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diff --git a/img/CAHcomparaison.png b/img/CAHcomparaison.png
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diff --git a/img/hybride_average.png b/img/hybride_average.png
index 42f4a1990c835b12d2687bbe99a28920aee35158..141055d4c3e9c9e16468bb4a75236be2fe460a1b 100644
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diff --git a/py/AnalyseData.ipynb b/py/AnalyseData.ipynb
index dfee5f7c484da557b78b5beaa245852383aa388e..be98352b26879fe9deb6b2bcb317f48450cfb132 100644
--- a/py/AnalyseData.ipynb
+++ b/py/AnalyseData.ipynb
@@ -15,255 +15,7 @@
    "metadata": {
     "lines_to_next_cell": 2
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "    movieId  tmdbId  userId  rating\n",
-      "0        31    9909       1     2.5\n",
-      "1      1029   11360       1     3.0\n",
-      "2      1061     819       1     3.0\n",
-      "3      1129    1103       1     2.0\n",
-      "4      1172   11216       1     4.0\n",
-      "5      1263   11778       1     2.0\n",
-      "6      1287     665       1     2.0\n",
-      "7      1293     783       1     2.0\n",
-      "8      1339    6114       1     3.5\n",
-      "9      1343    1598       1     2.0\n",
-      "10     1371     152       1     2.5\n",
-      "11     1405    3179       1     1.0\n",
-      "12     1953    1051       1     4.0\n",
-      "13     2105      97       1     4.0\n",
-      "14     2150    8393       1     3.0\n",
-      "15     2193     847       1     2.0\n",
-      "16     2294    8916       1     2.0\n",
-      "17     2455    9426       1     2.5\n",
-      "18     2968   36819       1     1.0\n",
-      "19     3671   11072       1     3.0\n",
-      "    movieId tmdbId  userId  rating\n",
-      "0        31   9909       1     2.5\n",
-      "1      1029  11360       1     3.0\n",
-      "2      1061    819       1     3.0\n",
-      "3      1129   1103       1     2.0\n",
-      "4      1172  11216       1     4.0\n",
-      "5      1263  11778       1     2.0\n",
-      "6      1287    665       1     2.0\n",
-      "7      1293    783       1     2.0\n",
-      "8      1339   6114       1     3.5\n",
-      "9      1343   1598       1     2.0\n",
-      "10     1371    152       1     2.5\n",
-      "11     1405   3179       1     1.0\n",
-      "12     1953   1051       1     4.0\n",
-      "13     2105     97       1     4.0\n",
-      "14     2150   8393       1     3.0\n",
-      "15     2193    847       1     2.0\n",
-      "16     2294   8916       1     2.0\n",
-      "17     2455   9426       1     2.5\n",
-      "18     2968  36819       1     1.0\n",
-      "19     3671  11072       1     3.0\n",
-      "    adult                              belongs_to_collection    budget  \\\n",
-      "0   False                                                NaN         0   \n",
-      "1   False                                                NaN    812000   \n",
-      "2   False                                                NaN  44000000   \n",
-      "3   False  {'id': 115838, 'name': 'Escape From ... Collec...   6000000   \n",
-      "4   False                                                NaN         0   \n",
-      "5   False                                                NaN  15000000   \n",
-      "6   False                                                NaN  15000000   \n",
-      "7   False                                                NaN  22000000   \n",
-      "8   False                                                NaN  40000000   \n",
-      "9   False                                                NaN  35000000   \n",
-      "10  False  {'id': 151, 'name': 'Star Trek: The Original S...  35000000   \n",
-      "11  False                                                NaN  12000000   \n",
-      "12  False  {'id': 155474, 'name': 'French Connection Coll...   1800000   \n",
-      "13  False  {'id': 63043, 'name': 'TRON Collection', 'post...  17000000   \n",
-      "14  False  {'id': 87805, 'name': 'The Gods Must Be Crazy ...   5000000   \n",
-      "15  False                                                NaN  35000000   \n",
-      "16  False                                                NaN  60000000   \n",
-      "17  False  {'id': 109609, 'name': 'The Fly Collection', '...  15000000   \n",
-      "18  False                                                NaN   5000000   \n",
-      "19  False                                                NaN   2600000   \n",
-      "\n",
-      "                                               genres  \\\n",
-      "0   [{'id': 18, 'name': 'Drama'}, {'id': 80, 'name...   \n",
-      "1   [{'id': 16, 'name': 'Animation'}, {'id': 10751...   \n",
-      "2   [{'id': 80, 'name': 'Crime'}, {'id': 18, 'name...   \n",
-      "3   [{'id': 878, 'name': 'Science Fiction'}, {'id'...   \n",
-      "4   [{'id': 18, 'name': 'Drama'}, {'id': 10749, 'n...   \n",
-      "5   [{'id': 18, 'name': 'Drama'}, {'id': 10752, 'n...   \n",
-      "6   [{'id': 28, 'name': 'Action'}, {'id': 12, 'nam...   \n",
-      "7   [{'id': 18, 'name': 'Drama'}, {'id': 36, 'name...   \n",
-      "8   [{'id': 10749, 'name': 'Romance'}, {'id': 27, ...   \n",
-      "9   [{'id': 80, 'name': 'Crime'}, {'id': 53, 'name...   \n",
-      "10  [{'id': 878, 'name': 'Science Fiction'}, {'id'...   \n",
-      "11  [{'id': 16, 'name': 'Animation'}, {'id': 35, '...   \n",
-      "12  [{'id': 28, 'name': 'Action'}, {'id': 80, 'nam...   \n",
-      "13  [{'id': 878, 'name': 'Science Fiction'}, {'id'...   \n",
-      "14  [{'id': 28, 'name': 'Action'}, {'id': 35, 'nam...   \n",
-      "15  [{'id': 12, 'name': 'Adventure'}, {'id': 18, '...   \n",
-      "16  [{'id': 12, 'name': 'Adventure'}, {'id': 16, '...   \n",
-      "17  [{'id': 27, 'name': 'Horror'}, {'id': 878, 'na...   \n",
-      "18  [{'id': 10751, 'name': 'Family'}, {'id': 14, '...   \n",
-      "19  [{'id': 37, 'name': 'Western'}, {'id': 35, 'na...   \n",
-      "\n",
-      "                                             homepage     id    imdb_id  \\\n",
-      "0                                                 NaN   9909  tt0112792   \n",
-      "1                                                 NaN  11360  tt0033563   \n",
-      "2                                                 NaN    819  tt0117665   \n",
-      "3   http://www.theofficialjohncarpenter.com/escape...   1103  tt0082340   \n",
-      "4                                                 NaN  11216  tt0095765   \n",
-      "5                                                 NaN  11778  tt0077416   \n",
-      "6                                                 NaN    665  tt0052618   \n",
-      "7                                                 NaN    783  tt0083987   \n",
-      "8                                                 NaN   6114  tt0103874   \n",
-      "9                                                 NaN   1598  tt0101540   \n",
-      "10                                                NaN    152  tt0079945   \n",
-      "11                                                NaN   3179  tt0115641   \n",
-      "12                                                NaN   1051  tt0067116   \n",
-      "13                                                NaN     97  tt0084827   \n",
-      "14                                                NaN   8393  tt0080801   \n",
-      "15                                                NaN    847  tt0096446   \n",
-      "16                                                NaN   8916  tt0120587   \n",
-      "17                                                NaN   9426  tt0091064   \n",
-      "18                                                NaN  36819  tt0081633   \n",
-      "19                                                NaN  11072  tt0071230   \n",
-      "\n",
-      "   original_language                   original_title  \\\n",
-      "0                 en                  Dangerous Minds   \n",
-      "1                 en                            Dumbo   \n",
-      "2                 en                         Sleepers   \n",
-      "3                 en             Escape from New York   \n",
-      "4                 it            Nuovo Cinema Paradiso   \n",
-      "5                 en                  The Deer Hunter   \n",
-      "6                 en                          Ben-Hur   \n",
-      "7                 en                           Gandhi   \n",
-      "8                 en                          Dracula   \n",
-      "9                 en                        Cape Fear   \n",
-      "10                en    Star Trek: The Motion Picture   \n",
-      "11                en  Beavis and Butt-Head Do America   \n",
-      "12                en            The French Connection   \n",
-      "13                en                             Tron   \n",
-      "14                en           The Gods Must Be Crazy   \n",
-      "15                en                           Willow   \n",
-      "16                en                             Antz   \n",
-      "17                en                          The Fly   \n",
-      "18                en                     Time Bandits   \n",
-      "19                en                  Blazing Saddles   \n",
-      "\n",
-      "                                             overview  ... runtime  \\\n",
-      "0   Former Marine Louanne Johnson lands a gig teac...  ...    99.0   \n",
-      "1   Dumbo is a baby elephant born with oversized e...  ...    64.0   \n",
-      "2   Two gangsters seek revenge on the state jail w...  ...   147.0   \n",
-      "3   In 1997, the island of Manhattan has been wall...  ...    99.0   \n",
-      "4   A filmmaker recalls his childhood, when he fel...  ...   124.0   \n",
-      "5   A group of working-class friends decides to en...  ...   183.0   \n",
-      "6   Ben-Hur is a 1959 epic film directed by Willia...  ...   212.0   \n",
-      "7   In the early years of the 20th century, Mohand...  ...   191.0   \n",
-      "8   When Dracula leaves the captive Jonathan Harke...  ...   128.0   \n",
-      "9   Sam Bowden is a small-town corporate attorney....  ...   128.0   \n",
-      "10  When a destructive space entity is spotted app...  ...   132.0   \n",
-      "11  Mike Judge's slacker duo, Beavis and Butt-Head...  ...    81.0   \n",
-      "12  Tough narcotics detective 'Popeye' Doyle is in...  ...   104.0   \n",
-      "13  As Kevin Flynn searches for proof that he inve...  ...    96.0   \n",
-      "14  Misery is brought to a small group of Sho in t...  ...   109.0   \n",
-      "15  Fearful of a prophecy stating that a girl chil...  ...   126.0   \n",
-      "16  In this animated hit, a neurotic worker ant in...  ...    83.0   \n",
-      "17  When Seth Brundle makes a huge scientific and ...  ...    96.0   \n",
-      "18  Young history buff Kevin can scarcely believe ...  ...   116.0   \n",
-      "19  A town – where everyone seems to be named John...  ...    93.0   \n",
-      "\n",
-      "                                     spoken_languages    status  \\\n",
-      "0            [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
-      "1            [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
-      "2            [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
-      "3            [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
-      "4           [{'iso_639_1': 'it', 'name': 'Italiano'}]  Released   \n",
-      "5   [{'iso_639_1': 'en', 'name': 'English'}, {'iso...  Released   \n",
-      "6            [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
-      "7   [{'iso_639_1': 'en', 'name': 'English'}, {'iso...  Released   \n",
-      "8   [{'iso_639_1': 'la', 'name': 'Latin'}, {'iso_6...  Released   \n",
-      "9            [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
-      "10           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
-      "11  [{'iso_639_1': 'cs', 'name': 'Český'}, {'iso_6...  Released   \n",
-      "12  [{'iso_639_1': 'en', 'name': 'English'}, {'iso...  Released   \n",
-      "13           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
-      "14  [{'iso_639_1': 'af', 'name': 'Afrikaans'}, {'i...  Released   \n",
-      "15           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
-      "16           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
-      "17           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
-      "18           [{'iso_639_1': 'en', 'name': 'English'}]  Released   \n",
-      "19  [{'iso_639_1': 'en', 'name': 'English'}, {'iso...  Released   \n",
-      "\n",
-      "                                              tagline  \\\n",
-      "0     She broke the rules... and changed their lives.   \n",
-      "1                The One...The Only...The FABULOUS...   \n",
-      "2             When friendship runs deeper than blood.   \n",
-      "3   1997. New York City is now a maximum security ...   \n",
-      "4   A celebration of youth, friendship, and the ev...   \n",
-      "5   One of the most important and powerful films o...   \n",
-      "6         The entertainment experience of a lifetime.   \n",
-      "7              His triumph changed the world forever.   \n",
-      "8                                    Love never dies.   \n",
-      "9   There is nothing in the dark that isn't there ...   \n",
-      "10             The human adventure is just beginning.   \n",
-      "11            Coming to a screen bigger than your TV.   \n",
-      "12  There are no rules and no holds barred when Po...   \n",
-      "13  A world inside the computer where man has neve...   \n",
-      "14  The critics are raving... the natives are rest...   \n",
-      "15       Adventure doesn't come any bigger than this.   \n",
-      "16                             Every ant has his day.   \n",
-      "17                         Be afraid. Be very afraid.   \n",
-      "18  All the dreams you've ever had and not just th...   \n",
-      "19                   Never give a saga an even break!   \n",
-      "\n",
-      "                              title  video  vote_average vote_count movieId  \\\n",
-      "0                   Dangerous Minds  False           6.4      249.0      31   \n",
-      "1                             Dumbo  False           6.8     1206.0    1029   \n",
-      "2                          Sleepers  False           7.3      729.0    1061   \n",
-      "3              Escape from New York  False           6.9      720.0    1129   \n",
-      "4                   Cinema Paradiso  False           8.2      834.0    1172   \n",
-      "5                   The Deer Hunter  False           7.8      943.0    1263   \n",
-      "6                           Ben-Hur  False           7.5      660.0    1287   \n",
-      "7                            Gandhi  False           7.4      730.0    1293   \n",
-      "8                           Dracula  False           7.1     1087.0    1339   \n",
-      "9                         Cape Fear  False           7.0      692.0    1343   \n",
-      "10    Star Trek: The Motion Picture  False           6.2      541.0    1371   \n",
-      "11  Beavis and Butt-Head Do America  False           6.5      169.0    1405   \n",
-      "12            The French Connection  False           7.4      435.0    1953   \n",
-      "13                             Tron  False           6.6      717.0    2105   \n",
-      "14           The Gods Must Be Crazy  False           7.1      251.0    2150   \n",
-      "15                           Willow  False           6.9      484.0    2193   \n",
-      "16                             Antz  False           6.0     1320.0    2294   \n",
-      "17                          The Fly  False           7.1     1038.0    2455   \n",
-      "18                     Time Bandits  False           6.6      255.0    2968   \n",
-      "19                  Blazing Saddles  False           7.2      619.0    3671   \n",
-      "\n",
-      "   rating  \n",
-      "0     2.5  \n",
-      "1     3.0  \n",
-      "2     3.0  \n",
-      "3     2.0  \n",
-      "4     4.0  \n",
-      "5     2.0  \n",
-      "6     2.0  \n",
-      "7     2.0  \n",
-      "8     3.5  \n",
-      "9     2.0  \n",
-      "10    2.5  \n",
-      "11    1.0  \n",
-      "12    4.0  \n",
-      "13    4.0  \n",
-      "14    3.0  \n",
-      "15    2.0  \n",
-      "16    2.0  \n",
-      "17    2.5  \n",
-      "18    1.0  \n",
-      "19    3.0  \n",
-      "\n",
-      "[20 rows x 26 columns]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import pandas as pd\n",
     "import numpy as np\n",
@@ -296,13 +48,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/valou/Semestre_6/lifProjet/lifprojet/py/dataFrame.py:7: SettingWithCopyWarning: \n",
+      "/home/valou/Semestre_6/lifProjet/lifprojet/py/dataFrame.py:8: SettingWithCopyWarning: \n",
       "A value is trying to be set on a copy of a slice from a DataFrame.\n",
       "Try using .loc[row_indexer,col_indexer] = value instead\n",
       "\n",
       "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
       "  movies_metadata.loc[:, 'id'] = movies_metadata['id'].astype(int)\n",
-      "/home/valou/Semestre_6/lifProjet/lifprojet/py/dataFrame.py:7: FutureWarning: In a future version, `df.iloc[:, i] = newvals` will attempt to set the values inplace instead of always setting a new array. To retain the old behavior, use either `df[df.columns[i]] = newvals` or, if columns are non-unique, `df.isetitem(i, newvals)`\n",
+      "/home/valou/Semestre_6/lifProjet/lifprojet/py/dataFrame.py:8: FutureWarning: In a future version, `df.iloc[:, i] = newvals` will attempt to set the values inplace instead of always setting a new array. To retain the old behavior, use either `df[df.columns[i]] = newvals` or, if columns are non-unique, `df.isetitem(i, newvals)`\n",
       "  movies_metadata.loc[:, 'id'] = movies_metadata['id'].astype(int)\n"
      ]
     }
@@ -313,12 +65,6 @@
     "    \n",
     "    location = \"../archive/the-movies-dataset/\"\n",
     "\n",
-    "    credits = pd.read_csv(location+\"credits.csv\")\n",
-    "    #Contains Cast, Crew, ID \n",
-    "\n",
-    "    keywords = pd.read_csv(location+\"keywords.csv\")\n",
-    "    #Contains ID, keywords\n",
-    "\n",
     "    links_small = pd.read_csv(location+\"links_small.csv\")\n",
     "    #Contains IMDB and TMDB IDs of all movies featured in the ratings_small.csv file (About 9000 movies).\n",
     "\n",
@@ -412,11 +158,11 @@
    "outputs": [],
    "source": [
     "# Protect execution\n",
-    "if __name__=='__main__':\n",
+    "#if __name__=='__main__':\n",
     "    #mat = MatrixReco(movies_metadata, links_small, ratings_small,algorithm='SVD')\n",
-    "    mat =  pd.read_csv('../archive/the-movies-dataset/predUser_MovieSVD.csv', index_col=0)\n",
-    "    mat.columns = np.int64(mat.columns[:].values)\n",
-    "    mat_imput = imputerData(mat, 'most_frequent')\n",
+    "    #mat =  pd.read_csv('../archive/the-movies-dataset/predUser_MovieSVD.csv', index_col=0)\n",
+    "    #mat.columns = np.int64(mat.columns[:].values)\n",
+    "    #mat_imput = imputerData(mat, 'most_frequent')\n",
     "    #TestEfficacite(mat_imput,ratings_small)\n",
     "\n",
     "# pour-l'algo-KNN-l'erreur:\n",
@@ -509,46 +255,13 @@
    "source": [
     "def methodeKMeans(X, q):\n",
     "    Xnorm = CentreReduire(X)\n",
-    "    model = KMeans(n_clusters=q, n_init=20).fit(Xnorm)\n",
+    "    model = KMeans(n_clusters=q, n_init=30).fit(Xnorm)\n",
     "    return model"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "947e0819-2693-4be4-bb61-437e70d7d1bd",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "pour conserver plus de  0.9 % d'information il faut conserver  3  vecteurs\n",
-      "on conserve  0.8979687525438856 % d'information pour les 2 vecteurs du graphique\n",
-      "efficacité du clustering:  0.41785049206059793\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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h7mOP5Tlt3769HA6HEhMTdd1112nLli0e+3/88UcZY5SSkqKrrrpK0dHRCg8PV69evbxO8Ttajx499M4772jz5s1avXq1pk6dqh49ekiS7r//frVt21bXXXddqecpateuXerZs6dWrVqlV155Re+//74OHDjg9WfNu+++W+beKzfddJNCQkI0ZcoUjRs3Tj/88IPHVLJFixbpvPPOU0REhBYtWqRFixZpwIABMsZo4MCBevbZZ3Xttdfq22+/1T333KNJkybprLPOKjEsKSo/P1/nnXee+vTpoy+//NL9pveKK65wH3MirlOSIUOGKCQkRO+//74+/fRT98+9spo3b55q167tNTh16dixozp16qSJEycW2/fuu++6gxnJ/p3XpUsXrVq1Ss8995y++eYbDRgwQHfccYd7upVkv+E/44wz9Prrr+uGG27Q119/rddee00tWrTQzp07lZyc7A7Qb7zxRvfn7dFHHy3Xdcpr586duuaaa3T11Vfru+++0/Dhw7Vp0yYNGDBAoaGheueddzR9+nSNHTtWUVFRpU51HDp0qJ599lldd911mjZtmi655BJdfPHFxXqrHa833nhDN998szp06KDPP/9cjzzyiEaNGlXi99CECRM0d+5cPfvss/r+++/VqlUr5ebmau/evbrvvvv05Zdf6sMPP9QZZ5yhiy++WO+9916xc3z11VeaMGGCnnjiCX366adq2LChrrrqKq99nUr7HvUmJydHZ599tmbOnKkxY8bok08+UVJSksf3VnkVFhbqwgsv1NixY3X11Vfr22+/1dixYzVr1iz16tVLOTk5x3xuAMehMocPATh5vffee0aSee2114wx9rSN6Ohoj2kTxhgTHh5uTjvttDKf1zXNIz8/3+Tn55vdu3ebF154wViWZbp06eLzvldccYWJiIgwqamp7m0FBQWmVatWRpLZuHGje7tKGIp+9FBub9MZvBkyZIgJCQkxa9asKfGYBx54wEgyP//8s8f2YcOGGcuyzJ9//mmMMWbjxo1Gkmnfvr0pKChwH/fLL78YSebDDz80xhizZ88eI8k8//zzJV5zy5YtJjg4uNh0pKysLJOUlGQuv/xy97bBgwcbSeadd94pdp5TTz3V9OjRw2PbK6+8YiSZlStXlvta3vTt29e0bNnS677Q0FBz8803+7y/McasXbvW/fl23e644w6P6RLLli0zksyTTz7pcd85c+YYSSY0NNTn+SWZW265xWO70+k08fHxxaYt7du3z8TExBhJZuHChcYYe7qNJBMbG2tOP/1089VXX5lvvvnG9O7d21iWZaZPn+5xjh07dpju3bt7PKbLLrus1GH+V1xxhXE4HF6nNQ4fPty88847Zv78+ebLL780gwYNMpKKTXHyZtCgQSY4ONj8+uuvHtvHjx9vxo8fb2bOnGlmzpxpHn74YRMZGWlatWplsrKyPI598cUXTc2aNd3fq6VNLTjnnHPcjz02NtZ8/vnnxY4pLCw0jz32mAkKCnIf26BBA/P7778XO7asz+l7771nnnrqKfPdd9+ZuXPnmrFjx5r4+HiTmJjo8byOGTPGXduFF15opk+fbj777DPToUMHEx4ebpYvX+7zOU1NTTVdunRx13LeeeeZ7Oxss2DBAhMREWHWrVvn8/7e/Oc//zGWZZlly5Z5bO/bt2+ZfqYd/TPS9TkaPny4x3Hjxo0zkszOnTvd27xN15s+fbqRZMaNG+exferUqWWaGun6+fTCCy94bH/qqaeMJPO///2v3Ncp6+8B12O/7rrrfNboi2tq4NH1ezNhwgQjyf07wRhj9u7da8LCwsy9997r3nbOOeeYevXqmYyMDI/733bbbSY8PNw9XfCJJ54wksysWbNKvKavKVplvY7reSr6u9YY779He/bsaSSZOXPmeBz76aefGknFvm5L4/rZfPfdd3tsnzx5spHk8fl0Tb08Wkn1F+V0Ok1SUpLp1q2bx/bNmzebkJAQ07BhQ/c21+/ypk2bmry8PJ/1FxQUmPz8fHPjjTeaTp06eeyTVOJrm2bNmhWrvyzfoz179vSYlvnqq68aSWbatGke9x06dKiRZCZOnFjifV0GDx7s8fhdv+uKTsM35sj0/ldeeaXE5wNAxSHgAeBVz549TUREhEdfnRtuuMFI8ngzciwBT9E3XZKMZVnmvPPOK7X/Tp06dcz5559fbLvrxVxFBjzJycmmX79+Po/p2rWradOmTbHtP//8s5FkXn31VWPMkReFDzzwgMdxhw4dMpLM2LFjjTH2G9qmTZuaunXrmueee84sXbrUOJ1Oj/u43lQsWbLEHZq5bldccYWpU6eO+1jXc3/0i3hj7Dfkkswff/zh3talSxeP0K081/Kmb9++plWrVl73hYaGFgtVjrZx40bTrFkzc/rpp5tPP/3UzJ8/34wbN87ExsaaIUOGeBz7z3/+08TGxpqPP/7Y7Nu3z/z000+mefPmxuFwmPDw8BKvcd9995UYRDz66KNGknniiSfMrl27zF9//WUGDBhgHA6HkWQWL15sjDnyhqNWrVomMzPTff+DBw+alJQUc/rpp7u37d2713Tp0sW0bdvWTJ482SxYsMC88sor7q+3/Px8r3Wmp6ebsLCwMvXZcbnttttK7evzyCOPGEnmxRdfLNM5XW/Wxo8f7962adMmEx0dbd566y33ttICnnXr1plffvnFTJs2zVx22WUmJCTETJkyxeOYJ5980kRGRponnnjCzJs3z0ybNs307dvX1KpVy+MxHetz6vLzzz+boKAgj74+rpChTZs2HqHsjh07TGRkpBk0aFCpz1VhYaHZuHGj2b59uzHGmNzcXNO6dWvz1FNPGWPs57JNmzamZs2aZsCAAWbLli0+z9e1a1fTrl27Yttdz/WxBjxHB5CuQMX19W2M94Dn/vvvN5JMWlpasccdFRXl0XPIG9fPpz179nhsd/28dAW25blOeQOeo9/8ltV3331nQkNDzaWXXlpi356iXN+/Dz74oHvbyy+/bCSZVatWGWOMycnJcQfqR/+8/e6774wk89133xljjOnevbtp0aKFz2uWFPCU5zrlDXhq1qxZrI7169eb0NBQ07VrV/Puu++W2qfMxfUHh6OD5/z8fBMcHHzCAp41a9YYSea5554rtq9Xr15eA56jQyeXjz/+2PTo0cNERUV5vOY5+neQJJ+vbbZu3epRf1m+R48OaS6//HITExNT7Bquz92xBDyDBg0yNWrUMHl5ecW+dsryRx8AFYMpWgCKWb9+vRYsWOAedr9//37t379fl156qaQjK2tJUoMGDbRx48ZynT8iIkJLlizRkiVLtGLFCu3fv1/ffvut6tat6/N+6enpxab3SPK67UTbvXt3qSvOpKenKzk5udj2lJQU9/6iEhISPD52Tf9xDWu2LEtz5szROeeco3HjxunUU09V7dq1dccdd7j7bLj6/3Tp0kUhISEet6lTp2rPnj0e14iMjPTaD2XQoEEKCwtzz8Nfs2aNlixZ4tEvp7zXOlpCQkKx50CylxPPy8tTfHy8z/s/8MADyszM1IwZM3TJJZfon//8p/7973/r+eef1zvvvKP58+e7j/3kk090+umn6/LLL1fNmjXVu3dvXXzxxTrllFNK/DrLz8/Xe++9p44dO6pz587F9j/22GO6++67NXr0aCUmJqp58+aS5H6OXOd1fV579OihmJgY9/0jIyPVs2dPLV261L3tv//9r5YtW6ZZs2bp6quv1plnnqlhw4Zp8uTJmjlzpiZPnuy11g8++EC5ubkefYJK4xrCf3SfJ5dRo0Zp9OjReuqpp7xO8/HmoosuUlRUlMc5R4wYoXbt2umSSy5x/+xw9dY4cOCAxxREl+bNm6tLly664IIL9PHHH6tPnz4aMWKEu3fV2rVr9dhjj2nUqFF69NFH1atXL11wwQX69ttvVaNGDd1zzz3ucx3rc+rStWtXtWjRwuMxuT6nZ599thwOh3t7cnKyOnbs6PE5LYllWWrUqJH758HYsWMVFBSkf//73/rjjz80aNAgPffcc9q2bZtq1apV6pSLivp5WNrPJV/1BAcHF5tma1mWkpKSvH7vHy04OLjY9V2Px3X/E3Gdknj7+V2aGTNm6OKLL1bfvn01efJkr9MljxYfH68LLrhA7733nnva5LvvvquuXbu6p0amp6eroKBAL774YrGft64pXK6fuWX5/VSS8lynvLw9n02bNtXs2bNVp04djRgxQk2bNlXTpk31wgsvlFqnVPzr29vXzPFwXefoFQdL2iZ5f5yff/65Lr/8ctWtW1cffPCBFi1apCVLlmjIkCHu/ltF+fpeLu9rB2/S09O91n88Py927dql/fv3KzQ0tNjXTmpq6jF/3QA4PiyTDqCYd955R8YYffrpp17nf0+aNEmjR4+Ww+HQOeecoxdffFGLFy8ucx+eoKAgr2+gS5OQkKDU1NRi271tCwsL89qL4Vhf/NeuXVvbtm0rtb6dO3cW2+5qfljeBqqS3cTX1Yxz3bp1+vjjjzVy5Ejl5eXptddec5/TNWe/NCW9+ahZs6YuvPBCvffeexo9erQmTpyo8PBwXXXVVe5jynuto7Vv314fffSRUlNTPV5Urly5UpLUrl07n/dftmyZ2rRp49GsVrIDJ8nu4dOzZ09JdvPg7777TmlpaUpNTVXDhg0VERGhV155xR1UHu2bb75RWlqauy/F0YKDgzV+/Hg98cQT2rhxo2rVqqXk5GSdc845aty4sfsNlqunkDfGGI8luJctW6a6desWe4NQ9DF58/bbbysxMdHdOLosjDGSvC8BPmrUKI0cOVIjR44sdbl6b+ctes5Vq1Zp8+bNXpsR9+7dW3FxcaU23e3ataumT5+u3bt3KzExUcuXL5cxxv28uISEhKhjx44e4d6xPqe+HlN5Pqdl8eeff2rs2LGaPXu2QkJCNHv2bLVt21bnnnuuJOmee+5Rx44ddeDAgRKXIC/Pz0N/SEhIUEFBgXbv3u0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\n",
-      "text/plain": [
-       "<Figure size 1400x1000 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Protect execution\n",
-    "if __name__=='__main__':\n",
-    "    c = methodeKMeans(mat_imput,2)\n",
-    "    ACP(mat_imput, 0.9, annotation=False, cluster=c,nom=\"KMeans\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
    "id": "249363d6-03ad-4589-9caf-4829de09a830",
    "metadata": {},
    "outputs": [],
@@ -560,7 +273,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "id": "75bc9e9e-e6fd-41e7-adaa-1ca6574c3bc0",
    "metadata": {},
    "outputs": [],
@@ -590,7 +303,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "id": "049e3572-ca57-4b85-b5b7-cff01e85f9e1",
    "metadata": {
     "lines_to_next_cell": 0
@@ -603,7 +316,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "id": "2ae07f21-8bb7-4329-9046-5c3a8b5ef17a",
    "metadata": {},
    "outputs": [],
@@ -646,7 +359,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "id": "e762272b-307f-48b3-890f-9385d2f5c115",
    "metadata": {},
    "outputs": [],
@@ -679,9 +392,13 @@
     "    X_pca=pca.transform(Xnorm)\n",
     "\n",
     "    colors = ['red','yellow','blue','pink','k','m','g','c']\n",
-    "    axs[0].scatter(X_pca[:, 0], X_pca[:, 1], c= model.labels_,\n",
+    "    scat = axs[0].scatter(X_pca[:, 0], X_pca[:, 1], c= model.labels_,\n",
     "    cmap=matplotlib.colors.ListedColormap(colors))\n",
-    "    print(\"efficacité hybride: \",metrics.silhouette_score(Xnorm, model.labels_))\n",
+    "    # Ajouter une légende qui spécifie les numéros de cluster de 1 à Qkmeans2\n",
+    "    legend_labels = [str(i+1) for i in range(Qkmeans2)]\n",
+    "    axs[0].legend(handles=[plt.scatter([],[], color=colors[i], label=label) for i, label in enumerate(legend_labels)],\n",
+    "                  title=\"Groupes\", loc='upper left')    \n",
+    "    print(\"efficacite hybride: \",metrics.silhouette_score(Xnorm, model.labels_))\n",
     "    axs[0].set_title('ACP hybride')\n",
     "    axs[1].set_title('dendrogramme sur centre Kmeans')\n",
     "    locSave = \"../img/hybride_\"+strat+\".png\"\n",
@@ -691,37 +408,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "id": "b4fd3120-d9e2-47c0-ae09-9e6ee7161a8e",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "efficacité hybride:  0.2964620162799592\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1800x600 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Protect execution\n",
-    "if __name__=='__main__':\n",
-    "    Hyb = hybride(mat_imput, 'average', 17, 6)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 13,
    "id": "35cdb749-eba9-461f-849f-787059fbd2e7",
    "metadata": {},
    "outputs": [],
@@ -760,7 +447,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 14,
    "id": "151b5a55-fafd-4960-9608-ee3dc7cb0acd",
    "metadata": {},
    "outputs": [],
@@ -778,7 +465,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 15,
    "id": "c309550c-5821-4b80-8b90-0b63b3677838",
    "metadata": {
     "lines_to_end_of_cell_marker": 2,
@@ -804,7 +491,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 16,
    "id": "d6e7b96a",
    "metadata": {},
    "outputs": [],
@@ -814,12 +501,12 @@
     "    BDInterpretable = []\n",
     "    for i in range(q):\n",
     "        BDInterpretable.append(PointCommun(tabGrp[i], movies_metadata, links_small,ratings_small))\n",
-    "    return BDInterpretable, tabGrp\n"
+    "    return BDInterpretable, tabGrp"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 17,
    "id": "0f5007f6-5767-40e9-af3e-5695be563b62",
    "metadata": {},
    "outputs": [],
@@ -827,13 +514,13 @@
     "def nbGroupe(tabgrp):\n",
     "    calc = pd.Series(index=range(1,len(tabgrp)+1), dtype=float)\n",
     "    calc2 = 0\n",
-    "    for i in tabGrp:\n",
+    "    for i in tabgrp:\n",
     "        calc2 += len(i)\n",
     "    for i in calc.index:\n",
-    "        calc[i] = (len(tabGrp[i-1])/calc2)*100\n",
-    "    plt.pie(calc, labels=calc.index, autopct='%1.1f%%')\n",
-    "    plt.title(\"répartition des utilisateur dans les groupes\")\n",
-    "    plt.savefig(\"../img/repartionUi_Grp.png\")\n",
+    "        calc[i] = (len(tabgrp[i-1])/calc2)*100\n",
+    "    #plt.pie(calc, labels=calc.index, autopct='%1.1f%%')\n",
+    "    #plt.title(\"répartition des utilisateur dans les groupes\")\n",
+    "    #plt.savefig(\"../img/repartionUi_Grp.png\")\n",
     "    return calc"
    ]
   },
@@ -847,7 +534,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 18,
    "id": "c26eb0cd-faaf-4c35-a37e-c656c6750b46",
    "metadata": {},
    "outputs": [],
@@ -861,12 +548,11 @@
     "        print(\"erreur tu es dans aucun groupe\")\n",
     "        return\n",
     "    calc = len(tabGrp[leGroupe])\n",
-    "    res = \"vous êtes dans le groupe \"+str(leGroupe+1)+\" qui est composé de \"+str(calc)+\" membres \\n\"\n",
+    "    res = \"vous etes dans le groupe \"+str(leGroupe+1)+\" qui est compose de \"+str(calc)+\" membres \\n\"\n",
     "    pourcent = nbGroupe(tabGrp)\n",
-    "    res +=\"c'est à dire \"+str(pourcent[leGroupe+1])+\" % de tout les utilisateurs. \\n\"\n",
-    "    res +=\"voici les autres utilisateurs de votre groupe:\\n\"+str(tabGrp[leGroupe])\n",
-    "    print(res)\n",
-    "    return res"
+    "    res +=\"c'est a dire \"+str(pourcent[leGroupe+1])+\" % de tout les utilisateurs. \\n\"\n",
+    "    res +=\"voici les autres utilisateurs de votre groupe:\\n\"+str(tabGrp[leGroupe])+\"\\n\"\n",
+    "    return leGroupe, res"
    ]
   },
   {
@@ -879,101 +565,184 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 19,
    "id": "eb7b7021-a960-4c39-b33f-4cfad42fa5a2",
    "metadata": {},
    "outputs": [],
    "source": [
-    "def SelectionGenres(BDI, ratings_small, movies_metadata):\n",
-    "    GrpParGenres = GroupeParGenres(BDI)    #df qui met les idMovie dans les collums genres\n",
-    "    nbEval = pd.Series(index=GrpParGenres.columns, dtype=float) \n",
-    "    pourcent = pd.Series(index=GrpParGenres.columns, dtype=float)\n",
-    "    for i in GrpParGenres.columns:#parcour les genres\n",
-    "        nbEval[i] = len(GrpParGenres[i].dropna())\n",
+    "def SelectionGenres(BDI, ratings_small, GrpParGenres, axs, nom= 'BDI'):\n",
+    "    nbEval = GrpParGenres.count().drop('id')\n",
+    "    pourcent = pd.Series(index=nbEval.index, dtype=float)\n",
     "    for i in nbEval.index:\n",
     "        pourcent[i] = (nbEval[i]/sum(nbEval)) * 100\n",
     "    nbEval = nbEval.sort_values(ascending=False)\n",
     "    pourcent = pourcent.sort_values(ascending=False)\n",
-    "    plt.pie(pourcent, labels=nbEval.index, autopct='%1.1f%%')\n",
-    "    plt.title(\"pourcentage des genres des films que votre groupe à évalué\")\n",
-    "    return nbEval\n"
+    "    axs.pie(pourcent, labels=nbEval.index, autopct='%1.1f%%')\n",
+    "    axs.set_title(\"répartion des genres des films evalué du groupe {}\".format(nom))\n",
+    "    return pourcent"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
-   "id": "b8a6cd24-ef5a-4d5d-bbbd-5c5c827f649f",
+   "execution_count": 20,
+   "id": "823295b4-6438-4719-8ec0-2c9c73de5e44",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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W6l7/wAMPYDAYHH97enpy9913s2nTJqxWa6nviwC7d+/mnnvuwd/fH7VajVarZfDgwVit1ms2IC3JsXv37k1ISAgzZ850bL9q1SouXLjgqBbL980339CsWTMMBoPjc2Pt2rUFqqduVGmv+dK6oYQjJCTE6W+NRoO/vz9JSUkAjp+hoaEFtg0LC3M8fiOu3md+25FrNXaLj48H4PXXX0er1Tr9GzFiBAAXL1502sbf39/pb71eD0BOTs51Y1yyZAkDBgwgPDycuXPnsm3bNnbu3MmwYcMwmUyO9ZKSktBoNPj5+TltHxwc7PR3UlISFouFqVOnFoi/T58+hcZ/9fb5r9GVrn4dS3Kcd955hwkTJrB9+3Z69+6Nv78/d911F7t27brmc5OUlFTg/Ao75/zXrH///gVi+fzzzxFCkJyc7LRNcV+zq6+hm3XeVz/fUPA1KMl5L1y4kCFDhjB9+nTatm2Ln58fgwcPJi4u7pqxlIWrr1mdTnfN5fnXfY0aNVizZg1BQUE8//zz1KhRgxo1aly3DUz+PaOoe8+NyH+uW7ZsWeC5Xrhw4TXfU2A/13vuuYcff/wRq9UK2OvMW7VqRf369QFISUlBCFHkvfDKc7uewvYRHx/Pvn37CsTv6emJEOK69wUo+N4rallhMZTnvb6o90teXh6ZmZmlvi+ePXuWDh06cP78eaZMmcLff//Nzp07HW0wrnWvL8mxNRoNgwYN4tdffyU1NRWwXyehoaH07NnTsc9JkyYxfPhwWrduzeLFi9m+fTs7d+6kV69exfrcKY7SXvOldUNfDeLi4ggPD3f8bbFYSEpKcrzx83/GxsYWSAQuXLhAQECA42+DwUBubm6BY1y8eNFpvXxXl2IEBgYCFGiMeqX8/bzzzjs88MADha5Tp06dIrcvqblz51K9enUWLlzoFO/V5+nv74/FYiE5OdnpRn31B4avr6/jG9Hzzz9f6DGrV69eZDz5x7nyNSrtcTQaDa+++iqvvvoqqamprFmzhnfffZeePXty7ty5IlvP+/v7Oy76K10dS/5rNnXqVNq0aVPovoq6KV7P1dfQzTrvwhKB0px3QEAAkydPZvLkyZw9e5Zly5bx9ttvk5CQwMqVK6/xDLhWhw4d6NChA1arlV27djF16lRGjhxJcHAwjzzySKHb5F+3Rd17rpT/rTg3N9eRdELBD5/85/qXX36hWrVqN3QuTzzxBD///DOrV68mIiKCnTt38vXXXzse9/X1RaVSERsbW2Db/Ebohd3nClNYCW5AQABGo5EZM2YUus219p3/nBb1fiyslOPqGK6811+tsHv91Y24oeikoKj3i06nw8PDA61WW6r74tKlS8nKymLJkiVOr/+ePXuK3CZfSe/JTzzxBOPHj2fBggU8/PDDLFu2jJEjR6JWqx3rzJ07l86dOztdP0CRDcuvdDOv+dK4oYRj3rx5NG/e3PH3okWLsFgsjhbI+cV+c+fOpWXLlo71du7cyeHDh3nvvfccyyIjI9m3b5/T/o8dO8bRo0eL9UZs164d3t7efPPNNzzyyCOFvinr1KlDrVq12Lt3L5988kmJzvVa9Hp9oZmnoijodDqnWOLi4gr0UunUqRPjxo1j4cKFDB8+3LF8wYIFTuu5ubnRpUsXdu/eTaNGjRzfGourS5cujBs3jnnz5vHSSy85lv/0009lchwfHx/69+/P+fPnGTlyJNHR0QWqTPJ16tSJCRMmcOjQIad1rj7n9u3b4+Pjw6FDh3jhhReKe6o35Gacd/5rsHfvXqdqlatfgxs974iICF544QXWrl3Lli1bir2dK6nValq3bs0dd9zBvHnz+O+//4pMOPLvLUXde66U/0G5b98+p/vP77//7rRez5490Wg0nDx5skBVQXH16NGD8PBwZs6c6ehNcWX1oLu7O61bt2bJkiVMmDDB0f3aZrMxd+5cqlSpQu3atYGSlaLm69evH5988gn+/v7X/HAtTOvWrdHr9SxcuNDpi9j27ds5c+ZMkdUqV2rbti1Go5G5c+c6etmA/QvgunXr6N+/v2NZZGQkP//8s9OHYlJSElu3bsXLy6vAvpcsWcL48eMdH6YZGRn8/vvvdOjQAbVaXer7Yv79+coPaCEE33///XW3Lemx69atS+vWrZk5cyZWq9Wp2u3KeK6MBezX8LZt26hateo1938zr/nSuKGEY8mSJWg0Grp3787BgwcZNWoUjRs3dtQF1qlTh2eeeYapU6eiUqno3bs30dHRjBo1iqpVq/LKK6849jVo0CAef/xxRowYwYMPPsiZM2cYN26co+Tiejw8PJg4cSJPPfUU3bp14+mnnyY4OJgTJ06wd+9e/u///g+Ab7/9lt69e9OzZ0+GDh1KeHg4ycnJHD58mP/++4+ff/65xM9Dw4YNWbBgAQsXLiQqKgqDwUDDhg3p168fS5YsYcSIEfTv359z587x4YcfEhoa6tTvuVevXrRv357XXnuN9PR0mjdvzrZt2/jxxx8BnOrIp0yZwp133kmHDh0YPnw4kZGRZGRkcOLECX7//XfWrVtXZJw9evSgY8eOvPnmm2RlZdGiRQu2bNnCnDlzCqxb3OPcfffdNGjQgBYtWhAYGMiZM2eYPHky1apVo1atWkXGMnLkSGbMmEHv3r354IMPCA4O5qeffuLIkSNO5+zh4cHUqVMZMmQIycnJ9O/fn6CgIBITE9m7dy+JiYkFvgmUxs067759+/LRRx8RHBzMvHnzHOedr7jnnZaWRpcuXXj00Ue544478PT0ZOfOnaxcubLIUrxbwTfffMO6devo27cvERERmEwmx7fzbt26Fbld3bp1efzxx5k8eTJarZZu3bpx4MABJkyYUODDqk+fPvj5+fHkk0/ywQcfoNFomDVrFufOnXNaLzIykg8++ID33nuPU6dO0atXL3x9fYmPj2fHjh24u7szduzYa56PWq1m8ODBTJo0CS8vLx544AG8vb2d1vn000/p3r07Xbp04fXXX0en0zFt2jQOHDjA/PnzHR98DRo0AOxDTXt6emIwGKhevfo1q4xGjhzJ4sWL6dixI6+88gqNGjXCZrNx9uxZ/vrrL1577bUiR5D08/Pj1Vdf5dNPP8XX15f777+fmJgYxo4dS2hoqNP9pyg+Pj6MGjWKd999l8GDBzNw4ECSkpIYO3YsBoOB0aNHO9YdNGgQ3377LY8//jhPP/00SUlJjBs3rtBkI/+57d69O6+++io2m43PP/+c9PR0p9ekNPfF7t27o9PpGDhwIG+++SYmk4mvv/6alJSU6573jRx72LBhPPvss1y4cIF27doVKFXv168fH374IaNHj6ZTp04cPXqUDz74gOrVqxdIqq92M6/5UilJC9P8lrD//vuvuPvuu4WHh4fw9PQUAwcOFPHx8U7rWq1W8fnnn4vatWsLrVYrAgICxOOPPy7OnTvntJ7NZhPjxo0TUVFRwmAwiBYtWoh169YV2Uvl6pb1+VasWCE6deok3N3dhZubm6hXr574/PPPndbZu3evo8uaVqsVISEhomvXruKbb75xrJPfqvfqVt/5x7+yBXl0dLTo0aOH8PT0dHQVzPfZZ5+JyMhIodfrRd26dcX3339faEvi5ORk8cQTTwgfHx/h5uYmunfvLrZv315or5LTp0+LYcOGifDwcKHVakVgYKBo166d+Oijjwp9Tq6Umpoqhg0b5nScI0eOFGjtXNzjTJw4UbRr104EBAQInU4nIiIixJNPPimio6OvG8uBAwdEt27dhMFgEH5+fuLJJ58Us2fPFoDYu3ev07obN24Uffv2FX5+fkKr1Yrw8HDRt29fp+sg/3m9sru1EIV3CQPE888/X2hc5X3ehw4dEt27d3c6799++63QngnXO2+TySSee+450ahRI+Hl5SWMRqOoU6eOGD16tMjKyrpmHGXRS2X8+PHF2ufV76dt27aJ+++/X1SrVk3o9Xrh7+8vOnXqJJYtW3bd5y83N1e89tprIigoSBgMBtGmTRuxbdu2Qnu67dixQ7Rr1064u7uL8PBwMXr0aDF9+vQC14MQQixdulR06dJFeHl5Cb1eL6pVqyb69+/v1AX5Wo4dOyYAAYjVq1cXus7ff/8tunbtKtzd3YXRaBRt2rQRv//+e4H1Jk+eLKpXry7UarVTl/1OnTqJ+vXrF7rvzMxM8b///U/UqVNH6HQ6R1fNV155RcTFxV0zdpvNJj766CNRpUoVodPpRKNGjcTy5ctF48aNnXpGXO/+O336dNGoUSPH8e+9995Cu1jOnj1b1K1bVxgMBlGvXj2xcOHCInupfP7552Ls2LGO2Jo2bSpWrVpVYJ+luS/+/vvvonHjxsJgMIjw8HDxxhtvOHr1FdZbqDTHTktLE0ajUQDi+++/L/B4bm6ueP3110V4eLgwGAyiWbNmYunSpQWeHyEK9lIR4uZe8zfqhhKOq2/sUtnK7+q3ZcsWV4dy0zz99NPCw8ND5ObmujoU6TZTVNd66cacOnVK6HQ68fHHH7vk+EUltdLt7/Yfk/Y2N3/+fM6fP0/Dhg1RqVRs376d8ePH07FjR9q1a+fq8MrFBx98QFhYGFFRUWRmZrJ8+XKmT5/O//73vxLXw0qSdOP27t3L/PnzadeuHV5eXhw9etRRzfHkk0+6OjypgpEJh4t5enqyYMECPvroI7KysggNDWXo0KF89NFHrg6t3Gi1WsaPH09MTAwWi4VatWoxadIkXn75ZVeHJkmViru7O7t27eKHH34gNTUVb29vOnfuzMcff3zDvcAkqSiKEEK4OghJkiRJkio2OT29JEmSJEnlTiYckiRJkiSVO5lwSJIkSZJU7mTCIUmSJElSuZMJhyRJkiRJ5U4mHJIkSZIklTuZcEiSJEmSVO5kwiFJkiRJUrmTCYckSZIkSeVOJhySJEmSJJU7mXBIkiRJklTuZMIhSZIkSVK5kwmHJEmSJEnlTiYckiRJkiSVO5lwSJIkSZJU7mTCIUmSJElSuZMJhyRJkiRJ5U4mHJIkSZIklTuZcEiSJEmSVO5kwiFJkiRJUrmTCYckSZIkSeVOJhySJEmSJJU7mXBIkiRJklTuZMIhSZIkSVK5kwmHJEmSJEnlTiYckiRJkiSVO5lwSJJUIQwdOpT77ruvwPINGzagKAqpqak3PSZJki6TCYckSdI15OXlFVhmtVqx2Wwl3teNbidJFYFMOCRJqlQWL15M/fr10ev1REZGMnHiRKfHIyMj+eijjxg6dCje3t48/fTTzJo1Cx8fH5YvX069evXQ6/WcOXOGlJQUBg8ejK+vL25ubvTu3Zvjx4879lXUdpJUGcmEQ5KkSuPff/9lwIABPPLII+zfv58xY8YwatQoZs2a5bTe+PHjadCgAf/++y+jRo0CIDs7m08//ZTp06dz8OBBgoKCGDp0KLt27WLZsmVs27YNIQR9+vTBbDY79lXYdpJUGWlcHYAkSVJZWb58OR4eHk7LrFar4/dJkyZx1113OZKI2rVrc+jQIcaPH8/QoUMd63Xt2pXXX3/d8ffmzZsxm81MmzaNxo0bA3D8+HGWLVvGli1baNeuHQDz5s2jatWqLF26lIceegigwHaSVFnJEg5JkiqMLl26sGfPHqd/06dPdzx++PBh2rdv77RN+/btOX78uFNi0qJFiwL71ul0NGrUyGlfGo2G1q1bO5b5+/tTp04dDh8+XOR2klRZyRIOSZIqDHd3d2rWrOm0LCYmxvG7EAJFUZweF0IUup+rGY1Gp20L266wY1y9nSRVVrKEQ5KkSqNevXps3rzZadnWrVupXbs2arW6xPuyWCz8888/jmVJSUkcO3aMunXrlkm8klSRyIRDkqRK47XXXmPt2rV8+OGHHDt2jNmzZ/N///d/Tu01iqtWrVrce++9PP3002zevJm9e/fy+OOPEx4ezr333lsO0UvS7U0mHJIkVRrNmjVj0aJFLFiwgAYNGvD+++/zwQcfODUYLYmZM2fSvHlz+vXrR9u2bRFCsGLFCrRabdkGLkkVgCKKqoiUJEmSJEkqI7KEQ5IkSZKkcicTDkmSJEmSyp1MOCRJkiRJKndyHA5JqgSEEGTkWkjLNpOWYyY9x0y6yf77lf9y8myoVaBWKahVChqV6tJP5YqfKjRq+99GrZpATz1BnnqCPA0EeekxaEvWvVSSpMpBJhySVAFYrDbOpeRw+mImpxKzOH3R/u98ag6p2WYycy1YbTenfbinQeOUgFz5e7iPkdohnngZZC8OSapsZC8VSbqNJKSbOJGYaU8orkgszqVkY7bePm/lcB8jdUM9qRvqxR0hXtQN9STS3x2VSo7IKUkVlUw4JOkWZbMJDsWmsys6mV1nUvj3TAqxaSZXh1VujFo1tYM9LiUh9mSkXpgXnrI0RJIqBJlwSNItIjvPwp6zqeyMTmHXmWR2n00lM9fi6rBcSq1SaBDmRZsof9rU8KdVpB/uelkTLEm3I5lwSJKL5ORZ2XQ8kX9OJbPrTDKHLqRjuUntLG5XGpVCwyre3FkzgI61A2kW4YtaVsNI0m1BJhySdBOl5ZhZezielQfi2HQ8EZPZ5uqQbmteBg131gqgU+1AOtUOIsTb4OqQJEkqgkw4JKmcXczM5a+D8aw8GMe2kxdvq8adt5vGVX24r0kYdzcOI8BD7+pwJEm6gkw4JKkcnE/NYeWBOFYdiGPXmWRkTcnNpVEptK8ZwP1Nw+lZPwSjTo4NIkmuJhMOSSojqdl5LPnvPEv3nGdfTJqrw5EucdOp6VEvmPuahtOhVqBs8yFJLiITDkkqpR2nk/npnzP8eSCOXItsk3ErC/DQ069RKPc3DadxVR9XhyNJlYpMOCTpBqTlmPnl3xjm7zjLiYRMV4cj3YBaQR48eWd17m8Wjl4jq1wkqbzJhEOSSuBEQiaztp5myX/nyc6zujocqQwEeOgZ0rYag9pWw8dN5+pwJKnCkgmHJF2HEIJ1RxKYtTWazScuIt8xFZNRq2ZAiyo8eWcUEf5urg5HkiocmXBIUhGEEKzYH8fkNcc4LqtNKg21SqFn/WCe6ViDJrKdhySVGZlwSFIh1hyKZ9LqYxyKTXd1KJILtYz05ekOUXSvF4yiyN4tklQaMuGQpCtsOpbIxNXH2Hsu1dWhSLeQWkEevNPnDrreEezqUCTptiUTDkkC/jmVxMTVx9hxOtnVoUi3sPY1/Xm3T13qh3m7OhRJuu3IhEOq1HafTWHS6mP8ffyiq0ORbhMqBe5vWoU3etaRc7dIUgnIhEOqlE4kZPLpisOsPZLg6lCk25RBq+KpO6MY3rkG7nqNq8ORpFueTDikSsVktvJ/607w3aZT5FnlqKBS6QV46Hmley0eaRkhh02XpGuQCYdUaWw+fpH/Ld1PdFK2q0ORKqBaQR6826cuXe4IcnUoknRLkgmHVOFdzMzlw+WH+G3PBVeHIlUCveqH8NH9DQjw0Ls6FEm6pciEQ6qwhBDM33GOz1ceIS3H7OpwpErE103L2HsbcE/jMFeHIkm3DJlwSBXS0bgM3vt1P7vOpLg6FKkS690ghA/vk6UdkgQy4ZAqGJPZypS1x5n+9ynMVnlpS67n565j7D31uVuWdkiVnEw4pArjSFw6L/y0W04XL92SejcI4aP7GuAvSzukSkomHFKF8NM/Z/lg+UFMZtnVVbp1+bnr+ODe+vRrJEs7pMpHJhzSbS0z18I7S/bz+17ZA0W6ffRpGMIn9zfEx03n6lAk6aaRCYd02zpwPo0XfvpPjqsh3Zaq+hn59vEW1AvzcnUoknRTyIRDui3N3HKaT1cckaOFSrc1o1bNZw825N4m4a4ORZLKnUw4pNtKWraZNxfvZdXBeFeHIkll5on2kbzXpy4atcrVoUhSuZEJh3Tb+O9sCi/+tJvzqTmuDkWSylzr6n589VgzOWaHVGHJhEO6LSzYcZZRvx2QY2tIFVqot4GvH29Ok6o+rg5FksqcTDikW97Ev44ydd0JV4chSTeFTqPig3vq80irCFeHIkllSiYc0i3LbLXx1uJ9LPnvvKtDkaSbbmCrCMbeUx+dRrbrkCoGmXBIt6QMk5nn5v7LlhNJrg5FklymVaQfPwxtgadB6+pQJKnUZMIh3XJi03J4YuZOjsRluDoUSXK5BuFezH6ilRwSXbrtyYRDuqUcjk3niZk7iUs3uToUSbplRAW6M/fJ1oT5GF0diiTdMJlwSLeMzccvMnzuv2TkWlwdiiTdcsJ9jMx9qjXVA9xdHYok3RCZcEi3hF/+jeGdJftkt1dJuoYADz0/Dmslh0OXbksy4ZBcbvbWaEYvO+jqMCTptuBl0DDziZY0r+bn6lAkqURkwiG51PwdZ3n31/3Iq1CSis+oVfPtoOZ0rB3o6lAkqdhkwiG5zOJ/Y3jjl73Y5BUoSSWmU6uY8kgTejcMdXUoklQsckQZySWW77vAm4v3yWRDkm5QntXGC/N3s3S3HBhPuj3IhEO66VYdjGPkgj1YZbYhSaVitQle/3kv648muDoUSboumXBIN9X6owm8+NNuLDLZkKQyYbEJnp/3H7vPprg6FEm6JplwSDfNlhMXeW7Ov+RZba4ORZIqlOw8K8Nm7eREQqarQ5GkIsmEQ7opdpxO5qnZu8i1yGRDkspDSraZITN2EJcmR+mVbk0y4ZDK3Z5zqQybtZMcs9XVoUhShXY+NYfBM/4hLdvs6lAkqQCZcEjl6kJqDk/N3kmmHK5ckm6KY/GZPPXjTkwywZduMTLhkMpNTp6Vp3/cxcXMPFeHIkmVys7oFF746T/ZE0y6pciEQyo3r/+8l4MX0l0dhiRVSmsOJ/DOkn2uDkOSHGTCIZWLL9ce54/9sa4OQ5IqtUW7Yvhi9TFXhyFJgEw4pHKw8kAcX6yRNzlJuhV8ue44qw/FuzoMSZIJh1S2Dsem8+qiPXIyNkm6RQgBry7cw6lEOUaH5Foy4ZDKTHJWHk//uIvsPNk6XpJuJRm5Fp6d8y9ZsreY5EJytlipTJitNh6f/g//nE52dSjSTZC2bRGpm37Es/k9+HV7BoDso1vJ2PMnefEnseWkEzr0S3TBUdfcT9xPb5N77kCB5caoFgQ9NAaAzIPrSd04G2E24dGoB75dhjnWs6TFE79wFKFDJqPSu5XdCVZQfRqGMO2x5q4OQ6qkNK4OQKoYRi87KJONSiI39hgZe1ehDYx0Wm4zm9BXqYfbHXeSvHJqsfYVeP97YL38rduak07szBdxu+NO+9/ZaSSvnIp/n5FofEJI+GUs+oiGuNVoCUDSqmn4dhoqk41iWrE/jul/n+KpDtdOBCWpPMiEQyq1Jf/F8NM/Z10dhnQT2PJyuPj7BPx7vUja1gVOj3k06ArYSx2KS230dPo76/AmFK0etzr2hMOSGoeid8O9bkcADBGNMF88CzVaknVoA4pag1uddqU5pUrn85VHaF7Nl6YRvq4ORapkZBsOqVTOp+Yw+reDrg5DukmSV3+NsUZLjJFNymX/mfv+wr1uR1Q6AwAav3CEOZe8+JNYczLIiz2GLjASa04GqX/Pw6/7c+USR0VmtgpenL+btBw5/Ll0c8mEQ7phQgheX7SXDNkQrVLIOrSRvLiT+HYaUi77z71wFPPFM3g06uFYpjZ4END3FS4un0Tcj6/i3qArxqjmpKz/Ac/m/bCkxXNh5ktc+GEEWUc2l0tcFVFMSg5v/rLX1WFIlYysUpFu2A+bT7PtVJKrw5BuAkt6Islrvyf44Q9QNLpyOUbmvtVoA6qhD6vjtNytdjvcal+uNjGd3Yc58Qx+3Z/jwnfPEHD3G6jdfYn98VUMVRugdvcpl/gqmlUH45m15TRD21d3dShSJSETDumGHI/PYPyqo64OQ7pJ8uJOYMtOJXbWyMsLhY3ccwfJ+G85Ea//iqJS3/D+bWYTWYc34dPhsWuuJyxmkv/6Gv9+r2FJiUXYrBgiGgKg9QsnN/YobjVb33Aclc0nfx7hzloB1AzyvP7KklRKMuGQSsxstTFy4R5yLTZXhyLdJIZqjQkd9n9Oy5JWTEHrXwWv1g+WKtkAyD6yGWE1416/yzXXS926AENUc/QhNcmLPwm2y2O+CJsFbPKaLIk8i423F+/n5+faoiiKq8ORKjiZcEglNnnNMTkpWyWj0ruhu6obrKLVozJ4OpZbczKwpidizbRXs5mTYwBQu/ui9rD3iLi4fCJqT398Ow112lfmvr9wq9UGtdGryBjyEs+QfWQToUPtXW41flVAUZGx9y/UHr6Yk2LQhdYqg7OtXHadSWHO9jMMbhvp6lCkCk4mHFKJ/HsmhW82nnJ1GNItKOfEPyStmOz4++KycQB4tx+Iz532qhJLeiIozm3VzcnnyY05RNCAD4vctxCC5FX/h2/Xpx09WFRaPf59RpK8+muE1Yxf9+fQeAaU8VlVDuNWHqVb3WDCfIyuDkWqwORIo1KxZedZ6D3lb84kZbs6FEmSyliXOoHMfKKVq8OQKjDZLVYqtg+XH5bJhiRVUOuPJvLbnvOuDkOqwGTCIRXLtpNJzN8hRxOVpIps7O+HSM7Kc3UYUgUlEw7puixWG6OXFZxgS5KkiiU5K48PfpcjB0vlQyYc0nXN2hrNsfhMV4chSdJNsHTPBdYfTXB1GFIFJBMO6ZoSMkxMWXPc1WFIknQT/e/XA2TJKQukMiYTDumaPltxRM6VIkmVzPnUHKaslV80pLIlEw6pSJZz/1I9eZOrw5AkyQVmb43mQmqOq8OQKhCZcEhF0qx6mxfjR/Ff5DTu8k92dTiSJN1EuRYbk9ccc3UYUgUiEw6pcAeWQMwOAPziNjM9ZyQrav1OFUOuiwOTJOlmWfzfeU4kZLg6DKmCkAmHVJAlF9aMcVqk2CzUOzefTcbXmFpjF1qVHKBWkio6q00wbqWcFVoqGzLhkAr651tIPVPoQ6qcZO4+P4kDIR/wTBU5EJgkVXR/HYrnv7Mprg5DqgDkXCqSs+xk+LIJmNKKtXpC2F28nNKfbSne5RuXJEku07q6HwufbevqMKTbnCzhkJzt+K7YyQZA0IW1/JT3Mr/WWkWQ3lyOgUmS5Cr/nE6Wg4FJpSZLOKTL8rLgi/qQc2PFp1b3IH7xHsbbpxsihFLGwUmS5Ep1Q71Y8dKdKIp8b0s3RpZwSJf9O+uGkw0AdVYCD1/4jIPhn/NoaGzZxSVJkssdjk1n2d4Lrg5Duo3JEg7JzpJnb7uRXnbTU8dU6csLCfeyJ92jzPYpSZLrRPi5sfa1TmjV8ruqVHLyqpHs9i0s02QDoErMH/wqRjK/1ga8tXJ4dEm63Z1NzuZ3Wcoh3SCZcEhgs8GWyeWya8WcTdtz3/GvzzuMjjxcLseQJOnmmbkl2tUhSLcpmXBIcHgZJJ0o10NoMs7zRNyH7I+YxL3BsrW7JN2u9p9PY1e0nOpAKjmZcEiwedJNO5Rnwi4mp7/Kupo/U9tdTgwlSbcjWcoh3QiZcFR2J9ZC7N6bekhF2IiK+ZVVmpHMqLUVd7Xtph5fkqTSWXUwTs4kK5WYTDgqu81fuOzQSm4GXc/9H3sCRvFaxEmXxSFJUslYbII52wuf/kCSiiITjsrs/L8Q/bero0CbdpoXE0axO/IrugfIumFJuh3M33EWk9nq6jCk24hMOCqzf2e7OgInvnFb+C57JH/WWkaE0eTqcCRJuobUbDO/7i7brvRSxSYTjsrKnAMHf3V1FAUoNgt1zy1gg/41vqq5E71Ktu+QpFvVLNl4VCoBmXBUVod/h9x0V0dRJJUphb4xX7Av+EOerXLW1eFIklSIo/EZbDlx0dVhSLcJmXBUVnvmuTqCYtGnHOWdi2+zI2o6bX2LP4utJEk3x8wtp10dgnSbkAlHZZQWA6c3uTqKEgm6sI6f8l5maa2VBOnNrg5HkqRL1h1JICFDtrmSrk8mHJXR3vkgbr+2EYo1jybnfmS7++uMq7EXtXL7nYMkVTQ2AX/uj3N1GNJtQCYcldGe+a6OoFRU2YkMOP85+8M/57FQOZGUJLna8n3yfShdn0w4Kpsz2yC5Ygyy5XZxPx+nvM6WGnNo4pXp6nAkqdLadSaFuDRZrSJdm0w4KpvbpLFoSYSf/5NfbS+zoNZ6fLUWV4cjSZWOEPDH/lhXhyHd4mTCUZnkZcOh31wdRblQLDm0Ofc9O33eYUz1w64OR5IqHVmtIl2PTDgqkyPLb+mxN8qCJuM8Q2M/ZH/EJO4LTnB1OJJUaew+m0pMSrarw5BuYTLhqEwqaOlGYTwTdvFF+qusr7mI2u5yVktJuhn+2CerVaSiyYSjsrCa4dRGV0dxUynCRvWYpaxSv8yMWltwV8tutJJUnpbLhEO6BplwVBZnt0NehqujcAklL5Ou575iT8AoXq92wtXhSFKFtf98GmeSslwdhnSLkglHZXFitasjcDlt2mleiH+f3ZFf0T0g2dXhSFKFJEs5pKLIhKOyOL7G1RHcMnzjtvBd1susrPUbEUY5doAklaU/D8iEQyqcTDgqg7TzkHDQ1VHcUhRh5Y5zC9mgf41pNXeiV8n2HZJUFg5dSCctW853JBUkE47K4IQs3SiKypRCn5gv2Bf8AcOrRrs6HEm67dkE/HM6ydVhSLcgmXBUBrL9xnXpU47xVuK77IyaTnvfNFeHI0m3tW2nZMIhFSQTjorOaql03WFLI/DCOubmvcxvtf4kRJ/n6nAk6ba0/ZRslC0VJBOOiu7cPxV+dNGypljzaHxuDlvd32BC1F7UimzfIUklcSQundRsmbBLzmTCUdHJ6pQbpspOpP+FzzkQ/hmDws67OhxJum0IAf+clqUckjOZcFR0J9e5OoLbnvHiAT5MfoMtNX6kmXemq8ORpNvCdtmOQ7qKTDgqMksuxB9ydRQVRvj5lSy2vszCWuvx1VpcHY4k3dK2nZQJh+RMJhwVWfwBsMn+8GVJseTQ+tz37PJ+mw+qy2ROkopyND5DtuOQnMiEoyK7sMfVEVRY6swLDI79iAMRE3kgOMHV4UjSLUcI2VtFciYTjoosdo+rI6jwPBL+ZWLaK6yvuYg7PLJdHY4k3VJkOw7pSjLhqMhkCcdNoSCoHrOUP1UjmVVrM+4aq6tDkqRbwp5zqa4OQbqFyISjorLkQsJhV0dRqSh5mXQ+N409/qN4s9pxV4cjSS53IkH26pIukwlHRRV/UDYYdRFtWjQj4kezJ/L/6BEg67Clyisz18KF1BxXhyHdImTCUVHJ9hsu5xO3lW+zXmZVraVEGk2uDkeSXOJYfIarQ5BuETLhqKhk+41bgiKs1Dm3iHX6V/m65g70KjlMulS5yGoVKZ9MOCoqWcJxS1GZUukdM5n9wWMZXjXa1eFI0k0jSzikfDLhqIgsebLB6C1Kl3KctxLfZWf177nTL83V4UhSuTsuSzikS2TCURElHQerHOHvVhYYu545uS/zW60/CdHL10qquE7Ey4RDspMJR0WUFuPqCKRiUKx5ND43h63urzOxxm7UimzfIVU8GbkWYtNkTxVJJhwVU9o5V0cglYAq+yIPnh/PgbDPGBx2wdXhSFKZOyZLOSRkwlExyRKO25Ix6QAfJL/O1ho/0sxbNrSTKo7jsuGohEw4Kqa0866OQCqFsPMrWWx9mUW11uKrtbg6HEkqteOyhENCJhwVkyzhuO0pFhOtzv3ALu+3+aD6QVeHI0mlcl6ONiohE46KSSYcFYY68wKDYz/mQNUJPBgc7+pwJOmGXMzMdXUI0i1AJhwVjc0GGbLhYUXjkfgfE9JeZUPNhdT1yHZ1OJJUIslZsuu3JBOOiiczDmyy3r8iUhBExvzGCtXLzK71N+4aq6tDkqRiScmWCYckE46KRzYYrfCUvCw6nfuaPX7/4+1qx1wdjiRdl9kqSMuRs1dXdjLhqGjkGByVhjb9DM/Fj2FP5FR6BSa5OhxJuiZZrSLJhKOikQ1GKx2fuG18nTmSVbV+JcrN5OpwJKlQyVmy4WhlJxOOiiYr0dURSC6gCCt1zv3MGt2rfF3zH/QqOUy6dGu5mClLOCo7mXBUNGbZ370yU5lS6R0zhf3BY3m+arSrw5EkB1mlIsmEo6KxyCJ1CXQpx3kj8V12RX1HR79UV4cjSTLhkGTCUeHIhEO6QsCFDcw2vcyyWisINcgbvuQ6SbJKpdKTCUdFI6tUpKsoNjONzs1li/F1JtXYjVqR7Tukm082GpVkwlHRWOSbWiqcKuciD5wfz4GwTxkaJnszSTdXhsm1AxLOmjULHx+fEm0TGRnJ5MmTHX8risLSpUvLJJ6r910cGzZsQFEUUlNTb/i4ZbGPGyUTjopGVqlI12FMOsiY5DfZVmM2zbzltOFl4dy0oZz5vJ/jX8Kvnxa5riUzmZhvn3Fa/8LskU7rxC98//Lj4+7BkpnseMx0/ghnPu9H+p4/y+t0yoVViFJtryjKNf/17t0brVbL3LlzC93+77//JiwsrNDHxowZg6Io9OrVy2n5zp07yczMRFEUOnfuXKr4r7Zz506eeeaZAsujo6MLPb/HH3+cdu3aERsbi7e3d7GO0blzZ0aOHOm0rKT7KEsy4ahoZJWKVEyh51ex2PoyP9dag79OjgJ5oy7MeAFbxkVQVIACQM6xLUUmBKmb5mBNvWK+I0WNOe4E8b98AIDFYsIU/R8oCihqEDZiZ7/iWD3+p7dBUXCLal5u51QerLbSJRyxsbHo9XqnZR4eHlSpUoVhw4bx008/0bdvX2bOnFlg25ycHH755ReeffbZIvcfGhrK+vXriYm5XPoXGBjIp59+iqenZ6liL0xgYCBubm5FPr5mzRpiY2Md/7766it0Oh0rV67E19f3ho+r0+kICQlBUZQb3seNkglHRSNLOKQSUCwmWp6bwQ6vt/mw+gEUpXQfCpWROTEaAMXgDio1Kjf7N8eUtdMLXT/r4Ab7+np3e1Kh0QBgOrnz0s/d9hU1RlBrAbBlpQCQ8Ns4+1xJGmN5nEq5Km3CYTAYyM11rjLOzMwkJiaGuXPnEhERwcqVK1m3bh0GgwG9Xk+DBg1Yvnw5L7/8Munp6bzzzjvUqVMHNzc3+vfvz88//0xkZCRjx44lNjYWNzc3pk+//LopioLFYsHPz4+///4bgB07dmCz2YiKisLDwwOtVouXlxdubm54eHigUqmoWbMmb7/9NgAzZ86kbt26GAwGFEVxlDhcXaWSlpbGM888Q/Pm9kTy7bffJj4+npCQEEJCQvD29mbDhg088cQTiCtKi7Zs2UKnTp1wc3PD19eXnj17kpKSwtChQ9m4cSNTpkxxlJJER0c7qlRSUlKwWOzVXIsXL6Z+/fro9XoiIyOZOHGi0/McGRnJJ598wrBhw/D09CQiIoLvvvuuxK+hTDgqGplwSDdAnRnLoNhP2F9lAv1D4l0dzm3jyqqOgg8W0Z7KZgYUEAIE9hmeARBYczLRBNe4tL0JLn0goKiwZCaTc2QTqNQoanUZncHNU9qEw8PDAwCVSsWECRPw8vJyfPsfNmwYmZmZBAYGolKp0Gq1BAYGcuLECQYMGMCCBQtQFAWz2cyCBQtYuXIlK1asYMCAAZw9exatVoteryc1NZUJEyYUaKtRt25dx+9ffPEFb775JqdPn8ZsNmOz2cjIyCAnJ4d77rkHb29vMjMzGTduHPXr1+edd97h448/5u2338bPz4/p06cTFhbGmTNn+OSTT5g2bRpCCPr27cupU6dITrZfU2fPnqVJkybUr1+fbdu2AbBnzx4A0tPTHUlEp06dqF+/Pu+99x5hYWFs2LCBOnXqkJmZSYsWLXj66aeJjY1l8eLFVK9enR07dgAQFBTEnDlzUBSFAQMG8Mgjj7B//37GjBnDO++8g7+/v1NiM3HiRFq0aMHu3bsZMWIEw4cP58iRIyV6DWXCUdGYZcIh3TiPxN2MT32VjTUXUNcj29Xh3PKyT//n+N2301DCnpiKe91O191O5eZNyOPj0YXWRl+1gWN5btxx1PnJhLABlxION18uTB9+aS0FYcrg/NfDOPfVkDI6k/JX2oQjv+TBZrPx+uuvk56eTkREBKGhoRw4cIDQ0FBiYmIQQpCZmcn58+eZM2cO8+bNIyMjAyEEiqIwZ84c+vXrR05ODiqVigULFhASEkJubi5qtZqsrCwA/vvP/trqdDri4uIcVRAmk4kpU6YAkJeXh16vJzQ0FJ1Ox6JFi/Dx8SE+Ph5FUTh06BAJCQm89dZbLFiwgBYtWqAoCl5eXoSHh9OvXz9GjRrF22+/zf79+/nqq68c55uWloaiKBw5coT27duzc+dO6tevD4CnpyexsbHcf//9tGzZkmnTphEaGsqECRM4fPgwy5Yt4/z585w6dQo3NzdCQkLw8/MD4NtvvwXsJTX33HMPISEhhIWFMWrUKGrXrs3QoUPx9fVFrVY7Vbv06dOHESNGULNmTd566y0CAgLYsGFDiV5DTUlfdOkWZ5FtOKTSURBUi1nG2CpWLmgfJMsrhzytCbNFT16uDqPZjMFiQm81oxUW1EJgESosQo2wqtDYVGiECo1NjcoGGqFGZVOwqRSEogZFhU1RQFEhUBCKgqJSsKGAUBBKfksIYS8FABTFhoIAoYB9zUuPXy4dQABCXFpPXF7GpeYQKKAoKML+89ISx01VcSy79FO59LvCpW246nFYdCKTyYBeq0e/cxEX1yRTPbQaRy9F9XM17aVj4timBaDJyyJ74duYszPRXqo2Afgo1I2aoZ7cBWhUaqw2G4pKIVCrEJ+ZhUGjx3Sp5MTPw5fkzCQ67ZzDmw+9ZA9PXDqXIv6PcPx26Ty4/BwVsV6Bx4V9oeL4nSK3cTqeR+mqgbp06QKARqNhyJAhzJkzh6pVq3Ly5Em2bt2K7VJJkVarJS/PPubH7t27UavVeHl5kZ6ejtlsZsqUKY51bTYbDz/8MCqVCkVRnL7RHzhwAACj0TlulUrlqIrw9vYmJyeH1NRUwsLCiI6O5pNPPuHRRx9Fq9U6qoCio6OxWCwcO3YMIQRxcXH4+Piwbds2MjMzGT9+PEIImjVrVuC8H3jgAX755Rf0ej1arf1aURSFkJAQjhw5wkMPPQTAsGHDHNtERUXx5Zdf0qpVK8xm5/ZZTzzxBKNGjaJ69er4+PhgMBiIi4sjNzcXvV7P3r17SUhIQKvVYrVaHQlwo0aNHPvIP35CQkLxX0BkwlHxCDnGglR6v9brRvYJDZ6KmbrJevLcAkgKPI4m8BwZ7kZi1X4k2KqRkutPjkmLZ14WYdY0/CwZaG2ZKGRjs2UjVCaEOhebYkJtNaPNMyOsgFWFzaKAGTDbwCRQmW3ozQoGM+hsWtQ2DRqhRS00qGwa1EKDItQoNjXYVCg2FdhUgBqbWodQay//VGmwqTUIRYNVUYNKhVWxJze2S0mEDRCKYq/VQFz679Lvwv67sFmxXVpq/5AVoNgutXWxodPbGxPmmnO5p0NP6kTUYM3OjRw9dwKA6ORjCGGzb3/pp6IoqFQK7w1+gokL5hKfcrlaRqhiOJdir9Iy6LVoVGpSs7KIT0lAAWzC/uFh0KhRKfbfl2xdSstqYLNasFlt9pit1nK+QkourHZdqjH+hrevU6eOo03Fjz/+iNls5tSpU7i7u5OVleVIGt544w0+/vhjAKZMmYJarXYkIADfffcdzz//PHl5eRiNRgwGA5mZmeTl5eHh4UFQUBAnT57k119/BSAxMZHExERHYmqzXb7HpqWlOX7PyLD3+MpPUPz8/IiNjXVUl/z2228IIVCr1aSlpTlKMLRaLQaDAS8vLxYsWOBIrBYtWkS9evUA+OWXXwrtxnplMrR7927GjBnDnj17SE5OdsSZnp5e4Hm8kre3NwkJCfz666888sgjzJgxg4YNGxaoLslPdvIpiuL0XBSHTDgqGq075KS4OgrpNvZrvW6MMZ3gh9P1iKvqxzHTdnxS3WgS344k7/oku53HnBFNixq78PePxWbYT5ZW4aKxDbHahsRQh2irL8dzNKgsEGABTzMYhA0VVnxEOgG2VPxsqfgqqQQbMwh0S8ebNBRVLhaVmVxVJibyyFEJUrV60jUa0lVq0lUK6djIEFbSbXmkW01kWnIg14KbRYWXTYeXTY+nVYenRYO7TYObRY27RYXBrMJgxp7Q5Al0ZhvaXCvaXCvqXAuqXDMqkxnFlAumXMgxIUwmEAKhKKAzIPRuCL3R/k9nJC/j8s389zVLmZmTRZRvkGNZlWSwqfXYVFpHIuRpcCc9J5M3v/6ywHMf7NOPlAz7h5gpz4rVmou9jECg0xoJ84/kdNxhTBYrRpsbkEmeWUHRPYMacG7ZYUOlBkUlUKkEiiJQ1Pafjr9Vwl56lP+3cjmhsidV+cttKNgQisCestnXsydi9mTM6XdhBYRTsuUdElLqa1OtVmO1WmnSpAl79uzBYrFQu3ZtR0mG2Wx2lD4AZGfbqwWHDx/O119/jUql4vnnn8doNOLm5kZqaio5OTmO6oOsrCxOnz4N2EsybDYbAQEBBAcHc/jwYUcJSH5pyKOPPsqiRYuwWCyOtheaS42A86tmNBoNR44ccWxz7733Mnz4cAYMGEBKSgrffvstKpWKYcOGObYFiIiIoGbNmo5Eo7AP90aNGrF27VrefPNNevToQY8ePZg7dy6BgYGcPXuWnj17FijhuLrEpn79+qSmpjJz5kweeOABfvrpJ1q3bo3NZrtcvVdGZMJR0ejcXR2BdBv7tV43RuccByHwOBCNZ1ACcabWJCb9QIJHNHe5PU6Hk5Fke0dwNCmRvw+5k5tbhWrVVEREpBNlXE5u7mGEsN/0s7Q1SfBsTay6LmdFOKcsXuww+WOy2euTNUIQYFPhb1XwMAt0eTZEjgVztoWMzDzM2dkEqtKpZsimqj6TGposgtVp+JOOj0jDw2LGaM5DZ0omz5JFht6dDIMX6Xp30j2NpOsMpGu0pKvUxKlUpCuCdGElQ5hJt+aSbs0hw5xFlqXw9iqKUOMlDPjYDE7JjIdVg7tVITNWA5vt62bacunRIIoV+044tjck/037OYvJs9nY37sHSk4uTwb48sW5TMc6asAKeCgKdX563l6NAtzt7kYNrZYJSRcB8LTlYUs8bn/egBZksxrwUix0OvQ5Qm/EptODzojQ6hFaAzaNHqHVITR6hEaHDR02tRaBDqG6VBKU/1NRY1Mu/USFjUs/hYJNqLDZFKxCwWoDq03BagWbTWC1CqwWgc0isF2jnYbO88a7cgIkJSVhtVoRQrBnzx60Wi1ms5nDhw8DYDabCQ0N5fPPP3faLr/HCtgTlrCwMGJiYggPDyclJQW9Xk9AQADZ2dlkZGRgtVoxGAwMHDiQmTNnkpSUREpKitMHfrt27diyZQt//vmnI8HJT0bWrVsHXC5ZsFgsHD161HH8JUuW4OXlhZeXFx4eHvz999+cOnUKm81Gp06X2//s2bOHX375hZ077b2XFi5cyMKFCwF7ImU2m3nnnXdo2LAhQ4cO5eLFizz11FMcOHCAhx56iF27dgH2qqHo6Gin0pgrvfbaayxYsICzZ88yZswYsrKyWLduHdOmTbvRl6pIMuGoaPQero5Auk0tqdeNMTnHEQg6m6ohUk7idvEEuUoYIbV6cnbfryxJnUjf1s/jdl5N07RgGuiDOF01nX0px/n7jACa4O7elFq1LPgHxKIVB3DPmEd1oN2l49jQkGZoSryuOedVtTljC+ak2Y3DJoHNXQFfLaAFjIA350QoMTYFXwsY8wTaPBsix4opy0x6Zi4X03PJzrOiKIIIQy5RlmwiLNlUNWcRkptOTSUDX9LwsqbiYUlGn5uMxnQRJffyoGcWlYYMgxcZbt6k6z3sCYtWT7pGdylhUchQIB0bqcLMOVse6ZY04lWXq0PSs3NZvve403M6uPMhcmZbQcCAAecBSN0u4JvL6+RXfmQKwQ8v1+bMjjjEcViakZbfhAWNSqFBnapkZuVy5kwsFmB1lj1pifTxQu2poJjSIfVSyUxOjqP9y80kVGp76Y/BDaEzIvQG0BoROj3uIQ2Bpje87/xeKmD/EDebzajVakdjUCEESUlJBbYzmUyO7qdms5kzZ85gNBqJjo5GpVKRm5vL+fP218bT0xMfHx/OnTvH/PnzHctMJhPWK6qptm/fDkBKSsHS5L/++guAHj16sGvXLpKTk3FzcyM7O9uRlJw9exaLxYJer2fOnDnccccdbNu2jffff9+x/dtvv023bt0wGAwAnD9/nsmTJzNkyBAsFgtvvfUW7777LsuWLWPUqFEA9O7dm1atWuHt7c2HH34I2Etq6tWrR05O4e37mjVrxqJFixg0aBCffvopHh4ejB49mqFDhxbjVSkZRQgXXJVS+Zl9N5ze5OoopNvML/W780H2sUutGGBMdDPqzd+BpUptNtV8GRC4u/9GUswpADq3GkRwcjhY7evbVILYCBP7bKc5nxDrtO+qEfbSDze3U+TmHkKIwgcZMyveJBlbE69tRIwSRbTVn+O5OhLN168n9hIKgVbwMoPRLNCYrFhyLORkmUnLzCMx3YTZ6nyr89RYqOmWQ6Qxh6r6TMKuKj3xtCRjMKegMyWhyklCsRUcmvv//snlxZX2hoFeRhWZJhv5X/IVBWb+8jDvvLKS9DQTL/x4P+nCwrwXVpIek1lgX6ig/vT6HH7pMFgguH8wcT/HIXIFuiCd/TnKMCNyBIre3qjVZrLh3dabqs9WLfic2PT4CCNeNj1eVh2eNi0eVi3uFg3uFjVuFhVGs4LRoqA3gz5PoM0TaPMuVTPlWVCbzKhMeSimPOdqphLW3QN4du9GlalTS7yd0zl5eTnaSqhUKnQ6HVarlV69evH777/TqlUrduzYQf369Tl69CgWiwWDwYDJZKJx48Y0adIELy8v1q5dy4cffshLL73kSDYCAgJITU3l6aefZs6cOYB9nA+DwUCPHj1YtmwZ999/P7/++ivVq1fn9OnTTJo0iTlz5rB7927uuOMOjhw5wu+//87dd9/N/fffz65du0hPTyc1NRWNRkPXrl1ZvXo11atX5/z581itVmw2G/PmzWPgwIFER0dTvXp1FEUhNjaW4OBgHn30UebPn8+aNWu46667AKhRowYxMTHk5eUxevRoxowZw/z583n33XeJjY2lWbNmvPPOO9xzzz3s3r2bJk2asGHDBrp06UJKSkqhQ7zPmDGDJ598kh07dtCyZctSvU5FkSUcFY1OlnBIJfNz/e58eEWyAVDzpL2KQRNzDH1DNbk5VjTGbiiq6QibjQ075lC3dgcaGzoisiyobArh0UbCqUdySG0OuZ/nWKy9mPjcWRvnznoAjTAYGlG7tpXAwHjgIHnmOMcxtSKNkOy/COEvGl8RX44mgkRDay5o6hNDVU5bvDluUpF1RQKRrgjSNdjvaEbAK79Fg70oXRECP6EiwKrgZRHoc20oJivmHAsHM838nZJLcmYuRdUIOEpPjNlEGLKpqssiRJPOlB++AnJRAI1KhVolUGwCqwCdCobs+5MJpkxsFsFn/60AYHV2FumFHEOrKHyZ6sVdmTY+fK8dMxccRrEACgT4eKA2akgwpZKbkwdmge3Sd0WNV+G38XRVLunk2p8GbaGr3CAVnjYj3jYD3jY9XjYdnlYtnjadczJjUTCYLyczOXWrUaWUR/bx8SEjI4NOnTqRlZXFG2+8waZNmxzVKseOHQPg4MGDPP3003z//fe89dZbjB07lv3793Po0CH8/f3x9PTEz8/PkWwAXLx4EZVKxYwZM/Dz80OtVpOZmUlubi579+4lLCyMNm3a8McffziqUd58803H7/nHvrKBqp+fHw899BAdO3Z0Oo9JkyZx3333UbNmTTIzMxk4cCBgH2ArNTUVHx8fjh49SnBwMDqdjj59+jiSDYB+/fqxf/9+R/UNwMCBAx37yXdleULnzp25VvlCbGwsDRo0KLdkA2TCUfHcwgnHp3/nsuSImSMXbRg1Cu2qqvm8m546AZcbJgkhGLsxl+/+NZNiErQOV/NVHwP1g67deGny9ly+3mXmbJqNADeF/nW1fNpNj0Fjb1k+b5+Zt9eayMoTPNlUx/geBse20ak2eszJZtcz7njpb/5wv660qH53Proq2dALNfr9Jx1LfLwF8TmQdtGDKvU6cu7ABgAOH/ubBP9outUYDImXv/37xWm4k2o096rK0eCL7E845ugeaDLBvn1qIAwIIzxcoVpkJu7up8nNPVBo6YfRcpaIzLNE8LNjmUAhXd+IBH1LLqhqc0aEcsrszmmTwFLIPVUoCkmKIEklLtXWKNhvfxrAAHiiFRAgFPwsCh5mG7pcASYLudkWMjPzSM7QsT7ZANjbnwirmbMx9iJ8TVB10kxZWElGZXSHnAxsOjde8Z6Msfo3+KUksr7qw/iTTv1aK4j57ywAVpvN0YXUSyfoknqAUA+FRid3c+BhDVW/gCgfFd7mNDadtLJkgJF+8yHYqJBrFaTnwqM5Zl7PUNurgnRul9qt6MhQa0hXq0hXIAMb6cJCui2PDIuJdEs2GeZMrOLGerNkqHLJUOVSkikAH6pdk4KdPovvm2++cQw7vnHjRsD+IWuz2Rw9SPKvM6PRyPfff8/dd9/t6LEye/ZsjEYjY8aMITk5mXbt2tGxY0e2bNlCu3bt+N///sd7771HVFQUa9euxWKxoCgKY8eOZf369WzatAm1Ws0bb7zBpEmTAHvVjq+vLykpKY7Slfwqkdq1a3Py5Enmzp3LZ5995qjaWL16teOc8quDCnPl8rLoIVKUzMxMDh8+zNSpUx3VMOVFJhwVzS3caHTjGQvPt9TRMkyNxQbvrculx9xsDo3wwF1nf3ON25LHpG15zLrPSG1/FR9tyqX7nGyOvuCBZxHJwLx9Zt5ek8uMe420q6rmWJKNoUvt9ZVf9DJwMdvGU7/nMOteI1G+Kvr+lE3nSDV9a9vfxMP/yOGzbvrKl2w06MFHWUedkg2AnplRiJzDjr+9lHTisSeyqYmNcPPeS3aave46Kekci9PG07fNixjOO99OjOkqmqQH0UAXyOmIdPamnyA1PdVpnfPnBefPuwMN0OsbUKu2jaDAeBTVYfLyzlMUBYF37l68c/dS64rlVsVIirEVcdqmxCg1iLYFcjJXz4W869+czQrEKoJYnQAd4K5gz07y25OAQUCQVcHXCkpsPGcvPXfmhNOgUqPzC0egYMtOQ/EJ49f4IFKUCKxad544fifm5PNc2PU9Kr0XttwsUBtRVCowm8hAxxj/8XTotYL+v/yBxZpD1QBPLuRaOJ9jpccdbuiNWiAHk1UwrImOL3fkocszEXHx9HXPrzBZek/S3Xwut1vRGUnX6shQa0lXq0lXFNIV515BGdYc0s1Z5FpLNjO1h7Z0X4Y6dOjg9A1dURQ0Gg15eXmO5fntFGw2G2FhYSxevNgxX8mwYcPw9/fHx8cHDw8PdDqdY6yJLVu28Pjjj9OrVy+GDx/OokWLeOihh2jYsCHTpk0jPj4eIQT79+9n0KBBzJ8/n1OnTqFWq8nIyMBoNOLj44NOp+PPP+1z6Gi1WlJTU8nOzmbAgAHMnj27wDl5enoSExNDVlYW7u72e/eWLVtQqVTUrl27VM9Xcb3wwgvMnz+f++67z2ksj/IgE46K5hZOOFY+7hzbzHsNBE3I5N9YKx2raRBCMPmfPN7roOeBuvZkYPZ9RoInZPDTfjPPttAVut9tMRbaR6h5tKF9m0gfFQMbaNlxwf7t7VSKwFuv8HAD++Ndqqs5lGijb234ab8ZnVpxHK+yWNigBx8XkmwA3BnrPFGVR0YMcAcA5jwNgRG9yN4/3/G4xZLHb5sn0rHlo4SmRDjadeTT5CnUOuFNTaUZFyJM7BfRxCRc4Gq5uXBgvwoIBUIJDVWIrJ6Fh0c0eXkHsNmu/wGnFjkEZG8kgI00uGJ5njqIRENbYrUNiKEapyy+nDBpSLOW7FuiSYGzGsFZDViv+PxUhVcFk4m85Bh7+wa1mip33knjtuH8t81EliWVO8I9WP/tKLBZUdQae0NHiwlhs6INqYUlK5VZ58OIWbER7w5DMVRvxrm5r6PxCsSSkcDeHjPo8bX9AyHPLYhJ2xPw8/cjsWpb1ldtWKK2J/ncczNwz80gtETPgl2uWk+Gmw/pxku9gnRupGsNpGs09tKVS72CMrCSbjNTTV+6XirHj9sb5FavXt1RijBu3Diys7P57bffyMzMdLSfsFgsdOnShYULF+Lj48PFi/aePsHBwbRs2dLR86NFixasXbuW1q1bk5eXx4IFCxwf9KGhoYwaNcrRIFOn0xEfH4/FYnF0VXV3d6d169a0a9eOqVOnotPpiI2NZdu2bZw6dYrz5887RjVdtWoVer3eMUopwNatW6lZsyZDhgxhzJgxJCYm8uKLLzJo0CCCg4NL9XwV16xZs5g1a9ZNOZZMOCoafdnPalhe0i59fvgZ7SULp1MFcZmCHjUuX5Z6jUKnSA1bY6w826Lw/dwZoWHuvhx2nLfSKlzNqRQbK05YGNLYnkTU8lORbRbsjrVSzUfFzvNWhjXRkZwjeH+9ifVDbt0krTwsaNCDT4pINgCqHnPuPmc8fxi873D8nRgTSnCNBsSfPOC03qadP1G7ZhuaedyFyCz4IacIhfAzRsKpS0pwTQ55xnL0wskii4ZjYwWxsW5APXS6etSqZSM4+CKK6hB5eedKdM46awLhWb8Rzm9ceRll6u6wV8uo77B32zV7ccoEucVoS6/ytn+AqqNqYT17Gq9X3kNbrxFJzwwEs5n0+x9kqxdkhAdi0wv+i1SRl2ofmdGaPwfLpYH6zHHHqdK6J5FeNs5mp+HVvC+odbjV70LWnpX49XoR0/nDCFMGGr9wtHU7oT+3n+TzR/jL0JWNx+sUGmNRbU8ClQz8SMPLmoK7JaXQnjvXo7fmos+IJyCjmHPvhPUu9r4L88MPP2A0GsnMzKRmzZqAvevom2++yblz59i0aRN79+4FwGq10qVLF0ejyhdffJHHHnuMX3/9lb179xIZGem074MHD/LLL78QFRXF1q1bAftAWoXp2bMnEydO5Nlnn0Wr1bJt2zb8/PwYNWoUY8aM4e6772bmzJn873//w2azsXbtWgIDA5k5c2aBnh9ubm6sWrWKl19+mZYtW+Lm5saDDz7oqLKpaGTCUdHcwiUcVxJC8OoqE3dGqGlwqX1GXKb95hvs4Vy1EeyucCat6G+ijzTQkpgluHNGFgKw2GB4Cy1v32lvMOhrVJh9n5HBS3PIMQsGN9bSs6aGYb/l8GIrHadTbdyzIBuzFcZ01tO/XsUt7VjQoAcfZxU94ZK3zYD68EmnZbrjO1Fa3u/Uy9Ji7YBaewyrOc9p3WMntnPR9yzdaz8BCUV/s/aN19I+PoJmXuEcDU7iQMJxTLlFzwOUlwcHD6o4eDAICCI4WKF6VDaenmculX7c2JD+HnlH8Mg7QtQVy2yKjhR9CxJ0TYlR1eSMLZhTeUbO5toKTdHU/oG43d2fzB+/w5Z8EaxWFG8f1CFh9v0lX8SaEIfi5o46ojoqTy9sKclYLyaAzWovEREC09tvc8TLG5V/AJneZ6jSrC0xU9Zj8Auk8+CBrH7d3iCwwYBXOfzLZHKTYzFUa4w+rPBkA0AIhTM5Bs7kXG57ci1X9tyJ0GcSpskkSJ1+Q6UnBbhd//jX4u/vT05ODiaTCYvFQk5ODrt376Zjx4589tlngD1xePvtt/nss8/o0qULUVH2V/aFF14AYMSIEbRq1coxGVv+QFs//vgj3bt3By4PsDVmzBjHsZOSktBoNDz55JOOZUaj0VFykm/kyJH8+eefPPLII1SpUoXatWsXGLHz6oabDRs2dGr8ebXCSh+unGX2diITjormNkk4XlhhYl+8lc3DCsZ7dUsKIQouu9KGaAsf/53LtL4GWoerOZFs4+WVJkI9chnVyZ503F9Xy/1XVJtsiLawP8HK//UxUPPLTOY/aCTEQ6HV9Cw6VlMT5F7x5jWc36Ann2QdvuY6/dKrg2W/0zJVZhqePlrSUy436MxKMxJe9y7O7vuzwD6SUy7wy67x9G3zPMYLhVeD5TOmqx3tPKIjMtibcYKUtOuPlBsfL4iPNwJ3oNXeQc2agpCQi6g1h8nNPXPd7a9FJfLwN23F37SVulcsN6t8STK2IVbTiBglksNxNv4C8v77B0Pn7vh+9n/kLF9C9m+LUIz2dgMZ338JNht+X9gnHtPf2QXTymX4fDIFTa26pE/6ENPKZfakw2JGURS83x9H2rQJJH/5GSgK7lN/YNWqWYg27VBvNbNv8Th7n1u1iqhXR1KlZhXczAKNyT5oWk62mfSMPC5m5JKTV7JGoRkWDbvTPdmd7gkEXXPdEpeeuPmXKJbC5Hdx3bx5M9nZ2dSuXRsvLy+nwb/yR/WMiopi27ZtPProo2RnZ5OZmekYSyM01F6JFHJp9FOTycTFixdxc3OjVq1a3Hvvvbz44ot8++23eHp68vbbbxMeHs6999573Rh79uyJt7c3H330ER988EGpz7kikQlHRWPwcXUE1/XiihyWHbOwaag7Vbwuf7CHeNh/j8sUhF5RM5SQLQj2KDoBGLU+l0GNtDzVzP7h1jBYTZZZ8MzvJt7rqEN1VSvwXItgxB8m5j5g5ESyDYsNOkXa3wq1/VX8E2Pl7joVK+H4qWFPPs28drIB0Op84RNseRtzSU9xfk4uXqiDV+Ae0hNjC6xvteaxbMsX3NniEcLTIim068gVNHkKNU94UUNpSmxELgeI5mx80Y1Gr2Q2w+HDCocPBwKBBAaqiKqRjZfXWcx5+7HaymbWW60thZCsPwnhT5oCbTMt/AXc1z+Mv+dOJvViFr41ovDp3Y+EPfbi+PzSjXweg57GlpxE8vND7Jm0Xo/i6YVITUFR2Uv6dA2b4v/1PFI/fBtdgyZgtmBa/Qd+3y0g95/NkGdC5OaCWkWcQUeSXth7/3qosLd21QH2RN5bKARYwNtqHzRNZbJizbGQnWUmLSOPixkFxycprpKWnqx0a8Yd113r2gIDA4mJiWHatGlUq1aNTp06sWTJEoKDgzl9+jSJiYnExcUhhODzzz9n/PjxjgHDcnJyHINoPfPMM4wZM8YxmubAgQMRQjjGtPj3338JCQmhX79+5OXl0a5dO5o1a0aVKlVIS0vD39/faQj1K6lUKoYOHconn3zC4MGDS3nGFYtMOCoar3BXR1AkIQQv/mni1yMWNgxxo7qv8wdYdR+FEA+F1acsNA2133zzrIKN0RY+72YobJcAZJsFqquKQNSXJuUSggLFIx9uyqV3TQ3NQtXsjrViuWLwBbO1QJvH2968hj35rBjJBkDo4cRCl3uak4BAp2U2qwqPkJ6kJ84qcn+bdy2gVlQrmnt2R2Rcv/hdEQphZwyEcQepl9p5HLlwokRdABMTbSQmGoDaaDS1qVkTQkIvotEcITf3xnpzFMbbW41KBU3q5fHCM/6AP2Dhq/9bywlfM6N1H5PwUTvOq2pzVuRwMs+daAx4vzkGr1ffw5aSjMovgJzli8n8/ksUbx+n/fuM+gwhBCmvPo3Hc6+CzYY15gxBK7aiGIykjnkD895/0dYoujdDmiJIy+9oY6DA+CQqIfAXCv5WFR5mgSHv0vgk2RayMvNIycwjKTO3TAYtDfTQl3ofzZo1Izg4mLVr1xIVFcUbb7zBd999x0svvcTkyZNJTEzkzJkz+Pv7k5CQQFJSErt376Zq1ao0adKEqKgofv31VzZt2sQXX3zBu+++y9tvv83q1as5deoUTz/9NGAfgvyxxx5j5MiR2Gw22rdvT1xcHHPnzqVGjRocOnTomvOMxMbG0qdPH0dJimRXqROO/FHd8kdiK4mhQ4eSmprK0qVLAfugKk2aNHHUrUVGRjJy5EhGjhxZpjFfl3dph9YpP8+vMPHTfjO/PeKGp15xtNnw1isYtfaRE0e21vHJ37nU8lNRy1/FJ3/n4qZVHD1QAAb/mkO4p8Knl5KQu2trmLQtj6ahakeVyqj1Ju6po0F9VSZyMMHKwoMW9jxr/wZ4R4AKlaLww395hHgoHLloo2VY2U5Y5ErzGvbis8xDxVq3isUbTkQX+ph78imuTjgAkuP8CL+jFeeP7Chyv8dP7SDR5yw97hiGEl/8In6feA3t4qvS1DOcY+FJ7E88hslUdDuPwlgscOQIHDkSANyJv38HatQw4eV9DotlP1ZrISN+FsO+fTksWpiGSgVjRsczdmww7e+0X1P//ptDu/bu+OT+h0/uf+SnA3l5gh/nZrFmTTYpySY8ggKoOewpjmz8C32bDuT9t4OMLz/FlpKMvn1nvF57n5y/fkfl5Y2ucXOSnrW34RAWiz2HtloQpRyLwaYoJCqQqLLZkxK3q8cnAa2AQKHgZwEPM2hzrQiTlbwsMxlZZpLTc0nLKXz02HxatYKf+7Wr14pr0KBBvPzyy6SnpxMVFcWWLVtYsGABc+bMYf/+/ZjNZvz9/fH19UWn0zF16lSee+450tLS2LTJPgpzXFwcISEhNG/eHIDmzZs7Dax1pTVr1rBjxw4OHz7s6MGS3zbkamlpaezcuZN58+bx22+/lcn5ViQVNuEoajCVfPndkG7UlClTrjlqm8t4hoJKAyVpzHWTfL3LflPqPNu5iHvmvQaGNrHfjN5sryPHIhixwkRKjqB1FTV/DXJzGoPjbJoNlXK5dOR/HfUoKPxvnYnzGYJAN4W7a2v4+C7nUhEhBM8sN/FFT71j3A+jVmHWfQaeX2Ei1wL/18dAuFfFqE6Z27AXnxcz2QDomxoBouBcFAD603sgonWhj2VltkJnPEBeTtFVF6mpcSzeOY4+bZ7H7ULRpVWFMWaoaJwRSANtAKerZbAv4wTJxWjnUZikJEFSkh6oiVpdkxo1IDQsCZ32GKbcE9fdPp8pRxBVQ0d4FS2Lf0njv/9yqFJVyx9/pJOQYOHuu+11gtOnJ3PxooW33w7iww/jiY8zc1cXN1q2DCAuzsLaPyagOpnH5Deb8erzr9Jz6L14tu3O8jc/xLJ4Llm//Yzfl7PI/H4KbvcOIGfFr2Qv/gldizbk/bcD90efvE6kpWdW4IIiuOCorVEBKq4cvtQoINim4GNRMJptaExWbDlWTJfak+jUquvek4vrnnvu4eWXX8bHx4fly5fTt29fAgICCAgIwGw2U6NGDSwWCx4eHsyaNYt3332XL7/8ErVazT333MOCBQvo3r07P//8s2NkzuXLl/PII484zdaab8+ePY4GoNdz7733smPHDp599llHI1TpsgqbcMTGXq5XXrhwIe+//75jxj6wtzAubOKd67FarfaGXd7eZRJnUcxmc4HR5YpFpQLPMEg7W/ZBlZIY7XXddRRFYUxnA2M6F/2htGGoc0NTjUphdGc9oztfu8hWURS2FNJItV9tLf1qV6yeKXMa9mJcCZINgCZniy7Z0Z7ej6amCkshA2iZsnSOyd2uxWq18PuWKbRt1p+IzFpQjDlSrqQ2X27nEVc1l/3KGc7Gl2Ssy6vjgWPH4Ngxf6AtPj7tqFkrF1+fGMyW/VithQ1AbteqtRutWtsbhi7+JY2NGzNZsSKdyEgdn3waQnCw/XpKTrKQkGBhx45s9u018emnIUz58iJLf01HrYEmjY18OTUMD10iGSk5vNBjOzrdDmidwuY/pvHgwDvwTl/EvBO76f6/l9jXvCkHPnif7F/n4/bwYLR1GxQZ482Uo0C0WoA6vz1JftWNvT1JG++ya8weGRnJ8uXLeeGFF5g9ezZfffUVYL+nDxkyhFmzZhEVFYUQwmm47/r161OnTh3HF8WjR4+yevVq1qxZwxtvvMG0adPYuHFjgfvu1dO5X8uGDRvK5iQrqIrxVa4QISEhjn/e3t4oilJgWb5Tp07RpUsX3NzcaNy4Mdu2bXM8NmvWLEcmXa9ePfR6PWfOnGHo0KHcd999xY4nLS2NZ555hqCgILy8vOjataujzzjYu2A1adKEGTNmEBUVhV6vv/ESlFu4WkUqfz/eQLIBEHCo4GBc+RQh8PUp+htqwrlI/KsUXsx8tW3//cLOvL9QipgD5HoUoRB61kCPM3V4yLMT9avUvmZ9enGlpgp27dSxenUUGzfcQ+yFQaiUfhj0tbl2Pyl45ZVA/lwZxdffVKFRo8sfUG++FcSkSWFs25ZN7Tp6tmzNIjXFSkCAhr59vHjvf0FUrarDx0eFv7+aXbtyyM21sX+/iYce8uGBXlks/mQO/3sxl8GZTzCh+mj+mGVkwcp7+PT5OgzxjqGzZx5V9KrrROhaVQylq04ZOnQos2fP5rfffkOj0fDcc8+RkJBAbm4uPXv2LLB+YGCg05fO9PR0Tp92br9jNBq55557+PLLL9mwYQPbtm1j//79V++KRo0aERMT45grRbpxFbaEoyTee+89JkyYQK1atXjvvfcYOHAgJ06ccBSvZWdn8+mnnzJ9+nT8/f0JCrp2d7GrCSHo27cvfn5+rFixAm9vb7799lvuuusujh07hp+fvYX3iRMnWLRoEYsXLy7dDdQnAs5uvfHtpdvW7Ea9mZBxsMTb1TMHIs4VnXAAeKmzSKSokifFaXK36zkV/S+JXmfpXf9plLgbm88DwDtRQ9vEqjT1COd41WT2XTxW5DTcJSGEwokTcOKEL9Aab+821KqVh4/veazW/VgsqSXaX2ysmQP7Tei0CmM/CCYtzcaXUy6SnmHljTeCUBSF/40K5uuvk5j2VRKtWrnRq7cn839KpWkzA3q9wssvnSctzcZ993tx331b8M/ZQr0rjpGnCuCisQ1x2obEUI3TVj+Om7SkWMpmzo3SqFrKhAMgLCyMhg0bMn36dA4dOsTQoUNp165doffKrl27MmvWLO6++258fX0ZNWqU03qzZs3CarXSunVr3NzcmDNnDkajkWrVqhXYV6dOnejYsaNjQK6aNWs6ut726tWr1OdVmciEA3j99dfp27cvAGPHjqV+/fqcOHGCO+64NJyz2cy0adNo3LjxtXZTpPXr17N//34SEhLQ6+3F/hMmTGDp0qX88ssvPPPMM4B9lsE5c+YQGFiwcV6J+BXvm6ZUscxu1OuGkg2AXknhQMHurVfyyD4P1Cjy8asnd7uejPREfvnnc3q3HYHHBbfiB1sIQ6aKhscDqKf1Jzoig31ZJ0lKTS7VPq+UlibYtUsLRKIokVSvDlWqpKE3HAdOXXd7YbMPnfHOu0F4XOri/dxwfz4YG89LLwWg16to2NDAtGmXe5nFnMtjzZoMvvm2Cq+MvMADD3rTsqUbTz91jkYNDUTVcK5C1NkuEpa1nDCWO02SlqWtSYKhNbHqupwlnNNmL06YFExFTY1bDiKNpe+holarMRgMVKlShSpVqjBw4EDHoFg2m42jR49y9uxZ5s+fT+3atalduzb9+vXD29ubl19+maVLl3Lw4EE6dOjAP//8g06nQ1EUrFYrKpUKIQSPPfaYY2p6gJ07d/Luu++yd+9eMjMz6dOnD2q1mlq1ajkGG1MUhe+//54//viDVatWER4ezsSJE7nnnnsc+zl48CBvvvkmf//9N0IImjRpwqxZs6hRw/5+mjlzJuPGjeP06dNERkby0ksvMWLEiFI/Z7camXBgLzLLl9+NKSEhwZFw6HQ6p3VK6t9//yUzMxN/f+eBb3Jycjh58vKojtWqVSt9sgHgX/SHglQxzWrUm4k3mGwA1I++fimDMfYIuF372rp6crfrsdms/LFlKq2b3Edkdt0St+u4mtqsUOOkF1FKE+Kr5LJffZYzcSUbBv16hIBTp+DUKW+gBfAHJlMH9DpPrLZ9WCwFz93PT01AgNqRbABERGgRAhITrVSp4ly7LYRg0hcXefY5f2w2OHEij44d3TEYVDRqZGTvPlOBhKMo7uYTVDefoDrQ7tIyG2rSDM2I1zXnvKo2Z2zBnDS7cdZkozzKQ6obS1/C0axZM0evwFOnTrFy5UpHe4spU6Zw4cIFfvjhB5o2bcqMGTP44osvOHjwILVq1SI6OprXX3+dAwcOMHnyZCIiIhg2bBh5eXl4eXnx0Ucf4ebmxoABA3j//feJjo4GYN26dQwZMoQvv/wSgIkTJ7J8+XK2bt2Kp+flwYLGjh3LuHHjGD9+PFOnTuWxxx7jzJkz+Pn5cf78eTp27Ejnzp1Zt24dXl5ebNmyxTGOx/fff8/o0aP5v//7P5o2bcru3bt5+umncXd3Z8iQIaV+3m4lMuHAeerf/JbUV/b7NxqNpWphbbPZCA0NLbRBkY+Pj+P3/NkCS02WcFQqMxv1ZlIpkg0A7/1nr/tBoz++Cxr3veY6hU3uVhz/7FlKfMRp2vjdjUi7dhfL4lCEQsg5AyHUJj0wikPecRyOPeEYabKsnTqlZs2aCKAq1aurqFI1DYPhBLmmIwis1G9gYNOmLHJybBiN9uQiJsaMSgWBgQWrBP5ckYGXl4p27dzJyLDHnD/OlMUiKO3M5Cqs+Jp24mva6TQYl0XxJMnYhjhtY2KUKKKt/hzP1ZFYykQwyq1kPZMKs3z5cjw8PLBarY7u0flzjkyYMIG33nqLRx55BIDPP/+c9evXM3nyZEejUrCXZue3+Xj55ZcZOHAga9eupX379gA8+eSTTkOJd+3a1SmGb7/9Fl9fXzZu3Ei/fv0cy4cOHeponPrJJ58wdepUduzYQa9evfjqq6/w9vZmwYIFjs+aK3u8fPjhh0ycOJEHHngAsE9Od+jQIb799luZcEgl16xZM+Li4tBoNAUmDSoX/jXL/xjSLWFGo958Ucpko62pCraL0dddT52SgLuXhqz0a3e5Lmpyt+uJPruXpOQYejV8BlVc2X3P9krU0CaxCk08wjheNYX9F4+RfY0uvMWRl5dHcvLlKpuUlBTi4uIwGo2cPu3N99/vICMjg0GDHqNWLTO9ep1l3tyFjB+XyJAhvqSlW/nu22R69vJEr3cu3UhJsTJvXipTptjnYvH0VBMRoWXJkjRaNDeye3cOjz7mU6r4i6IRGQRnryaY1VxZgZyjiSDR0IpYTX3OEcFpizfHTSqyijFKno9GTYCu9B81Xbp04euvvyY7O5vp06dz7NgxXnzxRdLT07lw4YIjacjXvn17p4b54FyanT8ba8OGDZ2WJSQkOP5OSEjg/fffZ926dcTHx2O1WsnOzubsWedegFfu193dHU9PT8d+9uzZQ4cOHQrtdZiYmMi5c+d48sknHYOOAVgslnLvCekKMuG4Cbp160bbtm257777+Pzzz6lTpw4XLlxgxYoV3HfffbRoUcQ0qDfK4AXugZBV+KiRUsXwQ6PeTC5lsgFwV2IgEF2sdX3cLWQV3VvUoajJ3a4nIzOJX7Z/Tu92w/G84HH9DUrA3s7Dn7qaNpyrlsXe7BNcTCl83JHruXDhArNnz3b8nT9deuPGjbnvvvvIzMwkLS2NzEzB7t0aIIoBA55i/fqVjBhxFm9vDR07efDEEwU/VKZ9dZGHBngTEHj59vzmW4GM+zyRX5ekMWCAD3fcUfoSg5IwWs4SkXmWCH4hfzQWgUK6vhEJ+hZcUNXmrAjlpNmD0ybhNJJ9bfeyidXd3d0xS+yXX35Jly5dGDt2LG+88QZQcOwlIUSBZYWVZl+97MrS7aFDh5KYmMjkyZOpVq0aer2etm3bkpfnfF1fnUxcuZ9rdavNX+f777+ndWvncW7KoufVrUYmHDeBoiisWLGC9957j2HDhpGYmEhISAgdO3Z0ZNllLqC2TDgqsOmN+zAlvWQlCEWpfTK32Ot6WZM5X4x5M641udv1CGFjxZavaNn4bmqYGiAKGfujNDQWheonPYhUGhNfJY8D6rNEx11/3Jq///6bI0eOcPHiRTQaDXXq1KFbt24EBAQUWDe/y/zhw4fZtWsXcXFxWCwWgoKC6N//YWrWrImbm0KuycKRw7v44osNJKfk0r6dO2++FYRWa/8wzMy08fyI84wbH8qMmVXL9HkoLQWBd+5evHP3UuuK5VbFSIqxFXHapsQoUdTwiSyX448ePZrevXszfPhwwsLC2Lx5Mx07dnQ8vnXrVlq1alWqY/z9999MmzaNPn36AHDu3LkCM8ReT6NGjZg9e3ahYysFBwcTHh7OqVOneOyxx0oV6+2gUiQcQ4cOZejQoQWWR0ZGFhjrwsfHx2lZUdtePWXw1e0z8hsd5fP09OTLL790ND662pgxY0o18mkBYU3hzJay2590yyjLZEMjVBgPnCp02vXCuKdGU5yJuuDak7sVx869vxNf5TTtAu9DpJa+XcfV7O089IRQi/SA6hz2iedQ7PEi23mcOXOGli1bEhYWhs1mY926dcydO5cRI0ag0xXeKPLMmTNERUXRtWtXDAYDe/bsYf78+Tz11FOEhoayZ4+KCRM2ceedHWnXviY/TF/AX3950a+fCSHMTP8+ibvv9iQ4+Pa5VatFDgHZGwlgIw2AOkEfAPXL/DidO3emfv36fPLJJ7zxxhuMHj2aGjVq0KRJE2bOnMmePXuYN29eqY5Rs2ZN5syZQ4sWLUhPT+eNN94o0UBgAC+88AJTp07lkUce4Z133sHb25vt27fTqlUr6tSpw5gxY3jppZfw8vKid+/e5ObmsmvXLlJSUnj11VdLFf+tpsIO/FXpVWnp6gikcvB9GSYbAHdlRyIyij+fiOHsvmKva7Oq8AgoOChTSZyNOcDvx77CGlq+tyqvixpanwjnUTrSpmoT3N0KdtN9/PHHadKkCUFBQYSEhHDvvfeSlpbmNMDU1Xr16kX79u0JDw/H39+fu+66C39/f8cgUtnZ2WRnZ9OyZUuELZCqVe/g701advzzCNu3d+D4cT0PP1Kn3M77ZvDwLO0csUV79dVX+f7777n//vt57bXXeO2112jYsCErV65k2bJl1KpV6/o7uYYZM2aQkpJC06ZNGTRoEC+99FKJx2Hy9/dn3bp1ZGZm0qlTJ5o3b87333/vKO146qmnmD59OrNmzaJhw4Z06tSJWbNmUb169VLFfitSxC05IYhUamkx8EXZf6uQXOe7xn2YWobJBsDHJ5tRa1HRE69dzabR8XfnyVivM938lfyDN19zcrdiURR6tX0W7zhvil0cUwoWjeBcRBb7ck6SmFJ4EXpycjJTp05l+PDhxf4QEkIwefJk2rdvT6tWrezdXydNol+/fkRFRfHjjz/SuHFjmjZtynfffce9995LWFgYYWEKkdWzcHc/RW7uAYQo+xKf8qHQqeNeNJqyG9pcun3dPuV0Usl4VwGPEMiMc3UkUhn4tnEf/q+Mkw2A6sczSrS+ypKHt4+a5IvFnxywOJO7XZcQrNz6Dc0a9aF2XmNEbvmOnqmxKFQ/5UF1GhNfNZcD6rOcvqKdhxCCVatWERERUaJvvFu3bsVsNlO/vv3LgKIoPPTQQ6xatYqVK1dSs2ZNmjZtyubNm6levToajYYZM2aQnZ1Nq1ataNWqFXp9A2rVFgQFxaMoh8jLO1/m519WjMYImWxIDjLhqMiqtIAjy10dhVRK3zTuw1flkGx4CB3aQ8Vvv5HPW5dNMsUfyKm4k7sVx3/7VhAffpoOwQ8iUm7Ot/zgc3qCqUW6fxSH/ezjefz222/Ex8czbNiwYu9n//79bNy4kUceecRpzJ2IiAinLpFJSUns27ePZ599lpkzZ9KmTRtq1qzJtGnTqFatGsHBwRzYrwAhQAihoSoiq2fi4XGGvLz92GzFbwRc3ry9mtz0Y44ZM4alS5eyZ8+em35s6dpkG46KLLy5qyOQSunrJn3LJdkA6J1RHZFb8g8nz5ySl5qVZHK36zl//jDLjnyJNaxMdldsXklqWh8P59jv/xF98jTDnxuOl9f1Z0AGOHDgAMuWLaN///5ERRX9PAgh+P333+nRowdCCOLi4qhXrx7u7u5ERkYWaIwOEBtrY9tWN1b/VZdtWweQnPQ4Gk1P9DrX92rx8m5aJvvZunUrarX6lp27JDo6GkVRZJJzHTLhqMiqlPH4HtJN9XWTvkxLKzh7ZVlpc+HGirrdEm5k1kwFjfEuFKVsbjnZ2en8snUcKSEp15vItcwIIfjf6i/469DfLOn/Jc9petMtrDVBfgW7xV5p//79/Pbbbzz44INOI0wWZvfu3bi5uVGnTh3HGA35vWasVut1Z5DOy4ODBxXWrwtizZrOHDs6GHNefwyGVqhUJetdURbKqoRjxowZvPjii2zevLnAoFsVzdVjfFQkMuGoyMKaQRnd4KWba1rjPuWabABUOXJjk5vpTvx7Q9ulXfSkSv2O11+xuITgr23fcdS4G8VQ/oMkvbf6C349uJqpd7+Pu86NpNRk3Pbl0v3MHdwTcCdRodVYs2YNv/56uepo//79LF26lB49elClShUyMzPJzMx0DM19paysLDZt2uT4Fm80GgkICGD79u2cO3eO06dPU7VqyUot4uMF27cbWf1XHbZs7s/FxMdRq3uh10eW6rkoDrXaDQ+PuqXeT1ZWFosWLWL48OH069evwJAEn332GcHBwXh6evLkk086PberVq3CYDCQmprqtM1LL71Ep06dHH9v3bqVjh07YjQaqVq1Ki+99BJZWVmOxyMjI/nkk08YNmwYnp6eRERE8N133zkez+9R0rRpUxRFoXPnzoC96+7IkSOdjn3fffc5DbUQGRnJRx99xNChQ/H29nZUr10vptuR/DSqyPQeEFj6N7x0c33VpC9fl1M1Sr4gqwfKsdM3tK0m/ixG9xtr/mWf3M33hrYtyp6Df7Ep9RcUv4JDR5elObuXkp6byYD5L9H8q/sd/34/so6gGD1dT9ck0OSB1WRGo7E/P//++y82m40VK1YwceJEx7+VK1cW2P/KlStp166dUzXNfffdx8GDB5k/fz7t2rUjPDy8wHbFZbHA4cMKG9YHsmZ1Bw4fGkxe7kMYDG1Qq0o3W29hvLyaoFKVvpngwoULqVOnDnXq1OHxxx9n5syZjpKeRYsWMXr0aD7++GN27dpFaGgo06ZNc2zbrVs3fHx8WLx4sWOZ1Wpl0aJFjoG29u/fT8+ePXnggQfYt28fCxcuZPPmzbzwwgtOcUycOJEWLVqwe/duRowYwfDhwzly5AgAO3bYe2GtWbOG2NhYlixZUqJzHD9+PA0aNODff/9l1KhRxY7pdiO7xVZ0y16E/350dRRSMf1fk758W84lGwBPJNen97d7r79iEQ4/Mo3YuBu7dQRUiSWmhJO7FYfB4EHf5s+juVDmuy6xPDcbJ8JT2Zd8jMzb4FupRgM1aghCw5LRaI6Qm3uq1PusXv1loqq/VOr9tG/fngEDBvDyyy9jsVgIDQ1l/vz5dOvWjXbt2tG4cWO+/vprx/pt2rTBZDI52lO8/PLLHDhwgLVr1wL2Yejvvvtu4uLi8PX1ZfDgwRiNRr799lvHPjZv3kynTp3IysrCYDAQGRlJhw4dHFPXCyEICQlh7NixPPfcc0RHR1O9enV2795NkyZNHPvp3LkzTZo0YfLkyY5l9913Hz4+Po6SmsjISJo2bepUMlacmG5HsoSjoguX7ThuF1NvUrIB0DymdNOFe5F2w9tejAklOKpBqY5fGJMpk8VbPicp+KLL72y6bBX1jvvxUGpruoe1Jsg/0LUBXYfFAkePKmxY78+a1e05dHAIuaaHMejbolbf2Jw2Pt6lb7R+9OhRduzY4ZgFVqPR8PDDDzNjxgzAPnR827Ztnba5+u/HHnuMDRs2cOGCPROdN28effr0wdfXXtL277//MmvWLDw8PBz/evbsic1m4/Tpy6WAV07QpigKISEhThO9lcbV82kVN6bbjewWW9FVa3/9dSSX+7JJX76/SckGQPCh+FKNn+Wedha48aTBYruxyd2KY832H2hU7y7q0RqRUz7T0ReX2qpQ7ZQH1WhEYnguB/QxnLwQ7dKYiiMpyUZSkg6oiUpVk5o1ITQsGZ32GKbc49fdXqXS410GCccPP/yAxWJxqkoSQqDVaklJSSnWPlq1akWNGjVYsGABw4cP59dff2XmzJmOx202G88++ywvvVSwNCYiIsLx+7UmaCuKSqUq0NDXbC7YnfvKbtIliel2IxOOii6gpn26+qQTro5EKsLNTjZqWPwQp0vX0t8QcwD8bzzhKM3kbsWx79BaEoKj6Vx1ICLp1hiVM/C8ni7UoKV/JIf94jkUd6LQD59bjc0Gx47BsWN+QBt8fNpSs1YuPj4xWC37sVgLTh/s490Stbp0xf4Wi4Uff/yRiRMn0qNHD6fHHnzwQebNm0fdunXZvn07gwcPdjy2ffv2Avt69NFHmTdvHlWqVEGlUtG3b1/HY82aNePgwYOOmWhvRP5cOlfPwxMYGOg09L3VauXAgQN06dLlmvsri5huRbJKpTKofWv2XZdgStObm2wA9E6uUup96I/tQqUqXX9U++RuoaWOpShx8SdZsm8S5rDyHZW0pDyS1LQ8HsZAy520r9oMT/cbq7JwldRUwa6dOtasjmLDhnuIvTAYRemHQV+H/D7Kfv53lvo4y5cvJyUlhSeffJIGDRo4/evfvz8//PADL7/8MjNmzGDGjBkcO3aM0aNHc/DgwQL7euyxx/jvv//4+OOP6d+/v1MbiLfeeott27bx/PPPs2fPHo4fP86yZct48cUXix1rUFAQRqORlStXEh8fT1qavcqxa9eu/PHHH/zxxx8cOXKEESNGFOgxU5iyiOlWJBOOyqBOH1dHIBVictO+TE+9uckGQKMzpR+4QsnNwcu3dF1Ry2Jyt+vJy8tmyZbxJAbFQykTpLKmy1FR97gvD6W2ontYG4L9SzYp2K1ACIUTJwSbNvqyenUr9u0dTHbWI/h4dy31vn/44Qe6deuGt7d3gccefPBB9uzZQ61atXj//fd56623aN68OWfOnGH48OEF1q9VqxYtW7Zk3759BaaBb9SoERs3buT48eN06NCBpk2bMmrUKEJDi58MazQavvzyS7799lvCwsK49957ARg2bBhDhgxh8ODBdOrUierVq1+3dKOsYroVyV4qlYHNCuNrQE7x6jyl8vdF077McEGyAfDzTD9EXOkbu518dApnLpS+VtYveDMXSju5WzHUr9OJhpr2iOzitev4v21z+XzTdzzZvD9juhXe2yI+8yIfrpvG/vijnE6OYVjzBwusu+n0Tv63+gsuZqXQs/adfN7rTXRqe3uA9NxM+s1+hvmPfEG4VzCJYXkcNMRwMjb6uoN83aq8vb155ZVXXB2GdAuSJRyVgUoNtXpcfz3pppjkwmSjaV5omSQbAJ55iWWyn+zMVuiMZT8OxNUOHt3I2vifUAKuP17HntjD/LR3GXUDa1xzvTyrGX83b15sO4h6QQXr223CxkvLP+TxJvfy6+PT2HPhMD/t/d3x+KcbvuHxJvcS7hUMQOAFHZ1PRfGwsRNNqtYr0FDxdlDaKeGliksmHJWFbMdxS5jUtC8zXZRsAPRIDCmzfbkllk1D5PzJ3W6GxIvRLNkzkbzwoks5svKyeen3D/m815t4Gzyvub+q3qGM7fYy/Rv0wlNfcKj45Ow0krJTGdzsPuoEVqd7rfYcvxgNwM6Y/eyNO8qTLfoX2M4jWU2L46EMNHewt/PwuHYct5LrDd8uVV4y4agsanYDdenGXpBKZ2LTfi5NNgDuOF12vSL0p3aX2b7KcnK368kz5/Dr5gnEB10AdcF2Hf9b/QVda7SlQ2Tpx7Dxd/MhyMOfTad3kmPOZce5fdQNqkGe1cy7f03k0x6voVYV3RZGZ1Ls7TxSWtIjtA0hAcGljqk8abVaxzDfknQ1mXBUFgYvOSaHC01o2o9ZqftcGoMiwONAdJntT3vuKDpjWc1hUraTuxXHhn/msE+1GeWKYdp/O7SW/XHHeLvTM2VyDEVR+PresUzZ+iN3/TCI+sG1eLhhX6Ztn0f7as0xaPTcP3cEnb5/jFn/Li5yPyqrQsRpd/rFNOA+vw7UCotCUW6tRrAAUVFRt2U1kHRzyHE4KpM6veHUeldHUemMb9qPH12cbAB0MlVDpJws0336ekF8TtnsK39yt3MHNpTNDovh8LHNJPifoVuNwVw4eZ4xa79k3sMTMWj0ZXaMVlUa8ceQyxN9nUo+x+KDq1g59Af6//QiT7Z4iM7VW9NtxhBaV21C3aBrtxsJuKCjE9Vp7hvB0YBEDsYfv2VmGG3QoOxHkJUqDplwVCZ1esOfb7o6ikplXNN+zLkFkg2AzvH+QNkmHF6qdOK5sWnuC2Of3G0v2Wk3r0dVUtI5FqeNR+fWhIvZKfSZ9bTjMauw8s+5vcz671dOvr7mmtUfxSGE4K2V4xnV5XlsQnAg/jh963TGqDXQpmoTtp/bc92EI59Hivr/27vzuKjq/fHjr1lYZ2HYQUBAFBQNAbfcNTHX0swtLdO0m1r9tDTr3uqrtty0btfyVmo3xTSva2bmXpaVS665oyKCKAKyKzsznN8fyCiBIjLDMPB5Ph7zwDlz5pz3IAzv+ZzP5/2mXZYXD9l7cskvh5PZsdy4WbkIV12xsbEhJCTEYucX6j+RcDQmuqbg2QZSzduJVCgzP2Iw39STZAOg+UXTNxFT37wKmO6PTEmxErem/ck3Q3O3e9Hri8nN2M//ZszDPccbSsuWpM7YNo/mrk2Z0mlMrZMNgDUnt+LsoOXRFt3ILrwJQEmpHodbXw2lNS/Fblsoo2WsjmB5e5L8CzhZEk9yekqtY62pkJAQY8VNQaiKmMPR2LQdbekIGoX6lmzYSQrsTte+A+hf2V87a/Jjmqu5W3XsbZRcu/I7BR6JtAoMpqV7Mxxt7HG219LSvWxC67xflzB9y/sVnncmNZYzqbHklRSQUZDNmdRYLtxaiXKn9LwsFu5fwdyoaQDo7DW0cPVn6eH1HE06zb7LR2nn8+CvW14qwy/ekUFXW/OEc3eCfep2noelLqfs2bMHmUx2XxU8BcsSCUdj03aMWK1iZvMj61eyAdAvtxlSgYkmW9zB7sLh8mrWJlXW3M0yP6cXLv7BrqvR4FF5ADg1N4OkG6kVtvVfPpH+yydyKuU8m87+RP/lE3l2feVLl7N3L+SFjqPw1tzuHPvxwL+zOWY34ze8weSOTxHRJNQkr8E12ZYecYGMtutFpF8bs488ODg4mKTvR0pKCi+//DLNmjXDzs4OPz8/HnvsMWNr+ap06dKF5OTkKiuSCvWLqDTaGK0fD2e+s3QUDdK8iMGsqmfJBsCHFyIJ+NY81TyPDF3CjWy9yY/r4RdjtuZu90OhsGXQwy/icM36E/QS+1Iu+d3ghJnmeXTo0KFCQ7QHkZCQQNeuXdHpdMydO5ewsDBKSkrYuXMnX375JefOnav0nJKSErEqxoqIEY7GKHJc9fsINfZBZP1MNgD8LuSY7dhOjuZZIWHu5m7VMRiK2bxvAVddE0BZ/5ag1oRNoZyQWB3DM9rT37szTdxNVwAOIDw8vNbHmDp1KjKZjEOHDjF8+HCCg4Np3bo1r776qrEDrEwmY/HixQwZMgSVSsV7771X6ZLK8uXL0el0bNmyhZCQEBwdHRk+fDh5eXl8/fXXBAQE4OzszMsvv1yhu2txcTGzZs3Cx8cHlUpFp06d2LNnT61fl3CbSDgao2a9Qedv6SgalH9GDOZ/WfUz2XAqtUcRY9rVKXfSlGSY5bh10dztfuw7spZjhp+Raax/jr28VIZvvCMDr7RmmHMPQnyCaj3Pw93dHR8fn1odIzMzkx07dvDiiy+iUlVe9aTT6Yz/nj17NkOGDOHUqVM899xzVR4vPz+fhQsXsmbNGnbs2MGePXsYNmwY27ZtY9u2baxcuZIvv/ySDRs2GJ8zYcIE9u3bx5o1azh58iQjRoygf//+xMbG1uq1CbeJhKMxkskg8hlLR9FgvB85mNX1dGQDYPCNQNCb/pJHOVWm6SejlstMcaFJy45mO/79ir10iB2JS5E8TVXozPJckm3oHhfAU7Y9aefXBju7B6s9YorRjYsXLyJJEi1btqx23zFjxvDcc8/RrFkz/P2r/uBUUlLCokWLiIiIoEePHgwfPpy9e/eydOlSQkNDGTx4ML179+aXX8rqEsXFxbF69WrWr19P9+7dCQoKYubMmXTr1o3o6Ohavz6hjEg4Gqvwp0HWcN48LUFCxnuRg1hTT0c2ynVMcjDr8e3ij5v1+HXV3K062dkpfHv4Q/KaFFo6FJNyzFEQEevJ6MKu9PBtj5P2/idfyuVywsLCah1D+VTC+xltad+++pLzjo6OBAXdrmfi6elJQEAAarW6wrbr18saGR47dgxJkggODkatVhtvv/76K3Fx5hsdbGysf4xQeDBabwjuB+e3WToSqyQh4/3IgazNsmxvlPvhHWOarq53YxN/CmVzOfriUrMcv7y5W+JJy090Nhj0bNn3KZ0jh9M0twWUmOc1W4JNkYzgi040l7cjuWkBJw0JJKUl3/M5rVu3RqOpfWO5Fi1aIJPJiImJYejQoffct6pLLn/114mkMpmsym2lpWX/f6WlpSgUCo4ePYpCUfGD2J1JilA7YoSjMYt81tIRWKWykQ3rSDZ89U5wMcGs55BJEs46876V1GVzt/tx4NgGDhfvQqZteJ/Z5KUyfBIcGXAllCd1PQjxaX7XkYdOnTqZ5JwuLi7069ePzz//nLy8ygXqzF1jIyIiAoPBwPXr12nevHmFm5eXaSfYNmYi4WjMWvQFTRNLR2FVJGS8GzmQdVaQbAAMym4KdbDyXavINfMZ6r65W3UuJRxla/yXSF4N99Kkc4oN3eP8ecq2F+38Hqowz8PHxwdfX1+TneuLL77AYDDQsWNHvv32W2JjY4mJiWHhwoV07tzZZOepSnBwMGPHjmXcuHFs3LiR+Ph4Dh8+zPz589m2TYwCm0r9+e0V6p5cARFPWzoKqyEh453Igay3kmQDIDyxbv4YqvOvmf0c5c3d6pObN9LYcHA+uU1MXza+PnHMkRMR68Howq709G2PTqsz2ehGucDAQI4dO0bv3r2ZMWMGbdq0oW/fvuzevZtFixaZ9FxViY6OZty4ccyYMYOQkBAef/xxDh48iJ+fn9nP3ViIwl+N3c0U+LQt6BvWRDhTk5AxN3Ig31pRsgGw/hsPpCvmTwYKOg7igONAs5/HxlaPoXBlnTZ3u1+dwocSkN+qQc3ruBu5ky2er7VHoWy4ozuC6YkRjsZO4yUKgVXDWpON0BL3Okk2AGwvHqmT85QUK3Ft2r9OzlVTB49v4o/CbcicGn7lS00XH5FsCDXW8GY8CTXX7RU4+jUYiiwdSb0jIWNO5EA2WlmyAdA/wwe49yoDU1FkpqLSKsm7Yb56H+XSbjV3S710u+vxztMX+PFsxQJNGns7Zj8eVeUxLl7PYPGePyptn9W/Jx7aslUJF1LS2HjsDLlFRbRu4smI9mEoFWWf0QqKS/j0p3280LMTzqrby44vJ54gM/Mq/cP+hjy5YY50yOwUqDqJiZRCzYmEQwBtE4gYC0eWWTqSeqX0VrLxnRUmGwCtE2re6rw2dCo9eaZv01ElvdQdhc15DCUlxm2eWjUv9Lw9r0B+HzUdXh/QEzvl7bdB9a1JkaWSxKqDx3mkZRAhXu6s2H+Ug5cS6doiAICtJ8/ROahphWSj3M3cDDYcmM+ALlPQXGt4SypVHb2Q24s/HULNiUsqQplur4K84Q8F369SmZzZVpxsADidSqzT82lL625eRV62Az4t+1TYppDL0TrYG29q++orZ6rt7Co8Ry4vS1LyiorJKyqmS3N/vJw0hDbxJPVG2Uqc+PRMrmbl0L1F4F2PK0mlbNv3OZe0Z5HZNqC3WaUMdbfalTEXGi+RpgpldH7QdjT8udLSkVhcqUzO/0UM4HsrTjY6F/pSmp5Qp+dUZSUAznV2vvTklmjdT3DjVnGqtJt5vLP5JxQKOf4uOgY81BJX9b0rlP77x9/RG0rx1KqJCm1Ocw83ANR2tmjt7biQkk6wpxvx6Zm0D/BFbyhl49HTjOwQZkxO7uXwiR9I9Y2ni/tQpOySavev79SdvFE6PVgJdEEQq1SE2zLj4bP2UGr+6/D1ValMztsRA9hsxckGwFtXIgj75nCdnrOoZUf2edVtMTkX7wyunf2amOTrlBgMuKtV3Cwq5qezsaTdzGNmvx6o7Cq3l79+I5dLaZn4ujihN5Ry9PJV/ohLZHLvhwlydwUgPi2T74+fJa+4mFZeHgyJCGV3TBwFxSV0aubHhiOnyCsupmvzALrdutRyNyqVMwPaTkZhxfM6ZLZyvGZ1QKGu/P0UhPshEg6hou+mwIn/WToKi2goyQbAij2h2B+o2x4vpUpbfu/1CQZ93b6luHruJencoQrbivR65m3bQ6+QZvQMub8KpUt/P4xMBs9161Dl42k3c1n6+2Fe6dudL345QPfgQEK83PnXzt94oWcnmui09z6BTEb/zi/glOIEVviuq+nth1O/AEuHIVixBnRxUTCJHjMbZVO3hpRsKCU5DqfN18H1buT6Ypx0df+zk1dFczc7pRIvJw3pufdfkMvfVUf6zar3lySJ9UdO8VjbUCQkkrJvEObrjcbejiB3Fy6lZVR/Aklix/7FXFCdRGZnXW+9Mgclmh6mqyoqNE7W9VMvmJ9rELQZZuko6lSpTM5bDSTZAOiTH4B009ylxqvmZJtf5+csb+52J73BwPUbuWjs7e/7OEnZN9A4VL3/ofgrqGxtae3jSemt0QnDrcZfhlLJuO1+/HlqO7/f3ITM2XomaWt6+CJ3EFP+hNoRCYdQWY/XGs0oR6lMzpsR/fmhgSQbAD1SdBY7t6YgxSLnXbxuJ2mSHRm5+VzOyOLr/ccoLNHTPqBsRcW2k+dYffC4cf/fLsRzOimFtJt5pOTcZNvJc5y6mkK35v6Vjn2zsIifzl5kaERrABxtbfDQqvk9Np6E9CwuXk8nwLVmk2WTkmLYfG4hBitoZSRX26DuagWBCvWeSFmFytxDoP0EOPyVpSMxK4NMwZsR/diadbr6na1IYOxNi53b8foFsGla5+fNzktjyfYT3MzPRmVni7+LMy/36YKLquxSy43CIrLyC4z7G0pL+eFEDDkFhdgoFHhp1Uzs3oFW3h6Vjv39n2fpGdIMJ8fbox+jO7RlzaHj7I1NoGdIEE1ddTWOOT//Bhv2f8ijDz+Pc6pzvZ3Xoenth9y2cXwAEcxLTBoVqlaQBf9pB/n3cW3aChlkCv4R0Y9tNUg2JIPE9U3XyT6QjT5Hj1KnxLmbM+6PuSO7yxLJ3JhcEuYnVNre4p8tsGtStrww93Qu11ZeQ39DjzZSS5MJTZArywYfDfkG4ubGETArAFvX6lcHqCVbohcYkIosUzVW7+nPb61mWeTcAO4+x7hyeo/Fzv+gwls/SsvS9kiFdVusrToKnR1eM9sjU4rBcKH2xAiHUDUHZ4iaA5tftnQkJmeQKfh7RD+213BkI21rGpm/ZOI7yRc7HzsKEgpIWpqE3EGO26Nu93xui3ktkNvfftNWast+9aRSiStLruA+yB31Q2qufHaFrD1ZuEaVLc1MWZeCS2+X+0o2AAbcDEQqOlOj12VKytTLOLRXUpBnmaXV2WlhODqdqJfN3e7l+JldpHrF09NnFFJm/anX4TQwUCQbgsmInyTh7iKeAZ92lo7CpB402QAoiCtAE6FBE67B1t0Wpw5OqFurKYgvqPa5So0SG52N8VY+ImLINWC4acDlERfsfezRRGgoulY2OpEXm0dBQgGuj7red4wPX1PV+HWZmk5juVoT9bm5W3WSU2LZdOYT9PVkuoRdkBOOYe6WDkNoQETCIdydTAYD/wWyhvFjUptkA8CxhSN5Z/MoSilLCAoSC8iLzUPTVlPtcy/Ovsi5aeeInx9PbsztFSQKjQKlTknumVxKi0vJu5CHvZ89pfpSrn19DZ9nfe56uaYqvucya/7CTExLtkXPX97czRoVFuby7b75ZHimW/bdWS5D93iQBQMQGiIxh0Oo3g/T4OhyS0dRKwaZgjciHmVH1oNfbpAkidQNqaRvu/XHoBQ8n/TEffDdPwUWJReRdz4PhwAHJL1E9v5sMn/JJPCNQFQhZaMReRfySFmdgv6mHk2YBu8x3qRtTcOQZ8C5pzPXoq+hz9XjGuVqvNRSFQ+Dms8+vgkGy84DyB4whWMFlv2Dr9IVkH31qwrN3axNWGgfQumEVFD3/5/qrk3QPSYSDsG0xBwOoXp9ZsPZ78smklohvVzJG+F92VmLZAMg52AO2Qey8X3BF3sfewoSC0j5X4px8mhV7LztsPO+3XvCsbkjJRklpG9PNyYcqmAVQbNvv7kXpRSRvT+boLlBxH8Qj+ujrmge0hD7ZiyqEBX2flXXihiU4w+GE7V6jaZgn3QGXCybcJQ3d0s8tcOicdTGybO7ue6ZQC+/p5Ay6i5xUmht0T5aeXmwINSWSDiE6jm6wCNvw9ZXLR1JjenlSl4P78uuWiYbUDaB032gO7qHdQDY+9lTklFC2pa0uyYcVXEIciDnQE6Vj0mSRFJ0El6jvUCCwsuFOLV3Qm4nRxWiIu9c3l0TjnZX60ePC7vzh5F1HYVUWrZc9fs//suZK4coMRTj4eTL2J4zaeoefNfnx147wcYDi0jOSsDJ0Y2o8FF0D33M+HjM1SOs27uQmwXZhAV0YUyPGSgVZUW0Copy+fC7qbw86CPkf2nuZo1SUuPYmPVvBnd4EZtrdXONxemxZsjtxJ8GwfQaxsV5wfzaTQDvcEtHUSN6uZJZJko2AKQiqdJvjEwuq3H9hMLEQpS6qt/Qs37LQqlWoo3Qwq25l5JBMn6V7lHS0vNsas0CMRNZUQFOOiX5RTf596ZpyOVKpg6cx1sjlzHs4ck42Krv+tz0G8ks2v4Pgrwe4o0nl9Av4ik27PuMPy/9BkCpVMrXuz+gW+hjzBiykMvXz7MvZqvx+ZsO/pduoY/hovGk1CBH7f6o2V+vuRUX57Nx30ekeaRCDebzPAj7EGccH3rwiaLjx49HJpNVul28eLHWsY0fP56hQ4fW+jiC5YiEQ7g/cnnZBFLM+4ZnKuXJxo8mSjYANOEa0n5I4+bxmxSnFXPj6A3Sd6ajbXe7aVfK+hSufnnVeD99Zzo3jt6gKKWIwqRCUtancOPIDVz6uFSO+YaetM1peD/tDYBCpcCuiR0ZuzLIv5hPXkweji2qbrcepHdBik802WutLSf7Qn48vgZntTvP9J5FgEdLXDVehPhG4u5092UYe8/+gLPag+FdX8TL2Z8urQbxcEh/dp9YB0BeYQ65hdn0CB2Ct0sAD/l3JiXrMgBxKadJTLtA7ztK82cmu+LTsqN5X2wd+fngck4rDyBzNE8RLpmNHN2Q5rU+Tv/+/UlOTq5wCwwMNEGEgrUTCYdw//w6QKcXLB1FtcyRbAB4P+2NU3snrq28Ruw/Yklek4xLLxc8ht2uTqnP1lOcUWy8LxkkUtamcPHti8T/M5782Hz8X/HHqb1TpeMnr0rGbYAbNnf02PCZ5EPOwRwuL7iM2wA3HJtVnXAMyKxfjbU0RWmcSthPU/cQlv44lze+fpJ5G16oMBpRlfjUs7TyrbgUO9SvA4npFzAY9KjtdWgdXYm5eoRifRFxKafwcW2G3lDC2t8/YXSP6cjlFf8gV9XczVqdOf8ru1P/B26mv+ThNDAQpcv99565Gzs7O7y8vCrcPv30Ux566CFUKhV+fn5MnTqV3Nzbq7WWL1+OTqdj586dtGrVCrVabUxcAObMmcPXX3/N999/bxw12bNnDwCvv/46wcHBODo60qxZM95++21K7pgsfOLECXr37o1Go0Gr1dKuXTuOHDlCXl4eWq2WDRs2VIj/hx9+QKVScfOm5Sr2NlTiQp1QM33fgfjf4brlikvdS4nchlnhUfxk4mQDQOGgwHusN95jve+6j+/zFf/wuw90x33g/Q1R+03xq7TNsZkjLT5oUe1zwy7Xr5Enx/SLpN9M5vezm3nkoeE8GjGGy9fPsWHfZygVNnQKrvpSx42CTDQOFefDaBycKS01kFuYg5PKlYlRb/PtgUV8u/9zQv060jlkALuO/48Qn0hsFXb8e9P/I7cwh55tnqBnm6HG5m6JJ7+ri5dudmnpCXyX828GdXoR2yTTjHbYBTuj7my+AiByuZyFCxcSEBBAfHw8U6dOZdasWXzxxRfGffLz8/nXv/7FypUrkcvlPP3008ycOZNVq1Yxc+ZMYmJiuHHjBtHR0QC4uJSNEmo0GpYvX06TJk04deoUzz//PBqNhlmzyirejh07loiICBYtWoRCoeD48ePY2NigUqkYPXo00dHRDB8+3BhH+X2Npvrl7kLNiIRDqBmlHTz5Ffy3N+gLLR1NBSVyG14L78NuMyQb9Z3z6Sv1qhWH3aU/kSSJpu7BPN5pEgB+bi1IzrrM72c23zXhAMrqv9xBuvXKZLe2B3k/xKxht/9QpWZf4dCFn3hj+BIWbJ5O74eeJNSvA++vm0Rz74fwcQ3i+pUAXHwCyUyKN/ErtYzikgK+2/svenV6Bs8MHzA8+P++3FGJy/C7T+KtqS1btqBW356nM2DAANavX2+8HxgYyLvvvsuUKVMqJBwlJSUsXryYoKCyFVsvvfQS77zzDgBqtRoHBweKiorw8vKqcL633nrL+O+AgABmzJjB2rVrjQlHYmIir732Gi1btgSgRYvbCfykSZPo0qUL165do0mTJqSnp7NlyxZ+/PFHU307hDuISypCzXmGlo101CMlchtmhvdhd9ZZS4dS5yKKvZFSrhvvp5aUMOvaNTrHXiDywnmeSIjnTOG9k8P/ZWUxOP4SERfOM/DSJb7PqbiKZn9eHgMuxdEx9gJ/T75G8R3le24aDAy4FMe1O4axba6cx0nlipdzxeWVXrqmZOVe5260Di7czK9YvCy3IBu5XIHKTltpf0mSWP3bAp7oPJlSqZSr6ReJCOyBxsGZFk3CiE0+eWtPGTaOUcgaSBG7cnsOruSkfC8y1YN/dtQ90QKF1nQrnHr37s3x48eNt4ULF/LLL7/Qt29ffHx80Gg0jBs3joyMDPLy8ozPc3R0NCYbAN7e3ly/fveflXIbNmygW7dueHl5oVarefvtt0lMvD2f6dVXX2XSpElERUUxb9484uLijI917NiR1q1bs2LFCgBWrlxJ06ZN6dGjhym+FcJfNKzfPqHudHoBmve1dBTA7WTj50aYbAA8mnb7E1+OwcDYxMsoZTKW+PrxQ2Ags9w90Mjv/qu+JiuLBelpvOjqxuaAQF5yc+Pd1FR+yS27hl0qScxKvsYonTOrmvpzqrCQDdnZxud/nJbGKJ0zTWxsKhy3lX8brmdfqbDtes5VXDSed40l0DOUc1ePVtgWc/UITd2CUSgq/1E9cG4bKnstYQFdkKSyZT2GUr3xq1R6u8x6TroG39Dudz23tYq5sJcfk1eAe82TDsdIDxwfuncfoJpSqVQ0b97ceCsuLmbgwIG0adOGb7/9lqNHj/L5558DVJhrYfOXnx+ZTEZ1dSn/+OMPRo8ezYABA9iyZQt//vknb775JsXFt+dRzZkzhzNnzjBo0CB+/vlnQkND+e6725fXJk2aZLxMEx0dzYQJE4yjaYJpiYRDeHBDvwCVZXstlMhtmNGIkw2AlvG337SXZmbgZWPDP729CXNwwMfGls4qFU1t7/4JdvONG4x00jFAq8XP1paBWi1P6pxYmlk20pBlMJBpMPCUTkcLOzt6q9XEFZeVdz+Wn8+ZwkKeca5ch2RU54HEX49h57FVpOUkcTh2N/tittKj9RDjPt8f/IoVP88z3u8W+hiZudf5dv8XpGRd5sC57Rw4t50+bUdWOv7Ngix2HFvFiK4vAuBop8FL15RfTm3kUsoZzif9SaBX6wrPyc4Ix1Gru4/vqnXJyLjCt8c+otDn/guEKXR2dVK+/MiRI+j1ej7++GMefvhhgoODuXbtWo2PY2tri+EvVXT37duHv78/b775Ju3bt6dFixZcvny50nODg4N55ZVX2LVrF8OGDTMmGABPP/00iYmJLFy4kDNnzvDss8/W/EUK90UkHMKDU3vAkC+q389MShS2vNq2D7804mRDJoH6dILx/s+5ubSxt2d6UhLdLsYyLCGe9XeMRlSlWCrF7i/1HexkMk4WFFAiSbgoFLgrlOzLz6OwtJSj+QUE29lRLEm8k5rKbC9PFFV8Imzn5Mjzj87lSNwvvL9+IjuOfcOTXabSoUWUcZ8b+Rlk3nGJxU3rzZQB/yQ2+QTzNrzAjmPfMLzrS0Q0qzzEvWHf5/RpOxLdHUnv071f52jcLyze8SZRbUcS4NGywnNKihRW29ytOnp9Md/v/TfX3K6AoppP6DJwGRmC3N780/iCgoLQ6/X85z//4dKlS6xcuZLFixfX+DgBAQGcPHmS8+fPk56eTklJCc2bNycxMZE1a9YQFxfHwoULK4xeFBQU8NJLL7Fnzx4uX77Mvn37OHz4MK1atTLu4+zszLBhw3jttdd49NFH8fWtXyu+GhLRS0WovW2vwaEv6/SUZclGb/ZkxdTpeeubXgX+TP3k9jXp8AvnAXjW2YV+Gg2nCguYd/06czy9GOJUeSkuwIK0NL7LyWaRrx+hdnacKSpkytWrZBgM/BrUHHelkqP5+cxPu06WwUAPlYo3PDz5b0YGN0oNPOmkY05KClkGA2OdnRl7a7SjMLIv+7VDzf49eBBOzjtJvdRwJxcHN3+YSIc+SLn6Kh/X9PLFqb/pa2OMHz+e7OxsNm3aVGH7ggUL+Oijj8jOzqZHjx6MHTuWcePGkZWVhU6nY/ny5UyfPp3sO5LjTZs28cQTTxgvq6SlpTF27FgOHDhAbm4uv/zyC7169WLWrFksW7aMoqIiBg0axMMPP8ycOXPIzs6muLiYZ599ln379pGamoqbmxvDhg3jo48+wt7+9hLgn3/+mT59+rBu3TpGjBhh8u+LUEYkHELtlRSWrVq5XjcjDSUKW14J682v2Y072QCYGx9JqzWHjPfDzp+jjb0D//O/PVnz/dRUThcWsNo/oMpjFJaW8m5qKj/cyEECXJVKHtNqWZqZye9BzXFVVv4UnFBczOSrV/g2IJBxiZcZ5+xCN5WKIQnxLPX1I8TenlK1jj0d3q9xJda60BCau1XHxbkJfYMnwPWKSYddMyfcJj1Uoy7EDd2qVauYNm0a165dw/Yelx+F2hGXVITas7EvWyqrrH3RoOqIZKOioLj8CvfdlUqC7Cq+YQbZ2pKsr/qTLoC9XM773t4cDQ7hx2ZB7G4WhI/SBpVcjrOicp0HSZKYnZLMLA8PJEkipqiIRzUaXJVK2js4crigLCZ5bjYap/q58j4v2wGfVlHV72jFMrOuseHIRxT43J5AKdfa4vJUS5Fs3JKfn8+ZM2f44IMPeOGFF0SyYWYi4RBMw7M1PP4fs56iWGHHdJFsGNlJCuxOx1XYFungSPwdM/QBEkqKaaKsuAKgKjYyGV42NihkMrbdvEEvlRp5FXMzvs3JQadQ8IhaQ/kUPv2tgVI9Ene2e9E51t8RhPRrIWjdvarf0YoZDMVs3ruAq64JyOwUuI5thUIj/qiW+/DDDwkPD8fT05O///3vlg6nwRMJh2A6YSOhx2tmOXSxwo5pYT35TSQbRv1ymyEVFFTYNs7ZmZMFBSzJSOdycTFbbuSwPjubp5x1xn3+nXadN5JvrxJIKC5mc04OCcXFnCwoYMa1JGKLipjuXnm5ZIZez+KMdP7hUba01UmhoJmtLSuysjheUMAfefmEOzgY99eUpJv4VZtOWXO3fpYOo07sO7KWm71KsPOvXMukMZszZw4lJSXs3r27QrEywTxEwiGYVu83ofUTJj1kebKxN/ucSY9r7bolVy69/JCDAwt9fNl24yZDEuJZnJHBGx6ePKa9PWE0Xa8n+Y65CwZJYnlWJsMS4pl09QpFksT//P3xsan8SfiD66lMcHHF846aCf/08mb7zRtMuXqF51xcCLsj4VBl1u/KnpnJrjQJ6WDpMMwurE9/WvbuaekwhEZOTBoVTK+kAJYPgqSj1e9bjaJbycY+kWxUsnpLEIpT5y0dxj0VB7Vlr9/fLB3GPdmrisnPWEZxQX71O1shn5atGfH2+yiqmPwrCHVJjHAIpmfjAKNXg7Z269mLlPYi2bgLp1J7FDFx1e9oYTbxp1Ha1u+3mfLmbg2R1t2Dx2f8QyQbQr1Qv98JBOul8YQxa8D2wa6LFint+X8PdRfJxl0MvhEI91h5Ul/ISg3odPX/baa8uVtDYmNnz5CZb+Gorbr+iiDUtfr/TiBYL6+H4MmlUMOGWeXJxv7s+n25wJI6JjlUv1M94aTItXQI96FhNXeTKxQMmvYaHgHNLB2KIBg1jN8uof4K6Q99373v3QttHHhZJBvV8o5Js3QI902dX/O+GZbQUJq7yWRyBrz4KkHtOlk6FEGoQCQcgvl1eQnaja92t0IbB15u040DItm4J1+9E1xMsHQY980x2Xoui1l9czeZjKjnX6RlV7EiRah/RMIh1I2BH0PIwLs+XGjjwEttuvKHSDaqNSi7KVjR4jLbi0csHcJ9s/bmbr2emURYn4Y5AVawfiLhEOqGQgkjvobmlctJlycbB7MvWCAw6xOeWLnceH2myExFpbWeVRJpSU3wbNa6+h3rmS4jx9Ju0BBLhyEIdyUSDqHuKG1h1DcQeLvVeIGtIy+1FslGTbidtY45EXfSqev/ipo76aUeKGyqLwdfX7R/bBidn3zK0mEIwj2JhEOoWzYO8NQaaNq5LNkI7cLBHJFs3K/QEnekK9aXcGgMWZYOoUasqblb274D6fn0c5YOQxCqJRIOoe7ZqmDsehY+/BSHRLJRI/0zfCwdwgNRZV+2dAg1Zg3N3UK796bPxCmWDkMQ7otIOATLsNPwUvd3ifCIsHQkVqV1gqH6neohh8STlg6hxup7c7cWHbvQb+p0ZFV09BWE+kgkHILFqGxULI5aTDvPdpYOxWo4nUq0dAgPRBn7J3KF9f1hrK/N3ZpFdmDQtNeQy61rArHQuImEQ7AoRxtHFkUtoqNXR0uHUu91LvSlND3D0mE8ELm+GJ2zdf5xzM/rhK2Do6XDMArt3pshM99CobSeSa2CACLhEOoBB6UDX0R9QV//vpYOpV7rk+Zu6RBqxcnWOrux1qfmbu0GP0H/F19FrrDO5E1o3ETCIdQLdgo7/tXzXzzd6mlLh1JvBccVWTqEWlEXplo6hAdWH5q7dR8znl7PTBRzNgSrJRIOod6Qy+S83vF1ZnWYhbyBNNEyFaUkx+H0JUuHUSuOqda8IkmGjcoyzd3kCgX9pkyn45DhdX5uQTAl8a4u1DvPhD7Dxz0/xk5hZ+lQ6o2o/ECkm9bQdfXu7OKOWTqEWslJ0+Dbum6bu9k6OPLErP+jTS/rqAkiCPciEg6hXoryj+KrR79CZ6ezdCj1QvcUJ0uHUGvKlAQcVNZT4rwq2el119xN4+rO6Hc+JCBcrOISGgaRcAj1VrhHOCsHrMRX7WvpUCwuMPampUMwCZ2m1NIh1EpJkQJX/wFmP49HYBBj3v8Y96YBZj+XINQVkXAI9VqAUwDfDPyGSI9IS4diMWrJFpuz1j1/o5yWbEuHUGtpV73N2tytWbuOjJ4zH7Wzi9nOIQiWIBIOod5zdXBlab+lPBv6rKVDsYgBNwORiqx7hUo5VY51Fi77K3M0d5PJ5XQZMZahM9/Cxt7epMcWhPpAJByCVVDKlczsMJNPen2C2kZt6XDq1MPXVJYOwWTsk85YOgSTKGvu1sdkx1M7uzDi7ffpPPwpZPL697a8fPlydDqdpcMQrFz9+8kWhHvo49+HtYPXEuIcYulQ6ozvuUxLh2AytheO0lBWPKdfa2mS5m6B4e145sP/4Bf6kAmium3//v0oFAr69+9fo+cFBATwySefVNg2atQoLlyw5mXNQn3QQH71hcakqbYp3wz8hqHNh1o6FLPzMKiRXYi3dBgmIy/MQ6uz7pUq5Wrb3E2uUNB9zHieeGMOjlrTr0JatmwZL7/8Mnv37iUxsXaXshwcHPDw8DBRZEJjJRIOwSrZK+15t+u7zO0yt0HX6xiU4w8G6+wQezc6+4YxHwUevLmb1t2DUXPm0XHIcLNUDs3Ly2PdunVMmTKFwYMHs3z58gqPb968mfbt22Nvb4+bmxvDhg0DoFevXly+fJlXXnkFmUxmjK2qSyqLFi0iKCgIW1tbQkJCWLlyZYXHZTIZX331FU888QSOjo60aNGCzZs3m/y1CtZDJByCVRvWYhjfDPyG5rrmlg7FLNpdtbV0CCanKU6zdAgmVdPmbs07PMwz8xbSJLiV2WJau3YtISEhhISE8PTTTxMdHY0kSQBs3bqVYcOGMWjQIP788092795N+/btAdi4cSO+vr688847JCcnk5ycXOXxv/vuO6ZNm8aMGTM4ffo0L7zwAhMmTOCXX36psN/cuXMZOXIkJ0+eZODAgYwdO5bMzIZziVCoGZlU/lMoCFas2FDMohOLiD4djUFqOCMC69c0QYpvGCs7yuX2eopDdLN0GCbl4RdP4snv7rmPwsaGHmOfI3LAY2aPp2vXrowcOZJp06ah1+vx9vZm9erVREVF0aVLF5o1a8Y333xT5XMDAgKYPn0606dPN25bvnw506dPJzs723j81q1b8+WXXxr3GTlyJHl5eWzduhUoG+F46623ePfdd4GyUReNRsO2bdtqPK9EaBjECIfQINgqbJkWOY1VA1c1mNGOIL1Lg0s2AOwu/WnpEEyuuuZuzk18eeqdj+ok2Th//jyHDh1i9OjRACiVSkaNGsWyZcsAOH78OH361G6FTUxMDF27dq2wrWvXrsTExFTYFhYWZvy3SqVCo9Fw/fr1Wp1bsF4NY/aWINzS2q01awevbRCjHQMyfYGG9+Zsk3gO21AFxYXW+39TWXlzt6VI0u1qqnKFko5DnqTTsNEoTVy3426WLl2KXq/Hx8fHuE2SJGxsbMjKysLBwcEk5/nr3BNJkipts/nLa5bJZJSWWne1WeHBiREOocEpH+34ZuA3BDkFWTqcBxZ2ueG2IXe2/tYwlfy1uZt3ixCemfcJXUc9U2fJhl6vZ8WKFXz88cccP37ceDtx4gT+/v6sWrWKsLAwdu/efddj2NraYqhmonKrVq3Yu3dvhW379++nVSvzzUsRrJ8Y4RAarDZubVj32DoWnVjE8tPL0Ut6S4dUI86nr9BQJ1hp5TdIpeEUNCuXnR6Ok2cs7QY9TnjfgXVexGvLli1kZWUxceJEnJwqZnXDhw9n6dKlLFiwgD59+hAUFMTo0aPR6/Vs376dWbNmAWVzOH777TdGjx6NnZ0dbm5ulc7z2muvMXLkSCIjI+nTpw8//PADGzdu5KeffqqT1ylYJzHCITRo5aMd6x5bR0evjpYO575FFHsjpTS8yynlVLlJlg7BLAIe8mb0O58S0W+wRSqGLl26lKioqErJBsCTTz7J8ePH0Wq1rF+/ns2bNxMeHs4jjzzCwYMHjfu98847JCQkEBQUhLu7e5XnGTp0KJ9++ikfffQRrVu3ZsmSJURHR9OrVy9zvTShARCrVIRGZWfCTv515F+k5KVYOpR7ej0pgnYrDls6DLMpjOzLfu1QS4dhMi5NVPQYHYxPsLOlQxGEekuMcAiNSr+AfmweupnJbSfjoDTN5DlzaBlfYukQzMr2wmFoAFNUbB2UdBvRglFvdhDJhiBUQ4xwCI1Wal4qC/9cyA9xPyDVo9kSMgnWLVEjZWVbOhSzOjx0CTezrWteTTm5XEbIw148PDQIR23DK84mCOYgEg6h0TubcZZ/H/k3B1MOVr9zHehV4M/UT+IsHYbZxY75jCvXrGuYQ66QEdLJi3YD/HFyv//qooIgiFUqgkCoayhf9fuKo6lHWXxiMX8k/2HReHqnugINP+HQlKQDVU9KrG/kShktO3vTrp8/Wrf6eylOEOozkXAIwi3tPNvx30f/y4m0Eyw5sYTfk363SBxBF/Mtct66psqKp74nHAqlnFZdvIns74/Gxd7S4QiCVROXVAThLs5knGHJiSXsubKnzuZ42EkKvvlUjlRQUCfns6SSoHB+93ve0mFUSWEjJ7RbEyIf9Uft3HC7EQtCXRIJhyBU43zmeb48+SU/Jf5EqWTessyP32zB05/FVL9jAyDJFfwe9Rn64vpT6lppI6d1dx8i+jVF5SQSDUEwJXFJRRCqEeISwse9PiYhJ4F1F9axOW4zOUU5ZjlXt2SNWY5bH8lKDeh0ctKvWz7hsLVXENqtCRGP+otVJ4JgJqIOh1Ct8ePHI5PJkMlk2NjY4OnpSd++fVm2bFmjasQU4BTArA6z2D1iN+91fY8wt7Dqn1RDfhfMk8jUV07KXIue3yNAS+9nWjL+w250Hd5CJBuCYEZihEO4L/379yc6OhqDwUBqaio7duxg2rRpbNiwgc2bN6NUVv5RKikpqdQtsiGwU9gxpPkQhjQfQkxGDGvPr2Vb/DYK9LWbd+FUao8ipuGvTrmTOi8ZuHtbd3OwdVAS3NGT1t2b4ObbeEaUBMHSxAiHcF/s7Ozw8vLCx8eHyMhI/vGPf/D999+zfft2li9fDpS1nl68eDFDhgxBpVLx3nvvYTAYmDhxIoGBgTg4OBASEsKnn35a4djjx49n6NCh/POf/8TT0xOdTsfcuXPR6/W89tpruLi44Ovry7Jlyyo87/XXXyc4OBhHR0eaNWvG22+/TUlJ3VbobOXaijld5vDziJ/5e8e/E+wc/MDHGnwjEPTWWQjrQTmknK+T88hk4BPizCPjWjF+fld6PhUikg1BqGNihEN4YI888ght27Zl48aNTJo0CYDZs2fzwQcfsGDBAhQKBaWlpfj6+rJu3Trc3NzYv38/f/vb3/D29mbkyJHGY/3888/4+vry22+/sW/fPiZOnMiBAwfo0aMHBw8eZO3atUyePJm+ffvi5+cHgEajYfny5TRp0oRTp07x/PPPo9FojF0v65LaVs2YVmMY02oMl7IvsTNhJ7su7+Ji9sX7PkbHpMZX38E+9jCE9Tfb8V2aqAjp5EVwR0/UzmJZqyBYklilIlRr/PjxZGdns2nTpkqPjR49mpMnT3L27FlkMhnTp09nwYIF9zzeiy++SGpqKhs2bDAef8+ePVy6dAn5rQ6bLVu2xMPDg99++w0Ag8GAk5MTX331FaNHj67yuB999BFr167lyJEjtXi1phWXHceuhF3sTNhJXM69L5es2+AHsfF1FFn9cfCxJeTdNN3IjtbNnsAwd0Ie9sK9qRjFEIT6QoxwCLUiSRIy2e3y1O3bt6+0z+LFi/nqq6+4fPkyBQUFFBcXEx4eXmGf1q1bG5MNAE9PT9q0aWO8r1AocHV15fr12y3bN2zYwCeffMLFixfJzc1Fr9ej1WpN+OpqL0gXxJTwKUwJn0JcdlzZyEfCrkrJh6/eCS4mWCZIC9Op9eTdfPDnK+0U+Abr8At1pWmoCzpPUXJcEOojkXAItRITE0Ng4O1JfyqVqsLj69at45VXXuHjjz+mc+fOaDQaPvroIw4erNi35K+TS8tXxPx1W/mqmD/++IPRo0czd+5c+vXrh5OTE2vWrOHjjz825cszqSBdEFPDpzI1fCpJuUnsv7afA9cOcDD5IIPSm4KUYekQLUJTmgXUoNOqDNx81TQNdcEv1BXvICcUSjEdTRDqO5FwCA/s559/5tSpU7zyyit33ef333+nS5cuTJ061bgtLq72KzH27duHv78/b775pnHb5cuXa33cuuKj9mFE8AhGBI/AUGogKy4GNAfIP3iQ/D//RMpvHOXNAVTZl6ku4XDQ2ODXysWYZIjlq4JgfUTCIdyXoqIiUlJSKiyL/eCDDxg8eDDjxo276/OaN2/OihUr2LlzJ4GBgaxcuZLDhw9XGBV5EM2bNycxMZE1a9bQoUMHtm7dynfffVerY1qKQq7ArUUbaNEG/vY8UkkJhWfPUnDyFIWnT1Nw+jTF8fHQQGueOCSeBM9w432ZDHSejrj5aXBvqsEnWId7U02FS3eCIFgfkXAI92XHjh14e3ujVCpxdnambdu2LFy4kGeffbbC3Iu/mjx5MsePH2fUqFHIZDKeeuoppk6dyvbt22sVz5AhQ3jllVd46aWXKCoqYtCgQbz99tvMmTOnVsetD2Q2Nji0bYtD27bGbYbcPArPnqHw9BkKT5+iMOYcxVevQh0vAzY1mZ0daptCWnb2MiYYbr5qbO3FW5MgNDRilYogWClJr6fk6lWKEhIoNt4uU5yQgD41FerJr7bM0RGbJt7Y+Phg6+NT9tXfH7vmzbFp2hTZPRJW4d7mzJnDpk2bOH78uKVDEYRqiY8RgmClZEoltgEB2AYEVHpMKilBn5GBPi0dfXoa+vR0DOnpt+6nY8jOpjQ/n9K8vLKvBQVIRUVIxcWVExWZDBQKZLduKJXI7exQ6JyQa51QODmh0GrLvuqckGu1KF3dsPHxwcbXB6VzDSaE1gMpKSm8//77bN26laSkJDw8PAgPD2f69On06dPH0uEJgtUSCYcgNEAyGxtsvLyw8fKq8XOl4mIkg8GYXDSmEYiEhAS6du2KTqfjww8/JCwsjJKSEnbu3MmLL77IuXPnLB2iIFitxvNOIgjCfZHZ2iJ3cEBma9uokg2AqVOnIpPJOHToEMOHDyc4OJjWrVvz6quv8scffwCQmJjIkCFDUKvVaLVaRo4cSWpqqvEYc+bMITw8nGXLltG0aVPUajVTpkzBYDDw4Ycf4uXlhYeHB++//36Fc+fk5PC3v/0NDw8PtFotjzzyCCdOnKiwz7x58/D09ESj0TBx4kQKCwuNj/3222/Y2NiQkpJS4TkzZsygR48epv5WCUKNNa53E0EQhLvIzMxkx44dvPjii5XqyQDodDokSWLo0KFkZmby66+/8uOPPxIXF8eoUaMq7BsXF8f27dvZsWMHq1evZtmyZQwaNIirV6/y66+/Mn/+fN566y1jEiNJEoMGDSIlJYVt27Zx9OhRIiMj6dOnD5mZmUBZTZvZs2fz/vvvc+TIEby9vfniiy+M5+zRowfNmjVj5cqVxm16vZ5vvvmGCRMmmONbJgg1IwmCIAjSwYMHJUDauHHjXffZtWuXpFAopMTEROO2M2fOSIB06NAhSZIkafbs2ZKjo6N048YN4z79+vWTAgICJIPBYNwWEhIiffDBB5IkSdLu3bslrVYrFRYWVjhfUFCQtGTJEkmSJKlz587S5MmTKzzeqVMnqW3btsb78+fPl1q1amW8v2nTJkmtVku5ubn3+20QBLMRIxyCIAiUjTIA96z3ERMTg5+fn7GBIEBoaCg6nY6YmBjjtoCAADSa231cPD09CQ0NrVS+v7xU/9GjR8nNzcXV1RW1Wm28xcfHGwvlxcTE0Llz5wrx/PX++PHjuXjxonHkZNmyZYwcObLKERtBqGti0qggCALQokULZDIZMTExDB06tMp9pL/0Drrb9pqW6i8tLcXb25s9e/ZUOrZOp7vv1+Dh4cFjjz1GdHQ0zZo1Y9u2bVUeUxAsQYxwCIIgAC4uLvTr14/PP/+cvLy8So9nZ2cTGhpKYmIiV65cMW4/e/YsOTk5tGrV6oHPHRkZSUpKCkqlkubNm1e4ubm5AdCqVSvjyEW5v94HmDRpEmvWrGHJkiUEBQXRtWvXB45LEExJJByCIAi3fPHFFxgMBjp27Mi3335LbGwsMTExLFy4kM6dOxMVFUVYWBhjx47l2LFjHDp0iHHjxtGzZ88qOyXfr6ioKDp37szQoUPZuXMnCQkJ7N+/n7feeosjR44AMG3aNJYtW8ayZcu4cOECs2fP5syZM5WOVd7M8L333hOTRYV6RSQcgiAItwQGBnLs2DF69+7NjBkzaNOmDX379mX37t0sWrQImUzGpk2bcHZ2pkePHkRFRdGsWTPWrl1bq/PKZDK2bdtGjx49eO655wgODmb06NEkJCTg6ekJwKhRo/i///s/Xn/9ddq1a8fly5eZMmVKpWPJ5XLGjx+PwWC4Z58jQahrorS5IAhCA/P888+TmprK5s2bLR2KIBiJEQ5BqIHx48cjk8mYPHlypcfKi0aNHz++1udZvnx5jSYLCgKUFQ/76aefWLVqFS+//LKlwxGECkTCIQg15Ofnx5o1aygoKDBuKywsZPXq1TRt2tSCkVVmMBiMKyGEhm/IkCE8/vjjvPDCC/Tt29fS4QhCBSLhEIQaioyMpGnTpmzcuNG4bePGjfj5+REREQHAihUrcHV1paioqMJzn3zySeN19RMnTtC7d280Gg1arZZ27dpx5MgR9uzZw4QJE8jJyUEmkyGTyZgzZw4AxcXFzJo1Cx8fH1QqFZ06daqw7LF8ZGTLli2EhoZiZ2fH77//LkpeNxJ79uwhPz+fBQsWWDoUQahEJByC8AAmTJhAdHS08f6yZct47rnnjPdHjBiBwWCocA09PT2dLVu2GFcOjB07Fl9fXw4fPszRo0d54403sLGxoUuXLnzyySdotVqSk5NJTk5m5syZxvPu27ePNWvWcPLkSUaMGEH//v2JjY01nic/P58PPviAr776ijNnztC+fXtR8loQBIsTCYcgPIBnnnmGvXv3kpCQwOXLl9m3bx9PP/208XEHBwfGjBlTISlZtWoVvr6+9OrVCyhrAhYVFUXLli1p0aIFI0aMoG3bttja2uLk5IRMJsPLywsvLy/UajVxcXGsXr2a9evX0717d4KCgpg5cybdunWrcJ6SkhK++OILunTpQkhICCqViokTJ1bYZ+vWreTn5zNy5Ejzf7MEQRAQCYcgPBA3NzcGDRrE119/TXR0NIMGDTIWaCr3/PPPs2vXLpKSkgCIjo42TjoFePXVV5k0aRJRUVHMmzfPWML6bo4dO4YkSQQHB1cof/3rr79WeK6trS1hYWEVnitKXguCYGmitLkgPKDnnnuOl156CYDPP/+80uMRERG0bduWFStW0K9fP06dOsUPP/xgfHzOnDmMGTOGrVu3sn37dmbPns2aNWt44oknqjxfaWkpCoWCo0ePolAoKjymVquN/3ZwcKhUfluUvBYEwdJEwiEID6h///4UFxcDZdUdqzJp0iQWLFhAUlISUVFRFZp+AQQHBxMcHMwrr7zCU089RXR0NE888QS2trYYDIYK+0ZERGAwGLh+/Trdu3evcbyTJk1i9OjR+Pr6ipLXgiDUOXFJRRAekEKhICYmhpiYmEojDuXGjh1LUlIS//3vfytMKi0oKOCll15iz549xjkghw8fNvbjCAgIIDc3l927d5Oenk5+fj7BwcGMHTuWcePGsXHjRuLj4zl8+DDz589n27Zt1cYrSl4LgmBJIuEQhFrQarVotdp7Pv7kk0+iVqsrdCBVKBRkZGQwbtw4goODGTlyJAMGDGDu3LkAdOnShcmTJzNq1Cjc3d358MMPgbJ5IOPGjWPGjBmEhITw+OOPc/DgwUojJ1URJa8FQbAkUdpcEMysb9++tGrVioULF1o6FFHyWhAEixFzOATBTDIzM9m1axc///wzn332mUVjycnJ4fDhw6xatYrvv//eorEIgtA4iYRDEMwkMjKSrKws5s+fT0hIiEVjGTJkCIcOHRIlrwVBsBhxSUUQBEEQBLMTk0YFQRAEQTA7kXAIgiAIgmB2IuEQBEEQBMHsRMIhCIIgCILZiYRDEARBEASzEwmHIAiCIAhmJxIOQRAEQRDMTiQcgiAIgiCYnUg4BEEQBEEwO5FwCIIgCIJgdiLhEARBEATB7ETCIQiCIAiC2YmEQxAEQRAEsxMJhyAIgiAIZicSDkEQBEEQzE4kHIIgCIIgmJ1IOARBEARBMDuRcAiCIAiCYHYi4RAEQRAEwexEwiEIgiAIgtmJhEMQBEEQBLMTCYcgCIIgCGYnEg5BEARBEMzu/wNX8N2G3PzwfwAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "# Protect execution\n",
