featRegCCvalsSnippets.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "672f9f73-1c5b-4023-b03d-905d9a6bc31c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import sys, os, time, math\n",
    "sys.path.append('/home/groups/ZuckermanLab/jalim/instalLocal/celltraj/celltraj')\n",
    "import jcTrajectory_CP as cellTraj\n",
    "import h5py, pickle, subprocess\n",
    "import umap, scipy, json \n",
    "from csaps import csaps\n",
    "import string, ast \n",
    "from joblib import dump, load\n",
    "from datetime import date\n",
    "from mpl_toolkits.axes_grid1 import make_axes_locatable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2a52c36b-847b-4526-a3a3-074893cc5c61",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.datasets import make_classification, make_regression\n",
    "from sklearn.feature_selection import RFECV\n",
    "from sklearn.linear_model import LogisticRegression, LinearRegression, Lasso, LassoCV\n",
    "from sklearn.model_selection import StratifiedKFold, KFold, train_test_split\n",
    "from sklearn.ensemble import RandomForestRegressor \n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from sklearn.decomposition import PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "64b0e3fb-b76b-41fc-af6c-e345a4517459",
   "metadata": {},
   "outputs": [],
   "source": [
    "trajl = 41\n",
    "wellsInfo = 'Awells'\n",
    "conditions = ['A2'] # LIGANDS or CONDITIONS\n",
    "tmSet = ['EGF1']\n",
    "n_conditions = len(tmSet) # Total number of Ligand Conditions\n",
    "today = date.today()\n",
    "date2day = today.strftime(\"%b%d-%Y\")\n",
    "sysName = 'LI204601_P'\n",
    "figid = f\"{sysName}_{date2day}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "573ebe5b-10e7-4c89-a4e1-9f014ac6416d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Indices for the ligands \n",
    "inds_tmSet = [i for i in range(n_conditions)]\n",
    "inds_tmSet = np.array(inds_tmSet).astype(int)\n",
    "nfovs = 1\n",
    "fovs = [i for i in range(1, nfovs + 1)]\n",
    "fovs = np.array(fovs).astype(int)\n",
    "dateSet = ['']\n",
    "pathSet = ['/home/groups/ZuckermanLab/jalim/LI204601_INCUCYTE/segsCellPose/bayesianTrackTest/']\n",
    "imagingSet = [0 for i in range(n_conditions)]\n",
    "modelList = [None]*(nfovs*(n_conditions))\n",
    "modelList_conditions = np.zeros(nfovs*(n_conditions)).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0bf28618-ac83-4dda-8632-e4b99d9686d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "i = 0\n",
    "icond = 0\n",
    "for cond in conditions:\n",
    "    modelList_conditions[i] = icond\n",
    "    modelList[i] = pathSet[imagingSet[icond]]+sysName+'_'+cond+'_'+str(fovs[0])+dateSet[imagingSet[icond]]\n",
    "    #print(\"Models: \",modelList[i])\n",
    "    i = i + 1\n",
    "    icond = icond + 1\n",
    "\n",
    "nmodels = len(modelList)\n",
    "modelSet = [None]*nmodels\n",
    "indgood_models = np.array([]).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1186e6e6-bcfe-4f25-b1fb-74693993ad78",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loaded /home/groups/ZuckermanLab/jalim/LI204601_INCUCYTE/segsCellPose/bayesianTrackTest/LI204601_P_A2_1.obj with 51054 cells\n"
     ]
    }
   ],
   "source": [
    "for i in range(nmodels):\n",
    "    try:\n",
    "        objFile = modelList[i]+'.obj'\n",
    "        objFileHandler = open(objFile,'rb')\n",
    "        modelSet[i] = pickle.load(objFileHandler)\n",
    "        print(f\"loaded {objFile} with {modelSet[i].cells_indSet.size} cells\")\n",
    "        objFileHandler.close()\n",
    "        test = len(modelSet[i].linSet)\n",
    "        indgood_models = np.append(indgood_models,i)\n",
    "    except:\n",
    "        print(\"ERROR in reading *.obj files\")\n",
    "        sys.exit(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f3cb6c82-bd37-4b87-85e0-1121406521c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "n_frames = 193 # Total number of frames (image snapshots) in one condition per FOVs\n",
    "cellnumber_stdSet = np.ones(nmodels)*np.inf\n",
    "# range of frame indices where cell numbers are higher: ~70-98%\n",
    "sframe = 70.*n_frames/100.; sframe = math.ceil(sframe)\n",
    "eframe = 98.5*n_frames/100.; eframe = math.ceil(eframe)\n",
    "cellnumber_frames = np.arange(sframe, eframe).astype(int)\n",
    "cellnumber_std_cut = .50 # This was set to 0.10 by Jeremy \n",
    "frames = np.arange(n_frames)\n",
    "# Abscissas at which smoothing will be done using CSAPS package\n",
    "abSmooth = np.linspace(frames[0], frames[-1], 10000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ec51aca4-8c01-491d-a585-ca8c22f84243",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in indgood_models:\n",
    "    ncells = np.zeros(n_frames)\n",
    "    ncells_smooth = np.zeros_like(ncells)\n",
    "    for iS in range(n_frames):\n",
    "        ncells[iS] = np.sum(modelSet[i].cells_frameSet == iS)\n",
    "    # Cubic Spline Approximation (CSAPS) to smoothen the data\n",
    "    splfov = csaps(frames, ncells/ncells[0], abSmooth, smooth = 0.98) # Scaled by ncells[0] to avoid large numbers\n",
    "    ncells_smooth = splfov*ncells[0] # smoothened cell numbers reverse scaled back to original\n",
    "    cellnumber_std = np.std(ncells[cellnumber_frames] - ncells_smooth[cellnumber_frames])/np.mean(ncells[cellnumber_frames])\n",
    "    cellnumber_stdSet[i] = cellnumber_std # Standard Deviation in Cell Numbers\t\t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ecdaec06-322c-49db-95dd-908ee14e33cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "indhigh_std = np.where(cellnumber_stdSet > cellnumber_std_cut)[0]\n",
    "indgood_models = np.setdiff1d(indgood_models, indhigh_std)\n",
    "\n",
    "inds_tmSet_models = np.zeros(nmodels).astype(int)\n",
    "inds_imagingSet_models = np.zeros(nmodels).astype(int)\n",
    "i = 0\n",
    "icond = 0\n",
    "for cond in conditions:\n",
    "    inds_tmSet_models[i] = inds_tmSet[icond] # Assign indices \"tmSet\" to all FOVs\n",
    "    inds_imagingSet_models[i] = imagingSet[icond]\n",
    "    icond = icond + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "18dd83b6-3f21-4ba4-a0f4-3bba0626a7ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in indgood_models:\n",
    "    if inds_imagingSet_models[i] == 0:\n",
    "        modelSet[i].Xf[np.isnan(modelSet[i].Xf)] = 0.0 #just replace with zeros for now? Not sure best..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c2d04cff-6e16-4a08-ab86-c70e19880421",
   "metadata": {},
   "outputs": [],
   "source": [
    "n_COMfeatures = 3\n",
    "Xf_com0 = np.zeros((0, n_COMfeatures))\n",
    "for i in indgood_models:\n",
    "    if inds_imagingSet_models[i] == 0:\n",
    "        Xf_com0 = np.append(Xf_com0,modelSet[i].Xf_com, axis = 0)\n",
    "\n",
    "av_dx = np.nanmean(Xf_com0[:, 0])\n",
    "std_dx = np.nanstd(Xf_com0[:, 0])\n",
    "for i in indgood_models:\n",
    "    modelSet[i].Xf_com[:, 0] = (modelSet[i].Xf_com[:, 0] - av_dx)/std_dx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "875bd2f1-ca97-4271-b2f3-899fedb5b975",
   "metadata": {},
   "outputs": [],
   "source": [
    "wctm = cellTraj.Trajectory() # import Trajectory object \n",
    "# Cell features: Zernike (49), Haralick (13), Shape (15), Boundary (15) --> total 92\n",
    "n_features = modelSet[indgood_models[0]].Xf.shape[1]\n",
    "Xf = np.zeros((0, n_features))\n",
    "indtreatment = np.array([])\n",
    "indcellSet = np.array([])\n",
    "for i in indgood_models:\n",
    "    if inds_imagingSet_models[i] == 0:\n",
    "        Xf = np.append(Xf, modelSet[i].Xf, axis = 0)\n",
    "        # Indices for each model for later access using them\n",
    "        indtreatment = np.append(indtreatment, i*np.ones(modelSet[i].Xf.shape[0])) \n",
    "        indcellSet = np.append(indcellSet, modelSet[i].cells_indSet)\n",
    "\n",
    "indtreatment = indtreatment.astype(int)\n",
    "indcellSet = indcellSet.astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "aed0a851-2944-4692-90e8-0fc4709c69c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in indgood_models:\n",
    "    if inds_imagingSet_models[i] == 0:\n",
    "        indsf = np.where(indtreatment == i)[0]\n",
    "        modelSet[i].Xf = Xf[indsf, :]\n",
    "\n",
    "indgood_models = indgood_models[np.where(inds_imagingSet_models[indgood_models] == 0)[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a100986a-5af5-4272-87c1-92bfba4412e9",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tracked cell 50891, 25 tracks, 46600 left\n",
      "tracked cell 50763, 23 tracks, 42400 left\n",
      "tracked cell 50735, 51 tracks, 41500 left\n",
      "tracked cell 50076, 1 tracks, 37700 left\n",
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      "tracked cell 2900, 1 tracks, 700 left\n",
      "tracked cell 584, 3 tracks, 100 left\n",
      "tracked cell 13, 1 tracks, 0 left\n"
     ]
    }
   ],
   "source": [
    "self = wctm\n",
    "all_trajSet = [None]*nmodels\n",
    "for i in indgood_models:\n",
    "    modelSet[i].get_unique_trajectories()\n",
    "    all_trajSet[i] = modelSet[i].trajectories.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7f02430f-8987-4fa7-8d87-de31aa7526cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get snippets along with their full single-cell trajectory indices  \n",
    "def get_snippets_with_traj_inds(self, seg_length): \n",
    "    n_sctraj = len(self.trajectories) # Number of Single-Cell Trajectories \n",
    "    traj_segSet = np.zeros((0, seg_length)).astype(int)\n",
    "    ind_map_snippet_fulltraj = np.array([])\n",
    "    for ind_traj in range(n_sctraj):\n",
    "        cell_traj = self.trajectories[ind_traj] # Select a single-cell trajectory \n",
    "        traj_len = cell_traj.size\n",
    "        #print(\"Length of a Single-Cell Trajectory:\",traj_len)\n",
    "        if traj_len >= seg_length:\n",
    "            for ic in range(traj_len - seg_length):\n",
    "                traj_seg = cell_traj[ic:ic+seg_length]\n",
    "                traj_segSet = np.append(traj_segSet, traj_seg[np.newaxis, :], axis = 0)\n",
    "                # Save indices of all snippets corresponding to \"FULL\" single-cell trajectory \n",
    "                ind_map_snippet_fulltraj = np.append(ind_map_snippet_fulltraj, ind_traj)\n",
    "                #print(\"Indices to map snippets to the full trajectory:\",ind_map_snippet_fulltraj)\n",
    "    return ind_map_snippet_fulltraj, traj_segSet"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e8af0e6-7889-4983-a9ae-764e45f7747a",
   "metadata": {},
   "source": [
    "Single-cell Trajectories Over The Cell Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "cd8ec5cf-aa27-48f3-b1e2-6bb492d0b7b8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "building trajectory data for model 0...\n"
     ]
    }
   ],
   "source": [
    "Xf_traj = np.zeros((0, n_features*trajl + n_COMfeatures*trajl))\n",
    "indtreatment_traj = np.array([])\n",
    "indstack_traj = np.array([])\n",
    "indframes_traj = np.array([])\n",
    "indmodel_traj_snippets = np.array([])\n",
    "for i in indgood_models:\n",
    "    print('building trajectory data for model {}...'.format(i))\n",
    "    modelSet[i].trajectories = all_trajSet[i].copy() # ALL Single-Cell trajectories \n",
    "    modelSet[i].trajl = trajl # Trajectory snippet length \n",
    "    # Get trajectory snippets of (all trajectories) a given length in a sliding window and mapped with single-cell trajectory indices \n",
    "    modelSet[i].snippet_map_fulltraj_inds, modelSet[i].traj = get_snippets_with_traj_inds(modelSet[i], trajl)\n",
    "    # Xpca (feature info) along the single-cell trajectory snippets, extracted directly from cell indices unique within a 'model' \n",
    "    data = modelSet[i].Xf[modelSet[i].traj, :] \n",
    "    datacom = modelSet[i].Xf_com[modelSet[i].traj, :]\n",
    "    data = data.reshape(modelSet[i].traj.shape[0], modelSet[i].Xf.shape[1]*trajl)\n",
    "    datacom = datacom.reshape(modelSet[i].traj.shape[0], modelSet[i].Xf_com.shape[1]*trajl)\n",
    "    data = np.append(data, datacom, axis = 1)\n",
    "    indgood = np.where(np.sum(np.isnan(data), axis = 1) == 0)[0] # Consider models as \"Good\" that don't have NaN in \"data\" \n",
    "    data = data[indgood, :]\n",
    "    modelSet[i].traj = modelSet[i].traj[indgood, :] # Cleaned trajectory snippets if any NaN \n",
    "    modelSet[i].snippet_map_fulltraj_inds = modelSet[i].snippet_map_fulltraj_inds[indgood]\n",
    "    # Store all trajectory snippets of a given length (picked in a sliding window) \n",
    "    Xf_traj = np.append(Xf_traj, data, axis = 0) \n",
    "    indtreatment_traj = np.append(indtreatment_traj, i*np.ones(data.shape[0])) # Indices of Treatments (Models) Along Trajectory Snippets \n",
    "    indstacks = modelSet[i].cells_imgfileSet[modelSet[i].traj[:, 0]]\n",
    "    indstack_traj = np.append(indstack_traj, indstacks)\n",
    "    ind_frames = modelSet[i].cells_frameSet[modelSet[i].traj[:, 0]].astype(int) # Frame indices at the start of snippets\n",
    "    ind_frames = ind_frames + trajl # Frame indices at the end of snippets\n",
    "    indframes_traj = np.append(indframes_traj, ind_frames) # Starting Frame Indices of ALL snippets\n",
    "    indtraj_snippets = modelSet[i].snippet_map_fulltraj_inds\n",
    "    indmodel_traj_snippets = np.append(indmodel_traj_snippets, indtraj_snippets) # Save for all models: map of snippets to the sc trajectories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "029bb752-e710-452d-aedb-7a0e90c66ebf",
   "metadata": {},
   "outputs": [],
   "source": [
    "inds_conditions = [None]*n_conditions\n",
    "for imf in range(n_conditions):\n",
    "    indmodels = np.intersect1d(indgood_models, np.where(inds_tmSet_models == imf)[0])\n",
    "    indstm = np.array([])\n",
    "    for im in indmodels:\n",
    "        indtm = np.where(indtreatment_traj == im)\n",
    "        indstm = np.append(indstm, indtm)\n",
    "    inds_conditions[imf] = indstm.astype(int).copy() # Condition (Model) specific trajectory snippet indices: Add up all FOVs\n",
    "    #print(inds_conditions[imf])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1a879dfb-17e9-433c-9006-9f3c16d53fef",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get Cross correlations & respective frame numbers along all single-cell trajectories\n",
    "def get_cross_corr_all_single_cell_trajs(filename):\n",
    "      cross_corr_sctraj = []\n",
    "      frame_num_sctraj = []\n",
    "      with open(filename, 'r') as file_in:\n",
    "          # Create an iterator over the file lines \n",
    "          file_iter = iter(file_in)\n",
    "          try:\n",
    "              while True:\n",
    "                  # Read two lines at a time: Cross correlations & the corresponding frame numbers\n",
    "                  line1 = next(file_iter).strip()\n",
    "                  if line1:\n",
    "                          data = ast.literal_eval(line1)\n",
    "                          cross_corr_sctraj.append(data)\n",
    "                          line2 = next(file_iter).strip()\n",
    "                          # Parse line2 as a list of integers\n",
    "                          frame_numbers = ast.literal_eval(line2)   \n",
    "                          frame_num_sctraj.append(frame_numbers)\n",
    "          except StopIteration:\n",
    "              # End of file reached\n",
    "              pass\n",
    "      cross_corr_all_sctraj_file = cross_corr_sctraj\n",
    "      frame_num_all_sctraj_file = frame_num_sctraj\n",
    "      \n",
    "      return cross_corr_all_sctraj_file, frame_num_all_sctraj_file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e896d537-cdd3-47d5-b4d9-401dd78e65a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get cross-correlation values along all single-cell trajectories (sorted as per trajectory length) \n",
    "cc_path = '/home/groups/ZuckermanLab/jalim/LI204601_INCUCYTE/dcompCCtraj_states/'\n",
    "cc_filename = f\"{cc_path}{sysName}_{conditions[0]}_1.dat\"\n",
    "cross_correlations, frame_numbers = get_cross_corr_all_single_cell_trajs(cc_filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "36f83254-c658-4f2a-a6e9-35c3f6258ec1",
   "metadata": {},
   "outputs": [],
   "source": [
    "cc_values_last_frames = []\n",
    "for cond in range(n_conditions):\n",
    "    indstm = inds_conditions[cond] # Condition Specific Indices\n",
    "    fid_snippets = indframes_traj[indstm].astype(int) # Map frame indices of snippets\n",
    "    indc_map_fulltraj_snippets = indmodel_traj_snippets[indstm].astype(int) # Map Indices of Full Trajectory to Snippets \n",
    "    ################## Identify the \"FULL\" trajectory index and locate snippets within it ##################\n",
    "    for j, ind_fulltraj in enumerate(indc_map_fulltraj_snippets):\n",
    "        possible_indices = np.where(frame_numbers[ind_fulltraj] == fid_snippets[j])  \n",
    "        indc_ccvals_traj = possible_indices[0][0]\n",
    "        #print(f'Indices of Entire Traj: {ind_fulltraj}, Indices of CC_traj: {indc_ccvals_traj}')\n",
    "        cc_vals = cross_correlations[ind_fulltraj][indc_ccvals_traj]\n",
    "        #print(f'CC values: {cc_vals}, Indices of Entire Traj: {ind_fulltraj}, Indices of CC trajectory: {indc_ccvals_traj}')\n",
    "        cc_values_last_frames.append(cc_vals)\n",
    "cc_values_last_frames = np.array(cc_values_last_frames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8116231e-f0be-4c94-82b6-5884c9e6ed3d",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = Xf_traj\n",
    "y = cc_values_last_frames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "88974c7e-6ae3-42ba-9135-ae72f5941a07",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Features afer PCA: 178\n"
     ]
    }
   ],
   "source": [
    "pca = PCA(n_components = 0.95)\n",
    "pca.fit(X) \n",
    "Xpca = pca.transform(X)\n",
    "print(f\"Number of Features afer PCA: {Xpca.shape[1]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "449e3a49-a2bf-498a-8ee0-1ab2ac6cfed8",
   "metadata": {},
   "source": [
    "Split data into training and testing to evaluate performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "19b73d91-ab50-4a5d-939f-31c2b68bf9e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(Xpca, y, test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "9f1527b2-a24a-4e06-b344-126209b0a296",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Variance of the data: 0.059469900056613276\n",
      "Standard deviation of the data: 0.24386451167936116\n"
     ]
    }
   ],
   "source": [
    "data = y\n",
    "variance = np.var(data)\n",
    "std_dev = np.std(data)\n",
    "print(f\"Variance of the data: {variance}\")\n",
    "print(f\"Standard deviation of the data: {std_dev}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "83d4e1d6-3d8f-44f1-9237-7a0b7fa15067",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Outliers: [-0.0454792  -0.01339921 -0.02996746 -0.02550145 -0.06179683 -0.15184884\n",
      " -0.29954489 -0.10761754 -0.08122208 -0.14067389 -0.17617326 -0.14803883\n",
      " -0.1671993  -0.03675874 -0.01703297 -0.26386195 -0.2050052  -0.01946207\n",
      " -0.00607028 -0.03194076 -0.00973431  0.00574344 -0.04060136 -0.002814\n",
      " -0.02852579 -0.02852579], Length of Outliars: 26\n",
      "Non-outliers: [0.3779671  0.34464673 0.32360622 ... 0.32859432 0.38018489 0.4266384 ], Length of non-outliars: 6475\n"
     ]
    }
   ],
   "source": [
    "threshold = 2.5 * std_dev\n",
    "mean_data = np.mean(data)\n",
    "# Identify outliers: Data beyond \"mean +/- 2*standard_deviation\"\n",
    "outliers = data[(data < mean_data - threshold) | (data > mean_data + threshold)] \n",
    "non_outliers = data[(data >= mean_data - threshold) & (data <= mean_data + threshold)]\n",
    "print(f\"Outliers: {outliers}, Length of Outliars: {len(outliers)}\")\n",
    "print(f\"Non-outliers: {non_outliers}, Length of non-outliars: {len(non_outliers)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "2477723d-3b30-4d20-b64d-859a14cfa68d",
   "metadata": {},
   "outputs": [],
   "source": [
    "non_outlier_condition = (data >= mean_data - threshold) & (data <= mean_data + threshold)\n",
    "non_outlier_indices = np.where(non_outlier_condition)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c2b2a370-2b5a-4811-9bb5-6a5153753c34",
   "metadata": {},
   "outputs": [],
   "source": [
    "cc_vals_non_outliers = y[non_outlier_indices]\n",
    "X_non_outliers = Xpca[non_outlier_indices]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d5e5bba8-af54-403d-a191-35cbe4ac2f6c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split Non-Outlier Data Into Training & Test Sets \n",
    "X_train_no, X_test_no, y_train_no, y_test_no = train_test_split(X_non_outliers, \n",
    "                                                                cc_vals_non_outliers,\n",
    "                                                                test_size = 0.2,\n",
    "                                                                random_state = 42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "0cc9b99a-ea1f-49a2-9a96-e2dfec9b3335",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_bins = 50\n",
    "plt.figure(figsize=(9, 6))\n",
    "plt.hist(non_outliers, bins=n_bins, density = True, alpha=0.5, color = 'g', label='Non-Outliers')\n",
    "plt.hist(outliers, bins=n_bins,  density = True, alpha=0.5, color='r', label='Outliers')\n",
    "\n",
    "plt.xlabel('CC Values')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Histogram of Outliers and Non-Outliers of CC Values')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9bcb604-cb30-4804-8a98-6644bbe7db56",
   "metadata": {},
   "source": [
    "See How Test & Training Sets Differ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "d8398eac-9c81-4cc4-a123-e1930af00ff1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "counts, bins = np.histogram(y, n_bins, density=True)\n",
    "plt.plot(bins[:-1], counts, 'k', label = 'Training + Test')\n",
    "counts, bins = np.histogram(y_train, n_bins, density=True)\n",
    "plt.plot(bins[:-1], counts, 'r', label = 'Training Set')\n",
    "counts, bins = np.histogram(y_test, n_bins, density=True)\n",
    "plt.plot(bins[:-1], counts, 'b', label = 'Test Set')\n",
    "plt.xlabel('CC Values')\n",
    "plt.ylabel('Probability density')\n",
    "plt.title('EGF_1')\n",
    "plt.legend(loc = 'best')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "3c2a74ad-f41a-4358-82d5-e9cb08049ad2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "counts, bins = np.histogram(cc_vals_non_outliers, n_bins, density=True)\n",
    "plt.plot(bins[:-1], counts, 'k', label = 'Training + Test')\n",
    "counts, bins = np.histogram(y_train_no, n_bins, density=True)\n",
    "plt.plot(bins[:-1], counts, 'r', label = 'Training Set')\n",
    "counts, bins = np.histogram(y_test_no, n_bins, density=True)\n",
    "plt.plot(bins[:-1], counts, 'b', label = 'Test Set')\n",
    "plt.xlabel('non-outliers CC Values')\n",
    "plt.ylabel('Probability density')\n",
    "plt.title('EGF_1')\n",
    "plt.legend(loc = 'best')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "3a66a24e-836f-4703-8db9-18994efaa352",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best alpha: 0.0013818764994801952\n",
      "Mean Squared Error: 0.05031970770707699\n"
     ]
    }
   ],
   "source": [
    "model_lasso = LassoCV(alphas=None, cv=10, max_iter=10000, n_jobs=-1) # Least Absolute Shrinkage and Selection Operator\n",
    "model_lasso.fit(X_train, y_train)\n",
    "\n",
    "print(f\"Best alpha: {model_lasso.alpha_}\") # Best alpha\n",
    "y_pred_lasso = model_lasso.predict(X_test)\n",
    "mse_lasso = mean_squared_error(y_test, y_pred_lasso)\n",
    "print(f\"Mean Squared Error: {mse_lasso}\")\n",
    "#print(f\"Coefficients: {model_lasso.coef_}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "10e46032-db30-4281-8123-3371ab202322",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10, 8))\n",
    "plt.scatter(y_test, y_pred_lasso, s=1)\n",
    "plt.xlabel('Actual values')\n",
    "plt.ylabel('Predicted values')\n",
    "plt.title('Predicted vs. Actual values: Lasso')\n",
    "plt.grid(True)\n",
    "\n",
    "# Calculate the range to include both actual and predicted values\n",
    "min_val = min(y_test.min(), y_pred_lasso.min())\n",
    "max_val = max(y_test.max(), y_pred_lasso.max())\n",
    "line_coords = np.linspace(min_val, max_val, 100)\n",
    "\n",
    "plt.plot(line_coords, line_coords, color='red', linestyle='--')  # Perfect prediction\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "ac0f057c-e4db-4325-8bab-e5b0e1a0e38b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best alpha: 0.001536545223963504\n",
      "Mean Squared Error: 0.04222363660125557\n"
     ]
    }
   ],
   "source": [
    "model_lasso = LassoCV(alphas=None, cv=10, max_iter=10000, n_jobs=-1) # Least Absolute Shrinkage and Selection Operator\n",
    "model_lasso.fit(X_train_no, y_train_no)\n",
    "\n",
    "print(f\"Best alpha: {model_lasso.alpha_}\") # Best alpha\n",
    "y_pred_lasso_no = model_lasso.predict(X_test_no)\n",
    "mse_lasso_no = mean_squared_error(y_test_no, y_pred_lasso_no)\n",
