{"cells":[{"metadata":{},"cell_type":"markdown","source":"<p style=\"text-align: center;\"><font size=\"10\"><b>MEMORY TEST ON DRUGGED ISLANDERS</b></font></p>\n<p style=\"text-align: center;\"><font size=\"4\">EXPLORATORY DATA ANALYSIS & CLUSTERING</font></p>"},{"metadata":{},"cell_type":"markdown","source":"An experiment on the effects of anti-anxiety medicine on memory recall when being primed with happy or sad memories. The participants were done on novel Islanders whom mimic real-life humans in response to external factors.\n\nDrugs of interest (known-as) [Dosage 1, 2, 3]:\n\nA - Alprazolam (Xanax, Long-term) [1mg/3mg/5mg]\n\nT - Triazolam (Halcion, Short-term) [0.25mg/0.5mg/0.75mg]\n\nS- Sugar Tablet (Placebo) [1 tab/2tabs/3tabs]\n\n*Dosages follow a 1:1 ratio to ensure validity\n*Happy or Sad memories were primed 10 minutes prior to testing\n*Participants tested every day for 1 week to mimic addiction\n"},{"metadata":{},"cell_type":"markdown","source":"<h3 class=\"list-group-item list-group-item-action active\" data-toggle=\"list\" role=\"tab\" aria-controls=\"home\">Table of Contents</h3>\n\n1. [Libraries & Packages](#libraries)\n2. [Initial Insights](#insights)\n3. [Data Preprocessing & Feature Engineering](#preprocessing)\n4. [Data Exploration & Visualization](#exploration) \n A. [Univariate Exploration](#univariate) \n B. [Bi/Multivariate Exploration](#multivariate) \n I. [Memory Score Comparisons](#memscore) \n II. [Difference Comparisons](#diff) \n III. [Difference Category Analysis](#diffcat) \n5. [Additional Feature Engineering](#features) \n6. [Clustering](#clustering) \n A. [K-Means Clustering](#kmeans) \n B. [Hierarchical Clustering](#hierarchical) \n \n<!-- 7. [Algorithm Comparison](#comparison)\n8. [Conclusion](#conclusion) -->"},{"metadata":{},"cell_type":"markdown","source":"<a id=\"libraries\"></a>\n## LIBRARIES & PACKAGES"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport seaborn as sns\nimport matplotlib.pyplot as plt\nimport plotly.express as px\nimport missingno as msno\nimport plotly.graph_objects as go\nimport plotly.figure_factory as ff\nfrom plotly.subplots import make_subplots\n\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","execution_count":1,"outputs":[{"output_type":"stream","text":"/kaggle/input/memory-test-on-drugged-islanders-data/Islander_data.csv\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"<a id=\"insights\"></a>\n\n## INITIAL INSIGHTS"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"df = pd.read_csv('../input/memory-test-on-drugged-islanders-data/Islander_data.csv')\ndf.head()","execution_count":2,"outputs":[{"output_type":"execute_result","execution_count":2,"data":{"text/plain":" first_name last_name age Happy_Sad_group Dosage Drug Mem_Score_Before \\\n0 Bastian Carrasco 25 H 1 A 63.5 \n1 Evan Carrasco 52 S 1 A 41.6 \n2 Florencia Carrasco 29 H 1 A 59.7 \n3 Holly Carrasco 50 S 1 A 51.7 \n4 Justin Carrasco 52 H 1 A 47.0 \n\n Mem_Score_After Diff \n0 61.2 -2.3 \n1 40.7 -0.9 \n2 55.1 -4.6 \n3 51.2 -0.5 \n4 47.1 0.1 ","text/html":"<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>first_name</th>\n <th>last_name</th>\n <th>age</th>\n <th>Happy_Sad_group</th>\n <th>Dosage</th>\n <th>Drug</th>\n <th>Mem_Score_Before</th>\n <th>Mem_Score_After</th>\n <th>Diff</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>Bastian</td>\n <td>Carrasco</td>\n <td>25</td>\n <td>H</td>\n <td>1</td>\n <td>A</td>\n <td>63.5</td>\n <td>61.2</td>\n <td>-2.3</td>\n </tr>\n <tr>\n <th>1</th>\n <td>Evan</td>\n <td>Carrasco</td>\n <td>52</td>\n <td>S</td>\n <td>1</td>\n <td>A</td>\n <td>41.6</td>\n <td>40.7</td>\n <td>-0.9</td>\n </tr>\n <tr>\n <th>2</th>\n <td>Florencia</td>\n <td>Carrasco</td>\n <td>29</td>\n <td>H</td>\n <td>1</td>\n <td>A</td>\n <td>59.7</td>\n <td>55.1</td>\n <td>-4.6</td>\n </tr>\n <tr>\n <th>3</th>\n <td>Holly</td>\n <td>Carrasco</td>\n <td>50</td>\n <td>S</td>\n <td>1</td>\n <td>A</td>\n <td>51.7</td>\n <td>51.2</td>\n <td>-0.5</td>\n </tr>\n <tr>\n <th>4</th>\n <td>Justin</td>\n <td>Carrasco</td>\n <td>52</td>\n <td>H</td>\n <td>1</td>\n <td>A</td>\n <td>47.0</td>\n <td>47.1</td>\n <td>0.1</td>\n </tr>\n </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df.dtypes","execution_count":3,"outputs":[{"output_type":"execute_result","execution_count":3,"data":{"text/plain":"first_name object\nlast_name object\nage int64\nHappy_Sad_group object\nDosage int64\nDrug object\nMem_Score_Before float64\nMem_Score_After float64\nDiff float64\ndtype: object"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df.info()","execution_count":4,"outputs":[{"output_type":"stream","text":"<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 198 entries, 0 to 197\nData columns (total 9 columns):\n # Column Non-Null Count Dtype \n--- ------ -------------- ----- \n 0 first_name 198 non-null object \n 1 last_name 198 non-null object \n 2 age 198 non-null int64 \n 3 Happy_Sad_group 198 non-null object \n 4 Dosage 198 non-null int64 \n 5 Drug 198 non-null object \n 6 Mem_Score_Before 198 non-null float64\n 7 Mem_Score_After 198 non-null float64\n 8 Diff 198 non-null float64\ndtypes: float64(3), int64(2), object(4)\nmemory usage: 14.0+ KB\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# PRINT UNIQUE VALUES FOR EACH COLUMN\n\nfor column in df.columns:\n print(column)\n print(df[column].unique())\n print('')\n ","execution_count":5,"outputs":[{"output_type":"stream","text":"first_name\n['Bastian' 'Evan' 'Florencia' 'Holly' 'Justin' 'Liam' 'Ava' 'Jamie'\n 'Josefa' 'Mark' 'Maximiliano' 'Ayano' 'Grace' 'Ai' 'Kaito' 'Jun' 'Takuya'\n 'Justine' 'Nik' 'Carlos' 'Anna' 'Daichi' 'Dean' 'Riley' 'Sofia' 'Darren'\n 'Fernado' 'Misaki' 'Orla' 'Robert' 'Valentina' 'Ryan' 'Jose' 'Shota'\n 'Anthony' 'Nina' 'Lara' 'Daiki' 'Felipe' 'Camila' 'Hama' 'Miki' 'Riko'\n 'Benjamin' 'Hina' 'Kevin' 'Takahiro' 'Megan' 'Akane' 'Ren' 'Laura'\n 'Ariane' 'Naoto' 'Jade' 'Tomax' 'Ami' 'Mai' 'Yuta' 'Marianne' 'Mathis'\n 'Martina' 'William' 'Tatsuya' 'Raphael' 'Fabian' 'Paula' 'Sho'\n 'Frederique' 'Killian' 'Jeremy' 'Lan' 'Riku' 'Rin' 'Karin' 'Christian'\n 'Ignacio' 'Joaquin' 'Momoko' 'Sara' 'Alejandra' 'Rok' 'Carla' 'Alexia'\n 'Nanami' 'Victor' 'Sophia' 'Kana' 'Aya' 'Eva' 'Shun' 'Adam' 'Ayaka'\n 'Ryouta' 'Antoine' 'Ciara' 'Mitsuku' 'Takumi' 'Kenta' 'Pia' 'Erin'\n 'Michael' 'Sakura' 'Chloe' 'Tobias' 'Shauna' 'Ross' 'Daniel' 'Asuka'\n 'Emma' 'Nathan' 'Akira' 'David' 'Manuel' 'Sean' 'Sebastian' 'Sophie'\n 'Diego' 'Dylan' 'Millaray' 'Cristobal' 'Nicole' 'Elias' 'James' 'Conor'\n 'Jacob' 'Maximilian' 'Aaron' 'Luka' 'Amy' 'Haru' 'Lukas' 'Ellen' 'Naoki'\n 'Rina' 'Noemie' 'Gregor' 'Teo' 'Alexander' 'Alexandere']\n\nlast_name\n['Carrasco' 'Durand' 'Gonzalez' 'Kennedy' 'Lopez' 'McCarthy' 'Morin'\n 'Price' 'Summers' 'Takahashi' 'Bernard' 'Hajek' 'Rodriguez' 'Steiner'\n 'Connolly' 'Castro' 'Fiala' 'Novak']\n\nage\n[25 52 29 50 37 35 38 36 63 27 39 26 48 51 44 53 55 31 62 40 28 68 56 54\n 47 43 30 32 49 34 41 45 42 72 33 46 59 66 65 60 83 24 69 80 73]\n\nHappy_Sad_group\n['H' 'S']\n\nDosage\n[1 2 3]\n\nDrug\n['A' 'S' 'T']\n\nMem_Score_Before\n[ 63.5 41.6 59.7 51.7 47. 66.4 44.1 76.3 56.2 54.8 90. 52.3\n 35.5 85.6 42.3 53.5 48.3 64. 74.3 45. 52.1 79.9 55.7 46.5\n 48.5 75. 43.9 74.9 74.5 58.9 36.4 58.8 59.9 40.2 74.2 50.\n 84.4 40.8 87. 64.4 60.9 46.4 55.2 61.8 65. 28.3 41.9 49.4\n 43.6 71.7 81. 46.7 31.7 65.6 57.3 72.6 54. 61.6 59.8 64.1\n 53.3 49.2 54.5 49.3 66.2 46.9 45.8 41. 65.1 76.2 39.6 42.5\n 56.9 74. 63.3 53. 59.6 36. 54.1 46. 67. 86.3 48.7 76.8\n 30.7 61.4 51.5 46.2 38.5 79.7 56.3 85.5 84.5 69.2 56.6 44.\n 83.4 62.8 40.5 55.9 89.6 53.6 36.3 47.8 69.7 88.7 81.9 40.\n 51.4 50.5 96. 62.3 48.6 49. 50.9 47.7 45.3 72.9 40.7 59.5\n 70.5 27.2 64.2 58.6 47.2 82.4 76.1 53.9 44.2 100. 78.8 57.1\n 54.6 52.7 48.2 41.5 70.9 30.1 33.4 46.6 43.4 44.5 77.8 42.7\n 53.8 57.6 44.9 52.5 49.7 58.4 67.2 72.1 60.2 74.4 110. 68.8\n 39.8 50.8 71.3 72.5 30.8 43.1]\n\nMem_Score_After\n[ 61.2 40.7 55.1 51.2 47.1 58.1 56. 74.8 45. 75.9 102. 63.7\n 84.3 32.8 56.3 44.6 72.5 65.4 49.2 44.2 73.3 52.7 46.1 54.\n 55.5 82.9 108. 46.8 70.8 79.6 50.9 50.8 65.6 44.5 88.1 49.4\n 96. 63. 48.1 64.9 66.6 74.3 87.4 114. 44. 55.6 69.2 90.\n 88.2 67.4 120. 59.7 53.4 86.4 77.2 60. 88.5 79.7 75.2 64.2\n 53.6 56.7 61.4 59. 48.5 44.1 61.5 81.4 41.7 47.6 45.6 59.2\n 62.9 52.1 56.8 46. 35.8 65.2 59.5 43.2 70.9 52.9 78.5 27.1\n 47. 66.4 50.2 41.3 41.9 88.9 56.6 83.6 65.8 38.2 46.2 54.1\n 28.9 41.5 33.4 60.8 89.9 48.3 80.4 57.5 40.3 49.3 58.9 71.9\n 80.6 42.2 46.9 51.4 66.8 50.4 40.5 41.8 37.9 41.1 74. 39.\n 37.8 57.3 83.1 73.1 49. 84.5 53.7 51.7 54.6 53.3 67.8 30.5\n 47.4 47.7 72.2 60.6 40.6 60.3 56.1 63.6 44.9 55.7 87.8 82.6\n 77.4 44.3 30.4 70.4 33.1 53.8 42.1]\n\nDiff\n[ -2.3 -0.9 -4.6 -0.5 0.1 -8.3 11.9 -1.5 -11.2 21.1 12. 11.4\n 5.2 -1.3 -9.5 2.8 -3.7 8.5 -8.9 4.2 -7.9 -6.6 -3. -0.4\n 5.5 7.9 18. 2.9 -4.1 5.1 -2.6 14.5 -8. 5.7 4.3 13.9\n -0.6 11.6 22.2 15. -16.3 4. 20.2 19.1 25.6 49. 15.7 13.7\n 19.8 19.4 18.3 33.4 25.5 39. 13. 21.7 20.8 38.7 4.6 6.\n 26.9 19.9 25.9 21.9 -1.7 0. 7.4 -4.8 1.6 3.1 -3.6 2.1\n -0.7 2.3 16. 5.3 -2.8 -0.2 10.6 1.7 5.4 3.9 -6.7 5.\n -4.9 3.4 9.2 0.3 -1.9 -40.4 -3.4 -3.2 -5.8 1.2 -16. -8.7\n -13.4 -7.1 4.9 -5.3 0.7 -9.6 -3.9 1.5 2. 2.2 7.3 6.3\n -7.8 4.5 1.8 -8.5 -4.2 -9.1 -9.8 1.1 -4.7 -6.9 -5.9 0.5\n -4. -3.5 0.6 6.9 -3.1 0.4 24.1 3.2 -5.6 -8.2 3. 7.8\n -8.4 -14.7 -4.5 -22.2 -7.4 8.6 -20.4 -2.1 0.2 -1. ]\n\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"## MISSING VALUES\n\nTHIS DATASET CONTAINS NO MISSING VALUES"},{"metadata":{"trusted":true},"cell_type":"code","source":"missing_percentage=df.isna().sum()*100/df.shape[0]\nmissing_percentage","execution_count":6,"outputs":[{"output_type":"execute_result","execution_count":6,"data":{"text/plain":"first_name 0.0\nlast_name 0.0\nage 0.0\nHappy_Sad_group 0.0\nDosage 0.0\nDrug 0.0\nMem_Score_Before 0.0\nMem_Score_After 0.0\nDiff 0.0\ndtype: float64"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"<a id=\"preprocessing\"></a>\n\n## PREPROCESSING & FEATURE ENGINEERING\n\nFor certain continuous variables I like to bin them into categorical variables to add a different perspective in the exploration. In this instance \"Age\" and \"Diff are two continuous variables that will benefit from being binned into a separate categorical variables. \n\nBelow I created new variables \"age_cat\" and \"diff_cat\". **\"Age_cat\"** will separate each patient into an age group: \"young adult\", \"middle age\", or \"senior adult\". **\"Diff_cat\"** will categorize the values in the \"Diff\" column as \"increase\", \"decrease\", or \"no change\"\n\nI created a new column with each patient's full name to ensure that each patient is uniquely identifiable in any exploration. "},{"metadata":{"trusted":true},"cell_type":"code","source":"# BIN AGE GROUPS and DIFF CATEGORIES\n\ndf['age_cat'] = np.nan \ndf['diff_cat'] = np.nan\n\n\nfor col in [df]:\n col.loc[(col['age'] >= 18) & (col['age'] <= 35), 'age_cat'] = 'young adult'\n col.loc[(col['age'] > 35) & (col['age'] <= 55), 'age_cat'] = 'middle age'\n col.loc[col['age'] > 55, 'age_cat'] = 'senior adult'\n \n col.loc[col['Diff'] > 0, 'diff_cat'] = 'increase'\n col.loc[col['Diff'] < 0, 'diff_cat'] = 'decrease'\n col.loc[col['Diff'] == 0, 'diff_cat'] = 'no change'\n\n \n# CREATE FULL NAME COLUMN\n\ndf['full_name']= df['first_name'] + ' ' + df['last_name']\n\n ","execution_count":7,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# DROP FIRST_NAME & LAST_NAME COLUMNS \ndf.drop(columns=['first_name', 'last_name'])\n\n# REORDER COLUMNS\ndf = df[['full_name', 'age', 'age_cat', 'Happy_Sad_group', 'Dosage', 'Drug', \n 'Mem_Score_Before', 'Mem_Score_After', 'Diff', 'diff_cat']]","execution_count":8,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"<a id=\"exploration\"></a>\n\n# EXPLORATORY DATA ANALYSIS\n\nIn this section we visualize our data and see what insights may be gleaned. "},{"metadata":{},"cell_type":"markdown","source":"<a id=\"univariate\"></a>\n\n## UNIVARIATE ANALYSIS\n\nIn this section I look at some prelimenary insights that the data has to offer. Using bar charts, histograms, pie charts, and box plots I observe how each variable is distributed.\n\n**AGE & AGE_CAT**\n\nThe majority of patients fall into the young adult (below 35) and middle age (36-55) categories, with young adults slightly out numbering middle age. Seniors occur far less frequently with only 18 out of the 198 participants falling into that category.\n\n**HAPPY/SAD GROUP**\n\nThe patients are evenly distributed among the \"happy_sad_group\" variable. In this variable, each patient was primed with happy or sad memories 10 minutes before testing. \n\n**DOSAGE AND DRUG DISTRIBUTION**\n\nThere is a fairly even distrubution of each type of drug and number of doses among the patient population. \n\n**MEMORY SCORES AND DIFFERENCE CATEGORIES**\n\nOverall there is a general increase in memory score as indicated in the box plots of the \"Memory_Score_Before\" and \"Memory_Score_After\" variables and the \"Diff_cat\" variable. The Before scores range from a minimum value of 27.2 to an upper fence value of 100 and maximum outlier value of 110. The After scores range from a minimum value of 27.1 to an upper fence value of 108 and maximum outlier value of 120.\n\n\n\n\n\n"},{"metadata":{"trusted":true},"cell_type":"code","source":"fig = make_subplots(rows=2, cols=1)\n\nfig.add_trace(go.Histogram(x=df['age'], name='AGE',xbins=dict(start=20, end=90, size=5)), \n row=1, col=1)\n\nfig.add_trace(go.Histogram(x=df['age_cat'], name='AGE CATEGORES'), row=2, col=1)\n\nfig.update_layout(height=1000, \n width=800, \n bargap=0.2, \n bargroupgap=0.1, \n title_text=\"AGE AND AGE CATEGORY COUNTS\")\nfig.show()","execution_count":9,"outputs":[{"output_type":"display_data","data":{"text/html":" <script type=\"text/javascript\">\n window.PlotlyConfig = {MathJaxConfig: 'local'};\n if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n if (typeof require !== 'undefined') {\n require.undef(\"plotly\");\n requirejs.config({\n paths: {\n 'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n }\n });\n require(['plotly'], function(Plotly) {\n window._Plotly = Plotly;\n });\n }\n </script>\n "},"metadata":{}},{"output_type":"display_data","data":{"text/html":"<div> <div id=\"60d0586a-7b26-4ffc-ac9c-dcf054c2f08f\" class=\"plotly-graph-div\" style=\"height:1000px; width:800px;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"60d0586a-7b26-4ffc-ac9c-dcf054c2f08f\")) { Plotly.newPlot( \"60d0586a-7b26-4ffc-ac9c-dcf054c2f08f\", [{\"name\": \"AGE\", \"type\": \"histogram\", \"x\": [25, 52, 29, 50, 52, 37, 35, 38, 29, 36, 63, 27, 39, 26, 26, 48, 51, 26, 44, 53, 55, 31, 50, 62, 25, 40, 35, 38, 28, 36, 53, 29, 39, 35, 68, 38, 50, 25, 29, 35, 26, 51, 56, 35, 28, 54, 51, 36, 35, 52, 47, 43, 30, 32, 53, 68, 27, 49, 35, 47, 34, 34, 27, 39, 40, 34, 37, 26, 29, 56, 28, 51, 52, 41, 37, 45, 42, 52, 72, 29, 26, 33, 40, 28, 40, 33, 27, 30, 33, 28, 46, 37, 27, 35, 27, 33, 30, 50, 40, 48, 34, 32, 42, 37, 29, 28, 59, 51, 37, 31, 38, 35, 37, 34, 34, 49, 35, 25, 29, 29, 27, 44, 25, 66, 36, 33, 37, 45, 28, 38, 43, 45, 27, 37, 27, 28, 30, 62, 54, 29, 34, 26, 65, 37, 48, 32, 29, 25, 37, 29, 37, 31, 40, 46, 46, 60, 49, 83, 49, 25, 24, 54, 25, 42, 42, 25, 65, 48, 35, 69, 38, 37, 32, 49, 30, 25, 50, 38, 33, 28, 32, 80, 63, 34, 51, 34, 28, 32, 73, 34, 34, 33, 39, 52, 41, 54, 40, 32], \"xaxis\": \"x\", \"xbins\": {\"end\": 90, \"size\": 5, \"start\": 20}, \"yaxis\": \"y\"}, {\"name\": \"AGE CATEGORES\", \"type\": \"histogram\", \"x\": [\"young adult\", \"middle age\", \"young adult\", \"middle age\", \"middle age\", \"middle age\", \"young adult\", \"middle age\", \"young adult\", \"middle age\", \"senior adult\", \"young adult\", \"middle age\", \"young adult\", \"young adult\", \"middle age\", \"middle age\", \"young adult\", \"middle age\", \"middle age\", \"middle age\", \"young adult\", \"middle age\", \"senior adult\", \"young adult\", \"middle age\", \"young adult\", \"middle age\", \"young adult\", \"middle age\", \"middle age\", \"young adult\", \"middle age\", \"young adult\", \"senior adult\", \"middle age\", \"middle age\", \"young adult\", \"young adult\", \"young adult\", \"young adult\", \"middle age\", \"senior adult\", \"young adult\", \"young adult\", \"middle age\", \"middle age\", \"middle age\", \"young adult\", \"middle age\", \"middle age\", \"middle age\", \"young adult\", \"young adult\", \"middle age\", \"senior adult\", \"young adult\", \"middle age\", \"young adult\", \"middle age\", \"young adult\", \"young adult\", \"young adult\", \"middle age\", \"middle age\", \"young adult\", \"middle age\", \"young adult\", \"young adult\", \"senior adult\", \"young adult\", \"middle age\", \"middle age\", \"middle age\", \"middle age\", \"middle age\", \"middle age\", \"middle age\", \"senior adult\", \"young adult\", \"young adult\", \"young adult\", \"middle age\", \"young adult\", \"middle age\", \"young adult\", \"young adult\", \"young adult\", \"young adult\", 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variables and observe any correlations between any of the variables. By performing bivariate and multivariate analyses we can determine which variables may be having the most effect on the change in Memory Score. "},{"metadata":{},"cell_type":"markdown","source":"<a id=\"memscore\"></a>\n\n### MEMORY SCORE COMPARISONS\n\nAside from name, the only patient information that we have to work with is age. While it would be preferable to have another variable such as sex to provide more insight, age may give an indication of how memory score might be impacted in this study. 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score. The higher the dosage, the greater the increase in memory score. \n* This is in contrast to the Drug T (Triazolam) and S (Sugar placebo) which had no discernable impact on memory score. "},{"metadata":{},"cell_type":"markdown","source":"A more generalized perspective with the bar chart below shows us that Drug A (Alprazolam) does indeed have a more positive impact on memory score as opposed to Drug T (Triazolam) and the Sugar placebo, which both resulted in a decrease in average memory score."},{"metadata":{"trusted":true},"cell_type":"code","source":"# Add histogram data\nx0 = df['Mem_Score_Before'].loc[df['Happy_Sad_group'] == 'H']\nx1 = df['Mem_Score_After'].loc[df['Happy_Sad_group'] == 'H']\n\nfig = make_subplots(rows=1, cols=2)\n\nbinstart = x0.min()\nbinend = x0.max()\n\ntrace0 = go.Histogram(x=x0, ybins=dict(start=20, end=120, size=10), name='Before')\ntrace1 = go.Histogram(x=x1, ybins=dict(start=20, end=120, size=10), name='After')\n\nfig.append_trace(trace0, 1, 1)\nfig.append_trace(trace1, 1, 2)\n\nfig.update_layout(height=500, \n width=800, \n bargap=0.2, \n bargroupgap=0.1, \n title_text=\"Memory Score Before vs After of Happy 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\"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Memory Score Before vs After of Sad Group\"}, \"width\": 800, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 0.45]}, \"xaxis2\": {\"anchor\": \"y2\", \"domain\": [0.55, 1.0]}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0]}, \"yaxis2\": {\"anchor\": \"x2\", \"domain\": [0.0, 1.0]}}, {\"responsive\": true} ).then(function(){\n \nvar gd = document.getElementById('373b14c0-5387-4bc4-9c70-0ddfb59b3e8a');\nvar x = new MutationObserver(function (mutations, observer) {{\n var display = window.getComputedStyle(gd).display;\n if (!display || display === 'none') {{\n console.log([gd, 'removed!']);\n Plotly.purge(gd);\n observer.disconnect();\n }}\n}});\n\n// Listen for the removal of the full notebook cells\nvar notebookContainer = gd.closest('#notebook-container');\nif (notebookContainer) {{\n x.observe(notebookContainer, {childList: true});\n}}\n\n// Listen for the clearing of the current output cell\nvar outputEl = gd.closest('.output');\nif (outputEl) {{\n x.observe(outputEl, {childList: true});\n}}\n\n }) }; }); </script> </div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"mem_score_avg = df.groupby(['age_cat', 'Drug'])[['Mem_Score_Before', 'Mem_Score_After']].agg('mean')\nmem_score_avg.reset_index(inplace=True)\nmem_score_avg.rename(columns={'Mem_Score_Before':'avg_mem_score_before', \n 'Mem_Score_After':'avg_mem_score_after'}, inplace=True)\nmem_score_avg = pd.melt(mem_score_avg, id_vars=['Drug', 'age_cat'], value_vars=['avg_mem_score_before', 'avg_mem_score_after'])\n\nmem_score_avg.rename(columns={\"variable\":\"avg_mem_score\"}, inplace=True)\nmem_score_avg.replace({'avg_mem_score_before': 'before', 'avg_mem_score_after':'after'}, inplace=True)\nmem_score_avg","execution_count":25,"outputs":[{"output_type":"execute_result","execution_count":25,"data":{"text/plain":" Drug age_cat avg_mem_score value\n0 A middle age before 54.869697\n1 S middle age before 58.192857\n2 T middle age before 55.134615\n3 A senior adult before 60.540000\n4 S senior adult before 67.925000\n5 T senior adult before 68.922222\n6 A young adult before 61.613793\n7 S young adult before 57.614706\n8 T young adult before 55.453333\n9 A middle age after 64.360606\n10 S middle age after 58.410714\n11 T middle age after 54.188462\n12 A senior adult after 65.840000\n13 S senior adult after 70.650000\n14 T senior adult after 66.400000\n15 A young adult after 71.779310\n16 S young adult after 56.782353\n17 T young adult after 55.756667","text/html":"<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Drug</th>\n <th>age_cat</th>\n <th>avg_mem_score</th>\n <th>value</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>A</td>\n <td>middle age</td>\n <td>before</td>\n <td>54.869697</td>\n </tr>\n <tr>\n <th>1</th>\n <td>S</td>\n <td>middle age</td>\n <td>before</td>\n <td>58.192857</td>\n </tr>\n <tr>\n <th>2</th>\n <td>T</td>\n <td>middle age</td>\n <td>before</td>\n <td>55.134615</td>\n </tr>\n <tr>\n <th>3</th>\n <td>A</td>\n <td>senior adult</td>\n <td>before</td>\n <td>60.540000</td>\n </tr>\n <tr>\n <th>4</th>\n <td>S</td>\n <td>senior adult</td>\n <td>before</td>\n <td>67.925000</td>\n </tr>\n <tr>\n <th>5</th>\n <td>T</td>\n <td>senior adult</td>\n <td>before</td>\n <td>68.922222</td>\n </tr>\n <tr>\n <th>6</th>\n <td>A</td>\n <td>young adult</td>\n <td>before</td>\n <td>61.613793</td>\n </tr>\n <tr>\n <th>7</th>\n <td>S</td>\n <td>young adult</td>\n <td>before</td>\n <td>57.614706</td>\n </tr>\n <tr>\n <th>8</th>\n <td>T</td>\n <td>young adult</td>\n <td>before</td>\n <td>55.453333</td>\n </tr>\n <tr>\n <th>9</th>\n <td>A</td>\n <td>middle age</td>\n <td>after</td>\n <td>64.360606</td>\n </tr>\n <tr>\n <th>10</th>\n <td>S</td>\n <td>middle age</td>\n <td>after</td>\n <td>58.410714</td>\n </tr>\n <tr>\n <th>11</th>\n <td>T</td>\n <td>middle age</td>\n <td>after</td>\n <td>54.188462</td>\n </tr>\n <tr>\n <th>12</th>\n <td>A</td>\n <td>senior adult</td>\n <td>after</td>\n <td>65.840000</td>\n </tr>\n <tr>\n <th>13</th>\n <td>S</td>\n <td>senior adult</td>\n <td>after</td>\n <td>70.650000</td>\n </tr>\n <tr>\n <th>14</th>\n <td>T</td>\n <td>senior adult</td>\n <td>after</td>\n <td>66.400000</td>\n </tr>\n <tr>\n <th>15</th>\n <td>A</td>\n <td>young adult</td>\n <td>after</td>\n <td>71.779310</td>\n </tr>\n <tr>\n <th>16</th>\n <td>S</td>\n <td>young adult</td>\n <td>after</td>\n <td>56.782353</td>\n </tr>\n <tr>\n <th>17</th>\n <td>T</td>\n <td>young adult</td>\n <td>after</td>\n <td>55.756667</td>\n </tr>\n </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Add histogram data\ny0 = df['Mem_Score_Before'].loc[df['Drug'] == 'A']\ny1 = df['Mem_Score_After'].loc[df['Drug'] == 'A']\n\nfig = make_subplots(rows=1, cols=2)\n\nbinstart = y0.min()\nbinend = y0.max()\n\ntrace0 = go.Histogram(y=y0, ybins=dict(start=20, end=binend, size=10), name='Before')\ntrace1 = go.Histogram(y=y1, ybins=dict(start=20, end=binend, size=10), name='After')\n\nfig.append_trace(trace0, 1, 1)\nfig.append_trace(trace1, 1, 2)\n\nfig.update_layout(height=500, \n width=800, \n bargap=0.2, \n bargroupgap=0.1, \n title_text=\"Memory Score Before vs After of Drug A\")\nfig.show()","execution_count":26,"outputs":[{"output_type":"display_data","data":{"text/html":"<div> <div id=\"413f051e-65fb-4f0c-8e40-2d78e1fcc6d6\" class=\"plotly-graph-div\" style=\"height:500px; width:800px;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"413f051e-65fb-4f0c-8e40-2d78e1fcc6d6\")) { Plotly.newPlot( \"413f051e-65fb-4f0c-8e40-2d78e1fcc6d6\", [{\"name\": \"Before\", \"type\": \"histogram\", \"xaxis\": \"x\", \"y\": [63.5, 41.6, 59.7, 51.7, 47.0, 66.4, 44.1, 76.3, 56.2, 54.8, 90.0, 52.3, 35.5, 85.6, 42.3, 53.5, 48.3, 64.0, 74.3, 45.0, 52.1, 79.9, 55.7, 46.5, 48.5, 47.0, 75.0, 90.0, 43.9, 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{\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Memory Score Before vs After of Drug S\"}, \"width\": 800, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 0.45]}, \"xaxis2\": {\"anchor\": \"y2\", \"domain\": [0.55, 1.0]}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0]}, \"yaxis2\": {\"anchor\": \"x2\", \"domain\": [0.0, 1.0]}}, {\"responsive\": true} ).then(function(){\n \nvar gd = document.getElementById('094d48cd-002a-4fd6-926d-eace7d110ace');\nvar x = new MutationObserver(function (mutations, observer) {{\n var display = window.getComputedStyle(gd).display;\n if (!display || display === 'none') {{\n console.log([gd, 'removed!']);\n Plotly.purge(gd);\n observer.disconnect();\n }}\n}});\n\n// Listen for the removal of the full notebook cells\nvar notebookContainer = gd.closest('#notebook-container');\nif (notebookContainer) {{\n x.observe(notebookContainer, {childList: true});\n}}\n\n// Listen for the clearing of the current output cell\nvar outputEl = gd.closest('.output');\nif (outputEl) {{\n x.observe(outputEl, {childList: true});\n}}\n\n }) }; }); </script> </div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Add histogram data\ny0 = df['Mem_Score_Before'].loc[df['Drug'] == 'T']\ny1 = df['Mem_Score_After'].loc[df['Drug'] == 'T']\n\nfig = make_subplots(rows=1, cols=2)\n\nbinstart = y0.min()\nbinend = y0.max()\n\ntrace0 = go.Histogram(y=y0, ybins=dict(start=20, end=binend, size=10), name='Before')\ntrace1 = go.Histogram(y=y1, ybins=dict(start=20, end=binend, size=10), name='After')\n\nfig.append_trace(trace0, 1, 1)\nfig.append_trace(trace1, 1, 2)\n\nfig.update_layout(height=500, \n width=800, \n bargap=0.2, \n bargroupgap=0.1, \n title_text=\"Memory Score Before vs After of Drug T\")\nfig.show()","execution_count":28,"outputs":[{"output_type":"display_data","data":{"text/html":"<div> <div id=\"10b4768d-6415-4e45-857c-86b50dd7b590\" class=\"plotly-graph-div\" 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\"y2\", \"domain\": [0.55, 1.0]}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0]}, \"yaxis2\": {\"anchor\": \"x2\", \"domain\": [0.0, 1.0]}}, {\"responsive\": true} ).then(function(){\n \nvar gd = document.getElementById('10b4768d-6415-4e45-857c-86b50dd7b590');\nvar x = new MutationObserver(function (mutations, observer) {{\n var display = window.getComputedStyle(gd).display;\n if (!display || display === 'none') {{\n console.log([gd, 'removed!']);\n Plotly.purge(gd);\n observer.disconnect();\n }}\n}});\n\n// Listen for the removal of the full notebook cells\nvar notebookContainer = gd.closest('#notebook-container');\nif (notebookContainer) {{\n x.observe(notebookContainer, {childList: true});\n}}\n\n// Listen for the clearing of the current output cell\nvar outputEl = gd.closest('.output');\nif (outputEl) {{\n x.observe(outputEl, {childList: true});\n}}\n\n }) }; }); </script> </div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"<a id=\"diff\"></a>\n\n### DIFFERENCE COMPARISONS\n\nIn this section we'll perform an exploratory analysis of the values in the **Diff** column. We'll correlate them with other variables. Our results should reflect findings from the above analyses, however it will provide a different perspective on the data. "},{"metadata":{"trusted":true},"cell_type":"code","source":"fig = px.scatter(df, x=\"age\", y=\"Diff\", \n color=\"age_cat\", \n template='plotly_dark')\nfig.update_layout(title_text=\"Diff vs Age\")\nfig.show()","execution_count":29,"outputs":[{"output_type":"display_data","data":{"text/html":"<div> <div id=\"3c4eb819-bf37-436f-8fea-25217038c8d9\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"3c4eb819-bf37-436f-8fea-25217038c8d9\")) { Plotly.newPlot( \"3c4eb819-bf37-436f-8fea-25217038c8d9\", [{\"hovertemplate\": \"age_cat=young adult<br>age=%{x}<br>Diff=%{y}<extra></extra>\", \"legendgroup\": \"young adult\", \"marker\": {\"color\": \"#636efa\", \"symbol\": \"circle\"}, \"mode\": \"markers\", \"name\": \"young adult\", \"orientation\": \"v\", \"showlegend\": true, \"type\": \"scatter\", \"x\": [25, 29, 35, 29, 27, 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\"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Diff x Age Category\"}, \"width\": 1000, \"yaxis\": {\"autorange\": true, \"dtick\": 5, \"gridcolor\": \"rgb(255, 255, 255)\", \"gridwidth\": 1, \"showgrid\": true, \"zeroline\": true, \"zerolinecolor\": \"rgb(255, 255, 255)\", \"zerolinewidth\": 2}}, {\"responsive\": true} ).then(function(){\n \nvar gd = 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score"},{"metadata":{"trusted":true},"cell_type":"code","source":"y0 = df[['Diff']].loc[df['Drug'] == 'A']\ny1 = df[['Diff']].loc[df['Drug'] == 'T']\ny2 = df[['Diff']].loc[df['Drug'] == 'S']\n\nfig = go.Figure()\n\nfig.add_trace(go.Box(y=y0['Diff'], name='A: Alprazolam', boxpoints=\"all\", boxmean=True))\nfig.add_trace(go.Box(y=y1['Diff'], name='T: Triazolam', boxpoints=\"all\", boxmean=True))\nfig.add_trace(go.Box(y=y2['Diff'], name='S: Sugar', boxpoints=\"all\", boxmean=True))\n\nfig.update_layout(height=600, \n width=1000, \n title_text=\"Diff x Drug\",\n yaxis=dict(autorange=True,\n showgrid=True,\n zeroline=True,\n dtick=5,\n gridcolor='rgb(255, 255, 255)',\n gridwidth=1,\n zerolinecolor='rgb(255, 255, 255)',\n zerolinewidth=2)\n )\nfig.show()","execution_count":31,"outputs":[{"output_type":"display_data","data":{"text/html":"<div> <div id=\"b6872cae-a9a8-4cb7-aa60-8a309252a14b\" class=\"plotly-graph-div\" style=\"height:600px; width:1000px;\"></div> <script 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</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"### MEMORY SCORE DIFFERENCE BY DRUG & DOSAGE"},{"metadata":{"trusted":true},"cell_type":"code","source":"x0=df['Drug'].loc[df['Dosage'] == 1]\nx1=df['Drug'].loc[df['Dosage'] == 2]\nx2=df['Drug'].loc[df['Dosage'] == 3]\n\ny0 = df[['Diff']].loc[df['Dosage'] == 1]\ny1 = df[['Diff']].loc[df['Dosage'] == 2]\ny2 = df[['Diff']].loc[df['Dosage'] == 3]\n\n\nfig = go.Figure()\n\nfig.add_trace(go.Box(y=y0['Diff'], x=x0, name='1 Dose', marker_size=3, boxpoints=\"all\", boxmean=True))\nfig.add_trace(go.Box(y=y1['Diff'], x=x1, name='2 Doses', marker_size=3, boxpoints=\"all\", boxmean=True))\nfig.add_trace(go.Box(y=y2['Diff'], x=x2, name='3 Doses', marker_size=3, boxpoints=\"all\", boxmean=True))\n\nfig.update_layout(height=500, \n width=1000,\n title_text='Diff x Drug & Dosage',\n yaxis_title='Diff',\n boxmode='group',\n yaxis=dict(autorange=True,\n showgrid=True,\n zeroline=True,\n dtick=10,\n gridcolor='rgb(255, 255, 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</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"### HIGHEST MEMORY SCORE DIFFERENCES\n\nIn this section we look at the samples containing both the 10 highest and 10 lowest values in the Diff column to determine which drug is associated with each. \n\nFor the highest values, 9 out of the highest 10 memory score differences were from the drug Alprazolam with one belonging to Triazolam\n\nFor the lowest values there was more of a mixture, with 4 belonging to Sugar, 4 belonging to Triazolam, and 2 belonging to Alprazolam. \n"},{"metadata":{"trusted":true},"cell_type":"code","source":"# CREATE DATAFRAME CONTAINING HIGHEST 10 VALUES OF 'DIFF' COLUMN\n\ntop_10_diff = df.sort_values('Diff', ascending=False)[:10]\ntop_10_diff.sort_values('Diff', ascending=False, inplace=True)\n# top_10_diff","execution_count":35,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"fig = px.bar(top_10_diff, x='Diff', y='full_name', color=\"Drug\",\n title='10 Patients with Greatest Mem Score Increase', \n text='Diff', orientation='h', hover_data=[\"age_cat\", \"Dosage\", 'Happy_Sad_group'])\n\nfig.update_layout(height=500, \n width=800, \n bargap=0.2, \n bargroupgap=0.1,\n yaxis={'categoryorder':'total ascending'}\n )\nfig.show()\n","execution_count":36,"outputs":[{"output_type":"display_data","data":{"text/html":"<div> <div id=\"7c96d4bc-7690-42ad-aa27-400dd56d8241\" class=\"plotly-graph-div\" style=\"height:500px; width:800px;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"7c96d4bc-7690-42ad-aa27-400dd56d8241\")) { Plotly.newPlot( \"7c96d4bc-7690-42ad-aa27-400dd56d8241\", [{\"alignmentgroup\": \"True\", \"customdata\": [[\"young adult\", 3, \"H\"], [\"young adult\", 3, \"S\"], [\"young adult\", 3, \"S\"], [\"middle age\", 3, \"S\"], [\"middle age\", 3, \"H\"], [\"young adult\", 3, \"H\"], [\"middle age\", 3, \"H\"], [\"senior adult\", 3, 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true});\n}}\n\n }) }; }); </script> </div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"low_10_diff = df.sort_values('Diff', ascending=True)[:10]\nlow_10_diff.sort_values('Diff', ascending=True, inplace=True)\n# low_10_diff","execution_count":37,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"fig = px.bar(low_10_diff, x='Diff', y='full_name', color='Drug',\n title='10 Patients with Greatest Mem Score Decrease', \n text='Diff', orientation='h',\n hover_data=[\"age_cat\", \"Dosage\", 'Happy_Sad_group'])\n\nfig.update_layout(height=500, \n width=800, \n bargap=0.2, \n bargroupgap=0.1,\n yaxis={'categoryorder':'total ascending'}\n )\nfig.show()\n","execution_count":38,"outputs":[{"output_type":"display_data","data":{"text/html":"<div> <div id=\"f984e3dc-0813-4b03-8e54-bad0fd5fd6a0\" class=\"plotly-graph-div\" style=\"height:500px; width:800px;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], function(Plotly) { 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\"x\", \"categoryorder\": \"total ascending\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"full_name\"}}}, {\"responsive\": true} ).then(function(){\n \nvar gd = document.getElementById('f984e3dc-0813-4b03-8e54-bad0fd5fd6a0');\nvar x = new MutationObserver(function (mutations, observer) {{\n var display = window.getComputedStyle(gd).display;\n if (!display || display === 'none') {{\n console.log([gd, 'removed!']);\n Plotly.purge(gd);\n observer.disconnect();\n }}\n}});\n\n// Listen for the removal of the full notebook cells\nvar notebookContainer = gd.closest('#notebook-container');\nif (notebookContainer) {{\n x.observe(notebookContainer, {childList: true});\n}}\n\n// Listen for the clearing of the current output cell\nvar outputEl = gd.closest('.output');\nif (outputEl) {{\n x.observe(outputEl, {childList: true});\n}}\n\n }) }; }); </script> </div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"<a id=\"diffcat\"></a>\n\n### DIFFERENCE CATEGORY ANALYSIS\n\nEarlier in this notebook the values in the \"Diff\" column were separated into three different categories: **Decrease** for the values that had a negative difference, **Increase** for the values that had a positive difference, **No Change** for the values that remained the same. \n\nIn this section I visualized the number of samples belonging to each of those categories according to their Drug Type, Happy/Sad group, Dosage amount, and age category"},{"metadata":{"trusted":true},"cell_type":"code","source":"diff_cat_count = df.groupby(['diff_cat', 'Drug'])[['Diff']].agg('count')\ndiff_cat_count.reset_index(inplace=True)\ndiff_cat_count.rename(columns={'Diff':'count'}, inplace=True)\n\nlabels = [\"decrease\", \"increase\", \"no change\"]\npie0 = diff_cat_count['count'].loc[diff_cat_count['Drug'] == 'A']\npie1 = diff_cat_count['count'].loc[diff_cat_count['Drug'] == 'T']\npie2 = diff_cat_count['count'].loc[diff_cat_count['Drug'] == 'S']\n\nfig = make_subplots(rows=1, cols=3, specs=[[{'type':'domain'}, {'type':'domain'}, {'type':'domain'}]], \n subplot_titles=['Alprazolam', 'Triazolam', 'Sugar'])\n\nfig.add_trace(go.Pie(labels=labels, values=pie0, name=\"Alprazolam\"),\n 1, 1)\nfig.add_trace(go.Pie(labels=labels, values=pie1, name=\"Triazolam\"),\n 1, 2)\nfig.add_trace(go.Pie(labels=labels, values=pie2, name=\"Sugar\"),\n 1, 3)\n\nfig.update_traces(hoverinfo=\"label+name+value\")\n\nfig.update_layout(title_text=\"Diff Category According to Drug Type\")\n\nfig.show()","execution_count":39,"outputs":[{"output_type":"display_data","data":{"text/html":"<div> <div id=\"e0bb1cad-e5c4-48ea-be4b-31fdc8175774\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"e0bb1cad-e5c4-48ea-be4b-31fdc8175774\")) { Plotly.newPlot( \"e0bb1cad-e5c4-48ea-be4b-31fdc8175774\", [{\"domain\": {\"x\": [0.0, 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observer.disconnect();\n }}\n}});\n\n// Listen for the removal of the full notebook cells\nvar notebookContainer = gd.closest('#notebook-container');\nif (notebookContainer) {{\n x.observe(notebookContainer, {childList: true});\n}}\n\n// Listen for the clearing of the current output cell\nvar outputEl = gd.closest('.output');\nif (outputEl) {{\n x.observe(outputEl, {childList: true});\n}}\n\n }) }; }); </script> </div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"**OBSERVATIONS**\n\nAlthough patients primed with sad memories do report an increase in memory score at a rate approximately 2% greater than patients primed with Happy memories, there does not appear to be a significant difference in how happy or sad memories affect memory score. "},{"metadata":{"trusted":true},"cell_type":"code","source":"diff_cat_dose = df.groupby(['diff_cat', 'Dosage'])[['Diff']].agg('count')\ndiff_cat_dose.reset_index(inplace=True)\ndiff_cat_dose.rename(columns={'Diff':'count'}, inplace=True)\ndiff_cat_dose\n\nlabels = [\"decrease\", \"increase\", \"no change\"]\npie0 = diff_cat_dose['count'].loc[diff_cat_dose['Dosage'] == 1]\npie1 = diff_cat_dose['count'].loc[diff_cat_dose['Dosage'] == 2]\npie2 = diff_cat_dose['count'].loc[diff_cat_dose['Dosage'] == 3]\n\nfig = make_subplots(rows=1, cols=3, specs=[[{'type':'domain'}, {'type':'domain'}, {'type':'domain'}]], \n subplot_titles=['1 Dose', '2 Doses', '3 Doses'])\n\nfig.add_trace(go.Pie(labels=labels, values=pie0, name=\"1 Dose\"), 1, 1)\nfig.add_trace(go.Pie(labels=labels, values=pie1, name=\"2 Doses\"), 1, 2)\nfig.add_trace(go.Pie(labels=labels, values=pie2, name=\"3 Doses\"), 1, 3)\n\nfig.update_traces(hoverinfo=\"label+name+value\")\n\nfig.update_layout(title_text=\"Diff Category According to Dosage\")\n\nfig.show()","execution_count":41,"outputs":[{"output_type":"display_data","data":{"text/html":"<div> <div id=\"0ffa3699-c850-4c10-b6b1-a1717be65603\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"0ffa3699-c850-4c10-b6b1-a1717be65603\")) { Plotly.newPlot( \"0ffa3699-c850-4c10-b6b1-a1717be65603\", [{\"domain\": {\"x\": [0.0, 0.2888888888888889], \"y\": [0.0, 1.0]}, \"hoverinfo\": \"label+name+value\", \"labels\": [\"decrease\", \"increase\", \"no change\"], \"name\": \"1 Dose\", \"type\": \"pie\", \"values\": [33, 31, 3]}, {\"domain\": {\"x\": [0.35555555555555557, 0.6444444444444445], \"y\": [0.0, 1.0]}, \"hoverinfo\": \"label+name+value\", \"labels\": [\"decrease\", \"increase\", \"no change\"], \"name\": \"2 Doses\", \"type\": \"pie\", \"values\": [26, 39, 1]}, {\"domain\": {\"x\": [0.7111111111111111, 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true});\n}}\n\n }) }; }); </script> </div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"**OBSERVATIONS**\n\nOn average, the patients who recieved a higher drug dosage reported higher increases in memory score. "},{"metadata":{"trusted":true},"cell_type":"code","source":"diff_cat_age = df.groupby(['diff_cat', 'age_cat'])[['Diff']].agg('count')\ndiff_cat_age.reset_index(inplace=True)\ndiff_cat_age.rename(columns={'Diff':'count'}, inplace=True)\n\nlabels = [\"decrease\", \"increase\", \"no change\"]\npie0 = diff_cat_age['count'].loc[diff_cat_age['age_cat'] == 'young adult']\npie1 = diff_cat_age['count'].loc[diff_cat_age['age_cat'] == 'middle age']\npie2 = diff_cat_age['count'].loc[diff_cat_age['age_cat'] == 'senior adult']\n\nfig = make_subplots(rows=1, cols=3, specs=[[{'type':'domain'}, {'type':'domain'}, {'type':'domain'}]], \n subplot_titles=['Young Adult', 'Middle Age', 'Senior Adult'])\n\nfig.add_trace(go.Pie(labels=labels, values=pie0, name=\"Young Adult\"), 1, 1)\nfig.add_trace(go.Pie(labels=labels, values=pie1, name=\"Middle Adult\"), 1, 2)\nfig.add_trace(go.Pie(labels=labels, values=pie2, name=\"Senior\"), 1, 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\"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Diff Category According to Age Category\"}}, {\"responsive\": true} ).then(function(){\n \nvar gd = document.getElementById('6a5f613f-fc64-4366-9e3b-72308f3f0d60');\nvar x = new MutationObserver(function (mutations, observer) {{\n var display = window.getComputedStyle(gd).display;\n if (!display || display === 'none') {{\n console.log([gd, 'removed!']);\n Plotly.purge(gd);\n observer.disconnect();\n }}\n}});\n\n// Listen for the removal of the full notebook cells\nvar notebookContainer = gd.closest('#notebook-container');\nif (notebookContainer) {{\n x.observe(notebookContainer, {childList: true});\n}}\n\n// Listen for the clearing of the current output cell\nvar outputEl = gd.closest('.output');\nif (outputEl) {{\n x.observe(outputEl, {childList: true});\n}}\n\n }) }; }); </script> </div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"diff_cat_age","execution_count":43,"outputs":[{"output_type":"execute_result","execution_count":43,"data":{"text/plain":" diff_cat age_cat count\n0 decrease middle age 33\n1 decrease senior adult 8\n2 decrease young adult 39\n3 increase middle age 53\n4 increase senior adult 10\n5 increase young adult 51\n6 no change middle age 1\n7 no change young adult 3","text/html":"<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>diff_cat</th>\n <th>age_cat</th>\n <th>count</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>decrease</td>\n <td>middle age</td>\n <td>33</td>\n </tr>\n <tr>\n <th>1</th>\n <td>decrease</td>\n <td>senior adult</td>\n <td>8</td>\n </tr>\n <tr>\n <th>2</th>\n <td>decrease</td>\n <td>young adult</td>\n <td>39</td>\n </tr>\n <tr>\n <th>3</th>\n <td>increase</td>\n <td>middle age</td>\n <td>53</td>\n </tr>\n <tr>\n <th>4</th>\n <td>increase</td>\n <td>senior adult</td>\n <td>10</td>\n </tr>\n <tr>\n <th>5</th>\n <td>increase</td>\n <td>young adult</td>\n <td>51</td>\n </tr>\n <tr>\n <th>6</th>\n <td>no change</td>\n <td>middle age</td>\n <td>1</td>\n </tr>\n <tr>\n <th>7</th>\n <td>no change</td>\n <td>young adult</td>\n <td>3</td>\n </tr>\n </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"**OBSERVATIONS**\n\nOn average, middle age patients responded more favorably to this study with a 5% to 6% higher rate of increased memory score. "},{"metadata":{},"cell_type":"markdown","source":"<a id=\"features\"></a>\n\n## ADDITIONAL FEATURE ENGINEERING\n\nLet's use Label Encoder to transform some of the categorical variables into numerical values so that we may run our algorithms. "},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.preprocessing import LabelEncoder\n\ndf1 = pd.read_csv('../input/memory-test-on-drugged-islanders-data/Islander_data.csv')\n\n# Happy Sad group: H = 0, S = 1\nle = LabelEncoder()\nle.fit(df1.Happy_Sad_group.drop_duplicates()) \ndf1.Happy_Sad_group = le.transform(df1.Happy_Sad_group)\n\n# Drug: A=0, S=1, T=2\nle.fit(df1.Drug.drop_duplicates()) \ndf1.Drug = le.transform(df1.Drug)\n","execution_count":44,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"<a id=\"clustering\"></a>\n\n## CLUSTERING"},{"metadata":{},"cell_type":"markdown","source":"<a id=\"kmeans\"></a>\n\n### K-MEANS CLUSTERING"},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.cluster import KMeans \nfrom sklearn.preprocessing import StandardScaler","execution_count":45,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"X = df1[['age', 'Happy_Sad_group', 'Dosage', 'Drug', 'Mem_Score_Before', 'Mem_Score_After', 'Diff']]","execution_count":46,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"X_clus = StandardScaler().fit_transform(X)\nX_clus","execution_count":47,"outputs":[{"output_type":"execute_result","execution_count":47,"data":{"text/plain":"array([[-1.2115957 , -1. , -1.2124665 , ..., 0.35179148,\n 0.01535702, -0.48982424],\n [ 1.03977399, 1. , -1.2124665 , ..., -1.04079408,\n -1.11799101, -0.35931743],\n [-0.87805945, -1. , -1.2124665 , ..., 0.11015563,\n -0.32188313, -0.70422827],\n ...,\n [ 1.20654212, 1. , 1.23721071, ..., -1.7275486 ,\n -1.53815907, -0.06101617],\n [ 0.03916524, -1. , 1.23721071, ..., -0.2777335 ,\n -0.39375398, -0.25677637],\n [-0.62790726, 1. , 1.23721071, ..., -0.94541151,\n -1.04059164, -0.36863935]])"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"clusterNum = 3\nk_means = KMeans(init = \"k-means++\", n_clusters = clusterNum, n_init = 12)\nk_means.fit(X_clus)\nlabels = k_means.labels_\nprint(labels)","execution_count":48,"outputs":[{"output_type":"stream","text":"[0 2 0 2 0 2 2 1 0 1 1 2 0 1 2 0 2 0 2 0 2 1 2 0 2 0 1 1 0 1 1 0 2 0 2 0 1\n 0 1 2 1 0 2 1 0 1 1 1 1 2 2 1 0 1 1 1 1 2 0 1 1 1 2 1 1 1 1 0 1 2 0 0 2 0\n 2 2 2 0 1 0 2 0 0 1 2 0 2 0 2 0 0 2 2 0 0 1 2 1 0 0 2 2 0 0 2 1 2 1 1 2 0\n 2 0 0 2 0 0 2 2 0 1 2 1 1 2 0 2 0 1 1 2 1 2 2 0 0 2 1 2 0 2 0 0 2 2 2 0 0\n 2 0 2 2 0 0 1 1 2 0 1 1 2 0 2 0 2 2 0 2 0 2 2 0 0 0 2 0 2 0 0 2 0 2 2 0 1\n 0 0 1 1 1 1 2 0 1 2 2 0 2]\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df['cluster'] = labels\ndf.head()","execution_count":49,"outputs":[{"output_type":"execute_result","execution_count":49,"data":{"text/plain":" full_name age age_cat Happy_Sad_group Dosage Drug \\\n0 Bastian Carrasco 25 young adult H 1 A \n1 Evan Carrasco 52 middle age S 1 A \n2 Florencia Carrasco 29 young adult H 1 A \n3 Holly Carrasco 50 middle age S 1 A \n4 Justin Carrasco 52 middle age H 1 A \n\n Mem_Score_Before Mem_Score_After Diff diff_cat cluster \n0 63.5 61.2 -2.3 decrease 0 \n1 41.6 40.7 -0.9 decrease 2 \n2 59.7 55.1 -4.6 decrease 0 \n3 51.7 51.2 -0.5 decrease 2 \n4 47.0 47.1 0.1 increase 0 ","text/html":"<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>full_name</th>\n <th>age</th>\n <th>age_cat</th>\n <th>Happy_Sad_group</th>\n <th>Dosage</th>\n <th>Drug</th>\n <th>Mem_Score_Before</th>\n <th>Mem_Score_After</th>\n <th>Diff</th>\n <th>diff_cat</th>\n <th>cluster</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>Bastian Carrasco</td>\n <td>25</td>\n <td>young adult</td>\n <td>H</td>\n <td>1</td>\n <td>A</td>\n <td>63.5</td>\n <td>61.2</td>\n <td>-2.3</td>\n <td>decrease</td>\n <td>0</td>\n </tr>\n <tr>\n <th>1</th>\n <td>Evan Carrasco</td>\n <td>52</td>\n <td>middle age</td>\n <td>S</td>\n <td>1</td>\n <td>A</td>\n <td>41.6</td>\n <td>40.7</td>\n <td>-0.9</td>\n <td>decrease</td>\n <td>2</td>\n </tr>\n <tr>\n <th>2</th>\n <td>Florencia Carrasco</td>\n <td>29</td>\n <td>young adult</td>\n <td>H</td>\n <td>1</td>\n <td>A</td>\n <td>59.7</td>\n <td>55.1</td>\n <td>-4.6</td>\n <td>decrease</td>\n <td>0</td>\n </tr>\n <tr>\n <th>3</th>\n <td>Holly Carrasco</td>\n <td>50</td>\n <td>middle age</td>\n <td>S</td>\n <td>1</td>\n <td>A</td>\n <td>51.7</td>\n <td>51.2</td>\n <td>-0.5</td>\n <td>decrease</td>\n <td>2</td>\n </tr>\n <tr>\n <th>4</th>\n <td>Justin Carrasco</td>\n <td>52</td>\n <td>middle age</td>\n <td>H</td>\n <td>1</td>\n <td>A</td>\n <td>47.0</td>\n <td>47.1</td>\n <td>0.1</td>\n <td>increase</td>\n <td>0</td>\n </tr>\n </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"cluster_centers = k_means.cluster_centers_\ncluster_centers","execution_count":50,"outputs":[{"output_type":"execute_result","execution_count":50,"data":{"text/plain":"array([[-0.15539757, -1. , -0.17475601, 0.14846529, -0.43431989,\n -0.49641565, -0.200327 ],\n [ 0.15497644, 0. , 0.42065164, -0.39590743, 1.09153632,\n 1.33585593, 0.65228292],\n [ 0.03916524, 1. , -0.14073272, 0.14846529, -0.38433235,\n -0.50547629, -0.28888519]])"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"cluster0 = df.loc[df['cluster'] == 0]\ncluster1 = df.loc[df['cluster'] == 1]\ncluster2 = df.loc[df['cluster'] == 2]","execution_count":51,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"fig = px.scatter(df, x='Happy_Sad_group', y='Mem_Score_Before', color='cluster')\nfig.update_layout(title='Memory Score Before Distribution by Happy/Sad Group')\nfig.show()","execution_count":52,"outputs":[{"output_type":"display_data","data":{"text/html":"<div> <div 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\"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"Mem_Score_Before\"}}}, {\"responsive\": true} ).then(function(){\n \nvar gd = document.getElementById('5b05418d-b4f1-41a3-94b4-0c342ec81309');\nvar x = new MutationObserver(function (mutations, observer) {{\n var display = window.getComputedStyle(gd).display;\n if (!display || display === 'none') {{\n console.log([gd, 'removed!']);\n Plotly.purge(gd);\n observer.disconnect();\n }}\n}});\n\n// Listen for the removal of the full notebook cells\nvar notebookContainer = gd.closest('#notebook-container');\nif (notebookContainer) {{\n x.observe(notebookContainer, {childList: true});\n}}\n\n// Listen for the clearing of the current output cell\nvar outputEl = gd.closest('.output');\nif (outputEl) {{\n x.observe(outputEl, {childList: true});\n}}\n\n }) }; }); </script> </div>"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"<a id=\"hierarchical\"></a>\n\n### HIERARCHICAL CLUSTERING"},{"metadata":{"trusted":true},"cell_type":"code","source":"from scipy import ndimage \nfrom scipy.cluster import hierarchy \nfrom scipy.spatial import distance_matrix \nfrom matplotlib import pyplot as plt \nfrom sklearn import manifold, datasets \nfrom sklearn.cluster import AgglomerativeClustering \nimport pylab","execution_count":53,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"df2 = pd.read_csv('../input/memory-test-on-drugged-islanders-data/Islander_data.csv')","execution_count":54,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"agglom = AgglomerativeClustering(n_clusters = 3, linkage = 'complete')\nagglom.fit(X_clus)\nagglom.labels_","execution_count":55,"outputs":[{"output_type":"execute_result","execution_count":55,"data":{"text/plain":"array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1,\n 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1,\n 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 2,\n 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 2,\n 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 2, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0])"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"dist_matrix = distance_matrix(X_clus,X_clus) \nprint(dist_matrix)","execution_count":56,"outputs":[{"output_type":"stream","text":"[[0. 3.5084854 0.57387657 ... 5.36378328 3.76619497 4.37664003]\n [3.5084854 0. 3.12338304 ... 3.57306662 4.25680045 3.84683935]\n [0.57387657 3.12338304 0. ... 5.06138384 3.6330393 4.21992853]\n ...\n [5.36378328 3.57306662 5.06138384 ... 0. 2.96862218 2.07825608]\n [3.76619497 4.25680045 3.6330393 ... 2.96862218 0. 2.30687926]\n [4.37664003 3.84683935 4.21992853 ... 2.07825608 2.30687926 0. ]]\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"Z = hierarchy.linkage(dist_matrix, 'complete')","execution_count":57,"outputs":[{"output_type":"stream","text":"/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: ClusterWarning:\n\nscipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix\n\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"df2['cluster'] = agglom.labels_\ndf2.head()","execution_count":58,"outputs":[{"output_type":"execute_result","execution_count":58,"data":{"text/plain":" first_name last_name age Happy_Sad_group Dosage Drug Mem_Score_Before \\\n0 Bastian Carrasco 25 H 1 A 63.5 \n1 Evan Carrasco 52 S 1 A 41.6 \n2 Florencia Carrasco 29 H 1 A 59.7 \n3 Holly Carrasco 50 S 1 A 51.7 \n4 Justin Carrasco 52 H 1 A 47.0 \n\n Mem_Score_After Diff cluster \n0 61.2 -2.3 0 \n1 40.7 -0.9 0 \n2 55.1 -4.6 0 \n3 51.2 -0.5 0 \n4 47.1 0.1 0 ","text/html":"<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>first_name</th>\n <th>last_name</th>\n <th>age</th>\n <th>Happy_Sad_group</th>\n <th>Dosage</th>\n <th>Drug</th>\n <th>Mem_Score_Before</th>\n <th>Mem_Score_After</th>\n <th>Diff</th>\n <th>cluster</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>Bastian</td>\n <td>Carrasco</td>\n <td>25</td>\n <td>H</td>\n <td>1</td>\n <td>A</td>\n <td>63.5</td>\n <td>61.2</td>\n <td>-2.3</td>\n <td>0</td>\n </tr>\n <tr>\n <th>1</th>\n <td>Evan</td>\n <td>Carrasco</td>\n <td>52</td>\n <td>S</td>\n <td>1</td>\n <td>A</td>\n <td>41.6</td>\n <td>40.7</td>\n <td>-0.9</td>\n <td>0</td>\n </tr>\n <tr>\n <th>2</th>\n <td>Florencia</td>\n <td>Carrasco</td>\n <td>29</td>\n <td>H</td>\n <td>1</td>\n <td>A</td>\n <td>59.7</td>\n <td>55.1</td>\n <td>-4.6</td>\n <td>0</td>\n </tr>\n <tr>\n <th>3</th>\n <td>Holly</td>\n <td>Carrasco</td>\n <td>50</td>\n <td>S</td>\n <td>1</td>\n <td>A</td>\n <td>51.7</td>\n <td>51.2</td>\n <td>-0.5</td>\n <td>0</td>\n </tr>\n <tr>\n <th>4</th>\n <td>Justin</td>\n <td>Carrasco</td>\n <td>52</td>\n <td>H</td>\n <td>1</td>\n <td>A</td>\n <td>47.0</td>\n <td>47.1</td>\n <td>0.1</td>\n <td>0</td>\n </tr>\n </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"fig = pylab.figure(figsize=(18,50))\ndef llf(id):\n return '[%s %s %s %s]' % (df2['first_name'][id], df2['last_name'][id], df2['Happy_Sad_group'][id], df2['Mem_Score_Before'][id])\n \ndendro = hierarchy.dendrogram(Z, leaf_label_func=llf, leaf_rotation=0, leaf_font_size=12, orientation = 'right')","execution_count":60,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1296x3600 with 1 