415 lines
130 KiB
Plaintext
415 lines
130 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/home/dlsaavedra/anaconda3/envs/new/lib/python3.7/site-packages/pysal/__init__.py:65: VisibleDeprecationWarning: PySAL's API will be changed on 2018-12-31. The last release made with this API is version 1.14.4. A preview of the next API version is provided in the `pysal` 2.0 prelease candidate. The API changes and a guide on how to change imports is provided at https://migrating.pysal.org\n",
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" ), VisibleDeprecationWarning)\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import pandas as pd\n",
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"from matplotlib import path\n",
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"import matplotlib.patches as patches\n",
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"from skimage import draw\n",
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"import scipy.ndimage as ndimage\n",
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"import Utils\n",
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"import georasters as gr\n",
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"import cv2\n",
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"from Utils import doubleMADsfromMedian\n",
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"from skimage.transform import resize\n",
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"import pickle\n",
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"import simplekml\n",
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"\n",
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"def order_rect(List_P_strings, top_bottom = False):\n",
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" #If top_bottom is false then sort right left\n",
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" if not top_bottom:\n",
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" List_P_strings = [[(List_P[0][1],List_P[0][0]),\n",
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" (List_P[1][1],List_P[1][0]),\n",
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" (List_P[2][1],List_P[2][0]),\n",
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" (List_P[3][1],List_P[3][0])] for List_P in List_P_strings]\n",
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" \n",
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" bboxes=sorted(List_P_strings, key=lambda x: x[0][0])\n",
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" bboxes = [(P[0][0], P[0][1], P[2][0]-P[0][0], P[2][1]-P[0][1]) for P in bboxes]\n",
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" df=pd.DataFrame(bboxes, columns=['x','y','w', 'h'], dtype=int)\n",
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" \n",
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"\n",
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" df[\"x2\"] = df[\"x\"]+df[\"w\"] # adding column for x on the right side\n",
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" df = df.sort_values([\"x\",\"y\", \"x2\"]) # sorting\n",
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"\n",
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"\n",
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" for i in range(2): # change rows between each other by their coordinates several times \n",
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" # to sort them completely \n",
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" for ind in range(len(df)-1):\n",
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" # print(ind, df.iloc[ind][4] > df.iloc[ind+1][0])\n",
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" if df.iloc[ind][4] > df.iloc[ind+1][0] and df.iloc[ind][1]> df.iloc[ind+1][1]:\n",
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" df.iloc[ind], df.iloc[ind+1] = df.iloc[ind+1].copy(), df.iloc[ind].copy()\n",
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" \n",
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" L_F = [np.array([[box[0], box[1]], \n",
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" [box[0] + box[2], box[1]], \n",
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" [box[0] + box[2], box[1] + box[3]], \n",
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" [box[0], box[1] + box[3]]]) for box in df.values.tolist()]\n",
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" \n",
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" if not top_bottom:\n",
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" L_F = [[(List_P[0][1],List_P[0][0]),\n",
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" (List_P[1][1],List_P[1][0]),\n",
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" (List_P[2][1],List_P[2][0]),\n",
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" (List_P[3][1],List_P[3][0])] for List_P in L_F]\n",
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" return np.array(L_F) "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"#path_T = \"Thermo.tif\"\n",
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"#path_String = \"Thermo_String_PV01.tif\"\n",
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"\n",
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"path_T = \"Pampa/THERMAL_06.tif\"\n",
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"path_String = \"Pampa/BP-B-5.tif\"\n",
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"ZonaPV = 'BP-B-5'\n",
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"path_kml_panel = 'Pampa/KML/Paneles_' + ZonaPV +'.kml'\n",
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"path_kml_mesa ='Pampa/KML/Mesa_' + ZonaPV +'.kml'\n",
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"\n",
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"panel_size = (29 , 50)\n",
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"#panel_size = (37 , 17) #weight, height size#\n",
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"#panel_size = (20 , 35)\n",
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"overlap = 0\n",
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"order_top_bottom = False # order top bottom or right left\n",
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"\n",
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"\n",
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"GR_String = gr.from_file(path_String)\n",
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"GR_T = gr.from_file(path_T)\n",
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"\n",
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"\n",
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"label_im, nb_labels = ndimage.label(GR_String.raster.data > 0)#, structure= np.ones((2,2))) ## Label each connect region\n",
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"\n",
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" \n",
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"L_strings = {} # {name: '001', points:(top-left, top-right, bottom-right, bottom-left) (x,y), 'panels' : }\n",
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"\n",
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"epsilon = 0\n",
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"\n",
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"List_P_strings = []\n",
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"for i in range(1, nb_labels + 1):\n",
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" \n",
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" countours, hierarchy = cv2.findContours(np.uint8(label_im == i), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)\n",
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" x_max = np.max(countours[0][:, 0, 0]) + epsilon\n",
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" y_max = np.max(countours[0][:, 0, 1]) + epsilon\n",
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" x_min = np.min(countours[0][:, 0, 0]) - epsilon\n",
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" y_min = np.min(countours[0][:, 0, 1]) - epsilon\n",
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" \n",
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" List_P_strings.append([(x_min, y_min), (x_max, y_min), (x_max, y_max), (x_min, y_max)])\n",
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"\n",
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" \n",
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"for i,List_P in enumerate(order_rect(List_P_strings, top_bottom=order_top_bottom), 1):\n",
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" \n",
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" L_strings[str(i)] = {'id': i, \n",
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" 'points' : List_P, \n",
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" 'panels' : {}, \n",
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" 'status': 'default', \n",
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" 'T':0}\n",
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"\n",
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"for string_key in L_strings.keys():\n",
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" \n",
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" string = L_strings[string_key]\n",
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" string['panels'] = {}\n",
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" Points = Utils.order_points_rect(string['points']).astype(np.int)\n",
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" \n",
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" ## If strings is vertical or horizontal\n",
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" if (Points[2][0] - Points[0][0]) > (Points[2][1] - Points[0][1]):\n",
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" split_Weight, split_Height = np.int((Points[2][0] - Points[0][0]) / panel_size[0]) , np.int((Points[2][1] - Points[0][1]) / panel_size[1])\n",
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" else:\n",
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" split_Weight, split_Height = np.int((Points[2][0] - Points[0][0]) / panel_size[1]) , np.int((Points[2][1] - Points[0][1]) / panel_size[0])\n",
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"\n",
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" split_Weight = max(split_Weight, 1)\n",
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" split_Height = max(split_Height, 1)\n",
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" M, maxWidth, maxHeight = Utils.perspectiveTransform(Points)\n",
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" sub_division = Utils.subdivision_rect([split_Weight, split_Height], maxWidth, maxHeight, overlap)\n",
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" sub_division_origin = np.uint(cv2.perspectiveTransform(np.array(sub_division), np.linalg.inv(M)))\n",
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" \n",
