8s8+o2ETbuV1KJLMjeYNS675UZSz2ONtw1DSWBO+N6Tp6dq/LWDweD3fccQfXXHMNgUCAY489llNOOQWAO++8k1tuuYWuri4OOOAALrvsMgBuvfVWbrjhBh544AEqKiq46667ALj22mu54YYbOP3008nNzeXOO+8cxB8tPVhj3wB7DFx0wzAhhEjFbFA6Oq/ECiH2gRE/2GFf2kvUgS4OxZWJEfChd5rZuWpB4jIWAE+gHY973N4d7zAqL/Tw6Y6epE9Bb88Oq4wl/jbRZSy6EXuScP/3ZvL2+g50zeDlD1ujGpQmz+zo27PD+rMw10lHlwQ7hBgu1mt1bzM7AIryXBTRv2dHoiCGU7UyOww0g4QZIB6nOcXJCpomK8frW8YSb1uXU0FRIBApY9GTPLZDVdDTMLlswMGO1157zf564cKFPPfcc/22mT17Nk899VS/2ydMmMBf//rXfrcXFBTw4IMPDvQQ9kuuqnn4FdVc2ESNgRNCiIEKhQ0JdgiRTgwdJVkZC3tRxuLJRPe2oneYzeMdicpYcooAOLDnbYwcJzB9b4542JRHMjuSjp6NPE1WHXu8xX/fBqWaHrtdbpaT0w43A0Cvr2mL06DUqpWPzewI9hk9a/1ZlOtiZ6MfIcTwsDIyWgcY7IiXZdG38WiipDeHo3dfyUpJ3C6VwAAalEY/dm9mR/9tFEXB7VR6p0AlLWNJz8yO0ZuHKABwVlbjmrMIFJWci26TrA4hxF4LaQauZIWfQoixJVGD0n0oYzGnsfjQ2xvNXSQIduhes8fanNDHXNB+76gtqy23y1gSb2MFLUJa8gal0WUsup54nG30yMbenh3mv0Ug3KeMJUGwozjXSVePlpYnG0KMRtZrr9UbsvteJNvOGWcdFR3sCGsGaqqeHZHgRMIyFqdCKGr07F717Ejwpud2qjHBjkTbqdKzQ4wU5/hZYOg4iiaM9KEIIcYgKWMRIs0YevxSlchtAx09C5FpLAEf4dpPQVHRIhkefYX3bDIfAnAYWmyZ7ShSYWd2JN6mdxpL4sZ+fctYUo1s7DtKNssdOwXBYqWT992+KM+FbiBNSoUYJr19c0jaL6c32NH/vv6ZHcnLWMK6gaYlLk9xOZU+DUqTZ3aEUkxjgUi2SNjAMAz0ZH1FJLNDjBSrTta6qiKEEHtDyliESC9Ggp4dyj5NY8nE8HcT/OQNMHS6/n5L3KwNs4xWwQB0xYGrah7h2hp87z0xqrI8yos8QPIyFusqayiUJLND7ZPZYSQ+QYme3GL9aWV2BBNkdmh9MjvG5ZkN+ju6pW+HEMMhHNVPpzlJKUsoSWaHy6FGBTsG1qA0WeDUFZnGokUyyVL17NCiy1jiBGMAPC6zjMV6O0v02GrUeNx0IsGOMUDNMxuBSbBDCLG3DMOIlLFIsEOItGEY8UtVrDIWNcGqNw7FnQla0MwWAbsZel/OymoclbPpMHJ5bfIPAPA+egP+Nx7B+7cb6F46OkpbinKddlO+RNQ+mR3xFv9Oh4IetfBPNi7SoWKnklsBkpxM89+gxx+/Z4d1AqVpBopiTmMBCXYIMVyie/K0Rk1k+WxXD9f9fnNv6UeKnh3Rr+WUDUojwYlEDZRdDoWQphPWjaSBDuuxU01jAasPSG9pTKLHtt7f0i25Q4IdY4CaawY7jM7YYMdovKIihBhdzCg9MnpWiHSi6/GDHfuY2RH1t6TN0J3l03ETpDNvuhkQ0SMnCFqY4EdL8T76YwIfLR3wYw8FVVUoL3Qnz+zoN3q2/zbWiYN1QqQbibNFHFGp7Fb6eUmBGbxo8cZeMbbKWLSo4IhDVSjIMWcGtMtEFiGGRXTmVvRElg83e1m/vZu2yGsxaYNSZ2wZS6LsCqczqowlaWaHEsnsSF7CYh1PSDNLUyDx+5PHqRIM9W6XrIzF+jnSyV6PnhXDT8kuAEWNyewI7fqUrkd/DIaB3+ki9+LbpXmpEKKfcCSnWspYhEgjqUbP7mOwwzVnERkLliRcTyj5pWQpAXIUX2RanGJGUy26Rs/yB3CUTB7RNUn1pGwCQT3h/fY0lkiJSbzFv5V2rukGLqwTmdS17taf4/JcKAq0dPQNdkQalIatq8Hm1dz8bAl2CDGcostYoieyNLebXwf6ZGHFDXaovb19wkmCGM6o4GmyQIZdxqIZcXuExGzrUGPLWBJOeFEIxDQ9TR7sSNasdSySYMcYoKgOlNxidG+LfVtw3av9Uk4l2CGE6Mu6chnvQ1oIMUYZBkqcdARln6axZNhfZi76Co6i8YkfNsec1JKvt+KsPBwlpxgcToyOxt41iaGP+Jrk++dWJm3Sak9jSdag1D45Mf+ebBqLI07PDrdLpSDHGXPF2DCM3tGzkROKkKbjcCjkZjlQFCljEWK4hDUdRYH8bGdMz46mjiAQNSY68j4Rrxw4uoxF1w08rvjvvdE9O5KNnnU5zGksepLASe8+wR/qncaSKBjrcal09oR7p7YkGT0Lve9h6ULymscINbcYPaqMxejp7L0zScqpEGL/Zi3mJbNDiDRiDEEZizsTtbA86bbhnBIAcsOt5mEEunHPOIKsU67qfUyHa8TXJKmm0fROY4lkdsQdPWv+OaDmg32u7lq3jctzxQQ7Qpph18Pb+9XMEyaHqpCX5aRdgh1CDAsrE6M4z0VzVAaW9bU/KjCpKImnNkW/lhNmdgxw9KzL2TthJXUZi9kc1Wo9kqxnRzCUemqLFYCJnkKVDiTYMUaouePsMpbQrk8IbVttNyDLOuMHktUhhIjLuuLgSjasXQgxphiGDsRZsCrW6NmBv94VdxYAjtIpKb8vlGkGO3JCzRhBPwR9qDmFeA4+lYxjvgJA1infHfVrEuvEI9XoWegtS9GTNBV0OOhXxuJ0KIzLjz2Jih5DG46T+l6Q46RDyliEGBbhsNm8vXKch52Nfvv2pshrNmiPidZxqErcIKrLqdjlwsmaito9gPTk41+tnh0DaVDqikxjsTM2EmzudioEQnpvBsh+1rNDVr9jhaKit9fj//BFuh67CUKB3vuivxZCiCihsPTsECLt6Hr8M/R9KGNRrDIWXU/Z8DygZtJjeMgKNKN3mdkdSnYhAK6ph5h/z8ge8GOPFDuzI8noWWefhX+yq7HRPTusBqWqgnnFuDM62NGbH65FTXCwAiv52Q4pYxFimIR187U3fUImje0hOrvD+IMaXT6zdi26jCXRRLuYaSy6kbBkeMCZHY7enh2prlE5Io9tvZck2qfHpRIMp57GotoB3uSPO9ZIsGMMCNfWEPrsXdA1fC89CFrkg9AwwOEksPoFmcgihIhLyliESEMJR8/ufRmL1tFk/ln3Gd7Hbkq6ngiGDZr0QjICLRjdbeZD5hSZf+ab/Tz09sYBP/ZIsUpUrJOUeLXu0TX2EJnGkiTYEY4KiqiKuW1xnosun2Y3OvRHBTusxw5rBtawrIJsKWMRYriEI4HGaePNUr4te3wxmViBcG/GRqIghkNVopoNJxtP3dsDKNnoWafTHD2bLHBicQ149KxCINRbQpeyjEUyO8RwM8e7RT4gda33DlUFXUOr35xygSKE2D8Fw1LGIkT6iT+NxS5D2YvMDr2tDrMkxrAbnvfV6g3x0WYvgZBhZna0byG0w9xOyTEzO5SsPHB60DtHf7DDHj0bSpz+bWd2RI+VTHSC4lDs5Zmm9wZFivMi42c7QnR0h2MzO6JHz9qZHU6ZxiLEMLGDHRVmsGPzbp9dwgLRZSyGPTq2L5dTGVD2lxW4SDl61mGWsQykQanVL8SKTSQKoHhcKsGQbr+XJWu0DKAbIxvseP755znttNM4+eST+dvf/tbv/ldeeYWzzjqLM888k6uuuoqOjo6k+5PV7xjgqpoHTlfsjaoD17QFYP0+JligCCH2byEZPStE+tH1+P017DKWgb/e7TWGosZteL5yQyffvvszbnp4K96tnzDTsQtHoAP/O4+ZD5ldFHlIBTW/BL1j9Ac7+jYojZex4Yg6OQFrGkvqMpboHhzj8s21279XtnDxbZ+wI6ovQCgcp4wlx0mXT7OzSYQQQ8cKduRlOyktcLG5zkdTe1Rmh1XGohl28LOv6DKWsJY62KFFmo8myhJzORV0w7xQlXoaywAzO5wqwUgfkGTb2T07tLh3D4uGhgbuvvtuHnvsMZ555hn+8Y9/sHnzZvv+rq4ufvrTn/LQQw/x3HPPMWvWLH73u98l3acEO8YAZ2U1uRffjnPy/N4bDcOsk3VEpger6oh3PxdCjD5SxiJEGkpZxjLw5Z21xsg49lJzrdGnuegDz+/GFzQX/UbtOhR0szWqroGioGTl9j58funYCHb0aVAab/EffXICyaexqGpvUMQMXpi3W5kdL65oQTdgR0NvjzU7OBIV7CjIMdd0nVLKIsSQi37tTZ+QxZY6nz12FnozO0Lh5L04dN18PWs6SctdrMdMliXmitS0+YJ6wkwNe1uH2Rw1VbDD4zJv90fexxONqB0NDUrfe+89jjzySAoKCsjKymLx4sUsW7bMvj8UCnHrrbdSVmaWTc6aNYs9e/Yk3acEO8YIZ2U1mYsuBafbvvrimXcCOV/+uZnlMeuoUd/9XAgx/EJJ5sMLIcYmw0jQoFQxz7JTjV7ty1lZTeZRF8RdR3h7wlSWeADY7phOGGfvnZm5MRkman7Z2Ah2WGUsVmZHnKcr+uTEnnaQpIwlempL38wO6ySjsa33RCqs9Q925Gebz6307RBi6MUEO8Znsrs5wM7GADmZ5vuo1bND05OUsUQFRZOVnlgBUG0AZSxgvmek6tlhlrH0ZmIkyhZxu1R7n5CsjMX8Ux+iYEd9fT21tbUx/3V2dsZs09jYSElJif330tJSGhoa7L8XFhZy0kknAeD3+3nooYc48cQTkz6uYhgjXJizj7xeLxs3bmTmzJnk5uam/oY0Ea6tIbRzHa6qefaixPvXH2NoIfK+etcIH50QYrR595MOfvHodu69ZqbdhEukv/31M3IkWM/1cKp64056xk2nee7ZMbcXf/o8+bs+oGXmSXRMOWZIHtvTtpPy1X/BoQXx542nbuG37fsKtr5F0aZX2HbCLRhO95A8vhBCiLHne9/7Hs3NzTG3XX311VxzzTX23x944AECgQDf//73AXjiiSdYv349//3f/x3zfV6vl+9+97tUVlZy++23J31cZ9J7xajjrKzud+XFOXEO/vefwvf2Y7imHCwZHkIIm4yeFWJ4DGdgqf1dJ+NKSph06KExt/c0rySwCyorJzK9z337whfQOPen6znrqHE8+14zsyqz+Kx2Ko8edChseZ/c0koOjXqcYIaX7k2vMLtzHe7qY0bteqS9K8RFt31KlkfFH9L5923z+22zblsX1z+0hdu/PpU5k7I5+yfr+NopFVxwbGm/bf/+egN/eame539xIL97ppbVG708euMcAL551wbausL0+DVKC93Ut5rZHcfNL+DHX57EDx/YRIZb5favT2NXo59v3v0Z119YxfEHFQ7tkyDEfu6mh7fgD+rc9Z0ZADz1ViMPL93Dwjl5fLy5i1MOK+KbZ0zg//3fVjq6w/z26pn99vHse008+Hwd/7jlAL726xpOXlDEt86Y0G+7Nm+Ii2//lO+eOYF/vtPEnKpsrruwqt92y1e1cM8/aykvcjMuz8WvvzU94fE/+ko9f3u1ga+fWsHDS/fw1K1zyc5w9Nvu1Q9bufPJXVx/YRW/+sdOfnb5FA6fnddvu5UbOrn1kW3cc9UMZk3MSvrc7Q3rgsCf//xnMjNjL7rl5cUeR3l5OatWrbL/3tTURGlp7HtuY2MjX//61znyyCO56aabUj6+lLGkASUzDwwd/9uPyVQWIUQMK1Vagh1CpBFdT9Czw2pQOjjLu56AGSwtKzSzNJo7zRN1R+Vc8zC622LWHEagB4DAB8+N6vWIVbPuC+p2ynpfdklJVziqJj7B/qJq3aMbjgKcclgxXzmhjJwshz3WMsujxpSxWN+fHTmWbv8IdggUYj8R6vNaPX9RKddfWMWFx5XhdqkEwr2v0URrKGvSXW8vjtTTWHTdsMdfJ9qfP6gPaBoL9PYWSTx6trcPiLld/P0Ndc+O8vJyKisrY/7rG+w46qijeP/992ltbcXn8/HSSy+xaNEi+35N0/j2t7/Nqaeeys033zygkk3J7EgDur8r8lXv2LjRejVFCDG8QjJ6Voj0Y+jxF3n70KA0mZ7ISXdhjhO3U6HNa/aScGblEAK0PZvwPnaT3dhU67Bqq0f3esRa1BsGLJjR/wonRI2N7QyhRybGJp7GYv4Zr/nguceY9ef/XtlCZ7fZoDQ7wxEzrtI6acnyxNbWCyGGjqYZZLhj3yutjCqPS7FHRYf15A1KwQycJGtQagc7UgRFrKCKfwANSq19WlNjEi3zPFawI2C+nyfq7eGI6isyUsrKyvjBD37AZZddRigU4vzzz+fAAw/kyiuv5Hvf+x719fV8+umnaJrG8uXLAZg7dy633XZbwn1KsCMNuKctIPDu4+Zf4oyNE0LsP9Zv66KxPcS8KdmUFLjtYEeqRldCiLEkwTQW67a9bFCaiJXZkZXhIDfLSUunmZmgdkfVXUcFNVzTjyDw/lPm7aN4PRI9RvLIOfGDHVkeFY9LpbUzlHLagbU/XU/cpDA/28kuzGBHVobDfm8Oa4adaeJxqShK7/MuhBg6YS1xEMPtUnuDHWGDTE/8SIId7AgbhDUjSSAhOtiRfPQsmAGMgTQotbaFZA1KI5lsASsoMnqnsQAsWbKEJUuWxNz2hz/8AYB58+axYcOGvdqfBDvSgLOyGrVkMgR9ZJ913ai8iiKEGB73/HMXu1uCOB0K//3VKYQ06dkhRNpJUMaiDHoZi3klMMujkpfloKUzhMup4J48n8B7/wAtHBPUcE2cg5JThJKVR/YpV4/a9Yi1qHc6FA6dGb/PiqIoFOc5afWGU05jiSljSTCitiC7d8md6VZ7Mzs0w57AoCgKGW4VfyB1GcvPH93OkdV5nHRoUcpthRD99S1jieZ2KrFlLAm2s9ZWVn+0RNkVVkBU08xSt4SjZyN3GEbioIS9T3uEdvIpKx5nbBlLyvexNKuik2BHmnBWTCe09aNRu7AQQgwPr19j4Zw86lqC3P7YDirHmSMjJdghRPowDD1+9kYkyLG3o2cTic3sMAMpHqeKs7Ka3Itv7zcdDsBRXIkRDo7q9Yi12D9oWg5ZngTF80BRrosWb4hIzDjhyYdqX7U1U97jnUxYPUDcTgWXUyFk9ezoExzJdKv2SUm0ls4Qd/x9B4fOzOXLx5exemMnuZkOCXYIsY+0JEEMT3Rmh2bgdMaPEFivXX9k20TBE1VVUBXz/UHTjYQlcdFrtYEGOwJBM3iS6H3f3aeMZbRndgw2KeJOE2rheIyuFoygb6QPRQgxDO56aie/+Nv2frf3+HUmjPNw62WTUVWoaw1wwbGluBN8UAshxiBDj395brAzO/y9mR25WebJuscdyYqorCbzqAv6BTXU/DL0jqZBefyhoigKpx9RzHmLSpJuV5TnorUzhG4kz+xwRmd2JLhabAU7PC4Vp0NBsxuUxqarZ3ocdrq5pc0b4vv3b2L99m4+29WDphsEQoZ98iKE2HuhqBKyvtwu1S4PGUjPjt6+GYkDFA6HYpexJHrc2GBH8uO3HzucvJmpZ8BlLOafepoFOySzI004isYDoLXV4SybNsJHI4QYSm+tbefl1W24neaC2WHXjOqENYMsj4OKIg+PXF+Ny6Em/FAVwvL888/zwAMPEA6Hufzyy7nkkkvibnf99ddz5JFHcu655w7zEYoYRoKeHdbZeKrOdgPUW8biIC+S2ZEqcKrml5oXX8IhFKdrUI5jKFx9dmXKbYpznazoDKfs2WGdJGh64uaDdmZHJNjRO40l9sQn0632C2J8urOH5o4QHpeCL6DbDUylt4cQ+y5RYBLA41To9kVeo2Ejps9PNLvHRjD5ewSYQVEtThPjePuDxAERe3/2NBY9Yb8O6D+NZSDleOlELvWlCTUS7NBb60b4SIQQQ6nbr3Hfc7Vmp/Cwwa4mv32fFbW3GmlluB0S6BApNTQ0cPfdd/PYY4/xzDPP8I9//IPNmzf32+bb3/623f1cjDBDR4nXs2OIGpRmelRyM3szE5JR881sCb1zdGd3DERRnotASKfLF5likHAaS289vp6gZ0d+jhksynApMcEOTYs9kcr09C9jCUT+XpjjwhfU7L/HK3cRYn9X1xzgD/+uS3nSnqxBqcetEoj0wghpBs4EpcDW9/tDyUtEIJLZkaSJMcROzhtwGUtIT5oFYgWoU5WxqHawI+nDjjkS7EgTjsJIZocEO4RIa++sb6ezW+PbSyYAsKWut3TNWvgmq0EXoq/33nuPI488koKCArKysli8eDHLli2L2eb555/nhBNO4NRTTx2hoxQx9AQ9O+wylkEKdvi1SI8J1e7ZYXX2T0TNLzMPsaNxUI5hJBXlmpkpje3mFBpHgrdWK6is6QbhgWZ26FbPjtgTLjOzI/Zsw2pAmJ/txBfU7fd6KWMRor+Vn3Xyr3eaaGgNJt0ueYNS1Q4qagMpYwmmnnxnlq+BnqT56L737BiMMhbJ7BCjmOLORMkpRm+TYIcQ6ezNNe1UFLk56ZAi3E4lJthhpZwnGpEm9j/19fXU1tbG/NfZ2RmzTWNjIyUlvb0LSktLaWhoiNnmG9/4Bl/60peG5ZjFAKQqYxm0aSw6WRnmGb7doDRlZkcpAHrn2A92FOeZwY7mdvOkKWVmh06ktLD/NtHBDoeqEI4ZPdu7XabH0T+zI9IPID/HiT+g4wua7/VSxiJEf9brpbEjebDDbFAa//3M41IJhnvLWBJOY+nXsyPx4zlUJWVvj70JdriienbsVRlLovexyPtQugU7xnzPjo0bN470IYwaExQXwY0fsO3VpwkUVI304QghhsB5B5l/fvzxh/zkbIB6Vq+ut+//xflAcAurVw//sYnR56tf/SrNzc0xt1199dVcc8019t91XY/p4m4YxqBN8xCDzzAMIEGwQxn8zI6sSPA0L2uAZSy54wCF4PrXcRRPHNVTWVIpzjN/5saOSGZHiiuiYS11z44Ml4rLqfSOntUNnFFnSJme/j07giEjsg8zEOK3Mzsk2CFEX4HI66UpkpGVSChBYBLMDDYrMJGskamjT7AjWdDB6VDsLK1Uo2fNfSc9fPuxgynKWByqgtup2OV4CTPU0jSzY8wHO2bOnElubvwZ6fuTcG0N3q5GMHQmrP4LuRffPqYXGEKI/p59t4kHX6jj9z+YRVVpBr97ppa31rTzxE8OQFEUVn3Wyf/78zZ+8+3pzJmUPdKHK0aQ1+tl48aN/PnPfyYzMzPmvry8vJi/l5eXs2rVKvvvTU1NlJaWDstxin1gRE5wk46eHcTMDk9sZoc7RbBD27MJMAjvWIv3sZvG9HqkqG9mR6JpLJGTBz1Jg1IrWOR2KThUc/SsphsYBjE9OzLijJ61RmDmZzvxB3X8ASljESIR6/XS2N6b2fH+px0cMCmbvEjQ0TCMSM+OJJkd9uhZPXVmRzD56FkAp9obiEkUFNmnMpZQ8mksACUFbnY3B5Lu1yE9O8RoFtq5zkxrBdDC5t+FEGmlZmcPZYVuqkozAJg2PpMuv0ZDm/mBbi2QpYxFWMrLy6msrIz5r2+w46ijjuL999+ntbUVn8/HSy+9xKJFi0boiEVK1md9vAalgz16NqDZ7ydWg1J3gkZ9lpj1xxhfj2R5HGS4VZpSZHaoUVdEtQQNSp0OhZxMBx6XiisyetZqUursU8biD+qRDB5TIGyOp83KcBDWDLyRK7TBsGGPsBVCmKwsCyuzo7UzxH//dTsvrmyxt9EjJ/SJghhup4qmY4+KTdWzwz/A0bPBQS1jMd+bAyEjaUYJwPhit/114nI88089zd5TZEWcJlxV83rzklSH+XchRFqpbwtSUdT7gVU9MQuAFRvMHgzRYyKFGKiysjJ+8IMfcNlll3H22WdzxhlncOCBB3LllVeybt3YPVFNW1ZmR7w0A7tnxyCWsUR6dlijZzPcyZeOrqp5vcEWh3PMr0eKc512g9JUPTvCevKxkvOmZDN1fCYOh5nZYQU7+o6eNYzeEzYwGxB6XAqZkee+vSts39cTlOwOIaIF+mR27Gg0p9ZZF4bALE2BxONdrUbMPX4t6XZWZoiV2ZFsAl50GUuiLLHo4EuqYId12hcM6aQavFdR5Inab4L9SRmLGM2cldVknXYtPc//hoyjvjRmU0aFEIk1tgU5fHbvVfkpFZnMmZTFM+80c8YR4+z67SzJ7BB7acmSJSxZsiTmtj/84Q/9trvjjjuG65BEIpFgR9y+Kvbo2cEsY4lkdlhlGM7k+3ZWVuOe+0WC614l58s/H/PrkYpiD6s2eoHEte7W1V1NsxqUxj/z+MmlUwB4eGkdmtabldF39CyY/Tgy3OYDBsM6bpdqBztavb29CHwBndzYSjUh9mtWjxsrI2tHgxnsiO7hYQUaE2V2WL2JuiMXkRJt1z+zI/FxmQ1KDfvreBSldzR1sn0BZNnvDwZqimhHdGaHjJ4VY5Z79hciX0ljOSHSjT+o09YVpiwqswPgvGNKqW8L8s4n7fT4rTIWyewQAuDee+/l9NNP5/TTT+dXv/oVYI7aXbJkCSeffDJ33323vW1NTQ3nnnsuixcv5uabbyYcDifa7ciy8q/jTmMZ5AalAc3OFHM6FOZMymJqRUbK73NWHQAYqHnjYm4P19bge+8JwrU1g3J8w2Ha+N5IQuppLIl7dkSzRs9a42f7ZnZAbPPRQEjH41Lt9/Y2b+/vpjQpFSJWdBmLYRh2sCN6OktvCVmqzI7kvTh6+2YkD2KAWaJiBSpzMhKv06xSlmRZIgAVxW5mRzJ8U73nVBT3ZnYkKnlJ18wOCXakEcXlQc0rQW/dPdKHIoQYZFb6ZXlhbLDjyOo8yovcvLK6DV9Qw+VUkjbIEmJ/8d577/HOO+/w9NNP88wzz/DJJ5/wwgsvcNNNN3H//ffz4osvsn79et58800ArrvuOn7yk5+wfPlyDMPgiSeeGOGfIIGkPTsGObPDr5OV0buv33x7BosPK075fWp+GQB6e+8I49CuT/D+5Tr8b/wF72M3jZmAx/QJvcGOxI39zD+T9eyI5nQo6DqEwv1PuKyARnST0mDIwONS7RKimDIWaVIqRAwr2BEI6Xh7NHZGyliaI8EPIG4JWTRPJIOtO1LGkrJnxwAalDpUxQ5U9r1wFc0OdqR4H1EUhYu+WDagbWMzOxIdn/mnBDvEqKYWjUdrq7P/Ht3garAEQzo1O7sHfb9CiMSsYEdZn2CHqipMrciksT1IT0CX5qRCRJSUlHDDDTfgdrtxuVxMmzaN7du3M2nSJCZOnIjT6WTJkiUsW7aM3bt34/f7OeiggwA499xzWbZsWb99dnZ2UltbG/NfU1PTsP5cRtJpLIPXoDQY1glrxj71AFILIsGOjt5gR3DNy0BkbO4Yalw6PTqzI9FJgmPvMzug96QsNthhZXb0BjECIR23U7Hva+uKLWMRQvQKhnvPfRrbg+xsCOBQzQBiVyR4EY7UaiQsY3EPLNjh6vNaTvbaj95H3wtX8faZ6n0E4LBZucyszCQnM/n7dGmhG2t3ktkhxjS1cAJ6qxnseHd9O5f9Tw2f7eoZ1MdYurKFHz6wmU+2Jw94NHUE+fY9n7Gt3jeojy/E/ihRZgdAUa6TNm8YX0CzaziF2N/NmDHDDl5s376dpUuXoigKJSUl9jalpaU0NDTQ2NgYc3tJSQkNDQ19d8kjjzzCCSecEPPftddeO+Q/SwwjWRmLNXr282d3Wenb+xTsyB0HihqT2aF3tfVuMIYal5YVuu2U89QjG80+HKlq7a3t7WBHdM8Oq4wlOrMjHCljidwXW8YSm9nR0BZET7OTFSH2RjCkU5hj9hjasKuHLr/GnEnZQG/fjnDkZZOwjGWAmR2qasad7QalyaaxRO7zuFQKchK3zbSmrAwk2KEoCr+4Yio3fHlS0u3cTpWSAnfS/aqqgqJIz44Yl156KaeffjpnnXUWZ511FmvWrNnrWti6ujouueQSTjnlFL7zne/Q3S0ZA5+Ho2g8hr+LbU//kaeeeJvmjhAv//u9AdfIhsI6z77XREd34lrlT3aY/0aPv95/IRjtw41edjT4Wf5B6979EEKIfurbgridCoW5/T8gi3JdeH0and1aTMq5EAI2bdrEFVdcwfXXX8/EiRNjAgGGYaAoCrqux729r8svv5xXX3015r///d//HZafI+rgzD/jBTvsBqWfL9jR0R22Jxnsy3uK4nCi5o2zMztC29cQ3vExuM0siaxTrh4zjUsVRbH7diTM7LCCHZoZ8EhVa+/qk/ruiFfGEt2zI2jgdil2w9KO7rAdUOmJ2s7bE+Ybv9nAax9HBZaE2M/4QzoTSsweFR98ZjYXXjDLbO5uva9ZmR2JghieAfbssBqK2q/lJG+X1j7Ki9xJA9K9PTsS7ytabqYzafDEYk3zSxZDcahK2gVL93lVbBgG27dv59lnn7X/mzVr1l7Xwv7sZz/j4osvZtmyZcydO5f7779/cH6y/ZRhmBHIvJpnuCHjYa6fW8MFLb/FN8Aa2b++Us+Dz9fxl5fqE26zYWcPbqfCqo1eNtYmzhqp2Wne98769rR74Qgx3BragpQWxv+ALIoEQHa3BKQ5qRBRVq9ezVe/+lX+67/+i3POOYfy8vKYspOmpiZKS0v73d7c3ExpaWm//eXl5VFZWRnzX3RGyLCwprHEHT07OGUst/1tOzf/aSuw76Os1fwy9PZGwrU1dD3+E9DCEI6UX2jB5N88ykyL9O1IdEXUGVPGMpCRkYnr/O0ylqiRsgErsyNyn25AQY7L3C4q2NHZoxHWDGp2DG5GrxBjSTBkUFbgJsujsnJDJwALZuYC0ZkdqRqUDmwai7WPPa0BADt7Ih7rdd+3HLmvgfbs2Fvjiz0oSuIyFvMxpYzFtnWr+SF4xRVXcOaZZ/Loo4+ydu3avaqFDYVCfPDBByxevDjmdrHvjO4OAFQMnGgc3PEKLkVDGUCN7LptXTz1VhPZGSovrW6ltTPUb5vmjhBNHSEuPK6M3EwHd/9zV8LmWDU7u/G4VFo6w3wqPT6E+FwaWoMJazwLc81Fb2Nb0E5zFmJ/t2fPHr773e9y5513cvrppwMwf/58tm3bxo4dO9A0jRdeeIFFixYxYcIEPB4Pq1evBuDZZ59l0aJFI3n4iSXp2TFYDUq31/vp8pmf7fuaLaYWlKF11BNY8zLokWxRQweHi8BHy8ZMg1KAAyZloygkrIu3nvaB9uxIVucfbxpLMDKNJSPq/d0KcscERSL721In5cNi/2W9Xu76zgzOX1TCmQvHMbksA6dDicrsSB7ssEbP9kTKWJJlazkjI2Uz3ar9uky0HSTv1wF7V8ayN044pJDzjkkenFdVxR6JnS72+dOws7OThQsXct999/HnP/+Zxx9/nLq6ur2qhW1rayMnJwen0xlze7zHGumGYKNRIKTb0bdQ2PyAc886ChQ1kuVqYLTvwfqV1VGT1sg+914zBTlOfv3N6ei6wb/e6f8cb9hlBi0OmZHDj788iZ2Nfn79j539tvP6wuxsDLBkYTEup8Jba9s/z48qxH6voS2Y8GqA9eGqG5AlDUqFAODhhx8mEAhwxx132OW2//rXv7jjjju45pprOO2005g6dSqnnHIKAHfeeSe//OUvOeWUU+jp6eGyyy4b4Z8ggSRlLFpLrfln86593n2XT8Pr0+x07H3N7EBRMbwtBNe8FHWbAnoYrX7zmJrIsnBOHg//aDYl+fHfg62TmLBmBTuS7y9ZZkdGnJ4dgZCBu0+wIzfLYTZdjCl3Mb/eVu9LuxMWIQbKH9JxuxQmlWXw9VPH850zJ6CqCiX5rr3I7IgtY0ma2RHJxKgs8SQtT4kuY0lmqDI75kzK5uunjk+6jUNV0q5nR+oCnwQOPvhgDj74YPvv559/Pr/97W859NBD7dtS1cLGq4mN90vyyCOPcO+998bcNnPmTH7605/u6+GPeb6AxhV3bkDTDMblu9je4Of6C6s4bn41riPPJ/T+E2Y2B6Bg9j/faZRzQNmshPv8bFcPB07JYUpFJsfNL+TZ95o58ZBCJpdn4gtovPCfFrbX+3E6FKaOz8TtVLng2FIef70Rry9Mbmbvr9NnkRKWQ2bk0uYNs3RlK6ceVsyUisxEDy+ESKC9K4TXpyX8gCyKZHYAUsYiRMQtt9zCLbfcEve+5557rt9ts2fP5qmnnhrqw/rcDD1+g9JwbQ2+1/8MgO+1h3FWTN+nvhj1kXTsy06uYEe9n6rSjL3eR7i2huC616wjjvyp4CibhrZno/nXSLbpWOjdoSgKFUWehPc7ooIdhpH8KjAkn8bicqo4HUpM49FgSMfjVHCoCh6XdRXZQabHEZNd64/sLxg22N0S2Kd/OyHGOiuzo6/SAjdNHZHMDj1FZke/BqWJI5hWIKSyJPF7BPS+Lww82JF0syFhBjvSK1C6z0/jqlWreP/99+2/G4bBhAkT9qoWtqioCK/Xi6ZpMdv3NSoago0yb61tp70rzNwp2RTkOPG4VNZtM7MuAoab2Imz5oumUG/l0xWr4+6vpdMsT5k1MQuAK0+vIDvDwZ1P7iIU1nlnfQd/WraH1z5uY3ok0AEwfYK5fUNrb/3tjgY/r3/cjqrArIlZfOO08eRmOvjVEzvtDBQhxMB9uKkLgAOn5sS9Pz/HaTecktGzQqS5BGUsoZ3rQI+c+OraPo923RP5PF8wM5frLqyKySYYqNDOdb3HaR4sOF14DjoZHJELI6pjzExkScU6ibFGXg509Gy8zA4wM/T80WUsYd3uIWA1Kc1wq2R51NjMjlDv11ullEXsh8zsKuIGO0oKXNRH3t/CkdeqM8Fr1e7ZkWIaS/R9leOSBxcHXsZiNSgd3MyOgZCeHVG8Xi+/+tWvCAQCdHV18fTTT/PDH/5wr2phXS4XCxYs4MUXXwTgmWeeiVsjOyoago0yS1e2Mqksg//3lcnc/vVpTJ+QyfbIiNfOwtkEcWGggsOJc+YRKIpKvtrDhLdvi5s2uiEynnZ2lRm8KMhx8e0l49lS5+PDTV3sbDQzOk46tJCzvjDO/j7rBWstjlo6Q3znfz/jtY/bmDM5myyPg4IcJ984bTzb6/1srJUPXyH21gefdVKQ42T6+PiZUQ5VIT/SiXufU86FEGODFUTo06DUVTXPDCQo6uca7bqnxczsSHX1MZm+x+I++BRyL74dz8Gnkv2lWwFwzzthTGR1DIQV3AjG6cERj3XSEwjGD45kuFV7yophGHYZC/T29Mj0qGR6HAmDHVv2yHpL7H+s14BVhhJt+oRMWr1hGtqCvWUszhRlLIG9CHakzOww/yxLmdkxND07BiIdMzv2uYzl+OOPZ82aNZx99tnous7FF1/MwQcfbNfCBgIBjj322Jha2FtuuYWuri4OOOAAuxb21ltv5YYbbuCBBx6goqKCu+66a3B+sjS2pc7HZ7U9fPuM8XbZz5SyDF75qA3DMGjMmMbfer7OdV/opOLAQwjtXEd40woAVCNMaMfafguMz3Z143QoTIsqMzl8dp79eDsbA1SO8/DD86tivs9aDDW0mcGO2qYAhgE/+tJEFh1YYG9njW1r7gwC2YP3ZAiR5jTdYPVGL4fPzkvaQbswx0mbNyyZHUKku0jqptKnjMVZWU3uxbcT2rkOV9W8fQ4k7GkNkp/t/FyB02TH4p56CL7iSoyu9BlLb6Wbx2s4Go+d2RGKfyKV6XHYWR9WtkhG5OQrw2NleKhkutWYMhYreJKX5ZAmpWK/ZAUcrTKUaPMj2bFrtnTZjZcTBTFcDgVVge4Uo2ej70sV7Jg+Pov5UwMp31uHqmfHQJijZ4f9YYfUPgc7AL7//e/z/e9/P+a2hQsX7lUt7IQJE/jrX//6eQ5jv2IYBn98sY5Mt8oXDym0b59ckYnvPy00todo6wqxSa/Cc1Q1zsgIJL/DhREOYhjQlDOLqj77/WxXD1MrMuwrB2BeIa4ocrO13kdtk5+pcfptZGc4yM102Glh9W3mFaE5k7PtyCRAcZ7ZU6ClIzwoz4MQ6Wzdti4+2d7NBceWsrG2B69PY8Gs3KTfU5TrYusev2R2CJHu7PKQ/gthZ2X1586W2NMapOJzZHUM5Fic42cR2rIqbu+2sag3s8PK1EixfYoylky3ak9ZCdpXqmMzOzLc5ija6MwOa3/TJ2Syu3lsjfcVYjBYwUFPnPK7SWUZ5Gc7Wbu1yx5Fm6iMRVEUPC4Vb4953pIq2KEo5mjXZE5eUMTJC4pS/gwjG+yQMhYxwpZ+0MrHW7oifTB6Y1VTys06sW17fLR5zRdmQSSt3brCQmEl7UYO77dVxOyzozvMxlofsyf2z7iYOj6Tjbt6qG8NMjFBo6vyIndvsKM1iKrQr2N5doYaGUPbf5ytEKLXIy/t4fqHtvDIS/XU7Ozhgw2dqAocOiNFsCMSUJTMDiHSnB6/jGWw7GkJUFH8+YMdyTgnzMbo6cD32p/GzESWZFTVvAocjPQlS1Vr3zt6Nn4ZS3QQw9qmt2eHFfRwkOVx9JnaYn5dku+myycXl8T+J1kZi6IoHDg1mzVbuwilKGMBmFjqodU7sGBHSb5rn/obxWONnnWOwLUr1ZF+ZSyyKh5jHn+tgbmTszn18NjI4KSySLCj3k+bN0RupsNuIgpmwCPr0FMpVr1s21Rr397SGeK6hzaj6wbHHVTQ7/GmlmfS1BFCN6AqQXpWeZGb+rbeYMe4fFe/NwVFURiX56RZgh1CJKTrBk+/08yCmbk4HQr/qengrXUdzJuaQ25W8kQ8a/ysBDuESG8GiUfPfl6hsE5zRyjp5JFB4TSDKYEVT4+pEbTJqKpCaIANSvtndsTeH92LozctX7Hvg+jMjqgylsi2RXkuuv162p20CJFKIEkZC5iN3ps7Quxq8gPJgxjVVb0XgZNtN7sqm4Vz8vflcOOyMjuSlS4PlXQcPSur4jEkGNZp6ghx0PScfmmfWR4H5UVuttf7aO0KU5jb/8TIGWlWdkj9UwR3fQrAU281Ut8a5BdXTI15UVumVvRmcyTK7CgrdNPQFkTXDRraggkXScX5LsnsECKJ+rYggZDO0fPymTclm2UrW9ndHIjpf5OINX5WyliESHMJprEMhsZ28+LGUGd26N7myFeGPYJ2rHOoyoB7dvRmdsTPBMnO6O3FEQgnL2Pp6dOg1O1UyMsyPwd6/BpCpLufP7qd37+wG4gKdiTIspg3xezbsXarOcEyURkLQPWkLPtrV5Jgx5WnjefbSybs3UEnMdI9O9ItSCrBjjHEChT0LRGxTCnPYNNuH23eEIWRE59oRsiPARyqrqXrsZsJ19bwyfZu5lRl2y/+fvuM9OlQlMSNd8qL3IQ1gxZviPq2YMIuw8V5Llo6JNghRF8vr27l7XXt7GgwrzRMLsvkyOp8uvwaqgpfOCD1FQOrWbBVviaESFNWGcsQZHY0tptZmqUFQxvscE2aj91z5HNMjhlNnI7oBqXJt+2b2dH3RCo7w0GXLxLsiGzj6VvG4lHNMpaAhhFpWhsI6nhcKjmZZrDD65Ngh0gf3X7NHohg2Vbv471POthYa06VtPrmuBNkdlj9iOqazR6DycpYBprZMdjs0bMj1bNDk2CHGCHNkUBBSUH/QAbAoTNz2dMaZNNuH4VxTnjCuz4BQFUALYxv6xq27PExJypy2VdpgYucDAdlBe64M6sBygvNIMjOBj9t3nDC+dHFeS5avCH7QzlaS2fITtUUYn/z6Cv1/N+yPWyPBDuqSj0cUW1OQzp4Wi752akDGAtm5vK/351BVYIMLCFEmjCGroylozu259dQcVZW45g8H8WTTe7Ft6fFCFqHqtDZYwYXsjOSZ9j1jp6Nn9mRk+GgJ2CWodgNF129QQ4wgx5ZHhVN723K6A/pZLh7gx1dEuwQaeSR5Xv41t0bWLu1C8MwMAyDF/7TAvQG9uzMjjg9O8DMkCrMddrbJ8vYKMl32QMWUvXhGUy9o2eH7SFtcyZlM2NC/4EUY5lcAhxDmtrNYMe4vPjBjkUHFvD7F+oIhQ07pT2aq2oeftUBuoamOKj3zEDXzV/sRBRF4eAZOUmb7lhXlNds7QLMspZ4xuW5CIUNOnu0mJO3N9a08Zsnd5HhVvnSohIuOK4s4WMJkW66fBqNkdf2ippOygvdZHocZHocfP3UioRZV30pisLMysSBSyFEmoiUsShD0KDUCnYMJMD6ebkmzcO//WMcJZOG/LGGg0NVaO8yn79UPZasq8n+yIlZ31T67Eiwoieg9Wu4mBFVxmJt1+3T8LhUAiEDjwQ7RJpq8YYJhAxu+b+tOB0KGa7eci9vT2yww53gAi1Aab7bHuaQLHtCURSqq7J4Z31H0qDIYLPKWIYzm8TyrTMGrxxntJDMjjGkucNM3UqU2ZGb6WRh5Gpw3J4dldVknXo1AG+6TuCjrgkoClQnCXYA3HTxZH54ft9htb1KC1xkZ6i8tKoN6A1+9FWc74r8HL2lLG+va+dX/9jJrIlZTK3I4M8v1dMtNaZiP7K93md//dmuHiaV92ZmnL+olFkTJYAhhIgyhD07Oro1FAX7ZHkoOcaZQQ6tZdeQP9ZwcDgU2rzm+sbqmZGIFdzwJ8jssDJDun1ab4NSu2eHI/Knam8XfVXb41LtaX1eX5j2rrB9XEKMZd0+japSD8fNL+DEgws5YHI2OZlODp+dh7cnjGEYdhlLomx0gNLC3vOoVAGFY+cXMHti1n5TxpKOJNgxhjR1hMjJdJDhTvwhesIh5pSWRNkf7nknEHJkYnS38tpHbUwqy0iZbpmKy6ly8RfL7StCycpYoLf3SDCk84d/1zGtIpPbrpjKl48vwzBgw86emO+7/7labvnTVilzEWOWYRg8824TL69upb0rdtG5rd4sXbFSkyeXSRmKECKJISxj6ewOk5vlGJZFtqPEvIiiNe0c8scaDg5VsctJUmZ2RE5mvD1hVLV/ZoedmeHXekfPRlLbrfuyMxzk9sngMHt2KDGZHXc/tZOfP7r98/54Qoy4Lr9GeZGHH55fxVVnVXLzJZN59MY5zJuSjaaDL6inLGMBKIn0JHI6lH4DH/o6em4Bd181Y1gno1hlLCMxjSUdSbBjDGnqCFGSHz+IYTlsVi43XTyJhQkaGiqqA2dJFUe6PyG7bTPzJifP6hioJQuLqSzx4HEpcbNKoDcAY42ffe79Zpo6QnzjtPF4XCqzJmahKlCzszvm+z7e0sXqTV7uempX2jXNEfuHHQ1+fv9CHXc9tYsr7/qMrXt6szm21/vJzXRwVGRs2SQJdgghkjCGsEFpR3d4WEpYANSCcnC60Zp3DMvjDbXo+vrcFJkxVrCj268ztTyz30lNb2aHTjAce/K26MB8bvnKZEoK3OREMjisjFgrsyM62LG7OcBnu3oka1aMed0+jZw4F2hzI5lU3h5tYGUskQz50Zo5MZLTWNKRBDvGkKb2YMpgh6IoHDOvIGH6Vri2BqVxMzlGN7fmPswlB7QPyrG5nCo3XzyJ//pSVcIoaWGuC0WBlg6zGekTbzSyYGYu86eZPQmyPA4ml2fw6Y7eYIdhGDS2BRmX7+LNte18776NbIs6URRiLFizxexn85NLJ5PhVrnp4a321INt9T6mVGRwRHUeikLaNYYSQgyyIS1jCZOfIithsCiqAzV3HKGNKwjX1gzLYw4lqxQlJ8ORsplhdEp8vFJFK9jR5dfiTGNx2BO6+vbm8AfNBqUel4rLqdDl02juDKMbULMj9kLSO+vbZT0lxpQuv0Z2Zv/zm+iyLbuMJcE0FoCySGbHcPbh2BsHT8/lzIXj7Mkx4vORYMco1u3XeHtduz3vuLkjxLjPOQ4utHOdvVBS9TDuxk/7bROuraF76b10L713rxYgk8szOWZeQcL7nQ6Fghwnje1B3lnfgdencd6ikpht5kzKZsOuHvtnbu8ymxGdv6iEmy6eRHNniN+/UDfgYxJiNFiztYvyIjcL5+Tzi69NpaM7zFtr29F1