-    "if __name__=='__main__':\n",
-    "    BDI, tabGrp = ClustersMovies(Hyb, 6, movies_metadata, links_small, ratings_small)\n",
-    "    SelectionGenres(BDI[0], ratings_small, movies_metadata)"
+    "def CompareSelectGenres(GRP, GRP2, ratings_small, nom1='BDI', nom2='BDI2'):\n",
+    "    GRP_DfGenres = GroupeParGenres(GRP)    #df qui met  dans les collums genres    \n",
+    "    GRP2_DfGenres = GroupeParGenres(GRP2)    #df qui met  dans les collums films\n",
+    "    fig, axs = plt.subplots(1, 2, figsize=(18, 6), sharey=False)\n",
+    "    prcEval = SelectionGenres(GRP, ratings_small, GRP_DfGenres, axs[0], nom1)\n",
+    "    prcEval2 = SelectionGenres(GRP2, ratings_small, GRP2_DfGenres, axs[1], nom2)\n",
+    "    locSave = \"../img/CompareSelectGenre.png\"\n",
+    "    fig.savefig(locSave)\n",
+    "    \n",
+    "    res = prcEval-prcEval2\n",
+    "    res = res.sort_values(ascending=False)\n",
+    "    resStr = str()\n",
+    "    resStr += \"votre groupe \"+nom1+\" evalue beaucoup de film de \"+str(res.index[0])+\" c'est \"+str(res.iloc[0])+\" de plus que le groupe \"+nom2+\"\\n\"\n",
+    "    resStr += \"votre groupe \"+nom1+\" evalue peu de film de \"+str(res.index[-1])+\" c'est \"+str(res.tail(1).iloc[0])+\" en moins que le groupe \"+nom2+\"\\n\"\n",
+    "    return resStr"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7564ede5-5db3-4a01-a408-d283c5b8d4a9",
+   "cell_type": "markdown",
+   "id": "43d337ba-7f6d-45ed-af30-35f128928bf7",
    "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "823295b4-6438-4719-8ec0-2c9c73de5e44",
-   "metadata": {
-    "lines_to_next_cell": 2
-   },
-   "outputs": [],
-   "source": []
+   "source": [
+    "On veut aussi comparer les stats du types notes, pourquoi pas faires des violin"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "2fccbd16-3626-48dc-8fd1-34902ee0b4b5",
+   "execution_count": 21,
+   "id": "9e02d8d9-0abd-4efe-8109-a17f1a0d8179",
    "metadata": {
-    "lines_to_next_cell": 0
+    "tags": []
    },
    "outputs": [],
-   "source": []
+   "source": [
+    "def EvalParGenres(BDI, ratings_small, links_small, axs, nom='BDI'):\n",
+    "    GRP_DfGenres = GroupeParGenres(BDI)\n",
+    "    ids_par_genres = {}\n",
+    "    Notes_par_genres = {}\n",
+    "    stats_par_genres = {}\n",
+    "    for g in GRP_DfGenres.columns.drop('id'):\n",
+    "        ids_par_genres[g] = GRP_DfGenres.loc[GRP_DfGenres[g] == 1, 'id'].tolist()\n",
+    "        Notes_par_genres[g] = RatingsFromMovies(ids_par_genres[g],ratings_small, links_small)\n",
+    "        stats_par_genres[g] = Notes_par_genres[g]['rating'].describe()\n",
+    "    axs.set_title(\"répartion des notes des films du groupe {}\".format(nom))\n",
+    "    data = [Notes_par_genres[key]['rating'] for key in Notes_par_genres.keys()]\n",
+    "    pos = range(len(Notes_par_genres))\n",
+    "    axs.violinplot(data, pos, widths=0.7, showmeans=True, showextrema=True, showmedians=True)\n",
+    "    axs.set_xticks(pos, Notes_par_genres.keys())\n",
+    "    return stats_par_genres"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "0f42ef83-c993-4d7c-ab04-36abb7195cd1",
+   "execution_count": 22,
+   "id": "d244b498-7866-43de-b65d-cb1f3206ddd2",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "def CompareEvalGenres(GRP, GRP2, ratings_small, links_small, nom1='BDI', nom2='BDI2'):\n",
+    "    fig, axs = plt.subplots(2, 1, figsize=(18, 6), sharey=False)\n",
+    "    stats = EvalParGenres(GRP, ratings_small, links_small, axs[0], nom1)\n",
+    "    stats2 = EvalParGenres(GRP2, ratings_small, links_small, axs[1], nom2)\n",
+    "    locSave = \"../img/CompareEvalGenre.png\"\n",
+    "    fig.savefig(locSave)    \n",
+    "    meilleurG= []\n",
+    "    meilleurG2 = []\n",
+    "    diff = []\n",
+    "    for g in stats:\n",
+    "        meilleurG.append((g,stats[g][1]))\n",
+    "        meilleurG2.append((g,stats2[g][1]))\n",
+    "        diff.append((g,stats[g][1]-stats2[g][1]))\n",
+    "    max_MeansDiff = max(diff, key=lambda x: x[1])\n",
+    "    max_Means = next(filter(lambda t: t[0] == max_MeansDiff[0], meilleurG))\n",
+    "    min_MeansDiff = min(diff, key=lambda x: x[1])\n",
+    "    min_Means = next(filter(lambda t: t[0] == min_MeansDiff[0], meilleurG))\n",
+    "    resStr = str()\n",
+    "    resStr = \"votre groupe \"+nom1+\" aime particulierement les films de \"+str(max_MeansDiff[0])+\" attribue une note moyenne de \"+str(max_Means[1])+\" c'est \"+str(max_MeansDiff[1])+\"de plus que le groupe \"+nom2+\"\\n\"\n",
+    "    resStr += \"votre groupe \"+nom1+\" n'aime pas particulierement les films de \"+str(min_MeansDiff[0])+\" attribue une note moyenne de \"+str(min_Means[1])+\" c'est \"+str(min_MeansDiff[1])+\"de moins que le groupe \"+nom2+\"\\n\"\n",
+    "    return resStr"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "622f1b3b-2182-4ad9-9d63-03d3040b3f2d",
+   "execution_count": 25,
+   "id": "2fccbd16-3626-48dc-8fd1-34902ee0b4b5",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "efficacite hybride:  0.2879286465035882\n",
+      "vous etes dans le groupe 4 qui est compose de 41 membres \n",
+      "c'est a dire 6.110283159463488 % de tout les utilisateurs. \n",
+      "voici les autres utilisateurs de votre groupe:\n",
+      "[1, 12, 15, 35, 53, 59, 72, 79, 97, 107, 122, 138, 142, 165, 170, 176, 189, 195, 210, 213, 262, 305, 310, 315, 325, 337, 353, 364, 386, 394, 414, 457, 461, 475, 531, 552, 557, 578, 620, 624, 628]\n",
+      "votre groupe 4 evalue beaucoup de film de Adventure c'est 3.235901608081824 de plus que le groupe Global\n",
+      "votre groupe 4 evalue peu de film de Drama c'est -5.731996149417881 en moins que le groupe Global\n",
+      "votre groupe 4 aime particulierement les films de Music attribue une note moyenne de 3.596629213483146 c'est 0.025346638112680786de plus que le groupe Global\n",
+      "votre groupe 4 n'aime pas particulierement les films de TV-Movie attribue une note moyenne de 2.764705882352941 c'est -0.6146044624746452de moins que le groupe Global\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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FL3oRAOAf/uEf8L//+784cuQIPvKRjwColva3Oiat1L630ecMDw9DlmXEYrF1vw+Hw+v+73A4Gh5bo++pnW89G3+3tLSExx577IJr6vV6oSjK+ev6ghe8AN///vdRLpdx8803Y3R0FHv37sWdd97Z7rQbnkftXGrnEYvFoChK02tTf17NqElW3HTTTRecz2c/+1koioJoNAoA+Pa3v41bbrkF//iP/4irrroKoVAIN998c8uGkrFYDLIsq76uasar3+/HL3/5S1x88cW49dZbcdFFF2F4eBi33XabKsd3t4RCoXX/t9vtTX+fz+fP//9Nb3oT/umf/gkzMzN41atehUgkgiuuuAL/+Z//2fL71tbWWj6belEbKxu/y2azNRyLwIXPZbvntd14bEWzMVT7zNpY/tCHPnTB+HnXu94FAC0d+x/5yEcgiiLe8573IB6PIx6PI51OA6hK5MTj8Qt05xkMBoPBYDA6gWkyMxgMBoPBIJr6LD8A6OvrA8dx+NWvfnXe0VrPxt810sitORBrTqa77roLoiji7rvvXpeZ+v3vf1/VMWml9r0LCwsX/G1+fh48zyMYDHb1HfXf08hhuri4uK5pWl9fH5xOZ1ON53rN2Ze97GV42ctehkKhgPvvvx+HDx/G61//ekxOTuKqq67q6piDwSB4nm96bTYeS6tj/eu//mtceeWVDV9Tczr29fXhC1/4Ar7whS/gzJkz+MEPfoA/+7M/w/LyMn7yk580PUaO45pe143Hona87tu3D3fddRcURcFjjz2Gr33ta/jkJz8Jp9OJP/uzP2t5zmbylre8BW95y1uQyWTw3//937jttttw44034tlnn70gY75GOBzGgw8+eMHvG11TSZIaNrlUkzVdewaWlpYwMjJy/vflcrmpc3jj813/vG7Uu56fn183HiVJQqFQaHisjcZtszFU+87aez784Q/jla98ZcPjrddW38gTTzyB6enphs7sW265BUA1aBIIBJp+BoPBYDAYDIYaWCYzg8FgMBgMqrjxxhuhKArOnj2LQ4cOXfCzb9++da9PpVL4wQ9+sO533/rWt8DzPF7wghcAqDqVbDYbBEE4/5pcLodvfOMbmo6tPiO3FTt37sTIyAi+9a1vrcsizGQy+O53v4urrroKLpdL03c34sorr4QkSfjnf/7ndb//9a9/vU7yAKhe15MnTyIcDje8rvUO6RoOhwNXX301PvvZzwIAjh071vUxu91uXHHFFfje97637lrKsoxvfvObGB0dPS9V0iyb+/nPfz4CgQCeeuqphudy6NCh85m69YyPj+M973kPrr/+ehw9erTlMV5++eX43ve+ty6rN5VK4Yc//OG612odr0B1PB44cAB/+Zd/iUAg0PJYSMLtduMlL3kJPvKRj6BYLOLJJ59s+tprr7226bO5kcnJSTz77LPrnLdra2v49a9/3faYas/4t7/97XW//9d//VeUy+W27weAF77whQCqzSTrOXLkCI4fP36+iWTtWB977LF1r3v22WebSlrceeed6+aAmZkZ/PrXv8Y111wDoDpXbN++HY8++mjTsVwvP7ORL3zhC7jnnnvW/fzlX/4lAOD222/HPffcs06WhsFgMBgMBqNTWCYzg8FgMBgMqnj+85+Pt7/97XjLW96Chx56CC94wQvgdruxsLCA//mf/8G+ffvwzne+8/zrw+Ew3vnOd+LMmTPYsWMH/uM//gP/8A//gHe+850YHx8HUNWd/fznP4/Xv/71ePvb3461tTV87nOfa5h52op9+/bh3nvvxQ9/+EMMDQ3B6/U2zDLkeR533HEH3vCGN+DGG2/EO97xDhQKBfy///f/EI/H8ZnPfKa7i3SOYDCID33oQ/jUpz6FP/qjP8KrX/1qzM7O4vbbb78gs/H9738/vvvd7+IFL3gBPvCBD2D//v2QZRlnzpzBz372M/zJn/wJrrjiCnz84x/H3NwcrrvuOoyOjiIej+Ov/uqvIIoirr76al2O+/Dhw7j++utx7bXX4kMf+hDsdju+9KUv4YknnsCdd955PtO0pjH793//9/B6vZAkCVNTUwiHw/jrv/5r3HLLLYhGo7jpppsQiUSwsrKCRx99FCsrK/jyl7+MRCKBa6+9Fq9//euxa9cueL1eHDlyBD/5yU+aZo3W+L//9//id3/3d3H99dfjT/7kT1CpVPDZz34Wbrf7vBQHoH683n333fjSl76El7/85diyZQsURcH3vvc9xONxXH/99bpcVyN429veBqfTiec///kYGhrC4uIiDh8+DL/ff16/uxE333wz/vIv/xI333wzPv3pT2P79u34j//4D/z0pz+94LVvetOb8Hd/93d44xvfiLe97W1YW1vDHXfcAZ/P1/b4LrroIrzuda/DX/zFX0AQBLzwhS/Ek08+ib/4i7+A3+9fp4nejJ07d+Ltb387/vqv/xo8z+MlL3kJpqen8bGPfQxjY2P4wAc+sO5Y3/jGN+Jd73oXXvWqV2FmZgZ33HEH+vv7G3728vIyXvGKV+Btb3sbEokEbrvtNkiShA9/+MPnX/N3f/d3eMlLXoIXv/jFePOb34yRkRFEo1EcP34cR48exXe+852mx37xxRe3vDY1ZzaDwWAwGAxG15jTb5DBYDAYDAajNbfddpsCQFlZWWn493/6p39SrrjiCsXtditOp1PZunWrcvPNNysPPfTQ+ddcffXVykUXXaTce++9yqFDhxSHw6EMDQ0pt956q1IqlS74vJ07dyoOh0PZsmWLcvjwYeUrX/mKAkA5ffr0+ddNTEwoN9xwQ8NjeuSRR5TnP//5isvlUgAoV199taIoinLPPfcoAJR77rln3eu///3vK1dccYUiSZLidruV6667Tvnf//1fVdfhq1/96gXH1ghZlpXDhw8rY2Njit1uV/bv36/88Ic/VK6++urzx1cjnU4rH/3oR5WdO3cqdrtd8fv9yr59+5QPfOADyuLioqIoinL33XcrL3nJS5SRkRHFbrcrkUhE+b3f+z3lV7/6VcvjUBRFAaC8+93vvuD3ExMTyi233LLud7/61a+UF77whefv75VXXqn88Ic/vOC9X/jCF5SpqSlFEAQFgPLVr371/N9++ctfKjfccIMSCoUUURSVkZER5YYbblC+853vKIqiKPl8XvnjP/5jZf/+/YrP51OcTqeyc+dO5bbbblMymUzb8/nBD36g7N+/X7Hb7cr4+Ljymc985vz92ki78fr0008rr3vd65StW7cqTqdT8fv9yuWXX6587Wtfa3sczcZIo3sMQLntttvO/782jo4cOaLqM2+55RbF7Xaf///Xv/515dprr1UGBgYUu92uDA8PK695zWuUxx57rO1xz83NKa961asUj8ejeL1e5VWvepXy61//+oL7WPue3bt3K5IkKXv27FG+/e1vK7fccosyMTHR9nvy+bzywQ9+UIlEIookScqVV16p3HfffYrf71c+8IEPtL0WiqIolUpF+exnP6vs2LFDEUVR6evrU974xjcqs7Oz614ny7Jyxx13KFu2bFEkSVIOHTqk/OIXv7jgXtTmhG984xvK+973PqW/v19xOBzKb//2b6+bw2o8+uijymte8xolEokooigqg4ODygtf+ELlb//2b9ue/0Zq3117DhgMBoPBYDD0gFMU1umBwWAwGAyGNbnmmmuwurqKJ554wuxDYTAYBPHrX/8az3/+8/HP//zPeP3rX9/z77/33ntx7bXX4jvf+Q5uuummnn8/g8FgMBgMht4wuQwGg8FgMBgMBoNhWf7zP/8T9913Hy699FI4nU48+uij+MxnPoPt27e3lUVhMBgMBoPBYKiDOZkZDAaDwWAwGAyGZfH5fPjZz36GL3zhC0ilUujr68NLXvISHD58GJIkmX14DAaDwWAwGJaAyWUwGAwGg8FgMBgMBoPBYDAYDAajY9q3U2YwGAwGg8FgMBgMBoPBYDAYDAajCczJzGAwGAwGg8FgMBgMBoPBYDAYjI5hTmYGg8FgMBgMBoPBYDAYDAaDwWB0TM8b/8myjPn5eXi9XnAc1+uvZzAYDAaDwWAwGAwGg8FgMBgMhgoURUEqlcLw8DB4vnm+cs+dzPPz8xgbG+v11zIYDAaDwWAwGAwGg8FgMBgMBqMDZmdnMTo62vTvPXcye71eANUD8/l8vf56BoPBYDAYDAaDwWAwGAwGg8FgqCCZTGJsbOy8T7cZPXcy1yQyfD4fczIzGAwGg8FgMBgMBoPBYDAYDAbhtJM9Zo3/GAwGg8FgMBgMBoPBYDAYDAaD0THMycxgMBgMBoPBYDAYDAaDwWAwGIyO0eRkvv3228Fx3LqfwcFBo46NwWAwGAwGg8FgMBgMBoPBYDAYhKNZk/miiy7Cz3/+8/P/FwRB1wNiMBgMBoPBYDAYDAaDwWAwGAwGPWh2MttsNpa9zGAwGAwGg8FgMBgMBoPBYDAYDAAdOJmfe+45DA8Pw+Fw4IorrsCf//mfY8uWLUYc26YnWywb9tkuu+ZbbwpGXYPNfv4AHddgs58/wJ4BNgbYGGDnz56BzT4GNjvsGWDPABsDbAyw82fPABsDm3sMbPbzpwlOURRF7Yt//OMfI5vNYseOHVhaWsKnPvUpPP3003jyyScRDocbvqdQKKBQKJz/fzKZxNjYGBKJBHw+X/dnYFEqsoKtt/6HYZ9/4tMvgU0gu+9jqSJj+0d+bMhnn/rz3wPPc4Z8tp5M/tmPDPvs6c/cYNhn68VmP38jn4FnP/US2G3kzgGKoiBdKGPf7T8z7Due/MSL4XaQb1QY9RzQ8Axki2Xs+fhPDfnsx29/ETwOGziO3LUgXShj723GnD9QvQZeSTTs87shXSijZqIaNQ88fvuLAAACz7ENBmHU1gDAuPsP/GYMSKIA0WS7OF+qoFSRG/7N6GdgI6LAQxLJkUTcTPZgsSyjUK5c8PtejgES1wWjxsBzn36J6c++GjbTM9CMzWoP19YGo9dCt91GtH+EPQPmk0wm4ff72/pyNVnUL3nJS87/e9++fbjqqquwdetWfP3rX8cHP/jBhu85fPgwPvGJT2j5GgaqTmYjKVZk4p3M0UzRsM/OlSpUOJcYm5t86cJNhl5kCmXYbXbDPr9bFAV48HTU0O94/GwCV25pHCBlkMFzS2nDPvvB01FcuzMCgn3MOHYmZujnPzQdw7W7IoZ+R6ccX0gikS0Z+h0PnKrOMSNBJ3YPscQHkuA4Dk/NJ5HKG5e5BFTHAMcBz9vaB7N9qmeiWZxZy/b0O2vPwEaGAhIuGvb39FgYVaKZIp44m+jZ920cA3Ybjxfs6O/Z96uhWfBFD1ZSBQwHnIZ9PoPRLY/OxnuyFl404sOQnz0LjO7RlMnciOuvvx7btm3Dl7/85YZ/Z5nMnfNfx5eQL7Z3MhXKFXzwO48BAD7/6v1w2FpbyTaBw4suGiQ6ewsAFhI5HJ1uv8HWev4A8Ns7++EjMEq/kRPLaTyzkGz5Gq3nLwgcfnt7H9wO8s+/VhZzZi2Lk8vNnU1qr4HPJeLSiSAAespi1MwDncwB1+8ZJDpaDQD3nVxDNF1o+7pO5gAAmOhzY+8I+ZtovecBm8Dh+dv64KFgDnx2KYXnFlNtX9fJGPC77Pit7X1dH6ORqH0GgM6ugc8l4re3k+VMqHF6NXN+3i+oCLh1cv6Oc17FA2MB9HsdXRwtwwiWU3k8NptQdf+BzscAKQ7VmbVM08Ca0c/ARib73NgW8bR9f6+YjWbx2Gy85Ws6Of+rtoURcpP17CdyJRxpEGTv1RgIuEQcmgypPNrekC2Wcc/x5bav6+T89476MRF2d32MRvPoXBxzKoJQWq/BYEDCpRNk3e9mZItl3H9yDbkW+yIt5x/xSbhoxEf0njBTKOO+k2sAjJsDgOo8EPLYcXA82PnBGkw0U8B9J9bavk7rNdg+4MWOQa8ux2h1DMlk3kihUMDx48fx27/9201f43A44HCQtXjTws5BL55eaL+5rsdhE5oajDW2RjzEO5gBwMbzbc9lI2rOHwDshGdx15gMuzAXy6JcURcLUnP+E2EXFQ5m4DeO4JDHjrmYykWyxTUIue1EGxKNODgexNEzMagNB6oZA/vH/MQ7mAFgJOBEpqAtcq92Dqh9Pg1s6XMjmikimVOX1dnuGuwZ9lHhYAaAAa+kObNP7RgY9JNvm/idouZnAFB/DfxOcsfBRMiFlVQByVzJMFsAAAb9EnMwE0rEK2H/KPDkfFJzhZ/aMTAacmJHhIzN5YBPwonldMP13shnoPGxkPVMjAScOBPNtnQu1aPm/Pu8DuIczEB1XvZINqQ3ZC72agyQmtVr1Pl3l27XO3YNehHPllAqq8/qbncNBIHDniHzA2xqcdltuETDvqjV+dsEDvtG/UTJAjViIZE//2+j54BYpohCuaLaMd1rQm4Hdg55Mb2qfl/Q7hp4JBtRAVWroMnT9qEPfQi//OUvcfr0aTzwwAO46aabkEwmccsttxh1fJuakYATXklfh5jLLmAi5NL1M41CEo1xBHMcPU5mm8BjUsfouiBwGA/Tcf/r0SvrnIbs9Y0E3XZs13EDPNnnRsQr6fZ5RjISdMJh0DwQdIsIusmVC6mH5znsHfFBELoPDAz4JGI3kI3wu0T4DHCEchwwEiB/LuzzGjtG+zzkOVhq8DyH/aN+w+YAoDq+mEwG2UR8Eg5NBuGy67vpFXgOu4d92DXoIyboKokCBnzmr88hj504TV6e5zDVp2+26ZZ+crNXzTo2l13AIAFjcCO8gclRAiHPfzscNgG7dc623DHghVPnudVogm47tvZ35xTkOGDvCPkOZgBYSubbv0gnFAVYTqqrnjOLLX0e3fxjAs/homFybAAroclyn5ubw+te9zrs3LkTr3zlK2G323H//fdjYmLCqOPb1HBcNcJm08GxAFQfpH2jdGQwAoDbbjNk4fc4yBa138h4yKWbk2XngJfY6GQrJFGAR4cFhWSHSivGwy5s1SHKOtnnoipaK/CcIQ4goz7XSFx2Gy4eDYDvwt8WdIvYM0zXeQPAjgH9x+xE2EXFxqrP7TBsEyTaeCIcWq2QRAGXTYZ0dzAC1Y3qJWMBahwMmxmvJOKKLWFMhF26aKgH3XZcsSVEZDXLtohHN7u/EwSewy5Cy4aH/BJCHn0CbxNhF9GJBxGvhEF/b+dnjgMuGiZzn2hkcpCD4CbYG4n4JN3s+Mk+F5FzoBom+9yY7OssUaA2zmnYEyayJdXVG3qx2EOndifwPIcDY4GubXiOA/aN+okLqFoFTbPqXXfdhfn5eRSLRZw9exbf/e53sWfPHqOOjYGqY0EvzdDdQz6qHiSe5+Bz6i9tEHDRkb1Y43wWY5dGX8TnoCqDcSORLsuZPZKNCqdSM6b63NjehbOtqq9I5saxFX0eB0ZD+o7b7QMe6mRTgKpjZO+IvyMni1ey4cAonQ61gMuu69wliYKuFSJGwvMcxg2qPhoNOqkYD5Io4NBkSNeM9gGfhEvGAsQ3QGb8BoHnsH3Ai0OToY4bNwtCNXv50okgsWuAJArYY2IQdMegl9hrw3Ec9gz5unbCux22rjMhe8GuQS9cjt7ZrdsiHvhdZO4TeZ4zrKpFomxvMNnn7roqdSggUbknqGdbxIuJDq7DnmFfzwM4nbKU6r3D1wzHtlYkUcDB8SDsXQSIaAk00Aqzrimgz+PoOmo52eeiZkKtJ2yAVlpYpyyIXuKy27Czi8wSSRSoy9zcSLcZdySW/2llIuzGjgHt44C0Bj5a2RHx6pLJDlTH0WiQfJmEZkS8EnZpfJaddgEXj9PtUNs+4OnKmKxn15CXqmsxGnTqns0s2njDnNdGYLfxODge0CWLcTTkxN4RVh5JK36niMunQhjTOH79LhFXTJGZvbyRiE/qyHnSLcMBJ/HXRxIF7Brs3J7leVDz/NsEHhePBXqS2T7ol4hvftdpcKnt5xIaVGnF9oin4319v9dhaiBLT7YPeDESVD9n7Rz0YshP9hxXQ1GUnkpl1GPW92rBaRdwyXigIynBnYNeKv1iNEHPLmuTM9nn7tjJFvJ0r11kFno34xF4DiHKMplrDAeciHTYiOWiYR9EipwqjXA7bF1pMJFeFq4WrdIZ42G6JDIaUdNm7TbrUhIF7BqiO3MDqOr1T6rUphQEDpeMB6iUyalHFPiuAm01BnwSdZkLPM/prs85FXZTtybYBB4Xjwa6sgsm+9zYNeijovkxozkCz2HnoBcHVMqdjIdduHSc3OzlRmyLeHSThlCD3yUSK5OxkUG/1LE9PNXnoaqq02W3Yf9oQBeZmGb4XSIVTkevAU5ml12goqJnI7Wsfq2JUwGXiH0jfkutgbsGvarsgql+t+bgpJkkciUUSuqbPOoJDU5moCqldUDj/DgedlE1DmiFrh3GJmfnoBeixkyuatdYejdUbodN11KxPo+DiuyFZuwY8Go2hgb9EjUNztoR6dBR7KVcKmMjk2GXKsPS7xKxnXIHcw2X3da1o23XkJc6x1oztvS5VWV3b4/QKQ3SiAGf1JVkAs+D2oDLkF/SLYtLEgWMasj8IYmqfJS/o3Ew6NdPy5JBBv1ex7leI81fMxZyYceAlzrbj+M47B3298R2sdt47BshU4u3GdsjXs09ChwiXRUcNUJuu2Fzl0jRvTciOEBTwGEjPM/homH1zXFtQnX9pOFea4Hjqn1WWlW7+ZwitujcONRolkxswJfKl4mXzKgRcttVz+tuhw3bKE28pA1r7LY3CXYbr9lhtLXPQ0Xn1FZEvPploOqdGd1rJFHQFH3jOHqdKo3o9P7Rft83wnEc9gz72m6wLhqmN8DUiPGQq+OgU8TnoC6DtRU8z2FnG+kUj2QjvvRZK1u7CDQM+Z3UBps4jsPWiD4bpC39bqo3mQLP4cCYtqbIHslGRaYeQzt9Hge2N9EWDXnshjQO7RV2G9/Wia4H+0b81O0VnHZBc9n7ZNhNZdYqUJVL6zPAlt077KPm3ndTzdgMvaTYzMJu41XLx+wc9FJzr7Vit/Et97u7h7xU7YcURcGyCXrM9Zj9/VrY0u9RFWzZPURfwJlWmJOZMgZ9kuqNFc9Xhf1pp18nxxDP06nHvJEhDRpCQbfdUgaFx2HTnM0PAEFKJVJa4bAJLTXLAy7RMhmsNTiOw1iHeso0Zi+1I+ASWz4P/V4HVUa1GkJue8fazFrmThLp9zi6zmaWRMES+vQOm6BJW32qj27HOqM1wwFnQ13G0aCT+jnQJ4mY6jPOUT4RdlFb7aY1gYD2hINdg96O9EebMRSQEKYo+O6yC7oHXDwG6Tz3kj6PHa42AXSHyGNAx6QtEqnavBf+3mUXqMtYT+bKpkll1FhOmZdJrRWB59rO7w6RR8CC/gBSYU5myuB5TnU2XsjtsERpuM/ZmWNxI36n3RLXw+1QL/3QZ0DjRLPxd1Am3U2JPcm0cp7Tumlsx5Bf0qxN6LILljQsOI5rmdnTybNCOhzHdRQstAkc9deD47iuO8qPBp2WcbYOqwyiCwKHCOXOJUZrBL7x821E82gzmAy7DMm4dNoFanu2AEBAw5zusgvUJ11IooApnZrzCTzXtAKAVDiO0z15wgpOZo7jMNAmiD7gkyyz9jdDFPiG44PGPSAJWcSJbAn5Eh2SGUD7hDIrJpyRDP0et02IWiNJUqnRRDocp0+zvpCFnG4OlU53tTpdNNEuWr8RSaSzqYcaKorS9G+y3PxvNGNrYkS2gkYDUy2VFve5XLHmGOhkk+kUBeozGgEg4nV0lcllpW7adpVBY7vAW+LeM1rTaDNM0wa5FRynf/NPgP4Mfy22Hc3nWc9I0KmLTTsUkDquCjITp46BAo6zzl65nW9Aorz5s1rK8oXZv2UK90MrhGQRk3IcapBb7InV/J2hL9aYWTcZao0LwUKbKj0y0GjPYqtH7YbZQkPgPGod7OdfbxEDshGtmjLkLLK5boRWXV3as5eaoSgKsi3GQKZY7uHR9A5bBxtsPaphSEAU+I6zMfwu0VLPgtrtAttXWJ98qdJwPYxliyYcjTFEvJKujbAdIk+9hJAW35FVAu+iwOsi+6FVz5oU9LTp7TbrBCDb7fktcpotKVdkFMsXOpmzBbps4VS+1NK27yU0SWbk28iL0NLI0CpYY9e1yVCbmWElJ5MeZYJWKImqUVB5b83WczICXqOlpPX1tCDLrZtCrKYLKFesd/+BqnOVAUQzRZQaGNQ1lpLml9sZQavsbT3fQyqdSr9oKS2ngUSupOp1+VLFMhmtjMacXs00DCZMr2Yt41wEqiXvehHxStQ72NJ59c6jbLFimXWg26QZgefgpXRPZNNRlFnPzzKbdkkFVvIJNGM5VWi4DmSLFaTy6uwFElhNkxMcjWeLKFGyl1xus+dJ5cvMFuwh1pldNxEZlRG5NGWRu1ZolUjYiCBwVJaFNUKWFeTL6iZJUiKhDP2pOpFbyWUAi8zJCKBx+ZwVmI+3vr/ZQgVxC2Xy1Sh2YPBaKeDWSoe7FUZouprJmoaN2FrGes8Bo0oqX8J8PNfwb/lSBTPRbI+PyDj07LNhhUbYagNNNZIaX08qna4BNaoN9OgMMOgpf2clKb12AReanKydspBovA4A7e1lkiBJokJRtNlaZpEplJFSEXRcTNAzDmjHGl63TYQsK0iqXCiyhUrDshEa6aQ8uh7RQtHqZL4EtT4zKzqYtDoYrZK5spHptfYb5zNrWUtm/WrNyGhXQkUjuWJFVWOQGRXjhDY6CaDmSxXLZPZrlQyqYSVNRllWNAXRFpo4IRl0I8sKnpxPtpREOb2atoyDxa2jXIYVqvvWMtqcMVpfTyrdNjGnOelGT5vWKvaxLCuIttnvJXIly9hAjUjkSohlms/z8/EcFRm5+VKFuGAYSU7vZszF1Nl4c7GcZZ570qF3ldmkaHEwAkA8Zw0nY7eSBxYKVmvK3EgXypZzsmo1EqxoVMWzRVVGSLZYIarsSg8qsqI5K5U2PTY1zMayqrRmV1IFy+mQqa3mueB9FrkOnToYbIJ1FsK1NlIxG4lnS5Z7DhjATDTbNoNPloHjCylLbCxtAq+Lvny14RndQSdZVjRrbtOQkaeGbjNwac7g1XNPY5X9UTJfQqVNo2dZBuKEOS/1ZLZNxUpFVrBAQTYziVVXa5kC0bJTFVnBfIss9nrypQqR19iKMCczZcSz2haIhMbXk0q3nWErFthc1Ejm1DtYFMV6JVIFjdn5aqVFaEJL2VezMmJayXbQzC5XqhBtIGlFlhVNJV+tSghpo1SRO5a+6NQ5zSCPTvTGacjGYainUK5gei2j6rXJXAlLSWvcf1EHB6Gty0xYEkjktCXdAFVNThqyGY2G5i2R1j1AK6yyP1DrG7BidStQTSZSs76rdUSaySqBdkq5omiWJuolq+lC2yBLPUwyozfQXyu1ydBaJpyyyKa60KUhUCzLkGWFWg2yerSOgXSh3HGjKBLRKtovy9Xx47BQqfhqWr0RspYpQFEU6hv81OikeYmiVDcmzi613UkhlS9rkkJayxSxpd/AA+oh3ejMdxKgIJFOs6+sJE2uNeAOANFsEeNhlwFHYzxGjl2Xnc6twEI8r2ljORvLYtCvX+M809BhKbeCNaBGf7PZ+0Juum1iuUsvcbfvNxM9g8WyXN1T0J7Vr/ZZSHb4zJBOPFdSZRelzzV+I/V+y7KCKKFZtmuZAoKEzptaK1RYJnNvoNOy3MRodbBZpdlRt00MFaXaedcrddeRmQS0Rt6tpkfbScl7rmgdJ3OpImtyMFaNaOs4WDud0wrlimWuQbakbT60UgZvoYvO0FaZCzvttVCoVADQvwbKstJRh3Cagwx7Pv5Twz57+jM3GPbZRqI1syqVL1ki2UAP/yDNTsYanQScu3kfSZQ0BFcaQatMhCwruje1T+ZKxDod1aI2EcsqPoGNZAvqn+lckVwns1pnuRmspIrYFjH7KBqT07gnKpVllCpy19r2jNawq0sZWmUjyhZJXWol5t/LzyABLZk7gHXGAFA1pLTocNboNOOFRDrZG1phQ1mjU+mcooVKZLVeAgvd/q7uo1XGQKZDZ6mWjRjJdDqfWek5YABab6eiaH8Piegh91CRFeo1qju9Dlbo09HtOdC6FsZzJd3n8XYN82hArWPSSnuBehQNMzvJ1yBKcGPSTKHcUXC/F3QynZHqzLcSLJOZMrQ2wOu2YR4JKIqCFQ3yAM1YTuWpLZXtBs4ShZFVtOhR12MlJ7PdxkPgOU0LJKlR+05gUgGApLHxk4PiTvIb6cYwtIpR2ek8mLSIPr9N0D4HAtW5k1ae+uSLAQCnVjOYWWmsQ1woV/DB7zwGAPj8q/e3rN55/vY+qq8HAPgkmyb9So/DRnXDM6CayVnuMosV+I2EFM22Qaf7Gyvsi7rNZO72/WZhhK7+SqqAXYO6f2xPUdvUl/b5rxlODfMYyRWNpDcmjWWLGPI7zT6MC9C6x+E4a+2LSIVdYcrQukDYLLCgLKcKHWWvbiSeLeleZmUGvMan1gJD4DxaO4l3+z5S8bvUl7z7nKKlDMtOsxBIzl7QilcSoWWfrGW8kE43TWCt4mTuVLMvmilapgGmR9KeI+Fx0JtX4bLb4LLbkC1U4BCFxj91TmWHrclrzv3kS/L5z6SVIb9Tkz00HCBvc6yVTqsYGtGNvj0JqHWsbcQK9lC3kh+lskxdRrcsK1jsoOFrOwolmVgdXLWolQO0qmPN51Rn49ptvCaHdC8plmXiE6JIfU68Gu1Bj8NmmT5FJGPN2cbCaF0gaM9UAYDTq+q6h6thWsfPMgvN2ewWMKhrdNp1N1esWCLAUGPAp755UcTrMPBIek+njkKrOBiB6rwe0OA47rfQGOjGSWoFB2siW+q4ZLFcUSzT8CTYQTNb2pt9Fcsykjp1eNfSPJZUnHYBY0F11Wkuu4ARCziZ9WzcpddYMgt7h3qaVtgX6dFnIUto6XszFpN5XRKOGjEbzRryub3CpTI7101xoLUVkiiosokjPgexzsV4jnzbrJOGy70g7NG2x9H6ekZn0L/SbjK0RuBpj9ifjeeQ1tGoXkzkkSB0kmS0JpYpdpV5Mx/P6Xg05tLvcajOZNXikKaBTpue0apB2Ix+j7r7KvAcwm7rGFSFLjaZ3byXFGai3QVKz1C+ma6hJchSw68y24lU1nTUa1zLFKnX5AWAqT43HGL7rcyuIZ8lAu6dBtoboed4MoNO9zdWqPDU2vSyEXGK+tTIsmJoktBKqqDLNTULtbI3kkUaoDci4m1vEw+oeI1ZkOrArSdXrBCpy+yTbJoqW8KUJxzQAnMyU4bWABzNeryFcgXPLaV0/9ynFpJUZ7RpLfun+VzrmenSOXI2ltOlYQ4J2G08gioWSZ9TJFp/rBM6DTTkKC8N3kjEp85xHHLbqQ821tNNmXBFVog0kNWSzJewnOzOMRTLFIktedRCQKPD2GkXqNafBfTVayyVZV2zYs3CJvDYOeht+ZqhgER9FjtQDbDq6RiOZUpUr4udJiSSmsmolnShrMt9W6UoyDAXyxku73JiWf/9Zq9Qm51vhSz+ZrSziR2itgrAXkNLkIPE4+Q49ck0As9Rn3BAC9adbSyK1kU2q6N+Wy9RFAVPnE3q0uBkI5lCGc8tp3X/3F6QLpQ1NzBLWUAmYiVV6DqDpyIreG6JzvveCJ8KDSqaNUgbkStWOi4TXU0XLBNwAaqZK2qcx24H3Y61egrlStcl3rTKRciygqfmk7p81tMLSer0ODdSa/6nFto314qi6C5xYQXJDKCawdZKo3tLn6eHR2McZ6IZ3RvY6ilH12s6DRjS7FgHgDNr+lSjRNNFpChoBpsvVXBy1XjbPZYpUVvxqHavbJVEm0ZIotCyqoVkHV5ZVqh4FgEyncwAVFU0AVVb0ApVTTRAt9W9yZBlRfPDnS6UqVxUTq6kETPQGTAbzWIxoX8DCaPpxNEazxapHAM1ShUZTy/q41yZj+css7G2C+2dh7Q7VjZytosNQLmiYMUi976GmvIwm9ZOoQSzmMij2wr/BUo3kSdW0rpJR2WLFTy9SG/WFlB1uipQPxhoDzAlciXdg+56Si+YzViosTZz2GO3RDVPrlgxROpmIZGjxrmxkU7Ly2nQPm1GtljGQkK/NezUCtlBBkVR8NRCEhUDEo4a8exSispqJ7U9Z/RsHEoirRogqm2OaAbpovYEMrMgVctfrd+Y0DiDJbHO7nMTML2W0bzQKgp9mQpn4zlMrxqvG/nUQsJQR7be5EsVTK9pv5eyDJygNHO7Iit4dDaOQkm/1ffxswlqN1X1xLLtx26C4s3URlL5Es50qUf77FKqY01n0sgUyqqei6iKcUID+VJFl7UsnqUvW+nMWla37LUai4k8Tq7QuS4AwEq6oGlTli6Uqa3sAoBVHaUyaqTyZRTK9DlUGiE22WGKHTaHIwlZVvD42YQhTghFwbmqQbrWxbV0oWMn80I8T6UjUZYVPD6X6DrQWs9KqtBV8N5opteyiBow9zWjXFHwxNkEVUHJUkVWfQ8XEnSOfTWUKzLSheZzAqkZuEB1LaYFUqujV1Lq5olsofOKWIY26Le+NgmpfKkjByNQ3aDGKXE0LKfyeHpBn6zVdsgy8OhcnAqHo6IoOL7QuXzI2VgOK5RlLcly1djTuxlCpaLgkdk41SWT+VJFlTZjLFOyxGJaqsi6bLILJRlPLSQt0fBqNqbO6RhNF6kfA7Ks4Mn5hG6ZnM8spahxOJ6N5/CsAb0JAOD0SkZ353UvUBQFMxqPW1HQk+C1URhVgaOnzrOZNGvqaQUn+tOLKUOzxzKFMo4vpKhZF8sVGc90UYlRkav2NC3nW+P4YtIQZ9Qzi0kiG6JHM0WcMiEQGs+WcIKiAOxzS2mUVCZPVCoKnl2i51nXwmIy33KPkCmUiRznAKiy0SsV8nqbrKQKmq6hVvuR0RnMyUwB8WwRD8/EunKwHDsTxxrhpeJr6QKeOKtvlL4d5YqCo2fiRE/wFVnBo3OJrjeDj5+NUyMRUq7IeGQubphjvFCScWQ6iiQFAYaN5EsVHNUwHxw7E6fGodaIfKmCh2diyBb0MWpWUwU8OpdAhaJMlY3MrGUwF1WffUTzGKjOf3HEMvo9q5WKgodnYqpLTM1iZi2D4zrpMDfj2aUUVZUutazOTjaL8/Ecldnb+VJFN6mUjVjByZwrVpreV5p1VgHguaVUT45/KZmnwtFcLMs4eibedRO4tXQRT5ylowl4LclkIW6M/S7LwNHZGFHJSNliGY/NxXu6H6znzFqW+Hmj1qdB63EuJwvUjH21rKQKqoLxj87FibT7SPZBNIKk441linjibELTe2i1BWmDOZkJZymZx9Ezsa4zuCpyNXtzTmX2W6+JZYp4dC5uiiZRqSzj6JkYkU6YmoNND+1EWQaeOJvA6dUM0RuJ2jkbXSJXLMt4eCZGfPClnkyhjKMzMU0brNr1pNGhni6Uq85AnR0sq6kCjp6JEReNb4csKzi5ktbcwLI2BkguF2xEsSzj2JmYIY6wQknGQ9NRojbWNRSlmm3Uq0al06sZPDlPfolwqSLjsbMJLCc7n7NPr2Tw7FKK+HOtx8hmlWuZAtH2QDvypQoenYu3tJGfXkxStc7XOLGc6mnG1Xw8h6cXyXU0Z4tlPDQT1S2reymZxyNzcaJ7llSreJI4GzPW4VmpKMQkI5UqMh6Zbf1M94KnF5NE2gdAtULj0bl4x47wmm+BNhu4EYuJPB4/q85/UNv3kXZfaaus7TbIpxfLqTwemY13lDREoy1IG8zJTCiFcgWPzcXx+Jx+OmyKAjy9kMIxwhaWeLaIR2bNcTDXKJRkHJ2JE3Vd5mJZ3HdqTfcyyZPLaTw8EyMqElkjkS3hyHS0Z/pUNemMmQ6laHpFRVZwYjmFB06vdbS4F0oyjpyO4pnFFNEbqhqKouDMWhYPnl4zzPhKZEt44HQUyyk6svvj2SIeOB3F6Q4b9dTGwNOLSSrGQCxTxAOn13SXy6mnfC6jeZqgwFv53Aa71zIWC/E8js3GiNUsX0rmcd/JNV0CrmfWsnjgdJTY0tmNGOn4KVe0N5Qmgdoacd+ptbZBSFmuVnM8cTZBhXxGLUPRDHmXs7HcOWkqMuZDoHqvZ6NZPHAqqltFU41ouoj7Tq4RKSeXL1Xw8JlYzyoQa8lIZkooKUpVJk/v+9wJVUnFBFEOwNqzcN/Jta6D7/FsCfedXMPMWoao510ttSSUJzRK6ZXKMh6ajuHJeXLWgzwhx6EWs69bvlTBo7NxPDbbXVXqmbUs7j+9hihF/blowmb2ATDWoygK5hN5PLeUMiyKu5Yu4r5Ta9jW78FIwAlebUtOA0jmSzjWYRRKb2rZfpdOBCGJ5nWhzRTKeHoxZWhTwni2hAdOr2FLnwfjIZepY6DG2XgOzywmex5sUJSqplkqX8buIR8EAq5FDUVRsJQs4MRyuusAiKIAs9EslpJ5bI14MOSTiLjvG8mXKnhqIdmTZi+lsozHZhMYDhSxY8ADG4FNomql4HptNOeiOSwnC8SOAUVRcHo1c67iohffV22MGssWsXvIZ+rcnytW8MisefJNsUw1yHdgLACPgwzzMFss49mltC7O5XoyhTKOTEcxGnJiqs9NbOd5WVYMzWQGqk0FAy67od+hF4pSvR4nltOaK1wWE3mspgvY0ufBcEAicr6vnJOD0Xu8a2E5WcCxSgz7RwOmN07MFqt60Ubaw8WyjEdn4xgKSNge8cJuM39cJLIlPHZW36bXalCUqoRSMl8yxR4+sZwmSsKnVJbx6Fwcl02GTN8bxDJFPLuU0jUJpyIreG4pjfl4HjsGPAh7HLp9tlHkSxWciWYxG812ZSMuxPNYThUwFXZjNOg0bT0oVWRTk+w6Id/jealGRa4GWU6vZnTzG2ULVQnKQb+Erf0eOO1k2oI0QsYuggHAmAWkGZWKgmcWU5iNZbFjwIs+ExaWXLGCR87EUTG5JKqe2ib/0ESw5wtOuSLj9GoGs7FsTxYcWa4adPPxHHYMmjMGqseh4JmllOHlgO1YTOSRLpRxYDRg+iIjywrmEznMrGV1z6IolmUcn0/i1Eoak2E3hgNO041noOo8mIvlcGIl3fM5YT6ew1qmgF2DPvR7yTCyM4UyptcyWEzkdXe21sbA6ZUMJsIu04ONNTKFMp6cTxra5KoZa+ki7j+1ht1DPgz4pJ5/fzxbxKNzCdUNfIwiV6zgyHQU+0f8pm4486UKTq1ksJDIGRpsmIvmsBDPYyzkwkTYZbpTbSOJXMnw+XA1XcC2iMfQ7+iWckXGQiKP2Wi2q1Ld8rnGVydX0xgJODEadMJlJ2MrVCxXqxjMmP82EsuU8NB0DJeMB0wJvFXkarDxTDTTMwfMQjyPlVQBW/s9GA06wXHmrIlzsey5Mm5Tvh6AOfbwcjJPZEOudL6M4wtJ7B3xm/L9iWwJJ1fThiZeZAplHDsTR8AlYmu/B0E3eUHHdKGMmbUMlto0+NNCpaLgxHIap9cyGAs6MRp09Xy+o6GycCO9PuaKrOBsLIfptYxh1XaLiTyWknkM+Z3Y0u82NeHEKpBhWW1y8qUKnl1KdaUz2CnZQtXRG/bYsXPQ2zNju1Spam2SWJqbzpfx2NkELhkL9MzIXEzk8exSypTrkT3n7O/zOrBzwNtTB2upUs0gMbIkXgvpfBkPTkdxYNRvSmZXuSJjPp7HTDRjeAZLoVTt0H5qNYPxkAujQadpDpZcsYKnFhK6NnfTSqFUHYuDfgk7B72mXYtUvoTp1WrGudHkSxU8s5jC6dWqs3k06DIt4DAbzeK5ZXM31uWKgsfnEljxF3o6BpaTeTwxr580VrfUZIR2DfkwEnD29LuLZRnTaxnM9SjYClQ3MNOr1e+c6nNjLEhGdQ9grB5zjXS+jEK5QmQ2dypfwnw8j/lETldne6VSlds4s5ZF2GPHaNCFPo/dNMdiraEvKVqXwG+y/S+dCPbUEb+cyuPZxe6rtzqhfC4BZz6ew64hH/xOsWffLcsKnl7sTaNHNaTzZTxweg37RwMIGex0zBUreHLB2Ca33bCYyCPktmO4h+thKl/CyZVMT6sa4tkSHp6JIei2Y1vE09Px34xopoiZtYyhGe6VioLp1SzORLMY8EmYCLt7Vs1VJqCSWyu9qj7vhXO5HkWpJh0tJnMY8ler3JizuXOYk9lEZFnBGZ3T/jullsU1EXZjMuw23NHwzGKKKGN6I9F0EdNr1Q2nkeSKFRxf7I00QDtWUwXEMkVs6XdjPOQyfLOVL1Vw7Ix5peHNKJVlHDsTx75Rf8+yu0sVGbPRqoHT62YnpbKMk8tpTK9lMBZ0YSzk7KmzYTGRx/HFJDEVDYuJPOLZEvaO+HoaaEjmSzi9kjFFG7JYlvHcUhrTa1mMh1wY62HpYKki4/hC0pQgazMWE3kkcyXsG/XDKxm7yVpK5vHE2URPpEG0oCjA8fnqpr8XjuZaGeT0Wsa0hk/lSrV0eDaaw9aIG4M+yTSnY41eNeJaSxd76kBpRbkiYylVwHw81xPd7LV0EWvpIhwijyG/EyMBZ0+D7YUyeQ7mGrV+JZdOBA2/JmYm3GwklS/joekoxkIubOlzG74elisyHj+bIEoqAqjOiY/MxrBnyI9Bv3EVPs8spYixAZvx7FIKYY/dcPtYb4m0TohlijhyOoqIz4Gt/R64eyyfJcsKllMFzKxletajp/q91YqGhXgeIY8dEyGX4RVdNOphG+2zkmUFZ+NV53KvJYOq31/tT7CQyGEkUK1yY85m7XS1ah4+fBgcx+H973+/ToezecgUynjgdBQnltOmO5hryHK12+YDp9aQzBtn2C8l86Yunmo5tZJG2kAH6Nl4DvefWiPCwVyjps/14Omooc0uShUZRwltPghUr8Njc8Z32pZlBSdX0vifE6s4tWKecwWoRfIz+N8Tq+c04Y1d2BWl2tzoibMJ4jYXNX32XjTAqUn0PHgqanrzoVrA4X9OrGJmzfhmePlSBUdOR4lwKmwke042YtnAjPK1dIFIB3M9x+eThl4DAFhJFfDrk6s4sZw2dQ6skS9V8OTZJB44HTXUFmpHoVzp2QabhMY3uWIFxxeS+NWJVRyfT/a8MWOhJJ9fA4+eifXEwS/LCo6diRPpYK5RTQiIGWoTLCfzuP/UGlFrgaKcawx1yth5QJYVHJuNE+dgriHLwBNnEzhrUIb1arpgqga5WsoVBSeXjWsSLp9r8H3fqVVi9sjLyQLuP7WGZxZTPfFVVGXzsvjfk6t44myipw7mjUTTRRw7E8f9p4xtDEqy/dcMIw95OZXHr09Wx5wZDuZ6ZLlaZVmzT2kMCJhJx07mI0eO4O///u+xf/9+PY9nUxDNFHFkOkqsgy1brODh6RiWU/ovcoqi4NSKcYu0nihK1eluBCeW0zg+nyQmwLCRVL5aJmmUYf3UfJLoTRVwzrCeTxpWshnLVKsHTq9kiHKyyjIwc25jtWrQJltRFDy1kCSmLLQRtQY4RjmaFUU5t4FdI26DVcvofPB0FCmD5gCSs/dqVOeAhCHPQaki46mFJBUbjKcWkoZ0E5flqj7uo7O9b3ClhvS5bMbZqDk6ob2UD1rLFA0PKjUjWyzjqfkkfn1yFWdj+spidErNwfDQdNRQZ/Op1YzmBoZmkC1WcGIlbchnz0azeGwuQUSAqRH5UnVPZNQ4eHox1fOASic8s5g0ZE9g1vzaCYvJnCF6tLliBQ/NxDC92juZKLXUmoY/eDpqaOJVPFvEg6ejeHrBfOdiPel8GY/OxvHIbBzZIvlzdS8wor6rXJHx5HwCj80mTJFKaoUsA9OrGTw4bewzYDU6qn9Ip9N4wxvegH/4h3/Apz71Kb2PydIksiUcOxMjfmNZkRU8NpvAJeOcrqUisWxJk3O9oGKiqd/8qt0IO1SWPSwl89hR9uhaHnV6NYPpVfId7cWyjIdnYrhqS1jXMpGlZN70jE21lMoyTiyndW/4MRvN4pnFlKrXmvUM5EtVre6pfje29uvbFGpmLYuFuLogllHnD6ibB55dSsHlEHSXTnl0LkGcc3kjtWDTvpGA7g0RnzirPtBk5jogy8DjcwlctVXfeXBGQxmgmvMHjLsG5Uo1OLx7yKfqM9Xy6Jz67D2zxoAsV+W9CuUKtkW8qj5TL9YyvZsfSmUZqUIZPoPlYTZyejWDUyvptjaxWc9APFvCsTNxBN12XDwW0FVKrlCuYGZNvS1otj08F81hPOTSVZ95Pp5TbQuZSUWu6tQfmgzpqlMbzRQ1BdvNXgufmk/iyi1hVZ+phmJZ1pTBbfYzIMvAcqqgq4RUtlitbFYTXDPTFsgUyjhyOopDk0HdZcROr2ZwctmYIJZerKYKiGYK2DviR8Srn3SM1v4PZu+JAO3H3I6KrODB01Gik06Ac32bTq/hkrEgkc0xSaMjS+Hd7343brjhBvzO7/xOWydzoVBAofAbQzmZJFfYvxfMRDPEO5jrmV7L6upkTmjsmv3uO49pev0Hv/OYqtf9482HVH9mMldGv1cf50JNh5sWKpWqLpKeTkZaHMw1VtIFyLKi26KaL1VwQoMxZfYzML2awaBP0lWTTcumyqjzB9Rfg/l4Tlcn83IyT7yDuYYsn9MidNt1fQZiGsrzzX4GKrKC5WQB42GXpuNohZaNtdbzB/S/BnrLKUQzRUOvgd7nfyaa7Xnn+V5LWETTxZ46mZdTedWOBbOfgVimiGcWU9gzrF+gJZEtadoPmP0MANVEET2dzDTZw7WMTr+OSQdas6PNHgPpfBn5UkW3eVBrRa/Z5w9oP+Z2nNJQzWj2PFiRqwHnA2MBzcfRjFS+hFMGVUnojSwDTy+kEHTZdWsMrTVwScKeSO++XWeiWeIdzDVkGXhuOY3Lp0JmHwrxaH5C7rrrLhw9ehSHDx9W9frDhw/D7/ef/xkbG9N8kFbCTH2hTkjlS7qWUBpRcms0eh5zoSyj1IMOqXqi95ilrdSkUlFQ0PGeJfMlYmVSGqEoQFxjcKgVFVlBnrJ5QO8xG6OgNLaeXLGCnI7la6RKRbUio3OZpJ7XsxfkSxVd9eiSOs4pvUCWe7t2ZQrlnpcMR7O9dWqTpL+rhtV0QVddYj3til6hNpNSDRVZoa78XO85IE+QLIBa9CxlLxrc+8MI9J6XaVsLEzl9/QJxjcE2symWZV0ljkTB3ObCnSDy+jZCjffY9uiWTKFsiGyO1dAUjp6dncX/9//9f/jZz34GSVJXKvDhD38YH/zgB8//P5lMbmpH85BfokaTGACGA05du6vbNUb+vvi6S9q+plCunI/Uff7V+3Xv/Gu36TeZOu0CAi4RcYqcTMM6d5T2OGxUaBDWEHgOkqjfGIh4JQRcWdVjwOxnwO2w6ToGBJ5DyO1Qnclr9vkD0LU0DgAmwi7Mx3PUBBuGAvpmsgdcdgg8p/r8SRgDYY++pXFeyaZac1fN+QPGzwN6lkiOBJ04vaY+g8vsMeB22BDuYXmkGY34EtmSrlU77dg56EUyV1KVwWT2M8BxwP5RP2w6Za8BgE+j7ILZzwAAXaUiBJ5DxCsR0+RMDUM628NBt4glDY1VzR4DgsDpWu1A457QoeN+AAAm+tw4Pq+uytvseRCo2q96+gVGAk7MxXLUJB8M+CRdpRLYMwBM9bmJbXzaiLGQU7dMdiujadf48MMPY3l5GZdeeun531UqFfz3f/83/uZv/gaFQgGCsH4gOxwOOBz6ajnSzFjIhbVMkYomDx7Jhgkdy4MBaNZxUqsPdP71NkHze9qhd/no9gHvuU7d5DuY+r0O3bVoI14HVZuKfq9DV4MKAC4a9uOphaQqyQAznwG/S8SeIZ/u57+l341YtqjKwWT2HOC0CxgN6qe/BwCSKGD/aHUMkNTgpBERnwPbddaiFXgOk31u1aXyZo8Bv0tEn1vveVBS7WTu5Fz0vgYDPn2dK6LAY++wH0/Oq2v4ZeYYcNoF7B3Rfx5shRlO5oqsIJEr9UxrUBR4HJwI4tRKBguJXMtsNjOfgYBLxJZ+DwIufa+LT7LBI6kPups9D1aTJPS9Blv63YhnS8Q1empEwCViWEctXqA6r06vZlWfv9ljYCzo0jUI5XbYwHFQnclq9vkD1UQZPRnySUjmSjgbay8jZ7YtMOiXMBrU1y/A8xwOjPnx9GIKUcIdjcMBJ7YP6NujhuM4OERe9V6AhGdAq2O8HQGXHTsHvXhuOUVc48uNDPgkTIbdZh8GFWgaJddddx0ef/xxPPLII+d/Dh06hDe84Q145JFHLnAwMy5EFHgcHA/q3kRJb4JuOy6dCOoe/erz2HWPgBlJyGPXXYPR7xRxaDJE/HUYDjixf9Sve1ZTxCfpnhVoFILA6W5QANXN2qUTQewe9sFGYKmUwHPYOejFoYmgrhmsNXySiEt0bqJkBA6xOl8bocMa9jhw5Zaw7ptWvRBtPPaN+rF/NKBrNUeNqT43sedej8su4MBoQPd5cDTohFfS/9kyApddwERI340lUA3gXTEV1pzR2UsiPgcunwrp3uioFYqiIGZS+WivJTMkUcCeYR+et7XvXOVcT7++JQGXiEvGAzg0GULIAMc7x3HYPeQj6pxbsXvIp/ua7bLbcGjSGDtDT8IeOy4ZD+qevSYKPPaN+KFz9bkhBN12bO3X17lit/GGPFtGwfPQff/O89V5YN+oHwKB+wGget67h33YO+I3xG532W04OB7E/lF/T/seqMUr2XDZZAh7hn2GZLA6CTznVjjt+h/vWMiFy6fC8BBqFwsCh70jfuzTuaLJymi6k16vF3v37l33O7fbjXA4fMHvGc0ReA77R/2YjeZwciVNVMk0zwOTYTcmw25DSiY5jsNk2E1FN2kAhkWrPI7qgvXMYoq4RniCwGFbvwdjBjgVauwe8uGh6Rjx2SsXDfl0D7TUMxJwos9jx2w0i9lYTnXpuFHwPDAScGEibHyDq4DLjoMTQTxxNoEcgQ0fAi4Re0eMNXhFgceeYR+GAxJOrWaIyOIQBA5jQRfGQy5DnMv17B7yQuA5zBLa/MnnFLF/1G/IdeC4qsH60EyMaJ1+QeCw14BgYw2nXcChiSDmYjmcWk0TU+HjsgvYGvHonsGthnShbNp1MEsb0WmvOpu39LsxH89hPp43xT4QeA4DPgkjASf8LuMDC36niB0DXuJt4q0Rj2HOQEkUcGgyiGeXUliIk1XlxnHVgKhReyKgWimzd8SPJ84m2mbxqdHEru8jo7anTLtMx4CruhYaUc0xFnJRUyo/5DeuTH7AJ8HvFHFiOU1UtWfE58C2iEfXhp/Nv0tC2OPAfDyHM9Gs6XsDn1PERNiFiAEVrfVU9xnkV7jXMMLJDFR9I5dPhnA2nsPp1QyKBNjGHFdNupvqcxMZACEZMsMFmwCO4zAedqHf68DxxSQRzoWAS8TuIZ/hGQWjQSfm4znimyAO+iVDI+ySKODAWACLiTyeWUoR4WgIeezYM+QzfCKVRAGXjAdwZDpKjFNhI7uGvIj0wMHgsAnYFvFiIuzGbDSLM9Fsz69J1bHoxFjIZahTfSN+p4grpkJ4ejFFlFE92efG1n53z8rjAy47Do7bEc8WTXM2CwKH8VDVudwrrTGOq2bM+5w2HF9IElUmNxSQsHvQZ6g+rdthw8VjARydiREVbK7B88CB0YDuklEXfk/VHhoKSJhZy+BMNGvaWBBtPLb0uTEScPZMm3gjamVUjCCR660u80YkUcCWfg+m+tyIZoo4G89hNV0wfDz4nCKGAxIGfVLPs5TGQi4oCvDsEpmO5ql+N6b6jC0PFgUeFw37MeCTcJwQGSmvZMOeYV9PqhgiXgmXjgt4ZC7eci/w7juPafrcmi5rO/7x5kPNj83nwEXDxmSwAkCfx4GQx07EPrgVAs9hi86Z3BuRRAF7R/wYD7twYjlt6jUJuERsj3h7EmyrR+A5jIVcGA06sZIqYHot2/PmiH1eByZCrp5JR5FeybERt4EBB/7c/R/yS5iN5TCzljHNTzDol7Cl392TAIsV6fqq3XvvvTocxubFaRdwcDyIxUQezy6lTIna2AQO2yIejOjc5K8ZHMfhohE/jpyOErmxBqoL/c5BfXVIm1FzZj+7ZJ6jTbTx2DHgwZC/d+XrbocNByeCOHamtVFtBjsGvLrrjrVDFHhs6fdgPOTCXCyHmWjW8OtiE6qLeS8dixceA4+9I370eRx4ejFpatDBaRewZ8jXM8NyIzVncyJbwsnV3mwwapnLE2HzxsCQ3wmPw4bHzyaQLZibuSLwHHYMejHSIykPv7Nakv/IbJyogFut4qqXpcyiwGNbpDr3qtHp1ZPaxtbM56BGPGeeY0GWgWS+pLv2rlY4jkPY40DY40ChXMHZWA5zsZyuNjLPV517YyGXrg3tOmE87ALHgbiM5q0Rj+EO5nr6PA5ctSWMkysZ0ypcas5EvfWH2+F3ibh8MoTH5uLEJOFsORdgMHpvuHPAiwez5O4JAWBbxNOzJAyfJOLgeBBr6QJOLKd7Oh7cDhu2RTymy3pyHIeIT0LEJyGWKWJ6LWNoxjvHndPb7XPrrrvdDreDngxZp13oidShTeAx1efGaNCJmbUsZqPZns0P/V4HtkY8PR8HVoNdPUIY9Fd1ak+upDEXbS/+r+f3bh/o3cJZw+OwYfeQD0+cTfT0e9XA88D+MX9PN5p2W9XRNhxw4umFpKpu63oxHHBiW8RjeGl8I3ySiEsngjg6EyOiLAaodrw3UiqkHTaBx+S5hfVsPIeZtazu18Z2Lmt1zETn8kYG/RICLhFPL6awaoKEzFjIhW0RDxE60X5XdYMRzxZxciWjqkGkVmpOtV7IYqjBK1U32M+YWDLtdtiwb9Tfc8My4Kr2QDh2Jk7EPGgTOFwyFux5BlONmk7veNiFk8tpQyWlOA4YCToxGSanFDJucmPoWNZ8J3M9Dls1u3ky7MZyqoAz0e4y2+w2HqNBJ0aCzp7bvq0YC7ngEPmmsgm9lErgOGDPsK+niQc1bAKPnYNeDPqrWc1qGyPqQdhjx65Bn2Hl4O1w2gUcOielNx+/cC/4xddd0vYzCuXK+Qzmz796f0dj3HZOf1Tvxt/NqDk22wVZzJILCXnsujeAVkPY40DIbcdyqoCTy2lD94aSKGBrxI1Bn9TTJrdqCLrtCLrtSOZLmFnNYimpn40o8ByGA86eyAQ2w+sgty/FRnptH1eTDzwYC1WdzXMx4yrdQh47tvZ7TA86WwXmZCYIUeCxa9CHiFfCE2cThm42bQKHPcPV7zKLQb+EdKGE6VWy9Dh3D/kMLw9uRshtxxVbwnh2KaWq03A3iDYeFw37emZENsNzLqOZBEfz7mFfzzIY22ETeEyEq83RTiyndRsPg34JOwa8RDgWNyKJAi4eC2AulsWzS73pMkzKc9CIqvPRjqVkHk8v6iepE/bYsbsHsjhasZ0rmfZJIp5dSvUsixUwviS4HV5JxKHJqqPZTB1Ch8jjkvEgERkcHocNB8YCWE0XDCmh72U5vFqyxbLp62BVl5m87uk8z2HQL2HQL2Epmcczi9qq/zgOmAi7MNVHRjCxERGvhIPjfMPKhl5JJdSqGMImr4l+ZzXweHIljZk1Y/cJPG9OBVsjBL66P/M5bRfYQe2coRtx2ATN7/FINhwYDfTc0T4WciGaKbYMKpohF2K38dgz5DPN8cpxVZ34fo8D02sZTK9ldLWNaZgXa/gkEftG/RjPuXQJQJFiCzvtAmwCR1Q1WzPMaljtsAnYMVCtMnxqIYmEjsF40cZj16DXlB4cVoY8LwPjnKMxhJDHmEwSv0vElVvCpjqYa2ztN78kp57JPrcpmRv1COc6De8f9cNmUKfhoNuOK6ZCxDjWao5mMx2fu4Z6VyKvBVHgsXvIh0sngnB1YfQ7RB4Xjwewd8SYRmZ6Mhp04bLJUFfnq4agWyTqOWjGgE/ClVtCiPi6O07hXHDxkvGg6UZ1K8ZCLlwyHjRs/tvIVL8b+wzqmq4Fl92GQ5NB07pru+wCLpsMEeFgrqdWQj+iUyYZz1dlAC6bDBHlYAbMz2IGqrrMSi8jPB0w4JNw1dYwRkPqxoTfJeLyqRC2RbymP+ftCLjsODQZMmWOttt4XDoZNN3BXIPnOWwf8OLAWACiQXZLbd4jwcFcz2jQhUvHQ3CIvbPXBv0SLpsMmZbJvWfYvCzyRnAcDG8ArRae57Cl34PLp8K6VRl5JBsuo2RerKcWgNoW8YDv4PEQz1UPk2QL+yjJnjXbZnI7bDg0Eez43m8k4nPgyi0h5mA2ALJ2EozzOGwCLh4N4NhsXNdSaZ+zWoZNymLCcRwuGvbhoZlYT0viGhHxObDV4KYOWoj4JDhEAUfPxFDRMbrZ53Vg/4jftMY+zfA4qtkTD5+J9rzp01S/m7gNxkaCbjsunQziyOkY8ipKBusRbTwOTZi3ceiEamZnCMfOxAzRo+v3OrCPwOegGQ6bgP2jATw2F8dyUrt8AMdVm7j1UmO3G0JuOy4ZC1bnPwN12Lb0u7Gl32PY52vFYRPOSwj1UofR5aj2hyBlw7UR27lgmyQKOLmc7vhzak4DEoLsjUj0uMFRI8oVBZlihbhgw0Zq1X88x+FMi0xXt8NGlN2rBo/Dhksngnh45jfrvdFSCXYbj0sngkQ2oer3OnBQDOChGX3tYZddwKWTQaJkU+rxu0RcNhnC0ZmY4TJ6k30ubIv0phdNM8RzPToenmm8D+iVXEiNLf0e4mwmj8OGS8eDeHQu3pVGccAl4uKxQM8bneoFz3OY7HPDaRfw+Jx66U2B53BwPGC6s3QjPslGfPNLAPA5zV8fOK567yVR6Ep2ddAvYe+IX8cjY9RD58yySeDPlay5dBKEl0QBB8bMz9baiE3gcfFYwNTsSq9kw0XDfuJ0qPxOERePBnSJ1gFVo4Jkx5rfJWL3kK+n39nvdWBLDxvbdIPDVn2GtYyHqnPRT5WDuYbdxuPgRFD38qwBn0T0c9CKPUO+jtaEbRHyNkvt8LtEQw3A4YCTKAdzDVGojvteZTS77GQ7mOuZ6nNjsov5+qJhch3MABlOZoCc46iRLZab/gz7JdhtPAqlygV6rKVKBdsibhTKlabvJxWnvRpwqj2XDlFo/1PnUKtJJbT7AaqB6IOEOphreCV97WG7rSoNRKqDuYYkVh3hRq4H2yIe0x3MNfxOEdubHIuRz8BGQh47JsNkJp/wPFdNGuiw4tlPuYO5nmqzPvX3afcQWRJZNcyS6dSCtOH5MptBv4SpDpMD/S4Re3rsb9hskGtNMABUN5sTYTeOzye7/qxRwpqc1COJAvaN+HH0TKynOpxAVZ96/2iAOOd7jaDbjgGfpEszrB2D5JdEDfmdWEoWetL8zSZUpUlICy60wiuJ8Eqiaj0qp10gqomTVkSBx75RP+4/taZLhrskCtg95KXSwQxUg3J9HgfOFLRpVJLsWGtFv9eBAZ+ka6MXoPrs7xggz8FcQzwXfH3wdNRQjV5B4HBgLECFg7nGlj435mJZzfqFfpeIQT+5z0G5IiNTIMPpmciWiJKP2vPxn2p+j1o91unP3KD5s3uF0y5g/5gfD00bV+FVC0STnrkOVO3hiFfCYqL79WAi7KIm+O6wCYatB2MhV1eBOyNQo89sJLVeHSTvDXiew44BL+5Pr2l+7/aIxxIO5hr9Xkl1f6cIQRKd9aiVyzCq+SXQXvOdhCzmjYwGnTi9ktH8viG/RO0+kBbIGy2MC+j3OHBch8/pVs/TaIJuO7b0e7oqhe2Ei4bJz/IcC7m6djIHXCIVkVIA2DHgQTRTMFw2Y2u/h3h94kY4RQEJqHMy0+Q8aobLbsNUnz5zw45B+o1rWweGUa/0jY1gqt+tu5N5POQifhz0Ivi6d9hPdPZiI3ieQ7/XoXlNHCA80JLKl3seZG9GMk9WJvNmxieJ2DXow1M6JJs0YnvES1UgeiTg7NrJzHEwvf+KViRRwIHRAB6aieo2TwTdIrZHyAy27h7yIZFbM6UR6p4hH7FJWfV4HDb4nCKSGipPXJQnnjRCrU3M8yDWsSiJAuw2vu14N6r5JdC6ASZAZra1wyZAtPGaG6PTEFSlHXaFKUCv+ZAnOCJbYzLswkqqoGnB7IahgERU48FmuO3dP6ouHT6jV7jsNoTdDkOzGASewxDBWW3NUBRFU3OoZK4EWVaINazUMuSXunYyizYe/YQ0NOqGtQ50+tfSRaKzOFvBc9Vx38r41pq54aQk+BJ02zESdGIumtP9swf9dKx/AC6QNSiW5QsyetqNgXypcsHnkLQukuTYzRTKqMgKMZVPT33yxU3/Vq7IeOBUNcOzkR7rgbHOy8pJYTjgxEIih1hG3zHilWwYU9k8kRT0CJwLPEdlgoHfJWI44MTZWPfrAccBOwd9xNqGdhuPnYNeTXq7ekDTughoTyAwqoGmmajdK8oysJYuENPYdCM+p9iTKt5OIbE5Yb5U0exgBoB0oWy5YAtpkGNdM5pS0CmKWyjJxGc1chyH3UNePHhav0h9M0Qbjx0DZGiQtUMPG1AvHbteMeCTDHUy93kcxGcyNiKaKWpq/FeuKFhOFah1MNY7hXgeyBUuPHe1Dka/U0Su7tqR5GBSSyJbUi2VUs+ZaJbaMaC1VN4KZfL1DPklzKxm2spDaHG0CzyH4QA942EzjIFkjgypDABQFCCVLxGzCWs1V59aSYPjuAtKfWt6rPOJPEaCTqJL39WwfcCLB09Fdf3MHQNe6q9LJxBSMNARW/rdWEjkuq70G/RLxGfzDfgknPXketYQTRA4bCdYRqsRWh1snTjkSKYiK5iNqZePm17LkOtklmxtncy9bn5Zj979cfSgUz/BcqqA0SCZmutWgbzRwriAaAdZaw0/J1uE30VeFGojXqmqm7gQzxumPeQQBUyF3RApcTLmNDgVm2F0Z2q98RscMTX6841AURQ810E278mVNPq9DmKy0rRglHMJIMvBpAZZVnB8sbOS6WSuhLPxHFE6qwx1HPjEf2p+D41O1s1OiqBMZqAq30GKk7kZiVwJ02ut9RiTuRJOr2aIbPKpBZ8kIuASNVUytcLtsCFIWTNYAMjo0KyxUlGQL1WIT7xphMMm6FLpN0yJXMj2iAcPpPUNrjRjMuymQiajRqkiI61Rxz9brFA79htxYjmNQkm94zyWKWE+nsMwgbawmkzhdrrJF7ze1ry5pRZcdoE4n4ksK5hZ09afpkY0XUQiW6LCL0YrzMlMAStpfbI5V1IFTBHW3KEZU31uLMTzhmkPff2tl2MkSN4C04xUvnujOq3DZ/QSp12AwHOoyMbknLgd9BlYs9FcR/cxV6xgei2DrZRvsjc7M9FsV8/xs0sphN126jYXT33yxXh4JoZkC+eK1syN520P63qMDGOpl0tYSRbwxNkLS6jVjIErtoaIrGAoVWTiAsEkyXc0olyR8cTZhKqMztOrGYTcduKd5u0YCjh1czLTKBcGVAMLepDMlahbC2tEfN05mUUbjwAlzpVa4pEezR5bIdp4jFG0LwSqSWidVP2upq2RxRnLFDEb1e5kfGYphRCBtjDJlQVeAvWYz8Zzmip7N3JiJY1LJ4I6HhGjHnJHMwNA1YiOZ/XJZE7mStREL112YzMshvwSVVmdemhUF8syNfe/ht3GI2fQxpsWPb6aXES5IuPpxWTDUjc12fzPLaYQcovnHS8kOloaUe9cenQ23rBsUq2DcbzPRa2jPV+qYHpVewfleioVBSdX0rho2K/TUfUGl90GoUE5fDPUZG6IAj3zYO0ZuO/kGvIt5kO1z4FN4PBb2/uoKpOvn6+S+Uzb+9tsDKTzFfR5yHOukRgE1iO4bSSnVjOq7QNFAZ6aT+LKLWFiNWjVENbRLg5TqlOtl5M5kSsh4iNvLlBDt5V4PslG1fw/HnYZ7mQeDTqJl9Db2FNgNpptWPHbbk8wF8shtGEuoWVPUENRFDy9mOrovZWKghPLaewdIcsWlsTOmtj1Ag9hUhmyrLStYmpHLMOymY2ErBHDWEe2WMZqqthQg7QeLXIRZ2M5DAUkKhaTQb9kmPbQACWGZc2gWE4VmkqHaLn/S8n8+YYWNIyBcuXC5k6N6EQyhbSyn2ZsBi3SVtSPU4fY3nnYysHosAlUjPuNZItlPLeURrZFWaTaZ2B6JYOI1wG3w0bVtShW9DW6S2UZIFOW7wJq92nApz6bq9Vz0Od1wO2g06hWFAWrmc4z+FbSBUwSWNFFokM3UygT2zQ2UyhrzmDLFiuYjWUxESbv/qtFEgVIotBV9hZQ1Z4lOWuuEeft4WQelSb69Frt4VpFI01rIVBtXCsIXNPr0A4SsxJbobdUzEY4DlRIiWndDwDW2xPU5oH5eB7RJpXeauaBmdUM+rx2+M49C6TMAR6HDbFybzTItUDKelG7/0uJQtvqxkb/3sizSylcNOIDQM4YsArsahLMZl9Mgi7REO0hgefgIywi14zNrkd7y1ePaH6P2mvwzKd+V/NnM+iGPFeJOjZ7oAHQv1ETjY2f9DLyPRRKBdUolOWOHSsAub0JUgXypCkUpap/S6JDai3dWZn4SqpAtZMZqGaUdetk9jroymQFmD1cD8dxcIoC0pXOglMuO31rgJ5SMRsJexxUVXluZqxuD3scNsR06sWlJ6Q4mTe7b4wmyBgxDEYDXHZbV5H6ZngpKxNjGANPyRiolcrff2qtaVWD2mx+0cbjt7b3GXOgPaDbO0bJLWc0QO9bR+NQcOnkHHZSnK1R6jKjvVSWoSgKcTYAiXIZAJAukOlk1trsqtv3kYTHIWC1syrx87gJcRgwOsdlFzqeN2h0Mke8DjzNoaPgUjsGKalurZePyxUruP/kWsPXqdkTXDoVPJ/FyyAHEp9NngckkY7qXwY5MCuDYB766HVYTBTw7GKy5esKZRkf/rcnAACHX7EXjhZas1v6PRgNkV8SVMMh8MhW9M08okWLlwH88x9dgbiKiG4nkim0UCvf6fM4sCy3LxNvlc0fdNupLgfq9r7SOi4e+uh1ODoda+kg0bIO7Bj0YdBPiVbEOZyigFSHWVsNP49AQ74ddp0kfvT6HDNwdplt5rQLxDmYFUVBpkim8zOdLwNkyVYCqCYLdIKvSy1bEtAjSNTtc8Qwn27uIY1Zu6LAI+Cy657lyXH06JPX2++STYBkF9o63ZvtCUIuB5X74Yc+eh0A4OmFFJaTjeXD1NrDW/u9GAmRFWAg0cnsFFlyHkM79HobNgGHPvVfmt9Tm1TbQUtJQLUJg75OZhtPz6Jai1ofX0hiMd5sMVXvYD00FSQyK6kZkgoN3o2okUyhkbDHgeVk51qkgL5Ng8yg20i6g9JIvNa1wGrrAFDNvNNLt1bguZZOeFLRqymRjUCNXbXYBB4uu9Cx7AWJmVvZYgUyeX1+AAApQjN/+zwOPMenNF+3fg9dwbVGSDrMXTQG2Rjr6dRRzPOgcv0DgD6P/k5mv1OkpkdLPTzPwWW3IdPBHO0QeSodzID17WES52aSjqnmF4mmi3h0Nt70dWp9IyMhJ3YMeHU/TgZzMjMIRzagLsqIzzSKWtR6JOBCLNNei6yVg9Vu4xHxSlRFIxUD7xVN4wAAhnwSZtYyyLZpBNoMh8hjLOTS+ah6S7eaYKRoijG0E3CJunWXD7hEquZBvaH91IcCTpxcTnf4XrKylgB05CToFaQem9MuYKrPo2kc+JwiRoP0VPI1Q48gOo1Oxppz4cRyGrNrjZs+akm62D3sw6CfvPlALZ06mSUbedUcagm49E+UMOIze0XE58DpFe1z9AAl8iCbEYnAikuSKl9qfhFXyIb5RB7JXOe+EZ4Hdg74iHKiWwm24yaYmkF1Zi3b0pBWa1SN97mwtd+j/4EaSLf6i40oGvCZRhP22MF1qUVW/Qy6DMuSznrc9VRkupzMPM9h54AXx87EO3r/9ogXAsUZjEC14VGnCDxHlKGkhdpasJws4MmziYavUbMOSHYBl00GdcuI7SUhHbPw9fysXqJX0I2yqe8ChgMSTq+mNWexOu0CkdUcJOsEF0oyShWZyEy/iZALK6mCqk2mwHPYM+yjzgZqhB5yNzRmMdacC2NBl6qqrlZJFxwHjAZdVF6HGp1WdtFc6eeTbOB56Fr54adYQmfIL+H0Skbz+2h2MtfrUmcKZTw0Hb1gPLSzhx2igMumgkSuazzPwW7jUSyT46sgNSi5LeLB0ZlYx+8fCbiYg9lAmJOZYGoG1ZZ+D+YTOVWLaiujalu/l6qHqVSRUSjpP8l2mglqJlUtMlFVNnMz+r30lYl220G9FblihTp94rDHgeGAE/PxnKb3RXwOqjN2ajhFoeMNhotALVa11MbpZJ8N6UK5bUZvo3WA44BDEyFqNUlddltXMgn1hCktmddr00HS5qUTHDYBQ34nzsa0zYPjIReRc0CGcJskW6jA7yJvk8nzHPaP+vHA6ShKbcb07iGfZSpZ9AgW09L4uBEBl9i1EybgslPtYAY6DxSQ6jBSA8dx8DhEVYEltXSq704CLrsNQbe2vaFHslHtWK/ft7nsNuwbDeDpheadUDfawxwHXDoRhN9JXsC5hoM0JzOhUoMhtx2DfqmjKkeHyGNLv9uAo2LUIHPUMNZht/Ho93TnIAq67VQ5mAHopr+5kXypQtTkrZaQuzvHSJCykrBcsWJotjHJ2WOt2DHggahhkyDwHHYOWkNviuO4jkvJaJv/mrFz0Kvp/tcYD7ngd9G7sQD0KWsVbTy1zqacTkE3vT7HTLRK/wgCh+EAmVIJpDb9q5Em+PgkUcCeIV/L1wwFJEsEWWvoUZBEs5OZ47iuq1FIrGjQithhfxnqK9p0XL9FG09lE8R6tGYl05zF3IjRoAshDY0bx0Mu4iVSSAuAkdwselvEg06mwi39HiIz2a0Eu7qUoGUCbQSNBlU0012Ts9afrW/jiF7g7sJJ5hB56ibT1bRx97/6+fSNAaDa+GoqrD76OhZytdQlpA2+ww0S7RurGqLAY0uftui7TeAwqfE9JKJHxhGtDmYASOiUvaVnFphZeBw2uDXcy36Pg8g5QFEUZAl24gJAlvCAbL/XgYivcRBetPGWa+pT1iH4Tptc2Ea0PPuN6EZ6i3Yoji8AqFalkfhZZqE1KzlIebJBI7ZH1EmBijaeCluYtP16J4ktvUISBQz6tCUQOEQeQxYLtpAIuaOGsY5uHIwA4HLQt5Aup4xzMq4Y+NlG0alzDQAECq1KrZIQWolni8Rv7puhpXnVMIGNrrpB7nBzTPumuh6tGZkRr0Sc0doJepTs0VoqrCiKbsHRWLbY8XNEElo216SWB+dLsq76okaQ0UGixmi2NOk3MhZ0WmLuq0ePXiU09iapx9ZlwKjb95NApUON/rKBvU56gZ5VabT26ahHayY2aVmyeuCVRARUOM8HfA4q1gPS7hHJmcwAmgaZmxF2O7ryqTDUQfaoYZynW4OQNqMikS0Zqp28ks4b0lTQSLq5HrlShSqnwnIqj1S+jEKpou6n/JtrUyire4+iAKc6aJhBAqLAQxDULZAkdirulHJF7liTN22Q/I4ZCDwHm8r7D5Crp6YVnfreUUksW9KtR0G5ohheKdILtJRIkhpnJV0qAyA/kxmoJmI0mhNpkwlTgx5SXxkK7mkrun1uaAictKNT2aN6e5lG9AwUk+bM6wSt4yBvQK8jElBTsUnLfoi0IBhpx7MRrdJBdhvZ52MVNm+9EGXEs92Vt8ayRWL1CBsxF88a+vmyDCzE8xgPa9N1NJPllHZh+xqKUs0Mp0GXsFSR8dxSGgDw7juPaX5/raNwO/7x5kNYTOQxHHB2re/XawrlChSVHrd8mb4Gh83oRuIkW6wgXShTLZdQI1+qQNbgcc1ZYEMNQJemf3p8hhnMxfRdE2djOUQoLxfU4igjtbkeDc9mLUhNeuZPI51hmrWHm5HMde8gTuZLGAY9e4J6KrKC1VR3VR1LyTxGKNoTNaLTwHkqX4aiKEQ2QVWDnpmoNGS1tmM5qS1gvJzKU7fnUYOaylQagroAWeOS46oyjSSj9b6Sag9aDbJHDQNA1aHQ7QZzMZGnRhqgUK5gKdm5Q1Uts7Gsaked2Swl810HGk4sp6nIZj6+kOzpxvuJswnqMjvmYjnVJdazUWNlR3rJ9Fp3mefTq3Rmrm9kei2jqcR+MZGnPnMN0EenPZkrIU9Z47tUvqR5I9mOWKaIGIW9CWqkC2XEMurXxIVEDmUCq5doCHooSjVYSTLJfLlhQ+cVC2Tsb0SPeXCN0p4UAHAmmu16Do+mi1TK5tXT6T0sVxRdAhVmoae2PukZmu3IFMo4E9Vm185Fc0jm6e/LUE+t+rUdtPhCSOofQdKxNEJRFM17u5VUQZeKIEZr6E/psjiyrODJ+WTXmn2KAjxxNomD4wHiI1JaHGjdkCtWsJwqEN9pN1Mo4+nFVNefky9V8NRCEhcN+4jNYDi1kl7nTPni6y5R9b5CuXI+g/nzr96vqdFdsSzjsbkEDo4HiV9MgWrTyjNr6oNOc7Esgm4RES/Z47wds9Fs15IXS8k8RoNO4jtLt+JsPIezMe2Bg8fmErhkPEBtJ/VEroREl4G2GnOxHLapbBRDAieW08Z87koah1xBYteDZsiygqcXkpreU64oeHYpjT3DPoOOqjNo2PACVWc4qRUxsqzgxHJjG2kulsWQX+q6URwpZItlXaSfcsUKErkSsVrlzVhLF3B6VZ/58PhCEm5HkNhx3YpyRcZqF83Rl1J5+CltAKennU56dUYr8qUKHp2Ld7RffvycPUjj2N9IIlvC8QV1e2RFAR6dJd8W1iKHZzQ2jVIUvURRFDyzlOooWP/E2eq+3wqSOaTCrizBKIqCJ+YTumUbJXMlPDqXIDqbtVyRMRs1ViqjnhkNzjozyBUrOHomhlKDDJ1OWEzk8cxS9w5rI5iLZS/QSHaIgrqfOqeyw6buPfUksiU8Nhcn+tkAqhusR2ZjmprYKUrVoFzuQXWAUaQLZTzXxImghVqwjTY99hqnVtI4Pp/sSJs4UyjjyHSU2uh9MydSJ8zqkAnXK5ZTecOyDhPZEhYS9M0LxxeTHVX2zMdzmgJ0vYAGuQyA3ONUFAVPLSSbZrWXKwqOnYlT87y3Q8+GyEY3V9abeLaIx+YSuiWhFMsyHp6JETu2W7GUKqDSRa+d+XiOeHu3GXq632j1MeeKFTw8E+u4V0/t/bTagzWWknk8fCaqaY+cKZTx4OkoEjlys7kFggL/pCZfKYqCpxdTmOuwWjedL+PhmRh1lcw0wZzMhFKuyHh0LmFIieyx2RixTpaFRL6nTQqTuRLiWTLLBlP5Eh6aierW7KnGXDSHJ+fJCjYsJvJ4WmUk2ijW0kU8tZAkUkKlVg70yGxnWQuKUs1kpUUypZ5iWcZjHZ53I/KlCh4/S9b4b0e+VMGxM7GuG1UWSjKOnI5iNkqPVBBQ3RBrkUZoR0VWdKkOMZqKrJzXpzeKE8tpYu2BjSiKguMLSSzEO3eMP7uUIsbRrCgK8TIUNUh00hbLMh6ZjWOxTaAkX6rgoemYbpUQZiHLCua7GPsbWUzmiZSQacRyKo9jZ+KaAuxqKJRkPDQTpU4+oNs5rFxRsEBp4oGelTecri7r3rCaLuDB6WjXwZFCScaR6WhP5Cn1pliW8eR8Ao93GHSqBpiiOLlC5p6IpIpzkrKqaxTKFRybjXdU1VlPplDGkdMxYv1AtEPOKGacJ1+q4KGZGFYN0guLZUo4cjpKZJnmrM7NjdRwpoeZ02pZSxfw0ExMdwdzjYV4Ho/MxYnYYCyn8nhyPmH2YQCoOrvVll31inypms1+YjndUQZrPdOrGTw0EyPy2W+ELCt4bC6uu25pNF2kwsmoKArmYlncd2pNt2zWiqzgmcUUHp6JUaHTnCtWDKm+WE0VcJbwTL7TqxnDs+yKZRknV4x1ZOtBRVbw2Fyi600FUHU065kZ3ymFstwTaTA9IE07Op4t4oHT6ufFql0dxcxahqoAWz3LqUJD3elOqVQUKioZZtYyeGw2obuDuUahJOPh6VhXzbV7yWq6oMvaTeuzQJ7LqzfUZIEeORPXrbq1UlHw+FwCTy8miXS2bkRRFJyN5/Drk6tdBZsBQJaB0ysZ3H9qDWuEafeTpBVOWiZzNFPEA6eiiOq0J8qXqln9p1fpnA9JhjmZCSOVL1VLmnXQXGtFtljBkWmyojeJbKnj0p9uWE0XiMrkWkzk8chsvKtSODVE00U8NBMzNUMpkS3hibOJrp2nejIfzxHjdFlM5HH/qTVdsziTuRIeOBXtuploL3h6MdV1w8tmzMdzPZXm0UqmUMbRMzE8vZAyZC6IZ0t44PQaTq9miN1cVEvhE4bNhc8upYgtlc6XKpob+nTK2ViO6IBDqSLj2JmYro26plezeMLkigYSs4ObQcqxVrP7q0EyrUF4RQGeW0rj6Bk6JRLOxvVfr0gOtNUqF4yu5gDOBbFmE0TbBDX0SozJFipYo7j5qx4QpErQklqyyfSqMeNzLprDkWkyk89qJPMlPDQTw/H5pK4Vz9liBcfOxPHYHDmySiQ5dkVCNJlrQZajMzFdg61A1TY4uVy1DUgZA1ZA08j58pe/jP3798Pn88Hn8+Gqq67Cj3/8Y6OObdNhdPbqRkplGUfPxIjRal0yKYtAlkFMl+kza9meOl1rmkRmGBbdNK0wmtMrGVNLyEoVGY/NxfHE2YQh8jEVWcHTCykcO0OuHtVsNGu4ZuSzSyndNO/1QlEUnF7N4IHT+gYXGiHLVcPqgdNRIkvJ52L6ymRspFKpOrFJZHot07O5UVGqWdMkki9VcGQ6akiwaTFRregxKkOyHfke2Xp6kNd5U9cJiXOBsZm1bFc2UixTwv2n1qhwKNbIFSuGzIXpfBkpAqUiKrKCR3WqXNDCM4spPEdo3xKg2vhRrww+oLrG0gYtjmG9WEsX8MBpY9bAelL5Mh44HSXGJ1CjVJFxfCGJB08Za6cuJwu47+QaThEgoSEyuYx1ZItlPDRjXJClRs02oKWqhXQ0jeLR0VF85jOfwUMPPYSHHnoIL3zhC/Gyl70MTz75pFHHt2lI5Ep4bM64jK1myDLw+NkEogQ4WoxeQEn97hqLiTyeNcG4zRUr1fKrHmdzP7uU0j0aqSfHF8xpEFdzquitx96ItXQRR06TJ5+RL1VwYtn47CVFqd5nsw3KGqWKjGOzcZxcTvc0+JIplPHwmShRjaDKld7IOMQyJWKCjDUqcu/L2JeSeeLm43KlqrlrZIVTNF08F9jt/RxAU8ZMqSyb5owHqpUnD5+J6jYWarJBZmezq2XVwHLuVYMai3bDU/NJwyQD2zGzliU26Ka3XbiWLhAhm6cFjuN0czTzhHusl1PVyla95DHaUalUZakWEmTYgolzlZe9CjZVZAWnVjKmV/kKPAdCEoghmuxkrlb4x5DsUaPGcqVa1UJDtS/paBrCL33pS/F7v/d72LFjB3bs2IFPf/rT8Hg8uP/++406vk1BoVzBYyZm01SbgsVNLR9UFAXpgnmOXrMzOdKFMo4vJE37/myxgifne/f98WyxJ07UbihXlJ5vNLLFcrVkrYeyMVWndsz0Z6Cekyvpns2H2WKFiGyeWnBBzywlLchydWPfC+e+Gs7Gcz1rAjuzRpZDYS1T6HnAWVGAFcJ0CZ+cTxouHQZUK5nMcCoVCHPqt8OsqpcTy2k8NZ80JPC2mMjj4TPkNsOukTBwg02SbB5QraowuxnZyeU0ccFHoLo26ImiAFHC7r8aeJ3kBAhSJbiAtXTBNDnBp+aTpmc0n43n8PBM1BRnbzJXwgOno6ZWOpKSzWzmcaTyJTw8E+tZkKWepxdSVFU7kUjHI6dSqeCuu+5CJpPBVVddpecxbTqWEoWeSWQ0o1xRMG9i5FJRYKpsgpkZOkA1S8fsY1hNFXoWaKBFB06vZmtqObWSMWUuKJVlnFwhx9HW68wqEpxrp1czpmjSb2R6NYM0Afq8vawuSeRKRGUzmjUOcgRVNOSKlZ46ec5Esz3PZiZVqqgZZmS6p/IlTBscAEhkS8RvJo0cKyQFOxRFIeZemNGIvB25ov73Km/AZxqNXjqxoo0MR14jTq32TjJrI4oCnDCxN02+VMEzi8YEFtVSKldlOsxqBmdnTmacXs30LNmkESd6mPBkRTSPnMcffxwejwcOhwN//Md/jH/7t3/Dnj17mr6+UCggmUyu+2Gsh5QoMgmSGZsVUnRhYz0ai7Q03cmVeud0kWXFVB2oVZ0713dKoVzpedTa7KZnsqxgscfyCK0gQTYj18PsFUUB8gQ5/Mom7axKJhrzG+m1XVSuKEj2IGu6HhLmWy2Y4YzsVWM6khvgAYCRidYkBdgyxQoxz0U8WzTNwdSMkgFrgxGfaTR6lfCT4sjbSL5UMb1PRrZQMc02no/niOjXky1WTEtCsRMSAHGYdBwVWTFUJkrVMVQUrBGQhEQrmkfOzp078cgjj+D+++/HO9/5Ttxyyy146qmnmr7+8OHD8Pv953/Gxsa6OmAr4pVsZh8CAMAniaZ9N89zkETBtO93Ocy9B14Tr309vRqLbpOvt1o8jt7dF57nTH0G3Q4bEUaNXeB73mjC7TBv7gGq997vImMOAICgy272IcBt790cIfAcJJu5Y6AeVw/PvZ5eXvN2eHq8RvA84Lb3dgyQ4kxTixnH26u5iIQ5rxVOA+1jqcfjvhUuUYBAQKMpoGqXc4Rp9hqxTpm59+oUPY6Z48xzoLXDYeNNvy+ijTd03mlF2O0w5Xs3IvAcAk5z1gYHITapw6QxIPBcT/fgjeA4wOckZ29GG5pnV7vdjm3btuHQoUM4fPgwDhw4gL/6q79q+voPf/jDSCQS539mZ2e7OmArMuSXTBd45zhg0C+Zegx+Ex9kn8mO/iGTrz0AeCRbz5zd/V4yDIh29Po4J8Lunn5fPVN95n13PRzHoc/T2+seIsCgnQq7TV8HAMDvEtHnMd/hEurhMQRcom4aj3oQMCngQFKgw+8U4eph8KffI8HW46y2IuE6wBsx43gjXofhwW+B5zARdhn6Hd1i5DUw2/6th+c5DPrMt4cBMuzyjRgxDkhJdNKCS4fAiFMUiAsi1OA4DmMhp6nHMBJwmmYX+V0iBgiYByb73KYl3zgJCf5JJgZizF6XB3yS6cEemul65CiKgkKheSq5w+GAz+db98NYj8tuw95hv6nHsGvIZ6qTFwAG/OY5esx2sAfddmyLeEz7fruNx4HRQM++z+Owmb54tMPlEDAe6u0x9nsd2D/m76mzkeOAPcM+05+Berb2eyD0yLh12Xt/nxsRdNtxcDxoajZ5xOfAwfEgERuvIZ/UEycjx8HUubcRLrsNfT0OcAVcouk2wEYuHgv0pKrB7bBh15DX8O+pR1EUU7UGO8GM4+U4DpdOBA17HiRRwKHJIDHVZM0wcn0mwZlTz44Br2mBthrDASdGg+bbBRvR2/HtdthMraDrFI8OjnE9PsNIJsJujJu0TxoOOLG139zEk70jPmwx6RgEnsPeEb+pyTdmZZHXI9r4ngff6xnwSdg97IMZW5IBn4Q9Q8xn2Q2aRs6tt96KX/3qV5iensbjjz+Oj3zkI7j33nvxhje8wajj2zRETHyQtg94MBIwN2IKAP0ehykRo5DHblp5cj2TfeYYFKKNx4GxQM+jplv7PcSWodQMjF45OuuJeCUcHA/CIRq/sIs2HhePBTBMwPNfj9MuYMeg8U4fnq862M24z40IuOy4fCrU8w02zwNbIx7sM2nMN4LnOeweNH5NHA+5iHQwTfW5e2oPbOkny9EOVJ3tRjuanXYBl4wHet7cpkyQDq5aSiZlXtsEHgdG/ZjU+ZkIuu24bIp8BzNQdYYb4WgPuETizl/gORwYC5iWYRvxObC7x0EntYTcdl2Dr2Zny3aKHmOWtHHfiB0DXkz12NE6HnZh95DX9GQDjuOwpd+DS8Z7uz/1OUVcNhUyPfGGBCezHhUD3TIScFb3Jj2UURoPu7B3xEdUhSONaLKql5aW8KY3vQk7d+7EddddhwceeAA/+clPcP311xt1fJuKkYATB8eDPet2axOqhpyZJfr1cByHrZHeHwtJWWw7BrzYNeTtmXPB7bDh8smQKRlsPM/hknHzNhLNEM4dl5nZHQGXHVduCRvq/B30S7hqSxjhHktTqGUk4DTcuL5o2I8AYVqckijg0okg9gz7erIWhDzVsVZ1apJlUAXdduwYMG6zH/aYW0HSCr9T7NnaPBpyIuQm6zmoEXDZcdlkyJDNTtAt4rLJkCnBbdqymAGY2mWd4zhsi3hwaDLUdU8HQeCwa8iLSyeCxOheqmFbxKO7bUjq/CcKPA5N9t7RUwu2krYW1uA4Dtsj+qyJLoeAYT+dTma3Xeg6+Eha5U4ztvZ7cHDC+MSTWsLRjgHzHcz1hD0OXLUljK0RYyscHSKPi0Z8uGwy2POeEI3opVxYM0jp0xHxVferQYPtVIfI45Jx8p4BWtE0er7yla8YdRyMcwTddlwxFcLjZxOGdpb1SDbsH/UTkcFbz6BPwmw0h2SuN111hwIScaVio0EX3HYbHj+bMLTRTsTnwJ4hn6mlMKLA4+BEEI/Mxk3vpAxUAy8XjwWIcDyKAo89wz4M+Bw4vpBCvlTR5XPtNh67hryIeMkqkW3E1n4PKrKCM2tZ3T9797CPuDLhGhzHYTjgRJ/HgRPLaczHc7p/h0PksT3iNT1box1jIRdypYruY8Aj2bCXYGcCAGzpcyOWLRo6N7odNt2cFkbhdthwaLJqF8UyRV0+czjgxK5Br2mZKhWFPiczCdnXfqeIK6ZCOLWawfRqRvP7g247Lhr2Uamz6HHYMBxw4mxMn/VgwCcRYes0o1ZR5neKeG45BdnARHqbwOGiYT8V/UL6vQ70eR1YTTWXqlTDzgHz5r9u4TgOfqeItXRn6wHHkaVF3o6Q244rpsJ4ejGJ5WR3973h53vs2DNE7rzI8xym+twY8ks4sZzGYiKv42cD4yE3JsMuU/fDGxEFHg6RR6FkXu8GEpztNSRRwMHxAOZiOZxYTuse9B70S9g56O15VZuVYVeSQCRRwKXjQcM0a0eCznOZQeRMHjU4jsOeYV9PNGkdIm9ollw3BN12XLElZEjUjueBnYNe7B8NELGgigKPg+NBRHzmGvdOu4DLJkPEbbrCHgeu3BLCSLD7jJNBv4Qrt4SpcDDX2DHg1X0u3DPsI0IiqB12WzXQcNlkSDf9QI6rloJdtSVMvIO5xvaIB0MB/Y7VZZJEglZ4nsP+Ub9hGUw1uRxSJFJaYbfxODge6FpSiuOAXUPec3aGeedtZlZwp8iEOMZ5vprVfKmG7D6Oq0rDHRwPEOtIUcO2iEeX+cAmcNgxSGYW80bGQi5cOhEyrGQ+4BJx5ZYwFQ7mGrsGvV2Vjw8FJGKr2NTSTfWN3ykSsf/Rgt3GY/9oABeN+HSTkBL4alXHwfEgFfOiJArYO+I/p6PfvU3c53Xgyi1hbIt4iBwPZku6kKZbXm2I6cIVW/STFbTbeOwf82PviJ/4PQFtsKtJKDzPYfuAFwfGArrp0PA8sHfEj91D5GiQNsLjsGFLn/HG765BH9ETisNWjdpN6th4wCHyuHQihDECGp3VI/Ac9o34TWty4XOKODQZ7LoM1yhsAo/dQz5cMt6ZPqkgVJ1Ve0f8pjaW65TtA15M9ukzNi4a8RGnQd0Ov6uavddtubTLIeCyqRB2DHiJNKibwXEc9gz5dAlEOcRq9QQtZfIOm1C1A3Res3ke2D/iJ6aDuRo4jsOOgaqDuJPnwCZwODgeJKKhl0KIw1YLpB1y0F2V+mkXjBdtVemFiTB5kkBaEQUeO3XoV7Bz0EvNHAhUnYKXT4V0dwSPh13UONjqkUSh4yQZkhNstNBNEg5pySRaGPI7ceWWcNdONq9kwxVbQkSsh1qp9S/ZOejtKCmtJg1y8ViAyIS7GmbLSZr9/c1w2W24dCLY9Z6oFmSgKfGKJujZZW5S+r0OHJro3gCy23hcOm6+kL1aJsIuQ7V3xkIuKrIWajqEF410n93tlWy4zCT9ZTXUHAg7B3unSQ1UnzFatBnDHgcunwpp0uqqZWhHCJWGUMu2iLfr4MjuYR+GKNUg5DgOk31uTdl79Qz6JVw+GSJOHkgtHMed09Du/PiFc3I4tDkUfJKIi0b07XK9e8hnuL6dUQwHnNg36te0Joq2anCBlHPW6rAtlCrtf8q/kVQqlFW8/tyPWkjJZK5HFKrZ+EF343lBPJcBT6rd0wkRr9SVLR/22KlcB0WBx/5Rvy4B51rT3x0US0aMBJwdzWekJ9ioxeuwdZzRGyZkHeiUqnRAEKMdNm4c9Es4RGhFs1pqWa2HNPZsCJxL2qDBB2DmuuWyC0TPE7U90YEOm0NP9rlxYJTOxCtaoHd22UR4JRGXTQXx8HQM2aJ2XVa7jcdlk8aVmhlB1aHgw/2n1nRvkOORbNhOaLOTZgz5nZBsAh6ZjXdUZht026kpix4LueAQeTxxNmGoBh9QlY7ZNUiXwL/LXg0WPDwTQzpfbvnamoPZKovojgEPShW5Iz22rREPFRIZ7Qi4qtp8D81EkS2oWw+29LuxpZ+uOa8RAs9h/2gAD5xe60inbt+I3/Tyw06JeCVsH6jguaV015812eem0slUT8QrYe8I8Nhsou1rBZ7DpRNkNPPplHffeUzT6z/4ncdUv/Yfbz6k9XCIQuA5XDwWxP2n1i5wml88GqD2mW/FjgEvVtMFzfaxwHPYPaRvwKqXVBMvvJBEAU8vpDr6DJ4HLhkjJ+DUDXuGfLjv1KpqW3nAJ1HhXFMDx3EIue2aNYoFnrNE0InnOewa9MEl2vDskvpnYarfja0WsAdr+CQRl02FcHQmhlSbPdGgX8JFwz5q9nxmjlMfJc9In8eBQ5MhPDQdVb0e7hzsPmmJ0R5reB42AbWSWa3RGoHncGAsQJWDuYYkCtgzrK8xXJMMoTFzIei2n2tUpe19XsmGA6N+KhzMNSJeCftGAoZqc4+GnNg9RI+xUY8o8Ng30vqe8jywz2JRWo7jsGvQq7nrcp/XgUmTpFiMwH5OS1fNejDolyzhYK5ht/HYO+zX/L7xsAt9lGtQToTdXVcjhT12bO3XT4LJTCJeSZXE0q4hL3EOZgqXHZB8yALPXeA46fc54NdJt5E07DYe2zpIlpjqc1NXydGI0aALWzs4f46r7gGs4GAGqokE4yF18znPV3XJrUSwA9kLv0ukcg/YjPGwS3XfkuGA01IO5hqiUJW/EFvsdzySjbo9nyjwpsk40jRHehw2XKRyXzASdDIHc48gy+pmtMTtsGHXoA9PnG2fuVNjW8RDdcQ24pUwHChiPq5PN+3tEfI2m1ro9zqwpd+Dk8vqstkEgTsXnKDP0djvdWDviF9VpppWhgISdg3Sm80DVOeDyT5307EwGnRRK43QCts5B/sDp6IqX89RlbmgFpfdhm0RT8tsLptAd9ZaM4JuO0aCTpyNqVsXJFHANotsrHYP+ZDMlTqqanKI/LlApXWehW39Hiwl800z20OESgNwGl22X3zdJW1fUyhXzmcwf/7V+3WXgCJ93Az4HOt6mAwTeN/1ZCTgxGw0h0yhdfZejapD0jqb66k+N5K5ElZS6jNZp/rcltPfnAy7MBfLts3iGwu6LBFgqKeT5n+dOKZJZ1vEg0SuhHi21PQ1VScr/VrczZBEAdsiHhyfTzb8O+n9qJoRdIuq53hdv5eyAG2/14GhgISFePNKV7uNx04L6NHTAn2ep03OgM+hOovPIfKWKA/fMeDRxTAKuu0YDdJ/PSZCLtWZ6VNhurNWIl6po2yVVvhdInZT7mCu0arssZ/yrM1WeCVRdUbnVJ+baF2xbuj3OlpmRPZ5HFQa1WqY6nOrrnSY7HNZJnNJ4Kva1J34+/YMWUOLsx6e51o28hwl1AbSWqXjEIX2P3VOZYdNxevP/aiF9KHDcdw6e4fGCj4tcBynqSphss9tmXmwxvYBj+pnySHymAhbo4qjHpvAt23exvOwZPaeyy5orvANUJx41QyO4zDVpkn8lj76G5+2o5nWtt3Gw0doE7t2hEwIikiiQKVed7vA8qBfstwaSDKEm4yMjXAcpzorZ9BnjYfJJvDY1WX0leeB3UN0ae82g+c5VdkoVjEqp/rcTZv6aEXgOeyjVC6lER6HramzyUOpQaUWNeWBAs9R2TlbLQ6b0DJbkdTO0HogiQL6Pe0DDQLPWS6j0e8SMaIxYDrolxC2aOCplQwKqedMY/BHMFK/SifqrysFh9s1/V6HKme6aOMxRHnz30a47DbVMkijQReVz50a2iXQ9HskqhNOmsFx2vSVOY4erVmthD2OpvdYEDjLaHG3QhIbBx3cDoHa/X/Qbe+5vFYnFQIk0K4xOM2V/TSyCUww66FW7sFKTqY+j6OrBXI85KYyKteMsKf9AhBw2S1jUO8c9OmyyE5aRI+whiwrUJpUSMrN/mARvJLYdnMdclvnGWhGuUXHn06ahNJEn7f9PBhy2y0TVKpnqs+temzzPCypw1hDEhubsnYbT+zzb6PQA2oj9FrWk6uTkckXDe4cTADVxJP2zuMhC2dwqZU/oK38WwuSKLR0sAz4rOtg1OI0djtsxK4JeuBuUunsddiodbJqQZaVhrIxxTK9trAo8D13jqrxMZBIuzG+CR4BoqDPymWobuRlJ722USOdNDkBqhkcVmr6BVSzN9oZSrSWBjXC47BhoMssHJugLgOcJgrl5pvofBONUivRzvBqF9WmnVJFbqnD2IluL02oMbytOgYcNkF1NnPEK1laOkBosnMg2ZkgaizxJgHSpVbypQpKdWtiKt97HUszUGMbDVhMh7getYk3ZjXQ6hWtqjZozUxUg5aKLStXdwHN/QNWagDeimypsc2bK5UhU5x00cuKLI6jd74oVVrve9vp1jP0ZXPMOlZD5TNitUfJ7bCp1mGtZzzkorLxXTvabfjsgrWcCt3qiw/5nUQ7HTohmW/e5CPV4m9Wod2m0UrVC42IZYst/57IWXsMOEWhbWaClZ2rrbSI67FCL4JWVJpUbZCcyc9xHETKNv6kO8Y3zoft5ker4HbYWlZo2QQOPqd110JB5bikIRO/G5oFXd0OmyX3QDW8DvWBZC2vpZHmlY29PQ6ziKYbz/myTLc93NfDzOKASyQ+oNyMdg0SzWiguJmhcxRtcpptqC54nQVXFa0awzxv3Q12O4cphdW4LQm4xK425VYsF0y2MJqSOesvpo4248HRpIzeKiRadBIHqqXj+SaZHVaA47iWmtQA2v6dZjwOW9tAi0PkETChcUwvaZad0kpKhgTazV+koaVJoBnEMuvnQ5qdClppVbHhc4qWLpVXe2ZWvgZA84xuq2fvSqJ6WaRmchJWoZlMnhX9AY1oFViMUhx09Epiz6Qe1fQ6IZV0GydyijmZewpdFi4DQPtyAK2vowm/U9RU8hbxStRG5Bjr4Tiu4y67As/BJ1kvg6FVJnOrv1mFdl3FRatFWjYQV+FEibdxRNNO2zFAePZlt7TTzqO17FELxSayQbJMth1Em5NZIvx447n1ToRSWd40mUutJCOsJJ3WCLXuM8XifSrsNr7hemjlah6gujdQe45Wr25rtt6RvA7qhaIoLZ3McYqdzAB61rhRTa8TUmnnZN4s9gApWHu2tShqI5KEJ/F0zIDPgVMr6iaKiAWzV2u0S8qwYtaGz2nDUlL7+zySzZJNb3ItGhvlLK7HC7R3IrdzQNKOGoMpU7S2UdXOiWz1IGM7XerN0E273MImqsgKSE3A1eL8KaioSCiUKw3/3Q61GcokO6sURWm45mWKZctr8QKAq0WG5mY4f0YVSRSQ2aBF7iR1AtQRt92GdBsNdp5v3iTWKjTzJdOsR6yWQrl1j5JMge49Ub/Xgdlo1tDvcDtsVAdi2u17CyUZsqxY0h9AIvSOpE2M6qi95VSZq4TdDpxaybR9Hceh48xXGmg3RVpxCu10s+SmeNFsRavshIqsWH4xbafFaGUNxmZdtDfSLMvTKtjaBRosPAaA9k2vrK5BCbTOUGxWPkwCLlH9uvTuO49p+uwPfucx1a/9x5sPtX0NxwESwdIzpYrSUI/U6vNfjVaOxM3gZFSDFRMvNtKowdtmaPqmJgAmiYLlx0Cz9W4T+JhRbJOtXSzLUBSF2jEQcIqwCZyhzetoT8xTk4RZlhXYLb4vIAXrrzwWRFT5cFityVkNr2RTpTds9WYX7c7Nilmcrg4zqTp9H+m0spU4rn22O+20ymQWBI5aY1INau+vVdeBGq0ylW0WHwNAeweSZLfuGlijVSCNJ/j+k5wZvBFJFIgOWDa7zSTffz1ppddpZV16QJ0sltrmgLRjb7AeMifzuddsgmBLM3vP4spxANrP9bRfA57n0Ocx1gncK0kOo1Bjo1h9T0QS1kzvszhqDQarGhY8z8FttyHVpjTK6s0u2jY9E6xnUHWaSUXTZl4LkiggXWn8HNhtvOUdbK2kEhpttqwEx3GQRKFteRjJ2Yd60Gqds+oaWA/PcxBtPEoNMjY5zvrPAdA60EDy+bfLQq/ni6+7pO1rCuXK+Qzmz796v67ORdIlF0ShcfMv2nSvO0UU+KZOFKvPg2ru8WYZBw0zmQmeA/VCjV68VfcB9TRbC9kYqNrCtO+JIj4HFhN5Qz7baReo713Ubp63CRxzMvcQsq1GRkPUGvtaNjC04VLhZKZZV0gN7TrNWjGDrZVDpRVWNbB8kthUh452Y0ENNoGvZig16G23GTaVAZfY1skccFt7HLTSWOxVN26zEXmu0SMAm2D9QBPQPEPNIfJEZ99KYnX+qqgof1Wrm3z+9TZB83taQYM96ZVsyG7QqfdYPNmgHlHgkcP69UDYBJtqnq8GXPMtdMutvh+o0cjJaHXJKIBlMtdoVrW5GRzsNoGHR2quze130W8Lh90OCDynujeXFmjPYgaq+94FNHfC+zZBjxKSsP4u3IKIAt92wbAJnKWNKoeK5g1WdzK5WzR6sQmcZUsk2zX6aoRVM3lC7uaa463+ZiWaPedWHf/19LcpnXOIvOWDDUyLtHn532ZwLgDV+b3RHE969i3HcfASfow1fBQ4awMbenA4HcKmWAdqNHIwqpGSsAKt7GGAjiCJHmyc8zmuvbSeFVBTsbUZ7IFmTubNMv5byUkYLTXRCwSeQ9hjzN4uYgEnc7DNvjdo4T5dJGL9lceitOsYb/VojZrNsxU1ietptYG2skEhdJCZZ9VMnrDH3lSL0gpRaTU0cyKoCUTRTtjjaDnPDfmlHh6NObQKplpVi51xIY0yVmlwjNJiq3kpCFb1bdh8hy3gVNBCI7vYqrbPRtqNT6vL59XYaA9slvvP81xbm0/Pyg5SafYcWHlPWM9Ak8Z1As8hbJHEm4hXf7vebuPb+pVowOOwtUzC3GgjMIzF+rtwi9JuMghYYLJohZpmLlZv+OJu4VwhPYOrGzopf7bqUBAFvmHk1ivZNo1UQPNMZusvbwLPtTQ4B/3OHh6NOUhicy3SzVAiCgDNCiebdZq3Io0y9mlwjNJQaSDa2lfPkYDfKa5zsvW5N5eTuZFttFmcjO0CSpvFybzxfgubJJMdUCEhuAkSDzwOW8P9Dg1roR54JRGuBlUN/V6HZTL6wx677k0M+70Oy0irNUuwctqFTfMckII1nrhNSDuDaTPp0G1WhBaReytn8HWiRSVrk3CmikbR+c2UwdVMCqVVMzAr0Sxzw+UQNkX2Csc1lwbaDOWxAFBuoulbNkC3j1QalcvTsA7SkD1ES9ICx3HrJDN8TuvPf/U0SqzYJD5muFqsdTy/edaCjWNgs9x/oLVkBs9btzdLPQJ/oT1kEzjLSgY2opHsgxWkMmqIAn+BNFS3WKnytZlUJJPK6D2bZ9axGO30lltluVoBNRlamyGLq1nk3so6hM0cKq0oVqzrZW6UybxZ9JgBpkcbdNkbXgMrGdXtaJahtFmy+UtN5rdKRYG8SRzNLvFCm4eGvhROu0C8tE+AooZJ9U77zZLFy2jtRJZsgmWy9Nqx0cm8Wc4baC2R5thEY8C5oen7ZpAJqSfUoILFanuidv1YtCAIHEIWcsA2C4oHLd4EnUTItmwZTWlnPFvduFaTodWJM5I2mkmCWLVCriIrLTuINyNX1P4eWnA1MCBpyODTi2axJOs//VV4nmvoTLWyZM5GbE0mvM0QaCiUKy2rO3IdzJc0slGLlOfpsYNIz7AJOMk+vno2S8ZqIxolVmyWdbDVs96JxBqtKJsguaYZrTKZN4N8Wo2N+0Ja1kG92LgGWDGTW8/M47Dbbqk50ibwEBvc781sG5iFtZ46xqahWeaW1tfQz+bysKXz5Y7el8qXdD4ScrAJ/AVG5GYoC6zRbFPViawKrTQyoDfTGGi0iRJ4blNkLrULoGUtHGCrh+YMPpIzhQWBo0p2wmrOBC00Wgs3yzq4mZ2r9Wy8CpvpurR69q1c3bmRC8eAKYdhGhsDzlbRYq5HEgXddOatJJVRQ2ywJ7DiOCAddsUpJVts7WyzcuYmABTK7R3IRRWvoZ18qfE5Nvs97axlCh2+r6jzkZBDRVYu2EhaWR5kI83Gupo5wioUyhfO941+Z1UabaIUq0baNpBqE3hLFzoLzNHGxvFeqSgoUzIPklzKG3TZqXLYbyYd8o2UGlTvbYaKPqC1zbtZqjmAC4MKmyXIALTOViZdkkhPsoX14z3Xxl9gNTZWuxbLFUsGW/p0cg6HLdggt9DA9tsMPiHS2DyzrsVot7FMWjhzEwAKKpyoVncytZKOyFjUqFhNd+YsTufLHcls0ECjDZTVg0z1NBvrmU3iXGs2D2wW5yIAVBpsIGQZm0KPuK0tkLO2LVCj4TxIyZzvstvgJFTiiDatRqvbfa1oVL23OSr6gFSh+TxXqXQms0YjG+932cpdrzfQKpN5szSCLpblC8Z6uaK0TUyzEskNNpEsAykL2sN9OjiH/S7RctU/+VIFlQbB1c2yJyQJa42sTcRSMt/m751lfNKCGoORlg1mp8SyxaZlUDELZu5mCuWuHCYLidbPDK2spC581lfT1n7+a5QrclPDweqBthpLyTwa7SOXkoVN4WQFgEKTuX4zZPQn2syJ7f5uFaIN1rxYhp5zJzWbOeQh87iaEc/+ZhxslvkPqMoiNMrUqsjKpnA0r7VJQGhkJ1mRjWNAlkFNRUe3tHIkW82R1oyVJrb/Zhn/ADAfz13wu7OxC39HOz6nraH2sBbChNod3bDcxP+1vImeAVLYHLOuxciXKg03VPUkcyXLZrKVKrKqEjCrZy60ciRmixXLRe0aGQ5aWIjnLFky1SjgtJQsWPJcN5LIlZoGWrKFiuUlIxRFwWw02/BvpbKMxTbBSKuQb5K9aPU1oNQiyFKjWJYtX9mgKEpDm2i1Q3klMwgT6MyVRAEeihqIyrKCtTq7KJ6lJ8jQLYWy3HQttHp2tywrbZ1om8XB0CiwavX7X0MUmsv6NNJotSILTfZJ8/HNYQvGs0UkGsz7i4m85exBjuO6dhKHPdaTylhINH4GYpmi5W1h0mBOZgo5E82qEvKfWcsYfzAmoHahKJRky2ayyLLSNlvdSpm7sqxgvsvzyRbbB2doYzVdaNgMMV+qWL6aAWicvajl77SzmMy3lEs4uZK2vCZjsSyj1GQTnbG4QanWiRbPWfs5iGaKDSW0YpkiNRvLkMsO0qSPSc2ubsZiMr9Og3iuy8A0TbSSkKPlGeiU1XShrd5mLFPcFJIBjbSpN4uTmeO4C5q+1dgMchmJXKmpTZAplNcF4KyILCt4ejHV8G8VWcGJ5XSPj8h4ulmjRRsPn07NA0lhJVVouSc6vWpNvxipWH/WtRjFsqy67MOKkTtAW1M7q5ZLr2YKTR0rNZaSectksy6n2p+vGqwWzZ9usWCeXs1Y5v43o51Gd7sSWpopV+S2RnOhJFveqGrlOLBaNcdG1EphWD2js1lAVVHaS4uRgk3gEXCJZh/GOvq89DiZFUXBmQ1VHWupguXngBr5FlU7VtwH1DOrck80Z8GS+Y00utdWv//1NHMmN3M+W4kza42r2mrMNKl6swpnotmGSTc1FhN5yznau3Eyhyhr6quGdvudhUSOZTP3EOZkpozZWFZ1ZpqiADNtFh0a0eI4tmoEf1FFVm+uWLGMHmez8hetrKTzltEnXEsXWjqPMoWypUtE86X2kjBrmaJlHe2nVzOqGqCeiWYsncHVShbKqpJRNdTqjrdrDkgzpYrcslSepsAiSV3eeZ6upn8rTap6pi1a0beRVo5ELYkZtJEtllX3IJmP5yxf2dNoz2PVfVAjbE1kMayeyZwrVrCcar3WRdNFpCzaqyRTKOPUavtM5eMLKUtplEuiAJejs6bBtPVbaMdyKt+2b5OiQNU4YeiDpln38OHDuOyyy+D1ehGJRPDyl78czzzzjFHHxtiALCuaI/Hz8ZylJlTgwsYWer2WFiqyorqxmxUkE0oVWTfZA1m2TlO8aRUBJCtnsarJziyVZUtKJuRLlQuy9pohy7BkmWCNbIv7my1Y797X0yprZ93rCiXLBltW04WWjqNMoUzNxrrPS46T2e+0w0aRY6ZZFp9VK/o20srWtXJvAi1BpHJFve1MI7KsNKz4s/L930izOUuwuCbz2bg6GU2rZvM/s5Rq2AB7I/lSxXL7ok6zmYOEVU51y/Squj3RZrEJSECTBfnLX/4S7373u3H//ffjP//zP1Eul/GiF70ImYy1HlhSiWaLmiUDqg5Ja5WMa8lEsGLWQjxbVLWYAsAaRY2PmtGquVsnxDJ0OBxakStWVGXvpPNl1dmOtKHWcUSLg0kLanX5aywnC5bNZm5V+lYoVyyry1+uyKqDqLJs3Ww2NZI4tMjmeBw2SGJnWUl6009RQ6B0odw06Kgo1upP0YxWFX71OtVWQ6vTuF2DQJopNdkYWPn+b6RRJjPHNc9wtgpqE4qWUwXL2UTxbBFRDWv8XCxnqcBLJxVHDpGHy24dPeZUvtQ2i7mGolQTMBnGo8nJ/JOf/ARvfvObcdFFF+HAgQP46le/ijNnzuDhhx826vgYdXSazWkFR2M9sgbvipbX0kJSQ+lztlChPpNdbbae6s+zQAm9lo3VqkU3VWozlDMWzGbtxGmiRmKHRlo5VxTFurr8Ws/Lqk5mNZJQNMlGkaKDTMpxqKHdGmfl7NUarRIqyhZzKtUoV2TN9iFNc4FWmo0Bq0jEqaGRLIbAc5bTnq0nWyyr1pktlWWkLLAHquesRodhRVawlLDOmuDvICM5SJEUlhq0Bg+tHGwkia7CGIlEAgAQCoWavqZQKKBQ+M3NTCaT3XzlpqbT9H5WFmAttEqAFCsyVWWvGymrTdtW+3kWMLhbSQR081qaUHsf9R4/ZlMoVzpqgmlFZzvQvlrFgnFGANqrdKyWvVRDTUYSTQ72Po8Dc1Fzs2xcdoGqLKdMmyqNzdD8r9U8Z1WpnE6eaytlMG6k2W225t1vjNigwZ+d4v2PGrQ2MiuUKoDTOlIJnfScSBWsE2xy2Kq6zFrk4fwWuv+A9n1ulvnFekLHM6+iKPjgBz+I3/qt38LevXubvu7w4cPw+/3nf8bGxjr9yk1Pp3ai1exLXkNE2oo6XMqmMhkBQN97aIWMBi0Z+lZ7/jc7nd5PK1Z1bGa0zmMWmPYuQFEUVc8DTWM/6LKDN9knEqZIKgNoPydSdPsNwYrPfjdY1enejM10+xtlMos2azuZtY5mq8WbO1nfLZZ7goBTW2ZywGJ6zFqHQNV2tNiDQCAdz7zvec978Nhjj+HOO+9s+boPf/jDSCQS539mZ2c7/cpNj8vemVYfTRkpamgUqW6GFXW4JJu2ceDQ+HrScHfYObcZnT5HJOHW8Ew7LXC+jbCr3DhYLYtFEgUIGubAGm6HtdaBGu26xmtZL2hC63m1u040wnGcqvWNFJ1jNQg8Z3opax9lXefbrelWXQPraZVQYTM7amEQnTzXkk2wRKJBI5qNASsm2zSjkV1oNRtwI06Nz4HW15OO16HdYeqVrGUPa5HMEAQOHovtB1wa/QQuu82y6wBJdDTzvve978UPfvAD3HPPPRgdHW35WofDAZ/Pt+6H0RnBTjuIuq0VsdLiNHVYbDEFtC2OLodAvYGpNULbDrM38Hqg5ZkOdzhvkI7a4JkVnasRr/ZMw4iPruxEtUhiczPGJnBUSwW1wi7wqud2jqPL0aoFNeuhj7INZZ+JmcQkOLm1Emqzxll1DazH0SLoasUAE1Adqx6Nz3Yn+qW00MyZatX734iGTmaLZzK77ILqcxQE7c8M6Qz4ta2XHGc9e1iL/IXfKVrOwap1jd8MNgEJaJp5FUXBe97zHnzve9/DL37xC0xNTRl1XIwGhN12OFpsqBshCBwiXsmgIzIHLVFYyYLGRdBlV53JSFOH+GY47YKuGwMrGBdeSYRPhVHhsgsdB6dIR225l9W0xwBgMuzW9PqQxw6fZL3rAKBlRobVsjXq4Tj1m0Wnnf5gYzP6VARc1LyGJMImZhIHXCJ4ysZKwGVvmck0HHD28GjMoVUQqVUgjnYGfNr2N1pfTxM8zzWUhmgVgLAajc7V6ufPcRwG/erGdcTrsJwtEPFKmpKvhvxOy1V4u+3qKxytuBcIuOyagicjQevbBCSgaeZ997vfjW9+85v41re+Ba/Xi8XFRSwuLiKXM7dJyWaB4zhMhLQ5F8ZDLsstKGrLIhwib8ksNp7nMKAycKDW8CCdsaBLl8+J+ByWyeib7Gt/TSb7tM0XNBF02dvObR7JZpn7XY/bYVNtJHEcsD3iMfiIzMPbwmBu9TcroDaAYsVAS412m2aXQ6BuU+Wy20yTdTIzi7obJpoE3sIeuyWrWTbSShLEag6Veob8kmoNc6ddsHwGW6MkHCvf/400qnS1YkXrRkaDTlXa62MhffZSpLFr0Kfq/EUbj60R6+2LOI5TXbHlc1pzPtiicr876Jc21ZxoJpo8cF/+8peRSCRwzTXXYGho6PzPt7/9baOOj7GB0aBTtdNEtPGYsOCCIgq8qoxuK2exjYbaO5gCLtEyTpYBn0OXTfeUhZyuEa/UMsPb5RAwZJEgQyMEnmub8deJrAQtbIt4VM2DE2G3ZeaBRlRL/xr/zWrNTTbSTiZA6+toRBT4ltmJegUoe03IpGxmWsfKkE9qaBtv6bNugK2eVn0atOpV0oQkChj0qQu4jodclisT30gjO3kzaJLXsNsulJGyYkXrRlx2W9ss/bCFK9r8LhET4fZr/a5BL/V9ipqh1s636hiI+KS2Nj/PV/dOjN6gWS6j0c+b3/xmgw6PsRGe51Q/IFv63JbM5AXUTZJq5ARoxSeJbSdTK0WsOU79uG/GoF+ynLNta3/za7Kt32P5DdVgG6PaKpn8jRAFHjsHvS1f47ILqqP7tCLwXNO53soZvIC6bH6OA8Ju6wZbgOZBV4FXX0ZMGmY4eyVRoDbrl+e5C5wMAbfd0hq89Ugi37BcmuMAj8Wztqb63G2zGB0ivylkUxo9v1ZOuGmEfUPw3YrVbI1ol0SzpcV+wQps6fO0DKhFfA5Ly+WokQwRbbyln4ftkdZ7ovGQ29LnTxrW9EBanEF/6wxGoGpojFpYc0aNA9mq0boa4y2cyJIoWC6LM+KTOm5iadXoZchtb5jx5nOKiFjYmKrR53HA1kSHzO8SLV8SFfFKLTXGdw/5qNNX7YRgg/XQ5RAsb0wKPNfWGel3ipZvfOSTxIY20aBforbpVdBlV1X+q+t3Ut4kesgvrVsPWtlIVoPjOHgbOBNddpvl1wCnXWgbTJoIuS0nHdiIjQ5lycJ6/M3YuO5b3Q6o4XbYmj4HYY/d8kF3nudw0ZC/4d9sAtc2KYN21ASTrB5w8rvEps+A3cZjUkW2O0M/6LS+GdjWJiK5td9t6SzGgIrF0uql0v1eR9Ny+ZGg05L3f/tAZ0bCRNi60ctGkjhqysasAM83b2zaLsvZKmyLeBo6o/q9Dss2fdxIwHXheQacm+Pc+9sEE63W+LcZjbIUac5cFAW+5xtCWqUyatgEHv114z1EudNcK40aH2lpiEUzrZrh2gRu0zR62jhnWN2p1Ih6XepG8hlWZryJ7d9Ms95qNHMyTobdlpXJqOG229rq02+G9aBZRv9E2GXZ6n5SYVebUoJue9OsE49ka7vxpB1fCx1OoJrFRmsGk1o4jmuquWtVLV6fJGIooO3cHCLfcgNCOyG3fZ3mnt3Go5/S5k2dMNAkk9fqc2ANl71x9sqWfuuO+Y00ytCxepCxRp/H0XIt3CzPQcTrWLfBctoF6jO3eu30DTYI1tBG/Xi3YqC9FY3kwDaLk9HtsDXt0TAadG4aR6MkrneqWlmPuxlSnTNxMzT9q6eRlKLLYaM+gKiFjU5G0cZbSj7y/2fvvMOcKtY//k3vyfbGLru0pVdRBK40RVT0ooINFVTEgr1d2xWwotyfvV4L5dqwI3YsgApIkQ5L34WF3YXtLZtsyvz+iIkn2fQ9SU7OzOd5eB5y9uRkZs6Ud955SyCkUgk0iuDzfbKGw4oEnaqjDkwmk6BLEhsdJCvi1sKJnPwACW26pIjTipWLTCoJGl+XHiu2jsolk1YhWqtdwBWHONxs4oDrBFvMGwyJRIJ0zoKapleK3j2Wi7+4tAa1XNRjwJc8k7fwpFPLRRd/PBgKmRRqn+RGNFhsAK5DpUDKVJ1KTk3SJ4VM6tXnE5U4j0/8WejHCo1SHOFlaBn3/tD5Gev+rJvFSq7JvxIhJ8B1MSKRSLzWQm0IpZMY4c5jGhHMaZHi670ULKSaGNGp5F7zXoZeJeo9IJdQh4pij8/vxtfwxhVakak84w1r8SQmU6/qkOhDIhF3sisuwSzVaEn2YlTLO8SkFfuJtVohC7iZ8EWlkFJxepnKOVSh5YDFjVQqgdFnvIt9DPiSolV4zQMZlFivcuFaaEgkLtdBWsgI4LmQIQJFaySYtOKaB+NpjZ/sVt9uxB5/PBj+rNTomgeVHQwQtCoZNdbcbrjvXEvJISMXNSeMYKCQgmImw+C99tEmDwNAGkcmSqeo/qE8F2jxbEjXeee0EHvya6FC3+wrIqRSSYeNgV6tEH2YCDfBEvuJZcMUColEAr1PO9BgyRNuQp/8VC0VVr1q5d9jnsZNha/VbjiJQcWERCLxUjDQYq3AhWuxpJBLqRj3bgLF3qZtc6nlWrApk18OUsikcdsU0hJeRswoZFKvw0aJxFvhJnbkMmmHZL+07AW4qChXsnLrrBZ5HF5/aBTeyR5pO2QBvGUBtQhkgXAJdqiolEup0Q/JZVIvjwadmr55QAjQ0dtEjK+i1aihZzEJVFeZVOLXbVCs6Hw2oTQIFDqVPGBMcjcSCZAXYfzmZEXJERwUcnqUa258lao0xB3zhZvUREWhNR93DIjB7T8SjGq5X68m2hQs3PculiQ/8bLIpq2viBWvMaCQiT50ni8dDpwpChvlRiWjWxbg1plGJbtvyBRaQkVw4SpTaVGsAggaHo02AyTuGKAxbI4QoGfkiRRfKwWucCF2NApZh4014LLkpUmw9l1AaVlQfeOO+ZKiVYhG0cAIju88qKZwY0XRlOcXrgWfnLJNlUQigcHnYEWjlFMXg4772sXSB+JhOCCTSqg4nKYBlYJuBaPCp840tgE3ZAxNeyE33DorKVsD3Yhl/YsWQojn/07O/8VOMEUybcYXMs48QONBixCgc/YVEb7x53wFLDHjb2MN0GfFKJd4v3NahItAcUjD/buY4ApRDic9ApUb7jwok0qoU64B3u+dIpnag1zq3Qdow9eCj4awSb5wl0Kx6FbiYWFM28G8mOEq1WiMT62U0ml0wUXhx/iGVmi0ZAZAVbgwf9g48rDNQY9A7BsyiQstSaAZwoHO2VdESOA9mdC2rvjGXwPoSnQCdNxM07JZ1ChlQQ9VaHL/tTmcnv87HAksSILgKhX9eTfQALcPtHP+TwvctU9KyRzIxdeCxd/aKHa4hytiOWjRKeUdkpnxDW0x7MWMt0cHfVu8jvJwYsqRSGg8ZA0ErZbMYln/osVi/3sj1G6nSx4OZLFMW8gIB+XGV0KAztmXIRr8uYaw0zp6CGatR5P7L0eeolLB6KVkpnFXCW9BmjahGgBA52v34Lvu0bahAABw9hEOkeyypVIJ9KrYKoHFZPVuo3D948JVLAeyaBMzHZTMFC4MFJ4tBIRWi14ikvUvWqy2vzdFlna61oRASmbawmXYHVxrdrr6gFBgS1GSQ+C9kNC2rvibNGlTMvvGm3JSdGIXyGpdpZBSFTKBu4DSuJhKAn6gB65i2UphH6Ad39ijNMYi5VqriCkOY6wPTH1DrSQzNK5/XLiHrDQq2HyHve8eiQaYJTODdstNi40rD9Pl3umboybUdbFi53r4Uj4eEgVdPU6MdBCo6MLfpEnb5rqjUE0PgRdTug4auApGmuKPueFupmkMleBwEi8hykajJTPl+CY5VcgpHAfcZD8iGgKxtDSWSgGtiNZLGtc/LtxwUTJaT1w5iOisKWxolIEY3ojFkydarBSHywiU8D7QdbHC3RPZKZcLEgVd2jiG6PBN6iGV0pnog1YCJbahLQ4bV550UnXM0BEat1e+p/RisuIMF65bNI17bN+Er1Sug9yYzCKaB2NpyaxVykVl8Uro0id0gPsqmUUrg0Ep4ln+ooJ7yGynzIrVn6GdTCahbj3g7oMo3BIJAgp3ISKDrjmjA74baZpCJDACK1JoU7BwFSq0x2KjJfElF9rDJgHeimU643B6byJ8lc6M5EUXQyWz2HIXUDj1ecG1YqVwKWSAWTIzGNx9EG1GF/6Mr1SU7YkBb1mArh4gHOjrdSLDV5igbV/pu5Gm7aQOoLsPBFKkKChLeMPtA7RvMGjq/258kx3SOA9ya0xr4iPuexeTdWrYcKospnlQKZcG9NrpLLFUYCcCGrs9Fwnllsy+8x6N86CIpj5GlNBobMGF5gN3f7JCrOQHIeOVn4CuLiAY6Ot1IoN25YJUKvFSKPi2Bw1w6y+V0iVcBOrvtG0suFnk5RK6p3Wa+r8bme88SNkhC+A9F9DYBwD65j1fZCI+bNOpYhNPMVbPTRS0HjC54Y4BGj06aN8TAeKb+xiRQ2O/58L1apZTtij4CxdJm3cv4D0GaNwTCQH6ep3IkPsMHAVlkyngrVCgcWFVULyYBhKmaROyuUKFirIMwr7QOAdIJBIoOUk91DJxKY7CgXu2Qtv4d0NptT1wNxJis17SKmNjcayL0XMTBY2baS5ceZgycRBAxz2R2OaBcKCvxgxfaPPm9EXDSWZLWyJ4f2sgjesi13qbtjxNQoG1epLjO3FQqFvwEqho3GRzhWjaFGyBlcxxLkiCUSrYYuqGtnfvRs3pA2olfX2Aa8FGo0cLQKflIhfuxlpsVt2xUAZLJN6bcTHA1r+//0/jfMASoIpv7mNEDo39ngtXBtYqxbXGhcLXsxEAlHL65gTuGKD90CVR0D0LiQDfhYT2hYVGuNZbCsriLvkmPKMVtZxZMruh1YpVo/hbCaWhTKgG6I7B54bSru9BzJ48sRjTGoVMdAopsdWnM9A4H8hl3pbctBleMBgAfXtBX7Re8jB9beErC4lZNgoE14Kd1hB6iYa+XicyZFIJ9Yk+aIdmS+ZASYOdlOmeufHHVJQLl7TKElyBSk1hH6A+6R1D1NYqsYidTONhlNjhhg0S72gIjFccTgoVKwwGQGfoTC5c62WxeeuEg68ugDbdAMCMLoUAewMiQEq5mzBXnxhI6ShmvIRqyt6/PYA22eF0xrkkwoF2BRuNLsKAd7gMOYXCFe3rIAA4aVwAOYjZWkUtl/F+gBarOM8MYSDm8RAIr8NGCuvPYAD0enO5UVEuD/vW2TdWPQ3QPgaEAH0jT4xQPo4IZ2NNmwWrL7TJ1DaHf2Vyu53yjkAxtIZQodEdjgvtsfkBOg9ZaUEqlfCewIi2WJUM8UPp1M9geEGj5SoX2mPzM0tmOhXrQoPuUSgSnE6ukpWuXSYhBFyjVQeFWmbuK6et+la7fyWz1e6Ic0kYQoGyKdADjUIkF1oVy1yctC0AlMF3eAsWLkN8cNc/QuFiyJ0CaT1wZjBot+Kn3aPTdz9AuxEKIzGwXpfk2BxOL6HS5qBLqPLdU9OmZAcAO0fLTluYiLZ2/8rkNhtTMtNKoBAqYofGuY+Lt3IlceVIJA6uVw+F40DsSjW+LY+ZJbMIIX7/Sw1e8jBl+yE3Yp8HGaGhXR6kUf7h4hsqgkYjFDul87+QYErmJMfio0yz2OhSMtp9lKo0WjLbOKEhAln2ipVWq93v9bZ2B/VCBq0ECqEidmittxuugtVB4QaLEOKlVKHxsEXsddYq+IuhLJG44jwzxIW3Z5u4x4M/2m2cdcBJYKdwXRT5NMgIA9oVbO0UjnsuvpbsNCqZ2ykzuhMiTMmc5LRaHT6f/SvdxIqvUplGxSLXatdqc1BlxdASoL8TArS20zMWuO+cxk0VV8FqpeygzY2ZMw/QqHDmrgU0WrD5Klh9D2BpgHvoLkZZQK3kT2RXyWXUuxSLEW9vhgQWJEGYfQxvfD/TAI3GNgxv2p309XsuZo5upJ0y4yvAT0xmCsOnWDiezjTpRYQEUzInOc0Wm/dnqy3AneLEd2PtcBJRbi6DYfbaWNNjzW5zOAOGywCAJgs9SmbuQUNrkDYRK1zlUrudroMWN62c/t5ioa8PcBXrNkLHHMjF92CBttBZAGBp/7sNLCKMy69V8mfJrFUxK2YxwpV/afTo8DUuoM3wBqDTgp3hDa3GFm64+79mivaCbnxDMNMYkpn73lkIzcRAYbcTFw1t3krlRjNdSmZ/Fmu0CdYtPgsoLQcNTW3B6xnq72KCq1T07Q80wD1YIYSegxY3hBA0cvp7Q1t7AkuTGLhhg6i05rf7WDJTqGRu4SiYfL28xIBWwZ9iWMPjs4QEjV4cXOyUe3S0+BreUCgPMUtmBo2HK1zqzX/LwHVm+uRh33AZtCWCtDmcMHPGQFMb3eMhUTAlcxJjdzg7KNLa2h0d4jSLGX8xGGkTsGgVqkNZKtOkZG7k9IEmCz31dsO1YAQAM0WhUgBX2BgbxyWwgUKhmmu5S6N7pG8MQhqVbdyNdaBQSsmMVCqBmiflsFiT/plFeLgQCQ6KLZkJIR3kX5rkQDdij03PCA4hxMvLk7Y9sd3hRCNHBq5ttiawNIlBCrrDZTT4GFz6fmbEB6ZkTmIa22zwJ0M2UiRU+XMLo2lBbWt3dLBYo0XJ7BsqxpfWdjs1oVO4Gymaxr+bNrt3n7dQpmSsa/VWKje12aiaBwFvxTKNSmbfGMy+ls00wPXiEKsll4Yn5TBfzxEatMg/gfBWMtM1D5rbHR2st5stdurCZ9EYi5vxNxab02seoM3oora13Us30tbuEK08EIgOlsyU5V/wNbSh0fBGCESsZP71119xwQUXIC8vDxKJBMuXL49BsRjh4Bsqw009RYPJnyKFJusNf6ExaAmXEKqeTicdyf+cTuJlzd5mdVBnxegbm7uNgvfOxVfJ7HTStQ4A3oluaFQy+yqVaYtL7XB6W2+JdR3kywJZx2N8ZyFBw5ofDDtH/qXtoNGfF5fDSUTp1RAM2t47wxvfOdBspUsWqPZjuVzTQpc1MzcGs28SQBqoN9Pt5S8UIlYyt7a2YvDgwXjllVdiUR5GBASy2BDr5sof/kQpmvbW/lxDLTaH6IVMQkhYgfxpCPbvstj2vkbTHAAAVh+lIm0xmf1Zr9PmJsz16KDRXdj3cJUWLw43vtZaFptDlG3Ah3JYIhFvTGauxRqNh01cq13aLFoDxWE3U5YMmSX+o5sORhcU7IO4+DOw8DXEEDtcS2bKImW4DK/8GODRGEoy0UQsrZ577rk499xzY1EWRoQEcv+g6dTe3yaS+FU9i5NAwkObzQG9SpyWSoBLqRiOHO0bq1eM+NtAtVjtSNUpE1CaxOBrue0bn1bMWGwdQ+YA9LmNc9vAQZt2BR2t18R+0OiL71pIiGudEFtYCD7qo1bIROs+y1WwtLU7kKJNYGESAFfBSJuy0Ve55oYpmRk04WuxSZMFZ1u7A1Y/Ria0hRHkWi/TlvTPbHP4PWBttToAQ/zLQzPi1UJRQCBFit1B4HQS0W4iuFA2d3bAn3LJdV3cSpZwLRV945SKEX/WWrSFy/BVqInRgjEQ/gRqoKN1t9hxUmzBB6BD3FHa9Az+1kKb0wkNxKFkdltqSyQE1gBKA6vd4ff/vuhUMi/Lb62IQmdw1z5bAPmIIU5sASZ+scvDvtA29zO88d0f0XTgHEihbncQ2B1OyGXJn4osnBjb3HawOZxhx+UWgywQyIOJRs+mRBPz3mS1WmG1/h0Lp6mpKdY/SQ2+CS68/kZIh+yitCChqN6B4k+LXagI11JD5M0AwL/CXezv3xdfBRtN1Q90kELdxtrnMy0HrW5860+TRw/gf84T02FTv7k/RHT/3Z/sCPvesqcnR1ocQeJ0Ei8FG40Wndwq01b9QOOdpjwtgP8wggx66ODVRFH/D3TQBLj2SnIRnDlHKgvM+WBr2PeKQRYIuCei0fokwcT8SGfBggUwmUyefwUFBbH+SWqQyQJvoGWUmPj6C2gvTf6DyrAJ9J7lIm8EeZjKo3DvS2b81ZG2RA++7mAiMFYIm0BjXQwWG5Hg2+NpUjADgG91aXOR9C8L0NUGtCOVSry822gbA4C3dx9t1Q803mnZD7mhq7YMXzrIwxT1f0WQvS8N+0FGkD2RyPUiQiTmlswPPvgg7r77bs/npqYmpmjmCZVMCrOjo2uIXCahZnPlb/GkaWOhkAdQMgc5gBAD4S4WYm8HAFD4USb6uyZmfOc7muYApdz/uw50XaxwlYy0HbIAgERC7xgA/M/1wTacycaexyYlughJAXftU1Cw/vsioTjhkzKA3EOdPETbi2d44Tvv0SQPqQMktJXJJKIxvGCyQHDYnkg4xFzJrFKpoFKpYv0zVKJTyf0mtBBzwjdf/C2eNCgW3WgVHd+1mDPHu1HKpZDLJAFjUrsRQ3ypUOhUHd81TXMAAKh8fOB8P4sZjVIGuUwC32TKBjVdfYCrSAjm5SNWfBWqtBw0u/Fd8yQSQK0Qz6aChrWMD7iJEcWW9DEcuApGmpRLQOD3rfUjI4kZyl47wwdfRWsgxasY0ShlUMqlHfIWpGgUCSoR/zBZIDhahcyvR7u/vTIjtkQsgbe0tGDbtm3Ytm0bAKC0tBTbtm3D0aNH+S4bIwSBlAgGtXgm01D4O5kUk/VSKPwJzxoRZ47nEo4ilYZFRaeUd1hQ9ZQpGFU+J9QqESmXwsHkR4AWk1AdDtzDRdos14COinUFBWsAF9+Nl1oh62DdzRA/3H5Ao+US17uPNovWQDKhjjKlDA3yPyMwvoctYjc68iVNp+xwLVXb8RpDnEilEuhVHfc/Rop0Y0IhYgls8+bNGDp0KIYOHQoAuPvuuzF06FDMnTuX98IxghNo0kzV0jOQfJVLNIUKAfxPmkZKlEuh6qlWyKiwaJVKJV4HSxqVjDolm69QraXMgi1d5+0tJJUCKZQJ1dyx7rsu0ICvqzhtCjaZVAIN51CRpsN2xt/Q5sXjCzfuKG0xKP3Jw3KZhDp5gMWepRvfOVCnpqv/Zxo6es9nGZlHPU346sE0ShlVFv1CIWJpbNy4cSAUZSoVMiaNwq9LAE3KBd+NNW3KNaVcCrWPAE3LaV2KRoFg/hMpFB22mDh1TdHQM/7d+Fox0uZOlqb3fudGjZI6V2muYpmGwyVffJXKgeKTihnu2ke7spFWaAsT5AtXBqZN2eh2ledi0iio82ig7GyB4YNaIfPy7NJSplxL1ym9xoBWJaduT0A7qT7W7L6fGfGBLUVJjFQqgclHoaRTy6myYJJKJV6LKW1u8kBHV3l/rvNixBRCiUyTkpmrXKHl/XPR+Ry0+H4WO3qVHErO3JdOoUCllNO9DvhabwdKCitmuIpl2pWNtEJb/F1faA8b5CsX0mR044bG987wRsdZC2ny7gVcYTS54z7Dj2UzQ9ykaBReiW9pNL4SAmwlSnJ8XQJoPK1RerlJ07fB4CoYpVJ6NtcqucxLkPLFX1wusWLUyP3+nxa44TKUCqloskhHAjd8UqgDGDHCdYWjcR3wtVymsQ24SmbaXIQZLmhXsHmFy6AwAaqvJ5+REnmYC21eTIyOBNsb0QA3hFwGRXtBhgu5TAo91/hKS/d4SBR0S2MioIMVKyWhErhwM8jTaMHGVSprlXKqTq1Tdf77u1Iupco9iqtQoi3+IOAdKoDG+gPem2sDhRsMrnKJxpjMUqkECk69FRQqmLhWrDQq2RkMrmKZtnAZQMdY7LTkKOFC43tneKNV0CcDcuEqFWkxvGJ4w33vLB5zYqBvJyYyfAUoPYXWO14Jn2T01V/H2VjrKVtMA7nA0BQqwxfa4g/6QqswoafYPdIXGkNFAN6KdhrnAVrHPoPhhmvFKqPwoIkrDysVUiot22mc+wNBaw4pNYUGV1yYPMzQUWRoJlTonoVEgEIm9bJe0lC4yVJRbsnMDQ2goez0OlD8YRZ/iV6UlFow0jj3BYLGpHdAx+R/DAaDLrzCZVCoXGFeTQwulOqYqZcF2EELg+2JEg97AyKA6xpM48TKtWSmfWGl7fRao5T5jTvI3KPoRUWpgpHG8AiBoDUmJa3KdQaD4cLLkpnSedANC5nDoBUavRgYDC5MHk487A2IAAXlilWukp3GWJxcaJxU9X7iz9Ke9IJmaHSPBQAphQeMgZBR2ha0hglhMBguuIYmtK8JtO+NGAClhsyg/HyJwYCETf8Jh70CEUC7IKnkbKxpVLJyodFyxTfBn1wmod6inWak7NVTD60x+GSs8zMYjL+gdBr0QPveiAE4aY2XwWAwGAmG7UhEAO1iFFehSKtywQ2NJ3e+IUJUFMYlZ/wNrVasdifbTNGOnNK+z2AwOkJj+DwulFefQTFMt86gHeJMdAkYFKqkxAftJ7W0Wy9zoVGm9lUq0x4yhXZo3VjbnUyioh0aPVkYDAaDwfAHrdtj2vUCDAYzvEk8TBsjAmgfR7QqlRgufBOe0RqTl+GC1tnAZqd8IWBQ78nDYDAYbpiejUEojcrMbA4YtGN30Dn2hQTTxogAwiQpBsX4WrKzZC8MGrExgYp6aA0Vw2AwGL6wvRFDQqnZAe3GZwwG8+5MPEwbIwIcbDVh/AWNPUHuo2SWM2s+BoWwdYDB8v4xGAyGC7YiMmiFdnnQSXn9GcySWQjIE10ARmDM7faw7rPYHBF/R6tMjlcfTn2499Be/7Z2h6jaIJy6tNsdsNr/HgN2Ownre8lQf4CNgUjrb7GJawwA4bVBC+sDEd0PiKv+AGC1/W25QWMbiLkP0E6471PMfYD2MRCxLCAyeRhgfSCaPZFSTtd+wPc+GvtAs1W89aedsMeAjfWBRCMhcfYnampqgslkQmNjI4xGYzx/OukoeuCbmD277OnJMXs2n8SqDWivP5AcbUB7/QE2BlgfYH2A1Z+NAdr7AO2wMcDGAOsDrA+w+rMxQHsfoB02BhJPuLpc5lzJYDAYDAaDwWAwGAwGg8FgMBiMqGGWzAImXPP+aEgWl4BYtQHt9QeSow1orz/AxgDrA6wPsPqzMUB7H6AdNgbYGGB9gPUBVn82BmjvA7TDxkDiCVeXy5TMDAaDwWAwGAwGg8FgMBgMBoPB6AALl8FgMBgMBoPBYDAYDAaDwWAwGIyYw5TMDAaDwWAwGAwGg8FgMBgMBoPBiBqmZGYwGAwGg8FgMBgMBoPBYDAYDEbUMCUzg8FgMBgMBoPBYDAYDAaDwWAwooYpmRkMBoPBYDAYDAaDwWAwGAwGgxE18nj/ICEEgCszIYPBYDAYDAaDwWAwGAwGg8FgMISJW4fr1ukGIu5K5ubmZgBAQUFBvH+awWAwGAwGg8FgMBgMBoPBYDAYEdLc3AyTyRTw7xISSg3NM06nExUVFTAYDJBIJPH8aVHT1NSEgoIClJeXw2g0Jro4cYfVn+76A6wNWP3prj/A2oD2+gOsDVj96a4/wNqA1Z/u+gOsDWivP8DagNWf7voDrA1iBSEEzc3NyMvLg1QaOPJy3C2ZpVIp8vPz4/2z1GA0GqkeSKz+dNcfYG3A6k93/QHWBrTXH2BtwOpPd/0B1gas/nTXH2BtQHv9AdYGrP501x9gbRALglkwu2GJ/xgMBoPBYDAYDAaDwWAwGAwGgxE1TMnMYDAYDAaDwWAwGAwGg8FgMBiMqGFKZpGgUqkwb948qFSqRBclIbD6011/gLUBqz/d9QdYG9Bef4C1Aas/3fUHWBuw+tNdf4C1Ae31B1gbsPrTXX+AtUGiiXviPwaDwWAwGAwGg8FgMBgMBoPBYIgHZsnMYDAYDAaDwWAwGAwGg8FgMBiMqGFKZgaDwWAwGAwGg8FgMBgMBoPBYEQNUzIzGAwGg8FgMBgMBoPBYDAYDAYjapiSuZMsWbIEKSkpiS5Gp1i9ejUkEgkaGhoS+gxG7CgqKsILL7zg+SyRSLB8+fKElYcRmLKyMkgkEmzbti3i715zzTW48MILPZ/HjRuHO++80/PZtx8wxEcyr0nz58/HkCFDEvb7tMyLYpoHmOwRH8TUZxiMZCGZ13MGQwwkWi7lG999oVAQWzszmJIZAHDy5EnceOON6Nq1K1QqFXJycjBp0iSsX78+5Hcvu+wy7N+/Pw6l7BxuxZXvv6uuugqjRo1CZWUlTCZTWM/yN0H5e8Ybb7wBg8EAu93uudbS0gKFQoEzzjjD6/u//fYbJBJJp9oymTab11xzjd/3cfDgwZj83qZNm3DDDTfE5NnR4qsQdZNM7zFS/L1z7r9rrrmmU89/8cUXsWTJEl7Kyifu/n7TTTd1+NucOXN4qTuQvBuydevWQSaT4Zxzzonoe/4UP4lek6KtCwDce++9+Pnnn2NQKm8CCbOVlZU499xzY/77/ojXGAGEuR4AQFVVFW677TZ0794dKpUKBQUFuOCCC4L2iUjll3gRaq4/99xzoVAo8N577/n9/o033ohBgwb5/dv8+fMhkUj8jrGFCxdCIpFg3LhxfFYnJn2GKwcpFApkZ2dj4sSJWLRoEZxOJ6+/lczEW5aONbGUfwPJlUIkHBk4kvU8VvIPG6eda1tu+8nlcnTt2hU333wz6uvr+S1kEhHNWi9G4q0LAIDPP/8cjz/+eMyez6Uz+4F40BmjLkZomJIZwNSpU7F9+3YsXboU+/fvx4oVKzBu3DjU1dWF/K5Go0FWVlYcSskPP/30EyorKz3/Xn31VSiVSuTk5EAikUT9XH/PGD9+PFpaWrB582bPtd9++w05OTnYtGkTzGaz5/rq1auRl5eH4uLiqMvAF4QQL2E+Vpxzzjle76KyshLdunWLyW9lZmZCq9XG5NlCo729vcM1h8MRlTAc7fcCwX3XL7zwAoxGo9e1F198MarnustpMpliqmS12WxRf7egoADLli1DW1ub55rFYsGHH36Irl278lE83uD7vYdi0aJFuO222/D777/j6NGjnXpWotekztRFr9cjPT09RiULTU5ODlQqVcJ+P15jRIjrQVlZGU455RT88ssvWLhwIXbu3Invv/8e48ePxy233OL3OzabjRf5JRaEmuuXLVuGyZMnY/HixR2+29bWhmXLlmHWrFkBn5+bm4tVq1bh2LFjXtcXL14ck/k0Vn3GLQeVlZXhu+++w/jx43HHHXfg/PPPDyiHdWYdSkbiIUvHS+51E0/5N5lJxHruT/6JZpwy/sbdfqWlpfjvf/+Lr776CnPmzEl0sRJCNGu9mOFrLvS39/VHWloaDAZDxM+PBj73NkIn3PanCeqVzA0NDfj999/xzDPPYPz48SgsLMRpp52GBx98EJMnT/bcc8MNNyA7OxtqtRoDBgzA119/DcD/6eZXX32FU045BWq1Gt27d8ejjz7qtQhLJBK8/fbbuOiii6DVatGrVy+sWLHC6xm7d+/G5MmTYTQaYTAYcMYZZ+DQoUOevy9evBh9+/aFWq1Gnz598Nprr4VV3/T0dOTk5Hj+mUwmv5aja9euxdixY6HVapGamopJkyahvr4e11xzDdasWYMXX3zRc+JWVlbm9xm7du2CXC7HP/7xDxQVFeHZZ5/F6tWrMWXKFPTo0QPdunXDU089heuuuw6PPvooGhoa8Nprr+Ff//oXunTpAp1OhxEjRmD16tWeZx45cgQXXHABUlNTodPp0L9/f3z77bcoKyvD+PHjAQCpqaleVl+EECxcuBDdu3eHRqPB4MGD8emnn3qe6S77Dz/8gOHDh0OlUuG3337DuHHjcPvtt+Nf//oX0tLSkJOTg/nz54fVzuHgtprn/nvxxRcxcOBA6HQ6FBQUYM6cOWhpafF8x93fvv76a/Tu3RtarRbTpk1Da2srli5diqKiIqSmpuK2226Dw+HwfC+Yq+uECRNw6623el2rra2FSqXCL7/8wlt9o+Wzzz5D//79oVKpPP2IS1FREZ544glcc801MJlMmD17tlc79evXDyqVCkeOHEF9fT1mzJiB1NRUaLVanHvuuThw4IDnWYG+xxe+Y08ikXS45ubw4cMYP348tFotBg8e7OVZEaickVrxNDY24oYbbkBWVhaMRiMmTJiA7du3e/7utvhctGiRx+KAEBJV3YcNG4auXbvi888/91z7/PPPUVBQgKFDhwIA/ve//yE9PR1Wq9Xru1OnTsWMGTMAANu3b8f48eNhMBhgNBpxyimnYPPmzVi9ejWuvfZaNDY2euYm93htb28POq/4a8/ffvsNCoUCVVVVXmW55557MGbMmKjawB+tra34+OOPcfPNN+P888/vYIm+YsUKDB8+HGq1GhkZGbj44osBuDxKjhw5grvuustTX25duLz++uvo0aMHlEolevfujXfffdfr7+GsSZ2ti3ue/fnnnzF8+HBotVqMGjUK+/bt89zja2Hs7s9PPfUUsrOzkZKS4llP77vvPqSlpSE/Px+LFi3yKsf999+P4uJiaLVadO/eHY888ohHMbVkyRI8+uij2L59u6fd3OX0DZexc+dOTJgwARqNBunp6bjhhhu85mN3+f7v//4Pubm5SE9Pxy233BK1EiycMQL4n8+HDBnitT7Nnz/f452Vl5eH22+/PeD3g8k48cJtrb1x40ZMmzYNxcXF6N+/P+6++2788ccfAFzv54033sCUKVOg0+nwxBNPdJA9ol0jQ80RkRLOXD9r1iysWrUKZWVlXt/99NNPYbFYcNVVVwV8flZWFs4++2wsXbrUc23dunWoqanxyK5unE4nHnvsMeTn50OlUmHIkCH4/vvvPX8fOXIkHnjgAa/vVFdXQ6FQYNWqVQA69plQa0e4uOWgLl26YNiwYXjooYfw5Zdf4rvvvvMal77v3eFwYNasWejWrRs0Gg169+7d4ZA2FvNHIujduzfy8vK8+iNXll63bp3X9fHjx+O9997D8OHDYTAYkJOTg+nTp+PkyZNe9/mTe+NFZ+TfH374AX379oVer/coaADXnLd06VJ8+eWXnrnd3Wah3mkguaK1tRVGo9FrzwC49nk6nQ7Nzc0xbSff9Twa+ScauddX/nG/r+eeew533nmn33F69OhRTJkyBXq9HkajEZdeeilOnDjhVZ9A8gzgP1xVSkqK5/luq8OPP/4YZ5xxBjQaDU499VTs378fmzZtwvDhwz19orq62us5wfbM7ud+/vnnfmXuYG0bzjhbunQpGhsbcf7556NHjx6oqqrC8ePH8d133wH4e35OSUmBRCLpMD9HW+9NmzZh4sSJyMjIgMlkwtixY7FlyxavdkmEPiKctT5UX+LuTbp27Qq9Xo+bb74ZDocDCxcuRE5ODrKysvDkk096/XY469bTTz+N7OxsGAwGzJo1CxaLxfO3X3/9lfd9gb+5UCaTYc2aNTjttNOgUqmQm5uLBx54wEuXNG7cONx66624++67kZGRgYkTJwIA9uzZg/POOw96vR7Z2dm4+uqrUVNT4/U9rjd6ZWUlJk+eDI1Gg27duuGDDz7wG2Iz0j1CqL1NsHb+4YcfoFarO3g033777Rg7dqzn87p16zBmzBhoNBoUFBTg9ttvR2trq+fvRUVFHj2TwWBA165d8eabb3r+7lbmDx061MsDzJ/H/oUXXujlTehP9xBOmaiCUI7NZiN6vZ7ceeedxGKxdPi7w+Egp59+Ounfvz9ZuXIlOXToEPnqq6/It99+SwghZPHixcRkMnnu//7774nRaCRLliwhhw4dIitXriRFRUVk/vz5nnsAkPz8fPLBBx+QAwcOkNtvv53o9XpSW1tLCCHk2LFjJC0tjVx88cVk06ZNZN++fWTRokVk7969hBBC3nzzTZKbm0s+++wzcvjwYfLZZ5+RtLQ0smTJkoD1LC0tJQDI1q1bO/xt1apVBACpr68nhBCydetWolKpyM0330y2bdtGdu3aRV5++WVSXV1NGhoayMiRI8ns2bNJZWUlqaysJHa7vcMzNm/eTKRSKRk0aBD5xz/+QRYvXkw0Gg3p1q0b+eSTT8jNN99MjEYjSUtLIy+++CJRq9Xk4osvJgDI0KFDya+//koOHjxI/vOf/xCVSkX2799PCCFk8uTJZOLEiWTHjh2ed7FmzRpit9vJZ599RgCQffv2kcrKStLQ0EAIIeShhx4iffr0Id9//z05dOgQWbx4MVGpVGT16tVe9R80aBBZuXIlOXjwIKmpqSFjx44lRqORzJ8/n+zfv58sXbqUSCQSsnLlyjB6VnBmzpxJpkyZ0uH6888/T3755Rdy+PBh8vPPP5PevXuTm2++2fP3xYsXE4VCQSZOnEi2bNlC1qxZQ9LT08nZZ59NLr30UrJ7927y1VdfEaVSSZYtW+b5XmFhIXn++ec9nwGQL774ghBCyPvvv09SU1O9+v+LL75IioqKiNPp7HRdAxGoDbh9yd2PHnvsMbJv3z5PP1q8eLHn/sLCQmI0Gsl//vMfcuDAAXLgwAFPO40aNYqsXbuW7N27l7S0tJB//vOfpG/fvuTXX38l27ZtI5MmTSI9e/Yk7e3thBAS8HuxwHfucOMeq3369CFff/012bdvH5k2bRopLCwkNpstaDl923Ts2LHkjjvu8Gordz9wOp1k9OjR5IILLiCbNm0i+/fvJ/fccw9JT0/3zEXz5s0jOp2OTJo0iWzZsoVs3749qj7hLtdzzz1HzjzzTM/1M888kzz//PNkypQpZObMmcRsNhOTyUQ+/vhjzz3V1dVEqVSSX375hRBCSP/+/clVV11FSkpKyP79+8nHH39Mtm3bRqxWK3nhhReI0Wj0zE3Nzc2EEEKmT59ORo0aFXBeCdSexcXFZOHChZ6y2Gw2kpWVRRYtWhRxGwTinXfeIcOHDyeEEPLVV195jbuvv/6ayGQyMnfuXLJnzx6ybds28uSTTxJCCKmtrSX5+fnkscce89TXXRduv/r888+JQqEgr776Ktm3bx959tlniUwm87QnIaHXJD7q4h7XI0aMIKtXrya7d+8mZ5xxBhk1apTn+/PmzSODBw/2fJ45cyYxGAzklltuIXv37iXvvPMOAUAmTZpEnnzySbJ//37y+OOPE4VCQY4ePer53uOPP07Wrl1LSktLyYoVK0h2djZ55plnCCGEmM1mcs8995D+/ft72s1sNnvawT0vtra2kry8PHLxxReTnTt3kp9//pl069aNzJw506t8RqOR3HTTTaSkpIR89dVXRKvVkjfffDOidnM/K5wxQkjH+ZwQQgYPHkzmzZtHCCHkk08+IUajkXz77bfkyJEjZMOGDV5l4n4/lIwTD2pra4lEIiFPPfVU0PsAkKysLPLOO++QQ4cOkbKysg6yR7RrZKg5ojMEmuvtdjvJzc31vDc348aNI5deemnA57nHyeeff0569uzpuT5r1ixyxx13kDvuuIOMHTvWc/25554jRqORfPjhh2Tv3r3kX//6F1EoFJ66vfzyy6Rr165ec/vLL79MunTpQhwOByEk8rUjHALJAIS4+vO5555LCPH/3tvb28ncuXPJxo0byeHDh8l7771HtFot+eijj7yez/f8kSimT59Ozj77bM/nU0891SNLP/TQQ4QQQqxWK9FoNOTtt98m77zzDvn222/JoUOHyPr168npp5/uaU9CAsu98aCz8u9ZZ51FNm3aRP7880/St29fMn36dEIIIc3NzeTSSy8l55xzjmdut1qthJDQ7zSQXEEIIbNnzybnnXeeV1kvuugiMmPGjJi0A3dO8507opF/opV73fKPu5z+5B/3OHU6nWTo0KHkH//4B9m8eTP5448/yLBhw7zmoWDyDCHe668bk8nkkfe5svH3339P9uzZQ04//XQybNgwMm7cOPL777+TLVu2kJ49e5KbbrrJ84xQe+ZQMnewtg13nBmNRs8427x5M9HpdESj0RBC/p6fi4qKyJw5czrMz9HW++effybvvvsu2bNnD9mzZw+ZNWsWyc7OJk1NTV5tHk99RDhrfTh9ad68eUSv15Np06aR3bt3kxUrVhClUkkmTZpEbrvtNrJ3716yaNEiAoCsX7/e89xQ69ZHH31ElEoleeutt8jevXvJww8/TAwGg5dcyue+INAccOzYMaLVasmcOXNISUkJ+eKLL0hGRoaXrDB27Fii1+vJfffdR/bu3UtKSkpIRUUFycjIIA8++CApKSkhW7ZsIRMnTiTjx4/3+h53X3jWWWeRIUOGkD/++IP8+eefZOzYsUSj0XTQGUS6Rwi2HwjVzna7nWRnZ5O3337b8zz3tf/+97+EEEJ27NhB9Ho9ef7558n+/fvJ2rVrydChQ8k111zj+U5hYSFJS0sjr776Kjlw4ABZsGABkUqlpKSkhBBCyMaNGwkA8tNPP5HKykpPfXzbiBDiJYO7n+2rewinTDRBvZKZEEI+/fRTkpqaStRqNRk1ahR58MEHyfbt2wkhhPzwww9EKpWSffv2+f2urwBwxhlndJg83333XZKbm+v5DID8+9//9nxuaWkhEomEfPfdd4QQQh588EHSrVs3jwDgS0FBAfnggw+8rj3++ONk5MiRAevoXqQ0Gg3R6XSef1u2bOmwSbviiivI6NGjAz7L3+Dzfcb06dPJxIkTyZtvvkl0Oh2x2WzkjjvuIADIiRMnyLJly4hKpSJXXXUVWbNmDQFADhw4QACQBQsWeD37zDPPJA8++CAhhJCBAwd6KeyDlYEQV9uq1Wqybt06r3tnzZpFrrjiCq/vLV++vEM9//GPf3hdO/XUU8n9998fsG3CZebMmUQmk3m9i2nTpnW47+OPPybp6emez4sXLyYAyMGDBz3XbrzxRqLVaj1CDyGETJo0idx4442ez8GUzBaLhaSlpXltzoYMGRKwnfnCXxvodDqiVqs979Hdj7jcd999pF+/fl51u/DCC73ucbeTe5NACCH79+8nAMjatWs912pqaohGo/EoNf19L1aEUjJzF9fdu3cTAJ6FMVA5I1Ey//zzz8RoNHY4XOvRo4dnEZ83bx5RKBTk5MmTnajp3+Wqrq4mKpWKlJaWkrKyMqJWq0l1dbXX4n3zzTd7CekvvPAC6d69u0c4MRgMAQVYf2168OBBIpFIyPHjx72uc+eVQO35zDPPkL59+3o+L1++nOj1el4PHkaNGkVeeOEFQohLWM3IyCA//vgjIYSQkSNHkiuvvDLgd/0pG33bYNSoUWT27Nle91xyySVem+ZQaxIfdXHPsz/99JPn/m+++YYAIG1tbYQQ/0rmwsJCj6KLEEJ69+5NzjjjDM9nu91OdDod+fDDDwOWa+HCheSUU07xfPb9HTfcefHNN98kqampXu/6m2++IVKplFRVVXmVz263e+655JJLyGWXXRawLIGIZIyEUjI/++yzpLi4OKAMwf1+KBknHmzYsIEAIJ9//nnQ+wCQO++80+uaPyVzpGtkOHNEZwg01xNCyP33308KCws989vhw4eJRCIhP/zwQ8Dnuftve3s7ycrKImvWrCEtLS3EYDCQ7du3d1Ay5+XleSlzCHHJMnPmzCGEEHLy5Ekil8vJr7/+6vn7yJEjyX333ef5HOnaEQ7BlMyXXXaZZ+719979MWfOHDJ16lSv58di/kgEXFm6qamJyOVyjyztPqhzy9KHDh3q8H33Zto9BgLJvfGAT/n31VdfJdnZ2V7PDtSnuPi+02ByxYYNG4hMJvPMD9XV1UShUHgMVaIlHBnYd+6IVP7pjNzrln/cbepP/nGP05UrVxKZTOZ1WOOWWzdu3EgICS3PhKtk5srGH374IQFAfv75Z8+1BQsWkN69e3s+h9ozhytzB5rDuQQaZ1Kp1OvduvfjFouF5OXlkVtvvZVIJBJSWlpKCPGen6Otty92u50YDAby1Vdfea7FWx8RzlofTl+aN28e0Wq1XgrzSZMmkaKiog7zvVunEM66NXLkSC9FPSGEjBgxwkte5HNfEGgufOihh0jv3r29Dn5fffVVotfrPfUbO3YsGTJkiNfzHnnkEa/DSEIIKS8v9xjgub/n3heWlJQQAGTTpk2e+926GF+dQaR7hFB7m1DtfPvtt5MJEyZ4Pv/www9EqVSSuro6QgghV199Nbnhhhu8nvHbb78RqVTq2VMUFhaSq666yvN3p9NJsrKyyOuvv04ICWyAGa6S2Vf3EE6ZaIL6cBmAyxW7oqICK1aswKRJk7B69WoMGzYMS5YswbZt25Cfnx92fLM///wTjz32GPR6veff7NmzUVlZ6RU3jZvQRafTwWAweFxstm3bhjPOOAMKhaLD86urq1FeXo5Zs2Z5/cYTTzzhcV8599xzPdf79+/v9f2PPvoI27Zt8/zr169fh9/Ytm0bzjzzzLDqG4iSkhKMHj0a48ePR2trKzZt2uSJAZSeno6xY8fCarWiT58+WL16Nbp27YqtW7cCAObNm+dVtzVr1njqdvvtt+OJJ57A6NGjMW/ePOzYsSNoOfbs2QOLxYKJEyd6PfN///ufl7sPAAwfPrzD930T7+Tm5nq5QnWG8ePHe72Ll156CatWrcLEiRPRpUsXGAwGzJgxA7W1tV6uFlqtFj169PB8zs7ORlFREfR6vde1cMupUqlw1VVXeVxGt23bhu3bt/OWZCoYvm2wbds2vP32256/u/sRl9GjR+PAgQNers7+3p1SqfR6fyUlJZDL5RgxYoTnWnp6Onr37o2SkpKA30sU3DLk5uYCgNc77Ww5//zzT7S0tCA9Pd1rbJSWlnqNjcLCQmRmZkb9O1wyMjIwefJkLF26FIsXL8bkyZORkZHhdc/s2bOxcuVKHD9+HIDLFc+dHAMA7r77blx//fU466yz8PTTT3cYx75s2bIFhBAUFxcHnFcA/+15zTXX4ODBgx4XvkWLFuHSSy+FTqfrdFsAwL59+7Bx40ZcfvnlAAC5XI7LLrvMayzyNRdzGT16tFefB4KvSeEQqi7+fsdfv/alf//+kEr/FlWys7MxcOBAz2eZTIb09HSvZ3z66af4xz/+gZycHOj1ejzyyCMRx4MrKSnB4MGDvd716NGj4XQ6vUJ89O/fHzKZzKtOnVkjwhkjobjkkkvQ1taG7t27Y/bs2fjiiy8Cxs2MVMaJBeSvEDzhxFX2N9f7EukaGe4cEQtmzZqFI0eOeEJTLVq0CPn5+TjrrLNw9OhRr/I89dRTXt9VKBS46qqrsHjxYnzyyScoLi7uMIc1NTWhoqIi6ByQmZmJiRMn4v333wcAlJaWYv369bjyyiv9ljnctaMzEEK8+oO/9/7GG29g+PDhyMzMhF6vx1tvvdVhnCdq/uAbriz922+/obi4GFlZWRg7diw2bdqE1tZWjyzdvXt3bN26FVOmTEFhYSEMBoPHDdi3HuGMp1jAl/wb7nwb6p0GkytOO+009O/fH//73/8AAO+++y66du3KS9isUDKwL5HKP52Re93yjzsEgz/5xz1OS0pKUFBQgIKCAs/f+vXrh5SUFM/v8CHPAN4yRHZ2NgB4jWnu3B7Ontnfc8ORTQCEPc5Gjx6Nbdu2YcOGDbjtttswceJE6HQ6vP/++6ioqEBFRQXGjx+PoqIiz/3BZLRQ9XaX/aabbkJxcTFMJhNMJhNaWlo6lC2W+ghfwlnrw+lLgCtcATe2cHZ2Nvr169dhvnfXJZx1q6SkBCNHjvQqj+9nvvcF/uZCdzm47TR69Gi0tLR45WHwnb///PNPrFq1yqt+ffr0AQC/72Tfvn2Qy+UYNmyY51rPnj2Rmpra4d5I9gih9gPhtPOVV16J1atXo6KiAgDw/vvv47zzzvOU7c8//8SSJUu86jpp0iQ4nU6Ulpb6Lbc7bBlfehx/7R9OmWhBnugCCAW1Wo2JEydi4sSJmDt3Lq6//nrMmzcP9957b0TPcTqdePTRR73iTHF/w43vhC2RSDyJFjQaTdDnA8Bbb73lJTQA8Gx03377bU/iIN/fKSgoQM+ePYPWIdjvh4tb8OjZsyfy8/OxatUq7Ny50zP55+TkQC6Xo7y8HPv27cOECRM8dZs9e3aHWDjuzeH111+PSZMm4ZtvvsHKlSuxYMECPPvss7jtttv8lsP9zG+++QZdunTx+ptvgid/C0Sw99RZdDqd17s4cuQIzjvvPNx00014/PHHkZaWht9//x2zZs3yih3nr0ydLef111+PIUOG4NixY1i0aBHOPPNMFBYWRlmz8PFtAwBeC6jvRtN9zd9zfNFoNF7f9fc9f7/h+71EwX2n7vJw32lny+l0OpGbm+s37ig3BiBfClU31113nScG+Kuvvtrh70OHDsXgwYPxv//9D5MmTcLOnTvx1Vdfef4+f/58TJ8+Hd988w2+++47zJs3D8uWLcNFF13k9/ecTidkMhn+/PNPL2UgAC+lk7/2zMrKwgUXXIDFixeje/fu+PbbbzsVp9WXd955B3a73WtuIoRAoVCgvr6el7kY6CjQ+xtXnZ1DQtXF3+/469e+RDrf/fHHH7j88svx6KOPYtKkSTCZTFi2bFmHWO6h8NdGvuUOVL7OrhGhxohUKu0wn3HXiIKCAuzbtw8//vgjfvrpJ8yZMwf/+c9/sGbNmg7l5auPdYZevXp5FBWhYsqHMx9F2mfCnSNiQa9evXDGGWdg8eLFGD9+PJYuXYprr70WUqkUeXl5XlnP09LSOnz/uuuuw4gRI7Br1y5cd911AX8n1Bxw5ZVX4o477sDLL7+MDz74AP3798fgwYP9PivctaMzlJSUeCU/8n3vH3/8Me666y48++yzGDlyJAwGA/7zn/9gw4YNXvclav7gG64sXV9f74lLmZOTg27dumHt2rVYtWoVJkyYgNbWVpx99tk4++yz8d577yEzMxNHjx7FpEmTOiQn4nt9Dxc+5d9Asp2bcN5pKLni+uuvxyuvvIIHHngAixcvxrXXXsuLnBhKBvYlUvmnM3KvW/7ZtWsXunfvjp9++qnDmHeP00DrJfd6qLXG37v0Fwvdnwzhe407twPB98zBnhtsLY9knBkMBs97fumllzB+/Hj06NHDc7D3888/e631oWS0UPUGXMrQ6upqvPDCCygsLIRKpcLIkSM7lC2W+ghfwlnrw+lLgcodap3nY93ie1/gbw4ItvflXvedv51OJy644AI888wzHX7HfXDi75nhXI9E1g13PxCM0047DT169MCyZctw880344svvvBKlOx0OnHjjTd65Rtxw01+HI2MHkrGduOv/cMpEy0wJXMA+vXrh+XLl2PQoEE4duwY9u/fH5alz7Bhw7Bv376QitxgDBo0CEuXLoXNZuswOLKzs9GlSxccPnw4oJWJrzI1mt//+eef8eijj/r9u1Kp9LIi9Ue/fv3w+++/A3Cd0q1evRo7d+5EXl6eZ/FRq9XYt28f/vjjD1x77bWexEatra1B26+goAA33XQTbrrpJjz44IN46623cNttt0GpVAKAV9ncSSyOHj3qFSxeiGzevBl2ux3PPvusRxn/8ccfx+W3Bw4ciOHDh+Ott97CBx98gJdffjkuvxsKbj9ys27dOhQXFwcUYoI9y263Y8OGDRg1ahQAV4LD/fv3o2/fvryVOVkYNmwYqqqqIJfLPdYT8eCcc87xCLmTJk3ye8/111+P559/HsePH8dZZ53lZdEAAMXFxSguLsZdd92FK664AosXL8ZFF13kd24aOnQoHA4HTp48iTPOOCPi8l5//fW4/PLLkZ+fjx49enSwCIwWu92O//3vf3j22Wdx9tlne/1t6tSpeP/99z1z8bXXXuv3GeHMxX379sXvv//uSZwIuMYQn30+nLoMGDCAt98Lxtq1a1FYWIiHH37Yc803eWe4a9jSpUvR2trqESTXrl0LqVQac6vfUGMkMzPTk+wKcFmr+lpJaDQa/POf/8Q///lP3HLLLejTpw927tzpZbECIGIZJxakpaVh0qRJePXVV3H77bd3ENwbGhp4U176o7NzRGeZNWsWbr75ZkyZMgXHjh3zjHe5XB5Sluzfvz/69++PHTt2YPr06R3+bjQakZeXh99//93L8nLdunU47bTTPJ8vvPBC3Hjjjfj+++/xwQcf4Oqrrw74m7FeO3755Rfs3LkTd911V8B7fvvtN4waNQpz5szxXOPDijqc+SNRuGXp+vp63HfffZ7rY8eOxQ8//OCRpffu3Yuamho8/fTTnrVz8+bNiSp2WPAl//qb28N9p4HkCgC46qqr8K9//QsvvfQSdu/ejZkzZ0ZcNr6IRP7prNx7/fXXY8qUKZBKpR3kH+44zc/Px9GjR1FeXu7pc3v27EFjY6Pnd0LJM77r2oEDB7w8gKMhnD1zOPhr286Ms3nz5nnWeZPJBIvF4mWc5js/R8Nvv/2G1157Deeddx4AoLy83CsBXDh0Vh/hSzhrfb9+/UL2pWgIZ93q27cv/vjjDy952W2xzCVW+wI3/fr1w2effealbF63bh0MBkNQHc+wYcPw2WefoaioCHJ5aBVfnz59YLfbsXXrVpxyyikAgIMHD3ZIuBcJ4ewHwm3n6dOn4/3330d+fj6kUqlXUuNhw4Zh9+7dndK3+dMbAR3nIofDgV27dmH8+PFBn8dHmcQE9eEyamtrMWHCBLz33nvYsWMHSktL8cknn2DhwoWYMmUKxo4dizFjxmDq1Kn48ccfUVpaiu+++84r8yuXuXPn4n//+x/mz5+P3bt3o6SkBB999BH+/e9/h12mW2+9FU1NTbj88suxefNmHDhwAO+++67HRXf+/PlYsGABXnzxRezfvx87d+7E4sWL8dxzz/HSJg8++CA2bdqEOXPmYMeOHdi7dy9ef/11z+JUVFSEDRs2oKysDDU1NX5PhO655x78/PPPePzxx9G3b1+sWbMGVVVVXpbhKpUK69evh8Viwfjx41FcXIyUlBQsX74cn3/+OUpLS7Fp0yY888wz+PbbbwEAd955J3744QeUlpZiy5Yt+OWXXzyLTmFhISQSCb7++mtUV1ejpaUFBoMB9957L+666y4sXboUhw4dwtatW/Hqq696ZWUXAj169IDdbsfLL7+Mw4cP491338Ubb7wRt9+//vrr8fTTT8PhcAS0iog33H60f/9+LF26FK+88krEHgaA6wR9ypQpmD17Nn7//Xds374dV111Fbp06YIpU6bEoPTC5qyzzsLIkSNx4YUX4ocffkBZWRnWrVuHf//73zHdkMpkMpSUlKCkpCTgQcGVV16J48eP46233vKyzmtra8Ott96K1atX48iRI1i7di02bdrkmQOKiorQ0tKCn3/+GTU1NTCbzSguLsaVV16JGTNmBJxXguG2fHriiScCbo6i4euvv0Z9fT1mzZqFAQMGeP2bNm0a3nnnHcybNw8ffvgh5s2bh5KSEuzcuRMLFy70PKOoqAi//vorjh8/HnDzcN9992HJkiV44403cODAATz33HP4/PPPoxpDnalLvOjZsyeOHj2KZcuW4dChQ3jppZfwxRdfeN1TVFSE0tJSbNu2DTU1NbBarR2ec+WVV0KtVmPmzJnYtWsXVq1ahdtuuw1XX321x1U1VoQaIxMmTMC7776L3377Dbt27cLMmTO97luyZAneeecd7Nq1y7OWaDQav94pkco4seK1116Dw+HAaaedhs8++wwHDhxASUkJXnrppQ5ulHzT2Tmis1xyySVQKBS48cYbceaZZ0asuP3ll19QWVkZUBF/33334ZlnnsFHH32Effv24YEHHsC2bdtwxx13eO7R6XSYMmUKHnnkEZSUlPhVWLvhc+2wWq2oqqrC8ePHsWXLFjz11FOYMmUKzj//fK8NqC89e/bE5s2b8cMPP2D//v145JFHsGnTpoh+O9BzQ80fiWL8+PH4/fffsW3bNi+jibFjx+Ktt97yyNJdu3aFUqn0yJIrVqzA448/nsCSh4Yv+beoqAg7duzAvn37UFNTA5vNFvKdhpIrACA1NRUXX3wx7rvvPpx99tnIz8/npd6REI3801m5d9KkSVAoFNi3bx+mTZsWcJyeddZZGDRoEK688kps2bIFGzduxIwZMzB27FiPS3koeWbChAl45ZVXsGXLFmzevBk33XST3zANkcLHntlf23ZmnI0bNw4DBgxAdnY2WlpaQAjBihUrAs7P0dCzZ0+8++67KCkpwYYNG3DllVdG7LkUC31EqLU+nL4UDeGsW3fccQcWLVqERYsWYf/+/Zg3bx52797d4Vmx2he4mTNnDsrLy3Hbbbdh7969+PLLLzFv3jzcfffdXuFAfLnllltQV1eHK664Ahs3bsThw4excuVKXHfddX4NK/r06YOzzjoLN9xwAzZu3IitW7fihhtu6JSnbDj7gXDb2d0HnnzySUybNs0rIsD999+P9evX45ZbbsG2bdtw4MABrFixIqBnuz+ysrKg0Wjw/fff48SJE2hsbATgmou++eYbfPPNN9i7dy/mzJkTluKdjzKJCeqVzHq9HiNGjMDzzz+PMWPGYMCAAXjkkUcwe/ZsvPLKKwCAzz77DKeeeiquuOIK9OvXD//6178CWkFNmjQJX3/9NX788UeceuqpOP300/Hcc89FFHogPT0dv/zyC1paWjB27FiccsopeOuttzyL7fXXX4+3334bS5YswcCBAzF27FgsWbLEy7WwMxQXF2PlypXYvn07TjvtNIwcORJffvml51Ts3nvvhUwmQ79+/TzuQb4MGzYMH3/8MZYtW4a5c+eivb0dWVlZXoumWq2G1WpFjx49PKeVXbt2xaBBg3DPPfegd+/e+Oc//4kNGzZ4/u5wOHDLLbegb9++OOecc9C7d2+89tprAFwW3I8++igeeOABZGdne9yNH3/8ccydOxcLFixA3759MWnSJHz11Ve8tRdfDBkyBM899xyeeeYZDBgwAO+//z4WLFgQt9+/4oorIJfLMX36dK+JPJFw+9GAAQMwd+5cPPbYY1HHi168eDFOOeUUnH/++Rg5ciQIIfj22295EWSTDYlEgm+//RZjxozBddddh+LiYlx++eUoKyuLuRLNaDTCaDQG/fvUqVOh1+u9XOpkMhlqa2sxY8YMFBcX49JLL8W5557r8boYNWoUbrrpJlx22WXIzMz0bGAWL16MGTNmBJxXgiGVSnHNNdfA4XAEVXpEyjvvvIOzzjoLJpOpw9+mTp2Kbdu2wWg04pNPPsGKFSswZMgQTJgwwcsd/LHHHkNZWRl69OgRMG72hRdeiBdffBH/+c9/0L9/f/z3v//F4sWLPbED41WXLVu28PZ7wZgyZQruuusu3HrrrRgyZAjWrVuHRx55pEOZzjnnHIwfPx6ZmZn48MMPOzxHq9Xihx9+QF1dHU499VRMmzYNZ555pkcuiDXBxsiDDz6IMWPG4Pzzz8d5552HCy+80CtOaUpKCt566y2MHj3aYz321VdfIT093e/zIpFxYkW3bt2wZcsWjB8/Hvfccw8GDBiAiRMn4ueff8brr78e89/vzBzRWbRaLS6//HLU19cHDXkRCJ1OF9TS+/bbb8c999yDe+65BwMHDsT333+PFStWoFevXl73XXnlldi+fTvOOOOMoK6dfK4d33//PXJzc1FUVIRzzjkHq1atwksvvYQvv/wyqLfSTTfdhIsvvhiXXXYZRowYgdraWi+r5mgJZ/5IFOPHj0dbWxt69uzp1c5jx45Fc3OzR5bOzMzEkiVL8Mknn6Bfv354+umn8X//938JLHlo+JJ/Z8+ejd69e3tida9duzbkOw0lV7iZNWsW2tvboxqjfNAZ+SdauVcqlaJnz54ghODJJ58MOE4lEgmWL1+O1NRUjBkzBmeddRa6d++Ojz76yPOscePGBZVnnn32WRQUFGDMmDGYPn067r33Xmi12k63Gx97Zn9t29lxdvfdd6OmpgYOhwPXXHNNyPk5UhYtWoT6+noMHToUV199NW6//XZkZWVF9IxY6CNCrfXh9KVoCGfduuyyyzB37lzcf//9OOWUU3DkyBHcfPPNHZ4Vq32Bmy5duuDbb7/Fxo0bMXjwYNx0002YNWtWSIPFvLw8rF27Fg6HA5MmTcKAAQNwxx13wGQyBVRO/+9//0N2djbGjBmDiy66CLNnz4bBYIhaDxDOfqBXr15htXOvXr1w6qmnYseOHR2s5QcNGoQ1a9bgwIEDOOOMMzB06FA88sgjfsOCBEIul+Oll17Cf//7X+Tl5XkO3q677jrMnDnTc7jRrVu3kFbMfJVJTEhIqGBWDAaDCsrLy1FUVIRNmzZ1cKlmMOLNxIkT0bdvX7z00kuJLgpmz56NEydOYMWKFYkuiih46KGH8M4772DdunVeylEGg8FgMITI+++/jzvuuAMVFRUeN2saYPJP7HjyySexbNky7Ny5M9FFYUSIWMfFsWPHUFBQgJ9++omXRJ0MeqHekpnBoB2bzYajR4/i/vvvx+mnn84UzIyEUldXh2XLluGXX37BLbfcktCyNDY24qeffsL7779PrbsT33z33Xd45ZVX8PXXXydcwfzUU09h+fLlHa6vXr0aEomE1ySPnWXcuHG8Wp8ngj179mD+/PkoKytLdFE8zJ8/PyGJXv/973+ja9eukMvlHitkf+9YIpFg/vz5cS9fuJSVlUEikWDJkiWJLoqoaGpqwtNPP40RI0YgJSUFCoUC2dnZOOecc/DBBx94hfjpzDtYsmQJJBIJryGy3M8U0jjvDGazGbt378aCBQtw4403UqNgZvJP7GhpacGmTZvw8ssv+00SxhAuYhsXv/zyC1asWIHS0lKsW7cOl19+OYqKirxyODAY0cAS/zEYlLN27VpPTOxPP/000cVhUM6wYcNQX1+PZ555Br17905oWaZMmYKNGzfixhtvxMSJExNaFjFQXl6Oa6+9Fh999BFOPfXURBcHTz31FKZNm9Yhy/mwYcOwfv169OvXLzEFEyl79uzBo48+inHjxsU12ajQ+PLLL/Hkk0/i4YcfxrnnnguVSgUAntBfDLo5cOAAzjnnHJw8eRI33HADHn74YaSmpqKyshI//PADrrvuOpSUlAg+zrJYWLhwIZ588kmMGTMGDz74YKKLEzeY/BM7br31Vnz44Ye48MILExZ+hREdYhsXNpsNDz30EA4fPgyDwYBRo0bh/fffpzKMJINfmJKZwaCccePGgUXNYQgFIVk/CcmSNRkxm81eMRULCgpQVVWVwBK5aGtrC5oAx2g04vTTT49jiRg0sWvXLgDoECOTHWp0nra2NqjV6oRYp/OB3W7HhRdeiLq6OmzcuNEr+RwAXHrppZg7dy62bt2aoBLSx/z58wXtTRArmPwTO5YsWcK8P5IUsY2LSZMmYdKkSYkuBkOEsHAZDAaDwWAwOoU77MCWLVswbdo0pKamesJhEELw2muvYciQIdBoNEhNTcW0adNw+PBhr2e4M67/9ttvOP3006HRaNClSxc88sgjHRLRPfrooxgxYgTS0tJgNBoxbNgwvPPOOx0OzIqKinD++efj888/x9ChQ6FWq/Hoo49CIpGgtbUVS5cuhUQigUQi8YQqCBQuY8WKFRg5ciS0Wi0MBgMmTpyI9evX+22H3bt344orroDJZEJ2djauu+46T+bqYBBCsHDhQhQWFkKtVmPYsGH47rvv/N7b1NSEe++9F926dYNSqUSXLl1w5513orW11eu+Tz75BCNGjIDJZIJWq0X37t3Dsp6SSCS49dZb8e6776Jv377QarUYPHgwvv766w73/v777zjzzDNhMBig1WoxatQofPPNN56/L1myBJdccgkAVwIzd5tzN9ruGIBGoxFarRajR4/Gzz//7PU71dXVuOGGG1BQUACVSoXMzEyMHj0aP/30U8j6fPPNNxgyZAhUKhW6desWMElTuP1169atOP/885GVlQWVSoW8vDxMnjwZx44dC1iGoqIiT/Ke7Oxsr3AY4YREcYci+OWXXzB79mykp6fDaDRixowZaG1tRVVVFS699FKkpKQgNzcX9957L2w2m9czXn/9dQwePBh6vR4GgwF9+vTBQw89FKL1gIqKClx66aUwGAwwmUy47LLL/B4aBarHNddcE5YFu9VqxT333IOcnBxotVqMGTMGf/75J4qKiryS/rrbYuXKlbjuuuuQmZkJrVYLq9UKp9OJhQsXok+fPlCpVMjKysKMGTM6vBvfZwaqg3tOeO+993D33XcjJycHGo0GY8eO9avw3bx5M/75z38iLS0NarUaQ4cOxccffxyy7l988QX27NmDhx9+uIOC2U1hYWEH7wt/hBqTXOrr63HttdciLS0NOp0OF1xwQYf+7a/VrgAA+opJREFU/uOPP2LKlCnIz8+HWq1Gz549ceONN6KmpiZkWRgMBoPBYNADUzIzGAwGg8HghYsvvhg9e/bEJ598gjfeeAMAcOONN+LOO+/EWWedheXLl+O1117D7t27MWrUKJw4ccLr+1VVVbj88stx5ZVX4ssvv8S0adPwxBNP4I477vC6r6ysDDfeeCM+/vhjfP7557j44otx2223+XUh37JlC+677z7cfvvt+P777zF16lSsX78eGo0G5513HtavX4/169cHDVfwwQcfYMqUKTAajfjwww/xzjvvoL6+HuPGjcPvv//e4f6pU6eiuLgYn332GR544AF88MEHuOuuu0K236OPPor7778fEydOxPLly3HzzTdj9uzZ2Ldvn9d9ZrMZY8eOxdKlS3H77bfju+++w/33348lS5bgn//8p0fZvn79elx22WXo3r07li1bhm+++QZz586F3W4PWRbApZh95ZVX8Nhjj+Gzzz5DWloaLrroIi8F1Jo1azBhwgQ0NjbinXfewYcffgiDwYALLrjAkxF+8uTJeOqppwAAr776qqfNJ0+eDAB47733cPbZZ8NoNGLp0qX4+OOPkZaWhkmTJnkpmq+++mosX74cc+fOxcqVK/H222/jrLPOQm1tbdB6/Pzzz5gyZQoMBgOWLVuG//znP/j444+xePHiDveG019bW1sxceJEnDhxAq+++ip+/PFHvPDCC+jatSuam5sDluOLL77ArFmzAADff/891q9fj+uvvz6cV+HF9ddfD5PJhGXLluHf//43PvjgA8yePRuTJ0/G4MGD8emnn2LmzJl49tln8fLLL3u+t2zZMsyZMwdjx47FF198geXLl+Ouu+7qcDDhS1tbG8466yysXLkSCxYswCeffIKcnBxcdtllEZc9FNdeey1eeOEFXHvttfjyyy8xdepUXHTRRWhoaPB7/3XXXQeFQoF3330Xn376KRQKBW6++WbPOFqxYgUef/xxfP/99xg1alSnlKJut+K3334bb7/9NioqKjBu3Div8bBq1SqMHj0aDQ0NeOONN/Dll19iyJAhuOyyy0JaL/74448AgH/+859RlxEIb0xymTVrFqRSKT744AO88MIL2LhxI8aNG+fV5ocOHcLIkSPx+uuvY+XKlZg7dy42bNiAf/zjHx0OMhgMBoPBYFAMYTAYDAaDwegE8+bNIwDI3Llzva6vX7+eACDPPvus1/Xy8nKi0WjIv/71L8+1sWPHEgDkyy+/9Lp39uzZRCqVkiNHjvj9bYfDQWw2G3nsscdIeno6cTqdnr8VFhYSmUxG9u3b1+F7Op2OzJw5s8P1VatWEQBk1apVnufn5eWRgQMHEofD4bmvubmZZGVlkVGjRnVoh4ULF3o9c86cOUStVnuVzZf6+nqiVqvJRRdd5HV97dq1BAAZO3as59qCBQuIVColmzZt8rr3008/JQDIt99+Swgh5P/+7/8IANLQ0BDwdwMBgGRnZ5OmpibPtaqqKiKVSsmCBQs8104//XSSlZVFmpubPdfsdjsZMGAAyc/P99T5k08+8WpXN62trSQtLY1ccMEFXtcdDgcZPHgwOe200zzX9Ho9ufPOOyOuy4gRI0heXh5pa2vzXGtqaiJpaWmEKwqH2183b95MAJDly5dHXBZ3H6murva6PnbsWK93TIjrHcybN8/zefHixQQAue2227zuu/DCCwkA8txzz3ldHzJkCBk2bJjn86233kpSUlIiLvPrr78ecGwCIIsXLw5aD0IImTlzJiksLAz6O7t37yYAyP333+91/cMPPyQAvMaruy1mzJjhdW9JSQkBQObMmeN1fcOGDQQAeeihhzzXCgsL/c4BvnVwzwnDhg3zGsNlZWVEoVCQ66+/3nOtT58+ZOjQocRms3k98/zzzye5ublec4gv55xzDgFALBaL13Wn00lsNpvnn91u9/yttLS0wzsId0y62zDQnPPEE0/4Lae7PEeOHOnQL9zPLC0tDVhPBoPBYDAY4oVZMjMYDAaDweCFqVOnen3++uuvIZFIcNVVV8Fut3v+5eTkYPDgwR1CUhgMhg5WfNOnT4fT6cSvv/7qufbLL7/grLPOgslkgkwmg0KhwNy5c1FbW4uTJ096fX/QoEEoLi6Ouk779u1DRUUFrr76akilf4tNer0eU6dOxR9//AGz2ez1Hd86DBo0CBaLpUPZuKxfvx4WiwVXXnml1/VRo0ahsLDQ69rXX3+NAQMGYMiQIV7tOmnSJK9QH+4Ei5deeik+/vhjHD9+PKK6jx8/HgaDwfM5OzsbWVlZOHLkCACXRe+GDRswbdo06PV6z30ymQxXX301jh071sEK25d169ahrq4OM2fO9KqL0+nEOeecg02bNnksbU877TQsWbIETzzxBP7444+wLChbW1uxadMmXHzxxVCr1Z7rbstOLuH21549eyI1NRX3338/3njjDezZsydkOfjk/PPP9/rsDq3gtgznXne/K8DVfg0NDbjiiivw5Zdfhm3Vu2rVqoBjk0/WrFkDwNVfuUybNg1yuf80Mr5zzqpVqwCgQxiM0047DX379u0QgiUSpk+f7hXvubCwEKNGjfL85sGDB7F3717PGOb2ofPOOw+VlZUhx4M/XnzxRSgUCs+/wYMHB7w3mjEZaM5x1wsATp48iZtuugkFBQWQy+VQKBSeeamkpCTiOjEYDAaDwRAnTMnMYDAYDAaDF3Jzc70+nzhxAoQQZGdneylJFAoF/vjjjw5Kruzs7A7PzMnJAQBPSISNGzfi7LPPBgC89dZbWLt2LTZt2oSHH34YgMu1P1iZIsX9u/6ek5eXB6fTifr6eq/r6enpXp9VKpXfsvn7HXd9ufheO3HiBHbs2NGhTQ0GAwghnnYdM2YMli9fDrvdjhkzZiA/Px8DBgzAhx9+GKrafuvhrou7HvX19SCEBGwbbr0C4Q5BMW3atA71eeaZZ0AIQV1dHQDgo48+wsyZM/H2229j5MiRSEtLw4wZM4ImlKyvr4fT6Qy7XcPpryaTCWvWrMGQIUPw0EMPoX///sjLy8O8efPiEjogLS3N67NSqQx43WKxeD5fffXVWLRoEY4cOYKpU6ciKysLI0aM8IRpCERtbW3QsckX7r7i+1tyudxvXwQ6jstQ4zVUfwxGoD7kfqa7L997770d+s+cOXMAIKhiv2vXrgDgdTAAuJTbmzZtwqZNmzBs2LCgZYxmTIaql9PpxNlnn43PP/8c//rXv/Dzzz9j48aN+OOPPwAEn9cYDAaDwWDQhX+zAAaDwWAwGIwI4Vr5AUBGRgYkEgl+++03j6KVi+813xjNADwKRLeSadmyZVAoFPj666+9LFOXL18eVpkixf27lZWVHf5WUVEBqVSK1NTUTv0G93f8KUyrqqq8kqZlZGRAo9Fg0aJFfp+VkZHh+f+UKVMwZcoUWK1W/PHHH1iwYAGmT5+OoqIijBw5slNlTk1NhVQqDdg2vmUJVtaXX34Zp59+ut973ErHjIwMvPDCC3jhhRdw9OhRrFixAg888ABOnjyJ77//PmAZJRJJwHb1LUu4/XXgwIFYtmwZCCHYsWMHlixZgsceewwajQYPPPBA0DonkmuvvRbXXnstWltb8euvv2LevHk4//zzsX///g4W827S09OxcePGDtf9talarfab5DIcq2n3GDhx4gS6dOniuW632wMqh33HN3e85ufne/2toqLCqz+q1WpYrVa/ZfXXbwP1Ifdvur/z4IMP4uKLL/Zb3t69e/u9DgATJ07Em2++iRUrVuDee+/1XM/KykJWVhYAlwW+vzK7iWZMBqpXz549AQC7du3C9u3bsWTJEsycOdNzz8GDBwOWg8FgMBgMBp0wS2YGg8FgMBgx4fzzzwchBMePH8fw4cM7/Bs4cKDX/c3NzVixYoXXtQ8++ABSqRRjxowB4FIqyeVyyGQyzz1tbW149913Iyob1yI3GL1790aXLl3wwQcfeBLqAS639M8++wwjR46EVquN6Lf9cfrpp0OtVuP999/3ur5u3boOlo3nn38+Dh06hPT0dL/tylVIu1GpVBg7diyeeeYZAMDWrVs7XWadTocRI0bg888/92pLp9OJ9957D/n5+Z5QJYGsuUePHo2UlBTs2bPHb12GDx/usdTl0rVrV9x6662YOHEitmzZErSMp512Gj7//HMvq97m5mZ89dVXXvdG2l8BV38cPHgwnn/+eaSkpAQti5DQ6XQ499xz8fDDD6O9vR27d+8OeO/48eMDjk1fioqKsH//fi9FaG1tLdatWxeyTO4x7puc7tNPPw07WeWECRMAuJJJctm0aRNKSkpw5plnepV1x44dXvft378/YEiLDz/80GsOOHLkCNatW4dx48YBcM0VvXr1wvbt2wP2ZW74GV8uuugi9OvXD0899RT27t0bVn19iWRMugk057jr5Vbk+x68/Pe//42qjAwGg8FgMMQLs2RmMBgMBoMRE0aPHo0bbrgB1157LTZv3owxY8ZAp9OhsrISv//+OwYOHIibb77Zc396ejpuvvlmHD16FMXFxfj222/x1ltv4eabb/a4kk+ePBnPPfccpk+fjhtuuAG1tbX4v//7P7+Wp8EYOHAgVq9eja+++gq5ubkwGAx+rQylUikWLlyIK6+8Eueffz5uvPFGWK1W/Oc//0FDQwOefvrpzjXSX6SmpuLee+/FE088geuvvx6XXHIJysvLMX/+/A7u7HfeeSc+++wzjBkzBnfddRcGDRoEp9OJo0ePYuXKlbjnnnswYsQIzJ07F8eOHcOZZ56J/Px8NDQ0eOK7jh07lpdyL1iwABMnTsT48eNx7733QqlU4rXXXsOuXbvw4YcfehRUAwYMAAC8+eabMBgMUKvV6NatG9LT0/Hyyy9j5syZqKurw7Rp05CVlYXq6mps374d1dXVeP3119HY2Ijx48dj+vTp6NOnDwwGAzZt2oTvv/8+oNWom8cffxznnHMOJk6ciHvuuQcOhwPPPPMMdDqdJxQHEH5//frrr/Haa6/hwgsvRPfu3UEIweeff46GhgZMnDiRl3aNBbNnz4ZGo8Ho0aORm5uLqqoqLFiwACaTyRO/2x8zZszA888/jxkzZuDJJ59Er1698O233+KHH37ocO/VV1+N//73v7jqqqswe/Zs1NbWYuHChTAajSHL179/f1xxxRV49tlnIZPJMGHCBOzevRvPPvssTCaTV0z0QPTu3Rs33HADXn75ZUilUpx77rkoKyvDI488goKCAtx1111eZb3qqqswZ84cTJ06FUeOHMHChQuRmZnp99knT57ERRddhNmzZ6OxsRHz5s2DWq3Ggw8+6Lnnv//9L84991xMmjQJ11xzDbp06YK6ujqUlJRgy5Yt+OSTTwKWXSaTYfny5Zg0aRJOO+00zJ49G+PGjUNqaioaGhqwYcMGbN++3RODOxDhjkk3mzdv9ppzHn74YXTp0sUT4qNPnz7o0aMHHnjgARBCkJaWhq+++ipkmBUGg8FgMBgUkpB0gwwGg8FgMETDvHnzCABSXV3t9++LFi0iI0aMIDqdjmg0GtKjRw8yY8YMsnnzZs89Y8eOJf379yerV68mw4cPJyqViuTm5pKHHnqI2Gy2Ds/r3bs3UalUpHv37mTBggXknXfeIQBIaWmp577CwkIyefJkv2Xatm0bGT16NNFqtQQAGTt2LCGEkFWrVhEAZNWqVV73L1++nIwYMYKo1Wqi0+nImWeeSdauXRtWOyxevLhD2fzhdDrJggULSEFBAVEqlWTQoEHkq6++ImPHjvWUz01LSwv597//TXr37k2USiUxmUxk4MCB5K677iJVVVWEEEK+/vprcu6555IuXboQpVJJsrKyyHnnnUd+++23oOUghBAA5JZbbulwvbCwkMycOdPr2m+//UYmTJjgeb+nn346+eqrrzp894UXXiDdunUjMpmMACCLFy/2/G3NmjVk8uTJJC0tjSgUCtKlSxcyefJk8sknnxBCCLFYLOSmm24igwYNIkajkWg0GtK7d28yb9480traGrI+K1asIIMGDSJKpZJ07dqVPP3005735Uuo/rp3715yxRVXkB49ehCNRkNMJhM57bTTyJIlS0KWI1Af8feOAZB58+Z5Prv70aZNm8J65syZM4lOp/N8Xrp0KRk/fjzJzs4mSqWS5OXlkUsvvZTs2LEjZLmPHTtGpk6dSvR6PTEYDGTq1Klk3bp1Hd6j+3f69u1L1Go16devH/noo4/IzJkzSWFhYcjfsVgs5O677yZZWVlErVaT008/naxfv56YTCZy1113hWwLQghxOBzkmWeeIcXFxUShUJCMjAxy1VVXkfLycq/7nE4nWbhwIenevTtRq9Vk+PDh5JdffunwLtxzwrvvvktuv/12kpmZSVQqFTnjjDO85jA327dvJ5deeinJysoiCoWC5OTkkAkTJpA33ngjZP0JIaSxsZE89dRT5NRTTyVGo5HI5XKSlZVFJk6cSF599VWv/l5aWur3HYQzJt1tuHLlSnL11VeTlJQUotFoyHnnnUcOHDjgde+ePXvIxIkTicFgIKmpqeSSSy4hR48eDdhHQ811DAaDwWAwxImEEI7fF4PBYDAYDEYCGDduHGpqarBr165EF4XBYAiIdevWYfTo0Xj//fcxffr0uP/+6tWrMX78eHzyySeYNm1a3H+fwWAwGAwGI1lg4TIYDAaDwWAwGAxGwvnxxx+xfv16nHLKKdBoNNi+fTuefvpp9OrVK2RYFAaDwWAwGAxGYmFKZgaDwWAwGAwGg5FwjEYjVq5ciRdeeAHNzc3IyMjAueeeiwULFkCtVie6eAwGg8FgMBiMILBwGQwGg8FgMBgMBoPBYDAYDAaDwYia0GmaGQwGg8FgMBgMBoPBYDAYDAaDwQgAUzIzGAwGg8FgMBgMBoPBYDAYDAYjapiSmcFgMBgMBoPBYDAYDAaDwWAwGFET98R/TqcTFRUVMBgMkEgk8f55BoPBYDAYDAaDwWAwGAwGg8FghAEhBM3NzcjLy4NUGtheOe5K5oqKChQUFMT7ZxkMBoPBYDAYDAaDwWAwGAwGgxEF5eXlyM/PD/j3uCuZDQYDAFfBjEZjvH+ewWAwGAwGg8FgMBgMBoPBYDAYYdDU1ISCggKPTjcQcVcyu0NkGI1GpmRmMBgMBoPBYDAYDAaDwWAwGAyBEyrsMUv8x2AwGAwGg8FgMBgMBoPBYDAYjKhhSmYGg8FgMBgMBoPBYDAYDAaDwWBETURK5vnz50MikXj9y8nJiVXZGAwGg8FgMBgMBoPBYDAYDAaDIXAijsncv39//PTTT57PMpmM1wIxGAwGg8FgMBgMBoPBYDAYDAYjeYhYySyXy5n1MoPBYDAYDAaDwWAwGAwGg8FgMABEoWQ+cOAA8vLyoFKpMGLECDz11FPo3r17LMpGPeZ2e8yerVVG/OoTQqzagPb6A8nRBrTXH2BjgPUB1gdY/dkYYH2A7j5Ae/0BNgZYH2B9gNWfjQHWB+juA7TXP5mQEEJIuDd/9913MJvNKC4uxokTJ/DEE09g79692L17N9LT0/1+x2q1wmq1ej43NTWhoKAAjY2NMBqNna+BSCGEoNuD38bs+YefOg9SqSRmz+eLoge+iclzy56eHJPn8k2s6g8kRxvQXn+A7jFgsTnQ55HvY/b8fU+cA5Vc+CGfWB+ITR/YOf9sGNSKmDybT2idB51Ogta/NhQD56+MyW/snH82JBIJ9Cphby5o7QMOJ4G53R6z9w+4+oBCJoVaIYy1wNxuh8PZcWsWyzHgi1QigU5gY4K2MdBitcN3ix6vPqCUSwUnG7W1O9B3buxkAb1KDolE2Pti2saAP2iRhy02B2wOZ4frsV4LfdEp5YLSF7ExkHiamppgMplC6nIjkiDOPfdcz/8HDhyIkSNHokePHli6dCnuvvtuv99ZsGABHn300Uh+hhEHnIRACuFMGgwGg+FLWW1rTJ9f3WxFfqo2pr/B6Byx7ANbjzZgTHFmzJ7P6BwSCbDlaANs9o4bLb7YcLgOqToFTilMi9lvMDrHlqMNMX3+hsN1GNo1RTBK5j0VTWgw2+L2exsO13W4plPJMbKHf+MhRnzYXt6AtnZHXH7Ltw/0zjGgIE1YslFJVVPMnr3hcB3G98mCjG2LGQJhd0UT6lvb4/qb/taCwQUpyDSo4loOhjiIyJLZHxMnTkTPnj3x+uuv+/07s2SOnrUHq9HQGlrQtNoduPuTHQCA5y4ZFPL0WaeWY1zvLF7KGGu+31UJhyN4F420/katAmf0Sg7FQnmdGTvKG4LeE2n9NUoZTu+RnhRuIW63mIoGC/ZVBhYww22DNL0SgwtSACSPW8y+ymYcPNkc9J5I+0Bhpg4D8ky8lTFWHKs3Y3sYCoZI6+/mH70yYdIK35K1srENW8rqg94TSRsYtQqcUpiaFGPgaK0ZO481hLwvmj6QbVJjeJHwlYur9p6E2RraRTDSNlAqpJjYT9g5NnZXNKKywQKrLbSyJZo+oFLIUJxtQNd0YSlUfDG321Fa04qy6sCHLpHW/x/FGVDIpIKfB47UtmLXscaw7hXDPLDreCOqGi0drsdyDPiSYVBhyF+yklA4UtOKXceD94No6j+iRxoy9Gpeysgn28sbUN1s9boWrz5wSmEqUnXKCEobe/48Uoeqho7jwpdo6z+2dyYUMmmnyxlLWiw2/H6whtd9sVQKjOqZAZNGWO87EOZ2O3Yea0SNz9jgEkn9izJ16JahE9Q6aHc4sWZ/Nfxp6GI1BwD+14IuqRr0zRWOvq6u1Yo/DtX6bRsukbZBcY4BvbINfBVT1MTEktkXq9WKkpISnHHGGQHvUalUUKnYCUg09MkxYmuEFhwquczvJMFFSJNFKIxqBcwRnOSHU3+TRvhKJTf5qRqU15nDboNw6t8zyyCoxTQY7nJmGVUoqwlzkQzSBpkGddLU3U2vbD2arbawLZtC9QG9Wo6+OckxB+QY1TiolsMeQqDmEs4YAACDWp4UCmYAyDVpUJTZjsowNlhA8DaQSIBB+SlJMw6yjCqolbKQAiWXcPtAjkl4igV/5KaocayuLaLvhNMGyVD/XlkG1Idx2O5LuH0gRatAfqommqLFFa1SDovNEVadgPDqb7U7k0KxUJiugwQSHDjZzPs8kGlQoX+esNbDLikav0rmcN+95/4wx4A/8lKENzcUpGlRXt8GSxhKFiC8+qfrlYJUMANAYbq2g5I5Hn3AqFEgRYCykVIWeV3Crb9UCsgFFBIgEHq1AgPzU1BSEb5Vd6g26JWtT4p1wI1WKcfgghRsKK0Ly8spWP31ajn65BghE9i7rzfbAq518VwHAMTdmjoUaToVeucaURrkwN2XUG1gUMvRI1PPR/EYHCI6srv33nuxZs0alJaWYsOGDZg2bRqampowc+bMWJWPatL1KmQZ+VXQp+qUyDYKU6Dyh0bJv/uiNgbPjBUSiQQ9svib+NQKWVJsqH0xqOSQ8+DHliYwy4xwkEolGNDFBJWi8xYWCrkUg/JNghOoAiGXSdEtQxeTZ/fkcVzFg97ZBl7mrh6Z+qQ6aFMrZDFZsxRyKXJNyTEXZupjc1CfDC6QSrkUgwpMkMXAj1mtkGFgvklQ8QYD4XASNLbxG0IhGuV9ouiarsXQrqlQyvmxNJRIgO6ZOgzKN0EuMOvFVJ0SqbrEzdF6tTxmc05nkEol6JHFnzwgkYBX+ZpvUrTKhBwEFmfrBRmbWKuK3d5NqxR+PGY3XVI0vOkGUnVKdBVYWJRwUCtkGNjFBGknpm6FXIrB+SmC3A81tglHsWtud4R9sBcvumfoeDsIk8kkSSMHJhsRDc9jx47hiiuuQO/evXHxxRdDqVTijz/+QGFhYazKRz19c428KUVVCikGdBGWxUYoUrT8KwWT6cQWALKNat6ULP3zjEk5kUokkk63gUohRaoArTPCQa2QYXhhWqdiRirl0qQJkcCla5qW9w13l1QN0gW4iQ6GXCbF0K6pnTpsyE/ToChGSvtY0jNLz7uSsThbL8jNhT/SdEreN9gqhVSQiiR/GNUKDOuaCgVPCkbApbAYXpQquORWgWgwt8PJc2jq2tbA7sZCJE2nxMge6Z1WvOnVcpzaLQ3dM4WpTAOAfrmxOVgJhVTqkhOF2i65Jg0yeDocK8rQwSjwxK99cgwxVa760itbH5N9Fx+kxPBwXIiW28Hon2fqtFxs1CgwON8k2LEeijSdEgO7pESlaHbvh2JhyMYHjW2hw6PFk2aLsMojkUgwuCAFenXn9rMyqQRDC5LHszPZiGhoLlu2DBUVFWhvb8fx48fx2WefoV+/frEqGwOAQibF4IKUTgubUqnLRTpZNlRu0ngWdiSS5BMmAKBPrqHTSWmKMnSCi7EWCXkpnbM6zDWpk1aYAlxW/cOLohOKVAqXQKUXWLb4cJBIJOifZ+LFkh1wKRiKkzTulkYpi1rZlmNSo3eS1lutkKEnj65saXpl0lgxA64xwLdFf2GaLqkOHE0aBYYXdu6QxY1Ro+j0oV28qTfzb9lktgrPQikUCpkUA7qYMKRrSsR9wW29fFpRmuCVixqlDP0SENquONsAg8Dbpl+usdPzgEmrQPckOHCVy6QYUpDC6wFbIHJT1ChMF26bpGiVnbJcDQbfe81YI5NKMDg/BcYoFe86lRxDClIE58URKZkGFQblR6ZoVsqlGCbw/VBLGDk44onQygO4ZIGhXVOiNsR06cVMgj1UEwPJPbtQgk4lx8AuJnRGP9Yv15RULtJujBo5b+6RgMs1SOiJHfzh2lgZo+4DKVoFemQKV3gMB5NGAUMnTi27pCSfS5gvaoUs4tN3pVyKYV1ToROwQBUKtUKGAV06n6hQJpMkVbgQf+hUcgyJ0MUvXa9Ev1zhWqeFQ36qhheLdplUkjQxybnkGNW8WbQla9gknUqO4YVpnfLuStUpMaxrCq9yRTyobYmN+2wslNfxIEOvwmnd0pCmD2+D6D5o7Z6pT5rDlWyjOq6eJ/lpGuSnCl9OUsql6N+JxMUymQQD8pLHglOrjHzNj5R0vVLw66JMKkFqDBRCUmlyhtKT/6Vki1S21yplGJqEa2AgMvQqDAhTRyKXSTC0a4qgFcztdmdYsabjSasAlcyAK9ZytB6e/fNMSefRmmyIY4ahgAy9Kuqg5EUZ2qRI8OMPiUTCa1zqrCSIQRmIFK0S3aPoAzKZ5K8FODkE6mDkRxk7LMOgEqxbVKSoFS5r1nAERJlMgmGFya1gdpOhV3V6w90v1ygKtyiTVhG20l2vlv8Vuy65x79EIkHfXGOnLZl6ZumTci6QSCS8xRHvlplcVsxcNEoZTilKjUrhnqZXYmgSWm+1250xc1eNlfI6HqjkMgwtSEG3EAfoqToFRnRLT0qLpR6ZOt5zs/gjTa9MKk+XNJ0ShenRyYN9c4xJtwaYtAoMzO+csVEgDEkkI8Qij0CKVpl0a4IbtzVnuF45Crkr7FoyefGEQ5ZBjX4hErhKpcDQrqmC99Roaxeed1GbgD2eNEqXojmSQ7jeOYakyk+WrCTnrEophenaiEM96FRydM8QbmKLcMg28DMRSCTJkegoGIVp2oituHpk6EUjUGQbVFFZc+Ql6SFLIDRKWUiBCnBtpoR8Yh8p3TN0USvMs4wqUQkVmQZVyBAyEgnQL8+YtBsoX7RKOQo6YWmnVcrQpZNhdxJJlkHdKW8OwNUGyT4fquQyV8KeCELoaJWypFGk+BJLa+M6gWWOjxSJRIIemXrkp/kf11qVDIPyk9dqTyKRoF+usdOxJ4Oh+WtsJJshQrcMXcTvNUWrSFqjmwy9iveExUq5KyRjssgIGTGwPEyW3ASBcHn6hefp2i83+Q5YwiXXpAkq43fPSI6k1xa78BS6QlR8c9Gr5OiVHd7cmK5XoiAJk10mI8mxqjAA/G3JFQl9cw1JuanikqJV8LJBSNEqky4mtS9SaWTWbBplcrpFB0Iuk0Z8UCCTSWIimCaaDL0q6GYpXZ+YzOSxRCqVoE9O5NZWUimSNg5zMHqFSF6Xl6IRfOzRSCnK0EVtzZxMrvKBCGW1GYqiDF3SKZP8oVPJw45ZK5EAgwpSkjJUFhBba2OXlbQtZs+PF72zDR3ik0okcMWzTdL37kYuk0Z8qBIu7riUydhGcpk04lj10XqECoXCdB2vh+WD8k1JZYSiVsg6FS7JH8mcq8ZNija04iw3RZ30hlah6J1j8CsfalWyqD0f4o3VJqxQGYBLTiCEJLoYQclP1cIUwhBTIkHEejRG9CSfVEE5OpU87LiUerU8Kd0DfZFI+FESJnOoDC4ZelXYSdCyjeqkV6r4kh5mDEY3aVql6NrATbDNhtgUzG5SdcqIrbqyDOqk2kiFi0ImDSpUiXFDoZBJka6LvF4yqUQU7ZGpV0Xdl+UyCXJEZM2fFWYYpAy9Kqk9OmpbrbF9fhKHzHAjkXTs2yatQhThkQCXwUAvnq1YAZd1n9Ddx4MRyZyulEuTMvG3L8U5el4SIXdJ1STlHjHaZHf+kMkk0InEsjeUQREN1puuMd6xT2fqVUlzuG4VoCUzAFgFFifaH6E831O0SlHuBYUKUzInIVlhho8Qi1IVADIiVCz6I1LlpFCRSiVhK1n4aDehEWnij1gkChEKwTZMKRrx1jvPFJl1fq5IFe4Agloqdza0glDJiGJtS9EqkjrhoxuJRILclOj6c65JI6oDN4lEguww4tUmc5icZost5pZNsVZixwtfV2g+lVFCID818pB5wdCp5Elj3RcItUIWdnz2VK0yaRRNwVDJZShK75xHi0wqSVqrbj7lGoNKLoo+AbjCiQVqG41SJjqvtkD4q2cyrQXtDmEqc20CLReXlBBGmGI4ZEwmmJI5CQk3i6ZKRKc1nT1tVymkorFoARB2+JBkjUMYDJVcGpG7fDQJopIFhzOw+5LdKXyBIFp0Eb7TWMazTDTtQawLbA5hu7dFizqKeU1M1gsZUVhyA+I5aOUiDUNB0NlkkYkkHlbGDWZbUmwgQ2G2eSdHNFuFaRHWGTqb/JZLN5GEzpGFWQcxHDK6yTGpO5UEMNOgStr9AZ9hD5M9hKIvigDvNBnD4USLv7Usmda3YDJ9IhFqubiQEEUUesgPsUHPrCMiwtlUue6LcUHiiFIu7VSyArGd4Ib7bsPtK8mERCKBOgLBUJWkgnQ4tFrtQf4mvg22m0gO0CQS8W0kuJjbg/WBwH9LZuRRaA3lIloQjRp5VIrTlCSy5gmXYAdtkdwjVGpaYm9lTEjyJwAEOirkG9tsSf3u/ZGhV/ESk1Yhl4blBZAMhPuKnSJSMKgVsk5ZZyZznhIFj7HJFXLxyAWAay73f108fT8U/mRis8AT13ERqnGIUMvFpc0W/D23tQtfUS4mxKt9ETHhZvkUejbQSOmMYB2p5aPQCTWReu4TWR9wE4n1jZisV3ypbLQE/FtVU+C/JTuRKA4IAZwiUzS4Mbfb0WAOnLQrWP9IZqJxJxSqC2I0SCQSaBSRWeerFFLIRWjNVBuGcjRZYw63251obItPUr7q5uQOmdFiteOEz5pnsztRXmdOUIliRxof4eN04ggd4XSSoAetXJot4jp01XTCOyeZPfz47LcSJP8Y4BIoiWtru120cjAXi82B+taObVDVaEkaRbtQra6TwZL5ZHPwPU9Ni1V0B89CRnw7DgoIV1BqEZkVW2csmcVmyRjuuxVbH2D8TbvdGVQxUNtihSXMw4hkI1IhTEwKRi4VDW1B/y7WPhBNnSwCzNjdGcINm+W5X2RrIOA6ZGkJQx6qabEm5Qa7psUa0DItNr+VfG0EuKz09p9o9ttWpbWtopsD+ci34Bu/OllpstjCHiPmdrtgFTjR0BkvPWUSHzjyOU8RJOec549Wqx32ANamTqf4Dln8cTyATNxud6I6Dl5BfCBUZa7Q91HtdmdIzy+HkyT9gXoykbyrDMU0mMOzyqk325J20+CPzrg7iykeVbvdGXaswXhZQcWbSOINJ4OLTzSU15uDnsgSApTVtsaxRPEj0jAQYgwbYXM4UV4fXMlMCHCkVnyWfNFslgJZ+CQr4cYh9dwvniXQw/EQ/d+N3UFwIoSFixCJ52bI7iCoD+IVIWSO1behLoC1usNBsLuiSVSysDrCAyb/zxDHoVNNBF4KhAD1IggL40Y8PToy+JTpbXbxtGKo9SJZlKzRYncE91xJBlnY7nAK1tJWqMpvN8cb2hCOauCoCL2bhIoItx3ixmJzhB1byGZ3isySVVxuTdESieI4mCt9MhPotN7/vcJeGKPB6SRhuQFXNLSJynLHTaTzmhjjU1c0tMERxjgQYx+IRmFsdxDRWTTSjNNJUBFBOJhQVv9Cw+EkcY+TnIwWPhabAwdPtgS9p761PaK+InT4SNiWrEnffIl0jESilBY6nVFGCVWRFQ58KrvaHeKRCUJZccYjvn8iqWy0BN0bNpptaBT4nljI1sJWu3DHCiEkbKODpjabaA3whIY4pAyKiFRpKCYlY6cEKhFZsUQyOVpsDkEvDNFgi/Ck1yLw09doONlsDUvR7nS6YpGJjXBc5Lk0W8UzD7oJ5Bboi8NJRNUHnE6C1jBjcPrSJCJr5kjXNAHvXaKiztwOWwRze32rLakOGWoTEDvwZHPyxK10c/BkS1jtdOhki2gO2/iIIyuCcMywOZwRHzjWh+kJmgx0pj8n81iw8LinEUsYLbsjdPz+FotddPtBLuEcJIcrNycKIfdHIZet3hyZfCemPZGQYUrmJKMlQmWJmGIwdWZxtCbR5jIUkVpxRqqQEzqRKgrE9O7dRGKRIEYXOXOE71RsCTDN7fawQ+YA4rJgsdgdYbnE+SOSNhM6kXhzuO4X7gYhGqKx8k0mBdOJpviPWavNiaa25JEXrHZH2JvFdruzQ2JARnLTYrFHHLO8rd2R1ApWLp0JGyFki8lQ8CnPWWyOpIzX70uLNbyxkEzzeyRY7Y6w9B1Cl4XbBLxf5fNwh2/qWiN7r7UC7wdigSmZk4xIT5LEdGrZmdAfYnKXj1jJKjJL3kgXYSEv2tESyVgQk2IN+CtmWYSbK7GNgUjns3BDLCUDndlgCllIjpRI13Yx1R2Irk8nixzgcJKEbYaTKXZ1pC6vYvHsiyQnRSDEoFiLVrZLJo+GYHRGWR7pIaWQiNaTyR+EiGOPEK5uQEw6AS7h7nPa7U5BH7gL2SDG4SCC7T+RynZtNkfSeW0lI0zJnGRE6j6ZzHG3uESS7M4fDW3JY8EUikjfaTILk/6IdBEWk4LNTSRro1NkC6k9ijlNLJZLbiIVjsTUBzpjvSWWJD8OJ4E1wgNnp1M8yhUguj6dLJuKRITKcHOiKYlCZiRJMfmGD5kumS1Z3UTbDmKRiTszRyRrGzidhHdFnBgSQ4e7HvJwPiVIIunNQlaLmHk8QIkFQlWCRyoPEhLZPpoRHUzJnGRIIwykJhFD4DUAtRG6QvhitTlFE48z0jcqki7gIdITSzEIkL5olOFnhtdGcG8yEI1gIDZZQh3hO9UoxNMHOhNfXyyx+aP16hHTXKiKInGZSp4c4yARoTLcWG2hY3sKBaNGEdH9pgjvFyp8KIj5TJ6WKKRR7mDFIhNHc+DuJlnXwuYww0JEQpMIQgoqZOENBoVcJJ3fh3BlXLlMIuikp0L3tmoVqJI5UtlOIZdCKhXnWBASwh1pDL/IZZENCmWYC4/QqWjovAunWAK9Rzoxim0ijXQDbHcQwZ8OR0qqNvzNcopWGcOSJAnJuZ8KiF4phyyCtSAlgv4idDpjZSkWi+5oM6Q3JInyMByM6sj7tFEjj0FJ+MXucCY8bmRVksQuVitkyDCowrpXLpMg26iOcYniAx/WZGLwapBHqWUOVyEndBydMEsVcsiAYES79gV9pgg8XcM1JtEqhL8GRoNGKQvL+CZVwPshp1P4e1Wh5niKVLYzqsU5DoSGOFZaiojUekelSP5X3GyxoT6KJD++HG9oE4XbvCLCgwaFiJTM7XZnVNZ49SKJxegmks1ytjG8TTgjeZBKJcjUh/9eMw3iUK4AzMUNiN6zJ5pkeUIlXR/ZZlEmk0SlmI43NS3tCQ9zdrLJmjQhM3pl6cOyTO2WoRO0BVskdCY/iRsxJAVXR7m/icYLQmjYHc5OhT7oTNipRFIXg+StjW22hM+5nUWrlEEWYq8nkQB6ESvXwtnr5JiEKwu3tvNvpc83LVZh7qUzItgPRXM/IzqSf6WljEhP4OUiUDAeONnCy3McDoIjta28PCuxRPhOk78LeIg2O7zYssqrFTKk6kIrTPRqOQxJoFiJhGiSHjmcJGmUJuES7kGDRikTjZs40DkX4WSNQ8nFYnNErSxuNNtEEzJDq5RHFDYoXadMCq8eIVgRt9udSXMgoVPJUZShC3qPQS1HQao2TiWKLYQQ1POgaGtosyV98j95FBbJEkl03xMa5k5aogvdYtIfNocTdZ0MnegPpxOobk6s90hnkUgk0KmCK5A1itCK6GQm16QJ+ne5TCJo5WIyHPwJtYxqhSyiA5TMMD2gGJ0j+Vdayoh0k5TsC8rJZgvqWvjb7BypNfNiBZJYItwYJPc+wovjDW1Rfa+upT0phepg5IQQqAAgV8Cn9tFijTKWZLTfEyrpOmVY4ZPEZsnemezWQs2MHQnH6s2dsnY5UmvmrzAJJk0XvjVzJPcmCpvDidoEh8pwk8i40JHSLV0XUMEikQD98oxJccAQDo1ttoiTfvrD4SCoTZKDhEDIogiuLJZ+0Flljyu2cXJtDqoaLTFLXFfRGN3eQkiECpmhDaGETnZ0KnnQOP3ZRrWgdSJCVeBysTv4T7zJF+EeIOhUcqhFlKdGyDAlc5IRaRy1tiSOu2axOVBS2czrMwkBdh1vTFrXKEJIxAtRc9Ir1V1UNLR1Kh7UgRP8WMQLhXCsU8Vkweom2tA5DSILmSKVSqAPY9MgNkv2zlhYWm3RhdsRCq1WO47WdU5JXNnYljSJ3UIRSULLZNhUnGy2CsZd9mSzJWksXaVSCbpn+rdmzjaqRTUH8nlIdLQuuT37otnfOBxEFGHzOuudl2yHDE4n6fTaF4y6lnbRrIs0Eyz/iNBzkzRZkqP/CbWc4Xq2ReIBx+gcTMmcZES6CMYiSUI8cDoJdh1vhC0G1octFjv2VfGrvI4XTRZ7xC7fyeL2Ggyr3dHpsCnVzVacFIArMl+Eo2BJBsVKJBBCorawqxSBpYov4cQYFUvyV8AVn9/cyezbyRo6x+kk2FPZ1GlLLkKAPRVNSXvQykUagSVjJPcmCiElJ7Y7CGpi4JoeK7IMKr/rXUGaOMJkAECDuZ1Xt/76VlvCk0x2hqYolYLJrkxstdp58fCMpdKWb47Vt8XcgvLgyeTcF7oJ5a1nTWKjs3AJti8SctJDQohgk+r50ixQJXO4ni3ReMAwokM8u08KqG9tj1iwaLbYcbJZOBuXcCDEtZmOpeVhRUMbSmuSy4qDEBKVENRotiWtYgVwJTjZXs7PgcPuiqak32C4CWeDFe0mTKiU1rRG7M3hpralPenmwmAQQsLqyw0i6QOEEOw/0flN4JFas2Dd/YJRUtXE26Fxq9WOXccbk85d2pfqCBRkQlemWe0ONMQgqVVnOJlEITMkEonfRNdiSPIGuEKp7K5o4v25eyqaol5TE4nN4YxaSVpW05q0c5/TSXjrB3Ut7Ulx+G5ut+NQdew9EetbbShPIsU7lxarPeT60WyxJ63hWbi0BgmL2CzQpHUA0NruSJqD/yaBKsPDlfHqzO1J46WV7IhD+qIAu8OJkqroBIt9Vc1oT6J4pPtPtMTFoufQyRYcq08egaK8rg31rdEtknurmpNyI+FwEuw43sibstThJNhW3pDULvNuwokhVyEgy7jO0mBu7/TBUEllco4Df1S3WMOKzVnZ0CYKgeponTnq+Y+Lw0mwu6IxqdrkwIlmVDbwO5arm60oqWxOWmVLk8UWUeicioY2QctBJ5uEEyrDTXWLNWk2vgD8hkHoTKJQoeB0Euw83hiTw7F2uzMpQ8gdPNkS9XhuMNuizu+RaA5Wt/BqPLC3slnQeWqcToKdx+LXPw+cbBaspWYgCCE4cKI5rPXjwMnmpJJ9IsHhJEE9PYRsbJVMfU6IxksWmyNsIyKb3YlKAfcFMcGUzEmA1e7An0fqo3YTttqc2HykLimUK/tPNMf1JHlvZXNSCJulNa2dsuKz2Z3YXFYvaGHSl3a7E1uO1vOa+BFwtcWmsrqoY/sKgdKa1rCUTjXNVhzgwfoz0VQ3W7H1aEOnlTDud59MAp0/Gs22sK2ZzO0ObD/WkNQbi6O1Zl5jqjeYbdh2rEHwihXnXwrxWCXrq2how84kVDA1W2zYerQhou/YHQRbjtYLNvmjEL0sXHFbk8OaubzO7FdG3n8ieQ9SgL8VzHzLQVwazDZsKxf+fAj87dFyvL5zcvu+quSQ/bkcONGMozyvBQ4nwZ9H6gUZZ5UQl9V2PBOiOZ3A9vLGpNgvA3/PD7Vhzg9u2ccugrjkXBxOgu3HGoIaXtS32gQbKjNZQmUALllKSOPDYnNgy5H6iELJ7atq4jX0FMM/TMkscJotNmwuq+/0Imu2OrCprE6wrjKEEOytauJdgAqHkoomwbpIOZwEJZVNONTJeMSAayLeXFYnmOz1wWix2mPaX+0Ogq3l9ahIsk2G00lwqLolov5wpNaMfVXJa71QXmfGDh4Vgq5Dt3rBu88HorbFii3l9XBEEJu9tqUd2441CNqS0x+uEEEtvITJ8KWupR1bj9YLtk1sDie2HWvg3YLZl5NNVmwVsPLVlwZzO/48Uh9V+KQWi911YB/EpTYRtNudgk1MmgwhM+pa23EgQCixupZ2HKpuSUpFs93hxPZjDXHZDNe3uuZDISfFc/wVKoKPfQIhLtn/cBL0DaeTYE9FU8wOG212J/48Ui+4/C0HTrYkxPrUYnNgW3mDoMcC8Jdy7Wh9xHN0XUu7INfBaGm3u+bJcA7iyuvM2FslvJwUyWQABginvC1Wt0wXmfzqdAI7jjUknQ4g2RBuFHTKcToJDte04khtK28ulG6L5oI0LXpk6iGTCiP4OSEEJZXNCR3s+6pcrkZd04WTJKa+tR0llU0RT57BsDsIth5tQF6KBr2y9VAIMCnY8YY27K9qjrkQ4HS64hHWm9vRJ8comPEQiPrWduytao4q1Ed5nRm1LVYU5xiQoVfFoHT8Y7E5UFLZFLaFRiQ4HATbjjagS6oGvbL0kAtwHPhisTlw4ET0m666lnasO1SDnll6dEnRQCLw5BcWmwO7K5pi6nHQYLZhQ2kt+ueZkKZTxux3IqXZYsOOY7Fxj/dHg9mGjaV1GNQlBSaBZmC3OZw4cKKl03KC2erAH4drUZSuQ1G6DlIBzPs1LcILleHGVTYiyPki3D5RVmNGXasNfXINMKqF2b99cSu64mnh1mC2YVNpHYZ0TYFWKaztYX1rO/ZUNvE+Jx6ubkVdazv65hqhUwmrzgDQ1u7ATh5DxgXC4SDYerQe3TP1KErXJny8H6puSYjRkZsWix3byhswtCBFcPKh00lwpM6MsprWqPdJzRY7/jhci65pOnTL0Al+/+MPQgiO1bfhUHUL7BEYXRyra0NtSzt6ZeuRZVDHsIThw+c+Px4kOq+J3eFEaU0rjtaZo5ad3Emwq5os6JNjENyaJwZYiwqQutZ27K1qijo8RjAIcbkeVzdbUZxtQKYhsQontzuUELKq7z/RDAch6JahS2g52u1OHKpu6bQ7YDAqGtpQ2+rqA9lGYSyydocTe6ua494XKhssaGqzY2C+CXoBbjJarXaU1rR2ul3M7Q5sO9qATIMK3TN1MAh4s13Z2IZ9Vc0RCY7RcLy+zbPBFJKSkYvd4UR5fVunNhR/P4tgb2UzKhos6JmlF2ydTzZbUFLZzEuyz1BYbU5sOVKPogwtumfoE650rGhow96qpohc//jAfQhdnG1AQZpwDlsJIahotODgyRbe+oPT6VIuVTVZUJyd+IM3Ibtt2h0EDWYbUgU0VzicBJWNbThc3Rq2J0JTm0uBmp+qRWG6FmqFLMaljJ5Gsw3bE+R5Ym53YGNpHQZ2MSFdAAfSNodLHj5WFzt52H3Y2D1Dj65p2oSvAW5ONluwp6Ip5nKQG0JcuWrqze3on2eESp6YMVJa04rS6sQnZnePwyEFqYJQwhLiijl88GQLL0pJp9OVBLOq0YIeWTrkGNUJP1wIB0IIav7yUIn2EK6t3YEd5Y1I07ehR6YeJk3i9kOECCv8RDi0Jai8hBCcaHKNAb7arK6l3XPgUpiuFaTxXbIiPI0KxbRa7ThwsgU1cdhwtLU7sL28Aak6JYqz9QlROAlJwezm0MkWSAAUJUDR7HQSHG+I/FQ2Wqw2J3Yea8QxnRm9shNr4dNksWHXscaEnea2Wu3YWFqL4mwD8lOFoWBpNNtQVtvKuwKiutmK6mYr0vVKFKXrBKU8aLXasbeqiZcEb+HS1u6K55VjUqNXtj5hGytf2u1OlNebUV5n5n0+aGqzYcuRepi0ChSl6xJ+2Oim3e7E/hPxP2gCXNaO1c3t6JdnTMiGw+kk2MdDrNHOQIjLq6exzYa+uYn17iCEoKrJgtLq1pitC2ar6+DNpFWge4YuIUo1p5OgziwsN3VfalqsglgnzO12HK9vw/GGtqjmREJcXj3H6s3I0KtQkKYV3EHb8YY27EvAIRMXu8OVILlXliFh3n2EuOXh1rgcNjqdrmSCFQ1tCff4sjuc2M+D10a0uJQudeiXa4y7bHC01sxLeEC+qG/9S9Gcn5Kwwwe3Yu1wTUtMjM8sNgd2H29CaXUrCjN0yDWqBXPQwsV9uHg0QPz9aKhraUddSx1StAp0TdMi06CKu6LdancK1pMpEPFWisd6DLgPXMrrzeiapkXXNKZs5gOmZBYANocTh6tbcaw+erP/aKlvbceGw3XIS9GgR5YurgqWksrEKBNCcfBkC2RSSVytuWJpvR6K+lYbNv7VB3pm6aGUx3diPVZvxv4TzQndVAGuRWZvZTPqW23ol5c4BUtNixVHaltjrmitbWlHbUs7TFoFCtO1yNTHX7hy4w4PdLSuNWH9oKrRgpoWK3pm6RN60GCxOXC0zozj9W0xDxnTaLZhu7kBerUcRek6ZBsT1weqm60oqWxKaIzkVqsdm8vqUJiuQ/eM+IVSsNod2F4ee5focKlqtKDZYsfQrilxt/j0bCaq+bHWCodGsyuRYIpWge6Z8bXwb2yzRRRfPRHUtrajV4J+2+kkqGm14nh9G2+hkwj5+7BVq5IhP0WLHJM67rKPd5kIDpxMbIgALoS4vPtarHb0zTXEdV1oNNuwtyq+Cd/cuD2+0vVK9MkxQqOM7/zXbLFhZwINLtzY7E5sL29AfpoGxVmGuKyFxxvaYpJ/obPUtbRj5/FGDMo3xXUcOJ0ElU0WHKmJ3UErF3O7AyUVfymb07XokqIRhLLZYnPg2F+Hi7E6cGow29BgboRGKUNBqhZ5Keq4hUkReuxvf9ji5l0RW+WyLw4HQWm1KwxHwV9eT0zZHD1MyZxAYuEGGi0VDW042WxBj0w98lNjH6+zvM4s6IDr+080Q6uUxdyyyWp3xVkVgrK9oqEN1X8p2fJMsXebcmUJbxFc0sUTTRaY2+0YXBA/BYvTSXCi2YKyGnNUMZc7Q6PZhh3mRmiVMnRN1yLPFF/Bssliw+7jTXGvtz/c4SRONlvRL9cYVwWbud2Oshozqpra4q5ob7HYset4Iw5Xy+JuyeJ0upQrQpkHCHFZNNSb2zEgzxRzJYO53Y6tRxsSHuPOl9a/kq8OKUiJm6fTyWYLDp1sTdhc0GB2Wfin6pTomamPS3zqWoEl2/JHi8UOq90RVyOEJosNlQ0WVDVZYiofm60O7D/RjAMnm5GhVyE3RY0MnSquayAhBHsqm2Ke5DMaKhraYHM4MbCLKeZtYnM4cfBkbEPFhUttSzvWH65Btww9CuMUQqOysQ0llYm1YvflWF0bmi12DOxiiqk8VN/ajr2VTTF7fmepbrbiUHULemYZYv5bbuVyWU1rQuQCi82BfVXNKKttRVG6LmHK5kazDeX1ZpxossTNAK+t3bUeHKppQZ5Jg4I0Tcxj9QotCWE42GOsGI+3ctkXh4N4LJuZsjl6OtViCxYsgEQiwZ133slTcejBYnNg85F6lFQ0JVzB7MbuINhX1YwNpXUx3eQ1ttkEeVrNhRBg5/FGWO2xm9xONFmw/lCtIBTMbmx2J0oqmrDlaH1M604IwfZjjYJRLPnSbHEpWGKdfdntErr2UE3CFa3mdgf2Vjbj94M1OFprjkvG9SO1rdgU4/kmGupa2rH+cC1ONsd+bFrtDuw63oj1h2pR0RB/BTMXtyXL2kM1OB6HQ0Cr3YFNZXWCnAcazTb8UVqL2pbYha8yt9uxqaxecApmN1abE38eqUezJbYW1s0WV+LBHeWNgpgL6lvbsamsDtvKG2LuFtog8FAZbhrNsbeydzgJyuvM+ONwLTYeds0L8ZKP3dbNO8ob8dvBGuw/0Rw3l+DdFcJUMLupbrZix/HGmMoEda3tWH+oVhAKZjdOpyuEXqz3RIDLg3L3cWEpmN00/pUYtiVGbWBzOP/qXzF5PG+4QmrFNpzlySYL1h2qRUkF/0kuI8Vqc2JfVTPWHqpBZWP8xmVNixUbS+uwqawOVY3xUzBzcThca9G6g7XYVt4QUxlI6P3eH7Escl2ra/+163hjQhTMXNzK5t8P1qCspjUu+2IxEbWSedOmTXjzzTcxaNAgPstDBQ3mdmworYuL0B4NLX8p2GpitLk+eLI5KSZVu4OgrCY2yo/SmlbsPNYYt4QekVLfasOm0vqYCZXxij3eGaw2J7aXN8bsxLbJYvMcNFltwtlZuOPibiiti6kC5ODJFhw40SLYucDhINh5rDFmh0DuAwb3QZOQ2sFqcx02/Xkkdptrm8OJrUcbEuISHS4OB8GOY42oj4G1qdPp6l9COWQOhP2vcRCLeZAQlwC/qaxOMKFCuNQ0W/HH4VqcaIrNHOB0EjTFWIHPFw0xfD/tdicOV7fg94M12FfVHHUyJ76w2Z04WmvG2oM12HW8MaYKhuMNbYIyNAhETbMVR2IUyqOioQ1bj9YnNFRSMNxeHbFYBwCXZ2dZTeIT3QWj3e7E1qP1MTl4Ka2JT9xtPjhwohnOGFiettud2HW8ETuONQouCZzV5sTu403YXt4QU+OjFqsdW4/WY9vRBkHJAzXNVmw4XIc9FU0xeTdJkGuxA7EossNJsLeqCVuO1CdcueyLw0Fw8GQLNh+pj7nxmZiIygegpaUFV155Jd566y088cQTfJdJ1DRZbNhytF6Qp9Vc7A6C7eUNGFKQwmvIiEazLaJYs9YwJnTuohfuAqgK0+3rWL0Z3TN1vLpJlNW0CiqxRSAsNgc2l9VhZI90Xt1ka1usgok7GAp3Ms6+uUZen3u8oQ17K5sEpVj0pcVix+ayevTK1qMwnd9EmJFsqmI1BwCh5wFCgF3HG6GSS3lPfLXzeCNONgn7oKW+1YYNpbUYnM/vOgC42jVcZVIi1wGHk2DbsQaM7pHBa8zWI3XmsBXs4dQfiF0bmNsdKK1pRa9sfl2Fdx1vCluBm6g+4Faym7Mc6MZzQuBmq13wsqCbxhht+o83tGF/VXNIl+FEjAFCXPHJqxotyDGp0T/PyGsYMZvDif1V4Xv1JVoePlTdghyTmtewCVWNFuypEG6YBDd2B8HW8nqcWpTGa/igZosN+5KkD1htTuyuaMIphalhPTMc7A4njtWHvx9I9BgwtztQ3WJFtlEd1v3hYLU7sOFwXViHLImUBaqbrag3t2NEt3Tew4iV17ly8wh5T1TR0IYTTRYMLkjhNW9DpPl/ErkncsN3vGqHk2BDaa3glMu+NJpt+ONwLU7pmhaXcGrJTlRK5ltuuQWTJ0/GWWedFVLJbLVaYbX+vZFuahK+MBFLjtSYk2ZTQQhQVmvmVbnQ0BaZJcAtH26N6P67P9kR1n1vzxge1n2EAE1tNt7awOkkOCpA1/BA2B0Ex+vb0D1Tz9szK5PAaofLiSYLemfzl/jEYnMIXpjicqi6BZkGFa9xycoj2FTEag4Awp8Hjje08apkPtlsEbyC2Y3TCeyrasbp3ZW8joFIkngleh1wOAhONFl4TQYbidttpPUH+G+D6mYrr0rmBnN7RBbCie4DZTWtyEtR83rgGuswJHzSYrGDEMKrkrW2xRr2YWuix0BVowVKuRTFPI6BenN7RPE4Ez0GCHGVOdekiagcwSirFbYFLxenEzhaZ0b/PBNvzzwRoRyQ6D5Q39rOa3z2lggP2hJdf8C1J+RTyXy4ujVsK/5Ez4N2B8Gh6hYM6MLfGHAZ8yTHnsjhJNhT0YQR3dN4Mz6L1HhBCHsiFc9JcsvrzIJXMLtxOoH9J5txalFaoosieCLuJcuWLcOWLVuwYMGCsO5fsGABTCaT519BQUHEhRQTyeIa6abZYuM1Bk2bwNyAwoHPMlvtTsG6BAaCb3d2IcTcjAS7g6CdR1fxJosNDoGGSfGH0+lKiMUXDicRnDtgKPgeA5F4cwiBNpsDFh7dJJNtDgDAe+igZHO5s9gdvLoJ8zmnxAOHk/AexiFW4ahigcNJYOY5RuiJJmtSKBbcnGyy8ho2RkhhssKFzzixDidJeNzZSOFbFkg2WQgALO389Vs+Zet4wXeZk20trDe386oXqGttTxrjO8A1ZvmUYVVyWcTWzImG7ySg9UmSm8JNi8UOWxLOXfEmItO08vJy3HHHHVi5ciXU6vBO8R588EHcfffdns9NTU1UK5rzUjRJESrBTZcUDa+WK+oIT79fvWJoyHusdofnpO65SwbxngGdz8lUo5QhVadIKiVTbgp/J/YAYFArBB2H1ReFXMprH8gyqJGqa4tZfD++MWoUyDXx1wdkUgky9eqwrRiFMAfk8Fh/ACjK0KKisS1pDhvyUvjNsJ2qVUImk4RdfyH0gUwDv+FCTBpF2Nbc4dQfiG0bGNQKXjPM56dqcCSCxG6J7gNGjYL3kDGtSWK546a13Q6dir95oHeOAS1We1jxNxM9BmRSCQYXmHh1E06J0N020WMAcM3dfCGTSpBlVAk66aEveTxacQNAhl4VUUzuRPcBpVwKo4a/OcCgSr4xEGmZQ9EjU4cdxxrDujfR8yAAdM/U86oXyE/VoKrJItg8Vb7kpWiQwuM8CAA6lTzsONRCGAN6HuUAwNWnalvqeH1mLClI0/IaRlWsRNRL/vzzT5w8eRKnnHKK55rD4cCvv/6KV155BVarFTKZd0dWqVRQqfgVzJOZglQN6lqtSaFkNGoUvMdijVRADTc+kOd+uSzi7wRDKgWMPMZfA4DibAO2Hm1ICovmHJMamTxvrPNS1KhoEE4G8VDk8axgBID+eUbsq2qOeabqzpKmV6JvDr9xKAGge6YO9eb2sMZAoucAvVqOLin8bixVchmG5KdgT2XiM4iHIjdFjZ5Z/IXLAQCpVIIeGXrsPxFeLMpE94FUnRJpPG8quqRqwlYyR1MXvtsgj+cxIJdJMbCLCbsrGsOy6ExkH9Cr5eifx29cfoBfq9B4wHd5ZVIJhhSk4GidGcfqzUETISdyDGQZVSjK0PEaixdwbdRTtIqwLRkTPQ/q1XKYNPy2QfcMPRrNNt6t5GNBqk6JPJ6NLjINKhjU8rANLxLdB7pl6HiVBzVKWVLVXyoFMgz8ygJZRjV6ZDlwuDp0IuxEzoMSCVCYruV9TySRSDCwiwkHT7YIOgmqVAoUpGp5z80AAAZ1+ErmRI8BALweNAEuo4s+uQYcONESUQipRJCboo5JHxAjEanhzzzzTOzcuRPbtm3z/Bs+fDiuvPJKbNu2rYOCmdERuUyKoQWpvFvG8U2mQYVTClN5TXQEACatIqmCpeeaNLy3gUGtwKlFadDynDiBbwrTtbwnugGAFK0SRRn8xTaNJTqVHD14jEftRq2QYXBBCgYXpPCeQIMPVAopBuabMKxrakzKp1PJcUphKlQKYZ8EG9RyDOvK/zwIuDasp3dPR2G6VpDZpTVKGYZ2TUH/PFNMTuy7pmtRmC78ecCglmNwvolXK17A5dEgdDnATaZBxftBCwCk6ZQY0S0dWUbhGiIUpmtxWlEarxa8AEAIiSghjxCwxuBgXCmXomeWHv/omYHibINg1gSp1HUQNKpnOgblp/BubAC4lCsDupgglwlwAfBBJnUpgvieBzVKGYYXpcHIs/Kab7KNagwtSOE94ZXLQj6Fd/fzWFCUoeU1L4EbPuOcx5r8VC2vXl1uumXocFq3NOjV/D+bD7RKGYYXpqFnloH3PSHg2hMN6GLC8KJUQc4FmQYVTu+ejl7ZBt7nAIBfD5FYo5RLYzIG8lO1GNFduAn1FHIpBhWY0D/PlHThTRJFRL3EYDBgwIABXtd0Oh3S09M7XGcERip1CZapOiUOnGgOar0Rb2QyCXpm6pGfym+YDC69svTYXFYfk2fziVwmidlplUYpw6nd0rD/RLPgXAUVcil6ZxtiqgDpnqFHq9UhaEtelUKKwQX8b6q4ZBpUSNMpUdHQhqN15oRbtqkUUnRN06JLiiYmghQXnUqOU4vSsLuiSZChQ3JT1OgdI4HSjUwqQa9sA3JTNCiraRWEFYdKIUVhmg5dUjUxF6TcAns4FjyJIF2vRP88fl3kufTJMcBqdwjas8mglqNfDKx43SjlUgzKT8HJZgsOnWwVTLzuVJ0SPTP1MdvwtDucguzzwYhlDGG5TIqu6Vrkp2pQ02pFZYMFNS3xj9msV8uRZ9Igx6SOyeGiL2qFDIPzU7DtWINgwydJpcCALibeD1rcKOVSnFKYisPVLThaZxbUuJBJJeiZFds9kVohwymFqdhxrCGkRa81jBjO3MOrcA+yQlk6ds/UxWw/lKpToiBNi3KBJ0XXqmQxtWA0qBU4rSgNxxvaUFbbKoiY7Uq5FEXp8ZEHAZcR0qlFqahpaUd5vRl1ESSI5huJxHW4VJCqjbniM43HxOKxJpZl1SrlGF6YispGC0prWhO+JwZca0B+qgaF6bq4yARiQphHZpTQJUWDTL0KB04KQ9GYZVShONsQ8xN1lyWrDmU1ws4q3SfHGNO2UMik6J9nQq5JgxKBuM3npqjRK8sQ84lU+pdVzK6KRpyMMLt2PFArZBhWmBKT01pfZFIJCtJcm+sTTVaU1bbynmAqFFqVDIXpOuQa1TFVqvuiVsgwrGsKjtW34eBJYbhJKeVS9Mk1IMsQPytTvUqOAV1M6JahQ1mtS9kc7422WiFDYbrrgCGefaBbhg4mjQI7jzeGHZ83Hrg31bFSLAAuxdqQglRsP9aQ0M1UIExaBYYUpMQl9lyWwRWa6USTFYerWxLmPm/SKtAjUx/zTZ9NoArFYNjikJ1JKpUgy6BGlkENq92BE41WVDS2xXRNVMqlyDGpkWtS8x4SIxxSdUoMK0jF1vJ6QRmdAH9b2sZ6PLgPXLOMapRUNsVdBvJHul6Jvrmx3Qe4cVt0761qCrofvOXDrRE91x2XNRRvzxju97pc5jKKyuA5bJ4vxdl6tLbbQ66DiVKyK+TSuKyF0r/2A11SNAlVNivkUhSla5Gfqo271aZEIkGmQYVMgwotVjuO1ppR1dQWt+SACrkUXVI0yE/VxM3DQCmXRhQ6KZFk8ZyfxBeJRIK8FA1yjGpUNLahtCYxY0AqdVlXF6ZreY9pTQud1qCsXr2ah2LQi1LuUjTmmTTYW9WcECserVKG4hxDzIUILt0zdGiy2AS5sQZcQd3j5cqc9pfbfGlNK47WtSYky65WJUOfHGNcT1PdiuYSabOgYjTrVHIM7Rp/90WJRIIck8uFvqbFirKa1pgLHAa1HN0ydcjUq2KqTAuGROISqtP1SpRUNifUqjnHpEZxduwPWQKhU8nRP8+E7hl6lNa0orKxLebKZo1ShqKM+B8wcHGFTUjDnsqmhK8JKoVrTY7XXCiTSjzxuYVgye4m06BC/zxjzD0auLjnwCyDCpVNFpRWt8IShlKBD/RqV2gkvhM8BkIIB2qREu8yq+QydE3Xomu6Fo1tNhyrN+NEk4U3GSlFq0BBmhaZelXC5j43Jq0rjNr28gbBxCd2eXPFJlRIIEwalzVneb0Zh6tbEzJOlHIpimPszecPmVTiWXv2VjUn3LI9RavAgC6muMjCEokEg7qYsOVoQ9DYtPFWsgMuD98h+fExOnGTKGVzIpXL/tCrXJ5UPbP0OFZvRnl9W8yMEbRK13qTa4qP1bYv2Ua14JXMMqmE9wTIgZBKJchP1SLP5BoDpTWtccllJZG4QmUVpeuSIoyRkGGWzAIh9a9N9rH6NhyqaYmLcCGVAkXpOhSl6+IuYLsVjJvL6gXjHusmw6BCcTb/cXiD4XbJyzWpsbcqfoo2mdQVEqRrmjYhmyyJRIJ+eUaoFVIcrk68ZXuqToFB+fGx3AtGhl6FDL0K9a3tKK1t5V3xlqpToChdFzdhIRy0Slec5uMNbXEPI6RRytAnxyCY9tAoZeiXZ0T3TJ1H2cz34ZNG6XL9zEmgcpmLWiHD0IIUlNe14WB1c0IO2zINKvTNNcb9kMEdQkunkuPQyZa4/rY/ijK06MFzBvlIkEol6JKiQa7x/9s773A5qvr/v2dmZ3u5veW29AohIZSAEAKEiIhBRVFAQOldQVT8CqGICP5AQbFRAiKCKIggCChNOgkhhfR2U2/K7X3r+f2x7GZ278zubJ8557yeJ8+Te++WKWfO+Zz3p9kLvrlw2iRM+ExcLub5RrjInBE+hwyfw4eJNR7s6RnGru7hrBwQogjUeR1oqnCUJGo5FS6bBUeMrcCqXb2qNmAxozh9ThmHFElgTEYUBbRUulDrtRe9QXJThRPjql0ltQHrfQ6UOaxYs6d3lOj0wDdnpX2/PxSOi6v3fu3QjKPwBAEYX+3+rF9E8eZEiyRiVnMZlm/v1t0IsNBIooBZTWUlqxMbE5sbyhzYU8C1ULaIaPkso7KYjmW9WC0ixlW70VLpwp6eYezsGsqbM87rkNFa6Sy6DZBMjdeGjfv60waWFGodANJH9Fd7bEUX4JXPwK7uIbR1DhXE0SAI0UCjcVVuQ/ZKMiNcZDYQoiig+bOJbvXuXt2dRrPBZbPgkEYf3AWqsaYH+TODYmlblyFqTwEHDetSLTSxhmg7u4awaX9hhRaP3VLQOnuZMK7aDVkSsWFvf8mOodpjK0hjm1wod1lR7rKiY8CP9e39OUf1WS0iptRFU1KNypgyBypd1qLVai5G7eVsscsSptZ70VThxLr2PvTmIcpBEIDWKhfGlsC5mA5BiK6BPoeMlbt6ihK1EP1eYEJNdANTSsZWueC0Slizp7ckIrsgAFPqvQVp8pcNsc1Fvc+OzQcGsKsrfxkvohgVUporiiukcHLDahHR+pljfFvnILZ36s/+qvLYMKWu8CXhckGWRMxqKsOGff3Y3Z043osVxVnns2Navbfk60OsQXJ77zDWt/cX1Mlhk0XMaIj2yjECDmu0TvOWA4MJpQXTiUDJ2CxSRu9xWKMN2Hwlar4mSyJmt5Tj4+3dqiVTiiGyx5BEAbOay1BmgKZskmIt3NoxiJ15rF0+ptyBCTXukgfX6EFSRHjv6BrCto7ssx1KlbGghc0iocptS+tUK9Q6AKSO6AdQUttQ+sz5WO9zYOO+/rxm/rk+i5gv1bxHK6VXlzijcFglzGkpx9aOAbR15L8RwphyBybVegyRCmOXJcxqLseytq6S16Jz2qINWIxwXZoqnCh3WbF6V29BIr1bKqORaqXeRChpqnDCIglYu6ev6PVoa712TG8o/aZKiyq3DUePk7G1YxA7OrObExrKHJhYaw5DMlareXvnELYUqCmcJAmYVu9FrYEF9xhuW7QZxo6u6PXIVoB02y2Y3uA1XARfMj6njCM/i+grpLMViI6DQ4pQc1IvtV477BYJK3b1FLVGtSRF05WNEs2vxCKJmFLnRZ3XjrXtfRjy5+ZsK3fJmFrvLWr6czJm1LWNdMiiKGB8tRu1n9XwTeWAkz9zrpphrgei5za13guX1YKN+4rreB9X7cK46uJm8qWj3ueI1u3f1VuQCNdSZbCkQxCiGY7lThmf7ukr+HpQ7bFhWoO35DaiLImY3VyO5TtGC82FFtljSKKAw5qMITArsUgHhdF1e/pyeh6cNgnT6r2GO0c9iKKA1qpotsO6vZmXWTPqfmhMuaOomRuZ4LRKhnDCWS0iZozxocZrw/r2/pyCUQQBaKl0YVyV8YJuaICLzAZFFAVMqPFAFIS8lhFoqnBicp0nb5+XD9w2Cw5rKsPyHd0lid4CopPWrKZyQxmZbpsFc1q1PfrZMrG29BF7WtT7HAiGSFE3VuUuq6EF5hgx49IqidicYUp9S6UTE2uN9dynQxCiRqTTJuHT3fmN7JQtImY3lxlebFUiCFEvvs0SvR6Z4vwsMspoRrUWUQdkWUFLKokiMMuAG0mfU8bhLeVYvr27KNHcFknArOZyw0dxRDvPV+S0JlZ7bDi0sXTZSjFK/f3ZYAQHfDJumwWzm8vx4dZO1fRpQQBmNvoM94zrobnSCdly0PFe6CjOyXUeNFU4sz7eQhIrp7Usz/ZwjddW0uxFPVS6bTiitRyf7OgpWIPw5konJtaUrkRSMlZLNNP147buotcoFwTgkEbjRLWr4bXLmNNagRU7u9E9mLkj3uuQMau59KUBc8VhjZZZW76jR3fmoxF1kBiVLiscVinlc17MaH4ljeXGWhtqPHY4rRYsbevKusTspFrjrnk0YO7ZhQHGVbvzlspR6bYWvdawXsqcVkxv8JXku2Pds41YgydWUiRfx9Za5TSswByjudKJ+rLiRBw5rJLhSmSko7XKldGcUOG2YkKNMZ97PdR47DhkTBnEPK1WskXE4S3lphKYldT57BkbRaIY3TSZbUMRm/8K5fyb3mBc8cn9WemkQjs+zSIwx4iNCWcWa2K5y2oYQUmWSn8MmWJEkRk42DBNjeYKp2GfcT3U+xzxc7PJUvp/CjEhFsWZ7h9gbIE5Rqxmb77KnZS7ZMxoMMZ8kI6YyF6I8nbjql2YVOsx3HWwWSQc1lwGucjBP9MavIbJbEqFJAqY2VgGb4Zrd6y5udnsQS0EIZqNZpPTn0+ZU8ZEA++HBEFAY3nqkhSFWgdSRfxLolC0fXkmuG0WzMhSO2oocxh+zTM7dMwwlDO2Kj+i4Ngql+GMCCW1Xjtaq4r/wE+tN3YdHptFwrjq3MeA1SJiXJVxF1clk2o9sBRhEz6x1m2o6HW91Hj1G8C1Xruhn3s9VHtsaM6TMTC51lPSWvT5oMqdmWhilyXTiup2WcrbGqikwm01fPq8y2b5TBQt3HdMbyhd/c1ssVmkrDYHRkqJtOTLa1ZESilKDAVCKf+JYrQhUnLDI4sopn2v0anz2fNiA2rRXOk0zWbbZpHytk+YUO0xzHygB7ss4bCmsrzaxvVldsOVR1HitFowo8FbtO+L1j02Rk8CPVgkMWP7qLXKSY3AHMNqEeHVYeNWuKyGf+YbyhyGc+jW+eyGHTPVHltW+3ij9B6hGXPvtBnBZbOkTZ9Ih0USTLGRHF/tRs9QcFRH5ULRUOYwTNH/VNR67Ngg9edUt7qhzGH4xTWGLIlorXRlXBYiE3xOGTUe4997NawZLPaZvNbItFa6sKdnJKfyAT6nbIrnPR2ZClRmFLSUNJQ5sOXAQF7r9reYRFQpd1kxrtqNLQWYC1s+azRsRqrcNmyA/rJKFklAmdM4NpAsCRBFlKxEWDbYSuiQnXbzKxm/R2/Do7afn5bxZxebsVUu9AwHM649mg6fU8YEA4uMatR57di4L7fG2E6bBJ+B5gO9OKzROrqrdmVeMisZp03ClLriCbjZUum2obXKldAAsRC47RZDR7lqUemyZrSWmCFKOxtEHd54MwTcyJKIWq8de3ry1+g4V4zuhHRYpYz3hkbMXqcNc+88ORlhhslVEARMa/DmLTU+FTZZNGz5kGREUci5ppJdRyqRkSh0lGGtSQVmAOjIYKPZOWjMJhKZYpFEVORYI6+aEuN6f39mXZX7R4IFq+VYDPyhMGRJiEYqav1LimBM+dpguCiZEvmipcKZd4NYtmQeAVVKkqNPB/zBjMbASCBsqChWQRBglcy1yclHXUdOdgiCgMm1nrxnNUyqMVc0LxC1BfQISqkopcMkV2q8dnjsuceIja1yGS5iUotxVa68lUnRYmqd8XuzaJFJc+xiN1YvBoFQBB069jp7e0dATHABmiqME2Vb7rIaOvszHCEYyKJvS99IcYIZWca4o4YTJxIhGAnmJhCEwgSBUMQUpQGcVguaKwrvtY6WZDD+9WAVh1XKOYI/FWUu80WxANEFNRMPd3vPCMZXG6+LcjZ47TL29mYmsCa83wTZHOkIhCLYlWGEAyHA9q5BU0QtqZFpFCNNEYzAwU7q6/b05e0zWyudplr/aBwDDquUs21XTOzW0o2Xtbct1PzbgD+EZdu6QIh6w6PxNW40Vxo7EksPLpsFtV57Tmugkkq31ZTRvIQQRHIUisImyiBQo6nCibU5rAeyRTRVoIUoCphQ486q6bEearw2Uz4LADAYCGUkHA/6Q7BazFunXo0dXYO6mr8N+kPY1+c3fEajxy6jzCkXLas7FU1pakSXmo4Bf1aN/9p7RqiN6jcKXGQ2AR2D/rx4HjsG/GgwSQ2alkondnYNIRwpjMfRZbOgxkRpwpEIwXAwt6irQb95NrMx7LJYMJHZbtKorC0HBjJKCwpHCDbu6y9ZY81cUUYbxqITk0mOYNTCHwwnfJ7Tar4lcMPe/qwMql1dw6jz2k3dBItVhgIheGwSguFwypRYvc8BAHjsFgwFQqZ8BmjBIUvoLvVBZEApx4rWd4fCEWzePwCrynoea3i0p3cYdT465r46X/5EZjPVnlUy4A/lXGZmwB9EJEJMG7maa1ZXuVM23bnXem3YtF+EP5h/D0FLhXmyepLZ15fZfLC3bwTlOY4fI9EzFMD2ziHdr9+wrx9lTrngkfG50ljuRM9QYZwqerHJoqFLqkUiBFsOZFdKbl/fCFpHnKbtV2MG+O7CBOzvy0+6+96+EdOIzLIkoqHMgc370tdczGRjHWNqg9cU5UNi9OfBqO4dLr1HNFMKWUtWNlG6fIze4SB2duk3pmK094ygzmtHpQm9toWKYATME8kaY2/vSMYbCiVr9vTh6HGVpkmRjbH2toX4eHs3+lJEdahFMKbimImVeT3GQsJ6PVogMZLVHwrj/c2do5zv6caATZYwd3yFYdZ+I6egJiMIgNOAm/I1e/owlMaBHokAq3b14qhxFaYv+VHhtEIShZwDMAQh8wayRiEf0X2RSNSeMqvYZpclyBYRwSx7VJhRWBEEAQ1lDmw7kN8sV5fNYtooZkII9vRkLjJPqvWYzg5UIxSO4NPdfRkF4gVDEazZ04fDW8oLd2B5oMZjg0US8tqLJFPqfQ7D2Etq7OoeTrv+p2Ljvn4c3lKRxyPiKDGPhcsokQjBgYH8iMzdgwHTlMwAol7rhb/6X0bv0bux3nTHqdkcUsnozYNRPeAPIhwhVBgW+cDIC6cWm/b1Z53VsHHfAI52WU153pyoMb1pv/5GZ2oMB8LY1jGICSZrbhOLYrTpFLliEYypEAVzrIOcKMpI1o7+gGrkqhKtMRAIEZQbpFSSy2YewdNptRgu8nF3zzAO9OuzjwOhCNa19+OwprLCHlSBEUUBHrslZ6HVabWYqlyOkq7B/DQ/7B4KmFZkBgB7DiKz2Xq0xKj22PIuMtd4zRd8EaPzs319JoTDBAf6jV8yQg9bOwazKjnVPRjAnp5hQwfeiaKAOp8du7pK1wCwocy4YyQcIWjrzG0u6B4MomswkHNmCEcdLjIbmKFACJ0DAQyNpC6TkEkk767uIdT57KZIkfUVsH6qWerTxlL79/WNqJYJADK7//v7RuIeezOMgeGgenmEZLKJZieEmEJw7RiIRil0DQSxQ2NB9SuMzL6RIGwq16BvOIC17RbUfmZQV7mNazwoUUYwbto3gF0qkdx6o1gn13sNbTRpMRQIYVvHYNpIXrX/J7NpXx8q3TJsFskUcwAQfVbznSLrD4YBk9Tojj0D+3r9WLtHO31S73MwsdaDRgM1lsmUfRk2vlRipFRhdwbNuwq1DgL6nDf5aDSWTwKhCDbqyHRT0tHvx76+kYI3FS407jyIzEa7n3pQ2sNa4momz0B770hcaDPLWqjEJkvoT7M/1MJqkj1QMl67DJuc35IZVS7ziMzJzWrbOgazKiHX1jkIryNxzJvlGYhdg6FACJs1Am/0zAOf7u6F137QeWrE86/zlk5k9jpkQ16T2P3f1TWM/hQZ2nrXgvV7++LOZyOer5nhV9PAsJ4iKwgCnrjoKPSkiVrINE260UQNYFgvFfCNP36Q8Xv0XoOth9TnvVN7IZjz09cyev2N//hU1+vMcP+BxEVflsS0gkiqKFabRTSlEUFj07NMKERp/rAJOozHiI3ZclckL9Hc5S6rKZ+DGNl0Eo8xmMN7843NIsEu62v+d+WTn2T02ZnYAg+dNyfta4wmSnYPBbKqTX+g3296kdkp534vnFbzRNHHYN0eTiYXodgsGa1qlDms2BfMT11ySRRGia1GhnVdAGDLHvY58u9U0YtR+1bxZ8A8mGdm5TBJpduaUeM3PWnSlQaJYuJwOJlhBqcAh1Mo8lVP1mbSVGkgmiKZjbgYI9PU4kLjdViySvctNl6D1XDtH8kukrcvy/cZCUceBOJ8fAantOQiFJtaZHbKOfWmUOJ1yKbIaOSwiSAIqPbYShLNbOYyMhxjwEVmA7P2toXY0zOCDe19KV+XSSTv+Bo3mk0UyVuIxm9mKZXBAZ665Gh06qi5mGk0O2AewXLZT04CAGzrGMLOFOUyYhHMd355BmwaG4j6Mgcm1pqrHq+SXDdGWtfF6Ky9bSE+2dGTMqsjk2fgkMYyVHnM42yTRCGnJkdqOAzYxCwd+WpWatZUaSA6FnKJ7DGauOZzyLqaOz/wzVlpX5PNOqgHQYiKMUYi2+MxmlieDXkRmU04/y37yUkghOCdTR2avSn02kJAtPHm7FZjN/9KRbb2jCiaew3I5zPsM1EUM5BYPg6AZkPkdGuB02bBUePM2fAsdg1S6SN618LZreUFLc2ZDypdxReZHVbzlNPjGBc+ggyOx55fQ9BsHYUL0aTOLOIiJ5rSOZDhZkhPNDtgnsZ/sdrJFlHUbACprMkWrVmnfv4TajyocpvXO53rxthuMIEpE6rdtrSlg/RgkQT4nOZb+t02Cd15FJnNaEBbJBGCgKybf8Y/x2AN3DLFa5dxIJhdQ2SjbSj1Ho/eMinx1+tcB/XgtlkM1zC4wmnNyvFEQ7Mrex6cpXYTisyFKh0GmDNNOtuSJ3ZZMo39q4bHbsnLOgiYz+mUbLfUeOxpHa5qa0G1x2ZKG0hJhUuGKAKRLM1CmyzBa7AyUGqUO+W8jXf932meIBSOcTH+08UwvO4MEArnP7U1XIgCnwUi5rHtGghg5c4e1dfo9dg6bBKOHldZkOMsFGKBDOECBMgXnDKnFTVem66oNzXKXVZUG7TGll5yiaYTRcBtUqOapRp0WlS4bOgezE+qu8duMW26sCgKOZWLAArjvC0mjeUOHNCR4ZKMIMBw3eS99tw2ysXAKI0SlVgkEVPrPVi1U7sRZjL1ZXZTO1ljWCQRFklAKMt5QBDMm9XDOYjLlp094zKpHRRDFAW4bBYMZNn0UInZAq+SaSizY6dKM+x0jDHYOpgJrNnDFkmE22bJuslnNpS7jPtcxHQRQgg+2taNIY0+G3q0EUEAjhhbkfVcykkNv6ocQ+MvQP1Eo9VkTEXM02wvk7DpwEBacSFV9FJTudP0nmvWmVTrQedg5g2PRBGYXOcp0FEVD5dVgiRlJ7J57HK8izTHfFS6rdiyP1+fZV6hKR8j2MxRbABQ4bLCZbNk3MSv1ms3XASnKArw2mX0aGSpxPDrqNust5t6MukinssMFv0do8Zjx5jyAHZ3p08ldlolTKo1/xoYw2aREApnJzpYLaIp54CYuNA3EsTH27pVX6M36EIUgWMnVMFi4rIRdlmCJAoZB87QIKi48yAyS5JguPJJmeKxyyhzpl8/lLhsFkM6DjnaeB1yUUVmI0f4K3WMQxt9+GRHT9r3aGkjjRUOVHvMn91kVMy/0lBMzKAKhSN4f0unZtSCHqNKFIG546tMF72VSxd5LYo5UecLURRQ5bLl1OzCjFGsoQJFnUciQCRCTCc62mUJU+u8+HS3/ugtAJhY44Gbgo2FIEQFme4sykYYLU0+E5R1+No6hrDtwMCo16RbByySgCPGVhhOZNOL1y7DLkt5aZJm5oYmkTzkTIYjxNTRzIIgYHy1C6t26Z8HBQEYW+Uq4FFlT5nTmlYkuPLJTzL6TL3RWwDw0HlzUv7d5zTu3Dm51oOhQChlloNFEjCzqYyqfhxWi4jB7JKaTFuPNyYuOK0WlLsGMZSmKXiqoItarx1eh/mFNqdVynhP47KZ0wZQkg97lgabGABaKl3oGerR/frWKvP0ZVIjuS71cCCMZW1dCRpJKnvYYZMwp6XcVA6mYo5VSRSyLsVTbCrdNtSX2dHek7k2YpNFTKg2b48iM0DHDEspSm9NS5VLV+F3LaOqzmdHmclq7ATDkYwjlfTQO2zO7uIVbmvWIrMkCqYU2fIhKGnhD0VMGcVQ57NjX9+I7nTxMqeMpgpzG5VKPHZLViKzmTcUyrVgar0HA/4Q+lLMY2rrwPQxXlS4zCuuAtFoZj1Ri6mwWkRDR2mkIhSO5KWsQjAcgSSab+5TUu2xwWmTMOTXt0ZUe2yGjeCrcFnR1qHe1LXUuGyWvDUQLASiKGDGGB8+2NqlWZ95WoPXsPc+W3Kpq25mB1OMKo8NOzozLxNw8P3m2g9pYZczF5ntBn6e9eLMg1BuFiEtHVVuq24HvEUSUGvyyM3kjFyn1YKZTeWawTdKe1gQgCNaK0xXJqWY+xeH1Vw12yfWeLC/359xhuukWo+pHA1mhC6ri2Kq3Ll1FzVjHbrOgUBBCt0PB8IY8IdMJzq5cjCInCZbNICoEJKPmmta9AwH4LCasy7ZhBo3Ogb8up6PiRSlCAPZR2GZLYtDC0EQMKnWjWVt6unCangdMuq85t5YANFo9FxFZjM622IM6hRU0zHgD5k2oj2GIAho8Dmwef/oqH41jFaLWYnPkb4u8wPfnJX2c/SWCsgEI9dmjGGzSJhS58Fqlcj2Op8dNSYXVdQwT2eRwuDJsWGX2ex/LbKJzrdI5toLqJGP9cvsa2AMQRBQ5bHq0giq3DbTZXDqoc5nx67uobQZQWPKHaYTmAEUNSDKbM4Xq0VEU7kDbR36nY4umwU1JszuNht07LoZIFeDKB9e32KzN4fSEGk/u7dwn10ocok+MWPkSjaNnTJhX5YN9IyAy2bRlZngsVtMLapx1ClzWuHOYJM9ptxhOieTGvkwfs2YvRCjZzjzCH7Vz8mgfqORyaSuZIWBM7mkz+oyp8ImS+n/KUTlWPSWnn+pMPJ1U1LrtavOieMpTYfNpSl2MMfGoUbAkmP3ZppKp2QKDbZAPkq+mLVsjBp6NQLaMjqUNJanz9hs0vEaI2KziEVrWO8wofOlNsMgmlqvjYp50OjQM8NSTjAHgxJAzt3oi81QIISOAoqMu3uGM26WUWpyqU9diNrWhSQSIdjWMQh/MKzvX1LDIz3v6ej3m7Z0CqDPEDCzoKZFtmO5EKV3Soktg8hsOyVR3IXIbDET+XKO5lLb30joLRkgijB89JZRGzGZqcxaZdI1dFglKtdAABhMU484FcPBEIjJJ9OhQG7rebp6zmYhm72hVlkZM5FLuZj4Z1AQ0R1Dr+MoF+eU0dG1JzKhgApEHUPFKltlxgj/TJ2GtGS2Gh16XVqUkWvkUddQwLCbGDW251BrTQ/BUAR7eoZNVau2PQeBIRQmONDvN03zv22dgxgOhDNudgTob3j00HlzsL69D0e0VhhegFBjJJR+kzQSpMugjEQIuoeyi+bsGAigpdKYjb8yhRCC4QzqlQ8Fwqgs4PEUi0zOWfMzTCou9A4F89a0djgQRseA35RltJQM6hSaIpHoORtZcKxwWrENxqrL7LZbTLUZS45MojVSaSQYzkkojESizlozpo0D0fVvf45BKPv6RlBhoj2RFtk4zwf8IVPtBzmpIYSgc0Df89AxEMCEGkLl3KjHPhwKhk1bKsdmEYtiv5ppzY+R6XWhxclodMw3khgkFI5ga45NYXZ0DSFgEu/1UCCEPT251d3Uw7aOQdNEM+/rG0HXQG6p0hv39ZvifPf3j2DbgeJstvtHQli3t68o35VP+keCusZD33AwqyZ5RmVP7zD8WQrn3YMB9FJSJqC9d0R3wzPAXHNdKjp0bqRS0TUYMOW12HxAX+1hvWzRWcvYyGRSn3t3T2Ed17kSq8tsJMwmwiULLUP+UEGbB5eKfJQS68jRniwl7b0jOa/lu7uHTZ3JBkSFlWzEki4KbMJwHiLxzWgHqNHeO6I7EG3QH8LOHPo7GRVCCLbqsJH0vMaoFKvEjxnLyGzrzEwz2N09bBpNzMyY053DEIQQrG3vyzm9KRwmWL27F7Oaygwftbll/2BR0qIDoQh2dA1hbJWxoxv7RoJY1567EDocCOPT3b04ZIzPsGOgezCANbsPnqueZkdAbg2P2ntGYLNImFBjjtqNI8EwPt2tfzysbe/D7OZyQ0fx6WEkGMbWHJ0P6/eaN3I9RtdgABv39Wf0nkAoglW7enDIGJ9puykPBUJ5EZnDEWK6LJb9fSN5dxb1j4Swu2cYYwzcEC8Ve3tH0JmBULazaxjVHrtha9SLogCfw2oop2CZ05jXSo09PcOqkf4b9/XjkDE+qiL38tGvpL132PC2rxq9Q0FsyHD90+LT3b04vKXclOnhQPbjoHPQj0AoYsqIxRj5qCtOQ23yrsFAxs/D5gP9sFtFahqihiMEa/f06XK47O/zY/P+AYyvdpluTSiWyCybbF5o6xjMOAgvHCH4dE8vZjaWmbJnlVkw10hiDEII1uzpw/48NSjrHgxg5a4eRAzsve0ZChS1XmRb52BCPV+j0TscxPLt3QjlyRg60O/H6t29hhwDXYMBrNjZkxBdoLdxUTYNj5S0dQxiU542LoVkOBDGx9u7M0qRHA6EsWx7l+nqciuJzoW9OXue+0dC2Ljf+PdZi/beYazYmd180DkQwLLt3aaN7Nu0bwCRPAUebDkwYJoohmA4gvV7CzNmN+7rN+V46BkKYG17b0bvCUcIVu7sMfT5lhtM1C03ST3mjgG/piN+f58/b6KkEegbCeYlI2fIHzZdRGvvUBDLd3bnrcdMzJ4y8pygRSRCsLMru+yMSATY1W3szI50+PNwz8x435Xs6xvBiiyeh0gEWL2rF7uLkDFcaEaC0Wc4E92grWMQq3f3mi6S3Wopjhgqm6hW+dYDA9icZVZe10Dgs/2UOfYCZoSLzAYlGI5gxc6evDX6idE5EMDyHd2GFVY3FTmFNxwmOUdHFor9/SN5FZhjHOj345Od3YYSWfb3f2YslXDR3945hHXtfYZtiLO3dwQfbuvMqiaXPxjB0rYu024s1rX3o3swP6mtu7qGs96clQp/KJqFsGZ3X05C68BICB9u6ypKOaJ8srd3JC8p4jFCYYL1JimTs769v2BzdTgczZQyEx0Dfnyysyer5yAQimBZW7dhHW5GKk/hsVuKFjmVLYQQtHUMYtWunpTZb7u6hrFyZ4+hbJ5s2ZHHfiXbM0wxLiX7+kawfEf+BOYYw4EwlrZ1ma6U1u6e3NK9d3YP59xQvpTko6ZqPno8lIJwhGDD3n6s3tWbtT1ICLBuTx/W7ukzpchGSNTJ8sHWTvRlUfZmf58fH2ztzKtdWWh4uYyDBMMRrN7Vm7N+0z0YxEdtXegbMdf8bxaMP5IYZNAfwtJtXRmlgmZCz1AQS7d1G+6h2t+fe521bNjTM5xV84xCEasttWpn4Tyt3YNBfLStC/0GGAO7uodyMpbyye7uYcNFevtDYaza1YNPd/fm5HAIhwnWt/dj+Q5zRe5s3j+Qd1F0w97+vDvwCsXunmG8v6Uzb8cbDEWwdk8fPt7ejSGdjdNKyVCgMHXT9/f5De902ds7UvDMnq6BgGmcLru6h7ByZ09OQtNIMIxlbV2GjOL02o1Tl9nojcFGgmEs39GDzfv1ZTgc6Pfjw22duhtkGZGhQCiv80HnQMAQNmAqCCHYvH8Aq3cVzh72ByP4eId5nK/hCMG2HPv0BEORgjdYLyT5EJkz6WthFHqHg/hwW2fe1uw9PcP4cFsXerJsqF0KeoYC+HBbFzbs7c9pTzQcCGPlzh58ssMctnAxRGaLJBi+jEj3YAAfbu3K21o45I/ahNs7Bw0bZGZWDGLOcmJ0DPjxUVtXwTtfjgTD+LgtsxSTQtPWURqDhxAYxtgKRwg+3d1XlOjq6Ga7G/v7SzcGdnYNYX17f1FqcOtlf5/fMGVl2nuH8cHWrryVzAGiotL7Wzuxq3vI8Avqzq4htOW4mdJibXuvIYWmGP0jQSxr68K6PX15z2YAoobaB1s7seXAgGHTBiMREhUXClQ7ceO+fsNGtQZCkaJFW2/eP2BoxxMhBJv29edtrQiFCT7Z0W24dOFoXWZjlMwwaj1mQgh2dA7h/a2dGdev9gcj+GRH1GFrxqjmnV3DebeVjGL7qhEKR7ByV2/BbAAlkQiwdk8fNu7rN4VdlI/xu7PbPA3hk8mHKDgSDBvW9kkmEokGHy1r68q7OD4ciO4FN+3rN8S+R4vhQBird/VGs5FU6u9nS+dA1BbeuK/f0NH9xaihbuQo5kiEYPP+/oKUOIpEoiX5lu8wdkk1s5HRaPrd736HQw89FF6vF16vF3PnzsW///3vQh0bc+zozD1KJxPCn23gtxig22rPUCCrlJd8sbev9J1Gs6ktlSvhCMGqncUx4pPZ1T2EDQWqNZornQOlrV8+Egzjkx3dWLM796afaiijmo3qwT/Q78+4wV0mRCLAql09hhMZwxGCjfv68dG2Lt0dw7MlEgG2HRjEB1s789JUL99s7RhQbeaVL2K1CY24sdq0P7conUyIpd8akXCEYNWu3ryLYbF04c0Gq9FeZpA6yGUOYxyHkt7haAbWxn39OdnJe3tH8N6WDsM5GVIRCkewpzf/x7u/f8SQ5fNGgmEsbetGR5HT2Xd0DmHFzh7DlhAIRwi25ymKNRwm2GGSLJZksikbp/o5JhCUBv0hLNveja0HBgsakLO9cwgfGiTDVUkwHMGmff14f2tHwfbHkUj02X93cwd2dA4Z0iYsishs0KZ/A/4QPmrrKngwYvdgNAjLLJmuRiej0dTY2Iif//znWLZsGZYtW4YTTzwRixYtwpo1awp1fMyws2voMw968b9724FBbC2x0Ly/xHWRIhGUVGQJfVaDu1RC++b9A3mt9ZeO3uGgYUWNGJ0DAWwrQc3C3qEgPixguRwlsbIpRkshDoQiWNveV/D5MBQmWLO71zCRS7H6kDs6h4q6FgwHwljxWeq5Ua7FUCBUlCi7QX8Iu7qNJTaNBMNFN3IP9PsN53AhhODT3b0FrZvY1jGUdeOYQlBmgEhmp00y3GZzR+cQlrV15c3pFAoTrNvTh5U7ewwdvRajczBQkACUSASGq0saCEWwPMMGx/mkcyCAVQYrmxZjf/9IXgMP9vQMG2bNzwR/nq5BPhoIFpLeoSCWtnUVbW846A9hWVu3YfYEvUPRPcr2zqGilFQMhaNBHh/v6M6bIyNf2IqwJtssUsG/I1N6hgJY2taV1+j1VITDUbuz1LoYDWQ0Yk8//XR84QtfwKRJkzBp0iTccccdcLvd+OCDDwp1fEywv3+k5ILb1gODJa1HZoS09VIew+rdvUWbQLXYuK+/KJsNQgjW7Ok1VIkMLdo6Botau3x/3wg+3tFVkOhlLUJhghU7ewwV1bV5/0DRrkH/iDFExu7BAD7c1