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9b7LMpb+Yvtg21/qqE3SAR0lkSTNkLRzd3PXRJQlrdh0r73ls0TSaZ2M31/SjZIel/SApJOb57L9FuDgHj1oRERERERERAwpQz3R9RxJO1LexLeP7ZHAaylvFlymbLc1PsD9wLub7l2wrOMZSmoi8AXnxrV8p6Mpb5q8pJNpRgCHAWsD21De2PiZ/ok4IiIiIiIiIgaT4XQY/RuAa21PA7D9KHBOS581Jf0S2AG4HZho+25JY4F7gZVsPwNlSyBwvu0fSDoAOBC4DvgwMB84xPYVPQ1O0tbAtygJuCeAS4FP2X6qg77bAT8CJgHTgfMoSZsVgWuAg203by3cSNI1wOuAa+tzza1zXQJsD7wUuBn4mO3batuuwNeADYDHgVNsf60pjk8DRwBLgCPrQe5IOht4wPYXevr83ZG0BnBMfeZru+i6J/AQcFVHjba/23T5T0kXAG9empjuXLQoh2v3k4mjR3PQmDEDHUZEREREREQMM8Omogv4C/B2SZMlvUnSKh302QeYDKwJ3AX06HyvahvgTkql0MnAmZLUi/FLgE/W8f9JqTQ6pLWTpLdTklx72P4D5Tc6C9gI2JCSJDu9ZdhE4IPAy4GV+dcKpiuAV9e2m4DmqrIzgY/WCrgtgN83ta0LrAGsR0nufVvSmr143t46EfguMLubfvsD59p2D+fdAbjtxQQWfWt6ezsXzpkz0GFERERERETEMDRsKrpsXyXpfZTk0SeAFSX9D3C47SW1209sXw9QK32+0Ysl7rP9/Tr2HOA7lG103SVmGvHd2HQ5Q9IZwI7AN5vu70U5P2pX27fWcY9Qqr+oa58A/KFl+rNs/722Xwzs1rTuD5vGHgvMk7SG7ceAp4HNJN1sex4wr2nOp4HjaoXb5ZLagU0pVW3d2VbS/JZ7q3fWWdJ44E2U3239LvptSPnOPtyDGJD0QWA8pRqv1zYdMYIpW221NEOjC6mSi4iIiIiIiP4ynCq6sH2F7XcDLwN2Bw7gX5MczUmpRUBbL6Z/bqztRfXPHo+XtImkX0iaLelxSgXT2i3dDgMubiS56rgRks6QdF8d9ydglKQVOoqNpueStIKkL0u6u46dUfs01t0D2BW4T9IfJf1n0zyPNLZxts7bA9fZHtX8oZxX9gKSXkJJGn6iZb2OTAKutn1vdwFIeg/wZWCXxjbOiIiIiIiIiBjehlWiq8H2s7Z/R9mKt0UPhiys/45ourduH4f1XeAO4NW2VweOBFq3Pu4FvEfSYU33Pk2ppNqmjtuh3u/JtsmJlITfzpRtiGObx9q+wfbulG2NP2MADu+nVHqNBy6SNBu4od5/QNL2LX0n8cJz115A0juA71NeBHBrd/0jIiIiIiIiYngYNokuSbtL2lvSmiq2pmxz63arne2HgX8C+9UqqA8Br+rjEEdSDnxvl/Qa4GMd9JlFObvr45IOaRr3BDBf0ssoB7b3Zs0ngUcoSbwTGw2SVpa0b93G+HSNbUnH0/Srx4AxwLj62bXefz3l3DUAJL2Rcl5YZ29bbPR7C+Ucsj0a21QjIiIiIiIiYvkwbBJdlPOlPgL8g5K0OR/4qu0Luhz1vI8Ah1OSQpsDf+7j+D5DqbBaQKk2uqijTrbvpyS7jpB0IOUMr5cCcylJu1/1Ys1zgfsoSbzbeWHS7wOU88Iep5wNtl8v5u4TLmY3PsDDtWlOyxsp96ecsbagebykDSW11/O7AI6mVK9dXu+3S+rx2zEjIiIiIiIiYuhSz19eN7hIWkypVjrV9tEDHU8MDZKuBLYFrre9U1d9x48f76lTpy6bwJYjE6ZNY3p7O+PaenNE3vKj8d0MxRchNF40MBRjj4iIiIiIoUPSjbbHd9Q2ZN+6aHvVgY4hhh7bbx3oGCK6Mq6tjYmjRw90GBEREREREUPSkE10RcTQNVQrliIiIiIiImJwG05ndEVERERERERExHKsTxNdkixpoaQT+mCuCZIe6Iu4erBWu6RXLou1YmBJ+r2kxZKuHuhYIiIiIiIiIqJv9UdF15a2j2pcSPqwpDskLZA0R9IvJY3sh3V7RNKU+jbD59hus31PP6y1vqRLJc2V9JikWyUd0NfrDCaSDugoiSRphqSduxizpOktie2SJrT02VvS32oi9W5J23cy196S7qzf90OSzpG0eqPd9lsob5iMiIiIiIiIiGGmX7cuStoROBHYx/ZI4LXAxf255iBzHjAT2AhYC5gEzBnQiJaCpBWWwTLX1oRj4zOlaf23Al8BPgiMBHYAOktMXgO8yfYawCsp59Ad36+RR0RERERERMSg0N+H0b+BksCYBmD7UeCcRqOkVYATgPcDqwA/BT5p+4mmPkcCnwLagaNsX1Dvv5OSwHgV8Bhwpu1ja9uqwA+AXYAVgH8A7wI+DmwPbCvpm8DZtg+VZODVtu/qZt6xwL3AAcCXgBHAKbY726r5hvo8C+v1tKbnmgCcb3v9pnszgANt/1bSscDmwJPA7sAMYI/6+WS9/2Hbv6ljpwBXA28BXgf8ocZ5KvBu4E5gL9szav/XAKcBrwceBo62fXFtOxt4gpKg2xHYXdLKwNeADYDH63N/rZPn7muTgeNsX1ev/9lZR9szW24tATZemkXvXLSICdOmdd8xemV6ezvj2toGOoyIiIiIiIgYhvr7MPq/AG+XNFnSm2piq9lXgE2AcZRkxHrAF5va1wXWrvf3B/5H0qa1bSGlQmoU8E7gY5LeU9v2B9agJGXWomxVe6JuqbwKOLRWDR3aQcxdzduwHbApsBPwRUmv7eT5rwO+XbfTbdhJn668m1IVtiYlSfZrym+2HnAccEZL/72BD9T2VwHXAmcBLwP+BhwDIGk14ErgQuDlwD7AdyRt3jTXREoSciQlgXYm8NFambcF8PuleJ6ubFW3eP5d0tGSVqyxrgCMB9aRdJekBySdLumlnU0kaTtJjwELKInBb/ZxrPEijGtrY+Lo0QMdRkRERERERAxD/VrRZfsqSe8DDgE+Aawo6X+Aw4FngY8Ar6uVXkg6kZJ8+XzTNEfbfhL4o6RfUqq/vtS8tQ24RdKPKNVHPwOepiS4NrZ9C3BjL2Luat6GybXq7GZJNwNbUhJJrfYCjgCOBl4j6VbgI7Zv6GE4V9n+NYCkS4D3AV+2vUTSjymJv1G259f+Z9m+u/a/AtjM9m+bxn+p9nsXMMP2WfX6JkmXAnsCt9V7l9m+pv69WNLTwGaSbrY9D5jXRdzbSprfcm/1DnsWf6Ikz+6jVLFdBDwDnASMBlaqsW1P+W0vA74AHNXRZLavBtaQtB7l/9iMLtbu1KYjRjBlq62WZmhEREREREREDID+rujC9hW2302pKtqdsp3uQGAdyta/GyXNr4mRX9X7DfOatv1BSYSMAZC0jaQ/SHq4Vu8cTKn+glIF9Wvgx5JmSTpZ0ko9ibebeRtmN/29COhwH5btebY/Z3tzSsJmOvAzSepJLPzreV5PAHNtL2m6pmXt1v6t142+GwHbNL73+t3vS6mga2jdArgHsCtwn6Q/SvrPLuK+zvao5g9wf2edbd9j+17bz9q+lVKttmfLc55m+0Hbc4Fv1Fi6ZPuflP9TP+6ub0REREREREQMff2e6GqoSYzfUba8bQHMpSQxNm9KiKxhuzlxs2bdZtewITCr/n0h8HNgg3rw+PcA1bWetj3Z9mbAGykVTJMaoXQTaqfzvhg1QfM1SqLuZZQtkiMa7XWL3jodj+5zM4E/tiSj2mx/rDnk5gG2b7C9O2Wr48/o35cKmOd/y3nAA63x9MKKlG2cERERERERETHM9evWRUm7Ay+lVFfNpxzOviNwmO1nJX0fOEXSobYfqlvNtmhs16sm1wPpt6EkrI6p90cCj9peLGlryplSjYPZ30xJpN1OOTj9acqh5FCqnF7ZRdidzrsUz/8VSnXZHfV7+Bhwl+1HJD0DrFoPv/8NcCTlQP5l4RfAlyV9gOerncYB7bZfsAWzHkS/F/AL249Jepznv88XTdIuwE2259RD8o8GLmnqchbw35J+RfktD6vP0NFc+1LOYZtJSYyeAPyur2KNiK5Nb28fEi9xmDh6NAeNGTPQYURERERERB/r74queZQzkv5BSTidD3y18eZEyvlVdwHX1eTJbymHvDfMrnPMAi4ADrZ9R207BDhO0gLKAfbNFUbrAv9b1/wb8Me6NsC3gD0lzZN0agcxdzVvb42gvElyPnAPZcvgbgC2H6tr/YDyFsGFlMqlfmd7AfA2yuH1syjf81foOtH2AWBG/Z0OBvbrw5B2opyHthC4HPgJcGJT+5eAG4C/U37PaZQEFpI2lNTedNj/ZsCfKW/pvIbytsmP9GGsETHETW9v58I5c7rvGBERERERQ47spd0R1sFk0mLgSeBU20f32cQRfUTSlcC2wPW2d+qq7/jx4z116tRlE1jEMNCo5BrsL3EYKnFGRERERETHJN1oe3xHbX26ddH2qn05X0Rfs/3WgY4hIiIiIiIiIvrHMjuMPiIiIiIiIiIioj8l0VVJsqSFkk5YhmtOkLRMzuV6ser3s/FAx/FiSZpcf2dL6teXMURERERERETEspVE17/a0vZRjYvBltyRNEXSYkkbNN3bWdKMAQzrX0ga21ESSdLZko7vwfhj6vidO2hbWdIdXSUHm9Zvb/o8d16c7WOAzXv5WBERERERERExBKSiZehZCBwNHDTQgfQ1Sa8C9gQe7KTL4cBDQFsPphtl+5m+ii0iIiIiIiIiBr9UdPWQpK0lXStpvqQHJZ0uaeWm9s0lXSnpUUlzJB1Z768i6ZuSZtXPNyWt0jL3kZLmSpohad9uQjkV2KezSjNJr62VX/Ml3SZpt3p/W0mzJa3Q1Pe9km7pyfO1rLGdpJmS3tyT764XTgeOAJ7qYM1/A/YDTurjNSMiIiIiIiJimEhFV88tAT4JTAXWB64ADgG+KWkk8Fvga8C7gZWAzeq4o4BtgXGAgcuAL1CqsgDWBdYG1qv9Lpc01fadncTxT+D7wLGUxM9zJK0E/B/wQ+BtwHbAZZLG275O0kLgLcCVdchE4MLunq9ljbcDPwD2sH19V19Yb0jaC3jK9uWSOupyGnAk8EQPp7xPkinPerjtub2N6c5Fi5gwbVpvhy33Jo4ezUFjxgx0GBEREREREbEcSkVXD9m+0fZ1tp+xPQM4A9ixNr8LmG3767YX215g+y+1bV/gONsP2X4YmAx8oGX6o20/afuPwC+B93cTzknAuyW1njW1LWVb35dtP2X798AvgH1q+48af9fk3K71XnfP17AX8D/Arj1Ics2t1WHzJc2nJNU6JKkNOBE4rJP29wIr2v5pN2sCzAXeAGwEvB4YCVzQg3HRB6a3t3PhnDkDHUZEREREREQsp1LR1UOSNgG+AYwHRlC+uxtr8wbA3Z0MHQPc13R9X73XMM/2wi7aX8D2w5JOB44Dvtuy1kzbz7bMt179+0Lgz5I+BrwPuMn2fT14vobDgHNt39pVfNXazWdkSTq7i76TgfNs39vaIGk14GRKUq5bttspVWkAcyQdCjwoaXXbj/dkjoZNR4xgylZb9WbIci8VcBERERERETGQUtHVc98F7gBebXt1yja6xh67mcCrOhk3i1Jd1LBhvdewZk3mdNbema8Cb6ZULTWvtYGk5t91Q8p2R2zfTkl87cK/bluErp+vYS/gPZI6rLx6EXYCPl7PEJtNSRxeLOkI4NXAWOCq2vYT4BW179gezO36b4f7ISMiIiIiIiJi+Eiiq+dGAo8D7ZJeA3ysqe0XwLqSDquHz4+UtE1t+xHwBUnrSFob+CJwfsvckyWtLGl7yjbIS7oLxvZ84OvAZ5tu/4XyVsbPSlpJ0gTKmWE/bupzIfBxYIeWdbp6voZZPJ+UOqS7GHthJ2ALyjlm4+o6HwW+DfyVkvhqtB0IzKl/z2ydSNI2kjaV9BJJa1EO759i+7E+jDciIiIiIiIiBqEkurrXqAj6DKUKagHlMPiLnutgLwDeSkkqzQb+Qam2AjiespXuFuBW4KZ6r2E2MI+S3LkAONj2HT2M7VuUQ+QbcTwF7Eap2JoLfAeY1DLfj4AJwO9bDmjv9Pma2b6fkpg6QtKBPYyzS7YfsT278anPNM92ez0zrLntUeDZer0EoL5dsvG2ylcCv6rP8VfgSaJACTYAACAASURBVJ4/oywiIiIiIiIihjHZ7r7XckDSYkpS5FTbR0taHXgMWLNWT8UwIOkY4FPAKsBqjWRZR8aPH++pU6d21hwdmDBtGtPb2xnX1jbQoSwzecvk8xpntA32s+2GSpwREREREdExSTfaHt9RWw6jr2yv2nLrv4C7k+QaXmxPphx+H/GiTW9vB0iiKyIiIiIiYpBIoqsDkv4MjKKcBxURvTCurW25qZTJWyYjIiIiIiIGlyS6OmD7jQMdQ0RERERERERE9E4Oo28iyZIWSjphoGMZzCQdIOnqgY5jaUiaXH9jS0qiNyIiIiIiImIYSaLrhba0fVTjoiZENl5Wi0s6W9JTkhbUz18lnSRpjWUVw4shaWxHSaT6XMd3M6a96XN0U/vh9XtYIOleSYd3sf6+LfMsqnO/HsD2McDmffS4ERERERERETGIJNE1OJ1seySwDvBBYFvgGkmr9XYiFUPldx5lu61+vtR0X8AkYE3gHcChkvbuaALbFzTN0QYcAtwD3NTfwUdERERERETEwMrWrV6QtArwFeD99dbFwBG2n5S0NnA2sB3wLHAbsKPtZyWNAU4DdgDagVNsn9rderYXAzdI2g34OyXpdbqkY4GNbe9X4xoL3AusZPsZSVOAa4AJwH8A/y5pe+CzwPrAw8BXbJ9Rx08AzgdOAY4AlgBH2j6rtq8FnFXnuwP4da++uBfJ9slNl3dKugx4E/DjHgzfHzjXtnu77p2LFuWw8V6a3t7OuLa2gQ4jIiIiIiIillNDpdJnsDiKUl01DtgS2Br4Qm37NPAApQprNHAk4FpN9X/AzcB6wE7AYZLe3tNFbS8ArgS270WsHwAOAkYC9wEPAe8CVqckzE6R9B9N/dcF1qgxfhj4tqQ1a9u3gcXAK4AP1U9/uE/SA5LOqonDF5AkyvdwW3eTSdqIklw8t2/DjM6Ma2tj4ujRAx1GRERERERELKdS0dU7+wL/bfshKAebA2cARwNPUxJBG9m+C7iq9tkaWMf2cXWOeyR9H9ib3lVGzQJe34v+Z9tuTgb9sunvP0r6DSVh1NjS9zRwnO1ngMsltQObSroB2AP4d9sLgb9KOoeSQOrK3JKTes4I4OTO+gJvAKYDa1ESaxcAHSUDj6UkaM/qZn0o2x2vsn1vD/q+wKYjRjBlq62WZmhEREREREREDIBUdPXOGEp1VMN99R7AV4G7gN9IukfS5+r9jYAxkuY3PpRqr96WvawHPNqL/jObLyTtIuk6SY/WGHYFmqumHqlJroZFQBulQm3Flvmav4POrG17VOMDXNhZR9vttqfafsb2HOBQ4G2SVm95hkMpyat32n6yBzFMAs7pQb+IiIiIiIiIGAZS0dU7syiJq0al1Ib1XmN74aeBT0vaHPhDrYaaCdxr+9VLu6ikNmBn4IR6ayGlQqph3Q6GPXcmVT1b7FJK4ucy209L+hnlkPfuPAw8A2xAOZ8LynP3p0bsz8Un6UPA54AdbD/Q3QSS3kRJQv5vv0QYUU1vb89ZblXOaIuIiIiIiIGWiq7e+RHwBUnr1DOkvkg5xB1J75K0cT1D6nHKge5LgOuBxyUdIemlklaQtIWkN3S3mKRVJL0e+Bkwj+e3600HdpC0oaQ1gM93M9XKwCrUpJWkXYC39eSBbS8BfgIcK2mEpM0oB7z3GUnbSNpU0kvqwfenAlNsP1bb9wVOBN5q+54eTrs/cGlNQEbEMpAz2iIiIiIiYqCloqtnGhVGx1MOc7+lXl9S7wG8GjidstVvHvAd21MAJL0b+DrlzYirAHfy/CH2HfmspE9QEpEzgF8Ae9YzsrB9paSLahxzKW+C3K3T4O0Fkj5OeUvkKpTD8X/es0cHylbCs4DZlKqus4A392J8d15JSWS9nJIkvBLYp6n9eMrZXTc0nft1vu2DASTdBpxo+4J6vSrlzZh79GGMER0a19aWs9wiIiIiIiIGCdnuvtdyQtJi4EngVNtH1zOiHgPWtD1/YKOLviDpGOBTlITfarVirUPjx4/31KlTl1lsMfQ0tiwm0TW05HeLiIiIiBjaJN1oe3xHbanoamJ71ZZb/wXcnSTX8GF7MjB5oOOIiIiIiIiIiL6XRFcnJP0ZGAUcONCxRERERERERERE95Lo6oTtNw50DBERERERERER0XND4q2LkixpoaQTBjqW/lKfceOlGDdFUp9WnUmaIOmBLtq/J+novlxzWZH0e0mLJV090LFERERERERERN8aEomuakvbRzXfkLSapHZJlw9UUK1qPI3Ps5KeaLred6Dj6wu2D7b9pY7aJB3QURJJ0gxJO3cxZknLdzehqb295bNE0mmdxSfplZJ+IWmBpLmSTm6K/S3Awb153oiIiIiIiIgYGob61sU9KW9JfJukV9h+cGkmkbSi7Wf6IiDbbU3zzgAOtP3bvph7mLvW9nYdNbR8p6sBc4BLOuoraWXgSuDblJcJLAE26fNoIyIiIiIiImLQGeqJrv2B7wG7APsCX2s0SPoc8BHg5cBM4CjbP61tB9S26+sc35H0VeC0Otci4PvAibafrf0PBK4DPgzMBw6xfUVPA5W0NfAt4LXAE8ClwKdsP9VB3+2AHwGTgOnAecA2lN/rGuBg281bCzeSdA3wOuBaYKLtuXWuS4DtgZcCNwMfs31bbdu1fmcbAI8Dp9hu/g4/DRxBSRYdafusev9s4AHbX+jp8/ehPYGHgKs6aT8AmGX7G033blmahe5ctIgJ06YtzdBYTkxvb2dcW1v3HSMiIiIiImKZGEpbF/+FpA2BCcAF9TOppcvdlATPGsBk4HxJr2hq3wa4h5IIO4GS5FoDeCWwY53vgy397wTWBk4GzpSkXoS8BPhkHf+fwE7AIR0819spSa49bP+B8hudBWwEbEhJkp3eMmxijfXlwMrAZ5rargBeXdtuonxXDWcCH7U9EtgC+H1T27qU72M9SnLv25LW7MXz9tZWdZvh3yUdLamzJOz+wLm23Un7tsAMSVfU+aZI+vf+CTmWd+Pa2pg4evRAhxERERERERHVUK7omgTcYvt2SfOBkyVtZXsagO3mrW0XSfo8sDVwWb03y/ZpUA6Cp2xz28r2AmCBpK8DH6AkgwDus/392v8c4DvAaGB2T4K1fWPT5QxJZ1ASat9sur8X5fyoXW3fWsc9Qqn+oq59AvCHlunPsv332n4xsFvTuj9sGnssME/SGrYfA54GNpN0s+15wLymOZ8GjqtbOi+X1A5sSqlq68629TdptnoX/f9ESbTdB2wOXAQ8A5zU3KkmN3ekJN46sz7wZsp38DvgE8Blkl7TUfVcVzYdMYIpW23VmyERERERERERMYCGbEUXJdF1AYDtWcAfKdU+AEiaJGm6pPk16bIFpZqqYWbT32tTKqHua7p3H6WaqeG5hJbtRfXPHu9ZkrRJPSB9tqTHgRNb4gE4DLi4keSq40ZIOkPSfXXcn4BRklboKDbKtsu2OnYFSV+WdHcdO6PpeQH2AHYF7pP0R0n/2TTPIy3nlj03bw9cZ3tU8we4v7POtu+xfa/tZ+uzH0fZothqEnC17Xu7WPuJ2ueKmtj6GrAWZctoRERERERERAxjQzLRJemNlO14n6+Jo9mUrYX7SFpR0kaUM7YOBdaqiZa/As1bDZu3vs2lVDBt1HRvQ+CffRj2d4E7gFfbXh04siUeKBVd75F0WNO9T1Mqqbap43ao93uybXIisDuwM2Ub4tjmsbZvsL07ZVvjz4CLe/lM/cV0/HyTgHO6GXsL//rbRkRERERERMRyYkgmuiiVW1cCmwHj6mcLYATlMPnVKMmOhwEkfbC2d8j2EkqS5wRJI2ui7FPA+X0Y80jKge/tkl4DfKyDPrMoZ3d9XNIhTeOeAOZLehlwTC/XfBJ4hPLdnNhokLSypH3rNsana2xLevlMfULSLpJG179fAxzN81tMG33eSKmw6/Bti03Op2yd3LlWvR1GSWT+rc8Dj4iIiIiIiIhBZcid0SVpVeD9wCTbs1vazgP2t71nPWPrWuBZ4FzK2wq78t+UA+nvARZTKsJ+2OWI3vkM8D/AZ4FplHOo3tLayfb9knYCpkh6inKG14WUZM0s4OvAe3q45rnA2ymVaY9SEkjNCbYPAKfXhNCdwH69f6w+sRNwtqQ2YA4lWXViS5/9gZ/UM9SeU8/tuh3YzPb9tu+UtB/lbZyNA/h36+35XBExvE1vbx90b1WdOHo0B40ZM9BhREREREQMaer85XWDh6TFlMqkU20fPdDxxNAl6UrKmxmvt71TV33Hjx/vqVOnLpvAImKZmTBtGtPb2xnX1uNjFvtdI568ACMiIiIionuSbrQ9vqO2IVHRZXvVgY4hhgfbbx3oGCJi4A22pNJgqy6LiIiIiBiqhuoZXREREREREREREf9iUCW6JFnSQkknDHQsywNJY+t3PiQq+/qCpLMlPSHpgYGOJSIiIiIiIiL61qBKdFVb2j5K0vaS2utnYU3ItDd9NuxosKQJgzGJoeJQSbdIWiRptqQpkvYe6Nj6Umfff33WA7sYt46kCyXNlzRP0gVNbWdLeqrl91+hk3leIennkmbV/zNjm9ttH0B5M2dEREREREREDDODMdEFgO2rbLfZbgM2r7dHNe7Zvn8g41sKpwKHAZ8G1gLWA74AvGMggxpEfgLMBjaivC3xay3tJzf99m22l3Qyz7PAr4A9+i/UiIiIiIiIiBiMBm2iqyuSPijpb5IWSLpH0kfr/dWAK4AxTZU/YyRtLWmqpMclzZH0jdr/BdVHkmZI2lnSurXyaq2mttdLeljSSpJeJen3kh6RNFfSBZJGdRLvJsAhwN62r7T9hO0ltq+uFUaNfmNqNdKjku6S9JGmtmMlXSzp3Prct0kaX9v+q6Xa6UlJU2rbOyVNq88+U9KxXXyva0g6U9KDkv4p6fhG5ZSkm1vWsKQJvfndulj3bcAGwOG2H7P9tO2lOpnZ9hzb3wFu6IvYIiIiIiIiImLoGKpnMz0EvAu4B9gBuELSDbZvkrQLcL7t9RudJV0KfMv2eZLagC26W8D27Josej/w3Xp7P+DHtp+WJOAk4E/A6sClwLGUqq1WbwFm2p7azbI/Am4DxgCvAa6UdI/t39X23YD3AR8EjgdOB7a1fRFwUX3W1YG/1LkAFgKT6rxb1Dmn2/5ZB+ufA8wBNgZWA34BzATOsL1lo5Okg4BPATd18zw9tS1wJ3BO/f3uAT5j+49NfQ6RdAhwL3Ci7Uv7aO1O3bloUd6EthyYOHo0B40ZM9BhRERERERERB8YkhVdtn9p+24XfwR+A2zfxZCngY0lrW273fZ1PVzqHEpyi1rZtA9wXo3hrlqd9aTth4FvADt2Ms/alG15z5H0QD2ParGkjSRtAGwHHGF7se3pwA+ADzQNu9r25XXb3nnAli1zvgS4EJhi+4wa5xTbt9p+1vYtlATYC+KUNJpydtVhthfafgg4Bdi7pd92lCTbbrYf7+R5x9Rne+5Tn60z6wNvA/4ArAt8HbhM0tq1/VTg1ZQtjUcDZ0t6UxfzRfTI9PZ2LpwzZ6DDiIiIiIiIiD4yJCu6atXPMcAmlGTdCODWLoZ8GDgOuEPSvcBk27/owVKXAd+T9Mq61mO2r68xvJySgNkeGFnjmNfJPI8Ar2i+YXt9lbcdPg2IUsX1qO0FTd3uA8Y3XTcnyxYBq0pa0fYz9d4JNZaPNzpJ2gb4MqWaa2VgFeCSDmLcCFgJeLAUq0F9pplNc20AXAzsb/vvnTwrwKzmiro6dkoX/Z8AZtg+s17/WNJRwJuAy2w3V45dXg+qfx9wTRdzvmibjhjBlK226s8lYoClYi8iIiIiImJ4GXIVXZJWoWwT/Bow2vYo4HJKsgjArWNs/8P2PpSKoK8A/1vP81pISZI15l4BWKdp3GJKYmdfSmXVeU3TnlTXep3t1SmVX6JjvwfWb5yp1YlZwMskjWy6tyHwzy7GPEfl7Y37AHvafrqp6ULg58AGttcAvtdJnDOBJ4G1bY+qn9Vtb17nfynwM+Cbtq/oSUy9cAsd/G5dMJ1/1xERERERERGxnBpyiS6er0p6GHimVne9ral9DrCWpDUaNyTtJ2kd288C8+vtJcDfKVVR75S0EuUtiKu0rHcucADlfKzzm+6PBNqB+ZLWAw7vLGDbdwJnUCqV3irppTWp9samPjOBPwMnSVpV0usolWgXdPeFSNoKOA14T91G2WwkpVJssaStgYmdxPggZQvo1yWtLukl9cD9xjbHHwJ32D65u3iWwk+BNSXtL2kFSXtS3kp5DYCkPSW11ZjeRkkq/ryzySStyvO/4yr1OiIiIiIiIiKGuSGX6Kpb+z5OqbSaR0nc/Lyp/Q7KOVT31POhxgDvAG6T1A58i/L2w8W2H6O8DfEHlMqphcADLetdAzwL3GR7RlPTZOA/gMeAXwI/6Sb0/0fZ6vgN4NG6zpeA/wLur332AcZSqrt+Chxj+8oefC27A2sCVze9FbFRdXUIcJykBcAXKd9bZyZREom3U77b/+X5LZd7A+9tefNiV+ei9ZjtRymJxM9Qvs/PAbvbnlu7fILy+8wHvgp8xPaUxvgOYnmCkoQEuKNeR0RERERERMQwJ7s3O8b6l6TFlO1zp9o+eqDjaZD0e+BC2z8Y6FjixZF0JrAX8JDtjbvqO378eE+d2t2LMmMoa5zRlbPYli+D8XcfjDFFRERERAxWkm603eHxUIPqMHrbg26LmaQ3UCq3dh/oWOLFs/1hypbQCKC8eTGH0ndt4ujRHDRmzECHERERERER0a0ht3VxWZJ0DvBb4LCWtyFGRCwXpre3c+GcOQMdRkRERERERI8Mqoquwcb2/gMdQ0T0r3Ftbdku1oVUu0VERERExFCyzCu6JFnSQkknLIO19pX0m/5eZ7iQNEPSzvXvYyWd392YoUbS5Pr/z5KS6I2IiIiIiIgYRgZq6+KWto8CkDS2Jh1uau4gaW1JT0masbSL2L7A9tteZKx9TsXHJf21Jl0ekHSJpH8f6NherKbfc8WW+2dLOr4H44+p43duujdK0jmSHqqfY7sYv5mkqZLm1c9vJW3WaLd9DLD50j1dRERERERERAxmg+mMrtUkbdF0PRG4d2knG+TVOt8CPgF8HHgZsAnwM+CdAxnUQJP0KmBP4MGWplOAEcBYYGvgA5I+2Mk0s+ocLwPWBn4O/Lg/4o2IiIiIiIiIwWUwJYPOA/YHDq/Xk4BzgY80Okj6XL1+OTATOMr2T2vbAbXt+jrPdyTdBRxoe7va51vA+4A1gH9QDpm/qrYdC2wGLAbeC9wP7G97am2fAZxe49oI+FVtX1zb3wUcT0nG3A4cbPuW1oeU9Grg/wH/afv6pqYLmvqsAZwG7AIsAr4PnGj72fqcBwLXUd4eOB84xPYVdewU4CrgLcDrgGuBibbn1vbdgJOA9YDpwMds/+2FP8e/xPxL4Fe2T2u6dwvwRds/62psL50OHAF8p+X+u4FdbC8CZkg6E/gQcFbrBLbnU74TJAlYAmy8NMHcuWhRzica5qa3tzOurW2gw4iIiIiIiIg+Mpgqus4H9pa0gqTXAiOBv7T0uRvYnpKomgycL+kVTe3bAPdQEmEdnQF2AzCOUu1zIXCJpFWb2nejVP+MolQCnd4y/v3AO4B/oySRDgCQ9B/AD4GPAmsBZwA/l7RKBzHsBDzQkuRqdVp9xlcCO1KSa80VTNsAd1Iqlk4GzqxJnYaJtf/LgZWBz9Q4NwF+BBwGrANcDvyfpJW7iAXgHGC/xoWkLSmJssu7GddjkvYCnrLd2Zxq+XuLTvo15ptPSVqeBpzYJ0HGsDOurY2Jo0cPdBgR/5+9e4/XfKz3P/56J4yxhiEajVNJSew9MzVot9kmh8pGp93uMClUJD+pqMghhxwrilRKopyilFKJVJOIGGZUsx1yGocxk9OMWXMQ5v3747pu3ZZ1nrVmnd7Px+N+WPf3Onw/3+89f318ruuKiIiIiIg+Mpgquh6kJG92At5EqeZ6Hts/avp6saTPU5ay/axem9NUdfTM83M/YLt5c/VTJB0BbAbcWq9d20i0SDqPkhBqdrrtObX9ckrSDEol2bdtNxJz35d0GPAG4A9t5ngJL1ya9xxJKwHvBSbZXggslHQK8EHg7Npttu2zav/vUyqgxgFza/s5tu+s7ZdQEnjUeX9p+ze17SuUJZRvBKZ1FBPl/Z4p6VW2/15judj2PzsZ82ib9z+akpRr75lbKMmojvZT+zVwqKQ963N+uM7XIdtjJa1Oqe6b3Vnfjmw2enRO44uIiIiIiIgYQgZTRReU5NZewPspFV7PI+lDkmZKml8rdrakVDU1PNDZ5JIOlnSbpAV1/Jptxs9t+nsxMKrNXl9t2xtrnjYGDm7EVefeEBjfThiPAS9r53rDOpQqrObkzGxKBdUL4qjL+WiKpbM4xzfPa3sZ5Z01z/0Ctp8CLgH2kPQiyu9zXmdjgHVsj218KBV0HTkGOM92R3uyHQgsoSw3/RmlKu3BLu6P7UXAmcAPJL20q/4RERERERERMbQNtkTXpZQN2e+x/bwqHEkbU/aqOgB4SU2e/I3nL2lzRxNL2o6y/9N7gLXq+AVtxvfWA8DxzYkd26NtX9RO398CG0ia3MFcjwJPU5JnDRsBD/VBnHOa563LHTfs5tzfBz5AWXq52Pb1fRBPw47AgZLmSppbY7pE0iEAth+3/QHb69negvLvtrOln81eRKn+6jSZFxERERERERFD36BKdNUKnB0om623tTolkfUIQD11r9N9mtoYAzxTx79Y0heANZYr4H85C9hP0jYqVpe0q6QxbTvWpX/fBC6SNEXSKpJGSXqfpENtP0upnjpe0pia4DuIdirceuESYFdJO0paGTgYeAr4U1cDa2JrGXAKXVdz9dSOlN9yYv3Moex39g0opzFKekndv20XYF/Kxv8vIGlnSZNq3zWAU4EngE433I+IiIiIiIiIoW9QJboAbE+3fXc71/+PkmS5HpgH/BtwXQ+mvhK4AriTsnxvKV0sdeyuejLjPpTN658A7qJuVN+BA2vfb1BOCLybctLj5bX9E8Aiysb611KW/X2vD+K8g7Kp/NcplWO7A7t3sddWsx9Q3ntfJN2a43rM9tzGh3JS4hO2W2uX1wN/BRZSToz8gO1ZjfGSZkn6QP06lrK0cQHlvW4KvLVxOmZEREREREREDF+yO1zt1z83lJZSqohOt33kCr15LBdJHwL2tb3tQMfSW5KOolTIrQqsXivo2jV58mRPnz59hcUWMRhNmTEDYFgdzDAYn2kwxhQRERERMVhJutl2u1tCrfBTF22PWtH3jOUnaTSwP2XZ5ZBl+xjK5vcRERERERERMcwMuqWLMfhIegtlb7N5dH56YkRERERERETEgFnhFV0x9Ni+knIYQERERERERETEoJWKroiIiIiIiIiIGBZGRKJLkiUtknT8QMcSA0vSuZKWSHpwoGOJiIiIiIiIiL41IhJd1QTbhwNIenlNfvXr0k1JYyV9T9JcSQsl3SnpkP6850CTNKW9JJKkaZI+2smYZZJamz57NrV/SdIDkp6UNFvS4V3EMLX2WyTpMklrN9ps7wXs0vsnjIiIiIiIiIjBKnt09a+vUva22hxYALwa2HJAI+oFSS+2/Uw/32aO7Q06aDsbOMb2IknrA1dJus32T9p2lLQF8G1gV+AW4DuUkyLf19OA7li8mCkzZvR02Ao3ddw49h0/fqDDiIiIiIiIiBhwI6miq1skbS3peknzJT0s6QxJqzS1W9J+kv4u6QlJ35CkDqbbCrjQ9hO2l9m+3faP6zwvqCprrnqStJek6yR9tcZyj6Q31usPSPpHm6qncyV9U9IVtSLqOknrSfpajfN2SZOa+o+XdKmkRyTdK+nAprajJf1Y0vmSngT2qu9leq2qmifp1D576V2wfYftRU2XlgGbdtD9A8Dltq+x3QocCbxL0pj+jnMgzGxt5cJ58wY6jIiIiIiIiIhBIRVdL/Qs8GlgOrABcAWwP/C1pj67UZJYawA3A5cDv25nrhuA4yWtBVxr++89jGUb4LvAS4BjgB/We20KbA9cKunSmtABeA/wFmAW8CvgeuAo4OA6/lTgTZJeVOf5GfD++pxXS7qjnrAI8Hbgf4EPAasCvwNOs32epBb6vjLtpZLmAYuBy4AjmpNbkg4FjqBUyN0LXNjBPFsAf2p8sX23pH9Squlu7klAm40ezbRJk7ruOICGQsVZRERERERExIqSiq42bN9s+wbbz9i+j7IMbvs23U6yPd/2/cDvgYkdTPcJ4ALgAOD/JN0lqSf7Q91r+xzbzwIXAxsCx9p+yvZVwD95fmXTT2v8S4GfAktt/6BpfCNrsxWwru1jbf/T9j3AWTx/ed/1ti+rlWhLgKeBTSWtY7vV9g2dxD2+VqE99wG27aT/7ZR3+DJgB+D1lKTcc2yfBIwBXgecR1kK2p6WdtoW1LERERERERERMYwl0dWGpFdL+kXdQP5J4ARgnTbd5jb9vZiSXHkB20tsn2D79ZSqrEuAHzVvjt6F5jVpS+qcba+1dNK/o74b0yYZBRwGjGvq/0CbWD5CqYq6XdJNknbrJO45tsc2f4BrO+pse67t/6tJtXuBzwHvbqefbc+oz3JMB9O1Uirtmq0BLOwk3oiIiIiIiIgYBpLoeqFvUSqMXmV7DUoCqKM9uLrNdiNptjrwCqCxLG90U7f1lvc+3fQApVqsORk1xvZ/N/Vx8wDbf7f9fuClwMnAjyWt3k/xmc7f+YuBV3bQNguY0PgiaRPK0ss7+yy6iIiIiIiIiBiURvoeXas2bwZPWQo4BngSaJX0GuDjwCO9mVzSkZS9u26lJBU/CcwH7rDdKukhYA9J3wb2pOPkTV+7EXhS0iHA6ZTn3hxYzfZN7Q2QtAdwpe1HagUYlP3MlpukKcA9lATcBsBJlP3DqPuJ7UOphptPWXb5sW6vPAAAIABJREFU/4ATO5juAuB6SdtRTl08FviJ7VR0RfTSzNbWYbUf3MzWVia2tFuIGxERERERQ9xIT3S1tvm+M/AZ4DuU5XMzKHtb7dDL+Q2cA2wEPAP8Bdi1afP4fYBvUiq9zqZpE/X+ZPtZSbsDp1A2dl8VuIOy2XtH3gqcKmk0MBt4X90LrC+8jpKgWgt4jLIZ/WFN7e+kJLZWAeYAX68fACS1ArvY/qPtWZL2q/O9BLga2LuP4hyU+ioJMXXcOPYdP74PIooY3Ca2tDB13LiuO0ZERERExJAj2133GuIkLQWeAk63feRAxxMDR9LZlNMk/2F70876Tp482dOnT18xgfXSlBkz+qQ6pTHHYD9lMla8RhI1/zb6V95zRERERET3SbrZ9uT22kZERZftUQMdQwwOtj9C2Vh/2OiLBNVwWpYWERERERERI1c2o4+IiIiIiIiIiGFhRCS6JFnSIknHD3QsMbAknStpiaQHBzqWiIiIiIiIiOhbIyLRVU2wfbik1ST9XdKHmhslHSXpunrKX7skHS3p/OUJQtLLJJ0t6WFJCyXdLukYSasvz7yDhaQp7SWRJE2T9NFOxiyT1Nr02bOdfmtLekTStV3cv8O5bO8F7NK7p4uIiIiIiIiIwWxE7NHVzPYSSR8BfiLpStvzJG0OHARsY3tZf91b0trA9ZTTFf/D9n2SNqSc9PhKyqmMPZnvxbafafouygED/fYM/WiO7Q266HMycBtdJ2i7M1dEREREREREDDMjLtEFYPsaSRcDZ0h6D3AWcCKwnqSrm5Mkku4DPkp5V4eVS3oHcLftCZL2Bj4HbAA8Apxs+9sd3PogYCGwRyMZZfsB4JNN9zsNeBewJvB34FO2/1jbjga2BJYCbwMOkrQHcB0wBXgd8G+StusoJknrAOcC2wLLgFnA9raX1aTbacB2lGTSRbYPqFVuhwH7AKsBvwY+YXtBt1/6cpL0H5Rn/w4raDP5OxYvHvSbtPfFiYsRERERERERw8VIWrrY1iHAVsClwCjgy511tv1r4ATgYtsttifUpn8AuwFrAHsDX5X0ug6m2Qn4SRcVVzcBE4G1gQuBH0lqPjXy7cCPgbHABfXaB4F9gTHA7C5iOhh4EFgXGEdJYFnSSsAv6viXA+sDP6xj9qqfNwGbAC3AGZ08Q2+8VNI8SfdK+mrzUs4a2zeAAwAvz1zDzcSWFqaOGzfQYUREREREREQMCiOyogvAdquk/0dJ7ky0/WxZ+dfjeX7Z9PUPkq6iVETd0k73lwAPdzFf8x5gp0g6AtgMuLVeu972ZfXvJTXmc23PahrXWUxPAy8DNrZ9F9CoFtsaGA98tmk5ZGMvrA8Ap9q+p/b9PPA3SXs3L51sMl7S/DbXWoCO9je7nZLcux3YGPg+cCrwsdp+IPBn2zdL+rcO5ujuXN222ejRTJs0qafDIiIiIiIiImKAjNhEVzWrzX97TNIuwFHAqykVcqOBv3bQ/TFKkqmz+Q6mLJUcT6leWgNYp6nLA+0Me961LmL6MnA0cFVNkn3H9knAhsDsjhJXlEqvhtmUfzvjgIfa6f+CPbIkTWunHwC25wJz69d7JX2Okqz7mKTxlETX6zsa3925ujN+JJvZ2jrol2p219Rx49h3/PiBDiMiIiIiIiJWsJG8dLE9iyhJIeC5JXPrNrU/b9mcpFUpSx+/AoyzPRb4FdBRadjVwDs7Otmx7q11CPAeYK0634I287W3dO+5a13FZHuh7YNtbwLsTtnna0dKsmwjSe0lP+dQqqMaNgKeAeZ18JzLy/zrmbemJAf/T9Jcyh5iW0uaW3+fnswVI8DM1lYunNdf/zQjIiIiIiJiMBvpFV1t3QmMkrQrcBVl/6pVm9rnATtLelHdZ2uV2v4I8EytpHoz8LcO5j8V2AP4vqQjbM+WtD5l36xzKXtsPVPne7GkQykVXT3RaUySdqMs67sbeBJ4tn5upCyrPEnSUfXa621fB1wEHCLpijpvY6+y9qq/ekzSFOAeSrJtA+Ak4Ge1+QrKnmEN7wWmAm+3/WwP54pOTGxpGRZLNYdLVVpERERERET0XCq6mtRTBPcHvktZkreIsnF7w4/qfx+TdIvthZRldZcAT1ASMD/vZP7HgTdS9sn6s6SFwG8pVVt3AVdSEjt3UpYHLqX9pYqdPUNXMb2KUlnWClwPfNP2tJo02h3YFLi/Pvd765jvAecB1wD31rg+0ZO4uvC6Gssi4E+UpNyB9Xmesj238aG8q6fr3wBIaq3VcJ3OFRERERERERHDm+zuHGI3tElaCjwFnG77yIGOJwaOpLOB/wX+YXvTzvpOnjzZ06dPXzGBDbBGFdRwqugaDs8yGOR9rhh5zxERERER3SfpZtuT22sbEUsXbY8a6BhicLD9EeAjAx1HRERERERERPS9LF2MiIiIiIiIiIhhIYmuiIiIiIiIiIgYFkZEokuSJS2SdHwPxsyqJ/j1O0kvrzH2eCmppPsk7dTH8ewl6dpO2q+QtGdf3nNFkXS3pH9KOn+gY4mIiIiIiIiIvjUiEl3VBNuHw/MSS631c5+kQ5s7297C9rSe3EDSRk1ztjYl2Brft+t6lsHP9i62v99em6Sj20si1XfR7ubvdczTbd7dJk3tb5R0o6SFkv4iadvO4pP0OknX1HnmSfpkU+yvBE7o9sNGRERERERExJAxIjaj78RY289Imgz8oe7a/5veTmb7fqCl8V2SKQm2u/og1uHuYtt7tL0oaW3g58DHgZ8A7wcul7SJ7Sfa6b8O8Gvg08CPgVWADfoz8IiIiIiIiIgYHEZ6ogsA29MlzQImAr+BsiQQ+KjtqyUdDbwWWAq8E7gf2NP29O7eQ9KuwHHAK4EFwNm2j+6g7/8ApwC7AUuAs4AJgIErgf9ne37TkImSTgU2piR59rS9VNJawHnANpTf+jpgP9sP1vvsBXwBWBd4FDjC9gVNcXyFckLhfGB/21fU69OA821/t7vPvxzeCMyz/aP6/XxJXwDeBZzdTv+DgCubnuMp4Lbe3PiOxYuZMmNGb4YOOTNbW5nY0tJ1x4iIiIiIiIhBbCQtXeyQpDcAWwKdVV69DfghMJZSYXRGD2+zCPhQHb8r8HFJ72gnlr2Bk4GdbP8NEHAiMB7YHNgQOLrNsPcAbwVeAfw7sFe9/iLgHEoCbCNK0uyMep/VgdOBXWyPoSSUZjbNuQ1wB7AO8CXgbEnq4TP3xO6SHq97o3286brqhzbXtuxgnjcAj0v6k6R/SLpc0kb9EfBwMrGlhanjxg10GBERERERERHLZaRXdD0qaVVgFKWC6rJO+l5r+1cAks4DPtWTG7XZ7+svki4Ctm9zz08BHwamNKqu6rLHRgLukVq5dVSb6U+3PafGdjmlMg3bjwGXNjrVzfh/3zRuGbClpPttPww83NQ22/ZZddz3gW8C44C53Xjc90jarRv9Gi4BvgPMoyTYLpU03/ZFwJ+A8ZLeT1mKOJVSFTe6g7k2AF4H7Az8lZKkuwj4zx7EA8Bmo0czbdKkng6LiIiIiIiIiAEy0iu61qHsqfUZYAqwcid9mxM8i4FRPTklUdI2kn4v6RFJC4D96v2bfRb4RiPJVce9VNIPJT0k6Ung/HbGtY2tpY4dLenbkmbXsdcAYyWtZHsR8N4ax8OSfinpNe3NaXtx/bO7a9susT22+dNZZ9v/Z3uO7Wdt/wk4DXh3bXsMeDtlSeI8SuXa1cCDHUy3BPip7ZtsLwWOAd4oac1uxh4RERERERERQ9RIT3RRkyunUPbf2r8fb3UhZcnjhrbXBM7khUvy3gwcUffoajiRsjfXv9teA9ijnXEdORjYDNimjv2vel0Atq+0vTPwMuB2yl5gg4Fpekbbf7C9le21gQ9SnunGDsb+pY5vngu6/84iIiIiIiIiYoga6UsXm50EfEfSmbUSqK+NAR6vm8RvTVmCd1WbPrMoFUtXSnra9s/ruAXAfEnrU6q+enLPJXXs2jQteZQ0jrJM8Le1TyvwbK+ebDlJejul2mw+sBVwIHBYU/sk4G/AasCxwIO2r+xgunMoSx9Pp7zPIynLTud30D+GoZmtrSPmIIH+loMKIiIiIiJiKBnxFV1Nfgk8AezTT/PvDxwraSHlpMNL2utk+1bKaYtnSdqFsvTudZRk1y+Bn/Tgnl+jJIceBW6gnMjY8CJKxdcc4HHKfmH9WdHWmfdR9iFbCPwAONn295vaP0d5hgco1WfvbDRI2k5Sa+O77d9RkmS/BP4BbEpJKkZEL+SggoiIiIiIGEpku+teQ5ykpcBTlE3bjxzoeGLgSLoDWJ+yj9iHO+s7efJkT58+fcUEFn2mUcmVgwRiKMm/24iIiIiI7pN0s+3J7bWNiKWLtkcNdAwxONjebKBjiIiIiIiIiIj+kaWLERERERERERExLAxIokuSJS2SdPwKuNd9knbq5diNJLVKWqmv41qRJJ0pKUs2AUm/k7RU0rUDHUtERERERERE9K2BrOiaYPtwAEkvr8mv1qbPrQMYGwC277fdYnuFn0Yo6TBJ99Z38aCki5vapkn6aHfnsr2f7S/2T6TPJ2mv9pJInSUc65hn2/z+U9r0eZ+k22qC9G5J23Uw16qSvippjqQnJH1T0sqNdts7APst31NGRERERERExGA02PboGmv7mY4aJb24s/a+tCLv1c699wQ+COxk+25J6wFvG4hYOtPH7+h629t2cJ+dgZOB9wI3Uk5e7MihwGRgS2Al4HLgCOCoPoozIiIiIiIiIgapQb1Hl6QptZrpEElzgXMkvUjSobWq5zFJl0hau2nMByXNrm2Ht5mvw7FNVWUfkXQ/8Lumay+ufV4h6Q+SFkr6jaQzJJ3fHGub+z1XxdRV3G1sBVxp+24A23Ntf6fOczywHXBGrXw6o15/TY3pcUl3SHpPUxznSjquzTs9WNI/JD0sae+mvqtK+oqk+yXNq8seV+vo9+jhT9pbxwDH2r7B9jLbD9l+qIO+u1NO13zc9iPA6UCnpyt25I7Fi5kyY0aXn+/MmdPLx4qIiIiIiIiIvjSoE13VesDawMbAvsCBwDuA7YHxwBPANwAkvRb4FqUaajzwEmCDprk6HNtke2Bz4C3txHIhcDOwDvBFYM8ePEd37t1wA/AhSZ+VNLl5j7C63POPwAF1WeUBklYHflPjeynwfuCbkrboYP71gDWB9YGPAN+QtFZtOxl4NTAR2LT2+UKbsc2/R1+ZJOlRSXdKOrIpubgSpUJrXUl31UTbGY3kWztUP83fN5C0Zh/G+pyZra1cOG9ef0wdERERERERET002JYuPio9l6M4DpgOLAOOsv0UgKSPUZI8D9bvRwP3S/og8G7gF7avqW1HAgc0zd/Z2IajbS+q7c9dlLQRpdJqpxrLNZIu78GzdXjvtsv/bJ8vycDewNHAUklftn1SB3PvBtxnu1FhdYukS+v7mNVO/6cpFVLPAL+S1ApsJunPwD7Av9t+vMZ5AiWB9vk69nm/RwfeIGl+m2trdNL/GspSw9nAFsDFwDPAicA4YOX6LNvV2H9GWY54eDtzXQF8UtLvKUsXD6zXRwMLOonhBTYbPZppkyZ12mfKjBk9mTIiIiIiIiIi+tFgS3St05z0qRuSP2J7aVOfjYGfSlrWdO1ZSkJkPPBA46LtRZIe6+bYhgdo33jgiUYSrJoNbNjlU3V97xcsw7N9AXBB3Uj9HfXvGbav7GDubdokl14MnNdBLI+1Sa4tBlqAdSkJoZubknyiJIwa2v4e7bmh7X5bku7rqLPte5q+/lXSscBnKYmuJfX6120/XOc6lY4TXccDY4GZwFPAWcAk4B9dxBwRERERERERQ9xQWLroNt8fAHaxPbbpM6ru2fQwTYknSaMpyxe7M7aj+zU8DKxVlwk2bNT09yJKkqhx75UoiaOe3PuFD28/bftHwF8oVU/txfgA8Ic2c7fY/nhnc7fjUUpiaYumeda03dIcUg/n7A1Tlx/afgJ4sLv3tb3E9gG217e9CfAYcPNAnJwZERERERERESvWUEh0tXUmcLykjQEkrSvp7bXtx8BukraVtApwLM9/xs7Gdsr2bMpSymMkrSJpW8rG5w13AqMk7VqrsI4AVu3NvSXtVecZUzex34WypO/Ptcs8YJOmIb8AXq2yEf/K9bOVpM2782xNz7iMUgH1VUkvrbGsL6m9/cr6jKRdJI2rf78GOJKyPLHhHOATkl5a9xL7FOWZ25trfUnjVbyhzpUTFyMiIiIiIiJGgKGY6DoN+DlwlaSFlI3btwGwPQv4f5Q9pR6mbPj+YHfGdtPU2v9xSvLkB40G2wuA/YHvUpYiLlqOez8JHAbcD8wHvgR83Pa1TXO9W9ITkk63vRB4M/A+YA4wl7Kp/KovmLlrhwB3ATdIehK4GtisF/P0xI7AXyQtAn4F/AQ4oan9i8BNlGTibcAMyhJFJG1UT59sVNe9EvgT5f1/HzjU9lX9HH9EREREREREDAKyV8RKtDY3lZZS9k863faRKzyAPlI3lN/U9h4DHUt0j6TfAG8AbrS9Y2d9J0+e7OnTp3c635QZM5jZ2srElpZO+8WK0/g9ujpIIGIwaRxskX+3ERERERFdk3Sz7cnttQ3IZvS2Rw3EfSNs7zzQMUT/mtjSwtRx47ruGBEREREREcPOYDt1MWLISfVQRERERERExOCQRNdysH30QMcQERERERERERHFUNyMvtskWdIiScevwHtK0jl1o/gbV9R9VyRJ50o6bqDj6A1Jv5O0VNK1XfeOiIiIiIiIiKFkWCe6qgm2D298qcmvTfvxftsCOwMb2N66p4Ml3SdpiaSFkuZL+pOk/SQNid9K0l7tJZHqc+3UyZhn6+mJjc+UNn3eJ+m2mri8W9J2Hcy1p6SbJT0p6UFJX5L0XOWi7R2A/ZbvKSMiIiIiIiJiMBoSyZMhZmPgPtuLlmOO3W2PqXOdBBwCnN2biZqTPIPc9bZbmj7TGg2SdgZOBvYGxgD/BdzTwTyjgU8B6wDbADsCn+nPwCMiIiIiIiJicBgqSZB+IWlVSgLlPfXSJcAhtp+StA5wLqVCaxkwC9je9jJJ44GvUxIurcBXbZ8u6SPAN4CVJbUCpwBfA86jJF1eDFwH7Gf7wa7is70A+LmkucANkk6x/TdJ04DzbX+3PsdewEdtb1u/GziAkvB5MfAKSacB7wLWBP4OfMr2H2v/o4HXAkuBdwL3A3vanl7bJ1ESba8CfgW42y+5bxwDHGv7hvr9oY462v5W09eHJF0AvKk3N71j8WKmzJjRaZ+Zra1MbGnpzfQRERERERER0cdGekXX4cAbgInABGBr4IjadjDwILAuMA44DHBdQng5cCuwPqVi6FOS3mL7bMqyuEZ10lGUd3wOpTprI2AJcEZPgrR9Y42l3eV6HXgHJbn22vr9pvqcawMXAj+SNKqp/9uAHwJjgZ83YpS0CnAZJVm3NvAj4H96En83TZL0qKQ7JR3ZqESTtBIwGVhX0l11OeIZklbr5rz/RUlS9ouJLS1MHTeuv6aPiIiIiIiIiB4Y0RVdwAeAT9j+B4CkY4BvA0cCTwMvAza2fRfQqH7aGljX9rF1jnsknQW8D7iy7Q1sPwZc2vheN8b/fS9inUNJNHXXibYfb4rj/Ka2UyQdAWxGSdgBXGv7VzXG8yjVYFASgSsDX7Nt4MeSDuri3m+QNL/NtTU66X8NsCUwG9gCuBh4BjiRkmRcGXg3JdH3NPAzSkLy8PYma5C0NyVJ9tEu4m3XZqNHM23SpN4MjYiIiIiIiIgBMNIrusZTkisNs+s1gC8DdwFXSbpH0qH1+sbA+LpR/Pya0DmMkpB5AUmjJX1b0mxJT1KSOmNrpVJPrA883mWvf3mgTRwH183cF9SY16TsY9Uwt+nvxcCoWlU1HnioJrkamt9Ze26wPbb5Q1kO2S7b99i+1/Yy238FjqUktqBUwAF83fbDth8FTgX+u7MAJL2Dsr/ZLnVMRERERERERAxzIz3RNYeSuGrYqF7D9kLbB9veBNgdOEjSjpQE0r1tEjljbHeUeDmYUjm1je01KEvpANTdICVtRUl0NU4zXETZdL1hvXaGPZeYqicUHkLZi2ytmnha0M0YHgbWl9Tcd6Puxt5LpsZm+wnKss1u7wsm6a3AWZRN/f/aLxFGRERERERExKAz0pcuXgQcIekmSiLlC8D5AJJ2A24H7gaeBJ6tnxuBJyUdApwO/BPYHFjN9k3t3GMMpSppvqS1gaO6G5ykRmLsNMrm842kzUzgXZK+S6m4+ggwr5OpxlCWAj4CvLhWp3W2lLDZ9XXsgZK+QdnLa2t6t/yyXZJ2AW6xPU/SayhLR3/U1OUc4BOSfk1Zuvgp4BcdzLUDcAHwzrq3WUTEkDCztbXLAzA6M3XcOPYdP77rjhERERERw9hIrehqVAcdB0wH/gL8FbilXoNywuDVlFMVrwe+aXua7WcpFV4TgXuBR4HvUpYCtudrwGq13w3Ar7sR3+WSFlKqxw6nLNXbu6n9q5QE2zzg+5TETmeuBK4A7qQsO1xKm6WNHbH9T8ppjXsBTwDvBX7SnbE9sCPwF0mLKKc6/gQ4oan9i5TN9O8EbgNmAMcDSNpIUqukRpXZkZTf4lf1equkK/o43oiIQWVmaysXzuvs/3dERERERIwMev7WS8OLpKXAU8Dpto+sFVILKMv32m6WHiOApN9QNti/0faOnfWdPHmyp0+fvmICi4gRrVHJ1dsDMJZ3fERERETEUCLpZtuT22sb1ksXbY9qc+m9wN1Jco1ctnce6BgiIiIiIiIion8M60RXM0l/AsYCHx3oWCIiIiIiIiIiou+NmESX7TcOdAwREREREREREdF/ht1m9JIsaZGk4/tgrpfX+UZMQrA7JE2R9OBAx9Ebkj5SN6i3pE0HOp6IiIiIiIiI6DvDLtFVTbB9ODwvWdU4ge8+SYcORFDdSZxJOlrS05IW1s+dks6Q9LIVGevyaC+JVJ/r/C7GLGr6nb7b1CZJx0l6SNICSdMkbdHJXDtIukXSk5LukbRvo8322bZblvcZIyIiIiIiImLwGa6JrvaMrQmOdwNHSlqhm5L3sCrsYttjgLWBdwLrATf3NtklaaXejBsAE2y31E/zXmr/C3wY2I7yTq4HzmtvAkkrAz8Fvg2sSTmA4FRJE/o18oiIiIiIiIgYcCNuSZ7t6ZJmAROB30h6EXAYsA+wGvBr4BO2FzQN+7CkowEBX7F9CkAd+7k6dizwW2A/249LejlwL2Xz+6OA+4CX1/nmSwLY2fb1ncT6NDBL0nuBW4CDgc9I2gv4qO1tG30lGXiV7bsknQssATYGtgfeLmlV4DjglcAC4GzbR9exjVj3Ar4IjAa+avv42r4a8C3g7cDDwDmdvOL+8ArgWtv31HjOBz7dQd+1gTWA82wbuEnSbcBrgVt7ctM7Fi9myowZvY96mJg6bhz7jh8/0GFEREREREREdGkkVXQBIOkNwJbAXfXSXvXzJmAToAU4o82wNwGvAt4MHCppp3r9QOAdlGTSeOAJ4Bttxm4PbA68Bfivem1srVrqMMnVzPazwM8oFU3dNRU4HhgDXAssAj5EScjtCnxc0jvajNkW2AzYEfiCpM3r9aMoCbJX1ufYswdx9MQ1kuZK+klNvjX8ENhU0qtrxdaelITkC9ieB1wE7C1pJUn/QUn4XdtPMQ9rM1tbuXDevIEOIyIiIiIiIqJbRlJF16O1qmkUcApwWb3+AeDUpmqhzwN/k7R309hjbC8C/irpHOD9wNXAx4ADbD9Yxx4N3C/pg01jj65jqVVcvTWHUq3UXT+zfV39eykwrantL5IuoiThLmu6foztJcCtkm4FJgC3Ae8B9rf9OPC4pNOBL3Rx/1skLWv6Pgr4cSf9twduoFSTHQf8QtJE289Qqsj+CNwBPAs8AOzQyVwXAd8FTqvfP277gS7ifYHNRo9m2qRJPR02rKSiLSIiIiIiIoaSkVTRtQ6lWuszwBRg5Xp9PDC7qd9sSgJwXNO1B9q0N9ZxbQz8VNJ8SfMpSaFnOxm7PNYHHu9B/+fdV9I2kn4v6RFJC4D9KO+k2dymvxdT3heU5237DrryOttjGx/gpM46277G9j9tzwc+SVmu2FxRthWwISVhdgzwO0mj284j6TXAxZTqtVWALYDPSdq1GzFHRERERERExBA2khJd2H627q+1FNi/Xp5DSVg1bAQ8AzSv19qwTfuc+vcDwC7NCR3bo2w/1HzbDv7utroX2O6UqiYoyxBHN7Wv186wtve6EPg5sKHtNYEzKXuOdcfDvPAd9Dfzr/gmUDbof9D2M7bPBdai7LvV1pbAHbavtL3M9h3AL4FdVkDMERERERERETGARlSiq8lJlCqfUZRlbp+W9ApJLcAJlKTKM039j5Q0WtIWwN6UiiEoyaLjJW0MIGldSW/v5L6PAMsoe4F1SdLKdZ+siygnL55am24FtpA0sT7D0d2YbgzwuO2lkram7OHVXZcAn5e0lqQNgE/0YGyXJDWeZaX6G5wCPESpkAO4CfhfSeMkvaguDV2Zf+2z1mwG8CpJO6h4JbAbPdyIPiIiIiIiIiKGnpGa6PolZeP4fYDvAecB11BOHlzKCxM5f6AkVX5LOXXxqnr9NEqV1FWSFlL2mNqmo5vaXkzZIP66utzxDR10fa+kVmB+nf8x4PW259R57gSOpewT9ne6t9H6/sCxNc4vUJJX3XUMZbnivcBVlPfVl8ZRkodPAvdQTqfcrZ46CXAyJVE1k/JOPg38T13miKQrJB0GYPtu4MPA6XW+PwCXAmf3ccwRERERERERMcjI7tVqukFL0lLgKeB020cOdDwxuNRDBr5K2evrtY1DCNozefJkT58+fYXFNhhNmTGDma2tTGxp6brzMDB13Dj2HT++644Rfaxx8ENvD8BY3vEREREREUOJpJttT26vbdidumh71EDHEIOX7XOAcwaDfwfkAAAgAElEQVQ6jhh8Zra2AiTRFRERERERMYQNu0RXRPStiS0tI6JKpFERExEREREREUPXSN2jKyIiIiIiIiIihplhmeiSZEmLJB3fi7GzJE1ZzvufK+m4DtrOlDRk9w6T9PL6fodcNaCknSS1SlomaaeBjiciIiIiIiIi+tawTHRVE2wfDs9LztzS3EHSOpL+Kem+xjXbW9ie1l9B2d7P9hfba5O0l6RnazKmVdK9ks6R9Or+iqevSbqvbRKpPleHJ0PWMUuanvuqNu2fqO/iSUnTJW3byVxvlHSjpIWS/tLc1/bVtluA+5fjESMiIiIiIiJikBrOia72rC5py6bvU4F7ByqYDlxfkzFrAjsBS4Cb28TdbUOo8mp32y318+bGRUnbACcB76a8k7OBn0paqe0EktYGfg58GRgLfAm4XNJaK+IBIiIiIiIiImJgDZUkSF85D9gT+Gz9/iHgB8A+jQ61uuujtq+WtDXwTeDVlITTBbYPqv1+BGwHrAbcCnzc9qy2N5Q0hpJ8+SvwScqJfw/aPqKzQG0/C9wN7C9pI+Bo4N11WeX5tjfoIOajgS2BpcDbgIMk/QU4Ddi8PselwEG2/1nHG/g4cDCwDnAhcIBt14TSycBewJPAKZ3F3Q9eDsyyfXON9QeU3+SlwMNt+r4RmGf7R/X7+ZK+ALyLkiDrkTsWLx7xG5TPbG1lYkvLQIcRERERERER0S0jraLrfOB9klaStDkwBvhzJ/1PA06zvQbwSuCSprYrgFdREi63ABe0HSzpJcBvgetsH2jbvYz7J5SkWne9HfgxparpAuBZ4NOUJNZ/ADsC+7cZsxuwFTABeA/wlnp9n9o2CZhMqazqDxdIekTSVZImNF2/AlhJ0jY16fZhYCYwt505VD9tr/WqGi7KiYtTx40b6DAiIiIiIiIiumWkVXQ9CNxBWRL4Jko1V2eeBjaVtI7tR4EbGg22v9f4u1ZRPSFpTdsL6uXxwB+A79v+8nLGPQdYuwf9r7d9Wf17CXBzU9t9kr4NbA98ren6SbbnA/Ml/R6YCPyakvT6mu0HACSdCEzp4v6XSXqm6fsqlGRgRz5Q20WpertS0mtqPAspFWjX1vb5wC4dJA3/BIyX9H5Kom8qJUE5uot427XZ6NFMmzSpN0MjIiIiIiIiYgCMtIouKMmtvYD3Uyq8OvMRyrLF2yXdJGk3gFoRdpKkuyU9CdxX+6/TNHZXyrLGM/sg5vWBx3vQ/4HmL5JeLekXkubWeE/g+bHC8yukFgON9Wrj28w3uxv3f4ftsY0PL6weex7b19leYnux7RMpyaxGBdtHKVVcW1ASZnsAv5A0vp15HqNUsx0EzAPeClxNSXBGRERERERExDA3EhNdl1KSUPfY7jRpY/vvtt9PWZ54MvBjSatTKoXeTqkMW5OyjxQ8f9ncWZSKqF/VMcvjncAf69+LaKpQqsv51m0bepvv3wJuB15Vl2EexguX+HXkYWDDpu8bdXPc8jD/im8CcLntO20vs/3rGtMb2x1o/8H2VrbXBj4IbAbcuAJijoiIiIiIiIgBNuISXbYXATtQKoU6JWkPSevaXkapMoKy39UY4CngMUrS6YQOpjiAslTyF5JW60mctWrsFZK+TlkqeExtuhMYJWlXSSsDRwCrdjHdGMpG8q2SXkPZeL67LgEOlLRBPb3w0J48R1ckbSTpPyWtImmUpM9Sqs2uq11uAnaVtImKnSlVdn/rYL5JklaWtAbwFcrG/1f2ZcwRERERERERMTiNtD26ALA9vZtd3wqcKmk0Zcne+2wvrSf/vQV4iLKk8EjaSR7VUwv3Bc4Ffibpbd24539IaqVUND0KTAO2sn1bnXOBpP2B7wIrAV+i66V5nwG+A3wOmAFcTEn2dcdZlMTSrZRk2Vd6MLY7xlAqzl5JOSlyJmUPrsdq+w9q2zRgLcqzfsz27QCSzgSwvV/t/zngv+vfv6ZUw0V0y8zW1mF90ubUcePYd/wLVv1GREREREQMG+r9QYCDl6SllIqr020fOdDxxOAgaUfK0tVVgf+2/fvO+k+ePNnTp3c3JxpD3ZQZM5jZ2srElpauOw9BjWfLAQuDUyPB2tvfZ3nHR0REREQMJZJutj25vbZhWdFle9RAxxCDj+3fAmMHOo4YvIZzImg4V6pFREREREQ0jLg9uiIiIiIiIiIiYnhKoquHJFnSIknHD3Qs0TOSdpLUKmmZpJ0GOp6IiIiIiIiI6FtJdPXOBNuHN77U5NemK+rmks6VdNyKul9PSLqvbRJJ0l6Sru1izJKahGqVdFWb9qmSZtcE42WS1u5krpdL+r2kxZJub47F9tW2W4D7l+MRIyIiIiIiImKQSqIrBovdbbfUz5sbFyVtAXwb+CAwDlgMfLOTeS6inCz5EuBw4MeS1u2/sCMiIiIiIiJisBiWm9EPJEmrAicD76mXLgEOsf2UpHWAc4FtgWXALGB728skjQe+DvwX0Ap81fbpvbj/PsAhwNrAtcB+tufUNgOfBD4FrAGcU2NbVts/DHwWWA+4EdjX9mxJnwO+0HSbVYELbO/V0/h64QPA5bavqTEeCdwmaYzthc0dJb0aeB3wZttLgEslfQr4H+DMnt74jsWLh8UG3lPHjWPf8eMHOoyIiIiIiIiIfpeKrr53OPAGYCIwAdgaOKK2HQw8CKxLqU46DLCkFwGXA7cC6wM7Ap+S9Jae3FjSDsCJlCTby4DZwA/bdHsnMJmSEHo78OE69h01nnfV+P5IqY7C9pca1VbA5sAjlAReX7pA0iOSrpI0oen6FpT3Qo3lbuCfwKvbmWML4J42CbBb6/URaWZrKxfOmzfQYURERERERESsEKno6nsfAD5h+x8Ako6hLL07EniakoDa2PZdlGQSkrYG1rV9bJ3jHklnAe8Druzhvb9n+5Y67+eBJyS93PZ9tc/Jth8HHpf0NeD9wHeBjwEn2r6tjj0BOEzSxrZn12urAZcBp9n+VSdxXCbpmabvqwC3dBH3LYAoFWdXSnqN7flAC7CgTf8FwJh25umo7/qd3LtDm40ezbRJk3ozdNAYDhVpEREREREREd2Viq6+N55SSdUwu14D+DJwF3CVpHskHVqvbwyMlzS/8aFUV41bnnvbbgUe4/mJngc6iG1j4LSm+z9OSTw1jz0buMP2yV3E8Q7bYxsfYP/OOtu+zvYS24ttnwjMB7arza2UZZbN1gAW8kI96RsRERERERERw0wquvreHErSaFb9vlG9Rl1SdzBwcN1k/feSbqIkn+61/ao+ujcAklanbMr+UFOfDduLrcZwvO0L2pu4JuU2o+wv1t9MSbJBifW5pYySNqHsEXZnO+NmAZu02b9rAnBhP8YaEREREREREYNEKrr63kXAEZLWrZvPfwE4H0DSbpI2lSTgSeDZ+rkReFLSIZJWk7SSpC0lbdXJfVaSNKrpswolobO3pIl1U/wTgD83LVsE+KyktSRtSFkmeHG9fibw+ZqAQ9Kakv63/r0LcCClUmtJH7yj50jaSNJ/SlqlPsdngXWA62qXC4DdJW1XE3fHAj9puxE9gO07gZnAUXWudwL/DlzalzFHRERERERExOCURFffcf3vccB04C/AXyl7Tx1X214FXE1ZYnc98E3b02w/C+xO2cD+XuBRyr5Za3Zyv0OBJU2f39n+LWUvsEuBh4FXUvb5avYz4GZKQuiXlOWI2P4p5bTIH0p6EvgbsEsd817KBvW3SWqtnx6fYtiBMcC3gCcolWdvBXax/ViNaxawHyXh9Y/a/7mlkJLObBPL+yib7T8BnAS82/YjfRRrRERERERERAxist11r3iOpKXAU8Dpto+UtAZlw/O16ubpg5YkA6+qG+GPOJJ2pCQBVwX+2/bvO+s/efJkT58+fYXE1l+mzJjBzNZWJra0DHQog17jPQ31Awg60jiYYLg+31C3vL9Pft+IiIiIGEkk3Wx7cntt2aOrh2yPanPpvcDdgz3JFVAr3sYOdBwxOE1saWHquJ6e/xARERERERGDSRJdy0HSnyiJk48OdCwRHRnOVUoRERERERERzZLoWg623zjQMfSEbXXdKyIiIiIiIiJiaBqWm9FLsqRFko7vo/mOk/SopLn1lMBWSSv1xdyxYkk6V9ISSQ8OdCwRERERERER0beGZaKrmmD78MYXSR+RdLukhZLmSfqlpDFdTSJpQ+Bg4LW217N9v+2WelJij0l6maSzJT1cY7ld0jGSVu/NfIONpCntJZEkTZPU5RJPSefUROWmTde+JOkBSU9Kmi3p8E7GS9Lhku6v/X9YDwwAwPZe/Os0yYiIiIiIiIgYRoZzous5krYHTgDeb3sMsDlwSTeHbww8ZvsffRDH2sD1wGrAf9RYdqbs8/XKXsz34jbfJWnI/qaStqX993A28BrbawBvBKZKelcH03wI+CDwn8B4yrv+ej+EGxERERERERGDzEjZo2sr4HrbMwBsPw58v9EoaU1KMmQXYDFwFiUxtgNwObCqpFbgx8DRwL3AyrafkbQ38DlgA+AR4GTb3+4gjoOAhcAetpfVWB4APtkUy2nAu4A1gb8Dn7L9x9p2NLAlsBR4G3CQpD2A64ApwOuAf5O0XUcxSVoHOBfYFlgGzAK2t72sVq+dBmxHSYJeZPuAmjw7DNiHkjj6NfAJ2wu6fvXdU5N2Xwf2BG5tbrN9R5vuy4BNad/uwNn1vSLpZOB3kj5ue3FPYrpj8WKmzJjRkyGDzszWVia2tAx0GBERERERERErxJCt/umhPwNvqUsE/1PSqm3av05JLG0CbE+pCvr/7N15lFxVuf7x7yNDIDSjYK4BgZ8iUVAI3gg4IPGCcFGcrqDXoAxeQUVExQFlMEQBRREBUUEEmRFQcWBwQGVUwCAQQUVQwhQSSEhCOiEM4fn9sXdBUVR3ujuddKf7+axVi649nfecQtfiXe/eZx/bV1CSX9PqdsW926z9ELArsAawD/AtSa/pIo4dgZ82klxd+DMwFlgHOA+4SNIqTf3vpCTc1gLOrW0fBPYDVgfuWUxMnwHuB9YDRlESWK5njl1S528MrA/8qM7Zu37eTHlGHcBJ3dxDX3wauNr2lHadkr5Qk433A6tRnk3bofXT/H0E8PJ+jHW5MbajgwmjRg10GBERERERERHLxLCo6LJ9Td3qtj+lempFSd8HPleHvA/YyvY8YJ6kb1KSR6f1YO1Lm75eJek3lIqov7QZ/kLgwcWsd07T129KOgwYw7NVTn+y/bP692OSAM6wfXvTvO5iehJ4MbCR7buARrXY1pStfp+z/VSde2395x7Acbb/Xcd+EbhN0j5NY5uNljSnpa0DOKfN2MY5aB8B/rNdP4Dtr9XqrLHAu4CuqskuBz4v6UJgNnBwbR/Z1dpdGTNyJFdutVVvp0VERERERETEABkuFV3Yvtz22ymVUu+kVCh9GFgXWJlSydRwD6WiabEk7SLpekmP1OTOW+ua7cyiJJm6W+8zkv4uaW5db82W9e5rM+05bYuJ6RvAXcBvJP1b0hdq+0uAe7pKXPH857MipSKsnWm212r+8GzSrJ3jgS8vbiuki5uBx4BJXQw7HTgfuJKyLfMPtT1vWYyIiIiIiIgY4oZNoqvB9tO2fwf8nnLe1UxKldNGTcM2BB5Y3Fp1C+RPgGOBUTWhcxnP3TrX7Arg3V0dGF/P1joYeC+wdl1vbst6bndbPY3J9jzbn7H9Usp5VgdJ2oGSLNuw9YD7ahrPfz5PATO6uM/e2gH4hqTpkqbXtj9JmtDF+BXp4vD++vtOtL2x7Q0oya4H6MHvGRERERERERHLt2GxdVHSOymHqP8amEM5nH57ykHvi+o2t6Mk7Ump+DqIkihanJUp5z89DDwlaRdgJ+C2LsYfB3wAOFPSYbbvkbQ+5dysMyhnbD1V11uxVlut0cvb7TYmSbsC/wD+BTwKLKqfGynbKr8maWJt+0/b11EqpA6WdHld92jggi6qv/piU56bdH2QkoS7tSYF96W8JbPx230c+Gq7heqbLdcG/k15u+ZxlGqx7s5FixgWbunsXOovWJgwahT7jR69VK8RERERERHRleFS0TWbkiy5k5LcOQf4hu3GYe6fAOZTkiPXUg46P31xi9YzvQ6kJGFmAxOAX3Qz/hHg9ZQKshskzQN+R6nauouSiLsc+Cdle+BC2m9VXJKYXk6pLOsE/gR81/aVthdRkkubAPdStvq9r845HTgbuJryxsmFlGfWL2w/ZHt641ObZ9p+rP79bkpibh7lt/t2/QAgqbNWw0HZonkZ5fe8HDjd9vf7K9aI6NotnZ2cN6O/Cj0jIiIiIiJ6T3a7nXDLN0kLgceBE20fPtDxxOAh6TRgd+Ah25t0N3bcuHGePHnysgksYilrVHItzRcsLItrDFVL+uzy7CMiIiJiOJF0k+1x7fqG5NZF26sMdAwxONn+P+D/BjqOiIiIiIiIiOh/w2XrYkREREREREREDHHLdaJLkiXNl3TUQMcy1NRn2+3WvuWNpBH1PK8nJR050PFERERERERERP9arhNd1Za2D21ukLRaTWhcNlBBdUXS3pKubfq+hqTrJP1E0koDGVt/kHRGaxJJ0sY1cdbtVllJ60h6uPn51Paxkm6StKD+c2w3axwr6U5J8yT9o75JEwDbj9vuAM7tan5ERERERERELL+GQqKrnd0oh9HvJOnFAx1MVyStTXkD4j3A+2w/OcAhDbRjgL83N0haGfg55W2LawNnAj+v7e3Mp7w9ck1gL+AESa9fahFHRERERERExKAxVBNdewEnA1OAPQAk7S7ppuZBkj4j6Wf177dJulnSo5Luk3RE07hGRdJeku6VNFPSoU39IyQdL2la/RwvaUR3AUpaF/g9cDvwAdtP1fZdJd0iaY6kP0raomnOVEmflTRF0lxJF0hapfaNl3R/vaeHJD0oaZ+WGI+t8c+QdLKkVZv6P1fnTJP0oab219bxKza1vUfSLT36JXpI0uuAVwE/bOkaT3lpwvG1IutEQMB/tVvH9kTb/7D9tO0bgGuA1/VnrBERERERERExOA25ty5K2pCSHDkAeISS9DoW+AVwiqRX2m5UDX0AaGyzmw/sSUk8vQr4raRbbP+safk3AmOATYEbJf20rnUosC0wFjClAukw4PAuwlwHuIqShPmYbdfYXwOcTqlImlzj+4WkMbYfr3PfC/w3sBC4DtibktQD+A9KJdP6wFuAH0v6me3ZlGqpl9YYnwTOA74EfFHSfwOfBXYA7gZObQRq+8+SZtX1Lm96bmd3cW+9JmkF4DvAvsCrW7o3B6Y0nlE1pbb/ajHrrgq8FvhuX+K6Y8ECxt98c1+mRh9NGDWK/UaPHugwIiIiIiIiYjk1FCu69qQkRv4GnA9sLmmrmii6gJKkQdLmwMbAJQC2r7T911oJNKXO3b5l7Um2H7N9K3ArsGVt3wP4su2HbD8MTAI+2E2ML6Eky37YksDZFzjF9g22F9k+k7IFc9umMSfanmb7EeCXlMRVw5M1jidtXwZ0AmMkqa79aduP2J4HHA38b5333hrLbbbnA0e0xHtm03NbB9iZkijrymdrRdocSXMoianuHAjcYPumNn0dwNyWtrnA6otZE0oC8Fbg1z0YGwPsls5OzpsxY6DDiIiIiIiIiOXYkKvooiS6TgWwPU3SVZSqrpspCZvzJR1GSURd2KiUkrQN8DVKNdfKwAjgopa1pzf9vYCShAEYTTlnq+Ge2taVW+val0vawXajbGgjYC9Jn2gau3LLWq0xNPfNamyBbIlxPWAkcFPJeQFl+98KTfE3J5ma7wXK+Vh/l9RBSYpdY/vBbu7vWNuHPXMhaWNKpdjzSBpNSXT9ZxdrdQJrtLStAczr5vpI+gblt3xzSzKxx8aMHMmVW23Vl6nRB6mei4iIiIiIiCU1pCq66qHjL6dsx5suaTqwDfB+SSvavh54AtgOmMBzt9+dR9ne+BLba1KqgUTPTKMkqRo2rG1dsn0CJbH2W0mvqs33AUfZXqvpM9L2+T2MoyszgceAzZvWXbO+gRDgQUqVWXP8zbE+APwJeDclQdhv2xaBrYEXA3+rv9cJwNb191uBspV0CzVl6IAtantbkiYBuwA72X60H2ONiIiIiIiIiEFsSCW6KJVbvwU2o2zpG0up6hlJSXwAnAWcBDxl+9qmuasDj9heKGlrSiKsp84HDpO0Xj1k/kuUKqhu2f46JbFzhaQxlEq0j0raRsVq9ZD8nmzT6+46T9e1vyXpRQCS1pe0cx1yIbC3pM0kjQQmtlnmLODzlDO0Ll6SeFpcTtlC2vi9vkSpvhtrexFwJbAIOLAeqH9Anff7dotJ+iLlt3uL7Vn9GGdEREREREREDHJDJtFV3z74XuDbtqc3fe6mVCDtVYeeTUl+tVYl7Q98WdI8SrLlwl5c/kjK4fFTgL8Cf+HZQ+67ZfsrwA+A3wGzKWdpnVT/voty2Hx/OLiud72kR4ErKAfrY/ty4HhK8ugu2ieRLqZUrV1cz/HqF/VNis/8XpTzt56sf2P7CeBdlC2pc4APAe+q7UjaQ1JzddfRlIq0OyV11s8h/RVvRERERERERAxe6uPxRYOCpIWUw9pPtN3VGw5b56wKPAS8xvadSzO+oUbSv4CP2L5ioGPpC0kjgBnASsDXbU/qbvy4ceM8efLkZRJbPHtGV85FWzqWxfPNb9h3S/rs8uwjIiIiYjiRdJPtce36luvD6G2v0odpHwP+nCRX70h6D2C62DK4PKgvHlhroOOIrt3S2dnrQ+knjBrFfqO7e/dDREREREREDBfLdaKrtyRNpRww/64BDmW5IulKyrlnH6znfUUMCrd0dgIk0RURERERERHAMEt02d54oGNYHtkeP9AxxPAwtqOjV1uvelv9FREREREREUPbkDmMPiIiIiIiIiIihrchleiSZEnzJR010LHE4CTp95IWSrp2oGOJiIiIiIiIiP41pBJd1Za2DwWQtHFNfnXWzwxJl0h6y0AFJ2lTSRdJmilprqQpkg6StMJAxdSfJO3dLokkaaqkHXsw//f1N1uxqa2z5bNI0re7WePTkqbX53t6fdsiALb/C/hoH24tIiIiIiIiIga54XJG11q2n5L0H8D7gIslHWD7jGUZhKSXATcAPwRebftBSWOAicDqwJxerreC7UVN31e0/VR/xrwsSdqDNv9O2u5oGrMaMAO4qIs1dga+APwXMA24GJhU23rljgULcgbUMnRLZydjOzoWPzAiIiIiIiKiC0OxoqtLtqfbPgE4AjhG0gsAJI2W9BNJD0u6W9KBjTmStpb0J0lzJD0o6SRJKzf1W9JHJd0pabak70hSFyFMAv5o+yDbD9aY7rA9wfacut5FTdVIV0vavOlaZ0j6nqTLJM0H3lwrpQ6WNAWYL2lFSV+Q9C9J8yT9TdK7m9bYRNJVdf2Zki5o6ttc0m8lPVKr3w6p7SMkHS9pWv0c31wl1R8krUlJ+H1+MUN3Ax4Crumify/gNNu3254NfAXYu7/ijKVnbEcHE0aNGugwIiIiIiIiYjk2XCq6Wv0U+AYwRtIdwC+BnwPvBzYArpB0h+1fA4uATwOTa9/lwP7A8U3r7Qq8FlgDuKmu96s2190R+OJiYrsc+BDwBHAMcC4wtql/AvDWes1Gwu39wNuAmbVy7V/AdsB0YHfgHEmb1OTaV4DfAG+u88cBSFoduAI4Fng7sBKwWV3/UGDbGofrszoMOHwx99IbRwPfqzF3Zy/gLNvuon9zSnwNtwKjJL3Q9qzeBDRm5MhevQEwIiIiIiIiIgbWsKroajKt/nMdSoJqPdtftv2E7X8DpwL/C2D7JtvX237K9lTgFGD7lvW+ZnuO7XuBP/DcxFSzFwIPdheY7dNtz7P9OKXybMta7dTwc9vX2X7a9sLadqLt+2w/Vte4yPa0OuYC4E5g6zr2SWAjYLTthbYb52ntCky3/c3aPs/2DbVvD+DLth+y/TClMu2D3dzGtrUC7pkPsGFXgyWNA94AdHnuVh23IeXZn9nNsA5gbtP3xt+rd7d2RERERERERCz/hmtF1/r1n48ArwZG12RMwwrUrXGSNgWOo1Q+jaQ8s5ta1muuQlpASba0Mwt4cVdB1QPpj6JUYa0HPF271uXZhM19baY+p03SnsBBwMa1qaOuAWVr4FeAGyXNBr5p+3TgJcC/ughtNHBP0/d7altXrrf9xpaYprYbWLePfhf4ZK1G62ZZ9gSutX13N2M6KZV1DY2/53W3cCy/bunszFlqPZAz0CIiIiIiYjgYrhVd76ac83QHJUl0t+21mj6r235rHfs94B/Ay22vARwCdJuN6cYVwHu66Z8AvJOyxXFNnk1UNV+v3Za9Z9okbUSpSDsAeKHttYDbGmvUc8r2tT0a+AjwXUmbUJ7Dy7qIaxqlCqxhQ56tiltSa1CSiBdImg78ubbfL2m7lrF70n01F8DtwJZN37cEZvR222LEUJMz0CIiIiIiYjgYVhVdkkZRqqUmUiqInpZ0I/CopIOBEylnY70SWNX2nylb3h4FOiW9AvgY8HAfQ5gI/FnSNyiVVNNrkukISmJqdeBxSuXXSMq5Vb21GiXx9TCApH2AVzU6Je0O/Mn2/cDsOnYRcAlwnKRPUZJ7KwOb1e2L5wOHSfpzHf8l4Jw+xNbOXJ5bHfYS4EbgP2l6zpJeT6nEa/u2xSZnAWdIOpeyTfQw4Ix+ijUGobEdHTlLLSIiIiIiIoDhU9E1p76l8K+Ug9x3r9v1sL2Icvj6WOBuYCbwA0pFFcBnKZVW8yiVUhfQR7b/BbyOUql1u6S5wE8oB93PoyRp7gEeAP4GXN+Ha/wN+CbwJ2AGZWvmdU1DXgvcIKkT+AUl4Xe37XnAWyjPYjrlXK831zlH1hinUJ7hX2rbEnMxvfHh2eTWDNtPNA3dC/hpjfMZkjaU1FnP78L2r4CvU85Ku6d+JvZHrBERERERERExuPa/M58AACAASURBVKnrl9ctfyQtpFREnWi7P98IGEOEpN9S3iB5o+0duhs7btw4T548edkEFn3SOJsrFV2DQ36PvlvSZ5dnHxERERHDiaSbbI9r1zekti7aXmWgY4jBzfZbBjqGiIiIiIiIiFg6hsvWxYiIiIiIiIiIGOKS6IqIiIiIiIiIiCEhia5KkiXNl3RUL+ZsJ+mOpRlXf1he4lwWJP1fPbze9Y2XERERERERETFEJNH1XFvaPhRA0sY1GXJp8wBJ50g6AsD2NbbHLI1AJL1R0h8lzZX0iKTrJL229u0t6dqerrU042ynXRJJ0hGSzunB3L3q/A+3tL9U0iWS5kmaKenri7n+/JrQ6pT0g0af7dNsd/TlviIiIiIiIiJicBtSh9EvJdtKeoPt65bVBSWtAVwCfAy4EFgZ2I7yRslBQ9KKtp/qx/XWBr4I3N7SvjLwW+A7wPuARcCmi1luS9t3LUk8dyxY8MybzGJwuqWzk7EdyVtGREREREREkYquxfs6cGS7DknjJd3f9H2qpM9KmlIrsS6QtErtW7tWJD0saXb9e4MurrkpgO3zbS+y/Zjt39ieIumVwMnA62q10py6/ghJx0q6V9IMSSdLWrW3cdb+XSXdImlOrSrbomXuwZKmAPMl9Wey9KvAicDMlva9gWm2j7M93/ZC21P68bqxnBrb0cGEUaMGOoyIiIiIiIgYJFLRtXjfAQ6UtKPtK3ow/r3AfwMLgesoSZqTKUnFH9b+FYDTgZOAd7VZ45/AIklnAj8Crrc9G8D23yV9FPiw7Tc2zTkGeCkwFngSOA/4EqVCqsdxSnpNje3twGTgA8AvJI2x3agoez/wNmBmf1V0SdoaGAfsX2Nrti0wVdLlwGuB24BP2P5rN0teLekFwB+Bg2xP7W1MY0aO5MqtturttIiIiIiIiIgYIKnoWryFwFF0UdXVxom2p9l+BPglJfGE7Vm2f2J7ge15dc3t2y1g+1HgjYCBU4GHJf1CUtvSFUkC9gU+bfuRuv7RwP/2Ns66zim2b6jVZGdStkxu2zL3PtuPdbP+X2pF2JxadfaFrgZKWgH4LiV59XSbIRvUezkRGA1cCvy8bmlsZ3tgY+AVwDTgkn6uPIuIiIiIiIiIQSj/8d8zpwKfk/T2Hoyd3vT3AkpiBkkjgW9RqqjWrv2rS1rB9qLWRWz/nVJlhaRXAOcAx1OqqVqtB4wEbio5LwBEqRzrVZzARsBekj7R1L9yUz/Afd2s2/Ca5jOy6gH+Xb3lcH9giu0/ddH/GHCt7cvrWscChwGvBG5tHWz76vrnE5I+CTxax3ZXARYR/eCWzs6cbdcHOW8uIiIiIqJ/pKKrB2w/CUwCvkJJIPXFZ4AxwDa21wDeVNsXu57tfwBnAK9qNLUMmUlJBm1ue636WbOPbxe8DziqaZ21bI+0fX5zSH1Ytzs7AO+WNF3SdOD1wDclnVT7pyzhNU3ff7eIiKUu581FRERERPSPVHT13NnAwZSKrDv7MH91SjJqjqR1gIldDawVXG8DLrB9v6SXUCq5rq9DZgAbSFrZ9hO2n5Z0KvAtSQfYfkjS+sCrbP+6l3GeClws6QrgRkql2Hjg6rolcmnYG1il6ftPgR8Dp9Xv5wCfkbQj8AfgQEpy7++tC0naHFiJUr21KmXL6QPtxkZE/xvb0ZGz7SIiIiIiYsCkoquH6vbCicA6fVzieEriZSYlYfWrbsbOA7YBbpA0v46/jVIVBvB74HZguqTGGwoPBu4Crpf0KHAFpYKsV2xPppzTdRIwu665d2/X6eU159ie3vgATwCP2p5b+++gHIp/co3pncA7bD8BIOlySYfU5UYBF1C2K/6bclbXrrUqLyIiIiIiIiKGMNn9vQtt+SRpIeXQ9RNtHz7Q8cTSIWkfyllpqwCb2f53V2PHjRvnyZMnL7PYIpZ3jbO5UtG17OXZR0RERMRwIukm2+Pa9WXrYmV7lcWPiuWd7R8CPxzoOCIiIiIiIiKi/w35rYuSLGm+pKMG4NrbSbpjWV83uiZpUv33wZKS6I2IiIiIiIgYQoZ8oqva0vahAJI2rkmOzvqZIem7klZa0ovUdTdpfLd9je1en5PVw2tNrYezDypNz3fFlvYzJB3Zg/kT6/wdW9pfI+nqpt/sk13M31bSbyU9IulhSRdJenGj3/ZEYPM+3l5EREREREREDGLDJdHVzlq2O4BXA68DPj7A8Qx7kl4G7AY82NK+LuXw/lOAFwKbAL/pYpm1ge9TDqHfiHKwf7YqRkRERERERAwDwznRBYDth4DfAps12iR9QdK/JM2T9DdJ727q20TSVZLmSpop6YLafnUdcmutOnqfpPGS7u/huntLulbSsZJmS7pb0i69vR9JIyQdL2la/RwvaUTtGy/pfkmH1NinStqjZe6xku6tVVMnS1q19v2yqQquU9LTkvbubXyLcRLl7ZFPtLQfBPza9rm2H7c9z/bf2y1g+3LbF9l+1PaCuuYb+jnOiIiIiIiIiBiEhv0ZRZJGAzsDJzQ1/wvYDpgO7A6cI2kT2w8CX6FUE70ZWBkYB2D7TZJM2SZ5V117fMvlulsXYBvgTGBdYD/gNEnru3evxjwU2BYYCxj4OXAY0HiT5H/U9dev4y6TNNn2HcAxwEvr3CeB84AvAV+0/famZ/bfwOnA73oRV7ck7Q48YfsySa3d2wJ/lfRHSjXXDcDHbd/bg6XfBNzel5juWLDgmTeZDVUTRo1iv9GjBzqMiIiIiIiIiH4xnCu6ZkqaAzwAzAd+3OioFUHTbD9t+wLgTmDr2v0kZUvcaNsLbV/b0wsuZl2Ae2yfansRJeH1YmBUL+9rD+DLth+y/TAwCfhgy5jDa2XUVcClwHtVskv7Ap+2/YjtecDRwP82T5S0KXAW8D7b93UTx0xJcxofYEJXAyV11Gt9qoshGwB7AZ8ENgTuBs7v5tqNdbegJOo+t7ixw9EtnZ2cN2PGQIcRERERERER0W+Gc0XXurafqlvzvkw5A+r1AJL2pGyX27iO7aBUQQF8nlLVdaOk2cA3bZ/ekwsuZl0olV4A2F5QK5s6enlfo4F7mr7fU9saZtue36Z/PWAkcFNTRZWAFZriX5NSIXa47WsWE8e6tp9qmntGN2MnAWfbvruL/seAi23/ua41iZJIW9P23HYT6ksBLgc+2YNY2xozciRXbrVVX6YuF4Z6tVpEREREREQMP8O5ogsA248BZwCvk7SupI2AU4EDgBfaXgu4jZL0wfZ02/vaHg18BPhu85sWu7K4dfvRNErFWcOGta1hbUmrtemfSUkobW57rfpZsx7Yj6QXULYy/sH2Kf0c8w7AgZKmS5oOvAS4UNLBtX8KZRtmQ+Pvts+uPusrgK/YPrufY42IiIiIiIiIQWrYJ7rqQe0fpFRTzQJWoyRSHq79+wCvahq/u6QN6tfZdeyi+n0G5Yyrdrpdt49WkrRK02dFypa+wyStV99W+CXgnJZ5kyStLGk7YFfgIttPUxJx35L0ohrj+pJ2rnOOqvfwySWMuZ0dKM9ibP1MoyQRv1P7fwi8W9JYSStRzhu71vac1oUkrQ/8HviO7ZOXQqwRERERERERMUgN50TXHEmdlOTU64B3uPgb8E3gT7Xv1cB1TfNeC9xQ5/6CsjWuseXuCODMei7Ve5sv1oN1++IyShVW43MEcCQwmVIF9VfgL7WtYTolQTcNOBf4qO1/1L6DgbuA6yU9SqmKGlP73k85FH5205sX96Af2J5VK+Wm255OSRzOtt1Z+38PHEI5T+whyoH0z5z5Jen2plg+TEk2Tmx+S2R/xBkRERERERERg5t690K/5Y+khcDjwIm2D1/c+KGsvgXyHNsbLG7sUCVpIuWctBHAavXg/7bGjRvnyZMnL7PYlrXGGV1D+RyyWLby79TAybOPiIiIiOFE0k22x7XrG/KH0dteZaBjiMHD9iTK4fdBefPiYD6UfsKoUew3evTiB0ZEREREREQwvLcuRsQgdktnJ+fNmDHQYURERERERMRyZMhXdMWzbF8JDNtti/F8Yzs6Bu1Wp8FcaRYRERERERGDUyq6IiIiIiIiIiJiSEiiqw1JljRf0lEDHUv0H0k71rcwPi1px4GOJyIiIiIiIiL6VxJdXdvS9qGNL5L+T9I/JM2TNEPSpZJWX1bBSNpZ0tX1+g9LukrSO5ZwzSMkndNfMdY1p7YmkSTtLenaHszdviYZj2xpX0/SeZLmSJot6dxu1thY0h8kLai/1zOx2L7Cdgdwbx9uLSIiIiIiIiIGuSS6ekDS9sDRwPttrw68Eriwj2v1+lw0SbsBFwFnUc7YGgV8CXh7X2LoxXUlaZn8OyJpJeAE4IY23T8FpgMbAS8Cju1mqfOBm4EXAocCP5a0Xv9GGxERERERERGDUQ6j75nXAn+yfTOA7UeAMxudkt4GHAm8DJgLnGb7iNq3MXA38GFgIjAVeJOki4DtgFWBW4GP2b699cKSBBwHfMX2D5q6rqofJL0MOBXYEjDwa+DjtufU/oOBA4E1gGnA/sBKwCH1Eu8C/mV7S0lXAtcB44HXAK+W9CJKEmpT4J/AJ23/sbcPcTE+A/yGkshqvv+dgJcA420vqs1tTymXtGmNeSfbjwE/kfQp4D3Ayb0N6I4FC4b0gei3dHYytqNjoMOIiIiIiIiI6Dep6OqZG4CdJU2S9AZJI1r65wN7AmsBbwM+VpNHzbanVILtXL9fDrycktj5C9DVdrwxlETPj7uJT8BXgdH1Gi8BjgCQNAY4AHhtrUbbGZhq+1eUKrULbHfY3rJpvQ8C+wGrA/OAS4ETKVVSxwGXSnphN/H0iqSNgA8BX27TvS1wB3CmpFmS/lwr7NrZHPi37XlNbbfW9mgxtqODCaNGDXQYEREREREREf0mFV09YPsaSf9DqYT6JLCipO8Dn7O9yPaVTcOnSDqfktj6WVP7EbbnN615euNvSUcAsyWtaXtuy+UbCaUHu4nvLuCu+vVhScdRqscAFgEjgM0kPWx7ag9u+YxGdVmtqLrT9tm173xJB1K2TZ7RxfyfSXqq6fvKlGReV04EDrfdWQrYnmMDYCdKRdw+lOqsn0vaxPbMlrEdlIq6ZnOB9bu5dpfGjBzJlVtt1ZepERHL3C2dnUO6CrUnJowaxX6jRw90GBERERExgJLo6iHblwOX1zOr3kw5M+sO4BRJ2wBfA15FSeqMqP3N7mv8IWkF4Chgd2A94OnatS7PT9TMqv98MWUL5PPUrYUnUrZCrk6p1Jtd476rbt87Athc0q+Bg2xP6+Z272v6ezRwT0v/PXSfPHqX7Sua4tubkqhqF/vbgdVtX9DFWo9RKtBOq99/JOlQ4A3Az1vGdlK2ZzZbg1KVFsuhnvyHe/7DNiKg/P8FkP8/iIiIiBjmkujqJdtPA7+T9HtKYgvgPOAkYBfbCyUdT0laPWdq098TgHcCO1LO7FqTkph6XjkTJZl2H6WSqatD2L9a19/C9qy6bfKkppjPA86TtAZwCnAMZXui2y3W0j6Ncgh8sw2BX3Uxt7d2AMZJml6/rwkskvRq2+8EptDzQ/dvB14qafWm7YtbUn6fGILyH7YRzxrb0TGsq1CHezVbRERERBRJdPWApHdSDo3/NTCHcjj99sCn6pDVgUdqkmtrSiLrN90suTrwOKVaayTlrKy2bFvSQcBpkmYBP6FULr0e2NN24yytucAcSesDn2uKfQyl+uo6YCGlQqpxNtsM4C2SXlATeO1cBnxb0gTKmybfA2wGXNLN/fXG4ZRquIYTKMm1r9TvFwPHStoLOAd4d9P9PIftf0q6BZgo6TBgF2CLGnMshxb3H+75D9uIiIiIiIholsPoe2Y2sC9wJ/AoJeHyDduNA+T3B74saR7wJUpCqDtnUbb/PQD8Dbi+u8G2fwy8j3Jg+zRKgupInt26N4nytsG5lIPjf9o0fQQlkTQTmE45/P6Q2tfYXjlLUtsztGzPAnalvBVxFvB5YNc252P1ie15tqc3PpRE3Pz6ZsvGGy7fAXy23t8XgHc2ri/pZEnNb1T8X2Ac5Tf7GrCb7Yf7I9aIiIiIiIiIGNxS0dXe48BNkk60fbjtqylb7Nqqiai2b0Wsh7+rpa2TsnWx2VndBVTfkth2u2A9OP4/W5q/WfumAFt3MW8W8MaWtvFtxl3bZv2u4ty4TdsZdH1wfevYvdu0XQO8uovxH235PhUY326spB0oFXEjKIf0R0RERERERMQQkkRXG7ZXGegYov/Z/h2w1kDHERERERERERFLR7YuRkRERERERETEkJBEVzckWdJ8SUf1w1obSuqUtEJ/xBZ9I2lS/U0tKRWNEREREREREUNIEl2Lt6XtQwEkbdycIFHxbUn/qG877JLte2132F5U514p6cN9DUrSVEk79nX+0tL6jJraz5B0ZA/mT6zzd2xqe7OkP0iaK2lqD9bYof4mC+q8jRp9ticCm/furiIiIiIiIiJieZBEVx9JEnAK5eDz7W0/MLARLf8kvQzYDXiwpWs+cDrwuR6ssS7lrZOHA+sAk4EL+jfSiIiIiIiIiBiMsnWrb1YATqO8CXB8fXshkt4GHAm8DJgLnGb7iNq3MXA3sBIwCdgO2FbS8cAZtg+Q9HrgBGBT4J/AJ23/sTeBSRoBHAO8tzZdCBxs+3FJ44FzgO8CBwGdwKG2z22ae1SdOwK4GPi07cck/RJ4c9OlRgIfqm9U7C8nAQfX+J5h+0bgxh5WsP0PcLvtiwAkHQHMlPQK2//oTTB3LFjA+Jtv7s2U6Ee3dHYytqNjoMOIiIiIiIiI5UgquvrmXOAVwH81klzVfGBPypv93gZ8TNK7WifXrZDXAAfU7YwHSFoHuBQ4EXghcBxwqaQX9jK2Q4FtgbHAlsDWwGFN/f8BrAusD+wFfF/SmNp3DCXJNhbYpI75Uo357TXWDkrV1XTgd72MrUuSdgeesH3ZEi61OXBr44vt+cC/yHbF5c7Yjg4mjBo10GFERERERETEciQVXX2zEzDJ9pzmRttXNn2dIul8YHvgZz1Y823AnbbPrt/Pl3Qg8HbgjF7EtgfwCdsPQTl8nbLF8vCmMYfbfhy4StKlwHvr+Vn7AlvYfqTOPRo4D/hiY6KkTYGzgPfYvq+bOGaW3Z3PGAl8vd1ASR3A0ZTnuqQ6gIdb2uYCq/d2oTEjR3LlVlv1Q0ixNN3S2ZnKu0EiVXgRERERETHQkujqm12BSyTNtn16o1HSNsDXgFcBK1O2/13UwzVHA/e0tN1DqarqjdZ17qltDbNrlVNr/3qUZNRNTQkqUbZpli/SmsDPKYmyaxYTx7q2n2qae0Y3YycBZ9u+ezFr9kQnsEZL2xrAvH5YOyK6kSq8iIiIiIgYaEl09c0fKZVWl0haaPu82n4e5ZypXWwvrOdvrdvFGm75Pg3YqKVtQ+BXvYytsc7tTWtMa+pfW9JqTcmuDYHbgJnAY8Dm7Q7Wl/QCyv39wfYpvYxpcXYANpC0f/2+HnChpGNsH9PLtW6nbMkEQNJqlDPTbu9yRizXxnZ0pPIuIiIiIiIigJzR1We2r6IcfP59SbvV5tWBR2qSa2tgQjdLzABe2vT9MmBTSRMkrSjpfcBmwCXdrLGSpFWaPisC5wOHSVqvvoHwS5QD6JtNkrSypO0o1WkX2X4aOBX4lqQXAUhaX9LOdc5RwGrAJ7t7Ln20A6UKbmz9TAM+AnynxvECSatQDvJXvdeVu1jrYuBVkt5T53wJmNLbg+gjIiIiIiIiYvmTRNcSsP1b4H3AGZLeDuwPfFnSPEqC5cJupp8A7CZptqQT66H2uwKfAWYBnwd2tT2zmzUuo1RhNT5HUN76OBmYAvwV+Etta5gOzKYkk84FPtqUBDoYuAu4XtKjwBVA46D691MOuZ8tqbN+9uju+fSU7Vm2pzc+wCLKFsvOOuRN9f4uo1SgPQb8pjFf0u2NWGw/DLyHkpibDWwD/G9/xBkRERERERERg5vs1h100SBpIfA4cKLtwxc3frCTNB44x/YGAx3LQJE0ETiIcn7aarYXdTV23Lhxnjx58jKLLXqvcQh9ti7GcJf/LeQZRERERAwnkm6yPa5dX87o6obtVQY6huhftidRDr+PiIiIiIiIiCEmWxcjIiIiIiIiImJISEXXMGL7SmDYbluMiIiIiIiIiKEtFV1LSJIlzZd0VD+stXFdb5kkICVdLmmvHo61pE2WdkxLm6RJ9fdaZs85IiIiIiIiIpaNJLr6x5a2D4XnJKsabyacKukL/X1BSeMl3d+m/UpJH+7JGrZ3sX1mP8fVNlkn6QxJR3Y1r2ncxDp/x6a2EZJOljRD0iOSfilp/S7mbyZpcn2b5WxJV0jarNFveyKw+RLcYkREREREREQMUkl0LT1r2e4AdgMOl/SWgQ5osJP0MsrzerCl65PA64AtgNHAHODbXSwzra6xDrAu8AvgR0sj3oiIiIiIiIgYXLJ1aymzPVnS7cBY4LeSXgAcAuwLrAr8CviE7bmtcyW9B/gmsKvt23p7bUlrA2cD21B+6+uAj9q+v/ZfCZxj+wf1+4eAzwH/AdwI7Gf7njbrvhE4H9jT9h96G1c3TgIOBr7b0v7/gF/bnlGv/yPguHYL2J5DSYQhScAioE9bLu9YsOCZ19XH4HRLZydjOzoGOoyIiIiIiIgYJFLRtZRJ2hZ4FXBXbdq7ft4MvBTooCR4WuftAxwD7NiXJFf1AuCHwEbAhsBj7a5Vr/cuSgLuf4D1gGsoyazWcTvX9vf0Z5JL0u7AE7Yva9N9GvAGSaMljQT2AC5fzHpzgIWUyq+j+yvOGFzGdnQwYdSogQ4jIiIiIiIiBolUdC09MyWNAFahVGX9rLbvARxn+98Akr4I3FYTWw2fAj4EjG9UX3VhdE3oNOsAzgGwPQv4SaOjHpjfVXLqI8BXbf+9jj0aOETSRk1VXbsDHwXeavuv3cQF5f6bv48Evt5uoKQOSjJqpy7W+idwL/AApULrr8AB3V3c9lqSVgP2Ap5XldYTY0aO5MqtturL1IiIiIiIiIgYAKnoWnrWpSSdPguMB1aq7aN5buLlHkrCsbks5XPAdxaT5AKYZnut5g9wbaNT0khJp0i6R9KjwNXAWpJWaLPWRsAJkubU5NkjgIDmQ98/BVzYgyQXwLotcZ3XzdhJwNm27+6i/3uUhOELgdWAn7KYii4A2/OBk4GzJL2oBzFHRERERERExHIsia6lyPYi29+kbKHbvzZPoySVGjYEngJmNLXtBBxWz+haEp8BxgDb2F4DeFNtV5ux9wEfaUmcrWr7j01jdgfeJelTSxhXqx2AAyVNlzQdeAlwoaSDa/+WwBm2H7H9OGU74taS1u3B2i+gVJO1fUtjRERERERERAwdSXQtG18DPi9pFcr5Vp+W9P+atuxdYPuppvG3A/8NfEfSO5bguqtTzuWaI2kdYGI3Y08GvihpcwBJa9Zzs5pN49mk1P6tCyyBHSjnmI2tn2mUrZTfqf1/BvasMa1ESRpOsz2zdSFJb5G0laQVJK1BObR+NvD3fow3IiIiIiIiIgahJLqWjUspyZZ9gdMpb0K8GribUu31idYJtm8FdgVOlbRLH697POXNjjOB6ylveGzL9sWUw+9/VLc53gY877q276Ukpg6W9OE+xtW65izb0xsfyjlcs2131iGfpTynO4GHgbcC727Ml3S7pD3q17UoycS5wL8ob1z8b9sL+yPWiIiIiIiIiBi8ZHugY1iuSVoIPA6caPvwgY6nNyRdDfzA9lkDHcuyImkicBAwAljN9qKuxo4bN86TJ09eZrFFRPTV+JtvBhjWL9DIM4iIiIgYPiTdZHtcu768dXEJ2V5loGPoC0kjgZdSqsqGDduTKIffR0RERERERMQQk62Lw1B9A+F04Cqa3tIYEREREREREbE8S0XXMGT7IWCNgY4jIiIiIiIiIqI/LbaiS5IlzZd0VE8XlTRV0o5LFlr/GowxNUgaL+n+Ps61pE36OZ4jJJ3TTf/tksb35zWXBUkjJHVKelLSkQMdT0RERERERET0r55uXdzS9qHNDZJWq0mDy5ZCXMslSdvVZ9JZk4Nu+t4pacOBjrE/2N7c9pXt+iSd0ZpEkrRxfRZtKwjrnCdantUKtW9dSddJmiVpjqQ/SXpDd/FJ2lHSX+pvcJ+k99a4H7fdAZzbl/uOiIiIiIiIiMFtSc7o2o3ytsGdJL24n+IZdLpKzrRj+xrbHTWZsnltXqvRZvvepRPlkPD1pufU0fQ2xE7gQ8B6wNrAMcAvu0mabQacBxwKrAmMBW5a6tFHRERERERExIBbkjO69gJOBnYB9gCObTdI0guAzwP7AmsBvwM+avsRSd8D1rO9Wx17DDAO2LGOPRvYpsZ5XZ13fx17JXAN8F/AFsCfgAm2Z9b+DwJHAh3Acb2IaWPKmwg/DEwEpgJvkvQh4HPAfwA3AvvZvqenD0vSPvWaGwAPA8fYPqWLsQcCHwV2AkYDJwCvBB4DfgIcZPuJpik7SrocWJeS5DnAtiW9DDgV2BIw8Gvg47bn1OscDBxIOa9rGrC/7d/VNVeWdBbwbuBeYC/bk+u8qcCHbV/R0/vvK9sLgTvqdV8ALKIkvNYBHmoz5TDgFNuX1++z6qfX7liw4JnX1cezJowaxX6jRw90GBERERERERHP06eKrroFbzxlC9i5wJ7dDD8QeBewPSVpMxv4Tu37DLCFpL0lbQf8HyWh4hrbD4GNgA0pSZ6TWtaeAOwDvAhYGfhsjW8z4HvAB+s1X0hJMPUkpobtKcmlnSW9CzgE+B9KZdE1wPnd3HM7DwG7UpJK+wDfkvSa1kGSDgf2BravSb1FwKcpSazXATsA+7dM2xV4LSWh9V5g58ZywFfrPb4SeAlwRL3OGOAA4LW2V69zpjat+Q7gR5RE4C94/rPvb/tLekTSTZLe09opaQqwsMbyg3qgfjvb1vF/lfSgpHMkrbP0wh5elqS7twAAIABJREFUbuns5LwZMwY6jIiIiIiIiIi2+lrRtScwxfbfJM0Bvi5pK9vtyl8+QqkwalRiHQHcK+mDthdI+gDwK2Ae8InGONuzKNVL1HlHAX9oWfuHtv9Z+y+kJGegbKu8xPbVte9wSlJnsTE1jTnC9vza/xHgq7b/Xr8fDRwiaaOeVnXZvrTp61WSfgNsB/zl2VvUccDWwJttz63zmrfdTZV0CiUJd3xT+9dqldYcSX+gbNf7le27gLvqmIfr+hPr90XACGAzSQ/bntoS8rW2L6uBnQ18qif3WX1WUvPzXlxC9URK0nMupYrtAknTbV/XGGB7C0mrUCrMVu5mrQ0oCc6dKFVqZwLfplQd9sqYkSO5cqutejttSEuFW0RERERERAxmfT2ja0/qgd62pwFXUbYytrMRcHE9SHwO8HdKkmVUnX8j8G9K9dGFjUmSRko6RdI9kh4FrgbWahxSXk1v+nsBZZsilAqm+xodNWHVvH2t25iq+1rGn9A0/pEa7/pd3PPzSNpF0vW1amkO8FZKlVbDWsB+lITa3KZ5m0q6RNL0+hyObpkHXTwHSS+S9CNJD9S55zTm1iTYpygVXg/VcaO7WXOVXpxXdqzttRofytbSLtn+i+1Ztp+qybVzKdVzreMW2j4f+IKkLbtY7jFqAtR2J+V5vbWHcUdERERERETEcqzXiS5JrwdeDnyxJl+mU87Ren8XiZD7gF2aEx+2V7H9QF3v45TKommUM6waPgOMAbaxvQbwpkYIPQjzQco2vUbMIynbF3sUU+WW8R9pGb+q7T/2IBYkjaBUpx0LjKrJn8ta7mU2ZQviD1veKvg94B/Ay+tzOISePQMo2xYNbFHnfqB5ru3zbL+Rksgz5aD3wcB0f48rAS/tom8Kz/3tIiIiIiIiImKY6EtF117Ab4HNKFvkxgKvAkZSDqZvdTJwlKSNACStJ+md9e9NKQfGf4Cy3ezzksbWeatTqnPm1DOWJj5v5a79GNhV0hslrQx8mefea5cxdeFkSmJv8zp+TUm79yKelSnJvIeBpyTtQtla9xy2r6RssbtY0ja1eXXgUaBT0iuAj/XiuqtT3lo4R9L6lMP0qfcwRtJ/1STcQsqzXtR+maVL0m6SOiS9QNJOlH8fflH7tm38jpJWrQfojwJu6GK5HwL7SHppTXAeDFyyLO4jIiIiIiIiIgZWrxJd9Yyk9wLftj296XM35Q2J7bYvnkBJWvxG0jzgemCbWv11DuXtg7favpNSrXR2Tb4cD6wKzKxzftXTOG3fDnyc8gbCBynVUvcvLqZu1ruYUu30o7oF8DbaJ/W6mj+PcgD+hTWWCfX67cb+lnJY/S8k/SflgP0JlDPMTgUu6Ol1gUnAayhnX10K/LSpbwTwNcrznU450P+QXqzdnz4JPADMAb4B7FuTflDi/A5l6+kDlG2Ib6tbZpG0h6TbGwvZPh04i5IIuwd4nPLsIyIiIiIiImKIU3nBYTcDpIWUZMGJtg9fJlFFLAU1gTqDsvXx67YndTd+3Lhxnjx58jKJbXkx/uabuaWzk7EdHYsfvIQmjBrFfqNHL35gRDzzoojh/AKNPIOIiIiI4UPSTbbHtetb7OHitlfp/5Ailj3bj1MO/Y9B7pbOToAkuiIiIiIiIqJXevoWvYgIAMZ2dCz1iolGZUZEREREREREb/TlMPrliiRLmi/pqIGOJQaepP+T1Fn/vdhkoOOJiIiIiIiIiP4z5BNd1Za2D21ukLRaTXhctiwDqW8PPELSnTUBN1XS6ZI2XpZxLE3tkkj1ns/pwdy96vwPd9H/+9rfZTWipLdLuq3+vn+UtFmjz/Zptpf+AVMRERERERERscwNl0RXO7tRDtnfSdKLl+F1fwy8g/ImxTWBLYGbgB16u1C7ZE93CaDBTtLawBeB27vo34PFbLeV9HLgXOCjlPO4fkl5g+Vy+1wiIiIiIiIiomeGc6JrL+BkYAqwR3NHrbL6nKQpterqNEmjJF0uaZ6kK2pSBkmXSvr/7N17vKZj2f/xzzdiGmuQTcPYZlvoMRhUTzI9pJRNG20MhZSn+kmKJFKjiHrCk4f2yl5UStkUqlE2xWCIGNlmO41hxqwZgzHf3x/neXNb7rWdNbM2832/XvfLuq/rPM/ruK57/joc53F9psP8WyW9p+MFJe0IvB3Y3fYNtufbnmX7VNun1TH7SbqjXudeSf/dNH+8pIckfVHSY8BPa6XULySdLekpYF9J20i6TtJMSY9KOkXSMnUNSTpJ0r8lzaqxblbPvUrSCZIeqOeulvSqem43SbfXNSdJen2//RIvOg44GXi8xbNbAfgqcFg3a7wD+Ivtq23PB74JrAFs38+xRkRERERERMQgs0RWuUhaGxgPHAg8QUl6fbvDsPdTklJLAzcDWwD7A/8ALgMOAo4GzgAOAf6vrr05JbHSakvkjsD1th/sIrx/A7sA9wJvBS6TdIPtm+r51YCVgHUoicovArsDHwA+CiwLbAJ8DpgMrFnj/TTwv8BOdd2NgFnA64CZde1vA5sCbwYeA7YFFkjaCDgPeA8wqa79W0mb2H62i3vpMUnbAONqnB9sMeQbwPdqXF0uVT8dv28G/KE3MU2dOzdN0TuY0t7O2Lbs/IyIiIiIiIjBaUmt6PoocKvtf1ASOJtK6vgauf+zPc32w8BfgL/Zvtn2M8CvKIkvgIuADeuWOYCPAOd3kgBaGXi0q8BsX2L7HhdXAZcD2zUNWQB81fYztp+ux66z/WvbC2w/bftG23+tFWP3Az/gxYqm54BRlASXbN9h+1FJrwA+BnzW9sO2n7d9bb3fDwGX2L7C9nOUhNirKAmxztxUq79mSpoJHN7ZQElLAd8FPmN7QYvz44D/pCYTu3EFsH2tflsGOAJYBhjZg7nRjbFtbUwYPXqgw4iIiIiIiIhoaYms6KIkun4EYPsRSVdRqrqay3emNf39dIvvbXX+M5IuAPaWdDSwJ6X/VyszKJVUnZK0M2WL3kaURORI4O9NQ6bbntdh2ksqxGoF1omUCqmRlN/5xhrvHyWdApwKrC3pV8ChwIj6uadFWGOABxpfbC+Q9CClcq0zW9q+uymmiUBnbzn8NCXxeF3HEzUB911KAm6+pJdNbmb7Tkn7AKcAqwNnU6rwHupyYgsbjxzJpC065j8jIiIiIiIiYrBa4iq6JL0Z2BD4kqTHaq+rbYE9F6Jh+RmUPl87AHNbJWyqK4FtJK3ZSWzLAr+kVEyNtr0iZQtkc3bHLaZ2PPY94E5gQ9vLU6qaXljD9sm2t6JsU9wI+AKlL9Y8YP0W6z9C2SrZiFPAWsDDndxnb+0AvLfp93gzcEJNyC1PSdidX8/dUOc8JGm7VovZ/oXtzWyvTEkartM0LyIiIiIiIiKGqSUu0UWp3LqC0sdqbP1sRql82rkvC9bE1gLgBOCsLsZdWa/9K0lbSVpa0ihJn5T0McoWu2WB6cD8Wt21Ux9CGgU8BbRLeh3wqcYJSVtL2lbSK4E5lOTW83XL4E+AEyWNkbSUpDfV5NsFwLsl7VDnHUJ5Y+W1fYitlX2B1/Pi7zGZ0v/sSEofsTFN595V52wF/K3VYvXZLiVpVcq2zd/avrOfYo2IiIiIiIiIQWqJSnRJGkFpdP5/th9r+txHSVDtsxDLnwm8gbJVrit7UKq0zqckcW6jVCxdaXs2pcn9BcCTwATgN32I5dA6dzZli+b5TeeWr8eepGxHnMGLjfgPpWyTvIHSpP+bwCtsTwX2pvTIehzYFdi1vxrR257Z/HsAzwJP1TdSusO56XXatMb169swj2ha8juUBvtT638/0R9xRkRERERERMTgJrvVTrjhQ9I8SvXRybaPWoTX+ShwgO23LKprxMKTtB9wEqUf2Sa27+1s7Lhx4zx58uTFFlu8aPzNNw/YGx4njB7NAWPGLPbrRiyMxhtil+S+gnkGEREREUsOSTfaHtfq3LBvRm97xKK+hqSRlIbq313U14qFY/unwE8HOo4YnKa0twMk0RURERERETFEDftE16Im6R3AhZRG8+cOcDgRw8bYtrbFXpnRqAiJiIiIiIiIoSmJroVk+/fAcgMdR0RERERERETEkm7IN6OXZElzJB070LE0SNpL0uUDHceiIul0SccMdBx9IemPkuZJunqgY4mIiIiIiIiI/jXkE13V5raPBJC0bk1+DVi1mu1zbO/Ul7mS7pf0tKTZkmZKulbSJyUNid9K0r6tkkj1vnbsYs7zktqbPuNbjNuwJqm6fLOlpPUkXVyf4eOSvtU4Z/u/gE/2/s4iIiIiIiIiYrAbEsmTJdCutkcB6wDHA18ETuvLQgOZ8Oul62y3NX0mtRhzKnBDV4tIWga4AvgjsBqwJtBlYiwiIiIiIiIihoehkgTpM0krA6cD2wNTgd8D422/pZ438CngEGAVSkP5A21b0vrAj4DNAde5/8/2zDp3LeA7wHaUpOF5tg+UtC/w8aZrvLmO2wi4C/is7Wu7i932LOA3kh4D/irpBNu3SZoEnG37x3X9jtczcCBwMOU3fq2k7wDvA1YA/gkcbPsvdfxEYBNgHvBe4F/APrYn1/NbUBJtGwKX1mexWEn6MDATuBbYoIuh+wKP2D6x6ditfbnm1LlzB6w5+YTRo/Pmv4iIiIiIiIheWhIquk4F5lCqe/apn452AbamJLQ+CLyjHhdwHDAGeD2wFjARQNJSwMXAA8C6wBrAzzouLGkl4BLgZGBl4ETgkpqA6xHb1wMPURJqPfUeYFtKAgtKJdRYYCVKMu/nkkY0jd+txr8i8BvglBr/MsCvgbPq3J8D7+9FHD21Rd1meJeko5or0SQtD3yNkozszhuB+yVdVtebJOkNiyDeRWZKezvnTps20GFEREREREREDDnDuqKrJqPeD2xmey7wD0lnAOM7DD2+VmnNlPQnSkLod7bvBu6uY6ZLOhH4av2+DSUB9gXb8+uxVg3O3w380/ZZ9ft5kg4CdqVUmvXUI5REU08dZ/uJxhfbzdv3TpD0ZWBj4JZ67GrblwJIOotSDQYlcfRK4H9tG/iFpM93c+03SprZ4djyXYz/M7AZJWm4KXA+MJ+SZAT4OnCa7QcldXNp1gTeRknc/QH4LHCRpNfZfra7yc02HjmSSVts0Zsp/WKgqsgiIiIiIiIihrrhXtG1KiWZ92DTsQdbjHus6e+5QBuApNdI+pmkhyU9Ren1tEodtxbwQFOSqzNjKAmcZg9QKsB6Yw3giW5Hvegl9ynpEEl3SJpVk1Ar8OK9wMufwYhaVTUGeLgmuRo63k9Hf7W9YvOHsh2yJdv32r7P9gLbf6dUb+1R4x4L7Aic1M01G56mJO0uq4mtb1Mq6V7fw/kRERERERERMUQN90TXdEpl0JpNx9bqxfzjKP2o/sP28sDelO2MUBJJa/eg2fsjlKbyzdYGHu5pEJK2piS6GhVjc4CRTUNWazHthcSUpO0oDe0/CLy6Jp5m8eK9dOVRYA29tJRq7Z7G3kfmxdjGU7aG/qv2KjsUeL+kmzqZeysD0EMsIiIiIiIiIgbesE502X4euBCYKGmkpNcBH+3FEqOAdsqWxjWALzSdu56SBDpe0nKSRkj6zxZrXApsJGmCpKUlfYjSN+vi7i4uaXlJu1B6Z51dq50ApgDvq/e0AbB/D+5jPiXxt7Skr9D1VsJm19W5B9X430fZttlvJO0saXT9+3XAUcBF9fQPgfUp20nHAt+n9Dx7R4uloFTdvVHSjnXr6sHA48Ad/RlzRERERERERAw+wzrRVR1I2ab3GKWh+nnAMz2cezSwJaX66RJK0gx4IYm2K+UNgP+iNIv/UMcFbM+gNLs/BJgBHAbsYvvxLq77W0mzKVVjR1Ia2O/XdP4k4FlgGnAGcE439/F74DLKGx8foLxdsdUWzpep2//eR3mb4ZOUe7ywqzl9sANwq6Q5lMTghcA36vXn2n6s8aEkHufZng4gaW1J7ZLWruOnUirvvl/j3R3Yrbf9uSIiIiIiIiJi6NFLWy8NPZLmURJXJ9s+qgfjvwmsZrvV2xdjmJN0BaXB/vW2d+hq7Lhx4zx58uTFE1iT8TffzJT2dsa2tS32aw8Wjftf3C8DaLwIYCBeQhCxMPJvN88gIiIiYkki6Ubb41qdG/JvXbQ9oqvzdSvcMsDfga0p2/w+vhhCi0HI9tsHOobo3ti2NiaMHj3QYURERERERMQQM+QTXT0wirJdcQzwb+AEXuz/FDEoDUQ1U0RERERERMRQN+wTXbZvoPTRioiIiIiIiIiIYWzYNqOXZElzJB070LHE4CFp/9q83vWNlRERERERERExTAzbRFe1ue0jASStW5MbL6lik3S6pGMWV0CSlpE0UdI/ayLufkk/kbTu4ophUWuVRKr3fHY3c+bUJFS7pB83ndtH0o2SnpL0kKRvdfwde7qW7dNsL7ld3iMiIiIiIiKGseGe6FqkJC3Vh2m/AHYDJgArAJsDNwJdvgGwk+u/LNnTVQJoCNjcdlv9NL8wYCRwMLAKsC3lWR3ax7UiIiIiIiIiYpgaykmRRULSz4HtgFcBtwCfsn17PXc68DSwDrA9sLukLwNn2/5xHbMv8HHbb2mx9o7A24GNbD9YD88CTm0asx9wGLAmMB34pu0f1HPjgbOB/wM+B1wh6R5gM2AeJYH2eUm3At8BXl/j/SXwedvPShJwIrAXsCzwADDB9m2SXgUcA+wBrEh5U+XbbT8taTfgOGANYEp9Lnf05Rn3lu3vNX19WNI5wNsW9XWnzp37wuvqF6cp7e2MbUvR2UCZ0t4+IL97f5swejQHjBkz0GFEREREREQsVqnoernLgA2B1wA3Aed0OD8BOJbyNsere7n2jsD1TUmuVv4N7AIsD+wHnCRpy6bzqwErUZJtB9Rju1MqxVas8T5PSYStAryJUgH16Tp2J+CtwEZ1/IeAGfXct4GtgDfXaxwGLJC0EeXNlQcDqwKXAr+VtEwv7787f5b0mKQLu9nK+Vbg9n5aa9AZ29bGhNGjBzqMGMKmtLdz7rRpAx1GRERERETEYrckVnQ9XoqaXjAS+Fbji+2fNP6WNBF4UtIKtmfVwxfZvqb+Pa/DWt1ZGXi0qwG2L2n6epWkyykVZjfVYwuAr9p+psYIcJ3tX9fzT1O2QjbcL+kHlAq0/wWeoyTpXkdJut1R13kF8DHgjbYfrnOvrec+BFxi+4r6/dvAZykJsUmd3MpNkhY0fR9BScZ1Znvgr5Tf4xjgYkljbc9vHlQr3sYBXW1H7NFa3dl45EgmbbFFb6bEMDC2rW3I/+7DoSItIiIiIiKiL5bEiq5VbK/Y+ADnNk5IWkrS8ZLukfQUcH9jTtP8rqqxujMDWL2rAZJ2lvRXSU9Imgm8q8P1p9ue12HaS2KStJGki2tF01PANxpr2P4jcAplu+Q0ST+UtHw9PwK4p0VYYyhbHKlrLKjXXKOLW9myw3M+vqv7tv1n28/anklJor2WsvWy+b7eU9fZ2fbjC7NWRERERERERAw/S2KiqysTKNsAd6Q0il+3Hm8u23KHOXMolUMNq3Wx/pXANpLWbHVS0rKUflrfBkbXBNGl3Vy/1bHvAXcCG9peHjiieQ3bJ9veCtiUsoXxC8DjlD5f67dY/xHKVslGnALWAh5uMba/uDlmSe8EfgTsavvvC7NWRERERERERAxPSXS91CjgGUrl1UhKJVR3pgDvkzRS0gbA/p0NtH0lcAXwK0lbSVpa0ihJn5T0MWAZSoP46cB8STtTemr15T6eAtolvQ74VOOEpK0lbSvplZQk3Tzg+Vql9RPgREljanXbm2ry7QLg3ZJ2qPMOoTyna/sQ28tI2lTS2HrNNuAEShKtsa3yvyi9x95v+/qFWSsiIiIiIiIihq8kul7qTMoWvYeBf1D6PHXnJOBZYBpwBi9vXt/RHpQqrfMpb1y8jdJz6krbs4GDKImlJykVZr/p9V3AoXXubEoV1PlN55avx56k3OsMSgVZY97fgRuAJ4BvAq+wPRXYm/K2x8eBXSmVVc/2IbZWRtcYnwLupVTS7WL7uXr+KEqF3aWS2uvnssZkSZdJOqKHa0VERERERETEMCW71U64oU/SPErV0cm2jxroeGJwqM3sT6L0I9vE9r2djR03bpwnT5682GKLgddo4j5cmtEP9fuInstvnmcQERERsSSRdKPtca3ODdu3LtoeMdAxxOBj+6fATwc6joiIiIiIiIjof9m6GBERERERERERw0ISXRERERERERERMSwk0QVIsqQ5ko7txZzbJY1fhGENWpLGS3pooOPoC0n712b2rm/JjIiIiIiIiIhhIomuF21u+0gASevWREjjDX/3Szq8ebDtTW1P6u8gJE2U9Jyk2fVzl6RTJK3e39daVFolkep9nd3FnKUkHSPpkXrfN0tasen85yQ9JmmWpJ9IWraTdTaSdJGk6ZKekPR7SRs3zts+zXZbf9xnRERERERERAwuSXR1bcWaFNkDOErS2xfTdc+3PQpYCXgvsBpwY1+TXZKW6s/gFpGjgTcDbwKWBz4CzAOQ9A7gcGAHYF1gvTq+lRWB3wAbA6OB64GLFmHcERERERERETFIDNu3LvYn25Ml3Q6MBa4AkHQ/8HHbV0qaCGxCScy8F/gXsI/tyXXs4cAngNcADwJH2v5VD677HHC7pA8BNwGHAIdK2rde+y2NsZIMbGj7bkmnA08D6wDbA7vXCqhjgPWBWcBptifWuesC9wH7Al8HRgIn2T62nn8V8D1gd+BR+vmthZJeDRxMqap7oB6+rWnIPjXe2+v4rwPnUJJfL2H7ekpyq7H2ScCXJa1se0Zv4po6d+4Lr6sfaBNGj+aAMWMGOoyIiIiIiIiIQS0VXT0g6Y3AZsDdXQzbDfgZL1YUndJ07h5gO2AFSiXS2b2pzrL9PKUqabtehD0BOBYYBVwNzAE+WuN7N/ApSe/pMOctlEqoHYCvSHp9Pf5VSoJsfeAdlMRTf3oDMB/Yo25PvEvS/2s6vylwS9P3W4DRklbuwdpvBR7rbZJrMJnS3s6506YNdBgRERERERERg14qurr2eK2EGgGcAPy6i7FX274UQNJZlAolAGz/vGnc+ZK+BGxD77bUPULZythTF9m+pv49D5jUdO5WSedRqr2a7+lo208Dt0i6BdgcuAP4IPBp208AT0g6GfhKN9e/SdKCpu8jgF90MnZNShJwI+C1wIbAHyTdZfsKoI1ShdbQ+HsU0GkCS9KawKnA57uJtaWNR45k0hZb9GVqvxosVWURERERERERg10qurq2CiXJcigwHnhlF2Mfa/p7LjBC0tIAkj4qaYqkmZJmUqrDVullLGsAT/Ri/IPNXyRtK+lPtUn7LOCTLWLoeA+Npu1jOqz3AN3b0vaKjQ9wfBdjn67//Zrtp23fSqmOe1c93k7p29XQ+Ht2ZwtKWhW4HPiu7fN6EG9EREREREREDHFJdHXD9vO2T6BURX26t/MlrQP8CDgQWLkmfW4D1Is1XgHsCvylHppD6aPVOL9aq9A7fD+XsqVyLdsrAN/vRQyPAms1fV+7h/N66tb6344xN9xOqS5r2ByY1tl2xNrz63LgN40+YxEREREREREx/CXR1XPHA4dJGtHLectREjjTASTtR6no6pakV9Y+WedR3rx4Yj11C7CppLE1nok9WG4U8ITteZK2ofTw6qkLgC9JenXdDviZXsztlu17KEm8IyUtW+/5Q8DFdciZwP6SNqlJrC8Dp7daS9LywO+Ba2y/rFl9RERERERERAxfSXT13CXAk5S3J/aY7X9Q+ntdB0yjNF6/pstJ8CFJ7cBMShXWDGAr24/UNe8CvgZcCfyT0my+O58GviZpNqW/1gW9uI2jKdsV76NUSp3Vi7k9tSflLZEzKM/6KNt/ALD9O+BbwJ9qHA9QGuQDIOkySUfUr+8Ftgb2k9Te9OnvKrSIiIiIiIiIGGRkd7ZbbMkhaR7wDHCy7aMGOp5YdGpF3UmU5vib2L63s7Hjxo3z5MmTF1tsnRl/881MaW9nbFtb94NjoTSe82B4CcHCWJh/MxNGj+aAMWMWQVSxKDVeWjHU/+0ujDyDiIiIiCWHpBttj2t1Lm9dBGz3djtiDFG2fwr8dKDjiMFpbFsbE0aPHugwBsyU9naAJLoiIiIiImLISqIrYggYDlVGsXj15d9MoyImIiIiIiJiqEqProiIiIiIiIiIGBaWiESXJEuaI+nYXsy5XdL4+vdESWcvsgBjsZF0uqSnJT000LFERERERERERP9aIhJd1ea2jwSQtG5NfjXeyHe/pMObB9ve1Pak/g5C0uqSTpP0qKTZku6UdLSk5fr7WgNB0vhWSSRJkyR9vIs5Czq8JXGfpvNrSLpI0hOSHpL0yW5iWFXSuZJmSnpS0jmNc7b3BXbu+x1GRERERERExGC1pPfoWtH2fEnjgKtq1/4rFtXFJK0EXAdcC7zJ9v2S1gIOBdYHbu3lekvbnt/0XZQ3aS7ox7AXl0dsr9nJubOBW4A9gE2AP0maavtPnYy/ELgBWAeYC2zWl4Cmzp07KHoW5Y2LERERERERET2zJFV0dcr2ZOB2YGzjWK3y2rHjWEmvlHSepF9KWqZWhm3QdP50Scd0cqnPA7OBvW3fX6/9oO3P2r61zv+OpAclPSXpRknbNa09UdIvJJ0t6Slg31opdaykayhJnfUk7Sfpjloxdq+k/25aYxVJF9dqpyck/UXSK+q5tSRdKGm6pBmSTqnHXyHpy5IekPRvSWdKWqGPj7tXJLUB44FjbT9n+xbgF8DHOhm/E7AW8AXbs+qcgc9WLYQl/U2AERERERERET21pFd0ASDpjZSqn+O6GfcqSpJlOiVZ9XwpouqxHYELu6m4ugH4GjAL+Czwc0nr2p5Xz+8OfAD4KLAssDfwEcp2vKmAgI2BXYB7gbcCl0m6wfZNwCHAQ8Cqdb03Apa0FHAx8Me63vPAuDpm3/q8SiwLAAAgAElEQVR5G/Bv4EzglDquv7xG0jRKsu7XwJdtz6n3Q9N/G393VqX1RspzOEPSzpRncKjtq3ob0MYjR+ZNhxERERERERFDyJJe0fW4pKcp2wm/S0mwdGZ54HfAPcB+tp/vw/VWBh7taoDts23PsD3f9gmUZNbGTUOus/1r2wtsP12PnW779jrnOduX2L7HxVXA5UCjMuw5YHVgnTr2L7YNbAOMoVRCzbE9z/bVdc5ewIm277XdDnwJ+LCkzhKlY2rF2Asf4C1d3PadlGq61YH/ArYCTqzPYzZwDXCUpBGStgTeD4zsZK01gZ2APwGrAScAF0lapYvrR0RERERERMQwsKQnulYB2ig9ssYDr+xi7BuB/wCOr4mhvphBSeZ0StIhddvhrJogWqHG2fBgi2kvOSZpZ0l/rVsTZwLvalrjf4C7gcvrtsZGE/61gAeae341GQM80PT9AUo1YGf76R6xvWLzB7i6k7HYfsz2P2ry7j7gMEo/roa9gNfW+/wecA6lKq2Vp4H7bZ9WE3k/q/P+s7PrR0RERERERMTwsKQnurD9fK2cmgd8uouhl1O2Nv5BUnOCZy4vrS5arYs1rgTe2+iJ1VHtx/VF4IPAq2uCaBYv3bbXKsn2wjFJywK/BL4NjK5rXNpYw/Zs24fYXg/YFfi8pB0oyaC1O6nSeoTS2L1hbWA+MK2Le10YpumebT9gexfbq9rellIZd30nc2+l9TOKiIiIiIiIiGFuiU90NTkeOEzSiM4G2P4WcC4l2dWokJoCTJC0lKR3Att3cY0TKVsgz5C0DoCkNSSdKOk/gFGUBNJ0YGlJX6nje2MZynbH6cD82qdqp8ZJSbtI2qC+ofEpSi+u5ymJo0eB4yUtV7cJNqqgzgM+J+m1tTn8N4DzO6n+6jVJ4yWtrWItym9xUdP510saVZv/713v58ROlvsV8GpJ+9TfZA9gDcr2x4iIiIiIiIgYxpLoetElwJPAJ7oaZPvrlF5eV0paidIwfldgJmWLXad9vmw/AbyZ0ifrb5JmA3+gVG3dDfweuAy4i7I9cB6ttyp2Fd9s4CDggno/E4DfNA3ZkFJZ1k7tTWZ7Uu05tiuwAfAvytbAD9U5PwHOAv4M3Ffj+kxv4urGljWWOcC1wG31HhreQWkq/yTwSeCdtqc3Tkpqb7ydsj7j3SjbUWcBhwO72368H+ONiIiIiIiIiEFIfW83NXRImgc8A5xs+6iBjicGjqTTKG+t/LftDboaO27cOE+ePHnxBBbRj8bffDNAr98a2td5MfDy2+UZRERERCxJJN1oe1yrc529NW9Ysd3pdsRYstjeH9h/oOOIiIiIiIiIiP63RCS6IiIiYvib0t7+QmXXYDBh9GgOGDNmoMOIiIiIWKIMiR5dkixpjqRjBzqWGNoknS7paUkPDXQsERExfE1pb+fcaYvq5cQRERER0ZmhVNG1ue27ASStS2mKPqeeexz4vu3jF2UAkiYCG9jeeyHWWB04BngX0AY8DJwPfMv2nK7mDgWSxgNn216zw/FJ9fiPO5m3KvAdynMxcKntveq5bwO7A6tRntc3bJ/ZRQyfAT4PrExp7H+w7asBbO8r6XTg7L7fZUREDEZj29oGTY+uwVRZFhEREbEkGRIVXV1Y0XYbsAdwlKS3D3RAXalvabwOeBXwJtujgLcDKwLr92G9pTt8l6Sh+pteCDwGrAO8Bvh207k5lDdCrgDsA3xH0ptbLSJpW+B4yr+JFYDTgF9JWmrRhR4RERERERERg8FQqujqlO3Jkm4Hxkr6O3AvsJbtGQCStgJ+B4wBngeOAD5BSTj9DviM7VmtqpEk3Q98nPKsjiiH9B7gHtubS9oPOAxYE5gOfNP2DzoJ9fPAbGBv2wtq7A8Cn2263neA91GSNP+kVCP9pZ6bCGwGzAN2Az4vaW/gGmA8sCXwBknbdRaTpFWA04G3AAuA24HtbS+QtBalqmo7ShL0PNsH1uRZy2fW9S/TM5J2AtYCxtt+vh5+4X+F2/5q0/C/SfoL8Cbg2hbLrQvcbvvGuvaZwHcpybNHexPX1Llz83/kY0ia0t7O2La2Ps/Nv/uhZ2F+84iIiIiI4WSoVv+8hKQ3UhJAd9t+DJgEfLBpyN7Az2w/B+xbP28D1qNsHzylu2vY/h3wDeB82222N6+n/g3sAiwP7AecJGnLTpbZEbiwkeTqxA3AWGAl4Fzg55Ka3xq5O/ALShXYOfXYR4ADgFHAA93EdAjwELAqMJqSwHKteLq4zl8XWAP4WZ2zL314Zr3wRmAqcIakGZJukLR9q4GSXgVsTUnQtXIZsJSkbes9fQyYQqkWi1gijG1rY8Lo0QMdRixG+c0jIiIiIoqhXtH1uKRlgRHACcCv6/EzgIOA79Vkx56UCiiAvYATbd8LIOlLwG21MqvXbF/S9PUqSZdTKqJuajF8ZbqpKrLd3DvqBElfBjYGbqnHrrPduM+nJQGcbrs58dNVTM8BqwPr1J5njWqxbSgVb1+wPb/Ovbr+t9Nn1jS22RhJMzsca6PzvlhrAjtRKuf2A94PXCRpA9uPdxj7/fosft/JWrOBX9bYBcwEdrbtTsZ3auORIwdNr5eIxWUw9TiKiIiIiIjoraFe0bUKJYFyKGXr3ivr8YuATSStR+mBNcv29fXcGErVUsMDlIRfn/5XuKSdJf1V0hM1ufOuGlcrMyhJpq7WO0TSHZJm1fVW6LDegy2mveRYNzH9D3A3cLmkeyUdXo+vBTzQWeKK3j2zR2yv2PzhxaRZK08D99s+zfZztn9W7+k/O9zX/1Aq9z7YReLq45Qqrk2BZSjVfBdLyvvdIyIiIiIiIoa5oZ7owvbztk+g9K36dD02D7iAUon0EeCspimPUBqeN6wNzAemUZqej2ycqNVgqzZfrvnatZrsl5TG6aNrQudSSiVRK1cC7+2sYXztrfVFyrbLV9f1ZnVYr1WC54Vj3cVke7btQ2yvR2nw/nlJO1ASS2t3bHBfdfXM+sOttL6vF0g6GtgZ2Mn2U10M3Rz4re27bC+oW04fBVo2r4+IiIiIiIiI4WPIJ7qaHA8c1tTP6kxKX6ndeOmWufOAz0l6raQ2Xuy7NR+4Cxgh6d2SXgl8GVi2ae40YN2mRNUy9fx0YL6knSlb8DpzIqVv1hmS1gGQtIakEyX9B6XH1vy63tKSvlLH90aXMUnaRdIGKnsen6I0538euJ6SEDpe0nKSRkhqVFR19cz6w6+AV0vaR9JSkvag9Ai7psb8JWAC8PbGCwa6cAPwbknr1bdQvh3YCLitn2KNiIiIiIiIiEFqOCW6LgGepLwZENvXUN4qeJPt+5vG/YRS4fVn4D5KJdhn6pxZlKqwHwMPUyq8Hmqa+/P63xmSbrI9m9IL7IJ67QnAbzoL0PYTlMqi5yhvD5wN/IFStXU3pe/UZZSE2wM1tlZbFTvVg5g2pFSWtQPXAd+1Pam+7XBXYAPgX/W+P1TndPrM+kN9LrtRtqDOAg4Hdm/qz/UNShXZPyW1188Rjfn1+3b165mUJvqTKIm8k4H/tn1nf8UbEREREREREYOT+tCje7GTNA94BjjZ9lG9mPdH4FzbP15kwcWQIuk04APAv21v0NXYcePGefLkyYsnsIhBYPzNNwOkGX0MSYPt3+9giyciIiJiOJF0o+1xrc4Nibcu2h7R/aiXkrQ1sCWwe/9HFEOV7f2B/Qc6joiIiIiIiIjof8Np6+ILJJ1B2Z53cN3KFxERERERERERw9ygTHRJsqQ5ko7ty3zb+9hewfbpktat6w2J6rWBsCQ9I0n3SHpW0tndj46IiIiIiIiIoWRQJrqqzW0f2fgiaX9Jd0qaLWmapEskjRrIALsjaWJNIB3U4fjB9fjEHq7zDkl/rvc+XdJVknZbiLjul7RjX+d3s/bEVkmker8te2LVOc81NZpvl7RehzGflXRfTYDeIWmjTtZaUdIZkv5dPxObz9ten9LcPiIiIiIiIiKGmcGc6HqBpO0pyYk9bY8CXk95q+DijKGv1U53Aft0OPbRerwn192D8rbHM4E1gdHAVyhvSOyVQV6xdb7ttqbPvY0Tkj5O6av1bqAN2AV4vJN1TgJGAusC2wAfkbTfIo08IiIiIiIiIgaFIZHoArYGrrN9M4DtJ2yf0ei/Jendkm6W9JSkB7uqlJL0/lrRtJmk0yUd03RuvKSHmr7fL+mLkm4F5khaWtLhdfvbbEn/kPTebmK/ARgpadO65qbAq+rx5rh2lzSl3sM9kt4pScCJwNdt/9j2LNsLbF9l+xN13vqS/ihphqTHJZ0jacUu7uE8YG3gt7Vy6rCmMPaS9K+6zpF1/mqS5kpauWnNrWpl2Su7ufeFJukVwFeBz9n+h4t7bD/RyZRdgW/Znmv7fuA04GOLOs6IiIiIiIiIGHiDucKn2d+Ar0s6GrgcmGz7mabzcyhVUrcDmwFXSJpi+9fNi9TKniOBHW3fXfJI3dqTUkn0uO35ku4BtgMeAz4AnC1pA9uPdrHGWTW+L1Kqu84ENm2Ka5t6bA/gD8DqwChgY2At4BddrC3gOODPwPLAL4GJwMGd3MPTkt4EfNz2lfX669Zxb6nX3Ai4XtKFtu+QNAn4IPC9Om5v4Ge2n+sirt7aVdITwKPAKbYb11qzfjaTdDown/Ksjra9oJO11OHvzfoS0NS5c194PXwMPRNGj+aAMWMGOoyIiIiIiIhYjIZERZftvwDvA7YELgFmSDpR0lL1/CTbf6/VTrcC5wHbd1jmYOALwHjbd/fi8ifbftD20/VaP7f9SL3W+cA/KVvkunI2sGetgPpw/d5sf+Antq+o6z5s+06gUUXVaRLN9t113jO2p1MqwDre+0vuoQtH237a9i3ALcDm9fgZlOQW9ZnvSUnedeaDkmY2f7q57gWU7airAp8AviJpz3puzfrfnYA3AG+r19+/k7V+BxwuaVTtCfYxylbGWIJMaW/n3GnTBjqMiIiIiIiIWMyGSkUXti8DLqtb2d5G6Vs1FfiBpG2B4ymVO8sAy9bzzb4AfM32Q/TOg81fJH0U+DylBxSUnlGrdBP7vyTdTekz9k/bD3aoJlsLuLTF1Bn1v6sD97VaW9JrgJMpVWajKMnLJ7u6hy481vT3XMq9AVwEfL82iN8ImGX7+i7WucD23h3idGeDbf+j6eu1kr5DqW47D2gk575leyYwU9IPgHcBP2qx3EHA/1ESkDPqGnu2GNetjUeOZNIWW/RlagywVOJFREREREQsmYZERVezWvH0B+CPvLgl7VzgN8BatlcAvs9Lt69BqQj6sqT3Nx2bw0urfVZrdcnGH5LWoSRXDgRWtr0icFuLa7VyJnBI/W9HDwLrtzg+tZ57f4tzDcfVGP/D9vKUyquO8XRMMnWadGrF9jxK1dVewEfoupqrP5gX72Eq8Cw9jLn2b9vL9mq2N6X8G+8qKRcRERERERERw8SQSHTVRu0flvRqFdtQtuf9tQ4ZBTxhe149N6HFMrcD7wROlbRbPTYFeJeklSStxkv7WrWyHCXhMr3GtR897/90PiXZ1uptkacB+0naQdIrJK0h6XW2TakeO0rSfpKWr+ffIumHTffeTql0WoNSudadacB6PYy74UxgX2A3Xr71cqHU37f5tz2IUkWG7bmUZ3dY3Y64JmV748WdrLW+pJUlLSVpZ+AA4JhWYyMiIiIiIiJieBkSiS7KVrxPULajPUVJtPyP7XPq+U8DX5M0G/gKrZNJ1N5TuwA/qkmQsyi9qO6nNLk/v6sg6ha7E4DrKMmiNwDX9OQGau+rK1v1yarbAPcDTgJmAVcB69RzvwA+ROk19Ui97jHURBBwNKV32SxK/7ILexDOcZTqtpmSDu1h/NcAC4Cb6tsM+9OHgbuB2ZSE2jdtn9F0/kBKMu8RyrM/F/gJgKTtJLU3jd0K+Htd6zhgL9u393O8ERERERERETEIqRQNDS6S5gHPUJqoHzXQ8UQh6Y/AubZ/PNCx9JWkqcAalD5iH+tq7Lhx4zx58uTFE1j0q0aPrvRY6508txjKBtu/38EWT0RERMRwIulG2+NanRuUzehtjxjoGOKlJG1NqRzbfaBjWRi2Nx7oGGLxmNLenqb0vTSlvZ2xbW3dD4yIiIiIiBikhsrWxRhAks4ArgQOtj17oOOJiEVjbFsbE0aPHugwIiIiIiIi+mxQVnTF4GJ7n4GOIaK3xra1ZctQRERERETEEiYVXRERERERERERMSwMyUSXJEuaI+nYPsy9XdL4RRDTJEkf7+91ByNJ+0q6eqDj6AtJR9d/O5aUisaIiIiIiIiIYWRIJrqqzW0fCSBp3Zq4uKl5gKRVJD0r6f7GMdub2p5Uz0+UdPbiDLo7kk6vMc+un9skHSdphYGOrSeafoulOxw/XdIx3cxpb/oc1XR+oqTnOpxfr4sYPi7p7jrud5LGNM7Z/iqwaT/cakREREREREQMMkM50dXKcpI2a/o+AbhvoIJZCN+yPQpYFdgPeCNwjaTleruQiqHyO69ou61+vt7h3PlN59ps39tqAUnbA9+gvB1yJcrvf96iDTsiIiIiIiIiBoPhtnXrLGAf4Av1+0eBM4FPNAbU6q6PU+79iHJI7wHusb25pH2Br1CSTI8DX7Z9jqSJwAa2967rrEtJorzS9vzmICStDvy+XnsycLbtNTvGYPvKrm7G9jzgBkm7AXdRkl6ndBeLpEnANcB4YEvgDZK2Aw4D1gSmA9+0/YM6fzxwNnAS8EXgeeAI2z+t51cGflrXu7Pe22C1K/Bz27cDSPo68LCk9W3f05uFps6dy/ibb14UMcYiNqW9nbFtbQMdRkRERERERCxmQ6XSp6fOBj4saSlJrwdGAX9rNdD27yiVP41Koc1rxdTJwM61ourNwJTeBFCTTlcBp9j+dp/v5KWxzgauALbrxbSPAAdQnsEDwL+BXYDlKQmzkyRt2TR+NWAFYA1gf+BUSa+u504F5gGrAx+rn0XhAUkPSfqppFU6nNtV0hO1x9qnulhD9dP8HWCzFmNjmBrb1saE0aMHOoyIiIiIiIhYzIZbRddDwFRgR+BtlIqq3loAbCbpX7YfBR7txdxNgC8DX7Ld39vlHgG26sX40xtVTdUlTX9fJelySuKs0dfsOeBrtTrtUkntwMaSbgDeD7zB9hzgNklnAG/t5vqPS835JkYC3+psLLA1Jam4MiWxdg7wjnr+AuCHwDRgW+CXkmZ28owvBc6X9H3gn5TqPNfr98rGI0cyaYstejstIiIiIiIiIgbIcKvogpLc2hfYk1Lh1WM1kfMh4JPAo5IukfS6XiyxF/Aw8IveXLeH1gCe6MX4B5u/SNpZ0l9rVdRM4F1Ac9XUjA5bMOcCbZQtnEt3WO+BHlx/FdsrNj7AuZ0NtN1ue7Lt+banAQcCO0lavp7/h+1HbD9v+1rgO8Aenaz1B+CrwC9rnPcDsylJ0IiIiIiIiIgYxoZjouuXwLuBe213l5Dxyw7Yv7f9dso2vTuBH9VTc3hpVdBqLdabSKlOOlfSUq3m1eOrdn8bL5LURqlS+0svYnnh3iQtS3ku3wZG18TTpbx0i19npgPzgbWajq3d4+D7phF7Z/G5i3PYPtX2hrZfQ7nvpYHb+jfEiIiIiIiIiBhshl2iq1Zl/Rel4Xx3pgHrNt5KKGm0pN1qr65ngHZKY3Yo2+reKmltSSsAX2qx3nPAB4DlgLPquncBIyS9W9IrKVsbl+3JvUhaVtJWwK+BJykN4XsaS7Nl6jWnA/Ml7Qzs1JMYbD8PXAhMlDRS0iaUhv/9RtK2kjaW9Ira+P5kYJLtWfX87pJeXd8guQ1wEHBRJ2uNkLRZHbs2Zcvjd2w/2Z8xR0RERERERMTgM+wSXQB1G1xP3rD38/rfGZJuojyPQyj9sJ4Atgc+Xde8AjgfuBW4Ebi4k2s/C7wPeA3wE8q2uU8DP6Zsa5xD99voDpM0u8ZwZr3em2sSr8exNMU0m5IcuoCSMJsA/KabGJodSNnG+BhwOi8m3PrLesDvKM/qNkqScc+m8x8G7q7nz6S8MfKMxsnaoH6v+nUEZZtkO3A9cB1wVD/HGxERERERERGDkOyX7d4b9CTNoyRDTradJEb0mKSvAp+nVLgtVyvWWho3bpwnT5682GKLiIi+G3/zzQCD5iUigy2eiIiIiOFE0o22x7U6NyTfumh7xEDHEEOT7aOBowc6joiIiIiIiIjof8Ny62JERERERERERCx5kuiKiIiIiIiIiIhhYVgnuiRZ0hxJxy7kOrdLGt9PYQ0ISUdI+vFAxzGQJG0kqV3S85J68lbOiIiIiIiIiBhChnWiq9rc9pHNByQtVxMel/ZkAdub2p60SKLrgqT9Jd0pabakaZIukTSqnjtd0jE9Xcv2N2wvtuROTazdV5/zQ5LO72LsJEnz6th2SVM7GffVmrzcsYu1VpL0q5rgfEDShMY523fZbgP+slA3FxERERERERGD0pBsRt8P9qC8tXEnSavbfrTVIElL256/eEN74drbA98A3mn7ZkkrAbsORCxdafWMJO0DfATY0fY9klYDdutmqQNtd1pxJml9yu/W8rdqcirwLDAaGAtcIukW27d3M+9lps6d+8Jbs2LJMGH0aA4YM2agw4iIiIiIiIg+WhIqulrZB/g+cCuwV/MJSfdL+qKkW4E5kpaux3as57eRdJ2kmZIelXSKpGWa5lvSJyX9U9KTkk6VpKbzH5N0Rz33e0nrdBLj1sB1tm8GsP2E7TNsz5Z0QI37sFoB9du69hhJv5Q0vVZTHdR03YmSzq5/r1vj3EfSvyQ9LunIprGvkHS4pHskzZB0QU20Nc/dX9K/gD92Evvvbd9TY3/M9g979Mt07hTgi5QkVkuSlgPeDxxlu9321cBvKEm3iC5NaW/n3GnTBjqMiIiIiIiIWAhLXEWXpLWB8cCBwBOUpNe3OwzbE3g38Ljt+U15KoDngc8Bk4E1gcuATwP/2zRmF0qyZ3ngRuC3wO8kvQc4glKZ9U/gcOA84M0tQv0b8HVJRwOXA5NtPwNg+4eS3gw8ZPvL9b5eUa9zUY1/TeBKSVNt/76Tx/EWYGNgI+B6SRfavgM4CHgPsD0wHTiZUim1Z9Pc7YHXAwtarPtX4GRJDwN/Am62/XwnMTQcJ+l4YCpwZPNWUUkfAJ61fWmH36KjjYDnbd/VdOyWGmuvbTxyJJO22KIvU2MISvVeRERERETE0LckVnR9FLjV9j8oSaZNJXXMZpxs+0HbT3ecbPtG23+1Pd/2/cAPeHki5XjbM23/i5LoGVuP/zdwnO076na/bwBjW1V12f4L8D5gS+ASYIakEyUt1cl9bQ2savtrtp+1fS/wI+DDXTyLo20/bfsWSkJo86Y4j7T9UE2uTQT2kNScGJ1oe04nz+hs4DPAO4CrgH9LOryLOL4IrAesAfwQ+G3dqoikNspzOriL+Q1twKwOx2YBo3owNyIiIiIiIiKGuCU10XUOgO1HKImYfTqMebCzyfXNfRdLekzSU5QkzCodhj3W9PdcSgIGYB3gO3Xb40xKRZkoCZ6XsX2Z7V2BlYDdgX2BzhrKrwOMaaxd1z+C0quqM13F+aumde6gVLI1r9XpM6qxn2N7R2BF4JPA1yS9o5Oxf7M92/Yzts8ArgHeVU8fDZxl+76urle1U6romi0PzO7B3IiIiIiIiIgY4paoRFfd7rch8KWaqHoM2BbYs0O1krtY5nvAncCGtpenJJO63E/X5EHgv22v2PR5le1ru5pke4HtP1D6YW3WSYwPAvd1WHuU7XfRew8CO3dYa4Tth5vD6slCtp+z/XNKP7TNuhvftHbjme4AHNT0e60FXCDpiy3m3QUsLWnDpmObA71uRB8RERERERERQ88SleiiVG5dAWxC2U44lpJ8GQns3MM1RgFPAe2SXgd8qhfX/z4lybYpgKQVav+pl5G0u6QPS3q1im0oWyT/WodMo2z3a7geeKo20n+VpKUkbSZp617E1xznsY0tlZJWlbR7TydL2lfSuyWNqo3tdwY2pfQd6zh2RUnvkDSiNv7fC3gr0OgrtgPlN2r8Xo9Qtlae2nEt23OACynVY8tJ+k9KJdxZPb/1iIiIiIiIiBiqlphm9JJGAB8EPmr7sQ7nzqIkwX7bg6UOpfSROgy4GTgf+K+exGD7/7N35/F2Tff/x19vYxo3khAuQURFjK1EL0qptGi/WlRbtIKIGooqRavGoj/R0qqZpmoOGkO1qiiqqXlImlBUzGmUBBnEzYTk8/tjrcNxcu655yY3OfeevJ+Px3m4Z++11/rsfdI/+nl81mfflntO/SEnkd4lJd5uLjN8Gqkp/MXAisCbwK8i4vp8/grg5ry1cFRE7CFpN+Bc4NV8zXjglGpiK3EBqaLqHkm9gbfyff65yutnkCrdRgDLAhOAw/NbEEstD5wJbETaHvk8sEdEjAeIiCnFgyXNA6ZFRHP+fhKwfUQUEpVHAFfmmKfkdV3RZVUZ19zspvSL0eDGRg7t3bvWYZiZmZmZWR1TRFU70DolSXOAuaTm8qfWOh6rrbyl8UlgBeCIiLi60vimpqYYPXr0kgjNOoBBY8cyrrmZAQ0NrQ+2Nis8W7/J1BaXQpK6o/wb62jxmJmZmdUTSWMioqncubqu6IqILrWOwTqOiHiR1BzfrCwnYhYfV8qZmZmZmdmSsLT16DIzMzMzMzMzszrVqRNdkkLSTEnD2nHOfSXdU8W40yWNqHD+WUmD2isuax+SDpLUnP/t9Kt1PGZmZmZmZmbWfjp1oivbPCJOBpDUNycwmvNnsqQ7JO1c7WQRcX1EfGVRg4qITSNiVEvnJW0l6U5J0yVNlfSEpAMXdd2OIr9N8UpJkyS9J+kFST+t4roD8m94cNExSTpT0v8kvStpVOHNlS3MUUiAFv4d/L5wLiKuiAg3YTIzMzMzMzOrQ/WQ6CqnR05mbE56q+FtkobWNqSPSdoGuB/4J5b+T0cAACAASURBVNAPWBU4HNil0nUtzCVJy5Qc6wi9184DGoCNge7A7sDLlS6Q1BM4ESh9S+JewPeA7YFVgEeB61pZf/OIaMifg1sZa2ZmZmZmZmZ1oCMkRBabiJgEXCBpeeBsSddGxHxJJwCHAKsDE4GTI+I2gJwQOzgitsvfNwXOBz4HfABcEBFn5SVWkHQt8E3gv8ABETE6X/danue+MqH9CrgmIs4uOjYG2Dtf25OUyNma9Bs9DBwWEa/n86PysUHAFsBnJL0IHAn8KF+znqQLgG+REk0vAj+KiAfzHFsBlwL9gdnA9RFxbD63HXAOsAnwHnBqRFwtqTtwESkhNwu4HDgrIuaXucctgVMiYlr+/nz+VPIL4MLCcyiyHvBQRLyS4xsBHNPKXIts/KxZbqC9FPEbF83MzMzMzDq/eq3oKvVHUlJrw/z9ZVJ1UHfgDGCEpDVLL5LUDbgPuBvoTaq++nvRkN2BP5De5Hc7cHFrgUjqCmwD3FJh2DLAVcC6QB9SIqp07v2BQ4FuwIR8bA9ScmyT/P1JYACpCuoG4GZJhTdRXkBK2q0MrA/clOPrA9xFSmitlq8fl6+5iPTMPg3sAAwBWtpu+RgwTNKBkjaocK/kdbcCmoDfljn9B6CfpP45aXkA6Tep5IG8bfKPkvq2tr7ZgIYGBjc21joMMzMzMzMzWwR1XdFV5I3831UAIuLmonMjJZ0IbAX8ueS6XYFJEXFu/j4HeLzo/EMRcSeApOtI1VSt6UlKZL3Z0oCImALcWviem+3/o2TY1RHxbNEYgF9ExNSieYqb5Z8r6RRSsu8pUnVaP0m9IuIdUmIKYF/gvoi4MX+fAkyRtCzwHWBgRLwHvCfpXFLC7Yoyt/FDUtXVkcDvJE0AfhgRd5UOzHNfms/Pz/dS7E3gQWA8MI9UhfflMmsW7JDvpytwJnCHpAER8WGFaxawYdeujBo4sC2XmJmZmZmZmVkNLS0VXWvl/04FkDRE0rjcCH46sBnQq8x161C5r9Skor9nAV2q6I81DZgPLFBBViCpq6ThkiZImgE8APTICaGCiWUu/cQxScdJ+k9u4D6dVI1VuM+DSNsWn5f0pKRd8/GW7rkXsAIfV4+R/16rzFgiYnZEnBURnyP1ILuJVFG2SpnhRwBPR8Sj5eYCTiNthVwH6EKqwrs/V8eVW/uBiHg/IqYDR5O2Pm7cwtxmZmZmZmZmVieWlkTXN4G3gPGS1iX1ljoSWDUiegDPAAuUEZESR+u3ZyARMYvUTP3bFYYdR6q82jpvLfxiPl4cY5SbvvCHpO2Bn5L6XfXM9/luYY6IeDEi9iFt6TwbuEXSSrR8z++QqsDWLTrWB/hfhfsgrzUDOAtYiZR0KrUj8M281XASsC2pAq2wXXNzYGREvB4RH0bE1aTKuE3KzFU2BMr/vmZmZmZmZmZWR+o60SWpUdKRpIqgE3PT9JVIiY+385gDSRVd5dwBrCHpR5JWlNRN0tbtENrxwFBJP5G0ao5jc0l/yOe7kfpyTc8VUKctxBrdgA9J97mcpJ8BKxdOStpP0mr5mUzPh+cB1wM7Sdpb0nKSVs3b/uaRqrKG5eewLnAsULw9kqL5T5W0paQVcl+wo/M648sMH0qquBqQP6NJVVsn5/NPAnvl33MZSfsDywMvlVl3U0kDJC0rqQE4l5SM+091j83MzMzMzMzMOqt6TXRNlzQT+DfwNWCviLgSICKeIyU/HgUmA58hvcFwAbkX1c7AbqRtii8CX1rU4CLiEVKPqS8Dr0iaCvwOuDMPOR/4FKmK6jFab7xezt9ITeVfIG0xnMMntzb+H/CspGZSY/rvRsSciPgv6ZkdR9rqOY5UUQWp79ZM4BXgIVKD+ytbuk1SQ/13SD3Sdga+HhHNCwyMmB4Rkwof4H1gRkS8m4ecTeorNo6ULDsG+HbemoikuySdlMc2AiOBGTnOvsCuEfFBq0/MzMzMzMzMzDo1RZTbAdc5SJoDzAUujIhTax2PdXy5gu88Uq+vTSLilZbGNjU1xejRo5dYbGb1bNDYsYxrbmZAQ0OtQ+n0Bjc2cmjv3rUOo8MZNHYsQId5iUhHi8fMzMysnkgaExFN5c516rcuRkSXWsdgnUtEXEWqNDMz63TGNaeiWCe6zMzMzMzK69SJLjMz6zwGNDS4umURFaqEzMzMzMysvHrt0WVmZmZmZmZmZkuZDpnokhSSZkoaVoO1t5dU7s2AdSs/7361jmNxy2/ObJb0gaQzax2PmZmZmZmZmbWvDpnoyjaPiJMBJPXNyZjm/Jks6VJJyy/qIqVJnoh4MCI2XNR5K6z3XUmP50TeW/nvIyRpca1ZC5IOkvS8pPfy7/VXSd1aGHu1pPeLft9mScvmc/0l/VnS25KmSvqbpBZ/H0nnSJooaYakCZJOLpyLiLkR0QBc3+43bGZmZmZmZmY115ETXeX0yImKzwDbAD+ocTxtIuk44ALgV8AaQCNwGPAFYIUahtauJO0AnAXsExHdgI2Bm1q57JyIaCj6zMvHewC3AxuSntcTwJ8rzHMFsFFErAxsCwyW9K1FuB0zMzMzMzMz6yQ6ZTP6iHhL0r3AJoVjkk4ADgFWByYCJ0fEbflcP1ICZADwAfD3iPiOpAfy5U9JCuAgYDIwIiLWrmLeocDBwGP52unAERFxV2nMkroDPweGRMStRafGAvuWjLsI2AWYBVwOnBUR8yutJ2kb4N6ieZcDJkVEX0lbkRJsGwOzgVuBYyPi/TJxrggMA/YGVgRuA46JiNmS/gJ8qWh4V+B7EXF1yTRbAo9GxFiAiJgKXFO6VjUi4glScqsQ33nAKZJWjYgpZcaXbjudDyzUtszxs2a58fMiGtzY6LfDmZmZmZmZ2RLT2Sq6AJDUG/gqKeFT8DKwPdAdOAMYIWnNfO7/AfcAPYG1SYkkIuKL+fzmuYpoZJnlKs0LsDUwHugFnANc0cI2xG1IiaNK1Ujk2LoDnwZ2AIYAB7a2XkQ8WqiGyvf5GHBjvmYecEy+ZhtgR+CIFtY/G+hPSgr2A9YCfgYQEbsVrbEnMAn4e5k5Hge+KukMSV/IybPWHJG3Jo6R9O0K475ISuAtkOQqkHSCpGbgdWAl4IYq1rd2Nq65mRsmT651GGZmZmZmZrYU6WwVXe/kHFJ34FHglsKJiLi5aNxISScCW5ESSx8A6wK9I+J14KFqF2xlXoAJEXE5gKRrgEtJW+wmlUzVC3gnIj4sHJD0CKkqbUVS4u5h4DvAwIh4D3hP0rnA/qSKtGrXuxCYCZyc72FM0bnXJA0nJdHOLw4wJ+gOAT6bq7CQdBYpUXRi0bj+wLXAtyNiYpln9mDeLngEcDSwnKTfAT8p2pJY7ELgOOBd4Cuk5zwpIh4uiW9t4BLg2DJzFK//S0lnk5J1e+R522zDrl0ZNXDgwlxq4Go4MzMzMzMzW+I6W0VXr4joQdoy9zBwd+GEpCGSxkmaLmk6sBkpuQRwPCDgCUnPSvpetQu2Mi8UJZgiYlb+s6HMVFOAXpKWKxq/bb6fKaTfohepV9eEousmkKqqqlpP0veBQcDgiJifj/WXdIekSZJmkPpnFd9DwWqkZzum6H7vzscL83cnJflOjYgHy8xRiO2uiNgNWAX4BjCUtO2y3Nh/RcSUiPgwIu4kNYv/RF8tSauRqvIujYgby81TMmfkrZOzSZV4ZmZmZmZmZlbnOluiC4CImA1cDWwjqZekdUm9rI4EVs3Jo2dIyS0iYlJEHBIRvYHvA5cWv2mxJa3N20aPAnNJSZ+WvMPH1WcFfYD/VbOApO1J2zS/ERHFVUyXAc8DG+Qm7SdR/h7eISWGNo2IHvnTPW9VRNIypOquf0TE8Gpiioj5EfF34H5SkrCqy4rjk9STlOS6PSKGVTlHwXLA+m28xszMzMzMzMw6oU6Z6Mo9n/YnVTdNIfVhCuDtfP5AipIqkvbK294ApuWxhS10k0n9sMqpOG9bRMR0UmXRpZL2lNQgaRlJA/I65G19NwHDJHXLibZjgRGtzS9pHWAkqdn9CyWnuwEzgGZJGwGHtxDjfFJi7zxJq+d515L01TxkWI716FZi+Yak70rqqWQr0lbJx1oYX/w8vgLsR3rTIpJWBv4GPBwRJ7Sy7jKSvl+y7g8o30fMzMzMzMzMzOpMZ0t0Tc9NxieTmqrvnreoPQecS6qamgx8hrS1sWBL4PF87e3A0RHxaj53OnBN3qq3d/FiVczbJhFxDilxdTzwVp5zOPBT4JE87Iek/lqvkHqJ3QBcWcX0OwJrALdIas6fZ/O5HwODgfdIiaxyTfcLfgq8BDyWtzneB2yYz+0DfB6YVrTGvmXmmEbq9fUiKcE2AvhVRFzfwppHk6rWpgO/Ag6JiFH53DdJv9+BRWs2S+oDIGnfovssjH853+sIUnP/iyrcr5mZmZmZmZnVCUVErWNYgKQ5pG1+F0bEqbWOx+pDrgScDCwPnBMRFXt3NTU1xejRo5dIbPVo0NixjGtuZkBDuZZ1trQp/FvwCx4WTeElD36OC+poz6ajxWNmZmZWTySNiYimcuc65FsXI6JLrWOw+hMRc4EetY7DbGk0oKGBwY2NtQ7DzMzMzMzqXIdMdJlZfXAFj5mZmZmZmS1Jna1Hl5mZmZmZmZmZWVlOdFUgKSTNlDSs1rF0RJJek7RTreNoC0ln5N80JLmi0czMzMzMzKyOONHVus0j4uTiA5JWym/+u3NxLCipb07EFN4wOFnSHZJ2XhzrLQ6S1pZ0q6R3JL0r6d+ShlZx3Wn53hdIoElaQdLzkl6vcP0Kkm7JSbiQNKj4fEScBmy6ELdkZmZmZmZmZh2cE10LZ0/SWyG/ImnNxbhOj4hoADYH7gVuqyZZVE4NqpeuAyYC6wKrAkNIbzxskaT1Sc/2zRaG/AR4q4q1HwL2AyZVG6yZmZmZmZmZdX7eurVwDgB+C+wC7Av8WtLngT8Ba0XEPABJ3wTOiIjPStoKuADYGJgN3AocGxHvt7ZYREwCLpC0PHC2pGsjYr6kADaIiJfyelcDr0fEKbmSaQRwEXAMcK+ko0gJqK1Jv/3DwGER8Xq+fhTwIPBl4LPAo8DgiHgnn98fOBNoAH7TSthbAsdExMz8fWxr9wlcDPwUuLT0hKT1SMmrY4HLW5ogP8/z8zXzqlizReNnzfro9fDWduOamxnQ0FDrMMzMzMzMzGwp4oquNpLUBxgEXJ8/QwAi4jFgJilJVDAYuCH/PY+UcOoFbAPsCBzRxuX/CKwObFjl+DWAVUhVVYeSfu+r8vc+pITbxSXXDAYOzOusAPwYQNImwGXA/kBvUpXW2hXWfgy4RNJ38zOrSNJewPsR0dJ20IuAk3LM1gkMaGhgcGNjrcMwMzMzMzOzpYgrutpuCPB0RDwnaTpwjqSBETEWuBHYh1Q91Q34GjlRFBFjiuZ4TdJwYAdy9VGV3sj/XaXK8fOB0yJibv5eqCQDIDfZ/0fJNVdFxAv5/E3A7vn4nsAdEfFAPncqcGSFtfciVWedCmwk6d/AIRHxZOlASQ3AWcBXyk2UK+OWi4jbSntuLU4bdu3KqIEDl9RyZmZmZmZmZraIXNHVdkNIlVxExBvAP0lbGSFVb31L0orAt4B/RcQEAEn9c0P5SZJmkBI7vdq49lr5v1OrHP92RMwpfJHUVdJwSRNyDA8APSQtW3RNcV+rWaRtipCquCYWTuQtiVNaWjgipkXECRGxKdAIjAP+JEllhp8BXBcRr5aekLQScA7ww1bu1czMzMzMzMyWck50tYGkbYENgBNzwmoSqd/VPpKWi4jngAmk3l3F2xYhbft7ntRTa2XSNrxySZ9Kvklqxj4+f58FdC06v0bJ+Cj5fhxp2+PWOYYvFm6tirXfBNYpfJHUlbR9sVW5x9evScmyctVoOwJHFT3TdYCbJP2U9Lz7Ag/mc38E1sxj+1azvpmZmZmZmZktHbx1sW0OIL39cEjRsU8BT5OSW38hJbeOIvXh2rdoXDdgBtAsaSPgcODtahaV1EjaCngacHREzM+nxgGDJT0L7EzaCjm6wlTdSNsXp0taJc9XrVuAxyVtBzwB/JwKiVJJZ5Ma3z9PekaHAy9FRLkqsB2B5Yu+P0lqOn8XMIeiBBuwLamv2Ba08PxyRV0hebeCpC7A3IgoTfyZmZmZmZmZWR1xRVeVcrJkb+CiiJhU9HmVlNApbF+8kdSs/v7C2wqzH5OqvN4jvTVwZBXLTpc0E/g3qd/XXhFxZdH5o4HdgOmkpNqfWpnvfFLS6R1Ss/i7q4gBgIh4FvgBKZH3JjANeL3CJV2B23Jsr5Aa4O9ebmBETCl+pqTG/dMiojkiPiw5NxWYn78X3m75rKTipOJ4UkJvLeBv+e91q71XMzMzMzMzM+uc5CKXlkmaA8wFLoyIU2sdjy06SaeRqsVWBFYqJMvKaWpqitGjKxXImZktWYPGjgXwizLK6GjPpqPFY2ZmZlZPJI2JiKZy57x1sYKI6FLrGKx9RcQZpOb3ZmZmZmZmZlZnvHXRzMzMzMzMzMzqghNdmaSQNFPSsDZc85qknRZx3e0ljW99pLUHSVdLmi2pUn8xMzMzMzMzM+uEnOj6pM0j4uTiA5JWktQs6c7FsWBEPBgRGy7MtZJOlzSivWNqD5I2lXSPpGmSpksaI+lrLYwdJGl+fs6FzwFF5/eW9IikWZJGtbJuxbkiYijpDZlmZmZmZmZmVmfco6t1e5Ia0n9F0poR8WatA+ok/gJcBuyav28JqML4NyJi7RbOTSW9MXIj4MtVrF1pLjMzMzMzMzOrU050te4A4LekKqB9gV+XGyRpGeB44BCgB/B34LCImCrpMmC1iNgzjz0baAJ2AnYARhQSM5JOyHOsDkwETo6I29oatKTdgV8AawHjgMMj4j/53GvAcGB/YE3gT/n8nHx+V+BMoC/wXL6PpyV9B7iiaJnlgUcjYlDJ2r2A9YDLI+L9fPjhtt5DQUTcl+c9eGHnWBjjZ8366K1ZndngxkYO7d271mGYmZmZmZmZLXbeuliBpD7AIOD6/BlSYfhRwB6kxFVvYBpwST53HPBZSUMlbQ8cBBwQEVFmnpeB7YHupLcDjpC0Zhvj7g/cCPwIWA24E/iLpBWKhu0LfBVYH+gPnJKv3QK4Evg+sCopIXa7pBUjYmRENEREQ77HV/I6paYAL+XY95DUWEXYq0uaLOlVSedJWqkt97wY5+rUxjU3c8PkybUOw8zMzMzMzGyJcEVXZUOApyPiOUnTgXMkDYyIcmU+3weOjIjXIfXPAv4raf+ImCVpP+Bu4D3gh4VxpSLi5qKvIyWdCGwF/LkNcX8H+GtE3Jtj+TVwNLAtMCqPuTgiJubzw4CLSMmuQ4DhEfF4HneNpJOAzwP/zOOXAW4ARkXE8DL3EJK+BJwAnAusJ+kh4KCIeLFMvM8DA/J/1wWuAX5DeqZt1W5zbdi1K6MGDlyIEDqOeqhIMzMzMzMzM6uWK7oqG0Kq5CIi3iAleg5oYey6wG258fp04D/APKAxX/8EqQJKwE0tLShpiKRxRfNsBvRqY9y9gQmFLxExn7QNcq2iMROL/p6Qryncx3GF9XMM6xSdBxgGdCNVsZUVEa9HxJERsX6ecyZwbQtjJ0XEcxExPyJeJW0B3bO6W118c5mZmZmZmZlZ5+JEVwskbQtsAJwoaZKkScDWwD6SylXCTQR2iYgeRZ8uEfG/PN8PgBWBN0jJl3JrrgtcDhwJrBoRPYBnqNzEvZw3SMmlwrwiJav+VzRmnaK/++RrCvcxrOQ+ukbEjXmu7wL7AHtGxAfVBJMrxy4hJe2quoS23/OSmMvMzMzMzMzMOjAnulp2AHAvsAlpK9wAUqKmK6kxfanfAsNysgpJq0n6Rv67P6m5+36kBvDHSxpQZo6VSImZt/N1B9J6cmgZSV2KPiuSKsa+LmlHScuTeoTNBR4puu4HktaWtApwEjAyH78cOEzS1kpWkvR1Sd0kDSRtcdwjIt5uKSBJPSWdIamfpGVyc/rvAY+1MH6QpD55vXWAX1K0VVPSspK6kLbaFu53+YWZy8zMzMzMzMzqlxNdZeSkyt7ARXkrXOHzKnAd5bcvXgDcDtwj6T1SUmfrXP01Ajg7Ip7KPapOAq7LSamPRMRzpJ5WjwKTgc/Q+tsK9wFmF31ejojxpKTaRcA7wG7AbkVvQITUY+se0nbKV0iJOCJiNKlP18WkhvovAUPzNd8AegIPSWrOn7vKxPQ+6Y2N9wEzSFVpc4vmKbVFvueZpGTcM3xyW+T++d4uIzXqn01KyAGQ49i+yrnMzMzMzMzMrE6p/Iv/lj6S5pCSMRdGxKm1jmdxkvQacHBE3FfrWJY0SVcAewFvRUS/SmObmppi9OjRSyawxWTQ2LGMa25mQENDrUNp0eDGRg7t3bv1gWb20QsmOvuLMhaHjvZsOlo8ZmZmZvVE0piIaCp3zm9dzCKiS61jsMUvIg4CDqp1HJaMa24GcKLLzMzMzMzM2oUTXWZ1bkBDQ4etKChUPJiZmZmZmZm1Bye6lkIR0bfWMZiZmZmZmZmZtbe6akYvKSTNlDSsRuufJOn3+e++OZ66TCZ21vuTdL+kOZIeqnUsZmZmZmZmZta+6irRlW0eEScXvkhaQdLpkl7MSbDXJF0pqW97LxwRZ0XEwYs6j6ShkuYVvdnwVUlXSerfHnEuCZK2k/SIpHclTZX0sKQtq7ju/tIEWk6q3SlpmqRJki5uKcEm6bdFz61Z0tz8FkwAIuLLwGHtcpNmZmZmZmZm1qHUY6Kr1C3A7sBgoDuwOTAG2LGWQVXh0YhoIMW8EzAbGCNps4WZbElWXklaGbgDuAhYBVgLOIP0VstK1+1L+e20lwJvAWsCA4AdgCPKzRERh0VEQ+ED3AjcvJC3YmZmZmZmZmadSKfadtZWknYCdgb6R8TEfPhd4JKiMQcCxwNrA28DZ0fE8HxuEDACuBD4MTAPOBx4Hzgf6AX8OiLOyuNPB/pFxH5lYmlxnUoiYh7wMnCEpD7A6cCehdgiYu2iNV4DDo6I+3IsmwFzSIm+YyU9DVwAbExKnN0KHBsR7+frI9/fcfnebgCOjIiQtCxwNjAUmAGcWyHs/jn2G/P32cA9le5TUnfgNGAI8GjJ6fWAiyNiDjBJ0t3AppXmy3OuBHwb2LW1seWMnzWr0zdLH9fczICGhlqHYWZmZmZmZrZE1HtF107AE0VJrnLeIiVCVgYOBM6TtEXR+TWALqSqpJ8BlwP7AZ8Dtgd+JunTVcTS2jrV+GNes1rfIFW09QCuJyXqjiElsbYhVbWVVkbtCmxJqnzbG/hqPn5IPjcQaAL2rLDuC8A8SddI2kVSzypiPQu4DJhU5twFwHcldZW0FrALcHcVc36blFR8oIqxdWlAQwODGxtrHYaZmZmZmZnZElHXFV3AqsCblQZExF+Lvv5T0j2kZNK/8rEPgGERMU/SH4DfARdExHvAs5KeBT4LvLKI61TjDdJWwGo9GhF/yn/PJm3ZLHhN0nDSNsDzi47/MiKmA9Ml/YO0VfBuUtLr/ELSUNIvgEHlFo2IGZK2A35KSgyuIelO4JCImFw6XlIT8AXgaFLFW6l/khJtM4BlgWuAP5UZV+oA4NqIiCrGLmDDrl0ZNXDgwlxqZmZmZmZmZjVQ74muKeRtdC2RtAtpy1x/UoVbV+DfxXPk7YOQkkUAxcma2UCre8OqWKcaawFT2zD+E5VsuZn9b0gVWV1Jv/+YkmuKK6pm8fG99S6Zb0KlhSPiP6RtjkjaiLQF9Hxgn5KYliH14Do6Ij6URJnzfwOGA9vmeK4kbaM8vqX1Ja1DSuIdUilOq71xzc2dfotoJYMbGzm0d+9ah2F1pN7/N7OwvFXbzMzMzKD+ty7eB2wlqVyVEJJWJPWp+jXQGBE9gDsBlRu/sNpxnW8CD+a/Z5KSVYU1lgVWKxlfWsl0GfA8sEFErAyc1IYY3gTWKfrep8rriIjngatJPcNKrUxKvI2UNAl4Mh9/XdL2pAq2dUg9uuZGxBTgKuBrrSw7BHgkIipW2pktTuOam7lh8gJFjGa2GHirtpmZmZlBnVd05abs9wK3SToMeAr4FLAvqaH8zcCKpD5OH+aqq68Az7RzKCss7Do5gdUHOJa0VXCbfOoFoIukr5MavZ+U16ikG2n7X3Ousjo8x1SNm4CjJN1BSrKdUCHmjYCvAyMj4vVcXbUP8FiZ4e+SqsUK1gGeIPVAezsi3pf0KnC4pF+TKroOIP2WlQwhVX1ZBzegoaFut4i66sYWh3r+34yZmZmZ2aKq94ouSE3T7wRGkpIqz5AqiO7LfbaOIiVxpgGDgdvbO4CFXGcbSc2kxNQoUuXTlhHx7zznu6RG8r8H/kdKPr3eypw/zmu/R+qdNbINt3E5aQvhU6S+Yn+sMPY9YGvgcUkzSQmuZ0hvc/yESCYVPnyceJtceBsk8C3g//K5l4APSU31kdRHUnN+IyX52DakXl83t+H+zMzMzMzMzKyT00L26e6QJM0B5gIXRsSptY7HOp5c4fd50ts4d6w0tqmpKUaPHr1kAltKFSqe6rU6pd7vz5Y8/5vqPPxbmZmZmS0+ksZERFO5c3W1dTEiutQ6BuvYImLnWsdgZmZmZmZmZovH0rB10czMzMzMzMzMlgJOdJmZmZmZmZmZWV3oMIkuSSFppqRhtY6lJZKulnRmreOwhZd/w9mSWmvcb2ZmZmZmZmadTIdJdGWbR8TJAJL65uTXv4oHSOol6X1Jr9UkwnYiabCk0fmNgW9KukvSdrWOq71I2lTSPZKmSZouaYykr7UwdpCk+flZFD4HlBm3iqS3JT1UYd01Jd0u6Y3876dv8fmIGArssmh3Z2ZmZmZmZmYdUUdLdJWzkqTNir4PBl6tVTDtQdKxwPnAWUAj0Ae4FPjGQsy1wAsFyh2rgb8A95Lub3XgKGBGhfFvRERD0eeaMmPOBv7TyrrzgbuBby9EzGZmBUwEuwAAIABJREFUZmZmZmbWiXWEhEhrrgMOAH6Svw8BrgUOKQyQtDFwGTAA+B9wYkTcns9dDcwC1gO2B54iJUFOyPNOBvaJiLGtzVVMUjfgduDfwNHANsAFQH/gBeDoiHikzHXdgZ8DB0bEH4tO/SV/kLRVnmtjYDZwK3BsRLyfzwdwJPAjYDlJBwIjgIuAY4B7JR2Vn93WpN/5YeCwiHg9zzEU+BmwGvAOcEpEXJ/PHQIcC6wNTAT2i4h/teHZ9MrP+/JCzHn9hSZpG2Az4HfAQS2Ni4jJwKXtkewbP2vWR6+Ht8VjXHMzAxoaah2GmZmZmZmZ1YnOUNE1AviupGVzoqUb8HjhpKTlSQmie0iVQz8Erpe0YdEcewOnAL2AucCjwL/y91uA37RhLiStCvwdeDgijgJ6An8FLgRWzfP9NY8rtQ3QBbitwj3PIyWseuXxOwJHlIzZg5TE2iR/XwNYBVgXOJT0216Vv/chJcwuzvGvlGPdJSK6AdsC4/K5vYDTSQnFlYHdgSnVPptsCvASMELSHpIaK9xrweqSJkt6VdJ5OUZyTMsCl5CSe1HFXNZJDGhoYHBjNf88zMzMzMzMzFrXGSq6XgfGAzsBXyJVcxX7PNAA/DIi5gP3S7oD2IeUsAG4LSLGAEi6DTgiIq7N30eSEijVztUb+CdwTUT8Kh/7OvBiRFyXv9+YK6p2A64uiXdV4J2I+LClGy7Emr0maTiwA2m7Y8EvImJqvgdIW/ZOi4i5+XyhEow8Zhjwj6Lr5wObSfpvRLwJvJmPHwycExFP5u8v5eu3r+LZFOIPSV8iVc2dC6yX+2odFBEvlrnl50lVYs+TEnPXkJKF38/njwIej4gxkj5T5vrFYsOuXRk1cOCSWs7MzMzMzMzMFlFnqOiClNwaSkqqjCg51xuYmJMvBROAtYq+Ty76e3aZ74W9U9XM9XXgU8BvS2KYUBJX6XUFU4BelbbWSeov6Q5JkyTNIPXy6lUybGLJ97cjYk7RHF0lDZc0Ic/xANBD0rIRMRP4DnAY8Kakv0raKF+6DvBymbCqeTYfiYjXI+LIiFiflLyayYJJysLYSRHxXETMj4hXgeOBPfN99CYluk4ud62ZmZmZmZmZWUFnSXTdSkowvRIRpQmlN4B1JBXfSx9SD6m2qmauy0nNzu8s2l73BimZQ4XrCh4F5pC2HrbkMlJ10wYRsTJwEqCSMaVb+Eq/HwdsCGyd5/hiPi6AiPhbROwMrJnXujyfnwisXyamhX7OETGRtPVws9bGFi7h4/vdKsf4nKRJpN5lW+Uk4LJVzmdmZmZmZmZmS4HOsHWRiJgp6cvAtDKnHydVCx0v6VzgC6Qtg1suxFLVznUkKTF0h6SvAXcCF0kaDNxEana/CXBHmXt5V9LPgEskfUjqefUBeWtmRBxP6kM2A2jOlVaHA2+38V66karVpktaBTitcCL3zNqa1GdsNtBM6gsG8HvgN3mr4b9ISa8P2vBskNST1Cj/OuAVUu+w7wGPlQtU0qA8biKpAf4vgT/n03cBfYuGf4f05s1vRMQ8ypDUBSgkwVaU1KW42s1sSRrX3LxUvdRgcGMjh/buXeswzMzMzMxsKdVZKrqIiNERscCWuvxWv92BXUhvD7wUGBIRzy/EGlXNFRFBavg+kZSQmQnsSqqimkLaerdrRLzTwjq/Ib3V8BRSAmsiKXn2pzzkx6RkznukhNrItt4LqZ/Xp/J9PEaqQitYJsf6BjCV1P/riBzbzcAw4Ia8/p+AVdr4nN8nJafuIyXsniG9BGBoC7FuQap0mwk8kscfleOZm7c2ToqIScC7wAf5bwAkNeceYgWF5B2karXZLaxrZu1oXHMzN0ye3PpAMzMzMzOzxUQpZ1N7kuaQkiEXRsSptY7H6pOkK4C9gLciol+lsU1NTTF69OglE5jVpUIl19LyUoOl7X5rwc+48/BvZWZmZrb4SBoTEU3lznWYrYsR0aXWMVj9i4iDgINqHYeZmZmZmZmZtb9Os3XRzMzMzMzMzMyskrpNdEkKSTMlDVuMawyS9Primr/WJPXNz7HDVP4tKklXS5pdz7+bmZmZmZmZ2dKqbhNd2eYRcXLhi6QVJJ0u6cWcBHtN0pWS+i7pwHIcI4q+ryXpeUkXStKSjqe9SdpU0j2SpkmaLmlMfkNlS+NXk3RDHjtN0vVF5/aW9IikWZJGtSGGq3Ki7qNeXBExlNRQ38zMzMzMzMzqTL0nukrdQnpz4GCgO7A5MAbYsa0TtWeVk6R1gQeA2yPiqOgobwhYNH8B7gUagdVJb1GcUWH8H4FJwLp5/K+Lzk0lvUXyl9UuLmk7YP22hWxmZmZmZmZmnVndbElrjaSdgJ2B/hExMR9+F7ikaMyBwPHA2sDbwNkRMTyfGwSMAC4CjiElca4oWeME4BBSomYicHJE3NZKXOsD9wPXFr9tUtL3gJ8AawBPAIdGxIR8LoDDgeOAXsANwJEREZKGAgcDj5Gark8HjoiIu/K13YHfAF8D5gNXAadFxDxJywJnA0NJSalzi+LZCzghIj5XdOw4YPuI2KPknnoB6wGXR8T7+fDDFZ7BV4B1gEERMS8fHls4HxH35XEHt/ggPznfcqTf6QDgqWquKWf8rFkfvTWrIxnc2MihvXvXOgwzMzMzMzOzDmdpqujaCXiiKMlVzlvArsDKwIHAeZK2KDq/BrAKqero0DLXvwxsT6oWOwMYIWnNCut9mlTJNbwkybUHcBLwLWA14EHgxpJrdwW2JFWl7Q18tejc1sB4UhLsHOCKou2Q1wAfAv2AgcBXSIkxSEm6XfPxJmDPojlvB9aTtHHRsf2A68rc1xTgpXz/e0hqrPAMAD6f471G0hRJT0raoZVrKjkGeCAinl6EOTqkcc3N3DB5cq3DMDMzMzMzM+uQlpqKLmBV4M1KAyLir0Vf/ynpHlLi6l/52HxS9dNcgNJWWhFxc9HXkZJOBLYC/tzCkpvlOUeWHP8+8IuI+E9e5yzgJEnrFqq6gF9GxHRguqR/AAOAu/O5CRFxeb72GuBSoDFXgu0C9IiI2cBMSeeRknbDSQmz8wvJQEm/AAble5sraSQpuXWypE2BvsAdpTeVK8u+BJxAqgpbT9JDwEER8WKZ57A2HyfcDgS+DfxZUr+IeKeFZ1eWpHXy8/tca2Nbs2HXrowaOHBRp2lXHbHCzMzMzMzMzKyjWJoquqYAlaqrkLSLpMckTZU0nbS9r1fRkLcjYk6F64dIGpcbqk8nJbJ6tTSeVCV1JXB/7tNVsC5wQdE8UwEBaxWNmVT09yygody5iJiV/2zI8y4PvFk093DSVkuA3qQtlwUT+KRrgMG5Omx/4KZC0q9URLweEUdGxPp53ZnAteXGArOB1yLiioj4ICL+kOP4QgvjKzkf+HlEvLsQ15qZmZmZmZlZJ7Y0JbruA7aStHa5k5JWBG4lNUFvjIgewJ2kBFNBi03ic6LqcuBIYNV8/TMl1y8gIo4lVUXdL6mQyJoIfD8iehR9PhURj1RzoxVMBOYCvYrmXTkiNs3n3yT1yiroUxLrY8D7pCq3wZTftriAXCF2CSnxV87TVHi2bbQj8CtJkyQVEn6PShrcTvObmZmZmZmZWQe11CS6ckPze4HbJH1O0nKSukk6LDd+XwFYkdSE/kNJu5C201VrJVKy5m34qLF9S4mdUkeSGtL/Pfez+i1wYt4eiKTuuRn8IomIN4F7gHMlrSxpGUnrF/XDugk4StLaknqSth6Wuha4GPgwIh4qt46knpLOkNQvr9EL+B6pQX45twE9JR0gaVlJe5Kq1x7O8y0rqQtpq+0ykrpIWr6FufqT+pYNyB+A3fIaZmZmZmZmZlbHlppEV7YnqUprJOmNi8+Qmq7fFxHvAUeRkj3TSBVLt1c7cUQ8R+pH9SgwGfgMFd40WHJtkPpKPUGqPHuQ9PbDP0iakePcpdpYWjGElNR7jnSft/Dxls7Lgb+R3lT4L+CPZa6/jpTAq1TN9T6pf9d9pLc3PkOqJBtabnBETAV2B35M+l1OAL5R1J9rf9L2xstI1WSzc6wASGqWtH2e662ImFT45CHv5J5kZmZmZmZmZlbHlHIs9UfSHFJy5cLiNxraopH0KdLbKbdoobF8hybpCmAv4K2I6FdpbFNTU4wePXrJBFalQWPHMq65mQENDa0Ptpor/FYd7aUGi0vhZQlLy/3Wgp9x5+HfyszMzGzxkTQmIprKnavbty5GRJdax1CnDgee7IxJLoCIOAg4qNZx2NJhQEMDgxsbax2GmZmZmZnZUqNuE13W/iS9Rmquv0eNQ1mqLU0VQmZmZmZmZmZt4USXVS0i+tY6BjMzMzMzMzOzlnT4ZvSSQtJMScNqHUsxSSdJ+n2t47C2kXRQbl4fkir26DIzMzMzMzOzzqXDJ7qyzSPi5MKXjpCkiIizIuLghb1e0laS7pQ0XdJUSU9IOrA9Y6wlST0kXSlpkqT3JL0g6acVxi8r6UxJb+TxYyX1yOe+K2m8pHclvSXpGkkrV5irkBxtzp+PEpIRcUVEuJO7mZmZmZmZWR3qLImuuiJpG+B+4J9AP2BVUpP3XRZiLklapuRYR9iSeh7QAGwMdAd2B16uMP4MYFtgG2BlYH9gTj73MPCFiOgOfJq05fbMVtbfPCIa8mehE5JmZmZmZmZm1nl0hITIIpG0InA2sHc+dBPw04iYK6kncB2wNeleHwYOi4jX87XrAVcDWwCPAeOBHhGxn6RBwIiIWLtordeAgyPiPkmnA/3y2L7Aq8BQ4P8BXYHzIqKl7Za/Aq6JiLOLjo0p3EMVcY/Kxwbl2D8j6UXgSOBH+Zr1JF0AfIuUaHoR+FFEPJjn2Aq4FOgPzAauj4hj87ntgHOATYD3gFMj4mpJ3YGLSAm5WcDlwFkRMb/MPW4JnBIR0/L35/NnAfl+f0RKTk3Ih58pnI+IiSWXzCMlCBer8bNmffR6+I5iXHMzAxpckGZmZmZmZmZWTj1UdJ0MfB4YAGwObAWcks8tA1wFrAv0ISV0Li669gZSgqkXKUF1wCLGsh2wIbAj8DNJG5cOkNSVVLV0S4V5WosbUsXToUA3oJAc2oOUHNskf3+S9FxWId3rzZK65HMXABdExMrA+qQEIZL6AHeRElqr5evH5WsuIiXNPg3sAAwBWtpu+RgwTNKBkjaocK8AnwE+BPbMWx1fkPSD4gGStpP0Linx9m3g/FbmfCDP9ceciKwLAxoaGNzYWOswzMzMzMzMzDqkTl/RBewL/DAi3gKQdAYwnFSFNAW4tTAwN7T/R/67D6nqaKeImEtKjPxlEWM5IyJmA09JeoqUePtPyZiepETWmy1NUinuIldHxLNFYwB+ERFTi+YZUTT+XEmnkBJxTwEfAP0k9YqId0iJKUjP876IuDF/nwJMkbQs8B1gYES8B7wn6VxSwu2KMrfxQ+AYUpXZ7yRNIP1Od5UZuzYpgdYfWA/YAPi7pBci4t58Lw8B3SWtBRwCvFZmnoId8v10JW1xvEPSgIj4sMI1C9iwa1dGDRzYlkvMzMzMzMzMrIbqoaKrNx9XNJH/7g2pekrScEkTJM0AHgB65KRNb2BaRMwsuXZRTCr6exapR1WpacB8YM2WJmkl7oLS7XwLHJN0nKT/5Cbu00nJpF759EGkxNLzkp6UtGs+vg7le2n1AlZgwWe9Vrl7iIjZuWH/50g9yG4iVZStUmb47Pzfn+frngb+AHytzLz/A+7O58uKiAci4v2ImA4cTUqeLVBdZ2ZmZmZmZmb1pR4SXW+QtvgV9MnHAI4jVTBtnbfofTEfF6miqqeklUquLZhJqghKF6Qk02qLGmxEzAIeJW2/a0mluD+aqtz0hT8kbQ/8lNT3q2dE9ADeLcwRES9GxD7A6qQeZ7fkZzGRtJWx1DukKrDSZ/2/CvdBXmsGcBawEinpVOrpCvdUznItxNhiCHzy2ZmZmZmZmZlZHaqHRNeNwCmSVpPUC/gZUNiy141ULTQ9VxKdVrgoNz0fDZwhaYXcgH23onlfALpI+rqk5Ul9v1Zsp5iPB4ZK+omkVQEkbS6pUKXUYtxt0I3U9+ptYDlJPyO9zZC83n6SVsuN5Kfnw/OA64GdJO0taTlJq+Ztf/NIVVnDJHWTtC5wLB8/60+QdKqkLfOz7UKqrJpOavj/CRHxMvAgcLKkFXNvs+8Ad+S59pXUJ79hcl1gGPD3FtbdVNIASctKagDOJSXjSreQmpmZmZmZmVmd6cyJrkL1z5mkhNXTwL+Bf+VjkBqWf4pUjfQYactbscGk5u1TScmkaz+aPOJd4Ajg96REyUzg9XYJPOIR4Mv584qkqcDvgDurjLsafyM1lX+BtMVwDp/c2vh/wLOSmkmN6b8bEXMi4r+kLYPHkZ7LOFKvMUh9t2YCrwAPkRrcX9nSbZIa6r9DqrDbGfh6RDS3MH4fUrXYFOCvpB5rhWTWJsAjQDPpbZPjSX26AJB0l6ST8tdGYCQwI8fZF9g1Ij5oYV0zMzMzMzMzqxOKqHa3WG1ImgPMBS6MiFMlrUzagtcz92Bqz7VOB/pFxH7tOa91HJIOBM4DugCbRMQrLY1tamqK0aNHL7HYzDq7QWPHAvglDouRn3Hn4d/KzMzMbPGRNCYimsqd6/BvXYyILiWHvgO83N5JLls6RMRVpEozMzOzxWpcc/NHCa+OZHBjI4f27l3rMMzMzMwWiw6f6Com6RGgB3BwrWMxMzMz62zGNacOAk50mZmZWb3qVImuiNh2Mc9/+uKc38zMzJYeAxoaOtzWxY5YYWZmZmbWnjpVM3pJIWmmpGGLMMfpksq+KTCff1bSoIWd3zo2SQdJas7/lvrVOh4zMzMzMzMzaz+dqqIr2zwiXpK0PemtggACupLeCFiwSX6DYJtExKbtEOMnSNqU1AB9S1KsL5PeKnhnxQs7MUk9gN+Q3uC4EvAmcEVEnN3KdQcAVwOHRMTv87EVgV+S+rN9CrgROLrcmxQl9QL+DGwELAv8B/hxRDwMEBFXAFdI6thvYTDrpDpqT6J6Ma65mQENDbUOw8zMzMysw+pUFV3FIuLBiGiIiAagkJzqUTi2MEmuxegvwL1AI7A6cBQwo6YRtZGStvx7OQ9oADYGugO7kxJ8ldboCZwIPFty6gSgCdgM6A9sAZzSwjTNwPeA1YCewNnAXyR1xqSumdknDGhoYHBjY63DMDMzMzPrsOry//xL6g38FtgOmAqcHRGXFw3pImkkqdroReDAiHgqX/sacHBE3CdpK+ACUrJmNnArcGxEvC9JpIqlfYEVgQnA4Ih4piSWXsB6wOUR8X4+/HDR+aF5ve2KjgWwQa5cuxqYlefYHngK+DYp+XMAMBnYJyLGFsV/CbA/sD7wB+AkUpXUdsDjwF4RMS2P/3y+j03yPRwdEaPyuVE51kGk5NJnJG0H/IyUSHoHOCUiri/zM2yZz03L35/Pn0p+AVwI7F1yfDfSbzj1/7N3p1F2VdXax/+PdDFUIDQaDa1KJ6AEiR2KRAUVBFTkooTehle5iIDYgbmCAgoXQRFE1Cs9iqIovSAaWlECRAQFpAdDQpum0gAJz/thrYOH8lSXVFKVquc3xhmpvfdaa899KmQ4pnPNXeM6iZLA+nrHBWzPA+6u414GLKAkvFYFHu/m/i9x95w5g7IyJW/bisVpIPYkioiIiIiIoWOprejqxs+AR4HRwC7AMZLe23T9Q8AvKcmP84DfSFquxToLgIOB1YG3A+8F9q/X3ge8i1JhNJKyre6pFms8BdwLnCPpw5IW5v+K35VSwbQ68CzwJ+DWenwBJVHV7KPAtjW2HSlbPA+r419GqShD0hrApcBRlO/iUOBXkl7RtNaewH7ACOAJSiJqO9sjgC2ByZ3EfBNwtKR9Ja3f3QPWpOJYSoLyPy7XT/PxmpJW7mK924F5wEXAT2z3Ksk1WE1ub+e8adP6O4yIiIiIiIiIxWLQVXRJWotSubRDre6ZLOknlITN1XXYLbYvqONPAL4AvA24rnkt27c0HT4o6TRga+C7wPOU5M9GwF9s/6NVPLYt6d2UCqzvAK+RdD3wSdv/7OFjXdiIRdKFwP62z6rH5wMHdBj/fdvT6vXrgMebKr4upCTsAPYALmvqFXaVpEmUSrcz67kzbN9Z584HXgA2lfSw7ccovbda+RwlSXgA8CNJDwGfs315x4GSlgF+UK+/UIrlXuJy4POS/kjpu3VgPT8cmNHq5rbfKGkY8BFg+U5i7NKGw4cPusqUwVihFhEREREREdEwGCu6RgNP257VdO4hYI2m40caP9h+gX9Xf72EpA0kXSJpqqSZwDGUqihs/wE4mbJNcJqkH0laqVVAth+1fYDt1wHrUJrmn9WLZ2ouwZnb4rhjZ+Kejl8H+C9J0xsfSpLw1U3jm7+r2ZTKtc8Aj0m6VNJGrQK2Pdf2Mba3AFYDfgH8UtKqLYbvD9xu+0+t1gKOBm6jVI/dCPyGkmjsskrL9jzbPwO+ImmzrsZGRERERERExNJvMCa6pgCrShrRdG5t4F9Nx2s1fqh9nNas8zo6ldJXan3bK1G2/71YbmT7pJrI2YSyTfCL3QVn+xFKcmzTemo2pTKpEc+rulujDz0CnG17ZNNnRdvfbhrzkrcT2v6d7W0pybC7gObeZy3ZbiQJV6T0GuvovcBHakJxKmVL5HcknVznz62JwjVsv5ayHfQW2wt6+JzLAa/t4diIiIiIiIiIWEoNukRXTSTdCHxL0jBJbwQ+CTQ3TN9C0s71TXwHUfpe3dRiuRGUtyO218qlzzYuSHqzpLfW3l6zKf2g/iPxImkVSUdKWk/Sy2pz+k803e+vwCaSxtStdkcs0hfQO+cAO0p6v6Rl6vc1TtKarQZLGiVpJ0krUr6zdlo8cx07oX5Hy9fn+jwwndoovoN9KA3/x9TPJOBI4PC61hqSRtc3P74NmECLRvR17NskvbPe9+WSvkx52+Wfe/idRERERERERMRSatAluqrdgHUpVVoXAl+3fVXT9d9StuA9Q+ndtbPt51uscygwHphFqVw6v+naSvXcM5StkU8Bx7dY47kay+8pSbM7KEmifQBs3wN8o17/J3B97x514dWk4IcolWpPUCq8vkjnfy9eRulnNoXyNsut+Xdz/v9YHjid8mbGKZTm+B+03d4ijum2pzY+lO9spu1G/63XUZKXsym9w75i+8rGfEmXSzqsHq5AqZh7ilLFt329b6uKvYiIiIiIiIgYRGS7+1EDhKR5lCTRSbYn9Hc8sfSRtC9wIjAM2Nj2/Z2NHTt2rCdNmrTEYlsSxt12G5Pb2xnT1rGtW98bP2oU+43+j9Z3MYg1XnYw2F7iELEwBup/DwM1roiIiIjekHSL7bGtri1Vb120Pay/Y4ilm+3TKZVmsRhNbi+Fe0l0RURERERExJK0VCW6ImLRjWlrW+z/T36jYiAiIiIiIiJiSVoqe3RJsqTZko5ehDUelLRNX8a1tKvf63r9HcfiImkbSe2SXsjvPiIiIiIiImLwWSoTXdVmtg9vPiFpxZrIuKy/gupI0j41gXRCh/MfrufP6OE6b5F0maTpkp6W9Jfab2ph45oo6VMLO7+btZeX9B1Jj9bfxwOSTuzBvK3rd3JU07nD6hqNz9yaqFq9kzXGSLpO0ox6//9pXLP9e9ttwMN98qARERERERERMaAszYmuVnahNKt/n6RX93cwTe4DPiapeavoXsA9PZks6e3AH4BrgPWA1YDPAtv1NhAVi/v3/lVgLPAWYATwbqDLvWySlgO+B/y5+bztY2y3NT7AscBE2092stR5wLXAqpS3Qn5W0k6L8jARERERERERsXQYbImuvYEfArcDuzdfkLSnpIckPSWpYyXYWyT9qVZLPSbpZEnLN123pP0l/VPSLEnflPS6OmempF80j29hKvA34P11vVWBLYGLOsTxTkk31jgekbRPvfS/wJm2j7X9pItbbO9a560i6RJJT0h6pv68ZtO6EyUdLekGYA5wNrAVcHKtkjq5KYxt6nM+I+mUmhhboVaRvaFpzVfW6qpXtHjeNwMX2p5SY33Q9lldfD8AXwCuBO7qbIAkAXsCZ3axzrrAubYX2L4PuB7YpJt7R0RERERERMQgMGia0UtaGxgHHAA8TUl6HV+vbQycCmxPqRj6FrBm0/QFwMHApHr+cmB/4LtNYz4AbAGsBdxKSVTtDjwF/AnYja4TMGdRqrguBT4O/JZSfdYc/+XAfsAFwErAWpKGA28HJnSx9ssobxLcFVgG+ClwMvDhpjF7UirA7gYErAGcY/snHdbagZKoWgm4BbjY9hWSfg7sAXy5jtsN+L3tJ1rEcxNwiKTngOuAO2y7s+AlrQN8AnhTjbszWwGjgF91Mea7wF6SJgCvpXx3x3UxvlN3z5kz6JqqT25vZ0xbW3+HEREREREREbFYDKaKrr2A223/HfgZsImkxqvldgEusX2t7WcpSaMXGhNrddRNtufbfhA4jbLtrdmxtmfavhO4A7jS9v22Z1ASVN29xu5CYJyklWusHSucdqckjn5m+3nbT9meDKxC+T091tnCdeyvbM+xPQs4ukX8Z9i+sz7j813E+W3b020/DPwRGFPPnwmMb9r2uCelMqyVb1G2GO5OSR7+S9LeXdzzJGCC7fYuxkBJXl7QzbhLKL/vuZTqsP+zfXM36w4ZY9raGD9qVH+HEREREREREbFYDJqKLkry6McAtqdIuoaSGLkNGA080hhoe7akpxrHkjYATqD0lRpO+V5u6bD+tKaf57Y4flVXwdmeK+lS4GvA6rZvkNTcY2stSi+vjp6hJOVeTSfb+mrV14mUqrNV6ukRkpaxvaAeP9JqbgtTm36eA7TV+P8saTawtaTHKL3CLmoxn3rPU4BTJL2cUq31U0l/sf2PDrHvCIywfX5XQdV1/gv4UBdjVgWuoFT1nUf5nVwgaZrtH3S1fisbDh/OxM27y19GRERERESS2YIyAAAgAElEQVRExEAxKBJdkrYE1ge+KukL9fQISlXXoZRqqNc3jR9OaejecColIbab7VmSDqJUBfW1syhN5Y9sce0RSvP2l7A9R9KfgI9SKqxa+QKwIfBW21MljaE8j5qX6rh0L2OHUtW1ByUZdoHted1NsD2XkvA6EtgY+EeHIe8FxkpqJNhWBhZIeoPt5qTWzpQtqRO7uN1rgQVN/cAerVsutwd6neiKRTO5vX2Jbf0cP2oU+40evUTuFREREREREQPXYNm6uDdwFSWRMqZ+NqVUZ21H6Xm1Q232vjzwDV767COAmUC7pI0obzRcHK4BtgW+3+LauZRG8LtKWlbSajVhBfAlYB9JX5S0GoCkzWoSpxH/XGB6rWr6eg9imUZJDPXG2cBHKMmuTpvLSzpI0jhJL6/PsneNsVXWYwKwAf/+vV1Eqczbt8O4vYGzuur1RXmLpSSNl/QySa8CPgb8tWePF0ujye3tnDdtWvcDIyIiIiIiYtBb6iu6JA2jNGHfy/bUDtfOBva2vYuk/6ZsZ1uRsk3x0aahhwI/oiSUbgPOB97T17HWJM3VnVx7WNL2lAb6PwFmULY5TrZ9o6T3UCrBviZpAfBPyvZAKA3YzwOeBKYA3+Gljehb+R5wpqTPAmfbPrAH8T8q6VbKtsXruhg6t8awHqVy7B7go7bvb7HmLGBW41jSXGC27aebzq1B+X3s33G+pB/WdT5je6aknSn9wU6tcVxM6VkWS9iYtrYlsvVzsL0wICIiIiIiIhaeui6QGZgkzaO8sfAk2129jTD6mKSfAlNsf62/Y+ktSe+lvLFxBWB7251tBQVg7NixnjRp0hKJbbBpJJ+WZKIr/dT6X34XEf82UP97GKhxRURERPSGpFtsj211bams6LI9rL9jGIokrUvplbVU/q9j21cDI/s7joiIiIiIiIhYPAZLj65YzCR9E7gD+F/bD/R3PBERERERERERHS2VFV2x5NUtotkmGhEREREREREDViq6IiIiIiIiIiJiUBhUiS5JljRb0kK/ZU/SOEmPdj9y0UjaStLdi/s+i5OkiZI+1d9x9IakT0pqr39X1uvveCIiIiIiIiKi7wyqRFe1me3DayKpvX5m18RGe9Nn7f4M0vZ1tjfs7HpT0q5d0lOSrpb0sSUZ46KQNFLSTyVNlTRL0j2SvtzF+ObnbZf0k6ZrH5d0t6QZkh6XdKaklbpYaxlJR0maUu99m6SRALb/z3Zb3z5tRERERERERAwEg7ZHl+3rgDZ48W2BDwAjbc/vx7B6azPb90paHdgOOFnSRraP7O1CkpZdws9+IrAi8HpgBrABsGk3czazfW+L8zcA77D9pKQ24DTgKODATtY5EtgSeDvwMLAJMK+3D3D3nDkvvoY9emdyeztj2pJPjIiIiIiIiCVrMFZ0dUvSvpL+Uat97pf0/7oYe6Ckv0tas+NWPUn7SLq+6diS9pf0z7r2NyW9TtKfJM2U9AtJy9exPd4iaftJ22cDnwW+Kmm1usaDkrZpuv8Rks6pP69b4/mkpIeBP9Tzv6xVVjMkXStpk6b5Z0g6RdKlNf4/S3pd0/VtJd1V554MqIuw3wycZ/sZ2y/Yvsv2BT153hbP/4jtJ5tOLQBabjuUtApwEPBp2w+5uMN2rxNdsfDGtLUxftSo/g4jIiIiIiIihphBW9HVjceBHYD7gXcBl0u62fatzYMkTQA+Amxt+wmpq7zOiz4AbAGsBdxKqSzaHXgK+BOwG3DmQsb9W8rv7C3A5T2cszWlquqFenw58AngOeBY4FxgTNP43eoz3FrjPBr4eK0q+1Wd+1vgAOAzwNmd3Pcm4OiaeLre9j97EOu1kl4G3AgcYvvBxgVJ7wQuBVYC5lB+L628AZgP7CLpYGAm8D3bp/Tg/i+x4fDhTNx8895Oi4iIiIiIiIh+MiQrumxfavu+Wu1zDXAlsFXTEEk6AXg/8G7bT/Ri+WNtz7R9J3AHcKXt+23PoCSZFjpzYvt54Elg1V5MO8L2bNtz6xo/tT3L9rPAEcBmklZuGv9r23+p2xybk2DbA3+3fUGN47vA1C7u+7k6/wDg75LulbRdF+O3BtYFNgKmAJdIejERa/t62ysDawL/CzzYyTprAitTtkq+BtgFOELStl3cOyIiIiIiIiIGgSGZ6JK0naSbJD0taTolibN605CRwH7At2qCqjemNf08t8XxQjcukrQc8Arg6V5Me6Rp/jKSvi3pPkkz+XeyqPnZm5NXc/h3vKOb17Lt5uOObM+1fYztLYDVgF8Av5TUMkln+1rbz9meDnyekqR6fYtx/wKuAH7eya3n1j+/UWO4vY7dvrNYIyIiIiIiImJwGHKJLkkrULbgHQ+Msj0SuIyX9pt6hrK18XRJ72g6PxsY3nT8qsUcbkcfomzL+0sv4nHTz+PrGttQqp7Wred7sifzMcp2zDKh7ONcq/PhTQHYM4FjKM3pX9OTOZS4O4trWeB1nVy7vWl+RERERERERAwhQ7FH1/LACsATwPy6ne59lG2GL7I9UdLuwIWSdrT9Z2AysLOkn1AqnD7JSyu2FotaBbUdcAJla+RT9dJkSv+sy4HNKNv0ruhiqRHAs5R+YcMpyaeeupTy1sedgYuA/6aLRF/tb3YF8FdKQvXzwHTg7hZjNwGWA/4GvJzyRsV/Af+o13cHrqNUkK1N6Rt2dav72r5P0nXA4ZIOBF4LfIzSeywGqcnt7XlD5gCQt21GRERERER/G3IVXbZnAQdSttI9Q6lyuqiTsVcB+wIXSdoCOJHSxH0apVH7uYs53L9KagfuBT4FHGz7f5quT6BUNj0DHAmc1816ZwEPUZJIf6c0jO+R+tbD/wK+TUmUrQ/c0NUU4HRKT7EpwLbAB223txg7Cjif0jj+fkql2Q61FxjAxpQG9e31nncDn25MlnS5pMOa1tsNWKfGeSkwwXbLxFhE9J28bTMiIiIiIvqbSqulwUHSPErF0km2J/R3PDHwSNqXkrAcBmxs+/7Oxo4dO9aTJk1aYrHFwmlUcuUNmRExkAzUf5sGalwRERERvSHpFttjW10bVFsXbQ/r7xhiYLN9OqXSLCIiIiIiIiIGmSG3dTEiIiIiIiIiIganJLoWgSRLmi3p6EVY44e1cXssAZLuk/ScpHP6O5aIiIiIiIiI6FtJdC26zWwfDiBp3Zr8au/w+Vhnk21/xvY3F+bGkiZK+tTCBr44SfqQpMmSZkp6UtLVktbtYvybJF1bv69pkj7fdO2bkv4mab6kI3p4/+Ul3SXp0ebztl9H7942GRERERERERFLiUHVo2sAGWl7fneDJC1je8GSCGhJkrQe5Q2POwN/ANqA9wEvdDJ+deAK4GDgAmB5YM2mIfcCXwI+04swvgg8Xu8dEREREREREUNAEl1LkKQzgLnAOsDWwIck7QE8avtrksYB51DeCvhlYAFwWG2g3pv7vAw4DPg08HJKEulztmfUqqoHgP8HHAEION72d5rmfqnOHQlcDXzG9tOSTgb2abrVMOAo20d0CGEM8IDtq+vxLOBXXYR8CPA72+fW42eBfzQu2j6zxrZ7D5//NcAedd0f92ROK3fPmfPi26kGuvGjRrHf6NH9HUZEREREREREv8rWxSVvPHA0MAK4vsX1VwErA2sAnwROkbRKL++xT/28G3gtparp5A5j3g2sT6m0+oqkber5A4EPUxJxo4FngFMAbB9gu812G/DOeu23Le5/K7CRpBMlvVtSd1VVbwOelnSjpMclXSxp7d48cAffpyT65i7CGkuNye3tnDdtWn+HEREREREREdHvUtG1eDwpqfn47bYbFUq/tX1D/Xleh3EAzwPfqFsfL5PUDmwI3NSL++8OnGD7fgBJXwXukLRv05gjbc8G/ibpdGA34PeUSq8DbD9a5x4BPCxpz8Z2TEmvAH5DqRL7j5In2/fX6rRDgF8AIyT9vK7b3iLeNYE3AdsCfwOOA34GvKMXz0yN7SPAsrYvrDEstA2HD2fi5psvyhJLxNJSdRYRERERERGxuCXRtXis3kWPrke6mftUh7lz6H2fqdHAQ03HD1F+16M6ieMh4A3153WACyU199NaUOf+S9JylD5a59n+eWcB2L4J2BVA0puB84HDga+2GD4XuND2zXX8kZRk4cq2Z3TzrC+StCIlSbZ9T+dERERERERExOCRrYtLnpfAPaZQElYNawPzgeb9bWt1uD6l/vwIsJ3tkU2fYbb/Va9/n9Jz62s9DaYmsH4NbNrJkNt56ffS+Pk/yt26sT6wLnCdpKn1nq+WNLWrNz5GRERERERExOCQRNfSb1lJw5o+y1G2/R0s6TW1P9YxwPkdKsUmSBouaRNgX0rFFcAPgaMlrQNlm6KkD9Wf/x+ld9d42y3foFjHvVPSpyW9sh5vBOxE59svTwc+ImlMjX8CcL3t6XX+cpKGUf6+Np53mRbr3EFJ4I2pn09Rkntj6L6SLiIiIiIiIiKWckl0LR7TJbU3fQ5ZjPc6lbL1r/E5HfgpcDZwLeUNi/OAz3WYdw1wL+WtisfbvrKe/x5wEXClpFmU5NRb67XdKM3tpzQ922EtYppOSWz9rfYYuwK4kLKt8D/Y/gOlefylwOPAepSm/Q0/rs+2G2X741xgTwBJW9V7YHu+7amND/A08EI9XtDJ9xcRERERERERg4TsJbGTbnCSNA94FjjJ9oT+jqcn6ha+B4DluugjNmhJupvyRstf2P5EV2PHjh3rSZMmLZnAFsG4225jcns7Y9p628ptcGg8+9Lw4oCIGDoaLwoZaP82DdS4IiIiInpD0i22x7a6lmb0i8D2sP6OIXrH9ob9HUP0rTFtbYwfNar7gRERERERETHoJdEVMQikoikiIiIiIiIiia4hx/aD9P5thhERERERERERA96gaEYvyZJmSzp6EdZ4UNI2fRlXDCySNqgN9BdI+lR/xxMRERERERERfWtQJLqqzWwf3nxC0oo1sXFZfwXViqRXS/o/SY9JmiXpLklHSlqxv2PrK5IOk/RA/f4flXR+F2MnSprX9CbHuztcHy7pB5KelDRD0rXd3Pvjkv5Rk5/3SdoKwPY9ttuA6/rkISMiIiIiIiJiQBlMia5WdqG8FfF9kl7d38EASFoV+BPwcuDttkcA2wIjgdctxHrLdjiWpH79vUraG9gT2KYmlsYCV3cz7QDbbfXTsWH8j4BVgdfXPw/u4t7bAscC+wIjgHcB9y/Ug0RERERERETEUmWw9+jaG/ghsB2wO3B844KkPYGjgDbghOZJkt4CfI+SWJkL/Ao4xPZz9bqB/6YkXF4FfBc4AzgH2AS4AtijMb6DQ4BZ9foLALYfAT7fdP/vATsDKwP/BA6yfV29dgSwKTAP2Ak4RNIewA3AOOBNwBtqFdOXgDWBJ4BjbZ9W11i9xvtO4AXgTmBr2y9IWqs++1aUROjPbB9Qk2eHAZ+mJOmuAD5ne0aLZ3wz8Dvb99Xnm0pJVvWapA3rc65pe2Y9fUsXU44EvmH7pnr8r4W5L8Ddc+a8+Br2gWxyeztj2tr6O4yIiIiIiIiIfjdoK7okrU1J/JxbP3s1XdsYOJVSdTQaWI2SEGpYQElirQ68HXgvsH+HW3wA2AJ4GyWh9CNKMm0tSiJqt05C2wb4dSPJ1YmbgTGU6qXzgF9KGtZ0/UPABZQqsHPruT2B/ShVTA8BjwM7ACtRqptOlPSmOvYLwKPAK4BRlASWJS0DXFLnrwusAfy8ztmnft4NvJaSIDy5k/hvAvaS9EVJY+u63flW3Zp4g6RxTeffWuM5sl7/m6SPtlqg3mcs8ApJ99YtkydLenkP7r/UGtPWxvhRo/o7jIiIiIiIiIh+N5gruvYCbrf9d0nTgeMkbW77NsqWxktsXwsgaQJwQGOi7eaKoQclnQZsTancaji2VhjdKekO4Erb99f1Lgc2B85sEddqwGNdBW77nKbD70j6GrAh8Nd67k+2f1N/nisJ4AzbdzbNu7Tp52skXUmp0roVeB54NbCO7XupPatqJdto4Iu259e519c/dwdOaHrGrwJ3SNq3aeyL8deqt32BI4B5kv7X9rc7eeQvA38HngM+DlwsaUytCFuTkjj8VY3t7cClkv5u+x8d1hkFLEf5/W5Vn/O3wNeAw+mlDYcPZ+Lmm/d2WkRERERERET0k0Fb0UVJdJ0LYHsKcA1lKyOUhMkjjYG2ZwNPNY7r2/kukTRV0kzgGEp1V7NpTT/PbXHc2V6ypyhJpk5J+kJtpj6jJulW7nD/R1pMe8k5SdtJuknS03WN7ZvW+F/gXuBKSfdL+ko9vxbwUMfEVTWaUlnV8BAlUdqylMj2uba3oVSdfQb4hqT3dzL2z7Zn2X7W9pmUbZjb18tzKQmro2w/Z/sa4I/A+1osNbf++X3bj9l+krItdfsWYyMiIiIiIiJikBmUiS5JWwLrA1+tyaqplC1wu9Xm7Y9RkjqN8cMplVYNpwJ3AevbXomytU99FN7vgY901jC+9tb6MrArsIrtkcCMDvd3i6kvnpO0AqUC6nhgVF3jssYaNan0BduvBXak9Pl6LyVZtnbHBvfVFGCdpuO1gfm8NMH3n0HZz9v+JXA7pTKrJ8y/n/f2Hs7B9jOULZmtvp+IiIiIiIiIGOQGZaKLUrl1FbAxpdfVGEqSZTilMf0FwA6S3ilpeeAbvPS7GAHMBNolbQR8tg9jO4HSN+tMSesASFpD0gmS3ljvPZ/SQH5ZSf9Tx/fG8sAKdY35krajqQJK0g6S1lPZ8ziT0pNsAfAXShLw25JWlDRM0jvqtJ8BB0t6jaQ2SpXb+a2qvyTtI+mDkkZIelm9/ybAn1uMHSnp/fVey0ranfKmxN/VIdcCD1OSlsvWeMY1Xe/odOBzkl4paRXgIErfsYiIiIiIiIgY5AZdoqs2bd+Vsn1tatPnAeBsYO/ay+q/KY3eHwMalUANhwLjKW9H/DFwfl/FZ/tpYEvKdrw/S5oFXE2p2rqXksC5HLiHsj1wHq23KnZ1j1nAgcAvKM82Hrioacj6lMqyduBPwA9sT7S9gFLhtR4lufQo8LE656eU7+9a4IEa1+c6CWEmpQruYWA6cBzwWdvXtxi7HOXtl08AT9Y1P2z77vosz1Oa729P+Y5+DOxl+y4ASYfVnmgN36Q0878H+AdwG3B0599WRERERERERAwWspf+XV6S5gHPAifZntDf8cTAJGl9ShJseWB/22d0NX7s2LGeNGnSkggtIiIGmXG33QYw4F5qMlDjioiIiOgNSbfYHtvq2qB466LtYf0dQwx8tv9JaY4fEREREREREYPQoNu6GBERERERERERQ1MSXRERERERERERMSgM2kSXJEuaLWnANyKXNE7So92PbDnXktbr43iOkHROF9fvlDSuL++5JEhaQVK7pOclHdXf8URERERERERE3xq0ia5qM9uHN5+QtGJNdlzW1zeTtFVdu70m2dx03C5p7b6+Z3+wvYntia2uSTqjYxJJ0rr1u2jZE64mzpq/p/mSLm66vqOkO+q1GyVt3FlsktaQ9FtJT0t6VNJnmuJ+1nYbcG5vnzkiIiIiIiIiBr7BnuhqZRfKGxrfJ+nVfbmw7etst9Vkyib19MjGOdsP9+X9BouaOGt8byOAh4FfwotvSjwX+AylkfzFwEWdJc2Ac4AHgFHAB4FjJL17MT9CRERERERERAwAg+Kti720N/BDYDtgd+B4SW8DfgOsYXsBgKSPAEfafqOktwDfA14PzAV+BRxi+7me3lTSvsCXgDWBJ4BjbZ/WydgDKYmd9wGje3DvbSRdDqwOnAccYNuSXgf8GNgMMPA74L9tT6/3+TJwILASMAXY3/bVdc3lJZ0FfISSeNrb9qQ670HgU7Z/39Pn74V3Aa+szwnwfuA629fXex8L/A+wNXB180RJbcA4YFfbzwN/lXQB8Angj70N5O45c158DXt0bfyoUew3enR/hxERERERERFD3JCq6KpbB8dRKoTOBfYCsH0TMBt4T9Pw8ZSkEcAC4GBKIuntwHuB/Xt5+8eBHShJpX2BEyW9qUWME4B9gK1tP9rDe+8AvJmS0NqVkhwCEPAtSrLs9cBawBH1PhsCBwBvtj2iznmwac2dgJ9TqqguAk7u5fMurL2BC2zPrseqHzocb9pirjr8SRdjo49Mbm/nvGnT+juMiIiIiIiIiCFX0bUXcLvtv0uaDhwnaXPbtwE/A3YDrpI0AtgeOBTA9i1Nazwo6TRKRdF3e3pj25c2HV4j6UpgK+DWek6STgDeArzb9oxe3PvbtUpruqQ/AmOAK2zfC9xbxzxR1/96PV4ArABsLOkJ2w92CPl625fVwM4GDurpswKHSjqg6bhHCVVJwylbS3dqOn0V8O3a/P5G4MvA8sDwjvNtz5J0AzBB0heBjYGPUiroem3D4cOZuPnmCzN1SEnVW0RERERERAwUQ6qii5LoOhfA9hTgGkoFEZTqrZ0lrQDsDNxq+yEASRtIukTSVEkzgWMoFVY9Jmk7STfVJunTKYm05jVGAvsB32okuXpx76lNP88B2urcV0r6uaR/1bnnNObWJNhBlAqvx+u40V2sOayLvlgdHW97ZOMDvLGH83YGnqb8Xqhx3kX5HZ0MPFbj/zvQ2VsqdwdeAzwCnEr5fS/UGy0jIiIiIiIiYukyZBJdkrYE1ge+WpNGU4G3ArtJWtb234GHKL27mrctQkmY3AWsb3sl4DBeuj2uu3uvQOk5dTwwqiZ/LuuwxjOULYinS3pHH937W5TeXG+sc/donmv7PNvvBNap447t6TMtJnsDZ9l280nbF9je1PZqlIq0dYCbWy1g+yHbO9h+he23AqsBf1ncgUdERERERERE/xsyiS5KEuUqyna2MfWzKWUL3HZ1zHmU5uzvor71rxoBzATaJW0EfLaX916esk3wCWC+pO0ojeZfwvZESkXShZLe2gf3HgG0U7Y0rgF8sXFB0oaS3lOTcPMoje4X9PK5+oykNYF3A2e2uLaFpGUkvQI4Dbi4Vnq1Wuf1kkZIWl7SHpTv+YTFGXtEREREREREDAxDokeXpGGUJu172Z7a4drZlCTYxZQ+Xd8CLrf9ZNOwQ4EfUd6aeBtwPi9tXN+l2jvqQOAXlITXxZQG763GXlXf0HiRpEafsIW995HAWcAMSq+usymN7alxfJvSpP55Sv+r/Xr6TIvBnsCfbN/X4tr3KI32n6ckIA9pXJC0O3CY7U3qqfcDh1MSmLcBH7C9UD26oucmt7cPml5deYNkRERERETE0ksddokNGpLmAc8CJ9me0N/xRP+r1WvTgOWA42wf2dX4sWPHetKkSUsktqXZuNtuY3J7O2Pa2vo7lEXWeI68hCAiFlUj+T/Q/j0ZqHFFRERE9IakW2yPbXVt0FZ02R7W3zHEwGL7WUrT/+hjgyU5NFiq0iIiIiIiIoaqodSjKyIiIiIiIiIiBrEhk+iSZEmzJR29BO61laS7F/d9+oukfSRd399xLAxJR9a/B5Y0aCsaIyIiIiIiIoaiIZPoqjazfXjjoCY71uvrm9i+zvaGCzNX0hmSnpM0q37ukPQtSSv3dZyLg6R1WyWR6nMd1cmc3SW1N33m1DW2aBrzJknX1uvTJH2+k7U2ljRJ0jP183tJGzeu2/46sEmruRERERERERGxdBtqia6lxXG2RwCvAPYF3gbcIGnF3i6kYkD/nm2fa7ut8QH2B+4HbgWQtDpwBXAasBqwHnBlJ8tNAXYBVgVWp7zd8ueL9wkiIiIiIiIiYiDI1q1K0luA7wGvB+YCvwIOsf1cvW7gv4GDgVcB3wXOAM6hVAhdAexh+zlJ44BzbK9Z544Gvg+8C2gHTrR9Uncx2Z4H3CxpJ+AeStLrZElHAOvZ3qOuvy7wALCc7fmSJgI3AOOANwFvkLQV8CVgTeAJ4Fjbp9X54+pznAh8GVgAHGb79Hp9NeD0ut5dwO969q0utL2Bs/zvV4IeAvzO9rn1+FngH60m2p4OTIeS5KM8y0JV7d09Z06ak/fAYHnjYkRERERERCz9BnSlzxK2gJLEWh14O/BeSmVRsw8AW1AqrL4E/AjYHVgL2BTYreOitZrqYuCvwBp13YMkvb+ngdmeBVwFbNWL59kT2A8YATwEPA7sAKxESZidKOlNTeNfBaxcY/wkcIqkVeq1U4B5wKuBT9TPYiFpHUpC8Kym028DnpZ0o6THJV0sae1u1pleY/4+cMziijfKGxfHjxrV32FEREREREREpKKrwfYtTYcPSjoN2JpSudVwrO2ZwJ2S7gCutH0/gKTLgc2BMzss/WbgFba/UY/vl/Rj4OP0rjJqCiXJ1lNn2L6z6fjSpp+vkXQlJXF2az33PPAN2/OByyS1AxtKuhn4KPAG27OBOySdSUlGdeXJUlD1ouHAcT2Iey/gOtsPNJ1bk1KZti3wt7rOz4B3dLaI7ZF1q+felERfr204fDgTN998YaZGRERERERERD9IoquStAFwAjCWkpRZFrilw7BpTT/PbXH8qhZLrwOMrhVGDcsA1/UyxDWAp3sx/pHmA0nbAV8HNqBU8g2nJI0anqpJroY5QBulT9iyHdbrSeJo9eb1JJ3Rw7j34j8rsOYCF9q+ua51JCWRtrLtGZ0tZHu2pB8CT0h6ve3HexhDRERERERERCyFkuj6t1OB24DdbM+SdBClqfmiegR4wPb6C7uApDZgG+Doemo2JVHV0CrB1uhvhaQVKD3H9gJ+a/t5Sb8B1GJeR08A8ynbM++q57rcNriwJL0DGA1c0OHS7TQ9T9PPPYm/kdRbg7J9M6JLk9vbF7k32/hRo9hv9Og+iigiIiIiIiJ6Kj26/m0EMBNol7QR8Nk+WvcvwExJX5b0cknLSNpU0pu7myhpBUlbAL8BnqE0hAeYDLxL0tqSVga+2s1SywMrUJNWtbrrfT0J3vYC4NfAEZKGS9qYsh1wcdgb+FXtSdbsdOAjksZIWuVNEH4AACAASURBVA6YAFxfG8+/hKRtJW1ev+eVKFV6z9BJ8/qIvja5vZ3zpk3rfmBERERERET0uVR0/bs66FBKc/kvUSq7zgfes8iL2wsk7Qh8h/JmxBWAu4GvdTHtS5I+T0lEPghcAuxSe2Rh+ypJ51MqnZ4EjgV26iKGWZIOBH5R738xcFEvHuMASrJpKqWq63Tg3b2Y3y1Jw4BdKf3AXsL2HyQdRukzNhy4HhjfNPdO4Jj6VsaRlAb0a1K2PN4MfKC+wTKiW2Pa2hapN1ve1BkREREREdF/ZLv7UYOApHnAs8BJtifUap8ZwCqtKoNicJL0deAQSsJvxVqx1tLYsWM9adKkJRZb9L9GkqovEl15kUHE0DZQ/y0YqHFFRERE9IakW2yPbXVtyFR02R7W4dTHgPuS5BpabB8JHNnfcURERERERERE3xsyia5mkm6kbHH7VH/HEhERERERERERfWNIJrpsb9nfMURERERERERERN8aUm9dlGRJsyUdvZjWX1tSu6RlFsf6sWgkbVB/PwskpZovIiIiIiIiYpAZUomuajPbhzefkLRiTYBctigL237YdltXDc4ljZc0qd7vMUmXS3rnotx3IJE0sWMSSdI4SY92Mae9w2eBpO/Xa+vWBGXz9QldrLWqpAtrQvMhSS++ndH2PbbbgOv64FEjIiIiIiIiYoAZklsXW9iF8kbG90l6te3HFsdNJB0CfAX4DPA74DngA8CHgOt7udaytud3d25pUJNPQEk6AtOAX3YYNrKHz3YK5XsdBYwBLpX0V9t39lW8ERERERERETEwJdFV7A38ENgO2B04vnFB0oOU5MmewOuAnwOHAWcA7wT+DPyX7WckrQs8ACzXIgm1MvANYF/bv266dHH9IOktwPeA1wNzgV8Bh9h+rl43cABwELCspH2Bc4DvAwcDV0k6EDgbeCvl93sD8Bnbj9Y19gH+B3gF8CTwNdvn1mufBg4B1gQeAfawfauk1wOnUhJH/wK+avuiXn3DPbcL8DgLUXVVk2QfBTa13Q5cL+kiyu/uK71d7+45c158DXsMDZPb2xnT1tb9wIiIiIiIiBiQhuLWxZeQtDYwDji3fvZqMeyjwLbABsCOwOWUZNfqlO/wwB7c6u3AMODCLsYsoCSsVq/j3wvs32HMhylJrI3r8auAVYF1gP1qPKfX47UpCbOT67OuCJwEbGd7BLAlMLle+y/gCMrzrwTsBDwlaTlKIu5K4JXA54BzJW3Yg2deGHsDZ9l2h/MPSXpU0umSVu9k7gbAAtv3NJ37K7DJ4gg0Bp8xbW2MHzWqv8OIiIiIiIiIhZSKrpLYud323yVNB46TtLnt5lKe79ueBiDpOuDxxnVJF1ISUt1ZDXiyq+13tm9pOnxQ0mnA1sB3m85/y/bT9d4ALwBft/1svd6oBKOOORr4Y9P8F4BNJT1ct2g2tml+CjjO9s31+N46fyugDfi27ReAP0i6BNiNkhhr5SRJxzcdLwtM7+y5m2Jduz7vJ5tOPwm8mZKQW41SXXcu8P4WS7QBMzqcmwGM6O7erWw4fDgTN998YabGEDe5vT3VgIto/KhR7Dd6dH+HERERERERS5khX9FFSXSdC2B7CnANpaqo2bSmn+e2OO7JXqengNUldZpcrG8FvETSVEkzgWMo1V3NHulw/ITteU1rDJd0Wm3EPhO4FhgpaRnbs4GPUXqEPSbpUkkb1alrAfe1CGs08EhNcjU8BKzRxbMeaHtk4wPs0MXYZnsB19t+oHHCdrvtSbbn12TjAZReaiu1mN9OqUZrthIwq4f3j4gBYHJ7O+dNm9b9wIiIiIiIiA6GdEWXpC2B9YGvSvpCPT0C2ETSoX3c2P1PwDzK1sMLOhlzKnAbsJvtWZIOovSsatZxS1/H4y8AGwJvtT1V0pi6pgBs/w74naSXA0cBPwa2oiTQXtcipinAWpJe1pTsWhu4p8XYRbUX8O1uxjSeVy2u3UPpXba+7X/Wc5sBaUQfS9SYtrZUAy6CVMNFRERERMTCGuoVXXsDV1H6XY2pn02B4ZTG9H3G9gxKE/hTJH24Vl4tJ2k7ScfVYSOAmUB7rbT67ELcagSlymy6pFWBrzcuSBolaafaq+tZSgXUgnr5J8ChkrZQsZ6kdSjN9mcDX6rxjqP0Kfv5QsTWqZp0XIMOb1uU9FZJG0p6maTVKD3GJtbv8yVqxdqvgW9IWlHSOyhvtDy7L2ONiIiIiIiIiIFpyCa6JA0DdqX035ra9HmAkhjpuH1xkdk+gfJWw68BT1CqqA4AflOHHAqMp2y1+zFw/kLc5rvAyym9rW4Crmi69jJKxdcU4GlKP6z9a2y/BI4Gzqv3/w2wan3j406UxN+TwA+AvWzftRCxdWVv4Ne2O24zfG19hlnAHZQE3W6Ni5IOk3R50/j9Kc//OPAz4LO2U9EVERERERERMQToP19uN3hJmkdJlJxke0J/xxNLlqT1gZuB5YH9bZ/R1fixY8d60qRJSyK0GEQa2+6ydXHh5TuMwWCg/j0eqHFFRERE9IakW2yPbXVtSPXosj2sv2OI/lP7do3s7zgiIiIiIiIiYvEYslsXIyIiIiIiIiJicEmiq49JsqTZko7u71gWhaQ7a+P5QUXSJyW119/Tev0dT0RERERERET0nSS6Fo/NbB/eOFhcSRVJ+9S1T+hw/sP1/BkLu7btTWxPXMi4/uN5JR0h6Zwu5iwj6ShJUyTNknSbpP/YZijpD3X9TrfdShoj6RZJc+qfY5qe6/9sty3Mc0VERERERETEwJZE19LvPuBjHRI/ewH3LMxiXSWQFrMjgS2BtwMrAXsC85oHSNqdbvrKSVoe+C1wDrAKcCbw23o+IiIiIiIiIgaxJLqWMElnSDqq6XicpEebjh+UdKik2yXNkHS+pK6a6E8F/ga8v85flZIwuqjDfXeq2xGnS5oo6fUd7vllSbcDsyUtW89tU68fIekXks6q1VZ3Smr5doOFIWkV4CDg07YfcnGH7XlNY1YGvg58qZvlxlGSYd+1/aztkwAB7+mreCMiIiIiIiJiYBpSb11ciuwKfIBS0XQDsA/wwy7Gn0Wp4roU+DilounZxkVJGwA/Az4MTAQOBi6WtLHt5+qw3YAPAk/ani+p4z12AnYG9gWOAk4G3rawD9jBG4D5wC6SDgZmAt+zfUrTmGOAUymJva5sAtxu203nbq/nr+hNUHfPmfPia9gjempyeztj2rI7NiIiIiIioj+komtgOsn2FNtPAxcDY7oZfyEwrlY97UVJfDX7GHCp7atsPw8cD7ycUvnVfM9HbM/t5B7X277M9gLgbGCzbmK6tVaPTZc0HfhKF2PXBFYGNgBeA+wCHCFpW4BaPfYO4Pvd3BOgDZjR4dwMYEQP5kYssjFtbYwfNaq/w4iIiIiIiBiSUtE1MDVXLc0BRnc12PZcSZcCXwNWt32DpO2ahowGHmoa/4KkR4A1msY80suYhkla1vb8Tsa/yfa9jQNJRwCdNeRvJNe+URNtt0v6ObC9pKuBHwCf76TSrKN2So+vZisBs7qb2NGGw4czcfPNezstIiIiIiIiIvpJKrqWvNnA8KbjV/XRumcBX6BUW3U0BVincaCSLVoL+FfTGHectATd3kUMKwFjgfMlTQVurucflbRVi/F3Am/USzNib6znIyIiIiIiImIQS6JryZtMqVRaVdKrKE3Y+8I1wLa03t73C+CDkt4raTlKQuxZ4MY+uvcisX0fcB1wuKQVaqP8jwGXULYdjqZs3xwDbF+nbQH8ucVyE4EFwIF1rQPq+T8svieIiIiIiIiIiIEgia4lp1GtdDbwV+BB4Erg/D5ZvLi69vXqeO1uYA9KEuxJYEdgx6ZG9APBbpSqs6coTfUn1Oex7amND/BEHT+tEb+kyyUdBlDPfZjSq2w68AngwwPsWSMiIiIiIiJiMdBLX04Xi0rSPEq11Em2J0haiVKVtIrt6f0bXUjaFzgRGAZsbPv+zsaOHTvWkyZNWmKxRUTReNtpeuTF0myg/j0eqHFFRERE9IakW2yPbXUtzej7mO1hHU59DLgvSa6BwfbpwOn9HUdERERERERE9L0kuhYjSTcCI4FP9XcsERERERERERGDXRJdi5HtLfs7hoiIpdHk9vYXt1jFkjd+1Cj2Gz26v8OIiIiIiOi1NKOPiIiIF01ub+e8adP6O4yIiIiIiIWyxCu6JBmYA3zX9uHdjN0H+JTtdy6J2Hqivt3vtbazHXEpI2kFylsdVwCOtf21fg4pIjoxpq0tzbL7SSrpIiIiImJp1l8VXZs1klyS1pVkSe1Nn7/2U1zdsn3MoiS5JL1f0rWSZkl6QtI1knbqyxj7k6QzJB3V4Vzjd9wysVrnPNfh78AyTdd3lHRHPX+jpI27uP+dHdaZL+liANvP2m4Dzu2jx42IiIiIiIiIAWQg9egaaXt+XywkSYBsv9AX6/UVSbsAPwUOAXYEZgFbAXsAF/VyrWU7fl+tzi1FjmtVYSVpfUpianvgJuCLwEWSNmr1rLY3aZor4D7glwsT0N1z5gzqyob04ImIiIiIiIjBZqnq0SVpS0k3S5pR/9yy6dpESUdLuoGyNfK1kjaSdJWkpyXdLWnX/8/efYbbVZVrH//f0uMOBIgEQj2CRBQhaAALTcGC0mwIQZqir6ICAso5IlIEAY8gzYoKCIiC2GgqikgvAQIekEgLhE4CgewUSrjfD2MsWCx2DTvZJffvutbFXnOOMeYz5wpfnusZz2waf7qkH0i6qFZXXS9pzabzb22a+1jdsoikwySd1TTuPEmP1piukPRSoqUldgHHA9+2/TPbT9t+0fY/bX+ujllT0mWSpkmaKulsSSOa1pgs6SBJtwEzJa1VK6U+K+kB4LLuYpL0YUl31Ht+SNKBTee2lzRR0jOS7pH0oXp8tKQ/1Wdxt6TPzetvOA8+CFxp+6qa2DoWWBnYvAdzNwNWAM6fj/ENSunBExEREREREUPRQKro6pKk5YCLgH2Ac4BPAhdJWsv2tDpsV2BrYBLweuD/gG/VY+sBf5V0u+3b6/idgQ8BNwNnAEcBO0kaDvwN+B6l8moxoLPtcpcAnwGeoyRhzgbGdjBuDLAq8NuubhM4GrgCWJqSoDkM2K9pzM7AR4CpwKh6bHNgHaBRwdZVTD8HdrR9paRlgf8CkLQR8EvgE8DfgZWA4XXOOcDtwGjgzcClku61/fcu7qW39pa0N3Af8B3bjeSU6oeW7+vWOLuyO/Bb2zPnJaAxw4YN2R5BQ7lSLSIiIiIiIhZeA6mia6qk6fVzYAfnPwLcZftM2y/YPge4k5KIajjd9u218udDwGTbp9XxN1MSR59oGv872zfU8c3JoG2AR20fZ3uO7Rm2r+8oaNu/qOefpSSl1pe0TAdDl6//faSzB2D7btuX1l5ST1AqwForl06yPcX27KZjh9me2TjWTUzPA2+RtLTtp+pzAfgs8It6/RdtP2T7TkmrApsAB9VnMRH4GSWp2JkDm37L6cBtXYwFOAl4E6X66hDgdEnvqecuBTaXtIWkxYFvAIsDw7paUNIwym99ejfXjoiIiIiIiIghYiAlukbaHlE/3+vg/Gjg/pZj91O2sTVMafp7dWDjloTLLsCKTWMebfp7FtBW/16V0tupS5IWkXRM3eb3DDC5cS8dDG9Una3UxXorSPp13VL4DHBWB2tN6WDqS8d6ENPHKf2u7ldphP+ueryzex4NPGl7RtOx1ufe6ntNv+UISjVdp2zfbHtaTUheTEk6fqyeu5NSmXUKJUk4ErgDeLCrNev8J4F/djMuIiIiIiIiIoaIgZTo6s7DlORVs9WAh5q+u+nvKcA/mxMutttsf7EH15oCrNntKBgPbA9sBSwDrFGPq4Oxk+q6H+9ivaMp97Ce7aUpTepb1/KrZr3yWJcx2b7R9vaU6qk/AOfW853d88PAcnU7Z0Prc+9rpum+bf/W9rq2lwcOpfw7uLGbNXYHfmm7o+cVEREREREREUPQYEp0XQysLWm8pEUlfYrSN+vCTsZfWMfvKmmx+tlQ0jo9uNaFwIqS9pO0hKThkjbuYNxw4FlKtdYw4DudLVgTLvsDh0jaU9LSkl4naRNJP21arx2YLmllyhsGe6vTmCQtLmkXScvYfh54BphbT/8c2FPSljWulVXebDgFuAY4WtKSktajbHM8ex5i65CkT0hqq9f9AC1voZT0jlqp9gbgJ8AFtdKrs/VWAd5L6bsWEREREREREQuJQdOM3vY0SdsAJwI/Au4GtrE9tZPxM2rS5Pj6eR1wKyXZ1N21Zkh6f73WoZTE0QlAa5+uX1LeCvgQZZvcIUCnFWO2fyupHTgYOBmYTWny/r91yOF1zafr/Z0JfLW7eHsZ067AKZIWoVSZfbrGdoOkPYHvUxrUPwZ8idIHbWfgx5TqrqeAQ21f2su4urIvJdEmSjP6z9m+vOn8icD6lP5i59H0G0raBfiG7ea3Xe4KXGu72+2nC7OJ7e1pSt9i/KhRfH706P4OIyIiIiIiIuaRFvTOLklzKImjk2wfskAvHgs1SUtQEniLAd+1fXhX48eNG+cJEyYskNgWtC1uuYWJ7e2MbWvrfvBCovE8huqbNgeTRgI2v0X/yPPvGwP1OQ7UuCIiIiJ6Q9JNtsd1dG6BV3TZXnJBXzMCoL6FckR/xzFQJKnzSqlui4iIiIiIGPwGU4+uiIiIiIiIiIiITiXRFRERERERERERQ8KATHRJsqSZko7qh2tvKmnSgr5uzH+S1pbULmmupL36O56IiIiIiIiI6FsDMtFVrW/7YABJa9TkV3v9PCbph5IWe60Xqeuu1fhu+0rbY17rul1cb7ykCfU+HpF0iaRN5tf1FjRJl7cmkSRtIenBbubtJOnfNcF5j6RN6/G31Of1VP38TdJburn+nKZ/Ky8lLW3/x3YbcOVrvM2IiIiIiIiIGIAWeDP612iE7RckrQD8BfgScEI/x9RjkvYH/hv4AiX+54APAdsDV/VyrUVtv9DdscFA0vuBY4FPATcAKzWdfhj4BHA/JTH7JeDXwHpdLPll2z97rXFNmjVryDYozxsXIyIiIiIiYigayBVdnbL9OHAp8FJlj6T/rpVAMyTdIemjTefWkvRPSU9LmirpN/X4FXXIrbX651Ot1UfdrLuHpKskfa9WG90naeuOYpa0DHAE8CXbv7M90/bzti+w/bU6ZiNJ10qaXqu9TpG0eNMalvQlSXcBdzVilXSQpEeB0yQtK+lCSU/UmC6UtEpLzPfW+7lP0i5N5z5Xq6oa9/r2enydWik1XdLtkrabpx+uc4cDR9i+zvaLth+y/RCA7em2J9s2IGAusFZXi0X3xra1MX7UqP4OIyIiIiIiIqJPDbaKLgAkjQY+CJzYdPgeYFPgUeCTwFmS1rL9CPBt4K/Ae4HFgXEAtjeTZMo2ybvr2lu0XK6rdQE2Bs4ARgKfB34uaeWamGn2LmBJ4Pdd3Npc4KvABGAV4BJgb15ZtbZDvebs+t8VgeWA1SmJy2HAacCOwCLAL4BTgB0kvR44CdjQ9iRJK9W5SPokcFhdfwKwJvB83R56QV3nA8AmwB8ljbP9mnuZSVqE8nv8SdLdlGf0B+Brtmc3jZsOtNV7/FY3yx4t6RhgEnCw7cvnJbYxw4Zx+QYbzMvUiIiIiIiIiOgHg62ia2pNeDwEzAR+2zhh+zzbD9eKoN8AdwEb1dPPUxJBo23Psd3jbYLdrAtwv+1Tbc+lJLxWAjoqlVkemNrV1kLbN9WqphdsTwZ+AmzeMuxo2082JYFeBA61/azt2ban2T7f9izbM4CjWtZ4EVhX0lK2H7F9ez2+F/Bd2ze6uNv2/cA7KQmmY2w/Z/sy4EJg5y4e20m1+mt6/b0u7GLsKGAxyvbETYGxwAbAN1uezQhgGeDLQFf7CQ8C3gisDPwUuEDSml2Mj4iIiIiIiIghYrBVdI2sPbqWomwD/DPwbgBJuwH7A2vUsW2UKiuAr1Oqum6Q9BRwnO1f9OSC3awLpdILANuzJDXGtJoGjOyqj5aktYHjKRVOwyi/z00tw6a0fH/C9pymNYYB36f0/lq2Hh4uaRHbMyV9CjiQUnl2NXCA7TuBVSnVa61GA1Nsv9h07H5KIqkz+zT3yKpVcmd1MraRsDu5USUn6XhKouvg5oE1/h8DT0hap25hpWXM9U1fz5C0M/Bh4OQu4o0ASu+yodqXbTBJD7mIiIiIiJhXg62iC4BazXQ68C5JIyWtDpxKqfZZvlb//B+lpxO2H7X9Odujgf8H/FBNb1rsTHfr9tK1wBzK1sDO/Ai4E3iT7aWBb3RwrdYtka3fDwDGABvXNTarxxvP4i+230+pPLuTcn9QEmgdVT49DKwqqfnfymqUqrrXzPZTwIMd3EdnGtszu0q0veISzNvvFRH9JD3kIiIiIiJiXg22ii4AJC0B7EqpppoGrEBJaDxRz+8JrNs0/pPAtbYfBJ6qY+fW049Rtrrd3cGlXt/Vur1h+2lJ3wJ+IOkFSs+w54GtgPfa/jowHHgGaJf0ZuCLjWv3wnBKldR0ScsBhzZOSBpF6ev19zqmnZefw8+A4yVdBdxM7dEFXE/ZJvp1SccB7wG2BTbsZVxdOQ34iqQ/12vuR93uWN/IOBW4jfJ7HEn5Df/duoikEfX+/gm8QHmL42Z1vYhujW1rS1+2iIiIiIiIQWywVXRNl9ROSU69C9iu9pO6AziOUjX1GPA24OqmeRsC19e5fwL2tX1fPXcYZYvbdEk7Nl+sB+v2iu3jKdsgv0lJYE2hVIv9oQ45EBgPzKBUWv1mHi5zArAUJTl0HWV7Z8PrKBVfDwNPUnp37V1jO4/Sz+tX9fp/AJaz/RywHbB1XfOHwG51u2Nf+TZwI/AfSgLrlhoLwAjgHOBpytbKtYAPNbZrSvqGpEvq2MUoibAnaqxfAXboi6b5ERERERERETHw6dUvB+x/kuYAzwIn2T6kv+OJoUHSmygJtcWBvW2f3tX4cePGecKECQsitBgAGr25UtEVC7v8v9A3BupzHKhxRURERPSGpJtsj+vo3IDcumh7yf6OIYYe23dRKsQiIiIiIiIiYggabFsXe0WSJc2UdFT3o/vsmpJ0mqSnJN2woK67IEk6XdKR/R3HvJB0maQ5tRdZRERERERERAwhQzrRVa1v++DGl5r86vaNi6/BJsD7gVVsb9TbyZImS5otaUbtG3aNpC+0vPVwwJK0R0dJpHpfW3UxZ66k9qbPFi1jdpL075q4vEfSpp2stbukmyQ9I+lBSd+V9FLlou33AV94bXcZEREREREREQPRoEieDDKrA5Ntz3wNa2xre3hd6xjgIODn87JQc5JngLvWdlvT5/LGifrmxWOBPSlvldwMuLeTdYZR3rI4kvIGxi0pTf4jIiIiIiIiYohbqBNdkpaQdIKkh+vnBElL1HMjJV1Yq6qelHRlo6pK0mhJ50t6QtJ9kvapxz8L/Ax4V61KOlzSsnWdJ+p2xgslrdKT+Gw/bftPwKeA3SWtW69zuaS9mu7jFVVUtWrtS5LuAu6qx06UNKVWOt3UXBEl6TBJ50r6Za0ku13SuKbzG0i6uZ77DbCge6gdDhxh+zrbL9p+yPZDHQ20/SPbV9p+ro45G3jPAo02IiIiIiIiIvrFYKn2mV8OBt4JjAUM/BH4JnAIcADwIPCGOvadgGuy64I6dmdgFeBvkibZ/rmkucBetjcBkLQ8cBqwI7AI8AvgFGCHngZp+wZJDwKbAv/Xw2k7UCqaZtfvNwJHAE8D+wLnSVrD9px6fjvgY5SqqSNrjO+UtDjwB+CEemx74BxKhVVf2kDSVOBJ4EzgaNsvSFoEGAf8SdLdlCTbH4Cv2Z7d+XIv2Qy4fV4CmjRr1ktvp4qhb2J7O2Pb2vo7jIiIiIiIiHgNFuqKLmAXSqXQ47afoFQO7VrPPQ+sBKxu+/laJWRgQ+ANto+oVUP3AqcCO3V0AdvTbJ9ve5btGcBRwObzEOvDwHK9GH+07ScbySDbZ9VYXrB9HLAEMKZp/FW2L7Y9l5JoWr8efyewGHBCfQ6/pSTNuvLOWgn30gdYrYvxVwDrAisAH6ckEL9Wz42q1/8EJdE3FtiAkpDskqQ9KUmy73U3NmJsWxvjR43q7zAiIiIiIiLiNVjYK7pGA/c3fb+/HgP4X+Aw4K+SAH5q+xhK36zRNXnTsAhwZUcXkDQM+D7wIWDZeni4pEVqUqmnVqZUO/XUlJY4DgD2otyfgaUpfawaHm36exawZO3vNRp4qCb5GpqfWUeua1S0NV1/cmeDa7Kw4V+SjqAkuo7m5Yq0k20/Utc6npLoOphOSNqB0t9sK9tTu4m3Q2OGDePyDTaYl6kRERERERER0Q8W9oquhymJq4bV6jFsz7B9gO03AtsC+0vakpJAus/2iKbPcNsf7uQaB1Aqpza2vTRlKx2AehqkpA0pia5GH66ZlKbrDSt2MO2lxFTtx3UQZfvksrZHULYw9iSGR4CVVbN9VVfVWX3B1NhsP0XZQuouZzSR9CFKld22tv81XyKMiIiIiIiIiAFnYU90nQN8U9IbJI0EvgWcBSBpG0lr1QTPM8Dc+rkBeEbSQZKWkrSIpHVrMqojwylVSdMlLQcc2tPgJC0taRvg18BZTUmbicDHJA2TtBbw2W6WGg68ADwBLCrpW5SKrp64ts7dR9Kikj4GbNTTe+gJSVtLGlX/fjOlR9ofm4acBnxF0gqSlqW8VfHCTtZ6H6UB/cdt39CXcUZERERERETEwLawJroa1UFHAhOA24B/ATfXYwBvAv4GtFOSPT+0fXndbrgtpVfUfcBUypsWl+nkWicAS9Vx1wF/7kF8F0iaQakeOxg4ntIkvuH7wHPAY8AZlMROV/4CXAL8h7LtcA4tWxs7Y/s5SpP6PYCnKG+A/F1P5vbClsBtkmYCF9f1v9N0/tuUvmD/Af4N3ELpdYak1eobLhtVFq/POAAAIABJREFUZodQfouL6/F2SZf0cbwRERERERERMQDpla2XhhZJc4BngZNsHyJpacqWvWVtT+96dgxFki6lNNi/wfaWXY0dN26cJ0yYsGACi4gYIBpvm02PwtdmoD7HgRpXRERERG9Iusn2uI7ODelm9LaXbDn0KeCeJLkWXrbf398xREQMdBPb219KiMS8mdjezti2tv4OIyIiImKhM6QTXc0kXQOMoLx5MCIiImK+GdvWxvhRo/o7jIiIiIiFzkKT6LL97v6OISIiYjAY29aWrW0RERERMSgtrM3oIyIiIiIiIiJiiBm0iS5JljRT0lE9HH+6pCO7H9k/6v2sNQ/zLpfUp9sxJW0h6cEuzv9Y0iF9ec0FRdJlkuZIuqq/Y4mIiIiIiIiIvjVoE13V+rYPbnyR9FlJd0qaIekxSRdJGr4gA5LU3vR5UdLspu+7LMhY5hfbX7D97Y7OSdqjoySSpMmStupsTUlvlHRh/e2mSvpu07l1aoLqaUl3S/poF+vsLukmSc9IelDSdyW9tEXX9vuAL/T4ZiMiIiIiIiJi0Bjsia6XSNoc+A6ws+3hwDrAuQs6DtttjQ/wALBt07GzF3Q8g4GkxYFLgcuAFYFVgLPquUWBPwIXAssBnwfOkrR2J8sNA/YDRgIbA1sCB87P+CMiIiIiIiJiYBhKzeg3BK61fQuA7SeBM1rGLCvpImAz4A5gvO17JK0B3AcsZvsFKFsCgbNs/0zSHpS3NV4HfBaYDuxt+5KeBidpI+BESgJuNnA+sL/t5zoYuwlwDrAbMBE4k5K0WRS4GviC7eathatLuhpYD7i23tfUutZ5wKbAUsCtwBdt317PfRj4HrAq8Azwfdvfa4rjAOAgYC7wDdun1eOnAw/a/mZP778bewAP2z6+6dht9b9vBkbX2AxcVu91V+BV2ydt/6jp60OSzgbeOy9BTZo1iy1uuWVepsZ8Nn7UKD4/enR/hxEREREREREDzJCp6AKuBz4o6XBJ75G0RAdjdgYOB5YF7gZ61N+r2hiYRKkU+i7wc0nqxfy5wFfr/HdRKo32bh0k6YOUJNfHbf+D8hudBqwOrEZJkp3SMm08sCewArA4r6xgugR4Uz13M9BcVfZz4P/VCrh1KRVVDSsCywArU5J7P5C0bC/utzfeCUyWdEndtni5pLfVcx09Y9V4e2Iz4Pa+CDIGhont7fzqscf6O4yIiIiIiIgYgIZMRZftKyV9jJI82hdYVNJPga/ZnluH/c72DQC10uf4jlfr0P22T61zzwB+CIwCHu1hfDc1fZ0s6SfA5sAJTcc/Sekf9WHb/6rzplGqv6jXPgr4R8vyp9n+Tz1/LrBd03V/0TT3MOApScvYfhp4HniLpFttPwU81bTm88ARtcLtYkntwBhKVVt33ilpesuxpbsYvwql6mo74O+U3++Pkt4M3Ak8DnxN0vfruM07eAavImlPYBylGq/XxgwbxuUbbDAvU2M+SpVdREREREREdGYoVXRh+xLb21J6OW1P2RLXnORoTkrNAtp6sfxLc23Pqn/2eL6ktWuz9UclPUPpJzayZdh+wLmNJFedN0zSTyTdX+ddAYyQtEhHsdF0X5IWkXSMpHvq3Ml1TOO6Hwc+DNwv6Z+S3tW0zrTGNs7WdXvgOtsjmj+UfmWdmQ1cVX+/5yjbKZcH1rH9PLAD8JF6nwdQeq91+lZIAEk7AMcAWze2cUZERERERETE0DZkKrqa2X4R+Luky+jZFreZ9b/DKL2qoGzd60s/Am6hNMufIWk/4BMtYz5J2RL5kO1GpdcBlEqqjW0/KmlsXacn2ybHUxJ+W1GSXMtQqrYEYPtGYHtJiwFfpiSQVp33W5xntwHv6eyk7dsoVVwASLqGV/dfo+n8h4BTgY80Jw0jIiKibAEfiNWx6b8YERERfWHIVHRJ2l7STpKWVbERJTnS7VY7208ADwGfrlVQnwHW7OMQh1OSaO11S94XOxjzMKV31z6S9m6aNxuYLmk54NBeXvNZYBolifedxglJi0vapW5jfL7GNrfjZea7syjbHbeqlWr7AVOBf9dY15O0ZK1uOxBYCTi9o4UkvY/Sh+zjjW2qERERMbCl/2JERET0laFU0fUUsA+lUfsSwCPA/9o+u8tZL/scpe/WdyhN2q/p4/gOBH4KfJ1SkfUb4H2tg2w/IGlL4HJJz1F6eP2Kkvh5GDiOspWvJ34JfJCSxHuS8pbC5gTbrsApNbk0Cfh072/rtbM9SdKngR/zctP87ZreSLkrZQvqYsCVwPttPwsgaTXKGzTfYvsByj0uQ+kr1rjElba3XlD3ExERMZCNbWsbcD0oB2KFWURERAxOst3fMcwTSXMo1Uon2T6kv+OJwUHSpZS3PN5ge8uuxo4bN84TJkxYMIFFj21xyy1MbG9nbFtvWuwNLdneE/NTI+Ew0BIh0TcG6u87UOOKiIiIgUnSTbbHdXRu0FZ02V6yv2OIwcf2+/s7hojXYmJ7O0ASXRERERERER0YtImuiFh4DcRtNwtKtvdERERERER0boE2o5dkSTMlHbWArne7pC3mw7qbSprU1+v2J0lbSHqw6ftkSVv1Z0zzg6R7JD0n6az+jiUiIiIiIiIi+lZ/vHVxfdsHA0haoya/2uvnMUk/lLRYX1zI9lttX94Xa7Wse6XtMfM6X9JKkn4u6RFJMyTdKelwSa/vyzj7g6TDOkoi1d95rS7mvV3SFU3/Dvatx1dr+vfR+FjSAZ2sI0nHSppWP99VU1d622vS9PbJiIiIiIiIiBg6+iPR1ZERttuAtwHvAr7Uz/HMN5KWA64FlgLeZXs48H5gBLBmf8bWXySNBP4M/ARYHlgL+CuUt1Dabmt8KP9GXgTO72S5z1PeSrk+sB6wDfD/5u8dRERERERERMRAMKB6dNl+vL4V7y2NY5JGAycDmwHtwPdtn1TPHVbHzgE+CjwA7G57Qj0/GdjL9t8kbQScCKwDzKYkSva3/Vwda0qC7avAisAJwOnAWcBbKYmYT9t+rm6HPMv2Kk3XOQXYDVi9jt3d9pwObnN/YEZd68V631OAfZvu+d011rWB/wD72r6mnrscuBJ4HyWRcy0w3vZUSWsA9wF7AN8GhtXndVSduwRwLLBjvdS5wEG2n+34FwFJKwL3AqvanlaPvaPe42jbz3c2txf2B/5i++z6/Vng352M3Q24wvbkTs7vDhxn+8Ea63HA54Af9zaoSbNmpR/SALSwv3ExIiIiIiIiOjdQKrqAl5JaHwSuq99fB1wA3AqsDGwJ7Cfpg03TtgN+TamI+hMl4dSRuZQk1khK1diWwN4tYz4EvAN4J/B14KfALsCqwLrAzl2Ev2Od/1+UBNQenYzbCvhdI8nVqlZ8XQScRKluOh64SNLyTcPGA3sCKwCLAwe2LLMJMKbe47ckrVOPH1zvbSyl4mkj4Jtd3BO2HwUu5+XkGMCngV/3UZKLGtOTkq6R9LikCySt1snY3YAzuljrrZR/Lw231mMxRIxta2P8qFH9HUZEREREREQMQAOlomtqbaO0DKVC6bf1+IbAG2wfUb/fK+lUYCfgL/XYVbYvBpB0JrBfRxewfVPT18mSfgJsTqncajjW9jPA7ZL+D/ir7Xvr2pcAG9B5kuUk2w/XsRdQkkkdWR54pJNzAB8B7rJ9Zv1+jqR9gG0pFWYAp9n+T73WuZRkX7PDbc8GbpV0KyWp9W9K0u4rth+vcw+nbBc8pIt4oNzzPsCPJC1CSfi1XrPZjpK26WbNZqsAb6ds4fwX8F3gHOA9zYMkbQqM4uV/Hx1pA55u+v400CZJtt2LmBgzbNhC+2a/iIiIiIiIiMFooFR0jbQ9grLV7mrKtjgo2wBHS5re+ADfoCQ7Gh5t+nsWsKSkVyXwJK0t6UJJj0p6htKQfGTLsMea/p7dwfeu9ku1xtHZ2GnASl2sMxq4v+XY/ZSKtp5eq7PzrWvfX49154/AWyS9kZKMetr2DV2MP9f2iOZPN+vPBn5v+8a63fNw4N2SlmkZtztwvu32LtZqB5Zu+r400N7bJFdEREREREREDD4DpaILANuzJZ0OHFgblE8B7rP9pj5Y/kfALcDOtmdI2g/4RB+s21t/Az4q6fBOti8+TEnwNVuNl5N/r0Vj7dub1n24u0m259TKsV2ANwNndjOlt24DmhNRjb9feluipKWAT1J6sXXldkoFWyMRtz4v32/EkDCxvX1Q948bP2oUnx/dkxx7RERERERE7wyUii7gpWbpu1IqkqZRkhXPSDpI0lKSFpG0rqQN52H54cAzQLukNwNf7LPAe+d4SpXRGZJWB5C0sqTjJa0HXAysLWm8pEUlfYrScP/CPrj2OcA3Jb2hJhK/RWm23xO/pPQd264Xc3rqNEryb6ykxShbKa+yPb1pzEeB6cA/ehDn/vWZjgYO4OUtnxHRzya2t/Orxx7rfmBERERERMQ8GCgVXdNrj64XKM3Dt6tbzeZK2hY4jvI2wSWASXTTQL0TB1Kay3+dUtn1G8qbCxco20/WtyoeCVwv6fXAQ5Qk1N22Z9X+VidSqtDuBraxPbUPLn8kJcl2W/1+Xj3Wk7ivlvQicHMXbzycJ7Yvk/QNShP+YcBVlIb7zXYHftm6BbH27brEdmN75k+AN1J6fQH8rB6LGDLGtrUN2v5xg7kSLSIiIiIiBj4tyNZFkuYAz1Iat3fXAL0vrvcA8GnbV8zvay0MJF0G/Mr2z/o7lnklaRKl39m5tj/T1dhx48Z5woQJCyawiB5qJIoGe6JrsMa/MMhvNLQN1N93oMYVERERA5Okm2yP6+jcAq3osr3kgrqWpDcAbwAmL6hrDmV1u+jbge37O5bXwvaY/o4hIiIiIiIiIuaPAdWjq6/UpMxdwMm2H+jveAY7SWdQmujvZ3tGf8cTEREREREREdGRgdKjq0/ZvhEY0d9xDBW2d+/vGCIiIiIiIiIiujOgK7okWdJMSUf1dywNknaR9Nf+jiN6T9LaktolzZW0V3/HExERERERERF9a0Anuqr1bR8MIGmNmvzqt0o022fb/sC8zpc0XtKEmnB5RNIlkjbpyxj7k6TLW5NIkraQ9GA3c+bUZ9JeG8Z3NO7Q+vtv1cVaa0i6WNJTkh6VdErj34vt/9S3M145j7cXEREREREREQPYYEh0DRmS9gdOAL4DjAJWA37IPDR47yjZ158JwD7wZdtt9fOqhvGS1gQ+ATzSzTo/BB4HVgLGApsDe/d1sBEREREREREx8AzmxAiSlgdOpyQzJgF/AbawvUk9b+CLwAHASOBXlISKa+LkVGB9wHXul2xPr3NXBU4ENqUkBM+x/WVJewB7NV3j3XXc2sB/gH1tX9NBrMsARwB72v5d06kL6gdJG9W11gFmA+cD+9t+rul+vgzsBywqaU/gLOBk4KvApZL2Ac4ENqb8vlcDX7D9YF1jD+BblDdSTgW+afvseu5zwP7AKsAU4NO2b5a0DvAjSuLoIeB/bP+p+1+oT50CHERJZHXlv4BTbM8BHpX0Z+Ct83LBSbNmvfS684iBYmJ7O2Pb2vo7jIiIiIiIiAFpsFd0/QCYCawI7F4/rbYBNqQktHYEPliPCzgaGE1JLK0KHAYgaRHgQuB+YA1gZeDXrQtLWg64CDgJWB44HrioJuBavQtYEvh9F/czl5KwGlnHb8mrq5F2oCSx3lK/rwgsB6wOfJ7ym55Wv69GSZidUuN9fY11a9vDgXcDE+u5T9b73w1YGtgOmCZpMUoi7q/ACsBXgLMlvarq6jU6WtJUSVdL2qL5RI3tOdsX92CdE4GdJA2TtDKwNfDnPo41ot+MbWtj/KhR/R1GRERERETEgDRoK7pqMurjwLq2ZwF3SDoD2KJl6DG1Smu6pH9QqpL+bPtu4O465glJxwOH1u8bURJgX7P9Qj12VQdhfAS4y/aZ9fs5taJqW0qlWbPlgalN672K7Zuavk6W9BNKtdoJTcePtv1kfQYALwKH2n62nm9UglHHHAX8o2n+i8C6kh6w/QgvbwXcC/hufWMl1GcjaVOgjfIcXwQuk3QhsDM1MdiBkyR9r+n7osD0zu6bUql1B/AcsBNwgaSxtu+R1EbZ6tnTvmj/BD4HPAMsApwB/KGHc19hzLBhXL7BBvMyNSIiIiIiIiL6wWCu6HoDJYEypenYlA7GPdr09yxK0gZJK0j6taSHJD1D2QI4so5bFbi/q6RUNZpS9dXsfkoFWKtpwMiu+mjVtwJeWJuoP0NJ8IxsGdZ6j0/UbXqNNYZJ+omk++saVwAjJC1ieybwKeALwCOSLpL05jp1VeCeTu5xSk1ydXePDfvYHtH4UKrqOmX7etszbD9r+wzKdssP19OHA2favq+rNQAkvY6yBfV3wOspz25Z4Nju5kZERERERETE4DeYE11PAC9Q+kk1rNqL+UdTenOtZ3tp4NOU7YxQkkmr9aC5+8OULYLNVqP0sWp1LTCHsvWwMz8C7gTeVGP6RlNMDe7m+wHAGGDjusZm9bgAbP/F9vspzdrvpPQpg3LPa3YQ08PAqjWJ1NDZPfYV8/J9bwnsU5N/j1J+43MlHdTBvOXq+VNq0mwaZRvnhzsYGxERERERERFDzKDdumh7rqTfAYdJ2ouSfNkNeKCHSwwHnqZsaVwZ+FrTuRsoW/qOkXQopXfWO2xf3bLGxcDJksYD51K2Ur6F0t+rNd6nJX0L+IGkFyg9r54HtgLea/vrNaZngPZaafVFSkKvN4ZTti9Orz3EGtsxkTSK0t/r73VMe703gJ8Bx0u6CriZkvR6Hrie0gft65KOA95D2Zq5YS/j6pCkETWmf1ISl5+iJOf2q0O2BBZrmnIjpWH+Ja1r2Z4q6T7gi3XrZBulb9utfRFrRPSNie3tedHDAJYXHkRERETEYDaYK7qgvIFwGcr2xDOBc4Bnu5zxssOBt1OSXRdRtrsBJYlGSeasRUmcPUhJwLxCrRjahlJFNQ34OrCN7akdXdD28ZQkzTcpCawp9R4aPaQOBMYDMyiVVr/p4b00OwFYivJGxet4ZSP219VYHwaepPT/2rvGdh5wFOXNlDNqTMvVNz5uR2nqPpXy1sPdbN85D7F1ZDHgSMrzmEppdr+D7Uk1rmm2H218KIm5p2y3A0j6hqTmpNfHgA/V9e6mJM++2kexRkQMeXnhQUREREQMZrJbd74NHJLmUBJXJ9k+pAfjjwVWtN3R2xdjISfpTZSKsMWBvW2f3tX4cePGecKECQsitIiFRqOSKy96iOgfA/X/wYEaV0RERAxMkm6yPa6jcwN666LtJbs6X7f3LQ78i7KV7rOUtwdGvIrtu4AR/R1HRERERERERMwfAzrR1QPDKdsVRwOPA8cBf+zXiCIiIiIiIiIiol8Mih5dkixppqSjmo/bvtH2WraH2V7D9tHuYi+mpNMlHVn/3lTSpPkde09IWqPeY68Tj5ImS9qqj+PZozal7+z8JZIG5fZQSfdIek7SWf0dS0RERERERET0rUGR6KrWt30wvCIx1N706dWb9WxfaXtMXwYoabWWmBoJusb3Tfvyev3F9ta2z+jonKTDOkoi1WexVmdrSnq7pCvqc3pM0r5N59aQ9A9JsyTd2VViT9IISWdIerx+DmuJfU3gOz25z4iIiIiIiIgYXAb71sURtl/o7yAabD8AvPROdkmmJOju7r+oBj5JIylvh/wq8FtK37VVmoacA1wLfLh+fivpTbaf6GC57wPDgDWAFYC/S7rf9mnz7w4iIiIiIiIiYiAYTBVdPSLpzZIulfSkpEmSduxk3BaSHmz6PlnS/0i6Q9JTkk6TtGTT+W0kTZQ0XdI1ktbrZVwfkXSLpGckTWmtNGoZ+/Eaz7qS1pR0maRpkqZKOltSa0P1sZJuk/S0pN804pa0rKQLJT1R7+lCSas0XWcPSfdKmiHpPkm7tMTxvTrvPklbNx2/XFJfNv3fH/iL7bNtP2t7hu1/12utDbwdONT2bNvnU14+8PFO1toW+K7tWbYnAz8HPtOHsUZERERERETEADXYK7peQdLrgUuBbwFbA+sBf5V0u+3be7DELsAHgZnABcA3gW9KejvwC0oSZQLwaeBPksbYfraH4c0EdgNuB9YFLpU00fYfWu5hT+BgYCvbd9ftfkcDVwBLA+cDhwH7NU3bEfgQMAe4GtgD+DElkXlaPb9IvYdTgB3qszoJ2ND2JEkrAcs1rbkxcAYwEvg88HNJK3fVA+01eCfwL0nXAGsB1wNfqhVybwXutT2jafyt9Xhn1PL3uvMS1KRZs1563XksfMaPGsXnR4/u7zAiIiIiIiKiFwZ7RdfUWmE1XdKBwDbAZNun2X7B9s2UxNAnerjeKban2H4SOArYuR7/HPAT29fbnlv7Uz1LSdD0iO3Lbf/L9ou2b6Nsx9u8Zdh+wNeALRrbHW3fbfvSWun0BHB8B/NOsv1wjfsCYGydO832+bW6aUa9p+a5LwLrSlrK9iMtycD7bZ9qey4l4bUSMKqHt7tj0+8yXdL0bsavAuwO7AusBtxHeT5QtoI+3TL+acobNzvyZ+C/JQ2vScLPULYyRvTYxPZ2fvXYY/0dRkRERERERPTSYK/oGtnco0vS14GNWxIriwJn9nC9KU1/3w80yjlWB3aX9JWm84s3ne+WpI2BYyjVRYsDSwDntQz7GnCE7eYtlStQKq82pSR3Xgc81TLv0aa/ZzXikjSM0rPqQ8Cy9fxwSYvYninpU8CBlGqtq4EDbN/ZuqbtWZKgqf9YN861/emW+++qEmw28HvbN9axh1OSmMsA7ZRKtmZLAzPo2D7AycBdwDRKwmznTsZ2acywYVy+wQbzMjUGuVTyRUREREREDE6DvaKr1RTgn7ZHNH3abH+xh/NXbfp7NeDhpnWPall3mO1zXr1Ep34F/AlY1fYylK2FahnzAcpWyeb+U0cDBtazvTRl22TrvM4cAIwBNq5zN6vHBWD7L7bfT6nWuhM4tRf305duo9xjQ+NvUbZ6vlFScwXX+vX4q9h+0vYutle0/VbKv/Eb5kPMERERERERETHADLVE14XA2pJ2lbRY/WwoaZ0ezv+SpFUkLQd8A/hNPX4q8AVJG6t4fW0u39n2uY4MB560PUfSRsD4DsbcTqm++oGk7ZrmtQPTJa1MqfrqzTVn17nLAYc2TkgaJWm72qvr2XqNub1Yuy+dBnxU0lhJiwGHAFfZnm77P8BE4FBJS0r6KKX32vkdLVSb9y8vaZHaQP/zwJEL6D4iIiIiIiIioh8NqURX7UP1AWAnSjXWo8CxlG2CPfEr4K/AvfVzZF13AqVP1ymUbYN3Uxq+98bewBGSZlCa5Z/byT3cSuk1dmpN1BxOeevg08BFwO96cc0TgKWAqcB1lP5VDa+jVHw9DDxJ6d21dy/W7jO2L6MkFi8CHqc0pG9OBO4EjKM8+2OAT9R+ZUjaVFJ709h3UN7KOINSDbdLD19EEBERERERERGDnObPS/T6lqQ5lKqjk2wfMp+uMRnYy/bf5sf6MTBImgSsTOkj9pmuxo4bN84TJkxYMIHFgNLo0ZUebX0vzzaifw3U/wcHalwRERExMEm6yfa4js4Nimb0tpfs7xhiaLA9pr9jiMFhYnt7mtLPBxPb2xnb1tP3WkRERERERPTOkNq6GBERA9vYtjbGjxrV32FERERERMQQNSgquhYE22v0dwwRMXCMbWvLFpqIiIiIiIhBJhVdERERERERERExJAyZRJckS5op6aj+jmWok3S5pL36O455IekeSc9JOqu/Y4mIiIiIiIiIvjVkEl3V+rYPBpC0Rk1+tdfPY5IulPT+/g6yK00Ju3ZJ0yT9XdKn+juunpJ0WEdJpHpfa3Uy55Km36m9JqL+1cG4zes6R3Zx/RGSzpD0eP0c1nze9prAd3p/ZxEREREREREx0A21RFdHRthuA9YHLgV+L2mPeVlI0qt6mkla5LWF16H1a8xjgNOBUyQdOi8LdRTzQGN7a9ttjQ9wDXBe8xhJiwEnAtd3s9z3gWHAGsBGwK6S9uz7qCMiIiIiIiJioBnwSZC+YvtR4MSaMDlW0i9tvyjpv4HPASsAU4CDbf8eoCbEPgfcAOwO/FDSKsBsYHVgc2B7SXcAJwObAe3A922fVNc4DHgLMAf4KPAAsLvtCT2IeSpwpqTZwFmSTrE9TdJkYC/bf2u6xlq2Py1pDeA+YC/gUGAysJmk84BNgaWAW4Ev2r69zj8dmElJDm0G3AGMt31PPf/+en8rAWcC6skznxc1/k2B1uTUAcBfKb9TV7YFtrY9C5gs6efAZ4DTehvLpFmz2OKWW3o7LYaAie3tjG1r6+8wIiIiIiIiopcWhoquVr+jJEvG1O/3UBIrywCHUxJKKzWN3xi4t85p9P8aX/8eTqk+uoCSPFoZ2BLYT9IHm9bYDvg1MAL4E3BKL2P+IyUpuVEv5mwOrAM04rgEeFO9j5uBs1vG70y5/2WBu6n3KmkkcD7wTWAk5Xm9p5fx98ZuwJW272sckLQ6JVl1RA/XUMvf6/ZdeLEwGNvWxvhRo/o7jIiIiIiIiOilhaaiq8nD9b/LAdhu3iL3G0n/Q0ko/bEx3vbJ9e8XJAH80fbVAJLeBrzBdiMJc6+kU4GdgL/UY1fZvriOPxPYrzcB235e0tRGzD10mO2ZTWv8ovF3rQB7StIytp+uh39n+4Z6/mzg+Hr8w8Adtn9bz51Aqa7qyo6StulFrM12A1p7cJ0EHGK7vT7/rvwZ+G9JuwOjKAmyYfMSyJhhw7h8gw3mZWpERERERERE9IOFsaJr5frfJwEk7SZpoqTpkqZTqn9GNo2f0sEazcdWB0Y35tc1vkFJsjQ82vT3LGDJ3vTOqtst39CIuYdeilHSIpKOqW8cfIaynRFeeZ+tMTb2bY1uXsu26fiZNDvX9ojmT08ClrQJsCLw26Zj2wLDbf+mJ2sA+1C2lt5FSVaeAzzYw7kRERERERERMYhvawKyAAAgAElEQVQtjBVdHwUeBybVLXGnUrYbXmt7rqSJvHLrmztYo/nYFOA+22+aXwED2wMvUHqFQemn1VyltGIHc5pjHF/X2IqS5FoGeIqe9dp6BFi18UWlpGrVzoe/JrtTKsvam45tCYyT1EjELQPMlfQ229u3LmD7SWCXpni/w8vPLSIiIiIiIiKGsIWmokvSKElfpjRo/x/bLwKvpySEnqhj9qT3/ZxuAJ6RdJCkpWr11LqSNuyDmJeTtAvwA+BY29PqqYnATpIWkzQO+EQ3Sw0HngWmURJk3+lFGBcBb5X0sVqFtg8dJ9ZeE0lLAZ+kvGWy2SHA2sDY+vkTJTnZ4ZsUJa0pafn6O2wNfJ5Xb4WMiIiIiIiIiCFoYUh0TZc0E/gXpd/UJxv9qmzfARwHXAs8BrwNuLo3i9ueS3nT31jK2w6nAj+jVB7Nq1sltVOawu8FfNX2t5rOHwKsSanKOhz4VTfr/RK4H3iI8kbF63oaSH3z4yeBYyiJsjfRy2fUQzsATwP/aLn+DNuPNj6UbYkza+UWkjatz6rhHZTfegZwNLBL4+2SERERERERETG0qbRcGvwkzaFULZ1k+5D+jicGJkmTKH3azrX9ma7Gjhs3zhMmTFgwgUVERCwAW9xyC8CAe9nKQI0rIiIiBiZJN9ke19G5IdOjy/aS/R1DDHy2x/R3DBERERERERExfywMWxcjIiIiIiIiImIhkERXREREREREREQMCUMy0SXJkmZKOqq/Y4mBQ9JWktolvShpq/6OJyIiIiIiIiL61pBMdFXr2z4YQNIaNfm1wHuSSVpF0vmSpkp6WtK/JO2xoONYkCQtLuk4SQ/WxNJ9kr7fzZx967iZkv4tae0OxpxWf8e1ehDD5nXskY1jtv9muw14YJ5uLCIiIiIiIiIGtCHTjH5BkLSo7Rd6Oe1M4FZgdcpbId8GrNjXsc1vkhaxPbeHw/8HGAdsBDxCuffNulh7L+CzwEeAfwNvBJ5qGbMJsGYPY10MOBG4vofxdmjSrFkvvQUqYigZP2oUnx89ur/DiIiIiIiI6HNDuaKrRyRtJOlaSdMlPSLpFEmLN523pC9Jugu4qx47UdIUSc9IuknSpl1cYkPgdNszbb9g+xbbl9R1tpD0YEs8kxvb6iQdJuk8SWdJmlGrwdaW9D+SHq8xfKBp7uWSjpR0Ta2kukDS8pLOrrHeKGmNpvFvlnSppCclTZK0Y9O50yX9SNLFkmYC75X0YUl31FgeknRgF/f8e9sPu5hs+5edPP/XAYcCX7V9Rx1/j+0nm8YsCpwMfLmL59zsAOCvwJ09HB+x0JjY3s6vHnusv8OIiIiIiIiYL1LRBXOBrwITgFWAS4C9gROaxuwAbAzMrt9vBI4Angb2Bc6TtIbtOR2sfx3wA0knA9fY7u22uW2B7YE9gF8AfwF+Bqxcj/0E+K+m8TsBHwSmAtfWz97A7nX+ocCekl4PXAp8C9gaWA/4q6Tbbd9e1xoPfBjYBlgcuA/Y0faVkpZtuW7rPe8v6TngSuD/bLuTsavUz7qSTgdeAH4JHG77xTrmq8AVtm+T1NWzQtLqwGeAtwOndDm4G2OGDePyDTZ4LUtEDDipUoyIiIiIiKFsoa/osn2T7etqtdVkSuJo85ZhR9t+0vbsOucs29PqnOOAJYAxnVzik5RkzyHAfZImStqwFyFeafsvdcvkecAbgGNsPw/8GlhD0oim8afViqinKUm7e2pvqsb8RuZmG2Cy7dPqfdwMnA98ommtP9q+2vaLNYn3PPAWSUvbfqrO6cjRwLHALpQE4v9n787jNh3r/4+/3tnGuIexNRnLKFvh+zVqlFRS6VtUtCFjS0nq5yupJEyMUNpI+2bfJVlKtr5CigaDJLJGGAZj5p4Za+/fH8dxcblc133fs97LvJ+Px/WY+zrP4zzOz3He4w+f+Ryf89+SduswdrX65/9QtnW+A9iRspURSasDn6Yk5PriWGCC7e4+jo+IiIiIiIiIIWKRT3TVrYAXSnpY0nTgSGCllmH3t1zzhdow/UlJ04Dl2lwDQE0IHWB7A2AUMBn4jXorTXpR8x6j2cDUpl5ZjQqzrh7Gt35vjB0DvKlu2ZxW17ETL+0f9pJ1Ax+hVHjdJ+mPkt7cLmDbz9v+oe23ACOBI4DjJL2uzfDGGr5pe1pTsnHrevwY4LCauOuRpA8AI2yf2dvYiIiIiIiIiBh6FvlEF/BjSi+ndWwvCxwItCahXth2V/txfRnYHlje9kjKFsZeE1e2pwLfBkYDKwAzgeFNcy9GqdhaGO4H/mh7ZNOny/ZnmkNuvsD2X21vC7wS+A1wVm83sT3b9g8pzeXXbzPkduCZ1ns1eRfwrZqIfLge+7Ok8R3GjmsauwOwr6TzeoszIiIiIiIiIga/RS3RtZSkYU2fVwAjgOlAt6TXAp/peQpGUPpIPQosLumrwLKdBks6StKGkhaXNKLOf6ftx4A7gGGS3lffFHgwZRvkwnAhsK6kXSQtUT+bdKi6QtKSknaStFzdNjmd0t+s3dh9a6P9peu6d6M8t5c1B7I9CzgT2F/SCEmrAZ+q8QGsC2wEjK0fKH3Lzm1z6wl1fGPs+cDPgd17fxwRERERERERMdgtas3oW/s2vRv4IvAzYH9KIuZM4J09zHExpffVHZSKrKN5+Ra/ZsMpSZlVKNv0rgW2AbD9pKTPUprLLwZ8E3igwzzzle0Z9Y2N362fVwA3Afv1cNkuwA9q5dntwM4dxs0GvgOsTanUugP4iO27O4zfm/I7eBCYRklOHVfjfKR5YN3xObXRL03ST+q4vWzPAGY0jZ0NzGx+g2NElDcvDoam9ONHjWLP0aP7O4yIiIiIiBhE1PlleIOXpKeAp4FjbU/o73hiYJD0LkrD/aWArW3/X0/jx40b50mTJi2U2CIWli1uvJHJ3d2M7erqfXA/asSYN59GzF+NJPdA+29roMYVERERA5Ok622Pa3duSFZ02R7W3zHEwGP7ckpz/IhF2mBIIA2GirOIiIiIiBh4BnWPLkmWNFPSEfNhri0kLZBtg5LWkNRdt/wNKJLeJun2Po49VNIpCzqmBUnSxPp3xpKGZKI3IiIiIiIiYlE1qBNd1Ua2D6rN5adJell/LUlHS/rVwgpI0r2Stmx8t/2v+kbDts3b5/FeV0jao+VYn5N2tq+yvd4CiGs1SedImirpSUm3SPp4h7Fr1sRTd9NnQtP5kZJOlPRI/Rzay733kHRnnef3kl5o8mP7EGCD+bTMiIiIiIiIiBhAhkKiCwDbT1Eaye/afLxWUe0InNgfcS3CTqY06R8DrEj5vUzp5ZqRNSHYZftrTcePpjT1XxN4I7CLpLZvUpT0duBIYFtgBeAe4PR5WEdEREREREREDBJDJtFVnQh8RNLwpmPvoazzIkm7S7pN0gxJd0v6dKeJJI2uFUmPSrpH0j5N5w6VdJakk+pct0oaV8+dDKwBXFArivZvqlhavI65QtLXJP2pXn+JpJWa5j9b0sO1EupKSfNUgdTTulurv3pad8ucS0g6vY5dss2QTYATbM+0/ZztG21fNJdL+ADwTduzbN8L/BL4RA9jz7Z9q+1ngK8Bm0taay7vHRERERERERGDxJDqUWT7GkkPAR8GGr2kdgFOs/2cpEeA9wN3A5tTkl9/tX1D8zySXgFcAJxHqQZbDbhM0u22L67Dtqn32R04HPgBsKntXSS9DdjD9mV1vjXbhDse2IpS9XQR8EXggHruIkoi5xngKOBUYOzcPhdgfq4bSUsDvwIeBXbusCXzL8APJX0fuMb2v/oQ532SDFwKfMn21ObwWn7esMMcajOWOv6uPsTwgttnzUpD7BhyBsMbFyMiIiIiIubWUKvoAjiJun1R0rKULWwnAtj+re27XPwRuAR4W5s5NgFWtn2Y7Wds3w38HPhY05irbf+uJnlOBjaawziPt32H7dnAWTQlsmwfZ3uG7aeBQ4GNJC3Xw1zH1v5k0yRNAy5sPjmf170s8HtK0mj3HvqObQdcBUwA7pE0WdImHcZOrfceA7wBGEFJ7jX8HjhA0ghJa1OSgMNfNkvxO2B7Sf9dE3JfBdzD+IhFytiuLsaPGtXfYURERERERCwQQ6qiqzoJOETSqpRti3favhFA0lbAIcC6lCTfcOCWNnOMAUbXpFHDYpTETcPDTT/PAoZJWtz2c32Ms/X6rhrjYsARlETRysB/6piVgCc7zLWP7V80vkjaghcr2ub3ujcFlgB2tO1Oi7P9BKVC7YC6LfPbwG8krdZ6ne1uYFL9OkXS3sBDkpa1PR3YB/g+8E/gMUrPrR073PdySYcA5wDLUfp7zQDm+I2a6w0fzhUbbzynl0VEREREREREPxlyFV11i9xVwE6UbYsnAUhaipL8+DYwyvZISvWP2kxzP3CP7ZFNnxG2t+5rGPOwhPGUKrQtKYmaNevxdnH2agGs+xLg68DlkvpUFlK3IH4bGE1pEN/rJY3w6/WP297J9qtsb0D5e3tdD/f7oe11bL+SsvbFgb/1JdaIiIiIiIiIGLyGXKKrOhHYG3gLL26BWxJYitJX6rla5fQ/Ha6/Dpgu6cuSlpa0mKQNe9h612oK8Jq5jH0E8DSlcmk45Q2C82K+r9v2N4HTKMmuldpNJOmoeu3ikkYAn6FU1z3WZuybJK0n6RWSVgSOBa6w/WQ9v5akFWs8WwF7UvqitbvvsHpfSVoD+BnwvVphFhERERERERFD2FBNdP0KWB643PZDALZnULbAnQU8QamcOr/dxbXv1AcofbPuofSQ+gWlwqovvg4cXHtmfXEOYz8JuA/4N/B3SlP3ubag1m37a8BvKM3q21VpDQfOBaZRmuCPoTTwb+c1lD5cMyiVV0/z0q2Jb6BstZxBebY72b61cbK+9XKn+nUYJQnXTUnc/ZnSJywiIiIiIiIihjj10GZpwJP0FCUpcqztJDPmgqR3Ar+wPbcVaINK7d+1H6XKbZkemukzbtw4T5o0qdPpiFiAGm88TZ+8iPlroP63NVDjioiIiIFJ0vW2x7U7N6ib0dse1t8xDAEbUqq3Fgm2JwIT+zuOiOjd5O7uF/7nN/pu/KhR7Dl6dH+HERERERHRLwZ1oivmjaTvUbYT7tbfsURExLyb3N0NkERXRERERCyykuhahNn+HPC5/o4jIqKdsV1d2cY0h1IBFxERERGLuqHajD4iIiIiIiIiIhYxi3yiS5IlzZR0RB/HnyDp8PrzFpIeWLARDlySrpC0R3/HMSckfVJSd/29r93f8URERERERETE/LPIJ7qqjWwfBCBpzZoE6W757LAwA2pKwHVLekzS5Qs7hnkhaaSk4yQ9LGmGpDskfbmH8YtJOlzSg3X8jZJG1nM/afldPC1pRod51pV0nqRHJT0u6WJJ6zXO2/6l7a75v+KIiIiIiIiI6G/p0dXZSNvP9XMMG9m+U9JKwFbADyS9tr45cI5IWnwhr+doYBngdcCTwLqUNzx2MhHYDHgz8C9gA+ApANt7AXs1Bko6AfhPh3lGAucDuwMzgK8C5wGvneuVRERERERERMSgkETXfCRpNPB9YHOgGzja9rH13KHA+pTkzYcoyZzdbE/qbV7bU4GTJc0GTpH0A9uPSboX2MP2ZU33WNv2zpLWBO4B9gAOAe4FNpd0NvA2YGngJuAztm+t158AzATWrGv4OzDe9l31/Lvr+lYBTgbUQ9ibAAfbfqJ+/0f9tHtuywP7UhJ799XDf+swdhngI8D72523fR1wXdP4o4GDJa1o+7Ee4n2Z22fNSmPnGDDGjxqVN+lFRERERET0IlsX5xNJrwAuoCSPVgXeBewr6T1Nw7YBzuDFqqMfzOFtzqMkJ984B9e8nVJV1YjjImAd4JXADcCpLeN3pFRXLQ/cCRwBUKvKzgEOBlYC7gLe0sN9/wIcIWl3Sev0EuN/Ac8BH61bHe+Q9P86jP0I8ChwZS9zNmwOPDynSa6IgWRydzenTZnS32FEREREREQMeKno6myq9JKCpTfbvq2H8ZsAK9s+rH6/W9LPgY8BF9djV9v+HYCkkylVTH1m+1lJU4EV5uCyQ23PbJrjuMbPtQLsCUnL2X6yHv51rYpC0qnAd+vxrYG/2/5VPXcM8IUe7vu/wOeBvYGfSboP+F/bF7UZuxqwHGV746spibjLJd1h+9KWsbsBJ9l2bwuXtBrwQ2C/3sa2s97w4Vyx8cZzc2nEfJXKwoiIiIiIiL5JRVdnK9ke2fTpKckFMAYYLWla4wMcCIxqGvNw08+zgGGS+pxslLQEsDLweF+vAe5vun4xSd+QdJek6ZTtjFAqtDrF2GjcPrp5rppoup8ObM+2faTtNwArAmcBZ0tql6SbXf88rF53M6XybevmQZJWp1SondTpvk1jVwYuAX5k+/TexkdERERERETE4JdE1/xzP3BPS3JshO2te72y77albPFr9KCaCQxvOv+qNtc0Vz6Nr3NsSamgWrMe76nXVsNDwOqNLyrlbqt3Ht4UgD0dOJLSnP7VbYbc3CbWdnYFrrF9d0+Das+vS4DzbR/RlxgjIiIiIiIiYvBLomv+uQ6YLunLkpau1VMbStpkXieWtIKknSjb8I5q6jc1GfiYpCUkjQM+2stUI4CngccoCbIj5yCM3wIbSPpwrULbh/aJtUbMEyRtImlJScOAzwHTgNtbx9Zm91cBB0laStLrgB2AC1uG7gqc0FOQkpalbBX9k+0D+ry6iIiIiIiIiBj0kujqbJqk7qZPj32ebD8PfAAYS3nb4VTgF5TKqbl1k6RuSlP4PYDP2/5q0/kJwFrAE5QG8qf1Mt9JwH3AvylvVPxLXwOpb37cDvgGJVG2DvCnni4Bjqc8hweBdwPvs93dYfyOlO2fj1GSahNsX944KenNlF5eZ7deKOkiSQfWrx+i9EvbveX3t0Zf1xoRERERERERg5P60NN7SJP0FKXK6VjbE/o7nliwJO0OHA0MA9bvaRvkuHHjPGnSpIUWW0QnW9x4I5O7uxnb1dX74CGisd68EGLONF5ckOcWnQzUvyMDNa6IiIgYmCRdb3tcu3OL/FsXbQ/r7xhi4bF9PKXSLCIGsLFdXYwfNar3gREREREREU0W+URXRMRgkOqmiIiIiIiI3g26Hl2SLGmmpLxNbz6TtIWkB/o7jgVJ0sT698e1qX5EREREREREDBGDLtFVbWT7oMaXmrRYuz8D6omkE2qM27QcP6Ye/3gf5xkvaVJtrv5QbcL+1nmIa4E9N0mrSTpH0lRJT0q6pS/rlHRIjWvLluOvl3RlXfsUSZ/rYY7hkn7UdO8rG+dsHwJsMC9ri4iIiIiIiIiBabAmugajO4DdGl9qNdF2wF19ubi+9fEY4EhgFLAG8CNg2zkNZCFVMp0M3E95k+KKwK7AlF7iWgv4KPBQy/GVgN8DP61zrQ1c0sNUPwNWAF5X//z8XK0gIiIiIiIiIgaVIbd1S9Ibge9RkhyzgXOA/Ww/U88b+H+U5MerKMmjE4BTKJU+vwd2bhr/fuBwYE3g78Betm+u574M7AMsCzwIfNb25R1CuwDYWdLytp8A3gvcDIxoif9TwH7AapRE0c6UZNhhwO62f90y5wVzsO69gX2BxSXdX+e4qZ77JDURJekLwJeB54EDbR8vaRPgQmBV28/VcR8BJtge22a9mwCftz2zfr+xw3Np9oN63x+1HN8PuNj2qfX708Bt7SaQtB6wDbCa7en18PV9uPfL3D5r1gtvgYroT4vaGxcjIiIiIiLm1lCs6HqeksRaCXgz8C7gsy1j3gu8AdgU2J9SAbQTsDqwIbAjlO1ywHHApymVRD8Fzpe0VE2o7A1sYnsE8B7g3h7iego4H/hY/b4rcFLzAEnbAYfWc8tSEjaP1XUMA86dx3V/EHgTsL7tzeuxjWx32T6zfn8VsBywKiX59cOanPtrjeXdTfPtTKncaucv9dqPSVqjh7iBF9b+jO3ftTm9KfC4pGskPSLpgh7mfBNwHzCxbl28pSbkIgatvIEwIiIiIiKib4ZcRZft5uqdeyX9FHg7pXKr4aha7XOrpL8Bl9i+G0DSRcDGwInAp4Cf2r62XneipAMpiZd/A0sB60t61Pa9fQjvJOBbkk6rMe1GqS5r2AP4Zk0qAdxZY3orMLVRSTUP6/667cd7ifFZ4LB6r99J6gbWoySuTqQkty6StAIludeaTGvYjlKdNQF4raRbgE81re0FkrooWzL/p8NcqwGvpyTZbgG+CZwOvKXD2A0pFW2jKUm/30r6u+22VWCdrDd8eN5yFxERERERETGIDLmKLknrSrpQ0sOSplMSKCu1DGvuFTW7zffGHqExwBckTWt8KFVfo23fSdkGeCjwiKQzJI3uKTbbVwMrAwcDF9qe3TJkddr37HoMWKmn3lp9XPf9bS592b1aEmqzePF5nAJ8oCamtgeusv1Q6wQAtp+wfYDtDSg9xSYDv5GkNsMnAifbvqdDTLOBc23/1fZTdfxmkpbrMPZZ4HDbz9j+I/B/dE6iRURERERERMQQMeQSXcCPgX8A69heFjgQaJdc6Yv7gSNsj2z6DLd9OoDt02y/lZIQM3BUH+Y8BfgCLdsWm+63Vpvjf6ZsffxgD/P2Zd3uQ3wd2f53jeVDwC503rbYet1U4NuUCqsV2gx5F7BPTdI9TEn4nVV7oEHpZdYce+Pndr/Xm/sSU0REREREREQMPUMx0TUCmA50S3ot8Jl5mOvnwF6S3qRiGUnvkzRC0nqS3ilpKUoSajalT1ZvjqVswbuyzblfAF+U9IZ6v7UljbH9JPBVSs+rD0oaLmkJSVtJ+uY8rHsK8Jo+jGt2EqWv2X/RQ88wSUdJ2lDS4pJG1HjutP1Ym+Hvomw3HFs/D1L6ov2wnj8e+JCksZKWoGyHvNr2tDZzXQn8C/hKvfdbgC2Ai+dwnRERERERERExyAylHl2NKp8vUprL709509+ZwDvnakJ7Un0L4g+AdSjJrKspyZSlgG9Q3nL4LHANsGcf5nwcaPtmRttnS1oROI3SDP5eSuXUfba/K2kKZdvjqcAMytsEj6iXz826D6X0HVu6xv5Ib/FTkls/pmwlnNnDuOF17CqU53Ytpbn+y7QmvyQ9Dzxhu7ue/0PtjfbbOu/VwPim8bcCR9o+1fazkralJA0PoDSm39X2P/qwtoiIQW9yd/egfWPs+FGj2HN0j10AIiIiIiJ6JHuedrMtdJKeAp4GjrU9QdKywJPA8h0qfGI+k3QX8Gnbl/V3LHNK0iHAfpRE5TK2O1bhjRs3zpMmTVposUVEzKstbryRyd3djO3q6n3wANOIOy8BWbAaSdCB9pwHalwRERExMEm63va4ducGXUWX7WEth3YA7kqSa+GQ9BFK9dwf+juWuWF7IqWZfUTEkDRYk0WDtQotIiIiIgaWQZfoaibpGmAksEd/x7IokHQFsD6wi+3/9HM4EREREREREREvMagTXbY36+8YFiW2t+jvGCIiIiIiIiIiOhmKb12MiIiIiIiIiIhF0EJNdEmypJmSjuh9dI/zXCRpt/kVV9O8lrT2XF57r6Qt53dMC5KkKyQtMts+JW0pqVvSfwbb7yoiIiIiIiIietcfFV0b2T6o8UXSkpIOlfTPmgS7V9JxktbsNIHtrWyf2NuN5iVxNb9JGifpQklPSJom6e+SjpC0fH/HNj+1S/hJ+rikqzuMX6Mmn5o/lvSFpjHjJd1X/378RtIKPdx/M0nXSZoh6WZJb22cs32Z7S7gX/NhqRERERERERExwAyEHl2/AlYDxgM3AssAOwPvAn7ZPFCSAA22RuiSNgMuAY4APml7iqQ1gE8CGwFX9GN4/cr2v4CuxndJrwbuBM6p3zcAfgq8D7gB+BnwI+BjrXPVBNj5wGeAXwM7AhdIeo3tJ+Y0tttnzRqybwEbP2oUe44e3d9hRERERERERMxX/dqjq1b+vBvY1vZfbT9n+0nbP7T9yzrmilr59CdgFvCa5i13ktaW9EdJT0qaKunMevzKepubapXQDvX4pyTdKelxSedLav2//a0l3V3n+pakV9Tr1pL0B0mP1XOnShrZx6V+Ezje9tdtT4GS4LF9iO0r6vyvkHRwrVx6RNJJkpar59asVU67SfpXvX9zVdy0pmqomXXsmpKWr1Vkj9ZKsgslrdbD7+MTkm6rYy+WNKYe37+l4upZSSf0ce1zalfgStv31u87ARfYvtJ2NzAB+LCkEW2u3QyYYvts28/bPgV4FPjwAop1UJrc3c1pU6b0dxgRERERERER811/V3RtCVxn+/5exu0CbAXcDqjl3Nco1VLvAJYExgHY3lySKVsl7wSQ9E7g68D/ALcC3wbOADZvmu9DdY4u4LJ6z1/U+34duBJYllJxdCiwb0+BS1oGeDNwcC9r/Hj9vAN4BDgJ+EFde8NbgfWAdYHrJP3a9m22X0i4STqyjvt3jfN4YHtgMeC4OucH28T5QeBA4APAP4EDgNOBzWx/k5KsQ9LqwLXAWb2sZ27tSvmdNmwAXNP4YvsuSc9QnsH1rcvg5X8/BGw4N4GsN3w4V2y88dxcOqAN1Sq1iIiIiIiIiP5+6+KKwEN9GHeC7VtrxdezLeeeBcYAo20/ZbttL6hqJ+A42zfYfhr4CvDmln5gR9l+vG6pO4ay/Q3bd9q+1PbTth8Fvgu8vQ+xL095zg83Dkj6Zq3CmimpkQDbCfiu7btr5dJXgI9Jak5GTrQ92/ZNwE2UbY80zbsDZQvoR2w/a/sx2+fYnmV7BmXrZKeYPw18vSbOngOOBMY2qrrq/EsDvwG+Z/t3Paz5N3V90yRNo2w17JWktwGjKNtZG7qAJ1uGPgm0q+i6BhgtaUdJS6i8sGAtYHhf7h8RERERERERg1t/J7oeA1bpw7ieKr72p1TtXCfpVkmf6GHsaOC+xpeaUHoMWLXDve6r1yDplZLOkPRvSdOBU4CV+hD7E8B/aFqn7f1rFXNvHaYAACAASURBVNa5vFhV95LY6s+LUxI/DQ83/TyLl/a22phSrfWhmohD0nBJP63bIadTqtFGSlqsTZxjgO81JacepzzX5mfzS+B220f1suYP2h7Z+ACf7WV8w27AOfX30tBNqUxrtiwwo/Vi248B2wL7AVOA91Kq8h7o4/0jIiIiIiIiYhDr70TXZcAbe+obVbnjCfth25+yPZpSlfQjdX7T4oOUhA7wwrbCFSnb/BpWb/p5jXoNlG2LBv7b9rKUhvmt2+TaxTeTstWvtz5RL4mt3vs5SsKmR5JWpiTN9rbdvC/tC5Stjm+qMTe2aLaL+37g080JKttL276m3uOAOtcne4tnbtRqse2A1rdp3kpT5Zqk1wBLAXe0m8f2H21vYnsFyrbP9YDrFkTMERERERERETGw9Guiy/ZlwKXAuZLeIGlxSSMk7dVLZdYLJG3XlCh7gpKMer5+nwK8pmn4acDuksZKWoqyPe/apsbnAF+qTdxXBz4HnFmPj6BUF02TtCrwpTlY6v7AJyQdIOmVNe7VgFc3jTkd+LykV0vqqrGdWbcR9rT+xSn9wk61fWbL6RHA7BrzCsAhPUz1E+ArKm85RNJykrarP28F7EOp1JrdtyXPsQ8B04D/azl+KvABSW+ricnDgF/XrZgvI2njum1xWUoPtgdsX7yAYo6IiIiIiIiIAaS/m9EDfBQ4iJJQWgWYSkl+HdbH6zcBjqlvKJwCfM72PfXcocCJtVpoT9tnSZpASQwtT+np9LGW+c6jNDlfDjiBsl0PYCKlQfyTwJ3AycDn+xKg7atrI/xDgAMkQdlOdx7w/TrsOMr2xSuBYcDFwP/2YfrVgLcBb5D0uabj61N6jJ1GeaYPAt+hTSP6GuO5NcF2Ru3L9STl93A2sAOwMnBbjR3gFNt79SG+vtoNOMn2S6r3bN8qaS9KwmtFShXg7o3zkn5SxzVi2R/Yuv78e0oCLVpM7u5OU/p+Nn7UKPYc3frS14iIiIiIiJgXaskrLNibSU8BTwPH2p6w0G4cAUh6FyXJuRSwte3W6rGXGDdunCdNmrRQYluYtrjxRiZ3dzO2q6v3wbFANJ7/UHyrZ/SvRgJ7MP7dGsyxDyYD9TkP1LgiIiJiYJJ0ve1x7c4t1Iou28MW5v0imtm+HBjZ33EMBEmy9K9U00VERERERCwY/d2MPiIiIiIiIiIiYr4YEokuSZY0U9IRc3DNFZL26HBuzTrnQOhhFvORpIn170p+vxERERERERFDzJBIdFUb2T6o8UXSkpIOlfTPmti4V9JxktbsvxBB0rKSjpH0L0ndku6s31fqz7jml05JQkknSDq8wzU71WfR+Myqc7yhaczrJV1Zz09pabzfPNeSkn5Vf9+WtEXzeduHABvM+0ojIiIiIiIiYqAZSomuVr8CtgHGU96guBHlbYrv6q+AJC0JXE5JtLwXWBbYDHgMeONczPeyiiRJi81jmAud7VNtdzU+wGeBu4EbAGoS8PfATylvXlwbuKSHKa8GdgYeXqCBR0RERERERMSAMiS3bknaEng3sK7t++vhJ4EftgwdI+lPwH8DfwbG257aZr7RwE+AtwKPA0fZ/nk99wpgf+BTlEbnlwN72X68TWi7AmsA77DdXY89Anyt6V4H1LleCdwPHGT73Hru4/XcdcBuwI8krQbMBsYAbwe2lbQUcDiwVl33L20fWucYBvwC2ApYDPgn8H7bUyStAHwHeA+wNPBH2x+s130K+DKwAiWRtJftB9uscX7YDTjJL74SdD/gYtun1u9PA7e1u9D2M8AxNebn5yWI22fNGpJNw/PGxYiIiIiIiBiqhmpF15bAdU1Jrk7GA7tTkkpLAl/sMO504AFgNPBR4EhJjcqwfYAPUpJMo4EneHlCrTmu3zcludq5C3gbpQptInCKpFWazr+JUu30SqDRk2x8/XkEJQk1k5JUGwm8D/iMpA/WsbvVuVenVEftRUmUAZwMDKdUnL0SOBpA0juBrwPbA6sA9wFn9LCGuSZpDLA5cFLT4U2BxyVdI+kRSRdIWmNB3H9RMLari/GjRvV3GBERERERERHz3ZCs6KIkcB7qw7jjbd8BIOksylbHl5C0OqWS6/22nwImS/oFsAuleuvTwN62H6jjDwX+JWkX28+1iev6ngKyfXbT1zMlfYWyrfG8euxB29+vPz8nCeA823+qx54Crmia42ZJp1MScb8Bnq1xrG375kY8NZm2FbCi7SfqtX+sf+4EHGe7sZXwK8ATkta0fW+HpUytsTUMB77Z09qrXYGrbN/TdGw14PWUKr1b6jynA2/pw3xzbb3hw7li440X5C0iIiIiIiIiYj4aqomux4B1+zCuuYfTLKDdfq7RwOO2ZzQduw8YV38eA5wr6T9N558HRgH/bhPXKvRA0q6UrXpr1kNdQHOj+nZVai85JulNwDeADSmVaksBjQTayZRqrjMkjQROAQ6qxx5vSnI1G03tlwVgu1vSY8CqwL0dlrJSc6JP0gkdxrXaFTiy5dhs4Fzbf61zTaQk0paz/WQf540YUCZ3dw/JrbHRv7I1OSIiIiIWdUN16+JlwBtr/6p59SCwgqQRTcfW4MUk1v3AVrZHNn2G2W5NcjXieo+kZdrdqG7b+zmwN6WyaiTwN6C5NMptLm09dhpwPrC67eUo/cUEYPtZ2xNtr09phP9+SnLp/rrOkR2ewZimOJehVIW1W+Nck/QWSlLtVy2nbuala2z8LCIi4gXZmhwRERERi7ohWdFl+zJJl1IqrfYCbqI0V98JeMb2cXMw1/2SrgG+LumLlEqxT1Le6gcliXSEpN1s3ydpZWAz2+e1me5kylbHcyTtC9wBLF+PTaZURxl4FEDS7pSqrDk1glKd9ZSkN1J6eF1S53wHMBX4OzCdspXxedsPSbqI0uD+/wHdwJttX0lJnJ0h6TRKE/gjgWt72LY4t3YDzmmpngM4nvLMjgVuBSYAV9ue1m6S2oy/kQRbsjbgf7qpuX1Evxvb1ZWtsREREREREfPZUK3ogtI0/nfAmZQ3D/6Nst3wsrmYa0fKVsIHgXOBQ2xfWs99j1I9dYmkGcBfKA3jX8b205SG9P8ALqUkmq6jbE281vbfKW89/DMwBfgv4E/t5urFZ4HDajxfBc5qOvcqSsXUdErS6o+U7YtQ+o49W+N7BNi3xn05Jbl0DqX32VrAx+Yiro5qMmp74MTWc7b/ABwI/LbGtTYlede49lZJOzVdcjtlu+OqwMW8+FbKiIiIiIiIiBjCNBSKXCQ9BTwNHGt7Qn/HEwOXpEMoPdCWApax/XynsePGjfOkSZMWWmyx6Gj05kpFV8SL8t/FwjFQn/NAjSsiIiIGJknX2x7X7tyQ2Lpoe1h/xxCDg+2JwMT+jiMiIiIiIiIi5r+hvHUxIiIiIiIiIiIWIUl0VZIsaaakIxbiPbeQ9MDCut+8qM9n7f6OY15Jmlh/z5Y0JCoaIyIiIiIiIqJIouulNrJ9UOPLQEvuSLpC0lOSVm86tqWke/sxrJeQtGa7JJKkEyQd3uGanSR1N31m1TneUM+/Q9L/SXqyt7VKWl/SJElP1M9lktZvnLd9CLDBvK80IiIiIiIiIgaaJLoGn5mUNyAOGbZPtd3V+FDeGnk3cEMdMhM4DvhSH6Z7kPLGzRUob7M8Hzhj/kcdEREREREREQNNEl19JOmNkv4saZqkhyT9QNKSTec3kHSppMclTZF0YD2+lKRjJD1YP8dIWqpl7gMlTZV0r6SdegnlWGDHTpVmkl5XK7+mSbpV0jb1+KaSHpa0WNPYD0m6uS/ra7nHWyXdL+kdfXl2c2E34CTXV4Lavs72yZTkV49sT7N9b71WwPPAgKnKi4iIiIiIiIgFJz2K+u554PPAJGA14CJK5dExkkYAlwHfBj4ALAE0tssdBGwKjAUMnAcczItVWa+iVB6tWsf9TtIk27d3iOPfwM+BQ4Gdm09IWgK4gFL99D/AW4HzJI2z/RdJM4F3ApfWS8YDp/W2vpZ7vAf4BfAR29f19MDmhqQxwObAJ+ZxnmlAFyWZ+9W5meP2WbNeeN15xPw0ububsV1d/R1GRERERETEkJOKrj6yfb3tv9h+zva9wE+Bt9fT7wcetv0d20/ZnmH72npuJ+Aw24/YfhSYCOzSMv0E20/b/iPwW2D7XsL5OvABSa29pjalJHe+YfsZ238ALgR2rOdPb/xck3Nb12O9ra9hO+BnwNZ9SHJNrdVh02rSaXwv4xt2Ba6yfU8fx7dleySwHLA3kGxVDChju7oYP2pUf4cREREREREx5KSiq48krQt8FxgHDKc8u+vr6dWBuzpcOhq4r+n7ffVYwxO2Z/Zw/mVsPyrpB8BhwI9b7nW/7f+0zLdq/fk04BpJnwE+DNxg+74+rK9hX8qWwlt6iq9ayfZzjS+STujDNVASXUf2cWyPbM+U9BPgUUmvs/3InFy/3vDhXLHxxvMjlIiIiIiIiIhYCFLR1Xc/Bv4BrGN7WeBASg8ogPuBtTpc9yAwpun7GvVYw/KSlunhfCffAt4BvKHlXqtLav69rkHZ7ojtv1MSX1vx0m2L0PP6GrYDPihp3z7EN8ckvYWSrPvVfJz2FZTE3aq9DYyIiIiIiIiIwS2Jrr4bAUwHuiW9FvhM07kLgVdJ2rc2nx8h6U313OnAwZJWlrQSpV/UKS1zT5S0pKS3UbZBnt1bMLanAd8B9m86fC3lDYX7S1pC0haUnmHNbx08DdiH0ger+T49ra/hQeBdwD6SPttbjHNhN+Ac2zOaD0p6haRhlN5nkjSsh0b575a0saTFJC1LqVJ7ArhtAcQbEREREREREQNIEl29c/3zi5QqqBmUZvBnvjCgJGbeTUkqPQz8k1JtBXA4pcH7zcAtwA31WMPDlETMg8CpwF62/9HH2L5HaSLfiOMZYBtKxdZU4EfAri3znQ5sAfzB9tSm4x3X18z2vyjJri9L2qOPcfaqJrK2B05sc3pzYDbwO0qF2mzgkqZrb216W+VIyhqfpGwnXRt4r+2n5lesERERERERETEwyXbvoxYBkp4CngaOtT2hVgM9CSxfq6diCJB0CLAfsBSwjO3nO40dN26cJ02atNBii4hYlDXecpveiAvWQH3OAzWuiIiIGJgkXW97XLtzaUZf2R7WcmgH4K4kuYYW2xMpb76MiIiIiIiIiCEmia42JF1D2QI337bmRURERERERETEgpVEVxu2N+vvGCIiIiIiIiIiYs4M2Gb0kixppqQj+juWGDok3SXpGUmtb76MiIiIiIiIiEFuwCa6qo1sH9T4UpNfa/dnQHND0oGS7pHULekBSW3faDiUSNpW0mRJ0yVNlXS5pDV7GP96SVfWZzRF0ueazv2fpEfrXDdJ2raHefaVdHcd+6CkoyW9ULloey3gyPm0zIiIiIiIiIgYQAZ6omu+aE509MO9dwN2Aba03QWMAy7vr3jm1pw8w5qMPAn4ArAc8GrgR8B/OoxfCfg98FNgRWBt4JKmIZ8DVrG9LLAncIqkVTrc/gLg9XXshsBGwD59jT0iIiIiIiIiBq9B26NL0iuA/YFPURrHXw7sZfvxWjl0D6WZ/CHAvcDmkj4BfAl4FXAdsKft++p8Bv4f8Pl6/hjgBOAUYANKImZn289I+hvwFdsX1GuXAB6iJLMmt4S6CXCx7bsAbD8M/KxpHfcCe9i+rH4/FFjb9s5N6/gEcBjQBXwFuB74JbAGcIrtveu1H6/P4zpgd+BxYGdgXeBrwFLAl2yfWMcvBRwBbF/PnQt83vZsSVvUtX+/PpNLJX2+PpO3UpJWtwJvt92awBoL3GO7kdCbAZxDZ/vVZ3Rq/f40cFvjpO2bm8YaWAJYnfLMX6LxnCvVOOeqCvD2WbNeeN15DF7jR41iz9Gj+zuMiIiIiIiIWAgGc0XXPsAHgbcDo4EngB+2jHk78DrgPZI+CBwIfBhYGbgKOL1l/HuBNwCbUpJoPwN2oiRVNgR2rONOoiSQGrYGHmqT5AL4C7CrpC9JGidpsTlfKm8C1gF2oCTgDgK2pCTgtpf09paxN1Mqo04DzqAk29auMf9AUlcdexQlCTa2nl8V+GrTXK8CVgDGUCqpvgA8QHl+oyjP023ivQF4bd02+I6m+3WyKfC4pGskPSLpAklrNA+QdKGkp4BrgSuASZ0mkzRe0nRgKqWi66e93D+GqMnd3Zw2ZUp/hxERERERERELyaCt6AI+Dext+wF4oRLqX5J2aRpzqO2Z9fynga/bvq1+PxI4UNKYRlUXcJTt6cCttWrrEtt31/EXARsDJ1IqnSZIWraO3wU4uV2Qtk+p1WK7A4cCT0n6lu1vzMFav2b7KeASSTOB020/UuO6qsb1xzr2HtvH13NnUpJih9l+ul7/DLC2pJso1V//bfvxpmdyGqVqDEo11CH1WiQ9C6wCjLF9JyVZ2G7Nd9eKsP2As4ARks6g/L6621yyGvB64N3ALcA3KUnItzTN+f5aObcl8No2VWTN9z8NOE3SOsCuwFxlOtYbPpwrNt54bi6NASIVeREREREREYuWwVzRNQY4V9I0SdMoW92ep1QaNdzfMv57TeMfp2xtW7VpTHNCZHab710Ath8E/gR8RNJIYCvgVDqwfartLSlbLPcCDpP0njlYa5/i6jAW2+3GrwwMB65veia/r8cbHq0JtoZvAXdSEmZ3SzqgU8C2/2J7e9srA28DNqck3dqZDZxr+6/1fhOBzSQt1zLns7YvolTobdPp3k3j/0nZXvmj3sZGRERERERExOA3mBNd9wNb2R7Z9Blm+99NY9wy/tMt45e2fc1c3v9EylbA7YA/t9y3rZqoOZuytXDDengmJeHU8Kq5jGdOTaUkmDZoeh7L1Yb5DS/Zlmh7hu0v2H4N8AFgP0nv6u1Gtv8K/JoX19zq5pZ7NX5Wh/GLA2v1dt+5GBsRERERERERg9hgTnT9BDhC0hgASStL2raX8V+RtEEdv5yk7ebh/r+hbLf7HKVnV1uSPi7pfZJGSHqFpK0ovbWurUMmAx+TtISkccBH5yGmPqtb/34OHC3plTXWVXuqNJP0fklrSxIwnVJB93ybcW+V9KmmeV8LbEPpV9bO8cCHJI2t2xMnAFfbnibptZK2krR0fUY7U6rD/thuIkl7NN13fco2zEH3lsuIiIiIiIiImHODMdHVqPb5HnA+ZRvdDEoS5U0dL7LPpTRfP6M2Kv8bZcvh3AVhz6a8SfDVlGqlTqZTmrb/C5hG6T/1GdtX1/MTKBVHT1C27J02tzHNhS9TtiL+pT6Ty4D1ehi/Th3TDfwZ+JHtK9qMm0ZJbN0iqZuyJfJcytpfxvYfKM/ot8AjlMb44+tpUXqbPQI8Skks7mD7BgBJb6v3aHhLve9M4Hf1c2APa4qIiIiIiIiIIUJ2u5fm9b/6hr2ngWNtT5C0LPAksLztaf0bXSHpq8C6tnfudXAMCJJup/RlO8v2J3oaO27cOE+a1PHljjEIbHHjjUzu7mZsV28v/ox2xo8axZ6jR/d3GLGIaLw8Ii8BWbAG6nMeqHFFRETEwCTpetvj2p0bsG9dtD2s5dAOwF0DKMm1AvBJyhsXY5Cw3VPFWkRUk7tLoWQSXRERERERMZgM2ERXM0nXUN5YuEd/xwIg6VPAMcDJtq/s73giorOxXV2pEJgLjeqKiIiIiIiIwWRQJLpsb9bfMTSz/XNKI/eIiIiIiIiIiBggBmMzegAkWdJMSUcshHudIOnwHs53S3rNgo5jYZC0haQHmr7fK2nL/oxpfpL0yfr7sqS1+zueiIiIiIiIiJh/Bm2iq9rI9kEAktasyYsbmgdIWknSM5Lu7cuEkj4u6ereR77Idpftu+fkmnqvVST9UtJDkmZI+oekiZKWmdO5BhpJIyUdJ+nhurY7JH25h/GLSTpc0oN1/I2SRjadf42kC+u5qZLavsFR0rqSzpP0qKTHJV0s6YW+XLZ/aTudySMiIiIiIiKGoMGe6GpnGUkbNn0fD9zTX8F0UpvZ/xlYGniz7RHAuym9yNbqz9jmk6OBLuB1wHLANsBdPYyfCGwGvBlYltLk/ykASUsClwJ/AF4FrAac0mGekcD5wHrAKOA64Lx5W0pEREREREREDAaDokfXHDoZ2A34Uv2+K3AS8KnGAEkH1O+vBO4HDrJ9rqTXAT8BlpDUDTxnu1FVtLyk3wKbA38Hxtu+q85nYB3bd0raGvg2sDowHTja9rfbxLkfMAPY2fZ/AGzfD3yuKc7NgO8B6wJ3AJ+zfU09dwVwFfBO4L8pSbPxtqdKWpOS3Ps48DVgeI3jiHrtUsBRwPb1VmcBX7b9dKeHKulVwN3A6rYfq8feAPweGG372ZZLNgEOtv1E/f6P+mk39/LAvpQKvfvq4b81Dfk48KDt7zYdu7ndXLavoyS3GnMfDRwsacVG3H11+6xZacg9yE3u7mZsVwr4IiIiIiIiFhVDMdF1CnBVTWatC4wArqUp0UWpLHob8DCwHXCKpLVt3yZpL2AP229tmXdH4L3ADcCJwBHAx9rc/5fA9ravqgmcV3eIc0vg140kV6ta8fVbYB/g9Brnb2ucjYTNeGArSrLuIuCLwAFN07yVUtm0LnCdpF/bvg04CNgUGAuYUvF0MDChQ6zYfrgm17YHflwP7wyc0SbJBfAX4Ij6DK62/c9OcwP/BTwHfFTS5ykJwu/Z/mE9vylwr6SLKAm0vwH/a/uWHuZs2Bx4eE6TXDE0jO3qYvyoUf0dRkT00eTu7vwDwwKWfwCIiIiIoW4oJroeAG6nJJLeQanmegnbZzd9PVPSV4A30vMWt1/XaiEknQp8t8O4Z4H1Jd1Uq5me6DBuReChHu73PuCftk+u30+XtA/wAeCEeux423fUmM6ibA9sNtH2bOAmSTcBGwG3ATtREkWP1GsnAj+lh0RXdSIl8fZjSYtRkn+t92z4X+DzwN7AzyTdV+95UZuxq1G2N65LSQyuA1wu6Q7bl9bz76j3upxS9XaepNfafqZTsJJWA35IqZ6bY+sNH84VG288N5dGREQMSPkHgIiIiBjqhmKiC0py6+OUnk+bUxInL5C0KyX5sWY91AWs1MucDzf9PKte085HKNVR35B0M3CA7T+3GfcYsEoP9xsN3Ndy7D5g1TmIqdP51rnvq8d6cx7wk/qGyXWBJxvJv1Y1wXYkcKSkZSmVZmdLWsP24y3DZ9c/D6vX3SzpDGBrSm+u2ZSqsIsAJH2b8oxfB9zU7v6SVgYuAX5k+/Q+rC0iIvrZ2K6u/ANDRERERMyTodiMHuAcSkXU3U09nwCQNAb4OaXSaMXag+tvgOoQz8uNbf/V9raU/l+/ofS/aucy4EOSOv0OHgTGtBxbA/j3vMTXYe416rEe2X6Ksp6dKM3iT+75iheum05Jei1D+62cjX5bnZ79zT2ce5m6XfIS4PxGX7KIiIiIiIiIGPqGZKLL9kxKk/Y92pxehpI0eRRA0u5A81sapwCr1Tf9zRFJS0raSdJytW/VdOD5DsO/S3m74Ik1+YakVSV9V9J/A78D1pU0XtLiknYA1gcunNO42jid0qB9ZUkrAV+l81sMWzWq5bbp6RpJEyRtUp/JMMp2w2mUbaUvUZv6XwUcJGmp+lKAHXhxracAm0rasm6Z3BeYStmG2XrfZYGLgT/ZPqD1fEREREREREQMXUMy0QVge1LjrYgtx/8OfIfylsIplEbof2oa8gfgVuBhSVPn4ta7UBqnTwf2ojRsbxff45Stlc8C10qaQek/9SRwZ22e/n7gC5RtjvsD77c9NzG1OhyYRKmUuoXSYP/wvlxo+0/Af4AbbN/b01DgeEpC6kHg3cD7bHd3GL8jpcrsMUoT/gm2L6/3vJ3yHH9C6Xm2LbBNoz+XpIskHVjn+RClYf3ukrqbPmv0ZX0RERERERERMXjJnqedev1G0lPA08Cxtntroh7zkaQ/AKfZ/kV/xzKnagXf0cAwYH3bd3caO27cOE+aNGmhxRYxkGxx440D7u1s40eNYs/RfWknGINR422L6dG1aMrvPyIiIuaEpOttj2t3btA2o7c9rL9jWBRJ2gR4PaWqatCxfTyl0iwiBpHJ3aUYNImuiIiIiIjoyaBNdMXCJ+lE/j979x1tV1Wuf/z70AmHECASCS1IF5SgoagEsKGAgl0MSlHwZwVEqugFFbBRFMSGVAFFQESagigdhAAREAgIgoGQUENyklDz/P6Yc+PmZJ8Wkpyck+czxh53rzXbu/bJuHfw3nfOBR8C9rE9ra/jiYh5a0F6A16j2iMiIiIiIqIrA/aMrjkhyZKmS5rjN/VJ2kbSI3MzrnlN0i8kdbv90/Zutpezfdp8CGuekPS5emaXJa3d1/FERERERERExNyTRNfsNrZ9qKTRTQeZT6+JkX5xuLmkwyW9WOOcIukGSW/rrL/tL9j+7lyOYYikUyRNkjRN0n2SDuqk7+gOv20jEfXRFn3/VttaViNKGirpeklP1We/UdI7Gu22T7a94Bw6FBERERERERFzTRJdnbB9re22mhTZsN4e0rhn+799GV8PnFNjfx1wHfAHSerYSdKi82j944A2YANgOWBHYLa3YMKrf+sa8weAduDPHWLdhe6327YDn6U89/LAD4CLOkuMRURERERERMTAkUTXHJC0h6R7aqXSg5L+Xxd995Z0t6RVJV0lac+mtt0lXVe/nyjpmA5jL5K0b/1+sKQH6pp3S/pwT2K1/SJwOvB6YEVJp0n6uaRLJU0H3lnvHdG07k6SxkmaWtd8f72/nKSTJT0m6VFJR3SRKNuU8mbGZ2zPsn2v7fN6EjOwG3Ce7elNMS0HHAYc2M3zPmd7vO1ZgICXKQmvFXq4dkRERERERET0U6lymTOPU6qOHgS2Ai6TdIvt25o71XOvPgxsbfuJFgVVzU4H/ijpANuzJA0F3g00EmMPAKOBScDHgTMlrW37sa4mlbQksDvwiO0nawxjgO3r7L9f+wAAIABJREFUMywBfLqp/2bAGcDHgCuBlYFlm2KcDKwNLANcDEwAftli6ZuAIyUtD1xn+/6u4mxaf1Bd+4Mdmo4Cfk55/p7McwewPrA48Gvbj/dkXLPxM2bkAOx5bMywYXmLXkRERERERMw1qeiaA7Yvsf2Ai6uByylJqAZJOhZ4H/BO20/0YM6bgWcpyS2AnYGrbE+u7efanliro84B7gc262LKT0iaQklEvZXytsSGC21fX+d6rsO4zwGn2L6itj9q+15Jw4DtgH1tT6+Jo+NqnK18FTgL+Apwt6R/S9quu98B+CjwJHB144akUcA7gBN6MB4A228GBlOSetf1dFzMP+Pa2zl78uS+DiMiIiIiIiIGkFR0zYGasDkMWJeSLBwE3NnUZQjweeCTtp/txdSnU6qrrqj/8ydNa+4K7AeMqLfagKFdzPV725/upG1CF+NWAy5tcX8NSnXUY02VaYt0NpftmZQqrKMkDQYOBs6VtLrtp7tYfzfgDNsGkLQI8DNgH9svdVMV1zGG54Df1m2m42z/s8eDgfUGDeKqTTbpzZDohVTLRURERERExNyWiq5eqlsBzweOBobZHkJJDDVnYJ6hbAs8tfmNf8B0SlKs4fUdpj8T2EnSxpRD3P9Y11wDOIlSHbViXfOuDmv2hrtomwCs1cn954GhtofUz2DbG7bo++rF7KmUpNcywJqd9ZO0GrANZetkw2BgFHCOpEnALfX+I5JG0zOLA2/oYd+IiIiIiIiI6KeS6Oq9JYAlgSeAl2p117YdO9m+CtgFuEDS5vX2OOAjkgZJWpuyTbB5zCOURM5vgPNrVRSUBJHrmkjaA9hoLj9Xw8nAHpLeLWkRSatIWr+eBXY5cIykwbVtLUlbt5pE0rckbSppCUlLAfsAU4DxXaz9GeAG281vZ3wWGA6MrJ/t6/23Av9ose4Wkras6y4t6SBgWKu+ERERERERETGwJNHVS7anAXsDv6dUbo0B/tRJ3yuAPYA/SXor5UyrFygHup9OOcOqo9OBN1GSXY157gaOAW6sY98EXD93nmi2mG+uMR9HSTJdTdm2CLArJdF3N+XZz6McVt9yKuBUynlbE4H3AjvYbu9i+V0pz98cj21PanyoyT5gsu0XACRdJukb9f6SwInAU8CjlMTYDrYn9uDxIyIiIiIiIqIfyxldr/Y8cKuk421/q3HT9kM0bRO0fSIlmTKbWsm1atP1JZSKooaO1V+Hd7j+L2Wb4NXNN20fChzak4ew3XHO5rbdu7tn+wLgghb9ngW+WD/dxXAEcES3wb56zPo96PMQHbZs2t6u6fvVwMadja/VcMdR/tazehNfRERERERERCzYkuhqYnupvlxf0uKULX6/tp0kzDxg+1RKpVksAMa1t+dQ+gXUuPZ2Rra19XUYERERERERvZKtiwsISRtQzrBaGfhxH4cTEQu5kW1tjBk2rPuOERERERERC5BUdC0gbN9DOXQ+YqExsq2NqzbZpK/DiIiIiIiIiAEiFV0RERERERERETEgDOhElyRLmi7pyB70/YakX8+PuKLvSPqbpOckXdfXsURERERERETE3DWgE13VxvWNhUgaUZNfs23ZtH2U7T3nR0Aq9pZ0V03EPSLpXElvmh/rzw+StpR0g6RnJT0t6XpJm3bR/w2SLpY0TdKTkn7YoX1nSffU3+sBSaN7EMPfOv69bb8L+MJreriIiIiIiIiIWCDljK6+8RNgB2Av4HpgUeDD9d6dvZlI0mK2X+ru3vwkaTBwMfBF4PfAEsBo4PlO+i8BXAGcCHwSeBlYt6n9vcAPatvNlAP7u4thF/LvOyIiIiIiImKhkkRAJelwYG3bn67X51KSM0sD/wS+aPtfte00YAawZu3zT+CjwMHAbsBk4FO2b2+xzjrAl4G32b65qemspj47AEcAawHPAifbPry2jQD+A+wJHAY8JOkUStLs5rr+zySdCpwEbAwY+AvwZdtT6jwHAXsDg4GJwJdsXylpUeAg4HPASsB9wIdsT5D0dkqSbt16fx/bN7T4OdcFsP3bej0TuLxFv4bdgYm2j226d0fT928D37F9U71+tIu5kLRc/W12BW7sqm9Xxs+YwTa3z/YnjLlkXHs7I9va+jqMiIiIiIiIGEAWhq2Lc+oyYB1Ksuc2mhJR1SeAbwJDKZVKN9Z+Q4HzgGNp7d3AIx2SXB1NpyRphlCqvL4o6UMd+mwNbAC8r15vDjxY4z0SEPA9YHjttxpwOICk9YCvAJvaXrbO8VCdZz/gU8D2lCTYZ4EZklYALgGOB1asz3eJpBVbxH8f8LKk0yVtJ2n5Lp4VYAtKwu6yum3xqsY2zpp4GwW8TtK/6zbPn0pauov5jgJ+DkzqZt3oQyPb2hgzbFhfhxEREREREREDSCq6OmH7lMb3Wu31jKTlbD9bb19g+9bafgGlIuqMen0OJZHUyorAY92sfVXT5R2SfktJbP2x6f7htqfX9aBURJ1Q214C/l0/AE9IOpZS5QRla+CSwBslPWH7oaZ59wQOtD2+Xv+zrvEZ4H7bv6n3fytpb+CDwGkd4p8qaUtKZdhJwOslXQrsZXtyi0deFXgnsCNwJbAPcKGk9SmJw8WBj1Gq514ELqQkGQ/tOJGkUcA76hyrtlirx9YbNIirNtnktUwREREREREREfNRKrpakLSopO/XQ8+n8r9qp6FN3ZoTNjNbXHe2J+spujljStLmkv4u6QlJz1IOTx/aoduErq4lrSTpd5Ierc9wZmMO2/8G9qVUeD1e+w2vQ1cDHmgR1nDg4Q73HgZWafUMtu+xvbvtVYGN6vgfd/LIM4HrbF9m+wXgaEpCcIPaBnCC7cdsP0mpJtu+4ySSFgF+RtlS2WdnlEVERERERERE30iiq7UxwE7Ae4DlgBH1vubC3FcCq9bKo86cDfwJWM32csAvWqztbq6/V++92fZg4NPNc9g+2/aWwBq13w9q0wTK2WAdTax9m61ON+dl1bXupVR9bdRJlztaxN8Y+wzwSGftHQymbHM8R9Ik4JZ6/5GevKUxIiIiIiIiIvq3hXXr4pKSmp/9hQ7ty1LO3XoKGEQ582musH2/pJ9Rtv7tBdxASTh+CBhh+/t1/adtPydpM0riravD3FtZlnKQ/RRJqwAHNBrqGV2rUN74+BylaqqR9Pw18F1Jd1O2Pr6Jksy6FDhB0hjKmxQ/CryR8nbFV6lbDncAzrH9iKTVKOd+3dSxb3Um8HVJ7wH+Tjkk/0ngntp+KvBVSX+mbF3ct9W69XmHN12vRjmg/63AE52sHRH9xLj29oXyBRFjhg3j88OHd98xIiIiIiIW2oqudkpyp/F5V4f2Myjb8h4F7qbzBM2c2hv4KXAiMIWyVfDDwEW1/UvAdyRNA/6PkljqrW8Db6Ekfy4B/tDUtiTwfUoyaRLlAPtv1LZj63qXA1OBk4GlbT8FfAD4OiUBeCDwgbqVsKNplMPx/yFpOuX3u6uOnU09D+zTlMq1ZyjVdDvWbYwA36VUZ91HSX7dTjlwH0mrS2qXtLqLSY0P/0tuTW6aKyKi3xjX3s7Zk1sdbRgREREREa3I7smOsP5J0nOUyqzjbX+rr+OJvifpCspbHm+2/e6u+o4aNcpjx46dP4FFRJcalVwL2wsiFqbnXpieNWaXv39ERET0hqRbbbc8EmpAb120vVRfxxALFtvv7esYIiIiIiIiImLeWFi3LkZERERERERExACTRFdERERERERERAwIC3yiS5IlTZd05ByO/4akX9fvI+p8i9XrqyTtWb/vIqm3bzaMfkbSaZJmSnqkr2OJiIiIiIiIiLlrgU90VRvbPhRA0l8kHdhokLRKTV61uvd620fZ3rO7BWyfZXvbeRP+7CSNkTS2vjHwMUmXSdpyfq0/r0naUNLlkp6RNEXSrZK276L/6ySdXfs+I+msprajJd0vaZqkeyXt2sU875R0Z53nKUkXSFql0W57d2C7ufWcEREREREREbHg6I+H0V8DbA38sF5vBdzb4t79tifN//C6J2k/4GDgC8BfgBeA9wM7Adf1cq7FbL/U3b0+cBHwc+AD9XpTQF30/wNwC7AGMAPYqKltOvBB4L46z58l/dv2DS3muRt4n+2JkpYEvlvj2LG3DzB+xoxX3gIVMbeMGTaMzw8f3tdhREREREREDEj9paKr2TXAOyQ1Yh8N/BgY1eHeNQCSDpd0ZneTStpd0nVN1z+RNEHS1FqNNLqp7XBJ50o6s1YZ3SlpXUmHSHq8jmtZHSZpOeA7wJdt/8H2dNsv2r7I9gG1z2aSbqxVSY9J+qmkJZrmsKQvS7ofuF/SNpIekXSQpEnAqZKWl3SxpCdqhdTFklbt8LwP1vj/I2mXpra9JN1T2+6W9JZ6f4O63XOKpH9Japk8kjQUWBM4yfYL9XO97ZZJvPpbrQYcYPvZ+nu8kmGyfZjte23Psv0P4Frgba3msj3Z9sSmWy8Da7fqGzG/jWtv5+zJk/s6jIiIiIiIiAGrP1Z03QwsCWwM3E6p3joa2LXDvR92NkEP3UJJSD0L7AOcK2mE7edq+wcpFVi7A6dQKrN+DaxS7/2Skuzp6G3AUsAFXaz9MvA1YCywKnAZ8CVKQq/hQ8DmwMz6P18PrECpiFoEGAScCnwCWLTG+FPgQ5KWAY4HNrU9XtLKdSySPg4cXucfC6wFvChpcUqV1inAtsCWwIWSRtke3yH+p4B/A2fW89FutN3Vf91vAYwHTpe0HfAgsL/tqzt2lLQ0parrZ51NJml14A5gMOW33KuLtTu13qBBXLXJJnMyNKKlVAhGRERERETMW/2uosv288A/gK0krQAMsf0gpcqnce+NwGxJkl6uc6btp2y/ZPsYSnJtvaYu19r+S90ieC7wOuD7tl8EfgeMkDSkxdQrAk92tbXQ9q22b6prP0RJmm3dodv3bD9te2a9ngUcZvt52zNr7OfbnmF7GnBkhzlmARtJWtr2Y7b/Ve/vCfzQ9i0u/m37YUoyqq0+4wu2/wZcDHyqRfwG3gk8BBwDPCbpGknrdPLIq1KSZ3+nJOyOoSTRhrbo+wvgn5TEYku2/2t7CDAU+CZla2tEREREREREDHD9LtFVXUOp2hrN/860uq7p3oSanJljkr5et+89K2kKsBwlcdLQXKE0k5K8ernpGkpiqKOngKGqb37sZO1161bDSZKmAkd1WBtgQofrJ5qqzZA0SNIvJT1c57gGGCJpUdvTgU9Szgh7TNIlktavQ1cDHmgR1nDK7zqr6d7DlAq22dh+xPZXbK9FqTKbDpzRySPPBB6yfXLdtvi7+nzv6PC7/IhydtcnajKtS7afBk6nJM36Y/ViRERERERERPRCf050jaYktq6t966nJEa2qu1zrJ7HdRBl29/ytTroWbo+TL2nbgSeo2wN7MzPKVVI69geDHyjxdodEz0dr79OqUDbvM6xVb0vgFqN9l5g5brWSbV9AmW7YkcTgdWazkEDWB14tIvnoK41ATiRVx8w3+yOFvG/iqRvU96WuK3tqd2t2WQxYCXKNsaIiIiIiIiIGMD6a6LrBmAI8Glqosv2M8AT9d5rSnQBywIv1fkWk/R/zKVEie1ngf8DTpT0oVp5tbik7SQ1zhVbFpgKtNdKqy/OwVLLUiqlptTtnIc1GiQNk7RjPavreaCdcpYVlHPG9pf0VhVrS1qDsl10OnBgjXcbyjllv+u4cD0I/9t17CJ1C+JngZs6ifUCYHlJu0laVNLHKJVi19f5DgHGAO+1/VRXDy3pI5LWq+u+DjgWuL1Wd0VERERERETEANYvt3PZniHpVmAD4K6mpmspSaHXmuj6C+UA+PsoyZ3jmH2r4ByzfaykyZTzo84CpgG3Us7RAtgf+BVwIOVw/XOAd/VymR8DZwNPUqqxjuF/VWSLUCq+fkOppBpHOewe2+dKWrGOXYVyztZnbD9c37L4M+AQSiXXrrZbnX/1AjAC+Ctly2U75fytr3byezzdNPeJlAqznWw/WbscVee8X3qlsO0o20cBSGoHtrN9bY35GEoV1zTgKuDDPfi9IuaLce3tPTqUfsywYXx++PD5EFFERERERMTAoR4cddSnJD1HqTo63va3+jqe6N8knQx8HHjc9tpd9R01apTHjh07fwKLhcI2t9/OuPZ2Rra1Or7vfxp98tbP/2kkBxe232Rheu6F6Vljdvn7R0RERG9IutX2qFZtC3xFl+2l+jqGGDhsfw74XF/HEQuvniSwelLxFREREREREbPrr2d0RUREREREREREvMpCneiSZEnTJR3Zfe9ezbuLpMvn5pwxd0h6QNILks7s61giIiIiIiIiYu5aqBNd1ca2DwWQNKImv25r7iBpaE2OPNSTCW2fZXvbztolLSHpcEn310TbQ5JOkTTiNTzHAkXSTpLGSZoq6UlJV3b3fPV3uVfSIx3uv13SzZKmSbpD0pZdzHGApLtq3/9IOqC53fZalMPtIyIiIiIiImKASaKrtWUkbdR0PQb4z1yc/zxgxzrvcsDGlLcuvru3E0ma7Zy1VvfmJ0lrA2dQ3uy4HLAm5Y2Ks7oZegDweIe5VgD+BPwIGAL8ELhI0vKdLQ/sCiwPvB/4iqSd5+xJIiIiIiIiIqI/WeAPo+8jvwF2oyReoCROzgD2anSQdHC9XgmYABxq+4Latjuwp+3ZKo8kvQd4L7Cu7Qn19rPAiU199gAOBFYFngB+YPuXtW0b4EzgBOBrwBWSHgA2Ap6jJND2k3QH8BNgA2AmcD6wn+0XJAk4FtgFWBJ4GBhj+y5JSwNHAB+jJJbuBN5re6akHYHvAasA44Av2r6nxe83EviP7Svr9bS6fqckrQl8GtgPOKmp6e3AZNvn1uszJf0f8BHg5I7z2P5h0+V4SRcC7wB+19X6rYyfMSOHgsdc1ZM3LkZERERERMScS0VXa2cCO0taVNIGwLLAPzr0eQAYTalY+jYlAbNyD+Z+D3BzU5KrlceBDwCDgT2A4yS9pan99cAKwBrA5+u9nSiVYkOAs4CXKYmwocDbKNViX6p9twW2Atat/T8JPFXbjgbeSkkwrUBJuM2StC7wW2Bf4HXApZTKqiVaxH8bsL6k4yS9U1JP/sv+BOAblKRcM9VPx3sb0Y2a0BsN/KsH60fMcyPb2hgzbFhfhxERERERETFgpaKrtUeA8ZSk1Dsp1Vyv0lRhBHCOpEOAzYALu5l7ReCxrjrYvqTp8up6sP1oSgIJyhbAw2w/D1DyOdxo+4+1fSZlK2TDQ5J+CWwN/Bh4kZK8W5+SdLunzrMI8FlgC9uP1rE31LZPApfYvqJeHw3sQ0mIXdUh/gdr5dl+wO+BZSX9DviK7faOzyvpw8Biti+o45rdAAyX9ClKIm8MsBYwqOWP92qHU5K5p/ag72zWGzSIqzbZZE6GRkREREREREQfSKKrc2cAu1MSOVsB6zQ3StqVksgZUW+1UaqnuvMUpZKqU5K2Aw6r/RahJHXubOryhO3nOgx7VYVYrcA6FhhVxy9GTX7Z/pukn1K2S64u6QJgf2Cp+nmgRVjDKVscqXPMkjSBso1xNrZvAj5RY9kUOAc4FDikQ5zLUM7d2r6TeZ6StBOl0uxE4C/AXynJyE5J+gply+noRkIwoj8Z196erbNNsu0zIiIiIiJ6IlsXO3c+sAPwoO2HmxskrUE5R+orwIq2hwB3MfsWu1b+CmwmadVWjZKWrGsfDQyrc1/aYW63GNrx3s+Be4F1bA+mbAt8ZQ7bx9t+K7AhJaF2APAk5ZyvtVrMP5GyVbIRp4DVgEdb9H11YPYtwB9ovd1wHUqy8FpJk2q/lSVNaryl0fbVtje1vQLwGWA94ObO1pP0WeBg4N22u0yIRUT/kG2fERERERHRE6no6oTt6ZLeBTzTonkZSmLpCXjl8Phuz4yq8/5V0hXABZK+APwTWJpyMPwLwLmUA+KfAF6q1V3bUhJpvbEsMBVol7Q+8MWmeDelJDlvA6ZTklsv1yqtU4BjJX0GmEzZjnkbZQviwZLeDVxD2bb4PHVrYzNJW1IOwb/Q9uN1/R2B01vEeRclYdbwduCnwFua4t2k9lsa+A7wiO2/tHpoSbsARwHvtP1gD36niAXSyLa2bJ2NiIiIiIjopVR0dcH2WNuzbeOzfTdwDHAjJRn0JuD6Xkz9MUqV1jmUNy7eRdli+Ffb04C9KYmlZyhnUv1pDsLfv46dRqk+O6epbXC99wxlO+JTlAqyxrg7gVuAp4EfAIvYHk95K+IJlMqvDwIftP1Ci7WnUBJbd0pqB/4MXEDZovgqtl+yPanxqWvOqtcv124H1jUnACsDH26MlzS6rtFwBOUctFsktdfPL7r9tSIiIiIiIiKi35PdahfcwkHSc5SqpONtf6uv44l5T9J4yrliv7f92a76jho1ymPHjp0/gUU0aZzNlYquWJj+LSxMzxqzy98/IiIiekPSrbZHtWpbqLcu2l6qr2OI+cv2en0dQ0RERERERETMG9m6GBERERERERERA8KATXRJsqTpko6cD2tdJWnPTtpWr+dELTqv4+iOpMsk7dbXcfQlSZ+rfw9LWruv44mIiIiIiIiIuWegb13c2Pa/GxeSPgccQDmjaQYwFti5HgA/T9j+L9A2J2MlLQF8D/gkMITyFsI/2v5abX8I2NP2X3sYy3ZzEseckDQEOBbYnvKWyseAk23/oJP+pvxNGofG/c72nk3tbwCOB7amnKt2iu0DW8wzFLgQWB9YFLgH2N/29QC2TwZOrutFRCzwxrW3v3J+0UA2rr2dkW1z9H8uIyIiIiJeMdATXa+QtDVwFPB+27dLWoHy5sAF2SGUtzFuRkkUrQFs1acRtSBpMdsvdbh9HCXBtQHlzZLrAht1M9WrEpNN8y8BXAGcSEn6vVzna6Ud+CxwPyVpthNwkaSVWsQYERELiJFtbYwZNqyvw4iIiIiIfm6hSXQBmwI32r4dwPbTwOmNRknLAScA21Eqi04CjrI9S9LuwF7AbcCulKTTl21f2TT/GpKuB94M3AiMsf2kpBHAf4DFbb8kaQ/gQGBVSoXWD2z/souYL7A9sV4/VD9I+g2wOiWJ8zLwHds/lLQFpZLqjcDDwD62r6pjrgLOtP3r+kx7AjcBnwOmAF+yfVnT79GoyJoFnAocZvvlpt/jZmA34GfAN1vE/k3bz9Tre+tnTuwOTLR9bNO9O1p1tP0cML4+wyKUpNjywArA43O4fkREnxnZ1pY30UVERERE9NDClOj6B/BdSd8GLgfG2n6+qf0EYDngDcCKtc9jwMm1fXPgPGAo8BHgD5LWrAkzgDGUJNkE4DJgf+DgFnE8DnwAeJBSnXWZpFts39ai703AfpJeAK4F7rJtANufkTSapq2LklYBLgE+A/wZeDdwvqT1bT/RYv7NKcm+ocDnKVv6VqlrnA5MBtamVGZdXJ/tl01jfwesBCzeSexHSloeuM72/S36dHRNTU7dAOxn+6F6fwvgIUmXURJodwFftX1nZxNJuoOyfXFx4Ne2e53kGj9jxkKxXSgWPNnCFRERERERMWcG7GH0Hdm+lpKgegslGfSUpGMlLVoPiv8kcIjtaTXBcgwlYdTwOPBj2y/aPodSNbRDU/uptu+zPRP4PTCykzgusf2Ai6spCbXRnYT9PeAHwC6U88Qe7eYw+U8Dl9q+1PYs21fUcdt30v9h2yfZfpmS2FoZGCZpGCVpt6/t6TVJdBywc9PYibZPsP1SfeaOvgqcBXwFuFvSvyV1dUbY1sAISnJqInCxpEYidtW69vHAcMrf78K6pbEl228GBlMSkNd1sW7EAidbuCIiIiIiIubMwlTRRd2Wd1mtGnoncC4lYfVHYAnKVr+GhymH1jc82qimamof3nQ9qen7DDo5gL4mew6jnDG1CDAIaFmZVBNQJwInSlqacvbUKZJutn1PiyFrAB+X1Hz22OLA31vN3xyz7RmSqHGvUMc9Vu9RY53QNLb5e6vYZ1LORDtK0mBKddu5klZvqoJr7n9N/fqCpH2AqZTzve4EZlKqwhrbKo+mbJXcAPhnFzE8B/xW0j2SxtnutG8r6w0alO1CEREREREREf3IQlPR1axWO10J/I1yQPqTwIuURFHD6sCjTderqCnrU9sn0guSlgTOB44GhtkeAlwKqMuBJeaZtk8EnqGcvwX/e0NhwwTgN7aHNH2Wsf393sRZ53keGNo0z2DbGzaH1NPJbE+lJL2WAdbs6TD+97vc0Zv1WlicsiU1IiIiIiIiIgawhSbRJWknSTtLWl7FZpTtcjfVyqnfU86UWlbSGsB+wJlNU6wE7C1pcUkfp1QTXdrLMJYAlqQcQv9Sre7atouY95W0jaSlJS1Wty0uCzQOjprMqxM4ZwIflPS+uiVzqTp+1d4EafsxypbKYyQNlrSIpLXqmyt7RNK3JG0qaQlJSwH7UA68H9+i74aSRtaY2yjbRh8FGlVrZwJbSHpP3Wa6LyU5OVtVm6QtJG1Z111a0kHAMMoZbRERERERERExgC00iS5KJdRewP2UbXFnAj+yfVZt/yownXJI/HXA2cApTeP/AaxDSbAcCXzM9lO9CcD2NGBvSlLtGcr5UX/qYshMStJnUl33y8BHbT9Y278HfFPSFEn7254A7AR8g5JMmwAcwJz9nXelJOburrGeRznDq6dMeVPjk5TKt/cCO9hub9F3GHAO5e/yIOWsrg/YfhHA9njK+WO/qLHsBOxo+wUASZdJ+kada0nKds+nKMmy7eu6vaq+i4iIiIiIiIj+R68+dmrgkPQcZfvd8ba/9Rrn2p3ydsMt50Zs0Xck7UE5WH8p4I1NScPZjBo1ymPHjp1vsUVEdNR482vOC4yBLv/WIyIiojck3Wp7VKu2AXsYve2l+jqGWPDYPpVSaRYRERERERERA8zCtHUxIiIiIiIiIiIGsCS6esD2adm2GBERERERERGxYEuiqwckWdJ0SUf2dSzx2kj6nKSfH2iCAAAgAElEQVT2+jddu6/jiYiIiIiIiIi5J4muntvY9qGNi5owuVfSNEmTJV0iadn5GZCkbSQ9Mj/X7ClJQySdImlS/Y3uk3RQJ31H1+RT88eSPtrU52t1rmfrvEt2sXYjMdmY69eNNtsn226bu08bEREREREREQuCJLrmgKStgaOAT9leFtgA+H3fRrXAOQ5oo/w2ywE7Ag+06mj7WtttjQ/wAaAd+DOApPcBBwPvBkYAbwC+3c36GzfNuedceJ6IiIiIiIiIWMAN2LcuzmObAjfavh3A9tPA6Y3GWm10JPAJYEngAuBrtmdKWh74DbA55fe/HviC7Ufq2KuAa4F3AW8GbgTG2H6yNwFK2gD4OTASeBQ4xPafattpwHPAWsAWwG3ArrYfru3rAycAbwWeAL5l+/eShgP3NS2zCLC0bXXyG33T9jP1+t766YndgPNsT2+6Ptn2v2p83wXOoiS/5pnxM2a88rrz6N6YYcP4/PDhfR1GRERERERELMRS0TVn/gG8T9K3Jb2jxTa6HwDrUpJMawOrAP9X2xYBTgXWAFYHZgI/7TB+DLAHsBKwBLB/b4KTtDhwEXB5neOrwFmS1mvqtgvwXWAoMI6SOELSMsAVwNl17KeAn0na0PbEDpVXFwC/6ySMm4AjJe0haZ1exD4I+BhNiUNgQ+CfTdf/BIZJWrGLqa6pWx3/IGlET9ePOTOuvZ2zJ0/u6zAiIiIiIiJiIZeKrjlg+1pJHwG+BOwDLCbpV8ABwCxgL+DNtdILSUdREkeH2H4KOL8xVz3g/u8dljjV9n21/feUbX+9sQVl2+D3bc8C/ibpYkrS6vDa5xLb19Q1DgWelbQa8HbgIdun1n63STqfknz6V1PcBwHrA529jfKrwNeArwC/kvQw8FXbl3UT+0eBJ4Grm+61Ac82XTe+Lws81WKOrSmJtkHAEcDFkkbafqmbtV9lvUGDuGqTTXozZKGVyreIiIiIiIhYECTRNYdqwuYySYsA7wTOBcZTqpwGAbdKr+zoE7AovFKxdBzwfmD52r6spEVtv1yvJzUtNYOS6OmN4cCEmuRqeJhSWdYwoelZ2iU9XcetAWwuaUpT38Uo2y2pz7AdJcG3ue2ZrQKo948CjpI0mLLN8FxJqzcSgJ3YDTjDtpvutQODm64b36d1svY19esLkvYBplLOCruzi3UjIiIiIiIiop/L1sXXyPYs21cCfwM2olQjzQQ2tD2kfpZretPf14H1KEmiwcBW9X6rc67m1ERgtZqEa1idclZXw2qNL5LagBXquAnA1U2xD6lbFb9Y+65H2Vb4CdsT6AHbUylJr2WANTvrVyvKtgHO6ND0L2DjpuuNgcm1Oq5HITB3f9+IiIiIiIiIWAAl0TUHJO0kaWdJy6vYjLpdrlZRnQQcJ2ml2n+V+uZAKNvtZgJTJK0AHDYX4lmq+QPcDEwHDpS0uKRtgA/y6vO0tpe0paQlKGd1/aMmri4G1pX0mTp2cUmbStqgVmZdSDlk/rpuYvpWHbdEjWkfYAql6q0znwFusN3x7YxnAJ+T9MZ6mP83gdM6WXdDSSMlLVoTeMdQEnz3dBVvRERERERERPR/SXTNmWco53DdT9kWdybwI9tn1faDgH8DN0maCvyVUsUF8GNgaUrl103An19jLKtQEmfNn9Uo53ptV9f5GeWtis1vPTybkmR7mvJ2xV0AbE8DtgV2plR4TaIcrr8k8Jb6HMdKam98OonLlEP3n6zzvBfYwXZn/QF25dWH0FNj+jPwQ8pZZg/XzysJQkmXSfpGvRwGnEP5uzwIjAA+YPvFLtaNiIiIiIiIiAFArz4KKVqR9BzwPHC87W/1dTyvlaTTgEdsf7OvY5nfJO1BOSNtKeCNth/srO+oUaM8duzY+RZbf7bN7bczrr2dkW29PU4u+sKYYcP4/PDhfR1G9EDjRQ95MUYMdPm3HhEREb0h6Vbbo1q15TD6HrC9VF/HEHNHfZvkqd12jBigxrWXosokuiIiIiIiYiBKoisi5oqRbW35/8T3A42qiYiIiIiIiIEoia6FkO3d+zqGiIiIiIiIiIi5LYfRd0GSJU2XdGQvxjwk6T2dtP2rvgEx+oCk99QD9Gd19jeKiIiIiIiIiP4ria7ubWz70OYbkpapCZNLezOR7Q1tXzU3gpI0oibiFriqPElLSDpG0iP1d/qPpOM66bt68xsc68eSvl7bd5B0naQpkiZJOknSsl2s/XZJN0uaJukOSVs22mz/1XYb8N+5/tARERERERER0eeS6JozH6O8hXFbSSvPjQkXxITVa3AIMArYDFgWeCfQ8mAg2/+13db4AG8CZgHn1y7LAUcAw4ENgFWBH7WaS9IKwJ9q+xDgh8BFkpafS88VEREREREREQuwgZRcmZ92A34BbAfsAhzdqpOk9YHLgENs/07SQ8Cetv8q6XBgI+A5YEdgP0l3AD+hJHRmUpI9+9l+oTfBSRpe49sSeBr4ge2Taltj3ZeB7YH7gT1s/7Np7AnAVkA7cJzt42vbFP73b0bAIGBN2w91CGFT4ALbE+v1Q/XTE7sC1zTmtH12U9sMSScB3+5k7NuBybbPrddnSvo/4CPAyT1c/xXjZ8zIwd09NK69nZFtbX0dRkRERERERCzkUtHVS5JWB7YBzqqfXTvp9xbgcuCrtn/XyXQ7AedRqo/OoiSfvgYMBd4GvBv40hyE+VvgEUoV1MeAoyS9u8O65wIrAGcDf5S0uKRFgIuAfwKr1PX3lfQ+ANtDmiqvfgJcCzzaYv2bKIm7L0l6kyT1IvZdgdO7aN8K+Fcnbaqfjvc26sX6MQdGtrUxZtiwvg4jIiIiIiIiFnKp6Oq9XYE7bN9dK5x+KGkT282lP6OBzwGfsf33Lua60fYf6/eZwK1NbQ9J+iWwNfDjngYnaTVKJdcHbD8HjJP0a+AzwJW12622z6v9jwW+DmwBvAC8zvZ3ar8HawXVzsBfmtb4JDAG2NT2iy3C+B7wDKXa7TjgKUmH2O4qgYWk0cAwSvKvVft7KdV0m3cyxQ3AcEmfqnOMAdaiVJ712nqDBnHVJpvMydCIiIiIiIiI6AOp6Oq9XSnVV9SteVdTki/NvgDc0E2SC2BC84WkdSVdXA9dnwocRanu6o3hwNO2pzXde5hSoTXburZn8b/qrzUoiaIpjQ/wDUryqRHjJsBPgQ/bfqJVALZftn2i7XdQqtWOBE6RtEE3se8GnG+7vWODpC0o1Wcfs31fJ+s+RalW2w+YDLwf+Gt9voiIiIiIiIgY4FLR1QuS3g6sAxzSeCsg5bD1DSXtb/uleu8LwEGSjrP9tS6mdIfrn1MObf+U7WmS9qVsPeyNicAKkpZtSnatzqu3GK7W9EyLUA54nwi8BPzH9jqtJpb0OuAC4CsdKtg6ZXsmcKKkbwNvBO7pZO6lgY8DH27RtgnlkPnP2r6yY3uH9a6mnBHWOOD/AeCYnsQasbAY196e8+f6iZx/FxERERHRO6no6p3dgCsoCZuR9bMRZWvcdk39plGqibaS9P1ezL8sMBVorwfZf7EHY5aUtFTjQ0lo3QB8r957M2Ub5VlNY94q6SM1EbQv5Q2SNwE3A1MlHSRpaUmLStpI0qa17/nAWbbP6SogSftK2qbOsZik3eqzdfVf1h8GpgCvqoKTtBHwZ8pZZxd192NI2qSeNzaY8pKAR2z/pbtxERELopx/FxERERHRO6no6qGaRPoEsKvtSR3afkNJgr2SiLE9pZ4p9XdJL9r+Vg+W2R/4FXAgJSl0DvCubsZ03Ob3XuBTlLcuTqSclXWY7Sua+lwIfJJy6Pu/gY80ztqS9EFKBdR/gCWB8cA3KVVfoylJsn2a5nqj7f92iGFmnWNtStXafcBHbT/YxXPsBpxhu2OV29eB1wEnS2q8OfFh2xvWeH8BYPsLte1AytskoSTIZqsQi1jYjWxry/lzERERERExIGn2vEI0SHqOUu10fA8TVQs8SYcDa9v+dF/HMr/VN0+eT0ngbd/dGWqjRo3y2LFj50tsEfNLY8tiEl0RsSDJ/26KiIiI3pB0q+1RrdpS0dUF20v1dQwx99TzvYb0dRwRERERERERMW/kjK6IiIiIiIiIiBgQFshElyRLmi7pyPmw1lWS9uykbXVJ7ZIWnddx1PVOk3TEHIzbXdJ1Pelr+/CebluU9JCk93TSNlrS+N7EuSCQ9ICkFySd2dexRERERERERMTctUAmuqqNbR/auJD0OUn3SpomabKkSyQtOy8DsP1f2222X+7NOEm/qAmy9ppUebHp+rJ5Fe/8ZPta2+t11i5pJ0njJE2V9KSkKyWN6KTvkvU3myzpaUkXSVqltq0k6beSJkp6VtL1kjbvLj5JS9R/L490iHst4KhePWxERERERERE9AsLcqLrFZK2piQnPmV7WWAD4Pd9G1XnbH+hJsjaKHGf07i2vV1fxzevSVobOIPyxsTlgDWBnwGzOhmyD/A24M3AcGAKcEJtawNuAd4KrEB5U+Qlktq6CeMA4PE5f4qIiIiIiIiI6G/6RaIL2BS40fbtALaftn267WkAkpaTdIakJyQ9LOmbkhapbbvXKqATakXQvfXte83WqH2mSbpc0tA6dkTdRrlY0zonS3pM0qOSjujttkZJ50qaVGO5RtKGnfRbVtLfJR2v4uC67W6apLslfbjFmKMlPSPpP5K2a7q/h6R76tgHJf2/prahki6WNKVWU13b+O2qkZLuqPGeI2mpOm6bjtVSzWOA/9i+0sU02+fb/m8n/dcE/mJ7su3ngN8BGwLYftD2sbYfs/2y7V8BSwBdVZOtCXwa+F5nfSIiIiIiIiJi4Okvb138B/BdSd8GLgfG2n6+qf0ESuXQG4AVa5/HgJNr++bAecBQ4CPAHyStafvp2j4G2A6YAFwG7A8c3CKO04HJwNrAMsDFdcwve/EslwGfBV4AfgCcRUkMvULSirXf5ba/We89AIwGJgEfB86UtLbtx5qe8fT6jJ8HTpa0im1TKps+ADwIbAVcJukW27dRqq4eAV5X59kCcFM4nwDeDzwHXA/sDvyim2e8DVhf0nHAn4BbbLd30f9k4CeSGtVcu9Tnn42kkZRE17+7mO8E4BvAzG7i7NL4GTNeed15xEAxrr2dkW3dFURGRERERET0T/2iosv2tZQE1VuAS4CnJB0radFaUfVJ4JBaOfQQcAzwmaYpHgd+bPtF2+cA44EdmtpPtX2f7ZmULZGvSjwBSBpGSYbta3u67ceB44Cde/ksp9Q4nwcOBzaWtFxTl+HA1cC5jSRXHXeu7Ym2Z9VnuB/YrGncw7ZPqueJnQ6sDAyrYy+x/UCtrrqakggcXce9WPuuUX+fa2tyrOH4uu7TwEWtfpsWz/ggsA2wCuX3fFLloP3O/uv6PuC/wKPAVMrW1O907CRpMPAb4Nu2n201Ua10W8z2Bd3FGbEwGtnWxphhw/o6jIiIiIiIiHmiv1R0YfsySiXSIsA7gXMpCas/Uip8Hm7q/jAlydLwaIfkzcOUhFLDpKbvMyjnQnW0BrA48Jikxr1FKBVdPVKTckdSKrJex//OrBoKNBI3OwDtdKiakrQrsB8wot5qq+NmewbbM2qMbXXsdsBhwLo15kHAnbX7jygJt8vrmF/Z/n6reSm/TfPv1inbN1GqwZC0KXAOcChwSIvuPweWolTjTQcOpFR0vXLovKSlKYm2m2y33JIoaRngh8D2PYmxO+sNGsRVm2wyN6aKiIiIiIiIiPmgX1R0NasVTVcCfwM2Ap6kVCWt0dRtdUp1UMMqaspO1faJvVx6AvA8MNT2kPoZbLvlGVudGAPsBLyHstVyRL3fHNtJwJ+BS2viBklr1PtfAVa0PQS4q8O4liQtCZwPHA0Mq2MvbYyt1WVft/0G4IPAfi3OMHtNbN8C/IHy92plY+C0evba85Sth5s1nZW2JCWh+Sjw/zqZA2Adym96raRJdc2V65loI+bCo0RERERERETEAqxfJLok7SRpZ0nL14PZNwO2plT3vEzZHndkPcB9DUrl05lNU6wE7C1pcUkfp2yNu7Q3MdSzsC4HjpE0WNIiktaqb4TsqWUpybKnKFVVR3XS7yuUarWLayXTMpRzs56Acrg8nSeNOloCWLKOfalWd23baJT0AUlr10TgVODl+pljkraUtJekler1+sCOwE2dDLkF2LUe9r848CVgou0n6/V5lPO2drXd2ZsboST/VqNsrxwJ7Ek5U20kvai8i4iIiIiIiIj+qV8kuoBngL0o51JNpSSxfmT7rNr+VcqWtweB64CzgVOaxv+DUu3zJGXr4MdsPzUHcexKSRzdXWM6j3K+VU+dQdk2+Wido2Xip26z/DwlOXMh5bmOAW6kJG7eRDkYvlv1zZR7U5KBz1Cqyv7U1GUd4K+U7ZI3Aj+zfVUvnqmVKZTE1p2S2ikVahdQthW2sj/lsPv7KQm57YHGWyXfTjlIf1tgiqT2+hkNIGl0XQPbL9me1PgATwOz6vVrSt5FRERERERExIJPrz66asEg6TlK5dPxtr/1GufaHdjT9pZzI7bo3ySNpx6Sb/uzXfUdNWqUx44dO38Ci4iIWIg13nKcszEjIiKiJyTdantUq7YF8jB620v1dQwxMNler69jiIiIiIiIiIh5o79sXYyIiIiIiIiIiOjSgE902T4t2xYjIiIiIiIiIga+AZ/oioiIiIiIiIiIhUO/S3RJsqTpko7sxZirJO3ZSduIOmefn1cmaXdJ183BuHnyDJJOk3REF+3tkt4wN9ec1+ozzZT0SF/HEhERERERERFzV79LdFUb2z60cSFpCUmHS7q/JsEeknSKpBF9EZykXWoSqL0mVWY1Xbf3RUzzgu022w+2apO0oaTLJT0jaYqkWyVt392ckk6tSbu1m+79UNIESVMlPSzp0C7GryzpT5Im1nlGdIh5d2C7nj5jRERERERERPQf/TXR1dF5wI7AGGA5YGPgVuDdfRGM7bNqEqiNklSZ2Liu9xYGFwFXAMOAlYC9galdDZC0JbBWi6aTgfVtDwbeDoyR9JFOppkF/Bn46BzGHRERERERERH9VJ9v13utJL0HeC+wru0J9fazwIkduq4h6XrgzcCNwBjbT7aYbzjwC2BL4GngB7ZPqm2LAAcCewFDgCuBL9h+uhfxHlzHrwRMAA61fUEnfX8EvA3YocZzBCUR9Cxwsv8/e3cetvlY/3/8+bIb94y1psY2ZY8YNWghQvqpREVlMLaIEqWNJFSUvtlV+koky5cSFalISijRDNlGlhHGjHXG3DPG+vr9cZ5XXS7Xvc123/fM63Ec19H1+Zzr57rVcfT2Pt8f++iWIbtJ+gYwBDjJ9rF1nk2BU4D1gGeBS4BDbT8vScCJwG7AksCD9be5vc65vKQrgHcBd9a2++q8BtayfW/LvlcC3gCcafv5evv6Hn6XxYDTgD2BW5vbbE9o6f4ysCZt2J4CfH9uHOOcMHMmW40bN6fTzBdjhg9n/xEj+nsbEREREREREf1qQcjo2ha4qSnI1ZUxwN6UANMSwBe66Hch8DAwAtgZOE5SIzPsYGAnYMva/jSvDqj15D5gC0rm2THAeZJe39xB0iKSzqQE5bazPQ2YAYylBNjeDxwoaaeWuTcH1qFksn1N0nr1/kvA54CVKIGzbYBP1bbtKEGstevcHwOebJpz17rP5YF7gd7URnuy9j1P0k6ShvdizOeAP9u+rV2jpMPqsc+HgWWAC3ox50JhfGcnF0yZ0t/biIiIiIiIiOh3gz6jC1gReLQX/c62fQ+ApIspRx1fQdKqlGDRB2zPAsZL+hGwByV765PAQbYfrv2PBv4taQ/bL/Zms7Z/1nR5kaTDgU2BX9Z7i1OCbYsBOzQyomxf2zTuNkkXUgJulzXdP8b2s8Ctkm6lHOG8y/YtTX0mSvphHXsy8AIwFFiXEjC8q2XLv7B9U33e8ynZXz09oyW9GzgMOAF4Qy2yv6/tf7X2r7/7J4G3djPntyUdD4yiBBun9bSPObXOkCFcu/HG83qZOTZYss4iIiIiIiIi5rUFIaPrSeD1PfaCyU3fZwLtamWNAJ6yPb3p3oPAyvX76sCltbj6VOAuSrZUbzKWAJA0VtL4pjk2oGRaNawJ7EgJWj3fNG4zSX+U9LikacABLeO6fEZJa0u6XNJkSc8AxzXG2r4GOJ2SmTZF0v9KGtbTnD2x/bDtg2yvQfndZgDndtH9ZODrNXOtuzltexzl+OUxvdlHRERERERERCw8FoRA19XAppJWmQtzTQJWkDS06d5qwCP1+0PA9raXa/osZfuRV83UhqTVgTOBg4AVbS8H3A6oqdtdlCOWV0pap+n+BcCvgFVtL0upI9Y8rjs/AO6m1NMaBnyleaztU22/FVifcoTxi72ct1fqsdLvUYJ67WwD/E8NxDUCazdKGtNF/8VoX7Q+IiIiIiIiIhZigz7QZftqytv9LpX0VkmLSRoq6QBJ+/RxroeAG4BvSVpK0obAvsD5tcsZwLE1YIWk10jasQ9LLAMYeLyO35s2wR/bF1KCUVdLagR0hlKyzWbV4vJdBYHaGUp542GnpHWBAxsNkjap2WKLU7KuZlGy1GabpOUlHSNpzVpvbCVgH+CvXQxZm3LMclT9AOxA+ZsuIumTdU7VZ/805ShpV+svRSmsD7BkvY6IiIiIiIiIBdygD3RVOwO/AS6i1G66HRhNyfbqq12BkZTsrkuBo2xfVdtOoWRV/V7SdErgZrPeTmz7TkrNqhuBKcCb6eJthLZ/AnwduEbSSErx+K/Xdb8GXNyHZ/oCJTA2nZJRdlFT27B672nKMc0nge/2Ye52nqf8hldTAmy3A88Be7XrbPsx25Mbn3r7iVpvDOBDlCL+04HzKG9nPK0xXlKnpC2apnwW6Kzf767XEREREREREbGAk+3+3kOfSJpFCZqcavvI/t5PDC6SzgJ2AR6zvWZ3fUePHu2bb755/mxsDmw1bhzjOzsZ1dGr8mkLlDHDh7P/iBH9vY2IiJhDjRerDIaXwERERET/k3SL7dHt2gbdWxdt5xhazDbb+1KOo8YgN76zJO0l0BURERERERENgy7QFRGvNqqjY6H7t+CNf/sfERERERER0bCg1OiaZyRZ0gxJx86j+VerNaYWnRfzxytJ2rf+3pbU7dHFiIiIiIiIiBhcEujqnY1sHwEgaWQNkixWryXpNEl3S1q5rxPb/rftDtt9ftOhpK0kPdzXcfODpOUk/VjSZEnTJd0j6ctd9F1J0vWSnpQ0VdKNkt7Z1L6kpJMkTZL0tKTv17dEdrX21pL+IekZSfdL2r/RZvss2wtfMauIiIiIiIiIhUACXXNAkoAfAlsBW9p+pI/jF+SjoycBHcB6wLLABylvTmynE9gHeA2wPHA88Oum3+cwyls0NwDWBt4CfLXdRDUAdinl77Is8DHgREkbzfkjRURERERERMRAtiAHWua1RYGzgDcDW9l+EkDS+4FvAmsA04CzbB9d20YCDwCfAI4CJkoaW+8tbvtFSdcC1wFbAxsCNwJjbD/Rl81JWg/4ATAKeAQ43Pavats5wKy6x7cB/wDG2n6wtq8LnAa8FXgcONL2xZJGAPc0LbMIsLRttdnCJsBXbT9dr++un1exPQuYUNdeBHiJEvBaAXgM2AE43vZTtc+plGDYUW2mWwEYBvzU5ZWif5d0F/Am4Naufq92JsycOSjqQC2sb1yMiIiIiIiIaJWMrtl3PrAusHUjyFXNAMYCywHvBw6UtFPL2C0pmU7v7WLuMcDewGuBJYAv9GVjNavp18Dv6xyfAc6XtE5Tt92AbwArAePr8yBpGeAq4II6dlfg+5LWtz2pHrPsqMf/LgX+r4tt/BU4VtLektbq5b5vowTgfgX8yPZjjab6oel6FUnLts5hewpwIbC3pEUlvR1YHfhLb/YwGI3q6GDM8OH9vY2IiIiIiIiIfpeMrtm3HXCM7anNN21f23R5m6QLKYGty5ruH217BkA5/fgqZ9u+p7ZfTDn21xdvoxwb/Lbtl4FrJF1OCVodXftcYfvPdY0jgGmSVgXeAUy0fXbt9w9JlwA7A3c0Fqj1ttYFNu9iD58BPgccBPyvpAeBz9i+sqtN295Q0lLAhygBvoYrgUMk/ZGSSXdwvT+EkjXX6kLgR8Ap9fpA2w91tW5X1hkyZKF7k2FERERERETEYJaMrtn3AeAoSfs035S0maQ/Snpc0jTgAErWVLOegi6Tm77PpASt+mIE8FANcjU8CDQXy//PHmx3Ak/VcasDm9Wi8FMlTaVkf72u0V/S9sAhwE62n223AdvP2j7O9luBFYGLgZ9JWqG7jdueZftC4LCmulrHAuMomWc3UIKGL1CONb5CPXZ5ESWrbglgfeBL9UhpRERERERERCzAktE1+26g1I66XNIs2xfU+xcApwPb254l6WReHejyPN7bJGBVSYs0BbtW45X1tVZtfJHUQaltNYkSAPuT7fe0m7gef/wJ8OHeZknZfkbSccDhwBsoQbWeLA68Ebi1BtMOqh/qWxRv6eJNlRsAE2z/rl5PkHQFsD1wRW/2G4PH+M7OQVFHDWDM8OHsP2JEf28jIiIiIiJigZaMrjlg+0/AhylH83aut4cCT9Ug16aUelvzlKSlmj/ATZRaYV+StLikrShBueZ6Wu+TtLmkJSi1uv5WA1eXA2tL2qOOXVzSJpLWkzQM+CWlyHy3Na8kHVnHLVH3dAgwlVp0vqXv2xp7kbR0PRY5HPhbbV9Z0ggVbwOOpH0heiiZX2tJ2rr2X4OSfdenQvQRc9P4zk4umDKlv7cRERERERGxwEtG1xyyfZWkjwEXSXoO+BRwgqTTgT9RjuwtNw+3sDLQenxwLUpdr+9TsqgeobxVsfmthxdQgkVvp7x1cTcA29MlbQecWD+LUIJEhwJvAdYBTpR0YmOiWpi+lYGzKZlkLwK3Ae+vxyRbLQmcSsngegH4ZyQTmi8AACAASURBVO07qbavAZxLKY7/EHCY7d83Bku6EriuHpW8rx4nPZVyDHMapdD+WW3WjUFuVEfHoKijNliyziIiIiIiIga7BLp69hxwi6RTbR9peyKvfAMgtq/glXW0ft5uoi7GvuKe7a1a2s8Bzulivmtb52uxZTdtT9g+oIt5J1DeGNlOd+s1z/FN4Ju97PsnYKNu2v8MjOymffuW64spAcZXkbQ3cBLl7/pyuz4RERERERERMTgl0NUD20v19x5i7qlvkzy7x44RERERERERMeikRldERERERERERCwQktG1ELK9V3/vISIiIiIiIiJiblugM7okWdIMScf2ou9XJP1ofuwr+o+kayTNktTtWyMjIiIiIiIiYvBZoANd1Ua2jwCQNLIGv16VyVbf2PeJ+bEhFQdLur0G4h6W9DNJb54f688PkjaXdIOkaZKeknS9pE16Me6a1r+RpPXq/WmS7pX0oW7GnyGps+nznKTpjXbbWwNti/BHRERERERExOC2MAS6BqJTgEOAg4EVgLWBy+j6TYddahe0a3dvfpI0DLgcOI3yfCsDx1DedNjduN1oOU5bn+WXdb4VgP2B8ySt3W4O2wfY7mh8gAuBn83ZE0VERERERETEYJAaXZWko4E1be9er38GbAEsDdwKHGj7jtp2DjATeEPtcyvwEeAwYE9gCrCr7XFt1lkL+DTwdts3NTWd39Tn/cA3gTWAacBZto+ubSOBB4BPAEcBEyX9GNgPuKmu/31JZwNnAhsBBn4HfNr21DrPlymBtmHAJOBTtv8gaVHgy8C+wGuBe4CdbD8k6R2UIN3a9f4htm9o83OuDWD7wnr9LPD7Nv2af5dl6/OMBW5saloXGAGcZNvANZKuB/YAjuxhzmUof5cPdNevKxNmzmSrca/6E8YAMb6zk1EdHf29jYiIiIiIiBhAktHVtSuBtSjBnn/QFIiqPgp8FViJkql0Y+23EvBz4MQu5t0GeLglyNVqBiXgsxwly+tASTu19NkSWA94b73eDLi/7vdYQMC3KEGi9YBVgaMBJK0DHARsYntonWNinedQYFfgfZQg2D7ATEkrAFcApwIr1ue7QtKKbfZ/D/CSpJ9I2l7S8t08a8NxwA+AyS331aavgA16MedHgMeBP/eibwwyozo6GDN8eH9vIyIiIiIiIgaQZHR1wfaPG99rttfTkpa1Pa3evtT2LbX9UkpG1Ln1+iJKIKmdFYFHe1j72qbL2yRdSAlsXdZ0/2jbM+p6AJNsn1bbXgTurR+AxyWdSMmYAngJWBJ4k6THbU9smvcTwJdsT6jXt9Y19gD+Zfun9f6Fkg4GdgDOadn/M5I2p2SGnQm8TtJvgP1sT2l9XkmjgXdSjnOu0tJ8N/AY8EVJJwHvrr/FH1vnaWNP4NyaCdZn6wwZwrUbbzw7QyMiIiIiIiKiHyTQ1UY9vncssAvwGuDl2rQS5SghlOOJDc+2ue7qTNWTwOt7WH8z4NuUrKUlKEGp1jpTD3V3Lem1lOyrLYChlOy9pwFs3yvps5QMr/Ul/Q441PYkSubXfW22NQJ4sOXeg5T6W69i+y5gr7qXdYHzgJMp2WLN+1wE+D7lGOSLNWjXPM8LNZvtNErg7GbgYnqu97UqJSC2X3f9IiIiYmAY39k5aEsGjBk+nP1HjOjvbURERAQ5utiVMcCOwLbAssDIer/dMbq++gOwSs1i6soFwK+AVW0vC5zRZu3WLKXW62/VexvaHgbs3jyH7Qtsbw6sXvsdX5seotQGazWp9m22GvBIN8/RWOtuStZXu+OGw4DRwEWSJgN/r/cflrRFHX+b7S1tr2j7vcAbKfXIujMWuMH2/T3tLyIiImJ2je/s5IIpr0pYj4iIiH6ysGZ0LdnyZsLnW9qHUjKGngSGUOpHzRW2/yXp+5Sjf/sBN1ACjjsBI21/u67/lO1ZkjalBN66LebexlBK9tlUSSsDX2w01BpdKwPXA7MoGWiNoOePgG9IupNy9PHNlGDWb4DTJI2hZFR9BHgT5W2Ir1AzuN4PXGT74ZpdtSvw1zb7nEbJFmtYlRLEeiulvhaSNqTU/VoE+BQlI+6cHp5/LP8N3kVERMQAN6qjY1CWDBisWWgRERELqoU1o6uTEtxpfLZuaT+XcizvEeBO2gdo5sTBwOnA94CplKOCHwJ+Xds/BXxd0nTga5TAUl8dA7yFEki6AvhFU9uSlKORT1CKv78W+EptO7Gu93vgGeAsYGnbT1LeXvh5SgDwS8AHbD/RZu3plOL4f5M0g/L73V7HvoKLyY0PNbgFTLHdCEDuQalr9hilmP97bD8HIGk1SZ2SVmvMKentlFpfrcc9IyIiIiIiImIBptms0z0oSJpFycw61faR/b2f6H+SrgLeBtxke5vu+o4ePdo333zz/NlYLNAa/7Z/MGYqRETMD4P5fycH894jIiIGK0m32G5bEmqBPrpoe6n+3kMMLLbf0997iIiIiIiIiIh5Y2E9uhgREREREREREQuYBTqjKyJioBjf2ZmCxYPImOHD2X/EiJ47RkRERETEgNLvGV2SLGmGpGN72f8cSd+c1/vqD/W3WHM2xl0r6RNzeS9bSXq4m/YzJA2qumeStq2F61+WtG1/7yciBqbxnZ1cMGVKf28jIiIiIiJmw0DJ6NrI9r2NC0n7Al8EVgZmAjcDH7c9vZ/21yeSOpsuh1AK4r9Urz9p+/z5v6u5y/YBXbVJWgL4FvAxYDnKmxQvs/257uaUtCVwLXCs7a823R9T51sJuArYx/ZTXcwxEjib8tbHfwMH2b667vlqoEPSxN48Y8TcNKqjI4WKB4lk3kVEREREDF79ntHVqgY7jgN2tT0UWA+4uH931Te2OxofSrBlh6Z7gz7I1QuHA6OBTYGhwLuBbv+fo6TFgVOAv7XcXx/4IbAHMJwS+Px+N1NdWNdaETgC+Lmk18zWU0RERERERETEoDJQMrqabQLcaHscQM3c+UlLn+UlXQG8C7gTGGP7PgBJpwAfBpYF/gV81vZ1te0c4OFGtpCkrYDzbK9SrycCpwNjgdWB3wJ72p4laXngp5RMocWA64EDbHd5vK+VpE0pwZz1gGeBS4BDbT/fpu/mlKDNWGB8L9ZeXdL1wIbAjfU3eaLO9TNgC2Bp4FbgQNt31Lb3Ad8FVgWeAU6y/d2mfXwe+DIlI+0rts9u91u22AS41Pakej2xfrrzeeD3wGtb7u8G/Nr2n+u6RwJ3SRramuEnaW3gLcB2tp8FLpH0WeAjwBk9rP8qE2bOHPCZHakjFBEREREREfFfAy6ji5LR815Jx0h6p6Ql2/TZFTgGWB64F2iu7/V3YBSwAnAB8DNJS/Vh/Y8C/w94AyVotFe9vwjlSNzqwGqUQNXpfZgXSrDoc5QjeG8HtgE+1dpJ0nspQa6P2P5jL9ceA+xNCRQtAXyhqe1KYK3a9g+gOavsLMpxyqHABsA1TW2vowQMVwb2Bb5XA349+StwqKRPSXqzJHXXWdLqwD7A19s0r08JzgFQA5rPA2t30ff+lgDYrfX+Aid1hCIiIiIiIiJeacBldNm+TtKHKQGgQ4DFJP0v8EXbjTpXv7B9E4Ck84ETm8af1zTdCZK+CqxDU7CkB6c2MpEk/ZoSNMP2k5QMLGrbscAf+/hstzRdTpT0Q2BL4OSm+7sABwDvs/3PPqx9tu17avvFwAeb1v1x09ijgaclLWt7GvAC8CZJt9p+Gni6ac4XgK/bfhH4Ta09tg4lkNWdb9V5dgNOAp6UdLjt1sy8hlOBI213tomJdQDTWu5NoxyJ7G3flXvYb1vrDBkyoGsqDfRss4iIiIiIiIj5bSBmdGH7Sts7ULKydqRkVTW/VXBy0/eZlAAHUI7aSbpL0jRJUykZSSv1Yfm2c0saIumHkh6U9AzwZ2A5SYv2dmJJa0u6XNLkOsdxbfb2WeDiRpCrD2t3te9FJX1b0n117MTap7HuR4D3AQ9K+pOktzfN82QNcr1q3u7Yfsn292y/k1KM/ljgx5LWa/Ob7AAMtX1RF9N1AsNa7g0D2r2YoC99IyIiIiIiImIBMyADXQ22X7b9B8pxug166i9pC0o9qY8Cy9tejpLR00gTmkF5C2LD6/qwnc9Tspk2sz2MUh+Mprl74wfA3cBadY6vtBm/C7BTrS01N9YeQwkWbksJ+o1sHmv777Z3pBxrvIy5XPjf9rO2v0fJ8HpTmy7bAKNr8G8y5U2Nn5X0y9p+B7BRo7OkNwJLAve0mesO4I2SmrO9Nqr3IyIiIiIiImIBN+ACXZJ2lPRxScur2JRyvK+n43JQjrO9CDxOOfL4NV6Z4TMeeJ+kFSS9jpI91VtDKbWxpkpaATiqD2Ob53gG6JS0LnBgmz6TKMGfgyV9qmnc7K49FHgOeJIS5Duu0SBpCUm71WOML9S9vdR+mt6T9FlJW0laWtJikvas+2h31u5ISr2tUfXzK+BMSr0xKPXEdpC0haRlKHW8ftFaiB6gHt0cDxwlaSlJH6LUWbuktW9ERERERERELHgGXKCLkvmzH+WNic8A5wH/Y/v8bkcVv6MUXr8HeBCYBTzU1P5TSq2uiZQ3/HV1XK6dkylvLXyCEnT7bR/GNnyBkmE1nRLMabu+7X9Tgl1flvSJOVz7XMpv8QjlDZWtAcM9KPXCnqHUBtu9D3N35VngBMpxyieAT1MK69/f2tH2dNuTG586dkZ92yb17ZAHUAJej1ECZv8p4C/pDEnNb1T8ODCa8s/Rt4GdbT8+F54pIiIiIiIiIgY42e7fDUizKBlHp9o+sl83Ews0SdtQsruWpBT77/ZlAqNHj/bNN988X/Y2O7YaN47xnZ2M6uixbNqgMmb4cPYfMaK/tzFXNV4cMJBfbhD/lb9XxPw3mP97N5j3HhERMVhJusX26HZt/f7WRdtL9fceYuFQ670t19/7iK6N7+wEWOACXRERERERETF/9HugKyJm36iOjgXq3yA3/q14RERERERExOwYiDW6IiIiIiIiIiIi+iyBrm5IsqQZko7t770MRJImStq2v/fRF5KOqX9TS0pGY0RERERERMQCJIGunm1k+4jmG5KWkdQp6TfzYkFJI2sgprN+pki6XNJ75sV684KkVSRdIukJSdMk/VPSXr0Yd1R99lcF0CQtIeluSQ93M34JST+vQThL2qq53fZRwPqz8UgRERERERERMcAl0DV7dqa8KXI7Sa+fh+ssZ7sD2Ai4Cri0N8Gidvohe+mnwEPA6sCKwFhgSncDJK1B+W0f7aLLF4HHerH2X4Ddgcm93WxEREREREREDH45ujV79gTOALYHdgO+K+ltwGXAyrZfApD0IeAY2xtK2hQ4BVgPeBa4BDjU9vM9LWZ7MnCKpMWB4yWda/tlSQbWsn1vXe8c4GHbX62ZTOcBpwGfA66SdDAlALUZ5W9/PXCA7Yfr+GuB64CtgQ2BG4Extp+o7XsA3wQ6gBN72PYmwOdsz6jXvakyfjrwZeD7rQ2S3kAJXh0KnNnVBPX3PLmOeakXa3ZpwsyZA7o4+vjOTkZ1dPT3NiIiIiIiIiIGjGR09ZGk1YCtgPPrZyyA7b8CMyhBooYxwAX1+0uUgNNKwNuBbYBP9XH5XwCvBdbpZf/XAStQsqr2p/y9z67Xq1ECbqe3jBkD7F3XWQL4AoCkNwE/APYARlCytFbpZu2/At+T9PH6m3VL0i7A87a7Og56GvCVuuegvHFxzPDh/b2NiIiIiIiIiAEjGV19Nxa4zfadkqYC35G0se1xwIXArpTsqaHA+6iBItu3NM0xUdIPgS2p2Ue9NKn+5wq97P8ycJTt5+p1I5MMgFpk/48tY862fU9tvxj4YL2/M3C57T/XtiOBg7pZexdKdtaRwLqS/gnsZ/vvrR0ldQDHAdu1m6hmxi1m+9LWmlvz0jpDhnDtxhvPr+UiIiIiIiIiYg4l0NV3Y6lH52xPkvQnylHGcZTsrRskHQh8GPiH7QcBJK1NOe43GhhC+e1vefX03Vq5/udTvez/uO1ZjQtJQ4CTgP8HLF9vD5W0aOO4Ja+sazWTckwRShbXQ40G2zMkPdnVwrafBg4DDpO0EvBd4DJJq9h2S/djgJ/afqB1HknLAN+hBA1jITC+s3NAHxmdHTlmGhERERERMX/k6GIfSHoHsBZwuKTJkiZT6l3tKmkx23cCD1JqdzUfW4Ry7O9uSk2tYZRjeOrjFj5EKcY+oV7PpATNGl7X0r81oPR5yrHHzeoe3tV4tF6s/SiwauOiBs1W7M2ma42v71KCZe2y0bYBDm76TVcFLpb0ZcrvPRK4rrb9Anh97TuyN+tH9LccM42IiIiIiJg/ktHVN3tS3n44tune0sBtlODWrynBrYMpdbh2a+o3FHgG6JS0LnAg8HhvFpU0nHIU8CjgENsv16bxwBhJdwDvoRyFvLmbqYZSji9OlbRCna+3fg78TdLmwE3A1+kmUCrpeErh+7spv9GBwL2222WBbQMs3nT9d0rR+SuBWTQF2IB3UOqKvYUufj9JS/Lf4N0SkpYCnmuTSRYD0KiOjhwZjYiIiIiIiNmSjK5eqsGSjwKn2Z7c9HmAEtDZs3a9kFKs/prG2wqrL1CyvKZTjj5e1Itlp0qaAfyTcnRvF9s/bmo/BNgBmEoJql3Ww3wnU4JOT1CKxf+2F3sAwPYdwKcpgbxHgaeBh7sZMgS4tO7tfkoB/A+262j7yebflFK4/2nbnbZfbGl7Cni5XjfebnmHpOag4gRKQG9l4Hf1++q9fdaIiIiIiIiIGJyUJJeuSZoFPAecavvI/t5PzDlJR1GyxZYElmmqTfYqo0eP9s03d5cgF3NbozZXMrqiP+Wfw4j5bzD/924w7z0iImKwknSL7dHt2nJ0sRu2l+rvPcTcZfsYSvH7iIguDYaXIowZPpz9R4zo721ERERERAwoOboYERExyIzv7OSCKVP6exsREREREQNOMroiIiJaDPSXIgz0bLOIiIiIiP6yUGZ0SbKkGZKO7cOYKyXt2XPPhYOkrSR1V4x+QJJ0n6TnJZ3X33uJiIiIiIiIiLlroQx0VRvZPqJxIWkJSUdL+lcNgk2U9GNJIwFsb2/7J/NjY3UfL0iaXj/3SDpd0uvnx/pzg6QdJY2X9IykJyT9ofFbdjNmCUl3twbQJI2U9EdJM2v7tt3M0fjtOps+b2y0214DOG4OHy8iIiIiIiIiBqAcXfyvnwOrAGOAccAywO7ANsBZszuppMVsvzgbQy+yvbukxYG1KQXUb5H0VtuPzsY+Fu3uDYNzk6Q1gXOBDwPXAB3AdsDLPQz9IvBY7d/sQuBG4H3183NJa9l+vIt5LrK9+2xu/z8mzJyZ40Hz2fjOTkZ1tP75IyIiIiIiInpnYc7o+o+aIfQeYEfbf7f9ou1ptr9n+6za51pJn6jf15B0jaQna7bS+ZKWa5pvoqQvS7oNmCFpMUmH1WNz0yXdKelDvdmb7Rds3wF8DHgc+HxdYy9Jf2l5DtcgE5LOkfQDSb+RNAN4t6T3SxpXs6weknR009iRdfyekv5dn6s5423pOufTku4ENulm26OAB2z/wcV025fY/nc3f4M3UAKL32q5vzbwFuAo28/avgT4J/CRnn+9GGxGdXQwZvjw/t5GREREREREDFLJ6Cq2BW6y/VAv+4sSkPkzMAy4BDga+GxTn12B9wNP2H5R0n3AFsBkYBfgPElr9jY7y/ZLkn4JvLeXe4SSnfY+4APAEsDbgLHAHcAGwFWSxtu+rGnM5sA6lCyymyT9wvZdwFHAGvWzDHBlN+v+A1hX0knAr4C/2+7sYa+nAV8Bnm25vz5wv+3pTfdurfe7soOkp4BHgdNt/6CHtdtaZ8iQAV2MOiIiIiIiIiJeKRldxYqUoEiv2L7X9lW2n6vH504Etmzpdqrth2w/W8f8zPYk2y/bvgj4F7BpH/c5CVihD/1/afv6uuYs29fa/me9vo1yJLB138fUzKlbKQGljer9jwLH2n6qBgRP7WpR2/cDWwErAxcDT9RssLZn0mp222K2L23T3AFMa7k3DRjaxfIXA+sBrwH2A74madeu9hoRERERERERC44EuoongV4Xepf0Wkn/J+kRSc8A5wErtXR7qGXM2FqcfaqkqZSMqtYxPVkZeKoP/Vv3sFkt6v64pGnAAW32MLnp+0z+Wy9rRMt8D3a3sO2/2v6o7ddQMtneBRzR2k/SMsB3gM90MVUnJWuu2TBgepu+2L6zBhRfsn0DcAqwc3d7jYiIiIiIiIgFQwJdxdXAppJW6WX/bwEGNrQ9jFJbSi193PgiaXXgTOAgYEXbywG3txnTJUmLADsA19VbM4AhTe2vazPMLdcXUI4Srmp7WeCMPuzhUWDVpuvVejkO238HfkEJ7rVaCxgJXCdpcu33ekmT61sa7wDeKKk5g2ujer9Xy9OH3zkiIiIiIiIiBq8EugDbVwNXAZdKemstHj9U0gGS9mkzZCgl02iqpJUpbwvszjKUgMvjAJL2pn3Q51UkLS5pPcoxw9dRjklCrVMlaZSkpSg1wnoyFHjK9ixJm1JqePXWxcDhkpavAcGuMrCQtLmk/SS9tl6vC3wQ+Gub7rdTAmij6ucTwJT6/SHb9wDjgaMkLVWPOW5IqYvWbu0d6x5Vn/Fg4Jd9eM6IiIiIiIiIGKQS6PqvnYHfABdRakDdDoymZHu1OobyJsBpwBWULKQu2b4TOAG4kRLEeTNwfQ/7+ZikTmAqJQvrSeCttifVOe8Bvl739y/gL11N1ORTwNclTQe+Rgle9dYxlOOKDwC/B37aTd+plMDWP+sz/Ba4lHJE8RXqGy4nNz6Uo5kv1+uXarePU/4WTwPfBnautdGQtEVdg6a+91KONp4LHG/7J314zoiIiIiIiIgYpGS3nm5b8EmaBTxHKRh/ZH/vJ+YfSROoRfJtt8vW+4/Ro0f75ptvnj8bi4gBY6tx4wAG9FtXB8MeI/piMP8zPZj3HhERMVhJusX26HZti83vzQwEtpfq7z1E/7C9Tn/vISIiIiIiIiLmjRxdjIiIiIiIiIiIBcJcCXRJsqQZko7tw5iJkradG+vPLf29J0l7SepNra3WcSPr32CuZuhJOkfSN7tp75T0xrm55rxWn+lZSQ/3914iIiIiIiIiYu6amxldG9k+ovmGpGVqMOQ3c3GdAU/SbvW5O2tQ5eWm686eZxgcbHfYvr9dm6T1Jf1e0tOSpkq6RdL7uuj7bkn/rP2elHRpfZtlo31JST+W9IykyZIO7W5fkj4j6YHa/2ZJmzfteS9g+9l74oiIiIiIiIgYyOb10cWdKUXft5P0+nm8Vr9pzaSyfX4NAnVQgiqTGtf13sLg18BVwHDgtcDBwDNd9L0TeK/t5YARlLdI/qCp/WhgLWB14N3AlyT9v3YTSdqM+mZGYFngLOBSSYvO4fNERERERERExAA3r4vR7wmcQQn27AZ8t10nSYsAXwL2A5YD/gAcYPspST8AXmN759r3eGA0sG3t+1NgM8qzXF/HPVz7XgtcB2wNbAjcCIyx/URt3wP4JtABnNiHPY0EHgA+ARwFTATe1ZsfRNJhdc7XAg8BR9i+tIu+/wO8HXg/sHnd6xrANOAs20e3DNlN0jeAIcBJto+t82wKnAKsBzwLXAIcavt5SarPvhuwJPBg/Y1ur3MuL+mK+nx31rb76rwG1rJ9b8u+VwLeAJxp+/l6+/qufhPbU1puvQSs2XQ9Ftjb9tPA05LOBPYCfttmupHAHbZvqXs5F/g+5fd+tKs9tDNh5sz/vEkpFlxjhg9n/xEj+nsbERERERERMRfMs4wuSasBWwHn18/YbrofDOwEbEnJ6Hka+F5t+zywYa1ftQWwL7CnbVP2fzYl02c1ShDn9Ja5xwB7UwIdSwBfqPt7EyVraI+65orAKr3cU8OWlODRe7v7LVrcB2xByTY6BjivNdtN0iI1mLMhsJ3tacAMym+4HCXwdaCknVrm3hxYB9gG+Jqk9er9l4DPAStRAmfbAJ+qbdtRglhr17k/BjzZNOeudZ/LA/cCvanD9mTte56knSQN72mApNUkTaX8Db8AfKfeX57y+9/a1P1WYP0uproSWFTSZjWLax9gPDC5F/uOhcz4zk4umNIaZ42IiIiIiIjBal5mdI0FbrN9Zw1gfEfSxrbbpch8EjioKRPraODfkvawPVPS7pTsnenAZxr9bD9JyU6ijjsW+GPL3Gfbvqe2Xwx8sN7fGbjc9p9r25HAQb3ZU1Ofo23P6MuPYvtnTZcXSToc2BT4Zb23OHAh5W+zQyMjyva1TeNuk3QhJdB2WdP9Y2w/C9wq6VZgI+CuRnZTNVHSD+vYk4EXgKHAusBNtu9q2fIvbN9Uf4Pzacl86+IZLendwGHACcAbapH9fW3/q4sx/waWk7QCJePt7trUOOo5ran7tLrndqZT/pn4CyBgKrB9DYz2yTpDhnDtxhv3dVgMIsnYi4iIiIiIWLDMyxpdYymZXNieBPyJcpSxndUpdZSm1qDYXZQspOF1/E3A/ZTAxcWNQZKGSPqhpAclPQP8mRIsaa7H1JzJM5P/Bk5GUI4OUteYwSszmbrdU/UQfSRprKTxTfNuQMm0algT2JEStHq+adxmkv4o6XFJ04ADWsZ1+ayS1pZ0eS3k/gxwXGOs7WsoWXDfA6ZI+l9Jw3qasye2H7Z9kO01KL/lDODcXox7CvgJ8Mta+6xRvL95T8MoAa12PkHJ4lqfksG3O3C5pJxNi4iIiIiIiFjAzZOMLknvoBQPP1zS5+vtocD6kr5g+8WWIQ8B+9huW8dJ0qcp9aMmUepmfas2fZ5yVG8z25MljQLGUQJiPXmUcuywscYQyvHFHvdUa3QB9ClLSNLqwJmUo4M32n5J0viW/d5FCTpdKWlr2xPq/QsoAantbc+SdDKvDnR15QeU32VX29MlfZaS0VYewj4VOFXSaymBxC8CR/bl2bpj+yFJ36Nk1LhSQwAAIABJREFUqvXGYpSjpsNqTbRHKdlpV9X2jYA7uhi7EfDrRhYf8Ns6/h3Az2frASIiBqDxnZ3JSpxPUssvIiIiYvCYVxlde1KCEm8CRtXPBpQi6du36X8GcGwNBCHpNZJ2rN/XphRh351ST+tLNaAFJXj2LDC1Hnk7qg97/DnwAUmbS1oC+Dqv/D263NMcWIYSHHu8zrk35Xd5BdsXAl8Brpa0Rr09FHiqBrk2pdQe662hlDcedkpaFziw0SBpk5ottjgl62oWJXNttklaXtIxktas9cZWomRZ/bWL/h+WtE7t+xrK8chxNbsLSibYV+u861KONp7TxfJ/B94v6Y0q3kOpP3Z7F/0jIiK6lFp+EREREYPLXM/okrQU8FFgrO3JLW0/pQTBft0y7BRKVtPv6xGzxyj1q64AzgOOt31rneMrwE8ljabUmLoAeIKS7XUCpYB8j2zfUTPFLqAEoE4EHu5pT/y3llaf1XplJ1De/vgyJYDTNovN9k9qAO4aSVtSisefIOl0yjHQiynF43vjC8D/UrLhxtXn2Lq2DQNOAt5ICXL9ji7ejtkHz1Pefng1Jeusk1I77TNd9F+Z8rd7LeVI4rXAh5raj6JkpT1ICWweb/s/b1yU1EnJdLuO8puuUedYnvI3/aTtu4mIWICM6uhIHcH5IFlzEREREYOLZqNG96snkWYBzwGn2p5rR94i5jZJZwG7AI/ZXrO7vqNHj/bNN988fzYW/WKrceMY39nJqI5elZ6LhUTjn4mBHERqBF8G8h4XFPmt54/B/DsP5r1HREQMVpJusT26XdtcyeiyvdTcmCdiXrO9L7Bvf+8jIgauUR0djBk+vOeOEREREREx4MyTYvQREYPFQM/ciYiIiIiIiN6bV8XoFziSLGmGpGN72f8cSd+s37eQNKGnMTFvSdpWUqeklyVt29/7iYiIiIiIiIi5K4GuvtnI9hEAkkbW4Fdny+djrYNsX2d7nbm5kab1B1xWnqQlJJ0g6eH6mzwg6aRu+v9R0uOSnpF0a+vbLSWNkfRgDTReVt+w2dVc35D0T0kvSjq6uc321bY7gH/P6TNGRERERERExMCTQNecW852R9Pnov7e0ABwODAa2BQYCryb8rbHrhwCvN72MGB/4DxJrweQtD7wQ2APYDgwE/h+N3PdS3m75BVz+AwRERERERERMcgk0DUfSNpK0sNN14dJuk/SdEl3SvpQU9uakv4kaZqkJyT1OXAmaYSkX0l6StK9kvZrajta0s8lXVTX/4ekjVrGXlIzrB6QdHBT29SmzLUZNaNsZJstbAJcanuSi4m2z+1qv7Zvs/1i4xJYHFi1Xu8G/Nr2n213AkcCH5Y0tIu5fmL7SmB6b36riIiIiIiIiFhwDLhjbwuJ+4AtgMnALpQMpjVtPwp8A/g9JQtqCUpmVF9dCNwBjADWBa6SdL/tP9T2HYFdgd0p2VSXSVobeAn4NfDL2r4KcLWkCbZ/Z3u5xgKSjgM2Bx5ps/5fgUMlPQ9cB9xu291tWNLlwLbAksDvgJtr0/rADY1+tu+r864N3NLL32O2TJg58z+vDI8F0/jOTkZ1dPT3NiIiIiIiImIuSUbXnHuiZjo1Puv1NMD2z2q208v1qOO/KMf8AF4AVgdG2J5l+y992YykVSkBqC/X8eOBH1GO/jXcYvvntl8ATgSWAt5GycR6je2v237e9v3AmcDHW9b4GDAG+Eido9W3gOMp2Vg3A49I2rO7fdv+AOWY4/uA39l+uTZ1ANNauk+rfSPmyKiODsYMH97f24iIiIiIiIi5JBldc26lpmN3vSJpLHAoMLLe6gBWqt+/RMnquknS08AJtn/ch+lHAE/Zbj669yCvzAx7qPHF9sv1WOUIyrHBEZKmNvVdlJKV1dj7xsDpwHa2H2+3AdsvAd8DvidpaWAf4MeSbrJ9V1cbr0GzKyUdIuk+278COoFhLV2HMR+OJq4zZAjXbrzxvF4mIiIiIiIiIuaSBLrmM0mrU7KktgFutP2SpPGAAGxPBvarfTenHB38s+17e7nEJGAFSUObgl2r8cojho36V0hahHJEcRLwIvCA7bW62PtrgEuBg2z36kyf7WcpAa9jgDcBXQa6miwGrFG/3wE01xB7I+V44z29WT8iIiIiIiIiFh45ujj/LUPJnHocQNLewAaNRkm7SFqlXj5d+77UzXxLSlqq8aEEtG4AvlXvbQjsC5zfNOatkj4saTHgs8BzlLpaNwHPSPqypKUlLSppA0mb1L6XAOf39GZJSZ+tBfiXlrRYPbY4lDZvXpS0rqTta9/FJe0OvAv4U+1yPrCDpC0kLQN8HfhFS8Za83yL199hEWCx+hss2t1+IyIiIiIiImLBkEDXnGt+E2GnpEO762z7TuAE4EZgCvBm4PqmLpsAf5PUCfwKOMT2A91M2Qk82/TZmlJIfiQlS+tS4CjbVzWN+SXwMUogbQ/gw7ZfqEcOdwBGAQ8AT1Dqey1LyfraAvhsy/Ou1mZPz9ZnnFzn+DSlntf9bfoKOBp4jBL8OwT4mO1/1N/rDuAASsDrMUrA7FP/GSydIemMpvnOrOvvChxRvzfXJ4uIiIiIiIiIBVSOLvbec8Atkk61faTtidTjhu3Y3qvp+7WUQFHj+ghKEKbduC9R6nR1q6f1gQ900zbL9u5dzDuJEiRqp7v1muf4IfDDXva9C9ishz4XABd00XZAy/VewF7t+krahpKVtiTdZ8lFRERERERExCCUQFcv2V6qv/cQc8b2H4Dl+nsfERERERERETFv5OhiREREREREREQsEJLRtZCxfXR/7yEiIiIiIiIiYl5IRtd8JMmSZkg6tg9j7pC01Tzc1kJF0jWSZkn6S3/vJSIiIiIiIiLmrgS65r+NajH6/5C0TH2D4W9aO9tevxazfxVJ50j65jza5xyRtLmkGyRNk/SUpOslbdKLcdfUgOBi9XpJSWdJelDSdEnjJG3fzfiPS5pQ131M0k8kDWu0296a8hbHiIiIiIiIiFjAJNA1MOxMeavjdpJe39+bmVM1sHQ5cBqwArAycAzlGbsbtxuvPk67GPAQsCWwLHAkcLGkkV1Mcz3wTtvLAm+s4wdkMDAiIiIiIiIi5q7U6BoY9gTOALYHdgO+22iQNBH4hO2r+zKhpP2AL1MCTX8BDrA9qbYZOAT4LDAMOBv4su2Xa/s+wBeB1wE3AfvbflDSl4CvNS2zJHC+7b1all8bwPaF9fpZ4Pc97HdZ4ChgLHBj477tGcDRTV0vl/QA8FZgYus8th9qufUSsGZ3a3dlwsyZbDVu3OwMjYiYp8Z3djKqo6O/txERERERMeAko6ufSVoN2Ao4v37GzoU5twa+BXwUeD3wIPB/Ld0+BIwG3gLsCOxTx+4EfAX4MPAa4DrgQgDb37HdYbsDWA94HLi4zRbuAV6qxwa3l7R8L7Z9HPADYHIPzzacEki7o5s+m0uaBkwHPgKc3Iv1IyIGjVEdHYwZPry/txERERERMeAko6v/jQVus32npKnAdyRtbHtOUol2A35s+x8Akg4HnpY00vbE2ud4208BT0k6GdgV+BHwSeBbtu+qY48DviJpddsP1ntLA5cBp9huV1fsGUmbUzLKzgReV+uP7Wd7Smt/SaOBd1KyzFbp6qEkLU4JBv7E9t1d9bP9F2BZSSsD+9Em86s31hkyhGs33nh2hkZEREREREREP0hGV/8bSwneUI8W/olylHFOjKBkcVHn7QSepNTKamg+4vdgHQOwOnCKpKk18PYUoJaxZwETbB/f1QZs32V7L9urABvU+V+VWSVpEeD7wCG2X+xqvtrvp8DzwEFd9WvZwyPAb3l1NltERERERERELIAS6OpHkt4BrAUcLmmypMnAZsCujbcOzqZJlIBVY51lgBWBR5r6rNr0fbU6BkoA7JO2l2v6LG37hjrXYcA6wL693UzNvjqHEvBqNYxyhPKi+vx/r/cflrRFXVOU4Npw4CO2X+jt2pSsxTX60D8iIiIiIiIiBqkEuvrXnsBVwJuAUfWzATCEUpi+NxaVtFTTZwngAmBvSaMkLUmpf/W3pmOLAF+UtLykVSlHBi+q98+gBN7Wh1IkXtIu9fv2wMHATraf7WpDktaV9HlJq9TrVSlHI//apvs0SrZX4/nfV++/Ffhb/f4DSk2wHbpbt661m6TVVKwOHAv8obsxEREREREREbFgSKCrn0hailIs/jTbk5s+D1CO6PX2+OJhlLcaNj7X2P4DcCRwCfAoJaPp4y3jfgncAowHrqBkTGH7UuB44P8kPQPczn+Dbh+jFKi/S1Jn/ZzRZk/TKZlpf5M0gxLguh34fGtHF/95fkqBe4Aptp+vwapPUoJgk5vW3a3+jqvV69XquDcBNwCdwPXABEqdrvj/7N17vFVVuf/xz1dUELcIpKKgSN6o9MTGQ2olSUcrNc3ymCaaoqlZx7RSf3mJFBNLT3nLSo9ZXvBemnnNS5GXNAVBS1PzAqEICgiyuXjB5/fHGEsny73XXgv2Zu3L9/16zZdrzTHmmM9c23Ne5zw+45lmZmZmZmZmXZwiot4xdBuSlgJvAOdHxNg6xhHAlhHxbL1iqBdJdwE7AA9HxM6V5o4YMSImTZq0agIzM7MOadSU9G4Yv5ykfXXm37kzx25mZtZZSZocESOaG/NbF1ehiOhV7xi6u4j4TL1jMDMzMzMzM7P24a2LZmZmZmZmZmbWJbiiqxuKCNU7BjMzs85ialPTu9vT6mH0gAEcMXBg3e5vZmZm1pm4oovUs0rSIknj6x2LtR9Ju+TG9e9I2qXe8ZiZmbVmalMTV82eXe8wzMzMzDoNV3S9Z1ipObukIcALwG0R8fnSBEkTgGcj4tSVuZGkU4EtIuLAFbz+UuDFiPj+ysTRHiRNAw6LiLsL58bkcztWuGYAsCyf+mtEfLYwPhr4EbAecBdwaETMa2GtRuBnwEdJb3/8v4g4DSDH1JDvZ2ZmVpXGhoa6NRqvZyWZmZmZWWfkiq7KdpD0yXoH0U3sGREN+SgmubYGLgK+SkqGLQZ+UWGdq4B7gf7ATsA3JH2h/cI2MzMzMzMzs47CFV2VnQWcDny6fEBSP+AKYHvS7/gAcGREvJjHBwIXAjsC84AzI+JiSbsCJ6Up+iLwXEQMa2l+rQFLOhz4HinRc3+OaWYeC+AY4NtAH+A3wPci4p08fihwPLAh8DBwRERMl/T/gB8UbtMTuDIixtQa3wo4ALg5Iu7NMY4F/ilpnYhY2Mz8ITm2ZcBzku4Htgb+UOuNn1682P8l3armHjpmZmZmZmb154quyn4ObNVCP6fVSImiTYHBwBLggsL41cCLwEBgH+AMSTtHxB3AGcC1uXppWKX5tQQr6b9IW/z2BTYCpgPXlE37EjAC2BbYCzg0X/tFUgJub2B94L4cExFxVqnaCvgw8CpwXS2xVeFKSa9KulPSsML5rYHHSl8i4jngTWCrFtY5FzhI0hqShgIfB+5uYa5Zm3APHTMzMzMzs47BFV2VLQXGk6q6lkuWRMRc4Hel77mR/Z/z501IlVl7RMRSYKqkX5G2391TfpNa51dwAPDriHg0r3si8JqkIRExLc85M/e3mifpXGB/4FfA14EfRcQ/87VnACdJ2jQipudzawG/B86LiNsqxPF7SW8Xvq8JPNpK3I8CIlWc/VHShyJiPtAALCibvwBYp4W1bgEuB44DegCnRcQjFe7doqG9e9etJ4t1Lq78MzMzMzMz6xhc0dW6i4EBkvYsnpTUW9JFkqZLep3UF6qvpB6kqqx5ZVvrpgODWrhHrfNbMjBfB0BENAFzy9aZUXaP0l6rTYHzJM2XNJ+0fVJl114CPB0RZ7YSxxcjom/pAL5ZaXJEPBARSyJicUT8CJgPjMzDTaRtlkV9SI3mlyOpP3AHcBrQC9gE+Jykivc3MzMzMzMzs67Bia5WRMRbwDjgh6TET8mxwFBg+4joA3wqnxcwE+gvqVh1NBh4qbRs2W1am1+tmaSEVQpEWhv4QNk6m5TdY2b+PAP4ejFBFRFrRcRf81onkJ73azXGtCKC937rJ4B3tzJK2ozUI+yZZq7bDFgWEZdHxNu5X9o1wO7tHK+ZmZmZmZmZdQBOdFXnClJyZdfCuXVIfbnm50qiU0oDETED+CvwI0m9JH2UlCC6Mk+ZDQyRtFqV85vTI88tHWuS3jh4iKRGST1JvcD+Vti2CHC8pH55u+QxwLX5/IXAifkth0haV9KX8+fdgKNJlVpLqv7VqiBpsKRPSlozP8fxwHqk5v6QfoM9JY3MibvTgBtaaET/TFpSoyWtJmlDYD8KPb7MzMzMzMzMrOtyoqsK+Q1+p5DeZFhyLrAWMAd4iLRlrmh/0hsAZwI3AqdExF157Pr8z7mSHq1ifnNOICXaSsefIuIeYCypd9jLwObAV8quuwmYDEwFbiVtRyQibgTOBK7JWzH/AeyWr9mP1KD+n5Ka8nFhhdhqsQ7wS+A1UuXZrsBuuQcaEfEEcCQp4fVKnv/uVkRJF5ZiiYjXSc30v5PXm5qfY3wbxWpmZmZmZmZmHZgiynfRdT+SlgJvAOdHxNh6x9NeJAWwZUQ8W+9Y6iG/xfJ3pOq83SPiz5XmjxgxIiZNmrRKYrPObdSUKUxtaqKxoaHqa0YPGMARAwe2PtHM6qr0sol6vZyk3vdfVTrzc3bm2M3MzDorSZMjYkRzY37rIhARveodg7W/XPHWt95xmE1tagJwosvMzMzMzKyNOdFlZtYGGhsaqv6v+aX/+m9mZmZmZmZty4mubiQi1PosMzMzMzMzM7POqVM2o5cUkhZJqkuT8fwGwKfrce+OQNJESYfVO44VIek5SW9KmlDvWMzMzMzMzMysbXXKRFc2LCJOLp6QtHZ+I+BttSwkaZSkF6udHxH3RcTQWu5RQyylJF6TpLmS7pG0X3vcqz1IOrW5JFJ+ri1auXZNSU8V/xaSNpB0taSZkhZIekDS9hXW+Lak5yW9nq85R9K7lYsRsTlwxgo+npmZmZmZmZl1YJ050dWcfUhvT/yspI3qHcxKGBYRDcBQ4FLgAkmnrMhCxSRPJ3A88ErZuQbgEeA/gf7AZcCtklp6vd3NwLYR0QfYBhgGHN0+4ZqZmZmZmZlZR9KZkiDVOBi4ENgNOAD4SWlA0jTgAuAgYFPgjjy/B3A70FNSU56+FTAXOBPYN5+7DvheRLwhaRQwISI2rrR2RCzN43sApwNDgCeBIyPi8dYeJiLmAFdIWgJMkHRBRMzN9zssIu7O658KbBERB0oaArwAHAacAkwDPiXpemAksBbwGPCNiHgiX38psCjH96kc4+iIeC6Pfwb4GbARcAXQ5r2+JH0QOBD4LnBx4Td4Hji7MPX/JP2ElAScXL5OKebSssA7QMVKspY8vXixm4ZbVaY2NdHY0FLu1czMzMzMzFaVLlPRJWkwMAq4Mh8HNTNtX2BX4IPAR4ExEbGIlBibGREN+ZgJnAzsADSSqoK2A75fIYT3rZ3j2hb4NfB14APARcAfJPWs4fFuIiUlt6vhmp2ADwOfy99vB7YENgAeJf1GRfsD44B+wLPA+Bz/esDvSM++HvAc8Mka4qjWz4CTgCWVJklqBNbMMbY0Z7Sk14E5pL/dRW0Yp9n7NDY0MHrAgHqHYWZmZmZm1u11pYqug4DHI+JJSfOBsyQNj4hiSc75OYmFpJtJSayWHAB8KyJeyfPHkRImY1uY39LahwMXRcTf8vfLJJ1ESqL9pZoHi4i3JM0hbd2r1qk5iVda49elz7kC7DVJ60bEgnz6hoh4OI9fyXtVVLsDT0bEb/PYucCxrdx731zFVhVJXwJWj4gbc7VcS/P6kCrKxhXifp+IuAq4StKWpH8vZlcbS9HQ3r2ZOHz4ilxqZmZmZmZmZnXQ1RJdFwNExExJfyFtTSwmumYVPi8GBlZYbyAwvfB9eivzW1p7U+BgSd8qjK/ZylrLkbQGsD4wr9prgBmF63uQKrS+nNd5Jw+tB5QSRuXxl/ZhDSyuFREhaQaVXRcRB5Y9QzQ3UdLawFmkhFqLJK1F6r/1UET8qJX7l2L9l6QngF8Ae1dzjdmqMrWpyVtju5nRAwZwxMCq/1e/mZmZmZmtgC6xdVHSJ0jb8k6UNEvSLGB7YP8qm7E3l4SZSUpSlQzO52o1AxgfEX0LR++IuLqGNfYC3gYezt8XAb0L4xs2c03xmUbnNXYB1iX14oLqem29DGxS+iJJxe9tYMscz33573YDsFH+Ow7J9+wJ/B54ibQFtBarA5u3VbBmZitialMTV81eoeJSMzMzMzOrQVep6DoYuIvl+3KtBTxO6r91cyvXzwY+ULaV72rg+5IeISWNfgBMWIHYLgZulHQ3KVHVm9RL7N6IWFjpQkn9c/xnA2dGxNw8NBX4iqTbST2o9iE1wG/JOqS3Uc7N9z+jhvhvJb31cW/gD8D/0HxibUX9g+UTZ58gNfbfFng1V7P9ltS766CIeOf9S7xH0mHAHyLiFUkfAU4E/tiG8Zq1icaGBm+N7UZcvWdmZmZmtmp0+oouSb1IjeB/FhGzCscLpH5OB7e2RkQ8RUpsPS9pvqSBpLckTiIly/5OauB+eq3xRcQkUp+uC4DXSE3Ux7Ry2WP5DZDPkt6e+J2I+EFhfCypSuk1UgP5q1pZ73LS1suXSG9UfKiG+OeQtjz+mJQo2xJ4oNrrq1j/7eLfjbQ98538fRkp8bUH8FlgvqSmfIwEkDSy8LZMSI