    "print(f\"Mean Squared Error: {mse_lasso_no}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "7ebd7e1b-5ebb-4d33-8c50-98b76061ad70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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WDd26dUNGRgbi4+Mxffp09OvXD1WrVkWzZs2kLhoAYP78+QCA0aNH5w4u4fz/Dh06+LweATHZyMjIKPC+8zZcsmQJ2rRpg7i4uHzva9lgBPK24aVLlwr8LykpCYUKFUKpUqVkTXPy5Mn5nuvlXKalzCssLMzlelP7XhKpZd3O3b1OderUwddffw1BEHD06FEsWrQIb731FsLDwzFhwgSX32nYsCFKly6NdevWYfr06V7vo+rQoQM+++wzrF271u00pRgyZAjef/99fP311+jduzfWr1+P0aNH57uS6Ut5tF/NzcjIyE22gYLbTs66j4qKyt1vf//9d3zzzTeYPHky7ty5g08//dRrTHKlpKTg+++/R2xsbL51nZGRkXt/mV1ERASmTJmSO3S9/WpV165d8dtvv0mK33HfcD6Bk5SUlLuuiIhXqIgIQJcuXfDvv/8iOzsbDRs2LPBTs2ZNAMgdqWzp0qX5vv/NN994HYzhvvvuQ40aNbBgwQKXjVI75ysLdh06dEBwcDBOnz7tMkZ7IlmzZk1UrFgRy5cvhyAIud9PTEzE3r17pa0QiA28X375Bbt378Z3332HQYMG5WvcOcfcunVrvPvuuwDgctRBT06ePIl9+/ahZ8+e+Omnnwr8PPLII1i3bh3+/fdfn9cjII7md/To0Xzvbd++HTdv3sz3ns1my9f4BICjR49q/sykmjVrolKlSli2bFm+bXjr1i2sWrUqdzQ+OapWreqyTMuZV9WqVfH333/nXsUAxAEhNm/eXGB+oaGhiq+aSC3rUtlsNjz00EOYPXs2SpYs6fFBuyEhIXj11Vfx22+/YerUqS4/8/fff2PPnj0AxJMKderUwfTp03H8+HGXn9+8ebPXbpO1atVCkyZNsHDhQixbtgwZGRn5rgjbl0NpebSPzuhc7r/77rt8r5Wu+/vuuw9vvPEG6tSpo9mDjG02GwRBKLAOvvjii9wurK6UL18egwcPRt++fXHq1CmX28JV/O3atQMgJrKODhw4gJMnT+Ze5SUiXqEiIgB9+vTB0qVL0alTJ/zf//0fGjdujJCQEPz111/46aef0K1bN/To0QO1atVC//79MWfOHISEhODRRx/F8ePHMXPmzAJdjlz55JNP0LVrVzRt2hRjxozB3XffjfPnz2Pz5s25SVqdOnUAAB9++CEGDRqEkJAQ1KxZE1WrVsVbb72F119/HWfOnMFjjz2GUqVK4cqVK9i/f3/uGdlChQph6tSpePbZZ9GjRw8899xzSE5OxuTJkyV3+QOAvn37YuzYsejbty8yMjIK3EcwadIk/PXXX3jkkUdQuXJlJCcn48MPP0RISAhat26d+7ng4GC0bt3a4/0G9rPEr7zyCho3blzg/zdu3MC2bduwZMkS/N///Z9P67FYsWIYMGAA3nzzTUyaNAmtW7fGiRMn8PHHH6NEiRL55tulSxdMnToVsbGxaN26NU6dOoW33noL1apV82k0Q28KFSqE9957D08//TS6dOmCYcOGISMjA++//z6Sk5MxY8YMQ+bVu3dvTJo0CX369MH48eNx+/ZtzJ0712Vjtk6dOtixYwe+++47VKxYEcWKFctN4ryRWtY9+f777zFv3jx0794d1atXhyAIWL16NZKTk9G+fXuP3x0/fjxOnjyJ2NhY7N+/H/369UOVKlWQkpKCnTt34rPPPsOUKVPQokULBAUFYc2aNYiJiUGzZs0wYsQItG3bFhEREUhMTMTKlSvx3XffSeo2+cwzz2DYsGFISkpC8+bNC6wvX8pjp06dULp0aQwdOhRvvfUWgoODsWjRIly4cCHf56Su+6NHj+LFF1/EU089hXvvvReFCxfG9u3bcfTo0XxXjxYvXoxnnnkGCxYskHQfVWpqKlauXFng/bJly6J169Z4+OGH8f7776NMmTKoWrUqfv75Z8yfPx8lS5bM9/kmTZqgS5cuqFu3LkqVKoWTJ0/iq6++yj1BICX+mjVr4vnnn8dHH32EQoUKoWPHjjh37hzefPNNVKlSRfIomkQBwcgRMYhIHfaRqg4cOODxc4MGDRIiIiJc/i8zM1OYOXOm8NBDDwlhYWFC0aJFhfvvv18YNmyY8Mcff+R+LiMjQ3j55ZeFcuXKCWFhYULTpk2Fffv2FRghztVoZoIgCPv27RM6duwolChRQggNDRVq1KhRYNTAiRMnCpGRkUKhQoUKTGPt2rVC27ZtheLFiwuhoaFCVFSU8OSTTwo//vhjvml88cUXwr333isULlxYuO+++4QFCxa4HaXNnX79+gkAhBYtWhT43/fffy907NhRqFSpklC4cGGhXLlyQqdOnYRdu3bl+xwAoXXr1m7ncefOHaFcuXJCvXr13H4mKytLqFy5slCnTp3c93xZjxkZGcIrr7wiVKlSRQgPDxdat24tHDlypMA2zMjIEMaNGydUqlRJCAsLExo0aCCsXbvW5XqEjFH+3n///QL/c/X9tWvXCk2aNBHCwsKEiIgI4ZFHHhH27NmT7zP20dv++eeffO87j97mjZR5CYIgbNy4UahXr54QHh4uVK9eXfj4449djiB35MgRoUWLFkKRIkXylQEpo/w5xuStrLvbp3/77Tehb9++Qo0aNYTw8HChRIkSQuPGjYVFixZJWh+CIAjr1q0TOnfuLJQtW1YIDg4WSpUqJbRt21b49NNPhYyMjHyfTU5OFqZOnSo0aNBAKFq0qBASEiLcfffdQv/+/V2uR1dSUlKE8PBwAYDw+eefF/i/r+Vx//79QvPmzYWIiAihUqVKQmxsrPDFF1+4LCfe1v2VK1eEwYMHC/fff78QEREhFC1aVKhbt64we/bsfCNY2svhwoULvS5/69atBQAuf+zl56+//hJ69uwplCpVSihWrJjw2GOPCcePHy+w706YMEFo2LChUKpUKSE0NFSoXr26MGbMmNxRSqXGn52dLbz77rvCfffdJ4SEhAhlypQR+vfvL1y4cMHr8hAFEpsgOPRxICIiIiIiIsl4DxUREREREZFCTKiIiIiIiIgUYkJFRERERESkEBMqIiIiIiIihZhQERERERERKcSEioiIiIiISKGAe7BvTk4OkpKSUKxYMdhsNqPDISIiIiIigwiCgBs3biAyMhKFCim81mTkQ7B+/vlnoUuXLkLFihUFAMKaNWu8fmfHjh1CgwYNhNDQUKFatWpCXFycrHleuHDB7YPz+MMf/vCHP/zhD3/4wx/+BN6PLw+sNvQK1a1bt/DQQw9hyJAh6Nmzp9fPnz17Fp06dcJzzz2HJUuWYM+ePRg5ciTKli0r6fsAUKxYMQDAhQsXULx4cZ/iJ88yMzOxZcsWxMTEICQkxOhwiFxiOSWzYxklK2A5JStwVU5TU1NRpUqV3BxBCUMTqo4dO6Jjx46SP//pp5/i7rvvxpw5cwAAtWrVwsGDBzFz5kzJCZW9m1/x4sWZUGksMzMTRYoUQfHixVm5kmmxnJLZsYySFbCckhV4Kqe+3ApkqXuo9u3bh5iYmHzvdejQAfPnz0dmZqbLHTgjIwMZGRm5r1NTUwGIKzQzM1PbgAOcff1yPZOZsZyS2bGMkhWwnJIVuCqnapRZSyVUly9fRvny5fO9V758eWRlZeHq1auoWLFige9Mnz4dU6ZMKfD+li1bUKRIEc1ipTxbt241OgQir1hOyexYRskKWE7JChzLaVpams/Ts1RCBRS8HCcIgsv37SZOnIixY8fmvrb3k4yJiWGXP41lZmZi69ataN++PS//k2mxnJLZsYySFbCckhW4Kqf23mu+sFRCVaFCBVy+fDnfe3///TeCg4Nx1113ufxOaGgoQkNDC7wfEhLCHV4nXNdkBSynZHYso2QFLKdkBY7lVI3yaqkH+zZr1qzApeQtW7agYcOG3HmJiIiIiEh3hiZUN2/exJEjR3DkyBEA4rDoR44cwfnz5wGI3fUGDhyY+/nhw4cjMTERY8eOxcmTJ7FgwQLMnz8f48aNMyJ8IiIiIiIKcIZ2+Tt48CDatm2b+9p+r9OgQYOwaNEiXLp0KTe5AoBq1aph48aNGDNmDD755BNERkZi7ty5kodMJyIiIiIiUpOhCVWbNm1yB5VwZdGiRQXea926NQ4dOqRhVERERERERNJY6h4qIiIiIiIiM2FCRUREREREpBATKiIiIiIiIoWYUBERERERESnEhIqIiIiIiEghJlREREREREQKMaEiIiIiIiJSiAkVERERERGRQkyoiIiIiIiIFGJCRUREREREpBATKiIiIiIiIoWYUBERERERESnEhIqIiIiIiEghJlREREREREQKMaEiIiIiIiJSiAkVERERERHpJzvb6AhUxYSKiIiIiIj0sWEDUKcOkJRkdCSqYUJFRERERETayskBpk4FunYFTp4Epk0zOiLVBBsdABERERER+bHUVGDgQGDdOvH18OHArFnGxqQiJlRERERERKSdl14Sk6nChYG4OOCZZ4yOSFVMqIiIiIiISDvTp4vd/D7+GGjc2OhoVMd7qIiIiIiISD3Z2cDmzXmvIyOBX37xy2QKYEJFRERERERquX5dHHjisceAb77Je99mMy4mjbHLHxERERER+e74caB7d+D0aSAszO+eN+UOr1AREREREZFvvvkGaNJETKaiooC9e4G+fY2OShdMqIiIiIiISJnsbODVV4HevYG0NODRR4GDB4H69Y2OTDdMqIiIiIiISJmffwbee0/8+5VXgB9+AMqUMTYmnfEeKiIiIiIiUqZdOyA2FnjgAaBXL6OjMQQTKiIiIiIikm7FCqBVK3E4dACYPNnQcIzGLn9ERERERORdZiYwejTQpw/w5JPAnTtGR2QKvEJFRERERESeXbkiDjzx88/i60cfBYKZSgBMqIiIiIiIyJP9+4EnngAuXgSKFQMWLxafN0UA2OWPiIiIiIjcWbBAvF/q4kWgZk0xuWIylQ8TKiIiIiIiKigjA5g1S7xXqnt3MZm6/36jozIddvkjIiIiIqKCQkOBNWuAVavEZ0wV4rUYV7hWiIiIiIhItGcPEBeX9/ree4EJE5hMecArVEREREREgU4QgE8/Bf7v/4DsbPFBva1bGx2VJTChIiIiIiIKZLdvAy+8IA5AAQBPPQVERxsbk4UwoSIiIiIiClQXLgA9ewIHDojd+mbMAMaNA2w2oyOzDCZURERERESBaMcOoFcv4J9/gNKlga+/Btq3Nzoqy2FCRUREREQUiH79VUym6tUDVq8GqlUzOiJLYkJFRERERBSIRo4Uh0bv1w8oUsToaCyL4x8SEREREQWCc+eAJ58EkpPF1zYb8OyzTKZ8xCtURERERET+butWoE8f4No1MYFavNjoiPwGr1AREREREfkrQQDeew947DExmWrYEHjnHaOj8iu8QkVERERE5I9u3gSeeQb49lvx9ZAhwLx5QFiYsXH5GSZURERERET+5uxZoGtXcSS/kBDgww+B4cP5fCkNMKEiIiIiIvI3RYsCN24AFSoAK1cCLVoYHZHfYkJFREREROQPBCHvClTZssD33wN33QVERhobl5/joBRERERERFaXmgr06AEsXJj3Xp06TKZ0wISKiIiIiMjKfvsNaNwYWLcOGDMm7zlTpAsmVEREREREVrV2rZhMnToFVK4sPm+qZEmjowooTKiIiIiIiKwmOxt44w2xm9+NG0Dr1kBCAtCokdGRBRwOSkFEREREZCXZ2UC3bsCGDeLr0aPFh/eGhBgaVqDiFSoiIiIiIisJCgIaNgTCw4ElS4DZs5lMGYhXqIiIiIiIrOD2bSAsTPx70iTg6aeBe+81NibiFSoiIiIiIlPLygJeeUV8OG96uvheoUJMpkyCCRURERERkVldvQo89hjw/vvAoUPiw3rJVJhQERERERGZ0eHD4r1S27YBERHAihXAU08ZHRU5YUJFRERERGQ2S5YAzZsDiYnAPfcA8fFAr15GR0UuMKEiIiIiIjKTDz8EBgwQB6Ho1Ak4cACoXdvoqMgNJlRERERERGbSvTtQtqw4kt933wElSxodEXnAYdOJiIiIiIx2+TJQoYL4d1QUcOoUUKqUsTGRJLxCRURERERkpAULgGrVgPXr895jMmUZTKiIiIiIiIxw5w4wYgQwdKh4v9SqVUZHRAqwyx8RERERkd6SksQh0PfuBWw2YOpUYOJEo6MiBZhQERERERHpac8e4MknxfumSpYEli0DOnY0OipSiAkVEREREZFefv8daNsWyMwUh0Jfs0Z8zhRZFhMqIiIiIiK93Hcf8PzzwD//APPnA0WLGh0R+YgJFRERERGRli5cAMLCxGdLAcCcOUBQkHjvFFkeR/kjIiIiItLKjh1AdDTQuzeQlSW+FxzMZMqPMKEiIiIiIlKbIIhXoh59VOzed/06cO2a0VGRBphQERERERGpKS0NGDAAGDMGyM4G+vcXR/YrV87oyEgDvIeKiIiIiEgtZ88CTzwBHDki3ic1axbw0kvs4ufHmFAREREREalBEIB+/cRkqmxZ4NtvgdatjY6KNMYuf0REREREarDZgC++EJ8zlZDAZCpAMKEiIiIiIlLq5k1g06a81w8+CGzfDlSpYlxMpCsmVERERERESvzxB9C0KdC1K7Brl9HRkEGYUBERERERybVhA9CoEfDrr0CZMuKzpSggMaEiIiIiIpIqJwd46y3xqlRKCtC8OXDoENCsmdGRkUGYShMRERERSZGSAgwcCKxfL74eMUJ8eG/hwoaGRcZiQkVEREREJMWKFWIyVbgwEBcHPPOM0RGRCTChIiIiIiKS4rnngBMnxGdNNW5sdDRkEryHioiIiIjIlexs4MMPgRs3xNc2m9jFj8kUOWBCRURERETk7Pp1ceCJ0aOBIUMAQTA6IjIpdvkjIiIiInJ07BjQowdw+jQQFgZ07y5enSJygVeoiIiIiIjsvvlGfFjv6dNAVBSwdy/Qv7/sySyJT0SLGduxJD5RgyDVZ7V4zYQJFRERERFRVhYwfjzQuzeQlgY8+ihw8CBQv76iycXtOI2LyemI23Fa5UC1YbV4zYQJFRERERHRtWvAkiXi36+8AvzwA1CmjOLJjWhTA5VKhmNEmxoqBagtq8VrJryHioiIiIioXDlsmvIJ9uw4gpo9hqJ/sG/N5P5No9C/aZRKwWnPavGaCa9QEREREVFg+uor4Ntvc19OvVYSX93dhN3evOD9VvkxoSIiIiKiwJKZCfzf/wEDBwKDBwN//gmA3d6k4v1W+bHLHxEREREFjitXgF69gJ07xdcvvwxUrw6A3d6kGtGmBuJ2nGbi+T9MqIiIiIgoMOzfDzzxBHDxIlCsGLB4sfiMKZKFiWd+7PJHRERERP5v/nygVSsxmbr/fjG5YjJFKmBCRURERET+79Qp4M4dMYn65RcxqSJSAbv8EREREZH/mzYNqFMHePppoBCvKZB6WJqIiIiIyP/s2QP07ClelQKA4GBgwAAmU6Q6ligiIiIi8h+CAMybB7RpA6xeDbz7rtERkZ9jlz8iIiIi8g+3bwMjRgCLFomve/UCxo41NCTyf0yoiIiIiMj6LlwQh0Q/eFDs1jdjBjBuHGCzGR0Z+Tl2+SMiIiIiy1gSn4gWM7ZjSXxi3pt79wLR0WIyVbo0sHkzMH48kynSBRMqIiIiIrKMuB2ncTE5HXE7Tue9Wa6cOPhEvXpAQgLw6KOGxUeBhwkVEREREVnGiDY1UKlkOEY8XC3vzXvuAbZtE0f2q1rVsNgoMDGhIiIiIiJLWBKfiLgdpzHuvsLoP+opYOvWvH9GRwNFihgXHAUsJlREREREZAlxO06j+uE9aNe/k9i1b9QoIDvb6LAowDGhIiIiIiLNuBxEQglBwEcXtmDRt5NRIv0G0KgRsGULEBSkTqBECjGhIiIiIiLNuBxEQq6bN4FevdBg3rsIEnKAoUOBnTuBKlUkT0K1xE7laZH1MaEiIiIiIs3kDiLRpoayCaSkAE2bAitXAiEhQFwc8PnnQFiYrMmoktipNC0mZP6FCRURERERaaZ/0yjsmdAO/ZtGKZtA8eJA48ZAxYrAzz8Dw4crer6Uz4mditNSM7kj4wUbHQARERERUT45OUB6OhARISZP8+YByclAhQqKJ9m/aZTypE7laY1oUwNxO06rktyR8XiFioiIiIjMIyUFeOIJ4Kmn8kbwCwvzKZkyC3tXPwC+XbUjU2FCRURERETmcPIk0KQJsG4dsH07cOSI0RGpil39/BMTKiIiIiIy3po14r1Sp07hVrmKGDp0FpZkljE6KlWpeR8XmQfvoSIiIiIi42RnA5MmAdOmia9bt0avli/h16ww/LbjtF91i1PzPi4yD16hIiIiIiLjjBiRl0yNHg1s3Yq+XRrySg5ZBhMqIiIiIjLO8OFA6dLAkiXA7NlASIjvQ62rwNdnRfFZU4GDCRUREZFB2OCigJXoUOYbNADOnQOeftqwcFzxdQAJud8ftfwwakzcgFHLDyuaHxmHCRUREZFBOOIXBZysLOCVV4CaNYEDB/LeL1bMuJjc8HUACbnf33A0CdmC+JushQkVERGRQTjiFwWUq1eBxx4D3n8fyMgAfvrJ6Ig88rXbobfvO1+h7lw3EkE28be7z5A5cZQ/IiIig3DELwoYhw6JD+tNTAQiIoAFC4BevYyOylCOV6j7N43C3L71MbdvfY+fIXPiFSoiIiIiykfVKyNffQW0aCEmUzVqAPHxAZ9MAdKuUKt9FdvTduXVMOWYUBERERGZgJkatKrd37dpEzBwIHD7NtCpk3jfVO3a6gTpxEzrTwopXQp96Xboan142q68p1M5JlREREREJmCmBq27KyOyk5aYGODxx4E33wS++w4oVUqDaEVarD9vy2vmJM7V+vB0xYv3dCpneEI1b948VKtWDWFhYYiOjsauXbs8fn7p0qV46KGHUKRIEVSsWBFDhgzBv//+q1O0RERERNowU4PW3ZURSUnL4cNAerr4d6FCwOrVwFtviX9rSM31Z0+UZm4+5XF5zZQEO4uOKoUgm/jbztMVLzM8+8uqDE2oVqxYgdGjR+P111/H4cOH0apVK3Ts2BHnz593+fndu3dj4MCBGDp0KH799Vd8++23OHDgAJ599lmdIyciIrI+M59dD0RWaNB6S1psCxcCTZsCw4YBgiC+GRSkS2xqrj97ogTA4/KaKQl2lpB4HdmC+Ju0ZWhCNWvWLAwdOhTPPvssatWqhTlz5qBKlSqIi4tz+fn4+HhUrVoVo0aNQrVq1dCyZUsMGzYMBw8e1DlyIiIi6zPz2XUyJ7dJS0YG6sbFIXjYMODOHeDGDfG3RdkTpXEdanpM0sycBJs52fM3hg2bfufOHSQkJGDChAn53o+JicHevXtdfqd58+Z4/fXXsXHjRnTs2BF///03Vq5cic6dO7udT0ZGBjIyMnJfp6amAgAyMzORmZmpwpKQO/b1y/VMZsZySmanZRkd8XBVzN99FkNbVlV1+isOXPjfdKuhd6Mqqk2XTCopCYV690a1X36BYLMhZ/Jk5Lz6qtjFz6J1a+/oSPSOFp8HZdXjgz8sg9pc1adqrBubINivx+orKSkJlSpVwp49e9C8efPc96dNm4Yvv/wSp06dcvm9lStXYsiQIbh9+zaysrLw+OOPY+XKlQgJCXH5+cmTJ2PKlCkF3l+2bBmKFCmizsIQERERBaDSJ0+i0XvvIez6ddyJiEDC2LH4Ozra6LCIJEtLS0O/fv2QkpKC4sWLK5qG4Q/2tdls+V4LglDgPbsTJ05g1KhRmDRpEjp06IBLly5h/PjxGD58OObPn+/yOxMnTsTYsWNzX6empqJKlSqIiYlRvNJImszMTGzduhXt27d3m/ASGY3llMzOXkZv3PUA5u89b4mrPrxCFSBu30bwyJGwXb+OnAcewM6XXkLzgQNZl5JpuTrm23uv+cKwhKpMmTIICgrC5cuX873/999/o3z58i6/M336dLRo0QLjx48HANStWxcRERFo1aoV3n77bVSsWLHAd0JDQxEaGlrg/ZCQEO7wOuG6JitgOSWzm7/3PM5eu424nefQv3l1o8PxqH/z6qaPkVQQEiI+tPeLL5D9ySe4tXNnwNelS+ITEbfjNEa0qWHK+6pI5FhO1Sivhg1KUbhwYURHR2Pr1q353t+6dWu+LoCO0tLSUMhpyM2g/40cY1DPRSIiIl0MbVmNN5iT8c6fB376Ke91u3bAsmVA0aLGxWQiHOglMBk6yt/YsWPxxRdfYMGCBTh58iTGjBmD8+fPY/jw4QDE7noDBw7M/XzXrl2xevVqxMXF4cyZM9izZw9GjRqFxo0bIzIy0qjFICIi0lzvRlVMO5oYBYiffgKio4Hu3QE397oHOrONrMdHI+jD0ISqd+/emDNnDt566y3Uq1cPO3fuxMaNGxEVJR4sLl26lO+ZVIMHD8asWbPw8ccfo3bt2njqqadQs2ZNrF692qhFICIiItKcoQ1jQQBmzwbatweuXgWqVwdc3E4RSNxtD7MNo672FTMmaK4ZmlABwMiRI3Hu3DlkZGQgISEBDz/8cO7/Fi1ahB07duT7/EsvvYRff/0VaWlpSEpKwpIlS1CpUiWdoyYiIiLSj2FdydLSgAEDgLFjgexsoH9/YM8eoGpVfeMwGSO2h5JkRu0rZuzS6JrhCRURERGRUoFyxtyQrmRnzwLNmwNLlwJBQcDcucDixQAfO2PI9lCSzKh9xcxsXRrNwvBh04mIiIiUcmxkmqWblRb6N43Sf/k+/RT473+BcuWAb74BWrfWd/4mZsT2GNGmBuJ2nEZ0VCm0mLHdkJEEDSmHFsArVERERCoLlKsmrui97DxjrqGpU4EXXgASEphMmYD9alNC4nV2uzMZJlREREQqC+T7DPRedq0HAQio5PjmTeDtt4GsLPF14cLAxx8DlSvrGoZZ17lZ4uJJBPNhQkVERKSyQG7w+NuyB0xy/McfQNOmwJtvAhMn6j57x2TFqHXuLWEyS1kw20iCxISKiIhIdYHc4PG3Zfe3BNGlDRuARo2AX38FKlYEnnhC9xAckxWj1rm3hCkgygIpwoSKiIh0Y5YuM3LoEbMV10ug8LcEMZ+cHOCtt4CuXYGUFKBFC/F+qWbNJH1dzXLrmKwYtc69JUx+XRbIJ0yoiIhIN2bpMiOHHjFbcb2QxaWkAD16ALGx4oN7X3gB2L5dvEIlkZrl1gzJij0GADzBQbIwoSIiQ/CMfGCyYpcZPWK24nohi7t4Edi2DQgNBRYsEAefKFxY1iT8tdzqeYJDyrGQx0vz43OoiMgQgfLsGMrPis8w0SNmK64XsrgHHgCWLwcqVBDvn1LAsdxmZmaqGZ2h7M970iNRdHUstA/MYe/+yOOl+fEKFREZwl/PbBIRmVJ2tjiC365dee917ao4mfJnenY/dHUsdL5CJvV4KfVKlq9XvHjFrCAmVERkCDP0lyci62AjzgfXrwNduojPmHrqKSA11eiI6H9cHQudEyipx0upXRV97dLIez4LYkJFRETkhpUa8VaKVQk1G3H+vq7yOXoUaNgQ2LQJCA/HnuET0GLewcBYdotSesJR6pUsX3uIsIdJQUyoiIiI3LDSmVgrxaqEmo04f19XuVasEIdAP3MGqFoV2LsXr4TV9WnZAyoZtRipiZivPUTYw6QgJlRERERuWOlMrJViVULNRpy/rytkZwPjxwN9+gBpaUD79sDBg0C9ej4vu5WTUSaD3nEdKcNR/oiIiNyw0uh7VorVaH6/rgoVAs6fF/9+9VUs7fo85n3+39xR43xZdj1HwFOb3NHynEfbCwQcUVAZXqEiIiIi8ic2m/hsqe+/B2bMwLxd5xRdVXK8WmH/G4Blu3vJvTqn1dU4M18F8vurtxphQkVEROTnjGjAmbnR6Je++goYMAAQBPF1RATQuTMA5Y1kx4TCil39lsQnot6ULag3ZQuWxCdK6jbqWG61Si7MvC55f5QyTKiIiIj8nBENODM3Gv3J0t1/4psWTwADBwJLlogDUThRY9Q4rZILLRPvuB2nkZyeieT0TMnl0LnLm9z1JmV5eBXI/zChIiIi8nNGNODYaNTBlSt4YGBP9Nq7Rnw9aRLQq5dqk3dMKLRILpbEJyJ23XHZibfUJGxEmxooGR6CkuEhksuhHoN2qHUViFeBzYMJFRERmQ4bCuoyohsPuw75xus+8MsvQHQ06p89iluhRbDj3c+AKVPEASlMwltyEbfjNLIFIMgGWQmM1Kuf/ZtG4UhsDI7Exkguh76WWz1PJGhxFZh1rzLm2euIiIj+x5+7i7HBQlJ43AeWLQMefhi4eBG4/35EHElAm1eeczstV2VOj3LoLbmw/39Kt9puExhXcZr56qeeJxK0WA/+XPdqiQkVERGZjpkbTL5ig4Wk8LgPVK0qDj7Rvbt4per++z1Oy1WZ06MceksupCQfruL09r1AOWmhRfIWHVUKQTbxN0nHhIqIiEzHn7uL+XOySOopsA9kZeX9s3lzID4eWLUKKF7c67RclTlv5dBdUqJ3sqJkf+FJC+USEq8jWxB/k3RMqIiIiHTka7IYKGffycHu3eJVqKNH895r0EDy/VKuypy3cuguKXH3/ooDF/L9VouS/SXQTloorROs1p3SzJhQERFRQLF6QsKz7wFEEIB584C2bYHTp4E339Rt1u4a1s7v2/enj7b9AQCYv/usqnFIGSnQ+f/+fIXbFaV1gpLulOQaEyoisiSrN4rNyMzrVM3YrJaQOJ/55xnkAHH7NvDMM8ALL4jd/Xr1ApYu1XSWjvuZu4a18/v2/cluaMtqqsYhZaTAi8npiF133Of6wcx1oCdK6wTWJephQkVElmS1RrEVmHmdqhmb1RoR9jP+9t9WP4Msp9GqRgPXko3k8+eBVq2ARYvEbn3vvQd8/TVQtKims1Wyn9n3p5ceuRcA0LtRFVXjkDJSYJANyBaQG7fSbW7mOtATpXWC1esSM2FCRUSWZLVGsRWYeZ2qGZvVGhH2M/5qnPk3AzmNVjUauJZrJP/+OxAdDRw8CJQuDWzeDIwfD9hsms9ayX5m3598SaScEyDHOKSMFDilW+18cSvd5mauA8ncgo0OgIhIif5NoyzTILYKM69TM8emtd6NqmDjxmOqnPk3gxFtauReeVDzs1pOw5m9K5q9wa/q9BpWB+rVA65eBdasEYdI1ygW5+8atZ85JkBK4nD+vNJtbsTyq12WyBhMqIiIiHTAhpNITqNVjQauFo1k5wTAVwu2/Ip/Uu/kTe+bb4CwMCA8XNNY1F4OpdROeq10Asb5ahrrCGtilz8iFViyjz4R6cpyXc/ILVW7hp05g1VfvYz3ds3Pm16pUpKSKamxuDtGadnFTc5xUWk3XLnHXk+f1/vePjvHbSC1jjAqVnKPCRWRCthQIiJveH+G/1DtPrwtW4CGDVHqz9/Q/dx+9K8aqkks7o5RWt5PqOVx0Z4kzNx8StY8PMWk9719do7bQGod4UusUhMsJmLyMKEiUgEbSkTkipRhqH2dLlmQIAAzZgAdOwLXrwONGwMJCUCFCprMzohjlJbzdByqXc48PMUkJ16tlk1qHeE4f291gXOsUpMxniiWxyYIgmB0EHpKTU1FiRIlkJKSguLFixsdjl/LzMzExo0b0alTJ4SEhBgdDpFLLKekpRYztuNicjoqlQzHngntFE3DVRlVY7pkkJs3gSFDgJUrxddDhwIffyzeM2VhetalvB8xj9y6QOq689d17KqcqpEb8AqVSfBsIxEFKn+u/7Q6k82r4hYlCOJVqZUrgZAQIC4O+PxzyydTepNztdef6xdAfl0gdd1Z7fESRmNCZRK8tOo//L3yJlKbP9d/WjVK2NjRl2r1us0GTJwIVKoE/PwzMHy4Ls+XCiTO28p+n9XMzacMjkxd9uUEwLrABJhQmQTPNvoPf24ckjn4W9LO+o+cma2M+1Sv5+Rg7bc/5y1Pp07AH38AzZqpH6jFaLGdPW0rX+Zn5jJpttgCERMqk+DZRv/BxiFpzUpJu5QDPes/bZipkSU3FrOVccX1ekoK0KMH2g7qCtu5s3nLI3FIdH+nxXZ23lbjOtREpZLhGNehpk/zs383dt3xfOXYqP1MyXDrpB0mVEQqU9I4NFPDh/SlZNtLbdyZoVzxQG8cM617ubGY7cSUoqT/5Elx9L7161E0OwMtb100zfKYhRbb2XlbKRmW3F2sQTYgW0C+cmzUfqbWcpE6mFARmYDeFbIZGtokUrLtpTbuzNCg5oFeW572ZTOte61unDet1avFZOr334HKlRG0Zw9mfDXJlMtj5PFA7+3sywlPAJjSrXaBcqz3fqbW9mI7QF1MqIhMQO8K2QwNban8vdJ3te3VWmYzNKgt3zA2OU/7shnWvRlvnNe0TsnOBl5/HejZUxwevU0b8flSDRuqPy+FnJffSscDOdTazo7rx9U+JXc/8zUuV9tLyTbU6l6zQMWEisgE9G74mKGhLZW/HuztXG17tZbZDA1qNfDg7p7Z92Uz7r+axvTxx8C0aeLfY8YAW7cC5cq5/bgRZdt5+c1ehpRyt53lrnO114+v5c9VPHIe9OtpOmrFGIiYUBEFIL0a2mo0Fvz1YO9JIC6zJzy4u2f2pNmMZVnTmIYNA1q3BpYuBWbNAoKDPX7ciLLtvPxmL0NK2ZczOqqUT1fk7Pco2UfTUysupeXP21Uyqcvnabubcb81O5sgCILRQehJjachkzR6PjWdfKPVE9HlPsFdT7nL/HBVFPvnGMupiWlVPq2CdanJ/fQT8PDDQFCQ+FoQJD9byp/KthHlVMr6cz4OefqOu/+Z+VjmzJ/KlBZclVM1cgNeoSIizc6Smvksl32Z5+8+a3QoRGRFWVnAuHFAu3bA5Ml578t4UK/Zrw7J6WWw4sCFfL/1IOXYJeeKnLvpGXEsc1z3craD2cuUv2JCRUSaHSzMXLHbl3loy2pGh+IW7x0SGdEtiuue68Cjq1eBDh2ADz4QX2dliVem/Iycfc9+csr+W4/yI+XYJec45G56RhzLHNc9uz2bHxMqIjJ14qMV+zL3blTF6FDc4kFUbJTdyshCyfAQXc8Oc91zHbh16BAQHQ1s3w5ERADffgtMny7rypRVyDnZZj85Zf9txfLj7VioZZLoPG3Hde9tO/Dkh/GYUBGZDCtGsjNzl0m9xO04jeT0TESEBuua8HPdG7sOTFsPfvUV0KIFcP48cO+9wC+/AE8+aXRUmpFzss1+csr+W0n5kbvd9U7afJ2fcze+elO2oN6ULbn3PTlO23Hde9oOS+ITEbvuuOWSV3/DhIrIZKx4Vo+0EYhXDp0Z1aiXs+5N2/j3kZHlz5T14F9/Ac8/D9y+DXTuDOzfDzz4oNFRmZaS8iN3u6tdP3jbl+VeKfL0zC/7yaLk9MzcQSTkDn1un2a2AATZENAngIzGhIrIZHhmnCiPFZJKUzb+Lc6U9WDlysBnnwGTJmHJax+hxaeH/C6JVkPM7J2S1ourpEHudle7fvC2L3ubn/P3PT3za0SbGigZHpLbnVnJ0OeO05zSrbap60l/x4SKDOevZ3eVskIDkojymLLxrwMt627TXCHcvx84eDDv9YABwJQpiNt51mODV42YlExD6XzVXIdJKdISAVdJg9HHP1/2ZVf3e9qTplsZWVgSn1igG9+R2BgciY0psLzOcXjaPq7WGdtV+mNCRYbj2V0isjKjG4FGMUvdrVkc8+cDrVoBPXoAV67k+5e3hrcaMSmZhtL5uvqe0kZ5ZAlp3dbcPXjXF67mqdeQ467u97T/Tk7PxMzNpyRPyzGOUcsP44218u6RMsu+GUiYUJHhAvXsLhH5hmdhjWWWulv1ODIygOHDgWefBe7cARo1AsLD833EW8NbjZiUTEPpfF19T2mjfMuYhyV1W7Ovw4TE66o1/l3N0/5e7Lrjhg/hrsSGo0n55mFkLOResNEBENkvfRNRfnzivWeOjSct1g/Xv2dmqbtVjSMpCejZE4iPF4dBf/ttYMIEoJC8889qxKRkGkrn6+p7I9rUyC3/crl73MGS+MTcKzXjOtRE/6ZRiI4qhcsp6YiOKpXvc0r2PVcxj2hTA7HrjiNbgGZ1BeB+3Y/rUFPxegSAznUjseFoEjrXjZQcu/1zjiMGkrZ4hYqIyKTYbcMzrc/Ccv0HmN27gQYNxGSqZElgwwbgtddkJ1P+Qu3ub47v20e2A4CExOvIFsTfdjM3n8LF5HRZ3eRcxWxPzDrXjVS9e6HSmOSa27c+Tk/vjLl968v6HusvfQVmLUFEZAHstuGZ1vcuabH+2U0xj1nWhT2OxEnTxHul6tQRB6Lo2NHQuKxqxYELbh/G7Tyynf09reo5e1KRkHhd9e6FjsxSlh3x+KEvJlRERBAbAWY7IAbqYAdqU9rY0WL986xxHjUHQlAjjuceHg68/DKwbx9Qg41QO6nbZMWBCwCAj7b94fZh3K5GtnO1n43rUBOVSobj4fvK+lQenJMKrZIMpfu10SNlmjERtComVEREAObv9jwMMlmXmZIYnjXOo+ZACIqcPw+8/TZGtK6OSiXDMfCxh4CZM4GICO3nbVKuGthSB3WYv/ts7t++lnG1BqywTwcAWszYDgCKTpL4+sBfd9OMXSdv9D61malutDomVEQWwLNI2hvashobun7KTEmMP1x1VKs+crUudNtWP/0EREcDb76J/oc3Wn6bqMVVA3tEmxoIsiF3UAd3hrasBgB46ZF7VVufapUHXxMHXx/4626a2QIQZJM+ep9UUvdRM9WNVseEisgCeBZJe70bVVG1UcUk2DzrwB+SGDPRsj7SfFsJAjB7NtC+PXD1KlC/PtCpkzbzksgs+wnguoHdv2kUpnSr7bXh3btRlXy/1eBqkAkl60pq4uBu+lokHvZpTulWW/XyLnUfZd2oHiZURBbAs0jWwySY60AqMzWopbBsfZSWBvTvD4wdC2RnAwMHAnv2AFWrGhqWmfYTdw1svRve7vYJtUb/czdPd13w+jeNyh2SXa39VMt1aoV91Gr1njdMqIgswFvF628Vkz+wwgFNa1wH0pipQS2FJc9qnzkDNG8OLFsGBAcDc+cCixYVeGCvL7S+emIVagzwI2efcLfe5W4Pb13wPMVktmOwFfZRq9V73jChIjKYGhWx0rN2pA+zHWz1YoWDuit6by9/a1BrSfG2SUwEjh0DypUDtm0DXnpJfHCvipQ2EK26n7jjaYAfJff2OH7HPvrfuA41cz/rbrRIuQM+eOuC52k/NXtyIGW9s97zDRMqIoOZvSImZRy3K7exteh9gsLfGtRaUrwvtW0LLFkCJCQADz+sSWz+1kBUytMAP1KHynfcJxy/I3UgEyUDPnjbD939f0l8otvnbpmFlP1G7+OUv9V7TKiIDKbGQdjVWTsyluN2VWMbB+pVLiJHkvelGzeAwYOBUw5Jcd++QOXKmsS1JD4RcTtOY0SbGn7TQHQkp/7xNMCPkqHyXX3HMR5PSZaaAz64WwdxO04jOT0TN25nqjIfLUjZb3hCwDc2QRAEo4PQU2pqKkqUKIGUlBQUL17c6HD8WmZmJjZu3IhOnTohJCTE6HCIXLJKOW0xYzsuJqejUsnw3OeqGMmfG5BmWzarlFHT+OMPoHt34MQJ4KGHgEOHgELanj+2758lw0MQERosq+yYrby5IqX+UVpORy0/jA1Hk9C5biTm9q0vaX0oXd++rOt6U7YgOT0TJcNDcCQ2Jt80Y9cdR7YA3epnK5QZs3JVTtXIDXiFKgDxTDeR9Zjt7KE/d2P0t64oZqfqMWnDBqBRIzGZqlgRiIvTPJkC8vZPALL2CzM83NUV522iZf2TkHgd2YL4G5BWtyhd31rUW1KHlVeTP9e/VsWEKgDpsSMuiU9EzOydmk2fKNCYrZFvZIKnRgOcJ5bMQ5VjUk4O8NZbQJcuQEoK0KKFeL9Us2bqBeqBff+0d7+Wul9o8XBXNcq28zbRsv6JjiqFIJv4GyhYt3i6x0ru+val3vLUtV7v+tlbN0jSHxOqAKRHQyhux2kkpaRrNn0iq7P6wU/rBoSn9aNGA9wqZ3gD4eSUz8ekGzeAHj2A2Fjx9ciRwPbt4hUqncndL7S410dK2fZW/+h5wsT5CpXzOvS0PHLWty/d5MzWxc7VclulTvNXTKgCkB5nUka0qYHIEuo934PImdoJiRrPTpGDBz/PPK0fNRp7ZutC6U4gnJzy+ZgUGgpcuyb+XrgQ+OQToHBhn2LS64SHFsdj5ys+QMHlkVr/7D97TfP14G1fVGtfVfIcKfv79pE/zVxfy1lPVj+hZ0ZMqEgT/ZtGYcsYbYamJQLUT0g8PTtFC1Zp0BvF0/pxbIQqbRjIbcga1QDhySkP7GNqFS4MfPstsHu3OLKfEyXbzsonPJyv+AAFl8db/WP//IajSZqvB6XDlcsl5zlSzokUAMX1tRmTcyuXb7NiQkVEluTp4KjkAObp2SlSyZmv2e6JMhup60evhoFRDRCenHIhOxt4/XVg/Pi89ypUABo2dPlxJdvOiBMeajW8XcXu/J63/cv++c51I/3mxI+nZR7RpgbCQ4KQlJyOUcsP5yZSGVnZufdNeauPPA2rbobkxTE+ntBTX7DRARARKdG/aZTbg5vzgyCl6N2oCvo3ry47Dse+9UrmS76xr3ctGwZWeHBnwLh+HejXD9i0SXzdrx/QoIHHrygpI57qFymU3HOjVv3hKna5y+N4/5Ia9w1pfQ+Sr9Pv3zQKseuOQwCw4WgSioWJw2mHBgdJHgbdOXGyxxMdVQqXU9LzdcE0gmN8PJmnPl6hIr8VCH2EuYyuSRklSi2OByme9dOfHlf67A/ujAgNZiPESEePilehNm0CwsOBpUu9JlOAMVeDrXJVzBM1r6xoeZVGytDzUo4BnetGIsgm/nYc0U/q8cNx+zkur6sumEaQWr4CoV2hBSZU5LfMcpldS1xG1+SMEuUrx4MUu/H5J7M1dAPSihXiEOhnzgBVqwJ794pXp0xKSZkxW/2hZrl3Ny21hni3Dz0fHVVKcbe7uX3r4/T0zpjbt36+bSH1+OH4HfvyRkeVwrVbGbABhl+hMls3an/DhIr8ViA0griM+k3DHSOHD5fzGbXnGUjM1tANOLGxQJ8+QFoa0L49cPAgUK+e0VF55A9lRukyuBox1d207I33mZtPKa5zHIeeT0i87jIZ8CWhU/LMJ/vyJiReR3pmDgQYf4VKqkBoV2iBCRX5LbMe0NRsrJp1GdWkxjIasZ7U2s5SzhYqOaOo9XOeAgkTUI3VqSP+njAB+OEH4K67DAmD21kaOSOm2hvvABTXOa6uDDknA94SOk9DqQPw+swnd2VjRJsaKBkeYqn7LwOhXaEFJlREOmNjtSB/bKiotZ2lnC1UckZR6+c8BRLu0+4p3rczMvL+fvJJ4NgxYPp0IChI3QBlcLWd9ai7tJyH47TVmo+cEVPtjXf7PUu+1jlKH6wsZSh1R/Znfd0VUdjjc6r6N43CkdgYHImNUTVBMaLnAnnGhIpIZ2ysFuSPDVK1trOUBoKSM4pSn/NE3nGfdk/Rvr14MXD//cDFi3nv1a6tfnAyudrOetRdWs7Dcdpqzad3oyqynxNnVJ3jbSh1d/u1faCJX5NSfH5OlRKO28rsw7UHCiZURDozc2PVyIeX+luD1JftrMd2MHM5tBquS/dk7duZmcCoUcCgQcC5c8BHH2kenxz27QxA1+f5aDkPx2nLmY/UOspTw9/Ta1+uwLh6X0mdKiXZsj+nS8pzqtTkbkRBd58h7dkEwf6o8cCQmpqKEiVKICUlBcWLFzc6HL+WmZmJjRs3olOnTggJCTE6HFPS+tkccrWYsR0Xk9NRqWS45GdvWJ0Zy6mc7WC2MkTq07qMmqIMXbkCPPUUsGuX+HrSJHEwikLmO+8bSPWku7Lhah24KqeuntNn/47zNBxfA/C6jt1tB1fv+/M2M8X+ayGuyqkauYH5airyS+zL65rZLslb5YyWFuUpZvZO05RPOdvBbGWIrMfwMvTLL0B0tJhMFSsGrFsHTJmiSTKlRt1hlXpSDb5c/XBu6Dt/x34fkn04cblXy9x9xtX7nqZn9fYJr5CbQ7DRAVBgUOsJ8P7GftZOqwOz3DNX/ZtGWWL7aFGeklK8T0+vM4FytoPWZYj8n6FlaPt2oGNH4M4d8b6ptWuBmjXzfcR5v/NlP1Sj7rBKPemNlPXormxIWQfO69rxuYAACjzw1nma3qbvLgZX77t6z778tzKykJyeiZmbT/FKDynGK1Ski0A6oyeH1meWDD/zrBEtylNkCXF6VhtO3CxnJ305y2uGM8RmiMEoapUhReuwSRMxgerRQ7xS5ZRMAQX3O1/2Qx6L8khZj76UDW+DeBi9LeyxAPB56HZn9n1h1PLDAVuvBBomVKQqdwdUszT6Ao3RByytaFGetox5GP2bRnl8voge69OqDXtfGrlmSFTNEIPVeVuH9rL97abDgP327YgI4KefgJUrATf3Ljjvd77shzwW5dG6PnO1rh3nae8GaB+wAtC3/rPHMq5Dzdx14Py8KKXx2PeFDUeT/KZeseqxSS9MqEhVbJSYi6FnnmVM00wVtXMjw7nbitaNMavuQ740zsyQ+JshBl+YYR/ytg7jdpxGxeMH0e6pR4AZM/L+cdddHu+Xct7vmBSpw9N61Oo5R87zVPPqo1yOscTtOI3k9MzcGOzLpDQe51EApdYrZtiP3bHqsUkvTKhIVVZvlJBrWlSkWjz/RApvByznA77eZdp5fmY+wDrypZFrhgayGWLwhRkaOx7XoSBg9tU9+Hr5a7jr5nVgxQrxvikyJSnlSY0y5+3qo7eh1tViny+Qv9uf0vrfvi/M7VtfVr1ihv3YHbbvPGNCRaqyeqOEXNOiIlX6/BNfSe2WZD9g612mvZ3BJXLF1I2d9HRgyBA0/mASgnOygT59gD17gMKFjY5MFVY56eGN3O7NapQ5V1cfHbsB+nIFy9N2cVfPj+tQM98y6V3/670fyym7bN95xoSKyCTMfFD2VpEqOYvoOE09K2op3ZJ8SWCUbkd33zN1Q1llZt4HzM60jZ3z54FWrYAvvxS79c2cCSxbJt47pQM9ypS/nPSQ271ZqzLnaeAKtR4p4e5/WiyTnO6TAHTdj/2l7JoBEyoyBBtOBVm5YjOyH7xc3g6YviYwSpddzwO8WZm53JAC6elA8+ZAQoJ4n9SWLcDLLwM2m6azdTy+6FGm/OWkh1mWw3ngCseH8wLeEw779o+OKuV2eezziI4qZYqE26i6zyzb3B8woSJDsOFUkFYVmx7Jq/PBydOBzOx8TWCUbkezHNi0LC/epm2WdUAqCQ8H3nwTqF9fTKoeeUTxpOSUS72H5rbaSQ9fRuPV43jiKg5Po686s382IfG62+WxzyMh8bqitoic9SDlocJGHTOtVnbNjAmVnzPrlSA2nArSo/uEVpwPTp4OZFLIKbdmK+NKGyVmObBpWV68Tdss68BMlsQnImb2Trf/M1PZBwCkpQGnHbbv888D8fFAlG/bVE65dHWFg2UqjxUfceBp9FVvn/U23ZLhIbiVkSVrP5KzHjyVQSnJH1kDEyo/Z9YrQTzIyae08aRG8ip13molynLKrVnLuCdGxuxuW+pxptSxfJgyGTChuB2nkZSS7vZ/pir7Z84AzZoBMTHAtWviezabKoNPyKlb/OX4ovWIdmo+4sAx8Y+ZvVP1x2HIGX3V1fOtnDnesxQRGozk9ExZ+5Faxzp/Orkc6HW6zwlVdnY2jhw5guvXr6sRD6nMn3bWQCd3dDo7NRoXUhtu7uYlt6KVe4bRamVcScze1qHUdexuW+pxptT5uS9qjNbl70a0qYHIEuFu/2easr9lC9CwIXD0KHDzJpCo7rbylyRJDq0SZsd1KXffcrcdHBP/pBTtH4fhrTx4m7fj/6OjSiHIBkRHlVJt/lpOx6z1oelO8OhMdkI1evRozJ8/H4CYTLVu3RoNGjRAlSpVsGPHDrXjIx8F4kHIFbkVkBkrLK1Hp/Nl3t7IjU1OubViGVcSs5wGgifutqXRz9vyJJAP1P2bRmHLmIfd/k+vsu+qTlwSn4gW07fh8MhXgY4dgevXgcaNxful6tfXPCapzFifuyN36HJfqbVvOSb+kSX0fxyGq3g8zdvx/wmJ15EtAAmJxl0YUHqPoJmY6gSPEQSZKlWqJBw4cEAQBEFYs2aNEBkZKZw6dUp4/fXXhebNm8udnO5SUlIEAEJKSorRofi9O3fuCGvXrhXu3LljdChC8+nbhKhXvxeaT9+myefN4Kt954Tm07cJX+07Z3QoBZg1tq/2nRPavPuj5HJq5HJ4m7eZ1rHcWKy0bEYwQ13qqk58dPJ3wvc1WwgCIP48+6wg3L5tWIzuWKk+1ztWNfctM5RTJdSur5SQs90DvT70latyqkZuIPsK1dWrV1GhQgUAwMaNG/HUU0/hvvvuw9ChQ3Hs2DGV0z0i17TsQqbk81JofZbUzFdqzBqbp/tT3H3eqDOD3tahmdax3PWkdLAKK115sDpXdeLHR1eg86k9yA4OAf7zH+Dzz4HQUK/T0nu7WenMud6xmqneMIrcdaDFcUCrewTdXln2cf9j3VuQ7ISqfPnyOHHiBLKzs7Fp0yY8+uijAIC0tDQEBQWpHiCRK1p2IVPyeSnMepk+UC2JT8StjCyUDAvx+BnHg4aVGmZG0usExszNp3AxOR0zN59SEqZs9vIwavlhv25MSB2FsuZnc4AWLRC082fg+eclN970rgvVqs+NGjLcTMzYkFb7YeqePl9vyhZcu3UHJcNDVD0O6DnKrxr7H9szBclOqIYMGYJevXqhdu3asNlsaN++PQDgl19+wf333696gESuWLFha8WY/VncjtNITs9EkdBgj59xPGiYtbFjtkaOGU5gaMFeHjYcTfLrxoR9OWPXHc9fpnJygA0b8l7fdRewe7c4sh+kN96MqAvV2EeMaESabd/Wex1IWX61H6bu6fPJ6ZlIz8zGjduZsublSM9t6mpfU2P/Y3umINkJ1eTJk/HFF1/g+eefx549exD6v8v7QUFBmDBhguoBEjlbEp+Y+8BGszfAHFml0Rgo7AeEoS2ref2M2Q8aajdy1BpRUGvjOtREpZLhGNehpi7zs5eHznUjLVEulBrRpgaCbEC2gLwylZIC9OgBdOkCfPGF2+9JabypURfKLYNq7CNG1AdK4zbjkOtKSFl+vR6mbn9mlQ1O+4ZMatXXUraxq31Njf3PiH3Y7BQNm/7kk09izJgxKFOmTO57gwYNQrdu3VQLjMgdpcOHa8HqFYKn+K2+bGowehQ1qdRu5Kg1oqDW9D5JYZ/f3L71/frkSP+mUZjSrXZemTpxQhy9b/168R4pN8+V0qrx5orcMqjGPmLESTGlcSvZR5U20LUkZfmVxmT/3v6z11Bj4gaMWn7Y5eccn1l1JDYGU7vXlrxNXK1TI57XqDUlxy8zxa8G2QlVdnY2pk6dikqVKqFo0aI4c+YMAODNN9/MHU6dSEtGDh9u5Ly04Cl+va96aPVdd+zLN3/3WVWm52uM9vuB3tlwUvZ01G7kyBly2Kx4QsA3uWUqKQFo0gT4/XegShWxi9/Agfk+a8S+7a0MOk/Xqj0ElMat5CHaWhzPfN0P9dhuG44mIVsQf7viS9dvV+tUrWUyUz2spOyYKX41yE6o3nnnHSxatAjvvfceCjucpapTpw6+cNMNgEhN3iojPXdSq1cInuLX+6qHVt91R0qXPznUivF2ZrbhSbqVRhR0x+onOxy9svJovt+6yM4GXnsN6NlTfFBvmzbAwYPiw3udGLFv+/pgV3/n6SHajkmOt+de+ZoQWWE7dK4biSCb+NsVX46FWrYRzFQPK1lOM8WvBtkJ1eLFi/HZZ5/h6aefzjeqX926dfHbb7+pGhyREnrupFavEDzFr/dVD3dyR+PTaFSl3o2qqDI9Xw+c9vuBuj7k3/fn6MXqJzscbf71Ur7futi/H5gxQ/x7zBhg61agXDmXH9W6wamkUW+17a/lFVXndeGY5Dj+7arO9zUhMno7SFmvc/vWx+npnTG3r+uHUftyLLR6G0GqQFlOT9wPb+XGxYsXcc899xR4PycnB5mZykc9ISJyxT6yUqWS4aaurPs3jfL5Jl8zL587Zh0kxqrr05UOD1YE8Nf/fuukWTPg3XeBSpWAfv08ftSXdS3lu86NeinlzYjt78u+4JzYqMm+LuzJRXRUKQDIl2B56t7r6f9S560Vb+tcy/VqJmathwOJ7CtUDz74IHbt2lXg/W+//Rb167vO7sm/8N4E87HCg/qUnuk0+gxnoDFi9DTy7L0n6+b7rZlvvgHOOtxTOH6812TKGzUGvnGsA8xc3nyJzdd6Ts7w4gmJ13OvJqjRvdc+7xUHLiiKXc4yOHM7xP//aHn8MNNoqGbYLwK9bSg7oYqNjcWLL76Id999Fzk5OVi9ejWee+45TJs2DZMmTdIiRjIZPXfcQN9BpdLqQX1qrn+lBzYjuxIEYvlTMnpayfAQ3MrIMs2AIyRTVhYwbhzQu7c4NHpammqTVmPgG8c6wMwnWOTE5nwfk69XF7QcXlzqvH0d4Mfdg7o91REuh/h3+A4Al8cPLZ5L5jxNPdtKZtgvzJDUGUl2QtW1a1esWLECGzduhM1mw6RJk3Dy5El89913uQ/5Jf/mvONq2SAK9B1UKq0e1Kfm+peTGJmlkR2I5U9uWerfNAoRocFITs8ssJ60fCgnqeTqVaBDB+CDD8TXjz0mDo2uErUHvvGXezUcy727RMIbbwNKONNq3UVHlUKQDahXpaSq07XzVkcUCwspcI+tHo9+cD6Z5DxNPZMcM+wXZkjqjKToOVQdOnTAzz//jJs3byItLQ27d+9GTEyM2rGRzqQ2Yp13XCkVk1ZD45JIqwf1qb3+jRy+15uY2TsLxOXLQBpmSAilcoxXSVlyt56MPGtOEhw6BERHA9u3AxERwLffigNROAw45St35Umvez7M2u1KSbl3dwUkdt1xAK6vxKjJ3bpMSLyObAE4ciHZp+m7e1C3p3Vlv8c2IjRY1rFLreeSOZ5Msk8zOqqUx6tjclnleGKGpM5IihIq8k9SDwbOO7eUikmroXFJHrkVs9rrX2o5MKKRnZRSMC6ly++4nFL62debsgX1pmwxrC++rwmsu/Vk5FlztVilMSPb4sVAixbA+fPAvfcCv/wCPPmk4smZ9d47s3a7ciz37hIJ+zodtfwwWszYnnsly/EKiKvublpxty7VegSFu7rAUx3hbp3r9egH+9W56KhSudNMSLyuapnjVXxrkJ1QFSpUCEFBQW5/yLqkHgycd24pFZPUaftt40Un3taf0RWz1CGSjRitKLKEegmcnJvo7WdYXXWZc/yMlttNqwTW7MmSFEpPNJlaVhbw8cfA7dtA587iEOkPPujTJOWUUamPQlBjnWpRtt3F5Vje5cTubj+xr9MNR5NwMTkdAAosi6vublrxlrzY+To4hRxS6xit9k/71bmExOu576ld5vQYsIR8JzuhWrNmDVavXp37s2LFCkyYMAEVK1bEZ599pkWMpBOpFZOW/d6NbvBbnbf1Z1T3KucbhAG4reCNKgNbxjysWsNfzk309n74jo0iJVeB1YqX8lN6osnUgoOBVauAadOA9euBkiV9nqScMuqum5arz/m6Th0b+2o1KqXEpUYibl+nnetG5l7Bcu5uL2U9qsVbPWEflMLb4BRyG/haDCChFlflXu361NfpWapusjDZCVW3bt3y/Tz55JN455138N5772H9+vVaxEgKaXVWQulZOCl4P4VvvK0/oxrOzhW6pwpezTJghjNzUrqeHImNwZHYGLf3JTLhMY7U+k7Lust+xt+nM/+//ALMmpX3ukoVYOJEoJBvPf+9jabmitR1pdY6XRKfiNh1xxU1Kl1tcylxqZGI28ve3L71FXep1ZO9y5+3rn9yG/hqDSChZARGb7RsD6nFbOXEX6l2D1WTJk3w448/qjU5UoEeZyXUngcbjspJ6SpnVIXvXKF7quDVLAOeyqdaz07RgmO/fPKdknLv6jveGr/2Lp5q719Sz/y79fnnyG71MPDyy9g+e5F6gUHZMUDqPu5pQAu592tlC0CQLe9htr4MkOMpfrkJpru6UEp8WpY5JXo3qpLvtztyG/jePi91XXnaHo7TUNqucRwkxAzbw47tKn2oklClp6fjo48+QuXKldWYHKlEj7MSPPNhHmp2Q/GF8/NVXDUu9KrgvY0OpcazU7Tgql8+Kaek3Lv6jrf6TqsRT6We+S8gIwMYNgx4/nkEZd7BpvuaYXpqGXnT8MKIY4Dc7WmPcUq32rJGp3X8rtTlkxubt/unPJ0MUtr4N/pKitz639vn1TiuOU5DaZnWY5AQo7edVFaJU02yE6pSpUqhdOnSuT+lSpVCsWLFsGDBArz//vtaxEgK6dFo5ZmPgsxyFUjpZ3zleGAyuu+2lNGhpDZS9dyuVj9RYfTBVI170JTcG6HViKdSz/znc/Ei0KYN8NlngM2Gw8PG4+1Bb2FQhzouP650mzmvE7W2vZrdK315JITcY5wa+663QTt8bfwbXS+rTY117jgNpe2a/k2jMKVbbU0HkJAzgqyRnMuYmWNVi00QBEHOFxYtWgSbzZb7ulChQihbtiyaNGmCUqXM3z0lNTUVJUqUQEpKCooXL250OH4tMzMTGzduRKdOnRASEmLY6G16azFjOy4mp6NSyfB8Ix/5C2/b0fH/AEy/zZ3LqTtab1c569Ws69LO07rSYznMvA8qWX57Gb1Rtg7idp7z/t3du8Uh0K9cEQecWLYM6NjR4zzUWmdGT8dK+4k79aZsQXJ6JkqGh+BIbMFnfPq6jGquI8dp9Y6OlFSXmpFZyo23cu8Ypz1pMXM9Fx1VCgmJ13ErIwvJ6ZmmiNXVMV+N3ED2FarBgwdj0KBBuT8DBgzAY489Zolkyqqcn0WhNMM3+gyBv50Vc0fu2TKjt4tc3raj49k9f7qC6bxd3W03pdtTyvDqVtl/pHS11HI5zHyFz5d9Yv7us9LW3dmzYjJVpw5w8KDHZMpeXqOjSkkq3954Wvdypql0G2pVvsxUT/tar+p1n6qatF7/3pZDr+3vWO6d5+mc9FmhnrM/kwsoOOS/v5GUUB09elTyD6nP+VkUSisuoxtkZt751ST3YGX0dpErULajM+ft6m67Kd2e3tbriDbi8Oq3MrIUnVzRs0Go5EGces3fyoa2rCZt3Q0YID64d98+oIa0UeZ2/v6Py/fllmNP617ONOV2JXSXGKpFi3p6Sbzrh3q7e9CvGel1PJB6T5lSatwfqQbHcu9tdFwt6jmtRm52HvLfH0lKqOrVq4f69eujXr16Hn/q16+vdbwByV4g7c+iUFpxGd0Q9tdGjq+M3i5y+cN21PIA7OkMoydShlePCA1GcnqmopMrajQI1FhvUsuPma4IuGJEfL0bVXG97s6fB7p3F69K2Q0YAEREeJ2mvbwCyFc+tKiXfJmm1Cu4CYnXNamftFgfcTtcP9RbaR1rRJk00wBD3gaDcZW82qlxf6TaHE+iLYlP1CwGNUY4dMcf2gtSSbqHKjFR+s4ZFWXulcZ7qPQj9d4UUpc/3YvjjdJlceynvuPlVpqVU7Xv5XHuly5nudXY7nrem2Tm+6AAfePzWJf+9BPQqxdw9SrQowewerXs6S+JT8TMzacAiFdH1CxTcsqdp89aqV6TGovS9e6O1DJphXuofC03zu/Z1w0A09YpruhRzzjOw35vlhn2I60Yeg9VVFSU5B/yX1LPftk/Z8bn+wQCq92L48tZVa2616nF1/k4rxtvD/r0RI0zhXqepTX7lVvDnxUmCOKDetu3F5Op+vVzH9wr9/4++5WSiNBgWeVDyv4nZx/19FkpV3DNcuVT6jL3b1rwod6+kLrPqHkM0Op44kv3UFfft1/tcTdyolnpUQ+qMcIh+fAcqhMnTmDTpk1Yv359vh/yX1IrOPvnzPh8H6nM3t3IEyn34pipoarkgOzr/RJaHjQcy467+XgqX2p1v9CiDOt5sFVjXlrux4Y+KywtDXj6aeDll4HsbGDgQGDPHqBqVQDy7+9TWidI+Z63zzhuIz3qJj1OKPmabKs1hL07ag0c4m1aSnkbNl5JXGonr+6oXefw8TfWITuhOnPmDB566CHUrl0bnTt3Rvfu3dG9e3f06NEDPXr0kB3AvHnzUK1aNYSFhSE6Ohq7du3y+PmMjAy8/vrriIqKQmhoKGrUqIEFCxbIni/JJ7XitH9O9kMoTcRsV3HkUOtMrl6UHNy1uF8iZvZOVQ6CrsqO83J4Kl+O/9PynhMr0WrkRF/mZdiJiQsXgObNgeXLgeBgYO5cYNEiIDzca2zu3vfluTvevuftM47bSI+6SY/t5muyrfUADGoMHGKPY//Za4rjcEfpFVNHRh3n/KneJXlkJ1T/93//h2rVquHKlSsoUqQIfv31V+zcuRMNGzbEjh07ZE1rxYoVGD16NF5//XUcPnwYrVq1QseOHXH+/Hm33+nVqxe2bduG+fPn49SpU1i+fDnuv/9+uYsREIw6U2L/nKyHUJqM2a7i+DMlB3cttk9SSsH5KNmHXMXmqvuJu4Er1Op+4U9lWM+unXK6a/nSYFNcPxcvDqSnA+XKAdu2AS+9BDg8G9JTbGo2MtU6vuhdTq2QtPk6AIMv5HYb9HX0YWdqXJ0yktT1Z+VeMOSa7Af7lilTBtu3b0fdunVRokQJ7N+/HzVr1sT27dvx8ssv4/Dhw5Kn1aRJEzRo0ABxcXG579WqVQvdu3fH9OnTC3x+06ZN6NOnD86cOYPSpUvLCTtXIA1KYfRN3RyUgnylx43m9nI651RRDH34nnzzUWsf8rQczvMw0831cmkVu57rRK95ySlbmXfuiHVp585iXfr770CRIkDlyprF5423h8/6ypcBWPyZc/k0ap9ztX2Qk41i/xzDjbJ10L95dUXzsidqSupcK9WdRrfPAplWg1IEy/1CdnY2ihYtCkBMrpKSklCzZk1ERUXh1KlTkqdz584dJCQkYMKECfnej4mJwd69e11+Z/369WjYsCHee+89fPXVV4iIiMDjjz+OqVOnItyhu4OjjIwMZGRk5L5OTU0FIK7QzMxMyfFa0YiHq2L+7rMY2rKqIctqn6fUea84cOF/8Vaz9NUt8k7qtu4dHYne0ZEApJcjuezT3fBiM4SEhOSbj1r7kKflcJ7H/J1/4uqNdMzf+Wfud6xCq9g9rT+16w0ty5xjrJLL1o0bsA0diuplyiAz5n+JS7X/dac28BgWWkhAaJCA0EKCJvumvSz9+GsasgVYcn9wpkZZdS6fWu1z3qbrGIddlw9/xsh7ga/2npG1fI7zGvFwNcV1rpXqTj3aZ1q0qTxN0yptOFdtUzW2gewrVK1atcLLL7+M7t27o1+/frh+/TreeOMNfPbZZ0hISMDx48clTScpKQmVKlXCnj170Lx589z3p02bhi+//NJlcvbYY49hx44dePTRRzFp0iRcvXoVI0eORLt27dzeRzV58mRMmTKlwPvLli1DkSJFJC41ERGRviIuXkTjGTNQ/MIFZIWGYut//oM7JUsaHRYRkV9JS0tDv3799L1C9cYbb+DWrVsAgLfffhtdunRBq1atcNddd2HFihWyA7A59f0WBKHAe3Y5OTmw2WxYunQpSpQoAQCYNWsWnnzySXzyyScur1JNnDgRY8eOzX2dmpqKKlWqICYmxu+7/GkpZvZOJKWkI7JEOLaMedjlZzIzM7F161a0b99eUpc/q5zdUJOU9ejMyPWkJF5XjFoGV/O1l9N5f0RgQPPqmsQjZ71ZaT9Qqzz4wkrrS06stg0bEDRxImypqcipWBF7/+//0Pqpp0zVfdrXdS/l+/YyVjIsBEVCg5GWkYXk25kuy5zZy0LLGduRfDsTJcNCsNtDNy81l8PbtOTsw94+6+qYr9c2cZwPAEXzNEN9piZeoXLNVTm1917zheyEqkOHDrl/V69eHSdOnMC1a9dQqlQpt4mQK2XKlEFQUBAuX76c7/2///4b5cuXd/mdihUrolKlSrnJFCDecyUIAv766y/ce++9Bb4TGhqK0NDQAu+HhISY6sBkNUMfvgdxO05j6MM1vK5Hqeu6f/Pqsvpd+wM569HeP/xWRhaS0zMRt/Nc7vrype+4nO/KidcTLba1lOWI23kOF5Nv51t3dueuu35fDXLW28ytfyI5PRMzt/7pUyx63E+gVnnwhZXqDUmx5uQAU6cCkyeLr1u2RPayZbh+6JCkulTP+0g87U9qfd9exm5lZOHKtdsoGR6CMsWKuCxzvsajtZfa35+7bTxtRzWXw9u05OzDUj/rWE712iaO8wGgaJ5K6zOz3rvlrb5RErenaVqpLgbyl1M1jl+yR/n78ssvc69Q2ZUuXVpWMgUAhQsXRnR0NLZu3Zrv/a1bt+brAuioRYsWSEpKws2bN3Pf+/3331GoUCFUNvDm3EBktqG3HVlp9BxX69HbUOEACowQN3PzKcUjLfn6AEWzkLIcnkZgiiyh3UhjWqw3b+Vcj+F7zVweLEkQgCefzEumXnhBHMmvQgXJk9Bz2Galo9nJeY6cvYyN61ATlUqGY1yHmm7LnBEjW8o53vRvGpU78IKnhy6ruRzepmVfvwC8LoeS/d15/lodnx3no3T9Ka3PrDpUulXjNivZCdW4ceNQrlw59OnTB99//z2ysrIUz3zs2LH44osvsGDBApw8eRJjxozB+fPnMXz4cABid72BAwfmfr5fv3646667MGTIEJw4cQI7d+7E+PHj8cwzz7gdlIICj6+VhNEJmbehwh0bFK6SLLl8bRSZJXGVshyeDphbxjxsisTAseHoibdy7k/DppudavuCzQa0agWEhgILFwIffwwULixrEnoO2+xrA1Tqc+SknkmXEo/jcquxDuQebxw/7+4h3mqeqPA0LbUeIi5n/nrMR+8TPVata60at1nJTqguXbqEFStWICgoCH369EHFihUxcuRItyPzedK7d2/MmTMHb731FurVq4edO3di48aNiIqKyp2X4zOpihYtiq1btyI5ORkNGzbE008/ja5du2Lu3Lmy521GZmugakGPZfS1kjD6rI2ch2+6SrLkMvqsnJwy4emz/nK1ROpySD3zbOX1YZU60ed9IS0t7+/Ro4Hjx4HBgxVNSup2N7Kek1tHO8fqS7lwnJbcdeBqvnKXxfHzSh/iLXX55VzF1qtx7ct8zFofGFHXGnlChFyTPcqfo7S0NKxZswbLli3Djz/+iMqVK+P0aXNfOjTzc6gcn0tgr2zN1idXDldj/Vvh2Qtm7Q9tJkviEzFzszgS57gONX16HorUMrEkPhGx644jW4Cq5YfPSzMvK9QXgA91RnY28OabwNq1QHy8+NBeF7Qoo0bUc0rn6fw9X8qF47QAyIpH7fKodZ3p7XNqlwFfyqmUWOSsfy3Kt5naBlapG81Iq+dQyb5C5ahIkSLo0KEDOnbsiHvvvRfnzp3zZXIBz92ZK2/MetbGFW9np8ywLIF61kbOuo/bcRrJ6ZmICA32uSuHqzLhKpa4HaeRLQA2ALcyslQrIysOXMj3m8xDr7PmvtY7iuqMa9eALl2A6dOBkyfFpEojrpbPiHpOaR3hHKsv5UJu1zCt7m1yjkUOqXFI+dytjCzM3HzK8PaDr/fAKpme2jHq2X5hdz3zUZRQpaWlYenSpejUqRMiIyMxe/ZsdO/eXfIzqMg1x8p1RJsaKBkeIqnhaHQXNTm8HUDMuixmSPS0oLQPvavKXM0bgV3FYp9+ifAQcZRDp3sQ5Cyro/m7z+b7LZe/lg0z0GswD93rnaNHgUaNgE2bgPBwYNkywOF+YbWZpV5VqxHoaXAHtcm9t0mP+kDqfiHleJucnplbn7qiV/3m6z2wSqandox67md67gMkjeyEqm/fvihXrhzGjBmDatWqYceOHTh9+jTefvtt1KpVS4sYA1L/plGICA32WNHZ+dOZCrMui1kaJGpz14fe20HU1YFNzcavq3LgPNqX3Cu5rj67JD4RaRniwDr255fIpXfZYALnnpR14ylZl1L2ffb110CzZsCZM0C1asC+fUDfvtrM63+k1KtmSgSk0Gu/M/J+L63ZT9yWDA8xPElQ++SJFidjvE1T7f3M2wAqWm4bM5dbs5KdUNlsNqxYsQJJSUn45JNP3A5xTr6TWpG728mtuEOYtbudGRI9Lban43I5rnujE0jncuC47M5XcqVuF1efjdtxGsm3MwEAvRtVUbSO9S4bRm8bM1PabUi3sv+f/4jJU1oaEBMDHDwIPPSQ+vNxIqVetVq50mu/c1x3UuoH57jMvF77N43CkdgYHImN8SlJ8MZqbRGl8aq9n3kbQEXLfcDM5dasfBqUworMPCiF2oy+aZE3+6tLz+1ppptvAe2WfUl8Iubv/BOja95Ep06d0OaDXbruM0rWs9m2jZmosW40Xb+XLwMNG4rd+6ZOBYKCJH1Nj7qU5co7JfVQIK3XJXvPoNg/x3CjbJ18D3iVu958WWdqrG8tj7Vy4vNlABU947QaUw5KQeZmhqsqZmG1M2SuKN2eSpbdbFcKpQ5cIVf/plHYMuZhj/PRkpKzgGbbNmZgLwsAfF43qq/fixfz/q5QAfj1V2DaNMnJlF5YrrxTUj/ouV61Os5Jna67+1F97TYphxFD4csh54qnkc/WYn0gHxMqE1KrUuQOkceql6/ddXWTw6rL7kjqwBVazEdL0VGlEGQTf5Nypi3jixcD99wjDjphV6KEcfHoyB9OYjnzVj8YvcxqJBO+TNd+H6rz/aj29QagwPzUTmjUSN70Og6Yrd4yuvxaHRMqEzLbTuYPrHq1To2yYOSya1lBG7FcaiyP4zQSEq8jWwASEq9Lno8VDnp6x2i6/TszE3jpJWDQIOD2bWDdOqMj0l0gHseMXmatrgRJnW7vRlXy/XY3v5mbT3kcXdaXhEbud7WuO+x14ajlh3W9EqaElPJgheOPUZhQmZDZdjJ/YOTVOl8qIF/KgprdoJTSsoFhpefouJuGu+3raT5GN9qk0DtGU12Nv3wZeOQR4OOPxdexscDy5cbGpDIlgzMEAqOXWe5Q2r4OfOXOigMXXJYP+/wAeK0D9SJ12ZQex+114YajSYZdCZNKyrawwvHHKJITqqSkJIwbNw6pqakF/peSkoLx48fjypUrqgYXqMy2k5FvfKmAfCkLald8VhgBT2tqLI+7kRWlzseodSpn+/vbdpcsPh6IjgZ27QKKFxevTE2eDBTyr3OX9roldt1xWY9W8HdmWGY59b7SeL3VBfN3n3UZg6tHX1jlZKec9eo4XXtd2LlupOnqROfll7ItArZul0ByLT9r1iykpqa6HP2iRIkSuHHjBmbNmqVqcET+wKgKSO35KukOYIYGhprUWB4p0/D0GaPWqR4NNUs7fx5o3RpISgJq1QL27wcef9zoqDQxok0NBNmAbAFey4NzncAuQ9pSUu/L3Sbe6oKhLat5jEGv+sHbcsmp0+SsV8fp2pd1bt/6BZbZ6H2BgyKpS3JCtWnTJgz08CT3gQMH4vvvv1clKCJ/4umGXCthdwBlpB40jT64eiO1QeEvyyvb3XcDY8cCTzwB/PILULOm0RFppn/TKEzpVltSeXCuE1hH5Kf2/ZJKGrxyt4m3uqB3oyqaNrqlrpeZm0/l3rPlivNyqFUnSa0rjd4XeLVJXZITqrNnz+Luu+92+//KlSvj3LlzasRE5Jf0rjzVnp+rA7XzAUir4c21siQ+ETGzd2o6D1c3Ynv6nP3+B7OtM6kNNanlzujGhCouXsw/LPrbbwMrVwLFihkXk06klgfnOsGfBslRY3pmuF9S7jYx+iqFWuvFeTnU2hZK9w29Gb0d/Y3khCo8PNxjwnTu3DmEh4erERO5wa4T1qZ35anH/JwPMnoNb66WuB2nkZSSruk8nG/EdpdYOW4vM68zO3f1j9RyZ3Rjwme7don3S/XsCWRkiO8FBQE2m7FxmYxznWBkI07t/UrrUVj12kes1rCWul7s92qN6yDtarGcbaHWcxDN3nuF7UzpbIIgCFI+2LlzZ0RGRuLzzz93+f9nn30WSUlJ2Lhxo6oBqk2NpyEbxfnp3Vo+zVsNrp5GrRajnuLtz08Pd8Xb8kpZH2ZeZ0viEzF/558YXfOmJuXUeV5xO07jVkYWktMzPe63Zl5ndmavf7xRvI4FAfjkE2DMGCArC6hTB9i0CYiM1CxWLetStVihzKodoxWWWU9Gl1M9t4ea9Z+Z61Izx6aUq3KqRm4g+QrVuHHjsHDhQowbNy7faH5XrlzByy+/jEWLFmHcuHGKgiBp1Ow6YfWzDkadwbfClQM1eVteXwdYMFr/plHYMuZh3eblPMKVt8+acZ3ZWf0Kk6J9OT0dGDxYfMZUVhbQpw+wb5+myZTR1H74q5HU3q+ssJ/KZeW2gZTRJ9WiZv1nn1Z0VCnT3X9q9XpeT5ITqrZt2+KTTz7Bxx9/jMjISJQqVQqlS5dGZGQkPvnkE3z00Udo184/slezUrPrhBUOfp74y8h5Zhdoy6sHszfCpB6s1V4O0z8MODERaNkSWLxYHAb9gw+AZcuAiAhtAzWY2g9/NZIWZUzLcmtEcmPltoGc0SedyV3XatZ/9mklJF433f2nZj9emYmsh2MMGzYMp0+fxsyZM9GvXz/06dMHH3zwAf7880+MGDFCqxhJA1Y4+Hli1E4eaJWLnstr5TOjVo7dWaBc/ZVdtocOBQ4dAsqUAbZuFUf0C4D7paKjSiHIJv72xAp1oxZlTItp2usT+yh19mnrUc8Y3TbwZRnljD7pzNV2NOtJHqO3Ebkm+2mDlSpVwpgxY/DJJ59g3rx5GD16NCpXrqxFbKQhvQ9+/tTgtCIrrH9vQ9z6Quvlt/JZXWdSG9BqM30j4T//AR59FDh4EAig3hgJideRLQA7f/9H0T5kRN3j64ApcmgxTXt9AiDftPV4WLvRibGvy6g0flfb0awnedTYRlZoE1iN5IQqISEBbdu2RWpqaoH/paSkoG3btvjvf/+ranDkP/ypwWlFUte/VStZNR/gqIQeyYBe28begE5IvK7pfJwZ3ZAr4NYtYP36vNc1aohXpqJMEp9OnEeplLsPKd33fCnv7uapRRlzN01f4rev83EdauabttYPazdD/a9FXSpluVxtR9Of5PEB22Tqk5xQffDBB2jXrp3L0S9KlCiB9u3b4/3331c1OPIf/lwxWYHWDxpU40Asd4hbR97i1rr86ZEMmPWZNH7pzBmgeXOge3dg82ajozGU42AqJcNDcCsjS9Z+rrQ8+VLe5cxTqyTCl/jd1Sdq1zPO68kMjWwt6lKly2W6kzwq0qqeN0NSbhTJCdUvv/yCbt26uf1/165dsXfvXlWCIv/jrWIK5J1QD1o/aFCNA7EvBy9vcVvtwDhq+WHUmLgBo5Yfzn2Pz6TRyebNQMOGwNGjQNmyQJEiRkeUK2b2TsPqyP5NoxARGozk9ExZ+7maXbC0mKdWSYQVTkw4ryczxKxFW8AMy+WJEe0fLa6sAuZIyo0iOaG6ePEiinl4+nvRokVx6dIlVYKiwBPIO6GZGNH4UYNWSYBRif6Go0nIFsTfdlZKdCx5gkQQgOnTgY4dgevXgSZNxEEoWrUyOrJcSSne7zGUsu6Vbh8993O9yrtWy6R1/FrsY2aoY7RoC5hhuTwxU/vH11iMbgsYSXJCVbZsWZw65b4i/+2331CmTBlVgqLAY7ad0JINQgMZccDSYxt5O7ho1XjtXDcSQTbxtxWp2UDQZV+8cQN46ingtdfExOq554CffwYqVdJunhqRsu7ZBSqPVZdJz0Y4n3ukLTMts6+xWHV/UoPkhOrRRx/FO++84/J/giBg2rRpePTRR1ULjAKDvaIGYKqd0ExnjMg1PbaRt4OLVo3XuX3r4/T0zmhcrbQlE3s1Gwi67IvffQesWgWEhACffgp89hkQGqrd/BSKLOH9HkMp695MDbhApEaCoud9Yv743CMznTQ1UxJiplisRnJC9cYbb+DYsWNo0qQJvvnmG/z3v//F0aNHsWLFCjRp0gTHjh3D66+/rmWs5IfMmrgYNdKQFRm1XJ62kV4xad14Nev+4Y3jQdnXbaFL479vX2DiRPGq1LBh2s3HR1vGPKzKkMpaNpqsUM8ZHaPe95xKmZ+ndeKPCbhWdavRZYuMIzmhqlGjBn788UfcunULffr0QYMGDVC/fn307dsXaWlp2Lp1K+655x4tYyU/ZNaK2kwjDZmdUcvlaRupFZO36WjdeDXr/iGHUc+V8SgnB5g9G7h2TXxtswHTpgHNmqk3Dz8ip5FohXrO6Bj13q+lzM/TOvHHqxZabQNP65HJln+T9WDfhg0b4vjx4zh06BC+/vprLF++HIcOHcLx48fRqFEjrWIkFZlth/aHilrqOvWHxrErZluuJfGJuJWRhZLhIT7HZPSy+cOVBKPXYQEpKeJw6GPHAv36ickVeSQnATHd9nbB6Bj13q+lzE/tdWKPY9Tyw6Zqc9hptQ08rUejE3nSlk0QBMHoIPSUmpqKEiVKICUlxeUztfxdixnbcTE5HZVKhmPPhHaaziszMxMbN25Ep06dEBISoum8jKTnOiXv6k3ZguT0TJQMD8GR2Bivnw+UcuosIMvtiRNiMvXHH+I9Up9+CgwebHRUXhldRpfEJyJux2mMaFPD0ie/zEytdWzkfu1YTtt8sAsXk9MRZAOyBQRWPeMG9yNzcFWfqpEbyLpCRdZn9Jk5f8R1GliMuMqr5bNZoqNKaTbMtpEKxLxqlTgU+h9/AFWqALt3WyKZMgMpz6zRs4xoNS8jy7laVy/Mcjyyx9G5bqQp4jEDs/fIsWI9byZMqAKMmXZof9l5zbROA5VjWRrXoSYqlfQ+GppSRnTb0PLZLAmJ1zUbZtvOiH3dHvN/tv8uDof+5JPAzZtAmzZAQoL48F7yiWO50HO/UDIvKWXQyC5ZaiVCZjke2eOY27e+KeLxxl/aI75gl0TfMKEiw3Dn9V96H5wcy5LWDQojzgBrOU89htk2Yl+3x/xSw/LA8uXim2PHAlu3AmXL6haHmlYcuGCqRp9judBzv1AyLyllUKv7iKRsL399lp9V+OtzveQwy9VNq+I9VKQZb/3+2Z/YWuRsL3s//pLhIYgIDdZ8G/tSloy+PyUQGL6v//e/4v1TffvqP28V2MvonFNFcfbabdXvR9F6+xi+/Q2Kwez3Kaodn5XrUj3Lh9nLhb/T6h6qYCkfOnr0qOQJ1q1bV1EgFHj6N41iImVC7g4szleBPBnRpgbidpzGrYwsyd/xhRXLkhkamXrRfft8/TWQng4MGSK+fugh8cfihrashrid5zQd6lmL7eRp+nrtB0bUEfZ60Kxn/M0en570LB9c7/5JUkJVr1492Gw2CIIAm83m8bPZ2dmqBEaklkBquKrBXeNHzkHAfnByXPeUn9aN2ICUlQW8+iowaxZQuLB4n1SdOkZHpZrejaqgf/Pqqk9X6waep+n7835g9hM9WsW34sCF3MTfzMtvFLOXC1JG0j1UZ8+exZkzZ3D27FmsWrUK1apVw7x583D48GEcPnwY8+bNQ40aNbBq1Sqt4yWSjfdqyeOuH7WSPv5muUHajKKjSiHIJv4mFfzzDxATIyZTAPDyy8ADDxgbk0VovZ96mr6n+zbMeq8JeTZ/99mAOuaynBIgMaGKiorK/Zk2bRrmzp2LYcOGoW7duqhbty6GDRuGOXPmYOrUqVrHSyQbb7SUR8oQyXpZEp+IelO2oN6ULaY6WKmxLhISryNbEH+Tj+yj9v30ExARAaxcCUybBgQFGR2ZKlYcuJDvtz9xrG+c9ystT4axEaydoS2ruTzm+us6D4STtv667dQke5S/Y8eOoVq1agXer1atGk6cOKFKUERq4lUSdRg1XHhyeiaS0zNNdbBSY10w0VfJ4sVAixbA+fPAvfcCv/wC9OxpdFSqmr/7bL7f/sp5v9JyH9Fq6HU1mKXxqjSO3o2quDzm+mviEQh1ub9uOzXJTqhq1aqFt99+G7dv3859LyMjA2+//TZq1aqlanCkDrNUzqQ+PbetUcOFlwwPQcnwEFMdrNRYF0z0VXL+PJCRAXTpAuzfDzz4oNERqW5oy2r5fvsr5/1Ky31Eq6HX1WCGxuuS+ETErjuuahyBkHj4K24772QPm75//3507doVOTk5eOh/oyb997//hc1mw/fff4/GjRtrEqhaAnHYdKOG6LTyEKpWweFXfcdyanE5OcCKFUDv3kAh/3y0IsuoOeg1wJEZBlKyH1uCbMCUbrUlxRGo5ZTHYWvRath02Uefxo0b4+zZs3jnnXdQt25d1KlTB9OmTcPZs2dNn0wFKp5Z0J9eV47MsG2lLKuVr5JaOXa/FB8PdO4MpKWJrwsVEp8v5afJFJmHXleVfZ2PGnWW/dgiNZkKZGY4DpPxJA2b7qxIkSJ4/vnn1Y6FNMIhOvVn77Ixc/MpTc80mmHbShn22MpDI1s5dr/z+efAiy8Cd+7gq05DYZsxg9tEQ2a4UkLyya2zXG1nMxxbrILrigAFV6gA4KuvvkLLli0RGRmJxETxDMjs2bOxbt06VYMLBDz77Z/sZ6wAGN4XXmtSzs5pcQbPcd/Rcj/i2UcTyMgAhg0Dnn8euHMHOx5shRn1n/Dr/coMzHAvj1Q8luaRW2fpvZ39vVcDBSbZCVVcXBzGjh2Ljh074vr167kP8i1VqhTmzJmjdnx+z0oHLJLO3mVjXIealmmMKz2ASemeokVXGcd9x9V+pNYBmYNHGMO+/Vat/wVo0wb47DPAZgOmTcNfny9GyfJ3WWK/sjIrnUywyrFUj0RBbp2l93aWsq2ssj2J7GQnVB999BE+//xzvP766wgOzusx2LBhQxw7dkzV4AKBlQ5YJJ+VGuNWO4A57juu9iOzLg/PvEoTt+M07jr5X7R5uqN431SpUsDGjcDEiejfrKpl9isrs1L9ZZVjqRnrJU/PAlMiZvZOj983qlcDkZZk30N19uxZ1K9fv8D7oaGhuHXrlipBBRL2vSWzGNGmRm4/eitw3nec9yOtlsfX+0oC6Z4sX9bViDY1sCr5b0SEFALq1gXWrAGqV9coUrI6e/myJypm3bfMXs+qUT8lpXj+vpR2D9tGZDWyE6pq1arhyJEjiIrKX9B/+OEHPPDAA6oFRkT68rcDmFbL42uDw+wNKjUpWlfZ2UBQUN726/cAUKMGEBGhbbBkeTM3n0JyeiZmbj5l2rrM7PWsGvVTZIlwDH3Y/+s3IkeyE6rx48fjhRdewO3btyEIAvbv34/ly5dj+vTp+OKLL7SIkVTGkZuIlPO1wWH2BpWaZK+rxESgZ0/g9deBHj3E9+rW1S5AFbFeJX+gRv20ZczDAfUcKiJAwT1UQ4YMQWxsLF555RWkpaWhX79++PTTT/Hhhx+iT58+WsRIKjNjH25/42s/dF++z3t0tGWl+0qMJmtdbd8OREcDCQnAyy8DmZnaB6gi1qvGsw8CNK5DTaNDIaIAo2jY9Oeeew6JiYn4+++/cfnyZVy4cAFDhw5VOzbSCG/21J6vjStfvu/4DCwmVmR6ggB88AHQvj3w779AgwbATz8BFjvDzXrVeEae7OCJLKLAJjuhateuHZKTkwEAZcqUQbly5QAAqampaNeunarBkXSuKnN3FTzPsGvP18aVL98PpGdgkcXdugX06weMGwfk5AADBwK7dwNR1qubWK8GNjNfoWSyR6Q92QnVjh07cOfOnQLv3759G7t27VIlKJLPVWVu5gre3/nauOrfNCr3/hOlz4Xy9AwsHmADi5rbW7Vp3boFNG8OfP01EBwMfPQRsGgREB7uc4xEejPzFUpvbQE19ukl8YmImb1T8ffVxmMc6U1yQnX06FEcPXoUAHDixInc10ePHsXhw4cxf/58VKpUSbNAyTNXlbmZK/hAJrWi9zUh9pTUMdlWh1UO2mpub9WmFREhPrC3XDnx/qkXXxQf3Euas0q5BawTq5mvUHprC6ixT8ftOI2klHTF31cbj3GkN8kJVb169VC/fn3YbDa0a9cO9erVy/2Jjo7G22+/jUmTJmkZK3ngqjI3cwUfyKRW9FomxEy21WGVg7aa29unaQkCcONG3uuZM4EjR4BWrXyOiwpyl4xYpdwC1orVrLy1BdSoH0a0qYHIEua5usxjHOlN8rDpZ8+ehSAIqF69Ovbv34+yZcvm/q9w4cIoV64cgoKCNAmSyJ9IHUpay+G1A2nobi1Z5ZlSam5vxdO6cQMYMgT45x/gxx/FQSdCQoCKFVWJiwpy9xwwq5RbwFqxWpUa9UP/plHoHR2JjRs3qhSVb3iMI71JTqjsD/LNycnRLBiyFj53RRn7urKfceW6y89K5YoHbYl+/118rtSJE0DhwsCBA+L9U6Qpd8mIlcqtWrFaqV4hIuuRPSjF9OnTsWDBggLvL1iwAO+++64qQZE1sCuGclx37qmxbqxy34XeDFkv338PNGokJlORkcDPPzOZ0gm7fecxY53LeqogrhOyKtkJ1X/+8x/cf//9Bd5/8MEH8emnn6oSFFkD+ygrJ3XdBeLBRY1yZcbGkxnoul5ycoDJk4GuXYHUVKBlS/GhvU2baj9vIidK6hWt61/WUwVxnZBVyU6oLl++jIou+ryXLVsWly5dUiWoQGLlBrMVz36aZX1LXXeBeHBRo1wx2XdN1/UyZgwwZYr49wsvANu2ARUqaD9fIheU1Cta17+spwriOiGrkp1QValSBXv27Cnw/p49exAZGalKUIEkEBvMRtJjfauZtAXKwUXtRNeKyb4edF0vw4cDZcuKz5b6+GPx3ikiC/FU/6pRZ7GeKojrhKxKdkL17LPPYvTo0Vi4cCESExORmJiIBQsWYMyYMXjuuee0iNGvWanBbJarO77QY32rmbSZ7eCiVRngiQU/ceZM3t+1agFnzwKDBhkXD5EP+Cw/IpJKdkL1yiuvYOjQoRg5ciSqV6+O6tWr46WXXsKoUaMwceJELWL0a2ZrMHviDwcQPda3EUmyXsmuVmXASicWyIXsbOC114CaNYEdO/Lej4gwLCQiLZmtzvKHE55EViZ52HQ7m82Gd999F2+++SZOnjyJ8PBw3HvvvQgNDdUiPjIRPg9EGiOGJHb3vBm1aVUGrDSMMzm5dg3o1w/YvFl8vWsX0KaNoSFRYDFiSHSz1Vl6HQOIyDXZV6jsihYtikaNGqF27dpMpgKEla6mBRq9zpayDOhL7lln3c9S//e/QMOGYjIVHg4sWwa8+aY+8yb6H3/oPeErs10xIwo0kq5QPfHEE1i0aBGKFy+OJ554wuNnV69erUpgRIFCjbOrZjtbSuqQe9ZZ17PUy5cDQ4cC6elAtWrAmjXAQw9pO08iF9h7gscAIqNJukJVokQJ2Gy23L89/ZCx2I/aenh2ldyRe9ZZt7PUO3eK3fzS04GYGODgQSZTZBheOScio0m6QrVw4UKXf5P5WK0ftVp9343oQ68Wnl0ld+SeddbtLHWrVsDTTwN33w1MnQoEBWk/TyIiIpNSfA8VmZPV+lGrdXXGyld5rHh2lVdCA9Dhw0Bqqvi3zQYsXgxMm8ZkioiIAp6kK1T169fP7fLnzaFDh3wKiHxjtX7Ual2d4VUefVntSij56MsvgWHDgI4dgVWrgEKFxB8iIiKSllB179499+/bt29j3rx5eOCBB9CsWTMAQHx8PH799VeMHDlSkyDJf6mVAFotkbQ6JrAB4s4dYOxY4JNPxNdZWcDt20CRIsbGRUREZCKSEqrY2Njcv5999lmMGjUKU6dOLfCZCxcuqBsdEZkSE9gAcPky8NRTwO7d4uvJk8Uh0XllytKsfL8pEZFZyT4yfvvttxg4cGCB9/v3749Vq1apEhQRERkoPh6IjhaTqeLFgfXrgdhYJlN+wCz3mwbafZiBtrxEgUb20TE8PBy77WcsHezevRthYWGqBEVERAbJzBRH8EtKAmrVAg4cALp2NToqUolZBi4yS2Knl0BbXqJAI6nLn6PRo0djxIgRSEhIQNOmTQGI91AtWLAAkyZNUj1AIiLSUUgIsGwZ8OGHwH/+AxQrZnREpCKzdNcNtPswA215iQKN7IRqwoQJqF69Oj788EMsW7YMAFCrVi0sWrQIvXr1Uj1AIiLS2MWLwNGj4ih+ANCkiZhUEWnELImdXrReXt4bR2Qs2QkVAPTq1YvJExGRP9i1Sxx8IjUV2LsXqFfP6IgoQDEpUI6PsiAylqI7jJOTk/HFF1/gtddew7Vr1wCIz5+6ePGiqsERkf/jzdoGEQTg44+Bdu2AK1eAe+8VB6AgMgjvM1LOLPfGEQUq2Veojh49ikcffRQlSpTAuXPn8Oyzz6J06dJYs2YNEhMTsXjxYi3iJCI/xTOrBkhPB4YPB+z1dd++wOefAxERxsZFAY33GSkXaF0oicxG9hWqsWPHYvDgwfjjjz/yjerXsWNH7Ny5U9XgiMj/8cyqzhITgZYtxWQqKAiYNQtYulRSMuVvVxP9bXmsrn/TKOyZ0I6JARFZjuyE6sCBAxg2bFiB9ytVqoTLly+rEhQRBQ5/a0Tp3UiXPb/Fi4FDh4AyZYCtW4ExYwCbTdJX/a1Llr8tDxERGUN2QhUWFobU1NQC7586dQply5ZVJSgiIqvSu5Eue36vvQaMHQskJABt28qal79dTfS35SEiImPITqi6deuGt956C5mZmQAAm82G8+fPY8KECejZs6fqARIRWYnejXSv87t1C4iNBTIyxNdBQcAHHwB33y17Xv52NdHfloeIiIwhe1CKmTNnolOnTihXrhzS09PRunVrXL58Gc2aNcM777yjRYxERJah983hHud3+jTQowdw7Jg4kt+nn+oWF5EvOIQ6EVmJ7ISqePHi2L17N7Zv345Dhw4hJycHDRo0wKOPPqpFfEREpMSmTeLofcnJQPnywNNPS/oaG7JkBhz9k4isRFZClZWVhbCwMBw5cgTt2rVDu3bttIqLiIiUEARg+nTgjTfEv5s0AVatAipVkvR1NmTJDDiEOhFZiayEKjg4GFFRUcjOztYqHiIiUurGDWDwYGD1avH1888Dc+cCoaGSJ8GGLJkBn6tERFYie1CKN954AxMnTsS1a9e0iIeIiJT65x9g+3YgJAT47DPgP/+RlUwBHKiBiIhILtn3UM2dOxd//vknIiMjERUVhQinh0EeOnRIteCIiEiG6tWBb78FihYFmjY1OhoiIqKAIDuh6tatG2wSHwJJREQayskBpkwBmjUDHntMfI8DBBEREelKdkI1efJkDcIgIiJZkpOBAQOA778HSpUCfv8dKFPG6KiIiIgCjuR7qNLS0vDCCy+gUqVKKFeuHPr164erV69qGRsREbly4gTQuLGYTIWGArNnM5kiIiIyiOSEKjY2FosWLULnzp3Rp08fbN26FSNGjNAyNiIi3aw4cAEtZmzHkvhEo0PxbOVKMZn64w/g7ruBPXuAQYOMjoqIiChgSe7yt3r1asyfPx99+vQBAPTv3x8tWrRAdnY2goKCNAuQiEgP83efxcXk2+Z9/pIgAK+9BsyYIb5u2xZYsQIoW9bYuIiIiAKc5CtUFy5cQKtWrXJfN27cGMHBwUhKStIkMCIiKZbEJ6pyZWloy2qoVDLcvM9fstmAf/8V/375ZWDLFiZTREREJiD5ClV2djYKFy6c/8vBwcjKylI9KCIiqeJ2nMbF5HSfryz1blQF/ZtXVzEylQiCmEwBwEcfAd26AZ07GxsTERER5ZKcUAmCgMGDByPU4SGRt2/fxvDhw/M9i2r16tXqRkhE5MGINjUQt+O07leWlsQn5s5Xsy6Cy5aJ90x9+y0QFCQOQMFkioiIyFQkJ1SDXNz03L9/f1WDISKSq3/TKEPueVLryphLWVnAq68Cs2aJr7/8EnjmGXXnQURERKqQnFAtXLhQyziIiCxFsytj//wD9O4N/PST+Pq11ziKX4DR5eonERGpRvaDfYmISKMrYwkJQI8ewIULQNGi4pWpJ55Qdx5keppe/SQiItVJHuWPiIg0tHIl0KKFmEzdey/wyy9MpgLUiDY1zD3iJBER5cMrVEREZnDvvUChQkCXLsBXXwElSxodERnEqPsCiYhIGSZURERGycwEQkLEvx96CIiPB2rXFhMrIiIisgQetYnIstR6qK8h4uOBmjXF33Z16zKZIiIishgeuYnIshxv3reUzz4DWrcGzp4F3nzT6GiIiIjIB0yoiMiyLHfzfkYG8PzzwLBhwJ074qATfBg6ERGRpfEeKiKyLEvdvH/xItCzpzh6n80GvPMOMGGC+DcRERFZFhMqIiKtJSYCTZoAV64ApUoBy5YBjz1mdFRERESkAiZURERaq1IFaNYMOHMGWLMGqF7d6IiIiIhIJUyoiIi0kJ4OCAJQpIg4ct/ixeLviAijIyMiIiIVcVAKIiK1JSYCLVsCzz4rJlUAUKwYkykiIiI/xCtURERq2r4d6NUL+Pdf4Px54MIF4O67jY6KiIiINMIrVEREahAE4IMPgPbtxWQqOhpISGAyRURE5OeYUBER+erWLaBfP2DcOCAnBxg0CNi1i8kUERFRAGCXPyIiX3XvDvz4IxAcDMyZA4wcyedLERERBQgmVEREvnrjDeC334Dly8XBKIiIiChgMKEiIpJLEIBTp4D77xdft24N/PEHEBZmbFxERESkO95DRUQkx40bwJNPAo0aASdP5r3PZIqIiCggMaEiIpLq1CmgSRNg9Wrgzh3g2DGjIyIiIiKDMaEiIpJi/XqgcWPxqlSlSsDOneLzpoiIiCigMaEiIvIkJweIjQW6dQNSU4FWrcTnSzVpYnRkREREZAJMqIiIPJk/H3jrLfHvF18Etm0Dypc3NiYiIiIyDY7yR0TkyeDB4j1TffsCAwcaHQ0RERGZDBMqIiJn27YBDz8MhISIPxs38kG9RERE5BK7/BER2WVnAxMnAo8+Cowfn/c+kykiIiJyw/CEat68eahWrRrCwsIQHR2NXbt2Sfrenj17EBwcjHr16mkbIBEFhmvXgM6dgRkzxNfBweIDfImIiIg8MDShWrFiBUaPHo3XX38dhw8fRqtWrdCxY0ecP3/e4/dSUlIwcOBAPPLIIzpFSkT+rPjZswhu1gzYvBkIDweWLwdmzuSVKSIiIvLK0IRq1qxZGDp0KJ599lnUqlULc+bMQZUqVRAXF+fxe8OGDUO/fv3QrFkznSIlIn9l+/prtHr1VdjOngWqVQP27QP69DE6LCIiIrIIwwaluHPnDhISEjBhwoR878fExGDv3r1uv7dw4UKcPn0aS5Yswdtvv+11PhkZGcjIyMh9nZqaCgDIzMxEZmamwuhJCvv65Xom0/rnHwS/8AJsd+4g+9FHkbNkCVC6NMAySybCupSsgOWUrMBVOVWjzBqWUF29ehXZ2dko7/Q8l/Lly+Py5csuv/PHH39gwoQJ2LVrF4KDpYU+ffp0TJkypcD7W7ZsQZEiReQHTrJt3brV6BCI3Krwwgso9ccfONmvHxAfb3Q4RG6xLiUrYDklK3Asp2lpaT5Pz/Bh021O9ygIglDgPQDIzs5Gv379MGXKFNx3332Spz9x4kSMHTs293VqaiqqVKmCmJgYFC9eXHng5FVmZia2bt2K9u3bIyQkxOhwiESHDsGWlgahZUsAQGb79iynZGqsS8kKWE7JClyVU3vvNV8YllCVKVMGQUFBBa5G/f333wWuWgHAjRs3cPDgQRw+fBgvvvgiACAnJweCICA4OBhbtmxBu3btCnwvNDQUoaGhBd4PCQnhDq8TrmsyjS+/BIYNA4oXBxISgCpVcv/FckpmxzJKVsBySlbgWE7VKK+GDUpRuHBhREdHF7g0vHXrVjRv3rzA54sXL45jx47hyJEjuT/Dhw9HzZo1ceTIETRp0kSv0InIau7cAV58ERg8GMjIAJo2FZMqIiIiIh8Z2uVv7NixGDBgABo2bIhmzZrhs88+w/nz5zF8+HAAYne9ixcvYvHixShUqBBq166d7/vlypVDWFhYgfeJiHJdvgw89RSwe7f4evJk4M03gUKGP4aPiIiI/IChCVXv3r3x77//4q233sKlS5dQu3ZtbNy4EVFRUQCAS5cueX0mFRGRW/v2AT17ApcuiVekliwBunY1OioiIiLyI4YPSjFy5EiMHDnS5f8WLVrk8buTJ0/G5MmT1Q+KiPzDZ5+JyVStWsDatYCMAW2IiIiIpDA8oSIi0swnnwDlygFvvAEUK2Z0NEREROSHeBMBEfmPv/4CXn8dyMkRXxcpArz7LpMpIiIi0gyvUBGRf9i5Uxx84u+/xfulXn3V6IiIiIgoAPAKFRFZmyAAH30EPPKImEzVrSsmVkREREQ6YEJFRNaVni4+W2rUKCArC+jTB9i7F6he3ejIiIiIKECwyx8RWVNiIvDEE8ChQ0BQEPDee8CYMYDNZnRkREREFECYUBGRNV25Ahw/DpQpA3zzDdC2rdERERERUQBiQkVE1tS4MbBiBdCgAXD33UZHQ0RERAGK91ARkTXcuiXeL3X4cN573bszmSIiIiJD8QoVEZnf6dNAjx7AsWPioBMnTgDBrL6IiIjIeLxCRUTmtmkT0LChmEyVLw/Mn89kioiIiEyDCRURmZMgANOmAZ06AcnJQNOmQEIC0KqV0ZERERER5eJpXiIyn7Q0YMAAYPVq8fWwYcCHHwKhocbGRUREROSECRURmU9oqDgIReHCwCefAM8+a3RERERERC6xyx8RmYcgiL+DgoBly4Bdu5hMqWhJfCJazNiOJfGJRodCRETkN5hQEZHxcnKA2Fixa589qSpdWnzWFKkmbsdpXExOR9yO00aHQkRE5DeYUBGRsZKTgW7dgLfeAj7/HNizx+iI/NaINjVQqWQ4RrSpYXQoREREfoP3UBGRcX79VXy+1B9/AGFhwGefAS1bGh2V3+rfNAr9m0YZHQYREZFfYUJFRMZYuRIYPFgcfOLuu4E1a4AGDYyOioiIiEgWdvkjIv1NmwY89ZSYTLVrJz5fiskUERERWRATKiLSX3Q0UKgQMG4csHkzUKaM0RERERERKcIuf0Skj/R08T4pmw3o0EG8f+r++42OioiIiMgnvEJFRNpbtgy4917gzJm895hMERERkR9gQkVE2snKAsaOBZ5+Grh4EZg71+iIiIiIiFTFLn9EpI1//gF69wZ++kl8/dpr4rOmiIiIiPwIEyoiUl9Cgvh8qQsXgKJFgS+/BJ54wuioiIiIiFTHhIqI1LVnD/DII0BGBnDffeLzpR54wOioiIiIiDTBhIqI1NWwIVCvHlCuHPDVV0CJEkZHRERERKQZJlRE5Lu//wbuugsICgJCQ4FNm4DixcVnTRERERH5MbZ2iMg3+/aJV6TefDPvvZIlmUwRERFRQGCLh4iUEQTgP/8BWrcGLl0C1q8H0tKMjoqIiIhIV0yoiEi+27eB554Dhg8HMjPFEfz27QOKFDE6MiIiIiJd8R4qIpLnr7+Anj2B/fsBmw2YNg149VXxbyIiIqIAw4SKiKS7cwd4+GHg7FmgVClg+XKgQwejoyIiIiIyDLv8EZF0hQsD77wDPPQQcPAgkykiIiIKeEyoiMiz9HTgt9/yXvftCxw4AFSvblxMRERERCbBhIqI3Dt3DmjRAnjkEeDy5bz3Q0IMC4mIiIjITJhQEZFr27YBDRsChw+L904lJhodEREREZHpMKEiovwEAZg5E4iJAf79F4iOBhISgCZNjI6MiIiIyHSYUBFRnlu3xHukxo8HcnKAQYOAXbuAu+82OjIiIiIiU2JCRUR5Jk8GVqwAgoOBjz8GFi4EwsONjoqIiIjItJhQEVGeSZOAtm2B7duBF17gw3qJiIiIvGBCRRTIBAFYs0b8DQDFionJVKtWxsZFREREZBFMqIgC1Y0bQM+ewBNPALNnGx0NERERkSUFGx0AERng1CmgRw/g5EmgcGGgeHGjIyIiIiKyJCZURIFm/XpgwAAgNRWoVAlYtYpDohMREREpxC5/RIEiJ0ccdKJbNzGZatWKz5ciIiIi8hETKqJAcfQoMG2a+PdLLwHbtgHlyxsbExEREZHFscsfUaCoVw+YOxcoWhQYONDoaIiIiIj8AhMqIn+2ahVQqxbwwAPi65EjjY2HiIiIyM+wyx+RP8rOBiZMAJ58UhzNLzXV6IiIiIiI/BKvUBH5m3//Bfr2BbZuFV937QoUKWJsTERERER+igkVkT85ckS8InXunJhEzZ8P9OljdFREREREfotd/oj8xbJlQPPmYjJVvTqwbx+TKSIiIiKNMaEi8gc5OcDnnwPp6cBjjwEHDgB16xodFREREZHfY0JF5A8KFQJWrBCfM/X990Dp0kZHRERERBQQmFARWdXBg8Dbb+e9LlcOmDgRCAoyLiYiIiKiAMNBKYisaNEiYPhwICMDqFkTeOopoyMiIiIiCki8QkVkJXfuAC+8AAwZIiZTjz8OxMQYHRURERFRwGJCRWQVly4B7doB8+YBNhvw1lvAmjVAiRJGR0ZEREQUsNjlj8gK9u0DevYUk6rixYGlS4EuXYyOioiIiCjgMaEisoLLl8Vk6oEHxKtS991ndEREREREBCZURNbQo4c4LHrHjkCxYkZHQ0RERET/w3uoiMzor7+Arl2BCxfy3uvVi8kUERERkcnwChWR2ezcKQ6D/vff4qh+mzaJg1AQERERkenwChWRWQgC8NFHwCOPiMlU3bpAXByTKSIiIiITY0JFZAbp6cDgwcCoUUBWFtC3L7B3L1C9utGREREREZEH7PJHZLRLl8Qh0A8dAoKCgPffB0aP5pUpIiIiIgtgQkVktBIlgJwcoGxZcSS/tm2NjoiIiIiIJGJCRWQEQRB/ChUCihQRny1VqBBw991GR0ZEREREMvAeKiK93boF9OsHvPNO3ntVqzKZIiIiIrIgXqEi0tPp0+JDeo8dA0JDgSFDgMqVjY6KiIiIiBTiFSoivWzaBDRsKCZTFSoAP/7IZIqIiIjI4phQEWktJ0fs3tepE5CcDDRrBiQkAC1bGh0ZEREREfmIXf6ItCQIwNNPA19/Lb4eNgz48EOxux8RERERWR6vUBFpyWYDHn0UKFwY+Pxz4NNPmUwRERER+RFeoSLSws2bQNGi4t9DhwLt2gHVqhkbExERERGpjleoiNSUkwNMmgTUrQtcvZr3PpMpIiIiIr/EhIpILcnJwOOPA1OnAmfPAitXGh0REREREWmMXf6I1HD8uPh8qT//BMLCgM8+AwYMMDoqIiIiItIYEyoiX337rfiA3lu3gLvvBtasARo0MDoqIiIiItIBu/wR+eLLL4FevcRk6pFHxOdLMZkiIiIiChi8QkXki8cfB2rUELv7TZ8OBHOXIiIiIgokbP0RyXX+PFCliviMqVKlgEOHgOLFjY6KiIiIiAzALn9EcixdCtx/P/Cf/+S9x2SKiIiIKGAxoSKSIjMTGDMG6N8fSE8HfvgBEASjoyIiIiIigzGhIvLm77+BmBhgzhzx9euvA6tXi13+iIiIiCig8R4qIk8OHACeeAL46y+gaFFg8WJxAAoiIiIiIjChInLvyhWgTRsgLQ2oWVN8vlStWkZHRUREREQmwoSKyJ3y5YE33gDi48UrUyVKGB0REREREZkMEyoiR5cuAbdvA9Wqia8nTBAHnyjE2w2JiIiIqCC2Eons9u0DoqOBbt2AW7fE92w2JlNERERE5BZbikSCID5XqnVr8QpVTg7w779GR0VEREREFsCEigLb7dvAc88Bw4eLz5p68knxnqm77zY6MiIiIiKyAN5DRYHrwgUxgdq/X+zWN306MH48ny9FRERERJIxoaLA9eKLYjJVujTw9ddA+/ZGR0REREREFsOEigLXvHlARgYQF5c3qh8RERERkQy8h4oCR1oa8O23ea8rVQI2bWIyRURERESKMaGiwHDuHNCyJdCrF7BypdHREBEREZGfYEJF/m/bNqBhQ+DwYaBsWaBMGaMjIiIiIiI/wYSK/JcgADNnAjEx4nOlGjYEEhKANm2MjoyIiIiI/AQTKvJPt24BffuKw6Dn5ABDhgC7dgFVqhgdGRERERH5ESZU5J+2bQNWrABCQsTR/ObPB8LCjI6KiIiIiPwMh00n//T448DUqUDbtkCLFkZHQ0RERER+ileoyD8IAjB7NnD5ct57b7zBZIqIiIiINMWEiqwvNRXo2RMYOxZ46ikgO9voiIiIiIgoQLDLH1nbqVNA9+7Ab78BhQsDgwcDQUFGR0VEREREAYIJFVnXunXAgAHAjRtApUrAqlVAkyZGR0VEREREAYRd/sh6cnKA2FjxytSNG0CrVuLzpZhMEREREZHOmFCR9aSlAd9+K/49apQ4RHr58sbGREREREQBiV3+yHqKFgXWrAH27xe7/BERERERGYQJFVnDypXikOgvvii+rllT/CEiIiIiMhATKjK37Gzg9deBd98FChUCGjcWf4iI6P/bu/e4qup8/+PvzR1JmRyUvDCoI5hdsIQsdJQsQCP1UR5LJ8rL0SbS8phnKrt5O5mPw2RjNkLNifRhDyTC21g6JlkqppYimGNUppJaOIZloJhy+f7+2D93ImjslbLA/Xo+HvsRa+3vXuuzdp92vPmuvRYAoAkgUKHpOnpU+uMfpdxc5/LkyVLPnvbWBAAAAJyFQIWmqbBQuvtuqbhYatFCysiQRoywuyoAAACgFq7yh6Zn8WKpd29nmOrSRdqyhTAFAACAJolAhabn6FHp5Elp4EBp2zYpKsruigAAAIB6ccofmp5HHpHatXOe8uftbXc1AAAAwHkxQwX7bdsmxcdLx445lx0OadgwwhQAAACaPAIV7LVggdS3r7RunfTss3ZXAwAAALiFQAV7nD4tjR8v/ed/SqdOSUOGSLNm2V0VAAAA4BYCFRpfSYnUv7+Unu48vW/GDGn5cik42O7KAAAAALdwUQo0rsJCKSnJGaqCg6XMTOnOO+2uCgAAALCEQIXG1b6982IT11wjrVghRUTYXREAAABgme2n/KWlpalz584KCAhQdHS08vLyzjt22bJlSkhIUJs2bdSqVSvFxsbqvffea8RqYUlV1c8/t20rrV0rbd1KmAIAAECzZ2ugys7O1qRJk/TMM8+ooKBAffv21R133KEDBw7UO37jxo1KSEjQ6tWrlZ+fr/79+2vw4MEqKCho5MrRUAGlpfLu109atOjnld27Sy1b2lcUAAAAcJHYGqheeukljR07VuPGjVP37t01d+5chYWFKT09vd7xc+fO1RNPPKGbbrpJEREReuGFFxQREaF33nmnkStHQzg2btSt//3f8tq+XXr6aenkSbtLAgAAAC4q275Ddfr0aeXn52vKlCm11icmJmrz5s0N2kZNTY3Ky8vVunXr8445deqUTp065VouKyuTJFVWVqqystJC5fhFxshr/nx5P/64fKqrVXP99apeskTy8ZF4z9HEnPkc4PMATRU9iuaAPkVzUF+fXoyetS1QlZaWqrq6WqGhobXWh4aG6vDhww3axpw5c3TixAnde++95x0ze/ZszZgxo876tWvXqkWLFu4VjV/kfeqUeqSlKWzDBknSwbg47Rw/XtVFRVJRkc3VAeeXm5trdwnABdGjaA7oUzQHZ/dpRUXFr96e7Vf5czgctZaNMXXW1ScrK0vTp0/XP/7xD7Vt2/a845566ilNnjzZtVxWVqawsDAlJiaqVatW1gtHXadOyadfPzkKCmS8vVX5wgvaERmphMRE+fr62l0dUK/Kykrl5uYqISGBPkWTRI+iOaBP0RzU16dnzl77NWwLVCEhIfL29q4zG3XkyJE6s1bnys7O1tixY5WTk6P4+PgLjvX395e/v3+d9b6+vvwHf7H5+jrvKXXokBxvvy1Hnz7S6tW812gW6FM0dfQomgP6FM3B2X16MfrVtotS+Pn5KTo6us7UcG5urnr37n3e12VlZWn06NFavHix7uSGsPYzRvrxx5+Xp0+Xdu6Ubr3VrooAAACARmPrKX+TJ0/WAw88oJiYGMXGxurvf/+7Dhw4oJSUFEnO0/W++eYbLfr/l9zOysrSyJEj9fLLL+uWW25xzW4FBgYqODjYtuPwWMePS2PHSvv2SXl5UkCA86a97drZXRkAAADQKGwNVMOHD9fRo0c1c+ZMlZSU6LrrrtPq1asVHh4uSSopKal1T6rXXntNVVVVmjBhgiZMmOBaP2rUKC1cuLCxy/dsX30l3X239K9/Oa/et3mzdNttdlcFAAAANCrbL0oxfvx4jR8/vt7nzg1J69evv/QF4ZetXi0lJ0vHjklXXSXl5Eh/+IPdVQEAAACNztYb+6KZqamRnn9eGjTIGaZiY6X8fMIUAAAAPBaBCg339NPSc885L0SRkiKtXy+1b293VQAAAIBtCFRouIcecgao11+X0tMlPz+7KwIAAABsZft3qNDE7dkjRUQ4f+7c2XkxisBAe2sCAAAAmghmqFC/mhpp6lTp6qulVat+Xk+YAgAAAFwIVKjr2DFp8GDpf/7HGay2bLG7IgAAAKBJ4pQ/1PavfznvL/XVV84b9f7f/0n33293VQAAAECTRKDCz5YskUaPlk6ckMLDpeXLpRtvtLsqAAAAoMkiUMFp+3bpnnucP8fHS1lZUkiIvTUBAAAATRyBCk4xMc57S7VsKb3wguRDawAAAAC/hN+aPdnOnVKHDj/PRKWlSQ6HvTUBAAAAzQhX+fNUmZlSbKz0xz9KVVXOdYQpAAAAwC0EKk9TWSk99pjzyn0nT0q+vs5/AgAAAHAbgcqTHDkiJSZKc+c6l599VnrnHef3pgAAAAC4je9QeYpt26ShQ6VDh6QrrpAWLXLebwoAAACAZQQqT1BTI40Z4wxT3bo57y/VvbvdVQEAAADNHqf8eQIvL+d9pUaMkD7+mDAFAAAAXCQEqstVSYlzJuqM6693hqrgYPtqAgAAAC4zBKrL0ZYtUnS0NHy49NFHdlcDAAAAXLYIVJcTY6RXX5Xi4pwzVJGRUtu2dlcFAAAAXLYIVJeLn36Sxo2THn7Yea+pYcOkrVuliAi7KwMAAAAuW1zl73Jw8KD0H//hvDS6l5c0e7b0+OOSw2F3ZQAAAMBljUB1OViyxBmmWreW3npLSkiwuyIAAADAIxCoLgeTJknffSc9+KDUubPd1QAAAAAeg+9QNUcVFdKzz0rHjzuXHQ7phRcIUwAAAEAjY4aquSkulu6+WyoslPbvlzIz7a4IAAAA8FjMUDUnubnO+0sVFkpt2jiv6gcAAADANgSq5sAYKTVVGjhQ+v57KSZGys+X+ve3uzIAAADAoxGomrrjx6URI6Qnn5RqaqQxY6S8PCkszO7KAAAAAI9HoGrqysqkDRskHx8pLU3KyJACAuyuCgAAAIC4KEXT1769tHSp87S/P/zB7moAAAAAnIVA1dTU1Dgvgd6tm3TPPc51ffrYWxMAAACAehGompKyMmnUKGnFCikoyBmk2re3uyoAAAAA50Ggaio+/9x5f6nPP5f8/KSXXyZMAQAAAE0cgaopWLFCGjlSKi+XOnSQli2TevWyuyoAAAAAv4Cr/NnJGOm555wzU+XlUr9+zvtLEaYAAACAZoFAZSeHQ6qocP78X/8lvf++FBpqb00AAAAAGoxT/uz2v/8rxcdLd9xhdyUAAAAA3MQMld18fAhTAAAAQDNFoAIAAAAAiwhUAAAAAGARgQoAAAAALCJQAQAAAIBFBCoAAAAAsIhABQAAAAAWEagAAAAAwCICFQAAAABYRKACAAAAAIsIVAAAAABgEYEKAAAAACwiUAEAAACARQQqAAAAALCIQAUAAAAAFhGoAAAAAMAiAhUAAAAAWESgAgAAAACLCFQAAAAAYBGBCgAAAAAsIlABAAAAgEUEKgAAAACwiEAFAAAAABYRqAAAAADAIgIVAAAAAFhEoAIAAAAAi3zsLqCxGWMkSWVlZTZXcvmrrKxURUWFysrK5Ovra3c5QL3oUzR19CiaA/oUzUF9fXomE5zJCFZ4XKAqLy+XJIWFhdlcCQAAAICmoLy8XMHBwZZe6zC/Jo41QzU1Nfr222/VsmVLORwOu8u5rJWVlSksLEwHDx5Uq1at7C4HqBd9iqaOHkVzQJ+iOaivT40xKi8vV/v27eXlZe3bUB43Q+Xl5aWOHTvaXYZHadWqFR+uaPLoUzR19CiaA/oUzcG5fWp1ZuoMLkoBAAAAABYRqAAAAADAIgIVLhl/f39NmzZN/v7+dpcCnBd9iqaOHkVzQJ+iObhUfepxF6UAAAAAgIuFGSoAAAAAsIhABQAAAAAWEagAAAAAwCICFQAAAABYRKCCZWlpaercubMCAgIUHR2tvLy8845dtmyZEhIS1KZNG7Vq1UqxsbF67733GrFaeCp3+vRsH330kXx8fHTDDTdc2gIBud+np06d0jPPPKPw8HD5+/vr97//vd54441Gqhaeyt0+zczMVI8ePdSiRQu1a9dOY8aM0dGjRxupWniijRs3avDgwWrfvr0cDodWrFjxi6/ZsGGDoqOjFRAQoC5duujVV191e78EKliSnZ2tSZMm6ZlnnlFBQYH69u2rO+64QwcOHKh3/MaNG5WQkKDVq1crPz9f/fv31+DBg1VQUNDIlcOTuNunZ/z4448aOXKkbr/99kaqFJ7MSp/ee++9WrdunTIyMvTFF18oKytLV199dSNWDU/jbp9u2rRJI0eO1NixY7V7927l5ORo27ZtGjduXCNXDk9y4sQJ9ejRQ3/7298aNH7//v1KSkpS3759VVBQoKeffloTJ07U0qVL3dovl02HJTfffLN69uyp9PR017ru3bvrrrvu0uzZsxu0jWuvvVbDhw/X1KlTL1WZ8HBW+3TEiBGKiIiQt7e3VqxYocLCwkaoFp7K3T5ds2aNRowYoX379ql169aNWSo8mLt9+uKLLyo9PV179+51rXvllVeUmpqqgwcPNkrN8GwOh0PLly/XXXfddd4xTz75pFauXKmioiLXupSUFO3cuVNbtmxp8L6YoYLbTp8+rfz8fCUmJtZan5iYqM2bNzdoGzU1NSovL+eXAVwyVvt0wYIF2rt3r6ZNm3apSwQs9enKlSsVExOj1NRUdejQQZGRkfrzn/+skydPNkbJ8EBW+rR37946dOiQVq9eLWOM/v3vf2vJkiW68847G6NkoEG2bNlSp68HDBig7du3q7KyssHb8bnYheHyV1paqurqaoWGhtZaHxoaqsOHDzdoG3PmzNGJEyd07733XooSAUt9umfPHk2ZMkV5eXny8eHjEZeelT7dt2+fNm3apICAAC1fvlylpaUaP368vv/+e75HhUvCSp/27t1bmZmZGj58uH766SdVVVVpyJAheuWVVxqjZKBBDh8+XG9fV1VVqbS0VO3atWvQdpihgmUOh6PWsjGmzrr6ZGVlafr06crOzlbbtm0vVXmApIb3aXV1te677z7NmDFDkZGRjVUeIMm9z9Oamho5HA5lZmaqV69eSkpK0ksvvaSFCxcyS4VLyp0+/eyzzzRx4kRNnTpV+fn5WrNmjfbv36+UlJTGKBVosPr6ur71F8KfYOG2kJAQeXt71/mr1JEjR+qk/HNlZ2dr7NixysnJUXx8/KUsEx7O3T4tLy/X9u3bVVBQoEceeUSS8xdXY4x8fHy0du1a3XbbbY1SOzyHlc/Tdu3aqUOHDgoODnat6969u4wxOnTokCIiIi5pzfA8Vvp09uzZ6tOnjx5//HFJUlRUlIKCgtS3b189//zzDf7LP3ApXXXVVfX2tY+Pj3772982eDvMUMFtfn5+io6OVm5ubq31ubm56t2793lfl5WVpdGjR2vx4sWcQ41Lzt0+bdWqlXbt2qXCwkLXIyUlRd26dVNhYaFuvvnmxiodHsTK52mfPn307bff6vjx4651X375pby8vNSxY8dLWi88k5U+raiokJdX7V8zvb29Jf08AwDYLTY2tk5fr127VjExMfL19W34hgxgwVtvvWV8fX1NRkaG+eyzz8ykSZNMUFCQKS4uNsYYM2XKFPPAAw+4xi9evNj4+PiY+fPnm5KSEtfj2LFjdh0CPIC7fXquadOmmR49ejRStfBU7vZpeXm56dixoxk2bJjZvXu32bBhg4mIiDDjxo2z6xDgAdzt0wULFhgfHx+TlpZm9u7dazZt2mRiYmJMr1697DoEeIDy8nJTUFBgCgoKjCTz0ksvmYKCAvP1118bY+r26b59+0yLFi3MY489Zj777DOTkZFhfH19zZIlS9zaL4EKls2fP9+Eh4cbPz8/07NnT7NhwwbXc6NGjTJxcXGu5bi4OCOpzmPUqFGNXzg8ijt9ei4CFRqLu31aVFRk4uPjTWBgoOnYsaOZPHmyqaioaOSq4Wnc7dN58+aZa665xgQGBpp27dqZ5ORkc+jQoUauGp7kww8/vODvm/X16fr1682NN95o/Pz8TKdOnUx6errb++U+VAAAAABgEd+hAgAAAACLCFQAAAAAYBGBCgAAAAAsIlABAAAAgEUEKgAAAACwiEAFAAAAABYRqAAAAADAIgIVAAAAAFhEoAIANDsOh0MrVqywu4xf5XI4BgAAgQoAcAGbN2+Wt7e3Bg4c6PZrO3XqpLlz5178ohro8OHDevTRR9WlSxf5+/srLCxMgwcP1rp162qNKygo0D333KPQ0FAFBAQoMjJSDz74oL788kubKgcANCcEKgDAeb3xxht69NFHtWnTJh04cMDuchqsuLhY0dHR+uCDD5Samqpdu3ZpzZo16t+/vyZMmOAa9+677+qWW27RqVOnlJmZqaKiIr355psKDg7Wc889Z+MRAACaCwIVAKBeJ06c0Ntvv62HH35YgwYN0sKFC+uMWblypWJiYhQQEKCQkBANHTpUknTrrbfq66+/1mOPPSaHwyGHwyFJmj59um644YZa25g7d646derkWt62bZsSEhIUEhKi4OBgxcXFaceOHW7VPn78eDkcDn3yyScaNmyYIiMjde2112ry5MnaunWrJKmiokJjxoxRUlKSVq5cqfj4eHXu3Fk333yzXnzxRb322mv1bvupp57SLbfcUmd9VFSUpk2bZukY1q9fL4fDoWPHjrnWFRYWyuFwqLi42LVu8+bN6tevnwIDAxUWFqaJEyfqxIkTrufT0tIUERGhgIAAhYaGatiwYe68bQAACwhUAIB6ZWdnq1u3burWrZvuv/9+LViwQMYY1/OrVq3S0KFDdeedd6qgoEDr1q1TTEyMJGnZsmXq2LGjZs6cqZKSEpWUlDR4v+Xl5Ro1apTy8vK0detWRUREKCkpSeXl5Q16/ffff681a9ZowoQJCgoKqvP8b37zG0nSe++9p9LSUj3xxBP1bufMuHMlJyfr448/1t69e13rdu/erV27dik5OfmiHEN9du3apQEDBmjo0KH69NNPlZ2drU2bNumRRx6RJG3fvl0TJ07UzJkz9cUXX2jNmjXq16+f5f0BABrGx+4CAABNU0ZGhu6//35J0sCBA3X8+HGtW7dO8fHxkqRZs2ZpxIgRmjFjhus1PXr0kCS1bt1a3t7eatmypa666iq39nvbbbfVWn7ttdd05ZVXasOGDRo0aNAvvv6rr76SMUZXX331Bcft2bNHkn5x3Lmuu+46RUVFafHixa7TAjMzM3XTTTcpMjLyohxDff7yl7/ovvvu06RJkyRJERERmjdvnuLi4pSenq4DBw4oKChIgwYNUsuWLRUeHq4bb7zR0r4AAA3HDBUAoI4vvvhCn3zyiUaMGCFJ8vHx0fDhw/XGG2+4xhQWFur222+/6Ps+cuSIUlJSFBkZqeDgYAUHB+v48eMN/g7XmVm0M6cZ/tI4K5KTk5WZmenaTlZWlmt2Svr1x1Cf/Px8LVy4UFdccYXrMWDAANXU1Gj//v1KSEhQeHi4unTpogceeECZmZmqqKiwvD8AQMMwQwUAqCMjI0NVVVXq0KGDa50xRr6+vvrhhx905ZVXKjAw0O3tenl51QkylZWVtZZHjx6t7777TnPnzlV4eLj8/f0VGxur06dPN2gfERERcjgcKioq0l133XXecWdmkz7//HPFxsa6dRz33XefpkyZoh07dujkyZM6ePCgK3xaOQYvL+ffN89+b859X2pqavTQQw9p4sSJdV7/u9/9Tn5+ftqxY4fWr1+vtWvXaurUqZo+fbq2bdt23tMXAQC/HjNUAIBaqqqqtGjRIs2ZM0eFhYWux86dOxUeHu6amYmKiqpzCfKz+fn5qbq6uta6Nm3a6PDhw7WCQ2FhYa0xeXl5mjhxopKSknTttdfK399fpaWlDa6/devWGjBggObPn1/rgg1nnLnwQ2JiokJCQpSamlrvds6+QMS5OnbsqH79+ikzM1OZmZmKj49XaGio5WNo06aNJNX6rtm570vPnj21e/dude3atc7Dz89PknMmMT4+Xqmpqfr0009VXFysDz744Lz7BQD8egQqAEAt7777rn744QeNHTtW1113Xa3HsGHDlJGRIUmaNm2asrKyNG3aNBUVFWnXrl21wkmnTp20ceNGffPNN64wceutt+q7775Tamqq9u7dq/nz5+uf//xnrf137dpVb775poqKivTxxx8rOTnZ7dmwtLQ0VVdXq1evXlq6dKn27NmjoqIizZs3zzUbFRQUpNdff12rVq3SkCFD9P7776u4uFjbt2/XE088oZSUlAvuIzk5WW+99ZZycnJc3zWzegxdu3ZVWFiYpk+fri+//FKrVq3SnDlzao158skntWXLFk2YMEGFhYXas2ePVq5cqUcffVSS89/bvHnzVFhYqK+//lqLFi1STU2NunXr5tZ7BwBwkwEA4CyDBg0ySUlJ9T6Xn59vJJn8/HxjjDFLly41N9xwg/Hz8zMhISFm6NChrrFbtmwxUVFRxt/f35z9v5v09HQTFhZmgoKCzMiRI82sWbNMeHi46/kdO3aYmJgY4+/vbyIiIkxOTo4JDw83f/3rX11jJJnly5df8Di+/fZbM2HCBBMeHm78/PxMhw4dzJAhQ8yHH35Ya9y2bdvM0KFDTZs2bYy/v7/p2rWr+dOf/mT27Nlzwe3/8MMPxt/f37Ro0cKUl5fXes7KMWzatMlcf/31JiAgwPTt29fk5OQYSWb//v2uMZ988olJSEgwV1xxhQkKCjJRUVFm1qxZxhhj8vLyTFxcnLnyyitNYGCgiYqKMtnZ2Rc8BgDAr+cw5ld8KxcAAAAAPBin/AEAAACARQQqAAAAALCIQAUAAAAAFhGoAAAAAMAiAhUAAAAAWESgAgAAAACLCFQAAAAAYBGBCgAAAAAsIlABAAAAgEUEKgAAAACwiEAFAAAAABb9P595NyjnT39XAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10, 8))\n",
    "plt.scatter(y_test_no, y_pred_lasso_no, s=1)\n",
    "plt.xlabel('Actual CC values')\n",
    "plt.ylabel('Predicted CC values')\n",
    "plt.title('Predicted vs. Actual non-outliers CC values: Lasso')\n",
    "plt.grid(True)\n",
    "\n",
    "# Calculate the range to include both actual and predicted values\n",
    "min_val = min(y_test_no.min(), y_pred_lasso_no.min())\n",
    "max_val = max(y_test_no.max(), y_pred_lasso_no.max())\n",
    "line_coords = np.linspace(min_val, max_val, 100)\n",
    "\n",
    "plt.plot(line_coords, line_coords, color='red', linestyle='--')  # Perfect prediction\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "10512b8d-dbcd-4abd-8cba-14757731c62a",
   "metadata": {},
   "outputs": [],
   "source": [
    "n_folds_cv = 10\n",
    "#cv = StratifiedKFold(n_fold_cv) # Stratified K-fold Cross Validations \n",
    "cv_kFold = KFold(n_splits = n_folds_cv, # n_splits fold cross-validations \n",
    "                 shuffle = True,\n",
    "                 random_state = 42) # Simple K-fold Cross Validations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c062cb32-8a9b-4fd8-8e7f-0fe051993fdc",
   "metadata": {},
   "source": [
    "Recursive Feature Elimination with Cross Validations "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "45047808-00f7-4685-a717-1c67f3490b17",
   "metadata": {},
   "outputs": [],
   "source": [
    "min_features_to_select =  1\n",
    "model_linReg = LinearRegression(fit_intercept = True) # Linear regression model\n",
    "rfecv_linReg = RFECV(estimator = model_linReg,\n",
    "                     step = 1, \n",
    "                     cv = cv_kFold, \n",
    "                     #scoring = \"accuracy\", \n",
    "                     scoring = 'neg_mean_squared_error',  # Using negative MSE as the scoring method\n",
    "                     min_features_to_select = min_features_to_select, \n",
    "                     n_jobs = -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "304c6acd-bf17-48a2-b81d-b5a70719ec7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "rfecv_linReg.fit(X_train, y_train) # Recursive Feature Elimination Cross-Validation\n",
    "y_pred_linReg = rfecv_linReg.predict(X_test) # Predicting the test set results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "87481cff-e5f5-4784-9896-e220e9665063",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10, 8))\n",
    "plt.scatter(y_test, y_pred_linReg, s = 1)\n",
    "plt.xlabel('Actual values')\n",
    "plt.ylabel('Predicted values')\n",
    "plt.title('Predicted vs. Actual values: Linear Regression')\n",
    "plt.grid(True)\n",
    "\n",
    "# Calculate the range to include both actual and predicted values\n",
    "min_val = min(y_test.min(), y_pred_linReg.min())\n",
    "max_val = max(y_test.max(), y_pred_linReg.max())\n",
    "line_coords = np.linspace(min_val, max_val, 100)\n",
    "\n",
    "plt.plot(line_coords, line_coords, color='red', linestyle='--')  # Perfect prediction\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "adbb3b45-a903-4619-8c7b-e3217a179a39",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Squared Error: 0.051060112865793275 R^2 Score: 0.12109430812475197\n"