g+31fqaUZ3L03Hz++MPZVJZIZocQIgkjPTI7wrU16O316G11eB+7acwHPKyrsLkp+nVAbI+OeMGOnKjGo4FIaUy8K9W9I2bNMmIrs8O6r6EtaF/pXrctNtjx23/V8ou/bbczR4QYzXTdoMefOrMjGNZxOpSkAUe7jCXJ2NmRNC7fxXfOnDCsE2DSmQQ7RqkNO7u56n8/4/bHdvDKh634gzqdPVrKzI5UXFXzwBHZh0LMbPtwbQ3dL9yD9y/XEfxoKcGPluL9242DugCZPzWHN9e28+SbjZQXuTmwz6SJ6qpsfAGdnZERnNY87fJCD8fMK+D4+YVs2NVNKMmHs9XwS4jRQNMN1m7t4qBIBtOksgwqitzU7OyhoT2IL6gzpTwDRVEYP84zwkcrhBj1Ij07lKHo2dFnWtpQMi++REpTtbD59zFsb4Id0T06qqsSZ3Z0+3sblLrjnJjZGSB9GpSCGeywxpkDrN/eZX+t6wZdfo26liDPvtuc8niFGGm+oI5u9E4qihbdu8Yf1OO+VqJZDUqlTGT/IMGOUUjXDX79hNmwq7zIzXPvNdsTTD5vsMNZWU3uxbfjmFANKIS2fUS4toZwbQ3ev91IcO3LQFRfDC2E7+3HBi3gceXp4/E4VbY3+Fm8oKhfnWr1JPNDv2aX2aS0PhLsKIu8MR0wOZtAyGBLXfzUy1ZviItv+4R/r5APbzG8uv0aT73VyKrPOglH9ZbZUuej268zf2pvYK+6KpuaHd18vNlcfMrIWCHEgA1RGYuuG3T2hMnPHvpJLGBdfIkEVlQ15uLLWGQFMPIGUAakqgqqapa8jC/uH+TO8qgoinnyFgjpuJxK3GaFTodCpluNalBq2MGO3EwHu5sDAMyZlMXGWp99McgX1DEM8/v//lqDNIAXo57VcyZ+ZkekjCWS2ZFsEou1j0y3OmrLWMTgkmDHKLRmaxd1LUEuP7mCLy0qZeseP8tXtQC9qVefh7OyGvecY8HQ8b/9GN7HbsL3zuOgxR9NFt720aClmBblmqlZBTlOTj60qN/95YVusjwq2yN1pI12sMP8uQ+INFT9pE/tqeXtte34gjp/f60xafaHEIPt7XXtPLx0D//vz9t46N+77ds/2NAJwIHTooIdk7Jo6wrz9DtNVBS5mVwupStCiAGygh3q4C7hunwaug55w5TZ4aysJufL/w2Kiqv6GJyV1fZ94doafO89MaZKWxyRc7CBZHaAGRyZNTErbhBDVRWyPGoks8NI2n8gJ9Nhnwj6Qzoed2/vEKuX7THzCghrht2jwwqOzJ2cjS+os6c1OKBjFmKkdEd+Z+NldkSXcwVDRspgh6IolBa6pUxkPyHBjlHoxRUt5GY6OHpuPl88uICcDAdPvdWEqhD3CsC+MAJWsMCAcJDw1lW9d6oOnDOPRB1X1bvNIKaYfvHgQv5+8wEUxRmPqygKk8sz2BZJvaxvC5KX7SDTY76RFeW6GF/s5pPt8YMdb65tJztDpaUzxKsftQ3K8QoxEHUtAZwOhaMOyOf1j9sJawZNHUH++XYTh8/KpSi39/d9ziQzaLerKcAx8wpSjj4TQgiLMUSjZ63x8cNVxgLgmnQgjorpGB1N9m3+D1/E+9fr8L/xyJjq5aHuRWYHwEHTczl2fkHC+7MzHHT5zCvV7iRjNHMyze00zSCsGWS4HJHbe49jxgQze7Cjx/w3toId0yMNsfe0BgZ0zE3tQdq88S+MCTGUvFawI05mh8el4nEpeHs0/KHkrxdLeZGbDLecBu8Phu8TTQxIS2eI9z/t4KwvlNjNqP7fpZNpaAsyb0o24z5nGYvFNXk+/nceA73vKDIF9/yTyT71arO05a/XmTW1DuewpZhOLsvkrXXtGIZBQ1uQ8sLYbJYDJmezYkMnhmHEnCQ2tAWp2dnDVxeX8+76Dv76cj1zJmVTVSpXzcXQ29MSpKzQzYmHFPLeJx2s2eJl6QetaLrBt8+cELPtpLIMMt0qvqDOMfPij4kWQoi49KEpYxmJYAeAc/xsAh8tpfvF36F1NKBt+6j3znCI0M51MVkfo5VzL3p2APzs8ilJ77cyNqzpKsm28/o0AtaIWiuzI3K1Oy/bQVFeb5o/9JYEWCWU9UkyOwzDwDAgrBv88MHNVJV6uO2KaXG31TSDu57axdlHj7MDLEIMBut3NtFY55xMJ16f2eMmVWYHwJWnjccXkHHM+wMJaY0yT77ZiAGccWSxfduBU3M46dAiyosGr3mhs7Ia9/yT+9yqgNOFZ94J9jYZx3zF/LrqQHsrK7008NHSIUkznVyeERmXFqKhNWiXsFjmT82hs1vjtr/toL2r9wrD2+vaATj2wAJ+cN5EDAN+9OBm6poHdsVCiM9jT2uQiiI3h8zIJdOtcu8zu3l3fQeXnFBGRZ/XrkNVOGByNuOL3UwbL6NmhRB7YYimsXREToTzhqlnh0XJzAUtRPDjZbGBDgAMdJ8X37v/GPUZHo69zOxIJTvDQZdfIxhOnpZvZXb0HVFrBTvG5bnsY+qMZHZYV8krit1kelT2tCQOdtz7zG5++MBmXni/heaOEOu2ddsTXvra0xrktY/bWFHTuZc/rRDJdSUpYwEzyOjtGVgZC8CEcR6mS0BuvyCZHaNIS2eIF1e2cOIhRf1OjoaCZ94JBNe9CloYVBX3gSfhmXdCzBUUZ9UBAIS3rsK7/UM8h59DYOWzoIftbfyqg6zF38Fz8KmDclxW/4Jte/w0tIdYeEDsle/jDiqkpTPEo6828ODzCjdcNAmA9du7qSzx2EGhO781nSvv3sDLH7Zy+ckVg3JsQsRjGAZ7WgLMmZSFx6Vy+Ow83lzbzuGz8zh/UWnc7/nB+RMJhQ0pYRFC7J0hmsYyUpkdRij5BYngin8B4He6yb349lGb5eGI/HMMNLMjlZxMB/WtQTJc6oDKWKwARLxgR5ZHRVWjMjt81lVyJxVFbuqTlLFs3ePjs9oePqvtITtDpduv8+mObg6enttvW2s/LZ1S6iL2XVgz2NXoZ0pF78WgZA1Kwcz48Po0wmGDrAy5li96yW/DKKDrBn9aVsf1D21G1w2+fHz8k6PBZk1myTj2UnIvuYPsU6/ut4iIuZKi6wT+88+YQId5u0bP8gcG7aqLFez4cJOXsGb0y+xwqAoXHFfGKQuKeP/TDrr9GoZhsHFXD7OiplqMH+fhgEnZ/EeuMIgh5u3R6AnodpDy/GNLOOHgQq6/sCpu8zkw+8/0/d0WQoiUhiqzY4SCHe6ZR/ZOZQFQHTgqZgJ93jtH+Xhaq9nhYGZ2dPs1egJa8syODAfdPo1AyAyCWX0IrGBHcb4LRVHIzXTawQ7rKnlOpoOKIg97WoPsaPDz0qrWfvv39oTJzXSgKnDtuRNxOhQ+2uyNeyxWOYwEO8Tn8cDzu7nqtxt57r3eyYpWgC7Lkyizw0lXjxYzflkIkMyOUWFXU4An32xiVmUWl55YPixZHRZnZXXSqySuqnn4VUec3h596Nqg1dXmZjopznPx/H+aURSYNTF+mtnxBxfy/H9aeO+TDuZPy6GtK8zsPtseWZ3PH16so741MKhlQEJEszrZVxSZwYvp47P40QVVyb5lRIVrawisexWgXzaXEGKUG6LRsx1dYTI9Ku4kkz+GgrOymtxL7oh5TwLwPnYThENApCGr6hjV42l7y1gGJ7MjO8OBt0fD69M44eDChNvlZDrxBXX7ynf06FmA4kgz+Lwsh13G0uXXUBTIdKtUFLtZ+Vknf1q2h5UbOplRmcmU8t4r6l6fxrHzC7jspHJys5w8936zPTa9rz1tEuwQn8/muh6WrmwhL9vBA8/vpjDXyTHzCujya2R61IQTVMzMjjAZruQ9bsT+R34bRoGdjebkkavPnsBxByX+QBsJzspqshZ/B9S+H94KjokHxNyut9UPWnbHlPIMdB2uOnNCwiZXsydmUVHk5vWP2/hsVw8AM/sEO46ozgOQ+lExpPa0mKm7FYM0LWkoBTetxPuXHxH8aCnBj5bi/duNo74WXgjRyxiizI7OnjD5g5SVsLecldVkn3q1nWFqZ54edxkZX/waAO75J43qwKzTYTUoHbzMDl9QxxfQqa7KTridlcFhBRjilbGYx+Wwe3V0+cJkexyoqkJFkYdQ2OCDz8x10tPv9E7G0XWDLp9GbpbT/rkOmpbD5jof3p4+Wb5EZ3b0v0+IRP5T08HqjWY29/3P7iY3y8Hvvz+LqlIP/3zL/H3s9msJS1jA/P1u7wpT3xaktECyZkUvyewYBXY2+FEUqCwZnVNDPAefiqNkMoF1rxJc+4qZ5eFwknW8uQDxvfsE4S0rCa55ieAnr8fU1Ia2ryX46VvoPW2o2YUDvor8lRPLOeHgwqTBH0VR+OLBhTz2WgMALqfClPLY53DCOA8TSz38p6aTs75Qsq9PgRBJWZkdo70sJbTrU3qevyv2Rm3g0w7CtTWEdq7DVTUv4fbRWSPO8mnoPm/S7YUQe8kaPasObrCjuSNkT+0YDaIzT4MfLiW89UPCtTWj9r1ksDM7cqIaMVZPStxI0dquucMKdpjHUVWawdSKDA6YbAZKcrOcNLWbn1XdPt3+vopi83PLMMxpd69/3M7lJ1dQnOei26+hG7ETMKqrsjEM2Fbv58CpOTHHYvXs6OgOmyNzhzlLSIwum3b30NgWpKzIzfTxiX+H/7R0D7tbAsybkkPNzh5+fGEVBTkuFi8o5g8v1rGjwU+XT0vYnBTM31FNB1WB044oTrid2P+Mnk+1/djORj9lhaN73rO16PDMO6HfyY6zcjbhLSsBw66pdVZW41/xNL5X/xizn+DaV8i95JcpFyuzJmYlLF+JdvYXSlj2QQsfbe5i9sQsXHE+WI+szuNfbzfR5dNiFg9CfF7rtnVx11O7cDkVinKdo/o1HK6toetvN/bvuaOooDrpeu43KC5PwgBFuLbGTiv3OxxxGxqb46qvt9PszWW1gt/pGtWNBYUYU4aojKWuJRC36eRIC9fWoHc2ga7hfewm+71ktJXjqaqZ3TFYnwPZkavYBTlOypME0vtldkQePy/byX3fm2Vvl5flYEtdVGZH5PvKI+WX5UVufnDeRL7xmw28s66ds75QQqc1oScqgDOxxMxg3NkYG+wwDIP61iCZHhVfQKfNGx71FwDE0AlrBv/14GZCYQOnQ+FP182mJN+Nrhv9epk1d4YwDFizpYsLji21L3R+8eAC/rSsjlc+bE2Z2ZETyTw6em6+/N6JGBLsGAV2NgaYVDY6szr6itfjwzXpQPwOF2hmba3h76Lrud8Q+uSN/jvYi6vIA5GT6eB750zk1ke2JQyOHFmdz5NvNrFqYyfHzY/NFPn76w08804Tiw8r4oJjyyQYIgasvSvMHX/fQUd3GE3Hvno2WoV2rosKdCg4KmagdzZhhAL4X3vY3i5RgML37j8gHBlPqIXNMph1r8aceHQvu6/3RMxmQDhEYN2rI34yIkRa0M3X2GBOY/EFNFo6w0wYN/pK8cz3rsj7SthcQxiGTtejN/QGVgd4IWUojctzUTnOM2gTtqxgRHVVVtJ9Jipj6SumQam/9+JPab6bvCwHJx5SyPhiN9kZKrXNZoaGVaoSXZozLt9Fhlultil2govVqPvQGbms3uSluSMkJ537sTZviFDY4MyF43hhRTNPvtlImzdMc0eIu74z3f6d7glo+AI6Fx1fyvQJWRwZKT8HKMhxcdisPF79qI38LCdlRYl/nyqK3KgqnJdgAp7Yf0mwY4SFNYPa5gCHzR59V1MGyllZTdbJ36Jn6b1gGObEliT09oZBTUU9fHYe/+8rkxMGO2ZNzCI/28mKmt5gR11zgH+vbOFfbzcxuSyDp95qYvNuH7ddMVVGgYoYr33UxqsftfKzy6faNdm6bvCbJ3fi9WncfdUMPtrcRVXJ6DtJiOaceEDUX1xknfRNgp+9T2BFvNdrb4ACwPf+k4S3fNB/s8g2WtN2epY/kKSRsUHw4+XoXW2oOYU4y6cR3rMZI9CDml+K1laH6snGc9BiCYgIkYpVxjIIwQ4jsq+6FjOQORqDHa6qefidrkiw1SC8ewOBD1+MDaxqIXxvP0bmMReP2HvIxSeU86VjB+9Ey7qKnaxfB/QPdiTKLMnNchAI6QRDOl0+jYklZi8Ph0Phjz+aTZbHgaIoTBjnYXck2GFldkSP01UUhYklHrvfnMUq5zxgcjarN3lp9UqT0v2Z9ft4yIxcfEGN599vse/bWOuz1+ytke0qSzI46oD8fvs56dAi/lPTSZs3zLTxmf3utxw0LYe/33QAecM8TUqMfvIbMcL2tAQIawaTSsdGZkcius9rLrz6XdUFR8VMlNwiDG8r2p6NBD9eTnD9a4Oa1h7vDdJ+fFXh8Nm5vPdJB2HN4O117fzqHzsBOOnQQq49dyJLV7Zw37O7+fd/Wjhj4bhBOSYxNvUENDzO3o7fL61qZc3WLl75sJVTDjPrQP/1ThOrNnr57llmA91ETXRHE8Vtvse4qo8h47CzcFZWE9r2YZLvMAh+tJzgx8t6T65694Y5IcEg+NEygsTe76iYiaN8GkZ3G6GN/4nsTie8yfw6mOARg+tewb3gTNTsgkHp8zGQHiNCjDl2sOPzB+b/8nI9Kzd0cuFxZcDoDHZYzUp97zxOeOsqwptWxN0uvO1DvDvWkLX4O3gOPnWYj9IsYXE6Bi87dFKZh2njM1k4Jy/pdgPN7LBG4nb2aGZJQFQma25m7+nA+GIPn+7oBnozO/qO051YksG6bbETWerbzACJleVo9RCJp2ZnN/98q4kj5+Rx4iFFSX8+MTa1eM3fneI8JxccW8Zba9s5dn4hr33Uxusft9nBDquZrTU1qK/DZuWSl+2gs1uzS7viURRFAh0iLvmtGGE7IpHxsVLGkoirah5+hzN2TByAw7yC7KysxvfuP9D2bKRvb4/hcNScfF5e3cafl+/h5Q9bmTUxixu+XGWPoz39iGLe/7SDh5ft4fiDC8nOcGAYBq991Mb7n3ZSkOPkilMrEs73FiNrc10PORmOzz1eWNMNvnPPZ1RXZXPDRZPwB3U+iSz6Hnu1gS8eXMiW3T7+vHwPR8/N5/Qx1AQrvMucuJJ5/NdwFJgnNq4ph+B//ynzdasouGYcDtAboEAnNo6hgNOFa+ohUdv0CYSoDvs1H66tIbT1w/7vC4kYBsEPngXArzpiTlrCtTUE1r4Cho5z/MyEjU/N7V5Fa9uNtusTMHT8DukZItKHYUQyqAYhs2Plhk627vGzaqM5iWN88egsO3BWVuOcOIfw1lUxtzsqZoKho9VvNm/QNXqWP4CjZPKYf70X5Li495qZKbfLyXSgKtDYnqKMJZKd4fWF6fLpCZs9Thjn4c217QRDuj29pW/T1cpSD6993IYvoJEZWRftiWQHzZiQicupJBw/++mObv7rQfPfq6UzJMGONNUW+fcvynNRlOvibzcdQHaGgy6fxltr27ny9PE41N7fk+IEzZFdTpXj5xfy7HvNSRuUCpGIBDtG2Kfbu0f1JJaBsq68hHauQ83MJVy/BYhtGta3t4eaGVu6M5RXYQ+fnccJBxfyz7ebUFW49pzKmBNjRVG47KQKvn//Jt5Y08bpR4zjg8+83PnkLkryXbR0hvh4Sxc3XzyJKRWJ0+jE8PP2hPnxQ1uYMM7D/353xoDKkAzDiLvd+m3dNLaHaGxv55gDC8h0q4Q1g3OPLuFf7zRxx993sKXOR0m+m2vPnTimSp5Cm/4D7kx0b4sd7Ih+3Vqvu4QBCkXFfdBiPPNOMPcXdxuFrMXfiWpebO4/sO5VgmteSlLmEoeu0bP0PoKbV2H4u9B2rbfvCq55CTADIp7Dz0bJyMFVNQ8A76M/7v840jNEpJPPWcZiGAaaDsGwzvZ684LLm2vaKc5zkuEevScT5hrCCVqk91DkYgr0ed3rWr+SlnTO8nI7Vc4+uoR/vd0UyS6J/7lkBTtaO8MEQnrCHmUTxnkwDLMspbNHQ1Egq88Vdatss7Y5YGc27mjwU5LvItPjoDjXxcbaHm56eAtXnjY+Zt1Us9O8gHDiIYW8scYMqrgTBGjE2NXiDaGqkB/JtrCyMo4/qID3PulgzZYuDpmRa5c7FSXI7AA4eUERz77XTH726H1/EqOXBDtGwCfbu1m6soWKIjfPvNfMMfMKRvUUh4GKbl4a7/p6b2+P+8Aw6Fn+AMEtq1CzCzG0MKF1r4JhJJz08HmoqsIPzp9Ifo6T0nxX3IDFzMpMplZk8OKKFk47vJhn3m2iOM/Fn66rpmZnN3f8fQffv38TV505gcWHxb+ibxgGe1qDlBW67TF0Ymj98+0megI6m3b7+HRHT8JGoVaAY3NdDz//63auObuSBbPM9GBdN1AUeGtdOx6XyvhiN/c9W8tB03JwqPCVE8soynPy5+X1ANz5reljqpltuLaG8LaPAOj6+80xWQ59mw7HBCjWvmKeWKhqv9TwgWwTvX/PvBNiRtJaAVFn+TSCW1YR3rQybnNTq/QlLl2zewT5VQdq2dQEARWzZwiMjqkNQnwuVrPOfRw9+/fXGvn3imauObsSPRI3CYaNUVnCEs1ZWU3uJXfEncCStfg7MX2Dwts+wrtrPbkX3272FFp2v5nl5XSnZZbXFadUUNsUYEeDP+E2VimKVW6SaLLF+GLz92B3cwBvT5icDEe/9Yx1gW5XY2+wY3u9315bFee7WLfNDGq8sKKFa86utL93T0uQnEwHC+fk88qHbWyu8zFnUv/PbV03+OfbTZx0aCEFOYlPhMXo1NIZojDH2e935/BZeWR5VF7/uI1DZuTS3BEi060mzZyeWpHJ7V+fyszK0V8yLEYfCXYMs4a2IP/96Da8PRqGAXMmZfHD8yeO9GENG7O3h2JemdI1whvjnMjEmfRg+TxXZxyqwpWnjU94v6IonHpYMfc9t5vHX2/ko81dfG1xOU6HwrwpOdz3vZn86h87uedftXy6s4fvnV1p93XYusfH8+8385+aTtq7whx7YAHXX1jVb7wWQLdfY0eDn1kTsyQgsg86u8P8adkezlhYTG6mk2febWbhnDzWbevmmXebYoIdbd4QedlO2rxhvn//Rk46tIjVG700tof436drefD7s3Co8KPfb8HjUtjdHOSI6jwuOr6UH/1+M69/3M7cydlkehycd0wpC2bm0eXTBjQWeahZrwU1MzdpSUdo5zrCO9b13jiAErJko6b3Zpt421uiT6s8B59qH6vh7yKw8pm9ywIB0DX0PZtib7PeawAM3XxfWfPSiNX0CzE49n30rLcnzFNvN+IL6Pxx6R7A7Hn13icd9knuaBZvIhyY7yGOksn43nqU8PaPscplA+teNQOdViA1HMT31l/JXHRpWgU8HKrCTy6djD/Yv2+aJTczttwkUf8DK+hV1xKgs0frV8ICZrmTqmI3KQ2GdXY1+TkiMkmjONc8vSgtcPHO+na+s2SCnXGypzVARZGb6irzc/TTHd1xgx2b63z8adkeegIal59ckfpJEMNuc10P733SyTlfGBczsQfMDKKi3P5BKrdL5Qtz83lnfQdXn63T6g1RnJ86mDUax2KLsUGCHcMkENJ5/v1m/v2fFsJhgwe/Pwtvj8aUioyE9ZXpKGFvj3iiUs+tev3g2pdB1/rV8w+W4yOlLn95uR6PS+XUw3szOApyXPz8a1P568v1/OONRuZOzuakQ4vo7A7zwwfM+tMjq/PIylBZurKVFm8ITTO48LgyewHw6Cv1PPVWI4GQweTyDA6alkMobDBnUjZfmJu/X/0u7I2WzhA/+8s2vnJiOZ9s72b5qlbeWtuOy6mgKvD1U8ezfFULT77ZxJV3beCbp49nxoRMrrhzA6ceVoTHrdLSGebx1xsBOH9RCf982yxLyXCrbN3jw+VQCIYNFh1YwOTyTH7+1anc8n9bOXpub/Pb0dJbx//hi/iWPxCTCRGvx4X3bzdGysYiFBUcTrvkI5VEJxZ7u83ePpZ75sL+pS+qA+f0w1CzC1E8WSkDIo6KmXgOOpmelx+Kfb/RNXqW3W9nlUVnmUjWhxgTIgG8fRk9++x7zfgCOuPyXexuNsfeHz3XDHaM9syOVJyV1WQu+greHWvN90ZVJRzp2xMtvH0N3h3ryDrlqrQKejpUJWkDR+tktK4lktmRIDsxJ9NBfrazN7Mjq/+pgsupMntiFi+tauW8Y0poaA+i6eYVeIDTjxzHzIlZjC/28N9/3c6aLV4OnWmug+pbg0wfn0lhrovyIjcbdvagaQaqSkxpqJWl8u76jkEPdoQ1I2G5j0iuozvMrY9so8un2VN7Vn3WybeXTCCsGRw4NQeAVm/i0cPHH1TIy6vbWLmhk5bOEMVxgiJCDBYJdgyT+56t5eXVbcyemMUPzp9I1RifvrKvUtbwW4s3QwcMgmteQmveiVZbE7tgiZywhOu3DOoJSnaGgz/812xqdnbjdqr9ItUOVeHyk8tZvdHL319r4IsHFbJ8VSuBkM79185kSnkmhmGQk+ngzTXtKIrCL/62nesuqEJV4W+vNvCFA/I5dGYu/3yrkWUftKIo8O8VLazYUMCNF00CzA+J/9R0kp2hcvisPLsBWDpo84ZoaAsyo9LMbNF1g8dea2ByeQZHzy3gw01enn2vmab2IGcsHMfJhxbx2GsNbNrt455/7sIf0lkwM5fOnjCaDjd8eRITxnm45IRy8rKcvLiihXufqeXEQ4rwB3Wefb+ZLLeDI6rzmDUxi46uMFecUkFhjou/vFxPIKRz8RfNgNTb69o5bJZ59aB6UjZ/v+UAXKNoQRSurcG/6nlCn77Z/05do2fZfWhtezB8XkKbV8YGOlDsnhuj/YQ+XulL3+N2z1wYPxNEUWIaIztKJve/umvodlZZ9GSY4JqXcM8/eUw8R2I/ZpWx7GWwIxjWefY9MxNuwcw8fvdMLdVVWSyYmcusiVkcMmPsXzl1VlaTdfr36XnhLtDC6M07e+/sk+nVs+z+mEam0dly6RgAzXCruJ2KPSI2WSnmhHFudjcH8AV0CnPjnypcdWYl1963kYf+XWef4E4pN9e2B07N4cCpOQTDOlkelTfWtHPozDw0zaChLcgx8woAmFOVzbufdHDez9Zz4fGlXHR8mb3/7ZFgx65Iec7eXGzYXNfDljofixf0Lzn+aLOXWx/ZxgPXzhrzAb6B2FzXw7Y9fk46dHAawX60yctnu3o4fFYuJxxcSEWRm988tctuOvvbq2cwY0IWLd4Q1XEydsD8/SjKdfLaR220doapnjTy2bIifUmwYxi8+0kHL69u48vHl0oqHolr+K1U/MC6Vwl+tNTcWNfMiQrxJEhLt7JAjHAAZ8UsjJBvr8perLKVRBRF4ZITy/jZX7bz5FuNLF3ZwoFTs5lSnmnff8Up47nilPF0+TRuengLv/z7DsDsUv7jL1fhcvZmjei6wZ9f2sOTbzZx3jElTKvI5Cd/3saWOh8A5YVuvnPmBA6dkWuXzQwHwzDYUuejvMgTd1G0dmuXGbSYkElbl5muWFXqSdi0c+3WLv68fA81O3sAs4TrilPGs3JDJ0+82UiGWyUUNrjziZ0U5jopyHHxu6dr+fd/mtnR4OeQGTl8vKULXYevnVJhL6qsx/O4VM5fVEpVaQa3PrKNx19vYPbELHY1+enya5z9hXEcNK13MX/uMSWctKCQmh09HDozF4eq9KsHdTtHJtMm3qIbdxbBlU/HHe9sMwy7h0U/Cqj5pWNq4Z4sa6RvJkiikh5rO2f5tJia/rh0LWGpy2A3OLT2h8OF3lILipJWJ1ZiCBn7VsayeqOXLp/G6UeMY86kLF7/uI1FBxaQm+XknqtmDMGBjgxHUf9yVeeUQ3DPPir2PcDQ7ZIWAO9jN0E4djB2cO0r5F7yy7R5XeZmOeyr8cmyQKpKM3hnXQcet5IwyDBtfCZfOraUx19vZFdTAI9LYXyf4IHbqbLowAJe/7iNK08bT09AQ9Ohosi84n/ozFxeX9NGbqaD5R+08uXjSu3P9B31ZsPT5s4Q767vYFJZBmHN7K+VqgT4sVcb+E9NJwtm5vUbafr46w2EwgYbdnbvF8GOf7zeyPufdnD03PykF8403WDzbl9Mme6nO7ppbAsyqSzD7sfy6c5uMtwqP7l0ir0mnViawa5GP79+cifvrDP/rTq7NYoSBMocqsIXDy7kX+80oQBH5+XH3U6IwSDBjiH22a4e7npyJ9PHZ3LJCeUjfTijSrITmeC6V/stOkxK5OpM/yyP4JZVoBuEt3xg3x9a/zrQP8X/8zpidh4HTcvhkZfMhpVXnh6/F0hOpoM7vz2dt9a2s3JDJ19dXIGrzwm0qipceFwZyz9o5fcv7OaAydlsqfPxw/MnUpzn4nfP1HLrI9vIz3byhbn5HDI9h8nlmUwY5+HjLV7+8O86Lj+5ggMmZ+PtCVNW6O4XcGjtDPG31xo48ZBC8rKcPPteE3XNQQ6cms2Xju1dXGiawa2PbENRoCeg8emOHjLcKmccWczlJ1fYaZ+BkM4vHt1uj6WzFOe5OOnQQs49uiQmK6auJcCND2+hKNfF106pINOt8shLe/jR780rAV+Ym8+qzzr51T92Mr7Yze+umUmmW+Wd9R387ulanA6FH55fxcoNnTR3hOxU2XgOm5XLjAmZbNrt48LjS+nx66za2Mn8qf0DWLmZTg6fnZdwX4MtWZ8N6z7d20rww38nD2pYVAeu6mPMTA8jQVmY9bvgcA24fGWsGUgpjVXTP6DJMJFJMFrbHgx/D1r7HrSd6+wSuugJMH17CgXWvYre3Za0RCbw0VK7YWK0dDuxEkPDMPYusyMU1nE6FN5c005etsNsvOxQ+PW3pg/hUY6c0M51sTeojpjJLDGNTLevwbtzPY6y6fHXHFqo32QXy1ic8DJhnIeuXT5OOLgg6Yn+kdX5LPuglS5/8gyQC48r47WP2vhsVw8zKzPjBiHO/kIJyz5o5d8rW5gdOZG2puEdf1ABR1Tn8d4nHdz11C4+29XD7CozG2B7g5+DpuVQ3xbkiTcbWLeti8929XDQ9Bx+cukUe/+GYXD3P3cxb0oOJx1ahK4brNvWjWHA2+vaOfsLJfa2m3f3sHZrt73//cGm3T40HWp29iTN3nrm3Sb++OIerjpzAksWjuP595u5/7ndgHkR8HdXz2ByeSYbdvYwqzIr5uLbtPGZTBufyUurW3l3fTunHWFezOsbaIp2+hHF/PPtJnQj+XZCfF4S7BhCm3f3cMuftpKX7eQnl02W+sABSljqoqhknXJVyrT0uCInL8CgBDwUReG2K6byzvoONu3uYWF14qi026ly4iFFSWfJZ2c4uOKUCv736Vo+3dHDgpm5nHhIIYqi8OD3Z/HBZ528vbadVz9s48UVLQD88PyJPPFmI7VNATtAYRjmFZNZE7OYPy2HxQuKaGwPceMft7CnNciylS2oqoJDhZICN/+33EtDe4irlkzA4VB479MOVm/yUlpgfvB88/TxbN7t46m3mti82wzAlBS4eXNNO16fxvfPq8TlUCnKc9LQFuTd9R38441GPtvVw21XTLWDKGu3mhkZt18xlYmREq5FBxbwyfZu/EGdRQcW8Pz7zTzyUj3XXzjJ7sp9zLwC5k3JxtujUZzniumhkuzf5ttLJvDqh20cNivPvoIwXKwTXoidOoLqIPjhi/36bLgPOxutfgvazjWJAxZ9RY2BdVZWE6iaGz9rweEi6+RvJWxgur9JNhlG727rMxEmQZZMnwkwnsPPNkfjtuxGq/005t83pkTm4+U4phwCWghtx5r4BziA5rFC2O8TSaax7GkN4FAVMlwq1963ieJ8F5t3+zjhkMJhzRAcCa6qefidbrNXT2RKlD0pzmpk+vZjhLd9aH6DrqHt+Szh/sLbPsS7Yw1Zi79jrj/Wvmy+ZzdsMSfIJQmAwugKivz8q1PRDVJOADxkRg45GQ66/Jo9xSWeDLfKN04bz+2P7bCzW/uaVJbBgpm5PP9+M1meUgAqis3MDkUx+4wcdUA+v326ljfWtDO7KhuvL0xLZ4hJZRlccmIZ/3yribXbuigvcrOippP2rpA9oeXTHT28vLqN1z9uZ1JZBqoKXT4NVTFHKkcHO555t5lMt0pBjpPt9X46usO8vLqVMxeOixl/q+sGhgEOh1lqG9aNfpmeYc3AEbnphf+0oBsGx8wriNuUM5mhHL3b2R2moc38JFq/rStpsOPttR0APPjCbt5Z387ard0cWZ3HJSeWcfOftnLPP2u5/RtT2bLHxwXHlsbdxxfm5nPvM7v5cJMXIOlzUV7k4bCZuaz8zJu2wY7BfO1Hry0lC3TvSLBjEGys7eHFFS0EwzozJmRx5lHj2Fbv46aHt5KVoXLHN6ZRkh+/SY+IL1XN/oDT0mMY9Cy9l+CmD1Bzi8yTnD2bMYI9qAXl6G31KO4MnONnxj057PumpaoKiw4sYNGBBYPyMy8+rJjDZ+exZmsXB0/PjSnPOHpuAUfPLcAfNDueP/TvOu56ahcAN108ifrWIMGwTk6mgw83dfHJ9m7eWNPOzgY/76zvwBfQ+cXXprJiQweBkMHlJ5VTmOvk/5ab5TO7mwJcd2EVz7zbREWRmz/81+yYKzQHTc/ht0/XcsWdGzjp0EJqdvYwqSyDkw8tiskiWbygmBf+08x9z+7m5dVtnLzADPB8uqObvCwHlSW9V5Lys50cdUBvkOico0s47Yjifk1aC3Jcez12bs6k7Ljd3YdSuLaGwMfLzaykyAlvvNykGLpGcEWCspNE4mQpWQv4dK43H0yJJsOYGRf3DTzoFBX4SMnQ0bauSr7NXjSPFfsx6/czQRmLYRjc9PBWOrrDTC7LoLkzRKs3RDBscOwgfV6NZtYFk2STpDKPuRjvjjVx1g8KzplHoGYXEq79FL3JLEG1MkiB/ll3fQKg0e/P/lXP43v5IXPsbeQ+67060Roj2YStz2ugJ9UupzkxY/mq1rjTWKIdPTefy08uZ8GsxCfS5y0q4cY/buWx1xpwOpR+J7fZGQ4Om5XLW2vbufzkcrs56aSyDCqKPFwdGV27rd7HVf+7kXfWdXDGwnEALF/VQqZbJTvTwR1/38EJkYsbZxw5jufeb6a+NUB5kYdgSOe9Tzo4dn4BgZDO+m3dPPtuE39/vZEtdT6uv7DKXs/8/fUG/vV2Exd9sYxXP2qjx6/xP1dOszNSDMPg+oc2EwwbHDE7j8deawDgz8vr+Z8rp8UdkWoYBq9/bDZWt3qWrKjp5LbHtvO/351hB4ueequR3c0BxuW5OG9RCRnufe/Ztmm3WQ7tciqs296NYRiENaNfhnFTe5DPanv48vGlbN3jp70rxLlHl3D54nLcTpXvnDGB//nHTn752A50Haqr4q+vFs7J575nd/Pkm2Yz+FRBjHOOKWHVRu+Y62PY96JWvEzd6PWgX1FxH34Oamb8jFD/hy+ie5txFFTgHD8j7v68j/7Yfr8KfvwSzukLUHOK+q3zUh3b3v4s6UCCHZ+Dphs8+PxuXvhPC1kes5nl6x+38+LKFupaAhTmuLjjymkJuxGL1JKlpydMS+87tWHFv2JOXsKbVwCJT0SDa14C+ly1bdtj9g7RNfyKimvG4bimLYh5U4jXZyHZG0e8KG1hrovj5ifOQshwq8yYkMVNF03i2vs2UVVqdtKPDjicdVQJum7wq3/s5Ol3m8nPdnLHldOYNj6TQ2fGLkauOGU8E0syuPeZWq74dQ3BsMG3zxjfLxX1pEOLOHBqDk++2cjyVa2ENYPvnjUhbn+O0w4v5s217fzv07t4/eM2rjpzAp/u6KF6UnbCfh6WfZ1GM5hv1okyM+J9rXe3oXhyAJ3QutdJOWFob1i/f4Ee+zGT/VzRr5X0r0IeGtYJStwgakzz5EHS599YglNiQCK/m4mmsWyu81HfGiQnw0HNzh6+efp45kzK5sPNXuZOHt4g8EhJVdrmrKwma/F3Yl/rkebGmUeeb3+mR59gDOi1b5XVbvoAva0OvWVX7H1L77Ubpfr7rVWe7pf5F6930HCdmBw7v4Dlq1oTNii1KIrCl6Mai8Zz0LRcTjrUnMBRWeKJW+5y7tElXP+HLTzw/G67b8Tk8tiT4MllGVSVenh9TRtVZRn4gzpvre3g+IMKOOHgQn78hy089loDE4rdnHtMCS+saObBF+r4f1+ZzIebvPiCOkfPLWBLXQ+vf9zOW2vbyXCbDVSnVGRywbGl6LrB8g9aCYYNHl66h8JcJ+GwwY//sIW7vjOD4jwXH23uomZnD6oCW+p8LJyTx6UnlvPTv2zjv/+6jXuumsm4qHGq/qDOLx/bzsrPvDgdClPKM6ks8fDiyhZCYYPHX2vgxosn88n2bh5euoe8LAden8arH7Xx7SUTGF/s5pUP21iycFy/AMK6bV089VYTeVkOjptfwPrt3RxZnc+siVlsrjM/W754UCGvfdzGj36/Ga9P456rZtgZtGD2FgQ48ZCiuOVNx84v4MPNXl5e3QZglyP1VZTr4sLjSu3Jd4l6dkT/Xjx569yYYxlsA8musF9XWhjH+JloDVuB2NcYQGDty4TrN6NbGbv0nktY5wZq0YR+r2UM3b6w5Y/63Nda62IyPbUdawmuWR67nb+L0Mb/xK5JDI3wpsi5zMcv4ZxxWOR2CG9e2e+CW99gS+/PsgW9fnP/n2WIJl6OFMUwBnoJa+g8//zzPPDAA4TDYS6//HIuueSSlN/j9XrZuHEjM2fOJDd3+DuId/s17v7nLt5d38E5XxjHJSeWk53h4NUPW/nLy/UsnJPPhceVUijjlIZFsvSuwEdL9zIDZC+pDpyzv0C45p3EiyFFxX3IaRAKoHW1QDhkBk/s2msHjsnzceSX4axIfYKtZheij5sKTVtRlQTb6fCefjAHHLnAzqhIdCLvrVrEo58UsK3ex6++Od1uXBZvYdVdXM3qzvF88eBClPrP4gZ4etrbeat1Io9+UkBZoZstdT6+dkqFnfqYrLfBgL/esxmtsxn0MJo1arDPv0vfYEG4fgvoOkpuMXpLLXqgC0dOsf3hpntbCG9ZDcYQ/a5EjstVfQyhmrfjnlB7jjgnYTq0GB6JpjIA8SfAWCInL0DM77Xe3UZ48wcxAdmhnvqyt5+RqT6Ha2pquPnmm+nu7mbBggX87Gc/w+lMv+slY2E94nvjL/jff5LCG5+Pe/+fl+/hybca+dOPqqlt8nPIjNyUgeb9VapsikT9dYChCYD2fxCcM44AhX49yaKPw33oGfb0rWTrhr4BkmQXaZwT57LOP5EDp+bYZdifJ5XeH9S49r5NTCnP5IbI5Lm+/vLSHv7+eiOqCplulSd/Mrff7+7fX2vgLy/Xx9x293emM7sqm7+9Us+jrzZw2uHFXHNOJc+918wDz+/mrKPG0eXTWLGhk7/ffACrN3r56V+2AfC1xeVsrvPx7icd3Pmt6eg6/Oj3m/nRlyaSnelgTlU2De1Brvv9Zg6ansutl07mlv/byrZ6P/99+RTeWtfORceXkelxsG2Pjx8+uJnp4zO54xvT7JKxP75Yxz/fbuKyk8p58q1G5k3O5gfnT+SSX35KToYZ2Hjw+7P4w7/r2LTbx5+vn83GWnMCnTU9B+C4+QX8+Mu9z92z7zXx4PN1FOY46QloBELmKd2EYjf3f38Wv3p8J9vqfVx52nh+9tftZuWbAUdUmyW+mR6VMxeO41dP7MShKjxw7ayE/37BsM7Nf9qKP6Dzu2tmJv23/mizly11Ps47pmSf3ntSfQb3/X3t+zse09j9g2fMCVaqimPiXNScQhzl09Fbd4MBRshP6JPXUxyR9TOM+CnzIFAY0M+hOsj9yv8MyhplpNcjIx7saGho4KKLLuJf//oXbrebL3/5y9x1111Mn568cdZIBjtWb+zkt0/X0twR4hunjeeco0tSf5MYUdYHdMrGhOlGceCYNA81Ox9UF6F1rxL3TU5x4JgyH0deKWrReMJ1n2F0NKHt2dR/e0XFfcjpaM270HbGCTJEbVc7/kRqtrWjAId+YT6l/m1oTdtiouJpR1Fxzjg8bhAn1SJTruyPHXv77zfc9bZ78xk5kM/hM844g1/84hccdNBB3HTTTcydO5eLL754SH+G4Taa1iPJMswCH76I1rCNrK/8ireayukJaJx2eDEGZpPpa363kdJCN7d/fdqgHMv+rnvpvb0T4lBwVMzAUT5tYAHQ0UpVcUw7DG1znOCJRVFxzT8Z9DB6VysE/Wi7N0RdpFFxVM01L9JMmGX+jhqgFlWg1W8BDNTiKoyOBnA4zd/dui3Q04YjJ/L5uMfczlE+Da1hK4YBK1vGUejbybgCF6UzZvc7qQ12tLK5zUPmxBnkde1AMwzGz64mXL8Fw4DVbeOYldlAbqYDR9lU1q5Yx44GP9u08Rxd1sK88hABZz5/Wp3JZEcdiw4sIKtyBm++uhoM8OVPRm3ZxkmHFJIxYbr9+Gu8pdR+WsPUfD/bOjIonz2bQ/KbYo4NYFOwgo0fraeswM12fTzTXHXsaQmSVTWD4ypa2brHx9JtBczPbUTxtTF79gSeqsllqqOOkGYwfvZsDorsVymdys71NfhDGvWOSjp3bOKYufk4y6fRsmUjO7fvIaOgmIOPmk9oz2bau8J0506mZvU6po3P5D/N45if28C8KTks3ZbPgqImuno0XtpZyAz3HrKNTjr0XHYrEzhzRidlhe6kF5mCe8zn2DM+cYAh7tcGqOMq0eo2gaHjKJuC1rILo8eLmluMs2K6+bugh8HhIvjxsji/l2rkPH0og4uDLc5Qhc/BUTETJbco9uLJUFEUMo69jMyjLvjcuxrp9ciIBzuefvppPvjgA26//XYA7rvvPgzD4Oqrr076fUOxuFi/rYvn32+mo9v8BVJVCIUNdjT4URQYl+9CN2B7vZ8JxW7+60tVCWdIi9FpICUKiicr/qJFUSPlMOkQ2R0+RuR/+8WFxTRL/RNj1958Rqb6HN69ezeXX345r7zyCgCrVq3it7/9LX/5y1+G9ocYZgNZj3R2dtLZ2RnzfcFgkLa2tkFbj4Rra+j4y49RSL6YDePkF93fYJNexfhiN21dYXwBc1F99dkTOP2IcZ/7WESkXv6xm0ALg8NJ7sW3xw1Wxr2oEsnisk/U175i7kdRAKV/FmGyzD+xz6x1CErUNfq+f4/eOOr2VPtJ9Xjxtu+7n+hVZdL99l1+pjrOBNtEH9pAHlf0kaIEzdomukfPQDNCE56DOFz2tLbo7Oh+gY++x5YqCBtve0M3Hy/Be93estYjeXl5ZGbGNjLOy8sjL693KuJQrEdGPAe1sbGRkpLezIjS0lLWrl0bs02ixcVg290cYGu9n7wsB4qioIcNVFXhC3PzURWF5o4gYd3gxEMqWLJwXL/OzGL0S9SYsO/X7pkLE6bQWcGSuG8ifUonkr7RRL3BDUuUdoQo9v+G0N6+uQ9wXwPp2REvNViI0aK+vp6Ojo6Y2/ouLlJ9Dve9v6SkhIaGhiE86pExkPXII488wr333htz28yZM/npT3/Kxo0bB+U4Cra+RSFazElYvK+dhLn2oM20Tx0PhPvsZQerV+8YlOMR4Dn0MjJbt+MrmkygoQcaVsffsHQhnsMmkLv7Ywyga8JBBAqqQAdKS/EsmGDvB7C3C+ZV4Aj5zP0XVOHJmU7u7o/J2f0hStRJlKGo9IybiebJQXd6KNjx/j5dNY46B094+SZ6G/vx42wDiX9HE329L9/zeb5fAYy+J/1Kgu9JdDux65mUj69Evo6zPVG3Rx1O6v0m2FfSx4+zTbzHTLqvJF/vy/cM5Pvj/V4OsACjHwMlsv/E322g0FM6C9+4GXg692BA1GvMiLz2ZqB5cnpf1xGewwvjv5b1UmjoAc808IDnsEIyW7ejuTLtx+i7L0iyXfR7T+lCc9vCueTu/hg10BX/2CL7UkK+gf0ske1Tvtftg69+9as0NzfH3Hb11VdzzTXX2H8fivXIiAc7dF2PqecyDKNffddwLC4Axqnw7WMHsmU769bsSr2ZGNs80+wFCmC+YYH9BgOxb0j2m1t+8jeteG9I1puV9UZpvbnF+9r6/oFsl9W8MWahBP3f0BNtBwNbWBmKQseko3CEA30+HBIvwKz9AgP6WVI9F4nerKM/KAb6XMbsK/rfP9HX1t89kQ+1QfxgEOLzGsjiItXn8EA+p9PBQH7Oyy+/nHPOOSfmtkHP7CjLwrv1DTMDgD4nSNFfO1xMWngK0yTAOgwO3cttz0lyX7Rk253Tr7+VZ94JFCeY4DKQwHz0xQDrd0lJcpGm38lxgos0CX9HE3y9L9+TTt8/mo5ltH5/9O+l3t1m9lPTwiiqGrcfW6KSmpgGowkyu61tihNkbFkNTuPdb0r2mu+73UAM1vtN7L4G/rMMLiuz489//nPczI5oQ7EeGfFgR3l5OatW9Y7ja2pqojT6JILhWVwIsW8G8qYw0G0G8ka5dxJ1bu/7JpeovGcgC6u+2yTaLtl+B9/gv1kLMZbszeIi1edweXk5TU1N9t+bm5v7fU6ng4GsR/pmxYD5XLe1tQ3acTgrq8m95I6UJZfS4yf9DWSqTLwpXIm+htjM1UQZiX2zW6ODLTHjNQc4uSz668/VmDwNvn80Hcto/f54v5fJpqr0/R1PNJEuUWZ3Mqleg2PJSP8s5eXlKc/Zh2I9MuLBjqOOOorf/e53tLa2kpmZyUsvvcTPf/7zmG2GY3EhRDoa6BtbsvKeRNsl+6AYyAJMCDH0BrK4SPU5PGHCBDweD6tXr+bQQw/l2WefZdGiRUN96MNuIOuR4TLQkksh9tZA1gUD+awf6O9ost/dvf2edPr+0XQso+374xnpE3UxPIZiPTLiwY6ysjJ+8IMfcNlllxEKhTj//PM58MADR/qwhBBCiP1Cos/hK6+8ku9973vMmzePO++8k1tuuYWuri4OOOAALrvsspE+7EEn6xEhhBBi5AzFemTEp7Hsq5EcPSuEEEKMZvIZOXzkuRZCCCHiG+nPSBknIoQQQgghhBBCiLQiwQ4hhBBCCCGEEEKkFQl2CCGEEEIIIYQQIq1IsEMIIYQQQgghhBBpRYIdQgghhBBCCCGESCsS7BBCCCGEEEIIIURakWCHEEIIIYQQQggh0ooEO4QQQgghhBBCCJFWnCN9APtK13UAenp6RvhIhBBCiNHF+my0PivF0JH1iBBCCBHfSK9Hxmyww+/3A1BbWzvCRyKEEEKMTn6/n/z8/JE+jLQm6xEhhBAiuZFaj4zZYEdxcTEAGRkZqKpU4wghhBAWXdfx+/32Z6UYOrIeEUIIIeIb6fWIYhiGMSKPLIQQQgghhBBCCDEE5BKEEEIIIYQQQggh0ooEO4QQQgghhBBCCJFWJNghhBBCCCGEEEKItCLBDiGEEEIIIYQQQqQVCXYIIYQQQgghhBAirUiwQwghhBBCCCGEEGlFgh1CCCGEEEIIIYRIKxLsEEIIIYQQQgghRFqRYIcQQgghhBBCCCHSigQ7hBBCCCGEEEIIkVYk2CGEEEIIIYQQQoi0IsEOIYQQQgghhBBCpBUJdgghhBBCCCGEECKtSLBDCCGEEEIIIYQQaUWCHUIIIYQQQgghhEgrEuwQQgghhBBCCCFEWpFghxBCCCGEEEIIIdKKBDuEEEIIIYQQQgiRViTYIYQQQgghhBBCiLQiwQ4hhBBCCCGEEEKkFQl2CCGEEEIIIYQQIq1IsEMIIYQQQgghhBBpRYIdQgghhBBCCCGESCsS7BBCCCGEEEIIIURakWCHEEIIIYQQQggh0ooEO4QQQgghhBBCCJFWJNghhBBCCCGEEEKItCLBDiGEEEIIIYQQQqQVCXYIIYQQQgghhBAirUiwQwghhBBCCCGEEGlFgh1CCCGEEEIIIYRIKxLsEEIIIYQQQgghRFqRYIcQQgghhBBCCCHSigQ7hBBCCCGEEEIIkVYk2CGEEEIIIYQQQoi0IsEOIYQQQgghhBBCpBUJdgghhBBCCCGEECKtSLBDCCGEEEIIIYQQaUWCHUIIIYQQQgghhEgrEuwQQgghhBBCCCFEWpFghxBCCCGEEEIIIdKKBDuEEEIIIYQQQgiRViTYIYQQQgghhBBCiLQiwQ4hhBBCCCGEEEKkFQl2CCGEEEIIIYQQIq1IsEMIIYQQQgghhBBpRYIdQgghhBBCCCGESCsS7BBCCCGEEEIIIURakWCHEEIIIYQQQggh0ooEO4QQQgghhBBCCJFWJNghhBBCCCGEEEKItCLBDiGEEEIIIYQQQqQVCXYIIYQQQgghhBAirUiwQwghhBBCCCGEEGlFgh1CCCGEEEIIIYRIKxLsEEIIIYQQQgghRFqRYIcQQgghhBBCCCHSigQ7hBBCCCGEEEIIkVYk2CGEEEIIIYQQQoi0IsEOIYQQQgghhBBCpBUJdgghhBBCCCGEECKtSLBDCCGEEEIIIYQQaUWCHUIIIYQQQgghhEgrEuwQQgghhBBCCCFEWnGO9AHsK13X6e7uxuVyoSjKSB+OEEIIMWoYhkEoFCI7OxtVlesaQ0nWI0IIIUR8I70eGbPBju7ubjZu3DjShyGEEEKMWjNnziQ3N3ekDyOtyXpECCGESG6k1iNjNtjhcrkA84lzu92Dss/169czd+7cQdlXOpLnJzV5jlKT5yg1eY5Sk+couWAwyMaNG+3PSjF0Bns9Ir/bqclzlJo8R6nJc5SaPEepyXOU3Pr16wFGbD0yZoMdVqqo2+3G4/EM2n4Hc1/pSJ6f1OQ5Sk2eo9TkOUpNnqPUpKxi6A3FekR+t1OT5yg1eY5Sk+coNXmOUpPnKLWRWo9IIa8QQgghhBBCCCHSigQ7hBBCCCGEEEIIkVbGbBmLEEKI9BMKhaitrcXv9yfdzul0UlNTM0xHNXplZGRQWVkpvTmEEEKIKANdT3xesh4xjdb1iAQ7hBBCjBq1tbXk5uYyefLkpPWd3d3dZGdnD+ORjT6GYdDS0kJtbS1TpkwZ6cMRQgghRo2Bric+L1mPjO71iJSxCCGEGDX8fj/FxcXSWHMAFEWhuLh4yK9aCSGEEGONrCeGz2hej0iwQwghxKgiC5OBk+dKCCGEiE8+I4fPaH2uJdghhBBCCCGEEEKItCLBDiGEECKBG2+8kRNOOIEXXngh4f27d+9Ouo9LL72UFStWsG7dOm6++WYAnnjiiYT7tLz33nssWbKEk08+mbvvvnvffgAhhBBCiP2UBDuEEEKIBJ5++mmWLl3KGWecEff+FStWYBjGgPY1b948brvtNgA+/PBDgsFgwm39fj833XQT999/Py+++CLr16/nzTff3PsfQAghhBCjyg033MC//vUvvvjFL8a9/4tf/CK1tbXDfFTpSYIdQgghxryaHd38440GanZ0D9o+v/3tb2MYBl/60pe49dZbueCCC1i8eDGXXnopzc3NPPTQQzQ2NvLNb36TtrY2li5dygUXXMCZZ57JKaecwocffhizvxUrVnDppZfy3nvv8dprr/Hb3/6WV155hSOOOIKuri7A7B5/2mmnsXbtWiZNmsTEiRNxOp0sWbKEZcuWDdrPJoQQQoj+hmI9IUaOjJ4dIuHaGkI71+GqmoezsnqkD0cIIcacVz5s5aVVrXHv0zQNh8MBQLdfY1u9H8MARYEp5RlkZziS7vvkBUWceEhR0m0efPBBZs2axW9/+1vuvPNOHn/8cVRV5frrr+e5557jm9/8Jo8//jgPPfQQ+fn5PP744zz44IMUFRXx1FNP8dBDD/Hggw/22+9RRx3FF7/4RQ4//HBOPPFEXn75ZZYtW8b555/PM888w9lnn01jYyMlJSX295SWltLQ0JDqKRNCCLEfkPOMvZNsPRFtX9YTx87L5vSFyUfPGobBHXfcwRtvvEFpaSmapnH44YcTCAS49tpr2bZtG1VVVdx2223k5+enPE7DMLjzzjt55ZVXcDgcXHjhhVx++eWsXLmSu+++G7/fT2dnJzfeeCMnnngizz//PH/84x9xOBxUVlby61//Go/Hw0MPPcTSpUvRNI2jjz6a6667ju7ubn74wx/S3NwMwHe/+11OOOGElMc0WkmwYwiEa2vwPvpj0DX8Tje5F98ub0RCCDFEuv0aViWJYZh/T7U42RuTJk3ixz/+MU8++STbtm3j448/pqqqKmYbVVW57777eO2119i2bRsrV65EVQeWPHneeefxu9/9jvPPP58XXniBRx55hBUrVsR0NjcMY9R2OhdCCDF85Dxj6AzVemL58uV8+umnvPDCC3i9Xs4880wAWlpauPTSS1mwYAH/8z//w3333cdNN92Ucn/Lli3jww8/5PnnnycUCnHxxRdz2mmn8eijj/KLX/yCadOm8f7773P77bdz4okncs899/DEE09QXFzM//zP/7B161aamppYv349Tz31FIqicN111/Hcc8+h6zoTJkzgoYceoqamhueee06CHSJWaOc60DXzL1qY0M518iYkhBB76cRDEmdfdHd3k51tXkmp2dHNjQ9vIRQ2cDkVfnzhJKonJb/KsjfWr1/Pf/3Xf/HVr36VxYsXo6pqvz4d3d3dnH/++Zx55pkcdthhzJo1i7/97W8D2v9hhx1GY2MjL730EpWVlZSVlVFeXk5TU5O9TVNTE6WlpYP2MwkhhBib5Dxj7yVbT0Tbl/VEd3fqcpeVK1dy8skn43K5KCoqYtGiRQBMmTKFBQsWAHDWWWdxww03DOCngQ8++IBTTz0Vt9uN2+3m2WefBeDXv/41r7/+OsuWLWPNmjX2sR1//PFcdNFFnHjiiSxevJjq6mqee+451q5dy7nnnguYvcLGjx/Peeedx1133UVDQwPHHXcc3/3udwd0TKOVBDuGgKtqHn5FMUOCDieuqnkjfUhCCJG2qidl88uvT2Ptti4OnJIzqIEOMBcVhx9+OBdddBFtbW288cYbnHzyyQA4HA40TWP79u0oimL3+bj++uvRNC3hPq3vA3M2/dlnn80vfvELe6Ezf/58tm3bxo4dO6isrOSFF17gvPPOG9SfSwghxNjjqpqHHwWQ84zBNlTrCUVRYi6SOJ3OmD/BzOCM/nsyTqczJtuztraWoqIiLr30Uo444giOOOIIFi5cyI9+9CMAbrnlFjZs2MCbb77Jddddx9VXX42maVx++eV87WtfA6CzsxOHw0F2djZLly7l7bff5vXXX+dPf/oTL7744oCzVUebsXnUo5yzshq1eCJKTpGklgkhxDConpTNhceVDXqgA+C0005jw4YNLFmyhMsuu4y5c+faXdKPO+44vvnNb5Kbm0t1dTWnnnoqp59+OoWFhdTV1SXc51FHHcWDDz5oNx09/fTT8fl8nHjiiQB4PB7uuOMOrrnmGk477TSmTp3KKaecMug/mxBCiLHFWVmNWjQeNb9MzjOGwFCsJxYuXMjSpUsJBoN0dHTw9ttvA7BlyxY+/fRTAP75z39y1FFHDWh/hx12GC+99BKhUAifz8c3vvENNm/ezPbt27n22mtZtGgRr776KpqmEQ6HOfnkkyksLORb3/oWZ511FjU1NRx55JE8++yzdHd3Ew6H+e53v8vy5ct59NFH+d3vfsepp57KrbfeSmtrq91EfSySzI4horg8KIoqb0BCCDGGffbZZwA8+eSTce+/+eabufnmmwG46667Yu675ZZbAPjrX/9q33bEEUcAZnDj9NNPB0DXdd5++23OOuss3G63ve3ChQt57rnnBuknEUIIkS4UVwZKdqacZ4wRJ554IuvWreOMM85g3LhxTJs2DYCqqiruu+8+du7cycyZM/nBD34woP2ddNJJrF+/nnPPPRdd17nssss48MADOf/88zn99NNxOp0ceeSR+P1+gsEg3/ve97jiiivweDwUFxdzxx13UFxczIYNG7jgggvQNI1jjjmGc845x25QumTJEhwOB9dddx15eXlD+fQMKQl2DBVdw9ATpzALIYQQAFdffTV79uzh4YcfHulDGfW6urr48pe/zIMPPkhlZaV9+6OPPsry5cvtwFJNTQ0333wz3d3dLFiwgJ/97Gc4nU7q6uq47rrraGlpYcqUKdx5551kZ2fT2dnJj370I3bt2kVRURH33HNPzDQcIYQYVQwd+vSOEqPbD37wg37BDKtfRl+vvfbaPu3vxhtv5MYbb7T//tOf/hSAM844gzPOOKPfPq666iquuuqqmNtycnJ46KGHUj7+WCFlLENF13ubBwkhhBAJ3H///Tz99NMUFaVunrY/W7NmDRdddBHbt2+PuX3z5s39FmbXXXcdP/nJT1i+fDmGYfDEE08A8LOf/YyLL76YZcuWMXfuXO6//34A7rnnHhYsWMDSpUv50pe+xG233TYsP5MQQuwTw8BAH+mjEENo1apVnHXWWXH/k1H0AyfBjiFiGBLsEEIIIQbLE088wa233hozlSYYDPKTn/yE733ve/Ztu3fvxu/3c9BBBwHmlbNly5YRCoX44IMPWLx4ccztAG+88QZLliwBzCtgb731FqFQaJh+MiGE2DuGYUhmR5pbsGABzz77bNz/ysrKRvrwxgwpYxkqUsYihBBCDJp42Ra/+c1vOO+882JKWhobG2NKUEpKSmhoaKCtrY2cnBy72711e9/vcTqd5OTk0NraKgtKIcToZOjmf0KIpCTYMVQMHfTwSB+FEEIIkZbeffdd9uzZw4033siKFSvs23VdjxnJZxiGPfYv+nag39+jv2dvx+ytX79+r7ZPZvXq1YO2r3Qlz1Fq8hylNlafo0q/Dz2ksWkYjn+sPkdOp5Pu7u5heazhepzRLhgMjrrfFwl2DBVdM/t2CCGEEGLQvfDCC2zatImzzjqLnp4empub+f73v891111HU1OTvV1zczOlpaUUFRXh9XrRNA2Hw0FTU5NdElNaWkpzczPl5eWEw2G6u7spKCjYq+OZO3cuHo/nc/9cq1ev5tBDD/3c+0ln8hylJs9RamP5Oer4wI3izhzy4x/Lz1FNTQ3Z2YM/jr6v7u7uYXmcscDtdjN//vyY20Y6+CE9O4aIIQ1KhRBCiCHzy1/+kqVLl/Lss8/yi1/8grlz53LPPfcwYcIEPB6PvcB69tlnWbRoES6XiwULFvDiiy8C8Mwzz7Bo0SIAjj32WJ555hkAXnzxRRYsWIDL5RqRn0sIIVKSnh1CDIgEO4aKoWNIGYsQQoxpN954IyeccAIvvPBCwvt3796ddB+XXnopK1asYN26ddx8882A2Wwz0T4B3nzzzZjO60ceeSTf+ta39v0H2c/ceeed/PKXv+SUU06hp6eHy/4/e3ceJ0V9J/7/VdXV3XNyDDAMMAygqIyCFxiPZNE1RsCIGnJsgtHkkRhXN6e/b9wQ9StxNx67MZpdo8nXJJtkPZIQo6IugjFGTRajgCig4wFyDefAcMzRV1V9fn/U0Xf3DNM9wwzv5x+hu7qqurqc9PGu93H11QAsXryYJUuWcMkll7B69Wq+9a1vAfDNb36TN954g49//OM8+uij3HrrrQN49EIIUYSMnh3UFi1axOOPP86FF16Y8/ELL7yQ1tbWXu/vSPznf/4nq1evBpLfV4YSKWMpF9uSzA4hhOgnZmsLiW3rCTbNwGhsLtl+n3jiCdatW0coFMr5+KuvvspXv/rVHu1rxowZzJgxA4DXX3+dD33oQ3nXPf/88zn//PMBaGtr43Of+xzf/e53e3n0Q9MLL7yQtezss8/m7LPP9u9PmzaNxx57LGu9CRMm8NBDD2UtHzFiBD/96U9Le6BCCFEuSjmTH0XJlev7xNFq1apVaZ+fQ40EO8pF2dKzQwgh+iC2/k/E3/xjzscsy6IjEABAxbqw9m4GpYhqGoH6KWjhwvWzodM+RnjGRwuuc91116GU4tOf/jSnn346LS0tHDp0iPr6eu69914ef/xx9u7dy7XXXssjjzzC3/72N375y18SjUaJx+PccccdnHnmmf7+Xn31VX784x9z/fXX88ILL/C3v/2NYcOGcfPNN/OnP/2JmpoaWltbufbaa/1SC4B///d/57Of/SyTJ0/u4ZkTQggxlCml0CSzo8cKfZ9IdSTfJ9S02TDrksLrKMVdd93Fiy++SH19PZZl8aEPfYhYLMY3v/lNNm/eTFNTE7fffjvDhw8vfpx59gdOieavf/1rbNvmlFNOYfHixYTDYR5++GGWLl1KJBIhGAzywx/+kHXr1rFhwwZuueUWfvzjHwPw2GOPcdddd3H48GFuvvlmLrzwQp5++ml+/vOfEwgEaGxs5Ac/+EFJelT1ByljKRfbGQklUVchhCgvFe1KpvMq5dwvAe9K/3/+53/S3t7Ob3/7W1asWMG4ceN46qmnuPbaa6mvr+fBBx9k+PDh/Pa3v+WnP/0pTz31FNdccw0PPvhgzv2ed955XHjhhXzjG9/goosu4oILLmD58uWA8yXliiuu8NfdsmULr732ml+GIYQQQsjo2fIo1/eJFStW8Pbbb/PMM8/wH//xH2zbtg2A/fv3c9VVV/HUU08xceJE7r///j7t7/3332fJkiX89re/ZenSpYwaNYpf/OIXdHZ28vzzz/PQQw/xzDPPcMEFF/DII49wxRVXMH36dL7//e9z0kknAVBbW8sTTzzBLbfc4h/Pj370I/7rv/6Lxx9/nAkTJvDBBx+U5Lz0B8nsKBPllbDYFgQkpiSEEL0VnvHRvNkXqd3PzdYWOh69CSwTAgbVl99Y0tTTSZMm8Z3vfIff//73bN68mTfeeIOmpqa0dXRd5/777+eFF15g8+bNvPbaaz0eXfrJT36S++67j0996lM888wz/PrXv/Yf+93vfsfChQvzltEIIYQ4BkmD0l4p9H0i1ZF8n+jJ2NnXXnuNiy++mGAwSF1dnd8ce8qUKcyaNQuAyy+/nEWLFvXg1eTf36uvvsrWrVv5zGc+A0AikeDkk0+mpqaGH/7wh/zP//wPW7Zs4S9/+QvNzblf10UXXQTA1KlTOXDgAAB///d/z+c+9zkuuugi5syZk3fbo5EEO8rFi7ZaFgSko7sQQpSL0dhM7cI7ylZju2HDBv7P//k/fPGLX2TOnDnouo7K+JLZ1dXFpz71KS677DLOOussTjrpJB555JEe7f+ss85i7969PPfcczQ2NjJ27Fj/sT/96U/84he/KOnrEUIIMcjZktlRDuX6PqFpWtr3BsMw0v4FpzQl9f6R7M+yLObNm8ctt9wCON9NLMti165dXHXVVXz+859n9uzZjB49mpaWlpz7Drglwpqm+ctuueUW3nnnHV566SVuvPFGvva1r3H55Zf36FgHmqQclIvXr0OalAohRNkZjc1UnveZsjQTW7VqFR/60If43Oc+x+TJk3nxxRexLOe9PRAIYFkWW7ZsQdM0rrvuOs4++2z++Mc/+uvk4m0HzheKK664gu9///ssWLDAX6e9vZ1oNMrEiRNL/pqEEEIMYlLGUjbl+D5x7rnn8uyzzxKPxzl06BB/+ctfANi0aRNvv/02AH/4wx8477zz+rQ/7/vH/v37UUrxve99j1//+tesX7+eSZMm8cUvfpEZM2bw/PPPZ32Pycc0TS6++GJGjhzJP/7jP3L55ZfnDZQcjSSzo1zcIIeyLbQiqwohhDh6XXLJJXzta19j/vz5AEyfPt0fCXfBBRdw7bXX8rOf/Yzm5mbmzZuHpml85CMfYc2aNXn3ed5553HPPfdQW1vL3Llz+fjHP85//dd/+emjAK2trTQ0NJT3xQkhhBiEpIxlMLnoootYv349l156KaNHj+b4448HoKmpifvvv59t27Zx4okncsMNN/Rpf9OmTeNrX/saX/jCF7Btm+bmZq699lpM0+Q3v/kNl1xyCUopzjrrLN5//30A/u7v/o7Fixfzb//2bzmfyzAMvvGNb/ClL32JcDjMqFGjuOuuu0pwVvqHpjJzcQeJWCzGhg0bmD59esm6wa5Zs4aZM2f2eT9K2Ry80/lSPPwbD6HX1PV5n0eDUp2foUzOUXFyjoo7ls9RS0tLj2pBU3t2DHa2bfOb3/yGzZs3+6mnvZHrnJXjM1LkVupzfSz//7+n5BwVJ+eouMF8jg7e8xkIVTHia78q6/MM5nPU0+8TfTWUvo/0Va5z7l34GajvI5LZUQ6pI2dl/KwQQogCvva1r7Fr1y7pzSGEEKJHnNGz8htjKFu9ejX/+q//mvOxBx98MK2/l8hPgh3lkPLmo6RnhxBCiAIeeOCBgT4EIYQQg4lMYxnyZs2axdKlSwf6MAY9aVBaDmmZHebAHYcQQgxCg7S6ckDIuRJCiGOQNCjtEfmM7D9H67mWYEc5pGZzSGaHEEL0WEVFhd9FXBSmlGL//v1UVFQM9KEIIYToT5LZUZR8n+g/R/P3ESljKQMlZSxCCHFEGhsbaW1tpa2treB68XicUCjUT0d19KqoqKCxsXGgD0MIIUR/UrYEO4ro6feJvpLvI46j9fuIBDvKIa2MpbzBDrO1hcS29QSbZpR0HrQQQgyEYDDIlClTiq63Zs0aTjvttH44IiGEEOIoo5SUsRTR0+8TfSXfR45uEuwoB9U/ZSxmawsdDy8C2yRqhKhdeIcEPIQQQgghhBjKpIxFiB4pWc+Op59+mksuuYSLL76YRx55JOvx559/nssvv5zLLruMf/qnf+LQoUMAPPHEE3zkIx/h8ssv5/LLL+fee+8t1SENnNTMDqt8wY7EtvXJBqiW6dwXQgghhBBCDF3KTiubF0LkVpLMjj179nDvvffy+OOPEwqF+OxnP8vZZ5/N1KlTAejs7OR73/sef/jDHxg7diz/8R//wX333cctt9zChg0bWLRoEZdeemkpDuWokNqno5w9O4JNM4hqupPGpgcINs0o23MJIYQQQgghBpbfcFMyO4QoqiSZHStXruScc85hxIgRVFVVMWfOHJYvX+4/nkgkWLx4MWPHjgXgpJNOYteuXQCsX7+eJ554gvnz5/Ptb3/bz/gY1FT/9OwwGpsJNDgBpcqLviIlLEIIIYQQQgxl3u8MCXYIUVRJMjv27t3LmDFj/Pv19fWsW7fOvz9y5Eg+9rGPARCNRnnwwQe56qqrABgzZgxf+tKXOPPMM7nnnnv4l3/5F374wx/2+Lk3bNhQipfgW7NmTZ/3Eezax0T39vvvvkOkvXwBj/FdXVQAW3bvo6sEx15MKc7PUCfnqDg5R8XJOSpOzpEQQohjjp/ZIWUsQhRTkmCHbdtomubfV0ql3fd0dHTw1a9+lWnTpvGJT3wCgPvvv99//JprrvGDIj01ffp0wuHwER55ujVr1jBz5sw+78dq28bhvzq3px5/HKET+r7PfA69ZmMDk+tHUlGCYy+kVOdnKJNzVJyco+LkHBUn56iwWCxW8osBQgghjgJSxiJEj5WkjKWhoSFthnFbWxv19fVp6+zdu5eFCxdy0kkncfvttwNO8ONXv/qVv45SikAgUIpDGlj9VMYCoKKdzr9dB8r6PEIIIYQQQogB5pexSGaHEMWUJNhx3nnn8corr9De3k4kEuG5555j9uzZ/uOWZXHdddcxb948br75Zj/ro6qqip///Oe8+eabADz88MO9zuw4Gqm00bNmGZ/HRkWcYIfd2V625xFCCCGEEEIcBSSzQ4geK0kZy9ixY7nhhhu4+uqrSSQSfOpTn+LUU0/lK1/5Ct/4xjfYvXs3b7/9NpZlsWLFCsApP7n99tv50Y9+xPe+9z2i0SiTJ0/m3//930txSAPL7p/MDhXrBpw3OrtTMjuEEEIIIYQY0vyMDpW3dYAQwlGSYAfA/PnzmT9/ftqyn/3sZwDMmDGDd955J+d2s2bN4oknnijVYRwd+mn0rIp0JG9LZocQQgghhBBDW1pGhwIk2CFEPiUpYxEZ+iuzw+3XoVWPwJaeHUIIIYQQQgxpKrVXh5SyCFGQBDvKQPVTg1Iv2BEY3YTqOlTWLBIhhBBCCCHEAEsNcEiTUiEKkmBHOaSWsVjlLGNJBjtAoboPle25hBBCCCGEEAMsLdghmR1CFCLBjnLot8wOp2eHPnqi81TSt0MIIYQQQoihK62MRTI7hChEgh3lkBrgUOULdtjR1MwOiK16CrO1pWzPJ4QQQgghhBhIktkhRE9JsKMcUqOsllm+p4l0gBHygx7x9S/Q8ehNEvAQQgghhBBiKJIGpUL0mAQ7ykCljZ4tfXqZ2dpC5K+/wdrfilZRi922zXs2sEwS29Znr79yiQRBhBBCCCGEGMxSAhxKyliEKMgY6AMYkso4etZsbaHj4UVgm6BpaMPGEpx8GtGXH3JWCBgEm2akr//Id8E2iQaC1C68A6OxuaTHJIQQQgghhCi/tAupZbioKsRQIpkd5ZD2JlTaMpbEtvXJfSqFho3R2EygYSrasDFZwYzEtvVgJZwocI6sDyGEEEIIIcQgIWUsQvSYBDvKQaWWsZQ2syPYNAP0gH9fqx0NQKDheDDjWVkbet2E5J2MrA8hhBBCCCHEIJI2elYyO4QoRIIdZaBKMHo2X58No7GZ4EkfTlkxhtnaQmDkOFT3IVSsO31H8eT9mk/fKiUsQgghhBBCDFZp2RyS2SFEIRLsKIfUAMcRBDu8PhvRF/8753QVvbLGv23t3kTHozehLOd5rIO70/e1NVm2ooWre30sQgghxNGis7OTSy+9lNbWVgB+97vfcemllzJ//ny++93vEo/HAWhpaWHBggXMmTOHm2++GdN0yj937tzJlVdeydy5c7n++uvp6uoC4PDhw1x77bXMmzePK6+8kra2toF5gUIIUUxaGYtkdghRiAQ7yqGPDUr9Pht5pqsoMw6hquQCy8TuOuA83YFd6fv64HW0quHOau2tvT4WIYQQ4mjw5ptv8rnPfY4tW7YAsHnzZn7xi1/w29/+lqeeegrbtnn00UcBuPHGG7n11ltZsWIFSimWLFkCwG233cbChQtZvnw506dP54EHHgDgRz/6EbNmzeLZZ5/l05/+NLfffvuAvEYhhCgqrYxFMjuEKESCHeWQEmU9kp4dTl8Nzbmj61l9NlQijhauAiMEmg4Bg9AJ5wBgp2R2xN75K6rrAKr7MADm5jd7fSxCCCHE0WDJkiUsXryY+vp6AEKhEIsXL6ampgZN0zjxxBPZuXMnO3bsIBqNcvrppwOwYMECli9fTiKRYNWqVcyZMydtOcCLL77I/PnzAbj00kt5+eWXSSQS/f8ihRCimNTfGRLsEKIgGT1bBn6AIxA8oswOo7EZQmGIR9GHjclewYyhV9ZS9YlFJLatJ9g0A6OxGa2yFutAMtgRf/N574iczXa/3+tjEUIIIY4GmdkWEyZMYMIEpwl3e3s7jzzyCHfeeSd79+5lzJjkZ+eYMWPYs2cPBw4coKamBsMw0pYDadsYhkFNTQ3t7e2MHTu2x8e3YcOGPr2+VGvWrCnZvoYqOUfFyTkqbjCeo1DHbhrd2xvWrcOsGlnW5xuM56i/yTk6ekmwoxy8MhbjyIIdykpAPOrs6sAuOh69iaqPXYsd6SDYNAOViEEwjNHYnNZwVKsagbllLWZrC0ZjM/ahPYAGmgYoMOMleHFCCCHE0WPPnj1cc801fPKTn+Tss89mzZo1aJrmP66UQtM0/99UmfdTt9H13iW/Tp8+nXA43PsXkGHNmjXMnDmzz/sZyuQcFSfnqLjBeo7MPZvoWOncnj79FAIjx5XtuQbrOepPco4KG+hAkAQ7ysFNL9MCIb9xaK827zqUvsCM073iJ2DbRI0g+sjx6G4fDn+V1hbs9h2gbDoevYnwh/8Be982jBPPwxh/AonNb2JtX09i+9sEJ558xC9NCCGEOFps2rSJa665hquuuoovfelLADQ0NKQ1GN23bx/19fXU1dXR0dGBZVkEAgHa2tr8kpj6+nr27dtHQ0MDpmnS1dXFiBEjBuIlCSFEYTJ6Vogek54d5eBmc2i9zOzwxs0mtqx1FgS8WJTm7sdpWKoih9GCobRtE9vWJ9/wzASxlx92bn6wCr2yFmv7BrAtOn9zc9Z0FyGEEGKw6ezs5Mtf/jLf/OY3/UAHOOUt4XDYv5q0dOlSZs+eTTAYZNasWSxbtgyAJ598ktmzZwNw/vnn8+STTwKwbNkyZs2aRTAY7N8XJIQQPSENSoXoMcnsKAcv6GCEQPUs2GG2ttDx8HecoIYb5Ki6+Dpia5/F2rc9WYKiB0A3nH2nCDbNIKoHnO11PRlksSzi76xMuZ8gsW19WvmLEEIIMdg89thj7Nu3j1/+8pf88pe/BODCCy/km9/8JnfffTe33HILnZ2dnHLKKVx99dUALF68mEWLFvGTn/yEcePGcc899wDwzW9+k0WLFvHxj3+c2tpa7r777gF7XUIIUZCMnhWixyTYUQbKz+wIoSyzR9sktq1PC1AAGJNPR6seSddj/+qvV3nhl4m99jiakV4XbDQ2U/GRzxF9+WHC5/0Dsb/+BlDOpJZp52F642z1QNZ0FyGEEGKweOGFFwD44he/yBe/+MWc60ybNo3HHnssa/mECRN46KGHspaPGDGCn/70pyU9TiGEKAvJ7BCixyTYUQ5eg9JAMHm7iGDTDKKa7kRoNQ2UQq8ajh2qSltPWTFUIg7B7CZohhvECE48mVjAIDDuBKou/JI73aWK7qX/TsV5n5GsDiGEEEIIIQajtMwOCXYIUYj07CgHv0FpEOyeZXYYjc0Exk0FQB8x1ilTCVVi7nwHSHaLt3ZtRJkxtIwyFgC9dpSzTtsWsBKEpn3YD2wEJ53qHFPl8KzthBBCCCGEEINASoBDSRmLEAVJsKMcbAs0HQKBXjUo9UpT7IN70KtHoGmaU3JiBJ39AfrwejDjaDkyO/QaZ862ueM95/6wMcl9V9YAoKKdR/aahBBCCCGEEANKSRmLED0mwY4yUMp2moTqAb9/R4+2sxLuDRutagTgZHzULryDig9/FgC9stYJoBjZwQ4tWIEWrsba+a6z7rDRyccCQQhVoqIdR/iqhBBCCCGEEANKGpQK0WMS7CgH2wYt4ExO6UWww5+4AujVyXITp/moE+ywuw8BZI2e9Wg1ddiH9jj7SMnsANAqaiSzQwghhBBCiMFKMjuE6DEJdpSDO/5V62WwQ6UEO7zMDv++HgAjjOo+7CzI0bMDQK+tc28YaNXp+9AralCRvmV2mK0tRFYuwWxt6dN+hBBCCCGEEL0kmR1C9JhMYykHZaMdQRkLZsK/qWcEKgC0UEUysyNHGQuAXuM0KdVrR6Fp6bEsraIGFTnyzI7wwW10/PFXYFtEjSC1C++QyS5CCCGEEEL0F8nsEKLHJLOjHGwrWcZi9bJnR8CJP5l7N2dlT2ihClTXQed2jgalAJqb2ZHar8N/rLIWuw9lLJXtW9zpMgosk8S29Ue8LyGEEEIIIUQvyehZIXpMgh1loGw7Wcaietezw+uzYW5aQ8ejN6UFPLRgpZ/ZkbeMxcvsyOjXAU6woy8NSiN1k5N3AoYzKUYIIYQQQgjRP2T0rBA9JsGOclBH1qBUmQm06pHevezsiVAFym9Qmq+Mxdne6tiXnRnSxwalseGNzn6qhksJixBCCCGEEP1MRs8K0XMS7CgH20r27OhhGYtSCsw4gZHjnawNTc/KntBCVf7EFi1PZofXgNTa9lZWZoheUQNmHJWIHdHL0k13O02TQIcQQgghhBD9TRqUCtFj0qC0HJRTxoJu9Dyzw7YAhV43jtqFd5DYtp5g04y0oIIWqkiunyezw+484B2Enxni7UOrqHUeiXbmzQwpRDejzvaRDpRSaJrW630IIYQQQgghjpBkdgjRY5LZUQbKdspYNF13G3r2QErGhtHYTOV5n8nKntBClcnbeTI7gsedmT8zpLLGOb4ejJ/NNWJW9zJCbAti3T17XUIIIYQQQojSSMvmkGCHEIVIZkc52JaT2REwejx6VnljZwPBvOtowZTMjjyjZ43G5vyZIRVOsMOOdhIocCxmawsdj94EVoJoIDliVjcj/jp25DCBiuriL0wIIYQQQghRGmmZHVLGIkQhEuwoh7QGpT18E7IK9+IAIKWMpVAZitHYnLOnhlbplbEUzuxIbFvvZ5qklsL4PTsAFTkMI8cV3I8QQgghhBCihFIDHD39nSHEMUrKWMrBbVCq6YEel7H4mR1GgcyOHpSxFOL37IgUnsgSbJoBXj+OlFIYr2cHgOo+3OvnF0IIIYQQQvRBSrBDSc8OIQqSYEc5+A1KndGzPXoj8np2BPIHMVKDHfkalBaiu2UsxcbPGo3N6KMmQsBIGzGrp0xxsSMS7BBCCCGEEKI/KSljEaLHJNhRBl6DUvSAt6D4NlYvMjv0gJM10lvhKkAj8f6raY1Hcz+ZBpZJYPyJ/qLUnh1Kgh1CCCGEEEL0L5nGIkSPSbCjHLwGpV5AoidNSt0ylkLlKX6D0iPI6gCwdrwDKMxt6+l49KbCAY+EO2Y2ZeqKbsb8SS9SxiKEEEIIIUQ/S72IKpkdQhQkwY5yUDaalpJ90YNgh/IaghaYxoKb2XEk/TrAbTzqcRuP5j2euFOyklryoptRtHA1WmUtdg/G1wohhBBCCCFKSDI7hOgxmcZSDradltmhbAut2DY9mMaiudNYtDxjZ4sJNs0gigaotMajuaiEU7KiYl3+Mt2MoYWrQdMks0MIIYQQQoj+lpbZIcEOIQqRYEcZKGU5jUa9zA6rJ5kdvejZcYRlLEZjM4HxJ2J37KfmE4tyjqcFUMqGhJfZkRLsSETQKqrRdEN6dgghhBBCCNHfpEGpED0mZSzl4DYo1XQ3lqR60LPDbVDak2ksR1rGAhAYOQ7NCOYNdACQiPs308tYnMwOrWqYTGMRQgghhBCiv6Vlc0hmhxCFSLCjHPwGpe7ptcyim3g9O7SCmR19K2MB0Cpqio6eVW5zUsgsY4mihavQqoZJGYsQQgghhBD9LSWbQ0lmhxAFSbCjHJSNltGzo+gmPWhQqgW9MpYjz+zQKmpQkc6Cb45pwY5oRs+OimqUGUd1HyKx/e0jPg4hhBBCCCFE7yhpUCpEj0mwoxy8MpaAkbxfTA9Gz+Jldhxhzw4ArbIWUGlBjCzxPJkdiSgqHiHx9sugbDp/c3Ph8bVCCCGEEEKI0pHRs0L0WMmCHU8//TSXXHIJF198MY888kjW488//zyXX345l112Gf/0T//EoUOHANi5cydXXnklc+fO5frrr6erq8CP8EFCeWUsmjd6tgdlLJbXoLRAzw49AAED6+DuIw4yaBU1zvMVKGXJldmhLBPdTjjlK17wpsj4WiGEEEIIIUQJSWaHED1WkmDHnj17uPfee3n00Ud58skn+d3vfsfGjRv9xzs7O/ne977Hgw8+yFNPPcVJJ53EfffdB8Btt93GwoULWb58OdOnT+eBBx4oxSENLOVkdlgHdwFg7tpYZAPAL2PJPyDHbG0By8Teu4WOR286ooCHk9lRJNiRI7PD+1cfMyk5ZUYPFBxfK4QQQgghhCglGT0rRE+VJNixcuVKzjnnHEaMGEFVVRVz5sxh+fLl/uOJRILFixczduxYAE466SR27dpFIpFg1apVzJkzB4AFCxakbTdoKRsV7SD6FyfDpfvZ+4oGJpQZh0AQTdPyruNkUbiPH2FWhd6rzA7NX0/FugEwGo6n4oKrAKia+0+Fp7oIIYQQQgghSkdGzwrRY/nTCHph7969jBkzxr9fX1/PunXr/PsjR47kYx/7GADRaJQHH3yQq666igMHDlBTU4NhOIcxZswY9uzZ06vn3rBhQwleQdKaNWv6vI+JkQi2uZuQZaLhlIBsfWU5B4/rzrvNqJ07qNECBZ8/HAkyTg+g2RZK09kUCRLr5fEGO/cyEdj01pt0ted+g6ze1cJYwAxVE9m3m3fXrCF0aCeNwAetu7ADYcYDG/ceJlqC8zXUlOJvaKiTc1ScnKPi5BwJIYQ45kgZixA9VpJgh23baRkJSqmcGQodHR189atfZdq0aXziE59gz549WesVymzIZfr06YTDR96wM9WaNWuYOXNmn/dzcKVBoL4Rs3sfWAm0gMGkc+dyfIEsiK69r5DYX1Hk+WdinjSNxLb1BJtmMOoIsirsznYO/e+PmTJuDOE8zxV7Yx/d6yBcN5awbTNz5kyiq3YSAaaMGY4x/kQ6VsOJU5oITu37+RpKSvU3NJTJOSpOzlFxco4Ki8ViJb8YIIQQ4iggo2eF6LGSlLE0NDTQ1tbm329ra6O+vj5tnb1797Jw4UJOOukkbr/9dgDq6uro6OjAsqy82w1KykavraPq4usAqLzgC8XLPcx44UksLqOxmcrzPnPE5SNahdOzwy7YsyMCgF4zChXtxGxtIfLCzwGI/OkXWO073fViR3QMQgghhBBCiN6T0bNC9FxJgh3nnXcer7zyCu3t7UQiEZ577jlmz57tP25ZFtdddx3z5s3j5ptv9rM3gsEgs2bNYtmyZQA8+eSTadsNWrYFWoDA+BMA0Ec0FN1EmQkIBMt9ZGhGEIJhVLQj/7G4PTu02tHYsS6nN4gbkMK2sPZsdteLlP14hRBCCCGEEC4lDUqF6KmSBDvGjh3LDTfcwNVXX80VV1zBpZdeyqmnnspXvvIV1q9fzwsvvMDbb7/NihUruPzyy7n88su5+eabAVi8eDFLlizhkksuYfXq1XzrW98qxSENLGWj6TpawM3U8CatFGIlepTZUQpaRU3BBqUkYqAH0KuHQyyCMXE66DoKIGBgTHImsKRObRFCCCHKrbOzk0svvZTW1lbAaZA+f/58Lr74Yu69915/vZaWFhYsWMCcOXO4+eabMU1nBHy+cfeHDx/m2muvZd68eVx55ZVp2apCCHFUkQalQvRYSXp2AMyfP5/58+enLfvZz34GwIwZM3jnnXdybjdhwgQeeuihUh3GUUHZljOe1Q1eKKt4sEOZcTDKn9kBoFfUoiKFR89qwQq0impAERjThDH5DGLb1jNi4e0Exh7nrJiQYIcQQoj+8eabb3LLLbewZcsWwGl4ftNNN/HQQw8xbtw4/vEf/5GXXnqJ888/nxtvvJHvf//7nH766dx0000sWbKEhQsX+uPuP/7xj3P//ffzwAMPcOONN/KjH/2IWbNm8eCDD/Lkk09y++2386Mf/WhAX68QQuQkZSxC9FhJMjtEBtsGTXdKRgDMRPFtzDhaP5SxAGiVtcVHzwYr0MLemNousE0S1WOcXiFGCNAks0MIIUS/WbJkCYsXL/Z7e61bt45JkyYxceJEDMNg/vz5LF++nB07dhCNRjn99NOB5Fj7QuPuX3zxRf+CzaWXXsrLL79MItGDz24hhOhvaWUsktkhRCEly+wQKZQNup7M7OhBGYuyEmihynIfGeCUsdgHduU/lkQULRR2Mzsg+trjWO07sSpGO9trGoQq/N4eQgghRLl5zc09ucbe79mzJ2u5N9a+0Lj71G0Mw6Cmpob29nbGjh1b7pclhBC9I5kdQvSYBDvKwbbQ9ECyB0dPenaYCbSqYeU9LpdWWYO9K3+DUuJRtGAl9uH9zt3V/wMoVOXo5D6CEuwQQggxcPKNvc+33Ps3Vb5x90opdL13ya+lHPW7Zs2aku1rqJJzVJyco+IG4zkauWsnI93bra3bOVTm1zAYz1F/k3N09JJgRzm4ZSzedBXVgzIWZcYh0D8NSlUihuo6iNnaAkBiy5sEJ5/mj7NVCadnh314r7cFAJqZHDWrhSqkjEUIIcSAyTf2PnP5vn37qK+vTxt3HwgE0sbd19fXs2/fPhoaGjBNk66uLkaMGNGr45k+fTrhcLjPr2vNmjXMnDmzz/sZyuQcFSfnqLjBeo4ih9cT/cC5PWH8eKaW8TUM1nPUn+QcFTbQgSDp2VFiStmAAj3gXDEKBHvUoBQrnuzxUUZmawuJd/4XbIuORxbR8fB3iL78EB2P3uQHP1QiCqEwwRPPTds2NrzRv60FK6RBqRBCiAFz2mmnsXnzZrZu3YplWTzzzDPMnj2bCRMmEA6H/S9YS5cuZfbs2QXH3Z9//vk8+eSTACxbtoxZs2YRDPZPHy0hhOgNpWxnEIJzZ2APRoijnGR2lJrtNgrSnDiSZoR61KBUmQm/x0c5JbatTx6jZeFlbWAmiK3/E4lt67G7DmPUjiY48WQCY4/D2rsFlE20bnJyR9KzQwghxAAKh8PcddddfP3rXycWi3H++eczd+5cAO6++25uueUWOjs7OeWUU7j66qsBZ9z9okWL+MlPfsK4ceO45557APjmN7/JokWL+PjHP05tbS133333gL0uIYQoSDkXVbEtaVAqRBES7Cg1703Hq/U1gj1qUIqV6JdpLMGmGUQDAbBM5xiV7UaFFfG1y/GCH2rUBACMphlYe5xcOSuc7CmiBStQ8UjZj1cIIYRI9cILL/i3zz33XJ566qmsdaZNm8Zjjz2WtTzfuPsRI0bw05/+tLQHKoQQ5aCUf1FVgh1CFCZlLKVmWwBobnqZk9nRg2ksZrxfMjuMxmaq5n0dgIq/uxJ9xPjUo0jeijoNTANjp/jLzIpa/7YEO4QQQgghhOhn3tRHNCljEaIICXaUWkYZC4FQ0QalSilnGks/ZHYABI8/CwAtVImKd6HXTchaRx8xDoDA2OPdjSpQgWTjNS0kPTuEEEIIIYToV8qdOKVpktkhRBES7Cgx5ZexeJkdQSjWoNSrueuHzA7AGXEbMLAP7UF1HcJoPNl97uQIvoAbAAmMngiaM0Y3fGh7cifBClQ8hhBCCCGEEKKfeGUsmi6ZHUIUIcGOUnPLWPzMjp707LCczA+z9W1/Iko5aZqGXjsKa9f7gMKYMI3ahXdQccHVBCZMc9YJVTiHtmsjKBsVOcy4Vb/yj08LVqASUsYihBBCCCFEv1E2oIGuJy+yCiFykmBHqblvOprboFQLFJ/Gkti2AQDzg9fTRsCWk14zGnP3Jud2bR1GYzOV532GkDtuNrH9LWdM7bb1fsKHZlvOfbwylpi8yQohhBBCCNFPlFJOzw5NenYIUYwEO0rNTi9jwQgVzewwt29wbymwTD+gUE5a7Si/54ZWMyq5vNKZuGK+/xodj96EXlkLgSBoOkoPEGya4awXdDI/SPRg0owQQgghhBCi75QtZSxC9JCMni0xlVHGohlBVFfhgECg4QT3lgYBww8olJM+LBng0Gvq/Nt21wHnONzAix3poHbhHSS2rWdTJMioxmZnRTfYoeIRv+RFCCGEEEIIUUZKOVkd0qBUiKIk2FFqfoNSr2dH8WksxpgmAILNf0fFWZdheAGFMtJr3WCHHkCrHu4vD046lagRBMv0Ay9GYzNGYzOxNWv89bwAh5KJLEIIIYQQQvQPt0GpJmUsQhQlwY5SczM7NH8aS6joNBZlmQCEmj/SL4EOcHp2AGg1dWhasprJaGz2Mzm8QEcuyTIWmcgihBBCCCFEv3BHzypNl8wOIYqQYEepeT07vABCoOfTWDQjWMYDS+eVsaSWsHi8TI5C/MyOuExkEUIIIYQQol94ZSxIZocQxUiD0lJzI6zx91/FbG1xMzsKl7H4ZS6B/gt2aLVOZoeKR45s+ktQyliEEEIIIYToVykNSpUEO4QoSIIdJWbu3ghA4q2X6Hj0JuzI4aI9O3DLWPoz2GEf2uP8u2/bEY27lZ4dQgghhBBC9C8lDUqF6DEJdpSYues995YzzUR1toMZLxx59cpYAv1XVeQENzT3+Xs/7lZ6dgghhBBCCNHPlALc0bNIZocQhUiwo8SM+snODc0ZI6vXTXDue9kbOagByOwINs0AI+i8UR7BuFvp2SGEEEIIIUQ/U7ZkdgjRQ9KgtMT0uokAhE79GOHTLsbc+Y7zgBl3ggu5+Jkd/Rfs6OnUlbykZ4cQQgghhBD9S0bPCtFjEuwoNdvJ0gifehFGYzPWng8AUGYcjeqcmyivgWk/TmOBnk1dyccrY0lsXI0xflq/jcwVQgghhBDimJU2elaCHUIUImUspeYFLrz+G0YISAlo5NzGCZD0Z8+OvrJ2vQ+AueWNI2pwKoQQQgghhOgtaVAqRE9JsKPElGU5N9zAheZla5jx/NsMwOjZvkpraHoEDU6FEEIIIYQQvZQyelYyO4QoTIIdpeZlaegZmR0Fgh0D0bOjr4JNM5yIMhxRg1MhhBBCCCFEL6WMnlWS2SFEQRLsKDFle5NVvMwOJ9hRKLMjq/RlEDAamzGmfgiMMLUL75CeHUIIIYQQQpSZchuUIg1KhShKgh2lljlG1v3XL1XJwR89288NSvsqOPEUMGPooycO9KEIIYQQQggx9PmjZ3Xp2SFEERLsKDW/jCXg/OtldlhFMjv0AJo2uP5z6CPHA2C37xzgIxFCCCGEEOIYoFIblEpmhxCFDK5f14NAZhlLT3p2KCsxqEpYPIE6N9hxQIIdQgghhBBClJ3boFSTBqVCFCXBjlLLaFDqNx0tUMaCmRhUzUk9+shxgIYlmR1CCCGEEEKUn1JoMnpWiB6RYEepZTYbNbyeHYUyO8xBmdmhGSH0YaMls0MIIYQQQoj+IA1KhegxCXaUmLIt50bWNJYCmR3W4MzsANCqhpPYuh6ztWWgD0UIIYQQQoihLaVBqYyeFaIwCXaUmmUCmt+gtMc9OwbZJBYAs7UFa88HqI59dDx6kwQ8hBBCCCGEKCOV1qBUgh1CFCLBjhLLbDaqeUGMgtNYTNAHX7AjsW198k3WMp37QgghhBBCiPJwG5QiDUqFKEqCHaVmW+n9NwJez44iZSzG4OvZEWyaAW4jVgKGc18IIYQQQghRHn4Zi2R2CFGMBDtKzTLRUjM79IATEChUxmIm/KDIYGI0NlMx+0oAquZ+FaOxeYCPSAghhBBCiCHMbVCqIZkdQhQjwY4SU5aZzHbwGMGCPTucAMngC3YAGI0nA6DXjhrgIxFCCCGEEGKIU7YzelaXYIcQxUiwo9Ts9MwOcCayFCpjcfp8DM5gh145DADVfXiAj0QIIYQQQoghLm30rJSxCFGIBDtKzTLTe3YACg1r17v5p5VY5qDs2QGgVTnBDjvSkfNxs7WFyMolMqlFCCGEEEKIvkoJdijJ7BCioMH5C/sollnGYra2QPdBrO6DdDx6E7UL78jqbaGsxKCZxtKytYt1mzs5dUoNCsWyVw7wZWDvrn00ZaxrtrbQ8ch3wbaIBoycr10IIYQQQgjRM8pvUKpLZocQRUiwo9QyyljSxrG641mzfvBbieSI2qNUy9Yufv+qxrrWjSgFuga2G0z+bE0FK9e0stTczkVn1gHw/Np2zt7xBCdYbvlOvtcuhBBC9NHSpUt58MEHAZg9ezbf+c53WLlyJXfeeSexWIx58+Zxww03ANDS0sLNN99MV1cXs2bN4rbbbsMwDHbu3MmNN97I/v37mTJlCnfffTfV1dUD+bKEECKbUinTWCSzQ4hCpIylxFRGGYszjlVz7uQZz5q5zdGgZWsXv3txDy1bu2jZ2sV3fr6JN7fr/nuqnfLe2qGqqNG6WfZaO//8s438fz/dyLJX22nfd9BZFw2ly2haIYQQpReJRLj99tt56KGHWLp0KatXr+aFF17gpptu4oEHHmDZsmVs2LCBl156CYAbb7yRW2+9lRUrVqCUYsmSJQDcdtttLFy4kOXLlzN9+nQeeOCBgXxZQgiRm7LdMhZpUCpEMRLsKLWMwIXR2Exg7BT04WPzl3EcZaNnW7Z28c8/28SvV+zmu7/YxPOvt5MwFX7QJkOnqqJW6wbAtLyliqmBVgDWJk7ito4vccefK2jZ2lX+FyCEEOKYYVkWtm0TiUQwTRPTNKmpqWHSpElMnDgRwzCYP38+y5cvZ8eOHUSjUU4//XQAFixYwPLly0kkEqxatYo5c+akLRdCiKOOm9mhSYNSIYo6utIJhgLLRMsYPatVjwTdyF/CYSWOqtGzazd2YFpOpDhhKmw/jUMR0DUUzvusocOsE2sx9g2jputQ2j5mG68zSneWfWA38p7VBG8fZvW7HfzbV46neZKTGpzaA8RbJoQQQvRUTU0N3/zmN5k3bx6VlZWcddZZ7N27lzFjxvjr1NfXs2fPnqzlY8aMYc+ePRw4cICamhoMt1m4t7w3NmzYUJoXBKxZs6Zk+xqq5BwVJ+eouMF4jiZGI0QPHEQ3YxjRLt4v82sYjOeov8k5OnpJsKPElG2ihSrTlmlGCNuM5d/mKCtj2X0g7t9WCjbvjgJw4ljFdZ84ASAtQNH1VAPt7+4GJ7mDE/RtfKXyCRSAgvH6Xn9/CUvx8PO7+fxFDWzaFeEnT+3AVmAE4KwTaxlZG+SiM+sk8CGEEKJH3nnnHf7whz/w5z//mdraWr797W+zZcsW56qnSymFpmnYtp1zufdvqsz7xUyfPp1wONy3F4PzpXnmzJl93s9QJueoODlHxQ3Wc3To1RDVo0ah4hHsg/GyvobBeo76k5yjwgY6EFSyX9hPP/00P/nJTzBNky984QtceeWVOdf753/+Z8455xwWLFgAwBNPPMEPf/hDRo0aBcAFF1zgNxEblKz0BqUAGCEw47nXh6Mqs+PtrZ08v+aAf18B77ZGANjU5nzxa55UnRaM0CprqVLdhIMaCVMxI7QZHRsNUBqM0/elPcfrGztZu2ljWpmhacErLc742hWr25kzq06CHkIIIYr661//yrnnnut/j1iwYAG/+MUvCAQC/jptbW3U19fT0NBAW1ubv3zfvn3U19dTV1dHR0cHlmURCAT89YUQoi/M1hYS29YTbJpRuib93uhZpEGpEMWUJNixZ88e7r33Xh5//HFCoRCf/exnOfvss5k6dWraOosXL+aVV17hnHPO8Zdv2LCBRYsWcemll5biUAZexuhZAC0YQiVyBzuUbTn1dkfBNJY3Nnbwb7/bhve2qQGpb6GW7WR0ZAYgtKph6GaUO7/YxLptMWbW/B3aH58DpdDQmDBuOJeMrmPjjgjvuYGTQu/Nlg3LXmtn+ep2PvmR0XTFbA4cTkjWhxBCiCzTpk3jBz/4Ad3d3VRWVvLCCy9w2mmn8fTTT7N161YaGxt55pln+OQnP8mECRMIh8P+lbilS5cye/ZsgsEgs2bNYtmyZcyfP58nn3yS2bNnD/RLE0IMYmZrCx2PfBcsk6gRzN+7r7dSRs8qCXYIUVBJgh0rV67knHPOYcSIEQDMmTOH5cuX87Wvfc1f5+mnn+ajH/2ov45n/fr1bNmyhf/3//4fJ510Ev/3//5fhg8fXorDGhDKzi5J0Yww5CtjcUezZmWD9LOWrV3c/F8f+FNWNM3pyWErJ/gAENDh1Ck1WdvqlcMAOGmMRfNxY4GxHHq9Ccw4WrCC6sogX79iIi1bu7jxwY3+/vztNSewYmW8X9s2/P7l9KyQFavb+dBJTrnL1PGVHI5Y0u9DCCGOYR/5yEd4++23WbBgAcFgkBkzZvD1r3+dD3/4w3z9618nFotx/vnnM3fuXADuvvtubrnlFjo7OznllFO4+uqrAVi8eDGLFi3iJz/5CePGjeOee+4ZyJclhBjkEtvW+9/zsUwS29aXJNih0kbPSoNSIQopyS/sXI3A1q1bl7bONddcA2TX7YwZM4YvfelLnHnmmdxzzz38y7/8Cz/84Q97/NylbAiW6/h6a2J3F9GDh3k3ZT91+w8wLB7LuW89EWEysH3nbg4PYE3Tsjc0bOWmxKE4vl5x4cnOG+jarU75yhmTFN373mFNevyB6t37GAtsWPMqidqxAEyIRjGrRoKyMdr38p772i49HZ5eG0Ap0HU4c7LNGZOU/zydUXhnlzfiNrte2rIVr7QcTlumazD/DIuxw2Fzm8aUMYqmUSU6MUdgoGvTBgM5R8XJOSpOzpHwXHvttVx77bVpy84991yeeuqprHWnTZvGY489lrV8woQJPPTQQ2U7RiHEsSXYNIOopjsBiYBBsGlGaXbslbHI6FkhiipJsCNfw6+euP/++/3b11xzDR/72Md69dylaggGpWkwc3BlgOox9TSl7CfS+TbRLf/LmWeemXVe7M4DHHoBmiYfR3gAm9s8/Or7QDeaBiFD558+kZyY8gl3nXznJ7HFoPPN39E8pZHgpFMBOPSqhjGmATQdc/tb/nYzZ8L5H8o9gcV7nmdf3cf9T+3IygBxZP9d2Qqeet1A0+h1s1NvGsywykBJskSkSVFxco6Kk3NUnJyjwmKxWMkvBgghhOg5o7GZwMRTsHa+W7oSFnCzOdzMDiSzQ4hCShLsaGhoYPXq1f79njb26ujo4A9/+ANf/OIXASdIktpQbFDKUcZC0A3GWAmnWWkqL71tAMtYXnzjAO9sd0ap6Br848fH9+oHv1bllLHE1i5HCwQxGptR8SgEK9CMICrambZ+ZoPTTPPOHs3khko/CLFxV4QDh53z9Nq7HTmDIN44XMhudvqhk2pROEGcGVOq2bwnCgqCQZ2nV+7zS3fAyTbx+oSgYOr4SjbuiqTd9vqHpJbRADy/tp22No2q0V1SViOEEEIIcYzTw1VYeqB0gQ7wMzs0TRqUClFMSX5hn3feedx33320t7dTWVnJc889x7/+678W3a6qqoqf//znnHHGGZx22mk8/PDDvc7sOOrkmMaiuQEOlYj5tz3KC3YMUIPSlq1d/L9ndiSPR8HhiNWrfdgH9wCQePtlEu+9Qu3CO1CJKFqoEi1UgYp1o5SNpuk93me+gEjL1i6eX9sOCqordB7/6748GSAOy04GPgBeXn+o8GvJ0SekGM39H+fzRuf1BzdKXxEhhBBCiGOcsi1neEFpd+qMzPZKZIQQeZUk2DF27FhuuOEGrr76ahKJBJ/61Kc49dRT+cpXvsI3vvENZszIXaMWCAT40Y9+xPe+9z2i0SiTJ0/m3//930txSANG5ZrGYriZHbnGz7pvgJre/8GOlq1dfOfnm0iYTlRY0yBoaDmbkBZi7fnAvaWcBkxb10EiihYMo1VUAwoV60ar6N1+c8kMgpx78gieX9vOH1cfwLSU06+J7Gan5aT8/wHQsgIs4GSMLPjIaLplsowQQgghxLHBSoDdu4uIxaU2KJXMDiEKKVntxPz585k/f37asp/97GdZ6911111p92fNmsUTTzxRqsMYeHZ2ZgdBN7MjR7AjmdnR/2Us6zZ3JgMdwBlTa/j8Rxt6/QPcmHw6/OURZy8BA2PCNGefoQq0sBPgUNFOKEGwI5MX/LjojDq/Dwg4JSUHDifylr2kCuhw/qnDeWndoaLrFqfI2VfEhscyMkaWr2rn1OOqGTcqzAkp5TISBBFCCCGEGAIsC5Td6wzngpTtNyiV0bNCFDaw806HGKWczAb09L4jfulKIsf4WdMbPdv/mR2pGRyhoHZEgQ6A4MSTIRAkMO4Eqi78EvrIce4DlX42h4p2leSY88nM+PBue2UvqX02UntwpJaYXHpOV1qfkGI9O7wyGls5Y3pnnVjLwUMHeW93oEdBE1vBG5u6eGNTF8+mLF++qp0zT6ihfkQo5/NLQEQIIYQQ4uinbLeExbKcL4ul2KeMnhWixyTYUUpemlpm4MItY8md2WHm3qYfjKh1/vN/aFotn71gbJ9+PGuhSoz6KRiNzVgHdrnLvDIWspqU9pdizVCPdF3PuSePSJsss2bNGqpGT+1VX5FMtoLV7xU+X8+uamfeWXV+HokERYQQQgghjjLe93zbBEr0Xd8fPStlLEIUI8GOUnKjt3kblObs2TFwmR1vbHR+UH9p7ngmja3o0760YBhlupkrbgaLlpbZMTDBjnLLFSDJ1VekN5NlekIpWPZae9H1Vqxq54ypNdSPDGVlpkggRAghhBCijNwLocoycxQ5HyFlu5kd0qBUiGIk2FFCySyNjDIWt2cHZnYZy0BOY3l53UEqQzpd0RJ0iTbCqIQTzFHxCOD27BjiwY6e6MlkmdRARF+CIJksBavfz33ul69q57Tja2ioC6X1DJEJMkIIIYQQfef/Nihlk1K3jEVGzwpRnAQ7Ssly38gyJ6t4ZSyJ/NNYyGxqWmbrPujgjU3Oj+CbfvEBd375+L6VsQTDYEYBUAnnX4IV6F6wI1benh2DUW+CIN7tVe8d5tV3OrBLEAyxFax1s3uezfF4wJ0g0xWzJQgihBBCCNFbtpn+bym4zU6d0bMS7BCiEAl2lJLtlaRklrG4wY+jqIzl8b8mJ4MkTMW6zZ19+wEbDKHc8hUVd4IdWqgCQhVOt+gyNygdSgr1Dpl39mhatva8kWpfskQsG36fMUEGsoMgUg4jhBBCCJGDe1FTWaXP7HB6dpR6rK0QQ4sEO0ooXxlL4QalbhlLP2Z2rNvUwRsbO9Bw3ieDhpY2meVIaEayZ4eX2aEFK9A0HS1cdUyXsZRabxqp5iuVgSPvGZIZBFm+qp3LzhtN3JQMECGEEEIIj/LKV0qa2aFk9KwQPSTBjlJyo7aZWRrJBqW5Rs96TU37J7OjZWsXN/3XB1i2c4V+zqy6klyZ14IhVOSwcyeRktkBYIQwt7+F2dqC0djcp+cRvVMoMJKvXKa3E2RsBU/+b3YGiK7DFeeNJhKzQcPvC9LWplE1uksCIUIIIYQY2qyU0bMloJRKaVAqPTuEKEaCHaXkZWnoGWUsQSezI1cZSzKzo3+CHY//tc3/EasU1I8MleZHp1GR0qA02bPDbG1BdR7A6myn49GbqF14hwQ8jhKFAiGZE2SOKAhip5dLJfuC6Lz+4EY+dFItgEyGEUIIIcSQpNyMDlWyzA43uOFmdsg0FiEKk2BHCflvZFllLG5mR84Gpbn7fJTD21s7+euGQ/79gN738hWPFgzlLGNJbFuP/8ZsmSS2rZdgxyCQLxCSGgQ58mapGpYNr7R0+EtWrG7nQyfVSuBDCCGEEEOHl9FRqmksXiaHZHYI0SMS7CglK3dJihYwnOjrAI+e/eOaA8ljAj42a2TJflRqRhj8BqURCBhoAYNg0wyiXuTZvS8Gr9QgSL5mqcUzQBRkTJtPDX4sX9XOmSfUUj8iKP0/hBBCCDF4ed/zrRJldniZHJqOJpkdQhQlwY4S8huU6oHsB4PhnA1K7fZdAJg73yc48eSyHVvL1i7e2Oj8mNTdpqQXnVFXuidIyewgEUMLOv06jMZmgifPJvH2y9R87nbJ6hhiepIBkjklZvP2Nt7bHcgbDLEVrH6vI22ZTIARQgghxGDi99cgpVFp33cKgKZpKMnsEKIoCXaUkj+NJTtLQzNCWWUsZmsL8bf+DEDnb24uWz+Llq1dLPr5JuKmQtdg7lmlaUqaysvsUEo5mR2hSv8xY9wJJN56kcCoxpI9nzi6FeoHsmbNXqpGT+X5te09ngyTOQFGyl6EEEIIcVRL7dNRhswOp2eHBDuEKESCHaVke2Us2adVM0JZZSyJbeuTNXxl7GexbnMnCTP5ZliypqQp/CasVgKViCbvA3qNk0Giug5A1bCSPq8YnDKDId5kmAOHEz0aiZtZ9vLJvxtNdaUh5S5CCCGEODqkBjhK1aA0q2eHlLEIUYgEO0qoYBmLkV3G0l/9LE6dUuP3MDKM0jUlTWM4wQ2ViKESMbSUzA7NDXbYne0Exkwq/XOLQS81+JE6ErcnE2Bslcz68MpdJPAhhBBCiIGkUoIdpS5j8TM7cMplNE0rsJEQxy4JdpSS+0aW2aAUnGklmZkdRmMzxpQzsHa8S80/fK9s/SyaJ1VTPyJEIAD/51NNZfkBmByvG4N4xO/ZAaBXjwTA7jyQa9NeSWxei7njHYKTT5f+H0NUZtZHZv+PQtkfqeUu0udDCCGEEAMmNcBRojIW5ZexuJkd4Fw01XJcaBVCSLCjpLyOy7nGyBohlJnIWqyFKtBqRpb1h3skZrH3YJzP/v3Y8v3YC3rjdWOoRNQvXQHQa5xgh+ps79NTmK0tdP7m/wKK6MolZetxIo4uufp/tGzt4vcv7yk4+lb6fAghhBBiwKSVsZQjs0NLXyaEyCLBjhIqVMbiNPDMnsaCGXeyPspo484ItoITG6vK9hyaV8ZixlHxKKRkdmjhKghWYOcIdpitLSS2rSfYNKNo4CK+cRXO2FLK2uNEHP2aJ1Vz61XH+aNvuyJm0XKX1D4fEvgQQgghRDkp28x5u487df7VNL+MRYIdQuQnwY5SKlDGghFExbqyFqtE3O93US5/WX/Qe7ayPYdfxuJmdqSWsYDTpNTuSi9jMVtb6Hjku2AliBqhopkaWjjZB6ScPU4y9SYgI/pXataHV+7S28CH1+BUyl2EEEIIUTKWlft2X6Q0KNVSy1iEEDlJsKOEVIEyFs0IY5vZmR3KjGUFBkqpZWsX//O3/QDc+Zut3Pnl48vzQy6lQSnxKFooM9gxEpXRsyOxbX2y9MdKFM3UUF2HANCqR1DzyVv6JfCQDMiYRI2glM4cxXIFPnrS5yO1wSk4WR9zZpV+PLMQQgghjiFWSvl6iTM7NE1HSWaHEEVJsKOUCpWx5GhQCjhlLGUcx7pucye2+x6YMBXrNneWqUGpW4pj5s7s0KpHYu3dnLYsbRqNphfN1DC3v+U+V7jkAYd82RvpARkpnRks8vX56Ml4W8uGZa+1s3x1O5+UyS5CCCGEOAKpE1hUGTI7kMwOIYqSYEcpFSxjCTklKxnKXcZy/Din9EMDguUaO0uyZ4cd7XLOQ1ZmRx2JD9akLTMamzGOOxNz02r0YWMKBhESm9di7XofwOkJUkJO9sYisC2igfTsDScgo/kfLvahvZitLRLwGIQyx9sWa3Bq55jsIoEPIYQQQvRIajZHyTI7pEGpEL0hwY4SSpax5GlQmqOMBTOGZpSvQan3PnjxrJHMmTWqjNNY3DKWbqfUxGx9Jy0ooKwExCMktrxJcPJpyeNzA0P2wd10/+m/CJ10blYgwWxtoXPJbTg9R7ScvU+KKdR3I7H1zWRWTkb2htHYjD5qIva+baBs4m+sIL7+T1LOMshlNjhNLXd59Z0OPxvKk2ukrQQ+hBBCCJFXWaaxpDQoxSljUcpGK83ehRhyJNhRSn4ZS47TGgyhcpSxKLO8mR3vtUYA+MrHJ1BdUb4Z3F6DUmvPJgDMTavp2PomtQvvACD+5h8B6FyymNqFdyaDILFuqKyFSAexVx8ntubprECCU0rifWAosEyUbaHlKBfKxWxtoePRm8CM52yEGhh7fHLlHI1PNT0ARhDMhPMhYyaIrf+TBDuGgFzlLs++uo/7n9pRsMwlNfDx1csmMO/s0eU+VCGEEEIMIiol2JF6u0/7zFnGIpkdQuQjwY5Ssi3QjWR35BSaEc75I10lYmUdPftuazeNY8JlDXRAsozF3POBu0T5WRJAMqKdkTmhYl3olcOwIx1p26QGEoJNM4jqAScFUA84+4pHoaJnV9QT29Y7gQoAM7sRamBEAwD66CaqL/lGVhBDmXECE07B2vqmc4wo4uueJzzjoxLwGILmnT2ayQ2VPZrsYtlw39Id7GqPSaaHEEIIIZLscmZ26DJ6VogekGBHCSkrkbOEBUiWqpgJCDnrKKWcBqVlKmNRSvH21i7qhwdp2dpV3h9hwZTXB84bcEqWRDRgOI0+tUBa5oSKdaMNr4f2nYDKmVlhNDYTmnEh8TefIzTrMuKvPYFKRNB6GOzIDJZk7l9FnBGketXwnMELZcYxho8mcPoc4m8sdxbaljQrHcJ6M9JWudNcNCAU1Mo38UgIIYQQg0ZaU9ISZXbI6Fkhekcf6AMYUiwLLcfYWQCrsx2AxLYNyYW26bxBlamM5ZWWQ3R0W3ywK8p3f7GJlq2973XRY7oBmo7d5YyXDZ/zKb9cxGhspuYziwEInTE3LUCgop0ERo4nMO4EtNpReXthaKFKCFcRHDfV2a4XTUqNxmbC5yxwnv/U7GwMO3LIP5aczDgEQoRPvSgZRc8RlBFDU/Okav7hgrF8ad4EfnDtVL44p4FPzx5NZgKXAmIJxfNr2wfkOIUQQghxFEnJ7FAlblCqpWZ2IJkdQuQjmR0lpCwT9OxJLGZrC/E1/wNA1+O3o3s/6N3pLOUqY/nLOvdHPOUdOws40eVgGGLdoBtUXnCV80bsCk45A8JVacuUUk5mR0UVgfrJ2If35s2UUJHD6BW14I60VfFIr45Pr6lzjjNHPxUvs8POE+xQZhwtGHICN8fPxNz2FrWf/RfJ6jgGpWZ8jKsL5+zt8eyr7ew/lGDUsCAXnVknWR5CCCHEsSitQWmJsi/8LA4ZPStET0hmRwnZHW0oM47Z2pK2PLFtfVbPCiDZsLRMZSy2O1JC18o7dtbj9e3Qa+vSghoevXY0dse+5AIzDraJFq5GHzYG1XUwOdEmgx3pQKusdTI86H2wg4STCeJlnqRS3Yedf/NldiSSE3MCo5vANiXQIZh39mg/0+Pck4f5yxXw6jsdLHutnRsf3Mh9T2wvb1aVEIIXXniBBQsWMG/ePL7//e8DsHLlSubPn8/FF1/Mvffe66/b0tLCggULmDNnDjfffDOm6fwg2blzJ1deeSVz587l+uuvp6tL/n8rhDhySkbPCjHgJNhRImZrC+amNRDvpuPRm9ICHsGmGcleHik9I5Q7ilYrUxnL7gNxjhtXwdUXN/RLHwEvQ0WrzT2ZIjPY4Y2Q1cJV6MOcbeyO/Tm3VZHDaJXDUoIdPS9jSV0/V7DDjjjBDuKRrG7ZyrbSSo30ihow46hE755fDE1eicunZ9cTDmpZo98sGz/o8eyr+3LuQwjRN9u3b2fx4sU88MADPPXUU7z99tu89NJL3HTTTTzwwAMsW7aMDRs28NJLLwFw4403cuutt7JixQqUUixZsgSA2267jYULF7J8+XKmT5/OAw88MJAvSwgx2KX07Ejr39EXqaNnNW/0rAQ7hMhHgh0lkti2PvkGlDqFBKdnRNXF1wNQecEXklkBXhlLGTI7onGLjTsjnHXSMP7hgrH9k0rvZ3aMyvmwPmwU9uFkMEPFugGczA43QGIfzv2DUEU63cwOp4yFXmZ2eMEJ1XUwx74PJ29nZncknOwbzXDKk7TKYf7xCOFpnlTNnV8+nnln1xHI8a5q2XD/Uzskw0OIMvjjH//IJZdcQkNDA8FgkHvvvZfKykomTZrExIkTMQyD+fPns3z5cnbs2EE0GuX0008HYMGCBSxfvpxEIsGqVauYM2dO2nIhhDhi/gU0rWSZHYpco2eljEWIfKRnR4kEm2YQ1XTnDSfXRJGJJwPJ3hGQUsZShp4d726PYNtwcj/2C9CCXrAjf2aH6mxHWSZawEjJ7KhOZnYcbsu5rYocRu9DGYuf2dGZv4wF3GBH9YjkfTf7xgvkaJW1zn4ih/1jFgKS/TwuOqOO59e2c+Bwglff6cCtJsOy4aHnd3PVRQ3Sx0OIEtq6dSvBYJDrrruOXbt2ccEFF3DCCScwZswYf536+nr27NnD3r1705aPGTOGPXv2cODAAWpqajAMI225EEIcKb+MJRiW0bNCDBAJdpSI0dhMoPFk7PZWaj55S1ZPB63C6ZfhZTMATs8KQHObbpbSi284P+pzXWUuF79nx7A8mR21owGF6jqANmxMSmZHFfow58un6sjO7FC2hYp2OYEGL9iROLKeHSSiqHjED5qA0w/Ef66MzA6/1Mgr0XGDHSplGyFSpTYxffbVfWlNTNdu7GTdBxv56mUTmHe2BMuEKAXLsli9ejUPPfQQVVVVXH/99VRUVCTHMuKkeWuahm3bOZd7/6bKvF/Mhg0biq/UQ2vWrCnZvoYqOUfFyTkqrpznaPjWLYwCTC1AZ9te3inBc4UO76QR2PTBB+hmjHrgrfXrSFTv7PO+85G/o+LkHB29JNhRQnpFFdSMyj06NVwFgIolf0wne3aUNrOjZWsXz61xxl/+68Nb+qVfB+BErgG9Jk9mR0r2hj5sDCrqZnZUVKOFKtEqqnOWsTgBCOX07PCnsfSyZxcBsfQAAJSwSURBVIdbjgJgdx0kkBLsUN2HneDL4bbsMpaM/0a6X8YiwQ5R3LyzRzO5oZKH/7Sb1993/rYsG+5buoONOyMyrUWIEhg9ejTnnnsudXVO5uRFF13E8uXLCXi9soC2tjbq6+tpaGigrS2ZQbhv3z7q6+upq6ujo6MDy7IIBAL++r0xffp0wuG+9+Bas2YNM2fO7PN+hjI5R8XJOSqu3OcoGv+AyLsQqqyhcsQwJpbgucxdw+h4BY6fegLEu+laD6ecfDKB0RNLcMTZ5O+oODlHhQ10IEh6dpSQsm3Q85xSIwy6kZbZ4f8AL3GwY93mTj913hs52x+87IfCmR34fTtSy1jAaWyaq4zF64+hVdaiBQwIBHtfxpLSUFRllLKoyGECI8c7x5YRxMicmKNVuhk6EuwQPdQ8qZrPf7QhLctKKWlcKkSp/P3f/z1//etfOXz4MJZl8Ze//IW5c+eyefNmtm7dimVZPPPMM8yePZsJEyYQDof9L19Lly5l9uzZBINBZs2axbJlywB48sknmT179kC+LCHEIOc3JS1lGYu7Hy2lQamUsQiRn2R2lJJtgx7I+ZCmaWjhqvTMgTJNYzlpopNFotE/I2c9tpttYXUdzPmHpbmZHbH1z6MPG51WxgKghSoxd72P2dqSlh3jNRDV3RISLVQJvc7siKJVDkNFDqdNZHFKZDrR68bD1jdzNChNz+zwGpTaUQl2iJ5rnlTNVy+bkFbSApLlIUQpnHbaaVxzzTUsXLiQRCLBhz/8YT73uc9x3HHH8fWvf51YLMb555/P3LlzAbj77ru55ZZb6Ozs5JRTTuHqq68GYPHixSxatIif/OQnjBs3jnvuuWcgX5YQYrBze3ZoRihr2t8RcwMb8Za/QMBpnm/u3khgTFNp9i/EECPBjlKyrWSUNQetoiY9s6NMDUprKp2Ay/mnjeCyc0f3yw8os7UFa+s6ALqX/oDAwjuyynmstm3OuptW07F1HaGTzwecIJDZ2oK18z1QNh2P3kRtyvZetoWWEuzobWYH8Sj6yHFYmcGOaBcom8DIce793D07/AalRgiC4bQJLkL0hFfS8vzadpa/1u5nX3lZHitWt0svDyGO0Kc+9Sk+9alPpS0799xzeeqpp7LWnTZtGo899ljW8gkTJvDQQw+V7RiFEMcYywTdgIBRsswOa+9mAOLr/+Qv6172nwRGjstZRi/EsU7KWEpJ2WiFgh3hKuzUH9NlGj27fa8TRPns3/fTyFm80bve2In00bsec3tK8zbLxNrfCuFKNE0vOLrXCyx4WRWEKo6ojEUfXg9oJN75X8zWFnffbiClpg6CFQV6dgT9RVpFrZSxiCPSPKmar18xka9dPiGrebCX5SFlLUIIIcTgp2wTAgaaHkgZQ9s35q73sxfaVs7v3UIICXaUlLKtvGUs4DTi9PpUQGqD0tKWsWzbG0XXYfyo0o+0zSfYNAOMoJPZkmP0rr+O190+YDiNSd1+HcGmGclzl7G9iubI7Ej0sowlHnXPt8Lcuo6OR2/CbG1BRQ4BTomMVlGTFcTwMzuCyf9GeqUEO0TfzDt7ND+4diqXnF2HnjLwQSkn4LH0dY2WrV35dyCEEEKIo5tloQUCTs++EmV2BEY1Zi/UAzm/dwshJNhRWqpAg1KcRpwqmqNBaYnLWLbvjTGuLkzQ6L//vEZjM7UL76Di/KvSSlAy1wmMPwmtpo7ahXegBYJ+vw6jsZnQWZcBUP2J76b37OjuAE1PNjINHllmh+pOKT1xs0cSrW8DYHe2O0GMfKNnU7JvtMphWY1Mheit1CwPLSPgseoDXZqXCiGEEIOY8stYAn7/jr7Sh48FIDzrMkIf+gQAlRd+WUpYhMhDgh2lVKBBKXiZHakNSmNOJoRe2tYp29qiNNWXNlukJ4zGZirP+0zBN9zAiAY0I4TR2IyKdfsBDABj7HHOOhlRazvS4UxicX8R9qRnR2LLm3S/+Gsne0MpSMQI1I1PyyzRK2uJvujUZ3eveAA0rUAZS/J8apXZGSBCHKl5Z4/m61llLRqWDfc/tUMyPIQQQojByHaCHZpugFWazA6v31/4rMsIN38EgEDduJLsW4ihSIIdpWRbRXp2ZDYojYMR8n/El4JpKXa0xeiMWEfljyStosYvS1GxLj+zA9wpK4CKd6dtY7W3glJ+n41i01jM1hY6f3MzsZVLnHIVtx+IPqoRY8pMtHA1tQvvcLIzvLRCy0JZZnpPFVLHA6f07KgcJsEOUVLZZS1O/xvLhoee331U/n9ZCCGEEAXYFlrAAD3g9O8oBa/fXzDsT2NRZqI0+xZiCJJgRympIpkd4SqIR/y6PZWIl7w56QtrnSkPGzZ38d1fbDrqfiQ5wY5ulLKxuw5id+xPCWI4gY/UgJDZ2oK1bT0qctjvs6G5DUrN1hYiK5f423si//u79Gapm99w9h+sIFA/CWXGCUyY5vYJcf8vEDDQwtXYh9rS95cjs8Mpd+lwMkaEKJHUspbUPh5rN3ZKSYsQQggxyCgr4ZSwBEqZ2eFe7DNCaG6wA0uCHULkI8GOElI9GD0LKT/mzVha48tSWL6q3XkOIGEq1m3uLLxBP3OajCoSH6xFdezD3rs5GcQIZwc7ck55CVWi4t10PPJdoi/9t789QGL725ibViWfUNcJjJvqPHcwjF49EqwEKtaF0diMMfVDEAxT9bFrsXa9B/HutP0lR88mMzvseDfYFuaWN8pzksQxbd7Zo7nmAoszT6jxl1k2/HjpDu57YvtRF8AUQgghRA6W5ZaxlK5nh5dxrAXD/ndTJcEOIfKSYEcpFevZ4f2Yd0sllFnazI43N3Xw/o5uNA10DYKGxqlTaopv2I+8gI+5eW1yoRvE8M9PSj8Op7t0ss9GsGmGU8ZimU4kW6m0UbWJ9/+W9nzG8bMw6pweIFqoEr1mpPMcnQecZQEDvXZ0RklLyuhbM578oMLJNIm/vhyAzt8tpmvZj7MyS4Toq6ZR8PmPNqT18bAVLHut/ajM2BJCCCFEBtt0ylgCpZvGQiLu9/vTvAtx3oU5IUQWCXaUkrLQCk1jqXCacaZmdpQq2NGytYtbfrkZ03ICHXPPquPOLx9P86Tq4hv3Iy/YoblBB9DSgxgAKZkdRmMz2oix6KOb/Ckvdveh9J2mjKpNNjd1AiRGw9TkmNpgBVq187x210HACTxplbV5R98qM542LcfJNHE/sGyL+BvPpmWCAHnLa4TojeZJ1Xz1sszGpRBPKJ5f2z4wByWEEEKIHvGnsegB5yJdKfbpZoVrmiY9O4TogZIFO55++mkuueQSLr74Yh555JG86/3zP/8zjz/+uH9/586dXHnllcydO5frr7+erq5BfMXStguXsbiTR/zMjkS8ZGUs6zZ3YlpOuYdSUD8ydNQFOiAl2OGWpgRPOd8PYiQzO9IblGqajjH2OIzGZjez4tnkg+GatFG3ek0dAKEZFzrbGiE/2OGUsYxwnqPLyexQkQ60ihqMxmbCZy8AoOryG/39ZWbfBJtmuB8uKU0VvDG229+m/o3f0vHwd4i+9FBWEESI3kptXOoFPRSwYlW7lLQIIYQQRzPbhEDAmcZSoswOp9+f89tBenYIUVxJgh179uzh3nvv5dFHH+XJJ5/kd7/7HRs3bsxa57rrrmPFihVpy2+77TYWLlzI8uXLmT59Og888EApDmlAKNsqOnoWnCkkUNoylnF17hsfR2f5ikevrAXA2rcNgIqZlyZH1Rph0PS0nh3g1iK6qXppmRUAZixt1K3dfdjZ73n/AOEq7MNt4AU7QimZHW4Zi4p2orsBGGPs8c6/I8en7D+e1pzUaGymduEdhM6Ym1zHHWPb+cgiava87XygKTu9HEaII+Q1Lp0zq85fZtlS0iKEEEIc1SzLCXQEjNJNYzFjaF7GsfTsEKKokgQ7Vq5cyTnnnMOIESOoqqpizpw5LF++PG2dp59+mo9+9KPMmzfPX5ZIJFi1ahVz5swBYMGCBVnbDSrKTk73yMHL7DB3v09k5RJU9yEoUbDj1RantOPC00ccleUrHi+zw9q/3blfk/wBp2kaWrgqK9iBGfej135mhaa7aYGJ9HG+bomLVjUMfdgY7MNtqLjXzKkCrbIGdAPVfdBZP9qRzDYJe6Nvkz1DVCKW1pwUnIBH9byvoY+ehD5yXPYYW09KOYwQfXXRmXWEg+ljqqWkRQghhDg6Kdt0JrHogdJNY0lEnYuD4JTIoIGUsQiRl1GKnezdu5cxY8b49+vr61m3bl3aOtdccw0Aa9as8ZcdOHCAmpoaDMM5jDFjxrBnz55ePfeGDRuO9LBzSj2+3mqKxzi0v5138uxDT0SYDET/9/c4yejQqUK814fnBNjSBi+84WSUvLz+AMeP3Ed3maZU9uX8AGhWgilAYs9WdODN9zajAq3+4xMJcHhXK20pzzM5FmXP/gO0u8vCM6+msn0LWBZ1H/yZ9X97mUSN8/c38oN3GaHprH3rXRpUiMCurRwOvsMYYMO772Nu20dTsIq2re/TtnoVU6Ld7D7YyYE1awgf2MYE4L231hHZ4wRQxu5vw4hbbMzxusfZOqggG/d0E44EGY+G99/VDA9j7+mfIbanG/b07ZwNRX39OzoW5DpHX/gIrN2qsfoDHYWGQrFi1X4aq/bSNGoADnKAyd+REEKIo5Zlgh5wmpSWLLMj7md2aJoGRjBvZofZ2kJi23qCTTPSsqCFOJaUJNhh27bzfziXUirtfj651uvJdqmmT59OOFyavhdr1qxh5syZR7z9wZd1xtSPZVKefSjb4uALoLk/iAFqQxoT+vCcAK882QrsB5z09niokZkzx/Zpn7n09fx4Dvw5iG7F0MLVnPmhc9IeO/T6CKpqKmlKeZ4Df7RomDCRKf4y59/Etg10fvBnmpvGEpxyBgBdu/9Komo4M2fNoqvtVRLv/JUR48cSeQtmnHkWetVwDr9ZT0VFgMZTpnHoOcX4KSdy3MyZmHvr6HgNpk5qJDTNeY6Odx9HhfWcr7tj41OoroPuYzM5vON/ie3dTrhhCoHOA0z/6Cf6fK6GolL9HQ1l+c7RTOATwH1PbGfZa+2AhmXD6tYRTDup4ajN6CoH+TsqLBaLlfxigBBCiF6wLSczWQ+AbfX491EhKhFDMyr8+1ogmDOzw2xtoePhRaBsogEjrb+dEMeSkpSxNDQ00NbW5t9va2ujvr6+6HZ1dXV0dHRgualdPd3uqFVk9Ky1872sZdqwMTnW7B2vcuZoHTebSXP7diQnsqQ8Fq5Ka1CqlO02eApmravXOpey7Y79yfUjh9GrhjuPDx+DihxOlrYEnQ8HvWYkqusAKtLhHo9bxuJOg0krizHjaIHcpUaaEXamtXj30UlUj8YYNxX78F6UUjm3E6KvLjqzjlBKScvr73dy44MbefbVMqV0CSGEEKJXlJVwfhfo7rXlEjQpdaYEplzkDeTO7Eh88Lrz/Vl6yIljXEmCHeeddx6vvPIK7e3tRCIRnnvuOWbPnl10u2AwyKxZs1i2bBkATz75ZI+2O1op2yo4jcV5o0mP6Kruw32e2LHvUIJRtQZXX9xwVPfr8Hg9MvTqHMGOUBUqluyZ4UWrNaNQsCP5A8/uPoTmBTuGjQYg/t4rzoNufxSteiR250F/Ko5W4QZfQtk9O9IaQWUeazAEZiz53NFO7GAl+vCxYMZR7nhbIUqteVI1d335eM6YmgxsWjbct3SHBDyEEEKIo4FtoQUMtIB7IbQUpSyJjO+lRjDnNJbAuKnuLU16yIljWkmCHWPHjuWGG27g6quv5oorruDSSy/l1FNP5Stf+Qrr1xeOJC5evJglS5ZwySWXsHr1ar71rW+V4pAGRpEGpcGmGc6bktdcE7B2tPRpRKlSire2dHHmibX8wwVjj/pAB6SMn01pTuo/FqpMz+zwMidyZFdoRgitchj24ZTMjpRghxc0sdu2AmDteMdZyTZRne2Y298C8KexaKHs0bfKTORvImuEnPHB3rqxTqxgJfpwJzvJPtS7/jNC9EbzpGquuqjBH0kLztjp+5bukLG0QgghxECzvAalbmZHCZqUOo3zk5kdmhF0vqtmCIxqBMBomi4lLOKYVpKeHQDz589n/vz5act+9rOfZa131113pd2fMGECDz30UKkOY2DZFlqBMhZvbGli23rsA7uIv/mc84CbXnYkb0QvvnmQw90WI2tL9p+y7PSKGiyccpJMzjSWlMwKK39mBzjZHaozeSVbdR9CrxoGgN2ZPqXCS+GLv/USoIj8+ZfOvr0yFiPojAfLzOwwcveE0YwwpJSxqGgn9qgKAsOdfin2oTaYMC3ntkKUQvOkar562QTuW7oDr2pKKWcs7Z/WHhgUmV5CCCHEUKTcBqXeBU5lm/StYweozIzjQDDtu6i/XjzqPDxuqgQ6xDGtJJkdwmXbBctYwAl4VJ73GcKnXexkDGj6EaeXtWzt4p7HnBGuT/x136C5kuv17MhZxpLZs8OLVucJdmi1o/zMDmWZqGiXn9kROn5W2n8PvbLWCXjYtrPArZ30Mk3Aze6IpY6ejed9boIhlFvGoqwEJGLYhmR2iP417+zRfP3yCWkZHiBjaYUQQogBZVtouuFMY3Hv91ki/SKclqdnh3/hzirRFBghBikJdpSIUjagCjYoTeVleVScf9URp5et29yJaTmXcy1LsW5zZ6/3MRAKl7FUQTzink/8aHW+JqHoAaz2HZitLajIYWeRG+wwGpsJ/92V/qrdf3wQvbIWjPQsGK9nh/P86WU0WPHCmR2WibItVMQ593awAi1chVZRI8EO0W/mnT2aH1w7lUvOrvODHgpYsapdSlqEEEKIAaBsr4zF/W1QgsBDVoPSPD07SETd9XOPpRXiWCHBjlLxsgWKZHak8rI8jjS97NQpNX463GCYwuLxos0q2pH1mBZ2moTipt8py03Ny9E3w2xtwdy0GhJROh69icTmtc4+3GAHgJbaQ8UysSMd1HzujmS9YzCcViLjBDsyMjvyNSj1jslMoGLOj0nLcI5fqxxOYsubfW4+K0RPNU+q5utXTGTOrGQQ0bKdkpbv/mKTBDyEEEKI/uT17HAzO1QfMzuUssGMZ2V2YGYHUfzvsqVoiirEICbBjlLxSiIKNCgttSnjnFGqpx1XM2hq883WFuLr/wRA5IVfZgUD/Cah3vjXAtNY0kpSLBNz6wZn3ZRgh9MUNr1cKDjxZIymU5x1U7I6AAhX+j1DlLLBSuTPKnGDHcqM+ZNd7GAFZmsL9sFd2O07+tR8VogjcdGZdYSDWlpdcExKWoQQQoj+ZZloeiDZz6+vmR1uU3wtLbMjlKeMRTI7hAAJdpSOV3bRwzKWUti4M4ICPvGRMYMi0AFugEIle2Zkzv3WwunBDv9NOpAd7Ag2zfCj5eg6+vAxzs2UYEe+ciGj4QRn3cr0YIcWqkpGw71AS97Rs+6HjRlPCXZUpr9GmW0u+lnzpGru/PLxzEspaQF4bvUBye4QQggh+oFStvNdMBBMTmPpa2aH2ycuNdtZy9eg1C1jkZ4d4lgnwY5S8TIM+jGz4/1W50f5CY2V/facfeUEKIJ5G7P6wQ6vb4ZbxqLlKGMxGpup/uTNAITO+Di2V0qS0SsjV7mQN388tTkppPfs8Mfe5unZ4Wd2JNKDHcGmGckPNj3Q59nmie1vEfnrbyRDRPRYrpIW01I8/KfdEvAQQgghys0bM6sHIJCcxtInCSfYkZbZkadBKX4Zi2R2iGObBDtKxK/D0/ovs2PVu4epCuvsac+O6B6tijVm9ctYvL4eRaaxBI+fBeEqVMc+4qufBqDr8TuKBgaMcU5mh919KG1dLaWMBTeCbm5dl3N/WkoZi+02KLWMCozGZqouvxGA8KzLsl6j2dpCZOWSHgUvzNYWOh9eRPTlh6UkRvSaV9LiWft+p/TvEEIIIfLozXe0gtzAhrn9Lez2Xc6yPmZZeBfhUoMdWp4GpckyFsnsEMc2CXaUiurfzI6WrV28sbGT7pg96H68FGzM6jYoja173vmg8UpJ8vTN0DSNwIhxWG1bkumBPSgdsQ61AWDv25YWRHDKWJzMjsR2Z1nivb/lDDSklbHEkj07AELTPoxWOSyrCavZ2kLHozcRfem/exS8kJIY0RdeSctpxzsZTApImINncpMQQgjRX8zWFjoe+S7Rlx7q8wWmxPa3nX1+8DqRl/7bWdjXMpaEV8aSkdmRoy9HsoxFMjvEsU2CHaXiNSjtp8yOVe8eRrm3h9KPF6t9JwCJt15yPmjatjgP5MnsANBHjkt+AEDO8phM5vYNyck5KUEELVQJ8ShKKczWt9y1Ve5Ag1/G4jYoDYb98hVN0wiMm4q16/20TRLb1jsBHKXAjBN5+aGCH6bBphmguVfmNb3PJTHi2NM8qZovfKwB3f0zMgKDZ3KTEEII0V8SW990ggPK7vMFJtPfVvlZHqrPDUqzy1jyZ3a4GdIyjUUc4yTYUSr9nNlRXeEEVTRtcI2dLcbev9295QQYbDfYkatnhydQNx7VsQ+A4Inn5iyPyeQ3N83oHeL0DFGQiGKMbnJW1rTc/UX80bNOz47M/h9GwwlYe7cQ+cujfkDD6eeRDIiZW94sePXAaGxGGzbWuT1pxhGPKRbHtuZJ1Xxp7jgArv5Yw6BpaCyEEEL0F2PCtOSdHlw4KyTQMNW9pZW1QWnezA63jAWZxiKOcRLs6IGe1O/5PTv6KdjRFbXQgIUXjh00Y2d7IjjptGTGRcBAGz7WvV04s8NTecEXehQQyNc7RAs5ZTQqHkEfXg9A6Ix5uQMobmRdJWKoSHawwynJUUT/8ggdD3+H2NpnMRqbCZ05N329YlcPvLrPXe8T+d/fSd8OcUQuO280lSGdP78hU1mEEEKITIH6KQDo9ZN7dOGsEGNUIwDBk2dTNed6Z2EfsyxUrsyOQO7MDhJu/7kC2SQl608ixFHMGOgDONp5PRawTKIBI/+bnzeNpZ/KWFq2dTNlXAWfv6ihX56vvxiNzVTNvZ7uZ+8nMGFasjyoQGaHPnK8u3EYO9JBT/8LGI3N2f8tvWBHrNtPAaw48+ME6idnbZ9sUBpHxbrQM4IdfqNTANuie8VPCIyZjB6qBjQnY0TZRa8eqFgXhKog2kn05YeIBoJ9/hAWx56NOyLEEjabdkVZ9PNN3HXN0AmSCiGEEH3mBg306pF5v2OZrS0ktq0n2FQ429bLwghPvwCtZhQAsbdeRquoPfLvb7mmsRhBUDbKttBSMof9BqV5enb4v2/MBFFDvleKoUsyO4pweizEi9fveT/K+yGzw7IV727vprlpaP5Q0UdPBsDauo742medhQV6dnhjXzFjdP7m5j5FqJOjbyPJFEB3Wda6XoMoM+aWsaT/9whNPSutZAVlk9i23lm3sobQWZcDUH3Fd/J+wChlQzyCPnyMt0AalYojsm5zp9/nJ24qHn5extAKIYQQHq8cREUO53zcbzL/4q+LNjBVCXdSohHGatsKQOKtF/vU+NSbxpLaoDRZUp0e1Eg2KM2d2eH3kEOBlZDvlWLIkmBHEWlX3AOB/FfgVf9ldrz4xgEicZvh1UMzMcfcviF5x7YBLS1ancn7EHHu9C0QoOXI7NDcCStZ/AalcezOA9iH9xM+uC35cGOzm7rodoYMBAk2zcB2+3uEjp+V9pw5udkhxrgTvSPscx2pODadOqWGkJEcQ/v6RhlDK4QQQvjcYIKKdOR8OBkgoHiAwExmYVh7N7sL+3bBKlcZi1fm7QdCvHW9BqV5gh1pPeS0Ar9vhBjkJNhRhNHY7L+RBEY15V1P9VOD0patXfzo8VYAfv/y3iH5Q8V5A3bPo64X7NcBEJx0qhN4yGg2eiRSe3b4wY5w7mCEFnSCHdb+7aiuA1h7NjFu1a/SIvbhM+YRnH4BaDo1n7sdo7HZb2YaGN3ob5+Pijn/fY3GZjBCBCZMk1RDcUS8MbRnTk2WW8UTiufXtg/gUQkhhBBHBy9gYOcJdvQmQJAcExvC8Nfr4wUrL4CSUtqted+RM8pV/OzkPGUsRmMzoVnzAQidepF8rxRDlgQ7ilCW6b9RWHs25U8/66cGpes2d2JaTjK6ZQ2dkbOpjMZmQjMucm5PPQstlCezImX9XM1Gj4QWckpW4m+9iL2/1WmSmi/Y4n7Y2Ptbk9vbVlbE3hjdBMrGaDgewA92aDWjIFSJvX9H3uNRsW5nv+Eq9OH16DX560iFKKZ5UjWfv6iBgPtdTQF/XC0NS4UQQgg/MBCP5Ox1YTQ2Ez53AQChs+b3qGeHFgw7F+UA47gz+/Q91Q+gpPXscLK8s443Ecm9PIVeNczb8xEdjxCDgQQ7ivCu7vvypZ+5DUoLlVuUwqlTatDcTPShNHI2k9cRW0Mr2K/DYzQ2U3neZ/ocCLDancBFouWvxN96EQL5G6Nqmpt1EvDKiTSUnh3p18JOLw8vS8MJdtSiaRqBuglYKcGSTMlgRzV67Wjsjv1FX4N01xaFNE+qZs7MOv9+wlI8/Cfp3yEGv3/7t39j0aJFAKxcuZL58+dz8cUXc++99/rrtLS0sGDBAubMmcPNN9+MaTop3jt37uTKK69k7ty5XH/99XR1yf8fhDjWpI5wzVfKorvNRvVwkb55bs8OzQiDmwlsjD+xT99TlRlzLsKl/NbQAtk9O5RSRTM7AHB/49iH9h7xMQlxtJNgRxHej00/wpDjxyyQzOzQyntKmydVM6rWYPLY8JAaOZvJG+Nqdx3In1lRBtbuTe4tBcpG07SC62vBkF/jGTzlfHad9cWsDzKvcamKpgY7nNenVdZi7Xw3b2DCC5Bo4Sr02lHYHfsKHk9i+1t0PPTPRF/87z41wRJD20Vn1hEKJv+2174v/TvE4PbKK6/wxBNPABCNRrnpppt44IEHWLZsGRs2bOCll14C4MYbb+TWW29lxYoVKKVYsmQJALfddhsLFy5k+fLlTJ8+nQceeGDAXosQYoCk9L3IF+zwJqLkfdzbPiULQ9N0CFYkAxBHKhFPNsf3uBcE0zI4LNP5XaLpYJkolTtzw/uNYx/a07fjEuIoJsGOIlTceSMwjj8LgKqLr8sdlfV7dpQ3s8O0FO2dJuecPHzIBjogJUDQecAvF+kPwSlnpByEDhW1hTcwwn5EvOLMS4iNyO7rkprZoZRCRTrQK2swW1swt65DxbryBibSgx2jUZ0HUF5gLYf4m8+7f4sytUXk1zypmru+fDzNTe70ISBhDs2yODH0HTx4kHvvvZfrrrsOgHXr1jFp0iQmTpyIYRjMnz+f5cuXs2PHDqLRKKeffjoACxYsYPny5SQSCVatWsWcOXPSlgshji2pTT7z9e3wghj+JMB8MvpraMGK5ISUIz6+WHoJCyk9O1IDNe7zaJXud9g83xuVn9nRluw9KMQQMzTHeZSSNw1j7HGYG19DHzE252qqnzI7drfHsW2YMDpcfOVBzAsQ2F0HCIye2G/PazQ2Q9UwAsPqnf+WRXqwaEbID3ZoVcOB7A+ytDKWeMTJGKmocQIRbvmTF5jIDKSll7GMcmapdx1Aqx2d83jsyKHkHZnaIgponlTNVy4Zz7cf3OgNPWJYZfmnSQlRarfeeis33HADu3btAmDv3r2MGTPGf7y+vp49e/ZkLR8zZgx79uzhwIED1NTUYLi1797y3tqwYUPxlXpozZo1JdvXUCXnqDg5R8WlnqPqne/hfcvfuGEt3W2xrPXrtm9hBHBg93beKXB+R27bwkjg9TfXg6YxUWkc3r2j4DbFjN2+kYpoNxv+9IR/ca1i/2bGA+++/RbR3c4FskDkIJOAmBYkBKxd/RoqMyMEGLtnF9UAVoI3X3kZK5z7Ap/8HRUn5+joJcGOIrzMDr3GqXFXiShmawuJbesJNs1I/ji1+yezY8c+5413wqihHezQ3TIPzHjRaSylFqiuQx82ximhKTQWFpxZ52403Al2ZH9B1sLu1fNot38lQKuowRjdRDRgOPWUup4zMJHM7KhGG+YEOOyO/eg5gh2JbRswN68FQK+fTPXcr0kzU1FQ86Rqvjx3HD9btgvbhp8+s5PJDZVDOmtMDC2///3vGTduHOeeey6PP/44ALadXoKolELTtLzLvX9TFSthzGX69OmEw33/bF6zZg0zZ87s836GMjlHxck5Ki7zHMWMdrrdhNjjxtcTPj37/HXve43YFhgW0mkscH67D64ltj3MzFmzADj8+nCqaqtpOsL/JmZrCx3tm0HZTFjz336jU3N7BR2r4cSpx/nZyVbbNg6/DJUjx2B17eP0U2egV2YHMjreewJvMO30SQ0YE6ZlrSN/R8XJOSpsoANBEuwowr+yXusEO8zdHxB75fdgJYgaoWRXZeVkdmhlnsayc78b7BjqmR0VycarWj+WsYCT9qciHah4BL16ZOF13aZT6IG0Y05bx12uYl3YqcGOxmaqP30rXb/9v4ROn5szMKFi3U6GSTDsZHYA9uF9MP6ktPXM1hY6f3OzU6eJky4pgQ7REwlLoeGUssRNxR9fb5dghxg0li1bRltbG5dffjmHDh2iu7ubHTt2EAgkLzy0tbVRX19PQ0MDbW1t/vJ9+/ZRX19PXV0dHR0dWJZFIBDw1xdCHGPSenYczrmK6mHPjqz+GqGK7KEHvZDYtj5ZMp+aDex+R05rrupOYtErarEgb5NSFY+gVY9EdR3APtQGOYIdQgx20rOjCC/Y4WV22Hs+SL5ppPZE8DI7ylzG0rovRm1lgGHVQztO5fXsAPq1Z4fz3DVOrWY86mdl5F3Xq8WsGp73SqCf2RHrSsvsAAgddyZa5TA/SJFJxbrRKqrRNM3P5sg1kSWxbX3aPnoytUUIcCY8GSkJac+tbpdGpWLQ+OUvf8kzzzzD0qVL+cY3vsGFF17Iz3/+czZv3szWrVuxLItnnnmG2bNnM2HCBMLhsH+VaenSpcyePZtgMMisWbNYtmwZAE8++SSzZ88eyJclhBgAyupJzw6nXLlog9KM/hp97dnhZP+63zNTypT9nh0pAQ2vEarXs0Pl/Y4ZITBmEgCxdX+UpvZiSJJgRxHJMhbnqro2fHQyoJHyZqP6qUHpe63dVIT0of9jJFjhn8v+nMYCbmZH1Mns0IIVhVd2o/Z61fD864QqQdNR0ZRgR2UyC0SvG499YFfOTVWsCy3kBEu0qmGgGzknshgTUrI4NB006b0geqZ5UjUfSxlFa9nwk6d3DP33GDFkhcNh7rrrLr7+9a9zySWXcNxxxzF37lwA7r77bu68807mzp1Ld3c3V199NQCLFy9myZIlXHLJJaxevZpvfetbA/gKhBADwcuOcDJ8c2d2kNKgtFBTT5WIp2Uma6FK6MM0FqOxGW14PfroScmscvBLvVObq3oZJH7Gcb7xs/Fu0J2Lp+YHa2SKnxiShnZ6QAn4ZSzVIwDQK4djHHcm5qbVVF1+Y0rPDrdBaRnLWDZs7mTjDucN7Lu/2DS0R89qGlq42vmwMQYg2BHpABSEC/fs8MpYtALBDue1VGVkdiRrJwMjx2Fuy93YTsW6/MwQTdPRKmsxP3gd88Rz08pUzJ3vAGAcPws0DWvPB3mPJ2fPGXFMu+jMOv609gDxhEIB7++IcOODG/nqZROYd3buZrhCHG0WLFjAggULADj33HN56qmnstaZNm0ajz32WNbyCRMm8NBDD5X9GIUQRzE3YKBV16Eiuaet+CNlle1m3+YuYcaMoqVldoT7PI0F28IYf0L6dzcjO7MDfxrLMPdY8pexpE2VydMsX4jBTDI7ilCxbghVogUMMEKoRNTPNDDqGpMrumUsWhmvqC97LVmacCyMifQ+QPq7Z4deWet8aFhmDxqUFg92gNNgVMW6/LRHPeXDUR85HvvwvrSovEfFIv40F7O1BdV9EGvv5rTou9naQvTF/3Zub12HFqz0g3SZzNYWOh79LtEXfy0RfOFrnlTNnV8+njNOSP5dWjbc/5RkeAghhDg2KCsBgSB61bACPTuSAYtCpSwqEU8vww5V+uUlRywe8bN9PVrAvW5t5ihj8XrG2dllLEopVDxCYNR4cpXHCDFUSLCjCBWPJK+sBysgHvF/SKZFaMuc2dGytYt1m5zghq5B0NA4dUqeaPIQ4fftCPR3z45k1oUWLJLZ0ZMyFpzX4md2aLpT2uLSR44DFPbB3VnbqVgXWoXz9+c0p1LOAyn9YjKbVqnIIefvNMdc9cS29ckPRDOR7DkjjnnNk6r5/EcbCKS8hVk2PPz8bgl4CCGEGPrMBBhBFGDtb819QSgR80s/CgY7zFhGZkd6zw6ztYXIyiU9vujkBSeyLsJ5DUpTMjvMti3u8R1Kvq5MZhxsC33URAJjp6APH5teHiPEECHBjiJUrDvZM8GNynp9PPxUNsrbs6Nlaxff+fkm9neY6BrMPatuSJeweJKZHf1fxuLfLlbG4mV2VPcgs8Pt2aFV1KQ1Mw3UjQcgsvL3WR96qT07gk0zcvaLMSZO954FAgb66EnutjmyO1L7n2iaRPBFmuZJ1Xz1sglpAY/XN3by3V9skoCHEEKIIc3JsNWxtr+F6j6UMwNWJaL+dDwVLdCkNGMaixaqgEQUpWwny/bh7xB98b97nmWbiIGysxrnZzYoNVtbiL/uNFuOrlziHGeOBqV+X49QJVpNHVplrQQ6xJAkwY4iVLw7+YPXHRulYu6X/lyZHWWYxrJucyemqfz79SNDQz7QAfjlGwPRs8O/XSSzA7dnR9HMjnAVKtaN2b4TlEr7YLPdutDEhj9nfeipWLd/HozGZkLTLwA0aj53u/+hZDQc5/x73BlOVN697/+duszWFqJ//mVyQdVw+WATWeadPZofXDuVM6cmM8diCcXza9sH8KiEEEKIMjPjaKisEa+pVCKGPszpZVW4jCV7GgsAibizT9sCVM7nyLk/90JrdmaH16DUCXYk903Kv0WCHX2cFCPE0UyCHUVkZXYkYrnLWMqY2XHqlBq8RIBjoXzF45WxaP1dxtKrzA7ng0yrGlF4vYoa7K6DWFvfREU70oIa1p5N7lrpH3pKKX/0rCcw9nhAERg90V/m/T2G3KalXnAkM9iR9gGIBl0H8o5WE8e25knVfP6ihoyRtAcku0MIIcSQpcyEU2bsfZfP0cNCmTH0YWOA/ONpvfVSy1gIOcEOFY+k7zMQ6FGWrYo5wYnMxvmapjvH62Z2pGUBe+U2OcpYUoMnWjDsT5kRYqiRYEcRToPIZM8OlUjt2ZHyxuD+iNTK0LOjeVI1dcOCNNWHj4nyFc9AlbHoqT07ijQotbucekjVdaDgelq4yunXkaPnRr7yFMwY2Bbm7o1+YESrcjprq+5D/r79iUHe36kX7Iiml7FkzmgHiDz/M2lSKnJqnlTNxSkjaU1L8d9/lP4dQgghhigrgV5ZS/icTwJQddn/ScuAVUpBPIrmlbEUumCUiKWPnnUzO1Qi6uzT/R4WPntBj7Jsk8GJquwHjZAf0DAamwk0nYJWNZyqeV/3X1fW/tzgiRaucn/fSLBDDE0S7CjCKWPxMjsqnDc2d2pGeoNSN7OjDGUsXVGLfYcSXHDayGMm0AEp88H7vYwlJXPGjcTnYra2EF/3HADdf3ywYNBAC1enfNho6T03GpsJnXU5AFXzkx+siS1vOs/zwVo/E8Qrl1HdyS7hXgaH/3da4WV2pE/rMRqb0WpGEqifQuWFXwIgvv5PMpVF5HXRmXWEg8n+Mm9s6uTGBzfy7Kv7BvCohBBCiNJTZhwCQYzxJwIQGD42fQXb9PtmaOHqog1K08pY3ItnKhF1nsfto6E69ufcPmt/KWUnmbRAMC2goWkB9JHjMMaf4CzI0bOD1P2FJNghhi4JdhQTTyljCVZgd6bUrfdTg9JNO503pKkTivSPGGL08ACVsQQrkiNlc0XQXU5ZiPvf3bYK1lymlqKEzpyX1fG64vQ5zo2UZlfm5jfcW8nyFm9muh3JzuwglJHZkatBqWViNJ6cHqjrYb2oOPZ4I2nPlJG0QgghBrEeTT8x42hGEN39rpUZzPACAlowDMEQ5vYNOfenlMpuUOoFPuIRJ9PXlXj3FaKvL/OPLd9xZmbxpj0GmDvf9bfx+725zUtVrswOP9hR5RynGUv+lhFiCDEG+gCOZk7PhJQxT6FKSPkBmauMpRyZHX/dcNA/nmNJMrOjf4MdznPXojr3FyxjCTbNIGoEnYi5l6mxJ0eAgZRmq8EKqj72j8m56C59VCNUDiO6+hkCYyZjNDa7I2kBLZkJkjuzw/0A9HqcuB+EKpr+Y1Qp5U6DqXaOXdOcshqZqy4K8EbSvrlpI5bXs82Gh/+0m89/tOGYyjYTQggx+CS2v03nI98FZRMNGHlHrCor4fSwcHu3qcjhjB05F4rszgOozoNYnQfoePSm7P1ZCUDlyeyIJYMdmoaKdRFZfj8A0YDhZmFoRI1g2n5TgxOpzNYWiBzGihz2j0XFOtFHNKRMainQoDRc6UyKAecibpHybSEGG8nsKCRjzJOWUdKQq0GpVuLMjpatXfzP35wUtzse3XpMXU31frwnPljT72UWXilL5n/zVEZjM7UL76Di/KuKzib3gh16TR3WrvezHrd2vAPRTuy2LSklK86VhfCsy/395+7Z4ZaxZGV2ZPyt+H/P1U5NZ+MpaFUjZK66KCrnSNr3paRFCCHE0S/+9kt+CUrBbFYzgWYEU7Joc2d22If24ORTkHdiC5DWs4NgskGpH+zIvIbpByVyTGnxMzvSgxFp67jbqKjb3L5gZoeXFVwJbgaKlLKIoUiCHQX4zYD8BqUZ0c54jtGzJWxQ2rK1i58+swPbfTNMmIp1mzsLbzSE2IedH1GJlr/2e18JTQsAGubuDwquZzQ2U3neZ4oGC+xOJ2BlH9iZ87Uktq3Pal5qdx0EoOIjn/X3rwUrIBjGzpXZ4f2dBgwIhrOCHV4PDy8YEqgbB3pAAh2iR7yRtKcfLyUtQgghBo/AqEb3llYwm9Xp2RFKyezIDHY43/sDY4/P3VjeY6aUu3jPHEo2KPWDHQEDv3G8d3z+QafvN19mR64m9yrW6fQV8bKIc2V2xJI9O7SQF+yQ8bNi6JFgRwFZPyIzMzvMlJ4ddml7drRs7WLRzzfxXqv7ZqQdW2NnAf/Hfm/mkJeC2dqC1bYFUHT+5uaSBFnsjpReLzleS7BpRtaoM9V9CPRAWr8PAL1yWFpqZa46Ti1cndWzw5vOkix3qclqYipEIc2Tqrn6Yw1pGR5eSYsEPIQQQhyNAiManH/djNy8F3ksp2eHpgfcBqSZZSzO936j4XiCJ54LRijn/vwMibSeHe5viHgU2y0zrrr0BiouuJqKC77gbQmAPqIha78qHnGCGqnjbHEuugVPOMc/lkDD8WCZTim4H+xIz+wwW1tIbH4DAu5rTTk2IYYaCXYUYG5/GwDL7ZTsvxkA6AYqV2ZHiXp2rNvcScJ03vQ04IypNcfU2FmA4OTTnH4dmt6vfSWcLAuvOUFpgiyhE88p+FqMxmYq/m4hAFXzvobR2IzddRCtaoQzQz2FVjUcO3P0bLAirYRKC1dn9+zImtpSA4lYzvRGIfKRkhYhhBCDiZexoNeOKpjNqsxEskF9ZW3eBqUYYQKjJ4KZIDDhpBz7caY2avmmsbiZHcHJp1F53meoPO8zaG5Axls3K4AS63ayMDSNTIGG48GME2iY6u9bC1f5wQ6VktlhtrbQ8ch3sVrfAiuB2driH2fqRVwhhgppUJqH2dpC94oHAIi+9BDBxpPTmvZoNSNz9uwoVbDj1Ck1TpRDQSioHZONAL2eGIlt6wk2zei3cgun8WgovfFoH/XktRjjnQ9M3R11proPolcPz1pPqxqWNXo2szu3VlGdo4zFDXa4jV/9EbXRLrTqEUf4ysSxaN7Zo5ncUMlDz+9m7Ubni5VX0jK5ofKYe68SQghx9PJ7bRxuK7yiGfebemqVtTl6djjf+7VQhVvqopzvUG7Ziy9nzw43oBCPguY+7n4PM1tbUP6xaVid2eNoVTySt3moXjPSeX1dB8ANtOgVNc5FME1Py+yIv/1y2v3EtvUYE6Ylj02IIUaCHXkktq1P1ri5Y0WTNX/uG0vmNBZNzxlxPRJTxlWi63BSYxXXzBt/zP54MBqb+72nRLmCLMVeSzL44Px4tLsOoVWNyFpPrxqOuX+Hf98ZMZYR7AhXpY02c/abI7PDez4Jdoheap5UzVUXNbDug/QpLc+vbT9m36+EEEIchbxgR0d2ECGVsgpndiSDGGG/iamKdEBGsMPPAEnN7NADYIScgIltQzDsB1bS+rahINqFUirtN0Wu73oeL9ihOpMl0/66RjAtg9ef9Ofdr6z1M9elQakYiqSMJY9g0wwIuGUBeoBg04zkGNKA4YwmTXlTUMouaXPS//nbPiwLPjJ9hPxwGAA9bTxaSn7wwc3AUF15Mjsqh2Fn9OzI/ABUlo19YHdav5FkGYs7GSY12CHEEfBKWvSUGO+KVe3Sv0MIIcRRwyvPUB37UV7ZeeY6SrnTWJxgR2Z/NEiZshKqQHen9mX19YCcDUqd+xXgTmPxvvOB95vDcLIw9IBzATUj8KDikeTvkAxaTR0Admd7Sh83N4vXH2fr0IePSdu2+48PYrW7F9Ak2CGGIAl25GE0NhM+9zMAVF36/zljP93IpxaqQgtWpJex2FZJm5P+14pdAPxqxS754XCM8IMdETezo/tgzswOrWq482HppiqqeLcfwAC3weq2dSh35roX8EiWsVSn/SvBDtEX884ezdyz6vz7lg2/WC7vW0IIIY4O/sVJZaM6D+ReybackvSUMpZCPTv8zI4c36FUwu3ZYWQEO0IVqEQsK9jhZRRXnH8V4Q99wtlHZqAlXiizIyXYEU3/roceTOvZkSxVca9SWCbWns3ucUsZixh6JNhRQGB4PQCG23zIi6hqFdVOtDatjMUuaXNSb7iLaR1b42aPZd6HmIp1OR9GiRh6jvISL2iR2PS6cz/alTaKLF+DVRXtcgJy7oevJpkdokQuOrOOcFDzh+a9taVLGpYKIYQoK7O1hcjKJcWn5qV8X7c78nwueU1FDS/YMcz5PpaaCZLas6PCKV2xc2R2+I0+MzI7CFai3MwOPZw+XdHPKB5/orvfjEBLrEBmR9Vw0HRU54GsLF6MYPo0Fi/YYQT9pvnGJKc3nQQ7xFAkwY5CbCcS6s+pdt+0tHAVZGZ2KDttGkZfnDTR7anAsTdu9lim6QEIVaKindjdB51lGWUsZmsLsVVLAeh68i6nqVW8G60iGexwxti6f7NuCRZ4jUyr/RrQZLBDrsCLvmmeVM2dXz6eM05IvldZNty3dAf3PbFdsjyEEEKUlDdVJPrir9OyWHNJLTvP16RUmW5AIKVnB5CW3eHsR3NGtlamZ+Om8TM7QhkP2Fh7t2B37EOrzF2inuwFkhFEKZDZoekBZ1JfZ3t2Fm9GGYv326Xm07dScf5V1C68I9mIX8pYxBAkwY4C/LQvN9jhZ3aEqtCC4ewylhJldoQMZz9/f/qIY27c7LFOq6hxriR0HQRAzyhjcRrnulcZbCdrwxlHlvwANBqbqZr//wEQPmeB33fEjnYl0xpJBjtsyewQJdA8qZrPf7QhbSStUrDstXbJ8hBCCFFSaYMEUrJYc1FmzL9gmTezw81+SPbsyBPsCIbRNC2l9DijiSmgTPf3QUpmh9nagr2/FfvATuwDu1BW7t4helVK49PUfca782Z2gFPK4pexaDq4pffoRjKQgzvVBTAmnZrsTRcMua9PMjvE0CPBjkLcN1FN94Idbs+OlDIW5XZPVrZdsp4d77U6zYW+dAxPYTlW6RU1TmaHG+zIHAnrN7EC0AIYE0+BeCStZwdAqPkjTrlKahPdjBG1mhGCQDBrRK0QR8prWBrI+GTxxtJKhocQQohScLJY3Q+blCzWXFQ86vS1CASJv7MyZxaI1wcNI9mzA7KDHX7/Pj2AVlGds0Gpta/V+dfthQGZE1fwG4lm8p43rRG9UgXLWAC0mpF+GYtWkZLFawTBTgl2JKJghNKy0TVNh2BYprGIIalkwY6nn36aSy65hIsvvphHHnkk6/GWlhYWLFjAnDlzuPnmmzFNJ5DwxBNP8JGPfITLL7+cyy+/nHvvvbdUh9R3Xo2b9+PS7XVgH9qbfBPy6vKUVbJpLO+1djNqmMGoYcGS7E8MHlq4GhXtQnUfAsjq2WE0NlPzmcUAhM6YS2DMJHe7jNGzeoDAmElpH7TO1Jb0kijNDa4IUSrzzh7ND66dyiVn16VNabFs+O8/7paAhxBCiD4zGpsxpn4IgIrzryo8Pc/7rm6ZWK1v5y578Xp2BJI9OyCjJ0cimjZhRasclvUdymxtIb7ujwB0/u5W/3nSSoyBwKjGnIeaK8iCGXPK5fOUsUBKZkfGhS0CRlqDUuIRP2CT9rxG2O9JIsRQUpJf53v27OHee+/l0Ucf5cknn+R3v/sdGzduTFvnxhtv5NZbb2XFihUopViyZAkAGzZsYNGiRSxdupSlS5dyww03lOKQSsJvSuQGO6wd7zj/7vmA+BsrnHXi7huobTuR0RLYsKWL6oqA/Cg4BmkV1ahoJ+bO9wGwDuzKWseYfLpTLxoMgz9iLPsDMDB2Ctbezcnso2hXdlCkoiZ3vakQfdA8qZqvXzGRr12enuXxxqZOvi0lLUIIIUrA66mnV48suJ5KxNwf/G5mRUbZi9naQnTtMudORs+O+Po/+QEL63AbKhHz72sVtVkNShPb1jul7RnPYzQ2U/2pW/z1AvWT87ymoNO/LTWjJOaUniRaW/L3JrFtVNdBrAO70i5saYEgpJWxRHNmiHiTYoQYakry63zlypWcc845jBgxgqqqKubMmcPy5cv9x3fs2EE0GuX0008HYMGCBf7j69ev54knnmD+/Pl8+9vf5tChQ6U4pNKwTNB0P9XLecNyL1W641L8jsslGj37+vsdtB1MsG1vjO/+YpMEPI4xWkUNdtdB4m86wbTO3y3O+mDTNA29egSq62DKPPUcwY76KajIYSIv/sppZBrrSht15jxfNSomwQ5RHl6Wx5kpjUttG+57UhqXCiGE6BsvIJCrb0baeokYujuxBICA4Ze9mK0tdDz8HeJr/gcA++Bu51/3YlPi3VfoePQmYmufxdq+AdV90M8M0SqzLxgFm2bkfB6A0NSzCIw7wX3et/MGLvTKYWnlMYktbzjbvP9azqwUs7WF+FsvAsq9MJsslyFgoOyMBqWh7MwOjLD07BBDklF8leL27t3LmDFj/Pv19fWsW7cu7+Njxoxhz549/u0vfelLnHnmmdxzzz38y7/8Cz/84Q97/NwbNmwowStIWrNmjX+7bkcrwzTdXxaOBBmnB9DcZqSasnjrjTUkauqp37+fUDzBxpTtj8RvXtHxYlDxhM2zf32X7n2q8Eb9aE0fX9+xoC/naNShLmojh9GUjYbTHXzrK8s5eFx6bed4gti7tnJg3etMADZu20mkO/15a7e3MgaIvvIYkVefBODgoU7eSTm+hphFoGMv7/Xzf1f5OypuKJ2jWY3wxsYAtgLQUMCy1/azfNV+5p9hcdZxR7bfoXSOhBBC9I6KdqT9m1cihj5sFFrVCMwdLdT+w21O2cueNemZGIDVtg0Ac+d73rOAZRJ/Z2Wy54absaFXDsNs35n2VEZjM4FxU7E72qn5xKKs8prA6ElYu94n8c5KEhtXUbvwjqx1tMratNGziXf+N+1YEtvWp23j9AOxk+cltWwlEISUqXsqHs1dxiKZHWKIKkmww7ZtvxEOOI10Uu8Xevz+++/3l19zzTV87GMf69VzT58+nXA4XHzFHlizZg0zZ87073e3ryG2M5iybCbmSdOcNxVdJ/rCLzn5hOMxxp9I59YVWImDadv3llKKn774DhpxNA2Chs68j5xw1DQpzTw/Iltfz1Gk6x2i2/7m39eMIJPOncvxGR+EnZsmYHe0M6oGIsDx9cMJn5H+vN0db+EOSUNTNiibsU3HMTnl+LpaX8Dc8U7eYzZbW0hsW0+waUbhethekL+j4obaOZoJVAzfx/1P7cDyv49p2Aqeet0gYdRx0Zl1vXqvG2rnqNRisVjJLwYIIcTRxMuq6ElmB0YFgeEjsHa0pH2fMSZMS1vXGH8SAMFJp+LnOQQMQtPOw9z8un8/2DSDeMf+3IEWpQiMmZT7e1PYKyHJHbgAtxdIaoNSr3mqpmdli4CTTRINGH7fESwLs9V5nVogmBb8UImIP3Ah7TmDFRCXzA4x9JSkjKWhoYG2tuTc6ra2Nurr6/M+vm/fPurr6+no6OBXv/qVv1wpRSBQmokmJWFbfqMij9HY7IxqanDS0PwoqG33uUHp8tf207ovzvmnDefqixtk7OwxKHU0rDH59JwRf3CmtFiH24i8+GsAup/7aVZaY/D4Wck7bl2rufO9tPUKNShNbH+bjocXEX3poaIz7IUoJl/jUifLo51v/7+N/MtDm6W0RQghRI9431+KNVpXZgwtGEYLV6Fi3aiULIjMRqGB8c73e6OxGW34WPTRk6hdeAehU52Lscak0/zvZioRQ0W7SGx/K/35Iof90bWZwief7/QFyRO4AFDKxm7f5X/vsvdvJzBpBhXnX5Xze6HR2EztwjsInnyBs/6BHcnvbVkNSnP37CAYTpbmCzGElCTYcd555/HKK6/Q3t5OJBLhueeeY/bs2f7jEyZMIBwO+ynHS5cuZfbs2VRVVfHzn/+cN998E4CHH36415kd5aSsRHISSwa/G7NX36bstDFOvdWytYsfL90BwMq3DnPqlBoJdByDUoMd4TPm5c2m0KtGQLQjmXppW1kz5oMTT0arGkFg7PGEP/wPAJibVqcFLrRwddYHvyf+9otgm05qZJEZ9kL0RL7GpQC2glfePsyND26Ufh5CCHEMM1tbiKxcUvAii7ItVMz5nLCLZHZ4U1Sc/mYqLYMhs+eGFgj5twO1o9GrhjmBjc52AEInz8ZobHb6ZGx4AYDO39ySdqx2pMNvcJrJC0zkC1yYrS1YW9ehoh1Or5B3V2If2kvopA87F1vzfC80GpsJ1E/C7y3ofm9TsW5U10H/+FS+aSzBMEoyO8QQVJJgx9ixY7nhhhu4+uqrueKKK7j00ks59dRT+cpXvsL69c4PpLvvvps777yTuXPn0t3dzdVXX00gEOBHP/oR3/ve95g3bx5vvfUWN954YykOqTQs0+/0nMl7o/Ca+Si3j8eRWre5061nB9NSrNssTSOPRakNRPONJQMnswOl/M+0fFcH9BH1aFXD/Q/p1LRJADveBcrG3Pxm9pO43b8L7V+II5EvywOcEbXLXmvnRpnaIoQQxxyztYWORxYRffHXBbNKU7M5imZ2JGIQDKOFnQtKXnN3Z9v0QIlmJDO6tapav0TG7tgPgF47CvCmrrgXilK+VynLhFi3P7o2Fz9LPEfgIq3/hmUSW/20cywFxs56gk0zwAj6WSN6ZS3m5rWoWKd/Lp0GpTmmsQQrZPSsGJJK0rMDYP78+cyfPz9t2c9+9jP/9rRp03jssceytps1axZPPPFEqQ6jpJRlps3ETuNmdvhlLMru0zSWEyY4b2IaEDQ0Tp1SU3gDMST548I0Hb1ufN719OoR7o0g+vAxVF96Q84PTb2mDvvAbvRJM/z9eoELs7WF+OvOVKTOx26jduGd/j6UUpjuqGV9eD3Vl/9zyXp2CAFOlkfzpGqmjqvkx0t3+MFej2XDfUt3sOrdw4ysDfa6p4cQQojBJ7FtvTMNEfL2tICUjAxNL9igVCkbzDiakRrs6AJGA2BHk/tB2ZhtWwkNd0rxtcpa7J3vO+u5wQ7NDXb4fTKsBOgB/4KQF3jJl9lRTHK/Jmga1jan91L3sz8mMHJ8we9iXtaI12stM3CS2LY+f4PSYFgalIohqSSZHUOWbRYtY4m/u9KJOttWn3p2BNzLmxfNHCm9Oo5hXhmLPmIsmhHKv17VCOeGFSd44jl5P/y06pHYXQf8fYXP/bSfNplvFjxAfP0L2Ad2ghFCmQkJdIiymXf2aO7+RyfL49zm2vR+HgpeaenwMz2kvEUIIYY2Z3Sr+0FQIKvUC3Dow8ZklaKkSThNO50yFiejwSt/cfbjbetE3LsevyNZ6us2ClVKZWV2GI3NVH38WwBUnPfp5MUit7Fovp4dxaTuNzBxelawoifbe1kjwaYZyYu2egBj4nSnpCfX6NmgTGMRQ5MEOwopUMZitW0FkjOvVaQDrQ9lLO+2Oil1X7lkvAQ6jmF+GYumF6xV9TM7gED9lPzr1dShug858+KDYSrPv8r/QPbTHd3nS505373sP5zltonqOpCW8ilEqXm9PG69+ric/TwgWd7y7Qc38l/P7uCldzQJfAghxBBjNDajj2oCoHrBTXkvtnhBCn3kOFS0M2fvMUjJwA5W5C5j8fp9eNmFKUEFvbLWydxIxLA790MgmFaeEjzemQiW2vDT21+hMpZiQtM+AppOYNio5MIjKCc2GpupuvRb8P+3d9/xcdR34v9fM9tUXWRLbrLkChbghk0xARsCmGJMCCEJIZSEXMg3l/J95L4/CDjO5cjdBZKHDy4kQAIhdwmBJISAKcE2tum2ca+wbrKKZcuyZLWVtk75/TG7s7vaXRVbtmTp/fzHW2ZnZ8er2c+85/15vwHPpbfhHDUxZXtjFFcWaKGM+1GIs5UEOzph6pkzOzr23zYDbac0jWX/YT9jCtzk5/TazCJxFjIaj9j/djZXVUkKdkzIuD41dzgAWu1+1KGjklpAx9Idlax8HMXn2QOKpIyP6NwCvbn2ZD+SED2SWM8jXdDDMOBvHzSweo/K/dHAx1/fq5PAhxBCDBSGNY3FMXxM5kWiQQV1+BgwjYwXZWIdRpSMNTuimR0JtS5iQYVYwMIMtGL6TqDmFySNo5SsPHC6Mey6aGBEMztOdhoLWHVD1OGj0Y6VA+Ca9pmM3fm64j5vvlWjI+jDDFu12NJNYzH8LQBoVVKMXgwscmbdmU5qdrhKZxBUHfZJoamop1SgdE9lGwX5LrxV7ZLZMYjFg2h0OlfV+hFVQOm8MJeSZwU79LpDOCfMSnneWVyGc8IM9OgPKoBzzNTYq61gnx7BaDwKoyafzEcSosdi9TyumV3Amu2NNLVG2LjX16Guh4IeDXwAOFS49fKR5GY7pZvVIPPrX/+aFStWALBgwQIeeOAB1q9fzyOPPEIoFOKGG27gBz/4AQBer5cf/ehHtLe3M3fuXB5++GGcTidHjx7l/vvv58SJE0ycOJFly5aRmyvfISH6Qiw7orPxTWyZWEDEDPggK029u2jRzXg3lg7TWAI+lKxc8r70sF3rIjbuigUsjKAPw3cCNW9k0qoVRUHNG47Z1pSyXacS7ABwjBhP5MBGALI+82WcJzkGU1QHztFT0Gr3x7utdMjs0Gq8hHesAqDtpX876cCKEP2RZHZ0ppNpLM7iMrKu+rp1xzQwW+rsiGlPbfi0hZZ2ncpjQR56rlyuUA5irtIZXfZfB9CP7gdMME3a/vKvGTNA1GiwA11DHVKUdhnH6CkYzcfiRbqiATz3jGvI+/K/WS9vPHrSn0mIk9X59JbkiqaxwMf/rjrG//fbg/z0+Qo5lg4C69ev56OPPuLVV19l+fLlfPLJJ7z55pssWbKEp556irfeeos9e/bw/vvvA3D//ffzr//6r6xatQrTNHnppZcAePjhh7njjjtYuXIlF1xwAU899VRffiwhBi3TNOwgh9lJS1l7Gsuw0Un3U5azp7EkBjuSMzuUrLy0HVKULCtgYfqtYEesOGkiJa8gKbMjts3qKUxjAVBjHflUJ46RJae0LsfYc9CPlRPcZDWEiNUdjOmshpsQZzsJdnTC7KRAKWDN44sv3WXrq0ze3dEUXQNENGk7O5h11X89JumHqJMfptg0FgDH0ML07znauloQWPt7tBovod3vgKLivuAqXBNmQVY+kX3rOq0hIsTpFpve8rXrRvPF+SNTWtYmMkzY8Gkr9z9zkJ/+8ZAUNh3ACgsLefDBB3G73bhcLiZPnkxlZSWlpaWMHz8ep9PJ4sWLWblyJUeOHCEYDDJr1iwAbr31VlauXEkkEmHz5s1cd911SY8LIc48M9huF+U0OsvsCLaBO9uuYdZVsENxeqIZDUpSsMMIttlBjY5iRUbNQDSzI02wQ81NE+xQHWnbu/aEY8R4a7uz89FrD57SuhRPLhg64W1WBpzRWp/0vKtkevx8R1V7XBtEiP5MprF0ppPMDoi2h7KnsihJdRR6IhSxDuqqIm1nRXRqSRfpg66S6QSdbmuqVScZIEpCsEMdmj6zw4z2iQ/vfJvwnrWg64BJ20v/Rs6190GoDf2YD9+LSyS1UfSp2PQWgOGOY4TdxbQHNF75qAE9TU013bC6uQCs2tLIxefmMzzfxZSx2RysDYBJn7S01Wq8KenS4uRMnTrVvl1ZWcmKFSu48847KSyMB3eLioqoq6vj+PHjSY8XFhZSV1dHU1MTeXl5OJ3OpMeFEGdeYjZHp5kdAR9qdn48+yLTsonTWBQFxZOT0o1FSTf9BVByrOwMvbkWtBD6icNoNd6k47aaNxytcod93wi0omTnJ9X2OCmxafLtTac8/op/3mgdthM1Sc87i8vIveUB2v/+n3gu+pz8LokBRYIdnTB1DVRXxuedxWW4L1xEeMvrkJ2PmjP0pN6nui7E9Im5zDknX+aai27p2Es9Y+tZpwslO98aFGQIdujHK6K3TDvQYT2hEd673ur/Gb2fqYaIEGdayQiYM2cUAPPOG8auijbaAxp//7ChQ20PS2LgI1G6IEhTayQlKNLxdmtAP6njtVbjxffCQ2DoBB1OCSD2kgMHDvCtb32LBx54AIfDQWVlpf2caZooioJhGEknILHHY/8mOpkTlT179pz09ne0devWXlvXQCX7qGtn4z7yNNcwLnr7yKH9NKvpP8OouhqchoOKA4coBSr3fYIvkHo8zqnzMhrwHjhEuM7PeMVJ69HD1Ef3TaC5gXD+aPan21eGxiSgaef7ZAOR8i2EK3ZQe9HXCA2zppYMaw1QEGpn26aPMR0uRh09jAvXKe/7YQd2MxxQAFOLULVhJc2TTq4znscYztjobQWo0bJp67h9hpOJisqx4/U0dXjubPwenWmyj/ovCXZ0xoiAo/MOK87RkwgDhAMn1Y1l3Z5mjjWFufS8IXz5ylEnt51iUOpOBggA7lwI+DD8rWmfdpVMJ2j9nFrfd10jVpzUPe0ytKqd1hWGk2h7JsSZkJjxMe+8YXZR0037fGkzPhJlCoJ0h6rC1bOH0+bXMFG4MP8I7rpPOKROITLyHKaOSw2WzKhby3Q9ggIYmsbRnVspkWDHKdm6dSvf//73WbJkCYsWLWLTpk3U18fTtOvr6ykqKmL06NFJjzc0NFBUVERBQQE+nw9d13E4HPbyPXXBBRfg8Xi6XrAbn2fOnDmnvJ6BTPZR187WfRQpN2mz6nIypmAIkzN8hpZtz4HD5PxxBbQBY4I1TBp1Zcq4KLSnBf8OOG/mLBwF42jdNpycvGxK5sxh69ateMwIeWPGMz7D+zS9n012y2HAChQopsHk7AjZ0eVDzkb8B9Yyc2opjuFj8Hn/Bp6iU9732qgcfNXr7Szz0nnXM/mkfyvm0HLobYyGagCmXH5j2k43LZtGMipbZVLCtp+t36MzSfZR5/o6ECTBjs7oOoojc2YHgOKJpr7pkR53Y/FWtfPoX6wDzz82nmD+9GGS1SF6lVbjxWy10rHbl/8cNc1VZGdxGY5x52K0HCf7ynvwv/k4rvMXkDXnJpzFZZjhIIG1vyP76n+SK9Ci30sMfHir2nsU+Ogpw4DVW62aS9PUQ1ya83sUTGbi5GdV32DF5tSicqrbYIbHSpiK4OCxj4dScOIQw/NdfTKl5mxXW1vLd77zHR5//HHmzZsHwMyZM6moqKCqqori4mLefPNNvvCFLzBu3Dg8Ho89MH3ttdeYP38+LpeLuXPn8tZbb7F48WKWL1/O/Pnz+/iTCTE4GYnTWDLU4dBqvBj11YBJ219+bD1WsQPf4U9Ts+ViNTti7VYTp7GYVr09tZPOKWp2PkbLcawOeErKhZ9YIXizrQmGj8EItHbaMre7upvB2+31jTuXcDTYka71LIA6pAijpT7tc0KcrSTY0QlT76JAKaBkxQemSg8zO3ZVtKHp0flzulWYVAa6ojdFqnd3axqKY0QxRmu9Xegra84iezn3tM8QWPu7U59/KsQZli7wkZhl0ZtBkBvd63Aq0RWZGmXOQxwIpwY7hijWINtA4ef+e9hnlEA0s2T11iZ+/s3J8jvQA8899xyhUIhHH33Ufuz222/n0Ucf5Xvf+x6hUIgFCxZw/fXXA7Bs2TKWLl1KW1sb559/PnfffTcAP/nJT3jwwQd5+umnGTNmDI899liffB4hBju7deuQQsxg+qy7SOVO4lNu9fgTacY5id1YAKtmR7sVpFb0MBh6xpodEG0h23Ic9/SrUEeMTwk8KHkFAHaRUqOtCcXhSqntcTK6ncHbDY6RpfZtJUPxVHVokXRiEQOOBDs6o0dQ1O4HO1C7l9nhrWpnV0UbkYh1oFaQwqTi9OhuIVM1dzhmewtGtFd8YmFTZUghuLPRo1cEhDgbJQY+EmUKgnRWsyM3S00qiqpgUKpa7ZlNEzSceLVJabdjmqMSzXTgVHR0kgPkmgS9e2zp0qUsXbo07XOvv/56ymPTpk3j5ZdfTnl83LhxPP/8872+fUKInjEDrYCCY+gojED6zI5Yu1lryq3DOvAaOqiOlHGO3Y3FDnbkYjRax2s1ErAe6yTYEWtc6RxXhufCG1OfjQY7gpuWE9yxEgKt6IHWflfU3VEYC74r4HKnXUYdWoTpO4HZRYMGIc4m8k3uRJetZ0mYxgLdmsbirWrnwd+VE9HiFfQ+e+FwFl08Qga4otd1u5Bp7jAwNPQT1rzUxJa1iqLgGDkevV6CHWLgyRQE6UqsKOqQbAfO3a9TeLyFkGsorkgrK0Z+k6mFM7ihY1HTg9uZVHWE5hEzKDixk2vH1nHoaKkdNHE6JOgthBjczIAPJSsXJWcIRoeuITFKtJ6ee84iPOdfiRHw0f63h3EUlhKp3kOkaieu0pnWmCcStMbn0YuXiifXnsbiiHVqyRDs0Gq86HXlAPjXPIujaGLKOEqPBk70I97kF/ezou52Zoc7CyXD+Yo6tAhMA8N3AscwqSMoBgYJdnRG13s0jaU7BUp3VbQR1pJbBXy0u5lFF6f27haiN3QnDTIW3NCPV4ArC8WdPJ/TMbKUSPmWbr+ntNYUA10sSKLVePG98yoAHsMPmHyxcDdZF03CWTzeXl6r8eJ770nApKD5E8jKZ75rO9OvHMGhqhPUZZ/DrMvnStBbCDGoGQGf1bo1Oz9jzQ694TCgkPPZr6O4stBqvKAo6McOoh87CEDQ+Vfy7/iZldkRbTsLoHiy7WCHp6nSek9fY9r3SZrSkSF4oR1O14UptbZHX1PyR1hTeUwz4xSbWNc+o+W4BDvEgNGzipqDTXemsXhysCaikDFSClZGx1/fq6OmPpTyXESzUpeF6CtKtFaHXldhF9tK5Bg5HrO9Cf/7z1uDCqyTt8D6l+z7MVqNF9+fHiT43h/wvbgkZXlPc9cZIpnWLUR/Y9XFiaZm6Jr1mPfDpO++vZweiS6nQ7ANo6GKoZufY/bx5Vx/5L+Z6pDsKSHE4GYGo8GOrDy7fkdHen0V6vDRdqFN6zjccSErOKE3H7NP8MHK7EDXCG55k5F7VwAQeOe5tOMNV8l066KnomYMXtjLxKgO3LOv71dTWAD0I3tBC0MkmPL7FKMOsYIdoa1vpn1exmbibCSZHRmYhm4NYLvK7FBUq9hRqD1jZkds6kpiRoeqgKooGKYp9TpEn7Oribc3oQ5P9+NsBfRC6/5KaOMr5Fx7H/5VT4OhE1Qd5Fz3bTyzbwCigw7DOumLDTYAfC88BIbOGEVFO3daxkGAVuPF9+IS0CIEna5+N2AQg4dW4yW0ey0AnulXp/0eWq2bo1TVmjcOKVcBk1o8q6rVyiVRP0t5FkKIvmAGfCg5Q1Gz8kCPYEZCdr2NGL2hGsfIeAFoqz6ZC7QIdtRDdWC0NqAdsPrYxmpoKB4rey7w9m/iyxrpj7/dmQrsLC4j/6uPdvlb0deSAkIZfm+MthPWsns/InJwE/l3/Mx+TqvxWuM4XZOxmTirSLAjk9iAtRsFepSs6Py/DAVK001dAVh40XCKhrmZMTFPUpdFn0osSKrmDEt5Pt4KzgRdI7x3ffxvxNDxr3oaR+EEnMVlqEMTUh+jxcLC+zbYV7UV00yfChqd+mK0HLeuPoCcAIo+o9V48T3/gJ21Ed61hvyvPpLyXVRHFAPgnDQH97nz8L/9W7sVeVJ7wmGjABPnxNm4p30G/+pnkgfm/SzlWQgh+oIZaMVRMA4ly2oHawZ9ScGOSPVujBOHcY6ZYj+WGJRAdRJ85zlweghv+0d8xXqESPVuzEg49k7YPeY6HK8TdWcqcG92TTld7IBQJwXrtSN743diF6s8k4GO2YkyNhNnDwl2ZBJNR+5ONeJYlDhTZsf0icmBDEWxuq9cM7tAghyiX1Cy8qziXYaWdhqLe+rFhD5+2c52ck2ei1axLb6AYdg/fFrFdvvh7M9+w3rsaPwH1ExTLT0xm4PEFrdplhXiTEiangKgRwh8+CLZV9yRNMAzmo8B4Jl9Pe5zL0MdWUrbX35stStMXN8h6+8l+6qv4xw9GUfhBCLVuwl/8j6mv5m8LyyVgaMQYtAz2lvQm+tQR1g1j8xAG+SPBKyxQtuffwymSfiTD/DMvtE+bsYCDlqNl6CiQKjD9HBFRc3Ox//hb+yHTECJZqcO9ONvd7JUXCXTCSpqfKxXMh3q/Nbrx18QX1DNHBwSor+RYEcGZjTYQRc1OyBexTlTzY6KWivJecakXK6cMYzWgC7ZHKJfURQFJXcYpq8hKcsjxllcRvY13ySw+rc4xk2LX2WJ/SgqCkpWHq0v/gi9cof9OjPYai0WnVer5AyldvoXGdHhRzZSvTt+lduMZ0G55ywa8AMQ0T85x56b8phWsR3f4T1J6buxYEesFaKiKFbqdWs9vj/9EPfMhXimX01o97vgyrLbIMYG5magldDWf+AYl/p+QggxkHRVvDxy+BOIBNGPeOOFRre8gWfGNTiLy6LZBdHxuWmkzS5IKioaEw1oGAFfwhRChcCISYxaNPADHTFdZaA4i8vwzLuN0PqXyLnx+9aydVsBki6EuaZcMmj2mTj7SYHSTIxYZoery0XtjixpMju8Ve089cYRAPZW+5kwOpsvXzlKAh2i31GjRUrVNMEOAMfoKYCCXrXLqtcB5HzuftShRShDigi8/ZukQAeAdmQfYFX2BjD9LURyC1PW7SqZnnYamOlrOMlPI8Spif0dOEpn4hg9NfqomVSHBsBoqrWWiwY7kjJCDJ3w9hX4XngQvWoHRIK0/flHScXdHAXjQAtjtsp3XQgxcFk1Hx4k+N4fMxbIjOzbEL8TDWqEd6yyl3eVTI9nf3ZaMNRlFxV1z76B/Dt/jmf2DckFR50umqZcJSftHXhmXQeQ0glHr7WCT+rQUWhHPiWw7q8ZC5VGDn+C/70/SCFT0S9IZkcGdmZHT6axpMns2H7QZweRNd3quiKBDtEfqXnD0Yl3ZunIaq8WL+aFouKe9hn0YwcJbXw1OeU/Wogx9rcRC3YAeJprUtbtLC7DOXkuWjTVn2iB4NicXSG6q7faHhut1nc2Z/6doCj4/vRD63vZYWqV3nwMJWdotDNXNA3Y0aFQnq7HV9xhrrM6fKz1cONRu+2fEEIMNElZGRlqPtjT/xTVCmoYOolB5uzLvoQ6cjyEAuTe8kDmgqEZpmt0fC4UnaIh4tSho1ByhhHatgLF4WTYob1oo3LQjh0AhxPnOZcS3vwawQ+eJ+hILVSq1Xhpe2EJGBqhTculkKnocxLsyMQOdqSvw5EoNo0l3ZVplyvWlhbpuiL6tdjkEdPfnPZ5+yQuWqBKHVqEojpwjptGyIynheJw4J5xLZEDG+0rMHrLcRxjpqLXHmRY5UcEtw3BDLYlDUQURUUtGEvuDd8jUr2b4Pq/omSogyNEOr1ZLT4WoFOHFqEOGUnuF5bS/reHrYF24nJNx+wpLBAfTId2ryW8Y1V0mpcKpp62faGjYJy1nsYjMHHWSW2rEEL0d0k1HzIVZNbCgELWFXeg5AwlsPLJpOVNXcNoqsVzYedTXDubrpH0XHSKhojTj+zFDLRi+pvxr/g1wwFfxQeoQwpRsodg+lusBU0zbdAqXUc+CXaIviTTWDKJFShVuzGNJUOBUm9VO+9sb8bjUrjrmtE88o3JktUh+iWtxmtnVfhX/zZt6qGzuIy8r/yHlR4KOMacYz2R+L1XVXIW/h9yb/gu6rDRmG2NABgtdSg5QwHIaqwgsPLJlFRWo70JNXeYVR/ksi+hDh2FIdNYRA9EqnZGg3Gp0016ymg5DqoDJTpPWc3OB0XFqDuU9L3VG6pBCyf9zTiLy8i94btkXXUPAI7CElAcZF1xR0oARskvAKcHvenoSW+rEEL0d45h8cy1nOu/k/YEWK+vRB1RTPblXyHrwhtxlM4Cdw55X/lPnMVl6PWVoIVxjj3nzG34IGNNxYzXTlMAtDBG4xHMtkYiez+KL5wmaJV0v5MuN0KcKRLsyMA0ou2Vutl6FpILlHqr2nnwd+VUHgsS0U1mTZaCpKL/siLx0ewMXc94kugquQDX5LkAmIEWtBoven1VfAHTtNvUqnnDMdqaMPUIpq8xmtZPvNVbhxNSs705qV6Imj8SQ+oYiB5Q3DnxO6dYLV5vOY46ZKSdXZQ0ANSsFoaR6t2Y7U3oxyvSzkH3XHC1ta7jFTiKJpB9+VdS07YVFTW/gMjBLTK/WQgxYOlNx+J3Ek6mk5Y5XoGjaKJ9333uPAj7UfMLAAh/8oH1csn6PG1cJdPB6SJxtJbEMFCGj04KQiWy2qxb3DOulawO0eck2JFJT1rPpilQ+o9NDYS16MHchF0VbWleKUT/YP+4pUmz7yhWY0Cr3IXvxSXWFW+nO+W1al4BRntjNGBh4ig+F5wukoY4qorRchytxovR3pxUL0QdMlIyO0SPRCq2W8dhhzNtV6EYrcZL+4pf077i1xkDDEbrcdQh8SuR8QEggInRcpzQljfjL0iTSaLmDbfrcDjGTMm4LUZzHUZjTcaifUIIcbaLda4C0OvKU543Q36M5jocRRPsx1wl1tSXwDu/J7R9BaFNrwLgf32ZHCtPk9hUzKwr78Z1zqXJYzYUa5w3NRqEGjIy5fVa7YH4ndiFYyH6kNTsyCRWUK5bBUqjdTiimR3eqnbWbmu2n3eoUqtD9G/d6b9uc8VP+NA1jIAv7WuVvAII+dEbDlsvK52Fe/LFVG1YyYjabaA4MP1NhLevILx7LWhh1OhUF7AyO8z2Zkw9krYrUrh8K+Fdq1HcOXhmytWDwS5StRvt4Cb7vtlaj++Fh8j/6iMpxdN8z//QqqEBhHetSVkGrGksrgmz7PuxvxH/mmfRj+4jvGMl9vWCToKEyrDR0HI8/jvRcburdxMvZCrzm4UQA5MV7FBwjJmKdiw12BH+5D0g+SKjEbIKiEb2riOy/+N4IXQ5Vp5WsbomWo2X0MEtKKYBqop7xrV4pl8NLjfhTa8SeOf3ZF30uaT/B/3oflBUHKMnozfK9EzR9yTYkYEZLcKI2vPMjq0HfPHngGvnDpcpLKLf66r/eox70lxCH79iZT9FT/DSvVbNs9JOY/M7jYAPT9nlNE/yM0oNoFXvigcVY1NcEqexRK8YGL5GHAlpkRC9Mv/Xf7Xvh3evJf/OR2XgM4iFd69NfVCPEPjgebLn32V/N8L7NtiBjtgyHQfNsalXHbujOIvLcE6cjX50XzQNWweHi6zLv4KrdEbK90+r8aIf/gSA0JbXcZ87L2WZeOFfrcusKiGEOFsZzcdQh4xEHVpI5MBGIoc/xTX+PMA6Vvrf/i0AgQ/+hLP4POtk+/CehBXEjtuKHCvPEGdxGbUXfY3J2ZGki1mR6O9axPshkQMbk2pRRSq2WR3Kcoej1+7vs20XIkamsWRi9Hwai1axHa3GS5bb2q2KAm6XwjWzC07fdgpxhtkpjgvu6rTbRSzYEd7zDgD+N/7LTjt1jBiHGWizu7XE/lUTp7HkW8EOM81UlkisRW2MoRH48AVJax3AtBovgfUvZf4/tgPTyfOMtcqdydND0nTNMpqPJ603fGAjYGIaesqy7slzk9qMO8ZMIfszX077d5BU58NIXwunu39PQghxNtObj6Fk5xPZvxF0jbaE43K6Dh4QnT7oSD62ey77khwrz6DQsBKyL/tScoZkNNgBJP1/Rar3oB/dj9nehHZoq5WdG5L2vqJvSbAjA9NuPdt1sMNorgcgcmAjvheXYBzdi8sBd149SjqwiAEp1jGls8FGLNhhn+wl/CCqI4qxUvejJ6Yeq7CkkibYEdzyZsoJruLOSnk/rWK71DwYoGItZYPv/QHfn35IaPuKlGVMfzNK/kiyrrybnBu+i3PihfEnE757RnMdZOfjnnUDarQQXnjHSvu7o9V48b+2DIDQxldTvk/O4jI8n7ndvu+ecnHG7bYH6l3UwunO35MQQvRXkcOfdh6MJnrsjbXhhtSgRmw8kHCsdBaXkXfHz1Cy8gATddho3FMukmNlH3OVTI/XKUz4/wrvWhNfKFr0XjqNib4mwY5M7AKlXbee1U9UYx2krRoGwYpdFA13M3tKvgQ6xKCl+04kP6A67B9ER8E467HYoCdoFfBN7MZitFmvj3g/SAliGG1NoDpwz7ou3gIXTrndqOifwvvWR1vKAoaOf+VTjPjk9aTvhFa7H1fJBWRf9iU8s28g+4o74tke0e+eaRpolTtwT76I3Bu/i3vaZ6KvjncGilTvto//mbIxsi++JT7Q82Q+xkvWhhBioIsc/pS25++3gtEZLjiYkaDVil5R4sdlRYmPCUZPBkXBWTI95VjpGn8+rgs+C1gBE7mo0fecxWXk3Ph9ADyXfMH+/zKjY7lYgB8g+PHfM/5/aTVe/O/+r/x/itNKgh2ZxAa73WhvldjJwlCcbGkr5WhDmIeeK8db1X6aN1SI/smqth6bUqDgnnGN/YOoxoIdkNRmTsmNFyhNqujdIYgROfAx6pBCPDOuJefa+9JeYRADh9FyPPkB02BIzRZ70Gu0NWL6TuAYM9VexFlcRs7n7gfAfeGNOIvLCO9+FzPQihKtxeGaMCvpGK9m51vfn9jXNsP3SW+otjOWAmt/1+lATbI2hBADWWTfuvgdLUIoTf2k8L4NAOi1BwETJW8E6rAx9nFRP14JpoFn7uK0x0o1Oz96y5SLGv2Ee/pnUbKHYLZa00Db3/o1kUNbUUdNImvBXWR/9hsARD5NvWAF8YzN0Ia/4XvhIQl4iNNGgh0ZmEb3p7EkXr3787DvcMAowQQimiktZ8WgldTO1umyKnhHGSdq7Nt6QzUASlZeUiZVxjTJg5sxmmoxmo/he3EJAFkL7gIg55pvnvJJZZe1IcQZFS7fSmT/x6gjS5MCEwrYg97QbqsujOJ0J73WU3Y5Sv5ItPIthLavwP/WLwEIbXwFrcaLs7iMrKu+bi1sGvhXP4NpGuB04xgzNWM2RroOKkIIMRgp0WmoFpPwrjUpv5/h3Wvs5zEMHCPGYTTXYoaDAOjRixuJAetEromz07a4F31HUVTUoomEvR/he/4BwjtWgBbGqK+yMikjgfjCaX4nrSzKaMZmtFC4EKeDdGPJpAfTWMAKeDjGTWPzh14UJYICuJzSclYMXp21s036UYu2kkus1xF7fc7138H/1hNkzbst3k0jWvAUsH9APbOuJ/ju/2IEfJwsrcZLaNdqa86paRJ0OGXqwRmg1XiJVO9Gzc7HCPiSvitajZf2vz0Mho7RdJSc676Ndqyc8I5V9vfGDLYR2rQcAP+aZ3EUTUx6vdnWiGka+Fc9Ha/mn9i2MDbYij4e/vR9iITIuviWjP/30kFFCDEYxI7PnbWkN8MBa3pKh2LMdneOqt1o1Z8CirWcw4lr8kVoVbvwr34Gz8xrCZdvAacHo7UBR4cuWND5eKInPq1qY9ehdmZOypNp5qfI7jYWuzgcYxj2/1NQUa3f6jS/k9bz8e+N3njEvgghRG+SYEcmPShQGrNqSyPHmyN8dtYwSkZlMWOiHEzF4Japna2rZDpBp9s+WUQLgxZJ+aFzz7wW/9rfE963AdfEC3EWl8Ureydc4VFzhqAMHU1415q0LUC7Ekun7Hji27ElqehdoX3r8b/ys/ggGQg63XaQyarQHw1QGDpGwEfuDd9FHT6WwDvPoZiGFehIF8SgQwZGhraF8cCF9X+vVUVbHbpSi+DG9NbAWwgh+qvwwS20/+3fwISg05Ux+K/XHkQdUYzRdMw6jqqqfXzVary0/XmpdUKsOnDPXIhn+tUYQWuKd3jnKsJ71tpj7rY//yjj+2QaT3SXt6qd+39bjmGCx6XwyDcmn/S6RKzbmJH6RPT31VlchmfebYTWv0TOjf835f/OMWoioKLkDcVsaySyay2RTz+Qi0yi18k0lgzMHtTsAOsg+qvlVmr+R3taJNAhRCcSp37lXHsfAEZLauEx/cg+CPsxjlfge3EJkcOfoh8rx1E6K6noo1bjxWw9jtF09KSKlyWlU9rMhHnCJ2+wT4vJ9Pm1Gi+BFb9KCnRYT4QJfPA8Wo0Xx8iS6IPJAYqkK0kZghgQ64bSITtPVcm59j57MOUsLiP/q4+g5I8E08BoqAKg/dVHpRaHEGLQCu9eEz0+mxlrcZimgVZXjqtkOnm3/xQUFde0y5MDzrHjtWmiDi3CWVyGfvxQfCW6lnT7dE1n2FHehhH9uZFp5qeuY7cx5zmX4p59A/lffcT+//dMv8ZaWAulvD60420wdRyjJkUfkXos4vSQzI5MjMzTWPZUtrFtv4+Lzh1iBzR2VbTFuiyh6dZBVIIdQmQWu0oTWP8Sid2MUq7M261rIwQ3L8dsb8I561qyL/uSva7k5XqekeEqmU4wdkd1WCfQpol/9TM4Ciec9AmtlTHyoNWlKSFj4VR1J7UYIHJoO1rtPlylMztdTqvx2gNZz/Sre6XuSaR6N0agjfCmV8E0CCZc1dPrK/GvfCr9VSFAq9yJr8aLc+olALjKriDropvt7XKVTMevOlESgx4dghgQD6oFPngerXKn9aBppkx3chaX4Zp4IeFdb8cflMweIcQgZkYST1CtWhwdfx/C3o8g5AdPLq7SGTjGTMVsrbefd4yKZU+kyaiL/dbGKKkB6940cmj8lEdVrGnm/obT8laDQncyHNWCseDOIbTtHzhGliRNMQ2s/Z11u3JHfNyV0LVPiN4iwY4MzNhV3g7TWLxV7Tz4bDm6AX//sJ5H/2kyZaW5nD8hHtiQWh1CdJ81pSV9/QP7OS0MKGjRiu6hjctxT7446eTXXi6hnR1ApHoPkf0fo+QVgKGl1ISIVO9GHTYaAOeUS1DzCwjvWGkFT7TwKZ3wBje/Fr9q1Usnz5HKXbT9ZakVQHCkTy3WarwEPn4Zbf/H1naoL5Jz3bfxzL4hZX1WQOaHoFuDzvDO1eTf+ejJf+ZtbxFY9XRqIMPQCW9fQXjX6uQreRCf750471sLo3k/tD7zgY/Juuhme3FncRm1F32NktqN6LGrQGmCGLFls+ffha/G22mNDc+shVY6dWzwLbU4hBADUHeD5UZDNcqQIszWaDesDrU4tBov/tf/C4DQpuW4p16Cc9w0QttXYuoaisNpBUIA96zr8cyIB0qcxWW4Zy4kvH1F9N0UnBNmk33FHactwBwIWb8tbqdCXnb3srZF57qaWqQf2QuRIPqxcnwvLrHHK8HtKxKmqBq4Z1xDeM+7KLnDz9CWi8FEgh2ZZJjGsquiDT06ho+lwZWV5jI0x9qVl18wlFsvL5SsDiG6qbOrA7Hn2l75GRg6pr/FeqJD4MBe7qV/Q03IxNBqvLS9+BB22hXxmhCA1c1FC1tpmFit1Bz5IwjvXhsNsHSvaFa6wWOkcieR6Mk6kBKEORlajRf/P/47PkjQIgQ+fhnn2HPt905bf8TQ8a98Cu1YecqVueCWN+xAh7WsRuCDP5E9/860QZRYMVHtWDkQzwSxCryusYqH0mFqSqKOgQ7VQc5138YI+FCz8/G//ZvUZdIEikLDSsg5d5r1f9hFodDuXIFyFpeRf+fPezXDRQgh+hOtxhv93YsQdDhwz7g27bFObzmO0XwM99zPEd7+D+sYm1CLAzpMUYkFQsaVEdr8Gv41z+A5/yrreOp04Z5+Vcp7eKZfbf3WRo/fpzPQAfBJVTtDcx20BXQafRoP/q6cr10Bc07bO4qO2bmR6t2Yhk4kcUqU6sA59hzCu9dith7H98JDSVNhYrobpBOiIwl2ZGLooDpRFCXp4XOL4y22TOB4UxhvVTv1LdaJxZevKmLK2ByEEN3X2dUBZ3EZnhnXEFz/UvSR9KmuzuIyXFMvIXJwM6ZpoigKkaqdSYEOIHlOaDSgEctC8L/xX+Tf8TNr6sPGV9H2rSOya03GollajZfg5teI7F1ndXCJFnEDaH99WdKyjqLOp8NoNV4iVbtwlc7I+HxKEAMTbf/HaPs32u8dqdqVpv6I9RnD21cQ3vm2neURPriZyKfvp75X5Q58NZ8mfebQ9hVpp56Ed76Nc8pFaOVb078v2MGk5Ncq1tSTDhkn2rHyhKt90eUyBDJ6Uii0O8XtTrUAnhBC9GeR6t2gRYhNGw1vX0F499qU37fQDusY7BwzGfe0/6Ttzz9GyR2atC5H0cSEO9Yx2mi3LkiEt/6D8Na3iAW+2/68NOU9Ojt+f1LZxs7yNmZPye/04qG3qp1dFW3dqpO3s9yHoij2kCCimVTUK52+RpyapKxb0yRSuTNhLAeg4J5xjZWV2SEokvh9sMc/hi6d8kSPSbAjA1OPpO3EEtasP8YxBW5qG8O8tamRVVsamT0lH4cKJUWZK/gLIU6OklcQv5OmNkOMs+QCwrvXEljzLO6yK1DSddRwOFGz8wlFp8QkiQZCsi/7Es7q3Wj71iU9njQYTHfyr2uEdq9NnqqhKNZ4T818uE1cV1BxUDRyKu3HN+AcPdluxxrc9lbmYEJCvROjrTFhXzmsAUTiNho6/lVPY2oRAu8/n7QWJX8kpq8h5TNrNV78K59MLSYaXV9sukwS1YHn4ltQsvJwlUxHO15BYOWT9nOx+h2dXu1T1YxXHmMkQCGEEN2TVJ8qpsPvW3Dz64TWWSek/hW/toqImzpma33SVITIoW3WOqddbrfqDiSdyJpJ73F051Ze25JHU2uE4fkurrmwgLLS1OP3p1VtPPCM1TXlxXfquG5uQXTZ5GCGt6qdB39XTkQzcThg4Zz0ywG8t6OJlnY96TETONFmrUeysU+PWEDL//6f0Kt2oFfuiD+pKOBw4Zl+NQDBWGc+IFKxE6PlOM7Rk9GOlRMp3xIf/0g9LdFDEuzIJDbfsIM12xpxqHD+hFxqG6Np7gZs3e9j1HA3bqc0uBGit5mh9oQ76WszAHa70NDm1wltX2FV+VYduKdfgzKsiND7z6NkD8W/4kniAzElGhQwOm1JmtiZxTr5T1NgU43+/dvTMKx5yKgO9KP77IyTRCnrMnVy6/cSrt9LOLqOoMORPLVDdVjZErpG4oDSCLQR3voPe5mc676No3CCFYDZsSr+HoZOYPVv4+uLDjqyL78d/6rf2G0CY/si9Mm76QMd6WQIZFjZNNFCtAlV+TuStq5CCNFz3UnzV7JyARPHuDL02v32lEg1O9+airhjlRWsj9EjhPeuj/92aGFCu9cS3L6SyO41AEQObuJYyfWs2HKYke2jWKg4UEw9drS3XmY6WLZ+KAeMeDB+1ZbGtIGM36+otbum6Ab2RcXv3DyOGy4ZaS/3xoYG+wKkpmdebke5j1++WhPfB8D4Qg/V9SG2Vap88lw5j3xjsgQ8ThNncRmuCTPQq3YkP96hRkv+HT8juP0tIrvfsQIjVTuiY6BUvdEpTwweEuzIwIzOIYR4mlxuloOPdrdgAu/vbEJVsA/IJhCKGBIhFuI0cJXOJOj8a5e1GYym2ugtq1WefmQvAOFP3rWuTikKpq8+5XXumdeiDi1KGiQ6i8vIvvY+KxvBNJI6s0QqdyQHOhTVmvaWnYujsDT+uNNF9hV3oNcdwl++mfbXl6G4s5MCAeGDm1KCJsnhELNDDQvFDiZEqndjtDcT3vyaNU1l498TXmYFhTzRzAfn6Mn4Vz2dXP0+tpkJgw51+Fja/vJj1KFFQHQAXb41vmWqiufiWzBDfoz2JrQDydvvnrmQ3Bu+m/IenRWiTdkeydYQQohuS5zmGHQ4rYw49zg6VqQIbngZUMi67IsYrQ0EVlmBdv+qp1OzAAEUFfe0y9AO77GvuscKeJtYv1W6prH6jQ94K3wlMIzDzsV8Pet1FEx0VD6IzOHDyIUcMEqSVh0LZKzc0siNFxfg8xscPOrnSEPqKa5uwK9fO8Lmfa0ANPt1vFX+Tpcbnu/C5VJ5fV1D/NKGYhUovWBiLtX1IUBJakMbmxKTeFvG9KfOVTrDytyIjWUcrpQaLc7iMhzVu8mUv2ozDfxv/yZtDTKA8MEt6McO4JowS8YRApBgR2aGBg4XeyraeODZ8pSLmroBl5Tls2mvzy5Y2tSm8ZBEiIXodd292u8qnZHQzi45hTa8d336lTucGadJmME27GwELUzgwxfJvuIOtNqD8YWi0zVCm5ZjtjURWPMsAO7pV+OZfQPO4jL0hsMARD55D4DwrjV2Aa7Ioa3xdSkqoGBGr4qlSEj7TG7dm2655ICCZ/YNOAon4H/vD/EOJtHtTxx0KE63FShpPGK1zTWxjoeKinvWdSn7KrR9RXSgbCSlpHYkGRtCCNFzkYrtaIc/xTXpwozHzaRaTdFaHGNUJ9q50wAI7VqLdmQvRn0FAO2vPop7+tXYv29pguCoDhov/Dq/8ZaRn/8dLtU3MKn1YxQzfpXPADQceLVJ9sve1S6mxj+aMuchvNqklCBHR4YBb37cmPa5xAZdhgkbvOmzOhOzSDpbbvaUPO682uq+tnpbExHNwESh/KifP64+hmnEZ56aJjgcMHNiHoXDXJxbnMPB2oA9DWfK2GwO1gbAhCljs2kN6GmDI7ELpkOyHeyv8aMoClPHxV+baerNQOIsLiP/q492WQDcyqh1klKkHKzxkWmSVG9m59v2dFklK4/w7nfRj3wKQPCjP2fsQgdS8HQwkWBHJrpGxFB5/O+HUwIdimK1l/3i/FF8cf4o/rj6GDvKrahwYocWIUTv6W6Byeyrv0Fg9TPxB6Mn/vbVqWgtCOfkuai5wzutB5Hc+ha0iu34qncldWuKdRKJj8h0KzAw4xp7vUbbieQVRwtwRSp3YkS7miROOznyzl8YWViI2d5ExK6Hkb41n6tkekKAJ7ofMrTwcxaXkXPlPXY1/liB0NTpJrEc4uQBR7qpJ7EgSm8VCRVCCGGJVO6k7c8/BkyC6/5CzvX/nPbk7URtPdYEFYsCYGg0vPUcnoa9mJh2QEABDE2j4liQUYoT1YygEA8YmKjsG/IZ1vhnsuHdsUALUIjDPYSJ7ngAQkfhvchFabM2DhglHAgnP+ZQ4eJz49MPNu712dnRHSmA26Vw87wRvPJRg31R8WSXi73/nVePtsfn375pLL9aXoNpwoe7W+3lEsf8ug7bDlrj+1VbmjKvPOE9br18JO0hA0zIyVJ55cOGlM+5YnP89srNjXzhipG0BQ3CmknhUBdVdQHcLgczJ+YmBVTO5gBJd8dwiUGRWM2O2G3/6mfiheUBDJ3Qx39Pt6pOu9DZF2kMwy7uLmOTgUuCHRm0tAZpajU42p6aTheLDMcONHdfOxpvtVUkyeVU7BQ4IcSZZ0ZCCfeSAwTdPSmPiWUjBN5/Hq1qJylTSqJTReyrEbEq96ZB219/Yv+AuibMIrjuL0mvjVR/gl6xLWVdnuIyGs6/mdI5c6wrD4e2ddqaz1lcRs51307KruishV9XGRZ2rRKtw7EvoYZHunXKQEEIIXqmq6vL/tW/JRbCME2D9hVPsvfDjwg6h+AYPRmtrhyn/wQTg59gYgUgFECNBjfc9V5QEqZGRrMxIjh45uC5wLlc7trGla6tqOiYqPxP8Gbe9V2csi1ebRIRtwunGYkvp1nLxQIZw/Nd5GapvPKRdYLvVGHuOfkJBUnjJ+grNjbw5OtHUgIUDpWkWh7zzhvGmu2NrNrcmLRsd5eLLfudm8clvX9rIE02yynSDfjbBw09eo1hZn7N+zub0z6+aksjMyfnYZqQ7VE5vzSXIydCXWaZnA06jic8Cc+lrUHWmYQudJ6Lb8EMtqO31FmFUmNRLS1sTVMePTklKKLVeJMCL7HxXrq/1Z5kinR32dO1nJqdn/GzDMSMl14Ldrzxxhs8/fTTaJrGPffcw1e/+tWk571eLz/60Y9ob29n7ty5PPzwwzidTo4ePcr999/PiRMnmDhxIsuWLSM3t+//OFvbgkRMh30/VlPQ7VSSAh0AZaW5PPKNyTK/T4h+wMrGcKcNEJzMSbmzuIzsBXfh+9OehOwJJWmqiB0U+fBFtIrtJHZHib1n7GqFdvhTjIYq9ENb4m+SZtpJ7L27M/WjJ9kVXe2HtJ8l2h5uoPzwCZFJV2MZMTh15wQgtszxNpXagwdRUBh1zjRG5YTskws1O5/6A/to9EVQPDmMrV6JgkE7Do7kXUDQOdQOYhS2H6QgfNQ+J7MyKkzG+3ZYDzR9YL93bIyqmHBIH8dkRw1qwhQQu6snKu9F5iZlYxwIlfBR5MIup50cMEr4mf8b9nKHKGFeWfpAxrzzhnU5Jr7hkpFMGJ1tT/HIlLVQVppLWWku18wuYM32xg7dXDIv19WJ/4yJeTgdVnHTWOKFqoCqKOiGiRINEundrM19JukGbDvQZt9f/0lryjIds0w6TrvpbEpO4v9FfxIbu3RWg8wen3XoQpcxAwTQa/ej1+4nvGMV7os/D0Efuu8EesV2ez2xyz/B6NRlM2TVjHGOnsyoravxndgPpklQdeCcNAc1f0RS8CQWOLGCLTutNrodutbFut+Fdq1FbzqKfviT6HJqypSc2PGmoa6RHO+bKJj4UTlach3tvnYUE/tYopgwrjCLnAOrSZzi3Y5KbekNmMF2CvJdFIwcQmjT8gGX8dIrwY66ujoef/xxXnnlFdxuN7fffjuXXHIJU6ZMsZe5//77+Y//+A9mzZrFkiVLeOmll7jjjjt4+OGHueOOO1i0aBFPPvkkTz31FPfff39vbNYpGZql0IYV7PC4FL61aGynkdLYQVYI0bdOR20Ia3rMNwms/o31gKqmdBxxFpeRfcUd+GJTZToEL+waGx/9heAHyS1fM007SXxdd7axt36U0n2WTLU4hBgoujOWEWeHg1u207D5bRQTwlMWcNQ9kRkT85jqqLav1Na7xnPswN6Uk4KOt101Wylu2x09mXBQk3c+QeewhOVM8vKyGV2zGgWTfBPsyRobP8CfmFkB5JiQE70dC1I40Bnv22ndiQYxYtNFYv8aprWeDg29gGhtUUDDyXuRuZQ46nCaEVSsk3UThW1aGf8Iz08bzEg37QSSp55YJ8XjOFg7i6kmfLuTqRTdHRP3ZOzc2+ssK83l6/N1wu5ihmQ77DE+JBcqTQycZAoQxLJZMk2jSRd42Ly/1ZrK040EhZNxMlkmHa3c3EjJCIXV+6uYOi6bquNBFAUmj7FudxUs6ex2x3OqWG2TjudZiTVP4q+/COX8IZynVjAyO0xw43JM08pMqpx2DweChUxs/phzWj5CSZMBYtr/KijRLCiwsqdCG/+etmZabAqYaegEEwInIeJ/zwAYOpGDmwAIbn+bo7nn4jAijAqUo2AkrTtxXe0otLjHMCxcm7RNseXaVjyJ9921hB255OR4GFO/HgWTXDMh2InBuKoV8RcmBESJzsJKPK6opsG4ymgHv2MQPBg/VplaZMC0+O2VYMf69eu59NJLGTZsGADXXXcdK1eu5LvftSryHzlyhGAwyKxZswC49dZbeeKJJ/jiF7/I5s2befLJJ+3H77zzzj4LdjRXVbPJuxM1ZwiFxw4xQtG4saSea26cJ4EMIc4ip2NahRkJ0FXr1O4EWlwTZhJc9+dOq5L3B1JQVAw2XY1lzqTEk/XOTsQ73nYGmtGzhvXoNadrXd19PSY4iiZZtwGlaDLG8XKcwWYMz1AomgjHDwEmjJyAWV9BOBhk/d5PUE5UWoPzglKUxkoU08RQHUxp/ZjYNWl984d49LG0fqDQ7DyKinXyM8SEIbEdnnRSkHo7fjKhM963K2U5pTn+EpPkgETSSUvCiUnHrIt0QQywghwaDnZq5zDbuQ9HmpM3HRVv3mUcGXkZ06ecz7vl5+A+uo0KXx65+PFqkyg3S/jCFSOZ2smV/oFQG6InSkbAnDmjUh7vmDHSHbFsluST8syZJTdcMjLDiXzn/y9NrRE27fN1Wp+ktxgmVDY4qGxo5v1dzQnPdF2/pDsUYMakXEYVuFmzrQnTAFWFc8fnkJ/jxONU+GhPS4baLnmoynSmT8zB31YYz0zaHAvaXc9nXQXRzkDRIEOHDKcKfSz3ZL2BCytDxC6I2+FvNKbj33ZsmY5/04nHi+L2T1O2PDlbK5rci0lB+GjG5RRMSoNe64H25G3quB2ZAqKJBX8Tl096v4SaPEfcUxkIof5eCXYcP36cwsJC+35RURG7du3K+HxhYSF1dXU0NTWRl5eH0+lMerwvHNyynene/8FJQkqUAl9ufILW+hFQOrtPtksI0T90t3VqV4GW7lYl7w+kFocYTLoay5wpzVXVlHh/TwGxVm+dn4in3A6cxGtO17pO5vXNH8YH4SGg9aP4c60JXbWqtsdvt20kScIg3onJVOcRUiQsk27g3/HxjicyHZ/reCKR9FYZnotlXQA4Or6I+EnZR9qFjDj3ArJH1eEqfz8lcDTi4oXMn5swTr1kAVu35nHeyGms2d7YZSaGOHUnk+F9slnh3qr2pCk9Pcky6U9MYOehdjgUP3vXDfg0TVvhdAwTdh7yA+kzk96JXMxh3eoM5DNymOA4igJJ07hq/KNZ5H6fOc59YBqoJE/72q6dS4uZT7uZxSK3lSmidvwc0eUNrL/nxL/ljscPa72KVV0n4f06W04xjaSsro7HG90ElXj2V5pDib2cicr6yAwuc+1K+1liy/xP8GZK28ZKsCPGMAyUhF8J0zST7md6vuNyQMr9ruzZs+cktzpZ46YPuBA9KcoG4DB1Kja9R4tyFhw1zoCtW7d2vdAgJ/uoa2frPvLMuZvsxkoCBRMI1fmh7hQ+R9E8698M6zlb99GZJPtI9KauxjJd6a3xiHGsEhWj05Pqzm6fzGtO17pO9vWJTvb9E9eTad0d36ezx9OdyKQGLlTeCn+GsbkBUBSOtmVxo3sdimlgovKP8GfIUUIogHPkKJx6gBrXREbmmRQ27AAUwvmjcftqAYX6kTM57CjlykKTkhGNgAtGXGO/p6t0IgAtGGmPh/6GvVw2Pnb7OFtPbVbDgHS2/o7E/l9jihLuD18AFfUKOW6To83Wl3/ssNTbbUHIy8r83L5aNWPHnN5hT5oguYFwpsfTvb7zZeJTtEzQEpczo8+P57+DdzJVrabMWYHPyGaCozYaFJmdNO1rm1aWskyFPiZpeYDLXdsZpviSMrESAyex5cqcFWQTYJH7I/u4km65y13bucq1JSmrK/F4k5fvoV3JYbjTjycn2z5+xI4lEV1hZ9tYcgmwV5/IqMnjOBq4iOJIBZojG63BSjSo0MeQrwbwahM5RAnfCNewdWtNhn1/9uiVYMfo0aPZsiVebK++vp6ioqKk5+vr6+37DQ0NFBUVUVBQgM/nQ9d1HA5Hyuu644ILLsDj8XS9YBcOmiqRVe/bcxzjUT0HEy++kilzJLNj69atzJkzp683o1+TfdS1s3sfnZntPrv30Zkh+6hzoVCo106+B4uuxjJd6a3xyNqqarQmBy4znmmaeFLdndsn85rTta6+eH0sY+KYZxJjwpWo0X2ZeCJRZY7louH1ZLkdXU61CYcNjoy8jOJCT9rMCsfoybQ2NlGXfQ4XXz43qQ7BmnXzGNLopXV4GaOmnE9rQGd62vpvn6c3yTGyawN1H/XWJ/JWtfPnt/dROLLwpAqcZrqdm6Xy96SWvFZwQ1WUDkVho1lPqpJU8yQ5eyX+2kvKhnDROfkZpvukX1f8swxBy5/N9ITtvGFsNlOTtn8Empm8zPSx2WzYVY3TM4yp9r6YTZ0J2blH7ONFeMoC9vnH2es9WBtAM2czamw2a8rnMfb4OrLcjrTL1Zmz2Zt7XdKxJ93xpjPF0SlT/8c+9sS/JbHpVNOj06l6OxOsrwOKvRLsuOyyy/jVr35FY2Mj2dnZvP322/z7v/+7/fy4cePweDz2QeW1115j/vz5uFwu5s6dy1tvvcXixYtZvnw58+fP741N6rEpc2eztvoe8v1NqDlDklIDp8yVQIcQQggxkHU1ljlThpWW4Ct5eNDU7DiZ1wcDAfImXJDx9Ya/lYJps5k+dzZajZdj61fR6IvQMv4K+0