{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Method of Simulated Moments (MSM) for Structural Estimation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Steps of MSM estimation\n",
    "1. Load empirical data\n",
    "2. Define a function to calculate empirical moments from the data\n",
    "3. Calculate the covariance matrix of the empirical moments (for the weighting matrix)\n",
    "4. Define a `HARK` agent type with the model parameters to be estimated\n",
    "5. Define a function to simulate the model and calculate the simulated moments\n",
    "6. Estimate the model parameters by minimizing the distance between the empirical and simulated moments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from copy import copy\n",
    "\n",
    "import estimagic as em\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from statsmodels.stats.weightstats import DescrStatsW\n",
    "\n",
    "from HARK.Calibration.Income.IncomeTools import (\n",
    "    Cagetti_income,\n",
    "    parse_income_spec,\n",
    "    parse_time_params,\n",
    ")\n",
    "from HARK.Calibration.life_tables.us_ssa.SSATools import parse_ssa_life_table\n",
    "from HARK.Calibration.SCF.WealthIncomeDist.SCFDistTools import (\n",
    "    get_scf_distr_stats,\n",
    "    income_wealth_dists_from_scf,\n",
    ")\n",
    "from HARK.ConsumptionSaving.ConsIndShockModel import (\n",
    "    IndShockConsumerType,\n",
    "    init_lifecycle,\n",
    ")\n",
    "from HARK.estimation import estimate_msm\n",
    "from HARK.utilities import plot_funcs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Load empirical data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Educ</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>Age_grp</th>\n",
       "      <th>w.obs</th>\n",
       "      <th>obs</th>\n",
       "      <th>lnWealth.mean</th>\n",
       "      <th>lnWealth.sd</th>\n",
       "      <th>lnNrmWealth.mean</th>\n",
       "      <th>lnNrmWealth.sd</th>\n",
       "      <th>lnPermIncome.mean</th>\n",
       "      <th>lnPermIncome.sd</th>\n",
       "      <th>BASE_YR</th>\n",
       "      <th>Wealth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>290</th>\n",
       "      <td>College</td>\n",
       "      <td>1995</td>\n",
       "      <td>(25,30]</td>\n",
       "      <td>2.765032e+06</td>\n",
       "      <td>478.0</td>\n",
       "      <td>4.126304</td>\n",
       "      <td>1.270230</td>\n",
       "      <td>-0.091128</td>\n",
       "      <td>1.133600</td>\n",
       "      <td>4.217433</td>\n",
       "      <td>0.594117</td>\n",
       "      <td>2019</td>\n",
       "      <td>61.948554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>291</th>\n",
       "      <td>College</td>\n",
       "      <td>1995</td>\n",
       "      <td>(30,35]</td>\n",
       "      <td>2.819045e+06</td>\n",
       "      <td>553.0</td>\n",
       "      <td>4.485061</td>\n",
       "      <td>1.226898</td>\n",
       "      <td>0.142599</td>\n",
       "      <td>1.091322</td>\n",
       "      <td>4.342462</td>\n",
       "      <td>0.651507</td>\n",
       "      <td>2019</td>\n",
       "      <td>88.682362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>292</th>\n",
       "      <td>College</td>\n",
       "      <td>1995</td>\n",
       "      <td>(35,40]</td>\n",
       "      <td>2.516753e+06</td>\n",
       "      <td>666.0</td>\n",
       "      <td>4.817262</td>\n",
       "      <td>1.522302</td>\n",
       "      <td>0.337608</td>\n",
       "      <td>1.249328</td>\n",
       "      <td>4.479653</td>\n",
       "      <td>0.774831</td>\n",
       "      <td>2019</td>\n",
       "      <td>123.626079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>293</th>\n",
       "      <td>College</td>\n",
       "      <td>1995</td>\n",
       "      <td>(40,45]</td>\n",
       "      <td>3.582522e+06</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>5.234296</td>\n",
       "      <td>1.587167</td>\n",
       "      <td>0.600269</td>\n",
       "      <td>1.340885</td>\n",
       "      <td>4.634028</td>\n",
       "      <td>0.670276</td>\n",
       "      <td>2019</td>\n",
       "      <td>187.597079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>294</th>\n",
       "      <td>College</td>\n",
       "      <td>1995</td>\n",
       "      <td>(45,50]</td>\n",
       "      <td>3.261238e+06</td>\n",
       "      <td>1114.0</td>\n",
       "      <td>5.712218</td>\n",
       "      <td>1.553071</td>\n",
       "      <td>0.890605</td>\n",
       "      <td>1.197825</td>\n",
       "      <td>4.821613</td>\n",
       "      <td>0.724982</td>\n",
       "      <td>2019</td>\n",
       "      <td>302.541454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>College</td>\n",
       "      <td>2019</td>\n",
       "      <td>(70,75]</td>\n",
       "      <td>3.276375e+06</td>\n",
       "      <td>1058.0</td>\n",
       "      <td>6.618749</td>\n",
       "      <td>1.407732</td>\n",
       "      <td>2.126120</td>\n",
       "      <td>1.112098</td>\n",
       "      <td>4.492629</td>\n",
       "      <td>0.957018</td>\n",
       "      <td>2019</td>\n",
       "      <td>749.007589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>College</td>\n",
       "      <td>2019</td>\n",
       "      <td>(75,80]</td>\n",
       "      <td>1.836669e+06</td>\n",
       "      <td>543.0</td>\n",
       "      <td>6.392050</td>\n",
       "      <td>1.659717</td>\n",
       "      <td>2.061754</td>\n",
       "      <td>1.144179</td>\n",
       "      <td>4.330295</td>\n",
       "      <td>0.901808</td>\n",
       "      <td>2019</td>\n",
       "      <td>597.079225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>College</td>\n",
       "      <td>2019</td>\n",
       "      <td>(80,85]</td>\n",
       "      <td>1.195969e+06</td>\n",
       "      <td>352.0</td>\n",
       "      <td>6.233572</td>\n",
       "      <td>1.491591</td>\n",
       "      <td>1.943915</td>\n",
       "      <td>1.059349</td>\n",
       "      <td>4.289658</td>\n",
       "      <td>0.820112</td>\n",
       "      <td>2019</td>\n",
       "      <td>509.572465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>College</td>\n",
       "      <td>2019</td>\n",
       "      <td>(85,90]</td>\n",
       "      <td>6.284131e+05</td>\n",
       "      <td>129.0</td>\n",
       "      <td>6.010967</td>\n",
       "      <td>1.363456</td>\n",
       "      <td>1.792840</td>\n",
       "      <td>0.990714</td>\n",
       "      <td>4.218127</td>\n",
       "      <td>0.744886</td>\n",
       "      <td>2019</td>\n",
       "      <td>407.877637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>College</td>\n",
       "      <td>2019</td>\n",
       "      <td>(90,95]</td>\n",
       "      <td>2.557529e+05</td>\n",
       "      <td>80.0</td>\n",
       "      <td>6.626294</td>\n",
       "      <td>1.356511</td>\n",
       "      <td>2.464512</td>\n",
       "      <td>1.090929</td>\n",
       "      <td>4.161781</td>\n",
       "      <td>0.788086</td>\n",
       "      <td>2019</td>\n",
       "      <td>754.679931</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>126 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Educ  YEAR  Age_grp         w.obs     obs  lnWealth.mean  lnWealth.sd  \\\n",
       "290  College  1995  (25,30]  2.765032e+06   478.0       4.126304     1.270230   \n",
       "291  College  1995  (30,35]  2.819045e+06   553.0       4.485061     1.226898   \n",
       "292  College  1995  (35,40]  2.516753e+06   666.0       4.817262     1.522302   \n",
       "293  College  1995  (40,45]  3.582522e+06  1000.0       5.234296     1.587167   \n",
       "294  College  1995  (45,50]  3.261238e+06  1114.0       5.712218     1.553071   \n",
       "..       ...   ...      ...           ...     ...            ...          ...   \n",
       "427  College  2019  (70,75]  3.276375e+06  1058.0       6.618749     1.407732   \n",
       "428  College  2019  (75,80]  1.836669e+06   543.0       6.392050     1.659717   \n",
       "429  College  2019  (80,85]  1.195969e+06   352.0       6.233572     1.491591   \n",
       "430  College  2019  (85,90]  6.284131e+05   129.0       6.010967     1.363456   \n",
       "431  College  2019  (90,95]  2.557529e+05    80.0       6.626294     1.356511   \n",
       "\n",
       "     lnNrmWealth.mean  lnNrmWealth.sd  lnPermIncome.mean  lnPermIncome.sd  \\\n",
       "290         -0.091128        1.133600           4.217433         0.594117   \n",
       "291          0.142599        1.091322           4.342462         0.651507   \n",
       "292          0.337608        1.249328           4.479653         0.774831   \n",
       "293          0.600269        1.340885           4.634028         0.670276   \n",
       "294          0.890605        1.197825           4.821613         0.724982   \n",
       "..                ...             ...                ...              ...   \n",
       "427          2.126120        1.112098           4.492629         0.957018   \n",
       "428          2.061754        1.144179           4.330295         0.901808   \n",
       "429          1.943915        1.059349           4.289658         0.820112   \n",
       "430          1.792840        0.990714           4.218127         0.744886   \n",
       "431          2.464512        1.090929           4.161781         0.788086   \n",
       "\n",
       "     BASE_YR      Wealth  \n",
       "290     2019   61.948554  \n",
       "291     2019   88.682362  \n",
       "292     2019  123.626079  \n",
       "293     2019  187.597079  \n",
       "294     2019  302.541454  \n",
       "..       ...         ...  \n",
       "427     2019  749.007589  \n",
       "428     2019  597.079225  \n",
       "429     2019  509.572465  \n",
       "430     2019  407.877637  \n",
       "431     2019  754.679931  \n",
       "\n",
       "[126 rows x 13 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scf_data = get_scf_distr_stats()\n",
    "scf_data[\"Wealth\"] = np.exp(scf_data[\"lnWealth.mean\"])\n",
    "scf_data = scf_data[scf_data[\"Educ\"] == \"College\"]\n",
    "scf_data = scf_data[scf_data[\"YEAR\"] != \"All\"]\n",
    "scf_data = scf_data[scf_data[\"Age_grp\"] != \"All\"]\n",
    "scf_data = scf_data[~scf_data[\"Age_grp\"].isin([\"(15,20]\", \"(20,25]\"])]\n",
    "\n",
    "scf_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Calculate Moments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "indices = scf_data[\"Age_grp\"].unique()\n",
    "\n",
    "\n",
    "def calculate_weighted_median(data):\n",
    "    stats = DescrStatsW(data[\"Wealth\"], weights=data[\"w.obs\"])\n",
    "    return stats.quantile(0.5, return_pandas=False)[0]\n",
    "\n",
    "\n",
    "def calculate_moments(data):\n",
    "    medians = data.groupby([\"Age_grp\"]).apply(\n",
    "        calculate_weighted_median,\n",
    "        include_groups=False,\n",
    "    )\n",
    "    return medians.reindex(indices, fill_value=0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "empirical_moments = calculate_moments(scf_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Age_grp'>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "empirical_moments.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Calculate the covariance matrix of empirical moments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Age_grp</th>\n",
       "      <th>(25,30]</th>\n",
       "      <th>(30,35]</th>\n",
       "      <th>(35,40]</th>\n",
       "      <th>(40,45]</th>\n",
       "      <th>(45,50]</th>\n",
       "      <th>(50,55]</th>\n",
       "      <th>(55,60]</th>\n",
       "      <th>(60,65]</th>\n",
       "      <th>(65,70]</th>\n",
       "      <th>(70,75]</th>\n",
       "      <th>(75,80]</th>\n",
       "      <th>(80,85]</th>\n",
       "      <th>(85,90]</th>\n",
       "      <th>(90,95]</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age_grp</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>(25,30]</th>\n",
       "      <td>78.737485</td>\n",
       "      <td>-0.371681</td>\n",
       "      <td>-4.040328</td>\n",
       "      <td>-9.422402</td>\n",
       "      <td>13.093843</td>\n",
       "      <td>5.090706</td>\n",
       "      <td>1.389485</td>\n",
       "      <td>-5.709443</td>\n",
       "      <td>10.695572</td>\n",
       "      <td>6.195027</td>\n",
       "      <td>1.978852</td>\n",
       "      <td>-5.239811</td>\n",
       "      <td>-52.026812</td>\n",
       "      <td>13.828528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(30,35]</th>\n",
       "      <td>-0.371681</td>\n",
       "      <td>111.941544</td>\n",
       "      <td>7.594072</td>\n",
       "      <td>2.187824</td>\n",
       "      <td>16.141333</td>\n",
       "      <td>-1.336970</td>\n",
       "      <td>5.330875</td>\n",
       "      <td>-5.597500</td>\n",
       "      <td>-0.134589</td>\n",
       "      <td>8.196271</td>\n",
       "      <td>19.774747</td>\n",
       "      <td>26.793106</td>\n",
       "      <td>37.315401</td>\n",
       "      <td>-42.416020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(35,40]</th>\n",
       "      <td>-4.040328</td>\n",
       "      <td>7.594072</td>\n",
       "      <td>577.131713</td>\n",
       "      <td>-2.877333</td>\n",
       "      <td>37.316779</td>\n",
       "      <td>-0.267094</td>\n",
       "      <td>-4.269315</td>\n",
       "      <td>-10.520714</td>\n",
       "      <td>-56.049443</td>\n",
       "      <td>8.061753</td>\n",
       "      <td>-142.578652</td>\n",
       "      <td>5.639516</td>\n",
       "      <td>-34.492753</td>\n",
       "      <td>14.923283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(40,45]</th>\n",
       "      <td>-9.422402</td>\n",
       "      <td>2.187824</td>\n",
       "      <td>-2.877333</td>\n",
       "      <td>1345.165864</td>\n",
       "      <td>9.970902</td>\n",
       "      <td>-24.375004</td>\n",
       "      <td>-12.797304</td>\n",
       "      <td>7.520201</td>\n",
       "      <td>-20.394739</td>\n",
       "      <td>26.082335</td>\n",
       "      <td>169.630000</td>\n",
       "      <td>12.434961</td>\n",