     ]
    }
   ],
   "source": [
    "mse = mean_squared_error(y_test, y_pred_linReg)\n",
    "r2 = r2_score(y_test, y_pred_linReg)\n",
    "print(f\"Mean Squared Error: {mse} R^2 Score: {r2}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "60f7a744-2892-4097-8211-6855ab669c8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "min_features_to_select = 1\n",
    "n_scores = len(rfecv_linReg.cv_results_[\"mean_test_score\"])\n",
    "plt.figure()\n",
    "plt.xlabel(\"Number of features selected\")\n",
    "plt.ylabel(\"Mean test accuracy\")\n",
    "plt.errorbar(range(min_features_to_select, n_scores + min_features_to_select), rfecv_linReg.cv_results_[\"mean_test_score\"], \n",
    "             yerr=rfecv_linReg.cv_results_[\"std_test_score\"])\n",
    "plt.title(\"Recursive Feature Elimination with correlated features\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "7ef06e17-af1b-472a-a3f2-923b42198026",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Predictive Features: 72\n",
      "Most Predictive Feature Indices:[  0   1   2   3   6   9  11  13  20  31  33  38  45  46  47  54  57  62\n",
      "  65  66  69  70  73  74  75  76  78  80  81  83  85  86  93  94  95  96\n",
      "  99 100 107 110 111 119 126 133 135 141 143 144 145 147 149 151 152 153\n",
      " 154 155 156 157 158 161 163 164 165 166 167 170 171 173 174 175 176 177]\n"
     ]
    }
   ],
   "source": [
    "print(f\"Number of Predictive Features: {rfecv_linReg.n_features_}\")\n",
    "selected_features = np.where(rfecv_linReg.support_ == True)[0] # Identifying the selected features\n",
    "print(f\"Most Predictive Feature Indices:{selected_features}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "230dffab-48b6-4116-a837-03a0e3a79f27",
   "metadata": {},
   "outputs": [],
   "source": [
    "rfecv_linReg.fit(X_train_no, y_train_no) # Recursive Feature Elimination Cross-Validation\n",
    "y_pred_linReg_no = rfecv_linReg.predict(X_test_no) # Predicting the test set results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "37b34a83-26dd-4a63-a949-3930c3efb1c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10, 8))\n",
    "plt.scatter(y_test_no, y_pred_linReg_no, s = 1)\n",
    "plt.xlabel('Actual CC values')\n",
    "plt.ylabel('Predicted CC values')\n",
    "plt.title('Predicted vs. Actual non-outliers CC values: Linear-Regression')\n",
    "plt.grid(True)\n",
    "\n",
    "# Calculate the range to include both actual and predicted values\n",
    "min_val = min(y_test_no.min(), y_pred_lasso_no.min())\n",
    "max_val = max(y_test_no.max(), y_pred_lasso_no.max())\n",
    "line_coords = np.linspace(min_val, max_val, 100)\n",
    "\n",
    "plt.plot(line_coords, line_coords, color='red', linestyle='--')  # Perfect prediction\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0732f78f-93d4-47b6-b24c-49972bd8e523",
   "metadata": {},
   "source": [
    "Random Forest Regression model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "fb096099-4dec-4d8d-9251-680c2ab237ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train_rf, X_test_rf, y_train_rf, y_test_rf = train_test_split(Xpca,\n",
    "                                                                y, \n",
    "                                                                test_size = 0.2, \n",
    "                                                                random_state = 42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "f7b17bd8-e1b4-4b97-8104-45236f7e79fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "model_RF_Reg = RandomForestRegressor(n_estimators = 40, # Number of Trees \n",
    "                                     random_state = 42) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "b3f1b3b6-b054-45ae-b973-bc0f2e1a2164",
   "metadata": {},
   "outputs": [],
   "source": [
    "rfecv_RF = RFECV(estimator = model_RF_Reg,\n",
    "                 step = 1, \n",
    "                 cv = cv_kFold, \n",
    "                 #scoring = \"accuracy\", \n",
    "                 scoring = 'neg_mean_squared_error',  # Using negative MSE as the scoring method\n",
    "                 min_features_to_select = 1,\n",
    "                 verbose = 1,\n",
    "                 n_jobs = -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "65ff99bf-7f5d-40a9-a425-2145a39a6fd2",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "rfecv_RF.fit(X_train_rf, y_train_rf) # Recursive Feature Elimination Cross-Validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "dfe71eec-4070-4284-9722-244198d44d4c",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred_RF = rfecv_RF.predict(X_test_rf) # Predicting the test set results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "ea84eb3e-939f-458d-bf46-065c2c76cedf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uX1VVBZfLBZfLhU6dOmHatGm49tprMW/ePMNxgUAADz/8MPr164eUlBQ4nU6kpKTg888/N+2LiRMnGv49cOBAALXhw+vXr0d1dXXEM3zBBRcgJyfH8Nrq1avRr18/DBs2zPD6TTfdBE3TIry3l112mcFj3LdvXwBAfn6+4Th6/dChQyY9E8kHH3yATZs2if+WL18u7sXr9UaE5/Xo0QMXX3xxRAgoUPfvvsGDByMlJQU///nP8fLLL+N///tfXG2Ph9/97ndwuVxITU3F4MGDsXPnTixbtsygkPruu+/ioosuQlZWlqGd48ePBwD861//En+2a9cOl156qeEaU6ZMsbx+Q/bJsGHDUFFRgSlTpuCdd97Bd999F7M/6Dv8pz/9qWE+tW3bFldddRU2bNhgCE0EzOd9dXV1UkNUGaahYEOLYVoIr7zyCjZt2oQtW7agrKwM27dvx4gRIwzHtGnTxhC2Bei5ABUVFUhJSRGLP/rv8OHD4seRQqW6detm+LzT6RQGiBUU23/aaafV6d4oX+Hcc8+NaONrr70Ws41Wr5lxyy23oLq6Gv/4xz8A6Ebe119/LULbAGDUqFFYsmSJMP5OO+00DBgwAIsXL67T/b322mv4/vvvcc0116CiogIVFRWorKzENddcgy+//BKrVq0CUP9+TIQ//OEPmDZtGs477zz885//xIYNG7Bp0yZceuml8Hq9dTrnLbfcgvXr1+O///0vAF0p0+12GxaCb731Fq655hpkZ2dj0aJFWL9+PTZt2iTGJRnQfLr66qsj5tOjjz4KTdNE6ORrr72GG2+8Ec899xzOP/98ZGZm4oYbbsDhw4frfH2PxyMMh2XLliEvLw+LFy/G/PnzDcfdfffdmD17NiZPnoxly5bh3//+NzZt2oRBgwaZjoH6HLrdbgAQxybyfBw9elSEncpkZWUZzkVkZmYa/p2SkhL19XjHctCgQfjhD38o/iPjka5v1Ua1ffX57svNzcUHH3yALl264Je//CVyc3ORm5uLJ598Mq57iMavf/1rbNq0CevWrcOCBQvg9/sxadIkQ/u/+eYbLFu2LKKN/fv3BwDD95+6sQbA9LXG6JOf/vSnImT0qquuQpcuXXDeeeeJ7zMzYo1rKBTCsWPHDK/HmvcM05zhHC2GaSH07dtXJFJbIXt5iE6dOqFjx454//33TT/Trl07ALU/ZocPH0Z2drZ4PxAIRCxqVChX4auvvop6nBWkOvbmm29G7LzLyG1UiXdhTLv4L774Im677Ta8+OKLyMrKwtixYw3HTZo0CZMmTYLP58OGDRvwyCOP4LrrrsPpp5+O888/P95bAwA8//zzAIA777xTiFqo748bN67e/QjoixCfzxfxujqGixYtQl5eHhYuXGh4PZ58PCumTJmCu+++Gy+99BLmzZuHv/3tb5g8eTI6dOhguG6vXr3w2muvGearWZtVyMunHqvupNN8evrppy0Vz2hx2qlTJzzxxBN44okncOjQISxduhQzZ87Et99+a/nMxMJutxue1TFjxmDo0KEoKirC9ddfjx49egCozSN7+OGHI+6nLrL9sZ4P2YvSsWNHfP311xHHlZWVAUCDKAEmAt2LVRvV9tXnuw8ALrzwQlx44YUIBoP47LPP8PTTT+POO+9E165d8ZOf/KTO93HaaaeJuTBixAh069YNBQUFKCwsFPXCOnXqhIEDB0Z4PAkyfjt27GgqTmT13dcYfXLzzTfj5ptvRlVVFdauXYvCwkJcfvnl2Ldvn+l3eaxxpXpjDNNaYI8Ww7RyLr/8chw9ehTBYNCwc0z/UYI8iR+8+uqrhs+//vrrEcpXKr1790Zubi5eeOGFqAtmq53IcePGwel0Yv/+/aZtpIVKnz590L17dyxevBiaponPl5SU4NNPP42vQ6AvDv79739j3bp1WLZsGW688UaRgG/W5tGjR+PRRx8FAFMVxGjs2bMH69evx1VXXYWPPvoo4r9LLrkE77zzDo4ePVrvfgR0dcHt27cbXlu9ejW+//57w2s2m02ch9i+fXuE8lcidOjQAZMnT8Yrr7yCd999F4cPH44IG6QivvIi8PDhw3GpDpKhoN6fKrwwYsQIZGRkYPfu3ZbziTwvMj179sSvfvUrjBkzBv/5z3/ive2YuN1uPPPMM6iursbcuXPF62ZjUFxcXOdQ1eHDhyM1NTXiGf70009FeCFxySWXYPfu3RH3+corr8Bms+Giiy6qUxuSxfnnnw+Px4NFixYZXv/qq6+wevVqIWYSjXi/+2QcDgfOO+88PPPMMwAg+idZXpTrr78eeXl5+Otf/yrG5PLLL8fOnTuRm5tr2k4ytEaPHo0TJ05EqEiSdz4ektknMmlpaRg/fjxmzZqFmpoa7Nq1y/T6ffr0QXZ2Nv7+978bvsOrqqrwz3/+UygRMkxrgT1aDNPK+clPfoJXX30Vl112GX79619j2LBhcLlc+Oqrr/DRRx9h0qRJuOKKK9C3b18UFBTgiSeegMvlwo9+9CPs3LkTCxYsiAg/MeOZZ57BhAkTMHz4cNx1113o2bMnDh06hBUrVoiF39lnnw0AePLJJ3HjjTfC5XKhT58+OP300/HQQw9h1qxZ+N///odLL70UHTp0wDfffIONGzciLS0NRUVFsNvtmDNnDm699VZcccUV+NnPfoaKigo8+OCDcYcOArWelylTpsDn80XkgTzwwAP46quvcMkll+C0005DRUUFnnzySbhcLowePVoc53Q6MXr0aNN8EYK8Wffcc09EPgyge5A+/PBDLFq0CL/+9a/r1Y/t2rXDT3/6U8yePRsPPPAARo8ejd27d+NPf/pTRFHYyy+/HHPmzEFhYSFGjx6NvXv34qGHHkKvXr1iGtbRuOWWW/Daa6/hV7/6FU477TSDuiNd96233sLtt98uVPHmzJmD7t274/PPP4967nPPPRd9+vTBjBkzEAgE0KFDB7z99ttYt26d4bi2bdvi6aefxo033ojy8nJcffXV6NKlC44cOYJt27bhyJEjWLhwISorK3HRRRfhuuuuw1lnnYV27dph06ZNeP/993HllVeK8/3rX//CJZdcggceeCDuPC2V0aNH47LLLsOLL76ImTNnolevXrj88svx0ksv4ayzzsLAgQOxefNmPP7443UOHe3QoQNmzJiBuXPn4tZbb8WPf/xjfPnll6bPx1133YVXXnkF+fn5eOihh5CTk4Pi4mL8+c9/xrRp0wyqeE1BRkYGZs+ejfvuuw833HADpkyZgqNHj6KoqAipqakoLCyMeY54v/ueffZZrF69Gvn5+ejZsyeqq6uFoh3N33bt2iEnJwfvvPMOLrnkEmRmZqJTp04GL2G8PProozjvvPMwZ84cPPfcc3jooYewatUqXHDBBZg+fTr69OmD6upqHDx4EMuXL8ezzz6L0047DTfeeCP++Mc/oqCgAHPnzsUPfvADvPfee1ixYgUAxFRdTXaf/OxnP4PH48GIESPQvXt3HD58GI888gjS09NFnquK3W7HY489huuvvx6XX345brvtNvh8Pjz++OOoqKiICK9lmBZP02pxMAwTC1Ja27RpU9TjSO3MDL/fry1YsEAbNGiQlpqaqrVt21Y766yztNtuu037/PPPxXE+n0/7zW9+o3Xp0kVLTU3Vhg8frq1fvz5C/c1MdVDTNG39+vXa+PHjtfT0dM3tdmu5ubkRKob33nuvlpWVpdnt9ohzLFmyRLvooou09u3ba263W8vJydGuvvpq7YMPPjCc47nnntPOPPNMLSUlRevdu7f2wgsvaDfeeGNM1UGZ6667TgOgjRgxIuK9d999Vxs/fryWnZ2tpaSkaF26dNEuu+wy7eOPPzYcB0XJTaWmpkbr0qWLNnjwYMtjAoGAdtppp2lnn322eK0+/ejz+bR77rlH69Gjh+bxeLTRo0drW7dujRhDn8+nzZgxQ8vOztZSU1O1c845R1uyZIlpPyIBtbVgMKj16NFDA6DNmjXL9Jj58+drp59+uuZ2u7W+fftqf/3rX4XCmIyZUuK+ffu0sWPHau3bt9c6d+6s3XHHHVpxcbHpfPzXv/6l5efna5mZmZrL5dKys7O1/Px87Y033tA0TdOqq6u1X/ziF9rAgQO19u3bax6PR+vTp49WWFioVVVVifPQfI+nD6I9hzt27NDsdrt28803a5qmK+tNnTpV69Kli9amTRtt5MiR2scff6yNHj3aMK/o+tRugpTtZLW5UCikPfLII1qPHj20lJQUbeDAgdqyZcsizqlpmlZSUqJdd911WseOHTWXy6X16dNHe/zxxw1qcHSNxx9/3PBZqzbF+31F433kyJGoxz333HPawIEDtZSUFC09PV2bNGmSUOEj6vvdt379eu2KK67QcnJyNLfbrXXs2FEbPXq0tnTpUsO5PvjgA23IkCGa2+2OUGJVseo34sc//rHmdDq1L774QtM0XdVw+vTpWq9evTSXy6VlZmZqQ4cO1WbNmqV9//334nOHDh3SrrzySq1t27Zau3bttKuuukpbvny5BkB75513GrVPXn75Ze2iiy7SunbtqqWkpGhZWVnaNddco23fvl0cY/VbsWTJEu28887TUlNTtbS0NO2SSy7RPvnkE8MxVnPESn2UYZojNk2TfLcMwzAMwzBMi4FqEB46dKhRhHQYhokfDh1kGIZhGIZpAZCAxllnnQW/34/Vq1fjqaeeQkFBARtZDNMMYUOLYRiGYRimBdCmTRv88Y9/xMGDB+Hz+dCzZ0/87ne/w/3339/UTWMYxgQOHWQYhmEYhmEYhkkyLO/OMAzDMAzDMAyTZNjQYhiGYRiGYRiGSTJsaDEMwzAMwzAMwyQZFsOIQSgUQllZGdq1awebzdbUzWEYhmEYhmEYponQNA0nTpxAVlZWzELhbGjFoKysDD169GjqZjAMwzAMwzAM00z48ssvY5ZVYEMrBu3atQOgd2b79u2buDWtF7/fj5UrV2Ls2LFwuVxN3RwmDnjMWh48Zi0PHrOWCY9by4PHrOXRVGN2/Phx9OjRQ9gI0WBDKwYULti+fXs2tBoQv9+PNm3aoH379vwF10LgMWt58Ji1PHjMWiY8bi0PHrOWR1OPWTwpRSyGwTAMwzAMwzAMk2TY0GIYhmEYhmEYhkkybGgxDMMwDMMwDMMkGTa0GIZhGIZhGIZhkgwbWgzDMAzDMAzDMEmGDS2GYRiGYRiGYZgkw4YWwzAMwzAMwzBMkmFDi2EYhmEYhmEYJsmwocUwDMMwDMMwDJNk2NBiGIZhGIZhGIZJMmxoMQzDMAzDMAzDJBk2tBiGYRiGYRiGYZIMG1oMwzAMwzAMwzBJhg0thmEYhmEYhmGYJMOGFsMwDMMwDMMwTJJhQ4thGIZhGIZhGCbJsKHFMAzDMAzDMAyTZFqUobV27VpMmDABWVlZsNlsWLJkSczP/Otf/8LQoUORmpqKM844A88++2zDN5RhGIZhGIZhmFOaFmVoVVVVYdCgQfjTn/4U1/EHDhzAZZddhgsvvBBbtmzBfffdh+nTp+Of//xnA7eUYRiGYRiGYZhTGWdTNyARxo8fj/Hjx8d9/LPPPouePXviiSeeAAD07dsXn332GRYsWICrrrrK9DM+nw8+n0/8+/jx4wAAv98Pv99f98YzUaG+5T5uOfCYtTx4zFoePGYtEx63lgePWcujqcYskevZNE3TGrAtDYbNZsPbb7+NyZMnWx4zatQoDBkyBE8++aR47e2338Y111yDkydPwuVyRXzmwQcfRFFRUcTrf//739GmTZuktJ1hGIZhGIZhmJbHyZMncd1116GyshLt27ePemyL8mglyuHDh9G1a1fDa127dkUgEMB3332H7t27R3zm3nvvxd133y3+ffz4cfTo0QNjx46N2ZlM3fH7/Vi1ahXGjBljagAzzQ8es5YHj1nLg8esZcLj1vLgMWt5NNWYUbRbPLRqQwvQPV8y5MBTXyfcbjfcbnfE6y6Xix+8RoD7ueXBY9by4DFrefCYtUx43FoePGYtj8Yes0Su1aLEMBKlW7duOHz4sOG1b7/9Fk6nEx07dmyiVjEMwzAMwzAMEzfBYFO3oE60akPr/PPPx6pVqwyvrVy5Ej/84Q95t4JhGIZhGIZhmjM1NcAvfwlMnQq0QFmJFmVoff/999i6dSu2bt0KQJdv37p1Kw4dOgRAz6+64YYbxPG/+MUvUFJSgrvvvht79uzBCy+8gOeffx4zZsxoiuYzDMMwDMMwDBMPhw8DF18M/PnPwMsvA5991tQtSpgWZWh99tlnGDJkCIYMGQIAuPvuuzFkyBA88MADAICvv/5aGF0A0KtXLyxfvhxr1qzB4MGDMWfOHDz11FOW0u4MwzAMwzAMwzQx69cD55wDfPIJ0L49sGwZcO65Td2qhGlRYhh5eXmIpkb/0ksvRbw2evRo/Oc//2nAVjEMwzAMwzAMkxQqKoBLLwWOHwf69QPefhvo3bupW1UnWpRHi2EYhmEYhmGYVkxGBvDkk8BVVwEbNrRYIwtgQ4thGIZhGIZhmKaktBTYvr323zfdBLzxBtCuXZM1KRmwocUwDMMwDMMwTNOwdq2ejzVhAnDkSO3rFjVvWxJsaDEMwzAMwzAM07hoGvD008AllwDffquHDJ482dStSipsaDEMwzAMwzAM03h4vXp44PTpQCAATJkCfPopkJPT1C1LKi1KdZBhGIZhGIZhmBZMSQlw5ZXAf/4DOBzA448Dd97ZKkIFVdjQYhiGYRiGYRimcZg9WzeyOnUCXn8duOiipm5Rg8GGFsMwDMMwDMMwjcNTTwE+n+7J6tmzqVvToHCOFsMwDMMwDMMwDUNVFfCXv+jiF4AuevHaa63eyALYo8UwDMMwDMMwTEOwfz9wxRXAjh2A3w/88pdN3aJGhT1aDMMwDMMwDMMkl/ffB374Q93I6toVGDSoqVvU6LChxTAMwzAMwzBMctA04OGHgcsuAyoqgOHDgc2bgZEjm7pljQ6HDjIMwzAMwzAMU39OnABuvBF4+23937fdBjz5JOB2N227mgg2tBiGYRiGYRiGqT9btgDvvAOkpADPPAPcemtTt6hJYUOLYRiGYRiGYZj6M2oUsHAhMHCgHjJ4isM5WgzDMAzDMAzDJE4oBMydC+zbV/vaz3/ORlYYNrQYhmEYhmEYhkmMigpg0iRg9mxdwt3na+oWNTs4dJBhGIZhGIZhmPjZtUs3rj7/HEhNBX73u1NW8CIabGgxDMMwDMMwDBMfb74J3HQTUFUF9OwJvPUWMHRoU7eqWcKhgwzDMAzDMAzDRCcYBGbOBH78Y93Iuvhi4LPP2MiKAhtaDMMwDMMwDMNEJxgEPv5Y//tvfgOsWAF07ty0bWrmcOggwzAMwzAMwzDRSUnRwwbXrdO9WkxM2KPFMAzDMAzDMEwkf/+7ripIdO/ORlYCsEeLYRiGYRiGYZhaAgFdSfAPf9D/nZcHXHJJkzapJcKGFsMwDMMwDMMwOkeOANdeC3z0kf7v++7TDS0mYdjQYhiGYRiGYRhGVxG88krgyy+Btm2Bl1/W/83UCc7RYhiGYRiGYZhTnb/9DRg5UjeyzjwT+Pe/G93IWrShBCPmr8aiDSWNet2Ggg0thmEYhmEYhjnVcbsBnw+YMAHYtAno16/Rm7BwzX6UVnixcM3+Rr92Q8CGFsMwDMMwDMOcimha7d+vuQZYuRJYsgRIT2+S5kzLy0WGx4UqX6BVeLXY0GIYhmEYhmGYU40NG4BzzwXKympfGzMGsDedeVAwPAdpbicqvP5W4dViQ4thGIZhGIZhTiX+8hdg1Chg82ZdVTBJJCPHalpeLrIzPJiWl5u0djUVbGgxDMMwDMMwzKlAdTXws58Bt90G+P3AVVcBTz+dtNOrOVbRDC+r9wqG5+CTmRejYHhO0trVVLChxTAMwzAMwzCtna++AkaPBp57Tg8PnD8feOMNoF27pF1C9UaZiVuQgbVgxd5WJXxhBtfRYhiGYRiGYZjWzPbtev7Vt98CHToA//gHMHZs0i9TMDzH4ImalpeLhWv2G8IAyfjK8LhaTYigFWxoMQzDMAzDMExr5owzgM6dge7dgbfe0v/dCKiGF2A0vlpDeGA0OHSQYRiGYRiGYVob1dW18u1t2wLvvQd8+mlcRpaaP1VXkQuzz7WmHKxYsKHFMAzDMAzDMK2JgweBCy4AHn+89rUePYA2beL6uJpbVddCwq2tAHGisKHFMAzDMAzDMK2FDz8EfvhDYMsW4A9/AE6cSPgUqqhFXSXXW5NUe13gHC2GYRiGYRiGaelomm5Y3XMPEAoBQ4fq+Vh1UBVUc6vMcq0SOQ+FEJ4KeVky7NFiGIZhGIZhmJZMVRVw3XXAjBm6kXXTTcDHHwM9ezZ1ywCcuiGEbGgxDMMwDMMwTJzUVRiiwQgG9fpY//gH4HQCf/4z8MILgMfT1C0TnKohhGxoMQzDMAzDMEycNDvvjMMB3HIL0K0b8NFHwLRpgM3WYJeri6FppTTY7IzWJMOGFsMwDMMwDMPESbPwzmgacPiw1KhpwO7dwMiRDX7pZBqazc5oTTJsaDEMwzAMwzBMnDR5HagTJ4CrrtKNqmPH9NdsNqBDh0a5fCxDMxEvVbMwWhsQVh1kGIZhGIZhmJbA3r3AFVcAe/YAKSn48KWleMDXo95qfos2lGDhmv1xnSeWAqHsparvuVo67NFiGIZhGIZhmObO0qXAsGG6kZWdDaxdiwd8PZISepfMEL54vFStPTeLYEOLYRiGYRiGYZoroRBQWAhMmgQcPw5ceCGweTNw3nl1Dr1TDZ1khvDFE1rZ2nOzCDa0GIZhGIZhGKa5MmcO8NBD+t+nTwc+/BDo2hVA3fPFVEOnIfPOzLxXrT03i2BDi2EYhmEYhmGaK7/8JXDWWcDLLwNPPgm4XPU+ZTIMnXjD/8y8V00uKNJIsKHFMAzDMAzDMA1MQnlJW7bU/r1TJ2D7duCGGxLObbI6PhmGTrzhf1ZG3amQp8WGFsMwDMMwTAvkVFioNgaLNpRg7B/XNvh14jJMgkFg5kzgnHOAF16ofT3sxUo0t6khc6HiNaCsjLpTIU+LDS2GYRiGYZgWyKmwUG0MFq7Zj7JKb4NfJ2a43tGjwGWXAY8+CgDYsfY/9c5tashcqPoaUKdCnhYbWgzDMAzDMC2Qxsyzac1My8tFVron7uPr2mdRw/W2bcP3Zw8GVq5EINUDLF6MX5x1Zb1zm+oaIpjIPdZVwfBUyNNiQ4thGIZhGKYF0ph5Nq2ZguE5WHnXqLiPT3qf/f3vwPnno+3XX6Ekoxum3PQH4Cc/MTVY4jWA5OPqYhgmco+NqWDY0mBDi2EYhmEY5hTlVAjfSjZJ7bPdu6EVFABeL9bmDsWEG5/A593OAGBusMhGTTQDSj4u3s8QizaUoMoXQIbHFdc9RuuPU91j6mzqBjAMwzAMwzBNQ8HwnGbjeVi0oQQL1+zHtLzcZtMmM5LaZ/364flLbkB1lRcvjLkJ7TzuqMbNtLxcLFixF1W+AOYV74HXH8SCFXsj2jMtL1f0JQDxd9X7ZNbfC9fsR4XXj+wMT1z3Ga0/5Os15zFtKNijxTAMwzAMwzQ5zTGMsb4eGdPPf/YZcPCg+GfqnCIsnngb7h7fTxhDVtcrGJ6DNLcTFV4/qv1By+vK3jD570NzOsBhA4bmdLDsb/mY+nKqe0zZo8UwDMMwDMM0OaoXpikh71qVL4AKr7/OHhnVmCn5/TOYufRJOPr3Bz75BPDUeo3iuZ4c1jeqd2es3XcEADB98RZsLjmGoTkdsLnkmPBSqV7CzSXHENQgjj1c6UXHtBSMmL/a9Jj6kizvX0vxdqqwR4thGIZhGIaJSmPk2jQnEQUykADUyyNDHp1fjugBz13TMevNx+GoqQFOOw3w++O+HvX/ghV7UeH1I83txFNThgjvVvH2MpRWeMWfcmhgaYUXC1bsxYj5q9ExLUV4q8ig2lVWacjhUvOzmkOeVXP0dsYDG1oMwzAMcwrTHBZR9aGlt785EE8fttSFbl0hA2nGuD71Mv4Khufgkxv74rp7b8ZVG5YCALbdeiewZAnQvj0Ao5fK6npWhhi1s39WOhw2oH9Wuun7AFBa4cWuskrhraL38gdmic9QfhZdkzxJpRVeFL6zs8mes5YagsihgwzDMAxzCtPSk9VbevubA/H0YXMK62sIXtv0JdqF/yy44AwR8kZGaJ1D1tavB666Cvj6a92wevVVDLr8cvH2og0lKHxnJ4IaDOITZOCQ54nypdR2UDtHzF+NoAYcrarBJzMvjnhfPR+dx+yeKISR5sS0vFzRxqZ6zpqTaEsisEeLYRiGYU5hWupOMVHf9rNHLL4+bMqwPhqj6Yu3NNhYPb/ugOFPol6ePE0DfvMb3cjq1w/YtAmQjCw6f1ADbACqfAFxb3RdCgWkXCwrYo1hwfAcTMvLNRhZKnIe1IxxfcT5CobnoGjSgBb9PdFUsKHFMAzDMKcwzSkvpi7I7W/owqytleY+B1SjI9GximdeTB3ZCwBwUjJ2AHMDJu55ZrMBixcDt94KbNgA9O4d8dlpebnI8LgAQIhgyNelsD4AEeF78rniGcNYc33Bir0in4vOBwAj5q8GgHrNkXjrd7W2TQ82tBiGYRiGaRXUxWhqDI9ea1xANiZmuUSJEG1e0NgQFdV+w3GxigZH8NVXwPPP1/47Jwf461+Bdu1MP0ty7RoAhw2Ge6vyBbB23xHhYbIBCGq6QRSzHSZYybZTH/gCwYjXC9/ZGXGNaPPZ6r142toaNz3Y0GIYhmlm8KKMYepGXYymxvDmtMYFZGNCY/TUlCF1Gqto84LGhkIGs9Jjzx/L861dCwwdCtx6K+65cS4WbSgx9WDRZ+m9oTkdkJ3hQdGkAQap9wqv3yD1nh72fMVzX2ZYybZTH7idDiEAQq8HtUgDMNp8tnovnra29DBmM1gMg2EYppnByf0MUzeaa8J8PEISLbVOUHMnVr/S2EwdeTpwZAdW3jUKLpcr8kQS6jxbtP4gjjy8AL9+7/9gDwbwebczsN7THZ+EjQ35+1z+7Ij5q4WSoCxgQe1asGIvfIEgqnwBTF+8RXicfIGgqJul3teiDSXC4zVjXB/De+o8lAUy6H2r481eH5rTIUIoxGqux/NsNtfntz6wocUwDNPMaO3qXgxzqhHPArIhNljYeIOoO0V5Ryo0Nn6/H8uX70j8Al4vOv7y5yjYskr/93XX4bOfzUZoQ5n4Drf6Po/2Xb/xQDlOVPuR4rSLOllBLXxJf0j8W66XpcqzL1ix13B+eS7IaodApKEn943V62QoynM2mcZSa5i/HDrIMAzTzGjuiekMo9KQ4a6nSihtQ4RNteaQxXjnhS8QMvwZi9c2fWk4r3ydiGsePAiMGIHxW1YhYLfjs+n3A4sWYUreWeI7PNr3ebT3yJCq9oeQ4XEhxemAx2WHx+VAhscVUftKlmLP8LiEwAYJaJDQhWyYmYUFmrFoQwkGF63E4KKVhv62yvlSP1vX57c1zF82tBiGYRiGqRcNuSBqDYuteLBadMe7UDU7rjXmvNB9qoaD+j71g9tpN/xpxWubvgQAPP3h5xEGCf07Yi5+/DGwZQvQqROcH3yAHz45B7DZEjYuzOTr8wdmwWEDJgzKAgB4/UG4nQ7smXMpthaONeSryeNcMDwHWwvHYmvhWMwY1wcOmy6g4QuEDEYRfUbOC4vW13K+GGGW86Xee32KHbeG+cuGFsMwDMMw9aIhF0Tx7Jq3JqwWqrEMTbPjWrp33MxgofsEgAyPy1B7Sn6f+oHqQc0Y1ydqPS65fpY8l+W5TX+n3KRFZ44Cfv97YPNm4KKLLNsQCzP5+qemDEHRpAHYXHIMVb4AAD03y8zDBsAgxU73VTA8RxhsgIagpnvK4jV41L72uByG/jZ77tV7n5aXK4y9RDdLWvr8BdjQYhiGYRimnjTkgshKKa21YrZQjWXELtpQgipfABkeV5Pv/icz1NPMYKH+mDGuD9LcTlR4/Sh8Z6cwnkjBj1T95Bwf8oIt2xZZj4vqaN1xyZnWoX5nd8InZUvw2Sb9PPOKdwN33w307Gk4bmhOB9gAlFf54vJE0tip8vV0/4GQnkjldjpMPWzkLTLrL3p+3E6HweCRjzUbM7ldM8b1wdbCschMSzF4tcyee3W+nurFjtnQYhiGYZg6cqrkDzUlrSF8KBHMFqrxFKKt8PqR5nY2+e5/MkM9zcZe7g/ZW0LeoOLtZcKwsmpLqssecd5rz+1h+FO9n6VvrgWGDweefhqPLHkc0DRU+83zvjaXHIMGXbQiHk8kjZ0qX0/e3LOz04VxqXrY5Npaan+pxhIZPENzOhgMc7N+MptT8XiXk7Hp0pq+V9nQYhiGYZg6cqrkDzUm6iKrMcOHmsMCry7325yM0WhtSbR/Y/WFHBrXPys9IkRNrVkF6CFws/L7ifNSmyhHy+x+8r/aiueeuR3YuRPo2hXLJ04FbDacnZ1uem/k0fK47DH7IVp/kTfqaFWNQVyDjCMAorZWZVhpUO4vWYGQjv9k5sXYXHJMGFEATL2hZkZVLO9yfYoV1+f45gwbWgzDMAxTR5rTArclIy/QmnKR1VIXeLJB0tTGYjTjqCH6VzZG1BA1uS0k6ECvAxAS53LBYgOhEAo+XISn/z4b7au/x84efYHNm7Gu21kA9Gua3Rt5tDLT3DH7Qe2veIwwCoFcsGKvELzQEJkDRZ8HYBmOauUNXbvvCIKa/qdaWNnq+64+xYrrc3xzhg0thmEYhqkjrSFZuy4kezGvylM3xiKrLip9VrksTe0Fk4nXmGnsdqt5ZMm6vqq4l8jzKEucU47W2D+u1dt04gRw9dXA/ffDrmlYMuxyvDD3RYz4214MzemADI8L5VU1QvLcTDRDDuGT7zVaCB6Nn1oDS/48SdWT4WiVA0X9Map3Z3E9NW8tnueN2rR23xHxWiLPT6Lj0pq+V1ucofXnP/8ZvXr1QmpqKoYOHYqPP/446vGvvvoqBg0ahDZt2qB79+64+eabcfTo0UZqLcMwDHOq09wW4skg2Z6J+iyW60pdVPqsclnU1ygMzSocrSGJ11BtbO+d6jlJ1vXjnS+kPjiqd2ehPEiGX9GkASI3q6wy3KZgENixA0hJAf76V0z+9zL8u6xK5IEBuuQ6iUPI7VA9jOQ1I+EJqpFlJotOXiOg1gsV2Vea+BwVYo7WB3LIX7xy67Jao5lnzOr5IS+Z2blb43dhLFqUofXaa6/hzjvvxKxZs7BlyxZceOGFGD9+PA4dOmR6/Lp163DDDTdg6tSp2LVrF9544w1s2rQJt956ayO3nGEYhjlVaanhaNFIttepKXaw1fydeBaAZvdt9hqFoZmGo9WDeNoZb1+atbshF8Lq9ay8OvWpGxYN6pfNJceEsWQWMpeVHp4T/61EweX34r0/vwaIdaNu4Oh1qYJR87AItTDwghV7EdQAG4yFglWvUc/MNkK5UA3ZczsdcfXF9MVbkHtvMTqmpRi8bVbqg2b9JRuOZHyZee3U+zD7vmuN34WxaFGG1h/+8AdMnToVt956K/r27YsnnngCPXr0wMKFC02P37BhA04//XRMnz4dvXr1wsiRI3Hbbbfhs88+a+SWMwzDMK0dq8VOa8o3IFpDaI98D/EuAM3u2+w1CkOjP5OFVTvNaivFMkDM2l2f4rKxUK9nJaxQn7phMrGeR1lKfdGGEoz7/Rr0WbwYH6TuEnNinbsr7v2qjThPaUW1OI/b6RB5WAAs+9yqMHC6x2Uqiw7oXqNdZZVCuXDtviOo8gWwYMVeLNpQghnj+oi6VgAsizeT52xXWaXBaJJDDeMRLyHpfACmXjuz+zU7X2v8LoyFTdM0LfZhTU9NTQ3atGmDN954A1dccYV4/de//jW2bt2Kf/3rXxGf+fTTT3HRRRfh7bffxvjx4/Htt9/immuuQd++ffHss8+aXsfn88Hn84l/Hz9+HD169MB3332H9u3bJ//GGACA3+/HqlWrMGbMGLhcrqZuDhMHPGYtDx6zhmXsH9eirNKLrHQPVt41Kinn5DFrHF7b9CWeX3cAU0f2ipD3rgtW41bf61h9Xp57AOo8D1/b9CUeXr4bQQ1JncdW1zK7F/X1WMcN7pGBrV9WGN5P9D6ueHg5frtoLkZ/8Rk0pxOBnTvx2lEXnl93ACd9AVRU+5GV7kFmGxd2fn0cA7q3xxXnnCba9fy6A4Y+jzbOseaAfF8f/fcbVAdCSHXa4Q3nZWWle8Q1qW0ZqS60cTtFX9CfmW1c2PX1caQ6HZgxrk9Cc07uQ/KAOWzAfZf1S8ozkgya6vvx+PHj6NSpEyorK2PaBi3G0CorK0N2djY++eQTXHDBBeL1hx9+GC+//DL27t1r+rk333wTN998M6qrqxEIBDBx4kS8+eablgPy4IMPoqioKOL1v//972jTpk1yboZhGIZhGIZpctqVlGDY/Plo+/XXCKakYOu0afjqoouaullMM+bkyZO47rrr4jK0nI3UpqRhs9kM/9Y0LeI1Yvfu3Zg+fToeeOABjBs3Dl9//TV++9vf4he/+AWef/5508/ce++9uPvuu8W/yaM1duxY9mg1ILxr2/LgMWt58Jg1DfXxdMUas3g8JPX1tNVnd74haAjPYbJpKI9WU1PXvo/HE2fmCXpt05d4+sPPAQB3XHJmVA+Q7N3xBUKoDgQxfkB3fPTfb+ANhOBx2rHp/jGGz9refBOO++6DraoKoR498PGdd+KrYRPw/KeHRBvivWe57QBMPU70b/IQ0TnpGnScev90Pxr03C7VQ0LnGTl/NSqqdSVC+TgbgPEDuuOxqweKtlK/XvCDTsIjCABPf/i5OAcAzM7XPVh0bhuA9FSX8PI15TPYlB6teGkxhlanTp3gcDhw+PBhw+vffvstunbtavqZRx55BCNGjMBvf/tbAMDAgQORlpaGCy+8EHPnzkX37t0jPuN2u+F2uyNed7lcvDBpBLifWx48Zi0PHrPGZeqoH2Dhmv2YOiq3zv1uNWYL1x5EaUU1Fq49iIILzmiQ60e7RjzXTzbJ6M/GQh23ggvOaLR+MmP64i0o3l6G/IFZeGrKkIj3Velvlbr2vdU8Uc8nHwe7A4XL9iCoAdkZHst+K7jgDMDuwIIVe+FJSYEvBFT4QgBs2FhSiUqfBg02+IIa8n7/ce293X8/MG+efpJLLkHwb39D5caNeP7TQzhQXtuGY94gPCkpmDrqB6b3vGhDCRas2ItKr1+vZbX2IKbl5aImZEPXjDR8V1aJ4zUavqmqRobHhU7t2mBoTgdsLjkm7pv6obzKh2+qqrFg1ReA3YGFaw/CF7KJ+3HYgBSnHdX+kLi+LdyPLpcLd4w5C4Xv7ERQ0wszn6j2Ixi2tjaWVIr2L1x7EN9UBQAAS7YdFu0GEH5dd2B4XHZsLKnEwrUHcd4Puoicr9SQDZ3atWk2z2Bj/6Ylcq0WI4aRkpKCoUOHYtWqVYbXV61aZQgllDl58iTsduMtOhx64mALiZhkGIZhmgnRRAaivZcM4QhR20chnuTy+l6/uSW3NxchjqaQqq7vNWmhTPLkKrEEJura9/HUV1LrbKlqfdGQixGTUASdZ8KgLDhsgMflMN5bRob+54wZwPvvA506AdAFTLIzPBia0wGF7+w0VSaUIdl6WlUOzekg+nFXWSWCGuB22oW0PAAM65Vp0Y82w3lLK7x6U8P3UzRpAGbl90N2hgcDs9PhsAETBmWJ88hCF6N6d0a7VBfs4pSaoRAyvZzqchiEMTwue1hN0QGvP4Sl28pQWuHF5pJjKJo0ABkelxjTeOfBqSjrTrQYQwsA7r77bjz33HN44YUXsGfPHtx11104dOgQfvGLXwDQw/5uuOEGcfyECRPw1ltvYeHChfjf//6HTz75BNOnT8ewYcOQlZXVVLfBMEwjcCp/sTMNQ1PKFovaPgqNYXREu0ZzMXrqQ12/K5I95vG0o77XzB+oGx35A83XQLEK7TYkap0tK7W+WBQMz8HWwrHYWjjW8Lkzu7TFae3dtUbbb34DfPwx8PjjgLM2wOvac3vgk5kXY+2+I6Yy7CpDczpATmBZtfubCGVDqkVVvL3MdPxINRDQImpXzRjXB1sLx2LGuD7ic9PycoURp6o2yjL2FV4/QmELsLSiWly7YHgO5kzWjSa3s1aefuGa/UJN0e20wyHd2NCcDigYnoM0txMVXr+pMqWV+mVdFSJbAy3K0Lr22mvxxBNP4KGHHsLgwYOxdu1aLF++HDk5+oP09ddfG2pq3XTTTfjDH/6AP/3pTxgwYAB+/OMfo0+fPnjrrbea6hYYhmkkkrkIauwfgdb8o9MY1NXzFIuG9OzEahfV9qnr5xlr6vpdkeiYxxqjeNpR33n21JQh2P9IvmnYIBBpOJu1KdbzNbhoJQYXrTS8T+eZvWRnxHtW9xaPEU9tGdW7szBK1PeXbtO9eKevegevPv9rvLxih359mw0YOVKcQy0uXeXTQ+ucYZeQes/0ubX7jhhypqr9QdH2p6YMMZQQiO2hq7Vs1OK/8lio5zIbE+rPgdnphrPL/QsAFV4/FqzYK4y9Cq8fGR4XZozrg6JJA4SxRQadWodLRm0j/T3WvG3N9bValKEFALfffjsOHjwIn8+HzZs3Y9So2iS8l156CWvWrDEcf8cdd2DXrl04efIkysrKsGjRImRnZzdyqxmGaWySGdLU2D8CrflHpzFoKM9TQ3p2YrVr5V2jop67qXaMk33epjAY6/pdoY55fQ0pq3bI521sD6JZm2I9XxVev1i8y+dx2HRxhgqvP2neWbnIb5UvgHnFuzG4aKWo+zSveDecwQBmf/hXPLVsAXL+txtjVr9huD4ZGCQOQQTCrqBASBPHyPckh/aRQWODHoq3aEMJJj69DqfPLMbEp9cBqC3QnD8wK+IeqRCw22k39K1qrGR4XCiv8qG8qgYZHhe6pafi/iU7UbR0lziO5gug17y6RhIQIYOQjvEFgpZ9S8aXWm9s4Zr9yB+YhQyPC1W+gGG+y0Wo5bkTa2xbc32tFmdoMQxz6pLIIiyZC5LG/hFoLT86TeVlaW45RdGgPhqa06Fe7WqqHeNkn7cpNhmS9V1h1nY5ty7WGFm1o6H7xOw5VRfrZoV1rZ4vcx1ooF2qCx6XXeROmbWBDKR4vzPkIr8VXj+8/hAqvH4RopdWUY6/vT4bUz97BwDwp/OvwV+HX4WhOR2iXmf64i3CKJkwKEsYJLJhIof2fTLzYiy9YySyMjzw+oNYuGY/tpdWAgC2l1Zi0YYSkR+3ueRYRJ/T2I/q3VkYKvI1yFhJczvh9Yfg9QdR6fWLAsr+kCaOU+eLmdeJjnE7Hcjw6CqNvkBQjA/1Z4XXj80lx8R5yeBcu+8ITlT7I4xmuQh1Is9VawhBtoINLYZhWgxN5elp7B+B1vKj0xzHq7H7Nl4vx+aSY/VqV1PtGCf7vM3VEI5n4W/Wdjm3LtlCEslCfk7pfmlBneizS7k/ahgfeboy09wRuVNyG0h4Idp1zTx8JIBBhkL+wCxc8v0hvLfobpx/aAdOuj2469oH8Ny4qSi8YhA2lxwT1yHj5oIf6GIYr236Eku31YqFDOuVCbdTF1KjP0lpsMoXwMYD5aI95NHpmJYCVzjkcGB2ekSon9V3o2yoyAqQGw+UI/feYnRMS0GGxxUh8Z6dkYoqXwALVuw1bNqQwIjH5TAYubKRqBtvQXj9IbidDpEPJguKqN47AKZhkM3t+W0OsKHFMEyLIdlf4pzX0rC0lB/dhpwHdQ0XSzaNZWDWpS+bMjQuFur4JaouaZZbF28fRfMqxfpMPP1Px3ZMSxFeFHVBbZb/UxdlwlhhkWSgALFVBs3GZOGa/Zgxrg9m5fcDANS8sxR/fvbX6FzxLfZnZmNSwe/x9unD4Avo3ibZGCHjZuuXFQD0+lfq9Si0r2dmG5w+sxj3L9kpPD6ywAWda1dZpfAyLb1jpEHYAwDKq3ziT9mLR+GBZDSVVnhx/5KdIs9se2klTlT7cXY4TBHQ867Kq2pEe+Qwytnhdnr9QWSmpQCACH+kMSLvmYovoHsH71+yE98erxZ5W2TYmgmVNLfntznAhhbDMDFpLgZJsr/E6+txaS790lxpDj+6VipYMg3peatruFh9aay5aRamFK9hYnWO5oQ6fom21Sy3Lt5z1KVfEvkMHSur18meDvJkzCvebchPko2BuhiLZmp0JB0uGyNmohqAMQ9IvWfynG3udAYqPO3wYe/huPKGP+B/nXsCALz+kLge3R8ZXVSwd+rIXhFGHz2nu8oqDW0h7xnJwZdX1QCAKCw8NKeDuM+hOR2wYMVezF6yE95wHSyvP2Qw1GRVv0qvH2aQITdn8gCR9ybX1aoMG1xef8jg9SqtqDbkz9E4rNqt16e1AcILuXDNfnj9tWGS/pBmkLhPxvfWqfL7yYYWwzAxac4LofpAi4pY8fpWNMd+OVV+vFTiMaKsxqshvUoNYUglYrwsWLG3QeeD2nd1MUyas+dTHb9ktDWad0c2LhIxaGKdO9qxstiBfL80dvIiHoDBGJDH1WxemoUlziveg9IKL+YV7xF1s8ibRm2QRTXUubNq9zcIavqfFBqX4XHhjmHdRI7YkbaZuKpgAWb8pBCV7jQhce5x2cW9yvlGn8y8GNeGRSOeX3cA/bPSDcIV1Pb+WbUKfhMHZWHGuD7Cg7R23xFhnIQ03QDaXHJM9EHx9jJRb4vqVMmGmvwMUWgg1cDKzkhFdoYH2RmpAAC7TX+DjNMJg7IMIYW28L16XA7L8VfHN93jMsxz+bP2OGqZWc2Dptjgak6wocUwTEya80KoPsj1RhpD3rkxOFV+vFTiMaKsxqs5eN4SIRHjBUDEQjeZRpfad4kYJrG8Hc2RZMyVaKIXsnFhZdAkq31mEuQyNHYTBtXWglLfi6VGKB9H75Mx4vUHRd0s9TuYalN5XI6IuVMd/nx1WHSiwuvHsMN78ZOfjkHBwfUiR+wXN16M34zviwyPC6nh/KRZ+f1i9k9ZZa2Xb+2+I4actR2llcjwuDB38gA8NWWIYcwqvX54XMZldXmVD0NzOiDD4xLGkctuQ7rHhVn5fbG1cGxE/xcMz0Fq+DxkIFb5goY//SFNzBEawzS3Exogihhnprnhdurncdh0w5DyruQ6XRMGZcHjsqPS68fEp9dhcNFKLFixF7Py+wrPng2w7LNYoaX0b7XuVnP8/WwI2NBiGCYmLW0hmijqF368i73m2C+nyo+XSjxGVHMcr0RIRKFQFgmwUiNrqPbJz020PjdrT1NsFDQX4448WLIqX1M+z7EMMRWztsq1oGjekjFC3qWhOR2EV4o+u7nkGDQAmWkpEfL5Z2enC2Ni2ugzcPveD/Dnv94NlJWhZNZcPLv6c+EZk5X65NA3oFZSfca4Pli0oQQjw0Z/RmqtlwmAyFkzk6enMSNPUmaaG3Mn19ae8vpD2FxyDL5AEH5JLl6Vv1chaXkAQgWwtMILXyAovFVq/hwZp3a7DcvCoiIARDjmsF6ZSHM7MWNcH8P34VNThqAmoIcZbi+tNBj7VNg6qOlKjISsEln4zk7DM2vm5Taru9XSv4/jxRn7EIZhmNYN/egQ8mKvJfwIyDkAlHvQEtqdTNQxbExkdbC6tiGec8hCBZ/MvDiu85rNbXkhnIy2q+2L97mhBbiqWqa+1tDU93lPVh+azeFE5nV92iF/FkDcc1HuM6u2yvOWQvbcTodY8I+YvxoVXj+yMzwGT6g6D+Tz7H8kH6iuBn71K2DJ8wCA5b0vwMz8O3H8uA8LVuwVn482p8qrfJi9ZCecdhvsttoQyc0lxzA0pwPW7jsiPEAADHlqRJrbiVG9O0d898rHzl6yUxyf6rKLHC2r/vcHaw2tE9V+5A/MwuaSYyiv8kGDrn5IfUfjUOULQFM+O6p3Z1Gcmo6l+lgAxBjkD8wSSos26GGEdC8kS79sW5noF3rtcKU3Qn2Q7n/hmv3YeKAcm0uOifafahuAABtaDMMwETTFYq8+0AKEfvRaioHYWkiGYR7POeozL60W4cncVEi0ffU1LJLBog0lKK/yCeGCutAUGzNm41mfdqiexGTORfnYBSv2osLrF4p5co6V6glTrz00pwMOV3rRMS0FV8z8B/66bD467d6GoM2Ox0fdgP877ypMGJyNzSXHUOULCMW+gdnpphsTuuCDbvD4Qxrc4ZQkXyCEb6pqv09lA1D1rpVX1cDrD6LKF8DWwrHivYVr9gsjZtGGEqS67Kj2hzBhUBaG9coUhg55UQvf2Rnh8SGCGlC8vQxFkwZgwYq98Pr1mlfk3a7yBVDlC+B4daR4RvH2MgzrlWnwLFb5AqgIC23QGD81ZQiG9cqMMLYBoH9WOraXVsJpt6G0wmvw8MkGlNn3CvUhEP/mUGuDQwcZhmEUWlpIg1lSO9N41FdURT5HPOGA8ryMN+ytMYRAYj03zSVET4YW2yRcIBNvexs7vG/RhpKIcK26tEO+P6tcRqs+qEsumHyshtrCuZSnpZ5r+uItyL23WISskXT6V/u/wl+enoZOu7ehMrUtbvrxg3h2+NVIb5MiwhzlfDIqHKzee5UvAJfdBhv0WlcU7gdoegiezWZaXBmofZ4o36zKF4h4j4RoyDjKyvDgqSlDInLvFq6prbElh1HOnTxAhCEGtVoPWYbHBbfTIdQT6VxStKEQ0ZA/R+Mwqndn0/w32RiT66gdDSspprmdBkl5Ckc0g3+TamFDi2EYpoWTaC5FfWlOC+ZktKW+50hUVCXRXKZoxJvTlKgQSH3rYdWnrfW9TiKY5UUR8bZXXqA2xjMhL8ytFsrxtEP1gMm5jGYLbpl4xsDsGLUQbjTjUA5Zk+t9nZZ7Glb8cBzKz+yL637+J3zc6xyDNDn1xcBsXSFwYHa6IadocNFKUV8qze1EVoYH15zbA+P6dxef1xApaS5DeUeEnFNFc6rS6xfenwyPC+VVNQZFSTk/zeOyo12qC2v3HRE5UrOX7MSCFf9FUNMNG3qdQhVtAL49Xo3yqhpkeFzifgEYjC4Vs/w3Gi8y4Cu9/ogxGtW7s+E8Gw+UGwx+ebw3HijH4cracNHGejaaI2xoMQwTk+a0sG5KuB90zBagVn3T0H2m7h7X5TrJMgDi9SgkU/Ah1jXNlP3ioS5tjPWZZHl+Epl/sSgYnoOthWOxtXCspepePO1tTBEPqiNF0uN1bUe0+5PzocyOiXUdK6+b2t/RjMP8gVlCZOK7IxU4/HkJghpwtKoGBatfxbz7nsNuTye4HLqKn8rSO0bi4Px8LL1jpDAYl26rlVh32ABfICi+P6hgcXUgBE9YpVC9b5LgX7BiL/IH6mp9NujCHPI9ygqAZACSyqJs2G4uOSZqXqm1s3ThjYD4O0FS8mQMklftmnN7wBV2ZdltEN461UCy8sAvWLFXhPlpgMHIrPIFsGxbmWiHhlpDmAx+eU7Qe8XbyyLmSrzy760FNrQYholJfRYRrelLNJmLqZbcL/FKO0d7PdltAVDn6yTLAFC9Q1YLiliqgYnMjViesLoaJXVR4ozVj8kKyU1k/tWHRNrbmOGDFEKnhjpatSOe8D/1GCsvRrTryNejnCMbELMOmNlmyaINJdhccgzpHhdOq/wG/3z1Hrz23qM4vW043M3hwJK9x4T4g6wESMZQ39nvYXDRSkxfvCWi+C+FvrmdtbWiqGAxqQeSMTjx6XU4fWYxBhetwP1hT1iF14/NJcewZ854HJifLwQnpi/egl4zi/HtiWpRI4vyouS+M/s7XduGSDI8Tjhsutog5VdlSMalL6BL3ZOyoQ1Al/apIiRW9uhRHpbqgfcFdIPNZbcZDDHKqyPDcWJY7l+tNSbPifyBWeI9da6ozyoZwdFUGFsybGgxDBOT+iwiGnOnt6FJ5mKqOfdLrEW12QLUqm8ojCaRoquJYCZjXtdzJDvkUh1j+vfmkmMJG0d1xaz/4zm/2id1+UxDkcj8qy9NWerB6trR7tWsHfLYqXlPZsfI55EX43J7om0qyKGN6R6XMIJi3Q9Qu1lC7Tln32YsffkuDPhmP3pVHsaaK3sCgCge7LDpoYHqQl72EhVvLxMGDIX7nZ2djoLhOSKUUSYr3di3lONF3iUgMr+JjLulYa+PP6jhRLUfa/cdQWmFVxhAHpcjYo6QV4zug+Tr6d9zJw/A1sJxwjAkFcSthWNF291OvT10rvyBWcLzScWgqWgy1bRSN3zI6ExzOw1jD0CEexZNGiBC1I9W1RhqjQG1XvOnpgzB/kfyDQIbsqLkqZS3xYYWwzAxqc8iojV9qSZzMdWc+6UuC32rvlETvxuK5iBgYuUVoJ3heOpfATAskOqLWf/HO/esxBKaI41lLDcmVtdO9F7lsZNDuoDYXlb5s9H6Qn6PPlM0aUDUOm5qWOuo3p3FvJ82+gz8dvtS/HXx/cj0Hsee7D7A5s1Av37iPEeralA0aQCOVtWIdtO9ZHhcIvyPBBnSPS4RGrerrFL0JaDnP80p3g1A92zJBqQrbJ1leGqFutX6XoXv7BSeJiKo6V4iuXaY22kXxu7Ep9eh8J2dQihj6R0jDQbM0aqaiM0OWS1w0YYSpLnJOHKE2+XGnHAxZfJ8Fm8vQ8e0FCHwYUOtkqFsAMlG5/TFW1AeFsHwBUKYMa4PZozrYwjxVA1ks/Btszmjzl+5nllrhOXdGYZpUBpbrrmlEE+/JLPG0aINJXh+7Re4M47fMlmOORkk43zJ7IuGQhUXoP+ofg0Qn8RxtNAwq34we51eI4ON+l+ee9H6Vb6fhvDWxDuejTn26rWS/SwkgnztRMZdRR7v1zd9ie2lleifpQsnyLlYZnNT/Z5S+8Jsjpl9ty1YsRe+cO5TlS+A6Yu3CKOPal5V+QIIasCuz8vw1JL5wHuvAwCWDB6Lk088hb49ehj6ZWhOhwhZdJIfnzgoS4TzyW2dV7wHXn8QdpsNg4tWomdmmwgDacGKvSi44AxDCGR2hgefzLzY0N9yn5ABRzllpBRIgYBj+nUTNaioXhV5ylRRk2l5uZhXvBulFV6ced9yUWSY7puk66lt+n1XR3z/TMvLFcfsKK0UOV0elx01gRCCmi4rL4+z7Pmic3v9QXFdudCy3A8L1+xHeVUNKrxeUTPM7Pkxm6+tfY3AHi2GYZhmSjJ30xeu2Y+ysApULJLtHUjG+RrDs1DfvDmr/BizOkGJnoegfih8Z2fMneN4QhWj9WsyvVhq36p5GdH6vjG9SlYhdA21EKSQM1Kjk4lH/c8sv8nqOiPmr8ah8pMAICS7Y+XiRQsXlK8fa47poXxBVIfD+ZZuq13IkyAFoIeo/fb1x4HXX4ff7sD9Y2/H49fcg+tGGxUFKbRNFmOQ52nx9rKIeykYnoM9cy5FdoYH/pCe12Um/V4dzlWSDaiOaSlhQ203yiq82HigXHimSA0RqBWtCGr6vVT7g4b+WbvviLgOhQYWTRpg6LeC4TmG+l6qgAblzUl1iWFTxpIMGgqvdJLee5iiSbWy8fKconOQEAlR5QuIHC7A+PzSPK0Oi3JogOXzE+tZbo1CGWxoMQzDNFOSudCdlpeLrHRPElrVNNSnL+L9sa7vgt5qIWpVJyjaeWiB/dqmLw3vTcvLjbpAUnfGY/WZujhTF6bUjvoudGL1bWMYfPUV9KjLou+1TV/GlLwncYVoIXmy3LZZe4HoYjCy50q+v1gL4WjjEs8mAh1DCnjqgh/QpdFt0EPUAOCREdfji46nYcqUh7H4nMsw7aIfiHPJfamqLxYMr5V075+VbjBCZWOW8hbllnhcDlw2QJd3Hx/+U83TonpYGnTJeTIWd5RWol2qnsNEt+ey2wzKg/R8kffM43LgmnN1D93GA+Ux51V5lU8Ie1DYpwzZXDSWdO+7yioR1Iw1sNxOPU+saNKACCObvE1PTRmCOZMHiH6q8PrhdjosQ/wWrtkv8uCizYdYz3Ii86+lwIYWwzBMMyWZu+kFw3Ow8q5RSWhV01CfvjD7sTZbNMdaBETzPlgRj5Fg1hZq8/PrDhiONVsg0euqghwQW9Jd/lw0r1h9FzpqP6h5GYkKPNSFeO4l2rXq0hfPrzsQU/Leqo4Xve+wRcptq+2NJQZD/WumIqjm4sniKbG8q7E2EeiYkKaJe8jO8GCiJIceCAQxpFQP6fMFQvgqMwszZi/C1wN+aPD2qP1vFmJLnjrK26J6VmTMUpjijHF9MGfyACEeMaZfVzx29UAAEH+q91ShSK/Lf6d+eCj8bBZO7G/IVaPnS9xzMCTk75dtK4vw7npces4VGaiysIfsyZKRDUo5J4vEMyYM0pUArZQkyUs1e8lO4cFUZerp2aB8Ll8gJK7nsOky96TWWJeNCXW+Nffc0HhgQ4thmEahpYYAtNR2RyPWLntrw+zHOp4kbZVY3gcz4jESzNpCbSbJaatzRjPSEjWO6uoViwfVO1YX4ynRZ9