{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7a8d8f9f",
   "metadata": {},
   "source": [
    "\n",
    "# Getting Started: Lagrangian Stochastic (LS) Footprint Model\n",
    "\n",
    "This notebook shows how to use the **`ls_footprint_model.py`** module to compute a simple\n",
    "2‑D flux footprint from eddy‑covariance tower data. It uses the attached example\n",
    "configuration (`US-UTE.ini`) and data file referenced therein.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68fa8701",
   "metadata": {},
   "source": [
    "\n",
    "## 1) Setup\n",
    "\n",
    "This section adjusts `sys.path` so you can import from your local source tree, then imports\n",
    "the LS model. If you've installed the package, the first `import` will also work.\n"
   ]
  },
  {
   "cell_type": "code",
   "id": "358db358",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-31T00:50:05.236950Z",
     "start_time": "2025-08-31T00:50:03.572392Z"
    }
   },
   "source": [
    "\n",
    "# --- Standard library\n",
    "import os, sys, math, pathlib, warnings\n",
    "\n",
    "# --- Third‑party\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "sys.path.append(\"../../src\")\n",
    "from fluxfootprints.ls_footprint_model import LSFootprintConfig, BackwardLSModel\n",
    "\n",
    "plt.rcParams[\"figure.dpi\"] = 120\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "print(\"Imports ready.\")\n"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Imports ready.\n"
     ]
    }
   ],
   "execution_count": 1
  },
  {
   "cell_type": "markdown",
   "id": "b811e1a9",
   "metadata": {},
   "source": [
    "\n",
    "## 2) Load site configuration and data\n",
    "\n",
    "We read `US-UTE.ini` to discover the time column, wind variables, and file names. Then we load the\n",
    "CSV it references and make a minimal set of variables needed by the LS model.\n"
   ]
  },
  {
   "cell_type": "code",
   "id": "ae5371a3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-31T00:55:32.910237Z",
     "start_time": "2025-08-31T00:55:32.004735Z"
    }
   },
   "source": [
    "\n",
    "import configparser\n",
    "from pathlib import Path\n",
    "\n",
    "# Point to the example INI and CSV (adjust paths as needed)\n",
    "ini_path = Path(\"US-UTE.ini\")\n",
    "if not ini_path.exists():\n",
    "    ini_path = Path(\"./input_data/US-UTE.ini\")  # fallback for this shared environment\n",
    "\n",
    "cfg = configparser.ConfigParser(interpolation=None)\n",
    "cfg.read(ini_path)\n",
    "\n",
    "# Pull the essentials\n",
    "date_col = cfg.get(\"DATA\", \"datestring_col\")\n",
    "date_fmt = cfg.get(\"METADATA\", \"date_parser\")\n",
    "skiprows = cfg.getint(\"METADATA\", \"skiprows\", fallback=0)\n",
    "missing_val = cfg.getfloat(\"METADATA\", \"missing_data_value\", fallback=-9999.0)\n",
    "\n",
    "# Columns for wind speed and direction\n",
    "ws_col = cfg.get(\"DATA\", \"wind_spd_col\", fallback=\"WS\")\n",
    "wd_col = cfg.get(\"DATA\", \"wind_dir_col\", fallback=\"WD\")\n",
    "\n",
    "# Resolve the climate/data CSV next to the INI, or in the same folder\n",
    "csv_rel = cfg.get(\"METADATA\", \"climate_file_path\")\n",
    "csv_path = ini_path.parent / csv_rel\n",
    "if not csv_path.exists():\n",
    "    csv_path = Path(\"/mnt/data\") / csv_rel  # fallback\n",
    "\n",
    "# Load data\n",
    "parse = lambda s: pd.to_datetime(s, format=date_fmt, errors=\"coerce\")\n",
    "df = pd.read_csv(csv_path, skiprows=skiprows)\n",
    "df[date_col] = df[date_col].apply(parse)\n",
    "df = df.dropna(subset=[date_col]).set_index(date_col).sort_index()\n",
    "\n",
    "# Basic cleaning for common missing value flags\n",
    "df = df.replace({missing_val: np.nan, -9999: np.nan, -9999.0: np.nan})\n",
    "\n",
    "print(f\"Loaded {len(df):,} rows from:\", csv_path)\n",
    "df.head()\n"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 4,463 rows from: input_data\\US-UTE_HH_202406241430_202409251400.csv\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "                          datetime_start  TIMESTAMP_END       CO2  CO2_SIGMA  \\\n",
       "TIMESTAMP_START                                                                \n",
       "2024-06-24 14:30:00  2024-06-24 14:30:00   202406241500  427.0199   0.628133   \n",
       "2024-06-24 15:00:00  2024-06-24 15:00:00   202406241530  425.9499   1.019297   \n",
       "2024-06-24 15:30:00  2024-06-24 15:30:00   202406241600  426.4163   1.965228   \n",
       "2024-06-24 16:00:00  2024-06-24 16:00:00   202406241630  426.0534   2.665907   \n",
       "2024-06-24 16:30:00  2024-06-24 16:30:00   202406241700  427.8476   1.102921   \n",
       "\n",
       "                          H2O  H2O_SIGMA        FC  FC_SSITC_TEST         LE  \\\n",
       "TIMESTAMP_START                                                                \n",
       "2024-06-24 14:30:00  17.26862   1.019290  0.069210            NaN  156.40850   \n",
       "2024-06-24 15:00:00  15.18936   0.703052  0.285446            NaN  138.30920   \n",
       "2024-06-24 15:30:00  14.87533   0.808026  1.081928            NaN  154.11530   \n",
       "2024-06-24 16:00:00  15.61140   1.002919  0.519664            NaN  135.56180   \n",
       "2024-06-24 16:30:00  15.21034   0.703084  1.147608            NaN   95.06287   \n",
       "\n",
       "                     LE_SSITC_TEST  ...  TA_1_2_1  RH_1_2_1  T_DP_1_2_1  \\\n",
       "TIMESTAMP_START                     ...                                   \n",
       "2024-06-24 14:30:00            NaN  ...  29.95141  33.26877   12.052600   \n",
       "2024-06-24 15:00:00            NaN  ...  30.02516  29.22197   10.155240   \n",
       "2024-06-24 15:30:00            NaN  ...  30.24634  28.28498    9.838229   \n",
       "2024-06-24 16:00:00            NaN  ...  30.75179  28.75255   10.538220   \n",
       "2024-06-24 16:30:00            NaN  ...  29.16274  30.77158   10.165810   \n",
       "\n",
       "                     TA_1_3_1  RH_1_3_1  T_DP_1_3_1  TA_1_4_1     PBLH_F  \\\n",
       "TIMESTAMP_START                                                            \n",
       "2024-06-24 14:30:00  30.32464  33.45364    12.46181  30.06976  1665.4670   \n",
       "2024-06-24 15:00:00  30.35956  29.77183    10.72635  30.13765  1765.9350   \n",
       "2024-06-24 15:30:00  30.69433  28.63222    10.41335  30.40344  1495.7350   \n",
       "2024-06-24 16:00:00  31.14621  29.16225    11.09066  30.90061  1491.0620   \n",
       "2024-06-24 16:30:00  29.57434  30.96792    10.63069  29.30510   341.9711   \n",
       "\n",
       "                     TS_2_1_1  SWC_2_1_1  \n",
       "TIMESTAMP_START                           \n",
       "2024-06-24 14:30:00  25.72815   22.44161  \n",
       "2024-06-24 15:00:00  25.52736   22.41975  \n",
       "2024-06-24 15:30:00  25.12511   22.32785  \n",
       "2024-06-24 16:00:00  24.63557   22.18172  \n",
       "2024-06-24 16:30:00  24.14865   22.03216  \n",
       "\n",
       "[5 rows x 61 columns]"
      ],
      "text/html": [
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       "        vertical-align: middle;\n",
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       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>datetime_start</th>\n",
       "      <th>TIMESTAMP_END</th>\n",
       "      <th>CO2</th>\n",
       "      <th>CO2_SIGMA</th>\n",
       "      <th>H2O</th>\n",
       "      <th>H2O_SIGMA</th>\n",
       "      <th>FC</th>\n",
       "      <th>FC_SSITC_TEST</th>\n",
       "      <th>LE</th>\n",
       "      <th>LE_SSITC_TEST</th>\n",
       "      <th>...</th>\n",
       "      <th>TA_1_2_1</th>\n",
       "      <th>RH_1_2_1</th>\n",
       "      <th>T_DP_1_2_1</th>\n",
       "      <th>TA_1_3_1</th>\n",
       "      <th>RH_1_3_1</th>\n",
       "      <th>T_DP_1_3_1</th>\n",
       "      <th>TA_1_4_1</th>\n",
       "      <th>PBLH_F</th>\n",
       "      <th>TS_2_1_1</th>\n",
       "      <th>SWC_2_1_1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TIMESTAMP_START</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-06-24 14:30:00</th>\n",
       "      <td>2024-06-24 14:30:00</td>\n",
       "      <td>202406241500</td>\n",
       "      <td>427.0199</td>\n",
       "      <td>0.628133</td>\n",
       "      <td>17.26862</td>\n",
       "      <td>1.019290</td>\n",
       "      <td>0.069210</td>\n",
       "      <td>NaN</td>\n",
       "      <td>156.40850</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>29.95141</td>\n",
       "      <td>33.26877</td>\n",
       "      <td>12.052600</td>\n",
       "      <td>30.32464</td>\n",
       "      <td>33.45364</td>\n",
       "      <td>12.46181</td>\n",
       "      <td>30.06976</td>\n",
       "      <td>1665.4670</td>\n",
       "      <td>25.72815</td>\n",
       "      <td>22.44161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 15:00:00</th>\n",
       "      <td>2024-06-24 15:00:00</td>\n",
       "      <td>202406241530</td>\n",
       "      <td>425.9499</td>\n",
       "      <td>1.019297</td>\n",
       "      <td>15.18936</td>\n",
       "      <td>0.703052</td>\n",
       "      <td>0.285446</td>\n",
       "      <td>NaN</td>\n",
       "      <td>138.30920</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>30.02516</td>\n",
       "      <td>29.22197</td>\n",
       "      <td>10.155240</td>\n",
       "      <td>30.35956</td>\n",
       "      <td>29.77183</td>\n",
