diff --git a/M1/Statistical Learning/TP4_Ridge_Lasso_and_CV.ipynb b/M1/Statistical Learning/TP4_Ridge_Lasso_and_CV.ipynb
index 4965a03..1d85bb2 100644
--- a/M1/Statistical Learning/TP4_Ridge_Lasso_and_CV.ipynb	
+++ b/M1/Statistical Learning/TP4_Ridge_Lasso_and_CV.ipynb	
@@ -34,25 +34,24 @@
    "cell_type": "code",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-03-19T09:18:59.373219Z",
-     "start_time": "2025-03-19T09:18:59.369013Z"
+     "end_time": "2025-03-26T10:33:52.177602Z",
+     "start_time": "2025-03-26T10:33:52.174201Z"
     }
    },
    "source": [
-    "\n",
     "import warnings\n",
     "\n",
     "warnings.filterwarnings('ignore')"
    ],
    "outputs": [],
-   "execution_count": 1
+   "execution_count": 4
   },
   {
    "cell_type": "code",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-03-19T09:19:03.853918Z",
-     "start_time": "2025-03-19T09:19:02.315325Z"
+     "end_time": "2025-03-26T10:34:01.222808Z",
+     "start_time": "2025-03-26T10:34:01.200754Z"
     }
    },
    "source": [
@@ -436,12 +435,12 @@
        "</div>"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 49,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "execution_count": 2
+   "execution_count": 49
   },
   {
    "cell_type": "markdown",
@@ -457,8 +456,8 @@
    "cell_type": "code",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-03-19T09:19:12.575121Z",
-     "start_time": "2025-03-19T09:19:12.561648Z"
+     "end_time": "2025-03-26T10:33:52.585039Z",
+     "start_time": "2025-03-26T10:33:52.568658Z"
     }
    },
    "source": [
@@ -824,12 +823,12 @@
        "</div>"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
-   "execution_count": 4
+   "execution_count": 6
   },
   {
    "cell_type": "markdown",
@@ -838,7 +837,7 @@
     "Answer for ex. 1 : \n",
     "\n",
     "\n",
-    "\n"
+    "It set the column named `Name` as the main column\n"
    ]
   },
   {
@@ -864,9 +863,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:52.804278Z",
+     "start_time": "2025-03-26T10:33:52.784889Z"
+    }
+   },
    "source": [
     "# Hint for Question (4) :\n",
     "ex = pd.DataFrame(dict(nom=['Alice', 'Nicolas', 'Jean'],\n",
@@ -876,20 +878,45 @@
     "print(\"data : \\n\", ex)\n",
     "print(\"First result : \\n\", ex.isnull())\n",
     "print(\"Second result : \\n\", ex.isnull().sum())"
-   ]
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "data : \n",
+      "        nom   age  exam\n",
+      "0    Alice  19.0  15.0\n",
+      "1  Nicolas   NaN  14.0\n",
+      "2     Jean   NaN   NaN\n",
+      "First result : \n",
+      "      nom    age   exam\n",
+      "0  False  False  False\n",
+      "1  False   True  False\n",
+      "2  False   True   True\n",
+      "Second result : \n",
+      " nom     0\n",
+      "age     2\n",
+      "exam    1\n",
+      "dtype: int64\n"
+     ]
+    }
+   ],
+   "execution_count": 7
   },
   {
    "cell_type": "code",
    "metadata": {
     "ExecuteTime": {
-     "end_time": "2025-03-19T09:22:51.269241Z",
-     "start_time": "2025-03-19T09:22:51.242330Z"
+     "end_time": "2025-03-26T10:33:53.092776Z",
+     "start_time": "2025-03-26T10:33:53.053583Z"
     }
    },
    "source": [
     "print(hitters.shape)\n",
     "print(hitters.columns)\n",
     "print(hitters.describe())\n",
+    "print(hitters.info())\n",
     "print(hitters.isnull().sum())"
    ],
    "outputs": [
@@ -941,6 +968,34 @@
       "50%     425.000000  \n",
       "75%     750.000000  \n",
       "max    2460.000000  \n",
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "Index: 322 entries, -Andy Allanson to -Willie Wilson\n",
+      "Data columns (total 20 columns):\n",
+      " #   Column     Non-Null Count  Dtype  \n",
+      "---  ------     --------------  -----  \n",
+      " 0   AtBat      322 non-null    int64  \n",
+      " 1   Hits       322 non-null    int64  \n",
+      " 2   HmRun      322 non-null    int64  \n",
+      " 3   Runs       322 non-null    int64  \n",
+      " 4   RBI        322 non-null    int64  \n",
+      " 5   Walks      322 non-null    int64  \n",
+      " 6   Years      322 non-null    int64  \n",
+      " 7   CAtBat     322 non-null    int64  \n",
+      " 8   CHits      322 non-null    int64  \n",
+      " 9   CHmRun     322 non-null    int64  \n",
+      " 10  CRuns      322 non-null    int64  \n",
+      " 11  CRBI       322 non-null    int64  \n",
+      " 12  CWalks     322 non-null    int64  \n",
+      " 13  League     322 non-null    object \n",
+      " 14  Division   322 non-null    object \n",
+      " 15  PutOuts    322 non-null    int64  \n",
+      " 16  Assists    322 non-null    int64  \n",
+      " 17  Errors     322 non-null    int64  \n",
+      " 18  Salary     263 non-null    float64\n",
+      " 19  NewLeague  322 non-null    object \n",
+      "dtypes: float64(1), int64(16), object(3)\n",
+      "memory usage: 52.8+ KB\n",
+      "None\n",
       "AtBat         0\n",
       "Hits          0\n",
       "HmRun         0\n",
@@ -976,7 +1031,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "As `Salary`is the **target** we want to predict,  if it is missing for a player,  we will remove this player. \n",
+    "As `Salary` is the **target** we want to predict,  if it is missing for a player,  we will remove this player.\n",
     "\n",
     "To simplify here, **we only take numeric features**  and ignore factors (i.e. categorical attributes) like  `League`, `Division` and `NewLeague`. \n",
     "\n",
@@ -1004,25 +1059,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:53.191743Z",
+     "start_time": "2025-03-26T10:33:53.186755Z"
+    }
+   },
    "source": [
-    "# Answer for Ex 3\n",
+    "# We remove the players for whom Salary is missing\n",
+    "hitters.dropna(subset=['Salary'], inplace=True)\n",
     "\n",
-    "# (1)\n",
-    "\n",
-    "\n",
-    "# (2)\n",
-    "# Complete with your code\n",
-    "\n",
-    "X =\n",
-    "Y =\n",
+    "X = hitters.select_dtypes(include=int)\n",
+    "Y = hitters['Salary']\n",
     "\n",
     "# check-point\n",
     "print(Y.isnull().sum())  # should be 0\n",
     "print(X.shape)  # should be (322-59, 20-4)=(263,16)"
-   ]
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0\n",
+      "(263, 16)\n"
+     ]
+    }
+   ],
+   "execution_count": 9
   },
   {
    "cell_type": "markdown",
@@ -1034,15 +1098,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:53.367971Z",
+     "start_time": "2025-03-26T10:33:53.348332Z"
+    }
+   },
    "source": [
     "#Answer for Exercise 4\n",
-    "from  # complete\n",
+    "from sklearn.model_selection import train_test_split\n",
     "\n",
-    "Xtrain, Xtest, Ytrain, Ytest =  # complete"
-   ]
+    "Xtrain, Xtest, Ytrain, Ytest = train_test_split(X, Y, test_size=0.3, random_state=42)"
+   ],
+   "outputs": [],
+   "execution_count": 10
   },
   {
    "cell_type": "markdown",
@@ -1054,15 +1123,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:53.539084Z",
+     "start_time": "2025-03-26T10:33:53.531578Z"
+    }
+   },
    "source": [
     "from sklearn.preprocessing import StandardScaler\n",
     "\n",
     "scaler = StandardScaler()\n",
     "XtrainScaled = scaler.fit_transform(Xtrain)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": 11
   },
   {
    "cell_type": "markdown",
@@ -1073,12 +1147,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:53.574140Z",
+     "start_time": "2025-03-26T10:33:53.568355Z"
+    }
+   },
    "source": [
     "XtrainScaled.std(axis=0), XtrainScaled.mean(axis=0)"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]),\n",
+       " array([ 2.41352831e-17,  9.65411326e-18,  1.93082265e-17, -1.20676416e-17,\n",
+       "         1.01368189e-16,  1.61706397e-16,  7.72329061e-17,  6.75787928e-17,\n",
+       "        -1.93082265e-17, -3.86164530e-17,  5.79246795e-17, -3.86164530e-17,\n",
+       "         2.89623398e-17, -3.25826322e-17, -6.75787928e-17,  8.68870193e-17]))"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 12
   },
   {
    "cell_type": "markdown",
@@ -1089,12 +1183,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:53.625854Z",
+     "start_time": "2025-03-26T10:33:53.619268Z"
+    }
+   },
    "source": [
     "type(XtrainScaled)"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "numpy.ndarray"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 13
   },
   {
    "cell_type": "markdown",
@@ -1105,10 +1215,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:53.657967Z",
+     "start_time": "2025-03-26T10:33:53.654162Z"
+    }
+   },
+   "source": "Ytrain = Ytrain.to_numpy()",
    "outputs": [],
-   "source": "Ytrain = Ytrain.to_numpy()"
+   "execution_count": 14
   },
   {
    "cell_type": "markdown",
@@ -1141,19 +1256,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:53.735321Z",
+     "start_time": "2025-03-26T10:33:53.685415Z"
+    }
+   },
    "source": [
-    "# Answer for ex. 4, complete with your code\n",
-    "coef_ridge = []\n",
+    "from sklearn.linear_model import Ridge\n",
     "\n",
+    "ridge = Ridge(fit_intercept=True, alpha=1)\n",
+    "ridge.fit(XtrainScaled, Ytrain)\n",
     "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n"
-   ]
+    "print(ridge.coef_, ridge.intercept_)"
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[-215.12785148  290.20873256   53.45833136   -7.60173315  -38.54941926\n",
+      "   73.36945017   32.60415669 -323.39710533  116.22147257   26.20493566\n",