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" for i,panels_coord in enumerate(order_rect(sub_division_origin, order_top_bottom),1):\n",
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" string['panels'][str(i)] = {'id' : i,\n",
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" 'points' : panels_coord,\n",
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" 'status': 'default', \n",
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" 'T' : 0,\n",
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" 'severidad': 'default'} \n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"## Save List in coordinate latitud and longitude ###\n",
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"geot = GR_String.geot\n",
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"L_strings_coord = {}\n",
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" \n",
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"for string_key in L_strings.keys():\n",
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" \n",
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" string = L_strings[string_key]\n",
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" points = string['points']\n",
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" string_coord = {'id': 'Mesa_' + str(string['id']).zfill(3), \n",
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" 'points': Utils.pixel2gps(points, geot), \n",
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" 'panels': {}, \n",
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" 'status': string['status'], \n",
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" 'T' : string['T']}\n",
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" \n",
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" for panel_key in string['panels'].keys():\n",
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" \n",
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" panel = string['panels'][panel_key]\n",
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" points = panel['points']\n",
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" panel_coord = {'id': panel['id'],\n",
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" 'points': Utils.pixel2gps(points, geot), \n",
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" 'status': panel['status'], \n",
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" 'prob': 0.0, \n",
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" 'T': 0, \n",
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" 'severidad': 'default'}\n",
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" \n",
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" string_coord['panels'][panel_key] = panel_coord\n",
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" \n",
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" L_strings_coord[string_key] = string_coord\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Display image"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<Figure size 432x288 with 0 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"image/png": 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\n",
|
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"text/plain": [
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"<Figure size 1152x1152 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
},
|
|
{
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"data": {
|
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"image/png": 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oZyyAIJnsL2gQNvxiHUhcJQsbsReQ0MJE7JzeWtwHIL5Lkva4RAOzY8K5bU684fVc9YKvIsy0L9uRKkFrqzwBaSn5N8k/m2ngYDPneLOmtK6OFZ8mL6XzMFNPacNwaVqtVfmqfQAEoG3gxKtfzbEv+Xz8lYeIEnO2n0zm74cO8ofI/lGOkjtlurHg6MHzNBJGE4keBYCWEsSqBKq6jr9TjvF5CBnm0Ho7pWPOvfVPmd92Ow/8yq8CcPTvfC6zm29KznYZctiL0ipf5rwym7Ycme0Q1bEha2Hh6lgt5anJXFWOqmxX6TL3wxzW0DTNewc+9Zkc+NRndoSy6rqKptHIDqmub5wgaSK+CWxOF2w2C5xEJrKmtK6O1VU2qimkCxbW+6aRp8QBaz4Q9Mq3qObIs0WuYwU0Oz4KJZ8YpXfN8lEEvI9MfcjgCWtK60pZGU0qZ3if0UUG3CERRWqAVcllyX6UaHbMS65jv89RsQKMRC9deiOoMI8NTpSFjuOrH8dvIfSnpIdziAFHtH+Y0DnFThOIjP8MHa3D9rFCC3UsyXJuJoNWIUbhzM6MiYvcvXMEd2g9Aq2ODRmF0HeMhzGenPtyouVmQxp80kBWTUUqSURY5qMqemg29I1sv0ofH4Jjezt1X7hy8yzTdSpjdUx83MNplmWjUb75zpiIGTyyzypMNfs3wRGd7AWp7TekwwLiSMfWbwVhZyfVeHH7tka7vGwUAHJNR6Wof+6xarQxFqKrQwDSp4PESCcNeohzD/cr01hM2fg0qoFGx9nFjAfjurzL6ljlx4jb/y/bRpvu54VBkfaR3uulMaPCLdp7bXGKUy0cf7vW2oleIXP73Fi798tAY+8Pt0E9moBzkei6YKFIb6GWT5TPoYLzMTnNwe35TArE1qEq+PUUtlo29Hm60SXFYFQ7wNT71Icpy0YjwTlNMcUKWMtMUWLsprIQHN5HYpQOrH4vYC9nW5PqV8BkTapf28eqjWIKu+W1L2UyCT2fB5Jv5PZxlEW0OLWuei/macqmq6i2nJfyHuTYYd5en9texyjs7k44fPA8i+DZ3W0g73/18dN84fVv51s+4U2P+ndxqW0UAHIuLcfdACRuyUrL7eO/2Pu+yoNFFXx2mqP2k6YhugQU+r7UnoKvOQqteX9bqe3ECWOwUQAI8miwxDlVFZqsiADwLvZGE59vqBs41IEEJlXh3AdP8KEfehN4YXbtcW76+s/rJv/oekDV6PIoBKiwM5+wWHhim7Kr4pSJi2s+0CqZrXzqYJ6NJM7FPdNU/X5ty5YTIsrmjcd46g/8AwA+8AO/yvn33sXWk68nRMG72F/ZQVm+a4TFwhN2fVJsLFySOItycA2g1bHF9pTQptyS6bssqqwkEFnE2X5abMieD81Aaftrm2gd0U1oD13J2fOzvDzXEi8KwfUi2eJI4MmjDwqyk0asU2Hz4nwZl9hGAaDmvgnqm6LxSnKdyjGuKa9DItl+GfwBEX/7be/i1Ot/neaaK9mdX4GcrMrjGy1W6Z/PiNimYt1IyoyZX5d3WSlzizRiSK3vGtI7UpSw8KSX6sbq51Il5RUO3vJ0Dv6bp3Pydb/E7h/+BQc+4RmDD6GV5iwBShvtwNVEJhsts40FBye7a0rrKtniSOz6gi0zYxTa88FbZjVv2kYwBXTRIk2T3j8wg62GuBEH7Ef2FtY084qfRqazlmNb5znU7K6d6FUynUVkEhPxy8hdlUmjXf6qBtIQTDUlthwM59/xbs78xpsBaK65gtmzbkaXtCoQn0EcBV1kqbNX3CQwmbZMfODgdBcnuh6BVtHELQFKlRMDuuIKLB+RilX85q1PupWtZ93a7ftw4vfG6phGmmnA+8ikCWz4Ba06wkdCn1xhGweAMnBSwtKEfZ2YT2oONJSbW0acEn2uqKq1GnGQwb+g5WtbXWgRZTZLo40TTZzofVF7+dloAFSrLCSjJTEVbVvfVCXxnTUT5jGc2NBRduy9LuqNZTRWO1yAJqYWPdm8aAlaNi4QdRxpyHEACLq/+vzcqBPOIs35xlt8p3RLkTz1FRoGVSBQekvzXg2hTKzX7EuV+I9RRkTQaQJw23oms3n5qG30nIuzi/I1XGobBYDcZAkTUNKU4ffh38Qc6Ckk+lyWt56iUrGGQcJUNNcNSqkTS1lYKxcDbKsWZNSSuAVoc5Hxuk/95WzjAFD2c+psuRPF+ZhTGXuP6W/bm7G35zG6btQqe2tfRVQd10xCybVpECRHwWuGQP05L3cbB4CsfFydRhDF+7inhG/Ncd6jQq3PmZOuKYy811+JSxipqkm+41y6dszHxSi0weFdLBST7bjulbFSloAS92xrnEmZl2fqzcKSUcFI9a4iy3eqjvQzZl/KKK8pHxZpmtijwoooMx/YauYcaHbxI1mJjQJA5S++mmqMH1Tf/CEXKGo3+ngSmWxILutGojT9lDBTyfyn66pKAbHJhYwu7JyyMWnZmsxpJHK42cGttfGrY97bTev+2l1eNvsMpBocMTvBBqiIlimwN1JFR6y22XmG5HsbjYwBIBm4NiI5iWw0LRt+QeMCEwmjiUSvSfUrYGtS/do+Zm0UU9gn/Mq/K33YnVBYgn4fwrxZPaWFys+xYKFZyI6y8aCHU2GIQsjU1mAE/CjFwZ5OUhb++MY5jk3P89SDd/O0jTv5gpvfcTG+jktqowCQ0MmGjZ9c32SAJi+hl5n5RzXAepRXF3u+UPGJSIt87wAytTW6HERMKzNz5hfRcXLnAOcWMzb9gi3XRaYvZxsFgGorNxn2OM/LRo9yHN3oYw64BQQLgXEfAAL4nCrxTSAujODvaJo0Mm7vThFRFmGLqzbPcufusUfz137MbBQAanyg8YFJXrJHFSY+7BlVLIjnqkpmESlJzhpUi5wItVSYF+Wu1/8R97/5L3naD3xl7/q14sM+Q4hC63yJQ9n5FgvPPPp1z9RVslT7oAOK3bRGIlE6CU8jsYAlHdeNRskPcuW5gc+y6HHecv4D9yStvcWDRKk6fRfzLtKGJunjsx9kIGuayDw0FxzNLicbxSrMEpbD0QbAkUadRrpRxn620dFGR4h9NYVNYU2VerjnTW/n2s95WmJquNjnzuefITvjbfCE6AjBlbhR4yJb0wVHts7TuMDMrau0roztLBomPjDxNn30V0tD1WmTneLa7EbX0uYScNQ5J992J1d/wbNRfp9FBl2IrhRutdUfokkOjW3PYPSRA9M5ByZztpo5R5rti/ulXCIbBYDO3H8AaWKqVCaaVKB0kWFnvKCi4dpfBwZV/Z8MptO/8y4mn/Is7nnwEIvWc9+pg5mI1g3gUrL/Stu6QgPRaZtCCi4y8y0Hm10mEjniz1+8L+QS2igA5B9sSrulsramk+4Ep4SKKFZsmEAtnB96hTN33v8gi9vfxYO/+lbmt53g/l94K4c/89MZ0quxpiuWwG8i7bTN8aiWJoOocYHDbg2glbE41azBot/eeyC72dt9bonGxx65WRwCx573ueWYe77/xzj0N59TEqVSa/IrIEkQaH2ZPicu0khg6lqum53i0HoEWh3TrYBMMido2bKgig2VY5bRUTPBvk4PygB4j/v2FwJtv3Z0NtdENDg0COo6X6rNSVmA82HCbmzWdI5VMpnErmluTR6zn9KV9QVKuRWrnJrqG5J4hhUBvy5Gvme6218PBLiye9umMneWKpnHht3YMFe/z/GXl40CQMTMSM5E92V9MKwIQpH/5P2LusKABH2Nu+XG9ovbDIDVqw/dOtrdhqaJOb7kcLQE3LpK60qZdJXqlxXbtHQCVFMXScka94uEGWEMkEHcx1ZY0B+HigKodOxJ3vxskhzpVl3Jgy3WI9DqWJLv6N7iGBlY3neswkQxTVTVKLK8TUE5fjkVFqvGWoNIrZqradIUmkhcOJyLzJqWqELjAlt+HIlUGAmAnFOaSagKTYHVbHZVvaCaUZiYg4Is9bqTDWsf1ua9EiNFnIhKJ62u9lWn7C4mLKYLGom00TORsKa0rpL5JhRKK+SgYOYlW9DQOEKm6QokhYb33Y0ckjN7GrGKP1040r2AZBqV0jUTTzoGl4WFjkV0bAK7sWGhfq1MXSWz6LL1tih8nXwzO45Q4j9DbqRTEebzmQqIhtFqEXpFxIcjElQOegZzDGmbke4jQquOhXrCONKQYwGQlptWc7xdTojWJX3rqqvEQc8c2VO7o38dv3cUSq/tc5iK1eTNmhUjfXLbRMK61cEqWc0UrOseNjmJCV3J3zQSgBeA2BMjDq0ezWoB4rBmdPe8ikGJ4r0DH5hO2iIqhASgDbdWZayErVUZj62NYyJe22Nmo5jCPumNLwE65WlHnwh74jjLnF9IVTOGtkzubMcbFygOKB3WXBdSWRfvI0c2d9icLDjQzLlido7j03M859B7+JJb3vaR/7IrZqMAEPSbuTlJ1eDN74iVz7LfCmpIMa1prT1pEJX6FSkruSTvqcBE59xDYkY2LkXEz4cp97cHH81f/zGzUQDIu05FARR66zKKa9phb4kVvwRYxone+fAp3vF1P83m46+AxvPUl/29sr/k1EiwEAKdwsOCmDU7caGORTvj7sXRR/+LeAxsFAByklsXVCAxYn1KH0Qc9Sqs40XXVo9ONeHeiXL0WTdxyzd9Qaa9Uq5nQkJwiAS8U0LsilIZkI3M70XZDQ1hJIHEUfwWNk2Eyv+ABIIaPKXggkQmLvRI865+v3rYPqf+9Hbe+eKf5cOv/2Mm1ZLcVBtN5mRPfQJRAWvsSPZJYJiSqHFppOnys1GMQFCpMPINNUCYRsyABOnmRRWIFg/ax7mWrBu7aoPn/Pd/iE4b/uxb38CVz76BrSddjaumSZ9HI7tuq8bLTiNWq0kB0vhxBBDNRgGgEB0zH4qYsC6ju5/+ykanMo0t2S+q4BSYpq9JgCs+9Umc/cD9bD7xmj3nryVDJhWq6yNGFWauZTc26249q2Sqwm7w+LwKGlYlc+oIsWv7ZHKdiBSwDUvd1X7S/NyCZiuVpHvwHXdx7Rc+qwcWsxpMKeNPKb6Q9nU0LoF8rY1fIXvw9Fapkzhs5+RcTKoIF8tIYE4u0NsOXYvL2k695S7u+dnfgabhwNNuJD7hSZw6PySTdWmPtvW0C0/M+jSA3bbhwGTO+TDh+HSbA273onwXl9pGAaD21LRTXRiHGRJN1WuiumaTrLZQI4SJDtj2lGOL3fIMrv62Tyz019MnB/vWHCBTc4T8ukk7nZ8uONekUezajdNsrQG0OiZRuk45Ct3dVzRk1qHdbMuolyLiUgSH0JHRCgizs02s2ItD6qNtg45EZD3CQqJzLILn3HzKIngmRwLTdb+w1THdCH1lBh03B9FexXnnUuNb621qpPleth06EKmgMQFOaxC5jodN3r/kpaOkEShKB9jsWC9ER5OJh5EAyE0D4vcCwTg5UX032FjhcRepGfXDWkGmwhDRxD6T6gEFQAVENT8okuTVQXp9PMyJn7nFaAKJowCQhqxn9jmSXKU0jNzVA4jk4WhJorVs0b3vp4M7qZCNZmXWCmlN5zxAJAafZUYJOFuTBRvNeEYfGAmA3KTrnJxcoL033qYzawklougw/6WDPhiY6LAbSUpnnyUFGnyT2hwkZ1vSvybim1BSGZr1YWOxcQDIRVwuNO6kc4SLoDBPV3V2vBYa1qa6JFufgYVoal9g4Br04UghhBSFFq+5YkjE+1hK4EWEnThZN1tZKbO8lO/AkSrHx8qp7q96uhs/nMaWXyJGlxzzOiRQTZE172gyCcSotNU+XeXYlItbt3taIbNpCbp2SxZUFOlTKobZ9qEpHUmsdsiTOJFecLC7/l4Fh7Ve6Aj3KXWy4VtmbjGajj2jAFAdfbbXVie6lL/LoLBUZuPDkt4Z6afukfskCyrl3ENlBtADi32OVOo3RcO9RBoX2JDx9I1fk+pXwNak+rV9zNooprBbf/nbOlJY7tDj87QBfXaiEc66ZEeyms885EHbe3VBTXtdT2WJzJ+KbDqBeeuJKkyblgPTBVuTOVMfeO5Vb+eo3+bvP+WPL8K3cWltFABqXCzOs4HH+D5pW3asVVJwrzKf6R11/WgZ+Dc+84aMfFbI9kiRSvfLBHdR5xAdMZzKvigAACAASURBVCZtfIo+p3ZPY/GBxgEg3wUSDTwWBOzViM5LtVpZamCQ6rkb8KsBTv7mOzjxW+9Ag3LzN30B0ysP9Uj1Uc1R3xsWMIKZ1aXe0Qln4sZF/U4ulY0CQNBJl+vX9qhTGY2LtNElCupACzZs0GKvd+87w5m3386t3/flZV9FSzHW9DOVk0nHp9eQuylWUegQHafaLRZ+HAWmRuFE13qwC+3j80g0nNrcPsCzx6m3fgBi5J3f9Bo+8KO/hYbYNWepQCoVWNvgCkd6WqUyIsJC/WiKbI4CQBMferIZU0q4DJqpD0wzsd5ANFRh1DTYSeZXGzAXD2yjbeDp3//38BsNp/7gL8s0aVYHKGeTNk2rwLQJ5dyQFLDrAlMrZhPX50ADBTz1zSuOdeymGFNo1KNYI7HjRAPNgSlHPvEGnCjHnnkjZ9/z4TJqad6nlg0JKRjpxBGisNs2ND4khUgG8Vh6po5iBFqma98vVVCPPKWDzkAfBvSUHUc+4Vq2338CEeXc++9l43FHOsBU56uva+dvo2PeetrgWUTHInh24jgSqTCSEWjoQNs26Md0HEpEipwnLc1t6uufM6grq7JDt1zNvbOGP33xa2kOb3LLF//V0v/LpjKf6SFmRbVRYkih7H+63eCkP/DofgmPkY0GQHsJY5RiUrttU0YMsxBdT9ZzoXMDPPlFnwGk0W4RkgvsZa/z7vKoszOfMG99avudc3VW8OFsmPHAYg2glbEHtjc7znwVjbYba+2f6ui0adqXlfGtwTgMMrbB96Q/RUemUuTNi+DY3pkSQhp9vI8sgsfJnIkbRwDRbBQAOn0y/TWL08wcrKLDWcJj/GXx2hHgl6krsqnJcgSc7wcWjaSvmonzYvzoqkbQjocgyDTiZunY0zszZFM56He5cnL2Yn0dl9RGASA5n/ub5httwAGQIHlVpKn9UyadFdkN9OU6ds5WUvsm0SLx6r1vch97y0GUJC2SKEgAPGiT/KgQXCalJXnzWhe2QqaboWumIqTeGZnWWkYaB+LjHi6zCQz3FAjfyGxDe6102jCnFfk+/7Qdg+SBLbeBimk0i9HlqTUyc+1oeqaOAkDNRuo/qnT5rNJEhcEUVh2X/JdE+pJyhkxDdfV+WSJWqVmlJ2QkjTwZnBqEOPfQSl8KZJ8PYXckS/lRAMhcGeNAu6IqzO+7vc5yERUWFn4GWh7FlvLssrID6NpAVW8Vp9zk1Or605wmher984OjiQWNAkBNEwitT2pT+iXlzJZ11+nerBzuOgAp3WikZAc5Ll+5ge0bu15kLoGpbtrSRse5MGUxEmnPKABUBH2ZhiHQk/V0LZ6WSNqjAw+CLhUT2v5F3TGYBqEPSo2uTJk6UfwsMJstSicfK3TlR+IDrTnRK2BrTvTaPmZtFFPYk3/+pfjcG8wNy/2aIHC/gOGA12zH7e1yKGVf6KREw+PTNXNxzXlKoWwemLM5XXDF1jm2mjnXbZ7miulZvvMZv3Ixvo5LaqMAkPUFq0WFRviqWzrV2fa68RzWgRB6Dm+9Sq/fq/VfJo+OsTpOsn4s92RdLDwTH9heTPNniGtO9CqZz5xoA02oRgNPppyWm5u503W6g8SXLll7o2bkdt19EOUWTtX5Uq5NSsM5W7vrJBBC6trc+I4yYn1Tx2CjABD0R5fedre8pZNVTw05TlMDwlvv03zs6be8n/t+8fcAmN91P9d9zedy/DlP7l1bAeds1OuuYeT+7po5tbGuE706JoNpSSAX/07oCLHfiMUs8Yj6WfVyk0kcoRDh6LNv5vCzbgHgfd/wSg4984n5+E4rVp/bWJCt+Lyd0oqhjY775uPokwEjAVBdVNxe1zIfVV/oHEOznhdhQNvonjtUFQfM7znJ5NgBmq1JJx9SAbryMTW9I1XzSJq1aeZtb/gFm37BQb9Opq6MGX3U9bZ1gLFRZUiEh47TXFNcVaUL9FWSnPt//8859teeUvwZKz7lhCLpmbeuyIVSlY5E0p81LROXyP2Hmh2ON+cu0rdxaW0UcaAEFs0ksm66MhsyBo0DDXWkud8vo97ftp3+o/dw/NNu6YGtVnaUc+RRx/tI03RVQOrPMZH20f8iHgMbBYDqm1+/Hu5T6D8qS0n3Uj2Gxy5OnoXGIwcPLO+rQe5T1gRmTeit8kIu85vk0Ion7vl8l6uNYgqrb8ZQXpM29p3b/RQbJgRc9u4Df/Aejn7ak5cWlxrq6FWl8KFVwTtXrjnz7ahoraMAEFTqVCjc52WjEOQlexXjuaCiNb9/zec9swQdyznyq5BHtBCl1EJMRRWEySQwbUKZOhtJydR1hbIVs1IkofJNJlnMV2vgS4eeXHhzWMoF6PlAVohBABs3vGhPGmT7GXgKmb/1HD98LtFYfcuGX+AksuV315HoVbShY2w3eJlmrF7yDwswuAqEqa9YVZCcShOftzWVAx0yKC01YioRyec6HyYsYpOKl4/ARgGgeevxzvWc53ZJMUxgj6zHRiDvYrX87k9/1h6qmEtFxLV6r3bS6+TqrEmrrS4HN4p1S7FRAOiBew8hjSI+lgxoUWaolO1iWjHRRCTDAn0pvxVjP6u+zPZ734pvtm0KWraLBo17G9LNXMuGWxRF7OVuowCQbPvEY5bMGIxJciOVtguyqGJIhnf0O/1Ypn0/Jzfvo16XB0H6RYM4sztLcaeJ9qattQ+0QqYz6z9AktxYt5y6YFilnkhzjySlBZokOBXwgE4rBpTBQjvGa2yk14fMzi1tGvkkgDZwfj5hc7ogIrTq2Y0NIdcIGoONAkAyi0WRampRjZLUpTaqGMk9g4y82bKv4jPPJ0inD4vpOM3Pxc7pFG2y+qKnEwKdgcwdzBMYzRG38natOs6GDY7485fq67moNgoAFUAYeBRK98K64ZyBqAaTkeXLSCUDsaDtT56WquOyyDA90jW7/hsO2gQcF1Nw0YkydS1BHdtxeim+mYtuowBQGXl0oOcSKimzdKCyqWdPZrUCT30Oq8Tq0ii0p0VmDjAW1atT1CsSYZ5prW10NBLZ9KnNwVimsLUqYwVsrcpY28esjWIKe+rrvoO2deiyTjquawUOlAixmVaxH82vuzfZk3kf6uaBovqQTG3VkJ34ucdttFx/9YNMfOCqzbMcn25zw+wBrpmc4p8+9c0f9e/+WNsoAOSc0jSRGPsy4mVN5UT6wUJ1nWo1RkFzzTLBgpF2LjpdfD6XAa7XM0wluVI5lBBbt6f+NLAOJK6SpVyT5EeXiigLq141sX7ey1QW6blDXSCGql+Y7O0EbfuHIHsEZ85HFJeA6xRax27wbNV02ZGAB0YCIDAgdMQx4+XErHfvAGNHdCNLN2LFIhS01ARA3J1z13/8BeLOArc144ZvfB5+6vFeCudnSMrXJuY24ZUYMZ9vO045EzYvzRdzkW1UTrSV3fVWI7GmrlZZ8fSaIkasK81Dt922bb/tvWw+5Xoe/50vYPPJ13PuT95bqKumiDXBYczhAu8j0sRcnaPr2RFUeGCxxd3zI4/V1/So2igA1ORK80MgmJXq9QPOcl3nueNGd8JCez193DF00SZKxvZ5msNp9BD6SVVrvelcnvqqAGddDTaqYzeOY/AfxW/ReJuujMeTRxykqCrMHHtXVhYlBkqt55qisXnDMe59z5184Ot+lObIAbZe8DeBzHzM5/A+jT6d1NmXimY1yLwom37Oll8rU1fGzN/x9Lk79Q2ubdilJ+ZW372t1Uj2wG+/jcPPfiJX/Z2/xolf+n1O/c6fcfRvfGK3ax7JWlyPrIamMMKs6rsBMHMts5GoMkYBIK1EgZIprHUnndqs7nO9pK4bx/WVq+mnoPiDadpyhw4Qtne7ZX5l1koqhBST0oWj2WqZ+bYUVZi6Fi+RiRsHgC6qDyQiN4rIb4vIu0XknSLydXn7cRH5TRF5T/55LG8XEfkhEXmviPyZiDzr4V2ni8/Uui7zcYzaGgcrpZrO6oSersxVq7Ojn3krD7753bz3JT/Ng7/7do58xjN6ZHorwmCjX6mVKImwBhm4+XwzadfFFR6mtcCLVfVPROQQ8FYR+U3gBcD/UNXvFZFvBr4Z+Cbgc4En58enAD+ef17QerIee105yA/r+CrYVy+7IzA9tMHNL31+jwIrYrp7N3Ckk5MeXZf5b9UxG4w4Y6G2XtTfQlXvVtU/yc/PAO8Grge+CPhvebf/Bnxxfv5FwH/XZH8AHBWRax/u9WpSvcC+4FkmDJRqyust6fNzCws0PtD4WKlhY0+d2uRKsSKaOUbCTpv+Tq3sTFwTyj5yE5EnAJ8E/CFwjareDQlkInJ13u164PbqsDvytrsveO78s67lM8lxnHqFZbYsDuxz5DrSFVwwK8U7CxG/X+2jrOAG0W3fRCST9dMUl/5eZ27BzK37hT1sE5GDwOuAr1fV0xfadcm2PcOIiLxQRN4iIm85MXhvmWCvjgMJnTIDOj/JLl72W/KogWLVPiZVw9/02arneTQK0bGInlY7hapfCuPLzy76CCQiExJ4flZVX5833yMi1+bR51rg3rz9DuDG6vAbgLuG51TVlwMvh8QHsqnBfBSVrlqZjUo1sOouPebzmC8zLK5go0oaRep6iVIcZJviQuxfQ6NDfEwy5+iYB0+rnu0we2Rf5graRQWQpOpNrwTerao/UL31BuAfAt+bf/5Ktf1fiMhrSM7zKZvqLmT3PXCoJD6N0tFFgYFKXSq1j5Lvd2i7kaF2qOvEaUlTZHNOmUwCMaZ82GzappFm4Qlt8m/CdsPk4Jw2pL7xO2GShIXqORvWbb8fjj0H+Crg7SLytrztJSTg/LyIfDVwG/Cl+b1fA54LvBfYBv7Rw7lIOLGRFBZSKSiKY9TJe1Q0US2Efj1xTfvYNhWIE0U9e7jTRdbTKLuTmHeG3Uk+eCHIwqFOcXNHO/O43C/sfDvhXDtloX69jH84pqpvZrlfA/A3l+yvwD//SK8j2ft1CrKQ7oIGiOLpSflfNElvCvknggs5e94ofselEc1a9lSABLKezJdj4yQdB1nS4zIgs0Nt0551bd5aVyhbHYuH26S+CILsOlxLB4xCeh8elN6X/LY40Ez4UZeFg11Gov9nIINTTpQ4006gmK/rdhxIV0XWlvlbbs5Rv/3ofxGPga1J9Stga1L92j5mbRRT2M0/911pqT736MIVRSnmE7Wdg2xTmqv8H5vtuvfZO2WRfJw4IflGE62cKbrnjm4F2KaeqdONBVsbqd3B1mTBM4/dwc0b9/K1H/+7F/eLuQQ2CgCZiU+U1KRr16RSFVLvUgMGJEc5Vq+hG4u1v71emSU5c+Y6N9qBx/b3KX0hTnPTXgHrm5Gj0W1MZLIdXTecWxnzTSiKitTwDTS4DB5FW+kVS0Bzm8s9Mmb6I5D0FR1qnQgFaGKn1NBcE9pr6vCcT1GrYGPsyv9GdaMJJo4CQJDppFaZPjg0dvqttBTXPogcaF1uoyKBWZNee61t4P5XvYZw5gzTJ97IsS99bgJPxYUWpdfQV3yKLTjfSYva4EpkeyzJ1FE40VaPuX64SUxdmn3MPUypfJXq4JK6r6Yk13///J++k8mN13LNi78GnS+Y33FnBzyLajstI5K9dk2XR4vRsbtoaOMovvJioxiBvO8nJo3cHiT5HaIxj0LSFVCw+NBAqbrM2vvuZ3rDteCU6ROuZf6B29h8yjV7Rq9CbHMRJ53K1fRou7sT5hvjiECbjeLPoW19YgXmB2SxYS5pJy45t9QPR/rZxO4xqR7Vvs11V7Lz3veBV3b/4n3ozja+CVnS08l/RBTnu5J54iw/lxzpOPe0wa35QKtmnbK0I4GVVbslUiWtntRqBUGZfnp1Fc2szpAKm8/6eHb/4r3c+x9fTnP1USbHtphMUom6EBxRrJ8GRSeWeocl9WqsCPvTJjAdCR8aRgKgoZS5iP5EWQSfdF4VJ7rUQTQla8XzKcCLeXpTRRq44gWfj/PKfa/4Jbae+aSe/t5ldMQyZRntI18Hkm/ku3K/6xqJK2Z1p8L0GnARp0LT5LrNwaWSzzkdb9Mb9GkbqkIkZdRRoX3gFCd+5OcRJxz5689gdtVhIBbmoZYCDBXPqBrBFHq1pp0oGyNhJI4GQJAT4ypEukZwpnNPFvvFM6Urz+tcd+PrAgwahemVB7n+O/5xoqkOGIjOxeJ3FUJ9bvSr0eVzZEDlUjIz165HoFWyQnwXxfUqcWR/SLRU7/CV71qXZTEaa4iuNOM1sli5jutIaEbPqPX2w+7PZqqCtg5cJzpcO9ErZI0Ppc+pFIfWltYhrc4A5/dpA2WqC1GiRkIeKdocibxQ8XGjxxrgnKOUgaH4ZYk3Ivn6u7FhJ65TGStjdYO5mpdsYkHvQtXHor/a8nkKm/o0pbTRoSLMS40g+g5zBsWyXvN1JTST9RBcYkLmHN289ZwPE66erKewlbEEmn7lsbTaoSt755JWfpplzZaXMhJ93e1HRGl8SGT76jpOlMbHpSAMUVjkUWix8MUv0uz7lEg30Ea/nsJWyWwKWj7V9Kedmjxvz0N0hPyeTV9mw2Z2Q/DYNtu3aXLv1F1HWLjk+xhtJGfjz4fJuk70Ktm8bfZ0I6xhY+2YAlKmOxMHFrWo9qelukbQMqulQZBBGB3OpwZzi4UHXCoyBQlIkpvOubDWha2S7e42LPIIZJFg1ZziMF/GRSaTJEte5sMMzVXv1/upDldg/e1z9bStp91t0IVDpikjH0LK1m9OFxxs5qNpezkKAMU7tggeUFhMtBDiS/OUTJJfNBGZxF7lMLN9Uxq1aRWhBqSJJc8m+XwxCLrjSxsEbR2hJcmLJslZbyQQRlJcYU2qXwFbk+rX9jFro5jCbvqv39/foCQ1ak1PzXmpIiiMQq9cc814FdJ7tq1Su/b0YpUGDAc6SVFv69xT/jwzyX/rqnP81etv4+rZGQD+wzN/8dH49R9TGwWAOiZh5ce4TB6zDoJAJrHa03wse2mttWn2pezlsMmcnct2McI9QCvI3CFB0EliJToUT1wX2VwpGzZ+s21KVk/kbTka3ANbNnFdtLgkXC+Aq57Z+aD0DxNjJDoggMyF3fMT7tk5VGomjsHGASCrllBNVWla6Uam0jPD2mAWxmA6hbi8kqoAZHSM9uQpTvzgT7G4615u/OGXIt7zwM//P8w/eAeTx1/P8ed/YV8jFnIIIOYRy1NaYe6GJj38OL76cTjRRdxXUVcbLbKatNSOuCbiJgGZpOfiNW1rOhqqayJuGnDTgJ+m582xKdd8y1czu/lG8Mr89juJi12uecnXQGzZve229BmyPr+YSpn+1HcjTkRGU2h8HADymmIyWbdV5DU2GtEPHIpLkh+XRx275XX1VrHXTvGbDc3hjaLg2H3/h9i49RbEKxtPv5n5+2+jdEc0PjWkOJDTzqmXlKwNDzknXj42CgAVXo+Bp/rJwNcwkphmFykdl2oZOt89pO6r0bsYxO3z+M1ZYjVubRDPbyfwSv4sThNJv0yhoFNlMms5Mt3h6OT8nqqtl6uNYhyVJvZoF2XxdQFHVYROsVFVJDOzdIgRm40WL05xBzaI51N9Hz2/g9vazLLq/PdoIBJQtfOkcx6c7HLQ747GiR7HCOS0N5KUNgWSifOmWc/SY+e1k/04a1JXnS9PXa5631WhgtlTbmTn3e8FgfPvfB+zW1JZRxMzppOQRr+mEzY6F1ObA9eOhhM9CgC5DJ7axHXA8j6Wh01Rvok9QeKyqqyljmJoueu7XsXitru59z+8CokBmTR8+Dv/K+Jg45YbEJcFjvV8Z8D0/dEm7lu07fKzUUxhQz9HAM3OsJWYG5pl0jtFxZLTihIjSOO57t+9oJDkATY+7oZyLQsYiUutvs23KklZBWLWkOUjxpJMHQeAslmsx9o0SZmG+jzp4TFmQw5QXKZjr1Zoex30vIuR783/qUacqWs54s8TRjIKjQZAJtFJvJy0zSQ7nYO9l8ZRW6xqRZcVmkANgCF4agBqTByhjvWYHXpVNKYRaSIRJ5HFmlS/OtY0saKzAphCoz8CmdUynPq1WU04q2tFR2KJehtw6ulR87TlVJOgsAaq6c8kEtWtOdGrZEmLTg9Ew9aX9ZhT8qj7yHR6smSpRzJHjN01h2bXTcWuMohiNyICtOpHM33BSAD0cGx4u/0APEGlU5SqLB2dOlBdOIZTVK1kUOfWlzEKu6FhMZI0BowEQD73jR9yl2v/ZAiYZZaAIWX1tff9Djx7pr0ePTY/9vu8EmG9Clsd8y6iuc2lyXXq5ip1rovB8+Lr0DnHTpToqkodA6fbmutS3t/7mZJCNQM7R6Wds1xbcqTHYKMAkJWNs/voc1WO0sWHruWkacigU7GaNh46sPglsp7SsbAqpKmZlrhsqjPoJm5Q2nc3enbjZDTFFdak+hUwWZPq1/axaqOYwm7+/v+EEd7V6BNV4xPropOSm5ZkTf5O4Q7VCVXRUiCzFxKo4j+WR6tTFst8pRhc+rnrcbPArTfezbOP3saRZpt//bTfuojfyqWxUQCo2U5LHnWdUkLy0tnMAtH14kddypKX3er36Lap11RgrDrlwmUBY68ksHbn8VWqQwUWDvVKG1MQcV1ofIVs96pQEeY1U0lBctWDOOm2UQ1GRCm9xsq2bMWHbim0VLHWCaKokwJGO4cFlyUD1R4AEqA9uryn6+VsowCQboaspqCbtoaaLx1MMdW+RIoMuujJqkr17elT3Pvyn2T+4Xt4wvd8N+HMWe555U8yv+cenvDdL8PhE30kkEEqpbBmOke6bhv3TnOXu43DiV64RGavb47xcJr8mMb0mFhdaO2kOLVlHwqyuMMr7vAmV3/dC5k98fHEmSLHNrn6X//T9HorEg5E2oORxSFlfjQyPx7S42hkcVAJG6khHS6pMs6G2ToXtpI2BISQucodyd6kOmmeyRujlO49vbCG4XHa4Dab4pDLtMF5Xxz37rpVoLIu+Ru1qDXa6JjHZl0faKXMKb1kV8pIYN12Us+KBA4ZTmVaacFqcJm4MNNY0/NMUXWuI+w3MdEflQISCdJV8AiUpr+Q2JOL6EfTM2McAKqW6XUXnaGJrdDQXvpBSgX77CxlR9zOWVe0l9InLJ/ARrgg1dSnxWFXJI1AKuBSOb1Jrtk4BhsFgAqR3bg6VTnetIPuSWz2c1k2pe2TeS/xIbJkqCPOWzyJKB2YVLqpMKSi5a7N+TBRGgmjSWWMYxy11ZQVjgpSqK3OZUJ9E5Y+nDVMyWLD7pHUG+IVYsuHv+eVhVQ//8Bt3PN9/demibdmdMV5z4689aC3ZfxaF7ZC5pqOKWgmUDrnDBmIvelL0uqoZhEqHR1DRJGZcMO3vaBzwIHNb/1H5RypMlnsNWipq3+o1yxU6+pUj0WZMQoAeR/RKL2Ogba94zVDUU9UQLMGKYlAb5xqG8HoHa951aYqfRRGV/xo0RyDGuCjzGjR0apfFxpfJXNOCx95aMvkOmm75mMpBTOhA4/tYwCybQa0+ryRiOC6/Xr+Vx60ct/WdSR6Bc0SmsOpqn5/mfWpq2Vreb9fed62xaVAJRPuVaUXz1RJYe36E1iRqTHYKAAE3XQD3Whhigwjkg3NCGLLLOwTpzHVR23WL8y09FIrMlzKlWiTakZPfBgNGxFGAqCHIrkP9+2Kjaebvcx6cclBOWBrrGI6Mms6p0pRZJTPlHtvYG03ScqMdSpjhWz/NkuUTj1g4Mm+zz6jkpmXbsldRrbBNespszvXEkBq9YBR1QcaBYCGnXKgkynbKLHsmIcyA1vjUwso6yWWzq+Vs12fM5YeY1aDKH2QVJcoZnXqOg60wuZcF2UZynBcWVl1U9kyMNVto1L3nnRMG3yiHkUpI48FLFPcqGMnhswQ0JzGSOd17MZmPYWtmvXiNnTdeCzO430HpBo86di9U4qTDkR1yKcGz1CEaN0LrY+qqiNaxiJHtwHOhwnn2nEwEteqjBUwWasy1vaxaqOYwj7+9d9e+SP992y6cS7lxRoXH5YDDX3FhZnFjuoz2JRZlviVoLFtPW3rUvunKFx51RmefOwE126c4j8/6+cf+S+9IjYKAG2fONCVkcucZIwpaKkFZz5QrmUoiZYxXL3VFTaWWZ3qqI9JP60teJb0ZPDG6NDgsNqN83XLy9Wy6QmP2m9Scb3K4CGVnEcgNlrkP23FG+v214ec3E0SVPa1EzSxl9TV4FLPjIVDpxHvIlvNOPpkwEgAFKd08buKF2ZZB7fIAMqJTR8zZSPSdezpjSr90ac9fYq7f/qVzE/cw83f+jJ277yTE7/+yyCOjetv5KrnflERNMaGriq9AFFwWXXUHlUmLnLV9CybfhxVWkcBoPboIChnfBwlpSoC4Ou3cwoj0mnDhm5RlVWPs02u/pf/jHtf+VO0BxSuPcrjXvQiXDPh3lf/DOfvv5vZNdcmpqtJhOx4zbxoAVl0/tFYGImjAFBhJErlB1nLSVGYkHwiu7HkLHlId1hrsC07/bRBaNIIs6HIwQPpEgR05giHlcWx0LWFChQOtARBFmkUQmC3bbhn9zCn282L931cQhsHgGwEqaODRjHN/okYLydI51w7OvUFRr1Ith+YiKTOOwLzO+8inj3H5LprOuYh5NGuOldLGRXb4HhwvsmDrAG0Olb7HDWhyzjNFRV1WJq3HDdkEO6Z09I+OknADNvbnPyFX+bKf/YVnexHpX99k1kHSV0SK8pJMxJKxzgAZGYAspfW6kmyJgxK1Q1I5Hv2Wa73gFBOqOAV1Zb7f/LnOPplz8VfcTDtHDMdMVZAzY61NimtopPItAlsNXOm67bfK2RliZ4TYnbzH4I1UTecu5BpG7j3P72Kxe13c+9/eSUbT3ki8w/ewYOv+zUAjj7vbzN70k17wUOa1uIUxANN0oU1EtersJWy4bS0BDwlQm3Sn9z6UvajqNYj2cRxzTd/de/to8/7G719i3iQKoCZr5GmYEn6iAAAIABJREFUPQqhbEw2CgA5KzRu4r5sNn3VNaOLbMci0+zj7+zHVFy25LddJ1ZEOk1lGqrnuQ+LF6UZyfQFIwGQeEWssHdF8nKl9VO17zKwZKt1X0ud7bJfxVQ0YEZX0h9pxWfTaQZSrl3kJBX0nIwERKMAkJWb6wsGO13YhWryDGtLPxS7xRSvZnUbBEfXzSf1KYvZaXdom/T3i+hYRM90zUhcHWua0KsyD920Vas1YC9ADAC1oBDYN5laa8TScR0LIAKdNj6HpQSijWw5U99qKvEyBhvFb1Fru4Y3d6/DstesQr3t2yfJL9t/7+sEmHw8dA568Kn6x5L+rWOwUQDIrFOR7j9l1dSLIUgMCBdqQgf0Rjo7F7gSyY7RKt+TQWNr+ocRM7jMbHQAWhbY2a/HhdBxp0W6HmH7tYECA05/hDI1hjWoG46E2AoxJFJ9VBmNtGcUAKpHk/rm2Yg07BdmpqSqqaVixsNYge133aROjViPsa7dpeQKaIBLubA2uh474HK2Nal+BUzWpPq1fazaKKawW3/528o0FPJyXgQmPvR0YHHPCq3v55gPY1Oek9S1x+c+qKHq2hzzMt2OL1NTPrfxoRfzhtA6dO7AK9dcc4qPP34Pxyfn1qT6VTFTWixCcixErAld9k+yO1Lf8OXL+wQc75RF61O5+uz0JrVFf4lf4jv0BYZmRty3ZnjiIxtNy6ZfrJOpq2RBBY2Otk0Aci7SBkfIuvh520mQbeUF3YprWFcoRtiY9m+wquSyLRQgWd+xWDntnXWxKXGUyrFjWoHBSAC0c35apg1xiuQljgxWX8NOy8NYUD2F7S66r6Y9eZo7XvZq5nec4ON+7iXM7zzB3T/2RsQL08cd59p/+YWYO2kFqOzz1KYxgaeNI1mCMRIAxTu2gG4EsD/wmFMJva46JdHZve5peiyUVFWgV/Vc9eIXcuKHf5rtM1M4fD3XfNuLEIETP/46Hviz+5k96QY0dK0wteJfEwXZdehGFyrwa0bi6phb0DU5UbrGKYaLuqXTAGR13NHuaT3DpN1TQUy365jcNkMan8r2CrjdGRs7V9HcPku8oIZSbJOa27aAxbHk5Fu1+jHYKAC0OB66TjtRUpsnSz0pSRNWeokNnOc6JVG1gzIxYu1zq1fCRgoannvnOzj5pjcxufIq5NABou+Ol3wuzdskgGuTOiPElEw9u+4XtkI2idQ9L2rSV9F/QQZFlYKok60GtPzcprxo/lJM/cHiLKLOsfGsW7nuWbdy8hd/ibPvfwdbz3hG7hOmXV5WSMLCucA8bY/Rca6dDspuXr42DgBBp4jYs1lT0aeh76PslfHUPq8BsHaEbdm+aGHqE011cwYbk1SNnu6copKuDbnrYareai3J14XGV8mG90L625QKOMv2tX32MQ2BEz/8ShZ33s29P/4TzG5+IjvveR+I0lxzJRtPvwWVWHnv9Eax0orTKY1PqowDfhz6+HEAyLxWN0iDy54n/fdMfNg715JsfuO4+l+/MPk3MY0sR/xndeeQ/CGSXBVc2genaC5IryH5UBuTlqOT8xybbH90v/OK2DgAlInr1CMNdCORiQvrpXW+8XuVElnqXPcLgxw9zF14lrNG9oLYa5I5uzQ9igrztqFVT9BxpCFHASDTd+2p21OXWRlSVJ3u6a1RjqunQIsFuI5otkeM2IslFe8d8Yri0Jia9BJhZ9Hw4HyTZl1cYYXMuMwq9FQYde5rCIpeXqzbvztnnd4YMBT3AV4XAqgCk3majLMIPhWu2m6nnG/WLS9Xxww0S0Ygo5Uuk/0MY0J9/JhDrEunK1kyA2msQKcZoC4v7Z0gs8hs0hIRdteBxNUxqRzZeqpyTkvPMLB6id170AFlD6/OemW4fkm7ocqj5NtUUksDUjJWMZBpDmRqXoVFNvyCyTqVsTqWhIXpxsbM3RDAN4GmiVXWXfriP+3A0PUEs6mnWpbXqQ36SdquxmJXV9HhUJdjQB4kpOunTorCgWbOocnOo/49PBY2DgBh3BvF51WUCDRNIoOBBaM7JNSFybttfX+nLrZZT33LhIW1qcRuf5UUzc5R6aiptMtYKpStOdErYLLmRK/tY9VGMYXd8tqX9l67vPpqmtSfvZbt1P0zLiT5gY6murwrz16r+6+W58ElTnQQ/DRy5bEzPOXYvRyfbvNDz3rNI/6dV8VGAaBha0oDRS0mFFEcCRRBulz4BVOaAwe7u8Z+Aciu3fgehaymEi+QSrystfErZlYhHjrANBWQTGFRVKgXUJ9CR2+tKULQMTWWWSmyEBOYoCLVS+pL711kEf2aULZKNpmEAooCjCX7mQpVRcroMpT61KPGsCcG7J8Ggw6MKtJrzhu9IlHLCNSqY7sdRyR6FE60y6PNsI2liOKdPbolvT23991g5CojmA80LhJPnuZ9/+oneNfzXkbDIm33gZNv+D0+8C2vKq/tvD734PA5iOly6kRz18N2n4a+l6ON4jcx3ZY5zLXjDJQOOtaJuRDb881ufGDadI/GRxof87SnTI7MuOVlz2fr467vrrloOf+Be5d+HrdsWsy5Orv2mpG4Qra729D6/siTHsnPGKYi6n3KdrpKHSW2nIEproGNDVSF3cUEp8LJN/1vDn3mJ3HiNb/NvG3K/mZ139RoBRaAqU8rw41mLSxcGWvv32RRR4TrrDt03XRqy9n5Qumw95cs200UGIJj+8wUDcLp/30HV37qZxLb3+Xsg0uqzmclKoAuHLSuFABd58JWzGYnPOq0TybMAFGBpVkDy315+l6xwnCNX1Jiu47JHTPO/MlbOPzkZzO7Y4rsCtM7O4fYugLVJH3DZpgp2/MJ89jg19Lm1bHFwditr2uZjg0qF/gte1IfXd65p9drzMP85Al277qTU3/8+8xP3MMDf/j/ceQ5/0faN6/OJdIBswXXgrrESNxpJ4/4d101GwWAwuGQWIJ5ViiNUh6OnyoDdUZNe82mMXDvj76C+d13cfdPvZxjn/e5HP2SzwPg7h/8EQ5+9nMIFg+wBi/2WYJ0qpA8hY1FkQEjARBQkduXKCz2K2YQK7CRny8BnTSeq7/+hb19Yw4JXPNNX9spMnIVsh4jUdJ1NOvKRJRGwrrZykrZcOoKklmA1ahQh5CNdOboyXEU7QIbtR9kwHSxG+kG9FgwQn33ngQpuyRFR/eR3RpAK2TmxxSnNwOhWSJ2V3IvC7vL2s9XLBusKo51AmWOZBvTEDpVSKSoMbRJ14mxOyxGYSdMSprlcrdxAMhGGAOSket9bsVdqygGzrbWuYnBSLa82KZ0ejLfKTu0dXn0GbAYRVPBhVZQD7NJy9Hp+eXBxsvQxgGgaprpbZYOWCUzb2rRmGmuUEakFP/pVmRLrZCqM0CtM092kDXSjU4G5ty1B6fMJi3Hp9ss1rqw1TFpUk+KwmvG1Bj5/apnfDnGgZiIEBIwqgy9Dqe9IaCsmV0JYNqyK4NFtfzUSc7Q53TK6XYclTlgJAByjXYjihU0kK4JS7SRJlsaaDpSmW3rEeyr/EcCY6W+UNtmidK0wVIWBYD1LOWSE64q3Hv+0HoKWyUT0aR+0P42lzlCEgfSHOiNKDqozCEMRqveibUHSMlpDlVwqtBI59Bn/0qrGFEbHEEdbiSk+nEAKFdTVUjOc95mCoqm2acrIXQleXuOdr/H2LBtwfBMYst4pPQoi+rLCk28piBiEM7vTnAHlY2RpDLWqowVMFmrMtb2sWqjmMI+7hf//R7OT622iBUDsBDs3aCP6gVqNw8H6R51Np+r3ldVaBe+7BNah7YOccrW4R2OH0i1gd782f/hkf3CK2SjAFDNP+5vN4D0yWZD27+tk70/fK8GVaoZVO9jmvwiCVKX8mF0TMh1JHqFTFXwfjmIbITYQxKz96v9oFt5X2hEMosl9uR6I55zEefSMixGwTWasvWmnRdd14leNduv6nypYD/QiJnVRPx6Wqpb4i7uP8Nt3/Uadm8/wce/9ptp7zvLB7/xFUyvvwppPDd++1ftER12fVyr5nTRWiXIukLZqlmdbO8a4aYttb/jBuAZKlMLAGpZzqFNnvCdX8lt3/ML+bjIwWc+ieu+/kvsiuXYEshkydQYhPnuhJ224eB0HEU2x/FnQB88hQxPUoGaz9GY5CZHkJPM2ZWRwo6vZT5RBTdtcAe2ykUEOPf2D/Khf/uTPPjG38synlh6wpvSY+IDzsUUk8oJ2Mm05fB0d13eZdXMZD11ONq0XxPXl/mYtCbEbjVVd95JmjBLjYQkh44uJWWB6RUHeOr//SJk0vDB734tB57xRKY3PS6lMlxE8meJQz8qJ1MPTXfYasYxAo0CQE2T0gJKf8neRocA53f9kjpAnYMtorSxG71cHq1SfSDXk/qE6FCZpKKZATY/6amced/9HLzmxhzB9uXckvk/MfhE9wipW0/j4rpf2CrZmZMHEB/3Vl21RGluA7XHqk17kp+2BK9SHGHhOPfABjpvcZupucrZt9/Jof/zOSxOzbA60unwTOnQxEx0i3T+xaKhjW40LZ9GAaDp3UnloEbhGGJF9nle7Tr0d2tKs7aBu1/1Eyzu+DD3fe+r2LzpSZz783ch3rNx0xM5vPUkuEfKSVTI2ffuIn4uxInSLjxt9Oyuq3OsjklbUUyhD6CabGbZcakAI32ucjlMKhA5z3Vf/TW994/9rc8px0cA1Y5Ln48t3Xryds2kxVYd7XoZvzq2OBJ7XXhQKbosNR6zkcJsvwFJbKmcvaKl7l+SI/+MBmS6qqyk6UsWUve7G5WNAkBxFvs3MlL1CNOu5VNFcS1E+qpyxkPaHh5Hdf48bQF9FYhWI1x2s8ZUnWMUAOpZBk3plpPJXgx9Vlfd2Eg3Su1zzlrxYa2cinwaRZBOoFgBS11SZ8RpUrUWnD+MVMnlYOMAUKaX9jxf2+a1azhn7+XVlU17hSK2DEAZDPXo04GnW2ktO1RVEZ/DA0ZUFB1NIhVGA6BqyqjN2aNPSUUF2m5/rXViQwfcjhmaNfK18xlDtRcKMP41qJey7yJ4thlHhbJxAMismkIQoMl1EysnWs3v8QwAZ0ulapOrzte7zv/P3pvH25ZV9b3fMedae5/m9k3VraJaoIoCCmlEEEREKWMv+tQYMSr2TSRqPsbmg3mKweaZGJWIEh5EReyQ8B5ESEwMnRrl2aB0BVTf163m1u3OPfvsveYc74/ZrLnW2acKk7q39l21x+ezP2c3a619zt7jjDnmnL+GaK+QEjfK5jnZfrANqiHaBMsDo8LJ6XgJql+oEEJFKBppIDMnEj9Mi0NKdmp2+in8U/N1O++TNk3L+7EDSrnXAeDT8R0TB+rD/txQhrFhJFDcqJRkLJd2QxN3KyVPkQAhaVLCxOTJO7J90NCcaiFxuyJoB4dTU6NeVrLoP69VmM5DxAMNJIGWoPoFCFmC6pfxeI1BDGFX/PbPdjZL0/0ss2t8xPy055QWBvm5HRb4wkyqO6xlcH7SQVTBu/nney/4jQq8sHJokycdfoBd9RZvfeEb/mF/6ALGIBKodCaE+dsFof8pX+k+VqXjA9bZ5mDb7Dw25kVTXaASw/UkH5tmgOIEFzWDhiLze06GMBGxIvIhEfmj+PhKEfmgiNwgIn8gIqP4/Dg+vjG+fsWnc31rw45lQhqG5tbPxTqXtJ4S6toH2yOteIKxHlu5QJWOyMP50i/EqX13X06TbJ4PeKUtVzFxg/jfPWc90A8A1xeP/y/gl1T1KuAh4Nvj898OPKSqTwZ+KR73iGErH7wy4hceHgel+HYY697aZGrpP4EK3d7Sse6hk9z+I6/npm/8aUQbxCinPvB33P2vf4M7f/I3aI6dCOeY4r1isgFtAsWYOcvEDUNo86wnkIhcAnwZ8Mb4WIAvAN4WD/kt4Kvi/ZfFx8TXXxqPf4T36CeI7/Q//Vv3+PT89iRLYXatcslPfgsrV10CgDt2gsn1t3DpT72Cy1/zLYwP7+4gHsvETU6KGNBaqaqAlR7KOtC5qEC/DPwI7Y7UQeC4qibmzJ1A8hB4AnAHQHz9RDz+EWObZ3zBkLAJ7B5vZs5QNj/JQiLUq5bR3nEYJo2y+eEbQD13vvo3OfrGd4MPZi+p6qXEMUY7gHpiVRvbZjDiCmc1gUTky4H7VPVvyqfnHLrT2m/5Wnnd7xKRvxaRv76/83w7LEnBkCh7H2ipPVIkUzKpS0PXvAomgLWKO3kaGsflP/3NmJWK03/1CUTaylNy0EyhHouGGVklfplAn2Z8DvCVInIr8PuEoeuXgX0ikrrIS4C74/07gUsB4ut7gWP9i6rqG1T1uar63MO0vUpbUTy2SJhHCoFccUzRfIf32p7TZm2F9WsvxxjPrmdcydYdD+z4XpL2zZSMlzbiB2N1cFYTSFV/XFUvUdUrgH8CvEdVvxF4L/C18bBvAd4R778zPia+/h79NJfK2xlX90tPdk8d1mrkjAlFNaI3yS9mbvSeX33KpWzechTvDWduPoo9fCCs9XihaSxNY/HeMJtWQWTBRaSijU276GA2Ux+rlegfBf6FiNxI6HHeFJ9/E3AwPv8vgB/7dC6WkiYNQQAucrkaF25lQmRPL1GcSuulGomGzoVFR+8F5wzNlnLLT7yFya1Hue2n3oLb8lCPuPVVv8XmDfew/rynx3OEpjFMt+qcPM2WxU8qaCR3gY23S0z0PzRU9X3A++L9m4HnzTlmAnzdP/Tas5ndtoosvVlOOVVPCZd24cuKletCsVKtXjj8L7+z+EWFPV/zxHDfC9NNYDPcx0nARqf3bcJj8eBHgZUxXVpeLlY096+GIaLqAccgrAA3EX1Y4KEzTnqnkSQB8+MEqs8Zk/hcZyRKDIzEB/PpFtaBnELTGJw3S6X6RYrRMRssneahEgnPpxFDS9xQjB3hycX18ve9faG5vb6ATyjIgs6TsUdFIg6liR5EAjVrsYGOYt9SfFHipWPpVFo39f0rtkU/sdJMqjzHhPf1FTljUuVSJfhleBAfQW2FRtAQYhAJ5NZdZEBo90tWQWIjs63KpPLQr0amm4D9UKOB61VUl2BapxFg317Xxyl86oHwgBc8shzCFi20XLDLc/Kei2H5IPUxJQxWdsyr4rzu+2n5nrRVEC8huSRWOXm4i56/MZgEyiHdPkdKwqBqp7JkLj1kcqCmfas+FQgSjoNMRkzPp3PSsJTYGvF1r4QeTcOxBsUvp/ELGiX7VKVHee79hNZdMFajlHyZbSptYoTZlGbWK/QqX3z/rjA5iKG1woy/z3IdaJEiDRvlcnKi3ZTDlNKyJNKXnCjQFI9FW5/V1IBrl3m6I+XHaNsHQaD6xARSIQD/CQudQ4hhJFBdDE25J4kwivJ78kGSd1tHXTbN6aU0DEpRttJ5aXeddmGyY2CXrikKmJZabeKGa9yrG0IsWRkLELJkZSzj8RqDGMKufMvPAG1/AVH/ubcLr9q68vjelD7PuoSuHF6xJ5aZrpDZGM6ZrjRMMRQaEwiHvjHomfBRr1+wwdMuuJfL147xi8/+w//Nv/yxj0EkULKxzKu7Bda5m0BhRqUqwdsLQoJA5MpLThAg0pZpp/qQcc9JQLNvXJePFcVWLlhJSeLkt7/nciV6gSKJhafKkUBl8z2/0gZXWVmSy2HvS43Pu2MnuecX3sLsrvt54ptfxeZHbuTBt/85CszufoAD3/oydn3W0zrJGhReBS00qNPv0UTl1yHEIBJIohdGy7Lw26pPilaIvL0/L7xvZ1V2zwpP+D9fwT3/9vcQUdaffRW7nvNkmsZyx4+/gdVrnwRQkAy771euO/mo0DrTJZxjYSKZqXRgrXOGCZ+GKAn6zzJn06utSm1ymZUKVqoIfU2vQ3P/g9i9u7BrI4TwvuWw1nLE0qJku4i4lPldoEis0xJQX5qoBPxNXLfpnMO2CtQOe9tNWBIrI4HTNj74cXZ99jV5CE1VS0zwqvfehD03q3mjNx3jB7IxNphpfImJ9t50VnqV7qxLi+PnXadNxPZ57TXLxng2/uaT7PvsJ2OzZ3yY5WVcdpmccWvFO0PjzRKRuEiRhq4Ohbl4PZH4NOKeO1UoJV7vmmXCzFtr9cdPYWpLtWeNpimm+On3MJ668ngvzLaqdhef7VXvfI5BVKAOxjlGGsKSiUpKnrLr6fdIHfJhpPgAaOO489W/ydatR7n91b/N1g13cPKDn2T9s66haSyqrV9HGkITTywzXOPenDGe2jpqs7T9XphIX1rqcDLrtPgyk5tPGsr6yVNWJZGo/UxYNzIrwpWv+aed43Zdc3FgdHgfKT2GZmYzR18jzaedzbW/q1dhcyDc+EEkUJKL016jDNDnd9kdmuedwkRP+pR4aQhK6WqNRzUkT0oOcYJETaJmVuGnFrYM4kMPNJRFRBhIAk1n1bameIbd5pXadWnuJlE/0UoFj2SbWdpXOmfzNVMFUgW/GYSksMoMkNMV1USyer7fK6xVUw7UG2f5Uzk3MYgEmpwYB+X5uJDXgV1AttzODbOXjnrq3OjDOyBvkagrFgddnG0ZRWYm46ntpsEUnnLiBLcapGdGxjE2pSvr+RuDSKD6/no7cKxcz4t45xL/LG77zkU/Ami+d538InlXRBR8FYiDid6jVnEr7XuKC6/XaRN2GPOXYSRQslXKOVRUjzxTL778kuy3kx5I4pllJGF6Lpm52HTTfD+xQNSEhMoC5xLO1ar1l1/uhS1QNHscMg0lR1ygE0PEN6fhRjMyNVB3fPvlbpNOVJCoNZ0w1Urc9U/NdBUSRVOS1do5nli9EpUnhbV+MJQeGEgCYRUdAYSEccUir9GCl5WgpTHEy/ZhTLs/JSpr5JfTqnNy8InEwsxALdkZQlgOiNN6tUptHWPjqGW5DrRYkZl+tM1NqhaW8GWWvZCS96dypFXq3tDWsll1O5W50sDJT71PD4ed+fqRmZoWJ5c90CJFXlrW8N9vpe1VCjhFp+0wLTKovU6EhaTjU1KkpCvu+7pXiaStTh3Tl9yPxU1UH+wuN5rxo/THP7axBNUvQMgSVL+Mx2sMYgi74rd+rrtjnhYKo8ACUMzE2llZfr4M7TbWyYyuHdbiHVs8NtoxoBNb7Mp7CQuPjSAzQ3VwwrVPuJu9owm/9fzfeBQ/hccmBpFAYn2UwohPxFlPTqLUPGsiFtLZLG0XBMMdpTgHyHZO0FKao40TZdOcyIwU2yQJauIsRKySV8NouRK9OBFYGdG7K9GQvWaAF66oQrEq6bbSQ2vWC8zVN0+NsihUMXF6M7686qjd89KioncyGF48DCSBwn9+u9GZLS3L2VMattLiHnS2I5IhSpZpKdQ1modOcP/rfoPZPfdx6a+9GtWGB3/ld/FbU8zqCof/2cuRuspoRMlJLG1VSjnjJbIyhpFEw/griDge46lqF26Vw1aOatQglcdUHok3Kh96lkrD/drDKP5Mr9c+uw3aPatc+C+/g/GTLkVqz9bHPsnoSZdw5FXfyfhJl7D50U/GX0LDe6Q+SQk90My0VdBsr3zncwyiAiX3nBYNqF2oRmSIioJ6Ig2oC99QlVblI/2IDAuxFSJVWIy0Sn3RAaa33YWxim5uUu1ZDb1OOq+/z2UIC4mE916xzWB24wdRgYz1GdjeJffFW9SETh6nYsBYxVQ+/LTR4SfeTO0xlVI6M6eqIgLji/czvekO7vyRX2brlrtYecqlJGPfzjCah1DNah9ilJVqNpj9sGFUoOLLTVEmUlVphpdKsd2RKMqJU5YiVZBGbAafZbqQ8Zx6/9+y9qwns/8rX8RD7/wzNv7871h/0WcixJVsopOz7TJm1YStjGogyQMDSaDW3ES2JVG69S0vE4M1hRWlsh7nhZmzOGcw1mfhhKQ1lO00d62iCnbPOn5zgjE+JF7KT7Szk6EuqKWlRG2WzNTFibYC+U5SCGQg/TzQfXodoK5cxFZbnFd8IiYaEN9w17/+baa33cvdP/NmDr38Oh74g/dw8gN/j1jDRT/0dRgbwPVExfwkwgBkLlh474AFWvLCFigSjbkEaZXM1NToJWWOkmnaMjg0Y56t8YECFOf+UgmXvfqbCzo0XPqvvrkr+xLeIFssGKNUlccVRrySmBrIElC2aJHXXnZ43cYhpkkr0MUszBQowZREVbR96gLv26sbE5Kj7KHqUYMxymxms2sPxOFrs8JMJatzbLKk9SxMVDaAs0q6jCnYqH3ZFS2SaOYsVhSvdKqTL46RojpB2I4or+e9oWmEZqvKIld+YpEtm/FBshXOsTZWy4Fw4weRQFuzupMwEPa1+lRnJe5FlYpimMDhcjZXr+3HJCxP+9xsVlFVDucMrrG4zdjTnLaYiVBvCdVG2IRtViPAPl5jxc6WXhmLFFuTOoo5SbvWI+1ul8COnvDGeryRLM3ScsC67+G9CUNRrER+s0JXBXUGbQQ5Y8FAfdxQbUgEnYGrgmSwmYFpYDqp8GpYrzfP+udyLmIQCaR3reYdAo0bnuVWk0JWoM/C4akkpY1Ooash3ZmDhwZYZoKJ2OrKC3rKpk3+iLkWtILZnsDU8HHDNajUS15YHEoDDQNJoPU7pcUpA4i0VJzknJNoOAWTIvPH4nmJFNgtXfG+hkQwkdrjxmC3BDcGPwK3Gtd3VrWl89iQrOIEmRULlDqczdRBJNDmkRbsDnMSIT4njm12TcXyUFtJKBIsRVSb98QkNG1fozUtM6OHhxaE5BmvTtCp4eR0hf2jM4/qZ/BYxSASaLY/UmTSd5dIg/GWLCilYKQqMUlMN/nyRqotEhG6SZZwRRkfRB7+MkMjoRTjjjxe8F7Bh0XEoSjVDyKBgBYdGMFkQNssJ/ipAl67JnRCy+UqWxMtzi++azWavVExmgmFMkvJExMowjrURSOO2gc/1ZlhYzoazEr0kpWxACFLVsYyHq8xiCHsijf/LNssCSAPUbpl26l6Dy+UIKcZTw0k64MEKOvIuZT9EnSbdUNGJJaKDHUGAAAgAElEQVSoAD8L/6fahOsduugET9r/AG994RsexU/hsYlBJFAWGqeFW0CbIM4VMI8kQC7b8UNiPKiE/rjsm/J6kOQkS+f2rZ5KtdjOexpF1YCHUdVgdty1O79iEAkUZkE7vyTJdrt4UkwXr5Mib39AhqI2J05y/797M9O77+OyN/wkAPf/+ltxJ08zuuJS9n/dl8bELN5iW3IGvpiqBBHPgczCBtMDidF8S2LgCaqRV5vLY2LFMXGfTKK3hpiwzZkkgMWA3bPCha/6NsZPvhSxyuaHPsbo8ou46FXfAbMZ0zvvjsyLtI2y/fdL2ywQ3AqXkNYFioxXpv3iS4hqRVFZCrxOgGK0Q1JCFXqvGf6qothxDeOaZGfQ3H+M0WUXgkB9+UVMb7qd8RVHsr1UiTdK9B71AjMDPiiAjAci8zuICpSqCGxnRGjsW8T4bckDbFOkL6Pj4pN6H+OpLzrE5PpbEYGt62/CnzmzradCWruFDNCPi421daza6bb3Ox9jEAnUN5aDNjFK24J+suxsdxBxO9aHW9GziMCu5z4FZjPu+Zk3IaOKav86xvbeH0ISWY+xDltHrpkJYLWlwNQCRcYux5a4tHoKCaPbKlOJnU7XSMem+wH/o/jk3CPpvYSD3/rlGFHue8M7WH/mk9rhqnPN9qdCS29e7sYvVlTRk6IDIOut96h28dAJ39x3NEzHhwQLBdrPPHf9zFuY3nYvd73mtznwtS/hwbe+FzHC3pd8BuMLd9PMgIhBMsbnpQUI1UzVI2JRgUr8UqFsEaPDyBDmJFHbND+cUn3pZAhgR8JlP/XNnXPWnv6tebbnfds8CwGkVgLUwu+miI2q9mqY+mF89IP4KwLhr58wXcceaFkZ0CZJ/zr9xwGBmF5rX/dxWu6c6SRK+1pbyRLQvmy0h7KZOogEMqLbfDKMbG+sgda1Z85rPUTHnHPLviYNiamyhdmeekHU4l08Pi5iuk0LjQGjjAfEjR9MAvWjX41MLhBxMS9WDRdXhtNxJfMiWWRCy9jIroS94dFELllyJVQnMLHI1GBmMJqE89yKcmY2YrZEJC5WlDMb25thJdunlGi+GJZMcQy0xzkJghpBVbW9dhr60kKlieJWXgRtbKhuLiwaytRgtyQr2ycI7aSplj3QIoYSK0XkbSVyoFcwhGrTnXXJtmFO42Zqvv+wzXZZjSRrIibzFR17XBV7LhMEzxEYWbeUuFukcLkxTkNMqDAzlbwI2MT7qXdJ58zbUE0p44shq/O6tEMahCGraSx+ZnLfExCPHrXS2i1EdbTauiWkdZHi9PG1Fp5afuEZttEySyWJZPqHn8r3PVhTdCjRiYXqBN8YmJqgdAaR+kFYPEyUH6sIwt7RJltuEB/9MBKouneUmRJZTR5a8JdPWwvFa8VzQO5P6OUfRNpPXGlOs3mtlKYKK8viBapA31EVtPJIpUFCT0GDS0u41kxYq2bLJnqRwtfKtmLSTwzt3pfyMe2xHXpQKcZJmzxoNG+ZBrKhUFofCH4M1A02rpAn/wT1goyDisiqHcZe2BJUvwAhS1D9Mh6vMYgh7PL/+PMtgQ9aBGLuhWKVLUXH58yucnS83uOx5XDXL9qR7SqNBDqzURh56vVpFpnyztBsVuw/fIonH3iAq3fdx88+8//53/zLH/sYRAKRwFpSPDZJZTU+l8iEBbArz9z6ka9TTMmL/idjsAvioahkLjwAM0MzqZHVGXXtmMb3tEbZXW1hl5DWxQmxhXGBRICZ9XnKDnEhTwuqTsma2PHCIQm3br6Th37nXWAMoyuewP5v+ApO