{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "4c407b11",
   "metadata": {},
   "outputs": [],
   "source": [
    "#!/usr/bin/env python3\n",
    "import os, glob\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from numpy.polynomial.polynomial import Polynomial\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "b298785d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 77 sonic files → 10308 rows\n",
      "Loaded 50 rain files → 7050 rows\n",
      "               TIMESTAMP  Rain   wT_Flux  wrhoqv_Flux  Average_Temperature  \\\n",
      "0    2024-03-14 00:00:00   0.0 -0.026757     0.001768           284.502020   \n",
      "1    2024-03-14 00:10:00   0.0 -0.026757     0.001768           284.502020   \n",
      "2    2024-03-14 00:20:00   0.0 -0.032390     0.001202           284.407633   \n",
      "3    2024-03-14 00:30:00   0.0 -0.032390     0.001202           284.407633   \n",
      "4    2024-03-14 00:40:00   0.0 -0.031528     0.002094           284.490481   \n",
      "...                  ...   ...       ...          ...                  ...   \n",
      "7045 2024-05-26 23:10:00   0.0 -0.028858     0.002551           287.906135   \n",
      "7046 2024-05-26 23:20:00   0.0 -0.028858     0.002551           287.906135   \n",
      "7047 2024-05-26 23:30:00   0.0  0.000000     0.000000           288.190650   \n",
      "7048 2024-05-26 23:40:00   0.0  0.000000     0.000000           288.190650   \n",
      "7049 2024-05-26 23:50:00   0.0  0.000000     0.000000           288.190650   \n",
      "\n",
      "      Average_Temperature_Corr  Average_H2O_Density  Average_CO2_Density  \\\n",
      "0                   283.876358             5.361980           751.861163   \n",
      "1                   283.876358             5.361980           751.861163   \n",
      "2                   283.782420             5.361250           752.242698   \n",
      "3                   283.782420             5.361250           752.242698   \n",
      "4                   283.862779             5.378899           752.604308   \n",
      "...                        ...                  ...                  ...   \n",
      "7045                286.940066             8.098943           778.446274   \n",
      "7046                286.940066             8.098943           778.446274   \n",
      "7047                287.173680             8.484140           771.996000   \n",
      "7048                287.173680             8.484140           771.996000   \n",
      "7049                287.173680             8.484140           771.996000   \n",
      "\n",
      "      wrhoCO2_Flux  Average_Wind_Ux  ...          G  Wind_Speed     PPM_CO2  \\\n",
      "0         0.137666         2.709073  ... -27.610618    4.281254  385.570578   \n",
      "1         0.137666         2.709073  ... -27.610618    4.281254  385.570578   \n",
      "2         0.180427         2.987826  ... -16.215020    3.947460  385.396855   \n",
      "3         0.180427         2.987826  ... -16.215020    3.947460  385.396855   \n",
      "4         0.164280         3.023096  ... -14.216496    4.066281  385.760797   \n",
      "...            ...              ...  ...        ...         ...         ...   \n",
      "7045      0.196521         2.350137  ... -47.605509    3.137624  403.467930   \n",
      "7046      0.196521         2.350137  ... -47.605509    3.137624  403.467930   \n",
      "7047      0.000000         1.800752  ... -76.920000    2.638803  399.979492   \n",
      "7048      0.000000         1.800752  ... -76.920000    2.638803  399.979492   \n",
      "7049      0.000000         1.800752  ... -76.920000    2.638803  399.979492   \n",
      "\n",
      "         F_CO2  uw_flux_corr  vw_flux_corr  uv_flux_corr  tau_xz_corr  \\\n",
      "0     0.070598      0.086863      0.084371     -0.078325    -0.107789   \n",
      "1     0.070598      0.086863      0.084371     -0.078325    -0.107789   \n",
      "2     0.092438      0.099332      0.090026      0.060704    -0.123380   \n",
      "3     0.092438      0.099332      0.090026      0.060704    -0.123380   \n",
      "4     0.084205      0.088235      0.120804      0.132254    -0.109546   \n",
      "...        ...           ...           ...           ...          ...   \n",
      "7045  0.101856      0.046229      0.055697      0.042015    -0.056760   \n",
      "7046  0.101856      0.046229      0.055697      0.042015    -0.056760   \n",
      "7047  0.000000      0.000000      0.000000      0.000000    -0.000000   \n",
      "7048  0.000000      0.000000      0.000000      0.000000    -0.000000   \n",
      "7049  0.000000      0.000000      0.000000      0.000000    -0.000000   \n",
      "\n",
      "      tau_yz_corr  tau_xy_corr  \n",
      "0       -0.104697     0.097194  \n",
      "1       -0.104697     0.097194  \n",
      "2       -0.111821    -0.075400  \n",
      "3       -0.111821    -0.075400  \n",
      "4       -0.149980    -0.164197  \n",
      "...           ...          ...  \n",
      "7045    -0.068384    -0.051586  \n",
      "7046    -0.068384    -0.051586  \n",
      "7047    -0.000000    -0.000000  \n",
      "7048    -0.000000    -0.000000  \n",
      "7049    -0.000000    -0.000000  \n",
      "\n",
      "[7050 rows x 88 columns]\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Where your merged_data_10min.csv files live (tower/sonic)\n",
    "DATA_ROOT = r'C:\\Users\\magda\\Master_Thesis\\Sonic'\n",
    "\n",
    "# Where your rain files live\n",
    "RAIN_ROOT = r'C:\\Users\\magda\\Master_Thesis\\Cloud_radar'\n",
    "\n",
    "# Date range of interest (folders named 2024-03, 2024-04, 2024-05, 2024-06)\n",
    "DATE_GLOB = '2024-0[3-5]'\n",
    "\n",
    "# Sonic height, von Kármán constant, gravity\n",
    "Z_SONIC = 2.99\n",
    "KAPPA, G,theta0 = 0.4, 9.81, 288\n",
    "\n",
    "# ── 1) LOAD ALL TOWER/SONIC DATA (10-min merged) ───────────────────────────────\n",
    "\n",
    "sonic_pattern = os.path.join(DATA_ROOT, '**', 'merged_data_10min.csv')\n",
    "sonic_files = glob.glob(sonic_pattern, recursive=True)\n",
    "if not sonic_files:\n",
    "    raise RuntimeError(f\"No sonic files found under {DATA_ROOT}\")\n",
    "\n",
    "df = pd.concat(\n",
    "    (pd.read_csv(fn, parse_dates=['TIMESTAMP']) for fn in sonic_files),\n",
    "    ignore_index=True\n",
    ").sort_values('TIMESTAMP')\n",
    "print(f\"Loaded {len(sonic_files)} sonic files → {len(df)} rows\")\n",
    "\n",
    "# ── 2) LOAD ALL RAIN DATA (10-min averages) ────────────────────────────────────\n",
    "\n",
    "rain_pattern = os.path.join(RAIN_ROOT, DATE_GLOB, '**', 'Rain_10min_Averages.csv')\n",
    "rain_files = glob.glob(rain_pattern, recursive=True)\n",
    "if not rain_files:\n",
    "    raise RuntimeError(f\"No rain files found under {RAIN_ROOT}/{DATE_GLOB}\")\n",
    "\n",
    "rain = pd.concat(\n",
    "    (pd.read_csv(fn, parse_dates=['TIMESTAMP']) for fn in rain_files),\n",
    "    ignore_index=True\n",
    ").sort_values('TIMESTAMP')\n",
    "print(f\"Loaded {len(rain_files)} rain files → {len(rain)} rows\")\n",
    "\n",
    "# ── 3) MERGE RAIN INTO SONIC BY TIMESTAMP ───────────────────────────────────────\n",
    "\n",
    "df = pd.merge_asof(\n",
    "    rain, \n",
    "    df,\n",
    "    on='TIMESTAMP',\n",
    "    direction='nearest'\n",
    ")\n",
    "\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "9f22744a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['TIMESTAMP', 'Rain', 'wT_Flux', 'wrhoqv_Flux', 'Average_Temperature',\n",
      "       'Average_Temperature_Corr', 'Average_H2O_Density',\n",
      "       'Average_CO2_Density', 'wrhoCO2_Flux', 'Average_Wind_Ux',\n",
      "       'Average_Wind_Uy', 'Average_Wind_Uz', 'uw_flux', 'vw_flux', 'uv_flux',\n",
      "       'IR20Up', 'IR20Dn', 'NetRl', 'SR15D1Up_Irr', 'SR15D1Dn_Irr', 'NetRs',\n",
      "       'Albedo', 'CSI', 'Net_Radiation_10min', 'AirTC_E5567_Avg',\n",
      "       'RH_E5567_Avg', 'AirTC_E5568_Avg', 'RH_E5568_Avg', 'AirTC_E5569_Avg',\n",
      "       'RH_E5569_Avg', 'AirTC_E5570_Avg', 'RH_E5570_Avg', 'AirTC_E5571_Avg',\n",
      "       'RH_E5571_Avg', 'WS_ms_D15008_Avg', 'WindDir_D15008_Avg',\n",
      "       'WindDir_D15008_StDev', 'WS_ms_D15014_Avg', 'WindDir_D15014_Avg',\n",
      "       'WindDir_D15014_StDev', 'WS_ms_D15463_Avg', 'WindDir_D15463_Avg',\n",
      "       'WindDir_D15463_StDev', 'BP_mbar_Avg', 'Temperature_K_2',\n",
      "       'Dry_Static_Energy_2', 'Temperature_K_2.99', 'Dry_Static_Energy_2.99',\n",
      "       'Temperature_K_4.47', 'Dry_Static_Energy_4.47', 'Temperature_K_6.69',\n",
      "       'Dry_Static_Energy_6.69', 'Temperature_K_10', 'Dry_Static_Energy_10',\n",
      "       'qv_2m', 'qv_2.99m', 'qv_4.47m', 'qv_6.69m', 'qv_10m', 'qs_2m',\n",
      "       'Virtual_Dry_Static_Energy_2', 'qs_2.99m',\n",
      "       'Virtual_Dry_Static_Energy_2.99', 'qs_4.47m',\n",
      "       'Virtual_Dry_Static_Energy_4.47', 'qs_6.69m',\n",
      "       'Virtual_Dry_Static_Energy_6.69', 'qs_10m',\n",
      "       'Virtual_Dry_Static_Energy_10', 'rho_air', 'rho_air_Tv', 'tau_xz',\n",
      "       'tau_yz', 'tau_xy', 'SHF', 'qv_sonic', 'wqv_Flux', 'LHF', 'G',\n",
      "       'Wind_Speed', 'PPM_CO2', 'F_CO2', 'uw_flux_corr', 'vw_flux_corr',\n",
      "       'uv_flux_corr', 'tau_xz_corr', 'tau_yz_corr', 'tau_xy_corr'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "f1824c0e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "stability_class\n",
      "Stable          50.663570\n",
      "Unstable        47.810219\n",
      "Near-neutral     1.526211\n",
      "Name: proportion, dtype: float64\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\magda\\AppData\\Local\\Temp\\ipykernel_35404\\398649826.py:90: RuntimeWarning: invalid value encountered in power\n",
      "  φm_unst = (1 - 15*ζ)**(-1/4)\n",
      "C:\\Users\\magda\\AppData\\Local\\Temp\\ipykernel_35404\\398649826.py:91: RuntimeWarning: invalid value encountered in power\n",
      "  φh_unst = 0.74*((1 - 9*ζ)**(-1/2))\n"
     ]
    },
    {
     "data": {
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TJmrQoIFeeeUVTZ48WSNHjpTFYtHRo0e1cOFCdejQQd9++63atm1rdrgAUGKkZGTqRFK65C2dSEpXSkam2SEBKGIHDhzQoEGD9N1330mSatSooTlz5qhXr168gywPV9y0ZdIAAACgcB0/flzPPPOMPvroI0lS+fLlNW3aND300EOyWpk+MsO0adP0119/SZKcTqc2btyoWbNmqWnTpmrSpIlefvllValSRc8884w2bNhgcrQAUDKkZWTpQEyyKvjZJEkV/Gw6EJOstIws+XoV2huCAbiI1NRUvfLKK5o2bZoyMjLk6empZ599VqNHj5aPj4/Z4bmsy6r+Fy1apC1btshut+dMGsTGxiomJkZ///23brvtNnXo0EG//vprUcULAABQ6jgcDs2YMUP16tXTRx99lLMUwv79+9W3b18atibas2ePzp07p99//10eHh6yWq365JNP1KNHD4WEhKhGjRr69NNP9eeff2rFihU6dOiQ2SEDAAC4BMMwtHz5cl1zzTWaNGmSMjIy1K1bN+3cuVMTJ06kYVuAy/oVFpMGAAAAhWvt2rWKiIjQ7t27JUmtWrXS/Pnzdd1115kcGbJ5eXmpRYsWatOmjRo3bqyPP/5YTqdTe/bs0bZt27Ru3TqtXbtW/fr1U3x8vPz8/JSUlGR22ADgsrw93dSkWpD+OHhGkuTudv5jNiEDSo+//vpLgwcP1rfffitJql69umbPnq3evXuzFMIluqym7Z49e5Senq4dO3boxhtvzJk0GDt2rNLT01W1alXVrl07Z9KgYcOGqlWrVlHFDgAAUGKdPHlSzzzzjJYuXSpJCg0N1ZQpU9SvXz8ma13UjBkz1KFDB0VHR+upp55S48aNVb16dW3ZskWVK1fWsWPHdOzYMe3cudPsUAHApVmtFnWqX1E+7lLm30fVoW55tb66oqxWGjlASZeWlqZXX31VU6ZMUUZGhjw8PDRy5Eg9//zz8vX1NTu8EuWyF4th0gAAAODKZWZmau7cuXrxxRd17tw5WSwWPfXUU3r55ZcVHBxsdnjIR5MmTbR582Y99dRTatWqlQzDkCS5u7tr0aJFkqSqVauqatWqZoYJACVCsK+nOtevqFV/S53rV5TN5ml2SAD+oxUrVmjw4ME6fPiwJKlLly6aN2+e6tSpY25gJdQVr/DNpAEAAMDl+eWXXxQREaEdO3ZIkq6//nrNnz+fTVxLkNq1a2v16tU6ffq0NmzYoIyMDLVq1UrVqlUzOzQAKHGyJ2uZsAVKtujoaA0ZMkQrV66UdP6X2LNnz9Ydd9zBUgj/wRU3bZk0AAAAuDSnTp3SqFGj9N5770mSQkJCNHnyZD366KMshVBCVaxYUbfddpvZYQAAAJgmLS1NU6dO1auvviq73S4PDw+NGDFCY8aMkZ+fn9nhlXhX3LSVmDQAAADIT2ZmpubPn6+xY8cqKSlJFotF/fv316RJkxQSEmJ2eAAAmMrpNHL9DaDk+PrrrzV48GBFR0dLkjp16qR58+apXr16JkdWevynpm02Jg0AAABy++233zRgwABt375dktS8eXPNnz9fLVq0MDkyAADMF5eSoQ1/xUiS1uyNUaurKijYl3VtAVd3+PBhDR06VF9++aUkqXLlypo1a5buvvtulkIoZLwfDwAAoBDFxMSoX79+atu2rbZv365y5cppwYIF2rBhAw1bAAB0frI2KjpWJxJSJUknElIVFR3LxC3gwtLT0/Xyyy+rfv36+vLLL+Xu7q6RI0dq7969uueee2jYFoFCmbQFAAAo67KysvT6669r3LhxSkxMlCQ9/vjjevXVVxUaGmpydAAAuA57plOJaQ6F+NqkBCnE16bENIfsmU55e7qZHR6Af1m1apUGDRqkv/76S5LUsWNHzZs3T9dcc43JkZVuNG0BAAD+ow0bNmjkyJE5a3o1bdpUkZGRatWqlcmRAQDgemzuVgV6e+h43DmVlxSbYleVYH/Z3HkzMOBK/v77bw0bNkzLli2TJFWqVEkzZ87Uvffey2RtMeA7IgAAwBU6c+aMHnvsMbVr107R0dEKCgrS/Pnz9ccff9CwBQDgIqxWi1qGh6hykI8kqXKQj1qGh8hqpQkEuAK73a5XXnlF9evX17Jly+Tm5qbhw4dr7969uu+++2jYFhMmbQEAAC5TVlaW3njjDT3//PNKSEiQdH7H3CVLlqhy5crmBgcAQAkQ7OupTvUqaNVhqVO9CrLZ2IQMcAXff/+9Bg4cqAMHDkiS2rVrp8jISDVs2NDkyMoemrYAAACX4Y8//tCAAQO0efNmSVKTJk302muvKT4+XuXLlzc5OgAASo7syVombAHzHT16VMOGDdPnn38uSQoLC9P06dPVp08fJmtNwvIIAAAAl+Ds2bPq37+/WrVqpc2bNyswMFBz587Vxo0b1bp1a7PDAwAAAC5bRkaGpkyZonr16unzzz+Xm5ubhg4dqr179+qBBx6gYWsiJm0BAADykZWVpbffflvPPfec4uLiJEl9+/bVlClTVLFiRUmSw+EwM0QAAADgsq1Zs0YRERHat2+fJKlt27aKjIzUtddea3JkkGjaAgAAXNTGjRsVERGhjRs3SpKuvfZaRUZGqm3btiZHBgAAAFyZY8eOacSIEfrkk08kSRUqVNC0adP00EMPMVnrQlgeAQAA4F9iY2P11FNPqWXLltq4caMCAgL02muvafPmzTRsAQAAUCJlZGRo2rRpqlevnj755BNZrVYNGjRI+/bt08MPP0zD1sUwaQsAAPA/TqdTixYt0ujRoxUbGytJeuihhzR16lSFhYWZHB0AAKWL02nk+htA0Vm7dq2GDBmiPXv2SJJuuOEGRUZGqkmTJuYGhouiaQsAACBp8+bNioiIUFRUlCSpYcOGioyMVLt27UyODACA0icuJUMb/oqRJK3ZG6NWV1VQsK+nyVEBpc+JEyc0Y8YM/fLLL5Kk8uXLa+rUqXr44YdltfIGfFfGVwcAAJRp8fHxioiIUIsWLRQVFSV/f3/NnDlTW7ZsoWELAEARcDoNRUXH6kRCqiTpREKqoqJjmbgFCpHD4dDMmTPVsGFD/fLLL7JarTmbjvXr14+GbQnApC0AACiTnE6n3n33XY0aNUpnz56VJPXp00fTpk1T5cqVTY4OAIDSy57pVGKaQ8E+nlKCFOzjqcQ0h+yZTnl7upkdHlDi/fzzz4qIiNCuXbskSXXr1tWSJUt0/fXXmxwZLgdNWwAAUOb8+eefioiI0Pr16yVJ11xzjSIjI9WhQwdzAwMAoAywuVvlZrVo/cE4tfWS1kfH6fra5WVzZ/IP+C9OnjypkSNH6oMPPpAkhYaG6pVXXlFoaKiuu+46k6PD5eI7IgAAKDMSEhI0aNAgNW/eXOvXr5efn5+mT5+urVu30rAFAKA4GZLTmSXpf3+zMgJwxTIzMzV79mzVrVtXH3zwgSwWi5566imWQijhmLQFAAClnmEYWrJkiUaNGqWYmPObntx7772aMWOGqlSpYnJ0AACULfZMp3adTNSWI/FqV0/aciRe/r7e6plZmeURgMv0yy+/KCIiQjt27JAktWjRQvPnz1fz5s0lnV/bFiUTrXYAAFCqbd++Xe3atVO/fv0UExOjevXq6YcfftBHH31EwxYAABMYmU79uCdGCamZkqSE1Ez9uCdGRqbT5MiAkuP06dPq27ev2rVrpx07dig4OFhvvPGGNmzYkNOwRclWopu2r776qiwWi4YOHWp2KAAAwMUkJiZq6NChatq0qX799Vf5+PhoypQp2rZtmzp16mR2eAAAlFknk+3KMpzy8zr/5l8/L3dlGU6dTLabHBng+jIzMzV37lzVqVNHS5YskcViUf/+/bV//3498cQTLIVQipTY5RE2btyoN954Q9dee63ZoQAAABdiGIY++OADPfPMMzp9+rQk6e6779aMGTNUrVo1k6MDAABVArwU7GPTmaRUSZIjy1D5AJuqBHiZHBng2n777TdFRERo27ZtkqRmzZpp/vz5uv76602ODEWhRLbfk5OT9cADD+jNN99UuXLlzA4HAAC4iB07dqh9+/Z66KGHdPr0adWpU0fff/+9PvnkExq2AAC4CC8vdw3rUkdh/uebtJUDvTWia115eZXYuTKgSMXExOiRRx5R27ZttW3bNpUrV06vv/66oqKiaNiWYiWyaRsREaEePXqoc+fOZocCAABcQFJSkoYPH67rrrtOv/zyi7y9vfXKK69o+/bt6tKli9nhAQCAf4hLyZA906k7m55fW37OPU3UoV4Fk6MCXE9WVpYiIyNVt25dLV68WJL02GOPad++fXrqqafk5sbGfaVZifs11kcffaQtW7Zo48aNl3S+3W6X3f7/6+IkJSVJOr97XnHtoJd9H3bsyxv5KRg5yh/5KRg5yh/5KZir5sgwDH300UcaPXq0Tp48KUnq3bu3pk+frurVq0sqnphdNT+uxIwcufLXgxq1ZCBH+SM/BSNHF3I6DW34K0YnElIV4n2+JbHtRLzKB3nJarWYGldGplOe7lZT4/g3XkP5K835iYqK0qBBg7R161ZJUpMmTTR37ly1bNlS0qV/zqU5R4XBlWtUi2EYRhHHUmiOHj2q5s2b6/vvv1fjxo0lSR06dFCTJk00e/bsPJ8zfvx4TZgw4YLjS5culY+PT1GGCwAAitCRI0f0xhtvaOfOnZKkSpUq6YknnlDTpk1NjgyuIjU1VX369FFiYqICAgLMDicXalQAAJCXxMREvffee/rhhx8kSb6+vnrggQfUrVs3JmtLiUutUUtU03b58uW6/fbbc71Is7KyZLFYZLVaZbfbL3gB5zXFUK1aNZ09e7bYineHw6HVq1erS5cu8vDwKJZ7liTkp2DkKH/kp2DkKH/kp2CulKNz585p0qRJmjNnjjIzM+Xt7a3Ro0dr+PDhstlspsTkSvlxVWbkKCkpSaGhoS7ZtKVGLRnIUf7IT8HI0YWcTkNr9v7/pK315A65V2+iztdUMmXCNVc8vjbFpthVOchHnepVcImJW15D+StN+cnKytLbb7+tsWPHKj4+XpL08MMP65VXXlGFCle+fEhpylFRcOUatUQtj9CpUyft2LEj17FHHnlE9erV07PPPpvnbxxsNlueP8B5eHgU+4vVjHuWJOSnYOQof+SnYOQof+SnYGbmyDAMffLJJxo+fLhOnDgh6fxSCLNmzVLNmjVNienfeA0VrDhz5MpfC2rUkoUc5Y/8FIwc5dbqqgqKio5VYkq6vCW1CA+VzeZpSixpGVlKsjsV4u8jfy8PyeqmJLtTToubbB6uM9XIayh/JT0/f/zxhwYMGKDNmzdLkho3bqzIyEi1adOm0O5R0nNU1FyxRi1RTVt/f381bNgw1zFfX1+FhIRccBwAAJQee/bs0cCBA/Xjjz9KksLDwzVnzhz16NHD5MgAAMDlCvb1VLcGYUpJs+vH09tVzsechq0k2dytCvT20LH4VEnS2WS7qpbzkc29RO7bjhImNjZWzz33nN566y0ZhqGAgAC9/PLLevrpp+XuXqJadigCvAIAAIDLSk5O1ksvvaSZM2cqMzNTXl5eeu655zRq1Ch5eXmZHR4AALhCVqtFnv9rjDqd5q3aaLVa1DI8RIqWEtMcqlrORy3DQ1xiaQSUXk6nU2+99Zaee+45xcXFSTq/FMLUqVNVsWJFk6ODqyjxTdu1a9eaHQIAAChkhmHo888/17Bhw3Ts2DFJUq9evTR79myFh4ebHB0AAPiv4lIytOGvGEnSmr0xanVVBQX7mjNxmz35a890yuZupWGLIrVp0yYNGDBAGzdulCQ1atRIkZGRuvHGG02ODK6GeX8AAOBS9u3bp27duunuu+/WsWPHVKtWLX311Vf66quvaNgCAFAKOJ2GoqJjdSLh/JIEJxJSFRUda/rErbenGw1bFJm4uDg9/fTTuv7667Vx40b5+/tr9uzZ2rJlCw1b5ImmLQAAcAkpKSl6/vnn1ahRI61evVo2m03jxo3Trl271KtXL7PDAwAAhcSe6VRimkMhvuc3ZAzxtSkxzSF7ptPkyIDC53Q69fbbb6tOnTpasGCBDMPQgw8+qH379mnIkCGsXYuL4pUBAABMZRiGli1bpqFDh+ro0aOSpFtuuUVz5sxR7dq1TY4OAAAUtuzNv47HnVN5SbEpdlUJ9mfzL5Q6W7Zs0YABAxQVFSVJatCggSIjI9W+fXuTI0NJwHdEAABgmgMHDqh79+668847dfToUdWoUUPLly/XypUradgCAFBKWa0WtagZrPJ+5zcVrRzE5l8oXeLj4xUREaHmzZsrKipKfn5+mjFjhv78808atrhkTNoCAIBil5qaqldffVVTp05VRkaGPD09NWrUKD333HPy8fExOzwAAFCE4lIytPFwnFIyMuUrqWmNcqZtQgYUJqfTqSVLlmjUqFE6c+aMJOn+++/X9OnTVblyZZOjQ0lD0xYAABQbwzD01VdfaciQIfr7778lSd26ddPcuXN19dVXmxwdAAAoatmbkB2LT1Woz/mWxJa/43VzgA+TtijRtm7dqoiICP3++++SpPr16ysyMlIdO3Y0OTKUVCyPAAAAisXBgwfVs2dP9e7dW3///beqV6+uL774Qt9++y0NWwAAyojsTchC/Wzys51v2iaxCRlKsISEBA0ePFjNmjXT77//Ll9fX02bNk1bt26lYYv/hElbAABQpNLS0jR58mRNmTJFdrtdHh4eGjlypJ5//nn5+vqaHR4AAChG2ZuQHYtPlXzcZZUU4O3BJmQocQzD0HvvvaeRI0cqJiZGknTPPfdoxowZqlq1qsnRoTSgaQsAAIrMypUrNXjwYB06dEiS1KVLF82dO1d169Y1OTIAAFDcnE5D9kynWtQMliQlpqTLW1LzmuVYGgElyvbt2xUREaFff/1VklS3bl3NmzdPnTt3NjkylCY0bQEAQKGLjo7W0KFDtWLFCklS1apVNWvWLN15552yWPihDACAsiYuJUNR0bFKTHMowMtd11YNkq97oNadlgK9PMwOD7gkiYmJGj9+vObOnausrCz5+Pho3LhxGjZsmDw92UwPhYumLQAAKDTp6emaOnWqXn31VaWnp8vd3V0jRozQCy+8ID8/P7PDAwAAJvjn5mNeHu76YU+M1uyNUYiPmxpIWrM3Rq2uqqBgX5pecE2GYWjp0qV65plndOrUKUnSXXfdpZkzZ6patWomR4fSiqYtAAAoFN98840GDRqk6OhoSdJNN92kefPmqX79+iZHBgAAzJS9+ViIr6cOxCTLkZmp2JQMJaZY1CBYOhafqqjoWHVrEMYyCXA5O3fuVEREhNatWydJuvrqqzVv3jx17drV5MhQ2rHSNwAA+E8OHz6s3r17q0ePHoqOjlblypX18ccf64cffqBhCwAAcjYfO5lkV2xKhrIMizzc3BQW6C3p/PIIiWkO2TOdJkcK/L+kpCSNGDFCTZo00bp16+Tt7a1JkyZpx44dNGxRLJi0BQAAVyQ9PV3Tp0/XpEmTcpZCGDp0qMaNGyd/f3+zwwMAAC7CarWoZXiIDMPQiYQ0eblbFODtpTNJaVI5KTHdoWohXrK5u95cWfbmaTZ3K1PAZYRhGProo480YsQInTx5UpJ0++23a9asWapRo4bJ0aEsoWkLAAAu26pVqzRo0CD99ddfkqQOHTpo3rx5atCggcmRAQAAVxTs66mbG1ZS4+rltPVIvE4lpivGZpWypKrlfNQyPMTlmqL/3Dwt0NtDLcNDWHe3lNu9e7cGDhyon376SZJUu3ZtzZ07V927dzc5MpRFNG0BAMAlO3LkiEaNGqUvvvhCklSpUiXNmDFD9913nywW1/pBCwAAuBar1aIqQd6qFOB1fimErEx9/320OtWrIJvNtZqh/9w8LdTPpmPxqVK0WHe3lDp37pwmTpyo2bNnKzMzU15eXhozZoyeeeYZeXl5mR0eyiiatgAAoEB2u12fffaZ7r//fqWlpcnNzU1DhgzRiy++qICAALPDAwAAJYjVapG3p5scDmfOx64me/O0UD+b/L08JCln3V1vTzeTo0NhMQxDn376qYYPH67jx49Lkm677TbNmjVLtWrVMjk6lHU0bQEAQL6+//57DRw4UAcOHJAktWvXTpGRkWrYsKHJkQEAABSN7M3TjsWnSpLOJttVtZyPS667iyuzd+9eDRw4UGvWrJEkhYeHa86cOerRo4fJkQHn8d0GAADk6ejRo7r77rvVrVs3HThwQEFBQXrnnXe0du1aGrYAAKBUy948rWo5H9kznS677i4uX3JyskaPHq1rr71Wa9askc1m0/jx47Vr1y4atnApTNoCAIBcMjIyNGvWLE2cOFGpqamyWq2KiIhQq1atdPfdd7N2LQAAKBOCfT3VrUGY7JlO2dytNGxLOMMw9Pnnn2vYsGE6duyYJKlHjx6aM2eOwsPDTY4OuBCTtgAAIMeaNWvUuHFjjR49WqmpqWrTpo22bNmiGTNmyNfX1+zwAAAAilX2+rs0bEu2/fv36+abb9bdd9+tY8eOqWbNmvrqq6+0cuVKGrZwWTRtAQCAjh8/rvvuu0+dO3fW3r17VaFCBb377rv65Zdf1LhxY7PDAwAAAC5bSkqKxowZo4YNG+r777+XzWbTuHHjtHv3bvXq1cvs8IB8sTwCAABlmMPh0Guvvabx48crJSUlZymEiRMnKigoyOzwAAAAgMtmGIaWL1+uoUOH6siRI5Kk7t27a86cObrqqqtMjg64NDRtAQAoo3766ScNHDhQu3fvliS1bt1a8+fPV5MmTcwNDAAAALhCBw4c0ODBg7Vq1SpJUvXq1fXaa6/ptttuY28GlCgsjwAAQBlz4sQJ9enTRzfddJN2796t0NBQLVq0SL/++isNWwAAAJRIqampGjt2rBo2bKhVq1bJ09NTY8aM0Z49e9S7d28atihxmLQFAKCMcDgcmjt3rsaPH69z587JYrHo6aef1ssvv6xy5cqZHR4AAABw2QzD0IoVKzRixAgdPnxYktS1a1fNnTtXderUMTc44D+gaQsAQBmwbt06RUREaOfOnZKkli1bKjIyUs2aNTM5MgAAUNY4nYbsmU5ZDcPsUFDCHTx4UJMmTdKmTZskSdWqVdPs2bN1++23M1mLEo+mLQAApdipU6c0cuRIvf/++5KkkJAQTZkyRY888oisVlZJAgAAxSsuJUNR0bFKTHMowEYtgiuTlpamKVOmaPLkybLb7fLw8NCIESP0wgsvyNfX1+zwgEJB0xYAgFIoMzNTkZGRGjdunJKSkmSxWPTkk09q0qRJCg4ONjs8AABQBjmdhqKiY3UsPlWhfjadSEhV+f8dBy7VypUrNXjwYB06dEiS1LhxY73//vtq2LChyZEBhYumLQAApcyvv/6qiIgIbd++XZLUvHlzzZ8/Xy1atDA5MgAAUJbZM51KTHMo1M8mfy8PGVmeUoKU7siSzWZ2dHB1hw4d0pAhQ7RixQpJUpUqVTRt2jR5e3urbt26JkcHFD7eiwAAQClx+vRp9e3bVzfeeKO2b9+u4OBgLVy4UBs2bKBhCwAATGdztyrQ20Nnk+06mZiu9dFxkqRf/jqruJQMk6ODq0pPT9fEiRN1zTXXaMWKFXJ3d9eoUaO0d+9e3XXXXaxdi1KLSVsAAEq4zMxMLViwQC+88IISExNlsVj0+OOP65VXXlFoaKjZ4QEAAEiSrFaLWoaHyDho6LeDsbLo/LIIpxLTFBUdq24NwmS10oDD//v22281aNAgHTx4UJLUsWNHRUZGqn79+pIkh8NhZnhAkaJpCwBACfb7778rIiJCW7dulSQ1a9ZMkZGRatmypbmBAQAA5CHI20PX1wxRzDm7fD0knTymcj6eSkxzyJ7plLenm9khwgUcPnxYw4YN0/LlyyVJlStX1syZM3XPPfcwWYsyg+URAAAogWJiYvToo4+qTZs22rp1q8qVK6fXX39dUVFRNGwBAIBLikvJ0He7Tun7PacUfSZZvx44I0mKio6Vm8UimzstirLObrdr0qRJuuaaa7R8+XK5u7vrmWee0d69e3XvvffSsEWZwqQtAAAlSFZWlhYuXKgxY8YoISFBkvTYY4/p1VdfVfny5c0NDgAA4CKcTkNR0bE6Fp+qEF9PxaVmKD4lQ/KTDFkkenFl3nfffadBgwbpwIEDkqT27dsrMjJSDRo0MDkywBw0bQEAKCE2bNigiIgIbdmyRZJ03XXXKTIyUq1btzY5MgAAgPzZM51KTHMo1M8mm7ubvD3cZAvwkiS1rFVOmU6D5RHKqCNHjmjYsGH64osvJElhYWGaMWOG7r//fiZrUabx3gMAAFzc2bNn9cQTT6h169basmWLAgMDNW/ePG3cuJGGLQAAKBFs7lYFenvobLJdZ5PTdfBMsnYcT5QkrTtwVm5WlkcoazIyMjR58mTVr19fX3zxhdzc3DRs2DDt27dPffr0oWGLMo9JWwAAXFRWVpbeeustPffcc4qPj5ck9evXT1OmTFGFChVMjg4AAODSWa0WtQwPkfOgod/+OiuLLAr08pAkxaXY5XQal31N5/+mc23uVlmtNPhKkh9++EEDBw7Uvn37JEk33nijIiMj1ahRI5MjA1wHTVsAAFzQxo0bNWDAAG3atEmS1LhxY0VGRqpNmzYmRwYAAHBlgn091aFOBZ1KSJcjy6lAm5tkxKtqOR/ZM525lkcoqCEbl5KhqOhYJaY5FOjtoZbhIQr29SzuTwmX6dixYxo+fLg+/fRTSVLFihU1ffp0PfDAA0zWAv/Cew8AAHAhsbGxevLJJ9WyZUtt2rRJAQEBmjNnjjZt2kTDFgAAlHjenm6qFOSlLKcUey5dkpSV5VSIn2fO8ghxKRn6btcpfbn1uL7bdUpxKRm5rvHPTc1s7lYdi09VVHTsFU3ronhkZGRo6tSpqlevnj799FNZrVYNHjxYe/fu1YMPPkjDFsgDk7YAALgAp9Opt99+W6NHj1ZcXJwk6aGHHtLUqVMVFhZmcnQAAACFw2q1qFXtUJ0+Z9fP+05KfpKPl4fqVQqQ1WrJ1ZAN9bPpWHyqFC11axCWM3H7z03N/P+3xEJimoONzFzUjz/+qIiICO3du1eS1KZNG0VGRqpx48YmRwa4NiZtAQAw2ebNm9W6dWv1799fcXFxatiwoX7++WctWbKEhi0AACh1grw9VMHfphY1giVJVYK8tf/UuZwlEf7ZkA31s+U0ZLP9c1Ozc+kOnU22K9Dbg43MXMzx48d13333qVOnTtq7d6/Kly+vxYsXa926dTRsgUvAdzQAAEwSFxenp59+Wi1atNAff/whf39/zZo1S1u2bFG7du3MDg8AAKBI2DOdOpeeqbAAL0lSiK9nTmP2Uhqy2ZuaZa+FW7Wcj1qGh7AZmYtwOByaPn266tWrp48//lhWq1UDBw7U/v371bdvX1mttKKAS8HyCAAAFDOn06nFixfr2Wef1dmzZyVJDzzwgKZNm6ZKlSqZHB0AAEDRsrlb5WaxKCo6Vm28pKjoWLUIr5Cz6VjL8BAp+vySBxdryAb7eqpbg7B8NytD8Vu7dq0iIiK0e/duSVKrVq00f/58XXfddSZHBpQ8NG0BAChGf/75pwYMGKANGzZIkho0aKDIyEi1b9/e5MgAAACKkUUydL7Rasgi/aPneqkNWavVwhq2LuLkyZN65plntHTpUklSaGiopkyZon79+jFZC1wh/uUAAFAM4uPjNXDgQDVv3lwbNmyQn5+fpk+frj///JOGLQAAKFPsmU5lOQ21rFVOktSyVjll/W8922zZDVkmaF2bw+HQrFmzVLduXS1dulQWi0VPP/209u3bp0cffZSGLfAfMGkLAEARcjqdWrJkiUaNGqUzZ85Iku677z5Nnz5dVapUMTk6AACA4mdzt8rNatGGg3G60UvacChOLWtXYCOxEmbdunWKiIjQzp07JUnXX3+95s+fr2bNmpkcGVA60LQFAKCIbNu2TREREfrtt98kSfXr19e8efN00003mRwZAACAuVLSM3UqMU3ykk4lpiklPdPskHCJTp06pZEjR+r999+XJIWEhGjy5MlM1gKFjH9NAAAUssTERA0ZMkRNmzbVb7/9Jl9fX02dOlVbt26lYQsAAMq8tIws7Y85pyBvT0lSqK9NB84kKy0jy+TIkJ/MzEzNmTNHdevW1fvvvy+LxaInn3xS+/bt0+OPP07DFihkTNoCAFBIDMPQ+++/r5EjR+r06dOSpHvuuUczZsxQ1apVTY4OAADANcSnZOhoXJpS09OlAMmR5Sz4STDVr7/+qoiICG3fvl2S1Lx5c82fP18tWrQwOTKg9OLXIAAAXAGn01BaRpacTkOStGPHDrVr104PP/ywTp8+rbp162r16tX6+OOPadgCAAD8j9NpaPvxBAX6uMvjf2vYxqc7dG3VQHl7upkcHf7t9OnT6tevn2688UZt375d5cqV04IFC7RhwwYatkARY9IWAIDLFJeSoajoWCWmOeSRla4fPpinNxfMV1ZWlnx8fDRu3DgNGzZMnp6eZocKAADgUuyZTiWlZ6pB5QBtzTi/jq2nu1UNqwTKarWYHB2yZWZmasGCBXrhhReUmJgoSXr88cf16quvKjQ01OTogLKBpi0AAJfB6TQUFR2ro3Ep2vPrt1o08yUlxZ2RJN15552aOXOmqlevbnKUAAAArsnmbpVk6Mc9MXJmZUrlpABPdx0+m6L6YQE0bl3A+vXrNWDAAG3dulWS1LRpU0VGRqpVq1bmBgaUMTRtAQC4DPZMp3bu2qV3p4/Vrs0bJElh1Wpp4fx5urXnLSZHBwAA4NriUjO07WiiTiXZ5edxvkHr7+2hxDSH7JlOU5dIcDoN2TOdsrlby2Tz+MyZMxo9erQWLVokSQoKCtIrr7yi/v37y82NpSuA4kbTFgCAS3Tu3DmNHz9es197Tc6sLHnavHTLQwP0yFOD1PO6GmaHBwAA4NKcTkO/HTirxNQM1Qj21rm0DElSYqpDvp7u/5vCNcc/l78K9PZQy/AQBfuWjaWusrKy9MYbb+j5559XQkKCJOnRRx/V5MmTVb58eXODA8owmrYAABTAMAx9/PHHGjFihE6cOCFJuqFTd9036AVdFV5LLcNDyuQ0BgAAwOWwZzqVkpGpAB9PxSTblZHllCQF+XqqzdWhptVT2ctfHYtPVaifTcfiU6VoqVuDsFJf40VFRWnAgAHasmWLJKlJkyaKjIzUDTfcYHJkAGjaAgCQj927d2vgwIH66aefJEm1a9fW3Llz1a3bzWX67XMAAACXy+ZulZ/NTbHJdhlOp3w8zk/WNqgcoGAf86Za7ZlOJaY5FOpnk7+XhyS5xHINRens2bN67rnn9NZbb0mSAgMD9fLLL+upp56SuzutIsAVmPfeAwAAXFhycrJGjRqlxo0b66effpKXl5cmTpyonTt3qnv37rJaLfL2dCuUhq3TaSgtI0tOp1EIkQMAALimQ7EpWn8wTgdizinJnqXa5X0lSYZxvnFqFpu7VYHeHjqbbNe5dIfOJtsV6O1h6nINRSUrK0sLFy5U3bp1cxq2ffv21b59+zRw4EAatoAL4V8jAAD/YBiGPv30Uw0fPlzHjx+XJN16662aPXu2atWqVej3K8vrpwEAgLIjM9Opj/44otNJ6aoa5K2j8WnadypZbWpKf8emKMWeeVlTrYW5aZjValHL8BAp+vyEbdVyPkWy/JXZG51t3LhRAwYM0KZNmyRJ1157rSIjI9W2bdtijwVAwWjaAgDKrOzC2Wqcn3Ddu3evhg8frh9++EGSVKtWLc2ZM0c9e/YssvuX1fXTAABA2ZKUnqnY5AyFBXnJy8NNZ5PtSkzLlCT5eLpr4+G4S66BiuKX3sG+nurWIKzImqpm/qI+NjZWY8aM0RtvvCHDMBQQEKCXXnpJAwYMYLIWcGH86wQAlEn/LJw9nela+t57+uqrr+RwOGSz2fTcc89p1KhR8vb2vuC5hTUlURbXTwMAAGVTgJe7Qvw8FX0mWaF+NmU6DQV4n29JJKY5dCIh7ZJqoKL8pXf28leFzaxf1DudTi1atEijR49WbGysJOmhhx7S1KlTFRYWVmT3BVA4aNoCAEqVS2moZhfOR+NS9NcfP+rt6eMVF3NSknTLLbdozpw5ql27dp7PLcwpiez1047Fp0qSzibbVbWcT6lcPw0AAJRt7u5W3Xd9dX30xxHFnEuXt7ub/LzO1zzH41Pl5u4uj0toYJbEX3pnxxzs6ylPd6uCfT2LPObNmzcrIiJCUVFRkqSGDRsqMjJS7dq1K5L7ASh8NG0BAKXGpTZU7ZlO7d23T0tmvKitG9ZJkipUqKA5cyN1z913ymLJv9lbWFMS2eunGQcNnU3OUJUg7yJZPw0AAMAV1C7vp2e71dO+0+f01rq/FJOULkkK9bcpLMBLDqdRYJOiJP7S2+ZulZvFot//Ois3q0VZTkOtwkOLJOa4uDi98MILWrBggQzDkL+/vyZMmKCBAwfKw8Oj0O8HoOjQtAUAlAqX2lBNTU3Vyy+/rGnTZyjTkSF3D0/dfP/jeqhHe912260XbdhKlzbZcSVLJxj/+rugz9PMDSwAAAD+C6vVop0nE3UiyS6HI0uSlJSWqbBAr0tqYhbXpmGFziIZskgWy/mar5DDdTqdWrx4sZ599lmdPXtWktSnTx9NmzZNlStXLtybASgWJapp++qrr+qLL77Q3r175e3trRtuuEFTpkxR3bp1zQ4NAGCyghqqhmHoyy+/1JAhQ3TkyBFJUrM2HfXgsPGqc1W4HIc3F1jsFzTZcblLJ2Q3mk8kpCnUz6YTCWmKio696OSumRtYAAAAFIaU9ExtORwvHw83JWQ4JEl/n01VjWCfS268FvWmYYXNnulUltNQ26tC5OXhrnRHpjKyjEJbHuHPP/9URESE1q9fL0m65pprFBkZqQ4dOvznawMwj+u+fyAPP//8syIiIrRhwwatXr1amZmZ6tq1q1JSUswODQBgsuyG6tlku86lO3Q22a5Abw/Z3K3666+/1KNHD91+++06cuSIqlevrmXLlmn9T6v1cLdW6lin/CXdI3uyo2o5H9kznbkmO/456Wtzt+pYfKqiomPldF58fvbfjeZQP1tOo/nfruT6AAAAriQuJUNr9sbo0NkUHYlLlfv/mq02D4sOxCRfVl2TvWlYYTRsnU5DaRlZRVZXZdepsSkZsmdmKTYlI6dO/S8SEhI0aNAgNW/eXOvXr5efn5+mT5+urVu30rAFSoESNWm7atWqXB+/8847qlChgjZv3sxi2gBQSl3qcgB5vVWuQQUvjRk7VjOnT1NGRoY8PT01cuRIPf/880o33PXD3hglpjkUYLv0gvlikx1XsinG5azJVhI33QAAAMiW/Qvo0+fSVT3YR8fiU5X8v5KnTkV/pTmyTKlriuOdTIW9pIPT6dR7772nkSNH6syZM5Kke++9VzNmzFCVKlUKM3QAJipRTdt/S0xMlCQFBwdf9By73S673Z7zcVJSkiTJ4XDI4XAUbYD/k32f4rpfSUN+CkaO8kd+ClZScxSfmqFNh+OVlOZQgLeHmtcsp3I+Fy+i/T0tuqlOiDIynfriy6/0yMhndPrEUUlSh5s6ad6c11SnTh05nYY27I3RiYRUhfjadDL+nEIlZWRkXHJs7hYpK8uprPNLsclqGAqwWXUiIVVy2hSbYlflIB9ZjSw5HBdOzmZrVj1AhjNLSWkOVQm0qVn1AGVlZeZcN9uVXr+wlNTXUHEhPwUzI0eu/PWgRi0ZyFH+yE/ByNH/S8/IUmJKuir4uiu0VpBik1KUlHo+L2EBHgrycvvPdY3TaSgj0ynPS1wywek0tOGv/68Jj8ed0wZnljrVq1DoSy78s07Nju9SXhf/fg1t27ZNQ4YM0e+//y5Jqlu3rl577TXddNNNuc4rK/g3VjBylD9XrlEthmGUyPdVGoah2267TfHx8frll18uet748eM1YcKEC44vXbpUPj4+RRkiAMAEp06d0ltvvaVNmzZJkkJCQvTYY4+pdevW+W4yBqD0SU1NVZ8+fZSYmKiAgACzw8mFGhUAcDlSUlL04Ycf6ptvvpHT6ZSXl5fuuece9erVSx4eHmaHB+AyXGqNWmKbthEREfr666/166+/qmrVqhc9L68phmrVquns2bPFVrw7HA6tXr1aXbp04ZtpHshPwchR/shPwUpijtIzsvT1jpOyuVvlZ3NXsj1T9kynejSqJK883jaXlpam6dOna+rUqbLb7XJz99BtDzyuvk8PU5abZ67nOp2G1vxj0jYuOVWhifvVuXNneXp6XvaE7z9d7oTH5Srq619MSXwNFSfyUzAzcpSUlKTQ0FCXbNpSo5YM5Ch/5Kdg5Ci32OQMvfNbtE4kpKm8v5cCbBbVskerQ4dO8vGxXfF1/13bZb8jqaCJ2St9XnHKyMjQmDFj9OGHHyomJkaSdOedd2rq1KmqVq2aydGZj39jBSNH+XPlGrVELo8waNAgffXVV1q3bl2+DVtJstlsstku/Obv4eFR7C9WM+5ZkpCfgpGj/JGfgpWkHLm5uSvQ1+v8eq9WN51NzVTVcj7y9bZdUER//fXXGjx4sKKjoyVJnTp11j2Dx8oSVEVZHractWL/+dxWV1XIWb+sUjl/ORIlT09Pubm5a/ORszqeaFeon03HE+2yHElStwZhl1y85/G/nUJV1NfPT0l6DZmB/BSsOHPkyl8LatSShRzlj/wUjBydF+hrVY3yAQqvECh3d6t2HomTLNKPB2LVvn6lK15LNi0jS0l2p0L8fc6v/W91U5LdKafFTTaP/NfI/WdNWCXYXy3DQ2SzFe6atldqx44dGjBggH799VdJUp06dTRv3jx16dLF5MhcD//GCkaO8ueKNWqJatoahqFBgwZp2bJlWrt2rWrVqmV2SACAInIpGzYcOnRIQ4cO1VdffSVJqlKlimbNmqW77rpL8amOnAI8r+f+c0Mxq5GlVYfPH2fDr8t3qZvFAQCAss3mblU5H08diUvV4TMp2ncyQU2qS7//dUaZhlV3Nqsqq9Vy2bXF5Wzumi37HkHeHnluMmumpKQkjR8/XnPmzFFWVpY8PT01duxYjRw5Ms9f+AEonUpU0zYiIkJLly7Vl19+KX9/f506dUqSFBgYKG9vb5OjAwAUtn82Vv9ZRKenp2vatGn6P/bePEyuszzTv89+au2q6r3Vrd2yJG/ybmMbbAwYzD5kEpKQX/aFwZABApMQICFkyEBYQoghITMZskIgJEwAGwxesMG7bHnVLrV6X2rfzn7O74/TXe5udUvdUktu4XNfly5b6lOn6lTX8nzP977P+4lPfALTNJFlmfe+97189KMfJZlMnvC2cxFFgZgqzRt4sZjo78vE8P0A3w/WhJBfS5yNicsRERERERERPx2IosCVG3NUTYfD+TrqjCPh+AF7RsrcelEvluevWFssZ7N/LmtVvwRBwFe/+lXe//73t/yOt7zlLbz+9a/nl3/5l6MqyYiIlxhLbzutQb70pS9RqVS48cYb6e3tbf3513/91xf7oUVEREREnCFmjdVZ0X3nnXdy4YUX8tGPfhTTNLnpppt46qmn+NSnPtUybJe67UJ8P8CwPXw/mHebqze305+Nz1RfqDRtj28/Pcb3n5ug2LBP+VoWu7+V/Hyt4fsBjxwpMFJqoskiI6UmjxwpnDOPPyIiIiIiIuLsUmzYPDZYpGG5eH6ANbNxPlkxsBzvtLTF7Ib9m3et45YLepY0Ydeqfnnuuee46aab+MVf/EUmJibYunUrd955J1//+tfp7Ox8UR9bRETEi8M5VWl7js5Mi4iIiIhYBY4dO8Z//+//nW9961sA9Pb28tnPfpaf+7mfQxBWXv06t8Iirc3fw5wV/Ybt8aMDU4yWDTqSWlh9e4QV5dsudn+LVXSs1YqPE7EwSsIPAqZrFobtkdDPKYkRERERERERcYaZa5YqksB0zaTaMGEDjFUsBjpCbTVXWwQr1BazG/YnYq1FYdVqNT72sY/x+c9/Htd1icVi/OEf/iG/93u/h6ZpOI5z1h9TRETE2uCcqrSNiIiIiHjpYVkWn/jEJ9ixYwff+ta3kCSJ97///ezfv5+3v/3tp2TYLqywGCs3W/8+iygKiKJA1XRbor4jqbVE/enc38KKjhP9fC1X385GSeTrFuMVgwcP5dk/WeNHB6ZOqyI5IiIiIiIi4qePWbM0l1A5ONWgYjrYM/qmbjmUmhbAHG1h8uNDBfZP1rhvFbXFXP1SMx3ydYu2mHLC/NszQRAE/Ou//ivbt2/nM5/5DK7r8pa3vIXnn3+eP/zDP4yyayMiIs6tStuIiIiIiJcWd911F7fddhsHDx4E4BWveAV/9Vd/xYUXXnha5z2uwsLXoAy26zNXH5/KUItZ5g7QOFlFx1I/n6iYPDVSXrPVt7NREv7hgAcPFwgQ2N6TZrRs8MiRwilVJEdERERERET89DG7EZ3SZQbzdQ5MVGlaHsqMpDJdn8PTdfwg4OrN7QSHA35yuIBAwPaeFGOrqC1Wkn97poat7t27l9tuu4177rkHgC1btvCXf/mX3Hrrrat2HxEREec+kWkbEREREfGispgYHhoa4n3vex/f/OY3Aejp6eHTn/40v/ALv3BKlbULWWjGFhoWnYC6wIxd6VCLWRZGHVy5KXdC83f28QwXG9iuT8WwWZeNs2e4tCrRDGeSXELlxm1dFOo2SU0iHVOpmc6L2mYYERERERERsXaYq4skUSCtqzh+gCgIiEJYaSsCnhdqwq42nVds6yJft0loEm1nQFssZ2DtqUZXzdW2wLz7qNfrfPzjH+ezn/0sruui6zof+tCH+MAHPoCu66d9XRERET9dRKZtRERERMSLxkIxfGl/iq/8zV/x8Y9/nGaziSRJvPvd7+aP//iPaWtrW7X7XWjG9mXiOGUWFewnE/ULTee5UQctsxW4cmMOWNz8FUWBbT0pnhgqsW+iTntS5brzOnlmpLJm8tZOREyV6EyF1yoIwooqkiMiIiIiIiJ+elmoi/J1i942nZu2d3BoqkbghcfpikhvJkZMCTXOXG0hniFtcaL820X13DI2z+cZ1IIAAnh+QFqXmXzqR3zkDz7A6OgoAG984xv5i7/4CzZv3rxq1xQREfHTRWTaRkRERESsKsttI1sohu/6wQ/4rS/8CSODhwG4/vrruf3227n44ovPyOOca8aKgcf3Bpc+dilRv1gFRkyRFo06SGjykuav7wccmKjRkdTY2pmkbDgM5hukdZnRsgGsLJrhbHOqFckRERERERERP90sFgFVNV00USapSFS80LX1A7hsQ7Y1bGwxbXHlptxpRxUsV6eeyrCyudo2l1B58FCeAIFNcpk/+bMPs3f3TwDYtGkTn//853njG994StcQERHx0iEybSMiIiIiVo3FTMxMTFlUHM+KYRpFPv9nf8qPvvefAHR1dfHpT3+ad7zjHasShXAiZs1Yx1nZYDFYugLj1Tu6l4xCWMr8nX0uulIaSS38aq4YDjdu60IQhHPCCF1Om2FERERERETES4vF5gO0JzSemCogSwJJOdQLsiBQqtv4ftDSEHO1RcNyeexo8bRy/lcSd3Aqcw3mGr2qLOLZJg//x//mC9/+R1zXQVE1fu8DH+Ajf/ghYrHYih57RETES5PItI2IiIiIWBUWVhcczdepmg5JTaZmuseJY8F3+cHX/pZ//uvPYhlNBFHkjW//Vf7vF/6cXC77Il/NyVmqAsPxgxVVnc4dzHFoqk6pYTNVs1iXjfGaC8Rzygg9UZthRERERERExEuPhRWzmbhK3XLYM1JhrGKjS2GmrSBAseFQNV1ySXXe7TVZ5L79xRVHFcxlpXEHy+kiWli1O3dGwcFH7+HvPvlH1AoTAFx4zY289yOf4Fdee82a13MRERFrh8i0jYiIiIhYFWZNTF2RODTVIF83eehwkUsG2tjSmZwnju+7715uu+029u7dC8C2iy/n3R/+M37h1le0TF3fDzDssGUupkorErgrmfRrmi5DxcaKr/dEFRgxVVqW2Tq34kMQwnMU6hZdaZ2kJvHY0SK3XNDzkjJCz9SU5oiIiIiIiIgXh9mKWcP2+M7TY+w+VmSyYuIDM5G2lE2PsmGRPEFH0unk/J/KOU7URbRU1W6HX+QjH7qN3Q/eB0Bnbz//33v/iFfecivXbOmItE1ERMSKiEzbiIiIiIhVQZNFUrrMPXsncbwA1w+oWy41M8xzBTh6bJi3/+l7+cbX/xWAzs5OPvnJT/GzP/+LxFS5JWSnqiZ3PD3O/skqoiiyqz/DzTu7l9UGt5LWt/v2TfGZu/bTtGzesw1+fGCamy7oW/Y1X9KfIQgCqqa76HCxEy0kFlZ8jFVMPD/ghvM6aU9qNCy3tZjQZHHVjcy1aI6e6pTmiIiIiIiIiLXNrNZ4erRC3fTwgmDezwOgYYa6R12gn04lqmAhp3qOxfTcYlW75nNNHv9/f8enP/1pbNtGVVU+8IEP8Pu//wdIqr6m9FZERMS5Q2TaRkRERESsCqIosGt9lgcPF5A8n1xcJa3JTFRMJst1vv0vf8d3vvKXGM0Goijyzne+k49//ONks/OjEA5N1fjEHXvZP1FDk0U25JKYdp64JvG6C3sXFbyzBqQiCstqffP9gErT5jN37WesbNCVDCsuvnDPIa7d0oWuy4uef1ZwzzUXU7rMDds66U3rKxLjCys+eoOAsbJBqWmjK1JrMdGwXe7bf3oZbgtZDXN0tU3fU53SHBEREREREXFuIUsCrj/ftBUARZawXJ8Ux+uM0x14uppDU+dquKQm88i93+NDn/kY+fERAG655Ra+8IUvcN5556343BERERFziUzbiIiIiIhVozetc92Wdo4WmqQ0iZFSkyPPPsa/f/iz5IcPA3DNNddw++23c9lllx13e9f1+T8PHGXvWBXH8zFtj3G5SXsyTaFuY9heKzNsVmTPNSBjM2bniVrfZo8/OFljtGzQFlPIxGeONR1GqyZb9GTrMS00OK/cmOOxwRdy1cbKBqIg0HtBz4qeq4UVH4WGza6BDHFVojZTuXvlxhyPHS3Oywn2g2BJ83o5zDVH2xMqR/INgiDgtSs455moiF2N1seIiIiIiIiItUtMldg1kOHe/VMsKLQFYEtXkkxcWVJnnG7O/2oNTZ3VcE888zz//sVP8MRP7gFg/fr1/MVf/AVvectbzvgw3YiIiJcGkWkbEREREbFqiKLANVs6CMhz12P7uPsrn2Hfj+8AIJ3N8ZlPfYpf+7VfRRTDVrSFVRTlpsPh6TqaLBIApu0xVTVpdibRFJH7DkzNG2qWiSnzqjMnqwbTdbtVvbGw9W2uYdmZVlFlkem6hT7jCbbpCuvSeut6XNfngQPTTFRNulJh9aft+jRs97TNxaUqPjIxZV4kwtyc4ELdZLRsculAlr7sqU0dfuGcMgen6hQaNmNlg0vWZ1mXOfk5z1RF7Gq0PkZERERERESsXURR4OYd3TRMh3v3TuH4futnEvDKHd2IJ+maOt2N3NU4h2WZ3PPPf8VffPbTuI6NLCu8+7+/j4//8UdIJBKnde4TMTvvIYpaiIh46RCZthERERERq9rqntZEnvneV/nyx/4Ys1lHEAQufvXP8PK338Zr33QFINAwXUpNm6dGyvNMWE0W0WQJTRZRZRHT8VAlias2ZhERGCsb8wT8y8/rnFedGQQBng/dKR3T9ea1vvl+QLnpUGrarePfeHEv331mHNMNx2C8+5VbW9EIxYbNAwem+dGBadK6TFdapyOp0bBdEqrMVM0ETs9cnDuYA14YuDa7mFiYEwwBrg97hkv0tK0sjmEWTRZJ6zI/3DuF63mAgCf57BkqLSviwT5DFbGr2bYYERERERERsXbxgwBvjmELoMmhPjRsb0133nz729/mPe95D4ODgwDcfPOr+MIXvsCOHdvP+H3fvW+KquWftMtpLc4tiIiIODUi0zYiIiLiJc5qtro/8MAD/M47/xvPP/csALmNO3nZL30QrXcrw0346wcOs7k9waHpOkOlJhk9vL9ZE/bVO7q5eUcXdz47jusFpGIyr97Zw9suHeC7z44fJ+CBVnVm3fJ4cqhETJXoz8W4YfMLObOz11hq2hzNN0hqMutzcbrSOh947fns7Eyyb/f9XL+tE3ihmnSyapCOyQwXw+rPnjad3rYY125tZ/dgadnm4onEc9lwlnz+F+YEtydU+jJxCjWL58Yq9KdjtCXVFWe67RrI8pPDBRwX2pM6fRmdmukua0GknsGK2NVqW4yIiIiIiIhYe/h+wMOH8zw5VEZVRGzrBeM2FVepWy7AinXGapiUJzvHkSNH+N3f/V2+853vANDf38/nPvc53va2t53xKAR/poNsrNykPRU/YZdTNNQ1IuKni8i0jYiIiHgJs1qt7hMTE3zwgx/kH//xHwFIpDO87bc/QLn/ZdRtiIsC63Mxnh2psH+8QmcqRrXpYNoeoyWD87qTVAwHxw940651dCRVJioWPW0aL9vaSUKXFxXwMVXi6s3tBIcDfnK4gEDA9p4UExWTp4fL9F7Qc9w1JjWJuuViOC9U4qZUgX1zrmc2QqAzpdOZCuMSpmsWoiCgSCK7B0tcviGLLIZVq6IoLNmudiLxvJznf25OcG9a45GjRX58cBrD8YgpMm+9dB2/dsPmFQnynjadl21p51ihQXdap9gIq48XWxC5rk/VdIlJ4YJhYUXsukyMS/ozy77vk7EabYsQVZlERERERESsNSzXJ1+3kSRQJRF4wbR1/YC2mNLSdsvtvFkNk/JE5zAMg0996lP82Z/9GZZlIcsy73//+/nwhz9MMpk8yZlXB9sNn6f2xImrj6OhrhERP31Epm1ERETES5iVDn9aaIS5rssXv/hFPvKRj1CtVhEEgVe++ef5/979+wR6kq8+MsR03UAUIa0raIqI6/m0J1Us12O6ZjFds0jHZDZ1JNFkkZgqcetFfccZbksJ+ExM4aqN7UzVLFK6TFtMpWY6reuYvabZa1yfS2A4Hq+9oJdMXEEUBRzHmXedc/NVO5IaPWkdAehOq+QSKgcmqzwxVGJTRwJFFEEAb2axcTJT1j8ccOO2LmKqtKznfzYnWBAK5KsmDx7KU27aaIpMuWnzb0+MsK0rxRt29S1bkIuiwLVbOhAF4YQLosPTdb726BCFuk1nQmLnzL/PVsSOV032DJW4/+D0mqrmiKpMIiIiIiIi1h6KKJDWZWzHo2a6835m2x67BjKIorDszpvTNSlnM2IfOpw/LoLrlgt6uPPOO3jPe97DkSNHAHjlK1/JX/3VX7Fjx47TfzJWgDqzqV5oWCBKS1YfR0NdIyJ++ohM24iIiIiXMLP5pkcLTXqDgELDXrIFbaER5k/s4w9+77088/RTAFxxxRV84Qt/RSmxnqFCnYf2TWG6HglVptSwUUSB9e1xyk2HctNGlsKKSk0RGcjFuXgg07qvxaotF8t/nRt7MFo2SGoSoiAcJ2YXq9KdNWwXY2E1aW9bDEUSySVUEppMqekwVbXY2B7nx4enEQWBG7Z2HLdYWCie65bLg4cLoQma0rhyY25ZLYCz1753vIp3/2FimkJKkzFkEdv1GSw1VizIT7Ygcl2frz06xJHpOt1tOoP5Bjuz4b8r4TqAp4fLiy5yXsxqjrVWZRJV/EZEREREvBRZ+P03q9kKDRs/EJjZV2dW8UiSgCy9oH+W03lzOibl7OOZrlnsn6yxvSfVOsehw0f44h/+Dt/59n8C0NfXx+c+9zn+63/9r2c8CmExZvVDXyZO1fKX3GyPhrpGRPz0EZm2ERERES9hyoZDw/IYKxuMlQ12DWTmDe6yXB9lpvX/vn1TjFdM4l6Nz33k4zx6138AkExn+NjH/5TffdfvIEmhkVo3XSqGS086hiIJjFYMGpbHResyJFSZg9N1IJwSfFFvG4OFBg8cOL5ac6Hgn5v/mtZlGpZH2bBnYg/k42IPIBT0V27MASsbcDXX1FREgR/snWSk1MR2faaqJmld4ch0g5GigSqLuD50JLV5i4VZ8TxcbGA6Hk8eK4IgktSklqC+ctPyHpsoCmxpT5CLqwwWGuFz43ikYgobs4lTEuQnWhBVTZdC3aa7TScX15BmWhhrlksspi17oXS2Tcu1VGUSVfxGRERERLwUWfj9d+WmHI8dLTJSauJ4Hs+OVQhmjp39ryKIpNSV2ROnalLO3eBtT6gYtseeoRLygMO//t2XuPOfvoRtmciyzO/+7u/ywT/4MB3ZthfFsJ3Lzdu78AVpSU0VDXWNiPjpIzJtIyIiIl6izArWsmFz2foMk1WTuCqRiSktsX1sus7zUzUMy+XIVJ3C499h/3f/N2ajBsBNb/o53vBr72PL+nUEQSgIcwmVN1/Sx/PjVR4bLKJIoEkisZhEX1bnjReta8UWaLLID/ZOMrpItebCAV1zBX9HUuNooclY2eCy9ZmZ2IP4vNiDsuHw/ecmWre/fGMWWQgri+VlGpxzTc1ZEVxq2vRlYkxUTBqWi0BAzXR5brRCXzbG+twLiwVRFNjWk2L3UIk9wxVqpsN1WztJx1SEmWiChCove/iWrsv83i3b+eSde5mqW2TiKm+9dB3Xn9+56oI8rcu0J1WOzBjshYoJWUhpoXRYzkLpxTAt10qVyVqr+I2IiIiIiDgbLPb9Z7s+DdtFlQT+35MTTNfs1vGzpm0mIdNwPLIruK9TNSkXbvBeuj7Ld++4g3/+vU8xOTIIwI033sj//NTnqOjd3HO4SlvMeNE3X0VRQFNOvAF9qkNdV3OT3TRdRqsm69I6uh5ZThERp0P0DoqIiIh4ibJQsIqCQM10MWyPR44UuHffJD/cO0XVdDBH9lL8wV9jTBwGINm3lbe866O89ZabeHq0zI8OTOMHAVdtbqc3raOqEm+6pJenRko4jocmS3SlNB4fLHP1xg76sjEADNujYjjkEiqqHMYPVAyn9RgWE/yzj7c3CBgrG0xWzXmRCJl4WF059/ZzM2izcfU40T07lXf2v3P/fVbAzhXBhbrFl350GMfzubA/g+n41CyXnrQ+b7Hg+wFPHCtRqJnIooDp+jw7WqYzpVKcE0WxkuFbN27v4pqNOYYrBh0xlbakekZMQFkWeftV61uZths7EuDRMrxPtlB6sUzLtVJlspYqfiMiIiIiIlaLk5l7i33/NWyXmCJx7/4phopNbC847na+H7BnuERfJrai7+xTMSnnbvBOjY/wN5/8I5584C4Aent7+cxnPsPP/uzPcdfzk+fk5utKh7qu5ib7ffum+Mxd+ykbDpmYwvtfcz43bu86pXNFREREpm1ERETES5alKhJ9P2CsZPDjQ3nKxQL5e/8vtad/AICkJ9n4ml9l3bVvIt6X4anhIseKBt0pjfsPTPP4sRLXbWnH8wO+fP8RRkoNPC9gW08KVRLD9rPhEj1tOhAKdAF48FAeSRTw/IBrNncALCr4E6rMVM0EoNCw2TWQIa5K1Ex3njk3awZ3JLV5GbRbO5PHie5iw+bhQ1MA3L1viqs2d5LQZBq2y2NHi8cJ2Jgq0ZeJcd2W9jALOK2Rr1t0p2O8/qLeeVW8s+bzcMlAVyQczyNft497vCutbtB1mfP01Oq8EE7Als4k/+OW7VRNl5gUcNddR+b9/EQLpRczPuFUq0xWk7VS8RsREREREbFaLMfcW+r7b0d3iq8+egzX8zjesoWq5TJVs1a8uXkqOkIUBXatS/Kvf/uXfPXLf4FtmUiSxO/+7u/yR3/0RySTKcpNh1LTXvXN17WWdb+am+ym6fKZu/YzVjbIJFTGygafuWs/12zMRRW3ERGnSPTOiYiIiHiJslhF4raeFPcfmubRwSkO3/8f5O/7B3wzbI9PXPQqtr7u19m8fh1bOhJYns/To1U0SWSyZqPJIooscnCyzr/tHqZuOqRiKpNVk0P5BpcOtLG+I03ZcDiab7B/okrZcNg3XsVyfeKaHIp4YWnBf+XGHI8NFudVUGZiynHid+7tZzNou1J6q6J3VnRrssgjRwqMlhp0AQcnqzwxUqWvTWesbJDSZdbnEscJWFEUuGZLB4IQLlwGcgmu3tx+XOyC7wdMVi2aVmg4245PShO49cJeOlLavMEcazX3VJZFckkVx3EW/flS1RwvVnzC3MXQi1nRulYqfiMiIiIiIlaD5Zp7S+nL7z03wWC+ibvE+Yt1B8fzVrS5eao64q677uK2227j4MGDALz85S/n9ttvZ+fOC5iomPz42XGKTZsjUw3SMYUN7fFV2Xxdbd2zGgbwanYGjVbNsMI2oZKNh9dVNhxGqyZb9OQpPb6IiJc6kWkbERER8RIml1B59Y5uqqZLUpX44b5JvnHnvfz7Fz5GbTQUskrXJnKv/m/o/TtoAq7jUGg42J6PHwSYnke15hJXRDZ1xHF8n3zDJq6IKJJASpexvIBcQqdQNyg3HZ4ZKWO6Ptt70kzXLLpSOlduymG7HrYXCtBL+jMEQUB1TlXqbAVlw3SxXJ+0Ji9qGs5dMJSaNuuy8dagsrmi23J9RkpNhksmXSI8OVSm2HTZ1JlkqNjk/J4UO3rbgOMF7HKqOUVRoCutYdgunh8QV2W60jqJmce9VnNPV2MR8GLEJ6w1A3wtVPxGRERERESsBisx9xYOc73zuXHu2TeFQIAQgADHVdsKIgT+8h/PqeiI4eFh3vve9/LNb34TgO7ubj796U/zi7/4i5SaDnc+O86DhwtUDJuUqjBdtwBIaPJpb76utu5ZLc2zmp1B69I6mZjCWNkAoNwI50CsS+srPldERERIZNpGREREvISZK/jKpQK3f/LjPHvftyAIELUEbTe8g9SltyKKEgFgAwfzBuM1F12T2dmToli3qbs2qiSQ0GTuP5CHIBzO5SNgOx65hIqHz7OjNbzAp2562J5HoW4hIDBSbrK1kaLpuOQSKvcdmKJmuqR0mRu2ddKd1HD8AN8PODJd518eGQpb1lIab79qPVs6w9173w8wbA+ATExpLRgaljuvQvfKTblw8WHaPHKkyGSlweUb4Ui+gSTJZHWZUVFg/0SNS/oz1C13noBdbjVnTJW4ZlM7ge+3VijXbGpv3WYt5p4WGzYPH86Tr9t0JFWu2dJxysbnasQnLJe1aoCvNFcuIiIiIiJiLbJSc2/2+8+wPSYrFq7nkYqr+AHUTAfTm398XyZOXJeXrQNWoiNs2+Zzn/scf/Inf0Kz2UQURd797nfzsY99jLa2tpaGOFZoYLseExWTghTm+ZcbFpmYwqt3dC97kO3pPt6TcTLNs5LN99XoDGrdnyrx/tec38q07cvEeP9rzo+iESIiToPo3RMRERHxEmVW8A0V6jz5g2/y93/5vzDrFQBSF91M2yt+BSkRzvCdWw3h+lC1HCzH5fFjLpIoIASEA78mahi2y8X9GfaOV2laDpoiccsF3SQ0FUUW6Yyp7C4WqVsuqgiCKGI0fB4fKtCZ0tFkkVLDoi2mMlpqUjddNFmi6biIosAdT40zVTfpTGjkGzZfe3QozF21XO7eO8me4TIAu/oz3Lyzu5VDO8/APVqk1LQ5OFnD9jw6kqEpaTkuogdHS2E0gjMjQucK2GLD5qHDeQp1m/akyrUnMDVFUeDmnd3ENWne8YvFOMCLn3vq+wF3753kocMFZEnA9QIatsfbLus/5XOeTnzCSlhqMWTYXjhtOap0jYiIiIiIOGVO1dzTZJGEJlExXKbrFspMzJTsB7hzBOa6NpX2hLZsHbBcHXH33Xfzrne9i/379wNw3XXXcfvtt3PJJZe0jpnVEN1pnVLTwfZqSAKYjkdXWqdhhx1ep2ParqbuOZEBbDjeiitwT6czaLHN/m/81rWMVk3WpfXIsI2IOE2id1BERETESxTL9dm9+3G+8ucf4fDzTwGQG9hK9ubfwu3euehthJk/jguiFOALHoEPkiQwXTE4PFnDI0AWJTJxhQCZa7d0kE2oHJys0ZXUmG5YOD6Yrk/V8mlPyHQkRHZ0p3E8l2dGK6Q0iZGSieW6HCs0aYup9