lnSeaCtYxArdvYYIoW00FE7SrZ1DhrinGPs7sl/Wryu7zXAc6Bk0/6BoqxJbR2ltX+U+BwySl0S0UhRzOEIwcqdPQULwjjQ78dH27oM52BJppBBEMVwaOuFEIJVu3oKXjIwHV0DAWwoYCZVtuTb+RgIRQyx/8qEcITkbb0OFilbKBu6BgNYviP/zd/TEY4QrNzVU9JSikB0XV62vaskYm/vUBAfbOvEfgOVFLVKYsF7NthlYzmXOwf8BWn4qoetBwaxyYBrgJnIejSFw2E89dRTGBwcxNy5c/N5TMxhlJpobSXsNF3qUhUAEChRNMuAP2QYI78YqXP9/pBpGm4QgrzWQ05FJEKwbm9/SRogEgJD1SMrtnFbamOaEIJ1ewtTezlTOgcChhDcuovYiCYYihhKZCpkiZDU32ucNNlgOFLUxoylKBmlhkUS4bJZSnoMRqrHvKt7qOCOhuFAGOvbi1P/PFsKWSfSSCUDeoeDBS8TpZc9PcOGsYliDBbAdi7EZxaSfEZeE5Te5tJi077+kjm/IxFg877SZbb1Dgc/y6wrydcDiEa0rmnvM4Q+AQCCIMBe4Ehju2ysSOZNOhv7FortnUOGLSlpBjIWmVevXg232w2bzYbLLrsM//jHPzBt2jTN1/v9fvT19SX84xwkGI6g1yAG1ZA/XLL0kIgBwlpLtZh2GURgBqJpKYVOESx1xHamFEt8OjDgL2oEczLhMDFEI9CRYLjoYmupRL0Y3UNBQzleSh3ZHY4Q+IPFfRaMlBpZqk2NUTZTQNTJUMzNxVAgbJjNRKlFXqM0HwSK4/gGgJ6hoGFscTUKGXFpBOdmjE4DRdUSgoybSxaaQDj/61QhPrOQiHlM9cjnZ+WTQX+o5HbpUCCMvuHSHMP2Ega9KQmHiaGyPB3WworAzgJ/fiYM+EOG0Av2FSnQjEYyFpknT56MFStW4IMPPsDll1+O888/H2vXrtV8/Z133gmfzxf/19TUlNMB04YsiYZ5qK0WsWSpEqWO3AEAp7U0x+B1lP7cY7htFohiYY0uj90456uHYh2vEdKkyw3QdMoqiZCk4l6IUs8/Hrul6OecigpXaceBJApFj6hw2oyxDgOlM/SdBliHY3hsxRU6LVLho4T0UkqR1yIJJZ8PlRRrLrJaRLgNbJs4CjgfFlq4yASj2Yceu3EcLgAKMkcZsQ5rKkRRyFvNeKPM+ck45NLXxZckAa4S2UVVbltJvleNSnfp90UxCr02G2ntd8oSZAP0hjBCnwyzkvHds1qtmDBhAubMmYM777wTM2fOxH333af5+htvvBG9vb3xfzt37szpgGmksdxZ6kMAADSUOSCUSOUywkNcqughn0M2jMDRUOYo+Hd47MY533QIAlDrtRflu+yyVNK5oM5nN4SBIYoCqlzFNTBLbdDKkoixla6SHkMM2SKipbL0a1IxDXurRYTHAGM/RnmJRP5yA5VJcFilol6HhjJHwR2sevGWUNjyGsAWUzKuyl2UjeaEGjckg9x/NQp5X7wGEnarXDbYDFIXtMJtNZQADxRmHBjtmddDvmxVo+5FRFEouR3WVO6ERSrNs1jvs8NnAHtkTLmjpOtxMu4C2qkWqfjBHakQRQEtFaV9BnxOuWT2OA3kPHsQQuD3a4eS22w2eL3ehH+cRJornRhTXnhxLxW1XjvGV5dO5Cj1+csWETWe4oiJyQiCgFlN5SU3rBsrHGgq0oR+aGOZoTd0MSbWeAq6qCczqdaNsSV4DpsrnZjeYJy5eWKtG5YiRfa6bBY0l9iQAYDWKhemj/EWvLFHKrwOGUeNrTCEoTmu2lW0MTCp1lMyB6sa9V570cUN2SJiTBGcjJlwyBhfUaK6K9xWTKh2F/x79OK0SkUb+8kYqVQGEHU2HDW2omBBALJFxKzmsqI42HOh3mcvWKaTkc5dFAXMbi4veQSby2bBIWN8JT0GNRrzvFfy2C2Ge+b1kA+HqMdugVwiEVUPLZUujK8pzbrUWuXEhBJ9NxDdFx/eXI7WqtLY5pIoYGqDF1PrjbMvAgqb6WG0LBIgui8q1TNQ7rLisKayknw3LWQ0u/74xz/G22+/jba2NqxevRr/93//hzfffBPnnHNOoY6PGabUeUpm6NV67Zje4C3pJttptaDOVxqRFwCaK5wlFT0dVgmzm8tLJu40lDkwudZTtO9z2ywlF9TS0VDmQHORIwkEQcD4ajcObfQVRWSQJAHTGryGE9nssoRpRTDuJEnAjDFewzg86n0OzGmtKHpEuSAATRVOzGkp3RyUjM0iYXJd4eekao+tpGuPGqIoYGKRDesJNe6SRS1pYbWImNVcXlChudwl49AxPsNEMQPRdaBU0YVGitqKYZej9lFrlSuvQmuF24qjxlag0kCp2VrYZakgWVVVHpshMpiUuGwWzGouK1m5ALc9+v1GFCDLnNa8OlzGVhkjgypT8vHMmuG5H/tZ8EGxbFRRBCbXeTChpnj7Qe1jETChxoPZLeVFjTgvc8o4cmyF4ZzuAOCyWgo2Foy49gPRZ2BaQ3H3afVldsxqMuYaYCYyunr79u3Dt771LUyePBknnXQSPvzwQ7z88stYsGBBoY6PGQQhKvZMayie8CYI0QiuQxqNscGKbnKLfxwum6XkKRmx4zhybEVR08RFEZj62bgrtshY47HjsKbykkVspaL1s0WtVNR47ThmfFVBxa8arw1zx1UaKopJSY3XXtB7IIkCZjWVGa7motcu4+hxFZhc5ynKsxEzqCfXeQyxDiip9zkKGtnvdciYYcBoNSA6/ouVWVLnsxtyQwVEHbBHjK1ARQHWxcYKB2Y1lRtOXAdKt+EzUo8IJVHBwY2jxlWi3JXbtbHJIg5p9JXUsZ8NE2rcea3dL4rR7Ckj4rVH16Vc73Wm1JfZcUSrMbJ5tJhSn599YqXbipoilYPLNz6HnLPz0WjOZS3qfQ4cPa6y4Gn7ZU4ZR42tLJrdoZcKlxVzx1ViSr2noI4np03CzKaykgR66EUUhYKt0UYoT6JFQ1nsGSjsMdpkETObyjC9wRi6mNnJaKQ+/PDDhToOzmc0lDngsVuwencvhvyF6/jrsEqY0eAz1KRil6ORa2t29xXtO0URnwn7xphMrBYRhzWVoa1zCFsPDIAUsOm30yphRqOvpN7LCpcVc1orsGpnD4YCpe9wLYrAlDqvIYRXq0XEjDE+NJQ5sL69L2/XJ/acVXuMH8XRUOYAAbBuT37nBEkScFhjGcoM0OhQDUEQ0FThRK3Xjs37B7CnAN2tbbKIiTUew2+0xle74Q9G8n4NnDYJhzUZu2zPxBo3BvwhdA8GCvYdXodsuJTQZGRJxKymMmw5MIC2jqGcPy8areU1rLAOlKZOrk0WDd8EzG2z4PCWCuzpGcbGff0IhTMzkhorHJhQbbyofT3YZQkTqt3YsLc/L5/XWukqWcNrPcQi2LccGERbx2BBv0sSBUyq8xh6TojhtlnQWunC1gPZXxOLJBh+3k9HfZkDW/YPZPVej91S1FJ4ueKwSji8pRy7uoewaf8AwhnOe6mQxGgGZVNF6foypUMQBDSWO1HntWN71xB2dA4hHMnPNbBaRIyrdmFMCftSZUKZ04ruwWD+P9dhzP1QjFjG967uYWzeP5C3+x+jvsyOSbUeHr2cR8wzwzKExx71Jm7a349dXfkXF+p8dkyp8xjSyK73OdAzFMTu7vyftxoTazyGq0cmCALGVrlQ4bTi0z29GC6A+NpQ5sCkWmNstNw2C44YW4G1e/pwoF+7vnuhcVglHFJi0V2NCpcVR42rxLaOQWzvHMzJ8dBc6cS4Kpch7rtexpQ5YBEFrNnTi0gk98+TP3PkGO25V8NqETGtwYsx5Q5s3NeP3qHcDUtRjJYHaq00zziYWu8BAUF7z0hePs/5mbFa6u7t6RBFATMbffh4ezf6R0J5/3yn1fhCewxBiKbOeu0y1rT3Zb3JtsvRed7oz38pMiyMtvaloqHMgQqXFWv29OlywthkEdPqvaZIkU9FY7kD+/v9OTuevA4ZrQZpNpuK6HPvRqUrag/7g3kwApLw2C2YMcZn2OhFNcZWudA1GEBPljbB1HqvoaO19VDvs2cdjNNosGhdvTSWO1HltmH93n505GG/VO6yYlq913ANLrWwSCLGV7sxpsyBzfsHsLc3e5vQjLYwAFQ4rdiG/Drd3HaL4e1h4GAATpXbhnV7+9A1kHsAhl2WMLXeY3rbwIgYf0QxiiQKmFLnxaFNvrylx4kiMH2MFzPG+Aw9oU6u9RQlwrq+rHjpyNngc0abcOWzDp8kCTik0YdpDV5DjQFZiqaoTKx1F6y5TSqqPDYcObbCsJts6bNU4SPHVmRVm8wuSziitQKTao3pXEpHrdeOQxvLck4RtVpEHN5SbniBKRmfQ8aclnJMzbEumc8p4+hxlZhQY65xIAgCptV78xJ17bBKmG2g2tPpsEgiDmsuy3tdYpssYnaL8YX2ZGq8dhzZWpHVpjhWGsYMz7+jBM3/3AZs/JOKaKRrWdrGQBVuK44eV0nFJlIQBExv8OY0NiQx2ovAKBl8eih3Re9hVZ4zsJornTjCwOnxWgiC8NleLvN72FDmKEh972KTbZ1yiySgzsTnb5ejzuEZY7LXB0QRmFLvweEt5aYRmJXYZQkzxvhwRGtFVrZRuUvG3HFVprOFgeh+IN+BAZUFLsWSb2JRzVPqPTntC+t8dhw9zhx9GcyIuZ4sBqnx2LOeRJXYZBGHt1Sg3mf8VDBRFHBoo6+gIkCZU8bUOuOnilmkaO3AfIivTpuEI1vzK1rnm5ZKV9E7i4+vcWNmo88UKTIeu4wjWisy2miVu6xRYcVApXGyocpty0lotlqiopqZUiSVCIKAMWUOHDm2IisxqLXKicObyw2dHp2KmNCcS23eaCO5MtMIzDFsFgmzmsthk/MzR1kkAbNMVo9WictmweEZNgOqdFsxywTR60qKHc1sVCdrKmKZXxM1agtXuK2Y2UhXA59o5FX29uvEWrcp1wFZEjGz0ZeXOv1Rod2HSbXG60WgF7ssYUqG+xiHVTJsHe5saCzPfE87psxhiuyddNT5og7XTANPHFYJc1or0Fhu3CArvfg+cxxnEoAwrjq6zzSjuA5ENZKKPIvCZhVZG8udOLy5ImPbONaTzOhBl2aHX1kTECsnkG2UidMajWI0Q/RODJtFwswmX0EMgVi6rJkMy5ZKF2Y2ZS+wlTll00RrlLuiHd8LHVUliQJmNpVhbJXLFHW4YsQ2WvVl6Y2qao8Ns5pK16U931S5bZjRkHmjNkkUMKu5zLQCsxKXzYIjWjNrhHZIow8Tasy7mY4RLR9RltXcIIrAzKYyU4orQHRjeFhTWc6ZTaIIzGoyr7Mlhl2WMKdFX4OucpeMmY3mKAuipNh1mT0mi2RW0lLpGpWZ5rBKprzveqj12rPK7Kh0W00tLglCtH7sIY2+rAMvJEnA7JZyw/cj0EOdz44ar36BaLrBshhzpcxpzdgeGJOFMG1UXDYLjmytQJnOIBKP3WLorM1ssEjR/jXpMlqAqA04rtptqj2fGpV5bIQsSQLKTKQPJeP7TN/Q6zQQBODQxjI0V5p3HTQL9Kw0lCNL0TqimXprZEs01daMEUseu4xpDfmNNpZEAYc2+Qzf3EaNKrcNh4wpy9iw9tgtmNlkrkgeuxxtcqHXcMoUiyRgdnO5KZrfqSEI0XI6qYxrh1UyVFPLfFHjtaO1KjPjYGq9tyQ1TguFJAo4ZIxPVwTL+Bq3obMXMiUWgZapcDSh2nj19zPFY5ezcrIomVZvrIa/uRBtjupNuSZaJMG0ncKLWb7CIgmmtBOVtFY5ExzxLZUuKgXmGBNr3RmVS4iV4aOBWq8dU7KI5o462czRk0Evk2o9usZ5nc9u2GbHudCQQYZuuUs2raNZC4sk4tDG9CW17LJkur1gJoytcqV0uIyvcZt2z5dMVR4jj6tcNlPaR0rssoRDG/XtCyZQNA6MDp0zDaXYZQmHjinL6D3T6r2mXlBrvXa05NHbNKXeY2oPbrXHhok1Ht2vj6VFm9GokCURs5rL8y6ISJIQrctrcqElumHUHgsTa92mvO96GF/t1i3AZBvxZXRkKdrIKhVeh4yxVcZv7pQpbpslo/PyOWU0VdARvVTtsWWdLt5U4aTuWShzWlOWARtf7TateFpMxxgNTjibRUpI+63z0b2RtFkkjK/WX/qgudJp2hRxNcaUOTLuqzK5zkud0GqXpbTXQRCi4gqN1PnsuoNvzFAyMhuslmhpxVTMGGP+Zo/pmFqv7nR2WiW0UhS5apclePPkKKNFcPXYZbSm2Rd4HTJaTNDwlhboVCAoxueUdadJex0yFZPH+Gp3XibT+jI7FQZGU4VDt8A2ocZt6lIJUgHqc89o8FGxoQaiDSDUIplEEah0mf/Z10IQBIzTIbQJAnS9zqz4HHLK7JYaCuZ/LZoqnLprt48zWUmcdIytdGVc2sBplagVGRo0SgcJAkwdxe+UpZybnerFzKUylCiz1Gh65rUYU+bQleFokQQ0G7jRdbaMq3bpjuZ22y1ooMzJFqOx3JFyrqj12qkVGK0WUVfWoyDkNwLUaHjssmYZBZ9Tps65ooYsiapZCpVuG3XrQT70HVHMb+mNUlOfZn5P93dOfjGv+sQwelODaHmYxHgn7Ow/wy5LmFyrPwLYyAiCgFYdnjirRcSYMvOL6jaLhBlj8pPi2VLppMLxEkMQBNXaqnZZojpNGIg2RU23aapwWU1RhzxbBEFIeX7FTLcvNpIoYIyOuuROq2TapiZaiKKQcar45Dp9KdVmxOeQVe0Dt81iaierKApwFSkTzew1ullFFAU06aixPKbMQWVmkyyJaNBp57ZUOqkTmmLYZSllYAENe4FU6BGPfQ7Z1OuBHmo0nKo0Bxwko7YvcFDoYMnHPS13WqlaF+yylNLpavYMZrNBz8hiCJfOTrI0bRqcVgvGVmUfhTW5zkNVsws9nWUrXFZqDOoypzXnNG/ZIqZNpTEjwTAZ9btwZPTvaCTdc0Bz1EqMVPc6pDI2aEJPtD5tAnMMXwaZSuUumdrrAESdLRYVlVlvpLuRKZajiBaH1GAgFP9/KBwp4ZEUDz22UT3FIqPe3h3llEdyVmmsBxZJKFh/E6NQrmNPpOc1ZseusebRKLJqEVCZ9/2hcAmOpLC4bBZdfVlSQVPQVQwBdOgeNGB+C5xB9HpiafPYtlQ4s0r3qnBbqZtIrRYxbW09M9eeViNXgbipnL5IHkIIRlSMp0AowsQG2+tILYzQ9gwkQwjBUEDbeFYKLjSip4wSTQ2ektGb/p5p3VIzouZPpWGr4bEVfvwKAuA2ce+OGIQQ9A8H4z/3j9AnLKhhl6WUEVpOm0RV0Ekyes5NFNUjHGmiXGMMlDnpCTjRwmOzpM3UodkWiKF1DWi//0oGRkbbvf1+Om3hXKOZadNGCCEIRrT3vsEQ/ftiI0GX4sIIRGdwWkTvC02CKAporcp8szw+hwhoI5NOMKXNyeC2WXKKtqKt4RUADPhDCKtEqxIC9KkYWrSRbtOop1almRnwh1IaTT1DgSIeTfGRRCHtPEdzBE+ZM3VNbiAaxVZFcX32GEEVp5palofZKEaEsdNqMX13eQDoGw4lZG90DflLeDTFRUtgjP6N7ghOUYeApuc1ZsehUSbNnWO0oxlIVzoMoCu7VwutNS+UQnijif6RIAIqNnHPUIDKDM9qd/b7Wp9TTuhhQAMjwYjqnjjGoJ8Nx7NRoHsHTikhnRMljanSDT6H7iYfQHQSpbUGT7qgXAr2jKOoyrJBgdMqwUlBpFYyPUNBzb/1Dmv/jRbSOlooi1xPpnsw9T3uHQ5SaVgrSScy0+ZsUyIIQtqSMJUuGxUCYioCoQjU9tA0pMgWQxihpelfV5JTrWuAbiebklRZHSxEcKaDhUhOQRBUMxwdFNq+aqQqJWmRBOoj2QH1UhEAVIVXGukaVJ/zIxE6gy68juz7TtBYTrDfn3pPlO7vnPxC7+6LYvSG+6tF9pgdURRQr7PxIUBP80NOlGzLH+hJqzcjqYRkGg2qZNJpZ7SLa91p7nEkQr+zQU7jdKS12V2MdLU2WRCYtMTkQCgCYvKMLqtFLHhGBi0Rfsnz4aA/RKUdrEaqe1is5pGlQk/WZoRyZ2sMNcHJRrGjVUmqQBIag0zU8AfV10I/4yIzkN5eNiOCIKAyy+CrbIO2jEx/mgzedH/n5Bc2Vh7K0BvJHDb55kqLTGoI1XhoFpnTiCcUaivp0uHy/T6jM6xhUALAcIpavbSQSkCkXVwEoiJKPl5jZiSVhm9KLJSPg3QCIS1RqqnQShEmRL+9ZGQKvX5R0/Qvaa4jBClr1tOEPUXac7r+HWZHz1aHwPzzgB7UsrdozuZRkqo0Fs1ls5RorYWsRDIPpLB3BygtlVCdRUSyTRbhobBnzUiKPbGev3PyCxsrD2XoNZYo2FupUuaQdQlIHnv2aSRmIF32H40dVh2ylPa81XBSuslKZThqpc3RRKo6iwxkx8Kv4x7THsGSSkQWRfqj2dNFaNEuMAFIWRKGhnIxnkKLzBQ4YQkhqushDSVT9CBq1KcXRfpFRj1rPY32sBpq91pO44ilBXuKjA/a+3PE0FrvaOvRpIbWGhBDK8rb7JS7rBnvdyop7dORrg9HKExMn91mJtiYdSnDotNgoDWCSxQFXdFZtJZIiJHu/qZLIzcjoihk1aiA1lpsqQwLFhrdpHoG0tVrpgE995j2iO5U95mFMSCJAmQNEUkU6Z37lKQa4zTMg4WMNKalVqkgCKrrIQ33Xy/qpRLMf2/ToWeNo30djKFmE9G4F1Aj1VhPFelPE1rjnIV5UBCElOdJ6xwgS5lHJVe46CuVAQBSmnEuimzU5zcK9O/AKERvfS2a63DpSR+lITonFemiU2gVWFJFK2hBa6pcKnGA5uc/hkUSoeVzo3X8K9Ezrmkd+zFSzYO0N36MofWss/AMAKlFFBoElkLaMjSVU1ETmVhYB2OoRrEyMAdYJTFtJB8r4yD5fgtC1E5igVT3mJVIZq31jvZshhip7jMNzlQtKlyZiczlGb7eLKR7zllwuhoJNmYdynDIkqawooTWOrSATnGF8jThdNeAVnEpU0OB5nTRVI0QfWkagtGCltHAwqayXMc9TtcYzuykcjrRvgbE0NpYsiAwAdprndMqURG14rJaClb+x22jZ35IXg8lUaC+6Z0StbIIFgqcLOkQBCHtXE/zfkhJ8v1mRWAGopmOWlk9LNiDgHb5LFr3g8mUObQjdGluglzm1B+Z7LRK1IqtqfbEAN1jwIiwMetShigKaTcGDqtE9QZTj2hIq7AYI1UtTodVorYWaabGIq2LKQBUpkh5ojUdKhktkZHmqIUY6ZqgeuwW6q+DU04xD1J+7jG0mh/SWjIrGYskqtbdp6WhnSgKaWtvZwst1wgYHZ3ldcrU2kFqqAnKrNTj9aTZE7EiMifv+1hZA2Jo7Q9o3gco0ZrPacpYSUWVR3vfU5VFgzyzkIl4SnMAUroIbdqDbowGG9YHhaSbUGj31ugxnGg3rlKl0NJsUGcamUHzOChzyqqRG5IoUNvYIRmtzUM2ZVXMhs8hp4zgqvc5ing0pSHV+TspngeVaM1wFATx6katB0O6qBYzUaiSGW6KIn2TRYQqRtbAGGo1RxnRmNOKaF5GRLZkpwJLkcxAKpGZjevgskqj5gFBoL98ZIwqlw2SirPN50xtK5sdWcPRrgbN+pDNIqXsx0Wzo8GIsDHrUkg6bwzt3ho9KbC0Nzqwy6JmIwO3jd7FNFPRmGYjWxAEVKssmpVuK7VNLpLRitSlPYIXiN7/ep9d429AncbfaMJqETVTZF0Ubyo4iagJyjQ1/y1UxLGLIlvBLksJ1ylVVBuNqNm8rNgB6Z71TBtjmZVkgY2FcilK1IIOLJLATEaDIAijHC4Oq4XqfZASURRQ6xlt99Z56beF9do7tM+FWhmeXofMxL7QSLAx61BIOq99utQxs0NA0r4mQtK/xswIgnZXeAdF0Um5Q/c4UNtIs+St1YpQYaXpW42G8VzmtFJfMiiGVlkMVgzKsMZaF44U+UBKiJoIS1OKcCHEYIdVok58KFeUiWLl+Y+hFlchaOY50EWqKD7ZIjKzFiYHYUiUB9sko3afWSmVESO5tBIrUcwxWN0T6bF3WIhqr3SrO5dZKSFpJNhYdSnEIUspU2GdFEWnqBHRsXkOR+gWFwHtkgA0p4Zlel9pF1rKVRo+sLSYatWe14pupQ23zaKaBqgW4U4raiKzKNI9DyrRmhNDehZKSkgWYa0Wkaq+FIUIHKCxrBbNqcDpoDyuIiX2FA3R9aaR00ByNDsrkewx1NZ8VhwMMZLXQjtD4x8AKpL2RA6rRHWpjBh61nOHSjkV2vDYLKolU/Q0SufkF7ZmXooQhNTpPzTXoQWAoA7lMBSm3+LWKhtC890fDoYL+nqzIUuJUTosiWucKGqbaJrS4NMhW0bPeBZR1FVWiQb8QfX10B9iR2ROzlygLUI3VXmsbKGxrBYLYoIWREVlZiHYIoZWiTzaS+dxDqLmWGQlqy3GKEcDY+PfIiWWUGNFZNcToexiIMtZEATYVbIXWLYNSgVbMy9D0B7RoGfzHKA9hBXaJUFo3lcM+kMZvT4YisAfoltoVgoqFokdcQ1I9QxQ/BAkoRapw1L0jppTlXZHa4xIhGjOb+Ew0eWQpQFBEBKyu2i7/YIg5D0ik8ZIZpmxGrRKQiqGH0siszbsXIPkUoIMmUEA1GtQs1aXOvmeRxga/zGU9l9yM0xasVnEtI1eWQk+UbMDLIyMAyPBr7hJGQmGEU4RqTtEefTmiI7z0/MaszMSUD9HWs89GI6gdziY8fu6BgMFOBrjoBSSgqGIakQTrWiNdVqfATXUnG4jGtGtNMLQcB/FYCCU8vwHRjJzypmVYDiScB1odDLnWxSmUWRmWVQNqKwDgTAb62AgFNHMXhzSsJNpJHn8s1QyCWDb4RxjMJC45g/72Rn/QDSjQ+l4pz2bNYYgCHDIqdd0Vvo1qe2JaA82MyJcZDYpfSOphbZshDgzoUdAot2wDIUjmotnP6XCQudAICtB6UC/P/8HYxACoQiCigWVEHaMKkD7OR9ixLAmhKhG9w9kGPFvZtR0Ja1meLSRbq5PZyvQQvI8EAxFqBMc892wh8bUWX+QrnueCaoba0acjanWO38woirA00gwnCwys/U8qJUUor0GbTJ9Sft/VmyAGP3+UELfpiF/CCEKnc5qpCsJYWcgwzEUjqhqRIOM7AmNBP2jjVL29o7k9HezM6hDQKZdZO4c1BZcOwb8VEaz7u4Zyup9B/r91Hox9/ePftb399Erqiej5VCj3dEWo3MwoCoktPcMUzkHqKH2bAcYiejvGWLb4RyjOylbhRCgZ4iuDJZ8NnS2y3Q2AOqi7J5ngppzeSQUZmIeTBdIcGCADZsoeS1kxckQQ63+Nks1uQf8oVGO55FAGL1p7ASa2NmVuE8MRwjaKddEYtjl1LIeC3WJ9/f7VbWRfX1sjAEjwUVmEzISDKMjjcHUPRjAUIDOSLZgODFyUwtazz9GqgkzEMqurISRGfCH0D2Y3TkRAuzuHs7zERkDNeNpTy8bAuNwIIxhDWdS91CAiWuwo0vd8TIUCKNjgA3BRW0MEMJG47t0Qmo3I5vLzsHRNhFt4z+fkcf5FKyNxAGF0zXT/g1mRssujkToL50UiZC0AgLtgTcxkkXlYJgNJ0MM1kXmPT3q+5xdWQbomI3hQFh1LtjeOURdZpMaNpWGd5n8nQa0noHOQT9TZRSNABeZTciOriHoKbO19cBg4Q+mBOiNUPYH6UuXjeEPpXc07KJMVG3ryG087+wepm48dAz4VSMUhvxh7GMgmjnVMxAKk7RRnmZnf/8IulIIaZv29SNC2ZhPhhCiuSbQLjKNBMNp18NgKEJ96ZShgLoDcm/fCFXj3yFLyJdeQmOpjI4Bf0L90Z1ddNlAqUhVHor2gIv9/f605TC6BwPUz4PA6Gj2SIQNZ2sMhvTkUfhDYc1gmr29I9TPAwCwtr1PVR8ZCYax5cBA8Q+oyNhSlMOwSAKV2UtKOgf8mvu+SARo66RTFzMqXGQ2Gf5QGLu69Xkk9/XRuahoRS6qQeP5A0B7z0haR8P+/pGEhnBmZiSo7p3OhGAogvZeejadhBBs2a9tNG09MECVwKJGuhTYdI4YMxOOEGzcm9poHgqEsV0j0pkWRlI4E2kXFfQ6UZJLSdDGnh71tSEYilA1B4iiAIecn0gkJ4Vps8mO6H19w8xELg0Ftec62mtR7tS5J0pOo6cRtf1RJnsmGmFFeE4VrUsIsC3HQB2js6t7KKWts7NriLoSWsmkEpmtDNRj3pImuHJPzzDz82ExoX/EUcb2Tn1RzAC9i0omTc1oTBMkhGimgyiJRKJiNA3s7hnOquFfMjRFNu3r86ds+jUUCGO3jnFiVkLhSFqDkeY6jFsPDOgSULZ1DFDrbANSC8nUi8zD+jZMtJVOUkIISek83EXZHJivmoq0icwdKhFMkQi9GX3JpMpooLkRcO9QUHe92b299AReaKF2r2m+/5woI8H0AWh7e0eoze4aCoSwaV/qoAtCgDV7+qhuAphKSE4lQNPA/r6RUU0vk4lEwEREu1HIaMTdeeedOOKII+DxeFBTU4MzzjgDGzZsKNSxcZIIhiMZ15Xd2ztCXSRHJg3caGz21jsc1F0yhJbIXT2iuh4G/SEqBBdCCLbqWCi3dgxSG83cPRRM63Ab8oepm/+AqEGtVYs5mUgE2JjG+DYzqTZNtDd/TeVkUpLO8DYzXRqNL+N/HwhQNQc481TmIl+fYxS0xOT2XjYil1KdI80iYyaO9HCEUF+bWW2uo/n+c6Ls1FFGk5BooBqNrGvv01UOcTgQThvtamZkKUUks0SXYzkZvfeVldIxRiAjkfmtt97ClVdeiQ8++AD/+c9/EAqFcMopp2BwkN4H1kjs7/dnXFOWEPo6agZD+q9BMEyfwJZJ+m//SMj0G+z+kWBeO2TTkD7dMRDQJaAFQxHs66fr+Y+h11lAg1MhmbaOoYwi+zv6/egfoe86AKk30LSLS3qjkoaDYWqdTXqa+3VSVC4kH+UyBCF9F3oz0TMU0HSkEALdJebMTKq6u36T24BaEEIyzlbaT6k9BEQbIIZU9jzp6lVzzE0kQrBHp/NkX98IdZG8B/r9GTWF390zRK3IaE0hMssWeuvG9AwFMorSzzRgk5MdGVmZL7/8Mi644AJMnz4dM2fOxJIlS7Bjxw58/PHHhTo+joLOLMUx2jqsh/TWCwEQzuC1ZiFT0czsUWx9OqP1dH+eya8HkNlGaT+lDQD1GhS0lUwghGBvX+YGUjulEVypNtCBUAQkH3V2DEgoHFEVFNQgBAhQtrGMoafGIk11GO3W3MVhuyxBoKhQabomtyw0wU1VBiJEqYNpwB9CMEMBtWcoSO2aoDXH610naEBtWqNoqlOlbySo+zkIRwi6KFoPAf012WNEIvnLjjUaoihAktQHfKooZ7Ozvz9TZyP9NoERyClfrre3FwBQUVGh+Rq/3w+//+DN7Ovry+UrmSbbqCyzR7JyEsk0qtfsnaXzHYVBQ1RHJmUAaK3Bpre2Im01GAcDYd11+ZXQJrbHCKcRDCIE0LC5TU268x71ekqFphEd8zlNvRnyEclMUxQzkH5uGwmGEQpHYKF4k51qOohQKqpmY9sSEn2fPU8NNI2E1m2m9f6rIaooymq/o4nBDLWBkQA96yGQXeBQ7zCd9jAAyKL6Oqf1exrIdJ87HIhm94ki3XNDqcl6xBFCcN111+Fzn/scZsyYofm6O++8Ez6fL/6vqakp269knmzNBNoMjEwMBpqidWJkejfNfvvzfQdpWFQyEYwo1ZaYJdv5nNZyCawiZDgzUrgUAoDOqER6xn4+xDHaBDY9YyBTpwzH+PBbmgitc3wmSCoXQaLA5k9FppH5NM2FhJCs5gFane4AIGtFMlNcLiObu0mbNmZEshaZr7rqKqxatQpPPvlkytfdeOON6O3tjf/buXNntl/JPK4sG7XQ1uAlk5SPVPWJzEqmUUj5SK8tJS5bfsev02r+DbY7g2vispn/fNVI1UVZic1C1/m7rZasNpNuO13rQIxUc7wo0rvB1NpIaL/e3OuAFnoEU5rmAFkSNdNh9ULT9QDS27iyRaTunJNJNR9YKI1gc2Rhy4kiYNNpO5gNrbWO1jVQDVEUkDzcaT//TPf4Lgr2QDEEQYAnC9vW66DTHgagmbFD83OQqT5mlyWqM5uMQlZX+Oqrr8bzzz+PN954A42NjSlfa7PZ4PV6E/5xsqPCbc3qfZWu7N5nVDIRWW2UpYUCgM8hZ/R6rz2z1xuNMqc8ymjMhQoKnocqt60grzUTeoV22kR2URSyuqe1HnsBjqb0pFoP7BQLS4Ig6HaYWSSBWpFZz/qW6ZppdHIVyWgrl1HlSb2mV2VpO5uJVE5XvQ5Zs+GySpAzPDefQ6YywxEALKKg6oCm9f5rkexUoblMAAB47RbdjkdRBMqcdM2H9WWOzN/jy/w9ZkHL4Uhj0F2MygzXeBp0ADOQ0YgjhOCqq67Cs88+i9dffx1jx44t1HFxVKj12DKOYBFFoL6MLnEhk8jWbKO/jUx1BmKR1yGbPjVWlkRUu/MzhiVJQA0FYluNx6Zr4yBJAup95j9fNcp1GsplDvqMibHVroxeX+6SUU6pUZVqPch3FoTR8Oh0IHopE1mVVHvSO1z0vMZM5BqVS1tUb7XbljKqtanCWcSjKQ2panXno463EREEAbXezJ7tOorFJUEQVO19mp2taiRHKNJcJgCInm+dV5+dX+22U+d0aPDZ4cwgmKTWa6fO8ayExYyGSpc1oyzlpgp61wEjkdFMc+WVV+LPf/4z/vKXv8Dj8WDv3r3Yu3cvhofp7NJpNCySiOYMjeWGMgd1Gwq9EYySqD/Sy0z4HLLu1Pcx5XRMpC1V+dkkNlc4qVhoRVHA2Kr0QmNLhZPalCCfQ4YljdOtzClTZ1AD0ejNBp3RG4IATKz1FPiISkeqSFaaxVUgOr71oNchY0YqXdaUz3i5y2p6R2syuUYy05bhJQgCWjXWwyqPzfTZXHpI5VDLpLyW2Wgs128byhYRtZQ5nJJRc7ZkIsDRQPL8RtseWI2WSqeuMmr52ksZCUEQML3ep+v8ZYuIibXuwh9UCdHKWqO1bBIQHQN6g29qvDbdARqc3MhoxP3ud79Db28vTjjhBNTX18f//fWvfy3U8XGSaKlw6hZNJEnAuCr6JlOnVUorLgGAx26hNi1Oj7NBtuj3bhsdr11GXY4RuVaLiBaKIpoayx0pN5Z2WUJLZWYRr2ZCFAXUphnf6f5uZibWunWJRS2VLqpFFpfNopkyXa5ThDUresumZJpKaCZEUUjpTG2ixNGqJFeRmca0Wa1otvEZZn2YlVR1SWmtxw9EBfQandHMzRQ73WOoORRodjKooZzfLJJARWBJOpxWS9qgojqfnVpb0OeUdQXeTK33UOd0TkZrvOvRTcxMndcOXxqbXxSBiTX0Bt0YjYzLZaj9u+CCCwp0eJxkLJJ+L9z4KjeVUXyCIOiqKUVb3SkldV57WoGJlqjdGBNq3Dk1PJpY66ZqgyEIAialmAsm1Lipuv9qNKRIfRVFukVmWRIxtT51jwOXzYJxOgxvs6MmJoui+evRp8NhldIKSA6rRP11aCx3qNbtt8sSdaUygNxrrNIoMgvC6KCKGq+dmYgll9Wiud57KRaZAWBcdfo9kWwRqXQ4JZMsKFsk9RIaNGNTnK+VgSjmGGOrXJpzgCgC43U8J2ZmbJUrpcjYUOagolxiOixa5TIoDbqLEd0TpxaQmytcWTWM5WQHfZYmA9T7HGnTZF02CxopNqj0RKjRHMUmigJaKrTFI0kSqLv/dlnChCyNpHKXlcpGD5Vum2qUos+Ze+S3GfA5Zc1UUBprzyVT5bZp1twXBGBagxci5Y4GQL0chM9hZeLc0zlSaigUWZOxWSTVzWNThYPKbKZc5jWLJFD7XNR6bbArNpBNlfSt+VqIoqAazeyyWahyrqvhtlnS2jtjK13UXwdgdEQ7zVHsWtgV8yNtTU5TYbNIaKlUz9ZsLHdSL64JgoDpDV5Vod1hlVIG5dCE2vmLIqhd95X4HLLmnsgmi7qi3Tn5g53ZlzIm1KSeLCfUuKmeUNJ1BqWxg24yDWV2zcjeBp9Dsy6TmWksd2RcZ1UUgSl19KbHqC2arRSXyUhGy3nAgsgORKNT1IzKOh/dzU2UqDldaXYyKknX+KqG4mh+Jck1ygWB3jkgl7WdxijmGIIgoFZxz2mP4E9Gbb5nZQ1IJR7IFpGa/iTpcFktCbVp3Yw9AwASIrdZi+JuqnCO2heKor4SizTgtFpUG71OqKErkzUVqiIzhc52LcZVuVXrc7dWakf6cwoDG08chZQ5rajSiFDyOWUqU0SVuG2WlNE8PoeV+snEIomo19hE0xbFHEMQBEypz0wwbq5wpaxdbHbKnFZ4FBtJh1VCFcU1WJNRqztukQRUpnFE0YJdlkY974IAKuvxa+G2WUbVm2NFXHFaLZr1WB1WiZnrUO6UYVVErZW7rNQ2fJJzaOCjVb+cFqoZWvuSUXPAex302j5KXDaL5r6nsdxB/X4ghigKcCrsXZeVjfuvRBm9TOsaoIUsiRiT5HCt8dqZEttbKhOFdpfdwkRGVwy1shiszH9A1O5NzvCTLaLuZumc/EG3tUk5WkJiUwbdls2KIAgpo5nTRTrTQq1KirDbbqFaVM2kCaDVIqJVI32MJpQNwKo8NipTxLVwWCU4kkpmVLpsVGdyJFOfZDz5nFbqUyOVCIIwas5jpRYrAE1xhXZns5Jkm6DCSe+5y5bs5zateo20wFqTMyVqziaW5kGtNOlUvRtoRCksuxiyA2LYGC2XESN5X8hCHWIlsiQm7IlqPXam9kRqex/a6zEnk6wRVHtsTAntRoG92ZciKl3WUc3fJElgZmNZnkpkprxURowypzwqgk+5uNLK+Gr1dJhkxlaxUYdPWRpArT4t7VS6Esd8BWPRbG6bJUFUrmZgDkhGWXvSahGpr8etRCuriYW1QInPcfC59zrpFRstuUQyU74esiQmJOOQpVEbaZZE9yqXbVSpAK9DZsrhCiChLjlr5w4gwea3MxbJDESzF5QZK6yUDlOS4HB2s3X+aqUxWFsXK5yJ2ezJe0ROcaDb2qQcQRBGCUo+h8yMt6ZMIw1Y0miAQiOCIIyqucZCeqTDqt7oSYlFEphJj3EkbCrYm9aTn3cvI8+/EmUkL0vCQgzlZtLO2Mbao1IuRBS110hacSpSgp0UjwFZoxeDvveytz6wgiAICbaA3TpadKaZaPPDxDkvXZN0GlE2vmPJ2aqGVWZn/MdIzuxiKasvhiPBFmDLHla73awNAVFMXAvddnrtQSPD9upDAcn1Fj0MbSpdNotqfUGvw8LUoprcPZoVgSld3el6Hzt1+JQbCZobO2nhTCqXwWYdwoPXgMWNlbL2oo2xjbWaw9ljl5laB4HEcU+zmCoIgmbT33SwsiayilJQYTGKNdkeZiXgRAlrdYhTwaI9DCSKrCyiLCnF2ponQKXxH2PXAEhc/1jbExgFftVNTnK5DNZSg9QMSNY6iic3AWLFqCpzyimbGLHU6IF1bEmROywaVKyj3EjkUk7ArIwWV9haBwG2OqhnW1s5lyhojvGxJjQ9Y28etEuJeyAWBVf+jB+EhXJ5amTrhKSFcISU+hBKh8qtZ3E0KO1B1sqFGAU2Z1+KSBYUWTMu1ARl1jbXys2mILBjVAmCgEqNutySJIyK8qcZQg4aVCzaVsp5MJXjgWaURjWLY0A5D7IWuQJES2Yoobn5qxYs7SOydaSw+GywhE1SOlzZE1iTywaxticCuMDIYa88QjLh8MH/h8KR0h0Ih8MwbO7GKSLZO8NSJA8AuGyjjWi139GM8pYzdvs1o9Y9NrZKpgQURlSQQYNKOQ+yKqIo73swxJ7KnDD3MTgEklPjWUyXJQwN+2QxTff7GIzyZwllkIHM4FqYvAdiMYJNYvCcOYmwGGigZCQUVvyfvT0RJzHwhrBkHBoIbm1yTI1aQX/Wivwr507W5tHkFPF0v6eVYPjgjQ+FGRsESbDmaIvhVxjSAcaNahZHgD1JVLbL7Jl3LKXIZutMy1ac5pgDpbDMSlYbJxHuR+KEGd8HjAQP2sD+IGP2sMqtZ3E0hCIRxf9ZvAKlhy9FZifpuWFNZEzeSFstIrORjAC//zFYi+ILKSJXAwxGMithVGNOEJb9iigODhvIkpggLrCYJh4m7ESuJPdi0Eu2tZzNAouZPEqUGVwsRrSSpE0R7fOAGqw62jkHiTA47pUobeCRIFv2cPIcCLCnDQA8+MoIcJHZ5CQvJGqTC83YLFLCxtrGmLgIjF48WDKqtRpdstbsJaFUAl9MmSSoKEIXjLAttLCKshQCi1GMRDHsaY9qztaZTrsTnvXNpNKJwGJE6yh7uDSHUVLofsI5eqB9/UuHMrPPz5jjUe3Ws+h0UNoCIb4nKgkMmiAc2pAV3aStDDb9Gh25UaIDKQGiKKhumlmL4lMaFRHGjUu27nwUQgiUNhS3p9iEdgExHQmlo0p3GEUh27IXMuXOhzBLBpAaimHBYiQzh8061JxEWBQVlShFdtYEd7XzZXFfqAy443ui0kC3tclhAqWgSHsqqB5Ysy/VNtusNTdSOhoYty2Z3GAl33MmNxgMN0CNwbzIXOoDKCLZ2jq0jxGWMrnUUN5eXjaBTaczi+fMSYTtWTBxHWBtTVCz/5l3vnJKAltKDIWISRsGFo1KpchIe5SOGsp7LgjsiWxq0ToSY5HMyjHAmL4+Cso1FFVEUUi477QLSWqICSIze+cPsHnflSSMgdIdRlHI1pFKuyOeRRtYiXIOYPFSJN9/FsdD8r6Qwx6sZzEk1KZn7HlQi2RmLZobSNwHCIzvi0sFv+wmJ3nyZHFhkRSbLRYFNjGhBh9791/tnFl7DpTCAWtR3MmwuKkEkurxMjgGEhwt1EuM6rAqrscQGHK0ZONIlSSB+jFC+31PB+sO5+RzZn08cNiE9XFvVQScWRhTGNUEZRZ7FUgJ+2K2n4dSwdaTRyHJD47EVr8zADw9UGbYYwuo33PWhoFsOXjCLNYlV8LiHAAk3ne7zN4YUM59rDmZYjA4/SdgSYjipPtiyFncbJkB1dHKYDabFiyuhcljnIsLHBbJtmY/LdgUNrDDypYwEtRodBhirAGick/E7YLSwK+6yUkuD8F8uQgGI9gsEtsRjAzuo0aRsJha2L4gDD4CAAC7fNCQtlvYMqqBxHWAtXI5MWgXVtPBkv1jyeJcWXBCs5jNpSS5fBprJAfasDDmOZxkslkfaMIhW+L/tzEWdBHSKI2h9XtasSn2xaw/D6WCX3WTIyXV4mTda8/i2SuNaplBcYX3MwBsClFRKTayCIvRW0BitIbdyt7SziOZOSzZP9lEqrFoH7AG85l9yqALBsrDcDhqWFmNtvgMp2If5OKRzCl/TyusZ/UaAX4HKEBZk5h1bw2LeqOF8ZrMap101X7HCqxH7rC6qVRGL9sYNK6khHmwhAdSQljrop4MS89+NumfLEV6swpLz4AaCc5GVhcCDvOwLrApAy1Y00W06i8HGavLzEtklB5+ByiAcZuS+UjWhDRxBgeD2oLKWloQ5yAMPgIAEiPYWRcaWIzgA9h0srJKNlHbrNfpZAHlHWZxGpQYb3zI4QBsZfWowWKgRQxekzkKd6qXHn4HOKZHGbUa4dtspiCEIBAOj/p9IMTWYso5CKtOJ54KfxBWr0SEO9eYwSKJGYtoPLKHw+Fw6IdVR3sMlgMtAhpistbvaYV1R4sR4BYnBSg3liymy4aVIjODm+wEkZ2x+x8IRxBRWTeHA6OFZw4bsPYMxOH2FPOEGVz/WCbTSB3WU6hZQDkDsLgUKtd/Fs+fwwHYzGLgRNEqi8FauQxO6eEWp8kJR0hCuQA/gxGcSmGZRYFJuXCwViZi0K8uJg9xkZlZwqwaUoyethqsXgrW5n/WyVRk5umj9MNioImSBHuYscg9DicGdzizi9a8x1rjP24Plx5ucZqc4WCimOYPsjWJAImLqVbBe5pRloYYCbIlrg6MhFR/3z8SLPKRcIwCaylhMVgvEUMYz2gBEjcXLIpNrJ1zppHJPJKZfpRTH4tBF8p1MBQmXGjmMAnrAhurNmAwHNHM4GBNZGZ9T2QEuMVpcpJFtn4N0Y1mwoxHMg8ponkDwQhTRnXvsLqY3D8SYtbIYPG8leKSnzFHS4xBRfQ+S3NADOWmKsjgMxBJympi0dnCWiZXps2NuMhMP0obmMVoxsGkLLbknzkcFmAx4EzJQOCgFsLSnihVoB1rQXhDQfb0MKPBLU6Tkyyy9TEYwak0pFmsOTQYSJxItUpI0Ej3UED19+EIYcrhooxgTx4PLOBnOJo/xoD/4NzP0hwQQxmlEWRMbARGi8osRnEMBw6eMwvnn7HIzMtlUI/S2abWr4J2lOsgwGZWG2sZHZzRsC6w9Q0dPH+W9oKhFJN+qr/RiDIIk9V9YanhFqfJSRbZtEQ3mlFOnCxGbvQx6mgY9IdSCgksPQv9w0qDir3FVCkuhcKECYFJCSEEvUMHn/vuITbmACXBkCKKlzFjGhgdxau8Hqyg3FQMMeBosVkk3a8VhMxFaTPCYhaHEmVPAjbt4VDKn1mA9VIJSlgV3Af97I17JZ2D/vj/OwbZ2QumilZmKQgvFI4kPAO9Q2w/D6WCfouTYvyh8KhyGYFghKnFJRIhCdEarHnqAqEIhpPSAbVKSNBGOhG5iyGRuUfhWOgdZue8YyTPeUOMRXMPJDlcuhQGNisoz5/FSGZ/KKk/A4PXYCBwcB5kIXopE9HYahEhCEIBj8YYsJjFoSShRwljYmM4QjCQFGTRw6A9xKJzQQsWLwUhBAMKm5i18RAKR9Cj2P8d6B8p4dEUl3AKpwpLZUN6hoMJtalZXAeMABeZTUz3oLqY2MWQ1y55QmVtMVUTlFkRmXvSRGv2DgWZiWLoUTzz6a4LjQwnCWxDjNVh7BxInPP7hoPMNflQiqosCqzJUSqsRfMDicJyv5/+eTCTSGa7rP+1ZobFyFUlLIvMfUnCAhDNaGBtLWRtH5QK1gKPgKj9q8xo0GqQTisdA4GE4LNhfzhBdKeZVM9+KgGaNrqTdLDknznFIWOR+X//+x9OP/10NDQ0QBAEPPfccwU4LI4etMRkpkTmpAmVJU8doC4oDwfCTAgM6cT0cISgnwHDIjktaCQQZq7+1BDjkcydSZHLhLBVLgYA/GGlyMzW+AdGi8qslQyJREjCPMBEJLOs34RnoVQGkOhcYMXJrEQpLIcZSo8GtG1CVgIvYrDmXEgFY8sggNFrHwtroZJ9faMjl9V+RyORVJHMDE0LySUDhxncFxuBjK3OwcFBzJw5E7/5zW8KcTycDNCqvcvSgpI8obK2p9AqjUJ7yZRQeHSZEDVovw5A9HlPHves1OWOkRy5OsJQZ+1IhKhG7/UyFtEeVtbmZ0xcATAqWo+12rRDwXDCPDgSDFEvMtosIkSdVjwzkcyKtW+YwU2lMvCCpcg1AJrRiizYgUoIW1N/SlKJbrSS3PybpXkwEiGqpRJZCb5LJSSz8ixEImRUA1iAvX2xEbBk+oZTTz0Vp556aiGOhZMBhBDNaL2RYDQ9TGagk3jynMnKJBpDqyzAYCCEcpe1yEdTPIZ0Gk0s1GdU21gNjIRQ4ynBwZSI5ChOlsolDAZCqilyrBlUyoYnLKbIJjd8YS1lOtnpGIlE5wGaxVVBEGCzSLocrg6Kr0OMSIRgRHEtBv1hVLlLeEAlQGkCR8DWHKAddEG/HaiEtX1QKli8FsnrAUuZff0jIdUgg77hIELhCCwM6CKaMPIoDAZCqhkMrO2LjUDGIjPHGATDJGUaUCDEiMhc6gMoMVq15lJ1mKUBvefHgtikJqgGGItiDCfdZ5YENi1B3c9QNDeQeM8ZeOxHkbyZZugRAKA+1wfD9IjMqYQC/2dOV2WZmOSSMZEUgQlOKx1bgWAkkiCyslA2LBmisIpZ09eS69If/D1b44C1uT8VLF6LUVlNDF0ErahtQqK2Mg0icypbYDgQhj8YVrUFJElI63CgwRbQWvdZ2xcbgYKPJr/fD7//YL3Ivr6+Qn8lE6QTUVhaVFhGKx2S9vuvV0RkQWxUO0fanQzJJOtLLEWvaN3rIANjX0ny2UYiBKIolORYjADtpSKSUZsHaZr/p938Skavv+5vq3S/tu3np2V6OIYk+X7TdP/1kvjYs3X+WvYwa2VDOAoYvPXJ9i9L82AqhxItziZuC6RGa7yzti82AgV36dx5553w+Xzxf01NTYX+SiaQ0myeLYxsrpNPUxTYOO8YWveZ9vufbvzHsOgtWGli1K6FRaL7/ieTfJv1jg8a0LrXMkPXAACSz5Y1gTl56WNtLVR75lmaBzij7zeL9z/xsWfr/LXsXomxuZCx000Ng9ciee1naR5MlcHNQnY3R3u8s7YvNgIFj2S+8cYbcd1118V/7uvr40JzHpAlAYKgnQ5nZaSTePJiyppxpbVoypTff73jW2ZgUbGpXAsrY8ZUsjOBJaNa7f4DgE1mawwo7zlL9z9G8lrImsis5lCkaVO59raFpT4EwyOLYoINyNo6CCQ+96xNg5r2MGPjgLHbzkkiebzTHnSkRKv3gCBo28pmg9sCqdHSB1i0B0pNwUVmm80Gm81W6K9hDkEQ4LJZMDAyur6OXZaYMaqSF08a6i1lgstqQSf8Kr+now6lFk5ZSulkieG2mb++VDrUztFtp/+8lSQ7VWgxJvXgslpGRXIDgNcuF/9gSohyzZMYcC4lM2pjydg1cCateaJI1zxAQ63EQiOKAuyKceC00W0HqaHM4GAtgjd5DojhYmwcsOhk1YLFS+FIeg5YWjs8dovq+PfYZWr0AZbuZzZo7YlY2xcbgYyv+MDAADZv3hz/edu2bVixYgUqKirQ3Nyc14PjpMZrl1VFZq+DnQfJIiVGrrBmXGlNmi7KxVVR1HayKGFhUXHbLaMi+FkTGJOjF2hp9qUHURTgc8gY9ic2PPE52BoDSlGVxYiF5KwNWjZUenF85niM/2y1QGBMZOMAHtvBeU9LdKQZC8MZHR4Ne4+FYAMlDFSJ0w1rGT1AVGRTohXdSyOiKKDcZcWQP3FvWOGyluiIOMVGFAW4baP3RKzti41AxkvRsmXLMGvWLMyaNQsAcN1112HWrFm4+eab835wnNRUutUnzXInW5OpMoKLlTIhMdSEJJfNwkQke5kz9YJhtYhMeHxlSUxwKtitElMiKzA6Yi3ZyKadSlditpAosmdU2ywHx4CNsfEPJJ4/ANgYWAOUiKIAp2Ie1BKcOHSj3Eiy6GRQisws2IFKyhyj1zxBYNDhylXmOCyKzMmBZh6GAs8AoNY7Onu+zmcvwZFwSkV5kj7gYHBfbAQynnlOOOEE5rqWGxUtMVlLfKYVZcQWaxFsPoc8Koo1nfhKC+VOK3Z1DWv+nSWRrUxxrqzcfyVOOXEpYy1NOnnO9zqszEWy2hUORprKJOgl2cHK4jVQCozKiFYOO7CUyacGy7Xp1VLl3TYLc2sha6WSUsGgxgyHLCWMAQ9jkfzVbltCNL/TZmEum4F1kvf/5QzpAUaCrZWXMqwWEV7HaG8NC9GbSpQNrliLZJZEAZ6kMcBKJHuFy5rSgGTJ2VKuiOBRi+ahHaWoLAiAm7E50GOXYVXMg5UMGlTKdSA5qpcF7EmNHq2MNX4EEqOXeSQzm7BWfzcZpbjEUsMvIJrN4E1ysrMUbBCDtfueCtYcLUA0g8OtcLiKjF0DiySiQpHdV60S2cyhmzKnNcHRUMGILmI02NuFUAb31iRGL7MWyQyMjlxlJZJVlkY7WZSwIrYDidFbPid74ooySsEuS8wZ1UDiWlDmYmMOUGJjPJLZnlwug8FroJwHWKjHzxkNa1GryShLZMgW9tbB5NIYPkbsYSUslonRgrXmlzFYX/8q3QeF5SqGAo44USQx0dHiZXBfbATYtsYoYJTAyGAUI+sRbMoUYassMlV3SCtKxWWzMHUdlBH8LDX5iKGMVnEymhaXWCqAvWugFJdYFFhFUYDMuNCujGJlMYKNw1FGsbJYm9eX1NyJtXrMnERYDDgA2OtLkkyZQlRk0R7mJO6JWNSGjAB7FghlJBtQHgd7D5JNUjR8YnBjnZgizJZBrZUCw2KKZAzWo1gcVvbmQCAxipP1McBiBB+Q6GxicQywHsXK4Ygiu+UyAMBlP7j+Wy0iFxc4TMJisIkSZdlQFm0hDuBkdC9oJLhFbnJkSUyIXmJxYVEKy1aZvcVEef6s1SP0qjQ+BHj0CsvYJbaegRg2BmvwaiEzKjay1pOAw+Fow2IUp1JUZq0BMIcTw8qoo53DicFSNrNR4TsSClA+SCx67JQbaxZrMivvuY0xgU0SBbhUUqFY7zDPMqwKbSzOfVqwGMEH8DHA4XA4MXgUM4dVlA1AORwW4c9A6eE7Egpg/UFSpkazni7LYrmQ5NpjoshmRD8nCqvzIYP+RU1YrccrMzj/czgcjhp8PuSwisgNQg7jMLoNMBR8BaYAVqO2YvDorYOwKK4k1+C1yRKTEf2cKKzOh4SU+giMA6vPP4vzP4fD4ajB50MOq/CRz+FwSg1X5zimh/XoZSUsGtX2pFq0vA4T47D3CAAAQhGuMrOOhVFxncPhcJLhsyGHVbg5yGGdSKTUR8Dh6hwF8Ag2DsskR7LzyHa2YdDPAgAIcYuKeXiKLIfD4XA4bBPhwgCHcXjgTenhagwFhPliwmGY5Eh2mYvMHAYJhvg6wDoiqx4WDofDSYKviBxWCXOBjcM4oTB/BkoNV2MoIMIXEw7DJJcI4UILh0UCYR7JzDoSj2TmcDgcAADhATgcRuHBZxzWCfI9UcnhIjMFcI2ZE4NFuyK50RsXWjgswr32HD71cTgcThS+N+KwCmFcX+OR3BxeLqP0WEp9ABxthgIhXa8bVrxO73ucVnPcej3nM8TPP/7/4UCYqmug51z8oTD8oXD852A4out9Zjh/gD8DrD8DgL5rMODnYyCT1wN0nT8AjAQPzoMsXgOaxwDr6L2fNI8B1p+BTM9/JMimLcDHANvnDwCDfrZtgYERescA6+h+BiieB8yCQIqcT9TX1wefz4fe3l54vd5ifrXpaP3RiwX77Lafn1awz84nhboGrJ8/YI5rwPr5A/wZ4GOAjwF+/vwZYH0MsA5/BvgzwMcAHwP8/PkzwPoYYB3+DJQevVouL5fB4XA4HA6Hw+FwOBwOh8PhcDicrOGRzAZGb3h/NpglJaBQ14D18wfMcQ1YP3+APwN8DPAxwM+fPwOsjwHW4c8Afwb4GOBjgJ8/fwZYHwOsw5+B0qNXy+UiM4fD4XA4HA6Hw+FwOBwOh8PhcEbBy2VwOBwOh8PhcDgcDofD4XA4HA6n4HCRmcPhcDgcDofD4XA4HA6Hw+FwOFnDRWYOh8PhcDgcDofD4XA4HA6Hw+FkDReZORwOh8PhcDgcDofD4XA4HA6HkzVcZOZwOBwOh8PhcDgcDofD4XA4HE7WWIr9hYQQANHOhBwOh8PhcDgcDofD4XA4HA6HwzEmMQ03pulqUXSRub+/HwDQ1NRU7K/mcDgcDofD4XA4HA6Hw+FwOBxOhvT398Pn82n+XSDpZOg8E4lEsGfPHng8HgiCUMyvppq+vj40NTVh586d8Hq9pT6cosPPn+3zB/g14OfP9vkD/Bqwfv4Avwb8/Nk+f4BfA37+bJ8/wK8B6+cP8GvAz5/t8wf4NSgUhBD09/ejoaEBoqhdebnokcyiKKKxsbHYX8sMXq+X6QeJnz/b5w/wa8DPn+3zB/g1YP38AX4N+Pmzff4Avwb8/Nk+f4BfA9bPH+DXgJ8/2+cP8GtQCFJFMMfgjf84HA6Hw+FwOBwOh8PhcDgcDoeTNVxk5nA4HA6Hw+FwOBwOh8PhcDgcTtZwkZkSbDYbFi9eDJvNVupDKQn8/Nk+f4BfA37+bJ8/wK8B6+cP8GvAz5/t8wf4NeDnz/b5A/wasH7+AL8G/PzZPn+AX4NSU/TGfxwOh8PhcDgcDofD4XA4HA6Hw6EHHsnM4XA4HA6Hw+FwOBwOh8PhcDicrOEiM4fD4XA4HA6Hw+FwOBwOh8PhcLKGi8wcDofD4XA4HA6Hw+FwOBwOh8PJGi4y58ijjz6KsrKyUh9GTrz55psQBAE9PT0l/QxO4WhtbcWvfvWr+M+CIOC5554r2fFwtGlra4MgCFixYkXG773gggtwxhlnxH8+4YQT8N3vfjf+c/I44NCHmdekW265BYcddljJvp+VeZGmeYDbHsWBpjHD4ZgFM6/nHA4NlNouzTfJ+0KjQNt15nCRGQCwf/9+XHrppWhubobNZkNdXR0WLlyI999/P+17zzrrLGzcuLEIR5kbMeEq+d+5556LY445Bu3t7fD5fLo+S22CUvuM3//+9/B4PAiFQvHfDQwMQJZlHHfccQnvf/vttyEIQk7X0kybzQsuuED1fmzevLkg37d06VJccsklBfnsbEkWRGOY6T5mito9V/674IILcvr8++67D48++mhejjWfxMb7ZZddNupvV1xxRV7OHTDvhuy9996DJEn4/Oc/n9H71ISfUq9J2Z4LAHz/+9/Ha6+9VoCjSkTLmG1vb8epp55a8O9Xo1jPCGDM9QAA9u7di6uvvhrjxo2DzWZDU1MTTj/99JRjIlP7pVikm+tPPfVUyLKMP//5z6rvv/TSS3HooYeq/u2WW26BIAiqz9jdd98NQRBwwgkn5PN0CjJmlHaQLMuora3FggUL8MgjjyASieT1u8xMsW3pQlNI+1fLrjQiemzgTNbzQtk//DnN7doqr5/FYkFzczMuv/xydHd35/cgTUQ2az2NFFsLAIBnn30Wt99+e8E+X0ku+4FikEtQFyc9XGQG8NWvfhUrV67EY489ho0bN+L555/HCSecgK6urrTvdTgcqKmpKcJR5of//ve/aG9vj/974IEHYLVaUVdXB0EQsv5ctc+YP38+BgYGsGzZsvjv3n77bdTV1WHp0qUYGhqK//7NN99EQ0MDJk2alPUx5AtCSIIxXyg+//nPJ9yL9vZ2jB07tiDfVV1dDafTWZDPNhqBQGDU78LhcFbGcLbv00J5r3/1q1/B6/Um/O6+++7L6nNjx+nz+QoqsgaDwazf29TUhKeeegrDw8Px342MjODJJ59Ec3NzPg4vb+T7vqfjkUcewdVXX4133nkHO3bsyOmzSr0m5XIubrcblZWVBTqy9NTV1cFms5Xs+4v1jBhxPWhra8Phhx+O119/HXfffTdWr16Nl19+GfPnz8eVV16p+p5gMJgX+6UQpJvrn3rqKZx22mlYsmTJqPcODw/jqaeewoUXXqj5+fX19XjjjTewa9euhN8vWbKkIPNpocZMzA5qa2vDv//9b8yfPx/XXnstvvjFL2raYbmsQ2akGLZ0sezeGMW0f81MKdZzNfsnm+eUc5DY9du2bRv+8Ic/4IUXXsAVV1xR6sMqCdms9TSTr7lQbe+rRkVFBTweT8afnw353NsYHb3XnyWYF5l7enrwzjvv4K677sL8+fPR0tKCI488EjfeeCNOO+20+GsuueQS1NbWwm63Y8aMGfjXv/4FQN27+cILL+Dwww+H3W7HuHHjcOuttyYswoIg4KGHHsKXv/xlOJ1OTJw4Ec8//3zCZ6xZswannXYavF4vPB4PjjvuOGzZsiX+9yVLlmDq1Kmw2+2YMmUKfvvb3+o638rKStTV1cX/+Xw+1cjRd999F/PmzYPT6UR5eTkWLlyI7u5uXHDBBXjrrbdw3333xT1ubW1tqp/x6aefwmKx4HOf+xxaW1txzz334M0338SiRYswfvx4jB07Fj/72c/wne98B7feeit6enrw29/+Fj/4wQ8wZswYuFwuHHXUUXjzzTfjn7l9+3acfvrpKC8vh8vlwvTp0/HSSy+hra0N8+fPBwCUl5cnRH0RQnD33Xdj3LhxcDgcmDlzJv7+97/HPzN27K+88grmzJkDm82Gt99+GyeccAKuueYa/OAHP0BFRQXq6upwyy236LrOeohFzSv/3XfffTjkkEPgcrnQ1NSEK664AgMDA/H3xMbbv/71L0yePBlOpxNnnnkmBgcH8dhjj6G1tRXl5eW4+uqrEQ6H4+9Llep64okn4qqrrkr4XWdnJ2w2G15//fW8nW+2PPPMM5g+fTpsNlt8HClpbW3FT3/6U1xwwQXw+Xy4+OKLE67TtGnTYLPZsH37dnR3d+O8885DeXk5nE4nTj31VGzatCn+WVrvyxfJz54gCKN+F2Pr1q2YP38+nE4nZs6cmZBZoXWcmUbx9Pb24pJLLkFNTQ28Xi9OPPFErFy5Mv73WMTnI488Eo84IIRkde6zZ89Gc3Mznn322fjvnn32WTQ1NWHWrFkAgD/96U+orKyE3+9PeO9Xv/pVnHfeeQCAlStXYv78+fB4PPB6vTj88MOxbNkyvPnmm/j2t7+N3t7e+NwUe14DgUDKeUXter799tuQZRl79+5NOJbrr78exx9/fFbXQI3BwUE8/fTTuPzyy/HFL35xVCT6888/jzlz5sBut6Oqqgpf+cpXAEQzSrZv347vfe978fNVnouS3/3udxg/fjysVismT56Mxx9/POHvetakXM8lNs++9tprmDNnDpxOJ4455hhs2LAh/prkCOPYeP7Zz36G2tpalJWVxdfTG264ARUVFWhsbMQjjzyScBw//OEPMWnSJDidTowbNw433XRTXJh69NFHceutt2LlypXx6xY7zuRyGatXr8aJJ54Ih8OByspKXHLJJQnzcez4/t//+3+or69HZWUlrrzyyqxFMD3PCKA+nx922GEJ69Mtt9wSz85qaGjANddco/n+VDZOsYhFa3/00Uc488wzMWnSJEyfPh3XXXcdPvjgAwDR+/P73/8eixYtgsvlwk9/+tNRtke2a2S6OSJT9Mz1F154Id544w20tbUlvPfvf/87RkZGcO6552p+fk1NDU455RQ89thj8d+999576OjoiNuuMSKRCG677TY0NjbCZrPhsMMOw8svvxz/+9y5c/GjH/0o4T0HDhyALMt44403AIweM+nWDr3E7KAxY8Zg9uzZ+PGPf4x//vOf+Pe//53wXCbf93A4jAsvvBBjx46Fw+HA5MmTRzlpCzF/lILJkyejoaEhYTwqben33nsv4ffz58/Hn//8Z8yZMwcejwd1dXU4++yzsX///oTXqdm9xSIX+/eVV17B1KlT4Xa74wINEJ3zHnvsMfzzn/+Mz+2xa5bunmrZFYODg/B6vQl7BiC6z3O5XOjv7y/odUpez7Oxf7Kxe5Ptn9j9uvfee/Hd735X9TndsWMHFi1aBLfbDa/Xi69//evYt29fwvlo2TOAermqsrKy+OfHog6ffvppHHfccXA4HDjiiCOwceNGLF26FHPmzImPiQMHDiR8Tqo9c+xzn332WVWbO9W11fOcPfbYY+jt7cUXv/hFjB8/Hnv37sXu3bvx73//G8DB+bmsrAyCIIyan7M976VLl2LBggWoqqqCz+fDvHnzsHz58oTrUgo9Qs9an24sKfcmzc3NcLvduPzyyxEOh3H33Xejrq4ONTU1uOOOOxK+W8+69fOf/xy1tbXweDy48MILMTIyEv/b//73v7zvC9TmQkmS8NZbb+HII4+EzWZDfX09fvSjHyVoSSeccAKuuuoqXHfddaiqqsKCBQsAAGvXrsUXvvAFuN1u1NbW4lvf+hY6OjoS3qfMRm9vb8dpp50Gh8OBsWPH4i9/+Ytqic1M9wjp9japrvMrr7wCu90+KqP5mmuuwbx58+I/v/feezj++OPhcDjQ1NSEa665BoODg/G/t7a2xnUmj8eD5uZm/PGPf4z/PSbmz5o1KyEDTC1j/4wzzkjIJlTTHvQcE1MQxgkGg8TtdpPvfve7ZGRkZNTfw+EwOfroo8n06dPJq6++SrZs2UJeeOEF8tJLLxFCCFmyZAnx+Xzx17/88svE6/WSRx99lGzZsoW8+uqrpLW1ldxyyy3x1wAgjY2N5C9/+QvZtGkTueaaa4jb7SadnZ2EEEJ27dpFKioqyFe+8hWydOlSsmHDBvLII4+Q9evXE0II+eMf/0jq6+vJM888Q7Zu3UqeeeYZUlFRQR599FHN89y2bRsBQD755JNRf3vjjTcIANLd3U0IIeSTTz4hNpuNXH755WTFihXk008/Jb/+9a/JgQMHSE9PD5k7dy65+OKLSXt7O2lvbyehUGjUZyxbtoyIokgOPfRQ8rnPfY4sWbKEOBwOMnbsWPK3v/2NXH755cTr9ZKKigpy3333EbvdTr7yla8QAGTWrFnkf//7H9m8eTP5xS9+QWw2G9m4cSMhhJDTTjuNLFiwgKxatSp+L9566y0SCoXIM888QwCQDRs2kPb2dtLT00MIIeTHP/4xmTJlCnn55ZfJli1byJIlS4jNZiNvvvlmwvkfeuih5NVXXyWbN28mHR0dZN68ecTr9ZJbbrmFbNy4kTz22GNEEATy6quv6hhZqTn//PPJokWLRv3+l7/8JXn99dfJ1q1byWuvvUYmT55MLr/88vjflyxZQmRZJgsWLCDLly8nb731FqmsrCSnnHIK+frXv07WrFlDXnjhBWK1WslTTz0Vf19LSwv55S9/Gf8ZAPnHP/5BCCHkiSeeIOXl5Qnj/7777iOtra0kEonkfK5aaF0D5ViKjaPbbruNbNiwIT6OlixZEn99S0sL8Xq95Be/+AXZtGkT2bRpU/w6HXPMMeTdd98l69evJwMDA+RLX/oSmTp1Kvnf//5HVqxYQRYuXEgmTJhAAoEAIYRovq8QJM8dMWLP6pQpU8i//vUvsmHDBnLmmWeSlpYWEgwGUx5n8jWdN28eufbaaxOuVWwcRCIRcuyxx5LTTz+dLF26lGzcuJFcf/31pLKyMj4XLV68mLhcLrJw4UKyfPlysnLlyqzGROy47r33XnLSSSfFf3/SSSeRX/7yl2TRokXk/PPPJ0NDQ8Tn85Gnn346/poDBw4Qq9VKXn/9dUIIIdOnTyfnnnsuWbduHdm4cSN5+umnyYoVK4jf7ye/+tWviNfrjc9N/f39hBBCzj77bHLMMcdozita13PSpEnk7rvvjh9LMBgkNTU15JFHHsn4Gmjx8MMPkzlz5hBCCHnhhRcSnrt//etfRJIkcvPNN5O1a9eSFStWkDvuuIMQQkhnZydpbGwkt912W/x8Y+eiHFfPPvsskWWZPPDAA2TDhg3knnvuIZIkxa8nIenXpHycS+y5Puqoo8ibb75J1qxZQ4477jhyzDHHxN+/ePFiMnPmzPjP559/PvF4POTKK68k69evJw8//DABQBYuXEjuuOMOsnHjRnL77bcTWZbJjh074u+7/fbbybvvvku2bdtGnn/+eVJbW0vuuusuQgghQ0ND5PrrryfTp0+PX7ehoaH4dYjNi4ODg6ShoYF85StfIatXryavvfYaGTt2LDn//PMTjs/r9ZLLLruMrFu3jrzwwgvE6XSSP/7xjxldt9hn6XlGCBk9nxNCyMyZM8nixYsJIYT87W9/I16vl7z00ktk+/bt5MMPP0w4JuX709k4xaCzs5MIgkB+9rOfpXwdAFJTU0MefvhhsmXLFtLW1jbK9sh2jUw3R+SC1lwfCoVIfX19/L7FOOGEE8jXv/51zc+LPSfPPvssmTBhQvz3F154Ibn22mvJtddeS+bNmxf//b333ku8Xi958sknyfr168kPfvADIsty/Nx+/etfk+bm5oS5/de//jUZM2YMCYfDhJDM1w49aNkAhETH86mnnkoIUb/vgUCA3HzzzeSjjz4iW7duJX/+85+J0+kkf/3rXxM+P9/zR6k4++yzySmnnBL/+Ygjjojb0j/+8Y8JIYT4/X7icDjIQw89RB5++GHy0ksvkS1btpD333+fHH300fHrSYi23VsMcrV/Tz75ZLJ06VLy8ccfk6lTp5Kzzz6bEEJIf38/+frXv04+//nPx+d2v99PCEl/T7XsCkIIufjii8kXvvCFhGP98pe/TM4777yCXAflnJY8d2Rj/2Rr98bsn9hxqtk/sec0EomQWbNmkc997nNk2bJl5IMPPiCzZ89OmIdS2TOEJK6/MXw+X9zeV9rGL7/8Mlm7di05+uijyezZs8kJJ5xA3nnnHbJ8+XIyYcIEctlll8U/I92eOZ3Nnera6n3OvF5v/DlbtmwZcblcxOFwEEIOzs+tra3kiiuuGDU/Z3ver732Gnn88cfJ2rVrydq1a8mFF15IamtrSV9fX8I1L6YeoWet1zOWFi9eTNxuNznzzDPJmjVryPPPP0+sVitZuHAhufrqq8n69evJI488QgCQ999/P/656datv/71r8RqtZIHH3yQrF+/nvzf//0f8Xg8CXZpPvcFWnPArl27iNPpJFdccQVZt24d+cc//kGqqqoSbIV58+YRt9tNbrjhBrJ+/Xqybt06smfPHlJVVUVuvPFGsm7dOrJ8+XKyYMECMn/+/IT3KfeFJ598MjnssMPIBx98QD7++GMyb9484nA4RmkGme4RUu0H0l3nUChEamtryUMPPRT/vNjv/vCHPxBCCFm1ahVxu93kl7/8Jdm4cSN59913yaxZs8gFF1wQf09LSwupqKggDzzwANm0aRO58847iSiKZN26dYQQQj766CMCgPz3v/8l7e3t8fNJvkaEkAQbPPbZydqDnmNiCeZFZkII+fvf/07Ky8uJ3W4nxxxzDLnxxhvJypUrCSGEvPLKK0QURbJhwwbV9yYbAMcdd9yoyfPxxx8n9fX18Z8BkJ/85CfxnwcGBoggCOTf//43IYSQG2+8kYwdOzZuACTT1NRE/vKXvyT87vbbbydz587VPMfYIuVwOIjL5Yr/W758+ahN2je/+U1y7LHHan6W2sOX/Blnn302WbBgAfnjH/9IXC4XCQaD5NprryUAyL59+8hTTz1FbDYbOffcc8lbb71FAJBNmzYRAOTOO+9M+OyTTjqJ3HjjjYQQQg455JAEwT7VMRASvbZ2u5289957Ca+98MILyTe/+c2E9z333HOjzvNzn/tcwu+OOOII8sMf/lDz2ujl/PPPJ5IkJdyLM888c9Trnn76aVJZWRn/ecmSJQQA2bx5c/x3l156KXE6nXGjhxBCFi5cSC699NL4z6lE5pGREVJRUZGwOTvssMM0r3O+ULsGLpeL2O32+H2MjSMlN9xwA5k2bVrCuZ1xxhkJr4ldp9gmgRBCNm7cSACQd999N/67jo4O4nA44qKm2vsKRTqRWbm4rlmzhgCIL4xax5mJyPzaa68Rr9c7yrk2fvz4+CK+ePFiIssy2b9/fw5nevC4Dhw4QGw2G9m2bRtpa2sjdrudHDhwIGHxvvzyyxOM9F/96ldk3LhxcePE4/FoGrBq13Tz5s1EEASye/fuhN8r5xWt63nXXXeRqVOnxn9+7rnniNvtzqvj4ZhjjiG/+tWvCCFRY7Wqqor85z//IYQQMnfuXHLOOedovldNbEy+Bscccwy5+OKLE17zta99LWHTnG5Nyse5xObZ//73v/HXv/jiiwQAGR4eJoSoi8wtLS1xoYsQQiZPnkyOO+64+M+hUIi4XC7y5JNPah7X3XffTQ4//PD4z8nfE0M5L/7xj38k5eXlCff6xRdfJKIokr179yYcXygUir/ma1/7GjnrrLM0j0WLTJ6RdCLzPffcQyZNmqRpQyjfn87GKQYffvghAUCeffbZlK8DQL773e8m/E5NZM50jdQzR+SC1lxPCCE//OEPSUtLS3x+27p1KxEEgbzyyiuanxcbv4FAgNTU1JC33nqLDAwMEI/HQ1auXDlKZG5oaEgQcwiJ2jJXXHEFIYSQ/fv3E4vFQv73v//F/z537lxyww03xH/OdO3QQyqR+ayzzorPvWr3XY0rrriCfPWrX034/ELMH6VAaUv39fURi8USt6VjjrqYLb1ly5ZR749tpmPPgJbdWwzyaf8+8MADpLa2NuGztcaUkuR7msqu+PDDD4kkSfH54cCBA0SW5XigSrbosYGT545M7Z9c7N6Y/RO7pmr2T+w5ffXVV4kkSQnOmpjd+tFHHxFC0tszekVmpW385JNPEgDktddei//uzjvvJJMnT47/nG7PrNfm1prDlWg9Z6IoJtzb2H58ZGSENDQ0kKuuuooIgkC2bdtGCEmcn7M972RCoRDxeDzkhRdeiP+u2HqEnrVez1havHgxcTqdCYL5woULSWtr66j5PqYp6Fm35s6dmyDUE0LIUUcdlWAv5nNfoDUX/vjHPyaTJ09OcPw+8MADxO12x89v3rx55LDDDkv4vJtuuinBGUkIITt37owH4MXeF9sXrlu3jgAgS5cujb8+psUkawaZ7hHS7W3SXedrrrmGnHjiifGfX3nlFWK1WklXVxchhJBvfetb5JJLLkn4jLfffpuIohjfU7S0tJBzzz03/vdIJEJqamrI7373O0KIdgCmXpE5WXvQc0wswXy5DCCair1nzx48//zzWLhwId58803Mnj0bjz76KFasWIHGxkbd9c0+/vhj3HbbbXC73fF/F198Mdrb2xPqpikburhcLng8nniKzYoVK3DcccdBluVRn3/gwAHs3LkTF154YcJ3/PSnP42nr5x66qnx30+fPj3h/X/961+xYsWK+L9p06aN+o4VK1bgpJNO0nW+Wqxbtw7HHnss5s+fj8HBQSxdujReA6iyshLz5s2D3+/HlClT8Oabb6K5uRmffPIJAGDx4sUJ5/bWW2/Fz+2aa67BT3/6Uxx77LFYvHgxVq1alfI41q5di5GRESxYsCDhM//0pz8lpPsAwJw5c0a9P7nxTn19fUIqVC7Mnz8/4V7cf//9eOONN7BgwQKMGTMGHo8H5513Hjo7OxNSLZxOJ8aPHx//uba2Fq2trXC73Qm/03ucNpsN5557bjxldMWKFVi5cmXemkylIvkarFixAg899FD877FxpOTYY4/Fpk2bElKd1e6d1WpNuH/r1q2DxWLBUUcdFf9dZWUlJk+ejHXr1mm+r1Qoj6G+vh4AEu5prsf58ccfY2BgAJWVlQnPxrZt2xKejZaWFlRXV2f9PUqqqqpw2mmn4bHHHsOSJUtw2mmnoaqqKuE1F198MV599VXs3r0bQDQVL9YcAwCuu+46XHTRRTj55JPx85//fNRznMzy5ctBCMGkSZM05xVA/XpecMEF2Lx5czyF75FHHsHXv/51uFyunK8FAGzYsAEfffQRvvGNbwAALBYLzjrrrIRnMV9zsZJjjz02YcwDqdckPaQ7F7XvURvXyUyfPh2ieNBUqa2txSGHHBL/WZIkVFZWJnzG3//+d3zuc59DXV0d3G43brrppozrwa1btw4zZ85MuNfHHnssIpFIQomP6dOnQ5KkhHPKZY3Q84yk42tf+xqGh4cxbtw4XHzxxfjHP/6hWTczUxunEJDPSvDoqausNtcnk+kaqXeOKAQXXnghtm/fHi9N9cgjj6CxsREnn3wyduzYkXA8P/vZzxLeK8syzj33XCxZsgR/+9vfMGnSpFFzWF9fH/bs2ZNyDqiursaCBQvwxBNPAAC2bduG999/H+ecc47qMetdO3KBEJIwHtTu++9//3vMmTMH1dXVcLvdePDBB0c956WaP/KN0pZ+++23MWnSJNTU1GDevHlYunQpBgcH47b0uHHj8Mknn2DRokVoaWmBx+OJpwEnn4ee56kQ5Mv+1TvfprunqeyKI488EtOnT8ef/vQnAMDjjz+O5ubmvJTNSmcDJ5Op/ZOL3Ruzf2IlGNTsn9hzum7dOjQ1NaGpqSn+t2nTpqGsrCz+PfmwZ4BEG6K2thYAEp5p5dyuZ8+s9rl6bBMAup+zY489FitWrMCHH36Iq6++GgsWLIDL5cITTzyBPXv2YM+ePZg/fz5aW1vjr09lo6U779ixX3bZZZg0aRJ8Ph98Ph8GBgZGHVsh9Yhk9Kz1esYSEC1XoKwtXFtbi2nTpo2a72PnomfdWrduHebOnZtwPMk/53tfoDYXxo5DeZ2OPfZYDAwMJPRhSJ6/P/74Y7zxxhsJ5zdlyhQAUL0nGzZsgMViwezZs+O/mzBhAsrLy0e9NpM9Qrr9gJ7rfM455+DNN9/Enj17AABPPPEEvvCFL8SP7eOPP8ajjz6acK4LFy5EJBLBtm3bVI87VrYsXzqO2vXXc0ysYCn1ARgFu92OBQsWYMGCBbj55ptx0UUXYfHixfj+97+f0edEIhHceuutCXWmlN8RI3nCFgQh3mjB4XCk/HwAePDBBxOMBgDxje5DDz0UbxyU/D1NTU2YMGFCynNI9f16iRkeEyZMQGNjI9544w2sXr06PvnX1dXBYrFg586d2LBhA0488cT4uV188cWjauHENocXXXQRFi5ciBdffBGvvvoq7rzzTtxzzz24+uqrVY8j9pkvvvgixowZk/C35AZPagtEqvuUKy6XK+FebN++HV/4whdw2WWX4fbbb0dFRQXeeecdXHjhhQm149SOKdfjvOiii3DYYYdh165deOSRR3DSSSehpaUlyzPTT/I1AJCwgCZvNGO/U/ucZBwOR8J71d6n9h3J7ysVynsaOx7lPc31OCORCOrr61XrjiprAOZLUI3xne98J14D/IEHHhj191mzZmHmzJn405/+hIULF2L16tV44YUX4n+/5ZZbcPbZZ+PFF1/Ev//9byxevBhPPfUUvvzlL6t+XyQSgSRJ+PjjjxPEQAAJopPa9aypqcHpp5+OJUuWYNy4cXjppZdyqtOazMMPP4xQKJQwNxFCIMsyuru78zIXA6MNerXnKtc5JN25qH2P2rhOJtP57oMPPsA3vvEN3HrrrVi4cCF8Ph+eeuqpUbXc06F2jZKPW+v4cl0j0j0joiiOms+Ua0RTUxM2bNiA//znP/jvf/+LK664Ar/4xS/w1ltvjTrefI2xXJg4cWJcqEhXU17PfJTpmNE7RxSCiRMn4rjjjsOSJUswf/58PPbYY/j2t78NURTR0NCQ0PW8oqJi1Pu/853v4KijjsKnn36K73znO5rfk24OOOecc3Dttdfi17/+Nf7yl79g+vTpmDlzpupn6V07cmHdunUJzY+S7/vTTz+N733ve7jnnnswd+5ceDwe/OIXv8CHH36Y8LpSzR/5RmlLd3d3x+tS1tXVYezYsXj33Xfxxhtv4MQTT8Tg4CBOOeUUnHLKKfjzn/+M6upq7NixAwsXLhzVnCjf67te8mn/atl2MfTc03R2xUUXXYTf/OY3+NGPfoQlS5bg29/+dl7sxHQ2cDKZ2j+52L0x++fTTz/FuHHj8N///nfUMx97TrXWS+Xv0601avdSrRa6mg2R/Dvl3A6k3jOn+txUa3kmz5nH44nf5/vvvx/z58/H+PHj44691157LWGtT2ejpTtvICqGHjhwAL/61a/Q0tICm82GuXPnjjq2QuoRyehZ6/WMJa3jTrfO52Pdyve+QG0OSLX3Vf4+ef6ORCI4/fTTcdddd436npjjRO0z9fw+E1tX734gFUceeSTGjx+Pp556Cpdffjn+8Y9/JDRKjkQiuPTSSxP6jcRQNj/OxkZPZ2PHULv+eo6JFbjIrMG0adPw3HPP4dBDD8WuXbuwceNGXZE+s2fPxoYNG9IKuak49NBD8dhjjyEYDI56OGprazFmzBhs3bpVM8okWUzN5vtfe+013Hrrrap/t1qtCVGkakybNg3vvPMOgKiX7s0338Tq1avR0NAQX3zsdjs2bNiADz74AN/+9rfjjY0GBwdTXr+mpiZcdtlluOyyy3DjjTfiwQcfxNVXXw2r1QoACccWa2KxY8eOhGLxRmTZsmUIhUK455574mL8008/XZTvPuSQQzBnzhw8+OCD+Mtf/oJf//rXRfnedCjHUYz33nsPkyZN0jRiUn1WKBTChx9+iGOOOQZAtMHhxo0bMXXq1Lwds1mYPXs29u7dC4vFEo+eKAaf//zn40buwoULVV9z0UUX4Ze//CV2796Nk08+OSGiAQAmTZqESZMm4Xvf+x6++c1vYsmSJfjyl7+sOjfNmjUL4XAY+/fvx3HHHZfx8V500UX4xje+gcbGRowfP35URGC2hEIh/OlPf8I999yDU045JeFvX/3qV/HEE0/E5+Jvf/vbqp+hZy6eOnUq3nnnnXjjRCD6DOVzzOs5lxkzZuTt+1Lx7rvvoqWlBf/3f/8X/11y8069a9hjjz2GwcHBuCH57rvvQhTFgkf9pntGqqur482ugGi0anKUhMPhwJe+9CV86UtfwpVXXokpU6Zg9erVCRErADK2cQpBRUUFFi5ciAceeADXXHPNKMO9p6cnb+KlGrnOEbly4YUX4vLLL8eiRYuwa9eu+PNusVjS2pLTp0/H9OnTsWrVKpx99tmj/u71etHQ0IB33nknIfLyvffew5FHHhn/+YwzzsCll16Kl19+GX/5y1/wrW99S/M7C712vP7661i9ejW+973vab7m7bffxjHHHIMrrrgi/rt8RFHrmT9KRcyW7u7uxg033BD//bx58/DKK6/Eben169ejo6MDP//5z+Nr57Jly0p12LrIl/2rNrfrvadadgUAnHvuufjBD36A+++/H2vWrMH555+f8bHli0zsn1zt3osuugiLFi2CKIqj7B/lc9rY2IgdO3Zg586d8TG3du1a9Pb2xr8nnT2TvK5t2rQpIQM4G/TsmfWgdm1zec4WL14cX+d9Ph9GRkYSgtOS5+dsePvtt/Hb3/4WX/jCFwAAO3fuTGgAp4dc9Yhk9Kz106ZNSzuWskHPujV16lR88MEHCfZyLGJZSaH2BTGmTZuGZ555JkFsfu+99+DxeFJqPLNnz8YzzzyD1tZWWCzpJb4pU6YgFArhk08+weGHHw4A2Lx586iGe5mgZz+g9zqfffbZeOKJJ9DY2AhRFBOaGs+ePRtr1qzJSW9T042A0XNROBzGp59+ivnz56f8vHwcE00wXy6js7MTJ554Iv785z9j1apV2LZtG/72t7/h7rvvxqJFizBv3jwcf/zx+OpXv4r//Oc/2LZtG/79738ndH5VcvPNN+NPf/oTbrnlFqxZswbr1q3DX//6V/zkJz/RfUxXXXUV+vr68I1vfAPLli3Dpk2b8Pjjj8dTdG+55RbceeeduO+++7Bx40asXr0aS5Yswb333puXa3LjjTdi6dKluOKKK7Bq1SqsX78ev/vd7+KLU2trKz788EO0tbWho6ND1SN0/fXX47XXXsPtt9+OqVOn4q233sLevXsTIsNtNhvef/99jIyMYP78+Zg0aRLKysrw3HPP4dlnn8W2bduwdOlS3HXXXXjppZcAAN/97nfxyiuvYNu2bVi+fDlef/31+KLT0tICQRDwr3/9CwcOHMDAwAA8Hg++//3v43vf+x4ee+wxbNmyBZ988gkeeOCBhK7sRmD8+PEIhUL49a9/ja1bt+Lxxx/H73//+6J9/0UXXYSf//znCIfDmlERxUY5jjZu3IjHHnsMv/nNbzLOMACiHvRFixbh4osvxjvvvIOVK1fi3HPPxZgxY7Bo0aICHL2xOfnkkzF37lycccYZeOWVV9DW1ob33nsPP/nJTwq6IZUkCevWrcO6des0HQXnnHMOdu/ejQcffDAhOm94eBhXXXUV3nzzTWzfvh3vvvsuli5dGp8DWltbMTAwgNdeew0dHR0YGhrCpEmTcM455+C8887TnFdSEYt8+ulPf6q5OcqGf/3rX+ju7saFF16IGTNmJPw788wz8fDDD2Px4sV48sknsXjxYqxbtw6rV6/G3XffHf+M1tZW/O9//8Pu3bs1Nw833HADHn30Ufz+97/Hpk2bcO+99+LZZ5/N6hnK5VyKxYQJE7Bjxw489dRT2LJlC+6//3784x//SHhNa2srtm3bhhUrVqCjowN+v3/U55xzzjmw2+04//zz8emnn+KNN97A1VdfjW9961vxVNVCke4ZOfHEE/H444/j7bffxqefforzzz8/4XWPPvooHn74YXz66afxtcThcKhmp2Rq4xSK3/72twiHwzjyyCPxzDPPYNOmTVi3bh3uv//+UWmU+SbXOSJXvva1r0GWZVx66aU46aSTMhZuX3/9dbS3t2sK8TfccAPuuusu/PWvf8WGDRvwox/9CCtWrMC1114bf43L5cKiRYtw0003Yd26daqCdYx8rh1+vx979+7F7t27sXz5cvzsZz/DokWL8MUvfjFhA5rMhAkTsGzZMrzyyivYuHEjbrrpJixdujSj79b63HTzR6mYP38+3nnnHaxYsSIhaGLevHl48MEH47Z0c3MzrFZr3JZ8/vnncfvtt5fwyNOTL/u3tbUVq1atwoYNG9DR0YFgMJj2nqazKwCgvLwcX/nKV3DDDTfglFNOQWNjY17OOxOysX9ytXsXLlwIWZaxYcMGnHnmmZrP6cknn4xDDz0U55xzDpYvX46PPvoI5513HubNmxdPKU9nz5x44on4zW9+g+XLl2PZsmW47LLLVMs0ZEo+9sxq1zaX5+yEE07AjBkzUFtbi4GBARBC8Pzzz2vOz9kwYcIEPP7441i3bh0+/PBDnHPOORlnLhVCj0i31usZS9mgZ9269tpr8cgjj+CRRx7Bxo0bsXjxYqxZs2bUZxVqXxDjiiuuwM6dO3H11Vdj/fr1+Oc//4nFixfjuuuuSygHksyVV16Jrq4ufPOb38RHH32ErVu34tVXX8V3vvMd1cCKKVOm4OSTT8Yll1yCjz76CJ988gkuueSSnDJl9ewH9F7n2Bi44447cOaZZyZUBPjhD3+I999/H1deeSVWrFiBTZs24fnnn9fMbFejpqYGDocDL7/8Mvbt24fe3l4A0bnoxRdfxIsvvoj169fjiiuu0CW85+OYaIJ5kdntduOoo47CL3/5Sxx//PGYMWMGbrrpJlx88cX4zW9+AwB45plncMQRR+Cb3/wmpk2bhh/84AeaUVALFy7Ev/71L/znP//BEUccgaOPPhr33ntvRqUHKisr8frrr2NgYADz5s3D4YcfjgcffDC+2F500UV46KGH8Oijj+KQQw7BvHnz8OijjyakFubCpEmT8Oqrr2LlypU48sgjMXfuXPzzn/+Me8W+//3vQ5IkTJs2LZ4elMzs2bPx9NNP46mnnsLNN9+MQCCAmpqahEXTbrfD7/dj/PjxcW9lc3MzDj30UFx//fWYPHkyvvSlL+HDDz+M/z0cDuPKK6/E1KlT8fnPfx6TJ0/Gb3/7WwDRCO5bb70VP/rRj1BbWxtPN7799ttx8803484778TUqVOxcOFCvPDCC3m7XvnisMMOw7333ou77roLM2bMwBNPPIE777yzaN//zW9+ExaLBWeffXbCRF5KlONoxowZuPnmm3HbbbdlXS96yZIlOPzww/HFL34Rc+fOBSEEL730Ul4MWbMhCAJeeuklHH/88fjOd76DSZMm4Rvf+Aba2toKLqJ5vV54vd6Uf//qV78Kt9udkFInSRI6Oztx3nnnYdKkSfj617+OU089NZ51ccwxx+Cyyy7DWWedherq6vgGZsmSJTjvvPM055VUiKKICy64AOFwOKXokSkPP/wwTj75ZPh8vlF/++pXv4oVK1bA6/Xib3/7G55//nkcdthhOPHEExPSwW+77Ta0tbVh/PjxmnWzzzjjDNx33334xS9+genTp+MPf/gDlixZEq8dWKxzWb58ed6+LxWLFi3C9773PVx11VU47LDD8N577+Gmm24adUyf//znMX/+fFRXV+PJJ58c9TlOpxOvvPIKurq6cMQRR+DMM8/ESSedFLcLCk2qZ+TGG2/E8ccfjy9+8Yv4whe+gDPOOCOhTmlZWRkefPBBHHvssfHosRdeeAGVlZWqn5eJjVMoxo4di+XLl2P+/Pm4/vrrMWPGDCxYsACvvfYafve73xX8+3OZI3LF6XTiG9/4Brq7u1OWvNDC5XKljPS+5pprcP311+P666/HIYccgpdffhnPP/88Jk6cmPC6c845BytXrsRxxx2XMrUzn2vHyy+/jPr6erS2tuLzn/883njjDdx///345z//mTJb6bLLLsNXvvIVnHXWWTjqqKPQ2dmZENWcLXrmj1Ixf/58DA8PY8KECQnXed68eejv74/b0tXV1Xj00Ufxt7/9DdOmTcPPf/5z/L//9/9KeOTpyZf9e/HFF2Py5MnxWt3vvvtu2nuazq6IceGFFyIQCGT1jOaDXOyfbO1eURQxYcIEEEJwxx13aD6ngiDgueeeQ3l5OY4//nicfPLJGDduHP7617/GP+uEE05Iac/cc889aGpqwvHHH4+zzz4b3//+9+F0OnO+bvnYM6td21yfs+uuuw4dHR0Ih8O44IIL0s7PmfLII4+gu7sbs2bNwre+9S1cc801qKmpyegzCqFHpFvr9YylbNCzbp111lm4+eab8cMf/hCHH344tm/fjssvv3zUZxVqXxBjzJgxeOmll/DRRx9h5syZuOyyy3DhhRemDVhsaGjAu+++i3A4jIULF2LGjBm49tpr4fP5NMXpP/3pT6itrcXxxx+PL3/5y7j44ovh8Xiy1gH07AcmTpyo6zpPnDgRRxxxBFatWjUqWv7QQw/FW2+9hU2bNuG4447DrFmzcNNNN6mWBdHCYrHg/vvvxx/+8Ac0NDTEHW/f+c53cP7558edG2PHjk0bxZyvY6IJgaQrZsXhcJhg586daG1txdKlS0elVHM4xWbBggWYOnUq7r///lIfCi6++GLs27cPzz//fKkPhcPhcDgcTpF54okncO2112LPnj3xNGsW4PZP4bjjjjvw1FNPYfXq1aU+FE6G0Ppc7Nq1C01NTfjvf/+bl0adHHbhNZk5HMYJBoNob2/Hj370Ixx99NFcYOaUlK6uLrz66qt4/fXXixY1qkVvby+WLl2KJ554Av/85z9LeiwcDofD4XCKy9DQELZt24Y777wTl156KTMCM7d/CsfAwADWrVuHX//614YvZcNJhLbnIhapfsghh6C9vR0/+MEP0NramtDDgcPJBi4ycziM8+6778ZrYv/9738v9eFwGGf27Nno7u7GXXfdhcmTJ5f0WBYtWoSPPvoIl156KRYsWFDSY+FwOBwOh1Nc7r77btxxxx04/vjjceONN5b6cIoGt38Kx1VXXYUnn3wSZ5xxRsnKr3Cyg7bnIhgM4sc//jG2bt0Kj8eDY445Bk888QSTZSQ5+YWXy+BwOBwOh8PhcDgcDofD4XA4HE7WMN/4j8PhcDgcDofD4XA4HA6Hw+FwONnDRWYOh8PhcDgcDofD4XA4HA6Hw+FkDReZORwOh8PhcDgcDofD4XA4HA6HkzVcZOZwOBwOh8PhcDgcDofD4XA4HE7WcJGZw+FwOBwOh8PhcDgcDofD4XA4WcNFZg6Hw+FwOBwOh8PhcDgcDofD4WQNF5k5HA6Hw+FwOBwOh8PhcDgcDoeTNVxk5nA4HA6Hw+FwOBwOh8PhcDgcTtZwkZnD4XA4HA6Hw+FwOBwOh8PhcDhZ8/8B3d52Zvctm7MAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 1800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def RecapGenre(Ui, movies_metadata, links_small, ratings_small):\n",
+    "    mat =  pd.read_csv('../archive/the-movies-dataset/predUser_MovieSVD.csv', index_col=0)\n",
+    "    mat.columns = np.int64(mat.columns[:].values)\n",
+    "    Hyb = hybride(mat, 'average', 10, 6)\n",
+    "    BDI, tabGrp = ClustersMovies(Hyb, 6, movies_metadata, links_small, ratings_small)\n",
+    "    \n",
+    "    res = str()\n",
+    "    ind,res = VotreGroupe(Ui,BDI, tabGrp)\n",
+    "    res += CompareSelectGenres(BDI[ind], movies_metadata, ratings_small, str(ind+1), \"Global\")\n",
+    "    res += CompareEvalGenres(BDI[ind],movies_metadata,ratings_small,links_small, str(ind+1), \"Global\")\n",
+    "    return res\n",
+    "print(RecapGenre(1, movies_metadata, links_small, ratings_small))"
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f70b8b2e-881f-4223-85e0-91b086bb6367",
-   "metadata": {
-    "lines_to_next_cell": 2
-   },
+   "id": "413d574f-55aa-4d8e-9da9-a19913089764",
+   "metadata": {},
    "outputs": [],
    "source": []
   }
diff --git a/py/AnalyseData.py b/py/AnalyseData.py
index 6cbb629957e23a2a21ddb3e1238e2f2e1737d842..0b073e6efa216d23ac3792f28b159ca43cb67ab7 100644
--- a/py/AnalyseData.py
+++ b/py/AnalyseData.py
@@ -43,12 +43,6 @@ if __name__=='__main__':
     