+      "  353.14584561  122.1676183  -121.03308298   93.78447846   36.78702805\n",
+      "  -14.33540126] 535.83825\n"
+     ]
+    }
+   ],
+   "execution_count": 15
   },
   {
    "cell_type": "markdown",
@@ -1170,18 +1299,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:53.759155Z",
+     "start_time": "2025-03-26T10:33:53.751938Z"
+    }
+   },
    "source": [
-    "# Answer for Ex. 6\n",
+    "from sklearn.linear_model import Lasso\n",
     "\n",
+    "lasso = Lasso(fit_intercept=True, alpha=1)\n",
+    "lasso.fit(XtrainScaled, Ytrain)\n",
     "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n"
-   ]
+    "lasso.coef_"
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([-230.44564808,  301.60792783,   40.17406635,  -10.38454116,\n",
+       "        -22.84228549,   70.6672065 ,   40.56803687, -395.18954578,\n",
+       "         36.12817932,   -0.        ,  486.21184889,  170.22079734,\n",
+       "       -133.5656457 ,   94.08801971,   35.12092631,   -8.15322646])"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 16
   },
   {
    "cell_type": "markdown",
@@ -1196,10 +1343,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:53.780921Z",
+     "start_time": "2025-03-26T10:33:53.777186Z"
+    }
+   },
+   "source": "alphas = np.logspace(-4, 6, 50)",
    "outputs": [],
-   "source": "alpha_s = np.logspace(-4, 6, 50)"
+   "execution_count": 17
   },
   {
    "cell_type": "markdown",
@@ -1210,37 +1362,130 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": "np.logspace(0, 3, 4)"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:53.807330Z",
+     "start_time": "2025-03-26T10:33:53.802462Z"
+    }
+   },
+   "source": "np.logspace(0, 3, 4)",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([   1.,   10.,  100., 1000.])"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 18
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": "10 ** (np.linspace(0, 3, 4))"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:53.850865Z",
+     "start_time": "2025-03-26T10:33:53.845506Z"
+    }
+   },
+   "source": "10 ** (np.linspace(0, 3, 4))",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([   1.,   10.,  100., 1000.])"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 19
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": "np.logspace(-2, 2, 5) == 10 ** (np.linspace(-2, 2, 5))"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:53.872536Z",
+     "start_time": "2025-03-26T10:33:53.868382Z"
+    }
+   },
+   "source": "np.logspace(-2, 2, 5) == 10 ** (np.linspace(-2, 2, 5))",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ True,  True,  True,  True,  True])"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 20
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.012679Z",
+     "start_time": "2025-03-26T10:33:53.899578Z"
+    }
+   },
    "source": [
-    "print(alpha_s)\n",
+    "print(alphas)\n",
     "\n",
     "fig, (ax1, ax2) = plt.subplots(1, 2)\n",
-    "ax1.plot(alpha_s, \".\")\n",
-    "ax2.plot(np.log10(alpha_s), \".\")"
-   ]
+    "ax1.plot(alphas, \".\")\n",
+    "ax2.plot(np.log10(alphas), \".\")"
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1.00000000e-04 1.59985872e-04 2.55954792e-04 4.09491506e-04\n",
+      " 6.55128557e-04 1.04811313e-03 1.67683294e-03 2.68269580e-03\n",
+      " 4.29193426e-03 6.86648845e-03 1.09854114e-02 1.75751062e-02\n",
+      " 2.81176870e-02 4.49843267e-02 7.19685673e-02 1.15139540e-01\n",
+      " 1.84206997e-01 2.94705170e-01 4.71486636e-01 7.54312006e-01\n",
+      " 1.20679264e+00 1.93069773e+00 3.08884360e+00 4.94171336e+00\n",
+      " 7.90604321e+00 1.26485522e+01 2.02358965e+01 3.23745754e+01\n",
+      " 5.17947468e+01 8.28642773e+01 1.32571137e+02 2.12095089e+02\n",
+      " 3.39322177e+02 5.42867544e+02 8.68511374e+02 1.38949549e+03\n",
+      " 2.22299648e+03 3.55648031e+03 5.68986603e+03 9.10298178e+03\n",
+      " 1.45634848e+04 2.32995181e+04 3.72759372e+04 5.96362332e+04\n",
+      " 9.54095476e+04 1.52641797e+05 2.44205309e+05 3.90693994e+05\n",
+      " 6.25055193e+05 1.00000000e+06]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x168541b40>]"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 21
   },
   {
    "cell_type": "markdown",
@@ -1257,24 +1502,70 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.103061Z",
+     "start_time": "2025-03-26T10:33:54.029474Z"
+    }
+   },
    "source": [
-    "# Answer for Exercise 7\n",
+    "from sklearn.linear_model import LinearRegression\n",
     "\n",
     "coefs_ridge = []\n",
-    "for alpha in alpha_s:\n",
-    "#complete\n",
+    "for alpha in alphas:\n",
+    "    ridge = Ridge(fit_intercept=True, alpha=alpha)\n",
+    "    ridge.fit(XtrainScaled, Ytrain)\n",
+    "    coefs_ridge.append(ridge.coef_)\n",
     "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n"
-   ]
+    "plt.plot(np.log10(alphas), coefs_ridge)\n",
+    "plt.show()"
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ],
+      "image/png": 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ZZUSjUc444wyeeOIJNE3LYuRCDHxnTi5h4eQSlqyv5rvPr+GZ/zcPVT14fzUhhOiPFNM0B/3sc6FQiEAgQDAYlP4zQmTY1xTlrAfeoiWh89NLpnLZbHnyTwjRf/T0+1vmZhLiGDY01803zhwPwH2vbqAhkshyREIIcfgkmRHiGLdofjkTS300tST58asbsh2OEEIcNklmhDjG2TWVey8+HrDGnvloR0OWIxJCiMMjyYwQgpkj8/jSiSMA+O7za0ikjCxHJIQQPSfJjBACgG+dM4ECr4PN1WF+9+6ObIcjhBA9JsmMEAKAXI+D75w7CYD/fWMzexpashyREEL0jCQzQoi0i6cPZe7ofGJJg++/uI5jYOQGIcQgIMmMECJNURR+dNHx2DWFZRtr+Nc6mYhSCNH/STIjhOhgbHEONywYA8AP/rmOcFwmohRC9G+SzAghOrnptLGMyPewPxjjl0s3ZzscIYQ4KElmhBCduOwaP7zwOAAef38nG/aHshyREEJ0L6sTTQpxTNBToMfBSIGhg2lYayMFpt6xTLOBzQ12F9haFyU7kz+eOqGYLxxfyitrqvju82v52/UyEaUQon+SZEYMPqZpJQZ6Aowk6G1Lwkog9ET7fipuJRqp1qWrslTMWpKxjO1o67FoRp0Dz2ldm/qR/Tyas2Ny486DwDAIDIfAUGvbP8xa55SAevQaXP+/8ybz5qZaKnY18mzFXpmIUgjRL0kycyQ2/BO2LO1BxR483trjR2B7cq1udjq8htmDssz9g2x3WHdXblqtD6Zh7WduZx5ra6UwdTCMjO0Dyo1UxqK3lmeUDQSqDRQNVK11rVqtOKmo9bO20VuTK4LWftMu2L+6m2vawT8E8sfAyJOsZegsKxn6DIYErIko731lA4tf3cBZk0vI8zo+07WEEKK3SDJzBIx9KzBW/wGAbhvfW7/fOx03O5dJA34vUm3WF73msG7lqHawOaxWD5vTKre5MsoyjtlcYHe3breuO+w72sttroy1o701RXO0xpCRuHTHNK2E7MDWoLb9ljoI7u28NO+3WqKadlvL9n9b19McVkJTPt9KbobPAYe3x2/dovnlPFuxl03Vzfz0XxtZ/MWpR/jLEEKIo0uSmSOwPa+RXScX9tLVFZSM9KZ9u628/biCmt7KPGaVt+4raoey9m0NFbX1eOa+hoKKioaq2FCxobWuVcXeWm5HVWxo2NEUB5riRFOd2LDWKnYUVQUUq9+HorWu1dZFaT2WsZ9uqWgtS29r7fuq1poYtLVs2DqWtW1rDtDsVuJyFG+99DpFseLW7OD09fw8PQXhKiuxqVoDu96HXe9BuBp2v28tYL03Q6bBqFPghCuhaPxBL2vXVH508RQu/c0HPPXRHv5j5nBmjsz77D+fEEIcZYp5DAzxGQqFCAQCBINB/H7/Ubvu1m0/Y9eu3xy16w0+KprmwWbLQdNycNjzsNtzsdvzsDvy27ftea3H8nE6h6BpzmwHPniYJtRvs5KaXe/BzvcgtLdjnVGfg9nXwoRzrVarbvz33z7hbxV7mTTEzz9vno9NG0AJohBiQOrp97ckM0fAMJKYpk57vxRrbR7Y5ySj34qZ7nPSfiyzzLQqAYa113qsvY7Rup25NlrrGK37OqZpYGKtMfX2MjOFiVVmmClMI4VpJrvfNhIYRjxjHUdvXZtGAt2IYegxUnoYXW9B1yPo+pHN6eNwFOJyluF0leFqW5xluFxDcLnKsNsLULL0hM+g0LjLarVZ/wJs+Vd7/xzfEJj5VZjxn1a/mwPUh+Ocfv9bBKNJvnfeZP7r5FF9HLgQ4lgjyUyG3kpmRNdM00DXo62JTYSUHiGVDJFMNZFMNpFMNJBMNlrbyQYSrduJRB2GET3k9e32PHK8E8jJmUhOjrX2esehae4++OkGmabdUPEEVPzB6osD1m2oiedZrTXlJ3d4NPwvy3dz93NryHHaeOOOBZT4P1vHYiGE6AlJZjJIMjMwmKZJKtVELFbZvsTbtvcTj1UST9TQ9RNdCm73yHSCE/BPJzd3liQ4PZWKW0/nrXgMdn/QXl44AU79Nhx3MSgKhmHyxYffZ/WeJs6bOoRfXzkjezELIQY9SWYy9Foy01wNLfU9q/uZb4t0cV6nax2sjtL967d1wM3czjyvQ1k3a6W130S6E++By4Edfo+MrseItGwlHN5IOLyJSHgTzeGNJJOdfw+KYicQmE5e3knk583D7z8BVbUfcQyDXtVaWPk7+OQZSEasstGnwRd+BoXjWLsvyAW/fhfDhCevOZFTxhVlN14hxKAlyUyGXktmXv8BvPvA0bveoKdkPJqc8Yhy5r5mb30SqfUpJK2rR6pdrYPItT8mnVIMEkYzcT1IVK+jOb6bGEFSmkrKppDSFEynh5yCE8krmE9+3knk5ExCUaQTa7diIfjg/+DdX1jj3Kh2mH8rnHIn97y2gyfe38moQi+v3XYKTpuW7WiFEIOQJDMZei2ZefvnsLwHTzP16C3u4a+hq0Huuis3D1bvswyIZ3asM0DpKqRsKimHHfxDceQfhz1/IvhKrU6wbYu36KBP9xwzGrbDK9+Era0DRAZGEDrjx5zxTye1zXFuP2s8t54xLrsxCiEGJUlmMkifmV6SHsn3wBF+D1zMjNF99QPWRscRfPVU+xQERvKA/VT7dANdTSmQjLaXJ8JWy0I8BLEQZjyEkjzMp6wUFfxDoXgSFE+GkuOsdeF4a0C8Y4lpwsaX4bVvQ3APAC8WXc+texbgsKks/cbnGFnQ84H4hBCiJySZySDJjACshCjeDLEmjGg9oaplNFe+QaJ+Hc54CkfCwJkwcKfs2GNxlMwpBTKpNigYByWtCU7pVGtk3cMYVXfASkSsFsn3H8TUk3w59V3e0yfzubH5/OGaufLIvBDiqJJkJoMkM+JgkslGqqtfoarqOYKhj61C08RluClzzqJMnYSzqQZq1kP1eogHO19Ec1qPMY8/G8YthPxBPgZL7WZ45U62bdvM5xOLSeDgp+eUctmpM7MdmRBiEJFkJoMkM6KnWlp2UFX1AvurnicW29NaqlBcdA7l5V/DlzPZmi6gZj1Ur7PWe5Zb47VkKpwA4xfC+HOsuZC0QfgUlWnCun/wm38s4cctF+AjypJL3QyZeW62IxNCDBKSzGSQZEYcLtM0aQquZM/u31Fb1z4zekHBAspH3khu7qzMylC7yRpNd/MSa5wWU28/7gzA2DOskXVHn3pUHlHvT/SmSi755ausjpVyqrqax09Lopz+Xek8LYQ4YpLMZJBkRhyJcHgTO3f9hurqlwCrH01u7hzKy28kP29+534i0UbYtsxKbLYu7TgWUenxcNLXrUHoBtGX/db9jXzhV++SMFV+anuEy8aZcMnvIUfGoBFCfHaSzGSQZEYcDS0tO9m16xH2Vz2HaSYB8PumUl7+NQoLz+q686uhw74KWPMsfPwktD1RFRgB826E6VeDM6cPf4re85u3tvHjVzfio4Ulzm8yJOCGy/4Iw2Yd+mQhhOiCJDMZJJkRR1Mstp/dux9jX+XTGEYMgEBgFhPGfw+f77juT2xpgBW/g48egUitVebKhdnXwInXg6+k94PvRSnd4JLffMAne5o41bmZx7kHRbPDOYuteZ4G2e01IUTvk2QmgyQzojckEnXs3vMEe/Y80TpBpkJZ2WWMGX0HDkdB9ycmo/DJU/D+r6Fhm1WmOeGEK+CU2yGvvC/C7xVba5qt200pg5+NWM6lNf9rHZh6OZz3S3B4shqfEGJgkWQmgyQzojfFYpVs3fZTqqv/CYDN5mPUqK8zbOiXDz4XlKHDplfgvf+FvSusMpsbTv8OzPnagO1T8/Cb2/jJaxvxuWwsPWUbpe9+1+oQXXI8XPVX8JdlO0QhxAAhyUwGSWZEX2hqWsnmzT+kObwOAI9nLOPHfZeCglMOfqJpwu4P4d/3ws53rLKy6XDBr6F0Si9HffRl3m46bUIRvz81gfLsVyFSA/5h8OVnrVGVhRDiEHr6/S2z7AlxlOTmzmL27OeYOOFe7PZ8Wlq2svqTRXzy6fW0tOzq/kRFgZHz4Cv/hAsetB7lrvwYHl0Ab/wPJGN990McBTZN5ef/MRWHpvLvTbX8vaEcrn3dGjU5tBd+fzbsfDfbYQohBhFJZoQ4ihRFY+jQK5g39w2GD/8qimKjru51Plx+Dtu3/xLDiB/sZGssmps/gknnW3NRvfNzeOQUq+VmABlX4uMbZ40H4Af/XEeVWgLXLLEGEIwF4cmLYe0/shylEGKw6NVkZvHixcyePRufz0dxcTEXXXQRmzZt6lDHNE3uueceysrKcLvdnHrqqaxbt65DnXg8zi233EJhYSFer5cLLriAvXv39mboQhwRu93P+HHfZc6JL5OffwqmmWDHzgdZ/tEFNDWtPPjJvlK4/E/WY805JVC3GX5/Drx8pzW31ABx