model comparison plot 4.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8add6620",
   "metadata": {},
   "outputs": [],
   "source": [
    "%run SAT_help_functions.ipynb\n",
    "\n",
    "datasets = ['Dutilh2013', 'Dutilh2019', 'Evans2017', 'Lerche2017', 'Rae2014', 'Wagenmakers2008']\n",
    "dataset_names = ['Dutilh 2013', 'Dutilh 2019', 'Evans 2017', 'Lerche 2017', 'Rae 2014', 'Wagenmakers 2008']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a8a6f1ca",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "0e3cf31b",
   "metadata": {},
   "source": [
    "## Using function to plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c6366f7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "def BIC_to_likelihood(BIC, k, n):\n",
    "    x = np.exp((-BIC+k*np.log(n))/2)\n",
    "    if x < np.log(2.2E-308):\n",
    "        return 2.2E-308\n",
    "    if x > np.log(1.7E+308):\n",
    "        return 1.7E+308\n",
    "    return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "aa6a9076",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "95261ef7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "145307fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_BIC_EJ(model):\n",
    "    \n",
    "    df = pd.read_csv(\"Parameter Estimates/\"+model+\"resultWagenmakers2008.csv\")\n",
    "    df_n = pd.read_csv(\"Parameter Estimates/n_Wagenmakers2008.csv\")\n",
    "\n",
    "    df[\"n\"] = df_n[\"N\"]\n",
    "    df[\"k\"] = [len(df.columns)-5]*len(df)\n",
    "    df[\"ll\"] = df[\"BIC\"] - df[\"k\"]*np.log(df[\"n\"])\n",
    "\n",
    "    BIC = np.array(df.groupby('Participant')['ll'].sum() + df.groupby('Participant')['k'].mean()*np.log(df.groupby('Participant')['n'].sum()))\n",
    "    return BIC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "c81bc1c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-1175.77034019,  -529.12451784, -1468.97109555, -1618.71957009,\n",
       "        -613.69209404,  -273.17728716,   943.72367936,  -785.03255678,\n",
       "       -1813.95787679, -1993.21504434,   106.69181832,   188.22763338,\n",
       "        -223.63468184,  -611.6140789 ,   345.44009167, -1107.53261211])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BIC\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "94d2edae",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Drift Rate Speed</th>\n",
       "      <th>Drift Rate Accuracy</th>\n",
       "      <th>BSpeed</th>\n",
       "      <th>BAcc</th>\n",
       "      <th>Collapse Speed</th>\n",
       "      <th>Collapse Accuracy</th>\n",
       "      <th>Non-decision Time Speed</th>\n",
       "      <th>Non-decision Time Accuracy</th>\n",
       "      <th>BIC</th>\n",
       "      <th>Frequency</th>\n",
       "      <th>Participant</th>\n",
       "      <th>n</th>\n",
       "      <th>k</th>\n",
       "      <th>ll</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>3.004488</td>\n",
       "      <td>3.550522</td>\n",
       "      <td>0.516220</td>\n",
       "      <td>0.569945</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.636364</td>\n",
       "      <td>0.357856</td>\n",
       "      <td>0.377005</td>\n",
       "      <td>-258.758052</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>156</td>\n",
       "      <td>8</td>\n",
       "      <td>-299.156900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>2.402747</td>\n",
       "      <td>2.310603</td>\n",
       "      <td>0.503449</td>\n",
       "      <td>0.599552</td>\n",
       "      <td>0.466667</td>\n",
       "      <td>0.085711</td>\n",
       "      <td>0.377105</td>\n",
       "      <td>0.379175</td>\n",
       "      <td>-131.605080</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>150</td>\n",
       "      <td>8</td>\n",
       "      <td>-171.690162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0.893472</td>\n",
       "      <td>1.762489</td>\n",
       "      <td>0.546061</td>\n",
       "      <td>0.537191</td>\n",
       "      <td>0.289474</td>\n",
       "      <td>0.068181</td>\n",
       "      <td>0.346250</td>\n",
       "      <td>0.399448</td>\n",
       "      <td>-13.165765</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>157</td>\n",
       "      <td>8</td>\n",
       "      <td>-53.615731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>2.336344</td>\n",
       "      <td>2.847524</td>\n",
       "      <td>0.500203</td>\n",
       "      <td>0.503030</td>\n",
       "      <td>0.000208</td>\n",
       "      <td>0.081876</td>\n",
       "      <td>0.344316</td>\n",
       "      <td>0.393658</td>\n",
       "      <td>-160.678389</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>147</td>\n",
       "      <td>8</td>\n",
       "      <td>-200.601849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>3.127804</td>\n",
       "      <td>2.542635</td>\n",
       "      <td>0.560067</td>\n",
       "      <td>0.666177</td>\n",
       "      <td>0.081395</td>\n",
       "      <td>0.460524</td>\n",
       "      <td>0.357555</td>\n",
       "      <td>0.354519</td>\n",
       "      <td>-164.218917</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>148</td>\n",
       "      <td>8</td>\n",
       "      <td>-204.196615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>0</td>\n",
       "      <td>2.473551</td>\n",
       "      <td>2.402917</td>\n",
       "      <td>0.813833</td>\n",
       "      <td>0.927307</td>\n",
       "      <td>0.826087</td>\n",
       "      <td>0.133394</td>\n",
       "      <td>0.311746</td>\n",
       "      <td>0.406767</td>\n",
       "      <td>-204.242102</td>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "      <td>309</td>\n",
       "      <td>8</td>\n",
       "      <td>-250.108832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>0</td>\n",
       "      <td>1.741959</td>\n",
       "      <td>1.688959</td>\n",
       "      <td>0.572304</td>\n",
       "      <td>0.704000</td>\n",
       "      <td>0.145410</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.331606</td>\n",
       "      <td>0.464750</td>\n",
       "      <td>7.393102</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>306</td>\n",
       "      <td>8</td>\n",
       "      <td>-38.395579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>0</td>\n",
       "      <td>2.097835</td>\n",
       "      <td>2.617806</td>\n",
       "      <td>0.750649</td>\n",
       "      <td>1.076347</td>\n",
       "      <td>0.515152</td>\n",
       "      <td>0.217062</td>\n",
       "      <td>0.317224</td>\n",
       "      <td>0.410499</td>\n",
       "      <td>-139.688114</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>305</td>\n",
       "      <td>8</td>\n",
       "      <td>-185.450608</td>\n",
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       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>0</td>\n",
       "      <td>2.344213</td>\n",
       "      <td>2.208976</td>\n",
       "      <td>0.824453</td>\n",
       "      <td>0.952635</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>0.225000</td>\n",
       "      <td>0.320416</td>\n",
       "      <td>0.414808</td>\n",
       "      <td>-147.625200</td>\n",
       "      <td>5</td>\n",
       "      <td>17</td>\n",
       "      <td>301</td>\n",
       "      <td>8</td>\n",
       "      <td>-193.282082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0</td>\n",
       "      <td>2.099490</td>\n",
       "      <td>2.204830</td>\n",
       "      <td>1.094247</td>\n",
       "      <td>1.374779</td>\n",
       "      <td>0.944444</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.241287</td>\n",
       "      <td>0.309254</td>\n",
       "      <td>-55.436520</td>\n",
       "      <td>6</td>\n",
       "      <td>17</td>\n",
       "      <td>299</td>\n",
       "      <td>8</td>\n",
       "      <td>-101.040068</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0  Drift Rate Speed  Drift Rate Accuracy    BSpeed      BAcc  \\\n",
       "0            0          3.004488             3.550522  0.516220  0.569945   \n",
       "1            0          2.402747             2.310603  0.503449  0.599552   \n",
       "2            0          0.893472             1.762489  0.546061  0.537191   \n",
       "3            0          2.336344             2.847524  0.500203  0.503030   \n",
       "4            0          3.127804             2.542635  0.560067  0.666177   \n",
       "..         ...               ...                  ...       ...       ...   \n",
       "91           0          2.473551             2.402917  0.813833  0.927307   \n",
       "92           0          1.741959             1.688959  0.572304  0.704000   \n",
       "93           0          2.097835             2.617806  0.750649  1.076347   \n",
       "94           0          2.344213             2.208976  0.824453  0.952635   \n",
       "95           0          2.099490             2.204830  1.094247  1.374779   \n",
       "\n",
       "    Collapse Speed  Collapse Accuracy  Non-decision Time Speed  \\\n",
       "0         0.000000           0.636364                 0.357856   \n",
       "1         0.466667           0.085711                 0.377105   \n",
       "2         0.289474           0.068181                 0.346250   \n",
       "3         0.000208           0.081876                 0.344316   \n",
       "4         0.081395           0.460524                 0.357555   \n",
       "..             ...                ...                      ...   \n",
       "91        0.826087           0.133394                 0.311746   \n",
       "92        0.145410           0.000081                 0.331606   \n",
       "93        0.515152           0.217062                 0.317224   \n",
       "94        0.800000           0.225000                 0.320416   \n",
       "95        0.944444           0.500000                 0.241287   \n",
       "\n",
       "    Non-decision Time Accuracy         BIC  Frequency  Participant    n  k  \\\n",
       "0                     0.377005 -258.758052          1            1  156  8   \n",
       "1                     0.379175 -131.605080          2            1  150  8   \n",
       "2                     0.399448  -13.165765          3            1  157  8   \n",
       "3                     0.393658 -160.678389          4            1  147  8   \n",
       "4                     0.354519 -164.218917          5            1  148  8   \n",
       "..                         ...         ...        ...          ...  ... ..   \n",
       "91                    0.406767 -204.242102          2           17  309  8   \n",
       "92                    0.464750    7.393102          3           17  306  8   \n",
       "93                    0.410499 -139.688114          4           17  305  8   \n",
       "94                    0.414808 -147.625200          5           17  301  8   \n",
       "95                    0.309254  -55.436520          6           17  299  8   \n",
       "\n",
       "            ll  \n",
       "0  -299.156900  \n",
       "1  -171.690162  \n",
       "2   -53.615731  \n",
       "3  -200.601849  \n",
       "4  -204.196615  \n",
       "..         ...  \n",
       "91 -250.108832  \n",
       "92  -38.395579  \n",
       "93 -185.450608  \n",
       "94 -193.282082  \n",
       "95 -101.040068  \n",
       "\n",
       "[96 rows x 15 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "fad6e17c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a9e7d832",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Frequency', ylabel='Boundary Separation Speed'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(df, x = \"Frequency\", y = \"Boundary Separation Speed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "32718408",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Frequency', ylabel='Boundary Separation Accuracy'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(df, x = \"Frequency\", y = \"Boundary Separation Accuracy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f0d552b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"Parameter Estimates/OUM2v2k2terresultWagenmakers2008.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3bc42ca7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Frequency', ylabel='Boundary Separation'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(df, x = \"Frequency\", y = \"Boundary Separation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "aabb283c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def BIC_to_exp(BIC):\n",
    "    return np.exp(-BIC/2)\n",
    "def BIC_to_likelihood(BIC, k, n):\n",
    "    return np.exp((-BIC+k*np.log(n))/2)\n",
    "#dataset = \"Dutilh2019\"\n",
    "#models = [\"DDM2v2c2ter\",\"OUM2v2k2ter\"] \n",
    "#sortby = \"OUM2v2k2ter\"\n",
    "def plot_BIC_comparison(ax,dataset, models, sortby = \"OUM2v2k2ter\"):\n",
    "\n",
    "    BIC_all = pd.DataFrame(columns = models)\n",
    "    for model in models:\n",
    "        if dataset==\"Wagenmakers2008\":\n",
    "            BIC_all[model] = get_BIC_EJ(model)\n",
    "        else:\n",
    "            if model == \"DDM2v1sv2a2ter\" or model == \"DDMfull\":\n",
    "                bic_dir = \"/Users/wangjiashun/Desktop/Reserach on SAT/datasets/transformed/\"+model+\"_\"\n",
    "                BIC_all[model] = pd.read_csv(bic_dir+dataset+\".csv\").astype('float64')[['BIC']]                \n",
    "            else:\n",
    "                BIC_all[model] = pd.read_csv(\"Parameter Estimates/\"+model+\"result\"+dataset+\".csv\").astype('float64')[['BIC']]\n",
    "    # solving the numerical issue\n",
    "    for i in range(len(BIC_all)):\n",
    "        tmp_max = np.max(np.array(BIC_all.loc[[i]]))\n",
    "        tmp_min = np.min(np.array(BIC_all.loc[[i]]))\n",
    "        np_max = -np.log(2.2E-308)/2 # 354\n",
    "        np_min = -np.log(1.7E+308)/2 # -354\n",
    "\n",
    "        if tmp_max > np_max and tmp_min < np_min:\n",
    "            for model in models:\n",
    "                if BIC_all.loc[i,model] > np_max:\n",
    "                    BIC_all.loc[i,model] = np_max\n",
    "                if BIC_all.loc[i,model] < np_min:\n",
    "                    BIC_all.loc[i,model] = np_min\n",
    "\n",
    "        elif tmp_max > np_max and tmp_min > np_min:\n",
    "            dif_max = tmp_max-np_max\n",
    "            BIC_all.loc[[i]] -= dif_max\n",
    "        elif tmp_min < np_min and tmp_max < np_max:\n",
    "            dif_min = tmp_min - np_min\n",
    "            BIC_all.loc[[i]] -= dif_min\n",
    "\n",
    "    for model in models:\n",
    "        BIC_all[model] = BIC_to_exp(BIC_all[model])\n",
    "\n",
    "    BIC_all[\"Sum\"] = BIC_all.sum(axis = 1)\n",
    "\n",
    "    for model in models:\n",
    "        BIC_all[model] = BIC_all[model]/BIC_all[\"Sum\"]\n",
    "\n",
    "    BIC_all = BIC_all.drop(labels = 'Sum',axis = 1)\n",
    "    BIC_all = BIC_all.sort_values(by = sortby, axis = 0)\n",
    "    BIC_all = BIC_all.reset_index(drop=True)\n",
    "    BIC_all.index += 1\n",
    "    if models==[\"DDM2v2a2ter\",\"OUM2v2k2ter\"]:\n",
    "        color=[\"#ff7f0e\", \"#1f77b4\"]\n",
    "    elif models==[\"OUM2v2a2ter\",\"OUM2v2k2ter\"]:\n",
    "        color=[\"#a1c9f4\",'#1f77b4']\n",
    "    elif models == [\"OUM2v2a2k2ter\",\"OUM2v2k2ter\",\"OUM2k2ter\"]:\n",
    "        color=[\"#a1c9f4\",'#699ADD','#1f77b4'] #3179C6 88BDDF\n",
    "    else:\n",
    "        color=[\"#F29A2E\", \"#1f77b4\"]\n",
    "        \n",
    "    return BIC_all.plot(ax = ax, kind='bar', title = dataset, legend =False, stacked=True, width=1,edgecolor='black'\n",
    "                        ,color=color)\n",
    "\n",
    "# DDM vs OUMk    [\"#ff7f0e\", \"#1f77b4\"]\n",
    "\n",
    "# OUMa vs OUMk   [\"#a1c9f4\",'#1f77b4']\n",
    "\n",
    "# DDMc vs OUMk   [\"#F29A2E\", \"#1f77b4\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e99272be",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_all_datasets(models, labels, sortby, xlabelsize=15, titlesize = 20, figsize=(18, 12)):\n",
    "    figure, axes = plt.subplots(2,3,figsize=figsize)\n",
    "    plot_BIC_comparison(ax = axes[0,0],dataset = \"Dutilh2013\", models = models, sortby = sortby)\n",
    "    plot_BIC_comparison(ax = axes[0,1],dataset = \"Dutilh2019\", models = models, sortby = sortby) # float 128 issue\n",
    "    plot_BIC_comparison(ax = axes[0,2],dataset = \"Evans2017\", models = models, sortby = sortby)\n",
    "    plot_BIC_comparison(ax = axes[1,0],dataset = \"Lerche2017\", models = models, sortby = sortby)\n",
    "    plot_BIC_comparison(ax = axes[1,1],dataset = \"Rae2014\", models = models, sortby = sortby)\n",
    "    plot_BIC_comparison(ax = axes[1,2],dataset = \"Wagenmakers2008\", models = models, sortby = sortby) # float 128 issue\n",
    "    \n",
    "    axes[0,0].set_title(\"Dutilh2013\",fontsize = titlesize)\n",
    "    axes[0,1].set_title(\"Dutilh2019\",fontsize = titlesize)\n",
    "    axes[0,2].set_title(\"Evans2017\",fontsize = titlesize)\n",
    "    axes[1,0].set_title(\"Lerche2017\",fontsize = titlesize)\n",
    "    axes[1,1].set_title(\"Rae2014\",fontsize = titlesize)\n",
    "    axes[1,2].set_title(\"Wagenmakers2008\",fontsize = titlesize)\n",
    "    axes[1,0].set_xlabel(\"Participants\", fontsize = xlabelsize)\n",
    "    axes[1,1].set_xlabel(\"Participants\", fontsize = xlabelsize)\n",
    "    axes[1,2].set_xlabel(\"Participants\", fontsize = xlabelsize)\n",
    "\n",
    "    axes[0,2].legend(labels = labels, loc='upper left', bbox_to_anchor=(1.03, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "a8c5c1f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_all_datasets_flat(models, labels, sortby, xlabelsize=15, titlesize = 20, figsize=(30, 4)):\n",
    "    sns.set_style(\"whitegrid\", {'axes.grid' : False})\n",
    "    figure, axes = plt.subplots(1,6,figsize=figsize)\n",
    "    for i in range(6):\n",
    "        plot_BIC_comparison(ax = axes[i],dataset = datasets[i], models = models, sortby = sortby)\n",
    "        axes[i].set_title(dataset_names[i],fontsize = titlesize, fontweight='bold', fontname='Arial')\n",
    "        axes[i].set_xlabel(\"Participants\", fontsize = xlabelsize, fontname='Arial')\n",
    "        axes[i].set_ylim(0,1)\n",
    "        axes[i].tick_params(axis='both', which='major', labelsize=7)\n",
    "    axes[0].set_ylabel('Model Weight', fontsize=xlabelsize, fontname='Arial')\n",
    "    axes[5].legend(labels = labels, loc='upper left', bbox_to_anchor=(1.03, 1),fontsize=10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d29987d7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "2aeed7ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"DDM2v2a2ter\",\"OUM2v2k2ter\"] \n",
    "labels = [\"Threshold DDM\",\"Self-excitation OUM\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "3f1fc7b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"OUM2v2a2ter\",\"OUM2v2k2ter\"] \n",