     location = "../archive/the-movies-dataset/"
 
-    credits = pd.read_csv(location+"credits.csv")
-    #Contains Cast, Crew, ID 
-
-    keywords = pd.read_csv(location+"keywords.csv")
-    #Contains ID, keywords
-
     links_small = pd.read_csv(location+"links_small.csv")
     #Contains IMDB and TMDB IDs of all movies featured in the ratings_small.csv file (About 9000 movies).
 
@@ -124,11 +118,11 @@ def TestEfficacite(matRec, ratings_small):
 
 # +
 # Protect execution
-if __name__=='__main__':
+#if __name__=='__main__':
     #mat = MatrixReco(movies_metadata, links_small, ratings_small,algorithm='SVD')
-    mat =  pd.read_csv('../archive/the-movies-dataset/predUser_MovieSVD.csv', index_col=0)
-    mat.columns = np.int64(mat.columns[:].values)
-    mat_imput = imputerData(mat, 'most_frequent')
+    #mat =  pd.read_csv('../archive/the-movies-dataset/predUser_MovieSVD.csv', index_col=0)
+    #mat.columns = np.int64(mat.columns[:].values)
+    #mat_imput = imputerData(mat, 'most_frequent')
     #TestEfficacite(mat_imput,ratings_small)
 
 # pour-l'algo-KNN-l'erreur:
@@ -147,7 +141,7 @@ def CentreReduire(data):
     return Xnorm
 
 
-def ACP(data, minPerte, strat='most_frequent', annotation=True, cluster=[], nom="") :
+def ACP(data, minPerte, annotation=True, cluster=[], nom="") :
     labels = data.index
     Xnorm = CentreReduire(data)
     
@@ -181,6 +175,8 @@ def ACP(data, minPerte, strat='most_frequent', annotation=True, cluster=[], nom=
             plt.annotate(l, xy=(x, y), xytext=(-0.2, 0.2), textcoords='offset points')
     plt.title("ACP qui conserve {} % d'info pour 2 vecteurs du graphique".format(res2vect))
     plt.suptitle("methode utilisé: "+nom, y=0)
+    plt.xticks([])
+    plt.yticks([])
     locSave = "../img/ACP"+nom+".png"
     plt.savefig(locSave)
     return plt
@@ -192,21 +188,15 @@ def ACP(data, minPerte, strat='most_frequent', annotation=True, cluster=[], nom=
 
 def methodeKMeans(X, q):
     Xnorm = CentreReduire(X)
-    model = KMeans(n_clusters=q, n_init=20).fit(Xnorm)
+    model = KMeans(n_clusters=q, n_init=30).fit(Xnorm)
     return model
 
 
-# Protect execution
-if __name__=='__main__':
-    c = methodeKMeans(mat_imput,2)
-    ACP(mat_imput, 0.9, annotation=False, cluster=c,nom="KMeans")
-
-
 def methodeAgglomerativeClustering(data, strat='ward', q=2):
     Xnorm = CentreReduire(data)
     return AgglomerativeClustering(n_clusters=q, linkage=strat).fit(Xnorm)
 
-
+# permet de trouver quelle est la meilleur méthode
 def deterQ(data,nbC):
     Xnorm = CentreReduire(data)
     matrix = pd.DataFrame(index=['kmeans','single','average','ward'], columns=range(2,nbC+1))
@@ -234,7 +224,7 @@ def deterQ(data,nbC):
 #res = deterQ(mat_imput, 30)
 #res
 # -
-#non utilisé mais montre qu'il faut utiliser les valeurs quand la courbe s'applanie 
+# utilisé montre qu'il faut utiliser les valeurs quand la courbe s'applanie 
 def deterCoudé(data):
     Xnorm = CentreReduire(data)
     
@@ -254,11 +244,12 @@ def deterCoudé(data):
         inertias.append(kmeans.inertia_)
 
     # Tracer la courbe de l'inertie par rapport à k
+    plt.figure(figsize=(14, 10))
     plt.plot(k_values, inertias, '-o')
     plt.xlabel('Nombre de clusters (k)')
     plt.ylabel("Inertie")
     plt.title("Méthode du coude")
-    plt.show()
+    plt.savefig("../img/deterCoude.png")
 #deterQ2(mat_imput)
 
 
@@ -292,21 +283,22 @@ def hybride(data, strat = 'average', Qkmeans1=16, Qkmeans2=5) :
     X_pca=pca.transform(Xnorm)
 
     colors = ['red','yellow','blue','pink','k','m','g','c']
-    axs[0].scatter(X_pca[:, 0], X_pca[:, 1], c= model.labels_,
-    cmap=matplotlib.colors.ListedColormap(colors))
-    print("efficacité hybride: ",metrics.silhouette_score(Xnorm, model.labels_))
-    axs[0].set_title('ACP hybride')
+    scat = axs[0].scatter(X_pca[:, 0], X_pca[:, 1], c= model.labels_,
+    cmap=matplotlib.colors.ListedColormap(colors[:Qkmeans2]))
+    # Ajouter une légende qui spécifie les numéros de cluster de 1 à Qkmeans2
+    legend_labels = [str(i+1) for i in range(Qkmeans2)]
+    axs[0].legend(handles=[plt.scatter([],[], color=colors[i], label=label) for i, label in enumerate(legend_labels)],
+                  title="Groupes", loc='upper left')
+    print("efficacite hybride: ",metrics.silhouette_score(Xnorm, model.labels_))
+    axs[0].set_xticks([])
+    axs[0].set_yticks([])
+    axs[0].set_title('ACP hybride, efficacité du clustering: {}'.format(metrics.silhouette_score(Xnorm, model.labels_)))
     axs[1].set_title('dendrogramme sur centre Kmeans')
     locSave = "../img/hybride_"+strat+".png"
     fig.savefig(locSave)
     return model
 
 
-# Protect execution
-if __name__=='__main__':
-    Hyb = hybride(mat_imput, 'average', 17, 6)
-
-
 def AgglomerativeComparaison(data, q):
     fig, axs = plt.subplots(2, 3, figsize=(18, 6), sharey=False)
     single = methodeAgglomerativeClustering(data, 'single',q)
@@ -330,10 +322,16 @@ def AgglomerativeComparaison(data, q):
     cmap=matplotlib.colors.ListedColormap(colors))
     axs[1][2].scatter(X_pca[:, 0], X_pca[:, 1], c= ward.labels_,
     cmap=matplotlib.colors.ListedColormap(colors))
+    axs[1][0].set_xticks([])
+    axs[1][0].set_yticks([])
+    axs[1][1].set_xticks([])
+    axs[1][1].set_yticks([])
+    axs[1][2].set_xticks([])
+    axs[1][2].set_yticks([])
     
-    axs[0][0].set_title("single: {}".format(metrics.silhouette_score(Xnorm,single.labels_)))
-    axs[0][1].set_title("average: {}".format(metrics.silhouette_score(Xnorm,average.labels_)))
-    axs[0][2].set_title("ward: {}".format(metrics.silhouette_score(Xnorm,ward.labels_)))
+    axs[0][0].set_title("CAH par single:")
+    axs[0][1].set_title("CAH par average:")
+    axs[0][2].set_title("CAH par ward:")
     
     locSave = "../img/CAHcomparaison.png"
     fig.savefig(locSave)
@@ -373,17 +371,16 @@ def ClustersMovies(clusters, q, movies_metadata, links_small, ratings_small):
     return BDInterpretable, tabGrp
 
 
-
 def nbGroupe(tabgrp):
     calc = pd.Series(index=range(1,len(tabgrp)+1), dtype=float)
     calc2 = 0
-    for i in tabGrp:
+    for i in tabgrp:
         calc2 += len(i)
     for i in calc.index:
-        calc[i] = (len(tabGrp[i-1])/calc2)*100
-    plt.pie(calc, labels=calc.index, autopct='%1.1f%%')
-    plt.title("répartition des utilisateur dans les groupes")
-    plt.savefig("../img/repartionUi_Grp.png")
+        calc[i] = (len(tabgrp[i-1])/calc2)*100
+    #plt.pie(calc, labels=calc.index, autopct='%1.1f%%')
+    #plt.title("répartition des utilisateur dans les groupes")
+    #plt.savefig("../img/repartionUi_Grp.png")
     return calc
 
 
@@ -398,46 +395,97 @@ def VotreGroupe(Ui, BDI, tabGrp):
         print("erreur tu es dans aucun groupe")
         return
     calc = len(tabGrp[leGroupe])
-    res = "vous êtes dans le groupe "+str(leGroupe+1)+" qui est composé de "+str(calc)+" membres \n"
+    res = "vous etes dans le groupe "+str(leGroupe+1)+" qui est compose de "+str(calc)+" membres \n"
     pourcent = nbGroupe(tabGrp)
-    res +="c'est à dire "+str(pourcent[leGroupe+1])+" % de tout les utilisateurs. \n"
-    res +="voici les autres utilisateurs de votre groupe:\n"+str(tabGrp[leGroupe])
-    print(res)
-    return res
+    res +="c'est a dire "+str(pourcent[leGroupe+1])+" % de tout les utilisateurs. \n"
+    res +="voici les autres utilisateurs de votre groupe:\n"+str(tabGrp[leGroupe])+"\n"
+    return leGroupe, res
 
 
 # ## les genres
 
-def SelectionGenres(BDI, ratings_small, movies_metadata):
-    GrpParGenres = GroupeParGenres(BDI)    #df qui met les idMovie dans les collums genres
-    nbEval = pd.Series(index=GrpParGenres.columns, dtype=float) 
-    pourcent = pd.Series(index=GrpParGenres.columns, dtype=float)
-    for i in GrpParGenres.columns:#parcour les genres
-        nbEval[i] = len(GrpParGenres[i].dropna())
+def SelectionGenres(BDI, ratings_small, GrpParGenres, axs, nom= 'BDI'):
+    nbEval = GrpParGenres.count().drop('id')
+    pourcent = pd.Series(index=nbEval.index, dtype=float)
     for i in nbEval.index:
         pourcent[i] = (nbEval[i]/sum(nbEval)) * 100
     nbEval = nbEval.sort_values(ascending=False)
     pourcent = pourcent.sort_values(ascending=False)
-    plt.pie(pourcent, labels=nbEval.index, autopct='%1.1f%%')
-    plt.title("pourcentage des genres des films que votre groupe à évalué")
-    return nbEval
+    axs.pie(pourcent, labels=nbEval.index, autopct='%1.1f%%')
+    axs.set_title("répartion des genres des films evalué du groupe {}".format(nom))
+    return pourcent
 