3SmjOGF4Ls2xFHc/twbTnQf/+QJMPM+aMPTZr8IH/5ftMIUQg0CvJjNvvfUWN910Ex9++CFLly4llUqxcOFCIpFIus5Pf/pTHnjgAX7961+zYsUKSktLOeuss2hubv/Qvu2223juued4+umneffddwmHw5x33nnout7VywrRb3i9Y5l2wuNMmfIgDkchLS1bqVh1ORs3fZ9U6hCJyeQL4ablMP3LgAkrfgv/Nxe2vN4nsR+pzNtNyzbW8PdV+8DeOvbMiddblf51N7x2FxjdTOophBA90KcdgGtraykuLuatt97ic5/7HKZpUlZWxm233ca3vvUtwGqFKSkp4Sc/+QnXX389wWCQoqIinnzySS6//HIAKisrGT58OK+88gpnn332IV9XOgCL/iCZDLJ164+p3P9XAJzOUiaM/wFFRWce+uTtb8I/vw6NO639Bd+CBd8Gtf/fKU4/3eS08cLN8xldlGN1en7/V7D0e1alyRfCxY+C3ZXdYIUQ/Uq/7AAcDFqzDefn5wOwY8cOqqqqWLhwYbqO0+lkwYIFvP/++wBUVFSQTCY71CkrK2PKlCnpOgeKx+OEQqEOixDZZrcHmDRpMdOnPYnbPYJ4vIpP11zPmrW3EI/XHvzk0afC1963Bp8DeOsn8PSXINrU22EfsetOGcXs8jya4ymuf7KCcDxl9Q+a/3X44mOg2mH9C1Y/mpaGbIcrhBiA+iyZMU2T22+/nZNPPpkpU6zHTauqqgAoKek48mlJSUn6WFVVFQ6Hg7y8vG7rHGjx4sUEAoH0Mnz48KP94wjxmeXnn8ScE19l5IjrURSNmppX+HD5Qior/8ZBG0odXjj3frjoYWuQvc2vwW9Ph5qNfRf8Z2DTVP7vqhmU+J1sqQlz518/af85p14KV/8DnH7Y/b7VN6hpz8EvKIQQB+izZObmm2/m008/5amnnup07MA5bUzT7Hqemx7WueuuuwgGg+llzx75cBT9i6a5GDv2m8ye9Tw+3xRSqRAbNn6bVR9fRUvLjoOfPO1KuOZf1pgtDdvgsTNg/Yt9E/hnVOxz8fCXZ+LQVF5bV8VDb25rPzjqc/Bfr4GvDOo2we8WQvX67AUrhBhw+iSZueWWW3jxxRf597//zbBhw9LlpaWlAJ1aWGpqatKtNaWlpSQSCRobG7utcyCn04nf7++wCNEf+XyTmTXz74wdexeq6qKpaTnLP/oCO3b+H4aR6P7Esulw/VtQfgokwvDXq60xaYz+2yl+xog8fnihNXfVz5ds4s1NNe0HS46Da5dC0URorrRaaHa+l6VIhRADTa8mM6ZpcvPNN/OPf/yDZcuWMWrUqA7HR40aRWlpKUuXLk2XJRIJ3nrrLU466SQAZs6cid1u71Bn//79rF27Nl1HiIFMVW2MHHEtc+e8Rn7+KRhGgu3bH+CjFRcSDK7q/kRvIVz9PMy9ydp/5+fwl8sh2tj9OVl2xYkjuHLOCEwTbn3qY3bVtz/ZSGAYfPVVGDEP4q1j0ax/IXvBCiEGjF59munGG2/kL3/5Cy+88AITJkxIlwcCAdxuNwA/+clPWLx4MY8//jjjxo3jvvvu480332TTpk34fD4Avva1r/HSSy/xxBNPkJ+fz5133kl9fT0VFRVomnbIOORpJjFQmKZJdfWLbN7yI5LJBkBh2NAvM2bMHdhsvu5P/PSv8OItkIpB3ii44i9QMrnP4j4c8ZTOlx79kFW7m5hQ4uMfN56E15kxD1UyCn+/Fja+BCjwhZ/BiddlLV4hRPb0i7mZuuvT8vjjj7No0SLA+vD+wQ9+wCOPPEJjYyNz5szh//7v/9KdhAFisRj//d//zV/+8hei0ShnnHEGDz30UI879koyIwaaZLKRLVsWs7/q70DbY9zfp6hoYfcn7f8Env4yBHeD3QuXPAYTv9BHER+e6lCM8x58l9rmOOceP4RfXzm94+eFocPLd0DF49b+KXfC6d+1noISQhwz+kUy019IMiMGqoaG99m46btEo9bcTkVFCxk//vu4nKVdnxCph2cXwY63AQUW/g/Mu7lfJgErdzbwpd9+SFI3+fbnJ3LDgjEdK5gmvP0zawJOsAYPPO9/B+xs4kKIw9cvx5kRQhwe6zHuVygf+TUUxUZt7RI+/PAsduz8P3S9iwkovQXw5X/AzK8CJiz5LvzzVkgdpDNxlswqz+f751sdgn/62kbe3nzAWDuKAgu+Cef/ChQVPv4TPH0lJCJdXE0IcSyTZEaIfk7TXIwZcycnzn6RgH86ut7C9u0P8MGHZ1JV9WLnsWk0O5z3Czjnx1YSsOqP8Kcv9ssB6a6aM4LLZw3HMOGWpz5md31L50ozvwKX/xlsLtjyL/jDBRCp6/tghRD9ltxmEmIAsToI/5Ot235KPL4fAL9/GuPHfYdAYEbnEzb/C579L+vx7YKxcOVfoWBM53pZFEvqXP7oh3yyp4mJpT7+esM8/C5754q7l8NTrU9rBYZbnZyHTO37gIUQfUZuMwkxCCmKQmnpBcyb+zqjR9+OpnkIhVazsuJS1q79OtHovo4njD8b/utf1pd//VZrxOAd72Qn+G647Bq/+fIMCnMcbKxq5suPLaeppYvbYiPmwH8tgfwxENwDvz8b1j3X9wELIfodSWaEGIA0zcWo8puYN/cNhgy5FFCornmJD5efxbZtPyeVCrdXLp0C174BQ2dBrAmevAhWPZmlyLs2JODmj/81h3yvg0/3Brni0Q+pD8c7VywaD9e9AWNOh2QL/G0RLPuRzLotxDFObjMJMQg0N69j85Z7aWpaDoDdXsCI4YsYOvTL2O2t/+aTUXj+Rlj3D2v/pFvhzHtAPfRYTX1lS3UzVz62nNrmOGOLc/jLtXMo9ncxk7aegte/Dx/82tqf8AW4+BFwyX/fQgwm8mh2BklmxLHANE3q6payZeuP049ya1oOQ4dewfDhX7Ue5zZNePPH8NaPrZNGn2rNXJ1TlL3AD7CjLsKVv/2Q/cEY5QUe/nLdXMpy3V1XXv0U/PProMetqRC+9BTkj+7bgIUQvUaSmQySzIhjiWEkqa5+iV27HyUS2QyAotgpLb2IkSOuw+sdA2uetUYMTrZATin8x++hfH6WI2+3p6GFL/32Q/Y2RhmW5+ap6+YyPN/TdeW9FdYj2+EqcOXCpU/AmNP6MlwhRC+RZCaDJDPiWGSaJvX1b7Jr1yM0BVe0lioUFZ7JyJHXE4i74K9fsWaqVjRrhN35t4HaP7rSVTZFueqx5eyoizAk4OLP185hdFFO15VD++GZL8O+ldbj6Avvhblf65eDBQohek6SmQySzIhjXTC4ip27HqGu7vV0WW7uiQwtupDij5airnnWKhy30Op74snPUqQd1YRiXPXYcrbUhCnyOfnLtXMYV9LNHFXJGLz0DfjkL9b+5Ivg3AesgQSFEAOSJDMZJJkRwhKJbGXX7t9SVfUCppkEQFPdjAuXU/bxchQ9Af5h1q2a4bOzG2yr+nCcL//uIzbsD5HvdfDkNSdyXFmg68qmCR8+BEv+PzB18BZZAwhOOr9vgxZCHBWSzGSQZEaIjmKx/VTuf5aqqn8Qje4GICecYurGFtwtCUxVQznrf2Dujf3iVk1TS4L//P1HfLo3iN9l48ErZ7Bg/EE6LVd+DM99DWo3WPvHXwaf/0m/aXESQvSMJDMZJJkRomumaRIKfcz+queorn4ZM9bIpC1hSmqtQetaRhyPctEjuPOPy3KkEIol+erjK6jY1QjAV+aN5K4vTMJl7+bR8lQc3lwM7/0vmIbV0fmCX1kDCQohBgRJZjJIMiPEoRlGnLq6N6na/w+ca15h3LYQqglJm8Le8SNJTbuMwqIzCARmoqpdTDfQB2JJnR+/upEn3t8JwNjiHH55+TSmDO3mthPAnhXw/Negfou1P+3LcM594DrIOUKIfkGSmQySzAhxeJLJRhrWPYz/jf/D3WyNJhzxaGwe7SVYlE9B/ikUFJ5KQf4CnM6+H6Pmrc213Pm3T6htjmNTFb5x1nhuWDAGTe3mllgyao0U/MH/ASb4h8IFD8LYM/o0biHE4ZFkJoMkM0J8RnoKfcVvUN78MWqsGYC6fDtbRntp8dgA8PmmkJ9/Cnm5cwgEZmCzefsktIZIgrv/sYbX1lUBMLs8jwcum9b9eDQAu963RkFu3GHtT70CTrsL8sp7P2AhxGGTZCZDbyUzqcZGjObmo3a9fqcn/zR6+M+nR//MenSpjErmobc7vG6H65sd6x6wTp9ntpVlHG9b2uqZrRW7O9Z2fuuxg5dnvG5Xx9p+hvTP1c3P0VOK0trBV8nYJ93pV1EUa9yZZIs1DcLmV1FMHRSFxtIC9hTE0e2t56iAquHJGYs/dwq+wFR8gSnYnD4UVQWbDUXTUGw2a9tuR7HZrH1Ns17rMJmmybMVe7nnxXVEEjo5Thv3XHAcl8wY2v31EhF4/R746FFrX7XDjP+Ez/03+IccdgxCiN4jyUyG3kpmah74BfWPPnrUrifEMc1uR7HbUR0OFJcLxelAdbpQnE5UpxPF6URxuVCdTtScnNbFi5aTQyMO/rC6hjVNOlGbk5mTh3HrF2dTPLQYReumg/C+Cnjjf2D7v619mwtOvA7mf0PGphGin5BkJkNvJTN7v/Ejmpc+28Pa2X+8tZMehXSYcSsHO0PpcrNjFeXg+5llma+lKN2saf8LXc1sfWg/WaG7cw9orWirqxxwnYw66eMH1knHkXE889iB5d1ds8PxQ8TfE20tPxzQ6pOxmJhgmNbM1G2tRNEQNO+HVNxqDFLsmPYcTJsL3UhipOKYqQSmoaMYQOui6KDoffffgqmoqHm5OAoK0AoKsOXnoeUXYCvIR8svwF5agt2swr7ht6jVraMkO3ww70aYd5N0EhYiyySZydBbyUzV3z4hVRE6atcTfcdUTEwbmDbA1rZtYmRsW2sDwwGmw8BwmBh2EzRA6f7WWYfbG5mbioqiKChq67r1Fo61raKoCqqqodo0NM2OatNQNRuazYaqadbaZsNmd2BzOrE7XWg222e6PXNU6CmoeNx6/Lmlvr185HyY/mWYfCFRvZGmpuU0Ni6nKbjSmgDTxEpudCu5cdpKCHhPwOeZgt89GbdWhplIYcZjmPE4RiyOmYi3b8ei6JEIRjiCEQ5jhMPokXB6PxYMEW0M4om3HNaPowVysLti2B3N2L069lwH9hMvwHHGdTjGjLduhwkh+pQkMxl6K5l578knWfPavw5Zr2dfNYf/hdT9l5jSxdahy63LZdZRDtjKaCk4oLztXKukda20bbWWKW17asZ26xd5xlpV1NY6KmrrWkFFVRQUNDRFQ1VUVMVmrbHWWtu+YkNTNDTFjk2xo6m29PbR+OLXzRRxvYWY3tK6jtCSaqYlFSSSChFJBWnRQximfsSvdSiKqmJvTWzaEhy704nD7cHlzcGV48Pt8+HK6bi4fT7cPj+uHN+RvyfJGGx6BVb/Gba+QbqJx5EDx11sJTbD54CiEI/XEgxW0BRcSVPTSsLh9ZgHvE+alkPAP41A7kwCgRkE/NOw2bqZk6kbpmnyzoYqfv/KanZu20tuPExBMsKCYhsnFWh4oyFSdfUkq6pI7tuHETr4HyWKTcUxcjjOScfjHDsW5/hxOMeOxT5smNUfSAjRKySZydBbyczqJa+w/u03jtr1eqwP/xJvT1wOVqmH6Vqnap3P6/TF2tVdpgNvq3TY7Hisw/VMUBUNFRUNG5qpoZk2bNjRTBsadmytZW2LzbRjMx3YDTs2w45Gz/86TyoJEmqMuBYnoUaJqhGiaoQWNUzKTLR26jUwDevWjWEYmLqOrqcwdB09lcLQUxgpHUNPoes6RipJKpHE0FM9juNgNLsdX34hOQUF5OQV4CsoJCe/EF9BQWt5Id7cvJ4nPMF98MlT8PGf2p8YAigYC1MugfKTYdhssLsBSKUihEKf0BSsINi0kmBoNboePuCiKjk5EwkEZpAbsBIcl+sgHXwzmKbJB9vrefCNrXyw3Wo90lSFL04fyk2njaW80HrySg+FSFZWkty3z1r27iWx4SOS2zeRaDIw9a4TFsXlwjl6NM4JE3BPPR7X8VNxTRiPYs/OODxCDDaSzGTorWTm6Y1P8+K2F3tUt0dJQV87SiF19bN1WZaZfHTz4m0tNp222zuIZLToKN2Wq6ig0Nqy09ba036sraxt0RTraZq2Vp+2fZtiQ1M1bKrV2uMw7HgTLlxxO664HWfCjitqwx2x44xoOMIqtmYFNXnw90zNsWMv9mAr9mAv8WArstZqTs9aj/RUilQiTjIWIxmPkYzHW5cYqXiceEuEeCRMNNxMLNxMLBwm2hwiFg4TizQTa24m3hI55OsA2J0ucoeUkTdkKPmt69zSMvLKhuLO6WbSR9OE3R9YSc2656ynodpoDhg607odVT7farVxeFtP0wmHNxEMrrISnOAqYrG9nS7vcBQR8E/DH5hurf3Ho2kHeSQbWLGzgV+9sYV3ttQBVheq0yeWcP4JQzhjUgk5zi4SVUPH3PIGyX8/RnzVu8SbFOJBG/GQg0SzHTPV+eNTcThwTZ6Ma+rxuKeegHvq8diHD8/e7UAhBjBJZjL0VjLzv6v+l8fWPHbUricGCRN8upfiVB7FyQKKk/mUJgoYlihhRHwIxanu5weKOGM05EYIFyaIl4BZ6sAT8OFz+PA7/fgcPnKduXhsniP+ctRTScINDTQ31BGur6O5ob51XUe4vp7mhjoijY2YptHtNVw+P3lDyigcNoLCEaMoGllO4YjyjklOvBnWvwjblsGu96yOw5lUG5RNh5EnwYh5UDIFAsPSrWvxeDVNwVUEW5Ob5uZ1mGbHlilF0fB6JxAITGtNbqbh8YxCUTq3qHy8u5EHl21l2caadJnTpnLahGLOO2EIp08sxuPoIrGJ1MGnz8CqP0LtRkwDEmGNuDGcuDaZaI1JdPMOjGDnW1Zabi6uE6bimTkLz+xZuKdMkdYbIXpAkpkMvZXMbG/azu7m3Uften2pJ792swcDv3RZp8sis+tts3N5+riZUWa2HzMxO+6b3ZcZrV/EhmlgmEb6WNu2YRropp4+3rZvmia6qaMbOrqpkzSS6KZOykihG9Y6ZaZIGSmSRpKkniRhJIjrcRJ6goRubSeNJHE9TjwVJ9X6BezWnQxPlDI8XsqItnV8CKXJQjQ6f/lW2+vZ4trFZtcuNrutteGAPFce+a588lx5FLgKyHPmke/OJ8+ZR4G7gEJ3IUXuIvJd+WhqN48nH4KeShGsqaZx/76MpZLG/fsIN9R3e15OQSHFI0dROKKcohHlFI0cRd6QoaiqCg3braRm53vWOrin8wWcASiZDMWToeQ4aymeDC4/uh6juXktwdBqQqFPCAY/Jh7f3+kSmpaDzzcZn28KPt9x+H1TWhMc673YXN3MPz+p5KVP97Ojrr2Vym3XOH1SMedPHcKpE4o7z/1kmrB3JXz8R1j7D0i03xYzc8pI5p1ENDGCaI1BdN1G4hs2YCY7NtUpbjee6dNwz5qFd/ZsXFOnojqdPfmVCHFMkWQmg4wALPqDpJ6kJdVCNBW11slo+36yhWisBaoTOKpNcurs5DV4yY907viqY7DNtYc1ni2s8WxhnWcrYS3a7euqikq+K58idxEF7gKK3EVWouMpothTTImnJH3Mpva8T1AiFqWpaj8NlXup37OL2t07qd21k1BtdZf1bXYHRSNHUTxqDMWjxlAyeiyFw0egNVe2JzeVq6BuMxjd9AkKjLCSnIKxUDjOWheMI2Y3CIU+JRj6mFBwNaHmNRhGrNPpmuYhJ2cSPt8U/L4p5ORMxO0ezaaaOC99up+XP93P7ob2W2Jeh8bnxhcxuzyf2eX5TBriw6ZlJJzxMKx/3mp52vE2pDJ+D6odRs7DKD+DOGOI7mykZeUKWlasRG9q6hCX4nDgPuEEPLNn45kzB/e0EyS5EQJJZjqQZEYMVEYsRWJfmOTeZhJ7wyT2NKM3xTvUMTFpzkuwP7+RHbn7We/dxl59P7XRWhpiDenWqUNRFZVCV3uS05boFHuKKfGWUOKxFo/94H1T4i0RanfvpG7XTmp377C2d+8iGeuccKmajcIRIylpTW6KR42hcGgZ9uAuqFkP1Wuhej1Ur4Pmyu5f1OmHgjGtyc1YjPzRxNx2grYgocROmsPraG7egGF0lfSpeDwj8XrH4fGMY294PG/tzGPJhhj7mjomRB6HxowRea3JTR7TRuS235JKxmDXu7BlKWxZYrVAZQoMhxFzMctmEdeH0LIjRMuqVVZyU1fXoaridOKZOQPPnLl4587Bddxx8mi4OCZJMpOh155men036945yAdsFh21voY9uNDBqnQ8ljH4XKex8bp6Msna6TBsS9sj4Gr7ee2j8SsZ48pZG4raXqe97gHlqmKN8ZKxrbTWUVUFVWs9rqnp/bYyrW1tU1FtCpqmdthWbSqazTrXZlfR7O1rza6iaYf/WG+qKU5iR5B465Kq7fwFbSvx4Bqbi32Mn8gQnTqjgbpoHXXROmpbaqmN1qbX1S3V1Efr0Xv4KLnP7qPEW5JOdkq8JZR6Sin1ljLEO4RSb2mnhMc0DJqq91O9fSvVO7ZRs2Mb1Tu2Eo907oSsqCoFQ4dTXD463YpTXD4aJ3ErwanZAPVb25em3XCwhM0ZgLyRmHkjSfryiDoVmm0RGpUaGo09JI3upiSxURmfy+amqWxqGMr66hzCiY7/cDVVYUqZn+kj8phQ6mN8SQ7jSnz4XXao39ae2Ox8F/T4AZd3Qdl0zKGzSGijaNln0PLpJiIfLUev7ZjcqF6v1Wozdw7eefNwjhsnj4SLY4IkMxl6K5n54PltrHpt11G7njj2KKqSTnBsdhWbQ8PmULE7NWtxaNg6rFXsLhsOl4bDbcPhsqEZJtRHoSqCsS8MtS2omRmgquAY4cM1NhfnuDwcw3JQDkiidEOnIdZATUtN+xKtoTpSnd6vbqkmnDzwsemu+R3+DslN2/bQnKGU5ZRR6C5EQSFUW031jm1WkrN9KzU7txMNBbu8Zm7JkHSCUzB8JIXDRhAoLkExktCwozW52dK63maVhasOGqeJAjlFpLx5JN0uog6I2KKE1EZa7AniTo2E3UqMDVOhMlzKlqYxbGkay5amcTREu36aa0jAxbgSH+OLcxhf4mNcvo1xifXkVK+EvSusJdbU+cTACMzS40mYw4lUQsvmWiKr13UaB0fLzcUzexae2SfimXOiJDdi0JJkJkNvJTOhuijhxvihKx5VR+fX1aPfek/69nbowHuQyuk+vWanY2bGRuYEj+3lZod5FduG3jc71W8vbzvHbFsbZodyw7DqGoaZHufFNGgd76W1zGg/buit5bqB0WHfRNdNDN1AT3WxThnordt60rCWVM9u+xwJm03FYVOwGSZ23cSugEMFu6LgsKm4i914h+bgGx3AOzQHt8+BK8eO3XHwjsLhRDid2FS3