/tcPsPmhj2MP7uPgK74ebKJx0M7MNiqmTpDdW9jKM/PCtLF4hqOROIgeKDEepFCjN7bQPzQ+eJVaxdYeM3LYke8cL0kfeuTyLamNVYf3cuGrvo2Lf+o78adPs3XDzUw+eRMXvup7GF12hM2PfiSs/4xdVsBXo8Gh53TF1sYorCV54gxsRr3ERC9OGBOFwutgdWCr9iYmiodHeGpiXSRl+xQJFmtiwpnI0kCg2r8bu1KFc6xhdtc9rDztSjDKyrVPZuvm20PFS/YJxVKAaUBO1myeWEEmQT54ZBrcch1occJWLkMrEsgrAbpKeCtEfUPrMgSjrx0tZWJp7FPic5NbjuJPb2B3jcEIpvLYXSM0guqBDBrDhcVFbwjGvWcsdlOYTis2Xb3ERC9aWOvzdkVIIE+ybCq3LKqq/eJ0zl5XmUClj4Y7dYYHfvOPOPJD/5jJTXfjHjoZeq/pBLO+mrdJ1BNcpF3sy2xYtZaZZJ/WTVdzeHT6LH4a5y4GUUfbxPG57xFaUFkakjqv59e6JMSUPAlJaIyCb7j3tf+JC775Cxkd2MXa1Rczuf4WrPVMPnoDq095Qu65Ot4YSSOoUoiSd94JJ6ery1nY+RQ77XwnM8MEW4XtgHyA03/xMSY33c39b/nvAFzwT1/K+tMv487/843Uh/Zw+GXPx4nHR91ojELl0RbFFmZ9M4vfsmw29bIHWqSwtrUVMBKU5nfaTS9DVMCbHeGtCaS/98XPYM/nPiNeKzy//tRLOPh/vCg/py4wL/Amm93ldai4Ie9XwhpSgHMsK9DChIlkvXDfY01rfTAPslEqaIDf8ZjW93SO/wYEZbMSCWkVhw+U6ChMZqLih7GKi8sNI9Nwoll9dP74xzgGkkBtb2MkQFqNKHiTgWMpOtBWwBrw2iUeBr8MxSX885wEK/03ylA1eN/O5K1VRMLvt6UjvBNOzVa4e3Pvo/XnP6YxiARKkVqOrLgxh6bTsUMQjUoZtPtlxWupwni2Jxi0SSSiOFLFkUzzCVWs5eL7RtCp5cRkZakPtEhR1ocSUG9FsVWTrZby8b3+KM/ieg20zUNdwEY7L60xS5EA1ijWuAzCRwXvIjZbbNiHmwZlDrNpWKtn1APBAw0igazxVLbby5SVpp8w2WOVdmM9gedL5ga0PU6qSEYU501+PiRPtIcqElWdQbcM0pigcD+TLFTeeDMY18KBJJBSW4fzBmt8Z9ruI5g+fV3ptTRbS+GKLz+fk4eh6CMmZXOeu6CcbMnp0EdNILxAE6Agfuwx0+AVNq4aRnbJyliYSImQkscXKhlCSI5+P1QazGlMmP7rjQ+dSlkr+jQfHyEeqoGZ4RoTAPY5Y4NvhtaB4mM3zdzrnK8xiATycT0HgDicpGHGGs/MmTzUpDSZJQtK5tN6sh5QfK7PEUv+qo0LsAwjimsMzgVXnwxcE1oR8/grzpylGQicY4mJXoBYYqKX8biNQQxhl//6L8RtCfIKnszCY7WBnlNaOiUkReCS0b5QRuKAtQ8zNyyFpPdTglvPegShZUKZdMmNXuBUzVVPvYvDq6f53Re88VH/LM51DCKBqBUV335hgFaSH2dHHSWqzksLPd2hmVXxHeB9NqzLdj5tLokLZMIUSTU20ZyT4DkC3oYZ41Lmd4FCxq5VqJ/TEWuJ+Umzpsi00HnnpENdcV7aZc8vStY8VEyAbRQr2pI0G4t1J0TwVgezBgRDSaCs+Vxw1wsp3zylj1WgtS+Q+cmTkiWKIWzdfDsP/f4fITaC6r/+S7j35/4DszuPcuSnX0l96HCgMheRQPtGglJrEO1kPgvkPI7hNNGS5HxDVUiwi23CCIm1kZgbNoG/CLcEBIvXxEB1eD8X/uh3cORV3407dZrZ0fu44Ae+ibXnPCNUoiTxm7j5WiRmBK3VdYO1ofJ4ZDDT+GFUIIktjihiQrOT/ClQxVbt95m3KsTESqQtcRBy8mT1ewF7wVp80SPWYGuoDydFEMVUxTaKUiSRot4g4qiMxxsDcYFyukygBYpi0U+MB6uxAmkUwkzYnzZsxEarEr/kYvYUI+1txZxg67Z78ac3qC+5IMzSKg30IEN+g+SJoS4ki3fC1mRE0p0247DlslyJXqBQFwHraZO0SB4RzYD7eWum81TKIJzv436EqOBOn+HB3/zPXPiDX5+rHRRinuHJzvCXru2mhk0dZdRkbV0GwJ3vMYgEKqOfPEAngfq4HhGTtaNLg5YAuI9CnDPHfa97G4e+6R9R7d8Fqi31y4QmWX2Ae6BhBpb6IRHACd5btA492cg0jAZCLBxEAiW3wZKJmmZlQJ5GKxGvk86TsFWa1cuKUcUaH/fTlJMf/BhbN93Fg78TQPUHX34dx//oL9j85O3Mjj7Aga/6HNaf+9R2Fx7aZh1yk52oP5XxrFdbZ/tjOScxiAQy1mXUX6LjlELjlU39TlcfOuhFt9up5VBmRNFo/7T/857Ovhc/PVcoVWHX0742HGc0W0QZ42l1X6Mmo1GqcVCvT/3WyDh22WUCLUzUtcvDVJpl2QiuL8Fknp6HRgH7gO4SjYhiSSIcXdX7UvG+a+pSXiAMbVXl8TZw850zNA2MzVJofKFiVLkW12N8Rxc6Pe9VsMWXnOEarq0qXUHyALYXlW2Ntqpk77EkC6wSuGXlckFKKmt9JjHmxcU5jfv5GINIoLpqh6hyuGqrg24jF5bQ1WxK1/tiJQoDbaf9lOa6EkBlgDMG9dq5XnlNazwzLI0aNl39aH4Ej1kMIoGA7IGaIlegRzjPGr9tZpZf668LzTlONVpjahqmAjZaiiFOIehIe6GZWrZcxWkz/l/8SxcrBpNAwadCOpjohHt23nQqTh9AXxq1dKCwBTFRehjqjFSMvRLANLU1EVbbNMHJxzvD7EwdPVPDVsZSaHyBorZuW1KU0af6mJKh0UuolGAmTftpK0/CWwPbFgJ9b6FSveCcpdHWO8NMAl21Ek+1lHdZnLDSqnFAl6KTbuk5X/RGia1RVoPWfEXztctovVO79GmbmmYtXJp9Cxuh9oGx6mQwa0AwkARKLIxUOVJ1qK1rGaDSZUJUyZ6Jtpp4lchU7W1TsB1Un14vkzVXIKWbPAJ27HBG0ZnBitLocjN1oSIlT8n3KunDVnyexoep9/Yhr+SB5WFMpcNsTRurljYh0ywvnRfEPYPnqql9UFDzgtYB/Hb3mb3sqodRhZasjAWIJStjGY/bGMQQdsVv/dw2IFgaa8Qoo1G7bZBl7aQVooKwyepU8D4Azbw3rVIrAcuTzHTTflt5TQE2JzXNtAIvWadaRLGVo6o806kFFZ516Z0cGm/w+ue+5Vx8PGc1BpFAOrGZZdEZkCPmYtPUxeMIs7DdoVujXUFmbKTjY0PceS5pHybctQmoRD8zqDPRM14QwuJmSjprDa4RKvFLeZeFirELVGIn3dXAgs6TATyiUK7ZlFDUMqT3XJrMRb8N9SGB1GgQsvJVSMA6OEi3Ap9R6FwUZzzehAZ+6Re2QGFqD1Vv/8sk/I3vyq5AN4GKF7btecXE27rxjmh1IIyuvITdX/hCHnzDW0EEu38PB7/r6xFjQwLbqJqfhi/rGdcNlfXMnKWqXFysXCbQ4oR2eVgJG53QiS5JZcTtjoB97iWRUOB94pAWd/WrC/Zy5Ce+DTuuuO9X34psPMjFP/5yzNoqD/7enzD9+PWsPeep+JmJCMX4e0SZ4Mr6vE4kAhNXLxGJCxVpaEp3i+SBbmLgi0olLekwowcJX3K5UVHv390C7q3B7l7DrAWRTLEGsSEpzahNijSEeS/MGhvfP6AFRks80GKFtT73Num/3hR7VWloUm03TvNwlUx2lLYfIohjtokWmuXp7ffgT20wvvQwqtAcO8nmR29i/9d8XsvqiFsbSS9oNq2YKJmlUe3dZG89Gcx2xjASqPL5vz1pRveZFt634PkUZc+j2nbNfSsoEcWfPsP9//FdXPLDXxdM5KYN9/3a27no+76CehzgHAG0T+aD+cag0c1ZphKSde9mcOtZbqYuTqT1mtS0WtmeQElFNYUwXyWsow8dQ53nrte+nYtecR2rh1YBxz2v/88c+NLnsnLZYQLorItYbGaxelVB1Co18rV17KvPLIXGFy3SlNmKZlhrN7YDx8ycBAovakdf+uT//BibN9zN0Tf/CUeBJ7ziJZz8y08wu/84D/3RX3Lwy5/P7hdck48vTVzEKDqCGSOYCbX17LaTpdXBIsXKaJb7jsp6Kuswosyc7VB2kswdwMx1dRO7WGg6iMILvuCpXHTdU/Lxzhs+4w9/uPM7mDgkbTU2V8I0lDaNxa40OK0QUcZmxj575mx+JOcsBpFAtfWRLqxZpd6KQgSahW2Ldvc95cpOIDRLdygr8UPhjscmEfJeFat6zXtHzHMsjK3DohiWQ9jCRFWYqyRIqzV+xyHKp+Me5poBG9YFqOVkTIkkrVdr4ru3zI6kHNtLTuOZaEXtl5johQlTfKGV8dtU4EvdZx/Rg/hH7kH6UNf+ewYFWBsWrGNiOW/jMGmy10arOR2uueVrVmS5DrQwkYBkEhMobVSWoDFDOKbB5Ar0cNysMuEezvEnIRvTEanPSsLlXoMyvfcSZIC9YaaWeplAixMJn5wSBdrkgYBGzFVE24o1T2ouIxLpqtWnKOGuEIdDCmsEyMsI3bWkdt2pFseKmT1qf/9jGYNIICNBd9AjncRJkYh+RrRjtz1vaII0xYdGTceIJZ1TQjHa4ZNcAZtouZCGsbTIWdWhqa/FMdVBfPTDSaD0pcN2xkRtXa42ZYLtJPKUqk5FMHEpzzFoZ/greWYj69hqhGlcPgBoon9GkpfZ2Bpxyq2wZqaP+ufwWMQgVrNSovSrz8g6xlUTh7f50+bK+HxL10pRp/OLipOqzIqdMSo2RJO3BkAde6DNac1kq2Y2C/M911g2zoy5f7qL2UBYGUtQ/QLEElS/jMdtDKIH+sL3/GBn5Tj1KKlPSUNN422YXRGGtFFBPGzU5H7Gq8GIz+S/Ji4Sltf0KnnJoFHDZlNjRLnnxB42z4yw1jMaN1GnqDt8ftaR29lTTfjFZ//hOfl8zmYMIoGSZG6aMY0Aeo1uipQw5RpQoyb3Lwlq6tV0FhIhrjYXWxMpqbZcxZlZzYmNVbYmAcCf7Q5o14wS02Pqq8H0QINIoAdOr3eVx4jT7Uxx3i77ko5LC4GuWDRMC40ptPNa+75GwHlh2lTMZpbZZo0duYwMSKKeqsLaaMaZac2ocpyajTlQb5zVz+RcxSASaONEgJdqn36TAfaa12nEatYuTIt9gQcmLZqQgpShwuSGOzj2lneDEcZXPoG9L3sJ9/27t4CxmNUVDn7PyzErVb5mCpGQoKMogDWqHI2zrFVT3EDaz0EkkJZ0nqyS2sIK81cqgY6jJrAm1Eeo6U7XjVwxs/sgF/zwdyLjigde//vM7jvNBT/2PQiGE+/4EyYfvp5dL3w6xkbJ3wwh6coNp2p384lDTHcfP2ufx7mMQSSQXW2CQmr0OC0rjPcSRMMTwCvlV3zN255eYcQ1QyFatRpsDaydYUdCtQbVqgIOUzWsXrGXetxk/E/odbo24k6FOqqhbc4qJs1S4m5hoq7DEOHiUmJVearKZWA7JJB8OL4Vv1SMaTUVc6Rti3hCYnhMb78Hf3qDtSsPsvmpW7nvje9CRhUHXvaCDqYaAsx2VLkMLzkzrVlb2+TUZMxTDt3XWYQ8n2MQA3GZGOnLTpidcggJx0rmuZe3dJ0MjO+FP73B0Te+myPf95UArF59CZf/wnez63nXcPI9f5uVWCFitAkN9syFGZ7E/TpjPCPTLCXuFimSjZKIZC1DYzwVXWRhSp4uGyP8NGb7Dnp6XZ3nzte+nSOvuI6Vw2s0kxlqwxBk18agvss9I9QiF4fUBK3dcu3HPRTTucEkUEmBr6zDmrBYKKVtpQrOSF6PSc9BCwjrszlUhWN//jEmN97NfW/+EwAO/ZOXcN/vvh8xgt21yhN+6Kvy9ZKVQprNpaRtGsMDus50ahlf4NhTbZ7Vz+RcxSASKCVNgLQqlXXUccaTFghTJZo5AxGxaCQAvkqR8fS4haIqhz7/qRx8ydMYRV574wzr135Lvm5fhwG6ZEbnDG5m2Tg9gsYsleoXLWyi8cThqzaecdWE7QbfblGk11OEZLD4HaRWdgLWW6O4YkUxQ0d65/fdgZK74eHRKdaWXhmLE7ZYwEsrzVY8hkDz2XLVNkHMDEPt4addFJiqiufLPbb2PbtDY19zel6fJXU4f81uLTHRixSjqv0yrGg2dGt8iyhMX3JWsI9Q1KpHzbGRaZFmSalyQYG9Brxtm3GvmrcssktQSiRi7zUjCFN54aHZOofq02f9czkXMYgEqk2ahbXVp1RQTckEbNtRT8+l6APtS6BYCdxPsyyvgkHwaKxeEc0YG3kIPZprDD6C60+7MReNTpy1z+NcxllfBxKRfSLyNhH5hIhcLyIvEJEDIvLfReSG+HN/PFZE5LUicqOIfFhEnvPpvUdbWca2CTCL+EVXxmPFMzKugzr0xbBkiwTsz8KAfK0EExFRahPgINb4nCzJNcgUFW+laqiso6rja7Vnoxlzyq08Oh/wYxznYiHxV4D/qqrXAM8Ergd+DPgfqnoV8D/iY4AvAa6Kt+8Cfv3TeYO+fVJ6HCwFfIa2jm241cbl++mYjg/GnCpUXrccCm36GROsMgFHnVahod2Rh2D2O7YNp92SWPiIISJ7gBcDrwBQ1SkwFZGXAS+Jh/0W8D7gR4GXAW/WgLP9y1i9LlLVex7ufcpFuZI1YSKdJ3u0S3tMZpvSbYLbX7597HzLo0+C5QmDbRMcxBumzjKqHCtxBug1AOy3ZlVQeDWe0ahh1UwHM40/2xXoicD9wG+IyIdE5I0isg5cmJIi/rwgHv8E4I7i/Dvjcw8b6b+/ZF9Awd0q6D7zzN6kV2Eq8TtWp52i7I8ab9ic1UydDcOpUVxj82p1ZfxyGv8PuP5zgFeq6gdF5Fdoh6t5MY9ns60pEZHvIgxxXAb89Ute+yj8qsv4X4mzXYHuBO5U1Q/Gx28jJNRREbkIIP68rzj+0uL8S4C7+xdV1Teo6nNV9bmHz9qvvoxPJ85qBVLVe0XkDhF5iqp+Engp8PF4+xbg5+PPd8RT3gl8v4j8PvB84MQj9T8AX/6B78/3kw9Xmjkl0HuKeWRCr5IB9DuRDdM1vUahcAnY5rTW1GjgvW/FnmfaVDSNYevkmNV9E5rG4O5e48jT7uPLLv4YM7W8+jPe+Uh/2sLHuVgHeiXwOyIyAm4GvpVQ+d4qIt8O3A58XTz23cCXAjcCZ+KxjxiJZVEZ32GgGpTKuAzX2Ck5jGjG/jyc4EL5eqO24+JTXj8LWVUwrZQn7D/Bncf2IWeEz7vwRp44vo87Zgc+nT9t4eOsJ5Cq/h0wjzT30jnHKvDP/qHv0ahhNIe6vFOUJnTtYmK3Ud7JzyuLN/QYrN6FGdmsSCpjPKO1KXtHm9zJPhBwGCZa87SVu/5hf+SCxiBWokMyGKbO5Kl7er4vBPZwq9Ap+pXq2MeOcv2v/ikYw/5rDvOsH3gBjTMcff8NfOp1H+Cl/+kVGIKkXuMsPu6lGYGVuuHgeINR3TCbCDedPsRl4wc5sNRIXJy4/8w64yhnVwof9JU0dloghO1JU26GmsP7eca//cfYUcUnfvZdHP3USdauuIB7338To8O72WxqZs6y1VQ0UXuxsmEBc7We0XjLpfuO84mnjh+2xzofYxgJdGwPNlJn+jK9reFJ18M9gc8yaXCHBFIV1OyFTWATzrgVjm7spXnvvVTXXs3s3r/j6KldQeAzrgFVxuO8sKUVlfHcfOogG9MRKyszjCgztdw2Hcb8cRAJ5LZsoOho4IVp5HjlULIlE5LEnugarGT82Bx9odiET2+/h+mDE2a7LueB3/5TDn331+P/64c5fWIVBMarM4zxeBGqyEPLMnhRZubByTonmjUuGi1pPQsT9eoMY30723K2xeAkrHLSKzTBwSdHQSZMj8OJ2rr6OMGdPsNDv/MODn//N7D1qU8xvvoyZGTze6gKzgkmOHszbYJW4lZTMa4aZt4wbSwnNlc440eDGcoGkUB5pzuCvFxHWq4FeKXhrM/SSOF9OfS1iMJGlQf/w1s5+E1fxPiCNSZ/ey+TD13P1kc+xezuo5x4+x9z8J9clzlh+XzgzLTO0/1ZY2nEsNGMmY0G8dEPI4GCFeUcDzC6RMKUQFBSgVrhgzy0xWsmfvvpv/gYWzffybHf/WMQOPTy6zjw5c8H4PZXvYlD3/BSoKVJu8h29d6G6xIchLyzVHWDEc+aWe6FLUwknwyQjktPspr0BbB+nmKHajBpaZPHxGQLOod7XvQZ7HrhM7GVo65dPDaA+C//2W+L5ixdVGK4sOCnFp2a7OmaYumVsUBRRSAXsI2wZ4wPivUxKcqKU0YJik9VqrUsiKLh0cglaSha65i5dsHROVOQG32kVBucEnqrRvCNsNEMAwsEA0mgJCwuoh0plzJcMZQB2J5jYJJu2VZFiusn2o8vkqYUTiiBY+m+sQ6tAQUvBrHK7nrC4erk//4fvgAxiAQa100Gu5eIwRb0Ltk3A9oZ+7yZUKkFVA55KYIJiyORMlTDUNdX5EjXShUJo4gqVe04VJ9mXYah0jqIBEqw0tZYxXf2utKwlrwzmkg5tr0EKRkY5UJjSjSnwsh4XM9LSkSZzGyncoXZnm+b+8hQdc7w0GyNB92us/qZnKsYRALlISZuZVTiI1U5vJ5VyLzJMFQXxcAfbjsjXWfmbYBxpKrkTT4v0YA2p3WnYU8KaT4mm/chOf3Ucv901zKBFimSA3L2yigB9rQa0Y2xHeed8ieQEy6fm/obCavLTUwcE/3IIFQzK8pK3eAVpr1tlOAXbzIjAxXqgnZ0vscgEigB2/t+GdAC6wN/SzvAemAbpge22zu11yrozVKyVD3roymTpsJ7v+28hKl2lWM0ajgw2nhE3NH5EoNIIIjsz7ihmZJm3ppPGQFwtp0rll+PFc2rYHQ7ATFJ/Y6Mo9G4iWo9XlsHRK9tAhmj7F7ZYn91ZlmBFimMKL74ctOXCqkxDkCzxitTH/5kg3Y9MHoJ1xR9TkqiFKmfSkwQCNQfp10ju9IiMzGXopUAACAASURBVHmHjayjNs1gRDaXVgcLELK0OljG4zUGMYR95Qf+GZVxkf/uqGODu+nqDK7fKTyShyyvJj/uY6bLKHuhLVd1TO7OzOosYN6kYU2CyObMWa46eD+ff/BT7LUbvOIpf/nofhCPQQwigUwBqPca7AiSxWU/d/qg+9IfIyVPmUDh+l0QfmeGVWCwp01NbTyTJtB9RtahkKk/EMD67tMA/p8vMYgESms//UpTGxctDJL/xfzkgTjdh9Bwx+NLC+9wTJzGF2tLVeUCoN9bps4Gjnzyjo8LlluzKm+PNN5Qi2O2dCxcnEh89pQwLs68IKwU20g2dCqt0AJsm4W1913WBXrwY/fx0X//54gV9j3lAp72ys/lv3zJ/82+qw8C8KKfu47R7jUmrsomc5V1rMb9OZ/2xuIqtosJNJQYRAJBqCazIjmm3uRhzIjPVaVdDAwQ2HkLiUBOtPGFe/jsX/4q7LjiQz/933joxmPsfuJBPu9XvzK/b7K4PDOtqWPytDv4aXgLlJ9x1bDl6yWgbJHiTDPKLNQUjbcdeZdycTEwUdv+JiVLZVzuhxIdWvbu5VRT4zaFRio8ltO3HeO93/sO9l17MVd+++cy04pZVOLYPZ52fOu9CtYbrFEaF6jXE61YY5lACxN3HN+HMT5qQ+9MHEy2A+n57AufXu8tJtbWMWkqjm+scupTD3L6gRnH9z2RJ/3aK6l3j7njdf+F2f+4l73PvxqAtZg8Y9vk9zCE4VUZMYu2C0vb7wWLk6dWM0WnxOKQkIAxOmumEbqRWBtIy+CAwOIwVWiUpw9u8cCb3sWh7305Z06sItWYyWll/Kxr2bj5LnY/7ylUUV7YSpef36jJ5nQZboJi+5TZ8zQGkUBiNFsztTwvQRsJ9k+2yJyCeZFpOz2gWQIDOUBnjgd//a3s+5ovw+7ag9+YIisWsZbNj9/B6LIjnNkYZxjszBtm9YxKfHZShNb2IO3VDWUrYxAJNBo12Zc9U3NUcJVBG9NWHpUW3K6QN628biMiysijjXDmrz7M9LY7Of72dwOw76u/mGO/9/9ixiOqQwdY/bIvwp82eODEzHCq9tS1y25BCWIybVov+XWztaxAixQdLehI8lM0s1TFKHO3/DzdiiTtT23CUsD6C5/J+gufGY4TBQMXv+b7W8KiekQc6gV1BtcY3JYNCZmA2Db8LlJ5Tk5X2PBjnCwr0MJE+m+HNIQVFgWZYQFITKSiSoWftD9TEmkvsdJQJ6laBdfDlJliFDEuPBeP8U6Cm2K8qQmOPVu+/rR0F8+HGEQC1dbhvAEMqgWY3gTQe64eEJOAzJcPzz3CG5Tn9I6VomoZ4xHTkheDtVSgEPnGhNdEl1sZixaVDdrMjTNZPR4MxjoohopcXGJ16PirQqeplpLBWiaNaJy9dZ+T9FNaTpmJxxjjUOuxNqi/1uKY6NLycmGiFP52XrNGT+Cqt19oyV1P1aE0mFMl+64mMYZ5taJlwgbKcnqcCIXpmJR5iWMvcXvkRLN2Nj6GxyQGkUBp01OL//5KhUaUxhfrQrRfcKoOXTIgqASKs1jmN96xDzJFb5VYqPO0iVI4F7wyJk3NyWaFVbtcSFyYGFcNzhtmEWZqaVei0389tElUVhAfe9nSFyz5rrZeqm2CpR6nJRGGBEpuh/MSKCh8BN5+bR27qi3WzJJYuDCRaDf9bQoAkYjFkdYULn3FRpQGg/cti7Qf3guaePVGs7luOjYlj0mmd2gE0ic8dLtha4yyXk3ZazeXm6mLFI2ajh9YxvE0VSD+ZZpOV7ouO+tIqA6lvEu4L3n6n4atfq9TJk/pRZZ+FzDM4t5q+B2HMX1PsQTVL0AsQfXLeNzGIIawL3zPD85V0sgw0gLS6koh8GLIS9jmmQ9yvaVgeOlEWBrZpcclVHZkXOSgtbyymbNszsLq89MP3Mtz9twGwCuf+t6z9pmcqxhEAiWRhH4CNd6Exb24Ou2lS39OCZAgsdBieGo1OQFnRZJY6boXpnNKB0RRybU9NdA2JtyqnUVM9Hwl/PMtBpFA0AWOZcMVE+Cs2dfCG5DApBhZ1zGmS423SV+4+qzKkaqJkGy/febH5wadLlsj4X8SY9V5E9XrY/O93I1fnEiuPOXjUBF8pvaEPaj+ea2Pajq/sj6fP/UV93/kfq5/3Z8iRli/6ghP/r7P58Tf3MJtv/dXqFeu/t7PZffVR9rhytssvDB1IQGnjc0Se8mpcIlIXKBINBvf859I/Qo0TH0Vhixth6l5VCAI60oNAZS/dmQXz/rFr0Xqmut/9l1s3nqUu/7oIzz3334VYtMw1/1dUqSKZQLWrdUUwuOWXhmLE/PWVkoOV6goDm+6PDAf+6J5kY4bH1yPjbejruHMx27HGPibH30H4/1rXPNDL8WsjHLilPaZVXTvSYqvIkotDofpNN7ncwzi38BrQUtGmLqKqauYuJozzXZV+JBQhsZbJk099zb1VZ69WePZvPUozYlNVvaM2Dq2wfP/zVdw4BlHuOddf09tXUcbEULiJhB/qkK1Cdw1i9/W8J+vMYgEmriKqQ+N8tTZwBKN0/Gpt0xcTaOtOtnU2facSOFJt3Ru49sqMT054eO//H6e+aOfT7U+4sAzLsJJxb5nXcbp2x7q0IVSSDGzCw11eN6grJst9pjNc/shnaUYxBD24Jl1gCzsNKqavN9VRzm6ckhrCpJhX/C73FQF8M7z4Z/5Y6767s+FfXvZdU3FLe+8npm3HL/hAVaO7O0kmxbT+dT3JBCZVxnM9D3FMBLolv0tHFVBRxpwyJXPErumCoCucjO0P+xAV6i8rhwnPvARTnziPq5//f8Egcu/9cWsXXs5f/XP/xAzrnnSj30FJ7ZWOoocRrRDLhRRGmfZEpipZap2yY1fpLBnwvqOChgHeiY8LwAezExQo6iFRgootKUHdW05Yn6kqFW48sVc/Asvjm+knLQKL7iWAy/8RyDKsalijmkGlgVvspio8fdTAh5odTTD4gOTdSCVaBAJJJcFzUH1QuOlW42cga3gwSQqLRNDFIlcMkmwVZV8v5q2OOikhaAWytl3OlY8GfbqLDQWfK3oSNGRR8aOqnZU66HvseKX60CLFKur07Di61pTFRstD7wXZrNAs/EaWBJ9BqtCTqBMNIzMCjyBVVFWqILNIY2Emwv3U9KZqaAePIGX1nhhq6nY8hUGz/oSD7Q4YUTRgiZjjM8kChHBWkU14HRUunSfMrKifIkqjNeht2CYlo+SU6L6cJOYuOojnSdWRJ0aNiYjTrsxHsPEL0H1CxcJUiqQxZ0A6rrJx2RsdLlmE++7uHmqOyVLAUhL13IuIBZDEgUSiDFhXPTOBm5YY4LroQui5FOt2PDDcOwZRALVlcMU+GWbKTlR4CkeZyKyENoZWDmcSUweF5U5EoMjGfKWiZV+GhOB+F4wdbTdTEkaaUUqihpDXTtGpsGrsLWsQIsT1nisScnTzn5ELMb7nFBpJz3tUfmYLPm1ohKFPa6w3SEuVBhPYH60+Olgs5nIgxDB+K7FUQP4pu28G29xmCUmepEiQS2Ii3Y2eXcBpiQWxuP62ofpGn1wmBRJVQ5d6TWAJiZX4xXnDCYC7zPMI/ZGKKyOZuyrz7B7IKvQMJAESvtNpflbwuOI8Z0qk8BgQIf+kyP2UHWpTp+8LgpkYgkoyx5jBTcsbZ42jQ0Ne6yOSR+x76x4vsYSVL8AsQTVL+NxG4MYwr74ff+8A5aH0KO4iGtOQ1EV4RQJwdjodlxOwkFDKwOctRQLYH0ScUhwVReb5r736sxZplsVYpQrDz/IVxz5MLvNJhMd8T3XfOAcfDpnNwaRQMkErkwGIxr2wZBMRe0zNx7ODmqek0+pUu9Tg+1N3AeLs7PCPzX9TBTptWpKLY6ROCbnd+eQYxAJBC0MNXl4wXabpo6lE9J5LtOPRQMMI37BJ66/h0+97gOIFXZffSEXf9FT+eTr3g8Ik6MnufirP5OLvvq5KGHXw8a1pqwCayVvq2TrzQEhEgeRQCW9Jnt8icuVp+ntfPclgOd5Y6QFx/Uju/isX/pq7Ljiw6/5Y2wFn/XLX4uq8Hc/8U4OfvaV+Tp1sTwQ8NeB0dGHjLiBJA8MJYEyqL6bKHm4Kr6/eQ488x6nc8cH1/PzYgUx4bXZ5ozpsQ32XroHj+tWsHlDYvJbFQ1D2ECm8cNIoKRCr9v7G2iZEuWwlX72q0//3BSnbnqA6YkJu64IHhkP/n+3cPj5l3eIhDvZJngfduRLxsaSF7ZA0fY8bttzZXgVPNupP8CO7AwImOhP/Mr7eParvyhf9/4/u4krv+E5+RqqXf/Vfoh0q9NSJ3qBou/jlf1Saafv7XF99mi0dtrBQcc3nr9/zX/j6d/32awdXMOIwzeOjduOceCqg0x9uI5IUKDXORUty+upMNGaDT9eIhIXKRIWGbrDE0p2LOxTj1OYh7Fe8irc874bOf6J+7j+9X+BIjztu59PszHl4HMuyQZ17bWUWekK1NvxP9OMOOMCjGOZQAsW89Z3UhKl6Dsvl8f2+5fEM7vopddw0Uuv2fZ+h553RYdtulOUa0JNvKZF8Y+oLXx+xCASaNLUnWrg7awzRU92Tv2KUUa/6c4OhjGy62FvdTrdL8/1SF6pLlewU5IOBcoBA0mg247v71SQ2joqO5/9WX7Zadsh4YVKJmnfLzWdW6pzzLt22uZoklxwAVgzotnqqZZm2/nnYwwigY4fW4eZaYXDrYal5Dm4Z+ZVINFWCxGC9ZMEMfFSD7pzfkqK0kqBAGdtJYXDNoZzBhtVP3bZCSsyW/ZAixT1SoMfmaA+r8m3gvwlqytYoxmTmp6LD72AS+LRrdA4/Uozj51RhtFCBrZdyLSrYa9uRWZY8Uul+kWK0bhpbZ4AWwxfidSXFvNSuOisDHEazhzLjISBTmD6VKAy5jq+Z1S9TwwM0rGuPUd9O3xu+PESVL9IUeo2pwU7WwwlXlpZXohQCxuA8JnTTtfWwNjy+Pgz7WsV75eoQHnnXVsIa0q6QPdRRiZIu0x8vRzCFilKY5MENy2Jg9b43NCG5wJjQyVwxcrr9LWiO2FdrnTdY1stauMDe1UhOCj6thnfVbezr+VWxgJFbR2NC//Rofpoxj2XADHno0prr68pEyat2ZRGLF2OWDGrKoayxMxwGhvvqMcY8qv9HSyeWprBzMKWmOgFiCUmehmP2xjEEPbCP/4RgI74N5AX9JxKXiBMYK6Ho9WkhcRZxDqXolHpZ2qPEh06rDxHd8K4Ap3WgFxjGY1nPPuiu7juwMfZ8GNunRziF5/9h2fpEzl3MYgESokzMq7TPBvb9kIpKdLqyzxUYidUqOOKc9lHJbJhvm5M0HARg4nOiQAm2o37SD4cmwanJnPDhhCDSKCkBlZWH9PD5mQqc9zyaOgiCMvti74AQ2K9puf6G7cJzpFCRHNvYEyY9qsKqzYsIh5r1jnZrDzKn8JjE4NIoKQYn/HQpXh4UVg6oDFP9skoNz3DS5KtEAInvrsJmxKug/vxBo3Xsgacb3HR1iqjumFsZkx8zUOzdU7Nlgm0MFHigVKkHXVod9LTsTAfiJ8SydKC0h742H1c/6t/Csaw++oLufp7X8z1P//HbN13ClMZrv1XX4rds04ZTgVr2mpm4jrU8dka91T72PLVYCwvBzELq6LXxbzhJdx8hGdsf62MxJ0v4bCrF+7mOf/ua3jur/xjpsc3OfaRuzGV5bN+5Wu5+IufxtE/uT7z8tO5yf6yFPH03nBitsLdk30c3drDQ9PVs/ypnJsYSAVynb2wsvpASQzUDGPtEAcL05VuNTKsHlqL9z3GCoZ2puc2Joz2rgSpYNP2W8laM0U25o1D3pmmZmM2jL2wQVQgiEmDUomjMq4l9hU3SFXGheMkCD5VxjGyTa4g6TayTU6uEzc+wPTEJnuuvQQ38/zZN/82t7/jo1z44ifl93feMHPtHleYyrfajYH06B4RxXg+xSASqPE22xwkRfp5XK95LNU8bInPyvLp+NRXTU9O+ORr38fT/uUX8tBf30q9PuJFb/4mnvyK53HLH/xtOJ4wE6ut64lcaZ4RNt6G6hcb8yHEIIawFCPT7Pjf3TJWd97EnEsIbDwffs1/4+rveRHjA+ucUqj3rGBEGe9b4fjHp3n2lkQbpmoD1YeAdjSmHSLHpmGtmtF3FjpfYxAJVBk3t+J0Zlo9tE9tXJSy2/5Flufe876bOP6Jo3zqP/w5CjzpW1/Ixm3H+OAPvB31yjN+7LpsI1VCV/tLhVaUkXXsqTZZtVM269Gj88c/xjGIBFqxDVPf7T3KaJvktrlOybMTyD49/4Trruai657SOe6CZ39JYZHp8drMXSvCG2zqqaxnZBp22S2seGbVEg+0MJGSpxy+siaQ+A5jtYzyCw9VzGR3Qy+JrBgAPkG1o0iQxDdLNlPaJTdWJaAtrlRbUdbsFmtmulTnWKSYuLDD1V88NOJDItCrDMX91EhPffej6NB2aBvqPqsjvZ4ZG3FVPG3Gzlw7eFbiWZEZ++wGo4Hshw0ige44vi8s5FnfoeZAt59J0X9c0nRS4qTpeDqyVCErd/v71ymtwJNXqqrQOMPYNKyYGSNxS8vLRYrj9+wJdxKVx2oAvpdI+XkjRme1r3hO4k666DZgvSb7gjkofKl9YIREilCpM2RWlLGZsWa2cGo47tYenT/+MY5BJJCsNhHILh3Ae2ZI7LRwl47zwaagDDdNFJ+0WUr7eB7fDNCtKuSUhJtLSWiVunaRO19xytccc+tzr3G+xSASaPfezbyb7n0Xu1MyNhJ61/eGnvb56Hsx702KShSIh8W5ibXhiuum6jUzMBVm04qTzQr3N7vZ8vXSbGWRIgG4OjTiZPzWA4yFGZGnDwXPjI3oeyHFAmBpspLA9iX+J7n1UPnO7xG2MQJh0XvDpqs50azlGdwQYhAJ1HLCNDaxvkPtATJ9R3P1kU5F8r5lYiROWMnMKKN8PlN7RLvVKw2dBcXaq8l8sDU7eZT++sc2lqyMBYglK2MZj9sYxBD23Hf/ONCu55Sg97SolzA6Je45N95zirCPaz5hSCyej8wLU1w/aQF1bDRVaBpD01jUCeu7J7zkkhu5YHSKWhzHmnX+zbPedvY+lHMUg0ggaOEZQm9hkLbMlvrMaWtBI4S1D/VwRV9VLhwaAUzrQaaJwxxlfH2xbGBMXFQ0gVbUqGWmFqeGU0tQ/eJEYmWkGVcf52yNxxIoOPN27ZVg/ZQiJWF+vXdObX3ndZFWTNzQVqDS5iBVLKcGxA9GbHwQCSS0ihyk+3FPKnHFVAUMHTEF6CZOP1SFhz5+L7e8/r2IEdavOsKV3/sF3PZr/52NWx5g5aK9PPEHvjjyz7pDI4Dxgq8MTiIuiFahbJcdhszdIBJoXAWhggSxsAX+GFqPCqt+x83QMlLyNWpYP7Kba3/h65FRxY0//585/dE70MbxnF/6Om77g7/h5F/dyP4XXNVeQbSoLqbDZq1MSJ6xmbGnGsY0fhCzsDphoAsBzL71QGJulLQea9Lma/eWWRbiWT+8wuoajKzDVMLpD9/KnicdpBLP/qsPcvr6O1vMT0/cPOspGs/YOtbMNPy+4thbnTmHn9DZi0EkUBqyauOCwGbxhZqYCAlInzDQZZ9U4qPL5yQiGY0oZ26+j+bkJoc/54kc//s7EVGO/93tuNOTbKPZN1WBth8CGJtALrR47HIlenEiffEJE10q0IfX55vsQhj2+kNYMqODMItzJybc+O/fwzN+8ksZH1hn15UH+esfehu7rzzI+MBaZsBmldYe5iiLM0jrmeqWoPrFiRZeWlaUh1egT8fNY0ckVXsjynQKH/25/8LV3/MiVg6uAcpVr3ge8Dxu/I2/5NDzr8iY6Mr4ONWP035t1dFq67JCq8NQb0NNn58xiAQy4jOdZ76dQcFI1e2M1LnXjEPM/R+4gZOfOMoNb/gzAK76jhdw45v+AjHCoc+8hEPXXkDjW5M6a8KaULiID1P84npWPBa/bTnhfI2BJFCwegrDVluN+qyMhHOu8nldJGI6Nj32arj0uqt4wnVXd77ww6/96mI3vRVoaFL1MS2s1UjRsKMYImJyjpvQ+RjDSSDxjGw7LOwEl+gPb6nJDrho21Ood9kmISdhx0s1nNd4C9IKN8y8DcJTkKG2AUxmWTEz9pkzS53oRYv0BZfUHVvwwTzCzNs87yzVPHxWw+wzNTylE2KjJleZUY/pUS4d1MZRGwdNzcxZvIY+bWxm7DET9pgJKwxDnWMQCTQyjqm3NGqo4u7XNnEFNCSPTxz1VkMo90SJ0qPCig2ceW8MXsNCZaOGiaszNdnQ8t3xQX8oVTQI2xY6HUW7S89us8ma2WK3mWZbqPM9BpFA0E6hyyQKKlJk3zBXDk9oToS+CEOjlomD0Q7Iwfa9bJzyt7SedhM3XS+cUxnPupkyirOv6TCW4IaRQEc3d3dUMVpYRwHpKBKljH4TrUUy9F15DNohMSb6j4uQDuelg7f2KswaG4xWJOhDG/HM1HDKL3fjFyZuuuOCwMawXdednBw7mOGqBiMW9dJ160nsjp4nhhhtTVigNWVRCZO/RPVJkI4osmnHjomrmGjNKb+CU8Mxt+tR/hQemxhEAqkPXC3dKig3QhgsBFpwj2bKjRjtGKQo0EWOCXlVICaE9hME2s0gq+F9XKIXkU1XvFE2ZmOONbuwhNnY3bP9Z/UzOVcxiARa3TOhaUyHF1aiA8swBafLe8FHRof01mVy1dIWfB8etxLCffIgGocwUXxjEKP4SZjie4Lh7kwtU7WD2cpYguoXIJag+mU8bmMQQ9gz3/kTNJHbNS+MaTWfyyjhFzuxVRMco+vYw3b/sQRO85KtLgFmkwpTKZdf+CAvOHQLB6oN9tozzNTyfU99///y37woMYgEyoLh81iAFIrzvS+9VFO1O+xNKduTqP82IRHTlUz0Te3RnAlAsnnQkvM5BpFAWaPQuk41yIa5eVrf3ndeMgC+fwwE+k66lifO0uP5eTLWY3KUetGNiV7xtc8Sv7W47Jm6dCxcoBjXTbFAqNsWB9MX2w2Tj+8PbeEcwmxKlcmt93Pnr74bMYbRRfu57Ae/jHve+Cds3HgPq088wiXf/Y9ychrf2i6oKKNRg6pQG5fhsk4NbiDt5yD+ipF1224rVcNaPWOtnjGyjnFxq03YuU+SvFX8Oe9WW8/uy/fx9F/6Jp72i9+INcrspjthusXTf/EbwTk2b7g7/y6pgmWhqyjyUJmARhxFt8Kl5eUCRW27Kq0Z31zsxPcjbWsklbF5Wxy5klkhLktiR4Yzf38zBz/zMmrj2fecy9n85J3sespFeU1IYpPkvCDeIBIkiNfMFmtmazB4aBhIAs0bsmwBFutzwTSuFKck8SqYOTO0dL4FHvifN3Hzm/6MtUv2I4dWGe+qqK1jvKtmcttmxiJ1SYo2X2MUmSMWjeyPYSTRIBKoVEidpwk9LxI4rEpCnDtssqZrHfmcKznyOVfyide+F1MJujkJsI3JhPGeEXVs4MvfxRf8NI9wxo9YkREeMxjf+EH0QJV4RsYxtk2m9owivQdCMpT9Ue5vjMs/y9s4emRkz7DZLNuJj3bVGIFjf3sH1nge+tvb2f3Ui/Lv0qcI9Zv3M37MxNec8Uuh8YWJxI1vUYmt1G9CDgZkYfh/GRk3ty9qCkaFL3b0H/irW7n1Dz8EwPol+7j2h7+A63/1T/ngK9/G+hMPs++pRwDt4I1KeIg1QWS8FkctjpnawfRBg0igKvqB9ZmhFDOd8IUG9kaKfpNdgvDLa1384iu5+MVXdq51zSs/r3ifJsJlC5tNbaWCJfdSnhUzY+LqwSwoDiKByng4yo7X+QjDvhVCSU6cV6nm9U0JGitpnae3NdJ4y0wrZlHiZWspsrlYUU67H+4Yeusv6ZzmYbw2OsfTNtclfLVUBlEnGc0YLKB8tricFkk0hBhEAqXhaycf0ln0E2vmzBlSpfl0hpTErYeuT6vXuIEaq5U1ngphFNenbPzdamniQqIbyPRlIAmUfLpm/uH/q+dVqP+/vTePly2r6jy/a+9zIuLe+16+KaeXI5ADZJJSzLMWlkKJXX6wPi2tVW2JNErTQ/mxSsvSj7aK6EctLa3CUluqQWi7FRFREC0QsZxalMERMIEEkpxeji8z33DvjThn79V/7OHsc+69mVnmS168k7E+n3gRceJMN2K9tdfe6/dbvyyoQn8GFRJqt+P4klNfylyWHLJENCyv10TBlpk0HLanaHQUX/04HGjI0RpacBCz40f1KnkBcMhMTU5Z2pBUWAEL7UD2Q1WguQtfb+ihaJhIy0EbSIVjWQcahQMlRmn6nw8l43Tn0DSUCId+I/K8Oj2IWP2eQ3XvuG6fMFwunA2MDS/YynOw3uSwPRWYGXge0JVWxtLYicUs9yQsK+up8VNade5JOKng9hCc240SlJxHB+corY3yTmm/xtkMLEv7OjWc9GurCLRM9tk7Lwj4HB8lB5SsuJO12zM2KByjXvJ6Tc+GeZJ2GhnZObXbLgKUiMcBKlJi1/tTbpr58Ntar6bxy2TtdtXRbwpwYFDLIdN4gB6DQpWO8pMs7t/bN+4fnolyT9ptVsB09KJM/VFQI7ipyetAFqWW0KlsDLZiZSyBrVgZK3vc2iiGsCe/8/U5WRVRrPWZiZGsBMaXslBDTHR4nY6hd3xpiaCYch/vgyYYBPC+dxbfhmP2HdjiJZfdxDP3fYHTfsq9zX5OuSn//hm/dga/hbNjo3AgSFJPg2eKynh2kJS09J1nN0JHyXD1vttmTLci5Au2RlVHUJmC94qYIEI3rVxECnRLCqtSxhJZVbkMm0j1J7tLBEqtVoYdNHazTPfJ8I5ufakUWjEqPTqRz5FOcBhU4/3g2dYJjVpqcatO9ctkaQGxsq4Hah+CuZKyThKUeyhzXrJSJe3DMAAAIABJREFUz9bNd3PLz/wXsMLs6CGO/ouX8Nkfegfbt9zLDe/4txhbaGVo6ENkbVhSUBOAaFPTMpMFjVjW7TyvM53rNgoHMsYjKtS2kxVIw1cyr4JjbwLh0KSIOOtXHOL6n/4XANz8U+/F33MvT/3xr+dTP/QbzCYNGJtzocaZ3sxEVbIM+STywgAaWQ1hS2O19Z0qT/yxrPG51VwbV5wr3Yl93ssyohCQ2pD4ZmZi2bjsILMDEwzK1Dp6JNTBariLK9NzX7FQG5qN43LD8XPdRuFAJbQCyM6To01s/pTKGaWV8NNkXiUzK1RDGeO+D32GW3/xj1m//CDTg1Nq6xAJbFgvhbxTjHTpWPVhSPMqNFpRS8t5Zms0vLBRrAMlCGodwfI5AkUH6rS8upa+qdhqJThbub2EtgZyoePiFz+J57z5Vaydv8HJD38mAO9jzawqk+p4fG0jQ9WG+yohskb8aNr8PuYOJCL/SkQ+ISIfF5FfEZGZiDxRRP5cRD4jIr8qIpO47zS+vyl+/oRHco3kLElopTaOSRRXKZ0oPZIqjxTDXRJWgc4hs0O1iyzeUm9MqGeWSjxC54QhIinTqmUWH9O6YX22YN9kzswETvxEHKV687luj6kDicilwLcBz1bVGwicu28Afhz4aVW9BrgfeE085DXA/ap6NfDTcb+HtapwgBQRShhHqd7zUI/dpJ+seI5/5Gb+4tvfwV98+ztoHjjN+c+8lA/9q3dz4qb7+Oi/eTenbrwjR6Re22Cgsp7zJttMExKRgCHadKtq/H/LNdZEpAHWgWPAPwL+efz8bcAPAj8PvCK+Bngn8J9ERPRhCnY2ogNLNmlpj4RsaER3JRgCXPTiJ3HRi5+U9xNRnvNT/zS/D6ahuTjQOkvjDd4batuyYRdh6r5aSPxvM1W9XUR+ErgF2AJ+F/gY8IBq7N4NtwGXxteXArfGY1sReRA4Atz7UNcxouhARGU3+g7QQw3ukIUaAOXTPkN7qJlcwgEt2iq3/537irmvecCtY0SZ+5oTK9HdhzcROUSIKk8EHgB+DXj5LruWdYa9PivP+1rgtQBXABeK4osEeEh1PhPmsqOFKJJypFLioPEW54McQlr1bp3hRDPj7sV+tqsucV7hgR6ZfSXweVW9B0BE3gW8EDgoIlWMQpcBqT/KbcDlwG0iUgEHgOPDk6rqm4A3QYBzQAdhTVpfwK6Q1p0OtQvkdY/hpYxkPehssYwgopk+XVoaslIetFGNo5TxWM/CbgGeLyLrEpZ2vwL4JPBfga+L+7wKeHd8/Z74nvj57z9c/gOhdcrMNp2sJYXMZcHX2k3qsoq9giYFn35iWiamDbO4mJRPbZs590FHw+84z1rV5NmgQNaWT3SgdTtn3c6pTctsJICyxzoH+nMReSfwF0AL/CUhcvw28HYR+eG47c3xkDcDvyQiNxEizzc8kuvMbJslKkvyYEqek9xSsgycjwuL5SJkcrCF2/2r8bE1THKKNoq8QHDkgIuucYnxYWFfPedQtclhexorntN+2su9zmV7zGdhqvoDwA8MNn8OeO4u+24Dr/z7XGfX2ReJouNyVd2p0GtIH8scbfGDVuLBtvn9bLBabUTZsEGBecvVLLzNTtd4y2ZT07SWwxubHJmd5qr1ezlcnWa/3Yqw1nGsQsNIShnQ7xEEfYdqvaXd68DBOSCs0wwj1vA6p5nEcxsWviJJi9cmQEucCmtVw+Vr93PZ5DjbWrPta7Z1wkk/43i7cQb+6rNvo3CgBxZrgbyHZJhEr0XdQzSfeqjpeto+jD7D16lV3pyKeVsFLpgo61WIUif9LEY6w7aGKf3cj+KrX4Hql8FWoPqVPW5tFHH06re/IUAn4vvdBqPcpT4OSUPdr/7OdFpgg+2BpBiw0erpXiv4hQ08s8qz/9AmN1xwJ88+8AUgrP/st1ucdGsAPOjW+P4vee+j/MvPvo3CgSbTFu87TE4Jkh+O0N4bxAupdULOaaQvE+ULinIyMb5gY/T1NJwzmInDzy2oZCd2SK6+OyQvKG66VY/EpbFE1UlU45LSU0oflDZEDpaMDgAT8TzJS9J5dxNZEVG8i4GsILBWxnFvsz8n8SEKbePUrJpsLqMlx0mUHiBGls6ZggMEgk32hUHUgi7CiMDi1ju5+xd+C7HC5OhhDr7sWdz9i+8HMUyvuoQLvvnl8RoF5Tk6573zfVTGMTUt3ggHqvGsAcFIHCgRCSESC2UnpQcistWm7QYt9imHr2RV/LGrKw7zpH/3aowot7/x3YhvufIN3wRVzR0//S6a245RXxZa/WprIi9MOD4Paz0T07KvnlOL50C19Yj6WJ8rNg4HkrL7RscLS6a9hcBQSXd+589YDnRp7UdEqWpFpMUImNqyftlBzNTiVZFKsJVQ1w5nFBelN1WF+7bWqWNtbOErJqbl6KxmZpoVqH6ZrCp4XqGpZadIqvQlvW18X8Ucx+8RDEqnq6znwT//NLe/9Q+ZXnqY6YEZah2nP3sP7sQma1ecjzUB0rqwVSbBzpuK1oT+0ZtNzdQ6tjZq9tttpuaRrI0vv43CgSZVm9vq2giuz5z1gpeVVpWTzzhvduhodNZfcT78gqs5/IKrufnnPsDJj3yajS+5kmNveh9Xfvc/pYpt8mrrsNbjnMlsDlXF+Zp5E77qW9cPcajeZN0sHquv44tqo3CguuCqJ2xz177X5O3ZgeLzUKl5L/OLFjMJX1W9PqGeCF/4yfdwxbe+hI0L1gCXWa9VFZwpC9vFJlbeG1xruH++jlNDvYJzLI8llUDoOGEpAmU8EJqTnDAP6wvR7TbVhzDcHf/o57njXR9BgLVLD9GennPq08e49c1/AMBlr/6HrD/l8kiHDlx9kZCbubgmNKlb5lrRODua/AdG4kAB29OhEneLQABGwz5t0ScjDW176syLcuGLr+LCF1+V92mc5bx/+LRedw8XFzKt8anDXmyq0BVz00xvfSSNFWAkDlSJz2WGhA6sIv+qrPalIazC56bjuzFTSyuhq+mR4BquEGdREYgc/VLmQERhAFqr072NwEbhQHvReSrjqAhTaCA3EEdCu5WUD5V9pnfTxigtRau6ANVDl8g3zuShMc30VLv9Dk03gVDiGIONwoFK2w3zUxU5RylJ0Pog0V227bUFOzVZcrS0PfcD8ia3qxK6RD1BZPqlktA5LSwouhUvbJksg+ULCOsQ+NWBv3yk3Ziuh7RITyss7NetHSXsdOLC1xKOa6WvC5Y6hAzXl1IupKIZQrtipi6RZfC8KYTnBkNajkqS8h52ohN1Z3f68hpWfJZGCAeE87UaknLvTS6uWhmugEtsvuBDQXUkUKxROBCE3GXhq6xYWGKjezhp3QOAP4hYpWxCud2gPQB+ik4psU621yp3LZ4NM+/tey7baBwIyM4DpVZGcp60PRQ6K9Op6yRKc4Jq5BnSLr9xIi5mh4tDn4sr3o7QVKp1nahlWglX42nUcHd7Hg9GYNm5bqNxoDSE7eY4CdBuxNN6W7Rx8Xl7SYuGnTyyVm3OkxIDNvf88UFWAUDjMOa8CSAz43FA01im0xYryqafrKjNy2Qz2/R+3JIt4TWo5xg0v97NhnlTT8Fwl85mpaW1nmQJodg0FvUVvjEwt9QXnGbDLmjUsj0SB1qxMpbAVqyMlT1ubRRD2JVv/VFoylaphMJX+V7DQ2qflXvUS/dapc/OiBhrkgIPBNCa1Q7VmJgbafjygFVMRDJm+SnCec6/6ASvuOJvmJqGua9XrIxlMVN7tHCKbH7gFBKkB7QlyzZlIPxwap8cSovXJrzWEgumg9cqYXko+VwC2Xvh5OaUk27Goer0KoleJrOVQ02k4UCOCEkoLpmYblspHicm6FqkY5JoXXLGxS13cfxt70KsUF90hP1f9WKO/+JvghGqi45w5Fv/+9CYPB0TO9SbymetMrUe11oeaNa4dtYUDavObRuFAxFRhkIxWvmBEk+i6xjt0XV6p8kRh3hccIj64gu4+Pv+V6Ty3Pef3wltw9HX/8+IwD2/8E6am29jds2l4T6K1UNjFTEeaxVnAqjs/sU6x93GSupgqWwwjRbRsGLY43T5zF4to0yyXWfpJtKDattRf2pLdcGBnDtJVWGPHMjXTQoGIhoiW6YMhXxo29VYdjrvuWqjcCBjFFS7H1U06IelCFRomqqCYlCjIYkeBqMylBG5YZWy9Ref5P5f+10mR49Qnzdj82Of5L63/x6To0eYHJhlsFl5Dx1PDUQczhnmbcXUNKuV6GWyqvK4GGWgIwUO9cCSo3ivO8Tk8vvBgqDGBHv/857MgRdewz1v+W22/vpGznv+dex/3pO5+82/zdZf3cj6c67P10qOM2TIJpRiHdvwjcFG4UCpS3xipHaQiv64FIavUKrwQ9RgsVcGxDsTopQuqCYGY5RqY0JVBWyP90K1McHObM6tEmzVGM0N0AEWbYUYz8y2WPxoYK2jcKDECxuSCp0fRJM0xbaamay96BOtozh71AhbH/s0x97zIQCmlxzCiOcL3/eLoMLkksPsf+aTcD45TmDJGlHqylFbF4RWnKWqAqCsUctMVrywpTFrfMD3SHidWuwaKWAXmc5D/CxtDzgenxPsDmAvUYXn0Auu4fALr86O6RX2P+8p/V7ULl6z6Aqb5Kdq49mO29dsQ6Oj+NqBETmQ84ZJ1WbFHq+CG1TUnfY7dXT5Sdzf793JI10nXSvJXRrjsbFrR+vCFKxkw6brLlobI5OnlvaMNUA/2zYKBwLy//YSYO/osyogwUo7J0mUoNDF1fSGsywTlYbGeG4bG4mX56mtslk0G4fAfFVR5k2V4RxrtmHdjCP/gZE4UF0MG8P/2Ro/F1FMERVKx7LRqUzMV5LZwblKzS9rPI2zXVSLOU8aJlPO1fikoarM6pZ1s2AijsUKVL88lmZhE+MyqTDxsGyRpyTnSGQ/6HdaTTO3h9LZKBtTJSRiik62avEqoVNrkWul6fukConzttY9CfBz2UbhQFZ8kGpCEO33is6OMtDxStJOvW10lGfY2cUMuiTbiKIxQYYuD0vHlXhYJcBoBaiNi9z4cdCbR+FA0LEmqiS2a0BdRxos8xkAvAkMDbQn0PJI4kIYmkwviiVQfckh692fUTbqBetmEfsDjWMaP4qSsFPTdeGIIisT0/YWGEtqMoSIkZwn2XDhsSqWBPLwF/Op2rre8JccyhVST+m57Ji2z25z0J5+bL6Is2CjikClgEralqSYet3q09AWuexAr5MHdIl2mXB7lcBGHczk0nGtN2A8qpbWB7JiStBT4wWA0346Gkz0KBwo5ROpqUJykEzXsboLE0NzgwWIYMKiPmWjfzg1vZwqnadVwzCLSQuRzoeVZ+cM3vrYrFM5ONliw8yZiBtJ7F+B6pfCVqD6lT1ubRRD2Et//9uDZnyUuPRqWHhLE7ldOf8pK+0RUvpQfK9EIGwLznuZiJc9fwC224rN+YSt7RrX2tC1fh4647Ov5dor7uSbL/1TDttTNFi+5qqPPxZfxxfVRuFA95ze2NEX2nlDG5tdpg7zNlbL0yrxQ/HT0ycpAVYNU/HaOmzE+aTaWVovWrQVi4XFtRZ1cQWxCorSAmy3NQ6DFb9KopfJHnhgA21Mx6DwxTOEgTrhohNoGjq6TjLPzq6tCovb7+T4r7wzgOgvPJ/Dr/46RIQTv/tHbP3lJ7joe14XztsK2ED9gXBNmSX6s3B6McGpBNXCFSZ6eUwXJqjkQHac0hHUa8GvIQwpJWNDBfHxsz68GoDJ4Qs5+m3/EgTu+ZW303z6DiZHL6H5wp3hHI0pQhZg+tBWADVhXWhbg0bGWHDRo0iizdQhU49MPUwdTD068WjtUauxPhEjkGHXrhsAasFXoLWiE0WnitYKExtWtg1IXWEvOMDJj/wZGy96VvC4mYOpQ9ZbzHqLmTjE+kxuFAM2kg03/YSF2tEUU0fhQJkYGLHPoR2rghfEhQcuRqb4jBckfR5HE/HkSIQCrSCtIA42/+YT3PGjP4E7dQqzb535pz/H7ClXd7cQeWABBx3uydi4BhVXxJP5kXztMJIhLPQ9JBL7IqgeghO5vRNlCFFl9w8AURJ4cO2Z1zN7znUc/9Xf5OR//RPWX/B0KIiDpupmZ6GUKp1yT6HLYdHRVOJhJA4kxmOGPAcBVUXxHVVHIzNDOuZGNkOmRyMgTZhFqVW0bZE6NqNam7L5sb/BbMw49Ucforn9Lk7+3p9y6Kuf18E8BuwQcilDmZoGjxnNEDYKB7JW8WkcsoE06JwBo+TfyaTsWAsKcnESQzd7ghB5okNsfeLvOPn+PwGguvgIF/0fr8NOAIFjP/QLHHz58wHtSSckgbp4NvyiwogykwVODcfbfWf+izgLNgoHqiqXBU4g9r5URSOzNEealIdEBCGWbmofmaR5mm8kaqIqG8+9jo3nXEdqZq4qIUkGLnv9t4J0emU+Lg2oT00WQk5krGNWtWz6KR4zGmD9KP6KxMOCRBg0qHqoumYH5ZRdczSCTmcsfc6AJh2S4eSExihKWJAsZTI7KUwTKdTak8gUEdbrBSf9jG2tV21+l8lq6/DSyTmJeEQE5+L6izdd2xeNzqOdE2nMjZJUbsdS7a4hKUpJyTpNn2kmFlZVqr53TuVcgICsVwsaX4FhpZm6TGZiOtNXYI5iuN4g4sNsK5Ul6IYy9XFZSIq1xjiNzxwxCUNh6rQBHYmxzyOLsI80dBKc1zlDXXcAtJVaz5JZQv4lcHuGlBoAT2wdFBuBd8cNWalDtqrGYqmxPkeZRGnu2KtxCCvWecpia9savO/AbLVpOWg3OeVmZ/ZLOEs2CgcKjNG+7CUJ4F7MrKDfcGEoCW5jYpwaM4QmDEUx1oaCbIvJ0S03UohDqI1Ew0SrTue3xrNhF8wkiE3ts9uP2ffxxbRROJCRUK7o0XCs7wHcF61FBGyUKkhicKVDZfgpZOdIVfhEVYZOVGUoMd66sBaV9FM17xMRifUmU9OwrRNmslIsXBpLfZqt6XeBHpYrW9fNiqxRTFGNN8UU3Xmh0QTVIEeY8ExQa9Yg4Av0OoF4b9hu+hCQtP2Um45m6Eo2CgdKHK3MnEhJbbHPpGqxpqtbhC4e/XNAUCMsZ1fpfMb43JDBpNpbNFe00yv7EpXn8Cq03rLpJ6PpjwgrTPRS2AoTvbLHrY1iCPuyD3wn222FNUHPa6NeZH783IU/MeGbh9x3W6j7GFHmrqL1hu22+2p248+nWVYdZ27zpgpow6bCtUntp4vu02nLCy/9PNdtHMOr4UG3xhue9u7H/Lt5rG0UDgSFamF0nPS+Nq6Xk/T0wwp5y7IhA8A0dupIeVWasbkBkL7kw3tncS4tVgZUpIsd9OvaUYsPSMSRwFlhRA4U6p8FaGvQOKGNUpO93tF0zmNQFt4GmabC4XqdOgqKclJsTu8rG6JQrqOpBGdaWPDg14MjnXQzPDKa1ehROFDrDY2zNM5SW0cjtv/jpo5lA+cAsljujuYLRBFeUTZvvofP/of3gzHMLjnERd/wpXzqO97K7PLzkcpwzQ//87B/EY2y9oZRZBEi04l2ypFJFbpzrBxoeezBrRltG1ZlrPWZwpMabqZuYkMZyrQSnabo5WfpvaqgF17EE37sNXgVbv+P7+HUvQs2/sFVXPavvxZVYXMeutC7NvLHTLgHM4HJ/jmn71vHNZYTizWmGy0NdqXavEy29bnzMupwYclAek34nkTpgQ5cP8QAecnowZ7FKAJhH+embB+fcuqvv8BN3/lLrD3jBs77ii8DCKD6KjijrRzTuuXSAw9y49YEtwhkx/12mwfdGnM/iq9+HA5UnzSZTuOtBjDYcIEiQYL2WKqWlNvusiymFk7/3ce5733/hcn5F7B+4Aou+65/i1QVd73lrbjLnszksqO4KvRElCoUXuvKcdHsJJ+Si8AJs9gf8aSbrRpMLZNtX9girYToYTREICI3LDEsksUo03OWEkwGUdapOMTA9FlP5ZJnPZXjv/YbnLrpk6w/8wYUWPsHT2F+/Bj22otiFOsS9Yl1nD89Fd57CU3G07LBSHhho3AgWXeBSgwhaS3F5jSKvpVw1lR62O03LMsUaULVtEhdBeLh/gm6DrrmwAnbN9/M/q98AUw9NII2Bp3ERBrYb7cx1uEqy8Jb7lgcYj4SOCuMxYGsBxMr36Zgg5Y7ZYxPH97aE5or858ib9r66xs58b7/D4DqoiOYCRz7oZ9BbMX0micwu/ZypHJ4b3OEq4xn0Vbcun0on9er0KjFqVkl0UtlAkIUjSum79kdYrU+iad05b9EAowOl4TmMhIRUFh/1vWsP+v6fC0UZk97SuFwim8MMvFZ7tKpcGCy4GQz64HwZ6ahVsd9zcZj+pV8sWwUDpQgExKB7gnkNVw09L6DWYTtRbRSyZQgr9LhpSl47ibgnH0cFlMHDhGFiHu2Eb0ohHYvC29ZW59z8vgG++qQQFvx7KvG0Wx8HA5kSyB7yYSIcAzre005hkhE8vawGCi+czJUMhTWGE9Vh9JI29iMgQxLAT6L7No6NOecNxULXzGrW04/UHF4ssl+u52daAw2mmp8wiuHhUTtPaAjp6YamS1Wn8PxHU0nMS7K4Q06x1ONbNh4zdxX2ijGepwzOG84sLbNzDZcvO8kemTB8cU6m37C+fXJL+I389jaOCKQKX/kbmgSBjDXaKkpuEin6ZVWkAOvS7NSj/dBAiFdp+OgGTwdhbkyLketqnKh60vsDpuKtAtfsc9uU4tblTKWyUou+rANXbKuX3R67yLlp6DkFBhmCLKZxvQRhl1+pcW5w3MHxg946u2m4raTB9la1OjCPmQ7vXPVRuFA1vo+u8J4qrjNeek5TgLGi0povqBdi7rS6RQyBwzYkTOFSNR/n3Kl5Eits2zNJywWFUjQ8phJu4pAy2ZWFMcgUojGWVkUXTGDpLXYd3gc7CLGAj1BOpEyLU/n6V47FzlhUTYTE3UyEOa+Hg0uehQOVA4/pSVtr6G5wfQedgLhh1JPJh7XZ6EOqNDFOdvG9pcMKs/EtHg1IH40s7BROJA1ISepbJcQexUqOhmChC6sjA+kQ+MxMXkJ+hbFjGyQqmTNi3IboMUaUiIg5llasaCJKOoN++ycqWmY+3o03PgVK2MJbMXKWNnj1kYxhL3w/d8VZCUHs6i0DjSc0g87zJfHJJB842JjhQKZWM7merKWztK2oQOHquTkuUQAuNZw9IIHeenRG4HQ3uUnnv7OM/YdnC0bhQMl93CDqTjsBNcDWQJqeI6UJ5UJddn5o7SOnZp6Btlewwavgm9ix/rYBP2+kxv4o0FFaDWNXyIbTrlTJCqB9UNLQPt0bEa8SlJx3v1auzlovygbH07QuUUWBlpB64CTnkalwj6L/9y1UTgQxBXgwbYy+uylg7pD5Vl0h9zB6c/fy81vfB9ihNklh7jqO76Ke37vk9z7ex9Hnefy7/ha5NDB7j68QV3snu8iVNYLk8pxyk3ZZ+erdaBlMiuhuUJZ+ypVBnerhyV7JOWF2WWHefJPvgqAW/7Db3Hyb2/l5N/ewlN//OuBMHS2zjFvbYCMxEe4uQDu10rZmC445aYcqLZWQ9gy2cKFFZqStmNkl9XnwlJBda+cJ50DQGzIYZwXvK25/2+P4R18/Lt+lY0rj/CE1/2jvOItQpB5ihBbrX0QYdGQZz3QrHGkPr0awpbJ7n8woPt69SrR3k/UkxroFUcLJxtGozT8GeXUR27k3l/+IJOjR9D9B2m24OLvfQ3Hf/l93PoHt7D27Bs6WpDRIJPgIsXZBVD9g5tr3DvdxwWTU6zZVYOppbH2gUnIW8qAk7hfcT4fWvsWTI24j0s5z14Ae0JeVD/pGRz93mdw/9vfjW5NmFx2Dc09a9grruPUp27DXjVDYrLc0Zs750EU5wyNt8x9vUIkLp1pfEQ1HrW6J21HS3IhhK6tSs+JpHACbVtkUgX46mwKYmhuuxNphfbzx6gPHMGeNkgjaBVgrn6i2XHFhqGsqhwb1QIjfpUDLZVNfdGNnkztCSD5yLyIij29rvWFEwF9Lpjvtm194kZO/t4fA4GVceBrX8aD7/wdjv2nn8Ps2+CCl34prvawFiKO2TaYRXQiE5sK18qkatlXjyPyJBuHA8HudGWIugfJkehTepSO6jy0KBeFwPoznhpYGUn5sBUOvvKfRFmpeM7KZ76ZL4ZOBLCKmTjW6paNao4RXdF6ls6S88QfLdByAo0n/YgBJTZIdkrZA8gUoHJfsZodUwx4o6ikJlIER0uaZBKm7D2rlOms4eBsKy9yrtaBlsl6zqOZ0yVVJBzm4YzCuQqSoXaYniGQHghDYkFaNFXo1JoZrwI00kWtfF9hCDO1Y2O24ILZqfzRlluJ7i6NZSrz4IdWOocYcsdKHa/h9L/HWC2n/NaFY70EOajkLJ4gK2VjrpW2x8gnVplWbebDL3z1kIrR55KNw4EiG9RkB+rXwLwr2/sWaEJRJCn8DGnOhG2e4DDBcQIQreTVi2hwHJGc82iaYClRKSgwM7ZcTWUc++z8IVfHzyUbhQMliYLkOJ0MU6p/dXSftHCYuomFoasTYJEiMChxjWi3YCHhqHCO4bBFcEgXHM0tDFuLmm1XcXCi7KtWtbClMlsV0/iBJafxA/hGqYsxFGEpj1XxvfxIRPEUEpuJbK8gppv+aylD3gaiYWU8G3ZOLY5NNw5I6ygcKA1JJeC9jEIl/yvlQv2ia0cLKrnyHeWnA5SFfQDjY3TqrT7ixXTJeZLVjD52oN7mwskJAOZ+/2P6nXyxbBQOlCSYhpbZqaaTfEoV+x4WSOjlTAkUX8pY+iQNLqWTRQCZ70D1RoLUZl6v9J14i1eh8RVzrTjdjkOxcAWqXwKTFah+ZY9XG8UQ9uzf+R6c371lS2lDecqS1lzmQJPKhabh7MRJl/CPlJhnpeYInnfOhCS6IBZONxaHHaP4AAAbLUlEQVQ86YL7WK8WLHyQU3jfS9545r6Es2SjcCDnAw8d+tDVZNZoZlEk6+SZZMf2IE6nOxwy5VTpzOXsbti4iihWJ3T5VOMtp5opc1dlwuO5bqNwoJSgSkyOh2D65Dyp89hui3g9aGsPoSg5wsguAc4ULWFcovIUtOduP2VqWyam3ZUVcq7aKBwoWZphmahbCt2w5fzu0SlP7wfnytHHG7ZvvZtjP/dexAqTiw9z4MXXc8+7/hSAxe33cfR1L2f/867D++hkZVRT0LjEMLMN++s5c1ex2a7WgZbGjPG7/iFG+rqoyR4qV8rkwUQRMg5zxUGuLUD19YE1nvgj3wTA577zzZz39CeGKrx2tJ5cuC3gIl4DJ6wyDrNqrrA8FvQwXO4HlExEqWJ3DlVJOPc9rdfyrlhorKdhsRHATixrF+7DGM/2sQeoDm1g1yY9MH6CH6Xr4mO7Fw0iMDV+VQtbNnM5T+nox+WsyxZdOkozuwxnycpI9cCffYY73vYHTC89THXeGirKiQ/dyMEXPLl/HhXUh1JG7lzmQ1POxSDRH4ONIpNrWsuirbLkU+sMrTMsWhuUBKMclPMG5yU/koBcSe8pZ2fl/vufey3X/dxrqY/s58EP34QROPHhz7D/OdcC3bKAVwmkwoQVivBarxLUEKNu2VhsFBHoxMm1rmez6YBlSSQutarzfjDVJr3WXokivQ8lDMEvHFJXGKO4ep2FzDhx5xy1FYvJQeZbYZbVNhZtDdoGTJBK0WABsl5ZUEdcQVqXxuSuacCBxXianlsb4KVNTGGGlB4th5IEfU2W0IUKW3/5CU588I9BlOrC89l46Zdw3+9/mOn1X0Jzz1p3vOteahWjT0V25lCDMzQEBcUx2CgcKHaNC5adhUDsayKeR+lLlUr+p3+uwpHEh3Psf9LT2H/100KR1ADbcPCZL0S8wOm4nw/3YZqI4NhQvA3KQUJXuN12FTPbcnCy9Vh9HV9UG4UD+f1tBG91ay87THdGoL321QR/9RJXIePONlTaJSbKRMdJzileoAnPpo0lDi8B1gq5xd7UtCtq81JZjhoJz7z7PrqrZ+22bzhPYrN2+FVCiSKK26HaidgJyEIQb5Cmc0BtDFpQZiemZc02NKshbImsoA/vwDUnK4tYDzcLKvctt+XXaZUwvjca+fAWb+PhRpFGkCY0fJgcbFivF6zZhsq4XfFL56KNw4EqDQmseQQRRovHblasQu/QyCzZrKqd00LkhAU2qvjuMHEhEgU5hCAGPDUt++w4GKqjcCBJCMDEDXsY04erIiRgPGS8c9hOP3dKDhtzKzUKtXa0HifoRNGpo7aO8+rtTOeZmVV3juWxyAXbKwLJYLqeA4xKnwhYnK8jGxZDVckVi/lQoPvE/UpH82F/tYrUngNr25w/PUUtDq/C/c36o/qTl8VG4UCSsDd7OtBwQ3xWjUXQnbgf1YRn1o7qLORFyowENppHtHDOuGt0MtGQSHsVanG5L9DxlWLh8pixGjhce3y+V6PNXLrYBRcuKSHXfkZt0qp2G2tvJu4nsa1dTujpBDa84DTopZ4n23hkNKrNK1D9EpisQPUre7zaKIawp/z6DxYyTCU8IzzvFWT75EHJBELoNMjStqEqoo+c91KgFwKNmcZkUqE4QStl/cLTXHP+vVy0doJaPMcX67z9hf/5zH8ZX2QbhQMlx9lZYU9V+L0C7RDiGvKdvvRTv0rfsTNCIm18hJrlMkpaANLQ4jetXqtEKEcopq5KGUtkyXFKyo1QALf2YEAEx9oZnsxgNpcaMyQ+vXOmA9obRVxsL5wOs2nBUUM0iuesxLNRzUeziAijcaBi2GIn4m8oHgedeFzo3BEiz1BrPr3f/sLd3P0Lv4VYmB49zIXf8tXc/hPvxM8b7PqUi7796xEzjcNaupGifqbdPXoV5r7a9Z7ORRuFAwEdD1463fgEbS1x0hk1qLIjXxpui0cwu+wIV/7oa7DWc8cb380D7/swa9deypFXfjn3/fofsvlXn2HtmTc8ZHlEVdhqa27bPDgaThiMxIGS89jCcZJ6c3AImx3DeYk9pU3veIUdEUgjOMhOwlAnokhtWbv2Uk795edCor25hT0vriqXWKLYezGB1ozxLLylXQQAWjUSVsYopvFWNDuP3ZG/9JPV0rnKR7I0dNn0mQkqO6c+8nfc9C//T9oHNpk+4Sjbn7mdz33bz7L92TvYuO7SrjOaKbrEFv2oyyGrEv+QMgznko3CgYbTd+hA8Y0zkfocgPZ7ceitdCvZVrSLYAQfOPT8a7nqjf8L1ZH93P++