 
-
-# Protect execution
-if __name__=='__main__':
+def CompareSelectGenres(GRP, GRP2, ratings_small, nom1='BDI', nom2='BDI2'):
+    GRP_DfGenres = GroupeParGenres(GRP)    #df qui met  dans les collums genres    
+    GRP2_DfGenres = GroupeParGenres(GRP2)    #df qui met  dans les collums films
+    fig, axs = plt.subplots(1, 2, figsize=(18, 6), sharey=False)
+    prcEval = SelectionGenres(GRP, ratings_small, GRP_DfGenres, axs[0], nom1)
+    prcEval2 = SelectionGenres(GRP2, ratings_small, GRP2_DfGenres, axs[1], nom2)
+    locSave = "../img/CompareSelectGenre.png"
+    fig.savefig(locSave)
+    
+    res = prcEval-prcEval2
+    res = res.sort_values(ascending=False)
+    resStr = str()
+    resStr += "votre groupe "+nom1+" evalue beaucoup de film de "+str(res.index[0])+" c'est "+str(res.iloc[0])+" de plus que le groupe "+nom2+"\n"
+    resStr += "votre groupe "+nom1+" evalue peu de film de "+str(res.index[-1])+" c'est "+str(res.tail(1).iloc[0])+" en moins que le groupe "+nom2+"\n"
+    return resStr
+
+
+# On veut aussi comparer les stats du types notes, pourquoi pas faires des violin
+
+def EvalParGenres(BDI, ratings_small, links_small, axs, nom='BDI'):
+    GRP_DfGenres = GroupeParGenres(BDI)
+    ids_par_genres = {}
+    Notes_par_genres = {}
+    stats_par_genres = {}
+    for g in GRP_DfGenres.columns.drop('id'):
+        ids_par_genres[g] = GRP_DfGenres.loc[GRP_DfGenres[g] == 1, 'id'].tolist()
+        Notes_par_genres[g] = RatingsFromMovies(ids_par_genres[g],ratings_small, links_small)
+        stats_par_genres[g] = Notes_par_genres[g]['rating'].describe()
+    axs.set_title("répartion des notes des films du groupe {}".format(nom))
+    data = [Notes_par_genres[key]['rating'] for key in Notes_par_genres.keys()]
+    pos = range(len(Notes_par_genres))
+    axs.violinplot(data, pos, widths=0.7, showmeans=True, showextrema=True, showmedians=True)
+    axs.set_xticks(pos, Notes_par_genres.keys())
+    return stats_par_genres
+
+
+def CompareEvalGenres(GRP, GRP2, ratings_small, links_small, nom1='BDI', nom2='BDI2'):
+    fig, axs = plt.subplots(2, 1, figsize=(18, 6), sharey=False)
+    stats = EvalParGenres(GRP, ratings_small, links_small, axs[0], nom1)
+    stats2 = EvalParGenres(GRP2, ratings_small, links_small, axs[1], nom2)
+    locSave = "../img/CompareEvalGenre.png"
+    fig.savefig(locSave)    
+    meilleurG= []
+    meilleurG2 = []
+    diff = []
+    for g in stats:
+        meilleurG.append((g,stats[g][1]))
+        meilleurG2.append((g,stats2[g][1]))
+        diff.append((g,stats[g][1]-stats2[g][1]))
+    max_MeansDiff = max(diff, key=lambda x: x[1])
+    max_Means = next(filter(lambda t: t[0] == max_MeansDiff[0], meilleurG))
+    min_MeansDiff = min(diff, key=lambda x: x[1])
+    min_Means = next(filter(lambda t: t[0] == min_MeansDiff[0], meilleurG))
+    resStr = str()
+    resStr = "votre groupe "+nom1+" aime particulierement les films de "+str(max_MeansDiff[0])+" attribue une note moyenne de "+str(max_Means[1])+" c'est "+str(max_MeansDiff[1])+"de plus que le groupe "+nom2+"\n"
+    resStr += "votre groupe "+nom1+" n'aime pas particulierement les films de "+str(min_MeansDiff[0])+" attribue une note moyenne de "+str(min_Means[1])+" c'est "+str(min_MeansDiff[1])+"de moins que le groupe "+nom2+"\n"
+    return resStr
+
+
+def RecapGenre(Ui, movies_metadata, links_small, ratings_small):
+    mat =  pd.read_csv('../archive/the-movies-dataset/predUser_MovieSVD.csv', index_col=0)
+    mat.columns = np.int64(mat.columns[:].values)
+    Hyb = hybride(mat, 'average', 10, 6)
     BDI, tabGrp = ClustersMovies(Hyb, 6, movies_metadata, links_small, ratings_small)
-    SelectionGenres(BDI[0], ratings_small, movies_metadata)
-
-
-
-
-
-
-
-
-
-
-
+    
+    res = str()
+    ind,res = VotreGroupe(Ui,BDI, tabGrp)
+    res += CompareSelectGenres(BDI[ind], movies_metadata, ratings_small, str(ind+1), "Global")
+    res += CompareEvalGenres(BDI[ind],movies_metadata,ratings_small,links_small, str(ind+1), "Global")
+    return res
+#print(RecapGenre(1, movies_metadata, links_small, ratings_small))
 
 
diff --git a/py/GenImage.py b/py/GenImage.py
new file mode 100644
index 0000000000000000000000000000000000000000..388a98fccbd56aebdb4ef65dfc3677782e33e883
--- /dev/null
+++ b/py/GenImage.py
@@ -0,0 +1,38 @@
+#Actualise les images sur la page principales
+
+
+from AnalyseData import *
+
+# Protect execution
+if __name__=='__main__':
+    
+    location = "../archive/the-movies-dataset/"
+
+    links_small = pd.read_csv(location+"links_small.csv")
+    #Contains IMDB and TMDB IDs of all movies featured in the ratings_small.csv file (About 9000 movies).
+
+    movies_metadata = pd.read_csv(location+"movies_metadata.csv", low_memory=False)
+    #Contains adult, belongs_to_collection, budget, genres, homepage, id, imdb_id, original_language, original_title, overview
+    # popularity, poster_path, production_companies, production_countries, release_date, revenue, runtime, spoken_languages, status
+    # tagline, title, video, vote_average, vote_count
+    
+    ratings_small = pd.read_csv(location+"ratings_small.csv")
+    #Contains userId, movieId, rating, timestamp
+    
+    movies_metadata = clean(movies_metadata)
+    links_small = cleanAnnalyse(links_small, ratings_small) 
+    
+    q=3
+    matKnn = MatrixReco(movies_metadata, links_small, ratings_small, algo_='KNN')
+    matKnn = imputerData(matKnn, 'most_frequent')
+    KMeansKnn = methodeKMeans(matKnn, q)
+    ACP(matKnn, 0.9, annotation=False, cluster=KMeansKnn, nom="KMeans_prédiction_Knn")
+
+    matSvd = MatrixReco(movies_metadata, links_small, ratings_small, algo_='SVD')
+    KMeansSvd = methodeKMeans(matSvd, q)
+    ACP(matSvd, 0.9, annotation=False, cluster=KMeansSvd, nom="KMeans_prédiction_Svd")
+    AgglomerativeComparaison(matSvd, q)
+    deterCoudé(matSvd)
+    hybride(matSvd, strat = 'average', Qkmeans1=16, Qkmeans2=6)
+
+
diff --git a/py/analyseArthur.py b/py/analyseArthur.py
index 7e1f671dff4fae9bf93674e43b2f9dd3306b18b3..0294ae902809743f8025287fcb682e05695eb15b 100644
--- a/py/analyseArthur.py
+++ b/py/analyseArthur.py
@@ -3,6 +3,7 @@ import numpy as np
 from system import *
 import sys
 import json
+import ast
 from recherche import *
 from surprise import Reader , Dataset , KNNBasic
 import csv
@@ -13,65 +14,41 @@ from FiltrageCollaboratif import idFromUserRating , infoFromId , StatUser , Comp
 from filtrage_actif import *
 from dataFrame import *
 from recherche_dans_bd import * 
+from AnalyseData import *
 
+#chemin vers archive
 location = "../archive/the-movies-dataset/"
 
-import ast
-
-# import import_ipynb
-# from TestBD.ipynb import dfToList
-md = pd.read_csv(CheminUnFichier("imdb.csv"))
-mov = pd.read_csv(CheminUnFichier("movies_metadata.csv"), low_memory=False)
-
-# print(md.dtypes)
-# print("j'ai affiché e head")
-# print(md["rating"])
-
-df=md
-gen = md
+# md = pd.read_csv(CheminUnFichier("imdb.csv"))
+# mov = pd.read_csv(CheminUnFichier("movies_metadata.csv"), low_memory=False)
+# df=md
+# gen = md
 #Liste sans les valeurs avec des nan
-df = df[df["rating"].notnull()]
-
-gen['genre'] = gen['genre'].fillna('Pas renseigné')
-gen['rating'] = gen['rating'].fillna(0)
+#df = df[df["rating"].notnull()]
+# gen['genre'] = gen['genre'].fillna('Pas renseigné')
+# gen['rating'] = gen['rating'].fillna(0)
 
+#fonction qui tri dans une base la colonne avec le x premiers
 def lesPremiers(base,colonne,x):
     sorted_d = sorted(base[colonne].items(), key=lambda item: item[1], reverse=True)
     s = [sorted_d[i] for i in range(x)]
     return tuple(s)
 
+#fonction qui tri dans une base la colonne avec le x derniers
 def lesDerniers(base,colonne,x):
     sorted_d = sorted(base[colonne].items(), key=lambda item: item[1], reverse=False)
     s = [sorted_d[i] for i in range(x)]
     return tuple(s)
 
-# ancienne version
-#  def geneChercher(legenre):
-#     matches=[] #pas sur de l'idée mais avoir une liste vide ds laquelle on append les occurrence
-#     for i in range(len(md)): # parcours jusqua len(md)
-#         if legenre in md["genre"][i]: # si dans md["genre"][i] il y a legenre cherché alors c'est cool
-#             match=md["id"][i] #pas sur de l'idée mais je le stocke dans une var
-#             matches.append(match) # pas sur de l'idée j'ajoute a la fin de ma liste la var d'avant
-#     return matches # pas sur de l'idée je retourne cette liste
-
-def filtreSurColonneStr(base,colonne,valeurs):
-    return base[base[colonne].str.contains(valeurs)]
-
-
+#fonction qui tri dans une base la colonne genre avec le genre cherché avec le x premiers
 def lesPremiersPrGenre(base,legenre,colonneTri,x):
-    # lesgenre = filtreSurColonneStr(gen,'genre',legenre)
-    # lesgenre.sort_values(by='rating')
-    if base=='gen':
-        base=gen
-    else:
-        base=df
     x=int(x)
     lesgenre=base[base['genre'].str.contains(legenre)].sort_values(by=colonneTri)
     return list(lesgenre['title'].reset_index(drop=True).head(x))    
     #return legenre.loc[:, 'title']
 
 
-def les_films_par_genre(df, genre, n):
+def filmsParGenre(df, genre, n):
     result = []
     for i, row in df.iterrows():
         if genre in row['genres']:
@@ -80,7 +57,8 @@ def les_films_par_genre(df, genre, n):
             break
     return result
 
-def dfToList(base):#fonction dans le code de valentin
+#fonction qui renvoi une colonne sous forme de liste
+def dfToList(base):
     l = list()
     s = str()
     for i in base:
@@ -89,6 +67,7 @@ def dfToList(base):#fonction dans le code de valentin
     del l[0]
     return l
 
+#fonction python qui demande dans le terminal de donner certaine info
 def recommandationBasique(base):
     justeGen=dfToList(gen['genre'])
     print("Parmit ces genres ",justeGen)
@@ -96,69 +75,27 @@ def recommandationBasique(base):
     x = int(input('Choisir un nombre de film :'))
     tri = str(input('Choisir sur quelle colonne trier (ex vote , rating):'))
     return lesPremiersPrGenre(base,genre,tri,x)
-    # lesRatings=[]
-    # for i in range(len(lesgenre)):
-    #     for j in range(len(gen)):
-    #         if lesgenre[i] == gen["id"][j]:
-    #             match=gen["rating"][j]
-    #             lesRatings.append(match)
-    # print(lesRatings)
-
-# print(lesPremiers(df,"rating",5))
-# print(lesDerniers(df,"rating",10))
-
-# print(gen.iloc[0])
-# print(geneChercher('Documentary'))
-
-# print("rating")
-# print(df["rating"])
-# print("genre")
-# print(md["genre"])
-
-def get_Gen():
-    df = gen 
-    return jsonify(df.to_dict(orient='records'))
-
-# testVar=lesPremiersPrGenre(gen,'Horror','rating',5)
-# print(testVar)
-# testVar=testVar.to_json(orient='records')
-
-# data = {"testVar": testVar}
-# json_data = json.dumps(data)
-#passer la var en json
-# testVar=testVar.to_json()
-# print(json.dumps({"res": testVar}))
-
-########print(lesPremiersPrGenre(gen,'Horror','rating',5))
-
-#(recommandationBasique(gen))
-
-#print x = int(input('Choisir un nombre de film :'))
-# genre = str(input('Choisir un genre de film :'))
-# print(lesPremiersPrGenre(genre,x))
 
+#extraire seulement une partie d'une colonne
 def extract_names(json_string,colonneVoulu):
     if pd.isna(json_string):
         return []
     try:
-        # Tenter de charger la chaîne JSON en un objet Python
         data = json.loads(json_string.replace("'",'"'))
     except json.JSONDecodeError:
-        # En cas d'erreur, retourner une liste vide
         return []
-    # Si la valeur est une liste de dictionnaires, extraire les valeurs pour la colonne spécifiée
     if isinstance(data, list):
         return [d.get(colonneVoulu, "") for d in data]
-    # Si la valeur est un dictionnaire, extraire la valeur pour la colonne spécifiée
     if isinstance(data, dict):
         return [data.get(colonneVoulu, "")]
-    # Si la valeur n'est ni une liste ni un dictionnaire, retourner une liste vide
     return []
 
+#extraire seulement une partie d'une colonne
 def extractForColumn(base,colonne,colonneVoulu):
     base[colonne] = base[colonne].fillna('')
     base[colonne] = base[colonne].apply(lambda x: extract_names(x,colonneVoulu))
 
+#écrire une nouvelle ligne dans un csv
 def writeInCsv(userId , movieId , rating , timestamp):
     ratings_small= pd .read_csv(location+"ratings_small.csv")
     newLine=len(ratings_small)+1
@@ -166,24 +103,24 @@ def writeInCsv(userId , movieId , rating , timestamp):
     ratings_small = pd.concat([ratings_small,ajouter], ignore_index=True)
     ratings_small.to_csv("../archive/the-movies-dataset/ratings_small.csv", index=False)
 
-def joinFiles(listeID, movie_metadata_df):
-    print(listeID)
-    listeID[1] = listeID[1].astype(str)
-    movie_metadata_df['id'] = movie_metadata_df['id'].astype(str)
+# def joinFiles(listeID, movie_metadata_df):
+#     print(listeID)
+#     listeID[1] = listeID[1].astype(str)
+#     movie_metadata_df['id'] = movie_metadata_df['id'].astype(str)
 
-    merged_df = pd.merge(left=listeID, right=movie_metadata_df, left_on='tmdbId', right_on='id')
+#     merged_df = pd.merge(left=listeID, right=movie_metadata_df, left_on='tmdbId', right_on='id')
 
-    merged_df['title'] = merged_df['title'].fillna('').apply(lambda x: x.encode('unicode_escape').decode('utf-8')).str.replace("'",'"')
-    merged_df['overview'] = merged_df['overview'].fillna('').apply(lambda x: x.encode('unicode_escape').decode('utf-8')).str.replace("'",'"')
-    merged_df['vote_average'] = merged_df['vote_average'].astype(str).str.replace("'",'"')
+#     merged_df['title'] = merged_df['title'].fillna('').apply(lambda x: x.encode('unicode_escape').decode('utf-8')).str.replace("'",'"')
+#     merged_df['overview'] = merged_df['overview'].fillna('').apply(lambda x: x.encode('unicode_escape').decode('utf-8')).str.replace("'",'"')
+#     merged_df['vote_average'] = merged_df['vote_average'].astype(str).str.replace("'",'"')
 
-    data = merged_df.to_dict(orient='records')
+#     data = merged_df.to_dict(orient='records')
 
-    return data
+#     return data
 
+#récup seuleme,t les lignes de la DF voulu (ici par rapport a une liste de film)
 def filtreTitre(listeTitre,df):
     df2 = df[['title', 'overview', 'vote_average']].copy()
-    #cette ligne ne semble pas marcher
     df2['vote_average'] = df2['vote_average'].fillna(-1.0)
 
     df2['title'] = df2['title'].fillna('').apply(lambda x: x.encode('unicode_escape').decode('utf-8')).str.replace("'",'"')
@@ -195,12 +132,14 @@ def filtreTitre(listeTitre,df):
     data = df_filtree.to_dict(orient='records')
     return data
 
+#renvoi le maximun id dans movies metadata
 def maxId():
     df=pd.read_csv(CheminUnFichier("movies_metadata.csv"),low_memory=False)
     liste = dfToList(df["id"])
     max_element = max(int(i) for i in liste if i.isdigit())
     return max_element
 
+#ajouter une nouvelle ligne dans movies metadata
 def newLineMovies(title,desc,listegenre):
     genre=transforme_format_df(liste_ID_genre(listegenre))
     maxa=maxId()+1
@@ -224,24 +163,22 @@ movies_metadata['id'] = movies_metadata['id'].apply(int)
 
 if __name__=='__main__':
     functionName = sys.argv[1]
-    if functionName == 'get_Gen': 
-        get_Gen()
-    elif functionName == 'top':
-        liste=les_films_par_genre(movies_metadata,sys.argv[2],int(sys.argv[3]))
-        for i in range(len(liste)):
-            print(liste[i])
-    elif functionName == 'lesPremiersPrGenre':
-        liste=lesPremiersPrGenre(sys.argv[2],sys.argv[3],sys.argv[4],sys.argv[5])
+    if functionName == 'top':
+        liste=filmsParGenre(movies_metadata,sys.argv[2],int(sys.argv[3]))
         for i in range(len(liste)):
             print(liste[i])
-    elif functionName == 'dfToList':
-        print(dfToList(gen['genre']))
-    elif functionName == 'dfToList2':
+    # elif functionName == 'lesPremiersPrGenre':
+    #     liste=lesPremiersPrGenre(sys.argv[2],sys.argv[3],sys.argv[4],sys.argv[5])
+    #     for i in range(len(liste)):
+    #         print(liste[i])
+    # elif functionName == 'dfToList':
+    #     print(dfToList(gen['genre']))
+    elif functionName == 'listeUtilisateur':
         liste = dfToList(ratings_small['userId'])
         liste = list(map(int, liste))
         liste.sort()
         print(liste)
-    elif functionName == 'extract':
+    elif functionName == 'extractGenre':
         extractForColumn(movies_metadata,'genres','name')
         print(dfToList(movies_metadata['genres']))
     elif functionName == 'idFromUserRating' :
@@ -250,7 +187,7 @@ if __name__=='__main__':
         ok=infoFromId(listeid,movies_metadata,links_small)['title']
         print(dfToList(ok))
     elif functionName == 'liste':
-        dff = mov[['title', 'overview', 'vote_average']].copy()
+        dff = movies_metadata[['title', 'overview', 'vote_average']].copy()
         dff['title'] = dff['title'].fillna('').apply(lambda x: x.encode('unicode_escape').decode('utf-8')).str.replace("'",'"')
         dff['overview'] = dff['overview'].fillna('').apply(lambda x: x.encode('unicode_escape').decode('utf-8')).str.replace("'",'"')
         dff['vote_average'] = dff['vote_average'].astype(str).str.replace("'",'"')
@@ -268,9 +205,6 @@ if __name__=='__main__':
         dff['overview'] = dff['overview'].fillna('').apply(lambda x: x.encode('unicode_escape').decode('utf-8')).str.replace("'",'"')
         dff['vote_average'] = dff['vote_average'].astype(str).str.replace("'",'"')
         dff['rating'] = dff['rating'].astype(str).str.replace("'",'"')
-        # dff['imdbId'] = dff['imdbId'].astype(str).str.replace("'",'"')
-        # dff['timestamp'] = dff['timestamp'].astype(str).str.replace("'",'"')
-
 
         data = dff.to_dict(orient='records')
         print(json.dumps(data))
@@ -281,13 +215,11 @@ if __name__=='__main__':
         StatUser(int(sys.argv[2]),ComprendreBudget,ratings_small,10,movies_metadata,links_small)
     elif functionName=='recommandation':
         type = sys.argv[2]
-
         if type == 'KNN':
             liste_meilleur = meilleur_Film(int(sys.argv[3]),entrainne_KNNBasic(ratings_small),movies_metadata,ratings_small,links_small)
             list = []
             for i in range(10):
                 list.append(titre_Par_ID_Film(liste_meilleur[0][i][1],join_Two_File(links_small,movies_metadata)))
-            # print(list)
             data = filtreTitre(list,movies_metadata)
             print(json.dumps(data))
         elif type == 'SVD':
@@ -305,37 +237,10 @@ if __name__=='__main__':
             data = filtreTitre(list,movies_metadata)
             print(json.dumps(data))
     elif functionName=='nouveauFilm':
-        mainTrouverGenre()
+        #mainTrouverGenre()
         liste=genreTrouver(sys.argv[3])
         newLineMovies(sys.argv[2],sys.argv[3],liste)
-        #titre , description
-
-
-
-
-    # elif functionName=='tinyDB':
-    #     #pour tinydb
-    #     movies_metadata['title'] = movies_metadata['title'].fillna('').apply(lambda x: x.encode('unicode_escape').decode('utf-8')).str.replace("'",'"')
-    #     movies_metadata['overview'] = movies_metadata['overview'].fillna('').apply(lambda x: x.encode('unicode_escape').decode('utf-8')).str.replace("'",'"')
-    #     movies_metadata['vote_average'] = movies_metadata['vote_average'].astype(str).str.replace("'",'"')
-
-    #     data = movies_metadata.to_dict(orient='records')
-    #     db = TinyDB('db.json')
-    #     table = db.table('my_table')
-    #     table.truncate()
-    #     table.insert_multiple(data)
-    #     # movies_metadata['belongs_to_collection'] = movies_metadata['belongs_to_collection'].apply(lambda x: json.loads(x) if isinstance(x, str) else x)
-        
-    #     # query = (Query().title.search('Toy'))    
-    #     # query = (Query().title == "Toy Story")
-
-    #     # result = table.search(query)
-    #     # # print(f"Found {len(result)} records.")
-
-    #     # for r in result:
-    #     #   print(r['title'])
-    #     # # print(result['title'])
-
-    #     res = movies_metadata['title'] == "Toy Story"
-    #     print(movies_metadata[res])
+        print(liste)
+    elif functionName=='statUser':
+        print(RecapGenre(int(sys.argv[2]),movies_metadata, links_small, ratings_small))
 
diff --git a/py/dataFrame.py b/py/dataFrame.py
index 8cb06c99077be81e1819ed4ac9da786ba6675914..0265d087314be851b2da9d0adeffb12270a6a01e 100644
--- a/py/dataFrame.py
+++ b/py/dataFrame.py
@@ -1,4 +1,5 @@
 import pandas as pd
+import numpy as np
 
 #supprime 3 lignes qui sont nuls
 def clean(movies_metadata):
@@ -19,6 +20,12 @@ def infoFromId(Movies, movies_metadata, links_small):
     tmdbId = fltr['tmdbId']
     return movies_metadata[movies_metadata['id'].isin(tmdbId)]
 
+def RatingsFromMovies(Movies, ratings_small, links_small):
+    idRating = []
+    fltr = links_small[links_small['tmdbId'].isin(Movies)]
+    idRating = fltr['movieId']
+    return ratings_small[ratings_small['movieId'].isin(idRating)]
+
 #Retourne de façon unique tout les genres possibles
 def UniqueGenres(movies_metadata):
     vrakGenre = movies_metadata['genres'][:]
@@ -48,9 +55,15 @@ def genresVal(val) :
 
 #Fait des groupes par genres
 def GroupeParGenres(movies_metadata):
-    UniqGenres = UniqueGenres(movies_metadata)
-    GrpMovieParGenres = pd.DataFrame(columns=UniqGenres)
-    for i in UniqGenres:
-        fltr = movies_metadata[movies_metadata['genres'].str.contains(i)]
-        GrpMovieParGenres[i] = fltr['id']
+    GrpMovieParGenres = movies_metadata[['genres', 'id']].explode('genres')
+    GrpMovieParGenres['genres'] = GrpMovieParGenres['genres'].apply(genresVal)
+    uG = UniqueGenres(movies_metadata)
+    for g in uG:
+        GrpMovieParGenres[g] = GrpMovieParGenres['genres'].apply(lambda x: 1 if g in x else np.nan)
+    GrpMovieParGenres = GrpMovieParGenres.drop('genres', axis=1)
     return GrpMovieParGenres
+
+def VartoName(dico, Variable):
+    for nom in dico:
+        if dico[nom] is Variable:
+            return nom
diff --git a/py/filtrage_actif.py b/py/filtrage_actif.py
index e3646c6b97c15e8b531ee3412314994ee2a94cff..a2f4e3ec6ddb3b4c004474f2e56e376a1d7b583a 100644
--- a/py/filtrage_actif.py
+++ b/py/filtrage_actif.py
@@ -180,12 +180,15 @@ def meilleur_Film2(num_Utili, algo, data=None, ratings_df=None, links_df=None, s
     retour [1] = liste_non_precis
     return retour        
 
-def MatrixReco(movies_metadata, links_small, ratings_small):
+def MatrixReco(movies_metadata, links_small, ratings_small, algo_='SVD'):
     '''
-        cree une matrice utilisateurs/flim avec leur prédisction,
+        cree une matrice utilisateurs/flim avec leur prédiction,
         utilise l'algo 
     '''
-    ALGO = entrainne_KNNBasic(ratings_small)
+    if algo_ == 'KNN' :
+        ALGO = entrainne_KNNBasic(ratings_small)
+    elif algo_ == 'SVD' : 
+        ALGO = entrainne_SVD(ratings_small)
     userList = ratings_small['userId'].drop_duplicates()
     filmList = links_small['movieId'].drop_duplicates()
     matrix = pd.DataFrame(index=userList, columns=filmList)
diff --git a/py/recherche_dans_bd.py b/py/recherche_dans_bd.py
index 89d17764e796e7f8624ab2e220d52d48fcb38ff6..8509ab3425ee7dc0f9d229e6b6dd9dd696c33d29 100644
--- a/py/recherche_dans_bd.py
+++ b/py/recherche_dans_bd.py
@@ -109,7 +109,7 @@ def liste_ID_genre(liste_genre, Df_movie_metadata=None):
 def transforme_format_df(genres):
     resultat_dict = []
     for genre in genres:
-        resultat_dict.append({"id": genre[1], "name": genre[0]})
+        resultat_dict.append({"id": genre[0], "name": genre[1]})
     return resultat_dict
 
 # print(transforme_format_df(liste_ID_genre(["drama", "comedy", "action"])))
diff --git a/static/connexion.html b/static/connexion.html
deleted file mode 100644
index 743d8df2f106128e438c0cdaddec017b97611642..0000000000000000000000000000000000000000
--- a/static/connexion.html
+++ /dev/null
@@ -1,64 +0,0 @@
-<body>
-    <header>
-      <div id="buttonCoDeco"></div>
-      <div id="allTheA">
-        <a href="/top">Top</a>
-        <a href="/liste">Liste</a>
-        <a href="/formFilm">Ajouter Film</a>
-      </div>
-    </header>
-
-    <div class="column">
-        <form action="/postConnexion" method="POST">
-          <div class="Element">
-            <label class="label"  for="utilisateur">Quel utilisateur :</label>
-            <!-- <input type="text" id="legenre" name="legenre"><br> -->
-            <select class="Saisie" name="utilisateur" id="utilisateur">  
-              <!-- <option value="r">r</option> -->
-            </select><br>
-          </div>
-          <button class="Envoyer" type="submit">Envoyer</button>
-        </form>
-    </div>
-    <script>
-      var user=null;
-      // Récupérer les données JSON du serveur
-      fetch('/user')
-      .then(response => response.json())
-      .then(json => {
-          user = json;
-          console.log("Valeur de user: " + user);
-    
-          if (user == null) {
-          var button = document.createElement("button");
-          var abutton = document.createElement("a");
-          button.textContent="se connecter";
-          abutton.href="/connexion";
-          button.id="connexion";
-          abutton.appendChild(button);
-          document.getElementById("buttonCoDeco").appendChild(abutton);
-          }
-          else{
-            var button = document.createElement("button");
-            var abutton = document.createElement("a");
-            button.textContent="se déconnecter";
-            abutton.href="/deconnexion";
-            button.id="déconnexion";
-            abutton.appendChild(button);
-            document.getElementById("buttonCoDeco").appendChild(abutton);
-
-            var a = document.createElement("a");
-            a.textContent="Stats";
-            a.href="/stats";
-            document.getElementById("allTheA").appendChild(a);
-
-            a = document.createElement("a");
-            a.textContent="Recommandation";
-            a.href="/formRecommandation";
-            document.getElementById("allTheA").appendChild(a);
-          }
-      });
-    </script>
-    <!-- <button id="more">Afficher plus</button> -->
-  </body>
-</html>
diff --git a/static/index.html b/static/index.html
index 7e7f51aa5eedfb543b2db22cbf8b491029482371..9d69d1ff3737fb823a6bda1d61f70fe8ee22a023 100644
--- a/static/index.html
+++ b/static/index.html
@@ -1,64 +1,79 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <meta charset="UTF-8">
-    <title>VAPEA</title>
-  </head>
-  <body>
+<!doctype html>
+<html lang="fr">
+<head>
+  <meta charset="utf-8">
+  <title>QssQss</title>
+</head>
+<body>
     <header>
-      <div id="buttonCoDeco"></div>
-      <div id="allTheA">
-        <a href="/top">Top</a>
-        <a href="/liste">Liste</a>
-        <a href="/formFilm">Ajouter Film</a>
-    </div>
+        <div id="buttonCoDeco" class="buttonCoDeco"></div>
+        <div id="allTheA" class="allTheA">
+            <a href="/top">Top</a>
+            <a href="/liste">Liste</a>
+            <a href="/formFilm">Ajouter Film</a>
+        </div>
     </header>
 
-    <h2>Quelle genre de film ? </h2>
-    <div class="column">
-      <form action="/getInfo" method="POST">
-        <!-- <div class="Element">
-          <label class="label"  for="base">Base :</label>
-          <input class="Saisie" type="text" id="base" name="base"><br>
-        </div> -->
-        <div class="Element">
-          <label class="label"  for="legenre">Le Genre voulu :</label>
-          <select class="Saisie" name="legenre" id="legenre">  
-          </select><br>
-        </div>
-        <!-- <div class="Element">
-          <label class="label" for="colonneTri">La colonne a trier :</label>
-          <select class="Saisie" name="colonneTri" id="colonneTri">  
-            <option value="rating">Note</option>
-            <option value="vote">Nbr de Vote</option>
-          </select><br>
-        </div> -->
-        <div class="Element">
-          <label class="label" for="x">Combien :</label>
-          <input class="Saisie" type="text" id="x" name="x"><br>
-        </div>
-        <button class="Envoyer" type="submit">Envoyer</button>
-      </form>
+    <div class="catchphrase">
+        <p>Un Site</p>
+        <p>Une Recommandation</p>
+        <p>Un Contenu</p>
+    </div>
+
+    <div id="divImg" class ="divImg">
+        <p>Visualisation de la donnée par la méthode <a target="_blank" href="https://fr.wikipedia.org/wiki/Analyse_en_composantes_principales">ACP</a> les points représente les utilisateurs </p>
+        <p>ici les utilisateurs sont regroupé par la méthode de clustering <a target="_blank" href="https://fr.wikipedia.org/wiki/K-moyennes">Kmeans</a> sur les prédictions <a target ="_blank" href="https://fr.wikipedia.org/wiki/M%C3%A9thode_des_k_plus_proches_voisins">KNN</a></p>
+        <img src="./img/ACPKMeans_prediction_Knn.png">
+        <p>ici les utilisateurs sont regroupé par la méthode de clustering <a target="_blank" href="https://fr.wikipedia.org/wiki/D%C3%A9composition_en_valeurs_singuli%C3%A8res">Kmeans</a> sur les prédictions <a target ="_blank" href="https://fr.wikipedia.org/wiki/M%C3%A9thode_des_k_plus_proches_voisins">SVD</a> (souvent plus pertinente)</p>
+        <img src="./img/ACPKMeans_prediction_Svd.png">
+        <p>On étudie les méthodes de <a target="_blank" href="https://fr.wikipedia.org/wiki/Regroupement_hi%C3%A9rarchique#La_classification_ascendante_hi.C3.A9rarchique_.28CAH.29">classification ascendante hiérarchique</a> dit CAH</p>
+        <p>ici trois méthode:<br>
+            <a target="_blank" href="https://en.wikipedia.org/wiki/Single-linkage_clustering">Single</a><br>
+            <a target="_blank" href="https://en.wikipedia.org/wiki/WPGMA">Average</a><br>
+            <a target="_blank" href="https://fr.wikipedia.org/wiki/M%C3%A9thode_de_Ward">Ward</a><br>
+        </p>
+        <p> récap avec des <a target="_blank" href="https://fr.wikipedia.org/wiki/Dendrogramme">dendrogrammes</a> pour 3 groupes</p>
+        <img src="./img/CAHcomparaison.png">
+        <p> il est important de déterminer quelles est le nombre de cluster optimal pour cela 2 méthode:<br>
+            <a target="_blank" href="https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html">l' indicateur silhouette:</a>
+            <br>la comparaison d'efficacité des méthodes de clustering par nombres de clusters<br>
+            les valeurs du tableau sont un <a target="_blank" href="https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html">indicateur silhouette</a>
+        </p>
+        <img src="./img/determinerQ.png">
+        <p>
+            <a target="_blank" href="https://en.wikipedia.org/wiki/Elbow_method_(clustering)">méthode coudé:</a>
+        </p>
+        <img src="./img/deterCoude.png">
+        <p>méthode hybride de clustering pour 6 groupes entre la CAH et Kmeans <br>
+            c'est cette méthode qui sera utiliser par QssQss </p>
+        <img src="./img/hybride_average.png">
     </div>
+
+   <!-- <div class="PersoOrdi">
+        <img class="imgOrdi" src="https://img.passeportsante.net/1200x675/2019-11-05/i92345-.webp"/>
+        <p>Vous etes constamment entrain de chercher un nouveau film a regarder ?
+        Ne perder plus votre temps
+        Vous avez fait le bon choix en utilisant notre site web</p>
+    </div>-->
     <script>
-      var user=null;
-      // Récupérer les données JSON du serveur
-      fetch('/user')
-      .then(response => response.json())
-      .then(json => {
-          user = json;
-          console.log("Valeur de user: " + user);
-    
-          if (user == null) {
-          var button = document.createElement("button");
-          var abutton = document.createElement("a");
-          button.textContent="se connecter";
-          abutton.href="/connexion";
-          button.id="connexion";
-          abutton.appendChild(button);
-          document.getElementById("buttonCoDeco").appendChild(abutton);
-          }
-          else{
+        var user=null;
+        // Récupérer les données JSON du serveur
+        fetch('/user')
+        .then(response => response.json())
+        .then(json => {
+            user = json;
+            console.log("Valeur de user: " + user);
+      
+            if (user == null) {
+            var button = document.createElement("button");
+            var abutton = document.createElement("a");
+            button.textContent="se connecter";
+            abutton.href="/connexion";
+            button.id="connexion";
+            abutton.appendChild(button);
+            document.getElementById("buttonCoDeco").appendChild(abutton);
+            }
+            else{
             var button = document.createElement("button");
             var abutton = document.createElement("a");
             button.textContent="se déconnecter";
@@ -76,8 +91,7 @@
             a.textContent="Recommandation";
             a.href="/formRecommandation";
             document.getElementById("allTheA").appendChild(a);
-          }
-      });
-    </script>
-  </body>
-</html>
+            }
+        });
+      </script>
+</body>
\ No newline at end of file
diff --git a/static/index.js b/static/index.js
index ee61e25651d3130efdc0b696dc0877fddcdc109e..4bbf0abfc6016efecb10c9d4b0fd81ca03f76c5f 100644
--- a/static/index.js
+++ b/static/index.js
@@ -10,39 +10,38 @@ const { Console } = require('console');
 const path = require('path');
 
 var user = null ;
+let dataStatsUser = "";
 
 app.listen(8080, () => console.log('Application listening on port 8080!'))
 
 app.use(bodyParser.urlencoded({ extended: true }));
 
 //permet de récupérer l'image et l'envoyer a express
-app.get('/img/ACP.png',(req , res ) =>{
-  res.sendFile(path.join(__dirname,  '../img/ACP.png'))
+app.get('/img/ACPKMeans_prediction_Knn.png',(req , res ) =>{
+  res.sendFile(path.join(__dirname,  '../img/ACPKMeans_prediction_Knn.png'))
 });
-app.get('/img/ACPaverage.png',(req , res ) =>{
-  res.sendFile(path.join(__dirname,  '../img/ACPaverage.png'))
-});
-app.get('/img/ACPsingle.png',(req , res ) =>{
-  res.sendFile(path.join(__dirname,  '../img/ACPsingle.png'))
-});
-app.get('/img/ACPKMeans.png',(req , res ) =>{
-  res.sendFile(path.join(__dirname,  '../img/ACPKMeans.png'))
-});
-app.get('/img/ACPward.png',(req , res ) =>{
-  res.sendFile(path.join(__dirname,  '../img/ACPward.png'))
+app.get('/img/ACPKMeans_prediction_Svd.png',(req , res ) =>{
+  res.sendFile(path.join(__dirname,  '../img/ACPKMeans_prediction_Svd.png'))
 });
 app.get('/img/CAHcomparaison.png',(req , res ) =>{
   res.sendFile(path.join(__dirname,  '../img/CAHcomparaison.png'))
 });
-app.get('/img/ComprendreBudget.png',(req , res ) =>{
-  res.sendFile(path.join(__dirname,  '../img/ComprendreBudget.png'))
-});
 app.get('/img/determinerQ.png',(req , res ) =>{
   res.sendFile(path.join(__dirname,  '../img/determinerQ.png'))
 });
+app.get('/img/deterCoude.png',(req , res ) =>{
+  res.sendFile(path.join(__dirname,  '../img/deterCoude.png'))
+});
 app.get('/img/hybride_average.png',(req , res ) =>{
   res.sendFile(path.join(__dirname,  '../img/hybride_average.png'))
 });
+app.get('/img/CompareSelectGenre.png',(req , res ) =>{
+  res.sendFile(path.join(__dirname,  '../img/CompareSelectGenre.png'))
+});
+app.get('/img/CompareEvalGenre.png',(req , res ) =>{
+  res.sendFile(path.join(__dirname,  '../img/CompareEvalGenre.png'))
+});
+
 
 //permet de récupérer le script js et l'envoyer a express
 app.get('/script.js', (req, res) => {
@@ -52,25 +51,62 @@ app.get('/script.js', (req, res) => {
 
 //route de base
 app.get('/', (req, res) => {
-    const html = fs.readFileSync("./newIndex.html", "utf8");
+    const html = fs.readFileSync("./index.html", "utf8");
     const css = fs.readFileSync('./newIndex.css', 'utf8');
-    const htmlWithCss = `<html><head><style>${css}</style></head><body>${html}</body></html>`;
+    const htmlWithCss = `<html><head><title>QssQss</title><style>${css}</style></head><body>${html}</body></html>`;
     res.send(htmlWithCss);
 })
 
 //route vers le formulaire pour le top
 app.get('/top', (req, res) => {
-  const html = fs.readFileSync("./index.html", "utf8");
+  const html = fs.readFileSync("./temp.html", "utf8");
   const css = fs.readFileSync('./style.css', 'utf8');
-  const htmlWithCss = `<html><head><style>${css}</style></head><body>${html}</body></html>`;
+  const htmlWithCss = `<!doctype html><html><head><title>QssQss</title><style>${css}</style></head><body>${html}</body></html>`;
 
   const dom = new JSDOM(htmlWithCss);
+  const body = dom.window.document.getElementById("container");
+
+  const form=`
+    <h2>Quelle genre de film ? </h2>
+    <div class="column">
+      <form action="/getInfo" method="POST">
+        <!-- <div class="Element">
+          <label class="label"  for="base">Base :</label>
+          <input class="Saisie" type="text" id="base" name="base"><br>
+        </div> -->
+        <div class="Element">
+          <label class="label"  for="legenre">Le Genre voulu :</label>
+          <select class="Saisie" name="legenre" id="legenre">  
+          </select><br>
+        </div>
+        <!-- <div class="Element">
+          <label class="label" for="colonneTri">La colonne a trier :</label>
+          <select class="Saisie" name="colonneTri" id="colonneTri">  
+            <option value="rating">Note</option>
+            <option value="vote">Nbr de Vote</option>
+          </select><br>
+        </div> -->
+        <div class="Element">
+          <label class="label" for="x">Combien :</label>
+          <input class="Saisie" type="text" id="x" name="x"><br>
+        </div>
+        <button class="Envoyer" type="submit">Envoyer</button>
+      </form>
+    </div>
+  `;
     
+  body.innerHTML=form;
   const select = dom.window.document.getElementById("legenre");    
 
   //fonction python pour récupérer tout les genres
-  const pyProg = spawn('python', ['../py/analyseArthur.py','extract']);
-  pyProg.stdout.on('data', function(data) {
+  const pyProg = spawn('python', ['../py/analyseArthur.py','extractGenre']);
+
+  let data="";
+  pyProg.stdout.on('data', function(chunk) {
+    data+=chunk;
+  });
+
+  pyProg.stdout.on('end', function() {
 
     let options=data.toString();
     //on récup une liste donc on retire tout les éléments qu'on ne veut pas afficher [ ; ] ; , 
@@ -80,64 +116,74 @@ app.get('/top', (req, res) => {
       option.text = options[i];
       option.value = options[i];
       select.appendChild(option);    
-      }
+    }
+    if(user!=null){
+
+      const div = dom.window.document.createElement("div");
+      div.id="divImg";
+      div.className="divImg";
+
+      const img = dom.window.document.createElement("img");
+      img.src="./img/hybride_average.png";
+      const img2 = dom.window.document.createElement("img");
+      img2.src="./img/CompareSelectGenre.png";
+      const img3 = dom.window.document.createElement("img");
+      img3.src="./img/CompareEvalGenre.png";
+
+
+      const p = dom.window.document.createElement("p");
+      p.innerHTML=dataStatsUser;
+      p.className="white-space";
+      body.appendChild(p);
+
+      div.appendChild(img);
+      div.appendChild(img2);
+      div.appendChild(img3);
+
+      body.appendChild(div);
+
       const outputHtml = dom.serialize();
       res.send(outputHtml);
+    }else{
+      const outputHtml = dom.serialize();
+      res.send(outputHtml);
+      }
     });
 })
 
 //route qui récupére les infos du formulaire top
 app.post('/getInfo', (req, res) => {
-  const base = req.body.base;
+  const html = fs.readFileSync("./temp.html", "utf8");
+  const css = fs.readFileSync('./style.css', 'utf8');
+  const htmlWithCss = `<!doctype html><html><head><title>QssQss</title><style>${css}</style></head><body>${html}</body></html>`;
+
+  const dom = new JSDOM(htmlWithCss);
+  const bod = dom.window.document.getElementById("container");
+
+  //const base = req.body.base;
   const legenre = req.body.legenre;
-  const colonneTri = req.body.colonneTri;
+  //const colonneTri = req.body.colonneTri;
   const x = req.body.x;
 
   //fonction python pour avoir les x meilleurs films pour un genre
   // const pyProg = spawn('python', ['../py/analyseArthur.py','lesPremiersPrGenre',base,legenre,colonneTri,x]);
   const pyProg = spawn('python', ['../py/analyseArthur.py','top',legenre,x]);
-  let html=`  
-  <html>
-  <head>
-    <title>Bonjour</title>
-    <style>
-    @import url('https://fonts.googleapis.com/css2?family=Lato&display=swap');
-      body{
-        background-color: #141414;
-        padding: 0;
-        margin-top:  10%;
-        color: #fff;
-        font-family: 'Lato', sans-serif;
-        text-align: center;
-    }
-      button{
-        background-color: #1a1a1a;
-        color: white;
-        border-radius: 15px;
-        text-decoration: none;
-        padding: 10px;
-    }
-      .white-space{
-      white-space : pre-wrap;
-    }
-    </style>
 
-  </head>
-
-    <body>
+  let html2=`  
       <h1>Voici ce qu'on te recommande</h1>
   `;
     
   pyProg.stdout.on('data', function(data) {
-    html+='<p class="white-space">';
+    html2+='<p class="white-space">';
     myString=data.toString();
-    html += myString;
-    html+='</p>';
-    html+='<a href="/"><button>Retour accueil</button></a>';
-    html+='</body>';
-    res.send(html);
+    html2 += myString;
+    html2+='</p>';
+    html2+='<a href="/"><button class="Envoyer">Retour accueil</button></a>';
+    html2+='</body>';
+    bod.innerHTML=html2;
+    const outputHtml = dom.serialize();
+    res.send(outputHtml);
   });
-      
 })
 
 //route inutile
@@ -185,11 +231,20 @@ app.get('/getValeur', (req, res) => {
 
 //route vers la liste de film
 app.get('/liste', (req, res) => {
-  const html = fs.readFileSync("./liste.html", "utf8");
+  const html = fs.readFileSync("./temp.html", "utf8");
   const css = fs.readFileSync('./style.css', 'utf8');
-  const htmlWithCss = `<html><head><style>${css}</style></head><body>${html}</body></html>`;
+  const htmlWithCss = `<html><head><title>QssQss</title><style>${css}</style></head><body>${html}<script src="script.js"></script></body></html>`;
   const dom = new JSDOM(htmlWithCss);
-  
+
+  const body = dom.window.document.getElementById("container");
+  const form= `
+    <label class="label" for="chercher">Chercher :</label>
+    <input type="text" id="chercher" class="Forminput">
+    <table id="liste">
+    </table>
+    <button id="showMoreButton" class="Envoyer">Afficher plus</button>
+  `;
+  body.innerHTML=form;
   //fonction python qui récupére tout les films de la BD
   const pyProg = spawn('python', ['../py/analyseArthur.py', 'liste']);
 
@@ -220,8 +275,19 @@ app.get('/liste', (req, res) => {
     first.innerHTML =`<tr>
     <th>Nom</th>
     <th>Description</th>
-    <th>Vote moyenne</th>
+    <th>Vote moyenne (sur 10)</th>
     </tr>`;
+
+    if(user != null){
+      first.innerHTML =`<tr>
+      <th>Nom</th>
+      <th>Description</th>
+      <th>Vote moyenne (sur 10)</th>
+      <th>Aimer/Votre note (sur 5)</th>
+      </tr>
+      `;
+    }
+
     tableBody.appendChild(first);
 
     pageData.forEach(row => {
@@ -260,14 +326,31 @@ app.get('/liste', (req, res) => {
 
 //route vers le système de connexion
 app.get('/connexion', (req, res) => {
-  const html = fs.readFileSync("./connexion.html", "utf8");
+  const html = fs.readFileSync("./temp.html", "utf8");
   const css = fs.readFileSync('./style.css', 'utf8');
-  const htmlWithCss = `<html><head><style>${css}</style></head><body>${html}</body></html>`;
+  const htmlWithCss = `<html><head><title>QssQss</title><style>${css}</style></head><body>${html}</body></html>`;
   const dom = new JSDOM(htmlWithCss);
 
+  const body = dom.window.document.getElementById("container");
+  const form= `
+    <div class="column">
+      <form action="/postConnexion" method="POST">
+        <div class="Element">
+          <label class="label"  for="utilisateur">Quel utilisateur :</label>
+          <!-- <input type="text" id="legenre" name="legenre"><br> -->
+          <select class="Saisie" name="utilisateur" id="utilisateur">  
+            <!-- <option value="r">r</option> -->
+          </select><br>
+        </div>
+        <button class="Envoyer" type="submit">Envoyer</button>
+      </form>
+    </div>
+  `;
+  body.innerHTML=form;
+
   const select = dom.window.document.getElementById("utilisateur");    
   //fonction qui récupére tout les utilisateurs qui existent
-  const pyProg = spawn('python', ['../py/analyseArthur.py', 'dfToList2']);
+  const pyProg = spawn('python', ['../py/analyseArthur.py', 'listeUtilisateur']);
   pyProg.stdout.on('data', function(data) {
 
     let options=data.toString();
@@ -290,37 +373,20 @@ app.get('/connexion', (req, res) => {
 
 app.get('/deconnexion' , (req ,res)=>{
   user = null;
-  let html = `  
-  <html>
-  <head>
-    <title>Bonjour</title>
-    <style>
-    @import url('https://fonts.googleapis.com/css2?family=Lato&display=swap');
-      body{
-        background-color: #141414;
-        padding: 0;
-        margin-top:  10%;
-        color: #fff;
-        font-family: 'Lato', sans-serif;
-        text-align: center;
-    }
-      button{
-        background-color: #1a1a1a;
-        color: white;
-        border-radius: 15px;
-        text-decoration: none;
-        padding: 10px;
-    }
-    </style>
-
-  </head>
+  dataStatsUser="";
+  const html = fs.readFileSync("./temp.html", "utf8");
+  const css = fs.readFileSync('./style.css', 'utf8');
+  const htmlWithCss = `<html><head><title>QssQss</title><style>${css}</style></head><body>${html}</body></html>`;
+  const dom = new JSDOM(htmlWithCss);
 
-    <body>
-      <h1>Tu es déconnecter</h1>
-      <a href="/"><button>Retour accueil</button></a>
-    </body>
-`;
-  res.send(html);
+  const body = dom.window.document.getElementById("container");
+  const rep= `
+    <h1>Tu es déconnecter</h1>
+    <a href="/"><button class="Envoyer">Retour accueil</button></a>
+  `;
+  body.innerHTML=rep;
+  const outputHtml = dom.serialize();
+  res.send(outputHtml);
 })
 
 //Récupére la valeur du formulaire de /connexion
@@ -328,85 +394,57 @@ app.post('/postConnexion', (req, res) => {
   //la variable globale user est mise a jour
   user = req.body.utilisateur;
 
-  let html=`  
-    <html>
-    <head>
-      <title>Bonjour</title>
-      <style>
-      @import url('https://fonts.googleapis.com/css2?family=Lato&display=swap');
-        body{
-          background-color: #141414;
-          padding: 0;
-          margin-top:  10%;
-          color: #fff;
-          font-family: 'Lato', sans-serif;
-          text-align: center;
-      }
-        button{
-          background-color: #1a1a1a;
-          color: white;
-          border-radius: 15px;
-          text-decoration: none;
-          padding: 10px;
-      }
-      </style>
+  const html = fs.readFileSync("./temp.html", "utf8");
+  const css = fs.readFileSync('./style.css', 'utf8');
+  const htmlWithCss = `<html><head><title>QssQss</title><style>${css}</style></head><body>${html}</body></html>`;
+  const dom = new JSDOM(htmlWithCss);
 
-    </head>
+  const body = dom.window.document.getElementById("container");
 
-      <body>
-        <h1>Tu es utilisateur : ${user} </h1>
-        <a href="/"><button>Retour accueil</button></a>
-      </body>
+  const pyProg = spawn('python', ['../py/analyseArthur.py','statUser',user]);
+
+  pyProg.stdout.on('data', function(chunk) {
+    dataStatsUser+=chunk;
+  });
+
+  let rep=`  
+    <h1>Tu es utilisateur : ${user} </h1>
+    <a href="/"><button class="Envoyer">Retour accueil</button></a>
   `;
-  res.send(html);
-      
+  body.innerHTML=rep;
+  const outputHtml = dom.serialize();
+  res.send(outputHtml);
 })
 
 //route vers la page de notation
 app.get('/rating', (req, res) => {
   const title = req.query.title;
 
-  let html=`
-    <html>
-    <head>
-      <title>Bonjour</title>
-      <style>
-      @import url('https://fonts.googleapis.com/css2?family=Lato&display=swap');
-        body{
-          background-color: #141414;
-          padding: 0;
-          margin-top: 10% ;
-          color: #fff;
-          font-family: 'Lato', sans-serif;
-          text-align: center;
-      }
-        button{
-          background-color: #1a1a1a;
-          color: white;
-          border-radius: 15px;
-          text-decoration: none;
-          padding: 10px;
-      }
-        input{
-          width: 25%;
-          background-color: #1a1a1a;
-          color: white;
-          border: none;
-          outline: none;
-          padding: .25em .5em .5em 0;
-      }
-      </style>
+  const html = fs.readFileSync("./temp.html", "utf8");
+  const css = fs.readFileSync('./style.css', 'utf8');
+  const htmlWithCss = `<html><head><title>QssQss</title><style>${css}</style></head><body>${html}<script>
+  function validateForm() {
+    const rating = document.getElementById("rating").value;
+    if (rating < 0 || rating > 5) {
+      alert("La note doit être comprise entre 0 et 5 !");
+      return false;
+    }
+    return true;
+  }
+  </script></body></html>`;
+  const dom = new JSDOM(htmlWithCss);
 
-    </head>
-    <body>
-      <form method="POST" action="/save-rating"> 
-        <input type="text" id="rating" name="rating"><br>
-        <input type="hidden" id="title" name="title" value="${title}"><br>          
-        <button type="submit">Envoyer</button>
-      </form>
-    </body>
+  const body = dom.window.document.getElementById("container");
+
+  let rep=`
+    <form method="POST" action="/save-rating" onsubmit="return validateForm()"> 
+      <label class="label" for="rating">Votre note (sur 5) :</label>
+      <input type="text" id="rating" name="rating" class="Forminput"><br>
+      <input type="hidden" id="title" name="title" value="${title}"><br>          
+      <button type="submit" class="Envoyer">Envoyer</button>
+    </form>
     `;
-  const dom = new JSDOM(html);
+  body.innerHTML=rep;
 
   const outputHtml = dom.serialize();
   res.send(outputHtml);
@@ -414,12 +452,26 @@ app.get('/rating', (req, res) => {
 
 //Récupére la valeur du formulaire de /rating
 app.post('/save-rating', (req, res) => {
-  //on recup la note
-  const rating = req.body.rating;
+  const html = fs.readFileSync("./temp.html", "utf8");
+  const css = fs.readFileSync('./style.css', 'utf8');
+  const htmlWithCss = `<!doctype html><html><head><title>QssQss</title><style>${css}</style></head>${html}</html>`;
+  const dom = new JSDOM(htmlWithCss);
+
+  const body = dom.window.document.getElementById("container");
+
+  //on recup la note en remplacant les , et ; par .
+  const rating = req.body.rating.replace(/[;,]/g, ".");
   //date de la notation
   const time = Date.now();
   const title = req.body.title;
 
+  const rep=`
+  <a>Votre note pour ${title} a été ajouté</a>
+  </br>
+  <a href="/"><button class="Envoyer">Retour accueil</button></a>
+  `;
+  body.innerHTML=rep;
+
   //variable qui correspond a l'id pour le film
   let id = null ;
 
@@ -437,8 +489,8 @@ app.post('/save-rating', (req, res) => {
     //fonction python qui stocke dans le fichier csv la note
     const pyProg2 = spawn('python', ['../py/analyseArthur.py', 'writeInCsv' , user , id , rating , time ]);
     pyProg2.stdout.on('end' , function(){
-      const html ='<a href="/"><button>Retour accueil</button></a>';
-      res.send(html);
+      const outputHtml = dom.serialize();
+      res.send(outputHtml);
     })
   });
   
@@ -446,11 +498,19 @@ app.post('/save-rating', (req, res) => {
 
 //route vers la page avec les statistique /\ seulement accessible si user != null
 app.get('/stats' ,(req ,res ) => {
-  const html = fs.readFileSync("./stats.html", "utf8");
+  const html = fs.readFileSync("./temp.html", "utf8");
   const css = fs.readFileSync('./style.css', 'utf8');
-  const htmlWithCss = `<!doctype html><html><head><style>${css}</style></head>${html}</html>`;
+  const htmlWithCss = `<!doctype html><html><head><title>QssQss</title><style>${css}</style></head>${html}</html>`;
   const dom = new JSDOM(htmlWithCss);
 
+  const body = dom.window.document.getElementById("container");
+
+  let rep=`
+    <div id="divImg" class ="divImg">
+    </div>
+    `;
+  body.innerHTML=rep;
+
   //fonction python qui dessine un graph pour un utilisateur donné
   const pyProg = spawn('python' , ['../py/analyseArthur.py' , 'plot' , user]);
   pyProg.stdout.on('end' , function(){
@@ -465,61 +525,50 @@ app.get('/stats' ,(req ,res ) => {
     res.send(outputHtml);
   })
 })
+
 app.get('/formRecommandation' , (req , res) => {
-  const html=`
-  <html>
-    <head>
-      <title>Bonjour</title>
-      <style>
-      @import url('https://fonts.googleapis.com/css2?family=Lato&display=swap');
-        body{
-          background-color: #141414;
-          padding: 0;
-          margin-top:  10%;
-          color: #fff;
-          font-family: 'Lato', sans-serif;
-          text-align: center;
-      }
-        button{
-          background-color: #1a1a1a;
-          color: white;
-          border-radius: 15px;
-          text-decoration: none;
-          padding: 10px;
-      }
-        .white-space{
-        white-space : pre-wrap;
-      }
-      </style>
+  const html = fs.readFileSync("./temp.html", "utf8");
+  const css = fs.readFileSync('./style.css', 'utf8');
+  const htmlWithCss = `<!doctype html><html><head><title>QssQss</title><style>${css}</style></head>${html}</html>`;
+  const dom = new JSDOM(htmlWithCss);
 
-    </head>
-    <body>
-      <form action="/recommandation" method="POST">
-        <div class="Element">
-          <label class="label" for="reco">Quelle méthode utiliser ?</label>
-          <select class="Saisie" name="reco" id="reco">  
-            <option value="SIM">SIM</option>
-            <option value="KNN">KNN</option>
-            <option value="SVD">SVD</option>
-          </select><br>
-        </div>
-        <button class="Envoyer" type="submit">Envoyer</button>
-      </form>
-    </body>
-  </html>
+  const body = dom.window.document.getElementById("container");
+
+  let rep=`
+    <form action="/recommandation" method="POST">
+      <div class="Element">
+        <label class="label" for="reco">Quelle méthode utiliser ?</label>
+        <select class="Saisie" name="reco" id="reco">  
+          <option value="SIM">SIM</option>
+          <option value="KNN">KNN</option>
+          <option value="SVD">SVD</option>
+        </select><br>
+      </div>
+      <button class="Envoyer" type="submit">Envoyer</button>
+    </form>
     `;
-  res.send(html);
+  body.innerHTML=rep;
+  const outputHtml = dom.serialize();
+  res.send(outputHtml);
 })
 
 //route vers la page de recommmandation pour un utilsateur /\ seulement accessible si user != null
 app.post('/recommandation', (req, res) => {
   const choix = req.body.reco ;
-  const html = fs.readFileSync("./recommandation.html", "utf8");
+  const html = fs.readFileSync("./temp.html", "utf8");
   const css = fs.readFileSync('./style.css', 'utf8');
-  const htmlWithCss = `<html><head><style>${css}</style></head><body>${html}</body></html>`;
+  const htmlWithCss = `<html><head><title>QssQss</title><style>${css}</style></head><body>${html}</body></html>`;
   const dom = new JSDOM(htmlWithCss);
 
-  const div = dom.window.document.getElementById("rep");
+  const body = dom.window.document.getElementById("container");
+
+  let rep=`
+    <table id="liste">
+
+    </table>
+    `;
+  body.innerHTML=rep;
+
   //fonction python qui calcule les meilleurs films pour un utilisateur
   const pyProg = spawn('python' , ['../py/analyseArthur.py' , 'recommandation' , choix , user]);
 
@@ -545,12 +594,24 @@ app.post('/recommandation', (req, res) => {
 
     const tableBody = dom.window.document.getElementById('liste');
 
-    const first = dom.window.document.createElement('tr');
+    let first = dom.window.document.createElement('tr');
+
     first.innerHTML =`<tr>
     <th>Nom</th>
     <th>Description</th>
-    <th>Vote moyenne</th>
+    <th>Vote moyenne (sur 10)</th>
     </tr>`;
+
+    if(user != null){
+      first.innerHTML =`<tr>
+      <th>Nom</th>
+      <th>Description</th>
+      <th>Vote moyenne (sur 10)</th>
+      <th>Aimer/Votre note (sur 5)</th>
+      </tr>
+      `;
+    }
+
     tableBody.appendChild(first);
 
     allData.forEach(row => {
@@ -588,62 +649,58 @@ app.post('/recommandation', (req, res) => {
 });
 
 app.get('/formFilm', (req,res)=>{
-  const html=`
-  <html>
-    <head>
-      <title>Bonjour</title>
-      <style>
-      @import url('https://fonts.googleapis.com/css2?family=Lato&display=swap');
-        body{
-          background-color: #141414;
-          padding: 0;
-          margin-top:  10%;
-          color: #fff;
-          font-family: 'Lato', sans-serif;
-          text-align: center;
-      }
-        button{
-          background-color: #1a1a1a;
-          color: white;
-          border-radius: 15px;
-          text-decoration: none;
-          padding: 10px;
-      }
-        input{
-          width: 25%;
-          background-color: #1a1a1a;
-          color: white;
-          border: none;
-          outline: none;
-          padding: .25em .5em .5em 0;
-      }
-      </style>
 
-    </head>
-    <body>
-      <form action="/film" method="POST">
-        <div class="Element">
-          <label class="label" for="title">Title :</label>
-          <input class="Saisie" type="text" id="title" name="title"><br>
-        </div>
-        <div class="Element">
-          <label class="label" for="description">Description :</label>
-          <input class="Saisie" type="text" id="description" name="description"><br>
-        </div>
-        <button class="Envoyer" type="submit">Envoyer</button>
-      </form>
-    </body>
-  </html>
+  const html = fs.readFileSync("./temp.html", "utf8");
+  const css = fs.readFileSync('./style.css', 'utf8');
+  const htmlWithCss = `<html><head><title>QssQss</title><style>${css}</style></head><body>${html}</body></html>`;
+  const dom = new JSDOM(htmlWithCss);
+
+  const body = dom.window.document.getElementById("container");
+
+  let rep=`
+  <form action="/film" method="POST">
+    <div class="Element">
+      <label class="label" for="title">Title :</label>
+      <input class="Saisie" type="text" id="title" name="title"><br>
+    </div>
+    <div class="Element">
+      <label class="label" for="description">Description :</label>
+      <input class="Saisie" type="text" id="description" name="description"><br>
+    </div>
+    <button class="Envoyer" type="submit">Envoyer</button>
+  </form>
     `;
-  res.send(html);
+  body.innerHTML=rep;
+  const outputHtml = dom.serialize();
+  res.send(outputHtml);
 })
 
 app.post('/film', (req, res) => {
+  const html = fs.readFileSync("./temp.html", "utf8");
+  const css = fs.readFileSync('./style.css', 'utf8');
+  const htmlWithCss = `<html><head><title>QssQss</title><style>${css}</style></head><body>${html}</body></html>`;
+  const dom = new JSDOM(htmlWithCss);
+
+  const body = dom.window.document.getElementById("container");
+
   const pyProg = spawn('python', ['../py/analyseArthur.py', 'nouveauFilm', req.body.title , req.body.description]);
+  let genre=``;
+  pyProg.stdout.on('data', function(data) {
+    //console.log("genre " + data);
+    let genres=data.toString();
+    genre=genres.split(/,|\[|\]/);
+  });
 
-  const html ='<a href=/><button>Retour accueil</button></a>'
-  pyProg.stdout.on('end', function() {
-    res.send(html);
+  let rep=`
+  <p>Voici les genres trouvés ${genre}</p>
+  <a href=/><button class="Envoyer">Retour accueil</button></a>
+    `;
+  body.innerHTML=rep;
+
+
+  pyProg.stdout.on('end', function(data) {
+    const outputHtml = dom.serialize();
+    res.send(outputHtml);
   });
 });
 
diff --git a/static/liste.html b/static/liste.html
deleted file mode 100644
index 86809f149c97e99c3b516ffd8d797ad604a42d21..0000000000000000000000000000000000000000
--- a/static/liste.html
+++ /dev/null
@@ -1,56 +0,0 @@
-  <body>
-    <header>
-      <div id="buttonCoDeco"></div>
-      <div id="allTheA">
-        <a href="/top">Top</a>
-        <a href="/liste">Liste</a>
-        <a href="/formFilm">Ajouter Film</a>
-      </div>
-    </header>
-    <input type="text" id="chercher">
-    <button id="showMoreButton">Afficher plus</button>
-    <table id="liste">
-    </table>
-    <script src="script.js"></script>
-    <script>
-        var user=null;
-        // Récupérer les données JSON du serveur
-        fetch('/user')
-        .then(response => response.json())
-        .then(json => {
-            user = json;
-            console.log("Valeur de user: " + user);
-      
-            if (user == null) {
-            var button = document.createElement("button");
-            var abutton = document.createElement("a");
-            button.textContent="se connecter";
-            abutton.href="/connexion";
-            button.id="connexion";
-            abutton.appendChild(button);
-            document.getElementById("buttonCoDeco").appendChild(abutton);
-            }
-            else{
-            var button = document.createElement("button");
-            var abutton = document.createElement("a");
-            button.textContent="se déconnecter";
-            abutton.href="/deconnexion";
-            button.id="déconnexion";
-            abutton.appendChild(button);
-            document.getElementById("buttonCoDeco").appendChild(abutton);
-
-            var a = document.createElement("a");
-            a.textContent="Stats";
-            a.href="/stats";
-            document.getElementById("allTheA").appendChild(a);
-
-            a = document.createElement("a");
-            a.textContent="Recommandation";
-            a.href="/formRecommandation";
-            document.getElementById("allTheA").appendChild(a);
-          }
-        });
-      </script>
-    <!-- <button id="more">Afficher plus</button> -->
-  </body>
-</html>
diff --git a/static/newIndex.css b/static/newIndex.css
index e9f9f2734ba60960d56e623f88caf12c57a13628..457a9de44eeff6793011d86995f6100b63086b22 100644
--- a/static/newIndex.css
+++ b/static/newIndex.css
@@ -18,27 +18,23 @@ header a{
     text-decoration: none;
 }
 
-.catchphrase{
-    font-size: 4em;
-    text-align: center;
-    height: 800px;
+.allTheA{
+    padding: 10px;
 }
 
-.imgOrdi{
-    width: 400px;
-    height: 300px;
-    border-radius: 50px;
-    object-fit: cover;
+.buttonCoDeco{
     float: left;
+    background-color: #1a1a1a;
+    color: white;
+    border-radius: 15px;
+    text-decoration: none;
+    padding: 10px;
 }
 
-.PersoOrdi{
-    display: flex;
-    justify-content: center;
-    padding: 30px;
-    line-height: 2em;
-    margin: 10px;
-    white-space: pre-wrap;
+.catchphrase{
+    font-size: 4em;
+    text-align: center;
+    height: 800px;
 }
 
 .divImg{
@@ -47,4 +43,4 @@ header a{
     margin: auto ;
     width: 50%;
     height: 50%;
-}
\ No newline at end of file
+}
diff --git a/static/newIndex.html b/static/newIndex.html
deleted file mode 100644
index 25294901b8c07cabf9a65e6eb2c1ff9ef93dd737..0000000000000000000000000000000000000000
--- a/static/newIndex.html
+++ /dev/null
@@ -1,92 +0,0 @@
-<!doctype html>
-<html lang="fr">
-<head>
-  <meta charset="utf-8">
-  <title>What a cool site!!</title>
-</head>
-<body>
-    <header>
-        <div id="buttonCoDeco"></div>
-        <div id="allTheA">
-            <a href="/top">Top</a>
-            <a href="/liste">Liste</a>
-            <a href="/formFilm">Ajouter Film</a>
-        </div>
-    </header>
-
-    <div class="catchphrase">
-        <p>Un Site</p>
-        <p>Une Recommandation</p>
-        <p>Un Contenu</p>
-    </div>
-
-    <div id="divImg" class ="divImg">
-        <p>Visualisation de la donnée par la méthode <a href="https://fr.wikipedia.org/wiki/Analyse_en_composantes_principales">ACP</a> les points représente les utilisateurs </p>
-        <p>ici les utilisateurs sont regroupé par la méthode de clustering <a href="https://fr.wikipedia.org/wiki/K-moyennes">Kmeans</a> sur les prédictions KNN</p>
-        <img src="./img/ACP.png">
-        <p>ici les utilisateurs sont regroupé par la méthode de clustering <a href="https://fr.wikipedia.org/wiki/K-moyennes">Kmeans</a> sur les prédictions SVD (souvent plus pertinente)</p>
-        <img src="./img/ACPKMeans.png">
-        <p>On étudie les méthodes de <a href="https://fr.wikipedia.org/wiki/Regroupement_hi%C3%A9rarchique#La_classification_ascendante_hi.C3.A9rarchique_.28CAH.29">classification ascendante hiérarchique</a> dit CAH</p>
-        <p>ici la méthode Average</p>
-        <img src="./img/ACPaverage.png">
-        <p>ici la méthode Single</p>
-        <img src="./img/ACPsingle.png">
-        <p>ici la méthode ward</p>
-        <img src="./img/ACPward.png">
-        <p> récap avec des <a href="https://fr.wikipedia.org/wiki/Dendrogramme">dendrogrammes</a> pour 6 groupes</p>
-        <img src="./img/CAHcomparaison.png">
-        <p>la comparaison d'efficacité des méthodes de clustering par nombres de clusters<br>
-            les valeurs du tableau sont un <a href="https://scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html">indicateur silhouette</a>
-        </p>
-        <img src="./img/determinerQ.png">
-        <p>méthode hybride de clustering pour 6 groupes entre la CAH et Kmeans <br>
-            c'est cette méthode qui sera utiliser par QssQss </p>
-        <img src="./img/hybride_average.png">
-    </div>
-
-   <!-- <div class="PersoOrdi">
-        <img class="imgOrdi" src="https://img.passeportsante.net/1200x675/2019-11-05/i92345-.webp"/>
-        <p>Vous etes constamment entrain de chercher un nouveau film a regarder ?
-        Ne perder plus votre temps
-        Vous avez fait le bon choix en utilisant notre site web</p>
-    </div>-->
-    <script>
-        var user=null;
-        // Récupérer les données JSON du serveur
-        fetch('/user')
-        .then(response => response.json())
-        .then(json => {
-            user = json;
-            console.log("Valeur de user: " + user);
-      
-            if (user == null) {
-            var button = document.createElement("button");
-            var abutton = document.createElement("a");
-            button.textContent="se connecter";
-            abutton.href="/connexion";
-            button.id="connexion";
-            abutton.appendChild(button);
-            document.getElementById("buttonCoDeco").appendChild(abutton);
-            }
-            else{
-            var button = document.createElement("button");
-            var abutton = document.createElement("a");
-            button.textContent="se déconnecter";
-            abutton.href="/deconnexion";
-            button.id="déconnexion";
-            abutton.appendChild(button);
-            document.getElementById("buttonCoDeco").appendChild(abutton);
-
-            var a = document.createElement("a");
-            a.textContent="Stats";
-            a.href="/stats";
-            document.getElementById("allTheA").appendChild(a);
-
-            a = document.createElement("a");
-            a.textContent="Recommandation";
-            a.href="/formRecommandation";
-            document.getElementById("allTheA").appendChild(a);
-            }
-        });
-      </script>
-</body>
\ No newline at end of file
diff --git a/static/recommandation.html b/static/recommandation.html
deleted file mode 100644
index 41e7b97282c6f4c31c4a5ceb8d5799e5385815d2..0000000000000000000000000000000000000000
--- a/static/recommandation.html
+++ /dev/null
@@ -1,52 +0,0 @@
-<body>
-    <header>
-      <div id="buttonCoDeco"></div>
-      <div id="allTheA">
-        <a href="/top">Top</a>
-        <a href="/liste">Liste</a>
-        <a href="/formFilm">Ajouter Film</a>
-      </div>
-    </header>
-    <table id="liste">
-
-    </table>
-    <script>
-      var user=null;
-      // Récupérer les données JSON du serveur
-      fetch('/user')
-      .then(response => response.json())
-      .then(json => {
-          user = json;
-          console.log("Valeur de user: " + user);
-    
-          if (user == null) {
-          var button = document.createElement("button");
-          var abutton = document.createElement("a");
-          button.textContent="se connecter";
-          abutton.href="/connexion";
-          button.id="connexion";
-          abutton.appendChild(button);
-          document.getElementById("buttonCoDeco").appendChild(abutton);
-          }
-          else{
-            var button = document.createElement("button");
-            var abutton = document.createElement("a");
-            button.textContent="se déconnecter";
-            abutton.href="/deconnexion";
-            button.id="déconnexion";
-            abutton.appendChild(button);
-            document.getElementById("buttonCoDeco").appendChild(abutton);
-
-            var a = document.createElement("a");
-            a.textContent="Stats";
-            a.href="/stats";
-            document.getElementById("allTheA").appendChild(a);
-
-            a = document.createElement("a");
-            a.textContent="Recommandation";
-            a.href="/formRecommandation";
-            document.getElementById("allTheA").appendChild(a);
-          }
-      });
-    </script>
-  </body>
\ No newline at end of file
diff --git a/static/script.js b/static/script.js
index 971bd465f02d37bf5db0aa969ef0cf637d616296..0ff9ef4b01cab17f51a4a4e7c714dff5c1661831 100644
--- a/static/script.js
+++ b/static/script.js
@@ -2,16 +2,18 @@ const tableBody = document.getElementById('liste');
 let data = [];
 let dataUser =[];
 var user = null ;
-let numRowsAlreadyDisplayed = 0;
+let nbrDeLigneDejaAfficher = 0;
 
 // Fonction pour ajouter des lignes à la table
-function addRows(startIndex, endIndex) {
-  for (let i = startIndex; i < endIndex && i < data.length; i++) {
+function ajouteLigne(start, end) {
+  //boucle qui parcours seulement entre index début et fin , on vérifie aussi qu'on dépasse pas la taille de data
+  for (let i = start; i < end && i < data.length; i++) {
     // Vérifier si la ligne a déjà été affichée
-    if (i < numRowsAlreadyDisplayed) {
+    if (i < nbrDeLigneDejaAfficher) {
       continue;
     }
     const row = data[i];
+    //on crée une tr par ligne a afficher
     const tr = document.createElement('tr');
     tr.innerHTML = `
       <td>${row.title}</td>
@@ -19,43 +21,47 @@ function addRows(startIndex, endIndex) {
       <td>${row.vote_average}</td>
     `;
     if(user != null){
+      //variable savoir si le film a déjà était liké
       let trouver = false;
       let note = 0;
       const allDataUser=JSON.parse(dataUser);
       allDataUser.forEach(recu =>{
+        //si correspond alors déjà liké
         if (recu.title==row.title) {
           trouver=true
           note = recu.rating
         }
       })
+      //si déjà liké on affiche la note mit par l'utilisateur
       if(trouver){
         tr.innerHTML += `
         <td>${note}</td>
       `;
+      //sinn il peut liké
       }else{
         tr.innerHTML += `<td><a href='/rating?title=${encodeURIComponent(row.title)}'>J'aime</a></td>`;
       }
     }            
     tableBody.appendChild(tr);
   }
-  numRowsAlreadyDisplayed = endIndex;
+  nbrDeLigneDejaAfficher = end;
 }
 
-// Récupérer les données JSON du serveur
+// Récupérer les données JSON de tout les films
 fetch('/data')
   .then(response => response.json())
   .then(json => {
     data = json;
-    addRows(9, 10); // Ajouter les 10 premières lignes
+    ajouteLigne(9, 10); // Ajoute 1 ligne
   });
 
-// Récupérer les données JSON du serveur
+// Récupérer l'utilisateur
 fetch('/user')
   .then(response => response.json())
   .then(json => {
     user = json;
   });
-
+// Récupérer les données JSON des films déjà liké
 fetch('/datauser')
   .then(response => response.json())
   .then(json => {
@@ -63,44 +69,55 @@ fetch('/datauser')
   });
 
 // Ajouter des lignes supplémentaires en cliquant sur le bouton "Afficher plus"
-const showMoreButton = document.getElementById('showMoreButton');
-let numRowsToShow = 10;
-showMoreButton.addEventListener('click', () => {
-  addRows(numRowsToShow, numRowsToShow + 10);
-  numRowsToShow += 10;
+const bouttonAjout = document.getElementById('showMoreButton');
+let nombreDeLigneaAjouter = 10;
+bouttonAjout.addEventListener('click', () => {
+  ajouteLigne(nombreDeLigneaAjouter, nombreDeLigneaAjouter + 10);
+  nombreDeLigneaAjouter += 10;
 });
 
 // Chercher des lignes qui correspondent au texte tapé dans l'input
 const chercherInput = document.getElementById('chercher');
 chercherInput.addEventListener('keydown', (event) => {
+  //si on appuie sur entrée 
   if(event.keyCode == 13){
     const searchText = chercherInput.value.toLowerCase();
-    //console.log(searchText.trim().length);
-    // console.log(data.length);
     tableBody.innerHTML = '';
 
-    const first =`<tr>
+    let first =`<tr>
     <th>Nom</th>
     <th>Description</th>
-    <th>Vote moyenne</th>
+    <th>Vote moyenne (sur 10)</th>
     </tr>
     `;
+
+    if(user != null){
+      first =`<tr>
+      <th>Nom</th>
+      <th>Description</th>
+      <th>Vote moyenne (sur 10)</th>
+      <th>Aimer/Votre note (sur 5)</th>
+      </tr>
+      `;
+    }
+
     tableBody.innerHTML=first; 
 
+    //trim pour retirer les espaces vides , si vide alors on affiche les 10 premiers films
     if (searchText == null || searchText.trim() == '') {
-      numRowsAlreadyDisplayed = 0;
+      nbrDeLigneDejaAfficher = 0;
       tableBody.innerHTML = '';
-      addRows(0, 10);
-      numRowsToShow = 10;
+      tableBody.innerHTML=first; 
+      bouttonAjout.style.display = 'inline';
+      ajouteLigne(0, 10);
+      nombreDeLigneaAjouter = 10;
       return;
-    }
-    
-    //marche pas très bien
-    if (searchText.trim().length !== 0){
-      showMoreButton.style.display = 'none';
+    }else if (searchText != null || searchText.trim() != '')
+    {
+      bouttonAjout.style.display = 'none';
     }
 
-    
+    //comme pour ajouteLigne
     for (let i = 0; i < data.length; i++) {
       const row = data[i];
       const title = row.title.toLowerCase();
diff --git a/static/stats.html b/static/stats.html
deleted file mode 100644
index df1740b863ce57a6905b6b405160cb61da6e56c2..0000000000000000000000000000000000000000
--- a/static/stats.html
+++ /dev/null
@@ -1,53 +0,0 @@
-<body>
-  <header>
-    <div id="buttonCoDeco"></div>
-    <div id="allTheA">
-      <a href="/top">Top</a>
-      <a href="/liste">Liste</a>
-      <a href="/formFilm">Ajouter Film</a>
-    </div>
-  </header>
-    <div id="divImg" class ="divImg">
-    </div>
-
-
-    <script>
-      var user=null;
-      // Récupérer les données JSON du serveur
-      fetch('/user')
-      .then(response => response.json())
-      .then(json => {
-          user = json;
-          console.log("Valeur de user: " + user);
-    
-          if (user == null) {
-          var button = document.createElement("button");
-          var abutton = document.createElement("a");
-          button.textContent="se connecter";
-          abutton.href="/connexion";
-          button.id="connexion";
-          abutton.appendChild(button);
-          document.getElementById("buttonCoDeco").appendChild(abutton);
-          }
-          else{
-            var button = document.createElement("button");
-            var abutton = document.createElement("a");
-            button.textContent="se déconnecter";
-            abutton.href="/deconnexion";
-            button.id="déconnexion";
-            abutton.appendChild(button);
-            document.getElementById("buttonCoDeco").appendChild(abutton);
-
-            var a = document.createElement("a");
-            a.textContent="Stats";
-            a.href="/stats";
-            document.getElementById("allTheA").appendChild(a);
-
-            a = document.createElement("a");
-            a.textContent="Recommandation";
-            a.href="/formRecommandation";
-            document.getElementById("allTheA").appendChild(a);
-        }
-      });
-    </script>
-</body>
\ No newline at end of file
diff --git a/static/style.css b/static/style.css
index 75eb421114b787b78e63c2ffb494a4c0e70569da..3046599fdff2eefb7236fe04ae4577b44e6fe54d 100644
--- a/static/style.css
+++ b/static/style.css
@@ -12,6 +12,7 @@ header{
     text-align: right;
     height: 50px;
     background-color: #1a1a1a;
+    margin-bottom: 50px;
 }
 
 header a{
@@ -19,6 +20,19 @@ header a{
     text-decoration: none;
 }
 
+.allTheA{
+    padding: 10px;
+}
+
+.buttonCoDeco{
+    float: left;
+    background-color: #1a1a1a;
+    color: white;
+    border-radius: 15px;
+    text-decoration: none;
+    padding: 10px;
+}
+
 .column{
     display: flex;
     flex-direction: column;
@@ -47,4 +61,34 @@ header a{
     border-radius: 15px;
     text-decoration: none;
     padding: 10px;
-}
\ No newline at end of file
+}
+
+.Forminput{
+    width: 25%;
+    background-color: #1a1a1a;
+    color: white;
+    border: none;
+    outline: none;
+    padding: .25em .5em .5em 0;
+}
+
+
+/* button{
+    background-color: #1a1a1a;
+    color: white;
+    border-radius: 15px;
+    text-decoration: none;
+    padding: 10px;
+} */
+
+.white-space{
+    white-space : pre-wrap;
+  }
+
+.divImg{
+    display: flex;
+    flex-direction: column;
+    margin: auto ;
+    width: 50%;
+    height: 50%;
+}
diff --git a/static/temp.html b/static/temp.html
new file mode 100644
index 0000000000000000000000000000000000000000..7805dbdd0efe66661a99314767733281750b110b
--- /dev/null
+++ b/static/temp.html
@@ -0,0 +1,50 @@
+    <header>
+      <div id="buttonCoDeco" class="buttonCoDeco"></div>
+      <div id="allTheA" class="allTheA">
+        <a href="/">Accueil</a>
+        <a href="/top">Top</a>
+        <a href="/liste">Liste</a>
+        <a href="/formFilm">Ajouter Film</a>
+      </div>
+    </header>
+      <div id="container" class ="container">
+      </div>
+      <script>
+        var user=null;
+        // Récupérer les données JSON du serveur
+        fetch('/user')
+        .then(response => response.json())
+        .then(json => {
+            user = json;
+            console.log("Valeur de user: " + user);
+      
+            if (user == null) {
+            var button = document.createElement("button");
+            var abutton = document.createElement("a");
+            button.textContent="se connecter";
+            abutton.href="/connexion";
+            button.id="connexion";
+            abutton.appendChild(button);
+            document.getElementById("buttonCoDeco").appendChild(abutton);
+            }
+            else{
+              var button = document.createElement("button");
+              var abutton = document.createElement("a");
+              button.textContent="se déconnecter";
+              abutton.href="/deconnexion";
+              button.id="déconnexion";
+              abutton.appendChild(button);
+              document.getElementById("buttonCoDeco").appendChild(abutton);
+  
+              var a = document.createElement("a");
+              a.textContent="Stats";
+              a.href="/stats";
+              document.getElementById("allTheA").appendChild(a);
+  
+              a = document.createElement("a");
+              a.textContent="Recommandation";
+              a.href="/formRecommandation";
+              document.getElementById("allTheA").appendChild(a);
+          }
+        });
+      </script>
\ No newline at end of file