    "labels = [\"Threshold OUM\",\"Self-excitation OUM\"] \n",
    "sortby = \"OUM2v2k2ter\"\n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "3b921c0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"DDM2v2a2Weibull2ter\",\"OUM2v2k2ter\"] \n",
    "labels = [\"CBM\",\"Self-excitation OUM\"] \n",
    "sortby = \"OUM2v2k2ter\"\n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5e422e07",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "2453cc2a",
   "metadata": {},
   "source": [
    "## Supplementary materials"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "4246c6ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uNHFxcaZHjx6mU6dO5vPPPzdJSUnmnXfeMUuXLjWdO3f2vV8eeeQRV++X/PuVQO+Xgj8XJ++XSZMmmcGDB5v27dubpKQkk5GR4Xu/bN261cTHx5sHH3yw0Ptl7dq1ju+l4L2SvD8IVsOXVJ3upJZ2Ui8Hq4md1rt2Na2TmtVJXRqs9nRSVwarHZ3Uh8HmiZzMETmdH7KbF3IyHxRsLsjJdSvY/I+TeR+n8z12cz1O5nic5GG+QLlojH025rPLyHx2WWmMfV6i5IVjnqk0r2t4lTHGOJt7Ccc6htP5EC/XL5zMX3i5bhGONQsv1yrCtU7hRWbl8zq7jLHOL5R/5WVNxI1Q1k8CKQ9rKm6FugbjL9Q1GX9erNEU5MV6jb9Q1m/8hbqe4y/U9R2gOLEZD8XOf0HB7ubp0KFDjsLLbrGhICcLDwUF2/iVlJRUaEHC6kbKbnHCn5sbqjvvvLPIDdXbb79dqJ3VDdWECRMKtdu2bZvp0aOHue2228ykSZNMamqqOXv2rHn00UeLtEtISDB9+vQpdGMbqF23bt1M7969C7V74IEHArYr2N+xY8dsz7to0SLz1ltvBTyvf9v169cH7bNly5Zm0qRJZteuXQFf82effeb4NRc8b2pqqjl48GDAdp06dTKNGjXyTSgGOq8xxhw/ftyMGjXKJCUlmU2bNpm2bduazp07m82bNwdsl5ycbFJTU03Hjh1Nly5dirRLT0931A5AeLjJSCtOszMQp3lqx23WWnGy+ToQp9lsxU1mB+LFpgOnGW/FafYH4rQeAJwIdk2zul4Vx0Yiu2vDhW4ksvusWn0Ohw8fbvkZs6uz7Wpru3raroa2q5nt6mS72tiuHrarge1qXrs61662DfS8gn2OHj3aJCcnm+3bt5sOHToE7HP79u1Fnjdq1Cjzn//8x2zatMl06NDBd8xqLJ9//nmRY4Gel5SU5Dtfwfo8JyfH7Nixw2zevNn07dvX5OTkBHxP/vnPfy7059OnT/sWD/OP5S+WnT17ttDz8hcjCzp8+LCpV69ewHPl5eUVeV5eXp7Zu3dvkXH69+0/TsBLTmvpYPVysJrYTb1rVdM6qVmd1KXBak8ndWWw2jFYfehknsjJHFGw+SEn80JO5oOCzQU5mQMKNv/jZN7HyXxPsLkeJ3M8dnlYsI1VLvqfxz8b/c8TKCPz2WVloOOB+gDCxauMMcbZ3Es41jGczod4uX7hZP7Cy3WLcKxZeLlWEa51Ci8yK59X2ZXfzi6/ACAQL9Zg/IWyJuPPizWagrxar/F3oes3/kJdz/EX6voOUJzYjIcSkZOTY1JTU83mzZvNjh07fDuyCxo2bJjlf4EUXGzIF+jbwwouPBgTfHH88OHDZubMmcFeUtD+8vLyzJ49e8zmzZvNrl27Ar5mJ+Oxkpqaag4dOhTwWHp6uvniiy/MiRMnjDEm4AJOQkKC2bt3r9m5c6eJj483K1euNMYUvblOSEgwe/bscdQuUH/+O/e9Pq/bPkviNV9oO2OMGTBggFmwYIGZPHmyadGihdm/f785cuSI6d279wW3S0lJ8bX7/vvvA7YDED5OMtKK2+wMxGme2nGbtVbcZrAVt+d3mtlenMsJu4y34iT7A3GTUYATVte0YNcru2uRk2uMk+tHwedZfe7dfKb9P6uBPod2nzG7mtOutva6TyfHvO7TrpYNdsyqtg2lTy+OuRlLwddQ8Nitt95qWrRoYdq1a2fatm1rGjVqZNq1a2fatWtX5FjDhg1N27ZtLY/ZPc/rPp2OEygOwWppp/VysJrYTb3rtKYN1EewutRt7WlVV9rVjsHqQydzJk7miIrzPG7aeHEeJ+NwMo8TrI2TOR6vzhNqH4Ha+I/X6dwWEC5eZYwxzuZewrGO4WQ+xOv1i2DzF17O4YdjzcLLNYNwrVN4lQP57bzILjftAMBfKGsw/rxYk/HnxRpNQV6t1/jzav3GX6jjC2V9ByhOFcP9z+Si/Bs+fLjlsYL/ZnxcXJzGjh2r5557LqQ+Gzdu7PrcgdrlPxasndP+ArWTpFdeecXTPp22i4qK0g033CBJmjp1qvr166caNWooIiKi0HOioqJ04403OmoXqD9/F3reBx54IGA7t32WxGu+0HaSlJWVpfj4eEnStm3bVLNmTUkq0tZNu27duvnaXX/99QHbAQgPN3kRiJvsdHv+gnl6oX04eQ1OM7gkz+/m+U5zvDjHEMrz3WQUEIzde9HuemX3vHnz5nk2hnA4cOCA5WfMrua0q63tPrd2NXSw53k5zmDH7GrZYMesattQ+vTimJuxFHwNBY/Nnz9fo0eP1pAhQ9SgQQMlJiZq5syZkqS9e/eW+WOA15zUQE7q5WA1sZPzBKtpL7QP/zbBak8vzhOsPnQyZ+JkjsjteQLNCzmpZYvz9RTsI9g4nMzjBGvjZI7Hq/OE2kegNv7jdTq3BYSDVxkTrK/8uZdwrGM4PaeX6xdO2ng5hx+ONQsv1wzCtU7hVQ7kt/Miu9y0A4CCQp179xfqmow/L9ZonPZ3Ia831PUbJ/3lKw39AV5iMx6KXVxcnMaMGaN//etftu3at2+vLVu26Pjx4+rYsaMnfbpp5yQ4vT5vOM99+eWXa+LEiRowYIBq1KihCRMmaNCgQcrOzi6V7caPHx+wXWkaY6jtJOnqq6/W6NGj9eSTTyo5OVmSNGvWLFWrVq1Y2wEIDzd5EYib7CyO83vRR6g3r16cP5zj92oMF/p8NxkFBGP3XmzWrJnl9erUqVOWzwt2zOrzV1r6PHTokOVnLDY2ttiPFayhS+J8To81adLEskatWrXqRXvsxhtv1Lhx4/Tiiy+qXr16hRaVysMxwGtOaiAn9XKwfpycJ1hN6LSP0nCeYPWhk/rRizZO5oWK4zzF1YeT+Zlgbbzoo6ydBwgXrzLGaV/hWMcoref0cs49HGsWZWn8Vu28yoFw9AUA/rxYAyko1DUZf16Przj683LzYWl/vYCnwv3VfLg4jBo1yixZsiQsfZb2duE699mzZ82sWbNMZmam77EffvjBPPvss2WqXVkYo5vXkpOTY957771Cj82dO9ecOnWqWNsBCJ/iyMiSPn+ofVzszw/nGNxkFODEhb4X7Z5Xlo/ZfcYu5mN2NerFfMz/Mat/bqk8HAO84lUtHawfJ+cpiT5K4jzB6kMn9aMXbcrSeZz04eT6H6yNF32UtfMA4eTlfI1XGeB1u9J4Ti/n3MMxz19a+3LTzqscCEdfABBIuNdggvF6fPQHlA4RxhgT7g2BAAAAAAAAAAAAAAAAAACUZZHhHgAAAAAAAAAAAAAAAAAAAGUdm/EAAAAAAAAAAAAAAAAAAAgRm/EAAAAAAAAAAAAAAAAAAAgRm/FQZixYsEAxMTFF/qtfv74aN26szp0766WXXlJaWlqxnD8vL0/z5s3TTz/9VGRM48aNc93fxo0bFRMToyeffNLLYXrqwIEDSklJCfcwAOCCkR0lj+wAAAAAAAAAAMAbrHOUPNY5AISKzXgoc+rVq6chQ4b4/nv44YfVs2dPVatWTW+++abuvfdeHT161PPzPvHEE3r22Wd15swZ32P169fXkCFDdPvtt7vu79prr9WQIUPUoUMHL4fpmdTUVHXp0kVr164N91AAIGRkR8kgOwCUdUxuljwmNwGUdWRHySM7AJRl5EbJIzcAlBesc5QM1jkAeKFiuAcAuFW/fn098sgjAY899dRTeu+99zRx4kQ9//zznp430M1v/fr1Vb9+/Qvq77rrrrN8HaXByZMnde7cuXAPAwA8QXaUDLIDQHlRr149tW/f3vdnY4yys7O1efNmvfnmm1q2bJn++9//6sorr/T0vE888YQWL16sZcuW+R7Ln9xs2rSp6/7yJzdjYmK8HKZnUlNT9ac//UkdO3ZUfHx8uIcDACEhO0oG2QGgvCA3Sga5AaA8YZ2jZLDOAcALbMZDuTJw4EC99957+uSTT8I9FABAGUF2AAD8MblZMpjcBFCekB0lg+wAUF6QGyWD3ABwsWCdAwBKF/6ZWpQrv/71ryVJx48f9z32zTff6Mknn9Rdd92lW265RY0bN1a3bt00ffp05eXl+dodPHhQMTExev755zVp0iTddtttuvXWW/Xoo48qJiZGmzZtkiR16NBB7dq1k2T99e0ZGRkaP368OnfurEaNGunOO+/U0KFDtXv3bl+bQF/fPmzYMMXExOjAgQN66aWX1KJFCzVu3FgJCQlaunRpwNe8bNkyPfjgg7rjjjvUoEED3Xbbberbt69WrFhRqF3+WJcsWaJ3331X3bp1U6NGjdS8eXM98cQTOnDgQKFx9O3bV5K0aNEixcTEaMGCBZKkrKwsjRkzRl27dlVsbKyaNm2qxMRELV682OHfEgCULmQH2QEAbgwcOFCSmNwEADhGdgAA3CA3AABusc7BOgeA0oVvxkO5sm/fPknS1VdfLUlas2aNBg4cqCpVqqh9+/a64oordPjwYX300UcaNWqU0tLS9NRTTxXqY+nSpTpz5ozi4+N14sQJderUSTfddJNSUlJ06NAhJSYm6rrrrrMcw4kTJ9SzZ0/t3btXDRo0UM+ePXXs2DEtWbJEa9as0ezZs3XzzTfbvo6hQ4dq3759+sMf/qDz589r2bJl+utf/6q//e1vGjBggK/da6+9pqSkJF1//fXq0qWLKleurF27dmnVqlXauHGjkpOTdddddxXqe+rUqdq+fbvi4uLUsmVLbdy4Ue+//742b96sxYsXKzo62vf1+CkpKapbt646dOjg+824QYMGaf369WrVqpXatGmjjIwMLV26VEOHDtXp06eVkJDg6O8KAEoLsoPsAAA3rCY3Z8yYoc2bNystLU1RUVGqVauW7r77bvXr10+RkT//HtzBgwcVFxen3r17q0aNGnrzzTeVm5ur1q1ba8mSJb7+OnTooGuvvVYrVqzQggULNHz4cA0cOFBDhw71tcnIyNDUqVO1dOlSHTp0SJdddpluvfVWDRkyRHXq1JH08+R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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"DDM2a2ter\",\"OUM2k2ter\"] \n",
    "labels = [\"DDM2a2ter\",\"OUM2k2ter\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "7e558f64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"OUM2v2a2k2ter\",\"OUM2v2k2ter\",\"OUM2k2ter\"] \n",
    "labels = [\"Full OUM\",\"Self-excitation OUM\",\"OUM2k2ter\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "656e6aba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fNWXKFPl8Pv/fQdWqVbVhwwaddtppAf3Mnj1b27dvl/T739Qrr7yiF154QZ999pmuvPJKzZgxQ+vXr9fWrVvVoUMHLViwQBs3blS7du00b948ffLJJ/rwww+1ePFiPfDAA8XmIK+//rpeeuklSVK7du2UnZ2tU089VaNGjdLFF1+sDz/8UBdccIHWrFmjCy64QJMnT1bfvn1VuXLlcv33Ant25xdOzh2cnB+4OQewmuc7mcOHm6c7mYc7nWt7NZd2Myd2Mt8NntM6nbOGm5e6nXtazSvt5o5ezA+drBGFWx9ysi7kZD0o3FqQkzWgcOs/TtZ9nKz3hFvrcbLG8/bbb1vGw0ceeUSSNHHixIC+i8bFtLQ0jRo1yjI2Fq7d3XvvvZYx8p///Kck6YUXXrCMlZJ9vBw7dqzlzwL/42Rtyssch5f5jWjkNaKZ03C79lJWeQwn6yFe5y/CrV94uU4RjZyFl7mKaOUpvIhZhbyKXVL4+IXIRZrzCBZpDiRYpDmRYF7lSIJFkjMpKtL8SSiR5lSCRZpjCeZVziVYtHMw4Xidoykq0nxNMLf5m2Be5HOCRZLfAeBchSwu7Nixo8aPH6+HH37Ytl3t2rU1YcIE3XrrrapVq5aee+45DR06VMeOHQtol5OTo9TUVEnSxo0bVbduXUkqNjk699xz9cwzz+jxxx9Xo0aNLCdPmZmZGjhwoA4ePKj3339fXbt21cSJE1WrVq1ibStVqqRatWqpUqVKatq0qSSpXr16xdpVq1ZNo0eP1meffaYJEyZo3759atOmjerWras+ffr42/3xj3/UyJEjlZubq5NOOknp6emqWbOmateuHdDf6aefrtGjR6tt27ZaunSpGjdurBUrVuikk04qtm+nJ4OffvppyJ+HpGIBL1qFbF4XsUnRO0HMyMjQjBkzVKNGDf9r2dnZGjRoUMDvpUuXLtq/f79OPvnkgJ+Rz+fTRx995H9t+fLlevPNNyVJ48aN04MPPqjHH39cxpiAz5Genq733ntP+/fvV9++fbVixQolJiaqX79+Ab+TDz74QIcOHVK7du0k/T5B3bt3r+XPR/r9ROCVV15RtWrVlJubqxtvvDHg97J161Y9+uijGjBggKZPn66TTjpJBQUF6t27d8DvpUmTJurfv79uv/12XXTRRbruuuvUuHHjYvvLyMjQO++8o6NHj+q6667Txx9/rKSkJPXr1y+g3dSpUzVjxgxVrlxZhw4d0sMPP6wXX3xRf/vb3zRjxoyAtu+++65ef/11JSUl+V87ceKE+vXrF1BcePfdd2vv3r2qV69ewM/Y5/MFfAe+++47/z5mzJihO+64Q//973+L/V7gntNYYsVpjLHiNPZYcRqTrLiJVVacxjArTmObFacxz4qbWGgl0gVTN7EzFKfx1I7TWGvFTTF5KE5jsxU3MTsUp3HcjtMYb8VNEXswp/MBOGcVH3744QfL4/6ZZ55peUy3O17bHYv37dtneYy1O37aHRsTEhJsj3t2x7Sic8lg69ati4vCqJIU0h06dEhvvvlmyO/Y008/bTnPPvXUUy3n1nbz6Ro1aoSdQ4eaMxcUFFjOk+3mxnbz4W+++cZyDlxQUGA5550zZ47lPDcvL89ybjtz5kx98MEHOnjwoHr16qXly5dLkgYMGCBjjLZs2aJ+/frJGKPKlSsHLNhK0tKlSzV9+nT/z3LAgAHy+Xzq1auXBg4cqFdeeUU+n0/9+vVT7969dd555+nhhx/WE088oaSkJF1//fVq06aNqlWrptmzZ2vevHn67bff1KNHDy1ZskSSNHDgQL377rt69dVX5fP5dPz4cd11112aPHmyf5xWx+Ty8PcCe3bnFzNmzAh77uDk/MDJOUC4eb6TOXy4ebqTebiTubaTubST+XK4ObGT+W64Oa0XRXBS+Lmnk3lluLljuPmhk3UiJ2tE4daH3KwL2a0HhVsLcnLcCrf+42Tdx8l6T7i1HidrPHbxsNC+ffvCxkUpdGws/JvPysqyjJGF7GKlJNt4CWecrE15mePwMr8RjbyG1zkNp2syXhRcF/IyjxGNC/GdrF94mbeIZs7Ci1xFtPIUXsSsQl7FLsl5/ELJRZrzCBZpDiRYpDmRYJHmSIJ5kTMpKtL8SSiR5lSCRZpjCeZFziWY1xfXR5qTCeZFjqaoSPM1wSLN3wSLNJ8TLNL8DgDnKmRxYadOnfT555/rwIED6tKli2W7sWPH6u233/ZPcs8991xNnTpV//nPfwLanX766Ro7dqzuvfdeZWRkSJJee+21gJOfQlWqVNFjjz2mmTNnqqCgIOR+P/jgA2VnZ+vbb7/191GrVi0NGzasWNsrrrhCd955pxo1aqShQ4eqbdu2WrFihf+KiEKFn6Fly5Zq2bKlDh48qPXr1+v7778PaPf0009r2bJlSk5OVvXq1fXyyy/L5/MVuyJl7NixmjlzppYsWaKGDRvq+uuv15dffqlnnnmm2BidngxOnz5dX3/9tS655JJifQQH42gXsnlVxCZF7wQxPz9flSoFHgISEhKUkJAQ8Nrrr7+uW2+9VVOmTNEpp5xi+TMxxqigoEAJCQm655579MADD+j5558vNhkvKChQ5cqVlZycrLvvvluJiYkqKCgoduXOiy++qPT0dB07dkx33XWX7aTn0KFD2rNnj0499dSAv4ETJ04U+3w///yz6tWrp3379qlu3br65ZdfivXn8/l02WWX6e2339aiRYuUnp6ubdu26eSTT9Ybb7wR8DNMTEyUz+dTfn6+8vPz/UnPoo4cOaL8/Hz/v/ft26fq1avrt99+K7bv/Px8HTx4MODuKgcOHCh2Bc1LL72kgQMHasyYMTrjjDNC/lwK+8vOzlaNGjV0ww03aP/+/Ro1apTl8QfOOY0lVpzGGCtuYo8VJzHJiptYZcVpDLPiNLZZcRrzrLiJhVYiLexyEztDcRpP7TiNtVZKUkweSrjYbMVNzA7FiyIKpzHeipsi9mBO5wNwzio+TJ482fK4f/ToUdtjutXx2u5YPHnyZMtj7Ndffy0p9PHT7tiYlJRke9yzO6adddZZlserHTt2xEVhVEkK6S6//HLL75jdPLt3796Wc2u7+bTdHLpnz56Wc+bKlStbzpPt5sZ28+Fjx45ZzoETExMt57x289w+ffpYzm2NMTp8+LBq1aqlxx57TNLvV0MfP35cjz76qN59912tWbNGDz74oGbNmuVPSGRkZGjNmjU65ZRTlJWVpdNOO02HDx/W8ePHVb16dW3atEnNmjXTF198oZSUFH355ZdKSEiQz+dT/fr1NWXKFH399deaM2eOJk2apOzsbNWsWVP79u3TgQMHlJ2draysLFWpUkXHjx9Xbm6u9u/fr9NOO02//vqrjhw5ooSEBB0/flyJiYlh/16mTp1arFg3kr+XSZMmKScnx/Lv5bTTTvPs76XouRSKszu/SElJCXvu4PT8INw5QLh5vpM5fLh5upN5uJO5tpO5tJP5crg5sZP5rtM5bSRFcFL4uaeTeWW4uWO4+aGTdSIna0Th1oecrAs5WQ8Ktxbk5LgVbv3HybqPk/WecGs9TtZ47OJhIbu4WDh+q9hYKDEx0TJGFv3ZWsXKhQsXKj8/3zJewhkna1Ne5zi8ym9EI6/hdU7D6ZqMFwXXRX+2XuUxonEhvpP1Cy/zFtHIWXiZq4hWnsKLmFW0Ly9ilxQ+fiFykeY8gkWaAwnmRU4kWCQ5kmBe5EyKijR/EkqkOZVgkeZYgnmRcwnm9cX1keZkgnmRoykq0nxNMK/yN8FKms8JFml+B4ALXjxbuaLLzc017733XsBrb775pjl8+HCZ7H/16tVm3LhxZtSoUeapp54yH330UbE27777bpmMJZTrrrvOHDt2LOC1o0ePmuuuuy7gtfz8fNO/f3+zbdu2sH3+9a9/Nfn5+f5/jxw50jz33HNm4MCBxfZ94sQJY4wxM2fO9O/n+uuvL9Znenq6eeqpp0xubq4ZMGBAyP1ee+21Zvfu3eYf//iHyc7ONsYYc+LEiWKfpV+/fuann34yDz30kNm9e7cxxpgff/yxWDtjjH/M+fn5Zv78+WbYsGGmS5cupk+fPgHtUlNTTU5Ojvnll1/MpZdeao4dO2Zyc3OLfZaePXuanJwcY4wxBw8eNDfccIP//UUtXLjQdO/e3aSlpZkRI0aYtLQ0c/XVV5tFixYVG+Pq1avNmjVrQv5MCr311lume/fuJisryxjz+/di+PDhpkmTJgHt3n33XdOtWzdTUFDgf+3mm28206ZNC9nvqlWrzO233x7yZ1coPT3dpKWlmT//+c8mPT3dHDlyxPz5z3/2/84Lbdy40aSmpppbb73VpKSkmNTUVNOpUyezatWqgHZWv//MzMyAf8+ePdtcddVV5tZbbzWPP/646dGjh+ndu7d57bXXAtq9/fbbpnPnzmb48OGmW7duZtGiRWbSpEnm+eefL7aP9evXm9TUVJOammoGDBjg///PP/+8WNtNmzaZL774wvLnYowxH3/8sencubPZv3+//7Vx48YV+70g/kQ79njFSQyzEs3Y5hWnMdKKm9gZitN4asdNrLXiJAZbcRqbrbiJ2aE4jeN2nMZ4K05jfyhu5gMoPaV1TLc6xpbW8dPumGZ3vLI7FoU7xlgdP+yODXbfe7vvtN131ep72LFjR9vvmNU8225u7WQ+HWoObTdntpsn282N7ebDdnPgcHNeq3mu3dx2xYoVpkePHgF/SwMGDDBz5871/3vr1q3mb3/7m+nVq5f/tXfffdc88cQTZsCAAWbKlCnmyJEjpn379mbJkiVm586d5sYbbzSpqammUaNGpnXr1iY1NdVs2rTJ3HjjjSF/LsYYs3z5cpOammpGjBhhpk6datq1a2e6du1qFi5caJYuXWo6duxoevfubbp27Wo+++wzk56ebl5//XWzYMEC061bN//fyx133OHq76XwfCXU30vRn4uTv5eJEyeaYcOGmU6dOpn09HSTnZ3t/3vZsGGDSU1NNbfcckvA38vKlSsdn0vBe2V5fhBuDl9W83Qnc2kn8+Vwc2Kn8127Oa2TOauTeWm4uaeTeWW4uaOT+WG4dSIna0RO14fs1oWcrAeFWwtyctwKt/7jZN3H6XqP3VqPkzUeJ/GwUKi4aIx9bCxkFyML2cVKY+zjJcpeNNaZYjmv4VWMMcbZ2ks08hhO10O8zF84Wb/wMm8RjZyFl7mKaOUpvIhZhbyOXcZYxy+Uf+UlJ+JGJPmTUMpDTsWtSHMwwSLNyQTzIkdTlBf5mmCR5G+CRZrPCRZpfgeAcxQXotQFJ0jsTgZ/+OEHR8HYLnlSlJNESlHhCtnS09MDEixWJ4Z2yZZgbk4Qr7zyymIniK+++mpAO6sTxOeeey6g3caNG03v3r3NxRdfbCZOnGg2b95sjh8/bu68885i7fr06WMGDBgQcKIeql2vXr1M//79A9rddNNNIdsV7S8zM9N2v3PmzDGvvPJKyP0Gt129enXYPtu2bWsmTpxotm3bFvIzf/rpp44/c9H9bt682ezduzdku65du5rmzZv7F0hD7dcYYw4cOGDGjBlj0tPTzbp160z79u1Nt27dzPr160O2y8jIMJs3bzZdunQx3bt3L9YuKyvLUTsA0eEmRlpxGjtDcRpP7biNtVacFJOH4jQ2W3ETs0PxoojCaYy34jT2h+J0PgA4Ee6YZnW8Ko3CKLtjQ0kLo+y+q1bfw5EjR1p+x+zm2XZza7v5tN0c2m7ObDdPtpsb282H7ebAdnNeu3mu3dw21PuK9jl27FiTkZFhNm3aZDp37hyyz02bNhV735gxY8x///tfs27dOtO5c2f/NquxfPbZZ8W2hXpfenq6f39F5+e5ublmy5YtZv369WbQoEEmNzc35N/k3/72t4B/HzlyxJ8MLdxWmPw7fvx4wPsKk6tF/fzzz6ZRo0Yh91VQUFDsfQUFBWbnzp3Fxhncd/A4AS85nUuHmy+HmxO7me9azWmdzFmdzEvDzT2dzCvDzR3DzQ+drBM5WSMKtz7kZF3IyXpQuLUgJ2tA4dZ/nKz7OFnvCbfW42SNxy4eFm1jFReD9xMcG4P3EypGFrKLlaG2h+oDiBavYowxztZeopHHcLoe4mX+wsn6hZd5i2jkLLzMVUQrT+FFzCrkVewqbGcXvwAgFC9yMMEiyckE8yJHU5RX+ZpgJc3fBIs0nxMs0vwOAOcoLkSZyM3NNZs3bzbr1683W7Zs8VfMFzVixAjL/0IpmjwpFOrubkUTKcaET/b//PPPZvr06eE+Utj+CgoKzI4dO8z69evNtm3bQn5mJ+OxsnnzZvPDDz+E3JaVlWW++OILc/DgQWOMCZmQ6tOnj9m5c6fZunWrSU1NNUuXLjXGFF8s6NOnj9mxY4ejdqH6C76ywuv9uu2zLD5zSdsZY8ytt95qZs2aZSZNmmTatGljdu/ebfbt22f69+9f4nazZ8/2t/v+++9DtgMQPU5ipBW3sTMUp/HUjttYa8VtDLbidv9OY7YX+3LCLsZbcRL7Q3ETowAnrI5p4Y5XdsciJ8cYJ8ePou+z+t67+U4Hf1dDfQ/tvmN2c067ubXXfTrZ5nWfdnPZcNus5raR9OnFNjdjKfoZim676KKLTJs2bUyHDh1M+/btTfPmzU2HDh1Mhw4dim1r1qyZad++veU2u/d53afTcQKlIdxc2ul8Odyc2M181+mcNlQf4ealbueeVvNKu7ljuPmhkzUTJ2tEpbkfN2282I+TcThZxwnXxskaj1f7ibSPUG2Cx+t0bQuIFq9ijDHO1l6ikcdwsh7idf4i3PqFl2v40chZeJkziFaewqs4UNjOi9jlph0ABIskBxPMi5xMMC9yNEV5la8J5lX+Jlik44skvwPAuUrRfiwzyr+RI0dabnvyySf9/9+xY0eNHz9eDz/8cER9tmjRwvW+Q7UrfC1cO6f9hWonSU899ZSnfTptl5SUpHPOOUeSNHnyZA0ePFi1atWSz+cLeE9SUpLOPfdcR+1C9RespPu96aabQrZz22dZfOaStpOknJwcpaamSpI2btyounXrSlKxtm7a9erVy9/u7LPPDtkOQHS4iRehuImdbvdfNJ6WtA8nn8FpDC7L/bt5v9M4XppjiOT9bmIUEI7d36Ld8crufTNnzvRsDNGwZ88ey++Y3ZzTbm5t9721m0OHe5+X4wy3zW4uG26b1dw2kj692OZmLEU/Q9Ftb7/9tsaOHau0tDQ1adJEAwcO1PTp0yVJO3fujPttgNeczIGczJfDzYmd7CfcnLakfQS3CTf39GI/4eaHTtZMnKwRud1PqHUhJ3PZ0vw8RfsINw4n6zjh2jhZ4/FqP5H2EapN8Hidrm0B0eBVjAnXV+HaSzTyGE736WX+wkkbL9fwo5Gz8DJnEK08hVdxoLCdF7HLTTsAKCrStfdgkeZkgnmRo3HaX0k+b6T5Gyf9FYqF/gBYo7gQpa5jx44aN26cHnnkEdt2nTp10ueff64DBw6oS5cunvTppp2TiYDX+43mvmvXrq0JEybo1ltvVa1atfTcc89p6NChOnbsWEy2e/bZZ0O2i6UxRtpOkk4//XSNHTtW9957rzIyMiRJr732mmrUqFGq7QBEh5t4EYqb2Fka+/eij0hPxr3YfzTH79UYSvp+NzEKCMfub7F169aWx6vDhw9bvi/cNqvvX6z0+cMPP1h+x1JSUkp9W9E5dFnsz+m2li1bWs5Rq1WrVmG3nXvuuXrmmWf0+OOPq1GjRgFJsvKwDfCakzmQk/lyuH6c7CfcnNBpH7Gwn3DzQyfzRy/aOFkXKo39lFYfTtZnwrXxoo942w8QLV7FGKd9RSOPEav79HLNPRo5i3gav1U7r+JANPoCgGBe5ECKijQnE8zr8ZVGf14WU8b65wVgI9q3TkTFMGbMGDN//vyo9Bnr7aK17+PHj5vXXnvNHD161P/ajz/+aB566KG4ahcPY3TzWXJzc817770X8Nqbb75pDh8+XKrtAERPacTIst5/pH1U9PdHcwxuYhTgREn/Fu3eF8/b7L5jFXmb3Ry1Im8Lfs3q8V7lYRvgFa/m0uH6cbKfsuijLPYTbn7oZP7oRZt42o+TPpwc/8O18aKPeNsPEE1ertd4FQO8bheL+/RyzT0a6/yx2pebdl7FgWj0BQChRDsHE47X46M/AKXBZ4wx0S5wBAAAAAAAAAAAAAAAAAAAsSMh2gMAAAAAAAAAAAAAAAAAAACxheJCAAAAAAAAAAAAAAAAAAAQgOJCAAAAAAAAAAAAAAAAAAAQgOJCxI1Zs2apYcOGxf5r3LixWrRooW7duumJJ57Q/v37S2X/BQUFmjlzpn755ZdiY3rmmWdc97d27Vo1bNhQ9957r5fD9NSePXs0e/bsaA8DAEqM2FH2iB0AAAAAAAAAAHiDPEfZI88BAIEoLkTcadSokdLS0vz/3X777erbt69q1Kihl19+Wddff71+/fVXz/d7zz336KGHHtJvv/3mf61x48ZKS0vTpZde6rq/M888U2lpaercubOXw/TM5s2b1b17d61cuTLaQwGAiBE7ygaxA0C8Y7G27LFYCyDeETvKHrEDQDwjbpQ94gaA8oI8R9kgzwEAxVWK9gAAtxo3bqw77rgj5Lb77rtP7733niZMmKBHH33U0/2GOplv3LixGjduXKL+zjrrLMvPEQsOHTqkEydORHsYAOAJYkfZIHYAKC8aNWqkTp06+f9tjNGxY8e0fv16vfzyy1q4cKHeeustnXbaaZ7u95577tG8efO0cOFC/2uFi7WtWrVy3V/hYm3Dhg29HKZnNm/erL/+9a/q0qWLUlNToz0cAIgIsaNsEDsAlBfEjbJB3ABQnpDnKBvkOQCgOIoLUa4MGTJE7733nj7++ONoDwUAECeIHQCAYCzWlg0WawGUJ8SOskHsAFBeEDfKBnEDQEVBngMAUJp4LDLKlT/96U+SpAMHDvhf++abb3TvvffqqquuUtOmTdWiRQv16tVLU6dOVUFBgb/d3r171bBhQz366KOaOHGiLr74Yl100UW688471bBhQ61bt06S1LlzZ3Xo0EGS9eMCsrOz9eyzz6pbt25q3ry5rrzySg0fPlzbt2/3twn1uIARI0aoYcOG2rNnj5544gm1adNGLVq0UJ8+fbRgwYKQn3nhwoW65ZZbdNlll6lJkya6+OKLNWjQIC1ZsiSgXeFY58+fr3feeUe9evVS8+bNdckll+iee+7Rnj17AsYxaNAgSdKcOXPUsGFDzZo1S5KUk5OjcePGqUePHkpJSVGrVq00cOBAzZs3z+FvCQBiC7GD2AEAbgwZMkSSWKwFADhG7AAAuEHcAAC4RZ6DPAcAlCbuXIhyZdeuXZKk008/XZK0YsUKDRkyRFWrVlWnTp106qmn6ueff9bixYs1ZswY7d+/X/fdd19AHwsWLNBvv/2m1NRUHTx4UF27dtV5552n2bNn64cfftDAgQN11llnWY7h4MGD6tu3r3bu3KkmTZqob9++yszM1Pz587VixQrNmDFD559/vu3nGD58uHbt2qVrrrlGeXl5Wrhwof7xj3/o//7v/3Trrbf62z3//PNKT0/X2Wefre7du6tKlSratm2bli1bprVr1yojI0NXXXVVQN+TJ0/Wpk2b1LFjR7Vt21Zr167V3LlztX79es2bN0/Vq1f3P45h9uzZatCggTp37uy/cnHo0KFavXq1Lr/8crVr107Z2dlasGCBhg8friNHjqhPnz6OflcAECuIHcQOAHDDarF22rRpWr9+vfbv36+kpCQlJyfr2muv1eDBg5WQ8Pt1fXv37lXHjh3Vv39/1apVSy+//LLy8/N1xRVXaP78+f7+OnfurDPPPFNLlizRrFmzNHLkSA0ZMkTDhw/3t8nOztbkyZO1YMEC/fDDDzrllFN00UUXKS0tTfXr15f0+2LtoEGD1KNHDz399NOSfl8knT17thYvXqzp06dr7ty5OnbsmBo0aKCbb75ZXbp0KfaZFy5cqDfffFP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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"OUM2v2a2k2ter\",\"OUM2v2k2ter\"] \n",
    "labels = [\"Full OUM\",\"Self-excitation OUM\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "618d608c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"OUM2v2k2ter\",\"OUM2k2ter\"] \n",
    "labels = [\"OUM2v2k2ter\",\"OUM2k2ter\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "6ac8ad23",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"OUM2v2a2k2ter\",\"OUM2k2ter\"] \n",
    "labels = [\"Full OUM\",\"Self-excitation OUM\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "8835017c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"DDM2v2a2c2ter\",\"OUM2v2k2ter\"] \n",
    "labels = [\"Linear CBM\",\"Full OUM\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "1c7f6f4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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aPXu2mjdvrjfeeEMJCQnq3r27r90//vEP1a5dW1WrVtXcuXPVrFkzzZo1S61atdJDDz3kazds2DD973//07PPPqurr77a8jF/+OGHeuWVVxQREaGePXvqk08+0c9//nN98sknGjZsmK/dxx9/rKSkJNWsWVPbt29Xo0aNdOzYMQ0dOrTQa3HOnDmaP3++mjRpopiYGGVmZuq1115Tt27d1Lt3b1+777//3nJcv/zlL33//89//lMZGRm6ePGikpOTNXnyZF122WWaNm2a7rzzTss+EJzTWGLFaYyx4jT2WHEbk6w4iVVWnMYwK05jmxWnMc+K21hopSRipBtFiad2nMZaK1Yx2Iqb2GzFacwOpKhx3I5djLfiJPYH4nU+AOv4cPDgQct5325Ot5uv+/btKynwXGw3x9rNn3Zzo5N5r6hzmtO5yG6OyT9/BJsbrN73bt7T/u/VQO/Dor7H7HLrBx980DKfvv766319+OfQCxYssMyZv/rqK8s8OTk52TI3tsuHmzdvbpkD79mzxzLnbdOmjeXzkpycbJnbHjt2TNOmTVNERITvdVC5cmVt27ZNV111VYF+UlJStGfPHkk/vabeeustTZkyRZ999pnuvPNOzZ49W1u2bNGuXbvUtm1bLVu2TNu3b9cdd9yhJUuW6JNPPtEHH3ygDz/8UE8//XShHOSdd97RG2+8IUm64447lJGRoSuvvFIjRozQbbfdpg8++EC//vWvtXHjRv3617/W1KlT1bNnT1WsWDGsXy+wZ3d94eTawcn1gZtrAKs830kOHyxPd5KHO821vcql3eTETvJd/5zWac4aLC91m3ta5ZV2uaMX+aGTNaJg60NO1oWcrAcFWwtysgYUbP3HybqPk/WeYGs9TtZ45s+fbxkP//Wvf0mSJk2aVKDv/HFxyJAhGjFihGVszFu7e/LJJy1j5D/+8Q9J0pQpUyxjpWQfL0ePHm35XOD/c7I25WWNw8v6RijqGqGsabhdeymtOoaT9RCv6xfB1i+8XKcIRc3Cy1pFqOoUXsSsPF7FLil4/ELxFbfm4a+4NRB/xa2J+POqRuKvODWT/IpbPwmkuDUVf8WtsfjzqubiL9Q1mGC8rtHkV9x6jT+39Rt/XtRz/BWnvgOUhktyU158fLzGjh2r5557zrZdjRo1NHHiRA0YMEDVq1fXhAkTNGjQIJ09e7ZAu6ysLCUkJEiStm/frpo1a0pSoaTipptu0rhx4/Tiiy+qXr16lknH8ePHlZiYqJMnT+p///ufOnbsqEmTJql69eqF2laoUEHVq1dXhQoVdMstt0iSatWqVahdlSpVNHLkSH322WeaOHGijh49qhYtWqhmzZrq0aOHr90vfvELDR8+XNnZ2brsssuUlJSkatWqqUaNGgX6u+aaazRy5Ei1bNlSq1atUv369bV27Vpddtllhc7t9CLq008/Dfh8SCoUKEK1AczrzV9S6C6skpOTNXv2bFWtWtV3W0ZGhvr27Vvg79KhQwelpaXp8ssvL/AcRURE6KOPPvLdtmbNGs2dO1eSNGbMGD3zzDN68cUXZYwp8DiSkpL03nvvKS0tTT179tTatWsVFRWlXr16FfibvP/++zp16pTuuOMOST8ldocOHbJ8fqSfEui33npLVapUUXZ2tu6///4Cf5ddu3bp+eefV58+fTRz5kxddtllys3NVffu3Qv8XRo0aKDevXvr4Ycf1q233qpu3bqpfv36hc6XnJysd999V5mZmerWrZs+/vhjRUdHq1evXgXaTZ8+XbNnz1bFihV16tQpPffcc3r99df15z//WbNnzy7QduHChXrnnXcUHR3tu+3ChQvq1atXgU15jz/+uA4dOqRatWoVeI4jIiIKvAe+/fZb3zlmz56tRx55RP/5z38K/V3gntNYYsVpjLHiNPZYcRqTrLiJVVacxjArTmObFacxz4qbWGiluAuNbmJnIE7jqR2nsdaKm03YgTiNzVbcxOxAnMZxO05jvBU3m7/9Oc0H4JxVfDh8+LDlvH/ddddZzul287XdXHz06FHLOdZu/rSbGyMjI23nPbs5LX8u6W/z5s3lYkNRUTagnTp1SnPnzg34Hnv11Vct8+wrr7zSMre2y6erVq0aNIcOlDPn5uZa5sl2ubFdPvz1119b5sC5ubmWOe+iRYss89yLFy9a5rbz5s3T+++/r5MnT6pr165as2aNJKlPnz4yxmjnzp3q1auXjDGqWLFigYVOSVq1apVmzpzpey779OmjiIgIde3aVYmJiXrrrbcUERGhXr16qXv37rr55pv13HPP6aWXXlJ0dLTuvfdetWjRQlWqVFFKSoqWLFmic+fOqUuXLlq5cqUkKTExUQsXLtTbb7+tiIgInT9/Xo899pimTp3qG6fVnBwOrxfYs7u+mD17dtBrByfXB06uAYLl+U5y+GB5upM83Emu7SSXdpIvB8uJneS7wXJaLzaPScFzTyd5ZbDcMVh+6GSdyMkaUbD1ITfrQnbrQcHWgpzMW8HWf5ys+zhZ7wm21uNkjccuHuY5evRo0LgoBY6Nea/59PR0yxiZxy5WSrKNl3DGydqUlzUOL+sboahreF3TcLom48VG5Txe1jFC8QF2J+sXXtYtQlmz8KJWEao6hRcxK49XsUtyHr9QdMWtefgrbg3EX3FrIv6KWyPx50XNJL/i1k8CKW5NxV9xayz+vKi5+PP6Q+nFrcn486JGk19x6zX+ilu/8Vfceo6/4tZ3gNJwSW7Ka9eunbZu3aoTJ06oQ4cOlu1Gjx6t+fPn+5LDm266SdOnT9e///3vAu2uueYajR49Wk8++aSSk5MlSbNmzSpw0ZCnUqVKeuGFFzRv3jzl5uYGPO/777+vjIwMffPNN74+qlevrsGDBxdq27p1az366KOqV6+eBg0apJYtW2rt2rW+Hfh58h5DkyZN1KRJE508eVJbtmzRd999V6Ddq6++qtWrVys2NlYxMTF68803FRERUegTEKNHj9a8efO0cuVK1a1bV/fee6+++OILjRs3rtAYnV5EzZw5U1999ZWaN29eqA//IBbqDWBebf6SQndhlZOTowoVCk4BkZGRioyMLHDbO++8owEDBmjatGm64oorLJ8TY4xyc3MVGRmpJ554Qk8//bRee+21Qklsbm6uKlasqNjYWD3++OOKiopSbm5uoU+KvP7660pKStLZs2f12GOP2SYLp06d0sGDB3XllVcWeA1cuHCh0OM7cuSIatWqpaNHj6pmzZr68ccfC/UXERGh22+/XfPnz9eKFSuUlJSk3bt36/LLL9ecOXMKPIdRUVGKiIhQTk6OcnJyfMXC/M6cOaOcnBzfv48ePaqYmBidO3eu0LlzcnJ08uTJAt/mceLEiUKf2HjjjTeUmJioUaNG6dprrw34vOT1l5GRoapVq+q+++5TWlqaRowYYTn/wDmnscSK0xhjxU3sseIkJllxE6usOI1hVpzGNitOY54VN7HQSnE3RLmJnYE4jad2nMZaK0XZhB1IsNhsxU3MDsSLzQdOY7wVN5u//TnNB+CcVXyYOnWq5byfmZlpO6dbzdd2c/HUqVMt59ivvvpKUuD5025ujI6Otp337Oa066+/3nK+2rt3b7nYUFSUDWitWrWyfI/Z5dndu3e3zK3t8mm7HPqee+6xzJkrVqxomSfb5cZ2+fDZs2ctc+CoqCjLnNcuz+3Ro4dlbmuM0enTp1W9enW98MILkn769O358+f1/PPPa+HChdq4caOeeeYZLViwwLeQn5ycrI0bN+qKK65Qenq6rrrqKp0+fVrnz59XTEyMduzYoYYNG+rzzz9XXFycvvjiC0VGRioiIkK1a9fWtGnT9NVXX2nRokWaPHmyMjIyVK1aNR09elQnTpxQRkaG0tPTValSJZ0/f17Z2dlKS0vTVVddpWPHjunMmTOKjIzU+fPnFRUVFfT1Mn369EKbXIvzepk8ebKysrIsXy9XXXWVZ6+X/NdSKMzu+iIuLi7otYPT64Ng1wDB8nwnOXywPN1JHu4k13aSSzvJl4PlxE7yXac5bXE2j0nBc08neWWw3DFYfuhkncjJGlGw9SEn60JO1oOCrQU5mbeCrf84Wfdxst4TbK3HyRqPXTzMYxcX88ZvFRvzREVFWcbI/M+tVaxcvny5cnJyLOMlnHGyNuV1jcOr+kYo6hpe1zScrsl4sVE5/3PrVR0jFB9gd7J+4WXdIhQ1Cy9rFaGqU3gRs/L35UXskoLHLxRfcWse/opbA/HnRU3EX3FqJP68qJnkV9z6SSDFran4K26NxZ8XNRd/Xn8ovbg1GX9e1GjyK269xp9X9Rt/Ra3n+CtufQcoFV78Bu6lLjs727z33nsFbps7d645ffp0qZx/w4YNZsyYMWbEiBHmlVdeMR999FGhNgsXLiyVsQTSrVs3c/bs2QK3ZWZmmm7duhW4LScnx/Tu3dvs3r07aJ9/+tOfTE5Oju/fw4cPNxMmTDCJiYmFzn3hwgVjjDHz5s3znefee+8t1GdSUpJ55ZVXTHZ2tunTp0/A8959993mwIED5q9//avJyMgwxhhz4cKFQo+lV69e5ocffjDPPvusOXDggDHGmO+//75QO2OMb8w5OTlm6dKlZvDgwaZDhw6mR48eBdolJCSYrKws8+OPP5rf/va35uzZsyY7O7vQY7nnnntMVlaWMcaYkydPmvvuu893//yWL19uOnfubIYMGWKGDRtmhgwZYn7/+9+bFStWFBrjhg0bzMaNGwM+J3n++9//ms6dO5v09HRjzE/vi6FDh5oGDRoUaLdw4ULTqVMnk5ub67utf//+ZsaMGQH7Xb9+vXn44YcDPnd5kpKSzJAhQ8zvfvc7k5SUZM6cOWN+97vf+f7mebZv324SEhLMgAEDTFxcnElISDDt2rUz69evL9DO6u9//PjxAv9OSUkxd911lxkwYIB58cUXTZcuXUz37t3NrFmzCrSbP3++ad++vRk6dKjp1KmTWbFihZk8ebJ57bXXCp1jy5YtJiEhwSQkJJg+ffr4/n/r1q2F2u7YscN8/vnnls+LMcZ8/PHHpn379iYtLc1325gxYwr9XVD+hDr2eMVJDLMSytjmFacx0oqb2BmI03hqx02steIkBltxGputuInZgTiN43acxngrTmN/IG7yAZSckprTrebYkpo/7eY0u/nKbi4KNsdYzR92c4Pd+97uPW33XrV6H8bHx9u+x6zybLvc2kk+HSiHtsuZ7fJku9zYLh+2y4GD5bxWea5dbrt27VrTpUuXAq+lPn36mMWLF/v+vWvXLvPnP//ZdO3a1XfbwoULzUsvvWT69Oljpk2bZs6cOWPatGljVq5cafbt22fuv/9+k5CQYOrVq2eaNWtmEhISzI4dO8z9998f8Hkxxpg1a9aYhIQEM2zYMDN9+nRzxx13mI4dO5rly5ebVatWmfj4eNO9e3fTsWNH89lnn5mkpCTzzjvvmGXLlplOnTr5Xi+PPPKIq9dL3vVKoNdL/ufFyetl0qRJZvDgwaZdu3YmKSnJZGRk+F4v27ZtMwkJCebBBx8s8HpZt26d42speK80rw+C5fCllac7yaWd5MvBcmKn+a5dTuskZ3WSlwbLPZ3klcFyRyf5YbB1IidrRE7Xh+zWhZysBwVbC3IybwVb/3Gy7uN0vcdurcfJGo+TeJgnUFw0xj425rGLkXnsYqUx9vESpS8U60xlua7hVYwxxtnaSyjqGE7XQ7ysXzhZv/CybhGKmoWXtYpQ1Sm8iFl5vI5dxljHL4S/cKmJuFGc+kkg4VBTcau4NRh/xa3J+POiRpOfF/Uaf8Wp3/grbj3HX3HrO0BpYFMeSpx/YcHuIurw4cOOgphd0SE/JwWI/IJtAEtKSipQmLC6oLIrUvhzc2F15513Frqwevvttwu0s7qwmjBhQoF227dvN927dze33XabmTRpkklNTTXnz583jz76aKF2PXr0MH369ClwgRuoXdeuXU3v3r0LtHvggQcCtsvf3/Hjx23Pu2jRIvPWW28FPK9/2w0bNgTts2XLlmbSpElm9+7dAR/zp59+6vgx5z9vamqqOXToUMB2HTt2NI0aNfItLAY6rzHGnDhxwowaNcokJSWZzZs3mzZt2phOnTqZLVu2BGyXnJxsUlNTTYcOHUznzp0LtUtPT3fUDkBouImRVpzGzkCcxlM7bmOtFSebsANxGputuInZgXix+cBpjLfiNPYH4jQfAJwINqdZzVclsaHIbm4o6oYiu/eq1ftw+PDhlu8xuzzbLre2y6ftcmi7nNkuT7bLje3yYbsc2C7ntctz7XLbQPfL3+fo0aNNcnKy2bFjh2nfvn3APnfs2FHofqNGjTL/+c9/zObNm0379u19x6zG8tlnnxU6Fuh+SUlJvvPlz8+zs7PNzp07zZYtW0zfvn1NdnZ2wNfkn//85wL/PnPmjK+ImHcsr2h2/vz5AvfLK0rmd+TIEVOvXr2A58rNzS10v9zcXLNv375C4/Tv23+cgJec5tLB8uVgObGbfNcqp3WSszrJS4Plnk7yymC5Y7D80Mk6kZM1omDrQ07WhZysBwVbC3KyBhRs/cfJuo+T9Z5gaz1O1njs4mH+NlZx0f88/rHR/zyBYmQeu1gZ6HigPoBQ8SrGGONs7SUUdQyn6yFe1i+crF94WbcIRc3Cy1pFqOoUXsSsPF7Frrx2dvELAALxogbjrzg1GX9e1Gjy86pe46+o9Rt/xa3n+CtufQcoDWzKQ6nIzs42qampZsuWLWbnzp2+Hdr5DRs2zPK/QPIXHfIE+jax/AUIY4IXyY8cOWJmzpwZ7CEF7S83N9fs3bvXbNmyxezevTvgY3YyHiupqanm8OHDAY+lp6ebzz//3Jw8edIYYwIWcnr06GH27dtndu3aZRISEsyqVauMMYUvsnv06GH27t3rqF2g/vx38nt9Xrd9lsZjLmo7Y4wZMGCAWbBggZk8ebJp0aKFOXDggDl69Kjp3bt3kdulpKT42n333XcB2wEIHScx0orb2BmI03hqx22steI2Bltxe36nMduLczlhF+OtOIn9gbiJUYATVnNasPnKbi5yMsc4mT/y38/qfe/mPe3/Xg30PrR7j9nlnHa5tdd9OjnmdZ92uWywY1a5bXH69OKYm7Hkfwz5j916662mRYsWpm3btqZNmzamUaNGpm3btqZt27aFjjVs2NC0adPG8pjd/bzu0+k4gZIQLJd2mi8Hy4nd5LtOc9pAfQTLS93mnlZ5pV3uGCw/dLJm4mSNqCTP46aNF+dxMg4n6zjB2jhZ4/HqPMXtI1Ab//E6XdsCQsWrGGOMs7WXUNQxnKyHeF2/CLZ+4eUafihqFl7WDEJVp/AqDuS18yJ2uWkHAP6KU4Px50VNxp8XNZr8vKrX+POqfuOvuOMrTn0HKA0VQv3zuQh/w4cPtzyW/zfl4+PjNXbsWD333HPF6rNx48auzx2oXd5twdo57S9QO0l65ZVXPO3Tabvo6GjdeOONkqSpU6eqX79+ql69uiIiIgrcJzo6WjfddJOjdoH681fU8z7wwAMB27ntszQec1HbSVJWVpYSEhIkSdu3b1fNmjUlqVBbN+26du3qa3fDDTcEbAcgNNzEi0DcxE63588fT4vah5PH4DQGl+b53dzfaRwvyTEU5/5uYhQQjN1r0W6+srvfvHnzPBtDKBw8eNDyPWaXc9rl1nbvW7scOtj9vBxnsGN2uWywY1a5bXH69OKYm7Hkfwz5j82fP1+jR4/WkCFD1KBBAyUmJmrmzJmSpH379pX7Y4DXnORATvLlYDmxk/MEy2mL2od/m2C5pxfnCZYfOlkzcbJG5PY8gdaFnOSyJfl48vcRbBxO1nGCtXGyxuPVeYrbR6A2/uN1urYFhIJXMSZYX3lrL6GoYzg9p5f1CydtvFzDD0XNwsuaQajqFF7Fgbx2XsQuN+0AIL/irr37K25Nxp8XNRqn/RXl8Ra3fuOkvzxloT+gJLApDyUuPj5eY8aM0b/+9S/bdu3atdPWrVt14sQJdejQwZM+3bRzEkC9Pm8oz12jRg1NnDhRAwYMUPXq1TVhwgQNGjRIZ8+eLZPtxo8fH7BdWRpjcdtJ0jXXXKPRo0frySefVHJysiRp1qxZqlq1aom2AxAabuJFIG5iZ0mc34s+insR68X5Qzl+r8ZQ1Pu7iVFAMHavxWbNmlnOV6dPn7a8X7BjVu+/stLn4cOHLd9jcXFxJX4sfw5dGudzeqxJkyaWOWqVKlUu2WM33XSTxo0bpxdffFH16tUrUFwKh2OA15zkQE7y5WD9ODlPsJzQaR9l4TzB8kMn+aMXbZysC5XEeUqqDyfrM8HaeNFHeTsPECpexRinfYWijlFWz+nlmnsoahblafxW7byKA6HoCwD8eVEDya+4NRl/Xo+vJPrzchNiWX+8QIkI9Vf14dIwatQos3Tp0pD0Wdbbherc58+fN7NmzTKZmZm+277//nvz7LPPlqt25WGMbh5Ldna2ee+99wrcNnfuXHP69OkSbQcgdEoiRpb2+Yvbx6V+/1COwU2MApwo6mvR7n7l+Zjde+xSPmaXo17Kx/xvs/oZpnA4BnjFq1w6WD9OzlMafZTGeYLlh07yRy/alKfzOOnDyfwfrI0XfZS38wCh5OV6jVcxwOt2ZfGcXq65h2Kdv6z25aadV3EgFH0BQCChrsEE4/X46A8oWyKMMSbUGwMBAAAAAAAAAAAAAAAAAAgHkaEeAAAAAAAAAAAAAAAAAAAA4YJNeQAAAAAAAAAAAAAAAAAAeIRNeQAAAAAAAAAAAAAAAAAAeIRNeSg3FixYoLp16xb6r379+mrcuLE6deqkl156SWlpaSVy/tzcXM2bN08//vhjoTGNGzfOdX+bNm1S3bp19eSTT3o5TE8dPHhQKSkpoR4GABQZsaP0ETsAAAAAAAAAAPAGdY7SR50DgFfYlIdyp169ehoyZIjvv4cfflg9e/ZU1apV9eabb+ree+/VsWPHPD/vE088oWeffVbnzp3z3Va/fn0NGTJEv/3tb133d91112nIkCFq3769l8P0TGpqqjp37qx169aFeigAUGzEjtJB7ABQ3rHIWfpY5ARQ3hE7Sh+xA0B5RtwofcQNAOGCOkfpoM4BwEsVQj0AwK369evrkUceCXjsqaee0nvvvaeJEyfq+eef9/S8gS6C69evr/r16xepv+uvv97ycZQFp06d0oULF0I9DADwBLGjdBA7AISLevXqqV27dr5/G2N09uxZbdmyRW+++aaWL1+u//73v7rqqqs8Pe8TTzyhJUuWaPny5b7b8hY5mzZt6rq/vEXOunXrejlMz6SmpupPf/qTOnTooISEhFAPBwCKhdhROogdAMIFcaN0EDcAhBPqHKWDOgcAL7EpD2Fl4MCBeu+99/Txxx+HeigAgHKC2AEA8MciZ+lgkRNAOCF2lA5iB4BwQdwoHcQNAJcK6hwAUDbx87UIK7/85S8lSSdOnPDd9vXXX+vJJ5/UXXfdpVtuuUWNGzdW165dNX36dOXm5vraHTp0SHXr1tXzzz+vSZMm6bbbbtOtt96qRx99VHXr1tXmzZslSe3bt1fbtm0lWX+te0ZGhsaPH69OnTqpUaNGuvPOOzV06FDt2bPH1ybQ17oPGzZMdevW1cGDB/XSSy+pRYsWaty4sXr06KFly5YFfMzLly/Xgw8+qNtvv10NGjTQbbfdpr59+2rlypUF2uWNdenSpXr33XfVtWtXNWrUSM2bN9cTTzyhgwcPFhhH3759JUmLFi1S3bp1tWDBAklSVlaWxowZoy5duiguLk5NmzZVYmKilixZ4vCvBABlC7GD2AEAbgwcOFCSWOQEADhG7AAAuEHcAAC4RZ2DOgeAsolvykNY2b9/vyTpmmuukSStXbtWAwcOVOXKldWuXTtdeeWVOnLkiD788EONGjVKaWlpeuqppwr0sWzZMp07d04JCQk6efKkOnbsqJtvvlkpKSk6fPiwEhMTdf3111uO4eTJk+rZs6f27dunBg0aqGfPnjp+/LiWLl2qtWvXavbs2frVr35l+ziGDh2q/fv36w9/+IMuXryo5cuX669//av+9re/acCAAb52r732mpKSknTDDTeoc+fOqlSpknbv3q3Vq1dr06ZNSk5O1l133VWg76lTp2rHjh2Kj49Xy5YttWnTJi1evFhbtmzRkiVLFBMT4/va/JSUFNWpU0ft27f3fVJu0KBB2rBhg1q1aqU77rhDGRkZWrZsmYYOHaozZ86oR48ejv5WAFBWEDuIHQDghtUi54wZM7RlyxalpaUpOjpasbGxuvvuu9WvXz9FRv70ebhDhw4pPj5evXv3VvXq1fXmm28qJydHrVu31tKlS339tW/fXtddd51WrlypBQsWaPjw4Ro4cKCGDh3qa5ORkaGpU6dq2bJlOnz4sK644grdeuutGjJkiGrXri3pp0XOvn37qkuXLnr11Vcl/bS4mJKSog8//FAzZ87U4sWLdfbsWdWpU0f9+/dXhw4dCj3m5cuXa+7cufrmm290+vRpValSRfXr11e/fv18i7GSfGOdMGGCMjMzNXPmTO3du1eVK1dWq1at9Nhjj6lmzZoFxiH9tMi5aNEivfzyy/rjH/+orKws/fvf/9aqVat08OBBVahQQfXr11evXr3UuXNnT/6OAFCaiB3EDgBwg7hB3AAAt6hzUOcAUDaxKQ9h4+LFixo/frwkqWPHjpKkUaNGSZLmzp2rWrVq+dru3r1bf/jDH5SSklIo4UhLS9PUqVPVunVr323t2rXT5s2bfQlHbGys5TjGjh2rffv2qX///nrqqacUEREhSerUqZMGDx6scePGafLkybaP5cCBA1qwYIFuuOEGSdJDDz2k7t27a/z48erQoYNq1qyptLQ0JScnq3bt2nr33XdVuXJl3/3feecdPffcc0pJSSmUcKSmpmrWrFmKi4uTJOXm5ur+++/X5s2b9dFHH+nuu+9Wu3btVK1aNaWkpKhu3bq+r5//9ttvtWHDBt1999165ZVXfH0OGDBAnTp10vTp00k4AJQrxA5iBwC4xSIni5wA4Baxg9gBAG4QN4gbAOAGdQ7qHADKLjblodzZsWOHJk6c6Pu3MUYnTpzQ+vXrtX//fv3qV7/SwIEDZYzRo48+qosXLxZINiTp5ptv1pVXXqljx44V6v9nP/uZWrVqVaSxXbhwQe+//76uuOIKPf74475kQ/opaRkyZIiuvvrqoP3079/fl2xIUs2aNdW/f3+9+uqrWrx4sR5++GFVqFBBo0eP1rXXXlsg2ZCk5s2bS5LS09ML9d2yZUtfsiFJkZGRio+P1+bNm3Xo0CHbceV9lfHevXuVnp6u6tWr+8b3wQcf6Kqrrgr62AAgFIgdxA4A8AKLnCxyAoBbxA5iBwC4QdwgbgCAFeoc1DkAlD9sykO5k5qaqtTUVN+/IyMjFRMTo9jYWD3yyCPq16+fqlatKkm+T0IdO3ZMu3bt0sGDB7V//359+eWXOn78uCQpJydHUVFRvv6uv/76AomCGwcPHlRGRobuuOMORUdHFzqed9EXzO23317otrwk4ZtvvpEkXX755fr9738v6adPzu3Zs0eHDh3Snj179Nlnn0n66bH580++JKlatWqSfkqY7NStW1dNmzbVli1bdMcdd6hJkyZq2bKlWrdu7fuEGQCURcQOYgcAuMEiJ4ucAOAWsYPYAQBuEDeIGwDgFnUO6hwAyh825aHcSUhI0MiRIx213bNnj0aNGqU1a9bIGCNJuu6669S0aVN9++23OnXqlO/2PJUqVSry2E6ePCnp/wfwosr7Wvr88i4ET58+7btt1apVGjt2rHbu3ClJioqKUu3atdWgQQPt3r270GOTpIoVKxa6LS/BCtTe39SpUzVjxgwtXrxYGzdu1MaNGzVmzBjdeOONevrpp3XnnXc6e5AAUIqIHcQOAHCDRU4WOQHALWIHsQMA3CBuEDcAwC3qHNQ5AJQ/bMpD2MrKylK/fv10/PhxPfTQQ4qPj1etWrV8F7ItW7b0/JwxMTGSpDNnzliOqUqVKkH7OXfuXKHb8hKNvE9tffnllxo0aJCqVaumF154QY0bN1ZsbKwqVqyoPXv26L333ivqw7BVuXJlDRo0SIMGDdKRI0e0ceNGffjhh1qxYoUGDx6spUuX6vrrry+RcwNASSN2EDsAQGKRk0VOAHCP2EHsAAA3iBvEDQAoKdQ5qHMAKDvYlIewtX79eh09elQ9evTQ0KFDCxxLT0/3feW5kws0p2rVqqWKFSvq66+/LvTJNEnq06ePDhw4oNWrV9v28/nnnys2NrbAbVu3bpUk/eY3v5EkLVq0SDk5OXr22Wf1hz/8oUDb3bt3SyreYwv0Kbrt27dr6dKl6tixo+Li4nTNNdeoa9eu6tq1q4YPH64FCxZo27ZtJBwAyi1iB7EDANxgkZNFTgBwi9hB7AAAN4gbxA0AcIs6B3UOAGVHZKgHAJSUvE+Cff/99wVuP3/+vJ599lnl5uZKki5evOiov7yvac/OzrZsU7FiRXXu3FnHjx9XUlJSgWOrVq3SN998o7i4ON9FrZXJkycrLS3N9+/vvvtOU6dOVUxMjO+r3K0e3w8//KCxY8e6emyBVKjw057d/I83IyNDM2bM0MSJE33Pn/RTYnP48GFJUs2aNYt8TgAINWIHsQMA3Mhb5Lz33ns1dOhQNWrUyFccK61FTn99+vRR06ZNlZmZadvP559/Xug2u0XO7t2761e/+pXvGylKcpFz5MiR2r59uyT5FjknTZqkP/7xj8rOzta2bduKfE4ACDViB7EDANwgbhA3AMAt6hzUOQCUHXxTHsJWkyZNdOONN+qTTz5R79691bhxY50+fVqrV6/WsWPHdMUVV+jEiRM6efKkKleuHLS/a6+9VpL0/PPPq1mzZhoyZEjAdn//+9+1bds2JSUlaf369WrcuLF++OEHLV++XD//+c/13HPPBT1XWlqa7rnnHsXHxys7O1vLly/X2bNn9fLLL/u+3v33v/+9ZsyYofHjx+vrr7/WDTfcoO+//14rV65UhQoVFB0d7fua+aLIe7xr1qzRqFGjFB8frxYtWuiuu+7SqlWr1KVLF7Vo0UJRUVHauHGjduzYoQ4dOiguLq7I5wSAUCN2EDsAwA03i5x5C5h23CxyLly4UElJSfrrX//qO5a3yNmqVStHi5wtWrTQlVdeKansLXJ+++23ev311xUZ+dNnCVnkBBAuiB3EDgBwg7hB3AAAt6hzUOcAUHawKQ9hq3Llypo+fbrGjh2rTz/9VF9++aV+8YtfqGHDhnrwwQe1YcMGTZgwQR9//LHuu+++oP0NHDhQe/bs0bZt27Rz507169cvYLvq1atr3rx5Sk5O1vLlyzVz5kxVrVpVnTp10qOPPuroa2tfeOEFrVu3TsuWLVNOTo7i4uI0cOBA3Xbbbb42devW1YwZM/Taa69p48aNWrNmja699lrdfffdevjhhzVs2DBt2LBBe/bsUe3atR0/b3muvfZaPfHEE3rjjTf09ttvq3LlymratKnGjx+vt99+W4sWLVJKSoouXryom266ScOHD1fv3r1dnwcAyhJiB7EDANxgkZNFTgBwi9hB7AAAN4gbxA0AcIs6B3UOAGWIAVBm/P3vfzd16tQx69atC/VQAADlBLEDALzz7rvvmjp16pi///3vju9z6NAh8/jjj5vWrVubhg0bmvj4eDN48GCzdetWk5SUZOrUqWNmzZpljDHm4MGDpk6dOqZnz54B+zpw4IDp0aOHueWWW0yzZs3MmTNnfGMaO3ZsgbYnTpwwI0eONG3btjUNGjQwzZs3N48//rj57rvvfG02btxo6tSpY5544gnfbXlxY8mSJWbEiBGmWbNmpkmTJqZ///5m8+bNhcb06aefmsTERNOsWTMTFxdnOnXqZP7xj3+YH374wdx///2mTp06Zvfu3QWeP/+x2h1LTk42t99+u7nlllvMhAkTjDHGZGVlmSlTppguXbqYJk2amN/85jema9euZsaMGebChQtO/iwAUGqIHcQOAHCDuEHcAAAURp0DQLiKMMaYUG8MBPCTYcOGKSUlRTNmzFCLFi1CPRwAQDlA7AAAuEHcAAC4RewAALhB3AAAuEXsABCuIkM9AAAAAAAAAAAAAAAAAAAAwgWb8gAAAAAAAAAAAAAAAAAA8Aib8oAyZOTIkdq5cydfywsAcIzYAQAAAAAAAAAAyivqHADCVYQxxoR6EAAAAAAAAAAAAAAAAAAAhAO+KQ8AAAAAAAAAAAAAAAAAAI+wKQ8AAAAAAAAAAAAAAAAAAI+wKQ8AAAAAAAAAAAAAAAAAAI+wKQ8AAAAAAAAAAAAAAAAAAI+wKQ8AAAAAAAAAAAAAAAAAAI+wKQ8AAAAAAAAAAAAAAAAAAI+wKQ8AAAAAAAAAAAAAAAAAAI+wKQ8AAAAAAAAAAAAAAAAAAI/8P3JrMDWoM2eeAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"DDM2v2a2c2ter\",\"OUM2v2a2k2ter\"] \n",
    "labels = [\"Linear CBM\",\"Full OUM\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2a2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "6b33488d",
   "metadata": {},
   "outputs": [],
   "source": [
    "pal = sns.color_palette()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "68bc4c12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'#1f77b4'"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pal.as_hex()[0]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "101f81e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_Weibull(t,a=2,a_prime=1.5,lam=1,k=3):\n",
    "    first = 1-np.exp(-(t/lam)**k)\n",
    "    second = a - a_prime\n",
    "    return (a - first*second)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "6f6a7434",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_boundary(ax,dataset):\n",
    "    \n",
    "    if ax is None:\n",
    "        ax = plt.gca()\n",
    "    T_dur = 1.5\n",
    "    \n",
    "    t = np.arange(0,5,0.01)\n",
    "    param = pd.read_csv(\"Parameter Estimates/DDM2v2a2Weibull2terresult\"+dataset+\".csv\")             \n",
    "    param_mean = param.mean(axis=0)\n",
    "    a_speed = get_Weibull(t,a=param_mean[\"Boundary Separation Speed\"],\n",
    "                           a_prime=param_mean[\"aprimeSpeed\"],\n",
    "                           lam=param_mean[\"lamSpeed\"],k=3)\n",
    "    a_acc = get_Weibull(t,a=param_mean[\"Boundary Separation Accuracy\"],\n",
    "                           a_prime=param_mean[\"aprimeAcc\"],\n",
    "                           lam=param_mean[\"lamAcc\"],k=3)\n",
    "    #['#1f77b4', '#ff7f0e'\n",
    "    ax.plot(t, a_speed, color=\"#1f77b4\")\n",
    "    ax.plot(t, a_acc, color=\"#ff7f0e\")\n",
    "    ax.plot(t, -a_speed, color=\"#1f77b4\")\n",
    "    ax.plot(t, -a_acc, color=\"#ff7f0e\")\n",
    "    ax.tick_params(left = False, bottom = False, labelleft = False, labelbottom = False)\n",
    "    ax.axis('off')\n",
    "\n",
    "    t_max = next(a[0] for a in enumerate(a_acc) if a[1]-param_mean[\"aprimeAcc\"] < 0.001)\n",
    "    ax.set_xlim(0,t[t_max])\n",
    "\n",
    "    #ax.legend([\"Boundary (Speed)\", \"Boundary (Accuracy)\"])\n",
    "    \n",
    "    #return ax\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "cc192588",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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YL4K0xeb+/vuyvtEpRyZAqZSviEj14fGY5ZTSFkHqPNgxy5RsP5xvsLl/Nx9itvCqmTkjIiLHye0yAyqpc2DHHNg++8hncIefqfzUeiS0GgnB0d6LVUSklnO5PSxNPcCEZbv4cdVuisrMciQ+dhuDW8VyYbckBqTEYrdX96EsERGpVHm7KyYN75hrJhFbhy2PanOYStvNT4fmQ82S1aoQKFKr1dQl7dauXct5553Ht99+S+vWrY94bdiwYVx//fW89tprnHfeedxyyy0ApKamMnToUCZNmsS8efN49913mTJlCg6HA4Dvv/+e1atX89BDD3H77bfj6+vL888/f+j3PvfcczRu3Jjzzz+fvn37cvvttzNmzBgAFi5cyBVXXFFtKjzVyYSnK95fhN0GdpsNG2Cz2SrOD9v/vt2GDV+HjQBfBwG+DgJ9HQT42gn0cxDg4yDAz0GAjzkP8nMQHuhHeKAv4YG++PlUszXEywpNp9yWqbB5ilkD93AN2plOuVZnQ0xLfciLiNQUrlIzaL5thtl2Lzvyi5xPADQZCC3PhJThEBLjrUhFROTPHNhhBs93zDb38oJ9R74e2xpanGkG0hu017O6iIi3OUtMH8vmybB5krmPH2RzQKO+0OZc08ei5CcRkSpTUOpi4qrd/G9xGst35hxqbxYbwj8HNuXs9vH4OKpZP72IiJwaxTlmotn2mbB1evmy1YeJSDYFIVqOMAUi7A6vhCkiVedEkmiqmxtuuIGNGzdy11130alTJzIzM/n222+ZPXs2P/zwAyNHjqSgoIBnnnmGhIQEnnjiCfz9/Xn//fcpKChg6NChDBw4kGuuuYb09HTuuecerr76am666SZWrFjBpZdeyn333ceAAQOYPn06zz33HB9++CHdunXjjTfe4PPPP2f8+PGEhoby8MMPs379eiU8eVOjsRNP+TWD/BxEBvkRHepPbKg/MeX72NAAEiIDSYoMJD4ikABfL32AZm01iU8bJ5pMZ+uwLMboFGh3AbQfY5ZXEhGRmqM4xwy+bPvN3OdzUg970Wa+vLU403yRi2rqrShFROTPeDym/PrmyeY+nr74yETWyEZmAL3VOZDQxZR3FxER77EsyNoCGybC2m/NTPKDbA5oOhA6Xmqev7VcqYhIldm0L58vFqfx1ZI08kpcACRHBXHzgKac2ymx+k1QFhGRU+vAjvKiEFPNZLPDK7YGRUPrc6DtaGjYS30tIrVETU54Ki4u5q233uLXX39l9+7dBAUF0bdvX+666y7i4+MZNGgQQ4YMYc6cOezevZv+/fvz2GOPER4eDpgqUU8//TSrVq0iIiKC888/n1tvvRV7+f1t4sSJvPrqq6Snp9OwYUNuvfVWhg83S4d6PB5eeuklvvzySxwOB//85z95/PHHlfDkTd8sTccCPJaFZVlYFnisw84Bj8c61Eb5ez0WOF0eSlxuSpweip1uSsq34rIj2wrLXOQWOQ99mTpesaH+JNULokl0MM1iQ2heP4RmMaEkRgaeurK7hVmw6RdY/6PJcnaXVbyW1BPaX2BmJgbVOzXxiIhI5bAsyFhvBl82/HTk4AtAXEdzj287GkIbeCNCERH5K0XZpkNu/Q+mU+7wDrnwJGh3PrS/EGJbeS9GERGpkL0d1n0Ha7878vk7IALajYFOl5rncFXrExGpEvklTj6an8p7c7aTXWj6uRMiArmxfxPGdE3y3gRkERGpPsqKzHjohp9g4y9QklPxWmicGRPtcDHEtfdaiCJy8mpywtNfGTRoELfccgvnnXeet0OpFEp4qkbcHov8Eic5RU6yi8rYn196aMvIL2VfXgm7DhSTdqDo0PriRxPga6dlgzDaJYTTLiGctgnhNK8fgm9Vl+AtyTMf8Ku+gG0zgfL/XBx+ZiZ5l6ugUT91zImI1ES56eYL3IafzNJJB6v72ezQ+DRT3a/VWRAQ7t04RUTk6MoKTdWn9T/ApklQVlDxWoN2JvGp7fkQFue9GEVEpELWVljxGaz8HPJ2VbTXbwfdrjWTD/yCvRefiEgtVlTm4rOFO3l71jb255cCEB8ewAMjWjGiXRw29W+LiAiA2wnbZ8HaCbDuRyjNrXgtrgN0utxMXAiM8FqIIvL3KOGp5lDCUw1kWRYHipykHygiNauIrfsL2JJhtm2ZhZS5PH/4GT8fOx0TI+jWOJLujaPokhxJiL9P1QWZtxvWfAMrvzDLahxUryl0vsKUZA+Jqbrri4hI1SnMNEturPoS0hdVtDv8ocVw6Hw5NBmk8r0iItWVs9gkPa360ix/53Gadpsdmg+FzleavaMKvy+IiMjx8bjNshnLPzHVV91m4J2AcDOA0u06qNfYqyGKiNRWJU43Xy1J480ZW9mdWwJAj8b1GDeyDa3iwrwcnYiIVCuuUlP5aeX/zHP7wb4WnwBTFKLT5aYohPrMRWoEJTzVHEp4qmXcHosdWYWs2ZVbvuWxZncu+b9bLs9ugzbx4fRpFk3/lBi6NoqsugpQu5fD0g9h9VcVM8ntvmYZpJ43QnynqrmuiIhUveztsPprWP0lZG6qaI9oaBJcO12uJe9ERKqzouzyJNYvIG1hRXtIA7N0UqfLNZAuIlJdFB+A5Z/C4nfgwI7yRhukDINeN6uqtoh4x4rPzd5mA2yH3YcOO/59m93XrArgOLg/2vHv3uMT4LV7XInTzdszt/HmzC2UOD3YbXBpj2TuHJJCZLCfV2ISEZFqrDDL9LMs/xgy1lW0RzaCjpdBp8tUYVukmqvNCU+1jRKe6gBPeRLU4h3ZLNp+gEU7skjLLj7iPSH+PvRuGsWAFrEMbhVL/bAq+B+3tMCUdVzyAexeVtGe1BN63gQtz9IschGRmsqyYO8qMwCz6n9QUl6+1+YwVZ+6XA1NB4Ld4d04RUTkz2VuhmUfmkGrosyK9manQ48boelgzUQUEakOPG6zTOmi/8DWaRXtCV2h7x3Q4kzdr0Xk1Bl3ipa2t9nBL8Rs/uV7v2BT8S4wEoLqQWC9w/ZREFofQuPAN7BSQtiVU8zTP69n4qo9AEQE+XLXkBQu6ZGMw66EUxER+R3LMuOhyz42q+KU5pl2uy+0PQ963gzxHb0aoogcnRKeag4lPNVRe3KLWbgtm5mb9jNr036yCsuOeL1rciTD28UxvG0D4iMq5wvhEdKXwsI3zWxyT3n1qfAk6HWLWQrJL7jyrykiIqdGWRGs+x6W/hfSFlS0hzeE7v8wlZ+0brmISPXlKoONE2HZR7D1N6D8a2C9puY+3vESM7AkIiLel7kZFrwJKz4Fl1luiegW0Pd2aDfGVEYREalKn4w2A7pYf9xD+TFHvuZxgbsM3M7y/WHHHudhx66jX/NEBUSYxKewuPJ9gqliGtnY7EPqn1D1qPlbs3jsx7Vs2JsPQLdGkbwwpgPJUerTFhGRP1FWBOt/MEUhDu8zT+5jEp9aDNdkYZFqRAlPNYcSngSPx2LN7lxmbNzPbxszWL4z54jXOzWM4Oz28YzqlEC9yi7Rm7cHFr8LSz+AoizTFhRlZpB3/4eZnSMiIjVXxnqzrOnKzyqqPvkGm2WSetwIUU29G5+IiBxb1lZY/J4pw35wJqJfCHS8FHrfYpYwFRER7yvIMIlPi9+tuF+HJ8Fp95hEVSU+iUhN5PGYBChXKTiLzAoCZflQVlh+XAAlOVB0AIqzzXLNB/dFmZC/D1zFf3kZfALNMkP1mkBMC4htDfVbQ1Rz8Dl6f7jL7eHThTt57tcNFJa5CfJz8MCZrbi0R0NsWl5URESOZdcyWPDGkUUhIhtBj5tMv7