       "      <td>9.041112</td>\n",
       "      <td>39.198754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(45,50]</th>\n",
       "      <td>13.093843</td>\n",
       "      <td>16.141333</td>\n",
       "      <td>37.316779</td>\n",
       "      <td>9.970902</td>\n",
       "      <td>2213.339739</td>\n",
       "      <td>-13.989562</td>\n",
       "      <td>-1.838498</td>\n",
       "      <td>31.312340</td>\n",
       "      <td>100.712927</td>\n",
       "      <td>-17.609319</td>\n",
       "      <td>17.421268</td>\n",
       "      <td>45.578331</td>\n",
       "      <td>52.952573</td>\n",
       "      <td>89.921968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(50,55]</th>\n",
       "      <td>5.090706</td>\n",
       "      <td>-1.336970</td>\n",
       "      <td>-0.267094</td>\n",
       "      <td>-24.375004</td>\n",
       "      <td>-13.989562</td>\n",
       "      <td>1527.340485</td>\n",
       "      <td>14.733277</td>\n",
       "      <td>56.594261</td>\n",
       "      <td>32.309802</td>\n",
       "      <td>38.808547</td>\n",
       "      <td>-100.367914</td>\n",
       "      <td>-48.581634</td>\n",
       "      <td>42.225114</td>\n",
       "      <td>-7.900472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(55,60]</th>\n",
       "      <td>1.389485</td>\n",
       "      <td>5.330875</td>\n",
       "      <td>-4.269315</td>\n",
       "      <td>-12.797304</td>\n",
       "      <td>-1.838498</td>\n",
       "      <td>14.733277</td>\n",
       "      <td>1708.687643</td>\n",
       "      <td>37.805573</td>\n",
       "      <td>-27.926395</td>\n",
       "      <td>-9.556498</td>\n",
       "      <td>75.322901</td>\n",
       "      <td>84.918302</td>\n",
       "      <td>-39.100823</td>\n",
       "      <td>-11.622967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(60,65]</th>\n",
       "      <td>-5.709443</td>\n",
       "      <td>-5.597500</td>\n",
       "      <td>-10.520714</td>\n",
       "      <td>7.520201</td>\n",
       "      <td>31.312340</td>\n",
       "      <td>56.594261</td>\n",
       "      <td>37.805573</td>\n",
       "      <td>3267.096856</td>\n",
       "      <td>-101.175101</td>\n",
       "      <td>1.004139</td>\n",
       "      <td>-27.080202</td>\n",
       "      <td>20.062823</td>\n",
       "      <td>118.732200</td>\n",
       "      <td>-143.400780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(65,70]</th>\n",
       "      <td>10.695572</td>\n",
       "      <td>-0.134589</td>\n",
       "      <td>-56.049443</td>\n",
       "      <td>-20.394739</td>\n",
       "      <td>100.712927</td>\n",
       "      <td>32.309802</td>\n",
       "      <td>-27.926395</td>\n",
       "      <td>-101.175101</td>\n",
       "      <td>13000.202130</td>\n",
       "      <td>-16.414305</td>\n",
       "      <td>-310.214803</td>\n",
       "      <td>95.090219</td>\n",
       "      <td>838.940789</td>\n",
       "      <td>-446.093482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(70,75]</th>\n",
       "      <td>6.195027</td>\n",
       "      <td>8.196271</td>\n",
       "      <td>8.061753</td>\n",
       "      <td>26.082335</td>\n",
       "      <td>-17.609319</td>\n",
       "      <td>38.808547</td>\n",
       "      <td>-9.556498</td>\n",
       "      <td>1.004139</td>\n",
       "      <td>-16.414305</td>\n",
       "      <td>4347.722505</td>\n",
       "      <td>1.784658</td>\n",
       "      <td>-13.300977</td>\n",
       "      <td>-22.299751</td>\n",
       "      <td>-109.678104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(75,80]</th>\n",
       "      <td>1.978852</td>\n",
       "      <td>19.774747</td>\n",
       "      <td>-142.578652</td>\n",
       "      <td>169.630000</td>\n",
       "      <td>17.421268</td>\n",
       "      <td>-100.367914</td>\n",
       "      <td>75.322901</td>\n",
       "      <td>-27.080202</td>\n",
       "      <td>-310.214803</td>\n",
       "      <td>1.784658</td>\n",
       "      <td>19767.327088</td>\n",
       "      <td>88.919075</td>\n",
       "      <td>-158.097593</td>\n",
       "      <td>388.548889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(80,85]</th>\n",
       "      <td>-5.239811</td>\n",
       "      <td>26.793106</td>\n",
       "      <td>5.639516</td>\n",
       "      <td>12.434961</td>\n",
       "      <td>45.578331</td>\n",
       "      <td>-48.581634</td>\n",
       "      <td>84.918302</td>\n",
       "      <td>20.062823</td>\n",
       "      <td>95.090219</td>\n",
       "      <td>-13.300977</td>\n",
       "      <td>88.919075</td>\n",
       "      <td>4582.977726</td>\n",
       "      <td>192.636538</td>\n",
       "      <td>-149.436556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(85,90]</th>\n",
       "      <td>-52.026812</td>\n",
       "      <td>37.315401</td>\n",
       "      <td>-34.492753</td>\n",
       "      <td>9.041112</td>\n",
       "      <td>52.952573</td>\n",
       "      <td>42.225114</td>\n",
       "      <td>-39.100823</td>\n",
       "      <td>118.732200</td>\n",
       "      <td>838.940789</td>\n",
       "      <td>-22.299751</td>\n",
       "      <td>-158.097593</td>\n",
       "      <td>192.636538</td>\n",
       "      <td>49368.887735</td>\n",
       "      <td>-325.915160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(90,95]</th>\n",
       "      <td>13.828528</td>\n",
       "      <td>-42.416020</td>\n",
       "      <td>14.923283</td>\n",
       "      <td>39.198754</td>\n",
       "      <td>89.921968</td>\n",
       "      <td>-7.900472</td>\n",
       "      <td>-11.622967</td>\n",
       "      <td>-143.400780</td>\n",
       "      <td>-446.093482</td>\n",
       "      <td>-109.678104</td>\n",
       "      <td>388.548889</td>\n",
       "      <td>-149.436556</td>\n",
       "      <td>-325.915160</td>\n",
       "      <td>45577.912602</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Age_grp    (25,30]     (30,35]     (35,40]      (40,45]      (45,50]  \\\n",
       "Age_grp                                                                \n",
       "(25,30]  78.737485   -0.371681   -4.040328    -9.422402    13.093843   \n",
       "(30,35]  -0.371681  111.941544    7.594072     2.187824    16.141333   \n",
       "(35,40]  -4.040328    7.594072  577.131713    -2.877333    37.316779   \n",
       "(40,45]  -9.422402    2.187824   -2.877333  1345.165864     9.970902   \n",
       "(45,50]  13.093843   16.141333   37.316779     9.970902  2213.339739   \n",
       "(50,55]   5.090706   -1.336970   -0.267094   -24.375004   -13.989562   \n",
       "(55,60]   1.389485    5.330875   -4.269315   -12.797304    -1.838498   \n",
       "(60,65]  -5.709443   -5.597500  -10.520714     7.520201    31.312340   \n",
       "(65,70]  10.695572   -0.134589  -56.049443   -20.394739   100.712927   \n",
       "(70,75]   6.195027    8.196271    8.061753    26.082335   -17.609319   \n",
       "(75,80]   1.978852   19.774747 -142.578652   169.630000    17.421268   \n",
       "(80,85]  -5.239811   26.793106    5.639516    12.434961    45.578331   \n",
       "(85,90] -52.026812   37.315401  -34.492753     9.041112    52.952573   \n",
       "(90,95]  13.828528  -42.416020   14.923283    39.198754    89.921968   \n",
       "\n",
       "Age_grp      (50,55]      (55,60]      (60,65]       (65,70]      (70,75]  \\\n",
       "Age_grp                                                                     \n",
       "(25,30]     5.090706     1.389485    -5.709443     10.695572     6.195027   \n",
       "(30,35]    -1.336970     5.330875    -5.597500     -0.134589     8.196271   \n",
       "(35,40]    -0.267094    -4.269315   -10.520714    -56.049443     8.061753   \n",
       "(40,45]   -24.375004   -12.797304     7.520201    -20.394739    26.082335   \n",
       "(45,50]   -13.989562    -1.838498    31.312340    100.712927   -17.609319   \n",
       "(50,55]  1527.340485    14.733277    56.594261     32.309802    38.808547   \n",
       "(55,60]    14.733277  1708.687643    37.805573    -27.926395    -9.556498   \n",
       "(60,65]    56.594261    37.805573  3267.096856   -101.175101     1.004139   \n",
       "(65,70]    32.309802   -27.926395  -101.175101  13000.202130   -16.414305   \n",
       "(70,75]    38.808547    -9.556498     1.004139    -16.414305  4347.722505   \n",
       "(75,80]  -100.367914    75.322901   -27.080202   -310.214803     1.784658   \n",
       "(80,85]   -48.581634    84.918302    20.062823     95.090219   -13.300977   \n",
       "(85,90]    42.225114   -39.100823   118.732200    838.940789   -22.299751   \n",
       "(90,95]    -7.900472   -11.622967  -143.400780   -446.093482  -109.678104   \n",
       "\n",
       "Age_grp       (75,80]      (80,85]       (85,90]       (90,95]  \n",
       "Age_grp                                                         \n",
       "(25,30]      1.978852    -5.239811    -52.026812     13.828528  \n",
       "(30,35]     19.774747    26.793106     37.315401    -42.416020  \n",
       "(35,40]   -142.578652     5.639516    -34.492753     14.923283  \n",
       "(40,45]    169.630000    12.434961      9.041112     39.198754  \n",
       "(45,50]     17.421268    45.578331     52.952573     89.921968  \n",
       "(50,55]   -100.367914   -48.581634     42.225114     -7.900472  \n",
       "(55,60]     75.322901    84.918302    -39.100823    -11.622967  \n",
       "(60,65]    -27.080202    20.062823    118.732200   -143.400780  \n",
       "(65,70]   -310.214803    95.090219    838.940789   -446.093482  \n",
       "(70,75]      1.784658   -13.300977    -22.299751   -109.678104  \n",
       "(75,80]  19767.327088    88.919075   -158.097593    388.548889  \n",
       "(80,85]     88.919075  4582.977726    192.636538   -149.436556  \n",
       "(85,90]   -158.097593   192.636538  49368.887735   -325.915160  \n",
       "(90,95]    388.548889  -149.436556   -325.915160  45577.912602  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "moments_cov = em.get_moments_cov(\n",
    "    scf_data,\n",
    "    calculate_moments,\n",
    "    bootstrap_kwargs={\"n_draws\": 5_000, \"seed\": 11323, \"error_handling\": \"continue\"},\n",
    ")\n",
    "\n",
    "moments_cov"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Define an agent type to simulate data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "birth_age = 25\n",
    "death_age = 100\n",
    "adjust_infl_to = 1992\n",
    "income_calib = Cagetti_income\n",
    "education = \"College\"\n",
    "\n",
    "# Income specification\n",
    "income_params = parse_income_spec(\n",
    "    age_min=birth_age,\n",
    "    age_max=death_age,\n",
    "    adjust_infl_to=adjust_infl_to,\n",
    "    **income_calib[education],\n",
    "    SabelhausSong=True,\n",
    ")\n",
    "\n",
    "# Initial distribution of wealth and permanent income\n",
    "dist_params = income_wealth_dists_from_scf(\n",
    "    base_year=adjust_infl_to,\n",
    "    age=birth_age,\n",
    "    education=education,\n",
    "    wave=1995,\n",
    ")\n",
    "\n",
    "# We need survival probabilities only up to death_age-1, because survival\n",
    "# probability at death_age is 1.\n",
    "liv_prb = parse_ssa_life_table(\n",
    "    female=True,\n",
    "    cross_sec=True,\n",
    "    year=2004,\n",
    "    age_min=birth_age,\n",
    "    age_max=death_age,\n",
    ")\n",
    "\n",
    "# Parameters related to the number of periods implied by the calibration\n",
    "time_params = parse_time_params(age_birth=birth_age, age_death=death_age)\n",
    "\n",
    "# Update all the new parameters\n",
    "params = copy(init_lifecycle)\n",
    "params.update(time_params)\n",
    "params.update(dist_params)\n",
    "params.update(income_params)\n",
    "params[\"LivPrb\"] = liv_prb\n",
    "params[\"AgentCount\"] = 10_000\n",
    "params[\"T_sim\"] = 200\n",
    "params[\"track_vars\"] = [\"aNrm\", \"bNrm\", \"cNrm\", \"pLvl\", \"t_age\", \"mNrm\"]\n",
    "params[\"PermGroFacAgg\"] = 1.0\n",
    "params[\"Rfree\"] = [params[\"Rfree\"][0]] * params[\"T_cycle\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "LifeCycleAgent = IndShockConsumerType(**params)\n",
    "LifeCycleAgent.solve()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Consumption functions\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "LifeCycleAgent.unpack(\"cFunc\")\n",
    "# Plot the consumption functions\n",
    "print(\"Consumption functions\")\n",
    "plot_funcs(LifeCycleAgent.cFunc, 0, 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "LifeCycleAgent.update()\n",
    "\n",
    "# Run the simulations\n",
    "LifeCycleAgent.initialize_sim()\n",
    "LifeCycleAgent.simulate()  # Note: simulate() does not return history; it updates LifeCycleAgent.history\n",
    "history = LifeCycleAgent.history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "raw_data = {\n",
    "    \"Age\": history[\"t_age\"].flatten() + birth_age - 1,\n",
    "    \"pIncome\": history[\"pLvl\"].flatten(),\n",
    "    \"nrmM\": history[\"mNrm\"].flatten(),\n",
    "    \"nrmC\": history[\"cNrm\"].flatten(),\n",
    "}\n",
    "\n",
    "sim_data = pd.DataFrame(raw_data)\n",
    "sim_data[\"Cons\"] = sim_data.nrmC * sim_data.pIncome\n",
    "sim_data[\"M\"] = sim_data.nrmM * sim_data.pIncome\n",
    "\n",
    "# Find the mean of each variable at every age\n",
    "AgeMeans = sim_data.groupby([\"Age\"]).median().reset_index()\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(AgeMeans.Age, AgeMeans.pIncome, label=\"Permanent Income\")\n",
    "plt.plot(AgeMeans.Age, AgeMeans.M, label=\"Market resources\")\n",
    "plt.plot(AgeMeans.Age, AgeMeans.Cons, label=\"Consumption\")\n",
    "plt.legend()\n",
    "plt.xlabel(\"Age\")\n",
    "plt.ylabel(f\"Thousands of {adjust_infl_to} USD\")\n",
    "plt.title(\"Variable Medians Conditional on Survival\")\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "age_groups = [\n",
    "    list(range(start, start + 5)) for start in range(birth_age + 1, 95 + 1, 5)\n",
    "]\n",
    "\n",
    "# generate labels as (25,30], (30,35], ...\n",
    "age_labels = [f\"({group[0] - 1},{group[-1]}]\" for group in age_groups]\n",
    "\n",