FKnMQqTC4WdemLqSN7xZS8t6rjRe+bGdbRkKW81fsjFTw59FTN7ZHFU9RxklULo3lDCTkUjQzraXm6tLjH5UBb30n835JH8Marv0Peoa2o9gcR1IAj3mBMZUmr+UqGIgBhKNige5GoiDDdW2aaW0igEyPnr0bf2e+j7+z34HLYwgZLZD87bEaJ9aE5HQzznNqzcI2u9ihLvPtDmpC/J7upwuvHog0lYc9ZEBkel5BoJ7qlp8JhA7IzUg1t0T2CQfH9tF3KyTpRrRuIZJgu21YmaoGZfU/IoX+qsShzotovaoOR50zuRzPZ9ljfTep8aw4iR/WFDS2GYRqFlhoC0FLbHY1Yu+ytDbMf67osmofmdAgv2OxxfS7ehbxZW6jN14bDi6yIZqQlahyZ9VNdFzqJGoCxQtSonk8i8zZWvlWiz3Zd+uLac3vUe6GYqLEuCxqorwGICD2NZsCo4yirFpp5Q61yxYb1yozIN+tdUYp3X52BsfvWI2C3o+OJckOoXV36AdANADIUyfBKddlR7Q9GnF++VwrTrQgbEF5/CP6ghqwMD0KStZOdkSpCFmeM6yNC8pZtK8P0xVuEp2rBir3i78XbyyJEN6hdMrOX1KoXVnj96JiWYni/tKIaQU3/E6gN1dMAVPtDQt1QhgRHpuXlCsOOrqF6mcnD1zEtxeAVB2AYVzl/zeOyi1ywWEqprcFDlShsaDEM0yi01C/YltruaETbZW+NHjyzHf66LJo3lxwTxUzVzyViWJjlQiWzfEJj7QJHmytmu9lqWJpMNEl7q/yiWMR6dpvjs13X50/uP9WLNC0vV7w/qnfnCA9ZNC+COo5yIVqz6/sCIcscG3kcry37D9544U6cfuQQqjp3w69+/gT81xWIdlvlBcrPMhkxaqirLJBBHjrKrXLYILwzqoLgw8t3R1yPQjrJgNH/tCGoAUu3leF1KYeScrfIAKn0+kVbaCwohwzQDcKAEgeoRgWSDL2JQw2AXqdsxrg+Iry0JhASYYcylV4/Nh4oN7xGkvCE7OHbVVYZNVeKQloB/fuQJOllj5aZbHtr8FAlChtaDMM0Ci31C7altjsa0XbZm4MHr74hYipmO/x1aVO0xH+136Id39R9HK2/Eul7M2MqFrK3QSaapD0ZDnKOSDzEenabw7Ot9nc8c8NsjOT+o/sCgMOVukJetP5NBCpEq0qn0/ndTruld2xaXi5Oa+/G/G1v4tG/PYCUk9/jm8HDkLZjK/76519iWK9MALXhjdE8n2TQkNoeYRbqJufBmeV8Fb6zEwtW7BUGkiscJ+hx2bG1cCwAiELBZ3Zph7KKWvVWCtEjT7eau2WDbtjRvV1zbg/MnVyr+BcIGU0rm3R9oDbHioQp6JiJg7IMRky7VJeoj1XtD4pz0J9kBMpXK62otvzOIg8VebbUOmsFw3OE0S0b97E2fFrjRl4s2NBiGCaCU/HLEDh171sm2bv8denTRAwRqnUTS3AgO8OD/lnpsEFX8Ep0jOXEfwAR96T2WzShgHj7eNGGEoz949qY7UrUaKtrCB+1KdZ40nuUhC+fW/Y2yDSGGEZ9aYjvB7W/Zc+U2fWs5jv1HxXHXrShxBDmJ/dvrDA/GbmIbTxqjbIxLHuMaOwu2LsBl779VwDAi0Mn4MdXzwG6djX0BYAIzyf1BS34KeQu1WUXIhCqp1oWhZHz4ORz1da7AjJS9fsc068bsjM8mJXfD4C+oUChdrvKKg3Git2me1nnTB6AzDR3RL+ke1ymnsEUpx6ilxUOQySp9zmTB+Dzhy8TSpL+sCG2cM1+jOrdGdkZHkwYlIXNJcdEv1L7nI5ao4o+FwhpwsPldNhEfpd8TfU760S1H4fKTwpFxdIKL9buOxLxDJoZ97Ge0Xi9/K0JNrQYhomgqXfcm4rmeN+N/QOU7EVtXfo0EWPPavEu9xvd09GqGmjQFbzqIxRh5slR+y0ZhsPCNbFrn9XFMI72mVjnk8fTLDSIjjEzMqMl1kfrk7o+A8l8duIx6BM93+CilSiv8hm8nvLiVe5rOU/NbL5T/20uOSY+I4f5yf1L4wAgwuAyC2slcYxohpnZ+KnP/sI1+/F6t8F4/YeXY9YVv8Vj42/H8UCtAScrI1ZKKoHyuage1az8fsjO8MDtdFgK1NBn7l+yE9MXb4l4fXPJMdFHPTPboDIsGvHRf7+1HDcq9CzqZmm1IYpy2CsZM6rCny+gqw1SKCPlXB2tqjEYiOVh9USX3SYEPJZtK0OVL4BVuw+bepL9JnKEeu5WEHab/j7ld+UPzBLy8gSFA9JpZINWxcpjH+uZs/p+aY6/vcmCDS2GYSJojrkLjUFzvO+W/gNUlz5NZNFttXi3EomIJqVd1zbV9fh4FiVWtc8SkXAHjGpxycoJszqPlbpfvG1VqeszkMxnJ5o3rq7n04v4hgwGqRpqR54dMu4BWBqr6uetwvxkSXiSP1fzqGSjitohH2cFGZCDi1YK79M8x//w+srtqPIF4ElxovDS21E86EdwO+3CQCLv19CcDijebgxxM1vUk8EI6CF7Zs+0bPjIBYzlMDgybCkEENALFssGLlDrnSX5+JCkGEj9IYdlHq7UDai1+45gxPzVGNW7syhgTCGPFCCozilSHQR0zxS1i0QsqJixLxAS51ZzuDI8tXWztHB7ZZZuKzPIuQ8uWgkAIn+P1CERbqdqMFptpphtDsjfb/F+Z7Qm2NBiGCaC5hKq09g0x/tu6T9AyexTM69CIj/csaS044U8OaN6d47LY2JlUMXKcSoYHln7TFXgU70MVteSw8iitS1R+eV4FlP1NXjq+gxEU8+raxusDBwrrEopWBn9ct/J3iRfICg8JLHyzobmdEDhOzsx8el1Meu+naj2G5T4VG/XwjW1ku/RFAEJWoBXeP3YcuA7/GXX68i752fo/qufofKkDzWBoKgJBehGY8e0FNy/RH+ul0q5VxkeF3pmtsH9YSU+s0V9hdePzDQ3ZozrYzCMKHSSIIEN2StGxppDsVK6hyXUh+Z0MNzP/Ut24uuwh1mDHhao5qPRmJL4hS9stC3dVgZfoFb1cM7kAZgQriUW1IB5xXtE232BYES/ZmekGnK3AN1TRfeTLsnMA0CFNwANuhGqy9DrIc/yGXyBkBDRsPIIkueNDEZ1g0vdTJGN2ESe++b425ss2NBiGIZpBOq60GuMH6BkhFg1RogjeRVsgMjfsLouLaLUxVcy2mgWphWr3cn0rMieDQBQw7PMrmWlFmemJpaIURPPvSWSk2Y1lnV5Bszkx+uaG5JIG+TcOqtSCgXD9aKvlPNnBfWd2+kQhnKstpJRvb20MmrdN9lLR4bIxgPlqPIF4AuEkOFxiZwvWkDHMjTJ2MjRvPjrPx5A/0X/BwDY3eE0ODQN/bPShTFCXpIdpZUR55kzeQC2Fo41vKeGqMleLrMwRQqBG5idjrX7jogwTTmPrWC4Xqcsw+MSRsg3x2u9UXLtK8DoGaryBVBe5cOCFXvFuSiMdu2+I5iWl2tQFST59ZAGIVBCeP1BcR7yWMkcrqxGSKs9F3nTyPBVw3dddpvIrdObYMPB+fmYM3mAuM9qfxD5A7OQ4XHB47IbPKeUW0fvqd5Mq80U1YhtyZuEyYINLYZhmEagOYcAJqNtjXF/9MOd7nGJxWMiwg60iJhXvDtugyvaQjyaJLlZu9UFh1WOUzznItEBOoeZypuMVRiZHJ6miglYIfdJPIupRBPl5WK6dcUqxDRZuSFW84K8rpRbF62Ugtm1zXKkaJzV+ldW5A/MEup1HpdDLKLVttL8zR+YJTYNlm0rC4en6V4VUupcuq0MHdNSIsbQrL1bJ3XBv17/Lc7asQEnXW78auI9eOSiWxCwO3C0qkZ4lemapM5HXpeB2eniOqkGWfVaERo1dE0VEZENJDI4vf4QfIGguKf7l+zEmfctFx5lMmPG9e8uQiXV2lcy/pAmvHOzl+w0tKvC60fhOzuFKAWgC1+Qh4gESmQpdl8gaOnd7p+Vbtgksdv0PqP8u4LhOZg4qPZ9um61FGY4uGglipbuMoQibi45hq2FYw25bh6XwzBfqyVpfDJSJz69ToQiA+alG6ye+9YsfGEGG1oMwzCNQHPe3bMKA0nkh7Ax7k9edMp5LIkKO1T7Q3EvrqOF98UrmW214DBTSJNrfSVyLvl91ZMXq23xiB3IyAZCMj2ucjJ+oqqHsUIgzfraylCMZ/5bGWiylwgwllKIx/izOi95XuJ5xp6aMgRZGR74Qxoy01KQmeaOKqlPnpsMjwtOKTzNFwhC1lfYXlpp6BM5lFcYx3//O3DBBcDBgziR3RM33PokPhyYJ/KoaKE+ffEWgzGU7nFha+E4zJ08AEeraoS3mmTVZ+X3M/SNurCneyneXmZQCVSp9ocM9+QPaeJYyod87OqBIlQyXjQA9y/ZiW+PV4vXgppRqv1wZe17ZCDtmXOp8Dy5nZH1r4hdZZUY1itTeLGDWq2hRKibKFW+gDCQKB9ONvysFFjJyKZ+pHMUTRogpPe3l1ZGhCJblW5Qac6bjg0BG1oMwzBo+F225hyDnoycmsa8PzWPxeq69B4AkTRO8sixFqw0H3yByDAeIl6Plnw+q/lFfZ5orS+zsUp0/BIVO4hWTyweooUIxjImohk4cs6anCuSaB5afcIh6fX7LtOlweUcrWjGX6zzWh0fT/titRWA8A5RKGOGxyUW/nIOE4W3DS5aidlLdgqjJagBf1q2DWW33w14vVjTayh+PPVJbEk/DV5/SHhWSDGPPGd0al8gKM4pC3OQl2XjgfKI+6CF/YIVe1HlC4g6Ur5AEDal3RnhfCp69uXCwXTY1JG9IvpmYHa6Ia/J47KHa2Y5MFeqbUX4FdUJp8NmyNuiv1NdLcDo2Va92xMHZYnNB7pPGasyAHJbgpquqqjeh4ZaBdYZ4/oYvGuzw3lxRLuw9D3lj9ltMIQiRxOLkduXjO+PlgYbWgzDtHiSYSSdarts0WjO3re6oOYPPDVlSMwFK32GCrCahfclUgQ21vyiPqckerXvx/5xren8Nhsrek3ORYlGXcQOzOqDxYuZsp3clmhjE4/RoOaKRMtDMxuXeAzoWF7Ka8PS2ZSjNa94D8oqvBFhWYB5KYL6blhYbUaYXUv2EMtCLwBEkV8yKEieXPZ0TBykGxDfBB342eR78eQFU3DL1Q/gvz6XMMRIcIEMLi18bjJ8KHSNzJQqXwAd01LE/RRvL8PGA+WiALO8sPcF9PC9VJdDnEuDbmCQYQNAKDFOy8sV6oFy257+8POI/tvz9XFoqK2XNSu/H+ZMHgC3U6/fparxmSHX3yPDcfaSneg7+z2h9vfJzIux8UA5Ct/ZKepbDcxOR/H2MnQLi3PQfWZ4XMKIXLvviDBO5xXvESGWKrvKKjFnsr6JMXFQFtxOh0GtkbxrVEyZxkEX0nAJg5bGr32qyxCKHE0sRn7GkvH90dKwaZqmxT7s1OX48eNIT09HZWUl2rdv39TNabX4/X4sX74cl112GVwuV+wPME1OcxqzEfNXo7TCi+wMj/BgJArtONOPTnOirm1TP5eMMWvofkrk/PEeu2hDiQj9mzGuT9yCBrHOLR8DIOrfh+Z0MBQZjRcas3s2OuBJScHWwrFxf5aeCwr7oYW2WXus7sUsv6K+40/nqPIFUOH11+u5Vc8rj/PGA+Uo3l6G/lnpOFpVE/f9JPp9Ytp3o05HuyM7cKLz2Vi49iDKwrlIDhuw/5F8w+etrlffvjYba1r0ynPCDHXu0H3RmNmgh/td7zyCEzv3YOlZo8TrtKi024Du6bqq4I7SSqS67DizSztsDwtcZHhcSHM7MS0vFxsPlGPpNj0MTRZ6qK3plIrSimrxPqnszRjXR4S4ZXhc2Fo4FtMXbxHnmjioNv9M/pxZaKHboeGxYUH8bqMDvbtl4GhVjRCe0dugb14s21YrP5+hnE9up3qPs5fsNA1HpHZVSsbr/kfykXtvsSHMkY4ltcLi7WVIcdojxDMof6t/Vjo+//YEqv0hTBiUhaemDBHhnkENlvNbfY4A49jHmjvyedT5R+dK1u9HU61DErEN2KPFMEyLJxkemOYc2ldXb1sin4vXK9jQnr9Ezh/vsXIeUryqc7Hmg7oIVndt1b/LHpa6Uun1x8xNkl8jz4yc82QVomim0GcmSmHWL4l6lM08KfHcTzxzU94tJ/W9HaWVQlHN6n4ARM3bioacx0d99/y6AwBqc7QmDDJXfQTqL9RBoXyqjLvZWJvlwZnlB6rHqWM2Z/IAbO1ZiukP3oxZbzyKHgf2wONyIN3jEh6u9qku4T3SAGSmuYUniTwy1C7ZK5wVLvbbPytdOq7WeHHabcKwIaU/j0vPQeo7+z2s3XdEHEsLfDLe6HN0XlXaHeHjtpdWGowsl90m+lI1lqhP5k4eACgVrWSPFwl7kCIgeZ+oXZQfF9SAvrPfQ7tUCuN01hZIBrBsWxnW7juCoAZThcKQBjHv3U4H5kweIIwsCve0AQaPt+rplMtgkNhIpdcPj8sed4kDs+8+s+cNaN0CGWxoMQzTpCTjC7Y5G0nJoK6GZCKfkxd1VovdwUUrhURyQ4UVym2ONTfiuT/Z6KjvYjZano9VTkwieVzRoHAeVaFOrSsmt21zyTEh607Xp7bRItasXfRaPAp38vUSNb7NnlszZch4z68KJNC9p7pqFdXqk5dFRJuX1L9yvg8QqfoYT7hgvM+CnMskt5/6I8VpDBGjUEDqJ9UgK3xnJwDda+FxOVBW4cXEp9fVFp2+eyQK/vYYcMstcAf8+NcZP8SBDlmoCQRR4fVj7b4jBmEEOZSV8nOKJg3AqN6dxRwkww6oLfZ7tKoGRZMGGIyiuZMHGCTxyftCBgf9KdcoKxieY6gz5QsEkRIW2SCFRhVSQAR0z0/hxP4itJeMJJKoJ68N/Um5Th6XHat2fyOKAo/p102ca2vhWOyZM94glpHmri0yrKsZ6vlYFd4A+mfV5pRpMK+1pZTZEgbcghV7MX3xFtwvedTSPS5DeQp5c2X64i0RhjsZmDWBUNwRAdFysdTnrTWH7rOhxTBMk9Kav2CTQX3Ch9TcDKrtY0asvBVazHn9oaTE18fjSarr3JDPre6qAsad1GjGmtl5zAwrtd3y3+U8LjUp3MqYNSswe99l/SKUISkEyAYYZJVlg4N2vsljQG07VH4SQU3fHVevRcda5WvFo54X7TPxbK7IypDxbhjQnKTFJRk3s/L7mhYHlok1/2XU92eM62MQRZBztMzu3+wcVvdj9SzI56PxJhl38kwB+uJdfmZpLlM/yf1Li/mgBmFs1YSL7JKH5/WlG4GLLwb+/GeEbDb8fuT1uO2K++BNbYP+WbpwRIXXL0LehuZ0EPexdt8RgydKfjZkIRR5E6BgeI6hBhx5sCiPjPLFCI/LjlG9OyPN7RRhwos2lBgME68/JJT1NpccE54mwmEDKr21ohO08VBeVYNl28owqndn7Jkz3iBRv2xbmfhzVn5fZGd4DNchhUD6DqLnXBbPGNW7c0RbiF1lerilDUahEplQWOXQYUNEcWNZHZAMwY5pKRGGLikJkuFOeZQ0JmYeWTNi5WKpz3SyNqSaI2xoMQzTpLQU4YWmCm1IliG6cM1+UdvHDHlRZyWwEGuxmmh7YtVMivXja9U38uvqvaifieYNjXaeeL2oVgv4aMas7Jl4bdOX4n1VGZIWs+Sxke+JQiUBRH2+VC+Z3GYqYquOTyJ9aPaZaHOaFtGyMmR9PdZqKJTM9MVbkHtvMTYeKBfXGJrTQUhfm8ntm80Fq9BU9f5pvsdr4FtdU+5Duj+ScSfPFKnU0TMre0ABRPSvLBBB3kwycgZmp2Ns5f/wj7/+CvjkE5xITcPcn8/Hn0ZMQWqKE0WTBogQQZm1+47E9P5R28gjtKus0rA5oIrOUHvpdUA3QCYOysKs/H4RYbGyx4uOJcNY7wujUTKuf3eDwVO8vQzzinfD69eNTsr/onvwuByG2lTy9wUZNRSqR8qK9JzLBlHx9jKM6dctop8ACA8cFXKeMa5PhDEFAE6HHtrnDLsBPS47ZozrI8Zx4qAsZKaloMLrj+jnFKeuqNgtPVWczxcIorTCi0PlJ9Eu1YW1+46IZ0J9NlTjP9r3jvpMJyIs1NJgQ4thmCbFShGrudFUnre6GqJmXgeqE2P2vozZwtZqsVrXMTPLFVGJ9eOr9o1ZmKB6L4n0p3xsXRf78udkw9HMiJSNWcqfICU0yvmh+yQ5awBCGVE1jOXCxmq7yQtjZjjLC1mzOW/Wh7E8VlahlTKy99ZMGVI9r9l1Ei0CTXlcy7aVCS/D2n1HhPT10m2RcvtmcyHWvFLDMeM18M2uaRWWpYaF+sKhfORVIOPcJh1vdg8TJSOXvIJL7xiJv2RVoM133+JAlxxM+Okf8EJGf5F7RRs05FnT/3MYSgaoYyPfE4WMLttWJoyn8qoaUW9LvtfaMOYaMYfJY0T3KBfXlb1ZlEdGUuq6SqG+FJbraM3K74cMj0tIxlcruVA05wqG56BGCeMrr6rBxgPlAIAx/bqKnLbNJccMyooel8MQBkneJFk5kIwp8ozReBUMz8HnD1+Gg/PzDWai22nHwjX7hWFJYyOHrtJGgt1mE/1Kn9FgrPcFwDCXKrx+g/fOKvwv0e/LlrLhWhecsQ9hGOZUJhkqY/GiflE3J+jHKNYPQaz+SrQ/KRQt0eupfVkwPAfXDs3C8uXLTd+PBzMVKVL8WrBib0JjJntm5AWUfC/x9rl6zwAi1LTkc8ercBer71Vija1qOKpGpHy9wUUrdSU1t76MknN+yPMlK5qp17Nqu9zGWAqGQ3M64HCl12AMxjPfAETMLbU9Zm2LNZfUOSt7ieRrJDJm+QOzhHobeQBp8S6rwFnNwXjnlVk4plVfmvW72g+k1qj2acHwHIyYvxpBTS+Am5nmFtej54nU4+R+kz8vt01+H7NmYfO31bij3bkoC+keIVv4vHS8HK5X+M5OQ//R+RdtKEHf2e/D6w/C47JjTL9uqAz3vdNuE+F0Xn9QGMIk3T9i/mqUV/mEIVHtD8JptwmP0bBemZhXvBvV/hBW7f5GGChEIBSC1xvEwjX7hSEwffEWLNtWhiMndAPjnje346N9R+ELBJHqcsDt1MMR39v5NfxhK5CET6bl5aJ/VrpQUqR2y14veV4sWLFXzKuaQBBj+nUV9wjo3wkBSWowJAmD+wJB0zkzYVCWuF6a22EQ8QA0sflE39mbS45BQ22x5tc3fYkqXwCucN9ToeU0txNVvoBoE4Uj0/hoqBUJ6Tv7fYzp11XMs0RJ9LltSbBHi2GYqDSmJ6c57GrFkzsUjUTzO+qL1fnkBHSz+0k0r0a+lhyaVOmNlEmOF7VPEw1Ji5U3Fe3YhiBaHo3avnjnenW4YLKc80OeA/p7It7gWP0gn4cMQzn8S1bYk6nLvSWKel4rr2giXtbaPK5+BiW4GeP6GJQC452DsdouK7bJfSm3mfLqZPW8aP1g9b7szZQX6DPG9TH0G3mIqK4THRs89CXS7/gFcPKk3r7H1mBqp9HCyAJ0JT2zHDLZs0T3TGGa84r3CAPI6w8JoQWHDcLDQ+F9JD5R5QtgXvEelFZ4DWGAZDBo0PtL9zDpnplqfzBCVdAf1MT34uCilTjj3mIsDcu1kwGxfOfXIh/V6w+i0uvHsF6ZSEupbRuF1C1YsVeEXKqBfKqBTlEBcyYPEJ6yVbsPo12qbtiT94raQXNPPq+Z+M2wXpniGFmdkf6tep/k7w9Az7+r8PoRCBkNvBnj+oi2BELGf4v+lIziZCirtkbY0GIYJiqNafzUNxcjGdCCwayYajzEuwhKRn+ahRDRgg1A1PCvRPNq5LZTUV2gtt7NjHF9Yi5wk6EiGO34aPdU32TreBbv0fJo1J1ota3q+WkxrOa80H2qOUFWC/54hSvkRbCalwYgpnFGx1PRVRIyoOub5Tqp5wD0xbVV2J/s5SS1Pso96ZiWIq5DBVzJGLQaO/l1Nc9p4Zr9ceWNJOt5TmQjINo8j9fDTcIT1J9kWJBH8ay9/0HxK3diwmfv462Lpwij0BcIGsQWSJRB3dghoQXZSCXPjexlctltIv9IViKcMCgLWwvH4qkpQ0TYmuqdAiKNGwBiTkwYlBVhqLjsNoMwR8jsAVOgvCsiXRGjoHufM3kAJg6qFYsg4Yi+s9/D6TOLceZ9y0WBYlJBrA73OQCDoSPXLwNIwMJmCKscXLQS0xdvEZ5Ds76hcUoNh3KWVegFn7cWjsXE8EaCy0HHOMTx/bPSDfeclZEqPKDy+WXKq3zNMuy/qWFDi2GYqDQH46cxiXdxSaiLuFj9ZfU+LXSnL96SkHdCVXZKxMsTC3XxBOjGG+XPUI4D7VjX15uX6FxL5Hgz74yMlQogLd7NdpJjtUfu+0T7hhbDnnD+yE/+b31Ug4l2qcurfAbVwngW8Is2lGDpttpFsKz4pta7MsuBkkP4KMeGVM7k3JtY9x9NpYzGgs5H56Fx3VVWaVrnSBaAUK8tt5sMQTm/L5ZXmMYpEU+3vIEjqxXK140nz8zqO4L6Z/YSo8hMtE0Jytlx2W3wOG244uN/4v9e/h06VlVgb9cz8MfBEwHoRnC1P4SgpnuezPKtaGOHhBaKt9eqWqqKddkZHnRpnyoMqAUr9or5Q8btog0lBg9WdoYHA7PTxb/Pzk4XoZ7UlqemDEHRJD0natXuw9Cgi0JkZ3gw/uzuEXlbKgO6txcCIOTh/PZ4NXyBEFx2Gyq9fvTMbCPuX94AWLX7G3Ge4u1lBiEOCtUrWrYLgG7g6G1zwBdWdwQgvF2vb/pSklUPQt528fp143OplNMG6G2mPLus8P16XA5Uh71zGnQxj0UbSjCsVybapbrgDNf1mpXfF13a60IYupeu9sRlFdURxZPTPS5kZ3jEHPb6Q40S+dLSYEOLYRhGwmxxGQ1aQM1estNUljteaLd36bYysSMfbziSWUJ8NC/P2D+ujaudsUQR6H0AUWtVRWtvLOI1OuP1lgGRBvSiDSWiz83qN9HYRMvVUdsxffGWiHyzePpGXtQXDM9BTVBfpO38+njUsErycpFXwszQplo6ZmqHhMfliFjoRvPE0TUoFC3VZReejEUbSsRuvdNuS3huyGNKY1EZzk2TDUzZy0qhZrTwlkPYVK+vXNCZwmHNiqvK8z8eQY5o9wcY5x/VmzK7biLeZhXywsgebtkbKLedxD96pAJ/LP4jCj/8C5xaCEv6jcaNU/+I0Om9MGNcH6S5nQYPtlkbZaEFMhjIuBzWK1MsyimnqsoXEKIZFSY5cer9VfkCOFR+Uvx7V5ke9nai2o+NB8oj5ku1yOUKYVpeLtbuO2JQXaTiyjLlJ3V5+kPlJ1ETqDWSvP6gCFPcUVppCMuk7w/Z6xbUagsky/iDusFF+V6qmAbZM9tLK4Xkfv+sdFNJd5VdZZUiD4vmc7U/GOHxWrhmv8GT6QvoRpL8HS6HIaqy8zboc4DGyeNyNGh9xZYMG1oMwzQZdVWsawzi3ammRaYGGBa4iaIWpFQX9WZ9ZdbGeNpdVplYrlIsI4EWNWYx+mp4VqLe0XhDqqxCPtVQSvIiyHWnFq7ZLxYiZvWbaBFPoTzR5qyax2ZmGFFOjGyYkzGmfm5c/+4A9F121RBTw/KG5nSIUBKUjWFVllr+e3aGB3MnDxA1gNTwx2gy/HIo2qz8fkLdTB6zNLczYU+vPPbycyZ7vehzT00ZIhaYM8b1EUIftJBvl+qKOO/afUeEpHX/rHTLOR7NMxnv/DTbwDEzAuPF6plU1STl9qnPCHm/AOAc7TjefPUeXLr1AwTsdrz109/g8YLZ+NWEQRFlH+Q8MyAyr4/yncjjAUBsRvkCIXhcdqR7XCJ8j2p1UV6WfH7y1FKYGhkuJJsui0jIzw59LtWlj68a/ud2OjA0pwOWbSsT56R8rsw2LnEtUml0hQU3SFE91WUXz/FsqRCw3QZDOJ4V8rm6padGqBoC+jko/2t7aSWqfLW1vVzhjQtV4p3y7uSNG7OwwvIqnzCKAT2fjb7Dp+XpIkd06oHZ6ZiV3y8sV6+bDRqAecW7hVR9ZlqKeOaa6296U8GqgwzDNBlq3kBzJZqanJzYDtRNcQmAIaGa5Iej5VjUh6x0D6aOir+dsRShaEEXS4Qi3nbL/R3t3GZtKK/yGZTrVCU7NcSRFpALVuwNhxPZ4HbaDR4cuU3lVTXw+oMGZTyz9soqX2Z9Qos7ecFOCl/ywvuxqwdi+fKvUH7Sj2l5P4hY2JdWeHG40ougphsVViqE8iJz4iCjuIPZ+NLxQ3M6oLTCaxCcMHsWzM4h96svEMTgopUR85oENgBEvCePvRwaG8vgp3GlfnbY9FAraj/lNQIQYV1Hq2rE9TYeKBdjR/elPovT8nItcyQXrtmPaaNORzvo3uOpo35gMAzNzlWXZ0NWs4umJin3mfyMUDjdtLxcFHQH8MI3QOfOcL7+Ok6m9gIUr698nhHzV4u/U+HsecV7UO0PwuWwIS3FKUL5FqzYK4wdrz8IW7jfybAa1buzob9lqL9ontSG/EWaDylOOwCbMEgoj5HUOYfmdMDafUeEt1M2kGzQi4LjyA7sOXwclIFEuVI0t7Sw4TWmXzfx3SJDaVbBoAaXwya8Vio2W+2x5Dly2PR7oDk5fkB3HPyuShjDshBFIKSJ56vC64cNek7a2n1HxP1Py8s15FXZpWt6/SEs21YGZ7iNFF4pn5P4/NsTAPSNKgrF1cOMQ6Ld9DxQnyaqQtuasWmaZj4LGADA8ePHkZ6ejsrKSrRv376pm9Nq8fv9WL58OS677DK4XK7YH2CanGSMWTQDprkg/7BkZ3jilgavy3WsFpz0frS+iqcvm+I5q8sYj5i/GqUV3jr1t5BF97iwtXBsxL/lNsnGUMHwHNPr0rEkiU0LRvl8ibZXHWtaxJnJtdOY3bPRgU7t2hgMOVKlo4UqtdGs/eq9RmsXyU/L3gh1wWl2r1ZjTf0DwODNkT0u9F59ni/1+mb3LrefFpXqOBCyYp7Zdcz6m+Zb1zQn7htYjXs2OuBJSRHjCiDu8TC7L6v+p+vaAMyZPEBcx+z8Zs8EAGD9eiA7G+jZU4wZzUn5XgGINtDfHeFFPHnjaa7Q52S5fI/LjppAyPCdumhDSbgosO7xmpXfz/QeqF30HBLqv+VwQDL46HucNrNkqfIMjwub7rsIy5cvR+F/XKjw6a8PzE7H0aoadExLMUi4q0aRGRSWSu1L97hMQwkJ8hbROdV7UpGNK0D/HlDl8OX5TOcjL5bZuTM8LvgCwYj7UtUjl20rgzMsAU/fP7QJpd+LA5lpKQ3+295Ua8dEbAMOHWRaLc05LI3RaQlCG3UN70l0/lGOjVX4Yay+ijeEqbGxanc0NbpY+TrRUIUE6N+jeneOCGFUc8/Mrkv9SmprlHxPbQISUzSkRTMVTJXzIijvBYgMv8lI1ReGVAiVwq7S3E4RNgcgIk8iWlinCnmA5NBVOXyS2upx2VFW4cX0xVsiPm9VaoCk06t8AYOgBb0XLb8jmlBJtFBaOaxQDX+jBaBchLtjWorhurIXzyxfDIBp+J4MFXtVw/fUEFGre6TQNLW/5NBXGfImWAmA0GcytRo88uYjWPPYX2vfPP98oGdPALVzmtou36vch3I4oSyHr/YRyeUDuiGhhmouXFNbZNfrD+H+JTsxr3h3xD1QuJvTYRMGAykMUrSeDRA5XxVePXeLvsepjyq8fjgddhEW6AsEce7cD/TrB0Li3CSysqus1sgCaosYU3FmM2RFQ4pSsDqW7tvtrFX+Uw0hJUpQSNrT74aaS0pjQwWoz85Ohw26uuAEk9w0AIYwyuyMVNEPcq4d5fR1aZ+KrYVjxfdoddjIskEvnGz1e3Sqrc3Y0GJaLc114dmUnGpfcMnAKi8hFnWZf7FyoRrqs0B0w0d+P1ERACvUBSeJiagiEqranFUOlpzrZLbYVo2qRRtKUF5VI5LyzT4L1Par26mLRBytqjEYxIs2lIgFjqywZoV8H1ZGEL0+e8lOjAznl7WRFlPqwpe8rmaqfYnMC9noocUyYCwTsLnkmKhTRPdL/a9eS86P21o4Fm6nAxVeP3yBkKWxI2NmaKjzJ1rumBnRNizkxTQtTtVctQUr9opwQTPDmAz7C37QCQBE4WDdw6ChtMILl92G/lnpBuNcHnO5lpVq+FptyMi5Wb5AUBgVqvG/cM1+pJeV4O8v3IXxO9dg0IMzgO+/j3iOSM2R2i6LX1j1IdUke2rKEGGojerdWRwry+TvKqs0nGNaXm5EvlG1PxQxn5ZRzaugJgRWiiYNwFNThghZ91SXw2CkLNtWZjA6qJ/cTjs06DWjvP4QvJIoRarLYSqyIrdQv4YNe+aMF0qIrrCCX+37ct9/ITx2gG7I6BsQDmGwyV42Fav4M7o3mlOyNPsnMy/GsF6ZAHRxDwrfXLvvSESIqScsAU/KkoANB+bnY+5kPf+SjG5fIGgw9un6E8LPzJzJA6KKSZ1qazM2tJhWS30Xnq2RU+0LLhnU1esmezniNUrq4+FTxRbMrvfapi8Nf8pY7bSr76siAGT4xKqTpCJ7SmQxEbkYspqwb6baFu+cVj0B+g66noSv1kkyE/CQFw6qOIKckJ8Mw3paXq4I86mo1neYp47sZVj4yQtfuQ3lVT7DWKhzKpp3CIAweqJ5+2jM+melG9QazfKpzMfGuGKU2ySXOaBcEdnQkPuIQrPqWvNO3VygherEQVnCCwYYFTUBCJU7Qs0N+2Tmxdj6ZQUAo0If5eL4QxoOlZ80qDvS/dBzoHr7VIEIdd7IBqusTqfO7YJju7H05btw1ncl+DatA+76SSHQtm3EWJGBVuH1o2NaithUUMfLaozNapDJRp8s/kPtJ2lxYsKgLAzN6YDCd3Zi4tPrIupF+UMaDlfqdaHkDY9qf9BQAJiKKpN3k/qJnmkyojzhftNzsLoajJRhvTKF6qJsbHn9QSzaUCKUENPcToNsP1Hh9YvxJ89daUW1EJLYM2c8MtPcpkYW2Z9mdlbPzDZYsGIvyqt82FFaaSh1QJsQtV752nDACq8fg4tWIsNjlGqg70Qbap836juaV/SnnPsqC9LIRh4Q6Z2vb03DlgYbWkyrpSWEpak0tMfpVDE+m4PnTl5omC1GGrKNVouf59cdMPxp5o2ghbxaO0ieO7IIAKAbPlQniXJeYiH/OBdNGmDwpKj5BbJhQQVNyYBVxQiiXU/2BEzLy4XH5TB4tKL1H4WdyYsIeo1ClsyUIlV1QTmUUTVMZIOHCprSou7ac3tELGZktUFqAyW568bPnojry/emegvl+1W/K+TvU/JcHK2qMVVrVM9Bc2lU786iFpPcBgpzM6vDRX2gepRJ6TAjnPeSyNxTx5n6a0dppfCOENQ3a/cdEQY3GXjRQk6njuwFQBdYoHbL9Z8ARNSok5+DaN4+K+OZ5gP1M3lIFm0oAUIhYO5c3Pb4dKT7qrA56yxMuukJtB9zkUGxko6XDaTtpZWG/jXz7tH3An1nUIifXMSWcokAXWCBDGpCfiYnDsrCsF6Zok7U9rARoUIlMeYV7zaEBqa5nSic2B8elx3V/pC4jtn37rBemdhaOBab7v+R+Dzdv/y80DirUufynCfjg8aAxsEKGyD63MrwiFZUmeTtvf6QeBZpI0RWIMzwuCIKPusbBrpwhsMGg/JhaljVUS2irtZ3q/T6DX2pfnfKHnwinkLgrQk2tBimGdHQHqeWaHzWhcY2bMwwy2Mwy51piLG2Mqhp8Ud/mu3E006+6tGQ5w6FNNHurbr4iNbXVrk1tMNMAgHyjzoZFos2lGDV7sMIasCq3YeFx8MXCGHBir3CoLC6vpqfk5mWYurRsuo/dcxot1iWf1cV5ShPRO7HaXm1Mu5y6JscDtczsw0cNl15DNC9kGQ00eJFrv0kL9JpLKrDRU1p8afeW7RcI9mwtHpm9IWxnudydnakPHrBcL0Y7tJtte2UazGZeQSdDpvI8yGj+uzsdNN2kPFcV9SFs4boHkkabzXsz8ybTFx7bg/x96V3jBRhWLRxID9n0cIo6fpmnj8aR7mftxaORWaaGxVePx56exu2nfcjYPZs2DUN/zjnMlw35RGcO+JsQ0io1UYEeYZIObK8ygePyy7yoChcVTbAqNCu1x+KKJ5sA0R4mmxQbzxQLnmZyw2KedkZtd4uhw2YO3kAJg6qLYBc7Q8Jo4YMP/18ugGybFtZRAiymsdGnv6M1Mg6bfSdMTSnQ4RQxNeVureINkUqvH6DbPys/H6iD1VjmwQyqFhzoqQ4I+tb0eaV3G75OSGpepfdhhSnXXhMzza0TRP9Q+GsQK2Xiq5FOYGygR3LW3WqbPgSbGgxTDOitX4BNaWRQzR22KS8+IqW+1OXsY6VT2V1PEGLv2htiPc9ujeqszJjXB/TXUwi2jiYGX7yAm7hmv2GAqQk9exVDAqra6jjoHrpYtX7UhcRdB15p17tJzOhB7NwQ/LO2cKv7SrTd/ApBO35dQfEPQIw5GRQaNeo3p2R5nZiTL9u8LjspqFG8r3R/VuJcEQbRzpXZpobGvTcNbM+kxfSqngCLVxl0lKcIs+Hdr4pFMpszsh9LO+0E/F894zp181SkEM2+Gm8aWzkos5qKB15jWO1wWphavYZeV7LBc7Lq3yGz5ZX1aDv7PdQXuWDDUCNzYFtoTT4HE7Mv/JuzJ/4a/icLqzafdjgkZLDawFgz5xLcWB+Pvp211XVAuFCu15/SBgwsrS37OWWvU9kwPbMbANAN5xl4Qy6V7nOW2lFtRB2mDt5AOSAvfyBWcKzSoYLGQlefwhVvgBmL9lpOJ/NpnvIq3wB4TFX89hozNqEDUcaT5oTI+avNjWGQhqEt4g8yxTuR4WAydCRiy2T8WWV0xWrFhfdrwz1Az3n1G65xh7CIap6EeaQMJSpxAigy8er4iH3hw0u2uBKD5+vMuxRXrhmf4S3yswLdqps+BJcR4thmhG0KG9tqAtoQv4hS+Z9m/Uj7Z4nw4hNRrvjGWur61B/Uv0ktV/V/pYXf3dKa9G6zDerNsnnooV5hdeP6Yu3GEKxzMaBzkkLHnWMhuZ0wOFKL4bmdMDQnA4o3l6G/IG6rLGeXO5AdXgn3OoaZshtJtnoaHOUFhFr9x3BiPmr0TEtBYcr9eRw8gRY9YkMtU+VHVdr/mwuOYapI08HjuzA1JG9sGDVFwBq5f9HzF8twqoAiPkAADWBWonoLMmYlMdObh+F8JnNJxX5PLH6On9glhgvWaCEoAWZDbXKbNH6KdoYmmH13SO/ByBCGMDq/GbtkT05gL5wnjqyF3BkB8b+cS2OeYMGr6bcHnVO0blJFl1ut9zXGw+UC0NCXWyLRX8oiFS3CzWBEN7+6W/w4ciJGDNlLBBuJxlMtNCn9lV4/cKbVDA8R4iE+EOaQXJcDukcMX+1mL/UBz0z22BHaSVSXQ5My6ut6bSrrBJL7xiJYb0ysXDNfqGgKZPhceJEdcAwb2h+kvG+dt8RVIY/t6usUnh3zPKc6KVASBNy8lTziTZKBvfIAPB9+E/j3KHxkKG6VC67Df6QXouKnr+Qpm+GVPkCQo6evICAbpCRB9GGSEVBAHDaretwqdC4HCo/KZ5PVZJeln+Xkb131MeB8EEUekkfofbSxsaCFXsNOV0bD5SL72qg9a5pEoE9WgzDNDjxhmI1JMncRWuodqu72FbXUfOpzMQU5Nfp37SAMBPDUJEXj2Ztiqb2Ji+WZY9GrGuR+h4Ag8du7b4jYpeUwmI2lxzDqN6dkZ3hwZh+XcXuqnztjQfK45IFV/vMKtmfjgFg8Gy4nY6oktvRqPIFMK94N8qragxKdhTCSd7Ha8/tERFWRqIZgL7QkedD/sCssJSzHUNzOmDhmv2muVjyGFCNIboPs91oebxUz6MZshKdGeTRmTAoS9yb7IFV89LMBBmiUVevLWHm6SSBBPU8AEQoHVFWqXtRyGtl9WwCMISDAubhnHKe3NzJteGiA7N176bdBti0EO76eBFeeX022oRzdb6tDuHlJ3+GguE5wrNEyJL75M0KasD9S3Zi+uItIueHvKRmfha6D9p0ACBy+DLTUlAwPEcIYAQ1YOLT64SQCi3eZQ9PmtuFoKaH/PWd/R4WrNhryD2i0DwyAEhuPZoPiOYZPdeUh0R8+sV3AICP/vuN2EixCoPL8LjQPlXv+8KJ/Q3v2aBfh3JKAd0IIrVOqklF+X6ygSYjG9CyMeZy2CJCECn8tTLs1S+t8BqMrPIqn8h3U6HnqmB4juhjKmPhdupS8HK/aoBBDAbQN0nkjYNY+VfNIY+6sWBDi2GYBsdqMdZSQyUbqt2qYWV1HTWfykxMwUziXA5Di4W6AJTbpIoBqBQMz8FEKTQo2j2a3ScdY7XoVA2zzSXHTHNFouVB0eLCLFzQzLiSwyRJVYzyG2aM6yN2pwvf2RkzpFNuX20oVjBCmn3RhhKM/eNayzEqGJ4jRDPSPS7DfHhqyhBkZXjg9YdE7g7VApMXjtQHpKpHOSPRjKi6zn+zxZXZwswsZFGdN2bziPKWJj69zjCuqpFGx208UB5XbTF5DsniHWr+oqxMKT9jFIa1ueRYRJ+qn6VwUFkW3WpRKud0Lb1jJPY/ko9szYfn33wIv/70HxhRsh3Tvt8dMeZqTaiA5AEKKN6g4u1lwlg+s0s7AEBWRqowEKhf6D5Ikc4XCEYI1eyUrru9tNIQKkehbDbo907fMxp0g6PC6xe5iHJenQ0Q3zUa9OdANgpcdj3nb2B2Orqle4QXrbTCC68/CI/LITYSRChyICTEUcjbOKp3Z2EMuuw2EcZLIXXyNdM9LgzrlSk2iQCI70L9e8Mh5nbRpAEGsQyX3SZy42ScdpvwyvmDGo5W1WDu5AFQowspzI88aITq9aR+8bgchg012tSiMELKNzs7bMgPDNfiCmrAvOLdAGDY4Ir3u8Es3zWZ5UOaE2xoMQzTZDRkrLaZ4luySHa75cWu7BlJ9DpWHjA6P3m0SAwjGhQC0jOzTYT6nJxobcWwXpnolq4balbqhYS8GJ6+eIvILaGiprKUOZ2DFgh9Z78njARScKN/q+pbQK0HpWNaimVRVzPjiu6DxAcAffFCO7uyARqrGC2dv1u6nuBvt0UWGgb0NpdVeqOOkywlrc5zeXHtsEHUAjMzamRVPdmzZ/YMmYk/RHvG6BgqQCsbUOp8WLShRIRXyVh5guQ+o7AoWSXPTFVRrntm1VZ5rOQ5JOfXqZ4OuV/oGctIdYn6Qqq31MzQP1pVYwglVL2qVu1ctKEEV93+F/ztL3fg4v99Bp8rBQ/9eCb+lH52xJjTc5EdNpgmDMoS88ipxLDJGyVkoB2urEbRpAGiX2QjFIDwhJBni4xc2YYbKBX+ltGgt3XjgfIItb2hOR0ickLnTB5gEH8Y1buzwYArnNgf+x/Jx+ffnhBlCORxqwkEsfFAOXrNLIZXkj/XRWV0o7HS6zcU6VWNUWo3QcYXeetIbOKpKUOQ5naKnNL7l+zExgPlIszXYdPbu2fOpRFeJPma5HWm8dGNLeO4kYEqf0bGH9JQNGkAZuX3NWyokZEm95GG2pzRo1U1ol/IAAaMXrFY5SQA6821aBspLRXO0WKYRqChcpEYayjnhf5e13yoxkDOFUlzOy1zSmJhlS9D599q15DXx6iEZgUtRneVVWL/I/mG9+KJu6eEabqv2Utqcz7MPqvmnQH6jzrdE32W/qTzef0h4dmiPCugVh2LdrCpT2SBBUq2N/MYqm2k+ymr8EKDvhCTF+B0PTmHhww/Nd+G/su9txiAvggyyxGalpeL59d+AeB7ALonhvKdKBRP9sCREAjdDyXuUy4NtW9aXi4mPr0O20srI3JD5HsfXLTS8hmi58Usl0hGzv0yC+syy4Gi8KpRvTsb8pbkZ9NsjCgfrH9WOo5W1Yj8GAqvow0MOW9Mvheaa/LzR9eQ+5XuJ1p41LXn9sDy5TuwbubFcLlqDQo5F7C8qgZefxDzivdE5GFR2+V2qYIqcjv/+/QLeOWNx5Dmr8ZX7Tvj9itnYXvXHyADkSGIT00ZYhrKKX9nUs4chUku2lCCFKeeC0n91i5VF0KQNzIqvH6DqiXdx4IVe8XzkuFx4mhVjfCCLFixV3iT3E49n+v+JTuhQt4h9btaHT8iIxzOtmhDiTA6vP4Q3tv5dcScMcuEcjvtIvez0usXcvnOcE5WvFAoqR5tYPycLNgR1PTvyXnFuw15UTboXsSyimpxbRL+SXM7w+HLdoN8O32mtKIaA7PTcc25PQxzDqj9rqLvTIKM3Rnj+mBe8R5Dba2hOR3CubFBeFx2ZKa5DXPVbDzMfs/U51ed48nMqW5q2KPFMI1Aa9qdaW5E2zGjBZZaE8qMeMaoocIZZOUxq1yheIgW6pXhceFkeBc0HminVA39qysaahdjZvcl553JCnBWuWJyfkU0L4fqfaFwJrpOu9TIXfVY90GhMrSLLtdCMpPIl0P25HunnBW1eKvc9pV3jQIAjP3jWtMaU/J9AxBhbpSkrp6P+pTyN0Kafj8k3W0212yINEblzYFo85U8QOQ5sfK+qfdCeXhyCGis78+npgxB/sAs7CqrxNCcDhE5ZhVeP+YV78bafUfQLrXWiJDDA8kbarXAUz26iT6j8hyt9teqZtLnzcIQzcIfDXP9j3/E3L8/hDR/NdafPhgFtz2D08eOEh6eaMjt1z3FdpHbJwt4LFixF15/UISoklGW7nGJdsjfY+p9ALohkZ3hQZrbZVh8j+rdGTWBEM7s0i6qXH9VTcDUQ6mG+tI90L2r84YEJjLChqTdZtwCsEFXC5RzwCjHikKUSUreZaZiIeEJ50hSPhoVLZahItk21Hqi1LDKsopqEV4pQ/XKqpTv9jmTB6A8HP63vbQSC1bsxbS8XMzK7ytCCsurfBEqih6Xw1DHLTMtBYD+PSEbYOS1nJaXG+EFp0gBtc6ajPrcWIXUtoaNaTa0GKYRaKm5SC0Bq1hvACJ/Qa0JZUY8Bk5DGcxynopVrpBZm+Jd5BUMDxfrrY4MybI6B4X+qYn/8SKHtAHGxXq0fqTioSSMYJUrRiEvcycPsPxxNhMXoYUShfHQznCsfqTEdaB2h3pe8R5D/SKzEESPywFvuGbQ2n1HDPdOeRC7yipjjmtZpVfsKsvG76INJWJBQ3WnyCOYEc5XkY1cuj6tD+lPCgOS74EWUHMmDzA13tWwTqv8O8pnI4+EVZ/LO+GALlMuh5DG8/0phwWaLdboPuV7pTApegbVz6h5WlbPaCxUT4xct0j9PF1j44Fy5N5bLMIuzdqAsWOBtm2BGTNw/uebsOaxH1vWw1OR8+H0hbUu1+92OqL2uTr+at+rzxLVhTMTBFFDPheu2W+okUX4g5ow7slDOX3xFsNivmB4DtxOBzTo3qLBRSuF8SwLSDhsEJL9ZLyQyaRJ/5ePJ7GZGeP6YGvhWLidDoPhQzW8KGcMADLT3NhccszUY0YbShRWmO6x3vQx+/yo3p3FuVUDbPaSnYbQQbn0BeXRqQYdoIdSjurdWdQlpHB2uT6Z+D1RcjmBWm8v3b+cOytzKm0+s6HFMI1Aa9qdaW6oP9pmifTxGLrxLJ4SMZgT2em2Oq/8ulmbEvmxmpaXi6xwzpSM1Tnq+kNI973xQDmA2h1SebFudr9W1zPb4Zdfj0fIgM5plecDwPTaag6N7MlYuGa/IVRHrickf6YmUHuMKhDQMbxbLNfSUouqkhgGLQLlRHtauJPhsGr3N2iX6hI71jPG9cGcyQNM75kWWyHJKDPbebbCzKilHfTSCi+mL94ijgOM+Rwel0OElcoGl2zQkAdFgzGENFayvOyJlY8hI1R2QJRVeDHx6XXCQ0ieAfUa5KkxE4Ch/rTymo+cv1p4CtX5SIY2GSBmnycjhBT1glq4fEJFRe1B/fsDe/di0VW/wuB5qw2eSTJ0ySiJ9Z1kZkADEP1n5iFbtEGXSpdrw6n5cSQssWr3N5hXvAdlFV4sXPMFcu8tRrf0VCG0QHOVVBWzMzwGUQfyVNFCnwRl5PA8n/TM6c/FYQDANef2MIj00EaO6pPKSq99PkQXZ6Vj7b4jwnOk5hLaUJsTRWNG3wk0Bup16Lml70rq4wxPfFk9FJ5s5lMzM8x8gaDwsMufkQU1qDYbtY08XrPy+6FnZhvcv2QnJj69zvI7nO6bVBXro/jZWrBpmhZ/oOkpyPHjx5Geno7Kykq0b9++qZvTavH7/Vi+fDkuu+wyQzx7a6C15mc11zGjvJIMj8uyNk4s4h2zaMdRLkZ2hkfs9tUHs2slOrcWffo/tDuyAyc6n42CC86Ieo66zlu6b/KkAIirDxK9P9X7kcg9qK+ruU/07xSnHV5/yLT9izaUiPwFQN/NnpXfTyymaRFRtHSX2G32uIzn6zWzWPTR3MkDxGepllaVLwBvTQ0eGxbEw9tT8U1VQLwnX4PqAVGfk1EQrd/7zn5PLAwpFNJqDtPCKdo8kPO5EG7Lgfn5hvds0EOaqL107QqvHw6bvpilkEYKZ6Q6aW6nXeT/yPl4Vm2Tc8MyPC6cqPaLPDGzRQ/lJJldgwwpmiNy3h9dV33e6fvxno0O+II2sbiXc83IGwlA3Kv6vSXPTao3dc1/1+CB9xfikydexLhf/DhivADj2Mv9rynvxfucq/cn/xuAuK7H5UBmWorI3aMwRFX1Tu17qvUWK88PgJgrO0orYbMBmqbLke9QlAzl89NzQc+0DXoo6+aSY6LelNuh4bFhQRT+x4Uqv3k9LjofzRX699nZtXmB9LrLYUPhhP4R32dqTS56VuTxM8PlMNbV8rjsBtGRiOOlXDJ9HBxCadHttIcNUr133E4Hema2MUjCy89KhnS/AAyRBERTrHWaah2SiG3AHi2mVdFQOTT14VRykSeD+o6hVe2fhrieVdgi5Tskc8fOzIOTqKeUJKdl6WlVVY/Uw+r6g0n3TTlUcshgon1t5p0k5L6P5Q1T1fHUUDCSNF677wgWbSgR9Waqw0aRWX7BwjX7DYpdXn9I9Jns9ZIXa2o4VqrL+BOsehNmjOsjvJB3XHKmeE/2oixcs1/kPjntNkOoXbTcRHnHnsKK5DGikCzyoqjhq7HGUgOEB4XqnZFXk5TtXHabCMkkgRKgNqwrM80d7tsgqmp0TwJ5AaflRS8zIO+u+wJBYWSRAiDVnaIcGyqWbKVsKIf3qvNHPVYmI9Ul+lCtEyf3v5UhIteNyzsjA499/AIee2cB2vqqEPrLXw3HknfDEy4QrJLqshvaOH3xFpGXZmXg0BjL+Vfq/coKdWP6dRVzlxbq1Rb3RqqHqYrEuDqnyJtMXiGaKxpqc4dUuXgZmm9BrdbrRKGFar0pQJd3jyZ2oUEXx9BD6hyiUDDdN+EPaoa5ufFAOcoqvKiqCRi8dE6HDYOLVuLbE8b8Ldn7mp3hwfgB3Y3tlDZKVEl4PReu1jOm534FRXH3Cq8fbqcDNWEDv9Lrxw6pHygKQT6nHHpJni0Zq9DteDyp0WiO67pEYEOLaVU0R6PmVHKRJ4PGHsP6hOSpY6sqLKnhTg1NrB8kkpw2k3ePZbio57a6Vq38cl+xuAZgmsRudX2VSq8/4sda7ns5PErN+SF5cvnaFC4kwrAk5H9T0VGr/IIFK/aivMoHQN9dJsOUFtNVvoBImKeQp2l5uSL/YUy/biJsR851kHPOSAzj2nN7iPkEwJB/s7nkGNLcTvhDmiHULprMPBkVHsXYo3ujkCxZ7MBqjlCfq/kpdH0KcaIaY7QApNwNCsmkHBjyUNG4ZnhcYiefFoMFw2uLq5oVlJVFNciolGuNUd2pwon9hQErjx3NGVmMguYYGTTy/KFyCBQGRqybeTEmDDK202quqwW3iQUr9qK69GsUzP4Zrvn0LQDAn86/FjPGTzfMd8rXoQLBNOZ07ln5/QwbD7ShQOFh8vOihjrKhqbqTZaV88yUGGXJ+OyMVJFb+cnMS7D/kfwIiXGzEN6Fa/YbQmHzB2bBoxQcBoy1o+iqstEUTbvC4zQ+C3abfg4KaZwY3tCQPT3k0ZbDFeVrfHu8WmxMLN2mqxv6g5rRsNZ0Y1v2VgHAgKx0Q0gv5TjKiNpfYaESEgIhMRj1dmsCQeHdA2rzOTUYPb1VvgA2Hig3FIJfesdIzA1/nwO6cWv2W6OGQMcrZmNFc1zXJQIbWkyrojkaNZyflRh1HUP1yz3eL2Wz68XbBnVs48kXa0iiediAWll3M3l31XCJlUMlGxtmogbzinejrEJfeNKxQKTUtNn1CfJ2aEBE8WG579XkbLrvecW7Ra4BXZu8QORNqvD6Ra2wGeP6CM+Jy2EzlcAGalUiKdwL0D1EC9fsFwYhXdvtdKBL+1Sh2CXnVG0uOWYwFtSFrszYP64V84kMFhKLIIEBVa1Rla9XNwLkekQzxvXBog1GVUY1V8dqjtA9kcgIGU5UJ6xjWopBKEH2OsuLdjKCgFqPDwmj0KI61eUQ/UQqjNFk1mkekQKfOlfNvp/lMaL5DUDMsc0lxyKEC6xqc7226UvRTlooy32nLobNfif6l+7FspfvxA9LtgNt2+LegiIsGPVTVAVthu85q+dWzWEiTxahQQ8lnb1kp7hvVYHRKl/ULGeNrksLeqOSoE309/TFW9BrZrGobeULhMJ9oSH33mKR56fOWwrjVCFjkp4DWeWSsHJU6cbEWYbXuqfrG0W0cQEAJ6r9ODtseMl4/SExl+Vr+EOaaT/JWHnPtpdWivF4fdOXpsd4/SGRc3W82i8ELqh/1Hlqt9mEAEc0RUp/SBObLQDEd9vCNfuRnZEqjosWbQDo37lUhJs2GhL1UDXHdV0icB0tplWh1mZgWg7ygqsuOU1yfksiX8pmc8bstXjyfZoaWgSpC2taVF07NFLJS84TkfN01LwCOWRIvpZcJ4eurQtF1CaGF00aUKdQRDqWrk+LWVpwyfcgi0zQfdMC1ibdG+VByDvfcq0wqs8VCFqsyFCrEul2OgwheGodMECXiZ4xzjgu1N+yQbS55Bg2lxwTC5v7l+iCEDPG/ADtoKsOelJSRLic6kUY1isTaW6noY/VPlfnhwotyrMzPMLIlAUhKL9IPjeACAlnen56zdTrhO0orcSEQbW1q+TnS64rJbdbfW1Wfl8xD9R8HbP7mVe8G15/CPOKd2PPnPGGsafzqs80PQtkbNMcoc8MzemAw5VeDM3pgGG9Mg3hlmptLuL5dQdMZfbl+Us12kzZuROvvDwDjpoaHO95Btq//y76V7ZBhjSHrM5L79M9qrXtZOh5JW8NzTFV1VN91gCIPMSB2emWc436qmNaCk4Pzwv52vJ8Jgn0ZdvKwka0Jj5LniH9c0HDeWaM6yPuMSPsvSShDnUMXHYbnI7a2lOysEVGqgu+kM3QZ/IYbS+txNzJAzCveI/hnPOKd0eIaFC7D5WftMwPjIftpZXwuOwi9M94HpvukZJepELSlNtXGZaq94c0UWRd3qCwh3Pd6BQelx1j+nXD5pJjKK/yGWoIZmd4InK2ZOSxp+dO3hAxe76j0dLXdWxoMQzTLFCNgkQTbdUv94Zqn/rjoHp65GNIPrixjDD1B2laXq5YlC5cs9/U0KLFNf3dKkyuyhcw7EzTteQEbzk0j4puqgtrK9ELamfhOzux8UC5QTSAjlOLD6ufzfC4DEZhx7QU7CqrFG2gPqH20uJSXhzLBoF8DdkYNZtrdIwvEITb6RDeLrfTHjEucr+pBqy8KKzw+vH8ugO4s49uUPTMbIND5SfFe0THtBTDONO1qnwB0W5qg9X4qoaE2rdkQKrznBL7yXMgG2XOcPJ+qsthWiTXbNEuj5Gc2ycb8ZRvRXlVZkaTXKB2cNFKw7iZFZIGEFEkNzPNHWGokGeKaklRP1D9NJWpI3thwaovxNyRIaGL/lnpSJO8JnL/LHi/FPPPPB/9M13osexNID0dBcocouclVmFn2ftA4hwksEGkKwtoeT7J8yE7wxNhGFOZAqu5tmDF3oh8KBVdGCMVhyurkeJ0GIzCXWWVWLimxvRzagis3H4z48Yf0tClvQulFbqhpQF4+sPPcd9APR8SdoeY3wAijApSxZSp9oeE0IZ8TbpnM/GKgWERDRLkiIbXH4LDpgtvyMeq7SBorm4tHIvpi7cIA5WeY/n3IaTp7asJhAwF0QE9jNbrDyE1XKDYbLNFxux3SD421oZPa4NDBxmGaRbEk9weLSTQTNQhFomEMFiFL0QLubNKDm6MnC1ahFEI2NCcDkIqXG1/NGlver8yvBOu9j/do1pgdc+c8TgwPz9i8WkW3ih7KCj8ShUbsIIWvzZAGHtLt5UJI0sNLVPbO3fyAEMbn5oyBPsfMbZbDiWjha2aj0NjTAt8OSRPhe6Z8pfk3Ks5kwcY6tYM7pEh+mVXWaUkkW70yMl9QGOv1otS20BGkZngA903hR/SPLIKLaXj5ZyMtBQnsjM8mJXf13BNGlPyElT5AiIcUh4jdSEvF0CdM3mAqLVG5yqt8GJe8W6MmL/aUEhWrfdDuW0ADOFwMlTonAwzCgWViSek6dpzexjqwsmQh3ZXWaVow6INJfjnu5swpuhdvX+qA/j1pb/GlEt/B6SnG8aP5hD197KwuIMazkX9Pqp354jaTVsLxwoZddVLoYpq0HwAjKGu5VU+g2iKGfKGjhm6iIcdGoAqXxD7H8nHmH5dDcekOB1ivqp4/SHdA6yIIdEYUbibnD8lFw+WQwyfX3dAzCc5rI/mlN0WaXgBECGFE6Q8RRm30yHqC1I+I4UlktR/LKjemIpV6pkvEDQYWXQszW25QLzb6RDGmfycUp+O6ddNnCORlAiz3NNTKZ2CDS2GYUxpbKUfOSk+3hweM2IZZHU91urHQc0VivYDksj16oO6kKfFZVllZMhQwfAcy4UgvQ9AyIer3iS5ZpSZwp+KOo7yYn5iWBGO8pbUhVu0/kv3uBCQFkXbw3V7AESIZNB9xdPe6Yu3oKzCKxLjO6alRIgImBHN8JcXrOSNkj2hWwvHYs+c8fq4fFkBwGjsAAjLnuuJ75R3Qd4I2i2WE+NVqC9lQ082umRvU9EkPQGejEu57+SFLY0ttVPNAaHF6+wlRgPaH9JEf5qNA50XMBZANRu3an9IN/LczohCq+r5ZC8XqRkC+oJfLnRevL3MIF5Ai3jKWyNxE7kdr4Vzal5TcmvkNss1v6hvVv31LYy+bjzu+vsjgKbB47LD50zBUa/fdA7J8yLVRBxCHWtq+4IVe8X55M0HMhCyMzzYM+dSwyZRuWQMbC45JoxPWf3OTOmS5hLV1DPzPs2ZXCtaUhm+VzL4HTYqjRDE2n1H8MnMi00LGsv3Qu0mpb/yKt3rqntuHAbFSZLUv+OSMwHoYboUSkjPvcdlFx59qzyvo1U1+GTmxRjWKxN2W6TpQxEONIflYtK00ZgodpveP1lS3pSM2+kwGFmArj5J15YFNkgdFKj1WE9fvAX3L9G/n97b+XWj5hy3FtjQYhjGlMYyCmSiGSrx7oIlkjirShY3BPLCKp62JUMSV16EGRbNqdZ1RuIxrNM9LsPCa3b4B5i8CNMXb8HgopXiddlrRSIPAAwGCC3uaYedFirtUl0RCzez8ZIX+hOkxZe8c23l1ZH7y2quF28vM8hIkwQ5oKupme38yl4sOSRWVkykRRV5owDzeUgKkfdd1g9PTRki5g7tQFPeRZrbGeFVzExzCxEOFTNxAzLKC4bnGBaEBcNzLMUezDYaaBzX7jtiujDTwv1C7SWpdZL5Vj2ZZl5TuW/vX7ITx6v1hfTZ4XON6t3ZYLCqoZtqcXLZSzCmXzfD3JTDSB02CO8bPQOqcMaiDSWmpRTkNs9eshNr9x0R8x6ahuu3LMdzL92DTieO4qzKMswa3kWSuA8Z5qds1JKxTOp98vwzy19U20vfNa9v+jLCYyWLZ8ghanLoLY2pLxAS3rXZS3YK45M8l26nPVwjzGhRkMFDhrkGGMQ4ZOXIKl8AvWYWY9Xub4RAisthiyimTN85pPRHbScPKylOkidr0YYSg0gQ2VKUt0TX1/Ok7AajSC60TGMse8Js0DeRyDCX1Ss9LrsQDSqaNCBhY8vttKNdqsvgnZOh0EfjZxxi/vgCQUNxYl2UJCg2aOTnXVVFjIfG3rBtjnCOFsMwpjSHOOpYeVlWx1kdqx6nhko1BGoeRyxDkY6Xc2ISDbFQc4ioYGnXNP0r/7VNX2Lh2oMRwglWCcpmuWZy7gN5EWQhCNn7ZZYHRtcDag0v+dwkyiDv+gIwDQWUQ1IA3Riw220IhRtDIXXTF28RO7i0GNXPK5ZVGFy0UpFqtiGkaaIgqZpLIRsSch+NmL8a0/L0GkOlFV4hBS63l7xIy8KLQarjJY/dtef2wPLlO8QikPqGFoiU9yELUyxYsRcbD5RH5D+phZkLhucIjx3J0xN6nt0elFV4MX3xFoPYgyoAQ/ehimWQqIQvEBJ9LguByP1AXjOzXDPA/LtgWl6uyKsKabq63dGqmoSeadnQpLkihxbKc5OMTfo7yanL0FwdlpMB4HsR+ilfj/LwyNgpGNwVb25+AT9Y+ToAoOSiy3DG0tdwRtu28GWUGPqMoHlEAh+F7+xE0aQBls+SnL8oL77l51bOh1q774i4X1XgxRZuO+X02G16YVxZpIHub+Ga/WL86U+3U/dOUS4TKfPJ7ZJVGhes2ItRvTvrXvmwIIPXH0SGx2UojkxjroYjEz0z22DpHSMNr1Eh68J3dmLzge+Q18b4GSpqXF7lE/lXc6Ti4oC+WSIXzZbnJfXFezu+xulhzxIVLi/eXiY2cJZuK8Oq3d+Y5s1FwxvOC5Oh8yPct/K/Ad0glfMO1dpixHs7vzb0IeWT0eZXtN9lOXdXDt09FWGPFsMwpjSHOOp4vWqJHkc75vF6v+qzK5foNeRd9GhFZ9U2WYXxmfH8ugMR/RWtnWZhdkNzOojY/rOz00UIGyF7v8wKqUa7nlXeG/09Wp9QWJ8/qImQHwqpI7li+uGn+UC7waUV1SIUiv7zhzRkZXiw9I6R+GTmxUKMAoAhVFGeg/Lf5QW/bMARw3plGiSYo81l2TsB6AvZzDQ3thaOxcYD5bhf8q7QvZ6o9mPjgXKMmL9ayIwv3VYm+o48drTYovHdeKAc3vDCedm2MkPumvwcmdXKofdrd8A1MY/UMFXVwLcKH5bztOR5TkVUXQ5bzDliJp9Pc5vqf00YlBVxDjJQg1LYWf5A/Tia8VRriNpOIZ8rdn1teEYXrtlvCPHrWvktvjtnOH7w7usI2ux4JO8mXDfmbqBtW8s+k6E2mNWEo/flcLDNJcfE+ai99F0zMPwcU2ifHJoo47TbhJT6/kfyMf7s7kKkgUIDKUxwaE4HVIe9Se5wnSq6Lsmv03GVJsaFXArhk5kX4+zweJPnZ1persh7ohBhyttU2RGu+yTX1pNzQ1fs+tpwfHZGqtg8II8WeWPJMyX3Pc0Vs3GQPVxksAU1o2gGhUamuZ2G4sDxOLkoRHauFIJJjOnXTXgNB2anGzavqO/MapLJHqyD8/PFdyB9XvU8y79BsiHakqXZkwF7tBiGabbE61VL5Dh5xzyWIZmMXbloHjb5OvIOrLwrbSZ/DUQuUOPySI06HTiyA1NH9hIeLbmddF753yryD6geBqSrUtHOdIbHJWTGCbNCqtH6RX1PPU5WKJTbJeeQ0C6urBzXMS0FO0orkSp5b+R+d4WLdsmLItkjtGhDiVgM2qAvymnXnTwFVb6ACGGiz5EHQ14AyeM1qndnFG8vw6jenQ3Kios2lOD5tV/gzj61nyFPH+1G0+JSzhfL8LjQM7ONyFMjj5nH5RAhVDRP8gdmiV3sBSv2ih3+w1I+n1OKZ9JzdfQizUFN91KQUULKd2v3HTFcKxpyfhjtkqteGdXAJIOLFrSyBDmACE8PvWbmWZXVH7ulezCsV2aEt4jmu8Omy8yr85E+b/C4hYLAkR2GPEOaa5Q7l+q0YfFbjyDz8904ltoOM678Hdb0HIz80zMBGFUJSTQhnu8fMw//og0lmFe8B6UVXvSd/b7hPmSP5JxwX8rez2G9Mg2eDn9Igy8QFPdFkQFHq2pErbHsDA8+mXkxRsxfLepp9cxsg9x7i9E/SzcihvXKFKIzdBzhstvgC4Tgsuvesm9PVIvQY0Cfe1Tvq2jSAKS5nQYlTEAPH+6e7sG3x6vhD+nql/IcsEF/Vkb17qw/x6EAgKAwbA5XVkfIpPsCQXF+UvMr3l4mQvBU6Xy7zTynyywIz+WwCcNSPg9txPgCIctnqtofwph+3QziMADEdwsZzad3SsOh8pMGsRfyFqreeup72egjDziNgVrWQ/bw0+bDqerJItijxTBMsyVer1o04QH1uGiCGyqNtSsn51SpO/FWnh/19Xg8UjJm/RqPZ9DsOhQSJB8jn9vsM2beBRkrLyL1FVArlkHtpp1z2m2na5JK4Offfi8MHrpHmg8ZHhf8QU0YWQ6bvoAnTwIZw7RonBNWK5SL2NLf5QTzguE5mBNWdZML5sr5ZnIIK+VxLFyzHwtW7DUImMj9uPFAucE7R14Sj8uBrYVjDSpmqS67yE0hhTkai6emDBGv+QIhoV6YPzBLLDjTUmr3ZBeuqa2RBuheCjkvi2qB1UjeO7PaQnL/TMvLNXjEVOR8MfKGADDcvwrlwcmGDnkh5Nw/8siRYt+84j1iXtIYEVQmwGxuUj4aXYtCPbPSa/Pg6Bmn3DpvQMMvR0zFwdwBuP62P2F1j8GGsEdaIG8vrYzIeZQ9BzQnqQC0LK4i9zONiddfayTRs6P2vzwnzTw0FC5MRpreT1pEGCrN2aJJA0Q+It2PLIpC55gY9nL5Qxq8/qB4Hv1BzVB8nCBDqGNainie6DNk4Iw/uzuyMzzITHOhVBK20QBRZDvN7YQ3UBtCZwOQ4qz17JFMemaa2zDn1u47Ev4+spnmV1kJZ6gMzE5HyOLg2nzDSw25p0Ctt0uDPl9oTswY10cIusjfl0u31RYhVtUqd5RWiv4n8Q9SRlQ94DYgQjhDFa2hel1mnEq5W2xoMQzTaqBFUzRVpFjGm5l4xYxxfRo0jJIWGZTYTj9c0XLU5AV5POGCQG1i/sPLd5v+wFGIX3mVL6qxql6HQoIod0NdEAK1ht30xVuQe28x5hXvMSyU1R9eK6OPxoQUCilcjKShgdoQPeofCpmr9gcjFgey0IKMnHNB7aGFsvwejV3HtBThUaMdadk7OC0vF0vFYn63WAAVby8zLBLle/cFQmLxNjJsFNBckJPUZSEEklKXjQqSZd54oNx0PlEf0DgCureBDES5b+i8LrsNNkQKEJDnSZaNNpO4lz9Dnh6r4sOygSmPl1VZAnpu+melR4inpLmdYpdf7+MgHDaAol69/qAhXE0WKCjeXiaEIdQwSaB2M2bRhhJRSmHlXaMMIgid7UHcqJWK9qzv2gfXT30Cld1OEwYT3Q+pEpqJLZC3jkJ424WFbqJt2pDxbBbCK8v3y17L8iqfeJ4oNC3D44IzPP7yRkFpRbUhDFVFNt6BWtELUhiMllvnUqwYfaGvK+0FNT0skAwiOQxOFnmhEOGQpnuj5e+6aXm5yErXvxuy0j1I97gM9+ELBEW/0H1PX7xFGC3V/qCY8y7VGgpj8TIAoyiODRBhnIBuHE18ep1ou0y6FPaX4rRLZQ72IPfeYvHdovYd9ZvDpoeCAhDCOVsLx4p6X/SdRd9lNCcnDMoyLeshq1fGkvtvbLGtpoINLYZpJZxKO0Sx8AWCUb0l0VBD8BKtzVUX5EWG7OmQ22I2von+WJGCndUP4Np9R8RCyWz33Orvcs6F2YJQvhbt0leHk9lpoawayaoXTDbapuXlRhQ0rpG8atR+uj4tJM7O/n/2zj0+iur8/5/NZpMsKSSAIIRiiCjKRYQiFAURrUKFr4q1FVG0rdgqtlq1VlG0iIBaf1QtVrGtWNtSLbYqYkGBqhRFEUUuCnhDBEpAQUjAXDfZ/f0xeWbPnJ3Znd3sZneTz/v14hWy2Zl5zmVmznOeW5Ft9jrAUDYkTkcyhKnIQlkWtCKP7GhvKa+0uPXIGKrxIKp8VXUNZpyGXu9L2p6fm2MuvipqrdYbWfCIrHYKsFiA1DTl0eaLLJAkDkWd/2rWyI0zxqBrhwJLRkNRmMTyJDWanGKLBFUxGD+wxJzrKnZtmzzcSC2vFtGWMZG5pPerar1SrUtSsFWQOCVxERNlSxRjNTOfKPmVNQEMKe1ouiiKJXLRO7vNedu7+gAeX3ATpt4zFefDsHr6cjwY0quTJZW+tFPi4iQ2Bghn6lTlEbc1UcSL/T7k5eaYlgoZ73mTBmPHfeMtadv1TJEiv1rwOT/Xa1G4j9QGEAiGzOQJeytrLIqPjKv8FKVwWFknlGg1sBpDRqHoLw/XmgqMnWLetX2BJS18gS8HojIYGSuNvxlKoVUbOdhkkRH5JPZKfdZNHl6KFTeOMo8Z1aeL5Xr5uV4zcYTMe9VdNwQjeURFTcC0qInlTLAzWIn7YrciQ7aBPYqwoykeSo3dFJc+cePL8YTdHjsV5qFYUQx7FPtRG2g0ny1itReFTAp9i6VR7iEPwkq+6qWgfq7GakbbCJSssU5eIC0RH50pUNEipJWQLTtEsVzGmoO8PGQ3LlZabzvsXgCp6FuntO9ulK5oskZDd2fS5VDRrSuq4qL+X2Jg9MWanXwL1+5EXq7XjG+KVb/Lrmitfm11t16QhYEsOiVphbjAqDE1ktpaMhK2L/BhWFknW3nENVCVQXa0+5cUhdNN53jQvsBnZg+rqAmgsiZgWoH8vhxU1ASadqNzzLgd6Sd1Z1h22dV2AfaFle2C0dUiv2Lh6VyY57h4aV/gM5UM1bqo30/62EazpKiIRVOKE6uuZXqGSbtjy6YtRd87X7a0UV/UA4hIKCOZN4GwK+XMCwZYakfJonfWhAEWFzHV5Vi1yqzc+gXmr9qO2qbFt7huqaUUJPHMO48/g788+jMM+GI7Av52CFQYC+euHQpMd0txtYrmNisWGlX5qw2Es/pJKnVRCOyshNES6ciYFPt9phWpqr7BVDplnHUFIgSj0LDumqq7cMq59VpaorjZWbRkwX581/bmZzWBIA5W1ZnKqbgKy99UagKNTRsdhtT7KmstyXxkfoxsUojLK40+VjdvRvXpYknWMaS0o6ncmW3QMnBIv0TjvJNLMKpPF9PatnlPJcqmGfeHai0WBevioT3Ro9iPu5vmrmyeALB4X0jRZHF3NRJ6GElK6hqkP0KW0gizJhiZP0fc9yoaGsNtVxMbCWp9LX1TTuaglIaww21YQLasa6KRdYrWo48+irKyMhQUFGDIkCF4/fXXo36/rq4O06dPR2lpKfLz89G7d2888cQTLSQtIS1HvIvudGG3aEsWbtyK3J5DXgCqO5QeY9Sceld2ljN5IdopXXbZ1OxkdZJFdWeyk2PGCx9gVJ8u5qJTt66I4qL+P5Z7iJ2yVBNoREmxkXQgVg0qlVjXVmONzju5xJIsQV1w6jEp4hqjZyS060t1DMS1SvjkyyNmjFhDMGQu6iUzWQjGoloKs8putCwK6xuCURcdJUV+M1GBE+qc0uMl1NTnW8rtY35kgVTfEIxQqvTix/rYOilMej+q9bj0HXF1Y8FOGVBrIqltlPtSjh/Vp4tZA0hc22Q8jIQW/Uwr6tzlH5kK2SwlJk8/t2r5EUtDTaAReypqUNBUV6l/SZFp1TtSZ1xvyohe+NXmJXjwiWn4xtcV2NTteFwx9VGM+NEE8/zSp5JcQHVNtNuQkU0CkVssyfm5OZYYJg/Cbq52Srid1en8h98wnwVd2xtWFomPUl0VC3w5ES5ykiBDtXDocbGSRVHqg8nGg/yT8gSC3+c105G/ryRqMPo/aMoPoMn91T4eUCyOYkWWmKuNM8aEN0SaFF3ZiGpfYFh6iv25Ean81+88ZLrkxsID58yBumUMgJnpU57BxX6fuUkkCU3uWPwB7lgcTuQjxbelePawsk7mvShjbijgjagJBJvcm8OulKIUyVxQEwLZPZN112UgNTHN2bKuiYYnFAq5DNVLP4sWLcLll1+ORx99FCNGjMAf/vAHPP7449i6dSuOOeYY22MuuOACfPHFF5g9ezaOO+44fPnll2hoaMBpp53m6pqHDx9GUVERKisr0aFDh2Q2hygEAgEsW7YM48aNg8/nXFSVZA6Jjpmk3wWQFRmJJPOYZNECIuNKGkOw/N0N0dwuon3HSZ75q8LZEe1kGXHfqzhwpBr3D2vELeu8OKp9O6yZdpalLWoBW0m4oGYe08fNTRvs2iOL4Gj9Fuvc0f4ufQQgIguimo1LzaRmWKNCyM/1mlka91TUWI6X6/S98yXHOBTjXDlmtkO9n+S8Xo9hPZKF8fknl1isU9IOGbNV1d/EkLKjovaJmqVO0tBLRjF1MaTWvFKz60ldJLssd3bzzgm79ko/qpkfAWOxLHFckp1R5FDnhzqmPq8H5w7oblp9pS1yrR7FfrP2kwfGjnxVXQMagiGc19TP6vmitclunun3v8RWyv0HAPneEH47sArj/vUv5PzrXwCAZ046GzPGXovpF33LMn4iizonJBbQbh6q7VTlXrh2p9mHHsCimMs1JHOj4WLnQX5ujiUznSDXn7v8I9Q1BM0aWWqMI5quU+DzmvF9Ts+fWP2q9qm0Ve1PuVZI+en35aAhGEKgMQS/z4tts77bpIxsNe9PNeuf1wOz5pcvx4OuHQowdXRv8/v53hDuH9ZovtN6TVtqXnt2U+2szoV52FJeGVe9q/ObCqmrzxu766v4fV5MH9834rkudcR0vB4jRkt1HwRgzpOpo8MZd2XMVFdnqcenzwUPgB33jY+4nl6TD4CpCNYGGs37LNWka+0Yj26QVRatBx54AFOmTMFVV12Fvn374qGHHkLPnj0xf/582++//PLL+O9//4tly5bh7LPPRq9evTBs2DDXShYhJPnIjmas2I1k4BRTFA/i6qK7UqmLLLuMerGuFc0aZZdEQpXHybURcN5JVIO9iwus7VH96VW5lih1l+wskW7dP/Q2i6UumluTxNO4sZY5uT7JAl4WfXc21ZkCDAuYWYMpx4OaQKNZk0q1aACIkKNWWxTJrrz8/5x+3cyded3yqFrjKpsKyc5uymBo1w7hpQ/2mpYOtWaP+n3p1/f3VEbUH1LHaFhZJ1trlMQrfVVVbzvviv0+HKyqs3X7VS286gJa78f391SasTHq4nL+KmsBbH1+SL8BRryOXdyZahGTGLaCJjdN3TUt7MLmtdwLalvsrD8y98RKM/OCAWbGwbqGRjNRS0mRH72WL0fOv/6F+pxc3DHmWtxy7i+AgnAck9q3qiujuJPOWbrVrKunzkO7Z4DIKrWp1Pge1SoPwLRaSuIPcZlVrS6Sgr0wPxfTx/c1E6OoLrmi8HQqzMPNY08wk2Z8ebjWMkdiPQ9VJUtkmDraqI+lyhTSfgJhd72aQKP5zBRrWY9iP7orrreNoXDphoZgyOzPBs3lb+R9r2LQzBUo9hsWLb8vx7TmiVXYiI1z3mxRWb/zUIRLZGF+rnmPTR/fz2Id9PtyzPT7ekzpeSeX6Kc321YTCFrql6mJO9Q5a1jVrct/sXKt33nI4oZtdz1JXjLzAuO5Je7A63YcRH1DuPZetsdWJYusqaNVX1+P9evXY9q0aZbPx4wZgzfffNP2mCVLluCUU07B/fffj7/97W8oLCzE+eefj1mzZsHv99seU1dXh7q6sEvI4cOHARhacyDgrlI3iR/pW/axOxa9sxsL3tiBKSPLzLibFpfh7c/RvunnxG/3atlru2z/gtWf4sCRGixY/SkAmP+fOMT+ZWXHxCElWLD6U5RXho+dOqqX7fVl/qrX1a+16J3dePiVTwAA133nePP4h1d+iIraAB5e+SHa5ec6yxpsRF5OCAg2mtezk2fhm59ZPps4pATfG9gFK1euRLHfi88P1eKef7+P9vk+1NQHUFLkx8QhJZZ7MN8bXoBU1dQi3xuCPzcHU0f1SuhelXEbVlqMjTkhQzbtmtJ3xQU+lHUqwJSRsa8lxzy88kMsWP0pBvUsRke/10j+EWzEmfe/gkNVdchrak9+TgiBQABHauqQ7w3BgxA6FfowrLQIZ97/Srgfg414+JVPcHRhLqaO6mX26be+2R7b9h1G324dcLA6YCYZkf5e8MYO1NTXm7KpYzhxSAkQbMTspVuNVPM5IbMPpB2zXnwfc1/agpvHnojzBhwNoByFucDXDSH4mo45cKQa/9lSjcaQcQ0EG9EQCODowlzUNTSipsEoiqrKXV3XgIragEUmdT727uzHtn31GFZaFNHn63ccMNtUU99oXlNt84EjNRaZJg4pMf8temc37lm2NaKQbEmR3+w/keO0447Cxt0VlvGbMrIMM8/r23S9XmZ/d2rnw7Z9hzGstAhvfvolcnNCePvTL/HGtLPw2+8PwC3/2oxlHxiFaL0emHNX5Brz4GrLva3OpwWrP8XUUWXmNaVPZB5PHWXIV1tfj3wv0CEvB6t+eToA41mw8uVKnFhbi7u6jcCz/lLkAwgGG815qs4zuacnDu2J2S++j3yv8d33dx/E1FFlmLv8QxR4QxhWWmT7DBCZ398dQke/19Kmh1d+iJr6AIoLfLjuO8djwRs7MKhnMd789EDTKIRQURtA10IfjtQZddQ+/aICD6+sMufLihtHGffDyg8BADefc7w5Zg2BAOa+tBXBYCPyvcb5aurrzeuLbPf8+32zjfqzOTfHmNvG/Ko3r5Pn1SaMQsi8nsGBI9W459/vY2z/7ngzEEBDIGDMpZwQDlXVoaapLldDMITcHA8K84z7evbSrcjxGveVXL8uaCg+Mg65OcCKD/agqMCHAq+htIeCDZbrFxeE+09l6qheWL/zEJYdCRc7v/mc47Dwzc/w8CufoK6hETmeoHmu7/braj4T1GemPNuK8z2obQiie1EB9lbWwqNY7bq192HFjaMwdPZ/EAw2Is8LvL/7oPkMkPMg2GA+3wd074D/HTKynDYEAnj70y+R7w2hpMiP335/gOVZoN7HMr7/2bIHuTnAf7bswfkDu+OlD/Yi1DQe8b5v4yVda8d4rpc1roPl5eXo0aMH1qxZY7FI3XPPPfjLX/6Cjz6KTOf83e9+F6tWrcLZZ5+NX//61zhw4ACuvfZanHXWWY5xWnfddRdmzpwZ8flTTz2Fdu3aJa9BhBBCCGk9BIM45pVX8L/RoxGkCzwhrZbq6mpceumlrlwHs8aiJXg8HsvvoVAo4jMhGAzC4/Hg73//O4qKDDP4Aw88gO9///t45JFHbK1at912G2666Sbz98OHD6Nnz54YM2YMY7RSSCAQwMqVK3HOOecwRssFGWPR+morjnTul3aLllN/yG617Jqnss/cjomTRUuOl53X4gIf3rCJc1Cvs+CNHWb71NTE6vfEilFS5MfSn5+KlStX4s53c+DPy0O7/FyLvNJfAEw3w/Km1M0FuYYPv8g88r5XUVEbcJTTrk/cjpugjp/aPvW49TsPYfmWvRjbvzuGlHY0d+vFIiKWI8CwaNw+rp+lzx9+5RMzCN4DoKgpW9x13znecu77vz8wwiojLoDSX04y6m1b9M5uzFq61fxdjz0BAH9uDm4eeyK+N6gbVq5ciSOd+2HBm7swqGcxlm/Zi8aQdYwky53Irl7TThbpW/Xa5w4I70br43rLvzabf1Pbrvapm/vNbg7olq7iAh/a5edarC56m+zOB8A8l4yH/F2dE3ofyHfdzGm7ay54YweuGXwU+t5+Awa+uwofrfkUf77sZlx7fBXuWp+D6kZjjSL9olru3vz0AOoaGqPeW/ozQ64pbZHv+3O96FiYZ9tGu7nvdC/q59fnQEHT3Jw4tCdu+ddmLN+y12LdVZ9Lg3oW46UP9poWJLGo6fe1+uxRkXkpVkn1c7t7pmNhftQ2SF95ANwxvp/5vUE9i7F1zyFce3wV7nw3x7RoAcZ8lLFSx03Gw25eynVUWQVfjge5OR6zQLJOSVEBqusazeMBYNyA7ti4uwKd2vnwwd7Dlu/7lL5V70OjT7w488Sulv4Ty6Yu99DZK02ZpPUit/SXPC+lTXb3ekuuT9K1dhRvNzdkjaJ11FFHwev1Yt++fZbPv/zySxx99NG2x3Tv3h09evQwlSwA6Nu3L0KhEP73v//h+OOPjzgmPz8f+fn5EZ/7fD4qAC2Am36ONwC/NTL5tGMx+bRj0yrDxG/3wrJlWzHx270cxyxVY6W3f/7qz7GnohbzV39ufr5w7U4cqmmEPy8PU0Yd1xRrYf1OPDLbJfGwBP3byOBGdv3zQTNXoK4xgLqgBz6fz5JAQoL+X7vlO8ZBOV7MX7UdU0b1jhgDOZ8cr36nc/t2mDLquIj2HappRE5OLoAQDtU0YlSfLth1yIjT6ty+wBLgXhf0oK7REyGn2m96n7gdNzmPjNtJPTti6D2vAYAlWHv+6s+bkh54sGTzPjw4aUhE367bWYkXN5WjwJeD28f3M8dNMuwBgC8nB8FQyFowevXnAIDqBuPcjcjB+p2HcHb/Hlj98X7UNTSitiGIYJOycaimEYvWG8HuagD73JWfYv7qzyP6pa5p8W0EpuegNhCE35eDzoX55lgjx4vnNu5DewDrdx9GfdCD1z7+CtUNHng9wEk9O2H1x/uRk+M1F4YVNQGzP6MlnpG+1RNjvNaUBl3GFZDA933I8eQgEAzBA6MmmSS1eGZ9OWa8uA39S4pwVNCDKaN6m/dbRPtzvKgPeoAcL3w+H+av/hzVDeFFrddjzK0vDtZi16F9ZkIMdVzVQPxhZZ3M88n51fkuc85IBmGda9IH8l11Ti9aX+747NLn8eTOAWDCBODDD1HnzcV73U7A5acdC+x/H6P7lmDxpn0o8OWY1/uiqgE9iv147eOvUFFjpE0vzvGY57zunBPNay9aX475qz/HdeecaK0jplz/cH3QkLsxiIq6Wsv4yzNQH3/93pPf71yyzayzpD7jjAQ2+9AY8qBz+wLz+ut2VqK6wYN9XzdgzbTI55IRe+UBGoGiQh+Q4zVlOqlnJ4z+7euWe12SpeR6DeVB5Pj37cssmfD8vhwEmhKmSPKMIaUdsfrj/Zi78lPcPPaE8HNSQe3bcCKYWnx+cB+6FhpLYpkHwpdVDVi8aZ+ZDGTdzkp8UWXEvM1f/Xl47jWxcO1O1AU9yMnxmkldgHASiq8DUuvL3kiw61Bd0zHG388/uQQPNiWWMN4P1uPqG4GvAw2Yu/JTTD7tWLMv5RlkyB4+5kB1g3n/qTJX1oUs39OZ8eI28xkpz42TenbEjBe3mc9ju+e8SqrWBC29Ro/nWlmTDCMvLw9DhgzBypUrLZ+vXLnSMbnFiBEjUF5ejq+//tr87OOPP0ZOTg6++c1vplRekjqSUVehNRTBSzXJ6CO9CG2qUIPDnWp5uE0T6zS/7JJB2KXTbm4aWj3NuZ6OXE3J7fTCUsfOLmHFihtHRRwj7cvPNRb9EiSvpmZ2I6fab3aJRFSiJfZQ095Leu6KmoCZoMMDoKquwawN1a2owFKfSQgXaT3XkmZezRZWmJ9r1qRSkz4crKo300FL/7+4ySgQWxsImnERjSFE1NeSxABGGmX7fpHaNVIDaPr4flgz7SwzucKcpdswu8ny9dIHey0JTyR1s5qOXf4mJQDkHrArpWBXqFYd11F9uphzSAr8ykK3yO/DroPVZlKLzXuMwsCb91Q6JsHQ7xlJQ32wqq4ptbfXrIkkZQb6lxRF3NcL1+60pIjX551eZFwShkhSCb08gmTxW7h2p6XtTinWI3jhBWDoUODDD1HRqSsuuew3qL3iR+ZO/vIte3FSjyIzQUO054SaVEAtHqzXjIvEWBz7vB7L/aZuJuhJd6Q/9GQjIYTnsiSpkOePXZ00u/aoY5DXlHRB6sSp957cU3cs/gBzlm7D1NG9seS6kdhx33h8MmecJWGSFNWVeZKf60X/kiJ4YNQPk3IYsUqH6PNDEqiEAIsFSa4lfxO1SC1zUdfQaHm/yfjNWboVFTUBdCrMt1hqjfulEdHwAGa7pN/W7zyE8x9+A71vW2rWM7NDnjl6Eg293pdekkPPVnl+U0KVYr/P/L8ct/rj/Vgz7Syz1qAUbAfCpR+i0RrqYsVL1ihaAHDTTTfh8ccfxxNPPIFt27bhxhtvxK5du3DNNdcAMNz+rrjiCvP7l156KTp37owf//jH2Lp1K1avXo1f/epXuPLKKx2TYZDMJxkL2rZ2syeiNDW3jxau3Wkp8JhKVGXCKQOfU4Y8u0xvdvNLXRyrixO1Poy6aEtGW9Rr6NkNo41PPGOnL7wAq5uLU7v0BUvnwjxLMVzJPgfAceFjNyZ2/S/1bwRxW6moCWDXwWpsv3c89lXWmotvpzbaFWT1ADimUzvz7+t2HDQLvtYEGlHk95n9L4suKQar8+XhWrMf9Xo++gJfzbypZ1CU+0ZSagOG66YotjIecq3wgrPRXHCq6e31AsTRUJVbmUPine9pOh8QXtR5EC6mCsCi8MgY2t0zdU3KYU0gaGbAk8W0LOol+yFgZIyURa2MxfiBJRHK/MK1RkF0Kab6YlOdNMm+KO2SzI1qdkunrJi291MwCPz614Yl68gRYNQoFG/djOf/cpMlrbUooHJNdawLm7If5HhgFp9Va4ypikBjCBZlS83yKIt3ycAXTdGQtkh/ADCz9c28YIDlGSfZVQFjI0P6XDYC9PaoMskYSPp+2eiQ9tQplh7AUEDmLN3qWJtQaiOqaeS3lFeayotsOtnVT5Q5oWZCVPtB2i3PmPCzJoT2iktuCMAz7+w2ryX3eGVNwLIBUBsIms8w9d4wspNG1vny+7zoUexHsd+HEIx5L1keAWOjQjYzGoIhs426e5/6zJE09+UVNTi+a3uL4qQ/X+cu/8g8R5Hfh3mTBpvPJ7vi7Wr/yXMAMDINSh87rTlaQ12seMka10EAmDhxIr766ivcfffd2Lt3LwYMGIBly5ahtNR4Se/duxe7du0yv/+Nb3wDK1euxHXXXYdTTjkFnTt3xsUXX4zZs2enqwkkCcjCpDmotYLaArqVwA3N7SNJ1+z12Bc8TBWq3G7aqveN0/yy+1z/THaQZQGSDFQrjNqmaOPjduzUtMoAzLpaqruZXFu3Sogs8jepW7Sl3FgQyO/FTYqKvvCxu4acU+87KRbqVF/n+qc3mG2Q1MRi8etcmIfNTYVOZ7zwgdmnav0okXn+qu0or7DGiaguV1JLTGJqRPY7FhvnDQRDWLl1n1mLqmrvYQSCIQzsUWQu8Ocs3YoZL3xgqT+j9kllTcC8b8YPLMHbn34JoBE3jz3RdMdRa0CtmXYWBs1cYSqAav0qvU5Wovf/nU3tAwzLgtRjcqoVJoj1okex3+a6xoB5EF68H6yqM3fWVcvJwao6i2I7b9JgS9/p81OdGyHAomhOHd3b7OeKpvT6dor9vsoajB9YEnH/mezZAzz8MADgmdO+h8Cc3+AymzAGr8ewNAVUrUJOoRSMnb9qO/qXFJk1mqRNVXUNaF/gQ2VNwJyj+n2nUlETMK1HIrf0o1hj1LaofacqTHKc3Mciq5qmvLImgOuf3hBRx0yO0VGVESBkWqLl3LWBoOV4fb4eqQ1YniniKgjA8dkhbZQ5MeOFD7Bux0FU1TXA78vBwap6zF3+kXEvBxuB/e/j3AHdsW5nJQ5W1Tf1Z7jmlPosGT+wxGzPjBc+MNtSUhxO4b/kupEY1OSOGwJwfNdvYNfBalTVNSAQDJn1suzqEk4eXopBM1dYyiCUFBfgYJVReFgUrR7FBQA8EfeeHLelvBLb7w3Xwrr+6Q1mP6j3kQeR72rd+l/X0GjeR+KeKNeRzS/1Oaa/C5Oxfss2ssqiBQDXXnstPv/8c9TV1WH9+vUYNSocfPzkk09i1apVlu+feOKJWLlyJaqrq7F792789re/pTWLxF3/J9tJZBepuX2k1oZpyX6OV+5Y7m3pQtxQxDLk1m0QcN8HsmOt1itSrS0AItyudJcqqc8jFjf9p9SxssSHaG6YsSxwMpdG9ekCwIjTkh1avfCw7MDKOWVhBKCpNtE2s19ld111UVPdbPyay430zfTx/Uzry+ThpTj/5BKzlpbUgNpSXolP7hmHz+8bj4uH9jT7Sf6uW96kT0TJkBo1kpRh4tCejm5fgrg26eOv1pdygz6/ZOFYUlwQMRbrdhx0rPnWuTDP/Bl2q9qGPRU1yM/1mjV9hpV1wpHagGkplPaLcip1y9SFoLpjrj7fpo7uHRFlIq6VsnAvzM+1bAKpcl//9AZL/bi+d75k2zb07Ak89RTu/sE03HL6lXj0jV2Wa97yr80AgLH9u+PcAd3h9cDsM0G1duypqMFXVfWmC2vY8tNozgsPwmOoWrrFyqi2V7WUqtZJ3UIdzX1X6mupfHmk1nTtDMHoI3H/E6t2/5IiW4vx3OUfmW6/ch9U1TXC78uBp2l+qcc71S5U+7EwPzci/sxufsi9LPdeRU0AtYFwLbG5yz8yE46ECZk/9WdBY8iw4OTl5pjuxaIw7qusNfuk750v4ZhO4YzVW8orsXHGGHTtYNxTnQrzoj6npa6asKei1lT6RLp9lbUR7wJps2xkqKiWU7mG3Iu6LGrfAeHNHN09UVwM/T6vqWQBsFi82ipZZdFq6zAJBEmUdOwiZcvOlbo77HbH3+levHnsCc2yAqrnVV+GMy8Y4LgL3Zw+ttu5V1HdMNdMOwsj7ns1wqVKLBbqzmistolVAYClTerOOwCL1UuuL/KoiqAuMwBTsTmmUztsKa9E/5IifFVVj/KKGoRg9Gu3In+Ei5qcQ6xmdn2s979qYTn/4TeweY9xPWmznEsUFEnkoPbJkNKOZtv6lxS5Gg9BnXeqwiBJQKQQ8dLN5RhW1ikicF/6XrdMyK63uoDUrYG69UFt05ZyQ8ndUl5pWg1lJ35Uny5mn8m88gCWRAzS5s6FeeYY6rFeqiVG7yuxeIgFUnVfdHqX6gqwurBcPedRPPfZ1zjlJxONa2zKx5ALL0bxx/tNpUDOt3zLXoweavzs+I12aAwhomjtkutGmv0o95Ru2czPDSdUCCF8Dv35Kq5itYFgxMJadTUdcd+rlrlt13dTR/fGnKXbTEuGmjUv0Bgy3e3U+SjjLPfTxhljIizGYomS63sAy6K8vKIWIQC7DlZHWETUMdMtZ7Hu0TXTzrLIKs+Cg1V1qAkEzTivmqAR//TSB3tR2+gxXfrke/6me6muIWi69crx0keiKMoGT00gaN4HQFjpsfM6mPniFgQaQ5j54hZLe+odshMObEpII8WtdWuYej+qc1Pka1+Qi963LcX4gSWW54nucdCpMN/sO9VaCkTOQ/UZDSDChbotknUWrbZMPHEXhLQG7Py8U5HIJF6Ln9O92FwroHpeNQ7FKW5LjftJBIlFkcVbrHg13Uop1sCDVXWW+IdYbXOKUVJ33lWrl6qUqckRJJlCsd+HgT2KTKuNHFuYn4uLh/ZEtyI/Lh7aE2umnYXzmqxPebk55g68aunRd2rt+jjafNl1sNr8qS7u5PvDyjqhW5Efw8o6WfpEXYSrCzMVfdwllkX+JgsqwFAYZCEIhNOx63NWZFCTrYglSre8qQt4N7GD4wcafZ3j8SBHKcOiKgyqVXTWhAHmnFAVtq+q6k0rYazkM+px8yYNRmF+LmoCQTMpTqwNS7nvVKvYtaf3wpbLr8GoO36Gu56ahWcXv2XpN8AaF7Vw7U7keY3lVd9uHcz2Obn5qveUatkUhbR9gc9MAmE3H2VhnJ/rxawJAyI2PfT7C0DU593k4aWoVZI2nHdyCXw54YQbqtVUtebqc0GfI7JhIvFWMheEAl8Oiv0+i/JVVdcQkSBEYjZzPIYyVFXXYInrkjnl93nNZ5PMaSC8sSJJaGZNGGCRpKApDqyhMYjyihrzHhLLqsRuqm0oaFLKZl4wAF9V1Vv6U6yOfl8OVn+83zJ2YhG+/ukNpntpoDGEsmlL0ffOl0wrIJr6WGKsZk8YgCXXjTQt8DVNbpf6/S0xiDOXbEHZtKU4/vZleL9JCayoaYiICZT7Q/U4UK3E+ble8z7qe+fLKJtmTUAkYy5ytmTYQKZCRSuLaItBhHYwY2DbQV20qdkEm5ukQ58/ibgbJvNetHMJmzdpsOlGpH8PQIRikgh6O3QFUvoFgK17mLhh1QSCloVmtGtFUw51FzBBz6alLkhlEb3rYLWZFUs9j96meZMGo6TYb+40qwsNFTvlT/+b9IPdnJJsg35fjrnABGBxvVRd+gwXHa/F1Wfh2p0Y8+Bqy3Wnju5tJniQn3bul6pSdEyndmhf4LNdqOuL4SGlHS3ulvL5+ScbaZ0l0cHc5R+Z89RuE0D+VlLsRyAYsqTmlu8BYZdJUYQEtT2i0Ofl5pgKi+4CZ3ecLo/d3/XxmzdpMGZeMMD8W/fA1zj+Rxej/8I/AAAWDRyD7//fUEwd3dtSR02/htQj2r7/a1TUBBwTA6ntuP7pDZasckV+n5lJr1NhHjbOGGPORzUxRrTsknqf9yj245hO7bCvsgbrdhyMaL9Q0JS0we/zYt6kwaarW1AbRzWrpzoXdIVX/xwIW4BkUS4uuaJkFvt9aAiGIhR+idkMBEOobXL9k42CGS98YPZHbaDRfDbJnNbdpKXvVc488Wh4Pcb51dbK/0WBsCoRoQhF0O/LwWzNNbaiJoA7Fn+AmS9uwZ6KGtP18sVNVkuqbJLUNTTC26TldCrMNzOjhue91VF2SGlHS1ISmXfSFvnp9cDcnOpfUmRJNiP3m3qvFWnuqUYMWKPpHSCuwc+8sxuA4cLdlsIzokFFK4toa3FFTtCyl93EoyjbLZiB6LuxsXCaP6pcdlmqVJJ9L6q749Fcg6MtIpOxAeF0PrmuZGrTrTtOmb7U/pRFVzTlUO3XycNLzR3j/FyvY+ZAO0uBLKDmLv8IB6vqI76jKhdOlh67PnFiztKtZkyGGo8BGLvgsihS40yMukTlpkVx8vBSbJv1Xey4L6xcz1+1PaKI6/xV280FX26Ox6KYiqI0aOYKrP54v9l/7++pNN3A9P6XPpcFnLqglSQe6rhJfEu0TJLqQlAsCb4cjxnrUez3WRQzuxhJvd8rm5RqVWGxu5djjVe0mCQ5z5ymItf9vvgM/1zwCwz7dD2qffn42fm34qExV+GykcY9KqUP9DgvUcIAoLYhnCjArr8kIY3at+JiJxkm1XvyYFUdAPs5KzF6TshYywbDkk3llvt7xgsfmJah47t+o2kJHzLjnKLdK/r9abdJJkkY9DIFoogBYZff804uQWF+rhkf2L8kHM+mWlhyczymdUtipeTcBTYZ/sTNTpezQcnesXF3BRpDkTGagGFhVDd7VKT9ogjWNwTxzDu7ccficMIhQU+OkpvjMeeMSn6u15xnatkGed40NFrdCtfvPGR5n4SVwwLL9/Jyc7DrYLVpgVNjquav2o6bx55gSa+vl30YUtrRsjEkzzLJsMn1WRgqWiTroGUvu4lHUVYX3jLuanprO6VCf+HHcoezs5TprhOxaK6Soy5iotXL0WXXLTzxvuCcLFj6+dTAfDvrjuoGKP2hWm5064Rb5dCprpFc9+axJ5hJKdS6XnJ9w+LVGGEtUZULUbacEkW4Uaprlaxg7yvWIA+MBZS6U6zWwLKrS6QydXRvlBT5Iz6T9Vhhfq5lR16vOQbATBmtHu/0/FQVwdkTjAWYLMDF2ipuUKK82o2hOt7iBhkMhXBOv24RyQzEKqrfa6o1dcYLHyhpCcILfTfvAjf3hX6e2kAQF2x5Dc8u/BW+WfkFdnbsjgsv/y2W9j0dQLg+l5ML4uThpbh9XD8AwLkDujtuCOh9LjXh1MW8fk+qGej2VNTg2NuWoq6h0XS9FPmcno2DZq5ATo7Hcn2Z+5LgYU9FDd7fU2laVcTdV1/wx7IkilvxnUqqfYnFU5VTmUNSfwoIbwjsqzTiA1V3vMnDS3HeycZ9m+v1mJYa1Z1v6ujemD6+r+mypyYMqQkEzU0jcR9WLa5TRpaZtbrUhCUil6Bu9sh4zFm6FVV1DabSp1qHAZjKVI/iAvQo9pvKXK7XE5F4RJK1iJVMrF/qZkMgGDKtU/qmizzbACO+UixYfl+OaV2bu/wjMwOjJPNRN9VUC7ZsDokSN318X3NjSK41sEdkIpO2DhUtknXQspcc1F3GZLpixlo8J6oou1Uq9L9FUybUvwOwvKiiLY5iXTNeZBETy7oSbe7bxS/FipuKpvSofxOlQDLFSZ+omRH1/pAN24NVdRaXSLfjqFvB9OyIch39+HU7Dpop68X9KJpSJ+cW9xe77+j3iv69804Ou+kV+HLMGIod9403FUFZHOkbB7IbbOfONn/VdgzqWQwAWNTkkjN5eClOalr8HdOpXYS1cUhpR0tGxiNKEdZRfbrEnEPFfp+54FMX4GJtVWvsqGOoWjtV61pebnjXW40JVMcjWlZEdS6JenCwqs4M7rfLaOnWdVDuE1kcC+edXILTdm6Gv6EOe04djQk/fBAfdekFwLgH1Jg2u42RhWt3YsEbO8w+dMqMp/e5uL/qSTP076pKQzAESwxaNNdIcakLNIbMmk5VdQ1minSvJ+wyKPFS6jNQd11VC9HbbQKJW3FIO3eRYtFcuHanqYiJEllZE4hQ7NU4LEn0YswLj5ntTtCT2Mh5dQuVmqjD78sxlZKHX/nETP+/62C1xdKk1wmUTQM1jquiJmDW3/MpSi0Qtrjtqahtsk56TKVOTaPu9+VYMvaqluYQjNprgGEpbgyFY0NVhpV1srxXpK35uV7LPJLiyvm5XtNtU/pHtWCHU/NHvqfE1X3JdSNtN07aMlS0CGmjqO4FsZSEeCw2bhfPiSrKavC8nRKkv/DduhKpO6xipZFsbrHa7WQlc2NxE9Qd40SstXbxSxU1gagWsmhKj/o3WQirO+1AOE3wi5vKI5Q0WZzUBIJmcVS77GY9iv3oXJgXobCJhVG3BKnnUN3O5Psik9cDS3IFp3mpWhNlx3jmki22blDqbq6qXAwr64TZTQVGp4/vZ9mpB8IZyewsNqs/3m8uXkTRuP7pDWbB3eVb9gKAuXAHYMnmJ30DGAuj1R/vNxf2otgITgt4VSYgXAtH/b7TBoB+fVnginWtJtCIkqaslKpCpY6H9IEs+IHwfaImMZCmiJXFDlXJs4srVP9+52KxeoZjDMX1q/Hhh4FHHsGq/7cAtd/oAMBY1Ir1KJrbqeryec+yrVGfr2qfV9U1OCqc8uwUly6xtOR47AtCq5sLcm9UNtXYkvlY35Q6HkBTDJwXgFEQ95x+3WwVRNV1VW+HXfFxuV7/kiLkN8XYqbFNarFcn1ecFWE+MyShiRqHpbrE5efmYOOMMehUmGe2xe4ZKpkni/0+zJ4wwLSASwzi9PH9sGnGWGMsaq3pydV76P0m1zhRNpdsKrcoSCf1sFolZ5zfv8lyFenGKEXRpZ/D1i4/ts06FwDMDTPVdRIwFGwgXMAYMO6/Oxd/YCquqiVSxlf6X95vQFjhrmtyc5XMnxIX6fd54fflmDGSdkWPVeh1ZIWKFiFtFHVHPRnuN/p5ndxkmuu/LbuyAGyVNf2FH8sCGu3vbuV1spK5sbi5lSUeRAER9xU3SrRTbSYgMjuhIC//XK8nok1GprScpqKg4ayEqqIp7ZUUxXpAuKD2i368LMIAWOaznVJm1z5VwRUCwZC5aBk0c4Vld13dZa9sSnihKhe6+6S6ux3LXVL6V929PropCYFYtgBEZKSUNqkLLtVNUxZGEr9lNxZ2qMer7kB2Yyi1lWTHX43P6lyYh4Vrw8Vql24ujzrfVNdTNQOjuCW5sTSv3PpFkyvXNkusoLhKrf54v0VhGHHwM/zlzT/iD69+bIz9y59i4bfG49HXP0dNIGi6l4n1aFhZJzPBiL7BMqS0o+nyKZZVschEszRL4gc7hVh/biy5biRmTxiA7kV+izJkt3kCwKx7Vd8QxHknR9a6M6xPjWb7xHVPj8tUrWqqwiTW7fMffsMyN8RKInGCFTUBMwkHYK2zJHFLHoTdaSVBiCi3PYr96F9SZCabEBlELvm/HlskFqNKJYupKHKxnrkeGEpgsd+H3CZTklNMlViNxGo7Z+lWlFfU4Piu37C4CqrnFnn1jTZ1w+yrqnqcf3JJxPVCgEVRCyGcZES9R4xkHI2mhV21cIrCnZ+bY84H1SKZn5uD+oagOTdi9Rm9jqx4QqGQ3eYEaeLw4cMoKipCZWUlOnTokG5xWi2BQADLli3DuHHj4PP5Yh9AWhQ7S1QiY5YMi9agmSvMgHGppZQqrn96g1nzKFadKBVZ0AGI2BFW+wBA1P5obn/p8tuNmVrHR1VO5NpSi8iuLXJssd9nxgsBMF33VEsHYCgCR2oDZk0dOUbqx/i8HnwyZ5xFdql5I30g1+xR7MeaaWfF1Uf6d+V3qdPUragA+ypr0a2oAFI7CoB5LRW1Xsz5J5eY6dp1OfV+lfkr/TGqTxezf0f16YL1Ow+hc2GeGduR7w3h/mGNeOijb+Cknp3M2ljTxxsxQPNXWet0ScyW2h/STvkeEC6uHGqSQ6y3Uk9LravlNKbqGMqiXqw8PYr9Zp0jrwfoVuQ3+wuApV/UubZ+5yFTTlEmRQ4394D0u1ht5KfdXASMhf7Fm/+DX7/8e3jr67H++jtwcbvhZhukbXpNLgDmc6iuIWgWkZX5suqXp2PZsmW4Z3MBvqxqMBe/arIGmVN295rMBX2uquMjiqvd/ASs9/+wsk6WMVSvPXf5R00Kj9Fb+ble8/oyFupY241D79uWWiw/cg2Z736f1+wjDwyrSV1Do+lyJ+MkY1OYn2uZT/KZxCoBhoWxa4cCs98kLbzeH9JGNW28XZ/J81HuNbX9cszBqnrUBBrh93kxfXxfy/MjLzfHVMrVWlrC7KYYujsXh2MO/T4v8nNzbMdbxiU/14ubx55g2WT05XiQ6/WYfwNgbiI0BEM47+QSS5069Vkk96rf50V9QyP6lxSZrofqM15/bsi4ORWIbu67PRHStXaMRzegRYsQEpNk7VAl4zxq0oNEcesK6WTJiXUe1dKiu+65jVECwrvYc5ZujdgtdoMaf6Qes+id3ZZ4GjsXKNVdzi79NmDvdil1X2RXWgKtZWErC28gbHkpzDN2WeWnKrtaO0muqVpX4plTTvF7m5ssauUVtehW5EdVXXhBaJdN0ajfVW/GMqiZvuTc4ibnVAwagOkOJa48qz/ejz0VNdh1sBqzJwyw7JgP6lmMFzeFa2NJGmtVcZA4I6e4JRWJndG/Iy5bek0zNUZO2lZV12Ba/iQ2TE3BrlreVOuYzDexlojMep2n/iVFpvXL7TNDriNWm/MUNyfVle2YTu1Q5A1h5suPYuaSB+CtrwcuuABDZv3KYlmQ+SWxaTJuVXUNpvKmKlkRloS68OK+f0mRmZxBtfKq15DnxpJNVpdu1R1Td5F1su6pzy8n12SxmojlQiw/qz/eb6knB8DxWbVw7U7k5YaXk6pMcvz08X3NsS/wec1ryvfPO7nEYimT+1zmk1xftfaK5VmeUaJY64kYpI1h5SYn4p4ecd+rZhzkihtHmVYbcaGTOZ3f1M783BxzTJZcNxIzLxhguibOvGCAbS086Tv1vqtpSk+vj3fY2iRurZ9akmAEQ2Hrquou3tCUvv3FTeFnvuq9Isq6MaaGBTVcV8v6vpL2qXXPnGKvkuGt0lqhokUIySqcFtaq0hNLkYoVR6YH9TstZNQ4Ih0nBUb/jn5+NZGFZMSqCQQTSp2ryjDjhQ/MhcSCN3ZE+PDrcrh1LZX4KL2v1RpA9Q1Bs+6MuPXJ/6eO7h2ROtjOXUgPsk8k2FqP3xHlwNeUIrrA5zVjWSSLm5pNEVAXpo1mcP+eihp0LsyzyKkr6eJadUyndmbwfjTXTjVBCmCknFbTVauWEUl64dQnqkKsJlIAwhngdAVW7SsZC7FASdsamgJFQgi7O8riT/pA0nfLfau63Enf6Uq0/F+tcxYLuW+feWc39jXFR+muYZOHl6JTYT5CAL78eAd++9iNuPjdfyPo8WDTT24CnnsO6NAhqvIuGSYbgiFzrCXhgd/nNRezcq+pVp6vquqxccYY5Od6LVnfVPlFiQXslShdAZGaX3bPPj1ey87i4JRts66h0aIEq/er/nydv8rIhihKbF5ujlmIV46fPLzUTJgwfXxfM2ZJkj7oSVbURBYSOyTPA9X9ThR5uXaBL8cSb6fH+QFGPSrVDVme4xIHOebB1ZbnmRqr5rTRJxkT6xoaMXl4qbnJIO2UsVTvTz0borgRqqjJM9RYNqfi0FLAONQ0LnpSIXUzRSyzIcC0lDWGDItb3ztfsri4HmmKW3NS7BmX5QwVLUJI0ognaUayUZWnWLtrbuPI3FpLZFGiW65iJbeQ+Bo14Ybqly+xS5IRS03h6wZ1sd4YCidUmDKyzDFNvHpsrBgGVVa1DequtKpsqu0FYFkAq7v1EmBe2bSzri8OdaUgWgZNu3gisRxJ4ohAMISSYj/O6Xc0gHDcg7oYk3OrWf3ylV38LeWVjoV7r396A5ZsCteZuXnsCdg267uYNcE6P1RFSOSVNOFTRpZh+vi+6FHsN9M0S8C9npVRvw/VfpdYKiBsSZDxUBVYdUx0i6ZqNVJjAQGru52alU/PfCeL12hKtGoRi4VunVyyKbIItSTSGf7Fx1jy5A04Zc821H+jPf77/xbg2mPHY+G63TGvI2nFpd8qagLo2qEAn983Httmfdecw3KvlRT5I5IHqHFJuvyinNrFGUofAeEsd7plXN38iWY9l/FQMw6qmyGSXVFfrNudK5wQxWNaXO0yE6rUN/WBKD3qGMlGk/STFCWW+KBts841rWPiFi0KtFiV1AQ5Yl3SLdSqpbdHsR9TRpYBAMor3WetFUQBrwkEMWjmCjPjX76iEE8ebi1mPH18P2ycMca859VsjDIOxf5cU3ahoTFk1r2bs3QryqYtxbodB7Fm2lmYPr6fxQKnyq8/N28ee4JW7thAxlAsXOKlABhWWfVZLzAuyxkqWoSQpJFO9wF1YRtrdy3aS8Htzpy8aNTaI3q73bx87BYt8vKTVOHTx/fD+IEl2FJeGZcblcggC1ZJqDBxaM9mvxRl0er3eS0vdXVR7hTgbbfgkx14Fdlp1b8LWJUCOafd4i7anJQ00sVN9X4kGYe6a6u6UMrPUX26oDA/F6P6dDF30nVlQB173SJjt3iVY1SX0+uf3mAu2CcO7Wme86uqeou1THdTtGuz00JedRHULX5OVl1VCb957Alm/SLVhVRXsvVFreqWpyvR8nexgLiJj5Tj1LpH+pjL/Pw6lIMOtV/j0y6lyHtvPW78uoetUmC3caTKpC9cVTlk0a66oYXbGV7eqskcovWLm7ZHe2bp1i27wsHqpoco/arCorvFijVMxrtWicESy4psQqmp2SVWTLeOqAlkjOQM3gj3T0G3GKtWW7mHxDIt1h/dQq27Pk8c2hOAoRzrliL5XVUEZcwXrt1pJskAws8su8RNUsxYVTDtrGQyDoX5YSVMEMu2WBLFVXDEfa9aEo3o8usbGZOHl1pKU9gl6hAFSzZnxJXbrnh9NNK5CZtucmN/hRBC3KEG4rc0qruJ/J5KZNEmmZ6ixUrYoQa3A+FjRW59ES6Lk6Wby+NKzAGEFyUbd1dgtBbalmgQs7RfDyrXx18fF32OyGJk7vKPsHHGGKzbcRAvbipHrteD3Bwj2FtdHMrCXT/P/FXbcbCqztzpd7oeYCxs5FyrP95vJugArEka1OPV5ANqPRlJwywLMDm/2maplaUm9hDFY+7yjyz9P3V0b1O2JZvKke9VIzoMhpR2xL7KGnPuyPiu/ni/aQnQY8vUY/QxUa8/eXg4kcfc5R85JkDQA+V7FPtt7z99jGLNM1W2eOamHLdw7U4zsN9yP4ZCZr9v9/XBj35wF3b26oe3jj8egKHMVtYETEuiWCFFbqf2SyIMsSDJPyNI/31bWfNzc1ATMMZIVbJ1y45d23Wrsd2xMl9H3PeqZVzlOyPue9VUdCQJg11/yhwtVrJmApHzzexihBNdqMk09lTUmIlR1AQpejKUg1V15n0l7phOcy9WiQ+5hyRDpFMb7eZVdV0D5izdhplLtqAhGMJJPYosFi5RnmRezF+13Sx4LO0fUtrR3LiReQXAVu5oc16sVhU1AfhyPCjMz8UxndqhbNpSeBRzVIEvx9LPAMxnqnpuiS1Vnx1AePNjztKt5jP0pB7h55W0d0hpR6zcus9SPkTaEA3dU6QtQYsWISRpNMd9IFN2vNxa5fQYJjs3HzfX0WtMqQqY6qIRjxuVirookV12OznUmAY3Y5CoT746Rxau3WkJ8AYMi0GR34dAYwi1gaC5mFSLEEvSB9UNcero3qbb0M1jT7BYv+zcIqU/pU6OuBWpiz/1+HmTBpuWILu4NdWNUt/tnTdpcIRFMuxuFZlkoH2Bz7R5yE7yond2mzvpat0pNTU/ADPJgO76uHLrFxG1qvTx0MdWZLtj8Qe2Ral1C1W0+aNfx81cc7oXox2rWlUBQ6l47oW3gDPOwOScL0z3qt0Dv42fnT8IAMyisyHAdHVUrZDRXIxrA5FugE6I3KP6dImZ0EfOLyUGdNdiu+Q0QGTSjGgxe7pFU5VRtWaKxQeA7XxTs/IV+X1mMg3ASDriAZDj8VisS+p9Jta1WmWTpCEYssSw6X2jj7FqdRNLuljk5izdZrFYqm28/ukNKJu2FH3vfNmMq6toSoUeaEosocbGihWzuEmZGjRzBb48YmQo9ftyTKuZWK4AY17NXf6Raa3T7011Hks77mgad8BIyQ8YyT8qawLYvKcSIYRrafl9RhITqXUlqAqe9FtNoNGsUwZYrZNiIRPEHVqOFSuzyAOEk9pEK1sAtO0YLipahJCMIJ1uhypuXwhuYpgSuY7uqib9EY8blX4+ebmLa4yTHPGMgd0CXbXS2C2E7YLoxRpot+iUgO75q8JZ72Qhp2bdk++oi5hYbQkX8/WYMTfq7q9+vLg8DSntiGFlnWz7URZgACz9oMZoyQJeddGyq50DGIrf2P7dAQAPv/JJxKJWrqOmBNfrTCWiEKiyCbr7o1rEWuaO7mIWbQzcKFG6i5rdsfqc0ufzNzevwxmXjQNefx0fnT8JC9/6PGLu6oWZ1fTb4oqoz2c1Tk1Xmq5/egNOnrncsc1LN5ebFgtJkiKKrJ4UQ9xnxZU0miVHRXcVVJNl6BYT1V1UxlAsFbLQHjRzhVkIVzaHxL1QEj5MHR1ObAPAjI8KwVAS9BpMqpVaktFIgogCxY3NLk6yR7FR6FwKe4uboLTXsDY2molrnOaPFD+uCTRi1tKtAIDignCyGgAo9uda3O8kaYfEL0r9L9UdUPpV4vNkbtm5JTs9o9RYRSHSvm3Eh0nSIUlKIt9Vz60+o3TrpKSWV2NA5bq6nFI/sUdxQYTC7fTsb8sxXFS0CCEZQabseCWy8x7P95yuI+iWskT7I2yRMV7NeuYtOzniiU+za2s0Kw1gH49mZw1UUyqrWe/kxS+xA3UNQXMhrsvutEgXF78vD9c2LaTsi8Tq51PdBu0WSOoCTOSXgsZLlELM/UuKIhJVqPNA5A3BcHt689MDAIy2ijvVMZ3amXL5m7Ks7amowcqt+yyZ29R22CkE0hd6hjEVpxg0dYEm/VHX0Gjp82jzyS4eDLDOEafyCuqxYg2RsTD789vH4MZtL+Pv/5iOzlUV2Nq1DFMm3I75//3MURZJsKBaC76qqnccb6eNFtW1VPpZVZ4kC6hYzlQFXI+lU5ONqKUWgEjlT0XuZ10B1jdDgMjU+rqMovzrLtIy5/NzjTl4x+IPzKQMonBJcW875VA2UACj6HlNwKgZtXHGGEwf38+cr/rmkygFap0q6e45S7eaypdYZ/w+I9arMN+LXtOWYl9ljaUEgU67/FxMH98XEnZ1pLbB9lktiS2kmLFaZFm8EqTmGRBpMbdTmgvzDaVVTdwxb9JgzJ4wwOxHKSDu9+XA5zUSkPhyPMhrsuhLNkE7d3Y1gyJgTSwkc+HioT3Rrchvbijp9/FXVfVNZ/NEpMAHrJtM6fZQyQQYo0UIyQic/OXTjVvf8mT5oCerH1TXLgCWui6L3tmN+as/j4h/iHVtPS5Hb6saJ2MXq6fGO0n8iF60VY0pAYzFpMQAyQ6yFC+tqmtATaAR63ceMi19shjWF+m67EJ+rhedCvMjZNX7QuKspPirFAeVmB792LnLP7LsPuvFQp3micgri6S5L21p+ksIwZBxxi3llZi/qt6MERRU1yu1P+2K2arWBMDIMqbKpMYoeT2IsOKpMV9SrNkYj6DZhmjzSf4mBW0lxskuhk/vZzWWzLaWVHU1cPXV+P7ChQCA5/uNxm3f/TkKOrTHzTZKnyqnjK0Uip06ujfW7ThoiYlT+1AvTL5wrVFTKhg0rChyr8m9OPOCAZZYQ3VeAdaYQpFJrqEWtdXnkV1Ml1OMlRTvVRPNyKJfd9WVczoVYNeRGFKnmDPpb2mrXEesQhVKnJx6vMyDYChkurkJErsEhLMxCl4PMH18X0weXope05YCgBm7JdcYVtYJM5dsgahrknVQHRu7/hX3wK7tC7Bm2llmbKMejyY/i/0+i7XXLrZRCqWHELbyy7NS6ripfXrHYsPyGAiGEAg2oqExiHNP6m7KbedxoMowdXRvszi0GnOm/q6PhX6P2sWYSWyeHoPaFqFFixCS8aQyfivWud1aeZy+53T+VMekObmBAOE6WvHuOtrF5dihLpjVc8vnqluk9IPqsmTnojV1dDibpMSM2LndyXl1i5ZqdfHAWJyJi426CNBduQSJ0RIlQrJ3xepD2U2XnWx9nji5vulWvpqGIPqXFDXVKfKa7lNqDSE1g1gstyTVmuDL8UTsrKuugna1vvRiuGumnYVjOrUD4Gw9dYNq4Zs8PHrNNNu+OngQGDkSWLgQQa8X94y5Gjf93y8x5pRjTUtfrFgysaio9cDsLGtqXJ7IN3f5R5bF/oI3dljGXOKHxCK3fuchjB9YgvU7D5kKhmo9UV1iVWVXn0d27pQyR9RskIARuxNCuG6T7naryqi7y9n1381jT3C0fAJhpV5/5qjXUTPe6S6hMg8kZkqsRFKnKhAM4UhtwJIFVEphqHND3EB9Xo/FpRIAunYoMK8vcaDDyjph+73jMaysU4Tl1G4MdG8E+dm/pMhS4Hvu8o8cLe561sxY7rc6gWDIkqwkmlutnm1Ub4f0kR5/Fc0NUHeJBpwLXQOZE5udSjyhUMjO5ZM0cfjwYRQVFaGyshIdOnRItzitFiND0zKMGzcOPp8v9gFNJJoxrS2S7L5yM2bJuqbsFOoZ7hJFlUteOPGe223bZMe+2O+z7EhKmyRLVayd4mT0pYzZPZsLUBc0TCF2mQObK8PCtTvNOBendusWnmK/z8z+l+g4RxtX3aKlLgLU6/W+balpJdl+73jLedVjZZdfFq26zHZ9ZfeZzA+/z4tOhXkRffvtWctx+8Ba3LLOi6Pat7OVOVZf2I2VOkYeALMmGIVv5Zh1Ow5GZEq0s1CIsqBaJ9S+i8X1T2/Ai5vKUdBUV8jOIhrXvA8GgQsvBN56C3jmGSwsKIs4XuZgsd+HuoZG1AaCOO/ksKVSEIuhKEJ2faBbemQ8870h3D+sEUe6nITJpx1rK6rIIahjate/6r2iZ4OM9Uyzs+j6fV5sm/XdqHNVvb7ef3qGTifU77cv8Nk+c/S+tLt/5yzdao6VuDqqzw27fnEjl9zPD6/8ELcPrMWM93yoqAuZzy4ZUyCc7dHpnrKz/KnHC35fDmoCwYjno34OwHn+q+M2c8kWBIIh+HI8mHF+/4jnlf6suP7pDVHvb72PAGuNPLd9HOs5mOj7V0h07dhc4tENaNEiWU2sXVsSJh195faaybIqJSJXoueWc+gWGLdMHd3bEuweq4/02Aq311R3JNWsWlIHym5X1Qm3Ac3zV223uM3ZZTLTLTw3jz3Bsotut5Oqt0svUhwt3kzfaVUtZOrY22V3tLPkyS67xK3osUZ2fRVtztQGGm3vleu+czwAI0BfZNZrNyXC5OGlZsKBEKy75zNe+MAsuBptEQbALP4844UPzJ37eDJjivtVTSBozm216G4sZXHEfa9i4VufA/VG3MjCdbsxZvAUPPenF4DRox0tPRJDJ3WIJPZOLFRSLFdio+xk0C09gOHe5wHgb4qTsUtAo8dsAZHujyK3mpVU5isQaSWQ+QYgIoW3er5Ki9tsjuVYu7m6ZFN5xLXk2aXGcUVDrfOmW6GlP+av2o5jOrXDkdoA1u04aHv/5ud6EQLMIub6c0P6xe0zUrc0vmEu9I1BqWuwuiF64PysFqudmhRCPtczqwKRLo76OVTrop13gPSJbPjkeo0kIjPO729+Ltb7IaUdI96xYvV6vymj4pylWx3jbu0KILvt42hzqznv32yCihbJappzk7Zmk7Vd29LxQHN7zVgKmdsFfiJyJXJuCWSWIPVoSpJdMUoAptuMU6C4k0sZYF1kxZrH6uLx4Vc+ARAuyOnkEhUvurudBIn7fTkY1aeLxe1G72/dVUz+b+eWpbfLLjuj4DSuTtcT7LI7ymJD/i/flwVk/5IiUw67BYiMkbjUqXNGAskLmrKtqS5N6jmu+87xEe500Ra5dveUrrxK0Ly4kKkLaDWpgH4OVRkCwskTvqqqt82MGW2Oqgs5ABaFtq6h0ZKW266Nh748iO5X/wiYMgUIhTB/1XZ8XOvFb7fVmOdXLZCSpVGUZGn/+IElpix+n9cS7xbtHl+4dif63vkyek1bir53voTVH+9HCEDHKO6TqhKlFo8GELEhYffsPKZTO8dELzNe+MBM4a2m8lc3diRmK1p6efk+EKkEyrNLLUgdDTs3U7Wt0h+b91Saiq3dvSnKr/wEgHU7DpoL9njc1QbNXIGZS7agvKLGLPIrG1ESqyWKqJzXrnCyoLriAuHU6rLp5PXATGIhYZV6tlU5h7guyv3idC/LfSiZFdWU//NXhYsZr/54f4Tro8wv2WypDQQj3iuDZq7A3OUf4eaxJ5ibCdGUfbc09/2bbTAZBslq9CDNeFAfXq3tJrdrW3P6KlHcXlN1R2gJ7IJ343HJEyVAdVVxc614/qaPofxTXXpG3PeqY2IKYero3pZ01QCw4sZRppvF3OUf4WBVHfre+RLyc70RbjFu+kfNnDZv0mDTStGpMF9Jo+7eciZyywLbrn9lzqiuTYmit9GuzeKepPaztG1LeaXpMgcg4t6TsSxX3MTUBA8S1yOLe3XsGwIB3D7QSO+OHK+RFKDeyBCmy6O2RS+EDYSLQ8s1xEVLH9v5q7ZbZBXlT3VHskuwoC8O5bzRnrXR7sVBM1fY7vwLv+rtxcCHfoVjv/gcDVu8eHnsZEwdfWJEAg05v8ynqroGVDa5a0qiBFUe1dVNdRu0w1jQGgt/kdUD4JCZmS0Smdtqpjcg7KY1f9V228Wn9KMoo3YxY+piX6d9gXHPq/e40/2tzl01+YT6PpG/220Sqe5vantlTHSrxvxV29G5MA9byivRragAvW9baiaeke/k53pREwgiP9cb0Rdqn+mup3o75fktvLjJeG4teGMHbjjBSJDTQ6mTpfeZHUNKO1rcQMVKrD7HhpV1wrxJgx2fN3LP6s90vUC5tFdcJ9VNIEGuW9cQNN2b9YyRgHFP5Od6zUQr8l5Ri7/r6wg5Tk+n7/Ydmo61SDqhRYu0WVqzyTrb2paqXS11J91pVz0Rl0onC0ci8jm5xzmNofSVmo45VmKKWROMXXNxQ1P/Vpifi5qAUX/Fznrkpn90dztVdnVnXAL+3bqcRAvAl36YN2mwxbXGKZlFNFSXOamXpVqn5i7/yFSkZPFlLMCMVW23ogIz+B1AhIVS+iNX8kXD3gUpBMOS5FQrSRaIkqHNLn2zarVRF54j7nvVYglwUnqfeWc39lTUoMifC6/HCM6fv2q7xYJll2DhSG3Y+qjPGX0u6/Ne5BPLguBkDQYALFuGCT+dgGO/+BwH2nfCxEn34t7/+SwWP71/5XwNTUkV6hsaI5TUvne+bLazf0mRmb4dAPre+TLKplnn1tTRvc06UlI4NgSgpqmvb/nXZpRNW4rjb1+GQTNXmKm/wjB9GAAAgnpJREFUgcg5IP2ku6Gqf5d7SawequusboUa1aeLxWpkV+g4mrUEsKZ+163o8nc7hVC1RqtjIveUJOpQrRpLrhuJ7feOR3lFLRpDhgKkyqfOh1gWNyd3NbHSqhQ0jZ8UdL/uO8djzbSzsPrj/WY71MLRds9tNVuo1M7qXJiHOxd/EGGZ190BVeu8apmTZ82LTTX4VMVadZ28eewJZuIWtQ82zhiDToV5ppKlx9Opc0LmuYy1usHh9BxyW7NQpzV7E9lBRYu0WVqzybo1t02I9rDW3ZvmLv/INmsUEFsptbuO9Kvqi58I0dzjYo2hyD2qT5eY15FzORUslposdot7NzFBw8o6Wequ6LK3L4j08XcT23H90xtQ1uSSpRfDVVHjBqQw8Iubyi3jpo+jHjcmblBinfMAZh0sqQ81fmCJZfElqZj3VNSarph2i1npj1xv+JUr7nqAoQCICibFR+UcohyfdtxRqKprgN+XA7/Pa6nJEwvpn/xcr7k4Xbq53LZPpTZRRU0Dtt87Hl9V1UdVsMRdTU2zrs8Zu4WlOu9juYFaCAaB2bMR+r//AyoqsH/At/Dfv7+EfQOGmP0Za5PivJPDGwPqPFCtU4C1JIL8TeK51HNum/VdfH7feGybdW5EjNbyLXvNgr0VNQGzjdKfds8diXuzeyaIq6EU7lb7TP27ZMiMFQtjp9ypz027/tT/rqO6DutjAiAi9gywuh+LO1tB0/F+X47p4qe6/aptjXUfqIqZIFbZ6eP7AgjH09k9J0OAqXCpypOqOBb7fWhf4MOwsk5YM+0ss1gzEL439HeTjI3qhqluptnVL5O5oLpZO9030u9q/a5oBcHl+5IFUjYUnbIX2v0uJHNzM5uhokVIGyUTd5XikSnaw1r+BsB8udvW20Fshaa5LwW38SnxWh91y5aquDhdU2IQwrEI4Z3PbbPOtQT1q3+PlmIbiD0WquKgLipiBVQv3VxuJkoAjJf+wap60zIgu8qyO66S6/VYZNJl1N3ZZNEmKZmL/D5zgZOf643YUfYgMhWzvuDQrWsS8wEYmSZVdxyxOkociCx8hY27K1BRE0Cnwnxsm/Vd27ECrFYgNemCmjhA+h9AxCJb2iQ/1Z1zVVlS2y33lrrgrayxJgXQXcVEua+qazAXqVJwVfrPdl5dfTVw553whEJYOOhcfH/iPbjovGGOcX86C9fuNGOj5k0aHCGXT1mNq0k91MVotGQf4jYrMVp9uxkZyXI8MItu2ymsantlXOyeCdI2tSCwXdIXNZ5GXP/srO92zxHV8rlwrZHtT41lioX0Qb2STEKXW2+b6n4sxYolC2V9QzhhifpsizXOugVc4uAEuzEAgDEPrsbCtTtNWdXYqlDTPw9giStcv/NQxHNy/MASs5SEuG06jbG6GSWo74doymS0zUKZB3OXf2TGXMl8d6o1OHV0b5zTr5tpFdXvQ73fncbB6b2QbR43zYWKFmnVZKIykSlk4q5SPNaOaA9rdXGovtzdWgDcXCeqW5NNm+z6WXePSwRVcZF+c9pxXvDGDstPHaf7JdaL0c41zCmoX1VqAPuAajle6kb5fTmme0xNoBEVNQG8uKnc3FWW3fGbx55g7loX5uVG3XW1k0tcEfU5IwkrquoaMKpPF/Qo9mPWhAFYct1IzJ5grTekLjjUxSMQTnyhFoYFYLordi7MM+OBZOErYzVlZJklI6NTbTa72Cg1PTgAMwmL9INq+Vhy3Uh8ft94LLlupKVfnHbOZTEoC0nAmnWyriFo6ypmuDXlm+MnYyvHOyWEWDnoLFTnFeDhSbdixnd/hqKiQsfkI3bPECe3RlFGCvMMF6wexX5LUg9ZjMrnse4VcUM7WG3EAnUv8mPjjDHm/LK738XCMKpPl5geCU6us3bfEQtZNOv71NG9zeQ+0s6bx55gxg+qlrxYzz7dQmMnk+6ymeMxbtz+JUUR31Fdk+XZNmfp1qhZSdXvqYqZ3K+zJ1iTj6iUVxrvIABmH9889gQUKZb/WRMGYOOMMVGzmM6bNBizJgxAMBQyNx3UwtDikqpnGlRdMzfOGGMmFLr+6Q227vAiZ7TNQnlWytjayaveG6oSlqhiFMuy3Jo9blRYRysGrKPVMqSqFkKy6y9lE7ECVBNJAmE5/s3P0H7/+1HrxMR9TsUNKZvGLFpfSr2S8QNLIrKxNee8+vfUflMTFlhqtMQYs3jul2iy6fVp7GrLRDuHkxxqkH1dQyNqAkGzUK9kWJOg7mh95qZf9YB+WYSoMsl36hoaLQHlcl67GlF2MsjYCdJv81dtx9RRvdB+//uWZ2Os2mwiozr3RJmSv6l13AqaYotkfOz6R+8PO9dBdbzrGoKmBc+plo+etGD+qu1mEL6lbfv3A126mG2sLt+Hw4VFEX2mJ5WINn/0uajW1rKrxWSXqMNuDAR5px3pchLmrvzUnCPRkirEuv9i3S9Oda1iySr0vfNl1AQazfpa6rGAYeWMle5fTewQ6z7U5QdiP/dFHrEuAfbxR/r39HFV5638bVhpEUa3+x9uXedFbaPH1ZyKRawaYmrbzz/ZeEfo46k+H6Q96kaV5Xlh09/R5r3dPaj/P5MVItbRIiTNtDUTtUosi1Vzd5ViWUcSQbV2ZNOYOfX1wrU7TatGIinUY8VCCHq/Oe04q7EHdrvBdvdLIn726nkk051dOnKnOejmvj2nXzfTsiSxDBU1ASzZVI4hpR1tFxtSd8spXk9vnxpHZCeTfEcSiajxMuKiVuT3oSYQND/TU1rPX7Xd3LEf2KMowjqmjpldUoto1sNou9LiCieumbKbfv3TG2zTuusuoOrnqluufK9TYV7Ejr8+HupCTtorKecBGPFYv/41cNxxwIcfmnOjXUk3s8+ASJdgsbLpcYV6G+z6zsmdLJab2qCZK9D3zpfMe0p1z5WEMzKXErUcO91zMpZOqdajWaBUWUQxVl1c5djZEwaY8XpyDbt2qFZUt++XeFyo1VTr4s5n1249JTsAy72pxhXK35Zv2Wse75TQxk6+WO7hqmVcP4dY/4DwO0K3CKquqqJcdm4qbq4+Z9V3he5i6eQ5oR6nxlIC0a1kxD20aMWAFq2WIV27Eq2Z5lqsYp4/BRatbCXRneZYx7vdiXaL3GcPffQN7DhoJHLQLTS6HNGsA26sQnpq+Vi7r9HQd77lPENKO5pJKoDwDredBUJ2hOU7gP3O7fVPb8CSTYarlOw027XPyaIlC85ivw91DY2oDQSRm+NBIBhCsd+HUX26uLJ0qvfZ/NWfR1hddEub0w61k9XRAyNeTHa6y6YtNcdr9oTwnHUab92C4daSEWte/eJbR+Hi390GLFtm/OH++4Ff/Sqi/91YVZ3mt913nCzQ+rHq72rcDWDMzbycEG444Ws89NE3MGXUcZZ5Ajhb+aLR3OeMHbr1OR4vCLtjncbf7bzUvx9rPsVj9ZfzqQlvipruxfU7D5kWrVvWeXFU+3aux0b6we/zor6h0ZX3Qqz+0K1QgLU8g9cDbL93vHk+9fk2a8IAc07qJQr0+1m3IGebFxAtWoSQtJFqP+hoGZraGrEsM7EWP0471fpOtJuYQzffmTKyzNxBVhMhOMXgJOpnL7E6aspjdWEaT3zgwrU7zax7stssu7EvbirHzWNPwPlKNjn9GmIFys3xWMZE/570n1rsVbVGqpax+au2Y1SfLsjP9aKuIYjVH+83FzOqhUSC+QPBkOWcbiydquXYzuoSLc7Crg9VC06x32dRsoBwqmtJWR4r8YCeTEG3ZMRrvZk8vBRr/q8rLr72e8CyZWjIy8fMi6dh4ekXR7Qn2hxUrVqSAh2w7tLbyaDH1QnR4kflWurclBitKSPLImLSKps2T+K12jf3OWOH3gdVdQ2Yu/wj2+eHfn2JKetcmGdaiZ0sWeq8dHP/y3dcZaJ0gTpPxZIlmRtF5vu/PxBAuKC7W6QPawONtnNHT4ojFjU1GY/eZ5OHW5MQyRxSn3HCwrU7zedbCGGlTc2kamehlkyk6jumLXsBpQoqWoQQkiKcAr91tz23yoydK6G+kHWziJk4tKfpSuImBXSiqAtANQlAIm44YZe0/AgXGFlczJs0GNvvHW8mCFCvIZaEwvzcqItt1TphLJ69EYV41QXg0s3lTe6DjRG1cuQ6avYxCYRXrxtNOdYX7HptLGmDXQIJfS6oyoL0hZ5Ncvr4vk0Z3/rGpRA7jal6Dt2dyVZJeuYZ4NvfBrZvB0pLcdXVv8Ofy0a6Xmir/SLts1to6hYFkUuvCae2T3XnUtsli2CnzJ0ikygmoSbZ9OdCrHIVTpsnydpU091lY6EX7AYM5cuulp2aStzNc0a+o2dVtJPZbmwTdeUDjILubvtSXJGHlHa0lA1Q0ZV33d02Vh9IPa2+d76E1R/vN5+nah+oxbIPVtVh7vKPzL6z60M5t5QHWbfjoKvEGiR+qGgRQogNdi9rt4uhaN+zW8w0Z6GkLzTiVZbU79vJkYj1CbB3tXKTAdTpenbtunnsCfD7cuBBZAFevS2yqJIirk5WDqkBVNfQiJvHnoBOhXmoqAlgztKtKJu2FF8errWk6R4/sMRUyJysFPMmDUZJsR+BYMgsLKr2TbTFoqBbjlWlSc2wJos+O4VWVRYky6EsftXruVGIdXQlUE+978qSuWQJMHEiUF0NnH028O67OPvS77pSSPV+UTcOZIxEYdYtCuoxqrKut0/iIIeUdnQsKi2IJfLhVz6xWHv6lxQBMKxATnIL0t5oNeTc4ibWMp5YKcCqDKlxRnZWQdWC6+Z5J99RN2jcblJFm2fqtd3IEes9oLZVnzvyvf4lRZa6bTJ33FogV279whILavdslHGTmFDVUjesrFOEpVK3RCdqOXT7XG/LUNEihBAFp8WNvjjTcesaE+9iRsUuqF1faMSrtMn3AftUx+quqpsXqlP/xdM/PYr96FyYF7Erbid7p8J8hBDbBc9pYaHXH1Nrd6mL9dpA2P2vMD/XXAAOK+uEwvxcnNPvaFOJssPO0iR1xDoX5pk70brlzCnZjJoAAYApo7rAVYPbxYqk1tESS8T6nYciZLKzOsWjLOup910pbueeC5x+OnDLLcBLLwFHHWWRwY3Sb3cNGSO1QLL028GqOosyGK2N6hySpBqA/X0jlsjK2oBpvRhS2tEsCL15T2XUIrDq8wZwrqvlFjcbGNGSJtihKkNqMh47q2Ai1nI7a726SeUUnxXvteQ6agITwa7fwhsb25CXa2z06FYsNanMlvJKS902u6Qydm2Wa9cqRbTt3hvquKklJFQrvZOl0sly2NyNMRKGihYhJKOJ17LUnPMCzgUlY7l7qC93pxe9vDxvHntCQrWz7Ba+bgLBdRa9s9sxW5j+wtQVlFgvVLv+U3dxo/WPej1RAlR3G7tYKnWR7Aa5tlgW1IxlMsYehBc0Is95J5eYNb3sds9j7QirYycyAEa2s/f3VFqUO1VOWbCrYyYKIWDMR3FFLPBFLvr0flMtM+riSpdJd/WzO1e0PrazNNrN30tv+jP+/kbT+Xw+4D//AX7zGyA3Uml1s4B2Usz0+1MsMDWBoEUZjFeZc4rdEgukmnhF3wzQx0Xd8Ji7/CNTGdTraqlxgm6fg27dkxNFPY9YdoaVdbIo7arS7wY7a72qRNhtDiTSJrtNDf35Iu57g2auMOOhagNGiYmSYn+EFevFTWFrnvqMibVxZTdnJXPi7KbaXbEsgaqyHI5ttbe4y7joyTLc3Af6c53YQ0WLEJIyElWI7Hb11Ae+00sgnus5vaTl5aaneVZ9+4HIXWx1IQHA4u4SrS3NIdHzLXhjR8RxagyFHW53idX+k/6QbFmyixtrIbRw7c6InWKnWKqlm8stCwS38SxfVdUDsCrOco1ZyoJGzjesrBN23Dce22ada7t77rQjbLcYFhnEQlngM17FHoRlke/Igv2eZVstFkFR+tWkHjWBIHI8hgXHbtx090DVLUuVSdzsdKuk2zng1tK4/cHH8MTD18A77dbwh3l5jt93mjdOY+7kFivKpp1l2Y0FV1ea9YLhKiVFfjM5y5DSjuY11eQwKupGhZ72W/+OU+yZndxuFJ1ku4Hpz6dozyu7a6vJNtQCvnJv2m0OJIJcZ1DP4gjZRQlXS0hIAonzbMZQjivweSNKNgD2G1dq20WZrKprABB5n8aLWLOk3ILdOew2sdwoULGsc8SAihYhWU4m+0gnqgg47UQLTgu+eK7n9JJ2Wsy5cWGKpRTG64bnRKLWHGHKyLIIpcCp3pdd7I76ud2CTnbmE3V9EqVB3SnWx0Vd4LpRwnWZVcVZzhktRk0U8vMffsPi0ijHqMqNelw0S5ccO318P1PBc1qwqMkG7GR3WvDbzVv5u90YTh4eznYGwHaR6EbRiaqUBQLADTdgxjP3oaChHqcHvzI+S5BY1ljAfmPk5rEnRLh7xmvB1d0x9e+vuHGUJSOjuHc5pSxXNyqcago6KffR+iLW39z83Y5o7x99Dtgp/XbWUvnbyq370BgC3t9TGXV8nZJauEXixzburogquyjJsglnpwDJcdPH98X2e8fjYps6eOrzR7XMzV+13TxXRU0gZv1EN94edi6pse5VtwpUst5nrR0qWoRkOZnsI52IX75+nN3izmnBF8/1mvOSdnp52Sk+dm2JtYiL9QLVd1vj3U2UVOGqm4iTW2Q8SqUuo7jhST+4WaC73U1VXeDcWiT0BU0sq9qgmStwsKoexX6jPsueihps3lMZEeivn/v6pzegvKIGfl+O6aK4p6ImIt5MVWJjWRtU64bTPSHWP6fCtbpy6lQQ28mqG8vdVr2mY/9++SW++PbpwO9+Z/x+xx3o8fp/sHB9ecKLtWgLeCf5on0u57QremyHOhdl3qnxPk7WWLt7B4id9U2NjbJb6DvJHev5GE+bBWnLHYs/iJjf+hyItlmlyibzUjLpFfhy4kqIEi+6m66T7HaKuY5+nHqPqZs2svGmxy4uXLsTlU2bHJU1AccNETWGL9pGk7rZ0PfOl2yLkdttYrm1XMezKdFWoaJFSJaTqDLTEiTq/x/vcfEsUpIho35MNMVH/W548V4XVZGIZhmbu/yjZvvFl1daF9d2FhL9b0676k676fJ3qVXjdoc9HneUaEq43ctfX0hGW7SJHDWBRhTm55oK+cAeRbYpnFXXS0moUd8QNF0UgejKWawNk9vH9Yt5n4s10imOUFdOJdakomlBp/eh3v+x3G1jzsd33gGGDMHRG97GkTw/pk2eCcyaBXi9zdowiraAj6a4i9x64hVJ2V3X0Og61bk+79R4HzcL2XhcpGPJYZe23ymeU70Hoh0bzWol6PM7Gm7mjL9JwZo+vl9Ub4LmbjbqbrpO6FY3PQNiLNx4Ucxftd0sGB5CZCkBQY3hUxXjaN4eorjK9wR9fON9J2byGiQToKJFSJaTqDLTmki3Vc/pRWPnHiNpeqNlnbJbGKovaVURsatZE00GO6LNISf3K7tj7Kx3o/p0cYz9cuMWmugOtp2VA0BE9jm32SGlPUuuG2kJ9JcYrNUf7zddL6VuVl5uDoaUdoSvyRwl1i07GfUYOZFZLCMTh/aMsHo5uQlFSxutjpvUFgPsLWBOfQq4c7e1UFVlZBX83/9QecyxuPpnj2DAz35o2xcqehtjzQc3blD6xoyeeEXcaGsCwbg3NHTryKJ3dps1kGRR7nTv6NakeBawTm5pglurXjzHCn6f1zbzXjScNqtmvPABRvXpEqFgCW6eGalCd/ezy+SnK2Bqplg3XhQyD9TkFdHa5wEsWRhlI87uvJKg5vyTS2zdo9XNiXieuVyDRIeKFiEk62mpF22suCQnC4C6iImV2t3JouP0krarWRNNBsAI0FdTxLvBjTJr1w9q/Rw330/kurFksbO0yQLGyVVq8vDoqa71GCwgHM8kdbMko13X9gUAYLFu6TLq/STnVy0jel84uQlFc4dU569dKuhoi6xmxcQUFuK/v5yN//YbgZefeAHjLj7LojS6vYec3B2drNpuFAc9HbmdwuB24albRx5+5ZOoNZDU43RrkriVRXMptWuT3XFuLNNOVq9oz1fDUtJoiafUcbNwV8sVRHOJ1ueJk8yxSGQDR910csrkpytg8bi+y98K83NNS/rk4ZHJgxau3Ym6hkZ4AJykJNtwUv7kvNtmnYsd90XWiHPj2poImRw/3pJQ0SJthpa46flgSQ+J7KglMlbxvoD0F1isxbvdMTp6W2WR2L+kKGbmNWHFjaMi3IdiucEkqszGip9RZbCrv+X2utHOrVqL1P5zcpWKp12SkMApS2WsHWlBCtjKT7u4EflM4oAki50bV0jAXjHT56NbhdqVArB3L/Duu+avt3v64If/Nw3z3vnSUWHScTv+TueLZXkFjCyN3Yr8ZkKTeZMGm3F5gNXaovdzPM+RWNaxaEqh7q4Z61i3SrjdhkQ86dKjjY/TPW2HuhHjlPnUDrfzSKc5yoQoNHaZ/NxspjnNGfncrpC4WM7FrbWmqa7fV1X1lgyYbmo0xnIVdGNddoobS6QcRGvHEwqFQrG/1nY5fPgwioqKUFlZiQ4dOqRbnFZLIBDAsmXLMG7cOPh8vtgHJMCI+17Fnooa9Cj2m7tS2XiNTKElxiyVJDJWie6epuo8Km7ao4+ZyFFV12DJMqcenwxZ9evYySjyF/t9KMzPtY0lkcWUuOG4bf+gmStQURMwM4ap7VHbByBmW+36Ixl91Pu2pWZCku33jjc/t7vP1LYCsP2/3RxwI6fb78x44QM0huA4XnjzTeD73wcaG4H164FvftNybkn5X+z3YeOMMa5lcJoH6hjr54uF3dxRZVi34yCWNNVF6lHsN+exBzBjEPU+l3E70uUkzF/9OYaUdnTMNBgNaW9lTQAhRN6f+nf1uRzPdd3cp/HILM8UAOa952ZOxXNdp3GPNY/t/u72ndbc+93pWSWfC36fF50K87CnosZMYiM/Ze5F69N4rx/PcUDks0Y/byreczrpWofEoxvQokXaDC3hXtZSLmyk+SQyVsnyRU/FTl8i7RE5ADjuhNrtGMeKC4t2nWixCXaWIfUcTm4x6vF255akD3UNjY47/UA4HX0060Fzg/GddrN197VoOFnLorlCull4qq53gLO7nATiS0ZJS1rue1/BM1fejsCoM4C9e/GZpx0Wr/0MgPX+UWNXdKL1p5MVMtr5YmE3d3S3TiAyyYjsUke77yYO7ZlwplG1vSGb6+vH6e6Da6adhdUf73dt8WmWa6iC3KsqsZLbTB5uTdTi1lLoNO5Oc0ieXet2HLQkKdIzRUajue+BWG6cQm2gMcJyLj9nuSheHO/14znO7hx2HhyM3QKi56kkpBUhrkLZfg3SfFpipy0a4naVTIVc5p64AQL2lh8nOeLpBzUuzCkuw+k6ACxKji5/tHPIYjHefsvP9aImEER+rtex7+evCqe4B2BZsEZri9NnTuiLYWHepMGu+hKI7CunwHY3nzv9Pdb3gfCOurR9wcptuP6fD+Di91cCAJadMAI3j7sBHT9twIQYbVDvSaf+lO+Ia5muGCV6L7uZe7o8fl8O8nO9ri0KseZItP6Odp+qbo1qce/mEKs/Yj0/5V41Njg8yM/NcSWTel2xjkSbf9Fkdepvu2eXGg95Q5x6eiLvElVm3QoJGEWOt5RXYvzAkpSsKezO6dQO/XOn547TeQldB2NC18GWIdvd0Noi2TxmrcHF0+nFKK40QKQLTiJjZned65/egKWbyzF+YAmGlXWydeVyki9VfR/tvOoCffXH+21lVdsAxHYhjEY0N8d4F2ZuxsyN+2O87nj692NeY/duHBh7Ho7atglBTw4eG3slPrx8KtbvqnDlviWL3WjzojlzJ1p74hljtzIsfPMztN//Po50OQmTTzvWUY5Yn7tpVzSXu3jP6+b7qbiH451vifaX+uwSRcs816he5pjNX/25q3Mn2hd2bppAdNffVOLkup2Od2U8Y0vXQUJIVNKdPCPd129J1La2lItnKvs3lruaB4go2iuuMW5dZAB79495kwZj+71G9ionlz4n+aTv7QoKu8EuONypWLTehtUf7zdlVV2ppA1OWb7iJZqbYyrcaexcxux2m52uq7YfgK0LoZrQwPZc99yDo7ZtAjp1Qs7yl3HtS3/CvEu/FeGepY63Krd6TzrdN5LUpHNhXrMT2cjv0dxE7eRw++yQbJFq1kg7OYRE54Xucmf393jO68YNNhXPTyeXXt26Go+cdqjPLkF1HwaMTJFu050n2hd27tQt8V5yaovqtphIMqJkkgrX+nRCRYuQNJLuB0oi14/Xnz1TcLMYTQZOMRPJPC/g/AKUmIVZEwZExIU4Lf6ag8QFOdX90uWTvo8Vs6Ji16eSVl1+RksJLcdLrJZdG+KNDbGTLVafpIrmLoZU5Vfi1HSFBIBj/BcAYO5c4LLL8PyfXsCI9d6I79jdC6rcsRbWQLhUwPt7KuPONKf3kdPCMpbMbp8dki1SzRppJ0cySObzzI18qXh+Rruum3igWLi5r9Xnott054n2hcivxqTanUvfWGrupp1dW1QLkh6fl444q3Qod6mk2YrW4cOHsXjxYmzbti0Z8hDSpkj3AyWR66v+7KkiFZagZPe1k4xOu/TNJdqOr4r6uX59p8VfPO3T/w7ANmX95OGl5sLdLmlGPH2jJuQQq0b/kiIU+33Iy80xFZpYY5Kf6zUVIDV4PtYi3+m84rZltxiPlcY/GXNcT2ARTcmMdh1V+ZU4NV0huXnsCdYkFNXVwMMPAxJ9UFgILFyIuR/XR7Vk6nFVdnI7zQ35vMDnRbzI/TB/lZG0Q64dq3hsovev1NGSn6ocmZQgQJ0fzY1dbc6cjtYvdn/TP4t1bTebXvJcvO47x7tKd94c3M4DfWOpuZt2dm1x2oRMl8dLpt0jzSVuReviiy/G73//ewBATU0NTjnlFFx88cUYOHAgnn322aQLSEhrJt0PlESuLw9qN4v1REmFpa+5fa2/dNQgdDtrRlVdAwDnBXCs8+sk8rLX26wu/hJdmMhxTrVx1IyEEni+ZFO5eR03ykE0RBn4qqq+qbBnEEdqA1FlVpWFROqYqefVrWu6YuKWZMxxN+eI5zrS9m5FBbhj8Qc4/+E3bBX3m0/IA0aMAK6/HrjvPttzOFky7eLD9BpusTYRpo/vm1CGwXgtVIk+Mxau3YkxD66O65iWIJb7ZjybDHYk67mdyALfzhU0XndxO+XYjfKZSoVE5JZsg07yu5XBbk479U26PW5aC3ErWqtXr8bpp58OAHj++ecRCoVQUVGBefPmYfbs2UkXkBCSWciDWt+pTSaJ7iC2REyUvMjFstIYQsTCzU0RXCfFzUmxAZKntEW7nhDr5QvYu5KpWb3UVOW6K1o8L281hbMq19TRveGBMQZzl38U9yLfDt3yAVgLHttZLGdeMCBh16Hm7JK7OUc815F+2lNRCwDYvKcy8u9DGnHhVRcAGzcCXboAp55qe454YoKipe2PJmeq+ly/f+J9rsxftR3llTWxv+jy3Ik+19w8Y/T7KdomQyyaG3+ZyDX1awOwVRzt7utkyZJKhUTmuhTTToUM8VqWSXzErWhVVlaiUydjwF9++WVcdNFFaNeuHcaPH49PPvkk6QIS0lbJlEQV6ZAj0YVUKl94YqmqrAmYMUFOQehuXlC6rE7H2NWxikUyAtpjvXwjXMmaUOtBzZs0GLMnWPuouZY5/f9Ffp/t95qDqlQPmrkCL24ylEcp/GoXV+SE0/2TDFndnCOR6wzsUWT5CcBwEbz/fuC73wUOHgROOcUoRDx6dKLiA0h9PJva/7H6wslaG+9zZero3igp8kf9TizLsEqizzU3zxg1EYSd5SYRRT2e+Es7mvOMUF1B9fM0R4GLpjwmQyGJ9p51clFW/15V15C0eyhVm3ttlbgVrZ49e+Ktt95CVVUVXn75ZYwZY1TiPnToEAoKCpIuICFtlXhfCql60GWT+0Aqd+DEUhVC2FXMTZyUECuZRXMW3nbnjpq4IIHr2b187fp7WFkndCvymzuw+nWS7S7bnEK1Tqi74xU1AVdj7oR+/8RaUOl/UzNFRosVS+a9v+S6kfj8vvFYct1ILFy7E2fPXIrPzzkPuPVWIBgEfvxj4PXXgZ7Nt2q7iWdTScS65Pb5pVprm7M5MHl4KVbcOCqha9mR6HMtnmeMUz81x7080edwc54RTpsyicrlRnl0q8An6mEQy0VZrMKxikK7JZF3fjatE1qauBWtG264AZdddhm++c1vonv37hjdtJu1evVqnHTSScmWj5A2S7wvhVQ96DLdfSCeHWv9+/HSHFcxt8ksdNwoEnbnduO+2Bz5ndqQyDxMVRB9oqi742JtkTGPV9Zou+puXLsk6cw9y7Y6Wj/s4lOSxfxV2+H/7BP0WLUc8PmARx8FFiwA0rSxGo/iCsT3/FKttanaHBB5pRyBfi07VKtTPOMbj9zJdNdOpL/i3YBIhGhyRYuru/7pDSivqIHf567wsk5zPQxivXeS/Y5O5HyZvk5IJ3ErWtdeey3eeustPPHEE1izZg1ycoxTHHvssYzRIiSJxPuyStWDLt0JO2IR78I+Fb7sbkh0fNzEFqjn1hdyLf3y1b/nJt5FxkRPLJJK3MhlZ21p7oaG2j9uXLsk6UxjCKiqa4jqqgo4pyqP1f5o8h7sOxDrpt8PvPYaMHUq4PE0+7yJEq87mNt7NlrSA7s2JdpOkVfKEQDulaeWiAVKl7t2tPMk4j6dyPWd4uqWbi5HCEB9QzBlz/7mJGVJpjdEoufL9HVCOkkovfspp5yC8ePHY8+ePWhoMDJrjR8/HiNGjEiqcIQQ9+gPukzxmW7phVeyv99c3Pq7R+uneBaT+kIuWS8+ty9S/Xu67E4B+XaJReKhuS5lbhdz8cwfu9gKtX+cXLuA8OJbTTrTEAxFdVVV41Ni9UdU5TYYBO69F9i0yTz3iJk3GpkGY5BqF6JkuIPZEct1K1kFc5sTN9TctibzWRxtQyeR66T6uezG8ukUV6fGnSZCJishdPlLPXErWtXV1ZgyZQratWuH/v37Y9euXQCA66+/HvdpaV4JIS1PPEHWLUFLL7zcfF+sCckoAul2QRur/dG+l4j7U6oTC7hFl8cpIN8psYhbEklYkKiF0e18k9gKwMhY6PZcdm3xeoDzTo5c6Dm5zsbqj6mjrRkbhUWvfIDVJ50O3H47cOGFQFVVzHbq522JjQwpI7Bux8GkLGLtrMJO8ZROn7mhOYpiIq7R6u/JfBZH29BJ5DrR2ubGfVptZzSrebTNKrEeS1ykMG/SYGy/dzzmTRqcMRuYyYIuf6knbkXrtttuw6ZNm7Bq1SpL8ouzzz4bixYtSqpwhJD4iSfIuiVoiQd5otaMFzeVN9slxc2CNhGXO5V4FvduvjvmwdUJKZnxLKCcLHnxJBCJh0QSFqjXS2ZSDXW339vkZbd+56GY34+2sN80YyzmTRoccazTmDj1hzouasZGAMCHH2L4pHEYtfVN1Ht9wPTpRiHiGPKqJDs+xwm1jEAyiKak2rUpWR4EybZ2RLMgJ/NZ7CamKFnPfDfJJlTLsZPVPJZMEg8pP+3IJAtQMpS+TLa2tRbiVrQWL16M3//+9xg5ciQ8ip92v379sH17+iceIW0dp4DudNESD/JErRkFPm+zrx3rBZ6oy10qKa+swdLN5QmnOnazgGrJBUm0+Bq778aTbj3WTrkd6m6/G0tdIolSFq41Cv0erKqzTevsxlpmUS4XL0b9kKEo3b8bX7Q/Cq/84Z/AlCkJWQfiJZHzNdedKxpO1q1o46+6nkZLrJBKFq6NTPOttiWZz5jmxBQlG7EcS1Y+J6t5LJnEoiU/7cgkC1AmKX3EmbgVrf3796Nr164Rn1dVVVkUL0JIemiLO1SJWjOmj+/bbCuGXbKKlnQvSeRaJUV+jB9Y0qx6VrHkiGVRaU5fRcvWlyxXTv37M174wLU7bryL20QWb/NXGSmdawJBV2md7WJqJg8vxZpbRmPy0seBCy9EXvXXeLvnAEy5bj7OnXKBpf1qlr9k1uwBEmu/6s6VCG6tcmr743EDlsQKuhtaKpE5oc6HtvA+EMvx+IElmDw8Mq2722eMxEOqcZE6mdSfmaT0EWfiVrSGDh2KpUuXmr+LcvWnP/0Jp2oV4gkh6aO1+ZJHI9GXn91xifSbm4QPqSKRa624cRTmTRqcUpclt/FH0eR3Goto2frsFAP1HLIos4uZskNN1AG4c8dNJG4w3ppmVXUN8Pu8rhUex5iaUAhYtw4AsO3iH+NXV/8Wl5w31DzOLnlDMmv2AOlZvLq9b9T2R1vYqtZBmTNAdDe0ZNNWF97rdx4yC4rb0VLP45Z+57qxwrcUYmEfNHNFWjYcM5m4Fa17770X06dPx9SpU9HQ0IDf/e53OOecc/Dkk09izpw5qZCREJIAmeZWkC0P3UT6zU3Ch1QRr+LglnjHy67NdueIp6/cxh9Fy+SnnyPWokxHEnUUN8UzuXFPTBVqopuKmgA6Fea5LvTr2M9eL/DUU8CiRei76Amsnm49n26x1c+TLfe1jrRjSGnHqPKrc8utu9zk4aW4fVw/ANHd0KKRSL9mkrWlJYn1vG2pBEHJeuc2955Kx7tfNmDU2o2ZtgZJF3ErWqeddhrWrFmD6upq9O7dGytWrMDRRx+Nt956C0OGDEmFjISQBMi03c1seegm0m/6AqclFzzxKg5ukfFyWwTXrs12Y64v3KP1ldNYxBMf4laxi+VKJgWgU1EU2C3NSXRj6ZdnngFuvBFAU7v/tAkLj/l2zOvOX7U9on/TeV9HGzP5m1PSF2nH+p2HXLudxoMbN7RoZMvzMl6S4SqsE+t5m8rncSqSjTR37NOxGTJ1dG+zuHs6NhwzmYTqaJ100kn4y1/+gg8++ABbt27FwoULcdJJJyVbNkJIM8i03c1seehmWr/FIlX9KucF3BfBdSub3ULCLukAEL32mN2xOjKeAKKe0232SCCyP+JdyCS68Gl2opuGBuDWW4GJE4GHHgKWLHG1qGvJDHPxoMbPqX2pZqGLlfQlmtupG1K1iM2W52W8JNLHmaR02sWiFvt9qKozasomu9RAIqRjM2Ty8Mji7tn2Lk0VcStau3btivqPEELs4EM3NSSjX6Um0fVPb4g4r1oE145EUn3bLSRkMXDn4g9w5+IP4loYuInzsktkocruNnukXX8kmmAj3oVPs8b6q6+Ac88F7r/f+P1XvwLGjUv6oi7ZRJtfavyc2pdqFrpYSV+iuZ26IVWL2Gx8XrpROhPp40xSOu1iUcXanegc0Pst2WOfSf3XFolb0erVqxfKysoc/xFCSKrJ1riQTCVaTaJYL/1EFpq6lUkUHa8HCMH45wFQVdfgaozdxHkBke520VziYsmufi/ehUyLL3w2bABOOQX4z3+Adu2Af/wDuP9+LHx3j6u0+LHGOFomyVTGm0j8nFMx4ZkXDHBM+mInVyIL3ETHMtnPsEx4JrrZ8ADit/okkiwmGX3hJsbU6bN4SJWy3pw+J8kjbkVrw4YNeO+998x/b7/9Nh577DH06dMH//znP1MhIyGEWMgkV5LWgNQk6l9SFHfqddV1Jt6Fjer6BcBMOlHs96HI77PdJY53gWznbmeX6rw5i7NUZxlsFosWAaedBnz+OdC7N7B2reE6iMQy79kRLZNksuNNdOz60k3/JusZkuhYJvsZlgnPxEQS26SCZF1LPU80pSWeOeBWeVO/m0hxeSf5uTnZ8sStaJ188smWf6eccgp+8pOfYO7cuZg3b14qZCSEEAt0hUjuDva8SYMx84IB2FJeGXea+liuM9EWC7rrl+rnb+eip8beqOnb9bTC6nXlOrLYUNulpjp3Y7VRr5MJCxdXMnToANTVGW6D77wDKPHUbu+jWAvJaAlHMtU1Md3PkGReX9L9J7O2WSIkktgmFTT3WmMeXB3hTpwK5U2IVQojkeLyQPPjD0lyyE3Wifr06YN33nknWacjhBBHJIVyW0Z3e3PDond2o33Tz8mnHRtxPolrkZTXkjI+2oIl1iJP5NxXWWNRqABYgrXtMgvaLTxERjV9e0VNwPy/UwC42ldDSjtiX2WNJSW+LEaiWW3U6+jnbC6SHjqWG58uk60MoRAWvr2r6Xz9MPm114CRI41U7grSx6KwxXNtu/NE+z1TUPtZ3FejfSdVsifzGSZzs0exP6P6WqUln9nNvVZ5pXFP2WVRba6iGOs5Y/fdIaUdsX7nobivrfdDMuQn8RO3Revw4cOWf5WVlfjwww9x55134vjjj0+FjISQNkwmWA4ykUR2baV4ql0RVTWuRVJeRxS3tUEWeU4FbOW8TkkJ7HZznaxUqoxq+vZivw9+n9fivhjNqmKXEt+N1UZNX5zsHXqnTIxjHlzteIytDOvWAYMH44XnXg+f74wzIpSsWNdOF6mOXXLT1kzqDzek2zqX7cgcWfTObgBASVF8JSXiIZ7zyHeTUVw+G5OrtBbitmgVFxfD4/FYPguFQujZsyf+8Y9/JE0wQkh2kapd4EQsN22BRHZtp4wsA/a/b1tENdHdz1g7tPHIKXOoqq7B1kpldy75bMR9r1rmSTSrSiyZ1bm8bsdBLN1cjvEDS7BxxpiIa+vfT3SO2sk0f9V2HDhS4yhbRH8sWABcey1QX4+5nf+BS8+5KSlj2JIk+37Xz+emrZnUH26ghb95yBxZ8MYO3HACsOLGUfD5fAmfryUsopl8fWIlbovWa6+9hldffdX8t2rVKmzduhXbt2/HqaeemgoZCSFZQKp2gVvTbm26rXN6EVUneRLZdU3mohhARPFLHbt6Nm7nSTyZFKNlZLT7fqI4ZTMsKfLHvlZ9PT7+3mTgqquA+npgwgSUPv+UraVQH291UQYg7dbjWIkBEq09JudT+zkZ85+khpZ8VsockQ2oRe/sblbWzHRbRNUkQ4km0iDJI25F64wzzrD8O/3003HiiSciNzdp4V6EkCwkVQpRIouelnpJx3uddL+AdTJNHjVDoF78UkeXPZmLY3UuS0bG8QNLXH0/mUweXooVN46Kfq3ycuDMM9Hn+b8jCA/+eM6PgWefNZJgNBGtlph8Nnf5RxkxH2IlBlCToLi596LNi0xob1sl1vi15NjIHJENqAVv7GhW1sxEM7Em672lJhlKNJFGskn3JmM6caUdLVmyxPUJzz///ISFIYRkL5nkvtJS7obxXidRl6RUuYJkmouU2zmU6ixrqhyTh5di3qTBrr+faizX+vBD4MwzgX37UP+N9rj9otsw6JpLgRzrHqrM02K/L6pCmGnzQUWXLRn3eEu0d9E7uzF/9eeWhAaZ8pxMNvE8p2KNXzrn4pSRZZi/+nPLXItHDj2LabzJbaTcRaLzRE0IlGgijWTTlkMAXClaEyZMcHUyj8eDxsbG5shDMgj6+ZJspaVe0m6v4ybTWTRS9ZLKJOU4HrIhy1qs52dSnq+9egE9ewJHHYW855/H3OOOs/2aOk/1a9089gTnmK8MwOneScY93hLtNawjtbZZN1sb8TynkhnbmWwmDu1pycrqJEe0eziR+Tl1dG/MeOGDpMyTZPVfstaBmbyJk2pcuQ4Gg0FX/6hktS7oVkGylZaKsXB7nebeS81xTWuNLhvZELcXa8wTnhO1tUDTu3bhxi9w3jm34B+/WwQ4KFlA9HmqJojIxDni1E/ZEkc1ZWRZ1KybrYlkxkmmE6mjFYto7qyJtG/y8FLMvGBAQvMkVc/5ZK0DM3m8U03cMVrp5tFHH0VZWRkKCgowZMgQvP76666OW7NmDXJzczFo0KDUCtiKyIbFDCFuSafC0dx7qTkvqWS9KDMp7s1NQoNkXKc5xBpz9e/RZJGU04ve2Q3s3g2MGgXMmAHAGNv3G/14eN2+ZsmquixlmrKV7e+hiUN7Ji1Fd6bTWhbTUkcrFvrcTFVSHDekIxlVa9zESwUJKVpVVVVYtmwZHnvsMcybN8/yL5UsWrQIN9xwA6ZPn44NGzbg9NNPx7nnnotdu3ZFPa6yshJXXHEFvvOd76RUvtZGa3loEgKk10KbqnvJzYsuWQvVluq/eK+TqFzJbo8+FrHGXP17NFmk5tm7f10MDBkCvPMO8Ic/AF99lbSxVYPnM82DIZ57hwu/tkWqxtuujpYd+txM56ZAOpJR0evJHXErWhs2bMBxxx2HSZMm4ec//zlmz56NG264AbfffjseeuihFIgY5oEHHsCUKVNw1VVXoW/fvnjooYfQs2dPzJ8/P+pxV199NS699FKmnyekDZPtO+N2uHnRuV2oxlq0tFT/xXudROVKdhrx5iw6orVhyoheOPbFF/HA47cA+/cDgwYZylbnzklT4JvjspRJcOHXtkjVeK+4cVRC91Q6N6fTce3W+E5NBXHnZL/xxhtx3nnnYf78+SguLsbatWvh8/kwefJk/OIXv0iFjACA+vp6rF+/HtOmTbN8PmbMGLz55puOx/35z3/G9u3bsXDhQsyePTvmderq6lBXV2f+fvjwYQBAIBBAIBBIUHoSC+lb9nH2kK4xW/TObix4YwemjCwz0/G6YeKQEkwcYqToTtc8S0T2aMdMHdWr6W+9XLUp2pgtWP0pDhypwYLVn5r9pJLM/rvlX5uxfMtejO3fHfd/f2CzruP2+3o/Oh0Xqx+ckLEY1LMIZ97/Slxj7NiG6mpc8vB05C5aBAAIXnopGh99FGjXDkjyHG7p+yPR+zga8d4PqZSF77ToJKPPEx1vJzhm8ZEJ79R0jVk81/OEQqFQPCcvLi7G22+/jRNOOAHFxcV466230LdvX7z99tv44Q9/iA8//DBugd1QXl6OHj16YM2aNTjttNPMz++55x785S9/wUcffRRxzCeffIKRI0fi9ddfR58+fXDXXXdh8eLF2Lhxo+N17rrrLsycOTPi86eeegrt2rVLSlsIIYSQqASDGHn77ej84YcI5uRgy5VX4rPx4wGPJ92SEUJIm6a6uhqXXnopKisr0UGpWWhH3BYtn88HT9OD/uijj8auXbvQt29fFBUVxYyVSgYe7SUTCoUiPgOAxsZGXHrppZg5cyb69Onj+vy33XYbbrrpJvP3w4cPo2fPnhgzZkzMziSJEwgEsHLlSpxzzjnw+XzpFoe4IF1jlord55ZCZK+ua0BFbQAlRf6IgrROxySjvZlyn0WzaKWKlpo3ybyOp6ICoVtvxZu/+AW+deONOLEVPRsz6T5OlUXL7l7LpHYnQrLkz8R+SPT5OObB1SivrHH1PLcjE/siW0jXO0283dwQt6I1ePBgvPvuu+jTpw/OPPNM/PrXv8aBAwfwt7/9DSeddFK8p3PNUUcdBa/Xi337rNmVvvzySxx99NER3z9y5AjeffddbNiwAT//+c8BGGnqQ6EQcnNzsWLFCpx1VmQ9m/z8fOTn50d87vP5qAC0AOzn7KOlx2zyacdaapxkEyK71CaZMqp3zL5LRXtTOWZu6q48OGlISq4d7fotNW+adZ1QCCgvB3r0MH7/8Y8ROO88fLVmTat7NiZ7PJpT78dJlmTUENLHbf7qz7GnohbzV3+elc8xt/LH6rtMfo7rYxarLVNGHef6eW5Hts+JTKCln4/xXCvuZBj33HMPunfvDgCYNWsWOnfujKlTp+LLL7/EH//4x3hP55q8vDwMGTIEK1eutHy+cuVKiyuh0KFDB7z//vvYuHGj+e+aa67BCSecgI0bN+Lb3/52ymQlhJBotOaMnulOSJDO6zcrC9rXXwMTJwLf/jbwxRfhz4uKkidgKyYV456Kc7ZEAoFUZl90K38y+y5Z7UlVopvmPM8Xrt2JqroGFPt9TCrRSolb0TrllFNw5plnAgC6dOmCZcuW4fDhw3jvvfdw8sknJ11AlZtuugmPP/44nnjiCWzbtg033ngjdu3ahWuuuQaA4fZ3xRVXAABycnIwYMAAy7+uXbuioKAAAwYMQGFhYUplJYSQtki6M1Gl8/oJLy4//RQYPhz45z+BL78E1q51fShTmhukYtxTcc6W2GRJ5WaDW/mT2XfJak+i50nlM2X+qu2oqAmgMD+3VW68kQRcB2fOnInJkyejd++Wf4lNnDgRX331Fe6++27s3bsXAwYMwLJly1BaakzOvXv3tkicGCGkbZAM16G2xuThpWntq3Ref+ro3uZ8cc3SpcBllwGVlUC3bsCzzwI2XhpOqIvHtjxHUzHu6Z7LieJmHqb62ZbMvrNrjyo/AFdtSej+hLu2JNqficpEsoe4sw4OHDgQW7ZswdChQzF58mRMnDgRXbp0SZV8aefw4cMoKipylVmEJE4gEMCyZcswbty4VhWH0JppC2M24r5XsaeiBj2K/VgzLTKmM9toC2OWNQSDwJw5wIwZRmzWaacB//oX0OSaL8QaM24GZCapvteaO+7Z/mxT5QeQlLY0Z8yyvT+zlXS90+LRDeJ2Hdy8eTM2b96Ms846Cw888AB69OiBcePG4amnnkJ1dXXCQhNCSKaRbjc4kl7ELe/6pzfEdM9TXfhcufPNnQv8+teGknXNNcBrr0UoWW6u1Zrj/YgzzXWny/Znmyp/JrQlE2QgmUncihYA9O/fH/fccw8+++wzvPbaaygrK8MNN9yAbt26JVs+QghJG1zEZgepCpaXxezSzeUxF7XqwtfVIvjqq4GBA4EFC4D584G8PNdy2p2fsVpti+Yu7DP52eZmLqvyJ7stYx5cHfd9lMn9SdJLQoqWSmFhIfx+P/Ly8lhNmxBCSIuTqmB5WcyOH1gSc1Hraof9nXcMCxZgZBNcvx648sq45bQ7f7qzPTpBBTA1tOaFfbrncnll6jcxeF+0HRJStHbs2IE5c+agX79+OOWUU/Dee+/hrrvuiqhxRQghmUyqXnaZ8hLNFDniIRGZk+W2o59HFrPzJg2OuaiNusPe2AjccQcwbBgwb174oNy481FFXMtJ9kwh3Ytmkn2key6XFKV+E4P3Rdsh7qf8qaeeinXr1uGkk07Cj3/8Y1x66aXoIcUVCSFEIdMD9VOVsS1TMsFlihzxkIjMycpwlpIsc4cOGVkFX3rJ+H337uSev4lMzZCXjVnVMv251dpJ91xeceMoS2KFVMzhbLwvSGLEbdE688wzsXnzZmzcuBG/+tWvqGQRQhzJ9F27VO2cpntHNtPkiIdslNmR998Hhg41lCy/H/jb34wkGEkmky2X2ejilunPLdKypGIOx3POTL6/SWzitmjdc889qZCDENIKyfRdu1TtnKZ7RzbT5IiHTJK5WZaNZ54BfvxjoLoa6NULeP55YNCgVIiZlZbLTCbTn1ukbcH7O7tpdjIMQghxIht3s9MBdyzTj90YJGzZ2LEDwUsvA6qrsXfoSODdd1OmZAGtzAqYAfC5RTIJ3t/ZDRUtQpoJF8nZQ6aOFV2V0o/dGCS8wCkrw8Pf/Ske+/ZFmHjBr4HOneM6PN552poVg0y9ZwlpKVrz/d0WoKJFSDPhIjl7yNSx4o5l+rEbg7gWOBs2AB9+aP7a+Y5b8LcJ1+Kn3+kTtyyZOk/TAfuCEJLNUNEipJlwkZw9ZOpYteUdy0yxWDRrDP72N+C004ALLwQOH272+VI1TzOlr+MhU+9ZQlob2fh8yAZcJcPYvHmz6xMOHDgwYWEIyUYyKXifRIdjlXmIxWLGCx8AQHaNTyAA3HxzuDbWsccCwWCzT6vO00Ag0OzzCbGC6jMxrTnvWUJaBibdSA2uLFqDBg3C4MGDzZ/R/hFCCEkv2bQzOXV0b3g9QGMI2eUe9sUXwNlnh5WsO+8EXnwRKC5Oq1jRiGUdSrWbXjbNS0LaGlNH90ax34equgbeo0nElaK1Y8cOfPbZZ9ixYweeffZZlJWV4dFHH8WGDRuwYcMGPProo+jduzeeffbZVMtLCCEkBtkU1zJ5eClmXjAgu9zD1q0DhgwBVq8G2rc3UrfffTeQk9ne+LHcGVPtppdN85KQtsbk4aUozM9FRU2A92gSceU6WFoafij/4Ac/wLx58zBu3Djzs4EDB6Jnz5648847MWHChKQLSQghxD3ZVgco2e5hKXeBu+MOYM8e4IQTgMWLgRNPTP410kCq3fSybV4S0tbgPZp84i5Y/P7776OsrCzi87KyMmzdujUpQhFCCEmcth7XkvJYg7/9zXAVnDsX6NAh+edvpbT1eUlIpsN7NPnE7efQt29fzJ49G7W1teZndXV1mD17Nvr27ZtU4QghhJB4SboLXHk58Mgj4d+PPhr44x9tlSzGIRFCCBHitmg99thjOO+889CzZ0+cfPLJAIBNmzbB4/Hg3//+d9IFJIQQQuIhqbuya9YA3/8+sG8f0KkTMGlS1K9ne+auTMw8SAgh2UrcFq1hw4Zhx44dmDNnDgYOHIiTTjoJ99xzD3bs2IFhw4alQkZCSJrhLj1pc4RCwPz5wOjRhpLVvz9wyikxD8v2uk9MWEFaCr5XSFsgbosWALRr1w4//elPky0LISRDyfZdekLiorYWuPZa4M9/Nn7/wQ+AJ54AvvGNmIdme4wDg+FJS8H3CmkLJJSL9m9/+xtGjhyJkpIS7Nxp7EQ8+OCDeOGFF5IqHCEkM8jUXXruiJKks3s3cPrphpKVkwP85jfAokWulKzWQKwU8IQki0x9rxCSTOJWtObPn4+bbroJ5557Lg4dOoTGxkYAQMeOHfHQQw8lWz5CSAaQqYsvujmlnjanzK5fD7z7rhGP9fLLwC23AB5PuqUipNWRqe8VQpJJ3IrWww8/jD/96U+YPn06cnPDnoennHIK3n///aQKRwgh0eCOaOppc8rshAlGbNb69cA556RbGgttTuklhJAsJ25Fa8eOHRg8eHDE5/n5+aiqqkqKUIQQ4gbuiKaeVq/MVlcD110H/O9/4c+uuQbo1SttIjnRXKWXihohhLQscStaZWVl2LhxY8TnL730Evr165cMmQghhGQIrVqZ3bEDGDEC+P3vgYkTjUyDGUxzld42Z50khJA0E3fWwV/96lf42c9+htraWoRCIaxbtw5PP/007r33Xjz++OOpkJEQQghJLitXApdcAhw8CHTpAtxzT8bHYjU3oyEzChJCSMsSt6L14x//GA0NDbjllltQXV2NSy+9FD169MDvfvc7XHLJJamQkRBCCEkOoRDw//4fcNttQDAIDB0KPPss0LNnuiVLOdmeep4QQrKNhOpo/eQnP8FPfvITHDhwAMFgEF27dk22XIQQQkhy+fpr4MorgX/+0/j9yiuBRx4BCgrSKxchhJBWSdwxWmeddRYqKioAAEcddZSpZB0+fBhnnXVWUoUjhBBCkobHA3z4IeDzGZkFH3+cShYhhJCUEbdFa9WqVaivr4/4vLa2Fq+//npShCKEEEKSTmEhsHgxsG8fcNpp6ZaGEEJIK8e1orV582bz/1u3bsW+ffvM3xsbG/Hyyy+jR48eyZWOEEIISZRgEJgzx7BgTZtmfHbsscY/QgghJMW4VrQGDRoEj8cDj8dj6yLo9/vx8MMPJ1U4QgghJCEOHwauuAJ44QXDZfC884D+/dMtlS0L1+40swEyWQUhhLQeXCtaO3bsQCgUwrHHHot169ahS5cu5t/y8vLQtWtXeL3elAhJCCGEuObDD4EJE4CPPgLy8ox4rAxVsgBrfSsqWoQQ0npwrWiVlhoP/2AwmDJhCCGEkGaxeLFhyTpyBPjmN43U7cOGpVuqqLC+FSGEtE7izjp477334oknnoj4/IknnsBvfvObpAhFCCGExM3ddwMXXmgoWWecAaxfn/FKFmDUt1oz7Sxas0hSWbh2J0bc9yoWrt2ZblEIabPErWj94Q9/wIknnhjxef/+/fHYY48lRShCCCEkbrp1M37ecAOwciXAGo+kDaO6pBJC0kPcita+ffvQvXv3iM+7dOmCvXv3JkUoQgghxBWNjeH///SnwFtvAQ8+aGQaJKQNM3V0b/Qo9tMllZA0Erei1bNnT6xZsybi8zVr1qCkpCQpQhFCCCExWbQIGDwYOHgw/Nnw4emTh5AMgi6phKSfuAsWX3XVVbjhhhsQCATMNO+vvPIKbrnlFvzyl79MuoCEEEKIhYYG4LbbgLlzjd8fesiIzyKEEEIyiLgVrVtuuQUHDx7Etddei/r6egBAQUEBbr31Vtx2221JF5AQQggxOXAAuOQS4JVXjN9vvRWYMSO9MhFCCCE2xK1oeTwe/OY3v8Gdd96Jbdu2we/34/jjj0d+fn4q5COEEEIM3nsP+N73gJ07gcJC4IkngIsvTrdUhBBCiC1xK1rCN77xDQwdOjSZshBCCHHJwrU7zdpLbSIGY+VK4PzzgdpaoHdvo17WgAHplooQQghxxJWi9b3vfQ9PPvkkOnTogO9973tRv/vcc88lRTBCCCHOqKmb24Si9a1vGenb+/UDFi4EOnZMt0SEEEJIVFwpWkVFRfB4POb/CSGEpNeqNHV0b/ParZbDh4EOHYz/d+4MvPEG0L07kBN3wlxCCCGkxXGlaP35z3+2/T8hhLRl0mlVmjy8tHVbstatM+KxZswAfvIT47MePdIrEyGEEBIH3BYkhJAEYUHQFLFgAXD66cCePcAjjxjp3AkhhJAsw5VFa/DgwabrYCzee++9ZglECCHZQqu3KrU09fXAL34BPPaY8fuECcBf/gLkJpy3iRBCCEkbrt5eEyZMMP9fW1uLRx99FP369cOpp54KAFi7di22bNmCa6+9NiVCEkIIaeWUlwPf/z7w1luAxwPMmmUUJWY8FiGEkCzFlaI1QykGedVVV+H666/HrFmzIr6ze/fu5EpHCCGk9XPkCDBsmOEqWFwM/P3vwLhx6ZaKEEIIaRZxbxX+85//xBVXXBHx+eTJk/Hss88mRShCCCFtiPbtgalTjbpY77xDJYsQQkirIG5Fy+/344033oj4/I033kBBQUFShCKEENLKqa013AWF224D3n4bOO649MlECCGEJJG4I4xvuOEGTJ06FevXr8fw4cMBGDFaTzzxBH79618nXUBCCCGtjN27jdTt9fXAm28ChYVGLFa7dumWjBBCCEkacSta06ZNw7HHHovf/e53eOqppwAAffv2xZNPPomLL7446QISQghpRaxaBVx8MbB/P9CpE/Dxx8DgwemWihBCCEk6CeXMvfjii6lUEUJICli4difmr9qOqaN7t67U8aEQ8LvfATffDDQ2AoMGAc8/D/TqlW7JCCGEkJSQUN7ciooKPP7447j99ttx8OBBAEb9rD179iRVOEIIaWvMX7UdeypqMH/V9nSLkjyqq4HJk4EbbzSUrMmTgTVrqGQRQghp1cStaG3evBl9+vTBb37zG/y///f/UFFRAQB4/vnncdtttyVbPkIIaVNMHd0bPYr9mDq6d7pFSR4//znw1FOA12tYtf76V8ZjEUIIafXErWjddNNN+NGPfoRPPvnEkmXw3HPPxerVq5MqHCGEtDUmDy/FmmlntS63wZkzjdTtr7wCXH+9UZCYEEIIaeXErWi98847uPrqqyM+79GjB/bt25cUoQghJJUsXLsTI+57FQvX7ky3KK2TUAhQN9569gQ2bQLOOCN9MhFCCCEtTNyKVkFBAQ4fPhzx+UcffYQuXbokRShCCEklrTIOKlP4+mtg4kRDqXruufDnOQmFBBNCCCFZS9xvvgsuuAB33303AoEAAMDj8WDXrl2YNm0aLrrooqQLSAghyaZVxkFlAp98AgwfDvzzn4DPBxw6lG6JCCGEkLQRd3r3uXPnYty4cejatStqampwxhlnYN++fTj11FMxZ86cVMhICCFJZfLw0tYVA5UJLF0KXHYZUFkJdO8OPPsscOqp6ZaKEEIISRtxK1odOnTAG2+8gVdffRXvvfcegsEgvvWtb+Hss89OhXyEEEIymWAQmD0buOsuIzbrtNOAf/3LULYIIYSQNkxcilZDQwMKCgqwceNGnHXWWTjrrLNSJRchhJBsYNUqYMYM4//XXgs8+CCQl5dWkQghhJBMIK4YrdzcXJSWlqKxsTFV8hBCsoxF7+xmBr+2zFlnAbfeCjzxBPDII1SyCCGEkCbiToZxxx134LbbbsPBgwdTIQ8hJMtY8MYOZvBra7z4IvDFF+Hf77sP+PGP0ycPIYQQkoHEHaM1b948fPrppygpKUFpaSkKCwstf3/vvfeSJhwhJPOprmtAsd/HDH5tgcZGw01wzhxg1CjgP/8xsgsSQgghJIK4Fa0LLrgAHo8nFbIQQrKQitoAjmrfjln8WjuHDhlZBV96yfj9W99KrzyEEEJIhhO3onXXXXelQAxCSLZSUuTHlFG0ZrVq3n8fuPBCYPt2wO8HHn8cuPTSdEtFCCGEZDSuY7Sqq6vxs5/9DD169EDXrl1x6aWX4sCBA6mUjRCSBay4cRStWa2ZZ54xihBv3w706gW8+SaVLEIIIcQFrhWtGTNm4Mknn8T48eNxySWXYOXKlZg6dWoqZSOEZCEL1+5kFsLWQn29EZNVXQ2ccw7w7rvAoEHplooQQgjJCly7Dj733HNYsGABLrnkEgDA5MmTMWLECDQ2NsLr9aZMQEJIdjF/1XYzC2EmW7oWrt2J+au2Y+ro3hktZ1rJywOefx74+9+NgsR81hNCCCGucW3R2r17N04//XTz92HDhiE3Nxfl5eUpEYwQkp1MHd0bPYr9GZ+FUFUIicJ77wF//nP49xNPBGbNopJFCCGExIlri1ZjYyPytEKUubm5aGhoSLpQhJDsZfLw0qywEE0d3du0aJEm/vY34Kc/BQIB4LjjAGVzjRBCCCHx4VrRCoVC+NGPfoT8/Hzzs9raWlxzzTWWWlrPPfdcciUkhJAUkC0KYYsQCAA33wzMm2f8Pm4ccNJJ6ZWJEEIIyXJcK1o//OEPIz6bPHlyUoUhhBDSwnzxBXDxxcDq1cbvv/61kQAjx7VnOSGEEEJscK1o/Vn12SeEEJL9rFsHfO97wJ49QPv2huvgBRekWypCCCGkVZB1W5aPPvooysrKUFBQgCFDhuD11193/O5zzz2Hc845B126dEGHDh1w6qmnYvny5S0oLSGEZDBvvmkoWSeeaChdVLIIIYSQpJFVitaiRYtwww03YPr06diwYQNOP/10nHvuudi1a5ft91evXo1zzjkHy5Ytw/r163HmmWfivPPOw4YNG1pYckIIyUB+8QsjLuvttw1lixBCCCFJI6sUrQceeABTpkzBVVddhb59++Khhx5Cz549MX/+fNvvP/TQQ7jlllswdOhQHH/88bjnnntw/PHH48UXX2xhyQkhJAMoL8e3HnoIOHzY+N3jAa67DujQIa1iEUIIIa0R1zFa6aa+vh7r16/HtGnTLJ+PGTMGb775pqtzBINBHDlyBJ06dXL8Tl1dHerq6szfDzctSAKBAAKBQAKSEzdI37KPsweOWXbhWbMGuRMnoueXX6Lh+usRePLJdItEXMD7LDvhuGUfHLPsI11jFs/1skbROnDgABobG3H00UdbPj/66KOxb98+V+f47W9/i6qqKlx88cWO37n33nsxc+bMiM9XrFiBdu3axSc0iZuVK1emWwQSJxyzDCcUQq+XXsJJCxbA09iIw8ccg3Wnn46qZcvSLRmJA95n2QnHLfvgmGUfLT1m1dXVrr+bNYqW4PF4LL+HQqGIz+x4+umncdddd+GFF15A165dHb9322234aabbjJ/P3z4MHr27IkxY8agA91rUkYgEMDKlStxzjnnwOfzpVsc4gKOWRZQWwvvz3+OnL/+FQDQcNFFWP397+Os88/nmGUJvM+yE45b9sExyz7SNWbi7eaGrFG0jjrqKHi93gjr1Zdffhlh5dJZtGgRpkyZgn/+8584++yzo343Pz/fUpRZ8Pl8vPFaAPZz9sExy1D+9z/gwguBd981amLdey9CN9yAxpde4phlIRyz7ITjln1wzLKPlh6zeK6VNckw8vLyMGTIkAjz4MqVK3Haaac5Hvf000/jRz/6EZ566imMHz8+1WISQkhm4PMBe/cCnToBy5cDt9xiJL8ghBBCSIuQNRYtALjppptw+eWX45RTTsGpp56KP/7xj9i1axeuueYaAIbb3549e/DXJjeZp59+GldccQV+97vfYfjw4aY1zO/3o6ioKG3tIISQlBAKhZWpo48GXnwR6NgR6NUrrWIRQgghbZGssWgBwMSJE/HQQw/h7rvvxqBBg7B69WosW7YMpaWlAIC9e/daamr94Q9/QENDA372s5+he/fu5r9f/OIX6WoCISRDWLh2J0bc9yoWrt2ZblGSQ3U1MHkysHBh+LPBg6lkEUIIIWkiqyxaAHDttdfi2muvtf3bk1q64lWrVqVeIEJIVjJ/1XbsqajB/FXbMXl4abrFaR47dhjxWJs2GVas8eMNSxYhhBBC0kZWWbQIISRZTB3dGz2K/Zg6une6RWkeK1YAp5xiKFlduoTdBQkhhBCSVrLOokUIIclg8vDS7LZkhULA/fcDt98OBIPA0KHAs88CPXumWzJCCCGEgIoWIYRkH8EgMGkS8Mwzxu9XXgk88ghQUJBeuQghhBBiQtdBQgjJNnJygOOOM1K4z58PPP44lSxCCCEkw6BFixBCsoVAwFCuAODuu4GJE4GBA9MrEyGEEEJsoUWLEEIynWDQUKxOPx2orTU+83qpZBFCCCEZDBUtQgjJZCorjdTtM2YAb79tJLwghBBCSMZD10FCCMlUtm0DJkwAPv4YyM834rEuuyzdUhFCCCHEBVS0CCEkE3nuOeCHPwS+/hr45jeN34cOTbdUhBBCCHEJXQcJISTTmD8fuOgiQ8k64wxg/XoqWYQQQkiWQUWLEEIyjbFjgY4dgRtuAFauBLp2TbdEhBBCCIkTug4SQkgm8NVXQOfOxv+PPRbYuhXo1i29MhFCCCEkYWjRIoSQdLNoEdCrF/DSS+HPqGQRQgghWQ0VLUIISRcNDcCvfgVccokRj/Xkk+mWiBBCCCFJgooWIYSkgwMHgO9+F5g71/j91luBp55Kr0yEEEIISRqM0SKEkJbmvfeA730P2LkTKCwE/vxn4Ac/SLdUhBBCCEkiVLQIIaQl+fRTYMQIoLYWOO444PnngQED0i0VIYQQQpIMFS1CCGlJjjsOuPxyoLwcWLgQKC5Ot0SEEEIISQFUtAghJNV88QXg8wGdOhm///73QG4ukMMwWUIIIaS1wrc8IYSkknXrgCFDgEmTgMZG47O8PCpZhBBCSCuHb3pCCEkVjz8OnH46sGcPsGsX8OWX6ZaIEEIIIS0EFS1CCEk2dXXA1VcDP/kJUF8PXHgh8PbbQPfu6ZaMEEIIIS0EY7QIISSZlJcDF10ErF0LeDzA7NnAtGl0FSSEEELaGFS0CCEkWYRCRj2stWuNbIJPPQWce266pSKEEEJIGuAWKyGEJAuPB3j0UeDb3wbefZdKFiGEENKGoaJFCCHNobYWWLUq/PvJJwNvvQX07p02kQghhBCSfqhoEUJIouzebWQVHDvWcBcUPJ70yUQIIYSQjICKFiGEJMKqVUZ9rHffBdq3NyxbhBBCCCFNUNEihJB4CIWAhx4Czj4b2L8fGDzYULZGj063ZIQQQgjJIKhoEUKIW6qrgcmTgRtvBBobjf+vWQP06pVuyQghhBCSYVDRIoQQtyxcaKRs93qBefOAv/4V8PvTLRUhhBBCMhDW0SKEELdcdRWwfj1w2WXAqFHploYQQgghGQwtWoQQ4kQoBPzpT0BVlfF7Tg7whz9QySKEEEJITKhoEUKIHV9/DVx8MfDTnxqWrFAo3RIRQgghJIug6yAhhOh88glw4YXAli2AzweceSZrYxFCCCEkLqhoEUKIyr//bWQTrKwEuncH/vUv4LTT0i0VIYQQQrIMug4SQggABIPA3XcD551nKFmnnWYkvqCSRQghhJAEoKJFCCEAcOAA8Mgjxv+vvRZ47TXDokUIIYQQkgB0HSSEEADo2hX45z+BTz8Frrwy3dIQQgghJMuhokUIabs8/7yR5GLCBOP3UaOYup0QQgghSYGug4SQtkdjIzB9OvC97wGXX25YsQghhBBCkggtWoSQtsWhQ8CllwIvv2z8ftVVQGlpemUihBBCSKuDihYhpO2webNRH+uzzwC/H/jTn4DLLku3VIQQQghphVDRIoS0DRYtMpJcVFcDvXoZ8VmDBqVbKkIIIYS0UhijRQhpG6xdayhZ55wDvPsulSxCCCGEpBRatAghbYP77wdOOAH4yU8Arzfd0hBCCCGklUOLFiGkdfLee8DkyUAgYPzu8wHXXEMlixBCCCEtAhUtQkjr469/BUaMAP7+d+Dee9MtDSGEEELaIFS0CCGth0AAuP564Ic/BGprgXHjjN8JIYQQQloYKlqEkNbBF18A3/kO8PDDxu+//jXw4otAcXFaxSKEEEJI24TJMAgh2c/69cAFFwB79gDt2wMLFwLnn59uqQghhBDShqGiRQjJfgoLgcOHgRNPBBYvNrILEkIIIYSkESpahJDsJBQCPB7j/yeeCLz8MjBgANChQ3rlIoQQQggBY7QIIdlIeTlwxhnAqlXhz047jUoWIYQQQjIGKlqEkOzijTeAb30LeP114OqrgcbGdEtECCGEEBIBFS1CSHYQCgGPPAKceaaRYfCkk4Bly1iAmBBCCCEZCRUtQkjmU1MDXHkl8POfAw0NwCWXAG+9BfTunW7JCCGEEEJsYTIMQkhmc/gwcNZZRgr3nBzgN78BfvnLcCIMQgghhJAMhIoWISSzad/eyCr4+efAokVGUWJCCCGEkAyHihYhJPMIhYC6OqCgwLBc/fGPwIEDwDHHpFsyQgghhBBXMEaLEJJZVFcDl11mxGEFg8Zn7dpRySKEEEJIVkGLFiEkc9ixA7jwQmDTJiA3F3j3XWDYsHRLRQghhBASN7RoEUIygxUrgFNOMZSsrl2BV16hkkUIIYSQrIWKFiEkvYRCRibBc88FDh40lKv164FRo9ItGSGEEEJIwlDRIoSkl1/8Apg2zYjHuuoqYPVq4JvfTLdUhBBCCCHNgooWISS9TJ5spHD/wx+AP/0JyM9Pt0SEEEIIIc2GyTAIIS3Pvn1At27G/4cNM2pkdeqUVpEIIYQQQpIJLVqEkJYjGATuvhvo3RvYsCH8OZUsQgghhLQyqGgRQlqGykojdfuMGUatrBdfTLdEhBBCCCEpg66DhJDUs20bMGEC8PHHRgzW/PnAj3+cbqkIIYQQQlIGFS1CSGp57jnghz8Evv4a6NkTePZZYOjQdEtFCCGEEJJSqGgRQlLHypXARRcZ/x89Gli0yChGTAghhBDSyqGiRQhJHWedZRQiPvFE4P77gVw+cgghhBDSNuCqhxCSXLZuBY49FigoALxe4IUXAJ8v3VIRQgghhLQozDpICEke//iHEX/1s58BoZDxGZUsQgghhLRBqGgRQppPQwNw883ApElG6vbdu4G6unRLRQghhBCSNrJO0Xr00UdRVlaGgoICDBkyBK+//nrU7//3v//FkCFDUFBQgGOPPRaPPfZYC0lKSBvhwAFg7Fjgt781fr/1VuCllwzXQUIIIYSQNkpWKVqLFi3CDTfcgOnTp2PDhg04/fTTce6552LXrl2239+xYwfGjRuH008/HRs2bMDtt9+O66+/Hs8++2wLS05I66Ro+3bkDh8OvPoqUFgIPPMMcN99RmwWIYQQQkgbJqsUrQceeABTpkzBVVddhb59++Khhx5Cz549MX/+fNvvP/bYYzjmmGPw0EMPoW/fvrjqqqtw5ZVXYu7cuS0sOSGtkLo6fPuee+DZtQs47jhg7VrgBz9It1SEEEIIIRlB1mQdrK+vx/r16zFt2jTL52PGjMGbb75pe8xbb72FMWPGWD4bO3YsFixYgEAgAJ9NkH5dXR3qlNiSw4cPAwACgQACgUBzm0EckL5lH2cPgZwcbPz5zzHsnXcQevJJoLgY4PhlNLzPsg+OWXbCccs+OGbZR7rGLJ7rZY2ideDAATQ2NuLoo4+2fH700Udj3759tsfs27fP9vsNDQ04cOAAunfvHnHMvffei5kzZ0Z8vmLFCrRr164ZLSBuWLlyZbpFIFHIr6hAYXk5DvbrZ3wweDCWDh4MOGx2kMyE91n2wTHLTjhu2QfHLPto6TGrrq52/d2sUbQEj8dj+T0UCkV8Fuv7dp8Lt912G2666Sbz98OHD6Nnz54YM2YMOnTokKjYJAaBQAArV67EOeecY2tpJOnH8/bb8F57LVBdjYY330SgtJRjlmXwPss+OGbZCcct++CYZR/pGjPxdnND1ihaRx11FLxeb4T16ssvv4ywWgndunWz/X5ubi46d+5se0x+fj7y8/MjPvf5fLzxWgD2c4bypz8BP/85UF8PnHgifF6vWR+LY5Z9cMyyD45ZdsJxyz44ZtlHS49ZPNfKmmQYeXl5GDJkSIR5cOXKlTjttNNsjzn11FMjvr9ixQqccsopvIkIcUNdHXD11cBPf2ooWRdeCLz9NtCnT7olI4QQQgjJaLJG0QKAm266CY8//jieeOIJbNu2DTfeeCN27dqFa665BoDh9nfFFVeY37/mmmuwc+dO3HTTTdi2bRueeOIJLFiwADfffHO6mkBI9rBnDzB6NPDHPwIeDzBnDvCvfwF0oSWEEEIIiUnWuA4CwMSJE/HVV1/h7rvvxt69ezFgwAAsW7YMpaWlAIC9e/daamqVlZVh2bJluPHGG/HII4+gpKQE8+bNw0UXXZSuJhCSPTz0kJGyvbgYeOop4Nxz0y0RIYQQQkjWkFWKFgBce+21uPbaa23/9uSTT0Z8dsYZZ+C9995LsVSEtEJmzwa++gqYPh3o3Tvd0hBCCCGEZBVZ5TpICEkhtbXAAw8AjY3G7/n5wBNPUMkihBBCCEmArLNoEUJSwK5dwEUXAe++C+zfD9x7b7olIoQQQgjJamjRIqSt89prwJAhhpLVuTPwne+kWyJCCCGEkKyHihYhbZVQyHAVPOcc4MABYPBgQ9k6++x0S0YIIYQQkvVQ0SKkLVJdDVx2GfDLXxoxWZdfDqxZA/TqlW7JCCGEEEJaBVS0CGmLfPYZsHgxkJsLzJsH/OUvgN+fbqkIIYQQQloNTIZBSFtkwADgb38DunQBRo1KtzSEEEIIIa0OKlqEtAVCIeD++w2l6tRTjc9YuJsQQgghJGVQ0SKktfP118CPfwz8619A9+7Atm1AUVG6pSKEEEIIadVQ0SKkNfPJJ8CECcDWrYDPB9x1F5UsQgghhJAWgIoWIa2Vf//byCx4+DBQUmJYtMRtkBBCCCGEpBRmHSSktREMAjNnAuedZyhZI0cC69dTySKEEEIIaUGoaBHSGtm0yfj5s58Br7wCdOuWXnkIIYQQQtoYdB0kpLWRk2PUxZo0CfjBD9ItDSGEEEJIm4QWLUJaA88/D/z0p0YadwBo355KFiGEEEJIGqGiRUg209gITJ8OfO97wJ/+BPzjH+mWiBBCCCGEgK6DhGQvhw4Bl14KvPyy8ftNN9GKRQghhBCSIVDRIiQb2bwZuPBC4LPPAL8fePxxQ+kihBBCCCEZARUtQrKN558HJk8GqquBsjLj95NPTrdUhBBCCCFEgTFahGQbnTsD9fXAmDHAu+9SySKEEEIIyUBo0SIkGwgGjbTtADBqFPDf/wLf/jbg9aZXLkIIIYQQYgstWoRkOu+9Z1ittm4Nf3baaVSyCCGEEEIyGCpahGQyf/0rMGIE8MEHwC23pFsaQgghhBDiEipahGQigQBw/fXAD38I1NYC//d/wMKF6ZaKEEIIIYS4hIoWIZnGvn3Ad74DPPyw8fuMGcALLwDFxWkVixBCCCGEuIfJMAjJJLZvN5JdlJcDHToAf/sbcP756ZaKEEIIIYTECRUtQjKJ0lKgTx9DyVq8GDjhhHRLRAghhBBCEoCKFiHppq7OSN3u8wG5ucA//wnk5RnKFiGEEEIIyUoYo0VIOtmzBxg9GrjppvBnRx1FJYsQQgghJMuhokVIunjjDWDIEGDtWiOj4N696ZaIEEIIIYQkCSpahLQ0oRDwyCPAmWcCX3wBnHQS8O67QPfu6ZaMEEIIIYQkCSpahLQkNTXAlVcCP/850NAAXHIJ8NZbQO/e6ZaMEEIIIYQkESbDIKSlCIWMwsOvvmokv/jNb4Bf/hLweNItGSGEEEIISTJUtAhpKTwe4PrrgfffB55+2ihKTAghhBBCWiV0HSQklYRCwK5d4d8vuAD49FMqWYQQQgghrRwqWoSkiqoq4NJLjcyCqrLF1O2EEEIIIa0eug4Skgo++wy48EJg82ajCPHatcAxx6RbKkIIIYQQ0kLQokVIslm+HDjlFEPJ6toVeOUV4OKL0y0VIYQQQghpQahoEZIsQiHg3nuBc88FDh0Chg0D1q8HRo1Kt2SEEEIIIaSFoaJFSLJ45BHg9tsNhesnPwFWrwa++c10S0UIIYQQQtIAFS1CksWVVxpWrD/8AfjjH4H8/HRLRAghhBBC0gSTYRDSHNauNZSrnBygXTvgzTcBrzfdUhFCCCGEkDRDixYhiRAMAjNnAqeeCsyZE/6cShYhhBBCCAEtWoTET2UlcPnlwIsvGr/v32/EZXk86ZWLEEIIIYRkDFS0CImHrVuN+lgff2zEYD32GPCjH6VbKkIIIYQQkmFQ0SLELc8+ayhVX38N9OwJPPecUS+LEEIIIYQQDcZoEeKG8nLgsssMJevMM436WFSyCCGEEEKIA7RoEeKGkhLg0UeBLVuA3/wGyOWtQwghhBBCnOFqkRAnNm0yklwMGmT8fuWVaRWHEEIIIYRkD3QdJMSOf/zDSN0+YQJw4EC6pSGEEEIIIVkGFS1CVBoagJtvBiZNAmpqgBNOMIoRE0IIIYQQEgdcQRIiHDgAjB0L/Pa3xu+33QYsWwZ06pReuQghhBBCSNbBGC1CAOC994z6WLt2AYWFwF/+Alx0UbqlIoQQQgghWQoVLUIAYPZsQ8k6/nhg8WKgX790S0QIIYQQQrIYKlqEAMCCBUC3bsC99wJFRemWhhBCCCGEZDmM0SJtky++MGKxQiHj944djTpZVLIIIYQQQkgSoEWLtD3WrjXir8rLgfbtgZ/+NN0SEUIIIYSQVgYtWqRt8ac/AWecYShZffsCo0enWyJCCCGEENIKoaJF2gZ1dcDVVxvWq/p64HvfA95+G+jTJ92SEUIIIYSQVghdB0nrZ88e4PvfN1wGPR5gzhxg2jTj/4QQQgghhKQAKlqk9bNtG7BuHVBcDDz9NPDd76ZbIkIIIYQQ0sqhokVaP2efbaRvP/10oHfvdEtDCCGEEELaAIzRIq2Pmhrg5z8HPv00/NmPfkQlixBCCCGEtBi0aJHWxa5dRqKL9euBN94wfnq96ZaKEEIIIYS0MWjRIq2H114DhgwxlKvOnY2CxFSyCCGEEEJIGqCiRbKfUAh48EHgnHOAAweAwYMNZes730m3ZIQQQgghpI1CRYtkN9XVwGWXATfdBDQ2ApdfDqxZA5SWplsyQgghhBDShqGiRbIbrxfYsQPIzQXmzQP+8hfA70+3VIQQQgghpI3DZBgku8nPB559Fti+3UjfTgghhBBCSAZARYtkF6EQcN99wJEjwD33GJ+VlBj/CCGEEEIIyRCoaJHs4cgRox7Wc88Zv194ITB0aFpFIoQQQgghxA4qWiQ7+OgjQ7Hatg3w+YDf/55KFiGEEEIIyVioaJHM58UXgcmTgcOHge7djZisU09Nt1SEEEIIIYQ4wqyDJLO57z7g/PMNJWvkSOC996hkEUIIIYSQjIeKFslsevUyfv7sZ8ArrwDduqVVHEIIIYQQQtxA10GSeTQ0GHWxAOCSS4DevRmPRQghhBBCsoqssWgdOnQIl19+OYqKilBUVITLL78cFRUVjt8PBAK49dZbcdJJJ6GwsBAlJSW44oorUF5e3nJCk7jxPPcc0L8/sHdv+EMqWYQQQgghJMvIGkXr0ksvxcaNG/Hyyy/j5ZdfxsaNG3H55Zc7fr+6uhr/v717j6qqzvs4/jlcREI5Sl5SMUkTtURMvKGr0TFEMnWKzAh01BrLmbGophobLbWx66Q19WjT4wKbCh1Hwx5XVoppiiEQCmMrTF1eMlNMChDvXH7PH2ckEVCgA5vjeb/WOmu1f2efs7+b7zq5P/z2+bFjxw4988wz2rFjh5KTk7Vnzx6NGzeuEatGrZWVqdd778krJkbas0dasMDqigAAAIB6c4lbB3ft2qVPP/1U6enpGjRokCRpyZIlCg8P1+7du9WjR48qr7Hb7UpJSak09uabb2rgwIE6dOiQrr/++mqPde7cOZ07d65i+8SJE5IcM2QlJSXOOiVc7Kef5DFxooI3bJAklT36qMr/+leJn3eTduHzwOfCddAz10PPXBN9cz30zPVY1bO6HM9mjDENWItTJCYm6vHHH69yq2CrVq302muvaerUqbV6nw0bNigyMlKFhYXy9/evdp+5c+dq3rx5VcaXLVuma665ps614/L8DxzQwJdekt+xYypt1kw5M2bo+1/9yuqyAAAAgCpOnz6t2NhYFRUV1ZgnLnCJGa28vDy1a9euyni7du2Ul5dXq/c4e/asZs6cqdjY2Mv+UJ5++mk9/vjjFdsnTpxQ586dFRkZecUfJurGlpoqz7/8RbYzZ1QeFKTU+HgNevBBhXp7W10aaqGkpEQpKSkaOXKkvOmZS6BnroeeuSb65nromeuxqmcX7narDUuDVk2zRxf78ssvJUk2m63Kc8aYascvVVJSopiYGJWXl2vx4sWX3dfHx0c+Pj5Vxr29vfngOduAAY7l2zt3Vtm77+pEejo/ZxdEz1wPPXM99Mw10TfXQ89cT2P3rC7HsjRozZgxQzExMZfdJygoSDt37tSxY8eqPHf8+HG1b9/+sq8vKSnRhAkTdODAAW3cuJFZKasVFkp2u2SzSS1bShs3Sm3bSuXlVlcGAAAAOI2lQatNmzZq06bNFfcLDw9XUVGRMjMzNXDgQElSRkaGioqKNGTIkBpfdyFk7d27V5s2bdK1117rtNpRD9u3S3fdJcXHS3/6k2Pswh8gJmgBAADgKuISy7v36tVLUVFRmjZtmtLT05Wenq5p06ZpzJgxlVYc7Nmzp1avXi1JKi0t1fjx45WVlaWkpCSVlZUpLy9PeXl5On/+vFWn4r7eeUcaOlT67jspIUG6aGVHAAAA4GrjEkFLkpKSkhQSEqLIyEhFRkaqT58+eu+99yrts3v3bhUVFUmSDh8+rDVr1ujw4cPq27evOnToUPFIS0uz4hTc0/nz0owZ0tSpjnA1ZoyUliZV8z04AAAA4GrhEqsOSlJAQIDef//9y+5z8Ur1QUFBcoGV669ueXnSPfdIW7c6tufMkZ59VvJwmXwPAAAA1IvLBC24mDNnpMGDpW+/lfz9pfffl8aOtboqAAAAoFEwtYCG4evrWPCiVy/pyy8JWQAAAHArBC04z7lz0qFDP2/PmOFYaTA42LqaAAAAAAsQtOAc338vDRsmRURI/12QRDabY2YLAAAAcDMELfxyqalSWJiUkSHl50u7d1tdEQAAAGApghbqzxjpf/5HGjFCOnZM6tNHysqS/vtHpQEAAAB3RdBC/Zw54/jbWA8/LJWWSjExjr+P1bWr1ZUBAAAAliNooX6eekr65z8dfxPr1VelZcskPz+rqwIAAACaBIIW6ueZZ6R+/aSUFMcy7jab1RUBAAAATQZBC7VjjLRx48/b7do5vo81YoR1NQEAAABNFEELV3bqlBQbK912m/Tuuz+PM4sFAAAAVMvL6gLQxO3fL911l7Rzp+TlJZ0+bXVFAAAAQJNH0ELN1q2T7rtPKiiQ2reXVq6Ubr3V6qoAAACAJo9bB1GVMdKLL0q33+4IWYMGSdu3E7IAAACAWiJooaqMDOkvf3EErmnTpM2bpU6drK4KAAAAcBncOoiqBg+W/vpXx8qCDz5odTUAAACAyyFowWHtWikkRLr+esf27NnW1gMAAAC4MG4ddHfl5dK8edKYMVJ0tHT2rNUVAQAAAC6PGS13VlQkTZwoffSRYzs8XPIgewMAAAC/FEHLXeXmSnfeKe3dK/n4SG+/LU2ebHVVAAAAwFWBoOWOVq2SpkyRTp1yfCcrOVkKC7O6KgAAAOCqwX1i7qasTHrhBUfI+vWvpawsQhYAAADgZAQtd+Pp6ZjBmjVLWr9eatvW6ooAAACAqw5Byx3s3CktXvzzdlCQNH++5MWdowAAAEBD4Er7ard8ufTAA45l27t1k0aNsroiAAAA4KrHjNbVqrRU+tOfpNhY6cwZaeRIacAAq6sCAAAA3AJB62p0/LgUGSktXOjYfvpp6eOPpYAAa+sCAAAA3AS3Dl5ttm+X7rpL+u47yc9P+uc/pbvvtroqAAAAwK0QtK42O3c6Qlb37tLq1dLNN1tdEQAAAOB2CFpXm6lTpZISacIEqVUrq6sBAAAA3BLf0XJ1eXmOBS/y838ee/BBQhYAAABgIWa0XFl6uuP7V0eOOJZvT062uiIAAAAAYkbLdf3v/0q/+pUjZPXqJb30ktUVAQAAAPgvgparOXdOmjZNeughx3exoqOljAwpONjqygAAAAD8F7cOupKjRx1Lt2dkSDab9Pzz0syZjv8GAAAA0GQQtFxJ8+aORS9at5aWLZOioqyuCAAAAEA1CFqupHVr6f/+zxG4unWzuhoAAAAANSBouRr+ADEAAADQ5LEYBgAAAAA4GUELAAAAAJyMoAUAAAAATkbQAgAAAAAnI2gBAAAAgJMRtAAAAADAyQhaAAAAAOBkBC0AAAAAcDKCFgAAAAA4GUELAAAAAJyMoAUAAAAATkbQAgAAAAAnI2gBAAAAgJMRtAAAAADAyQhaAAAAAOBkBC0AAAAAcDKCFgAAAAA4GUELAAAAAJyMoAUAAAAATkbQAgAAAAAnI2gBAAAAgJMRtAAAAADAyQhaAAAAAOBkBC0AAAAAcDKCFgAAAAA4mZfVBTR1xhhJ0okTJyyu5OpWUlKi06dP68SJE/L29ra6HNQCPXM99Mz10DPXRN9cDz1zPVb17EImuJARLoegdQXFxcWSpM6dO1tcCQAAAICmoLi4WHa7/bL72Ext4pgbKy8v15EjR9SyZUvZbDary7lqnThxQp07d9Z3330nf39/q8tBLdAz10PPXA89c030zfXQM9djVc+MMSouLlbHjh3l4XH5b2Exo3UFHh4eCgwMtLoMt+Hv78//4FwMPXM99Mz10DPXRN9cDz1zPVb07EozWRewGAYAAAAAOBlBCwAAAACcjKCFJsHHx0dz5syRj4+P1aWgluiZ66FnroeeuSb65nrometxhZ6xGAYAAAAAOBkzWgAAAADgZAQtAAAAAHAyghYAAAAAOBlBCwAAAACcjKAFSxQUFGjSpEmy2+2y2+2aNGmSCgsLa9y/pKREf/7znxUSEiI/Pz917NhRv/3tb3XkyJHGK9oNLV68WDfccIOaN2+usLAwpaamXnb/zZs3KywsTM2bN1fXrl31j3/8o5EqxQV16VlycrJGjhyptm3byt/fX+Hh4Vq3bl0jVgup7p+zC7744gt5eXmpb9++DVsgqlXXvp07d06zZs1Sly5d5OPjo27duikxMbGRqoVU954lJSUpNDRU11xzjTp06KCpU6fqxx9/bKRqsWXLFo0dO1YdO3aUzWbThx9+eMXXNLnrEANYICoqyvTu3dukpaWZtLQ007t3bzNmzJga9y8sLDQRERFmxYoV5ptvvjHbtm0zgwYNMmFhYY1YtXv517/+Zby9vc2SJUtMbm6uiY+PN35+fubbb7+tdv/9+/eba665xsTHx5vc3FyzZMkS4+3tbVatWtXIlbuvuvYsPj7evPzyyyYzM9Ps2bPHPP3008bb29vs2LGjkSt3X3Xt2QWFhYWma9euJjIy0oSGhjZOsahQn76NGzfODBo0yKSkpJgDBw6YjIwM88UXXzRi1e6trj1LTU01Hh4e5u9//7vZv3+/SU1NNTfffLO58847G7ly9/Xxxx+bWbNmmQ8++MBIMqtXr77s/k3xOoSghUaXm5trJJn09PSKsW3bthlJ5ptvvqn1+2RmZhpJV7wgQf0MHDjQTJ8+vdJYz549zcyZM6vd/6mnnjI9e/asNPbQQw+ZwYMHN1iNqKyuPavOTTfdZObNm+fs0lCD+vbs3nvvNbNnzzZz5swhaFmgrn375JNPjN1uNz/++GNjlIdq1LVnf/vb30zXrl0rjb3xxhsmMDCwwWpEzWoTtJridQi3DqLRbdu2TXa7XYMGDaoYGzx4sOx2u9LS0mr9PkVFRbLZbGrVqlUDVOnezp8/r+3btysyMrLSeGRkZI092rZtW5X9R40apaysLJWUlDRYrXCoT88uVV5eruLiYgUEBDREibhEfXu2dOlS7du3T3PmzGnoElGN+vRtzZo16t+/v1555RV16tRJwcHBeuKJJ3TmzJnGKNnt1adnQ4YM0eHDh/Xxxx/LGKNjx45p1apVuuOOOxqjZNRDU7wO8bLkqHBreXl5ateuXZXxdu3aKS8vr1bvcfbsWc2cOVOxsbHy9/d3doluLz8/X2VlZWrfvn2l8fbt29fYo7y8vGr3Ly0tVX5+vjp06NBg9aJ+PbvUggULdOrUKU2YMKEhSsQl6tOzvXv3aubMmUpNTZWXF/+EW6E+fdu/f7+2bt2q5s2ba/Xq1crPz9cf/vAH/fTTT3xPqxHUp2dDhgxRUlKS7r33Xp09e1alpaUaN26c3nzzzcYoGfXQFK9DmNGC08ydO1c2m+2yj6ysLEmSzWar8npjTLXjlyopKVFMTIzKy8u1ePFip58HfnZpP67Uo+r2r24cDaeuPbtg+fLlmjt3rlasWFHtL0LQcGrbs7KyMsXGxmrevHkKDg5urPJQg7p81srLy2Wz2ZSUlKSBAwdq9OjRWrhwod555x1mtRpRXXqWm5urRx55RM8++6y2b9+uTz/9VAcOHND06dMbo1TUU1O7DuHXYXCaGTNmKCYm5rL7BAUFaefOnTp27FiV544fP17lNxGXKikp0YQJE3TgwAFt3LiR2awG0qZNG3l6elb5Td8PP/xQY4+uu+66avf38vLStdde22C1wqE+PbtgxYoVeuCBB7Ry5UpFREQ0ZJm4SF17VlxcrKysLGVnZ2vGjBmSHBfwxhh5eXlp/fr1GjFiRKPU7s7q81nr0KGDOnXqJLvdXjHWq1cvGWN0+PBhde/evUFrdnf16dmLL76ooUOH6sknn5Qk9enTR35+frr11ls1f/587tJogpridQgzWnCaNm3aqGfPnpd9NG/eXOHh4SoqKlJmZmbFazMyMlRUVKQhQ4bU+P4XQtbevXu1YcMGLt4bULNmzRQWFqaUlJRK4ykpKTX2KDw8vMr+69evV//+/eXt7d1gtcKhPj2THDNZU6ZM0bJly/juQSOra8/8/f311VdfKScnp+Ixffp09ejRQzk5OZW+94qGU5/P2tChQ3XkyBGdPHmyYmzPnj3y8PBQYGBgg9aL+vXs9OnT8vCofJns6ekp6edZEjQtTfI6xJo1OODuoqKiTJ8+fcy2bdvMtm3bTEhISJXl3Xv06GGSk5ONMcaUlJSYcePGmcDAQJOTk2OOHj1a8Th37pwVp3DVu7AUbkJCgsnNzTWPPvqo8fPzMwcPHjTGGDNz5kwzadKkiv0vLKv62GOPmdzcXJOQkGD5sqrupq49W7ZsmfHy8jKLFi2q9JkqLCy06hTcTl17dilWHbRGXftWXFxsAgMDzfjx483XX39tNm/ebLp3725+97vfWXUKbqeuPVu6dKnx8vIyixcvNvv27TNbt241/fv3NwMHDrTqFNxOcXGxyc7ONtnZ2UaSWbhwocnOzq5YbdoVrkMIWrDEjz/+aOLi4kzLli1Ny5YtTVxcnCkoKKi0jySzdOlSY4wxBw4cMJKqfWzatKnR63cXixYtMl26dDHNmjUz/fr1M5s3b654bvLkyWbYsGGV9v/888/NLbfcYpo1a2aCgoLMW2+91cgVoy49GzZsWLWfqcmTJzd+4W6srp+zixG0rFPXvu3atctEREQYX19fExgYaB5//HFz+vTpRq7avdW1Z2+88Ya56aabjK+vr+nQoYOJi4szhw8fbuSq3demTZsu+2+UK1yH2Ixh/hMAAAAAnInvaAEAAACAkxG0AAAAAMDJCFoAAAAA4GQELQAAAABwMoIWAAAAADgZQQsAAAAAnIygBQAAAABORtACAAAAACcjaAEAcAmbzaYPP/ywQY8RFBSk119/vUGPAQCwDkELAGCZtLQ0eXp6Kioqqs6vJagAAJoyghYAwDKJiYl6+OGHtXXrVh06dMjqcgAAcBqCFgDAEqdOndK///1v/f73v9eYMWP0zjvvVNlnzZo16t+/v5o3b642bdooOjpakjR8+HB9++23euyxx2Sz2WSz2SRJc+fOVd++fSu9x+uvv66goKCK7S+//FIjR45UmzZtZLfbNWzYMO3YsaPWdb/99tvq1KmTysvLK42PGzdOkydPliTt27dPv/nNb9S+fXu1aNFCAwYM0IYNG2p8z4MHD8pmsyknJ6dirLCwUDabTZ9//nnFWG5urkaPHq0WLVqoffv2mjRpkvLz8yueX7VqlUJCQuTr66trr71WEREROnXqVK3PDQDgPAQtAIAlVqxYoR49eqhHjx6aOHGili5dKmNMxfNr165VdHS07rjjDmVnZ+uzzz5T//79JUnJyckKDAzUc889p6NHj+ro0aO1Pm5xcbEmT56s1NRUpaenq3v37ho9erSKi4tr9fp77rlH+fn52rRpU8VYQUGB1q1bp7i4OEnSyZMnNXr0aG3YsEHZ2dkaNWqUxo4d+4tm7Y4ePaphw4apb9++ysrK0qeffqpjx45pwoQJFc/fd999uv/++7Vr1y59/vnnio6OrvQzBQA0Hi+rCwAAuKeEhARNnDhRkhQVFaWTJ0/qs88+U0REhCTp+eefV0xMjObNm1fxmtDQUElSQECAPD091bJlS1133XV1Ou6IESMqbb/99ttq3bq1Nm/erDFjxlzx9QEBAYqKitKyZct02223SZJWrlypgICAiu3Q0NCKWiVp/vz5Wr16tdasWaMZM2bUqd4L3nrrLfXr108vvPBCxVhiYqI6d+6sPXv26OTJkyotLVV0dLS6dOkiSQoJCanXsQAAvxwzWgCARrd7925lZmYqJiZGkuTl5aV7771XiYmJFfvk5ORUBBdn+uGHHzR9+nQFBwfLbrfLbrfr5MmTdZptiouL0wcffKBz585JkpKSkhQTEyNPT09Jjtsin3rqKd10001q1aqVWrRooW+++eYXzWht375dmzZtUosWLSoePXv2lOS4VTE0NFS33XabQkJCdM8992jJkiUqKCio9/EAAL8MM1oAgEaXkJCg0tJSderUqWLMGCNvb28VFBSodevW8vX1rfP7enh4VLlVrqSkpNL2lClTdPz4cb3++uvq0qWLfHx8FB4ervPnz9f6OGPHjlV5ebnWrl2rAQMGKDU1VQsXLqx4/sknn9S6dev06quv6sYbb5Svr6/Gjx9f4zE8PBy/97y49kvrLi8v19ixY/Xyyy9XeX2HDh3k6emplJQUpaWlaf369XrzzTc1a9YsZWRk6IYbbqj1uQEAnIMZLQBAoyotLdW7776rBQsWKCcnp+Lxn//8R126dFFSUpIkqU+fPvrss89qfJ9mzZqprKys0ljbtm2Vl5dXKbBcvMCEJKWmpuqRRx7R6NGjdfPNN8vHx6fSghK14evrq+joaCUlJWn58uUKDg5WWFhYpWNMmTJFd911l0JCQnTdddfp4MGDNb5f27ZtJanSd80urbtfv376+uuvFRQUpBtvvLHSw8/PT5Lj738NHTpU8+bNU3Z2tpo1a6bVq1fX6dwAAM5B0AIANKqPPvpIBQUFeuCBB9S7d+9Kj/HjxyshIUGSNGfOHC1fvlxz5szRrl279NVXX+mVV16peJ+goCBt2bJF33//fUVQGj58uI4fP65XXnlF+/bt06JFi/TJJ59UOv6NN96o9957T7t27VJGRobi4uLqNXsWFxentWvXKjExseK7ZhcfIzk5uSJAxsbGVlml8GK+vr4aPHiwXnrpJeXm5mrLli2aPXt2pX3++Mc/6qefftJ9992nzMxM7d+/X+vXr9f999+vsrIyZWRk6IUXXlBWVpYOHTqk5ORkHT9+XL169arzuQEAfjmCFgCgUSUkJCgiIkJ2u73Kc3fffbdycnK0Y8cODR8+XCtXrtSaNWvUt29fjRgxQhkZGRX7Pvfcczp48KC6detWMSPUq1cvLV68WIsWLVJoaKgyMzP1xBNPVDpGYmKiCgoKdMstt2jSpEl65JFH1K5duzqfx4gRIxQQEKDdu3crNja20nOvvfaaWrdurSFDhmjs2LEaNWqU+vXrd9n3S0xMVElJifr376/4+HjNnz+/0vMdO3bUF198obKyMo0aNUq9e/dWfHy87Ha7PDw85O/vry1btmj06NEKDg7W7NmztWDBAt1+++11PjcAwC9nM6z7CgAAAABOxYwWAAAAADgZQQsAAAAAnIygBQAAAABORtACAAAAACcjaAEAAACAkxG0AAAAAMDJCFoAAAAA4GQELQAAAABwMoIWAAAAADgZQQsAAAAAnIygBQAAAABO9v+PcHIluDPoMwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10, 8))\n",
    "plt.scatter(y_test_rf, y_pred_RF, s = 1)\n",
    "plt.xlabel('Actual CC values')\n",
    "plt.ylabel('Predicted CC values')\n",
    "plt.title('Predicted vs. Actual CC values: Random Forest Regression')\n",
    "plt.grid(True)\n",
    "\n",
    "# Calculate the range to include both actual and predicted values\n",
    "min_val = min(y_test_rf.min(), y_pred_RF.min())\n",
    "max_val = max(y_test_rf.max(), y_pred_RF.max())\n",
    "line_coords = np.linspace(min_val, max_val, 100)\n",
    "\n",
    "plt.plot(line_coords, line_coords, color='red', linestyle='--')  # Perfect prediction\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "68650679-50a7-4695-bac6-5b1ddff22aa0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_scores = len(rfecv_RF.cv_results_[\"mean_test_score\"])\n",
    "plt.figure(figsize = (5, 4))\n",
    "plt.xlabel(\"Number of features selected\")\n",
    "plt.ylabel(\"Mean test accuracy\")\n",
    "plt.errorbar(range(min_features_to_select, n_scores + min_features_to_select), rfecv_RF.cv_results_[\"mean_test_score\"], \n",
    "             yerr=rfecv_RF.cv_results_[\"std_test_score\"])\n",
    "plt.title(\"RFE with correlated features\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "b58d2845-d38f-4948-87b5-1ce577abeb3a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Predictive Features: 19\n",
      "Most Predictive Feature Indices:[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 16 17 18 19]\n",
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "Fitting estimator with 15 features.\n",
      "Fitting estimator with 14 features.\n",
      "Fitting estimator with 13 features.\n",
      "Fitting estimator with 12 features.\n",
      "Fitting estimator with 11 features.\n",
      "Fitting estimator with 10 features.\n",
      "Fitting estimator with 9 features.\n",
      "Fitting estimator with 8 features.\n",
      "Fitting estimator with 7 features.\n",
      "Fitting estimator with 6 features.\n",
      "Fitting estimator with 5 features.\n",
      "Fitting estimator with 4 features.\n",
      "Fitting estimator with 3 features.\n",
      "Fitting estimator with 2 features.\n",
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "Fitting estimator with 15 features.\n",
      "Fitting estimator with 14 features.\n",
      "Fitting estimator with 13 features.\n",
      "Fitting estimator with 12 features.\n",
      "Fitting estimator with 11 features.\n",
      "Fitting estimator with 10 features.\n",
      "Fitting estimator with 9 features.\n",
      "Fitting estimator with 8 features.\n",
      "Fitting estimator with 7 features.\n",
      "Fitting estimator with 6 features.\n",
      "Fitting estimator with 5 features.\n",
      "Fitting estimator with 4 features.\n",
      "Fitting estimator with 3 features.\n",
      "Fitting estimator with 2 features.\n",
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "Fitting estimator with 15 features.\n",
      "Fitting estimator with 14 features.\n",
      "Fitting estimator with 13 features.\n",
      "Fitting estimator with 12 features.\n",
      "Fitting estimator with 11 features.\n",
      "Fitting estimator with 10 features.\n",
      "Fitting estimator with 9 features.\n",
      "Fitting estimator with 8 features.\n",
      "Fitting estimator with 7 features.\n",
      "Fitting estimator with 6 features.\n",
      "Fitting estimator with 5 features.\n",
      "Fitting estimator with 4 features.\n",
      "Fitting estimator with 3 features.\n",
      "Fitting estimator with 2 features.\n",
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "Fitting estimator with 15 features.\n",
      "Fitting estimator with 14 features.\n",
      "Fitting estimator with 13 features.\n",
      "Fitting estimator with 12 features.\n",
      "Fitting estimator with 11 features.\n",
      "Fitting estimator with 10 features.\n",
      "Fitting estimator with 9 features.\n",
      "Fitting estimator with 8 features.\n",
      "Fitting estimator with 7 features.\n",
      "Fitting estimator with 6 features.\n",
      "Fitting estimator with 5 features.\n",
      "Fitting estimator with 4 features.\n",
      "Fitting estimator with 3 features.\n",
      "Fitting estimator with 2 features.\n",
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "Fitting estimator with 15 features.\n",
      "Fitting estimator with 14 features.\n",
      "Fitting estimator with 13 features.\n",
      "Fitting estimator with 12 features.\n",
      "Fitting estimator with 11 features.\n",
      "Fitting estimator with 10 features.\n",
      "Fitting estimator with 9 features.\n",
      "Fitting estimator with 8 features.\n",
      "Fitting estimator with 7 features.\n",
      "Fitting estimator with 6 features.\n",
      "Fitting estimator with 5 features.\n",
      "Fitting estimator with 4 features.\n",
      "Fitting estimator with 3 features.\n",
      "Fitting estimator with 2 features.\n",
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "Fitting estimator with 15 features.\n",
      "Fitting estimator with 14 features.\n",
      "Fitting estimator with 13 features.\n",
      "Fitting estimator with 12 features.\n",
      "Fitting estimator with 11 features.\n",
      "Fitting estimator with 10 features.\n",
      "Fitting estimator with 9 features.\n",
      "Fitting estimator with 8 features.\n",
      "Fitting estimator with 7 features.\n",
      "Fitting estimator with 6 features.\n",
      "Fitting estimator with 5 features.\n",
      "Fitting estimator with 4 features.\n",
      "Fitting estimator with 3 features.\n",
      "Fitting estimator with 2 features.\n",
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "Fitting estimator with 15 features.\n",
      "Fitting estimator with 14 features.\n",
      "Fitting estimator with 13 features.\n",
      "Fitting estimator with 12 features.\n",
      "Fitting estimator with 11 features.\n",
      "Fitting estimator with 10 features.\n",
      "Fitting estimator with 9 features.\n",
      "Fitting estimator with 8 features.\n",
      "Fitting estimator with 7 features.\n",
      "Fitting estimator with 6 features.\n",
      "Fitting estimator with 5 features.\n",
      "Fitting estimator with 4 features.\n",
      "Fitting estimator with 3 features.\n",
      "Fitting estimator with 2 features.\n",
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "Fitting estimator with 15 features.\n",
      "Fitting estimator with 14 features.\n",
      "Fitting estimator with 13 features.\n",
      "Fitting estimator with 12 features.\n",
      "Fitting estimator with 11 features.\n",
      "Fitting estimator with 10 features.\n",
      "Fitting estimator with 9 features.\n",
      "Fitting estimator with 8 features.\n",
      "Fitting estimator with 7 features.\n",
      "Fitting estimator with 6 features.\n",
      "Fitting estimator with 5 features.\n",
      "Fitting estimator with 4 features.\n",
      "Fitting estimator with 3 features.\n",
      "Fitting estimator with 2 features.\n",
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "Fitting estimator with 15 features.\n",
      "Fitting estimator with 14 features.\n",
      "Fitting estimator with 13 features.\n",
      "Fitting estimator with 12 features.\n",
      "Fitting estimator with 11 features.\n",
      "Fitting estimator with 10 features.\n",
      "Fitting estimator with 9 features.\n",
      "Fitting estimator with 8 features.\n",
      "Fitting estimator with 7 features.\n",
      "Fitting estimator with 6 features.\n",
      "Fitting estimator with 5 features.\n",
      "Fitting estimator with 4 features.\n",
      "Fitting estimator with 3 features.\n",
      "Fitting estimator with 2 features.\n",
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "Fitting estimator with 15 features.\n",
      "Fitting estimator with 14 features.\n",
      "Fitting estimator with 13 features.\n",
      "Fitting estimator with 12 features.\n",
      "Fitting estimator with 11 features.\n",
      "Fitting estimator with 10 features.\n",
      "Fitting estimator with 9 features.\n",
      "Fitting estimator with 8 features.\n",
      "Fitting estimator with 7 features.\n",
      "Fitting estimator with 6 features.\n",
      "Fitting estimator with 5 features.\n",
      "Fitting estimator with 4 features.\n",
      "Fitting estimator with 3 features.\n",
      "Fitting estimator with 2 features.\n"
     ]
    }
   ],
   "source": [
    "print(f\"Number of Predictive Features: {rfecv_RF.n_features_}\")\n",
    "selected_features = np.where(rfecv_RF.support_ == True)[0] # Identifying the selected features\n",
    "print(f\"Most Predictive Feature Indices:{selected_features}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "56f4c436-9507-42ee-9c3f-4203bf737e92",
   "metadata": {},
   "outputs": [],
   "source": [
    "pca.fit(X_non_outliers) \n",
    "Xpca_no = pca.transform(X_non_outliers)\n",
    "\n",
    "X_train_rf_no, X_test_rf_no, y_train_rf_no, y_test_rf_no = train_test_split(Xpca_no,\n",
    "                                                                            cc_vals_non_outliers, \n",
    "                                                                            test_size = 0.2, \n",
    "                                                                            random_state = 42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "2e68f6f4-6b16-4c94-932c-4b45a01cbd67",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "Fitting estimator with 15 features.\n",
      "Fitting estimator with 14 features.\n",
      "Fitting estimator with 13 features.\n",
      "Fitting estimator with 12 features.\n",
      "Fitting estimator with 11 features.\n",
      "Fitting estimator with 10 features.\n",
      "Fitting estimator with 9 features.\n",
      "Fitting estimator with 8 features.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RFECV(cv=KFold(n_splits=10, random_state=42, shuffle=True),\n",
       "      estimator=RandomForestRegressor(n_estimators=40, random_state=42),\n",
       "      n_jobs=-1, scoring=&#x27;neg_mean_squared_error&#x27;, verbose=1)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RFECV</label><div class=\"sk-toggleable__content\"><pre>RFECV(cv=KFold(n_splits=10, random_state=42, shuffle=True),\n",
       "      estimator=RandomForestRegressor(n_estimators=40, random_state=42),\n",
       "      n_jobs=-1, scoring=&#x27;neg_mean_squared_error&#x27;, verbose=1)</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">estimator: RandomForestRegressor</label><div class=\"sk-toggleable__content\"><pre>RandomForestRegressor(n_estimators=40, random_state=42)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">RandomForestRegressor</label><div class=\"sk-toggleable__content\"><pre>RandomForestRegressor(n_estimators=40, random_state=42)</pre></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "RFECV(cv=KFold(n_splits=10, random_state=42, shuffle=True),\n",
       "      estimator=RandomForestRegressor(n_estimators=40, random_state=42),\n",
       "      n_jobs=-1, scoring='neg_mean_squared_error', verbose=1)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rfecv_RF.fit(X_train_rf_no, y_train_rf_no) # Recursive Feature Elimination Cross-Validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "7ca82575-ce14-4707-bd82-33c830ac92a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_pred_RF_no = rfecv_RF.predict(X_test_rf_no) # Predicting the test set results\n",
    "\n",
    "plt.figure(figsize=(10, 8))\n",
    "plt.scatter(y_test_rf_no, y_pred_RF_no, s = 1)\n",
    "plt.xlabel('Actual CC values')\n",
    "plt.ylabel('Predicted CC values')\n",
    "plt.title('Predicted vs. Actual non-outliers CC values: Random Forest Regression')\n",
    "plt.grid(True)\n",
    "\n",
    "# Calculate the range to include both actual and predicted values\n",
    "min_val = min(y_test_rf_no.min(), y_pred_RF_no.min())\n",
    "max_val = max(y_test_rf_no.max(), y_pred_RF_no.max())\n",
    "line_coords = np.linspace(min_val, max_val, 100)\n",
    "\n",
    "plt.plot(line_coords, line_coords, color='red', linestyle='--')  # Perfect prediction\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "c4f62991-5750-435a-a326-12e91958dc94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "Fitting estimator with 15 features.\n",
      "Fitting estimator with 14 features.\n",
      "Fitting estimator with 13 features.\n",
      "Fitting estimator with 12 features.\n",
      "Fitting estimator with 11 features.\n",
      "Fitting estimator with 10 features.\n",
      "Fitting estimator with 9 features.\n",
      "Fitting estimator with 8 features.\n",
      "Fitting estimator with 7 features.\n",
      "Fitting estimator with 6 features.\n",
      "Fitting estimator with 5 features.\n",
      "Fitting estimator with 4 features.\n",
      "Fitting estimator with 3 features.\n",
      "Fitting estimator with 2 features.\n",
      "Fitting estimator with 20 features.\n",
      "Fitting estimator with 19 features.\n",
      "Fitting estimator with 18 features.\n",
      "Fitting estimator with 17 features.\n",
      "Fitting estimator with 16 features.\n",
      "Fitting estimator with 15 features.\n",
      "Fitting estimator with 14 features.\n",
      "Fitting estimator with 13 features.\n",
      "Fitting estimator with 12 features.\n",
      "Fitting estimator with 11 features.\n",
      "Fitting estimator with 10 features.\n",
      "Fitting estimator with 9 features.\n",
      "Fitting estimator with 8 features.\n",
      "Fitting estimator with 7 features.\n",
      "Fitting estimator with 6 features.\n",
      "Fitting estimator with 5 features.\n",
      "Fitting estimator with 4 features.\n",
      "Fitting estimator with 3 features.\n",
      "Fitting estimator with 2 features.\n"
     ]
    }
   ],
   "source": [
    "n_scores = len(rfecv_RF.cv_results_[\"mean_test_score\"])\n",
    "plt.figure(figsize = (7, 5))\n",
    "plt.xlabel(\"Number of features selected\")\n",
    "plt.ylabel(\"Mean test accuracy\")\n",
    "plt.errorbar(range(min_features_to_select, n_scores + min_features_to_select), rfecv_RF.cv_results_[\"mean_test_score\"], \n",
    "             yerr=rfecv_RF.cv_results_[\"std_test_score\"])\n",
    "plt.title(\"RFE with correlated features: non-Outlier CC values\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "be133a09-4ee0-4b3c-bc90-7c9c5b2ddbbb",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Single Cell dynMorph Analysis",
   "language": "python",
   "name": "sctmd"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.19"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}