l/qFfDExElPNUkSniSP9iTW8yva/by8+o9LEk9cGgSjq/DxqCWsYzpkkT/FjH4OiqxPLqzGFZ8BnNfhpxU0+YXAl2vht63QUhs5V1LROqkeVszcdhsOOw27HZbxXH53mEHu82Gr8NOWKAvof4+2FWOvPI4i2H11+aL3KF1y22QMgx63QyN+p3QbEoRETnFSgvMkqWL3oH9G0ybzQFtR0Of/4MGbb0bn4iIGCW5sOR9mP8GFGaYtshGMOB+U/FJs8ZFpC6xLHNfzN8L+XvMlrcbctMgezsc2GGOLc/Rf97uA1HNILYVNGgHCV0gvjMEhB16S1p2EXd/tZKF27MBOC0lhudGt6dBuAbGRETkL+TtNstUL/nAJPAC+IdBl6ug960aGxXxIiU81RxKeJJj2pdXwi+r9/DNsl2s3pV7qD06xJ/RXRK4rEcySfWCKu+Cbhes+w7mvAT71pg2n0BT7anP/0FwdOVdS0TqlEZjJ57Q+202CPX3ISzQl/DyLTLIj/iIABIiAomPCKRJTDDJUcGVmwBa21kWbJthEp82T65or9/OLLvRehQ4fLwUnIiI/CXLgm2/wdxXzP6gZkOg7x2Q3FsJrCIi1YGz2CQ+zXkJCvebtugUk/jUehTY9R1GRAQwy+fl7IQD2yFrm5mklbHebKW5R/kBm7mfJnSBhM6Q2BVPbDs+WJDGc79uoNTlISzAh8fPacs5HeNV7UlERP5aWSGs/NxUbM3aYtp8AqDrNaYoRFicd+MTqYOU8FRzKOFJjtuGvXl8vSSd71bsIrOgDAC7DQa3qs9VvRvRu2lU5X2BsywzED7zOdi1xLT5BkOP682He1C9yrmOiNQZQ/41E7dl4fFY5XtwHzo2e7fHoszlodT1JzP7jsLXYaNxdDAp9UPpmBRBp4aRtIkPI8BXM6f/UuZm8yVu5eemND1AZGMzYN7hIvDx9258IiJybLuXmwqt676vmBWf2A363A4tztRguohIdVBWaGaNz/l3xazxuA4w9Clo3M+bkYmIVG+WZSpvZKyDfWthzwrYtdQkR/2efxgk92F/THeeWhvF93vrYWFnRPs4xo9uT4i/JnaJiMhx8HjM2Ois5yvGRh3+0OVK09cSnuDV8ETqEiU81RxKeJIT5nR7mL4hg4/npzJnS+ah9uaxIVzVpxGjOydW3kC/ZcHmKfDbU+ZLJZil7nrfCr3+qXVsRaRKlLrc5BW7yC12klfiNPtiJ1kFZezOKWZXTjHpB4rZur+AojL3H37e12GjU8NI+qfEcFrzGNrEh2l5vGMpyobF75qqT8UHTFtovLnXd7kS/IK9G5+IiBxb1laY/xos/xTcpaYtphUMuA9anaPEJxGR6qAkz0w2mP8alOaZtpThMORxiEnxbmwiIjVJwX7YvcwkP+1aCmmL/1AJqtgnnFllKcxyt2NLRG+evGIYzeurH1tERI7TweraM8ZD2gLT5vCDTpeZycIRDb0bn0gdUBsSniZMmMD999/Pk08+yZgxY7wdTpVRwpOclC0Z+Xw0P5VvlqZTWD7oHx3iz3X9GnNpj4aEBvhWzoUsCzb+AjOehr2rTVtwDPS/DzpfCT5+lXMdEZET4PFY7MkrYfO+fNbuzmP5zhyW7zxAVmHZEe+LDvHnzHYNOLtDPF0aRir56c+UFsCyD2Heq5C/x7QF1oOeN0OPGyAgzLvxiYjIsRVkwMK3YNG7FYM+sW1gwFhoeZYSn0REqoPCTJjxrFnuznKDzQFdr4b+YyEkxtvRiYjUPB437F0F22fD9lmwcz6UFRzxlvVWIxwth5HSbwzEd9ZzsYiIHB/Lgh2zTeJT6hzTZveBjpfAafdCRJJ34xOpxWpDwtO1117Lzp07qV+/Pp988om3w6kySniSSpFX4uTrJem8N2c7u3KKAQgL8OGKXo24uk8jokIqaVkiy4J138G0xyF7m2mLbAyDH4bW5+rLooh4nWVZpGYVMXvzfmZuymT+1sxDCaEAceEBjO6cyMU9GpIQEejFSKsxV6lZ5m7OS3Bgh2kLjDQVn7rfAP4hXg1PRET+QnGOSXya/3pFFZEG7WDA/Wapu8paBltERP6+zM0w5VHYONGc+4eZ+3T368GhpZdERP42txN2r4DtM3BumIRj9xLsVAyrWMEx2FLOgDbnQuP+4KikCcMiIlK77ZgDM5+D7TPNucMfelwPfe+EoHrejU2kFqrpCU9ZWVn069ePp59+mrFjxzJlyhSSkmpnkqQSnqRSOd0evl+xm7dmbmVLhpnJEujr4Ko+jbjhtCZEBFVSJSa301QBmTEeCjNMW0JXGPYMJHWvnGuIiFSCMpeHuVsz+WnlHiav3Ut+qQsAuw0GtazPFb2S6dc8GpsGf//I7YK1E8ya5ZmbTFtQNPS9HbpeC35BXg1PRET+QvEBmP+GWUKpLN+0xXU0A+opZyjxSUSkOtgxByY9CHtWmPPY1nDm89Cor1fDEhGpLdz5+/n1u4+xNv1Kf/sqQm3FFS8GRUHrc6DtaGjYC+wO7wUqIiI1w84FMO2JiopP/uGmv7zHjeovF6lENT3h6dNPP+WVV15h/vz5DBgwgAsuuIBbbrkFgKKiIp599lkmTZoEwNChQ3nooYfw9/cnKyuLJ554glmzZhEYGMjo0aO544472LVrF4MHD2batGkkJiYC8Oqrr7Jo0SI+/vhjJkyYwJdffklUVBQLFizg0UcfZdCgQTz11FPMmDGD/Px8EhMTufvuuzn99NMB/vRaDz/8MJmZmbz11luH/p4nnniCvLw8nn/++T/8rUp4kirh8VhMXrePN2dsYWW6Wc4i1N+Hf5zWhGv6NibEv5JmC5YWmJnjc18GZ6Fpa3s+nD5OpRxFpNopcbqZtj6DTxemMm9r1qH2tglh3DKwOUNb19dyd0fjccPqr8zSGwe2m7aQ+mb2SperwLfmPWyKiNQpRdkw/zVY8FbFM3tiNzj9MWjUx7uxiYgIeDyw/COY+hgUZ5u2tufD0CchLM67sYmI1BKT1+7lvq+W0qpsDaP8l3Ku/xJ8Syr6hgiNg9ajoMOFZpKAJgeIiMifsSzYMhWmjoN9a0xbaBwMGAsdL1PFVpFKUNMTni655BKSkpIYP34848aNY86cOUyZMgWbzcadd97Jxo0befzxxwkICOCee+6hf//+3HfffVx00UU4HA4efPBBCgsLueOOO7jxxhsZMGDAXyY83X///dx4442MHDmSyMhInn/+ebZv386jjz5KYGAg7777LlOmTGH27Nn4+fn96bWaNm3K9ddfz/z58wkJCcHj8XDaaafx5JNPMmDAgD/8rUp4kiplWRbT1mfwwuSNbNhrZnXXC/bj5gFNubxXMv4+lTRrJX8vTH8Cln8KWOATYJY+6nsH+AVXzjVERCrRlowCPlmQyheL0yh2miXvUuqHcOeQFM5o00AVn47G7TJL3c18DnJ3mrawBFMppOMlmgkpIlLdFWbBvFdg0X/AWWTaUobB4EehfmvvxiYiIiZBdfqTsOR9wAK/EOh/L/S8WUsuiYhUgh2Zhdz4yVI27M0n0Mfi/f7F9CqaAet/hJLcijfWbwedr4D2YyAw0mvxiohINefxmInC05+s6C+Pag6DH4ZWI5U8K3IS/jSJxrIq+jVPBd+gE/5/ec+ePQwcOJBXX32VIUOGMG/ePK6++mo+/fRTmjdvTq9evfjggw/o0aMHAEuWLGH9+vV069aNc845h6lTpx5a/m7q1KkUFRXRuXPnv0x4euCBB1ixYsWhf14TJkygbdu2pKSkALBt2zaGDx/OjBkzyM3N/dNrnXXWWZx22mnce++9jBw5kkWLFnHrrbcyZ84cfH3/2DehhCc5JTwei59W7+GlKZvYnmlmdSfVC+T+4a0Y3rYSB/Z3r4BJD0DqXHMelmiWuWt1tj7YRaRayi4s4/052/lw3o5Dy911b1SPB0e0okNShHeDq65cZbDiE5j1AuTtMm0xrUx1Py2RJCJS/eXvg5njYel/wXIDNuhwMQx8QFVaRUSqg90r4Oe7IX2xOY9tAyNfgcSuXg1LRKQ2KCpzcdvnK5i6fh8A95zRgpv7JWHb+hus/hLW/wTuUvNmh7/p1+58BTTqB3a7FyMXEZFqy1VqJi3Meh6KyqsHJvU046MJnb0bm0gNddQkGsuC98+AtIWnLpCknnDNryc07vXuu+/y6quvsmDBAgIDA3G5XPTu3ZshQ4Zw4YUXMmbMGJYuXUpISMgRP/fLL78wbtw4Fi7849+Xnp7+lwlPL774InPnzj30Mx6Ph6lTp7Jo0SK2bdvG2rVrycnJYdq0aaxevfpPrwXw1FNPsWvXLt544w0ee+wxnE4nTz755FHfeyIJT3qalr/NbrcxskM8U+44jfGj2xEb6k9adjE3f7qMC99ewKr0nMq5UHxHuGoiXPAxRDSEvHT48nL4dAxkb6uca4iIVKJ6wX7cfUYL5owdxK2DmhHga2fRjmzOeX0ud36xgsyCUm+HWP34+EHXa+DWZWaZjYAI2L8ePr8Q/jsC0pd4O0IRETmW0Ppw1r/gn4vMsh1YsPIzeLULTH7IVBgRERHvie8I10yGc16HoCjIWAvvng4/3wul+d6OTkSkRgvy8+Hty7twTZ/GADw/aSNjv9uIs9lQOP99uGsDDH/OVHlyl8Kar+GjkfBqJ5j3GhTnePcPEBGR6sfHH3reBLetgNPuNRVh0hbAOwPhu5shb4+3IxSpRar/hPuJEydSUlJCly5daN26Ne3btyc3N5dff/0Vt9v9pz93tOpJBx2teI3L5Tri3N/f/4jze++9l/HjxxMWFsbFF1/M22+/fVzXAjjrrLOYM2cOBQUFTJkyhREjRhzz/cdLFZ6k0hSWunh71jb+M2srJU4PAOd1TmDs8JbEhlbSOphlRTD7RZj7MnicZkZMvzuhz+3gW/PW2hSRumFPbjHPT9rIhGWmclF4oC8PjmjFmC6JWubuzxQfgDkvwYK3KmZBthpplkiKbubd2ERE5K+lL4Wpj8KO2ebcP9w8t/e8yXTaiYiI9xRmmUraq/5nzsMSYcSL0GKYd+MSEakFPpy3g8d+XIvHgj7Nonjj0i6EB5YP/lgW7FkByz6C1V9DaZ5p9w2GjpdAjxsgurnXYhcRkWosbzdMfaziGd432PSz9Pon+AZ6NzaRGqKmLmm3fft2hg0bxkMPPXRoyTqALVu2cMcddzB+/HgeeOABPvroI7p2NVWcp06dyuuvv85zzz3HWWedxYwZM4iLiwPgo48+YsGCBYwbN45+/frxww8/0KJFCwDuuusuMjIyDlV4eu2115g+fToABQUFdO3alS+//JL27dsDMHPmTK6//nqmTp1KSUnJn17rjTfeAGDIkCGceeaZfP3118yaNQuHw3HUv1kVnsQrgv19uHNICtPvGsC5nRIAmLBsF4NfmMl/527H5fac/EX8gsw6tTfPhyYDzCD4jGfgjZ6weerJ/34RkSoQFx7Ivy7oyPf/7EOb+DByi53c+/UqLnlnIalZhd4Or3oKjIQhj8Nty6DjZWCzw/of4PXu8NOdUJDh7QhFRORYErvAlT/Cpd9A/bZQmmsSoF7rBmu/Mx0JIiLiHcFRcN7bcNkEiEg2lbQ/vxC+usosUSoiIn/blb0b8c4VXQnyczB3SxbnvzmPtOzyATSbDeI7wVkvwV0b4eyXIaYVOAth8TvwWlf4ZDRsngKeSuhLFxGR2iMs3jzDXzcdErubz47pT8Br3WHNBPWziJwMmw38gk/ddoKFECZOnEhERAQXXnghKSkph7YzzzyTZs2a8eOPPzJq1CieeuopVq1axerVq3nppZfo2bMnzZs3p2fPnjz44INs3LiRhQsX8p///Ic+ffoQHR1NXFwc7733HmlpaUyYMIEZM2b8aRx+fn4EBgYyefJk0tPTmT17No8//jgAZWVlx7zWQWeeeSYffPABw4YN+9NkpxOlCk9SZVak5fDo92tYmZ4LQJv4MJ4Y1ZbODSMr5wKWBWu/NbMS88tLN7YaadavDU+snGuIiFQyl9vDe3O289LUTZQ4PQT7ORg3sg3nq9rTse1bB9Meg02/mnPfYOh9K/S+BfxDvRubiIgcm8djZiBOe7ziub1hLzjjaUjo7N3YRETqurJCM5Fs/utgeczEg+HPQ7vzT7gTVkREKqzZlcu1Hy5mX14psaH+fHxtD1o0OEr/hWXB9lmw8C3Y+AtQPlwT0xL63gltR4PD55TGLiIi1ZxlmUqBUx+FPLOqBA17m/HR+I5eDU2kOjuRqkHVyfDhw+nTpw8PPfTQH1775JNPeOqpp5g6dSqvvfYakydPxtfXlzPPPJOxY8fi5+dHRkYGjz32GHPnziUkJIQLL7yQW265BZvNxty5c3niiSfYtWsXvXr1olu3bsyaNeuoFZ7AVI4aP348GRkZJCYmcvXVV/Pvf/+bsWPHctZZZx3zWgAbN25k5MiRfPbZZ3Tp0uVP/+YT+XelhCepUm6PxeeLdvLcrxvIKzFrPl7ULYmxw1sSEeRXORcpzYcZz8KCN8Fym0HwAfdBz5vBcey1IkVEvGVnVhF3f72SRduzARjRLo6nz21HeJDuW8e0Yw5MeQR2LTXnIfVh8CPQ4RKwq3CliEi1VlYIc18xy1O7ik1b+4vMfTw8wbuxiYjUdbtXwA+3wt5V5rzlWaYCSUisV8MSEanJ9uQWc9X7i9m4L5/wQF8+uLrbsScDZ2+DRe/C8o8rlruLaAi9b4NOl2nJIhEROVJZEcx7Beb8u7yfxQbdroVBD5mJDCJyhJqa8FSbzJ07l4cffphp06YdswiEEp6k2sksKOXZXzbw9dJ0AKJD/HninDYMbxdXeRfZuwYm3gVpC8x5bGsY+ZpZTkNEpBpyeyzemrmVl6ZswuWxiA8P4I3LutAxKcLboVVvlgXrvoep4+DAdtPWoD0MexYa9Tnmj4qISDWQu8uUXV/5uTn3CYQ+/wd9bjNlnUVExDvcTpj9L5j1HHhcEFgPRrwIbc/zdmQiIjVWTlEZV/93Mct35hDk5+Dty7vQr3nMsX+oJBcWvwvz34CiTNMWHAu9boau10JAWNUHLiIiNUduupkkvOYbcx4UDUMehw4Xa5KwyGGU8OQ9GRkZLF26lLfffpuhQ4dy8803H/P9SniSamvR9mzun7CKrfsLARjWpgGPn9OG2LBKuql4PGbgZMrDUJQFNjv0uAkGPajBExGptlam5fB//1vOjqwi/Bx2xo1sw8Xdk7TE3V9xlcKi/8DM5ypmPrYaab7M1Wvs3dhEROSv7VpmlqfeOd+ch8aZak/tL1KHnIiIN+1ZBd/dDPtWm/PW58CIf0FwtHfjEhGpoYrKXNzw8VJmb87E12HjlYs6Hd9E4LIiWP6Jqd6Rm2baAsKh963Q40bwP8oSeSIiUndtnwUT74bMjeY8qSeMeAEatPNuXCLVhBKevGfr1q2cf/75dOzYkTfeeIPAwGNXLlXCk1RrJU43r/+2hTdnbMXlsQgL8OGhEa0Z0zWx8gb3C7Ng0v2w6gtzHpEMZ78MTQdWzu8XEalk+SVO7v5qJZPW7gNgTJdEnhjVlgBfh5cjqwEKM+G3p2Dpf8HygMPPLGva7y7NehQRqe4OVu2b8gjkpJq2uI4w7BlI7u3V0ERE6jRXGcx+AWa9AJbbzBI/618m+UlERE5YqcvNHV+s4OfVe7Hb4Jnz2nFht4bH98NuJ6z+Cua8BJmbTFtgPeh7O3T7B/gFVVncIiJSw7jKYOFbMONZcBaawhDdr4eBD5ikWZE6TAlPNYcSnqRGWL8nj3u/XsXqXbkAnJYSw3Oj29MgvBJvMJunwE93VMyA6XgpDH0SgupV3jVERCqJZVm8NXMbz0/agMeCjkkRvHNFV2JC/b0dWs2wb62pFLJthjkPjoFBD0Ony8CuxDERkWrNWWI65Ga9AGX5pq3NuXD6YxCZ7N3YRETqst0rTLWnjLXmvP1FcOZzGiwREfkb3B6LByas5oslpq/6gTNbcv1pTY//F3jcsPZbmPEMZG0xbcGx0O9O6HI1+GrgTkREyuXugskPms8NMJ8XQ5+E9heAVpaQOkoJTzWHEp6kxnC5Pbw3ZzsvTtlEmctDWIAPj5/TlnM6xldetafSfJj2hFn2CMt8qJ/5HLQepQ91EamW5mzO5J+fLSO32EliZCAfXNWN5vVVpvy4WBZsmmS+zB3s/KvfDoY9DY1P825sIiLy1wr2w29PwrKPyqv2+ZslO/reAf4h3o5ORKRucpXCzPGmsojlgfCGcO5b0KiPtyMTEalxLMvi2V828PasbQDcfnpzbj895cR+idtlVjaYOb6iSmpoPAy4DzpeBg6fSo5aRERqrK3T4ed7KvrKG/Y2y9zVb+PduES8QAlPNYcSnqTG2ZKRz51frmRVuqn2NLxtA54c1ZaokEqsarJzIfxwa8XatS1GwIgXIew41ksXETnFtu0v4Jr/LmZHVhGh/j68cVln+jWP8XZYNYerDBa/CzOfhRLz2ULLs2DI4xB1ArMnRUTEO/auhl/vhx2zzXloHAx+FNpfCHa7d2MTEamrdi6ECf8oH1y3QZ//g4EPgo+ftyMTEalxXv9tC89PMv3Utw1qxh1DUk58ArDbCcs/gVnPQ94u0xbdAoY8BinDNNlXREQMVynMf918XjiLwOaAHjfCgLEQEObt6EROmYNJNI0aNSIwMNDb4cgxFBcXs2PHDiU8Sc3idHt4c8ZWXpm2GZfHIjrEj/Gj2zO4Vf3Ku4ir1CyTMedf4HGBfxgMfQI6X6kvgCJS7WQXlnHDx0tYvOMAPnYbL4zpwKhOCd4Oq2YpzDKl3pe8D5Yb7L7Q4wY47R4IjPB2dCIiciyWBRt+gskPwYEdpi2+Mwx7Fhr28GpoIiJ1Vmk+/DrWDLADNGgH570Dsa28G5eISA30n1lbefrnDQDcNKAp957R4u+teuAqhcXvwaznoPiAaUvuA0OegMQulRixiIjUaDlpMOkBWP+DOQ9pAGc8BW1Ha4xU6gS3282mTZuIjY0lKirK2+HIMWRlZZGRkUFKSgoOh+OY71XCk1Q7a3blcueXK9i0rwCAq3o3YuzwlgT4Hvs/5hOyb62p9rRrqTlv3B9GvgKRjSrvGiIilaDU5eaer1bxw8rdADx6dmuu7tPYy1HVQBnrzZe5rdPNeVCUmY3e+UqVehcRqe5cpbDgTTNxoSzftLU9H04fBxFJXg1NRKTOWv8j/HAbFGeb5UeHPA7dr1cVPhGRE/TenO088dM6AK4/rQn3D2/595KeAIpzYO6/zbOzq8S0tTkXBj8C9ZpUSrwiIlILbJ4Kv9wD2WZ5VZoMgDNfhOhmXg1L5FTYs2cPOTk5xMbGEhQU9Pefu6RKWJZFUVERGRkZREREEBf31yt1KeFJqqUSp5vnft3I+3O3A9AqLoxXL+5Is9jQyruIx22+/E1/ElzF4BtsBk26XacOOhGpVjwei8d/Wsd/5+0A4NZBzbjz75Q6r+ssCzZPgckPQuYm0xbTCoY9DU0HeTc2ERH5a/n7YPoT5VVFLPAJhD63mSWV/IK9HZ2ISN2Tvxe+/ydsmWrOmwyEUW9AWLx34xIRqWE+mr+DR75fC8DVfRrxyFmtT67PJzcdfnsaVnwGWKbadc8bTbXrgPDKCVpERGo2ZwnMe8VMLnOXgsPP9K/0uwt8tdSX1F6WZbF3715ycnK8HYocQ0REBA0aNDiuZ2IlPEm1Nn3DPu7+ahXZhWUE+NoZd3YbLuyWVLmD/FlbTbWn1LnmPLkPjHwVoppW3jVERE6SZVm8Nn0LL04xiTpX9krm0bPbYLcr6emEuZ1mibvfnoaSHNOWMgyGPgnRzb0amoiIHIc9K+HX+yue30PjYchjpuqTJi6IiJxalgWL3zXLj7pKIDASzn4ZWp/j7chERGqUTxem8uC3awC4olcyj41sc/J94HvXwJRHYOs0cx4cA4Mehk6Xgb0SV1MQEZGaK3sb/HwvbJliziOS4cznIeUM78YlUsXcbjdOp9PbYchR+Pr6/uUydodTwpNUexl5Jdz55UrmbMkEYES7OJ4+rx3hgb6VdxGPB5a8B1MeBWehmS0+6CHoeZO+/IlItfLJglQe/n4NlgUXd0/iqVHtlPT0dxVlw8znYPE74HGB3Qe6/QP63wtB9bwdnYiIHItlwbrvYcrDkLPTtCV0heHjIbGrd2MTEamL9m+CCf+APSvMeafLYNh48A/xalgiIjXJF4t3MnbCaiwLLuvZkCfOaVs5E383TYZJD0DWZnPeoJ25Rzfqc/K/W0REaj7LMktW/zoW8naZtpZnwbBnISLJu7GJiPwFJTxJjeDxWPxn9jZemLQRl8ciISKQly/qSNdGlTwgfSAVfrwNts0w54nd4ZzXISalcq8jInISvlmazj1fr8RjwejOiTx3fnscSnr6+zI3mxnpm3415wERMPAB6HoNOCoxuVZERCqfswQWvA6zXjQTFwDaXwiDH4XwBO/GJiJS17jKYMYzMOclwILIxjD6XSWiioicgK/L+3wsy1T3HlcZlZ7A3KMXvwMzxkNprmlrfY6pdh3R8OR/v4iI1HylBTBzPCx4w0wQ9g2C/vdBz5vBx8/b0YmIHJUSnqRGWZmWw23/W05qVhF2G/zf4BRuGdSscgf6LQuWfQiTHoKyfHD4w4Cx0Ps2cPhU3nVERE7C9yt2ceeXK3F7LM7pGM+/LuiopKeTtXU6THoQMtaZ8+gUGPoUNB8ClbmUqoiIVL78vTDtCVjxKWCZTrk+t0PvW8EvyNvRiYjULTvmwrc3QG4a2BxmkKTfXepTERE5Tl8tSePeb1ZhWXBt38Y8NKJV5SQ9ARRmwm9PwdL/guUxKx30vwd63arBbBERMfatg4l3wc555jymJYx4ERr19W5cIiJHoYQnqXEKSl088t0aJiw3ZRW7N6rHvy/qSHxEYOVeKDcdfry9Yt3a+E6m2lP9NpV7HRGRv+nn1Xu47fPluDwWY7okMn50ey1vd7LcLpP0+ttTUJRl2poOhjOegthW3o1NRET+2u7l8MtYSFtgzsMSYchj0Ha0kldFToF3Z2/DbrNht4HdbsNms+E4eG6zYSvfO+zm2GG3EeDjINCvfPN1EFR+HBbgS4CvlpivsYpzzCDJmq/NeVIPOO8/ENnIm1GJiNQY/1tklrcDuOG0Jowd3rLykp4A9q6Bn++pGMyOag4jXoAmAyrvGiLidee8Phe7jfJncht2++HP4zYc5c/ndrt5Zvd12Anx9zFbgM8fjkMDfIkJ8Sc2zF/P6rWdZcHKz2Hyw1CUadraXwRDn4CQWO/GJiJyGCU8SY317fJ0Hvp2DYVlbiKDfHnpwo4MaFHJH7IHP9B/HQsluWD3hdPugX53apkjEakWflm9h39+tgyPBVf0Suaxyip1XteV5MKsF2DBm+BxmpnpXa4yS90FR3s7OhERORbLgrUTYMqjproImIH2Yc9AQhfvxiZSyzUaO7FSf1+Ar53IID+zBftSL9ifuPAA4sMDiI8IJD4ikISIQCKCfPUMXF2t+tIkPpXmgV8onPk8dLhISagiIsfhkwWpPPTdGgD+ObApdw9tUbmfd5YFq76AyQ9B4X7T1na0qXYdFld51xERr6ns5/PDhQX4UD8sgMTIQJKjgmlYL4jkqCCax4aSGBmoibm1RVE2TH8ClnwAWBAQDoMfgS5Xg11JbyLifUp4khotNauQWz5bzupdudhscMvAZtx+ekrlL+uUtwcm3gkbfzbn9dvBqNchrkPlXkdE5G/4dnk6d365Esuqoll/dVnWVpjyCGz4yZz7h0P/e6H79Sr1LiJS3TmLYd5rMOdf4CwybR0uhsGPagBHpIr83/+W47HAY1lYloXbY+GxwLLM3pxbWOXvcXksSl0eistcFDvdFJeZrcjp5kR6q0IDfGgWG0Lz2JDyfShtE8KJCfWvuj9Wjt+BVLPE3c755rzNuXDWSxAY6d24RERqgA/n7eDRH9YC8H+Dm3PHkJTKv0hxDkx/Epa8Z5a58ws1E766X6/lSEVquGnr9x16JvdY5lnc7THP4wefzT2HPauXuTwUlrooKHNRUOKioPSwfamL3GIn+/NLKXV5jnndEH8fWjQIpVVcKO0SwumSXI+mMcHqs67J0pfCxDtgz0pzHt8JRvwLEjp7Ny4RqfOU8CQ1XonTzVMT1/PxglQAejWJ4uWLOxIbGlC5F7IsWPONKfVbnG2qffS9wwx8+6gTVUS867OFO3ngW1Pq/PbTm3P76VXQAVaXbZ8Nk+6HveafMfWawJAnoOUIzU4XEanu8nbD1Mdg1f/MuW8Q9LoFet8KAWHejU1EjsqyLArL3BwoLONAURnZhWXkFDnJLChlT24Ju3OK2ZVTzO6cYjILyv709yREBNI+MZwOSRF0SoqgY8MI/H00C9krPG6TgDrjWfC4ICwBzn0bGvfzdmQiItXee3O288RP6wC4a0gKtw5uXjUX2r3CTPrdtdSc128LI16Ehj2r5noiUiNZlkVeiYv9+SXsyS0hLbuY1OxCUjOL2JFVyLb9hZS5/5gQFRHkS5eGkXRvXI/+LWJoUT9UCVA1jccNi98zFZ9K8wAbdLsWBj0MgRHejk5E6iglPEmt8f2KXdw/YTVFZW5iQv159eJO9GwSVfkXKsgwSU/rvjPnMa3gnNchUctjiIh3vT9nO4+Xd4DdP7wlN/Rv6uWIahmPG1Z8BtMeh8IM05bUA04fB8m9vRqaiIgch/SlZqnq9EXmPCjaTF7ocrWq9onUYCVONzuyCtm8r4AtGWbbsDePbZmFf6gSFeBrp1ujevRsEkXvplG0T4yo/ArRcmy7lsI3/4DsrYAN+twGAx/SfVhE5C/8Z9ZWnv55AwD3DmvBzQOaVc2FPB5Y9iFMHQclOaat46Uw5HEIjq6aa4pIreJ0e9ieWcj6PXms25PHip05rEzPocR5ZBJU/TB/+qfEMLBFLANaxBLop4kJNUb+PrMc6uovzXlwDAx9EtpfqMnBInLKKeFJapUtGQXc/OlSNu0rwG6Du89owY2nNa2atYLXfQ8T7zLrm9vsZpb4wAfAN7DyryUicpxe/20Lz0/aCMDj57Thil6NvBtQbVSaD3NegvlvgKvYtKUMM0sk1W/t3dhEROTYLAvW/2CSV7O2mLbIRmY2YpvzwG73angiUnnyS5ys2ZXHqnQzwLJo+wEyC0qPeE9UsB+DW8UypHUD+jWPJsBXgyynRGmBqZ667CNzHtcBznsXYlSlVkTkWA7v83nwzFb847QmVXexwiyY+igs/9icB0TA4Eegy1Vg1+eliJyYMpeHdXvyWLIjm7lbMpm/LeuIBKggPweDW9VnRLs4BrSI0XN5TbF9lhknzdxkzpP7wogXILaVd+MSkTpFCU9S6xSVuXjouzVMWLYLgMEtY3nxgg5EBFXBbMGibPjlvoos5qjmptpTwx6Vfy0RkeP0wqSNvPabGcR9bnR7LuiW5OWIaqm8PTBzvBmosdyADTpcDAPvh4iG3o5ORESOxe009+8Zz1ZU7YvrCEMegyYDvBmZiFQRy7LYklHAvK1ZzNuaybytWeSXuA69HujroH9KDKM6xTOwZayWvjsV1v8IP9wGxdngEwhnPAldr9WscBGRY3hl2mb+NcUMLD9yVmuu6du4ai+4c6EZzN632pzHd4az/gXxnar2uiJSq5U43Szans2MjfuZvG4v6QeKD70W6u/DyI7xXNy9IW0Twr0YpRwXVxnMfxVmPm8mB9sc0P0fMGAsBEZ6OzoRqQOU8CS1kmVZfLE4jUd+WEuZy0NCRCCvX9qZjkkRVXPBDT/DT3dAwV7ABj1vgkEPgV9w1VxPROQYLMviyYnreW/Oduw2ePOyLpzRpoG3w6q9MjebdcvXfW/OHX7Q/XrodxcE1fNubCIicmylBbDgDZj7MpQVmLamg8zySlqyWqRWc7o9LN6ezeR1+5iybh+7cioGWcIDfRnRPo7zOiXQJTkSmxJwqk7eHvjuJtj2mzlPGQYjX4OQGO/GJSJSjf1r8kZemW4mup2S6t5uFyx+F6Y/CWX5ZrWD7jfAoAfBP7Rqry0itZ5lWaxMz2Xiqt1MXLWH3bklh15rmxDGRd0acl7nBIL8fLwYpfylA6nw6/2wcaI5D4oy46Sdr1RlQBGpUkp4klpt7e5cbv50GalZRfg6bDw0ojVX9Equms7K4hyY9CCs+MScRzaGka9C436Vfy0Rkb9gWRZjv1nNF0vS8POx8/E13enRJMrbYdVu6UtNufcds825fxj0uQ163qwEWBGR6q5gP8x6Hpa8B57yii8pw8yS1XEdvBubiFQ5y7JYuzuPH1ft5vvlu9mbVzHI0jQmmMt7JjO6SyKhAb5ejLIW83hg4VvmWdpdBsExMOpNaD7E25GJiFRLlmXx/KSNvDFjKwBPnduWS3skV/2F8/fCpAdgzTfmPDQeznwOWp6l6nwiUik8HosF27L4fHEak9bspcxtlr0LD/Tl8p7JXNE7mdjQAC9HKce0dTr8MhYyzRKsNGgHw8ZDoz7ejUtEai0lPEmtl1fi5L6vV/HLmr0AnN0hnmfOa0eIfxVlg2+eCj/+H+Slm/Nu18Hp4zTbRUROOZfbw42fLGPq+n2EBvjw1Y29aNkgzNth1W6WBVunwZRxFeXeQ+qbak+drwRffSEXEanWsrfDzOdg1f/AMh2rtDwLBtwPDdp6NzYROSXc5YMsE5bt4pc1eygqcwMQ5Ofg3E4JXNGrES0a6Pt9ldi7Bib8AzLWmfPu18OQx8E30LtxiYhUQ5Zl8cwvG/jPrG0AjB/djgu7NTw1F98y1Sxzd2CHOU8ZbhKfIk7R9UWkTsguLGPCsnQ+XpBKalYRAH4OO+d2SuDGAU1pHK0JptWW2wmL34MZT0NJrmlrcy4MeQIikrwbm4jUOkp4kjrBsizen7uDZ35ej8tj0TQmmDcv60JK/SrqpCzJgymPwNIPzHl4QxjxIqQMrZrriYj8iRKnm8vfW8jiHQeIDfXnm5t6k1QvyNth1X4ej5nxOP0JyEk1baFx0PdO6HyFEp9ERKq7zC0w81lY/TVQ/pW5zbnQfyzEtvRqaCJy6uSXOPl2+S4+mp/KloyCQ+0DW8Rw88BmdGuk5YsrnbMEpo6DhW+a85iWcN47ENfeq2GJiFRHlmXx+E/r+GDuDmw2eP78DpzfJfHUXNxZbCqkzn0FPE7wDTLVUXvcBA4tOyUilcftsZiybi9vz9rG8p05ADjsNs7rlMBtg5urr7s6K8yE356Cpf81k8p8AqHv7dD7Vq2IICKVRglPUqcsTc3mn58uZ29eCYG+Dp45rx2jOiVU3QW3zYAfboWcnea89TmmdGNYXNVdU0Tkd3KLnIx5ex6b9hXQJDqYr2/qTb1gP2+HVTe4ymD5xzD7RcjbZdpC46FfeeKTj7934xMRkWPL2GASn9Z+W95gg7ajzX28fhuvhiYip45lWczflsXH81OZtHYvnvKetK7Jkdw0oCmDWsZi01I+lWvLVPjuZijYBw4/GPQw9LoF7HZvRyYiUq1YlsWjP6zlo/mp2Gzw0gUdq7a/+/cyNsBPt8PO+ea8fjs4+9+Q2PXUxSAidcbS1Gxe/20r0zdkAOBjt3FBtyRuG9ScBuGaYFpt7VkFv46F1LnmPKS+SZLteJmSZEXkpCnhSeqcrIJS/u9/K5izJROAS3s05JGzW+Pv46iaC5YWmEGS+W+A5Qa/UBj8sFnqzl5F1xQR+Z29uSWMfnMeu3KK6ZAUwWfX9SC4qpb2lD9ylcKyj2D2vyB/t2kLSzAD5p0uV+KTiEh1t3eNeaZf/2NFW/MzoO8dkNzLe3GJyCm3I7OQt2dt45ul6ZS5zdKXrePCuPuMFAa2UOJTpSrMMpPINk405437w7lvQVi8d+MSEalmLMviwe/W8NnCndht8PJFnTi7wym8V3o8sOITs+JB8QHABl2vgcGPQGDEqYtDROqMZTsP8NKUTczebMb5An0d3NC/CTec1pRAP427VUuWBeu+M9VcDy6JGt0ChjwGKcNA36NE5G9SwpPUSW6PxcvTNvPq9M1YFrRPDOf1SzpXbenLvavhx9th1xJzHt8Jzvo3xHesumuKiBxmS0YB5781j5wiJ6elxPDelV3xdWiG9Cl1KPHpRcjfY9pCGkCvm6HL1RAQ5t34RETk2Pasgjn/gnXfm3LsAEk9TeJTyhnqoBOpQzLySnhvznY+WZBKYZkbgM4NI7j7jBb0bhrt5ehqEcuCZR/Cr/eDswgCIuDsl6HNKG9HJiJSrXg8FvdPWM0XS9Jw2G28enEnzmx3ilcZKMyEyQ/Bys/NeUh9GPYMtDlPz8kiUiUWbc/muV83sCT1AAANwgK4b3gLzumQgN2u+0615CqFJe/DzOegONu0JfeFIY9DYhfvxiYiNZISnqROm7Exg9u/WEFOkZPwQF9eurADg1rWr7oLejyw9AOY+hiU5oLNDt1vgEEPgn9o1V1XRKTc8p0HuOSdhRQ73ZzbKYEXx3TQlz9vcJaYxKe5/65Y6s4/HLpdCz1vgpBYr4YnIiJ/IWsrzHsFVnwG7jLTFtvaJD61OU8l2UXqkAOFZbw1cysfzt9BidMkQvZpFsX9w1vRNiHcy9HVIplbYMJ1sHu5Oe94GQx/Vn0pIiKH8Xgs7vl6Fd8sS8fHbuP1SztzRpsGpz6QbTNh4p2QtcWcNzsdznwB6jU+9bGISK1nWRY/r97LM7+sJ/1AMQCdGkbw1Kh2tI7X5NJqqzjH9I0veBNcJaatzXlmhZx6TbwZmYjUMEp4kjpvV04xN3+6jJVpOQD8c2BT7jg9BZ+qrHqSvw8mPQBrvjbnofGmo67VSM12EZEq99vGDK77cAluj8U/+jXmwRGtvR1S3eUqg9VfmS93mZtMm8MfOl0GvW9VZ6CISHWXvxcWvAGL34eyfNMWnmSWr+58BQTV8258InLKZOSV8NpvW/h80U6cbgubDcZ0SeTuM1oQGxrg7fBqB7cTZjxjlonGgsjGcO7b0LCHtyMTEak23B6Lu75cwXcrduPrsPHWZV0Y3KoKJ/j+GVcpzHnJVLh2l4FPAPS/F3rdCj5+pz4eEan1Spxu3p+7ndenb6GwzI3DbuOaPo24/fQUgv01Kanayk2H6U+VVwe0wO4LnS+HfndBeKK3oxORGkAJTyJAqcvN0xPX8+H8VAB6NYnilYs7ERPqX7UX3jINJt4FB7ab8+ZnwJnPQWSjqr2uiNR53yxN566vVgLwwJktuf60pl6OqI7zeGDjz6Yz8ODSpzY7tBwBPW6E5D5KiJVa7Z+fLcNus2G3gd1mw2YDh81m2uxgK3/Nx27H39dOoK+DQF8HQX4OAnwdhAX6Ui/Yj8ggXyKD/AgP9K3a5HWR3yvOgSXvmZmJhftNm08gdLjQVHStr+RikboiLbuIFyZv5PsVuwEI9nNw88BmXNu3MQG+Di9HV0vsmAvf3gC5aYANet4Mgx4CvyBvRyYiUi243B7u+HIlP67cjZ/DzttXdGFgCy9Vks7cAhPvgO2zzHlMKzjrJUju5Z14RKTW25tbwuM/reXn1XsBiA8P4PFz2nJ6ay8kf8rx27sapjwCW6ebc4cfdL4S+t0JYfHejU1EqjUlPIkc5oeVuxn7zSqKytzEhvrz2iWd6d64imdlO4vNTJc5/waP01T26HObWQ7DL7hqry0iddp/Zm3l6Z83APDimA6M7qIZE15nWZA61yQ+bZla0V6/LfS4AdqNAd9A78UnUkUajZ1Y6b8zOsSPhMggEiMCSYw0W1K9IFo2CKN+mD82JRFKVXCWwJpvYOGbprPuoManQddroMUIzWgXqSOWph7giZ/WsaK8mnRCRCAPjmjF8LYN9BlUGYpz4Nf7YeVn5rxeExj5GjTq49WwRESqC5fbw23/W87Pq/fi52Pn7cu6MLCll5KeLAtWfWFWPCjKMm2dr4DTH1NFVBGpMr9tyODh79ccWubu3E4JPHp2ayKC9J28WtsxB357BlLnmHOHP3S92oyZhnphmVYRqfaU8CTyO1sy8rnpk2VszijAYbdx37AW/KNfk6rvkNy/EX6+B7bPNOdhCTD0CbNmrTpDRaSKPDVxHe/M3o7DbuPdK7p6r/NL/ihjPSx8G1b+D1zmizmB9aDLVdDtWpX0lVrlv3O347HAY1lY5fuKcwu3xxy7PRYlTjfF5VuJ001RmZvcYicHCss4UOQkt9j5l9eLDPKlVVzYoa1LciSNooI0AC2Vx7IgdR4sfAs2/ASWx7QHx0DHS80AT5SqK4rUdh6PxQ8rd/PsLxvYm1cCQP+UGB4/pw3JUZrgVCk2T4EfboN8U1GL7tfD4EfBP8S7cYmIVANOt4dbPlvGpLX78HXYeOPSLgzxZoWTomyY+igs+8icB0XD0Cehw0Xq/xaRKlFc5ubfUzfxzuxteCyICfXnmXPbqdpTTbB9Fvz2NOycb859AqDrtdD3dgjRGIaIVFDCk8hRFJa6eODb1YdK0A9tXZ/nx3QgPNC3ai9sWbD+R5j8IOTsNG3JfWDYsxDXvmqvLSJ1ksdjcddXK/l2+S4CfO18el1PuiRHejssOVxRNiz/BBa9A7nlnw02BzQfagbMmw8Fh9ahFznI5faQU+xkX14J6QeKy7ci0g8Usz2zkG37C/Ac5RtQ/TB/ejSOomeTKHo2qUfj6GAlQEnlyNkJSz+E5R9Dwb6K9sb9odPlZvlSLcMkUqsVl7l5c8YW3pq5jTK3B38fO7cMbMb1/Zvg76Nl7k5aSS5MfqhiAD0iGUa+Ck36ezcuEZFqwOn2cPv/VjBx9R587DZeu6QTw9rGeTeo1Hnw0x2w31Qdp2FvGPGiloEWkSqzbOcB7vlqJVv3FwJwXqcExp3ThrCAKh7zk5NjWbBtBsx4BtIWmjafQOhypVnWOjLZq+GJSPVQ5QlPpaWlTJkyhX379tGwYUMGDhyIj48G5aT6syyLTxbu5Ikf11Hm9pAcFcSrF3eifWJE1V/cWQzzXoXZ/yqv6mGDjpfAoIe0Vq2IVDqn28