    "# Generate mappings between the real ages in the groups and the indices of simulated data\n",
    "age_mapping = dict(zip(age_labels, map(np.array, age_groups)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'(25,30]': array([26, 27, 28, 29, 30]),\n",
       " '(30,35]': array([31, 32, 33, 34, 35]),\n",
       " '(35,40]': array([36, 37, 38, 39, 40]),\n",
       " '(40,45]': array([41, 42, 43, 44, 45]),\n",
       " '(45,50]': array([46, 47, 48, 49, 50]),\n",
       " '(50,55]': array([51, 52, 53, 54, 55]),\n",
       " '(55,60]': array([56, 57, 58, 59, 60]),\n",
       " '(60,65]': array([61, 62, 63, 64, 65]),\n",
       " '(65,70]': array([66, 67, 68, 69, 70]),\n",
       " '(70,75]': array([71, 72, 73, 74, 75]),\n",
       " '(75,80]': array([76, 77, 78, 79, 80]),\n",
       " '(80,85]': array([81, 82, 83, 84, 85]),\n",
       " '(85,90]': array([86, 87, 88, 89, 90]),\n",
       " '(90,95]': array([91, 92, 93, 94, 95])}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age_mapping"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Define a function to calculate simulated moments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def simulate_moments(params, agent=None):\n",
    "    agent.assign_parameters(**params)\n",
    "    agent.update()\n",
    "\n",
    "    agent.solve()\n",
    "\n",
    "    agent.initialize_sim()\n",
    "    agent.simulate()\n",
    "    history = agent.history\n",
    "\n",
    "    raw_data = {\n",
    "        \"age\": history[\"t_age\"].flatten() + birth_age - 1,\n",
    "        \"b_nrm\": history[\"bNrm\"].flatten(),\n",
    "        \"p_lvl\": history[\"pLvl\"].flatten(),\n",
    "    }\n",
    "\n",
    "    sim_data = pd.DataFrame(raw_data)\n",
    "    sim_data[\"Wealth\"] = sim_data.b_nrm * sim_data.p_lvl\n",
    "\n",
    "    sim_data[\"Age_grp\"] = pd.cut(\n",
    "        sim_data.age,\n",
    "        bins=range(birth_age + 1, 97, 5),\n",
    "        labels=age_labels,\n",
    "        right=False,\n",
    "    )\n",
    "\n",
    "    sim_data = sim_data.dropna()\n",
    "\n",
    "    return sim_data.groupby(\"Age_grp\", observed=False)[\"Wealth\"].median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Age_grp'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jokJigEJExSvp5p0zI1dP3iUYCcgeiMi5Z/mC/+wmg4FT64BjK4BfhgOjNgPO7rBYt2OB0Pna5TYv6z0a8yIBq8yi/DwM2PMN0G4s4OSq96ioEBigEFHRzoxIuWe2mZGTWvJicQcjd3vTengmcDEUuHYKWDMJeCSj+sUSSXCSfBPwqwPU6KT3aMxPyKOAVxAQdwE4sBhoNlTvEVEhMEAhoqJx5SQwvyeQcOXO+2RJ5o5lmhLqHu3mA/T7CljwCLBvAVCzCxDyMCxOanJmW3vZwdeW2trnlYMj0Go0sHaSlkjcZIh1JUfbGAYoRFQ0Nk3VghOppglskT0gKZ19k9ASV7UD0PZlYNtnwB8vARWbWl7p8eFfgBuXtZmn+gP0Ho35ajII2DhVmzELWwvU7qH3iKiAGFoSUeFdOw0cWa5dHrQceOon4MHXtSZpegcnRlLZIcHS7eta6XF6LjkwltDWvuUowJGdt+/KRTrrDtEub88oxyaLxACFiApPZiYk6bVGF6B8A5gl2aum/7eAk1tm6bGlOL0BiD4COLkzryIvWj4P2DsC57cCEf/qPRoqIAYoRFQ40lL+wE/a5fbjYdaMpcdCSo8lidcSGGdPpCpJuuPSvXlV1JrYCc6iWCwGKERUOJKMmJas9aGo3AZmT97kJUk2PUUrPZbKI3MmJdpn/gHs7LUEUMobSSQWsvQoze3I4jBAIaKCuxUD7J2nXW5n5rMnOUuPS1fILD02Z8YZgDp9gDKV9R6N5ZClRkmOlqZ2xuonsigMUIio4HZ/DaQkAP71tfJdSyGlx33lTctOKz2WRm7mKO4ScPhn7XKbl/QejeVpnXHMQhcAiXF6j4byiQEKERW8Q6zxk2n7cZbXl6PaA1rpsZDS4/gImJ1dXwLpqUCV9kDFJnqPxvLU6KztyZR8A9j3vd6joXxigEJEBe9qKiW7PtW05QdLlK30+HnzKj2WT/x7jW3tOXtSINKkrfUY7fLOL4G0FL1HRPnAAIWI8i81SUuOFbJLsL0DLFK20uNN5lV6LJ/45ZN/2dpa+TYVTP3Htd2v4y8BR37TezSUDwxQiCj/ZJ8T6WoqLewbPgWLpkqPp5hX6bF80pdP/EI2wGO79oJzKgW0GKldlgBUmt6RReCrnojyJz0N2DYjs5TTGrqayp4twb0zSo+f07/0WEpj5RO/u582A0CF02w44OiqbWR5bqveo6E8YoBCRPlz9Dcg5ozWMKzps7AKkuD7yOcZpcdhwNo3dW5rn7HjcsuR2gwAFY67L9Doae2ycWmSzB4DFCLK35vnlumZ7cRdPGA1spYeSwKwXqXHkgsjzdkkL0Y++VPRUMmydsDJNcCVE3qPhvKAAQoR5V3YOiBK3jzdM9f1rYk5lB4b29o3fkYLmqho+FYHavfULu+YpfdoKA8YoBBR3m39VDuXDeus9c1TlR431Kf0OOoocOpvtrUvLpJwbEzyvnnFPGYkY85qFVuS+zSjPrDSQjoylwAGKESUN+e3Axd2AA7OmfucWCNVejxXn9JjY36E7BUk/WWoaMl+URWbAmlJwJ5v9RmDzMpJgPTbGGBGA2BmI2227tAyIPYCsHcucCNSn7GZGQYoRJQ3WzJmT6Ss2LM8rJoepcfyxnVwqXa5TcYyExV9MrQxuN7zDZByu/h/pszUHP4VWDkO+Lwp8GkIsHwUsH8hEHcBsHcEAlsBHSYC5UK0rzmxqvjHZQEc9R4AEVmAyweBU+u0pQdpzGYLpPRYcm6Or9Sm30dtApzdi+/n7fpKK3MOagNUalZ8P8fWhTwCeAVpwcGBn4Bmw4r2+9+OBc5vA85uAc5uBqKPZL9f/oZkCVE2MqzSAQhqlZlsLrN26/8HHFtZ9OOyQAxQiOj+tmZU7tTtqyUb2gJj6fGl0MzS44c/K56flXQjc1dotrUvXg6OWn7P2klasmyTZwvXCE/2pLqwEzi3WQtIpNeKIUfekl9dLSCRU+U2gKt37t9LevFIgCLfJzEOKOUFW8YAhYju7dpprfeJaDcONsVYevx9H630WDafk/yQorbvByApDvCtAdTqXvTfn7JrMgjYOBW4dgoIWwvU7pH3r01JBC7u1oIImSW5tFfb0DEr+T0aAxLZ6NG9bN6+d7laQNlawNWT2uxd/QGwZQxQiOjepGusfCKs2Q0IqA+bU+1BbVZDmqdJMqMkWXpWKLrvn5YK7JytXZb8CLa1L34upYFmzwLbPgO2f3HvAEW2Hbi0TwtIZJbkwi4tyTYrr0Cg6gMZQUn7wr0+gnsBW09qS4sMUIiI7pG4uf8n7XJ7Gy5/fOhtraJHpu+l9HjQb0UXSMjsVFw44FYWaPhk0XxPur8Wo7QlnvNbtQCkYpPMrRwiD2bOkEj1WkqOrQ88/LPPkJSpoi0JFoXgh7Ul1bB12myNDXcSZoBCRHcnny6NiZuSzGerjKXHX3XIKD3+IrOhW1G1tZfGd06uhf+elDdeFYF6/YGDS7TlnuoPAee2aCfJ/8hKtnWQQEQFJQ9oVV5FFZDkVKGxtgnnjcvaa61WN9gqBihElLtbMVrehWg/Qe/RmE/p8YpXgPXvam9WFRoV7nvKxnUyK+NYCmj+XFGNlPJKltQkQJE8FDkZOZcGqrTNnCWRJNeSWnqTnyPLPHu+1ZZ5bDhAyfcRv3TpEp555hn4+vrC1dUV9evXx969e033GwwGTJ48GeXLl1f3d+7cGWFhYdm+R0xMDAYOHAhPT094e3tj+PDhuHnzZtE8IyIqurJXmdoOaADU6KT3aKxz12NjW/tGA7UN7ahklW8ANHhS27qhWkeg0zvAcxuA188BTy/R9u+RvKuSzguS15g4vkpbcrJR+Trq169fR9u2beHk5ITVq1fj6NGj+OSTT1CmTBnTY6ZNm4aZM2dizpw52LVrF9zd3dGtWzckJiaaHiPByZEjR7Bu3TqsXLkSmzdvxsiRVrivB5GlkrLXXXMyK3eKazrbYnc9Ll/4XY+jj2d8arfL2MiOdNHvK+A/EcDg37Q8q0pNtVJkPVVpp5UY37oKhO+GrcpXgPLRRx8hMDAQ8+bNQ4sWLVC1alV07doV1atXN82ezJgxA2+99RYeffRRNGjQAN9//z0iIiLw229ameKxY8ewZs0afPvtt2jZsiXatWuHzz//HIsXL1aPIyIzIEs7ibGAT3WgzqN6j8bMdz1eWbDvY2yhL9P5ttJbhvLGwSmz3FyWeWxUvgKUP/74A82aNcNjjz0GPz8/NG7cGN98843p/rNnzyIyMlIt6xh5eXmpQGTHjh3qupzLso58HyN5vL29vZpxyU1SUhLi4+OznYiomKQmacmxot1YwN5B7xGZb+mxadfjy/n7etlrxdjW3lY681L+BPfKDFAkmdoG5StAOXPmDL788kvUrFkTa9euxejRo/Hyyy9jwYIF6n4JToS/v3+2r5PrxvvkXIKbrBwdHeHj42N6TE5TpkxRgY7xJLM4RFRM9i8CbkYCpSto6/N099JjtetxjLa3Sn52Pd79NZCWDAS2BAJbFOcoyVLV6KwlT18/B0TlaJdvI/IVoKSnp6NJkyb48MMP1eyJ5I2MGDFC5ZsUp0mTJiEuLs50Cg8PL9afR2SzpGmYNK8SMkMg5bV079JjR9fM0uO8tkbfM1e7zLb2dDfOGYm74vifsEX5ClCkMqdOnTrZbgsJCcGFCxfU5YCAAHUeFRWV7TFy3XifnEdHR2e7PzU1VVX2GB+Tk4uLi6r4yXoiomIgTcOunwVcfYCmQ/QejYXtevxu3nY93v9jRn5PNaB2z2IfIlmwEGM1zwrYonwFKFLBc+LEiWy3nTx5EpUrV1aXJWlWgoz169eb7pd8Ecktad26tbou57GxsQgNDTU9ZsOGDWp2RnJViEgnss5t3BSw5fPFu3OvNWn6bN5Lj2WGSrqXCqncYX4P3UutHtrux5GHtKUeG5OvAGXcuHHYuXOnWuI5deoUFi1ahK+//hpjxmglcnZ2dhg7dizef/99lVB76NAhDB48GBUqVECfPn1MMy7du3dXS0O7d+/Gtm3b8OKLL+LJJ59UjyMinYT9BUQdBpw9gBYj9B6NBZce/+fuj5VPwrHntRmqhk+X5CjJErn7al2cjT1RbEy+ApTmzZtj+fLl+Omnn1CvXj289957qqxY+poYvfbaa3jppZdUfoo8XhqwSVlxqVKZ+wn8+OOPCA4ORqdOndCzZ09VaiyBDhHpOHuy5RPtcrOhWiktFbD0eF7upcdyjLcZ29qPAJzdSnyYZMnLPCtha+wM0rzEwsiykVTzSMIs81GIisC5bcD8noCDMzD2EFA693wwuo+/3tb21pEZktHbAc/ymffJpnPzegAOLsC4I4BHOT1HSpbi+nngswbaUs+rYYB7WViy/Lx/c19vIgK2fprZcp3BSeFKj2VrgNxKj01t7Z9icEJ5V6ay9poypAMnVsOWMEAhsnVSeXLqb+0TWlHs0GvL7lZ6fOUkcGJV5gZ1RAXam+dP2BIGKES2zli5I1vPS+krFU65WtlLj2W3YmOgImXFUppMVJA8lNMbtD46NoIBCpEtu3oKOPp75qaAVPSlx8uGAgcWa7e34QwVFYBfHaBMFSAtCTid2cbD2jFAIbJl22T2xKBtTOZfV+/RWI+spccxp7U3lorNgKBWeo+MLPX1FJwxi1LQzSktEAMUIlsVdwk4sES73H6C3qOxztLjPl9mXpe29vJGQ1QQIQ9r5yfXAqnJsAWOeg+AiHQieRGyBFG5HTesKy7VO2pBipSKGt9giAqiUnPAvRyQcAU4vxWo/hCsHWdQiGxRwjUgdL52uT1zT4pVo6eBjpPY1p4Kx94hc+8mG1nmYYBCZIt2zQFSbgHlGwLVO+k9GiLKi+CMPBQpWc/aY8dKMUAhsjVJN4DdX2mX241nXgSRpaj2gLZX1o3LQMQ+WDsGKES2Zu93QGIc4FuDeRFElsTRBajZxWb25mGAQmRLUhKBHbMy+54wL4LIsgTbTrkxAxQiW3JgEXAzCvCsCNR/XO/REFF+1ewC2DsB18KAKydgzRigENmKtFRg64zMnhyybwwRWZZSXlouig0s8zBAIbIVR5YDsecBN1+gyWC9R0NEBRVsG8s8DFCIbIGUJG79VLvccjTg7K73iIiooGpLPxQ7rZJHOkJbKQYoRLYgbC0QfVQrUWzxnN6jIaLCKO2f2f1ZeqJYKQYoRNbOYAC2ZMyeNB8OuJbRe0REVFjBvaw+D4UBCpG1O78NuLgbcHABWo3RezREVJR5KOe2ArevwxoxQCGydls+0c4bP6NNDROR5fOtDpQLAdJTgZN/wRoxQCGyZhH/Aqc3AHYOQNuX9R4NERWlkIxZlOMrYI0YoBBZs63TtfN6/YEyVfQeDREVxzLPqfVAym1YGwYoRNbqykng6B+Zbe2JyLqUbwh4BWo7k5/+B9aGAQqRtdr2mZTwaD0T/OvoPRoiKmp2dlZdzcMAhcgaxYYDBxdrl9uN13s0RFRcgjMClBOrte0srAgDFCJrtOMLLbu/SnsgsLneoyGi4hLURuttdDsGuLAD1oQBCpG1SbgKhC7QLrfn7AmRVXNwBGr10C4f/xPWhAEKkbXZNQdIvQ2UbwRU66j3aIioxMqNV2qdo60EAxQia5IYD+z6WrvcfoKWREdE1q1aR8DRFYgLByIPwlowQCGyJnu/A5LigLK1MnskEJF1c3YDanTSLh+znmoeBihE1iIlEdgxS7vcdixgzz9vIpsR8rDVlRvzPxiRtdi/EEiI1ho3NXhc79EQUUmq2VXb0iL6KHDtNGwuQPnvf/8LOzu7bKfg4GDT/YmJiRgzZgx8fX3h4eGB/v37IyoqKtv3uHDhAnr16gU3Nzf4+flh4sSJSE21rtptohIn/Q+2zdQut3kJcHDSe0REVJLcfIAq7ayqmiffMyh169bF5cuXTaetW7ea7hs3bhxWrFiBZcuWYdOmTYiIiEC/fv1M96elpangJDk5Gdu3b8eCBQswf/58TJ48ueieEZEtOvIrEHsecCsLNB6k92iISA/BvW07QHF0dERAQIDpVLZsWXV7XFwc5s6di08//RQPPfQQmjZtinnz5qlAZOfOneoxf/31F44ePYqFCxeiUaNG6NGjB9577z3MmjVLBS1EVADp6cCWT7XLrUZrCXNEZHuCe2rn4buAm9GwuQAlLCwMFSpUQLVq1TBw4EC1ZCNCQ0ORkpKCzp07mx4ryz9BQUHYsUPrbifn9evXh7+/v+kx3bp1Q3x8PI4cOXLXn5mUlKQek/VERBlOrgGuHAOcSwPNn9N7NESkF69KQIXG2h5cJ1bBpgKUli1bqiWZNWvW4Msvv8TZs2fRvn173LhxA5GRkXB2doa3t3e2r5FgRO4Tcp41ODHeb7zvbqZMmQIvLy/TKTAwMD/DJrJe6WnA5mna5ebDAdfsf39EZKPLPMdW2laAIksyjz32GBo0aKBmPlatWoXY2FgsXbq0+EYIYNKkSWoJyXgKDw8v1p9HZDH++QCI+BdwcgdavaD3aIjIXMqNz27SGjfaapmxzJbUqlULp06dUvkokkciAUtWUsUj9wk5z1nVY7xufExuXFxc4Onpme1EZPNk99Itn2iXH5kJlM4+O0lENqhsLcC3BpCWDJxaB5sNUG7evInTp0+jfPnyKinWyckJ69evN91/4sQJlaPSunVrdV3ODx06hOjozOSddevWqYCjTp06hRkKkW2JOQssH6VdbjEKqD9A7xERkTmws7OaZZ58BSivvvqqKh8+d+6cqs7p27cvHBwc8NRTT6nckOHDh2P8+PH4559/VNLs0KFDVVDSqlUr9fVdu3ZVgcigQYNw4MABrF27Fm+99ZbqnSKzJESUx46xSwcDiXFApeZA1/f1HhERmZPgjAAlbB2QmgRL5ZifB1+8eFEFI9euXUO5cuXQrl07VUIsl8X06dNhb2+vGrRJ5Y3kqcyePdv09RLMrFy5EqNHj1aBi7u7O4YMGYJ333236J8ZkbVaPVHbEMzNF3hsAeDorPeIiMicVGwKeAQANyOBs5uBml1giewMBsvbm1nKjGXGRhJmmY9CNuXfhcDvY+RPFxi0HKjeUe8REZE5WjlO2zy06bPAw5/BEt+/uRcPkaW4fBD4c4J2ueN/GJwQUR66yq7S2hFYIAYoRJbgdiywdBCQmqhtCtY+I1AhIspNlfaAi5e2gejFvbBEDFCILKGV/W+jgevnAO8goO9XgD3/dInoHiQ3rVZX7fLxFbBE/C9HZO62f6a1rXZwBh7/Xtu1lIjofrKWG1teuikDFCKzJhn46zOq3HpMy9hng4goD2p0BhxcgOtngehjsDQMUIjMVfxl4OdhgCEdaPi0lo1PRJRXLh6ZyfTHLa9pGwMUInOUlgIsexZIuAL41wN6faJ1iCQiyo/gXto5AxQiKhJ//xcI3wm4eGp5J85ueo+IiCxR7Z6AnT1w+QAQewGWhAEKkbk58huw4wvtcp/ZgG91vUdERJbKvSwQ2CqzJ4oFYYBCZE6uhgG/v6hdbvNy5tbpREQFFdLbIpd5GKAQmYvkBGDJICD5BlC5LdDpHb1HRETWlIdyfhtwKwaWggEKkTmQHgWyd8aVY4CHPzDgO8AhX3t5EhHlrkwVwL++VhF4YjUsBQMUInOwdy5wcAlg5wAMmAeUDtB7RERkTUIsb5mHAQqR3i6GAmsmaZc7/xeo0lbvERGRtS7znN6gLSdbAAYoRHpKuAYsGwKkJWsJsW1e0ntERGSN/OsB3pW1DUdPrYclYIBCpBfZAv3XEUBcOOBTDXh0FpuxEVHxsLPL3Jvn+J+wBAxQiPSy+WPg9HrA0RV4/AeglJfeIyIiW8hDObla61Zt5higEOkh7G9g41Ttcu/pQEA9vUdERNYusCXgVhZIjNNKjs0cAxSikibtpn99TmqLgaZDgUZP6T0iIrIF9g5A7R7a5WPmX83DAIWoJKUmAUuHALevA+UbAd0zZlGIiEpCyMOZeSjSf8mMMUAhKklr3wQi9gGlvLVNAJ1K6T0iIrIlVR8AnD2AGxHa/yIzxgCFqKQcXArs+Va73O8boExlvUdERLbGqRRQo7NFLPMwQCEqCVFHgRWvaJc7vAbU6qr3iIjIVgVbRrkxAxSi4pYYDywdBKTcAqp1BB58Q+8REZEtq9UVsHcCrp7QdlA3UwxQiIqTJKH98SJw7RTgWRHo/62WSU9EpJdSXkDV9ma/Nw8DFKLitHM2cPR37dPKYwsA97J6j4iICKZlHjPOQ2GAQlRczu8A1k3WLnf7EAhsrveIiIg0tXtq55f2AvGXYY4YoBAVh5vRwLJngfRUoF5/oMUIvUdERJTJszxQKeND0wnzTJZlgEJU1NJSgZ+HATcjgbK1gYdnchNAIjI/wea9zMMAhaio/fM+cG4L4OQOPPED4OKh94iIiO4eoMj/q9uxMDcMUIiK0vFVwNbp2uVHPwfK1dZ7REREuStbAygXrC1Fh/0Fc8MAhaioxJwBlj+vXW45Wss9ISIyZ8G9zLbcuFABytSpU2FnZ4exY8eabktMTMSYMWPg6+sLDw8P9O/fH1FRUdm+7sKFC+jVqxfc3Nzg5+eHiRMnIjU1tTBDIdJXym1gyWAgKQ6o1ALo8q7eIyIiyvsyT9jf2v8xawhQ9uzZg6+++goNGjTIdvu4ceOwYsUKLFu2DJs2bUJERAT69etnuj8tLU0FJ8nJydi+fTsWLFiA+fPnY/LkjHJMIku06lUg6hDgVhZ4bD7g6Kz3iIiI7q9CY62JZEoCcGYTLD5AuXnzJgYOHIhvvvkGZcqUMd0eFxeHuXPn4tNPP8VDDz2Epk2bYt68eSoQ2blzp3rMX3/9haNHj2LhwoVo1KgRevTogffeew+zZs1SQQuRxdn3PfDvQsDOHhgwF/CqqPeIiIjyRioMTcs8K2DxAYos4cgsSOfOGTsiZggNDUVKSkq224ODgxEUFIQdO3ao63Jev359+Pv7mx7TrVs3xMfH48iRI7n+vKSkJHV/1hORWbh8APjzVe1yx/8A1R7Ue0RERPljDFBOrAbS02CxAcrixYuxb98+TJky5Y77IiMj4ezsDG9v72y3SzAi9xkfkzU4Md5vvC838rO8vLxMp8DAwPwOm6jo3b4OLBkEpCUBtboD7cbrPSIiovyr3BYo5Q3cugZc0FY7LC5ACQ8PxyuvvIIff/wRpUqVQkmZNGmSWj4ynmQcRLpKTweWjwZizwPeQUDfOYA9i+KIyAI5OAG1e5hdNU++/qPKEk50dDSaNGkCR0dHdZJE2JkzZ6rLMhMieSSxsdkbvkgVT0BAgLos5zmreozXjY/JycXFBZ6entlORLraNgM4uRpwcAEe/wFwzczFIiKy6HJjgwEWF6B06tQJhw4dwv79+02nZs2aqYRZ42UnJyesX7/e9DUnTpxQZcWtW7dW1+VcvocEOkbr1q1TQUedOnWK8rkRFY/z24EN72uXe04DKjTSe0RERIVTvRPg6ArEXgAiD8EcOObnwaVLl0a9evWy3ebu7q56nhhvHz58OMaPHw8fHx8VdLz00ksqKGnVqpW6v2vXrioQGTRoEKZNm6byTt566y2VeCszJURmLeEq8PNwwJAGNHgCaDJE7xERERWesxtQ/SFt48DjfwLls7cQ0UORL5pPnz4dvXv3Vg3aOnTooJZtfv31V9P9Dg4OWLlypTqXwOWZZ57B4MGD8e67bGxFlpB3Mgq4EQH41gR6fcpNAInIeoT0Nqs8FDuDwUwWm/JByoylmkcSZpmPQiVmy6fA+v8BjqWAERsA/7p6j4iIqOjcigE+rqHNEL+8H/CpCj3fv1l2QJTvvJOPGZwQkfVx8wEqt9EuyzKPzhigEOU376TxIL1HRERUPEIe1s4ZoBCZOeadEJEtqd1TO7+wA7h5RdehMEAhul+/k1N/a3knjy8AXDz0HhERUfHxDgTKS+sEA3BiFfTEAIXobph3QkS2KNg8qnny1QeFyGYw74SIbFW9foCrd+Zyj04YoBDlxLwTIrJlvtW1k864xEOUE/NOiIh0xwCFKCvmnRARmQUGKERGzDshIjIbDFCIBPNOiIjMCgMUIsG8EyIis8IAhYh5J0REZocBCtk25p0QEZklBihku5h3QkRkthigkO1i3gkRkdligEK26fyOzLyTHtOYd0JEZGYYoJDtSbgG/DxMyzup/zjQZLDeIyIiohwYoJBt5530ns68EyIiM8QAhWzL9s+AU+u0vJPH5jPvhIjITDFAIdvKO1n/XmbeSUA9vUdERER3wQCFbAPzToiILAoDFLJ+zDshIrI4DFDI+jHvhIjI4jBAIevGvBMiIovEAIWsF/NOiIgsFgMUsk7MOyEismgMUMg6Me+EiMiiMUAh68O8EyIii8cAhawL806IiKwCAxSyHsw7ISKyGgxQyHow74SIyDYDlC+//BINGjSAp6enOrVu3RqrV6823Z+YmIgxY8bA19cXHh4e6N+/P6KiorJ9jwsXLqBXr15wc3ODn58fJk6ciNTU1KJ7RmSbmHdCRGS7AUqlSpUwdepUhIaGYu/evXjooYfw6KOP4siRI+r+cePGYcWKFVi2bBk2bdqEiIgI9OvXz/T1aWlpKjhJTk7G9u3bsWDBAsyfPx+TJ08u+mdGtoN5J0REVsfOYDAYCvMNfHx88PHHH2PAgAEoV64cFi1apC6L48ePIyQkBDt27ECrVq3UbEvv3r1V4OLv768eM2fOHLz++uu4cuUKnJ2dc/0ZSUlJ6mQUHx+PwMBAxMXFqZkcsvG8k0WPa0s7kncyciOXdoiIzJS8f3t5eeXp/bvAOSgyG7J48WIkJCSopR6ZVUlJSUHnzp1NjwkODkZQUJAKUISc169f3xSciG7duqkBG2dhcjNlyhT1hIwnCU6IFOadEBFZpXwHKIcOHVL5JS4uLnj++eexfPly1KlTB5GRkWoGxNvbO9vjJRiR+4ScZw1OjPcb77ubSZMmqWjLeAoPD8/vsMkaMe+EiMhqOeb3C2rXro39+/erQOHnn3/GkCFDVL5JcZJgSE5E2fJOfhnOvBMiIiuV7wBFZklq1KihLjdt2hR79uzBZ599hieeeEIlv8bGxmabRZEqnoCAAHVZznfv3p3t+xmrfIyPIcpT3slvzwPxl9jvhIjIShW6D0p6erpKYJVgxcnJCevXrzfdd+LECVVWLDkqQs5liSg6Otr0mHXr1qlEGVkmIsqT7TOBsL+Yd0JEZMXyNYMiuSA9evRQia83btxQFTsbN27E2rVrVfLq8OHDMX78eFXZI0HHSy+9pIISqeARXbt2VYHIoEGDMG3aNJV38tZbb6neKVzCoTy5sBNY/652mXknRERWK18Bisx8DB48GJcvX1YBiTRtk+CkS5cu6v7p06fD3t5eNWiTWRWp0Jk9e7bp6x0cHLBy5UqMHj1aBS7u7u4qh+XddzPecIju5UYk+50QEdmIQvdBMfc6arISV04CC/sDcRcA3xoZ/U5K6z0qIiIqpvfvfCfJEpW48N1aM7bb1wGf6sDAnxmcEBFZOQYoZN6OrwJ+HgqkJgIVmwJPLwXcy+o9KiIiKmYMUMh87Z0H/DkeMKQDNbsBj80DnN31HhUREZUABihkfiQtauMUYNNH2vXGg4DeMwAHvlyJiGwF/+OTeUlLBVaOBf79Qbv+wOvAg5PYiI2IyMYwQCHzkZwALBsKhK0F7OyBXp8CzYbqPSoiItIBAxQyDwlXtUqdS6Fah9gB84DgnnqPioiIdMIAhfQXc1brcRJzGnAto1XqBLbQe1RERKQjBiikr4j9wI+PAQnRgFcQ8MwvQLlaeo+KiIh0xgCF9HNqPbB0MJB8E/CvDwxcBniW13tURERkBhigkD4OLAZ+HwOkpwJVHwCeWAiU4rYFRESksc84Jyq5HidbpwPLR2nBSb0BWut6BidERJQFZ1Co5KSnAWveAHZ/rV1v8xLQ+V3AnnEyERFlxwCFSkZKIrB8JHD0d+16tylA6xf0HhVZofR0AzadvIItYVfh5+mCqmXdUa2sO4J83eDi6KD38IgojxigUPGTXYgXDwTObwMcnIG+c4B6/fUeFVmZxJQ0LP/3EuZuPYtT0TfvuF+aEVcq44oqvlrAIoFL1XIe6nIFb1c42LNbMZE5YYBCxSvuIrBwAHDlGODiCTz5I1C1g96jIity9WYSFu48jx92nMe1hGR1m4eLIx5uWB63ktNw9moCzl5JwI2kVITH3FYnmV3JytnBHpV93TKCFmMA46Gul/Vwhh23WiAqcQxQqPhEHdUasN2IAEqX15JhA+rpPSqyEqeib6jZkl/2XUJyarq6raK3K4a2rYInmgeidCkn02MNBgOu3kzWgpWrN3EmI2iR6+ev3UJyWjrCom+qU04S7KjAJeNUrZx2XqWsOzyz/AwiKlp2BvnLtTDx8fHw8vJCXFwcPD1Z/WGWzm0DFj8FJMYBZWtrDdi8A/UeFVk4+Xe1/fQ1fLvlDP45ccV0e8NKXniufTX0qBcAR4f8JV2npRsQEXtbBS3nVACToAUwV2/i4vXbqvDsbsp6uGRZLnLXlo/KuSPIxw2lnJjvQlSY928GKFT0jvwG/DoCSEsGAlsBT/0EuPnoPSqyYDJDsvJgBL7dchZHL8er22TVpUuIP0Z0qIZmlcsUyzKM5LWEx9zKCFgyZ13kuiwt3Y0MRWZzjAm6zav6oFf98lwqIpsXzwCFdLPrK2D16/JZFwjuDfT/FnBy1XtUZKFibyVj0e4LWLD9HKLitYDA1ckBjzWrhKFtq6oAQC/xiSmZMy5XEnDuWublm0mpdzz+8WaV8EHf+nDK5wwPkTXJz/s3c1CoaKSnA+v/B2yboV1vNhzo+TFgz2luyr/z1xLw3dazWLr3Im6npKnbypV2wbNtqmBgyyB4uznrPUSVf9Kgkrc6ZZUz3+VIRLxK4pXnEhGbiNnPNGHuClEecAaFCi81GfjjReDgEu36Q28D7Sdo89xEeST/ikLPX8c3W87gr6NRptyP4IDSKr9EqnIstY/J+mNReOmnf1VVUW3/0vhuaHO1BERka+K5xEMlJumGtuHf6Q2AnQPwyOdA44F6j4osSGpaOtYcicQ3W87iQHis6fYHa5fDc+2qoW0NX6vI3Th8KQ7D5u9B9I0kNRv03ZDmqF/JS+9hEZUoBihUMm5EAYseAy4fAJzcgccXADW76D0qshA3ElOwZE845m07h0uxt9Vtzo726NuoIoa3r4pa/qVhbaRaaOi8PTgRdUPl0nz+VGN0ruOv97CISgwDFCp+V08BC/sBsecBt7LAwKVAxaZ6j4osgAQj87edxeLd4ap5mvBxd8YzrSpjUKvKanbBmkly7Zgf96lmcdK89r+P1MXg1lX0HhZRiWCAQsXr4l5g0ePArWtAmapajxPf6nqPiszcwYuxqkz4z0OXVe8RIT1DZBmnX5OKNtU3JCUtHW//dhiL94Sr68PbVcWbPUPYbp+sXjyreKjYnFwLLHsWSLkFVGgMPL0M8Cin96jIjDfu+/tYFL7deha7z8aYbm9dzRcjOlTFg7X8YG+Db8pSajylX30E+rjh47UnVEfci9dvYcYTjeHqbDuBGtG9cAaF8i50AbByHGBIA2p0Bh5bALh46D0qMkO3k9Pwc2g4vtt2TpXbCkd7OzzcsIKaLahXkcmhRn8ciMCrSw+odvsNA73x7eBmVr/MRbYrnjMoVKQkht00Ddj4oXa94dPAIzMBB/ZyoOyi4xPx/Y7zWLjrPGJvpajbPEs54umWlVUPkwCvUnoP0ew80rACynuVwojv96oqpr6zt2H+0Oao4Wd9ScJE+cEZFLo3eXn8OQHYO1e7Lv1NpM+JFZR9UtG5npCM2RtPYcGO86aN+2Q/mmFtq+CxZoFwd+FnofuRmaZn5+1WmxdKUPfVoGZoXd1X72ERFSkmyVLR2TYTWPe2vFS0zrAtRug9IjKzpZx528/iy42ncSNRq8hpEuSNkR2qoUudACZ95tO1m0kY+UOoaljn5GCHj/o3QL8mlfQeFlGRYYBCRUOary3sDxjSgR7TgJaj9B4RmVFztZ9DL2L63ydNe+RIx9c3egTjgVrlrKKxml5kg8IJyw7gz4OX1fWxnWvilU41eUzJKuTn/Ttfu1ZNmTIFzZs3R+nSpeHn54c+ffrgxIkT2R6TmJiIMWPGwNfXFx4eHujfvz+ioqKyPebChQvo1asX3Nzc1PeZOHEiUlPv3FyLdHT9HPDzMC04aTQQaDFS7xGRGZDPM2uPRKLbjM1449dDKjiRlu3Tn2iIVS+3x4O1/fhGWkhSbv35k43x/ANa6f6Mv8NUwGJcOiOyFfkKUDZt2qSCj507d2LdunVISUlB165dkZCgZemLcePGYcWKFVi2bJl6fEREBPr162e6Py0tTQUnycnJ2L59OxYsWID58+dj8uTJRfvMqOCSbwGLnwFuX9dKiXt9ypwTUmXC/b/cjlE/hOL0lQSUcXPC273rYMOrD6Bv40o2WS5cXORYymyUlCLLMtmv+y5hyHe7EXdbSzwmsgWFWuK5cuWKmgGRQKRDhw5qyqZcuXJYtGgRBgwYoB5z/PhxhISEYMeOHWjVqhVWr16N3r17q8DF319r8Txnzhy8/vrr6vs5O9+5S2lSUpI6ZZ0iCgwM5BJPcZCXwy/DgcO/AO7lgJEbAS+ugduyE5E38PHa4/j7WLS6XsrJXjVXG/lANe7KWwI2nbyCFxaGIiE5DTX8PDDv2eaqfwqRJSq2JZ6c5AcIHx8fdR4aGqpmVTp37mx6THBwMIKCglSAIuS8fv36puBEdOvWTQ36yJEjd11akidkPElwQsVk++dacGLvqPU5YXBis2TfmInLDqDHZ5tVcCKf5Ae2DMLmiR3xarfaDE5KiOT0LHu+DQI8S+FU9E1Vhrw/y6aKRNaqwAFKeno6xo4di7Zt26JevXrqtsjISDUD4u3tne2xEozIfcbHZA1OjPcb78vNpEmTVDBkPIWHa+2hqRiSYv9+R7vcbQpQpa3eIyIdxN5KxpRVx/Dg/23EstCLkK70PesH4K9xHfBB3/rw82Qvk5JWp4InfhvTFnXKe+LqzWQ8+fUOlQtEZM0K3JxAclEOHz6MrVu3ori5uLioE5VkUizLiW2xemT+9nOY/c8pxGeUDLes6qNyIRoHldF7eDZPmtwtfb41Xly0DxtPXMHzC0Pxdq86GNauqt5DIzKfAOXFF1/EypUrsXnzZlSqlLkEEBAQoJJfY2Njs82iSBWP3Gd8zO7du7N9P2OVj/ExVMKSE4DFAzOSYpswKdYGS4YlCfPTdScRGZ9oKhl+vUcwHmTJsFnxcHFUrfDf+eMIftx1Ae+uPIoLMbdUsjJ7zpBNL/FIPq0EJ8uXL8eGDRtQtWr2yL1p06ZwcnLC+vXrTbdJGbKUFbdu3Vpdl/NDhw4hOlpLuBNSESTJMnXq1Cn8M6L8J8X+/iIQdVhLin1iIeDEKXxbIH/P645GocdnW/DaLwdVcCIlw58+3hB/vtweHVkybJYcHezxfp96eLNnsLous16jftiLW8ls1UA2XMXzwgsvqAqd33//HbVr1zbdLomrrq6u6vLo0aOxatUqVTosQcdLL72kbpeSYmOZcaNGjVChQgVMmzZN5Z0MGjQIzz33HD78MGOvl/tgo7YitO0zYN1kLSl2yAqgchu9R0QlYO+5GExdfRx7z19X173dnPBixxp4plVl1YeDLMOqQ5cxbsl+JKWmo35FL8wd0ow5QmSbnWTv9mlq3rx5ePbZZ02N2iZMmICffvpJlQZLhc7s2bOzLd+cP39eBTIbN26Eu7s7hgwZgqlTp8LRMW8rTgxQiqFTbM//Y96JDQiLuoFpa0+omRNjybDsLjzqgeqsyrFQ0hZfNhqMSUhWM2DzhjZHLX9uNEjmia3uKW9JsV8/qOWdNHoGePQL5p1YsctxtzFjXRiWhYarqhzJV3i8WaBqo+7PT9wW7/y1BAydtwdnriagtIsjvnymKdrVLKv3sIjuwACF7p8UO7erlnciSbFDVzPvxErF3UrBl5tOY962s2oZQHSvG6D6mEjTL7Ku8vCR34di97kYONrb4cN+9VUQSmSp79/cA93WMCnWZkqGv99xDrP+OW1qj96iig/e6BmMJiwZtkrebs744bkWeO3ng/h9f4Q6D4+5hfFdajHZmSwSAxRbs30mcORXLSn28e8Br4p6j4iKUFq6Ab/uu4jp604iIk4rGa7tLyXDtVmVYwNcHB0w44lGCPJxw+cbTqmTlCFPG9BA3UdkSRig2Fyn2P9ql7tPZcWOFZGV2g3Ho/HRmuM4GXVT3VbBqxTGd62Nvo0rskeGDZEgdELX2ggs44Y3lx9SsymX4xLx9aCmapaFyFIwQLEVMWeBZUMzOsU+AzR/Tu8RURHZd+E6pq46rnIPhJerVjI8qDVLhm3Z480DUcHbFaMXhqqdqPt9uV1tNFjZ113voRHlCZNkbSUp9tsuQPQRoGJT4NlVzDuxksqNaWtO4M9Dl9V1F0d71fb8+QeqqyCFyLgb9bD5e3Ap9jZ83J3xzeBmaFqZeUikD1bxUCb59f48FDiyXEuKHbmJeSdWUK0huQWSBJuSZoCs3jzWNBDjutRS+7UQ5RQdn4jhC/bi0KU4OEsn2r71WOFDumAVD2XvFCvBCZNiLV5Sahp+2HFeBSfGypwHapXDpJ7BCA5goE53J91ll4xqpbrOrj0SpSp8jlyKw1u968DJocCb2hMVK86gWLNT64EfB7BTrIWTP9FVhyJVAqxUZBg383uzZwg61Cqn9/DIgqSnGzDrn1P4ZN1Jdb1FVR/MHtgEZT24WzyVDC7xkJYUK51iE2OBxs8Aj7BTrCUKPR+D9/88hn8vxKrrfqVd8GrX2ujftBIrc6jA/j4ahbFL9uNmUqqq9vpqUDPUr+Sl97DIBsQzQLFxTIq1igRYmTGRmRPh5uyAUR2qY0SHqnBz5sosFd6p6JsY+f1e1R5fEqyn9q+Pvo0r6T0ssnLxDFBsGJNiLT4Bdub6U/hhZ2YCrCQzSjdQ7lJLRS0+MQVjF+9XPXTEc+2q4o0ewXBkXgoVEybJ2jImxVpsAuz32yUBNgzxianqNibAUnGTHay/HdwM0/8+qZKvv916Fsci4/HFU01Qxp1N3UhfnEGxJkyKtTjy57fy4GVMW3sc4TG31W1MgCU9rD50GROWHcCt5DRUKuOKrwc1Q50K/P9KRYszKLYo5gzw8zAtOJGkWHaKNXt7z2kJsPvDsyTAdquN/k2YAEslr0f98qhWzgMjvt+rqsX6f7kdHz/WAL0bVNB7aGSjOINiDZgUa1HOXdUSYFcfzkyAle6vz7VnAiyZRx7USz/9iy1hV9X10Q9WV5VjDJqpKDBJ1maTYv2AUZsAT37iMUfXE5Ixc0MYFu48b0qAfaJ5EMZ1qQm/0gwoybx2xZZlx682nTHlQ818sjG83LiFAhUOAxRbsnW6tkOxJMUOWQlUbq33iCiHxJQ01ZZekhBvZCTAPli7HCb1CEHtgNJ6D4/orv44EIHXfj6AxJR0VPF1w9eDm6GWP1+zVHDMQbEVp/4G/v6fdrnHRwxOzIzE/iskAXbNcVy8npkA+59eIWhfkwmwZP4eaVgB1cu5Y+T3oTh37Rb6ztqGTx5vhO71AvQeGtkAzqBYclLs1x0zOsUOAh75nJ1izciejATYAxkJsP6eWgfYfkyAJQsUk5CMMT/uw44z19T1lzvVxNhONWHP1zLlE5d4bCopthkwdBXgyL00zMFZSYBdfRxrjjABlqxLalo6Plx1HN9tO6uudw7xw/QnGqF0KealUN4xQLFmTIo120+YM9drCbCp6UyAJev1S+hFTFp+CMmp6Wr5R/JSqpfz0HtYZCGYg2LNts3I3imWwYnuCbALtp/DF/9kJsB2lATYniFMJiSrJBtV1vT3wKgfQnH6SgL6fLENnz3VCA8F++s9NLIynEGxtKTYhQNkGgXo9Qmbsem8bf2KgxGYtuYELsVqCbAh5T3xn54haFezrN7DIyp2V24k4YUfQ7Hn3HWV/jahSy2M6VgDdsyFo3vgEo/VJsU+CCTGMSlW5z1zft8fgW82n0FY9E11GxNgyVbJMs97K4/ih53n1fUe9QLwf481hLsLJ+cpd1zisTZJN4HFA7XgRJJiZfaEwUmJ7/q6aNcFzNt2FlHxSeo2DxdHjOpQDc+1rwZXZwe9h0hU4pwd7fFen3qoW8ETb/9+WHVHPnMlAV8PborKvu56D48sHAMUcycTXL+/AEQfBTz8gSd+YMVOCbocdxvfbT2Ln3aH42ZSqmnGZGjbqniqRRC8XFnBQPRkiyDU9C+N0QtDcSLqBh75Yhs+f6oxN7ykQuESj7nb8imw/n+AvRPw7EogqJXeI7IJxyPj8fWmM6qTplTliJp+HhjRoRoebVQBLo6cMSHKKSo+USXPygaYstr5Ro9gjGhfjXkpZMIcFGsR9jfwozEp9lOg+XC9R2TV5E9hx+lr+GrzGWw6ecV0e8uqPhj1QDU8WMuPjamI8pCn9fZvh7F070VTN9qP+jfgMigpzEGxBlfDgF+GacFJk8FAM7lMxdWAatXhSHy9+TQOX4pXt0kc0qNeeYzsUA0NA731HiKRxZDZRQlI6lf0wv9WHFWzkKeib+KrQU0R6OOm9/DIgnAGxdxcPQVsmw4cWAKkp7BTbDG6lZyKJXvCMXfrWdNeOaWc7PF4s0AMb1eVSX5EhbTrzDW88OM+XEtIRhk3J8x6ugna1GAZvi2Lz8f7t31+v/nmzZvx8MMPo0KFCmpd8bfffst2v8Q7kydPRvny5eHq6orOnTsjLCws22NiYmIwcOBANThvb28MHz4cN29qJZs26/IBYOkQ4ItmwL8LteCkSnvgiYUMToqhf8P/rT2B1lM2qE94Epz4uDtjbOea2P5GJ7z7aD0GJ0RFoGU1X6x4qZ2aTbl+KwWDvtutks4t8HMx6SDfSzwJCQlo2LAhhg0bhn79+t1x/7Rp0zBz5kwsWLAAVatWxdtvv41u3brh6NGjKFVKa/ktwcnly5exbt06pKSkYOjQoRg5ciQWLVoEm3N+O7DlE60Jm1Gt7kC78UBQSz1HZnXOXLmJb7acxS/7Lqr+DaKyr5sqEx7QpBLXyImKQQVvVyx7vjUm/XoIy/+9hHdXHsXhiDh82Lc+Sjnxb46KaYlHZlCWL1+OPn36qOvyrWRmZcKECXj11VfVbTKN4+/vj/nz5+PJJ5/EsWPHUKdOHezZswfNmjVTj1mzZg169uyJixcvqq+3+iUeOeRhf2kVOuE7tdvs7IF6/YF24wD/unqP0KqEno/BV5vOYN2xKHXoRaNAb9XDpGvdADZXIyoB8v7w3bZz+HDVMaSlG9Cgkpda8mFeim2J1ytJ9uzZs4iMjFTLOkYykJYtW2LHjh0qQJFzWdYxBidCHm9vb49du3ahb9++d3zfpKQkdcr6BC1Sepq2j87WGUDUIe02B2eg0UCg7cuATzW9R2hVreglIPl68xmEnr9uul12YB3ZoTqaVynD0keiEiR/b5LbFRxQGmMW7cPBi3HoNmMzXu8ejEGtKrNCjoo3QJHgRMiMSVZy3XifnPv5+WUfhKMjfHx8TI/JacqUKfjf//4Hi5WaBBz4Cdj2mdayXji5A82HAa3GAJ7l9R6hVW3e9+u+S/h2yxmcuZqgbnN2sEffxhUxokNV1PDjBn5EempboyxWvNgOE5YdwO6zMXjnjyP48+BlfDSgAaqWZe4XWViZ8aRJkzB+/PhsMyiBgYGwiBb1ofOBHV8ANy5rt7mWAVqOBlqMANx89B6h1Yi9lYyFO89j/vbzuHpTm20rXcoRz7SqjKFtqsDPU8t/IiL9ybLO4hGtsHDXeUxdfRy7z8Wg+4zNmNC1Foa3q8ZlVyr6ACUgIECdR0VFqSoeI7neqFEj02Oio6OzfV1qaqqq7DF+fU4uLi7qZDFuxQC7vwZ2zQFuZywvlK4AtHkRaDIEcPHQe4RWIzzmlioTXro3HLeS09RtFbxKYVi7qqr9tuyXQ0TmR5Z0Breugo61/fDm8kPYEnYVH646jj8PReLjAQ1Qy5+znbauSP97S9WOBBnr1683BSQy2yG5JaNHj1bXW7dujdjYWISGhqJp06bqtg0bNiA9PV3lqli0+MvabMneeUCKtryg8krajgUaPsly4SJ0+FKc6vi66tBllXAnQsp7qsTXXg3Kw8kh3xX0RKTTbMr3w1pg2d6LeO/PozgQHoteM7fg5Ydq4vkHq/Nv2YblO0CRfiWnTp3Klhi7f/9+lUMSFBSEsWPH4v3330fNmjVNZcZSmWOs9AkJCUH37t0xYsQIzJkzR5UZv/jiiyqBNi8VPGZJ8kokv2T/IiAtWbvNvz7QfhxQpw9gz1K6our4uuXUVZVfsu3UNdPt7WuWVR1f29Uoy8RXIgskf7ePNw9Umwv+Z/khrD8ejU/WnVS7I08b0AD1KnrpPUSyhDLjjRs3omPHjnfcPmTIEFVKLN/unXfewddff61mStq1a4fZs2ejVq1apsfKco4EJStWrFDVO/3791e9Uzw88rb0YTZlxpGHga3TgSO/AgatrwaCWgPtJwA1OstfnX5jsxKyr8f2U9ew5nCkqsqJSdACQFmj7t2gvNqIjP+8iKyHvIdIe3xJno29laL+1kc/UB0vdarBTTqtADcLLG4XdmnN1cLWZt5WowvQfjxQuU3Jj8fKJCSlqs36JCjZcDwaN5NSTfd5uzmhX+NKGNauCiqVYf8EImvu+PxfqfA5dNm0m7jMpjQOKqP30KgQGKAUBzlMp9drzdXOb8u40Q6o20drrla+YcmMw0rF3UrB38eisOZIJDafvIKkjE6vwt/TBd3qBqB73QC0qOoDR65JE9mM1Ycu4+3fD+PqzWS1iaf0UhnfpTY7P1soBihF3Vzt2B9aYBJ5ULvN3glo9JSW/OpbvXh/vhWLvpGIv45EYe2RSOw4fQ2pGcmuIsjHDT3qBaBbvQA0quTNJk5ENux6QjLeW3kUv/57SV2v4uumdkyWvX7IsjBAKQqpycDBJcC2GcC1jKRgJzeg6bNA6xcBr4rF83NtoCxYAhI57T1/3dR6XtT2L60CEglMpNskE16JKKsNx6Pw5q+HERmfqK4Pbl0Zr3UPZjsBC8IApTCSE4B93wPbPwfitWgdpbyAls8DLUYB7ozY8+tU9A2VTyLLN4cvZd+moGGgt1q66VbXH9XKsT8MEd1bfGIKpqw6hp92h6vrFb1dMbV/fbSvWU7voVEeMEApqH9/BNa9DdzKKGH18NdmS5oNBVzYNCiv5CUlgciaI5dVYHL6SkZPGFkds4PKI5GgRDbqk51OiYjya2vYVbzx60FcvH5bXX+iWSDe7BUCL1cnvYdG5rhZoMVzKqUFJ96VgXbSXO1p7Ta6L2mWJpvySUAiyzeXYrV/GsLJwU71KOleLwCdQ/zh68GGdURUOO1qlsXasR3w8doTmL/9HJbsDcfGk9H4oE99dK6TfT84skycQcmZEHt8JVC7F+DA2O1+klPTsfPMNbV0I8muxj1whKuTAx6sXU4FJR2D/eBZip9qiKh4yKaDr/9yEGczNgh9tFEFvPNwXfi4O+s9NMqBSzxUbG4np2Fz2BWsPRypyoLjEzN7lMjmfF1C/FWia4ea5VgGSEQlupP59HUn8c2WM5CCQF93Z7z7aD219QWZDwYoVKTibqdg44lotXyz8cQV3E7RNuUTZT2cVS6J5JS0quYLZ0f2KCEi/ewPj8VrPx/Ayaib6rpUBf7v0brwK83lenPAAIUKRZZq9pyNwa6zMWrq9FhkfLZyYMmal6UbOTUJKsOt0YnI7LbImPXPacz+55TqryQdqN95uA76NKrI9gU6Y4BC+SIJrbvPXlPBiAQlZ7JU3RhVL+euBSV1y6NeRU/+kROR2TsSEYfXfj6IIxFae4OHgv3wQd96KO/F6kG9MEChu5Jf95mrCSoYMZ6yVtwYSaM0KQduXsVHnft7cnqUiCxPSlo6vt58Bp/9HYbktHSUdnFU5chPNg/kBy0dMEChbOW/xyPjVSCy55wWkMieFlnJEo3sCNyiShm0qOqL5lXKwNuN2e9EZD3Com5g4s8HVY6KaFvDF1P7NUCgDzcdLUkMUGy89PfQpThTMCLnN7JU2ghJZG0U6I2WVbXZEckjcWeraCKygQ9s87adVb1TZENSaYfwevfaGNy6Cvf7KiEMUGys7PffC9exOyMg2XfhOhJTMncCFu7ODmhaxccUkDSo5AUXR5YAE5Ftkn4p0jdF/meKxkHeGNG+mmokyUrE4sUAxcr3oQg9dz2jwuaami1JScv+Kyzj5mTKHWlZ1Rch5UvD0YF/dERERunpBvy46zymrj6OhGStdUJZDxc81qySyk+p7Ouu9xCtEgMUGyr5Ff6eLioQkYBETjXKeXC6kogoDy7H3caPOy+oVvlXbmR2w5btOZ5uGcRZlSLGAMWCpaalY+/566p1/KaT0dk22jOq4utmqrCRwCTQx5XZ6EREhaz2WX8sGj/tvqC6ZRvfGaUZ5YCmgXiqBWdVigIDFAvMI9kSdgV/HY3C+mNRuH4r5Y6SX+OSDUt+iYiKV3jMLSzZE57rrMpTLYLQpQ5nVQqKAYoFuJ6QjPXHo/HXkUgVrWdNbJWuh52C/dGljp+aISnDDa+IiMxuVkVyVaqU5axKfjBAMeOofN3RKPx1NBJ7zl1XJW9Z28d3reuPrnUCVB8SJrUSEZn/rIr0U3m6RWXOquQRAxQzIYf2eOQNlU8iQYmx3bJRSHlPdK3jrwKTOuXZPp6IyBJmVTYcj8aiXdlnVWT35AHNKuGp5kGcVbkHBig6klmRvediVD6JBCXhMZlt5KWwplkVHxWUdKsbwA6GREQWPquydG+4mlmJzjGrIrkqMiPOWZXsGKCUsMQUSXK9qvJJJK8kJiGzlbyLoz3a1yynZkk6BfvB18NF17ESEVHR4qxK3jFAKQGxt5JV8pTMkmw+eRW3U7RGP8LL1QmdQvxU9NyhVlm4ObONPBGRLeCsyr0xQCkmsuvvuiORWHskSrWWz5nkKklSMlMiJcFOTHIlIrJZ0tNKZtSlAmjTSc6qGDFAKSJyaE5EZSa5Hr4Uf0d/kq51A1ROSd0KTHIlIqK8z6q0qe6rutXa0qxKPAOUgpNZkVDVyTVSJbpeiLmVPcm1so+aJZHZEnYVJCKi/MyqqFyV3GZVmlbCky2CUNXKZ1UYoBSQTMX939oTuJYlyVWi2g41y6oI96EQP7WZFBERUWFcvJ7RVyXHrEr1cu6o4uuuPgBX9nVDkK+bui5pBNYwy5Kf929mb2ZRupSjCk5Ukmuwn5opkQocdxceJiIiKjqVyrhhQtfaeKVTzWyzKrL/Wm57sNnbARXLuKKyj3tG0OKGIB8tiJGTNRZjcAYli4SkVBwIj0XzqkxyJSKikhUdn6jyHs9du4UL1xJw/tot7RSTkG07lNyUK+2Cyj4SrGQGLeqyj5vaPsVcciS5xENERGQlDAaDWgbSApaMwCVGC2IkmIm7nX2D2dxWB2SZSGZeJGAxXpZzv9IusJfpmRJiMQHKrFmz8PHHHyMyMhINGzbE559/jhYtWtz36xigEBERaeJupahZltxmXqLiM/NbciPNRIPuMvMiS0pFvZpgEQHKkiVLMHjwYMyZMwctW7bEjBkzsGzZMpw4cQJ+fn73/FoGKERERPd3OzlNVaNmzrxkBjDS2ytrP6+cejUoj1lPN4HNBSgSlDRv3hxffPGFup6eno7AwEC89NJLeOONN+75tQxQiIiICt+iPyL2draZF3U5I4gZ3q4qXuseDJuq4klOTkZoaCgmTZpkus3e3h6dO3fGjh077nh8UlKSOmV9gkRERFRwsnyjLe1I75Vy2e5LTzcgOe3eibnFTZdSlatXryItLQ3+/v7Zbpfrko+S05QpU1TEZTzJTAsREREVD0mcLeXkoO8YYAFkpkWmg4yn8PBwvYdERERExUiXJZ6yZcvCwcEBUVFR2W6X6wEBAXc83sXFRZ2IiIjINugyg+Ls7IymTZti/fr1ptskSVaut27dWo8hERERkRnRrTfu+PHjMWTIEDRr1kz1PpEy44SEBAwdOlSvIREREZGtByhPPPEErly5gsmTJ6vE2EaNGmHNmjV3JM4SERGR7WGreyIiIjK792+LqOIhIiIi28IAhYiIiMwOAxQiIiIyOwxQiIiIyOwwQCEiIiKzwwCFiIiIzA4DFCIiIjI7ujVqKwxj6xappyYiIiLLYHzfzksLNosMUG7cuKHOAwMD9R4KERERFeB9XBq2WV0nWdlYMCIiAqVLl4adnV2RR3cS+ISHh7NLbQYekzvxmOSOx+VOPCZ34jGx3eNiMBhUcFKhQgXY29tb3wyKPKlKlSoV68+QF4e1vkAKisfkTjwmueNxuROPyZ14TGzzuHjdZ+bEiEmyREREZHYYoBAREZHZYYCSg4uLC9555x11ThoekzvxmOSOx+VOPCZ34jHJHY+LFSTJEhERkXXjDAoRERGZHQYoREREZHYYoBAREZHZsdgA5dq1a/Dz88O5c+dg7h588EHVUE5O+/fvL7afw2NyJx4Tyz8uzz77rOm4/Pbbb8X2c3hM7sRjYvnH5b///a/puMyYMQOWxGIDlA8++ACPPvooqlSpggMHDuCpp55SHfhcXV0REhKCzz77LNvjN27caPolZT1FRkbe9WecOHECHTt2hL+/P0qVKoVq1arhrbfeQkpKSrbHLVu2DMHBweox9evXx6pVq7Ld/+uvv2L37t0oyWMif0Ddu3dX3fokI1yOzYsvvpht/6KCHJOsTp06pbr5ent733GfOR6TrOT4SLM/eb6xsbGFOibyTyq3r9m5c6dZHpPcjktu41+8eHGhXyuSg/9///d/qFWrlnodVqxYUf3srOR7N2nSRN1fo0YNzJ8/P9v98rd8+fJl6PFakbE0aNBA/c7kDWnMmDH5/r1nJd8vt6+RU3R0tFkfk7yMvaCvk7Vr16JVq1bq/0m5cuXQv3//O978zeWY5PZa2bNnDzp16qT+F5YpUwbdunVT70uFea2I9evXo02bNuq4BAQE4PXXX0dqaiqyOnjwINq3b69eo/J/ftq0adnuf/XVV9VxKe7mpsXCYIESEhIMnp6ehh07dqjrc+fONbz88suGjRs3Gk6fPm344YcfDK6urobPP//c9DX//POPVCsZTpw4Ybh8+bLplJaWdtefI9/ru+++M+zfv99w7tw5w++//27w8/MzTJo0yfSYbdu2GRwcHAzTpk0zHD161PDWW28ZnJycDIcOHcr2vc6ePat+/r///lsixyQmJsYwe/Zsw549e9TY//77b0Pt2rUNTz31VKGOiVFycrKhWbNmhh49ehi8vLyy3WeuxySrRx99VI1dfv7169cLdUyMz0OOcdavkWNkbsfkbsdFfua8efOyjf/27duFfq289NJL6nUnfztnzpwx7N271/DXX3+Z7pfb3NzcDOPHj1fHRf5m5TitWbPmju8lP3/58uWGkjomn3zyiaFChQqGH3/80XDq1CnDgQMH1PPIz+89p1u3bmV7rJy6detmeOCBB8z+mORl7AV5ncjzdXFxUf9X5TiHhoYaOnToYGjcuLHZHZPcjsuNGzcMPj4+hmeffdZw/Phxw+HDhw39+/c3+Pv7m14LBXmt7N+/3+Ds7Gz43//+ZwgLC1Pvb8HBwYYJEyaYHhMXF6d+zsCBA9XP/emnn9R731dffXXH96tcubJh+vTpBktikQHKsmXLDOXKlbvnY1544QVDx44d7/jDyfpmVBDjxo0ztGvXznT98ccfN/Tq1SvbY1q2bGkYNWpUib7x5OWYfPbZZ4ZKlSoVyTF57bXXDM8884x6U8sZoJj7MZHATf6prl+//q4BSn6OSV6eh7kck7sdl/v9Uy/IcZE3EkdHR/VP+16vo7p162a77YknnlBvfCX5xpPzmEiAL//o5Q3lboridxUdHa0C1e+//97sj0lexl6Q14n8HHmdZA1i/vjjD4OdnZ3pDdxcjklux0U+BMrPvHDhgum2gwcPqtsksCjoa2XSpEnqQ2BWclxKlSpliI+PN/0vK1OmjCEpKcn0mNdff119KLCGAMUil3i2bNmCpk2b3vMxcXFx8PHxueP2Ro0aoXz58ujSpQu2bduWr58rSxpr1qzBAw88YLptx44d6Ny5c7bHyfSe3G5Ox0Q2V5QlhKxjL+gx2bBhg1qumDVrVq73m/MxOXr0KN599118//3399yoqiCvk0ceeUQtA7Rr1w5//PGHWR6Te