VFMdqaYqUs2+llr2tTRSHQ0TNkxMxY2pujFUD6bqwVTcVpOZqaOYKTTFINfuJc/po8AVoMDpp8idR6k7jyG48DSESezZRcvOLTTs2EaotqbLeGwOJ/lDh1E4bAQFw0dSMGwEhcNH4C8str7cEy2YTbswa7dB7RbM+u0oTbsgtBuleR+KkTjke2mqGimnm4TTRtxuEtMSxB2QcKjUmX62xEewOVrO1ugItkTKaYzndXutPI/C0FwHw/O8jPQYDDcqGRbdwPDGjxja8CFOpfMz/abqJqaMpaUxj8jeJC2bqzBjHT93tEAAz4mzrdabE0/EOX68JDdiUJBkJoP0mRH9iWmY6CmDVGtyk0oapJK6tZ3QScYNknG9dVsnmdBJxXWSCas8GU+RiOokYykSMZ14NGVtR/UjTpRsdhVXjh1Xjh13jh1XjgN3jh2334HbZyfh1qiymexUdDYrKTbEE2yKxIgavZeg2UjhVgy8ho4nmcQdjeJsDqE01eOMRnDHo7jiUVyxFtzxFlyxKN5YC3mRCDnxJO5oHE8igTuewpNI4kmk0FpnLNecBnaPjt2jY/Po1jQGbdseHZvbOKxbtoYCCZtKi+ogpHipN33UpPLZlyqiKlVIEC8h00MILyHTSxAvQdNLGBegUOBOUOxsoVgLUWrUUBbfTVmymjIaKFEaKVUa8JhxYg12Ig0BWhp8tFSmMBMHjKIcCOCeMQP3tGnWcvwUVM/B+zoJ0R9JMpNBkhlxrNCTBol4inhL25LssB0LJ4nWx4jWthANJqxywyRhdtGy1gNxG0RcKmGXSsSlEPfaSHk0zBwbqs+OzWfH4bPjybFjU1WSpklM12lORgklozQnY7SkErToCaK6TsyABHZM1Y2peo/4/XAkYjjjMZyJGK54DGciijMewxuPkhOLkhOP4Y3FyYlH8bVEyYlG8Uci+CMRAuFmclrC5BjNOJ0pbG4Dm8tKcDSXjs1lYHO3rl0Gqu2zf5TqpkIzHoKmlxAeQq3rZtPTYT9keoirdlANNFXHqSbwGi2UN1QzoqaWgqpmHHVJOPBhMFXFOXYU7umz8MyYjnvaNOwjRshAfqLfk2QmgyQzQnTNTBrEd4eIbWmkYWsTH4YjrM7R2OxRiSjgiRt4YybetnXMIJAwcUcN1MNojFE1BU/AQU6uE2/AiTe3fcnJdeL2qtgqt5LatIHo5o1ENm0gvm0HMUMh7PYQ9nhp9ngJuz00e3IIe7zUBbzU5fpo8OUQ8lplLa4c4s4cUjb3UX2fNEPHruvYDR2HaeAwdJymgdMwcBo6TsPAm4qSF28iL9FIbiJIoHXxpYL4kyFy9DAePYLbjOJW4rjUBC4lgV058jm84qaNIDkETS9Bw0NLgxOjHhz1STz1UZzRzo+6mx4njtFl5Ewai+f4abhmzMc+WvreiP5FkpkMkswI0bXtLXGWNYR4oz7EB01hYkb7x4HNNJnaqHNc0GBMWGdss0F5xMDjsWMf7kMdmoNe4CblsdESThEJxmkJJmgJxomEWtfBBLHwIeZ2yGBLRnDGm3DFm3DGG3Emg+T47fhK/QRGlZA7eRTOsSOo90G13khluJLKSCVVkSoqw5Xsj+xnf3g/cUPHVD3tfXZUL6Zi7aumF7uRg2rmoOBGUT2gujFUFynNSUpzkLA5SNgdmJ9xsMHD4TTi+FNhcpPNBFJh/Kkwfj2c3g6kwvhSEWs/2UxuwqqXq4cI6GFsHDqrTLaoROscROsdROscxBrtmEbnVhnDphDPdZAo8qIPyUcbU05g2lxKJs0jr2Qkitb774cQmSSZySDJjBAW0zRZE47yfHUTr9Q1sTPasQNsmdPO6fl+Ti/wcUqeD09UJ7E7RHxXiMSuZhJ7m0E/4CPDpmAv8WIv8WAv8WIrteaZ0gJOFEUhldQJrt9O48q1NG7YRfOuGiIRg7gzl7gjl7gzQNyZi6H1bJA4p8dGTp6TnDxX6zpz24U310HQaKIuWkdNSw21LbXURGs6PpLeUktdrK77MXhMsKUUnEkXdt2FZriw6S5cZgCHGcCu+NHUHFC9mDYPhmpDV1UMRe2wTm8rCoaqYSiKtagqOgqGksCgBZ1mTDOCQRiTBKaZwCSOSRKIg5kAM96+YFhBYqKaurVgoJoGimmgoKOZYDdNHKaJwzBwmTouQ8dtpshJ6gypgSE1UFKrkF+n4KtX0fRu5kzz6Kg+SOXYaPG7iAQ8xPJ9mCX5eAqH4SsdT/7IWRQPnYDb7erR71GInpBkJoMkM+JYtzkS4/maRl6obmJbtP1JGLuicGLAy+kFfk7P9zHR6zpoPwozaZCoDJPY2ZbghDAi3bS8aAakgqRqtpGq3ooRqcGMBTFjTZjxMI6xo/FMn2F1VJ0+DbOojEhTgnBTnEhjnHBjjHBjnHBTnHCDtZ2M9+yWjMtrx5tn3cJKr3M77mtOhXAyTDARpCneRDAeJBgL0twSItLcTLgqRLQmhh4xMONgHKSBSTHBjg2X6cBtOvDgwIFKiy1KyB6i0R6kyR4kZAsT0iIEbc0EbWHi6qGfpuorqmEypAFG1piUV5uMrIHyapO8g8xHaigmYb9JLGBi5OgoHgPDo5J0u0h4PCS8fnD4UT15ePNKKRgyjoKhk8grGY/fnyu3tMQhDbpk5qGHHuJnP/sZ+/fv57jjjuOXv/wlp5xySo/OlWRGHIt2R+O8UNPE8zWNrAu3j2TrUhXOKghwYXEup+b7yLF99lsHpmmiN8SIb62hZfU2Ersb0MMqijMf5WC3aFTQfA5UvxPN50DzO6z9HDuKTUWxZy5auiypG0TCSZobWxOeJmuJtN7SCocSpJI968xjUxVcdgWXpuJUQCFJ1AzTrIVo0JpIaDEMLYGpJNODPTpMG7mmh1zDS65pLagpqp317HfUss9R07pUU2NvwFAO/fHqMBz4Uz58hg8/fjy4cSlOPIoLt+rCo7rwatbarbhwKU40U0MxAcMEU7H6Lxm0likohjV0QEJPkDKSpPSUtTZS6KZBytTR0UmpKVrUOC1qlGYtRpMtSkiLEdZiRNUYMTWOMxqhsDFKWYNJaaNJWQMMabASH2c3s05kavJAkw/CPpO4x0R3mShOA9Nlojts6C4HSaeThMuDouZgt/lwOwPk+orJKxxGSekYCkvHkJc/FJtDpng41gyqZOaZZ57h6quv5qGHHmL+/Pk88sgjPPbYY6xfv54RI0Yc8nxJZsSxojKW4OXaIM/XNFIRap9jyKbAqfl+Li7O5ezCwBElMABGNEpLxSpaPvyAyAcfElu/vuPgRaoN17STcB03F1vpWBQtFz2URA8lrJacXvrUMU2TlAlRE6KGScyAqGkSM0yiBtbahORhvb6JppjYFAUNiNkiNDuCNDhrqXHvp9FVS8weIaFFSWoxElqMuC1KSk2gGE7MRCFmqpBi9zDKfMUM95cwpqCUiUVDmVIyjFx35/m3+oqZMjATOkZcb1/HdfRYkmi0hVikhWiomZamZprDQYLRIOFkhJgRI2bGiCab0Fsa0CKN2CMhvOEw/uY4ec0p8psNHD1IdjKFXdbS4oQWp0LcaZJ0gO4wMR0mugN0u4puUzFsGqZNI2WzY2g2dM2BYXOgO5wodjd2uwen3YvXlYPPm0uev4jC/DIKCoaS6yvEHyjCZnf0zhsrjppBlczMmTOHGTNm8PDDD6fLJk2axEUXXcTixYsPeb4kM2Iwq4wleKm2iX/WBFkRar8noADzc3O4qCSPc4sC5Nk/+9w+ZjJJdM1aIh9+QMsHHxJdvbrTTNCOMWPwzp2Ld95cPLNnowUCXV9LN9DDSYxQAj2UQG+OW+vWRMdMGZhJo32d7LiPbkDrtBOoCoqmdL3v0FCdGopDQ3G2b9cmm1i5Zz3baitRdDuqbkc1HKi6E1vKi5ZyoxoOQEXhsz+6bGKCXcXlsePNseN026wRntumtMjYtjm09EjQqqZaU2a0TbPRxXb7tCAZ2+n/Rzru9ECS7UF1mKk+feyAgSkN08DUdfRUCkNPYRoGhpGyBpA0dEzTwDSsOqZpYOg6RkLHSKSIR1uIhiPEWyLEQyHioSBmNAzJGIaexDSSKHoSLZXCntKxJw1sutk+X/wBX0mZe8phZMGGYt0GMxTQVTBUMJXW8tZtUwVTMTFb3zdTsRaU1ldSrXXb8bb311A6vulm25uvmJjp/YwTALNtrhXMjPIDfqKMqVmsWm2/x4zjmad3cECQHPjekVF+4HwyXV3v0A48TSvyccu9v/psF+tGT7+/+/3MZYlEgoqKCr797W93KF+4cCHvv/9+l+fE43Hi8fZ+AaEDhgIXYqDbl05gmliZ0QKjACcGvJxfnMv5RbmUOO2f6fpmKkVsw0ZaVq4k8uEHRFesxGhp6VDHNmRIe/IyZy72kuIeXVvRVGwBJwR6/5ZBSyhBfWWYuj0htmzdyq6aDUTMeuugBprpxpb0Yk/k4UjkotggOGoPews2sMn+CXWpGlwpL+5kDq5UDq6klzyjGFesDKM5D2ciF1fKg8fU8GkaThSUpAFm6xdR0iQeTBAPHt2+MVZCkgAzgWnGW9dWJ2Fr3XYsCaTATGKaqYzttvIUoGOaOqCDqWN1Lj7yx8UPSgUcrUt/1vuDdQ8qajR74xb1+2Smrq4OXdcpKSnpUF5SUkJVVdfzrixevJgf/OAHvR5b9Y5t1O+RuZmO3qyWXfyB0NW1Myel7K6842yVHQ+3bqT/6m6bfBIlY2LL1jqqVd42caV1vH1p31dbJ6lUW7fV1skqVVRVBUVB1TRUVUPVNKs8va+iaBqqqqJqti474BqmybpwlLcbw7xS29ThFpICzAl4Oa84l/OKcin9DAmM0dJC9NNPaamoIFpRQcvqTzAPSF603Fw8c+bgnTcX79y52EeO7DeDrqWSOo37W6jbG6Z+X/vSEo4Rc1fR4tmHYWvtN2SCK1FEqXccw8qHYRa3sNW5hk8T/6aiYSXRVOvEnQbYNBsTS8cyMmcSdXUlLN+Yw+qgG1BAhRMn5nPZ7OF84fjS9OzZpmmSShgkoini0RSJtiWmk0rqpBJtIz9bozsnIhFikWbiLSHikTCpRIRUooVUogU92UIqGUVPtqAnoxipKHqqBdPo62lUANTWf+/Wv3FrX23970BN//fT1rygtM8Amy7v6r/L9LbSXTtYd//Gui5va42yWpvM9NpsHfW5fQoUk+7bgDJewez6WK84zJc5aENNFpif7W+no6LfJzNtDvzQNE2z2w/Su+66i9tvvz29HwqFGD58+FGPafOH7/LR83876tcVxzZVa014NBspVSOhqsQUlaSioqsax2kaEzQbXqeTQo+bIV4PXpcLzWZnrcPOBrsDm8OB3eHE5nRidzqxOdrXmsOBGmnB2LWL1IZNJNetI7VhI2oy2eFDUfX5cM+YjvdEK4FxTpyY9adPTNOkuSFG/b5Ie9KyN0xTTRQzY4wcXY0R9VYSK9qPqVqtDDbNwfjy45g7bw7x/DCv7nyFh/c+wubazR1eo8hdxCnDTmF+2cmEGsv520d1/HFHQ/p4YY6DS2YM47LZwxlT1LG/SyqRINocspZQiJbmINFQ236w47p1MfTP3gqiahoOjxen243D7cHp8eJwu3F6vNidLuwuJ3anq/3373Ra/y5cLmttd6DZ7dZis6HZ7Kg2Gza7tW4ra0vOheiv+n0yU1hYiKZpnVphampqOrXWtHE6nTidvd+EnVdaRvkJM3r9dXpDf+wq1aOYOtQxuyk2W492nNTSzOgU0L5ptv4l19a3oO0vubbDRnu5YWT0L8j4a880WieqbFub7X0K2soNA8MwrP4Guo6hG9a1u2DoeusXnHVrwt66dCUF7DnUe3YoCjB5BJgmNlXD7nDg8Obg8Pmwu9w4qndif60Kx5se7C4XDpfLKm9bu93WF6fTid3l7vAlane50WxdtzYdjGmatIQSNOyL0LA/Qn1lmIZKazsZ6/rL3+m1kT/UTdC+g90NG9K/7/z8fObOncuICSN4o/INvrnxNtbVr8v48RWmFk3llKGn8Llhn2Osbwzvb9zHg39by87K93EYCcaYcaYW2ZlZ6mK4F5KVm9nw5zAfR8LEws1Em5uJNodIxqKf6Vdgd7nx+P24cvy4/X5c3hxcOT5cOT7cOe3brpwcnN4cXN4cHB4PNrtDkgwhGEAdgGfOnMlDDz2ULps8eTIXXnihdAAWA05UN9jcEmN9cwsbm1vY2Bxhc3MLDfEEqmGg6Tpq63D5x7vtzPS6OMFrZ6zTjqKnMFIpUskEejJJKplETyZIxeMkGhtJ1NWRaGgg3lBPor6eRDBIytCtQdpUpXVp3bbbre3uBo47ShRVTSc7NocDm8Naa3aH9TSJomHoKnpKJRlXiEd14i0GehLStzLIvK2h4vbb8fodeAIOPH5riSYirF+3jkgkApjkBgKUlBTTTJAdjduoCVWhGNbwNzZDpcCRR54awG3Y0eMJEtEo8WgL5hG0lIDVWuL2+Tsu/gBun89a+wO4fX48rWu3z4/N0d87jwiRHYOmAzDA7bffztVXX82sWbOYN28ejz76KLt37+aGG27IdmhCdGKaJk0pnap4kupEkv3xJJWxJBsjMTZEomxviXfRr1ADp5vjclycnOfjc3k+5ga8eDMeoTZaWkjV1ZHct4/Erj0kdu0isXs3iV07Se7egyfRdSdTxenEOX48rsmTcU2ahGvyJJzjx6O6rJFaDUMnFY+TjMdJxKIkY7HWJUoibm23l0dJtK2jUZLxWHqdjMVIxuMkY9a+nrKeyzUNg0S0hUS0pcv4PotkC4S67jJHW5tstLaSnVs3AOAH/Bw4cWWs9f+6Zmp23F4vbq8XV2briDenfT/dgpKTTlKcHq+0lgjRxwZEMnP55ZdTX1/PD3/4Q/bv38+UKVN45ZVXGDlyZLZDE4OUaZokTJOYbtCsG4R1nXDKoDmlE9YNmnWdcOt2MKlTlUhSFU+mE5jMOY66kmfTmOiyMdGmMMFIMT4ZY3RLM67dDaQq6kjV1dFYV0dtXS16bR2p2tpOTxN1YrPhGDYM+8gROMtHWUnLpEk4R49GsXX/n7qqajjcHhxuD17yPsvbhWmYhJvihOqiBGuj1ro6TFNNiFBdM7FIFFqfoGl/qiYFpo6ipnB5VVxeBadHwZVjw+lRcbpUTFof+9VTGLrRutbTna9jsRh79uwhGo1iKCam3yRoCxJMBtEVMFQTl9PD2MLxTCqeTLGvFM1mT/cTMVQ7S7Y08cK6OkK6RkJ1sGDyMO4493jGlEgrrhADxYC4zXSkeus2099Wr+dfdcf2Y989/cdjwiG73B94ra56x5jpRelUZnQ4bj1c2rbWUWgdJBXdbHv4VCGhQBKFBJBAIakoJFvXR8ofj1EcCVMYaaagOUh51T5G7dlJ+fat5NdUfaYnEBSXC3tpKY6RI3GUj8Q+YgSOEa3bQ4YcNGk5EqZpEm1O0lwfI1QfbV3HaK6PEqqL0VwfQ08d/HaV2+8gr8RDbuvStu0vdKFqh9exWNd13nvvPd58800iSoTd+bvZlbuL5lQzAC7NxcLyhZw/5nxml8xGO2A0YsMweWblHh5YupnaZuvJoBkjcrn7C5OYVZ5/WLEIIXrPoLrN1F+t3rCFl0qldWiwsyeTeGJRPPEonmgUbyyKOxbDG4viibXgjUYpDDZS0NRIYbCRwqYGCoJNOFKHni1acbtRc7xo3hzUnBy0gnxshYXYCousdVFh634hWmERqtfTK7cwTNMkFk62JijtCUtm0pJKHDxZUVWFnAIXgSI3gUI3/kI3gSI3/iIX/kI3DtfR+bipra3lH8/9g7X1a9lasJXKnEoMDEjBEO8QvjTxS3xx3BcJOLsetK86FOPOv33CO1vqABhZ4OFb50zk81NK5faQEAOUJDNH4HSngv/DZdkOI7sOc1j4TF1NW9Nh5IluGg2V1vEr1dZxIxSztSxjrWKiGSYqJqppjS6qmgaqaZ2nYWIzDeyGgcM0sRkGdkwcho7dMHFgWscwcCrWODBoWutaRdFsKDYNVA3Fb0cpGo7iGIPidKA6HChOJ4q9de2wozqdqF4vqs+H6s1By/Gier0o9r4ZmME0rKeDmhusBKVt3ZaoNNfHDj2nkQLegBN/gQtfgZWg+Fq3A4VucvKch93CcrhWVKzgkTcfYbNvM41ljenyWSWzuGrSVZw6/FRsavcfa0vXV/PNZz+hsSWJy65y58IJ/Oe8chw2mfBQiIFMkpkjcMYXL+CMbAchBJCIpQinJ1+M0dwQ75C4hBtjGKlDZ57egANfQXuS4st34S904S9w48t3odmz86Xfkmzhl8t+yfN7nydaaD3+7FAdnDv6XK6cdCUT8yce9PxoQudHL6/nz8t3AzB5iJ9ffWkaY4t9vR67EKL3STIjRD+WSui0hBK0NCdoCSaINieItM0U3RhvnT06RqKbsVcyKQp485z48l3pxV9oJSltiUu2kpXuhBIhnt74NI9/+jhhPQw28Kt+vnLCV/iP8f9BvuvQ/VvWVQb5+tOr2VoTBuC6U0Zx59kTcB7hZJtCiP5Dkhkh+oBpmqSSBvFIknhLitgB63hLkngkRbS5PXFpaU50O0BcVxxuGzl5TmvJdaYTFF+Bi5x8Fzm5vX8b6Gipi9bx5PoneWbTM0SS1uSZ3qSXzxd+nm+f922ctkMPimkYJr9/bwc/fW0TCd2g2Ofk/stO4JRxRb0dvhCij0kyI44JbSPzGoaJaVh9SAzdRNcNDN1sfezXTC+6bmCkrLWebJtLx0BPZWy37qcSOsl4N0tMJxFPkYzpGPpne3BQs1mDxHl8rQPEBZwZSYuLnHwn3lznUetgm037wvt4fO3jPL/1eeK69ZSRP+FnYtNELpt2GQvPXNijTro1oRh3ZHTyPXNSCT/9j6nke2VwOiEGo4H/6ZdF69+tZPOKbkbuOlxH8QH5z/qw/UGf0jcz63U+cOCpmdMFdHVe22tlzDBA2zQDptl+wNpvnWqgrcxoTU7M9jWm2bE8nbhY676aJ+5QVFXB6bXh9Nhxta6dHhtOr7V257SPaOvxO3D7HThc2qB/ymZHcAePrXmMl7e/jG5arVGjXKMo3VnKkOgQPnfK5zj99NN79D68t7WOW576mIZIApdd5bvnTuaqOSMG/XsoxLFMkpkjEKyLsm9TU7bDEEdI1RRUm4qmKda2qqBqKqrNWtvs1qJlrDW7is2motk1NLuKw6Vhdx6wuGwd9p0ea1++VNttbdzKo2se5V87/4XROq3CSWUnMYc57HpvFwoKCxYs4NRTT+3R+/bn5bv43gvr0A2TSUP8PCidfIU4JkgycwTGzSqhcFjOoStmwWf9wux0mpK5qXRZ3unc1g2li7rWyK0ZxUrGdZXWUxWrRFHTFVr3lfQ1FLXj2jpXQWlbq9YxVbW229aKatWxEpa2fUku+trGho08+umjLN21NF126vBTuX7q9TSsb2DZsmUoKJx66qmceuqph7yebpjc+/IGfv/eDgAumlbGjy+ZissunXyFOBZIMnMECofl9NtkRoj+aF3dOn7z6W94c8+b6bKzRp7F/5v6/5iYP5G33nqLf//73wCcdtppLFiw4JDXbI4l+frTq1m2sQaAO84az82nj5UkVYhjiCQzQohet7pmNY98+gjv7nsXsFrjzik/h+umXse4vHEAvP322+lE5owzzuCUU0455HX3NLRw7R9Wsqm6GadN5YHLpnHu1CG994MIIfolSWaEEL3CNE3eq3yPx9Y8RkV1BQCaonHu6HO59vhrGRUYla67detWli2zRtM+88wzOfnkkw95/YpdjVz/5ErqwgmKfE4e+89ZnDA8t1d+FiFE/ybJjBDiqEoZKZbuWsrv1vyOTY2bALCpNi4YcwHXTrmW4f7hHeqHw2Gee+45AGbNmtWjROaF1fv472c/JZEymDzEz2NfmUVZrvvo/zBCiAFBkhkhxFER1+O8sPUFHl/7OHvDewFw29xcOv5Srp58NaXe0k7nGIbBc889RyQSobi4mLPPPvugr2EYJr98fTO/WrYVsMaP+d8rpuF1ykeZEMcy+QQQQhyR5kQzf930V55c/yT1sXoAcp25XDnpSq6ceGW3s1cDfPDBB2zbtg2bzcZ//Md/YD/IxJvxlM5//+1TXvykEoDrPzeab54zEU2Vjr5CHOskmRFCfCbbm7bzzKZneHHbi4ST1rxHpd5SFh23iIvHXozH7jno+Xv37uWNN94A4POf/zzFxcXd1m2OJbn+yQre31aPTVW49+IpXD57xNH7YYQQA5okM0KIHksaSf69+988s+kZPqr6KF0+OjCaa46/hs+P+jx2tfvWlTaxWIxnn30WwzCYPHkyM2bM6LZudSjGosdXsGF/CK9D4+Evz+Rz42V+JSFEO0lmhBCHVB2p5u9b/s6zm5+lNloLgKqonDrsVC6feDlzh8xFVXo2iaVpmvzzn/+kqamJ3Nxczj///G7HhNlaE+Yrv/+IfU1RCnMcPPHVE5kytPvbVkKIY5MkM0KILhmmwYqqFTyz6RmW7V6WnjOpwFXAJeMv4dLxl3bZqfdQPv74Y9atW4eiKFxyySW43V0/hVSxq4Fr/rCSppYkowq9/OGrJzKi4OC3roQQxyZJZoQQaYZp8HHNxyzZuYTXd71OTbQmfWxmyUyumHAFZ4w4A7t26FtJXamtreWVV14B4PTTT2f48OFd1luyropbnvqYeMrghOG5/P4rsyjIcX6m1xRCDH6SzAhxjNMNnVU1q1iycwlv7H4jfRsJIMeew7mjz+WyCZcxPm/8Eb1OMpnk2WefJZVKMXr0aObPn99lvT8v38X/9/xaDBNOn1jMr6+cjschH1VCiO7JJ4QQx6CkkWR1zWr+tfNfvLH7DeqideljPruP00acxsKRC5lXNg+H5jgqr7lkyRKqq6vxer1cfPHFqGrHPjamafLA0s082DqGzOWzhnPvxVOwaT3riyOEOHZJMiPEMSCaivJp7aesql5FRU0Fn9Z+SjQVTR/3OXycPvx0FpYvZO6QuUctgWmzYcMGVqxYAcDFF1+Mz+frcDyRMvjOc2v4W4U12N7XzxjHbWeOk8kihRA9IsmMEINQMB5kVfUqVtWsYlX1KtbXrydlpjrUCTgDnDbcaoGZO2TuZ+4HcyiRSIQXXngBgJNOOomxY8d2ON4YSXDDnypYvqMBVYEfXXQ8V86RMWSEED0nyYwQA5RpmlS3VLMztJOdwZ3WunV7X3hfp/olnhJmlMxgZvFMppdMZ2zu2B4/Tn0k3nrrLWKxGCUlJZx++ukdjm2rDfNfT6xgV30LOU4bD145ndMmdD94nhBCdEWSGSH6obgepzHWSEOsgYZYQ3q7MdbIvvA+doZ2siu0q8OtogONCoxiRvEMZpbMZEbJDMq8ZX1+26a2tjZ9e+nss8/GZmv/yHlvax1f+1MFoViKoblufr9oNhNKfd1dSgghuiXJzBF4bstzvLbztaN2PYWj+EXTg0t19XoHlmV++WUe61Cvw6bScX3A+V3tdzhHaS9XUdP1M+u2tSaoitqpPHP7wP0Dy1U618ms11aeXmfE3yEuFAwMDMOw1qaBaZropo5pmumyWCpGXI+3r/VYh7KYHiMYD9IYa6Ql1XLoXyCgKRrDfcMp95cz0j+S8kA55f5yxuSOIc+V16Nr9KalS5dimiYTJkxg9OjR6fI/L9/F915Yh26YzByZxyNXz6RQHr0WQnxGkswcgd3Nu3m/8v1shyEGKZtiI8+VR54rj3xXfnpd4imh3F9OeaCcYb5hPZo+IBu2bdvG5s2bUVWVs846CwDdMLn35Q38/r0dAFw0rYwfXzIVl13LZqhCiAFOkpkjsHDkQkYHRh+6Yh8zMQ9dx+xc58DzuqpzYL3MOm3l6bXZ+XqZdTL3M49nlhum0anMNM1O5Zn7B24bGB3qtS0H1m9rUclsXWk71lV8JibW/8x0q056aW1V0hTNagVSVJyaE5fmwmlrXWtOXDYXLpsrfSzgDKQTGJ/dN2Cf5jEMgyVLlgAwe/ZsCgsLCcdT3PrUxyzbaA3Ed8dZ47n59LED9mcUQvQfkswcgUkFk5hUMCnbYQjR76xevZrq6mpcLhcLFixgb2ML1/5hJRurmnHaVO6/7ATOm1qW7TCFEIOEJDNCiKMqHo+zbNkyABYsWMB7O5v51t8/pSGSoMjn5Lf/OYtpw3OzG6QQYlCRZEYIcVS99957hMNhcvPyeH6Pm2deWAnAcWV+fvufsyjL7XpiSSGE+KwkmRFCHDXBYJD337c6xb/TUkbFqn0oCvy/U0Zz+8LxOG3S0VcIcfRJMiOEOGqWvv46qVSKKsNHRdDN0Fw39192AnNHF2Q7NCHEICbJjBDiqFi+dgtr16wBYEVyOBdPH8YPLjwOv6t/PjouhBg8JJkRQhwR0zR58sNdLH/tBYoU2E0RP/jSyfK0khCiz/TaxCw7d+7kmmuuYdSoUbjdbsaMGcP3v/99EolEh3q7d+/m/PPPx+v1UlhYyK233tqpzpo1a1iwYAFut5uhQ4fywx/+sNsxUIQQfWdzdTOLHl/B7/75DkVKGENRufvaSyWREUL0qV5rmdm4cSOGYfDII48wduxY1q5dy3XXXUckEuHnP/85ALquc+6551JUVMS7775LfX09X/nKVzBNkwcffBCAUCjEWWedxWmnncaKFSvYvHkzixYtwuv1cscdd/RW+EKIg9hc3cz/vrGFV9bsRzENvujcC8Cpp5zM2GEyUaQQom8pZh82cfzsZz/j4YcfZvv27QC8+uqrnHfeeezZs4eyMusvuaeffppFixZRU1OD3+/n4Ycf5q677qK6uhqn05q75cc//jEPPvgge/fu7dHooaFQiEAgQDAYxO/3994PKMQgl5nEtH1yXDI0gq9+PTk5Odxyyy3p/06FEOJI9fT7u9duM3UlGAySn5+f3v/ggw+YMmVKOpEBa2bdeDxORUVFus6CBQs6fECeffbZVFZWsnPnzi5fJx6PEwqFOixCiM9uU1UzN/1lFWf/8m1e/tRKZL5wfCnP/79ZFIa3AXDGGWdIIiOEyIo+6wC8bds2HnzwQe6///50WVVVFSUlJR3q5eXl4XA4qKqqStcpLy/vUKftnKqqKkaNGtXptRYvXswPfvCDo/wTCHHs2VTVzK+WdWyJ+cLxpdx6xjgmlvpZtmwZ8XickpISTjjhhOwGK4Q4Zh12MnPPPfccMlFYsWIFs2bNSu9XVlZyzjnncOmll3Lttdd2qNvVbSLTNDuUH1in7c5Yd7eY7rrrLm6//fb0figUYvjw4QeN+bP4cHs9H+9u6lHdnsyl19Pp9g68ltLFmd29Xof39YC6SkadDmWtO0rrpoLSum7fb/0fauu5imJtt11Pbd1XM7fVtmMKWlu5qqCpVpktY1tT2xebqmDXVGyagl211m3bqiqTFh4J3TD5ZG8T/95Yw7KNNayrbG/VPPf4IdxyxlgmllpNvfF4nI8++giAz33uc6hqnzb0CiFE2mEnMzfffDNXXHHFQetktqRUVlZy2mmnMW/ePB599NEO9UpLS1m+fHmHssbGRpLJZLr1pbS0NN1K06amxpp198BWnTZOp7NPmrvf3lzLQ29u6/XXET2nKmDTVJyaisNmLc70WrPKNBWnXcVl03A7Whe7hseh4Wpdu+1WuddhI8dlI8dpw9e6znHZBtVItsFokne21LJsYw1vbaqlPtL+NKGiwOentLfEZFq1ahWxWIz8/HwmTZIJV4UQ2XPYyUxhYSGFhYU9qrtv3z5OO+00Zs6cyeOPP97pL7d58+Zx7733sn//foYMGQLAkiVLcDqdzJw5M13n7rvvJpFI4HA40nXKyso63X7qa1OGBviPmcOOyrV62g3bxDywoIs6mdc1uynvWNZWz8woNDHb65nt+2b6/Mx9KzLDzLiWCYZpdlpbi1XPMK3WgLZya9sqSy+miWGYpAxrnTQMUrq1fyDDhETKIJEyIH6od/Ozc2gqOa72BCfgtndY/AfsB9x2cj3W2ueyo2WpBSme0qlsirG3sYX1lSGWbaxh5a5G9Iz30ue08bnxRZw2sZhTJxRRmNP5DwNd1/nggw8AOOmkk6RVRgiRVb32NFNlZSULFixgxIgR/PGPf0TT2v+SLS0tBawPxGnTplFSUsLPfvYzGhoaWLRoERdddFH60exgMMiECRM4/fTTufvuu9myZQuLFi3ie9/7Xo8fzZanmQYn07QSmpSekeDoBknDTCc0iZRBPKW3rq0loRvEkzqxlEE0kSKaMGhJpogldFoSOtGkTrR1HYmnCLctsRSRhH7EcSsK+F0dE5y27RynHa9Dw+u04XW2rh02POkyGzZVyUj8THSjc0LYHEuxtzHK3sYW9jVF09vVoa4zvDFFXs6YVMJpE4qZVZ6HXTt4crJ69Wqef/55vF4vt912G3a7jPIrhDj6evr93WsdgJcsWcLWrVvZunUrw4Z1bL1oy580TePll1/mxhtvZP78+bjdbq688sr0ODQAgUCApUuXctNNNzFr1izy8vK4/fbbO/SJEccmRVGwawp2Ddz0zW0f3TCJJKzEJhxP0RxLEYolCUWTBKNJgi2t626WloSOaZLe393QJ2F34LZrDMtzM7LAw8ljCzl9YgkjCjw9Pt8wDN577z0A5s6dK4mMECLr+nScmWyRlhnRXyRSRmsik6CpNfFpaknS1JrchGMpWhJWC1AkniIST9HStp1IEYnr6IbZobO0pijWdkYnao9DY1ieh2F57tbF2h6a6ybf6+jR+Ezd2bRpE0899RQOh4NvfOMbuN3uo/gOCSFEu6y3zAghOnPYVIp8Top8A3c8lrZWmVmzZkkiI4ToF6TXnhCix3bv3s3u3btRVZW5c+dmOxwhhAAkmRFCHIa2VpkTTjhBbtkKIfoNSWaEED1SW1vLpk2bAOtxbCGE6C8kmRFC9Ehbq8zEiRMpKirKcjRCCNFOkhkhxCEFg0E+/fRTAObPn5/laIQQoiNJZoQQh/Thhx9iGAYjR47slXnOhBDiSEgyI4Q4qGg0SkVFBSCtMkKI/kmSGSHEQa1YsYJEIkFxcTHjxo3LdjhCCNGJJDNCiG4lk8n0zPbz588/opGDhRCit0gyI4To1urVq4lEIgQCAaZMmZLtcIQQokuSzAghumQYBu+//z4A8+bNQ9P6ZjJPIYQ4XJLMCCG6tGHDBhobG3G73cyYMSPb4QghRLckmRFCdKmtr8zs2bNxOBxZjkYIIbonyYwQopPq6mp2796NoijMmjUr2+EIIcRBSTIjhOhkxYoVAEyaNEkmlBRC9HuSzAghOojFYnzyySeAdYtJCCH6O0lmhBAdfPLJJySTSYqKiigvL892OEIIcUiSzAgh0kzTTN9imj17tgySJ4QYECSZEUKk7dixg7q6OhwOB1OnTs12OEII0SOSzAgh0tpaZaZOnYrL5cpyNEII0TOSzAghAAgGg2zcuBGAE088McvRCCFEz0kyI4QAoKKiAtM0GTlyJMXFxdkORwghekySGSEEqVSKVatWAfI4thBi4JFkRgjBxo0bCYfD5OTkMGnSpGyHI4QQh0WSGSEEH330EQAzZ86U2bGFEAOOJDNCHOMy52GaOXNmtsMRQojDJsmMEMc4mYdJCDHQSTIjxDFM5mESQgwGkswIcQyTeZiEEIOBJDNCHKNkHiYhxGAhyYwQxyiZh0kIMVhIMiPEMUrmYRJCDBaSzAhxDMqch0k6/gohBjpJZoQ4Bq1atSo9D1NJSUm2wxFCiCMiyYwQxxhd16moqACkVUYIMTj0STITj8eZNm0aiqKwevXqDsd2797N+eefj9frpbCwkFtvvZVEItGhzpo1a1iwYAFut5uhQ4fywx/+ENM0+yJ0IQadTZs2EQ6H8Xq9TJw4MdvhCCHEEbP1xYt885vfpKysLD04Vxtd1zn33HMpKiri3Xffpb6+nq985SuYpsmDDz4IQCgU4qyzzuK0005jxYoVbN68mUWLFuH1ernjjjv6InwhBpWVK1cCMGPGDGy2PvkIEEKIXtXrn2SvvvoqS5Ys4e9//zuvvvpqh2NLlixh/fr17Nmzh7KyMgDuv/9+Fi1axL333ovf7+fPf/4zsViMJ554AqfTyZQpU9i8eTMPPPAAt99+u4yNIcRhqK+vZ/v27YCVzAghxGDQq7eZqqurue6663jyySfxeDydjn/wwQdMmTIlncgAnH322cTj8fQ9/Q8++IAFCxbgdDo71KmsrGTnzp1dvm48HicUCnVYhBDtrTLjxo0jLy8vy9EIIcTR0WvJjGmaLFq0iBtuuIFZs2Z1WaeqqqrTkxR5eXk4HA6qqqq6rdO231bnQIsXLyYQCKSX4cOHH+mPI8SAl0wm033WuvtvUgghBqLDTmbuueceFEU56LJy5UoefPBBQqEQd91110Gv19VtItM0O5QfWKet8293t5juuusugsFgetmzZ8/h/phCDDrr168nGo0SCAQYN25ctsMRQoij5rD7zNx8881cccUVB61TXl7Oj370Iz788MMOt4fA+ovwqquu4g9/+AOlpaUsX768w/HGxkaSyWS69aW0tLRTC0xNTQ1At+NjOJ3OTq8rxLGu7RbTzJkzUVUZlUEIMXgcdjJTWFhIYWHhIev96le/4kc/+lF6v7KykrPPPptnnnmGOXPmADBv3jzuvfde9u/fz5AhQwCrU7DT6WTmzJnpOnfffTeJRAKHw5GuU1ZWJrP8CtFDVVVV7NmzB1VVmT59erbDEUKIo6rX/jwbMWIEU6ZMSS/jx48HYMyYMQwbNgyAhQsXMnnyZK6++mo+/vhj3njjDe68806uu+46/H4/AFdeeSVOp5NFixaxdu1annvuOe677z55kkmIw9DWKjNx4kR8Pl+WoxFCiKMrq23Nmqbx8ssv43K5mD9/PpdddhkXXXQRP//5z9N1AoEAS5cuZe/evcyaNYsbb7yR22+/ndtvvz2LkQsxcMTjcT799FNAOv4KIQanPhsxq7y8vMtRe0eMGMFLL7100HOPP/543n777d4KTYhBbc2aNSQSCQoKChg1alS2wxFCiKNOegEKMYiZpsmKFSsAq1VGbs0KIQYjSWaEGMT27t1LdXU1NpuNE044IdvhCCFEr5BkRohBrK3j73HHHdflKNxCCDEYSDIjxCDV0tLCunXrAJg9e3aWoxFCiN4jyYwQg9Qnn3xCKpWitLSUoUOHZjscIYToNZLMCDEImaaZvsUkHX+FEIOdJDNCDEI7duygvr4eh8PB8ccfn+1whBCiV0kyI8Qg1NYqc8IJJ8g8ZUKIQU+SGSEGmebmZjZu3AiQnuNMCCEGM0lmhBhkPv74YwzDYPjw4ZSWlmY7HCGE6HWSzAgxiOi63qHjrxBCHAskmRFiENm4cSOhUAiPx8PkyZOzHY4QQvQJSWaEGEQ+/PBDwBokz263ZzkaIYToG5LMCDFI7Nu3jz179qCqqtxiEkIcUySZEWKQaGuVmTJlCj6fL8vRCCFE35FkRohBIBQKpedhmjt3bpajEUKIviXJjBCDwIoVKzAMgxEjRlBWVpbtcIQQok9JMiPEAJdMJqmoqACkVUYIcWySZEaIAW7NmjW0tLQQCASYMGFCtsMRQog+J8mMEAOYaZrpjr9z5sxB07QsRySEEH1PkhkhBrAdO3ZQU1OD3W5n+vTp2Q5HCCGyQpIZIQawtlaZadOm4Xa7sxyNEEJkhyQzQgxQ9fX1bN68GbBuMQkhxLFKkhkhBqjly5cDMG7cOAoLC7McjRBCZI8kM0IMQLFYjNWrVwPyOLYQQkgyI8QA9PHHH5NIJCgqKmL06NHZDkcIIbJKkhkhBhjDMNK3mObOnYuiKFmOSAghskuSGSEGmE2bNtHU1ITb7eb444/PdjhCCJF1kswIMcC0PY49c+ZMHA5HlqMRQojsk2RGiAFk//797Nq1C1VVmT17drbDEUKIfkGSGSEGkLZWmcmTJxMIBLIcjRBC9A+SzAgxQIRCIdauXQvI49hCCJFJkhkhBoh33nkHXdcZMWIEw4YNy3Y4QgjRb0gyI8QAEAwGWbVqFQCnnXZalqMRQoj+RZIZIQaAtlaZ8vJyRo0ale1whBCiX+n1ZObll19mzpw5uN1uCgsL+eIXv9jh+O7duzn//PPxer0UFhZy6623kkgkOtRZs2YNCxYswO12M3ToUH74wx9immZvhy5Ev9DU1JRulTn11FOzG4wQQvRDtt68+N///neuu+467rvvPk4//XRM02TNmjXp47quc+6551JUVMS7775LfX09X/nKVzBNkwcffBCwOj2eddZZnHbaaaxYsYLNmzezaNEivF4vd9xxR2+GL0S/8Pbbb2MYBqNGjaK8vDzb4QghRL/Ta8lMKpXi61//Oj/72c+45ppr0uUTJkxIby9ZsoT169ezZ88eysrKALj//vtZtGgR9957L36/nz//+c/EYjGeeOIJnE4nU6ZMYfPmzTzwwAPcfvvtMpS7GNQaGxvTE0pKXxkhhOhar91mWrVqFfv27UNVVaZPn86QIUP4/Oc/z7p169J1PvjgA6ZMmZJOZADOPvts4vE4FRUV6ToLFizA6XR2qFNZWcnOnTt7K3wh+oW2VpkxY8YwYsSIbIcjhBD9Uq8lM9u3bwfgnnvu4bvf/S4vvfQSeXl5LFiwgIaGBgCqqqooKSnpcF5eXh4Oh4Oqqqpu67Ttt9U5UDweJxQKdViEGGjq6+vTrTLSV0YIIbp32MnMPffcg6IoB11WrlyJYRgAfOc73+GSSy5h5syZPP744yiKwt/+9rf09bq6TWSaZofyA+u0df7t7hbT4sWLCQQC6WX48OGH+2MKkXVvv/02pmkyduxY+TcshBAHcdh9Zm6++WauuOKKg9YpLy+nubkZsIZdb+N0Ohk9ejS7d+8GoLS0lOXLl3c4t7GxkWQymW59KS0t7dQCU1NTA9CpxabNXXfdxe23357eD4VC8mUgBpS6ujo+/fRTQPrKCCHEoRx2MlNYWEhhYeEh682cOROn08mmTZs4+eSTAUgmk+zcuZORI0cCMG/ePO69917279/PkCFDAKtTsNPpZObMmek6d999N4lEIj1D8JIlSygrK+v2yQ6n09mhj40QA01bq8z48eMZOnRotsMRQoh+rdf6zPj9fm644Qa+//3vs2TJEjZt2sTXvvY1AC699FIAFi5cyOTJk7n66qv5+OOPeeONN7jzzju57rrr8Pv9AFx55ZU4nU4WLVrE2rVree6557jvvvvkSSYxaNXW1qaHMJC+MkIIcWi9Os7Mz372M2w2G1dffTXRaJQ5c+awbNky8vLyANA0jZdffpkbb7yR+fPn43a7ufLKK/n5z3+evkYgEGDp0qXcdNNNzJo1i7y8PG6//fYOt5GEGEzeeustTNNkwoQJHZ70E0II0TXFPAaG0g2FQgQCAYLBYLrFR4j+qKamhoceegiA66+/Pn37VQghjkU9/f6WuZmE6EfefPNNACZNmiSJjBBC9JAkM0L0E9XV1axfvx6QvjJCCHE4JJkRop9oa5U57rjjuh12QAghRGeSzAjRD+zbt48NGzYAsGDBgixHI4QQA4skM0Jkma7r/POf/wRg6tSpFBcXZzkiIYQYWCSZESLLli9fTlVVFS6Xi4ULF2Y7HCGEGHAkmREiixobG/n3v/8NWINI5uTkZDkiIYQYeCSZESJLTNPklVdeIZlMMnLkSKZPn57tkIQQYkCSZEaILFm3bh1btmxB0zTOP/98mZ5DCCE+I0lmhMiCaDTKq6++CsApp5zSo8lbhRBCdE2SGSGy4PXXXycSiVBYWJieVV4IIcRnI8mMEH1s165dVFRUAHDeeedhs/XqfK9CCDHoSTIjRB9KpVLpMWVmzJhBeXl5dgMSQohBQJIZIfrQe++9R11dHV6vl7POOivb4QghxKAgyYwQfaSuro63334bgHPOOQe3253liIQQYnCQZEaIPmCaJi+99BK6rjNmzBimTJmS7ZCEEGLQkGRGiD6wevVqdu7cic1m47zzzpMxZYQQ4iiSZEaIXhaJRFiyZAkAp512Gnl5eVmOSAghBhdJZoToRbqu8/e//51oNEpJSQlz587NdkhCCDHoSDIjRC967bXX2L59O3a7nYsvvhhN07IdkhBCDDqSzAjRS1asWMGKFSsAuOSSSygtLc1yREIIMThJMiNEL9i+fTuvvPIKAGeccQYTJ07MckRCCDF4STIjxFFWX1/PX//6V0zTZOrUqTL3khBC9DJJZoQ4iqLRKH/5y1+IxWIMGzaM888/Xx7DFkKIXibJjBBHia7rPPvss9TX1+P3+7n88sux2+3ZDksIIQY9SWaEOEr+9a9/sW3bNux2O1/60pfw+XzZDkkIIY4JkswIcRSsXLmSjz76CICLL76YIUOGZDkiIYQ4dkgyI8QR2rFjR/rJpdNPP53JkydnOSIhhDi2SDIjxBFoe3LJMAyOP/54TjnllGyHJIQQxxxbtgMQYqCqrKzkL3/5C9FolKFDh3LBBRfIk0tCCJEFkswI8Rls3ryZv/3tbySTSYqKirjiiivkySUhhMgSSWaEOEwfffQRr776KqZpMnr0aC677DJcLle2wxJCiGOWJDNC9JBhGLz++uu8//77AEybNo3zzz9fJo8UQogsk2RGiB5IJpP84x//YMOGDYD11NIpp5wifWSEEKIfkGRGiEOIRCI89dRT7N27F03TuPDCC5k6dWq2wxJCCNFKkhkhDqKuro4///nPNDY24nK5uOKKKygvL892WEIIITL06jgzmzdv5sILL6SwsBC/38/8+fP597//3aHO7t27Of/88/F6vRQWFnLrrbeSSCQ61FmzZg0LFizA7XYzdOhQfvjDH2KaZm+GLgQ7duzgscceo7GxkdzcXK699lpJZIQQoh/q1ZaZc889l/Hjx7Ns2TLcbje//OUvOe+889i2bRulpaXous65555LUVER7777LvX19XzlK1/BNE0efPBBAEKhEGeddRannXYaK1asYPPmzSxatAiv18sdd9zRm+GLY1Q4HOb1119n9erVAAwdOpQvfelL5OTkZDcwIYQQXVLMXmriqKuro6ioiLfffjs9KmpzczN+v5/XX3+dM844g1dffZXzzjuPPXv2UFZWBsDTTz/NokWLqKmpwe/38/DDD3PXXXdRXV2N0+kE4Mc//jEPPvgge/fu7VEHzFAoRCAQIBgM4vf7e+PHFYOAYRisXLmSZcuWEYvFAJg+fTpf+MIXZAwZIYTIgp5+f/fabaaCggImTZrEH//4RyKRCKlUikceeYSSkhJmzpwJwAcffMCUKVPSiQzA2WefTTwep6KiIl1nwYIF6USmrU5lZSU7d+7srfDFMWb37t08+uijvPLKK8RiMUpLS7nmmmu48MILJZERQoh+rtduMymKwtKlS7nwwgvx+XyoqkpJSQmvvfYaubm5AFRVVVFSUtLhvLy8PBwOB1VVVek6B/ZTaDunqqqKUaNGdXrteDxOPB5P74dCoaP4k4nB5MBbSi6Xi9NPP51Zs2ahqjJ1mRBCDASH/Wl9zz33oCjKQZeVK1dimiY33ngjxcXFvPPOO3z00UdceOGFnHfeeezfvz99va5uE5mm2aH8wDptd8a6u8W0ePFiAoFAehk+fPjh/phikDMMg48++ohf//rX6URm+vTp3HzzzZx44omSyAghxABy2C0zN998M1dcccVB65SXl7Ns2TJeeuklGhsb0/e5HnroIZYuXcof/vAHvv3tb1NaWsry5cs7nNvY2EgymUy3vpSWlqZbadrU1NQAdGrVaXPXXXdx++23p/dDoZAkNAKAWCzGp59+yooVK6itrQWsf2Pnnnuu/BsRQogB6rCTmcLCQgoLCw9Zr6WlBaDTX7iqqmIYBgDz5s3j3nvvZf/+/QwZMgSAJUuW4HQ60/1q5s2bx913300ikcDhcKTrlJWVdfuYrNPp7NDHRhzbTNOksrKSlStXsnbtWpLJJCC3lIQQYrDo1aeZJk6cyIIFC/je976H2+3mt7/9Lf/7v//LihUrOOGEE9B1nWnTplFSUsLPfvYzGhoaWLRoERdddFH60exgMMiECRM4/fTTufvuu9myZQuLFi3ie9/7Xo8fzZanmY5N8XicNWvWsHLlyg6te4WFhcyaNYsTTjgBt9udxQiFEEIcTE+/v3utA3BhYSGvvfYa3/nOdzj99NNJJpMcd9xxvPDCC5xwwgkAaJrGyy+/zI033sj8+fNxu91ceeWV/PznP09fJxAIsHTpUm666SZmzZpFXl4et99+e4fbSEK0MQyD/fv3s2rVKtasWZMegFHTNCZPnsysWbMYMWKEzKkkhBCDSK+1zPQn0jIzuDU2NrJ9+3a2b9/Ojh070rc4wRoiYObMmUybNg2Px5PFKIUQQhyurLfMCNFbIpEIO3bsSCcvjY2NHY7b7XYmTJjAzJkzKS8vl1YYIYQY5CSZEf2WaZqEQiFqamqoqamhtraW/fv3U11d3aGeqqoMGzaMUaNGMXr0aIYOHYrNJv+0hRDiWCGf+CLrkskkzc3NNDU1pROXtuQlc/DDTCUlJenkZeTIkfL0mhBCHMMkmRG9wjRNEokE0WiUWCxGJBIhFAp1Wpqbmzv0cTmQqqoUFBRQXFxMUVERxcXFjBgxQiZ9FEIIkSbJzDHONE10XSeVSnW5TiaTJBKJTuvM7Xg8TjQaTScubdtt4wn1hM1mIxAIpBOWtuSloKBAbhkJIYQ4KPmWOAKbNm1i27Zt6f3MB8O62j6cdU8WwzA6bWeuDcNA1/X0duai63p66U2qquJ2u/F4PPj9/i4Xn8+H2+2WjrpCCCE+E0lmjsCePXv46KOPsh3GUaWqKpqmYbPZ0DQNu92Ow+Hodu1wOHA6nbjdblwuF263O724XC4cDockKUIIIXqVJDNH4MDHfg+13ZP1wZa2Oqqqpsu629Y0DVVV08uB+6qqphOWtnVbHSGEEGIgkWTmCIwdO5axY8dmOwwhhBDimCZ/hgshhBBiQJNkRgghhBADmiQzQgghhBjQJJkRQgghxIAmyYwQQgghBjRJZoQQQggxoEkyI4QQQogBTZIZIYQQQgxokswIIYQQYkCTZEYIIYQQA5okM0IIIYQY0CSZEUIIIcSAJsmMEEIIIQa0Y2LWbNM0AQiFQlmORAghhBA91fa93fY93p1jIplpbm4GYPjw4VmORAghhBCHq7m5mUAg0O1xxTxUujMIGIZBZWUlPp8PRVGO6rVDoRDDhw9nz549+P3+o3pt0U7e574h73PfkPe5b8j73Dd68302TZPm5mbKyspQ1e57xhwTLTOqqjJs2LBefQ2/3y//sfQBeZ/7hrzPfUPe574h73Pf6K33+WAtMm2kA7AQQgghBjRJZoQQQggxoEkyc4ScTiff//73cTqd2Q5lUJP3uW/I+9w35H3uG/I+943+8D4fEx2AhRBCCDF4ScuMEEIIIQY0SWaEEEIIMaBJMiOEEEKIAU2SGSGEEEIMaJLM9IJ4PM60adNQFIXVq1dnO5xBZefOnVxzzTWMGjUKt9vNmDFj+P73v08ikch2aAPeQw89xKhRo3C5XMycOZN33nkn2yENOosXL2b27Nn4fD6Ki4u56KKL2LRpU7bDGtQWL16Moijcdttt2Q5lUNq3bx9f/vKXKSgowOPxMG3aNCoqKvo8DklmesE3v/lNysrKsh3GoLRx40YMw+CRRx5h3bp1/OIXv+A3v/kNd999d7ZDG9CeeeYZbrvtNr7zne/w8ccfc8opp/D5z3+e3bt3Zzu0QeWtt97ipptu4sMPP2Tp0qWkUikWLlxIJBLJdmiD0ooVK3j00UeZOnVqtkMZlBobG5k/fz52u51XX32V9evXc//995Obm9v3wZjiqHrllVfMiRMnmuvWrTMB8+OPP852SIPeT3/6U3PUqFHZDmNAO/HEE80bbrihQ9nEiRPNb3/721mK6NhQU1NjAuZbb72V7VAGnebmZnPcuHHm0qVLzQULFphf//rXsx3SoPOtb33LPPnkk7MdhmmapiktM0dRdXU11113HU8++SQejyfb4RwzgsEg+fn52Q5jwEokElRUVLBw4cIO5QsXLuT999/PUlTHhmAwCCD/fnvBTTfdxLnnnsuZZ56Z7VAGrRdffJFZs2Zx6aWXUlxczPTp0/ntb3+blVgkmTlKTNNk0aJF3HDDDcyaNSvb4Rwztm3bxoMPPsgNN9yQ7VAGrLq6OnRdp6SkpEN5SUkJVVVVWYpq8DNNk9tvv52TTz6ZKVOmZDucQeXpp59m1apVLF68ONuhDGrbt2/n4YcfZty4cfzrX//ihhtu4NZbb+WPf/xjn8ciycwh3HPPPSiKctBl5cqVPPjgg4RCIe66665shzwg9fR9zlRZWck555zDpZdeyrXXXpulyAcPRVE67Jum2alMHD0333wzn376KU899VS2QxlU9uzZw9e//nX+9Kc/4XK5sh3OoGYYBjNmzOC+++5j+vTpXH/99Vx33XU8/PDDfR6Lrc9fcYC5+eabueKKKw5ap7y8nB/96Ed8+OGHneammDVrFldddRV/+MMfejPMAa+n73ObyspKTjvtNObNm8ejjz7ay9ENboWFhWia1qkVpqamplNrjTg6brnlFl588UXefvtthg0blu1wBpWKigpqav7/9u7YJZk4juP45ykIQsXBG2oxjpaKtlOEWhQHx2ixIYKcxUGXcD3CyUGiycUtaIijpUGXcHR1C6eGEx7xD3AIn+HhEaShhycfj9/xfm331eGDy33ux1f9KcdxFrOPjw/1+33d399rNptpc3MzwIThsbu7q6Ojo6XZ4eGhnp6e1p6FMvMFy7JkWdaX77u7u9Pt7e3i2vd9FQoFPT4+KpPJ/M+IofC3n7P0+6uAuVxOjuOo0+loY4MDxu/Y2tqS4zjq9Xo6Pz9fzHu9ns7OzgJMFj7z+VyVSkWe5+n19VW2bQcdKXTy+byGw+HSrFQq6eDgQDc3NxSZFTo9Pf300wJvb2/a29tbexbKzIokk8ml62g0Kkna39/nyWuFfN9XNptVMplUs9nUZDJZvLazsxNgMrPVajVdXV0plUotTrve39/ZRVqxcrmsh4cHPT8/KxaLLU7D4vG4tre3A04XDrFY7NMOUiQSUSKRYDdpxarVqk5OTtRoNFQsFjUYDNRutwM5LafMwCjdblej0Uij0ehTSZzzB/D/7OLiQtPpVK7rajwe6/j4WC8vL4E8YYXZn12CbDa7NO90Orq+vl5/IOAb0um0PM9TvV6X67qybVutVkuXl5drz/Jjzh0AAAAYjGUDAABgNMoMAAAwGmUGAAAYjTIDAACMRpkBAABGo8wAAACjUWYAAIDRKDMAAMBolBkAAGA0ygwAADAaZQYAABiNMgMAAIz2C/10FgXHwgt5AAAAAElFTkSuQmCC"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 22
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.141323Z",
+     "start_time": "2025-03-26T10:33:54.136808Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "linReg = LinearRegression(fit_intercept=True)\n",
+    "linReg.fit(XtrainScaled, Ytrain)\n",
+    "print(linReg.coef_)\n",
+    "print(coefs_ridge[0])\n",
+    "coefs_ridge = np.array(coefs_ridge)"
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[-212.17552979  307.84554012   70.19893491  -33.94121908  -61.98261284\n",
+      "   80.93907097   87.9354101  -854.87222296  301.36091121  -32.55986525\n",
+      "  575.96472518  276.24716079 -147.21083025   92.98658147   49.1730284\n",
+      "   -8.23077394]\n",
+      "[-212.18873763  307.85651187   70.19704929  -33.94181179  -61.97778652\n",
+      "   80.94031337   87.91930611 -854.70162148  301.23727914  -32.56030861\n",
+      "  575.95219431  276.23085108 -147.21581673   92.98728123   49.16991958\n",
+      "   -8.231394  ]\n"
+     ]
+    }
+   ],
+   "execution_count": 23
   },
   {
    "cell_type": "markdown",
@@ -1300,26 +1591,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 114,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "((16, 50), (50, 16))"
-      ]
-     },
-     "execution_count": 114,
-     "metadata": {},
-     "output_type": "execute_result"
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.178048Z",
+     "start_time": "2025-03-26T10:33:54.165251Z"
     }
-   ],
+   },
    "source": [
     "from sklearn.linear_model import lasso_path\n",
     "\n",
     "alphas_lasso, coefs_lasso, _ = lasso_path(XtrainScaled, Ytrain, n_alphas=50)\n",
-    "coefs_lasso.shape, coefs_ridge.shape"
-   ]
+    "coefs_lasso.shape, coefs_lasso.shape"
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "((16, 50), (16, 50))"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 24
   },
   {
    "cell_type": "markdown",
@@ -1332,61 +1628,81 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 115,
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.259091Z",
+     "start_time": "2025-03-26T10:33:54.196219Z"
+    }
+   },
+   "source": [
+    "coefs_lasso = coefs_lasso.T\n",
+    "plt.plot(np.log10(alphas_lasso), coefs_lasso)\n",
+    "plt.show()"
+   ],
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
-      ]
+      ],
+      "image/png": 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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "source": [
-    "coefs_lasso = coefs_lasso.T\n",
-    "plt.plot(np.log10(alphas_lasso), coefs_lasso)\n",
-    "plt.show()"
-   ]
+   "execution_count": 25
   },
   {
    "cell_type": "code",
-   "execution_count": 116,
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.349032Z",
+     "start_time": "2025-03-26T10:33:54.282613Z"
+    }
+   },
+   "source": [
+    "#the values of alphas chosen by defaults are also on a logarithmic scale\n",
+    "plt.plot(np.log10(alphas_lasso), '.')"