M/PlrCjI37CQ/05asbe5FSP9TbYcnvedyw8RdTLWTH7Ir2kAbmM6LTZaoWInIcSpxuNu3LZ8OefNbtyWPt7lxWpuVS5vYc8b6EiEDOaNOAYW0b0CU5EoddyU9yktxO2DQJln4AW6YB5V/F/UKg9SjocCEk9wW73ZtRikgV2ra/gIe/X8PcLWY5nyYxwTx5Tlt6N4v2cmS1xNbpptpTbpo573IVnD4OAjWhQ0TqNpfbw11freT7Fbtx2G38+8KOnN3By33MrjKY/xrMeh6cRWZiV8+bYMBY8FeflIhUvhKnm5embuKdWabaU0JEIC9d2JHujbW0ZrVnWbB1mlnqbtcS02ZzQJtzoc9tENfBu/GJiFdVSsJTaWkpH374IRMnTuStt94iLs7MEEhNTeXqq69mz549h94bFxfHW2+9RUpKysleVuSUWJmWw82fLmNXTjG+Dhv3DWvJNX0aYz8Vg145aabM75pvzLlvEPS+zXyA+6n8vYhUnqIyF5e+u5DlO3NoEBbANzf3JiEi0NthyZ/ZvwmWfwQrPoeizIr2Rv0qqoVoGQ+R41bidLNs5wEWbstmwbYslqflUOaqSICKDvFjSOsGDG/bgD7NopX8JCfvQCqs+NQsW5qTWtEengRtR5tOu7gOWtpDpBayLLPM3RM/rSezoBSAMV0SeWhEa8KDNMP8pJXmw5RHYcl75jw4FoY9Y+6tuqeKSB3m9ljc8/VKJizbhd0G/7qgI6M6JXg7LNP//etYsww0QGgcnPEUtDlP920RqRJLUw9wxxcr2JldhN0GNw9oxv+d3hxfhyYfVXuWZSY5zHvFVH46qHF/M3babLA+O0TqoJNOePJ4PFx11VUsXrwYgA8//JDu3bsDcNlll7FkyZI//ExMTAy//PILISEaiJOaIbfIyX3frOLXtXsBGNgihhfGdCAqxP/UBJC+BCY9UFGyMaQBDLwfOl6mZYxEpNLkFJUx5q35bM4ooElMMF/f2Jt6wX7eDkuOxVUGm341y3dsnQZWeYKGbxCkDIN250Oz08HnFH1eidQSxWVuZm/ez69r9zJ13T7ySlyHXosPD2BM1yTGdE0kMVLLkMlJsizYuQBWfg5rv4PS3IrXIhuZyk9tRkFcR3XaidQyucVOXpi0kU8WpmJZEBvqz5Oj2jK0TQNvh1Y77JhjlkvK3GTOmw4yyyXVa+LduEREvMjtsbh/wiq+XJKOzQbPn9+B87skejssY/MU+PkeOLDdnDfuD8Ofg9iW3o1LRGqlglIX435Yy9dL0wHokBjOqxd3pmGU+nlqjD0rzUo5ayaA5TZtsW2g961msoOPxjVE6oqTTnj67rvvGDt2LAA9evTgkUceoWnTpmzatImRI0dis9kYNWoU999/P+vWrePuu+8mKyuL//u//+PGG2+slD9C5FQ4tMTdT+soc3mIDfXn3xd1pHfTU1R63rJg3fem4tOBHaatXlMY+ICZ8aKlL0SkEuzJLWb0G/PYnVtCh8RwPvtHT4L9lVhZI+Smw4rPzHawgxAgIBxanW2+6DU6TYmyIifI6fawYFsWv6zZy8RVe8gtdgIm9+S05jFc1C2JIa3r46OZgHKynMUmiXXtt7BpcvnS1uUikqHFcJPMmtxHHXcitciSHdnc+80qtu0vBOCs9nE8NrLNqZtgVZu5SmHuyzDrBXCXgk8AnHaPmf2t+6iI1FEej8VD36/hs4U7sdngyVFtubRHsrfDMpwlpmrH7BfBVWKWK+p+vVnmLjDC29GJSC00cdUeHvh2NbnFTkIDfHhhTAfO0ASEmiVnJyx4E5Z+CE7znYqQBtD5cuh8BUQ09G58IlLlTjrh6YYbbmDWrFmMHDmS8ePHH2p//fXXefXVV/Hx8WHOnDlEREQA8M033/Dggw/Svn17vvzyy5MKXsQb1u/J49bPl7MlowCbDW4Z2Iz/G9z81A1yuUphyfumw+7gMkYN2sGgR6D5EM38FpGTtiWjgDFvzeNAkZN+zaN578pu+PloIL/GsCzYvdwsh7pmAuTvrngtOMYMlrc4E5oMAD/NWhI5ESVON5PW7uV/i9KYvy3rUHtCRCDX9WvMhd2SCPJTUqFUgrJC2DQJ1n33x+Qnv1BoNghShkPTgRCqzliRmq7E6eblaZv5z6xtuD0WkUG+jBvZhpEd4rHpO/7Jy9pqqj1tn2nOY1rCmc9D49O8G5eIiJdYlsVjP67jv/N2AHDPGS24eUDT6vOZk70dJj9UscxdUBQMfgQ6XQ52h3djE5FaZ3dOMbd8toxlO3MAuLZvY+4b1lL94TVN8QFY8gEsfAsK9pU32qD5UOh6tdnrM0SkVjrphKe+ffuSlZXFt99+S8uWFeVFL7roIlasWEG3bt34+OOPD7WnpaUxZMgQwsPDWbhw4clcWsRrispcPPbDOr5YkgZA1+RIXr64EwkRgacuiNJ8k7U871UozTNtid1hwH3QVOvUisjJWZGWwyXvLKCozM3ZHeJ5+cKO2O26r9Q4Hg/snGeSn9Z+B8XZFa/5BECTgRUVQ0Lrey1MkZpoR2YhXy5J44vFaWQVlgEQEeTLFb0acVXvRloSVCpPWSFs/c1Uf9o0CQozjnw9ppVJfGoyAJJ7g3+oV8IUkZO3Oj2Xe75eyYa9+QAMbhnLU+e2o0F4gJcjqwUsC1Z/Bb/eXzF5rNVIGPokRFaTyiYiIqeQZVm8OHkTr/22BYB/9GvMA2e2qj5JTwBbp8MvYyFzozlv0N4krDbs6d24RKTWcbo9PPfrBt6Zbarmd0yK4PVLO5/aMT+pHK4y2DjRFI7YPquiPSwBOl9pKj+FxXsvPhGpdCed8NSuXTtcLhcLFiwgPDwcgLy8PHr16oXH4/nD0nXZ2dn07t0bHx8f1qxZc3LRi3jZDyt388CE1RSUuggP9GX86PYMa3uKZ1gXZcOcl2DRf0ypX4CErtD/PlV8EpGTMmvTfq79cDFOt8UlPRry1Ki21avjS06M2wk75pgB8w0/Q+7OI19P6GIGy5sMMAm0vhpYEzkeJU43Xy1N551Z29iZXQRAgK+dS7onc/PApkRrSSKpTB6PqeK36VfYPBn2rAQO+0pv94H4TmYQqGFvSOoBwVFeC1dETlyZy8NbM7fy6vTNON0WoQE+PHJWa87vkqhn8cpQlA0znoHF74LlMZMAet8Gfe9Q9VMRqZPenb2NJyeuB2BMl0SeOa9d9Vqu2+2ERe+Ye/fBSb9tR8PgR5WwKiKVbvLavdz91UrySlxEBPnyrws6MKilJonWWJlbYOkHsOKzionANgeknAHtLzCTgH2V1CZS0510wlPXrl0pLCxk8uTJJCUlAfDLL79wxx13YLPZ+OKLL2jfvv2h969atYoLLriAevXqMW/evJOLXqQa2JlVxK2fL2Nlei4Al/dM5sERrQjwPcWlEfP3wtxXTNbywSUv4jvBafeY5S7s1eiLqojUGD+u3M1t/1uOZcHVfRrxyFmtNdBSG1gWZKyDjT/Dxl9g19IjX/cJMIPljfubBKi4Dir5K/IX3B6LX9fs5a2ZW1m9yzwXBvs5uLZvY647rQlhAb5ejlBqpaJss0TTthlmO7Djj++JbgFJ3SG+I8R1hPpt1KEnUgNs2pfPPV+tPNTXMKBFDM+c1464cP3/Wyn2rYVf7oMds815WAIMedwMouv7jojUMV8tSWPshNW4PRZDW9fnlYs7nfq+7b9SsB+mPw7LPgYscPhDzxuh310QEO7t6ESkFknLLuKWzyrG/G7s35S7h6ZUr2RQOTHOElj/g1nybudhuQl+IdDyLGh3vukDd6jvTqQmOumEp4svvpgVK1bw6KOPctFFFwFwyy23MHXqVKKjo5kzZ84R73/ggQeYMGECPXv25L///e/JXFqk2ihzeXhx8kbenrUNgGaxIbx0QUfaJXrhy1ZBBsx7BRa/B05TZYDoFOh9K7S/EHxUZUBETsxXS9K45+tVgPmCd9+wFkp6qm3y98KWaRWD5ofWOS/nHw6JXU2lkKRuppJgQJhXQhWp7izLYvbmTF6YvJFV5Z1jEUG+3DygKVf0alT9Bg6kdjmwA1Lnw875sHNBxfIfh7M5ILaVSX6K62ASoeq3Ab/gUxysiPwVl9vDO7O389KUTZS5PYT6+/DwWa0Z01XVniqFZZmBj0kPVVQ/TephEp+0XJKI1DGT1+7lls+XU+by0LtpFP+5oish/j7eDuuP9qyESQ9WJKwGRcGA+6HLVRqoFpFKU+py88zPG/jvvB0AdGsUyWuXdKZ+mCri13gZG2Dl57BmwpErIARFQetR0G6M+U6gIhIiNcZJJzy9//77PPfccwQFBXH99deTmZnJJ598gs1m4/LLL+eBBx4AYOvWrXz00Ud88cUX2Gw2xo0bx4UXXlgpf4RIdTFz037u/mol+/NL8bHbuP305tzYv6l3Mr8LM2H+6ybxqdQMthFSH3rcCF2vgcCIUx+TiNRYnyxI5aHvzFK0t5/enNtPT/FyRFJlLAv2bzSJT9tnmmXwDpaNP8RmBsuTukNiN2jQDmJaKqlW5DCWZSo+vTB5I1v3FwIQFx7A2OEtGdkhXgPVcmoUZkHaQlPJb88K2L0CijKP/t7wJDNRIjoFYlIqjoNjVO1ExMs278vn7q9XsTItB4D+KabaU3yEqj1VCmcxzHsVZv+romJ2izPNckmxLb0bm4jIKTRvayb/+HAJhWVu2iWE896VXYmtjoP7lgWbJsGUhyFzk2mLam4SVlsM17OriFSaiav2cN83qygodREd4s9rl3SiZxMtG18reDyQvhhWfwVrvz2yryQsEVqeCc3PgEZ9wbcafhaKyCEnnfBUUlLCmDFj2Lx586FOe8uyqFevHj/99BP16tUDoEePHuTl5WFZFh07duSzzz7DruxIqYUOFJbx4Her+Xn1XgA6NYzgpQs60ijaSzOmS/Nh6Yew4A3I22XafIOhw4XQ7R9Qv7V34hKRGue9Odt54qd1ANw3rCU3DWjq5YjklHC7YN9qSFsM6YsgbRHkpP7xfXYfk/TUoB3Ub1uxD1YngNRtLreHb5fv4t9TN7Mrxwyidk2O5NGz23inGqjUbZZlvhPsXmFmxx9MgirM+POfCYiAqKYmISqiYcUWngQRSeAfempiF6njXG4P783ZzotTNlHmMtWeHjqrFRd0TVISbWXJ2wMznzXLJVlusNmh46Wmckh4grejExE5JVal53DVB4vJLiwjPjyA96/uRssG1bTCs9sJyz6E356pGKhO6gGDHzED1CIilWBHZiE3frKUDXvzcdht3D+8Jdf2baxn8NrE7YLtM2D1N7D+RyjLr3jNNwiaDISUoSYBKizOa2GKyNGddMITQG5uLi+++CJTpkyhrKyMbt26MXbsWBo1anToPRdffDGrV6/m7LPP5sEHHyQkJORkLytSbVmWxXcrdvHId2vJL3UR6Otg7PCWXN4zGbvdSw9BrjJYOwHmvgIZayvaG/WD7v+AFiPAUQ3LFItItfLGjC0896tZHueRs1pzTd/GXo5IvCJ/n5kBk7YQdi+HvauhJOfo7w2sB9HNzWzL6GamWkhUc4hsBD5+pzJqEa8qcbp5b852Xpu+hWKnG5sNLuiSxN1ntCAmVNXRxMsKs8zs+N9vB1KBv+gyCIyEsAQIiTUVZQ/tDzsOioaAcH3fEKkEWzLyufurVawor/bUr3k0z45uT4KqPVWe/Ztg2mOw4Sdz7hMAXa6GvrdDaAOvhiYicirsyCzkmv8uZltmISH+Prx2SScGtIj1dlh/riQX5rwEC96qqNTXdJBJfIrv5N3YRKRWKC5zc/+EVXy3YjcAI9rH8dzo9gRXx6U/5eQ4i2Hrb7B5kqkmmL/nyNcbtIeUYdB0ICR00YoHItVApSQ8HY/Vq1cTFxdHdHT0qbicSLWwK6eYu79cyfxtWQB0b1yP50a39161JzCzunfMgUX/gQ0TzaxFgNA46HgJdLoM6jXxXnwiUu29NGUTL0/bDMBT57bl0h7JXo5IvO5gxZC9q8u3VWZ/YMef/4zNDqHx5ZVCjlI1JKQ++CtBXmqfvbklPPvL+kOdZKH+Ptw1NIXLezXC4a3EeJE/4yyGrC3mfp6TBjk7ITfNVPrL2WkGl06EfzgEhpskqYNbQAQEhIFfCPgFl2+/Pz54HgQOf9OhaHdUxV8sUiO4PRbvzdnGC5NNtacQfx8eGtGKC7up2lOlSlsEUx6FnfPMucMful4NfW7XzG4RqfVyisq48ZOlLNiWjcNuY9zINlzes5r3/+TvhVnPw9L/gsdl2lqNhEEPQUwLr4YmIjWfZVl8ND+VJ35ah8tj0Tw2hLcu70LTGPVf1lqWZfq5N02GTb/CrqUcMSnM4Q+J3SC5NzTqY479vDj+K1JHnbKEJ5G6yuOx+HRhKs/8soGiMjcBvnbuOaMlV/WuBoNauemw5H3zJbAoq6K9UT/ofAW0Oht8NUtURI5kWRbP/rqBt2duA+CZ89pxcfeGXo5KqqWyQsjaaqqEZG2BzM2QtRkyt4Cz8K9/3i/EJD6FNqjYB8dAUL3ygfLy/cFzfWZJDbI0NZvHflzHqnSTMNIhMZynz2tHm3gtcyc1SEmuSYTK3wsF+8q3jIp9YYapClh6golRx8PuU5785Pe7vT84/Mzex9+02X3AbgebwyRK2Rx/0lbebrMfvc1mB5sNsFXs4Y9tNhv0vKny/2aR39mSUcC9X69k2c4cQNWeqoRlwbYZMONZSFtg2hz+0OUq6HMbhCd6MzoRkSpV5vJw/4TVfLMsHYDr+jbm/jNbeb9P+69kbzf37VVfAJZ5hms3BvrdDTEp3o5ORGq4panZ3PTJMjLySwnx9+GFMR0Y1lZVQOuEgv2wZQpsnmwKSxTuP/J1uw/EdzYJUA17QlxH05+tSSkiVarSE55WrVrFsmXL2LNnDwUFBTz11FMATJo0ifbt2xMXpxlQUjelZRdx3zermLfVJBZ1SY5k/Oh2NIsN9XJkgKvUVHta/rEp1XgwQ9k/zCQ9tTsfGp2mJShE5BDLsnj8p3V8MHcHAI+e3Zqr+2h5OzlOlmUGw3PKq4TkllcNObjl7jq+hKjf8wk8MgHKL8RUifpDtZBg8AutOPYNrBgUP3yg/NDe3wyKi1Qyj8fi00U7ee6XDeSXunDYbVzTpxG3n56isuhSu7idJjmqOAeKD1RsJeXnpflQVmASZcsKjzwuLSg/L6iYqV8TjKuCJC+Ro3B7LD6Yu53nJ22ktLza0wNntuLi7qr2VKksC7bPhN+eqUh8svtA29HQ+1Zo0M678YmIVBHLsnj9ty28MHkTAENa1+ffF3asGd9X9q2D356qWKIUG7QZBafdA/XbeDMyEanhMvJLuOWz5Szang3ATQOacteQFHwc6j+sMyzLTPBNnQs75pp93q4/vi84FuI6mC2+o9mHJykJSqQSVVrC0/Lly3nsscfYuHHjEe3r168HYNiwYezatYvrrruO2267TZ0uUidZlsXni9J4+uf1FJS68HXYuLF/U/45sBkBvtVkSYacnbDiM1j+KeTurGgPjoE255nOvMRuGvgVEVPp6ZcNvD3LVHq6b1hLbhrQ1MtRSa1Rmm+qghTsragckr8XCjPLB8qzzb6ofH9widaqYvcBn4Ajk6EcvkepEuLzu6ogjt+12//4noPVQGw2OOf1qv07pFrKyCvhsZ/WMXHVHgASIgJ5/Jw2DG5V38uRiVQzrjJwlx62LwV32ZF7V8kf2zwu8znh8ZTv3eV715+0ucHyHNZW3m5ZgFWxhz+2Hdyf/77X/jFJ3bRtfwH3fL2KpakHAOjbLJpnR7cjMTLIy5HVMgcTn2Y+D6lzKtqbDoLet0GTARq8EJFa6YeVu7n7q5WUuTyk1A/hzctq0DJOu5bBrBdg48SKtpZnmcSn+I5eC0tEajan28P4Xzbw7pztAPRpFsUrF3UiKsTfy5GJV1iWGV89mAC1exns32D6Fn4vMBIatIfolPKtudnCEvRdQuRvqJSEp8mTJ3PnnXfidruxLAuHw4Hb7cZmsx1KeGrfvj1lZWXYbDbGjBnD448/ftLBi9RUu3KKefi7NUzfkAFAo6ggnhzVjr7No70c2WE8HjNrcfVXsPY7M7B8UEgDaHkmtBxhKj/5+HktTBHxLsuyeGnqZl6ZthmAWwc1484hKUpsllPLskyC1O+ToI6oFPK7yiGlBRXHzuLfDY6XD5Z7gyqC1Gm/bcjgoe/WsCunGIDhbRvw6NltaBAe4OXIRESkJvh9tadgPwf3n9mKS3s01PN5Vdi1FOa9Cuu+rxjIqN8Wul1nlk7yryGJACIix2lp6gFu+mQpGfmlBPs5eH5MB85sV4NW9Ni7BmY9b+7bB5PXmw0xS5Q26qdBZhH5W35cuZv7vllFUZmb+PAA3risCx2TIrwdllQHZUWwby3sWQF7Vpp9xvo/r17tGwxRTSuSoCKSzRLaEUkQGq+xWJE/cdIJT3v37mXYsGGUlJTQvn177rjjDlq0aEHv3r2PSHhatmwZ48ePZ+XKldhsNt5//3169epVKX+ESE1kWRa/rtnLuB/Xsi+vFIBRHeN5YEQrYkOr2aCW22mWulv9FWz8BcryK17zD4PmQ8yXw6aDIFSVCETqojdmbOG5X02Vx4u7N+TJUW1x2NVRJDWYZf111RC387DKH7+vAnKsds+R7zm8Iki/u7z9l4uXFZW5eHnaZt6dvR23xyLE34f7hrXg0h7J2HVfFRGR47A9s5B7vlrJkvJqT72bRjF+dHuS6qnaU5U4sAPmvwHLPwZnkWnzD4MOF0HXayG2pVfDExGpTBn5Jdz2+XIWbDOTY6/t25ixw1viW5OWccrYALNfhDVfVySsNmgPvW6BtueZas4iIidg0758bvx4KdsyC/Fz2Bk3so2WmJajc5VCxjqThJu1GTLLt+xtf7GCgQ1CG5jl8MITzRYaByGxZoWe4BhzHFhPK/RInXPSCU9PP/00H330Ee3atePTTz/Fz8+PoqIiOnfufETCE0BpaSlXXnklK1euZOjQobz88ssn/QeI1HT5JU5enLyJj+bvwGNBiL8Ptw5qxtV9GuPnUw0/lFylsH22Wft8489miaHDNWgHzU6HpoPN0ne+1Sx5S0SqzCcLUnn4+zVYFpzRpj4vX9Sp+izXKSJSw6zbnccD365mRVoOAF2TI3nmvHY0rx/q3cBERKRGcHssPpy3g+cmbaDE6SHoYLWn7g2VQFtVirJhxWew5D0zYHFQcl/ofAW0Ogv8gr0Xn4hIJXG5PbwweRNvzdwKmO8qr1/amfphNawfOGsrzH/d3LtdpsouofHQ4wbochUERngzOhGpYfJKnNz95UomrzNjZhd0TeTxc9qqf1yOj9tpJlJkbjJb1hbISYPcdLO5S4/v99jsEBRtkp+CoiAg3HyeBUT87rj83C8IfMu3g8d2/TcrNctJJzwNHz6cHTt28Pbbb3PaaacB/GnCE8CcOXO47rrrqF+/PjNnzjyZS4vUKqvSc3j4+7WsLB/UahwdzMNntWJQy2pcMcnjgfTFsHkSbJlqSjIezuFvkp4a9YHkPubYTzNKRWqzX1bv4f/+t4Iyt4fujevxzuVdCQ/SzDgRkb/D7bH4ZEEqz/26gcIyN74OG/8c2IybBjTF30edDyIi8te2ZxZy79crWbzDVHvq1SSKZ0e3IzlKiTdVxuOB7TNg8XtmotjB6iF+IdD6HFP5KbmvZl6LSI03ae1e7v5yJfmlLqJD/Hjl4k70bhrt7bBOXFG2SVZd+B8ozDBtvsHllfqugQZtvRufiNQYlmXx1sxtPD9pAx4L2iaE8ealXVRpVU6OxwNFmZCbdlgSVJopSFGYCQUZ5vOr+EDlXM8nAHwDzWfh7xOifAJMJUSH32H7YxzbfUwClc0ONsdhx+Wb3WHaDx3bf3fsOPLYZoOEzpXzd0qtcdIJTx07dqS0tJR58+YRGRkJHDvhKTs7m969e+Pr68vq1atP5tIitY7HYzFh+S6e/WUDmQUmW3dAixgeGtGKZrE1YDZ/QYZZ+m7rNLM/+AXxILuv+YKY2A0SukJiV6jXROuji9Qy87dmcf1HS8gvddEkOpj3rupG42gNqIiI/F27c4p5+Ls1TNtgnq2axYYwfnQ7uiTX83JkIiJSE3g8Fh/O38H4X021Jz8fOzcPaMqN/ZtqxnlVy02H5Z/Ays/NjO2DwpOg3RiTABXXQf0iIlJjbc8s5KZPlrJhbz42G1zTpzH3nNGiZn6+uEph9Vem6lPGuor2xO4m8anNKDMALCLyF+ZszuTWz5dxoMhJRJAvL1/Uif4pMd4OS2o7t9MkQBVmQOF+k9BbkgvFOVBSvhXnmLaSHCjJM0tylxWVL819Uikjp864XG9HINXMSSc8denShaKiImbOnElsbCxw7ISnXbt2MXjwYEJDQ1m8ePHJXFqk1sovcfLa9C28P3c7TreF3QYXdE3i9tNTaBBeQ0oDW5YpubhjDqTOhR1zIX/3H98XGGnWSG/QrmIf3VxrpYvUcOv35HHdh0vYlVNMeKAvb17WuWbO8hMRqSYsy+KnVXt47Me1ZBaUYbPBZT2SuXdYC0ID9NwkIiJ/bUdmIQ9+t5q5W7IASI4KYtzINgxsEevlyOoAy4K0hWbZpLXfQmlexWsRySbxqfU5kNBFyU8iUuMUl7l57Me1/G9xGgBNY4L51wUd6ZAU4d3A/i7Lgu0zYckHsOEn8LhMe2AkdLwUOl8JMSnejVFEqr1dOcXc9MlSVqXnYrPBHaen8M+BzXBoeWmpjiwLXCXlyU+FFUlQhxKiytvcZSaxyl12lOOyo7Q7ze+23OBxm+q3Vvnec/jxYa95PIcdH+Vn7lzr7X9aUs2cdMLTqFGj2LhxI88//zxnnXUWcOyEp08//ZQnnniC1q1bM2HChJO5tEitt21/Ac/8soEp5Wv++vvYuaZvY27s35TwwBo2sGVZkJMK6Utg11KzFN6eVUdfd9bhB1HNzRfH6BYV+8hG4B9yykMXkb8nI7+E6z9ayoq0HHzsNh47pw2XdG+ITR34IiJ/W05RGU//vJ4vl6QD0CAsgCdGtWVI62q8DLKIiFQbBxNon5y4jn155vv4sDYNeOTs1sRHqGrFKeEsho2/mMSnzVPAVVzxWlgipAyFZkOg8WnqAxGRGmX6hn3c981q9ueX4rDb+OeAptwyqDl+PjV4Cc/8fbD8I1j6oVk+6KD4zmbJu7ajIVgT/ETk6EqcJiH080Xm/tG7aRQvXdiR+mE1pLCBiEgNcNIJT//+97956623SEpK4ptvviEsLOxPE5527tzJBRdcQG5uLtdffz133HHHSf8BInXB0tRsnvl5A0tSzfqr4YG+3NC/CVf0akSIv4+XozsJrjLIWAt7Vx+2rYGy/D//maAoM/sxouFh28HzJPDTslki1UmJ0829X6/ih5Wmwtvozok8OaotgX41sLS5iEg1Mm9LJvd/u5rUrCIAzmzXgHEj2xAbqk4zERH5awWlLv49ZRMfzNuB22MR4Gvn+n5NuKF/U4Jrcj9DTVNWaJKe1v8AmyZBWUHFaw4/aNgLmg+BpoMhpiXYa3DSgIjUCQcKy3jkh7X8WN4P1CY+jBcv6EDLBmFejuwkedywZSosed/cty23abf7QLPTof2F0GK4lrwTkaP6akkaj3y/lmKnm3rBfrw4pgMDW6rKqohIZTjphKecnBzOOOMM8vLySExM5J///CfNmzdn9OjR2Gw2Vq1aRXp6OtOmTeOdd94hNzeX4OBgJk+eTFRUVGX9HSK1nmVZTFufwfhfN7A5w3SARQT5cl3fxlzZu1HtWcrE4zGVoDI3wf6NkLkR9m8y5yU5f/3zQdEQFgfBMX/cQmLNjJuD5z7+Vf7niIi5f705cysvTNqIx4KWDUJ567IuNIpWgqKIyMkocbr599TNvDN7G26PRViADw+c2YoLuyWpmp6IiByXDXvzeOS7tSzakQ1ATKg/dw9N4fwuSVpu41RzlpgllDZPgc2TTd/I4YKiILk3NOoHyX0gtrUSoESk2vpp1W4e/m4NB4qc+Dns/OO0xvxzYDOC/GpBUm1BBqz5Blb+D/asqGj3DzNJT63ONomqfkFeC1FEqp8tGQXc+vly1u8xSxtf17cx9w5rWbOr4ImIVAMnnfAEsGDBAm688UZKSkqO2bFuWRY+Pj68+uqrDBw48GQvK1InuT0W36/YxWvTt7AtsxCAsAAfru3bhKv6NKp5S92diOIcUzo4Z6fZDqRWHOekQmneif0+32AICDNfRo+6Dwf/ULP5BlZsPoFHnvsGgU+A2dTZKPKn5m3N5LbPl5NZUEaovw9PntuWczomeDssEZEab+3uXMZ+s5rVu3IB6NmkHk+d246mMVoGR0RE/pplWfy6Zi/P/rrhUOXAlg1CeXBEK/o1j/FydHWUZUHWFpP8tGUKpM4/cuk7gMBISOhitvjOkNDZTPQSEakmMvJLeGDCaqauzwDMctwPjGjF2e3jas8Ejf0bTeLTqi8hL72i3TfIVH5qNRJSzjB9zSJS55U43Tzz83o+nG8S29slhPPqxZ00MVhE5CRUSsITwKZNm3jsscdYunTpn76nVatWPPLII3Tq1KkyLilSp7k9Fj+t2s0r0zazdb9JfAr2c3BBtySu6dOYpHp1cAZJcY5JfCrIgML9ZivIgMLMivODm8dVNTHYHODwBbuv2R869inf+x127GvKHh98j90BNjvYbOX7P9uO8vqIF6vm7xGpZPvySrjls2Us3mGW6Dy7QzxPntOW8KBanKwpInIKuNwe/jtvBy9O3kSx042vw8a1fZtw66BmWppIRESOS6nLzcfzU3ll2mbySsx35j7NorhzSAu6JEd6Obo6zlUGu5fDjtmQOhd2LgRn4R/fF54E8Z0groOpABXbEiIaaXKWiHiNZVlMXrePJ35aR/oBk7jZvVE9xo1sQ+v4WpQE5PFA2kJY/6PZcndWvObwM9X5mg0uX6K0henfFZE6a/Lavdz7zSpyipwE+zl48ty2nNsp0dthiYjUSJWW8HTQli1bWLhwIenp6RQUFBAQEEB8fDxdu3alXbt2lXkpEcEkPv28eg+vTd/Cxn35ANhtMKxtA67r14TODdUp+QeWBcUHzFaabypDleT9bp9bcV5WYErLu4rBWQzOInPuLDZt7jJv/0UwLtfbEYgcN5fbw+u/beWV6ZtxeyziwgN47vz2mj0uIlIJ0rKLeOT7Nfy2cT9gZlE/OKIVZ9WmWdQiIlKlDhSW8er0LXy8YAdOt+k27J8Swx1DUuiYFOHd4MRwO2HvKti1zGy7l5kqIxylm9c3yAyux7Y2+3pNoV5jiGys5ZZE5JQpcbp5Z9Y2Xp+xhRKnB7sNLu2RzJ1DUogM9vN2eJXLsmDPSlj/A6z7AbI2H/l6WCI0G2SSn5oMgMAIb0QpIl62O6eY2/+34tDS0qM7JzJuZGtCAzQxWETkRFR6wpOIeIdlWczenMk7s7cxe3PmofYOSRFc2r0hZ3WIqx1rpFdHHnd58lOJ6XT0OM3+8GOPq7ytrOL4iNfKzJdhy3PY9vvz328HX3fDwAe8/U9B5IStSMvhji9WsL18ec5zOyXw4IhWRIf4ezkyEZGab+q6fTz201rSss0s6p5N6vHYyLa0aBDq5chERKSmSMsu4vXftvDV0nTcHtN9OKhlLDcNaErX5Egl0lY3JXlmgH3XUshYZ7b9m8Bd+uc/ExpnEp/qNYbwRAiLh7CE8n08BESoComIVKpdOcU8/fN6Jq7aA0CIvw9X9k7m2r5NqFfbEp8O2r/RLFG6dRrsmHvkfdlmh/ptIbkPJPeChr0hRBMCReoKl9vDq9O38Or0zXgsSIgI5Pnz29O7WbS3QxMRqTGU8CRSC23cm8+7s7fx/YrdlLk9AIT6+3Bu5wQu7t6QVnG1qFywiNRoRWUunvt1Ix/O34FlQXigL/cPb8kFXZOw29WxLiJyMkqcbv4zaxuv/7aFUpeZRT2mSxJ3DEmhQXiAt8MTEZEaIjWrkFembeHb5emU5z3RqWEEN5zWlKGt6+u5vTpzu+DA9vIEqPWwfwNkbzdb6XFUivYNMklRIfUhOAqCoiAoGoKjy48PbvXAPxT8QsGhyXYi8tfmb83iiZ/WsW5PHgBBfg4u75XMP/o1qd0T4cqKIHUebJlqEqAyN/3xPVHNTfJTUg+zTGl0C91bRWq5hduyuOurlYeW/ryyVzL3DW+pIgYiIsfhhBKeXnvtNQAiIiK47LLLjmj7O2655Za//bMi8tcyC0r5akk6ny/ayc7sokPtHZIiOLdjPGd1iK/dXyBFpMZYmZbD/RNWH+roahMfxoMjWtG7qWaziIicrLTsIp7+eT2/rNkLQICvnev6NuGG/k1UKl1ERI7b9sxC/jNrG98sS6fMZSZXNYkO5srejTi3cwJh+kypOSwLig+UJz9tM0lRebsgbzfk7THHxdl/73f7BpvkJ/9QCAirOPYLBd8A8An83T7AJFb9vs3uYzaHb/mxrxnwP3TsC3bHYcc+qkYlUsN4PBZT1+/jlembWbPL9AcF+Nq5rEcy1/dvQmxoHZikkbfbJEClzoOd802C6u/5BEKDdib5Kb4TxHeEqGbm3icitUZBqYunf17PZwt3AtAoKohnzmtPr6ZRXo5MRKR6O6GEp5YtW2Kz2WjYsCGTJk06ou3vWL9+/d/6ORE5MR6PxdytmXy2cCdT1u3DVT4l02G30a95NOd2SmBI6/rKFhcRr3K5PXwwdwevTNtMfqkLgMEtY7l3WEstwSQiUgmWph7gmZ/XsyT1AAD1gv24bVAzLurekABfh5ejExGRmmJ/fikfztvBR/N3kFdintuD/Byc0zGeS3sk0zYh3MsRSqVwFkP+HjMYX5ABRVlmK8yEoszy4yxzXHwA3GXejhhsDpMEhc0sE3Vos5Vv9j957bDj379+6xIv/1EitZ9lWfy2MYOXp25mZbqpPufnY2dEuzgu6dGwbi2jWpQNaQtNAtTu5bB7BZTl//F9dl+T9BTbEmJbQ0xLiG0FkY2UCCVSw83atJ/7vlnFntwSAMZ0SeSBM1sRWVuX/RQROUknnPAEkJycfETC09+1YcOGv/2zIvL37M8v5adVu/lu+a5DXyDBzJ7p1zyGM9o0YHDLWD08iYjXZBWU8sq0zXyycCfu8gTNYW0acMugZho8ERE5SZZlMXndPsb/soFtmYUA1A/z5/rTmnJJ94YE+inxSUREjk9BqYtvlqbzyYJUNmcUHGpvnxjOeZ0SVFW6rnGVQmk+lOaV78u3kjzTVlYAzhJwFf/JvsQkWbnKjz0usySfx3nksdtp9qfKuONY+k9EKoVlWczanMnLUzexbGfOofaU+iFc0r0h53ZOJDywjiXzeDyQvbU8+al827va3FOPxuaAiIZQrzHUawKRjc1xZGMIT4AA9auJ1AR5JU6e+3UDnyww1Z6igv146KxWjOqYUHcSQEVEjtMJJTyJSO2ybX8B360wyU+HL3nnsNvo3qgep7euT/+UaJrGhOghSkROua37C3hx8kZ+WbOXg08rA1rEcFXvRpzWPAa7XfclEZG/y+n28MXiNF7/bcuhWYNRwX5c168Jl/dKJsRflT9FROT4WJbF4h0H+GRBKr+s2YPTXVFVum+zaEZ1imdI6wb6bJHK5XFXJD8dnhBleco3q+IY/qTd+l279cf25N7e/CtF6iTLsliVnstnC3fy/+zdd3gc1dXH8e82adWrJVmyLLn3XsA23ZgOpgQCgfCSHhJKSEIIJfQACaRAgCSEhFBDx3QMpmPce7dlW7ItWb2X1bZ5/7hqbmCjsiq/z/PMMzN3RpojJ8zO3jn33DfWFNDgCwBmwO7Z49O5YMoApmUn4uir/ULBIFTvgeLNULLJrIs3QulW8NV/9c+GxUBsukl+im1aYlIhKgWiUyCqn1mHRXXN3yIiX2lFXjk3vrqOrUUmyfGoQYncdvYYRqfHhjgyEZHuo90JT4sXL2bQoEGkpqZ2VEwi0sUsy2LT3hre31jI/A1FbNpbvc/x/nFujh2WzLHD+jFraDKJqv4kIl1oW1ENj36ynddX59NU8InspEguOzqLCyYPUEU6EZF28PqDvLJyD49+ksPu8gYA4iJcXDJ9IJceNZDMxMgQRygiIj1JaW0jb64pYN7qAtbsrmxpD3PYmTEkiTmjUzl5VCppce7QBSkiIj1GtcfHvFX5PLt4F1uKWqd2S4oK45QxqZw2tj8zBicR5rSHMMpuIhiE2kIo3wHlO6FiZ+t2ZZ6ZfvRwuSIhMhki4sAdD+GxpjrU1y3hMeB0m8Wu/01EOoLXH+Rfn+/goQ+30egPYrfBJdMH8qtTRuhdnYgIHZDwdPbZZ7Njxw5+//vfc+6553ZQWCISSrvL65m/oZBPt5awdGc5jf7gPseHpkQzLTuRadkJTMtOZEBChCpAiUinyy2t48lFuby8Yg81Hj8ALoeN44encN6kDGaPSsHt0lRMIiLfhC8Q5I3VBTzySQ47SsxUd3YbnDQylctnZHHM0GRV1hMRkSOys7SOeavyeXNNQcs0qs3GZcQxa2gyM4ckMTU7gcgwVX8SEZFDsyyLlbsqeH7pbt7fWERVQ+vUlrFuJyePSmXO6FRmDEkiPlIJAAflrYPqAqjaA9X5rdu1xVBXDHUlUFtiphrtCI5wcLnBGWHWrkiTCOWK2HftDAe7ExwusLvA4WxaH2zf2bq22dsstqa1Y7/2NseHzu6Yv0skRPZU1HPvu5t5e+1ewNz7rjppKJfPyFafuIj0ae1OeJo0aRIej4f33nuPrKysjopLRLoJjy/A0p3lfL6thM+2lu4zkqZZSkw44wfEMS4jnnEDYhmbEUdKjEZrikjnqGv0M2+1Gd23sU1FuqgwB8cO68fsUSmcODKF5OjwEEYpItIzBYIWCzYV8fSiPL7IKW1pH5wcxbenZXL2hHTS4yNCGKGIiPQ0lmWxvaSWDzYWs2BTESt3VdC2N9LlsDEpM4FpgxKYmJnAxMx4+sXoWV5ERA7OFwiyZEc5767fy/wNRZTWNrYcs9lgZFosRw9O5OjBSRw1KFEJUEfCssBba5Kg6suhsQo8X7dUt253VLJUZ7i9KtQRiHSIJTvKuOPNjS394qmx4VwzexgXTc3E5VBlNRHpe9qd8DR9+nRqamr4+OOPSUtL66i4RKSbKq/zsjy3nOV5FSzLLWfdnir8wQNvI6mx4QxPjWF4agwjUmMYlhrNsNQYosM1alNEOs7Wohrmrcrn9dUF5Fe2dqrYbDAmPZajByVx9OAkpmUnEhfpCmGkIiI9T05xLc8szuPlFXuobfS3tE8flMjciemcMba/phUVEZEjVlLTyOfbSli0vYwvt5ft8xzfLCM+gomZ8YxMi2F4mulXyEyMxKFqgyIi0kYgaCo/vbuukM+2lZBTXLvP8eYEqImZ8YxOj2VMeiwj02JUWbCzBPzg94CvwSQ/+TyHWDctfg/4GyHoh4APgr6mbb/ZDvj2Pda8HwyAFTz8JRiEK78I9b+OSIcJBC1eWbmHBxdsa3mWzkqK5JqThnHOxHQlPolIn9LuhKdbb72VF198kcsuu4xbbrmlo+ISkR6iwRtgfUEV6/ZUsT6/irX5VWwvqeVQd5aUmHCyk6LISookOzmKgYmR9I9zkxprFs23LiLfRDBosb6gigWbivlwUxEbCqoPOCc7KZLxA+IZPyCOEWkxDEuJITU2XFNyioh8jdpGP2+sLmDe6nyW7ixvaXfabcwamsyJI/px/IgUBiVHhTBKERHpiSzLYnd5A19uL2XlrgpW765kW/HB+xTcLjvDUmIY3C+KzIRIMhMjyEyMJDPB9Cs49WJHRKTPK6lpZMnOMhZtL2PxjjK2l9QdcI7dBoOSoxidHsfItJiWvuqspEhi3BosJyI9R6M/wP+W7OLhj3MorfUCZuDAD48dxLenZSq5U0T6hHYnPHk8Hq677jo++eQTpkyZwmmnncaoUaNITEwkPPyry0+np6e359Ii0k3VNfrZXFjN1qJathbVNC21lNQ0fu3PJkWFkRrrJi3OTWpsuNmOdZMa5yYxMoy4CBfxkS5i3C6N7BSRQyqq9rB4RxlLdpazeHsZO0oP7OACiHE7GZwcRUZCBOlxEaTHmyUjPoL0eDeJUWFKiBIRaaOgsoG31hbw+uqCA5JLs5IiOX54P44b1o+p2QmaOkJERL6RGo+PdXvMgKqthTVsLa5hW1Etjf7gIX/GYbeRFBVGv5hws0SHt2wnRIYRG+Ek1m36Epq3I8McetYXEenlims8LNtZwfqCKjYWVLOhoHqfKfD2lxQV1pT8FEVanJuUGNM/3bzuFxOO2+Xowr9AROTr1Xv9PPllHv/+YmfLPS4h0sV3Z2TznekDSYtzhzhCEZHO0+6EpxNOOAHLsigqKjqiTgKbzcbGjRvbc2kR6WGq6n3kldeRW1ZPXqlZ7yqvo7DaQ1FVI97AoTsvDybG7SQ+0mWSoCJMMlRshIsYtxO3y0FkmFkiXA4iWradZh3mwO104HTYcDnsuJrWTocNl92OXclUIr1KRZ2X9QVVrN1jKtJtK64ht6yewEGm5GzLabe13mciw4iPcBEXae450W5n6z3G5cAd5iCy6X4T5rTjtJv7isNuw+Ww4bAfrM2GzWbDhimzbsNG8+NU231zvM15ejEjIt1ATnEtH24q4tOtJSzLLccX2PeeOjg5ikkDE5g0MJ7JAxMYlhqtsuoiIvKNBIIWu8rr2VJYQ15ZHbsr6tlV3sCe8nr2VDQccX8CmCSpqDAHblfzYjdrp4Nwl90847schDtNX4HDbsNptzetbW3WbY+btb3peb35WZ5DPfO3aWO/5/6Wnz/ge4K+C3SlcyZowK5Ib1Nc42FDQTUbC6rJKa4lr6yOvLJ6yuq8h/XzMeFO0zfUtl+6abu5X6j5s8X0S9vbbDtaPl+aP3vUFy0iHcXjC/Dyij089tkOdpXXA+aZ95TRqXz36CxmDEnSs6SI9DrtTngaOXLkN7uwzcamTZvac2kR6UUsy6Ki3kdhlYeiGg9FVR6TCFXtMW3VjVTWe6lq8FHnDXR6PM3JCC67HZfTJEQ57faWJAanw47dBnabDXtT8sHB1ua46Zi0t2lrPa/1HPZ7ztz/sXP/B9G2ew9dMqlT/h1EerNGf4CdpaZTq6CyoWnxkN+0XXwYVelC7aDJUBx4P5GeY+vdp4c6BJFvpK7Rz5fby/h0azFf5hy8sp7TbmNQchTDU2MYmhLN8NQYBjVV2YuL0NQRIiLyzQSDFiW1jZTUNLau2yxVDT6qPT6qG3xUe/xUN/jwf83AB5FmufedGeoQRKSL1Hh85JXVm6W8juLqRoprTL9089r7FdUG28Nmo00y7UGSax2t7Q7bvkmwrYPjmtraDJ7bN+G2tX/54Am3Bx+I11s888OjQh2CSJfxB4K8u76QpxflsTS3vKV9UHIU503K4NyJGQxMigxhhCIiHafdCU+vvfbaN/7Z8847rz2XFpE+yusPUu3xUVnvo6rBR1WDSYSqqvdR2eCjrtFPgy9AvTdAgzdwwHaDN0C910+jP4g/YH2jkaDdjTrgRDpeoz9AeZ2Xyvrm+03TdoOPinqvudd4g3h8be4tvgANXj++gIUvYO4x/qCFP9i83domcjC6n0tvUVHnZfXuSlbtqmDlrkrW7K6kptF/yPNjwp1mStGECPrHuUmODicpOoykqHASo8JIig4jxu0kKtxJVJhTUxuLiMg3ZlkWHp/pV6jx+PH4AjT6A3h85tm+Zd3U1ugPEAyaZ/hA23XAIhAMHtDuCwSxACywsLAszNK83RKHOam5zbKspnXT8aa25nObf166jmXB/358dKjDEJFuwrIsqhp8lNW17Yv2tvRJVzX4TB9Rcx+0L4inabu576jtcXUNdS31t0hftbmwmmcX7+LVlXv2KSYweWA8cydmcMqYVPrHRYQwQhGR9ml3wpOISE9nWc2dkha+YBCf33RYepvWvkCwabHwB4J4m5IYLCBoWViWRTBotoOW+X1Bq3nfdEgG27RZLee17h9sWq2D3ZwPdse2gB8cM6ij/1lEpBM1/3fvD1oHvPzY50XHVxyzzMF99tu+QJGex7IsBiRodJX0TpZlUVDlYVtRDduKatlWXMPWolp2lddTfphTR7QV4XIQ7XYSHe4kKtxBVJiTMKedMIfdTFfcVKGzZd9hx+U0+w67DRut1TZtNlvL6OW2FTiBfSp1tpxL6zk9Pe2qp1ey787/C1w0LTPUIYiIiIhIN2VZZhCuxxds6h8KtkmmbZtka9oD+yXXHqovqW0/krnOwZJq2/7cgb+nNcau/TfpbOdOygh1CCIhVdfoZ/6GQl5blc/CnNJ9ki7HZcRx8qhUTh6dwqi0WE2zKSI9ihKeREREREREJGTqvf6WKUXzKxoorGqgrM5LeZ2XslovpXWNlNd5qfX4VSFPegyNIBcREREREZHuqLjawxtrCnh3fSErd1Xsk+CYFBXG0UOSmDkkiZlDkslOimyZDlNEpDsKScJTSUkJ77//PpdeemlXX1pERERERER6IMuyaPQHqWv0U9cYoLbRT22j3+x7/aYip9+MlG5bodPr33e/eaohq6kyZ0vVzbZtsE+lzpZR0Vbb9tD+e4S6pl+oh06F/J//a/znimmhDkFERERERETkK5XUNPLx5mLe31jEwpxSGnyBfY4nRoUxMTOeiZnxTMiMZ0x6LMnR4SGKVkTkQB2S8FRXV8eTTz7J559/Tnl5OYFAgP1/rWVZeL1e6urq8Hg82Gw2Nm7c2N5Li4iIiIiIiIiIiIiIiIiIyDfk9QdZs6eSL3PK+HJ7Kat2VeINBA84Lzk6jOGpMYxIi2FoSjTZSVFkJUXSPy4Ch6bDE5Eu1u6Ep4aGBi6++GK2bt0KcECiU8uFbLZ9jjkcDjZs2NCeS4uIiIiIiIiIiIiIiIiIiEgHavQH2FhQzerdlazeXcma3ZXkldcfsuJzmMNO/3g3KTHhpMS4SYk169Q266TocGLcTlwOe9f+MSLSaznb+wuef/55tmzZAkBqairjxo2jtLSU1atXM3r0aIYMGUJFRQWrV6+mtrYWm83GxRdfzI9//ON2By8iIiIiIiIiIiIiIiIiIiIdJ9zpYNLABCYNTGhpq/f62VZUy5bCGrYU1bCztI7csjp2l9fjDQTJK6snr6z+a3+322Unxu0ixu0kxu0i1u0kxu0kOtyJ2+Ug3Gkn3Nm0dpltd9PaYbfhtNuw77d22GzmmMOG3WbDabdjt4PdZsNmAxum+pTZpmW7aatl24Yp5NK83foztv1+pnXbZrMd8DtbW6QjpcW5Qx2CdDPtrvB02WWXsXz5ciZNmsQTTzyB2+1m3bp1XHjhhZxwwgn84x//AMDj8XDHHXfw2muvkZqayltvvUVMTEyH/BEiIiIiIiIiIiIiIiIiIiLStQJBi4LKBvZWeSiu8VBc3UhRjYeSpnVxdSPFNY1UNfhCHar0cLn3nRnqEKSbaXeFp+3bt2Oz2bjyyitxu01G3ejRowkPD2f58uUt57ndbu655x7y8vJYtWoVL7zwAj/84Q/be3kREREREREREREREREREREJAYfdRmZiJJmJkV95nj8QpLbRT43HT7XHR43H37SY7dpGP42+AI3+YNMSoNHXuu3xBfEHgwSD4A8GCQQtApaFP2ARtCz8Qcu0NS3+oIVlWS3T8DVXgbEsq832gW0czvkc+Htpc0xEuka7E55qamoAGDZsWEubw+Fg0KBBbNmyhdzcXLKzswFTzu173/seK1eu5MMPP1TCk4iIiIiIiIiIiIiIiIiISC/ndNiJjwwjPjIs1KGISC9hb+8viIiIACA8PHyf9qysLMBUgGpr3LhxAOzcubO9lxYRERERERERERERERERERERkT6m3QlPKSkpAOzZs2ef9oEDBwKwbdu2fdodDgcAtbW17b20iIiIiIiIiIiIiIiIiIiIiIj0Me1OeJoyZQqWZfHUU0/t0z548GAsy2LRokX7tK9btw4At9vd3kuLiIiIiIiIiIiIiIiIiIiIiEgf0+6Ep/PPPx+At99+mx/+8IcsW7YMgKOOOgqbzcbSpUt58skn8Xg8rF+/nvvuuw+bzcawYcPae2kREREREREREREREREREREREelj2p3wNHHiRC688EIsy2LhwoW8+OKLAKSnpzNnzhwsy+K+++5j0qRJXHjhhezatQtoTZQSERERERERERERERERERERERE5XO1OeAK44447uP7660lKSiIzM7Ol/a677mLMmDFYltWyAJxxxhlceOGFHXFpERERERERERERERERERERERHpQ2xWcxZSB7Asi7q6OqKjo1va/H4/7733HqtWrcLhcHDMMcdw3HHHddQlRURERERERERERERERERERESkD+nQhCcREREREREREREREREREREREZHO1CFT2omIiIiIiIiIiIiIiIiIiIiIiHQF55GcPG/evA69+Lnnntuhv09ERERERERERERERERERERERHq3I5rSbuTIkdhstg67+KZNmzrsd4mIiIiIiIiIiIiIiIiIiIiISO93RBWeAA4nP8put9O/f39iYmLwer3s3buXhoYGc0Gnk8zMzCOPVERERERERERERERERERERERE+rwjqvB0KA888ACPP/44mZmZXHfddZx00km43e6W48FgkCVLlvDAAw+wceNGLrnkEm699db2XlZERERERERERERERERERERERPqYdic8LViwgKuuuoohQ4bw3HPPERcXd8hzvV4vl156KevXr+eee+7hvPPOa8+lRURERERERERERERERERERESkj7G39xc8+eST2Gw2fv3rX39lshNAWFgYv/zlL7Esi+eee669lxYRERERERERERERERERERERkT6m3QlPmzZtAmDixImHdf6oUaMAyMnJae+lRURERERERERERERERERERESkj2l3wpPD4QCgpqbmsM4vLS0FIDIysr2XFhERERERERERERERERERERGRPqbdCU+DBg0C4NVXXz2s85966ikAhg8f3t5Li4iIiIiIiIiIiIiIiIiIiIhIH9PuhKfzzz8fy7L417/+xfPPP3/I8yzL4uGHH+bFF1/EZrNx8cUXt/fSIiIiIiIiIiIiIiIiIiIiIiLSx9gsy7La8wu8Xi+XXXYZa9euxWazkZ2dzbHHHktWVhZut5uGhgZ27NjBJ598wt69e7Esi1NOOYWHHnqoo/4GERERERERERERERERERERERHpI9qd8ARQUVHBNddcw7Jly8wvtdkOOKf5MnPnzuXOO+8kPDy8vZcVEREREREREREREREREREREZE+pkMSnpotWLCAN998k8WLF1NVVdXSnpSUxHHHHccFF1zA1KlTO+pyIiIiIiIiIiIiIiIiIiIiIiLSx3RowlNbHo+H6upq4uPjCQsL64xLiIiIiIiIiIiIiIiIiIiIiIhIH9NpCU8iIiIiIiIiIiIiIiIiIiIiIiIdzR7qAERERERERERERERERERERERERA6XsyN+SUNDA0888QTvvfcee/bswePx8HWFo2w2Gxs3buyIy4uIiIiIiIiIiIiIiIiIiIiISB/R7oSnxsZGLr30UjZt2gTwtYlOIiIiIiIiIiIiIiIiIiIiIiIi31S7E56eeuqplkpN/fv3Z+bMmSQlJREWFtbu4ERERERERERERERERERERERERNpqd8LTO++8g81mY+bMmfz9739XopOIiIiIiIiIiIiIiIiIiIiIiHQae3t/QW5uLgDXXnutkp1ERERERERERERERERERERERKRTtTvhyek0RaKys7Pb+6tERERERERERERERERERERERES+UrsTngYPHgxAfn5+u4MRERERERERERERERERERERERH5Ku1OeDr33HOxLIunn366I+IRERERERERERERERERERERERE5pHYnPF188cUcffTRvPbaa9x///1UVVV1RFwiIiIiIiIiIiIiIiIiIiIiIiIHsFmWZbXnFzz88MP4fD6eeuopPB4PdrudzMxMEhMTcTqdh76wzcaTTz7ZnkuLiIiIiIiIiIiIiIiIiIiIiEgf0+6Ep5EjR2Kz2TjcX9N8rs1mY9OmTe25tIiIiIiIiIiIiIiIiIiIiIiI9DGHLsF0mKZNm9YRcYiIiIiIiIiIiIiIiIiIiIiIiHytdld4EhERERERERERERERERERERER6Sr2UAcgIiIiIiIiIiIiIiIiIiIiIiJyuJTwJCIiIiIiIiIiIiIiIiIiIiIiPYazvb9g3rx53/hnzz333PZeXkRERERERERERERERERERERE+hCbZVlWe37ByJEjsdls3+hnN23a1J5Li4iIiIiIiIiIiIiIiIiIiIhIH9PuCk8AR5IzFRkZSXJyckdcVkRERERERERERERERERERERE+ph2V3jKz8//yuMej4fKykpWrVrF008/TUVFBffddx9nnHFGey4rIiIiIiIiIiIiIiIiIiIiIiJ9ULsTno5EeXk5F110ESUlJbz88ssMGzasqy4tIiIiIiIiIiIiIiIiIiIiIiK9gL0rL5aYmMi1115LY2Mj//rXv7ry0iIiIiIiIiIiIiIiIiIiIiIi0gt0acITwFFHHQXAkiVLuvrSIiIiIiIiIiIiIiIiIiIiIiLSw3V5wpPP5wOgoqKiqy8tIiIiIiIiIiIiIiIiIiIiIiI9XJcnPL322msAJCcnd/WlRURERERERERERERERERERESkh3O29xcUFBR87Tk+n4/y8nLeffddnnnmGWw2GzNnzmzvpUVERERERERERERERERERKSb8wWC1Hr81Hj8VHt81Hj81LRZ13kDeHwBGv1BGpvX/iCN/gCNPrPtCwQJWhb+oEXgIIt/v23LsrCarm9ZZssCmjb3aWs+8SvPbzpqWa3nsd8x6Tzbfn9GqEOQbqbdCU+zZ88+ovMty8LtdvOjH/2ovZcWERERERERERERERERERGREPEHguyt8lBQ2UBxTaNZqj0U1zRS1LQurvZQ7fGHOlQR6WXanfDUnNl4uLKysrjzzjvJyspq76VFRERERERERERERERERESkk9V7/WwtqmVLYTVbCmvZWVpLXlk9uyvq8QUOP2cgwuUgxu1sWlzEuJ3Eul1EhTuIcDkIdzkId9qbFgfhLjtup4Mwpx2nw4bTbsNus+F0NK3tdux2cNrtOOw2HPbWc+x2sGHDZjPXtkHLttkz+81NNputzXbzWbY2P9OmvWnDtt+5ItJ1bNaRZizt57XXXvvac+x2O5GRkWRlZTF8+PD2XE5EREREREREREREREREREQ6SaM/wIaCalbvqmT17krW7qkkr7yeQ2UWhDns9I93kxrjpl9sOKkxblJiw0mNDSclxk1qbDhJUeFEu524HPau/WNEpNdqd8KTiIiIiIiIiIiIiIiIiIiI9Exef5DVuyv5cnspX24vY/WuSryB4AHnJUeHMyItmhGpsQxNiSY7KZKs5CjSYt047KpuJCJdq91T2omIiIiIiIh0NsuyaPQHqW30U9fop7bRT63HT53XT11jAF8giC8QxBuw8PmD++4Hgi1t/qBF0AKwCAbBwuxbltm2LHOtoAUWEDQHCFrmWNCysKBpRGPoxg+FeuiSRk59tf9cMS3UIYiIiIiIiIh8pZKaRj7aXMQHG4tYmFNGgy+wz/GkqDAmZsYzMTOeCZnxjEmPJSk6PETRiogcqEMTniorK5k3bx5Lly5l79691NfXExERQXp6OpMmTeKcc84hNTW1Iy8pIiIiIiIiPVi9109BZQN7KhrIr2ygqMpDaZ2X8lovZXWNlNV6Ka/3UuPxEwgqzUZERERERERE5JsqrvbwxpoC3lm3l1W7K/cZUJUUFcaMIUnMHJLMjCFJZCdFYrOpapOIdF8dNqXdCy+8wH333YfH4wHMiNiWizTdCMPDw7nhhhu45JJLOuKSIiIdwrIs/MGmkf9NFQD8zZUA2rQ1VwTw+ZsrA7SO8g+2jPpv3Q62VAcw1QP2P7+1moBFMGgdMEr+YHfnQ92wf3DMoI7+ZxGRTtR83wm0uZdYTe0tVUPaVhrZ75hlDu6z3/Y86bkGJESGOgSRThEMWhRUNbCtuJZtRTVsK6pla3Etu8rqqKj3HfHviwxzEB3uJDrcSVS4k8gwB+EuB2EOGy6HvWUJc+6377Bht9uw22zYbea7qs0GNsza3mbb1nwOYLfbsHHw83sy81dJZ7hoWmaoQxARERGRbqq5em2jL4g/GCQQbO0nMmvT/+wPmLaA1XSsaf9g/UVt+5HMNQ7S17TPzx26P6k3di2dOykj1CGIhFRto5/56wuZtzqfhTmltB1PNn5AHCePSmX2qBRG949VgpOI9CgdUuHpP//5D/fff3/LA9GgQYMYMmQIERER1NXVsX37dvLy8vB4PNx55500NjZyxRVXdMSlRaQP8vqDVDX4qGrwUtXgo7Le17Rvtusa/TT4AjR4A9R7A63bPj8N3ubtQMsXSl+g53+DU8KTSMdr9Acoq/VSWe+jssFLVb2Pyqb7TGWDl1qPudd4mu4xDW3WXr+5tzR3WvkCFv6mpMnmDiyRg8m978xQhyDSISrqvKzaXcGqXZWs3FXBmt1V1Db6D3l+jNtJRnwEGfER9I93kxwdTlJUGEnR4SRGhZEUFUaM20VUuIOoMCf2np5pJCIiIWNZFg2+ANUNZnpUT9MzvccXNGt/m21fAG8gSCBw8BfRLfuBfdv3nSZ1/xfKLZEcYnBDa5zAAb9Lutb/fnx0qEMQkW7CsiyqGnyU1npb+qab+6Wb1x7fvv1DzfseX5AGb+t+gy+ge3oXU8KT9FWbC6t5ZnEer63Mp87bOl3dlKwE5k5MZ87oVPrHRYQwQhGR9ml3wtP27dv505/+hGVZTJgwgTvuuIORI0cecN6mTZu44447WL16NQ888ADHHXccgwcPbu/lRaSXsCyL8jovhdUeiqsbKaz2UFjloajaQ2G1h6LqRirrzZfJem/g639hOzntphqA02EjrKkiQPO202HDYbfjsIPdZmsZ/W+3mTHydlvziH8b9oOcY9+nYoA5p7lKQFv7Z9Hv/1pPSfYi7dPoD7CztI7c0noKKhvMUtVAfqWHgsoGSmoaQx3iV7I1VR2x2ZqrjjRV6rAdeL8QEelstY1+vswp5dOtJXy5vYydpXUHnONy2BiUHMWw1BiGpUQzPDWGQclRZCREEOt2hSBqERHpDQJBi9LaRkpq2ixt9isbvFQ3+Kn2+Khu8FGtKVJFROQgqj0+dpXVk1tWx67yeoqqPBTXNFJUbdbFNY14/cFOubbdBk67HYfdhtNuw+FoWttt+7Y3LbBff5CttXprc38R+/QXtZ7fek5rH1LbKrbNfc4H668WkZ7BHwjy7vpCnlqUy7Lcipb2wclRnDcpg7kTMxiYpCrzItI7tDvh6cknnyQQCDBq1CieeuopwsPDD3reqFGjePLJJ7nkkkvYtGkTL774Ir/97W/be3kR6UGq6n3kltWRW1ZHXtOXx93l9eytMklO3sDhf2G02SAm3El8ZBhxES7iI13ERriIi3ARE+7E7XIQGWaWiDAnEa7m7aa1y0G404GreZoTux2X03yBdDlsKtkp0stU1HlZl19llj1VbC2uIa+s/mtfdLgcNuIiwoiPdBHfdK9p3o9umkIpIsyB2+Vovc+4HIQ57Tgddpx2G06Hubc0b7scpqPKZbe3SYrctyNpn44m9u/E0v1JRLqHnOJaFmwq4tMtJSzPKz+gaubgflFMHpjApIHxTMpMYFhqNC6HPUTRiohITxYIWuSV1bG1qIbcsnp2l9ezq7yePRUN5Fc0HFF/QjOn3bbP87zb6cDtshPuan6+t+N2OZoGPtnbvHhu+yJ6v/b9X0bDfi+cW5/x4WAvnFvPZb+fgX1fVouIyJGzLIuSmkY2FFSzcW8124pqyCuvJ6+snvI672H9jphwJ/FRLuIjTL90XFOfUWyEi6jmPqIw87kS0dRP1NwW4Wret+MOcxDutDf1D+nuLiLt5/EFeGnFHh77bDu7yxsAcNhtnDomlcuOzmLG4CT1LYtIr9PuhKclS5Zgs9m49tprD5ns1Cw8PJxrrrmGn/70pyxcuLC9lxaRbqqu0c/mwmq2FNaytaimaamltPbrq6UkR4eRGusmLdZNStM6LS6clFg3SVFNyU0RYUS7nS0diCIi+yuq9rB4RxmLd5SzZEcZOw5SaQTMFEqD+0UzID6C9Hg36fERpDdNqZQeH0FCpEtfAkVE2iiobODNNQW8vrqAjXur9zmWlRTJCcP7cdzwfkzJSiA+MixEUYqISE9W4/Gxdk8Va/dUtfQp5BTX0vgVVTUcdhvJ0WH0iwmnX3S4WceEk9w0NWqs20VshJMYt6tlO8Ll0LO+iEgvV1ztYWluOevzTYLTxoIqSmsPndiUHB1GVlIUAxMj6R/nJiUmnNRYNymx4aTEuOkXE47b5ejCv0BE5OvVNfp5alEe//5iZ8t7uIRIF9+dkc13pg8kLc4d4ghFRDpPuxOeCgsLAZgwYcJhnd98Xn5+fnsvLSLdQIM3wPoC0xG5Pr+KtXsq2VFad8g5yFNjw8lKiiI7KbLly2N6vNt8cYxxE+bUqH8ROXLBoMW6/Co+3FTEgk3FB7yEBxiUHMX4AXGMy4hjZFosw1KjSYkJ10sOEZGvUdvo5/XV+by+qoClueUt7U67jVlDkzlpZArHD+9HdnJUCKMUEZGeyLIsdpXX8+X2MlbmVbB6dyU5JbUH7VNwu+wt06EOTIwkMyGSzMRIMhMjSIt141QVQRGRPq+4xsOSHeUs2lHG4h1l7Cg5cACc3QaD+0Uzun8sI9LM50pWU191dHi7X5mJiHSZRn+A55bs4pGPc1qSOTPiI/jRsYO4aFomkWG6p4lI79fuO53DYbLZGxu/vnJL2/P0clGkZyqv87Ist5zlueUsy61gfX4V/oNMCZUaG86ItFiGp0QzPC2G4akxDE2J1pdGEelQWwprmLc6nzdWF5Bf2dDSbrPBmPRYjh6UxNGDk5iWnUhcpCuEkYqI9Dw5xbU8vSiXV1bmU9voB8z9dXp2InMnZnD62DQSolTFSUREjkxJTSOfbyvhy+1lLNpets9zfLMBCRFMyIxnVFN/woi0GDITIjXlj4iI7CMQtFiRV8F76wv5dGsx2/dLcLLZYGRaLJMGxjO6fyxj0mMZmRZLRJiqNHWKgB/8DeBrWvyeg699DU3neSDQaH4u6IOAD4J+swR8TW37HQv4wAqAFWyzWBDcv22/41d+Eep/HZEOEwhavLJyDw8u2NbyLJ2dFMk1s4dx9oR0XBoIICJ9SLszD7Kysti8eTOff/45F1544dee//nnnwOQmZnZ3kuLSBfw+AIs2VnO51tL+HxbKVuKag44JyUmnPED4lsqp4zNiKNfzFdPcSki8k3VNfp5bVU+zy3ZtU8lp6gwB8cN78fsUamcMKIfydG6D4mIHKlA0GLBpiKeWpTLwpyylvbByVFcPD2Tsyek0z8uIoQRiohIT2NZFjnFtXywqYgFG4tYtbtynwpOLoeNSQMTmJ6dyMTMeCZkxqtPQUREDskXCLJ4Rxnvri/k/Q1FLdM3gUlwGpUWy9GDkzh6cCLTByVqqu0jYVnQWAN1JVBfDp4q8FQ2rQ+xNFa3bvs9of4LRHq9xTvKuOPNjWxq6hdPi3VzzexhXDh1gBKdRKRPanfC03HHHcemTZt48MEHOeaYY+jfv/8hz927dy8PPvggNpuN448/vr2XFpFOsru8nvkbCvl0awlLdpbj9Qf3OT4sJZppgxKZlp3A1KxEBiREqGqbiHS63NI6/vtlLq+s2ENNU6URl8PGCSNSOG9SBieNTMHt0gg9EZFvwhcI8vrqAh79OIcdpWZUtN0Gs0elcvmMLGYNSVZVDREROSI7SmqZt7qAN9cUsLN034ob4zLiOGZYMjOHJDE1K1GVNkRE5CtZlqnk9MKy3by/sYiqBl/LsVi3k5NHp3LK6FSOHpykBKdD8dZBVT5U72laF5jt2mKz1JVCXXHHJS053WZxRTStI8HlBmdE07rpmCMcHE6wu8DhAruzae3ar73Nvt0JNnvTYmvdtjvatO93XKSH21NRz73vbObtdXsBc++7+qRhfHdGlvrERaRPs1mWdeBcVEegrKyM008/nZqaGhISErjqqqs49dRTSUpK2uec9957j0ceeYTy8nKio6N5//33SUxMbPcfICLtZ1kWG/dW8/6GIuZvKGRz4b5VnNLj3Bw7rB/HDk9m5pBkEjV1iYh0oW1FNTzycQ5vrCmgeQbN7KRIvjsjm/MnZWg6JRGRdmj0B3hlRT5//zSH3eWmDHpchIvvHDWQS48ayICEyBBHKCIiPUlpbSNvrC7g9dX5rNlT1dIe5rAzc2gSc0anMntkKmlx7hBGKSIiPUVVg495TVW+2848kBwdxpzRaZw+No2jBycR5lRCC8Eg1OyF8h1QsRPKd7ZuV+SZSk2HyxUFUUngjgd33OEvYdGtSUx2/W8i0hG8/iCPfbadv32UQ6M/iN0G3zlqIL+cM0Lv6kRE6ICEJ4BPPvmEa665Bq/X21LlJTY2lsjISOrr66muNmX1LMvC6XTyyCOPqMKTSDewvaSW11flM291AbvK61vaHXYbRw1K5ORRqRw3vB9D+kWpgpOIdLntJbX86f0tvLu+sGXKixNG9ON7swZx7FBVGhERaQ9fIMjzy3bz6Mc57K0yI3iTo8P44bGDuezoLKLD210MWERE+gjLsli6s5xnluzivfV78QXMw7vDbuPYYcmcOzGDk0en6rNFOo5lQTAAQR8EfBD0myXgAytoFqymbatp2b89eJB268D27Fkh/mNF+h7Lslizp4rnluTxxpoCPD4z+4DbZeecCelcMHkAU7MTcfTVfqFgEKp2Q8lmKN7UtN4IJVvB3/DVPxsWA3EZEJvRuo5OhegUiEqB6H4Q1Q/CorrmbxGRr7Q8t5ybXlvH1qJaAI4enMitZ41hdHpsiCMTEek+OiThCWDVqlXcfffdbNiw4ZDnjB49mttvv53x48d3xCVF5BsoqWnkzTUFzFudz9o2oy3dLjvHDevHqWPSOGlkiiqmiEjIlNU28uCH23h2yS4CTSWdTh+bxs9PHMrYjLgQRyci0rNZlsX8DUX88b3NLVPXpcaG85PjhnDJ9IGaUkhERA5bbaOfl5fv5tklu9hWXNvSPmFAHOdPHsCZ4/uTHB0ewgilS/kbwVMNjdXQWNNmabPv94Cv4RBrj3lR7/OY/bZJTPtsN+13ldurvv4cEekQlmXx6dYSHvpwGyt3Vba0j0iN4TtHDeTcSRnERbhCF2AoBINQlgMFq1qXovXgrT34+XYnxA+EhEGQOBgSB5nthGyIGwBuJUmI9ATVHh9/eHczzy7ZBUBSVBi/O2s0cyemqziBiMh+OizhqdmmTZtYunQphYWF1NbWEhkZSXp6OlOnTmXMmDEdeSkROUzBoMUXOaU8t2QXCzYV4Q+2jrY8blgy507KYM7oVCLDNNpSRELHHwjyn4U7eejDHGobTQf2yaNSuP7UkYxIiwlxdCIiPd+KvHLueWczK/IqANNhdvVJQ7l4+kDcLiU6iYjI4Smu8fDkl7k8vSiPao95bo8MczB3YgaXHjVQgxR6C18DVBeYpa4Y6sqgvgzqS6GutGm7zGx7KiHgDXXEYHOYl/02G9jsrQu2Nm0HO2Zvc8y277Grl4f4jxLp/SzL4qPNxTz04baW6VDDnHbOGtef7xw1kClZCX3nBX99OexaDLu+hPxVsHf1wZOb7C5IHgb9RkLKaEgZCf1GmcQmh/r4RXqyT7eW8NtX1rZU475o6gBuOmMU8ZEqUiAicjAdnvAkIt1HSU0jL63YzfNLd+8zZd2EzHjOn5Sh0ZYi0m2s3l3Jja+uY9NeMw3u2IxYbjpjFDOHJIc4MhGRnm93eT33vLOJd9cXAqay54+OHcyPjxtMjLuPjZAWEZFvbEdJLf/6fAevrMjHGzDTCw1OjuKKWdmcOymDWH2m9ByWZV6qV+yE8h1QkQtVe0xyU81eqM6Hhopv9rvDoiE8pmmJbbMdA043uCKa1m5wRpi1K3LfY85w8zLf4TRruxMcTeuDbrvA7jDJSiLSYwSDFh9sKuKhD7exocD0B7lddr57dBY/Om4wKTHuEEfYBaryYdciyFsIeYugZNOB5zgjoP94SJ9klv4TIGmouf+JSK9R2+jn929v4n9LTVWn7KRI7j1/PDOGJIU4MhGR7k2p3iK90ObCah7/fCdvrC5o6YSMcTs5f1IGlxw1kJFpKl0rIt1DvdfPH9/bwpOLcrEsiItwcdMZI7lwSiZ2uzqrRUTaw+ML8M9Pd/DoJzk0+oPYbXDR1EyumzOc1Ng+8PJAREQ6RF5ZHQ9+uI15q/JpKhjN5IHx/OT4IcwZlarn9u4s4DcJTcUboXgTlG4x++W50HgYU7W5IiE2HaJTITLJLFHJEJnctN3UFpHQmtxkV9VIEfl6X24v5e63NrGxaeBbZJiDy2dk88NjB/XuAbreepPclLMAcj6Esm0HnpM8HAbOgMzpkD7Z7Ktqk0ivtmRHGb96aQ17KhoAuGJmNr85bYRmZREROQydcqcMBAK8+uqrvPTSS+Tm5mKz2Rg0aBBnnHEGF198MWFhKrsn0tEsy+KzbaU8/vkOPt9W2tI+ITOeS48ayFnj++vhqLME/OBvAJ8Hgj4I+CDoN+XcA76mNn/T2ttmu/m8pnOsYJvF2m//YEubc068KdT/CiJHbPXuSq57YTU7S+sAOH9SBjedOap3d2yJiHQBy7JYsKmYO9/awO5y01k2Y3ASt58zRlOEiojIYdtdXs/DH+Xw8so9BJoynWaPTOHKE4YwNTsxxNHJATzVZuqj/JVQtKE1wemrppqLSYfEQZAwCOIGmOSm2IymdTq441Q1SUQ6VH5lA/e8vYm31+0FIDrcyRUzs/n+MYNIjOqF740sC0q3wrb3TYJT3pcQaGw9brND2jjImmWSnAbOgOh+oYtXRLqUPxDkoY9yePijbQQtyIiP4P4Lx2vWAxGRI/CNprT78ssveeyxx9iwYQMRERHMmTOHq666ioSEBLxeL1deeSVffvklYDrbgZY5ljMzM3n88ccZOHBgB/4ZIn1XIGjx9rq9PPJRDluKagCw2+D0sf35wbGDmDwwIcQRdkPBIHgqTXn2xmrTKXjQdZVZe+vA19BmqQe/p3U/6Av1XwS3H8bITJFuwh8I8vDHOfztoxwCQYv+cW7++K3xHDtMHToiIu21u7yeW19fz8dbSgBIi3Vzy1mjOHNc/5bvZCIiIl+los7LQx9t45nFefgCpl/vhBH9uO7k4UzIjA9tcGIEfLB3LRSshPwVJsmpdCtwkG5eVyT0Gwkpo6HfCEgaYhKcErIhLLKrIxeRPsrjC/DYZ6b6rMdnqs9ednQW1508nITeluhkWSYBdeMbsOnNA6s4xWXCkJNg6GwYdDxExIciShEJsYLKBn7x/GqW5pYDcMHkAdwxdwzR4SpcICJyJI444emJJ57g/vvvx7KsfZKZsrOzee6553jsscd44oknAHC73QwaNAi73c6OHTtoaDCji7Ozs3njjTdU6UmkHfyBIG+t3cvfPtrG9hJTHSUqzMG3pw3ke7OyyUzsY51WlmWSmCp3QU0R1JUcfKktgfpSU1mpM9idYHeZOdQdrtZtu7OpLax12+4y5Yibz7E5zMhJm/1rloOcc+YDnfP3iHSwomoPVz23kmW5FQCcMyGdu+aOJS7SFeLIRER6Nn8gyBMLc/nzB1tp8AVwOWz88NjBXHXiUKLUWSYiIoeh0R/g6UV5PPThNqo95jvzMUOTuW7OcKZkaTBVSPm9Jrkp93PIXQi7l4Kv7sDz4gZCxiRIGw+pY0yiU3wW2O1dH7OICGZA/PwNRdz99saWqZqmD0rk9rPHMDo9NsTRdaBgEHYvNglOm96Eqt2txxxhkH0sDD3ZJDklD1f1PJE+7v0NhVz/8lqqGnxEhTn4/XnjOHdSRqjDEhHpkY4o4Wnz5s1ccMEFBAIBIiIiOOqoo3C5XCxdupTq6mpmz57NwoUL8Xg8XHrppVxzzTXExpqHVo/Hw7/+9S8eeeQRbDYbd999NxdccEGn/WEivVUgaDFvVT4Pf5zTMg1UXISLHxwziP+bmU1cRC9OGmioNAlNLUvevvuN1Uf2+8KiITwW3LFfvQ6LNqMenRHgarMcsO/Wl1WRr/Dl9lKu+d8qSmu9xIQ7ufu8scydqC9yIiLttT6/ihtfXce6fFPx8ejBifz+vHEM6Rcd4shERKQnsCyLd9cXct+7m9lVXg/AyLQYbjlzNMcM03QaIWFZULoNcj6AbR/ArsXgb9j3nIgEyJgKGVMgYzKkT9Y0SCLSrRRXe7jptXUs2FQMQP84NzedMYqzxvei6rPFm2Ht87D2Jaje09ruioRhc2DUOTDsFNPPLCJ9nscX4J53NvHUojwAxmXE8bdLJpGdHBXiyEREeq4jGur78ssvEwgEGDp0KP/9739JTjadHtXV1Vx++eV8+OGHAJxyyinccsst+/ys2+3m6quvprS0lBdeeIEFCxYo4UnkCFiWxYJNxfzxvc1sK64FID7SxY+OHczlM7KIcfeSRKdgECpzoWQrlG5pXZduNVPMfZ3IZIhNh6h+Zonu17odlQJRyU3byeAM7/Q/R0TM/evvn27ngflbCFrm5ck/LpuiL3IiIu3U4A3w1w+38vjnOwkELWLdTm4+cxQXTc3sPS8QRESkU20urObWeRtaptJIiQnn16eM4IIpA3DY9VnSpXwNsOPTpiSn983ArrYikyBrlqkSkj0L+o1S5SYR6bbeWlvALfPWU1nvI8xh58fHDeZnJw4hMqwXVJ+tLYZ1L5tEp71rWtvDY2HEGTDqbFPJyRURuhhFpNvJKa7lqudWsrmwBoAfHTuI608dSZhTz3MiIu1xRE+XS5YswWazcdVVV7UkOwHExsZy9dVX8/Of/xybzcb5559/yN9xwQUX8MILL7B169ZvHrVIH7M8t5z73t3M8jwzBVRchIufHj+E787I6tnz+fq9ULQeCte1LkXrwVt76J+JTIaELIgf2GZp2o/LNJWYRKTb8PgCXP/yWt5cUwDAt6YM4K65Y4kIc4Q4MhGRnm1hTik3vbaOvDJTiePMcf257ZzRpMS4QxyZiIj0BDUeH39dsI3/fplLIGjhdtn58XFD+MlxgzUValfy1pnkpo1vwNb5+05T5wiDrJkwdA4MOQlSRqmqtIh0exV1Xn73+nreWrsXgDHpsfz5oomMSIsJcWTtFAyYinsrnjBrK2Da7U5zn57wbRh+Orj0fUxEDvTS8t3c+voGGnwBkqLCeOCiCZw4IiXUYYmI9ApH1INRUlICwJgxYw44NmnSpJbt4cOHH/J3DBw4EIDy8vIjubRIn7SjpJZ7393MBxuLAHC77Hx/1iB+cvyQnjd1nWVBRS7kr4A9y2HPMihcCwHvgec6wiF5mJnPvN+I1nVCNoSpIoxIT1Fc4+HHT61g9e5KnHYbd8wdw3emD1TVERGRdqis9/L7tzfx0gozXUL/ODd3zR3LyaNTQxyZiIj0BJZl8ebavdz91kaKaxoBOH1sGr87azTp8apE0SV8DbDlHdjwGmxbsO9UdbEDYPipZhqk7GMhXNPTikjP8dHmIm54ZR0lNY047DZ+fuJQrjpxaM+uXlJTCCufhpVPQtXu1vaMKTD+Yhh7vplJQETkIDy+ALe/sYHnl5n7x6yhSfzloomkxCo5UkSkoxxRwlNNjSmzFxcXd8CxmJiYg27vLywsDIDGxsYjubRIn1Lj8fG3j3J4YuFOfAELuw2+PS2Ta2cPJy2uhzwIWRaUboO8LyB3IeQthJq9B54XkQD9J0DaOEgbb9ZJw8ChEaUiPdmmvdX84L/LKKjyEBfh4u+XTWbmEHUAiYh8U80vqO98cwOltV5sNvju0Vlcf+qI3jO1sYiIdKrc0jpunreOhTllAGQlRXLHOWM4QaPLO59lwa7FsOY52DAPGqtbjyVkw6hzYPS5kDFZVZxEpMdp8JoX+i8sNy/0h/SL4s8XTWRCZnxoA/umLAt2fgrL/wOb34ag37RHJMDES2HKFWawrojIV9hTUc/Pnl3J2j1V2Gxw3cnD+fmJQzVttHRPlmUGZvjqTRVaX33Tdn2btgYINELAZ4pZBLz7bvsP0hb0gxU0lRKtQJvt4H7bhzrWtt0y+7/cGOp/LelmjiijIBAIYLPZcLkO7FBv2+ZwfP00NZZlHcmlRfqEYNDilZV7+MN7WyitNUmBJ47ox81njmJoSg8o+1tbDNs/gpwPYccnUFe873G7yyQ0DZgGA6aakTCJg9WZJ9LLLNpexo+fWk5No5/ByVH8+4ppDEpWdTYRkW8qv7KB381bz0ebzbPVsJRo7rtgHFOyEkMcmYiI9ATBoMV/v8zlj/M34/EFCXPa+fkJQ/nJ8YNxuzTVdKeq2gOrnoE1/zNVr5vFZcK4C2HMuWbwl/pFRKSH2llax5XPrGBzYQ02G/xg1iB+feqInvn54m+EtS/CokegZFNre+ZRMPX7MHouuFQNUUS+3hfbSrn6fyupqPcRH+niwYsncfzwfqEOS3q7gA/qSsy72rpSqC8DTxV4Ks26oXLf7caq1oQmX31oYxdpB5VQEekm1u6p5Hevb2DN7koABidH8buzRnPiyG480jIYNFPTbX0PchaYKeracoRD5nTImgXZs0yik74UivRq76zbyy+eX403EGT6oET+9d2pxEWq8oiIyDcRCFo8vSiX++dvoc4bIMxh5+cnDuWnJwwm3NkDXyCIiEiX21lax29eXsOy3AoAZgxO4r4LxpGVpAEJnSYYhB0fw7J/w9Z3zYhkgLBoU8VpwsWmn8Teg6d4EhEB5m8o5NcvrqGm0U9ydDgPXTKxZ1b3ri839+ylj7UO4HVFwcRLYMr3IG1saOMTkR7Dsiz+/ul2Hpi/haAFYzNi+fulU8hMjAx1aNKTBYMmkalqD1TtalrvMdOu1pWaz67aYpPM1BGcEeZdblgUuCIhLNKsXZHgDAdHWNPiOoxtJ9gcYLOD3dFm227WNkdTu32/Y1/xMyL7UcKTSIjVeHz86f2tPLUol6AF0eFOrpk9lCtmDuqe85v7G2HnZ7D5Ldj8zoFVnNLGw9CTYchJTQlOPWQKPhFpt6cX53Hr6+uxLDh1TCoPXjypZ47oExHpBjYWVHPTa+tY3ZQMPzUrgfsuGNczqn6KiEjIBZqqOt3fVNUpKszBjWeM4jvTB2LXNBqdo74cVj9rXppX7Gxtzz4WJl8OI880Lw1ERHo4fyDI/e9v4Z+f7gBgWnYCD39nMqmxPawfuGw7LHoYVv8P/A2mLSYdjv4pTP4/iIgPaXgi0rNUe3z8+sU1vL+xCICLpg7gzrlj1T8uh8fvNRVhS7eapWx7m+SmfDOV3OGwOSAqGaJSIDLRfJa545vWcWbbHWf2w+PM95O2CU2uSA3MkB5HCU8iIWJZFu+uL+SONzdQVG0+qM6blMGNZ4wkJaabfTkM+MxUdetehi3vgrem9Vh4LAybA8NOMUlO0d24IpWIdJpHP8nhj+9tAeA7Rw3krrljNR+59GyWZZJ8A41N8483mv22bUFf61ziwUCbbX/rfOMt21/RbllA03TPx/4qpH+2hF6918+DC7bx+Bc7CQQtosOd3HD6SC7VC2oRETlMO0pq+c3La1meZ6o6zRqaxH3nj9fI8s5SvhMWP2qmrmueCiI8FiZcYqZAShkZ2vhERDpQcY2Hq59bxZKd5QD88JhB3HD6SFyOHvRytHgzfP4ArH+ltQpf2niYeTWMOc9UphAROQJbi2r46dMr2FFaR5jDzh1zx3DJ9IGhDku6I58HijdC0Yam5KZtULbNfKewAl/xgzaI6Q/xmRA3wCwx/SGqn3kvG9XPJDlFJChhSfqcb5TwdNttt+FwHDoj9auOBwJf9R+rSN+QX9