Ri0UkP5i/t9pLWNIUFwIKTeB8h+lZZaS6fu9BkzpzxXS/cQ7FWwR1rmwDd6qaTWCMl0zKx6T6nuyVvkbOKOXMmpXlmPInHiysyreCS5GNE+uWS19VTnU2ZGuhNNnol2DFq1Ch+8IMfcPfddxOJRLjtttuYMWMG3/zmN/n+97/P9OnTWbZsGUuXLqWtrY3zzz+fu+++G4Cf/OQnPPjggzz99NOMGTOGxx57rDc26aQMKy1hzpzejawLIYQQov/LNJbpC1PmzpYLLZ3oyRV5Z3EZxV8qozh6P+MJhxDijOnq5PtUXt+TZcTA1yvBDoDFixezePHipMeeffZZ+/a0adN4+eWXU143btw4nn/++ZTHhRBCCCHOpHRjGSGEEEKcnToWYRVCCCGEEEIIIYQ4q0mwQwghhBBCCCGEEAOKBDuEEEIIIYQQQggxoEiwQwghhBBCCCGEEAOKBDuEEEIIIYQQQggxoEiwQwghhBBCCCGEEAOKBDuEEEIIIYQQQggxoEiwQwghhBBCCCGEEAOKBDuEEEIIIYQQQggxoDj7egNOlmmaAITD4V5dbygU6tX1DTSyf7om+6hrso+6Jvuoa7KPMov9NsZ+K8XpczrGI/Ld7prso67JPuqa7KOuyT7qmuyjrvXVeEQxz9KRkM/nY//+/X29GUIIIUS/dc4555Cfn9/XmzGgyXhECCGE6FxfjUfO2mCHYRi0t7fjcrlQFKWvN0cIIYToN0zTJBKJkJubi6rKjNXTScYjQgghRHp9PR45a4MdQgghhBBCCCGEEOnI5R4hhBBCCCGEEEIMKBLsEEIIIYQQQgghxIAiwQ4hhBBCCCGEEEIMKBLsEEIIIYQQQgghxIAiwQ4hhBBCCCGEEEIMKBLsEEIIIYQQQgghxIAiwQ4hhBBCCCGEEEIMKBLsAN544w1uvPFGFi5cyAsvvNDXm9Nv3HXXXSxatIjPfe5zfO5zn2Pnzp2sX7+exYsXs3DhQh5//PG+3sQ+0dbWxk033URNTQ1Axn3i9Xq59dZbue666/jRj36Epml9tclnXMd99NBDD7Fw4UL7u7R69Wpg8O6jX//61yxatIhFixbxi1/8ApDvUUfp9pF8j5L98pe/5MYbb2TRokX8z//8DyDfo7OdjEfSk/FIejIe6ZqMRzon45GuyXika/16PGIOcseOHTOvuuoqs6mpyWxvbzcXL15sHjhwoK83q88ZhmFefvnlZiQSsR8LBALmggULzOrqajMSiZj33nuv+d577/XhVp55O3bsMG+66Sbz/PPPNw8fPtzpPlm0aJG5fft20zRN86GHHjJfeOGFPtzyM6fjPjJN07zpppvMurq6lGUH4z5at26d+eUvf9kMhUJmOBw27777bvONN96Q71GCdPvo7bfflu9Rgo0bN5q33367GYlEzEAgYF511VWm1+uV79FZTMYj6cl4JD0Zj3RNxiOdk/FI12Q80rX+Ph4Z9Jkd69ev59JLL2XYsGHk5ORw3XXXsXLlyr7erD536NAhAO69915uvvlm/vSnP7Fr1y5KS0sZP348TqeTxYsXD7p99dJLL/GTn/yEoqIigIz75MiRIwSDQWbNmgXArbfeOmj2Vcd9FAgEOHr0KEuWLGHx4sU88cQTGIYxaPdRYWEhDz74IG63G5fLxeTJk6msrJTvUYJ0++jo0aPyPUpw8cUX88c//hGn08mJEyfQdZ3W1lb5Hp3FZDySnoxH0pPxSNdkPNI5GY90TcYjXevv4xHnaV37WeD48eMUFhba94uKiti1a1cfblH/0Nrayrx58/jxj39MJBLh7rvv5p/+6Z9S9lVdXV0fbuWZ95//+Z9J99N9f+rq6lIeLywsHDT7quM+amho4NJLL+UnP/kJ+fn5fOtb3+Lll19m6tSpg3IfTZ061b5dWVnJihUruPPOO+V7lCDdPnrhhRfYtGmTfI8SuFwunnjiCX7/+99z/fXXy/HoLCfjkfRkPJKejEe6JuORzsl4pGsyHume/jweGfSZHYZhoCiKfd80zaT7g9Xs2bP5xS9+QX5+PgUFBdx222088cQTsq86yPT9ke9V3Pjx43nyyScpKioiOzubu+66i/fff3/Q76MDBw5w77338sADDzB+/Hj5HqWRuI8mTZok36M0vv/977NhwwZqa2uprKyU79FZTP6f0pPxSPfIeKRrMh5JT8YjXZPxSNf663hk0Ac7Ro8eTX19vX2/vr7eTncbzLZs2cKGDRvs+6ZpMm7cONlXHWT6/nR8vKGhYdDuq3379rFq1Sr7vmmaOJ3OQb2Ptm7dyte+9jX+3//7f3z+85+X71EaHfeRfI+SlZeX4/V6AcjOzmbhwoVs3LhRvkdnMRmPpCfjke6R35Guye9IKhmPdE3GI53r7+ORQR/suOyyy9iwYQONjY0EAgHefvtt5s+f39eb1ed8Ph+/+MUvCIVCtLW18eqrr/Iv//IvVFRUUFVVha7rvPnmm4N+X82cOTPtPhk3bhwej4etW7cC8Nprrw3afWWaJj/72c9oaWkhEonw17/+lWuvvXbQ7qPa2lq+853vsGzZMhYtWgTI96ijdPtIvkfJampqWLp0KeFwmHA4zNq1a7n99tvle3QWk/FIejIe6R75Hema/I4kk/FI12Q80rX+Ph4Z9DU7Ro0axQ9+8APuvvtuIpEIt912GzNmzOjrzepzV111FTt37uSWW27BMAzuuOMOZs+ezaOPPsr3vvc9QqEQCxYs4Prrr+/rTe1THo8n4z5ZtmwZS5cupa2tjfPPP5+77767j7e2b0ybNo377ruPr3zlK2iaxsKFC7npppuAwbmPnnvuOUKhEI8++qj92O233y7fowSZ9pF8j+IWLFjArl27uOWWW3A4HCxcuJBFixZRUFAg36OzlIxH0pPxSPfIeKRrMh5JJuORrsl4pGv9fTyimKZpntZ3EEIIIYQQQgghhDiDBv00FiGEEEIIIYQQQgwsEuwQQgghhBBCCCHEgCLBDiGEEEIIIYQQQgwoEuwQQgghhBBCCCHEgCLBDiGEEEIIIYQQQgwoEuwQYhC79957aWxs5Jvf/CYHDx7slXX+6le/4qc//SlAr65XCCGEEAOTjEeEEKeDs683QAjRd9atWwfAs88+e1rWf7rWK4QQQoiBQ8YjQojTQYIdQgxSDz30EAD33HMPBw8e5KWXXsLv9/PYY48xZswYKioqyM7O5r777uP555+noqKChQsXsmTJEgDeeecdnn76aSKRCFlZWfzwhz9k9uzZSe/x2c9+ll/+8pf4/X4ef/xxxo8fz4EDB9A0jYcffpg5c+YQDodZtmwZmzdvRtd1zjvvPJYuXUpeXt4Z3ydCCCGEOLNkPCKEOF1kGosQg9QjjzwCwB/+8AfGjBljP757927uu+8+XnvtNfLy8njmmWf47W9/yyuvvMKLL75IXV0dlZWVPP744zzzzDMsX76cf//3f+d73/sefr8/4/vt2rWLe++9l+XLl3Prrbfy+OOPA/DMM8/gcDh45ZVXeP311ykqKmLZsmWn98MLIYQQol+Q8YgQ4nSRzA4hRJLi4mLOO+88AEpKSsjPz8ftdlNQUEBubi4tLS1s3ryZ48eP87Wvfc1+naIoVFdXZ1zv2LFjKSsrA+C8887j1VdfBeC9997D5/Oxfv16ACKRCCNGjDhNn04IIYQQZwMZjwghTpUEO4QQSdxud9J9pzP1MGEYBvPmzeO///u/7cdqa2spKipi9erVadeblZVl31YUBdM07XUtWbKEBQsWANDe3k4oFDrVjyGEEEKIs5iMR4QQp0qmsQgxiDkcDjRN6/Hr5s2bx7p16ygvLwfg/fff5+abbyYYDPZ4XZdffjkvvPAC4XAYwzD48Y9/zGOPPdbj9QghhBDi7CTjESHE6SCZHUIMYtdffz133XUX7e3tPXrdlClT+OlPf8q//Mu/YJomTqeTp59+mtzc3B5vwz//8z/z85//nM9//vPouk5ZWRkPPvhgj9cjhBBCiLOTjEeEEKeDYsZyt4QQQgghhBBCCCEGAJnGIoQQQgghhBBCiAFFgh1CCCGEEEIIIYQYUCTYIYQQQgghhBBCiAFFgh1CCCGEEEIIIYQYUCTYIYQQQgghhBBCiAFFgh1CCCGEEEIIIYQYUCTYIYQQQgghhBBCiAFFgh1CCCGEEEIIIYQYUP5/kOfLepfHd8gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1296x1512 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rpt_country(df, 'UK', history=7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Daily Rankings\n",
    "\n",
    "Daily rankings by variable. By default, countries included iff cum_deaths > 100."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Daily statistics for 2020-12-14 \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Country1</th>        <th class=\"col_heading level0 col1\" >Geoid1</th>        <th class=\"col_heading level0 col2\" >Daily Cases</th>        <th class=\"col_heading level0 col3\" >Country2</th>        <th class=\"col_heading level0 col4\" >Geoid2</th>        <th class=\"col_heading level0 col5\" >Daily Deaths</th>        <th class=\"col_heading level0 col6\" >Country3</th>        <th class=\"col_heading level0 col7\" >Geoid3</th>        <th class=\"col_heading level0 col8\" >Cum. Cases</th>        <th class=\"col_heading level0 col9\" >Country4</th>        <th class=\"col_heading level0 col10\" >Geoid4</th>        <th class=\"col_heading level0 col11\" >Cum. Deaths</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row0_col0\" class=\"data row0 col0\" >United_States_of_America</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row0_col1\" class=\"data row0 col1\" >US</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row0_col2\" class=\"data row0 col2\" >189,723</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row0_col3\" class=\"data row0 col3\" >United_States_of_America</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row0_col4\" class=\"data row0 col4\" >US</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row0_col5\" class=\"data row0 col5\" >1,340</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row0_col6\" class=\"data row0 col6\" >United_States_of_America</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row0_col7\" class=\"data row0 col7\" >US</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row0_col8\" class=\"data row0 col8\" >16,256,754</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row0_col9\" class=\"data row0 col9\" >United_States_of_America</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row0_col10\" class=\"data row0 col10\" >US</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row0_col11\" class=\"data row0 col11\" >299,177</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row1_col0\" class=\"data row1 col0\" >Turkey</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row1_col1\" class=\"data row1 col1\" >TR</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row1_col2\" class=\"data row1 col2\" >29,136</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row1_col3\" class=\"data row1 col3\" >Russia</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row1_col4\" class=\"data row1 col4\" >RU</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row1_col5\" class=\"data row1 col5\" >488</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row1_col6\" class=\"data row1 col6\" >India</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row1_col7\" class=\"data row1 col7\" >IN</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row1_col8\" class=\"data row1 col8\" >9,884,100</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row1_col9\" class=\"data row1 col9\" >Brazil</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row1_col10\" class=\"data row1 col10\" >BR</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row1_col11\" class=\"data row1 col11\" >181,402</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row2_col0\" class=\"data row2 col0\" >Russia</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row2_col1\" class=\"data row2 col1\" >RU</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row2_col2\" class=\"data row2 col2\" >28,080</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row2_col3\" class=\"data row2 col3\" >Italy</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row2_col4\" class=\"data row2 col4\" >IT</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row2_col5\" class=\"data row2 col5\" >484</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row2_col6\" class=\"data row2 col6\" >Brazil</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row2_col7\" class=\"data row2 col7\" >BR</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row2_col8\" class=\"data row2 col8\" >6,901,952</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row2_col9\" class=\"data row2 col9\" >India</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row2_col10\" class=\"data row2 col10\" >IN</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row2_col11\" class=\"data row2 col11\" >143,355</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row3_col0\" class=\"data row3 col0\" >India</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row3_col1\" class=\"data row3 col1\" >IN</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row3_col2\" class=\"data row3 col2\" >27,071</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row3_col3\" class=\"data row3 col3\" >India</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row3_col4\" class=\"data row3 col4\" >IN</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row3_col5\" class=\"data row3 col5\" >336</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row3_col6\" class=\"data row3 col6\" >Russia</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row3_col7\" class=\"data row3 col7\" >RU</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row3_col8\" class=\"data row3 col8\" >2,653,928</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row3_col9\" class=\"data row3 col9\" >Mexico</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row3_col10\" class=\"data row3 col10\" >MX</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row3_col11\" class=\"data row3 col11\" >113,953</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row4_col0\" class=\"data row4 col0\" >Brazil</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row4_col1\" class=\"data row4 col1\" >BR</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row4_col2\" class=\"data row4 col2\" >21,825</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row4_col3\" class=\"data row4 col3\" >Brazil</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row4_col4\" class=\"data row4 col4\" >BR</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row4_col5\" class=\"data row4 col5\" >279</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row4_col6\" class=\"data row4 col6\" >France</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row4_col7\" class=\"data row4 col7\" >FR</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row4_col8\" class=\"data row4 col8\" >2,376,852</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row4_col9\" class=\"data row4 col9\" >Italy</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row4_col10\" class=\"data row4 col10\" >IT</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row4_col11\" class=\"data row4 col11\" >64,520</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row5_col0\" class=\"data row5 col0\" >United_Kingdom</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row5_col1\" class=\"data row5 col1\" >UK</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row5_col2\" class=\"data row5 col2\" >18,447</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row5_col3\" class=\"data row5 col3\" >Ukraine</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row5_col4\" class=\"data row5 col4\" >UA</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row5_col5\" class=\"data row5 col5\" >249</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row5_col6\" class=\"data row5 col6\" >United_Kingdom</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row5_col7\" class=\"data row5 col7\" >UK</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row5_col8\" class=\"data row5 col8\" >1,849,403</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row5_col9\" class=\"data row5 col9\" >United_Kingdom</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row5_col10\" class=\"data row5 col10\" >UK</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row5_col11\" class=\"data row5 col11\" >64,170</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3level0_row6\" class=\"row_heading level0 row6\" >7</th>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row6_col0\" class=\"data row6 col0\" >Italy</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row6_col1\" class=\"data row6 col1\" >IT</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row6_col2\" class=\"data row6 col2\" >17,937</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row6_col3\" class=\"data row6 col3\" >Mexico</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row6_col4\" class=\"data row6 col4\" >MX</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row6_col5\" class=\"data row6 col5\" >249</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row6_col6\" class=\"data row6 col6\" >Italy</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row6_col7\" class=\"data row6 col7\" >IT</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row6_col8\" class=\"data row6 col8\" >1,843,712</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row6_col9\" class=\"data row6 col9\" >France</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row6_col10\" class=\"data row6 col10\" >FR</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row6_col11\" class=\"data row6 col11\" >57,911</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3level0_row7\" class=\"row_heading level0 row7\" >8</th>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row7_col0\" class=\"data row7 col0\" >Germany</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row7_col1\" class=\"data row7 col1\" >DE</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row7_col2\" class=\"data row7 col2\" >16,362</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row7_col3\" class=\"data row7 col3\" >Iran</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row7_col4\" class=\"data row7 col4\" >IR</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row7_col5\" class=\"data row7 col5\" >247</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row7_col6\" class=\"data row7 col6\" >Argentina</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row7_col7\" class=\"data row7 col7\" >AR</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row7_col8\" class=\"data row7 col8\" >1,498,160</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row7_col9\" class=\"data row7 col9\" >Iran</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row7_col10\" class=\"data row7 col10\" >IR</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row7_col11\" class=\"data row7 col11\" >52,196</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3level0_row8\" class=\"row_heading level0 row8\" >9</th>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row8_col0\" class=\"data row8 col0\" >Ukraine</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row8_col1\" class=\"data row8 col1\" >UA</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row8_col2\" class=\"data row8 col2\" >15,627</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row8_col3\" class=\"data row8 col3\" >Turkey</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row8_col4\" class=\"data row8 col4\" >TR</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row8_col5\" class=\"data row8 col5\" >222</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row8_col6\" class=\"data row8 col6\" >Colombia</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row8_col7\" class=\"data row8 col7\" >CO</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row8_col8\" class=\"data row8 col8\" >1,425,774</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row8_col9\" class=\"data row8 col9\" >Russia</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row8_col10\" class=\"data row8 col10\" >RU</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row8_col11\" class=\"data row8 col11\" >46,941</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3level0_row9\" class=\"row_heading level0 row9\" >10</th>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row9_col0\" class=\"data row9 col0\" >France</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row9_col1\" class=\"data row9 col1\" >FR</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row9_col2\" class=\"data row9 col2\" >11,533</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row9_col3\" class=\"data row9 col3\" >Poland</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row9_col4\" class=\"data row9 col4\" >PL</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row9_col5\" class=\"data row9 col5\" >188</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row9_col6\" class=\"data row9 col6\" >Germany</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row9_col7\" class=\"data row9 col7\" >DE</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row9_col8\" class=\"data row9 col8\" >1,337,078</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row9_col9\" class=\"data row9 col9\" >Argentina</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row9_col10\" class=\"data row9 col10\" >AR</td>\n",