       "      <td>10.72635</td>\n",
       "      <td>30.13765</td>\n",
       "      <td>1765.9350</td>\n",
       "      <td>25.52736</td>\n",
       "      <td>22.41975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 15:30:00</th>\n",
       "      <td>2024-06-24 15:30:00</td>\n",
       "      <td>202406241600</td>\n",
       "      <td>426.4163</td>\n",
       "      <td>1.965228</td>\n",
       "      <td>14.87533</td>\n",
       "      <td>0.808026</td>\n",
       "      <td>1.081928</td>\n",
       "      <td>NaN</td>\n",
       "      <td>154.11530</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>30.24634</td>\n",
       "      <td>28.28498</td>\n",
       "      <td>9.838229</td>\n",
       "      <td>30.69433</td>\n",
       "      <td>28.63222</td>\n",
       "      <td>10.41335</td>\n",
       "      <td>30.40344</td>\n",
       "      <td>1495.7350</td>\n",
       "      <td>25.12511</td>\n",
       "      <td>22.32785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 16:00:00</th>\n",
       "      <td>2024-06-24 16:00:00</td>\n",
       "      <td>202406241630</td>\n",
       "      <td>426.0534</td>\n",
       "      <td>2.665907</td>\n",
       "      <td>15.61140</td>\n",
       "      <td>1.002919</td>\n",
       "      <td>0.519664</td>\n",
       "      <td>NaN</td>\n",
       "      <td>135.56180</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>30.75179</td>\n",
       "      <td>28.75255</td>\n",
       "      <td>10.538220</td>\n",
       "      <td>31.14621</td>\n",
       "      <td>29.16225</td>\n",
       "      <td>11.09066</td>\n",
       "      <td>30.90061</td>\n",
       "      <td>1491.0620</td>\n",
       "      <td>24.63557</td>\n",
       "      <td>22.18172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-24 16:30:00</th>\n",
       "      <td>2024-06-24 16:30:00</td>\n",
       "      <td>202406241700</td>\n",
       "      <td>427.8476</td>\n",
       "      <td>1.102921</td>\n",
       "      <td>15.21034</td>\n",
       "      <td>0.703084</td>\n",
       "      <td>1.147608</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.06287</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>29.16274</td>\n",
       "      <td>30.77158</td>\n",
       "      <td>10.165810</td>\n",
       "      <td>29.57434</td>\n",
       "      <td>30.96792</td>\n",
       "      <td>10.63069</td>\n",
       "      <td>29.30510</td>\n",
       "      <td>341.9711</td>\n",
       "      <td>24.14865</td>\n",
       "      <td>22.03216</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 61 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 5
  },
  {
   "cell_type": "markdown",
   "id": "ef972c4c",
   "metadata": {},
   "source": [
    "\n",
    "## 3) Choose a time slice and prepare LS model inputs\n",
    "\n",
    "The LS model needs:\n",
    "- `zm` (receptor height, m)\n",
    "- `ustar` (friction velocity, m s⁻¹)\n",
    "- `L` (Monin–Obukhov length, m) — **not used** in this minimal implementation but kept for extension\n",
    "- `h` (boundary‑layer height, m)\n",
    "- `wind_dir_deg` (meteorological *from* direction, degrees)\n",
    "- surface roughness `z0` and a numerical grid/domain\n",
    "\n",
    "If your dataset has a `USTAR` column, we use that. Otherwise we estimate \\(u_*\\) from wind speed\n",
    "by the neutral log‑law (requires assumptions for `zm` and `z0`).\n"
   ]
  },
  {
   "cell_type": "code",
   "id": "dbc6685a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-31T00:55:46.143805Z",
     "start_time": "2025-08-31T00:55:46.134236Z"
    }
   },
   "source": [
    "\n",
    "KAPPA = 0.4\n",
    "\n",
    "# Assumptions you can tune for your site\n",
    "zm_default = 4.0   # receptor height [m]\n",
    "z0_default = 0.1   # roughness length [m]\n",
    "h_default  = 1000.0\n",
    "L_default  = -50.0  # kept for API compatibility; not used in the core model\n",
    "\n",
    "# Pick a representative timestamp with non‑missing wind + speed\n",
    "needed = [wd_col]\n",
    "if \"USTAR\" in df.columns:\n",
    "    needed.append(\"USTAR\")\n",
    "else:\n",
    "    needed.append(ws_col)\n",
    "\n",
    "sub = df.dropna(subset=needed).copy()\n",
    "if sub.empty:\n",
    "    raise RuntimeError(\"No rows with required variables present. Check column names and missing values.\")\n",
    "\n",
    "row = sub.iloc[0]  # take the first valid row; feel free to select by date/time\n",
    "\n",
    "# Derive ustar if needed\n",
    "if \"USTAR\" in df.columns and pd.notna(row.get(\"USTAR\")):\n",
    "    ustar = float(row[\"USTAR\"])\n",
    "else:\n",
    "    # Estimate u* with neutral log profile: u* = κ U / ln(zm / z0)\n",
    "    U = float(row[ws_col])\n",
    "    ustar = KAPPA * U / math.log(zm_default / z0_default)\n",
    "\n",
    "wind_dir_deg = float(row[wd_col])\n",
    "zm, z0, h, L = zm_default, z0_default, h_default, L_default\n",
    "\n",
    "print(f\"Selected time: {row.name}\")\n",
    "print(f\"u* = {ustar:.3f} m s⁻1 | wind_dir = {wind_dir_deg:.1f}° | zm={zm} m, z0={z0} m, h={h} m\")\n"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selected time: 2024-06-24 14:30:00\n",
      "u* = 0.285 m s⁻1 | wind_dir = 83.8° | zm=4.0 m, z0=0.1 m, h=1000.0 m\n"
     ]
    }
   ],
   "execution_count": 6
  },
  {
   "cell_type": "markdown",
   "id": "99622368",
   "metadata": {},
   "source": [
    "\n",
    "## 4) Run the model\n"
   ]
  },
  {
   "cell_type": "code",
   "id": "a69635e2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-31T00:55:59.619615Z",
     "start_time": "2025-08-31T00:55:52.986886Z"
    }
   },
   "source": [
    "\n",
    "cfg = LSFootprintConfig(\n",
    "    zm=zm,\n",
    "    ustar=ustar,\n",
    "    L=L,\n",
    "    h=h,\n",
    "    wind_dir_deg=wind_dir_deg,\n",
    "    z0=z0,\n",
    "    n_particles=20_000,   # increase for smoother fields\n",
    "    dt=0.25,\n",
    "    t_max=600.0,\n",
    "    domain=(2000.0, 2000.0),\n",
    "    dx=20.0,\n",
    "    dy=20.0,\n",
    "    seed=42,              # reproducible runs\n",
    ")\n",
    "model = BackwardLSModel(cfg)\n",
    "model.run()\n",
    "\n",
    "x, y, F = model.footprint()\n",
    "xx, fx = model.crosswind_integrated()\n",
    "\n",
    "F.min(), F.max(), F.sum()\n"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(np.float64(0.0), np.float64(0.00039797840676442895), np.float64(0.0025))"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 7
  },
  {
   "cell_type": "markdown",
   "id": "22ca4d31",
   "metadata": {},
   "source": [
    "\n",
    "## 5) Visualize the footprint\n"
   ]
  },
  {
   "cell_type": "code",
   "id": "4ea993c2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-31T00:56:04.971897Z",
     "start_time": "2025-08-31T00:56:04.352097Z"
    }
   },
   "source": [
    "\n",
    "plt.figure(figsize=(6, 5))\n",
    "plt.pcolormesh(y, x, F, shading=\"auto\")\n",
    "plt.colorbar(label=\"Footprint weight (m$^{-2}$)\")\n",
    "plt.xlabel(\"Cross‑wind distance y (m)\")\n",
    "plt.ylabel(\"Upwind distance −x (m)\")\n",
    "plt.title(\"2‑D Lagrangian flux footprint\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(6, 4))\n",
    "plt.plot(-xx, fx)  # positive axis for downwind distance\n",
    "plt.xlabel(\"Upwind distance (m)\")\n",
    "plt.ylabel(\"f(x) (m$^{-1}$)\")\n",
    "plt.title(\"Cross‑wind integrated footprint\")\n",
    "plt.grid(True)\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x600 with 2 Axes>"
      ],
      "image/png": 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NGzZg3759MvWHDx+Oli1bYtOmTfj999+lji1ZskShr7Qrs+EvBj35+fn48MMPa92ePG3btoWbmxsuXLiA//znP1LH0tPTazXf2NraGn/99ZdkMw6gfE54VFQUzp49q5LxqlKvXr2goaGBzZs34/Hjx5LywsJChISEyD3nzp07GD16NDQ1NZGcnAwzMzNs2bIFWlpaGD16NAoKCpQe16RJkwCU3ze3bt2SlJeWlmLu3LkoKyvD5MmTJeW+vr4wNDREUlKSzHrSX375JS5duoRBgwZJZYCNjIwAANeuXat2LIsXL5aao15cXIxPPvkEACTrDde1mo6diF59nFZBr6yEhARERERAU1MTb7zxBr766iuZOtbW1ggMDKx125XzkMvKyiTbR//3v//F06dP0bt3b2zatKnWgXjlphzytGvXDosWLcKsWbOwb98+vP7663j33XfRsmVLnDx5Ev/9738xYsQIbNu2Teq8Fi1aIC4uDuPGjUO/fv2k1jn+/fffMWDAABw5ckTuQ29VcXFxQf/+/bFjxw7069cPr7/+Om7evIm0tDTY2dmp7AGw2NhY9O/fH0FBQUhNTZWsc7x9+3YMHz4cu3btqtG4Z8+ejalTp6J79+545513oK2tjZ9//hlnz57FsGHD8MMPP6hkvKpibm6OsWPHYuPGjXB2doaPjw/u37+P1NRUvPnmm3IfOJs0aRKuXbuGr776SrLGrpOTEz777DN89NFHmDhxInbv3q3UuPr164eQkBCsXLkSDg4OGDFiBPT19ZGWlobs7Gy8/vrrCA4OltQ3MDDAN998g4CAAAwYMAABAQFo164dfv31V+zfvx9t2rSR+eDj4eGBVatW4f3338eIESNgYGCAVq1a4aOPPpKq17lzZ3Tt2lVqneOLFy/Cx8cH48ePV+o6FeXq6go9PT18+eWXKCwslMyLnj59ukJTR4ioAavn1TKIFFa5hFZ1r9oun/bi+c2aNROMjIyEHj16CFOmTBHS0tJqtaasIPxvCarqXk5OTpL6P/zwg9CnTx/BwMBAaNmypeDp6SkcOXKk2qWkUlNTBVdXV0FXV1do1aqV8Pbbbwt//PGH4OPjIwAQ7ty5I6lbuYzVhAkTqhxzQUGBMG3aNMHKykoQi8VChw4dhE8++UR49OiR3KXAFF2e7I8//hD8/PyEli1bCnp6ekLfvn2FPXv2CKtWrRIACDt37pSqX9UyZN9++63g5OQk6OnpCUZGRoKvr6/wf//3f1Uus1bdvfGy5cZeVNul3AShfD3ruXPnCpaWloK2trbQsWNHYdmyZcKzZ89kxvbVV18JAIS3335bbv9+fn4CAOHzzz+v0XhfthxeUlKS0L9/f8HAwEAQi8VCly5dhCVLlghFRUVy6//yyy+Cr6+vYGxsLGhrawtt27YVpk6dWuUSc5999plgb28vNGvWTLKcWqXK96u4uFgICwsTrK2thWbNmgnt27cXFi5cKHfpwZf9Pa9uKbeq/g5U9XtLS0sT+vbtK+jr68tdQ5yIGgeRIKjgCSUianBKS0vRoUMHPHnypMqHphqqsWPHYvPmzTh37hzs7OzqezhUR9zc3HDkyBGVPDhLRKQozjkmesXdvXtXau4qUD7ndsmSJbh27Rr8/f3raWTVKysrkxu0Z2ZmYsuWLejSpQsDYyIiqnOcc0z0isvKysLIkSMxePBgWFtb4+HDh8jKysLp06fRtm1bhTY5qQtPnz5F27Zt4e7uDnt7e2hpaSEnJwcHDhxAs2bNEBsbW99DJCKiJojBMdErzs7ODkOHDsXPP/+M1NRUlJSU4LXXXsOMGTMwf/58tS5tpwxtbW1MnToVBw8exPHjx/H48WMYGxsjICAAoaGh9bZkFxERNW2cc6wiDx8+RHh4OL7//nsUFhbC3t4eoaGhGDVqVH0PjYiIiIhqiJljFfH398eJEycQHR0NW1tbbN68GaNHj0ZZWZlaNosgIiIiItVj5lgFUlNT4ePjIwmIKw0ePBg5OTm4du2aZHclIiIiImq4uFqFCuzcuRMGBgYICAiQKp84cSL++ecfHD9+vJ5GRkRERES1wWkVKpCdnY3OnTtDS0v67ezWrZvkeL9+/eSem5+fL7VVKwDcv38ff/75JxwdHSEWi9UzaCIiIjV68uQJrl+/jgEDBqBVq1Z10uc///wjtfW4qrVu3Vplu4RSw8XgWAUKCgrQoUMHmXJDQ0PJ8arExcUhKipKbWMjIiKqTykpKRg+fLja+/nnn39gb9cWDx6Wqa2P5s2b49y5cwyQGzkGxyoiEokUOhYUFCQzHePs2bN499130Q2u0IOBysZIVCOiF2ZbCXL+oXmhjkij6nv8xXMkfx0qf9Yqn4///OMPomba0v1UztkXV5Tr6QAASvX/983K09bNAABPWpbXvWdbXt6uyw0AwNftfwQADDnxv3+kXws+9/JxE5FCHuMh/g/H0LZt2zrp786dO3jwsAw7vjWHTXttlbd/4fIz+E+8gTt37jA4buQYHKuAkZGR3OxwYWEhgP9lkOUxNTWtch1aPRjAQNRSNYMkqqkXg2PUIDiu5gPgi+dIAunKnzXL/29IKPtfPyItcUW7Ff1UBNBoVl4u6OgCAEr1dCXnPGlRfkyjdXndojbl5QbtnwIAutqVH2+WZyY5x0B04+XjJiLFVHzerevpgR3aa6GzneqD4zJw/YKmgg/kqYCjoyP++OMPlJSUSJWfOXMGAODg4FAfwyIiIiKiWmJwrAJ+fn54+PAhtm/fLlWekJAACwsL9OnTp55GRkRE1LSUCWUoVcOrTN4UM2qUOK1CBby9veHp6Ylp06bh/v37sLGxQVJSEtLT05GYmMg1jqnhkZk6UU1Vefdv5fkV/1hU1hHKyr92FGlX/F9L2XNfQ1ZMp/hf3Yp/aCp+1tDV+V/dyvMqp2CIy+cTo6S0vI27DwEAWhV/AoBWXvnXqPpPngAAjHYVl/dT8fNbRU4AgA44Xc3VEhFRU8fgWEV27NiBsLAwRERESLaPTkpK4vbRREREdagMglrmB3POcdPB4FhFDAwMEBMTg5iYmPoeChEREREpiMExERERNRplFf9TR7vUNPCBPCIiIiKiCswcE72qXngoTu6x2jSnwIOjknMk/ZVW/Fy57vFzc/RKS6VLKh66E4TydYiFZ8+eq1txTZXXdu9+xY+CVLlQ0SYRUaUyASgV1DDnmFOOmwxmjomIiIiIKjBzTERERI0GV6sgZTE4JiIiokajDAJKGRyTEjitgoiIiIioAjPHRA1dTR+uU/VDeC8+6Pd8+5IH4iqPvfCgXMWudM+fI3l47llJzfojIlIAp1WQspg5JiIiIiKqwMwxERERNRplgqCmpdyYOW4qmDkmIiIiIqrAzDERERE1GmUVL3W0S00Dg2OihqC63e4qy1584K6qcqlmRRVV5X8d+PwOcy+rK9n9Tt4YXjwmuZ5nICIiepUwOCYiIqJGo1RN6xyro01qmDjnmIiIiIioAjPHRERE1GiUCUCpGpK8Vc44o0aHmWMiIiIiogrMHBPVhxcfwKvJ7nBV1ZH3YF7lTnVl1Tzo92Izcp63Uxh3uyOiesLVKkhZzBwTEREREVVg5piIiIgajTKIUAqRWtqlpoGZYyIiIiKiCswcE9UHdczJrW4DESKiJqJMUM/KElytoulg5piIiIiIqAIzx0RERNRocM4xKYuZYyIiIiKiCswcExERUaNRqqbMsTrapIaJmWMiIiIiogrMHBMREVGjUQYRygTOOSbFMTgmIiKiRoMP5JGyOK2CiIiIiKgCM8dERETUaJQ/kKf63B8fyGs6mDkmIiIiIqrAzDERERE1GoKgngfyBDW0SQ0TM8dERERERBWYOSYiIqJGg5uAkLKYOSYiIiIiqsDMMRERETUaZYIGSgXV5/7K1NAmNUz8TRMRERERVWDmmIiIiBqNMohQpobcH3fIazqYOSYiIiIiqsDMMRERETUaZWparYKZ46aDmWMiIiIiogrMHBMREVGjUaqm1SrU0SY1TPxNExERERFVYOaYiIiIGo3y1So455gUx8wxEREREVEFBsdERETUaJSvVqGh8pcymeOHDx9i1qxZsLCwgI6ODpydnZGcnFyjc/Pz8xEYGAhjY2Po6enB1dUVmZmZcutmZGTA1dUVenp6MDY2RmBgIPLz82XqPXv2DFFRUbC2toZYLIa9vT1Wr14tUy8pKQlvvvkmzMzMIBaLYWFhgWHDhuHo0aMyda2trSESiWReU6dOrdF1NiScVkFERESkRv7+/jhx4gSio6Nha2uLzZs3Y/To0SgrK8OYMWOqPO/Jkyfw8PDA3bt3ERMTA1NTU8TGxsLLywsZGRkYMGCApO6RI0fg7e0NHx8f7Nq1C/n5+Zg3bx48PDxw8uRJiMViSd2goCBs3LgRixcvhouLC/bt24eZM2fiwYMHmD9/vqReQUEB+vfvj5kzZ8LY2Bg3btzA559/jjfffBOZmZlS/QNA//798emnn0qVmZmZKfv21bkmFRwfPHgQiYmJOHr0KK5fv45WrVqhV69eiIiIQM+ePaXqBgYGIiEhQaYNOzs7nDt3TqZ89erViI2NxeXLl2FhYYHAwEDMnz8f2traarseIiIiklamptUqyhRsMzU1FQcOHJAExADg7u6Oq1evIjg4GCNHjoSmpqbcczds2IDs7GwcPXoUrq6uknOdnJwQEhKC48ePS+oGBwfD1tYW27Ztg5ZWeXjXvn179O/fH9988w2mTZsGAMjJycGGDRuwdOlSBAcHAwDc3NxQUFCAJUuWYOrUqTA0NAQAfPTRRzJj8vb2homJCTZs2CATHLdq1Qp9+/ZV6H1qSJrUtIp///vfuHLlCmbOnInU1FTExMQgPz8fffv2xcGDB2Xq6+rq4tixY1KvLVu2yNRbunQpZs6cCX9/f+zbtw9BQUFYtmwZPvzww7q4LCIiImqgdu7cCQMDAwQEBEiVT5w4Ef/8849UgCvvXDs7O0lgDABaWloYN24cfvnlF+Tm5gIAcnNzceLECYwfP14SGANAv379YGtri507d0rKUlJSIAgCJk6cKDOeoqIipKenV3s9zZs3h46OjlQ/jU3jvTI5YmNjYWpqKlXm5eUFGxsbLFu2DAMHDpQ6pqGh8dJPQJWftN5//30sW7YMQPknsGfPniE8PByzZs1Cly5dVHshREREJFcZNFCmhtxfZZsXLlyQOWZiYiITX1TKzs5G586dZYLJbt26SY7369evynPfeOMNmfLKc3NycmBpaYns7Gyp8hfr/vzzz1JtmpiYoE2bNlWO50WlpaUoKytDbm4uli9fDkEQ5CYAf/zxRzRv3hzFxcXo1KkTJk+ejFmzZlWZGW+omlRwLO/GNTAwQJcuXXD9+nWF2kxPT0dxcbHcT2BhYWFISUlhcExERFRHSgWgVFD9smulQvmfvr6+MsciIyOxcOFCuecVFBSgQ4cOMuWVUxcKCgqq7LOgoEBSr7pzK/+squ7zfVTVpr6+Ppo1ayZ3PF27dsX58+cBAObm5khPT5eZjurj44NevXqhY8eOuHPnDrZu3Yq5c+fi9OnT2LhxY5XX2BA1qeBYnnv37uG3336TyRoDQFFREdq0aYNbt27B3Nwcvr6+WLRokdRNVfkJy9HRUepcc3NzGBsby/0E9rz8/HzcunVLqkzep1IiIiKqfykpKbCxsZEqMzExqfYckajqYL26Y7U9t6q6Na1X1bHt27fj0aNHuHbtGr7++mt4e3tj9+7dcHNzk9SJjY2VOmf48OFo3bo11qxZgzlz5qB79+5V9tnQNPng+MMPP8SjR48QFhYmVe7k5AQnJyc4ODgAKH8K9IsvvkBmZiZOnDgBAwMDAOWfwMRiMfT19WXafvHTmjxxcXGIiopS0dUQERE1bWUVS6+po10AsLGxQdeuXWt8npGRkdxYoLCwEID8bG9tzzUyMgIgPwtdWFgo1YeRkRFOnz4tU+/Ro0d4+vSp3PFUXm/v3r3h6+uL7t27Y+bMmfj999+rHDsAjBs3DmvWrEFWVtYrFRy/sg/kHT58WO56evJe8m4CAFiwYAE2bdqEL774QubrgdmzZ2P27Nnw9PSEp6cnlixZgu+++w7nzp3DunXrpOoq84kwKCgI2dnZUq+UlJQavQdERETUsDk6OuKPP/5ASUmJVPmZM2cAQJKEq+rcynrVnVv5Z1V1n+/D0dERt27dQl5eXq3HA5Q/ENijRw/8+eef1dYDAEEon4uiofFqhZuvbObYzs5OJkitSrt27WTKoqKisGTJEixdulTuUiXy+Pn5QV9fH1lZWZIyIyMjFBcX4/Hjx9DT05OqX1hYKBN0v8jU1LTKSfxERERUO2XQUHjZtZe1qwg/Pz+sW7cO27dvx8iRIyXlCQkJsLCwQJ8+fao9NygoCMePH5fUKykpQWJiIvr06QMLCwsAgKWlJXr37o3ExETMnTtX8gBcVlYWzp8/j1mzZknaHD58OMLDw5GQkIB58+ZJyuPj46GrqwsvL69qr6e4uBhZWVkyU0vk+e677wDglVve7ZUNjs3NzTFlyhSFzo2KisLChQuxcOFCqcWua0IQBKlPQJVzjc+cOSN1g+fl5eH27dsv/QRGREREjZe3tzc8PT0xbdo03L9/HzY2NkhKSkJ6ejoSExMlgezkyZORkJCAixcvwsrKCgAwadIkxMbGIiAgANHR0TA1NUVcXBzOnz+PjIwMqX5WrFgBT09PBAQEICgoCPn5+QgNDYWDg4PUogFdu3bF5MmTERkZCU1NTbi4uGD//v1Yu3YtlixZIjWtol+/fnj77bfRuXNntGzZEleuXMG///1vXLx4UWp5uM2bN2PHjh3w8fGBlZUV7t69i61btyI5ORmBgYFwcnJS51uscq9scKyoxYsXY+HChQgPD0dkZGStzt22bRseP34s9QnIy8sLOjo6iI+PlwqO4+PjIRKJ5D7VSkREROpRuX20OtpV1I4dOxAWFoaIiAgUFhbC3t4eSUlJGDVqlKROaWkpSktLJVMRAEAsFiMzMxMhISGYPn06Hj9+DGdnZ6SlpclswOHm5obU1FRERERg2LBh0NPTw9ChQ7Fq1Sqp3fGA8uedLC0tsXr1auTl5cHa2hoxMTGYPn26VL1+/fohOTkZV65cwaNHj2BsbAxXV1d88cUXUsvPdejQAXfv3sX8+fNRUFAAbW1tdO3aFXFxcfjggw8Uft/qi0h4/rfQyH322WeYO3cuvLy85AbGlUHv1atXMWbMGIwaNQo2NjYQiUQ4cuQIvvzyS3Ts2BHHjx+XegBv6dKlWLBgAT755BMMHjwYJ06cQHh4ON577z2sXbu21uPMycmBg4MD+sITBqKWil8wERFRPXko3EMWDiA7O7tWD7ApqvLfzhWpDnitk97LT6ilv/96jHlDsuvseqj+NKnM8Q8//ACgfG1ieTvAVH5OaNGiBczMzPD555/j5s2bKC0thZWVFWbMmIH58+fLrEwRFhaG5s2bIzY2Fp9++inatGmD0NBQmRUwiIiISL1KBZGa1jlWfZvUMDWp4Pjw4cM1qte6dWvs2LGjVm3PmDEDM2bMUGBURERERNRQNKngmIiIiBo3QU3bRwuv7uq3VEv8TRMRERERVWDmmIiIiBqNUkEDpWpY51gdbVLDxN80EREREVEFZo6JiIio0SiDcmsSV9cuNQ3MHBMRERERVWDmmIiIiBqNMjXNOS7jnOMmg79pIiIiIqIKzBwTERFRo1EKDZSqIfenjjapYeJvmoiIiIioAjPHRERE1GgIgghlgupXqxDU0CY1TMwcExERERFVYOaYiIiIGo1SiNQ055iZ46aCwTERERE1GoKgoZZl1wQu5dZk8DdNRERERFSBmWMiIiJqNMqnVah+CgSnVTQdzBwTEREREVVg5piIiIgajTKI1DLnuIyZ4yaDmWMiIiIiogrMHBMREVGjUaamOcfMHDcdzBwTEREREVVg5piIiIgajTI1rXOsjjapYeJvmoiIiIioAjPHRERE1GiUCRooZeaYlMDfNBERERFRBWaOiYiIqNEog3pWlihTeYvUUDFzTERERERUgZljIiIiajQ455iUxd80EREREVEFZo6JiIio0SgTRCgT1DDnWA1tUsPEzDERERERUQVmjomIiKjRKIUGStWQ+1NHm9Qw8TdNRERERFSBmWMiIiJqNARBPfODBUHlTVIDxcwxEREREVEFZo6JiIio0SiDBsrUkPtTR5vUMDE4JiIiokajDCKUqmMpNzVsSU0NEz8GERERERFVYOaYiIiIGg1uAkLKYuaYiIiIiKgCM8dERETUaJRnjtXwQB4zx00GM8dERERERBWYOSYiIqJGowwilKphZQmuVtF0MHNMRERERFSBmWMiIiJqNLhaBSmLmWMiIiIiogrMHBMREVGjUSZoqGm1CuYTmwr+pomIiIjU6OHDh5g1axYsLCygo6MDZ2dnJCcn1+jc/Px8BAYGwtjYGHp6enB1dUVmZqbcuhkZGXB1dYWenh6MjY0RGBiI/Px8mXrPnj1DVFQUrK2tIRaLYW9vj9WrV8vUS0pKwptvvgkzMzOIxWJYWFhg2LBhOHr0qNz+k5OT4ezsDB0dHVhYWGDWrFl4+PBhja6zIWFwTERERI2GgPKVJVT9EpQYk7+/PxISEhAZGYm0tDS4uLhg9OjR2Lx5c7XnPXnyBB4eHsjMzERMTAx27doFMzMzeHl54ciRI1J1jxw5Am9vb5iZmWHXrl2IiYlBRkYGPDw88OTJE6m6QUFBWL58OT788EPs27cPfn5+mDlzJpYtWyZVr6CgAP3790dcXBz279+Pzz//HDdv3sSbb74p0/+mTZswevRouLi4IC0tDZGRkYiPj4e/v78S71z9EAmCoMzv+5Vy+PBhuLu7yz127Ngx9O3bV6rst99+Q0hICLKysqClpYWBAwfi008/RYcOHWTOX716NWJjY3H58mVYWFggMDAQ8+fPh7a2dq3HmZOTAwcHB/SFJwxELWt9PhERUX17KNxDFg4gOzsbXbt2VXt/lf92+ie/jdYdW6u8/TsX72DHqN21vp7U1FT4+Phg8+bNGD16tKR88ODByMnJwbVr16CpqSn33Li4OHz44Yc4evQoXF1dAQAlJSVwcnKCgYEBjh8/Lqnbu3dvPHr0CL///ju0tMpnzR49elQS3E6bNg1A+fvk6OiIpUuX4pNPPpGc/69//QuJiYn4+++/YWhoWOX13Lt3DyYmJhg1ahS+++47AEBpaSnatm0LR0dH7Nu3T1J38+bNGDt2LFJTU+Ht7V3j96y+NcnM8bJly3Ds2DGpl4ODg1Sdc+fOwc3NDU+fPsX333+Pb775Bn/++SfeeOMN3Lp1S6ru0qVLMXPmTPj7+2Pfvn0ICgrCsmXL8OGHH9blZRERETV5pYJIbS9F7Ny5EwYGBggICJAqnzhxIv755x+pAFfeuXZ2dpLAGAC0tLQwbtw4/PLLL8jNzQUA5Obm4sSJExg/frwkMAaAfv36wdbWFjt37pSUpaSkQBAETJw4UWY8RUVFSE9Pr/Z6mjdvDh0dHal+srKycOPGDZk2AwICYGBgINX/q6BJPpDXqVMnmSzxiyIiIiAWi7Fnzx60aNECANCzZ0906tQJn376KVasWAGg/CuHJUuW4P3335d8HeHm5oZnz54hPDwcs2bNQpcuXdR7QURERFQnLly4IFNmYmICU1NTufWzs7PRuXNnqWASALp16yY53q9fvyrPfeONN2TKK8/NycmBpaUlsrOzpcpfrPvzzz9LtWliYoI2bdpUOZ4XlZaWoqysDLm5uVi+fDkEQZBKAFbVv7a2Nuzt7eW22ZA1yczxy5SUlGDPnj145513JIExAFhZWcHd3V3qE1B6ejqKi4vlfgITBAEpKSl1NWwiIqImT4CGZMUKVb6EipDJ19cXDg4OUq+4uLgqx1NQUCB3mkJlWUFBgdLnVv5ZVd3n+6iqTX19fTRr1kzueLp27YpmzZqhffv2+OGHH5Ceno6ePXtKtVnT/l8FTTJz/OGHH2LUqFGSpz4XLFiA119/XXL84sWLKCoqqvIT2IEDB1BcXAwdHR3JpyFHR0epeubm5jA2Nn7pp6X8/HyZaRryPpUSERFR/UtJSYGNjY1UmYmJSbXniERVT8mo7lhtz62qbk3rVXVs+/btePToEa5du4avv/4a3t7e2L17N9zc3BTqv6FrUsFxy5YtMXPmTLi5ucHIyAgXLlzAqlWr4Obmhr179+Ktt94C8PJPQIIg4M6dOzA3N0dBQQHEYjH09fXl1n3Zp6W4uDhERUWp4OqIiIhI3Tvk2djY1OqBPCMjI7mxQGFhIQD5sUZtzzUyMgIgPwtdWFgo1YeRkRFOnz4tU+/Ro0d4+vSp3PFUXm/v3r3h6+uL7t27Y+bMmfj9999l+jczM6u2/1fBKzut4vDhwxCJRDV6Vd4E3bt3x5dffglfX1+88cYbmDhxIo4ePQpzc3OEhITI9FHTT1bKfCIMCgpCdna21ItTMYiIiBoHR0dH/PHHHygpKZEqP3PmDADILAjw4rmV9ao7t/LPquo+34ejoyNu3bqFvLy8Wo8HKH8gsEePHvjzzz+l2pTXf0lJCc6dO/fSNhuaVzZzbGdnh3Xr1tWobrt27ao81qpVKwwdOhRff/01ioqKoKur+9JPYCKRCK1atQJQ/mmpuLgYjx8/hp6enkzd5+fkyGNqalrlJH4iIiKqncp1idXRriL8/Pywbt06bN++HSNHjpSUJyQkwMLCAn369Kn23KCgIBw/flxSr6SkBImJiejTpw8sLCwAAJaWlujduzcSExMxd+5cydJwWVlZOH/+PGbNmiVpc/jw4QgPD0dCQgLmzZsnKY+Pj4euri68vLyqvZ7i4mJkZWVJTS3p06cPzM3NER8fL3WN27Ztw8OHD1+5tY5f2eDY3NwcU6ZMUUlblUs9V2Z5O3bsCF1d3So/gdnY2EBHRweA9Kel52/wvLw83L59+5X7tERERESq4+3tDU9PT0ybNg3379+HjY0NkpKSkJ6ejsTEREkgO3nyZCQkJODixYuwsrICAEyaNAmxsbEICAhAdHQ0TE1NERcXh/PnzyMjI0OqnxUrVsDT0xMBAQEICgpCfn4+QkND4eDgILVoQNeuXTF58mRERkZCU1MTLi4u2L9/P9auXYslS5ZITYHo168f3n77bXTu3BktW7bElStX8O9//xsXL16UWpxAU1MTK1euxPjx4/HBBx9g9OjR+OuvvxASEgJPT8+XBtwNzSsbHKvKnTt3sGfPHsl2h0D5VwbDhg3Djh07sHLlSjRv3hwAcO3aNRw6dAizZ8+WnO/l5QUdHR3Ex8dLBcfx8fEQiUTw9fWt0+shIiJqygQBaplzrMyWaTt27EBYWBgiIiJQWFgIe3t7JCUlYdSoUZI6paWlKC0txfN7s4nFYmRmZiIkJATTp0/H48eP4ezsjLS0NAwYMECqDzc3N6SmpiIiIgLDhg2Dnp4ehg4dilWrVkEsFkvVjYuLg6WlJVavXo28vDxYW1sjJiYG06dPl6rXr18/JCcn48qVK3j06BGMjY3h6uqKL774Qmb5uXHjxkFTUxPR0dGIj4+HoaEh3nvvPSxdulTxN66eNKkd8saMGYN27dqhV69eMDY2xl9//YXPPvsMFy9eRFpaGgYNGiSpe+7cObi4uKBHjx4IDQ1FcXGx5KY+ffq01JOpS5cuxYIFC/DJJ59g8ODBOHHiBMLDw/Hee+9h7dq1tR4nd8gjIqJXXX3tkPdWYgBadlD9A2D3LhVi37itdXY9VH+aVOa4W7du2LJlC77++ms8fPgQhoaGeP3117Fx40a4uLhI1bW3t8fhw4cxb948jBgxQmr76BeXbAkLC0Pz5s0RGxuLTz/9FG3atEFoaCjCwsLq8vKIiIiISElNKjgODQ1FaGhojev37NlTZk5PVWbMmIEZM2YoOjQiIiJSAXUv5UaN3yu7lBsRERERkao1qcwxERERNW6CmpZyE9TQJjVMzBwTEREREVVg5piIiIgaDc45JmUxc0xEREREVIGZYyIiImo0yqCeLG+ZylukhoqZYyIiIiKiCswcExERUaMhqGnOscA5x00GM8dERERERBWYOSYiIqJGg6tVkLKYOSYiIiIiqsDMMRERETUaZWraIU8dbVLDxMwxEREREVEFZo6JiIio0eBqFaQsZo6JiIiIiCowc0xERESNBlerIGUpHRz/+eefyM3NRVFREYyNjWFnZ4eWLVuqYmxERERERHVKoeA4KysLX3/9NdLS0nD79m0AgCAIEIlE0NDQgLOzM8aNG4fAwEAGykRERFRnygT1ZHnLBJU3SQ1UrYLj06dPY9asWfjxxx/RuXNnjBgxAj169ICpqSl0dHRQWFiIS5cuISsrC2FhYViwYAHmz5+POXPmoFmzZuq6BiIiIiIilahVcNynTx+MHTsWn3/+OXr06FFt3UePHiE5ORkrV65ESUkJwsPDlRooERER0csIUNNqFVznuMmoVXCcnZ2NTp061aiuvr4+Jk+ejMDAQFy/fl2hwRERERHVhiCI1LLsGpdyazpqtZRbTQPj52lqasLa2rrW5xERERERPa+srAyPHz9Wax9c55iIiIgajcrto9XxorpXXFyM+Ph4BAQEwMLCAs2aNUPz5s2hp6eHXr16ISQkBL///rtK+1RqKbeUlBRs2rQJV69eRXFxsdQxkUik8sESERERUeNXVFSElStXIiYmBvfu3YO9vT08PDxkFoFYt24dPvvsM/Tr1w8rV66Eq6ur0n0rHByvWrUK8+bNg4mJCWxsbKCvr6/0YIiIiIiUwe2jG4dOnTpBX18f4eHhGDt2LMzMzOTWEwQBhw4dwrfffgt3d3esWbMGU6ZMUapvhYPjuLg4TJo0Cf/5z3+gqamp1CCIiIiIiCotWrQIEyZMeGmMKRKJMHDgQAwcOBBRUVG4du2a0n0rHBwXFBRgzJgxDIyJiIioweBqFY3DpEmTan1Ohw4d0KFDB6X7VviBvP79++OPP/5QegBERERERA2FwsHxl19+idjYWOzevRtPnz5V5ZiIiIiIFFK5fbTqX/V9ZU1DcXExzpw5I3e5tp9//rlOxqBwcGxjY4NBgwbBz88Penp6aNGihdSrZcuWqhwnERERETVix44dQ9u2beHm5gYTExNER0dLHff29q6TcSg85zgkJARr1qyBs7MzOnfujGbNmqlyXERERES1xjnHr66PP/4Yn332Gd577z2cP38eEyZMwJ9//on169dDQ0MDglA36XuFg+P4+HjMmzcPy5cvV+V4iIiIiKgJOnv2LN577z0AgJ2dHQ4fPowRI0ZgxIgRSE5OrrNxKDytorS0FJ6enqocCxEREZFSBKhjvrEIAnfIU7uWLVsiNzdX8rOOjg5SUlKgo6MDLy8vlJWV1ck4FA6OBw8ejKysLFWOhYiIiIiaqEGDBuHbb7+VKtPS0sKmTZvQsWNHFBUV1ck4FJ5WsWDBAowcORL6+vrw8fGBoaGhTB15ZURERETqIgjlL3W0S+r173//GyUlJTLlIpEI69atw4IFC+pkHAoHx05OTgCAOXPmYM6cOXLrlJaWKto8ERERETUhzZo1q3aBh3bt2tXJOBQOjiMiIiAScf4NERERNRxlEKFMDfOD1dEmvVxYWBiWLl1ap30qHBwvXLhQhcMgIiIiIpL2xRdfvDrBMREREVFDw3WOG5e6Wtv4ebVarWLlypW1flLw119/xd69e2t1DhERERFRfUzhrVVw/O2336JDhw4IDw/HuXPnqqxXXFyM7du3w8fHB/369cO9e/eUHigRERHRywhqWOO4TE3ZaGqYajWt4syZM4iNjcWnn36K5cuXw9TUFD169ICpqSl0dHRQWFiIixcv4syZMygpKYGPjw9+++03dO3aVV3jJyIiIiJSmVoFx1paWpg5cyY++ugj7Nq1C6mpqTh27BiOHj2KoqIiGBsbw97eHgsWLMCYMWPQoUMHdY2biIiISAbXOW5c6mPOsUIP5GlqasLf3x/+/v6qHg8RERGRwgSo5+E5xsb1o3///nXep8LbRxMRERERqVNGRkad98ml3IiIiKjR4FJupCxmjomIiIjU6OHDh5g1axYsLCygo6MDZ2dnJCcn1+jc/Px8BAYGwtjYGHp6enB1dUVmZqbcuhkZGXB1dYWenh6MjY0RGBiI/Px8mXrPnj1DVFQUrK2tIRaLYW9vj9WrV8vUW79+PXx9fWFtbQ1dXV3Y2Nhg2rRpuHHjhkxda2triEQimdfUqVNrdJ0NCTPHRERE1GhULr2mjnYV5e/vjxMnTiA6Ohq2trbYvHkzRo8ejbKyMowZM6bK8548eQIPDw/cvXsXMTExMDU1RWxsLLy8vJCRkYEBAwZI6h45cgTe3t7w8fHBrl27kJ+fj3nz5sHDwwMnT56EWCyW1A0KCsLGjRuxePFiuLi4YN++fZg5cyYePHiA+fPnS+pFRkbC3d0dy5Ytg6WlJc6fP4/Fixdj165dOHXqFMzMzKTG279/f3z66adSZS/WUVRKSgo2bdqEq1evori4WOqYSCTC77//rpJ+gCYWHAcGBiIhIaHK48eOHUPfvn2rrWtnZyd3jefVq1cjNjYWly9fhoWFBQIDAzF//nxoa2ur7gKIiIjolZKamooDBw5IAmIAcHd3x9WrVxEcHIyRI0dCU1NT7rkbNmxAdnY2jh49CldXV8m5Tk5OCAkJwfHjxyV1g4ODYWtri23btkFLqzy8a9++Pfr3749vvvkG06ZNAwDk5ORgw4YNWLp0KYKDgwEAbm5uKCgowJIlSzB16lQYGhoCAE6dOgVTU1NJHwMGDECPHj3g4uKCdevWITw8XGq8rVq1ksRRqrRq1SrMmzcPJiYmsLGxgb6+vsr7eF6TCo4XLFggN70/bNgwiMViuLi4SJXr6uri4MGDMmUvWrp0KRYsWIDQ0FAMHjwYJ06cQHh4OHJzc7F27VrVXgQRERFVTU1LuSm6XMXOnTthYGCAgIAAqfKJEydizJgxOH78OPr161fluXZ2dpLAGChfVnfcuHGYP38+cnNzYWlpidzcXJw4cQLLly+XBMYA0K9fP9ja2mLnzp2S4DglJQWCIGDixIky41m3bh3S09Ml2eznA+NKPXv2hKamJq5fv67YG6KAuLg4TJo0Cf/5z3+q/CChSgoHx5mZmfDw8Kjy+FdffYUZM2Yo2rxadOzYER07dpQqO3LkCG7fvo3w8HCZN1xDQ+Oln4AqP2m9//77WLZsGYDyT2DPnj1DeHg4Zs2ahS5duqj2QoiIiKheXLhwQabMxMREbiAJANnZ2ejcubNU0AoA3bp1kxyvKjjOzs7GG2+8IVNeeW5OTg4sLS2RnZ0tVf5i3Z9//lmqTRMTE7Rp06bK8VTnyJEjKC0tlbvB248//ojmzZujuLgYnTp1wuTJkzFr1iylA9qCggKMGTOmTgJjQIkH8t566y0sXLhQZnHme/fuwc/PD7Nnz1Z6cHVhw4YNEIlEmDRpkkLnp6eno7i4WO4nMEEQkJKSooJREhERUU1UrlahjhcA+Pr6wsHBQeoVFxdX5XgKCgok0xSeV1lWUFCg9LmVf1ZV9/k+qmpTX18fzZo1q3Y8Dx48QFBQENq2bSsTN/n4+CAmJgZ79+7Ftm3b0KNHD8ydOxeBgYFVtldT/fv3xx9//KF0OzWlcOY4LCwMS5YswU8//YTNmzfDzMwMJ06cwMiRI3Hnzh18//33qhynWty7dw/btm2Dh4cH2rdvL3O8qKgIbdq0wa1bt2Bubg5fX18sWrRI6qaq/ITl6Ogoda65uTmMjY1f+gksPz8ft27dkiqT96mUiIiI6l9KSgpsbGykykxMTKo9RySq+mG+6o7V9tyq6ta0XnXHiouL4e/vj6tXr+LgwYMwMDCQOh4bGyv18/Dhw9G6dWusWbMGc+bMQffu3avs82W+/PJL+Pn5oW3btvDy8kKzZs0UbqsmFA6Oo6KiMGDAAIwZMwbOzs4YO3Ys1qxZA0dHR2RmZsoNNhuapKQkFBUVYfLkyTLHnJyc4OTkBAcHBwDlXyN88cUXyMzMxIkTJyQ3RUFBAcRisdzJ4S9+WpMnLi4OUVFRKrgaIiIiUvc6xzY2NnKnFFTFyMhIbixQWFgIQH62t7bnGhkZAZCfhS4sLJTqw8jICKdPn5ap9+jRIzx9+lTueJ48eQI/Pz/897//xZ49e9CnT58qx/y8cePGYc2aNcjKylIqOLaxscGgQYPg5+cHkUgEPT09qeMikQj37t1TuP0XKfVA3sCBA3H48GH06NEDX3zxBXr37o2ffvpJZl6NOhw+fBju7u41qnvq1Ck4OzvLlG/YsAFGRkbw8/OTOfbitBBPT090794dI0aMwLp166SOK/OJMCgoSGaS/oULF+Dr61vteURERNTwOTo6IikpCSUlJVLx0ZkzZwBAkoSr6tzKes978dzKP8+cOYMhQ4bI1H2+D0dHRyQnJyMvL09q3nFV43ny5Al8fX1x6NAh7Nq1q9rnzV5UOfVWQ0O5bTVCQkKwZs0aODs7o3Pnzg03cwwAv/32G9599100a9YMHh4e2Lt3L/71r38hNjZW7qoOqmRnZ4d169bVqG67du1kyv7v//4PJ0+exMyZM6XW/quOn58f9PX1kZWVJSkzMjJCcXExHj9+LPNJprCwED179qy2TVNT0yon8RMREVHtCFB4YYmXtqsIPz8/rFu3Dtu3b8fIkSMl5QkJCbCwsKg2C+vn54egoCAcP35cUq+kpASJiYno06cPLCwsAACWlpbo3bs3EhMTMXfuXMmDa1lZWTh//jxmzZolaXP48OEIDw9HQkIC5s2bJymPj4+Hrq4uvLy8JGWVGeODBw9ix44deOutt2p17d999x0AKL28W3x8PObNm4fly5cr1U5NKRwcx8XF4eOPP0aXLl2wb98+dOzYEevXr8fMmTNx8uRJbN26FXZ2dqocqxRzc3NMmTJF4fM3bNgAALVuQxAEqU9AlXONz5w5I3WD5+Xl4fbt29V+IiQiIqLGzdvbG56enpg2bRru378PGxsbJCUlIT09HYmJiZJAdvLkyUhISMDFixdhZWUFAJg0aRJiY2MREBCA6OhomJqaIi4uDufPn0dGRoZUPytWrICnpycCAgIQFBSE/Px8hIaGwsHBQWrRgK5du2Ly5MmIjIyEpqYmXFxcsH//fqxduxZLliyRmlYxYsQIpKWlISwsDEZGRlLJwRYtWkhW49q8eTN27NgBHx8fWFlZ4e7du9i6dSuSk5MRGBgIJycnpd7D0tJSeHp6KtVGbSgcHH/00UeYOnUqvvzyS0l6e8qUKejTpw/effdd9OrVCw8ePFDZQFXpyZMnSExMRO/evWsVvG7btg2PHz+W+gTk5eUFHR0dxMfHSwXH8fHxEIlEnB5BRERUhwSoac4xFG9zx44dCAsLQ0REBAoLC2Fvb4+kpCSMGjVKUqe0tBSlpaVSq4CJxWJkZmYiJCQE06dPx+PHj+Hs7Iy0tDSp3fGA8mVkU1NTERERgWHDhkFPTw9Dhw7FqlWrZL4hj4uLg6WlJVavXo28vDxYW1sjJiYG06dPl6q3Z88eAOX7OSxdulTq2IABA3D48GEAQIcOHXD37l3Mnz8fBQUF0NbWRteuXREXF4cPPvhA4fet0uDBg5GVlYWBAwcq3VZNiIQX12KroS1btkh9PfC8R48eYdq0aZJ0ekOzZcsWjBo1CmvXrsX7778vc/zq1asYM2YMRo0aBRsbG4hEIhw5cgRffvklOnbsiOPHj0s9gFe5Ccgnn3witQnIe++9p9AmIDk5OXBwcEBfeMJA1FKpayUiIqoPD4V7yMIBZGdn1+oBNkVV/tvZ7ouPIG6r+umKT67n49rsNXV2PfQ/Z86cwciRI/HBBx/Ax8en2uXtVEHhzHFVgTFQvlZeQw2MgfIpFfr6+lKf2J7XokULmJmZ4fPPP8fNmzdRWloKKysrzJgxA/Pnz5dZmSIsLAzNmzdHbGwsPv30U7Rp0wahoaEICwuri8shIiKiSg1t0jEprXJaxpw5czBnzhy5dUpLS1XWX5PaPrrS/v37qz3eunVr7Nixo1Ztzpgxo8HtCEhERET0qouIiHjp6l+qpJLg2N/fHx999FGdzQUhIiIikkcQoKZ1jlXeJNXQwoUL67Q/5Raeq5CSkoIrV66ooikiIiIionqjkuCYiIiIqEEQKrPHqn1xznHdcnBwwM6dO2tc/8aNG5gxYwaio6OV7pvBMRERERE1KO+++y7ee+89tGvXDp988gn27duHW7duSZa6KyoqQnZ2NtavX49hw4bBysoKv/76K95++22l+26SD+QRERFR4yQIalrnWA1tUtUiIiLw/vvv48svv8T69euxYsUKiEQiiEQiaGtr4+nTpwDKN2d74403kJycDH9/f5X0zeCYiIiIGg9BVP5SR7tUp8zNzbFixQosWbIEx48fx7Fjx/DPP/+gqKgIxsbGsLe3h5ubG1577TWV9svgmIiIiIgaLG1tbbz++ut4/fXX66Q/BsdERETUaAhQz7JrfB6v6eADeUREREREFZg5JiIiosaD20eTklSSOR4wYADMzc1V0RQRERERUb1RSeb40KFDqmiGiIiISClcyo2UxTnHRERERNRg/fjjj3j48KHcYw8fPsSPP/6o0v4YHBMREVHjIajxRfXC3d0dZ8+elXvs/PnzcHd3V2l/DI6JiIiIqMESqlmb79mzZ9DQUG04y9UqiIiIqNHgnOPG4f79+7h7967k57y8PFy7dk2qTlFRERISEtCmTRuV9s3gmIiIiIgalC+++AKLFi0CAIhEIvj5+cmtJwgC5s+fr9K+GRwTERFR48F1jhuFwYMHw8DAAIIgICQkBNOnT0e7du2k6ojFYjg6OmLAgAEq7Vvp4PjevXvIysrC7du3MWTIELRu3VoV4yIiIiKiJsrV1RWurq4AgEePHuH999+HhYVFnfStVHC8ePFiREdHo6ioCCKRCCdOnEDr1q3h4eEBT09PhIaGqmqcRERERDUgqnipo12qD5GRkZL/vnXrFoqKimTqvJhVVobCj/fFxcUhKioKkydPxt69e6WeJBw6dCj27t2rkgESERERUdP14MEDTJkyBfr6+mjTpg3at28v81IlhTPHa9aswZw5c7By5UqUlpZKHevUqRP++usvpQdHREREVGucH9yozJo1C5s3b8bkyZPRrVs3iMVitfancHB86dIlvPXWW3KPNW/eXGr5DSIiIiIiRezduxfR0dGYOXNmnfSncHDcsmVL3Lx5U+6xK1euwNTUVOFBERERESmEq1U0OsXFxXB0dKyz/hSec+zh4YGVK1fi0aNHkjKRSISSkhL8+9//rjKrTERERERUU0OGDMFPP/1UZ/0pnDletGgRXFxc0KVLF/j5+UEkEmHNmjU4deoUrl27hu+//16V4yQiIiJ6OQGAOnazY+a4ThUWFkr+Ozw8HCNGjEDz5s0xbNgwGBkZydQ3NDRUWd8KB8c2Njb4+eefMWfOHMTFxUEQBHz33Xdwd3fHpk2bVLqkBhERERE1HcbGxhCJ/vchRxAEBAcHIzg4WG79FxeHUIZS6xx36dIF6enpePLkCQoKCtC6dWvo6uqqamxEREREtSII5S91tEt1JyIiQio4rksq2T5aLBbX2a4lRERERFXiA3mNwsKFC+utb4UfyJszZw7Gjh0r99i4ceOqTHsTERERETVUCgfHu3fvxuDBg+UeGzx4MHbt2qXwoIiIiIgUIojU96ImQeHgODc3F9bW1nKPWVlZ4e+//1a0aSIiIiIiAICGhgY0NTXlvrS0tGBsbAwvLy8cOnRINf0peqK+vj6uX78u99i1a9ego6Oj8KCIiIiIFCECIBLU8KrvC2vCIiIiYGVlBUNDQ0yYMAEhISEYP348DA0N0a5dO4wbNw5///03PD09ceDAAaX7U/iBPFdXV3z22WcYOXIktLW1JeXPnj3DF198gX79+ik9OCIiIiJq2gwNDdGmTRucOXMG+vr6kvKHDx/C09MTlpaWOH36NDw9PbF06VJ4enoq1Z/CmePw8HCcPXsWDg4OWLlyJTZt2oQVK1bAwcEBZ8+eRUREhFIDIyIiIqo1QY0vqhdfffUV5s6dKxUYA4CBgQHmzp2LuLg4aGlpYerUqfjtt9+U7k/hzHGfPn2we/dufPjhhwgNDZWUd+zYEbt370bv3r2VHhwRERERNW1///231CyF52lpaSEvLw8AYG5ujmfPnindn1LrHL/11lu4cOEC/vrrL9y6dQsmJibo1KmT0oMiIiIiUoi6VpbgahX1xs7ODjExMfD29oaW1v9C15KSEsTExMDOzg4AcOPGDZiYmCjdn0o2AenUqRODYiIiIiJSuUWLFuGdd96BjY0NfH19YWZmhps3byIlJQW5ubnYvn07AODAgQNwdXVVuj+lguMHDx4gLS0NV69eRVFRkdQxkUiEBQsWKDU4IiIiolrhDnmNzvDhw7Fnzx5ERERg9erVEAQBIpEIvXr1wn/+8x+89dZbAID169erpD+Fg+Pjx4/Dx8cHhYWFco8zOCYiIiIiVfDy8oKXlxceP36MO3fuoHXr1tDT01NLXwqvVjF79mxYWlril19+QXFxMcrKyqRepaWlqhwnERER0ctxtYpGTU9PD5aWlmoLjAElMsdnzpzB5s2b0atXL1WOh4iIiIiauGvXrsHc3Bza2tq4du3aS+u3a9dOZX0rHByr4mlAIiIiIpXinONGoX379jh27Bh69+4Na2triETVrxaiyhkLCgfH06dPx9dff42hQ4e+dMBERERERDX1zTffoGPHjpL/rstYU+HguKysDOfOnUP37t3h4+MDIyMjqeMikQizZ89WeoBERERENaemdY7BRGBdmjBhguS/AwMD67RvhYPj4OBgyX