KR1xisGRwt1+jIxfAJEH/I1i7Lh8OjRAg8dLuB6HiDw8JE8cU3idRf2tnJoNVnkvv1FhopNYorESKmJgEBmJndLU2QkSabYsIirMm+5dB1vungdMVVCFAVc1+fOZ8Z5fLCIIoWD05qWx9su719S4OYSKq+7sHdRIbzWck/DQXFlXM8jm9CZrprsGS5z64W9yEK4svL9xcaHrJzVvvbFFkOZ+AtV22shLiEiIiIiIuJc5lTNPVkS2dieoGG61CwXxwsIAphrVxZrDhs7EisaJnYiHTEyMsL73/9+vv71rwPQ1dXFn//5n/NLv/RLCML8+5irIQayMZ4ekXBcH0USKdQtXB9+dGDqtLqPVlP3LGUAK6LAfafYdXQqnUEn2uzf0hVl2EZErAaRaRsR8SKw1qaGRpw51urvulgs8v4P/j5//3f/myAIUGMJLnvrb9N7zRsoND2OlaxFbxcA9kzemOdDTBTQNIkgCJiq2xiOjyQKiPiUjIDOpMb27hQxVWa0bJLUJQYLYbVCJq7Sl9EZL5uIQsC9+6fRFYG65ZKKqfS2aTwzUqFpe2xqT1C1XKqmg65INCyXpK6Qb1hs6kwgAWNlE0mEbEKHQKBm2hTq9ry2M8v1GSsbDOYbjJYNRstNTMenL6VAHPqzMbb2tFE3PXRF5Iatna3fW7Fh86P9U/znU6N4fsC2njSm4bBnpMytF/WS0OVFf98new2sdu7p6rzmBAhmLXooGjbPDBUBuHvfFNds7VoV83M1r33hYmhdJkbD8hgrG2sqLiEiIiIiIuJcZqXmnuX6VA2HVExGVyUqpo2zSHbtdMPk4GSVHT3pZX9PL6YjbNvm85//PB/72MdoNBqIosi73vUu/uRP/oRMJrPkNc3VEP/lsn5sx2fvRBVVltnek2a0bPDIkcJp6YjV0j1LGcCOH5zV2K0TbfYnogrbiIhVIXonRUScZdbaoJyIM8eJftcvlpnr+z5/+7f/m9//g9+nWCgAcPEr3sAlP3MbtprCsFxM1znhOQRAYWZgBOGuegA4foAogusHrcgEw/b42uPD9Gdi9Gfj9LbFGCubvGxrOwlVpmY5HBivIYiQ0BSGixaiJLGjR6NquViOjx+EWbPrsnEsN2AgG8PzA6aqFqokEldlbr//MKWGzXCpSUqV0RQRXRZpT6rz2s4UUWCiavLMaAVZhKbl4Xg+ihgK246EysXr2pis2XSkVJ4aKbeydZu2x1TVQBQEapbDZNkgPkcAL/b7Bpb1fl/OAmg5r5nT/XyJqRK7+jM8fCRPzbRRJIFL1rXx9HCZ8XKTTmCs3DztRctcVjPzde5iyPcDvv302JrKC46IiIiIiHipoYgCYxWDxwdL1C2HpRp2KqbHs6NVbrng5N/TCzXR7PH33nsv73rXu9i7dy8A1157LV/84he5+OJLWtrgRJ1Rcw1Vw/b45hMjJDWJdEylZjqroiNOpnuWu0ZYzAD2/eBFit2av9kfERGxekSmbUTEWWStDsqJWH1O9LsuG86LYtwfPnyYl11/A088/hgAHQNb+JUPfJzrrr+BY4UG//HECLbrU2me2LQNABfQBHA8D0WSEQFZDDBtkMTw+hVZIADGik2EALZ2JcnEFV6+rZOpmkVnUuW5sSqSJGI6HiMlg4QmoYowXrEYzDcoGDZJVcZyPY7k6+zoSXHxQAbH8zk0UScTV6haLsPFJmldwbQ9hvJNkprExf0Zzu9JzXtvOX5ALq6Sjsn4PiR1n7gqsqEjAZRoS2g0bZ9N7fF5VZrHCg1GyyaXDrRxfk+KZ0crVEyHpC6zayCDJovcf3Ca4WKDtpjKcLGBHwQIwOicSk//cMCN27pacQvLZTlmrO8HPHQ4z7FCg+60zlCxie36vP6i3mVnsC2WwXvpQJb7D07TntCgDO0JbU2bn7OLoRdv4RIRERERERExi+MHZHQFSTyxqecG8PjRPCdTFnM1UUqX2bU+S1Av8sEPfoCvfvWrAHR0dPCpT32KX/7lX6ZsuHz/uYll6e65hmpMlehMhfpNEISzoiOWu/m+1EDcsx27tdhm/67+zJrUh3NZq52QERGLEZm2ERFnkbU4KT7izHCioUhn27gvFot8+ctf5kMf+tBMFEKcl/3M7+Bsv4V7y7D77oMYtkfVdICgFX9wInzAckFXAtp0GcsLqJguohRmlAki6IqIDOi6guH47B2vk4tr3LCtE0USqJouhutiOh5Nx0OTRVwjjE04kq9TajpIIsiiiCQKqJJIb1onpcns6G0L/10QKI9V6U7rjJQMJBEycQVVFjiUr/PVR4d4541b6Uhq+H6A7wcM5GJkYgrjZQPLcTFtcDtiAOzqb+M1F6xDFIV5VZp+EDBaNpms2WzpTFJt2iiyxA3ndfCyrZ04fsBY2QijFwoGqhTGRyQ0mVxCRZVFVFnkwcMFCnWbzpS2bLN+uZs9ExWTBw8XcFyPqZqNabvsn6gBcMO2zmVvDCzM4AVoiymMFmt0AoWGxbpcCkUUMGxvzQretZYXHBERERER8VJEk0XiukTNsCkb3gmPHSwYFJs2PWps0Z/P1US6IvGDZ0b43Oc+x4Nf/xJGs4EgCLzzne/kT//0T8lms8dpqJVsaJ9NHeH7AYbt8fDh/LzNfme/z451aXoTL9g2JzN2Vzt260ScbODuWiTqeo0414hM24iIs8hamxQfceZY6ncNUGrapHWFhBZ+BJ+JCfee53HXXT/gb778Zb535x185StfIQgCNl31Krpe/RsYsRwADcuhbjp4PnjBTJXsMudMCYDlwEjZoD2hEgQBng9xVUQUwHE8fFEi8D3iusxIucl3nrbYN1GlI6Xx2p097BkqkU0oqJZI0wmfA1kUUSURTQ6zayUhoGm7oMoMlw0GiwYNxwuNxFITUYSxkonlerh++PgblocfwONHi3y/Y4JbLujhscEipaaN7wfENRkEkVxSpdRweHK4wvXb4P6D0/iCxE3nd837/RUbNrv6MyQ0iarpcvPOHnatz9Kb1lsDyo4VGjwxVCahSTQsj13r4cLeNA8eyiMKMFwKRXhSk1Zk1i9ns8f3A/YMlzBsD8f1OJJvYDkel23IMlldeQbbwta9qze387Dv4ZShLxNnW0+KH+ydXPOC92wuXCIiIiIiItY6K60wXI2KRNf1OThew/MFBMKOraWP9bC9pasHZjVRLqFy19338m9f+BOKI4cBOP+iy/jH//M3XHnlFccd35HUQBAYLxsr2tA+Gzpi1kScrlnsn6yxvSdNSld4frzKV34yCAJ0JxR+ef3yN/JXM3rqZJxo4O5aI+p6jTgXiUzbiIgVcjriJar8evE4220wc3/XpaZNV0rnyo05DMfjaL7BaKlJV1onG1foa4vzowNTVFdxwv2PHnqMW299XevvQ2PTfOELX+Dfm9spGi5G08YPIPDB4wUB7S+jyhbCab+yJOB4AbYHZcPF9cJz1SwfVQwNYCEIUGUJ1/Xx/AARAVUROZpv8J1nxvF9n6Qmk56pxhWBhCZhe2GWreX6WK6HJIrkEgpxVaJYt3h6uMI7X7EFURCQRBFFEhmvGDw/VqXYsEGANl1BkgSeHS2TUGWOFRuUGjbjFZOm7fK6i7qZqFg8drRAvmYAsH+ihoNIQpW4aiaTdu57NRNTFn0dWa5P0w6HlymigK6IGJaH4wcECHhBgOUGpHSFlK4gCMKyq+yXs9ljuT5V0+XS9VmGCg3GqyZJXWFnbxuqLJ52RX8uoXLz9i6+Nwg3bevkvkPFc0bwns2FS0RERERExFplpRWGix2/lA460Tnufn6S58ZqSFJAUhWpnaClS5OhI7b0Y9JkEa9e5LN/9kc89sP/BCCezvDL7/kQ17/+v3LhJQPHHZ/WZY7mm0xVTUbKTQZycSarBg8dzvPymYGzJ4qtOpM6Yq6JmEuomLbLk0MllPVZvv3UGHXToSutM14JdWq14azJrs250VRruQsr6nqNOBeJTNuIiBWwGu0UJ9qxjfJ1zgwvVhtMLqFy5aYcPzmYp2G7PHq0QMPySGoyXSmdqaqFLAr4mWBeK9RKDDDf99m9ezff/OY38X2f//W/PknDdKnE+tl6yVVk121h0/VvptS/lfO1EdSDPrIA1om70xAJIxCWqogQBRDFcCCZCDRsf95xtg+dugSiiCyGxxteQComkNRkPB+eH6/SkVJxPQ9RlFBEuGBdhi0dCR4/VmS6btOmy2ztzmLYLpNVi6ZVp2l7bJIlsvEX3ksS8I3dI9iOyxOGQ9P2MCUfzwswHI9S06LUsGnYLrmkyvS4yVPDFRRRoGw4rYQ1zw8o1CymaxYJVV70vbqYqPNnhq/1tOm0xzWKTQtZEvD8gOu3tqPKEo8PFpiq2RQbNlXTWXaV/XI2e+Yau+f3JJmqmUhCaKyvVkX/7P25Z3kycURERERERMTpsdIKw8WOr+91iasStWUWGcyeo9gwiasCNcPDPUk31/r2JKYfEF/kZ67rcvvtt/ORj36UWrUKgsBFN7+N33n/HxJoSdIxBdf1afhBy4QtGw4Ny2Oo2GAw32RTZ4JL+jPULZd79k1x/4FpZElk10CGm3d0n/WuobmVw7oicfFAhgOTdUarJo7n05HSySU0GiKAyXTTIqZITFRN4ORdm2d6bTn3/C/WzI6VsLAQYqpm0ZPWUaJ1d8QaJjJtIyKWyWq2Uyy2Yxvl65wZTvR7A864kHnsaJGpmklHUuNooclY2eCy9Rl29qYpNmwMx8Oy/RUZYENDQ/zgBz/ghz/8IXfffTfT09MAJBJJznvtr/LMRIPhosGlv/1Z2mIqo+UG/++pca65Co6WbCzv5NcqimHV7UJtPXvLtCYS0xS6UxqW5/PceP2442wCJN+naQVkEiKZuILpeBycqFFsOiiSgCxAuemB4HLVphy/9LINOK7PYLGBIAq0J1Teelk/33x8hCPTDcqGj2H7pGMKDcslocvEVAnD9pAkgZt39tCwfA7n62iSgOsHrUre8YpJLqniegHbelLhY/SCeRfZNB1UOayGnX1daLKI5fooooDjB8e9XooNm4cP53H9gHzNQhLC/N3L1mdJ6XLLkM8mVBRZwguCFVfZLzUheO7f5xq715/XCQE43srv62SoUcxLRERERETEOcVKKwwXHh8EAbuHyqzL6PS2xVp6+tU7unH8AEUUsNywgnbWMJ09R0yVcfyABZJrUXrbNNL68RbFAw88wLve9S6eeeYZAM674BLe+q6PovScx5GqB9Q5lq9z3/5pNCUcjnXT9i4eGyxSNmyu2JjFdFwsx8PzfZ48VmS0YtKd0gB46HCBhCrx2gt7z2jhzELtpsnhfIYHD+WRxHCz/6pN7bzq/C7u3TfJeMVEEgWahg3AwYk6ecMlXw8LP9ZlYlzSn1n0vs702nLu+dO6TMPyKBv2mu7CmquXx8pG63n8wd7JaO0dsWaJTNuIiGVyJtsponydM8dSv7eJislTI+VVFzJzxdjC++4NwmFVk1UTURComg59mRgCMFoO255mDbDZIU9i4KFpLzyuX/mVX+Hv//7v592npsfZdNn1JLZdy+fuPkggyLh+mC8rAQ6grfAl6i7RuSYKEFNE2tM6CVUODciMxsGpOrb3QoVuAJiGj6ZKqLKAKAi06RJ1E0bLJqIAkiDy1EgVx/PwEdg/XuULPzxAvm7RtFx62+JMVk2++sgQjuuRTaoYtk9PWkKRBB46UuD1F/Xi+AGCHyAAhydrWJ6HIgpoisTO3hTdaR3DCeMLpserbOtJ0ZPW2NCe5JL+NqYqJoP5KhBOOLZ9H9v1KRsOAI8cKTBWNpiomvSkdfoysdbrZfa9O1o22DUQDrxQZZHrz+vguq2drdtXDIdt3Wmu3JQjocqnHK8y+1mzlBCfa+zCmdmUiGJeIiIiIiIizi1WOldj4fHjVQuA7rTe0tNjZYPvPjNOvm4xWGiEbfGKxMUDbdywpZOulEZMFbl33yQTFWMmNiucobAUA7nEPD0xOTnJBz/4Qf7hH/4BgFwuxy/e9vtccOOb6UjH+MnBaRw/IBNTeHK4gq6I9LbpPHwkjywJGI7X0uFXbGxn30SNctNFEAISqkwmrqLIIjXTJV+3j1vXzbb7AyeMUFgOi2m3tCbjeD4+IAkCAaHOyqY0fu+W7Xzmrv2UDYeetA6YTDdM2lNxPN9HV8JCgPsPTh+3ljnTa8uF559bmHKydfKL3VmaS6i8ekc3331mHM/3ySXUaO0dsaaJTNuIiCVYbCf0TFWXRfk6Z47Ffm99mRh7hkunHEmwFAvF2JUbc/Puu9Cw2TWQabWWzZpdEBp70+UaxvhRnt5zhL/55BPse/YpBvc/w57nDrBtYz+W67Nx40YkSeKqq65i3QVXIay7iKBzCyMVm3LTwfbAC15Qw8uMqF02ImC7PoenmsQVUGSZiaqFrggQBDgzd6gCui7TndIQBIFy06bcdMk3LFwvQBbDNvumHRAQZpgV6xbPT9RRRBBFkcP5JnFVYtdABkkSaVou27pT+AEkNZmpmsW3nx7jaL7OnqEyZcNmumYRBKBIAqIocqzQQFckFEnkFds6eWqkhO361G2fYsPmmdEqV2zKsTGnAUNsbE/Qk01QaIbVswEwUjIYLxsMl5o4no83E/w7a5DOfe/ecF4Hdcvjled3k5ipFFntOJSTCfG5nxln6vMjGvAVERERERFx7rDSDdeFx29qj9OV1Cg2bERBYLpmMl23cTyf8bLBnqESmiLRnlD59901nhoqs6k9xmODJZ4ZKVEzPRQRnJn5B0uR0aSZ7qaAL33pS3z4wx+mWq0iCAK/8Ru/wUf++OP8ZMRCk0VUWUSecYItNyChSciiQDqmYrseFcMhG1eZqoVRAqbj8bIt7YhBwN8/WKbQsJElgR29KdZlEnQk1Xnrutk83j0jZYAlIxSWo+eWipuQRYHHj5VIawo717WhiGEXmOX6vHxbJ5f0tzFds4iJ8MTD99KeOHHl82wnYbnpUGraq7a2XHiNJytMWWqdvFY6Sx0/jE/rTOnR2jtizROZthERi7DUF8qZqi5bbUP4xd7BXEssFJ19mRjbe9M8cqSwqib5okYacOWmXOv8s68ZNXDwEEnFdURR4J//+Z/5xCc+wf79+/G846Xs//n37/OyV74Ww/HYcfN/5dBv30ZnNsMn7tzLZMVgqGhQNz0sd/VN2oU4Aa3etoYDsuOS0EVsJzRsA8Lq3oQukFRFJFGgYXnUDJtCw0YAJAEMe75oN90X/j8IIHB9BML2/ieHyuzqT2G6PtN1mw25OClNZu9YBddz2TfZZLJmElckmo6P6/mkNJmYImC6AfmGPdNyBilNpmF7ZGMquYTKRNWkbrl0pTVoQm8mRl82Tm9aI18PW9EyMYXRskF3m47vQ1tMbb1eFr53Cw2b/mx83utoteNQTnWTZ7U/F040mCP6DIqIiIiIiFhbrHTDdeHxczNLu9MxJFEkqckMFZvEVBlZFGjaHk3bY6TU5NtPjWI4PrIYDr71mdGRJ6Dpwe5HH+a2297FU089BcDll1/O7bffztVXX43vB7QVJlqDu1zPD6OwVJmq4WB5PjXLJaZIXLExx3XndfDY0WJLh1+yvo3f/vvd1G2PhCpRMV0OTNR54yXruGpz+7xupQcPTfPA4Wnwwwe9WITCYgUbCe34jqql4ib62jTSMZnhYhNBCHXo+lychu1y3/7iC51eSZkOYLjUZECUFq18nttJWGraHM03SGoy63Nx8nWLdZkYvh/g+8GytZnvB4xXTfYMleZlGWdiyrIKUxYWK6yVztIzWYy12kSaOiIybSMiFnCiL5QzVV22mu3Ga2UHcy0x+3ubqJjsGS7xyJECR/MNEqpMb5tO2XBYnzu9L+qFYswyDJ5++mlq+5uMjRzjwMHDHDywnwMH9rcyaV/1qlcB4TCx559/HoD29nZ6Np3P5vN3suOCi8lt3MnT9Rjfe3aC3jadbELluWmbS3WbpmVTbFh4fmhUnmnDdiEBYfRC2Zx/zx5QtQIalk2+bmMHhFENQtgSFwjzM82EOeeTmN82JwWhUJmuOazPxujLxNAUkXv2TTJWNVv5sSJgumEsguOGYlQSRC5Yl+RY0aBqOIgITNZNJEQu25AlqcnYro/pepTqBuuBfMNiR3+WQsNmXSbWqrQVgcmKyUAuTsWwGcglFs2SXc5793RF66kIzbP5uRB9BkVERERERKxNTrTherLj566DlJkc0KFiE0UMI78sx8d2PRRZJF+zaNo+QRAatSeKRJjFbZS580t/zO/95zcAyGazfOITn+A3f/M3kSSp9Xiu3tyOe8hnMN9AV0QMx6duOWRjKnXbIamGw2pdNyCjK/PWbkfzDcozg79SmgylJrbnU67b3LtvCs8PaIsprG+P88DBPKMlgzZdoTcTw/H8eREKC/XcgckaTwyV2NSRIBtX5+mfpeImetpi9GXCsWtVw+XStM6VG3M8drTIcLHBWMVkuNjEc3U6gGrTpZl0j6t8XqyTMKlJ1C0Xw/HIxFUalse3nx5btjabndnwk8MFTNtl1/rsPM26mP7NxJQl18kvRmfpUobnqa69z7aBGmnqCIhM24iI4zjZF8pKxc5yWQ1DeC3tYK5Fnhopt4SMJAg8O1rhWKFBR0rjVTu7l/0cua7LxMQEo6OjjI2NMTIywuDgIJuueS1a92YAvv/db/GVP/vgkuc4ePAQ1738JjRZ5NWvfjXf/e53ueSSS+jp6eWu5yc5VmgQV2UeGyzQtA3Wtys0bDcc5DVZ458eHmSkaFA1HQRBwDhRr9mLgBfMVNJ68/8NaE0OFgjjFmaLd2f/fxZFAFkSiSkipuejyBJNx2X/RJ2G46JKIjXDwZRCFzgAEoqEKktIgoAii8Q1iVxCpdx0qFsu7XGVuuXw0OEi3SmNqbqF4/pc0BsHE3rTMYaLBtdtaeeaLR34foDr5RFnzjc303b29bLS9+7pitaVCs2z+bkQfQZFREREREScXVbbSHJdn6rpktZl5AUbwnPXQbMRX6IgcDTfpNSwsORwmFbdcl8wak9i2Aa+xx133MHgP/wzR8wGADe96ef4rfd9mNdcsa1l2M5SrFvsHiyF1Z+Wy6aOBIoi0t2m8fqNvYiCwL6JKruHSiQ0mSs2ZMnOGF3r0nqrg6puOmH3VVzm0HSNI4Um129tZ6jYZPdQCdtxEQKYqIR6eyAXpyOpIgHFuo0ETNcs2hMqSU2m1LCZrJqsz8YZKobm7OygNk0WuXpzO8HhgHzdZkMu1jJdO5IafW06lw7EWrMaQpNOZbgYrluatgsqlA0bVZa4anM7oiC0DL3+bJyLBzI8cGC6pS/X5xIYjsdrdvTwyGA4n2ExbbbY62dWzx0thNFgjhcwVjbZ2pVoadal9O9SWvZsV7eezPBcqX4/2wZqpKkjZolM24iIBazWF8qpCKjTNYTXajbu6YjJ1RKic5+bpCZjOh6KBJetz9K0HZ4dqdClC5RKBaamppiammJycpLrrruObdu2AXDnnXfy67/+60xOTuL7x9e1fvYvt7Bl+4VUDIcd520ll2tn8+ZNbNy4kU2bNnH++edz/vnn0z2wmQMV+Mbjw7QnVa7d0sFrX/s6LNdHEAS6UhrfeGyYfMPC9nw2dyRwvbBS9dnRMjXLw7BcqqaDucbM2uUiAYocmq2iKNCTVik2XZyZ16rteoBAXJGI6zIpTUYEaobLWNmgpy1G0/ZwPR/b92jTFUw3IBAE+jM6siTSnlDxfBCEsG0rpohYbkBKVyg3LfwgoCulMVExqc08kdduaafhwCu2dWF5Po8NFmnYLl0pjTfv6iOlK4u+Flfy3l2Nz5iVCM2z+bmwVj+DIiIiIiIifhpZbSPp8HSdrz06RKFuk0sovPWyfnb0pBfVGbNapNx0iKkikiAgIPDokWm+XZg46X15jTKN53+ELMKXf/i3AAxs3ckvvPePufqaa5mumTxwYJrXXxTGERi2x3TD5M/u2MtwsUmp6WC6XjikNqOhShKlhkW+4TBSMuhK6dy1d4JvPjHCQC7Grv4M15/XyftevY3P3LWfkbJBJq7whkv6KDVsEAR0RSYTC9g/UePC/ixtCYMDExU8X+DKDTl62mL8+Q/2M1Y2MG2PuCahSBIXrGtjpNTE9QMOTNWQBAHL9bBdH8PxSOkyGzsSrbkTgiBw2cYsByZqVAyHgVyCqze3I8si4ky1797xCoOFJpNVg7gscO0GSMcUik2bx44WueWCHm65oKc1KG0pfRmbiSxYTJsZjrfo62dWz/WmNeqmw6jdpFA3SekSmzqSLc26Ev17NgfZLtfwXO7jfzEM1EhTR8wSmbYREQtYjS+UF6uV4cXI51loqi78++k8F6dz2yAIqFarFItFSqUS09N5nnjyIEdHxrjsmlcwSTvdbTEO7XmQL3z8f1AvF3HM5nHn+dKX/rpl2sZiMcbHxwGQZZmenl56e3vp7+9n48YN7Lr4Im6Y2VFXL+/n9375LYvuXH9z9wgPH8nP5KwG4S59UqXUcBCEgO8/O8lU3aQ9rmE1LcbKJutzsGe4ElaWuh6214rYOidRZYGkJqOrEuuzMX7migEeP5pnz3CVvkwM3/cpNBzWZXSKzbCNbV02Tlda5WghzLAVBQHbC0hoKr9+/Saatsf+iTqaKuJ6PjFFpjOlsz4X59mxKqWGzabOBL4fIElw7aZ2cgmFJ4bKTNeakIJS02ZdLoUmi9x/cJrhYoO2mMpk1eDhQwV2rEsz0BZD15f++jzZRsNqidblCs2z+blwLmWEzSXKC4uIiIiIONdYbSPJdX2+9ugQR6brtMUVHjlSYN9kjbdfMcDLtnYuqsFFUSATV8jFQ32W1CSOFBpIhBFai+GZdQp3/AXG4cfA9+h45a+yc+dO8v0v5zd+5ze4aEM3fgBDRYO94zVqpkPT9jiar3M032Co2KQrpTJZ8/D8AMfzqJsOmbhILqFxJG+wri2GHwRMVgwcz0erSvzbE8M8fqzIDds6+V//9SL+/oGjlJs2ddOlbnvosoTpuJQNh/akiuf7XLQuTWdSoS8T53U7e/jM3Qc4PFXDsD0maxY9aZ3utMahySoBAp7v4wUBoyWDkZKBJgnENYW7n59gqmHTmdC4bEOWsbKBKAjzKnFnf2eiKLC1O8k3d48wXTORRAHbC4tFLuxrQ5CklnnXsFx+cihPw3bJxlW29aQIgrCad91MZ1hMlVraLAgCxqsWm9rjKKLAfUu8fubqub5MnMmqhSJLbGhPnJbRerYG2S5meJaa4dDmTFxZ8f2+GAbquaqpI1afyLT9KSBabB7P6T4np/OFcqZ34k50bWdyB3Ox+11oqm7rSbV2jNtiClduCjOZFnsugBM+v7PP41CxSSamsHdwjOeeeITzMiLlcqllxhaLRQqFAhdddBGvfe3rMGyP79/xHd72tv+yaDUsQNGETde/BVUUeT5vUJoYaf1MkhU6OjtJtuWIt+UYMRWKDZtcQuXyyy9n9+7dxDOdPJX3eXq0CsB5nUkSusykH/CDvZNcuTFHyfXZM1xqtZftGsjSldIoGw5PDpdwvIBMXGO6ZvC9Z8fDQViBwDOjFYoNi+60juX5eH5AsW4zXTWomDa2A/YaN2sFTtwJl1AgHVPxgwBVEik3XYaLBhXTI6nLFJo2siDSn4shAg3LpW46JHWZmCryhot6+f5zk0zXTVKazLpcjGMlg3WZOK/Y3omuSFQNh8cGS2TjKkldZmdPmomqyUA2ThAEHJyq862nRoirMildpi+tAdCXCd8zjh9OwR2rmIyUTMbKBs+ODiJJArm4yvtfcz43bu867tqWu9FwtkQrnN3KhrN5X6tFlBcWEREREXEuslIj6URrCN8PmKxZ5GsWXWmNcsNFlkRM2+PwVANJFBddy/h+wETFpG66jJaaPD9WYTDfxJ0jwX3HxMkPo/WeB4CoxXGmB8H3UHvPQ2nr5n+++3/yPx6TiWsKxwp19gxXmKia5OIq33xihHLToS0WziLwvIB8zUaceQ4kAUoNUGQJUYQtXQn2jVcZKZkUGjbrs3EMOxzS5XjhLIO2mEouqTPdcHlqpEIurnLF9iy2F7A+F+dVO7tba5rNnSmu3txO0/UZKxvUTJeRsonn+Uxgcv3WdkRBZF0mRr5h43lhJ1fVdEjHVIaKBqYbYNoelubPixlw/OC435XvBzw7UkES4OL+NjzPp9gwAXA8n6oRDvqqWQ5/e/8RRksGXSmNbEKlbrnoSmjqzdXiFw9kqJoOu4fKAHQlNSbr1glfP3P13Kt2dLFrIEtPm37amu5MRQ3OZaHhOVRsULc8vvfc+HF5w6dyvrNhoJ6LmjrizBCZtuc40WLzeFbrOTnVL5QzuRNXatrsHsqf8NpO13Be7HaLPaeZmDLPnJ7Nf8roEm2ayL6paUZHRiiWy3hmgwnToFItY+7YxfndKfZNVHnyid3c/59fJYaN2axTrVapVCpUq1Wq1Spvf+/H6b30lYyWDfY9eD/f+NT7lnzsmUyGu/dNUbV8BgtOy7DVdZ1cLkc2m0OMt6GlMlx10fmkOxMcmKxT1Pu45j1/xYb+Xvp6u2kGGrm4iumEYtXwA+5+fpK3Xd5PIpHkvO0X8YO9kzx8tIjnhQMWvvfcOL2ZGDds7eDAZI3dQyWalovp+GzrSfLo0SL37J0kqct0pTSGSk0SqkSAj+X65GsW2YRK0/YwHBcEgVLDptSwaDo+MUWk2HDxeWFo11pFAuKaRNPyWnG2EvOFY4BAzbRJ6wqqJFC3HL7z9BjdaQ1JFBgpmWiygCD47Bmu4voBqizQdHxu2q7wK9dtQhZE7js4je2GlRHDxQYiQivyoGq6tCdVKoaNLAkoksC6bIyL+tp49FgBCJBFgYbl4AcBr9zWDpNw8/YuNE3FdX0mquHwh46EysNHCziuR18mxljZ4DN37eeajbl5Fbcr3bA5G6J1lrNpEp/N+zpdorywiIiIiIhzlZUYSSdaH83+rNCwqJkuk7UwfspyPPpzCdZl9ePWMq7rM1Rs8uxYmUeOlmhaDu0JlWOFJlXDxSqNYQ7uwTj6BObgHpBkBt79TwiSgiCI5G65DSmRRe3cgCYFCEKoGvs7Ejw/2mS6btGR0Gg6Hvm6hSAIiDN/2uIy5aZNaSbaqm77uH5AwnT55u4R/EBAEkEUwu/5Qt2kZrmAQDau4Xqwb7zKhvYYSU2kM5mkYXlk4yqv2dnTmmGyqT0xT8vYtofpeAwXmti+j+l4+EHAPfunOK8rRUKT0SSBhhdQNhxcL2Ck1KRQt5AFyMbVsAq2ZhwXMzCXiYrJY4NFqpZL1XLpzehoM7m+XhDQn41z5cYcPzmUZ7TUJJNQadguQQCTVZP+bIzethijpSZ3PjNOW0ymarocyTfIxhU2dSQoNmyePFZElyUma+air59ZPTcbvzD7vJwLzDU8S02buuWR1GRiinRKWu/FMlDPJU0dceaITNtzmGixeTwreU7OVIXymcjEneXxwRKjFatlktquz+sv6j3hkIClzun7Ho1Gg2azSaPRYCxf5rGDYxTKNSTP4h1vfg3nb+rH9wP+8T/v5s5vfwvBNanU6kieTVx0GZosYpsG/+33P0Z2yy52DxYZefROHv+HTyx5XW953ycZdxOYjo87PsZd//HVJY+dLBRxS02623SacpJs73qy2SyeEgctSSqdIZPN0tuZ4/zzujk0VWOgPUV6/U7+5o7H6OrIYQYykihgOR6PHi2Sjatcsj7D08NlNBl2bujhWSWOktQQVZ12WeTgVJ2OpEZvQmW6ZvLkcIldGzI8frTI44NFBgtNRAG29aSRBYGxiomAgCyJTFdNpmoWCV3CtDwePlxAFgWGSk0IoLdNJyaJTFUtSg0H03ERRAHH8XBcH02WIAjwAyg2XSQBHFFgtmBhjRfZ4gOm4yGJIPgzgjkASQRFFvH9UFiLAjRsF1WWyCVVxkoGdcslHVPQVJFa02K4ZOD4oVFtOAGTFZPOlEqbpjBVtygbNpm4SsV0yMVVuts0etI6huMdVyVxzeYOEMCwPTRZoj8boz2h4wU+TdvDdgNi0PoscPyAnrSO4/qUDJsgCEjoCpm4hiiKlA2H0arJFj3Zel/5M4Mj1mr21Nk0ic/mfZ0OUV5YRERERMS5ynKNpBOtj4B5P9valeDgZJ2a55OKKVy2IUOp6cxbyxyervPVR4d4ZriCF/joisjRfJPh5x6l9PR9GIN78KpT8x6DlMjgVqZQcusAiG3cteg1PT9UYqTmkdFl0jGFhuVgWB6IUPB9REki8D2m627rNgFguAEEPsWGgw9s70qjKFA1HCZrFq7n05eJ0ZuJMVUzmaqaHJyuo4gCKV3hgr4UDdtFFIV5MQVztYAHbO5I8OxIFcsNSylcP8CwXLZ2paiZDs+OVluDazVVwvICZEnEwyOpSQwWDJKazBUbtSV/V08MFWlYLildptiwOTzV4OoNbeDDGy/uIxHTMGyPUtOmM6XRtH0UWWSiapKJK3SndYCw6GViip60ziUDWcZKBl3pUO80bZ+HjhTpa9Mp1G1EQVj09VM2nHlm/5Ubc6E5/SIaiMtdw8/NXP7ec+PEFOm0tN5qGqgr8SHOFU0dceaITNtzmGixeTzLfU7yNWte/s9qVigvJqCu3JQ7SRSAj2VZmKaJYRhI8TaeGK6GO4PTY6TMKZ7e/TD1pwYJPAfLNBmcLNFoNin8+q/zlusvJhNT+Pdv/T++9i//jGEYNJtNLCs8n2EYNJoG7/uzL9J73kW0xRT2fO+rfOiD71/yOlTtn/nD3/55LNdn7/PP8f2vfnnJY8fGxzksDjBeMSnbLxjIkiwTT6YR1ThaPEGgxLBEHcfzcT0PtWM9P/s7HyCWSHLDBRvoyGVIp9Ok02lUPcH9Iw7TloDnBWy/+AoSH/0XDCfMb5LEUCjpssj5A2k2yUM81XTY0SfTnUvxxJCHU/fpTQvcs3+KqaqFJMKRfIOG7dKwPXoycS7oayPfsMnXbdZ3JEioEqoiIguAEGC5Hvm8xed/cID9kzVkAWwvwHBcXC+gL6Mhi1C3HR46nOeZ0QrpmEKpaXMk38CwPXRFJKbK9GdiVE2PvrREwwqFYXdKJydAoelQNx2aloMbhEalLgrYfoDlnGPTxgJI6SKm6yMg0nBCyzmuSFStAFUCVZKwPI9iw2oNYKsYTsu0tjyfmZu1jOq641Os24iiQG9GpyetUzNd2nQFWRToSb8wdXd2YdGTCoXr7PvfsD2yCYX79k2Rr1tAgCxJtCdV3MILl6DJIn2ZGK4fsLUzySOHi9Qth4phU2k69GVirEvr8ypX0rqMJAgz542yp84ForywiIiIiIi1ynKMneUYSQvXR34QzlMwbA9RFCg0LHRZIqZKnN+Tpj8X59KBLEfzdaqmS0KVuXJjrlVt+pX79vP4k08yun8PuYtuoiomqRgutaF91J++K7xTUUbr30Fswy5iW69E6dyEIJzc5Pruc3lMLwACBrIJ8g0Lx/dJqwply8UPPGTBX7SIYbxqhdWggkDdspksWHiBz3ndKQp1C8cLKNUNDozXKDRsbM9HEKBh+7ieT1c6RsNy0WRx0edTEQWajofje4gCiGI4Q6M9qbMuG6PSlDlWaHLxQIaYLIWFF0HAFRuyfPXRIcYrJjv7UmRiKildJhNTFrkGk4eOFIEwCgFAkQQGsnGY0anFps2jRwocnKpTbphoikyl6jLQHuf8rvBaxyomxwpNRCGcNzJVNelMakxVTYp1iyeHStiuhyzAeLlJzbB43cXd89bDC83+A5M1nhgqsakjcdL185kqjlppR+1s5nI2rp6S1lt4HathoK6lTukoZvPcIDJtz2GixebxLOc5ydctvnTvAYbzVXKaQFKFqfERrtnQhuPY7NixA2mmBeXpp5/myJEjWJY1749pmliWxXve8x5SqRQAX/va1/j+978/5xgLwzRpNE3K9Sbv+cSX2LxxPVdvbudLf/HnfPazn20d67ruvOu4/d/uxmnrp9SwueMf/p7H/v1vlrzmG15xE3fnukloEv/v/t1885v/tuSxxyam2bhDZKTUZKIeCgFBEEgkEshaDD0WJx5PoMTiuKLS+hDfeeFFvPpnf41MOoUnaXS3t3H55h48SWei6dPWv41HJlzaYiptl91A1/ZvocfivO6SgRmBKCMKAg8emgZBIBNXGSoYTAcZMtf+LOvb47z5FVvoSGqtx+r7AUPeOM2xCqWGFQoTwyGly7g+BATUTRdPlRgqGlzRBdM1i2LDptAITbPetIYqS+RrFg3LZWdvqjXA4IK+NjJxGVkU2DXQxkTVwnY9fN+nLxWj6bpMV0wOTdXRZZHJmhlOXk1o6EpA3YRC00YUoa9NZ7puM121SMcUCnWLqRkx7PsBNc8nCAKGiz6qLDJcbKCIAutzcdIxmbgq4/o+SS2sCs43Hdo0GUvxGauYLJ7MuzaRBEjGJFRJJBXXaFoOqgyBIIYxB6KAKAlkEyqTFQPbC+hMywS+T9V0GSsbqLKI5x4vxwXCDRdFDKsBdg1kyNcsCg2b/lyc687rQJZFZJYWRAld5rqtnZi2z56RMgC7BjJcuSnHQ8deuC9RFLhyUw7b9WnYLj9zeT93752kbocRCe9/zfmoqsS9z023xOxo2SATV+nLxKiZbpQ9dQ4Q5YVFRERERLzYnGxuREqX2bU+S29aX3To78mMpLnro6rpsHuwgK7I5BJhVebdz08yVTPJJTR29qa4eCBLfyaGLAs8um+Ehx99km/9436KQ/t58sk9jAweJvDDgoLztQz+xmvxAohtvhzPqBLbsAtt4EJEVV/xc1G3PNIxZaadv05WF0noCk3XIyaJ1Cyb0hITziwPZNdDVySOFhoQQE+bji5L6IrEdM3iSL5JzXQggKQmYTg+BD6iICCLAvfunyKuSmFRwILK0tnBX3FVxvU8HD/UvaIIlWa4se8FAf/y8DFsL0CVBF5zYQ9xRWayatGwPFK6T910GSo0MWyPxIKYrT1DJUzbxQsCyk0by/G5YmOOYtMkDfznnlEGyxZJTWIgG2fveIVqs0FXWmVdJsblm3I8O1Jh30SdDbk4gihSrFsUmzZdKQ1ViWO6YXW0KoWdgPsnajRsj70TdT725gu5fGMufD7nmP1JTabUsJmqmWztTJ6wm/VMmZInqxhfilPVemfiOnw/4KHDeY4VGnSn9Re1U3otmccRJyYybc9h1spi0zRNbNvGcRxs2573/0EQcMEFF7SOffTRR5menp53rGmaPPHEE4yNjfHOd76zdexXvvIV9u7d2zp27n9d1+VrX/ta69gPf/jD3HPPPeH5LJtqw8CybQLPRfA9hoaOoWkavh/wMz/3C/zojn9f8noKhQK5XPhldfvtt/PlLy9dYfpLv/RLLdP20Ucf5Stf+cqSx9bq9dYHs2maFIvFRY8TRZFirYEr2zRsl87eXjo2bKNdF+js7sH0ZSqOQCwWozuXpr+3mz0jZfoyMXZddR2jv/I/kFWNnes7sFHoa2/jis3dPDxcY+vW81oVyDtf8Qa+/tBbsZGIqzK251M1womaY2WDzZ3Jlhh8xxtuYuuOi8jXbXIJhc0dSQYLDaqmS68msSmXYPyRQWzXRYglkRWdpuMxVTExHY+ULtOfjeMHEATQn9F5eqSM4/r0dCeJqxI/OZifF/VQNhzqlsvTI1WqhtOabjVRMTFdH9f1EaXw8VkzpndHQqFpuQzk4nSmdAoNG8P2ODzdwPWDcDc8odGb0fnVl23kmbEKhbpNd1uMfN2m1LBDcaeLCEbA0ekmpuOR1mUqpkPg+TSsUCkKIvSmVOqWx3DJoD+XwPcDFFlgtNykYbkookBMk6gYHiUjzMFS5dC8lDWVkbJByXDobdPpTupcsC7N/okaQ8UGoxULhDBWYIl5amuSIAAxCF/HTdNBlkUSmoLnBzQsDzeAhCQiSwKZhEpMkdBVkXzNRRDCagIBSMQUkoHAVMMGQBagO63hAnXbCz/7gK60TUKVuW5rR8v0d12fBw5MM1k16EwdL4hyCZW3Xd7PrRf1AmEVrufN3zgpNmweO1qkYYcVJr9y3SZuu3Ero1WTdWkdXZcxbO+4yn7L9blxWxeiKES71ucIUV5YRERERMSLxcnmRuiKxD17J3nwcIHrtrRzfm963tDfy9dnkSWRtC7Pi0tbaOxevbmd6nMO//HkKJNVk/akynTNYqJiYrge9WKeQ1PHeKI2wc03vIx/friXqapNZd+Pefz/fOS4xy3F20it34EhxhFmdKravYVc95bTf1IE0FURw/ZIxTUsJ6BqOFjLaDxzPTDwado2uiKyd7yCpsgzw2+lMM4qCOO8XD9AAGRRZH0uTl9a57GjBdbnYnSmYuyfqM6rLL2wv42YIpGNK9QtEcn1EQjIxFUsz6O7Tee+/dPUTIeYJlM1bO7ZO0lckmjaHuOVJo7nUTNdcgmNdbkY123tbBlllutTM13O607x2GCJQsNBVyQ25BKMlurh7zUQGC0ZdKZUNNlDFAR0VSIT13hmpEI2rvK6naGJOVE1QwPasFEkkZ29aa7a1E5Mkbjr+Qm+98wY+ydqM9XUEpM1iy/cc5DP/9ylpGLKPLPfdv3W66YtrqDK4qLdrKsd3zj3dXyijlr5BKf2/YCYIvHqHd2tbryTPZYzFUM5UTF58HA4J6NmevRljs+LPhtEMZvnFpFpe5YoFosMDQ0B4Lpuy3h0XZdkMsn27dtbx85Wa849Zvb/u7q6eNOb3tQ69h/+9otUKhVM2yHwXO7xvNax69at4w/+4A9ax952222MjY0dd/+O4zAwMMBXv/pCtuitt76evXv34nnz799xHNatW8f+/ftbx95www08/vjji153R0cH09PTrb9/8IMf5Ec/+tGix8ZisXmm7Te+8Q3uuOOOJZ/Tf/mXf0EUQ3Fy8OBBHnrooSWPtW0bTdPC/CHx+A9ERdWI6RqapuE4L2zfbt26lWuvvRZN0477o6oqSCq+HyCKAq9//evp6upC13UUReVQwaRkBZRMH1+QsdU22hMqFcPhV3/jd3jrz/wsqXgMMxB5bqKJ4Yl0tCW5dls3PzmY5/vPTZBJKOx8xVu4+tVv5RKO8spX3UJMU/nuM+MtQ2q8YkDZpDetobdfwqTaC0HADds6aVoeNdOhkVAxqkV2T1hcppo0bZe84WN4DmXDYKpq0pHU6E5p/OeePLbrU6jb7OxrY0tnEghb1Ju2y7FCnfv2T+MHsK07xWNHCzykSMiyRCahUjVcGo5LNqGyrSdF3fKoWy6W67dyRZuWy4ZcnG3dKbJJjWeGy/zoQPg6uWFbZ0usFuoWPW0aSU1itGKiKQJNB4IgbKdPazLpmIzlhVWZ+yZqlEyfa8/r4IoNOfaOVfja48PIkoAkhNlO+brFQC5G1XQIggDX9Xl+vMZU1aIno1NqOlSaNtWmg+GGlbHHCk0cPxR5mhpW+SZUmZrlMVE1cb2AquWiSQKFmo3heAjBbIyC12rhCgJwvPD1YnsuciAxVGwymG+wvTfO0UIdzw+ozQw6IAhYl9HDql0nWLN5tiKgiCDMmMySJLGhPQ4IFOomPgLZuEQuGVbK9qR1NnUk0VWJmCzx7FiFyapFUpPpTirYPiiSSE9K48nhMqbn05vWaU/qdKX01sJkrtEGYfRBw3L5yaE8PzowTTom05nS6UhqxwkiURTmVTd4cxYCC4XMVC0cCHHLBT1s6Uq2jluqsv9cGtQQERLlhUVEREREnG0WM078wwFXb2yn0Ah10bFCE8cLkDyfI/kGTw6X6UhqdKU09oyU+ebuEVK6TEdK46271rGtO8Vk3WLPUKlVLTprBCuSGM4dMMo8cfd3KE8cw5geximM4FnN1uMqFfL03/SLOJ6PmRwg1t5L76btiB2buOCii7EzG5lwdZqWNxNlsHpYPuTrDpIAsgj5qknDCVqRWcu5PX74mAw3FHe26yKJkEzJBEBCFbENF8MK88gEwWe8avB3PzlKIAiMlHS60zHyNQtVFlqVpWXDxg+g3HSoW07Y+RcEPDVUJqZI3HphLw3LY317nFxCJ183maxaSLJAZyoccpyvhVWy6ZjEUKGBLIoto0yTRVK6zGNHC+iKQDYmY7s+h6arVOoWl2SgM63SldIYrxjosoTt+nSnNDIJhaPTDe7dP4UoCFzY34Y6ERqrr9zR3arUhtAcvm5rB48eydOwPRKqRDqm4AUBg/kG//LoEBva4+wayHLlprCQaaQUvg4nqiYPHymQjSts604f1+G7mvGNCzc0rtyUW7Kj1vMWf4EstimynMdxJmIofT9gz3AJw/ZwPY/RUpOpqsErd3Sf9U7pKGbz3CIybc8Sv/7rv04QLP6ldsstt/C9732v9fef+ZmfoV6vL3rs9ddfP8+0/eQnP8nExMSix1566aXzTNs777yTI0eOLHrstm3bWv9fbNjsPXSUwcGjix7baDTm/V2WX3gZiaKIoiioqoqiKGSz2XnHbt++nUaj0fq5qqrIskyxWGTDhg3zjn3LW97C9u3bW8fNvY2iKPOez/e97338/M///Lyfz71NPB4HQpPl3R/6U17zq++jZkPR8BnobON3XrGVjpTGQj7wgQ/wgQ984Lh/n/0CeHDUJlUYZ9f6LDfd9EpuvvlmfD9oBZ5rssihqQajpSb1QGK8atGV0thbEahZbaQFmYblUSNGR5vGRN3isaNFrt3czrNjFUZLTbrSOpmYCE1QZRFZFrlhW2frC2ggF6ctppKvW3QkwfUCbNfl8cEi01UrnJYZk1FEmKxaPCWUuH5rJ+KMiVk3PVK6wkTF4Gg+HLC1pSvBaNnga48O8YFXn88jRwqMlppMVE0G8w0s16c9rvDkUBFNFpEkkZQqEQQCubiC7wf0pjWOFZtIgsC6bJzXXtBLJq5QbNo8cGAaWRJ5dqyCIogUmhbr2xNMVJo8cGCal5/XwWjJoD2pUjM9GlYDgYC4qhAEAuszOmXLQxIEynWbku/BQHg9NSfADQISisRVm9r5ztPjDGRjjJUtRC9AFkXGKyZ/9r29qKJEzbQZLhlIAggEVAyXoWIDVRbDYWl+gECA7Yb/FQKfrpTGSNlixLCxvLAIuFloIs34dKoY/lsY4xB+0HqA7QFewAtJXC84hU+PNufd1idsuaqZDo67dgaQCbzw+AQgroA0IzRVRUYUQBJEBnIJtnel+P7eSY4VGnQkVLJJlYv72tjUkeSNu8JBFD85lGeqZiKJYDg+nh8guh6aKtHZFuO3N3dwcLKO5Xt0pXTeftX6ViXJrNE2+34sNW2O5hskVJm0LjNcDJ/Tvjadddk4vh+0NllOxHKFzFrpdoiIiIiIiDjX+WnOVvRnTMTZ/86yUG/ULZcHDxc4lm/yxFAJz/cxXZ+4KtOV1snFFQ5N1uhpi6FJIvvHa4xVDLb3JPnx/gkefGo/3XKDydERSlOjSPU8hYkRavlxfuc3f5PO696GKAhM5Isc/f7fzX+Qgojc1o2SW4eT6MKwPQIB/HgH637rbwkC8AI4KAukAxnDcjDP0MiFAHCDsGp2NUxhPwDfg6maRUdCpWp6WG44FLczqdCwfMbKFooIiALPjtocmqxjej5dKR3H91EkgTueHsd0PSzHC403HzRFwHQ9dg+VmKxYmK7LZNXBC6DcsMjEFGqWy/BMkYbl+ViOTExzmKpZ6Irc0peiKLBrfZZ79k6FFdCOj+36PHS4SF9ahgxMVS2yCRVZEmhYLjFVQpYEDozXMByX87oSTFYN1AnxuMrShQbmL123kWdGq0zWwli5muGS1mU0WeCHe6f4yeECL9vSzpUbwriwC9e1UWrYjJdNZEnkyk25496rqzmQ+7hKUODKmeiGhXNjxEV8ltOpJj0TMZSWG0bBXbo+y1i5SaERVkDvWp896595UczmuUVk2p4lFEVBFEVkWW79URQFWZbp6OiYd+wVV1yBYRitn889dufOnfOOfcc73kGtVpt37OzxfX1984792Mc+Rr1eX/S8bW1twAsfbu/44P8ioUDN8unLJXn5+T1oWmiwatp8c/Puu+9umbWzWbBL8dd//dfH/ZvjONxxxx3ceuut8/79N3/zN0/8pM7h6quvXtZxoihw08UbiSdTlJozbdXndczLUj0Zc78AlmpZmjWPkppEX0ZnqmqgSCIbcjGalsdgoUlvWuNooclY2eCy9Zl55lAqpvDbr9jCTw6Gw9IyuoQz+MJk+9l23rGSwePHSjRtj+m6jSSKXL05x3OjFaZrNtmEynCpTNNxuXhdBt8PDbabzu/knv1TPHg4jzPTimM6HjXLZWMuQUyV6Z6ZJjrdsGe+3FVGSiY9bTqjJRPHh3zDDgdpxVUM20OTBC5Y18Z/PDnCWMVkc0cCQRRQ5LBty/cDfnIwz3TNZH0uzg/2TjBdtdnYEacnrTNeNXn8WJn/eHKEqumiSgJXbMwhiZBQZbpSCpIosn+iRlKVqRoONcsjJoe7qw3bpWI1qZsusihwYV8brheEX4qygGAH2J7PSLlJoR7mRAVBWEHrBlA4lA+Fohfu7rtBWEUqywJCEJCOyyR1ZaZ9yW61aQWEBq1LeLwTDrkNX3MzP5/9c7KvZNsHVQAngCUiu140BEIjOSCMQJBFiKkKjutRtTzivkBMEenL6YyWDJ4dqWB5obk+XTPRFIlcl0ZPJkYuoYYV6hf14gcBh6ZqTNdtDk3WaE/ovP6iHm44v4vetI7vB1RN97jWP5j/fkzrSrjRkdK5eCADQNVwOa9ToWl7fPvpsWVlNq1EyESt9REREREREafHi5mtuFKzeDnHzz2mbDg8fGgKgLv3TXHN1q7Wtc1WVh4rNHB9nz1DJXxgsmpieT6+7zOcr1OvljgmNrm3UWRqcpw7KgW8egGh7wIGrng1Tw6WmRo5woEv/taSj/vOB3fT3349Rwt1DC1D8oKbkHP9yO39KLl1KNk+BPmF57xh+y3tOpeGG9CorTWFemJmvWXPg8naTOyWKOB4AZNVB0UGURARBAHDdhGCcICY5/oMFhp8+b5DxFWJhhOgiNCc6aILZrrqbNfHdsLuu5dt6eCBg9MUajYb2xO86dI+vr1njKP5Bk3bxfV8TMenI60yVDSQBJHA9cmb4QA0SYCSYTNWNlFlEdv1QQBxZojbPQcmed1F/fzi1RuwXZ8HDk3z8OECh40m2biEKErEVJmK4eD4QavYYCkT9I/edAFfuvcwEzUTRQrnbTx8tIQgBMgi4WvTC2jYLu1JDdPxSGgyzZkuyoWsVkHDUgUUCU1u6e6G5fLY0WI4DFg7XqOfTjXpmSjMmLu+OK8rSbJqsak93qqAPptEhSfnFpFpe5b4+te/zq233oqiHD8lciH33nvvss/753/+58s+9h3veMdJj5n9cLvssstI6Qo1M/xg23r+uiU/3GarWM8VTtdkmX2OcgmVQ1ONJVuWkppM3XJpT8L153Vy5aYcAfDX9x3G8XzqpkNvWwyAiYqB6wVUDJuBXAJNFompGm+8pG9m99Dje4PzH0exafP3Dw8yWjLoSmlk4iodSY1Xnt+F5wdIgkBclTiSb9CwwkB7QQBZEqnZLqbrMV4xqTQdknrYfiMKMFkzkcZDo3VLV5L2mEJMkRgvNzBsl73jVVRFxHQcFFFEU0S60jqPDxbpSmsUGxaqJOArIlXTJhsPn4+JislDRws8eCgfRhq4QZh/KoYt8/cfnEYRAibrDo7n05nUKRs233t2nFxCIZfQSOoquYTKZN0moysU6yaO7+O5LuBiOj6+IGC54QCvJ4ZKXDTQhuMHjJWaSKJA4AeUGg4Ny8OZ2b2flRxzU03tmX/0Ad8Jd+ObdkAuKYRCeomNf3/Of4U5f59FZG597eLYa6WsdgEBoMkCuiziB9CwPQRgU0eC0YqFEAT0tMXCv5ealAybjR0JUpqMYftkYgob2xNc0p9pnbNqubh+QNkIjfa3XtrPjTu6WNcWa703RVEgl1x88TZXkCW0sBJlqmrhuD69mRi7UjqyBOMVc9m77CsVMlFrfURERERExPJYaHqebLjQmdwUXalZfFy79sYcMSX8/p+tlMzXLH5yaKboIqbQsDwqTYNOYLTU4Ef7JnlZv06pVODQsVHu2XOQZw+P0KwUaVSKXH71tSQvfSX9GZ3nDxzmwY/8bGvo10Jyl9m0X3QjFdPB0TNhtWwyh9TWhdzWHVbOtnWRaO/B7t/M4HQDw3LxJJ32N7z/hM/NOTROYUV4MwUZtvdC7JjngoiP64YFG4IACi8UdYyWLUQBUjE5rGwVBQwHECDwwbQ9LNdnfU7C8QIuG8hSs1w2dyT4990jjFcNgiAgJksYgoDn+YyWQlP28HSd3/ynx2nYHklNoiutYTkecS3M3w2CAF2WMJ3w0SZkGVUSW6/TWy/oRRLA9X0IAop1i5phz2u5n+0CLTXt4wzMG8/v4ou/cBnfeGKExwcLOH4YhaDKIpvak3SndRq2S1yRuP9gHtfzAAGLcGjaYsPxllprr2SD5GQFFL4f8MjRAmNlg46kxli5SSfzq9lPt5p0tQszFq4vNnckXlSjNCo8OXeITNuIebxUSuVPx2SZfY6O5usU6iYQ0J5Q6UioHJlusLkjgSZLDGRjFBo2mixhOB57hkqUmg5Ny8XzA0btJpNViwvXpRkrGxyebtKeVLl5Z888syqmSjgLgpx8P+CBA9MMFZrkkioNO7QbG7aGKApk4yojpSayJNCeUPGDgKbtIksSF/e38dRwmVLDZlt3kmP5cGjWQDZGUg/FZd1yubQ7xWsv6OH7eycZLDR4erjMSLlJpenSnlJJqBLXbG5na1eSqumyLhtDlUQGp+s07XD3kyBsR/eCgK/MGMyG7TFRaTJdt1FEgYFsgrrlMFJs0pPWadoeuiwii5DUZI5M1VElEd+3EQWBSwYybMgmOJyvUzUcHNd/oap1piJ3S2eCTEyl3LTpa4uhbhLxNmS467lxpmYqbGOahGu4LKfrKiAUeZbjYVouhuMjiQKCd+Kc2cV+doY6yc4KcTkc2uAEYYVCAJiOj+kFrM/FqBgunSkNxwvQFYktnUm6UjqaKlJqOOwayCJJAvcfnG4tdh4bLFJu2ly+PsN41aI9qc4zbE/Gws+sbDzMbPOCgPW5OJf0Z7j/4PSKd9kjIRMREREREbG6LJovqUiLVsONV02eHi6f0FBdzAC2XB9FFE46cGi5rdOz55SABw5MM1E16Uyq7B0tc/+BaSDAtUwYf5Y2weLBvceYyhcR7QauUadaKXPTq17NG152MWMVkx/v2c9/ee+bl3yOTMvi0v6rwogzWw4NW0FATmSQEjm0tnYSmU6CeIZU/w48wPPBV+Js/sC38ITj12wCUA5AtT2cc1mIniYzM40XNaR9QoMWIdT8QuiBtmLBRAEs10MRwzgEEVClmRgHAgQ/oOn4NG2PveMVGpbH7mNFaqaHLAYIgoAXhHMxZEnA8XzKTQvPd5iumsiyiDYzR2NdNoYAeJ6P6Xg0HRdtRrJm4yqG47XeH9M1i30TVbZ1p2lYDsWmM6/lfmGEWFKTWJ9LzFvjW66PIotcsamd0ZJBqWljOh5dKY1iw6Y/G+eidW08dqyE40J7Uqcvo1Mzw2pbw/EW3fyYq7NXukGyVAFF2XB45EiB6ZrF/ska23tS4eeGr0EZbNdH0154385m8p5qNelqF2astfVFVHhybhCZtj9FrEYW1LlUKn+msq9Odt7Z58gPAkbLJq4PfZk4VdMhoYo8eCSPLku4XkBKl/EDiKsyP3h+komqycZcnFhcpWk5yJKIJkt0pnTO60pRNhwOTNTY1J6YJz4X5vSMFJv8+MA0FcOmajr0ZWJM1SwuXZ8lpkrh4zscUKjb3HBeJwhgOT4dSZVdA1nuPzhNd1pnqmYzUmjiBmGEwEA2wSX9MTqSOtdta+f//niQkZJB1bCZqpmUDRdFEMjEVLIxmamaxS9ctYGYInGs2OCbTwzz/ESViukSV0Wajo8gChycqNG0XLIpDT8ImKi4FBs2bTGVrrRGmy3TtD1UKawOnq5aBEDNdBElgfakiukGTNdMHjtaZGN7kmdHq0zXLVK6iuOEWUztcZWYrlIzHSqGQ812uagvjeH6tCc0dq3Psn+iTrFpM10Ld81nTdvZ3/RiRmtrJz6AuuXRnlLJxKQwE3imQ0zkp7cqAUCTYEtXOIhBUySEQMCUfXzfo9ywyVddzutOE1clNEVkQyKBLAqYrs9U1WRdNk5clRgvG7TFVIaLDWzXp2G7rYWaIAhUZwTgcgXEws+sbd1prtyUI6HKrc2mU92IioRMRERERETE6jDXJM0lVI7m6/hBwC07e477nl6XibFnqNSqolvMUF1oAm3rSXFgosZY2WCiatKT1unLxFrm0KymFnyXer3GVL7EU08dwjUbTNoGhVKZ6f7N3Hj+a9FkkaPHRviDP/wQo1NFypUqlWqVZr2GY9SwGlW2vfJnyd74q3QkVeRmnn/74G8see09PT284WUX88SxMrIQdijGU2nURAYhlkZOZAi0FFoqw+bLr2SkZFA3bSxHYv1/+wpqMoMky8dlyDqAaTotDbuYYQuhjrUBx/bXzIyEWc6mGXGyaxcESMckmpaH64W6PiDsxPN9cOwA13XCuDMx/FlclcnE5HDQsCAwWQkHdtUsB98PkCSw3QCl9V+BwAdP9CnUHJyZal5dFFAkkablkK9bOG6A6QY4ftgpacwU6BSaFmldbr0/tJlq3X3jVS5c10ZHUmNbV5LOuErDdHn4cJ7hkkFmpnOy0nRpJN3WGh/C92ZalxktG5zXnUSWwqIMXZXIxtXWILuXbWnnWKFBd1qn2AirdhVR4L6TbH6carbsQoMT4PvPTTBSatKeCKP5njhW4qpNAjXDoptw/stiFfEJTV4TJilE64uIlROZtj8lrGYW1FrbAVqMM5V9tdzz5hIqr7uwl0sHsuwZLlE1XbSYyiGnwWjRQFfCjKqAgAvjMkfzTQJ/5su8ZrFBkVjfnmBdJoYxs5OZ0hVUWWxVAc7dtZyb03NwqsYn79jH/slaK+vVcjwu25jjuq0drd9XEAQ4rk8uoXDN5o7WlxWEJtZwsYHpuDg+dCTDCl3H99nQnuCqTe385FCe0VKTlCazf8LE9XykAHwB8nUTXYlTKRp884lhCg2byarJWNlAlUVEIay07ErpWI7HwakabTEVeabSOAgCNnckaTouI6UmXUmN87qSpHWZdMIJK2cFgbSuoEhha5wz0wbfk/FI6zIV00ZXJC5el2TPUBEw6cvGGCk7VHwfVRKYrBgMFxukNYmutjgpRaTYdMLMW0EI4yKYyaIVQBZmps6eAMNxsR0Jx/NBEEmoAUIA6ZjMeNVZc2J4tdAVkYbt0ZmOoQhh1llWkJlu2EzVbAQxbDW7dnMH15/XiaqIPHa0SKlpc+lAlss2Zrnr2QnGKiYjJRNRBEEQ6ErpTNVMYOWV/bMLsExMOeFn1rmyERUREREREbFWOZViibm3mY0z0hWJQ1MNCnWT0bLJpQPZ476nL+xNc+dTx3BNg8mKjdFs8PihBtaQjuBanH/++Rx10oyUmgjNIn//z/+XcqWO5FtUa3Uq9QayZ4Nn8Yb/8vN85APv5pEjBZ58cg8f+ZXXL/l43/L//Q61t97Mt/dN8cPHnuUbX/2nJY8tl0p0SwJCABVfJbN+B0o8hZpIocbTxJNpfDXBxr4udm4/H4CG5dDZFufX/89PiMd09o5XmKxaYTaq6yFLIvGeFI7p0BQEEATUdAd+ELbhLyQAHJ/QCAyCVjGCu4QYXYsadXt3goP5xQdwnylmK24X4gcgItCZ1MjXbVw/aD2Xs/m+lg+aJJDUJGq2R2B76GmNrjYNw3ZIx1VKzbCiI67KWI6PKAt4gU9al5ClMPbA8Xws3wNBxPE8mlaA5XoEQUDDdMkmFAZyKY5MNxHEgM0dccDAdHy2d6d5fKjUiurLxDSqrcHKJpos8Oc/2E97QuXQVB1FFPEJmKxaxFWRHb3pVgXq95+boGI4SIJAJq7ieAEX9GXmFUDMvt+v3dKBKAjz9LTjB4tWyhu2hzgzqPhUsmXnfnbMHmPY3rzzbOtJ8uNDeR46UqA3pdA9c9vFsnuXM3wsImKtEpm2PwWczmTEpVjLO0Bn4npP5byiKNCXjdHTpmPYHj94fpK67XJ+b5pK06FhuZQaJvcfyCOJofA6vydFEATUTI/LsnGu29rBY4PF46oAF+5azub02LbHvzx8jJFSk+60xlTNwnY9dvSm+OWXbaQjpeH7AXfvneShwwVkSeC58SqG4/O2y/pb13H15nZs12ffRJ3L1mfZua4NSQioWx5XbQpb1Rq2S1dap9y0Z1qCfNriCk3LxXYDKk2HrnSYVXus0GSsaiARoAgiuixhuz6G4+K60J7U8HyfsuEwXTORRZGOlMZQwaNmumzsSGDYLs9P1NAkif5sjKs2tRPXZB48nKdQtwnw6U7rbO1IcmCqRtUIYyaOyU2MmV6vbExlrGJj2C4F20MURRq2SUESGatYyJJImy7TmVQYLhqokoCihBm4pguqIpCSRcpND4/5gm52oJjjBUxULfwgaA0tU6Qwz0qTOGOTdM8GS4lYCRACgZgicfmGHATw5FCRQ1UTAtAUEd/3GSkaaJJIT1uYbzXXSPX9gImqyXCxSXebzmTRRJFE3nzpOnYPllZsqK5k4+Zc2IiKiIiIiIg4WyxlwC4WLwAwWmzw6KFxCtUGXdk0L9/ZTyamMDY5zfPPPMXu3buxbRvHcWg0mtSbBtV6g/bzLqNj43baYgppa5L//T8/wch0Bduy8Jzwz79JAarg8r73vZ+3/+Iv0bBdbv/qd/jj3/qZJR//+/7go1z+5l+jI6lxdLzM9/7pS0see/TSq/j+MxM8fqxIvvSCSFO0GGosgajFkbQ4ejyJnOnmL3+4nz3DZQoVn95X/RrxRILOXJau9iw1X8KXEzSFGD1dHdT9gMmaSdORuPq/fxGC0IyqOz5xWWR9R5y4LPFctcEN1KlbHlYxLHDIxn3EADw/wPN8XA8cz2fPUAVNCYdkSTNDcQNY0nG1fIhpAp4f0J5Ucb2Aqfq5UUTQEZfZ2HX2TdulnhtZBD8IqBgusiQiiz71mSxZYc4fPwiHj7luAFKoSQUhNHIzMYXs+gzG4SJ12w0rcv2ApCpz6fo0h6ZNFMfDcjzUGUNTFqFpe4i+QHebji6LaIrCxo4kQ0WDAFifDeeg9GdjdKf1eVF9mgwX97dRs1yKdZupisloxcTK6gwVmzQtj0xcZqJq0p+NU2yYPHKkgACMzlSz5+sWfZkYN27rauUzL2QxPe37wXGV8pm4yn0HpqiZbljpuim3aDW974cxegvvaymNPzcSLQgCDkzU6UqoXLmpnbphQgVKjcWze1fSxRcRsdaITNufAk5nMuJawrQ9JEk+qaFypq73VM8rigKiKNB0XLpSGg3LpWY6TNcsLuprww188nWHzqTCls4khu3SnY7x+ot6kWVx0SrA43YtZ3J68g2bfN2iI6kSINDXFqNqOFy5sZ11M0PNDNtjz3AZ1/PIJnSmqyZ7hsvcemEvCT18y+cSKq+/qBeAiaqJKgkMFQ3qlsv/396dx8lR13kD/9RdfU/33JNMJvcdIAchIUA4AyiC7j4iyiK66i764ILKo3H3WSX7UhZXFl0PRHwJ+LiyoiJeKBhZQJeEOyGEJBy5k8nMZI6e7umzjt/zR80005mZ7pkck57k83695pV0za+rq35TXfWtb/2OP25rQ5VPgybLiPo1CCHg1xVAkjCtNoB4Ko/asImQoWJWXQh7utOoCxs42JuFpiswVQWSLCGdd6BIMuZODmLBpCrsbE+iJ5WDDO9pcypnI+c4aAr7kMlZOBDPQggvsdeRBOrCPnxk1VSETRWH+mdQ3dLai0dfbYXruBACsIWL9kTW2z54wynE0173elcATv+spi5cKDJgOYDjWGiOmRCSBNf1uou5kKCrAgFTgako6M04kERxUDcwsZiiAJYtoPRP6mY7LiwHSDhu0URmE40MIGTKsBwXeat/Arb+5bGghpXTazC/MYz6iImgoSJgqHj78G5oqoyApgKyl9DeG08XvjODH/7kbBcNYROW7cIF0Bz1oyFsImSUbiU7nKN5cFPJD6KIiIgGCCGQz+eRy+WG/EyZMgXBYBAAsH//fmzZsmXYcrlcDu973/swc+ZMAMALL7yABx98ENlsFvG+DDriSWSyOcCxYcgu/uXLX8KSlefj+V1dePwPv8f/+/cvwbXzsHI55HNZOLZV2L6PfPHfYOE6BAwFT//pCXz9c3874r6873//X9wwcz4O9KTRs3MXnvzNz0csu//gQWiyhBd2deGNzlxhuaTqkDUTqulDwO8HVBNbOgWqDvfBVBXsTSpoOe99cDUDUHToZgA+nx9TG6JoqqnC7Nlz8cLuw9jXk0Ov5ceiL/4S/oAf9SETPRkH1UENEN5YmI11Afz5jcPoyljw6Tqazr8WthDwBw2kJcCxBVwh4OYsdGUBSRZIWQ5sW6AtnoEL9E9yK6DoBrr78nizLwvheMniZNaCrAj4NQVBQ0bQVOB2u8g578ScLgCrP1E42nG3EhkXEoCetAVdkVETUJHI2GV7j50sEUPGkilRTI75URs0sH5b+8neJADeEAiuCwQMBY4QSGacIePgKvDuB1J5r85VWUIq78BO5jCvsRYfWuENG2fZLl7eF0cyk8eUqB+z6oLoyViQZCCgKwgaKpJZ25vITshwhYRYQEUsoEORJeRtge5UHooiwXGAXV0pLK0HzphUhYCpDhmqrz7sw/493QgZKvbHvRa5u7uyiPhUyJLXG64x4kNdyESV30BXXx4Aiu57k1m7cF9bXC/FD3kGx9NHDlM2qcqHVM4pHtoEwNlT3xlbtsqvI5Vz8NstrUVJWdcVyOQdbNzZOeLQKAOfdTiZg09XMLehCrUhE7btfccef/0QDibyCBoqmqM+HErkMK26cufnOVHDPdKphUnbU8BEnzysJ+1dNB577RAiAbPsUAcnan+PZb2GKiPq1xEN6LBdgZ60hYaIiRWzaiAJgfZkDg1hEznbRU3MmylS7V/vaJ5adqVyqAWw+UAPejIWOlN5VPk0xNNeoveiOXXDnOglQAw8Ex5KVWWcP7u2MDh9X85G0FDg07yxWqv8OmbWhbxxQuvCkPuTldGAhsVTonh1fxwHejKQhEBHIofaoIZExoKiq5hRG8SSKVEETBVdfTkEdQWNVT7MawyjM5lFa28WOw+n0BTxeRda14UECVU+FaosQ5G8i/Hzu7oR8anQVRn7etLo6cvDdQQEJOiqhMlBE3kXaAxqAJLozdqI+nWk8hZSeRuWI/q7lAm4LpC1bGQg0HswD7t/oCpJ9saXclwglXOREjZcURwnS4P+VSDBkQRcCZBct9BdqkLj4lGRAOiqNxzFwqYw3ujoQyrrwBHe0AOrZtXikxfNxKa98cIxGTZlVAe8LmC2EMhlHYR8GqZGA8N+ZwxVRlOVD7YrvGM3443FPFwAWM6p8qCKiIjGbqSbXCEEXNeFLMuQJG95X18fkskkLMsq+hloFbpkyRLouhdzbt26FW+++WbhdwM/2WwWr776KlauXIm6ujoAwBNPPIE//elPRWUH///f/u3fMG3aNADAj3/8Y9x7773DlrMsC48++ijOPvtsAMA3v/lNfOYznxlx39evX49LL70UAPC73z2GT33qkyOWnTVrViFp+9Zbb+F73xu5Neofnt+G9uBMJLMW2uN9iHe0jlhWWDls2t+DurCJSFUVGltmwKcI1NXVIStU5KHClTUkbRlJvQYuvFg3FW3Eun/5Klr7HPRaQCwchC2piIaCCIf8CNdPwWOvHUJrPINY8wys/srvIOkGMnmBRMaCpimYUx9EX9ZBwFBwoDuDZNbCwV6Blqv+N4QEdPfloSpefNJYF0TUr+HtrI0Xdnchk3PgCIGcqyOTsuE4GaiKAk024UIgm7Gw5UAverM28v0P/xXJG3rAr8rIOQKOK2BoCnyajEPxHEKmhPqQlwCLpy24gyauak94iWcHgNkfmngNChz4ghpSlgvLcgvjph6LgRjUdgRMHQj0JwQrweA5HwzF63333sWTsLApguXTqnGwN4XvPv3WydzEAgdAXVhHNGDgzfY+OALQZMB239mHgbh/gCJ5LXQVybun/dWmg5hdF8Ks+hDmNUTwzFsdmBLz46yWGLbs60EyZ0OWJNiuQDrvzZPRlcgi7FNRHTDgCMCyHJw5OYJ03sW8hhBChopk2jueVs32hsI7cqi+w4ksArqCRMZGOu8gnbPhGgI5W0Jj2EDQUHEokYVPl9HZl8WU6gAUScLBeAbAyPe93ak8Nvb3eqwO6lg5o2bIffrge1nXFfjtltYhMXrAUHH5ggZk8g6efrNjSFJ2YHLiIROMoTjGH/iswetJZPLYciCO80wgZKoI5hx09eXQnsh6Q7EFDcQz1nEZSvF4OlHDPdKph0nbU8BEmjzsSK4r8NKeHgBeUme0LeZOxP4ey3oL7wVQE9ChKzJCPhUyvNaxU6sDuGxe/Ygz2ZZ7atkY8cGOe4nM82bW4KkdHXAFsGJ6DNevnIq6iFl4r09XcNbkKjy3qxPJbB6aIuGsyVXDJrMGLnzdfXn87rVWhE21cIHM2S4unF1XGI9oYNnA9vt1FU9ua8db7UnYEKgOGpheG8TkqB/NMT9WzqgBgMLFKObX4UoCrYkc0jkLk6PeIPYhwxufVpKBnv4xlXRVQX1Yx+utvZgU9aMmoONAdwbpvI2p1T4ksw4kCQiaGlbNrEV1QIG77xAWTgpj26EkLNdB3lGgKi6c/tYLjvC632Qsb1gDVQJUpT+AFhIEBLKW99T8yBEO/BpgaCqyeW+8MVu4UPqfWlda9zNDBnyahERODJtIDhsyutOiMIav5QKaKsOvexPiLWqOYcWMWmw5EIemSDhjchRrFjSgJmTgnOlK4ZicWhvGF66ch3ueehsd/V2h3rd4Es6bU1tyAj/Ae/+U2NF/byf6gyoiokqyZ88e/M///A8AwHEc2LZd+FFVFVdddVWh7G9/+1scPHiwqMzAj6Io+OIXv1goe++99+L1118vKmNZFmzbhuu6+NnPflYoe/vtt+OZZ54Zdr22bWPz5s0wDG8m8xs//vd45vHfQDgOhHDgDCoHAJ2dnaiu9q43t912G77//e+PuO/79u1Dc3MzAOD+++/HN77xjRHLfuYznykkbZ999lncddddI5b9P//n82iYNAWGKqO1tRUbNmwYsWw6nS78X1WH3pppmgbDMGAYRmFZdyqPNsvE9HlnwDQNVIcDCPp9MAwDmqZD1TTEauoLXY8XLlyED930WfRkBQ71WbCgQFE0hIN+BHwGDgen4TevHsTMmgBqZy3GDXf8GJpuwpE19OQBKBpcWQNUDVokgP3daViOi+qGufjK//sDqnu2YeXqS/HHHYex/WACqbyFzr48Ovvy2PBmB/KuQMgM4LxrPoK6sInHtrQinrbQGDLQFDGRsVw0hg20JbLoTuehyCoUw4/DfTlACNhCALaD/V0pVAdN9OUd1IYEakMG9vekkbdsSPDGdTU1Gc1RH3YeTmGH7cIVLpJZuzCxFODFPvGMA0l2YGjePAWJjAVAQtZ24ArAtl3YEmBqGi5b0IA9XSlsP5RAddBAX9aGoVtIWw6ytoO+nD3iOLJAcZLPpwLZnI2gqUHTZGiqgpxzfMbWkiUgaihI5t3+BxfjH6Wq/WHdQH1oipf01BUJi5ur8H/fMx/TakKF+4lD3alx38bhKPAmIktmHeiqDQkCugzkbK9eB3rgSZI3vvBAMjpjC2iKgKQo6M1aeHF3F9oSWSxriaG9N4u8I7C1NYmpNSE0Rf2Y3RCGqcp45s3DOGNSBDPqgnj8tUPozdoIGjq6Mzn4dRVTY0G82tqL2qCBGfUhvN3WCwB4cVc3zp+rIxbQC0P17WhL4GcvHUBnKgfLdjGrIYTJsQB8mgxNkbG4OYqs7UBRZPTlHNhuDnVhH5a0RCEdMUbtkcOlPLmtHc/t8ob6c1yBdM7BXy+dPOK97HDDJQzE6AOteJNZuyip25PO49m3O9GRzBYmGNu8rwf+mQq6U/khMb4sSwiYKlbOqMHzu7pwOJmD2X+fGzY1NMsK2hM51IeN/uEgvORoJY1re6KGe6RTE5O2p4iJOmZjzvaCJB+AoKECsjKqFnMnan+PZb2D35vK23hxd3fRRVBV5TF94QavL5/P4+m9QHXAQMhvoiagozdt49plzQj5taL3ybKES+bXw28oRU9FR9qXeMbC83u68FZHHzJ5B4unRJG1vFlFjxzTaPDfpMqnIWAomFYbxIrpMbQn82iJ+XDRnPqi9w08DX3mzQ4cjGcwtyGMTfu8RP302iAaIz6EfRH0ZSz89xuHkcpZaKn2I+zT0JO20Rj2LupVfg1vtCegSAKJjANNAaIBHefNqkFzlYHH9wFnTK5CPOtCVRUc7s1BUSRMqvKjL2dhb3caWeudbk6yBKiKBMvxkpyuq0AIF3lbQIU3K6zremUVWYGqyPDpEhojhtcNyhVI5Sz0pJ1Rh8SmgqIucMeTBCDqUzCpygdNlWHZLrrSeURMDXVhH7oSaQAJLGmOIRQ0YNsu3u5I+Cq4EQAAM3hJREFUoT3hTQIWMlU0VvnQUu3H5fMb8L+Wejexg/+Ww30/Lptbj/29GdT4dESC+phmgS3X/WokE/lBFRFRpfn2t7+NnTt3Dvu72tpadHR0FF7fdddd+POf/zxsWb/fX5S0/c1vfoM//OEPI36uEKLQIvb111/H008/PWJZ27ahaTqe39WFrngCyXj3iGWdQQkwRVEgSRJ0XYemaYWfgdeDTZ8+HatWrRpSRlEUdHZ2wu8PFMqed955uO2224rKDfzkXQlvpw3s2nwQEZ+Giy5/N345e3bh96qqAbICv2nAMHTMmjWrsN4bbrgRB6Nn4kCvhcbqEDpTDmbUh/GFy+cWemgN3OxPPut83PWflxaSIpcvaEA8Y+HJ7e3YvD+OJw4D7S8fwCXz6zF73gK8+yP/gDcOJfFmRxJdqRxaezLoU2TAUCECAUiOi12dKSSyArbZjMZIf2+YZBbTagI41OsNY5XJ2wiaOhIZC7sPp6DAwYcmAV19OWw7mMBf3u6EoXgJnKAp49WDvQjoKuY1RfDq/h7sPJyGqkioCXrzMDy14zAaIgb6shaaqvxoCEuYWh1A3hHoy9n9rVtVqLI3o31XOoemiA+KLKMmZCIW0LC/24Zlu4AkwdRUdKfy6E7l4ddlyJAKgddAlCD6X6iyBEWWkM57E9gKSYItJNiO1wsrYKioDRiwHReHkzm0JfLY35NFUFe8YSxsB7qqQIwQ2EnwknwDApoCVwK60jYSWRuKLCNoeI0CSiV9R0sA0FQNPuEga0nIjHGlg1vFjpUEIOpXUeXTURvSsb87jXjGgl9XYWoqlrRU4R+vmIeG/rFZB+jmyeshVZTWlgAhgL6cDV1T0Bz1IxYy8Nq+bvTmXMgYuG8QcODdR7jCu1ewXUCRHTi2QCrn4I3WBNr6W5KGTQ1C5LHzcBLnzazBihk1CBsqVEVGeyKDoKGiOqjDBVAT0hH2qwj7NNjCRSygY19XCnu709AlAcSA9mS2KAGZzdr4xvo30ZbIIuLX0JHNYs/hNG69ZBK6sxamVfuxZr4Xez/1Rjv2dmfQGDbQlcrjzbZkyUZFmbyDzQfisByBKr+Bw8ksNh+I412L3hly70jlYvThGl7UhUyk8u8kchdPiWJHWwKpnFMyxh/c6vapHQqcvXvQl7NxKGlBkiRMjvoR8emFydMqqUceew3SWDBpewqZiGM2GqqMsE+DBe8i2Zm2R91i7kTt77Gsd+C9Pl05LknlgfXJwtuerlQOkBX09A+LMNIFc6DLTLnPHwj8W+MZzG0IYfO+HuxoS2DVjOqySbCc7SKRtdEUMREyNSiy9/T2yLGQBl4nBj1VDcysRl/OwfvOmgRVlQt/70sXNuCl3d3IWA4iPg3pvIOulDd8Ripnw68pONibQc5yUeXXManKh7c6+tBc5bU+EQK4ZG4ddFVBZzKLl/f1YMX0auw+nEJfzsbhvixyNiC5XlJWCMBQJUyLBRDP2sjkLeRsCy4AXQbCpoqs5XjjtuoKwqaGRZOrML3Wj60HEohn8th2KImedB6O884MswqGttYFAEWRoQpvSAXHLU7eSvBmo807w7eQHbIu9I85K3nfI02VsWxqDKvn1CKdc1AT1rHx7W5sP5RA1rKhq94x9OWrF6Iu4kc8Y+GJ19vw8t5utPdmveE8ptdg5Ywa7wHDCN/BI78fpqlilhkaxRYP//4BY+0iNFEfVBERVZra2lrIstyfUFSLfqLRaFHZ888/H9XV1YXfD37P4JagAHDddddh2bJlQ9Y58DM4aXvrrbfi/e9/f9HvFUUpWvfATe5H/2EtPvbJW5B1ABsyrljYhKDfGHabv/Od7+C73/3uqOrh5ptvxs0331y0rDuVx3Nvd8Da8zLe6NMRTeURC+hYs2YN1qxZM2QdrivwxOttXuupgR5k0Wpcc80CyLI07LUuNOha5ygGcmoIzY0yYn4Dqp5DV18eiayNWNAb8zGeHn6inUzewXM7O7FxZxdsxwEgYePOw1AVCe9e2IiAruJwnzdc1+7DKW/4KAjEMxa2H0pgfmMYtuvCcYG6kAlVkVAbNlAb0tGdsjC7LgRTl5HM2phdH8LGnZ3Iuy4ihndN/9Xmg4XJaztTOagZL3YKmCrmN4VhOS62HcqgJ5XH/KYQUjkb+7rz6MvmkTJV5Kw02hM5XDqvDmvmN+DqM5rwmy0H8eT2w4j4FOzvTqMrbUEGIEsyhBCYHDWxaZ8Mv65CMSXEMxYkyZsoKmKqyORtr5Uu0D/+qJdkk2TA1BTUhQ0saY7i7Y4+WI4Lv6FgT2cayZyNar+GWFCHqal4YnsHwoaKmoCGtkQOEBKqAzrisGDqCjRZwuGUhSPJ0sDQWp5YQMOB3lwhNk7lXWSdfGH7RkqxHvm7kcpKAAxNgqnrMHQFdlca6VEkbhUAsuKtVBKAM4ZcrwTAUIGArmJKtfdgwxHAGZOjCPs1TK/2ozZsYvWcOtQEjSHvDx3x8GS8yACaIxraUpZ3TACw4dVrNm+jLe9AkYCQqcGGjazVH50L770DdVRocZtzkbMdKLKEkKnBcl0ksxbOmBxFY1U1JEhYPbuucO82MERdb8bC6tn1cCGQs1yETO+hQyygoy7sg+24eL01iUVN3ljWtUGjKLl3MJFFPGOhKqAj6tfhCm/s5MPpHGbVhQoNhyzXm3B64L5toIWt5YpR3Pf2HxijbHZSKkYfLql79rQYXtz9zsTcWcvGqhnVWF1iUrTB6wuYKpZPi2HjXu/+dFq1H3VBr2eGLEkV2SOPvQZpLJi0pZNKliUsmxrFxj3eSfZUajF3PJPKA/XRVOVHIje6ehrN5x/5lM8/U0Eq5xQFFSMZy8XmyLJd/V1dAmbxxHPNUT8mRXzI5L2UZ8ZyCuMbhUwVYZ+KnrSK6oCCnO1id2casxtyyPdPOBb2aTjYm0NN0EDecdEQ8aEv52BKdQCRA3Gv1YUGWK4DISQEdBXnzaxGfZUPm/fFsaPdgt9QkLe9Qcl0VcbkqA9NVT7EAgZ603nkbQdZy8XF8+pgOQIza+N49UACezuT6M068OkqaoMa3upIw4V3knXhtbTQVAmKrKA2aKAnnSu0GAa8hG5NwEAya6ErPfw4ZIbiBY81fhXJvIPutAVdkRALGvCrCjKWg7ztoi5sYtXMGpwxOYr/emEfOnqzaAhrgNOD2rABVZVREzLwweVT8N6zJhW6T5YLjE6Uo+0iNBEfVBERVZq1a9fiXe9615CWp8P5yle+Mur1fvjDHy7qQQFgxAdtq1atKrs+ub/bbTIQQ6x/tvPpUT9mzRj5WiFJR39Ne+fBdhq1AFrj6bJdbEu1njJUuey1Lmx6re52He4DALT3ZjG9NohwfyJnYB6C3Z0pBA0VU2L+QvwFAJ19eaiKhGjARDbvYndnEk/t6IAsSVjQFMbW1l7sOpyC35ARNk3kbSCR6x+LVZKQybtY2hLFebNqkMjYcITABbNq8fLeHqTyduGB+uFkFmGf98B+atQA7E60J3JQVAmToz7I/V2pbVcgbOqwHQFZBnpSOQRNFft6MrAdF+2JHM5qjmBSlR/dqRw0VcFZzVGoqoyQKuPyhY3Y05XGge40AoYGQ1MwozaIkE9DzvbmQ5heE8Ss+hBsW6CzLwdT84bYenV/HDnbBRyv7lVVRlBXkch6yVW/rmJufQh9eQdzG0LY2dmHrOWgMWLAzMiQBaCpCgK6itbeLKr9GpqqfIj4dQghML0miO1tCSiyBFOzkchYsPvHwe1v9IuwT/HmbDBVAH2YHAugK+siZGroy1mwXW9iW0NXoCoSfJqCzr4c8rZAlc+bGFdI/a11+7uJaf3Nd4XrImcDpgr4DQWyJCPk1zCzLoKZdUFs3h+HIknY35NGLu/CGibfpste61FTU1Af8oanMHUVubyNvC0gyd6QExnLmwDYVAHHAaBI0GUJOdtLdIdNDX5Dwez6IPK2C11VcP6sGqyYXoOAoZbuXaXJGM+07eDZPkxdQy0kOACyOQc524GpynBcAUcISIoMTVURMSXosousZUM1JNiui6zlDQWhqTIs14Xb35Mu7NOwoCkCt3/Oj5ZqP/py7/RgHNh3n6YUtXIFvPOHJktYv729cJ5ojvqgKwrqQyqQAA735VAfCUDrr89JYRNVPg2t/WPTJjMWGiMmbji7pagH3NEkCX26grOaq7BxZxeSWRuq4r0eTexdKkYfLqk7XOvccveig0X93sOvdy9qRMDnjWE7kBSvxPwCew3SWDBpSyfdkSdZnqxGdsncOriSctxaFh55AR8YN2i0F+PRXmzGUnbwRTbi03D2tBh8qoLfbZGx5UAvQqaKvOMioCvoTudgKAr0/oBj2dQopH0J9GYsNMcCuGR+A95sS6I3Y+HqxZOw4a1OtCWyyOYdGJqMKbEA/vb86Xi7ow97ujKYVQdMrfajI5lDRyKLabUBOC7Qnc5DU2QcTuXRrKtoqQ4Uxuw1NQVTaoLI5138eedh2LY3EcpeLQPhAlV+DfF03huD19ChKxJmN4TQl/Uh3/9E3nYFmiImrju7Ba8djOP7f9mF7j6rMNmBoQBhQ4GseK1JptWFEAua2NWRxP6ejNd1T3g3sxGfho5kFi/u6cblCxqw9vK5SGRt+BSBP/5x15C/y1gCohOFXYSIiE49g1uVKrLXRd3pv1YdzYQr432TO3Btqg4YQNwboqrctalUYmQ01zpVlXHd8in46Qv70NWXx/TaIK5bPgWyLBUlfIOGgr6cjYz1Tvdhn66gJuglSDt6MzjUm0POdjGrTkdbIgtVkXDDyha8sKsLv97soLsvj4ApQ9O8ZGF1SIcDgWhAR9Zykch6ddxU5T28HkiwxDMWNu7sxMF4Fo4LNFb5gU4gm3fQmsghnrER8akwdRW+/p5Ahqagqy+H+ogPkuS1Fs47XsLOdV3MqAsgnPTiq4ZB8zTUBA38/QUz8NSODmzY2YmIT8OZU6KAEMhYDtbMa0BdyMD+ngyqfBp60nk0Rnw4q6UK3/rTW/AbaSiShIaID00RE3VhE1sP9KI7lUdVQOtPpvnwgbOb8fLeHryytweKLKGl2o/trUloqjfhU9bx6isW0BFPe7FyY5UJn+6Nh+u4wKy6IF5vTSJrObBdF6qsYEq1H/VBA+dMrQK6tuJdixqxrzeH3nQejuMl6KbEfAibGnZ3pxHyaZBlCemcg/qIgTmNKjRZQU86j+k1PmxrT6GrLw9TlZG1XRiui/qAhhkNEaRzFqZWexMBtyWzOHdmNdTdEkxVgSoL7O5KozvlNQoYiC39hoqc7aA2ZKAx6kdj1I8zJkXQVGVi1+E0ElkLedvBvq60N2GxqXqJ+5wDXZVhOS7CPg0+XUVAVwp/v7OmRNEYNkf8bg4+Nziui6FtlE+cwe1F45k8VEVBNu9NPgdJgqEryOQchAwVUZ8ORZIQTwOrZlTDcbzJpS3bxmttfUjnHSiSBMgyqgLeZL4OJMysC6E75T1AEEDRuWq41vYD3/+Bfwef56ZUB3HpghDeaI3DSnjDkCiKivXb2wvn0c+tmYN//+MbhUl+P7dmDqLh4lbNR3P+lGUJl8yrR0BX0NmXR01Qx4oSQ+6NxZFJ3ePVg87sb4AyEXrkTYRtpMpw8u/WifqZJ6mV30QiyxIM7fglsY71BmgsF5vRlB22xSW8VigXzavD+m3t2NuV6n8KDjSGfVg9aOKrqH/oZ0yrDiBnu0jmLOztSsMRAkFdRSrvIGiqeL01ARcCIUNBVwrozXgJ3ZBPQ9jUoMgSVNlrhTApYmLxlCgun99QGD5g4PMUAIeSWezs6EMsYGJnVwqpnA1V9p7CR0wVy6dWIWe5iPQP7RA0FNSHfehO5TC1Jojl06uxfHo1zplRjQf/ZxfebO/D4b48NFlCTciAJMveOHGagrkNIdQGNcxJW2is8mFvVxrzGiMI+/RCl6fCTKtBHZY1niHx2LCLEBHRqWXw9bw6oON/3u6CBIFzZ9Yc04Qr43mTO3BtOtidRC28IaomxUIlr02l4qrRXutm1Abxhf4HrmFTharKyOSdooTvlFgAGcvBFQsaUeXXCvWwYkYNUnkHL+3phiJbWNgUwlktUfRlLWzY2YWu/sTLJy+aiSe3t2PrwV7EVB0XzamDI4BzplUjaKhIZu0hMeFAguXIWevjKW9s/Om1AURCJp7f3Y2+nIP5jWFEAwYcITA15kfQjGFGTQD/9dJ+RP06In4dMb+Og/EMMnkX02qCw8agNSED71s8Cboqoy2RBYQo1F2sP4kk9SfBWqoDOGd6Nap8Gi6ZW4ddnSnUBHQkst7D/Mvm1aN9Xg6b9/V4M9rrKlbNqkFN0MD0miCuWtRU+Nv/cVsbdnel0Rg2AEnCzvY+6Ko3Ee+ZzRHMrAsVGhYAQMZ2sP71Nry0pxtCCAQMFZP6J+c9uyWCjU9vxQVzatHeZ+G3W1rR1ZdHVUDFJfMb0Ze3Ec840BUZik/H1Bqvq/v06gCa+seAPdyXw+TqIP6wtQ2WLbBocgjvWtSIHW1JdPfl0VTlw3XLpyDq1wtJwSsXNqA3bSOZ85KvT25vx4F4FoYiQ0AglXdgKApWzajGmc0xrJxRjZCpFVp77utOo8qnYWZdCA1hHy6aUwtVkaHJEvryDoK6AssVhTobaWzUwY6M9bfs7Sn/ZRyFUkNG6ApgDZqITgagq0DA1AqDDrtwkLccZPIOLMdFMmejqy+HvCMQ8qnwmxqmVwcQNDWsnFGNl/d249t/egvxrDfZ8ucun4M59WFs3t+DRP8QImdPjRW1NB5tz7LhznNNQQ1/3APUBL1JyAa/98K5dVgxNYaDiSwmhU2YJYbPG+v5MxbQccUohtw7Ho53D7qJ0CNvImwjnXwTMml7zz334Otf/zoOHTqEBQsW4Jvf/CbOP//8k71ZRBPSsd4AjeViU65sqVYodSETa6+ci4ee34eudA7VfgMfWjEFdWGzKCF55GcM3Cg9/UYPQoaCxoiJ1w70QlNlnDsjhhd2d0FAwlnNEaTzNnozNppjPlw8tx7LWmJ4fncXDFWGqSnIWg4sR8ByReHkOfjzBreOWT2rDo7rImO5qPKrmFodRNBUUeXTcFZzFLomFyarm14bKrpROWNyFP/2vxYjnrHQl7Hwyv44klkL1UEd02qD2NOZQjJrY05DpHDDMDDRWzJrTbikJ7sIERGdWgZfzw3V6/oN4fVOqQmWb7Faynjd5A5cm55zHVhxb4iq0VybRoqrxnKtU1UZseA7LZFHSvgOTtgOfPZfL5mMK+Y34MkdHWhPZuG6Ljbv64GAhKCh4GA8A0mS8IU1c7E/nsH2Q73oyzmFVn9V/UMPlIoJZdmbtb4hYqIzkcbGjtcwqz6ExT4Ds+pCeLMtgXlNEdSHTZw9LYaArhZiknN70tjblUJ92ER3Kj+qsStVVS4aA3Rw3Y1U3ytm1BQeYjfHAoWxPSdV+dAYNof9+wzufeS93/u8syZX4WPnToOqyAjqCpz+v8ng7Q1AxQfOnoKrz5xU+JsNJDEdx2vhGvXr+OSFM/E357Rgf08auzr7kM5745jOrg3hQE8abYks8raD+rCBpqiJvOPi/Nm12LI/jt6MhZsvnomZdSHMqglC1xXY/XNMDCT4ARTVx+AebH97/nTs787gmTcPI5t3UC9LaIyYWDQ5incvaiyaz+Cc6dUAUJQMjwxqHR/r/w4Obi8/msTCkbF+Ty4/ineVJ+BN+GtqEjI5AVkCGqMGICmIp/LIOw4CugpHCKSyNiDJ6ElZ8Pe3UPflXViOC1mWoCkS4ikLkASaY34snlKFsE/DmvkN8Gne3CVXLmrCRbPqhiRKGyJDj62R9h0YuWfZkec5uz85XhM0h32vaaqYYQbL1tPRnD+ZWCQ6uSZc0vbhhx/GrbfeinvuuQerVq3C97//fVx55ZXYtm0bpkyZcrI3j2hCqpSLcblWKDPrQ/jHd80bEpyWMxAkTYkFML02iGTWgiLLiPgMr8umJKEmaOKiufVIZm1ctaipcLP0Znuy8ER8YPiIkZKhR7aOAVD4v9w/9tfgIK5Usnxg3NmakIEpNYGicvMawsPenFTy2E3lsIsQEdGpY/D1vDrgddmXIJC1nLLX0koSC+i4ZG4dHt/jDVFlGKMb0mGkuOpor3VjHZIq5NdwwRwvyXk4mYOpq5jbEC7qjeMAmFEXxLQjYgwAY3oYH/F5CaSByXKFELhwTt2IidiVM2oKs7mPZezKcpMbHbnNYy0/ls8rVR+D92Xgf45TXCYS0BEJ6JjfFBky7ERPxhtjuKnKX5gDojFsonGEbTkywX/k/h25H229WbTGvUl9a0MGJkW9oS8GN0g42v0fjSNj/Xjq2JO2MgCf5iXw68MmqvwaQqaKN9r7YKgyZtYFIQmBWFDH24dTaOvNQZEBxxEwdQX1ERM9aRuprIW6sImArqLLn8PiKVWYXhtEPG1Bk2W8sLsLiaxdNMTLkYnSUsfWsfQsGxgKbuB7NtEaaBDR0ZtwSdu7774bH/vYx/Dxj38cAPDNb34TTzzxBL73ve/hX//1X0/y1hHRsRjNTclwwWk5g4OkWECHBAmOC9iuA8cV3kyxll24kYwNGrh/rC1Aj9y+wf8v9xR9JMO1Hh7LzclEUSkPD4iI6NgceT1fOaMaEIDliAn3YHFwS8zjtb6judaN9To/UD6Td0r2xjnWa+/Adhw5We5IidhjiVfGuq3HY99OZFxyZHJ18LATiayNmuDwQ1Qcy+c0RLzJage3dvZaxA9N/p2I/R8S61f5ABzdEAne0AcSJkV9mB7z4/w5dXCEgCLLeKs9gazlImu5WDDJxJz6EBxXYEZNCH5DQdDU0Je1EE9baIj4sGFnJ/b3pGHqMjpTOdSFDFiOQCJjo6nKh3TewcF4ZkwT5pbd9zGcC0f6nk2U8ygRHb0JlbTN5/N4+eWXsXbt2qLla9aswYYNG07SVhHR8XQiko9HBkkrptcAktfVaOD/+RFuJCdSMpRJTyIiqhRHXj8BTIhraSU7mqRlwFTHpTfOWCbLZbwyvMHDTpyo74osS8O2dh7P7+TgBwr7u3qPah267A2JoMheInpafQhXLmrES3u68aftHbBsG1GfhqzlQhZAOu9gctQHCcDBeAa+/vktptUGcdm8eqyYXo2X93Tjf3Z2wq8qWNwSQyZvoyZo4IKZtXhs66HjMmHusd5XHO9JqYmo8k2opG1nZyccx0F9fX3R8vr6erS1tQ37nlwuh1wuV3idSCQAAJZljdvEPAOfU8kTAZ1MrJ/yTsc6UiXAcdyiLmUjGU39hHQJF8+uRt52C12Mhvu/LEvDrmcs21OJTsdjaCxYP+Wxjkpj/ZR3Muqokv8ep0uMOnD9HPz/iXQtPRW+20fGQCPFOkdjYD2OY0PTpAn39x0PR3MMncjvyok8HsbCdRzkLReG3D+ZmTzcVGLvUCXAFUDIUBAyVQASon4N15zRgNWz6xD1KVjUGMLGnYdhyzLOnBxBzraRyVtoCGo4uyXirUi4SGQsTIoYWDolDCEc1AZVXDArhp5UFgFDQdjU0JeTkMnl4bo2woaM1ngacA10pXJoqvJDFg4syy25zaX2ZSx/X37PSjsVztMnGuuotEqOUSUhROmzYwVpbW3FpEmTsGHDBqxcubKw/Ktf/Sp+/OMfY8eOHUPec/vtt2PdunVDlj/00EPw+/0ndHuJiIiI6ORJp9P40Ic+hN7eXoTD4ZO9OUUYoxIRERGdnkYbo06opG0+n4ff78fPf/5zvO997yssv+WWW7B582Y888wzQ94zXCuG5uZmdHZ2jlvwblkW1q9fj8suuwyapo3LZ04krJ/yWEelsX7KYx2Vxvopj3VUGuunvJNRR4lEAjU1NRWZtGWMOjGwjkpj/ZTHOhpZTzqP7z75BpYo+/HPL8nIuRJ8CuD0Zyh8uoywoSFkaoj4NMxvisAWAjG/jskxP5ZPiyHq14es86U9PUhkLIR9GpZNjQ4pU2p7Rnqv64qi1snjicdQaayf8lhHpVVyjDqhhkfQdR1Lly7F+vXri5K269evxzXXXDPsewzDgGEYQ5ZrmjbuB+vJ+MyJhPVTHuuoNNZPeayj0lg/5bGOSmP9lDeedVTJfwvGqBML66g01k95rKOh6iIa/vHdC/H44/tx34fPxrSaMHRVQU8mDwCI+nXIkgTLEQibKhwAmizBcsWI47rWRTRcsch/VOPGlnvvMKfsccVjqDTWT3mso9IqMUadUElbAPjsZz+LG264AcuWLcPKlStx3333Yd++fbjppptO9qYRERERERER0SgNJEaXTq0uJDGiodLZ0XJJjGOZ7I4T5RFRJZlwSdsPfOAD6Orqwr/8y7/g0KFDWLhwIX7/+9+jpaXlZG8aERERERERERER0TGbcElbAPjUpz6FT33qUyd7M4iIiIiIiIiIiIiOO/lkbwARERERERERERERvYNJWyIiIiIiIiIiIqIKwqQtERERERERERERUQVh0paIiIiIiIiIiIiogjBpS0RERERERERERFRBmLQlIiIiIiIiIiIiqiBM2hIRERERERERERFVECZtiYiIiIiIiIiIiCoIk7ZEREREREREREREFYRJWyIiIiIiIiIiIqIKwqQtERERERERERERUQVRT/YGjDchBAAgkUiM22daloV0Oo1EIgFN08btcycK1k95rKPSWD/lsY5KY/2UxzoqjfVT3smoo4F4byD+q2SMUSsT66g01k95rKPSWD/lsY5KY/2UxzoqrZJj1NMuaZtMJgEAzc3NJ3lLiIiIiGg8JJNJRCKRk70ZJTFGJSIiIjq9lItRJTERmh4cR67rorW1FaFQCJIkjctnJhIJNDc3Y//+/QiHw+PymRMJ66c81lFprJ/yWEelsX7KYx2Vxvop72TUkRACyWQSTU1NkOXKHhWMMWplYh2Vxvopj3VUGuunPNZRaayf8lhHpVVyjHratbSVZRmTJ08+KZ8dDof5BSmB9VMe66g01k95rKPSWD/lsY5KY/2UN951VOktbAcwRq1srKPSWD/lsY5KY/2UxzoqjfVTHuuotEqMUSu7yQERERERERERERHRaYZJWyIiIiIiIiIiIqIKwqTtODAMA1/+8pdhGMbJ3pSKxPopj3VUGuunPNZRaayf8lhHpbF+ymMdVR7+TcpjHZXG+imPdVQa66c81lFprJ/yWEelVXL9nHYTkRERERERERERERFVMra0JSIiIiIiIiIiIqogTNoSERERERERERERVRAmbYmIiIiIiIiIiIgqCJO2x8FXv/pVnHvuufD7/aiqqhrVe4QQuP3229HU1ASfz4cLL7wQr7/+elGZXC6HT3/606ipqUEgEMDVV1+NAwcOnIA9OPF6enpwww03IBKJIBKJ4IYbbkA8Hi/5HkmShv35+te/Xihz4YUXDvn9ddddd4L35vg7mvr5yEc+MmTfV6xYUVTmdD6GLMvCF77wBSxatAiBQABNTU348Ic/jNbW1qJyE/UYuueeezBt2jSYpomlS5fiL3/5S8nyzzzzDJYuXQrTNDF9+nTce++9Q8o88sgjmD9/PgzDwPz58/Hoo4+eqM0fF2Opo1/+8pe47LLLUFtbi3A4jJUrV+KJJ54oKvPggw8Oe07KZrMneldOiLHUz9NPPz3svu/YsaOo3Ol8DA13TpYkCQsWLCiUOZWOoT//+c94z3veg6amJkiShF/96ldl33M6nodONsao5TFGLY0xanmMUYsxRi2PMWppjFHLY4w6slMuRhV0zL70pS+Ju+++W3z2s58VkUhkVO+58847RSgUEo888oh47bXXxAc+8AHR2NgoEolEocxNN90kJk2aJNavXy9eeeUVcdFFF4kzzzxT2LZ9gvbkxLniiivEwoULxYYNG8SGDRvEwoULxVVXXVXyPYcOHSr6uf/++4UkSWLnzp2FMqtXrxaf+MQnisrF4/ETvTvH3dHUz4033iiuuOKKon3v6uoqKnM6H0PxeFxceuml4uGHHxY7duwQGzduFOecc45YunRpUbmJeAz99Kc/FZqmiR/84Adi27Zt4pZbbhGBQEDs3bt32PK7du0Sfr9f3HLLLWLbtm3iBz/4gdA0TfziF78olNmwYYNQFEXccccdYvv27eKOO+4QqqqK5557brx267gaax3dcsst4mtf+5p44YUXxJtvvim++MUvCk3TxCuvvFIo88ADD4hwODzk3DQRjbV+nnrqKQFAvPHGG0X7PvhccrofQ/F4vKhu9u/fL2KxmPjyl79cKHMqHUO///3vxT/90z+JRx55RAAQjz76aMnyp+N5qBIwRi2PMWppjFHLY4z6Dsao5TFGLY0xanmMUUs71WJUJm2PowceeGBUAbHruqKhoUHceeedhWXZbFZEIhFx7733CiG8L5amaeKnP/1poczBgweFLMvi8ccfP+7bfiJt27ZNACg6oDdu3CgAiB07dox6Pddcc424+OKLi5atXr1a3HLLLcdrU0+Ko62fG2+8UVxzzTUj/p7H0FAvvPCCAFB0QZuIx9Dy5cvFTTfdVLRs7ty5Yu3atcOW//znPy/mzp1btOzv//7vxYoVKwqvr732WnHFFVcUlbn88svFddddd5y2enyNtY6GM3/+fLFu3brC69Ge4yeCsdbPQEDc09Mz4jp5DBV79NFHhSRJYs+ePYVlp9IxNNhoAuLT8TxUSRijDo8xammMUctjjFqMMWp5jFFLY4xaHmPU0TsVYlQOj3AS7N69G21tbVizZk1hmWEYWL16NTZs2AAAePnll2FZVlGZpqYmLFy4sFBmoti4cSMikQjOOeecwrIVK1YgEomMel/a29vx2GOP4WMf+9iQ3/3kJz9BTU0NFixYgNtuuw3JZPK4bft4OJb6efrpp1FXV4fZs2fjE5/4BDo6Ogq/4zE0VG9vLyRJGtJFdCIdQ/l8Hi+//HLR3xUA1qxZM2JdbNy4cUj5yy+/HC+99BIsyypZZqIdK8DR1dGRXNdFMplELBYrWt7X14eWlhZMnjwZV111FTZt2nTctnu8HEv9LF68GI2Njbjkkkvw1FNPFf2Ox1CxH/7wh7j00kvR0tJStPxUOIaOxul2HpqoGKMyRh2MMWp5jFHfwRi1PMaopTFGLY8x6vFX6ech9YR/Ag3R1tYGAKivry9aXl9fj7179xbK6LqOaDQ6pMzA+yeKtrY21NXVDVleV1c36n350Y9+hFAohL/6q78qWn799ddj2rRpaGhowNatW/HFL34Rr776KtavX39ctn08HG39XHnllXj/+9+PlpYW7N69G//8z/+Miy++GC+//DIMw+AxdIRsNou1a9fiQx/6EMLhcGH5RDuGOjs74TjOsOePkeqira1t2PK2baOzsxONjY0jlploxwpwdHV0pH//939HKpXCtddeW1g2d+5cPPjgg1i0aBESiQT+4z/+A6tWrcKrr76KWbNmHdd9OJGOpn4aGxtx3333YenSpcjlcvjxj3+MSy65BE8//TQuuOACACMfZ6fjMXTo0CH84Q9/wEMPPVS0/FQ5ho7G6XYemqgYo3oYo3oYo5bHGPUdjFHLY4xaGmPU8hijHn+Vfh5i0nYEt99+O9atW1eyzIsvvohly5Yd9WdIklT0WggxZNmRRlNmvIy2joCh+wqMbV/uv/9+XH/99TBNs2j5Jz7xicL/Fy5ciFmzZmHZsmV45ZVXsGTJklGt+0Q50fXzgQ98oPD/hQsXYtmyZWhpacFjjz025MZhLOsdT+N1DFmWheuuuw6u6+Kee+4p+l0lH0OljPX8MVz5I5cfzTmpkh3t/vzXf/0Xbr/9dvz6178uuhFbsWJF0UQqq1atwpIlS/Dtb38b3/rWt47fho+TsdTPnDlzMGfOnMLrlStXYv/+/bjrrrsKAfFY1zkRHO3+PPjgg6iqqsJ73/veouWn2jE0VqfjeehEYIxaHmPU0hijlscY9egxRi2PMWppjFHLY4x6fFXyeYhJ2xHcfPPNZWfnnDp16lGtu6GhAYCX0W9sbCws7+joKGTvGxoakM/n0dPTU/QUuqOjA+eee+5Rfe7xNto62rJlC9rb24f87vDhw0OeVgznL3/5C9544w08/PDDZcsuWbIEmqbhrbfeOunBzHjVz4DGxka0tLTgrbfeAsBjaIBlWbj22muxe/du/Pd//3dRC4bhVNIxNJyamhooijLkqd7g88eRGhoahi2vqiqqq6tLlhnLMVgpjqaOBjz88MP42Mc+hp///Oe49NJLS5aVZRlnn3124Ts3URxL/Qy2YsUK/Od//mfhNY8hjxAC999/P2644Qboul6y7EQ9ho7G6XYeOpEYo5bHGLU0xqjlMUYdO8ao5TFGLY0xanmMUY+/ij8PnfBRc08jY53k4Wtf+1phWS6XG3aSh4cffrhQprW1dUIP0P/8888Xlj333HOjHqD/xhtvHDKb6khee+01AUA888wzR7294+1Y62dAZ2enMAxD/OhHPxJC8BgSQoh8Pi/e+973igULFoiOjo5RfdZEOIaWL18uPvnJTxYtmzdvXslJHubNm1e07KabbhoyuPqVV15ZVOaKK66Y0AP0j6WOhBDioYceEqZplh2sfoDrumLZsmXiox/96LFs6klxNPVzpL/+678WF110UeE1jyHPwIQYr732WtnPmMjH0GAY5SQPp9t5qJIwRh0eY9TSGKOWxxi1GGPU8hijlsYYtTzGqKN3KsSoTNoeB3v37hWbNm0S69atE8FgUGzatEls2rRJJJPJQpk5c+aIX/7yl4XXd955p4hEIuKXv/yleO2118QHP/hB0djYKBKJRKHMTTfdJCZPniz+9Kc/iVdeeUVcfPHF4swzzxS2bY/r/h0PV1xxhTjjjDPExo0bxcaNG8WiRYvEVVddVVTmyDoSQoje3l7h9/vF9773vSHrfPvtt8W6devEiy++KHbv3i0ee+wxMXfuXLF48eIJV0djrZ9kMik+97nPiQ0bNojdu3eLp556SqxcuVJMmjSJx1B/HVmWJa6++moxefJksXnzZnHo0KHCTy6XE0JM3GPopz/9qdA0Tfzwhz8U27ZtE7feeqsIBAKFGUDXrl0rbrjhhkL5Xbt2Cb/fLz7zmc+Ibdu2iR/+8IdC0zTxi1/8olDm2WefFYqiiDvvvFNs375d3HnnnUJV1aLZkCeSsdbRQw89JFRVFd/97neLjpV4PF4oc/vtt4vHH39c7Ny5U2zatEl89KMfFaqqFt2oTRRjrZ9vfOMb4tFHHxVvvvmm2Lp1q1i7dq0AIB555JFCmdP9GBrwN3/zN+Kcc84Zdp2n0jGUTCYL8Q4Acffdd4tNmzYVZj7neagyMEYtjzFqaYxRy2OM+g7GqOUxRi2NMWp5jFFLO9ViVCZtj4Mbb7xRABjy89RTTxXKABAPPPBA4bXruuLLX/6yaGhoEIZhiAsuuGDIE49MJiNuvvlmEYvFhM/nE1dddZXYt2/fOO3V8dXV1SWuv/56EQqFRCgUEtdff73o6ekpKnNkHQkhxPe//33h8/mKLkoD9u3bJy644AIRi8WErutixowZ4h/+4R9EV1fXCdyTE2Os9ZNOp8WaNWtEbW2t0DRNTJkyRdx4441Djo/T+RjavXv3sN/Lwd/NiXwMffe73xUtLS1C13WxZMmSolYXN954o1i9enVR+aefflosXrxY6Loupk6dOuxN5s9//nMxZ84coWmamDt3blGwMxGNpY5Wr1497LFy4403FsrceuutYsqUKULXdVFbWyvWrFkjNmzYMI57dHyNpX6+9rWviRkzZgjTNEU0GhXnnXeeeOyxx4as83Q+hoTwWo/5fD5x3333Dbu+U+kYGmitMdJ3huehysAYtTzGqKUxRi2PMWoxxqjlMUYtjTFqeYxRR3aqxaiSEP0j7BIRERERERERERHRSSef7A0gIiIiIiIiIiIioncwaUtERERERERERERUQZi0JSIiIiIiIiIiIqogTNoSERERERERERERVRAmbYmIiIiIiIiIiIgqCJO2RERERERERERERBWESVsiIiIiIiIiIiKiCsKkLREREREREREREVEFYdKWiIiIiIiIiIiIqIIwaUtERERERERERERUQZi0JSKqUGeddRYkSRry09raerI3jYiIiIhOU4xRiYjGB5O2REQV6o9//CMOHTqEJ598EjNnzkQoFMKXvvQlNDU1jcvnf+QjH8HatWsLr88991z83d/93bh8NhERERFVJsaoRETjg0lbIqIKVVdXh9/+9rd417veheXLl+Ott97CunXrxuWzXdfFY489hmuuuabwesuWLViyZMm4fD4RERERVSbGqERE44NJWyKiCvWtb30Ln/70p3HffffhJz/5Cerr64/buu+4445hu7XdfffdAIBnn30WsizjnHPOAQDs2LEDqVSKATERERHRaY4xKhHR+GDSloioAj3//PO47bbb8LOf/Qwf/vCHRyx3xx13IBgMlvz5y1/+MuR9n/70p3Ho0KHCzyc/+Um0tLTg2muvBQD85je/wXve8x7IsneZeOWVV6CqKs4444wTs8NEREREVPEYoxIRjR9JCCFO9kYQEVGx5cuXY8WKFfjWt75Vslx3dze6u7tLlpk0aRJ8Pt+Iv1+3bh0eeOABPPPMM2hpaQEAzJkzB3fddRfe8573AAA++9nP4sknn8Srr746xj0hIiIiolMFY1QiovGjnuwNICKiYm+//TZefPFFPPLII2XLxmIxxGKxo/6s4YLh7du348CBA7j00ksL5V555RV2OyMiIiI6jTFGJSIaXxwegYiowmzYsAE1NTVobm4uW/Zou54BwwfDgNft7LLLLiu0fBBCYPPmzVi6dOnx2UEiIiIimnAYoxIRjS+2tCUiqjCWZSGXyyGbzcI0zZJlb7rppsIYXyOZNGnSkGUjBcMA8Otf/xof//jHC6937tyJ3t5etmIgIiIiOo0xRiUiGl9M2hIRVZgLL7wQ2WwWH/3oR/G5z30Oc+bMQSgUGrbs0XQ9+8pXvoLvfOc7+N3vfgfDMNDW1gYAiEaj6O3txYsvvohf/epXhfKvvPIKAEBRFGzdurWwXNM0zJkzZ4x7R0REREQTEWNUIqLxxaQtEVGFmTFjBn7961/j9ttvx/nnn49cLoe1a9fijjvuOOZ1CyHw9a9/HYlEAitWrCj63XPPPYetW7finHPOQV1dXWH5pk2bAGBI+RUrVmDjxo3HvE1EREREVPkYoxIRjS9JCCFO9kYQEdHI7rnnHnzlK19Ba2vrCf+sq6++Gueddx4+//nPn/DPIiIiIqKJizEqEdGJxYnIiIgqWDwex/PPP4/ly5ePy+edd955+OAHPzgun0VEREREExNjVCKiE48tbYmIKti6devw7LPP4sEHH0RTU9PJ3hwiIiIiIsaoRETjgElbIiIiIiIiIiIiogrC4RGIiIiIiIiIiIiIKgiTtkREREREREREREQVhElbIiIiIiIiIiIiogrCpC0RERERERERERFRBWHSloiIiIiIiIiIiKiCMGlLREREREREREREVEGYtCUiIiIiIiIiIiKqIEzaEhEREREREREREVUQJm2JiIiIiIiIiIiIKgiTtkREREREREREREQVhElbIiIiIiIiIiIiogry/wHHKl3RSLeRGQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ── After merging rain into df via merge_asof ───────────────────────────────────\n",
    "\n",
    "# 3) Flag rainy periods\n",
    "df['Flag_Rain'] = (df['Rain'] > 0).astype(int)\n",
    "\n",
    "# 4) Basic QC filters\n",
    "#    Flag large T mismatches between sonic and corrected mast temp\n",
    "df['Temp_Diff']   = df['Temperature_K_2.99'] - df['Average_Temperature_Corr']\n",
    "df['Flag_Temp']   = (df['Temp_Diff'].abs() > 1).astype(int)\n",
    "# Windspeed mismatch flag: sonic vs. mast\n",
    "df['Windspeed_Diff']  = df['WS_ms_D15014_Avg'] - df['Wind_Speed']\n",
    "df['Flag_Windspeed']  = (df['Windspeed_Diff'].abs() > 1).astype(int)\n",
    "\n",
    "# 2) Drop any record flagged for rain, temp, or wind‐speed\n",
    "df = df[\n",
    "    (df['Flag_Rain']      == 0) &\n",
    "    (df['Flag_Temp']      == 0) &\n",
    "    (df['Flag_Windspeed'] == 0)\n",
    "]\n",
    "\n",
    "#    Keep only dry, non-spurious records\n",
    "#df = df[(df['Flag_Rain'] == 0) & (df['Flag_Temp'] == 0)]\n",
    "\n",
    "# 4) drop NaNs/infs in key fields\n",
    "df = df.replace([np.inf, -np.inf], np.nan)\n",
    "df = df.dropna(subset=[\n",
    "    'uw_flux_corr','vw_flux_corr','wT_Flux',\n",
    "    'Virtual_Dry_Static_Energy_2','Virtual_Dry_Static_Energy_10',\n",
    "    'WS_ms_D15008_Avg','WS_ms_D15463_Avg','Dry_Static_Energy_2.99','Average_Temperature_Corr'\n",
    "])\n",
    "\n",
    "# 5) compute u*\n",
    "#df['u_star'] = ((df['uw_flux']**2 + df['vw_flux']**2)**0.5)**0.5\n",
    "\n",
    "\n",
    "# θ at 2 m and sonic (2.99 m)\n",
    "df['theta_2']      = df['Virtual_Dry_Static_Energy_2']    \n",
    "df['theta_sonic']  = df['Virtual_Dry_Static_Energy_10'] \n",
    "\n",
    "# 5) Compute flux scales and stability parameters\n",
    "\n",
    "# friction velocity\n",
    "df['u_star']     = ((df['uw_flux_corr']**2 + df['vw_flux_corr']**2)**0.5)**0.5\n",
    "\n",
    "# temperature scale\n",
    "df['theta_star'] = - df['wT_Flux'] / df['u_star']\n",
    "\n",
    "# Monin–Obukhov length (using 10 m temp in K)\n",
    "df['L']          = - df['u_star']**3 / (KAPPA * G / df['Average_Temperature_Corr']  * df['wT_Flux'])\n",
    "\n",
    "# stability parameter\n",
    "df['zeta']       = Z_SONIC / df['L']\n",
    "\n",
    "def classify_stability(zeta):\n",
    "    if zeta < 0:\n",
    "        return 'Unstable'\n",
    "    elif zeta > 0:\n",
    "        return 'Stable'\n",
    "    else:\n",
    "        return 'Near-neutral'\n",
    "\n",
    "df['stability_class'] = df['zeta'].apply(classify_stability)\n",
    "print(df['stability_class'].value_counts(normalize=True) * 100)\n",
    "\n",
    "\n",
    "# 6) Vertical gradients by finite differences\n",
    "\n",
    "# ∂U/∂z between 2 m and 10 m\n",
    "df['dU_dz'] = (df['WS_ms_D15463_Avg'] - df['WS_ms_D15008_Avg']) / (10.0 - 2.0)\n",
    "\n",
    "# ∂θ/∂z between 2 m and 10 m (Temperatures already in K)\n",
    "df['dT_dz'] = (df['theta_sonic'] - df['theta_2'])     / (10.0  - 2.0)\n",
    "\n",
    "\n",
    "# 7) Stability functions and final QC\n",
    "\n",
    "df['phi_m'] = KAPPA * Z_SONIC / df['u_star']     * df['dU_dz']\n",
    "df['phi_h'] = KAPPA * Z_SONIC / df['theta_star'] * df['dT_dz']\n",
    "\n",
    "# remove low‐turbulence and extremes\n",
    "df = df[df['u_star'] > 0.1]\n",
    "df = df[(df['zeta'] > -1) & (df['zeta'] < 1)]\n",
    "df = df[(df['phi_m'] > 0) & (df['phi_m'] < 10)]\n",
    "df = df[(df['phi_h'] > 0) & (df['phi_h'] < 10)]\n",
    "\n",
    "\n",
    "# 8) Campaign‐wide stability‐function plot\n",
    "\n",
    "ζ       = np.linspace(-1, 1, 400)\n",
    "φm_unst = (1 - 15*ζ)**(-1/4)\n",
    "φh_unst = 0.74*((1 - 9*ζ)**(-1/2))\n",
    "φm_st   = 1 + 4.7*ζ\n",
    "φh_st   = 0.74 + 4.7*ζ\n",
    "\n",
    "#df = df[(df['phi_m'] > 0) & (df['phi_h'] > 0) ]#& (df['u_star'] > 0.1)]\n",
    "\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 5), sharey=True)\n",
    "\n",
    "# φ_m panel\n",
    "ax1.scatter(df['zeta'], df['phi_m'], s=8, alpha=0.3, label='measured')\n",
    "ax1.plot(ζ[ζ<0], φm_unst[ζ<0], 'k--', label='BD unstable')\n",
    "ax1.plot(ζ[ζ>0], φm_st[ζ>0],   'k-',  label='BD stable')\n",
    "ax1.set(xlabel=r'$\\zeta=z/L$', ylabel=r'$\\phi_m$', title='Momentum Stability')\n",
    "ax1.legend(); ax1.grid()\n",
    "\n",
    "# φ_h panel\n",
    "ax2.scatter(df['zeta'], df['phi_h'], s=8, alpha=0.3, label='measured')\n",
    "ax2.plot(ζ[ζ<0], φh_unst[ζ<0], 'k--', label='BD unstable')\n",
    "ax2.plot(ζ[ζ>0], φh_st[ζ>0],   'k-',  label='BD stable')\n",
    "ax2.set(xlabel=r'$\\zeta=z/L$', ylabel=r'$\\phi_h$', title='Heat Stability')\n",
    "ax2.legend(); ax2.grid()\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "23033ca2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median deviation: -42.94%\n",
      "Mode deviation: -42.00%\n"
     ]
    }
   ],
   "source": [
    "# --- Evaluate deviation from Businger–Dyer curve for phi_m in unstable regime (ζ < -0.1) ---\n",
    "df_unstable = df[df['zeta'] < 0].copy()\n",
    "df_unstable['phi_m_BD'] = (1 - 15 * df_unstable['zeta'])**(-1/4)\n",
    "df_unstable['rel_diff'] = (df_unstable['phi_m'] - df_unstable['phi_m_BD']) / df_unstable['phi_m_BD']\n",
    "\n",
    "# Median and mode (via binning)\n",
    "median_rel_diff = df_unstable['rel_diff'].median()\n",
    "mode_bin = df_unstable['rel_diff'].round(2).mode().iloc[0]\n",
    "\n",
    "print(f\"Median deviation: {median_rel_diff:.2%}\")\n",
    "print(f\"Mode deviation: {mode_bin:.2%}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "3987ab01",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.45560498817262407, -0.52, 1081)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Evaluate deviation from Businger–Dyer curve for phi_m in stable regime (ζ > 0)\n",
    "df_stable = df[df['zeta'] > 0].copy()\n",
    "df_stable['phi_m_BD'] = 1 + 4.7 * df_stable['zeta']\n",
    "df_stable['rel_diff'] = (df_stable['phi_m'] - df_stable['phi_m_BD']) / df_stable['phi_m_BD']\n",
    "\n",
    "# Median and mode (via binning)\n",
    "median_rel_diff_stable = df_stable['rel_diff'].median()\n",
    "mode_bin_stable = df_stable['rel_diff'].round(2).mode().iloc[0]\n",
    "num_points_stable = len(df_stable)\n",
    "\n",
    "median_rel_diff_stable, mode_bin_stable, num_points_stable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "b396389f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.6653682589180304 -0.73\n"
     ]
    }
   ],
   "source": [
    "df_stable['phi_h_BD']= 0.74 + 4.7*df_stable['zeta']\n",
    "\n",
    "df_stable['diff'] = (df_stable['phi_h'] - df_stable['phi_h_BD']) / df_stable['phi_h_BD']\n",
    "print(# Median and mode (via binning)\n",
    "df_stable['diff'].median(),\n",
    "df_stable['diff'].round(2).mode().iloc[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "d6ea540e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import mode\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "dd82f534",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median deviation: -37.97%\n",
      "Mode deviation: -46.00%\n",
      "N points: 2451\n"
     ]
    }
   ],
   "source": [
    "# Ensure clear-sky filter is available and remove missing or out-of-bounds values\n",
    "df_cs = df[\n",
    "  #  (df['CSI'] > 0.7) &\n",
    "    (df['zeta'] > -1) & (df['zeta'] < 1) &\n",
    "    (df['phi_h'] > 0) & (df['phi_h'] < 10)\n",
    "].copy()\n",
    "\n",
    "# Define theoretical BD curve for φh\n",
    "df_cs['phi_h_BD'] = np.where(\n",
    "    df_cs['zeta'] < 0,\n",
    "    0.74 * (1 - 9 * df_cs['zeta'])**(-0.5),\n",
    "    0.74 + 4.7 * df_cs['zeta']\n",
    ")\n",
    "\n",
    "\n",
    "# Compute percent deviation\n",
    "df_cs['phi_h_dev'] = 100 * (df_cs['phi_h'] - df_cs['phi_h_BD']) / df_cs['phi_h_BD']\n",
    "\n",
    "# Median and mode\n",
    "median_dev = df_cs['phi_h_dev'].median()\n",
    "mode_dev = mode(df_cs['phi_h_dev'].round()).mode  # Round to nearest integer for mode\n",
    "\n",
    "print(f\"Median deviation: {median_dev:.2f}%\")\n",
    "print(f\"Mode deviation: {mode_dev:.2f}%\")\n",
    "print(f\"N points: {len(df_cs)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "2ac65302",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median deviation: -38.55%\n",
      "Mode deviation: -34.00%\n",
      "12.444444444444445\n"
     ]
    }
   ],
   "source": [
    "# Define clear-sky daytime: CSI > 0.7 and SW_down > 50 W/m²\n",
    "df_clear_sky = df[(df['CSI'] > 0.7)]# & (df['SR15D1Dn_Irr'] > 50)]  # Replace 'SW↓' with actual column name\n",
    "df_cs_unstable = df_clear_sky[df_clear_sky['zeta'] < -0.1].copy()\n",
    "df_cs_unstable['phi_m_BD'] = (1 - 15 * df_cs_unstable['zeta'])**(-1/4)\n",
    "df_cs_unstable['rel_diff'] = (df_cs_unstable['phi_m'] - df_cs_unstable['phi_m_BD']) / df_cs_unstable['phi_m_BD']\n",
    "median_cs = df_cs_unstable['rel_diff'].median()\n",
    "mode_cs = df_cs_unstable['rel_diff'].round(2).mode().iloc[0]\n",
    "within_15_cs = (df_cs_unstable['rel_diff'].abs() <= 0.15).mean() * 100\n",
    "print(f\"Median deviation: {median_cs:.2%}\")\n",
    "print(f\"Mode deviation: {mode_cs:.2%}\")\n",
    "print(within_15_cs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "6a063368",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1600x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Create figure and subplots\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 7), sharey=True)\n",
    "\n",
    "# Common plot parameters\n",
    "scatter_kwargs = dict(s=20, alpha=0.5, edgecolors='none')\n",
    "line_kwargs_stable = dict(color='black', linewidth=2.5, label='BD stable')\n",
    "line_kwargs_unstable = dict(color='black', linestyle='--', linewidth=2.5, label='BD unstable')\n",
    "\n",
    "# --- φ_m subplot ---\n",
    "ax1.scatter(df['zeta'], df['phi_m'], **scatter_kwargs, label='Measured')\n",
    "ax1.plot(ζ[ζ < 0], φm_unst[ζ < 0], **line_kwargs_unstable)\n",
    "ax1.plot(ζ[ζ > 0], φm_st[ζ > 0], **line_kwargs_stable)\n",
    "ax1.set_xlabel(r'$\\zeta = z/L$', fontsize=20)\n",
    "ax1.set_ylabel(r'$\\phi_m$', fontsize=20)\n",
    "ax1.set_title('Momentum Stability Function', fontsize=20)\n",
    "ax1.tick_params(labelsize=18)\n",
    "ax1.legend(loc='upper left', fontsize=18)\n",
    "ax1.grid(True)\n",
    "\n",
    "# --- φ_h subplot ---\n",
    "ax2.scatter(df['zeta'], df['phi_h'], **scatter_kwargs, label='Measured')\n",
    "ax2.plot(ζ[ζ < 0], φh_unst[ζ < 0], **line_kwargs_unstable)\n",
    "ax2.plot(ζ[ζ > 0], φh_st[ζ > 0], **line_kwargs_stable)\n",
    "ax2.set_xlabel(r'$\\zeta = z/L$', fontsize=20)\n",
    "ax2.set_ylabel(r'$\\phi_h$', fontsize=20)\n",
    "ax2.set_title('Heat Stability Function', fontsize=20)\n",
    "ax2.tick_params(labelsize=18)\n",
    "ax2.legend(loc='upper left', fontsize=18)\n",
    "ax2.grid(True)\n",
    "\n",
    "# Final layout\n",
    "#fig.suptitle('Stability Functions Compared to Businger–Dyer Curves', fontsize=22)\n",
    "plt.tight_layout(rect=[0, 0, 1, 0.95])\n",
    "output_path = os.path.join(DATA_ROOT, 'stability_functions.jpg')\n",
    "plt.savefig(output_path, dpi=300)  # save at high resolution for report\n",
    "plt.show()\n"
   ]
  }
 ],
 "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": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