71WZPmibNmyaNGiBb777rtct0PPz3FZsWKFWhZduXIlqlatqqbDn3vuOcTExJjdccl5TNatW6c2Jb106ZJaMpbp8ccff1xt4paf3/v9yOvQzc0NAwYMMPtjkpexF+R1Ij9D/hbnzZuHtLQ09b/7hx9+UMfAycnJrI5Jbseldu3a8PX1xdy5c5GcnIzbt2+ry/K6ybm0nJ/XSlJSklq2yUpSGBITExEaGqquy/Pv0KEDnJ2dsx0XSU+4fv06LJ1FBijnz59XuRV3s337dixZsgQjR4403SZ/LHPmzMEvv/yiTrJWJ0mJ+/btu+/PkzVAeaHUrFlTrfXJG5yRrK1KjkpWcj2veRzFfUwkN0f+icjav2w+9e233xbqmEjuhiSjyfrv3TazMtdjIn/wcjw+/vhjBAUF5fo1BTkmHh4e+OSTT1TQ9ueff6p/Pn369Mn2D8hcjsndXivyml66dKl6Y5b1/xdeeAGff/55oY7LmTNn1M+S4yJvZvKakX+sWd/Q7nZcJFdK/tHrdUxk7BKgfPjhhyqx8Oeff1aBlbzhyptQXn/v9yNvZE8//bR64zH3Y5KXsRfkdSLB619//YU333xT5ZdIHsfFixfV69Hcjklux0XyQyQ/ZuHChepYyOtCPsiuXr0ajo6OBX6tdOvWTb2X/fTTTypwk2DZ+N5jzLW523Ex3mfpLHI3Y3lB5owsjQ4fPqySl6RdcNeuXbNFuXLKGnScPn0a06dPV9H6vUiwI9tDS9LTxIkTVdLfa6+9Bks4JvL85FicPHkSkyZNwvjx4zF79uwCH5MRI0aof0oStZu7nMdEnr98qnnmmWfu+jUFOSYy6yDH1ah58+ZqxkoCIfnEZG5ye628/fbbpsuNGzdGQkKCGv/LL79c4OMib/ASFEpwIkmyxjc1+fQpn/Cyfj9zOyYydkmGnzlzpun/iLxRSKLiP//8o948Cvt7l0+/x44du+//H3P8P3u3sRfkdSJvpPJ/ZciQIeoDhPyvnTx5sgpkJWCWZFJzPi5yffjw4Wjbtq0pmJD3iF69eqnkWQlaCvJa6dq1q7r/+eefx6BBg1TwJn+nMoNzr9lfa2KRz1J+2blNX8n0vWRSy8yJVNvcj0xly7LN/cingDp16qg/nqlTp6qyLXkRCvmHFRUVle3xcl1uN4djIuOQyhH5I/jqq6/w5Zdf3jPT/X7HRJZ35I9PPhnISf4wZUpWLsuygDkfE+PSlHHs8loxPk6CuMK+TrJq2bJltq8xl2Nyr9dKzvHLp1gJMAp6XOTTtBxnY3AiJEAUFy5cuOdxkdm5rJ/MS/qYyNiF/N0bSXWJPM449rz83u9FZjNlKSTnMoq5HpO8jL0grxNZKvby8lLVJxIcy4cfmY2QCpZdu3aZ1THJ7bgsWrRIVenIEpUEHlKNJLedPXsWv//+e6FeK+PHj1dVhvKau3r1qvrwLWTp9F7HxXifpbPIAEVexBKMZHXkyBFVEixReM4yxruRXhPGf0R5ZfxkJeeidevW6g8pK4n65Xa9j0lOxjHf603nfsdEPjnJY4wnmXKUKU653LdvX7M+JjLlLLNgxrEbl7vkE0nW8tGieJ3k/BpzOSZ5fa3I+KVc8l6blt3vuMgnSimJlE/QRjKTJypXrmxWxyXnMZGxC5npMZIlHnmTMI69MK+VmzdvqiUMCfBzMtdjkpexF+SY3Lp1644ZAQcHB3Vubv9nczsuxvFnnekxXjeOvzCvFTs7O7WkJIGYzNDIB2Yptxby/Ddv3pyt9YUcF5nFkr9fi2ewQJIhLVnfkmkvpFRTsqqlqiRrCZdkmRtJ9vJvv/2msqrl8a+88orB3t7+nln6CxcuNCxZskRVI0jJsVyWskMp6cpaPipj+b//+z/DsWPHDO+8844u5aM5j8mff/6pSqRlHPKzV65caQgJCTG0bdu2UMckp9yqeMz1mOSUW8VBQY7J/PnzDYsWLVLPVU4ffPCB+ho5/uZ2THI7LlIZ8M0336ixyPOWygAp6Zw8eXKhjotUZTRp0kSVjO7bt0+VGEvlUpcuXe4oH504caI6LrNmzdKlfDS314qUokvliPzu5Dn37t3bUKdOHVNlSV5+73fz7bffqmqM3KpdzPmY3G/sBXmdSDWdVOxIOe3JkydVmbFU50jViZQ2m9Mxye24yHikTHr06NHqvULKfeW9SP4vRkREFOq1Mm3aNPXz5Hu+++676n9G1ucWGxuryowHDRqkHrN48WJ1nFhmrLMWLVoY5syZoy7LP3t5UeY8yS/E6KOPPjJUr15d/WFJzfqDDz5o2LBhwx1vtlljNvllyz9YDw8Pg7u7u/rn9OGHH2brDyGWLl1qqFWrlqpZl39oEhzkVBJvPFmPiTy31q1bqz8Sec41a9ZU5WdZ/6kU5JjkJUAx12OSlwClIMdE/vlI8Cf/GKQ/gvxMKUU012OS87isXr3a0KhRI9PrvGHDhuq+rGWfBX2tXLp0ydCvXz/1veUfqfSKuHbt2h2/B/n5clyqVaumvk9uivuNJ+drRXpMDBs2zODt7a2ec9++fbOVkubl9258jcnvNSv523z66afvOhZzPSb3G3tBXyfSv0P6nsjrTz5sPvLII+qN3ByPSW7HRXr7yIc/+V8oZb8PPfRQtp46BX2tdOzY0fQ/XIL7VatW3TEW6c8jrS8kSKpYsaJh6tSpuY6ZAUoJMs4I5KWpWF7JJ8asTYeKUkm88fCY3InHxDqOS0m88RTHMZFPyDVq1LhnQy5bOyaW/jqx1NdKZQsMUCwyB0VIhrQkw0rpVVGRsrCcbYKLQo8ePVC3bl0UNx6TO/GYWP5xkSoGKdO0xGMi2xlIqbKxn0dRseRjYumvE0t7rXz44YfquNwrudtc2UmUovcgrJ28iI21+tJ/I2tTHVvFY3InHpPcyT4vxj2kJKnQ3d0dto7H5E48JrmT5G5jc0SpRJOKKUvBAIWIiIjMjsUu8RAREZH1YoBCREREZocBChEREZkdBihERERkdhigEBERkdlhgEJERERmhwEKEeWLbBgpm7lJsyoiouLCPihElC/PPfec6kw5d+5ctduv7LRqzmSn16LuzklExY8zKESUZzdv3sSSJUswevRoNYMyf/78bPf/8ccfqFmzJkqVKoWOHTtiwYIFarv42NhY02O2bt2K9u3bq+3jZev4l19+GQkJCXn6+ZcvX1Y/V762atWqWLRoEapUqYIZM2aYHiM/78svv8Qjjzyiuol+8MEH2Lhxo7r9zz//RIMGDdT4WrVqhcOHDxfh0SGiosQAhYjybOnSpQgODkbt2rXxzDPP4LvvvpMNR9V9Z8+exYABA9CnTx8cOHAAo0aNwn/+859sX3/69Gl0794d/fv3x8GDB1WwIwHLiy++mKefP3jwYERERKiA45dffsHXX3+tWpzn9N///hd9+/bFoUOHMGzYMNPtEydOxCeffII9e/aott8PP/ywmmEhIjOk926FRGQ52rRpY5gxY4a6nJKSYihbtqzaJl68/vrrhnr16mV7/H/+8x+1u+z169fV9eHDhxtGjhyZ7TFbtmwx2NvbG27fvn3Pn33s2DH1vfbs2WO6LSwsTN2WdZdWuT527Nhct7JfvHix6bZr164ZXF1dDUuWLCnAkSCi4sYZFCLKE8k32b17N5566il13dHREU888YTKRTHe37x582xf06JFi2zXZWZFloUkh8V46tatG9LT09UMzP1+vvzMJk2amG6rUaMGypQpc8djmzVrluv3aN26temyj4+Pmgk6duxYnp4/EZUsxxL+eURkoSQQSU1NzZYUKxMWLi4u+OKLL/KcwyJLP5J3kpPs4FxUuJMtkeVjgEJE9yWByffff6/yN7p27ZrtPsk5+emnn9RsxKpVq7LdJ7keWcnsx9GjR9XMR37J95dx/Pvvv2jatKm67dSpU7h+/Xqev8fOnTtNgZB83cmTJxESEpLvsRBR8WOAQkT3tXLlSvWGPnz4cHh5eWW7TxJeZXZFEmg//fRTvP766+px+/fvN1X5SAWNkPukekaSYqVcWWY6JGBZt27dfWdhJDm3c+fOGDlypKrSkdLhCRMmqIoe4/e/n3fffRe+vr7w9/dXCbxly5ZVARYRmR/moBDRfUkAIsFBzuDEGKDs3bsXN27cwM8//4xff/1VlfJKEGGs4pFlICG3b9q0Sc1cSKlx48aNMXny5Dz3UpFZHAkuOnTooKp0RowYgdKlS6uy4byYOnUqXnnlFTUDExkZiRUrVsDZ2Tlfx4KISgYbtRFRsZEeJHPmzEF4eHixfP+LFy+qXip///03OnXqdNfHSVmy9GWRWSBvb+9iGQsRFS0u8RBRkZk9e7aq5JFllG3btuHjjz/Oc4+TvNiwYYNKtK1fv75q2vbaa6+pRm0yo0JE1oUBChEVmbCwMLz//vuIiYlRyaiSIzJp0qQ8fe2WLVvQo0ePu94vgYk0VXvzzTdx5swZtbTTpk0b/Pjjj2xlT2SFuMRDRGbh9u3buHTp0l3vL0jlDxFZLgYoREREZHZYxUNERERmhwEKERERmR0GKERERGR2GKAQERGR2WGAQkRERGaHAQoRERGZHQYoREREBHPz/7XuSlX6wOWxAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "simulate_moments({}, agent=LifeCycleAgent).plot()\n",
    "empirical_moments.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Estimate the model parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Matthew\\anaconda3\\envs\\HARKlatest\\Lib\\site-packages\\optimagic\\deprecations.py:247: FutureWarning: Specifying bounds via the arguments lower_bound, and upper_bound is deprecated and will be removed in optimagic version 0.6.0 and later. Please use the `bounds` argument instead.\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "init_params = {\"CRRA\": 3.009252, \"DiscFac\": 1.006925}\n",
    "lower_bounds = {\"CRRA\": 1.0, \"DiscFac\": 0.9}\n",
    "upper_bounds = {\"CRRA\": 10.0, \"DiscFac\": 1.1}\n",
    "\n",
    "res = estimate_msm(\n",
    "    LifeCycleAgent,\n",
    "    init_params,\n",
    "    empirical_moments,\n",
    "    moments_cov,\n",
    "    simulate_moments,\n",
    "    optimize_options={\n",
    "        \"algorithm\": \"scipy_lbfgsb\",\n",
    "        \"error_handling\": \"continue\",\n",
    "    },\n",
    "    estimagic_options={\n",
    "        \"lower_bounds\": lower_bounds,\n",
    "        \"upper_bounds\": upper_bounds,\n",
    "    },\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>value</th>\n",
       "      <th>standard_error</th>\n",
       "      <th>ci_lower</th>\n",
       "      <th>ci_upper</th>\n",
       "      <th>p_value</th>\n",
       "      <th>free</th>\n",
       "      <th>stars</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CRRA</th>\n",
       "      <th>0</th>\n",
       "      <td>4.293911</td>\n",
       "      <td>1.883043</td>\n",
       "      <td>0.603213</td>\n",
       "      <td>7.984608</td>\n",
       "      <td>0.02259</td>\n",
       "      <td>True</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DiscFac</th>\n",
       "      <th>0</th>\n",
       "      <td>1.024171</td>\n",
       "      <td>0.004468</td>\n",
       "      <td>1.015415</td>\n",
       "      <td>1.032928</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>True</td>\n",
       "      <td>***</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              value  standard_error  ci_lower  ci_upper  p_value  free stars\n",
       "CRRA    0  4.293911        1.883043  0.603213  7.984608  0.02259  True    **\n",
       "DiscFac 0  1.024171        0.004468  1.015415  1.032928  0.00000  True   ***"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat(res.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'CRRA': 4.29391054139843, 'DiscFac': 1.0241712636017626}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res.params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CRRA</th>\n",
       "      <th>DiscFac</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CRRA</th>\n",
       "      <td>3.545852454446082</td>\n",
       "      <td>4.135502633124609e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DiscFac</th>\n",
       "      <td>4.135502633126173e-05</td>\n",
       "      <td>1.9959331612810724e-05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          CRRA                 DiscFac\n",
       "CRRA         3.545852454446082   4.135502633124609e-05\n",
       "DiscFac  4.135502633126173e-05  1.9959331612810724e-05"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(res.cov(method=\"robust\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'CRRA': 1.883043402167375, 'DiscFac': 0.004467586777311743}"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res.se()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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f26RJEzWahKOnbNczJigpx5BP07qbP7FwVFXcrgcKHwoSjqp7EjwmtIPJBBm7Ehd2N+jDf9lmClDb80nYVUrhwdiMxMDjQA8avVHsGtVh3Ai9U09Dv/nbc1Oj7ezWs+0SYZwURzvRI6N3wybGdhL372vcuHFICkwVQHHKY23bHl7/7Gai/SkBr5WErjM95krvStPjrTZv3mzdhuef3cuJhaLl8uXLasQYu5Of1oWlw4cTps7geePE48Ru2qf9zvG8Omrmb1dBPDtCisH4ALqFmUiQxBU7fJri8G7GuXA7emV4M04o74U9sNuKP4Ls6qFoohucoiShOAHGpHC4OZ+82J3EH1TGprDrjU/2CTF69Gg1xJmf4fDsEiVKqK4zBhzSu8DlxD4521N7a8KECahevbr6geX38lhxGDxvEIyL0nMUffLJJ/jjjz9UlwXjNvSh57oH4UnwvNCrw2HsTZs2VV1rkydPVm2MT3A8DXrKKBzZrcJ90MXPDNu0O+5TcFx4XbDNHB7Oc2ubQZkBz+w2oEdM746gp5ABrYy3YkwFb8S8/tiFYBuMbC98auf1wSd92qALEObkedpxpDjgjY7xSozNYLwGPVW2uWJ03nrrLSVi2X1IAUevIj0CW7duVQLF3iBtHV73emwUg2IZr8JjwXOZVDgMm4KRXTEc2q8PPWe3TErVjaPY4TlncDCvXXrzKK4oOBnDw65VvduT54DbMcsy/97YDc5cXDxHiYVijceYvxv6w4y9UBjxgY6/JTwuceOu+PfEv0UeJ17//Fvlb0RKZJAXkkEqjvQSXJAJEyao4ZQVK1Z8bB2HT3PIJ4dw+/n5WapVq6aGZMYdlqsPyeRQ3rjEN1yTQ4Pr16+vhuxmzpzZ8uabb1qHFXO4qg6HkXJ466lTpywNGza0+Pv7q+HVHDobd0h83KHn5Nq1a5aePXta8uTJo4agcgg5h4b/9NNPTz0u+tDzJxHf0HNCeznUl9/H782VK5elWbNmlrlz58ba7t9//1XHkUOnuQ2Ht0+ZMuWpQ885lH3kyJHKRg7LLVeunGXp0qXqePE9HX0YdHxDym2PF4fn8zgVK1ZMHW8Of69UqZJl9uzZFnvh0OMOHTpYcubMqdqcIUMGdaynTZsW61zdv3/f0qdPH+t2HI5P+9imuPbRprjEHV5MmAagfPnyaqg60x9w+LI+vPppn/3555/VZ/Sh6vp1GveY69dTt27d1DXL72KKAdvrNTHHnFy8eFEN9+ZQaB7zdu3aWS5fvvzYdvYOPSdr165Vf6f8e02XLp2lefPm6u/NFv3Y2KZusPd7IiIi1DHjkH/9+uPfJa9BtjluSgT+LfBvndvxb/fzzz+3rFmzJt6h5yVLlnxi2zp27Kg+x/3FR3znl5w4cUJ9jtOWLVseW8/UC/p55W9So0aNLP/9999j+5Oh588WN/6XHLEkCIIgCILgyEjMjiAIgiAIpkbEjiAIgiAIpkbEjiAIgiAIpkbEjiAIgiAIpkbEjiAIgiAIpkbEjiAIgiAIpkaSCsaUEGA2TSaZSkzKd0EQBEEQjIPZc5h0lOU+4iZ4tEXEDqCEztPq8AiCIAiC4Jiwnl7u3LkTXC9iB7CmZufBYtp1M8CU8UwX37BhQ1X3yRWQNpu/za7WXiJtljablYgUaDOLsdJZ8bQSKyJ2bKoVU+iYSeywijTb40p/ONJmc+Nq7SXSZmmzWYlIwTY/LQTF0ABlVoEdMGCAKiDp5+enCvcNGzbssQrWLLrG6rLcpn79+jhx4kSs/bAoHItO8oClT59eFWdLSgFDQRAEQRDMh6Fih9WBJ02ahPHjx+Po0aPqNav2srKuDl9///33qgrzzp07VTXnRo0aITQ01LoNhc7hw4exZs0aLF26FJs3b1ZVhQVBEARBEAztxtq2bRtatGiBpk2bqtf58+fHzJkzsWvXLqtXZ9y4cejfv7/ajvz+++/Ili0bFi5ciPbt2yuRtHLlSuzevRsVKlRQ21AsNWnSBN98842K0BYEQRAEwXUxVOxUrVoVP/30E44fP44iRYrgwIED2LJlC8aOHavWnzlzBlevXlVdVzqBgYGoVKkStm/frsQO5+y60oUO4fYcgkZPUKtWrR773rCwMDXZBjjp/YecEhqeznXOUiQ+MjISnp6eqjuPc1dA2uz51D5t9os/aXimo6P/fSb0d2pGpM2ugbQ5adj7WUPvCJ999pkSGsWKFYOHh4eK4RkxYoTqliIUOoSeHFv4Wl/HedasWWOt549+xowZrdvEZdSoURgyZMhj7zMqnMFScaFtmTNndrqgsezZs+P06dNwJaTNT/9huHHjhhLvzgy7rF0NabNrIG1OHCEhIY4vdmbPno0///wTM2bMQMmSJbF//3707t1bdT117do11b63X79+6Nu372ND1zj8Le5oLHpyLl26pJ6gGSTtLE/FtDs4OFjFOLlKokRp85PbTIFz5coV9bCQK1cupzxGFGv8YWzQoIHTPXwkFWmztNmsRKRAm/WeGYcWOx9//LHy7rA7ipQqVQrnzp1TnheKHT6xkmvXrimhocPXZcuWVcvc5vr167H2S2HCEVr65+Pi4+OjprjwYMc94DwZDIamAEuTJg2cBb3bjSPYnEWgJRdp89PbTC8ok2jqXVrOSnx/q2ZH2uwaSJsTh72fM/SOQPdT3B9odhnpLnYOSadgWbduXSwVx1icKlWqqNec3717F3v37rVus379erUPxvYkF3atEW9v72TvSxCMRr+O9etaEATBFTDUs9O8eXMVo5M3b17VjfXPP/+o4OTu3bur9Xz6ZLfW8OHDUbhwYSV+mJeHXpaWLVuqbYoXL47GjRvjzTffVMPT+ZTbq1cv5S1KyZFYzujyF4S4yHUsCIIrYqjY4RBxipd3331XdUVRnPzvf/9TSQR1PvnkExWTwLw59OBUr15dDTX39fW1bsO4HwqcevXqKU9RmzZtVG4eQRAEQRAEQ8UOa1kwjw6nJz2JDh06VE0JwZFXDHIWBEEQBEGIi2tEcbog3bp1Q4YMGVQMFOM0ChUqpAQjg7ddmdq1a6uu0ZTaThAEQXB8XCPzmovCbj1mnGYc0/Lly9GzZ08Vuc6h94mFAa30srnKKCdBeIyIUMDdE/CQn01BcDbkzmViOLyeo9ny5cuHd955R2WWXrx4sVrHDNIfffSRyrfCHC0cubZx40brZ3/77TeVmZrblyhRQu3r/PnzqqQHA8a7dOmihuJz39yGiepY0oPvlS5dGnv27LHu69atW3jttdfUdzFpI1MMsCxIXE/K+++/r2K02C1JuwcPHhxrG8ZsvfHGG8iSJYvKh1S3bl2VdVuHiSJr1KiBP/74Q9nJbNsMVL9//75a//rrr2PTpk347rvvlHDjdPbsWbuOJfc3cuRIFTzP7lcG1TP7ty0XL15U7aT9PKbM6s2RgzqsA8dit/S0FS1aVNlpC+358ccf0axZM3WcGHzPDOEnT55Ux4f7ZNbxU6dOxfochSy/i3FsBQsWVMfB1T14Kc75ncC3JYDvSgOn1httjSAIiUTEThKSuIWERxoyJbdUBXOxhIeHq2UGdPNG+tdff+Hff/9Fu3bt1Kg224ryTA3A4qy//PKLKrSqZ6r+9ttvUa1aNTV6jnXNOnfurMRPp06dsG/fPnVD52vdXuYpKl++PJYtW4ZDhw6pYHN+Rq+BpjNt2jR1Q6dAYAFYdrvZZtakjQxkX7FihUo18MILLyjvFXMq6VC8LFq0SBWE5URxM3r0aLWOIoepCjhyj8n1ODGZpL2MGTNGiQq2m0H1FJDHjh1T61iuoVatWioBJcUfRRiFm55GYcGCBfjggw/w4YcfqmPAQHx2NW7YsCHWdwwbNkwdOybYZGbxDh06qG3pjaOA5DHludP5+++/8fbbb+O9997DkSNHlFiiUOUoRyGFOLYC+P1lIOQWcO8S8EcrYNlHQLh9mVsFQTAe8ccmkocRUSgxcJUh331kaCP4eyf+lPEGyVxFq1atUjdFemimTp2q5vrwfHp5OMqN79ODQdj9NXHiRJQpUybW/lhklTdgwpFz9Fi8+OKLSoyQTz/9VIkKJn+kh4YeHe5fhzbQFmbQrlixovV9eoQGDRqklplqYPz48cpuZtdkzTSKI4odPSEkC72yIOzcuXOtVe4pLtgGenUIRRX3wZs/36NXhV6ThBJOPgm2myJHbyNFH8UKvTQMkKd3iwVp6dkhjJPSoa30LOmfZwbvHTt2qPfr1Klj3Y4C6JVXXol1HDlisVGjRuo9CiZuYyuOGFvEJJzsYqRnh+9RaOnHUkgG+/4AlnwAWKKAIo2BwDzA7p+16fQGoNWPQO5HdfkEQXBMROyYGAoKdvdQtFAE0EvAriF2VzEGh8VXbWHXVqZMmayvKQwoQOJi+55et4xdU3HfozChqOB3UUBR3NDzQe8SvytuHbK438Ws2Xp2bHpK6D2xtY88fPgwVrcOu5fYzRTfPpKLrX3scrLN3k1PTLly5axCJy5Hjx61CjIdesfobUrssaWnjMk1eW55XLZu3Wotnkt4vLkNPXPx1XoT7IBeyb/HAOuHaa/LdgKaf6fF6xR9CVjUC7h1EpjSAKjxIVDzE8BTEo8KgqMiYieR+Hl5KA+LUd+dGBi/wm4NxnLQg6NXxaZo4CgtdgVxbottSQx2e8WXhM42Pbe+Pr739C6cr7/+Wt3UmWKAN252VdEboXepxbdffT/6PmgzhYttXJEOY4t04lb+tt1HcnmSfTxWKf0d9hxbHheWXGGsUNzgcdtcVEIi4LFd+Rmw60ftdfW+QL2BPPja60L1gHe3Acs/AQ7OBjZ/DZxcC7w6HQjMbajpgiDEj4idRMKbTVK6koyAT/XsSol7E6QHgk//9EpQEKU29DwweJkxPfqN+vjx4yrw2V4Yn8Mq9hQzDBZOKvRWpUapBHpkGNvE+KH4vDsMNuZxsC1wy9eJOQYJHRcGMMd3noUkEPYAWNwLOLxAe914NFD5nce388sAtPkZKNYEWNoHuPwP8FNt4NU/gbzJL1MjCELKIr+OLgi7rzp27KgCYefPn48zZ86oeBgWYGUQcUrD+BsGGm/btk115zDeh/E8iYEjyRi/wjIhq1evVoHI3N8XX3wRa+TX06BQYgA0P3/z5s0U8/rQs8JuLdpHEXP69GnMmzdPBYHrRW8ZOMz4JgaBs9uJx942likp9O/fXwWZM5ibQeQ8vnzN94VEcmkv8GNNTei4ewFtpsQvdGwp2Qr432YgWykg+AbwW1MtzkcQBIdCxI6LwiBeih2ODmKALW/SDK5lzEtKwxsvPRAMsuUQal0UJNajxiHWNWvWVAG6FGwcVn7u3DlrbIs9UFyw644eFQ5hZ5B2SkCPEUUYR6wxkJnddRwFpncTsr3symNAMuvAsXuR54DHIznwmFLcUEwySLxy5coqcJopAQQ7iY4CNn8DTGkI3D4FpMsFdFkIlGpr3+fT5wV6rAKKvwxER2ieoRWfAVEy/F8QHAU3S3LHM5sABntypE5QUJAK+rSFgZ70fLAIqTPFQNBjoQexukr3hrT56W121utZR0+QSUEZN4YqSdw9D8z/H3B+m/a6REug+Titmyqx0EvI+J2N2mhGFKwNtJ0K+McftG5Ym50AabO0OSXu37a4xh1BEAQhLgfnApOqa0LHOw3QchLQ7rekCR1CsVn7Uy1Q2SsAOL0R+KUecON4SlsuCEIiEbEjCIJrQQ/MmkHAvB5AWBCQ+0Xg7b+Bsh0ejbhKDsWbAz1Wa91bt08Dv9SXrMuCYDAidgRBcB0iw4EF/wO2jtNe1/wY6LYSyFgwZb8n+/PAmxuAvFU0QTW9LbDr55T9DkEQ7EbEjiAIrkFoEPBnGy03Dgt6stuqbv/UK+wZkBnosggo00HLwLz8I2DZhxK4LAgGIGJHEATzc+8yMLUJcGazFp/TYbbWbZXaePoALScC9YdwPAiw+xdNcD28k/rfLQiCFRE7giCYm+tHtbiZa4eANNmAbsu1LMjPCsYBVe8dJ3C5AXDn3LOzQRBcHBE7giCYF2Y2/rWRVq08U2GgxxogR+zCts+M4s2A7iuBdLmBWyeAXxsDN44ZY4sguBgidgRBMCd3LwAzXtVidfJU0kZIZTA42WKO0sAba4AsxYD77Fp7Cbi831ibBMEFELEjCIL5CL0HzHgFeHANyFoS6Dg32cn9Uox0OYHXlwM5ywEht4BpzYGzW422ShBMjYgdIVmw3pNt1XFBMByOdprzOnD9iBaj02EW4JtwZlVDCMgEdFkM5KsOhN0DprcGjq822ipBMC0idkwK60dlyJAB77zzeCHDnj17qlpTr7/+Ooxm48aNypa7d+8abYpgBlj9hkO8T60DvPw1oZM+DxwSCrBOc4EijYHIUOCv14BD84y2ShBMiYgdE5MrVy7MmjULDx8+jFUbacaMGSlS8JN1TYwiKioqxSqWpzRGHheXZ/t4YO9UbZh3m1+0riJHxstPG6VVqh0QHQnM7QHsof2CIKQkInZMTJkyZZAnTx7Mnz/f+h6XKXTKlYt9E1i5ciWqV6+uuqQyZcqEZs2a4dSpU9b1Z8+eVR4YiqdatWqpIpJ//vnnY99548YNVKhQAa1atUJYWJgSJKNGjVKFJ/38/JRNc+fOte6zTp06apleqCd5m/TussWLF6uK5T4+PqpiOb+Dlcwp7NKmTYv69esrb5EOq6I3b95c7T8gIEBVHGfhOZ1NmzahYsWKan85cuTAZ599hsjIR0nf8ufPj3HjYrLtxlC2bFkMHjzY+pp2T5o0CS+//LL6jhEjRqj3lyxZoiqR81hlzpxZHRMdW7v5mUqVKiXKbiEejiwGVg/QlhuNAIo1hVPg4QW0+gmo0IOuKWBpb2BL7GtOEITkkUqpQ03uJo8IMea76ZZPZO0edmdNnToVHTt2VK9//fVX9Z7tjZUEBwejb9++KF26NB48eICBAweqm/P+/ftjVdOmGBgzZowSS7yJr1q1yrruwoULaNCgASpXrowpU6bAw8ND3finT5+OyZMno3Dhwti8eTM6deqELFmyKHE1b948tGnTBseOHVMVaymIEiIkJARffvklfvnlFyXIsmbNil69euHIkSP466+/kD17djVnBd2DBw+q72OXXXh4uPpeigZumyZNGrW/S5cuqW0psH7//Xf8999/ePPNN1W7bMWMPXD70aNHK2Hk6emJZcuWqeP3xRdfqH3TBluxYmt3zpw5sWDBAjRu3Nguu4V4uLAbmP+WJhZefAOo/C6cCv6NNR0D+AYCW8YCawcBoXeBeoOMtkwQTIGIncRCoTMypzHf/fllwDsgUR+hyPn888+Vp4Bs3bpV3WDjih0KDlsoiihIeJN9/vnnre/37t0brVu3fux7KFYodHiD5w2f3g56L0aOHIm1a9eiSpUqaruCBQtiy5Yt+PHHH5WHKGNGbYQMhcvTAp3ZPTRx4kTlHSL07FDIcU7BQC/Se++9p7w1fJ/fzXVsW6lSpazfr8N90fM1fvx4ZW+xYsVw+fJlfPrpp0rs2Yq8p9GhQwclInXat2+vpiFDmDlXIyG7Cb089K7ZY7cQTy6d6W2AyIdAoQZA4y9TpqDns4Y21x+kCR6KnS3fasPmG4422jJBcHpE7JgcCpamTZuqbiCLxaKW2aUSlxMnTqgb/M6dO3Hz5k1rPAxvurZih11UcWFMUI0aNdQN37bL5+TJk8obQxFkCz0WcbvR7MHb21t5nnToBWHsTpEiRWJtR5FFzw95//33VZD26tWrVRcXBYS+j6NHjyoRRqGjU61aNeXZunjxYqLimuIeF3rE6CWKj+TaLdhw9SDwe0ut2CaLbrb7LfVqXT0rmG2ZgmdpH2DPr/B4eBduXs2MtkoQnBon/1UwqCuJHhajvjsJdO/eXXWbkAkTJsS7DeND8uXLh59//tnqJaHIoTCxhV0qcWG8C2/IS5cuxccff6ziUAhFA2GXjv6e7WcSC7u4bIUJ98+usr1796o5beZ77O5hlxh544030KhRI2UDhQPjh9gNRw+QPdC7Q5H4tADkuMflSd1xce22Re+qSq7dLlMG4vcWWndPrgpavSsfk3T1Veimjdaa/xbcD89HxXSngIgGgJeX0ZYJglMiAcqJhTdbdiUZMSXRNc9YEIoW3qR5A43LrVu3VDdU//79Ua9ePRQvXhx37thfqJCC4I8//kD58uVVwDG7gohtIHGhQoViTew+0r01hJ6OxELvED93/fp1637Z3cM543d0+F1vv/22Cs7+8MMPlaAjbOf27dtjiRl28zHQOXfu3FbP2JUrV6zr7927hzNnzjzVNnph1q1bZ7fd+mSP3QIv2hPAtJe1pHw5ygKd5jleLp3k8nwboP1MWDx9kf3eAXjM7w5EyUg/QUgKInZcAHoP2GXD+Ju4ngTCET/sPvnpp59U19P69etVsHJiv4OjsxiXUrduXVy9elWJBsai9OnTB9OmTVOju/bt24cffvhBvSb0JtFbQ68QR3Lp3iB7YDcQY5K6dOmiBAFFCL0lDBSmR0SPMWIQNdfxuzds2KBEDnn33XdVUDW9JQxOXrRoEQYNGqTarsfrsC0Ucn///bfqfuratWu8xzAu3M/MmTPVnMeen2VwdUJ279q1S3lv7LHb1QkIuwbP6a2A4OtAtlJA5wWAn0kTWxZpiKj2sxDl5gX3k2uABf8DohP/YCAIro6IHReB3Tp6105ceGNn0DKFAruuKE6+/vrrRH8HRyHxBs9h0hQJ9FwMGzYMAwYMUDdy3qzpZeINnUPRCbu3GMTLUV7ZsmWzdrfZCwN6KRro+eD+OdJr9+7d1ngbelA4skn/bgoNBibr380RUhQaFGn0ovTo0UN5uHT69eunAqk5FJ/xTi1btsRzzz33VLtq166NOXPmqKHyHKrO48Hvic/uokWLqv3aa7dLE3QBVU+MgtuDq0CW4kCXhY5TBiKVsOSrhl0F3ofF3VNLOrjsQ21UqCAIduNmiRuQ4IKwayIwMBBBQUGPCQIm4ePTNW/OHJLsLDB+he1iexIzqsiZkTY/vc3Oej0rQm7DMqUB3G6dhCVTIbh1WwGkyQqzw+5nivKm+cPguSBmeH31PkD9xKVHcMY2MzWEl4vEKUmbvVL8/m2La9wRBEFwbiJYTqGDEjoPvTIissMClxA6tlhKtAKax4x25LD0v8cabZIgOA2Gih1mp2W8RtyJ7nv9KZTLjCfhKBUOv7127VqsfTD4ld0L/v7+KlcLRwPZZsAVBMHJYRqEhW8D57fD4pMW25/7CEiXAy5J+deBBkO15XVDgN1TjLZIEJwCQ8UOYxQ40kWf1qxZo95v166dmjN2hCn3GfvARHEc5WOb0I5xDRQ6HGm0bds2FfTKfDLMFyMIgklggr3DCwB3L0S1nYb7ftpIOZel2gdAjQ+1ZcbvHNTKrwiC4KBih8N6OdRWnzgih8GfDAhl/xtLDowdO1YFd3JYM4M6KWp27NihPs/8IxxhxHIEDAJ96aWXVEAsc8nEzQ8jCIITsutnYNv32nKLCbDkr2m0RY5B3QFaWQzG7yx4GzgdOyO6IAgOmlSQ4oSihcN+2ZXFkUEMXmKyOh2m8+doFeZGYf0lzplOn6N4dJhHhplnDx8+nGCWXmaq5WQb4ET4fXETxvE1Y7gZCOqoVbbjQ4871213BaTNT28zt+G2vK7tGUJvJG7HV8BjxSesX46oWp8jukRr69+nK1WWT7DN9UfA48ENuB9dBMtfHRHZeTGQ3RxZtuU8uwYRKdBmez/rMGJn4cKFuHv3rrXqNfO0MOFc3HpJFDZcp29jK3T09fq6hOAwaNuaRTr0FDH2J+5wanqdmP/FGb1F9+/fh6shbU4YXsMs78ECo44c25Y++BSqcYi5JRpnM9XCgaCigE0hVb3L25WIr83u3i+jcprjyPLgKKKmtcLfRQYgxMc8gdtynl2DNcloM0sSOZXYYZcVu6H0woipCXOn2CbNo2eH2WobNmwY79BzJp5jgLQzDdXl0ztvgEzsZ1tiwcxIm5/eZl7PLGVRs2ZNx72e712G568fwc0SjuiC9ZDr1T+RizlmYp7i+MPIemuuNDz3iW0OrQPLHy/D9/oh1L8yAZFdlwMBWeDMyHmWNtuL3jPjFGKHFblZGZvZZHXoTeFTKL09tt4djsbSU+pzbpuoTV+vr0sIljCIrzYTD3bcA84gaN5EmMPEmXK36F0auu2ugLT56W3mNtw2vmvdIYh4CMztomVHzloC7q9Og7vP43XGHNb+VCTBNntlAjrPA35pALc7Z+A1uwPQdakp6oTJeXYNktNmez/nEHcEBh5z2DhHVukwIJmNsK0vxPpNHGrOStWEc6bhZ6ZeHapEemdYl0kQBCeC8UeLegJX9gN+GYHXZgI+aY22yjlImx3oPF87bpf/AWZ3ASKdr9tdEFILd0d4MqXYYc0hxsfoMCMiU/ezu4l1gRiw3K1bNyVwGJxM2O1EUdO5c2ccOHBA1RJiqn/m5klKVW3BNaBngzFigoOxZaxWDoFdVq/8DmTIb7RFzkXmwkDHOYCXP3BqHbDkfSkrIQiOInbYfUVvTffu3R9b9+2336qaREwmyBgDdk3ZdnVxNAmHq3NOEcS6SKw3NHRoTNItQQVqs9Alq4FTADI2qXnz5glW5DYTgwcPVikJ4sKcTowPExyI/5YD64Zpyy99BRSoYbRFzknuCkC7aYCbB3BgJrBxlNEWCYJDYHjMDr0zCZXnYgAlc+ZwSghWzWZtDeFxKCJ5U2fMEwt7cpg+A8LoAaP3i5W+XZEnxXMJBnDtCDD/TS1nDHPHvNjDaIucmyINgWZjgSUfAJu+BALzAC90NtoqQXBtz46QerCiNrtsGMRN7xgrZ7MiObsG9cSMFEQtWrRQo80Y6/TKK6/EKsmhe0f++OMPVd6D3Yvt27ePNdR57ty5SkhxlA9LezA3UnBwsLX6d+/evWPZxQrfeooBwv0OHz5ceeVoBwUsq4XfuHHDalvp0qWxZ88e62eYKZsijt1RhQsXVsKY1cEvXrxoXc/0Auze1MuQ8L34urEY98XElbr9b731lko1oENbafM333yDHDlyqG0oFl0pH0aqEXIbmNkeCH8A5K8BNB5ttEXmKStR4yNteWlv4KT5PbmC8CRE7CQSeqFCIkIMmRJToP727duqq+rdd99FQEDAY+spFBgvRTHBbVmOg8Hdp0+fxquvvhpr21OnTilxwC5DTtx29OjR1i6h1157TXVDHj16FBs3blQlPRJjq95lWa1aNfzzzz8qUJ1xWBQ/7Jrct2+fyqzN17b7ZX6FESNG4Pfff8fWrVtV1m3GeRG2gWKP4k4vRxK3XYSijIkoM2TIoMqXsDQJu1Z79eoVazvGjfE4cK6XJdHFk5BEoiK0QNq754D0+bQ4HQ/XGoWSqtTtD5R+FYiOBGZ3Ba4eNNoiQXDdbixn42HkQ1SaUcmQ797ZYSf8GXxoBydPnlTCoGjRogluQzFEr8aZM2dULA+hcKBA4I3/xRdfVO9RFPHGzlwuhEKEn6XQoIhgcjoKHHpkCL08iaVJkyb43//+p5ZZ22zSpEnq+/U6aZ9++qmKy7JNPUDPyvjx41GpknY+GOhO2+nJYhA7PUJ6UsiEmDFjhso9w3bropD7ZFzTl19+aU1SSTHE9xkfxkzeFGQ8Bm++ye4XIUms+gI4+zfgnQZ47S/AP6PRFpkL5l16ebzKW6SO85+vAG+sBQJzGW2ZIDxzxLNjUuzxrNATQ5GjCx3C0W30+nCdbTeTLnQIu3L04f5lypRBvXr1lMChMPn5559x586dRNvLbiodXWDYiib9Pds0AxQyuiAjFCHsZrO1/WlwW7bB1vtFDxMFHlMd6FBE2ZZXsD0GQhLY9zuw60dtudWPQDZJFZEqeHoDr/4BZCkG3L8M/NkOCA0y2ipBeOaIZyeR+Hn6KQ+LUd9tL4xjYWyK7Q07qcRN2sT96snsKADY/cUCrSy38cMPP+CLL77Azp07UaBAAZXELq7wii/WxfY79EzA8b1nVM2rJx0DIZGc3wksjclgXvtzoHgzoy0yN34ZtCHpv9QHrh8G5vYAOsxmhkmjLROEZ4Zc7YmENzl2JRkxJaYEQsaMGVXQ7cSJE63BwrYwM3Xx4sVVKQxOOqwiz3WJScpIu+gNYUAwY25Y02zBggXWyvbs6rLNSH3o0CGkBOw+sw1aprBj3A7bRWgHv+9JcFsGMdseI8b/UKQ9qQtQSCLsUpndGYiOAIo3B2p+bLRFrkH6vJrA8fQFTq4Btn5rtEWC8EwRsWNiOHqIN/uKFSti3rx5OHHihOq2+f7771X8C0dNsauoY8eOKgiYsS4MAq5VqxYqVKhg13fQgzNy5EglOjiyi3mQOIpKFxwUXMuWLVMTh7qzIj3FVEp5W5hDiDYw6SSDpNmtxfbq3W+MR9q/fz9u3rwZq9K9DtvOkVxMakkRxgBk7pNxSXGLzArJJCIU+Ksj8OCaKgWBlpPFu/AsyVkWaPKNtrx+OHB2i9EWCcIzQ35pTAxv9hQhderUUSOTnn/+eVVwjYG1DACmR2bRokUq+JZJGyl+mHxw1qxZdn8Hh6uzgjYDjDm0nRmsx4wZY03aRwFCIaGLKO6f9qQErFDPwOUOHToozxLjblhQVofD7Tkcnd9HD9PMmTPj3QfzDnFEGoVS27ZtVQwSg5GFFIRdmcz7cnmf1q3SfoYpajc5HeU6AWU6AJZoYG534IHEnQmugZslsWOETQirpjKwlV0g8VU9p3eA8ScOWyU6HhhPwnaxPWYsisnRYczfY+slMnub4yOxbTbset4+AVj1uZbZlzWcCtZO0m4Y78UkohTXrlIsMcXbHB4M/FwPuHEUKFAT6LwQcH8UfO8IyHmWNqfE/dsW17gjCIJgbEDy6gHacqORSRY6QgrhHQC8Mg3wCgDObAY2SiJHwfyI2BEEIXUzJM/rAViigOfbAJW0XEqCwWQpCjT/Tlve/DVwcq3RFglCqiJiR3BKWMIhpQKdhVSCPeSLegFBF4CMBYFm47REd4JjULodUIEFmC3A/LeAoEtGWyQIqYaIHUEQUoedPwLHlgEe3kDbqYBvwv3pgkE0GgXkKAOE3NI8cFGRRlskCKmCiB07kThuwQw8s+v40j5gdX9tueEIbdiz4Hh4+QLtfgN80gHntwN/jzHaIkFIFUTsPAW9REB4eLjRpghCstGvY9vSFykOyxHM7aYlDizWDKgo9cMcGnYxNh2rLW8aDZzfYbRFgpDiSLmIp8D6S8zFwkR5HBrnLEOaOSSZNzYONXYWm5OLtNn9qdvyOub1zOs6VfPp3DkLBOYFWoyXOB1nid9hZuV/ZwHz3gTe2QL4BhptlSCkGCJ2ngIT77HoI3OTnDt3Ds7UXfHw4UP4+fklqsyEMyNtfnqbKYjy5s2besdn72/A4QWAuyfQ9lctgaDgHDC7Mr06d88BS/sAbaaIUBVMg4gdO2CNJRbWdKauLCZrYmZjZkZ2pQRV0uanX8up5vW6eghY+Zm2XG8gkOdRRXrBCWAAOQXOr42AQ/OAQg2Asq8ZbZUgpAgiduyENwhnyqDMmAwWyqTNrnLjlzYb2GZm5WWcTmSodpOs8p5xtghJhwK1Tj+tdtbyj4A8FYFMzxltlSAkG9cIbBAEIXVZ/jFw8ziQNgfQSgp8OjXV+wL5qgHhD4B5bwBREUZbJAjJRn6RBEFIHgf+Avb/Cbi5A21+AQIyG22RkBxYJ6v1T1qAMgu3bhhhtEWCkGxE7AiCkHRungCW9tWWa30G5K9utEVCShCYG2j+vba8ZRxwaoPRFglCshCxIwhC0ogIBeZ0AyKCgfw1gJofGW2RkJKUbAm80FUrJ7Hgf8CDG0ZbJAhJRsSOIAhJY/UXwLWDgH9moPXPWveHYC4ajwayFAMeXAMWvs1kTUZbJAhJQsSOIAiJ58giYPcv2nKrH4F0OYy2SEgNvP21umaevlpl9O3jjbZIEJKEiB1BEBLHvcvA4pih5dV6A4XrG22RkJpkKwE0HqUtrxsCXNprtEWCkGhE7AiCkLhyEIvf1+pf5XwBqBtT7FMwN+W7ASVaANGRwNzuQOg9oy0ShEQhYkcQBPvhEHPWUPLwAVpOAjxcI3mjy8OyERydxXpnrHu2tLcmfAXBSRCxIwiCfQRdAlb205brfA5kLWa0RcKzxC890Jb1sjy0chL/TDfaIkGwGxE7giDYWc38fSDsHpCrAlBVykG4JCwfoXddrvhE8/IIghMgYkcQhKfDp3iOxtG7r2SYuevCoPR81YGIEGCJdGcJzoGIHUEQnkzQRWDV59py3S+ALEWMtkgwEtY9e/l7bTj66Q3A/hlGWyQIji92Ll26hE6dOiFTpkzw8/NDqVKlsGfPHut6i8WCgQMHIkeOHGp9/fr1ceLEiVj7uH37Njp27Ih06dIhffr06NGjBx48eGBAawTBpKOv2H2V+0WgSi+jLRIcAVZCrx0Tv0UhfP+a0RYJguOKnTt37qBatWrw8vLCihUrcOTIEYwZMwYZMmSwbvPVV1/h+++/x+TJk7Fz504EBASgUaNGCA0NtW5DoXP48GGsWbMGS5cuxebNm/HWW28Z1CpBMBH//AGcWqd1X7WYKN1XwiMofHOUAULvAis+NtoaQXginjCQL7/8Enny5MHUqVOt7xUoUCCWV2fcuHHo378/WrRood77/fffkS1bNixcuBDt27fH0aNHsXLlSuzevRsVKlRQ2/zwww9o0qQJvvnmG+TMmdOAlgmCWbqvvtCWGZQq3VeCLR6ewMvjgZ9qaxm1jy4Bijc32ipBcDzPzuLFi5VAadeuHbJmzYpy5crh559/tq4/c+YMrl69qrqudAIDA1GpUiVs375dveacXVe60CHc3t3dXXmCBEFIbvdVRaBKT6MtEhyRHKWBah9oy8s+Ah7eNdoiQXA8z87p06cxadIk9O3bF59//rnyzrz//vvw9vZG165dldAh9OTYwtf6Os4plGzx9PRExowZrdvEJSwsTE069+5p2UAjIiLUZAb0dpilPfYgbU453Pb/Cc9T62Dx8EFks++AqGhtMhg5xw5Itb7wPLIIbrdPIXrVF4hqOs78bU4FpM1Jw97PGip2oqOjlUdm5MiR6jU9O4cOHVLxORQ7qcWoUaMwZMiQx95fvXo1/P39YSYYx+RqSJuTh2/4bdQ9qgWfHs7WCqd2ckBA7EEBRiPn2LHImKk9atweAff907H9QW7cTFvC9G1OLaTNiSMkJMTxxQ5HWJUoEfuPonjx4pg3b55azp49u5pfu3ZNbavD12XLlrVuc/369Vj7iIyMVCO09M/HpV+/fsqbZOvZYexQw4YN1YguM0C1ywuoQYMGKgDcFZA2p0CbLRZ4zHoN7tEPEZ2rAop2+Q5FHSgoWc6xo7a5CaJWXIbHvqmoevMvRLbeDHj5m7zNKYu0OWlt1ntmHFrscCTWsWPHYr13/Phx5MuXzxqsTMGybt06q7hhwxiL884776jXVapUwd27d7F3716UL19evbd+/XrlNWJsT3z4+PioKS482Ga7yMzYpqchbU5m8sBTWvJA95aT4O7jC0dEzrED0nAocHI13O6ehdffXwGNRpi/zamAtDlx2Ps5QwOU+/Tpgx07dqhurJMnT2LGjBn46aef0LOnFgzp5uaG3r17Y/jw4SqY+eDBg+jSpYsaYdWyZUurJ6hx48Z48803sWvXLmzduhW9evVSI7VkJJYgJLb2lSQPFJKIbzqg2bfa8o6JwKW9RlskCI4hdl588UUsWLAAM2fOxPPPP49hw4apoebMm6PzySef4L333lN5c7g9kwVyqLmv76Mnzj///BPFihVDvXr11JDz6tWrK9EkCEIiRl+xknVYkFb7SpIHCkmhSCOgVDvAEg0seg+IDDfaIkEwvhuLNGvWTE0JQe/O0KFD1ZQQHHlFr5AgCEnkwEzgxOqY2leSPFBIBo1HA6fWA9cPA1vHAbU+MdoiQTC+XIQgCAZz7zKw4jNtuU4/IEtRoy0SnJmAzEDjL7XlTV8B1/8z2iJBELEjCHD17qslMd1XOV8AqrxntEWCGSjVFijcCIiOABa/B0RHGW2R4OIkuhuLI53mz5+Ps2fPqi4mjphq27YtatasmToWCoKQyt1XqwAPb6DlJK0EgCAkFzc3oNlYYEJl4OIuYNfPQOW3jbZKcGES5dl5++23VSkGBhTfunULN27cUMHBderUUUHEgiA4afcVK1hnLWa0RYKZCMwNNIhJ3rpuCHDnnNEWCS6M3WKHo6ZYsPPXX3/FzZs3VU0qDhun4GE9K45+4vBwQRCcpfvqg5jRV+WBqu8bbZFgRsp3A/JVAyJCtOuN150gOLLYodBh1uHXX39ddV9Zd+Duju7du6t8OFOmTEktOwVBSJXRV95Ai4nSfSWkDu7uQPPvtVF+pzcA/8422iLBRbFb7Ozbtw+tWrVKcH3r1q1VFmNBEBwc6b4SniWZCwG1PtaWV30OPLxjtEWCC2K32GHXVe7cuRNcz3WM4xEEwYGR7ivBCKp+AGQuCoTcBNYONtoawQWxW+yEh4c/sQaFp6en2kYQBAdm/wzpvhKePZ7ej0pJ7P0NOL/TaIsEFyNRv3QDBgyAv79/ssqsC4JgYPfVyn7asnRfCc+a/NWAsp2A/dOBpX2A/20CPFyr4KXgBGKHeXTiViiPbxtBEBy0+2rZh4+SB0r3lWAEDYYCx5ZrpSRYLLTaB0ZbJLgIdoudjRs3pq4lgiCkHocXaDcZdy+gxQTpvhKMISAT0HAYsKgnsHE0ULIVkD6v0VYJLkCyy0VERkaqSuSCIDgoIbeBFTHFGGv0BbKVMNoiwZUp2/FR7p3ln0juHcGxxM6SJUvw22+/xXpvxIgRSJMmDdKnT4+GDRvizh0ZUigIDseqL4DgG9pomBofGm2N4OowT1vTsZqX8fgK4L+lRlskuAB2i52xY8ciODjY+nrbtm0YOHCgClqePXs2Lly4gGHDhqWWnYIgJIWTa4EDM3iHAVqMBzx9jLZIELTg+GoxcWP07oTdN9oiweTYLXYOHz6MqlWrWl/PnTsXDRo0wBdffKESCo4ZM0Z5fwRBcBDCHgBL+mjLFd8C8lQ02iJBeETNj4EM+YH7l4EtMcPSBcFosXP//n1kypTJ+nrLli2oV6+e9XXJkiVx+fLllLdQEISksX44EHQeCMwD1BtotDWCEBsvP6DhCG1523jg7nmjLRJMjN1iJ1euXDh69KhaZkDygQMHYnl6mD05oRw8giA8Yy7sBnZO1pabjwN80hhtkSA8TrGmQP4aQFQYsGaQ0dYIJsZusdOuXTtV7POPP/7Am2++iezZs6Ny5crW9Xv27EHRokVTy05BEOwlMhxY/B6T6wCl2wOF6httkSAkHKzcaKQWU3Z4vmRWFowXOwxGfvHFF/H+++9j//79mD59Ojw8PKzrZ86ciebNm6eWnYIg2MvfY4AbRwH/zEDjUUZbIwhPJkdpoFwnbXlVPyA62miLBBNid2YxPz8//P777wmu37BhQ0rZJAhCUrl2GPj7G235pS8B/4xGWyQIT6fuAC3x5aW9wME5QInWRlskmIxkJxUUBMFBiIrUMtNGRwJFmwDPtzHaIkGwj7TZtISXZN0QLeGgIBghdjJkyICMGTM+NhUoUACNGjXCmjVrUtIuQRASy44JwOV/AJ9ALWkb4yEEwVmo3BMIzAvcuwR3XsuCYEQ31rhx4+J9/+7du9i7dy+aNWumcu9I3I4gGMDtU8AGBnoCaDQcSJfDaIsEIXF4+QINBgNzu8N9+w/wLRJzPQvCsxQ7Xbt2feL6smXLYtSoUSJ2BOFZY4mGx7LeQGQoULA2UK6z0RYJQtIo2RrY+SPcLuxE8StzAMQELguCo8Ts0LPz33//pdTuBEGwk/w3N8D9/HbAyx9o/p10XwnOC6/dmBGEeW9vhRu7ZQXBkcROWFgYvL29U2p3giDYQ9BFlLw8S1uuN0hLvy8Izkyu8oh+vp1adF87QKqiC44ldqZMmaK6sgRBeEZYLPBY/iE8o0MRnbuiVv9KEExAVJ0BiHTzhvuFHcCRRUabI7hSzE7fvjHDAuMQFBSEffv24fjx49i8eXNK2iYIwpP4dxbcT69DlJsnopt+B3d3ySQhmIR0OXEyWxMUu7oQWDMQKNJYC2AWhNQWO//8E3/fabp06VT18/nz56th6IIgPAMe3ABWfqYWj2VvicKZCxttkSCkKCezNkXRBzvgdvecVuetem+jTRJcQexIhmRBcCAodB7egSXr8+oJWKSOYDaiPHwQVac/PJf0AjZ/A5TtCKTJYrRZgpMifm9BcDaOrwIOzQXc3BHV9FtY3Ox+ZhEEp8JS6hUgR1kg/D6wYYTR5ghOjIgdQXAmwu4DS/toy1V6wpKznNEWCULq4eb+qJjtvmnAtSNGWyQ4KYaKncGDB8PNzS3WVKxYMev60NBQ9OzZE5kyZUKaNGnQpk0bXLt2LdY+zp8/j6ZNm8Lf3x9Zs2bFxx9/jMjISANaIwjPgLVDVDp9NcS89udGWyMIqU++qkDxl1XyTKz+QoaiC87p2SlZsiSuXLlinbZs2WJd16dPHyxZsgRz5szBpk2bcPnyZbRu/agablRUlBI64eHh2LZtG6ZNm4bffvsNAwcONKg1gpCKnN8B7P5FW2byQG9/oy0ShGdDgyGAhzdwaj1wQuowCk4odjw9PZE9e3brlDlzZuuQdubuGTt2LOrWrYvy5ctj6tSpStTs2LFDbbN69WocOXIE06dPVzl+XnrpJQwbNgwTJkxQAkgQTENkGLD4fUYxAOU6aWUhBMFVyFgQqPQ/bZnenagIoy0SzC52Ll68iAcPHjz2fkRERJLy7Jw4cQI5c+ZEwYIF0bFjR9UtRVhclPusX7++dVt2ceXNmxfbt29XrzkvVaoUsmXLZt2GFdjv3buHw4cPJ9oWQXBY/h4D3DwGBGQFGg432hpBePbU/BjwzwTcPA7smWq0NYKTYfcwDnYxtWjRQokQxtZ06NABEydOVLE05Pbt26hTp47qWrKXSpUqqW6nokWLqv0PGTIENWrUwKFDh3D16lVVfiJ9+vSxPkNhw3WEc1uho6/X1z2ptAUnHYojQnHFyQzo7TBLe1y6zdePwvPvsWDFq8hGo2HxTMNGmrvNCeBq7SXS5hg8/OFe81N4rPwElk2jEVmiDeCbDmZBznPSsPezdoudzz77TGVo3blzJ+7evateU9ywKylDhgxqG0siA8fY7aRTunRpJX7y5cuH2bNnw8/PD6kFq7NTWMWFbWGgs5lYs8b1+rfN1GY3SxRqHB+GDNERuBL4Anad9gDOLDd1m+3B1dpLpM38e8iCOj45kDbkCs7+8R6O5HoVZkPOc+IICQlJWbGzdu1aLFiwABUqVFCvt27dinbt2ql4mnXr1qn36PFJDvTiFClSBCdPnlRZmRl3Q2Fl693haCzG9hDOd+3aFWsf+mgtfZv46NevX6zyF/Ts5MmTBw0bNlQZoc0A1S4vIB5HLy8vuAJmbLP7jvHwCDkNi086ZO4yDU3S5TB9m5+Eq7WXSJtjt9mtiDcwuyMK3VqL/O2GAenzwgzIefZK0j70npkUEzsMGNY9OMTHx0eViKDgoYeHQcLJhbFAp06dQufOnVVAMhtPIcUh5+TYsWMqpqdKlSrqNecjRozA9evX1bBzwgNHwVKiRIkEv4e2c4oLv89sF5kZ2+Qybb55Etg0Wi26NR4Fr0x5zd9mO3G19hJpcwzFmwIFasLtzGZ4bRoJtJ0CMyHnOXHY+zm7A5QZQPzvv/8+NpKKw8K5rlmzZok0Efjoo4/UkPKzZ8+qUVatWrWCh4cHXnvtNQQGBqJHjx7KA8NSFYwV6tatmxI4lStXVp+nJ4aihuLowIEDWLVqFfr3769y88QnZgTBaYiOBhb1BCJDgefqaqnyBUFgF0JMkL6blkn84l6jLRKcAPfExNf89NNPj72vCx4O/U7KyC4KGwYov/LKKyp5IIeVZ8mi1T/59ttvlYiiZ6dmzZqqa4reJB0Ko6VLl6o5RVCnTp3QpUsXDB06NNG2CIJDsftn4MIOwDuNllMnmV3EgmAqcpQByrymLUuiQSElu7HYXZRQIBAFz7x583Dp0iUkhr/++uuJ6319fVXOHE4JwYDm5csfD9gUBKflzllg7eBHydRMEpMgCClK3f7A4fnA+e3Af0uB4s2Ntkgwg2eHguZJwbtcT+EhCEIy4BPq4veAiBAgX3WgfHejLRIExyQwF1Cll7a8ZiAQKYlkhRRKKshcOCzFwBFYxYsXV6UemjdvrjIdJya/jiAICbD3N+DMZsDTD3j5e8Dd8CTnguC4VO8NBGQBbp8G9vxqtDWCA2P3L+mePXuUwGGXEYeLMfMxR0wFBASoQGPG1Ny/fz91rRUEMxN0EVg9QFuuNwDI9JzRFgmCY+OTFqgTUxCXIxcf3jHaIsHZxU7v3r1VYU6Knr///ltlPj5+/LiKuzl9+rSK5+FIKEEQkth9tbQvEH4fyP0iUOltoy0SBOegXBcgSzFN6Gz51mhrBGcXO/v27VNDvHVYLoLvMYkf8+989dVXmDt3bmrZKQjm5vAC4MQqwN0LeHk84O5htEWC4Bx4eAL1YwL6d/0MPLhhtEWCM4sdJu1jzI4ORU5kZKQ1aLlw4cKqPpYgCImET6QrPtWWa3wIZC1mtEWC4FwUaQzkLKcF9m/7zmhrBGcWOy1btsTbb7+NlStXqiR/rFBeq1Ytaw0rZjfOlStXatoqCOaEw8yDrwOZCgM1HpUxEQTBTpiHqnY/bXnXL8CD60ZbJDir2Bk+fLjKVszRV/Xq1VNVw3/99VH0O+tiscCmIAiJ4Nw2bQQWYfJAT8n8LQhJonBDIFd5IPIhsFW8O0ISkwqmSZMGs2bNQmhoqOq+4mtbWLpBEIREEBkGLPlAW36hC5C/mtEWCYLze3f+bAvsngJUfR9Im81oqwQHIdFJPJjVOK7QEQQhCWwZB9w8DgRkBRpIiRNBSDaF6gO5KsR4d8YZbY3grGKHxTZZe4qFPxmrwxw7pUqVwoABA+wusy4IAoAbx4G/v9GWXxoN+GUw2iJBMId3p05M7A6TDN6/arRFgrOJHVYUZ7FN5tOpVq0a3N3d0b17dzRt2lTl2nnhhRdw9apcWIJgV0Xzpb2BqHAtzqBka6MtEgTz8Fw9IHdFIDJU8u4IiRc7n332GcaOHaty6fzxxx9YuHAh1q5di9GjR+PIkSPInz8/+vWLUdSCICTM/unAua2Alz/Q5BupaC4IKe7dicmqvGcqcO+y0RYJziR2/vvvPzRu3Nj6un79+jh16pTKvePl5YVBgwZh2bJlqWWnIJgDDoldHZNpnD/IGaR4riCkOAVrA3mrAFFh4t0REid2mEOHuXR0KHSio6ORKVMm9Tp37tx48OCBvbsTBNdk1RdAaBCQvTRQ6R2jrREE8+fdYWqHoEtGWyQ4i9hhYPIbb7yByZMnY+rUqWjVqhVefvlleHt7q/X79+9HgQIFUtNWQXBuTq0HDs4G3Ny1nDpMcy8IQupQoCaQr5oWG6cPBhBcFrt/bT///HMEBwdj2LBhKqFgo0aN8N1338Xy/EyaNCm17BQE5ybioVbok1R8C8j1gtEWCYILxO58AfzWBNg7Daj8LpC5sNFWCY4udjw9PfHll1+qKT4qVqyYknYJgrnY/DVw5wyQNidQNyZmRxCE1IWJOou8BBxfoZVlaf+n0RYJzpJUUBCERHL96KP09U2+BnzSGm2RILgOrIjOruP/lgLndxhtjeDsYufo0aMq2aAgCHFy6izpDURHAkWbAsWbGW2RILgWWYtp5VjI6gGAxWK0RYIzi53w8HCcO3cupXYnCObgn9+BCzsArwCgyVdGWyMIrglHZjGv1cVdwNHFRlsjOHLMTt++McGVCXDjxo2UsEcQzJVTZ81AbZlxOoG5jbZIEFyTtNmBqu8Bm77UYncYx+OpjSQWXAO7xQ5HXpUtWxbp0qWLd73k2BGEOKzsp+XUyVFGG4ElCIJxUOwwo/Lt01runUryN+lK2C12ChUqhD59+qBTp07xrmeenfLly6ekbYLgvJxYAxyaqwVGNhsnOXUEwWg4MKD2Z8CyvsCm0UCZ9oBv/A/vggvH7FSoUAF79+5NcL2bmxssEvglCEDYA2BpH22ZWZIlp44gOAYvdAUyFQZCbgFbxxltjeCIYmfMmDHo3bt3guvLlCmjykcIgsuzYQQQdAEIzPuoIKEgCMZDD2uDIdry9glSRsKFsFvsZM+eHfnySdFCQXgil/YCOydry82+BXzSGG2RIAi2FG2iFQmNDAU2jDTaGuEZIUkFBSGliIoAFr8PWKKBUq8AhesbbZEgCPGVkWg4XFs+MAO4dsRoi4RngIgdQUgptv0AXDsE+GUEGo8y2hpBEBIidwWg+Mvag8m6mG4twdSI2BGElODWKS2HB2k0EgjIbLRFgiA8iXqDADcP4PhK4OxWo60RHEHs3Lt3L7XtEATnhaMQl3ygxQAUrKMNaRUEwbHJXAgo31VbZvJPGU1sauwSOxkyZMD169fVct26dXH37t3UtksQnId/pgNn/wY8/bSgZMYECILg+NT6TCsjcWmPlJEwOXaJnTRp0uDWrVtqeePGjYiIiEhtuwTBObh/FVjdX1uu0w/IWMBoiwRBsJe02YAqvbTldUO1QQaC64qd+vXro06dOmoirVq1Uh6e+KakMnr0aJWY0DaXT2hoKHr27IlMmTIpwdWmTRtcu3Yt1ufOnz+Ppk2bwt/fH1mzZsXHH3+MyMjIJNshCHZDt/eyD4HQu1pJiMo9jbZIEISklJHwzwzcOgns+91oa4RUwq4c9tOnT8e0adNw6tQpbNq0CSVLllTiIqXYvXs3fvzxR5QuXTrW+yxPsWzZMsyZMweBgYHo1asXWrduja1btWCyqKgoJXSYA2jbtm24cuUKunTpAi8vL4wcKfkThFTm8ALgv6WAuyfQYqKUhBAEZ4QlI2p9Aqz4BNg4Gij9quTHMiF2/Tr7+fnh7bffVst79uzBl19+ifTp06eIASwg2rFjR/z8888YPjwm9wGAoKAgTJkyBTNmzLB6jKZOnYrixYtjx44dqFy5MlavXo0jR45g7dq1yJYtmypUOmzYMHz66acYPHgwvL2lqq2QSgTfBJZ/rC3X+AjI/rzRFgmCkFTKdwN2TATunNXmFD+CqUj0o+iGDRusy3otLHY/JRV2U9E7w64yW7HDOlyMDeL7OsWKFUPevHmxfft2JXY4L1WqlBI6Oo0aNcI777yDw4cPo1y5cvF+Z1hYmJrijjbj95klHklvh1na42ht9lj2EdxDbsKSpTgiq7zPL4URuNp5drX2Emnzs8ANbrU+h+fCt2DZOg6RZToBAVnwLJHznDTs/WyS/O6///47vv76a5w4cUK9LlKkiIqV6dy5c6L289dff2Hfvn2qGysuV69eVZ6ZuB4kChuu07exFTr6en1dQowaNQpDhjyeSIqeopTsnnME1qxZA1cjtduc/e5eVDqzABa4YXPGV3F31VoYjaudZ1drL5E2pzIWb9Tyy4/0D8/iwvT3cDBPFxiBnOfEERISYtd2iRY7Y8eOxYABA1T8TLVq1dR7W7ZsUd1cN2/eVHE29nDhwgV88MEHqpG+vr54lvTr1w99+/aN5dnJkycPGjZsiHTp0sEMUO3y2DZo0EDFMLkCz6TND+/C88eP1GJ0lfdQtW7MSA6DcLXz7GrtJdLmZ9dmtxLpgBmtUeD2JuRp/zUQmOeZfbecZ68k7cPePICJFjs//PADJk2apAKBdV5++WUVtMw4GXvFDrupmLvnhRdesL7HgOPNmzdj/PjxWLVqFcLDw1VOH1vvDkdjMSCZcL5r165Y+9VHa+nbxIePj4+a4sKDbbaLzIxtMrTNywYBwdeBTIXhUfdzeDjIsXW18+xq7SXS5mdAkXpAgZpwO7MZXlvHAC0m4Fkj5zlx2Pu5RJeL4IinqlWrPvY+3+M6e6lXrx4OHjyI/fv3W6cKFSqoYGV9mY1Yt26d9TPHjh1TQ82rVKmiXnPOfegJDwlVIr0zJUqUSGzTBOHJnFgL7P9T9e+jxXjAy89oiwRBSGnqDtDm+2cCN08abY2QQiRa7BQqVAizZ89+7P1Zs2ahcOHCdu8nbdq0eP7552NNAQEBKqcOlznUvEePHqq7iUHR9AR169ZNCRwGJxN2O1HUMFbowIEDyhvUv39/FfQcn+dGEJJMaJBWEoJUehvIq12DgiCYjDwVgcKNAEsUsFEK+pqFRHdjMbD31VdfVd1NeswO897QAxOfCEoO3377Ldzd3VUyQY6e4kiriRMnWtd7eHhg6dKlavQVRRDFUteuXTF06NAUtUMQ1DDzexeBDPmBejFPfoIgmJO6XwAnVgGH5gE1+gLZShptkfCsxQ6Fx86dO5UQWbhwoXqPuW8YO5PQUG97YSkKWxi4PGHCBDUlRL58+bB8+fJkfa8gPJFD84F/ZwFu7kCrnwDvAKMtEgQhNWFG9BItgCOLgA0jgfbsvhacmSQNPS9fvrzKqiwIpufeZWBpTNB9jQ+BvJWMtkgQhGdB7c+BI4u1LOmX9gG5Hg2mEVwgZkcQXIboaGDhO1rtq5zlgFqfGm2RIAjPiqzFtNIRZMMIo60RkomIHUFIiF0/Aqc3Ap5+QOufAQ/XGg4qCC5P7U+12ncn1wLnthttjZAMROwIQnxcPwqsGaQtNxwGZLZ/pKEgCCYhY0GgXCdtef0w1kgy2iIhiYjYEYS4RIYD898EosKAQg2AF98w2iJBEIyi5seAhzdwbitw+lFtSMHFxA5TNXNU1tGjR1PGIkEwGvbPXz0I+GXUkgcmo9CtIAhOTmBuoEIPbXmdeHdcRuy88sorqpwDefjwocp0zPdKly6NefPmpYaNgvDsOLsV2Pqdtvzy90DahMuOCILgIjDXjlcAcHkfcERLuSKYXOwwmWCNGjXU8oIFC2CxWFT9qu+//x7Dhw9PDRsF4dllSV7wNssfA2U7AcWbG22RIAiOQJqsQNX3tOW1Q7SubsHcYicoKAgZM2ZUyytXrlRJBv39/dG0aVOcOHEiNWwUhGfDik+BoPNaluSXRhttjSAIjgTFTkBW4M4ZYO9Uo60RUlvs5MmTB9u3b0dwcLASO6xPRe7cuaMyHguCU3J4AXBg5qMsyT5pjbZIEARHwicNUKeftrzpS80TLJhX7PTu3VtVJs+dOzdy5syJ2rVrW7u3SpUqlRo2CkLqZ0le0ltbrt5XsiQLghA/5boAmQoDIbcexfYJ5hQ77777rvLs/Prrr9iyZYsq1EkKFiwoMTuCk2ZJflfLkpyjLFD7M6MtEgTBUfHwBBoM0Za3TwCCLhltkZCatbE4AouTLYzZEQSnY9dPWu4MyZIsCII9FG0C5K0CnN8ObBwJtEi4ULXgZGKnb9++du9w7NixybFHEJ4d1/8D1tpkSc5SxGiLBEFwdJh3q8EwYEp94J8/gcrvAtlKGm2VkBJi559//on1et++fYiMjETRokXV6+PHj8PDw0NVQxcEp8qSHBkKFKovWZIFQbCfPC8CJVoARxZpZWU6zTXaIiElxM6GDRtieW7Spk2LadOmIUOGDNaRWN26dbPm3xEEh2fTaODqvzFZkidIlmRBEBJHvUHAf8uAk2u0gsEFtcE6gkkClMeMGYNRo0ZZhQ7hMoOTuU4QHJ4Lu4Et32rLzcdJlmRBEBJPpucelZFYM1Ab7CCYR+ywFtaNGzcee5/v3b9/P6XsEoTUITwYWPA/wBINlH5Vc0ULgiAkhVqfAN5pgSsHgCMLjLZGSEmx06pVK9VlNX/+fFy8eFFNrInVo0cPtG7dOrG7E4RnC/vXb58C0uYEXvrKaGsEQXBmAjID1d7XltcPB6IijLZISCmxM3nyZLz00kvo0KED8uXLpyYuN27cGBMnTkzs7gTh2XFqPbD7Z2255QTAL73RFgmC4OxwNFZAFuD2aWDf70ZbI6SU2GEdLIqaW7duqVFanG7fvq3eCwgISOzuBOHZ8PAOsLCntlzxLeC5ukZbJAiCWcpI1PzkURkJdpULzi92dChsSpcurSYROYJTFPm8fxnIVAioH5MBVRAEISUo/zqQPh/w4Bqwc7LR1ggpIXZYAHTAgAGoWrUqChUqpMpE2E6C4HAcXgj8OyumyOePgLe/0RYJgmAmPL2Buv215S3fASG3jbZISG65iDfeeAObNm1C586dkSNHDrhJfhLBkbl/DVja51GRz9yxy5wIgiCkCM+31YqDXjukpbZgVnbBecXOihUrsGzZMlSrVi11LBKElMJiARb3Ah7eBrKXAmp9arRFgiCYFRbFZqLBGe20mnuV3gYCcxltlZDUbiwmEMyYMWNiPyYIz569U4ETqwEPH63IJ13NgiAIqUXhBkDeqloZGmZpF5xX7AwbNgwDBw5ESEhI6lgkCCnBzZPAqi+05fqDgazFjbZIEASzw7AO/t6Qf6YDN44bbZGQ1G4sloQ4deoUsmXLhvz588PLy+uxIqGCYCjRkcCCt4CIEKBATc2dLAiC8CzIWwko2gQ4thxYPwx49Q+jLRKSInZatmyZOpYIQgrhvvVb4NJewDcQaDlJ60sXBEF4VtQbCBxbARxdDFz+B8hZzmiLXJ5Ei51BgwaljiWCkAKkDz4F9/3faC+ajgUCcxttkiAIrga7zVl779+/gA2jgI6zjbbI5ZFHXsE8hAej/LnJcLNEAc+3AUq1NdoiQRBcuUiomwdwYhVwcY/R1rg8iRY7UVFR+Oabb1CxYkVkz55djcyynQTBKNzXDUaasGuwpM0BNB1jtDmCILgymZ4DyrymLW8YabQ1Lk+ixc6QIUMwduxYvPrqqwgKCkLfvn1VtXN3d3cMHhwThS4Iz5rjq+Gxb6pajGo+HvDLYLRFgiC4OjU/Atw9gVPrgPM7jLbGpUm02Pnzzz/x888/48MPP4Snpydee+01/PLLL2o4+o4diTuZkyZNUrW10qVLp6YqVaqopIU6oaGh6NmzJzJlyoQ0adKgTZs2uHbtWqx9nD9/Hk2bNlUFSrNmzYqPP/4YkZGRiW2W4Mw8uAEselctnsrSEJYCtYy2SBAEAchYACjbUVsW745ziZ2rV6+iVKlSapkChN4d0qxZM5VZOTHkzp0bo0ePxt69e7Fnzx7UrVsXLVq0wOHDh9X6Pn36YMmSJZgzZ44qUXH58mXlRbLtUqPQCQ8Px7Zt2zBt2jT89ttvSngJLpQleVFPIPgGLFmK40jOV4y2SBAEIY53xws4swk4u9Voa1yWRIsdCpQrV66o5eeeew6rV69Wy7t374aPj0+i9tW8eXM0adIEhQsXRpEiRTBixAgloOghooiaMmWK6jKjCCpfvjymTp2qRI3uQeJ3HzlyBNOnT0fZsmXx0ksvqaSHEyZMUAJIcAF2/6IFAHr4ILLlj4h2lyzJgiA4EOnzAi900ZY3jjLaGpcl0UPPW7VqhXXr1qFSpUp477330KlTJyVK2J1ET0xSoZeGHhxWVWd3Fr09ERERqF+/vnWbYsWKIW/evNi+fTsqV66s5vQyMcGhTqNGjfDOO+8o71C5cvHnNggLC1OTzr1799Sc38fJDOjtMEt74uXGf/Bc3R8sRRtVbxAiMhQGcNbcbXbF8+zC7SXSZhNQ5QN4/vMH3M7+jcgT62HJX8P8bbaDlGizvZ9NtNhht5MOg5R18UHvDD01ieXgwYNK3DA+h16dBQsWoESJEti/fz+8vb2RPn36WNtT2LArjXBuK3T09fq6hBg1apQKtI4LPUWM/TETa9asgRlxj45AzWODERgZimtpS2PH9VxsrKnb/CRcrc2u1l4ibXZuSmWoiYI31yJo4afYUvgLrbSEydtsL8lps72lqxItduJCocIpqRQtWlQJG3ZbzZ07F127dlXxOalJv3791CgyW89Onjx50LBhQxUobQaodnkBNWjQ4LGSHmbAfe0AeIRegMU/MzJ2n4kmabKZvs3x4WptdrX2EmmzSdp8vxwsEyogU/BxNC0eAEvB2uZv81NIiTbrPTMpLnYYBJw5c2YVGEw++eQT/PTTT8obM3PmTOTLly9R+6P3plChQmqZcTmM/fnuu++U14hxN3fv3o3l3eFoLOb3IZzv2rUr1v700Vr6NvHB2KL44ot4sM12kZmxTTi1Htg5SS26tZgArwy5zd/mp+BqbXa19hJps5OTMS/wYg9gx0R4/v0lUKR+vN4dU7XZTpLTZns/l+gA5ZEjR8LPz08ts/tq/Pjx+Oqrr5QASk7Mjk50dLSKp6HwYSMYH6Rz7NgxFRuke5I4ZzfY9evXrdtQJdI7Q/ElmJDgW8CCd7TlF98AijY22iJBEAT7qNYb8PQDLu4Gjq8y2hqXItGenQsXLlg9MQsXLkTbtm3x1ltvoVq1aqhdO7Zbzp7uJI6gYtzP/fv3MWPGDGzcuBGrVq1CYGAgevToobqbmJmZAoYB0RQ4DE4m7HaiqOncubMSXIzT6d+/v8rNk9iRYYKzDDN/F3hwFchcFGg43GiLBEEQ7CdtNqDS/4Ct44B1Q4DCDQB3D6OtcgkS7dlhEPGtW7esAb3sayO+vr54+PBhovZFj0yXLl1U3E69evVUFxaFjr7Pb7/9VuXvYTLBmjVrqq6p+fPnWz/v4eGBpUuXqjlFEEeGcX9Dhw5NbLMEZ2DHROD4SjXMHG2nAF6ah1EQBMFpqN4b8A0Erh8B/pUCoQ7r2aEQeeONN9Sw7uPHj6s8OYRDvfPnz5+ofXHI+pOggGLOHE4JwRih5cuXJ+p7BSfk0l5gzSBtufFIILuW2FIQBMGpYCmb6n2AtYO1rMrPtwY8pSfC4Tw7FB70oty4cQPz5s1TpRwI8+KwdIQgpDihQcCcbkB0BFCiBVChh9EWCYIgJJ2K/wNYsDjoPLDnV6OtcQkS7dnhyCgGJcclvrw1gpAicTqL3wfungPS5wOaf59gfgpBEASnwNsfqPUpsLQ3sPlrrX6Wh3TLO5TY2bx58xPXM7ZGEFKMvVOBIwu1ysFtpwJ+sZNMCoIgOCXlOgPbxwO3TgLbJwDVPzLaIlOTaLET34grN5snbZZ9EIQU4eohYMVn2nL9IUDu8kZbJAiCkDJ4eAJ1BwBzumqip1xXoy0yNYmO2blz506siSOqVq5ciRdffNFaFFQQkk3YA2DO60BUGFC4EVClp9EWCYIgpCyMQcxZDgh/APctY422xtQk2rPD/DfxjdBiJmTmxGGgsiAkmxWfArdOAGlzAi0nSZyOIAjmg79r9QcDv7eA+77f4F+sqNEWmZZEe3YSggU4meFYEJLN4YXA/umAmzvQ5hcgQBvxJwiCYDpYI6tgbbhFR6DYlUd55ASDPTv//vtvrNcWiwVXrlxR1dDLli2bkrYJrkjQJWDJB9py9b5A/mpGWyQIgpC60LvzU23kvrMdkdcOA7nlXmq42KGgYUAyRY4tLOHw66+SL0BIBtHRwMK3gdC7QM4XgNoxwcmCIAhmJmc5RBdvAfeji+CxeTTQ4S+jLTIdiRY7Z86cifXa3d0dWbJkUdmOBSFZcETCmc2Alz/Q+mfAw7Uq/wqC4LpE1fwUbkcXw/34CuDSPiDXC0ab5Npih+UZBCHFuXIAWBdT06zxaCCzVmxWEATBJchcBBczVEGeO9u0MhKd5hptkalIUoDypk2b0Lx5c1X9nNPLL7+Mv//+O+WtE1yD8BBg3ptaOYhizYAXuhhtkSAIwjPnWI5WsLh5ACfXAOd3Gm2Oa4ud6dOno379+vD398f777+vJj8/P1W1fMaMGaljpWBu1gwAbh4D0mSXchCCILgswT7ZYCndXnuxYbjR5rh2N9aIESPw1VdfoU+fPtb3KHjGjh2LYcOGoUOHDilto2Bmjq8Cdv+iLbecKMPMBUFwaaJqfAT3g7O1+MUzfwMFahhtkmt6dk6fPq26sOLCrqy4wcuC8ESCLgIL3taWK78LFKpntEWCIAjGEpgHKB9TOmLDCK0YsvDsxU6ePHmwbt26x95fu3atWicIdhEZrpWDeHgbyFEGqDfIaIsEQRAcgxofAh4+wPntwKn1Rlvjmt1YH374oeq22r9/P6pWrare27p1K3777Td89913qWGjYEbWDgYu7gZ8AoF20wAvSV0gCIKgSJcTeLEHsGMisH448FxdiWV81mLnnXfeQfbs2TFmzBjMnj1bvVe8eHHMmjULLVq0SK49gitwZDGwY4K23GoSkLGA0RYJgiA4FtX7AHt/Ay7vA46vBIq+ZLRFriV2SKtWrdQkCInm1ilgUUwF86rvAcWaGm2RIAiC45EmK1DxLWDrOC12p3AjZvE12irXEjskPDwc169fRzRT/NuQN2/elLBLMCMRD4E5XYGwe0DeKhKnIwiC8CSqfQDsngJcPQj8twQoIb0nSSXRMvHEiROoUaOGyq3DbMoFChRQU/78+dVcEBJk5WfaH61/JqDtr1IOQhAE4Un4ZwQqv6Mtb/paRmY9S8/O66+/Dk9PTyxduhQ5cuRQRUEF4akcmKX1P8MNaPOLFoAnCIIgPBmKHQYqXzsIHFsBFGtitEWuIXY4Cmvv3r0oVqxY6lgkmI+bJ4GlMUkoa32qjSwQBEEQ7PPuVHwT2PItsOlLLVBZnAyp341VokQJ3Lx5M/HfJLhuPp153YGIYCB/DaDWJ0ZbJAiC4FxU6QV4+QNX9gMn1xptjXnFzr1796zTl19+iU8++QQbN27ErVu3Yq3jJAixWDdEq2julwFo/RPg7mG0RYIgCM5FQGagQndteeNoid1JrW6s9OnTx4rNsVgsqvCnLXyP20RFRSXFDsGMnFgLbB+vLbeYKHE6giAISaXq+1odwUt7gNMbJBwgNcTOhg0bErtfwdV5cB1YGFP3irkiJKhOEAQh6aTNBpR/Hdg5Gdj0FVCwjsTupLTYqVWrFoYOHYqPPvoI/v7+idm/4Iow9xILfAbfALKWBBoMM9oiQRAEc+Td2fOrVjPr7BapiJ4aAcpDhgzBgwcPErNvwVVhKYhT6wBPPy2fjtS9EgRBSD4MBXihi7a8+SujrTGn2GFMjiA8lUv7gLVDtOXGo4CskqJAEAQhxajWG3D3As5sBs7vMNoacw49lwSCwhMJDQLm9QCiI4DiL2v9y4IgCELKkT4PULaDtszYHSHlkwoWKVLkqYLn9u3bidmlYBbo+VvUC7h9GgjMA7z8vQTPCYIgpFZF9H+ma+ECF/cAuSsYbZG5xA7jdgIDA1PPGsF52fkjcHSx5l5tN03LqyMIgiCkPBkLAGXaA/v/1Cqid15gtEXmEjvt27dH1qxZU+zLR40ahfnz5+O///5ThUWrVq2qkhYWLVrUuk1oaCg+/PBD/PXXXwgLC0OjRo0wceJEZMuWzbrN+fPn8c4776gh8mnSpEHXrl3VvlnDS3gG8MlidX9tudEIIHd5oy0SBEEwNzU/Bv6dBZxaD5zdCuSvZrRF5ojZSY14nU2bNqFnz57YsWMH1qxZg4iICDRs2BDBwcHWbfr06YMlS5Zgzpw5avvLly+jdevW1vVMYti0aVOEh4dj27ZtmDZtGn777TcMHDgwxe0V4iHkNjDndS1Op0RLLaeOIAiCkPrenXKdteX1wyWr8lPwNHI01sqVK2O9pkih54iFRmvWrImgoCBMmTIFM2bMQN26WrbIqVOnonjx4kogVa5cGatXr8aRI0ewdu1a5e0pW7Yshg0bhk8//RSDBw+Gt7d3itst2ObT+R8QdAHIWBB4+QeJ0xEEQXiW3p39M4Dz27T4nUL1jbbI+cVONG9sqQzFDcmYMaOaU/TQ21O//qMTyGrrefPmxfbt25XY4bxUqVKxurXY1cVurcOHD6NcuXKPfQ+7wzjp6DW9+F2czIDejtRsj/vWcfA4sRoWT19Etv4V8PDjF8LMbXY0XK3NrtZeIm12DZLUZv+scC/fDR67JiN63TBE5a3pVA+cESlwnu39rMMEtVBM9e7dG9WqVcPzzz+v3rt69aryzLA2ly0UNlynb2MrdPT1+rr4YDwPg63jQi+R2TJEs3swNch0/z9UOzlKLe/P2RHn955n9BTM3GZHxtXa7GrtJdJm1yCxbfaOeB4N3H3geWU/9swchivpK7jUeQ4JCXEuscPYnUOHDmHLli2p/l39+vVD3759Y3l28uTJo+KF0qVLBzNAtcsLqEGDBvDy8krZnT+4Bs9fPoIbLIgu3R7PNxuN5x3gaSJV2+yguFqbXa29RNosbX4aboGnga1j8eKD1Yhs/wXg7gFXOc/3YnpmnELs9OrVC0uXLsXmzZuRO3du6/vZs2dXgcd3796N5d25du2aWqdvs2vXrlj743p9XXz4+PioKS482Gb7w0rxNkVHAYtY9+o6kKU43JuNhbuDxUWZ8Tw+DVdrs6u1l0ibXYMktbn6+8CeKXC78R+8ji0GSr8CVznPXnZ+LlEZlFMaBj1T6CxYsADr169HgQIFYq0vX768asi6deus7x07dkwNNa9SpYp6zfnBgwdx/fp16zZUivTQlChR4hm2xkXYOAo4+zfgFQC88jvgHWC0RYIgCK4N85pVe09b3jASiHKdWCd7cTe662r69OlqtFXatGlVjA2nhw8fqvVMYNijRw/V5cQcOgxY7tatmxI4DE4m7HqiqOncuTMOHDiAVatWoX///mrf8XlvhGRwYi2w+WttmRmSsxQx2iJBEASBVHoH8M8M3DmjjdASHEfsTJo0SY3Aql27NnLkyGGdZs2aZd3m22+/RbNmzdCmTRs1HJ1dU0xEqOPh4aG6wDinCOrUqRO6dOmCoUOHGtQqkxJ0EZj/prZcoQdQqq3RFgmCIAg6PmmAGn0f1cyKfDTiWDA4Zsee3D2+vr6YMGGCmhIiX758WL58eQpbJ1ihS3RON+DhbSBHGaDRSKMtEgRBEOLCB9Ft44F7F4E9vwKV3zHaIofBUM+O4CSsHQxc3AX4BGp1r7x8jbZIEARBiAt/m2t9rC1v+hJ4eMdoixwGETvCkzm6BNg+XltuOVFLUS4IgiA4JuW6AFmKaUJn8zdGW+MwiNgREub2GWBhT225Si+geDOjLRIEQRCehIcn0GCYtrzrJ+13XBCxIyRARCgwpysQFgTkqQTUH2y0RYIgCII9FG4AFKwNRIVrYQiCiB0hAVZ/AVw5APhlBNpOBTxcK7GXIAiC08KM9g1HcAE4shA4vxOujogd4XEOzgV2/6Itt/4ZCMxltEWCIAhCYsj+PFCuk7a86nMOf4YrI2JHiM3NE8CSD7TlGh8BhR9VnBcEQRCciLr9tWz3l/YAh+bBlRGxIzwi4iEwuysQ/gDIVx2o3c9oiwRBEISkkjY7UC3m4XXtEC0W00URsSM8YvnHwPXDQEAWoO0ULapfEARBcF6q9gLS5gSCzgM7J8NVEbEjaLCWyj9/aAFtbaZoTwSCIAiCc8NizfUGaMt/jwGCb8IVEbEjANeOAMs+1JbZdVWwltEWCYIgCClF6fZA9tJA2D1g42i4IiJ2XJ3Qe8DszkBECFCwDlDzI6MtEgRBEFISd3egEYeiA9g7Fbh1Cq6GiB1XhkMRF/cCbp0E0uUC2vwCuHsYbZUgCIKQ0hSoCRRqAERHAuuGwNUQsePK7JgEHFkEuHsC7X4DAjIbbZEgCIKQWjQYEpNocBFwcQ9cCRE7rsr5HcCamKC1RiOBPBWNtkgQBEFITbKVBMp20JbXDHSpRIMidlyRBzeAOa9r7szn2wAV3zLaIkEQBOFZUOdzwNMXOLcVOL4KroKIHVcjOgqY1wO4fwXIXARo/r1WR0UQBEEwP4G5gUpva8trBwFRkXAFROy4GhtGAmc2aSnEX/kD8EljtEWCIAjCs6R6H8AvA3DjP+DADLgCInZcieOrgb+/0ZZf/h7IWsxoiwRBEIRnjV96rfah/gAcHgKzI2LHVbhzFpj/prb84ptAqbZGWyQIgiAYRcU3gfR5tZCGHRNhdkTsuAIs/ja7CxB6F8hV/lFyKUEQBME18fQB6saMyN36HRB8C2ZGxI4rsPJT4MoBwC8j0G6adpELgiAIrs3zbR+Vkdj0JcyMiB2T4/bvX8De32IKfP4CpM9jtEmCIAiCo5SRaDhMW979C3DlX5gVETsmJl3IeXis+OhRgc9C9Yw2SRAEQXAkCtYGSrQELFHA0j5AdDTMiIgdsxJ6Dy+e/QFukaFAofpAzY+NtkgQBEFwRBqPArzTApf2APvYE2A+ROyYEYsFHkt6IU3YNVjS5QZa/6y5KwVBEAQhLulyAnW/0JbXDtay7JsMuQOake3j4X58OaLcPBHV5lfAP6PRFgmCIAiOzItvasHKoUHA6v4wGyJ2TFngc5BaPJSrIyw5XzDaIkEQBMHR8fAEmo3TBrNwYMuZzTATInbMRPBNYE43FWgWXbI1zmaua7RFgiAIgrOQuzxQobu2vOxDIDIcZkHEjpkKfDJD8v3LQKbCiHppjBT4FARBEBJHvYFAQBbg5nFg2/cwCyJ2zMLfY4BT6wFPP+CV3wGftEZbJAiCIDhj3axGo7TlzV8Dt8/ADIjYMQOnN2rF3EizsUC2EkZbJAiCIDgrpdoCBWoBTF3C7iyLBc6OiB1n594VYN4bHG8OlOsMlO1gtEWCIAiCM+PmBjQdA3j4AKfWAf9Mh7NjqNjZvHkzmjdvjpw5c8LNzQ0LFy6Mtd5isWDgwIHIkSMH/Pz8UL9+fZw4cSLWNrdv30bHjh2RLl06pE+fHj169MCDBw/gEkRFAvN6AME3gGzPA02+NtoiQRAEwQxkLvwo987KfsDdC3BmDBU7wcHBKFOmDCZMmBDv+q+++grff/89Jk+ejJ07dyIgIACNGjVCaGiodRsKncOHD2PNmjVYunSpElBvvfUWXIINI4BzW7XMlyzw6eVntEWCIAiCWajSC8hdEQi/Dyzu5dTdWZ5GfvlLL72kpvigV2fcuHHo378/WrRood77/fffkS1bNuUBat++PY4ePYqVK1di9+7dqFChgtrmhx9+QJMmTfDNN98oj5FpYTDylm+15Ze/BzIXMtoiQRAEwUy4ewAtJwGTq2mxoXunPhqa7mQYKnaexJkzZ3D16lXVdaUTGBiISpUqYfv27UrscM6uK13oEG7v7u6uPEGtWrWKd99hYWFq0rl3756aR0REqMnheXANnvPfghssiCrXFdFFm9P4WJvo7XCK9qQQ0mbz42rtJdJm18Bh2xyYD+51+sNjTX9YVvVHZL6aQPp8DtNmez/rsGKHQofQk2MLX+vrOM+aNWus9Z6ensiYMaN1m/gYNWoUhgwZ8tj7q1evhr+/PxwaSzSqnPoaWYNvIMg3DzZH10D08uUJbs7uPVdD2mx+XK29RNrsGjhkmy25US2gKDIHH8PdaZ2wrdCngJu7Q7Q5JCTEucVOatKvXz/07ds3lmcnT548aNiwoQp0dmTct34Lj/uHYfHyh3/XWWicuUiCapcXUIMGDeDl5QVXQNps/ja7WnuJtFna7BDcKQnLz7WQ5cFRNMt6BdGspeUAbdZ7ZpxW7GTPnl3Nr127pkZj6fB12bJlrdtcv3491uciIyPVCC398/Hh4+OjprjwYDvkRWZb92rTaLXo1uRreOUo+dSPOHybUgFps/lxtfYSabNr4LBtzloEaDAUWP4RPNYPhUfRRkCm5wxvs72fc9g8OwUKFFCCZd26dbEUHGNxqlSpol5zfvfuXezdu9e6zfr16xEdHa1ie0xFyG1gbg9V9wqlXgHKdjTaIkEQBMGVqNADKFATiHwILHxXS3/iJBgqdpgPZ//+/WrSg5K5fP78eZV3p3fv3hg+fDgWL16MgwcPokuXLmqEVcuWLdX2xYsXR+PGjfHmm29i165d2Lp1K3r16qWCl001EovD/Rb1BO5dBDI+p2VJlrpXgiAIwrPE3R14ebyW7uTCDq1MkZNgqNjZs2cPypUrpybCOBouM5Eg+eSTT/Dee++pvDkvvviiEkccau7r62vdx59//olixYqhXr16ash59erV8dNPP8FU7PwROLYc8PAG2k2VuleCIAiCMWTIp2VXJgyrYHiFE2BozE7t2rVVPp2EoHdn6NChakoIjryaMWMGTMulfcDq/tpyw+FAjjJGWyQIgiC4MmVeBU6uBQ7OBua9CbyzBfANhCPjsDE7AoDQIGBuNyA6AijeHKjoIpmhBUEQBMem6Rgt307QeWBpH4fPrixix1HhhbP4PeDOWSB9Xq2fVOJ0BEEQBEfANx3QZgrg5gEcmgccmAlHRsSOo7L7F+DIIsDdC2j7G+CX3miLBEEQBOEReV4E6nyuLS/7CLh1Co6KiB1H5MoBYFXMBdRgCJC7vNEWCYIgCMLjVO8D5K8BRAQD83oAkeFwRETsOBqh94A5rwNR4UCRl4DK7xptkSAIgiAkXCy01Y+Ab3rg8j/AhuFwRETsOFqcztLewO3TQLrcQMuJEqcjCIIgODaBuYAW47Xlrd8Dp9bD0RCx40jsm6YFejHgq+2vgH9Goy0SBEEQhKfDEcMVuvOpHZj/P+BB7FJORiNix1G4cQxY8Zm2XG8gkNdk5S4EQRAEc9NoJJC1BBB8HVjwNhAdDUdBxI4jEBmm1b1ivZGCdYCq7xttkSAIgiAkDi8/oO1UwNMPOLUO2P4DHAURO47A2iHAtYOAfyag1WSt/oggCIIgOBtZiwEvfaktrxsKXNwDR0DuqkZzYi2wY4K23GIikDa70RYJgiAIQtJ5oQtQshUQHQnM7a5VA3Dl2lguDwO4Fr6tLbMURNHGRlskCILJYP3ByOhIhEWFqSkiOkJNfM92irJEWedR0VGItEQi2hKt3tM/ExEVM4+OUNtE858lWn0H5/zH9233ofYZ854FFrXMudo+5rNWWxncCoZ6RONK8BVs2boFnh6ecHdzh4ebh3Xu4e4R72svdy/4ePjA28NbTVz28vCCp5vnY5/zdH/0Hpe5jZq7e8Lb/dHnOfE91moU7ITHqvl3wKW9wN1zwJIPtO4tA4+hiB2j4B/4wneB4BtaQFeDhIudCoLg/PCmHh4djtDIUKvwCIuMmUeFITQq1PradjkkIgSHHx7GsX+OKZFh/WzMFB4VriZ9Wc2jY7+mqHBGDp47CEfADW5W4URBxYliSF9WosjTB74evvD19FVzvg7wDEA6n3RI550OgT6Baq4mn3RI45UGabzTqM+aEt9ATeD82gg4vECLRy3f1TBzROwYxc4fgZNrAF7orC/CwC5BEAyHnogH4Q9wP/w+7kXcU3N9Co4IxsPIh2qiaOE8JDIklmixnWyFDZd1z0WSOJoy7aOXgjdo69zGo6F7PuJ6S2y31z0lureDXhLrBHf1nr69reeE67hM4cD39c/ydVyvSXRUNA4fOYxixYvBzd1NeYUo2JQ3iXN6jmImeoF0rxTFoK3w00VffJ/TvU1xPVuc9M/q8LxRgHJKaXis0nqnVcIo+mE0Vm5cicz+mZHRN6OaMvllQibfTMgWkA3Z/bPD38sfTkPuCkDdAcDaQcCKT4E8lbSYHgMQsWMEVw8BawZoy41GANlKGG2RIJjGe8Kb24OIB0qwUJzcj7j/SLyExxYv1vci7uNemLaO4iW14U2eT/T0ANBDQG+A3mVi6yVQXTLu3rhy4QqKPFdE3ehst9M/q7pt3L1jdeHo+9b3p+/LGbpjIiIisPzUcjQp1gReXl6G2EBxpHvSKH4oVuPrzrP1rFH86uJWCeGIEHV9BYUFxZpz4rWp2hodgduht8F/5NLlS0+0i54hXfhkD8iOXGlyIVfaXMidJrdaTu+T3rHOcdX3gTObgCC2y7jK6CJ2njVhD4C53R6Vg3jxDaMtEgSHg0/dcW8OXL7z8A72hO7Bkb1HlEAJCg/C3bC7SqhwPd/jk3lK4O/pr564OfEGwy6HAK8A+Hn6WScKCjXXxUqMSNHFhi5KVNdGzDZ8PzExIOrGf2s5mpQz7sbviuiCNLW6mSimKHiUEI+4j7shd7Fh+wYUfL4ggiKCcOvhLdwKvYXbD2/jxsMbuBZyTW2v/z2cuHMiweuW4idHQA5k88+mTQGP5nnS5FHeuWcGRxez98LTB/AOgFGI2DGiHMTN40DanFp6bUdS4IKQwl4WPt3yh1kXJLqXxdbzwvV3Qu+obfiEyzmFyxO7fI49+bvZNUJhQoHC2AhdtKjJK20sEWO7rIsavqYgEYTUFFP6tZcDORCRJgJXvK6gyXMJi1p6Hq8FX8PVkKu4GnxVBXFfenAJl+5fUnOKInomKYQSEkOebp7Imy4vnkv/HAqlL2Sd506bO/XihxygGoD8NT9L9k4FDs7RykG0mwoEZDbaIiGFiIyKRlhkNMI5cTmC8yiER3L0iQVRFs4Zc8CYEM4tiIiKRkSUPteWI6O0baOjOVpF+yw1snrPoi1r6/hkaEFEZBSOn3fH4dXHATd37bvUZyxWzwFn7m68/fMhy8362kPFTHC9GzzctWWu97C+1t6zuIXB4v4Q0W4PEY2HiEQIIiwPEW55gLCoYIRG38fDyAcIjryvpgcRmpclKOxurLiHpEChogd0BnoHqtd3r91FqUKlkNEvowr6VJO3NueNg9uwu4c3E0EwE7o4KpShULzr2dV2OfgyLj+4rEQRvUFqCr5mFUcUQ6eDTqtpzbk1sT7PGCF6hDixi4xT3rSaMGIXGWOunBURO8+Ky/u1AC1SfzCQt7LRFpme0Igo3AuNwL2HkQgJ5xSFh+FR2jyCy5GaQKHQiHwkOvT3lHCJmcIio9R7oRHRMfuJtNkPAxstxqbLunTWju0i4ebxEG4eIXDzCIabZ8zcw3bO6SFgs+zmlsyRPBZ3IDoA7tF+cIc/POEHTzc/eLkFwMedMSj+8HUPhJ9HOgR4BiINJ69ApPVKB39vH/h6ucPXy0PNPd2AQ+f3oVqGysiQxg9pfT3VFODtqYSaILgy7CotGFhQTfFhsViU+Dl19xRO3j2p5moKOqW8rCp2KPQ2Dt86/NhnGe+VPzC/tv/0BZEvbT7VXUYRxABqh4oTigcRO8+Ch3eBOV21OJ2iTYCq7xltkWN1dUREIThMEw3BMSJCFycULA/1eUS02lZ/72GceXB4BK7e9MCwgxtxLzRSiRQjoFfEx9Md3p7u8PJgPg/NU6JPnjFeE67nMrfRJq7niBVtH+6xPCxc5t6jlWclCsExHpb7uHL9HDJmDUCUWygiLMExUwjCoh8gLPq+mtMLQ29MkrG4wwN+cLP4wS3aD4j2hYVTlD+iIn0RFemHiAhfWCL9YIn2U+9rUwAQ7a06luyHMTe3YqZ4jzB+/G93rHf4O5vG2xMBPp7w9/FAGs69PZQI8vfxRJqY97iecyWQfDyRztcLgX7alI6Tryc8tQMtCKbDzc3N6rGplqtarN9hdifT83PlwRXVTaYvn713FmeCzqig6+N3jqspLuz+ojeI4oeeoMIZCqNw+sKqe4zdwo6AiJ3Uhv0Oi3oCd84C6fMCLSc6ZZwO/xg0r8Yjj4YSJWGRCI4RJxQs+npb70dIjBjRtwlWn4lZDo9Uhyjl4LF91HXCh/20vl4I8PaAn7cH/L094eelLfvFeAuU0KA4iREcvNnpYoXv+Xh5wMdDe83t/XgDjfm8f8w++b6Pp4fahgIlITjyQsWshD9Qw5r1ZeuIIZtRQVog4qMRQ7YjOGKRBjhr5wAidmaxSyiDTwY1aiO9b3rrMruB9LmeE0SfMwj3aU9uWvI6i/KMRUQ+8pJxrnvKQm0E66PJpvtP96KpudYdGBoZhbCY7XhNXbt1B+4+/ngQFoX7oRwZo3Xv3Q+LVFNyoRiyFT/6Muf1i2dDlecyJfs7BMGRcHNzs/7dF8tYLN4BA+weo+jRvUEXH1xUcULXQ64rIURRxGkrtsb6bM6AnJr4yVAYrxR5BTnS5IARiNhJbXZMAv5bCnh4A+2mAX4ZUuVrGMeh3yx4owgJDcPVEODgpSCERbnhYURkLO+JJjg0scKbhq2IiddzEhGVwqIkNryPauJBExJKTOhzig0KlJhJFxy62FDveXvA292Cw/v3oGHtGsiY1k/dqAJSuHuDQ0614cua+LhCMfIg9pBmBt/ytT7c2TpFMLYlGd6VeGJZ2H8ffj8c+bPnR6Bv4GPBtrYChnN+LrX63VV+FQ/NU4VUinNUI5OWL0eTJjVUEKcaah4Zrbor74dGatd3mHYtKy9hWBQe8FpX17nNFKoJo3sP2c0ZgaCHEervgejbXLr7+LmauvUMfu9eCdULS7yd4Dp4uHsgT9o8aqqZu+Zjv4n0BOmB0hRE7CJjgPT1h9e1GKLgy9h0cROaF2xuWBtE7KQi+7auQtm1A1QBsn3FPsbRi5kQee6setLlE7AepMo5XzPIlU+p+tOt/mT7aFmbh8aZc+I+HscTOLAzxdtFsaF7SAJ8NIGiz3Whoi8rwRLjSeF7elcC1+nL/Cz3ldw+X94Iw04DxbKnjXc0A58+4uZaoTAJDg9WHhPrFBkzHDRGoKjtYl6nVFIxDg9Vo3680mojhmJGDSkRE5Nx1XZSAibmfduRQtabf03XHJbMa0aL5/FA1rTJ2xf/FnXhw4ldofpriqmdp29j0/EbeG/mPizuVR15MjpRcjdBSCU4jF0XQojjtOFABTUy7O4J5Q3iKDCjELGTWjy8g1xr34W7JRJLoyqj194SwN5Dz+zrVTwIohAY4GcVF7oIUQLDuhx7rnXxaAGhenePv5dnLC+LUYGgel6KuEnhdEES9DAIBx4ewI7tO7QcLDaJvLg+uSODEvKsqBFA3mliD12OM7xZH87MZQ6JlmHNjgc9UpnS+KgpPrpXi8IrP27HvxeD8L8/9mLeO1XV34UgCPFDj3KF7BXUZDTyi5ta+ARib+YWKH1nDRbl+hR1vfg0rrn4PRkX4q4HpGoBq4wT0eYMbvVQMSNq8tKXte6b+OYqtsQmxoT7jYyMjHH313SoJ36rdyVM6wayjUexJpCLWaev170q9MLYlW7/zJNjVnRhotem0Ycqq7wsMcu6WLHd1ipsUrErSHBc+AAwuVN5NP9hC45cuYfPFxzE2FfKOPwoFEEQROykHu7uaNJzLBARip+9fGE2mB6dyd/0BHC2y/prfdlWyFDsJBcOgYyVJC5GgLC2zM2LN1GueDlk8Mtgzb9i2/1DQSP5V4SkkjO9H8Z3eAGdpuzEgn8uoXTuQHSrVsBoswRBeAoidlIbJxA6HCHEDLZqCrvz2HJcUcN5cgJt6V2JG0gbK07FZjmuqOGUUJZPa1r9Eq4ZvyI8Gzga64smxTF06REMX3YUxXOkQ+WCMkJLEBwZETsmhLEtFCXXo65j77W9uBd5z5osSp9Yd0VfpsclKbBysT5cMdbQZe9ANaRZHw0U18Mi3hXB2elWLb8a6UjvTs8/92HJe9WV10cQBMdExI6TwCG29Kiw9snNhzdjTXHFC70xkZaYfCPr7BcuFCoZfDOoictMHa6/pwsZ2zws7DoS0SK4IozTGdmqFI5dva/idxqP26xy8WjrYraJSaRoT0iP7SZxY4D4tx8c7IFvj295VAIkoQ8npg0236UtazbrX69KjKhyIgl9/lH71FJMSRKr3Y8aYIcx2met+wJw544H/ri869FvjM06W9t0m1XZk5hSKBxEwXEUjInk+wkdIkvM8Y2O1sqvcFArXz8JfW1C28U9R9rLGBvjOc460dHRuHrVHSvuHVDJReO22fa6sN23HvfJz+gJTDnXj4l+nt1i9mXd1iZm1DY3GJulHxf9WMfeVvsexk/yuOnlbbSSNryXuKlBLlqakEcDXTjPm8lfxZkagYgdBxExzEfA5Ew3Qm5o84c31DLFjFp+eCPR1Zx93XyRLU02ZPLLpIQLJwoX29dM8805vS4iXATBfvgD/mPn8mg9aRtu3A9TQ9VTDzfcCLUzc6RpcMOZ+3fhWrjjwO1rMCtr+tRE4WzJzBGRRETspCIcQUTBQqFiK2D0OWuUcJ6YIdH0rGT2y2ydKFY4Z1FEWwGTxiMN1q5aiyZNJH5FEFIL5trZ9HFt5eHRsX3eT9hJEP+K+LbnyMrt27ejSpUq8PT0tGv/9nsn9Nfa47z2RK+9VkVnE9jPI6/No20f7Suup+qJpsTyJOjfzzbv3bcPL7zwAjw8PB6z1dY2a4HcmPf0Qrn0NHCf8ecg09CL3dLz8Wj5kdfKdvQnvyOW1866HP9xsbU17nGNZVFMO6KionDo8GGULFkS7jGjPfXzmNA517xRWp62KBYS1vO30eVie1wt2vHRvDFcb7t9tHqtt+WRN0h7rY6lygVnmxOOhYYfHT/b8jZcr2dH1xPT6pnTjUzVIGInFWm5sKXy2NgrYrL6Z0UW/yzI6qfNs/hlifWaIoYJnOyBwbqCIKQ+zE9VLm/qZEbX/5avHQbK58vgMg8ubHPUOQsal8zmUm1efusQmlTK6zJtfpaI2ElFKFA4aslWuFiX/bIocaMLnIRGGAmCIAiCkDxMI3YmTJiAr7/+GlevXkWZMmXwww8/oGLFioba9MdLf9jtiREEQRAEIXUwRUTqrFmz0LdvXwwaNAj79u1TYqdRo0a4ft2+LqTUQoSOIAiCIBiPKcTO2LFj8eabb6Jbt24oUaIEJk+eDH9/f/z6669GmyYIgiAIgsE4fTdWeHg49u7di379+lnfc3d3R/369dUIhvgICwtTk869e/esAWJmCezV22GW9tiDtNn8uFp7ibTZNZA2Jw17P+tmedoYRQfn8uXLyJUrF7Zt26aGZup88skn2LRpE3bu3PnYZwYPHowhQ4Y89v6MGTOUR0gQBEEQBMcnJCQEHTp0QFBQENKlS2dez05SoBeIMT62np08efKgYcOGTzxYzgTV7po1a9CgQQOXGcYobTZ/m12tvUTaLG02KxEp0Ga9Z+ZpOL3YyZw5s0o6de1a7KyTfJ09e/Z4P+Pj46OmuPBgm+0iM2Obnoa02fy4WnuJtNk1kDYnDns/5/QByt7e3ihfvjzWrVsXq8YIX9t2awmCIAiC4Jo4vWeHsEuqa9euqFChgsqtM27cOAQHB6vRWYIgCIIguDamEDuvvvoqbty4gYEDB6qkgmXLlsXKlSuRLVs2o00TBEEQBMFgTCF2SK9evdQkCIIgCIJgqpgdQRAEQRCEJyFiRxAEQRAEUyNiRxAEQRAEUyNiRxAEQRAEU2OaAOXkoFfMsDcTo7NkpmQabbbJVRJUSZvN32ZXay+RNkubzUpECrRZv28/rfKViB0A9+/fV3OWjBAEQRAEwfnu44GBgeYtBJoSMOMyC4qmTZsWbm5uMAN6va8LFy6Ypt7X05A2m7/NrtZeIm2WNpuVeynQZkoYCp2cOXPC3T3hyBzx7DBwyd0duXPnhhnhBeQqfzg60mbz42rtJdJm10DanHie5NHRkQBlQRAEQRBMjYgdQRAEQRBMjYgdk+Lj44NBgwapuasgbTY/rtZeIm12DaTNqYsEKAuCIAiCYGrEsyMIgiAIgqkRsSMIgiAIgqkRsSMIgiAIgqkRsSMIgiAIgqkRsePETJo0CaVLl7YmZKpSpQpWrFhhXR8aGoqePXsiU6ZMSJMmDdq0aYNr167BTIwePVplve7du7dp2z148GDVRtupWLFipm2vzqVLl9CpUyfVLj8/P5QqVQp79uyxrufYioEDByJHjhxqff369XHixAk4K/nz53/sPHPiuTXreY6KisKAAQNQoEABdQ6fe+45DBs2LFadI7OdZ2b75e9Vvnz5VHuqVq2K3bt3m6q9mzdvRvPmzVVWY17DCxcujLXenjbevn0bHTt2VPe29OnTo0ePHnjw4EHSjeJoLME5Wbx4sWXZsmWW48ePW44dO2b5/PPPLV5eXpZDhw6p9W+//bYlT548lnXr1ln27NljqVy5sqVq1aoWs7Br1y5L/vz5LaVLl7Z88MEH1vfN1u5BgwZZSpYsably5Yp1unHjhmnbS27fvm3Jly+f5fXXX7fs3LnTcvr0acuqVassJ0+etG4zevRoS2BgoGXhwoWWAwcOWF5++WVLgQIFLA8fPrQ4I9evX491jtesWcM7vmXDhg2mPc8jRoywZMqUybJ06VLLmTNnLHPmzLGkSZPG8t1335n2PL/yyiuWEiVKWDZt2mQ5ceKE+vtOly6d5eLFi6Zp7/Llyy1ffPGFZf78+eoaXrBgQaz19rSxcePGljJlylh27Nhh+fvvvy2FChWyvPbaa0m2ScSOyciQIYPll19+sdy9e1cJH/546Bw9elRdeNu3b7c4O/fv37cULlxY3RBq1aplFTtmbDd/DPlHHx9mbC/59NNPLdWrV09wfXR0tCV79uyWr7/+Otax8PHxscycOdNiBnhNP/fcc6qtZj3PTZs2tXTv3j3We61bt7Z07NjRlOc5JCTE4uHhocSdLS+88IISB2ZrL4krduxp45EjR9Tndu/ebd1mxYoVFjc3N8ulS5csSUG6sUwC3cF//fUXgoODVXfW3r17ERERodyDOuz6yJs3L7Zv3w5nh+78pk2bxmofMWu76eKlS7hgwYLKtXv+/HlTt3fx4sWoUKEC2rVrh6xZs6JcuXL4+eefrevPnDmDq1evxmo36+NUqlTJqdutEx4ejunTp6N79+6qG8Cs55ldOOvWrcPx48fV6wMHDmDLli146aWXTHmeIyMj1W+1r69vrPfZlcN2m6298WFPGzln1xV/A3S4PetY7ty5E0lBCoE6OQcPHlTihv357MdfsGABSpQogf3798Pb21tdMLZky5ZNXWjODEXdvn37YvVz67BtZms3fwR+++03FC1aFFeuXMGQIUNQo0YNHDp0yJTtJadPn1YxaX379sXnn3+uzvX777+v2tq1a1dr29hOM7VbhzEOd+/exeuvv65em/U8f/bZZ6ryNYWbh4eHEgIjRoxQgp6Y7TynTZtW/V4zLql48eKqHTNnzlQ390KFCpmuvfFhTxs550OOLZ6ensiYMWOSj4OIHSeHN0AKm6CgIMydO1fdCDZt2gSzcuHCBXzwwQdYs2bNY09HZkV/yiUMSKf4YXDj7Nmz1ROhGYmOjlZPdSNHjlSv6dmhuJs8ebK6xs3OlClT1HmnN8/M8Br+888/MWPGDJQsWVL9ljF4l+0263n+448/lMcuV65cSuC98MILeO2115T3Tkg9pBvLyeHTHp8Iypcvj1GjRqFMmTL47rvvkD17duUK59OhLRy9wXXOCn8Qrl+/rn4gqPQ5Udx9//33aplPB2Zsty18ui9SpAhOnjxp2vPMURr0UNrCJ2G9+05vW9zRSM7ebnLu3DmsXbsWb7zxhvU9s57njz/+WHl32rdvr0bbde7cGX369FG/ZWY9zxxxxt8sjiziw9uuXbtUFyW7qM3Y3rjY00bO+TsftwuQI7SSehxE7JjwiTgsLEyJHy8vL9UfrnPs2DF1s6Ab1VmpV6+e6rrjE6A+0QNAt7e+bMZ228IfyVOnTilBYNbzXK1aNdUOWxjXQY8W4VBl/ujZtpvdIezPd+Z2k6lTpyoXPmPSdMx6nkNCQlQchi30dvB3zOznOSAgQP0N37lzB6tWrUKLFi1M3V4de9rIOYW9rbdr/fr16rqgZztJJCmsWXAIPvvsMzV8kUM2//33X/Wa0eqrV6+2DlXNmzevZf369WqoapUqVdRkNmxHY5mx3R9++KFl48aN6jxv3brVUr9+fUvmzJnVUGUztldPK+Dp6amGJnN47p9//mnx9/e3TJ8+Pdbw1fTp01sWLVqkrv8WLVo43RDduERFRalzydFocTHjee7ataslV65c1qHnHKrMa/uTTz4x7XleuXKlGlnEdAr8reZIy0qVKlnCw8NN09779+9b/vnnHzVRZowdO1Ytnzt3zu42cuh5uXLlVOqJLVu2qNG3MvTcReGQTeYi8fb2tmTJksVSr149q9AhvHDeffddNRydN4pWrVqp/B1mFztma/err75qyZEjhzrPvDHwtW2+GbO1V2fJkiWW559/Xg1JLVasmOWnn36KtZ5DWAcMGGDJli2b2obXP/NNOTPMJcSbQ3ztMON5vnfvnvrbpYjz9fW1FCxYUA3BDgsLM+15njVrlmon/545BLtnz55q6LWZ2rthwwZ1HcedKG7tbeOtW7eUuGHeJeYh6tatmxJRScWN/yXNJyQIgiAIguD4SMyOIAiCIAimRsSOIAiCIAimRsSOIAiCIAimRsSOIAiCIAimRsSOIAiCIAimRsSOIAiCIAimRsSOIAiCIAimRsSOIAiCIAimRsSOIAhOyfbt21UdJdsaUoIgCPEhGZQFQXBKWBU8TZo0mDJliiqKmTNnTqNNEgTBQRHPjiAITln5fdasWXjnnXeUZ+e3336LtX7x4sUoXLgwfH19UadOHUybNg1ubm6qkrLOli1bUKNGDfj5+SFPnjx4//33ERwcbEBrBEFIbUTsCILgdMyePRvFihVD0aJF0alTJ/z6668saqzWnTlzBm3btkXLli1x4MAB/O9//8MXX3wR6/OnTp1C48aN0aZNG/z7779KOFH89OrVy6AWCYKQmkg3liAITke1atXwyiuv4IMPPkBkZCRy5MiBOXPmoHbt2vjss8+wbNkyHDx40Lp9//79MWLECNy5cwfp06dXXWCM9/nxxx+t21Ds1KpVS3l36BESBME8iGdHEASngvE5u3btwmuvvaZee3p64tVXX1WxO/r6F198MdZnKlasGOs1PT7s+mLMjz41atQI0dHRyjMkCIK58DTaAEEQhMRAUUNvjm1AMh3UPj4+GD9+vN0xP+zeYpxOXPLmzZui9gqCYDwidgRBcBoocn7//XeMGTMGDRs2jLWOMTozZ85UcTzLly+PtW737t2xXr/wwgs4cuQIChUq9EzsFgTBWCRmRxAEp2HhwoWqy+r69esIDAyMte7TTz/F+vXrVfAyBU+fPn3Qo0cP7N+/Hx9++CEuXryoRmPxcwxKrly5Mrp3767idwICApT4WbNmjd3eIUEQnAeJ2REEwam6sOrXr/+Y0CEcWbVnzx7cv38fc+fOxfz581G6dGlMmjTJOhqLXV2E72/atAnHjx9Xw8/LlSuHgQMHSq4eQTAp4tkRBMH0cCTW5MmTceHCBaNNEQTBACRmRxAE0zFx4kQ1IitTpkzYunUrvv76a8mhIwgujIgdQRBMx4kTJzB8+HDcvn1bja5izE6/fv2MNksQBIOQbixBEARBEEyNBCgLgiAIgmBqROwIgiAIgmBqROwIgiAIgmBqROwIgiAIgmBqROwIgiAIgmBqROwIgiAIgmBqROwIgiAIgmBqROwIgiAIgmBqROwIgiAIggAz83+h2cRrDy0algAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "LifeCycleAgent.assign_parameters(**res.params)\n",
    "LifeCycleAgent.update()\n",
    "LifeCycleAgent.solve()\n",
    "LifeCycleAgent.initialize_sim()\n",
    "LifeCycleAgent.simulate()\n",
    "history = LifeCycleAgent.history\n",
    "\n",
    "raw_data = {\n",
    "    \"Age\": history[\"t_age\"].flatten() + birth_age - 1,\n",
    "    \"pIncome\": history[\"pLvl\"].flatten(),\n",
    "    \"nrmM\": history[\"mNrm\"].flatten(),\n",
    "    \"nrmC\": history[\"cNrm\"].flatten(),\n",
    "}\n",
    "\n",
    "sim_data = pd.DataFrame(raw_data)\n",
    "sim_data[\"Cons\"] = sim_data.nrmC * sim_data.pIncome\n",
    "sim_data[\"M\"] = sim_data.nrmM * sim_data.pIncome\n",
    "\n",
    "# Find the mean of each variable at every age\n",
    "AgeMeans = sim_data.groupby([\"Age\"]).median().reset_index()\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(AgeMeans.Age, AgeMeans.pIncome, label=\"Permanent Income\")\n",
    "plt.plot(AgeMeans.Age, AgeMeans.M, label=\"Market resources\")\n",
    "plt.plot(AgeMeans.Age, AgeMeans.Cons, label=\"Consumption\")\n",
    "plt.legend()\n",
    "plt.xlabel(\"Age\")\n",
    "plt.ylabel(f\"Thousands of {adjust_infl_to} USD\")\n",
    "plt.title(\"Variable Medians Conditional on Survival\")\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Age_grp'>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "simulate_moments(res.params, agent=LifeCycleAgent).plot()\n",
    "empirical_moments.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}