3y/y5pEXBbPk5qq3jNzMzMzMzMrOPqrBVdbwCTJZ0fEWNJbwp8n4j4ZuHzkLKxU8u+H9rMEkfno3zdicDGNax9B5UrropzW91OGBHPk7ZmNjc2jbItiRHRRNq6WHR5YXxM2fyJLP98dwBbtRZXnntqC+er2SbZ3L3/QoUtlhFxH+/1EyMiDqm0vqSngUHAddXEY2ZmZmZmZmadR6dMdEVEr3rHYJ1TRAytdwxmZmZmZmZm1j46/dZFMzMzMzMzMzMzcKLLzMzMzMzMzMy6iC6d6JIUkhZJGl/DNSNzH6eVue+QfO9OuTW0NZJGSXqx3nGsCElfy83sQ9IW9Y7HzMzMzMzMzNpOl050ZcMi4mRYLgF1a3GCpAmSToXU3LyefZwknSrpLUkL8/GMpAskbVSvmGrVXBIpP9eEVq5ZVHir4q8KYz0lnSNppqTXJP1C0hoV1uoh6fQ8f6GkKZL6AkTEJRHR0NK1ZmZmZmZmZtZ5dYdEV3N2kPTJegdRwbURsQ7QH/gSsCHpLZMrlOyS1KMtg2tHwyKiIR+HFc6fAIwAtiG9/XFb4PsV1hkHfAL4ONAH+CqwtH1CNjMzMzMzM7OOokturavCWcDpwKfLBySNAiZExMb5+ybAecBIUmLw6og4StJqwEnA4cBawB3AtyJiQTNrrgucDewOvAP8BjglIpZVCjIi3gKekLQf8ChwLHCcpDHAYRGxY+EeAWwZEc9KuhRYAmwK7ATsJalnfubNgQXAJRFxar52CPACMAb4IdAbOCcixufxtYBfAnsBL+f4V6U9gTMjYl6O53zgTOCU8omS+gHfJiXNpufT/1iRmz69eDGjpkxZsYjNKpja1ERjgwsLzczMzMzM2lp3TXT9HDha0i4RcXdLk3Il1C3An0hVQctIlUWQkkJjSMmyV4DLgQvyvHKXAbOBLYC185ozgIuqCTYilkm6CfhcNfOz0aTE2h7AmsAOwEHAE6TKqLskTY2I3xeu2REYSqqaeljSDRHxT1JCafN8rA3cXkMctbg3JxD/Cnw3Iqbl88oHhe8bS1q3mcTifwBvA/tI+g7wOnBeRPy8nWI2q1ljQwOjBwyodxi2ik1tanLyvBNyYtrMzMysc+muia6lwHhShVOLiS5gO2AgcHxEvJ3P3Z//eQBwdkQ8DyDpROAfkg4pLiBpALAb0DcilgCLJJ0DHEGVia5sJmkrY7VuiogH8uelwMTC2OOSriZVexUTXeNyjI9JegwYBvwT2Bf4Zq6ompcrqn7Qyv0flfRO4Xsv4LcV5u8EPESqJjsduEVSY/7dbweOkfRnoAdwdL6mN6k6rWhjYF1Ssu6DwJbAPZKeiYi7Wol5OUN792bi8OG1XGJmZl2ME9NmZmZmnUt3TXQBXAwcL2nPCnM2AaYXklxFA4Hphe/TSb9n+f81vCmwBvCy9G5R0mqkiq5aDALm1TB/ufUlbQ/8mFTNtSbQE7i+7JpZhc+LgdJ/wh5Ytl7xuVuybUQ8W7j/qaSKtmZFxL3545uSjiFVYn0Y+DspKdkXmAq8QfrbDSdV0pVbkv95Wk7aPS7pGlJ1W02JLjOzttTY0ODkuZmZmZlZO+uuzehL/a/GkXpSqYVpM4DBkppLCM4kJbFKBpO2zM1uZo03gPUiom8++kTE1tXGmrfz7Qncl08tIlUzlcY3bOayKPt+FfAHYJOIWBe4kJafu9zLpKRfyeAqr1sZQY4vIpZExFERMSgiNgPmApNb6HH2eOF6MzMzMzMzM+tGum2iK7uCVNm0awvjD5OSPD+WtLakXoW3NV4NfEfSByU1AGeQ3pa4XPVXRLwM3An8VFIfSatJ2lzSTq0FJ2kNSR/O99qQ1NAe4DFga0mNknoBp1bxrOsA8yJiqaTtSD28qnUdcKKkfpI2Br5Vw7WtklR6lh75t/wp8BJp2ySSBkkaqGQHYCzNNKIHiIjnSAnBkyX1zL/ffqS+aGZmZmZmZmbWhXXrRFeuCDqFFnpf5fE9SVvu/g28SEqaAPyalCi7l/TGwqW0nAA6iLRd8EngNVKvqo0qhLafpCZgPqkKay7wnxExM8f1DHAaqb/Yv3ivb1gl3wROk7SQ1F/ruiquKRlH2q74Ailpd0UN11ZjAHAtabvi88AQYI9cdQepCf5fSZVslwEnRMSdpYsl3S7ppMJ6+5Oq7eYCtwJjI+KeNo7ZzMzMzMzMzDoYRXTdHV6SlpK2DZ4fEWPrHY/VX37EWluDAAAgAElEQVRZwDmk5vgfKb1MoDkjRoyISZMmrbLYzKzrKr1t0T26rFbd5d+dzvycnTl2MzOzzkrS5IgY0dxYl25GHxG96h2DdSwR8RvgN/WOw8zMzMzMzMzaXrfeumhmZmZmZmZmZl2HE11mZmZmZmZmZtYldNpEl6SQtEjS+CrnXyrp9PaOqzvozL+lpD9JWiqpmgb+ZmZmZmZmZtaJdNpEVzYsIk4ufZH0NUlPSVooabakWyWtU88AayVpmqQl+RnmS/qrpCMldYq/laQxzSWR8nPtUuGaZZKaCseownh/STfmxOZ0SaMr3L+npHMkzZT0mqRfSFqjNB4R/wUcuXJPaWZmZmZmZmYdUZdpRi9pJ+AMYNeImCKpP7BnncNaUXtGxN2S1gV2As4DtgcOqXUhSatHxNttHWA7eDAidmxh7OfAm8AAoBG4VdJjEfFEM3NPAEYA2wA9gJuB7wOn1BrQ04sXv/smJTOzlTG1qYnGhoZ6h2FmZmZm1uV1iiqhKn2MlCyZAhAR8yLisohYWJjTL1d5LZT0N0mblwYknSdphqTXJU2WNLIwttxWPUmjJL1Y+D5N0nGSHpe0QNK1knrlsX6SbpH0aq4wukXSxtU8UEQsiIg/APsBB0vaJq85UdJhhfsvV0WVt3X+j6R/Af+q4vlOlXSdpMvzb/OEpBGF8eGSHs1j1wKr7G2WktYG/hsYGxFNEXE/8Afgqy1csidwfv77vwqcDxy6aqI1M2teY0MDowcMqHcYZmZmZmZdXpep6AL+BvxQ0jjgTmBSRLxRNmd/YFfgUeAyYDzwlTz2CHAasAA4Brhe0pCIWFrl/ffNay8FHgDGABeSkom/yeM9gF8DFwBfrPbBIuLhnFgbCfyjysu+SKoCW5K/t/Z8XwD2JlWNnZ5j3EHSmsDvgXPzub2Aq4Ezq42/SsMlzQHmAVcAP8qVaFsByyLimcLcx0iVbs1RPorfN5a0bkQsqCWgob17M3H48FouMTMzMzMzM7M66jIVXRFxHylRsy1wKzBX0tmSehSm3RARD+cEypWkbXCl6ydExNyIeDsifgr0BIbWEML5ETEzIuaRtss15nXnRsTvImJxri4bT8tJmkpmAv1rmP+jXNW0JMfR2vPdHxG3RcQyUqJpWD6/A7AGcG5EvBURvyUlzSrZIfcXe/cABleYfy9pq+EGpOqt/YHj81gDKTlXtABoqffa7cAxktaXtCFwdD7fu5WYzczMzMzMzKyT6zKJLoCIuD0i9iQlhPYiVVUdVpgyq/B5MSmJAoCkYyX9M289nA+sC6xXw+2bXVtSb0kX5Sbqr5OSOn3LEnDVGESqdqrWjOKXKp6vPP5eklYHBgIvRUQUxqe3cu+HIqJv8QD+3dLkiHg+Il6IiHci4u+kyrN98nAT0Kfskj7AQpo3HpgCTAX+SqpGewt4pZWYzczMzMzMzKyT61KJrpKcMLkH+BOpUqii3K/qe6Tthf1yYmYB722BW8TyFUEb1hDOsaTKqe0jog/wqdJtq11A0sdIia5SH65q4nk3MVXF81XyMjBIUnFupeqsthC8F9szwOqStiyMDwOaa0RPRCyJiKMiYlBEbAbMBSbnSjUzMzMzMzMz68K6TKJL0l6SvpKbv0vSdqQtgg9Vcfk6wNvAq6Skyg9YvopoKrC7pP55O9y3awhtHVKfrPn5TZBVv/1PUh9JewDXABNytVMpnr1ztdgWwNeqiKHS81XyYL72aEmrS9ob2K7aZ6iGpN0kDcifPwSMBW4CiIhFwA3AaZLWlvRJUrXeFS2sNUjSwPzvwA55rZrfuGhmZmZmZmZmnU+XSXQBrwGHk94y+DowAfjfiLiyimv/SOrt9AxpW95Slt/6dwWpAfo0UqP7a2uI61xgLWAOKel2RxXX3CxpYY7hZOBsUpP4knOAN4HZpKb6rT1ja8/Xooh4k9T7bAzpN96PlHhqSzsDj0taBNyW1z+jMP5N0m/4CqkR/jci4gkASYMlNUkqVZltTtqyuIj025wQEXe2cbxmZmZmZmZm1gFp+dZLnYekpcAbpCbwY+sdj3UOku4iNdh/OCJ2rjR3xIgRMWnSpFUTmJmZWTNGTZkC0OXfAtyZn7Mzx25mZtZZSZocESOaG1t9VQfTViKiV71jsM4nIj5T7xjMzMzMzMzMrH10pa2LZmZmZmZmZmbWjTnRlUkKSYskjV9F9xsp6ekK45dKOn1VxNJdSOqZ+3m95d/WzMzMzMzMrOtxomt5wyLiZABJQ3LyqykfsyXdIqlNtr5FxH0RMXRFrpU0RtL9bRFHW2suQVf4LStulc1vtXy1/NkkNUqaLGlx/mdjhTWeKPzNmiS9LelmgIh4IyIaaL15v5mZmZmZmZl1Qk50ta5vTo4MA+4CbpQ0pr4hdVlnAv8snpC0JnAT6S2a/UhvUrwpn3+fiNg6Ihry32wd4N/A9e0atZmZmZmZmZl1CJ22Gf2qFhGzgPMkrQGcKenyiHhH0gnA4cAGwAzg5Ii4UVJPYDawY0T8A0DS+qTEy6bAR4AJEbFxHhsOXAJsCdwGrNDrMCV9AjgP2Ap4BjgmIv6axyYCDwI7A0OBicAhETEvj+8AnJ1jm56vnSjp46QkX8nqwKyIGLIiMbYQ98eBbYD/A75WGBqV73dupFeEni/pOOC/gDtaWfZTpL/L71YkpqcXL373TUpd1egBAzhi4MB6h2FmZmZmZmbWJlzRVbsbSMmT0rbD54CRwLrAOGCCpI0i4o08d//CtfsCf4mIV4oL5uqk3wNXAP1JFUj/XWtgkvoDtwLnAx8gJa1ulfSBwrSDgEOBgcDbeS6SBuVrT88xHAf8TtL6EfFgoUqqH/AQcHWt8VWIuwfwc+Ao3p/g2xp4PCe5Sh7P51tzMPDbiFjUJoF2MVObmrhq9ux6h2FmZmZmZmbWZlzRVbuZ+Z/9ASKiuC3uWkknAtuRtttdRapQOjmPjwYuambNHYA1eK9q6beSvrsCsX0e+FdEXJG/Xy3paGBP4NJ87opChdlYYKqkg4EDgdsi4rY87y5Jk4DdSdsFS84HFhWeqTnHSTqq8L21hOrRwN8iYrKk/ygbawAWlJ1bQNqW2CJJvYF9gC+0cu8WDe3dm4nDh6/o5R1eV69WMzMzMzMzs+7HFV21G5T/Wdrud5CkqZLmS5pP2n63Xp7zJ2AtSdtL2hRoBG5sZs2BwEtlVUvTVyC2gc1cN70QM6TtlcWxNXK8mwJfLj1HfpYdgY1KkyV9nbSVcHREvFMhjp9ERN/SAXy0pYmSBpISXS0lzpqAPmXn+gALK9wfYG/S3+gvrcwzMzMzMzMzsy7CFV21+xLwCvB0Tl5dTOp59WBELJM0FRBA7uF1HWn74mzglohoLkHzMjBIkgrJrsGkbZG1mElKWBUNZvleVpuUjb0FzCElwK6IiMObW1jSSOCHpJ5j5RVWK2M7UjLtSUkAa5GSg7NICbongGPLfpuPkrY6VnIwcHlZ8tDMzMzMzMzMujBXdFVJ0oC8He8U4MRc0bQ2qafUq3nOIaSKrqKrgP2AA/Ln5jxI6pd1tKTVJe1NSgC1EpJ6FQ9SE/utJI3O6+xHaix/S+G6AyV9JG/tO43Uw2oZ6a2Ge0r6nKQeec1RkjaWtAlwLXBQRDzT+q9Vk9uBIaRqt0bgB8AUoDHHNRFYRvpteha2RP6ppQUlbQx8muW3XJqZmZmZmZlZF+dEV+vmS1oE/J3Ur+rLEfFrgIh4EvgpKVE1G/gP4IHixRHxN1JPq4GkpM77RMSbpK12Y4DXSImxG1qJ6xPAkrJjAbAHcCwwF/h/wB4RMadw3RWkfl2zgF6kbYNExAxgL+AkUuJuBnA86d+RnYENSb3DmvLxRCvxVSUi3oiIWaUjP8Nb+XPpt/kiqYn+fFIj/S/m80g6oJlYvkqqsKu1Is7MzMzMzMzMOjF5Z1ciaSnwBnB+RIytdzztQdJEYEJE/KresdSDpJ6khOQawFkRMa7S/BEjRsSkSZNWSWz1MGrKFKY2NdHY0FDvUKwFowcM4IiBA+sdhpnVUenFIV355SjQuZ+zM8duZmbWWUmaHBEjmhtzj64sInrVOwZrXxHxBtC33nGYVWNqUxOAE11mZmZmZmY1cKLLrBtrbGjwf4HuoEoVAmZmZmZmZlY9J7q6kYgYVe8YzMzMzMzMzMzaS6duRi8pJC2SNH4V3GeL9rxHZyFpSP49Ol2SVNIuuZH+O5J2qXc8ZmZmZmZmZta2OnWiKxsWESfDckmYW4sTJE2QdGo1i0maKOmwdoizmnuPkbSs8GbDFyT9RtJW9YhnRUiaVp5Eys91fxXX7pT/fqeXnf9W/i1elzRJ0o4V1vizpFfz3Mck7VUai4i7I6IB+PcKPJqZmZmZmZmZdXBdIdHVnB0kfbLeQaygB3MyZl1gF2AJMFnSNiuyWGepvJK0BnAe8Ley89sDPwb2If0mlwA3SurRwlLHABtFRB/gCGCCpI3aLXAzMzMzMzMz6zA6RRJkBZwFnA58unxAUj/gCmB70vM/ABwZES/mLZAjSYmyc4FLI+KofOkukm4H1gOuAo6KiJC0OXAxMAwI4I/A/0TE/Hy/acAFwEHApsAdwMERsbTSA0TEMuA54JuSBgOnAvtIGgVMiIiNC880DTgsIu7OlWvbAEuBLwDflfQ4KYn0YVLi7HfAdyPizXx9AN8Ajm3m+XoAZwJjgNeBn1aKeyUcC9wJbFB2fgjwRERMzrFeDvwiz3u5fJGIeLz4FVgD2KS5ua15evHiLt0QfGpTE40NDfUOw8zMzMzMzKzNdNWKrp8DW7XQh2k14DekpNNgUuLnAoC8BfI+UpKnoZDkAtgD+BgpobUv8Ll8XsCPgIGkRNImpKRU0b7ArsAHgY+Skka1uIGUgKvWXsBvgb7AlcAy4DukJNbHgZ2Bb5Zd09LzHZ7HhgMjSJVVbUrSpsChwGnNDN8O9JC0fU66HQpMBWZVWO8WSUtJ1WETgUltHXNX0NjQwOgBA+odhpmZmZmZmVmb6aoVXUuB8aSqrruLAxExl1TRBECu4vpzFWv+OFdpzZf0Z6ARuCMingWezXNelXQ2cErZtedHxMx8v5vztbWYCfSvYf6DEfH7/HkJMLkwNk3SRcBOwLmF880+HynpdW5EzMjx/wgY1cr9fy/p7cL3NYFHK8w/HxgbEU2SyscWkv5e95OSivOB3SIiWlosIvbIWyF3AT4UEe+0Em+zhvbuzcThw1fkUjMzMzMzMzOrg65a0QVpO+EASXsWT0rqLekiSdMlvQ7cC/St0POppFhBtBhoyOttIOkaSS/l9SaQKqdavbYGg4B5NcyfUfwiaatc5TQrx3hGDTEOLFtvehX3/2JE9C0dvL96rBjbnsA6EXFtC1MOI1VxbU1KmB0I3CJpYKUAIuKtiLgd+JykL1QRs5mZmZmZmZl1cl020RURbwHjgB+SKoFKjgWGAtvnhuWfyudLc1qsFGrBj/I1H83rHVh2v7bwJdKWSoBFQO/SQE7QrV82v/wZfgk8BWyZYzyphhhfJm3HLBlc5XXV2hkYkZNws4D9gG9LuimPDwNujohnIuKdiLgjx/SJKtdfHdi8jWM2MzMzMzMzsw6oyya6siuAnqT+WCXrkLbzzZfUn/dvM5wNbFbDPdYBmvJ6g4DjVzzc90jqIemDkn5G2io4Lg89A/SS9Pm8Pe/7pGdsLcbXgSZJHyI1nq/WdcDRkjbOjfxPqOU5qjAW2Iq0VbIR+AOpGu+QPP4I8HlJmyn5TJ7/j/KFJH1I0m6S1pK0hqQDSYnMv7RxzGZmZmZmZmbWAXXpRFd+c+EpLN/f6lxgLWAO8BCpD1XReaS3G74m6fwqbjMO2BZYANxKahy/Mj4uqYmUmJoI9AE+FhF/B4iIBaStgL8CXiJVeL3YyprHAaNJ/a4uBlraJtici0lvknyM1GdrZZ9vORGxMCJmlQ5SEnJRRJS2al4OXEP6LV4n9fP6ekQ8BSDpQkkX5rkivQjgFeBV4Bhgv4io1B/MzMzMzMzMzLoIVejp3eHlN+u9QWr2Prbe8VjHJmlnUmP7nsDuEVHxJQQjRoyISZP8wkarj1FTpjC1qYnGhlpb+lVn9IABHDGwYqs7M+sARk2ZAtDlX47SmZ+zM8duZmbWWUmaHBEjmhvr1G9djIhe9Y7BOo+IuAfoW+84zOptalMTgBNdZmZmZmbW5XTqRJeZWVfW2NDQLhUCpeoDMzMzMzOzrqZL9+hqb5JC0iJJ46ucf6mk09s7LmuZpHH5bxaSnOg1MzMzMzMz60Kc6Fp5wyLi5NIXSV+T9JSkhZJmS7pV0jptfVNJ0yTt0tbrrixJQ5pLIlWb5JN0Sr5+l8K54yX9I/+mL0hq8c2Whfs3FY53+7dFxCnA1iv4eGZmZmZmZmbWgbmipQ1J2gk4A9g1IqZI6g/sWeewOg1JmwP7AC+XDwEHAY8DmwN3SpoREddUWK5vRLzdPpGamZmZmZmZWUfkiq629THgwYiYAhAR8yLisohYWJjTL1d5LZT0t5zcAUDSJyQ9ImlB/ucnag1AUk9J50qamY9zJfXMY6MkvSjpJElzclXYAWXX/kTSv3M12oWS1spjN5dVSb0jacwK/k4tuQD4HvBm8WREnBURj0bE2xHxNHAT8Mk2vreZmZmZmZmZdXKu6GpbfwN+KGkccCcwKSLeKJuzP7Ar8ChwGTAe+Equ/roVOBq4GvgycKukLSJibg0xnAzsADQCQUoKfR8obd/bEFgPGJTn3SZpUk4gnQlslq99C7gK+AFwYkS8W5kmaVfg18A9NcRVkaQvA29GxG2SKs0TMBK4qJUlp0sK4C7g+IiYU2tMTy9e3KWbdo8eMMBv3TMzMzMzM7MuxRVdbSgi7gP2BrYlJa3mSjpbUo/CtBsi4uG8re5KUlIJ4PPAvyLiily5dDXwFLVvfTwAOC0iXomIV4FxwFfL5oyNiDci4i85zn1zAulw4Du5Em0haRvmV4oXStoKuBzYLyJmVIhjjqT5pQMY3dJESQ35Xt+u4vlOJf17+5uW7kuqrNsU+E9gHdLvbAVTm5q4avbseodhZmZmZmZm1qZc0dXGIuJ24HZJqwGfBq4Hnua9CqRZhemLgYb8eSAwvWy56aTKq1qUrzM9nyt5LSIWNTO+PtAbmFyoqBLwbpJO0rqkCrGxOalXyXrFHlmSLq0wdxxwRUS8UGlBSUeRenWNbKZSDoCIaAIm5a+z8zUvS+oTEa+3EvNyhvbuzcThw2u5pNPoypVqZmZmZmZm1n25oqudRMQ7EXEP8CdgmyoumUmqQioaDLxU463L1xmcz5X0k7R2M+NzgCXA1hHRNx/rRkQDQE7cXQX8OSJa2zZYq52BoyXNkjQL2AS4TtL3ShMkHQqcAOwcES/WsHaUlmizaM3MzMzMzMysQ3Kiqw1J2kvSVyT1U7IdsBPwUBWX3wZsJWm0pNUl7Qd8BLilwjVrSOpVOFYn9ff6vqT1Ja1H6rE1oey6cZLWlDQS2AO4PiLeAS4GzpG0QX6eQZI+l68ZD6wNHFPVj1GbnUnJwMZ8zAS+Dvw8x3EAaWvjZyLi+UoLSdpe0lBJq0n6AHA+MDEiFrRD3GZmZmZmZmbWgTjR1bZeI/W5+hfwOinB9L8R0WqPqNxwfg/gWGAu8P+APVppon4bqQqrdJwKnE7auvc48HdS0/vTC9fMynHOJPWuOjIinspj3wOeBR6S9DpwNzA0j+1Pal7/WuHNiwfQBiJibkTMKh3AMtIWy6Y85XTgA8AjhXtfWLpe0hOFWDYD7gAWAv8A3sixm5mZmZmZmVkX5x5dK+cNUk+r8yNibETcS6pOalZEjCn7PhHYuPD9flID9VZFxJAKw0fno6Vrx5MqtMrPLwVOykct9yvOm0Yz2wTLn72VNYaUff9gK/O3Lny+mlTV1ixJpwDfJf3toqV53cHUpib36urApjY10djQ0PpEMzMzMzMze5cTXSshInrVOwarTUSMIzW/N+vQGhsaGD1gQL3DMDMzMzMz61Sc6DLrphobGrrsWyXNzMzMzMyse3Kiqxsp3yppZmZmZmZmZtaVdNtm9JJC0iJJ7+tVtQLrbNHC2AGS7lyZ9a1tSbpU0hJJL9Y7FjMzMzMzMzNrW9020ZUNi4iTASQNyUmrpsLx2MosHhFXRsRn2ybU5VVKsNWTpFHNJZEkTZR0WAvXfFrS3yXNlzRX0o2SBhXGB0m6SdI8SS9KOrKVGNaXdFVe7zVJ7771MjfF323Fn9DMzMzMzMzMOqrunuhqTt+IaMjHsHoH0008CXwuIvoCA4F/Ab8sjE8AXgAGAJ8HzpD06Qrr3QDMAjYFNgB+0h5Bm5mZmZmZmVnH4h5drZC0HXAe8GFgCfA74LsR8WZh2u6Svg30AX4DfC8i3pE0BjgsInbMa50H7A2sS0rmfDsi7stjpwIfAZYCXwL+DRwcEZNqjHdd4GekqqXFwMXAGYV4DgceBQ4CXgb+JyLuKVx7NrA78E5+llMiYlmubtu8cKu1gU/nvl8rJSJml51aBmyRY2oARgH7RsRbwGOSfgscCvy5mef/LLAJMCoiluXTU1YkrqcXL2bUlBW6tMOb2tREY0NDvcMwMzMzMzMza1Ou6GrdMuA7wHrAx4GdgW+WzfkSMALYFtiLlIRpziNAI9AfuAq4XlKvwvgXgGuAvsAfgAtWIN6fkRJpmwE7kRJahxTGtweez89zCnCDpP557DLgbVKSaTjwWeAwgIgYVqp0A74LPE1KmLUJSYMlzSclE48DzioNlf2z9HmbFpbaIcd2Wd4G+Yikndoqzq6isaGB0QMG1DsMMzMzMzMzszbliq73myO9m1M5PSKK296mSbqIlEA6t3D+zIiYB8yTdC6wP/Cr8oUjYkLh608lfR8YCpR6gd0fEbcBSLoC+HYtgUvqAewHDI+IhcBCST8Fvgpckqe9ApwbEQFcK+lY4PO5af5upK2bS4BFks4BjgAuKtxjR+B0YMeIeL2FUAbmpFVRA2kLYrMi4t9A35x0Oxx4Kp9fKOkBYKyk40lVb/8NvNrCUhvzXoLukDz3JklbRMSclu7fnKG9ezNx+PBaLjEzMzMzMzOzOnKi6/3Wi4i3S18kbUXazjcC6E36zSaXXTOj8Hk6qc/U++Sk0mF5PEhbHdcrTJlV+LwY6CVp9WI8rcUOrJljKMYzqPD9pZzkKo93U2AN4OVCom81Cs8maRPgOtKWymcqxDEzIjYunpA0sZoHiIh5ki4jbVEclJ/9AODnOZbngStJCa/mLAGmRUQpsXeNpJOBTwI3VRODmZmZmZmZmXVO3rrYul+Sqou2jIg+wEksv40OUk+oksHAzPJFJI0EvgfsC/TLjdcXNLPWypgDvEVKWhXjeanwfZAKmaxCvDOAN0iJvr756BMRW+f41wJ+T6oGu70NY27O6qQm8n0AImJ6ROwREetHxPbAB4CHW7j2cVIS0czMzMzMzMy6GSe6WrcO8DrQJOlDwDeamXO8pH654ukY4NoW1nmbtOVudUk/ICdyVsKaknqVjnzuOmC8pHUkbUrqp1XcMrgBcLSkNSR9mdRk/7aIeBm4k7Slso+k1SRtXuhv9WvgqYg4izYmaW9JQ/M91ydV0E3J20GR9OH8PGtKOpC0NfHsFpa7Eegn6WBJPSTtQ6poe6Ct4zYzMzMzMzOzjsWJrtYdB4wGFpLeYNhcEusm0nbGqcCtvNcPq+iPwO3AM6TtgktZfsvjiniCtFWvdBwCfAtYRNridz+p6f2vC9f8DdiSVP01HtgnIubmsYNIWx+fBF4DfgtslMe+AnxJUlPhGLmS8ZcMAu4g/cZ/J73x8UuF8c/l53kNOBLYNSLe7dFVjCUnx75A+rstAE4A9qq1P5eZmZmZmZmZdT5avl1T9yFpKWmr3vkRMbbe8awKksYAh0XEjvWOpV4kXQJ8GXglIraoNHfEiBExadKkVROY2So0asoUAL9swawT6C7/89qZn7Mzx25mZtZZSZocESOaG+u2zegjolfrs6yriYivAV+rdxxmZmZmZmZm1va8ddHMzMzMzMzMzLoEJ7q6kYi4tDtvWzQzMzMzMzOzrq1Lb12UFMBi4NyIOLmd7zWN1P/q7va8T0cg6VRgi4g4sN6x1ErSpcB+wNyI2LjO4ZjVzdSmpnf7ytiqNXrAAI4YOLDeYZiZmZmZdUndoaJrWHmSS9La+U19t9UrqJZImihpqaSFkl6XNFnSCZJ61ju2akgaJenFZs5PlHRYFdf/RlJI2qJwrr+kayXNyceVkvpUWGN9SVdJmi/pNUlXlsYiYgywW+1PZma28qY2NXHV7Nn1DsPMzMzMrMvq0hVdFexDeuPiZyVtFBEv1zugMkdFxK8krQ18DDgX+IykXaLG12RKWj0i3m6XKNuYpB2BzZsZOh3oB2wGCPgdcCrw3RaWugF4BNiUVNG3TVvHatbZNTY0+A1hdeAqOjMzMzOz9tVdE10HAxeSKnsOAH5SGpD0PeBooA8wE/hmRNyTt7y9GBHfz/NGAROa2/4m6UPA7cCJEXGNpOuBkcBawGPANyLiidaCjIhFwERJXwCeAj4P3NJaLHkb5S/zsw3NCbPjgMOBDYAZwMkRcWOePwY4DHiI9EbC+fm5b8/jHwQuBbbNc55uLfZaSVod+Bnpb/NY2fAHgd9HxOt57o3AF1pY57PAJsCoiFiWT6/Q/2f59OLF7f7/lHoLk5mZmZmZmVnb6Q5bF5cjaTAwCrgyHwcVxoYCRwEfi4h1gM8B02pcf1vgTuBbEXFNPn07sCUpyfRovm/VIuLfwCRSsqxa+5MSY31zRddz+fp1gXHABEkbFeZvT0pgrQecBVwiSXnsKmByHvshKRnV1r4D3BsRjzcz9nNgD0n9JPUD/pv0mzZnB9JzXCZprqRHJO3UDvGuNG9hMjMzMzMzM2tb3bGi6yDg8Yh4UtJ84CxJwyNiCrAM6Al8RNKrETRDk18AACAASURBVDGtxrVHkiqivhoRfy6djIhflz7nRu6vSVo3IhbUsPZMoH8N88+PiBmFGK4vjF0r6URgO+CmfG56RFycY7wM+AUwQNKapO2Tu0TEG8C9km5u5d4D829b1ABMaG6ypE2ArwP/2cJ6jwJrAnPz93tyfM3ZGPgsqULtEFJS7CZJW0TEnFbiXs7Q3r3bdWuXtzCZmZmZmZmZta1uV9FFSnRdCRARM4G/kCuUIuJZ4Nuk/k+vSLpGUi37yo4E/lpMcknqIenHkp6T9DrvVYitV2Pcg4B5NcyfUfwi6SBJU3OD9vmkvlXFGGaVPkTE4vyxARgIvJa3UZZMb+XeMyOib/EA7q8w/1zgtAqJv+uBZ4B1SFtKn6OFpBmwBJgWEZdExFu5qm4G8MlWYjYzMzMzMzOzTq5bJbokfYK0hfBESbMkzSJt2ds/94giIq6KiB1JjcwDODNfvgjoXVhuw2ZucSQwWNI5hXOjgb2AXUjbBoeUwqkh7k1I1U731RDLu03rJW0KXEzalvmBnHj6R5UxvAz0y32+SgZXG3uVdgb+t/A3AXhQ0uj8eRhwUUQsiogmUn+13VtY63EKz25mZmZmZmZm3Ue3SnSRKrfuAj4CNOZjG1LSaDdJQyX9l6SewFJSdVCpoflUYHdJ/SVtSKr8KrcQ2BX4lKQf53PrkN7wODff54xqg5XUO/eXugl4GLithliK1iYlf17N6x5ClW8ijIjppP5g4yStmd+MuGe1z1ClrUjJrNLfhHyPG/PnR4DDJK0laS3gCN7fsL7kRlJi7uBcTbcPqRrugTaO2czMzMzMzMw6mG6T6JLUC9gX+FlEzCocLwBXkJJgPYEfA3NIW/k2AE7KS1xBSq5MIzWbv7a5+0TEfOAzpMTZD4HLSVv9XgKeJL21sDUXSFoIzCZt6/sdsGtEvFNLLIWYngR+CjyY1/wPakv8jCZVvs0DTsnP1GYi4pXi3ySfnhMRS/LnQ0mVcC+SfsfNgDGl6yU1SRqZ15pHeiPjccAC4ARgr1r7c5mZmZmZmZlZ59PVm9G/AUyWdH5EjAX6NTcpIr5Z+LpdC3OWAvuVnT6nMD6k8HkeqUKpZK+y61pMFEXEqJbGViSWwrmTgZNbWO9S4NKycyp8fp4q3/gYERNJDeHLz4+q5vrye+fvL1ChiiwiGsq+30dK5r2PpEuALwOvVBtPe5ra1LTKmtKPHjCAIwbW0nLOzMzMzMzMrHPp0omuiOhV7xisY4mIr5HejNmtTG1qAnCiy8zMzMzMzLq0Lp3oMuvoGhsamDh8eLvfZ1VVjZmZmZmZmZnVU7fp0WVmZmZmZmZmZl1bh0x0SQpJiySNr8O9R0p6elXf19qfpK1y4/plkg6rdzxmZmZmZmZm1rY6ZKIrG5YbqCNpSE5+NeVjtqRfSFpjZW+S192i9D0i7ouIoSu7boX7jZY0KT/Hy5Jul7Rje91vVZM0sTyJJGmUpBdbuWZp4e/7dGFsTUm/lTQt/61GVRnHlnnNCaVzEfFMblx/X+1PZmZmZmZmZmYdXUdOdDWnb05U/AfwceB/6hxPTSR9FzgXOAMYAAwGfsH738pYzVrv66/W3LlO5KiIaMhHeaLxfuBAYFYN6/0ceKTNojMzMzMzMzOzDq9TJkYi4hVJdwEfKZ2TdAJwOLABMAM4OSJuzGNbAJcAjcBbwD0RsZ+ke/Plj0kK0tv4ZgMTImLjKtb9/+zdebyd47n/8c8XIWIn0gipEHJqCKUkPSkdqLR0oKa2FNEaaqg6fjjVwZSKalCnlBgOx9CYoqYaaqyhMRWtIbSG1JQIkTSDkJ0QxPX7474Xj2Xttfba2cnaw/f9eq3XXs9zD8/1PCsvf1yu+372AfYHHspj5wIHR8St5TFLWhn4FbBvRPyx0PSn/EHSZsAZwIbAW8C1wE8i4p3cHsAhwOHAcpL2BS4DzgT+G7hD0qHApcDmpN/3AeCgiHilEPMvgVWBWcCxEXF5bjsA+AmwZr7X70fEY5I2BP43P79XgaMi4sYqP1G7yfd+eo5vUWvGSNqd9Fv8FVi3RvcWTVqwYIlu4j6xuZmhTU1LbH4zMzMzMzOz7qazVXQBIGkg8A1SgqnkBWBLYGXgeOAySavnthOAPwOfICVxzgSIiC/n9k1zJdGVFS5XbV5ICaVJQH/gFOBCSaowzxeAnsB1VW5tESlh1T/33xo4uKzPzvmapSTfJ4F+wNrAgaTf9Pf5eC1SwuwsAEkrAWOBbSOiN/BFYGJu2xUYDewF9AF2BGbn5aF/Ij2/1YD/B1wuqb2Xd54kaZakB1q7PLESSX1ICcUj2i2yJWRoUxMjBwxodBhmZmZmZmZmXUZnq+ialXNIKwMPAteUGiLi6kK/KyUdBWwG3ECq4lobGJgrm+5v7QVrzAswJSLOB5B0MWkp4gA+vsxuFWBWRLxX5VqPFg4nSzoP2Ipc0ZSdFBFz8vUA3geOi4iFub1UCUbuMwb4S2H8+8DGkl6OiNeA1/L5/YFTIqK03O/5PH5LoAk4OSLeB+6WdBOwBykxVslYSb8tHC9HqrBqyS+Ap4F3gN2BP0kaGhEvVBnTkhOACyNiauV8Y+sN6dWLCcOGLdYcZmZmZmZmZrb0dLZEV/+IeE/SiqSqndtIVUlI2ou07G5w7ttEqowC+DkpAfI3Sa8Dp0bERa25YI15oZDQiogFOblSaT3abKC/pOVaSnZJWh84DRgO9CL9Po+WdZtadjwzIt4uzNEL+B3wTVIFG0BvSctGxHxJuwE/JVWePQAcERHPAoNI1WvlBgJTc5KrZAqwRqV7yA6NiAsKMY0gLbGsKCIeLhxeLGkPYDty5V1rSRoKbAM4O1XBxObmJboUc0kYOWAABw4c2OgwzMzMzMzMrJPolEsXI+ItYBzwBUn9Ja0NnE/av2qViOgL/BNQ7j89Ig6IiIHAj4Bzim9abEmteev0IPA2aelhS/4XeBZYLyL6AEdXuFbUOD4CGAJsnucoLc8sPYvbI+JrwOr5Wufn9qnAOhVimgYMklT8t7IWaa+uJSVo2zMeQUpIvixpOimh911Jj7VfaLa0TGxuZvyMGY0Ow8zMzMzMzDqRzlbRBYCkFYAfkKqpZpP2jgpgZm7fF9i40H9X4MG8bPH13Le0sfkM4FPkpXplVqo2bz0i4g1JvwTOlvQeac+rd0kVSF+JiJ8DvYE3gWZJGwA/Ll27Dr1JyxfnSuoHHFdqkDSAtL/XXblPMx8+hwuA0yTdDzxGSnq9CzwMzAd+LulU4EvADsDn6oyrIkl9c0z3AO8Bu5GSc4cX+qzAh4mv5SX1BBZGRHmS7/+APxSOf0pKfP24PWLt7IY2NXWqpZidrfrMzMzMzMzMGq+zVXTNldRMSk59AdgxkqeBU0lVUzOAz5DeNljyOeDhPPZG4LCIeCm3jSYtl5sr6XvFi7Vi3rpExGmkZZDHkhJYU0nVYtfnLj8FRgLzSJVWlTbHr+V0YEXSGxUfIi3vLFmGVPE1DZhD2v/r4Bzb1cAYYHy+/vVAv/zWwx2BbfOc5wB75eWO7aEH8GvS85hF2ux+54iYVOgziZSYWwO4PX9fG0DS0ZJuzfewIFfvTY+I6aRE3tsRUW+y0MzMzMzMzMw6IX28KKbxJL0NLATGRsSoRsdjXYOk9YC/A8sDB0fEuGr9hw8fHo888sjSCG2JK1VHdcaKrs4Uc2fhZ9s4fvZWr+7yb6Yz32dnjt3MzKyzkvRoRAyv1NYhly5GRM9Gx2BdT0Q8B/RtdBxmZmZmZmZmtmR0tqWLZmZmZmZmZmZmFTnRZWZmZmZmZmZmXUKnS3RJCknzJY1Zite8VdLerewbktZd0jFZ/SStIKlZ0ruSft3oeMzMzMzMzMysfXW6RFe2aUQcAyBpcE4uNefPDEk3Sfpae10sIraNiIvbYy5J35B0r6R5kmZKukfSju0xd0cgaVx5EqnwG1XcEy6PeafwGzZLWrbQPlTSo5IW5L9Da1y/4lwRsTAimoDL2+l2zczMzMzMzKwD6ZCb0bdR34h4T9Ingd2A6yQdUuvNekuTpF2Ai4CfADsA84Atge8DN9Y513IR8V6tc53IKRFxbPlJScsDNwCnA+cAPwJukLReRLxTz1z1mrRgwQdvUursJjY3M7SpqdFhmJmZmZmZmS1RnbWiq0URMT0izgBGA7+RtAyApCMlvZArqZ6W9O3SGEn7SLpf0m8lvS7pJUnbFtonSNq/cPxDSc/kvrdLWrtWXJIEnAacEBEXRMQbEfF+RNwTEQfkPutIulvSbEmzJF0uqW9hjsmSfiHpSWC+pHVzpdR+kl4G7s79rpY0XdIbuXpso8Ic2+X7nyfpVUk/LbTtJGmipDfzs/pmPj9Q0o2S5kh6XtIBdf8wbTeClJA9PVdkjQUEfHUpxtDpDW1qYuSAAY0Ow8zMzMzMzGyJ6koVXeX+CPwPMAR4BniBVD01HdgVuEzSuhHxWu6/OXAx0B84ELhQ0hoREcVJJe0MHE2qyHoOOBK4AvhijXiGAIOAa6r0EXAScC/QB7iWlLA7vNBnD+BbwCyglLnYCtgQeD8f3wr8EHgH+A1pqV5pud+FwPci4j5JnwD+I9/XZsAlwC7AXcDqQO885grgKWAgsAFwh6QXI+KuGvdcj4MlHQy8BJwYEdfm8xsBT5b9Dk/m87fVOVddhvTqxYRhw9oy1NrJxObmLlNV15G4ws/MzMzMzLqqrpzompb/9gOIiKsLbVdKOgrYjLQsDmBKRJwPIOli0jK5AaTEWNGPgJMi4pnc90TgaElrR8SUKvGskv++1lKHiHgeeD4fzpR0GnBcWbexETE1X7t0bnREzC/Mc1Hpu6TRwOuSVo6IN4B3gU9LeiIiXgdez133Ay6KiDvy8at5/CBgC2D7iHgbmCjpAuAHpIRYJT+VdEjhuFbl4FjgCOAN4Ouk32d6RDwANOXzRW/wYRKunrnMDFf4NVpHS+COHDCAAwcObHQYZmZmZmbtoisnutbIf+cASNqLtDfW4Hy+iVS9VfJBQisiFuQkUqWSh7WBMySdWjinfL1qia7Z+e/qpEqjj5G0GilRsyUpkbMMHyaiSqZWGPrBubzx+hhS1dqqfFjl1Z+U/PkucCxwcl4CeWREPEiqNrulwtwDgTkRMa9wbgowvOJdJr8t7pElaTAt3DNARDxWOLxF0uXAd4AHgGZSdVtRH9L+ZvXOZZ3M0KYmV9WZLUETm5sBnOgyMzMzsy6jKye6vg38G5iU99A6H9gaeDAiFkmaSEpQ1WsqMCYi6n1z36Q89rvAb1vocxIQwCYRMTsvkzyrrE98fNhHzo0EdgK2ASYDK5OSZQKIiL8DO0nqARwCXEVKck0F1qkw9zSgn6TehWTXWuSKryUk+PC3eQo4QpIKyxc3Ac5uw1xmZg3XkRK4HamyzMzMzMysPXS5zeglDcjL5o4DjoqI94GVSAmPmbnPvsDGbbzEucBRpQ3eJa0saddag3KS5ifAKEn7SuojaRlJW0j6v9ytN6mCaa6kNYCftSG+3sBCUgVZL+DEUoOk5SXtmZcxvgu8CSzKzRcC+0raOse1hqQN8jLJvwInSeopaRPSMsd6E30tkrSLpKZ83a/z0bdQTsgxHipphcKSyLvbMJeZmZmZmZmZdWFdKdE1V9J84B/AdsCupb2qIuJp4FTgQWAG8BnauJQtIq4jbfD+B0lvAv8Etq0+6oOx1wC7kTaKn5Zj+TUf7hN2PPBZ0hLDm0kb6tfrEtLSwleBp4GHytp/AEzOsR9ESgQREX8D9gV+l69/D2mZJqQN8AfnmK8Djivs5dUeDsvxziW9QOCAiJiQ43oH2BnYK7f/ENg5nycn7p5qzVxmZmZmZmZm1rV1xqWLC4FHJY2NiFERMZlWLE2LiGOAY1poGweMKzunwvcRZW2XApe2MFfVWCLiNlp4W2BEPAX8Z9npUwvtg8v6T6bs3iOimbR0seiSwvdvVontOlIiq/z8K8D2LY0r67tPhXMfi7Osfcsacz7Ox59Lqe1yCtVl1eaStAIpudgDOKXaNc3MzMzMzMys8+l0ia6I6NnoGKxzioiFQN9Gx2FmZmZmZmZmS0ZXWrpoZmZmZmZmZmbdWLdIdEkKSfMljWl0LK0laYKk/RsdR1ciaX1JzZIW+dmamZmZmZmZdT3dItGVbZr36ULS4Jz8eqzYQVJ/Se9ImtyQCFtJ0mhJlzU6jkoqJegkjZD0So0xb+ckVLOkSWXt+0t6PrfdJmlgW+aKiH9FRBNw32LcopmZmZmZmZl1UN0p0VXJSpI2LhyPBF5qVDDd3CER0ZQ/Q0onJW0FnEjaYL8f6fe5oi1zmZmZmZmZmVnX1uk2o29nlwJ7Az/Lx3uR3lB4QKmDpCPz8WrAVOCY/HZCJO0D7A88BOwHzAUOjohbc/tkYP+IuDMfjwbWjYjv5+PPA6cBnwamAIdFxITFuSFJOwInAWsAE4EfR8QzhXjOA34ArA5cn9vfzu3bA78GBgNPAwdFxJOSdgMuLFymB/Bg+dsol5AdgKvzGymRdALwqqR1IuKFJXnhSQsWMOLxx5fkJayKic3NDG1qanQYZmZmZmZm1ol094quy4DdJS0raUOgN/BwWZ8XgC2BlYHjgcskrV5o3xyYBPQHTgEulKRaF5a0BnAzKbHUD/gpcK2kVdt6M5LWJ1U7HQ6sCtwC/EnS8oVuewLfANYB1geOzWM/C1wE/AhYhZQQu1HSChFxZalCChgIvEjtqqp6nSRplqQHJI0o3lb+FI8BipV4rZ3LOpGhTU2MHDCg0WGYmZmZmZlZJ9LdK7peISWptgG+Qqrm+oiIuLpweKWko4DNgBvyuSkRcT6ApIuBc4ABwPQa1/4+cEtE3JKP75D0CLAdcHHbbofdgJsj4o4cz2+Bw4AvAhNyn7MiYmpuHwOcSUp2HQCcFxGlRN/Fko4GPg/ck/svA4wHJkTEeVXiGJuvXbIcqdqtJb8gVZC9A+xOSs4NzRVbt5Ce+7nAc8AvgQB6tWGuugzp1YsJw4bVO8zMzMzMzMzMGqS7V3RBSm7tA+xBqvD6CEl7SZooaa6kuaRKov6FLh8ktCJiQf7amvVWawO7lubNc29BWlLYVgNJSyBL8bxPWm65RqHP1ML3KXlMKZ4jyuIZVGgHGEOqeju0RhyHRkTf0gfYvlrniHg4IuZFxMKIuBh4gJTwIyLuAo4Drs3xTgbmkZKUdc1lZmZmZmZmZl2bE10pgfIt4MWImFJskLQ2cD5wCLBKTtr8k48upatmPh+tPPpk4ftU4NJiQigiVoqIk9t6I8A0UsKqFL9IyapXC30GFb6vlceU4hlTFk+viLgiz7U7KRm4S0S8uxgxtkZQeMYRcXZErBcRq5F+r+VIv0Pdc5mZmZmZmZlZ19XtE10RMR/4KmlT+XIrkRIlMwEk7Uv1vaHKTSTtAdZD0nBgl0LbZcAOkr6R9wjrKWmEpDVbOfcyeUzpswJwFfAtSVtL6gEcASwE/loY91+S1pTUDzgauDKfPx84SNLmSlaS9C1JvSUNIy1x3DkiZtZx/zVJ6pufQU9Jy0naE/gycHtu7ylp4xzTWsD/AWdExOv1zmVmZmZmZmZmXVu3T3QBRMQjlfZwioingVOBB4EZwGdIS+FaaxRp0/fXSRvZjy/MPRXYiZRsmkmqqPoZrf9N9gDeKnxeiIhJpL2/zgRmkd5YuENEvFMYNx74M2lD+RdJm+ETEY+Q9uk6K8f7PGlJJznOTwD3S2rOn1tb+xBq6JFjmJlj/n+khNqk3N4zx9wM/I30W4wqDZZ0dCGWWnOZmZmZmZmZWRemiGh0DEucpLdJlU1jI2JUrf5dlaTJwP4RcWejY2kESesBfweWBw6OiHHV+g8fPjweeeSRpRGamXUTIx5/HKDDvOiio8VjH9ddfqPOfJ+dOXYzM7POStKjETG8Ulu3eOtiRPRsdAzWeBHxHNC30XGYmZmZmZmZ2ZLhpYtmZmZmZmZmZtYlONEFSApJ8yWNaXQsS1JEDO6uyxYBJG2T9xd7X9I2jY7HzMzMzMzMzNqXE10f2jQijgGQNDgnv24udpB0maTRi3shSaMlXbYY48dJ+vXixrEkSJpcnkSStI+k+6uM+YukmZLelPSEpJ0KbV+R9A9JcyXNlnSdpDVaEcdW+Tf84DlFxJ0R0QS83MbbMzMzMzMzM7MOzImu6j4v6UuNDqIbOAxYPSL6AAcCl0laPbc9DXwjIvoCA4HngP+tNpmkHsAZwMNLLmQzMzMzMzMz62ic6KruFKBi5ZSkT0i6KVcivZ6/r1loHyjpRklzJD0v6YB8/pvA0cBueRndE9X610vSAXn8nDzfwEJbSDpU0ouSZkn6H0nLFNp/KOmZfD+3S1o7n/95jrX0eVfSuLbEV0lEPBkR75UOgR7AoNw2IyKmFbovAtatMeURwJ+BZ9srRjMzMzMzMzPr+LrFWxcXw9nAoZK2qbC31TLA74HvAcsCFwFnATvn9iuAp0hVSBsAd0h6MSJuk3QisG5EfL8wX0v972ptsJK+CpwEfD3P9VvgD8CXC92+DQwHmoA7gUnABZJ2JiXgdiBVTR2ZY/piRJxCSvohaRCpUuqq1sbVythvArYBVgBuBx4ptK0FPAn0ISW6WkwC5uTcD4HPkn6PNpu0YMEHrww366xGDhjAgQMH1u5oZmZmZmbWBbiiq7q3gTFUqOqKiNkRcW1ELIiIebnfVvBBMmgL4BcR8XZETAQuAH5Q6SL19q9iT+CiiHgsIhYCRwFfkDS40Oc3ETEnIl4GTgf2yOd/BJwUEc/k6qoTgaGlqq4c54rA9cAZEXFLlTiuz3tqzZU0FzinVuARsT3QG9gOuD0i3i+0vZyXLvYHjqV6pdZYYFRENNe6pllXN7G5mfEzZjQ6DDMzMzMzs6XGFV21nQ/8TNIOxZOSegG/A74JfCKf7i1pWVJV1pycACuZQqqkqqTe/i0ZCDxWOoiIZkmzgTWAyfn01LJrlEo91gbOkHRqoV157JR8fCEwKSJ+UyOOnYsVcJL2AfavFXxEvAvcKukwSS9ExI1l7XMkXQw8IWmNwnLH0nV2AHpHxJW1rtUaQ3r1YsKwYe0xlVlDuCLRzMzMzMy6Gye6aoiIdyUdD5xAWg5YcgQwBNg8IqZLGgo8TkoOTQP6SepdSF6tBbxamrbsMrX6t9Y0UsIKAEkrAauUzTOocB9r5TGQEmBjIuLyShNLOpJ0v1vUGVNbLAesU6VtNdIyxjllbVsDwyVNz8crA4skfSYidsLMzMzMzMzMujQvXWydS0l7R32zcK438BYwV1I/4LhSQ0RMBf4KnCSpp6RNgP2AUhJpBjC4tBF8K/pXsmzuW/osD4wH9pU0VNIKpOWHD0fE5MK4n+WN9AeR3nZYqn46FzhK0kYAklaWtGv+vi1wKKlS661WP7VWkLSBpG0lrSiph6Tvk/YUuye3f0fSEEnLSFoVOA14PCLKk1wAo4D1gaH5cyOpIm/f9ozZzMzMzMzMzDomJ7paISIWkRJZ/QqnTwdWBGYBDwG3lQ3bAxhMqpi6DjguIu7IbVfnv7MlPdaK/pUcSUq0lT53543rRwHXAq+RqqJ2Lxt3A/AoMBG4mbQckYi4DvgN8AdJbwL/BLbNY3YDVgWeKbx58dwqsdVDwGjg38BMUvJtt4goPZc1SM92HvAP4H3ShvppsHRuKZaImBcR00sf0nOZ30JSzMzMzMzMzMy6GC9dTBYCj0oaGxGjcgWUih0i4ioKbxqMiGnAiLJ5ziu0vwJsX+liETGbsiWA1fpXGL8PsE8LbeeSqrNacktEjG1h7KWk6rVWX69C38EVzo0DxrXQ/xlg8yrznQmcWaX9oCpt+xSPJW1NSgKuQHp7o5mZmZmZmZl1IU50ARHRs9Ex2JKXK976NjoOs6VpYnOzN6XvQCY2NzO0qanRYZiZmZmZdVleumhmZraUDG1qYuSAAY0Ow8zMzMysy3JFVzcSEardy8y6kqFNTUwYNqzRYZiZmZmZmS0VXaqiS1JImi9pTKNj6Uwk7SPp/kbHsaRJWj9vpL9I0v6NjsfMzMzMzMzM2leXSnRlm0bEMaUDSftJelbSPEkzJN0sqffSCETShJx827Ts/PX5/IhWzCFJh0r6Z07ivSLpakmfaWNMg/O1l0g1X77n/cvOjZD0Sgv9V5B0oaQp+Td6XNK2hfY9C296bJa0IMf/n/XOFRH/iogm4L52vGUzMzMzMzMz6yC6YqLrA5K2Ak4E9oiI3sCGFN6cWOdcbU0M/QvYqzDPKsDngZmtHH8GcBhwKNAPWB+4HvhWvYEsqeTWYloOmApsBawMjAKukjQYICIuj4im0gc4GHgReKzeuczMzMzMzMysa+vSiS7gc8CDEfE4QETMiYiLI2IegKRv5aqfNyVNlTS6NLBQ+bSfpJeBu/P5qyVNl/SGpHslbVQjhsuB3SQtm4/3AK4D3ilca1lJR0t6IVciPSppkKT1gP8iJerujoiFEbEgJ39ObuM93Jub5+YKqS8U+v9W0uuSXipVQknaVdKjxRuSdISk61vzA9QSEfMjYnRETI6I9yPiJuAl4GMVW9newCUREe0wl5mZmZmZmZl1IR2xwqc9PQycIOl44M/AIxGxsNA+n1Rt9RSwMXCHpIkRUUzibEWqBHs/H98K/JCUqPoNKZE1tEoM04Cnga/nsXuRKrR2KPT5CSkBth2pAmwTYAGpauuViPhblfnrvYcBpORP34h4D0DSEGBz4GKgP3AgcKGkNYAbgfMkbRgRz+T5vg/8ukpMbSZpAKlq7akKbWsDXyY9/8WaqzUmLVjAiMcfb8tQsw5hYnMzQ5uaGh2GdXATm5sb+t+6kQMGcODAgQ27vpmZmZl1LV26oisi7gO+A3wWuBmYLem0UnVVREyIiH/k6p8ngStISaGi0blS6K085qKImJcTZqOBTSWtXCOUS4C9ckKpb0Q8WNa+P3BsREyKwo3YDAAAIABJREFU5ImImA2sArxW4x7rvocWTImI8yNiESnhtTowIN/nlaTkFrmCbTBwU5W5xkqaW/rU6PsBST1IicOLI+LZCl32Au6LiJfaYS6zLm9oUxMjBwxodBhmLZrY3Mz4GTMaHYaZmZmZdSFdvaKLiLgVuFXSMsBXgKuBSaQqpc2Bk0mVUMsDK+T2oqmlLzlBNgbYFViVD6u8+gNvVAnjj8CpwGzg0grtg4AXKpyfTUo4tajee6hieulLRCyQBFAqBbkYuELSscAPgKvKKuPKHRoRFxRiHAFcVuM+liE9m3eAQ1rothdpz7WqWjlXTUN69WLCsGFtHW5m1ikMbWpq2H/rXDVrZmZmZu2tS1d0FeWKp7tI+1RtnE+PJy3NGxQRKwPnAiofWvg+EtgJ2Ia02fngfL58TPm1F5CWLf6YyomuqcA6Fc7fBawpaXiV6eu9h4/tbVVLRDxEShptSXoGle6hzZSyaheSllV+NyLerdDnS8BA4JrFncvMzMzMzMzMuqYuneiStJOk3SV9QslmpGV9D+UuvYE5EfF2bhtZY8rewEJSpVUvWlFdVHA0sFVETK7QdgFpL7H1cpybSFolIp4DziFVU42QtLyknvmejmzjPcwkVaJ9qo7YIS2/PAt4LyLur3NsLf9L2kNshyrLK/cGri29SGAx5zIzMzMzMzOzLqhLJ7qA14EDgOeAN0nL5/4nIi7P7QcDv5I0D/glcFWN+S4BpgCvkjaYf6h69w9FxLQqCaLT8rX/nOO8EFgxtx1KSjCdDcwlLXH8NvCnttxDri4bAzyQ99D6fCtv4VJSJVx7V3OtDfyItKH/9PwmyGZJexb69AS+R1pCWT7+aEm3tnYuMzMzMzMzM+u6utoeXQuBRyWNjYhREXEvsHVLnSPiGlpYCpcrr1R2rpm0dLHokirzj6jStmbh+yLSWww/9ibDiAjgjPypNE9d95DP/5KUFCt5CBhX1qd83EzSGx6r7rVV6Z4jYgKw5sc6p7YplWIs6/M20LeFthML36vOJWk94O+kvczGVbummZmZmZmZmXU+XSrRFRE9Gx1DF/Zj4O95OWWnlGOvmDAzMzMzMzMzs86vSyW6bMmQNJlUKbVzg0MxMzMzMzMzM2uRE11WU0QMbnQMZmZmZmZmZma1dPXN6M3MzMzMzMzMrJtwoqsGSSFpvqQxdYx5StKIJRhWQ0maIGn/RsfRFpJekPSOpKqb6puZmZmZmZlZ5+NEV+tsGhHHAEganJNfzfkzWdKRxc4RsVF+02DdCom1ZkmzJd0labd2uIelQtLoSkmkfF/rtjDmcEkvSnpT0jRJv5O0XKF9sKS/SFog6VlJ21S5/q2F36Y5J7X+UWqPiHWAE1sab2ZmZmZmZmadl/foaru+EfGepOHAPZIejYg72mnuTSPieUn9gW2BsyRtEBHH1zuRpOUi4r12imtJ+RMwLiLmSuoHXAMcCpyW268AHgS2y59rJK0XETPLJ4qIbYvHkiYAd7clqEkLFjDi8cfbMtQ6iJEDBnDgwIGNDsPMzMzMzMyWEld0LaaIeAR4ChhaOpervLbJ30dLukrSJZLm5WWNw1s596yIuBT4MXCUpFXK5y9c47L8vVRxtp+kl8lJHklXS5ou6Q1J90raqDB+nKSzJd2cY3xY0jqF9q/lSqo3JJ1FegNju4mIFyJibulywPvAuvna6wOfBY6LiLci4lrgH8B3a80raTCwJXBpe8ZrncPE5mbGz5jR6DDMzMzMzMxsKXJF12KS9HlgY+CkKt12BL4D7Av8GjgL+Hwdl7mB9FttBtzayjFbARuSkkbkcT8E3gF+A1xOITkH7AF8E3gMuBgYA+yeq8quzWNvAA4BDqKdk0eSRgLnAr2BWcARuWkj4MWImFfo/kQ+X8tewH0R8VJbYhrSqxcThg1ry1DrAFyNZ2ZmZmZm1v24oqvtZkl6i7Sk7hzg+ip974+IWyJiESlBtGk9F4qId0nJn351DBsdEfMj4q08x0URMS8iFgKjgU0lrVzo/8eI+Fte5lhMgm0HPB0R1+Q4Tgem17j29yTNLX5acY/jI6IPsD4p4VUqxWkC3ijr/gYpIVbLXsC4VvQzMzMzMzMzsy7Aia62609KwvwUGAH0qNK3mBhaAPQsbrZei6QewKrAnDrim1oYv6ykk/MbB98EJuem/lVibMrfBxbniogoHrfgqojoW/y0NuiIeI60FPScfKoZ6FPWrQ8wjyokbQF8krTfl5mZmZmZmZl1A050LYaIWBQRpwJvAwcvwUvtBLwH/C0fzwd6Fdo/WSm8wveReY5tgJWBwfl8a/baeg0YVDqQpOLxErIcUNoj7CngU5KKFVyb5vPV7E2qUmteAvGZmZmZmZmZWQfkRFf7OBn4uaSe7TmppH6S9gTOBn4TEbNz00TS/lk98sb2u9SYqjewEJhNSpCdWEcYNwMbSfpOrkI7lMqJtTaTtL+k1fL3TwNHAXcBRMS/SPd7nKSekr4NbELaN6yl+VYEdsXLFs3MzMzMzMy6FW9G3z5uBl4HDgDObIf5npAUpI3jnwD+OyLGF9pHAVfka94DjKf6/l2XAN8AXiUtfxxFepNjTRExS9KuwFjg96Q9xh6o625q+xIwRlITMBO4OsdYsjspafU68DKwS0TMBJC0JXBrRDQV+u9M2sfrL+0cp3UyE5ubvSl9A40cMIADBw5sdBhmZmZmZtaNONFV20LgUUljI2JUREymbMlf3rdqo8Lx4ML30WV9Pza+rL3mcsKIeBHYvIW2SvE1k5YuFl1SaN+nrP8EYM3C8W2kTeJrKr/fwvlq97xvjTknk/ZBq9R2Hx/uJ1Y6dwUpEfgxkiYBawBXVbummS2eic1p1bATXWZmZmZmtjQ50VVDRLTrckRrrIgY0ugYbOkZ2tTEhGHDGh1Gt+RKOjMzMzMzawTv0WVmZmZmZmZmZl1CQxJdkkLSfElj6hgzQdL+dfRfS1KzpGXbEN+5kkbV7mmdjaTj87+9yJvrm5mZmZmZmVkX0ciKrk0j4pjSgaTlJY2W9FxOREyWdJGkwW2ZPCJejoimiFhUrZ+kfSTdXzb2oIg4oS3XrUVSH0mnS3o5J+Kez8f9l8T1ljZJgyslkSSNk/TrFsZ8WtIjkl7Pnzvz2xeLfT4r6d78zGZIOqxKDFtLelbSAkl/kbR2qS0ijqOwn5qZmZmZmZmZdR0daeniNcCOwEhgZWBT4FFg63on6qiVOpKWB+4iJVq+CfQBvgjMBjZrw3wfu8+2VLB1ANOAXUhvjuwP3Aj8odSYk4C3AecBqwDrAn+uNFHu+0fSWxv7AY8AVy7B2M3MzMzMzMysg+gQCSFJ2wBfA9aPiKn59BvA2WVd15b0ALAJ8CAwMiJm5aqvl4D9geOAyZL2yud6RMR7kvYBfgmsCswCjgUeA84FekhqBt6LiL6SxgGvRMSxkj4BXEp6y+FywAPAQRHxSo59AnAf8NXyuCrc6l7AWsBX8psQAf4NfFA9JulI4ABgNWAqcExEXJfb9sltfwP2Bs6RtCbwFrA2sBWwk6QVgF8D6+TneGHpbYiSegIXANsCywLPAdtHxAxJ/YBTgW8AKwL3RMTOedwBwC9IyaP78zOYVuEe6xYRc4G5+ToCFpGSWSU/AW6PiMvz8ULgmRam+w7wVERcnecbDcyStEFEPFtPXJMWLPCG2p3YxOZmhjY11e5oZmZmZmZmXUZHqejaBvhbIcnVkpHAvqQk0PLAT8vatwI2JCVqPiBpJWAssG1E9CZVUU2MiGeAg4AH8zLHvhWuuQzwe1IiaS1SUumsOuMq3udthSRXJS8AW5Kq2o4HLpO0eqF9c+DFfK3SHmcj8/fepCTUfFJSrS/wLeDHknbOfffOcw8iVUcdlO8JUkKvF6nibDXgdwCSvgqcBHwPWB2YQqHiqr1Imgu8DZwJnFho+jwwR9JfJf1b0p8krdXCNBsBT5QOImI+6Zl6uWI3M7SpiZEDBjQ6DDMzMzMzM1uKOkRFFynh8lor+v0+Iv4FIOkq0lLHotE5sUEqDPqI94GNJb0cEa+18npExGzg2tJx3kD/L3XGVbIKaTlmtetdXTi8UtJRpGWNN+Rz0yLizPz9vXyfN0TEA/nc28CEwhxPSrqClAS8Hng3x7FuRDxZiicn07YFVomI1/PYe/LfPYGLIuKx3Pco4HVJgyNicgu3MqvsN+gFnFLj3vvmpOTepGRayZrAZ0lVf//I81wBfKnCNE3AzLJzb5CSgHUZ0qsXE4YNq3eYmZmZmZmZmTVIR6nomk2qFKpleuH7AlJSo6hiRVhOfu1Gql56TdLNkjZoTWCSekk6T9IUSW8C9wJ9y/bCqhVXSc37lLSXpImS5uYKp41J+1aVVLrHj5yTtHnehH2mpDdI912a41LgduAPkqZJOkVSD1KF15xCkqtoIIXEU65Imw2sUeVW+kdE39IHGF/tvgtzzyctJ71E0mr59FvAdRHx94h4m1Tp9kVJK1eYopm091lRH2Bea65vZmZmZmZmZp1XR0l03QlslvebWhzRYkPE7RHxNVKi6Vng/FpjsiOAIcDmEdEH+HI+/7GSsVa4E/hGrlr6mPx2wPOBQ0iVVX2Bf5Zdq1K85efGkzZ0HxQRK5MSRwKIiHcj4viI+DRpCef2pGWOU4F+kiot35xGWrpZinMlUlXYq9Vvt82WIVWAlRJpT/LReyx9r/QbPEV6kUHqkGJdJ583MzMzMzMzsy6sQyS6IuJO4A7gOkn/KWk5Sb0lHSTph4s7v6QBknbMSY+FpKqfRbl5BrBmfiNiJb1JFUVz82btxy1GKJeSEkrXStpA0jKSVpF0tKTtgJVISZyZOe59SRVd9epNqs56W9JmpD28yHN+RdJnckXam6SljIvycs5bSRvcf0JSD0mlpN54YF9JQ/NG9ycCD1dZtlgXSV+TNEzSspL6AKcBr/PhhvO/B76dr9+D9EbF+/Mm9uWuIy1R/W7eeP+XwJP1bkRvZmZmZmZmZp1Ph0h0ZbsAtwBXkvZU+icwnFQFtbiWIVVmTQPmkParOji33U2q9pkuqdKbEk8nvYFwFvAQcFtbg4iIhaQN6Z8lJfbeJL1BsT8pcfQ06a2HD5IScJ8hveWxXgcDv5I0j5TouarQ9kngmnztZ0j7cF2W235ASnw9S3ob5OE57rtIyaVrSXubrQPs3oa4WtKXtOfWG6SN49cFvpmXKRIRdwNHAzfnuNblo8m7pyTtmfvOBL5L2pz/ddLm/e0Zq5mZmZmZmZl1UIqotXJvCVxUeptUWTU2IkYt9QCs25J0HPATYAVgpYhY1FLf4cOHxyOPPLLUYjPrSkY8/jiAX+jQwTX6d2r09TuD7vKMOvN9dubYzczMOitJj0bE8EptDXnrYkT0bMR1zSLieNJm9mZmZmZmZmbWxXSkpYtmZmZmZmZmZmZt1qUTXZJC0nxJY9ow9ilJI1p5jXXbFGD1eUdLuqx2T6uHpBckveNna2ZmZmZmZtb1dOlEV7ZpRBwDIGlwTkw9VuwgqX9OfkwunYuIjSJiwtINtXUkjZD0SqPjqKSlBF21hKCkwyW9KOlNSdMk/U7ScmV9DpP0Uk5cPiNp/bbMFRHrkN4aaWZmZmZmZmZdTEP26OoAVpK0cUT8Mx+PBF4ibVBuS9+fgHERMVdSP9JbIQ8FTgOQtD+wH/At0psiP0V6o2Ldc5nZ0jOxufmDTZqtY5rY3MzQpqZGh2FmZmZm1m66Q0VXJZcCexeO9wIuKXaQNFnSNvn7spKOzsve5kl6VNKgQvdtJD0n6XVJZ0tSHreOpLslzZY0S9LlkvoWrjFQ0rWSZuZqpUMX98YkbShpgqS5efnljoW2cZLOlXRHvo97JK1daN8gt82RNEnS9wpxNhc+CyS12+s6I+KFiJhbCgN4H1g3X3sZ4DjgvyPi6UheiIg59c5lZmYfNbSpiZEDBjQ6DDMzMzOzdtNdK7ouA+6TdCSwPtAbeBg4oIX+PwH2ALYD/gVsAiwotG8PfA7oAzxKqiq6jZRoOQm4N7ddC4wGDs8JnD8BN+S51wTulDQpIm5vy01J6pHnvAj4OrAFcIOk4RExKXfbk1QZ9TBwCnA5sIWklYA7gF8C2+Z7/LOkpyLiKaCpcJ3LaeckqaSRwLmk32IWcERuWjN/NpY0DniPlJQ8PiLer3OuukxasMDVKO1o5IABHDhwYKPDsKVoaFMTE4YNa3QYZmZmZmbWjXTXiq5XgEnANqTKrkuqd2d/4NiImJQrip6IiNmF9pMjYm5EvAz8BRgKEBHPR8QdEbEwImaSls9tlcd8Dlg1In4VEe9ExIvA+cDui3FfnyclpE7Oc94N3ERKpJXcHBH3RsRC4BjgC7k6bXtgckT8PiLei4jHSIm5XYoXkPQLYAPgh1Xi+F6uKPvgUyvwiBgfEX1IicdzgRm5ac389+vAZ4Cv5PvZrw1zWYNMbG5m/Az/DGZmZmZmZrZkddeKLkjJrX2ALwJfBtar0ncQ8EKV9umF7wvI1U+SVgPGAluSqouW4cO9pdYGBpYlgZYF7mv1HXzcQGBqWaXTFGCNwvHU0peIaJY0J49bG9i8LJ7lSMs8yfezLXAYsHlEvFUljqsi4vvFE61d6hgRz0l6CjgH+A5Qus4peUniXEnnkarrzq9zrroM6dXL1SjtxJVxZmZmZmZmtjR014ouSNVK3wJejIgpNfpOBdZpwzVOAgLYJFcYfZ+0nLE050sR0bfw6R0R27XhOiXTgEF5WWTJWsCrheMP9haT1AT0y+OmAveUxdMUET/OfYcAFwPfi4ipLFnL8eHzngS8Q3qOizuXmZmZmZmZmXVh3TbRFRHzga+SliXWcgFwgqT1lGwiaZVWjOsNNJOqkNYAflZo+xvwpqRfSFoxb3i/saTPtfYeJPUsfvKc84GfS+ohaQSwA/CHwrDtJG0haXngBODhnLi6CVhf0g/y2B6SPpc3t+9D2kvs2Ii4v7Xx1XEf++fqNyR9GjgKuAsgIhYAV+Z76i1pTdJeajfVO5eZmZmZmZmZdW3dNtEFEBGPRES1JYklpwFXAX8G3gQuBFZsxbjjgc8CbwA3A38sXHsRKQk1FHiJtGn6BcDKrQx/DdKyvuJnELAjaTP5WaQle3tFxLOFceNJbzGcA/wnaXN6ImIeaR+s3UkVXtOB3wAr5HsYApxWfPtiK+NsjS8B/5A0H7glf44utB9CShhOAx7M93ARgKQty2KpNZeZmZmZmZmZdVFdfY+uhcCjksZGxKiImMyHSwc/IiLuBAYXjovfFwG/zp/ycSo73qfw/SlSMqno1EL7ND66UXxxntEV7yi1TaCF+8i2qtI2KyIOamHeSaTlnJVUu15xjtEtnG9xfETsW2PON2lhk/6IuI/CGyFrzSVpEilJeFW1fmZmZmZmZmbW+XTpRFdE9Gx0DNaxRMSQRsfQXU1sbv5gU/qRAwZw4MCBDY7IzMzMzMzMuppuvXTRzJa+ic3NjJ8xo9FhmJmZmZmZWRfUpSu67KOKyyrNlrahTU1MGDbsg6ouMzMzMzMzs/bWaSu6JIWk+ZLGLOHrDM7XclKwk5O0Td5I/31J2zQ6HjMzMzMzMzNrX5020ZVtGhHHFE9IWiknM25pVFAtUXKopH/mJN0rkq6W9JlGx9ZeJE0uTyJJ2kfS/a0Yu1VOKn5s0//c/vvcvm6VOQZL+oukBZKeLcYSEXdGRBPwch23ZGZmZmZmZmadRGdPdFWyC+lti1+XtHqjgylzBnAYcCjQD1gfuJ6W33TYokoVZp256kxSD9LzebiF9i2AdVox1RXA48AqwDHANZJWba84zczMzMzMzKzj6oqJrr2Bc4EngT0BJO0q6dFiJ0lHSLo+f/+WpMclvSlpqqTRLU0u6bu5amljSetIulvSbEmzJF0uqW8L49YD/gvYIyLujoiFEbEgIi6PiJNrxVFYQrmfpJeBu3Ol1AOSfidpDjC6VkySfiHpVUnzJE2StHU+v6ykoyW9kNselTQot31R0t8lvZH/frHuX6W2I4A/A89WeHbLAWcCh1SbQNL6wGeB4yLirYi4FvgH8N32D9fMzMzMzMzMOppOWwFUiaS1gBGkhMgcUtLrt8CNwHmSNoyIZ3L37wOlJXLzgb2Ap4CNgTskTYyI68vm35dUJbRNRDyfl9CdBNwL9AGuBUYDh1cIb2vglYj4W5VbaE0cWwEbAu8DuwGbA38AVgN6AGu0FJOkIfnZfC4ipkkaDCyb5/0JsAewHfAvYBNggaR+wM2kKrQrgF2BmyWtGxGzq9xLq0laG/ghKUl1VoUu/w3cGxFPSqo21UbAixExr3DuiXy+bpMWLPDG6e1kYnMzQ5uaGh2GmZmZmZmZdXFdKtFFShI9GRFPS5oLnCJpWEQ8LulKUnLrGEkbAYOBmwAiYkJhjiclXUFKKBUTTIeTkjEjIuKVPO554PncPlPSacBxLcS2CvBateBbGcfoiJgPkJM+0yLizNz2Xo6npZgWASsAn5Y0MyImF+bdH/h5REzKx0/ka/wAeC4iLs3nr5B0KLADMK6FW7le0nuF4+WBx6rc+lhgVEQ0lyeyclXZj4D/rDK+pAl4o+zcG6TknzXQ0KYmRg4Y0OgwzMw6pYnNzV3+f7z4f4iYmZlZe+mKia7zAXLF0j2kqq7HgYtJSZpjgR8AV0XEQgBJmwMnk6qoliclg64um/tnwK9KSa48bjVSkmZLoDdpKejrLcQ2G6i6Z1gr45ha7bhaTLkK7XBShddGkm4HfhIR04BBwAsVwhoITCk7N4XqyaOdI+LOQkz7kBJpHyNpB6B3RFzZwlynk557eQKrkmZSFVtRH2Behb41DenViwnDhrVlqJmZmdXB/0PEzMzM2kuXSXTlfaPWA46SdEQ+3ZuU0PlpRDwk6R1SAmhk/pSMJy2Z2zYi3pZ0OtC/7BJfB26TND3v/QRpiWAAm0TEbEk7U3npHcBdwNmShkfEIy30aU0cUeO4akwRMR4YL6kPcB7wG1Libypps/d/ls03DVi77NxawG0t3EO9tgaGS5qej1cGFkn6TETslNu3kHRKYcyDkg7L91L0FPApSb0Lyxc3JT1X60C6Q3VCd+fqDLP2M7Spyf/jxczMzKyVutJm9HsDdwCfBobmz8ZAL2Db3OcSUtLnvYi4vzC2NzAnJ5c246NJsJKngG+SklU7FsY1A3MlrUGq+qooIp4DziFVlY2QtLyknpJ2l3RkHXHU0mJMkoZI+qqkFYC3gbdIyxkBLgBOkLSekk0krQLcAqwvaaSk5STtRnrGN7UhtkpGkd4+WfrNbiRV5e2b29cnJatK7ZCWTV5XPlFE/AuYCByXn+23SXuNXVve18yWLFdnmJmZmZlZI3SJii5JPYHvAXtFxPSytktJSbA/AZcCJ+RP0cHAqZLOAu4BrgI+9vbEiHhC0vakzdjfBY4nJc/eIO2LdSlp4/SWHJo/ZwP/QVpSeD/wq3riqKFaTCuQlkZuCLwL/BU4MLedltv/TKoiexb4dkS8ku/5DOB/85zbR8SsOuOqKFdefbC0UNJbwPyImJPb/13sn/fwmhURb+Xjc3O/g3KX3Ul7h70OvAzsEhEz2yNWaz+uTjAzMzMzM7MlQRHlK986B0lvAwuBsRExqpVjVgT+DXw2V1hZNyJpa1J11wrAdhHxl2r9hw8fHo880tIqU2ur0pJFJ7rMzP89qM3PqOPzb2RmZrb0SXo0IoZXauu0FV0R0bMNw34M/N1Jru4pIu6i/go5MzMzMzMzM+skOm2iq16SJgMCdm5wKGZmZmZmZmZmtgR0m0RXRAxudAxmZmZmZmZmZrbkdKW3LpqZmZmZmZmZWTfWLRNdkkLSfEljGh2LLV2S9pPUnP8NrNvoeMzMzMzMzMys/XTLRFe2aUQcAyBpcE58NJd9dmvvi0paXtJoSc/lZNtkSRf9f/buNMyuqkz7+P9mjKECYdBIGFUGFZQgAWwVTQuooAhOKBEhKNrKCw5tI7OCzeAIiogDMgoooCAqxAExCjQggUQUJCpDDIRAGEJSCQES7vfDWoWHk3NqgKQqqbp/13Uuz9lrevau9Id+eNbakjZd2msNlFZJpHrP5/di7P51/IEN1yZIWtz0txnXzRxjJN0saUH93zFdbbbPtN3xHG8tIiIiIiIiIpZjQ+aMrl4aaXvRMl7jJ8CGwHhgCrAGsC+wM3BmXyaStEpzvK2urSgkrQ0cAdzWovl622/oxRyrAZcD3wBOB/4LuFzS5raf7Es80xYseOaV4bH0TO3sZExHco0RERERERGx9A3liq5ekfRaSbMkrdxw7V2Sbq3fd5B0vaQ5ku6XdFpNtrSaaxdgV2BP2zfZXmT7Mdvftn1m7XOApL9JmifpLkn/1TB+nKR7JR0maRZwdq2U+omk8yXNBSZ0F5OKUyQ9KOkxSbdK2rq2vUDS1yVNr23XSnpBbXunpNvqnJMkvWIZPO6TgFOBh57HHOMoCdxv2H7C9qmUt22++fmHF0vDmI4Oxo8aNdBhRERERERExCCUiq4e2L5B0nxKouS39fJ44ML6fTHwGWAypVJrInAQpaKo2S7An2zP6GbJB4F3AHcBbwQmSrrJ9i21/cXAOsAmlETlYcCewPuA/YDVgVd2E9Nb6rxbAI8BLwfm1Lm/BmwFvA6YBewIPC1pC+BHwF7ApDr3LyS9sq9VUu1I2gEYW+Pcu0WXbSU9BDwC/BA4qU3l2lbArbbdcO3Wev1XfYlpy+HDmbTttn0ZEhEREREREREDKBVdz/ZQrVjq+nRVLf0I2AdA0ghg93oN2zfbvqFWZ90DfA94U5v51wXu7y4A21fYvtPFH4DfADs1dHka+EKtVnq8Xrve9s9sP2378R5iegoYQUlwyfbfbN8vaSXgw8CnbN9ne7Ht/7P9BPB+4Arbv7X9FCUh9gJKQqydWxqfJXB4u461Wu504BDbT7fo8kdga+BFwHsof4tD20x/874mAAAgAElEQVTXQUngNXqs3nNEREREREREDGJJdD3berZHNnz+Vq9fCLxb0urAu4FbbE8HkLSFpF/W7Y1zgROB9drM/zCwfncBSNpN0g2SHqkJot2b5ptte2HTsGdViHUXk+2rgdOAbwMPSPq+pDVr+zDgzhZhjQamd/2oyagZwAbd3MprGp8l8KVu+h5EqcK6vlWj7bts310TeX8Bvgi8t81cncCaTdfWBOZ1s35EREREREREDAJJdPWC7dspiZ7dePa2RYDvAHcAm9teEziSciZUK1cBO0jasFVjTaT9lFIxNaomiK5sms8thjZf6zYm26fa3o6ynW8LSnXUQ8BC4GUt5p9J2SrZFaeAjYD72txnX+0MvKsm5mZRKsW+Lum0Nv1N+2d8G/DqGmOXV9P6gPuIiIiIiIiIGESS6Oq9C4FPUs63uqTh+ghgLtAp6eXAJ9pNYPsqyjlfl0naTtIqkkZI+rikDwOrUc7Ymg0skrQb5Uytvmobk6TtJe0oaVVgPiW5tbhWaZ0FnCxptKSVJf1HTb5dDLxd0s513GeBJ4D/ew6xtTIBeAUwpn4mA8cBR9WYd5M0qn5/OXAM5c2KrUyinJv2SUmrSzq4Xr96KcUaEREREREREcupJLqebY6kzobPfze0/YjyRr+rbTe+FfB/KFVe84AzgIt6WOO9lCqtiyhnR/2Vcgj7VbbnUZJpFwOP1nl//hzuo7uY1qzXHqVUqT1MqSDrGvcX4CbKoe9fBlayPQ3YF/gWpfJrD2CPpXUQve05tmd1fYAngbm2u87a2hm4tb4U4ErgUsp2TAAkTZR0ZJ3rScqh+ftRDtn/MLDX0oo1IiIiIiIiIpZfevbL6YYGSQspFUmn2j5moOOJ/iPpAOAUynlkr7R9V7u+Y8eO9eTJk/sttoiIoWbclCkAecNtN/KMln/5G0VERPQ/STfbHtuqbZX+DmZ5YHvYQMcQA8P22cDZAx1HRERERERERCx92boYERERERERERGDwqBJdEmypPmSTnie82xa5+r3arfns7akeyTtspTjmSDp2m7aJ0raf2muuaxJ+kg9f82SNhvoeCIiIiIiIiJi6Rk0ia5qG9tdb+obyITVxk2H2ncl4bp+79TfMS0LtnezfW6rNkkjJZ0laZakeZL+LumwnuaUtH99Xge2ab+6p7+rpDGSbpa0oP7vmIaYz7Td0Zv7i4iIiIiIiIgVy2BLdC0XbP/LdkfXp17epuHaNQMaYP84BegAXgGsBbwTuLO7AZLWBo4AbmvT/kF6OFdO0mrA5cD5wNrAucDl9XpEREREREREDGJD8jB6SfcAB9q+qv4+FtjM9r4t+r4H+DrwDuBx4AxgG8DAr4H/Z3tOH9Z+O3A88DLgMeBM28e26dvXtcdIOhnYBPgVsL/thTWB9ENgR8rf/Drg47bvretMAD4PvBB4CDja9gUNcXwN+AgwBzjI9sR6fRJwvu0ftAh/+zrPo/X3HfXTnZOAU4G9WzyLtYAvAPsB13czx7h6j99weaXoqZL+B3gz5Zn02rQFC555k1IsXeNHjeJjo0cPdBgRERERERExyKSiqxuSDgC+DOxi+6+AKMmY0ZRKpY2AY/s47XxKsmYk8HbgE5L2Wkpr7w28DXgJ8GpgQr2+EuVNg5sAG1OSZqfVddagJJd2sz0CeB0wtWHOHYFpwHrAV4AzJakX93kDcIKkAyRt3lNnSTsAY4HvtulyIvAdYFYPU20F3FqTXF1urddjOTC1s5MLH3hgoMOIiIiIiIiIQWhIVnT10qeBDwPjuiqfbP8T+Gdtn12rp77Ql0ltT2r4eaukHwFvAn62FNY+1fZMAEm/AMbUsQ8DP+3qVA/s/33DuKeBrSX9y/b9wP0NbdNtn1HHnQucDoyi54TTIcBngIOB70uaDhzSVQ3WSNLKdd5DbD/dnEeTNBZ4PfApYMMe1u2gVMo1egwY0cO4JWw5fDiTtt22r8OiB6mSi4iIiIiIiGUlFV3tHQp8uyvRBCDpRZJ+LOk+SXMp50Ct15dJJe0o6feSZkt6DPh4izme69qNyacFlKQPkoZL+p6k6XXsH4GRkla2PR94f43jfklXSHp5qzltL6hfezzM3fbjtk+0vR2wLnAxcImkdVp0P4hShbXElkRJK1GSYJ+yvaindYFOYM2ma2sC83oxNiIiIiIiIiJWYEM10TUfGN7w+8Ut+rwFOLqek9XlJMr5WK+2vSawL2VLYV9cCPwc2Mj2WpStes1zLO21PwtsCexYx76xXheA7V/b3hVYn3KO1hl9vKdu2Z5L2Xq4BmVbZbOdgXfVNzTOomyf/Lqk0yhJqrHARbXtpjrm3jZvr7wNeHXT9spX0+aA+4iIiIiIiIgYPIZComt1ScMaPitRzqD6gKRV67a497YYdxvlvKtvS3pnvTaCUjE0R9IGlMqrvhoBPFIPid8BGN8Pa4+gnMs1p1ZUPbPlUdIoSe+sZ3U9UddY3NebaibpGEnbS1pN0jDKtsM5lPO+mk2gnDs2pn4mA8cBR1G2HY5uaNu9jtkOuLHFXJNq/J+UtLqkg+v1q5/vPUVERERERETE8m0oJLo6KUmers+bgWMobz18lJJQubDVQNt/przx8AxJu9W+r6EkX64ALn0O8RwEfFHSPMqbDi/uh7W/AbyA8kbFG3j22wdXolR8zQQeoZwXdlAf5m7HlAPwH6pz7wq83XbnEh3tObZndX2AJ4G5th9z0dg2uw57wPaTAJImSjqyzvUksBflwP85lLPO9urqGxERERERERGDl579croVl6SFlIqkU20fM9DxxPKpvs3yFGAY8Erbd7XrO3bsWE+ePLnfYhsqxk2ZwtTOTsZ09HjU2wpr/KhRfGz06IEOI2K51/Vyirz4o708o+Vf/kYRERH9T9LNtse2ahs0b120PWygY4jln+2zKZVmEcvE1M5StJhEV0RERERERP8bNImuiFhxjOnoGLT/5bvrv+xHRERERERE/xsUZ3RJsqT5kk7o47jbJI1bRmHFckbSFpI6JS2WdOBAxxMRERERERERS9egSHRV29g+CkDSpjX51Vk/D0j6paRdGwfY3sr2pP4OVNL6ks6UdL+keZLukHRcffPhoCDpSEl31+d/r6SLuuk7SdLChr/XtIa2V0qaLOnR+rlK0iu7mesVkq6W9Jikf0p6V1eb7b/b7gCuWWo3GhERERERERHLjcGU6GplZE1sbAP8FrhM0oSBDEjSOsD1lLcg/oftEZQ3Eo6kvAmyr/Ot0vRbkgb07yppf+BDwC71+Y8FftfDsINtd9TPlg3XZwLvBdYB1gN+Dvy4zbqrAJcDv6z9PwacL2mL53M/EREREREREbFiGOyJLgBsz7L9TeBY4MtdiSBJ90japX5fSdLhku6U9LCki2tSitq+n6Tpte2YprGrS/qGpJn18w1Jq7cJ57+BecC+tu+p8c2w/Snbt9b5vilphqS5km6WtFNDHMdK+omk8yXNBSbUiqgTJF0HLABeKukASX+rFWN3SfqvhjnWqxVucyQ9IumahmeykaRLJc2u93paw/M5uj6DByWdJ2mtNve4PfBr23c2PP/v9+Vv1sX2HNv3uLweVMBiYLM23V8OjAZOsb3Y9tXAdZSkW0REREREREQMckPtMPpLga8CWwJ/a2r7JLAX8CZgNnAq8G1gn7pV7nTgbcCfgBOBDRrGHgW8FhgDmFJVdDRwTIsYdgEutf10N3HeBHwReAz4FHCJpE1tL6ztewLvA/YDVgf2pSRzdgOmURJCWwLvAO4C3ghMlHST7VuAzwL3Ai+s870WsKSVKdVQV9f5FlOqsQAm1M9/Ag8C5wGn0TqJdANwqqT7gN8DU2wv7uZ+AU6S9KUa/1HNW0olzQE6KMnZz7eZQ22ubd3D2i1NW7AgB4svA1M7OxnT0THQYURERERERMQgNCQquhrMrP+7Tou2/6IkWO61/QSl+uu9dTvce4Ff2L7W9pOURIsbxn4Q+KLtB23PBo6jfRXRusD93QVp+3zbD9teZPvrlGRW43a+623/zPbTth+v186xfVsd85TtK2zf6eIPwG+Arsqwp4D1gU1q32tqxdQOlIqoQ23Pt73Q9rUN93iy7btsdwJHAB9o3jrZFT9wCPBW4A/Ag5IO7+aWDwNeSkkefh/4haRnbeO0PRJYCzgYaJd9uoOShDtU0qqS3kJJXA7vZu3oZ2M6Ohg/atRAhxERERERERGD0FCr6OqqwnqkRdsmlDO8GiutFgOjKMmfGV0XbS+Q9HBDv9HA9Ibf0+u1Vh6mJJnakvRZ4MA6h4E1KedTdZnRYtizrknaDfgCsAUloTkc+Ett/iolkfcbSQDft/0lYCNguu1FLeZvdY+rUJ7Pfc2dbV8AXCBpVUql3AWSptj+dYu+Nzb8PFfSPsDuwLea+s2X9F1gtqRX2H6wqf0pSXvVcYcBk4GLgSda3E+Pthw+nEnbbvtchkZERERERETEABhqFV3volT8TGvRNgPYzfbIhs8w2/dRKrA27Ooo6QWUyqwuMymJsi4b8+/qsWZXAe9qd2B8PY/rMGBvYO1ayfQYz96W5xZDn7lWzwf7KfA1YFSd48quOWzPs/1Z2y8F9gD+W9LO9Rls3KpKq809LgIeaHOf1LWesn0JcCu930LYdR5XK11Juw1aNdq+1fabbK9r+62USrE/9XLdiIiIiIiIiFiBDYlEl6RRkg6mVDgd0eZ8rO8CJ0japI55oaQ9a9tPgD0kvU7SapStiY2JmB8BR9cx61G2Np7fJpyTKRVa5zastYGkkyW9GhhBSSDNBlaR9Pnavy9Wo2x3nA0sqtVdb2l4Hu+QtJlKOddcSuXaYkpC6H7gS5LWkDRM0usb7vEzkl4iqYNyTtlFraq/JE2Q9HZJI+oh9rsBWwE3tug7UtJb61qrSPog5UyxX9f2XSVtK2llSWvW5/coS56x1jXfq+tcwyX9D6V67pw+Pr+IiIiIiIiIWAEN9kTXHEnzKVv2dgfeZ/usNn2/Cfycsp1vHuVA9R0BbN9GOXPqx5RE0DxKZVjXlrjjKdvkbq1r3VKvLcH2I8DrKOdk3VjX+h2lauuflATPRODvlO2BC2m9VbEt2/Moh+tfTEkKja/31mVzSmVZJ3A9cLrtSfXA+D0obzX8F+XA+vfXMWcBPwT+CNxd4zqkTQhzgSPrHHOArwCfaDjvq9GqlGc1G3iozrmX7a6qu5GUJNtjwJ01trd1Hcwv6UhJExvm+xDlb/QgsDOwaz1zLSIiIiIiIiIGOZUzyFdskhZSkk6n2m71psOlvV4HJYGzue27l/V6sXRI2pzyRsvVgINsn9Nd/7Fjx3ry5Mn9EVoMIl1v6sz5bhE9y/+99CzPaPmXv1FERET/k3Sz7bGt2gbFYfS2hy3rNSTtQam8EuXsq78A9yzrdWPpsf0PSoVYxDI1tbPzmf/HZ7AaP2oUHxvd7p0bERERERERA2Owb11cmvakHMg+k7L17wMeDOVwERF9NLWzkwsf6PY9FBEREREREQNiUFR09QfbBwIHDnQcEbH8G9PRMai3sAz2arWIiIiIiFhxpaIrIiIiIiIiIiIGhSGf6JJkSfMlnTDQsSzv6rPabKDjeK4krS6pU9JTklq+FTMiIiIiIiIiVlxDPtFVbWP7qK4fklaTdKykf9Qk2D2SzpK06cCF+ExskyQtlLRRw7VdJN0zgGEtQdJHJN0haZ6kByRdIWlED2PWkTRb0rUN19aTdJ2khyXNkXS9pNf3Yv0l5rL9hO0O4ILndXMRERERERERsVzKGV2t/QTYEBgPTAHWAPYFdgbO7K8gJK1se3GLpvnAMcDH+iuWvpD0JuBE4G22p0haB9ijF0O/DPyNZydgO4EPA/8ATHkpwC8kvcj2oj7O1SfTFizIWUQt5G17ERERERERsbxKRVcTSbsAuwJ72r7J9iLbj9n+tu0za5/Rkn4u6RFJ/5T00Ybxx0q6WNJ5tZrpNkljG9pfUauy5tS2dza0nSPpO5KulDQf+M82YZ4K7NNuG2G7NSS9VtIsSSs39H2XpFvr9x1qxdQcSfdLOk3Sam3WeIOkGZJaxbg9cL3tKQC2H7F9ru15be4HSf8BbA2c3Xjd9kLb02w/DQhYDKwNrNPXueL5y9v2IiIiIiIiYnmWiq4l7QL8yfaMbvr8CLgNGA28HPitpLts/662vxN4N3AAcDxwGvBaSasCvwDOAt4CvAG4XNJY29Pq2PHA7sA7gJZJJuA+4AzgWEql2TN6WOOGmkB7M/DbhvUurN8XA58BJlMq2iYCBwHfaFrjrcAPgPfY/lOL+G4E/lfSccBvgMm2n2hzL9TE27eBjwKvatPnVsqzXhX4ge0Hn+tcvbXl8OGD+s15z0Uq3CIiIiIiImJ5loquJa0L3N+usZ6N9QbgsFptNJWS9PlQQ7drbV9Ztx3+ENimXn8t0AF8yfaTtq8Gfgns0zD2ctvX2X7a9sJu4jwJ2EPSVk3Xe1rjR13f65lZu9dr2L7Z9g21iu0e4HvAm5rmfx/wfWD3NkkubF9DSfS9BrgCeFjSyY2VZE0+Cdxo++Z2N2v71cCalMTcte369WauiIiIiIiIiBickuha0sPA+t20jwYeadqGNx3YoOH3rIbvC4BhklapY2fUbXjtxnZXSfYM27MplWJfbBFfd2tcCLxb0uqUZNQttqcDSNpC0i/r9sa5lHO21mua/9PAxbb/0kN8E23vQdliuCcwATiwuZ+k0ZTk1FHNbS3mXGj7R8DhkrZpbu/LXBEREREREREx+CTRtaSrgB0kbdimfSawTtMbBDembCfsyUxgI0mNz715rPsQ61cp53ht19s1bN9OSXztxrO3LQJ8B7gD2Nz2msCRlHOxGr0P2EvSp3sTYK1M+x1wNeXcrGY7UBKLt0uaBXyT8vxndVMBtirw0qU0V0REREREREQMEkl0NbF9FeX8qsskbSdpFUkjJH1c0ofr2V3/B5wkaZikVwMfAS7oxfQ3Ut6Y+DlJq0oaR3kb4Y+fY6xzgK8Dn+vjGhdSKp/eCFzScH0EMBfolPRy4BMtlp1JefvkJyUd1CouSXtK+oCktVXsQNkCeUOL7hOBTYEx9fN5ypsux9heXA/Qf4Ok1SS9QNJhwKh6n32aq1WsERERERERETF45DD61t5L2f52EaVC6CFK8qtrm+A+wHcpSZ9HgS/Y/m2LeZ7F9pP1DYinA0dQqqz2s33H84j1m8Cn+rjGjyhnfE20/VDD9f+hnL/1OUqC6CLKwfXN9/EvSTsDkyQ9afsHTV0epSTSTgNWp5x59lXbSyQD6yH1z2z1lPQY8JTtrmurU94y+VLgKeAvwNttz6z9PwgcaXurXswVS8HUzs4cSt+NqZ2djOnoGOgwIiIiIiIihqQkuuAJ4GZJp9o+BkqyCPhC/SzB9r2UtyK2aju26fc9NGz/s30bSx7w3tU2oadgbY9r+t0JvKjpWts1avu/aFHNZ/uPlDcbNvp8Q3vjfdwNbNJm/j9Sqr76zPY5wDkNv//Avw/zb9X/AtpU0zXPVc8le4Cy9fErzyW+iJ6M6ehg/KhRAx1GRERERETEkDTkE122hw10DNE/asXXyIGOY0U3pqODSdtuO9BhRERERERERCwhZ3RFRERERERERMSgkERXREREREREREQMCoM+0SXJkuZLOqEPY3aSNO15rrtpXXtQbg+VNE7SvQMdR19JulPSk5LOH+hYIiIiIiIiImLpGvSJrmob20fBsxJQVzR2kHS+pGMBbF9je8sBiLMrlmMlPSVpXv38XdJpktYfqJj6StKekqZKmivpIUm/k7RpD2NWk3RHcwJN0hhJ10h6TNK9kj7fzRyHSvprfW53Szq0sd32y4ATn8etRURERERERMRyalBWG/XSayW93vZ1Ax1IGxfZ3lfSqsAWwHGUt0NuZ/v+vk4maWXbi5d6lK3X2gw4D3g3cDXQAbwFeLqHoYcCD9b+jS4ELgPGAZsC10qaavvnrZYH9gNuBV4G/EbSDNs/7ut9TFuwgHFTpvR12KA2tbOTMR3Nf56IiIiIiIiI5cNQqehq5SvA8a0amrflSdpI0qWSZkt6WNJp9fpKko6WNF3Sg5LOk7RWmznXknSmpPsl3SfpeEkr9xSk7ads3wa8H5gNfLbON0HStU1ruCaZkHSOpO9IulLSfOA/Jb1d0pRaZTWjq4Kt9u+qdNtf0r9qFdZRDe0vqHM+Kul2YPtuwh4D3G37dy7m2f6p7X+1GyDpJcC+wEktmjcFLrC92PadwLXAVm2e11ds32J7ke1pwOXA67uJNfpgTEcH40eNGugwIiIiIiIiIloayhVd3wY+KWkX21e161STUb+kVCZ9CFgMjK3NE+rnPymVSOcBp9V+zc4FHgA2A9aoc84AvtebYG0vlnQ58Nbe9K/GA7sD7wBWA15LqXa6Ddga+G2tjPpZw5g3AFtSqsj+JOlS238DvkCpkHpZjX9iN+veArxc0inAz4GbbHf2EOu3gCOBx1u0fQPYT9IxwEuB/6AkKrslScBO9PIZN9ty+HAmbbvtcxkaEREREREREQNgKFd0LQROoE1VV4MdgNHAobbn215ou6uS6oPAybbvqomcI4APNB9AL2kUsBvw6TrHg8ApwAf6GPNMYJ0+9L/c9nW2n65xT7L9l/r7VuBHwJuaxhxn+3Hbfwb+DGxTr+8NnGD7EdszgFPbLWr7Lso2ww2Ai4GHajVYyz1vkt4FrGL7sjZT/hJ4LyUJdgdwpu2benH/x1L+jZ/di74RERERERERsYIbyokugDOAUZL26KbPRsB024tatI0Gpjf8nk6pkmve27UJsCpwv6Q5kuZQqoxe1Md4NwAe6UP/GY0/JO0o6fd1C+ZjwMeB9ZrGzGr4voB/n5c1umm+xvtegu0bbO9t+4WUqqo3Akc195O0BqU665BW80haB/gV8EVgGOXv8VZJB3W3vqSDKdVrb7f9RHd9IyIiIiIiImJwGNKJLttPUQ55/1/KIeatzAA2bq7SqmZSklhdNgYWUbYoNs/xBLCe7ZH1s6btludMtSJpJWAP4Jp6aT4wvKH9xS2Guen3hZSthBvZXgv4Lu3vu9n9lCRTl417OY5afXUpZbtks80pZ3BdI2lW7be+pFn1LY0vBRbbPq+eu3Uv8GPKlsyWJH0YOBzYufaPiIiIiIiIiCFgSCe6qh8CqwNva9P+J0qS50uS1pA0TFLX4eY/Aj4j6SV1W96JlLclPqv6q74l8TfA1yWtWQ+xf5mk5m2DS5C0qqRX1LVeDJxcm/4MbCVpjKRhlG16PRkBPGJ7oaQdKGd49dbFwBGS1pa0IW0qsGrMb5D0UUkvqr9fDrwTuKFF979SEmhj6udASqJwDCVB+PcyhcbX5/ZiysH8f26z9gcpf4dd6xbKiIiIiIiIiBgihnyiy/ZiykHrLc++qu17UA6R/xdwLyXRAnAWJVH2R+Buyrlf7RJA+1EOhL8deBT4CbB+N6G9X1InMIdShfUwsJ3tmTWuv1O2810F/IPyJsKeHAR8UdI84POU5FVvHUfZrng3JWn3w276zqEktv5S7+FXwGW0OEC+VmnN6vpQtmY+XX8vtj0XeDfwGcpzm0pJjp0AIGmnukaX44F1gZskddbPd/twnxERERERERGxgpLdvLttcJG0kLJt8FTbxwx0PDGwJE2jHpJv+8Pd9R07dqwnT57cP4FFrEDGTZkCkLeSxvOWf0s9yzNa/uVvFBER0f8k3Wx7bKu2VudODSq2hw10DLH8sL3lQMcQEREREREREcvGkN+6GBERERERERERg8NyXdElycAC4Bu2j3oe80wEfmz73KUWHM/Et7ntfz6HsfcAB9q+amnG1F8kTaDE/4aBjqW3JK1OOetsdeDLto8e4JAiVlhTOzuf2a7TH8aPGsXHRo/ut/Wi/yyLf0v59xIRERExdK0IFV3bNCa5JK0m6VhJ/5A0X9I9ks6StGm7CWzv1psklyRL2mzphP3cSTpH0pOS5tXPXyWdJGmtgY6ttyR9RNIdNf4HJF0haUSbvl3329nwWblFv/3r3+jAHtbeRdIt9d/HDEl7A9h+wnYHcMFSucmI6BdTOzu58IEHBjqMWEHk30tERETE0LZcV3S18RNgQ2A8MAVYA9gX2Bk4s7GjJFEO3H+6v4NcCr5i+2hJw4BXUd5YeJ2kHW3P78tE/f0cJL0JOBF4m+0pktahvLmyO1/prsJK0trAEcBtPaz9SuBCYH/gt8BawMg+hB8RvTCmo6PfDl7uz8qx6H9L+99S/r1EREREDG0rVKJL0i7ArsAWtmfUy48B327oMwm4DhgHvAZ4laQfAOfb/kGt2DoTGAM8BfzO9vsl/bFO8ee6JfEjti+S9FHgMGAd4Frg47ZnNoS1u6RPA2sCZwOH2X5a0suAM4BtAAO/Bv6f7Tl9uWfbC4GbJL0T+DtwAHCapGOBzWzvW+97U+BuYFXbi9o8h52Az1EShbMp2/e+V8ePA84HTqn3uxg40vbZtX3den/jgDvq/bSzPXC97Sn1Hh4Bnu+20ZOAU4G9e+h3NPA92xPr74frp8+mLVgwoP8PU7beRERERERERPTNirB1sdEuwJ8aklztfAj4GDACmN7U9r/Ab4C1KQmfbwHYfmNt38Z2R01yvZmSYNkbWL/O9eOm+d4FjKUkk/YEPlyvq44dDbwC2Ag4trc32sz2PEqF0k59GNb8HB4E3kFJyh0AnCLpNQ39X0ypgNoA+Ajw7VpJBSWZuJDyHD7Mv++zlRuBt0o6TtLr69lYPTlI0iOSbpb0nsYGSTtQnvF3ezHPa+uYv0i6X9L5taJshZKtNxERERERERF9t0JVdAHrAvf3ot85tp/Z4lZ27j3jKWATYLTteylVWu18EDjL9i11niOARyVtavue2ufLtWLpEUnfAPYBflAPqO86pH62pJOBL/Qi9u7MBLbrQ/9nPQfgiobvf5D0G/uBbF8AACAASURBVEri7JZ67Sngi7YXAVdK6gS2lHQT8B7gVXXb5F8lnQu8kRZsXyPp3cBBwKeAVSR9HzjU9uIWQ04FPkupznsLcJGkWbavq2d1nQ4cUivlerrnDSkJvrdQnte5lGTmB3sa2GzL4cP7bWtWs2y9iYiIiIiIiOi7Fa2i62FKRVFPuqv4+hyl2upPkm6T1F1l0mgaKsJsd9YYNmiz1vQ6BkkvkvRjSfdJmkvZFrheL2LvzgbAI33o/6znIGk3STfUyqk5wO5NMT1ck1xdFgAdwAspSdHme23L9kTbe1C2fO4JTABaHiJv+xbbD9teZPtKymHx767NBwG32r6++1t9xuPA2bb/Xv9eJ1LuMyIiIiIiIiIGuRUt0XUVsIOkDXvo57YN9izbH7U9Gvgv4PRu3rQ4k1L9BYCkNShVZfc19Nmo4fvGdQyUbYsGXm17TcqB+T2WI7UjqYOydfOaemk+MLyhy4tbDHvmOdTtgz8FvgaMsj0SuLKXMc0GFrHkvfbI9tO2fwdcDWzdmzE17q64dgbeJWmWpFnA64CvSzqtzdhb6ebvHxERERERERGD1wqV6LJ9FeWcqsskbSdpFUkjJH28h8qsZ0h6X0Oi7FFKUqRrO90DwEsbul8IHCBpTE0UnQjc2LBtEeBQSWtL2oiyTe+ien0E0AnMkbQBcGifb7jEu7qk7YCf1XjPrk1TgTdK2ljSWpQ3EnZnNWB1atJK0m6U7X09qtsNLwWOlTS8vtlw/25i3lPSB+pzUT1j603ADW36v1dSh6SVJL2FkhT8eW2eQDnjbEz9TAaOA45qs/zZlL/ZSyUNpxys/8ve3GdERERERERErNhWqERX9V5KJdJFlDOd/ko5qPyqXo7fHrixnj/1c+BTtu+ubccC50qaI2nvWol0DKUS6n7gZcAHmua7HLiZkni6gvJGRyjJmNfUGK+gJIr64nOS5lG2Kp5X13hdPSML27+lPINba1u3yZx6mP0ngYspCbPx/DuZ1BsHU7YxzgLO4d8Jt1YeBT4K/APo2rb5VdsXtOn/KUqV3Bzgq8BHbU+qcc+pVXizbM8CngTm2n4MQNIHJT1zDpntsyjP60bK9son6n1HRERERERExCAne/nd5SVpISVRcartYwY6nlix1aq8B4BVga/YPq67/mPHjvXkyZP7JbZm46ZMYWpnJ2M6OgZk/WVl/KhRfGz06IEOI56nrpcl9NfLGvp7veg/y+JvO9j+vQy2+xmM8jeKiIjof5Jutj22Vdty/dZF28MGOoYYPGw/AYwc6DiGqqmdnQBJdEVERERERMQys1wnuiKGsjEdHYPqvw53/RfviIiIiIiIiGVlRTyjKyIiIiIiIiIiYgmDOtElyZLmSzqhD2PukbTLsoxrMJB0rKTzBzqOvpC0haROSYslHTjQ8URERERERETE0jWoE13VNraParwgaY2a8LhyoILqjqRJkhZKmidprqSbJR1eD1NfIUg6UtLd9TnfK+mibvp23W9n/UxraPtgw/VOSQtqAnO7NnMdLGmypCckndPYZvvvtjuAa5bWfUZERERERETE8mMoJLpaeS/lbY5vkbT+QAfTxsG2RwDrA58FPgBcKUl9nUhSv57FJml/4EPALjWxNBb4XQ/DDrbdUT9bdl20fUHD9Q7gIOAu4JY288wEjgfOet43EhERERERERErlKF6GP3+wHeB3YAPAl9r1UnSy4GJwBG2fyzpEmAn4AXAn4FP2L6t9j0HmA9sCrwRuB0Yb/vOhrm+BWwHzAaOsX1xT4Hang9MkvRO4A7g7cAv63r32j66zj8OON/2hvX3PcB36v1tKWkN4H+AjwIvAmYAR9m+rPafABwI3AB8BJgDHGR7Ym1/CXAO8Jra55mqqxa2B37dde+2ZwHf7+lee2l/4DzbbtVo+9Ia71hgw+ez0LQFCwbsAPWpnZ2M6egYkLUjIiIiIiIiVlRDrqJL0sbAOOCC+tmvTb/XAL8BDrH943p5IrA5JVF0Sx3faB/gOGBt4J/ACXWuNYDfAhfWsfsAp0vaqrdx2/4XMJmSaOutfSiJsZG2FwF31vFr1TjPb6po25GSwFoP+ApwZkMF2YXAzbXtfykJp3ZuAPaTdKiksZJW7kWsJ0l6SNJ1NWm3BEmbUJKI5/VivhXamI4Oxo8aNdBhRERERERERKxQhmJF137ArbZvlzQH+IqkbW03lu7sRKlq+pDt33ddtP3MdjhJxwKPSlrL9mP18qW2/1TbLwBOrtffAdxj++z6+xZJP6VsobytD7HPBNbpQ/9Tbc9oiP+ShraLJB0B7ABcXq9Nt31Gjf9c4HRglKTVKFVau9h+AvijpF+0W9T2+ZIMHAAcCyyU9FXbX2oz5DBKBdyTlC2av5A0pqsirMF+wDW27+7NzT9fWw4fzqRtt+2PpSIiIiIiIiJiKRiqia4zAGzPlPQHSnVSY6Lr48AfGpNctSrpBOB9wAuBp2vTekBXomtWwxwLgK69Z5sAO9bEWpdVgB/2MfYNgP/rQ/8ZjT8k7Qf8N2V7JTW+9Rq6PBO/7QW1mKurz6N1G2WX6cBG7Ra2fQFwgaRVgb3q9ym2f92i740NP8+VtA+wO2WrZ6P9gBPbrRnLv6mdnQO2HRRg/KhRfGz06AFbPyIiIiIiIpatIbV1UdLrKFsPj5A0S9Isyna9fZoObP84sLGkUxqujQf2BHahbP3btGvaXiw9g5I4G9nw6bD9iT7EvhHlfK+uNwbOB4Y3dHlxi2HPnGNVt/2dARwMrGt7JPDXXsZ/P7B23YLZZePexG37qVpJdiuwdW/G1LifFZek1wOjgZ/0co6IZ5na2cmFDzww0GFERERERETEMjTUKrr2p5yV1Xgu1wsoSZjdgK7tePOAtwG/k/Ql24cDIyhvanyYkmDqS2XRL4EvSfoQ0HXe1xig0/bfuhsoaThl2+ApwJ+AK2vTVOCzko4HVgM+3UMMa1ASSLPrvAfQy8ST7emSJgPHSTqSst1xD+DnbWKeUNf5IyUh91ZgK+DGFn1HUpKNfwAWAe+nnMPVfD/7Az+1Pa+7WGvCchVgZWBlScOARfWMshhgYzo6Bmw76EBWkkVERERERET/GDIVXTXhsTfwLduzGj53U7YQPutwddtzgF2B3ST9L+UA9OnAfZTzpG7o7do1OfMWyvlTMylbBL8MrN7NsNMkzQMeAL4B/BR4m+2uLZM/pLz58R7KofkX9RDD7cDXgevrnK8CruvtPVAq2nYEHgG+QPcHws8FjgT+RXl741cob6i8tkXfVYHjKYmxh4BDgL1sP/NWx4a/3bnNgyUdKWliw6WjgceBw4F96/eje3eLEREREREREbEiG+wVXU8AN0s61fYxlLchLsH2QQ3fN234/giwTUPXPZuGntfQd0LTnJOADRt+T6O8AbFHtsf1os9CSvVTo1Ma2jdtMeYo4Kg2850DnNN0TQ3f76KXb3y0fSlwaS/7zqZUrHXXZyEwsk3biU2/j6UcgL8ESZsDN1Eq4M7pTXwRERERERERseIY1Iku28MGOoZYftj+B20SZhERERERERGx4hsyWxcjIiIiIiIiImJwS6IrIiIiIiIiIiIGhSGb6JJkSfMlndCLvjtJmtZTv1i+SdpCUqekxZIOHOh4IiIiIiIiImLpGrKJrmqbekA7kjatya/O+rlH0uEAtq+xveVzWUDSSElnSZolaZ6kv0s6bGnexPKovg3x7vos75XU9q2QkiZJWtjw7BvfuPhKSZMlPVo/V0l6ZTdzbSrpytp3lqTTJK0CYPvvtjuAa5bqzUZERERERETEcmFQH0b/HI20vUjSfwC/kzTV9q+ex3ynAGsArwAeA7YAtl4KcfYrSavYXtTLvvsDHwJ2sX2npBcD7+xh2MG2f9Di+kzgvcB0SmL2/wE/Bl7dZp7TgQeB9SkHz/8WOAg4tTexN5q2YAHjpkzp67BoY2pnJ2M6OgY6jIiIiIiIiBjEhnpFV1u2rwduA7aWNE7SvV1tkg6XdGet0Lpd0ru6mWp74ELbj9p+2vYdtn9S5+mqInsm4Virmw6s3ydIuk7SKZLmSLpL0uvq9RmSHqxJpa6x50g6XdLEWhl1naQXS/pGrXC6Q9K2Df1HS/qppNm1+uqTDW3HSvqJpPMlzQUmSNqhVlfNlfSApJO7uedf276zPstZtr/fh8f/DNtzbN9j24CAxcBm3Qx5CXCx7YW2ZwG/ArZ6LmvH0jWmo4Pxo0YNdBgRERERERExiKWiqwVJAl5HSZC0Kum5E9gJmAW8Dzhf0ma272/R9wbgBElrA9fa/kcfw9kR+AGwLnAcpZrpF5Rkz5uAn0r6qe3O2n9v4K2UJN2VwPXAF4DP1vEnA/8paaU6z+XAPsCGwFWSptn+dZ1rz3p/+wGrA1cD37T9Q0kdtK9MuwE4VdJ9wO+BKbYX93CfJ0n6EjANOMr2pMZGSXOADkpy9vPdzPNN4AOSJgFrA7sBx/SwdktbDh/OpG237bljrDCmdnamSm8pSHVeREREREQsr1LRtaSHgEcoyaXDbf+uuYPtS2zPrBVaFwH/AHZoM98hwAXAwcDtkv4pabc+xHO37bNrougiYCPgi7afsP0b4EmeXeF0me2bbS8ELgMW2j6vYXxX5mZ74IW2v2j7Sdt3AWcAH2iY63rbP6v3+TjwFLCZpPVsd9q+oVXAts+v9/1W4A/Ag13nnbVxGPBSYAPg+8AvJL2sac6RwFqU59hdpuIPlATlXOBeYDLws276R0QfpTovIiIiIiKWV6noWtJ6PZ1FJWk/4L+BTeulDmC9Vn1rguhE4ERJawKHA5dI2riX8TzQ8P3xOmfztY5u+rfruwkwulZKdVmZZx/UPqMplo8AXwTukHQ3cJztX7YK2vYFwAWSVgX2qt+nNFSLNfa9seHnuZL2AXYHvtXUb76k7wKzJb3C9oON7bVK7dfA9ygVeR3AWcCXgc+1ijOGljEdHanSi4iIiIiIGMRS0dVHkjahVD4dDKxbK43+Sjk/qlu251KSXmtQzpKaX5uGN3R78VINuL0ZlGqxkQ2fEbZ3b+jjxgG2/2F7H+BFlOTRTySt0d0itp+yfQlwK70/hL/rPK5WVqI8rw1atK1DqXg7rVa8PQycTUmaRURERERERMQgl0RX361BScTMBpB0AN0kcCQdI2l7SatJGgZ8CpgDTLM9G7gP2FfSypI+DLys3VxL2Z+AuZIOk/SCuv7WkrZvN0DSvpJeaPtpyj1AORy+ud8ESW+XNELSSnWr5lbAjS36jpT0VknDJK0i6YPAGymVWUjaVdK2Nb41KWeMPQr8rXku2w8BdwOfqHONBPYH/ty3RxMRERERERERK6IkuvrI9u3A1ymHvD8AvAq4rrshlKqih4CZwK7A2xsOj/8ocCjwMCUZ9H/LJvKmoMqZXXsAYyjJoYco55Kt1c2wtwG3SeqkHvpezwJrNhc4EvgXJSH2FeATtq9t0XdV4HhK4vAhytlee9meVttHAj8CHqO8BGAz4G1d60o6UtLEhvneXeOcDfwTWAR8ppt7ioiIiIiIiIhBYiif0fUEcLOkU20fY/se2myXq28A3LDh91HAUb1ZxPbxlEROu/aJlG2MrdrOAc5p+P3P5hhtN8Y1oantB5TkVeP4VRp+z6S8cbHV2se2uLZvu/to6ncpcGkv+86mHIzfrv0S4JJu2k9s+j0VGNeqr6TNgZuA1Wh4rhERERERERExOAzZRJftYQMdQ/Qv2/+gVIhFRERERERExCCUrYsRERERERERETEoJNG1FEiypPmSTuhF3yMl/aCnfsuKpI0ldUpauRd9x0m6tz/i6i+SPlLv35I2G+h4IiIiIiIiImLpSaJr6dmmnt2FpE1rImWJraG2T7R9YH8E1JCA66yfObb/ZbujHka/LNceKeksSbMkzZP0d0mH9WLc/jXuAxuubS3p15IekuRezNF8343nlJ1pu+O531lERERERERELK+G7BldQ8g29RD6/nYKsAbwCsobE7cAtu5ugKS1gSOA25qangIuBk4HftbL9QfqviMiIiIiIiJigCTR1c8kHQts1vUGQ0mXADsBLwD+DHzC9m217RxgAeWtjDvV9vcAhwP7Aw8A+9ie0of1NwXuBla1vUjSAcDnKG+VnA182fb32ow9HPgo8CJgBnCU7cvaLLU9cLTtR+vvO+qnOycBpwJ7N160PQ2Y1t9bDactWMC4Kb1+tLGcm9rZyZiOFPNFREREREQMZtm6OPAmAptTkke3ABc0te8NHA2sBzwBXF/7rQf8BDj5ea7/IPAOYE3gAOAUSa9p0/dOSsJtLeA44HxJ67fpewNwgqQDJG3eUxCSdgDGAt/tY/zt/LFum7y0JvdiiBvT0cH4UaMGOoyIiIiIiIhYhlLRNcBsn9X1vVZ7PSppLduP1cuX2b65tl8GHGT7vPr7IuDgHpa4RdLT9ft5NCXGbF/R8PMPkn5DSWbd0iLWSxp+XiTpCGAH4PIW6x4CfKbG931J04FDbE9s7lgPxj+9tj8tqYdb6tGbKIm24cDxwC8ljbG9qC+TbDl8OJO23fb5xhIRERERERER/SQVXQNI0sqSviTpTklzgXtq03oN3R5o+P54i9897cV6je2R9fPJFjHsJukGSY9ImgPs3rR+Y9/9JE2VNKf23bpdX9uP14P3twPWpZyxdYmkdVp0Pwi41fb1PdxLr9j+o+0nbc8BPkXZ+vmKpTF3RERERERERCy/kugaWOOBPYFdKNsBN63Xn3dJU29IWh34KfA1YJTtkcCVrdaXtAlwBqVCa93a96+9idX2XOBEyuH0L2nRZWfgXXWr4SzgdcDXJZ32nG6sRQi9iTMiIiIiIiIiVmzZurhsrS6p8Rk/2dQ+gnLu1sOUbXYn9ldg1WrA6pRD6BdJ2g14CyWB1WwNSsJoNkA9xL7tWxQlHQP8inKA/kqUyqo5wLQW3ScAwxp+X0o5f+zMOpdqnKvV38MA236ixbpbAasCf6Ec8H88cB/wt3axRkRERERERMTgkIquZauTsr2w6/PmpvbzgOmURMztlHOl+o3tecAnKdsKH6VUmP28Td/bga9TDsN/AHgVcF130wNnAw8BM4Fdgbfb7mwx9xzb/5+9+4y2qyrbPv6/qCEcWh40GLpSFFDCY1AeAY2KBUTFCgaFKGDhtaBYKIKAghURBBvSQ1ex0FWMCAICJqCIIGDooYdwUijhej/MuWGzs/cpIeTknHP9xtgje6811yzrMPxwe897Tm98KAHBmU11ytamvL8b6u85NAXMJF0gab/6czRwJjATuI2SJbe97Sd7mGtEREREREREDAHJ6Fo4HgeulXSU7QNsT6PzVrk/NL7UoM+7W+6f3HR/YvMN2z8Hft70+xZ6+Bvanm8OrXOzfQxwTIfnJwNrNP3eH9i/03gtz36Dkk3Vb7bHt/yeRg9bD21v2/T9EmDDTm1rJtoRlL/Z053aRURERERERMTgk0DXQmB7RO+tYnFg+wRKpllEREREREREDDHZuhgREREREREREUNCMroiImKxN7W7m/FTpiyUviaMHs3Hx4xZKH1FRERERMTiZbHL6JJkSbMkHboAz94gafwLMKfJknZf2P0uLob6+ppJukTSXEmXDfRcImLRm9rdzWn33TfQ04iIiIiIiBfI4prRtWkttI6kdYD/AlNs/2+jgaRVKaf53WN7HQDbGzfdPwhYz/aHF9ms+0DSOOAgYEtKgfV7gHOA79l+ZACntlBJ2gr4DrAxMA+4EdjL9tW9PHcJ8EZgadtP1WuTgS2Ap2qzu223LTgvaSfgYGA1SsH5C4DP2J4JYPtNkiYCwyKwFzFUjO3qYvJmmz3vfhZWVlhERERERCyeFruMrh4sL2mTpt8TKAGwQUPS64DJwOXAy22vDLydEsDZdACntlBJWhE4F/ghMApYnRJ8eryX53amc/D107a76qfjqYqUd7ul7ZWAl9b+Fuj0x4iIiIiIiIgYXBbXjK52TgF2Bb5Uf+8CnAzs0WggaRolU2cpYL9ySTsAt9retGbyHAi8CHgQ+KrtU1uzv5qyyJ7JKmoa4yXARXXsa4BJttdonYPtP7RZw3eAE2x/s3HB9h3A15qeX6LOfQ9gOeBCSkbSo03zmgh8HRgJHGH70PrsDJ79m6reXxd4tL6/19b7lwOftH1Xmzki6WOU97wa8Dfg47Zvl/Tl+v4algVOtT2xpYsN6tpOr7/nABe3G6tpzJXqe9gFuKKntj2xfWfLpXnAegvS102zZyf7YzGT2koRERERERHRk8GU0TUJ2EnSkpJeAawAXNWuoe0LgcOAM2sG0KaSlgeOAra1vQLwOmBqfyZQA01/Bo62/b1+Prs88H/AL3tpOrF+3kjJSOoCjm5psxWwIfBm4MD6PrC9ciPrCTgS+AtwN+XvfAKwNrAWJfDU2mdjnjtQAm3vpQQE/wKcXvv/TlP/rwAeAM5q083NwDxJJ0naVtIqvawZyt/rx8D0Dve/KelBSZf3VodN0laSHgUeA94H/KAP48diLrWVIiIiIiIiojeDKaPrLuAmYBtKEOjkBejjaWATSXfYvhe4tx/PbgR8Fdi3KVOpP1ahBJyeCeRI+g7wcWBp4Ju2vwHsDHzf9m21zb7APyV9tKmvg23PAa6TdB1l2+ONTf3uSNnaubntJ4GHaAqw1UL/f+owz0/UudxY2x4G7Cdpbdu312vLAb8GjrR9fmsHtmfWGl1fAY4FVpN0PrCH7fkiFbVu2ZbA54A1Wu/Xfv4FPAHsBPxO0ljbt7ZbgO3LgJUkrU7JjJvWYa092nDkyIVSEygWjmTXRURERERERG8GU0YXlODWROBDlAyvPrM9C9gR+CRwr6TzJL28H13sTMmO+kV/xm3yCCXQ9pKmOX251uk6h2eDjmOA25ueu73eG910rTnraTYl6wsASZtRsrXeY/uBem2kpJ9Kul3STOBSYGVJS7aZ59rAkZJm1K2QD1O2Qa7e1OY44Cbb3+60WNs32p5Yt3VuUtc1X2ZV3ar5I+BzrdtEm/q6yvZjth+3fRJl6+V2ncZueu5uytbPM3prGxERERERERGD32ALdP0SeAdwWyO7qAee74J9ke23UIJN/6ZkGwHMotSzalitTX8HUep6ndYUIHrOc/X6i9pOpgTarqJsCezJPZRgU8NalGL1ve7ZkvQiStDs07ab01/2pmx1fK3tFYHXNx5p082dwCfqNsjGZznbf61j7FP72q23+TTY/jdwIiXg1WpFYBxwpqTpQONUxrskbd2pyw5zb2cp4GV9nWtEREREREREDF6DKtBVg0VvohSc7819wDo1YwhJoyW9q9bKehzophQqh1Kr6/WS1qpF0fdt09+TwAeA5YFTar83AyMkvUPS0pStjcv2MKcvAx+TtI+kF9d5rUEpGN9wOvB5SetK6uLZWmNts50aJC1FCQSeavvMltsrUOpyzZA0iqbi9238BNhX0sa135UkfaB+3xb4LLBD3TrZaS4vl7R3XRuS1qRk4V3ZpvmjlGyvsfXTyNR6NXCVpJUlvU3SCElL1ZMZX085EKDd2DvXv6MkrQ0cCvyxh/VGRERERERExBAxqAJdALav6VSbqcXZ9d+HJP2dsta9KRlTDwNvAPasff4eOBO4HrgWOLfD2E9QMrJeDBxPKXa+J/BzyrbGWZRaYp3mfhklUPd64Oa6NfBCYDLww9rseMoJiZdSTlicC3ymD+tdA9ga2EtSd9NnLcqWweUoGWlX1jE7zfEc4NvAGXWb4z+BbevtHSkZazc29f+TNt08Rjnh8SpJs+qY/6S8/9bxbHt640MpcA9wX33fSwPfqNcfrO9iB9s3AdSgVmOdUGqp/ZUSyLycUtdtDyIiIiIiIiJiyJM93w6/ASVpLiXj6ijbBwz0fGJokfR7YAvgb7bf3FPbcePG+Zprrlk0E4tejZ8yhand3Yzt6uq9cT9MGD2aj48Zs1D7jIWrcRDBwjgcYmH2Fc/fC/H3GGp/46G2nqEof6OIiIhFT9K1tse1u7fYnbpoe8RAzyGGrlqjLQKAqd3dAAl0RUREREREDBGLXaArIqKTsV1dL0jmR0RERERERAwNg65GV0RERERERERERDvDNtAlyZJmSTp0oOcyWNV3uN5Az6M/JJ0oaY6kjocGRERERERERMTgNGwDXdWmtvcHkLRODdw0ThOcJmmfRTURSQdJerJp/BslvW9Rjb+wSdpY0sWSHpE0Q9K1krbrw3MntAugSdpG0t9rcPJOSR/s8Lwk7S/pDkkzJZ0hacXGfdsTefYUyYiIiIiIiIgYQoZ7oKudlW13Ae8HDpC0KIuXn2m7q46/FzBJ0uj+diJpodZeW8D+fgf8HhgNvBj4LDCzl3G2Al7W5vpGwGnA/sBKwFjg2g7d7AJ8BNgSGAMsB/xwAeYfEREREREREYNMitF3YPsaSTdQgiq/l7QEsB+wByV4ciHwGduPShoB/JySKbQk8B9ge9v3SZoIHAi8CHgQ+KrtU/sw/kWSHqMEfu4DkLQ98A1gHeBfwCdtX1/vTQN+DOwMbChp4zqPicDXgZHAEbYPre1fAxwJvAKYA/wS+ILtJ+p9A5+mBNyWAtaV9CXgC4CBr3aau6RVgXWBYxv9AZf3tN4aTPshsCtwXcvtrwI/tX1B/f1Q/bTzTuA423fWfr8NXCLpU7Zn9zSHVjfNnp1i5YuRqd3djO3qGuhpRERERERExGIsGV0dSNoC2AS4pV6aWD9vBF4KdAFH13u7UjKN1gT+B/gkMEfS8sBRwLa2VwBeB0ztw9iS9A5gGUpAC0n/CxwPfKKO8VPgt5KWbXr0Q8A7gJWBp+q1rYANgTcDB0p6Rb0+D/g8sCrwf/X+ni1T2QF4LbCRpLcDXwTeAqwPbNPDEh6ivLdJknboY1ba54FLG4G7FlsASPqHpHslTZI0qkM/qp/m38vWOccgNrariwmj+53gGBERERERS2BfTQAAIABJREFUEcNIMrrm92ANHo0ADgd+Xa/vDHzf9m0AkvYF/inpo8CTlODTejVQc21tszzwNLCJpDts3wvc28PYH6xZW8tQgjP72p5R7+1ByWq6qv4+SdJ+lCDQn+u1o5oymRp9Hmx7DnCdpOuATYEbbTdv/Zsm6afAG4AfNF3/pu2Ha38fBE6w/c/6+yBKYG0+ti3pjcA+9R2uK+kyYDfb/2ltL2lNSgDv1R3eyxqU7YhvBe4BTqJkf+3cpu0FwJclnQU8AnylXh/Zoe+ONhw5ksmbbdbfxyIiIiIiIiJigCSja36rUrK1vgiMB5au18cAtze1u50SKBwNnAJcBJwh6R5J35G0tO1ZwI6UDK97JZ0n6eU9jH2W7ZVtj6RsWdxF0ifqvbWBvWth9xmSZlAyyMY0PX9nmz6nN32fXdeGpA0knStpuqSZwGF17c2a+xvT8vt2emD7Ltuftv2yOvdZwMkdmv8AOMT2ox3uz6EE2W623V3n2qmw/fHA6cBk4AbgT/V6TlmMiIiIiIiIGOIS6GrD9jzbhwNzeXY73z2UgE3DWpTtgffZftL2wbY3omxP3J5SFB3bF9l+C/AS4N/AsX2cwzRKdtI766U7gUNrIKzxGWn79ObH+rHMH9f5rG97RUr9MbW0ae7vXkpgrWGtvg5Us8yOoWwFbefNwHdr0K0RmLtC0oT6/Xr6uDbbT9v+mu11bK9BCXbdXT8RERERERERMYQl0NWzb1G2wY2gZAl9XtK6krooWUVn2n5K0hslvVLSkpSTBZ8E5kkaLelddQvj40A3pTZWryStAbydEqiBEiD7pKTX1hpey0t6h6QVFnBtK9S5dtcss0/10v4sYKKkjSSNBL7Ww9xXkXSwpPUkLVGL038MuLLDIxtQtlSOrR8oAb5z6vcTgI9Kemkd+yvAuR3GHiXpZfUdbQR8n5It9nQv64uIiIiIiIiIQS6Brp6dR6nztAdlS9wpwKXAfynZXp+p7VYDfkEJHN1IqZk1ifJ+96Zkgz1MqYHVWvC92Y6SuiV1A1dTTio8GMopkHUeR9c53UIpjr+gvghMAB6jBNHO7KlxPfHwB8AldexLemj+BOVkyD9Q3sk/KYG+tvO1fb/t6Y1PvfxgrS2G7eMp2x6vomyZfBz4bOP5+s62rj9XBc6nbJW8ADje9s96WltEREREREREDA3DuRj948C1ko6yfUDdKvicrXu2DWzcdOmQ+qGl3emUjK9W91KCW72yfRBwUC9tLgQu7HBvnZbf05h/PeObvl8KtNYLO7Dpfus2Rmx/i5Ll1nB8h7nMopxEuUA6jP01OmSR2e5q+n4z5ZTJtiQdB3wAuH9B5xcRERERERERi6dhG+iyPWKg5xCLnu3dgN0Geh4RERERERERsfBl62JERERERERERAwJCXRFRERERERERMSQMGQDXZIsaZakQwd6LkORpIMkTRroefSHpA1q4fp5knYf6PlERERERERExMI11Gt0bWr7FgBJ61BOS5zV0mY32z2eOLioSZoMbAE8CRj4D3A2cITtxwdwan0maT/KKZEvAmYAl9vesZdn1gf+AfzC9oebru8O7EM53fIy4GO27+nQxyjgOOCtwIPAvrZPg2cK1XfV9xsBwNTubsZPmTLQ0+jVhNGj+fiYMQM9jYiIiIiIiMXaUA90tbOy7acGehJ98GnbP5e0PLA58APgLZK2qadB9pmkpRblmiXtCnwE2Mb2rZJWA97Vh0ePAa5u6esNwGHAGykBvyMpJ1x2Os3yGOAJYDQwFjhP0nW2b+jvOm6aPXuRBkASyIhOpnZ3A+S/j4iIiIiIiF4Mx0BXW5JOBGYD6wJbA9cB76NkEu0K3Ad8yPaU2n4aJajyEeBlwBnAfsCJwFbAVcAHbD9S259d+12u9v2pvgRfbM8CJkt6F/Bv4B3AuXW+d9n+au1/PDDJ9hpN8/sxsDOwYQ2YfZGSZfVi4E5gf9vn1PYTgd2BKymnEs4A9rR9Qb2/bl3b/9Y2N/Uw7c2Bi2zfWtcwHfhZT+uUtFMd86/Aek233gmc3XhXkr4O3C3pZY3+m/pYnvI328R2N3CZpN9S/kb79DT+QEsgY+CM7epi8mabDfQ0ejQYMs4iIiIiIiIWBwl0PdcHgbcBNwDnA1cAXwP2Bg4Gvk/JLGp4H/AWynucAmxGCRL9C7gA+Gx9jvr7Y5Rso28Dp1IyjvrE9h2SrqEEy87t42MfogTGHrT9lKRb6/PTgQ8AkyStZ/ve2v61wEnAqsDHgeMkrV4zyE6r7+Ottd15wG86jHslcJSku4E/AVNsz+s0SUkrAocAb6a8v+fcrp/m3wCbALe2tN0AmFe3KDZcR+fsrx5tOHLkIguAJJARERERERER8fwN2WL0PXhQ0oymzyua7p1j+1rbc4FzgLm2T65BmjMpgaxmP7R9n+27gb8AV9meUutondPc3vbxth+r9w4CNpW0Uj/nfg8wqh/tj7J9p+05dQ5n277H9tO1Ltl/gNc0tb/d9rF1vScBLwFGS1qLkqV1gO3HbV8K/K7ToLYnAZ+hBA3/DNwvqaeMqq8Dx9m+s82984EPSnqVpOWAAyl1y0a2adsFPNpy7VFghR7GjoiIiIiIiIghYjgGula1vXLT58ame/c1fZ/T5ndXS199ai9pSUnfknSrpJnAtMZc+jn31YGH+9H+OYEjSbtImtoI8lGyoprnML3xxfbs+rULGAM8UrdRNtze08C2T7W9DbAy8EngEElva20naSywDXBEh37+SMmq+2UdcxrwGHBXm+bdwIot11as7SMiIiIiIiJiiBuOga6BMAF4NyWgsxKwTr2uTg+0krQm8GpK5hiU0yObs5pWa/PYM0XrJa0NHAt8Gvgf2ysD/+zjHO4FVqk1sBrW6su8bT9p+2zgekpgrdV4yvu4Q9J0Sh2x90n6e1Mfx9he3/aLKQGvpercW90MLFVPb2zYlLIVNSIiIiIiIiKGuAS6Fo0VgMeBhyjBqcP6+qCkkfXkwd8Af6Ns5QOYCmwnaVQ91XCvXrpanhL4eqD2+1HaB57mY/t24BrgYEnLSNqKUiS+05wnSnqHpBUkLSFpW2BjSoH+Vj+jFPMfWz8/odT/elvta4SkTVSsVdsf2Sjy3zLPWcCvKNljy0vakhJgPKUv64yIiIiIiIiIwW04FqOfIT0nielA299/gcc8mRK4uZuy9fAA4FO9PHO0pMZ2vluAXwCH2366XjuFkiE2rX5OoBTNb8v2vyQdTiko/3Sd0+X9WMMESt2uh2sfJ1O2JbYzk3IC5SRgScqWw0/ZvqzNvGZTTrsEQFI3pTbaA/XSCEoh/JdRtiCeQHl/jfb7AVvb3rZe2hM4HrifEljs0+mWi4Op3d2LrCj9hNGjc8JjREREREREDDlDOdD1OHCtpKNsH2B7Gj1s07M9seX3z4GfN/2+hab3ZXudlvYf7vS87W5KZlGzk3uYy/hO95razAV2bLl8RNP9dVruYXt/YP8O/Z0InNhyTU3fb6Oc2Ngr27+iZFb1m+2DWn7PAF7VQ/vDWn4/DOzQrm3d0ng1sAwtax1OpnZ3AyTQFREREREREUPOkA102R4x0HOIxYvt/9A5C23Aje3qYvJmrQd7LnyLKmssIiIiIiIiYlFLjS5AkiXNknToQM8lXjiSNpDULWmepN0Hej4RERERERERsXAl0PWsTevWPuCZ4Nd6L8RAkl4i6ThJ90p6TNK/JR3ccqrhoCZpP0n/rYGluySd2UPbyZLm1rbdkm5quf/m+o5mS/pTPUGyU1+jJJ1TA5e3S5rQuGf7ZttdPHtyZUREREREREQMIQl0LWKSRlGKuS8H/J/tFYC3ULbUvWwB+luq5bckDejfVdKuwEeAbWpgaRzwx14e+7TtrvrZsKmvVSn1vg4ARlFOf+wYNAOOAZ4ARgM7Az+WtPECLyYiIiIiIiIiBo0EuvpA0omSvtH0e7yku5p+T5P0RUnXS3pU0pmSOtUI+wLl9MAP1wL52L7T9udsX1/7O1LSnZJmSrpW0jNF4CUdJOkXkiZJmglMrBlRh0q6nHKC4UslfVTSjTVj7DZJn2jqY1VJ50qaIelhSX9pBMckrSnpV5IekPSQpKPr9SUkfbVmSd0v6WRJK3VY4+bARbZvreubbvtn/XztDe8FbrB9di3AfxCwqaSXtzasGXHvAw6w3V1PefwtJegWEREREREREUPckC1GPwA+CLwdmAtcDkwEftKm3TbAr2w/3UNfVwOHAI8CnwPOlrRODfRAOcHxA8AuwLLAhynBnG2BmyinS24IbA/cBrweuEDS1bb/DuwN3AW8qPa3BWBJSwLnApfU/uZRsrGo65kIvBG4n3Jq5NG0DyJdCRwl6W7gT8AU2/N6WC/ANyV9q85/f9uT6/WNgesajWzPknRrvf7vlj42AObZvrnp2nXAG3oZu62bZs9eZIXbp3Z3M7ara5GMFRERERERETFUJaNr4TnK9j22HwZ+B4zt0O5/gHt76sj2JNsP2X7K9uGUYNaGTU2usP1r20/bnlOvnWj7hvrMk7bPs32riz8DFwONzLAngZcAa9e2f7Ft4DXAGOBLtmfZnluzoqBsA/y+7dtsdwP7Aju1bp1szB/4DPA24M/A/ZL26WHJXwFeCqwO/Az4naTGNs4uSsCv2aPACm366U/bxcrYri4mjB490NOIiIiIiIiIGNSS0bXwTG/6PpsSMGrnIUqQqSNJewO71z4MrAis2tTkzjaPPeeapG2Br1GynJYARgL/qLe/S9kCeLEkgJ/Z/hawJnC77afa9D8GuL3p9+2U/35GA3e3NrZ9KnCqpKWBHer3KbYvatP2qqafJ0n6ELAd8EOgu66/2YqU7Z+t+tO2VxuOHMnkzTZbkEcjIiIiIiIiYgAk0NU3syiBoobVnkdffwDeI+ngdtsXaz2urwBvptSmelrSI5TtiA1u0+8z1yQtC/ySsrXxN7aflPTrRh+2H6NsX9y7Fmr/k6SrKcGytSQt1SbYdQ/QfNrhWsBTwH09Ldb2k5Stl18BNgHmC3R1WEtjvTcAuzatbXlK0f4b2jx3M7CUpPVt/6de27RD22Ftanf3ItuWuTjLltGIiIiIiIihJVsX+2YqsJ2kUZJWA/Z6Hn19n5JldJKktQEkrS7p+5JeRdlm9xTwACVocyDzZyn1ZhnKdscHgKdqdtdbGzclbS9pPZV0rpmUWlzzgL9RtlV+S9LykkZI2rI+djrweUnrSuoCDgPObJf9JWmipHdIWqEWsd+WUlPrqjZtV5b0tjrWUpJ2ptQUawTEzgE2kfS+WuD/QOB62631ubA9i3JC4yF1/ltS6pmd0s/3F8NEtoxGREREREQMLcno6lkjS+oUShH5afVzAiUjqv8d2g9Leh3wDeCqmqF0NyWQdAsl++gCSnbSLOAI2m9V7GmMxyR9FjiLEvD6HeX0wYb1KYXkXwQ8AvyoUfxd0juBo4A7KOs/jVJc/3jK9sVLgRGUQNRnOkxhJrAfMAlYkrLN8VNN9b6aLV3fxcspwbZ/AzvYvqmu5QFJ76vznUQJlu3UeFjSfsDWtretl/asc72fsk30U7aT0dVibFdXtmVGRERERETEkJNAV/E4cK2ko2wfIKmRQfUQQD3tcMeWZ45ofLG9TvMN2wf1NJjte4CP9dBkt/pp+E5Pfdse3+baMcAxHcY/gqb5t9y7g1JTq/X605STIA/pYd6Ntr+iZFb1yvYDwOa9tPkDJRDW7t5hLb8fps38ASStTznRchngxL7MLyIiIiIiIiIGjwS6ANsjWi7tCNxqe8ZAzCdeGLVu18oDPY+IiIiIiIiIeGEk0NVC0l8pwZDdB3ouERERERERERHRdwl0tbD9uoGeQ0REq+F8UmZOx4yIiIiIiL7KqYsREbFYy+mYERERERHRV4M6o0uSgdnAD2zv34f2JwJ32f7qCz23oW4wvktJ2wC/BkYCb61F7iMGhZyUGRERERER0buhkNG1aXOQS9Jukv4t6TFJ90k6T9IKAznB/pI0TdKcuoYZkv4q6ZOSBsXfS9Iykg6XdJekbkn/ldT2lMeW594gyZK+0XRtv9pH4zNH0tOSVm3z/Fotbbtrf3tDOb3Rdhdwx0JdcEREREREREQsFgZF4KSvJL0BOAz4kO0VgFcAZw3srBbYO+sa1ga+BXwFOG5BOpK0qDP39gXGAa8BVgDeCPRYXEjS0sCRwFXN120fZrur8QG+DUy2/WBrH7bvaGn7SuBp4JcLY1ERERERERERsXgb1FsX29gcuML2FADbDwMntbRZRdJ5wOuBfwETbN8KIOlI4L3ASsB/gL1s/6XeO5GmrXqSxgOTbK9Rf08DjgZ2oQSnLgR2tT1X0irAKcBrKe/8cuCTtu/qbUG2HwV+K2k6cKWkw23/U9LkOv7P6/gTgd1tb1V/G/g0sFcdc91e1ncQsBEwF3gPJetpV9vX1PubUQJt6wPnA+5h2psD59i+p/6eVj892Ru4GHhxpwaSBHwEOKSXvhp2AS613dvYbd00e/aQLP6dwt4RERERERExVA2pjC5KNtDbJB0saUtJy7Zp8yHgYGAV4Bbg0KZ7VwNjgVHAacDZkkb0Y/wPAm8H1gVeBUys15cATqAEwNYC5lCCYn1m+2/AXcDW/XhsB0pwbaP6u7f1vQs4A1gZ+G1jjpKWodS2OqU+ezbwvh7GvRL4gqQ9Jb2yBqg6krQ28DF6D2BtDYym7xlauzB/oHPYS2HviIiIiIiIGKqGVEaX7b9Iei+wJ/A5YClJPwO+ZHtebfarGjRC0qnA95uen9TU3eGSvgpsCFzXxykc1chikvQ7SlAJ2w/RFJyRdCjwpwVY4j2UQFNffbNmtVHn0dv6LrN9fp3jKZRsMIAtgKUpRf8N/ELSF3oaF3gE2Bk4AnhI0r62OwWdjgIOsN3dS0xsV+AXtrt7alTn3wiK/aK3tp1sOHJkin9HREREREREDCJDLaML2xfYficlIPRuSlbV7k1Npjd9nw08s4dL0t6SbpT0qKQZlC1+8xU970HbviWNlPRTSbdLmglcCqwsacl+9A2wOvBwr62edWfzjz6sr3X+I2p9rzHA3TXI1XB7p0Ftz7N9jO0tKdlhhwLHS3pFa1tJ7wRWsH1mTwuRtBzwAfqeobUr8Mu+BMUiIiIiIiIiYmgYcoGuBttP2/4jcAmwSW/tawbQVyjbD1exvTLwKNBIMZoFjGx6ZLV+TGdvSubUa22vSKkPRlPfvZK0OSXQdVk/5vNMYKoP6+vJvcDqLVsQ1+rLvG3PsX0MJcNrozZN3gyMkzS91iHbEdhL0m9a2r2XEuSb3NuYCxAUi4iIiIiIiIghYEgFuiS9W9JOklZR8RrgDZSaUb1ZAXgKeICy5fFAYMWm+1OB7SSNkrQaz27r64sVKHW5ZkgaBXytrw9KWlHS9pTaWZNs/6NpPu+t2WLrAbv1YQ49ra8nV9RnPytpqbo99DU9zHkvSeMlLVfb71rHb1fZ/QBgA8o2z7GU2mDHAh9tabcrcHJLVlkn7wFmsGDbQyMiIiIiIiJikBpSgS5K1tAelBMFZwKTgO/aPrUPz14EXADcTNmWN5fnbv07hVLLahrldMAet9q1+AGwHPAgJeh2YR+e+Z2kx+oc9qfUEmsO/hwBPAHcR8lc6m2Nva2vI9tPUDKqJlLe8Y7Ar3p4ZA5wOGUr5IPA/wPeZ/u2Nn0/Znt641OfndVcW0zS6sCbgJNbn5f0E0k/abncn6BYRERERERERAwRGsyxAElzgccpReAPGOj5xOJN0psphwIsC2xnu8eMr3Hjxvmaa65ZJHOL6Mn4KSUZMocjPH95l4uXF+LvMdT+xkNtPUNR/kYRERGLnqRrbY9rd29Qn7poe8RAzyEGj1qzbeWBnkdEREREREREvDCG2tbFiIiIiIiIiIgYpgZ1RldERERExECbusd6jO8a6FlELDwTJsDHPz7Qs4iIWDDDJqNLkiXNknToQM8lBo6kSyTNlXTZQM8lIiIiImJxM3UqnHbaQM8iImLBDbeMrk1t39J8QdLylJMLL7W93QsxqKTdgC8BqwOzgWuAnWw/9kKMtziQtBXwHWBjYB5wI7CX7avbtJ0IHEc5cbFhe9uT6/11gB8B/0c5fOAXta+nOoz9UuAo4A21/fG2vwxg+011vN2f5xIjIiIiABh77C0pRh9DxvjxAz2DiIjnZ7gFutp5PyUY8lZJL7F978LsXNIbgMOAt9ueImkU8M6FOcaiIGmpToGlNm1XBM4FPgWcBSwDbE15z51cYXurDvd+BNwPvIRSTP73wJ6UYFbr2MvU+8cAO1KCbBv0Zd6tbpo9+5mTlIabCaNH8/ExYwZ6GhERERERERH9Mmy2LvZgV+AnwPXAzgCStpA0XdKSjUaS3iPp+vr9NZKukDRD0r2Sjq4BlnY2pwRxpgDYftj2SY1sLkmTJT2TXSRpYvO2urrlck9J/5H0mKSvS3pZHX+mpLMaY0saL+kuSV+WdH+d2w6StpN0s6SHJe3X1PcSkvaRdKukh2pfo+q9derYu0m6A7hE0ghJk2rbGZKuljS6zZo3qGs93fY823NsX2z7+n7/dYp1gbNsz7U9HbiQkinWzkTgHtvftz2rPrOg4w5LU7u7Oe2++wZ6GhERERERERH9NqwzuiStBYwHPg08TAl6fc/2lZJmAW+iZAcBTAAau9XnAZ+nbEFcA7iAkmH0gzbDXAV8XdLBwMXANbZ7ymxq5+3Aq4E1gb8Dr6ME5R4CrgA+BJxU264GjKBsk5wIHFvX8GpgLeBaSWfYvg34LLADZYvfA5QMqWNqfw1vAF4BPF3fz0p1Ho8DY3nudsOGm4F5kk4CzgCutP1IL2vcTNKDlL/DKcA3mzLIjgR2kjQZWAXYFjigQz9bANMkXUAJMv4T+Iztf/Qy/nw2HDlyWG5DGK5ZbBERERERETH4DfeMrl2A623/Czgd2FhSI7JxOjXgI2kFYLt6DdvX2r7S9lO2pwE/pQSE5mP7L8B7gf8FzgMekvT95myxPvi27Zm2b6AEbi62fZvtRylBtuZozJPAobafpASZVgWOtP1Yff4G4FW17SeA/W3fVYNvBwHvl9QcAD2oZkbNqX3/D7BezdS61vbMNmueCWwFmBJoe0DSbztkfwFcCmwCvBh4H+W9f6np/p8pGVwzgbsoAcZfd+hrDWAnStBuDOWd/6aHjLuIiIiIiIiIGCIS6IJTAWzfQwmo7FrvnQa8V9KylEDV323fDiBpA0nn1u2NMyk1uFbtNIjtC2y/ExgFvJuSadWfYujN+8jmtPndfKD1Q7bnNd1r93yj/drAOXUb4gxKwfh5QHNA6s6m76cAFwFnSLpH0nckLd1uwrZvtD3R9hqUINYY2me8UYN2/7X9dM28OoRSOw1JS9QxfwUsT3nPqwDfbtdXXd9l9Z0/AXyPEpx7RYf2ERERERERETFEDNtAl6TXAesD+9aA1XTgtcCHauH1fwG3U7bJNW9bBPgx8G9gfdsrAvsB6m3MGsj5I3AJJfgDMAsY2dRstee3sn65E9jW9spNnxG2725q42e+2E/aPtj2RpTtk9tTgoU9sv1v4ESeXXOvj/Ds+xxF2Sp5tO3HbT8EnEDJsGvn+uY5R0RERERERMTwMWwDXZTMrd8DG1FqTY2lBGJGUoJbUIJbnwVeD5zd9OwKlG103ZJeTjldsC1J75a0k6RVVLyGss3xytpkKiVzbKSk9YDdFtYC++AnwKGS1q5zfZGkd3dqLOmNkl5Zt13OpGxlnNem3csl7S1pjfp7Tcp2xCtb29b72za2Ndb3eQDwGwDbDwL/BT4laSlJK1P+dtd1mOYkYAtJ29R57gU8SMlWi4iIiIiIiIghbFgWo5c0AvggsEs9xa/53imUQMrvKDW5vglcUAMuDV8EfgZ8GZgCnEkpXN/OI5Rg2dHAssC9wHdtn1rvH0Epmn4fJRvpVGCb57nEvjqSkjl1saQxwP2UtfymQ/vVKMGxNYDu2nZSm3aPUbLjvlADUzOAc3lu3a1mbwZOlNRFeQ+TKNtBG95L2fb4FUpg7U+UwwAaBwr8C9jI9h22b5L04TrPF1OK97+rbmOMPpra3Z2i9IuRqd3djO3q6r1hRERERETEMDecAl2PU04cPMr2AZQ6T/OxvWfT9ztok/Vm+1Lg5S2XD+zQ36WUQE5bNYD21pbLBzXdV0v7rVp+f7Xp+2RKEKrx+ylatlQ2P2/7aeD79dM6r2ltnj2dWpC/J3Xr4wd7a9fU/ouU4GGn+1Mpp2O2u3cHz61Rhu1fUWp6zUfS7yknM/6tr/OLGGhju7qYMLrTWQ4RERERERHRMGwCXbZHDPQcYuDZfstAz2EwGNvVxeTNNuu9YcQglIzFxUeyFSMiIiJiYRvONboiIiJiACVbMSIiIiIWtmGT0RUREQHJWIyIiIiIGMqGRUaXJEuaJenQhdjnzpIu7kO7gyS1K9jeuH+DpPELa169zKVb0ksXxViLK0knSpoj6a6BnktERERERERELFzDItBVbWp7fwBJ69TgV3f93CfpXEl9rt9k+1TbrUXk+832xrWI/HwkrSHpl5IelPSopH9Imtiyhj5n5dnusn3b851zX0jaWNLFkh6RNEPStZK266H9iySdVts+IunUNm1GSXpA0mU99PMOSZfVfqZLOlbSCo37ticC2z7f9UVERERERETE4me4b11c2fZTklYDdgTOkfRp2ycO8LwaTgGuA9amnBr5SmC1AZ1RG5KWtD2v5fLvgB8D29ffm9NyimOLXwFXU9Y6G9ikTZtvAzfSc4B2JeAbwKXAssBpwHeBT/a8ivndNHv2sCxYneLQERERERERMVgNp4yujmxPt30kcBDwbUlLAEjaR9Ktkh6T9C9J72k8I2lic2ZRzWD6vaSHa4bYfk1DLCPp5NrPDZLGNT03TdI2Haa2OXCi7Vm2n7I9xfYF9d6l9d8ZNSuFl+LMAAAgAElEQVTt/2p/H5N0Y82KukjS2k1jWdJ69fuJko6RdF6d11WSXtbU9uVN67lJ0geb7p0o6ceSzpc0C3hj86QlrQqsCxxr+4n6udx220wsSW8F1gS+ZPtR20/antLS5v8owa8TOrwrAGyfZvtC27NtPwIcC2zZ0zPxXCkOHREREREREYPVcM/oavUrSvbPhpTMoVuBrYHpwAeASZLWs31v80N1a9wfgO8B7wSWBjZqavIu4L3ARynZRkcDW/RhPlcCx0j6IfBX23c03Xs98F9qVlqdxw7AfnUO/wH2AU4HXteh/w8Bbwf+DpwEHArsJGl54PfAgZRtfq8CLpZ0g+0b6rMTgO0oGVvLtPT7EHAL5X39HLjC9n09rHML4CbgJEnbArcBX7T957quJYFjgD0oWW398Xrghl5btbHhyJEpWB0RERERERExiCSj67nuqf+OArB9tu17bD9t+0xK8Og1bZ7bHphu+3Dbc20/ZvuqpvuX2T6/bu87Bdi0j/P5APAX4ADgv5KmStq8h/afAL5p+8Ya/DoMGNuc1dXiV7b/VtueCoxtWs802yfUTLK/A78E3t/07G9qltbTtuc2d2rblCyvacDhwL2SLpW0fod5rAG8FfgTZWvm4cBvamYYwGeBq2xf28Pa51Nrru1KCdhFRERERERExBCXQNdzrV7/fRhA0i41uDRD0gzK1rlV2zy3JiX7q5PpTd9nAyP6UkTe9iO297G9MTAamAr8WlKnWldrA0c2zfdhSl2s1Tu0b51XozDT2sBrG/3UvnbmufXB7uxl7nfZ/rTtl9X+ZgEnd2g+hxJYO65uWzyj9r+lpDGUQNf+PY3XStIWlPpc77d9c3+ejYiIiIiIiIjBKVsXn+s9wP3ATTUL6ljgzZStd/MkTaV9QfU7KdsAXzC2H5T0PUqG0ijAHeZxqO35TizspzuBP9vu6RTKduO3b2jfKekYyjbKdq6nbLds5zXAS4B/1fjecsBykqYDq7cpgo+kzYDfAh+z/ce+zjMiIiIiIiIiBrdkdAGSRkv6NPA1YF/bTwPLU4I5D9Q2H6X9SYAA5wKrSdpL0rKSVpD02oUwr29L2kTSUrUO2KeAW2w/VOf1NPDSpkd+AuwraeP6/EqSPrAAQ58LbCDpI5KWrp/NJb2ij/NeRdLBktaTtETdgvgxSs2xds4BVpG0q6QlJb2fkoV2OXABsA5lW+VYyjbEKcDYDkGuTYALgc/Y/l2/Vh0RERERERERg9pwD3TNqKcG/oNSWP0Dto8HsP0vSq2oK4D7KEXQL2/Xie3HgLdQspKmU2p5vbFd234aSQkCzaAUaF+bUtge27MpxeMvr9sLt7B9DvBt4AxJM4F/UorJ90tdz1uBnSh1y6bXfpftYxdPUIJTfwAa83gcmNhhvIfrur4IPEopov9u2w/afryeijnd9vR6/8n6HYB66uTW9efewIuA4+r1bkkLVIw+IiIiIiIiIgYXlbrhQ5ukuZRAy1G2Dxjo+cTAkXQcpcj//bbX66ntuHHjfM011yyaiUXEIjF+yhSAnKg6hA21v/FQW89QlL9RDDXjx5d/J08eyFlERPRM0rW2x7W7NyxqdNkeMdBziMWD7d2A3QZ6HhERERERERGx8A33rYsRERERERERETFEDLlAlyRLmiXp0H48c4Ok8fX7QZImvWAT7HkeCzS2pPGS7noB5jNZ0u4d7q1V618tubDHfSFJukTSXEmXDfRcIiIiIiIiImLhGnKBrmpT2/sDSFqnBr8ahcmnSdqnubHtjW1PXliDS9qvaby5kuYNtcLotu+w3dXu5EMASVtJ+qukRyU9LOlySZv31m8NRFnSfNtqJa1f32fHYGA9pfIiSQ9Kmq8Ane03AZ/sbR4RERERERERMfgM1UBXOyvb7gLeDxwg6S0v1EC2D6tBoC5KUOWKxm/bG79Q4y4uJK0InAv8EBgFrA4cTDkQoKfndqbnunHHAFf3MvyTwFmkDldERERERETEsDMsitE3s31NzaoaC/weQNI0YHfbf2huK2lp4GRgGeBDlEDN+rZvqfdPBO6y/dW+ji/pSOC9wErAf4C9bP+lTbvWsXcGvgysATwAfNv2T1ue2Rv4CjAP2M/2CfX6O4BvAC8DHgWOs31QvTcC+DmwLbBkndP2tu+r3a4t6XLgVcAVwATbD0paB/gvsLTtp1qmvwGA7dPr7znAxb28l5WArwG71HFa7+8EzAD+CnQ8LdH2TcBNkno8UbEvbpo9+5mTlAajCaNH8/ExYwZ6GhERERERERGLzHDK6AJA0hbAJsAtvbRbDvg1Jbj1QdtPLKQpXE0Jso0CTgPOrsGm3sa+H9geWBH4KHCEpP9temw1SvBsdUo20zGSVqn3ZlECSCsD7wA+JWmHem/X+tyawP9QMtDmNPU7oY73YkrQ7Yt9WOPNwDxJJ0natmkePTkM+DEwvfVGzRA7BNi7D/0EMLW7m9Puu6/3hhERERERERFDyHDK6HpQ0rLACOBwSiCpkxWBC4HrgM/Znq/W04Ky3Vxf6nBJXwU2rGN1HNv2eU3P/VnSxcDWwN/rtSeBQ2p21fmSumu/V7bUH7te0unAGyjv4ElKgGs929cD17ZM+QTbNwNIOgt4Vx/WOFPSVpTssmOB1SSdD+zRlCn2DEnjgC2Bz1Ey1lp9nZKFdqek3oZfaDYcOZLJm222yMZbmAZzJlpERERERETEghpOGV2rAl2UjKTxwNI9tN2CslXvWwszyAVle6GkG2uR9hmUbKpVexu7ZkZdWQu7zwC2a3nuoZYthLMp60XSayX9SdIDkh6lZG01nj0FuAg4Q9I9kr5Tt002TG/XZ29s32h7ou01KBl0Y4AftHkfSwA/ogT1WrdAImkssA1wRF/GjYiIiIiIiIjhazgFurA9z/bhwFxgzx6aXgx8E/ijpNFN12cDI5t+r9af8SVtTcly+iCwiu2VKTWzmtOU5hu7ZqL9EvgeMLo+d37Lcz05DfgtsKbtlYCfNJ61/aTtg21vBLyOsj1yl/6sqze2/w2cSAl4tVoRGAecKWk6zxabv6u+r/HAOsAd9f4XgfdJ+nubviIiIiIiIiJiGBtWga4m3wK+3Fobq5nt71ACRH+U1Mh+mgpMkLSkpLdTtv/1xwrAU5Ri8ktJOpAS6Olt7GWAZetzT0naFnhrP8d92PZcSa+h1N0CQNIbJb1S0pLATMpWxnn9XNdzSHp5zVxbo/5ek1JQ/8o2zR+lZHuNrZ/t6vVXA1cBP6MU0W/c/wlwHvC2DmOr/l2Xqb9H1EBhRERERERERAxxwzXQdR7wCLBHT41sf51Sx+oPkkZRaki9k3L63870XOernYuACyjF2m+nZJbd2dvYlG2WnwXOqvOeQMnQ6qs9gUMkPQYcWPtpWA34BSXIdSPwZ2DSfD30z2PAa4GrJM2iBLj+SZti8i6mNz6UYB7AfbafsD275X43MNf2AwCS1pLULWmt+tzalGL6N9Tfc4Cbnud6IiIiIiIiImIQ0EIuQTXgJM2lnFZ4lO0DBno+sXiR9HtKHbS/2X5zT23HjRvna665ZtFMbCEbP2UKU7u7GdvVp5JqA2bC6NF8fMyYgZ5GDCONgxoG60ET0bvB8r9/fdVYS/6bXXzlf1diqBk/vvw7efJAziIiomeSrrU9rt29IXfqou2O2xEjbL9loOcQxdTuboAEuiIiejC2q4sJo0f33jAiIiIigCEY6IqIYnHPAGj8P+AREQvb4v6/fxERERHxwhmuNbp6JcmSZkk69AUeZ6Kky17IMeJZki6RNDfvPCIiIiIiImLoSaCrZ5va3h9A0jo1+NVdP9Mk7TOQk5N0oqRvDOQcOpG0laS/SnpU0sOSLpe0eR+eu6S+56Warq0j6XxJj0iaLuno5vstz+8k6aY67v2STpL0zMmWtt8EfHKhLDIiIiIiIiIiFisJdPXfyra7gA8BB0p6+0BPaHFTA0vnAj8ERgGrAwdTDgno6bmdab+d9kfA/cBLgLHAGygnSbZzObCl7ZWAl9b+FstgYEREREREREQsXAl0LSDbVwA3AJtIeo2kKyTNkHRvzThaBp6TCdacoTRZ0u7t+pV0pKQ7Jc2UdK2krRdkfpL2kHRLzab6raQxTfcs6bOSbpP0oKTvSlqi6f7HJN1YM6gukrR2vf7lpoy2bklPSjqxzfAb1Hd0uu15tufYvtj29T3MdyXga8CX29xeFzjL9lzb04ELgY3b9WP7TtsPNl2aB6zXadyIiIiIiIiIGDpSjH4BSBLwOkqwZQolmPJ54BpgDeACSsbRDxag+6uBQ4BHgc8BZ0tax/bcfszvTcA3gbdSgnHfA84AXt/U7D3AOKAL+ANwE/BzSTsA+wHvBP4D/H/27jtarqpu4/j3oRtuIBQNhi5NgVeCBlEBiWIBFcWKBgSkWHh5FQUrIkXBCiI2UOmIoiIoKIIt0tUAQUWpElpIJIEEbgoIPO8fe1+cDDNz7027Jc9nrVmZc3Y5v3Pm4lr+1m/v80ngh8DLbX8Z+HK9xvrAn4AftwjhNuBJSWfV615n++Fewj4e+A4wrUXb14F3SZoIrAHsBhzZ4f53BH4JrAbMrffab7fOnTtkN0zveR19RERERERExLIkFV39NwN4CPg+8Enbv7N9ve3rbD9hewpwKmV5Xb/ZPtf2zDrXCcDKwBb9nGYv4HTbN9h+DPgU8DJJGzX0+ZLth2zfQ0nIvbuefz/wBdv/tP0EJQE1tqeqC0DSs4CLgK/b/lWLe3gE2BEw8D3gwVpV1vL96JLGATtQljq28kdKUvER4D5KQvGidjdv+6q6dHE94CvAlHZ9h6u8jj4iIiIiIiKWRano6r+1awLoaZI2B06kVEiNoDzX6xdmckmHAQcCYyiJotWAtfs5zRjghp4D292SZlL2yppST9/b0P/uOgZgQ+Drkk5oDKuOvbsenwbcavtL7QKw/U9gv3pPzwfOZcGEGrVtOcoeXB+2/UQplntG+2WU5OHLKRVopwNfovUyx8YY7pf0a0pV2Ys69W1lixEj8nr6iIiIiIiIiCEkFV2Lx3eAW4DNbK9GWfrXk7GZU/8d0dB/nVaT1P24PgG8E1jD9ijKEka16t/BVErCqmfeVYG1gPsb+qzf8H2DOgZKAuz9tkc1fJ5l+5o61ycpFWYH9DUY27cAZwJbt2hejZIgPF/SNMrSTYD76vNYs8b6TduP2Z4JnAG8vo+XXwHYpK+xRkRERERERMTQlUTX4jGSsqyuu1YvfbCnwfaDlATT3pKWl7Q/7RMvI4EngAeBFSR9lpII6mR5Sas0fFYCzgPeK2mspJUpyw//VJdV9viYpDXqXlsfBs6v508BPiVpKyibxEt6R/2+G/AhYA/b89oFJOn5kg6TtF49Xp9SyXVdi+6zKdVkY+unJ4H14hrzDOAu4IOSVpA0CtgXuKnNtfeStIGKDYHjgN+1fXoRERERERERMWwk0bV4HA5MAB6l7El1flP7QcDHgJmUvaauaTPPZZSN7G+jLBOcz4JLDFv5JDCv4fN727+jbNZ+AfAAJbH2rqZxP6csr5xM2bj9NADbF1KWBf5I0iPA3ymbvwPsCTwb+GfDmxdPaRHTo8D2wJ8kzaEkuP4OHNbc0cW0ng8lyQcw3fbj9ftbgV1r2x2UZOBHAGpSq1vSBrXvlpTn2w1cTdlk/6AOzy8iIiIiIiIihgnZHugYBiVJ84HHgJNtt33D31AkyZRllncMdCxLm6TfAC8F/mx7l059x40b50mTJi2dwJZBPW+0zD5osTTl7274y28cS1v+5mK4GT++/Dtx4kBGERHRmaTrbY9r1ZbN6NuwvcpAxxCLn+3XDHQM8V+Tu7uf/j8Iw8mE0aN535gxvXeMiIiIiIiIxSpLFyMiFqPJ3d2cN336QIcRERERERGxTEpF1zLIdn/f4hixRIzt6hp2Sz2GY4VaRERERETEUJGKroiIiIiIiIiIGBaWqUSXJEuaI+m4JTR/zxsAl18S8w82kiZKOnCg4+gPSQfU38iSNh3oeCIiIiIiIiJi8VmmEl3VNraPAJC0UU14rFCPJekbkm6RtG5/J7Z9j+0u20/2d6yk8ZKeqkmYbkn3Szqmv/MMFpJGSTpd0jRJj0q6TdIn+jBu3/qbHNh0/nmSLqlzzZD05Tbjd2p4hj0fS3obgO3TbHctnruMiIiIiIiIiMEke3RVkgScCrwM2Nl2v3aTlrSC7ScWMYyptter820MXCnpRtsX9XciScsvTMKtzVwCZPupfgz7GrAq8AJgNrA5sHUv11kD+BRwc9P5lYDfAN8C9gSerPM9g+0rga6GseOBi4Ff9yN2AG6dO3fQ77eUt/tFRERERERE/NeyWNHVyvLAmcA4YHxPkkvSGyTdKOkRSfdKOrpnQEM12AGS7gF+36JCbKKkz0m6ulYiXS5p7b4EZPsu4Bpgy4ZrPl/SbyQ9JOlWSe9saDtT0nck/UrSHOCVkqZIOlzSXyXNlnS+pFVq/zVqhdSDkh6u39drmG+ipOMkXQ3MBZ4n6TW12m22pG8CnTa13w44z/bDtp+yfYvtn/Zy218ATgZmNJ3fj5IEPNH2HNvzbf+1t2dY7Qv81PacPvYfMvJ2v4iIiIiIiIgFpaKr+AGwPvAq27Mazs8B9qFUGG0N/EbS5KYKq50pVUtPAaNbzD0B2A24F7gUOBz4ZG8BSdoM2AE4pR6vSqlq+myd74XA5ZJutt1TATUBeD3wRmCleu6dwK7AfOBqStLoFEqS84zavjxwOvBNYI+GMN5Tr3UrsAZwAbA/8HPgEOADwDltbuE64LhapXWV7dt7ud+XUBKNB9eYGr0UmCLpUkoC7e/A/9n+Wy9zjgDeDuzeqV87W4wYMajfCDjYq80iIiIiIiIilrZUdBWvBX7clOTC9kTbf6sVSX8FfkhJbDU6ulYZzWsz9xm2b6vtPwbGdohjjKRZkh4BbgP+BFxV294ITLF9hu0nbN9ASTy9vWH8z21fXeOdX8+dbHuq7YcoS/jG1nubafsC23NtPwoc1+LezrR9c12SuRvwD9s/tf0f4CRgWod7+T9KAvEQ4B+S7pC0W6uOdfP+b1OSV62WR64HvItS7TUG+CXw87qksZO3UarD/thLv4iIiIiIiIgYBpLoKt4IHCVp/8aTkraX9Ie6vG82pYKpeenhvb3M3ZgMmkvD/lEtTLU9yvZqwChgHnBWbdsQ2L4mwmZJmgXsBazTSywtry9phKRTJd1dE2tXAKO04BsjG+cb03hs222u19M+z/bxtl8MrEVJ8v1E0potuh8M/NX2tW2mm0epCrvU9uPAV+ucL2h3/Wpf4Owaa0REREREREQMc0l0FddQlrd9XdKEhvPnAb8A1re9OmXJX/O+VEskiWJ7dr1+z7K7e4E/1kRYz6fL9gcXMpbDgC2A7Wti7RX1fOP9Nc73AGV5Z+lUNqhfnz6w/QhwPGVz+o1bdNkFeEt9Q+M04OXACXUfMIC/0s/nLGl9YDxwdn/GRURERERERMTQlURXZfuPwFuB70rqWQ44EnjI9vy6h9SEthMsZpK6KMv1evbfugTYXNJ7JK1YP9tJ6q2qqZ2RlEqpWbXK6qhe+v8S2ErSW+tm+x9iwWqy5viPrPGtVDfA/zAwi7LfV7P9KNVZY+tnEnAMcERtPxd4qaRX14qzQylLEv/ZId73ANfYvrOX+4qIiIiIiIiIYSKb0Tew/RtJewLnS3qMsqSup7Loj5Tld6OWYAhjJHXX749RNnTfq8b2qKTXAifWz3LATcBHF/JaJ1EqxmYAU4ETWHAj+gXYniHpHZR9ss6gbEJ/dYf5XfttADxBqcp6g+3uZ3Rs2htN0uPAI7WqDdu3StqbUlH3HOAG4E11GSN1k/orbR/fMM0+wFc6xDcsTO7uHrKb0k/u7mZsV6eVvBERERERERH9s6wluh4Drpd0su0jbU+haSmi7V+y4D5aP201UZuxC5yzPb6p/UzgzDbzTaSXCjvbtwJvaNO2X4tzGzUdH93wfSplaV+jUxvam9uw/Wtg804xNvT9PPD5vvRtMbbVtX8G/KxN/2dscm/7+a36Snov8DXK30Krje9jKRnb1cWE0a1eVBoRERERERGxcJapRJftVQY6hhhYts+gVJoNC2O7upi47bYDHUZERERERETEoJA9uiIiIiIiIiIiYlgY0okuSZY0R9JxA3T9UyQdORDXHgzq8990oOPoD0lnSpon6b6BjiUiIiIiIiIiFq8hneiqtrF9BICkjWry5YbGDpLWlvS4pCkLexFJ+0m6qvGc7Q/Y/tzCztnhWuMlPSWpu37uk/RjSdst7mstKZK2knS5pIclzZJ0vaTX92HcGa0SaPWNizfUxOa9kt7ZZrwkHSHpHkmPSPqRpNV62uteZs/Y0ysiIiIiIiIihr7hkOhqZVVJWzccTwDuWtjJJA3EXmZTbXcBI4GXArcAV0raZWEmG4B7uBj4DTCa8qbEDwGPdBogaUdgkxbnt6S8IfIIYHVgLHB9m2n2Ad4D7ACMAZ4FfGOh7iAiIiIiIiIihpThuhn9OcC+wMfq8T7A2cBBPR0kfbIePwe4FzjC9oW1bb/a9uc6zx8obztcUVI38ITtUZLOBO6z/RlJ44FzKW/0+wTwJPDpuvk5kt5AeQvhJsBs4LTGtyC2Y9vAfcBnJa0JfAkYJ2kjSvJuRdtP1GtMBM61/f0W9/BtSWcA3wO2AQxcBvyv7Vl1/BTgm/V5bQj8GtjX9vza/jHgo3XsZ9rFLGltYGPge7Yfr6ev7nSfNRH3jRrrTU3NnwFOtX1pPZ5ZP63sTnm299Z5vwT8XtIHbc/tFEOzW+fOZfyNN/ZnyFI1ububsV1dvXeMpW5yd/dS/9uZMHo07xszZqleMyIiIiIiYrAZrhVd5wLvkrS8pBdQqqL+1NTnTmAnSoXQMcC5kp7b0L498C9KImxv4APAtba7bI9qc9116nzrAgcA35K0Rm2bQ0kgjaIkzT4oaY9+3tfPgBdJWrWP/Rvv4ThAwBcolU4vANYHjm4a805gV0qi6oXAfgCSdgUOB14DbAa8usN1ZwJ3UJ7pHpJG9yHWjwBX2P5ri7aX1hj+JukBSefWpF8rqp/G45VrzMPK2K4uJozuy6ON4W5ydzfnTZ8+0GFEREREREQMuOFa0XUfcCslGfNKSjXXAmz/pOHwfEmfAl4C/Lyem2q7Z8nbE5Log/8Ax9YKq1/V6q8tgOtsT2zo91dJPwR2Bi7q813BVEripl2i7Rn9G++Bkny6ox4/KOlE4KimMSfbngog6WLKMkEoCbAzbP+9th0NvLvVRW1b0iuBTwInABvX/c0OsH17c39J6wPvB17c5j7WoyxHfC3lGZxFqf7aq0XfS4GPS/ox8DClug5gRJu529pixAgmbrttf4dFMLara6n+7QzmysOIiIiIiIilabhWdEFJbu1HScac29woaR9Jk+tG6bOArYG1G7rcuxDXnNmzjLCaC3TV620v6Q+SHpQ0m1IhtnarSTpYl7JscFYf+y9wD5KeUzdnv1/SI5Tn0hzDtFbxU6rAGue7u9OFbd9n+xDbm1CWQc6hRcKxOomSIJzdpn0eJcl2m+1u4Hig3cb2pwM/BCYCN1OWnUJJfkZERERERETEMDacE10XUJYI/sv2AkkZSRtS9qo6BFirLkX8OwsueXPTfM3H/XUe8AtgfdurA6c0Xa8v3gLcYHsOJXEEC1YqrdPUvznmL9RzL7S9GmVJZl9jeICy1LHHBn0cR90v61uUZGIruwBfkTRNUk+i7VpJE+r3v9LH52/7KdtH2d7I9nqUZNf99RMRERERERERw9iwTXTVZNCrgANbNK9KSZw8CCDpvbRPwvSYDqwnaaWFDGkk8JDt+ZJeQnkTZK9UrCvpKMq9fBrA9oOU5M3edS+y/WnxxsIWMXQDsySty3836++LHwP7SdpS0gieueSxMeY1JB0jaVNJy9XN6fcHrmszZHPKBvlj+e9Syd2BC+v3M4D3SnpevfYngEvaXHtNSZvU57YlcCKlWuypftxrRERERERERAxBwzbRBWB7ku07W5z/B2XvqGspCaz/oZe3AgK/p1QHTZM0YyHCORg4VtKjwGcpiaNOxtQ9vrqBv9QYx9u+vKHPQZRk1UxgK+CaXuY8BngR5a2Pv6Rsbt8n9Y2HJ1Gewx3133YeBzYCfgs8QqmWe4y6sX2Luf9te1rPp56eYXtebT+dsuzxT5Qlk48BH+oZL6lb0k71cG3gV5SKt0uB021/t6/3GRERERERERFDl+xFXZE3cCTNpyQ9TrZ95EDHE4OfpNOAdwD/tr1pp77jxo3zpEmTlk5gMWz0bAw/EJvR5+UJvcuzGv7yG8fSlr+5GG7Gjy//Tpw4kFFERHQm6Xrb41q1Dem3LtpeZaBjiKHF9gHAAQMdR0REREREREQsfsN66WJERERERERERCw7kuiKiIiIiIiIiIhhYcgnuiRZ0hxJxy3k+E9L+n79vlGdb4V6PFHSgfX7XpIu7zTXskTSmZI+P9Bx9IekV9eN65+S9OqBjiciIiIiIiIiFq8hn+iqtrF9BICkyyR9vKdB0ro1edXq3Dq2j7d9YG8XsP0D269dMuEvSNIUSfMkPSpplqRrJH1A0pD4vSStJOkESffVxNJdkr7Wh3E719/l8w3nnivpF5Km1raNepljI0l/kDRX0i2NCS3bv7XdBdyzCLcXEREREREREYPUkEic9NMVwM4Nx68Abmlx7nbb05ZmYP20u+2RwIbAF4FPAKctzEQ9FWpL0aeAccBLgJHAK4EbOw2QtCLwdeBPTU1PAb8G3tbHa/+wXmst4Ajgp5Ke3efIIyIiIiIiImLIGtJvXWzjCuBjkpaz/RSwE3AScGzTuSsAJB0NbGp7706TStoPOND2jvX468BbgdWB24FDbV/ZMOdWwGPAm4EplETN24CP1PMH2O51KaTt2cAvJE0DrrwkncYAACAASURBVJN0gu2/S5oInGu7Z9llc3wGDgEOpfzOG/ch5i2B+cBbKFVP+9qeVNu3pSTaNgN+BbhD2NsBF9qeWo+n1E8nhwGXA89puv/pwLf7kqyTtDnwIuC1tucBF0g6lPLcT+ltfLNb5859+pXhy4oJo0fzvjFjBjqMiIiIiIiIiIUyHCu6/gysDGxTj18B/Aa4o+ncFYt4nb8AY4E1gfOAn0hapaF9d+AcYA1KhdFllOe9LnAscGp/Lmb7z8B9lCRdX+0BbE9JYPUl5jcBPwJGAb8AvgllKSJwUb2fNYGf0LnC6jrgo5IOlvQ/ktQpSEkbAvtTnsui2Ar4l+1HG87dVM9HLyZ3d3Pe9OkDHUZERERERETEQht2FV22H5P0J+AVku4GRtn+l6QrG85tCfxxEa9zbsPhCZI+A2xBSawAXGn7MgBJP6FUUn3R9pOSfgR8V9Io27P6cdmplERTX33B9kP9iPkq27+qMZ9DqQYDeCmwInCSbVOWA36003WBh4G9gK8BMyV9yvZZbfqfDBxpu7uXnFhvuoDZTedmU5KL/bbFiBFM3HbbRYlnSFnWqtciIiIiIiJi+BmOFV1QqrVeQal+uqqeu6rh3L22716UC0g6TNI/Jc2WNIuyHHDthi6NpTHzgBm2n2w4hpKY6Y91gYd67fVf9/Yz5sY9y+YCq9Qlg2OA+2uSq0fb52f7Sdvfsr0DpTrsOOB0SS9o7itpd2Ck7fP7cV/tdAOrNZ1bDXi0Rd+IiIiIiIiIGGaGc6JrJ0pi68p67mpgBxbDskVJO1E2h38nsIbtUZTKoUUqR+rlmttREl09ibs5wIiGLuu0GPZ0YmoRY34AWLdpCeIGfYnb9jzb36JUeG3ZossuwDhJ0+o+ZHsCh0r6eV/mb3Iz8DxJIxvObVPPR0RERERERMQwN1wTXddQKon2pia6bD8MPFjPLer+XCOBJ+p8K0j6LM+sJFosJK0m6Y2UvbPOtf232jQZeKukEZI2BQ5YgjFfW8d+SNIKkt5KeaNiu5gPlTRe0rNq/33r9VutjTsS2Jyyd9hYyt5g3wPe2zDfKpR91wBWbtpX7Gm2b6M8l6MkrSLpLcALgQv6eJ8RERERERERMYQNy0SX7bnA9ZTkyN8bmq6kvNVvURNdlwGXArdRlvDNp2mZ4GJwsaRH67xHACfSkPyh7H31OGWJ5FnAD5ZUzLYfp+wxth+lMmtP4GcdhswDTqAshZwB/C/wNtv/ajH3o7an9Xzq2DmNe4vVc931+y38d+knkk6R1PhGxXcB42qcXwTebvvBvtxnRERERERERAxtWnDbpaFH0nzgMeBk20cOdDwxeEnahVLdtTLwett/6NR/3LhxnjRp0lKJbTAYf+ONTO7uZmxXf7eOi0Y9z3Bpvsggv13fDcTvE0tXz4s18hvH0pK/uRhuxo8v/06cOJBRRER0Jul62+NatQ35ty7abrmMLaKZ7d9RlrRGLDFju7qYMHr0QIcRbeT3iYiIiIgY3oZ8oisiFp9Uugxd+e0iIiIiIiKG6R5dERERERERERGx7BmWiS5JljRH0nGLYa6N6nypfmtQ36p430DH0V+S7pT0uKRzBzqWiIiIiIiIiFi8hmWiq9rG9hGwQLKqu36mSPrkQATVl8SZpKMl/UfSo/Vzm6RvSnru0ox1UUh6s6TJkh6RNEPS7yRt1MuYlSTd0pxAq7/XvIbf7/IOc6xc38Q4XdJDki6WtG5Pu+1NgOMX8fYiIiIiIiIiYhAazomuVkbZ7gLeDhwp6TVL8+L9rAo73/ZIYE3gLcA6wPULm+yStPzCjFvIa20KnA0cBqwObAx8G3iql6EfA/7dpm13213189oOc3wYeBnwQmAMMAv4Rj/Cj4iIiIiIiIghaplcjmd7kqSbgbHAbyQtB3waOAh4FvBr4P9sz24Ytr+kowEBX7V9AkAd+/E6dhTwO+ADth+qFUx3AQcCRwFTgI3qfLMkAbzG9rUdYv0PcLOkPYEbKMmjwyXtBxxoe8eevpIMbGb7DklnAvOADYGdgTdLWhn4PLAJMBs4zfbRdWxPrPsBnwNGAF+zfVxtfxbwHeDNwAPAGR0e8VjgrvqWQ4BHgQs69EfSxsDewEeB73Xq24uNgctsT6/z/gg4cWEmunXu3KdfGb4smNzdzdiuroEOIyIiIiIiImKhLWsVXQBIeimwNXBHPbVf/bwSeB7QBXyzadgrgc2A1wKflPTqev5DwB6UZNIY4GHgW01jdwZeALwOeEU9N6pWJ7VNcjWy/STwc2CnvvSvJgDHASOBq4A5wD6UhNwbgA9K2qNpzI7AFsAuwGclvaCeP4qSINuk3se+Ha57A/B8SV+T9EpJfcmefIOSbJzXpv0Hkh6UdLmkbTrMcxqwg6QxkkYAewGX9uH6y7yxXV1MGD16oMOIiIiIiIiIWGjLWkXXjFrVtApwAnBRPb8XcKLtfwFI+hTwd0nvbRh7jO05wN8knQG8G/gt8H7gENv31bFHA/dIek/D2KPrWGoV18KaSlnK2Fc/t311/T4fmNjQ9ldJP6Qk4S5qOH+M7XnATZJuArYB/gm8EzjY9kPAQ5JOBj7b6qK2/yVpPKU668fAyFpZdYjt7ub+kt4CrGD7wjqu2V6U5JkoSxMvk/R827Na9L0NuAe4H3gS+BtwSKs4e7PFiBFM3HbbhRkaEREREREREQNgWavoWptSrXU4MB5YsZ4fA9zd0O9uShKwsbzl3qb2MfX7hsCFkmZJmkVJCj3ZYeyiWBd4qB/9F7iupO0l/aFWRs0GPkB5Jo2mNXyfS3leUO63+Rm0Zfs62++0/WxKFdorgCOa+0laFfgy8H8d5rra9jzbc21/gbLvVrvKtu9QEplrAasCPyMVXRERERERERHLhGUt0YXtJ+v+WvOBg+vpqZSEVY8NgCeA6Q3n1m9qn1q/3wvsZntUw2cV2/c3XrbN9z6re4HtDlxZT82h7KPV075Oi2HN1zoP+AWwvu3VgVMoVVJ98QDPfAZ9YvsvlITT1i2aN6PsW3alpGm133MlTevwlkbTPu5tgDNtP2T7McqSyJdIak7oRURERERERMQws8wluhp8Efi4pFWAHwIfkbRx3U/qeMpbD59o6H+kpBGStgLeC5xfz58CHCdpQwBJz5b05g7XfZDy9sHn9SVISSvWfbJ+SHnzYs/G6jcBW0kaW+/h6D5MNxJ4yPZ8SS+h7OHVVz8GPiVpDUnr0aECS9KOkg6S9Jx6/HzgTcB1Lbr/nZJAG1s/B1ISjGOBeyVtIGkHSStJWkXSxyhVaFe3mAvgL8A+klaXtCIlmTnV9ox+3GtEREREREREDEHLcqLrl5SN4w8CTgfOAa6gvHlwPs9M5PyRsnn97yhvXby8nv86pUrqckmPUpI527e7qO25lA3ir67LHV/apuuekropy/R+AcwEXmx7ap3nNuBYyj5ht1M2m+/NwcCxNc7PUpJXfXUMZbniXcDllOfVzixKYutv9R5+DVxIWaK4ANtP2J7W86EszXyqHj9JSc59h/Jb3Q/sSqmgmwkgaad6jR6HU36/2ylJxdcDb+nHfUZERERERETEECV7oVbSDWqS5gOPASfbPnKg44nBQ9KtlL3Ofmx7/059x40b50mTJi2dwCIWwfgbbwTIyxMiyH8PsfTlby6Gm/Hjy78TJw5kFBERnUm63va4Vm3D8q2LtlcZ6BhicLK9xUDHEBERERERERFLxrK8dDEiIiIiIiIiIoaRQZPokmRJcyQdN9CxLAxJN0saP9BxLApJ4yXdN9BxLEmSjql/Z5Y0LCsaIyIiIiIiIpZVgybRVW1j+wgASRvVZMQvGztIOlfS0QMSXQe2t7I9sVWbpDPrvbyp6fxJ9fx+fbmGpAmSJknqlvSApEsl7biwMddrb7qw43uZez1JF0iaIWm2pL+1u09JW9b7erh+fitpy4b2lSWdImm6pIckXSxp3TZz9fzddDd8nt6nzfZRwFaL+34jIiIiIiIiYuANtkRXKy+VtMNAB7EY3Abs23NQq4neAdzZl8GSPgqcBBwPjAY2AL4NvLm/gSylSqZzgHuBDYG1gH2A6W36TgXeDqwJrE15y+SPGto/DLwMeCEwhvJWx2/0cv1Rtrvq53MLexMRERERERERMXQMhaVbXwY+D7yyuUHSGpSEyvaUe7ka+IDt+2r7ROBK4FWUJMm1wATbM2r7T4CdgGcBNwEftH1zbTsTmAtsXPvcBLwN+CQlYTUdeLftG2v/KcCBtn/b5j4uBvaWtIbth4Fdgb8CI5vu6SDgo8B6lETR3pRk2LHAe23/rGnOi+u4lwBfB14AzAMuAD5q+/HabuAQ4FBgBUn31jluqm0H1HtC0mHAJ4AngU/bPkPSdsAlwLq2n6j93gYcaXtsi/vdDviI7Tn1+MY2zwXbsyjJKySpXrex0mxj4DLbPfH9CDix3XyLy61z5z79JqWIwWxydzdju7oGOoyIiIiIiIgBNxQqur4FbC7p1S3algPOoFQNbUBJ8Hyzqc8E4L3Ac4CVgMMb2i4FNqttNwA/aBr7TuAzlCqjxyiJshvq8U/pX7JlPqVS6V31eB/g7MYOkt4BHF3bVgPeBMykVDOtAlzYYf4ngY/U2F4G7AIc3NRnD0pScEvbr6jntqlVT+fX43WA1YF1Kcmvb9Xk3F9qLK9pmG9vSqKxlevq2HdJ2qBD3E+TNIvynL5BqVzrcRqwg6QxkkYAe1F+u07ulnSfpDMkrd2X60cMVWO7upgwevRAhxERERERETHghkJF13zgOEpV1wLVUrZnUiqXAKgb2f+hafwZtm+r7T+mJI96xp/eMPZo4GFJq9ueXU9faPv62n4hcLDts+vx+ZQKqf44G/iKpPOAnSmVYf/b0H4g8OWaVAK4o15rR2BGTyVVKz1xVlMknVqvcVLD+S/YfqiXGP8DHFuv9StJ3cAWlMTVWZTk1qWS1gRexzOTaT3eQakKOxJ4vqS/AQc13FurexglaVXKc7m7oek24B7gfkpC72+0f/YzKNVkkylLJr9FSWC+rpf7foYtRoxg4rbb9ndYRERERERERAyQoVDRBfA9YLSk3RtPShoh6VRJd0t6BLgCGCVp+YZu0xq+zwW66tjlJX1R0p117JTap7H6p3FPqXktjvu1Vsj2VcCzKVVil9ie19RlfVrv2TUTWLvT3lqSNpd0iaRp9X6OZ8F7gbIUsjczmxJqTz8z4Fxgd0ldlGq3K20/0GoS2w/b/qTtrSh7ik0GLqpLE9uqSx1PAc6W9Jx6+juUira1gFWBn9Gmost2t+1Jtp+oSx0PAV4rabVe7zwiIiIiIiIihrQhkeiy/R/gGOBzQGOi5DBKtdH2tlcDepbjdUymVBMoG7m/mrJUb6N+jF0U51LiPrtF273AJi3OX0upbNujw7zfAW4BNqvP4tM8817c72gbB9v311jeAryH9ssWm8fNAL5K2Uh+zT4MWQ4YQVk+CbANcKbth2w/Rlna+JI+Lknsuecl/btGRERERERExAAbEomu6hxgZcom7j1GUiqrZtWldEf1Y76RlH23ZlKSKsd37r7YnEzZ5+qKFm3fBw6X9GIVm0rasC6l/Cxlz6s9aiXbipJ2k/TlOnYk8AjQLen5wAf7EMt04Hn9jP9s4OPA/9BhzzBJX5K0taQVJI2s8dxRl5s2932NpG1rld1qlL3PHgb+Wbv8BdhH0uqSVqQsl5za81KBprm2l7SFpOUkrUV53hMblqNGRERERERExDA1ZBJdtp+kJLIaK4JOorwxcQZlD6lf92PKsyn7QN0P/KOOX+JqVdLvbD+jusr2Tyj7kZ0HPApcRL1f2ydS3sb4GeBBSvXXIbUPlE32J9Rx3wPOp3dHA2dJmiXpnX28hQspm/9f2PBGxVZG1L6zgH/VMW9q03cU8ENgNmXp5qbArrbn1/bDKRVtt1Pu/fWUqjIAJN0saa96+DzK38GjwN8pycx39/HeIiIiIiIiImIIU4t8y4CQNJ+SlDjZ9pEDHU+0J+lO4P22f9tr50FG0lGUhOHKwKo1gdrSuHHjPGnSpKUWW0RELLrxN94IkJeJxFKTv7kYbsaPL/9OnDiQUUREdCbpetvjWrUNmrcu2l5loGOI3kl6G2Xfq98PdCwLw/YxlP3eIiIiIiIiImKYGTSJrhj8JE0EtgTeY/upAQ4nIiIiIiIiImIBg3aPLkmWNEfScUvhWpdK2ndJX2eosz3e9nNsXzbQsSwsSWdKmifpvoGOJSIiIiIiIiIWr0Gb6Kq2sX1Ez0FNfm26KBNKOlrSuY3nbO9m+6xFmbfNtUZJOl3SNEmPSrpN0icW93UGE0njWyWRJE2UdGAfxp/R/DvX5NTjkrobPst3mGOCpLtrovSi+kZOAGzvB+zW/zuLiIiIiIiIiMFusCe6hrqvAV3AC4DVKW8dvHNAI1oIkpbKEldJOwKbtGn+su2uhk/LTeQlbQWcCrwHGA3MBb69RAKOiIiIiIiIiEFlyCa6apXP5xuOF6gkkvQJSffXSqpbJe0iaVfg08CetSroptr36WojSftJukrSVyU9LOkuSbs1zLu6pNMkPVDn/3yH6qLtgPNsP2z7Kdu32P5pnWejWrm0QsPczXFcLelrkmZJ+pekl9fz90r6d+Nyy/o8vl2XYXbXsetIOqnexy2Stm3oP0bSBZIerPf4oYa2oyX9VNK5kh4B9pP0EkmTJD0iabqkExfyp2upPodvAIcs4lR7ARfbvsJ2N3Ak8FZJIxc1xoiIiIiIiIgY3IblZvSStqAkTLazPVXSRsDytu+UdDywqe29O0yxPXAWsDbwPuA0Sevadj0/HdgUWBW4BLiXUkXU7DrgOElrAFfZvr2ft7I98H1gLcqbAn8EXFyvvTNwgaQLakIH4J3A64CbgV8B1wJHAYfV8ScCr5S0XJ3n58C7gfWA30q6tWH/rTcD7wD2AVamvGXx67bPkdQFbN3Pe+nNR4ArbP9VUqv2gyUdDNwFHG/7gjbzbAVc03NQf/PHgc2B6/sT0K1z5z79yvCBMGH0aN43ZsyAXT8iIiIiIiJiqBmyFV29eJKSnNlS0oq2p9juz5LBu21/ry6POwt4LjBa0mjK/k6H2p5j+9+U5YnvajPP/wE/oCTd/iHpjsbqsD64y/YZNY7zgfWBY20/Zvty4HFK0qvHhbavtz0fuBCYb/vshvE9FV3bAc+2faztx23/C/he031ca/uiWok2D/gPsKmktW13276uQ9xjahXa0x9gx3adJa0PvB/4bJsuJwObAc+hVGidKWmHNn27gNlN52YDQ6qia3J3N+dNnz7QYUREREREREQMKcOyosv2HZIOBY4GtpJ0GfBR21P7OMW0hrnm1gqjLmBNYEXggYaqo+UoFV2t4pgHHA8cL2k14JPATyRt0Mc4GjMd8+qczee6OvRv13dDajKqoX154MqG4+Z7OgA4FrhF0l3AMbYvaRP3VNvrNZ6QNLFNX4CTKAm85gQVALZvaDj8laQfAG8Frm7RvRtYrencasCjHa7f0hYjRjBx221777gEDGQlWURERERERMRQNZQruuYAIxqO12lstH2e7R0pSR0DX+ppWoRr3gs8Bqxte1T9rGZ7q94G2n6EkvRaFdi4xk+ne1iC7qVUi41q+Iy0/fqGPgs8J9u32343parqS8BPJa26mOLZBfhKfTtlT5LxWkkT2vQ30HJ9I2XZ5jY9B5KeR6nuu20xxRoRERERERERg9RQTnRNBl4vaU1J6wCH9jRI2kLSqyStDMynVDP1vKVvOrBR3aeqX2w/AFwOnCBpNUnLSdpE0s6t+ks6UtJ2klaStArwYWAWcKvtB4H7gb0lLS9pf9q/cXBx+zPwSN2w/1n1+ltL2q7dAEl7S3q27aco9wD/faaLanNKcmps/QDsTll+iaS3S+qqz/u1wN7AL9rM9QNgd0k71UTcscDPbPe7oisiIiIiIiIihpahmOjqqTQ6B7gJmEJJPp3f0Gdl4IvADMoyxOdQ3rYI8JP670xJjUvi+mofYCXgH8DDwE8pe3i1i/WMGsdU4DXAGxo2jz8I+Bgwk6ZN1JekumfX7pSk0l01vu8Dq3cYtitws6Ru4OvAu+peYIsjnn/bntbzqadn1KWfUBKE91MSbF8BDrI9sWd8fcvkTnWum4EPUBJe/6bszXXw4ogzIiIiIiIiIgY3lRcJDj6S5lOWCZ5s+8i6x9VsYA3bszqPjmhN0mmUt0n+2/amnfqOGzfOkyZNWjqBNenZo2ug9giLiBiq8r+fsbTlby6Gm/Hjy78TJw5kFBERnUm63va4Vm2DdjN626s0ndoTuDNJrlgUtg+gbKw/6E3u7l4mNqWfMHo07xszZqDDiIiIiIiIiGFg0Ca6Gkm6BhgFHDjQsUTE4jO5u6ziTaIrIiIiIiIiFochkeiy/fKBjiFiaRvb1TXsl0EsCxVrERERERERsfQMxc3on0GSJc2RdNxSuNalkvZd0teJxU/S5nXj+iclpTowIiIiIiIiYpgZFomuahvbR/Qc1ORXx83GeyPpaEnnNp6zvZvtsxZhzgmSJtWEywM1cbbjosQ5mEia2JxEkjRe0n19GLuZpPmNz1zSXvVZ9Xzm1t/2xW3mWFPShTXxebekCT1ttm+z3QVcuQi3GBERERERERGD1HBKdA16kj4KnAQcD4wGNgC+Dbx5IeZ6xrLTVueGmG8Bf2k8YfsHtrt6PsDBwL+AGzrM8Tjl+e4FfEfSVksw5oiIiIiIiIgYJJaJRJekMyV9vuF4gQojSZ+QdL+kRyXdKmkXSbsCnwb2rJVEN9W+T1csSdpP0lWSvirpYUl3SdqtTQyrA8cC/2v7Z7bn2P6P7Yttf6z2eYmkayXNqtVe35S0UsMclvS/km4Hbu+5jxr/NOAMSWtIukTSgzWmSySt1zDHfpL+Ve/1Lkl7NbQdJOmfte0fkl5Uz7+g3vcsSTdLetPi+F2ans+7gFnA73rpui9wtm23mGNV4G3Akba7bV8F/AJ4z+KONyIiIiIiIiIGn6FeAbTIJG0BHAJsZ3uqpI2A5W3fKel4YFPbe3eYYnvgLGBt4H3AaZLWbZGIeRmwCnBhh7meBD4CTALWAy6lVDCd1NBnj3rNefXfdYA1gQ0picsRwBnAO4HlgdOBbwJ71ETQyfVeb5X03DoWSe8Ajq7zTwI2Af4jaUXg4jrPa4EdgZ9LGmf71g730meSVqMkAXcBDujQb0PgFcD+bbpsDjxp+7aGczcBOy9MXLfOnTtgm6VP7u5mbFfXgFw7IiIiIiIiYqhaJiq6evEksDKwpaQVbU+xfWc/xt9t+3u2n6QkvJ5LWTbXbC1ghu0n2k1k+3rb19l+wvYU4FSemaT5gu2HbM+rx08BR9l+zPY82zNtX2B7ru1HgeOa5ngK2FrSs2w/YPvmev5A4Mu2/+LiDtt3Ay8FuoAv2n7c9u+BS4B3d3gmJ9fqr1mSZtX+nXwOOM32vb302we40vZdbdq7gNlN52YDI3uZd9AZ29XFhNGt/owiIiIiIiIiop1lvqLL9h2SDqVUM20l6TLgo7an9nGKaQ1zzZUEJeHSbCawtqQV2iW7JG0OnAiMo1RmrQBc39StORn0oO35DXOMAL4G7AqsUU+PlLS87TmS9gQOp1SeXQ0cZvsWYH2gVYJvDHCv7acazt0NrNvqHqoP2f5+Q0zjgXNbdZQ0Fng1sG2H+XrsQ9nfrJ1uYLWmc6sBj/Zh7mfYYsQIJm7bl7AiIiIiIiIiYjBYVhJdcyiJox7rNDbaPg84ry6hOxX4EmVfp2fsA7UIrgXmU5YG/rRNn+8ANwLvtv1oTcC9valPc0zNx4cBWwDb255WE0k3AgKwfRlwmaRnAZ8HvgfsREmgbdIipqnA+pKWa0h2bQDc1qLvwhgPbATc05AkXF7SlrZf1NNJ0g6UpFu7Z0eNaQVJm9m+vZ7bBri5w5gYYJO7uwdsiehQMGH0aN43ZsxAhxERERERETEkLCtLFycDr5e0pqR1gEN7GiRtIelVklamJKLmUZYzAkwHNpK0yM/J9mzgs8C3JO0haYSkFSXtJunLtdtI4BGgW9LzgQ8uxKVGUu5hlqQ1gaN6GiSNlvSmulfXY5QKqJ57/T5wuKQXq9i07on1J0qi8OM13vHA7sCPFiK2Vr5LSbCNrZ9TgF8Cr2vqty9wQV2O2ZLtOcDPgGMlrVqTY28GzllMsUYsVZO7uzlv+vSBDiMiIiIiImLIGO4VXT3VTudQlsdNqZ8zKJVPUPbn+iLwAuA/wDWUTeUBfgLsDcyUdFdjhdFCBWOfKGk68BngB5QldddT9tGCsqTwu8DHKVVY5wOv6udlTgLOA2ZQqrFOoFSRQUlsHkZ5HqYkAA+usf1E0lp17LqU5/Qe23fXtyx+G/gUcD+wT13uuMhszwXm9hxL6gbm236w4dwqlM3139Y8XtKngZ1s97zt8mDKxvn/piwX/WDDPmQxCI3t6soS0TZS6RYREREREdE/eubLAYceSfMpFUon2z6yLkGcDaxhe9bARheDhaTNgL8AKwEH2z6zU/9x48Z50qRJSyO0ZVZPIieJrtbyfCL6L//dxNKWv7kYbsaPL/9OnDiQUUREdCbpetvjWrUNi4ou26s0ndoTuDNJrmhU9+0aNdBxRERERERERMSSMSwSXY0kXUNJZhw40LFERERERERERMTSM+wSXbZfPtAxRERERERERETE0jfk37ooyZLmSDqu9969zrWBpG5Jyy+O2IYKSUdLOneg41jSJL26/r5PSXr1QMcTEREREREREYvXkE90VdvYPgJA0kY1+bVCPZakb0i6RdK6nSaxfY/tLttP1rETJS30EkhJUyQ9LmntpvOTa4wb9WGOlWoi6vaa0Jsi6fS+jG0z33hJ9y3M2D7OP6U5iSRpP0lX9TJmXk1CdUu6vKHtlZL+JmmWpJmSLuz0O3aay/ZvbXcB9yzibUZEP2R1XQAAIABJREFURERERETEIDRcEl0tSRJwKjAe2Nn2/QMQxl3Auxti+h/gWf0Y/1PgTcAEYHVgG+B6YJf+BtKT/Bukdq9Jxi7br204/w/gdbZHAWOA24HvLORcERERERERETGMDebEx6JaHjgN+B9gvO2ZAJLeAHwe2ASYDZxm++jathElMbUicAywE/BSSScBZ9o+RNLLga8DmwO3AR+2fU2HOM4B9gG+UY/3Bc6uMVCv+6x6/HbKRvp/A14D7FD/3dz2vbX7bOBbDWPfC3wcWA94EPiS7VNr23jg3HrtjwBXAm8EVpbUXafYvP67kqSzgbdQKp72tT1J0seAl9p+W8M1vwE8afvQDve9WNie3nTqSWDTJX1dgFvnzn36leGxZEzu7mZsV9dAhxERERERERHDxHCu6PoB8HzgVT1JrmoOJfE0CngD8EFJezQPrkshrwQOqZVBh0haE/glcDKwFnAi8EtJa3WI4zpgNUkvqHt/7UlJPjX6KvBi4OXAmpTE1VPAq4E/NyS5Wvk3JXm1GvBe4GuSXtTQvk6dc8N637sBUxsqnqbWfm8CflSfyy+Ab9bz5wK7ShoFT1eF7UlJ4C1OP5D0oKTLJW3T2FD3TpsFzAMOB768sHPF4DK2q4sJo0cPdBgRERERERExTAzniq7XAsfYntV40vbEhsO/SvohsDNwUR/mfANwu+2eJM8PJX0I2B04s8O4nqquPwK3AE8voZS0HLA/pWqq5/w1tW0t4IFOAdn+ZcPhH+ueVDsBN9RzTwFH2X6sztluqqts/6r2OQc4tM7/gKQrgHcA3wN2BWbYvr5DWBdJeqLheKWGeFrZq7YL+DBwmaTn9/x2tu8BRtVE40GUZ7hQc/XHFiNGMHHbbfs7LGKxmtzdvcQrCyeMHs37xoxZoteIiIiIiIhYGoZzRdcbgaMk7d94UtL2kv5QK35mAx8A1m45wzONAe5uOnc30HGTe0qiawKwH2XZYqO1gVWAO1uMmwk8t9PEknaTdJ2kh2rV0+tZ8H4etD2/l/gApjV8nwus0rCn11nA3vX73vRezbWH7VE9H+DgTp1tX217nu25tr8AzKIk65r7PVRj+Xm7/cb6OldEFJO7uzlvevMK4YiIiIiIiKFpOFd0XUOptLpE0nzb59Xz51GW5e1me37df6tdostNx1MpSwAbbQD8ulMgtu+WdBclCXVAU/MMYD5lz7Cbmtp+C3xY0nq2n/GmREkrAxdQqsV+bvs/ki6iVDO1u4fm4764CPiOpK0pCcSPL8Qc/WEWvIdGKwDPoSzVfGgR54oY9MZ2dS3RysLsQxcREREREcPJcK7owvYfgbcC35X09np6JPBQTXK9hFJp1c504HkNx78CNpc0QdIKkvYEtgQu6UM4B1D2C5vTFONTwOnAiZLGSFpe0sskrWz7t8BvgAslvbhec6SkD9RKtZWAlSmb0D8haTfKks1OpgNrSVq9DzH3xDif8vbH8yh7ht3T17G9qftv7SBpJUmr1M3v1wauru1vlbSFpOUkPZuyL9qNtbqrX3NFRERERERExPA2rBNdALZ/Q9k8/UxJu1OW0R0r6VHgs8CPOwz/OvB2SQ9LOrluav9G4DDKssKPA2+0PaMPcdxpe1Kb5sMpb1r8C6VK6Uv897d5OyXBdj7ljYt/5//Zu+9ou6py/ePfhxrCCUXRaGhRevESNIAFJF4QL02xS5AiWIAfimJBQBQQUBGkC14E6REUKSJ4BTEoIEKASEekSUuogZwUWp7fH3Nu3Bz3aeEkJ+ec5zPGHjl7rbnmetfaDO8Y733nO2EscKXt6cBX6jM8S0naXdJNHHcDE4D7JU2T1NPGPGdQdrDs6yb0I4CTKPE/SukBtmXTBgLLUyrmplPe0RzKzpAASDpZ0sk9nCsiIiIiIiIiBjHZc7OSbcEhaTbwAnCc7QP7O57BStJKlCbwb7H9fH/HMzckbUZZ6rk4sJXtP3U1fuzYsZ40qbPcZMS811hWOD+WLmbjhRgs8t90zG/5by4Gm3Hjyr8TJ/ZnFBERXZN0k+2xrc4N+B5dtof1dwyDXd0Zch/glwM1yQVg+4/AMv0dR0RERERERETMGwM+0RXzlqQlKX29HqIsBYyIiIiIiIiIWCAl0RVdqs3z2/o7joiIiIiIiIiI7gzoZvSSLGmGpMP6O5bBpr7bVfs7jr4kaXFJ7ZJeknRof8cTEREREREREX1rQCe6qvVsH9B8QNKSNaFxWX8F1RlJu0i6pun7UpKulXSBpEX7M7a+IOn0jkkkSaNr4qxlBaGkIyQ9LOl5SQ9J6vh7NhKa7fXz827u/2LT2HZJCwPYfsF2G3BOHzxqRERERERERCxgBkOiq5VPUHZi3ELSW/s7mM5IWha4ktL/6tO2X+rnkPrLqcCatpcC3guMl/SxDmPWs91WP5/vZr4jmsa22X5lnkQdEREREREREQuUwdqja2fgZGBLYAfgSEmfBL5t+12NQZK+DmxieztJWwOHAqsAzwGn2j6ojhsNPADsAnwfGA4cbfuwen5x4EfAp+rU5wP72n6hswAlLQdcAUwGdrM9px7fpsYxGrgT2N32rfXcg8AJwE7AysDvgZ1tz5Y0DjgbOBrYF3gF2N/2L5piPKzGuDhwIfA127Pq+W9SdlY08J2mODcALgWWt/1yPfZx4EDbYzp7vt6wfU+HQ3OAfl82ec/Mma9uGR7RHya3tzOmLS3yIiIiIiIiemrQJbokrQSMA/YCnqEkvY4ELgF+Jmkt23fV4Z+lJJUAZlASSHcA6wJXSJps+6Km6TcG1gBWB26Q9Js61wHAu4ExlETRxZRk0YGdhPkG4GrgL8Aetl1jfydwGrAtMKnGd4mkNZqSZp+i7H44G7iWknw7uZ57C7A0sDzwQeDXki6y/SwlEff2GuNLwLnAd4H9JP0P8A1gM0pC75RGoLZvlPR0ne/ypvd2VifPNlckfZvyzpasMZzbYcifJS0EXAfsY/vBLqbbU9KedZ7DbV/Ql7FGzC9j2toYP3LkPL/P5Pb2QZnUHT9yJF8cNaq/w4iIiIiIiPlo0CW6KMmqW23fKWkacISk9W3fIuk8SpLmAEnrUKqmLgWwPbFpjlslTQA2BZoTXQfXCqi/S/o7sB5wF6Vq7Mu2nwCQdDDwMzpPdK0IDAN2bSS5qi8AP7P9t/r9DEn7U5JoV9djx9l+rN7nt5TEVcNLwCG18uoySe3AGpL+Vuf+L9vP1GsPpyST9qMkz35h+/Z67iBg+6Z5z6jv7XJJbwA+BOzZybMBfEPSXk3fu10ia/uHkn5Un2c7SlVdw6bA9ZRKukOBSyWNaVSYdXAc8PV6/RbAeZKm2L62uxg6WmP4cCauv35vL4uIBcDk9naAJLoiIiIiIoaYwZroOgXA9mOSrqZUdd1CSdhMkPQdYEfg/EallKSNgB9SqrkWoyzv+1WHuac0/T0TaKwpGkXps9XwUD3Wmb/XuS+XtJntRinFysDOkr7cNHaxDnN1jKH53NMdkj+NGN9ESRLdJKlxTsDCTfHf1CH+ZmcDd0lqoyTF/mL78S6e70jbzcsfR1Oqq7pUk363SPoQcDBlKSW2/1yHvChpb+B5YC3gthZz3Nz09TJJ5wAfo1S/RUQLY9raBl1SdzBWqEVERERERPcGVTN6Se8FVqMsx5siaQqwEbC9pEVsXw+8CGwCjOe1y+/OpSxvXNH20pTlgKJnHqMkqRpWqsc6ZftYSmLtCknr1sMPA4fZXqbpM9z2hB7G0ZmngFnAOk3zLl13IAR4nFJl1hx/c6yPAn8FPkpJEPbpssUWFqH0SuuM6flv05uxERERERERETGADapEF6Vy6wpgbcoSuDGUCq3hlMb0AGdSGrq/bPuapmtHAM/Uxu4bUhJhPTUB+I6kN9Um89+lVEF1yfYRwLHAlZLWoFSi7S5pIxVLStpa0ohexNLqPnPq3EdLejOApOVr5RSU5vm7SFpb0nDgey2mORP4FvAOSiP7PiFpIUlfkrRsfeYNgf8H/LGeX0fSGEkL14qyo4BHKUtGW833CUltdd4tqH3O+ireiIiIiIiIiFhwDZpEl6RhlGV1x9ue0vR5gFKBtHMdehYl+dWxKmlP4BBJ0ymJqvN7cftDKc3jb6Usp7uZfze575Lt7wM/pyR2nqX00jqh/v1PSrP5vrBvne96Sc8DV1Ia62P7cuAY4Ko65qoW119IqVq70PaMPoqp4aPAfcB0SoLw+PoBGAmcR1mueD+lr9o2tl8CkLSDpDua5tqbkgibBvwY+EKH/msRERERERERMUjptb3QBxZJs4EXKA3aO2v83vGaJYAngHfavndexjfYSLoP+JLtK/s7lrkhaXFgKrAocITtg7saP3bsWE+aNGm+xBbRXxq9rAZrj67B9lzRvfz2Mb/lv7kYbMaNK/9OnNifUUREdE3STbbHtjo3oJvR2x42F5ftAdyYJFfvSPo4pd9Vq2qvAaFuPLBMf8cREREREREREfPGgE509ZakBymNybfr51AGFEkTKX3Pdqz9viIiIiIiIiIiFjhDKtFle3R/xzAQ2R7X3zFERERERERERHRn0DSj74okS5oh6bD+jmUwkDRR0uf7O465Iek+SS9K6nZXzIiIiIiIiIgYWIZEoqtaz/YBzQckLSmpXdJl/RWUpHGS5tQ42iU9KqnLJukLMkkHtUoi1WTjqt1cu5ikuyU90uLc3pIeqAnLuySt3sX9X2p6n+2S3t44b3sV4PC5eLSIiIiIiIiIWMANpURXK5+g7Nq4haS39mMcj9lus90GbAzsJmmu+ohJWrivglIxP/8b+SZlR8yOcXwe2A3YGmgDtgGe6mKe8xrvs37unyfRRkRERERERMQCZUj16GphZ+BkYEtgB+DIxonauP4EYCdgZeD3wM62Z0saB5wNHA3sC7wC7G/7F/XarYFDgVWA54BTbR/Uk4BsPyDpOkrz94vqfGsCxwPvAp4EDrR9fj13OjCrxrgp8BFJP+8i9mWBs4CNKL//tcDuth+p802sx8YB7wTeIelt9f5vrdeqJ8/SG/UenwX2AU5pOr4Q8D1gF9t31sP39fX9W7ln5sxXtwyPGKwmt7czpq2tv8OIiIiIiIjoE0O2okvSSpRkzjn1s1OLYZ8C/gd4G/BfwC5N594CLA0sT6k2OrEmkQBm1PmWoVQh7dHTCi1JqwHvA66v35cErgDOBd4MbA/8VNI6TZeNBw4DRgDXdBP7QsAvKAmwlShJshM6hLEj8MU633PABcB3gOUoSab39eRZeul4YP8aT7MV6mddSQ/X5YsHd1Nptq2kZyTdIWmPeRBrxKAxpq2N8SNH9ncYERERERERfWIoV3TtBNxq+05J04AjJK1vu7mE5zjbjwFI+i0wpuncS8Ahtl8GLpPUDqwBXG97YtO4WyVNoFRbXdRJLKNqDAtRkksX8u+E1TbAg41qMeBmSRdQll3eUY9dbPva+vdsSZ3GbvtpSuKKeu4w4E8d4jnd9h31/JbAnbZ/Xb8fA3y9k+do+JSkbboZ8ypJHwUWsX1hrZZrtkL9dwvgHZTk4R+AR2iq/GpyPvC/wFRK1doFkqbZntDTeBrWGD6cieuv39vLIiIiIiIiIqKfDNmKLkqi6xyAmhC6mrKUsdmUpr9nUvpDNTxdk1z/cV7SRpL+JOlJSc8Bu1OqoTrzmO1lbC9FSeTMAs6o51YGNpI0rfGhLLN8S9P1D7eYs2XskoZL+pmkhyQ9D/wZWKZDb6/m+UY1f7ftTu7X7Pz6PK9+OhtYK9aOAL7cyZBGhdcRtqfZfhD4GbBVq8G277T9mO1XbF8HHEtJCkZERERERETEIDckE12S3gusBuwnaYqkKZTqn+0l9UWV27nAJcCKtpem9AHrUV8r28/V67ethx4Gru6QOGqz3bwkz72I7euUyrONamLt/fV4c3zN8z0OrNj4olIutiJ9ZzVgNPCX+jv8Bnhr/V1GA/cAL9K7Z2xm5kFPsYiIiIiIiIhY8AzJRBelcusKSsP3MfWzLjCc0pj+9RoBPFObv29I6aHVI5LagM/w72WJlwKrS9pR0qL1s4GktV5HbLOAaZLeQGn03pXfAetI+lhNAn6F11aTvV63UxJnjd/h85Rlh2OAh23PBM4DviVphKQVgC9Q3st/kPQRScvWHSM3rPFe3IfxRkRERERERMQCasgluiQNozRqP972lKbPA5QdBTsuX5wbewKHSJoOfJfSN6oroyS11z5fDwFvoCxPxPZ0Sn+qzwCPUZYk/ghYfC5jOwZYAniK0vD+910Ntv0U8Engh8DTlAqsa7u6pjdsv9z8OwDPAHPq91fqsL2Adsrz/5VS8XYagKRN6ntr+AzwT2A6cCbwI9tnEBERERERERGDnkrLpcFN0mzgBUqD9gP7O57oP5LuoeyUeb7tXbsaO3bsWE+aNGn+BBYRfWrcLWVfkWwoMfTkt4/5Lf/NxWAzblz5d+LE/owiIqJrkm6yPbbVuSGx66LtYf0dQywYbK/R3zFERERERERExLwx5JYuRkRERERERETE4DRoEl2SLGmGpMP6YK6Vas+shfsitoFC0kGSzu7vOOYlSVdJmi3pmv6OJSIiIiIiIiL61qBJdFXr2T4AQNLomvxapH6XpOMl3S1p+a4msf0v222NZuiSJkr6/NwGJelBSS9KWq7D8ck1xtE9mGOxmoi6tyb0HpR0Wk+u7WS+cZIemZtrezj/xpKuk/ScpGckXStpgx5cd1Xz71aPjZZ0maRnJU2RdELz+Q7Xf0bSPfW+T0g6Q9JSjfO2/xvYvU8eMiIiIiIiIiIWKIMt0dWSJAE/A8YBm9p+tB/CeADYvimmd1B2P+ypXwMfBsYDSwPrATcBm/U2kM6SRH2lJpYuBY6n7CC5PHAwZUOArq7bgdZ9434KPAG8FRgDbErZ2bKVa4H32V4aeHud79DeP0VEREREREREDDRDIdG1MHA6MBYYZ3sqgKStJd0i6XlJD0s6qHFBczVYXQq5CXBCXc54Qh3zXkk31sqhGyW9t5s4zgJ2avq+M3Bm8wBJS0g6StJDdd5r6rHNgQ8CH7F9o+2XbT9n+0Tbp9ZrPyfpLknTJd0v6UtN846T9IikfSVNASYAlwOj6jO1SxpVhy8m6cw6zx2SxtY5vinpgg7xHi/pmBbPujqA7Qm2X7E9y/YfbN/a2cuRtDTwPeBbLU6/jbJL4mzbU4DfA+u0msf2w7afajr0CrBqZ/eNiIiIiIiIiMFjKOy6eA6wIvDftqc1HZ9BSTzdAawLXCFpsu2Lmi+2fYCk9wFn2/45gKQ3AL8DvkJJGn0S+J2kVW0/3Ukc1wM7SloL+AfwaWBjXlttdCQlgfNeYAqwETAH2By4wfbDXTznE8A2wP3A+4HLJd1o++Z6/i2U6qqVKQnOjeozrdCYoBS+8WHgY8DnamwnAO8GzgYOkrSM7Wm1KuzTwJYtYvkH8IqkM4BfAtfbfraL2AEOB06qz93RscBnJE0Elq33PLCziSRtTPl9lgJmAh/t5t4t3TNz5qtbhg8240eO5IujRnU/MCIiIiIiImIAGQoVXVtQqoGak1zYnmj7NttzaqXRBMqSuJ7YGrjX9lm1umoCcDewbTfXNaq6PljHv7qEUtJCwK7A3rYfrZVQ19l+AXgj8HhXE9v+ne37XFwN/IFSidYwB/ie7Rdsz+piqmtsX1b7k51FWSKJ7ceBP1OSegD/Azxl+6YWsTxPSeIZOAV4UtIlkka2umGtGnsfZaljK1dTEoDPA48Ak4CLOhmL7Wvq0sUVgB8DD3bxvEPO5PZ2zp06tb/DiIiIiIiIiOhzQ6GiaxvgUknP2j6tcVDSRsAPKdVciwGLA7/q4ZyjgIc6HHuI0ouqK2dRkkVvo8OyRWA5YBhwX4vrnqYuB+yMpC0pS/9WpyQwhwO3NQ150vbsbuKD11ZUzQSGSVrE9svAGcAelOTVZ+vztGT7LmCXGtualIqwY2jqU1bPLUTpwbW37ZdrVVnH8/9H6bH2XqANOA34Ea2XOTbH8Kik31Oqyt7Z1dhW1hg+nInrr9/byxZ4g7VKLSIiIiIiImIoJLquo1RaXSpptu1z6/FzKcvytrQ9u/aaWq6TOdzh+2OUJYDNVqL0juqU7YckPQBsBezW4fRTwGxgFeDvHc5dCewtaQXb/7FToqTFgQso1WIX235J0kVAc9ao4zN0/N4TFwEnSVqXkkDsMtH06o3suyWdDnypxemlKP3TzqtJroXr8UckfRK4i7L09IRa3faCpF9QllX25P6LUN5pRAwxk9vbk9gdgia3tzOmra2/w4iIiIiIfjIUli5Sl/J9DPhfSZ+oh0cAz9Qk14aU3Qw7M5Wyg1/DZcDqksbXhvWfBtam7DTYnd0o/cJmdIhxDqVS6SeSRklaWNJ7JC1u+0rgCuBCSe+q9xwhaXdJu/LvirQngZdrddcW3cQxFXhjbQLfI7Ui7NeUJOENtv/VapykNSV9XdIK9fuKlEqu61sMf45SITemfraqx98F/K02ln8A2KM+9zKURv4dk4GNe+8gaSUVKwOHAX/s6TNGRMTANqatjfEjW66Uj4iIiIghYChUdAFg+4qakDpP0gvAnsBRdRfFq4HzgWU6ufxY4AxJewBn2f6KpG3q8ZOAfwLbdNjtr7M4Wi1NbPgG8APgRsoSvb8DH6rnPgEcAJwHvJVSAXYFcIjt6ZK+Up9hceC3wCXdxHG3pAnA/ZIWpiTqeuIM4POUfmKdmU5pdr9PTUxNoyQBv9kiDtO0XFLSsPrn1LpcEkqS8hhgX8ouin8CvlbHrwTcCaxdE29rU5Y1Lgs8S0lK7tfDZ4uIQWRMW9ugXH4cERERERGdU8kzDHySZgMvAMfZ7nRHvnh9amLpbuAtten8gCLpCsoukjfY3qyrsWPHjvWkSZPmT2DzUWMpVxIAMZjlv/OImF/yvzcx2IwbV/6dOLE/o4iI6Jqkm2yPbXVu0FR02R7W/ah4PWpj+H2AXw7EJBeA7Q/2dwwLgnnRu2j8yJF8cdSoPp0zIiIiIiIiojcGTaIr5i1JS1L6ej0E/E8/hxMLmMnt7QBJdEVERERERES/SqIreqQ2z882VoNEX/cuys52ERERERERsSAYErsuRkRERERERETE4DdoE12SLGmGpMP6O5ZYMEjaXFK7pDmSNu/veCIiIiIiIiKibw3aRFe1nu0DACSNrsmv9g6fT8/voCStLulXkp6S9JykWyXtI2nh+R3LvCBpMUlHSXqkvuMHJB3dg+s2rb/RoU3H3irpEkmP1XOjezDP3vWeMyTdJWl1ANtX2m4D/vU6Hi8iIiIiIiIiFlBDsUfXMrZf7q+bS1oF+BvwC+Adth+XtAbwPWAEMK2X8y1s+5Wm74v05/NV+wFjgQ2Bx4GVgfd3dYGkRYFjKe+m2Rzg98APgOu6u7GkzwO7AVsDdwFvB57tXfjFPTNnDsreU5Pb2xnTlnZrERERERERMfgM9oquHpH0bklTmiuqJH1U0q317w0l/VXSNEmPSzpB0mJNYy1pd0n3SnpW0omS1MntDgaus72P7ccBbN9je7ztaXW+X9V4npP0Z0nrNN3rdEknSbpM0gzgA5IelLRvjXeGpEUkfVvSfZKmS7pT0keb5lhV0tV1/qckndd0bh1JV0h6RtJUSfvX44tLOqZWVj1W/168k2fcALjQ9mMuHrR9Zjc/w9eBPwB3Nx+0PdX2T4Ebu7keSQtREoZfs31nvfd9tp/p7tqhZExbG+NHjuzvMCIiIiIiIiL63FCs6PoPtq+vSaP/Bq6oh8cD59a/XwG+BkwCVgAuB/YEjmmaZhtKgmcp4Cbgt5RKpI42p1Q8deVyYFfgReBHwDnAmKbz44Gt6j0bCbftKVVMT9l+WdJ9wCbAFOCTwNmSVq3Jte9TkkofqNePBZA0ArgSOBLYFlgUWLvOfwDw7hqHgYuB7wAHtoj/emAfSS8CfwFut+3OHlbSyvV53wmc0M276coK9bOupNOBl4EzgYNtz+ntZGsMH96nOxNGRERERERExLw1FCu6nqqVWY3PWvX4BEqyqJHw2aoew/ZNtq+3/bLtB4GfAZt2mPeHtqfZ/hfwJ16bmGr2Rspyvk7ZPs32dNsvAAcB60laumnIxbavtT3H9ux67DjbD9ueVef4Va2ommP7POBeylJCgJcoywlH2Z5t+5p6fBtgiu2j6vHpthtLCXcADrH9hO0nKZVpO3byCD+gJOh2oCQHH5W0cxePfBxwoO32rt5LD6xQ/90CeAclkbc9ZSljRERERERERAxyQ7Gia7lOelidC1wnaQ/gY8DNth+C0jwe+Aml8mk45b3d1OH6KU1/zwQ6a4L0NPDWzoKryycPo1RhvYnSowpgOeC5+vfDLS59zTFJOwH7AKProbY6B8C3KFVdN0h6FjjK9mnAisB9nYQ2Cnio6ftD9dh/qD3DTgROlLQEpVrrNEk32L6rQ5zbAiNqMu71mlX/PaIuA50m6WeUpOUpfTB/dGFye/uA6mk2fuRIvjiq5X/CERERERERMUANxYqulmzfSUnebMlrly0CnETpHbWa7aWA/YHOenB150rg412cHw98hLLEcWn+nahqvl+rZYCvHqtLAU8B9gLeaHsZ4PbGHLan2P6C7VHAl4CfSlqVkixbpZO4HqNUgTWsVI91yfYs2ydSGsKv3WLIZsDY2pNsCvBp4KuSLu5u7hbuoSz37HSZZASUpNy5U6f2dxgRERERERHRx4ZiRVdXzgW+AryHsuyuYQTwPNAuaU1gD+DJubzH94AbJf2YUkk1pSaZDqIkpkYAL1Aqv4YDh8/FPZakJHueBJD0OWDdxklJnwT+avsRSgLKlD5klwI/kfRVSnJvMWDtunxxAvAdSTfW8d8Fzm5183r9ZMoOii9R3uUIoFW5z4HAD5u+H0tJoH2/ab5hQGOjgMUlDWtasvkq2zNrY/1vSbqFkij8AvDj1q8p+tLSCE6IAAAgAElEQVSYtrYB09NsIFWeRURERERERM8NxYquaZLamz77NJ2bAIwDrrL9VNPxb1AqraZTKqXmepmd7fsoibTRwB2SngMuoPSymk5pnv4Q8ChwJ6Wxe2/vcSdwFPBXYCqlX9W1TUM2AP4mqR24BNjb9gO2pwMfpDSin0Lp6/WBes2hNcZbgduAm+uxVmbV+08BngL+H/Bx2/e3iHV6rTCbYntKvXZGh50SZwGN/l138+8likg6WdLJTWP3qmMfq89/LnBaJ3FGRERERERExCCiLjbDG9AkzaZURh1nu9XOgDHESNqMklRcHNjK9p+6Gj927FhPmjRpvsQ20DUqpAZaRddAiTd6L79xRMwv+d+bGGzGjSv/TpzYn1FERHRN0k22x7Y6N2iXLtoe1t8xxILF9h+BZfo7joiIiIiIiIiYN4bi0sWIiIiIiIiIiBiEhmSiS5IlzZB0WC+u2UTSPU3fH5S0+byJMOYVSadLmiXpkf6OJSIiIiIiIiL61pBMdFXr2T4AQNLomvz6XfMASWdLOgjA9l9srzE3N5L0EUmTJT0v6SlJf5Q0+nXGv0CTtI6kP0h6VtI0STdJ2qqTseMkzemwScDOTeePlHSvpOmS7pa0Uxf3faukSyQ9Vn/T0c3nbe8CbNk3TxkRERERERERC5JB26NrLr1b0vtsX9v90J6RtCplJ8WPAVcBbcAWwJy+usf8IGkR2y/34pLfAicB29TvGwDqYvxjtlfo5NwMyk6Q/6jz/F7SP21f12LsHOD3wA+AVucjIiIiIiIiYpBKouu1jgAOBT7Q8YSkccDZrZIxktYELgf2s/3LDqfHAA/URugA0yk7/zWuPR14xPZ3Wt1H0oPAicCOwCrAL4H9gdOBjYG/AZ+0/WytXnoA2BU4hJJU2w+4CTgVWKnOvVfT/XcFvgm8BbgB+KLth+o5A3sBXwUWkfR24CfADpSdCx8Cxtu+vcP7WA54G3CK7Rfr4blOHtr+XtPXv0n6C/AeWiSybE8Ffirpdf+3fc/Mma/upBRdm9zezpi2tv4OIyIiIiIiIoa4obx0sZUTgdV703tL0juBPwBfbpHkArgZWFPS0ZI+IGlusgEfBz4IrE6pbLqckuxajvIbfqXD+I2A1YBPA8cABwCbA+sAn5K0aY19uzrPx4A3AX8BJnSYa7s639qUSrT31ziWqfM/3SLep4F/AmdL2k7SyB4845slTZX0QH1XS7YaJGkJSlXXHT2YM+aTMW1tjB/Zk585IiIiIiIiYt5JRddrzQYOo1R1XdmD8ZsAuwE72v5TqwG2769VWvsA5wMjJP0S2Mt2ew/jOr5WKlGrmZ6wfUv9fiGwWYfx37c9G/iDpBnABNtPNF2/PnA18CXgB7bvqucOB/aXtHKjqquef6aefwkYAawJ3NC4rsUzW9IHgG8DRwFvk3QNsJvte1tccjel8u1uYGXgDErl2JdajD0Z+Dvwf52/rr6xxvDhTFx//Xl9m4iIiIiIiIjoI6no+k+nACMlbduDsbsD13WW5Gqwfb3tT9l+EyU59n5KlVVPTW36e1aL7x2rxHo6fmXg2NosfhrwDKWP1vJN4x9ueo6rgBMolW9TJf2vpKVaBWz7Edt72V6l3mcGpVdZq7FTbN9pe47tB4BvAZ/oOE7Sj4F1gU/Zdqu5IiIiIiIiImLoSqKrA9svAQcD36fr5ulQEl0rSTq6F/PfCPyGkrCBkgAa3jTkLT2P9nV7GPiS7WWaPkt0aPL+moSS7eNsv4uyDHJ1Sn+vLtl+mJIcW7e7sU33fM27l3QwZbfELWw/38N5IiIiIiIiImIIydLF1s4C9gX+B2i11K5heh3zR0k/tP3tjgMkbQysBVxs+4nauP7DlOV5AJOBr0s6FFiM0vh9fjkZ+L6kybbvkLQ0JZH0q1aDJW1ASY7eTEnQzQZeaTFuWcpznAXcD7yB0iD/+k7mHVfHPQysAPwQuLjp/H7AeOD9tlv1BOs43zBg4fp1cUnD6lLOiFdNbm/PZgODWDZIiIiIiIgYmlLR1YLtV4DvURI03Y2dRmkUv6Wk77cYMo2S2LpNUjvwe+BCyg6PUJJBfwcepDS1P+/1xt9Tti8EfgT8UtLzwO2UqqnOLEVZ2vksZcfFp4EjW4x7ERhN6XPWmPcFYJdO5n0n8FdK8uy6Or65wf7hlB0j75XUXj/7N07W75s0jZ8FNPqf3V2/R8QQkg0SIiIiIiKGJg3FVkeSZlMSL8fZPrC/44n5R9KpwCcpDf1X7Wrs2LFjPWnSpPkTWMxXjUqubDYQERGvV/5vSgw248aVfydO7M8oIiK6Jukm22NbnRuSSxdtD+vvGKJ/2N6NslNmRERERERERAwyWboYERERERERERGDQhJdERERERERERExKCzwiS5JljRD0mHz8B7jJD0yr+bvRRwHSTp7Lq6bJ/FLmijp852cW6k2gV+41fkFlaSrJM2WdE1/xxIRERERERERfWuBT3RV69k+oPFF0mI1KXRvTYI9KOk0SaP7L8R/k7R/0+6AsyW90vT9jv6Ory/Y/pfttrpD5X+QtLGk6yQ9J+kZSddK2qCTsbt0eEftksY1nZ9Y32Pj3D2dxSXp5A7zvCBpelPc/w3sPvdPHhERERERERELqoGS6Oro18CHgfHA0sB6wE3AZr2dSFKfN+S3fXhNArVRkip/bXy3vU5f329BI2kp4FLgeOANwPLAwZSdLjvT/I7abE/scH6vpnNrdDaJ7d2b5wEmAL96XQ8UEREREREREQPCgNt1UdLmwAeB1W0/XA8/B5zYNOZzwLeAFYAngR/Z/lk9Nw44m5KE+RpwBXBqh3usBZwEjAEeBfazfUk9txVwJLAi8DxwtO0jexH/scDHKAm6e4Gv2v5Li3GLAmcCiwHbAzt09kxN13wd2Bd4Bdjf9i/q8a2BQ4FV6rs61fZB9dww4OfAlsDCNaZtbE+t064s6Vrgv4C/AuNtP1Wr5x4AFrX9cofwVwewPaF+nwX8oafvqK9IWhL4OLDN3Fx/z8yZr24ZPj+NHzmSL44aNd/vGxERERERETHQDcSKrs2BG5qSXK08QUluLAV8Djha0jubzr+FUmm0MvDF5gtrgum3lMTMm4EvA+dIalQRnQp8yfYIYF3gql7GfyMlgfYG4FzgVzXZ1BzDEsBFlAqoT9l+sYfPtDSlemo34ERJy9ZzM4CdgGWArYE9JG1Xz+1cr1sReCOlAm1W07zj6/3eTEm6faMHz/gP4BVJZ0jasimOrqwv6SlJ/5B0YItKux/U89c2L2vsxscpScE/93B8v5vc3s65U6d2PzAiIiIiIiIi/sOAq+iiJGMe72qA7d81fb1a0h+ATYCb67E5wPdsvwAgqfnydwNtwA9tzwGuknQpparqIOAlYG1Jf7f9LPBsb4K33dxs/ihJ3wHWAP5ejy0F/L5+39u2e/hMLwGH1OqqyyS113mv77AM8FZJE4BNKcm0lyjvdFXbt1KWgDb7he1/AEg6n7JktLtnfF7SxpTqslOAt0i6DPhCU6VYsz9TkoYPAesA5wEvAz+o5/cF7gReBD4D/FbSGNv3dRPKzsCZjXfYW2sMH87E9defm0vnWn9UkEVEREREREQMFgOxoutp4K1dDahVRNfXJujTgK2A5ZqGPGl7dieXjwIerkmuhocolVJQqoS2Ah6SdLWk9/QmeElfl3RXbdI+jVJN1RzbuynLBH/YnKDpwTM93WEJ4UxKwg5JG0n6k6QnJT1HqdpqXHsW8H/ALyU9JumIWtXWMKXVnN2xfZftXWyvQElijQKO6WTs/bYfsD3H9m3AIcAnms7/zfZ02y/YPgO4tj5/pyStSEnmndmTeCMiIiIiIiJi4BuIia4rgQ0lrdDqpKTFgQsofbRG2l4GuAxoLtvqqsLnMWBFSc3vZiVKry5s32j7I5SlfBcB5/c0cEmbUKqTPgUsW2N7rkNsf6BUMv1R0shePFNXzgUuAVa0vTRwcuNa2y/ZPtj22sB7Kcsjd+rpM/WE7buB0ykJrx5dQtfP1t15KM9wne37e3jPiIiIiIiIiBjgBlyiy/aVlAbyF0p6l6RFJI2QtLukXSl9pBan9GZ6WdKWwBa9uMXfKD2tviVp0doPaltKxdNiknaQtLTtlyjN6F/pxdwjKEvyngQWkfRdylLFjs94BCU59UdJy/XBM40AnrE9W9KGlL5bAEj6gKR3SFq4Ps9LvXym/yBpzVq5tkL9viJl6ef1nYzfsimptyZwIHBx/b6MpA9JGlZ/6x2A91Oq0LqyEyW5FhERERERERFDxIBLdFWfoFQ0nUepiLodGAtcaXs68BVKpdWzlKTOJT2duDZ+/zBlF8KngJ8CO9WqJIAdgQclPU9ZAvjZXsT9f8DllGbtDwGzgZZN9W1/n1IxdiWw6Ot5JmBP4BBJ04Hv8toqtLcAv6Ykue4CrqbsSvl6TAc2Av4maQYlwXU78PVOxm9G6R02g/K7/gY4vJ5blLJj5JOU3+PLwHa27wGQtJKkdkkrNSary0lXAH71Op8jIiIiIiIiIgYQzWWf7vlG0mzK7oPH2T6wv+OJgU3SFZQ+aDfY3qyrsWPHjvWkSZPmT2DVuFtuYXJ7O2PaetQKLeZS4x3P780GIiJi8GlsJJP/mxKDxbhx5d+JE/szioiIrkm6yfbYVucW+F0XbQ/r7xhi8LD9wf6OIfrfmLY2xo8c2d9hRERERERERB9b4BNdEUNNKo0iIiIiIiIi5s5A7dHVLUmWNEPSYX0454OSNq9/HyTp9fayivlM0n2SXsxvFxERERERETH4DNpEV7We7QMAJI2uya/XVLFJOl3SofMzqLp740GS7q3JuAclnSZp9PyMY16S9BFJkyU9L+kpSX/s7Pnqu3ipNpVvfN7edP77km6T9LKkg7q57+Ud5nlR0m2N87ZX4d+N7iMiIiIiIiJiEBnsia4F1a8pOzuOB5YG1gNuouw+2CsdE3edHZufJK0KnEnZZXFp4G2U3SvndHHZebbbmj73N537J/At4Hfd3dv2ls3zANeR3RcjIiIiIiIihoQkujqQ9GFJd0iaJmmipLV6cM3vJH25w7FbJW3XYuzmwAeBj9i+0fbLtp+zfaLtU+uYz0m6S9J0SfdL+lLT9eMkPSJpX0lTgF/UiqhfSzpb0vPALpI2lPTX+hyPSzpB0mJ1Dkk6WtITkp6rsa5bzy0h6ShJD9Vz10haopfvZgzwgO0/uphu+wLb/+rJb9CR7TNsXw5M7811tYJsE+CsublvRERERERERAwsaUbfRNLqwARgO2Ai8DXgt5LWtv1iF5eeQaleOr7Osx6wPHBZi7GbAzfYfriL+Z4AtgHuB94PXC7pRts31/NvAd4ArExJVu4LfAT4JLATsDiwdo1/ErACcDmwJ3AMsEWdd3XgOWBNYFqd+0hgHeC9wBRgI2BOL9/NzcCako4GLgFutN3exfMCbCvpGeBx4ATbJ3Uzvid2Av5i+4G5ufiemTNf3TJ8fpnc3s6Ytrb5es+IiIiIiIiIwWIoVnQ9VSuSpkmaRlk+2PBp4He2r7D9EiXpswQl6dOVi4HVJK1Wv+9IWYrXKjn2Rkoyp1O2f2f7vloNdTXwB0plUsMc4Hu2X7A9qx77q+2LbM+xPcv2TbavrxVjDwI/AzatY18CRlASXLJ9l+3HJS0E7ArsbftR26/Yvs72C715N3XZ4ThKsu98yjs/XVJnGZzzgbWANwFfAL4rafuu3lEP7QSc3gfzzDdj2toYP3Jkf4cRERERERERMSANxYqu5Wy/3Pgi6fSmc6OAhxpfbM+R9DAlYdMp2y9IOh/4rKSDge2BT3Qy/GlKJVWnJG0JfK+OWwgYDtzWNORJ27M7XPaaCrFagfUTYGy9fhFKHzBsXyXpBOBEYCVJFwLfAIbVz30twurVu7F9PfCpGssGwHnAAcB+Lcbe2fT1OknHUt7fhFZz94SkjSmVb7+e2znWGD6cieuvP7eXR0RERERERMR8NhQrurryGGU5IFB6WQErAo/24NozgB0oDeVn2v5rJ+OuBDaUtEKrk5IWBy6gVEyNtL0MZQmkmoa5xaUdj50E3A2sZnspYP/mOWwfZ/tdlGWKqwPfBJ4CZgOrtJh/rt+N7RuB3wDrdje26VnU7aiu7Qz8pgdLJiMiIiIiIiJikEii67XOB7aWtJmkRSl9t16g7NzXpZrYmgMcRRfNz21fCVwBXCjpXZIWkTRC0u6SdgUWo/TYehJ4uVZ3bTEXzzICeB5ol7QmsEfjhKQNJG1Un3EGJbn1iu05wGnATySNkrSwpPfU5FuP342kjSV9QdKb6/c1KbtMXt8qUEkfkbRsbZK/IfAVynLQxvlFJQ2j/Pe6iKRhkhbu7MFr8/xPMsCWLUZERERERETE65NEVxPb9wCfpTSVfwrYFti2m0b0zc4E3gGc3c24T1CqtM6jNIO/nbLE8Erb0ymJnvOBZyk9xC7p3ZMAZSnieMpOhafUezUsVY89S1mO+DSlgqxx3W3AjcAzwI+AhXr5bqZRElu3SWoHfg9cCBzRSayfAf5ZYz0T+JHtM5rOnwLMoiwJPaD+vSOApE3qPZptR3mvf+rkfhERERERERExCMlutQpu4JM0m1JxdJztA+fTPXcCvmh74/lxv+g9SfdQm+Tb3rWrsWPHjvWkSZPmT2ARERExIDV2aE5fzxgsxo0r/06c2J9RRER0TdJNtse2Ojdom9HbHjY/7ydpOLAn8NP5ed/oHdtr9HcMERERERERETFvZOliH5D0IUpPranAuf0cTkRERERERETEkDRoK7rmJ9v/ByzZ33FERERERERERAxlg76iS5IlzZB0WH/H0h1Ju0i6Zi6uG12fs08Tl5JOl3RoF+fbJb29L+85r9VnmiXpkf6OJSIiIiIiIiL61qBPdFXr2T6g+YCkJWui5rK+vpmkHerc7TWpMqfpe8cdAgcs22227291TtI6kv4g6VlJ0yTdJGmrTsbu3/x+mt7Zck1jNpd0c01aPizpU53M9QFJt9V7Pi3pQknLN8W8C7Dl63vyiIiIiIiIiFgQDZVEVyufoOzKuIWkt/blxLbPqUmgNkpS5bHG93psKPgtcAUwEngz8BXg+VYDbR/e4f38CJho+ykASWtTep8dACwNjAFu6uS+dwIfsr0MMAq4Fzipz54qIiIiIiIiIhZYQ7lH187AyZRE1A7AkZI+CXzb9rsagyR9HdjE9naStgYOBVYBngNOtX1Qb24q6dvAFyjJn4eBA2xf2MnYHwPvAbYGNu7BvXeQ9H1gOHC07cPqPBsCxwJrAbOAC4B9bL8oScBP6jtYHHgIGG/79jrnspJ+B7yfkkQab/u+Oq+B1Wz/s0PcywFvA06x/WI9fG0P34+AHYFDmg5/B/iZ7cvr96fr5z/Yntrh0CvAqj25d0f3zJz56pbhsWAbP3IkXxw1qr/DiIiIiIiIiH42JCu6JK0EjAPOqZ+d6qlLgLdJWqtp+GeBs+rfM+rYZSjJpz0kbdfL298HbEKpTDoYOLtjRZmkhSSdAvwXsIXt53p4742BNYDNgO82PccrwNeA5SiJs82APeu5LShJrNXr3J/mtUmk7WucywL/BHrS6+zpOvZsSdtJGtmDaxo2oVSBXdB07N0AdUni45LOlvSGziaQtJKkaZSk3jeAI3px/xhgJre3c+7UjvnNiIiIiIiIGIqGakXXTsCttu+sCZEjJK1v+xZJ51GSWwdIWgcYDVwKYHti0xy3SpoAbApc1NMb2/5V09fzJO0HbAhcXI8tCkyg/DbbNiqienjvg23PAv4u6e/AesBdtpuX+T0o6Wf12mOAl4ARwJrADbbv6hDyb2zfACDpHEr1V3fPaEkfAL4NHEVJHl4D7Gb73m4u3xn4te3mXmYrUKq8tgAeA84AjqdUobW6/7+AZWoy7AvA3d3F3Moaw4czcf315+bSmI9SdRcRERERERENQ7Kii5LoOgfA9mPA1ZQEC5QkyvimJXTn234BQNJGkv4k6UlJzwG7U6qkekzSTpIm12bp04B1O8yxKvARStLqxabrenLvKU1/zwTa6rWrS7pU0hRJzwOHN661fRVwAnAiMFXS/0paqrs5u2P7Edt72V4FWJlSkXZmV9dIWgL4JOU3aDYL+IXtf9QE2OFAy8b2HWJ4ps51cV/vSBkRERERERERC54hl+iS9F5gNWC/mviZAmwEbC9pEdvXAy9SltCN59/LFqE0RL8EWNH20pQeX+rFvVcGTgH2At5YG6bf3mGOu4DPAZdLWqOP7n0SpappNdtLAfs3X2v7uNqXbB3KEsZv9vSZesL2w5RE2rrdDP0Y8AwwscPxWwHP5e0XofRDW6q7gRERERERERExsA25RBelcusKYG3K7n1jKAmY4ZTG9FAqj04AXrZ9TdO1I4BnbM+uDd7H9/LeS1ISNk8CSPocLZI/tidQklFXSlqlD+49grLjYbukNYE9GickbVCrxRalVF3NpvT0mmuSlpV0sKRVa7+x5YBdgeu7uXRn4EzbHZNavwA+J+ntkoYD+1KXk7a498ckrVHv+ybKUstbanVXRERERERERAxiQyrRJWkY8CngeNtTmj4PUCq3GssXz6IkoM7qMMWewCGSpgPfBc7vzf1t30npWfVXYCrwDjrZjdD2GZSdB6+SNPp13vsblMTYdEpF2XlN55aqx56l7Lj4NHBkL+Zu5UVKb7MrKQm224EXgF06u0DS8sB/02J5o+3T6vG/1RhfAL7SdG27pE3q1+WB31Oe9TZgDvDR1/k8ERERERERETEA6D+LZwYXSbMpiZHjbB/Yw2uWAJ4A3tmD5ukxgEg6ldIH7Anbq3Y1duzYsZ40adL8CSzm2rhbbmFyeztj2nrUPi5aGD9yJF8cNaq/w4iIGJAam6JkA5sYLMaNK/9OnNifUUREdE3STbbHtjo36Bt02x42F5ftAdyYJNfgY3s3YLf+jiNiQTG5vWxwmkRXREREREQMBoM+0dVbkh6kNGrfrp9DiYgeGtPWlv9P+lxqVCJEREREREQMBkl0dWB7dH/HEBERERERERERvTdgmtFLsqQZkg7r71g6I+l0SYf2dxzzw0B8Vkmb18b1cyRt3t/xRERERERERETfGjCJrmo92wcASBpdk183Nw+QtJykF+sSxAFJ0oOSZkmaLmmapOsk7S5pQPxekhaTdJSkR2pi6QFJR3cydqU6pvljSV9vGvMmSefWd/GspHO6uPcYSX+R9Fy9/3cb52xfabsN+FefPnBERERERERELBAGROKkG0tKWrfp+3jggf4Kpg9ta3sEsDLwQ2Bf4NS5mUjS/F6iuh8wFtgQGAF8AGjZCMj2v2y3NT7AO4A5wAVNw34DTKG8izcDR3Zx73OBPwNvADYF9pD04df3OBERERERERExEAyGHl1nATsD36zfdwLOBL7QGCBpLeAkYAzwKLCf7UvqudOBmcDbgE2AvwMfB75d550KbG/7lu7maiZpBHAJcBuwN/Ae4FhgdeAfwN62r+vu4Ww/B1wiaQpwvaSjbN8uaSJwtu2f1/vtAnze9sb1u4G9gK9Sfue3SToW+BiwNHAv8FXbf6njDwLWBmYDH6VUPe1se1I9vz4l0bYacBngLsLeALjQ9mP1+4P10xM7AX+2/WC97xbAisA426/UMV11zx4NnFPH3ifpGmAdym/RK/fMnJlG3QPA5PZ2xrS19XcYERERERERsQAYDBVdZwOfkbRwTUKNAP7WOClpUeC3wP9n786j7KrK9I9/H5lDAQHB0GEUFVRQQhsEByS2NAqCI9ISZBARxR/azgqIQMsgKKIgNjTKJLMg2qLMGmUQNEC0RQERiGEKhBCgkjDm+f2x9w2Xy701hEpuUvV81jqr6pw9nPecAtby9d37XE6pBvo0cJakjZrm2Bn4GrA68CTwe+Cmen4B8J1BzIWklwJXAdfa/gywKvBL4DjgpXW+X9Z+A2L7D8A9lGTcQL0P2IKSwAL4IyVBtxql8uknkpZv6v8e4FxgNCUx9P36PMsCP6MkFVcDfkJJBnZyPfB5SZ+S9DpJGkTMuwOnN51vCdwGnC7pYUl/lLR1H+O/C+wuaZn6d3kTcOUg7h9LmHE9PUwcM6bbYURERERERMRiYDhUdN1DSYRsQ1kid0ZL+5ZAD/BN2/OAX0u6GNgFOKT2ucj2jQCSLgI+ZfuMen4epTJqoHONBX4LnG77W/Xau4G/2/5xPT9H0meAHYHTBvGs91ESTQN1pO2ZjRPbZza1HSPpa8BGlCo2gGts/wpA0o8p1WBQnnsZ4Lu2DVwg6fN93Rd4BNgVOBZ4WNL+tk/vYwyStgLGUJKLDWsD2wJ7Ax+lJNh+LumVtme0meZiyj8DXwSWAv7L9h/7um8nG40axaTNNluQoRERERERERHRBcMh0QUlsbEn8GbgbZTldQ1jgWk1MdUwFVir6Xx60+9z25w31kUNZK53A73AiS0xTG2JuXXcQKwFzOy313OmNZ/UDd73rvEYWJlStdbwQNPvc4Dl6/5eY4F7a5KrofV55qvLBk8ATpC0ArAXcIqkP9j+Wx/x7gFcaLu36dpc4G7bjf3JzpV0IPAW4Octz7cacCklMXk2sCYlKTfd9g/6uG/EiDalt3ehLdOdOGYM+4wdu1DmjoiIiIiIaDUcli5C2bj83cCdtlsTMPcB67R8sXBdyv5agzWQuU6mJFt+JWnFpnHrtcw1qBgkbU5JdF1TL80GRjV1WbPNsPmJqVot9RXKMs1VbY8GHgUGsqzwfmCtliWI6w4kbttzbZ9AqfB6bad+NSH2IZ6/bBHgz/S9H1izDYBnbZ9h+xnb91CWYm4/wPERMYSm9PZy9vTp/XeMiIiIiIgYIsOiosv2bEn/RkmmtLqBkhT6sqRjKJVAO1I2TB+sgc61HyXhdbGk7Smbtx8vaSJwPmX53Wspy+z6JGllSpXa9yibz/9fbZoCfEDSDw0oLFYAACAASURBVCkVVx/j+ZVorVYCngEeApaW9FVKRddA/L6O/YykEyh7eb0R+E2HmD9b47sBeJqyhHEl+t5E/v3ArDZzXgR8W9IelP3Y3k9J+F3bZo7by+01kZLgehnwH8Cv+3/EiJFrXE/PQlmmm485RERERETEojZcKrqwPdn2P9pcf4qSmNkOmAH8ANjd9q0LcI8BzVWX+O1DWTr4c0pybAfgC8DDwJeBHTrsMdXwC0mP1zkOpGxg/9Gm9mOBpyjJrdOBs/oJ/zLgEkoyaCrl64rT+hzx3PM8Rfla456UZOJ/AD/tY8hc4BjKUsgZwP8DPmj7zj7G7AGc0bI8krrH2Hsoe249Svka5nsb707SiZJOrH0fq3F+rsY5BfgLcPhAnjMiIiIiIiIilmxqySsstiQ9Qfki4nG2D+p2PLHkkfQOyjLX5YDtbbetSGsYP368J0+evEhii+iWRtXVwqzoykcdImI4y3/rYriZMKH8nDSpm1FERPRN0o22x7drW2KWLtpevtsxxJLN9lXA6G7HERERERERERELx7BZuhgRERERERERESNbEl0RERERERERETEsjLhElyRLmi1pwBuUS5okae8ObevXORfrZaB10/YRvbeZpG0k9UqaJ2mbbscTEREREREREUNrxCW6qk1tH9g4kbSspEMk/b0mwe6WdIqk9bsXIkg6QNJdNTlzj6Tzmto6Jt/asf1J299YOJE+X32fx9SYe+szHNvPmP+s/WZL+pukDet1STpQ0j8lPSbpXEkrd5hj3Xq/5sOSvgBg+0rbPcA/h/yhIyIiIiIiIqLrRmqiq9UFwHuAicAqwKbAjcA7uhWQpD2A3YBtanJmPHBVt+LppEMl2/6UeN8IrAS8Hbi5jzn2Bj4GvBvoAXYAZtTm3Snv4S3AWGAF4Ph289j+p+2exgG8DphH+dJiRERERERERAxzi/Vyu0WhLmH7d2BD29Pq5UeBE1q6rifpWuD1wO+BibZntPRB0ljgROCtwEzgKNsn17aXAF8GPk75+t9VwCdtz2wT2ubAZbb/AWD7AeB/6jyHA1sBW0r6LnCa7f0kvZqSBHoD8BBwkO3z65jTgHtsf03SBOBM4FjgK8CzwAG2T619lwMOB3YGlgMuAj5ne27T2OOBzwFXUBJRrbFfZPu+en53PV6gvpODgT1t/7Ve/kdTlx2BHzX+NpKOAn4taV/bc9rN2WR34He22967P7fNmTP/k+ERw9WU3l7G9fR0O4yIiIiIiIghkYou2Ab4Q1OSq5OJwEeBlwHLAl/s0O8c4B5K9dFOwBGSGpVhnwHeB2xd2x/hhQm1huuB3SV9SdJ4SUs1Guqyy6uB/Wr10n6SVqQknc6uMe4C/EDSxh3mX5NSvbYWpZrqBEmr1rajgA2BccAra5+vt4xdDVgP2KdD7J+X9ClJr5OkDjEArF2PTSRNq8sXD60JMADVg6bz5YBX9TFnw+7A6QPoFzFijevpYeKYMd0OIyIiIiIiYkiM+Iou4KXA/QPod6rt2wEknU9Z6vg8ktahVHLtYPsJYIqkH1Iqnq4CPkFJTt1T+x8C/FPSbrafaZ7L9pmSTEmuHQI8Ielbtr/ZIb4dgLsbVVnATZIupCTbbmnT/2ngv+p9fyWpF9hI0g2UirPXNyrNJB1BSaDtX8fOAw62/WSHWI6kJPF2pVSNPSxpf9vtkk5r15/bUpYajgYupyQLTwYuAb5c3/kjlAo0gFEd7k2NeStgDGVZ6gLZaNQoJm222YIOj4iIiIiIiIhFLIkueJhSvdSfB5p+n0PZS6rVWGCm7cebrk2l7FcFpQLqIknzmtqfpSRk7m2dzPZZwFmSlqFUgp0l6Wbbl7W593rAFpJmNV1bGvhxh+d5uCW51nimNShJpBubCrEELNXU96GayGvL9rOUSrUTJK0A7AWcIukPtv/W0n1u/Xm07VnALEknAdtTEl2nAOsAk+rzHENZznhPp/tXewAX2u7tp19EREREREREDBNZughXAm+UtHa/Pft3H7CapJWarq3Lc0msacB2tkc3HcvbfkGSq5ntp23/BPgzsEnjcku3acBvW+busb3vIJ9hBiX5tHHTPKvUzd3nhzTQyWzPtX0CpRrrtW263AY81WlO2/NsH2x7fdtrU6rT7qVNYrChJtc+RJYtRkRERERERIwoI76iy/aVkq6gVFp9EvgT5ct+uwJP2T5lEHNNk3QdcKSkL1IqxT4GfKR2ORE4XNIetqdKWgN4s+2ft84laU/KhvK/A2YD7wQ2Bm6oXaYDGzQNuRj4pqTdgHPrtXFAb5sqqr6eYZ6kk4FjJe1n+0FJawGbdKgkewFJnwWm1FifprzLlWjz5UXbcySdR1meeDNl37CPA9+qc60GrArcCbwG+A5lyeW81rmavB+YBfxmIPFGxMIzpbd3if+ow8QxY9hn7NhuhxEREREREQOQiq5iJ+BXwHmULy7+hbLc8MoFmGsXYH1KdddFlL2srqht3wP+F7hc0uOUTdu36DDPY8ABwD8pSZujgX1tX9M0106SHpF0XF0uuS3w4XrvByibyi+3AM/wFeAO4HpJj1Hew0aDGD+XssTwAUqF2P8DPmj7zg799wN6a9y/p+wH1kgwrk7528ym7Nd1iu3/aQyUdKKkE1vm2wM4w/aAK88iItqZ0tvL2dOndzuMiIiIiIgYII20XICkJ4AngeNsH9TteGLRqV+/vJCS/Nvedp8VX+PHj/fkyZMXSWwRw1GjkmtJ/qjDcHiGiFi48t+JGG4mTCg/J03qZhQREX2TdKPt8e3aRtzSRdvLdzuG6A7bV1G+6hgRERERERERw1CWLkZERERERERExLCQRFdERERERERERAwLSXQNkCRLmi3p8G7HsiDqpu0jek8ySdtI6pU0T9I23Y4nIiIiIiIiIoZWEl2Ds6ntAyVtVRMmvTX55abzXknrDsXNJB0g6a465z2SzmtqmyRp74HOZfuTtr8xFHH1R9Kyko6pMffWZzi2Q991W95db32fX6jt75Z0jaRZkh6QdLKklfq4992S5jbNdXmjzfaVtnsoX7KMiIiIiIiIiGFmxG1GPxRsXw30AEhaH7gLGG37maG6h6Q9gN2AbWz/Q9KawHuGav6hImnpNs+9PzAeeCNwP7Ae8LZ2423/k/ou63wvB+6gfB0RYBXgMOB3lK8lng18C/hkH2HtaPvKQT9Mi9vmzJn/JaUYGhPHjGGfsWO7HUZEREREREQMU6noGmKSVpH0I0n3S7pX0mGSlqptL5H0NUlTJT0o6QxJq3SYanPgMtv/ALD9gO3/qfMcDmwFfL9WLX2/Xn+1pCskzZR0m6Sdm+I6TdJh9fcJtdrqCzWO+yV9tKnvcpK+LemfkqbXZY8rtIz9iqQHgFM7xH6R7ftc3G37jAG+wt2B39m+uz732bYvtT3H9iPAycBbBjhXLEam9PZy9vTp3Q4jIiIiIiIihrFUdA2904HpwCuBFYGLgWnAScCe9Xg78CBwBvB9SuVWq+uB4yTdC/wGuNn2swB1+eRbgDNt/xBA0orAFcDXge2A1wOXS7rF9i1t5l+TUi21FvDvwAWSflaTSUcBGwDjgKcpVVRfp1RqNcauRqnUapcsvR74vKSngKuBv9h2n2/tObsDfS2xfBvQ7nmanSXpJcDNwJds/2mA936ejUaNYtJmmy3I0Ggj1XERERERERGxsKWiawhJGkNJMn3W9mzbDwLHAh+uXXYFvmP7Ttu9lMTRhyW9IOFo+0zg08A7gd8CD0r6ah+33wG42/aptp+xfRNl+d9OHfo/DfyX7adt/wroBTaSJODjwOdsz7T9OHBE0zMAzAMOtv2k7blt5j6SkizbFZgM3FuXYvZJ0lbAGOCCDu3/DuxBSbp1siuwPiUJ9xvgMkmj+7t3RERERERERCz5UtE1tNYDlgHuL/kioCQTp9XfxwJTm/pPpfwNxgD3tk5m+yxKddIywPvq7zfbvqzDvbeQNKvp2tLAjzvE+nDL3lpzKHtlrQGMAm5segYBSzX1fcj2Ex3mpVaenQCcUJc87gWcIukPtv/WaRwliXVhTQI+j6QtKZVlO9m+vY97X9t0emRNsG0F/KKP+0ZERERERETEMJCKrqE1DXgSWN326HqsbHvj2n4fJSHVsC7wDGWpY0e16uonwJ+BTRqX29z7t033HW27x/a+g3yGGcBcYOOmeVapXyucH9JAJ7M91/YJwCPAazv1qwmxD1GWfra2bQb8L7CX7asGeu+mWNVvr4iIiIiIiIhY4iXRNYRs3w9cDhwjaeW6+fwrJG1du5wDfE7SyyX1UJYEntfua42S9pT0bkkr1Xm2AzYGbqhdplP20Wq4GNhQ0m6SlqnH5pJeM8hnmEfZ8P1YSS+rsawl6Z0DnUPSZ+um9StIWrpWVa1E2TOrk/cDsyjLDZvn2gS4FPi07T6rsiStK+ktkpaVtLykLwGrA9f2NS4iIiIiIiIihocsXRx6uwPfBP5KSe7cSdmvCuAUyvLF3wHLA5dR9uFq5zHgAOBMyrLBqcC+tq+p7d8DTpe0L/Bj25+RtC3wnXq8BPgT8PkFeIavUPbBul7S6pRllf9d4x2IucAxlA35DdwOfND2nX2M2QM4o82m9V+gLKf8kaQf1WtTG1Vykk4EsP1Jyvv+b+AVwBPAFGA72w8PMO5YyKb09mZT+hFkSm8v43p6+u8YERERERExRDTwj+GNbJKeoCxLPM72Qd2OJwZP0jsoG/QvB2xv+zd99R8/frwnT568SGIbCSbcfHMSHyPQxDFj2Gfs2G6HscAaidl8gTUiOsl/J2K4mTCh/Jw0qZtRRET0TdKNtse3a0tF1wDZXr7bMcSLU/f3yhcYu2hcT0/+h0BEREREREQsNNmjKyIiIiIiIiIihoUkuiIiIiIiIiIiYlgYUYkuSZY0W9Lhi+h+h0g6s0PbAZJ+uCjiWFjq+3xlt+MYDEmnSZor6Z5uxxIRERERERERQ2tEJbqqTW0fCCBp/Zqs+WVzB0lnSjpkYQZh+wjbe7drkzRB0jxJvfW4R9L5kjZfmDENJUkbS7pc0iOSZkm6UdL2Hfoe0PSsvTURNa9+8RFJ35b0d0mPS7pV0u593PdfJP2vpPvq33b95nbbewLbDd2TRkRERERERMTiIpvRF1tKeovta7sdSJP7bK8tScBawD7A1ZLeXTdVHxRJS9t+Zsij7OwXwH8DO9TzzQG162j7COCIxnlNMr7N9ox6aTawI3B7nedSSXfYvq7NdPOAS4EjgXbtA3bbnDnzv6QUL16+uBgREREREREL20is6GrnaOCwdg2SVpV0saSHanXSxZLWbmofWyuIZkq6Q9LHO8yzjKRzJF0oadm+ljU2c3GP7a8DPwSOqvM1qtHmJyslTZK0d/19T0nXSjpW0kzgEEmvkPRrSQ9LmiHpLEmjm8bfLemLkv4s6VFJ50lavqn9S5Lur9VSe3WKuVZivRw42fZT9bjW9jX9PW9N7O0GnN70Dg62favtebZvAK4G3tThfU23/QPgj/3dKxatcT09TBwzptthRERERERExDCWiq7iBOAzkraxfWVL20uAU4GdgaWAU4DvA++r7ecAtwBjgVcDV0i6s7nqStIKwAXAQ8BHbD9b8jmD9lPgU5JWHGD/LYBzgZcBy1Aqw44EfgesDFwIHAJ8tmnMzsC7gCeAa4E9gRMlvQv4IvAO4C7g5D7u+zBwB3Bm3Yfs97anDzDmrYAxNbYXqO9yc+AHA5xvgW00ahSTNttsYd8mIiIiIiIiIoZIKrqKJ4DDaVPVZfth2xfanmP78dpvawBJ6wBvBb5i+wnbUyhVV7s1TbEyZSndP4CP2n72RcR5H2X53+j+Ojb62z7e9jO259q+w/YVtp+0/RDwncazNDnO9n22Z1KWH46r13cGTrX9F9uzKQmytmwbeDtwN3AMcL+k30l61QBi3gO4wHZvh/YTgT8Blw1groiIiIiIiIgYQVLR9ZyTgS9J2rH5oqRRwLGUKqdV6+WVJC1FqeKaWRNgDVOB8U3nW1KqqXapCaAXYy3AwCxgjQH0n9Z8IullwHGUqqmVKInOR1rGPND0+xzKM1J/3tjUNrWvG9u+B9iv3ncd4H+AM+iw5LD2WwH4EPDeDu3fAjYB3j4E7zIiYkCm9PYu1vv1TRwzhn3Gju2/Y0RERETECJCKrsr208ChwDd4/qbpXwA2ArawvTLwtnpdlAqr1SSt1NR/XeDepvPLKcsFr5L0Yjcoej9wU62oml2vjWpqX7Olf2sy6Mh67fX1WT5Chw3i27gfWKfpfN0BjsP2NMry0E366foBYCYwqbVB0qGUryVua/uxgd47ImI4m9Lby9nTB7oyPCIiIiJi+EtF1/P9GPgKpXrr7/XaSsBcYJak1YCDG51tT5N0HXCkpC8CGwIfoySQaOp3tKTlKMmuCU1fE+xX3Zx9LLB3Pd5T53xI0r3ARySdRFny94p+plsJeLQ+y1rAlwYaB3A+cKqkMyhLEg/u1FHSqpR9v34M3AmsBuwFXN/PPfYAzmit1pK0PzCR8iXGh/sLtG6gv1Q9XU7S8raf6G9cREQ743p6Ftv9+hbnSrOIiIiIiG5IRVeTun/WwZTETMN3gRWAGZREzaUtw3YB1qdUd10EHGz7ijZzfwP4GXBlTZj1Z6ykXqCX8gXB1wETbF/e1OfjlGTVw8DGwHX9zHko8K+UZNcvKZvbD4jtSyjv4teUjeZ/3Uf3pyjv5ErgMeAvwJOUje3bqom3f6Msb2x1BKWC7O+SeutxQNPYXklbNfWfS3lvALfW84iIiIiIiIgY5jSStjqS9AQl4XKc7YO6HU8sepJ+RNkH7EHbr+yr7/jx4z158uRFE1hELJYaFVOLe0XX4hpfxEiQfw9juJkwofycNKmbUURE9E3SjbbHt2sbUUsXbS/f7Riiu2x/jLK8NCIiIiIiIiKGmRG3dFGSJc2WdHi3Y4lFT9JpkuZKuqfbsURERERERETE0Bpxia5qU9sHNk4kLSvp65Juq0mweyVdImnbbgbZl5qw63PpXTdImtAuiSRpkqS9+xi3hqSzJc2S9Iiks5raVpN0nqQZ9ThL0sp9zPVpSXdJekzSZElvbbTZ3pPy9caIiIiIiIiIGGZGaqKr1QXAe4HdgVWBlwPfA97drrOkRbbkc1Heq8t+CjwArAe8DPh2U9thlL/LBpQvS44BDmk3iaQtgG8COwGrAD8CLpK0VLv+ERERERERETF8jPhEl6RtgH8H3mv7BttP1eNS2//Z1O9uSV+R9GdgtqSlJW0p6bpahfQnSROa+r9c0u8kPS7pSkknSDqzqf09km6pYydJek1f9xrE86wi6QxJD0maKulrkl5S2/aUdK2k4yU9KulWSe9oGfsjSffXqrbDGgmi+ny9TYebn/fFqJVz6wBfsv2o7adt39zU5eXAz2w/ZvtRytctN+4w3frALbZvdPnSwhnA6pTkWUREREREREQMYyOlWqgv2wA32B7Ink27UKq8ZlCqin4J7AZcCrwDuFDSq20/BJwNXFvnfyPwK+B/ASRtCJwDvA+YBHwO+IWk19p+qvVetp8ZxPMcT6lk2gB4KXA5cD+lsglgC0oF2+rAB4CfSnq57ZnA6cB04JXAisDFwDTgJNubNm4gaR/g88BNg4irL1sCtwGnS9oOuBP4ou3f1vYTgE9JOqeef5D6Ltu4BPhyreyaDOwFTKFUiw3KbXPmzP+SUiy5Jo4Zwz5jx3Y7jIiIiIiIiFgERnxFFyXhMz8JUveDmlUrnp5o6Xuc7Wm25wIfAX5l+1e259m+gpJY2V7SusDmwNdrddg1PD8x8x/AL21fYftpyjK9FYA3d7jXgNTqq/8A9rf9uO27gWMoybiGB4Hv1qqp8ygJpndLGkPZu+qztmfbfhA4Fvhwyz3eSllK+B7bj3UIZWx9h/MP4K0d+gKsDWwL/AZYs8b8c0mr1/abgGWBh+vxLPCDDnM9DlwIXAM8CRwM7FOru2KEmdLby9nTp3c7jIiIiIiIiFhEUtFVEievapzUyqbRdaP3v7f0ndb0+3rAhyTt2HRtGUqyZiww0/aclrHr1N/HAlOb7jlP0jRgrQ73GqjVKQmhqU3XprbMe29L0mdqjWe9Gv/9khptL2mOQ9I6wPnAHrZv7yOO+2yv3XxB0qQ++s8F7rbdqDo7V9KBwFuAnwM/Af5E2UdNlMTgmcDObebam1LFtTFwByWBdrGkzWzf10cML7DRqFFM2myzwQyJxUwq8iIiIiIiIkaWVHTBVcDmktbutyc0J4imAT+2PbrpWNH2NylLBVeTNKqp/zpNv99HSSwBoJJZWge4t8O9BmoG8HTz3MC6LfOupaZMVm2/rz7Pk8DqTc+zsu2Na4wrAD+jVINdsgCx9eXP9P28m1KWT8623QucCGzfR99f2L69VtpdSvl7vLlD/4iIiIiIiIgYJkZ8osv25ZQqrJ9J2kLSspKWoewb1ZczgR0lvVPSUpKWlzRB0tq2p1KWMR5S53sT0Fz5dT5lueA76r2+QEkyXTfI8Jet911e0vJNcx8uaSVJ61H20jqzaczLgM9IWkbSh4DXUJZg3k/Zz+sYSStLeomkV0jauo47BbjV9tGDjHEgLgJWlbRHfZc7UarQrq3tfwT2lrRCTbjtQ6nwauePlHe7gYp/BzYE/rIQ4o6IiIiIiIiIxciIT3RVH6BsvH4mMAu4C9gVeFenAbanUZbSHQA8RKmI+hLPvdNdgTdRlkYeBpxHSWZh+zbKHl/HU6qwdgR2bNqIfqBuoSz7axwfBT4NzKZs6H4NZVP8U5rG3EBZqjkDOBzYyfbDtW13ytLHvwKPUDat/5fa9mHg/S1fXtxqkPG2VZeLvgf4IvAo8FXKVzBn1C57Ub6meA+lOm0DYM/G+JZYzgDOpWzy/xhwHPAJ27cORawRERERERERsfgaiXt0PQncKOk42wcB2H4SOKQebdlev821G4CtX9gbbP8DmJ8IknQecGtT+0WUSqYB3atNH/XR/JG+h3o/YL82DY8C+9ZjMPdr7jeJsrl86/UJ/Yy7Gnhdh7a7eH5FXGt7T9PvBr5ejxeQ9CPgQ5RN+SMiIiIiIiJiGBlxiS7by/ff68WTtDkwk1Idti2l+uubi+Le0ZntjwEf63YcsehM6e1dYjelnzhmDPuMHdvtMCIiIiIiIpYYIy7RtQitCfwUeCllyd2+tpfM/7UdEYvclN5egCS6IiIiIiIiBiGJroXE9i+AX3Q7jma2TwNO63IYEYvUuJ4eJm22WbfDGLQltQotIiIiIiKim7IZfUREREREREREDAtLdKJLkiXNlnR4t2NZUtV3+Mpux7GoSDq0/jNjSalojIiIiIiIiBhGluhEV7Wp7QMBJK3fnMBQcbykWyWt9WJuMhQJIUkflnRDTbQ8WH//lKQBfdFwSdD6N2i6fpqkwzqM2VVSb9Mxp87xhpZ+y9a/5T0DuH/zfAc12m0fDGz8Ih8zIiIiIiIiIhZDwyHR1VZNHp0ETAC2tn1vl+P5AvA94FuUjerHAJ8E3gIs28XQus72WbZ7GgfwKeBO4KaWrl8CHhzgtKOb5vzGUMYbEREREREREYun4bp0ayngR8DrgAm2HwaQ9GrgeOANwEPAQbbPr22nAbOB9YG3AX8FJtr+h6Tf1Xn/JMnAx4DLgR8DW1De47XAJ22/oNpI0irAfwG7276wqelmYNeWfscD2wFzgJOBI2zPk7QnsDdwfb3/LOBTti+R9CbgiqZ5lwYesL2+pDdSEmyvAeYCFwKft/1UmziXAw4HdgaWAy4CPmd7rqRfAG9v6j4K2KtucD/U9gDOsO2m2F4OfAT4POW9LHS3zZmTDcGXcFN6exnX09PtMCIiIiIiImIRGa4VXWcBrwb+rSnJtSIlGXQ28DJgF+AHkpqXse0CHAqsCtxBSfpg+221fdNaIXQe5d2dCqwHrEtJIn2/QzxvoiSOft5P3McDqwAbAFsDuwMfbWrfArgNWB04GviRJNn+fVM11KqUZNg5dcyzwOfqmDcB76BUTLVzFLAhMA54JbAW8PX6DnZsusdOwAPAVf08z6BJWo+SaDyjpel44ADKex6IqZLukXSqpNWHMsZYcozr6WHimDHdDiMiIiIiIiIWkeFa0bUtcKjtWU3XdgDutn1qPb9J0oWUpM0t9dpPbf8BQNJZwHc63aAm0OZXZ9UN8X/TofvqwAzbzzT1vw54LSUB9k5KRdh/AJvZfhx4XNIxwG6U6jSAqbZPruNPB35AWQL5QNO9jqNUph1Y47yxqe1uSSdRkmjfbQ6wLvX8OPB62zPrtSMoicH9m/ptSElCfdD2tE7vB5jRsvXYKEpyrj+7A1fbvqvpnu8HlrZ9kaQJ/YyfAWwOTAFeCpxASXy+cwD3fp6NRo1i0mabDXZYRERERERERHTJcE107QBcLOkR26fUa+sBW0hqTn4tTVl+2NCcMJoDdFzzJGkUcCzwLkoVFcBKkpay/WxL94eB1SUt3Uh22X5zneceSnXY6pS9uqY2jZtKqap6QXy259RE0vwYJX2CsifZlrbn1WsbUhJ24ynJpqWB5uRXwxq1/camBJUoy0Ab869CqUo7yPbVHV5Nw+otib3T+unfsDtwRNO4FSkJsu0HMth2LzC5nk6XtB9wv6SVbT82wBgiFgtTenuzfLbLsvw1IiIiImLJMlyXLl4H7Ah8T9LEem0a8Fvbo5uOHtv7LuA9vgBsBGxhe2XKcjsoyaFWvweeBN7bx3wzgKcpCbmGdYEBbaIvaSvgG8B7bT/a1PTfwK3Aq2qcB3SIcQZlWeDGTe9nlbpUEUkvoVR3/cb2SQOJabAkvQUYC1zQdPlVlH3Trpb0APBT4F8kPSBp/QFM29jna9h82TIiFp0sf42IiIiIWLIM14oubP9W0geAiyQ9BVwMfFPSbsC5tds4oNf23wYw5XTK3ll31POVKImhWZJWzLacqQAAIABJREFUAw7uI5ZZkg6l7Akm4FJKxdjrgRVrn2clnQ8cLml3YDXKxuvf7i8wSesA51E2u7+9pXkl4DGgt27Gvy9lI/7WGOdJOhk4VtJ+th+UtBawie3LKPuVrQj8Z3/xvAh7ABfWpZsNfwHWaTp/M2UvtH+lzXNI2oKyUf/fKZV2xwGTWpJ/EUuEcT09WT4bERERERExCMO1ogsA21dQ9r06jbKkb1vgw8B9lGWAR1H2yBqIQ4DTJc2StDNlj6sVKJVQ11OSV33FcjQlcfVl4EFK4uwk4CuUCjSAT1P217oTuIZSQXXKCyZ7oXcAawIXSOqtR2PfsS8CE4HHKV8rPK+Peb5CSeRdL+kx4EpK1RqUjfq3BB5puseuHeYZNEnLU772eHrzddvP2H6gcQAzgXn1/Nk69pamWDag/C0epyTJnqyxR0RERERERMQwJ9v991pMSXqCksg4zvZB3Y4nFn+SDqYkHJcDVmyzn9p848eP9+TJkzs1RyxUjb25UtEVfck/JxHdl38PY7iZMKH8nDSpm1FERPRN0o22x7drW6KXLtpevtsxxJLF9qHAod2OIyIiIiIiIiKG3rBeuhgRERERERERESNHEl0RERERERERETEsjLhElyRLmi3p8IV8nwMk/XBh3mOg6sbxG3Q7jm6TtGF9F89K2rvb8URERERERETE0Bpxia5qU9sHAkhavya/lq7nknS8pFslrbWgN7B9hO0FSqZIWlvShZJmSHpU0v9J2rNdvAOMpcf2nQsSy2BJmtSaRJI0QdI9fYzpbTmelXR8bdu1pW1Off43dJhrfUm/kvSIpAckfb/xrmzfbrsHuHoIHzkiIiIiIiIiFhNL9Gb0Q02SgJOANwFb257epVB+DPwJWI/yVcnXAWt2KZaOJC3V11cLB6omnxpzrghMB35S284Czmpq3xM4CLipw3Q/AB4E/gUYDVwBfAo4brBx3TZnzvwvKUUsalN6exnX09N/x4iIiIiIiJhvpFZ0tbMUcBowHpjQSHJJerWkKyTNlHSbpJ3r9S1rxdBSjQkkvV/Sn+vvh0g6s/7eqMLaQ9I/a6XWgX3Esjlwmu3Ztp+xfbPtS2rb7+rPWbXC6U31HntJ+lutZLpM0npNcVnSK+vvp0k6QdIvJT0u6QZJr2jq2/Z5m8b+d62Ymg28fYHedN92oiSqOlVd7QGcYdsd2l8OnG/7CdsPAJcCGw99mBEL17ieHiaOGdPtMCIiIiIiIpYoqeh6zlnAOsC/2Z4F86uLrgC+DmwHvB64XNIttq+vyZ5/q30AJgJn93GPtwIbARsCf5D0U9t/a9PveuCEunzvOtv/bGp7G3AXMNr2MzXO9wEHADsCfwe+CpwDvLlDHLsA76JURZ0OHA58uJ/nvaXpGbcHdgCW7eNZF1THRFZN3r0N2KuP8d+jPMskYFXKcxy0IIFsNGoUkzbbbEGGRkREREREREQXpKLrOdtSKoFmNV3bAbjb9qm1suom4EJK1RGUZNIuAJJWoiSAzunjHofanmv7T5SliZt26PchSkXTQcBdkqZI2ryPeT8BHGn7bzX5dQQwrrmqq8VPbf+h9j0LGDfA5wX4ue1rbc+z/USH+Y+TNKtxABf3Eft8ktYFtqYk39rZHbja9l19TPNbSgXXY8A9wGTgZwO5f0REREREREQs2ZLoes4OwMGSmquF1gO2aEna7Mpz+2WdDXxA0nLAB4CbbE/t4x4PNP0+B2i7AY/tR2x/1fbGwBhgCvCzuodYO+sB32uKcSYgoNNm+p3i6O95AaZ1frz5PmN7dOOgvNuB2B24po9E1u50ToIh6SXAZcBPgRWB1SlVXUcN8P4RERERERERsQRLous511GW/n1P0sR6bRrw2+akTf2C4b4Atv8KTKUsj+tv2eICsT0D+DYwFlgNaLc31TTgEy1xrmD7ukHers/nbYS0QA8yMB0TWZLeQnkHF/QxfjXK8tPv237S9sPAqZRKu4iIiIiIiIgY5pLoamL7t5TKrP+RtBNlyd2GknaTtEw9Npf0mqZhZwOfoewd9ZOhiEPSUZI2kbR0XRK5L3BHTdw8BMwDNmgaciKwv6SN6/hVJH1oAW49kOddKCS9mVKB1ukd7gFcaPvxTnPUpOBdwL713Y2u4/401PFGRERERERExOInia4Wtq8A/oPyBcYJlL27PgzcR1nydxSwXNOQc2q/X9dEy1AYBVwEzALupCwpfE+Nbw5l8/hr6/LCLW1fVOM6V9JjwF8oVWaDUpNI/T3vwrIHZe+wFySyJC0P7Eybai9JB0i6pOnSBygb7T8E3AE8A3xuoUQcEREREREREYsVtfm43bAm6QngSeA42wv0Nb5YMkl6FfBHytciP2X7tL76jx8/3pMnT14UoUVELJAJN98MkC/ERnRR/j2M4WbChPJz0qRuRhER0TdJN9oe365t6UUdTLfZXr7bMUR32P47MLrbcUREDKUpvb3z/4f2SDdxzBj2GTu222FERERERBdl6WJEREQs8ab09nL29OndDiMiIiIiumzEVXS1kmRgDvBd2wcuonteApxru+0XBlv6GniV7TsWfmTDn6R/UL7MeL7tj3Q7noiIF2tcT0+WTEGq2iIiIiICSEVXw6aNJJek9SVZUm89pku6WNK/D9XNbG83kCRXfyRNkrT3UMQ01CS9V9IUSY9JmiHpKknrd+g7WtLpkh6sxyEt7etL+o2kOZJulbRNH/dV/Wrlw/U4WpIa7bZfARwxNE8ZEREREREREYuTJLo6G227B9gUuAK4SNKe3Q1pySDplcAZwBeAVYCXAz8A5nUYcizlS5PrA28EdpP00ab2c4CbgZcCBwIXSFqjw1z7AO+j/N1eD+wAfOJFPE5ERERERERELCFG/NLF/th+APiepGWAoySdYXuepK8CHwdeBkwDDrR9EUBNiO0NXA98DJhF+crfJbV9EnCm7R/W872ALwFrAn8A9rE9dUFjlvQS4IAa3wrApcCnbT9aq6ruoiR/DgEEfNv2MU1jv1zHjgauAj5pe6ak7wN7Nt1qeeAw24e0hDAOuMv2VfX8ceDCPkLeEdjO9hzgbkk/AvYCTpW0IfCvwLa25wIXSvos8EHgxDZz7QEcY/ue+jzH1Gdp17dPt82Zk6UwI1g2tY6IiIiIiFjypKJr4H5KSWptVM//AWxFqVg6FDhT0r809d8CuA1YHTga+FHzEroGSe+jJKU+AKwBXE2pYHox9qzH24ENgB7g+y193g68CtgW+GrTcsDPUCqitgbGAo8AJwDY3s92T610e2tt+3mb+98EvFrSsZLeLqlnADGr5fdN6u8bA3fafryp/U/1ejsb1/aB9I1oK5taR0RERERELJlS0TVw99WfqwHY/klT23mS9qcsu2skfqbaPhlA0umUpXtjgAda5v0EcKTtv9W+RwAHSFrvRVR17Qp8x/addc79gb+0LAc81PZs4P8knQrsAlxZ49mvqSLqEOCfknaz/Uy9tgbwM0qV2AtKnmzfKWkC8HngfGAlSefWeXvbxHspJdm2B+Ud7UVZygglSfdoS/9HgbU6PHtr/0eBHkmy7Q5j2tpo1Khs8DxCpZIvIiIiIiJiyZSKroFrJFZmAkjavW62PkvSLEoF0upN/ecntOqSPChJmFbrUZZGNuaZSalo6pTIGYixQHOSbColqTmm6dq0lvbGGq31KPuRNeL5G/BsY2xdwnkBcLbtczsFYPt62zvbXoNS+fY2yv5a7XwGmAv8nZIoPAe4p7b1Aiu39F+Zshyyndb+KwO9g01yRURERERERMSSJ4mugXs/8CBwm6T1gJOB/YCX2h4N/IXnL78bqGnAJ2yPbjpWsH3di4j1PkrCqmFd4BmgeS3WOi3tjYq1aZT9sprjWd72vbX9eEqS6WsDDcb2HylLPzfp0D7T9q6217S9MeWfyz/U5luADSSt1DRk03q9nVtq+0D6RkRERERERMQwkkRXPySNkbQfcDCwv+15wIqAgYdqn4/SIYkzACcC+0vauM61iqQPDWL80pKWbzqWoVREfU7Sy+v+WEcA5zWWHlYHSRpV7/tR4LymeA6vyTwkrSHpvfX3T1D27ppY30Nbkt4q6eOSXlbPXw28h7I5f7v+r5D0UklLSdqO8uXEwwBs3w5MAQ6uz/d+ytcUO21ufwbweUlrSRpL+fLjaZ1fX0REREREREQMF9mjq7NZdfP42cBk4EO2LwWw/df6Nb/fA/MoyZVrF+Qmti+qyahza3LpUeAK4Cd9j5zvv+vRcBawO2Up4u8oX0a8DPh0y7jfAndQkp3ftn15vf49SmXa5TVR9CAlCfZzyj5eGwD3Ne2rf4TtI1rmnkVJbB0maUVgRp3j6A7P8Abgu5SvPN4O7Gq7uQrrw5Rk1SPAP4GdbDeSjFsBl9QN8gFOqjH+Xz3/Yb0WEREREREREcOcRvrWRZKeAJ4EjrN9ULfjWdgkrQ/cBSzTUuE1Iki6jbL/2fm29+qr7/jx4z158uRFE1gsVibcfDNTensZ1zOQD4Z2x8QxY9hn7Nj+O8aw1vhwQj6ckXcR3ZN/9mK4mTCh/Jw0qZtRRET0TdKNtse3axvxFV22l+92DLHo2N6o2zFEvFhTesvHS5PoioiIiIiIeL4Rn+iKiGhnXE/PYvv/zjeqByIiIiIiIuL5kugaYWzfzYJ9HTIiIiIiIiIiYrE2Ir66KMmSZks6vNuxDBeS9pR0TbfjGAxJy0nqlfS0pMO6HU9EREREREREDK0RkeiqNrV9IJQN2Wvy65fNHSSdKemQF3sjSYdIOvNFjD9N0lOSHq/HXyQdKWmVFxvboiLpY5JurfFPl/RLSSt16LuapPMkzajHWZJWbmrfsb6DXknXSXptP/feRtJNNbk5TdLOALafrF9nPGtIHzYiIiIiIiIiFgsjKdHVzpaS3tLtIDo42vZKwBrAR4EtgWslrTjYiVQssr+1pK2BI4Bd6jO8Bji/jyGHAasCGwCvAMYAh9S5XkVJTH0SGA38AvhfSW2X3dYk2NnAgcAqwDjgxhf9UBERERERERGx2Bvpe3QdTUmyvL21QdKqwI+BLSjv6Vrgk7bvqe1jgROBtwIzgaNsnyzpXcABpYveB/zD9qad+vcXoO0ngD9Keg9wOyXp9f1aefZK2x+p8awP3AUsY/sZSZNqzBOAfwVeJ2kr4MvA2sBDNYaT6vgJwJnAscBXgGeBA2yfWttfCpxa57sVuKyPsDcHfm/75voMM4HT++j/cuBnth+r97oIeE9teydwte1rattRwNeBrYGr2sz1NeAk25fU84frMWi3zZmTTb9HqCm9vYzr6el2GBERERERETFII72i6wRgQ0nbtGl7CSWxsx6wLjAX+H5T+znAPcBYYCfgCEnvsH0ppZrpPNs9tjftq/9AA7X9OHAFsNUgnm83YB9gJWAq8CCwA7AyJWF2rKR/beq/JqUKai3gY8AJNeEH5V09AfwLsFc9OrkBeKekQyW9RdJy/cR5ArCDpFXr/T4INBJV4vmb5zfON+kw15YAkv5P0v11Oepq/dw/4nnG9fQwccyYbocRERERERERgzTSK7qeAA6nVHVd2dxg+2HgwsZ53cj+N/X3dSiVWTvUiqspkn5ISSy9oMposP37cB/whkH0P832LU3nzXuS/VbS5ZTE2U312tPAf9l+BviVpF5gI0l/pCSfXmd7NvAXSacDb2t3U9tXS/oA8CngP4GlJf0P8CXbz7YZchOwLM9VXl0F/KD+fgXwzVpxdh2l2mxZYFSHZ16b8l63pbyv04HjgV079O9oo1GjmLTZZoMdFhERERERERFdMtIrugBOBsZI2rH5oqRRkk6SNFXSY8DvgNGSlqJUZc2sVVYNUymVUO0Mtn8na1GWPQ7UtOYTSdtJul7STEmzgO2B1Zu6PFyTXA1zgB7KPmFLt8w3ta8b277E9o7AasB7gT2BvTt0/wllWeZKlGqzf1CWUWL7VmAPSjXd/TXev1Kq49qZC5xq+3bbvZTquu37ijUiIiIiIiIihocRn+iy/TRwKPANnr9E7gvARsAWtlfmueolUSqFVmv5iuC6wL2NaVtu01//fknqAbYBrq6XZvP8qqY12wybH0ddPngh8G1gjO3RwK94/jN38hDwDLBOS/z9sj3P9lXAr+m83HBTyr5as2ty6kSaklO2L7C9ie2XAgdTlpP+scNcf+aF7z8iIiIiIiIiRoARn+iqfgwsB7yr6dpKlOqgWXWPp4MbDbanUZbRHSlpeUmvp+xpdVbtMh1Yv/GlwwH070jScpLeAPwMeISybxjAFOBtktaVtAqwfz9TLVuf8SHgGUnbUZb39asuN/wpcEitdHstpcqqU8zvlfThuueWJL2Rsnn89R2G/BHYW9IKklag7Cv2p6b53iBpKUlrACcBv6iVXu2cCnxU0gaSRlGWOl48kOeMiIiIiIiIiCVbEl3MT+QcTFlm1/BdYAVgBiVBc2nLsF2A9SnVWhcBB9u+orb9pP58WNJNA+jfzpclPU5ZqngGcCPw5rpHFnXseZQKphvpJ5lTl01+BjifkjCbCPxvX2Na7EdZxvgAcBrPJdzaeQT4OPB34DHKMsRv2e6U2NuL8m7uoVS5bUBZ6tjwPWAWcFv9+fFGg6RdJc3fh8z2KZT3dQNleeWTlOeOiIiIiIiIiGFO9vBf5SXpCUrC4zjbB3U7nuiOunxzOrAMcLTtQ/vqP378eE+ePHmRxBYxGBNuvpkpvb2M6+kZ0nknjhnDPmPHDumcsXBNuPlmgHw4g7yL6J78sxfDzYQJ5eekSd2MIiKib5JutD2+XduI+Oqi7eW7HUN0n+0ngdHdjiNicTSltxcgia6IiIiIiFiijYhEV0TEcDOup2dIqwcaFQkRERERERFLsmGzR5ckS5ot6fAXOc9pkg6rv28l6bahiXDJ0/wuhgNJG0rqlfSs9P/Zu/Mou6oy/ePfh9lQQEAwGKaIDCq0BDuK0iKxRRQERVTEIIOKiPxwnplRULBVBoFGbRUwgAwCioAMahAQlQABQUQEwpwAgZBUBszw/P7Yu+TmcutWVVJJJZXns9ZdqXvOPvu851SxVvv2u9+tAwc6noiIiIiIiIjoX4Mm0VVtY/twAEkjavKrs+FzR08TNLJ9g+0tF0egNbbNGr5/UdITkrZaHPdb0iQdJunB+t4flXRBm7GdTZ95kr7fYtzR9b3t1Iv7by5ptqSxXcds/8N2B3DDQj9YRERERERERCy1loeli0Ntzx3oINqRdARwMLCj7X8MdDyLStL+wL7ATrbvl7Q+8O7uxtfkU9e1q1Maxl/UOEbSK4H3A0/0MozTgVv6GHpERERERERELMMGW0VXr0h6laRrJT0j6V5Je3UzbrSkRxu+T5T0NUl/k/SspJ9KWq3h/G6SJkiaKumPkl7bi1iOAw4E3tKV5JI0XNIvJD1Vq6I+3TD+GEkXSjpH0nRJd0sa1XB+Yq0Ou1PSc5Iu6G2MkraVdFud9wKg8bq7JO3e8H1lSU9LGtnisV4PXG37fgDbk2z/sKd3Ub0feJIXV12dBnwF+FdPE0jaG5gK/LaX94yIiIiIiIiIQWB5qOhaQK0YuhY4CtgFeC1wjaS7bd/diyn2Ad4BzAAuB44AjpD0OuAnwO7AeODDwK8kbVl3+2vlBGAbSpLr4RrfCnXeXwIfAjYErpN0r+2r63XvBvYEPgIcR0kCvbFh3r2AdwKzgZuAA4Az28UIGLgMOLnO9x7gfODEOuc5dfzl9fuuwBO2J7R4rj8Bp0p6DPg9cLvted28g2b7A+fYdtcBSR8A/mX7SkltL5a0JvB14G3Ax3p5z5bunTkzDbqXEWOGDctugREREREREbFcVHQ9XauXpkr6IrAbMNH2T23PtX0b8AtKJVFvnGb7EdvPAMdTklEAHwd+YPvPtufZPht4ngUTUM12Bn7TleSqXg+sZ/vrtv9l+wHgR8DeDWNutH1lTR79jJIsa3Sq7cdrjJcDXVVX7WJ8I7AycLLtObYvZsGlf2OBXWsiCcrSxJ+1eijbY4FPURKC1wNPSvpqm/cAgKSNgR2BsxuOdQDfBD7b0/XVN4Af236kl+NjGTehs5PzJk8e6DAiIiIiIiJiKbA8VHSt29ijS9KXge0kTW0YsxLdJG1aaEygPAR0lZFsAuwv6VMN51dpON/K3sCPJT1j++iGeYY3xbciCy7lm9Tw80xgNUkrNTxn8/nexGjgscZKqvp8ANh+XNJNwPskXUqphvtMdw9m+1zgXEkrA3vUn29vqEprZT9KEu/BhmPHAj9rOtZSXUa5E7BtT2N7Y8shQxi3bb9MFYtRqu4iIiIiIiKiy/KQ6Gr2CHC97bcv5PUbNfy8MfB4w7zH2z6+D3P9g5KYGSdplu0T6jwP2t58IeNrp9sYJe0IbCBJDcmujYH7G4adTeknthJws+3Herqh7TnARZK+AmwN9JToOqHp2NuADSUdUr+vB1wo6UTbJzaNHQ2MAB6uSxw7gBUlvcb263qKNSIiIiIiIiKWbcvD0sVmvwa2kLRvbai+sqTXS3p1L6//f5I2lLQOcBhwQT3+I+BgSdupWF3SuySt0W6y2hdsJ+BLkj4L/AWYJukrkl4iaUVJW0t6/cI97gLaxXgzMBf4tKSVJO0JvKHp+suA11Equc7p7iaSDuiaV9IKknYBtgL+3Oaa7YENaNptkZLo2pqy/HIkJbH4Ccquis1+CLyyYeyZwBWUJZQRERERERERMcgtd4ku29MpvbH2piRNJlEarq/ayynOA64BHqif4+q84yk9sE4DngX+SWkC35uY7qAkY46uc+xOSdQ8CDwN/B+wVi/ja3efbmO0/S9Kg/sD6rkPApc0XT+L0s/sFc3nmkyjJAEfpux++G3gk7ZvbHPN/sAl9ffTeM8pddfGSbYnAfOAZ213Akg6TNJVdezMprGdwGzbT7V9MRERERERERExKAympYvPA7dKOtX2kbYnAi236LN9L/Cubs4d0PDzOMquh41usf2tbq79DfCb3gRrW03fxwNrNxz6EC3YPqbp+0QantP2iB7GdxtjjaGnplQPA5d2JZq6mecS2ifCWl3ziV6OG9H0/Zttxh7T+F3S5pQG+6sAZ/Ulvli6TejsXK56dU3o7GRkR8dAhxEREREREbHUGTSJLturDXQMg11drvkxyo6Lyxzb9wFDBzqOiEU1sqODMcOGDXQYERERERERS51Bk+iKxUvSx4GTKTsg/mGg44loNLKjIztkRkRERERERBJdfdG8bG55YvtHlGb2ERERERERERFLpeWuGX1ERERERERERAxOy2WiS5IlzZB0/EDHEkuOpJ0kdUqaL2mngY4nIiIiIiIiIvrXcpnoqraxfTiApBE1+dVZPxMlfXVx3VjSFpIukvS0pOck3Snp85JWXFz3XJIkrSLpu5Iere/zQUkndTN244b33vWxpC80jPlUnWOapPGS3tzm3iMl3VDf66OSjuo6Z/s62x2UnSMjIiIiIiIiYpBJj64FDbU9V9Io4HpJt9q+tj9vIOmVwJ+BnwL/YfsJSVsCRwNrAFP7ON+Ktuc1fF/J9tz+jHkhfA0YBbwBeALYBHhLq4G2HwY6ur5LegXwT+AX9ft2wAn1+tuAg4FLJa3f+NwNzgMuBUYDI4AbJU2w/au+PsS9M2cy+vbb+3pZLGETOjsZ2dHR88Do0YTOzvzNL2Py9x8RERERsaDluaKrW7bHA3cDI7uOSfqopHskPSvpakmbNJyzpIMl3VfPny5J3Ux/LPBH25+3/US93722x9ieWue7SNKkWpX0B0lbNdzrLEn/K+lKSTOAt9YKtK9IuhOYIWklSV+VdL+k6ZL+Jum9DXNsJun6Ov/Tki5oOLeVpGslPSNpsqTD6vFVJZ0s6fH6OVnSqt084+uBS20/7mKi7XN6+fr3A/5ge2L9PgK42/attg2cA6wLvKyb60cA59qeZ/t+4EZgq27GxiAwsqODMcOGDXQYEQMif/8REREREQtKRVcLkt4IbA18q37fAzgM2B24D/gqcD6wfcNlu1ESPGsCtwKXA79pMf1OlIqndq4CPgr8CzgROJeGpBswBti13nOVeuxDwLuAp2tV2v3ADsAk4APAWEmb1eTaN4BrgLfW60fV51wDuA74Tn3WlYHX1PkPB95Y4zDwS+AI4MgW8f8J+LykfwE3AHfVJFVv7Ffja3wXX66VXePre5lQn6uVk4H9JB0JbAq8Cfh2L++9gC2HDGHcttsuzKURy6SRHR35m4+IiIiIiGVaKroW9LSkWcDNwBnAZfX4J4Bv2b6nLgv8JjCysaoLOMH21LoU7/csmJhq9FLKcr5u2f6J7em2nweOAbaRtFbDkF/avsn2fNuz67FTbT9ie1ad46JaUTXf9gWUBN0b6tg5lOWEw23Ptn1jPb4bMMn2d+vx6bb/XM/tA3zd9pO2n6JUpu3bzSN8i5Kg24eSnHpM0v7tnhlA0g7AMODihsPTKcsYbwSepyzxPKhN4uzXwPuBWcDfgR/bvqWne0dERERERETEsi+JrgWtS+kX9UVKj6eV6/FNgFMkTZU0FXgGELBBw7WNFUYzaeg71WQK8PLuApC0oqQT6rLDacDEhti6PNLi0gWOSdpP0oSGmLdumOPLNf6/SLpb0kfr8Y2A+7sJbTjwUMP3h+qxF6nLBk+3/V/AUOB44CeSXt3N3F32B35hu7Ph2IGUKq6tKNVnHwZ+LelF95a0DqWK7uvAavV53iHpkB7uGxERERERERGDQBJdTWqS5rvAbKArQfII8AnbQxs+L7H9x4W4xXXA+9qcHwO8h7LEcS1Kzykoial/h9kq9K4faqXZj4BDgZfaHgrc1TWH7Um2P257OKVa7QxJm9XnfGU3cT1OSfh12bgea8v2LNunA8/ywjLIF5H0EsoSy7ObTm0DXG77H7U67TeUirjtm+egLFWcZ/sc23NtPwr8nLLMMyIiIiLIE+QnAAAgAElEQVQiIiIGuSS6uncCpTfUasCZwNe6msJLWkvSBxZy3qOB7SX9j6T163ybSRoraShl58XnKZVfQyjLJPtqdUri66k6/0coFV3U7x+QtGH9+mwdO4+y7G99SZ+tzefXqL2xoPQkO0LSepLWBY4Cxra6eb1+tKSX1Mb4+9fnared23spO07+vun4LcC7JG2q4u3AFpTEXbN/lNtrjKQV6vv9IHBHm/tGRERERERExCCRRFf3rqAkgT5u+1JKz6mf1+WEdwG7LMykdSfAN1F3E5T0HKUH1XhKP6pzKMsCHwP+Rmns3td7/A34LqXX2GTgP4CbGoa8HvizpE7gV8BnbD9oezrwdkoj+kmUvl5vrdccV2O8E/grcFs91sqsev9JwNPA/wPeZ/uBNmHvD5zTovfWOZSqrHHANOBUSnXd3wEknSnpzPrc04A9gc9RfncTKL+r49vcNyIiIiIiIiIGCfV+M7zBQ9JsStXUqbZb7RoYg5Ckt1GSiqsCu9purh5bwKhRozx+/PglElvEQBt9eym4zK6LsazK33AMlPztxWAzenT5d9y4gYwiIqI9SbfaHtXq3EpLOpilge3VBjqGWPJs/5bSHD8iIiIiIiIiBqEsXQQkWdIMSVniNohJ2kJSp6R5kg4c6HgiIiIiIiIion8l0fWCbWwf3vWlJr82Wxw3kvRyST+W9ISk6ZL+LulYSasvjvsNBEmHSXqwJpYelXRBm7EjJF0p6VlJkySdJmmleu41ksbXc89Kuk5St7s3Nsy5uaTZkv7dML/u3NgB3NAvDxkRERERERERS5UkupYwSetQmsS/BHiT7TUoDeCHAq9ciPlWavouSQP6e627LO4L7FQTS6OA37a55AzgSeDlwEhgR+CQeu5x4P3AOsC6lOb5P+9FGKdTdmyMiIiIiIiIiOVEEl29IOksScc1fB8t6dGG7xMlfVHSnZKek3SBpO76gH2esrvih21PBLD9iO3P2L6zzneKpEckTZN0q6QdGu51jKSLJY2tO0AeIGmcpOMl3QTMBDaV9BFJ99SKsQckfaJhjnUl/VrSVEnPSLqhKzkmaSNJl0h6StIUSafV4ytIOkLSQ5KelHSOpLW6ecbXA1fXHSaxPcn2D9u84lcAF9qebXsS8Btgq3rtVNsT626MAuYBbSvtJO0NTKV9ci0iIiIiIiIiBpnlshn9YrIX8E5gNnATcABwZotxOwGX2J7fZq5bgK8DzwGfAS6SNML27Hr+PcAHgP0oOwh+mFJBtQtwLyUhtCWwG/AA8BbgKkm32L4N+ALwKLBene+NgCWtCPwa+F2dbx6lGov6PAcAb6VUX50DnFbHNfsTcKqkx4DfA7fbntfmeU8B9pY0Dli7PscCu2FKmgp0UJKzR3U3kaQ1Ke/ubcDH2tyzR/fOnPnvnZQiFsaYYcM4aPjwgQ4jIiIiIiJiuZGKrv5zqu3HbT8DXE5ZgtfKS4En2k1ke6ztKbbn2v4uJZm1ZcOQm21fZnu+7Vn12Fm2767XzLF9he37XVwPXAN0VYbNoSwT3KSOvaFWTL0BGA58yfaMWmF1Y71mH+B7th+w3Ql8jZKcelGy1PZY4FPAO4DrgSclfbXNI19PqeCaRknAjQcua5pzKLAWcCjQLvv0DeDHth9pMyZisZvQ2cl5kycPdBgRERERERHLlVR09Z9JDT/PpCSMWplCSTJ1S9IXgAPrHAbWpPSn6tIqibPAMUm7AEcDW1ASmkOAv9bT/wMcA1wjCeCHtk8ANgIesj23xfzDgYcavj9E+fsZBjzWPNj2ucC5klYG9qg/32776qY4VwCuBn4AbE+p2voJcCLw5aY5Z0g6E3hK0qttP9k010hKxdy2LeLvsy2HDGHctv0yVSyHUg0YERERERGx5KWiq3dmUBJFXdZfhLmuA97bXcP42o/rK5SlkGvXSqbnKMsRu7jFpf8+JmlV4BfAd4BhdY4ru+awPd32F2xvCuwOfF7S2yjJso1bVWlRmsJv0vB9Y2Au0LZkpVaMXQTcCWzdYsg6lATbabaftz0F+CmwazdTdiXtNmhxbjQwAnhY0iTgi8D7JN3WLsaIiIiIiIiIGByS6OqdCcCuktaRtD7w2UWY63uUCq2zJW0CIGkDSd+T9FpgDUoC6SlgJUlH1fF9sQplueNTwNxa3bVz10lJu0naTKWcaxqlF9c84C+UZZUnSFpd0mqS/qtedj7wOUmvkNQBfBO4oFX1l6QDJL1L0hq1if0ulKWJf24ea/tp4EHgk5JWkjQU2B+4o871dknbSlqx9t/6HvAscE+L5/4hZefKkfVzJnAFZQllRERERERERAxySXS111Ul9TNK4mUipdfVBQs9YenhtT2lT9afJU2n7A74HPBPyjK+q4B/UJYHzqb1UsV295gOfBq4kJIUGgP8qmHI5pTKsk7gZuAM2+Nqw/jdKbsaPkzpl/XBes1PKO/hD5TE1GxKH65WpgGH1TmmAt8GPtnQ76vZnpRG/k9R3sFc4HP13FBKku054P4a2zu7GvNLOkzSVfW5Z9YdHifV3Rs7gdm2n2r7wiIiIiIiIiJiUFDpQb58kzQbeJ7SUP7IWjn0HGXp4NSBjS76i6TNKTtargIcYvusduNHjRrl8ePHL4nQYhDq6tG1rPR5W9bijWiWv+EYKPnbi8Fm9Ojy77hxAxlFRER7km61ParVuTSjB2yv1nTog8D9SXINLrbvo1SIRSwREzo7l5mm9BM6OxnZ0THQYURERMRSYMKEFxJeETE4jRkDBx000FEsHkl0NZH0R0oy5MCBjiUiYkkZ2dHBmGHDBjqMiIiIiIhYzCZMKP8m0bWcsL39QMcQEYPDyI6OLGWJiIiIZc7IkVm6GDGYDfaKzaWqGb0kS5oh6fg+XDNR0k69GLexpE5JKy5alC3nPkBSd43WB6Vl8ZklrVr/BuZIOm6g44mIiIiIiIiI/rU0VnRtY/ufjQckrQ5MBv5ge9eFmdT2w8Ay0YBG0lmUnRKfr4ceAi4HTrD93EDF1ReSPgZ8CdgAmAmMB/auO0I2j10H+F/gbfXQ1ZRdGqfV8ysCxwIfBdag7Mz41lY91CR9G/gQsBZlx8kf2j4ewPbzQEd9vxERMcgsS33xlnVjhg3joOHDBzqMiIiIiBdZqiq62ng/Jemzs6SXD3QwfSFpYZOJ37a9BrAe8BHgjcBNNenX1xgkaYn9riXtCHwT+FB9hlcDF7a55DhgbWBT4JXAMOCYhvPHAtsDbwLWBPYFZncz14+BV9les14zRtKeC/0wERERsYAJnZ2cN3nyQIcRERER0dLSWNHVyv7AmcAuwD7Ad1oNqsmcLwMfpzSU/y1wsO1nJI0AHgRWtj1X0kfq2A2Bp4ATbf+gzjMaGAucBHwFmAccZvun9fxLgZ8Co4G/UyqQGuMwcCjwWco7foWkU4A9KZVG9wGftX1DTw9uezZwi6R3A/+gJL1Ok3QMsJntD9d7Nj/fOOCmGuPrgP+QtMPieuYmrwdutn17fYZngLPbjH8FcFlDBdelwLvrz2tT3uM2th+q4+9q877ubTo0H9iszb0jImKQSF+8JSNVcxEREbE0W+oTXZI2piRXDgWeoSS9Wia6gE8DewA7UhI5pwKnU5ayNXsS2A14AHgLcJWkW2zfVs+vT0lKbQC8HbhY0mW2n61zzgZeTknSXE1JMjXaA9gOmFW/3wJ8HXgO+AxwkaQRNZHVI9vTJV0L7ACc1ptrKJVPuwD3AgK2XMzP3OXPwDckHQtcA4yvywa7czpwiKTz6/f3Ab+qP/8HMBd4v6TPAdOAU2yf3t1kkr4KHAGsXmM8r829u3XvzJn5P+ZjoU3o7GRkxzKxWjoiIiIiImLQWBaWLu4H3Gn7b8D5wFaSuvt/134CONz2ozWxcgwlQfKihJ7tK2zf7+J6SkJmh4Yhc4Cv255j+0qgE9iy9ot6H3CU7Rm276J1tdK3bD9je1a931jbU2zPtf1dYFVK4qkvHgfW6cP4s2zfXe85Zwk8M/VZb6BUr70OuAKYIul7bTYCuA1YBZhSP/OAM+q5DSnJty0oCbb3A8dIenub+59A6eX1OuBnlORixBI1sqODMcOGDXQYERERERERy5WlvqKLkuj6EYDtxyVdT6nqalVqswlwqaT5DcfmUXo+LUDSLsDRlATKCsAQ4K8NQ6bYntvwfSalmf16lPf2SMO5h3ixxvNI+gJwIDAcMKXX1LotrmtnA0pVW281x7C4n/nfbF9FqRhbAXgrcBGlsuwHLYZfBNwBvIdSefYdyjLKvXihIu7rNWl4p6SfA7sC17a5v4HbJb2D0uPr8+3ibWXLIUOyBCYiIiIiIiJiGbJUV3RJ2h7YHPiapEmSJlGWA36omybvjwC72B7a8FnN9mNN864K/IKSUBlmeyhwJSXJ0pOnKEvpNmo4tnGLcW643w6Uvld7AWvX+z3Xy/t1zdEB7AR09fWaQUlUdVm/hxiWxDO/OAB7vu3fAr8Dtu5m2DbAD2q1WCelH1vX7pp3Nj9LH61EaXAfEREREREREYPcUp3oolRuXQu8BhhZP1tTEjy7tBh/JnC8pE0AJK0n6T0txq1CWTr4FDC3Vjrt3JuAbM8DLqEsnxsi6TU1znbWoCSKngJWknQUpaKrR5JWlfSfwGXAs5SG8AATgLdI2ljSWsDXephqiT2zpPdI2lvS2nXHxzdQ+qb9qZtLbgEOlPQSSS8BDqJUeGH7fkpy7/D6Ll4NfBD4dYv7riDpE033/X+UTQkiIiIiIiIiYpBbahNdklajVEB93/akhs+DlL5LrRItp1CamF8jaTolsbJd8yDb0ymN6y+kJI/G8ELz8944lLKkbxJwFi8kn7pzNXAVZdfEhyhN3R9pewV8uT7DM8A5wK3A9rZn1Ge4FriAUvF0Ky0SP42W8DM/S9n58j5K8/ixwP/YPreb8R8FRgCPAo8BmwIHNJz/EGVZ6hRKz68ja5UYkvaRdHfD2PcC9wPT632/Xz8RERERERERMciptDJaOkiaDTwPnGr7yH6ee1NK4mUlL00PHUtMXb45GVgZ+LbtY9uNHzVqlMePH79EYouIiEXTtUtueisufnnXC8r7iMFm9Ojy77hxAxlFRCxOg+G/c0m32h7V6txS1Yze9mqLcfqtgYlJci2/6k6cQwc6joiIiIiIiIhYPJbapYv9SdLngR8CXx3oWCIiIiIiIiIiYvFYqiq6Fhfb3wO+N9BxRERERERERETE4rNcVHRFRERERERERMTgt0wmuiRZ0gxJxw90LP1B0gGSblyI60bUd9GvlXmSzpJ0XJvznbW5/zJF0hY19nmSDhzoeCIiIiIiIiKify2Tia5qG9uHNx6QtHpNZFw5EAFJ2qfev1PSLEnzG753DkRMi4PtDtsPtDonaVxzEknSaEmPdjdfTdhdKelZSZMkndaVvJO0iqSLJU2sSb3R7WKT9GpJv5P0nKR/SnpvQ9z/sN0B3NCX542IiIiIiIiIZcNg69H1fuB5YGdJL7f9xJK8ue1zgXOhJHeAsbY3XJIxLKPOAJ4EXk7ZFfFa4BDg1Hr+RuBk4KJ2k9Tk2C+BM4G3AzsCl0va1vY/+hrUvTNn/nvL8Fh6jRk2jIOGDx/oMCIiIiIiImIpsCxXdLWyPyXJcSewT+OJWhH0RUl31mqfCyStVs+NlvSopC9IelLSE5I+0nDtuyTdLmmapEckHdPXwCR9VdL9kqZL+ltjpVGLsf8j6UZJa/Xy3vtIeljS05IOb5jnDZJuljS1PtNpklap5yTppPq8z9X3snXDnGtLuqLG+2dJr2yY15I26+s7aOMVwIW2Z9ueBPwG2ArA9r9sn2z7RmBeD/O8ChgOnGR7nu3fATcB+/ZjrLEUmdDZyXmTJw90GBEREREREbGUGDQVXZI2BkYDhwLPUJJe32kathfwTmA2JQFyACUxBrA+sBawAaUa6GJJl9l+FpgB7AfcDWwNXCtpgu3L+hDi/cAOwCTgA8BYSZs1Vp1JWgH4AbAxsLPtmZJ6c+83A1sCWwB/kXSJ7XsoiaHPAeOBDYGrKJVSJwM7A2+p1zxHSRJNbZjzQ/Vd3QacDRwP7N2H5+2LU4C9JY0D1gZ2AY5ciHnUzbGtWxzv0ZZDhjBu220X5tJYQlJxFxEREREREY0GU0XXfsCdtv8GnA9sJak5S3Gq7cdtPwNcDoxsODcH+LrtObavBDopySNsj7P9V9vzbd9Z59+xL8HZvqjee77tC4D7gDc0DFm5zrsOsLvtmX2497G2Z9m+A7gD2KZee6vtP9mea3siJYnWde0cYA1Kgku272la6nmJ7b/YnktZjtn4rnpyaq0imyppKvDrHsZfT6ngmgY8SknM9SWJ2OXvlCWQX5K0sqSdKc87ZCHmioiIiIiIiIhlzGBLdJ0LYPtxSvJk/6Yxkxp+ngl0NHyfUpM6LzovaTtJv5f0lKTngIOBdfsSnKT9JE1oSP5s3TTHZsB7KEmrfzVc15t7t3yuusvgr2uD92nAN7uurcv6TgNOByZL+qGkNXuas5c+bXto1wfYrbuBtYrtauASYPUa39rAiX24HwC25wB7AO+ixP8F4EJK8iwiIiIiIiIiBrlBkeiStD2wOfC1mtSZBGwHfKhr975FdB7wK2Aj22tRlju2WibXXXybAD+iLKt8aU3+3NU0xz3AR4CrJG3ZT/f+X0qV0+a21wQOa7zW9qm2/5NSTbUF8KXePlM/WgfYCDjN9vO2pwA/BXZdmMls32l7R9svtf0OYFPgL/0XbkREREREREQsrQZFootSuXUt8BrKEruRlIqpIZR+T4tqDeAZ27MlvQEY08frVwcMPAVQG92/qG+U7fMpyajrGpq/L8q916AsB+yU9Crgk10nJL2+VoutTOlBNpuem733O9tPAw8Cn5S0kqShlN/nHQ2xrtq1cQCwiqTVJLVM9kl6bT0/RNIXKTs5nrV4nyIiIiIiIiIilgbLfDP6mgDZC9iv7tjXeO5nlKTJ5Yt4m0OA70o6jbIk8kJgaG8vtv03Sd8FbgbmA+dQmuG3Gnt23Rnxd5J2XMR7fxH4IfBl4HbgAuC/67k1gZMoFU+zKcsHm5v3Lyl7Uhrkf4WSbPs9pYl+l3uBTerPV9d/XwFMlHQYsIPtroTmvsCBlJ5nNwBvt/384g0/BtKEzs40pe9nY4YN46Dhwwc6jIiIiIiIiD6T7YGOoc8kzQaepzSXX5jd+WI5JGlz4BZgFeAQ22e1Gz9q1CiPHz9+SYQWC2n07bczobOTkR19aSEX7XS9z+w4GsuaroR3/nYXv7zrBeV9xGAzenT5d9y4gYwiIhanwfDfuaRbbY9qdW6ZrOiyvVrPoyIWZPs++lCJF8uGJGX6V6rjIiIiIiJiWTZYenRFRERERERERMRyLomuiIiIiIiIiIgYFJb5RJckS5oh6fiBjiWWbpJ2ktQpab6knQY6noiIiIiIiIjoX8t8oqvaxvbhAJJG1OTXSvW7JH1f0t8lbbAkg5L0sXrf6ZImS7pC0hpLMoYlTdLE5iSSpAMk3djmmpGSbpD0nKRHJR3VcG50TUx1Nnz27+H+sxrGXtN1zvZ1tjuAhxfxMSMiIiIiIiJiKbRMNqPvLUkCfgC8CdjR9uQleO8dgW8C77R9u6R1gN2X1P37i6SVbM9dzLc5D7gUGA2MAG6UNMH2r+r5x21v2If5drd93aIGde/MmWnMvZTLjosRERERERHRaLBUdLWyInAWMAoY3ZXkkvQuSbdLmibpEUnHdF3QUA22v6SHJT0t6fCG82+QdLOkqZKekHSapFW6uf/rgZtt3w5g+xnbZ9ueXucaJ+nAhrkXqHqqcRwi6b5aEfYNSa+s958m6cKue9eqp0clfVnSkzW2PSTtKukfkp6RdFjD3CtI+qqk+yVNqXOt0/QOPibpYeB3klaTNLaOnSrpFknDFu3Xs4ARwLm259m+H7gR2Kof549BamRHB2OG9eefYkRERERERCzLBnNF17nARsB/257acHwGsB9wN7A1cG2tHrqsYcybgS2BLYC/SLrE9j3APOBzwHhgQ+Aq4BDg5Bb3/zPwDUnHAtcA420/38dneCfwn/U5bgO2B/YBpgA3Ax8Czq5j1wdWAzYADgB+BFxbr98YuFXSz20/AHwa2APYEXgKOBU4vc7XZUfg1cB8YH9grRrH88BIYFYfn6Wdk4H9JB0JbEqpwPt2w/mXSZoMzAQuA46wPaPNfOdKWgG4HfiS7TsWJqgthwxh3LbbLsylERERERERETEABnNF187AhU1JLmyPs/1X2/Nt3wmcT0nqNDrW9qyaILkD2KZee6vtP9mea3siZVlk87Vd97kB2BN4HXAFMEXS9ySt2IdnONH2NNt3A3cB19h+wPZzlCRbYxZmDnC87TnAz4F1gVNsT6/X3w28to79BHC47Udr8u0Y4P1dfc2qY2zPsD2rzv1SYLNadXWr7Wlt4r6sVn5NlTQVOKOH5/w18H5K8uzvwI9t31LP/Z2SWHs58N+UxN332sy1D6VCbBPg98DVkob2cP+IiIiIiIiIGAQGc0XXbsCvJT1r+yddByVtB5xAqeZaBVgVuKjp2kkNP88EOuq1W1CSLKOAIZT3d2t3Adi+CriqVhe9td7nXkqCrDcae4rNavF9/YbvU2zPazjX6vquZkabAJdKmt9wfh7QuAbskYaff0ap5vp5TRqNpSTK5nQT9x6NPbIkHQAc2GpgXTL5G+BQSq+u9YGLJU22fYbtSbzw+3hQ0pcpicNPtJrP9k0NX79VG9fvAFzeTawR0WRCZ+ci96cbM2wYBw0f3k8RRURERERE9M5gruj6I6X5+ymSxjQcPw/4FbCR7bWAMwH1cs7/pVQYbW57TeCw3lxbq8d+C/yOkmCDsoRySMOw9V904eLzCLCL7aENn9VsP9Ywxv/+wZ5j+1jbr6Esn9yNsvyzP2wKzLN9Tq2Ue5RSkbZrN+NN739fCzM+IhbRhM5Ozpu8xPb+iIiIiIiI+LfBXNGF7esl7UmpXvqX7YuBNYBnbM+W9AZgDKWHVm+sAUwDOiW9CvgkpcfVi0h6D/AS4GpgKqU5/Y7AZ+uQCcCekv4PGA58jAUrsBanM4HjJe1v+yFJ6wHb2/5lq8GS3go8DfyN8vxzKBVg/eEf5RYaQ0lwvQz4ICUpiKTRwAOU5NyGlGq87uLcmFJ5dgslifspyhLOm1qNj4jWRnZ0LFJ/uuxWGhERERERA2UwV3QBYPtaSuLkLEm7U5rHf13SdOAo4MI+TPdFSmJsOqXZ+wVtxj4LfBy4j5IcGgv8j+1z6/mTgH9RkltnU5rnLymnUKrarqnv4U/Adm3Grw9cTHmOe4DrKc+zyGqvrz0pTf6fpSQA7wKOr0NeR2m8P4NSpXcXpZk+AJLOlHRm/boGperuWeAxSjP/XWxP6Y9YIyIiIiIiImLpNhgqup6n7Ch4qu0ja5P4BZaq2b6CF/pTQUnavEg3145u+PkPwKuaLjuqm7n+ALytu6BtP01pmN/omIbzzXG8uen7EQ0/j6NUO3V9n9viOd7c8PN8Sq+xFzV17+YdnE9p2t8j2yNaHDsLOKvNNb+jVLy1OtcyzobzBzf83Nhw/0UkvQ34BaUvW39VpEVERERERETEUmKZT3TZXm2gY4hlQ+2Tlh0YIyIiIiIiIgapQb90MSIiIiIiIiIilg/LVaJLkiXNkHR8z6P/fc0Oku5t+D5R0k6LJ8JYnCRtIalT0jxJBw50PBERERERERHRv5arRFe1je3DASSNqMmvKxoHSBor6RgA2zfY3nJhbiTpPZImSJom6WlJv5U0YhHjX6pJGtecRJI0WtKjba4ZIelKSc9KmiTpNEkrNZzfS9I9kqZL+pukPdrM1dn0mSfp+wC2/2G7A7ihHx41IiIiIiIiIpYyy2Oiq5U3Svqv/pxQ0mbAOcAXgLWAVwBnAPP78z6LW2PCaTE6A3gSeDkwEtiRsjsmkjag7PD4eWBN4EvAeZJe1moi2x1dH2AYMAu4aLE/QUREREREREQMuGW+GX0/+TZwHPDW5hOSRgNjbW/Y4tyrgKuAr9n+edPpkcCDtQE6wHTKjn9d154FPNq1e2LzfSRNBE4H9gVeCfwcOIyye+GbgT8DH7D9bK0SexD4KPB1yg6TXwNuBX4MbFznPrTh/h+lJI3WB/4CHGT7oXrOwKHAZ4GVJG1K2flwH8qOhQ8BY2zf1eplLoRXAKfZng1MkvQbYKt6bkNgqu2r6vcrJM2o7+TJHuZ9fx2zUBVc986cyejbb1+YSyOWWRM6OxnZ0dHzwIiIiIiIiKVQKrqK04Et+tJ7S9LrgGuAT7VIcgHcBrxK0kmS3ippYf6X4/uAtwNbALtTkmqHAetSfnefbhq/HbA58EHgZOBwYCdK0mgvSTvW2Peo8+wJrEdJBJ3fNNcedb7XADsDb6lxDK3zT1mI5+nOKcDekobUCq5dgN/Uc+OBeyS9W9KKNfbngTt7Me/+wDm23Y+xRgxqIzs6GDNs2ECHERERERERsVBS0VXMBo6nVHVd14vxOwAfA/a1/ftWA2w/UKu0Pg9cCKwh6efAobY7exnX921PBpB0A/Ck7dvr90uBtzWN/0atirqmVj2db/vJhuu3Ba4HPgF8y/Y99dw3gcMkbdJV1VXPP1PPzwHWAF4F/KXrujZOlfSdhu8rAVPbjL8e+DgwDVgROBu4DMD2PEnnAOcBqwH/olSyzWgXgKSNKUsgP9ZDrN3acsgQxm277cJeHhERERERERFLWCq6XvAjYJik3Xsx9mDgj90lubrY/pPtvWyvR0mOvYVSZdVbkxt+ntXie3OVWG/HbwKcImmqpKnAM4CADRrGP9LwHL8DTqNUvk2W9ENJa7aJ+9O2h3Z9gN26GyhpBeBq4BJgdUq12trAifX8TpSlpaOBVSjJq/+TNLLN/QH2A260/WAP4yIiIiIiIiJikEiiq7I9BzgW+PVKMwMAACAASURBVAYl6dPOwcDGkk7qw/y3UJI5W9dDM4AhDUPW7320i+wR4BONySjbL7H9x4YxCyz3s32q7f+kLIPcgtLfqz+sA2xE6dH1vO0pwE+BXev5kcAfbI+3Pb++xz9TlmS2sx+lMiwiIiIiIiIilhNZurignwFfAd4J3Ndm3PQ65reSTrD91eYBkt4MvBr4pe0na+P6d/NC8mUC8AVJx1EqlT7bf4/RozOBb0iaYPtuSWsBO9tuuTuhpNdTkqK3URJ0s4F5/RGI7aclPQh8si537KD01rqjDrkF+KqkkbYnSNqWUh13RndzStqeUp2W3RYjBsiEzs5Bu5nDmGHDOGj48IEOIyIiIiIiWkhFVwPb84CjKVVGPY2dSmkUv4ukb7QYMpWS2PqrpE5Kc/VLKcvwoCTV7gAmUpraX7Co8feW7UspSwN/LmkacBelAXx31qQs7XyWsuPiFOA7bcb31Z6UxOFTwD+BucDnaqzXA8cAF0vq2rnym7avAZB0mKSrmubbH7jE9vR+jDEiggmdnZw3eXLPAyMiIiIiYkBoedqQTtJsyo59p9o+cqDjiSVL0uaUCrFVgENsn9Vu/KhRozx+/PglEVrEoNJVyTUYN3MYzM+2rMvvZsnJu15Q3kcMNqNHl3/HjRvIKCJicRoM/51LutX2qFbnlquli7ZXG+gYYuDYvg8YOtBxRERERERERMTikaWLERERERERERExKCTRFRERERERERERg0ISXT2QZEkzJB3fy/EbS+qUtOLijm1R1Ubu/zfQcSxJkn4nabakGwc6loiIiIiIiIjoX0l09c42tg+XtJqkqZL+u3mApJMkXWz7YdsddQfHbkkaLenR/gxS0gGS5tVE2zRJEyTt1t1429+0feBiiOFFSSRJEyXt1M01Z9aYuz7P1x0Wu86/uiaonpP0T0nvbXP/tnPZ/m/g4EV8zIiIiIiIiIhYCiXR1Qe2ZwMXAPs1Hq/VWx8Czl5SsUjqbiOBm213UJqu/xi4UNI6fbh+ibN9cE0OdtTYzwcugn/H+Uvg18A6wEHAWElb9HWuiIiIiIiIiBjclppkxzLkbOBqSYfYnlmPvYOSNLxK0gjgQWBl23Nrkum7dcxLgOuBfYCrgFUlddY5tgCmACcCe9VjFwJfsf28pNHAWOD7wOeAa4F9uwvS9nxJPwFOBTaV9Glga2A28G7g85I2BDaz/WEASW8Gvg28BpgOHGn7LEmrAsfXuFYFLgU+Z3vWQry/tiStDrwP6KpEexUwHDjJtoHfSbqJ8uxH9nGuPrl35sx/bxke0Vdjhg3joOHDBzqMiIiIiIiI5UoquvrI9h+BJ4A9Gw7vC5xne26LS34GDAG2Al5GSdjMAHYBHm+oPnocOBx4IzAS2AZ4A3BEw1zrU6qaNqFUNnWrVkIdCHQC99XD7wEuplR7nds0fmNK8u37wHo1hgn19ImURNxIYDNgA+CodvdfBO8DngL+0BVaizGiJO36OlfEEjGhs5PzJk8e6DAiIiIiIiKWO6noWjjnUJYvjpW0JiWB9F/NgyS9nJLQeqntZ+vh69vMuw/wKdtP1uuPBX7AC5VL84GjbT/fZo43SpoKzAX+CbzX9nOSoCxrvKyOm1WPNd77Otvn1+9TgCkqgz4OvNb2MzWubwLnAV/rIYZGa7aJudH+wDm1egvg78CTwJcknQS8FdgR+P1CzNUnWw4Zwrhtt12YS2M5l0rAiIiIiIiIgZFE18I5Bzha0gaUJYn/tN3qf9luBDzTkOTqyXDgoYbvD9VjXZ6qfcLa+ZPtN3dz7pE2120E3N/i+HqUirRbGxJjAtrtKvmiGCRNbDO+a8xGlCTWx7uO2Z4jaQ9KpdlXgPGUJZ3tkn0t54qIiIiIiIiIwS2JroVg+2FJN1CqoHahJL5aeQRYR9JQ280VTq2qjB6nLEu8u37fuB5rd01ftLv+EcpSyWZPA7OArWw/toj378l+wB9tP9B40PadlKQVAJL+SM+N/1vOFRERERERERGDV3p0LbyzgUMpSxbPbTXA9hOUvldnSFpb0sqS3lJPTwZeKmmthkvOB46QtJ6kdSl9sMYutidY0LnATpL2krSSpJdKGml7PvAj4CRJLwOQtIGkdyyGGPYDzmo+KOm1klaTNETSF4GXtxrXm7kiIiIiIiIiYvBKomvhXQysDfy2JrS6sy8whxd6TX0WwPbfKYmtByRNlTQcOI6yNO9O4K/AbfXYYmf7YWBX4AvAM5RG9NvU01+h9Pv6k6RpwHXAlv15f0lvAjYELmpxel/KBgBPAm8D3t7Vp0zSxpI6azP93swVEREREREREYNUli727HlKf6pTbXc1hafunLhG82DbE2nYKbA2cN+/1cS2P9ri8Kfrp3nsOEryplu2z6KbKibbx/R0zPYNwHYtxs0GDquftrqLwfaIHq67GVi9m3NfAr7UzbmHgY7eziXpWsrOln9pF0/EoprQ2bncNqWf0NnJyI6OngdGRERERET0syS6emB7tYGOIfqP7bcPdAwRg93Ijg7GDBs20GFERERERMRyKImuiIjFYGRHB+O23Xagw4iIiIiIiFiuDIoeXZIsaYak4/twzQ6S7l2ccfUHSWdJ6rZP17LyHEsLScfWvxVLSqI3IiIiIiIiYhAZFImuahvbhwNIGlETGVc0DpA0VtIxUPpR2e7XhuoN95koaVZtkj6pJqsWS8OaxfkcC6Ph3a/UdLzbhJ2kfeq76vrMrHP8Zz3/JUl3SZou6UFJLft1Ncw3RNIZkp6W9JykP3Sds300sFU/PGpERERERERELGUGU6KrlTdK+q8BuvfutjuAkcC2wNf6+waDpSLJ9rm2O7o+wCHAA5RdJ6E099+PssvlO4FDJe3dZsofAusAr67/fm6xBR8RERERERERS41BkShp49vAccBbm09IGg2Mtb1h/T4ROI2SUNkE+A2wv+3ZktYGfkbZkXAl4CbgYNuP9hSA7UmSrqYkvLru/W7gW8AGwATgk7bvqee2BX4MbA5cCbg5ZuD7lOTNtZJ+3PQcr6vXb1afYT5wn+0jJB0AHGj7zQ1zGtjc9j8lrQocD+wFrApcCnzO9ixJlze9xyHAR+sui/1tf+Ac2waw/e2Gc/dK+iXwX8DPmy+UtCXwbmBD29Pq4VsXJoh7Z85cbnfNi0WTXQcHt+V5R82lWf67i4iIiAgY/BVdpwNbSNqpl+P3olQMvQJ4LXBAPb4C8FNKAmxjYBYlKdYjSRsCuwD/rN+3AM4HPgusR0lmXS5pFUmrAJdRkmrrABcB72uacv16bhPgoKZ7rUJJTp1Vx5wPvLc3cVYnAltQknKbURJxRwHY3r2h4ur9wCTgt32Yu1ckbQK8BTinm/MCdgDu7maK7YCHgGPr0sW/Smp+hxGLVXYdjFjy8t9dRERERMDgr+iaTalQOg64rhfjT7X9OECtYBoJYHsK8IuuQbXp/e97mOuyWi3VAfwOOLoe/yBwhe1r61zfAT4DbE+pvloZOLlWM10s6fNN884Hjrb9fL2+8dwbKb/TU+v1l0j6Sy+euyuB9HHgtbafqce+CZxHw7LLmqg7B3if7UfaTPl0U2xDKBV2PdkPuMH2g92cP4YXEo+tbAhsTfl9DQfeBFwh6W9dVXO9teWQIdk1LyJeJDtqRkREREQsvQZ7RRfAj4BhknbvxdhJDT/PpCSpupqb/0DSQ5KmAX8Ahkpasc1ce9heAxgNvApYtx4fTqk4AsD2fOARSvXUcOCxriV71UMs6Cnbs7u5Z6vr2yWjGq1HSUbdKmmqpKmUpY/rdQ2QtBbwS+BI2zf0MN+6tod2fSgJs97YDzi71QlJh9bz7+pK9LUwC5gDHGf7X7avpyQld+7l/SMiIiIiIiJiGTXoE1225wDHAt+gNDVfGF8AtgS2s70mZWkdvZmvJlrOAr5TDz1OWXZYJihlTxsBjwFP8P/Zu/d4zcd6/+Ovt+MYC0MYjWMoFTujhtTWNnvTgZJql5wp6WDrqDYloZ1Dfh2EipSEiNCZHNKIQgZDkUkYhkEGY2bNODTj/fvjum7uud3rNLNm7llr3s/H437Mur/X4fv5fpf1R58+13XBupq/FGqD1il7uV278es3/Tybksxq3HudprbplCTR5k0JqtXqUkUkLUNJVv3e9mm9xLDA6sEBY4AL27R9EDgM2KGPvdFuWxSxRURERERERMSSb9gnuqqzKZurv20Bx69CSQLNkLQGLyxD7K8TgTdLGgtcALxd0g6Slqck0Z4B/gRcB8wFPiFpOUnvAbYZwH2uA+ZRTiVcTtKuLeNvBTaXNFbSCMoyQOD5yrLTgW9KWhtA0rqS3lq7HAOsTFlmuajsB1xke1bzRUl7AccCb7Z9Tx9z/AG4H/h8fQf/Tqmqu2wRxBsRERERERERS5ClItFlex4lObXGAk5xIrASperpesqSvoHc/1HKvlZH2J4M7E05OXE6sAuwS11m9yzwHsom+E9Q9vO6eAD3aYw/AJhR7/NrSiIN238HvkzZr+wu4NqWKQ6lbJp/fV2ieSWlkg1gD8oeYE9I6q6fvQbwGnpVE2+70X7Z4leAlwA3Nt371KaxtzdiqRV8uwI7A09Sknf72r5zsGKNiIiIiIiIiCWT5t/OaWiS9DQlmXOS7SM6Hc+SRNINwKm2e9q8faki6UjgM5QKv5VrErStcePGeeLEiYsttohY8o2/5RaAbEYfS7X8Hcwv7yOGm/Hjy78TJnQyiohYlIbD37mkm2yPa9c2LE5dtD2i0zEsKSRtD0ymVIvtBbyGAVagDWe2j6bs2RYRERERERERw8ywSHTFfDaj7APWBdwNvNf2Q50NKSIiIiIiIiJi0Uuia5ix/T3ge52OIyIiIiIiIiJicVsqNqMHkGRJsyUd0+lYonMk3S3pWUnndDqWiIiIiIiIiBhcS02iq9rS9uGNLzX5teniDEDSNpIukTRD0uOS/izpA4szhkVJ0lHtkki9vWtJoyT9SNI/6+eolvaNJP1e0hxJd0rasZf7S9JXJT1WPydIUqPd9ibAsQv+hBERERERERGxpFraEl0dJekNwFXA1cCmwEuAjwE7LcBckrRMy7WhuhT1m8BIYCNgG2CfluTfecAtlPd1OHChpLV6mOvDwLuALSkb8b8D+MiiCTsiIiIiIiIiliRDNTEy6CStCHwV2K1eugA41PYzktYEzgS2A54Dbge2t/2cpDHAycB/AN3AN22f1MNt/h/wI9tfbbp2U+OeklYHzgZeT/nd/BH4qO0HavuEem088Frg3yTdBRwMfKqOeZmkbwHvAVYD7gI+ZfuaOsc2wHeAVwBPAT+2/Znath1wAvBqYBZwhO0zJa1Wn3EnYA5wOnCs7ef6+377sAuwk+05wBRJPwA+CPxQ0ivqs77F9lPARZI+Bfw3cGqbufYDvt70zr4OHNhD315NnjPn+SPDY/HYc/RoPjxmTKfDiIiIiIiIiCEqFV0vOBzYFhhLqQbaBvhibTsEeABYCxgNfAFwraj6FXArsC6wA/ApSW9tnVzSSOANwIW9xLAM8ENgQ2ADSiLqlJY++1CqllYB7qvX3kVJjr26fr+xPscawLnATyWNqG3fAr5le1VgE0pCD0kbAJdSElpr1fGT6piTKUmzjYHtgX2BwV5uqZaft6g/bw7cY3tWU/ut9Xo7m9f2/vSNJcik7m7OfeSRTocRERERERERQ1gqul6wF/Bx2/8EkHQ0cBpwBPAv4KXAhrb/ATRXR61l+8t1jnsknQ7sDlzWMv/qlETWQz0FYPsx4KLG97px/u9bup1p+/amPgDH2X68aZ7mPbK+LumLwGaUpM+/gE0lrWl7OnB90/Nfafu8+v0x4DFJywLvB7aqyaZZtUpqH+AHPTzKbpLe0dNztvFb4DBJ+1ESiR+kLGUE6AKebOn/JCWx2E5r/yeBLkmy7QHExGYjRzJhq60GMiQWQqrnIiIiIiIiYmEl0fWCMbxQIUX9ubGG6v8BRwGX18TS92wfT6m8GiNpRtO4ZamJsBZPUJY9vhS4s10Aterrm8DbKIkxgFUkLWt7Xv0+tc3Q+a5JOgT4UI3fwKrAmrX5AODLwJ2S7gWOtv1rYH3g7jZzrwmswIvfTU+JJoALbO/dElNvSaZPUKrG7qIk2M4D9qht3TX+ZqtSlla209p/VaB7oEmuiIiI6Nmk7u78HxTVpO5uxnZ1dTqMiIiIqLJ08QXTKImrhg3qNWzPsn2I7Y0p+0l9RtIOlATTvbZHNX1Wsb1z6+R1/6nrKHtL9eQQSuXV6+vSwv+o15uX9bVL2Dx/TdKbgEMp+36tbnsUpapJNY67bO8BrE3Zk+xCSSvXZ9mkzdzTKVVgre/mwV6eY0BsP257L9vr2N6c8t/ln2vz7cDGklZpGrJlvd7O7bW9P30jIiIiFsrYri72HD2602FERERElYquF5wHfFHSjZTE0ZeAcwDqMrw7KRVPM4F59fNnYKakQ4GTgGeBVwEr2b6xzT3+l1IVdh9whu3HJG0JfN727pR9t54CZkhaAzhyAZ5jFWAu8CiwnKTDaKpwkrQ3cJntR5sq0eYBPwa+IGk34GLKnlzr254k6QLgGEn7Uvb9+gzwtQWIrS1JmwAz6uctlD3Itgew/XdJk4Aj6xLMnSinKfaUMDyLkoi8hPJ7PIRSLRYRERGDZGxXV5b3R0RExBIpFV0vVEN9BZgI3Ab8Bbi5XgN4OXAlZVncdcB3bE+oywl3oWzcfi+l+un7lCTRi29k/wn4r/q5R9LjwPeAS2qXE4GV6jzXU/auGqjLKJvK/52yxPBp5l/a+DbgdkndlI3pd7f9tO37gZ0piaHHKRvRNyqjPg7MBu4BrqVscH/GAsTWk9dR3vks4Dhgr+Z9yCh7no2jLP88Hniv7UehVLDVZ2k4jXJAwF+AvwK/qdciIiIiIiIiYpjT0rJ1kaSngWeAk2wfIWlVypK+1W3P6H10DBeSJlP2F7vA9gd76ztu3DhPnDhx8QQWjL/lluxzEku8xn+jqWSJpVljb678HUQMT+PHl38nTOhkFBGxKA2Hv3NJN9ke165tqVm6aHtEy6X3A3cnybV0sb1Zp2OIiKEre/FERERERCzZlppEVzNJfwJGUU4mjIglRCplIiIiIiIiYmEM+T26JFnSbEnH9HeM7TfafrXtCYswtCFL0nhJD3Q6jsEmaUdJ3ZKek7Rjp+OJiIiIiIiIiME15BNd1Za2D298kbSCpC9JmlyTYA9KulTSWzoZZI3tTElfafq+uaSHJB3SybgGi6QprUkkSftLuraXMWMlXSPpSUkPSPpSU9v4mpjqbvrs10cMn5R0b/3d/03SKwBsX2m7C7h/IR8zIiIiIiIiIpZAw3Xp4oWUDcf3BW6p1/4LeDtweWtnScvZnrv4wnv+vmNrPF+2fcrivv8S5FzgZ8B4YCPgWkmTbP+ytk+zvV5/JpL0IeAAyu/6b8DGlNMaIyIiIiIiImKYGy4VXc+r1URvBna1fYPtZ+vnt7Y/2dRviqRDJd0GzJa0nKTDJN0taZakOyS9u2XuA2uFUKP9tfX6GEkXSXq0VhJ9oh9xbgNcCXyhkeSStExTDI9JukDSGrVto7pMcz9J90uaLqm5iu2o2v+sGt/tksY1tfcYo6SVaqXZE5LuALZuavucpItaYj9Z0on9+430y0bAj23Ps303cC2w+UAnkbQMcCTwadt3uLjb9uODGGtERERERERELKGGY0XXjsANtvuzx9QelMqf6bbnSrobeBPwMPA+4BxJm9p+SNL7gKOAdwETgU2Af9Xkyq+AX9T51gOulDTZ9mU93Hcb4CDgk7bPbrr+iTr/9sCjwEnAt+u8DdsBmwGvAP4s6WLbf6tt7wTeA3wA+ApwCrBtP2I8sj7PJsDKwKVN9zsHOErSKNszJC1HObFypz7e7UCcCOwr6QhKBdYbgBOa2teW9AgwB/g58EXbs9vMs179bCHpTGAucBZwtO3nBhrU5Dlznj9CPRa9Sd3djO3q6nQYERERERERMYQNu4ouYE1KogoASWtImlH3f3q6pe9JtqfafgrA9k9tT7P9nO3zgbsoSSkoJzSeYPvGWin0D9v3Uaqf1rL95Vo5dg9wOrB7LzFuCzzJ/AklgI8Ah9t+wPYzlMTae2tyqeFo20/ZvhW4Fdiyqe1a25fYngec3dTWV4y7AcfYftz2VEqCjfpOHgL+QEn8AbyNkhi8qZfn+3l95zMkzQC+00tfgF8D7wWeAu4EfmD7xtp2JzAWeCll+enrgG/0ME9jeeNbgH8D/pOS2Dugj/vHEmBsVxd7jh7d6TAiIiIiIiJiCBuOFV2PAS9vfKnL1kZJ2pSSuGo2tfmLpH2Bz1CW0gF0URJnAOsDd7e534bAmJrQaVgWuKaXGL9NqZ66QtJ/2W7sIbUh8DNJzdVH84Dm//X/cNPPc2qMPbWNqEmyvmIcw/zv4r6WeH8EfIySHNubkkTrzbtsX9n4Iml/SqLwRerSzN8CB1P26loHuFDSI7a/Y/vhpue6V9L/Ar+hJAVbPVX/PcH2DGCGpNOAnWvsA7LZyJFM2GqrgQ6LiIiIiIiIiA4ZjhVdvwO2ltSfzcvd+EHShpRkyMHAS2yPAv4KqHaZSklOtZoK3Gt7VNNnFds793LfecBelNP/LpO0atNcO7XMNcL2g/14lt70FeNDlERewwYt438OvEbSFsA7gB8vZDzNNgbm2T7L9ty65PQnlORUO+aF30mrycCzNP1eIyIiIiIiImLpMewSXbYvB35PWT73ekkrSFqeslywNytTEiSPAkj6ALBFU/v3gc9Kep2KTWty7M/AzLqx/UqSlpW0haStX3SH+eP8F2U54HTgEkkrA6cCx9R5kbSWpF0H+g7a6CvGC4DPS1q9Jgg/3hLr05STLM8F/mz7/kGIqeHvgCTtWTfjX4eyB9itlIbxkjao73x94HjKXmMvYnsOcD7wv5JWqc9yIGVpZEREREREREQMc8Mu0VW9h5LcOAeYAdxLqaB6W08DbN8BfB24DniEssfTH5vafwocQ0n2zKJUOa1R98PahbKP1L2UxNX3gdX6CtL2szXWpymbxX8P+CVwuaRZwPXA6/v/2D3ep68Yj6YsV7wXuJz2SxN/RHknfS1bHGhsMynv4NPAE8AkSiXdMbXLaym/k9nAn2pb84mRp0o6tWnKg4FuYFoddy5wxmDGHBERERERERFLJtlDe5VX3WD+GcrG8kd0Op7hStIGlI3h16nJqSFH0g7ARcCKwM62f99b/3HjxnnixImLJbaIiIihonEicfaxjBiexo8v/06Y0MkoImJRGg5/55Jusj2uXduQ34ze9ohOxzDcSVqGskn/T4ZqkgvA9u+AUZ2OIyIiIiIiIiIWjSGf6IpFq+4d9ghlaWOPSz8jIiIiIiIiIjotia7ole3ZQFen44iIiIiIiIiI6Mtw3Yy+LUmWNFvSMX33XnJI2qjG3mNiUtKlkvZbnHENRZKOrv8N9Po+IyIiIiIiImLoWaoSXdWWtg9vfKkJj00H+yaS9pc0T1K3pJmSbpX0jsG+T4PtnWz/aFHNP1CS1pN0kaTpkp6U9BdJ+/dj3JH1d7Jj0zVJ+qqkx+rnBEnqZY7dJP1N0ixJd0h6V6PN9pHA5gv7fBERERERERGx5FkaE12L03W2uygboH8H+ImkQd0MvSaBlsTf49nAVGBD4CXAvpS9vnokaRPgvcBDLU0fBt4FbAm8BngH8JEe5lgXOIeyef6qwOeAcyWtvaAPEhERERERERFDw5KYIOkYSWdK+krT9/GSHmj6PkXSZyXdVquUzpfU56mPtp+jJH5WBl5e51pN0lmSHpV0n6QvNhJWkpaV9LVaDXUP8PaWOCdIOkbSH4E5wMb12oeaxn+9jr9X0sHNS/XqczRXTB0l6Zym79tK+pOkGbUSbXy9/oZaodb4PC1pSg+PvTVwpu3ZtufavsX2pX28qlOAQ4FnW67vB3zd9gO2HwS+DuzfwxzrATNsX+riN8BsYJM+7h0RERERERERQ1z2KBq43SinDz4N/JGScDm1twGSlgU+APyLcnohwMnAasDGlIqnyymVTD8ADqRULW1FSdJc1GbafYCdgMlA6zK+A2vb2Dr+p/19uFoR9Zs6/2+BHYCLJL3S9nXUjeklLQ9cAVzXw1TXA9+WdDLwJ9v393Hf9wHP2r6kzarEzYFbm77fSs/LDycCf5P0zvocuwDPALf1dv92Js+Zw/hbbhnosOigPUeP5sNjxnQ6jIiIiIiIiOiQVHQN3Em2p9l+HPgVJZnUk20lzaAkxb4G7G37nzXx9X7g87Zn2Z5CqVLap47bDTjR9tR6n+PazH2m7dtrtdS/Wtp2A75VK6CeAI4fwPPtDVxi+xLbz9m+gpI82rml30mUJNrhrRNU7wOuAY4A7pU0SdLW7TpK6gKOBT7Vw1xdwJNN358Eutrt02V7HnAWcC4lwXUu8JF6emQMY5O6uzn3kV5Xx0ZERERERMQwl4qugXu46ec5QG/lI9fb3q4mcn4AvAm4AFgTWIEXqruoP69bfx5D2d+qua3V1DbXGlrH99a31YbA+yTt0nRteeD3jS+SPgKMB7atyzJfpCbYDgMOk7QmJdH3c0nr2XZL96OBs23f20NM3ZT9thpWBbrbzENdknlCje9m4HXALyXtZHtSD/O3tdnIkUzYaquBDIkOSvVdREREREREpKJrfrOBkU3f1xmMSW13AwcB+0jaCphOWca4YVO3DYAH688PAeu3tL1o2l5u+RBlr6qG9Vvae3vOqZSk06imz8q2jweQ9Cbg/4BdbTdXWfXI9nRKomsMsEabLjsAn5D0sKSHa7wXSDq0tt9O2Yi+Yct6rZ2xwB9sT6wVaTcCNwA79tA/IiIiIiIiIoaJJLrmNwnYWdIaktah56V0A2b7MeD7wJfq8roLgGMkrSJpQ8opgY0N4S+gJH7Wk7Q6pTJqIC4APilpkpBMcQAAIABJREFU3XrK46Et7ZOA3SUtL2kc5aTDhnOAXSS9tW5qP6Juyr+epPWB84F9bf+9twAkfVXSFpKWk7QK8DHgH/U9tNoB2IKSpBoLTKOcqvjt2n4W8Jn6PGOAQ4Aze7j1jcCbJI2tcWxFqaQb8B5dERERERERETG0JNFVNKqjzqZsdD6Fsjn8+YN8nxMpibTXAB+nVFbdA1xL2UvqjNrvdOCyGsvNwMUDvM/plPhvA24BLgHmAvNq+xGUUwifoCwbPLcx0PZUYFfgC8CjlAqvz1H+W9mBUv11YdPJiz1VVo0EfgbMqM+4IfDOdh1tP2b74canxvlErYQDOI2yH9pfgL9SNpk/rTFe0u2S9qpzXQ0cVWOcRdnI/1jbl/fxziIiIiIiIiJiiFObbY6GLUlPUzYoP8n2EZJWpWxsvrrtGZ2NbtGRtBNwqu0N++w8zEk6klI9tyKwcq2ua2vcuHGeOHHiYostFs74W25hUnc3Y7u6Oh3Ki+Q0yIgYThp7ImYfy4jhafz48u+ECZ2MIiIWpeHwdy7pJtvj2rUtVRVdtkfYXs32EfXS+4G7h1uSS9JKknauywbXBY6kVFct9WwfXf8bGNFbkitisOQ0yIiIiIiIiMVnqT11UdKfgFHAhzodyyIgypLE84GnKEv9vtTRiCIWg7FdXUtchUFOg4yIiIiIiFh8ltpEl+03djqGRcX2HGDrTscREREREREREbE4LVVLFyMiIiIiIiIiYvhKoquFJEuaLemYQZhrgqThuDQSGJrPJ+mAelqkJW3a6XgiIiIiIiIiYvAk0dXelrYPb3yRtKKk4yTdL+kpSXdJ+pwkLaoAmhJu3ZIek/Q7Se9fVPcbbJJGSTpD0sOSZkn6u6RDe+i7pqQ/1uecIek6Sf/e0mdjSb+uc02XdEI/Ytivvsfnk3G2f2B7yTuWLyIiIiIiIiIW2lK7R9cA/RRYB9gZuBMYB5wNrA98orVzTYANRhJsS9v/kLQmsBNwiqRX2j56oBNJWs723EGIqb++CawMvAp4EngFsEUPfbuBDwJ3AQZ2BX4laW3bcyWtAFwBfJtyUua8Ol+PJK0OfB64fUEfYPKcOdlIfAiZ1N3N2K7kMCMiIiIiIpZmqejqg6QdgLcA/237r7bn2r4e2Bv4n8byt7qM7xhJfwTmABu3zLOJpKtq1dJ0ST+WNKo/Mdiebvts4GPA5yW9pM45RdKOTfc4StI59eeNajXTAZLuB66q139aq6yelPQHSZs3jT9T0rcl/aZWTt0gaZOm9jdLurOOPYXek3lbA+fafsL2c7bvtH1hD8/3tO3Jtp+rc84DVgfWqF32B6bZ/obt2bX/bX28tuOAk4DpffSLYWJsVxd7jh7d6TAiIiIiIiKig1LR1bc3AzfYntp80fYNkh4AdgD+US/vQ6m8msyLk0CiJF/+AKwKXAQcBXxqALH8gvI72wa4tJ9jtqdUVT1Xv19KqZ56Fvgq8GNgbFP/PYC3ATcDPwKOAXavVWUX1bG/AA4GPkqpbGvneuCYWll1re27+gpU0m3AK4Hlge/b/mdt2haYIulSSgLtr8DHbf+lh3m2oVTdHQTs1td9e7LZyJFM2GqrBR0eEREREREREYtZKrr6tibwUA9tD9X2hjNt316rvv7V3NH2P2xfYfsZ248C36AkofqtzjmdFyqd+uOoWgX1VJ3jDNuzbD9DSbRtKWm1pv4X2/5zXebYnATbGbjD9oU1jhOBh3u578fr+IOBOyT9Q9JOfTzfayhJwD2Ba5ua1gN2p1RojQF+A/yiLmmcj6Rlge9QEmHPtbZHRERERERExPCVRFffpgMv7aHtpcy/NG5qD/2QtLakn0h6UNJM4BzmT5L1SdLywFrA4wMY9nxMkpaVdLyku2sMU2pTcxzNyas5QGPTozHNc9k2vTyv7adsH2v7dcBLgAuAn0rqNUlXlyWeBxwmact6+SlKVdiltp8FvlbnfFWbKQ4CbrN9XW/3iYiIiIiIiIjhJ4muvl0JvF7S+s0X6/K49al7X1XuZZ7javtrbK9K2eNroBvW7wrMBf5cv88GRja1r9NmTHNMe9Y5dgRWAzaq1/sTx0OU5y0Dyob76/fcvSkAeyZwLGVz+pf1Zwxl+WJjn7Pb6P3dNtsBeHfdh+xh4I3A1+ueYhERERERERExjCXR1QfbVwK/Ay6StHmtitqWsizvu/3Ze6pahXK64AxJ6wKf628MktaQtBfl1MGv2n6sNk2i7J+1vKRxwHv7EcMzwGOUBNmx/Y2Bslxwc0nvkbQc5bTJdom1RsxHSNpa0gqSRgCfBGZQ9i9r7butpO1q35UkHQqMBm6oXc4BtpW0Y12a+ClKJd3f2tx6f0ql19j6mQgcDRw+gGeNiIiIiIiIiCEom9H3z39TkiW/pSzzexD4PnDCAOY4GjgLeJKyef3ZwKf7GHOrJFM2jr8V+LTtc5vajwDOA54ArgbOpff9u84C3lrjf7yO/1h/grc9XdL7KPtk/bDG/8fehtR+G1Cq0G4D3m67u03fFeu8GwP/Av5S+06r954saW/gVGBtykb576zLGKmb1F9Tl0rOaJ5Y0rPATNtP9uc5IxaFSd3djL/llk6H0RF7jh7Nh8eM6XQYERERERGxlFDZaikaJD1NqXo6yfYRnY4nBpekDwDfBEYAr7Z9T099x40b54kTJy622GJ4Gn/LLUzq7mZsV1ffnYeZxnPn9NKI4aWRuM/fdsTwNH58+XfChE5GERGL0nD4O5d0k+1x7dpS0dXC9ohOxxCLju0fUirNIhabpTXZs7RWsUVEREREROdkjy5AkiXNlnTMAMZMkbTjoowrBl89cfJZSed0OpaIiIiIiIiIGFxJdL1gS9vzbVguaWVJ3ZIu6VRQvZE0QdKHOh1HO5J2lTRJ0kxJ0yX9TtJGfYxZQdKdkh5o0/ZJSffWhOTfJL2ihzkurb+zxudZSX9ptNvehIFtwh8RERERERERQ0SWLvbuvZT9ut4i6aW2H+p0QEOBpE0pG9+/B7gK6ALeAjzXx9DPAf+s/Zvn+xBwAPB2ykmLG1M24H8R2zu1jJ1QY4iIiIiIiIiIYS4VXb3bj3LS323AXj11kvTKWm20e/3+U0kPS3pS0h8kbd7U90xJ35b0G0mzJN0gaZOWua6Q9LikyZJ2G2jQkpaR9EVJ90n6p6SzJK1W2zaqSzU/LGmapIckHdIy9rC6xO8xSRdIWqO2ndJSLTVX0lFtQhgL3Gv7dy5m2b7I9v29xPwyYG/guNZnAY6knDh5R53vbtuP9+M9bAS8iXJCZEREREREREQMc6no6oGkDYDxwMHA45Sk19fa9Hst8HPgINu/rpcvBT4IPAt8FfgxJfnTsAfwNuBm4EfAMcDuklYGrgC+BOwEvAa4XNLttm8fQPj7189/UiqkzgJOAfZp6vOfwMsp1VFXSbrV9pXAJ4B3AdsDjwInAd8G9rB9cH0fSBpbY/1Fm/vfDLxS0jeBXwI32u7uI+aTgS8AT7VcX69+tpB0JjC3Ps/RtvuqENsXuMb2vX30a2vynDlL9Gbae44ezYfHjOl0GBERERERERFLjFR09Wxf4DbbdwDnAZtLaj027U2URM5+TUkubJ9Rq5ieAY4CtmxUVFUX2/6z7bnMnwR7BzDF9g9tz7V9M3ARZQnlQOwFfMP2PTXB9HlKIq05sXm07dm2/0I5hXCPev0jwOG2H2iK/73NYyWtRUnufdz2izJBtu+hJAnXBS4AptdKtq7WvnW+dwPL2f5Zm+b16r9vAf6NkqDbg7KUsS/7Amf2o9+QM6m7m3MfeaTTYUREREREREQsUVLR1bN9gdMBbE+TdDWlqqs5sfNR4Grbv29ckLQspULrfcBavLAv1ZrAk/Xnh5vmmMMLe1JtCLxe0oym9uUY+NK7McB9Td/vq/OMbro2taX935pi+Jmk5mqpeXXsg5KWBy4EzrX9k54CsH09sBuApK2B84HDKUm359UqthOAnXuYqlHhdYLtGcAMSafV/qf3dH9J2wHr1FgXyGYjRzJhq9bc5pJhSa40i4iIiIiIiOiUVHS1IemNlGV9n697bT0MvB7Yo6Uq6qPABnWJXsOewK7AjsBqwEaNaftx66mUxNmopk+X7Y8N8BGmURJWDRtQlvw1lwCt39I+rSmGnVpiGGH7wdp+MjAL+GJ/g7F9I3AxsEWb5pdT3tE19T1fDLy0vveNgMmUJaDu7/2q/SiVc30tmYyIiIiIiIiIYSKJrvb2o+w/9WrKssKxlCTNSMreWQ2zKHtt/Yek4+u1VSgnNT5W+x87gPv+GniFpH0kLV8/W0t6VS9jlpM0oumzPGWp5aclvawuFzwWOL8ulWw4QtLIulH+BygVV1A23z9G0oZQlilK2rX+/BHK3l179rY/lqTtJB0oae36/ZXAO4Hr23T/KyXp1njPH6Ik5MYCU23PqbH9r6RVJK0HHFjfVU/3X4lSUXdmT30iIiIiIiIiYvhJoquFpBGUJXcn23646XMvZQnhfs3963K6NwM7Sfo/ykbp9wEPAnfQPrnTlu1ZlL2odqdUWD1M2cx+xV6GfZeyvK/x+SFwRo31D8C9wNPAx1vGXQ38A/gd8DXbl9fr36LsO3a5pFk1/tfXtj0om9dPazp58QttYppBSWz9RVI38FvgZ5Qliq3PPLf5PVM2/n+ufp9Xux0MdNd3ch1wbn1GJL2p3qPZuyjLRH9PRERERERERCw1skdX8Qxwk6STbB8BrN6uk+2Dmn7eqOnnx4Etm7ru2jL0rKa++7fMOYEXNlzH9mTg7f0J2vb4Xpq/XD89OcP299rM+RzwjfoZyP2a+/0V2KU/fduMnUDT+6jXZlKSf+36X8MLe5w1rp1HqWp7EUmTeWGT/IiIiIiIiIgYRpLoAmyP6HQMsXjY3qzTMQyWSd3d2ZR+CJjU3c3YrrYHjkZERERERMQgy9LFiIhFaGxXF3uOHt13x4iIiIiIiFhoqehaytieQv9OgIwl3NiuLiZstVWnw4iIiIiIiIhYYixxiS5JBuYAJ9o+fDHc73bgf+reUIM575uA7w+npXLNJG1E2eh++ZbTHJdokq4C3ghMtL1dp+OJGO6G2xLbPUeP5sNjxnQ6jIiIiIiI6MGSunRxy0aSS9JGktx0yt8jkr4jafnBuJHtzQc7yVXnvWZBk1yS9pc0r+mZ75X0Q0mvGOw4FxVJ20n6k6QnJT0u6Y+Stu7HuKvq73u5pmsHS5oo6RlJZ/YxfkVJ35Q0TdITrf+t2P4v4KML82wRsXSa1N3NuY880ukwIiIiIiKiF0tcRVcvRtmeK2lt4DLgf4ATOxzTonSd7e0kLQtsBBxCORnyDfVUwwGRtNziqryStCrwa+BjlNMNVwDeRDndsrdxe9H+v8lpwFeAtwIr9XH7w4BxwBbAssCvgC8CR/b/CSJisAynJbbDqTItIiIiImK4WlIrunpk+5/AFcCrG9ckjZF0kaRHa/XTJ5rajpJ0gaSzJM2SdLukcU3tUyTtWH/eRtJ1kmZIekjSKZJWaOprSQdJuqvO9X+SNqljZtb7rFD7jpf0QMt9PivptlrldL6kPk97tD3P9t22DwKuBo5qN3+bZzlK0oWSzpE0E9i/n8/30fp8T0j6tiTVtmUlfU3SdEn3AG/vJexX1NjPq/E/Zfty27f1NEDSapRk1P+2eQcX2/458Fhf7wvYBTjJ9uO2HwVOAj7Yj3ERERERERERMcQNpYouoCS1KJU936rfl6FU7fwC2ANYD7hS0mTbl9Vh7wTeA3yAUhl0CrBtm+nnAZ8GJtZ5LgUOYv7KsbcBrwPWB26m7Pe0FyUJc12N4Uc9hL9bHf808Edgf+DUATz+xcBxA+i/K/A+YF9gRUpysK/newewNbAqcBPl3f4WOLC2bQXMBi7q5b5/B+ZJ+hHwE+B620/0EeuxwHeBh/v/eG2J+TfbF7CepNVsPzmQiSbPmbPEVnBM6u5mbFdXp8OIiIiIiIiIWKIMpYqu6ZJmAA9SEi0X1utbA2vZ/rLtZ23fA5wO7N409lrbl9ieB5wNbNnuBrZvsn297bn1dMLTgO1bun3V9kzbtwN/BS63fU9NolxKSQT15CTb02w/TkkgjR3A80NZwrfGAPpfZ/vntp+rVVX9eb7jbc+wfT/w+6YYd6McEDC1xt9jws32TGA7wJTfxaOSfilpdLv+tcLu34GTB/BsPbkU+KSktSStAzSq+0YOwtxLjLFdXew5uu3rjIiIiIiIiFhqDaWKrjXrHl0rAV+mVBm9EdgQGFOTYA3LAtc0fW+uEpoDjGi3Z1Xd7P0blD2eRlLez00tcTTvRPxUm+/r9PIMrXEM9OiudYHHB9B/avOXfj5fa4yNsqExLfPd19uNbf+NUrGGpFcC51Aqx/ZoiWkZ4DvAJ+vvt69n6ssxwChgEmVPsNMpycd/DnSizUaOHDZ7C0VEREREREQsDYZSRRcAtp8CzgTeIGlNSvLlXtujmj6r2N55Aab/LnAn8HLbqwJfYP5lcJ32bl5I4M2mqUqpblq/Vkt/t3xfmOd7iLJcs2GDfo7D9p2U39kWbZpXpSTezpf0MHBjvf6ApDf19x5N93rK9sG217W9MWVJ6U21mi8iIiIiIiIihrEhl+iStCKwD6Xy6DHgz8BMSYdKWqlumr6FpK0XYPpVgJlAd61C+tigBb6A6vO8TNLJwHjg6Nr0d0pl2tslLU85WXDFPqZbmOe7APiEpPUkrU453bCnmF8p6RBJ69Xv61Mqua5v0/1JSrXY2PppJChfB9xQxy9XN+5fFlhW0ghJbasRJa1bDyeQpG2BI8iJixERERERERFLhaGU6JohqZuyVPANwDtdzKOctDcWuBeYDnwfWG0B7vFZYE9gFmXJ2/mDEfgCekN93pnABErl09a2/wJQ9wQ7iPKsjX3LHmg/1fMW5vlOBy4DbqVswn9xL31nAa8HbpA0m5Lg+itwSGvH+jt8uPEBHq1Nj9h+tv78Rcqy0MOAvevPXwSQtIGkbkmNCrNNgD9R3sePgMNsXz6A54yIiIiIiIiIIUp26+q2zpL0NGVvpZNsH7EY7nc/sLftPyzqe0XnSbqCcuLmn23v0FvfcePGeeLEiYsnsIhhqHFq6XDZ6264PU/EgsrfQsTwNn58+XfChE5GERGL0nD4O5d0k+1x7dqWuM3obY9YXPeStBZlX6spi+ue0Vm239zpGCIiIiIiIiJi0RhKSxcHVd3D6y7gZNv3dzqeiIiIiIiIiIhYOEtcRdfiYvtGYFSn44iIiIiIiIiIiMGx1FZ0RURERERERETE8LJUJbokWdJsSccMYMztksbXn4+SdM4iCzAWOUlH1/8GLGmprWiMiIiIiIiIGI6WqkRXtaXtwwEkbVQTHt31M0XSYc2dbW9ue8JgByHprZL+IGmWpEclXS3pnYN9n06RtJ6kiyRNl/SkpL9I2r+HvttKukLS4/Vd/FTSS5vaV5R0qqRHap9fSVq3h7leLWmipCfq50pJr2602z4S2HywnzciIiIiIiIiOi8VLcUo23MljQOursdUXrGobibpvcAZwGeAXYBZwJuAvYFfDnCu5WzP7etaB5wN3ApsCDwD/BuwTg99Vwe+B1wGzAVOAX4IvK22fxJ4A/Aa4EngdOBk4D1t5poGvBe4j5LI/R/gJ3XsgEyeM+f5I9QjYuAmdXcztqur02FERERERMRSZGms6OqR7YnA7cDYxrVa5bVja19Jy0s6r1YtrSDpVZImSJpRlzu2rc6SJOAbwP/Z/r7tJ20/Z/tq2wfWPptIukrSY7Ui6seSRjXNMUXSoZJuA2ZL2rRWph0g6X7gqtrvp5IerhVVf5C0edMcO0u6o1aUPSjps01tu0qaJGmmpLslva1eHyPpl7Wq6h+SDuzldW4NnGl7tu25tm+xfWkP7/1S2z+1PdP2HEqi69+burwMuMz2I7afpiSu2lZl2Z5he4ptAwLmAZv2EmdELCJju7rYc/ToTocRERERERFLkVR0NZG0LbAFcFwf/VYCLgQepVRhLQP8ilKl9RZgO+AXksbZntwyfDNg/Tq+x1vUGP4ArApcBBwFfKqpzx7A24HpQON/SW4PvAp4rn6/FPgg8CzwVeDHvJDE+wGwm+1rJK1OSSYhaRvgLEpV1O+AlwKr1DHnURKBY4BXAldIusf279o8w/XAtyWdDPzJ9v29PG+r/6j3afgB8C1JY4AZwF712XokaQbQRfndfGkA937eZiNHMmGrrRZkaERERERERER0QCq6iumSngKuA74D/LyXvqsCvwXuBj5gex6wLSWpcrztZ21fBfyakoxq9ZL670M93cD2P2xfYfsZ249SKsC2b+l2ku2ptp9qunZUraB6qs5zhu1Ztp+hJMq2lLRa7fsv4NWSVrX9hO2b6/UDgDPq/Z+z/aDtOyWtT0ngHWr7aduTgO8D+/TwGO8DrgGOAO6tFWJb9/TMDZJeQ0lMfa7p8t+B+4EHgZmUZN6Xe5vH9ihgNeBgIOsPIyIiIiIiIpYCSXQVa1ISVZ8FxgPL99J3W8p+T8fX5XFQKpym2n6uqd99QLsN0x+r/760TRsAktaW9JO6pHAmcE6NsdnUNkOfvyZpWUnH16WHM4Eptakxz38DOwP31Y3w31Cvr09J4rUaAzxue1bTtZ6ekZo8O8z25pSKs0nAz+vSzbYkbUqp1Pqk7Wuamr4LjKAkCVcGLqaPiq4aw2zgVOAsSWv31T8iIiIiIiIihrYkuirb82x/HXgaOKiXrpdTlhX+TlJjyeA0YH1Jze9zA0oFUqvJlITUf/dyj+MAA6+xvSpleWRrgsgvGjX/tT2BXYEdKZVNG9XrArB9o+1dgbUpFWwX1PapwCZt5p4GrCFplaZrPT3j/EHZ04GvUZJla7TrI2lD4ErK3mVntzRvSdnv6/FanXYysI2k1uRfO8sAI+khIRcRERERERERw0cSXS92PPC/kkb01MH2CcC5lGTXmsANwOw6bnlJ4ymnKf6kzVhTTls8QtIHJK0qaRlJ20n6Xu22CtANzJC0LvMv4+uvVSinHT5GSfQc22iom+fvJWk12/+iLAecV5t/AHxA0g41rnUlvdL2VOBPwHGSRtQlhgdQ9v16EUlflbSFpOVqcuxjwD9sP9am77qUDfS/bfvUNtPdCOwraTVJy1MSkdNqAq11rjdL2qpWtK1KWfb5BPC3fryziIiIiIiIiBjCkuh6sd9QEiO9nSiI7f+jVEJdSVn2+E5gJ8rm8N8B9rV9Zw9jLwTeT9kofhrwCPAV4Be1y9HAa4EnazwXL8BznEVZWvggcAdlc/hm+wBT6rLGj1KqxrD9Z+ADwDfr/a8GNqxj9qBUhk0DfgYcafuKHu4/svaZAdxT52h7EiXwIWBj4EhJ3Y1PU/tnKZV2d1EOANgZeHejsZ5yuVf9Ooqyaf6TlCWYmwJvq6c1RkRERERERMQwphe2mRr+JD1NqXI6yfYRnY4nFj9JR1Iq6lYEVq6HCbQ1btw4T5w4cbHFFhFLtvG3lHMtchprLO3ytxAxvI0fX/6dMKGTUUTEojQc/s4l3WR7XLu25RZ3MJ1ku8fliLF0sH00pWIuImLAJnV3P/8/8iOWVpO6uxnb1dXpMCIiIiLaytLFiIiIiOi3sV1d7Dl6dN8dIyIiIjpgqaroGihJBuYAJ9o+vNPxxMKR9ArgZmAl4CO2v9/hkCJiiBnb1ZXlWhERERERS7BUdPVty0aSS9JGkty8YXr9vH9xBiTpKEnnLM579pekCZI+1HJtvKQHehlzjqSHJM2U9Pfm8fWEyAslTanvfnwf92/93cyTdDKA7b/b7gKuWbinjIiIiIiIiIglUSq6Fswo23M7HcQwchxwgO1nJL0SmCDpFts31fZrgROBn/Y1UU1kASBpZcqJln2Oi4iIiIiIiIihL4muQSJpW+DnwLqNk/wkvRs42vZrJG0DfAt4FfAUcBHwGdvP1r4GPgYcAqwJnAsc7AEeiynpnZTE0brAJOBjtv9W26YApwH7AC+t8X7M9tO1/R3AV4CNgDuAj9q+rVas/aDpNssD19keP5DYemL79uav9bMJcFN9PyfW+Ho8IbEH7wX+yQJWcE2eMyebTg8he44ezYfHjOl0GBEREREREdFBWbo4SGxfD8wG/qvp8p6UhBXAPODTlCTWG4AdgINapnkHsDWwJbAb8NaBxFD3oDoP+BSwFnAJ8CtJKzR126vOuwnwCuCLdexrgTOAjwAvoSTEfilpRdvn2+6q1VJjgHvqfQaNpO9ImgPcCTxUY19Y+wFnDTRZGEPPpO5uzn3kkU6HERERERERER2Wiq4FM11S8/c31Kqp84A9gCskrQLsDHwWoGkZHsAUSacB21Orlarjbc8AZkj6PTAW+O0A4no/8BvbVwBI+hrwSeCNwITa5xTbU2v7McDJlGTXgcBptm+o/X4k6QvAtsDVtf8ylMTdBNun9RLHSfXeDcsBM3oL3PZBkj5OSQKOB57pzwP3RNIGlPd7wILOsdnIkdl0eohI5V1ERERERERAKroW1Jq2RzV9/lavnwu8R9KKwHuAm23fB6XaStKvJT0saSZwLKW6q9nDTT/PAboYmDHAfY0vtp8DplKWMTZMbfr5vjoGYEPgEEkzGh9g/aZ2gGOAVYBP9BHHJ5rfD6VSrU+259m+FliPsoxzYewLXGv73oWcJyIiIiIiIiKGiCS6BpHtOyjJo52Yf9kiwHcpy/JebntV4AuAXjTJwplGSVgBoFJ2tj7wYFOf9Zt+3qCOgZIAO6YlgTfS9nl1rt0p1Wrvtf2vQY671XKUpZULY1/gR4MQS0REREREREQMEUl0Db5zKRVP/8H8p/2tAswEuuvJggtbsbSMpBFNnxWBC4C3S9pB0vKUje2fAf7UNO5/JK0naQ1Ksu38ev104KOSXq9iZUlvl7SKpK0oSxzfZfvRhYx7PpLWlrS7pC5Jy0p6KyUUhAY9AAAgAElEQVShdlVTnxUljahfV6jP22OSUNIbKVVsOW0xIiIiIiIiYimSRNeCmSGpu+nzmaa28yh7TF1le3rT9c9SqrxmUZJK57Nw9qCc3tj43G17MrA3JSk1HdgF2KVxsmN1LnA5ZUP5eyinLGJ7ImWfrlOAJ4B/APvXMbsCqwPXNj3zpQsZf0PjtMkH6n2/BnzK9i+a+kyuz7gucFn9eUMASV9oE8t+wMW2Zw1SjBERERERERExBCgH0vVM0tOUiqiTbB/R6XgWlqQpwIdsX9npWDpB0suBG4EVgINsn9lb/3HjxnnixImLI7RYSONvuYVJ3d2M7RrotnZLtj1Hj+bDY8b03TEWi8ahBzmkIiIihrPx48u/EyZ0MoqIWJSGw9+5pJtsj2vXllMXe2F7RN+9YqiwfRcwqtNxRPTHpO5ugCS6IiIiIiIiBiCJrogYFsZ2dQ2rSptG9VBERERERET0X/bo6oMkS5ot6ZhOx7KwbG+0sMsWJW1U38mQS5JK2rHuL/acpB07HU9EREREREREDK4kuvpnS9uHN77URM+mg30TSftLmte04fu9kn4o6RWDfa9FRdKU1iRSfa5r+zF2+/puv9J07T8l/UXSDEmPSfqZpHX7mOeT9d3NlvS3xvuzfaXtLuD+BXy8iIiIiIiIiFiCJdG15LmuJmNWA3aknDB4k6QtFmSyoVJ5JWl54FvADS1NdwBvtT0KGAPcBXy3l3k+BBwAvB3oAt5BOYEyIiIiIiIiIoa5JLoWkqQzWyqQxkt6oOn7FEmflXSbpCclnS+pz03ubc+zfbftg4CrgaPazd90jx3rz0dJulDSOZJmAvtL2kbSdbUq6iFJp0haoWm8JX1U0l2SnpD0bUmqbctK+pqk6ZLuoSSQFoVDgMuBO1vewyO2pzVdmge0raaTtAxwJPBp23e4uNv244so5oiIiIiIiIhYggyJap9hYDfgbcDTwB+B/YFTBzD+YuC4AfTfFXgfsC+wIvBq4NPARGA94FLgIODEpjHvALYGVgVuAn4F/BY4sLZtBcwGLhpAHP0iaUPgg8BrgVPatG8A3FZjm1djame9+tlC0pnAXOAs4Gjbzw00rslz5mRD8CFiUnc3Y7u6Oh1GREREREREdFgSXYvHSY2qJEm/AsYOcPw0YI0B9L/O9s/rz09RElcNUySdBmzP/Imu423PAGZI+n2N8beUJN2JtqfW+I8Dxvdx/59Lmtv0fQXg5l76nwQcYbu7FpLNx/b9wChJa1CSXP+fvTuP93Su/z/+eFonZhhLaGxTYUjlVCPqR00p34ioqIwUkaV8tWiRpSiUioQWCSNjSyV9SVGassbgkKURmmkmBoMZM2PGMp6/P97vDx/H2efMnDlnnvfb7XM7n+t6L9fruo5Dt1ev9/v658s6FevVn9sDbwCGU6rEpgFndBFzDGAtQ4cydu21+zuMiIiIiIiI6GdJdC0e05u+P0XZa6on1gV6svxuavNB3Yz9JGA0sBLl935LmzFtY2yUx4xoM9+Ublx/1+a3O0raG9ivvY6SdgaG2b6oq0ltPy7pHOB2Sevafq5Nl3n153ebknanAzvSi0TXqJVWYsKb3tTTYRERERERERHRT5LoWnhzKcmjhnUWwTU+CFzT3vUkLQu8sk1/tzn+CXAbsIft2ZI+D+zWzWs/BKzfdLxBd4Pupu2A0ZIaibZVgQWS3mB7l3b6LwesRVnG2Db5Nwl4hpfff0REREREREQsBbIZ/cJrBXaUtLqkdYDP98WkdRP4V0s6lbJU8JjadC8wRNL765sKj6Tsw9WZYcCTwBxJmwIH9SCUXwKHSFpP0mrAYT25j244CtiEslSyBfgdpfpqHwBJH5I0StIykl5JqUy7rb0N5m0/BVwEfEXSMEnrUZY6XtbHMUdERERERETEEiiJrt5rVA2dC9wOTKbsB9XlErwuvE3SHEpiagKlcmlL2/8AsD2LspH8z4H/Uiq8prU/1Qu+BIwFZlOSSD2J8Qzgj5R7vJWyMX6fsT3b9vTGh7L8cG5TImtdyl5hs4F/AM9TKtwAkPRTSc0b+x8MzKHsa3YDcD5wVl/GHBERERERERFLJtlZ5dUZSfOBpykbyh8laRVgFrBa3QcqBghJ21HeGrkisKPtv3TWf/To0Z44ceJiiS2ircYbP7NP3JIjv5OIiFgajBlTfk6Y0J9RRMSiNBj+ziXdYnt0e23Zo6sLtoe0OfVR4P4kuQYe23+mvIkxYkBonTPnheRK9L/WOXNoGTq0644REREREdFvkujqAUnXUxIl7b5BMCIiBq+WoUMZu/ba/R1GRERERER0IomuHrD99v6OISKWHi1Dh2aZXERERERERA9kM/qIiIiIiIiIiBgUlvpElyRLmivpuB6M2UDSHEnLLsrYllSSjpY0vr/j6A1J4yTNk9TVmyojIiIiIiIiYoBZ6hNd1Ra2jwCQNLImv16yrLMmSI4FsP0f20NtL+jrQCRNkDRf0mxJT0q6RdJhklbs62stCpLGtJdEqvfV5d5mks6uz3+jpnPrSrpU0uOSpkk6sJuxvGwu23sDO3TvbiIiIiIiIiJiIEmia8l0sO1hwKuAQ4GPAb+XpJ5O1DZhtySTtA3w2naaxgP/BtYG3g8cL+ldvZwrIiIiIiIiIgapAZMEWZJIGklJvCxv+zlJE4BrgHcDbwRuAMbanlH7XwxsC7wCuB04yPZdXV3H9lxggqQPAP+kJHkukzQOmGb7yDr/GGC87fXq8WTgJ8CewChJKwNfAj4NrAVMBY6wfUntvzflTZI3AvsCM4HP2L6itr8aGAe8ufaZ1NNn1pWakDsV+CTlGTXODwXGAB+x/Sxwu6RfAZ8C/tKTuXpq0lNPMea223o7PLpp7Nprs/+IEf0dRkRERERERAwCqejqO2OBfSiJpBUoiaWGK4CNa9utwHk9mdj2f4CJlGRZd+1BSYwNt/0ccH8dvypwDDBe0qua+m9FSWCtCXwXOLOpgux84Jba9i1KAqmvfQH4m+072pxXm5+N76/vxVyxhGmdM4fzH364v8OIiIiIiIiIQSIVXR2b0Wal4EqUBFBHzrZ9L4CkXwIfaDTYPqvxXdLRwBOSVrU9qwfxPAis3oP+p9ie2hTDxU1tF0n6GvBW4NJ6bortM2qM5wA/BtaWtAKwJfAe208Df5P0f11ce4SkmW3ODaUsQXwZSesDBwBvadtme7ak64CjJH0ZeB3wYeDRns7VU6NWWokJb3rTwk4TnUjFXERERERERPSlVHR1bE3bwxsfSlVTZ6Y3fX+KkthB0rKSviPpfklPApMb8/cwnnWBx3vQf2rzgaRPSGqVNLMmoV7fJoYX4rf9VP06FBgBPFGXUTZM6eLaDzY/u/r8ru2k/8nANztJ/O0JvLre008oFXEdvTWxq7kiIiIiIiIiYpBKomvRGwvsAryHsmxwZD3f7Y3la5XSWyj7gAHMpVSYNazTzjA3jd8QOAM4GFijJp7u7GYMDwGr1X2+GjbobuzdtB3wPUnTJTUSbjdIGgtge4rtnWy/0vZWwBrATb2ZKyIiIiIiIiIGryxdXPSGAU8Dj1GSU8d3d6CklSjLBn9ASez8vja1AodKOpayH9jnu5hqZUri69E67z50vsfVC2xPkTQROEbS4ZTljjsDv+vufXTDJrw06fpQvcbtNd7NKBVcTwMfAbYHNuvNXBERERERERExeKWia9H7BWWp33+BuylvLezKaZJmAw9TluL9Gnif7edr+7mUxM1k4Ergos4ms303cCLlbZAPA28AruvBPYylbFb/OPCNek99xvYjtqc3PvX0DNvz6vf/AR4AngAOpDyLF/bokjRH0rbdnCsiIiIiIiIiBinZ7rrXICZpPqVS6BTbR/V3PLFoSToT2B14xPZGnfUdPXq0J06cuHgCW0qNue02WufMoWXo0P4OZYnTeC55IUJEREQsTmPGlJ8TJvRnFBGxKA2Gv3NJt9ge3V7bUr900faQ/o4hFh/b+wL79nccEV1pGTqUsWuv3d9hREREREREDChLfaIrIvpXqpYiIiIiIiKir2SProiIiIiIiIiIGBQGRKJLkiXNlXRcP13/cEk/r99H1nhSDTcASRonaZ6kaf0dS0RERERERET0rQGR6Kq2sH1E40DSCpKOlvSvmgSbLOksSSP7+sK2j7e9X1/MJelVks6U9JCk2ZL+KekYSSv3xfz9TdKY9pJIkiZI6vIZSjq7JhI3anP+PZJurb/rqZI+0pu5bO8N7NC9u4mIiIiIiIiIgWQgVyX9ClgPGAvcBqwMfBzYDjizH+PqkKTVgRuA64G32Z4saX3gS8BrgTt6ON9ytp9rOhblTZrP92HYi42kbSjPoe351wHnA58ErgJWBYb3Zq6emPTUU4y57baFmSK6kDcuRkRERERERF8aSBVdL5D0HuC9wC62b7b9nO1Ztn9k+8zaZx9J99SqqQckHdA0foykaZK+IumRWl21q6QdJd0r6XFJhzf1P1rS+A5i6fA67fgiMBv4uO3JALan2v6c7TvqfD+sFUtPSrpF0rZt4viVpPGSngT2rpVSx0m6DngKeE0X976mpMskzaz3eY2kZWrb+pJ+I+lRSY9JOq2eX0bSkZKm1Of1C0mr9uiX1oW6FPRU4OB2mo8ETrd9Rf1dP2b7/l7OFUuQvFkwIiIiIiIi+tJAreh6D3CT7amd9HkE2Al4AHgHcIWkm23fWtvXAYYA6wJ7A2dQqoXeAmwA3CLpQtsPdBFLV9dpG/dvuqi4uhn4JjAL+BxwsaSRtufX9l2A3YFPACtSqtj2oizHmwQIGNVJTIcC04BX1vm2BixpWeAy4Oo63wJgdO2zd/28q97vL4DTar++8gXgb7bvKIVpL7E1cL+kfwBrAn8GDrH9eC/m6rZRK62UtwFGREREREREDCADsqILWAN4qLMOti+3fb+LvwJXAts2dXkWOM72s8CFlATKD23Ptn0XcBfwxq4C6cZ1ehr3+Fqx9JztEynJrFFNXW6w/Vvbz9ueV8+Ns31XHfNsFzE9C7wK2LD2vca2gbcCI4Av255re77ta+uYPYGTbD9gew7wNeBjnWzIP6JWjL3wAbbp6J7r8s0DgK930GU9SlLtw8DGwCsoFVu9mSsiIiIiIiIiBqmBmuh6jJKs6ZCkHSTdWJfnzQR2pCSzXpjD9oL6vZEweripfR7Q5eZB3bhOT+M+tC47nFXnW7XNfO1Vsb3kXBcxfQ+4D7iyLms8rJ5fH5jSvOdXkxHAlKbjKZRqwI7WnD1oe3jzB7i2g74AJwPftD2rg/Z5wNm2762JtuPrPfVmroiIiIiIiIgYpAZqoutPwFslrddeo6QVgV8D3wfWromW31OW9fWZXlznT8AHG3titTPftsBXgY8Aq9X5ZrWZz+0MfeFcVzHVirVDbb8G2Bn4oqTtKMmyDTqo0noQ2LDpeAPgOV6aGFwY2wHfkzRd0vR67gZJY+v3O2j/vnszV0REREREREQMUgMy0WX7T5T9tC6R9BZJy0kaJulASZ8CVqAs+XsUeE7SDsD2iyCUnl7nJGAV4BxJGwJIWlfSSZLeCAyjJJAeBZaT9PXav89ikrSTpI1UNq96krIX1wLgJsqyyu9IWlnSEEn/rw67APiCpFdLGkqpqLqog+qv3tgE2AJoqR8oSbhL6vezgX0kvUbSSpRk4GW9nCsiIiIiIiIiBqkBmeiqdqNUKl1EqXq6k7J5+p9szwYOAX4JPAGMBX7X1wH09Dp18/S3U/bJ+ruk2ZSN1WdRlhP+EbgCuJeyPHA+7S9VXJiYNqZUls0BbgB+bHtCXca5M7AR8B/KhvUfrWPOAs4F/gb8u8b1vz2Jq4uYH7E9vfGpp2c09iCzfRZlA/y/U57L0/UeAZA0p/F2yq7mioiIiIiIiIjBS2Uf8iWbpPmU5MYpto/q73hi4JJ0JuWtlY/Y3qizvqNHj/bEiRMXT2AREREREUuAMWPKzwkT+jOKiFiUBsPfuaRbbI9ur62jt+YtUWwP6e8YYnCwvS+wb3/HERERERERERF9byAvXYyIiIiIiIiIiHjBUpHokmRJcyUd19+x9Ie6h9Vr+juO/iZpk/osFkjar7/jiYiIiIiIiIi+tVQkuqotbB8BIGlkTX5d3txB0nhJRy/shSQdLWn8QoxfT9KvJc2QNEvSPyTtXdsasXd72antobYf6G08PSFpQtskkqQxkqZ1Me5jku6pCcn7G5vLS1pB0q8kTa73PaYbMbQ7l+17bQ8Frun9HUZERERERETEkmppSnS1Z2tJ/6+/g2jHuZS3LW4IrAF8Ani4XyNqh6Rl+2ie9wInAPsAw4B3AM2JuWuBjwPTXz66x3NFRERERERExCA1IDajX4S+CxwLvKttg6TVKAmnrSjP6TrgQNvTavsI4KfANsDjwAm2z5D0PuDw0kW7Avfb3qKj/h3EtSXwBdtz6/FtTW1/qz9nSgJ4r+0bJH0K+DKwDnATsL/tKTVWAxvbvk/SOGAuMJKSBLobGGv7/tp3U+BU4C3Ao8BRtn9Z28YB8ygJuHcCuwB/6vDpdt8xwDdt31iP/9tosP0McHK9/oKFmavHJk168XUUi9rYsbD//ovnWhERERERERGD1NJe0fUjYBNJ72mnbRngbEpSZwNKgue0pvYLgGnACGA34HhJ29n+A3A8cFFdMrhFZ/07iOtG4Ed1Cd4GbdreUX8Or/PfUBNqhwMfAl5JWZp3QSf3vQclIbQacB9wHICklYGrgPOBtWq/H0vavGns2Np/GKXSaqHUqrDRwCsl3SdpmqTTJL2iP+darFpb4fzz+zuKiIiIiIiIiAFvaa/omk9J2hxLm8ok248Bv24c143s/1K/r0+pzNrJ9nygVdLPgb2AP7e9SE/7A7sDXwWOAjaV9A/g07Zv7uA+DgC+bfueer3jgcMlbdio6mrjN7Zvqn3PA06q53cCJts+ux7fKunXlMTcXfXcpbavq9/ndxDPKZK+33S8HDCzg75rA8vXa2wLPAtcChwJHNHBmI705VwwahRMmNDjYT22uKrGIiIiIiIiIga5pb2iC+AMYG1JOzeflLSSpNMlTZH0JGXJ4PBaNTQCeNz27KYhU4B1O7hGj/rbfsL2YbY3pyRvWoHfqq5VbMeGwA8lzZQ0k7I0Up3E07zX1VPA0KZ5tmrMU+fak7IcsmFqB3M2O8T28MaHkkDryLz681TbD9meQUm87diN6yzKuSIiIiIiIiJigFnqE122n6Us4/sWJTnUcCgwCtjK9iq8uGRQwIPA6pKGNfXfgBf3g3Kby3TVv7P4ZgDfpyTLVm9nbijJpwOak0u2X2H7+q7mb2eev7aZZ6jtg5pD6uGcnbL9BGVJ50LP25dzRURERERERMTAs9QnuqpzgRWB9zWdG0apEJopaXXgG40G21OB64FvSxoi6Y3AvsB5tcvDwEhJy3Sz/0tIOkHS6yUtV5NjBwH31eWUjwLPA69pGvJT4GuNvbQkrSpp9148h8soe5btJWn5+tlS0ma9mKsnzgb+V9Ja9SUAn6+xACBpRUlD6uEK9Rl2VN3W6VwRERERERERMXgl0QXYXkBJZK3edPpk4BXADMrm8H9oM2wPypsLHwQuAb5h+6radnH9+ZikW7vRv62Vap+ZwAOUJYUfqLE+RdlX7Lq6vHBr25cAJwAX1mWWdwI79OARUOeeDWwPfKzGOb3Ou2JP5+qhbwE3A/cC91DeMnlcU/skStJxXeCPvPjmRyQdLumKHswVEREREREREYOU7MG/ykvSfOBp4BTbR/V3PNE/JG1MSYKtAHzG9rjO+o8ePdoTJ05c9IGNGVPevNjS8tLzY8fC/vsv+utHRERERFSN9yQtjncyRUT/GAx/55JusT26vbal4q2Ltod03SsGO9v/Aob3dxzd0tpafibRFREREREREdFtS0WiK2KJ19Ly0nR6I8UeEREREREREd2WPboiIiIiIiIiImJQGNCJLkmWNFdSNhuPbpF0taT5kq7t71giIiIiIiIiom8N6ERXtYXtIwAkjazJr5csyZQ0TtKx/RPeS0naRNLFkmZImiXpDklflLRsf8fWFyTt3V4SSdJkSe/pZNxrJF0maXZ9Nt9tajtY0kRJT0sa18X1JelYSf+tz3eCpM0b7bbfDRzYu7uLiIiIiIiIiCXZYEh0DRiSXgv8HZgKvMH2qsDuwGhgWC/mW7bN8YDcc03SCsBVwNXAOsB6wPimLg8CxwJndWO63YFPAdsCqwM3AOf2ZbwRERERERERsWQakImRhSXpYkoi5BXA7cBBtu+qbeOAp4BX1z63Ax8GDgM+CTwM7GH7ttr/MODTwFqUBNYRti/p4NLHANfb/mLjhO1JwNgexDYP2BB4J7CLpJ8DPwH2BEZJWhn4UkcxSdoIOBNoAZ4F/mz7o7Vtc+Bk4C217Ye2j5e0InAC8JEa5i+Br9p+uuun3S17Aw/aPqnp3B2NL7Z/U+MbTUmCdebVwLW2H6hjxgNf6FVUkyYtnk3hW1vLZvQRERERERERsVCW1oquK4CNKYmgW4Hz2rR/BDgSWBN4mlIVdGs9/hXQnJC5n5KYWpWSyBov6VUdXPc9dfzCxDYWOI5SAdZYIrgH8H5guO3nuojpW8CVwGqUpNGpAJKGAX8C/gCMADYC/lzHHAFsTUmObQG8lfJ8+srWwGRJV9RlixMkvaGXc10IbFSXiC5PSU7+oc8iXRRaWmDs2K77RURERERERESnBmtF1wxJzccrAS/s+WT7hSVwko4GnpC0qu1Z9fQltm+p7ZcAn7H9i3p8EXBw01wXN13nIklfoySCLm0nrjWAhzoLvBuxXWr7uvp9fr3PU2xP7WZMz1IqwkbYnsaLybKdgOm2T2zMTVlmCaVa7H9tP1LjOgY4HTiqg9vYWtLMNudW6eS21wPeBXyAklz7HHCppE1tP9PJuPY8BFwDTAIWUCra3t3DOYpRo2DChF4NjYiIiIiIiIjFb7AmutaslU3AC0v+Gt+XpVRE7Q68Eni+MQZoJJMebpprXjvHQ5vm+wTwRWBkPTW0ztWex4COqr26G9vUdoa+5FwXMX2FUtV1k6QngBNrcm19SiVYe0YAU5qOp9RzHbnR9jZtYprcSf95lOWGV9S+36dUjG1GWb7ZE98AtqTcz3Tg48DVkja3/VQP5+pfra2LZ+nkQDN2LOy/f39HEREREREREUugpXHp4lhgF8oywlV5MRmkjgZ0RNKGwBmUCq81bA8H7uxkrj9R9vtamNjczrgXznUVk+3ptj9tewRwAPDjum/XVOC1HcT1IKUKrGGDeq6v3EH799UbWwAX2Z5m+znb4yjLNF/XR/NHf2pthfPP7+8oIiIiIiIiYgk1WCu6OjOMsu/WY5QljccvxFwrUxI0jwJI2gd4fSf9vwHcLOl7lEqq6TXJdDQlMdUXsXUak6TdgRvqssUnat8FwGXASZI+T9ncfgXgdbb/DlwAHCnp5tr/67z0rYgLazxwqKT3AH8BDgFmAPfUmJej/LO6LLCspCHAc81Ve01uBnaXdGF9BnsCywP39WG8i0dLS5ZOtpUKt4iIiIiIiOjE0ljR9QvK0rv/AncDN/Z2Itt3AydSNqt/GHgDcF0n/e8H3kap1LpL0izg18BEYHZfxNaNmLYE/i5pDvA74HO2/217NvBeYGfKkr9/UfbNAji2xngH8A/KJvnH9jS2TmKeRFli+FNK8m0X4ANN+3MdSVneeFjtN6+eQ9IGkuZI2qD2PYGy3LEVmEl54+KHbbfdMywiIiIiIiIiBhnZfbVibPGTNJ9SAXWK7Y42Ro94gaSrKG95vMn2dp31HT16tCdOnLh4AmurUbmUiq6XynOJiIiIWKTyP7ciBr/B8Hcu6Rbbo9trG9BLF20P6e8YYmCx/d7+jiEiIiIiIiIiFo2lceliREREREREREQMQkl0RURERERERETEoDDgEl2SLGmupOMW8XUOl/TzRXmNNtebIGm/Xow7WlJfvgGxMa/rGyHba9tT0pV9fc3FQdIx9Z8f17c5RkRERERERMQgMeASXdUWto8AkDSyOWmh4lRJ/5S0bm8vYPt4271JPF1R3wI4R9Kzkp5pOv5pb+NZktg+z/b27bW1/X00nR8nqcM3NUpaSdKPJc2QNEvS39rps0L9vU7rZJ4VJP1K0uQax5g2sX8D2Lyre4yIiIiIiIiIgWdQVbRIEnA68DbgnbYfXtwx2N6hKZ5xwDTbRy7uOAagn1H+edwMeBxoaafPl4FHgKFdzHUtcDJwcV8GGBERERERERFLtsGU6FoWOBN4AzDG9mMAkjYFTgXeAjwKHGX7l5K2Bn4LrGt7Qe37QeAY22+UdDSwke2PSxoJ/BvYG/gWsBLwA9vdXj4paTXgXGArynO/DjjQ9suqkyS9Cvgj8Avb35f0Q+BDwKrAv4DP276macgKkn4BfBD4D/BJ2xPrXIcBnwbWAqYCR9i+pLZtVJ9ZC/As8GfbH22a9z2SrgDWBM4HDrZtSXsD+9neprv33xlJo4APAOvZfrKevqVNn1cDHwe+CJzR0Vy2n6EkuZC0YKECmzTpxfeuLm6trdDSXq4vIiIiIiIiIjoymBJd5wHrA++2PRNA0srAVcDXgR2ANwJXSrrL9o2S5gLvrn0AxlISOh3ZBhgFbALcJOk3tu/pZnzLAGcDH6Ek5c4CTgN2be5Uk2pXAt+3/bN6+mbgm8As4HPAxZJG2p5f2z9ASYTtAxxb5926tt0PbAtMB3YHxkvayPZDlKTdlcC7gBWA0W1i3gnYEliFknj6P+AP3bzfntgKmAIcI2kv4CHgaNu/bupzKnA4MG8RXH/J09ICY8f2dxRLptbW/ktAxpJv7FjYf//+jiIiIiIiIvrJYEp0bU+pxprZdG4nYLLts+vxrZJ+DewG3AVcAOwBXCVpGLAj8KVOrnGM7XnA7ZJuB7YAupXoqhVmLyRu6mb6f2nT7Xtr3H8AACAASURBVHXAkcDXbF/QNLZ5s/kTJR1JSbjdXs9da/v3dd5zgc83jW1evneRpK8BbwUupVRxbQiMqJVl17aJ5zv1ec6U9BdK5Vd3E10zykrSF6wEfLeDvusBr6c8nxGUpaeXS7rb9j210m4525e03XNrkRo1CiZMWGyXi4iF1NpafibRFRERERGx1BpMia6dgMskPWH7rHpuQ2ArSc3Jr+UoSwihVG9dL+kgSkXUrbandHKN6U3fn6LrvaJeIGkl4AfA+4DV6ulhkpZtLJ0E9gTuA37VZuyhwH6UJJApFVZrdhLXEEnL2X5O0icoy/1G1vahTWO/QqnquknSE8CJTc9uoe4XWNP2c033MK6TvvMoSbdj65i/1sTa9pL+Q0mQ7diDa8dg1tKSBGS0L5V+ERERERFLvcGU6Loe2JmS7Jpv+3zKnlR/tf3e9gbYvlvSFMqyxq6WLS6sQylVWFvZni6pBbgNaC57OpqSCDtf0sdsL5C0LfBVYDvgLtvP16SU6IKkDSn7WW0H3FDna22MtT2dsn8XkrYB/iTpb7bv65tb7rY7OmnbmJKku6ZWiK0ArCppOrC17cmLPLqIiIiIiIiIGBCW6e8A+pLtv1Iqs34maTfgMmATSXtJWr5+tpS0WdOw84FDgHewaN/SN4xSuTRT0urAN9rp8yxlH62VgXMlLVPHPUfZSH85SV+nVHR1x8qUCrBHASTtQ1kiSD3eXdJ69fCJ2nfhNnDvnb9RNtH/mqTlJP0/YAxlQ/47KXuvtdTPfsDD9fvU9iaTtKKkIfVwBUlD1GYdZUREREREREQMPoMq0QVg+yrgo8A4SrJke+BjwIOUpXgnACs2Dbmg9rva9oxFGNrJwCuAGcCNdLDXVX1r4Icob0k8i5LsuQK4l7Jh+3w6SPC0M9fdwInADZTk0Bsob3ts2BL4u6Q5wO+Az9n+d09vbGHZfhbYhbI8cRalCu0Ttv9p+znb0xsf4HHg+XrceFvmXZL2bJpyEiWpuC7l+c2jLGONiIiIiIiIiEFMtvs7hh6RNB94GjjF9lH9HU8MLJK+QdmzbEVg5ab90V5m9OjRnjhx4mKLLbqhsQdT9uiK9uSfj4iIiIWW/5xGDH6D4e9c0i22R7fXNuD26LI9pOteEe2zfQxwTH/HERERERERERF9b9AtXYyIiIiIiIiIiKVTEl29JMmS5ko6rr9jie6RtImkOZIWSNqvv+OJiIiIiIiIiL6VRNfC2cL2EQCSRtbk15z6mSzpsEVxUUlHSxq/KOZeWJImtE0iSRojaVoX4z4m6Z6aPLxf0rb1fNvnOkdSp3uzdTSX7XttDwWuWcjbjIiIiIiIiIgl0IDbo2sAGG77OUmjgb/WDdKu6u+glmSS3kt5G+ZHgZuAV7XTbbjt5/poroiIiIiIiIgYhJLoWkRsT5R0F9ACXAUg6VPAl4F1KEmY/W1PqW0GDgIOBdYEzgcOdg9fiynpA8C3gXWBVuAg2/fUtsnA6cBelATQb2v7/Nq+E3AsMBK4GzjQ9h2SPgqc2XSZ5YEbbI/pSWydOAb4pu0b6/F/l4i5Jk168XUUsWRobYWWlv6OIiIiIiIiIpZQWbq4iEjaGng9cF893hU4HPgQ8ErK8rkL2gzbCdgS2AL4CPA/PbzmJnXOz9dr/B74P0krNHXbs877WmAT4Mg69s3AWcABwBqUhNjvJK1o+yLbQ+uyvxHAA+3E3iuSlgVGA6+UdJ+kaZJOk/SKNl2n1LazJa25kHPFQNXSAmPH9ncUERERERERsYRKRVffmyFpRWAIcCKlagpKAunbTdVVxwOHS9qwUdUFfMf2TGCmpL9QqsH+0INrfxS4vLFUUtL3gc8Bbwcm1D6n2Z5a248DTqUkuz4NnG7777XfOZIOB7YG/lr7L0OpNJtg+/RO4jilXrthOWBmB33XplSI7QZsCzwLXFpjOgKYQUn+tVIScD8CzqP9JGBXc/XMqFEwYUKPh0VERERERERE/0hFV99bExgKfAkYQ0m8AGwI/FDSTEkzgccBUZYYNkxv+v5UnacnRgCNpBm2nwemtrnG1KbvU+qYRnyHNuKrMa7f1A5wHDAMOKSLOA6xPbzxoVSqdWRe/Xmq7YdszwBOAnas9zDH9kTbz9l+GDgY2F7SKj2dKyIiIiIiIiIGtyS6FgHbC2yfCMwHPlNPTwUOaE4A2X6F7ev78NIPUhJWAEgSJVnVvE/V+k3fN6hjGvEd1ya+lWxfUOf6GLAHsJvtZ/sqYNtPANOA7u5F1uinPpgrIiIiIiIiIgaRJLoWre8AX5E0BPgp8DVJmwNIWlXS7gsx9zKShjR9VgR+Cbxf0naSlqdsbP800JxM+6yk9SStTtkz7KJ6/gzgQElbqVhZ0vslDZP0JsoSx11tP7oQMXfkbOB/Ja0laTXKHmOXAdR4RklaRtIawCmUpZOzejpXRERERERERAxuSXQtWpcDTwCftn0JcAJwoaQngTuBHRZi7j0oS/Uan/ttTwI+TklKzQB2Bna2/UzTuPOBKykbyj9AecsitidS9uk6rcZ8H7B3HbMLsBpwraQ59XPFQsTe1reAm4F7gXuA2yjLJAFeQ9mnbDblmT1d7x0ASYe3iaWzuSIiIiIiIiJiEJOdVV69IWk+Jelyiu2j+jue7pA0GdjP9p/6O5b+IGljShJsBeAztsd11n/06NGeOHHi4ggtIvrCmDHlZ14iERER0Wv5z2nE4DcY/s4l3WJ7dHtteetiL9ke0t8xRM/Y/hcwvL/jiIiIiIiIiIhFI0sXIyIiIiIiIiJiUEhF11LE9sj+jiEiYpFqbX2xFjv6ztixsP/+/R1FRERERESXluiKLkmWNFfSUrGZuKS9JV3bi3Ej67Pq08SlpHGSju2kfY6k1/TlNRe1ek/zJE3r71giIgaE1lY4//z+jiIiIiIiolsGQkXXFrbvk7Qt0Hi7noCVgLlN/V5n+z+LPbp2SNoTOL0eLgusCDzVaLc9tD/i6mud3YekzYEfAFtSfl/3A0fZ/n07fccAV9P0jIDP2j6ntn+X8qbFVSlvhPyZ7XaTn5LeBZwCrA8sAP4GHGz7vzXmvSWNA8b35F4jYoBoaRnYu2ouiVIhFxEREREDyBJd0dXM9jW2h9bkyub19PDGuSUlyQVg+7ymWHcAHmyKc1Akubrh/4CrgLWBtYBDgCc76f+SZ9RIclVnApvaXgV4OzBW0oc6mOdu4H9sDwdGAP8CfrKQ9xIRERERERERA8BAqOjqkqQRwE+BbYDHgRNsn1HbjqYkxp4GdgEmAx+uny/U8/vavrL23wf4CrAe8Gid6/Ta9lXgg8A2tp+TdBBwMPAW2/O7GethwKcpyZ+pwBG2L+mg7/eAtwHvr/d2LPBaYBZwpu2j2wzZU9K3KNVuP2hUPUl6K/BDYDNgHvBr4Iu2n5Ek4CRgT0rl2RRgrO0765yrSboceAcliTTW9v11XgMb276vTdxrAq8GzrD9TD19XXeeT3tsT2pz6nlgow76Ptzm1IKO+nZp0qTBUcmQvXUiIiIiIiJiKTFgKrq6cAEwjVLBsxtwvKTtmtp3Bs4FVgNuA/5Iufd1gW/y4jJDgEeAnYBVgH2AH0h6c237HvAMcKSkjYHjgY93N8lV3Q9sS1mGdwwwXtKrmjtIWkbSGcAbge1tz6Is0/wEMJyS+DpI0q5t5t4GGAVsB3xd0mb1/AJKUm9NSuJsO+AztW17ShJrkzr3R4HHmubco8a5GnAf0J390h6rfcdL2lXS2t0Ys5akhyX9W9IPJK3c3CjpMElzKL/nlYEON4yRtIGkmZSk3peA73bj+oNT9taJiIiIiIiIpciAr+iStD4lwbNTTTi1Svo5sBfw59rtGtt/rP0vBj4EfMf2AkkXAj+TNNz2TNuXN03/V0lXUhJTt9p+XtIngFspCaHv2r6tJ/Havrjp8CJJXwPeClxazy1PSdwtB+zcqIiyPaFp3B2SLgDeCfy26fwxtucBt0u6HdgCuMf2LU19Jks6vY49GXgWGAZsCtxk+542If/G9k0Aks6jVH91dY+ue2UdBpwIvLpusr+v7X+1M+SfQEv9uSFwTr3OAU1zfkfSCbXfrpSqto6u/x9guKTVKdVz/+wq5naNGjXw9/oZDBVpEREREREREd00GCq6RgCP257ddG4KpVqroXk52zxghu0FTccAQwEk7SDpRkmP16qgHSmVUADYngz8BRgJ/KinwUr6hKRWSTPr/K9vnp+yzG4XStLqmaZxW0n6i6RHJc0CDmwzDmB60/enmu5pE0mXSZou6UlKJdqa9X6uBk6r9/KwpJ9JWqWrObtie5rtg22/lpK8mgv8ooO+023fbft52/+mLB3drZ1+ronFeZQqs65ieJySNLu0r99IGRERERERERFLnsGQ6HoQWF3SsKZzGwD/7elEklak7F/1fWDtuqH57ylvDWz02ZGy/O/PlKWMPZl/Q+AMyr5ea9T572yeH7iHsmTyCkmjms6fD/wOWN/2qpQ9yZrHdeYnlKqmjeuG7oc3j7V9iu23UPYy2wT4ck/uqyu2p1ISaa/v7hA6v7flKHuVdcdylP3QVumqY0REREREREQMbAM+0VWTKNcD35Y0RNIbgX2B83ox3QqUDdkfBZ6TtANlDyvghU3WzwT2Az4J7FwTX921MiWJ82idbx/aSf7YvoCSjPqTpEZCZxilcm1+3Vx+bA+uO4zyxsM5kjYFDmq6py1rtdjylKqr+ZQ9vXpN0mqSjpG0Ud1vbE3gU8CNHfQfU/fVUl2K+h3qUs46/oA6p+q9f5YXl6W2netDkkbVca+kLIG8rVZ3RURERERERMQgNuATXdUelKWEDwKXAN+wfVVPJ6nLHw8Bfgk8QUkm/a6py8+AS23/3vZjlITazyWt0c3576bsWXUDZTnlG+jgbYS2z6FslH+1pJGUzeO/KWk28PUaY3d9qd7LbEpF2UVNbavUc09Qlnw+RqloWxjPUH4ff6Ik2O6kvN1y7w76v5nyTOZSkpZ3Un4PDR+kbOI/GxgPnFo/AEiaI2nbergu8Ifa9x+UNzR+cCHvJyIiIiIiIiIGANnu7xg6JGk+JUFyiu2j+jueGPgknQnsDjxie6PO+o4ePdoTJ05cPIEtKmPGlDcvtrT0dyQvNXYs7L9/f0cRg03j5QsD/SUSS5o814iIpUr+tR8x+A2Gv3NJt9ge3V7bEr1Bt+0h/R1DDC6296VU4kV/aW0tP5PoioiIiIiIiD62RCe6IqIPtLQsWan6xv99EBEREREREdHHBsseXS8jyZLmSjquj+abIGm/vpgr+o+kqyXNl3Rtf8cSEREREREREX1r0Ca6qi1sH9E4qMmvTvdlWhQk7Svpn5JmS3pY0uWShi3uOBYnSdtIul7SLEmPS7pO0pYd9N1b0oK6qXzjM6apfbOaoJol6T5JHW4uX9/MeKyk/9b+EyRt3mi3/W7gwL6814iIiIiIiIhYMgz2RFe/k/RO4HhgD9vDgM3o2RsTlwiSur3MVdIqwGWUNyOuTnkT4jGUFwt05AbbQ5s+E5que2mdb3Vgf2C8pE06mGd34FPAtrX/DcC53Y09IiIiIiIiIgaupTbRJemtkm6QNFPSQ5JOk7RCU/t7axXWLEmnAWoz/lOS7pH0hKQ/Stqwg0ttSUni3AZg+3Hb59ieXed5yZLIWt10bdOxJX1G0r9qRdi3JL22xv6kpF824pY0RtI0SV+R9Ei9r10l7Sjp3lpZdXjT3MtIOkzS/ZIeq3OtXttG1mvvK+k/wNWShkgaX/vOlHSzpLXbuedN6r1eYHuB7Xm2r7R9R49+ScWmwAjgB3Wuq4HrgL066P9q4FrbD9heAIwHXteL60ZERERERETEALM0b0a/APgCMBFYD7gC+AxwsqQ1gV9TKoMuBQ6mLHc7F0DSrsDhwM7Av4DDgAuAt7dznb8D35J0DHAlMNF2Z5VN7Xkf8BZgfeDWep09gccoFUt7AOfUvusAQyhVVHsDZwBX1fEbALdIutD2A8AhwK7AO4FHgVOAH9X5Gt5JqUJ7HvgksGqN42mgBZjXTrz3AgsknQNcCNxo+4ku7vFNkmYAj1Oe87dtP0ebBGMl4PUdzHMh8NFa8fXvGvMfurh2+yZNGvgbp7e2ls3oIyIiIiIiIpYCS21Fl+1bbN9o+znbk4HTKUkdgB2Bu23/yvazwMnA9KbhB1ASMffUZMzxQEt7VV22rwE+BLwZuBx4TNJJkpbtQbgn2H7S9l3AncCVtWJpFiVB96amvs8Cx9W4LwTWBH5oe3Ydfxfwxqb7OML2tJp8OxrYrc0yxaNtz7U9r869BrBRra66xfaT7dzzk8A2gCmJtkcl/a6D6i+Av1ESV2sBH6Yk2r5c2/4JPAJ8WdLykran/J5W6mCuh4BrgEmUJNzulITm0qmlBcaO7e8oIiIiIiIiIhaLpbaiq1b8nASMpiRNlgNuqc0jgKmNvrYtaWrT8A2BH0o6sXlKShXVlLbXsn0FcIWkZYB3ARdTEjGndzPch5u+z2vneJ2m48fqkr1GW3vjhzbdxyWSnm9qXwA0J6Sa7/tcSjXXhZKGU5YFHlGTai9h+x5KRRmSNq19T+al1WKNvg80Hf5D0jcpia5v2362VtCdCnyVUoH3Szre7+sblOWi61OSkx+nLLvc3PZTHYxp36hRMGFCj4ZERERERERERP9ZahNdwE+A2yibxM+W9Hlgt9r2ECVRApQ3+TUfU5I/x9k+rycXtP088GdJV/Pi0ru5vLQ6aZ2XDVx0pgKfsn1d2wZJI+tXN87VhNYxwDG1/feUhN2ZnV3E9j8ljaNUkHWHaVqyWPf2alTbIel6Xlyq2dYWwEW2p9XjcZJOpuzTNbGb149FrbV14C8LjSVPlupGRERERCz1ltqli8Aw4ElgTq04Oqip7XJgc0kfqsv4DuGlCaifAl+TtDmApFUl7d7eRSTtIuljklZT8VZK0ubG2qUV+JCklSRtBOzblzfZhZ8CxzWWXEp6paRdOuos6V2S3lCXXT5JWcq4oJ1+m0o6VNJ69Xh9SiXXjW371vYdGssa6+/iKMreaI32N9aN8FeS9CXgVcC4DsK8Gdhd0tp1s/29gOWB+zp9EhEx8GWpbkRERETEUm9prOhqVCh9CfgZ8BVKZddFwLsBbM+oiatTgLMpS/ZeqHqyfYmkoZQlfBsCsygbvl/czvWeoCTKTgNWpFSLfa+pGuwHlKV2DwN3AOcB7+mrm+3CDymVU1dKGkHZC+simpJMbaxDSY6tB8ypfce30282sBXwxbrEcSZwGS/uu9XWdpTKq6GU5zCesu9Zw17AfpSE1TXAexsb+kvaALgbeJ3t/wAnUPb6agVWpiS4Pmx7ZqdPIhavlpYsC42IiIiIiIg+J9td9xqAJM2n7ON0iu2jJK1CSUitlqTH0kvSVcDWwE22t+us7+jRoz1xYlY79rnGksUkuiIGhvzNRkQsVfKv/YjBbzD8nUu6xfbo9toGbUWX7SFtTn0UuD9JrqWb7ff2dwwRERERERERsWgM2kRXs7p5+XDK8reIiIiIiIiIiBiElopEl+2393cMERERERERERGxaA2Kty5KsqS5ko5byHnGSTq2ft9W0qS+iTCWFJKuljRf0rX9HUtERERERERE9K1BkeiqtrB9BICkkTX5Nafpc3tPJrN9je1RiyJQFYdIurMm6KZJuljSGxbF9fqDpG0kXS9plqTHJV0nacsO+u4taUGb39eYpvYJNTnVaOswASnpk5JukfRkfa7flfRC5aLtdwMH9uW9RkRERERERMSSYTAlutoz3PbQ+tmiv4Np8kPgc8AhwOrAJsBvgff3dKLmJE5n5xan+obLy4BTKfe3LnAM5S2YHbmh6Xc11PaENu0HN7V1loBcCfg8sCawFbAd8KVe3kpEREREREREDCBLxR5dzSRtSknAvAV4FDjK9i/b6TcGGG97vXo8GTgd2At4FSUxdZDt+bV9J+BYYCRwN3Cg7TvamXdj4LPA22zf1NR0XlOf99e5XgvMAs60fXRtGwn8m7Kx/jeAyZLOAj4N3AR8EvixpLOBM4AtAAN/BD7beOukpK9SEm2rAA8Cn7H9Z0nLAl8F9gXWAu4FdrU9VdLbKUm6Ter5z9m+vp3HvAmA7Qvq8Tzgynb69TnbP2k6/K+k84B39WqySZNefO9q9J3WVmhp6e8oIiIiIiIiYhAa7BVdLyFpZeAq4HxKEmcPSlJo825OsSfwP5QE1CbAkXXeNwNnAQcAa1ASYr+TtGI7c2wHTGuT5GprLvAJypsi3w8cJGnXNn3eCWxW44FSvfRAva/jAAHfBkbUfusDR9d4RwEHA1vaHlbnmFzn+SLluexISYJ9CnhK0urA5cAp9R5PAi6XtEY78d8LLJB0jqQdJK3Wyb02vEnSDEn3Sjqqnaq0b9f265qXNXbDO4C7etA/FrWWFhg7tr+jiIiIiIiIiEFosFd0zZDU+H4sMBWYbPvseu5WSb8GdqN7yZDTbE8FqBvfn0pJdn0aON3232u/cyQdDmwN/LXNHGsAD3V2kTbL9u6QdAElsfXbpvNH255bYwF40Papte054L76AXhU0kmUCjCABcCKwOskPWp7ctO8+wFfsd3YB+v2eo29gH/ZPreev0DSIcDOwLg28T8paRtKZdgZwDqSfg982vbD7dzy34DXA1OAzYGL6j18u7Z/lVIl9wzwMeD/JLXYvr+duV4gaR9gdL2nnhs1CiZM6NXQiIiIiIiIiFj8BntF15q2h9fP94ENga0kzWx8KFVa63RzvqlN36dQqqWo8x7aZt71m9qbPUZZ+tghSVtJ+oukRyXNomyevmYnsbzsWNJaki6U9F9JTwLjG3PYvo+yj9XRwCO1XyPW9YH2Ekgj6j03m0LZf+tlbN9je++69PP1dfzJHfR9wPa/bT9v+x/ANynJx0b7323Ptv207XOA6ygVZx2qFXDfAXawPaOzvhERERERERExOAz2iq62pgJ/tf3eXo5fv+n7BpS9rRrzHmf7uG7M8WfgR5JG257YQZ/zgdMoSZr5kk7m5Ykud3H87XrujbYfq4mf017obJ8PnF83jj8dOIGy/9hUytLMO9vM9yAloddsA+APHdzDi4HZ/5Q0jrK0sztMWXrZq3ZJ76NUkr2/Js4iImJhtLYu2j0Lx46F/fdfdPNHRERExFJjsFd0tXUZsImkvSQtXz9bStqsm+M/K2m9ul/V4ZQldlCSKgfWSixJWlnS+yUNazuB7X8BP6Ys/RsjaQVJQyR9TNJhtdsw4PGa5Hor0JsNjYYBc4CZktYFvtxokDRK0rvrHmLzKZvFL6jNPwe+Jen/s3fnYXJV1frHvy+DIiRMxoE5CBIQJH01ivdekHhRFGVSBDUggwJX/OFVwQHlhkEBQUUFUXFmCggIKIIoCEYmGQK3QQNEmcMQJISEJBDG9/fH3gVFUdXpDkk63f1+nqeernPOPvusU9WNT5Zrr/PGei+b1j5cv6d8duMkLSPpI8CbKJ/pi0jaUNKBkhqN/Nei9P26pl2gtY/X6xrnAuOB39btlSW9t35Gy0jaldJ3648d5vovSmP/nebTBy0iIpYE3d1w+un9HUVEREREDBJDqqLL9mxJW1MaqX+Hkui7idKAvTdOpzw9cHVKIuaIOu8kSftQKqbeSEkcXUnpPdXO/9TXD4B1gUfr+K/V458GjpV0AqXH11mUxvR9cThwCuWpjbcDpwKfr8deSVnWtxHwNHA10Pi/0r9Tj19MqSK7Dfig7fvqkyWPA35U59y2w7LA2ZTm+AdIWhmYSUmIfbHNWCgN+k+SNAx4iLLM8qh6bFnK57whJRl3G+UpkFMAJK1N6d/1Jtv3UpJkKwG/b+rPdoXtbebzeUVERCddXYuuZ2GebhsRERERC5Hs1hVvA4+kecCTwPG2xy+ia9wN7G37T4ti/lg8JF1CeUjAdba36mnsmDFjPGlSp9WlERFDRCMRtagTXXn4R0TEEiH/WY4Y/AbD37mkG2yPaXdsUFR02V6uv2OIgeFl9GeLiIiIiIiIiCXcUOvRFRERERERERERg9SgqOhaHGyP7O8YIiIiIiIiIiKis1R0RURERERERETEoDBkEl2SLGmupCN7OX5XSRe3nL9+fX+SpCPq+y0kTVk0US88AyXORU3SHZKeknRaf8cSEREREREREQvXkEl0VaNtHwwgaWRNXi1TtyXp+5Juk7SG7Qm2t57fhLavsD1qUQQraXNJV0uaJWmGpKskva0e21PSlb2da1HG2Y6kHSR1S3pM0nRJl0oa2WHsRZLmNL2ekvS3NuO2rN/ZET1cV5KOkfRIfX1TkhrHba8HHLUQbjEiIiIiIiIiljDp0UVJjgA/Bv4d2NL2Q/0cEpJWBC4A9gPOAl4BbAE82Z9xtZK0jO1nWvatD5wCfAi4DBgGbA08124O29u0nD+xnte8b1ngOODa+YS0L7AjMBowcAlwJ3Bir26o2ZQpLzx3NWJJM24c7Ltvf0cRERERERGxRBlqFV3tLA2cBIwBxjaSXL2tmJI0VtJ9TdsH1eVxsyXdIumDTcf2lHSlpG9LelTSXZK2aT8zGwDYPsP2s7afsH2x7ZslbURJ3Px7rYCaWed/ZZ37XkkPSTpR0qs6xHm3pC9IurlWjJ0pabmm49vWiqyZtaps05ZzvyzpZmBuoyquSRdwl+1LXcy2fY7te3vxeY6kJPRObTl0IHAxcNt8ptgDONb2fbbvB44F9pzfdSMGlO5uOP30/o4iIiIiIiJiiZOKLpgArAX8l+2ZC2G+OyiJmmnAzsBpkta3/WA9vhlwMjCCUn3087pU0i3z/AN4VtLJwK+Aa2w/CmD7VkmfAva2vXnTOccAb6Akmp4GTgcOAb7SIdZdgPcB84CrKAmhEyW9BfgFsB0wCdgNOF/SKNuNirKPAR8AprdWdAE3AhtK+i5wPnC97Tk9fWhNdgeusH1X9/XjJgAAIABJREFUY4ekdYBPAG8BTpjP+RsDNzVt31T39d2oUTBx4gKdGrFIpdIwIiIiIiKirVR0lSV1Zy2kJBe2z7b9gO3nbJ8J/BN4e9OQe2z/1PazlITXasDr2szzGLA5ZfndT4GHJZ0v6SVj4fnll/sAn7c9w/ZsSi+qj/YQ7vE11hnA7ygJMuo8P7Z9ba0mO5myZPIdLedOtf1Em9jvBMYCa1CWXU6vDfyH9RBLw+6UCrsXxQmM72WybBgwq2l7FjCsuU9XRERERERERAxOSXTBtsChkj6xMCaTtHvTkr+ZwCaU6q2GaY03th+vb9smgGzfantP22vWeVYHvtfh0q8BlgduaLr2H+r+TqY1vX+8KY51gAMb89S51qrXb5jaw7zYvsb2LrZfQ6lweydwcE/nSNoceD3w66Z92wHDa9KwN+YAKzZtrwjMaVMxFxERERERERGDTJYuwtWUJXoXSJpne4Eb39Qldj8FtgL+avtZSd3Ay64msn2bpJOA/27sahkyHXgC2Lj2pno5pgJH2j6yp5B6O5nt6yWdS0nW9WQP4NyWyq2tgDGSGkm5lShLOt9se4c2c0ymNKK/rm6PrvsiIiIiIiIiYpBLRRdg+y+UJwT+RNKHX8ZUK1ASQA8DSNqL+Sd32pK0oaQDJa1Zt9ei9MW6pg55CFhT0ivqPTxHSbJ9V9Jr6zlrSHrvAlz+p8CnJG2mYgVJH5A0vJexby5pn6Y4NgS2b4q93TmvovQ0O6nl0HhKY/6u+jq/xrdXh6lOAQ6o9746pYl965wRERERERERMQiloquyfYmkjwBnSnpyvie0n+MWSccCfwWeoyRdrlrAkGZTGtcfIGllYCZwAfDFevwySqXSNEnP2R4BfJnSfP4aSSOA+4EfAX/s431MkrQPpfH7GymVYlcCl/dyipmUxNYRklagVJudCXyzh3N2pPTT+nNLLLMpnwUAkp4A5ta+YkjaArjIdmPZ5Y8pDfn/Vrd/VvdFDC7d3QOnKf24cbDvvv0dRUREREREDAEaKq2LJM2jNFQ/3vb4/o4n+oekKdQm+bZ77Ms2ZswYT5o0afEEFtEXY8eWRFdX13yH9rtGnHmC6cDVSKguqu9wUc8fERF9kv8sRwx+g+HvXNINtse0OzZkKrpsL9ffMUT/sz2qv2OIWCgGSvJooFSdRURERETEoJAeXRERERERERERMSgM6USXJEuaK6mnpwsurGvtKenKRX2dxUXSWEn39XccfSXpDklPSTqtv2OJiIiIiIiIiIVrSCe6qtG2DwaQNLImv25sHiBpRE2O3L04ApJ0mKSnJc2ur39IOkHSaovj+guDpB0kdUt6TNJ0SZdKGtlhbON+5zS93tBm3Jb1+zmih+u+UtKJkh6SNEPS7ySt0Thuez3gqIVwixERERERERGxhEmiq70VJG3StD0OuGtBJ5O0IL3QzrQ9HFgV+CDweuCGBU12SVp6Qc5bwGutT3ni5IHASsC6wA8pT6Ls5Ezbw5ped7bMuSxwHHDtfC7/WeDfgU2B1SlPgPz+At1IRERERERERAwoQ6YZfR+dCuwBfLFu705J3OzTGCDpoLr9WmAqcLDt8+qxPeux6+o8PwRub76ApG9REjIfsD2rUyC2nwYmS/oIcCMlefSFeo29bW/eNKeBN9q+XdJJwBPAOsCWwA6SXgkcAawHzAJ+bvuweu5ISjJvT+DrwPLAd20fWY+/CvgRsAPwIPDLHj6/LuAu25fW7dnAOT2M740DgYspn3dP1gX+aPshAEm/Ar6zQFecMiWNtGPJNFCeuBgREREREbGYpaKrvdOAj0paWtJGwHBeWkl0B7AFpWLpcOC0lmqrzYA7KYmZ53uASVpK0k8pFUdb95Tkamb7WeC39Zq9Na5eezhwJTCXkrRbGfgAsJ+kHVvO2RwYBWwFHFLvH+BQSoJsPeC9lAReJzcCG0r6rqR3SRrWi1i3q0sNJ0var/mApHWATwBf68U8Pwf+U9LqkpYHdgUu6sV5EQNHVxeMG9ffUURERERERCxxUtHV3n3AFODdwLso1VwvYvvsps0zJX0FeDslGQXwgO3GkrlnJAEsC5xB+dy3s/1UH+N6gLKUsbd+a/uq+n4eMLHp2M2SzqBUe/2maf/htp8AbpJ0EzAauBXYBfi07RnADEnHA4e0u6jtOyWNBQ4AzgKG18qq/W3PaXPKWcBPgIcoCcJzJM20fUY9fjww3vac+jn25B/AvcD9wLPA34D953dSW6NGwcSJC3RqRERERERERCx+qejq7BTKMr6PUSq8XkTS7rXZ+kxJM4FNgBFNQ6a2mXN9ytK/wxcgyQWwBjCjD+NfFIOkzST9WdLDkmYBn+LFMQNMa3r/ONCoxlq9Zb57erqw7Wts72L7NZQqtHcCB3cYe4vtB2w/a/tqSi+uD9eYtwOG2z6zp+s1+RGwHPBqYAXgXFLRFRERERERETEkJNHV2TmU5X132n5RUqcupfsppVLo1bZXBv4ONJcbuc2ctwJ7ARdJGtWXYCQtBWwHXFF3zaX00Wocf32b01pjOB04H1jL9krAiS0x9+RBYK2m7bV7eR62r6cknDaZ39jGKU1xbQWMkTRN0jTgI8DnJP22w7mjgZNsz7D9JKUR/dsltSb0IiIiIiIiImKQSaKrA9tzgf8C9m5zeAVKMuZhAEl70cskTl2O91XgT5LWm994ScvWPllnUJ682GisfhOwsaQuScsBh/Xi8sOBGbbnSXo7pYdXb50FfEXSKpLWBD7TQ8ybS9pH0mvr9obA9sA1HcbvUOdVjet/eGEJ6HhgA0qD+y5Kou6nlIRhO9cDu0taqT6p8dOUZaTT+3CvERERERERETEAJdHVA9uTbN/RZv8twLHAXyl9pd4MXNU6rod5T6Y0Vr+sPu2wnY9ImgPMpCR3HgHeavuBOsc/6hx/Av5JaTY/P58GviZpNqW/1lm9jZnScP8eypMZL6Y8mbKTmZTE1t/qPfwBOA/4ZofxH6U8lXI2ZcnoMfUzwvZs29MaL8qTJOfWXmFI2qJeo+ELlH5k/6QkIt8PfLAP9xkRERERERERA5TsdivshgZJ84AngeNtj+/veGLRkzSF0uvsLNuf6GnsmDFjPGnSpMUTWMRgNXZs+ZkHOwxci/o7zO9IRMQSJf9Zjhj8BsPfuaQbbI9pd2xIP3XR9nL9HUMsXrb71BstIiIiIiIiIgaOLF2MiIiIiIiIiIhBYdAnuiRZ0lxJR/Z3LANR/fzW7+84FhZJh9ffB0sa0hWNEREREREREYPNoE90VaNtHwwgaWRNcsypr7slHbS4A5K0p6Qrm7ZXlHSVpHPq0wIHNElr1nuZLmmWpL9J2rPD2F2bvo85kh6v39FbW8a9QtJtku7r4brvkHSJpBmSHpZ0tqTVGsdtHwpsvLDuMyIiIiIiIiKWHEO5omVl289IGgP8pTYyu6Q/ApG0CvBHypMHd7f9TH/EsZCdCtwErENp+P9m4PXtBtqeAExobNeE2HjgxpahXwT+BQzr4bqrAD+hfJ7PACcAvwTetwD3EBELQ3f3Cx0vY+Dp7oaurv6OIiIiIiKiV4ZKRVdHticBk4EuSa+v1USvbhyX9NZaGbSspPUkXSbpkVqpNEHSyk1j75b0BUk31yqmMyX12PBe0gjgshrDbo0kl6RtJXVLminpakmb9uY6ksZKuk/SgZL+JelBSXs1nftKSd+WdK+khySdKOlVTce/WM95QNInmva/rY5fpmnfTpK6O9za24CTbM+1/Yzt/7N90Xy+joY9gFPc9EhQSesCuwHf6OlE2xfZPtv2Y7YfpyS6/rOX142IiFZdXTBuXH9HERERERHRK0O5ogsoS92ATYBv2J4maSKwC/CjOmQ34Fe2n5YkSqLlcmBF4BzgMOBzTVPuQqkemgdcBewJnNjh8qsCfwGuAPZrJHYkvQX4BbAdMKnGcL6kUbaf7MV1Xg+sBKwBvAf4taTf2H4UOAZ4A9AFPA2cDhwCfEXS+4AvAFsBdwE/bQRq+3pJj9T5Ggmr3SiVW+1cA/xA0veBq23f22Hci0haB3gn8ImWQ98Hvgo80Zt5mryTkkTsuylTUoWypBg3Dvbdt7+jiAXV1TWwn10cEREREREDxlCu6Jou6Qngr8APgd/U/SdTEjhIWhr4GDWZY/t225fYftL2w8B3gC1b5j3e9gO2ZwC/oySUOlkL2AD4ZXP1ErAP8GPb19p+1vbJlOV/7+jldZ4Gvmb7adu/B+YAo2qibh/g87Zn2J4NHAV8tJ63S43l77bnUpJ4zZo/m1WB91ISZe3sTEngjQfuqtVpb+vhs2jYHbjC9l2NHZI+CCxj+7xenP+8WgV3CGXJYwxU3d1weqdfs4iIiIiIiIgXDOWKrhGAKdVYHwOWBZ4CfgucKOkNlCTULNvXAUh6LXA8sAUwnJIofLRl3mlN7x8HVu8hhpuAs4GLJG1l+//q/nWAPSR9pmnsK1rm6uk6j7T0+Xqc0tfqNcDywA0l5wWAgKXr+9WBG5rOu6cl3tOAWyUNoyTFrrD9YLsbq9VjBwEH1eWZ3wZ+I2nNlqReq90pybcSnLQC8E3g/T2c8xL1SZEXAZ+1fUVfzn3eqFGpQlkSpKouIiIiIiIiemkoV3RRq6WOpSz/+3TdNw84C9gV+DgvXpr3DUpybFPbK1Kqm8TLYPs44GjgEkmb1N1TgSNtr9z0Wt72GS/nWsB0ytK/jZvmXcl2o7n7g5Qqs4a1W2K9n1IB90Fe+tl0ZHs6JdG1OmW5ZluS/rOO+XXT7jcCI4ErJE0DzgVWkzRN0sgO86wD/An4uu1exRgRERERERERA9+QTnQ1ORr4UlPj+FMoPa+2p1QxNQynLAOcKWkNFtKSONvfBI4D/iRpFKU31qckbaZiBUkfkDT8ZV7nuTr3d2t1GpLWkPTeOuQsYE9Jb5K0PHBom2lOAb5EeYpix6WEko6RtImkZWrc+wG3236khxD3AM6pSyob/k5JvnXV197AQ/X91DbXXYPS3P8Htjv1RouIiIiIiIiIQSiJruJCyhLEfQBsXwU8B9xo++6mcYcDbwFm1XPOXVgB2P468DPg0qZYTqjvb6ck3haGL9f5rpH0GKXyaVSN4SLge5RE0e31Z6vzKEsrz6t9vDpZvo6dCdxZz9m+0+CaZNyF0gfsefWJjdMaL2AG8FzdfraeO1nSrvWUvSnN9g+VNKfx6iHOiIiIiIiIiBgk1HO7pIFP0jxKI/fjbY/vw3mXAafb/tkiC26AknQH8N+2/9TfsfSVpEOBA4BXAis0kmXtjBkzxpMmTVpssUUHjR5d6Zc2MOX7i/nJ70hExBIl/1mOGPwGw9+5pBtsj2l3bNA3o7e93PxHvVh9OuBbgB0WfkQDm6SdKH3K2lV7LfFsH06pzIuBpLu7f5vSjxsH++7bf9ePiIiIiIiIXhn0ia6+knQysCPlaX2z5zd+KJE0EXgT8PHa7yti8OvuLj+T6IqIiIiIiFjiJdHVwvYe/R3Dksr22P6OIYaorq7+q6vtz0qyiIiIiIiI6JM0o4+IiIiIiIiIiEFhQCa6JFnSXElH9ncsPZF0mKTT+juORUXSREl793ccfSHpk/VJjJa0fn/HExERERERERELz4BMdFWjbR8MIGlkTVzMaXrd1N8BvhxNybw5kh6RdKmkj/R3XL0laWVJv5A0TdJsSf+Q9OUOY7do+e4aiaid2oy9rB7ruOy25bObI+n5J2fa/rntYQvnLiMiIiIiIiJiSTLYenStbPuZBT1Z0tK2n12YAb1Mo23fLmkEsA1wgqQN65MD+0TSMi/ns1kA3wVWADYCZgEbAJu0G2j7CuD55JOkscDvgD80j5O0K73/nR1t+/Y+R91sypT0Z1oSdHeXHl0RERERERER8zGQK7p6RdKGki6RNEPSFEm7NB07SdKPJP1e0lzgXZLulvQFSTdLmiXpTEnL1fGrSLpA0sOSHq3v12yab11Jf6kVTJcAI1pi2V7SZEkz67K/jXpzD7an2z4V2A/4iqRX1/nulvTupvmfXyrZVOX2SUn3ApfV/WfXKqtZki6XtHHL5/EDSRfWe7hW0npNx98j6bZ67gmAegj7bcDpth+1/Zzt22z/ujf3C+wB/Nr23KZrrwQcCnypl3PEYNHVBePG9XcUERERERERMQAMtoquF5G0AnAJcAilImpT4GJJk21PrsPGAe8HtgVeUfftArwPmAdcBewJnEhJDP6yHl8a+AVwArBjPe904K/A1sBmwIXAb2ssGwBn1LETgc8Dv5P0JttP9fKWfkv5zt4OXNTLc7akVFU9V7cvAj4BPAUcA0wAmstlPka59xuBk4EjgY/WqrJz6rm/BfYHPgWc2uG61wBHSloFuNL2P3sTrKTlgQ8D27UcOgr4ETCtN/MAl0taCrgaOMD23b087wWjRvXfk/4iIiIiIiIios8GW0XX9FotNVPSFyjJq7tt/9L2M7ZvpCRrPtx0zm9tX1WrjubVfcfbfsD2DMoSui4A24/YPsf247ZnU5JAWwJIWptSxTTe9pO2L6/nNnwEuND2JbafBr4NvAr4j97eXD1vOrBqHz6Tw2zPtf1EneMXtmfbfhI4DBhdq6UazrV9XV3m2JwEez9wi+1f1zi+R89Jp8/U8/cHbpF0u6RtehHvTvUe/9LYIWkM8J/A93txPpTvZCSwIfAAcEFPPb0iIiIiIiIiYnAYbP/4H9Hch0rSl4DNJM1sGrMML65CmtpmnuYEzuPA6nW+5Sm9p94HrFKPD5e0dB3zaPNyO+AeYK36fvW6DYDt5yRNBdbo7c1JWhZ4DTCjt+fQdH81ziOBnes8jSqvEZQ+WvDSe2/0zlq9eS7brvG3VRNrRwFHSVoROAg4W9LaNYHYyR7AKbZdY14K+CHwWdvPSD2tlnz+2pfXt09J+izwGKWq7W/zPTmine7u9GtbUOmxFhERERERi9FgS3S1mgr8xfZ7ehjjPsx3IDAK2Mz2NEldwP9RelU9CKwiaYWmZNfaTfM/ALy5MZFKxmYt4P4+XH8H4Bnguro9F1i+6fjr25zTfH/j6hzvBu4GVgIepedeWw0P8kLSrjn++bL9mKSjgK8A69IhUSdpLWAs8N9Nu1cExgBn1iTX0nX/fZJ2ro3s5xsCvbvHiFjY0mMteiPJ5MFl3DjYd9/+jiIiIiKGqMGe6LoAOFrSx4Ff1X1dwBzbty7AfMOBJ4CZklalNEcHwPY9kiYBh0v6KqWP1nbA+XXIWcBBkrYCLgc+CzxJ6SHVo3qtbYDvAMfYfqQe6qb0z7oIGE1ZkvmH9rM8H/+TwCOUBNlRvbnp6kLKUx8/VO/p/9E+sdaIeXyN5SbKEtnPAjOBKT1c4+PA1bbvaNo3i1pRV61FSfS9FXi4zXU3BpalVG+9CjiCkkxckO87oujqSr+2iIje6O4uP5PoioiIiH4yqBNdtmdL2pqSIPoOJeFyE3DAAk75PUrD+emUCq1jeaERPZSKqZMpFUt/BU4BVq6xTJG0G6XP1BqUJNV282lEf5MkUxrH3wR83vbpTcfHUxrcP0rpaXU6PffvOgV4LyXxM6Oev99877rEP13SzsDxlIb8p1Ia9Xc8pY5bm1KFdjPwAdtzejhnd+BbLdc1TcspG0/ABB5qLFOtib4rbB8FvI7StH5NSsXb1cC2ta9YREQsiZJMHjxSmRcRERH9TLUV0oAiaR6lMul42+P7O54YOCTtRemzthzwJtt3dho7ZswYT5o0abHFFkuoxj/a8o/wiEUjf2ODS77PiAEvf8YRg99g+DuXdIPtMe2ODciKLtvLzX9UxEvZ/iWl0iwiIiIiIiIiBpml+juAiIiIiIiIiIiIhWHQJrokWdJcSUcuhLnWljRH0tLzHx1LMkknSXpC0n39HUtERERERERELFyDNtFVjbZ9MICkkTX5tUzdlqTvS7pN0ho9TWL7XtvDbD9bz50oae+XE5ikcZIm1QTag5IukrT5y5lzSSJpY0kXS3pU0kxJN0h6f4exX62fQ+P1hKTnJI2ox0+S9FTLmI5Jx/rZ3lMTnb+pT60EwPaelCdYRkRERERERMQgM9gTXW1JEvBjYCywpe37F/P1D6A8wbHxlMC1gR8COyzAXC/ps9ZuXz/4HXAJ5f5eC/wP8Fi7gbaPqonEYbaHAccAE21Pbxr2zeYxjaRjK0kbU77bj9drP075bCMiIiIiIiJikFsSEiKL29LAz4E3A2NtPwIg6QPAEcB6wCzg57YPq8dGAncBywKHA1sA75D0PeAk2/tL+g/gOGAD4B/AZ21f3XpxSSsBXwP2sn1u06Hf1ReS3l7n2gh4AjgHOMD2U/W4gf2BzwHL1CcJngZ8H/g8cImk/wFOBTajfM9XAZ+yfV+dY0/gEOA1wHTgf21PqMf2AQ4A1gSmArvZvlHSRsCPgC7gfuArts9vc48jgHWBnzZirtefr5qE/Hj9jBbErsDvbF9e5xsP3CppuO3ZfZppypQ8Jj2guxu6uvo7ioiIiIiIiOiFoVjRNQHYEPivRpKrmgvsDqwMfADYT9KOrSfXpZBXAPvXyqL969K4C4HjgVcD3wEulPTqNtf/d2A54LweYnyWkrAaUcdvBXy6ZcyOlCTWm+r264FVgXWAfSnf7S/r9tqUhNkJAJJWqLFuY3s48B9Adz22M3BY/SxWBLYHHpG0LCURdzGlQuszwARJo9rE/whwO3CapB0lva6He221BaUS65yW/Z+WNKMugdyph/M3Bm5qbNi+A3iKkoCM6LuuLhg3rr+jiIiIiIiIiF4YihVdWwOH257ZvNP2xKbNmyWdAWwJ/KYXc34A+KftU+v2GbWiajvgpJaxrwam236m02S2b2javFvSj2ss32va/w3bMwBKERTPAYfafrIeb1SCUcccCfy56fzngE0k3Wv7QeDBun9vyjLB6+v27fX8LYBhwNG2nwMuk3QB8DFKYqw5fkt6F3AQcCywrqQrgU/a/men+672AH5te07TvuOBAymVdlsDZ0qaZrtdldiwOq7ZLGD4fK77UqNGwcSJfT4tIiIiIiIiIvrHUKzo2hY4VNInmndK2kzSnyU9LGkW8ClKRVVvrA7c07LvHqBdk/tHgBE99dGStIGkCyRNk/QYpZdXayxTW7Yftj2vaY7lJf24NmV/DLgcWFnS0rbnAh+h3OODki6UtGE9dS3gjg73OLUmueZ3j9i+z/b+ttejVJXNBU7pdM815lcBOwMnt8x1o+1HbD9j+/eUqrwPdZhmDqUSrdmKQN+WLUZERERERETEgDMUE11XUyqtjpPUvB7pdOB8YC3bKwEnAuowh1u2H6Akc5qtTelj1eqvwDzK0sNOfgTcBrzR9orAV9vE0hpD6/aBwChgszrHO+t+Adj+o+33AKvVa/20Hp9K6VPW6gFgLUnNvzOd7vHFgdlTgR8Am8xn6IeAGcDE+U1J5+9mMjC6sSHpDcArKX3TIiIiIiIiImIQG4qJLmz/hZJU+YmkD9fdw4EZtufVZvA9NeV5CHhD0/bvgQ0kjZO0jKSPUHpnXdDm2rMoTeB/UPtXLS9pWUnbSPpmUyyPAXNqpdV+C3CbwynLF2fWHmKHNg5Iep2k7WuvricpVVCNpxj+DPiCpLeqWF/SOsC1lKqsL9V4x1IShr9qvbCkVSQdXs9dqjan/wRwzXxi3gM4xfaLknaSPixpWJ1ra2A3SlKynQnAdpK2qPf3NeDcPjeij4iIiIiIiIgBZ0gmugBsX0JZvneSpO0ozd6/Jmk2JRF1Vg+nHwd8WNKjko6vTe23pVRRPQJ8CdjW9vQO1/4O5amG/ws8TKmi2p8X+oF9gZJom02ptDpzAW7xe8CrKE9UvAb4Q9OxpWqsD1AqqLakNru3fTZwJKXCbXaNadX69MTtgW3qnD8Edrd9W5trPwWMBP5ESdj9nZJQ27NTsJLWAP6L9ssbP0upHJsJfAvYp7mnmqQ5tYcYtidTlmROAP5FSfi1NvKPiIiIiIiIiEFILcUzg4akeZTkyvG2x/d3PLFkkPRzSh+wf9lev6exY8aM8aRJkxZPYBERQ9XYseVnHv4xOOT7jBjw8mccMfgNhr9zSTfYHtPu2KB96qLt5fo7hljy2P4k8Mn+jiMiIiIiIiIiFr4hu3QxIiIiIiIiIiIGlyS6IiIiIiIiIiJiUBjQiS5JljRX0pELcc5dJV3cco22vZxqE/Q3tDu2gNe+W9K7F+C8kyQdsbDiqHOOrPfednmrpK9K+tnCvOaiJmmD+p09K2nv/o4nIiIiIiIiIhauAZ3oqkbbPhhelJyZU18PSbpA0nt6O5ntCba37uXYYbbvbN0vaXJTDM9Kmte0/dXe39qSy/ZRtjsmi2oi7K56z/dJ6vjkSEkbSbpM0ixJt0v6YMvxrSTdJulxSX+WtE4Pc60q6byaAL1H0rimmP9hexhwRR9vNyIiIiIiIiIGgMGQ6Gpn5ZrQGA1cApwnac/FdXHbG9ckWCOpsn9j2/ZRiyuO/iJpD+DjwLvrZzAGuLTD2GWA3wIXAKsC+wKnSdqgHh8BnAuMr8cnAR2TZsAPgKeA1wG7Aj+StPFCuK2IiIiIiIiIWMIN1kQXALan2T4OOAw4RtJSAJIOknSHpNmSbmmuIJK0p6Qr280naXNJUyW9q253XNbY4fz1auXSI5KmS5ogaeUOYzesFVEfrdtnS5pWq54ub5O8WUXShfWerpW0XtNcx9W4H5N0g6Qtmo69XdKkeuwhSd9pmXdXSffWeA9uOu8wSad1uNW3AX+0fQc8/z38pMPYDYHVge/aftb2ZcBVlEQZwIeAybbPtj2P8l2OlrRhm89sBWAnYLztObavBM5vmqtvpkwpz11d0NdPOt1yRERERERERCwKgzrR1eRc4LXAqLp9B7AFsBJwOKWCaLWeJpD0XuAMYCfbf17AOAR8g5LY2QhYi5K4ab3WW4CLgc/Y/lXdfRHwxnofNwITWk77WL1JjdBVAAAgAElEQVSXVYDbgea+ZdcDXZSKqNOBsyUtV48dBxxne0VgPeCslnk3p3xuWwGHSNqoF/d5DbC7pC9KGiNp6R7GqsO+Ter7jYGbGgdsz6V8f+2qtDYAnrX9j6Z9N3UYu2h1d8Pppy/2y0ZEREREREQMZW0bjQ9CD9SfqwLYPrvp2JmSvgK8nbKErp2dgU8B77f9twUNwvbtlCQUwMO1eurQlmFbAJ8EPt6cULP9i8Z7SYcBj0payfasuvtc29fV4xOA7zSd21x5dayk/6Ukr24CngbWlzTC9nRKkqrZ4bafAG6SdBNlOeit87nP0yQZ2IuSyJsn6Vu2j24z/DbgX8AXJX0XeBewJdC492HAwy3nzAKGt5lrWD3Wm7HzN2oUTJy4QKcyduyCnRcRERERERERC2yoVHStUX/OAJC0u6RuSTMlzaRUD43o4fzPAWe9nCRXve5rJf1K0v2SHgNOa3PdTwFXNye5JC0t6ei63PIx4O56qPncaU3vH6ckfRrnHyjp1rrscSalkq1x7icplVC3Sbpe0rYt8XSctye1qf+7gZXrPX2tVsW1jnsa2BH4QL3WgZSqsvvqkDnAii2nrQjMbnPZvoyNiIiIiIiIiEFmqCS6PkipGppSn9j3U2B/4NW2Vwb+TvsldA07AztK+tzLjOMbgIFN61LB3dpc91PA2rW6qWEcsAPwbkqSamTd31PMZUDpx/VlYBdglXq/sxrn2v6n7Y9RlkQeA/y69rpaKGw/XSvobuaF5YitY262vaXtV9t+L/AG4Lp6eDKliqxxPytQllhObjPVP4BlJL2xad/oDmMjIiIiIiIiYpAZ1IkuSa+TtD9leeBXbD8HrEBJNj1cx+xFhwRMkwcoPar+R9KnX0ZIwylVRzMlrQF8sc2Y2cD7gHdKOrrpvCeBR4Dlgb48uXE48AzlfpeRdAhNVU+SdpP0mvrZzKy7n+3D/C9RG/p/QNJwSUtJ2obSJ+vaDuM3lbScpOUlfQFYDTipHj4P2ETSTrWv2CHAzbZva52n9u86l1I9toKk/6QkCE99OfcTEREREREREQPDYE10zZQ0F/gb8H5g50aPK9u3AMcCfwUeAt5Mecpfj2zfS0l2fVnS3gsY1+HAWygVVRdSkjLtrjUTeA+wjaSvA6cA9wD3A7fw0j5aPfkjpZH9P+oc84CpTcffB0yWNIfSmP6j9emGL8djwFeBeynJs28C+9WnILbzceBBStXdVsB7bD8JYPthypMUjwQeBTYDPto4UdJXJV3UNNengVfVuc6o101FV0RERERERMQQINv9HcMCkzSPUul0vO3x/R1PLNnqksbrgVcAn7Z9Uk/jx4wZ40mTJi3YxcaOLU9e7OpasPMjOhk3Dvbdt7+jiFh4Gg/vWNCHf8SSJd9nxICXP+OIwW8w/J1LusH2mHbHBvRTF20v198xxMBh+5+U5vgRA1N3d/mZRFdERERERERbAzrRFbFE6+oa2CnyWPI0/q+XiIiIiIiIaGuw9ugCQJIlzZV0ZB/OmSxpbH1/mKTTFlmAsdhJOrz+TlhSEr0RERERERERg8igTnRVo20fDCBpZE1wzKmvuyUd1DzY9sa2Jy7qoCS9V9LlkmZLeljSXyRtv6ivu7hIWlPSOZKmS5ol6W+S9uxh/N6Sbq/fyx8krd50TJKOkfRIfX1TknqYaytJt0l6XNKfJa3TOGb7UMoTICMiIiIiIiJikBkKia52VrY9DPgwMF7SexbnxSV9GDib8jTFNYHXAYcA2y3AXC+pSlpCKpVOpTzdcR3g1cDulKdcvoSkLYGjgB2AVYG7KE9MbNgX2BEYDWwKbAv8d4e5RlCeZjm+zjUJOPNl301ERERERERELPGGaqILANuTgMnA84/Gq1Ve7243XtI7JF0taaakm5qWOO4s6YaWsQdK+k2bOQR8B/i67Z/ZnmX7Odt/sb1PHbOepMtq9dJ0SRMkrdw0x92SvizpZmCupPVrpdonJd0LXFbHnS1pWq2oulzSxk1zvF/SLbWi7H5JX2g6toOkbkmPSbpD0vvq/tUlnS9pRq2+2qeHj/dtwEm259p+xvb/2b6ow9jtgLNtT7b9FPB14J2S1qvH9wCOtX2f7fuBY4E9O8z1IWCy7bNtzwMOA0ZL2rCHWCMiIiIiIiJiEFgSKn/6jaR3AJsA3+jF2DWAC4GPA38AtgLOqQmU84EfS9rI9q31lN2AI9pMNQpYC/h1T5erMV0OrAicQ0nYfK5pzMeADwDTKRVhAFsCGwHP1e2LgE8ATwHHABN4Ian3c2AX21dIWgVYt97n2ymVZh8GLgVWA4bXc86gJAZXBzYELpF0p+1L29zDNcAPJH0fuNr2vfO5X7VsQ/lu7qAsNbyp6fhNdF5++KKxtudKasxxWw8xvNSUKQve/Lu7uzSjj4iIiIiIiIjFZqhWdE2X9ATwV+CHwEsqr9rYDfi97d/XCqxLKMvi3m/7ScryuN0AauXUSOCCNvO8uv58sNOFbN9u+xLbT9p+mFIBtmXLsONtT7X9RNO+w2oF1RN1nl/Ynl3jO4xS2bRSHfs08CZJK9p+1PaNdf8ngV/U6z9n+37bt0laC9gc+LLteba7gZ9REn/t7AxcQVlCeFetEHtbh7G/B3aRtKmkV1GWcRpYvh4fBsxqGj8LGNahT1fr2Mb44W3GLjpdXTBu3GK9ZERERERERMRQN1QrukZQEimfo1RGLUupeurJOsDOkpr7aC0L/Lm+Pxk4Q9L/UpI/Z9UEU6tH6s/VKL2oXkLSa4HjgS0oCZqlgEdbhk1tc+rz+yQtDRxJSTi9hheqvEZQEj87Af8LHF2XQB5k+6+UarPft5l7dWCG7dlN++4BxrS7B9uPAgcBB9W+Wd8GfiNpTdtuGXuppEMplWsrAd8FZgP31SFzKJVtDSsCc1rn6TC2MX52m7E9GzUKJk7s82kRERERERER0T+GaqIL288Cx0r6IPBp4HvzOWUqcGqjj1ab+a6R9BQlOTWuvtqZUufaiZL8aecblETcprYfkbQjcELrJduF0fR+HKW5+7uBuykJpEepywJtXw/sIGlZYH/gLEqSayqwHi/1ALCqpOFNya61gfs73MMLQdnTJX2b0mtrVV5I9jWP+QHwAwBJG1CScH+vhydTGtFfV7dH133tTK7Xoc61Qr2fTuMjBpbu7gVfUrskGzcO9t23v6OIiIiIiIgBbqguXWx2NPAlScvNZ9xpwHaS3itpaUnLSRorac2mMadQElLP2L6y3SS1CukAytMe95K0oqSlJG0u6Sd12HBKZdLM2hvsiwtwX8OBJylJpeUpTzUEQNIrJO0qaSXbTwOPAc/Wwz8H9pK0VY1rDUkb2p4KXA18o977ppRljhPaXVzSMZI2kbSMpOHAfsDttl+S5KrzbaJibeAnwHG1KgzK53pAjWV14EDgpA73fR6wiaSd6nd6CHCz7b7154qIxae7G04/vb+jiIiIiIiIQWDIVnQ1uZBS6bQP8P1Og2xPlbQD8E1KU/ZnKRVG+zUNO5XyxMCv93RB27+WNAc4uF7zCUrF0bfqkMMpyZ1ZwO113s/38b5OAd5LqbiaQemV1Rzrx4ET6hLHKdT+Yravk7QXZfngusBDwP+jNHL/GHAipbrrUeDQ2qusneUpSafV6v1dC2zfYexywOmUyqvZwC9rvA0/Bt4A/K1u/6zuA0DSZOAo2xNsPyxpJ0rC8bR63Y92uG7EwNPVNfiW1A7GCrWIiIiIiOgXgz3R9SRwg6TjbY+3fTcvfrpfo8Jq46btkU3vD2sZey0vbQrf7GFgLiXB0iPbf6A8vbHdscnAW1t2H9suxrp9Ny+9rzmUpYvNTml6/74eYjuPkqRq3X8fsG2n81rGfqY34+rYmcCmPRw38KX6and845btP1GeCvkStRfYAZTfjXbLPyMiIiIiIiJigBrUiS7b81uOuLDtB1xv+5+L+brRS7YPp1TMRURERERERMQgM6gTXYuTpLspVVU79nMoERERERERERFDUhJdC0nrcsKIiIiIiIiIiFi8BtRTFyVZ0lxJRy7Caxwmab49tgaS+oTFi/s7jiWBpMPr75AlJdEbERERERERMYgMqERXNdr2wc07JK0gaY6k3/dlIkljJd23cMNbOCTtIKlb0mOSpku6VNLIeqxPybj6NMKtF1WszSSNbJdEknSSpCN6OG8XSbdKmi3pFkk7Nh27qH6/jddTkv7Ww1xbSbpN0uOS/ixpncYx24fS9PCBiIiIiIiIiBg8BmKiq50PU56it7Wk1fo7mJdL0vqUJyQeCKwErAv8EHiuP+NqtbAqoiStQXlS5QHAisAXgdMlvRbA9ja2hzVewNXA2R3mGgGcC4wHVgUmAWcujDgjIiIiIiIiYsk2WJZu7QGcCGwD7Ap8u3GgNok/AdgdWAf4Qx2/NHAR8EpJc+rwDerPV0g6BfggcC+wh+1Jdb6NgB8BXcD9wFdsn1+PnQTMBUYC7wRuAcbZvkPSD4B5tg9siu13wKW2v9dyP13AXbYvrduzgXPqOe8DvlreakfgDtujJa0EfAd4PyUh9kvgUNvPStoT2Nv25nUOU54QeSAwAjgd2N+26/FPUJJNrweuA/a1fU/TufsDn6P8/qzb6UvpgzWBmbYvqtsXSpoLrAf8q3lgrWrbAtirw1wfAibbPruOPwyYLmlD27f1KaopU2Ds2D6dErFIdXdDV1d/RxEREREREbHEGvAVXZLWBsYCE+pr9zbDdgHeR0nKbArsaXsuJTH2QFO10AN1/PbAr4CVgfMpiTIkLQv8DrgYeC3wGWCCpFFN1/oYcDiwCnA70OgndjLwMUlL1blGAFsBZ7SJ90ZgQ0nflfQuScMaB2z/ATgKOLPGPLpp/meA9YF/A7YG9u7ho9sWeBswun4+761x7UhJpH0IeA1wRZsYdwQ2A97Uw/x9MQm4VdL2kpauMTwJ3Nxm7O7AFbbv6jDXxsBNjY36Pd9BlivGYNDVBePG9XcUERERERERS6zBUNG1O3Cz7VskzQS+KenfbP9f05jjG0msWkU1v5KIK23/vo4/lVK9BPAOYBhwtO3ngMskXUBJbh1Wx5xr+7p67gRKlRW2r5M0i5LcugT4KDDR9kOtF7d9p6SxlKV8ZwHDJf2KUnU1p3W8pNdRknYr234CmCvpu8C+wI873OPRtmcCMyX9uX4mfwD+G/iG7Vvr3EcBX5W0TqOqqx6f0fNHyHRJzdvLA99sN7BWnZ1CqSxbDngK2LkmqVrtDnTs9UX5fh5u2TcLGD6feF9q1CiYOLHPp0VERERERERE/xjwFV2UxMcEgJrM+gtlaWKzaU3vH6ckQ3rSOn652o9qdWBqTXI13AOs0ctrnQzsVt/vBpzaKQDb19jexfZrKEv13gkc3GH4OsCywIOSZtaE348pVWeddIpzHeC4pnlmAOLF9zi1h3kbRtheufGiJLHakvRuShJsLPAKYEvgZ5K6WsZtTllO+eserjuH0uer2YqU5Z8RERERERERMYgN6IouSf8BvBH4iqRG76vhwMaSvmD7mflM4T5e8gFgLUlLNSW71gb+0cvzTwP+Lmk0sBHwm96cZPt6SecCmzR2tQyZSlnqN6IX9zw/U4EjbU/oKaSXeY1WXcDljT5owPWSrgXeDXQ3jduDUjH3kqq2JpNpSnRKWoHS62vywg05IiIi2hnb/b3yf11FxICUlqARMdAN6EQXJaFxCS/uy/UqSm+nbSj9tHryEPBqSSvZntWL611LaTb/JUnHAv8JbEfpdTVftu+TdD2lkuucuszwJWrl0kbAb23/S9KGlL5hJzfF/Z5Gws32g5IuBo6VNJ5S1bQusKbtv/QmtiYnAl+X1G17cm1yv3Wjufsicj1wkKQu292S/o1SxfbDxgBJrwJ2pvQO68l5wLck7QRcCBxCWdrat0b0EbF4dXfn4Q9DVf5FFRGxRElL0IgY6AZsokvScpQm6rvbntZy7FRKEqzHRJft2ySdAdwpaWnm01zd9lOStqckYL5Ceeri7n1MopxMSXR9tocxMymJrSNqRdJ04Exe6HF1NmXp4yOS7rL9Fkqy72jKkx6HA3cCx/QhLgBsn1eb3/9K0jqU/laX1GsuErb/Up+O+Ovab+xh4CjbFzcN27HG8ufW8yVNruMn2H64JrlOoFTQXUvphxYREUui/Itq0JnY9bn0uIyIiIh+I3thr0JbdCTNoyzRO972+P6OZ0FIeiclATOypddXLAaSDqU0+X8lsILtZzuNHTNmjCdNmtTpcEQsLI1KrvzDOGLgy99zRETEEm8w/M+1pBtsj2l3bEBVdNlerr9jeDkkLUup5PpZklz9w/bhwOH9HUdERERERERELHyD4amLA4KkjShLElcDvtfP4UREREREREREDDoDqqJrILN9K7BCf8cRERERERERETFYDbmKLkmWNFfSkYv4Ol+V9LNFeY3+JGlPSVf2dxx9IemVkuZIelrSEf0dT0REREREREQsXEMu0VWNtn0wgKSRNfm1TN2WpO9Luk3SGgt6AdtH2d57Qc6VdJKkpyTNrq+/S/qGpJUWNJ7FTdIn62c4W9JDki6UNLzD2Mk1AdV4PSPpd03HfyJpiqTnJO05n+t2nMv/n737DrerqtM4/n2RJgQIRUC6igRUhowEsVCioAwoTUUl9BnBERELoggioILKKM1eaSEKSJUiKBqaUgIGlBJ6CCX0QBII9Z0/1jqwOdxybtrNvXk/z3Oee/Zea6/92/vgg/78rbXsZ20PAU6Znc8aEREREREREfOG+TXR1SVJAn4BjAQ2tX1/P4ZzpO0lgDcAewDvBq6U1OfpjzV5N9d+a0mbAkcAO9ZnWAc4rbv+tt9ue0hNQi0B3Auc3uhyA7A3cH1v9+5grIiIiIiIiIgYpLJG1yteB/wGWBcYafsxAElrAz8C1gceAQ62fZqkdwNnAyvbfrH23R44zPZ/SDoUWNP2zpLWAO4Gdge+DSwGHG271+mTtmcA10raBriNkvT6cXP8eu/WPRay/YKkscCVlKTdO4F1JW0MfBVYpT7L923/ol4/EhgNHA18DXgROND28bV9WeD4Ot6twEU9hL0B8A/b/6zP8DhwYm/PWm0CLA+c0XgHP6kxzOhwjG7H6pMJE17ZdzVi1CjYa6/+jiIiIiIiIiJ6kIquV5wCrA18oJHkWhz4MzCGkjDZEfippLfbvgqYDnygMcao2rc7GwHDgM2Ab9adGDtie2qNZeOOnwh2AfaiVDZNBB4GPgIsSUmYHS3pnY3+KwJLASsD/wP8RNLSte0nwAzKrpH/XT/duRrYQtJhkt4naZE+xLwb8Afb0/twzdwYK+Zn48fDmJ7+ox0RERERERHzglR0veJDlGqsKY1zHwHuaVU1AddLOgP4OHAT8DtK8uvPdf2prYCv9HCPw2w/A9wg6QZgPeCWPsT4AKWyrFMn2L6pcXx+4/ulki6mJM5aUwKfB75l+wXgAknTgGGSrgU+Bqxbk0b/lnQipWLqNWxfLumjlOmGXwAWlPRLYP9W9VtXJC1Gebfb9OEZ59xYw4bB2LGzGkoMBqnsi4iIiIiIGBBS0fWKjwCHSGpWKq0ObChpSusD7ESpfIJSvfXRWrH0UeB62xN7uMfkxvengSF9jHFl4PE+9J/UPJC0paSrJD1en2UrYLlGl8dqkqs9xjdQkqLN8Xp6TmxfaHtrYBlgW8q0zd4W5/8o5fku7aVfJ2bnWBERERERERExACTR9Yq/A1sDx0oaVc9NAi61PbTxGWL7swC2b6YkfLak92mLs0TSEGBz4PJ6ajplra+WFV9zEbhx/SKUtap+AKxgeyhwAaAObv8I8AKwauPcap3Ebfsl25cAfwXe0Uv33YCTbLuXfp2YnWNFRERERERExACQRFeD7UsplUC/lPRx4DxgLUm7SFqofjZoW1trDLAvZRrfbN/dT9IiktanLHz/BGVBeIDxwCaSVpO0FPD1XoZaGFiEmrSStCVlumav6nTDM4FDJS0m6W2URFJ3MW8r6VOSlq47Pr4L2BS4qodrVgHeTxeL1ktaWNKilKTcQpIW7WkXyZ7GioiIiIiIiIjBK4muNrb/DHwSOIGyw+CHgE9R1seaDHyfkjBq+V3t91fbj87GUL4qaSpl+t1JwHXAe1sLq9c4TwVurG3n9TRYXcx+X+A0SsJsFHBuH+LZhzKNcTLl3RzfQ98ngD2B24GnKLs5/p/tU3q4ZhfKTo13dtF2MfAM8F7gl/X7JgCSdpJ0U1v/nsaKiIiIiIiIiEFK89vMLkkzgGeB42wf3N/xxNxTp28+BCwEHGn7sJ76jxgxwuPGjZsrscU8buTIsvPi8OH9Hcng1Hq32fwhYuBrbd6R/zxHRETMswbDv64lXWd7RFdt892ui7YX7e8Yon/YfhYY2t9xRESb4cNh1Kje+0VERERERPRivkt0RUTMlFQcRUREREREzPMG7BpdkixpuqTDO+x/gqTvzOm4BjJJIyXd199xzEmSDqv/3FhSEr0RERERERERg8iATXRV69k+qHUg6X8k3SppqqSHJJ0vaYlZvYmksZI+PQvXn1ATK9u0nT+mnt+9w3FGSRonaZqkByVdKGmjWYjLktac2et7GXsVSWdIelTSk5L+1dNzSvqEpFvqb3ezpO266LNw/X07SsZJOqQ+4+atc7YPAd4+M88UEREREREREfO2gZ7oepmkTYEjgB1tLwGsQ9lhcF5xG7Bb66BWE+0AdLQzoKQvA8dQnnEFYDXgp8C2fQ1kLlUynQxMAlYHlgV2pSwE31U8K1N2ZvwysCSwPzBG0vJtXfcHHu7k5pLeAnwceHBmgo+IiIiIiIiIgWfQJLqADYB/2P4ngO3HbZ9oe2qjz9K1ymuqpKtrMgQASe+VdG2tPrpW0nvr+cOBjYEf10qqH9fzx0qaJOkpSddJ2riX+P4IvE/S0vX4v4AbgcnNTpL2bKtseqekpYBvAZ+zfabt6baft/1H2/vX694l6R+SptRqrx9LWrgxriV9TtLtwO2SLqtNN9Tn+mSj736SHq7j7FHPbVCr5BZs9PuYpPE9/B4n1FhfsP1P2xd203cVYIrtC12cD0wHmr/Pm4Cdge/29JIbfgx8DXiuw/4RERERERERMcANpjWKrga+Lekw4GJgXN1lr2lHSoLpeuBE4HDgU5KWAc4H9gV+R6m0Ol/SmrYPkvQ+YLTtXzfGupaSfHoS+AJwuqQ1bM/oJr4ZwLnAp4CfUSqcTgI+1+ogaQfgUGA7YBwl0fM88B5gUeCsHp7/ReBL9bpVgAuBvSlVYC3bARsCz9h+RpIp0z/vqPcfCawILAWsDHwQ+IOks21fK+mxeq6VsNqZUrnVlauAn0j6EfB32/f2EPs44JY6tfN8YGvgWUoisOVHwIHAMz2MQ32OHYDnbF8gqbfu3Zsw4ZV9V2P+Nn58WYw+IiIiIiIi5mmDpqLL9uXAR4F3UpIlj0k6StLrGt3OtH2N7ReAU4DW/3L9MHC77ZNr9dHvgFspCZfu7jfa9mO1/w+BRYBhvYR5ErBrrdDaFDi7rf3TwJG2r62VTXfYnkiZ+vdojbu7eK6zfVWN5x7gF/UeTd+tlW49JYueB75VK8YuAKY1nutESnKLmhzcAhjTzTg7AJcDBwN3SxovaYNuYn+R8m7GUBJcY4DP2J5e77U9sKDtnhJ91L5DKNM7v9hb34iODR8Oo0b1dxQRERERERHRi8FU0UWdGnehpAWA9wOnAxMoSR949TTBp4Eh9ftKwMS24SZSqpq6JGk/SmJqJcCUtaWW6yW+KyS9AfgGcF6tqmp2WZWu1+x6DFhO0oLdJbskrQUcBYwAFqP8tte1dZvUU3yte7Xdo/meRlMqr4YAnwAut93lGli2nwAOAA6QtBzwA+BsSavYdlvsmwNHAiMp1XbrA+dK2hK4vbZt1UHsAIcBJ9u+u8P+3Rs2DMaOneVhIiIiIiIiImLuGDQVXU22X7J9CfBX4B0dXPIAZdH0ptWA+1tDNhvqelxfoyR7lrY9lDKFsZN5cqOB/SgVTO0m0ViXquEflKmPr9mJsOFnlCq0t9pekjLNrz0ev+aqPrB9f41le2AXup+22H7do5RE10rAMl10GQ5cZntc/e2upUxF3Rx4K7AGcLmkycCZwBslTZa0RhdjbQbsW9snU5KHp0n6WscPGhERERERERED0qBJdEnaVtKnJC2t4l2UqXtXdXD5BcBakkZJWrAuzP424Lza/hDw5kb/JYAXgEeABSV9k1LR1YnjKOtcXdZF26+Br0havz7DmpJWt/0k8E3KmlfbSVpM0kKStpR0ZCOmp4BpktYGPttBLO3P1YmTgK8C69LDmmGSvi/pHfV9LlHjucP2Y110vxbYWNLweu1/UjYAuBH4NyVZNbx+Pl3jHk7XFWqbUZKbrf4PAJ8BftLH54yIiIiIiIiIAWbQJLqAJ4A9KVPdnqJUTv2f7VN6u7AmXz5CqbR6jJLI+UitRAI4Fvi4pCckHQdcRFmQ/TbKFMcZdDYtsLUb5CXt0/dq2+mUBfLHAFMpa3gtU9uOAr5Mmfb4SL3fPryyztdXgFH1ul8Bp3YQzqHAiXWnxk90Ej8lubU6cFZrDa1uLFb7TgHuqtds01VH25fWWP4gaSpwBnCE7YvrmmOTWx/gceClevwigKSbJO1Ux3qsrf+LwBO2p3X4fBERERERERExQKmLfMuAIGkGZeHy42wf3N/xzE8k3UlZLP4v/R1LX0k6hJIwXARYvJUs68qIESM8bty4uRZbRETEgNfarThrXEZERMyzBsO/riVdZ3tEV20DdjF624v2dwzzI0kfo6z19df+jmVm2D6MsmB9RERERERERAwyAzbRFXOfpLGUtct2sf1SP4cTEREREREREfEqSXRFx2yP7O8YIiIiIiIiIiK6M2AXo5dkSdMlHd7fsQwWkk6Q9J3+jmNOknSnpOckje7vWCIiIiIiItqBhDMAACAASURBVCJi9hqwia5qPdsHAUhaoya/5rkqtRrXQ83YJC0o6WFJHe0GIGlJScdIulfSNEl31OPlZjKm3SVdMTPXdjj+tpLGS3pK0qOSLpG0Rjd9D5X0fH2u1ufNtW21tvPT6vvcr5uxvijprnrfByQd3Xzvtt8CHDEHHjkiIiIiIiIi+tlAT3TNdbOQSJsCbNk43gp4osN7LgxcArwd+C9gSeC9wGPAu/oayJxOBkpaEzgJ2A9YCngT8FOgp3W9TrU9pPG5C8D2vc3zwLp1nDO6GeePwDttLwm8A1gP2He2PFhEREREREREzNPmueqnOUHSu4BjgXWAZyhJki/bfq5WGd0NLGT7hdp/LDDa9q8l7Q7sCVwD7Ab8VNLxwK8oSRQDFwGfsz2lhzBOBnalJGKo308CXp4qKGkZ4IfAFsDrgUttb1f7rga83/a02v1h4NuNaw+ocS4PTAIOsn1WbWt/hr8BHwYWkjQNeMH20DrU0pLOBzYBbgZG2b5T0k+AGbb3a9zzj8Alto9pe9bhwN22L6nHU+k+MdVXuwKX2b6nq0bbdzYORUmKrTlTd5ow4ZV9VyPajRoFe+3V31FEREREREREw/xS0fUi8CVgOeA9wGbA3n24fkPgLkoS6XBKAuW7wEqU5NmqwKG9jHE2sImkoZKGAhsD57T1ORlYjFK5tTxwdD2/OfCnRpKrK3fWMZcCDgNGS3pjN8+wM/C/wD9qpdTQRr8d6/VLA3fU5wU4EdhR0gIAdcrkZsDvuojlemDtOm3w/ZKG9BB3y9aSHpd0k6TP9tBv1xpLtySNkvQU8CglGfmLDu4f0bnx42HMmP6OIiIiIiIiItrMFxVdtq9rHN4j6RfApkB7JVJ3HrD9o/r9BUoC6I56/Iiko4BDehljBqWa65OURNm59RwANSm1JbCs7daUxkvr32WB5jO8hu3TG4enSvo6ZVpjK5n2qmeQ1N1QZ9q+psZ0CnBUHf8aSU9Sklt/Bj4FjLX9UBex3CVpJPBl4DRgCUm/B/bpJll3GvBL4CFKQu4MSVNsvyqJJmljYAXgD92/CbA9Bhgj6a2UxNhrYuzIsGEwduxMXRqDXCr9IiIiIiIi5knzRUWXpLUknSdpcq30OYJS3dWpSW3jLS/p95Lur+ON7nC8kyiJl9a0xaZVgccbSa6mx4A3dnG+GdOudfH3KZKmUNanasY0qZtL201ufH8aaFZjnUipBqP+Pbm7QWxfZfsTtt9AqTTbBDiom743237A9ou2/06ZZvrxLrruBpzRS2Vbc9zbgZso64NFRERERERExCA3XyS6gJ8BtwJvrYuUH0ipqgKYXv8u1ui/Ytv17Tsjfree+4863s6N8XpyOSVhtQLQvuPhJGCZOq2x3V+ALSQt3tWgklanrBm2D6UibCjw77aY2p+ho90e24wGtpW0HmXK5tmdXGT7WuBMSvKto0toe5+SXg/sQC/TFruwIPCWPl4TEREREREREQPQYEx0LSJp0cZnAWAJ4ClgmqS1gZfXgLL9CHA/sLOk10n6b3pPjCwBTAOmSFoZ2L+TwGwb2BrYpn5vtj0IXEhZ7H5pSQtJ2qQ2n0xJhJ0haW1JC0haVtKBkrYCFqckhx4BkLQHvSeVHgJWqTs6dsT2fcC1NZ4zbD/TVT9JG0naU9Ly9XhtYBvgqm76b1ufWXXjgH157fpl21N2rvxbTzFK+nTjvm8Dvk7ZsTIiIiIiIiIiBrnBmOiaRtlZsfX5APAVYBRl979fAae2XbMnJVn1GGUh+L/3co/DgHcCTwLnU6qVOmL7Jts3ddO8C/A8pfrsYeCL9ZpnKQvS30pZH+spyg6KywFX276ZslvjPygJrHWBK3sJ5a+UaX2TJT3aafyUiqp16WHaIiUhtQ3wr7qr45+As4Aju+n/KcqaZ1MpUzq/b7u9cms34KT2BKGkjes9Wt5X7zsduKB+DuzkwSIiIiIiIiJiYFNb3mDAkDQDeBY4zvbB/R3P/KJWmY0G1rD9Un/H01eSJgArA6fZ/u+e+o4YMcLjxo2bO4HFwDJyZNl5cfjw/o4kBoNRo2Cvvfo7iojZo7VZRzZziYiImGcNhn9dS7rO9oiu2gbsrou2F+3vGOY3khYCvgD8eiAmuQBsD+vvGCIiXjZ+fPmbRFdERERExGwxYBNdMXdJWgcYB9wA7NHP4UT0v+HDB/b/BRLzhtb/nRYREREREbNFEl3REdu3UBa9j4iIiIiIiIiYJw3GxegjIiIiIiIiImI+NKASXZIsabqkw2dhjJGS7puF+6/ZTdtOki6e2bgGIkn3SNq8v+PoC0mH1X+GLCkVjRERERERERGDyIBKdFXr2T5I0saSptVPK3ExrfFZbW4GZfsU2x+aHWNJWqPteR6SdJ6kD86O8ecGSatIOkPSo5KelPQvSbt307f9eadJes1OmpIWlnRrb4lKSZ+QdIukqZJulrRdq832IcDbZ/X5IiIiIiIiImLeM2ArWmxfDgyBkigB7gaG2n6hH8PqkqQFZzKuobZfkLQi8EngLEn72D5hLsYws06mLFy/OvAssC6wYi/X9Pb77Q88TP3duyJpZWA0sC3wJ2Ar4HRJa9h+uPPwgQkTslB0dG38+LIYfURERERERMxTBmJFV68k7dGo6LlL0md66LtvrfpZRdK7JP1D0hRJD0r6saSF2y7ZXNLtkp6Q9BNJquPsLumKxriW9DlJtwO313N7SrpD0uOSzpW0UifPY3uy7WOBQ4HvS1qgcY+Xp1JKOkHSd+r3kZLuk/Q1SZOB4yUtXSvDHqnxnydplcb1YyV9W9KV9d1dLGm5RvsukiZKekzSQb2EvQFwgu3ptl+w/U/bF3byvF2R9CZgZ+C7vXRdBZhi+0IX5wPTgbfM7L0jXmP4cBg1qr+jiIiIiIiIiDYDtqKrFw8DHwHuAjYBLpR0re3rm53q9LjtgU1tPyJpBeBLwDhKwuRCYG/gmMZlH6EkcZYErgP+SKkc6sp2wIbAM5I+QEnSfAi4CfgB8PsaX6fOBP4PGAbc0kH/FYFlKFVVCwCLAccDnwBeB/wW+HGNs2UUsCUwifL8XwEOkPQ24GeUCqmr67OsQveuAn4i6UfA323f20G8EyUZ+DOwv+1HG20/Ag4EnulljHHALZK2Ac4HtqZUlN3Ywf1fbdgwGDu2z5dFRERERERERP8YlBVdts+3fWet6LkUuBjYuNFFko4CtgDeb/uRet11tq+qFUj3AL8ANm0b/nu2p9TEzd+AnuYvfdf247afAXYCfmv7etvPAl8H3lOnXXbqgfp3mQ77vwQcYvtZ28/Yfsz2Gbaftj0VOJzXPt/xtm+rMZ/GK8/3ceA825fV+A+u43dnB+Dy2u9uSeMlbdBN30cpycPVgfWBJYBTWo2StgcWtH1Wbw9s+0XgJGAMJcE1BviM7em9XRsRERERERERA9ugrOiStCVwCLAWr1Qy/avRZSiwF/BJ2082rlsLOAoYUa9ZkFK11TS58f1pelgvilIV1bIS8HJFme1pkh4DVgbu6eS5al+Axzvs/4jtGa0DSYsBRwP/BSxdTy8h6XU1QQTdP99KNJ7H9vQaf5dsPwEcQKkGW45SwXa2pFVsu63vNEolFsBDkvYBHpS0JPAicCSlkqxXKrtAHgmMpLzv9YFzJW1pe3wnY0REzFXjx2c9wBg8soZhRERE9LNBV9ElaRHgDEpiZQXbQ4ELADW6PUGZgni8pPc1zv8MuBV4q+0lKVPlmtf1VTOh8wClYqkV5+LAssD9fRhve8q0zAn1+GlKQq6lfbF3tx3vR5n2uGF9vta0yU6e8UFg1dZBTZot20nQdQriDyjJsk6q0VpxC3grsAZweV1r7EzgjZImd1MNNxy4zPY42y/ZvpYy1XLzTmKNiIiIWZA1DCMiIqKfDcaKroWBRYBHgBdqddeHgH83O9keK2knyk6GW9u+mjJl7ilgmqS1gc/WcWaHMcDvJY2hrK91BHB1nSLZo7p22A6UKrUv2G5NGRwPjJJ0E/BByjTEcV2PApTnewaYImmZOl6n/gBcLWkj4BrgW/SQKJX0fcrOi7cCr6e8yztsv6YKTNKGwBTKov1LA8cBY20/KenfNBJswHsp64q9k65/m2spVWTDbY+X9J+Uaas/7cOzRkTMPcOHZz3AiIiIiIjZZNBVdNW1p/alrC/1BGVx9XO76ftnYA/K1Lb1KQuvjwKmAr8CTp2NcV1CWa/qDEp11FuAT/Vy2RRJ0ynTLrcCdrD920b7FyiLrU+hrAF2di/jHUNJOj1KWSy+u0X0u4r/JuBzlITdg5R3e18PlywGnFVju4tSzbZNN33fXGOZSklIPgvsWO/7Qt11crLtyZRpmy/V4xcBJN1Uk5bUNdkOBf4gaSrlfR9h++JOnzUiIiIiIiIiBia1LZc0T5M0g5IEOc72wf0dTww8kg4Bvkyp+lu8sTbZa4wYMcLjxvVUIBcRMYtaa3OloisiIiIi5pLB8F9BJV1ne0RXbQNq6qLtRfs7hhjYbB8GHNbfcURERERERETE7Dfopi5GRERERERERMT8aUAluiRZ0nRJh8/GMXeS1Ov6TZIOlTS6h/abJI2cXXHNDZLGSvp0f8cxt0jaXNI0SS9Jyi6MEREREREREYPMgEp0VevZPghA0ho1+TWtfh6SdJ6kD3Y6mO1TbH9oVoOy/XbbY7trlzSixvaEpCmSbpZ0uKSlZ/Xe8xJJ97QnkSTtLumKDq7dtP6e32mce6OkcyU9UNvW6GWM90q6RtJUSTfWXSIBsP0X20OAe/v8YBERERERERExzxuIia6uDK0JjPWAPwNnSdq9f0N6haT3AmOBK4G1bQ8F/gt4gRLzfE/SQsCxwNVtTS9RdmT8WAdjLEPZYfP/gKHAkcAfB1syMSIiIiIiIiK6NqAWo++N7cnAsTVp8n1JJ9l+SdIBwJ7A8sAk4CDbZ0GpNgI+bXujevx24BhgfeB54FjbR9RbLCzpJGB7SlXQbrbH1evuqeP8pYvQjgSOt/3dRqz3Aoe0jiUtABxY43w9JbnzedtP1iqmu4HdgW8DiwFH2z68XjuFV35L1fY3AU8CJwMb1vYrgf+1fV9X70/SfwP7AysC1wB72Z4o6avANxtdFwFOsb17V+PMpP2Aiym/0ctsPwT8VFIn/6y+F3jI9un1eLSkbwIfBX7T54gmTHhlO4qIiDlh/HgYPry/o4iIiIiIGDQGS0VXuzMpCZNh9fhOYGNgKcqOe6MlvbH9IklLAH+hJJlWAtYELml02Qb4PaVa6Fzgx70FImlx4D3AGb103b1+3g+8GRjSxfgb1WfaDPimpHUAbA+1PaRWtR0LXA7cT/l9jwdWB1YDnukuZknbURJtHwXeUMf4XR3/yMb46wCPAKf19uydkrQ68N/At2Z1qPppP/eOWRw3ImLOGD4cRo3q7ygiIiIiIgaNQVXR1fBA/bsMQKPCB+BUSV8H3gWc03bdR4DJtn9Yj2fw6ql0V9i+AEDSycAXO4hlaUrCaXLrhKQjgb2AhYDv2v4OsBNwlO27ap+vA/+WtEdjrMNsPwPcIOkGyrTHWxrjfhIYBWxg+3ngMRoJtrqI/9+6ifMzNZZbat8jgAMlrW57Yj33euBsSpXbBT0889mSXmgcLwxc30P/44CDbU+T2vNUffJ3YCVJOwJ/oLyLt1Aq3Ppu2DAYO3ZW4omIiIiIiIiIuWiwVnStXP8+DiBpV0nj6yLwUygVPst1cd2qlOqv7kxufH8aWLSDKXVPUNaZermCzPZX6zpdZ/FKsnElYGLjuom1bYUe7j+kdSDpPynVWtvbfqSeW0zSLyRNlPQUcBkwVNLruohzdcq0z9Y7epxSDbVyo89vgAm2v9/LM29Xq8yG1ufcu7uOkrYGlrB9ai9j9sr2Y8C2wJeBhyjroP0F6HKqZkREREREREQMLoO1omt74GFgQp0W9yvKdL9/2H5R0nheO8UNyvpdO87OQGxPl3Q1ZUpgd9VUUKrQVm8cr0ZZrP4hYJWe7iHpDZSk2T62/9lo2o8y1XFD25MlDQf+SffPfrjtU7q5xwF1rI26ap8FmwEjJLWSeEsBL0pa1/a2fR3M9qXABgA1CXkn8MMeL4qIiIiIiIiIQWFQVXRJWkHSPpRF3r9u+yVgccCUdaWoUwG7W7PpPGBFSV+UtIikJSRtOBtC+yrw35IOkLR8jWMVyoLxLb8DviTpTZKGAEcAp9p+4bXDvaImc86gLA7fXhW1BGVdril1R8JD2q9v+Dnw9boYP5KWkrRD/b4lsC+lUuuZzh65YwcDawHD6+dcSmLy5SmbkhalLIAPsEg97pKk/5S0kKQlgR8A99m+aDbHHBERERERERHzoMGS6JoiaTrwL2ArYAfbvwWwfTOloucflOqodSm7D76G7anAB4GtKdMEb6csDj9LbF8BfADYBLitTg38EzAW+FHt9lvKDomXUXZYnAF8voPhV6EstP9FSdMan9Uou0e+HngUuKres7sYzwK+D/y+TnP8N7Blbf4kZYH6Wxrj/7zT5++J7am2J7c+lMTcdNuPN7o9A0yr32+txwBI+nlbLF+lPO8kynTR7WdHnBEREREREREx75Pt/o6hY5JmAM8Cx9k+uL/jiYFF0maU6rdFgK1s9zSVlBEjRnjcuHFzJbaIiIiIiIiIuWHkyPJ3IO+9Juk62yO6ahtQa3TZ7nbKWkRvbF8CDO3vOCIiIiIiIiJizhgsUxcjIiIiIiIiImI+l0RXREREREREREQMCvNsokuSJU2XdPhMXn+gpF/X72vU8Rasx2Mlfbp+30nSxbMv8phXSVqrLqT/Yuv3j4iIiIiIiIjBY55NdFXr2T4IQNJFkr7aapC0ck1edXVuRdtH2O41mWH7FNsfmjPhv5akUZLG1YTLg5IulLTR3Lr/nNZMIjbOjZR0Xw/XrCPpr5KelHSHpO3b2heT9FNJj9Y+l/Uw1jKSzqpJ0omSRrXabN9mewhw+Sw8YkRERERERETMo+b1RFfTZcCmjeNNgFu7OHe77clzM7BOSfoycAxwBLACsBrwU2DbmRjrNRsJdHVuXldjPgc4D1gG2AsYLWmtRrdf1rZ16t8v9TDkT4DnKO93J+Bnkt4+B0KPiIiIiIiIiHnMQEqMXAbsL2kB2y8BG1OSRt9qO3cZgKRDgTVt79zToJJ2Bz5te6N6fCzwUWAp4Hbgi7Yvb4z5duBZSnLqHuBj9fOlev5/bL9mKqSkpYBvAXvYPrPR9Mf6QdK7gGMpCZ1ngDOAL9t+rrYb2Af4IrCgpD2A0cCP6v3/LGlf4GRgQ8rveyXwv7bvazzvN4E3AI8C37B9Sm3bE/gysAowCdjZ9vWS1gF+BgwH7ge+bvvcnt5rH6wNrAQcbdvAXyVdCewCHCxpGLANsIrtp+o113U1kKTFKb/FO2xPA66QdG4d64C+BjbhsQmMPGFkXy+LmC+NWncUe62/V3+HERERERER87mBVNF1DbAIsF493gT4M3BH27lup7V16FpKQmcZYAxwuqRFG+1bUxJJSwP/BC6ivMeVKYmsX3Qz7nuARYGzerj3i5SE1XK1/2bA3m19tqMksd5Wj1essa5OqYZaADi+Hq9GSZj9GF5OBB0HbGl7CeC9wPjatgNwKLArsCQlufSYpIUoibiLgeWBzwOn1ATU7KBuzr2jft8QmAgcVqcu/kvSx7oZay3gRdu3Nc7dQElORsQcMn7yeMb8a0x/hxERERERETFwKrpsPyvpamATSROBobbvknR549zbgEtn8T6jG4c/lPQNYBglYQJwue2LACSdTqn++p7tFyX9HvilpKG2p7QNvSzwqO0Xerh3s1LpHkm/oEzNPKZx/ru2H6/3B3gJOMT2s7W9VQlG7XM48LfG9S8B75B0r+0HgQfr+U8DR9q+th7fUa/fGBhSn/ElSsXVecCOlMRYV46T9IPG8YJA+/touRV4mFKtdzTw/vrMrZhXoSS9zqBUfr0HOF/SzbZvaRtrCPBk27kngSW6uXePhi07jLG7j52ZSyPmK6l8jIiIiIiIecVAquiCUq21CWWK4hX13BWNc5NsT5yVG0jaT9ItddHzKZQpjMs1ujzU+P4MJXn1YuMYSsKl3WPAcj2to1V3BTxP0mRJT1HW8lqurduktuNHbM9ojLGYpF/UhdiforyzoZJeZ3s68Engf4EHJZ0vae166arAnV2EtRLlvb7UODeRUsHWnX1tD219gI9019H285QqtQ8Dk4H9gNOA1uL1zwDPA9+x/ZztSylJsK42EJhGqUZrWhKY2kOsERERERERETFIDMRE18aUxFZr57wrgfcxG6Yt1uqlrwGfAJauSZon6Xp6XV/9A5hBSep052eUCqe32l4SOLCLe7uX4/0oFWgb1jE2qecFYPsi2x8E3ljv9avaPgl4SxcxPQCsKqn5z8pqlLW6ZgvbN9re1PaytrcA3kyZqgpwYx+Guo2ydtlbG+fWA26aTaFGRERERERExDxsoCW6/g4MBXamJrpsPwE8Us/N6vpcSwAv1PEWlPRNXlshNFNsP0lZBP4nkrarlVcLSdpS0pGN+z8FTKuVVp+diVstQamCmiJpGeCQVoOkFSRtU9fqepZSAdWqRvs18BVJ66tYU9LqwNXAdOCrNd6RlHXKfj8TsXVJ0n9IWrS+k69QknAn1ObLgHuBr0taUNL7gJGUtdFepVasnUnZoGDx2ndbyppqERERERERETHIDahEl+2nKTvuLQL8u9F0OWWh9FlNdF0EXEipDJpIqcBqnyo402wfRdnV8BuUZNokyi6KZ9cuXwFGUaba/Qo4dSZucwzwesqOilcBf2q0LUCp+HoAeJyyFtbeNbbTgcMpC/BPrTEtU3d83AbYso75U2BX27fORGzd2YWyVtjDlAX4P9hac6xObdwW2IpSXfer5v0lHSjpwsZYe9fnfxj4HfBZ26noioiIiIiIiJgPyG6f+TZvkDSDUnV0nO2D+zueGPjqlMZrgYWBvW2f0FP/ESNGeNy4cXMjtIgBbeQJIxk/eTzDVxze36HMFqPWHcVe6+/V32FERERERMwRI0eWv2PH9mcUs0bSdbZHdNU2z+66aHvR/o4hBhfbt1OmvkZEdGn85PEASXRFRERERAxQ82yiKyIiBo7hKw5n7O5j+zuMWTbyhJH9HUJERERERMyCAbVGV0RERERERERERHdme6JLkiVNl3T47B67h3tuLGnCTF67mqRpkl5Xj8dK+nT9vpOki2dnrIOFpEMlje7vOPpC0lr1t36x9RtHRERERERExOAxpyq61rN9EICkNWry6/pmB0nLSXpO0j2zejPbl9seNpPX3mt7iO0Xu2g7xfaHZjW+vqrJthmSpkp6StJ1kg6QtMjcjmVm1d0Q766JpfskdbuDpKR1JP1V0pOS7pC0fVv7ZpJulfS0pL9JWr2HsZaRdFZNtk6UNKrVZvs220Mou3RGRERERERExCAzN9foWlzSO2z/ux6PAu4GBkzyZi7bx/avJS0ObAAcA3xQ0ubu41aZkha0/cIcibLr++0G7AJsbvtOSSsC23QXG3AO8HPgg8CmwB8l/aft2yQtB5wJfBr4I/Bt4FTg3d3c/ifAc8AKwHDgfEk32L6pr88x4bEJWa8nogODacfFiIiIiIgY2ObmGl0nA7s1jncFTmp2qFVLd9ZKppublT2SfibpD43j70u6RMVISfc12u6RtL+kG2tlz28krSDpwjr2XyQtXfu2Ks5ek/STtLukKxrHx0qa1Kiy2rjRdqik0ySdVO9xk6QRjfZ1aqXWlNrWZeKnne3ptsdSEkXvAT5cxztB0nca43f1Dr4m6UZguqQFe3m/u0u6QtIPJD1Rq7G2bLS/SdKl9do/A8v1EPYGwEW276zPMNn2L7vpuzawEnC07Rdt/xW4kpIoA/gocJPt023PAA4F1pO0dvtANSn4MeBg29NsXwGc2xgrIuaA4SsOZ9S6o3rvGBERERERMYfNzYqu0cDlkg4A1gKWAK4G9mz0uRPYGJgM7ACMlrSm7QeB/YDxknav/f4HGG7bkrq638coFUILAv8E/rNeczNwIbAvcFgfn+Fa4FvAk8AXgNMlrVETMFCSUR8F9gC+A/wYeLekhSjVSL8FPgRsBJwjaYTtjtYWs32vpHGU93Neh/HuSEmMPWr7BUk9vV+ADYETKUmsvYDfSFq5VpCNAf5R498QOJ9SidWVq4DjJN0P/A34Z1dTQ6uufjwB76jf3w7c0GqwPb0+x9uBW9uuWwt40fZtjXM3UKrE+mzYssMGxS5yEREREREREfOLuVnRdR8wAdicUtl1UnuHWrXzgO2XbJ8K3A68q7Y9DewMHEVJmn3e9n3tYzT8yPZDtu+nrMl0te1/2n4WOIuS+OoT26NtP2b7Bds/pEy7bK4NdoXtC2pS52RgvXr+3cAQ4Hu2n6tVS+dRElF98QCwTB/6H2d7ku1navzdvt9qou1f1fhPBN4IrCBpNUqV1sG2n7V9GSVx1yXbo4HPA1sAlwIP1wRnV24FHgb2l7SQpA9RElOL1fYhlMRi05OURGm7vvSNiIiIiIiIiEFmblZ0QUlu7Q68F9gEeGuzUdKuwJeBNeqpITSmyNm+RtJdwPLAab3c66HG92e6OB7S1+Al7UdZK2olwMCSvHoK3+TG96eBReuUyJWASbZfarRPBFbuYwgrA3/vQ/9JzYPe3i+N+G0/XSvlWn2esD290XcisGp3N7Z9CnBKrWbbrn7/p+2L2vo9L2k74EfA14BxlN/22dplGuU9Ny0JTO3itn3pGxHRpfGTx8/R9flGrTuKvdbfa46NHxERERExP5ubFV0AZ1Cm0t1le2Kzoe6k9ytgH2BZ20OBf9OY2ibpc5QqqgeAr86toOu9N6YkYj4BLF3je5Kup961ewBYVVLzfa8G3N+H+68KrM8rOwZO55WqJ4AVu7js5UXrO3m/PXgQWLqugdWMv1e2nZctNwAAIABJREFUn7d9OnAjr0xHbO9zo+1NbS9rewvgzcA1tfkmXqmMa63D9ZZ6vt1twIKSmgnU9brpGxEx142fPJ4x/xrT32FERERERAxac7Wiq66v9AHgiS6aF6ckZh4BkLQHjcSIpLUo616NpFRLXSPpQtvj53Tc1RLACzW+BetUvPbqoe5cTUlMfVXSD4H3AVtTpgP2SNJitd/RlOTPBbVpPLBfXZB+YeCLvQzV4/vtie2JdX2wwyQdSJnuuDVlofeuYt693ucyynNvQVlT6+pu+v8HJUm1ALA3ZcrkCbX5LOD/JH2Msi7YN4Ebbbevz9X65+tM4FuSPk3ZdXFbSgVhRERHhq84fI6tz5edXCMiIiIi5qy5XdGF7XGt3fjazt8M/JCy4PlDwLqU3feo0/9GA9+3fYPt24EDgZMlLTKXQr+Isoj9bZRpezNomxrYHdvPURaq3xJ4FPgpsGtXyZqGH0uaSnkXx1Cq4f6rMf3xZMpC6/cAFwOn9hJDt++3Q6Moi9A/DhxCF2usNTxF+X3uBaYARwKfrbsgdmUXStXYw8BmwAfrWmrYfoSyscDhlATphsCnWhdKOlDShY2x9gZeX8f6Xb1vKroiIiIiIiIi5gMqG+rNxgGlGZT1lY6zffBsHTxiFtQpjddSKuD2tn1CT/1HjBjhcePGzY3QImIe0aq4mtMVXdnRNSIiIiL6y8iR5e/Ysf0ZxayRdJ3tEV21zfapi7YXnd1jRswOtRJwaH/HERERERERERFzxlyfuhgRERERERERETEnzJOJLkmWNF3S4XPxfmvOgXEPlTR6do87N0m6R9Lm/R3H7CLpfyRNm1O/eURERERERET0n3ky0VWtZ/sgAElr1MTEtPq5p+56OGBJGinpvsbxwpLOlHSlpE53c5xnSRoq6beSJkuaKuk2SV/rpu/Gjd92WiMR9bFGnzdLOq+O9aikI7sZay1J50h6RNLjki6SNKzVbvs3tofM/ieOiIiIiIiIiP42Lye6ujK0Jik+Dhws6YP9HdDsUHeOPJOyftSHbD/VzyHNDkcDQ4B1gKUou06+ZrdNANuX2x7S+gAfAaYBf4KSBAT+DPwVWBFYhbILZ1eGAucCw4AVgGuAc2bTM0VERERERETEPGy2L0Y/N9geJ+kmYDglAYKk04GNgdcDNwCftX1TbTsBmAG8BXg3cD2wq+2JjWE3l3QhsBwwBtjHtiW9BfgVsB5g4CLgc7an1LFXAn4EbEJJzhxt+7hOn0XSYsDZdewP236mnn83cBTwNmAi8AXbY2vbWOBy4APAfwD/AEbZflTSGsDdwO7At4HFakyH12sXAL4K7ElJCl0C/K/tx2v7LsB3KEmqoxpxrgjcBaxq+7F6bn1KMmol28+3PdoGwDdsP1GPb62fTuwG/MH29Hq8O/CA7aMafW7s6kLb11CSW624jwa+IWnZVtydmvDYhJd3SIuI+cP4yeMZvuLw/g4jIiIiIiJm0kCr6AJeTgK9A7ijcfpC4K3A8pRE1iltl+1ESfwsB4zvov0jlOTMesAngC1atwO+C6xEqU5aFTi0xrEA8EdKYm1lYDPgi5K2oDOL1LhnANs0klwrA+dTEk7LAF8BzpD0hsa1o4A96vMuXPs0bUSpatoM+Kakder5fYHtgE3rMz0B/KTe923Az4BdatuylOopbE8GxtZ307Iz8PsuklwAVwGHS9pD0ls7fB+txN/HgRMbp98N3CPpwjptcaykdTscchNgcl+TXBExfxq+4nBGrTuqv8OIiIiIiIiZNNAquh6t0/wWBX5IqYQCwPZvW98lHQo8IWkp20/W0+fbvqy2HwQ8KWlV25Nq+/dqldYUSX+jVIv9yfYdvJJQe0TSUcAh9XgD4A22v1WP75L0K+BTlMqv3iwBvAfY0fazjfM7AxfYvqAe/1nSOGArXkkAHW/7tvo8p1GmBjYdVhNnN0i6gZLAuwX4DKVa7b7Gu7q3VnJ9HDiv8Z4OBvZpjHkiJVH2M0mvA3bs4r4tnwe+VK//paSJwOdtX9jLO/kY8ChwaePcKsD7670uAb4AnCNpbdvPdTeQpFUoSbwv93LPLg1bdhhjdx87M5dGRERERERERD8YaBVdy1Gm1H0FGAksBCDpdZK+J+lOSU8B9zT6t7QSWtieBjxOqVpqmdz4/nS9D5KWl/R7SffXsUc3xl0dWEnSlNYHOJCyNlQnHqUkxU5sqwJbHdihbdyNgDf2Fm8H7asDZzXGvQV4sca8Eq9+T9OBZiXUOcDbJL0Z+CDwZJ0q+Bq2n7F9hO31KZVhpwGnS1qmm3fRshtwkm03zj0DXGH7wprY+kEdc52uBgCo1W8XAz+1/bte7hkRERERERERg8BAS3Rh+0XbP6RM99u7nh4FbAtsTln4fI16Xo1LV219kTSEMiXwgQ5u+V3K+ln/YXtJSrVVa9xJwN22hzY+S9jeqg/PcyZlvaw/SHp/Y9yT28Zd3Pb3Oh23B5OALdvGXtT2/cCDvPo9LUZJKLVinUFJWO1Emd54cofP+BRwBLA48Kbu+klalZLAPKmt6UbKb9ARSUtTklznttYmi4iIiIiIiIjBb6BNXWz6HmVK3M8pUwCfpVQfLUZJqrTbStJGlIXKvw1c3Zi22JMlgCcpUxpXBvZvtF0DPCXpa8BxwHOUKqPX27620wex/bu6s+A5krakVI1dW6u8/kKpXHs3cEdryuEs+Dll7azdbE+slU/vtX0O8Afg6sZ7+havTYaeVD/LAwd1d5M67fFPlPXLFqBMN5wCTOghtl2Av9tu351xNLCfpM2Bv1GmTz5KqUZrv++SlGmjV9o+oId7RUT0i/GTx2eji/nQqHVHsdf6e/V3GBERERGD3oCr6Go4n7KQ+p6UxMtE4H7gZspC6O3GUNbWehxYn1KV1InDgHdSkl3nA2e2Gmy/CGxNWc/rbkry5deUqrI+sX0isF+9xxspFWoHAo9QqrD2Z/b8XscC5wIXS5pKeVcb1hhuAj5HeVcPUt7vqxJrtq8EXgKut31PT48EHE95Jw9Qpjp+uE4b7c6uvHoR+tY9J1Aq6X5eY9qWsnj/cwB1kfoDa/ftKWun7SFpWuOzWg/3jYiImGPGTx7PmH+N6e8wIiIiIuYLevVSSPMGSTMoFVrH2T54Nox3AnCf7W/M6lgBkv4KjLH96/6Opa8k7QEcTdnQ4G227+qu74gRIzxu3Li5FltEDH6tSq5sdDF/ye8eERER85KRI8vfsWP7M4pZI+k62yO6apsnpy7aXrS/Y4iuSdqAUuG2bX/HMjNsH0+pNIuIiIiIiIiIQWYgT12MuUzSiZQ1w75oe2p/xxMRERERERER0TTXE12SLGm6pD7vhifpJkkj6/dDJY2u39eo43ZZoWZ790xbnHW2d7O9lO0T+juWmSXpf+qaXZa0Zn/HExERERERERGzT39VdK1n+yB4VZLq+mYHSctJek7SPa1ztt9ue+zcDbXvJG0h6TJJUyU9IulSSdv0d1yzi6QTJH2n7VyPyUZJn5D0d0lPSxrbRftwSdfV9uskDW9r/5KkyZKelPRbSYv0EF+3Y9n+je0hfX7oiIiIiIiIiJjnzUtTFxeX9I7G8SjKToZzVHeJmVkY7+PA6ZSdIFcBVgC+SdmdcZZjm93xzkWPA8cA32tvkLQwcA4wGliasvPiOfU8krYADgA2A9YA3kzZDfM1ehsrIiIiIiIiIgaveSnRdTKwW+N4V0qy6GWS7pG0eW8DSdpD0i21ououSZ9ptI2UdJ+kr0maDBwvaWlJ59Xqqyfq91Vq/x0kXdc2/n6Szu7ivgKOAr5t+9e2n7T9ku1Lbe9Z+7zl/9u70yi7qmrt4/+HXiAxAtI3UdCIdKVE0StoaFRAFOy4GBGCIjavV70qVxoRUBHsUFFUxIY2CAooiigIRBARCBhAmiggGJrQBBKS0Ifn/bDWgU1xqiqVVHKqKs9vjDOqzl5rrz33qTO8l5m55pZ0kaQZkh6QdKqkUd3u8fOSrgPmStqoVkp9SNJ/gIvqvF82KpwukbRJY42dJd1Y7/8uSZ9rjO0qaYqkhyXdKmnHenxtSedIelDSLZI+3Nfn3B+2/2T7DODuNsPjKA9G+I7tx20fAwjYro7vDfzU9g22HwK+DEzo4VJ9rRURERERERERw9Rgqg46BbhU0gHAy4ERwBXAgiRc7gN2AW4D3gicJ+kq263tkWsCqwAbUJJ9K1KexLc7sDTwM+D7wG7AOcBxkja2fVM9f0/gOVv3qjHAesCveolNwJHAJcBI4EzgMODTjTnvA94GPECpCAN4E7Ax8HR9fx7wQeAJ4GvAqUBri95Pgd1tXyrpRcBLACS9lpI8fA9wIbAW5XMGOA24AVgbeAVwgaTbbF/Yy70MlE2A62y7cey6evwP9edvGmPXAmtIWtX2jH6uNd+mzpj6zCPhIwba+M3Gs9+W+3U6jIiIiIiIiGFlMFV03QlMBXagVPCc1Pv0ntk+1/atLv4MnA9s05jyNHBorfh51PYM22fafqQ+TfAISmIJ248Dp1OSW9TKqdHA79pcetX6855eYrvF9gX12vdTKsDe1G3aMban2X60ceww23Nbx2z/zPbsGt9hwBaSXljnPgm8UtJI2w81EnwfAn5Wr/+07bts3yxpPWBr4PO2H7M9BfgJ8IGe7gP4nKSZrRclmbSgVgZmdTs2i2eTcN3HW7+P4Pn6Wiui46ZMn8LE6yd2OoyIiIiIiIhhZzBVdEFJbk0A/otSifWyBVlE0k7AoZTKsFbF1vWNKffbfqwxf0Xg28COlL5OACMkLW17HqXP02mSvkBJ/pxRE0zdtaqL1qKH/mKSVgeOoSTeRtT4Huo2bVqbU585JmlpSjLuvcCLebbKazVKUufdwBeAo+oWyANsX06pNvt9m7XXBh6sSb6WO4Cx7e6h+mbzSZaSRrPgPdXmUKrbmkYCs3sYb/0+m+fra635NmbVMUyaMKm/p0X0KZWCERERERERi8ZgquiCso3vbcBttu9YkAXq0/jOBL4JrGF7FCW5o8Y0dzvts5Rth1vZHklJstE6x/bfKFsEt6E0yT+5h8tPpSSk3t1LiEfW629er7Vnt9jaxdf92HhgV0r12wspFWbNeK+yvSuwOvBr4Iw6Pg3YsM3adwOrSGpWPa0P3NXLfQykG4DNa4+zls3r8db4Fo2xLYB722xbnJ+1IiIiIiIiImKYGlSJLttzKU3D912IZZYDlgfuB56q1V1v6eOcEcCjwExJq1Cqwbo7idK36ynbf2m3SO0L9RngkNoQf6SkpSRtLenHjWvNqddaB9i/n/fXWuNxSgXZisBXWwOSlpP0fkkvtP0k8DAwrw7/FNhH0vY1rnUkvcL2NOCvwJGSVpC0OWWb46kLEFtbkpaWtAKlinCpep1l6/CkGuMnJS0v6RP1+EX150nAhyS9svYc+wJwQg+X6mutiIiIiIiIiBimBlWiC8D2ZNu3LsT5s4FPUqqYHqJUP53Tx2nfAV5Aaf7+N9o3LT8Z2JSeq7la1/8V8N+URvF3A/dSGte3mqkfDryassXwXOCsvu6pjZMoWwvvAm6sMTd9ALhd0sPAR6n9xWxfCexD2aY5C/gzpSE/lAb4o2vMZ1N6mF2wALH15AOUZOIPKZVxjwLH17ieoDT+3wuYSfnsdqvHsf0H4OvAxfW+76CRjJR0nqSD5metiIiIiIiIiBi+9NyH0y2GC0qPUaqRjrF9yGK9+EKQ9ALK0xxfbftfnY4nFoykVqJvBeCVtm/rae7YsWM9efLkxRZbLDlaPbrSA27Jk7/9kil/94iIiBhMxo0rPydN6mQUC0fS1bbb9hVf7M3oba+wuK85QD4GXJUk19Bm++fAzzsdR8SU6VPSlH4JNGX6FLrW7Op0GBERERERw9Zge+rioCTpdkqj9906HEpERAxhXWt2MX6z8Z0OIyIiIiJi2Eqiaz7YHt3pGCJieOlasyvbmCIiIiIiIgbYoGtG3ymSLGmupCPmY+42kqYujrg6QdLo+nkMq0SopJdLmiNpnqSFebJnRERERERERAxCSXQ91xa2D4bnJHvm1Nftkg4AsH2p7TELcgFJh0k6pfF+HUk3SzpGkgbmNjpH0qTuSSRJ4yTd2cs5G0u6SNIsSbdIeme38e3rZ/SIpIslbdDLWqtIOrsmLe+Q9MweIdv/tL0ycOlC3GJEREREREREDFJJdPVtVE2OvA/4oqQdB2rhmrC5BDjH9ie9uB+BOQjUqrHfAL8DVgH2A06R9PI6vhpwFnBIHZ8MnN7LkscCTwBrAO8Hfihpk0V2AxERERERERExaAyrrWmLku3LJd0AbCrpMeAU2+sC1EqvDwOrA9OAg22f3dt6kjYELgJOsn1I4/gHgf2BNYErgf1s31HHTHn642eB1YCJwCdsW9IEYF/gb8CHgJnAx22fV899IXA0sDPwNOXJg4fanidpaeBrwATgYeBbjXjeCxxge8vGsc8C29geiOb8rwDWBr5dE30XSboM+AAlufUu4Abbv6zXPgx4QNIrbN/cXEjSSsC7gU1tzwH+IumcutYBAxBrRETEAsmTVgef8ZuNZ78t9+t0GBERETHAkuiaD3VL4X8BmwB/bzPlVmAbYDrwXkpF0ka27+lhyZdSKrmOtf3VxnV2Aw4C3g78i5KcOa1eu2UX4DXASOBq4LfAH+rYVsCJlCTYfsBPJa1TE0gnAvcCGwErUSqopgHHUZJ0uwCvAuYCZzaudw5wnKSNbd9Uj+0JfKWHe+uvdts1BWxaf98EuLY1YHuupFvr8Zu7nfdyYJ7tfzaOXQu8aUECmzpjav6jJBaJKdOn0LVmV6fDiIhYYk2ZPgUgia6IiIhhKImuvj0AmJLEOsD2hZLGNSe0qo2q0yUdCLyWsiWvnU0pVVXdt+B9BDiylVCS9FXgIEkbtKq6gKNszwRmSroY6OLZRNcdto+v554I/ABYo1aC7UTZhvkoMFfStynJsOOA3YHv2J5Wzz0SGFfv7XFJp1OSWwfXbYCjKYmynhwj6ZuN98tQKszauRm4D9i/xrQtJTF1cR1fGbi/2zmzgBFt1lq5js3P3IiO6Vqzi/Gbje97YkQMG3nS6uCSf8iKiIgYvpLo6ttqtp/qbYKkvYDPUBJAUBIuq/VyyjmU5M5Fkt7YSGJtAHxX0rcacwWsA7TmTG+MPVKvRfcx24/U3vYrU3pbLQvc0+h3vxSlogvK1sFpzy7zzLVaTgROk/QFyjbAM2w/3sv9fdL2T565gZIYPKXdRNtP1kq27wGfp/TgOgNorT+HUr3WNBKY3Wa5/szt05hVx+Q/SiIiIiIiIiKGkCS6FlJtKH88sD1wee15NYX2W/KeYfszkpbn2WTXXZRk0xG2Tx3gMKdREkc9Je3uAdZrvF+/W6x/k/QEZXvm+PoaMLavo7G9UNJfKck1gBuAvRtjKwEb1uPd/RNYRtLLbP+rHtuih7kRERERERERMczkqYsLbyXK1sb7ASTtw7P9pfryCUpD+gslrQH8CDiw9ZRASS+szeAXSu0Vdj7wLUkjJS0laUNJreTSGcAnJa0r6UW0b9x+EvB94Cnbf1nYmJokbS5pBUkrSvocsBZwQh0+m/IAgHdLWgH4InBd90b09T7nUp7Q+CVJK0l6A7ArcPJAxhsRERERERERg1MSXQvJ9o2UpxReTmn2vhlw2Xyea0pfriuBPwGXUp5++AtJDwP/oPTWGgh7AcsBNwIPAb+iJJSgVKT9kdK4/RpKsqi7kykJvEWRNPoAparsPkpl3JtbWyNt3095kuIRNe6tgD1aJ0o6SNJ5jbU+DrygrnUa8DHbqeiKiIiIiIiIWAKo5FpC0mOU7X3H2D6k0/EMNpJayaNXN7YFDimSXgZcRUn4fdz2Cb3NHzt2rCdPnrw4QouIiGGs1fg8fR8Hj/xNIiJiSTZuXPk5aVIno1g4kq62PbbdWHp0VbZX6HQMg9zHgKuGapILoMY+qtNxRERERERERMSikURX9EnS7ZTm+rt1OJSIiIiIiIiIiB4l0RV9sj260zFERERERERERPQlzegjIiIiIiIiImJYWOITXZIsaa6kIxZyndF1rVTJDWKSTpD0qKQ7Ox1LRERERERERAysJT7RVW1h+2AY/AkrSa+V9HtJMyU9KOlKSfss5JoTJP1loGKsa24i6XxJD9VYr5a0cw9zx0l6WtKcxmvvxvgqkk6X9EB9nSpp5HzE8PP6t9yodcz2BGCngbjHiIiIiIiIiBhcBmUyJ9qT9HrgAuDLwF7ADODVwOeBny/iay9te14/Tvkt8ENgl/r+NZSG9j252/a6PYx9BXgR8NK6xpnAYcBneol3a2DDfsT7PFNnTH3m8eMRw9n4zcaz35b7dTqMiIiIiIiIhZaKrn6QdLukHRrvD5N0Sg9z313nbyppQ0kXSZrRqEga1Zj7eUl3SZotaaqk7XsI4RvAiba/ZvsBF1fb3r2u8yJJv5N0f62k+p2kdRvXmSDptnqdf0t6v6SNgR8Br6+VVDPr3BMk/bBWj80FtpW0saRJtULrBknv6OHeVwNeAhxv+4n6usz2glaNvQT4te2Hbc8CzgY26Wlyrcb7HvCJBbxexBJjyvQpTLx+YqfDiIiIiIiIGBCp6FoE6lbCg4EdbN9St84dCVwCjOTZiqRPSxpDSci8xvbdkkYDS7dZc0Xg9cAhvVx6KUpl1+51jZ8B3wd2k7QScEy9zlRJawGr2L5J0keBfW1v3W298cDOlKqslYC/1zXfAmwN/EbSWNtTu503A7gFOEXST4DLbd/b22cGrC7pXuAR4NfAF2zPrWPHAh+XdFp9/27gnF7W+l/gEtvXSb0VkfVuzKpjmDRh0gKfHzEUpGoxIiIiIiKGk1R0DbxPA/sD42zfAmD7FtsX2H7c9v3A0cCb6vx5wPLAKyUta/t227e2WfdFlL/XPT1d2PYM22fafsT2bOCIxnUAngY2lfQC2/fYvqGPe/lNrcR6GugCVgaOqhVaFwG/A97XJg4D2wK3A98C7pF0iaSX9XCdm+v6awHbAVtSPqOWa4DlKAm0GZTP7AftFpK0HvAR4It93FtEREREREREDDNJdA28/YFjbT/zVD9Jq0v6Rd2e+DBwCrAalCQYJTl2GHBfnbd2m3UfoiSq1urpwpJWlHScpDvqdS4BRtX+WnOB/wY+Skk8nSvpFX3cy7TG72sD02rSq+UOYJ12J9q+0/YnbG8IbADMBU7qYe502zfaftr2v4H/A97TmPJL4J/ACEpF3K2Uz7Cd7wBfqlscIyIiIiIiImIJkkRX/8wFVmy8X7PNnLcAX5D07saxIwEDm9seCexJozG77Yl12+AGdd7Xui9q+xHgcsq2vZ58FhgDbFWv88Z6XHWNP9p+MyVZdjNwfGv5HtZrHr8bWE9S8zuzPnBXL/G0Yp9G2X64aV9zG9dt7jncAjjO9lzbcyg9xdo+wRHYHviGpOmSptdjl0saP5/XjoiIiIiIiIghKomuni0vaYXGaylgCrCHpGUljeW5VUctNwA7Asc2mrWPAOYAMyWtQ6n6AkDSGEnbSVoeeAx4lLI1r53/AyZI2l/SqvX8LST9onGdR+t1VgEObVxnDUnvqL26Hq/xtK5zL7CupOV6+TyuoCT6/q/e/zjg7cAvuk+sTfEPl7SRpKVqc/oPAn9rt7CkcZLWV7EecBTwm8aUq4B9Jb1A0guA/YBre4jz5ZTEWFd9UeM8u5d7i4iIiIiIiIhhIM3oezan2/s3UxrBn0bZRvhnYCKwSvcTbV8raRfgXElPAodTtu3NojRpP5nSMB1Kf66jgI2BJ4G/UhI5z2P7r5K2q+t9QdI84F+Uaiko2/YmAg9QKrC+BexWx5aiVHydTKmYmgJ8vI5dREnQTZf0tO3V2lz7iZq4+wFwIKWSay/bN7cJ9QlgNPAnyhbNOcDFwP+0uy/g1cCplD5kMyjN6A9qjH+Q0kj/Tkql15XAhNagpDnATrYvtX1fc+HajP4B24/2cO2IJd6U6VPSlD5iEZoyfQpda3b1PTEiIiIiFloSXaW66WpJx9g+xPbtPHfbXHdbtTvY/Tzbk4E1GlO27HbKt+q864DXzm+wtq8Eduph7G5gXLfDx9Wf9/DcxvTN854A3tbt2IQ2827oaY1u8+YCe/c1rzH/aJ7bfL77+L8pVVk9ja/cy9hz/paSfgq8F7iv/RkREREDq2vNLsZvlh30EREREYvDEp/osr1Cp2OIxcf2h4APdTqOiMGka80uJk2Y1OkwIiIiIiIiFtqQT3RJMvAI8B3bBw/QmpOAU2z/ZCDWi8FD0gmUp0/OsL1uh8OJiIiIDsm27cVr/Gbj2W/Ltt05IiIiBtRwaUa/RSvJJWm0JEuaU1/3SvqdpDd3OkgASWtJ+qmkeyTNlnRzbdy+UqdjGwi1sfydbY5PkrTvfJz/8/r326jN2CqS7pf0l17Of5ukv0iaWZ+8eLykEa3xuiWz7dbPiIiIiBh4U6ZPYeL1EzsdRkRELCGGfEVXL0bZfkrSmpQKnrMlfcL2CZ0KqD4J8XJKw/nX2769PmXwc8CGwHX9XG8Z20813guQ7acHMOzFRtLWlM+hJ18DbqL3BO0Lga8Al1Aa/U8EvgF8dIDCjIiIiGEg27YXn1TORUTE4jRcKrp6ZHu67e8ChwFfk7SUpP0lndmcJ+l7kr7T/XxJG0q6SNIMSQ9IOlXSqMb47ZI+J+k6SbMknS6pp75fnwFmA3vW5vXYnmb7U7UpPZK+K2mapIclXS1pm8a1DpP0K0mnSHoYmFArpY6QdBllC+dLJe0j6aZaMXabpI801litVrjNlPSgpEslLVXH1pN0Vq2amiHp+/X4UpK+IOkOSfdJOknSC/v/1+iZpGWA7wGf6GH89cCmwM97W8f2RNt/sP2I7YeA44E3DGSsERERERERETE4DeeKru7OolT2jAFOAQ6TNMr2zJpk+W/ab2kTcCSlQmh7UygyAAAgAElEQVQkcCYlafbpxpzdgR2Bx4DLgAnAj9qstQNwVh8VV1cBXwJmAZ8CfilptO3H6viulKcG7kWpWNoT+ECNfWqNdwywC3Ab8EbgPElX2b4G+CxwJ/Diut7rAEtaGvgdcFFdbx4wts6ZUF/bUp5WeBLw/TpvoPwvcInt60ph2rNqbMcCHwY26+e6bwRuWJCAps6Ymn+BjGFvyvQpdK3Z1ekwIiIiIiIiBsSwr+hquLv+XMX2PZTE1XvrsR2BB2xf3f0k27fYvsD247bvB44G3tRt2jG277b9IPBboKf/alwVuKe3IG2fYnuG7adsf4uSzBrTmHK57V/bftr2o/XYCbZvqOc8aftc27e6+DNwPtCqDHsSWAvYoM691LaB1wJrA/vbnmv7MdutXljvB462fZvtOcCBwB41QdjO2rVi7JkXsHVP91y3b34E+GIPUz4JXNHu79Ob2pdt717WjVjida3ZxfjNxnc6jIiIiIiIiAGxJFV0rVN/Plh/ngh8jLK1bU/g5HYnSVodOIaSKBpBSQ4+1G3a9Mbvj1ASRu3MoCSZeiTps8C+dQ1TqshWa0yZ1ua05xyTtBNwKPDyGu+KwPV1+BuUirTza+XUj20fBawH3NHs+dWwNnBH4/0dlO/OGsBdbebf3f2JhvVJlj35DvAl27O6D0ham5Lo2rKX859H0uso/bneY/uf/Tm3ZcyqY9K7IyIiIiIiImIIWZIqut5J2XY3tb7/NbC5pE0p2/xO7eG8IykJp81tj6QkxdTD3L78CXhnqydWd7Uf1+cpWyFfZHsUZQtj83puc+ozxyQtT9le+U1gjbrG71tr2J5t+7O2Xwq8HfiMpO0pybL1e6jSuhvYoPF+feAp4N6+b3m+bA98oz4lsZU0vFzSeEql2VrAjXXsu8Br69yl2y0m6VXAOcAHbV84QDFGRERERERExCA37BNdktaQ9AlKhdOBrf5YtefVryhVP1fa/k8PS4wA5gAzJa0D7L8Q4RxNqdA6UdIGNb51JB0tafN6raeA+4FlJH2xzu+P5SjbHe8HnqrVXW9pDUraRdJG9QmND1N6cc0DrqRsqzxK0kqSVpDUauJ+GvC/kl4iaWXgq8DpPVR/LYiXA1tQtny2tn2+HTgbOA8Y3Rj7IvB3oMv2vO4L1cTlH4D/sf3bAYovIiIiIiIiIoaA4ZzomilpLmXL3s7Ae23/rNucEynNzdtuW6wOB15Nqaw6l9LUfoHUHl7/RemTdYWk2cCFde1bgD9SEjv/pGwPfIz2WxV7u8Zsyla/MyhbLMdTqptaXkapLJsDXA78wPakmjR6O7AR8B9Kw/r/ruf8jPIZXQL8u8b1P/2Jq4+Y76tPx5xuu1XR9YDtR2tvtObYLODJxjwkzWk8nfKzlEb7P63H50haoGb0ERERERERETG0qPQhH7okPQY8TmkIf0g/z10fuBlY0/bDiyK+GFwk/ZTyEIL7bG/U29yxY8d68uTJiyewiIiIWGxaT1VOL87FI593RMTgMm5c+TlpUiejWDiSrrY9tt3YkG9Gb3uFBTmv9sn6DPCLJLmWHLY/BHyo03FERERERERExMAb8omuBSFpJUoj9TuAHTscTkREREREREREDIAlMtFley6wcqfjiIiIiIiIiIiIgdOxZvSSLGmupCM6FUNvJN0gaVyn41hUJN0uaYdOx7E4SdqhNqd/ekm794iIiIiIiIglQaefuriF7YMBJI2uya9zmxMknSLpsMUdmO1NbE/q73mSxkm6s/F+OUlnSbpM0sgBDbIDJB0m6ZQ2xy2pbXN3SdtKuljSLEm3txn/sqTrJT3V7m8tabykO2pi9NeSVuklvtH1Wo9IurmZ0LL9J9srU54qGRERERERERHDTKcTXe28TtIbOh3EQJC0PHAWMAp4yxLc9H4u8DNg/x7GbwH+Dzi3+4CkTYDjgA8AawCPAD/o5VqnAX8HVgUOBn4l6cULHHlEREREREREDBmDMdH1deArPQ1K+rCkWyQ9KOkcSWs3xl4h6YI6NlXS7o2xEyT9QNJ5dfvaZZLWlPQdSQ/V6p9XNeY/s7VP0lKSDpB0q6QZks7oraqonrMi8FtgWeBttS8Ykl4n6a+SZkq6trk9UtKkWt10maTZks6XtFoda1W87S3pP5IekHRw49xeY5T0gVoVNaPbeWvW6qdVG8e2lHS/pGV7u8f5ZftK2ycDt/UwfqLt84DZbYbfD/zW9iW25wCHAO+SNKL7REkvB14NHGr7UdtnAtcD7x6I+4iIiIiIiIiIwW0wNqM/FvikpB1s/6k5IGk74EjgLcANwDeBXwBvrE9SvAD4IrATsDlwvqQbbN9Ql9gdeGs99/fA5cChwGeBw4GjgW3bxPRJYDfgTcD9wDE1zvf1cA/LA+cBs4D32n68xr8OpWrpA8AfgO2BMyW9wvb99dzxNf5pdY3PAQc01t4aGAO8HLhS0lm2b+otRkmvBH4I7AxcUT/DdQFsT5c0qX42P6zX2BP4he0ne7i/xWkT4K+tN7ZvlfQE5f6vbjP3NtvNhNm19Xi/TZ0xlXEnjFuQUyMiYpAav9l49ttyv06HERERERGLyGCs6HoMOIL2VV3vB35m+5qaPDoQeL2k0cAuwO22f277KdvXAGcC72mcf7btq20/BpwNPGb7JNvzgNOBV9HeR4CDbd9Zr3sY8B5JPSUKRwCvB05sJbmqPYHf2/697adtXwBMpiSgWn5u+5+2HwXOALq6rX14rVa6lpLE2WI+YnwP8LtaFfU4pSrq6caaJ9bYkLQ0JYF3cg/3BrB7rUh75tXL3IW1MiVh2DSL8hkvzNyIiFjCTJk+hYnXT+x0GBERERGxCA3Gii6A44H9Jb292/G1gWtab2zPkTQDWAfYANiqW9JlGZ6bsLm38fujbd6v3EM8GwBnS2omh+ZRekbd1Wb+A5QKq5MkzbH9x8Y67+12X8sCFzfeT2/8/kibmHoa7y3GtSkVYgDYnls/t5bfAD+S9FJKpdQs21e2ua+WM2zv2Twgyb3MXxhzgO5N/EfSfptjf+b2acyqY5g0YdKCnBoREYNQqnQjIiIihr9Bmeiy/aSkw4EvU7YZttxNSegAULcrrkpJNk0D/mz7zYsgpGnAB21fNr8n2D6rNqP/laR32L64rnOy7Q8vzhgl3QNs3Hi/IuVza8X6mKQzKBVzr6D3aq7F7QaerVqjJuOWB/7Zw9yXShrR2L64BZB/vo+IiIiIiIhYAgzGrYstJ1MSGjs2jk0E9pHUVZNIXwWusH078Dvg5bXp+rL19RpJGz9v5f77EXCEpA0AJL1Y0q59nWT7NOATwG/qkyRPAd4u6a2Slpa0gqRxktZdxDH+CthF0taSlgO+xPP/9icBE4B31DgHTG2UvwKlek31vpdrjC9bx5cClqnjS9fhUymf2TY1sfkl4KxufbgAsP1PYApwaF3jnZRebWcO5P1ERERERERExOA0aBNdtW/WocAqjWMXUvpLnQncA2wI7FHHZlOa1O9BqfyaDnyNkixbWN8FzqE0t58N/A3Yaj7v40RKs/tzgbWAXYGDKA3jpwH7MzB/hx5jrM34/x8lUXgP8BBwZ7c4L6P07bqmJg4H0hspW0N/D6xffz+/MX58PfY+4OD6+wcasX+UkvC6j9Jv6+OtEyX9SNKPGmvtAYyl3ONRwHsajf4jIiIiIiIiYhiTvahaK/VxYekx4HHgGNuHdCSIeA5JFwETbf+k07EsCpK2pyRJlwd2rttJezR27FhPnjx5scQWERGLXqtHV/ovRr4Li1c+74iIwWXcuPJz0qRORrFwJF1te2y7sY716LK9QqeuHc8n6TXAqykVZ8NSrQgc1ek4IiKic6ZMn5Km9MGU6VPoWrP7g60jIiJiOBiUzehj8ZJ0IrAb8Kl2va8iIiIihpOuNbsYv9n4ToexRJly1HcYd0Kno4iICIApU6BrGP97TxJdge29Ox1DRETE4tC1Zle2T0VERMQSrasLxg/jf+9JoisiIiIiIhaprgM+nSRzREQsFoP2qYsDRZIlzZV0RKdj6YukcZLu7Htm23MtaaMBjucwSaf0Mn6DpHEDec1FTdLh9ftgSUn0RkRERERERAwjwz7RVW1h+2AASaNrkmNOt9d/D9TFJG3TWHdum+utP1DX6iTbm9ie1G5M0rqSzpT0gKRZkq6XNKGntSTtLukmSbMl3ShptzZzlpN0c2/JwB7+vs881dP2ocAm/brRiIiIiIiIiBgSluSKllG2n1oUC9u+FFgZSuIF+PeivN4gdTJwLbAB8DiwGbBmu4mS1gFOoTzx8Q/AzsAvJY22fV9j6v7AfdTPtg8L/XlPnTE1T+aKiBhG8qS9iIiIiOFvSanomi+SXidpuqSlG8feKem6+vtrJV0uaaakeyR9X9Jy/bzGPo3KpdskfaSXuZ+s1U3rzue1d5D0L0kPSTpWkuo6G0q6SNKMWmF1qqRRjet8XtJdNaapkrZvrLmcpJPq2A2SxjbOu13SDj2E/xrgBNtzbT9l+++2z+th7rrATNvnuTgXmAts2LjWS4A9gSN7+rwiIiJ6kyftRURERAx/S3JF1/PY/pukucB2wAX18HhgYv19HvC/wGRKcuY84OPAd/pxmfuAXYDbgDcC50m6yvY1zUl1u907gTfZvl/SGvNx7V0oCaaRwNXAbykVUqIkiC6pY2cChwGfljQG+ATwGtt31wq0pRtrvgN4F7AP8BXg+8Dr5uM+/wYcK+l7wF9t/6eXuZOBmyS9AzgXeDulCuy6xpzvAQcBj87HtQHukGTK33F/2w/M53nPGLPqmDRNjYiIiIiIiBhCluSKrgdqdVTrtXE9fhrwPgBJIyjb6E4DsH217b/VCqXbgeOAN/XnorbPtX1rrVz6M3A+sE1jiiQdDbwV2Nb2/f249lG2Z9ak0sVAVz33FtsX2H68rnd049x5wPLAKyUta/t227c21vyL7d/bnkfZjrjFfN7qe4FLgUOAf0uaIuk1PXwm84CTKAnFx+vPj9ieWz+QdwLL2D57Pq77ACXZtwGwJTACOHU+Y46IiIiIiIiIIWxJTnStZntU43VTPT4ReJek5SmVTNfYvgNA0ssl/a5ub3wY+CqwWn8uKmknSX+T9KCkmZREWnONUcB+wJG2ZzXOm59rT2/8/gjP9glbXdIv6vbEhyn9sFaDkgQDPk2p8Lqvzlu7lzVX0Hw8rdD2Q7YPsL0JsAYwBfh1aztlt89kB+DrwDhgOUoS7ieSuiStVMf+p69r1uvOsT25JgTvpVSrvUXSyPk5PyIiIiIiIiKGriU50dWW7RuBO4CdeO62RYAfAjcDL7M9krKV7nmJm57U5NmZwDeBNWyPAn7fbY2HKFsQfy7pDQN07SMBA5vXc/dsnmt7ou2tKVVQBr42v/c0P+q2wW8CawOrtJnSBVxSE1RP274KuALYAXgZMBq4VNJ04CxgrZrwGz0/l68/5/vvFBERERERERFDUxJd7U0EPknpofXLxvERwMPAHEmvAD7Wz3WXo2wTvB94StJOwFu6T7I9CXg/cLakrQbg2iOAOcDM+oTD/VsDksZI2q4m4R6j9MCa18/7eh5JX5O0qaRl6hbQjwG32J7RZvpVwDaSuuq5r6Js57wO+AewHiUZ1gXsC9xbf5/W5rpb1XtaStKqwDHApGZ1XEREREREREQMT0tyomumpDmN12caY6dRttFd1K2J+ecoVV6zgeOB0/tzQduzKQm0MyiVW+OBc3qYewGlAfw5krZcyGsfDrwamEVp9n5WY2x54ChKb6vpwOqUarGFtSJwNjCT0nh/A0pj++epvcoOA34laTal6u2rts+vWxCnt17Ag8DT9f08gPo0yPfX5V5KacA/m5Ike5zacy0iIiIiIiIihjfZ7nvWECbpMUqy4xjbh3Q6nugsSYcCn6Ek+FZqJcvaGTt2rCdPnrzYYouIiIgYjsadMA4gT7OOiIgBI+lq22PbjfXZVHyos71Cp2OIwcP24ZQKt4iIiIiIiIgYZpbkrYsRERERERERETGMDMlElyRLmivpiE7HMpxJOkzSKZ2OY6BIWr72Y3tS0lc6HU9EREREREREDKwhmeiqtrB9MICk0TX5dU1zgqTVJD0h6faORNgLSbdL2qHxfg9JD0l6UyfjGiiSPiTpZkmzJd0r6dz69MV2c1eRdLqkB+rrVEkjG+M/ljRV0tOSJvRx3eUl/UzSw5KmNx8yYPtx2ysDpw7UfUZERERERETE4DGUE13trCRp08b78cC/OxXM/JK0N3As8Lb6BMIhrSbrvgq8z/YIYGPKkyZ78hXgRZQnJm4IrEF5CmPLtcDHgWued+bzHQa8jPKUx22B/5O0Y//uICIiIiIiIiKGouHWjP5kYG9g//p+L+Ak4MOtCZLWBr4HvBGYA3zb9jF17AXAj4B3ANOBnwOftL1uHT+grrU6MA042PbZdWwCsC/wN+BDwEzg47bP6y1gSftRkkJvtT25HnshcDSwM/B0jeNQ2/P6uo6kScClwHbA5sDlwHjbD9Tx19W1XwncAXzK9qQ69hLgBODVdf2pjTjPBf5g+3uNY9cBX7T962639Rrgctt/B7D9IHBiLx/DS4Bf2364rns25W9APf/YevyxXtZo2QvYx/ZDwEOSjgcmAH+Yj3OfY+qMqc88JSiiP8ZvNp79ttyv02FEREREREQscYZbRdcpwB6Slpa0MTACuKI1KGkp4LeUCqF1gO2BT0t6a51yKDCaUln0ZmDPbuvfCmwDvJDy5L5TJK3VGN+KkhxaDfg68FNJ6iXejwFfBrZvJbmqE4GngI2AVwFvoSS35vc644F9KAm55YDP1ftfBziXUkG1Sj1+pqQX1/MmAlfXdb9MSRo2Y3rm85C0BeUz/H2b+7oCeKukwyW9QdLyvXwGUKrZdpH0IkkvAt4N9JogbKeeuzbl79tyLbBJf9eKWFBTpk9h4vUTOx1GRERERETEEmm4VXTdSUkA7UDZtnZSt/HXAC+2/aX6/rZa8bMH8Edgd+BjjWqgY2hsobP9y8Zap0s6EHgt8Jt67A7bxwNIOhH4AWUb3vQe4n0zcDFwfeuApDWAnYBRth8F5kr6NrAfcNx8Xufntv9Zx8/g2eqoPYHf224lpy6QNBnYWdLF9fPZwfbjwCWSftuI9TfAjyS9zPa/gA8Ap9t+ovtN2b5U0rso2w0/BSwj6cfA/rbntfkcrqEk5GbU9xfWe+qvlevPWY1jsygJz34bs+oYJk2YtCCnxhIsVYARERERERGdM9wquqAktyYA76NUeDVtAKwtaWbrBRxESRJBqQaa1pjf/B1Je0ma0jh3U0r1U8szCS3bj9RfV6ZnHwVeDvykUZG1AbAscE/jOsdRqrPm9zrNxNojjbENgPd2u/+tgbXqvT9ke27j3Dsa13mc0mdrz1oZ9z7KVtG2bJ9n++2UyrFdKX+TfXuY/kvgn5SE1EhK5dyCPO1xTv05snFsJDB7AdaKiIiIiIiIiCFmOCa6zgTeBtxm+45uY9OAf9se1XiNsL1zHb8HWLcxf73WL5I2AI4HPgGsansU8A+gt62JfbmPsn1yG56tYJoGPA6s1ohxpO2B2H43DTi52/2vZPsoyr2/SNJKjfnrdzv/ROD9NeZHbF/e1wVtP237QuAiSmKwnS2A42zPtT2H0idt5x7m9nathyj3sUW3tW/o71oRERERERERMfQMu0RXrUjajvbVQ1cCD0v6vKQX1F5em0p6TR0/Aziw9opah5LUalkJMHA/gKR96Dlx0594767x7ijp27bvAc4HviVppKSlJG1Yn2S4sE4B3i7prfXeV5A0TtK6NSk4GThc0nKStgbe3i3WyynN8b9FL9VcknaVtEf9HCXptcCbKA3u27kK2Lf+TV5A2aZ5bWO95SStQEkqLlvj7um7exLwhXrtV1AeHnBCXx9MRERERERERAx9wy7RBWB7su1b2xyfR0nedAH/Bh4AfkJpLg/wJUqfr38DfwJ+RamuwvaNlATP5cC9wGbAZQMU7zRKsus9ko6kPDlwOeBG4KEax1o9r9Cv6+xK2a55P6XCa3+e/R6MpzS6f5DSmL97jzPqsc3ofWvhQ5QE07+Ah+vcb9g+tYf5H6Q8BOBO4C7KwwAmNMbPBx4F/gv4cf39jQCS3i+pWbF1KGXr4x3An+t1+/3ExYiIiIiIiIgYemS70zH0m6THKAmoY2wfsgiv8zFgD9sDUU01LEjaC9jP9tadjqW/6tMf76X0QPu67cN7mz927FhPnjy5tykRzzPuhHFMmT6FrjW7Oh1KRETEoND6v4t5yE9ERAwUSVfbHttubEg+ddH2CotiXUlrUaqJLgdeBnwW+P6iuNZQJGlFypMUF+SJiB1XG+qP6nQcEREREUuSrjW7GL/Z+E6HERERS4ghmehahJajPOHwJcBM4BcM0aTOQJP0VuAsypbOiR0OJ2JQy79aR0REREREdEYSXQ21IftCN5gfjmz/kdKQPyIiIiIiIiJiUBqWzeh7IsmS5ko6YgHOvUHSuPr7YZLaNmOXdJCknyxkqLGISDq8fgcsKYneiIiIiIiIiGFkiUp0VVvYPhhA0uia8LimOUHSapKekHR765jtTWxP6mtx21+1vW9P45JGSvqOpP9ImiPplvp+tQW/pcGj8Zku0+34CZK+0st5K0r6gaQHJM2SdElj7DBJT9bPq/V6aS9rbS/pZkmPSLpY0gatMduHApss5G1GRERERERExCC0JCa62llJUnPL4njg3wN9EUnLARdSEi07AiOB/wJmAK9dgPWeV5EkaemFDLNTfgysAmxcf/5vt/HTba/ceN3WbpGaMDwLOKSuMxk4fdGFHRERERERERGDRbZuFScDewP71/d7AScBH25NqNVd+9r+U/NEScvWucsB7wMOAjayvWeb6+wFrA9sa3tOPXYf8OXGegfU664OTAMOtn12HZtQx66s8f5A0rrAo8AGwJuAXSUtD3wF2BCYBfzU9mF1jRWAnwA7AUsD/wJ2sX2vpFWAbwFvBV4A/Nn2bvW8DwOfpySP/gJ81PbdvX+s80fSGOAdwLq2H66Hr17A5d4F3GD7l3Xtw4AHJL3C9s39WWjqjKmMO2HcAoYRS6rWI9QjIiIiIiJi8UtFV3EKsIekpSVtDIwArujrJEkvAH4NPA7sbvuJPk7ZAfhDI8nVzq3ANsALgcOBUySt1RjfCriNkghr9RobX38fQUlCzaUk1UYBbwM+Jmm3OnfvuvZ6wKrARymJMigJvxUpFWerA9+u97kdcCSwO7AWcAfliZQDZau65uF16+L1kt7dbc7bJT1Ye6V9rJe1NgGubb2xPZfymWa7YiwWeYR6RERERERE56Siq7gTmEpJRG1LqdDqy0jgD5Skyqdsez7OWZU+KpValUjV6ZIOpGxr/E09drft79Xfn5IE8Bvbl9VjjwGTGmtcJ+k0SrXXr4Enaxwb2b6uFU9Npu0ErGr7oXrun+vP9wM/s31NnXsg8JCk0bZv7+FWHqixtawIfL2HuetSnnZ5JrA28HrgXEk32r4JOIOytfFeSlLsTEkzbZ/WZq2Vgfu7HZtFSQL2y5hVxzBpwqT+nhYRERERERERHZKKrmedBEygbD9s+0TFbl4HbA4cNZ9JLii9uNbqbYKkvSRNkTRT0kxKAqjZqH5am9Oec0zSVrUJ+/2SZlGqtlprnAz8EfiFpLslfb1uv1wPeLCR5Gpam1JxBUCtSJsBrNPLraxme1TrBUzsZe6jlATcV2w/YfvPwMXAW+r1brR9t+15tv8KfBd4Tw9rzaEkIZtGArN7uX5EREREREREDANJdD3rTMo2v9ts39HXZOB8yna+CyWtMZ/X+BPwVkkrtRusTwc8HvgEpbJqFPAPoFka1S6p1v3YROAcYD3bLwR+1FrD9pO2D7f9Skoj/F0o2xynAatIGtVm/bspPcBaca5EqQq7q/fbnW/X9XO+ee5n0nQDsEXrTY11w3o8IiIiIiIiIoaxJLqq2stpO2DffpzzdUpS6cL6tL++nExJKJ0p6RWSlpK0qqSDJO0MrERJ4twPIGkfSkVXf42gVGc9Jum1lB5e1DW3lbRZfTrjw5RKqnm27wHOozS4f5GkZSW9sZ42EdhHUldtdP9V4Ipeti321yXAf4ADJS0j6Q3AOErlGZJ2rTGp3s8neXYrZ3dnA5tKendtvP9F4Lr+NqKPiIiIiIiIiKEnia4G25Nt39rPc75M6X31p/rUwt7mPk7pA3YzcAEl0XQlZVvhFbZvpDz18HJKP6rNgMvar9arjwNfkjSbkug5ozG2JvCreu2bKH24Wls1P0BJfN1MeRrkp2vcFwKHUKre7qFUSO2xAHG1ZftJYFdgZ0o/reOBvRrJqT2AWyjbD08Cvmb7xNb5tUH9++ta9wPvpjTnf4jS02vAYo2IiIiIiIiIwUvz315q6JP0GOUJicfYPqTT8cTiJ+lQ4DPA8sBKtuf1NHfs2LGePHnyYostIiIiIiIiIvom6WrbY9uOLUmJroj+qBVxUzsdR8QAWg14oNNBRAygfKdjuMl3OoabfKdjuMl3evDYwPaL2w0ss7gjiRhCpvaUIY4YiiRNznc6hpN8p2O4yXc6hpt8p2O4yXd6aEiProiIiIiIiIiIGBaS6IqIiIiIiIiIiGEhia6Inv240wFEDLB8p2O4yXc6hpt8p2O4yXc6hpt8p4eANKOPiIiIiIiIiIhhIRVdERERERERERExLCTRFdGNpB0lTZV0i6QDOh1PxIKQ9DNJ90n6R+PYKpIukPSv+vNFnYwxYn5JWk/SxZJuknSDpE/V4/lOx5AkaQVJV0q6tn6nD6/H852OIU3S0pL+Lul39X2+0zGkSbpd0vWSpkiaXI/lez3IJdEV0SBpaeBYYCfglcD7JL2ys1FFLJATgB27HTsAuND2y4AL6/uIoeAp4LO2NwZeB/y/+r/N+U7HUPU4sJ3tLYAuYInJ9AcAAAK9SURBVEdJryPf6Rj6PgXc1Hif73QMB9va7rI9tr7P93qQS6Ir4rleC9xi+zbbTwC/AHbtcEwR/Wb7EuDBbod3BU6sv58I7LZYg4pYQLbvsX1N/X025T+i1iHf6RiiXMypb5etL5PvdAxhktYF3gb8pHE43+kYjvK9HuSS6Ip4rnWAaY33d9ZjEcPBGrbvgZI4AFbvcDwR/SZpNPAq4ArynY4hrG7xmgLcB1xgO9/pGOq+A/wf8HTjWL7TMdQZOF/S1ZL2q8fyvR7klul0ABGDjNocy6NJIyIGAUkrA2cCn7b9sNTuf7Ijhgbb84AuSaOAsyVt2umYIhaUpF2A+2xfLWlcp+OJGEBvsH23pNWBCyTd3OmAom+p6Ip4rjuB9Rrv1wXu7lAsEQPtXklrAdSf93U4noj5JmlZSpLrVNtn1cP5TseQZ3smMInSVzHf6Riq3gC8Q9LtlNYf20k6hXynY4izfXf9eR9wNqXVTb7Xg1wSXRHPdRXwMkkvkbQcsAdwTodjihgo5wB719/3Bn7TwVgi5ptK6dZPgZtsH90Yync6hiRJL66VXEh6AbADcDP5TscQZftA2+vaHk35/58vsr0n+U7HECZpJUkjWr8DbwH+Qb7Xg57s7MqKaJK0M6XHwNLAz2wf0eGQIvpN0mnAOGA14F7gUODXwBnA+sB/gPfa7t6wPmLQkbQ1cClwPc/2fjmI0qcr3+kYciRtTmlgvDTlH57PsP0lSauS73QMcXXr4uds75LvdAxlkl5KqeKC0vZpou0j8r0e/JLoioiIiIiIiIiIYSFbFyMiIiIiIiIiYlhIoisiIiIiIiIiIoaFJLoiIiIiIiIiImJYSKIrIiIiIiIiIiKGhSS6IiIiIiIiIiJiWEiiKyIiIiIiIiIihoUkuiIiIiIiIiIiYlhIoisiIiIiIiIiIoaF/w/UTUwMHbM3WQAAAABJRU5ErkJggg==\n"},"metadata":{"needs_background":"light"}}]}],"metadata":{"kernelspec":{"name":"python3","display_name":"Python 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