       "                        <td id=\"T_19a39e42_5c37_11eb_beaf_3af9d3d753e3row9_col11\" class=\"data row9 col11\" >40,766</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f7f6a5c5d90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rpt_daily_stats(df, asof, ['cases', 'deaths', 'cum_cases', 'cum_deaths'], show_nice_names=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Daily statistics for 2020-12-14 \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Country1</th>        <th class=\"col_heading level0 col1\" >Geoid1</th>        <th class=\"col_heading level0 col2\" >Cases (per mil.)</th>        <th class=\"col_heading level0 col3\" >Country2</th>        <th class=\"col_heading level0 col4\" >Geoid2</th>        <th class=\"col_heading level0 col5\" >Deaths (per mil.)</th>        <th class=\"col_heading level0 col6\" >Country3</th>        <th class=\"col_heading level0 col7\" >Geoid3</th>        <th class=\"col_heading level0 col8\" >Growth Rate Cases</th>        <th class=\"col_heading level0 col9\" >Country4</th>        <th class=\"col_heading level0 col10\" >Geoid4</th>        <th class=\"col_heading level0 col11\" >Growth Rate Deaths</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row0_col0\" class=\"data row0 col0\" >Luxembourg</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row0_col1\" class=\"data row0 col1\" >LU</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row0_col2\" class=\"data row0 col2\" >67,230</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row0_col3\" class=\"data row0 col3\" >Belgium</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row0_col4\" class=\"data row0 col4\" >BE</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row0_col5\" class=\"data row0 col5\" >1,567</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row0_col6\" class=\"data row0 col6\" >Lithuania</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row0_col7\" class=\"data row0 col7\" >LT</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row0_col8\" class=\"data row0 col8\" >3.00%</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row0_col9\" class=\"data row0 col9\" >Latvia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row0_col10\" class=\"data row0 col10\" >LV</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row0_col11\" class=\"data row0 col11\" >4.71%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row1_col0\" class=\"data row1 col0\" >Montenegro</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row1_col1\" class=\"data row1 col1\" >ME</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row1_col2\" class=\"data row1 col2\" >66,582</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row1_col3\" class=\"data row1 col3\" >Peru</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row1_col4\" class=\"data row1 col4\" >PE</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row1_col5\" class=\"data row1 col5\" >1,128</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row1_col6\" class=\"data row1 col6\" >Denmark</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row1_col7\" class=\"data row1 col7\" >DK</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row1_col8\" class=\"data row1 col8\" >2.98%</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row1_col9\" class=\"data row1 col9\" >Croatia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row1_col10\" class=\"data row1 col10\" >HR</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row1_col11\" class=\"data row1 col11\" >2.94%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row2_col0\" class=\"data row2 col0\" >Czechia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row2_col1\" class=\"data row2 col1\" >CZ</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row2_col2\" class=\"data row2 col2\" >54,562</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row2_col3\" class=\"data row2 col3\" >Italy</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row2_col4\" class=\"data row2 col4\" >IT</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row2_col5\" class=\"data row2 col5\" >1,069</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row2_col6\" class=\"data row2 col6\" >Estonia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row2_col7\" class=\"data row2 col7\" >EE</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row2_col8\" class=\"data row2 col8\" >2.84%</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row2_col9\" class=\"data row2 col9\" >Syria</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row2_col10\" class=\"data row2 col10\" >SY</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row2_col11\" class=\"data row2 col11\" >2.86%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row3_col0\" class=\"data row3 col0\" >Bahrain</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row3_col1\" class=\"data row3 col1\" >BH</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row3_col2\" class=\"data row3 col2\" >54,317</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row3_col3\" class=\"data row3 col3\" >North_Macedonia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row3_col4\" class=\"data row3 col4\" >MK</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row3_col5\" class=\"data row3 col5\" >1,021</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row3_col6\" class=\"data row3 col6\" >Latvia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row3_col7\" class=\"data row3 col7\" >LV</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row3_col8\" class=\"data row3 col8\" >2.70%</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row3_col9\" class=\"data row3 col9\" >Georgia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row3_col10\" class=\"data row3 col10\" >GE</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row3_col11\" class=\"data row3 col11\" >2.78%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row4_col0\" class=\"data row4 col0\" >Belgium</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row4_col1\" class=\"data row4 col1\" >BE</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row4_col2\" class=\"data row4 col2\" >53,075</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row4_col3\" class=\"data row4 col3\" >Bosnia_and_Herzegovina</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row4_col4\" class=\"data row4 col4\" >BA</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row4_col5\" class=\"data row4 col5\" >1,011</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row4_col6\" class=\"data row4 col6\" >Azerbaijan</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row4_col7\" class=\"data row4 col7\" >AZ</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row4_col8\" class=\"data row4 col8\" >2.61%</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row4_col9\" class=\"data row4 col9\" >Lithuania</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row4_col10\" class=\"data row4 col10\" >LT</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row4_col11\" class=\"data row4 col11\" >2.59%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row5_col0\" class=\"data row5 col0\" >Armenia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row5_col1\" class=\"data row5 col1\" >AM</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row5_col2\" class=\"data row5 col2\" >50,269</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row5_col3\" class=\"data row5 col3\" >United_Kingdom</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row5_col4\" class=\"data row5 col4\" >UK</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row5_col5\" class=\"data row5 col5\" >963</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row5_col6\" class=\"data row5 col6\" >Croatia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row5_col7\" class=\"data row5 col7\" >HR</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row5_col8\" class=\"data row5 col8\" >2.36%</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row5_col9\" class=\"data row5 col9\" >Hungary</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row5_col10\" class=\"data row5 col10\" >HU</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row5_col11\" class=\"data row5 col11\" >2.49%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3level0_row6\" class=\"row_heading level0 row6\" >7</th>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row6_col0\" class=\"data row6 col0\" >Qatar</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row6_col1\" class=\"data row6 col1\" >QA</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row6_col2\" class=\"data row6 col2\" >49,773</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row6_col3\" class=\"data row6 col3\" >Montenegro</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row6_col4\" class=\"data row6 col4\" >ME</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row6_col5\" class=\"data row6 col5\" >935</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row6_col6\" class=\"data row6 col6\" >Sri_Lanka</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row6_col7\" class=\"data row6 col7\" >LK</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row6_col8\" class=\"data row6 col8\" >2.32%</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row6_col9\" class=\"data row6 col9\" >Greece</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row6_col10\" class=\"data row6 col10\" >EL</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row6_col11\" class=\"data row6 col11\" >2.46%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3level0_row7\" class=\"row_heading level0 row7\" >8</th>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row7_col0\" class=\"data row7 col0\" >United_States_of_America</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row7_col1\" class=\"data row7 col1\" >US</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row7_col2\" class=\"data row7 col2\" >49,403</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row7_col3\" class=\"data row7 col3\" >Argentina</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row7_col4\" class=\"data row7 col4\" >AR</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row7_col5\" class=\"data row7 col5\" >910</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row7_col6\" class=\"data row7 col6\" >Uganda</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row7_col7\" class=\"data row7 col7\" >UG</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row7_col8\" class=\"data row7 col8\" >2.28%</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row7_col9\" class=\"data row7 col9\" >Serbia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row7_col10\" class=\"data row7 col10\" >RS</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row7_col11\" class=\"data row7 col11\" >2.38%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3level0_row8\" class=\"row_heading level0 row8\" >9</th>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row8_col0\" class=\"data row8 col0\" >Georgia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row8_col1\" class=\"data row8 col1\" >GE</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row8_col2\" class=\"data row8 col2\" >47,804</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row8_col3\" class=\"data row8 col3\" >United_States_of_America</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row8_col4\" class=\"data row8 col4\" >US</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row8_col5\" class=\"data row8 col5\" >909</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row8_col6\" class=\"data row8 col6\" >Serbia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row8_col7\" class=\"data row8 col7\" >RS</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row8_col8\" class=\"data row8 col8\" >2.25%</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row8_col9\" class=\"data row8 col9\" >Luxembourg</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row8_col10\" class=\"data row8 col10\" >LU</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row8_col11\" class=\"data row8 col11\" >2.38%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3level0_row9\" class=\"row_heading level0 row9\" >10</th>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row9_col0\" class=\"data row9 col0\" >Slovenia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row9_col1\" class=\"data row9 col1\" >SI</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row9_col2\" class=\"data row9 col2\" >46,285</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row9_col3\" class=\"data row9 col3\" >Czechia</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row9_col4\" class=\"data row9 col4\" >CZ</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row9_col5\" class=\"data row9 col5\" >902</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row9_col6\" class=\"data row9 col6\" >South_Korea</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row9_col7\" class=\"data row9 col7\" >KR</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row9_col8\" class=\"data row9 col8\" >2.16%</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row9_col9\" class=\"data row9 col9\" >Azerbaijan</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row9_col10\" class=\"data row9 col10\" >AZ</td>\n",
       "                        <td id=\"T_19b2f98c_5c37_11eb_beaf_3af9d3d753e3row9_col11\" class=\"data row9 col11\" >2.34%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f7f6a5d8490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rpt_daily_stats(df, asof, ['pm_cases', 'pm_deaths', 'gr_cases', 'gr_deaths'], show_nice_names=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Daily statistics for 2020-12-14 \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Country1</th>        <th class=\"col_heading level0 col1\" >Geoid1</th>        <th class=\"col_heading level0 col2\" >Fatality (spot)</th>        <th class=\"col_heading level0 col3\" >Country2</th>        <th class=\"col_heading level0 col4\" >Geoid2</th>        <th class=\"col_heading level0 col5\" >Fatality (lagged)</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row0_col0\" class=\"data row0 col0\" >Yemen</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row0_col1\" class=\"data row0 col1\" >YE</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row0_col2\" class=\"data row0 col2\" >29.09%</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row0_col3\" class=\"data row0 col3\" >Syria</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row0_col4\" class=\"data row0 col4\" >SY</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row0_col5\" class=\"data row0 col5\" >16.41%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row1_col0\" class=\"data row1 col0\" >Mexico</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row1_col1\" class=\"data row1 col1\" >MX</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row1_col2\" class=\"data row1 col2\" >9.12%</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row1_col3\" class=\"data row1 col3\" >Malawi</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row1_col4\" class=\"data row1 col4\" >MW</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row1_col5\" class=\"data row1 col5\" >12.50%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row2_col0\" class=\"data row2 col0\" >Ecuador</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row2_col1\" class=\"data row2 col1\" >EC</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row2_col2\" class=\"data row2 col2\" >6.87%</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row2_col3\" class=\"data row2 col3\" >Greece</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row2_col4\" class=\"data row2 col4\" >EL</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row2_col5\" class=\"data row2 col5\" >6.48%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row3_col0\" class=\"data row3 col0\" >Sudan</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row3_col1\" class=\"data row3 col1\" >SD</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row3_col2\" class=\"data row3 col2\" >6.30%</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row3_col3\" class=\"data row3 col3\" >Saudi_Arabia</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row3_col4\" class=\"data row3 col4\" >SA</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row3_col5\" class=\"data row3 col5\" >5.89%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row4_col0\" class=\"data row4 col0\" >Bolivia</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row4_col1\" class=\"data row4 col1\" >BO</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row4_col2\" class=\"data row4 col2\" >6.13%</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row4_col3\" class=\"data row4 col3\" >Mexico</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row4_col4\" class=\"data row4 col4\" >MX</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row4_col5\" class=\"data row4 col5\" >5.21%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row5_col0\" class=\"data row5 col0\" >Chad</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row5_col1\" class=\"data row5 col1\" >TD</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row5_col2\" class=\"data row5 col2\" >5.76%</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row5_col3\" class=\"data row5 col3\" >Guatemala</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row5_col4\" class=\"data row5 col4\" >GT</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row5_col5\" class=\"data row5 col5\" >5.21%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3level0_row6\" class=\"row_heading level0 row6\" >7</th>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row6_col0\" class=\"data row6 col0\" >Egypt</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row6_col1\" class=\"data row6 col1\" >EG</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row6_col2\" class=\"data row6 col2\" >5.69%</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row6_col3\" class=\"data row6 col3\" >Egypt</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row6_col4\" class=\"data row6 col4\" >EG</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row6_col5\" class=\"data row6 col5\" >5.17%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3level0_row7\" class=\"row_heading level0 row7\" >8</th>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row7_col0\" class=\"data row7 col0\" >Syria</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row7_col1\" class=\"data row7 col1\" >SY</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row7_col2\" class=\"data row7 col2\" >5.65%</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row7_col3\" class=\"data row7 col3\" >Angola</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row7_col4\" class=\"data row7 col4\" >AO</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row7_col5\" class=\"data row7 col5\" >5.14%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3level0_row8\" class=\"row_heading level0 row8\" >9</th>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row8_col0\" class=\"data row8 col0\" >China</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row8_col1\" class=\"data row8 col1\" >CN</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row8_col2\" class=\"data row8 col2\" >5.15%</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row8_col3\" class=\"data row8 col3\" >Guam</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row8_col4\" class=\"data row8 col4\" >GU</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row8_col5\" class=\"data row8 col5\" >4.84%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3level0_row9\" class=\"row_heading level0 row9\" >10</th>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row9_col0\" class=\"data row9 col0\" >Iran</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row9_col1\" class=\"data row9 col1\" >IR</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row9_col2\" class=\"data row9 col2\" >4.71%</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row9_col3\" class=\"data row9 col3\" >Bosnia_and_Herzegovina</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row9_col4\" class=\"data row9 col4\" >BA</td>\n",
       "                        <td id=\"T_19ba7324_5c37_11eb_beaf_3af9d3d753e3row9_col5\" class=\"data row9 col5\" >4.62%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7f7f6a5d85d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rpt_daily_stats(df, asof, ['fatality0', 'fatality7'], show_nice_names=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Timeline Charts\n",
    "\n",
    "Cumulatives cases and deaths against the timeline for each country. Day 1 on the timeline is the first day when total cases exceeds 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g_list = ['CN', 'BR', 'RU', 'IN', 'US', 'IT', 'UK', 'SE']\n",
    "#g_list = ['DK', 'FI', 'NO', 'NL', 'SE']\n",
    "timeline_chart(df, 'Cumulative cases on a common timeline',\n",
    "               geoid=g_list, y='cum_cases', log_scale='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "timeline_chart(df, 'Cumulative deaths on a common timeline',\n",
    "               geoid=g_list, y='cum_deaths', log_scale='', marker='')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Quick chart\n",
    "\n",
    "Generic chart to quickly plot different variables\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "chart(df, 'Fatality Rate', geoid=g_list, x='cum_cases', y='cum_deaths',\n",
    "#chart(df, 'Quick', geoid='UK', x='timeline', y='deaths',\n",
    "      log_scale='', filter_timeline=True, marker='')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inflection point - Where does the plateau start?\n",
    "\n",
    "Monitor the  daily cases / deaths against the China timeline. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g2_list = ['IT', 'FR', 'W_EU','SE', 'UK', 'IN']\n",
    "chart(df, 'MA Cases v. Timeline', geoid=g2_list, x='timeline', y='std_deaths',\n",
    "      log_scale='', filter_timeline=True, marker='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "chart(df, 'PM Deaths v. Timeline', geoid=g2_list , x='timeline', y='population',\n",
    "      log_scale='', filter_timeline=True, marker='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Normalise by population size\n",
    "# df['std_deaths'] = df['ma_deaths'] / df['population']\n",
    "# df['std_cases'] = df['ma_cases'] / df['population']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}