+   ],
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1693d5520>]"
+       "[<matplotlib.lines.Line2D at 0x1687627d0>]"
       ]
      },
-     "execution_count": 116,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
-      ]
+      ],
+      "image/png": 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V6zWhUEiBQCD+KCkpsWKpAK4QlWoA6bJVeJEkny+xrmAYRq/HL6utrVUkEok/zp49a/oaAVw5KtUA0mWrj42KiorU0dGRcKyzs1NDhgzRqFGjer3G7/fL7/dbsTwAGXC5Uv31AEOlGsBA2Oqdl4qKCtXX1ycc27dvn8rLy3uddwHgPFSqAaTL1HdePv30U73zzjvx562trTp+/LhGjhypsWPHqra2Vu3t7dq6daskaenSpVq3bp1qamq0ZMkSNTU1afPmzXrllVfMXCYAi1GpBpAOU8NLc3Oz5s6dG39eU1MjSVq8eLFeeOEFhcNhtbW1xV8vLS3Vnj179Mgjj+i5555TcXGx1q5dS00acCHuUA3gSvmMyxOxLhGNRhUIBBSJRJSXl5ft5QC4QtSpAW8ZyO9vW828AIBEnRpAcoQXALZDnRpAMoQXALbDHaoBJEN4AWA71KkBJGOrL6kDgMuoUwPoC+EFgG1RpwbQG8ILAMeiTg14EzMvAByJOjXgXYQXAI5EnRrwLsILAEeiTg14F+EFgCNRpwa8i4FdAI5FnRrwJsILAEejTg14D+EFgKtRpwbch5kXAK5FnRpwJ8ILANeiTg24E+EFgGtRpwbcifACwLWoUwPuxMAuAFejTg24D+EFgOtRpwbchfACwPOoUwPOwswLAE+jTg04D+EFgKdRpwach/ACwNOoUwPOQ3gB4GnUqQHnYWAXgOcNpE5NKwnIPsILACi1OjWtJMAe+NgIAFJAKwmwD8ILAKSAVhJgH4QXAEgBrSTAPggvAJACWkmAfTCwCwAp4iaPgD0QXgBgALjJI5B9hBcAyCDq1ID5mHkBgAyhTg1Yg/ACABlCnRqwBuEFADKEOjVgDcILAGQIdWrAGgzsAkAGUacGzEd4AYAMo04NmIvwAgAWo04NpIeZFwCwEHVqIH2EFwCwEHVqIH2EFwCwEHVqIH2EFwCwEHVqIH2WhJf169ertLRUw4cPV1lZmV5//fU+z21oaJDP5+vxePvtt61YKgCYbuH0sTr06Fy9smSmDj06l2FdYIBMbxtt375dK1eu1Pr163XzzTfr97//vaqrq/XWW29p7Ni+/w97+vRp5eXlxZ+PHj3a7KUCgGWoUwNXzmcYhtH/aVduxowZuvHGG7Vhw4b4scmTJ2vBggUKhUI9zm9oaNDcuXP18ccf66qrrhrwz4tGowoEAopEIgnhBwCchDo1vGYgv79N/diou7tbx44dU1VVVcLxqqoqHT58OOm1N9xwg4LBoCorK3XgwIE+z4vFYopGowkPAHAy6tRAcqaGl66uLl26dEmFhYUJxwsLC9XR0dHrNcFgUJs2bVJdXZ127NihSZMmqbKyUgcPHuz1/FAopEAgEH+UlJRk/O8BAFaiTg0kZ8k37Pp8ib1AwzB6HLts0qRJmjRpUvx5RUWFzp49q2eeeUZz5szpcX5tba1qamriz6PRKAEGgKNdrlN/PcBQpwb+w9R3XvLz8zV48OAe77J0dnb2eDcmmZkzZ+rMmTO9vub3+5WXl5fwAAAno04NJGfqOy/Dhg1TWVmZ6uvrdc8998SP19fX6+677075z2lpaVEwGDRjiQBgS9ydGuib6R8b1dTUaNGiRSovL1dFRYU2bdqktrY2LV26VNJXH/u0t7dr69atkqQ1a9Zo/PjxmjJlirq7u7Vt2zbV1dWprq7O7KUCgK1QpwZ6Z3p4WbhwoT766CM9/fTTCofDmjp1qvbs2aNx48ZJksLhsNra2uLnd3d3a9WqVWpvb1dOTo6mTJmi3bt3a968eWYvFQAchTo1vMr073mxGt/zAsALwpELunn1/h5DvYcencs7MHAk23zPCwDAHNSp4WWEFwBwIO5ODS8jvACAA1GnhpdZ8iV1AIDMo04NryK8AICDpVKnlqhUw10ILwDgclSq4TbMvACAi3GHargR4QUAXIxKNdyI8AIALkalGm5EeAEAF6NSDTdiYBcAXI5KNdyG8AIAHsAdquEmhBcAAHVqOAozLwDgcdSp4TSEFwDwOOrUcBrCCwB4HHVqOA3hBQA8jjo1nIaBXQBAynVqGkmwA8ILAEBS/3VqGkmwCz42AgD0i0YS7ITwAgDoF40k2AnhBQDQLxpJsBPCCwCgXzSSYCcM7AIAUsINHmEXhBcAQMq4wSPsgPACAMgY6tSwAjMvAICMoE4NqxBeAAAZQZ0aViG8AAAygjo1rEJ4AQBkBHVqWIWBXQBAxlCnhhUILwCAjEqlTi1RqcaVI7wAACxHpRrpYOYFAGApKtVIF+EFAGApKtVIF+EFAGApKtVIF+EFAGApKtVIFwO7AADLUalGOggvAICs4A7VuFKEFwCALVGnRl+YeQEA2A51aiRDeAEA2A51aiRDeAEA2A51aiRDeAEA2A51aiTDwC4AwJaoU6Mvlrzzsn79epWWlmr48OEqKyvT66+/nvT8xsZGlZWVafjw4ZowYYI2btxoxTIBADYTDOSo4upRSYNLOHJBh//VxTCvh5geXrZv366VK1fq8ccfV0tLi2bPnq3q6mq1tbX1en5ra6vmzZun2bNnq6WlRY899pgeeugh1dXVmb1UAIDDbD/apptX79cDz7+hm1fv1/ajvf9ugbv4DMMw+j/tys2YMUM33nijNmzYED82efJkLViwQKFQqMf5v/jFL7Rr1y6dOnUqfmzp0qX65z//qaampn5/XjQaVSAQUCQSUV5eXmb+EgAA2wlHLujm1fsTWkmDfT4denQuHzE50EB+f5v6zkt3d7eOHTumqqqqhONVVVU6fPhwr9c0NTX1OP+OO+5Qc3Ozvvjiix7nx2IxRaPRhAcAwP2oU3uXqeGlq6tLly5dUmFhYcLxwsJCdXR09HpNR0dHr+dfvHhRXV1dPc4PhUIKBALxR0lJSeb+AgAA26JO7V2WDOz6fIn/ugzD6HGsv/N7Oy5JtbW1ikQi8cfZs2czsGIAgN1Rp/YuU6vS+fn5Gjx4cI93WTo7O3u8u3JZUVFRr+cPGTJEo0aN6nG+3++X3+/P3KIBAI5BndqbTH3nZdiwYSorK1N9fX3C8fr6es2aNavXayoqKnqcv2/fPpWXl2vo0KGmrRUA4EzUqb3H9C+pq6mp0aJFi1ReXq6Kigpt2rRJbW1tWrp0qaSvPvZpb2/X1q1bJX3VLFq3bp1qamq0ZMkSNTU1afPmzXrllVfMXioAwIW4O7X7mB5eFi5cqI8++khPP/20wuGwpk6dqj179mjcuHGSpHA4nPCdL6WlpdqzZ48eeeQRPffccyouLtbatWt13333mb1UAIDL9HV36jkTR/MRk4OZ/j0vVuN7XgAAlx3+V5ceeP6NHsdfWTJTFVf3nKNE9tjme14AAMgm6tTuRHgBALgWdWp34q7SAABXo07tPoQXAIDrBQM5/YaWcOSCWrvOqzR/BAHH5ggvAADPo07tLMy8AAA8ra86NV9oZ1+EFwCAp3F3auchvAAAPI06tfMQXgAAnkad2nkY2AUAeN5A6tS0krKP8AIAgFKrU9NKsgc+NgIAIAW0kuyD8AIAQApoJdkH4QUAgBTQSrIPwgsAACmglWQfDOwCAJAibvJoD4QXAAAGgJs8Zh/hBQCADKJObT5mXgAAyBDq1NYgvAAAkCHUqa1BeAEAIEOoU1uD8AIAQIZQp7YGA7sAAGQQdWrzEV4AAMgw6tTmIrwAAGAx6tTpYeYFAAALUadOH+EFAAALUadOH+EFAAALUadOH+EFAAALUadOHwO7AABYjDp1eggvAABkAXXqK0d4AQDAhqhT942ZFwAAbIY6dXKEFwAAbIY6dXKEFwAAbIY6dXKEFwAAbIY6dXIM7AIAYEPUqftGeAEAwKaoU/eO8AIAgEN5tU7NzAsAAA7k5To14QUAAAfycp2a8AIAgAN5uU5NeAEAwIG8XKdmYBcAAIfyap2a8AIAgIOlUqeW3FWpNvVjo48//liLFi1SIBBQIBDQokWL9MknnyS95sEHH5TP50t4zJw508xlAgDgatuPtunm1fv1wPNv6ObV+7X9aFu2l5QWU8PLAw88oOPHj2vv3r3au3evjh8/rkWLFvV73Z133qlwOBx/7Nmzx8xlAgDgWm6sVJv2sdGpU6e0d+9eHTlyRDNmzJAkPf/886qoqNDp06c1adKkPq/1+/0qKioya2kAAHhGskq1Uz8+Mu2dl6amJgUCgXhwkaSZM2cqEAjo8OHDSa9taGhQQUGBJk6cqCVLlqizs7PPc2OxmKLRaMIDAAB8xY2VatPCS0dHhwoKCnocLygoUEdHR5/XVVdX66WXXtL+/fv129/+VkePHtXtt9+uWCzW6/mhUCg+UxMIBFRSUpKxvwMAAE7nxkr1gD82evLJJ/XUU08lPefo0aOSJJ/P1+M1wzB6PX7ZwoUL4/976tSpKi8v17hx47R7927de++9Pc6vra1VTU1N/Hk0GiXAAADwNW6rVA84vCxfvlz3339/0nPGjx+vEydO6MMPP+zx2r///W8VFham/POCwaDGjRunM2fO9Pq63++X3+9P+c8DAMCL3HSH6gGHl/z8fOXn5/d7XkVFhSKRiP7+97/rpptukiS98cYbikQimjVrVso/76OPPtLZs2cVDAYHulQAAJAiJ92h2rSZl8mTJ+vOO+/UkiVLdOTIER05ckRLlizRXXfdldA0uvbaa7Vz505J0qeffqpVq1apqalJ7733nhoaGjR//nzl5+frnnvuMWupAAB4mtPq1KZ+z8tLL72k6667TlVVVaqqqtL111+vF198MeGc06dPKxKJSJIGDx6skydP6u6779bEiRO1ePFiTZw4UU1NTcrNzTVzqQAAeJbT7lBt6u0BRo4cqW3btiU9xzD+s1s5OTn661//auaSAADAf7lcp/56gLFznZq7SgMA4HFOq1NzY0YAAJByndoOjSTCCwAAkNR/ndoujSQ+NgIAAP2yUyOJ8AIAAPplp0YS4QUAAPTLTjd4JLwAAIB+2amRxMAuAABIiV1u8Eh4AQAAKUvlBo9m42MjAADgKIQXAADgKIQXAADgKIQXAADgKIQXAADgKIQXAADgKIQXAADgKIQXAADgKIQXAADgKIQXAADgKIQXAADgKK67t5FhGJKkaDSa5ZUAAIBUXf69ffn3eDKuCy/nzp2TJJWUlGR5JQAAYKDOnTunQCCQ9ByfkUrEcZAvv/xSH3zwgXJzc+Xz+TL6Z0ejUZWUlOjs2bPKy8vL6J+Nnthva7Hf1mK/rcV+W+tK9tswDJ07d07FxcUaNCj5VIvr3nkZNGiQxowZY+rPyMvL4x+/hdhva7Hf1mK/rcV+W2ug+93fOy6XMbALAAAchfACAAAchfAyAH6/X0888YT8fn+2l+IJ7Le12G9rsd/WYr+tZfZ+u25gFwAAuBvvvAAAAEchvAAAAEchvAAAAEchvAAAAEchvAAAAEchvKRo/fr1Ki0t1fDhw1VWVqbXX38920tyjYMHD2r+/PkqLi6Wz+fTa6+9lvC6YRh68sknVVxcrJycHN1222168803s7NYhwuFQpo+fbpyc3NVUFCgBQsW6PTp0wnnsN+Zs2HDBl1//fXxbxmtqKjQX/7yl/jr7LW5QqGQfD6fVq5cGT/GnmfOk08+KZ/Pl/AoKiqKv27mXhNeUrB9+3atXLlSjz/+uFpaWjR79mxVV1erra0t20tzhfPnz2vatGlat25dr6//5je/0bPPPqt169bp6NGjKioq0ve+9734TTiRusbGRi1btkxHjhxRfX29Ll68qKqqKp0/fz5+DvudOWPGjNHq1avV3Nys5uZm3X777br77rvj/wFnr81z9OhRbdq0Sddff33CcfY8s6ZMmaJwOBx/nDx5Mv6aqXttoF833XSTsXTp0oRj1157rfHoo49maUXuJcnYuXNn/PmXX35pFBUVGatXr44f+/zzz41AIGBs3LgxCyt0l87OTkOS0djYaBgG+22Fb37zm8Yf/vAH9tpE586dM6655hqjvr7euPXWW42HH37YMAz+fWfaE088YUybNq3X18zea9556Ud3d7eOHTumqqqqhONVVVU6fPhwllblHa2trero6EjYf7/fr1tvvZX9z4BIJCJJGjlypCT220yXLl3Sq6++qvPnz6uiooK9NtGyZcv0/e9/X9/97ncTjrPnmXfmzBkVFxertLRU999/v959911J5u+16+4qnWldXV26dOmSCgsLE44XFhaqo6MjS6vyjst73Nv+v//++9lYkmsYhqGamhrdcsstmjp1qiT22wwnT55URUWFPv/8c33jG9/Qzp079e1vfzv+H3D2OrNeffVV/eMf/9DRo0d7vMa/78yaMWOGtm7dqokTJ+rDDz/Ur371K82aNUtvvvmm6XtNeEmRz+dLeG4YRo9jMA/7n3nLly/XiRMndOjQoR6vsd+ZM2nSJB0/flyffPKJ6urqtHjxYjU2NsZfZ68z5+zZs3r44Ye1b98+DR8+vM/z2PPMqK6ujv/v6667ThUVFbr66qv1pz/9STNnzpRk3l7zsVE/8vPzNXjw4B7vsnR2dvZIlMi8y5Pr7H9mrVixQrt27dKBAwc0ZsyY+HH2O/OGDRumb33rWyovL1coFNK0adP0u9/9jr02wbFjx9TZ2amysjINGTJEQ4YMUWNjo9auXashQ4bE95U9N8eIESN03XXX6cyZM6b/+ya89GPYsGEqKytTfX19wvH6+nrNmjUrS6vyjtLSUhUVFSXsf3d3txobG9n/K2AYhpYvX64dO3Zo//79Ki0tTXid/TafYRiKxWLstQkqKyt18uRJHT9+PP4oLy/XD3/4Qx0/flwTJkxgz00Ui8V06tQpBYNB8/99pz3y6wGvvvqqMXToUGPz5s3GW2+9ZaxcudIYMWKE8d5772V7aa5w7tw5o6WlxWhpaTEkGc8++6zR0tJivP/++4ZhGMbq1auNQCBg7Nixwzh58qTxgx/8wAgGg0Y0Gs3yyp3npz/9qREIBIyGhgYjHA7HH5999ln8HPY7c2pra42DBw8ara2txokTJ4zHHnvMGDRokLFv3z7DMNhrK3y9bWQY7Hkm/fznPzcaGhqMd9991zhy5Ihx1113Gbm5ufHfjWbuNeElRc8995wxbtw4Y9iwYcaNN94Yr5YifQcOHDAk9XgsXrzYMIyvKndPPPGEUVRUZPj9fmPOnDnGyZMns7toh+ptnyUZW7ZsiZ/DfmfOT37yk/h/N0aPHm1UVlbGg4thsNdW+O/wwp5nzsKFC41gMGgMHTrUKC4uNu69917jzTffjL9u5l77DMMw0n//BgAAwBrMvAAAAEchvAAAAEchvAAAAEchvAAAAEchvAAAAEchvAAAAEchvAAAAEchvAAAAEchvAAAAEchvAAAAEchvAAAAEf5P2x7u5PfDg7cAAAAAElFTkSuQmCC"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "source": [
-    "#the values of alphas chosen by defaults are also on a logarithmic scale\n",
-    "plt.plot(np.log10(alphas_lasso), '.')"