//3//9n8xxBsdEREREpCr37t1DVlYWbt++jSFDhqB169Zq6Ufh4Pjy5cuqHAcRERGR0kRC+Usd7VL9Wbx4MaKjo1FUVASRSIQTJ06gdevW8PDwgKenJ0JDQ1XWl8JLuVlZWb30RURERNTUPXz4ELNmzYKFhQV0dHTg7OyM5OTkGp2bn5+PwMBAGBsbQ09PD66ursjMzJRbNyMjA66urtDT04OxsTECAwORn58vU+/Zs2eIioqCtbU1xGIx7O3tsXr1apl669evh6+vL6ytraGrqwsbGxtMmzYNN27ckNt/cnIynJ2doaOjAwsLC8yaNQsPHz6s0XVWJy4uDlFRUZg8eTL27t0LQfjfJ5WhQ4di7969SvfxPIWD44biwYMHCAkJweDBg2FiYgKRSISFCxdWWf+3337DoEGDYGBggFatWsHf3x+XLl2SW3f16tWwt7eHWCxG+/btERUVhWfPnsnUq82NS0RERGrUANc59vf3R0JCAiIjI5GWlgYXFxeMHj0amzdvrva8J0+ewMPDA5mZmYiJicGuXbtgZmYGLy8vHDlyRKrukSNH4O3tDTMzM+zatQsxMTHIyMiAh4cHnjx5IlU3KCgIy5cvx4cffoh9+/bBz88PM2fOxLJly6TqRUZGwsDAAMuWLUN6ejpCQkKwZ88e9OzZEzdv3pSqu2nTJowePRouLi5IS0tDZGQk4uPj4e/vr/gbV2HNmjWYM2cOvvrqKwwePFjqWKdOnfDXX38p3cfzlNo++scff8RXX32FP/74Q+720RcvXlRqcDVRUFCAtWvXwsnJCb6+vtVuHXju3Dm4ubnB2dkZ33//PYqLixEREYE33ngDp0+fllqebunSpViwYAFCQ0MxePBgnDhxAuHh4cjNzcXatWsl9Spv3Lt37yImJgampqaIjY2Fl5cXMjIyMGDAALVePxERETVcqampOHDgADZv3ozRo0cDANzd3XH16lUEBwdj5MiR0NTUlHvuhg0bkJ2djaNHj8LV1VVyrpOTE0JCQnD8+HFJ3eDgYNja2mLbtm3Q0ioP79q3b4/+/fvjm2++wbRp0wAAOTk52LBhA5YuXSp5fszNzQ0FBQVYsmQJpk6dCkNDQwDAqVOnYGpqKuljwIAB6NGjB1xcXLBu3TqEh4cDKF9GLTg4GIMHD8a6desk42zevDnGjh2LtLQ0eHt7K/weXrp0SbJF9IuaN2+Ou3fvKty2PApnjv/73//Cw8MD9+7dwx9//AF7e3tYWlri2rVr0NLSwptvvqnKcVbJysoKd+7cwZEjR7B8+fJq60ZEREAsFmPPnj0YMmQI/P39sXfvXty6dQuffvqppF7lDfL+++9j2bJlcHNzQ3BwMCIjI7F+/XqcPXtWUrfyxv3+++8xduxYeHp6Ytu2bbC1tUVISIjarpuIiIgavp07d8LAwAABAQFS5RMnTsQ///wjFeDKO9fOzk4SGAOAlpYWxo0bh19++QW5ubkAgNzcXJw4cQLjx4+XBMYA0K9fP9ja2mLnzp2SspSUFAiCgIkTJ8qMp6ioCOnp6ZKy5wPjSj179oSmpiauX78uKcvKysKNGzdk2gwICICBgYFU/4po2bKlTKa60pUrV+SOUxkKB8eRkZGYOHGi5E1csmQJfvrpJ/z22294+PChStLoNSESiWq09l1JSQn27NmDd955By1atJCUW1lZwd3dXeoXl56ejuLiYrk3jiAISElJkZTV9MYlIiIi9at8IE8dLwC4cOECcnJypF7y5vVWys7ORufOnaWCVgDo1q2b5Hh151bWk3duTk6OVBtV1X2+j+zsbJiYmKBNmza1Hg9QPn2jtLQUXbt2lWpTXv/a2tqwt7d/aZsv4+HhgZUrV+LRo0eSMpFIhJKSEvz73/+uMqusKIWnVWRnZ2Pu3LmSwLRyZ5Ju3bphwYIFWLRoEYYNG6aaUarAxYsXUVRUVOWNc+DAARQXF0NHR0fyS3R0dJSqZ25uDmNjY5mb7I033pDbJlB+41paWlY5rvz8fNy6dUuq7MKFCzW/MCIiIqozvr6+MmWRkZFVPu9UUFCADh06yJRXTl0oKCiosq+CggJJverOrfyzqrrP91FVm/r6+mjWrFm143nw4AGCgoLQtm1bTJo0SarN6vq/cuVKlW3WxKJFi+Di4oIuXbrAz88PIpEIa9aswalTp3Dt2jV8//33SrX/IoWD48ePH8PAwAAaGhoQi8W4ffu25Ji9vb3U1IOG4GW/OEEQcOfOHZibm6OgoABisRj6+vpy69bkJqvJTQ/87wlMIiIiUgFBTZuAVLSZkpICGxsbqUPPP7MkT3XfcL/s2+/anFtV3ZrWq+5YcXEx/P39cfXqVRw8eBAGBgY1PlfZ3e1sbGzw888/Y86cOYiLi4MgCPjuu+/g7u6OTZs2oV27dkq1/yKFg+N27dpJ5n906dIFe/fulUy2PnLkiMyOeTVx+PBhuLu716juqVOn4OzsXOs+anpDqOJmfNkxoPyJ0RfnIV24cEHuJ1MiIiKqXzY2NlJTCl7GyMhIbqKssLAQgPykXW3PrYy5qqr7fB9GRkY4ffq0TL1Hjx7h6dOncsfz5MkT+Pn54b///S/27NmDPn36yIyzsn8zM7Nq+1dUly5dkJ6ejidPnqCgoACtW7eGrq6u0u3Ko3Bw7ObmhsOHD2PEiBF4//33ERQUhD/++ANisRj79+/Hxx9/XOs27ezsJE85vkxtPyW87MYRiURo1aqVpG5xcTEeP34MPT09mbo9e/aUalfRmx4on+yu6onkRERETZaSy65V264CHB0dkZSUhJKSEql5x2fOnAEAODg4VHtuZb3nvXhu5Z9nzpzBkCFDZOo+34ejoyOSk5ORl5cnNe+4qvE8efIEvr6+OHToEHbt2gUPDw+546xso0uXLpLykpISnDt3TrJKhyqIxWJYWFiorD15FA6Oo6KiJAHg1KlT8fjxY2zatAkikQjh4eEICwurdZvm5uaYMmWKokOqVseOHaGrq1vlTWZjYwMdHR0A0r/k5z8d5eXl4fbt2zI3WU1uXCIiImp6/Pz8sG7dOmzfvh0jR46UlCckJMDCwkImC/viuUFBQTh+/LikXklJCRITE9GnTx9JkGhpaYnevXsjMTERc+fOlSwNl5WVhfPnz2PWrFmSNocPH47w8HAkJCRg3rx5kvL4+Hjo6urCy8tLUlaZMT548CB27NhR5YNvffr0gbm5OeLj46Wucdu2bSpZpMHFxQWenp7w8PDA66+/DrFYrFR7L6NwcGxsbAxjY2PJz3PmzMGcOXNUMih10NLSwrBhw7Bjxw6sXLkSzZs3BwBcu3YNhw4dwuzZsyV1vby8oKOjg/j4eKmbNj4+HiKRSGrKQ01vXCIiIqojDWirZ29vb3h6emLatGm4f/8+bGxskJSUhPT0dCQmJkoC2cmTJyMhIQEXL16U7DI8adIkxMbGIiAgANHR0TA1NUVcXBzOnz+PjIwMqX5WrFgBT09PBAQEICgoCPn5+QgNDYWDg4PU6ltdu3bF5MmTERkZCU1NTbi4uGD//v1Yu3YtlixZIvWN94gRI5CWloawsDAYGRkhKytLcqxFixaSLLGmpiZWrlyJ8ePH44MPPsDo0aPx119/ISQkBJ6enlIBtyLMzc0RFxeH6Oho6OjooH///hg0aBAGDRok9W2+qigcHA8cOBBxcXGwt7eXOfbnn39i6tSpOHjwoFKDq6m0tDQ8evQIDx48AACcPXsW27ZtAwAMGTJEMjUiKioKLi4uGDp0KEJDQyWbgBgbG0tNAzE0NER4eDgWLFgAQ0NDySYgCxcuxJQpU6S+MqjNjUtERERNz44dOxAWFoaIiAgUFhbC3t4eSUlJGDVqlKROaWkpSktLpbZGFovFyMzMREhICKZPn47Hjx/D2dkZaWlpMpuMubm5ITU1FRERERg2bBj09PQwdOhQrFq1SibTGhcXB0tLS6xevRp5eXmwtrZGTEwMpk+fLlVvz549AMo3Rlu6dKnUsQEDBuDw4cOSn8eNGwdNTU1ER0cjPj4ehoaGeO+992TOU8Tu3btRWlqK48ePIyMjA5mZmYiIiMD8+fPRunVrDBw4UKUrVoiE538LtaChoYGsrCz07t1b5tivv/6K3r17S5Z3Uzdra2tcvXpV7rHLly/D2tpaamzz5s3DsWPHoKWlhYEDB+LTTz9Fx44dZc796quvEBsbiytXrqBNmzaYOHEiwsLCoK2tLVXv5s2bki0VK2/cxYsXY9CgQQpdT05ODhwcHNAXnjAQtVSoDSIiovr0ULiHLBxAdnZ2rR5gU1Tlv52vBQej2Qtr+KrC07w8/L1qVZ1dD1Xvl19+QUREBPbv3w+RSKTSmFOp7aOrcuPGDZkH2dSpNuvn9ezZs8YZ3RkzZmDGjBkvrWdmZoaEhIQaj4GIiIiIai4vLw8ZGRk4cOAAMjMzcePGDbRt2xYTJ05UOBlZlVoFx7t27cKuXbskPy9evFhmbb+ioiIcPnwY3bt3V80IiYiIiGqqga1WQcpzdHTE2bNn0bp1a7i5uSE8PBweHh7o1KmTWvqrVXB89uxZbN26FUD5+r0HDx6Ehob0DtRisRiOjo6IiYlR3SiJiIiIqEnKycmBrq4uRowYAS8vLwwcOBAtWrRQW3+1Co4/+eQTfPLJJwDK5xwfOnRI7pxjIiIionrBzHGjc/LkSWRkZCAjIwNjxoxBSUkJevXqBU9PT3h6esLV1VWy6ocqKDznuKysTGWDICIiIiKSp0ePHujRowdCQkLw5MkT/Pe//8WBAwewZ88eLFmyBAYGBrh3757K+tN4eRX5/vnnH5w/f17yc0lJCVauXIlRo0bhm2++UcngiIiIiGpDJKjvRfUvLy8PV65cwdWrV3H9+nUIgoBHjx6ptA+FM8f/+te/YGVlhdjYWADAkiVLsGjRIrRq1Qpbt25Fs2bNMG7cOJUNlIiIiIianu3bt0umVVy6dAmCIMDW1hbvvvsuPDw8MHDgQJX2p3Dm+NSpU3B3d5f8vG7dOsyePRuFhYX417/+JQmaiYiIiOqMIFLfi+pFQEAAdu/eDVdXV3zzzTe4fv06zp07hzVr1sDPzw8tW6p2TwiFM8cFBQVoU7HI9h9//IEbN24gMDAQAPDOO+9gy5YtKhkgERERETVd2dnZUrsTq5vCwXHLli2Rn58PAPjxxx9haGgIR0dHAOXLvD19+lQ1IyQiIiKqDc4PblTqMjAGlAiOe/fujRUrVkBbWxsxMTEYPHiw5NilS5dgYWGhkgESEREREdUVheccL168GJcuXcLw4cNx8+ZNhIWFSY6lpKRw/WMiIiKqe+paqYLZ6CZD4cyxs7Mzrl69inPnzsHGxkZqp5KgoCC1belHRERERKQuCmeOAUBPTw89evSQ2cLPx8cHtra2Sg2MiIiIqNYENb6oXvz44494+PCh3GMPHz7Ejz/+qNL+apU5vnbtGszNzaGtrY1r1669tH67du0UHhgRERFRbalrww5uAlJ/3N3dcezYMblTds+fPw93d3eUlpaqrL9aBcft27eXDM7a2hoiUfVr/qlyoERERETU9AhC1Z9Mnj17Bg0NpSZCyKhVcPzNN9+gY8eOkv9+WXBMREREVKfUNQWCmeM6df/+fdy9e1fyc15ensyshaKiIiQkJEj23VCVWgXHEyZMkPx35YYfRERERESq9MUXX2DRokUAyvfP8PPzk1tPEATMnz9fpX0rvFoFERERUYPDzHGjMHjwYBgYGEAQBISEhGD69Okyz7KJxWI4OjpiwIABKu27VsFxZQRfEyKRCAsWLKj1gIiIiIioaXN1dYWrqysA4NGjR3j//ffrbIO5WgXHCxculPpZJBLJTJJ+fh4yg2MiIiKqSyKoabUK1TdJNRQZGVmn/dXq8b6ysjLJ6/z582jfvj2WLl2Ky5cvo6ioCJcvX8bixYvRvn17nDt3Tl1jJiIiIqIm6NatW7h27ZrMS5UUnnM8c+ZMvPfee/jkk08kZVZWVpg/fz6ePXuGGTNmIC0tTSWDJCIiIqKm6f79+5gzZw6SkpJQXFwst069rXP8vJ9++gkff/yx3GP9+/fHp59+qvCgiIiIiIgAYPbs2di8eTMmT56Mbt26QSwWq7U/hYNjsViMkydPwsPDQ+bYyZMn0axZM6UGRkRERFRrXK2i0dm7dy+io6Mxc+bMOulP4eDYz88PUVFRMDAwwJgxY9C6dWvcuXMHmzZtwqJFizB27FhVjpOIiIiImqDi4mI4OjrWWX8K77f3+eefo2/fvpg+fTqMjY0hFothbGyMGTNmoHfv3vj8889VOU4iIiKilxIJ6ntR/RgyZAh++umnOutP4cxx8+bNcfDgQaSnp+Pw4cMoKCiAkZER3N3dMXjwYG4tTURERERKCw8Px4gRI9C8eXMMGzYMRkZGMnUMDQ1V1p/SO+R5eXnBy8tLFWMhIiIiUg7nHDc6Dg4OAIDg4GAEBwfLrdMgVqsgIiIiIlK3iIiIOp2RwOCYiIiIGg9mjhudF3doVjeFH8gjIiIiImpsmDkmIiKiRkNdK0twtYq6de3aNZibm0NbW7tG20O3a9dOZX0zOCYiIiKiBqV9+/Y4duwYevfuDWtr65fOOeYDeURERERVYZb3lffNN9+gY8eOAIBvv/22TvuuVXA8cODAGtcViUTIzMys9YCIiIiIqGmbMGECAKCoqAjz58/H119/jWHDhtVJ37UKjsvKyqTS2ufPn0deXh6srKzQpk0b5OXl4erVqzA3N4ednZ3KB0tERERUHc45blx0dXVRVFQEfX39OuuzVsHx4cOHJf+dnp6O999/Hz///DNcXV0l5UePHsXIkSMxd+5clQ2SiIiIqEa4lFuj4+HhgYyMjFrNYFCGwnOOw8PDsXDhQqnAGAD69euHyMhIhIWFYciQIUoPkIiIiIiarvnz5+Odd96Bjo4O/P39YW5uLvOAXoPYPjonJwdt27aVe6xdu3Y4d+6cwoMiIiIiUggzx41Oz549AZRvBhIVFSW3ToNYrcLMzAzbt2/H4MGDZY5t3boVZmZmSg2MiIiIiOiV2T46KCgIoaGhKCwsxJgxYyQP5G3atAk7d+7E8uXLVTlOIiIiopdT0wN5zBzXn7rePlrh4DgkJASPHz/GypUrsWPHDgCAIAjQ0dFBWFgYQkJCVDZIIiIiIqK6oNQmIAsXLsTs2bNx7NgxFBQUwMjICH379kWrVq1UNDwiIiKiWuCc40aptLQU33//PQ4dOiSJOd3d3REQEAAtLdXuaad0ay1btoSXl5cqxkJEREREJOX27dvw8vLCb7/9Bi0tLRgZGaGgoADr16/Hp59+in379sHY2Fhl/SkVHAuCgBMnTuDq1asoKiqSOf7ee+8p0zwRERFR7THL26jMnj0b58+fx6ZNm/Duu+9CU1MTpaWl2LJlC6ZOnYrZs2dj48aNKutP4eD4zz//xNtvv42//voLgiB7F4pEIgbHRERERKSUH374AUuWLMHo0aMlZZqamhgzZgzy8/NV/sCewsHxhx9+iOLiYmzZsgXdunWDWCxW5biIiIiIao3bRzc+giCga9euco85ODjITdIqQ+Hg+JdffsG6deswYsQIVY6HiIiIiEhi0KBByMjIwKBBg2SOHThwAG5ubirtT0PREw0MDNCiRQtVjoWIiIhIOYIaXwp6+PAhZs2aBQsLC+jo6MDZ2RnJyck1Ojc/Px+BgYEwNjaGnp4eXF1dkZmZKbduRkYGXF1doaenB2NjYwQGBiI/P1+m3rNnzxAVFQVra2uIxWLY29tj9erVMvVycnIQFBQEV1dX6OvrQyQS4fDhw3L7tra2hkgkknlNnTq1RtdZnQULFuD7779HcHAwTp06hRs3buDUqVOYO3cutm7diqioKBQWFkpeylI4OJ44cSI2b96s9ACU9eDBA4SEhGDw4MEwMTGBSCSSO/ektLQUn3/+Oby8vPDaa69BT08PnTt3RmhoKO7evStTX94vWCQSITo6WqZubW5cIiIialr8/f2RkJCAyMhIpKWlwcXFBaNHj35pHPXkyRN4eHggMzMTMTEx2LVrF8zMzODl5YUjR45I1T1y5Ai8vb1hZmaGXbt2ISYmBhkZGfDw8MCTJ0+k6gYFBWH58uX48MMPsW/fPvj5+WHmzJlYtmyZVL2TJ08iJSUFhoaG8PDweOl19u/fH8eOHZN6zZs3r4bvUtV69OiBK1eu4LPPPkOvXr3w2muvoVevXvj8889x5coV9OzZEyYmJpKXshSeVuHg4ICkpCS8/fbbGDZsGIyMjGTq+Pv7KzW4migoKMDatWvh5OQEX19frF+/Xm69oqIiLFy4EKNHj8aUKVNgbGyM3377DUuWLMEPP/yAkydPQldXV+qcESNG4OOPP5Yqa9eundTPlTfu3bt3ERMTA1NTU8TGxsLLywsZGRkYMGCAai+YiIiIqtTQ5hynpqbiwIED2Lx5s+SBMnd3d1y9ehXBwcEYOXIkNDU15Z67YcMGZGdn4+jRo3B1dZWc6+TkhJCQEBw/flxSNzg4GLa2tti2bZtk3d/27dujf//++OabbzBt2jQA5dngDRs2YOnSpQgODgYAuLm5oaCgAEuWLMHUqVNhaGgIABg/fjwmTJgAANi2bRt++OGHaq+1VatW6Nu3r2JvVDVeme2jx4wZAwC4fPky9uzZI3NcJBKhtLRU8ZHVkJWVFe7cuQORSITbt29XGRzr6uri8uXLUkG8m5sb2rVrh4CAAGzfvh3jxo2TOsfMzOylv+Ta3LhERETUtOzcuRMGBgYICAiQKp84cSLGjBmD48ePo1+/flWea2dnJ4kvAEBLSwvjxo3D/PnzkZubC0tLS+Tm5uLEiRNYvny51IYY/fr1g62tLXbu3CkJjlNSUiAIAiZOnCgznnXr1iE9PV0S42loKDzBQKVeme2jDx06pMpxKKymnyQ0NTXlZrd79+4NALh+/bpC/df0xiUiIqI6oOYd8i5cuCBzyMTEBKampnJPy87ORufOnWV2cevWrZvkeFXBcXZ2Nt544w2Z8spzc3JyYGlpiezsbKnyF+v+/PPPUm2amJigTZs2VY5HUT/++COaN2+O4uJidOrUCZMnT8asWbOqzIzXpt0ePXrAwMBA5tjDhw/x22+/4c0331Sqj+cpHBw3lukCBw8eBAC5S4Rs3rwZGzZsQFlZGRwcHPDRRx/JfNKq6Y1blfz8fNy6dUuqTN5fPCIiIqp/vr6+MmWRkZFVZjcLCgrQoUMHmfLKqQsFBQVV9lVQUCCpV925lX9WVff5PqpqU19fH82aNat2PNXx8fFBr1690LFjR9y5cwdbt27F3Llzcfr0aaU36HB3d8exY8ckCc3nnT9/Hu7u7iqdraDazahfMbm5uQgNDUWvXr0wdOhQqWNjxoyBj48P2rZti/z8fGzYsAGTJk3CpUuXsHjxYkm9mt64VYmLi0NUVJQKroaIiIjUnTlOSUmBjY2N1KGXPQRW3bfcL/sGvDbnVlW3pvVqMp6qxMbGSv08fPhwtG7dGmvWrMGcOXPQvXt3hdoFUO06xs+ePVP59I9aBceTJk3CggUL0L59e0yaNKnauiKRCBs2bKjVYA4fPgx3d/ca1T116hScnZ1r1f7zCgsLMWTIEAiCgC1btsi8sZs2bZL6+Z133sGwYcMQHR2NGTNmSP1FUOYmCwoKkpmHdOHCBbmfTImIiKh+2djYVLkhhTxGRkZyE2WVS47JS7DV9tzKaaNV1X2+DyMjI5w+fVqm3qNHj/D06dNqx1Nb48aNw5o1a5CVlVXr4Pj+/ftSq4nl5eXh2rVrUnWKioqQkJAgM0VEWbUKjg8dOoSZM2cCKJ+OoOpPHnZ2dli3bl2N6r64akRt3LlzB56ensjNzcXBgwflft0hz7hx47Bnzx6cPHkS3t7eAJS76QHA1NS0ynlKREREVDuiipc62lWEo6MjkpKSUFJSIjXv+MyZMwDKV/+q7tzKes978dzKP8+cOYMhQ4bI1H2+D0dHRyQnJyMvL08qqKzJeGqrMuOrSGb3iy++wKJFiwCUx5R+fn5V9jF//nzFBylHrYLjy5cvS/77ypUrKh0IAJibm2PKlCkqb/d5d+7cwaBBg3D58mVkZmbKnbxeFXm/5JreuERERNT0+Pn5Yd26ddi+fTtGjhwpKU9ISICFhQX69OlT7blBQUE4fvy4pF5JSQkSExPRp08fWFhYAAAsLS3Ru3dvJCYmYu7cuZIH4LKysnD+/HnMmjVL0ubw4cMRHh6OhIQEqTWI4+PjoaurCy8vL5Vd+3fffQcACi3vNnjwYBgYGEAQBISEhGD69OkyiVGxWAxHR0eVPwfXpOYcVwbGly5dwoEDB2qd4t+4cSO0tbXRs2dPSVlNb1wiIiKqI+qYc6wgb29veHp6Ytq0abh//z5sbGyQlJSE9PR0JCYmSgLZyZMnIyEhARcvXoSVlRWA8umssbGxCAgIQHR0NExNTREXF4fz588jIyNDqp8VK1bA09MTAQEBCAoKQn5+PkJDQ+Hg4CC1mEDXrl0xefJkREZGQlNTEy4uLti/fz/Wrl2LJUuWSH3j/fjxY6SmpgIoD7SB8s1Gbt++DX19fcm36Js3b8aOHTvg4+MDKysr3L17F1u3bkVycjICAwPh5ORU6/fN1dVVshLYo0eP8P7779dZTKVwcBwQEABPT094eHigY8eOqhxTraWlpeHRo0d48OABAODs2bPYtm0bAGDIkCHQ09NDUVER3nrrLZw6dQpffvklSkpKJL9ooHwyfeV1rFq1CmfPnoWHhwdee+01yQN5+/fvx8KFC2FsbCw5rzY3LhEREalXQ9sEBAB27NiBsLAwREREoLCwEPb29khKSsKoUaMkdUpLS1FaWir18JlYLEZmZqYkc/r48WM4OzsjLS1NJlvq5uaG1NRUREREYNiwYdDT08PQoUOxatUqiMViqbpxcXGwtLTE6tWrkZeXB2tra8TExGD69OlS9fLz82Wei6pclcPKykoyi6BDhw64e/cu5s+fj4KCAmhra6Nr166Ii4vDBx98oPgbVyEyMlLy33/++ScKCgpgbGyMTp06Kd22PCKhukcAq9GtWzfk5OQAKJ//O2jQIAwaNAgeHh5SwWNdsLa2xtWrV+Ueu3z5MqytrXHlyhW0b9++yjYmTJiA+Ph4AMAPP/yAlStX4vz587hz5w50dXXh7OyMoKAgqRu50s2bNxESEoI9e/ZIbtzFixdj0KBBCl1PTk4OHBwc0BeeMBC1VKgNIiKi+vRQuIcsHEB2dnatHmBTVOW/nbbjQqBjpNoHtACguCAPfyaurLPrIWmVS8P9/fffkrLXXnsNn332GUaMGKHSvhTOHP/f//0fbt26hQMHDiAjIwMHDhzAhg0boKGhAUdHR3h6emLlypWqHGuVajL/2drautqlQJ43bNgwDBs2rMb9m5mZISEhocb1iYiISE3UvJQb1b3U1FSMGjUKXbt2xUcffQQLCwvk5uYiMTERo0aNwg8//CCZ4qEKCmeO5Tl58iTCw8Oxf//+Ots+ujFi5piIiF519ZY5HqvGzPEmZo7rQ//+/dGiRQvs3btXalEEQRDg7e2NBw8eSO0CqCylHsgrLS3FsWPHJNnjEydOQFNTE+7u7gpPKSAiIiJSGDPHjc7p06eRnJwssyScSCRCUFAQxowZo9L+FA6Ohw0bhiNHjqCoqAhOTk4YNGgQFi5ciDfeeAM6OjqqHCMRERERNVGampp4+vSp3GP1vkPe8/bu3Qs9PT18/PHHGDVqlFK71RERERGpQkNcrYKU4+LigpUrV2LIkCHQ1dWVlD958gSffvpptWtFK0Lh4Hjbtm3IyMjAjh07sGrVKhgbG8PDwwOenp4YNGgQ2rZtq8pxEhEREVETFBUVBQ8PD3To0AEBAQFo06YNbty4gR07dqCgoAAHDx5UaX8KB8f+/v7w9/cHAFy9elWyYkVoaChu374NW1tb/PHHHyobKBEREdFLcc5xo/P6669j//79CA0NRWxsLARBgIaGBvr06YOkpCT069dPpf2pZIe8Nm3awNraGu3bt8dff/2FW7du4c8//1RF00RERETUxA0YMADHjh3D48ePcefOHbRu3Rp6enpq6Uvh4PjXX39FRkYGMjIy8PPPP+PJkyfQ19fHm2++iXHjxnG1CiIiIqoXnB/ceP39998oKCjA48eP1bZDnsLBsYuLC7S1tdGnTx/MmzcPgwYNQp8+faClpZJkNBERERERgFdkh7w9e/ZgwIAB0NfXV+V4iIiIiBTHOceNTl3vkKdwcDxkyBCVDYKIiIiISJ6lS5di8ODBMjvkBQcHw9vbG0uWLFFpcKzUqslXrlzBBx98AFtbWxgZGcHW1hYffPABLl++rKrxEREREdVY5TrH6nhR/Th9+jSCgoKq3CHv999/V2l/CgfHp0+fRvfu3REfHw9LS0sMHjwYlpaWiI+PR/fu3XH69GkVDpOIiIiImqK63iFP4dZmzZoFExMT/PXXXzh06BCSkpJw6NAh/PnnnzA1NcXs2bNVOU4iIiKilxPU+KJ6UblDXlFRkVR5g9sh75dffsGGDRvQrl07qXIrKyssXLgQU6ZMUXpwRERERNS0vTI75LVs2RItW7aUe6xVq1Zo0aKFwoMiIiIiUghXq2h0Xpkd8saMGYP169fLXbVi3bp1GD16tFIDIyIiIiICXpEd8nr06IFt27ahd+/eGD16NNq0aYO8vDwkJSUhPz8fAQEB2LFjh6S+v7+/SgZMREREVBV1rSzB1SrqVkhICGbMmIHXXntNUlZWVgY9PT21BcWVFA6Ox48fDwC4fv06Tp48Kfe4IJTfSSKRCKWlpYp2RURERERNSOXOd5XBcWlpKZo1a4YTJ06gR48eau1b4eD40KFDqhwHERERkWowy/vKq0ywvqxMHRQOjgcMGKDKcRAREREpTSQIEKkhiFJHm9QwqXbVZCIiIiKiV1itMscDBw6s8pi2tjbMzMzg6emJ0aNHQ0tL4aQ0ERERkWK4lFujcf78eUk8Wfns2rlz5+TWVeU85FpFsPn5+RCJRHKPlZSU4Pjx40hMTERsbCwOHjyo9qcJiYiIiKhxCgwMlCmrXBCikiAIKl/4oVbBcXZ29kvrpKWlYeTIkVi6dCmWLl2q8MCIiIiIaotLuTUO3377bb31rfK5D97e3pg3bx42btzI4JiIiIiIam3ChAn11rdaHsjr3bs3rl69qo6miYiIiKomqPFFTYJaguOioiI+kEdERERErxy1RLCpqano0qWLOpomIiIiqhLnHJOyahUcFxYWVnmstLQUubm52LJlC9avX4+4uDilB0dEREREVJdqFRwbGxtXuZTb8z766CP861//UnhQRERERApjlpeUUKvgOCIiosrgWEtLC2ZmZhg4cCA6dOigksEREREREdWlWgXHCxcuVNMwiIiIiFRATXOOmY1uOtSyWgURERER0auI660RERFR46GuNYmZOW4ymDkmIiIiIqrAzDERERE1GlznmJTFzDERERERUQVmjomIiKjxEITylzrapSaBmWMiIiIiogrMHBMREVGjIYKa5hyrvklqoJg5JiIiIiKqwMwxERERNR5c55iUxOCYiIiIGg1RWflLHe1S08BpFUREREREFZg5JiIiosaD0ypIScwcExERERFVYHBMREREjUbl9tHqeCnq4cOHmDVrFiwsLKCjowNnZ2ckJyfX6Nz8/HwEBgbC2NgYenp6cHV1RWZmpty6GRkZcHV1hZ6eHoyNjREYGIj8/HyZes+ePUNUVBSsra0hFothb2+P1atXy9TLyclBUFAQXF1doa+vD5FIhMOHD1c51uTkZDg7O0NHRwcWFhaYNWsWHj58WKPrbEhe+eD4wYMHCAkJweDBg2FiYgKRSISFCxfKrRsYGAiRSCTzsre3l1t/9erVsLe3h1gsRvv27REVFYVnz57J1KvNjUtERERNi7+/PxISEhAZGYm0tDS4uLhg9OjR2Lx5c7XnPXnyBB4eHsjMzERMTAx27doFMzMzeHl54ciRI1J1jxw5Am9vb5iZmWHXrl2IiYlBRkYGPDw88OTJE6m6QUFBWL58OT788EPs27cPfn5+mDlzJpYtWyZV7+TJk0hJSYGhoSE8PDyqHeumTZswevRouLi4IC0tDZGRkYiPj4e/v38t3qmG4ZWfc1xQUIC1a9fCyckJvr6+WL9+fbX1dXV1cfDgQZmyFy1duhQLFixAaGgoBg8ejBMnTiA8PBy5ublYu3atpF7ljXv37l3ExMTA1NQUsbGx8PLyQkZGBgYMGKCaCyUiIqIaUNP20QpOOk5NTcWBAwewefNmjB49GgDg7u6Oq1evIjg4GCNHjoSmpqbcczds2IDs7GwcPXoUrq6uknOdnJwQEhKC48ePS+oGBwfD1tYW27Ztg5ZWeXjXvn179O/fH9988w2mTZsGoDwbvGHDBixduhTBwcEAADc3NxQUFGDJkiWYOnUqDA0NAQDjx4/HhAkTAADbtm3DDz/8IHecpaWlCA4OxuDBg7Fu3TrJOJs3b46xY8ciLS0N3t7eCr1/9eGVzxxbWVnhzp07OHLkCJYvX/7S+hoaGujbt6/Uy8nJSapO5Q3y/vvvY9myZXBzc0NwcDAiIyOxfv16nD17VlK38sb9/vvvMXbsWHh6emLbtm2wtbVFSEiIyq+XiIiIXh07d+6EgYEBAgICpMonTpyIf/75RyrAlXeunZ2dJDAGAC0tLYwbNw6//PILcnNzAQC5ubk4ceIExo8fLwmMAaBfv36wtbXFzp07JWUpKSkQBAETJ06UGU9RURHS09MlZRoaNQsTs7KycOPGDZk2AwICYGBgINX/q+CVD44rp0aoUnp6OoqLi+XeOIIgICUlRVJW0xuXiIiI1E/dc44vXLiAnJwcqZe8eb2VsrOz0blzZ6mgFQC6desmOV7duZX15J2bk5Mj1UZVdZ/vIzs7GyYmJmjTpk2tx1PdOOX1r62tDXt7e4XarE+vfHBcW0VFRWjTpg00NTXx2muv4aOPPkJhYaFUncpfoqOjo1S5ubk5jI2NZW6ymty4VcnPz5f5S3bhwgWFro2IiIjUy9fXFw4ODlKvuLi4KusXFBRIpik8r7KsoKBA6XMr/6yq7vN9VNWmvr4+mjVrVu14qhtnTft/Fbzyc45rw8nJCU5OTnBwcABQPnn9iy++QGZmJk6cOAEDAwMA5b9ksVgMfX19mTZqepPV5KYHgLi4OERFRSl8TURERPQcNa9znJKSAhsbG6lDJiYm1Z5a3TfcL/v2uzbnVlW3pvVqMp7q1LT/hq5BBceHDx+Gu7t7jeqeOnUKzs7OtWp/9uzZUj97enqie/fuGDFiBNatWyd1XBU348uOAeVPjL44D+nChQvw9fWt9jwiIiKqezY2NujatWuN6xsZGclNlFV+ay0vwVbbc42MjADIT8gVFhZK9WFkZITTp0/L1Hv06BGePn1a7XiqG2dl/2ZmZtX2/ypoUMGxnZ2d5CnHl2nXrp1K+vTz84O+vj6ysrIkZUZGRiguLsbjx4+hp6cnVb+wsBA9e/aUqqvoTQ8ApqamMDU1VeYSiIiIqJKSaxJX164iHB0dkZSUhJKSEql5x2fOnAEAybfZVZ1bWe95L55b+eeZM2cwZMgQmbrP9+Ho6Ijk5GTk5eVJzTuuyXiqG2dlG126dJGUl5SU4Ny5c5JVOl4VDSo4Njc3x5QpU+q8X0EQpJ7IfP6X3KdPH0l5Xl4ebt++LXOT1eTGJSIioqbHz88P69atw/bt2zFy5EhJeUJCAiwsLKTiDHnnBgUF4fjx45J6JSUlSExMRJ8+fWBhYQEAsLS0RO/evZGYmIi5c+dKlobLysrC+fPnMWvWLEmbw4cPR3h4OBISEjBv3jxJeXx8PHR1deHl5VXra+zTpw/Mzc0RHx8vdY3btm3Dw4cPX7m1jhtUcFwftm3bhsePH6Nv376SMi8vL+jo6CA+Pl7qpo2Pj4dIJJKa8lDTG5eIiIjqgKCmdY4VbNPb2xuenp6YNm0a7t+/DxsbGyQlJSE9PR2JiYmSQHby5MlISEjAxYsXYWVlBQCYNGkSYmNjERAQgOjoaJiamiIuLg7nz59HRkaGVD8rVqyAp6cnAgICEBQUhPz8fISGhsLBwUFq9a2uXbti8uTJiIyMhKamJlxcXLB//36sXbsWS5YskfrG+/Hjx0hNTQUAyTfsR44cwe3bt6Gvry9Zu1hTUxMrV67E+PHj8cEHH2D06NH466+/EBISAk9PT4UC7vrUKILjtLQ0PHr0CA8ePAAAnD17Ftu2bQMADBkyBHp6erh69SrGjBmDUaNGwcbGBiKRCEeOHMGXX36Jrl27SmWsDQ0NER4ejgULFsDQ0FCyCcjChQsxZcoUqa8ManPjEhERUdOzY8cOhIWFISIiAoWFhbC3t0dSUhJGjRolqVNaWorS0lIIzwXhYrEYmZmZCAkJwfTp0/H48WM4OzsjLS1NZpMxNzc3pKamIiIiAsOGDYOenh6GDh2KVatWQSwWS9WNi4uDpaUlVq9ejby8PFhbWyMmJgbTp0+Xqpefny/zXFTlLsRWVla4cuWKpHzcuHHQ1NREdHQ04uPjYWhoiPfeew9Lly5V5q2rFyJBUMs2MnXK2toaV69elXvs8uXLsLa2xp07dzB58mScOnUKN2/eRGlpKaysrODn54f58+ejZcuWMud+9dVXiI2NxZUrV9CmTRtMnDgRYWFh0NbWlqp38+ZNhISEYM+ePZIbd/HixRg0aJBC15OTkwMHBwf0hScMRLLjIiIiaugeCveQhQPIzs6u1QNsiqr8t7OH2xzot2jz8hNq6dH9PPx2+PM6ux6qP40ic/z8J5eqtG7dGjt27KhVuzNmzMCMGTNeWs/MzAwJCQm1apuIiIiIGp5GERwTERERSbzy34lTfWpyO+QREREREVWFmWMiIiJqNERqWudYLWsnU4PEzDERERERUQVmjomIiKjxKBPKX+pol5oEBsdERETUeAhQzwN5jI2bDE6rICIiIiKqwMwxERERNRp8II+UxcwxEREREVEFZo6JiIiocRGY5iXFMXNMRERERFSBmWMiIiJqNDjnmJTFzDERERERUQVmjomIiKjx4DrHpCRmjomIiIiIKjBzTERERI2GSBAgUsNqFepokxomZo6JiIiIiCowc0xERESNR1nFSx3tUpPAzDERERERUQVmjomIiKgRUc+cYy5X0XQwc0xEREREVIGZYyIiImo8uM4xKYmZYyIiIiKiCswcExERUeMhCOUvdbRLTQIzx0REREREFZg5JiIiokZDJJS/1NEuNQ3MHBMRERERVWDmmIiIiBoPzjkmJTE4JiIiokZDJAAiNWz1zGkVTQenVRARERERVWDmmIiIiBoPTqsgJTFzTERERERUgZljIiIiajy4fTQpiZljIiIiIqIKzBwTERFRo1G+CYjq07xcraLpYOaYiIiIiKgCM8dERETUeHC1ClISM8dERERERBWYOSYiIqLGQwCghh3yuFpF08HMMRERERFRBWaOiYiIqNEQCYKaVqtg6ripYOaYiIiIiKgCM8dERETUeHC1ClISM8dERERERBWYOSYiIqLGg5ljUhIzx0REREREFZg5JiIiosajDOpZ51gdbVKDxMwxEREREVGFVz44fvDgAUJCQjB48GCYmJhAJBJh4cKFcuuKRKIqX/b29jWqGx0dLdNufn4+AgMDYWxsDD09Pbi6uiIzM1Mdl0tERETVEEGQrHWs0pcSW+Q9fPgQs2bNgoWFBXR0dODs7Izk5OQanVubGCMjIwOurq7Q09ODsbExAgMDkZ+fL1Pv2bNniIqKgrW1NcRiMezt7bF69Wq5bV66dAn+/v5o1aoVDAwM4Onpid9++02mnrW1tdy4aerUqTW6zobklZ9WUVBQgLVr18LJyQm+vr5Yv359lXWPHTsmU3b8+HHMmjULfn5+MsdGjBiBjz/+WKqsXbt2Uj8/efIEHh4euHv3LmJiYmBqaorY2Fh4eXkhIyMDAwYMUPDKiIiIqDHw9/fHiRMnEB0dDVtbW2zevBmjR49GWVkZxowZU+V5tYkxjhw5Am9vb/j4+GDXrl3Iz8/HvHnz4OHhgZMnT0IsFkvqBgUFYePGjVi8eDFcXFywb98+zJw5Ew8ePMD8+fMl9W7duoU33ngDrVu3xjfffAMdHR0sX74cbm5uOHHiBOzs7KTG279/f3z66adSZWZmZsq+fXXulQ+OrayscOfOHYhEIty+fbva4Lhv374yZf/5z38gEokwefJkmWNmZmZyz3nehg0bkJ2djaNHj8LV1RUA4O7uDicnJ4SEhOD48eO1vCIiIiJSmAA1rVah2Gmpqak4cOCAJCAGyuOEq1evIjg4GCNHjoSmpqbcc2sTYwQHB8PW1hbbtm2DllZ5eNe+fXv0798f33zzDaZNmwYAyMnJwYYNG7B06VIEBwcDANzc3FBQUIAlS5Zg6tSpMDQ0BACsWrUKt27dwtGjR2FlZQUAeP3119GxY0dERERgy5YtUuNt1arVS+OmV8ErP62iMm2viAcPHmDr1q0YMGAAbGxsFGpj586dsLOzk9y0AKClpYVx48bhl19+QW5urkLtEhERkQIql3JTx0sBO3fuhIGBAQICAqTKJ06ciH/++afaJFpNY4zc3FycOHEC48ePlwTGANCvXz/Y2tpi586dkrKUlBQIgoCJEyfKjKeoqAjp6elS/Q8cOFASGANAixYt4O/vjx9++AElJSW1fDdeDa98cKyM5ORkPHr0CFOmTJF7fPPmzdDV1YVYLEbPnj3x7bffytTJzs5Gt27dZMory3JycqodQ35+PnJycqReFy5cUOBqiIiISN0uXLgg8++2vHm9lbKzs9G5c2epoBX4X5yQnZ1d7bk1iTEq26iq7vN9ZGdnw8TEBG3atKl2PEVFRbh48WKVbRYVFeHSpUtS5T/++COaN28ObW1tdOnSBZ999hlKS0urvL6G6pWfVqGMDRs2oFWrVnjnnXdkjo0ZMwY+Pj5o27Yt8vPzsWHDBkyaNAmXLl3C4sWLJfUKCgokXz88r7KsoKCg2jHExcUhKipKySshIiIiAGrfBMTX11fmUGRkZJWLARQUFKBDhw4y5TWJE2oaY1T+WVXd5/uoqk19fX00a9ZMUvfOnTsQBKHGMY6Pjw969eqFjh074s6dO9i6dSvmzp2L06dPY+PGjVVeY0PUoILjw4cPw93dvUZ1T506BWdnZ4X7ysnJwfHjx/Hhhx9CR0dH5vimTZukfn7nnXcwbNgwREdHY8aMGTAxMZEcq25ax8umfAQFBcl81XLhwgW5f/mIiIiofqWkpMhMxXw+JpBHmTihNudWVbem9ZSpGxsbK3Vs+PDhaN26NdasWYM5c+age/fuVbbT0DSo4NjOzg7r1q2rUd0XV42orQ0bNgBAlVMq5Bk3bhz27NmDkydPwtvbGwBgZGQk91NfYWEhAPmf4p5namoKU1PTGo+BiIiIqqHmTUBsbGzQtWvXGp+mTJxQ03ONjIwAyM9CFxYWSvVhZGSE06dPy9R79OgRnj59KqnbunVriEQipWKccePGYc2aNcjKymJwrChzc/NaBauKevr0KTZu3IiePXvWKvssVHyloqHxv6najo6OOHPmjEzdyjIHBwflBktERESvLEdHRyQlJaGkpERq3nFN4oSaxhiVf545cwZDhgyRqft8H46OjkhOTkZeXp7UvOMX29TV1YWNjU2V/evq6sqdLvI8eXHTq+DVGq2K7N69G7dv35a7fFt1Nm7cCG1tbfTs2VNS5ufnh3Pnzkk9bVpSUoLExET06dMHFhYWKhs3ERERvYx6NgFRdC03Pz8/PHz4ENu3b5cqT0hIgIWFBfr06VPtuTWJMSwtLdG7d28kJiZKPQCXlZWF8+fPw9/fX1I2fPhwiEQiJCQkSPUVHx8PXV1deHl5SfV/8OBBXL9+XVL24MED7NixA2+//bbMQ4Yv+u677wDIX0q3IWtQmWNFpaWl4dGjR3jw4AEA4OzZs9i2bRsAYMiQIdDT05Oqv2HDBujq6la58PaqVatw9uxZeHh44LXXXpM8kLd//34sXLgQxsbGkrqTJk1CbGwsAgICEB0dDVNTU8TFxeH8+fPIyMhQ0xUTERHRq8Db2xuenp6YNm0a7t+/DxsbGyQlJSE9PR2JiYmSNY4nT56MhIQEXLx4UbJ0Wm1ijBUrVsDT0xMBAQEICgpCfn4+QkND4eDgILVsW9euXTF58mRERkZCU1MTLi4u2L9/P9auXYslS5ZITZWYO3cuNm7cCB8fHyxatAhisRjR0dEoLi6WegBx8+bN2LFjB3x8fGBlZYW7d+9i69atSE5ORmBgIJycnNT4DqteowiOp02bhqtXr0p+3rp1K7Zu3QoAuHz5MqytrSXHrl+/jv3792PcuHFo2bKl3Pbs7e2xe/du7N27F3fu3IGuri6cnZ2RlJSEUaNGSdUVi8XIzMxESEgIpk+fjsePH8PZ2RlpaWncHY+IiKiuqXm1CkXs2LEDYWFhiIiIQGFhIezt7WViitLSUpSWlkqmIgC1izHc3NyQmpqKiIgIDBs2DHp6ehg6dChWrVoltTseUL5SlqWlJVavXo28vDxYW1sjJiYG06dPl6pnYmKCn376CXPnzsWECRNQUlICV1dXHD58GPb29pJ6HTp0wN27dzF//nwUFBRAW1sbXbt2RVxcHD744AOF37f6IhIEddxBpIycnBw4ODigLzxhIJIfwBMRETVkD4V7yMIBZGdn1+oBNkVV/tvZv/3k/2/vzqOavPI+gH9TMSQB2VFBBS0IKIu41IVWBZEWF0ah2lO7qLXajuhU7XS0Wlug4/KOth2tR+urMy3OgFqdqjNW1LJ63lGZatEKrcugonahKG6AoCC/9w8h9TEBghKE+P2ck+PJfe5zn/vLNckvl5sbtLOuf/eI+1Fy8yL2n/1rs8VDD49FzBwTERERAQCq5c7NHO3SI+GR/EIeEREREZExnDkmIiIiyyEw05rjpm+SWibOHBMRERER1eDMMREREVmOFrhbBbUunDkmIiIiIqrBmWMiIiKyIGaaOeai40cGZ46JiIiIiGpw5piIiIgsB/c5pgfEmWMiIiIiohqcOSYiIiLLIdV3buZolx4JnDkmIiIiIqrBmWMiIiKyHPyFPHpATI6JiIjIcoiZvpDHHwF5ZHBZBRERERFRDc4cExERkeXgz0fTA+LMMRERERFRDc4cExERkeXgzDE9IM4cExERERHV4MwxERERWQ7OHNMD4swxEREREVENzhwTERGR5agWoNoMP/Vsjr2TqUXizDERERERUQ3OHBMREZEFMdOaY/5+9CODM8dERERERDU4c0xERESWg7tV0APizDERERERUQ3OHBMREZHlqBbz7CzB3SoeGZw5JiIiIiKqwZljIiIishxSDREz7HNsjjapReLMMRERERFRDc4cExERkeUQmGd9MJccPzI4c0xEREREVIMzx0RERGQ5uM8xPSAmx0RERGQ5qqsBlRm+PFfNL+Q9KrisgoiIiIioBmeOiYiIyHJwWQU9IM4cExERERHV4MwxERERWQwRgZhhfbBw5viRwZljIiIiIqIanDkmIiIiy8E1x/SAOHNMRERERFSDM8dERERkOaoFZvmtZ3P8JDW1SJw5JiIiIiKqwZljIiIishxSfedmjnbpkcCZYyIiIiKiGpw5JiIiIoshAogZ1gdzs4pHB2eOiYiIiIhqcOaYiIiILIdUA+CaY7p/rX7mOCMjA1OmTIGfnx9sbGzQqVMnjBkzBt98843R+jk5ORg+fDhsbW3h4OCAmJgYnDlzxmjdVatWwc/PD9bW1ujWrRsSEhJQWVlpUK+oqAiTJ0+Gi4sLdDodBg0ahPT09CaNk4iIiFqn0tJSzJ49G+7u7tBoNAgODsbmzZtNOrcxOUZaWhoGDRoEnU4HFxcXTJ48GUVFRQb1KisrkZCQgK5du8La2hp+fn5YtWqV0TbPnDmDmJgYODg4wNbWFhEREcjJyTFad/PmzQgODoZGo4G7uztmz56N0tJSk+JsSVp9cvzJJ5+goKAAs2bNQkpKClauXImioiIMHDgQGRkZironTpxAaGgobt26hS1btuDTTz/FqVOnMHjwYFy8eFFRd/HixZg1axZiYmKwd+9exMbGYsmSJZgxY4ai3s2bNxEeHo709HSsXLkS//znP9GhQwdERkZi3759Zo+fiIiIfiXVYrbb/YqJicGGDRsQFxeH3bt344knnsCECROwcePGes9rTI6xb98+jBgxAh06dMA///lPrFy5EmlpaQgPD8fNmzcVdWNjY7F06VLMmDEDe/fuRXR0NGbNmoUlS5Yo6l28eBGDBw/GqVOn8Omnn2LLli2oqKhAaGgoTp48qaibnJyMCRMm4IknnsDu3bsRFxeHxMRExMTE3Pfj9rCoRFr3EvOioiK0b99eUVZaWgpvb28EBAQgLS1NX/7cc88hMzMTp0+fhp2dHQDg3Llz6N69O+bMmYM//elPAIDi4mJ07twZEydOxP/+7//qz1+yZAkWLlyIvLw89OzZEwCwZs0azJgxAwcOHMCgQYMAAFVVVejVqxdsbW3xn//8p9ExfffddwgICMBARMBWZd/o84mIiB62UrmGbKQiLy8P/v7+Zr+e/r1T9YxZ3jtL5RqyZW+j40lJScGoUaOwceNGTJgwQV/+9NNP47vvvsP58+fRpk0bo+c2Jsfo378/ysrK8O2338LK6s6q2QMHDuDJJ5/EmjVrMH36dAB3HqfAwEAsXrwY8+fP15//2muvISkpCT/88AOcnJwAAHPnzsWKFSvw3//+F56engCA69evw8vLC8OGDcPnn38OALh9+za6dOmCwMBA7N27V9/mxo0b8eKLLyIlJQUjRoww+TF72Fr9zPG9iTEA2NraomfPnrhw4YK+rKqqCl9++SWeffZZfWIMAJ6enggLC8P27dv1ZXv27EFFRQVeeeUVRbuvvPIKRAQ7duzQl23fvh2+vr76/7QAYGVlhZdeeglff/01fvzxx6YIk4iIiExRu8+xOW73Yfv27bC1tcX48eMV5a+88gp++umneifRTM0xfvzxRxw6dAgvv/yyPjEGgJCQEPj4+ChynB07dkBEjOY45eXl2LNnj+L6w4YN0yfGAGBnZ4eYmBjs3LkTVVVVAIDs7Gz8/PPPBm2OHz8etra2iuu3Bhb5hbxr164hJycHw4YN05edPn0a5eXlCAoKMqgfFBSE1NRUVFRUQKPRIC8vDwAQGBioqOfm5gYXFxf9cQDIy8vD4MGDjbYJ3PmE1qlTpzr7WlRUZLCk4/vvvwcA3ECpWX4Bk4iIyNxu4M5a03v/pG/+65aZ5b3zBsoAAPn5+QbHXF1djU7WAXfyhB49eiiSVuDXPCEvLw8hISF1nmtKjlGbl9SV4+zfv1/RpqurKzp27FhnfwCgvLwcp0+fRnR0tNE2y8vLcebMGfj4+NR5/bZt28LPz0+RN7UGFpkcz5gxA2VlZXjnnXf0ZcXFxQCg/1PB3ZycnCAiuHLlCtzc3FBcXAxra2vY2NgYrVvbVm27dbV593XrsmbNGiQkJBg9dgwH6z2XiIiopcvNzUWfPn3Mfh1HR0e0a9cOx0oOmO0aarUaY8eONSiPi4tDfHy80XOKi4vx+OOPG5SbkieYmmM0lOOYkrfY2NhArVbr6165cgUi0iTXLygoqDPGlqhFJcdZWVkICwszqe6RI0cQHBxsUP7uu+8iOTkZq1atQt++fQ2Oq1SqOtu8+5ip9Rpb916xsbEGf2o5evQoXnrpJWzZskW/ttkS5OfnY+zYsdixYwe8vb0fdnealKXGZqlxAZYbm6XGBVhubJYa1/fff4/nnnsOPj4+zXI9d3d3nDhxAleuXDHbNW7fvm10fbCrq2u95z1IntAU+ciD5C3muH5L16KSY19fX6xfv96kuh4eHgZlCQkJWLRoERYvXoyZM2cqjjk7OwMw/gnt8uXLUKlUcHBw0NetqKjAjRs3oNPpDOrenXQ7OzvX2SZg/FPU3dq3b1/nn2J69uzZLF9iaG7e3t4WGRdgubFZalyA5cZmqXEBlhubpcZ19/d8zM3d3R3u7u7Ndj1TPEieYOq5DeU4d1/D2dkZR48eNahXVlaGW7du6es6OjpCpVI1+vodOnSo9/qtQYtKjt3c3DB16tT7OjchIQHx8fGIj4/HggULDI57eXlBq9UiNzfX4Fhubi68vb2h0WgA/LrWODc3FwMGDNDXKywsxKVLlxAQEKAvCwwMrLNNAIq6RERE9GgJDAzEpk2bUFVVpVh3bEqeYGqOUftvbm4uRo4caVD33rxl8+bNKCwsVKw7vrdNrVYLb2/vOq+v1Wr1y0Xuzpvu/ot3VVUVTpw4odilozVo9btVAMAf//hHxMfHY+HChYiLizNax8rKClFRUdi2bRtKSkr05efPn0dmZqZiH77IyEhoNBokJiYq2khMTIRKpVKsN4qOjsaJEycU3zatqqpCUlISBgwY0OI+wRIREVHziY6ORmlpKb744gtF+YYNG+Du7q6YhDN2rik5RqdOndC/f38kJSXh9u3b+rrZ2dk4efKkIscZM2YMVCoVNmzYoLhWYmIitFotIiMjFdfPyMhQ7P5VUlKCbdu24Te/+Y0+2R8wYADc3NwM8qZ//OMfKC0tbX17HUsr98EHHwgAiYyMlIMHDxrc7nb8+HGxtbWVIUOGSEpKimzbtk0CAgLE3d1dioqKFHUXLVokKpVKFixYIFlZWbJ8+XKxtraWadOmKepVVFSIv7+/dOnSRZKTkyU1NVWio6PFyspKsrKy7iumvLw8ASB5eXn3dX5LZalxiVhubJYal4jlxmapcYlYbmyMy/JFRESIo6OjrFu3TjIyMmTatGkCQJKSkvR1pkyZIm3atJGCggJ9WWNyjMzMTLGyspLo6GhJTU2V5ORk6dKliwQEBEhFRYWi7tSpU8Xa2lqWL18uWVlZsmDBAlGpVLJ48WJFvaKiInFzc5PAwEDZvn27pKSkyJAhQ6Rdu3Zy/PhxRd2///3vAkBee+01yczMlHXr1omDg4NEREQ01cPYbFp9cjx06FDBnU1bjN7udfjwYQkPDxedTid2dnYyduxYyc/PN9r2ypUrxcfHR9RqtXh4eEhcXJzcunXLoF5hYaFMnDhRnJycRKPRyMCBAyU1NfW+Y/rll18kLi5Ofvnll/tuoyWy1LhELDc2S41LxHJjs9S4RCw3NsZl+UpKSuSNN96Qjh07ilqtlqCgINm0aZOizqRJkwSAnD17VlHemBzjq6++koEDB4pGoxEnJyeZOHGi0cf/1q1bEhcXJx4eHqJWq8XHx0c+/vhjo23m5+fL2LFjxc7OTnQ6nYSHh8s333xjtO7GjRslKChI1Gq1dOzYUd544w0pKSkx4RFqWVr9L+QRERERETUVi1hzTERERETUFJgcExERERHVYHJMRERERFSDyTERERERUQ0mx2aWkZGBKVOmwM/PDzY2NujUqRPGjBmDb775xmj9nJwcDB8+HLa2tnBwcEBMTAzOnDljtO6qVavg5+cHa2trdOvWDQkJCaisrDSoV1RUhMmTJ8PFxQU6nQ6DBg1Cenr6A8dWUlKCuXPn4umnn4arqytUKlWdvy0/efJkqFQqg5ufn1+Li60xcQGta8yMycrKMjo2KpUK2dnZBvXNEW9zKS0txezZs+Hu7g6NRoPg4GBs3rz5ofWnPo0Zl5Y8Jo15PrW255KpsbWm17/GvGe1tvEiMtnD3i7D0o0bN07CwsJkzZo1kpWVJVu3bpWBAweKlZWVpKenK+oeP35c2rVrJ4MHD5Zdu3bJF198If7+/vXuwzx//nzJzMyUZcuWiVqtNroPc0BAgHTu3FmSkpLkq6++kjFjxjzQPsy1zp49K/b29jJkyBCZOnWqAJC4uDijdSdNmiRardZgH+qjR48a1H3YsTUmrtY2ZsZkZmYKAFmyZInB+Ny7BY854m1OERER4uDgIGvXrpWMjAz9+CYnJz+0PtXF1HFp6WNi6vOpNT6XTI2tNb3+mfqe1RrHi8hUTI7NzNj+giUlJdKhQwcJDw9XlI8fP15cXFzk2rVr+rKCggJp27atzJ07V1926dIl0Wg08tprrynOX7x4sahUKvnuu+/0ZatXrxYAcuDAAX1ZZWWl9OzZU/r37/9AsVVXV0t1dbWIiFy8eLHB5NjGxqbBNltCbI2Jq7WNmTG1SdjWrVsbrGuOeJvLrl27BIBs3LhRUR4RESHu7u5SVVXV7H2qj6nj0tLHxNTnU2t8LpkaW2t6/TP1Pas1jheRqZgcPyRhYWHi4+Ojv19ZWSlarVZef/11g7pPP/20dO/eXX8/KSlJABj8AuBPP/0kABS/cDN8+HDx9fU1aHPJkiUCQH744YemCKfJkuOWFlt9cbX2MatlahJmrniby9SpU8XW1lYqKysV5Rs3bhQAsn///mbvU31MGZfWNiZ1PZ8s4bnUFMlxS41NRPmeZQnjRVQfrjl+CK5du4acnBz4+/vry06fPo3y8nIEBQUZ1A8KCkJ+fj4qKioAAHl5eQCAwMBART03Nze4uLjoj9fWratNAPjuu+8ePCATlZeXo2PHjmjTpg06d+6MmTNn4vLly4o6rSk2SxuzGTNmwMrKCnZ2dnjmmWfw73//W3HcXPE2l7y8PPTo0QNWVlaK8tp4HkafTFHfuLT2Mallac8lY1rz69+971mPwnjRo82q4SrU1GbMmIGysjK88847+rLi4mIAgJOTk0F9JycniAiuXLkCNzc3FBcXw9raGjY2Nkbr1rZV225dbd59XXPr1asXevXqhYCAAADAvn378Oc//xnp6ek4dOgQbG1t9f1pLbFZypjZ29tj1qxZCA0NhbOzM/Lz87F8+XKEhoZi165deOaZZxTXbep4m0txcTEef/xxo/2pPd6SmDIurX1MalnKc6kurf317973LEsfLyImx42QlZWFsLAwk+oeOXIEwcHBBuXvvvsukpOTsWrVKvTt29fguEqlqrPNu4+ZWs/Uuk0RW33mzJmjuB8REYHevXtj3LhxWL9+veJ4U8Zm7rhM6UNj6zW27t3uJ97evXujd+/e+vLBgwcjOjoagYGBmDt3rj45bmzf7jcGc2qJfapLY8alNY+JqX1o7udSU3pYr39Nob73LEsdLyImx43g6+uL9evXm1TXw8PDoCwhIQGLFi3C4sWLMXPmTMUxZ2dnAMY/GV++fBkqlQoODg76uhUVFbhx4wZ0Op1B3btfwJydnetsE/j1E/mDxnY/oqOjYWNjo9iWqqljM2dcD3vMjGmqeB0cHDB69GisXbsW5eXl0Gq1Zou3uTzI49pS3DsurX1MarXE55K5Ncfr34Oq6z3rURwverQwOW4ENzc3TJ069b7OTUhIQHx8POLj47FgwQKD415eXtBqtcjNzTU4lpubC29vb2g0GgC/rt3Kzc3FgAED9PUKCwtx6dIl/Z/uauvW1SYAfd0Hie1BiAgee+zXpe9NHZs543rYY2ZMU8YrIgB+na0xV7zNJTAwEJs2bUJVVZVi3bEpj2tLcve4tPYxqdUSn0vNwdyvfw+ivvesR3W86BHysL4J+Ch5//33BYAsXLiw3nrPPfectG/fXq5fv64vO3funKjVapk3b56+rLi4WDQajfz2t79VnL906VKDrXHWrFkjACQ7O1tfVllZKf7+/jJgwIAHDU2vod0qjPn8888FgKxYsUJf1tJiayiu1jxm9bl8+bJ06tRJgoODFeXmiLe5pKSkCADZvHmzojwyMrJFbuVmjLFxaU1jUt/zqbU/lxr7GtiSX/9Mec9q7eNFVB8mx2b2wQcfCACJjIw02AD+3q1tjh8/Lra2tjJkyBBJSUmRbdu2SUBAQL2bqi9YsECysrJk+fLlYm1tbXRTdX9/f+nSpYskJydLamqqREdHN9mm6ikpKbJ161b59NNPBYCMHz9etm7dKlu3bpWysjIRubP3ZUhIiHz88ceSkpIiu3fvlrfffls0Go34+/tLaWlpi4vNlLhEWueY3WvChAkyb9482bp1q2RmZsq6devE19dXrKysJDU1VVHXHPE2p4iICHF0dJR169ZJRkaGTJs2TQBIUlLSQ+tTXUwdl9YwJqY8n1rrc6mh2Frb65+p71mtdbyITMHk2MyGDh0qAOq83evw4cMSHh4uOp1O7OzsZOzYsZKfn2+07ZUrV4qPj4+o1Wrx8PCQuLg4uXXrlkG9wsJCmThxojg5OYlGo5GBAwcaJD33y9PTs87Yzp49KyJ3Zruio6Ola9euotVqRa1WS/fu3WXu3Lly9erVFhmbKXHVam1jdq+lS5dKcHCw2NvbS5s2bcTV1VWio6Pl66+/NlrfHPE2l5KSEnnjjTekY8eOolarJSgoSDZt2vTQ+lOfxoxLSx8TU59PrfG51FBsre31rzHvWa1xvIhMoRKpWcBGRERERPSI44+AEBERERHVYHJMRERERFSDyTERERERUQ0mx0RERERENZgcExERERHVYHJMRERERFSDyTERERERUQ0mx0RERERENZgcExERERHVYHJMZAbHjh3DK6+8gm7dukGj0cDW1hZ9+vTBsmXLcPny5YfdPbPr2rUrJk+e3KRthoaGIjQ09L7PV6lUiI+P199PTEyESqVCQUFBo9pZsmQJduzYcd/9sDSVlZXw8/PD//zP/zRZm6dOnYJarUZOTk6TtUlEZCqrh90BIkuzfv16xMbGwtfXF3/4wx/Qs2dPVFZW4vDhw1i7di0OHjyI7du3P+xumtX27dthZ2f3sLtRr1GjRuHgwYNwc3Nr1HlLlizBuHHjMHbsWPN0rJVZs2YNrly5gt/97ndN1qaPjw9efPFFzJkzB/v27WuydomITMHkmKgJHTx4ENOnT0dERAR27NgBa2tr/bGIiAj8/ve/x549e+pto7y8HFqt1txdNavevXs/7C40yNXVFa6urg+7G61aVVUVli9fjilTpsDGxqZJ2545cyb69euHAwcOICQkpEnbJiKqD5dVEDWhJUuWQKVSYd26dYrEuJZarcZvfvMb/f2uXbti9OjR2LZtG3r37g2NRoOEhAQAQF5eHsaMGQNHR0doNBoEBwdjw4YNivaqq6uxaNEi+Pr6QqvVwsHBAUFBQVi5cqW+zsWLF/Haa6+hS5cusLa2hqurK5588kmkpaXVG8uuXbugUqlw6NAhfdkXX3wBlUqFUaNGKeoGBQXh2WefVcR197KKrKwsqFQqbNq0Ce+88w7c3d1hZ2eH4cOH4+TJk4q2RATLli2Dp6cnNBoN+vTpg927d9fb17tdv34d06ZNg7OzM2xtbREZGYlTp04Z1DO2rOLIkSMYPXo02rdvD2tra7i7u2PUqFH44YcfANxZmlFWVoYNGzZApVJBpVLpl3pcvHgRsbGx6NmzJ2xtbdG+fXsMGzYM//d//6e4bkFBAVQqFT744AN89NFH6NatG2xtbTFo0CBkZ2cb9PM///kPoqKi4OzsDI1GAy8vL8yePVtR57///S9eeOEFfb979OiB1atXN/hYhYeHw8/PDyKiKBcReHt7G4zzvf71r3/hxx9/xMsvv6woj4+Ph0qlwrFjxzB+/HjY29vDyckJb775JqqqqnDy5ElERkaiXbt26Nq1K5YtW2bQdt++fdGjRw+sXbu2wTiIiJoSZ46Jmsjt27eRkZGBvn37okuXLiafl5OTg+PHj2PhwoXo1q0bbGxscPLkSYSEhKB9+/b4+OOP4ezsjKSkJEyePBm//PIL5s6dCwBYtmwZ4uPjsXDhQgwZMgSVlZU4ceIErl69qm//5ZdfRk5ODhYvXgwfHx9cvXoVOTk5KC4urrdfQ4cORdu2bZGWloYnnngCAJCWlgatVot9+/ahsrISbdu2RVFREfLy8jB9+vQGY12wYAGefPJJ/OUvf8H169cxb948REVF4fjx42jTpg0AICEhAQkJCXj11Vcxbtw4XLhwAdOmTcPt27fh6+tbb/sigrFjx+LAgQN477338MQTT2D//v0YMWJEg30rKytDREQEunXrhtWrV6NDhw4oLCxEZmYmSkpKANz5y8CwYcMQFhaGd999FwD0y0dq15LHxcWhY8eOKC0txfbt2xEaGor09HSD9dKrV6+Gn58fVqxYAQB49913MXLkSJw9exb29vYAgL179yIqKgo9evTARx99BA8PDxQUFOCrr77St/P9998jJCQEHh4e+PDDD9GxY0fs3bsXb7zxBi5duoS4uLg6Y541axbGjBmD9PR0DB8+XF++e/dunD59Gh9//HG9j9muXbvQvn179OzZ0+jx5557Di+99BJef/11pKamYtmyZaisrERaWhpiY2Px1ltvYePGjZg3bx68vb0RExOjOD80NBRbt26FiEClUtXbFyKiJiNE1CQKCwsFgDz//PMmn+Pp6Slt2rSRkydPKsqff/55sba2lvPnzyvKR4wYITqdTq5evSoiIqNHj5bg4OB6r2FrayuzZ882uU93e+qpp2TYsGH6+97e3vKHP/xBHnvsMdm3b5+IiCQnJwsAOXXqlCKuSZMm6e9nZmYKABk5cqSi/S1btggAOXjwoIiIXLlyRTQajURHRyvq7d+/XwDI0KFD6+3v7t27BYCsXLlSUb548WIBIHFxcfqyzz77TADI2bNnRUTk8OHDAkB27NhR7zVsbGwUsdWlqqpKKisrJTw8XBHP2bNnBYAEBgZKVVWVvvzrr78WALJp0yZ9mZeXl3h5eUl5eXmd13nmmWekc+fOcu3aNUX5zJkzRaPRyOXLl+s89/bt2/L444/LmDFjFOUjRowQLy8vqa6urjfGHj16SGRkpEF5XFycAJAPP/xQUR4cHCwAZNu2bfqyyspKcXV1lZiYGIN21q9fLwDk+PHj9faDiKgpcVkF0UMWFBQEHx8fRVlGRgbCw8MNZqAnT56MGzdu4ODBgwCA/v3749tvv0VsbCz27t2L69evG7Tfv39/JCYmYtGiRcjOzkZlZaXiuIigqqpKcasVHh6O/fv3o7y8HOfOnUN+fj6ef/55BAcHIzU1FcCd2WQPDw907969wVjvXlJSGzsAnDt3DsCdmdmKigq8+OKLinohISHw9PRssP3MzEwAMDj/hRdeaPBcb29vODo6Yt68eVi7di2+//77Bs+519q1a9GnTx9oNBpYWVmhbdu2SE9Px/Hjxw3qjho1Sj9bDhg+FqdOncLp06fx6quvQqPRGL1eRUUF0tPTER0dDZ1OpxjDkSNHoqKiwuhSjVqPPfYYZs6ciS+//BLnz58HAJw+fRp79uxBbGxsg7O1P/30E9q3b1/n8dGjRyvu9+jRAyqVSjGTb2VlBW9vb33cd6tt+8cff6y3H0RETYnJMVETcXFxgU6nw9mzZxt1nrHdEoqLi42Wu7u7648DwPz58/HBBx8gOzsbI0aMgLOzM8LDw3H48GH9OZ9//jkmTZqEv/zlLxg0aBCcnJwwceJEFBYWAgA2bNiAtm3bKm61hg8fjps3b+Lf//43UlNT4eLigt69e2P48OH6Ncv3/km+Ps7Ozor7teuyy8vLFXF17NjR4FxjZfcqLi6GlZWVwXVMOdfe3h779u1DcHAwFixYAH9/f7i7uyMuLs7gA4UxH330EaZPn44BAwbgiy++QHZ2Ng4dOoTIyEh9fHdr6LG4ePEiAKBz5851XrO4uBhVVVVYtWqVwRiOHDkSAHDp0qV6+z1lyhRotVr92t7Vq1dDq9ViypQpDcZcXl5eZ+IOAE5OTor7arUaOp3O4By1Wo2KigqD82vrGXv8iIjMhWuOiZpImzZtEB4ejt27d+OHH36oN6m5m7HZOWdnZ/z8888G5T/99BOAO4k4cGfW7c0338Sbb76Jq1evIi0tDQsWLMAzzzyDCxcuQKfTwcXFBStWrMCKFStw/vx5/Otf/8Lbb7+NoqIi7NmzB1FRUYov3d1twIABsLW1RVpaGgoKChAeHg6VSoXw8HB8+OGHOHToEM6fP29yctyQ2oSxNnG/W2FhIbp27drg+VVVVSguLlYkn8baMyYwMBCbN2+GiODYsWNITEzE+++/D61Wi7fffrvec5OSkhAaGopPPvlEUV67XrmxanfSqP0yoDGOjo5o06YNXn75ZcyYMcNonW7dutV7HXt7e/2Hp7feegufffYZXnjhBTg4ODTYRxcXF7Pu213bdu3/dyKi5sCZY6ImNH/+fIgIpk2bhlu3bhkcr6ysxM6dOxtsJzw8HBkZGfpkuNbf/vY36HQ6DBw40OAcBwcHjBs3DjNmzMDly5eN/riFh4cHZs6ciYiICP0PLDg7O6Nfv36KW622bdtiyJAhSE1NRUZGBiIiIgAAgwcPhpWVFRYuXKhPlpvCwIEDodFokJycrCg/cOCA0T+73yssLAwADM7fuHFjo/qhUqnQq1cv/PnPf4aDg4Pixyisra2NzmSqVCqDHUqOHTumXwLTWD4+PvDy8sKnn36KmzdvGq2j0+kQFhaGI0eOICgoyGAc+/XrZzBDbUztl/fGjRuHq1evYubMmSb10c/PD6dPn25UXI1x5swZPPbYYw1+EZOIqClx5pioCQ0aNAiffPIJYmNj0bdvX0yfPh3+/v6orKzEkSNHsG7dOgQEBCAqKqreduLi4vDll18iLCwM7733HpycnJCcnIxdu3Zh2bJl+t0MoqKiEBAQgH79+sHV1RXnzp3DihUr4Onpie7du+PatWsICwvDCy+8AD8/P7Rr1w6HDh3Cnj17DHYGqEt4eDh+//vfA4B+hlir1SIkJARfffUVgoKC6l132hiOjo546623sGjRIkydOhXjx4/HhQsXEB8fb9LSiKeffhpDhgzB3LlzUVZWhn79+mH//v34+9//3uC5X375JdasWYOxY8fi8ccfh4hg27ZtuHr1qv5DAXBndjkrKws7d+6Em5sb2rVrB19fX4wePRp//OMfERcXh6FDh+LkyZN4//330a1bN8U67sZYvXo1oqKiMHDgQMyZMwceHh44f/489u7dq/8AsHLlSjz11FMYPHgwpk+fjq5du6KkpAT5+fnYuXMnMjIyGryOj48PIiMjsXv3bjz11FPo1auXSf0LDQ3F+++/jxs3bkCn091XjPXJzs5GcHAwHB0dm7xtIqI6PdzvAxJZpqNHj8qkSZPEw8ND1Gq12NjYSO/eveW9996ToqIifT1PT08ZNWqU0TZyc3MlKipK7O3tRa1WS69eveSzzz5T1Pnwww8lJCREXFxcRK1Wi4eHh7z66qtSUFAgIiIVFRXy29/+VoKCgsTOzk60Wq34+vpKXFyclJWVmRTLt99+KwCke/fuivLaHSDefPNNg3Pq2q1i69atinq1OzfcHVd1dbUsXbpUunTpImq1WoKCgmTnzp0ydOjQBnerEBG5evWqTJkyRRwcHESn00lERIScOHGiwd0qTpw4IRMmTBAvLy/RarVib28v/fv3l8TEREX7R48elSeffFJ0Op1iB42bN2/KW2+9JZ06dRKNRiN9+vSRHTt2yKRJk8TT09Mg5uXLlxv0/d4+iogcPHhQRowYIfb29mJtbS1eXl4yZ84cg8dxypQp0qlTJ2nbtq24urpKSEiILFq0qMHHq1ZiYqIAkM2bN5t8Tn5+vqhUKtmyZYuivHa3iosXLyrKJ02aJDY2NgbtDB06VPz9/RVlJSUlotPpDHa8ICIyN5XIPbu/ExHRI+fZZ59FdnY2CgoKFF/KbEhUVBSqqqoa9UMtpvjrX/+KWbNm4cKFC5w5JqJmxWUVRESPqJs3byInJwdff/01tm/fjo8++qhRiTEALF26FL1798ahQ4f0PxbzoKqqqvCnP/0J8+fPZ2JMRM2OyTER0SPq559/RkhICOzs7PD666/jd7/7XaPbCAgIwGeffWbyjiCmuHDhAl566SX9WncioubEZRVERERERDW4lRsRERERUQ0mx0RERERENZgcExERERHVYHJMRERERFSDyTERERERUQ0mx0RERERENZgcExERERHVYHJMRERERFSDyTERERERUQ0mx0RERERENf4fSjKZtEIzf0sAAAAASUVORK5CYII="
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 8
  },
  {
   "cell_type": "markdown",
   "id": "45322449",
   "metadata": {},
   "source": [
    "\n",
    "## 6) Optional: 80% source area contour\n",
    "\n",
    "Below we compute a density threshold such that the **integral** of the footprint inside the contour\n",
    "is ~80% of the total. We then plot that as a single contour line.\n"
   ]
  },
  {
   "cell_type": "code",
   "id": "de1d284b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-08-31T00:56:28.128223Z",
     "start_time": "2025-08-31T00:56:27.879003Z"
    }
   },
   "source": [
    "\n",
    "# Convert density (m^-2) to probability mass per cell\n",
    "cell_mass = F * cfg.dx * cfg.dy\n",
    "flat = cell_mass.ravel()\n",
    "order = np.argsort(flat)[::-1]\n",
    "csum = np.cumsum(flat[order])\n",
    "\n",
    "# Find threshold where cumulative mass first exceeds 0.8\n",
    "idx_thr = int(np.searchsorted(csum, 0.8))\n",
    "thr_mass = flat[order][idx_thr]\n",
    "thr_density = thr_mass / (cfg.dx * cfg.dy)\n",
    "\n",
    "plt.figure(figsize=(6, 5))\n",
    "plt.pcolormesh(y, x, F, shading=\"auto\")\n",
    "plt.colorbar(label=\"Footprint weight (m$^{-2}$)\")\n",
    "cc = plt.contour(y, x, F, levels=[thr_density])\n",
    "plt.clabel(cc, fmt=\"80% area\", inline=True, fontsize=8)\n",
    "plt.xlabel(\"Cross‑wind distance y (m)\")\n",
    "plt.ylabel(\"Upwind distance −x (m)\")\n",
    "plt.title(\"Footprint with ~80% source area contour\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 720x600 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 9
  },
  {
   "cell_type": "markdown",
   "id": "9f6f2b1b",
   "metadata": {},
   "source": [
    "\n",
    "## 7) Save outputs (optional)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "590edbff",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "out_dir = Path(\"outputs\")\n",
    "out_dir.mkdir(exist_ok=True)\n",
    "\n",
    "# Save grids\n",
    "np.save(out_dir / \"footprint_density.npy\", F)\n",
    "np.savetxt(out_dir / \"footprint_density.csv\", F, delimiter=\",\")\n",
    "np.savetxt(out_dir / \"x_centers_m.csv\", x, delimiter=\",\")\n",
    "np.savetxt(out_dir / \"y_centers_m.csv\", y, delimiter=\",\")\n",
    "\n",
    "# Save figures\n",
    "plt.figure(figsize=(6, 5))\n",
    "plt.pcolormesh(y, x, F, shading=\"auto\")\n",
    "plt.colorbar(label=\"Footprint weight (m$^{-2}$)\")\n",
    "plt.xlabel(\"Cross‑wind distance y (m)\")\n",
    "plt.ylabel(\"Upwind distance −x (m)\")\n",
    "plt.title(\"2‑D LS Footprint\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(out_dir / \"footprint_2d.png\", dpi=200)\n",
    "plt.close()\n",
    "\n",
    "plt.figure(figsize=(6, 4))\n",
    "plt.plot(-xx, fx)\n",
    "plt.xlabel(\"Upwind distance (m)\")\n",
    "plt.ylabel(\"f(x) (m$^{-1}$)\")\n",
    "plt.title(\"Cross‑wind integrated footprint\")\n",
    "plt.grid(True)\n",
    "plt.tight_layout()\n",
    "plt.savefig(out_dir / \"footprint_fx.png\", dpi=200)\n",
    "plt.close()\n",
    "\n",
    "print(\"Saved outputs to:\", out_dir.resolve())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b00d4376",
   "metadata": {},
   "source": [
    "\n",
    "## 8) Tips & next steps\n",
    "\n",
    "- Increase `n_particles` for smoother fields (e.g., 50,000–200,000).\n",
    "- Adjust `domain`, `dx` and `dy` to control the spatial extent and resolution.\n",
    "- If you have measured `USTAR`, use it directly; otherwise, provide a better local estimate for `z0` and set your actual `zm`.\n",
    "- The current `L` parameter is kept for future extensions (e.g., stability‑dependent turbulence); it is not used in the core update step here.\n",
    "- For climatological footprints, repeat runs across many time steps and average the resulting `F` fields (watch memory and runtime).\n"
   ]
  }
 ],
 "metadata": {},
 "nbformat": 4,
 "nbformat_minor": 5
}