j7DvGU/iyT/7Og4852pO/vHfhN6LCdaR7qXoE+RVWKsCsfDAdIv1avFYfiVfNBvFEAb0yICPZHtKWHp8rmL4MgKtCwB4bRuo6qACvT7Frk+ROjTKtOet057e7lokSldUUSWUNqwyrVvOm2yzZhsMuurSukwWok33vuOChaEtNV6AzmH2Yqfm+lgUpDOinPjo57jn3X8OwOToYY684gXc9u/fxYN/8DdIZbnkX39dL3/ODaiIi4xGmVUBiTgx7WgYGTASBzq9FXjmadHPGMXawP5MuYbbReJSi8YJvc9Uel3P1p59PZc/66n53G1rufh7XpVb/rbeQBuPjYXUlAup1YwScCpBNx6ozEorY2msvXutmwEJhZhKBIbthVTcMWMvnMlqEofv75PoPo2ACaUKWoFK0TWHWJ8dRguYrVNh4VPPIbOi9SyTVZsm43X6Y0nC5nSvy892WFnWSvJQRYf7XKVINB5LZmX4CbhKUBFMpXgn0Ib72gunNAYbhQO1a8U0fPBbqQy29ctewRGk2JZ2i6RS9Zo5X0jAOKsR1Gq3jwGtI3aoCezTjAUqpvGVBEy0H5E/jcKBdNblE1p6TKpvpn+GvDHt9tkRkTxZbVCVTocMUPGdSk86Nl2zjUOaIdbEQrkkrTW5uBK+ajC1TCb0sc1JlimhA3cbQorosMNSS18nO5wt51cMjk2OaxVpDTQE0bvoRHc+sJ/NpuaK8+7HiI6mnDEeByrHqbSgV2CZg2mOQqIJ70zfkYqoopXujFIPlc/UUcjFhkRbao9YH9u7VGwtajbbyWgWEWEsDmS1Hw0SWyIxS0tNsOHvPxxJhlGpdJqyPFHCN2L0EQGxXc9ESXIKLuiWNY3FqzCz7WoWtkwm1qPJE4bcMCHTkPN7JfPfu+n/wLN6Q2LnoEl8LrfwTaB70dgLCBAfV6XDMYmH5p1hvVqwUc1H06l+HA5klIAfLTYWiW9mlMIOMmC24dBULgnEyCP5WRMjqNvHaGBsJIyRlzCVV7JcVNtY1qtmNJLfwIqVsQwmK1bGyh6vdkaGMBF5C/BPgLtV9Ya47TDwq8ATgJuB/0FV7xcRAf4j8NXAJvDNqvoX8ZhXAd8XT/vDqvq2R3L9J/6/PxLuI7JE+1TmIoGOlvsg5g3S299EbI8qQaUwntNYn/HSzkVZp3hMJy+VrhFb5DnbMTWs8qLrbuIp++5k0034sae/65H8eUttZyoCvRX4qsG27wY+qKrXAB+M7wFeDlwTH68Ffh6yw/0A8DzgucAPiMihR3Jxa30onhqfcTn5IUGQLj2MDQ+JQDFjPMa6cGyBCSqdB9iRZJviGiY+krhdeOgOcD6N4VQzZdNN2PTjaDR+RhxIVf8IOD7Y/AogRZC3AV9bbP+/NdifAQdF5Cjwj4EPqOpxVb0f+AA7nXJXS05hih+z+1GHD/Jn1hb7GY3O5/fAD3XV+5I7VlUuO68xPsNBykq/pOUE7XojWlYLiQ9nF6nqMQBVPSYiF8btlwK3FvvdFrfttf0RWamLunP7zuXmcshJBMKeXqqScdGLW+/inv/rNxEj1Bcf4eLXfQ13/syv4x48zezqS7jwm16ar+Fcp8WaI5iQNeiNKG5EqefZ+Et2Kx7oQ2zfeQKR14rIR0Xko/fQOU+fELhb9Ok/+ufsf1ZGpcklR7jsDd/KpT/4raBw/3s/xPTKi7n89d+Mn7dsff6u3BK4kzro8iNjFak0O9HcVzQ6DlDZY+lAd8Whifh8d9x+G3B5sd9lwB0PsX2HqeqbVPXZqvrsC+gTCpMNnWH34ayo4svOR95ed5JOUlf4ecvkiovxXphceTGbN96WHag7oXY5VcQE4QO153Q7zcCyc90ey7/iPcCr4utXAe8utn+TBHs+8GAc6t4PvExEDsXk+WVx28NaSTdOFpSYZdfEdkiBNibkMmU+k86XnOz0R2/k1n/zRtyJU0wuu4DNT94MwObHb8ad3O7uxZscffpy4IALlfix4KHhzE3jfwV4CXC+iNxGmE39GPAOEXkNcAvwyrj77xCm8DcRpvGvBlDV4yLyBuAjcb8fUtVhYr7H9RVjyMTAob5XUm3uD1tdM4be2Cn9Xq7JCfY/98nse85TuOct7wURdNFy2+vfSnXBIeyBfb17KV9nnlmEt/rIkV91aS1MVf/ZHh99xS77KvC/7XGetwBveXT3Ir3XqoOIQ/xhh9Py4r1TKYYwxTctpq5wTjBrM2Q64fxX/3dYqxz7+few/rSrOzhHPI8IuelVTqaNZsGVBG89120Uf0XXQUP3mIl1kaZUM1SV3PRy9/OG/Tb/6jMcf8+foQqTo0eYXHERt7/+LYgR9n3p06mOHIidziI1eo9lAAS2FjX+Ya57LtkoHAjSym83LPQ6dQxyntKSU5VmBxFq33OuY+PZ1+N910vosh/8nzAmDJfq+8NVeV0tmzYobM3DAuJYkuhROJD3ElquuK7soLZcG/JdI6kBlHRH6YMQmUzMhfpKz2W0G1ixUFk+qwoOj8HgCZgg2Klbdq7aKBxo+9Q01KUSDcdqR68RaJuullXWq9LQ5ookO0UkazzOd60wJVE7eu+jk0rIc8R050+zPucMVaW4BNuOmGj/SBpanwM2Cgeyd05C/hpHLZVAuUlUHD8JYK+20j7C0GoAiBnFVGH6bm23dpQWJ8ucCfoOaEzqVqY4l6bv6bhuOaBtw42ph21Xsy7jgLWOwoGMo7dmLYC03Xu7kEDFkWKHCDhL9BxvwFulMRpWx6rAvJDK56JsV5H3RQRK5RDFe5tZrdDVzlLdrTGKeqFxFm9XEWhpbHHEBWGToapuLGCWiI6MIlQJUauVMDAppCFKAF+ZXnHFV6BTDxOPmThs5WIxNjhLcjDvDFJ1Qxd0dbUEjd2rb/W5aKNwIACtgzohsBPamjarhJc+flCA4rPuV6xlSSpLJLjzAnTbosaitqKdKs3EI3VwqKpysZxhmM9r3FaFPZhgJt3wZivPzBbh8Ry3cThQjjSyk78lxWfJMj46HkuYtWV9DKED4UN2MHFgWgm8+EXSRAVfK4tJ4MbjgdZgTxmaDcts1tA0FYt5BXOL3ViwXi1YjKRDxzgcKAeLqCaYmanx2cQV6TRTS5ZmbSXovnSuNCTa4GBaga/jeU043jQSJJ22BZ1XgeLsBbsVGlypCtsPTqnurakX0GxUQepgJMPYClS/BCYrUP3KHq82iiHsyrf+aMfzitPzkmDYC7JDPljeDj32apFg9/YR2A2oD8X2JMDrJM/6pA2SB0/4kju4+rx72HI1/8/zH1XdeClsFA4EdHmMSqAUF6WENKMKCXK3Xz4uWek4GRym/W3D3MUUnxsgSlx2gnPkXIlW2G4rTrfTFbV5mSxXBeJ/d7FdmSEIWmj+WItItSP9K53LDBxrx0UHq9p59haS7aBdHxJ6QfATzUKHa7ZZ1cKWyvKsq1sZLnE5XbSh8xrV/nCWVqfDhx3nq7ATH/gjtj72CS763tdx/y+/l8Xnb2fyhEs4/I1fk/fRdA0vaNScT0sKKspa3bBmx1HGgLEk0XG9R1JUkK6/c/i8D/QKXTQi2D0+ytd5W+UxdXiILmhuOwYCi1tuQxcLLv7+14JvWdx8SyjeFgVckgDvxEPtu471BOLiWOAco/grMokwdkRNoLGefsaQdSE6wEn3OWLJodL7U3/4UfZ92TMAWNx0C7MbrgJgdsNVzD97a3Dg1Ngqli1y13rol0VURiP3NA4HSlEFIju1lB3w+UfNDlRuS2TC8nzQx0q3ju2/+zzr0Wn81laAthrFrs/wm1tdhb5gxObz2a4OlmxixlHOGEUOlCvjxvcAXwlQ1tlO4FhuG/QQLedO/slfsu9FT8vDoFlfQ7dDd3qdb2E3ppmVGla9i2ul/Mv2C6krZuoSmbF9Gs4QETicbeXmCrvNxHbZrzl2L/Ob7+TEBz9Mc/td+FOnaW47xv4X3sDWxz/LeS95RqQvK3iDsfG8Sm4uFTQXut6Icz8Oas84HCiDv4rhrFiv2U2BEMB7GAID+7jm4IDnf+PLgHDOW7/vzRx55Zdz71t/mzte/yamT7iY9WsvzewPjw/T9ySZkCQ0JdxcSqBXtJ4lsw6LrANAfRzO4nuN27w3e0hbagbnSwcUyue/4kdeg3PK+a/+ajoZTM1XKIH0eBMiT5rWx+s0UTt1DDaKv2JIGlSVh53jlKjCFJGSQ+XePgNpqE6Mrrtu91kBHEv3ZRJ6EdSFrq1AbDY+jlnYKCJQiV9OOY+nS5Ir63vrhdBFor3oOGXCPXSYPne+axmTE3LpRHn7dbiwDrS/2gZmZ+aPP8s2CgdKP2LKaYzxeUqfPnfe9EiFJeMiWZe3DLflK+3CraebgZEA+B6JO/VqXhJUemam4TSrLq1LY/PtOrekC8OQ6SXSdeWys1RxxtZEinFaVOwiUn/o6hJu6UWscnvoCx3eBwdLBMTw3jtAwNgwC2u8XSXRy2TtPTOwgWGRu9RLt4A3l9C/2VhHXQeClnOm12msNJGgN5ZmUWGfziET9jn3Eco0oDJfIncHCYuXYeGy9YZTbjqaDh2jcKDJAyar6ZT/sTUEB9QE6o4z0NrQJaPXYLzqKviU5QeK2V0se6TFyUDXCfvYXP3vO1GKWLYC1xp8G3okzqcr3filsua8gMkRB6gEnlhqdejBOOkcJqbR2dHCiNezQEyMfLEqsj1K4brkI4kBW6gSCt2KeKit+Q7Y1hhcUiwciez3KBzIzxIllYD8a4UdGXLpJIUaj0TKcTnxEgU7j44m0secxagW5BLIDFgI7AxfxQiXHC4RFRtBWhNIhWqoRyJ5uQLVL4HJClS/sserjWIIu/IX/l0fzwwdyTCoL3U2RCAWyMM8VMXKxKCBPUkiU5xkbRdNLREl5EyaGjgoiI9DpBfsItzL5IYHecbFt3F4sskbn/n2M/k1nBUbhQNhdYcD6cAZ0mspHEaTPFOqnCtk4PJglqQlNFYDzlkJSfZOfbF4PjTmULF0ERtRtd6ORjt+HA60q6Sl7qTe7LpJ82eJBw9kPbGs2gyc+OAfsPlXH+f813wj9/z8L7K48y6u+KkfRirbwX9scZykK0hOrAXwyGohcZlMKp+HDfXS4ZKTxcjSawBemicPZX2HkuxI2rQs7giYaHNgjQu/41u45+d/Ca09lK1aInQjy1420s3YTBckxxKBxvHfIJUthOw8afVXjGIqRSJAXqrikUDwNiwm7nz48GyVUx/6czZe9Mxw7jWLObAWwlVd7J+UmtOj9qFrSO3DupNRrChrdjyic+OIQNI5TXgPiZmRPycWRofDXY5Mg80FS1Ubz/wzn+O8f/x8HnyPBlhGXJg0E4fEHtWZ3ZrHQUHxoUlDTMoq65mYdjTUnlE4EAW8Iul9ZelJ7bDRISUZDGEFmbBcEitxPaf++GNsvOhpXY0tJt8Z/WggwcXUa9fQszt15IgVBV4Zx0LiKBzI9GpXqZlm97mPmqW58XcGhhWRQvowjdLaO+9l8YVjnPz9D9PcdhcnPvAhDnzV84G+5kaCg4gkB/Okvog+9g0yokxHwsiAkTiQDHpClxoXwUwvEvVmaGmoGxRBy+aa5/+PARPtVbjjB9/Ega98Dnf+yFtY3HInd/7YWzn8DV/J7JrLwZtuWSCdVzTAWmPfxY3JYuVAy2YllKLDRXdRIUAzyO/TcycI5xnif/KPH00ELMrlb/gWAC79/m/OQLbwuY+NNiX3q+6OjcVWAwcmW6MZvmAkDgQMfswyodaI3Un7dKqCaRKakIs9RcICL53OOwThlxSi8N53gnNeelEMQKznwGSbMdloHChZqX1qIni99yMSfninkh0ngceGrAygJ2+Q3udzCRETVLQBNqF+4qXDZ4edQ16UYBxjUS0chQMlByijTupBOOw6H1KgbvhKw1/5Y5cRKYHFOsC8FoD5dI4u4gUHFoyRPrMjOZh45r5aOdAyWcmI2M12SkDtMd2Kthtth6gEVPLJMoBfCgB/PE4lYaMj/DXx9IFGLe1IJC/H4UCRTJi4Vol9kYed2B86T7Hjj5vem/iDl4n4MH9JrIvEwEhOlIfBOFymyOdjHhWGuLDiXVWeqWmD8O4u/YfORRtFHK2i7ntlHdZ4Kut7P35lXU+VJ702xufWL9AlxRT72uJ9ikBDvr0thstkJuZh5TXryrHPzqnFrTDRy2SnNmdUletFBgAbo5I6G2AUre3Rno0JpdOUaA8B8aTPiEs70mdwhPzGsL42z9FPVfAKrbNdn84YAQ+tb+XcZ9XeZYls8cCURYJR1D60p4vNNtWZDHxXJwEAHxcUbeW6xcVo5ZR9t6EMuqEwMTNcMWtrizWglG81i/A1T22LxeOxo1kLWmGil8BWmOiVPW7tnI9AInIS+NTZvo+HsfOBex/i8ytV9YIv1s2cSRtDDvSpZQ//IvLRZb/Hv6+thrCVPSpbOdDKHpWNwYHedLZv4BHYuXCPfy8755PolZ1dG0MEWtlZtHPagUTkq0TkUyJyk4h899m+HwARuVlE/lZE/kpEPhq3HRaRD4jIZ+LzobN9n2fKzlkHEhEL/CzwcuB64J+JyPVn966yfbmqPr2Yun838EFVvQb4YHw/CjtnHQh4LnCTqn5OVRfA24FXnOV72steAbwtvn4b8LVn8V7OqJ3LDnQpcGvx/ra47WybAr8rIh8TkdfGbRep6jGA+HzhWbu7M2zn8kr0boisZZhSvkhV7xCRC4EPiMiNZ/uGHks7lyPQbcDlxfvLgDvO0r1kU9U74vPdwG8Qhtq7ROQoQHy+++zd4Zm1c9mBPgJcIyJPFJEJ8A3Ae87mDYnIhojsT6+BlwEfj/f1qrjbq4B3n507PPN2zg5hqtqKyP8OvB+wwFtU9RNn+bYuAn4jdqmvgF9W1feJyEeAd4jIa4BbgFeexXs8o7ZaiV7Zo7JzeQhb2RLYyoFW9qhs5UAre1S2cqCVPSpbOdDKHpWtHGhlj8pWDrSyR2UrB1rZo7L/HxJkZGlTsQYrAAAAAElFTkSuQmCC\n",
|
|
"text/plain": [
|
|
"<Figure size 1152x1152 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"## Load List in coordinate latitud and longitude to pixels ###\n",
|
|
"string = L_strings_coord['22']\n",
|
|
"panels = string['panels']\n",
|
|
"\n",
|
|
"\n",
|
|
"epsilon = 0\n",
|
|
"matrix_expand_bounds = [[-epsilon, -epsilon],[+epsilon, -epsilon], [+epsilon, +epsilon], [-epsilon, +epsilon]]\n",
|
|
"\n",
|
|
"#geot = GR_RGB.geot\n",
|
|
"geot = GR_T.geot\n",
|
|
"geot_S = GR_String.geot\n",
|
|
"\n",
|
|
"\n",
|
|
"Points = Utils.gps2pixel(string['points'], geot) + matrix_expand_bounds\n",
|
|
"\n",
|
|
"\n",
|
|
"\n",
|
|
"plt.figure(0)\n",
|
|
"plt.figure(figsize=(16, 16))\n",
|
|
"plt.imshow(GR_String.raster.data)\n",
|
|
"plt.title('Origin Image')\n",
|
|
"ax = plt.gca()\n",
|
|
"\n",
|
|
"for Poly_key in L_strings_coord.keys():\n",
|
|
" \n",
|
|
" Poly = L_strings_coord[Poly_key]\n",
|
|
" poly = patches.Polygon(Utils.gps2pixel(Poly['points'],geot_S),\n",
|
|
" linewidth=2,\n",
|
|
" edgecolor='red',\n",
|
|
" alpha=0.5,\n",
|
|
" fill = True)\n",
|
|
" plt.text(np.mean([x[0] for x in Utils.gps2pixel(Poly['points'],geot_S)]), \n",
|
|
" np.mean([y[1] for y in Utils.gps2pixel(Poly['points'],geot_S)]) , \n",
|
|
" str(Poly['id']).split('_')[-1], bbox=dict(facecolor='red', alpha=0.8), fontsize=10)\n",
|
|
"\n",
|
|
" ax.add_patch(poly)\n",
|
|
" \n",
|
|
"plt.figure(1)\n",
|
|
"plt.figure(figsize=(16, 16))\n",
|
|
"plt.imshow(GR_T.raster[0,Points[0][1] : Points[2][1], Points[0][0]: Points[2][0]])\n",
|
|
"#plt.imshow(GR_T.raster[Points[0][1] : Points[2][1], Points[0][0]: Points[2][0]])\n",
|
|
"#plt.imshow((GR_RGB.raster[:3,:,:]).transpose((1, 2, 0))[Points[0][1] : Points[2][1], Points[0][0]: Points[2][0],:])\n",
|
|
"\n",
|
|
"plt.title('Subdive Origin Image')\n",
|
|
"ax = plt.gca()\n",
|
|
"\n",
|
|
"for Poly_key in panels.keys():\n",
|
|
" \n",
|
|
" Poly = panels[Poly_key]\n",
|
|
" poly = patches.Polygon(Utils.gps2pixel(Poly['points'],geot) - (Points[0][0], Points[0][1]),\n",
|
|
" linewidth=2,\n",
|
|
" edgecolor='red',\n",
|
|
" fill = False)\n",
|
|
" plt.text(np.mean([x[0] for x in Utils.gps2pixel(Poly['points'],geot) - (Points[0][0], Points[0][1])]), np.mean([y[1] for y in Utils.gps2pixel(Poly['points'],geot) - (Points[0][0], Points[0][1])]) , \n",
|
|
" str(Poly['id']), bbox=dict(facecolor='red', alpha=0.0), fontsize=8)\n",
|
|
"\n",
|
|
" ax.add_patch(poly)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"# Save KML"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Listo\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"\n",
|
|
"kml=simplekml.Kml()\n",
|
|
"\n",
|
|
"\n",
|
|
"for string_key in L_strings_coord.keys():\n",
|
|
" \n",
|
|
" string = L_strings_coord[string_key]\n",
|
|
" points = string['points']\n",
|
|
" \n",
|
|
" pmt = kml.newpolygon(name= string['id'], outerboundaryis = points)\n",
|
|
" pmt.extendeddata.newdata(name='Mesa', value=string['id'])\n",
|
|
"\n",
|
|
"kml.save(path_kml_mesa)\n",
|
|
"\n",
|
|
"\n",
|
|
"kml=simplekml.Kml()\n",
|
|
"\n",
|
|
"\n",
|
|
"for string_key in L_strings_coord.keys():\n",
|
|
" \n",
|
|
" string = L_strings_coord[string_key]\n",
|
|
" points = string['points']\n",
|
|
" \n",
|
|
" for panel_key in string['panels'].keys():\n",
|
|
" panel = string['panels'][panel_key]\n",
|
|
" points = panel['points']\n",
|
|
" \n",
|
|
" pmt = kml.newpolygon(outerboundaryis = points)\n",
|
|
" pmt.extendeddata.newdata(name= 'Id integer', value= str(string_key).zfill(3) + '_' + str(panel['id']).zfill(3))\n",
|
|
" pmt.extendeddata.newdata(name= 'Id panel', value= str(panel['id']).zfill(3))\n",
|
|
" pmt.extendeddata.newdata(name='Zona PV', value= ZonaPV)\n",
|
|
" pmt.extendeddata.newdata(name='Cód. Fall', value= 0)\n",
|
|
" pmt.extendeddata.newdata(name= 'Tipo falla', value= panel['status'])\n",
|
|
" pmt.extendeddata.newdata(name= 'Mesa', value= string['id'])\n",
|
|
" \n",
|
|
"kml.save(path_kml_panel)\n",
|
|
"print('Listo')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.7.7"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 4
|
|
}
|