nA7+at56PNpjpSdlIkd587jmOGdaOSv8Eg7FoE616Cja9DQ3nrseg0MzJx5JlmpKIzLHRxikhIWZbFXz7YykMf5QBwzUlDuW7OcGw2vZSXLmRZ0FhtRtU3VJjPrIZK8NaCtw4aa1u3vXVN2232ffVtkpq84PeYZKZQUMJTn/bx5mJumbee/EozuviMcWncdvaYnjdSWkREQiIQtHhi4U7un7+FRr+p6nTTmaaqk57PO0H+Clj4EGx6o/WFeeo4mP5DGHehqjmJSK+zIq+CK59ZQXFNI9HhTv74rfGcMa5/qMM6fIXr4LP7YeMbtAw6GnYKzLwGso8BfVaKyDfw5poCfvPyWhp8AdLj3Pz9silMyIwPdVjSHXjroWg97F0De1dDwRoo2WQGwh6MKwqSh0LycEgaBglZTclNmRCbroRckUOwWZZlHe7JI0eO7JAOEsuysNlsbNq0qd2/S6QnsSyL55bu4p63N1HnDeBy2Ljy+CH87MSh3aesZeUuWPUsrH7OlEtsFpUCY8+HsRdAxlRlCIsIlmVx77ubeewzU8L8htNGcuUJQ0IclfQajTVmHvKaQqgtalo3zUveUHFgctNXjoDpAHYXON0mydcRbtZ2l5lH3O5snVPc7myde7x5jvF92u37nmNzNHWq2sAGzH2kc/8O6ZaKqj3c+eZG3l63F4CM+AjunDuG2aNSQxyZSDdiWabyrN8DAe9BqvA1rz0Htu1TYa9tZT7/4bU1V+mzrNaqfC1dKfu3NbV/6z+h+XeSPmt7U1WnFU1VnY4Zmsx9F4xjQIKqOnUoy4Idn8BnD0DeF63tQ2bDrGtg0PF6YS4ivdIbawr49Utr8PqDDE+N5u+XTWFIv+hQh3V48leaRKct77S2jTwLjrse0ieGLCwR6dl8gSD3vbuZf39hpjKeNTSJhy6eRFJ0eIgjk5CwLKjMg9yFkPelGRxRuqV1YERbEYmQNg76jTDJTcnDTIJTbLq+S4h8A0dc4ekI8qNEpI3d5fXc8MpavtxeBsDUrATuu2AcQ1NiQhwZ5mXB5rdg5dOm4665kz48FkadA+O+ZSo5OTQLpogYlmVx51sbeWJhLgC3nz2aK2YNCm1Q0nNYlkliqtx18KW6AHx1R/57XZGmbG9E0/zk4TEQFt00F3nUvtvhMa3bzghwhpvFEda0Dm9NbnKEKdFXOkUwaPHskjz++N4Wahr9OOw2fnDMIH5x8jAiw/TcJb1IwGeSUz2VTcmqzUvTvrfWJLruU4nvIFX5DjUKsjtSwpN0kUDQ4j9f7OSB901Vp+hwJzefOYqLp2WqqlNHak50+uQ+2L3YtNmdMPZbZgqktLEhDU9EpLNYlsXDH+Xwpw+2AjBndCp//fZEosJ7wPeVoo3w0d2w5e2mBpuZsu64X0PqmJCGJiI9W3GNh6ueXcXSXDMzys9OGMKvThmBw67n7z7Dssx0dHkLm5YvoTr/wPOiUkxybf8J0L9pHTdAiU0iHeiInko3b97cWXGI9FrBoMUzS/K4793N1HsDuF12fnPqSP5vZnboH34qd8Py/8DKJ6G+rLV90HEw6XIYdRa4IkIXn4h0S5Zlcd97m1uSne49f5zmJJeD89ZBWY758tc8H3npNtPmq//6nw+LgZhUM5Vq8zq6X1NCUwJEJrZJcEoAl6b9kp5jRV45t7+xkXX5VQBMyIznnvPGMiY9LsSRiRwBT5VJVG2uxldbBLXFbdZNS2NVx1/b7tovUfUgCavN7Q5XayW+fSrv7dd2sAp9tqZz7XZzPrY2lfmav8/t36aOS+kaOcW1XP/yGlbtqgTg2GHJ3HfBeDLi9T2+w1gW7Pi4KdFpiWlzhMPU75kpkOIyQhufiEgn8vqD3PjqOl5ZuQeAHx07iN+ePir0fdpfp3wnfHIvrH0RsMwz3LiLzBTy/YaHOjoR6eGW55bzs2dXtkzv+cCFEzhtbFqow5KuUFsC296HnA8g9wuoK9n3uN0FGZMhayZkHgXpkyBG/98Q6Ww9IA1fpOfKr2zg1y+uYdEOk0w0fVAif7xgPNnJUaELyrIg93NY+hhsfru1nGJMOkz8Dky6DBJVpUVEDu2vC7bxz0/NNHa/P2+skp3EfLZU7YHCdU3LWrOuzDv0z9jsEJsB8QPNPOTxA1uXuAHmy2BYCD8vRTrJ3qoG7nt3M6+vLgAgJtzJr08dwWVHZ3X/FwfS9/gaTJJq+U6o2t1UiW93a0W+I01kcseBO74pWbV5iTeVZfepyNemKl94dOu2K8JML+oIV+U96dMCQYvHP9/Bnz7YitcfJCbcyS1njeKiqarq1KF2LYEFt8GuRWbf6YYp34NZ10Js/9DGJiLSySrrvfzk6RUs2VmOw27jjnPGcNnRWaEO66tV7zVT1618srUy6Oi5cOLNZtogEZF2sCyLJ7/M5e63N+EPWgxLieaf353C4J4yvaccOcuCvWtMktPW98wUqbSZCcvphgHTTIJT1iyzHaYpxUW6mhKeRDqBZVm8tiqf217fQE2jnwiXgxvPGMllR2VhD9WLLL8X1r8CX/4Nije0tmcfC9N/DCPO0JR1IvK1Hv0khwc/3AbArWeN5tKjunlnl3SOmiLYs9SMci9YbRKcPId46R2ZZOYgTx7atG6alzw+y1TgEOkjPL4Aj3++g0c+3k6DL4DNBt+emsmvThlBv5jwUIcnfV1dKZRuNUvJ1tbtyl3s05l3MBGJEJsO0alNS8qB66h+JtnJ7uiSP0ekN8spruHXL61l9e5KAI4b3o/7zh9Huqo6dZySrfDhHbD5LbPvdMPU75tEJ43QFpE+ILe0ju//dxk7SuuIDnfyyKWTOX54v1CHdWieKvjiL7D4H+BvMG1DZsPs35nqGiIi7VTv9XPTq+uY1zR47azx/fnDBeN7xvSecmR8DbD9I9g63yQ61ezd93j/CTD8NBh8AmRMMZWlRSSkdCcW6WAVdV5unreOd9YVAjB5YDx/vmhi6Ko6earNqJZFj0KNeRjDFQUTLobpP4KUUaGJS0R6nH9/sZM/vrcFgBtOG8n3j1E1uD4h4DcJTXuWwe6lJtGpcteB59md0G8UpI2DtLFmnTIGopK6PmaRbsQfCPLqqnweXLCN/ErT+T41K4Hbzh7DuAGavk66WHNFvr2rzSjFgtVme/8y7G254yFpSJsqfJkmaTU+02yHazSrSFfwB4I8/sVO/tymqtPvzhrNhVMHqKpTR6nea6ZAWvW0qYZts5sq2CfcaBI7RUT6gLV7KrniiWWU13nJiI/g31dMZWRabKjDOriAD1b819y7680MC2QeBbNvhexjQhqaiPQeuaV1/PSZFWwurMFht3HTGaP4/qxsPYP3JgE/7PgE1r8Mm94Cb03rMVcUDDkRhp1iFlV6Fel2lPAk0oE+2VLM9S+vpaSmEafdxnVzhvOT4wbjdIRguoXaElj8CCz7T+tUE9GpcPSVpgR7RHzXxyQiPdbTi/O4662NAPzi5GFcecKQEEckncayoGSz+ZK341PIWwiN1fudZIOU0ZA5HQZMhbTxpjy8RrSItLAsi3fXF/Kn97ewvaQOgP5xbn57+kjOmZCujjHpGnVlsHsx5K9oTW5qfhm0v7iB0G94UyW+NktUMuj/ryIhta2ohl+/vJY1TVWdjh/ej/suGEf/OFV16hC+Blj4kKkO0lwZZMSZcPJtmgJJRPqUL7eX8qMnl1PnDTAuI45/XzGVlBh3qMM6kGWZqYXe/x2UmSrkJA2DOXfCiNP17CoiHebttXu54ZW11Db6SY4O55HvTOKowRrc2SsEg2Zg77qXYMM8qC9tPRY7AEaeCcNPgaxjwNUNPwtFpIUSnkQ6gNcf5IH3t/DYZzsAGJoSzV+/PZGxGSEYtV9TBF8+BMv/A75605Y8HGZeA+Mv0stoETliLy7fze/mrQfgp8cP4drZw0IckXS46r2w/UOT4LTzU6gt2ve4O87MQZ55lFlnTAF3Nx3hKRJilmXx+bZS7p+/hXX5Juk8IdLFz04YyndnZOF2aUov6UTlO2HXoqZlsZmWbn/NFfnSJ0D/iWZJHQ1hIapIKyKH5A8EeezzHfz1g214A0Fi3E1VnaaoqlOHsCzY+Lp5YV7VVME08yjzwnzg0aGNTUSki83fUMjV/1uF1x9k5pAkHrt8KtHdcaqmgtXw/i2Q+7nZj0wylfimXAEOVygjE5FepNEf4J63N/HkojwApmcn8rfvTCI1VokvPV7xJljzP1j/KlTtbm2PTIIx58G4C2HAdLCHoJCFiHwj3fCJVaRn2VVWz9X/W8maPeaF1uUzsrjpjFFd/zKrphAWPmgSnfwe05Y+GY673swnqw9nEfkG3lhTwA2vrAXge7OyueG0EXq50htYFhRtgC3vwpZ3oGDlvsedEeYlz+DjzXzkaePBriQNka/iDwR5b0Mh//x0R0uiU1SYgx8cO5gfHTuIGLc636UT1JWZRNUdn5ilMu/Ac/qNNMmq6ZOakpvGaHSiSA+wtaiG619a09LXcOKIftxzvqo6dZiiDfDuDa0vzGMHwCl3wpjzVRlERPqcl5bv5oZX1hK04NQxqTx48aTuN1CjtgQ+vANWPQNY4Ag3Mxkc+0szSEtEpIPsLq/n58+tZG3Tc/iVJwzhV3OGh2YmF+kYPo8Z6LDiCTNArFlYNIw6G8Z+y/SDK3FWpEdSwpNIO7yxpoCbXl1HbaOfuAgXf/zWeE4dk9a1QdSXwxd/hqX/ak10ypgKJ/wWhp6sjjoR+cY+3VrCL19YjWXBd44ayK1njVayU08W8EHuF01JTu+2jmIHwAYZk2HwiSbBKXO6KgKKHCaPL8BLy3fzr893sqvcVNd0u+x8Z3oWPz9xCEnR+m9JOlAwCAWrYOu7sO192LsWsFqP250msWngDMiaaSqVRCaGLFwROXJef5C/f7Kdhz/ehi9gEeN2ctvZY7hgcoaexTtCfTl8fA8s/zdYQXC6Yda1MOsXEBYZ6uhERLrc45/v4O63NwFw0dQB3HPeuO71Uj/gg6WPwSf3QWO1aRv7LZh9KyRkhTY2Eel13t9QyK9fWkO1x098pIu/XDSRE0emhDos+aZKc0yS0+pnoaHCtNkcpkjE+Itg+Kng0oASkZ5OCU8i30C918/tb2zgxeV7AJiWncBfL55ERnwXfjA21sCiR+HLv4G3xrRlHgXH3wBDTlKik4i0y6pdFVz5zAr8QYtzJqRz99yxesHSEwWDkLcQ1r9iRrE0lLcec0bAkBNhxOkw7FSISQ1dnCI9UG5pHS8s382Ly3ZTVucFzNR1l8/I5v9mZpMYFRbiCKXX8NbB9o9g63uw9X2oK973eMro1oTVrJkQHh2SMEWk/dbtqeL6l9ewudB8xz95VAp3nzuOtDhVZWs3y4K1L8L8m6C+1LSNngtz7tILcxHpkyzL4oH3t/DIx9sB+PFxg7nx9JHdq+8n50N470Yo3WL2+0+A0/+oaUdFpMP5AkH+8O5mHv9iJwCTBsbz8Hcmd+07P+kYfi9sfsvMhtNczRVMRdcp/weTLoPY9NDFJyIdTglPIkdo095qrnpuJdtL6rDZ4OoTh3LN7GFdN/LF32g+qD97oLWTLm0czL5NFZ1EpEPkFNfw/f8uo94b4NhhyTxw4QTsdt1begzLMlPUrXsFNrwKNXtbj0X1MwlOI86AQcdrFLvIEfL4AszfUMj/lu5i8Y7WBMKM+Ah+dOwgLpqWSWSYvmJJB2ishW3zYcM82PYB+Btaj4XFwNDZZkTikJOUsCrSC3h8Af66YBv/+nwHgaBFYlQYt509mnMmpHevF889VWkOvP1LMwUomKk+z7gfBh0X2rhERELEsixuf2MDTy4y0yH/5rQRXHn8kO7zmVO+E+bfDFveNvuRyaai06TLwN7NptoTkR6voLKBq55bycpdlQD88JhB/Oa0kYQ5u1G1O/l6DRXm3emSf0JtUVOjDYadAlO/D8Pm6DNEpJdSb7zIYbIsi2cW53HX25vw+oOkxobzl29PZOaQ5K4KADbOgwW3Q0WuaUscAifdDKPPA7sevkSk/QoqG7j830upqPcxITOef1w2RV/ueoqqPbDqWVjzP6jY2drujoNR58DYCyD7WHDo8U/kSHj9QRbvKOO9DYW8vXYvVQ0+wOSYHz+8H9+emsmc0anda9oH6Zl8DWbK0Q2vHZjkFJ9lklVHnAYDZ4JTFcREeotlueXc8PJadpTWAXD2hHRuP3u0pkTtCP5G+OKv8PmfINBopq87/jcw42rdR0WkzwoGLW55fT3PLdmFzQZ3nzuWS4/qJpXufB5Y+CB88Wfwe8x0zdN/bGY0iIgPdXQi0gu9vXYvN766lmqPnxi3kwcunMCpY9JCHZYcicpdZjaclU+Bz3ynIjoNJl9ulvjM0MYnIp1Ob7xEDkNVvY/fvLKG+RtMVvCJI/rxwIUTuq4DcvcyeP9m2L3E7EenwYk3wsTL9OJaRDpMRZ2Xy/+zlIIqD4P7RfHEFdOICtc9plvze2Hru+YLXc6HgGXaXZGmktPYb5kqIE69MBM5Eg3eAJ9tK2H++kIWbCqi2uNvOZYe5+aiaZlcODVTpc2l/YJB2L3YJKtumAeN1a3HEgbBmHNh9Llm+o7uMuJeRDpEVYOPB+Zv4ZkleVgWpMSE8/vzxjFntKq2dYjcL+DNX0DZNrM/ZDac+SdIHBTSsEREQikQtLjx1bW8uHwPNhvc/60JfGvKgFCHZWz7AN65vnUA16DjzfR1KSNDG5eI9Eq1jX5ue30Dr6zcA8CEAXE8/J3JZCaqGn6PsXcNLHzIDBqzAqYtZQzMusYM/HW4QhufiHQZvcUU+Rprdlfys2dXkl/ZgMth44bTRvKDYwZ1TYnfyl3wwW1mSiIwL7BnXQszr4awqM6/voj0GfVeP99/chk5xbWkxbp5+gdHkRilUc/dVskWk+S05vnW6U3BVHCafDmMPFOfEyJHwOMLsDKvgsU7y1m8o4zVuyrxBoItx5OjwzhlTBqnjUlj1tBkHJrmU9qrIg9WP2vu45V5re1xmaZjbsx5SnIS6aUsy+KNNQXc9dYmSmsbAbho6gBuPnM0cRHqlG+3xhr44FYznQVAVAqcfh+MOV/3VBHp0wJBi+tfWsOrq/Kx2+Av357I3IkZoQ7L9H+/dyNsfsvsx/SHU+8xz8O6b4tIJ1iRV8F1L6xmV3k9dhv8/MShXDN7GC5V7u7+LAu2f2SqATZPVw0w+ATz3nTIbH12iPRBSngSOYSWKeze2oQ3ECQrKZKHL5nMuAFxnX9xX4PJTP7iL01TWdhg4qVw0i0Q27/zry8ifYovEOTKZ1ayalclcREunvrBdFUt6Y6CAdjyjpmHPPfz1vboNJh0KUy6DBIHhy4+kR7C4wuwpbCGzYXVbNpbw/r8KtbuqdonwQkgIz6C08amcdrYNCYPTFCSk7RfwAdb34PlT5gOuuaqfGExMGYujL8YsmZpqmqRXmx7SS23vr6ehTllAAzuF8Xdc8cyc2hyiCPrJXI+hDevhardZn/K9+Dk2zUNkoj0ef5AkF++uIY31hTgsNt48OKJnDU+PcRBeWHR3+DT+03/t80BR18JJ/wWwmNCG5uI9EoeX4C/fLCVf32+g6Bl+n3+evFEpmUnhjo0+TqWZZ71P7kH8leYNpsDxp5vEp36TwhtfCISUkp4EjmIukY/N722jtdXFwBw6phU7r9wArHuTh5taVmw6Q2YfwtU7TJtWcfAafdC//Gde20R6ZOCQYvfvLyWT7eW4HbZ+c8V0xieqo6lbqW+HFY9DUsfb/1ssDlg+KmmmtPQOZreVKQNXyBIZb2PomoPeyoa2FNR37RuYGdpLTtL6whaB/5camw4Rw9OalmykyK7pqKn9H6Vu2DFf2HVM1Bb1No+6HhzHx9xBoSpbL5Ib1bv9fOPT7bzj0934A0ECXfaufqkofzouMGEOx2hDq/n81TB/JvNMzNAfBac8zcYfHxo4xIR6QZ8gSDXPr+Kd9YV4rTbePg7kzhtbIgH1OZ9CW9dByWbzX7WLDjjAUgdHdq4RKTXWrmrgutfWsP2kjoAzp+Uwe1zx3T+Oz9pH8uCHR/Dx/fCnqWmzRkBU66AGT+D+IEhDU9Euge9HRPZT05xDVc+s5JtxbU47DZ+e9pIfnhsF0xhV7LFzFPeXIYxdgCccpfK94pIp7r33U28tiofh93G3y+dwpSshFCHJM2KNsLSf8KaF5qq/QERiTD1ezD1BxDXDUrPi3SQJxbuJGiZCptByyJoQdCysCyTmBloagsEg3h8QRp8ATzeAA2+APXeAFUNPirqvVTUean2+L/2eolRYYzqH8OotFhG9o9lalYCWUpwko5kWZC3EJb8Aza/DVZTBbGofqYi3+TLVZVPpA8IBi1eX5PPH97dQmG1B4ATRvTjznPGMjBJiY4dYuv7pqpTjRmwxvSfwOxbITw6tHGJiHQDvkCQq55byfwNRbgcNh69dApzRqeGLqD6cjPtaHOCamQynPp7GP9t9X+LSKeo9/r564JtPN5U1alfTDj3njeOk0N5L5SvZ1mw8zP4+B7Yvdi0Od0w7Ycw61qITgltfCLSrSjhSaSNN9YU8NtX1lLvDZASE84jl07u/HKWvgb47AEz52zQB45w84F9zC8gLKpzry0ifdpjn23nX5/vBOCPF4znxJH6ohBylgW5X5gpTbd/2NqeOg6O+gmM+xa4NN2g9D53vLmxQ3+fzQZJUWEMSIgkIyGCAQkRDEiIZGBiJCPTYkiJCVdyk3QOnwfWvwyL/wFF61rbBx0PU79vqjk5w0IXn4h0mRV5Fdz51kbW7K4EzJQZt5w5itPGpukzqCM0VMJ7N8Ka58x+4mCY+whkzQxpWCIi3YUvEOSa/61i/oYiwpx2/nnZlND1+1gWrHke3r8Z6s20rkz+PzPtaKSmkhKRzvHR5iJ+N28D+ZVmIOn5kzK49ezRxEfqO3m3lvuFSXTKW2j2HeGmP+WYX0BMWkhDE5HuSQlPIkCjP8Dv397EU4vyAJgxOImHLplEv5jwzr1wzofw9q+gwiQcMPw0OP0PkJDdudcVkT7vlRV7uOcdUzr8pjNGcsGUASGOqI8LBmHL2/DFXyF/uWmz2WHkWXDUT82LG70Yk17szPH9cdhs2G1gt9mw2Ww47K3bze0Ouw23y0GEy0FEmJ2IMCdup524CBeJUWHER4aRGBVGXIQLh13/zUgXaqiEZY+bik51JabNGQETLjYJqymjQhqeiHSd3eX13D9/C2+sMRWHosIc/PykoXx/1iDcLk1f1yFyF8JrP4Gq3YANZvwcTrxZ04OKiDTxB4Jc98Jq3l1fSJjDzj+/O4UTR4Qo2al0G7z9S1OpA6DfKDjrL5A1IzTxiEivV1jl4Y43N/Du+kLADDy4c+4YZo9SVadurXCdqQK4/SOz7wgzU9cdcx3Epoc0NBHp3myWZVmhDkIklPZU1PPz51a1jLq86sShXDdneOe+JKspgvk3wvpXzH5Mukl0GnW2XmiLSKf7eHMxP3xqOYGgxY+OHcTNZ44OdUh9l98L6140Vf5Kt5o2p9tMdzTjKkgcFNr4RETkq1XvhcWPwvInwFtj2uIyYfqPYNJ3NWJdpA8prvbwt49yeH7ZLnwBC5sNLpqSya9OHU5KjDvU4fUOfi98cq+phooFCYPgvH/CwKNCHZmISLcRCFr86sXVzFtdgMth4x+XTQnNS36fx9yvv/gzBLxmMMDxvzF9Hap4KiKdwOML8O8vdvLoxznUeQM47DZ+cMwgrp09jKhw1f/otqr2wEd3m0qAWGB3weTL4dhfQpwGaYvI19MdXvq0T7YU84sXVlNZ7yMuwsVfvj2Bk0Z24hfAYBBW/AcW3AmNVaZ6x/SfwEk3Q3hM511XRKTJyl0V/OzZlQSCFudNyuDG01VxIiR8Hlj5pEl0qs43beFxMP2HpqKT5iEXEeneyrabe/ia/5kXOAApY8zIwzHngUNftUX6ivI6L//4dDtPfplLoz8IwDFDk7nxjJGMSY8LcXS9SOk2eOWHsHe12Z90GZx2n/pSRETaCAYtfvPyWuatLsBpt/HwdyaHJtlpx6emqlNZjtkfejKc8YAGdYlIp7Asi7fX7eW+dzezp8JMXzd5YDy/P28co/rHhjg6OaSGSpMYu/jvEGg0bWMvgJN+p88LETki6oWVPikQtHhwwVb+9nEOlgXjB8TxyHcmk5nYieXPC9fBm79onaoofRKc9VdIn9h51xQRaSOnuIbv/3cZDb4Axw/vxx+/NR67pnzqWj4PrHzKjHCs2WvaotPMNBxTrgC3voSLiHRre9fA53+Gja8DTcWSB84wiU7DTlG1VpE+pKjaw7+/2Mmzi/Oo8wYAmJKVwK9PGcGMIUkhjq4XsSxY8V+YfxP46sEdD+c8BKPnhjoyEZFuJRi0uPHVdbyycg8Ou42/XTKJU8ekdW0QdaUw/2ZY+7zZj041yaljztNzsoh0iiU7yrh//haW51UA0D/OzQ2njeScCenq9+6u/I2w7N/w2R+hwfzvRtYxcMqdkDEltLGJSI+khCfpc8pqG7n2+dV8kVMKwGVHD+R3Z40m3OnonAs21pqS64v/DlYAwmJg9q0w7Qdg76RriojsZ29VA5f/eymV9T4mZMbz6KWTcTnsoQ6r7/A3mkSnz/8MNQWmLTYDjv2VGZ3uDA9tfCIi8tUK15tn+s1vtbYNPw1m/QKyZoQsLBHpermldfzzs+28siIfb8BUdBrdP5brTx3BCSP6YdML3Y5TVwpvXANb3jb7g46H8/4BsemhjUtEpJuxLItbXl/PC8t3Y7fBX789kdPH9e+6AIJBWPU0fHAreCoBm+n7nn0ruFXtUEQ63spdFfz5/a0t7/kiXA5+evwQfnzcYCLC9N6tW7Is2PAaLLgdKvNMW/IImHMnDD9VibEi8o0p4Un6lBV55fz82VUUVnuIcDm49/xxnDspo/MuuOMTeONqqNxl9kefa0a1xHbhF04R6fOq6n3833+WUlDlYXC/KJ64YprmLe8qfi+sakp0ap66LjbDzEE+6btKdBIR6e6KN8En98HGeU0NNhj3LVPRKXVMKCMTkS5kWRaLtpfx1KI83t9YSLCpwNu07ASuPGEIJ45IUaJTR8tZAPN+BrVF4AgzL82P/jnYNWhDRKQty7K47Y0NPLdkFzYb/PmiiZw9oQsTQ4s3wVvXwa5FZj91HJz9VxgwtetiEJE+wbIsVuRV8MjHOXy8pQQAl8PGRVMzufqkYaTFuUMcoRzS3rXw3m8hb6HZj06DE2+CiZeCQ+8pRKR9dBeRPsGyLP6zMJd739mEP2gxpF8U/7hsCsNSYzrngp5q+OB3puw6QNxAOOvPMGxO51xPROQQPL4AP3hyGVuLakmNDeep708nMSos1GH1fsEgrH8ZPrq7dcRKTLpJdJp8uRKdRES6u9JtJtFp/Su0TF035nw44bfQb0RIQxORrlPj8fHqynyeXpxHTnFtS/tJI1O48oQhTMtODGF0vZTPAwtugyX/MPv9RsIFj0PauNDGJSLSDVmWxZ1vbeSpRXnYbHD/tyZ07uDetrz18Nn98OVDEPSDKxJOvBmO+qleXotIhwoELd7fUMhjn+9g1a5KABx2GxdMzuDqk4aRmRgZ2gDl0OpKTf/4yifBCoIzAo75Bcy8GsKiQh2diPQSevKUXq/a4+M3L63lvQ2FAJw9IZ37zh/XedVNti2AN69preQx7Udw8m0Q3knJVSIih+APBLnquVUsz6sgxu3kye9PZ0CCvgB2KsuCnA9Nad6idaYtOhWO/bVJdHJppJGISLdWvgM+/SOsfcF0xgGMOhtOuFEVnUT6iEDQVHN6ddUe3ltfSL03AEBUmIPzJmdw+YxshnfW4Km+rnA9vPojKN5o9qf/BObcAa6I0MYlItINWZbFve9u5omFuQD84fzxfGvKgK65+LYF8PYvWwd4jTgDTv8jxGd2zfVFpE8or/Py6so9PL04j7yyegDCHHbOn5zBT44fwqBkJcx0WwEfLHscPrkXPFWmbcz5Zvo6fVaISAdTwpP0ahsKqvjZsyvJK6vH5bBxy5mjuXxGVueUmm+ogPk3w+pnzX7CIJj7MGQf0/HXEhH5GpZlcfNr61mwqYgwp51//980RqbFhjqs3m3PCjMaPfdzsx8eC7OuhaOv1IgVEZHurrYEPvsjLP+PGaEOMPx0OPFG6D8htLGJSKezLIsNBdW8uaaAeavzKapubDk2pF8Ul8/I5vzJGcS4XSGMshcLBmHJ382ggYAXolLg3EdVJVtE5BAsy+KP87fw2Gc7ALjnvHFcNK0LXiDXFMJ7N8KGV81+TDqccT+MOqvzry0ifUIwaLFoRxn/W7qL9zcU4Q2YgUjxkS6+e3QW352RRUqMBpR2azkfms+K0i1mP22cSYrNmhnauESk11LCk/RKlmXx/LLd3PbGBrz+IBnxETxy6WQmZsZ3zgU3v2PmKq8tBGxw9M/gpFsgTJVURKTrWZbFXW9t4oXlu7Hb4G+XTGL6IE230WlKt8GHd8KmN8y+Iwym/xiO/RVE6t9dRKRba6yFRY+YqTi8TdNVDTnJPMtnTAltbCLSqXyBIEt3lvPBxiI+2FhEfmVDy7G4CBdnje/P+ZMzmDwwoXMGTYlRvRfmXQk7Pjb7w0+Hc/4G0f1CG5eISDf2lw+28vdPtgNw59wxfOeogZ17wYAflv0LPvo9eGvAZjdT1514k2Y1EJF2syyL1bsreXvtXt5Zt5eCKk/LsXEZcVw8PZPzJmUQGaZX2t1aRZ5JdNryttmPTIKTfmdmPbA7QhubiPRq+nSQXqfe6+eW19bz6iozpdzskSn86aIJxEeGdcLFyuHd38C6l8x+0jCY+wgMPKrjryUicpj+9P5W/rNwJwD3XTCeU8ekhTiiXqp6L3x6H6x8GqwAYIOJ3zHTHqk0r4hI9xbwwcon4ZM/QF2xaes/0ZRXH3x8SEMTkc5hWRbbimv5MqeUL7eXsWhHGTUef8vxCJeDE0b0Y+7EDE4c2Y9wpzrlO92mN+GNq03FbGcEnPp7mPp9UIKZiMghPbhgGw99lAPArWeN5vIZ2Z17wV1L4O1fQdE6s58+Gc76C6RP7Nzrikiv5vEFWLKznE+3lDB/Q+E+gw9iwp3MnZTOxdMGMjYjLoRRymHxe80gss8eAH8D2BxmMPAJN0BEQqijE5E+QAlP0qvkFNfws2dXsrWoFofdxq9PGcFPjhuM3d4JnWUb5sE7v4a6EjOqZebV5iW3K6LjryUicpge+TiHhz82HV93zh3DRVOVeNPhGmvgi7/AokfNlzgwI9Fn3wqpo0Mbm4iIfDXLgo2vm8p85WZUPAnZ5h4++jyw20Manoh0nBqPj3X5VazdU8Wa3ZUsyy2ntNa7zznJ0WHMHpnKnNGpHDMsGbdLSU5dorEW3vstrHra7PefAOc/Dv2GhzYuEZFu7pGPc/jLgq0A3HzGKL5/zKDOu1hdKSy4DVY9Y/bd8XDybTD5/1SpQ0SOmNcfZENBFSvyKvgip5TFO8rw+IItxyPDHJw8KpUzx/fn+OH99FzeU+z41LwnLTWfTWQdA2c+ACmjQhuXiPQpSniSXuP11fnc+Oo66r0BUmLC+dslkzhqcFLHX6i22HyAb3zd7PcbBec+oikvRCTk/v3FTu6fb+bGvvH0kZ0/yq+vCQZg9bPw4V2t1UAyj4KT74CsGaGNTUREvt6e5aa8+p6lZj8yGY6/AaZcAc5OqAYrIl3C4wuws7SObcW15BTXklNcw5bCGnaU1mFZ+57rdtmZlp3IjCFJzBySzLiMOBydMUBKDm3PCnj1h1C+A7DBrGvhxJt1HxYR+Rr//HR7S5/PDaeN5EfHDe6cCwWDsPK/sOAO8FSatomXwZw7ICq5c64pIr2KLxBkR0kdmwur2bi3mlW7Klmzu5JGf3Cf89Ji3Rw/vB8njuzH8cNTiAhTklOPUVMI79/SOvtNVD845fcw/iJVaxWRLqeEJ+nxPL4Ad7+9kWcW7wJg5pAkHrx4Ev1iwjv2QpYF6142U9g1lJuyjMf+Eo67HpwdfC0RkSP03JJd3PXWRgB+cfIwfnL8kBBH1Mvs/Azm3wSFTSXcEwfDnLtg5Jn6Eici0t1VF8CC22HtC2bfFWmqs864CtyxIQ1NRA7OsixqG/1U1PmoqPdSXu+lst5LWa2XgkoPBZUN5Fc2UFDZQFmd95C/JyM+ggmZcUwYEM+kgQlMyIzTVHWhEgzA53+GT+4100HHDoDz/gGDjg11ZCIi3d7jn+/g3nc3A/CrOcO58oRO6vMpWGWmr8tfYfZTx8KZf4KBR3fO9USkR7Isi+oGP8U1HgqrPewqr2dXWT25ZXXkldWzo6QObyB4wM8lRLqYkpXAtOxEThiRwvDUaGzqV+1ZggFY9jh8dDc0VgM2mPZDOOkWiIgPdXQi0kcp4Ul6tNzSOq7+3yrW5Vdhs8HVJw7l2pOHd/wIzeq98PYvYcs7Zj9tHMx9xJRdFxEJsVdX7uHmeSYR5yfHDeba2cNCHFEvUrYdPrgVNr9l9sPjzPzj036kUegiIt2drwG+/JuZhtRXb9omfMdMXxfbP7SxifRS1/xvFUHLwrIgaFkEghZBy7wUCVoWgTbbwSAELItGX4B6b4AGX4CG5rUvcEB1pq8S63YyNCWaYSkxDE2JZmhqNOMy4kiO1uCkbqEiD179MexebPbHnA9n/RkiEkIbl4hID/Dkl7nc/fYmAK6dPYyrO6PPp6HCvLxe9m/AgrAYOOlm0/fh0CskkZ5swcYiApaFZVkEguYZvXlp2W96Zg9YFj5/kNpGP3WNfmoa/dR6/NQ2Ni0eP9UeHyU1jQdUa9pfdLiTkWkxjOofy7iMOKZkJzA4OUoJTj3ZnuXw1nVQuNbsp0+CM/8MGZNDG5eI9Hl6WpUe69WVe/jdvPXUeQMkRLr4y7cncsKIlI69iGXB6udg/o3gqQK7C47/DRxzHThcHXstEZFv4J11e/n1S2uwLLh8Rha/PX2kvjh2BE8VfHY/LP4HBH2mqt/U78EJN0FUJ0yXKiIiHceyYP0r8MFtUL3HtGUeDafdq444kU72xpqCDv19ES4HCZEuEqLCSIgMIyEqjPQ4N+nxEU2Lm4z4COIiXHoG7o4sC9a+CO/82owAD4uBMx+A8d9WlVQRkcPwzOI8bntjAwA/P3EIvzi5g5OdLAvWPG+mJaovNW1jvwWn3K0BAiK9xA+fWt5pvzsuwkVKTDiZiZEMTIwkK8ksw1JiGJAQoefz3qK+HD68E1b8F7DAHQezb4MpV4Bd1XNFJPSU8CQ9To3Hx62vb+C1VfkATB+UyF+/PZH0+IiOvVDVHnjzWshZYPbTJ8HcRyF1dMdeR0TkG3pn3d6mUfRw4ZQB3H72GH2RbK+AH1b+Fz6+B+rLTNuQ2XDqPZAyMqShiYjIYchfCe/d2FpFJC4T5txhqonoM1Kk091y5igcdht2mw27DWw2W9O+2W5ud9htTfsmqSnC5SAizCyRLicRYQ5i3E7cLnWg91gNlaZS9vpXzH7m0XD+PyEhO5RRiYj0GM8v3cUt89YD8JPjB/PrU0Z0bJ9P4Xp453rY9aXZTx4OZzwAg4/vuGuISMhNyIzH0eb522GzYbfT9Fze+qzevO9y2okOdxAd7iQ63EW029m037ztJCUmnH4x4XpW7+2aC0J88LvWfvIJl8CcOyG6g4tPiIi0g82yjqRIuEhordldyTXPryKvrB67DX5x8nB+fuLQjp3CzrJMpvL7vwNvDTjC4cQbYcbVKuErIt3G66vz+eWLawgELeZOTOfPF03s+Ok8+5qcD2H+zVBiSsWTPNwkOg2bE9q4RETk61XvhY/ugtXPmn1XpKnKOvNqcHXwwAgREflquV/Aaz+Fqt2mUuoJv4Vjfqk+FRGRw/TS8t385pW1WBb84JhB3HLmqI5LdqorNdPXrXwSrKB5bj7uephxFTjDOuYaIiLSsxVtNIMXdi0y+/1Gwpl/guxjQhuXiMhBqKdBeoRg0OKfn+3gT+9vwR+0yIiP4MGLJzI1O7FjL1SRC29cAzs/NfsDpsPcR6Df8I69johIO7y8Yg+/eXkNQQu+NWUAf7hgvJKd2qNkqynfvm2+2Y9IMFPXTf2epi8VEenufA2w6BH4/M/gqzNt4y+G2bdCXEZoYxMR6Wv8XvjkHvjir4AFCYPggsdhwNRQRyYi0mO8vGJPS7LTFTOzOy7Zye+FpY/Bp3+ExirTNvpcOOUuiB/Y/t8vIiI9X2MtfHofLHoUrIBJij3ht3D0z9RPLiLdlhKepNsrrvbwyxfX8EWOmUf8zHH9uef8ccRFdOCHazAIyx6HBbebFyXOCJj9Ozjqp5qDVkS6lWcW5/G719djWXDJ9IH8/tyx2JXs9M3Ul8OnfzD3/6Af7E6Y/mMzsjGygxNqRUSkY1kWbJwH798KVbtM24BpcNp9erEuIhIKJVvg1R/B3jVmf9J3zT05PDq0cYmI9CAvLNvFb19dh2XBZUcP5LazR7c/2cmyYNv7MP8mKMsxbWnjzT06e1b7gxYRkZ7PsmDTG/DejVCdb9pGnQ2n3gvxmaGNTUTkayjhSbq1jzYX8euX1lJe5yXC5eD2c0Zz0dTMjp2vvGw7vH5V63zlWbPgnL9B0pCOu4aISDtZlsXfPsrhzx9sBeD/ZmRx+zljOvZ+2FcEfLDs3/DJveCpNG3DTzejGpOHhTQ0ERE5DHvXmE64vIVmPzYDTr4Dxn0L9LkoItK1LMsMIHj/FvB7TLXUsx+E0XNDHZmISI/y7JI8bn5tPdCBfT6F6+GDW2H7h2Y/qp+phDrxUg3yFRERo3wHvPMbyPnA7MdnwRkPwPBTQhuXiMhhUsKTdEseX4A/vLeZJxbmAjCqfyx/u2QSQ1M6cGRgMACL/27mLPc3gCsK5twBU38AdnvHXUdEpJ2CQYs739rIf7/MBeCak4Zy3ZzhSnY6Us2jGt+/BUpN4hgpo+HU38OQk0Ibm4iIfL2aIvjoTlj1LGCZqqyzroVZ10BYVKijExHpe2oK4fWfQ84Csz/kJJj7KMT2D21cIiI9zFOLcrn19Q0AfH/WIH53VjunsavaAx/9Htb8D7DA7oKjrzQVrd2xHRO0iIj0bD4PLHwQPv8TBBrBEQazfgHH/hJcEaGOTkTksCnhSbqd9flV/PLF1WwtqgXge7OyueG0kbhdHTjqpGiDqepUsNLsDz4Bzn4IErI67hoiIh2g0R/g+pfW8saaAgBuO3s035s1KMRR9UDFm0z59u0fmf3IJDjpFph0OTj0OCQi0q35G2Hxo/DZn8BbY9rGXQgn3w5xA0IamohIn7XxDXjzWmgoB6cb5twJ036kAWQiIkfo31/s5K63NgLw4+MGc+PpI795slNDJXzxFzPIN9Bo2sacD7N/B4mDOyZgERHp+bYtgHevN9WdwLwjPeNPkDw0pGGJiHwTesMn3YYvEOTRj7fzt4+24Q9aJEeH8cdvjeekkakddxF/I3x2v/niF/RDeByccidM/j9NfyEi3U55nZefPL2cZbkVOO02/nTRBOZOzAh1WD1LXRl8cg8sfwKsQNOoxp82jWqMC3V0IiLyVSwLNr0JH/wOKnJNW/pkOP0PkDk9pKGJiPRZjTXw7m9h9TNmP20cnP84pIwMbVwiIj3QY59t5553NgPwsxOGcP2pI75ZspPPA8v/A5/9ERoqTFvWLJhzFwyY0oERi4hIj1a5G+bfaPpaAKLT4LR7THKs3pGKSA+lhCfpFrYV1fCrl9awdk8VAGeMS+Puc8eRGBXWcRfZtQTeuBpKt5j9kWeZeWhVal1EuqHtJbV8/7/LyCurJ8bt5NFLJ3PssH6hDqvn8Hth2b/gkz9Ao/lsYeRZZuR50pDQxiYiIl+vcB28dyPkfm72Y/qbik7jLlL1EBGRUNm1GF79MVTmATY45hdwwk3g7MC+GxGRPsCyLB79ZDv3zzf91NecNJTr5gw/8mQnv9ckoH72AFTnm7bkEabvY/ipenktIiKGvxEWPQyf3g/+BrA5zFSnx9+gqU5FpMdTwpOElD8Q5N9f7ORPH2zF6w8S63Zy17ljOWdCevvmKW+rsQY+vBOW/guwICoFzrgfRs/Vlz4R6Za+2FbKz59bSVWDjwEJETxxxTSGpcaEOqyewbJg63sw/2Yo327aUseZkSqDjgttbCIi8vVqS+Cju2DlU4BlpkmaeTXM+gWER4c6OhGRvsnfCJ/+wVTLtoIQNxDO+wdkzwp1ZCIiPY5lWdz37mb++ZmZRui6k4dz7cnDjuyXBPyw9nlzb67cZdpi0uGEG2DiZeDQax8REWmy/SN453ooyzH7WbNMMYjU0aGNS0Skg+jJV0JmY0E1N7yylnX5pvLG8cP78YcLxpMW5+64i2z7AN78BVTvMfsTL4NT7oLIxI67hohIB7Esi79/up0H5m8haMGkgfE89t2p9IsJD3VoPUPRBph/E+z4xOxH9YPZt8LES8HuCGloIiLyNXweWPJ3+OxP4K0xbWPOhzl3QPzA0MYmItKXFayGeVdC8UazP+ESM7WopocWETligaDFTa+u44XluwG46YyR/Pi4I6hCHQzA+lfhk3tbB3lFpcCxv4IpV4CrA/vVRUSkZ6vKN33lG+eZ/agUOPX3MO5CFYMQkV5FCU/S5Ty+AA9/lMM/Pt2OP2gR63Zyy1mjuXDKgI6r6lRXBu/9Fta9aPbjs+DsB2HIiR3z+0VEOliNx8evXlzD+xuLALhwygDuOncsbpcSdb5WbQl8/HtY+aQZce4Igxk/h2N+qZK8IiLdnWWZzrcPbmuaIgnoPxFOuw+yZoQyMhGRvs3vhc/uh8//BFYAIpPhrD+batkiInLEGv0BfvH8at5dX4jdBveeP45vTzvMxP6AD9a+CAv/CqVbTVtkkqmCOu2HEBbZWWGLiEhP4/eaAWWf/AF8dWCzw/SfwIk3atCCiPRKSniSLrV0Zzk3vrqW7SV1AJw+No07zhlDSmwHjT4JBmHNc/DBrVBfZj7Ij/4ZnHgThEV1zDVERDrYmt2VXPv8KnLL6glz2Llj7hgunpbZcUmgvZW/EZb807yIaaw2baPnwpw7ISE7pKGJiMhhyF9hpiDdtcjsx/SH2bfB+G+D3R7a2ERE+rK9a2Hez6BondkffS6c+SeISg5pWCIiPVVdo5+fPrOCz7eVEuaw8+DFEzl9XP+v/0FvPax6Gr78G1SZqlC442DmNXDUTyA8pnMDFxGRnmXHp2b6utItZj/zaDjzAUgbF9q4REQ6kRKepEuU1jZy7zubeWWlmVouOTqcu+aOObwvdoercD28/SvYvdjsp4yBc/4GA6Z03DVERDpQIGjxj0+385cPtuIPWqTHuXn0silMzIwPdWjdW3M1kAV3QMVO09Z/Apx6L2TPCmloIiJyGKry4cM7Ye3zZt8VCbOuhZlXa5CCiEgoBXymotNn90PQDxGJJtFp7PmhjkxEpMeqrPfyvf8uY9WuSiLDHDz23akcM+xrEkgbKmHZ47D471BfatqiUkw166nfVzVrERHZV9UeUwhi/StmPzIZTrkLxl+sAWUi0usp4Uk6VSBo8dzSXdz/3maqPX5sNrh4Wia/PW0UcZGujrmIpxo+uQ+W/MOUWXdFwQm/haOvBEcHXUNEpIPtKqvn1y+vYenOcgDOHNefe84b13H3xt4q9wvz5S1/hdmPTjXVQCZcoi9vIiLdnbcOFj4ICx8Cf4Npm3AJzL4VYtNDG5uISF9XsBreuBoK15r9kWfBWX+B6JSQhiUi0pPtrWrgiv8sY0tRDXERLv77vWlMGphw6B8o3wFL/wWrnmmtZB0/0AwOmHgZuDpolgQREekdvPVN/SwPmn4Wmx2m/gBOugUi4kMdnYhIl1DCk3Sa1bsrufX19azdUwXAmPRY7j537Fd/qTsSlgUbXoX3boLaQtM2eq6p8BGX0THXEBHpYP5AkMe/2MlfF2zF4wsSFebgjrljuWByhqaw+ypFG0xFp23zzb4rCmZdAzOugvDo0MYmIiJfLRiAtS+Yqk41e03bwJlw6u8hY3JoYxMR6eu8dfDxPbD4UbCCEJEAZzwAYy8AfT8REfnG1udX8YMnl1FU3UhKTDhP/+AoRqQdZAo6y4Kdn8Lif8DW9wDLtPcbBcf+EsacDw69xhERkTb+v707D5OzqhM9/q2q3veklyydlewbJAFCIEBQFmVTBBkfwYW5z4zjMpvj3HEZ5zou9zrqjHdWdfS6jOLouDCMIlcRkBACgSQkEEgI2ZNOJ+lOd3rvrq6uqvvH6U51Z2G5dlLd6e/ned7nfevUm7wn6HPeU+f8zu+k07D1x/DwX0PboVA27Qq48W/CTgiSNIbYU9awq2/p5ou/fIn7t9QDUJqfw5+/aR7vWjmdWHSYBsuO7YQH/xz2PBY+j78AbvoSzL5ueP5+SToLnjvYwsfv28q2w2GV3hWzKvn87UuYXun2PWfUWhcmYLb8O5CGaA5cfA+s/qirzSVppEunYdfDYQDu6AuhbNwMuP4zsOAtTqRLUrbtegQe+DC07A+fF90Ob/4bKJ2Q3XpJ0ij3yPaj/NEPNtPVm2ROTQnfuudSpo4vGnpTb1dYFPD0v0Lj9kz57OvhsvfDrDeayVqSdKq6jfDLj0HdhvC5fBrc8BlYeJvjLJLGJAOeNGw6433865rdfH3tHnoSKQDuWD6Fj944j5rSYUq329sFa/82bIORSkAsH676SEjra0pfSSNUfUs3f/urHdy3Oay2qCjK5S9vWsDbL55iVqcz6T4Oa78cBv6S8VC28K1h+7rKWdmtmyTp1dVtgoc/BfvWhs8F5aHfftn7ISc/u3WTpLGuswl+9fEw0Q5QNgVu+TLMfVN26yVJ54HvrNvLZx7YRioNV86u4l/uXk55YW74Mp2G+s3w7HfhhZ9mtq3LLYZld8OK90HVnOxVXpI0crXVhwVlA3343GK4+iOw8kPOj0oa0wx40m+tL5niJ5vq+PKvX6ahPUxKr5gxnr+6ZSFLppQPz0PSadj+M3jok9ByIJTNuQFu/ELI7iRJI1Brd4JvPL6Hb6zdQ7wvBILevqyWT9y8gKoSJ3tPK9EDz3wd1v4d9LSEsumrQjaQKZdktWqSpNfg2C549DOw7b/C51g+XPYHcOWHoWh8dusmSWNdKgXP/Ts89FfQ3QxEQhv9xk9C/mm2WZIkvWbJVJrP/WIb3163D4B3XDKVz71tMbmxKHQ1w/M/gs3fy2Q+hZD9dMX7YNm7wgIBSZJO1tMGT/4jPPUvkOgCIrD0brj2r6B0YrZrJ0lZF0mn0+lsV0KjUyqV5ufP1/P3D+9k77FOAKaNL+LjN87nzYsnDl/Wkvot8KtPwP514XPZlLAP7fxbTM8oaURq6ojzrXV7+e6T+2mP9wEhEPSTtyzgwikV2a3cSNXXGwb+1v5dZt/x6gVw/adDgKvtvSSNbO1HYM0XYNO/QTpJGIC7C675OFRMzXbtJEn1m+HB/57Z+qJmEbzln2DKxdmtlySdBzrjffzJDzfz8PYGAP7izfP4wKopRPb8Brb+GLY/kMleHcuHhW+B5e+B6Ve6bZ0k6fT64rDhm2HXm66mUDZ1ZZgfnbwsu3WTpBHEgCe9bul0moe3N/B3D+3gpSPtAIwvzuOD18zi3ZdPJz8nNjwPaj8Cj3wWtnwfSENOAVzxx3Dln0Je8fA8Q5KG0a6GDu5dv5//2HCQ7kQSgLkTSviz6+fxpkUT3L7udJIJeO4HsOZL0Nqfwa+sFt7wCbjonRAdpneKJOns6GyCJ/8BnvlG/0pDYO6NcO3/gAkLs1s3SVLIKvLoZ2Hjt4E05JXA6o/Cyg9ALDfbtZOkUW/fsU7ef+8mXjrSTmFOmm+v7mZl52Ow/ecQb83cOHEJLH8vLHk7FI7L/ZovsQAAGvhJREFUWn0lSSNcKhmCZR/9n5nx8so5YZxlwa0uDJakkxjwpNcslUrz0LYjfOWx3TxfF36slRbk8L6rLuB3r5xJSf4w7ZAYbw+pGdf9IyRC5iiW3AnXfsrV4ZJGnJ5Ekke2N3Dv+v08tafpRPmS2nL+8I2zuX7BBKJRf4ScIpUM6dzXfAGO7w1lJRPgqo+EAUD3HZekka2rGZ78J3j6XzN99imXwnWfhhmrsls3SVLobz/7XXjkM/3b1xHGVq7/LJRNym7dJOk88dCLR/jojzaxIPECb8vfxG35G8ntyYwNUToJFr0NLvwds3FIkl5ZOg07fw0P/zU0vBjKSieFzNlL74bYMM3BStJ5xoAnvapEMsX9mw/xtTW72d0YJjMKc2P87qoZvO/qC6goyhueByUTsOk7YfK7szGU1V4Cb/48TF0xPM+QpGHQ25di3a5j/Pz5eh568Sgd/dvWRSNw7YIJvHvldK6aU2VGp9NJ9sGL98GaL0LTzlBWVAVXfhgu+W+QV5Td+kmSXln38bA4Yf3XoDdke2XS0pCZzy1IJWlk2LsWHvokHN4SPtcshJu+BDOuzGq1JOl80dfWwK/+63vw8i+5OrqV0kh35suiSlh4Gyy+A6Zd7pZ1kqRXd2B9WKiwf134nF8OV30YVvyB4+WS9CoMeNIZtfUk+MnGOr75xF4OtYQfbWUFObz3ihncc8UMKkvyh+dBqRRsuz+kWG/eE8rGzQzpGRfe5o9CSVmXTqfZ19TF2p2NPP5yI0/tbqKzN3ni+8nlBdy+fArvvGwatRWFWazpCNYXhy3/Duv+Ho7vC2WF48JWpSveB/kl2aydJOnVdLfA+q/C+q9AvC2UTVwC13wC5t1ooJMkjQSNL8PDn4IdD4bP+WUhIPXS33dFuCT9NpIJqN8Me9eQeOmXxOo3ESUzrZIuriEy9wZYdDvMXG2bK0l6bfY9EZJA7H08fI7lw2V/EBYHF43Pbt0kaZQw4Emn2NXQzr89uZ+fPltHV/+EflVJPr9/1UzuumwapQW5w/OgdDoMwj32eTiyNZQVV8Pqj8LF90BsmJ4jSa9DKpWmvrWbnQ0dbKtvY/OB42w+0EJTZ++Q+6pK8rl5yURuvWgyy6eNc9u6M4l3hOx9T/0ztB8OZUWVcNkHwo+3grKsVk+S9Co6GkKg04ZvQjxsa82ExXDNx2D+LQY6SdJI0HksjK1s/DakkxCJheypqz8KJdXZrp0kjT6pJBx+DvatDZPQB9ZDb8eQW7alZ5Az/0bmXnVn2K7ORbuSpNcinQ7vljVfyGR0iubA0rtC/718SnbrJ0mjjEsNBIRt6x7Z3sD31u9j3a7MPuNzakq4Z9UM7lg+hYLc2PA8LJ2GnQ/Bb/5XJr16XknI8nH5h8zyIems6EkkaetJ0NadoLW7j7buBG09CY519FLf0s2h493UtXSxp7HzRLDnYLmxCMunjePqudWsnlvNwkllBjm9kq5meOYb8PRXw/ZHAKWTYdUfw/L3QF5xdusnSXplTbvhyX8K2fmS8VBWvSAEOi14ixM6kjQS9LSGoNQn/zmzzei8m+C6T0P13OzWTZJGk45GOLQpc9RtzAT79+vOKWdN7zzWJhezq2IVn3vPm5gzoTRLFZYkjTrpNOx+FNZ8EQ6uD2WxPFj2brjyT6FiWlarJ0mjlQFPY9xLR9r48cY67t986ET2kmgErlswgXuumMHlsyqJDNeq7YFApzVfCD8cAXKLQ4aPK/7I9IySXrfrv7yGZCpNMp0mmUqTOnENqUFl8WSK3r7Ua/57c2MRLqgqYe7EUpZOrWDZtAoWTiobvsDP81njyyHIacsPoC9sh8r4C0Ia3gvfATnDtB2qJOnsqN8MT/w9bP8ZpPvfnVNWhMG3uTca6CRJI0G8A575Oqz7B+hpCWWTlsINn4OZV2WzZpI0sqXT0HYIjm6Dhm2h73voWWg9cOq9+eUwYxWNVSv47IuV/PzIONJEufnCSXzzjgspyXdqRZL0GqRSYW708S/BoY2hLJYfdrpZ9SdQXpvV6knSaGevfAw62tbDg1sP89Nn63jhUNuJ8qqSfO64uJZ3XTadqeOLhu+ByT548T/hif8NDS+GstwiWPH7IatTcdXwPUvSmLKzoePVbxokEoGyglzKCnMoL8ylvDCXiqI8aisKqa0oZHJFITOripleWURuzAnd1yydhj2/gae+Art+nSmfsCRMkC+8DWJ2OSRpxBpox9f9A+x5LFM+54YQsDrtcreuk6SRINENG78Fa78MXcdCWdVceMMnYMFbDUqVpAF9vdB6EJr3QvPuENzUsD0c8bbT/IEIVM+D2ouhdjnUXkKqZjHfeuoAX/rVDuJ9KcoKcvjsbYt5y0WTh2+BsCTp/NXbGbJmP/01aNoVynIKw9bTq/4YSidmt36SdJ6IpNPpdLYrobPvcGs3/3frER7cephNB44z8L96bizCtfMncOclU1g9t5qc4ZzgT3TDlu/Dun+Elv2hLK8kvMyv+CMoqRm+Z0kak57a3UQsGiEWhWgkQiwaOXEefJ0bi1BWmEtJXo7b0A2nRDds/XHYRqNhW39hBObdCCs/CDOudIJckkayeAc894OwBemxHaEsEoMlbw+rDCcsym79JElBTyts+Gbod3c2hLJxM+Gaj4c2O2omWkljSDodstu1H4H2w9B2OJxbDsDxvXB8H7TWZbKVniyaA5VzoGYBTFwMtZfA5GVQUHbiloPNXfz5j5/j6b3NAFw9t5ov3nEhE8sLzv6/T5I0urUeCtlYN30nk401vyxkdHJuVJKGnQFP56lUKs3WQ608tqOR3+xoYMvBliHfL59Wwa0XTeatS2sZX5w3vA9vq4cN/wc2fhu6w49Ciirhsg/Ait+DwnHD+zxJ0rnVsD38YHvuB2HyBcIWpcveFbYprZyV1epJkl5F0+7QX998b2aFe15JaMcv/xBUTMtu/SRJQUcDrP9KCHYaaK/Lp8Lqv4CL3gmx3OzWT5L+f6RSkOyFZBx6u6C3A+LtIRNGb0cIyu9pge7j0NUcxpdPnJug/Sj0db/6c3KLYNyMECBaMx9qFoajcjbknH48vC+Z4t71+/nSr3bQ2ZukKC/GX968gLtWTDOrkyTplR3aFHZA2HY/pPpC2biZsPIDsPQuyC/NavUk6Xzl/jLnkfqWbp7e28SaHY08vvMYzZ29J76LROCS6eO4cfEkblwykUnlhcNfgbqNYbXh4Jd5+dQQsbzs3ZA3jNvkSZLOrd6u0L5v+g4cfDpTXjENVrwvtPOFFVmqnCTpVfX1wksPwLPfDdvXDRg/K7TjS+8asqpdkpRFx3aG8ZXN94aAAIDq+bDqT0NGJwOdJJ1t37sdSIdsSqec+538XaqvP5Ap0X8efN2XKUsnh6eOheOgdFLmKK8NE8vjZ4ZzSc3ryjr95O5jfPpn29hxtB2AS2eM42/vvIjplcXDU19J0vmntxO2/ax/zHx9pnz6lXD5B2Hum83GKklnmQFPo1QqlWZvUycb9jbzzL5mntnbTN3xoStbSvJzWDW7kmvm1fDG+TVMKDsLKXfjHfDCT8PLvP7ZTPm0y0PU8rybIeb/zSRpVEqn4fBzYa/x53+YyeYUicH8m0Ia3gveCNFh3A5VkjS8Gl+GZ/8tZOXrasqUz74eLns/zLIdl6QRIZWEnQ+F7S92P5opr70ErvozmHuj7bWkc2f3I+fmOZEo5JVCfknIOJpfAnnFYeufovFQOP7Uc+nEcOQOz4LeuuNdfP7Bl/jF1sMAVBTl8pEb5nHXimnEomZ1kiSdJJ2GQ8/C5u/C1p9CbwiUJZoLi+8Ic6OTl2a1ipI0lril3SjQl0yxv7mLFw61srWulRfqW3nxUBvt8b4h98WiERZNLmPV7CpWz63m4unjyI2dpcGw+s0hyGnrT0KqYYBYXniZX/Z+X+aSNJo174WtPw7HsZcz5RXTYPl7w5ZHpROzVz9J0ivraoYX74PnfzQ0K1/pJFh6Nyx/d9jeQ5KUfV3NsOX7YavR4/v6CyMw70ZY+UGYceXrylAiScNiyw/6255I5gyZ9uiUskjIPhfLG3Q+zXX0pHty8rPWxvUkknxtzW6++thu4n0pohF418rp/Nn1c6koOv2Wd5KkMayzKSwK3nwvNGzLlI+bEcbLl74LyiZlrXqSNFYZ8DRCpNNpmjt7qTvezYHmLnY1dLCrsYNdRzvYe6yT3mTqlD+TlxNl6dQKVswYz4qZ41k+fRwl+Wcxm1JbfQhwev5HcHRrpnz8LLj4vXDRXVBSffaeL0k6ezqPwQv3wdYfQd2GTHlOQUi9u/w9cMEbXFUuSSNVohte/mXoq+98KLPFdCQKc94U+uuzrzf7qiSNBKlk2F50873w0i/CFk8ABRUhKPXS3zMwVZLOkp5Ekh9tPMhXH9vN4dYeAFZeMJ5P3bqIBZPc4lmSNEhfHHY9EgKdXnoQUolQnlMAC94S+u7Tr3TMXJKyyNHusyyZStPWnaClO0FzZy+N7XEaO+Lh3N7D0bY4dce7qDveTVfvmfcvL8iNsmBSGUtqy1lcW86S2nJm15ScvQxOA3raYPvP4fn/gL2PA/3xcbG88DK/+B5XG0rSaNVaF36ovfQA7HsC0v3voUgUZq6GC38H5t8CBQ74SdKI1NsZgpu2/SycBzKvAky8EC58R8jA6gpDSRoZmnaHbE7P/RDaDmXKJyyBFb8HS34H8oqyVz9JOo919fbx/fUH+PraPTS2xwGYXF7AX968kJuWTCTi+LYkCSCZCPOhL9wX5kfjrZnvJi0NQU6L3w6FFdmqoSRpkDEZ8PTTTXWk0mnSacKZcE6lQ6algfLTfe5LpuhOJOlJhHM8kaS7/+hJJOlOpIgnknTE+2jtTtDe0/eq9RlsQlk+U8YVMau6mNk1JcypKWV2TQm1FYVEz9We4Z1NsOPB8CLf85vMSkOAaZeHCfCFt4V90yVJo0c6HdLtvvSLEOR0+Lmh309eFiZZFt/ulnWSNFJ1NcPOX8P2n8Guh6GvJ/Nd+VRYcmfor9csyF4dJUkZzXvgxfth2/1D+9+F40KbvfRumHSRC8kk6Sxp70nw3af2880n9tLcGca5aysKef81s7jz4ikU5MayXENJUtb1dsHuR2D7AyF7dk9L5rvSSbDodlj6Tpi4JGtVlCSd3pjc0m7Gx35xzp9ZnBejoiiP6tJ8akrz+88FVJfmM2VcIVPHFzGpvCA7P7DS6TAAt/PXYQJ8/zpID9pCr2pumDRZcqcp1SVptOk+HrI37f5NmBhv2T/oy0gIZJ1/E8y7CSpnZa2akqQzSKXgyPOhr77zITi0cWhffdyMkHl14Vth8nLTqEtStqXT0LQrjK+8+J9Dg5wiMZj1Rlh2d+h/5+Rnr56SdJ7bcaSd/9hwkJ9sOkhb/6Lk6ZVFfOia2dy2rJa8HPvNkjSmHd8Xxlp2PQx71kBfd+a7oipYdFvImj11pWMtkjSCjckMT6vnVhONQDQSIRKBSCRyms8RIjCoPHyXG4tQkBujIDdGYW6Mgtwohbkx8k98DufCvBgVRbmUF4bjrG8993r1dsLeteFFvuvX4cU+2MQLw8TJgluhep4rDSVptOiLw8GnYc9j4ajfPHRiPKcgTLLMuwnmvhlKqrNVU0nSmRzfF9Kn710Le9dAx9Gh39cshPk3h/76xCX21SUp2xLdYZHBzofCMXiMJRKDmVfBorfB/FuhuDJr1ZSk811HvI8HnqvnhxsOsuVgy4ny2TUl/OEbZnPLhZPIGWnj9JKkc6O7JSR82Ps47HoEmnYO/b5iepgTnX8zTL0MomYAlKTRYExmeBqT4h1wcD3sWxde6Ic2QWrQdnvRXJh+Ocy5IbzQzeQkSaNDRyPUPQMHn4G6DXDo2aGrUQCq5sEF1/QfqyGvOBs1lSSdTioVMoHUPQP7nwxBTq0Hht6TWwyz3gBzrofZ10H5lOzUVZIUJBMhc9O+JzLH4D54LA+mrwrZ9xbcCsVV2aurJJ3n+pIpNu4/zn3P1vHA84fp6k0CkBONcN2CCbzj0qlhAXTURQKSNKa0HgpZsg8+E+ZFDz83dGFwJAbTVoZxljk3wIRFLiiTpFFoTGZ4Ou+lUmGLukObwsu8bmP/izw59L7yaTDnuvAyn3k15Jdmp76SpNcm3gEN20KbXrch/Fg7vvfU+0omDApwugbKJp/jikqSzqijEY48F/rodRvCuadl6D3RHKi9GGZcFfrp01a67ZEkZVO8Heq3hODUfevgwHpIdA69p6w2BKbOeVP/GEtJVqoqSWNBa3eCNS838uj2ozz2ciMtXYkT311QVcw7Lp3K7cunUF1qH1qSxoTeLji8JTPOUrcR2utPva9yTuirz7w6jJsXVpzjikqShpsBT6NdXxwad8DRF+HoC+Go3ww9rafeWzENpl8JM1aFlYbjZhitLEkjUSoJLQeGtu1HXjh9cBNA9XyYugKmrAjnqrm275KUbX1xaNoNjS/Bka2Zo+PIqffmFMLkZaENn3kVTF3pRLkkZUtPKzS8FCZMDj0L9c/CsZ3ASQnSCyrC2MqMVTBztSvCJeks6u1Lse1wGxv2NvPoSw1s2NdMXyrTLpcX5nL9wpDN6ZLp44jYHkvS+SmVgpZ9ob/e2H80bIOj205N+hCJhj76lEvDFnUzr3ZhsCSdhwx4Gg1SKehsCBMmTbvC0bwnDLg17Tr1JQ6QUwCTLgorw2svDpMnFdPOfd0lSaeXTEBbfQhiatod2vWm3dC8G47vg2Tv6f9cyUSYuBhqL4Gpl4azK1EkKTt6u6D1ILQchJb9oU0/tjMsSGjZPzRV+gkRqJwFk5f3B6teAhMWQyz3nFdfksasVDL0xVv29wen7oDG7WHi5HQrwQHKp0Ltcph2RQhyqlkE0ei5rbckjQHpdJpDLd1sOdjC5gMtbD5wnBfq2+jtG9q3nl1TwrXza7h2wQSWT6sgJ2abLEnnhYE50ZaD0HogjJU37oCG7WHMZfBW0oOVTAxjLFMuDcfkpZBXfC5rLknKAgOesi3RE17cHQ3QcTQc7UehtS68yFvrwnGmiW8IqwonLoGahTBhYVgdXrPQSRNJyoZEN3Q1QeexcO5qCpMpbfXQdihz3XGUU1aJDxbLC5mbJiwOAU4TFoXr4qpz9k+RpDGrLx7a8c5G6DqWuW4/EjLwDQQ5dR175b8nvyxk3Zu4OPTXJ14Y2nMH3CTp7EklQ7s9MMbScTS03611/cGp+0Ibnkqc+e8oqw1979rlIUB18jIoqT5n/wRJGgs64n3sO9bJ3kHHnmOd7DvWSWv3qW10RVEuS6dWcNWcaq5bUMP0SvvUkjSqpNMhm+qJsfP+8Zb2I2E+tOVgGG95tTnRWH4Ya6meBzXzoXpBCG4qqzXjqiSNQWMz4Cne0b/aOh1esAMrr9Pp/rLUoOv00HtTfeFF2xcfdI5DX+/Qc6I7vLh7WiHe1n/ddurnM0UinywSDRmaxs+Cytn9xwUhsKl0ki9xSWPTkPZ8oO0mc31KW39yG58KK0aS8dCeD27T+3oy7fzAdW8HxNvDc+Pt4ejtCO161/HwIy3R9drrH80N24tWzupv3y+A8ReE6/IpEI0N+38ySRqRXlf//DR99VRfpg1PJk7qo/cObc9PtN3tg462cO5uCQNv8bbXXvf8spD1o2IqVEyH6rlh4K1qLpRMsJ8uaWwZaM8HDhj6eaDdHtI3HyjvH3Pp68kciYHreBg/6YuH/vbAeMvJR3dL6JOfNsPeSaI5YZxl3Ayo6p8sqVkYJk4Kys/ifyRJGvk64n0kU2nS6TTJVJpUGlLpNKn+z+k0/eUDZdCTSNLZ20dXvP/cm6Qz3kdbd4LGjl6OdcQzR3sv3YnT7FrQLycaYeHkMpZOrWDZtAqWTR3H9Moit6qTpNfrdOPnp53/PM24y0BfPZk4dbzlxPXAmHkH9HZCb//Y+YmyDug+nlkc/EqLDgaLRMPcZ/nU0GevnhsCm6rnh/57bGxOb0uSThVJpwdmh8eQvx5hA1exvDAZUlITzsXVmUmT8inhumyyGZsk6WQjrT0fEM2FosqQjalofPhxVjY5rDIpq81cF1W6DYYkwchsz6M5UFQV+ubF/eeSmkH99P5BN7cVlaSMkdKeR6KZdrtkQtjeomxSmBypmB7OZZNdYCBJZzDjY784J8+pLM5jZlVxOKqLmVkZzjMqiynItY2WpN/aSOmfD5ZXMmjsvCpkUi2fNmisZWoYO3dOVJL0GhgCe0aRsBo7Es1cEwkTHzl5IWXiiXN+CFoafM4pgIKysN1cfllYHVjQfz75c0GFK78l6aw4uS2PZtrzgetIbGh7PqQtzx/azueXQF4p5A8cJeGcVxoCm4oqw5FfarsuScNuUJ/85LY8mnuaPnr/OZY3tJ3PLxvahg+04/mloX8+EOBkH12ShteQPnk0008fXB6NQk5haK9z+885hZBbEMZZcgpCeUH5SUdFZpyluCa04wYzSdKwiUQgGokQi0SIRCAWjRCNRIhGINp/XZgboygvRlF+DsV5MYrycijKi1FakENVST5VpflUl+SF6/7PJflOT0hSdp1mjGXI2Hk0jKsMHls5cd1/5JX0j5sX91+XDiorCQvFiqr6A5wqQ39ekqRhMjYzPCW6OWNAUyTixIYkjRYn2vPT/RizLZekUWNw//yUdt02XZJGjUT3GQKbbMclaTTpSSRDgFM0BDW5lZwkjVKOn0uSznNjM+BJkiRJkiRJkiRJkiRJ0qgUzXYFJEmSJEmSJEmSJEmSJOm1MuBJkiRJkiRJkiRJkiRJ0qhhwJMkSZIkSZIkSZIkSZKkUcOAJ0mSJEmSJEmSJEmSJEmjhgFPkiRJkiRJkiRJkiRJkkYNA54kSZIkSZIkSZIkSZIkjRoGPEmSJEmSJEmSJEmSJEkaNQx4kiRJkiRJkiRJkiRJkjRqGPAkSZIkSZIkSZIkSZIkadQw4EmSJEmSJEmSJEmSJEnSqGHAkyRJkiRJkiRJkiRJkqRRw4AnSZIkSZIkSZIkSZIkSaOGAU+SJEmSJEmSJEmSJEmSRg0DniRJkiRJkiRJkiRJkiSNGgY8SZIkSZIkSZIkSZIkSRo1DHiSJEmSJEmSJEmSJEmSNGoY8CRJkiRJkiRJkiRJkiRp1DDgSZIkSZIkSZIkSZIkSdKoYcCTJEmSJEmSJEmSJEmSpFHDgCdJkiRJkiRJkiRJkiRJo4YBT5IkSZIkSZIkSZIkSZJGjf8Hpb6zkRCWzdkAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 2800x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_all_boundaries(xlabelsize=15, titlesize = 20, figsize=(28, 4)):\n",
    "    sns.set_style(\"whitegrid\", {'axes.grid' : False})\n",
    "    figure, axes = plt.subplots(1,6,figsize=figsize)\n",
    "    for i in range(6):\n",
    "        plot_boundary(ax = axes[i],dataset = datasets[i])\n",
    "        axes[i].set_title(\"\")\n",
    "        #axes[i].set_title(dataset_names[i],fontsize = titlesize, fontweight='bold', fontname='Arial')\n",
    "        #axes[i].set_xlabel(\"Time\", fontsize = xlabelsize, fontname='Arial')\n",
    "        #axes[i].set_xlim(0,t_max)\n",
    "        #axes[i].set_ylim(0,3.5)\n",
    "        axes[i].set_ylabel(\"Boundaries\")\n",
    "        axes[i].tick_params(axis='both', which='major', labelsize=7)\n",
    "        \n",
    "    axes[0].text(x=-0.1, y=-0.5,s=\"Boundaries\",size=20, rotation = \"vertical\")\n",
    "\n",
    "    axes[5].legend(labels =[\"Speed\", \"Accuracy\"], loc='upper left', bbox_to_anchor=(1.03, 1),fontsize=10)\n",
    "plot_all_boundaries()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f844b550",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "d4565c75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Participant</th>\n",
       "      <th>Block</th>\n",
       "      <th>Practice</th>\n",
       "      <th>Cond</th>\n",
       "      <th>Stimulus</th>\n",
       "      <th>Frequency</th>\n",
       "      <th>Response</th>\n",
       "      <th>Time</th>\n",
       "      <th>Censor</th>\n",
       "      <th>Correct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>894</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>5798</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0.734</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>895</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>6554</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.536</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>896</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>1177</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.514</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>897</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>4796</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.466</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>898</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>1299</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.446</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22020</th>\n",
       "      <td>22020</td>\n",
       "      <td>32027</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>3232</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0.637</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22021</th>\n",
       "      <td>22021</td>\n",
       "      <td>32028</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>4696</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.584</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22022</th>\n",
       "      <td>22022</td>\n",
       "      <td>32029</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>2574</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0.824</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22023</th>\n",
       "      <td>22023</td>\n",
       "      <td>32030</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>6334</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.739</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22024</th>\n",
       "      <td>22024</td>\n",
       "      <td>32031</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>1195</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.708</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>22025 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0.1  Unnamed: 0  Participant  Block  Practice      Cond  \\\n",
       "0                 0         894            1     10         0  Accuracy   \n",
       "1                 1         895            1     10         0  Accuracy   \n",
       "2                 2         896            1     10         0  Accuracy   \n",
       "3                 3         897            1     10         0  Accuracy   \n",
       "4                 4         898            1     10         0  Accuracy   \n",
       "...             ...         ...          ...    ...       ...       ...   \n",
       "22020         22020       32027           17     20         0  Accuracy   \n",
       "22021         22021       32028           17     20         0  Accuracy   \n",
       "22022         22022       32029           17     20         0  Accuracy   \n",
       "22023         22023       32030           17     20         0  Accuracy   \n",
       "22024         22024       32031           17     20         0  Accuracy   \n",
       "\n",
       "       Stimulus  Frequency  Response   Time  Censor  Correct  \n",
       "0          5798          5         1  0.734     0.0        0  \n",
       "1          6554          6         0  0.536     0.0        1  \n",
       "2          1177          1         1  0.514     0.0        1  \n",
       "3          4796          4         0  0.466     0.0        1  \n",
       "4          1299          1         1  0.446     0.0        1  \n",
       "...         ...        ...       ...    ...     ...      ...  \n",
       "22020      3232          3         1  0.637     0.0        1  \n",
       "22021      4696          4         0  0.584     0.0        1  \n",
       "22022      2574          2         1  0.824     0.0        1  \n",
       "22023      6334          6         0  0.739     0.0        1  \n",
       "22024      1195          1         1  0.708     0.0        1  \n",
       "\n",
       "[22025 rows x 12 columns]"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Frequencies = [1,  2, 3,  4,  5,  6]\n",
    "participants = [1,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17]\n",
    "df = pd.read_csv(\"/Users/wangjiashun/Desktop/Reserach on SAT/datasets/transformed/Wagenmakers2008/SpeedAccData_new.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "643b59ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "save_dif = \"/Users/wangjiashun/Desktop/Reserach on SAT/datasets/transformed/Wagenmakers2008/dataByFreq/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "f15d68b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in Frequencies:\n",
    "    for j in range(len(participants)):\n",
    "        d = df[df[\"Frequency\"]==i]\n",
    "        d = d[d[\"Participant\"]==participants[j]]\n",
    "        d.to_csv(save_dif+\"Freq\"+str(i)+\"/sub\"+str(j+1)+\".csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "83b1d592",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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