-   ]
+   "execution_count": 26
   },
   {
    "cell_type": "code",
-   "execution_count": 117,
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.502618Z",
+     "start_time": "2025-03-26T10:33:54.416713Z"
+    }
+   },
+   "source": [
+    "fig, ax = plt.subplots(figsize=(8, 6))\n",
+    "ax.plot(np.log10(alphas_lasso), coefs_lasso)\n",
+    "ax.set_xlabel('log10(alpha)')\n",
+    "ax.set_ylabel('Lasso coefficients')"
+   ],
    "outputs": [
     {
      "data": {
@@ -1394,27 +1710,22 @@
        "Text(0, 0.5, 'Lasso coefficients')"
       ]
      },
-     "execution_count": 117,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 800x600 with 1 Axes>"
-      ]
+      ],
+      "image/png": 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"
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
-   "source": [
-    "fig, ax = plt.subplots(figsize=(8, 6))\n",
-    "ax.plot(np.log10(alphas_lasso), coefs_lasso)\n",
-    "ax.set_xlabel('log10(alpha)')\n",
-    "ax.set_ylabel('Lasso coefficients')"
-   ]
+   "execution_count": 27
   },
   {
    "cell_type": "markdown",
@@ -1436,33 +1747,68 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.530858Z",
+     "start_time": "2025-03-26T10:33:54.527857Z"
+    }
+   },
    "source": [
-    "# Hint for Ex. 8\n",
-    "\n",
     "ind = np.array([[0, 1, 1], [0, 1, 1], [0, 1, 0]])\n",
     "\n",
     "print(\"1.\\n\", ind)\n",
     "print(\"2.\\n\", ind == 0)\n",
     "print(\"3. Le nombre de 0 de chaque colonne est :\\n \", (ind == 0).sum(axis=0))\n",
     "print(\"4. Le nombre de 0 de chaque ligne est : \\n\", (ind == 0).sum(axis=1))\n"
-   ]
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1.\n",
+      " [[0 1 1]\n",
+      " [0 1 1]\n",
+      " [0 1 0]]\n",
+      "2.\n",
+      " [[ True False False]\n",
+      " [ True False False]\n",
+      " [ True False  True]]\n",
+      "3. Le nombre de 0 de chaque colonne est :\n",
+      "  [3 0 1]\n",
+      "4. Le nombre de 0 de chaque ligne est : \n",
+      " [1 1 2]\n"
+     ]
+    }
+   ],
+   "execution_count": 28
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.614964Z",
+     "start_time": "2025-03-26T10:33:54.561469Z"
+    }
+   },
    "source": [
-    "# Answer for Ex. 8\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n"
-   ]
+    "nb_lasso = np.array(coefs_lasso == 0).sum(axis=1)\n",
+    "plt.step(np.log10(alphas_lasso), nb_lasso)\n",
+    "plt.show()"
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ],
+      "image/png": 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vdhkAupmAz6OAz/VvSQC6Add/tbehoUHnndfysB6Ph1/tBQAAbXL9x5CZM2fqiSee0JAhQzR69GhVVVVp+fLluuOOO9zuCgAApAHXw8hTTz2lhx9+WHfddZdqa2uVk5OjefPm6ZFHHnG7KwAAkAZcDyOZmZlasWJFu7/KCwAA8Fm8mwYAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGCV6y/KA5C6jDFqbI7ZLiOuoSl1agFgD2EE6CGMMZpdXK7KQ3W2SwGAFrhNA/QQjc2xlA0iebl9lOH12C4DgCVcGQF6oIqlUxXwpc7JP8PrkeM4tssAYAlhBOiBAj6PAj7++QNIDdymAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVUkJIx9++KG+/e1vq1+/fgoEArrssstUWVmZjK4AAEA318vtA9bV1enqq6/WlClT9Oc//1nZ2dl67733dMEFF7jdFQAASAOuh5Fly5YpFArpueeei68bOnSo290AAIA04fptmo0bNyovL0/f+MY3lJ2drcsvv1zPPPNMu+2j0agikUiLDwAA6DlcDyPvv/++Vq1apeHDh2vLli268847tXDhQv32t79ts304HFYwGIx/QqGQ2yUBAIAU5hhjjJsH9Pl8ysvL086dO+PrFi5cqN27d6u8vLxV+2g0qmg0Gl+ORCIKhUKqr69XVlaWm6UBPVpD00mNemSLJGnf49MV8Ll+lxZADxaJRBQMBjt1/nb9ysigQYM0atSoFusuvvhiHT58uM32fr9fWVlZLT4AAKDncD2MXH311dq/f3+LdQcOHFBubq7bXQEAgDTgehi59957tWvXLj355JM6ePCg1qxZo9WrV2v+/PludwUAANKA62Fk/PjxWr9+vV566SWNGTNGP/nJT7RixQrNnTvX7a4AAEAaSMoTbDNmzNCMGTOScWgAAJBmeDcNAACwijACAACsIowAAACrCCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArCKMAAAAqwgjAADAqqS8KA9Axxlj1NgcS3o/DU3J7wMAOoMwAlhkjNHs4nJVHqqzXQoAWMNtGsCixuZYlweRvNw+yvB6urRPADgTrowAKaJi6VQFfMkPCRlejxzHSXo/ANBRhBEgRQR8HgV8/JME0PNwmwYAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYlPYyEw2E5jqNFixYluysAANANJTWM7N69W6tXr9all16azG4AAEA31itZBz5+/Ljmzp2rZ555Rj/96U+T1Q1ghTFGjc2xcz5OQ9O5HwMAurukhZH58+frhhtu0NSpU88YRqLRqKLRaHw5EokkqyTAFcYYzS4uV+WhOtulAEBaSEoYefnll7Vnzx7t3r37rG3D4bAee+yxZJQBJEVjc8z1IJKX20cZXo+rxwSA7sL1MHLkyBHdc8892rp1q3r37n3W9kuWLFFRUVF8ORKJKBQKuV0WkBQVS6cq4Dv3EJHh9chxHBcqAoDux/UwUllZqdraWo0bNy6+LhaLqaysTCtXrlQ0GpXH879v3n6/X36/3+0ygC4R8HkU8CXtbicA9Aiufxe97rrr9Ne//rXFuttvv10jR47Ugw8+2CKIAAAAuB5GMjMzNWbMmBbrzj//fPXr16/VegAAAP4CKwAAsKpLbnaXlpZ2RTcAAKAb4soIAACwijACAACsIowAAACrCCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArCKMAAAAqwgjAADAqi55UR5wLowxamyOuXa8DK9HjuN0ur+GJvdqAQAQRpDijDGaXVyuykN1rh0zL7eP/t+dE9sMJMnoDwBwZtymQUprbI65HgwqDtW1e+Ujkf7ycvsow+txszQA6JG4MoJuo2LpVAV8nT/5NzTFlPfT/3Otv7Pd7gEAdAxhBN1GwOdRwNd1U7ar+wOAnorbNAAAwCrCCAAAsIowAgAArCKMAAAAqwgjAADAKsIIAACwijACAACsIowAAACrCCMAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsMr1MBIOhzV+/HhlZmYqOztbN910k/bv3+92NwAAIE24Hka2b9+u+fPna9euXSopKdHJkyc1bdo0nThxwu2uAABAGujl9gE3b97cYvm5555Tdna2Kisrde2117rdHbo5Y4wam2Ptbm9oan/buWjvuMnqDwDQPtfDyOfV19dLkvr27dvm9mg0qmg0Gl+ORCLJLgkpwhij2cXlqjxU1+V95/30/7q8TwBA25L6AKsxRkVFRZo0aZLGjBnTZptwOKxgMBj/hEKhZJaEFNLYHOtwEMnL7aMMr+ec+svwepSX26fL+gMAdIxjjDHJOvj8+fO1adMm7dixQ4MHD26zTVtXRkKhkOrr65WVlZWs0pACGppOatQjWyRJFUunKuBr/+Sf4fXIcZxz7vNst4Xc7g8AeopIJKJgMNip83fSbtMsWLBAGzduVFlZWbtBRJL8fr/8fn+yykA3EfB5FPAl/a6hHMfpkn4AAB3n+ndlY4wWLFig9evXq7S0VMOGDXO7CwAAkEZcDyPz58/XmjVr9Mc//lGZmZmqqamRJAWDQWVkZLjdHQAA6OZcf4B11apVqq+v1+TJkzVo0KD4Z+3atW53BQAA0kBSbtMAAAB0FO+mAQAAVhFGAACAVYQRAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWOX6i/LwP8YYNTbHbJeRshqaGBsAAGEkaYwxml1crspDdbZLAQAgpXGbJkkam2MEkQ7Ky+2jDK/HdhkAAEu4MtIFKpZOVcDHybY9GV6PHMexXQYAwBLCSBcI+DwK+BhqAADawm0aAABgFWEEAABYRRgBAABWEUYAAIBVhBEAAGAVYQQAAFhFGAEAAFYRRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGAACAVYQRAABgFWEEAABYlbQw8vTTT2vYsGHq3bu3xo0bpzfeeCNZXQEAgG4sKWFk7dq1WrRokR566CFVVVXpmmuuUX5+vg4fPpyM7gAAQDfWKxkHXb58ub73ve/p+9//viRpxYoV2rJli1atWqVwOJyMLs/KGKPG5liX9dfQ1HV9AQDQnbkeRpqamlRZWanFixe3WD9t2jTt3LmzVftoNKpoNBpfjkQibpckSWpsjmnUI1uScmwAANB5rt+m+fjjjxWLxTRgwIAW6wcMGKCamppW7cPhsILBYPwTCoXcLsmqvNw+yvB6bJcBAEDKSsptGklyHKfFsjGm1TpJWrJkiYqKiuLLkUgkKYEkw+vRvsenu37cjvTb1tcNAAA+5XoY6d+/vzweT6urILW1ta2ulkiS3++X3+93u4xWHMdRwJe07AUAADrJ9ds0Pp9P48aNU0lJSYv1JSUluuqqq9zuDgAAdHNJuVRQVFSkgoIC5eXlaeLEiVq9erUOHz6sO++8MxndAQCAbiwpYeTWW2/VJ598oscff1wfffSRxowZo9dee025ubnJ6A4AAHRjjjHG2C7isyKRiILBoOrr65WVlWW7HAAA0AHncv7m3TQAAMAqwggAALCKMAIAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArCKMAAAAqwgjAADAqpR7je3pPwgbiUQsVwIAADrq9Hm7M3/YPeXCyLFjxyRJoVDIciUAACBRx44dUzAYTGiflHs3zalTp3T06FFlZmbKcRzb5bQQiUQUCoV05MgR3ptzFoxVxzFWHcdYJYbx6jjGquPaGytjjI4dO6acnBydd15iT4Gk3JWR8847T4MHD7ZdxhllZWUxWTuIseo4xqrjGKvEMF4dx1h1XFtjlegVkdN4gBUAAFhFGAEAAFYRRhLg9/v14x//WH6/33YpKY+x6jjGquMYq8QwXh3HWHVcMsYq5R5gBQAAPQtXRgAAgFWEEQAAYBVhBAAAWEUYAQAAVhFGzqKurk4FBQUKBoMKBoMqKCjQv//97zPu893vfleO47T4TJgwoWsK7kJPP/20hg0bpt69e2vcuHF64403zth++/btGjdunHr37q0LL7xQxcXFXVSpfYmMVWlpaav54ziO3nnnnS6s2I6ysjLNnDlTOTk5chxHGzZsOOs+PXVeJTpWPXlehcNhjR8/XpmZmcrOztZNN92k/fv3n3W/nji3OjNWbswtwshZ3Hbbbdq7d682b96szZs3a+/evSooKDjrftdff70++uij+Oe1117rgmq7ztq1a7Vo0SI99NBDqqqq0jXXXKP8/HwdPny4zfbV1dX6+te/rmuuuUZVVVX60Y9+pIULF2rdunVdXHnXS3SsTtu/f3+LOTR8+PAuqtieEydOaOzYsVq5cmWH2vfkeZXoWJ3WE+fV9u3bNX/+fO3atUslJSU6efKkpk2bphMnTrS7T0+dW50Zq9POaW4ZtGvfvn1Gktm1a1d8XXl5uZFk3nnnnXb3KywsNLNmzeqCCu254oorzJ133tli3ciRI83ixYvbbP/AAw+YkSNHtlg3b948M2HChKTVmCoSHatt27YZSaaurq4Lqktdksz69evP2KYnz6vP6shYMa/+p7a21kgy27dvb7cNc+tTHRkrN+YWV0bOoLy8XMFgUFdeeWV83YQJExQMBrVz584z7ltaWqrs7GxddNFF+sEPfqDa2tpkl9tlmpqaVFlZqWnTprVYP23atHbHpby8vFX76dOnq6KiQs3NzUmr1bbOjNVpl19+uQYNGqTrrrtO27ZtS2aZ3VZPnVfngnkl1dfXS5L69u3bbhvm1qc6MlanncvcIoycQU1NjbKzs1utz87OVk1NTbv75efn6/e//71ef/11/fKXv9Tu3bv11a9+VdFoNJnldpmPP/5YsVhMAwYMaLF+wIAB7Y5LTU1Nm+1Pnjypjz/+OGm12taZsRo0aJBWr16tdevW6ZVXXtGIESN03XXXqaysrCtK7lZ66rzqDObVp4wxKioq0qRJkzRmzJh22zG3Oj5WbsytlHtrb1d49NFH9dhjj52xze7duyVJjuO02maMaXP9abfeemv8v8eMGaO8vDzl5uZq06ZNuuWWWzpZder5/BicbVzaat/W+nSUyFiNGDFCI0aMiC9PnDhRR44c0S9+8Qtde+21Sa2zO+rJ8yoRzKtP3X333Xr77be1Y8eOs7bt6XOro2PlxtzqkWHk7rvv1pw5c87YZujQoXr77bf1z3/+s9W2f/3rX60S85kMGjRIubm5evfddxOuNRX1799fHo+n1U/2tbW17Y7LwIED22zfq1cv9evXL2m12taZsWrLhAkT9OKLL7pdXrfXU+eVW3ravFqwYIE2btyosrIyDR48+Ixte/rcSmSs2pLo3OqRYaR///7q37//WdtNnDhR9fX1+stf/qIrrrhCkvTmm2+qvr5eV111VYf7++STT3TkyBENGjSo0zWnEp/Pp3HjxqmkpEQ333xzfH1JSYlmzZrV5j4TJ07Uq6++2mLd1q1blZeXJ6/Xm9R6berMWLWlqqoqbeaPm3rqvHJLT5lXxhgtWLBA69evV2lpqYYNG3bWfXrq3OrMWLUl4bnV6Udfe4jrr7/eXHrppaa8vNyUl5ebSy65xMyYMaNFmxEjRphXXnnFGGPMsWPHzH333Wd27txpqqurzbZt28zEiRPNF7/4RROJRGx8CUnx8ssvG6/Xa5599lmzb98+s2jRInP++eebDz74wBhjzOLFi01BQUG8/fvvv28CgYC59957zb59+8yzzz5rvF6v+cMf/mDrS+gyiY7Vr371K7N+/Xpz4MAB87e//c0sXrzYSDLr1q2z9SV0mWPHjpmqqipTVVVlJJnly5ebqqoqc+jQIWMM8+qzEh2rnjyvfvjDH5pgMGhKS0vNRx99FP80NDTE2zC3PtWZsXJjbhFGzuKTTz4xc+fONZmZmSYzM9PMnTu31a8vSTLPPfecMcaYhoYGM23aNPOFL3zBeL1eM2TIEFNYWGgOHz7c9cUn2W9+8xuTm5trfD6f+fKXv9ziV78KCwvNV77ylRbtS0tLzeWXX258Pp8ZOnSoWbVqVRdXbE8iY7Vs2TLzpS99yfTu3dv06dPHTJo0yWzatMlC1V3v9K8Ifv5TWFhojGFefVaiY9WT51Vb4/TZ79vGMLdO68xYuTG3nP92DgAAYAW/2gsAAKwijAAAAKsIIwAAwCrCCAAAsIowAgAArCKMAAAAqwgjAADAKsIIAACwijACAACsIowAAACrCCMAAMAqwggAALDq/wNxSHx0sgZNiQAAAABJRU5ErkJggg=="
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 29
   },
   {
    "cell_type": "markdown",
@@ -1475,32 +1821,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.687251Z",
+     "start_time": "2025-03-26T10:33:54.639809Z"
+    }
+   },
    "source": [
-    "# Answer for Ex. 9\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
+    "nb_ridge = np.array(coefs_ridge == 0).sum(axis=1)\n",
+    "plt.plot(np.log10(alphas), nb_ridge)\n",
+    "plt.show()"
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ],
+      "image/png": "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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 30
   },
   {
    "cell_type": "markdown",
@@ -1531,14 +1875,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.710558Z",
+     "start_time": "2025-03-26T10:33:54.707998Z"
+    }
+   },
+   "source": "alphas = np.logspace(-4, 6, 50)",
    "outputs": [],
-   "source": [
-    "from sklearn.linear_model import RidgeCV, LassoCV\n",
-    "\n",
-    "alpha_s = np.logspace(-4, 6, 50)"
-   ]
+   "execution_count": 31
   },
   {
    "cell_type": "markdown",
@@ -1554,17 +1899,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.738765Z",
+     "start_time": "2025-03-26T10:33:54.732482Z"
+    }
+   },
    "source": [
-    "# Answer for Ex. 10\n",
+    "from sklearn.linear_model import RidgeCV\n",
     "\n",
+    "ridgeCV = RidgeCV(alphas=alphas, store_cv_values=True)\n",
+    "ridgeCV.fit(XtrainScaled, Ytrain)\n",
     "\n",
-    "\n",
-    "\n",
-    "\n"
-   ]
+    "print(ridgeCV.alphas)"
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1.00000000e-04 1.59985872e-04 2.55954792e-04 4.09491506e-04\n",
+      " 6.55128557e-04 1.04811313e-03 1.67683294e-03 2.68269580e-03\n",
+      " 4.29193426e-03 6.86648845e-03 1.09854114e-02 1.75751062e-02\n",
+      " 2.81176870e-02 4.49843267e-02 7.19685673e-02 1.15139540e-01\n",
+      " 1.84206997e-01 2.94705170e-01 4.71486636e-01 7.54312006e-01\n",
+      " 1.20679264e+00 1.93069773e+00 3.08884360e+00 4.94171336e+00\n",
+      " 7.90604321e+00 1.26485522e+01 2.02358965e+01 3.23745754e+01\n",
+      " 5.17947468e+01 8.28642773e+01 1.32571137e+02 2.12095089e+02\n",
+      " 3.39322177e+02 5.42867544e+02 8.68511374e+02 1.38949549e+03\n",
+      " 2.22299648e+03 3.55648031e+03 5.68986603e+03 9.10298178e+03\n",
+      " 1.45634848e+04 2.32995181e+04 3.72759372e+04 5.96362332e+04\n",
+      " 9.54095476e+04 1.52641797e+05 2.44205309e+05 3.90693994e+05\n",
+      " 6.25055193e+05 1.00000000e+06]\n"
+     ]
+    }
+   ],
+   "execution_count": 32
   },
   {
    "cell_type": "markdown",
@@ -1575,29 +1945,69 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.765343Z",
+     "start_time": "2025-03-26T10:33:54.762563Z"
+    }
+   },
    "source": [
-    "# Hint for Exercise 11 : \n",
-    "\n",
     "ind2 = np.array([[1, 2, 3], [4, 5, 6]])\n",
     "\n",
     "print(\"1\\n\", ind2.shape)\n",
     "print(\"2\\n\", ind2.mean(axis=0))\n",
-    "print(\"3\\n\", ind2.mean(axis=1))\n"
-   ]
+    "print(\"3\\n\", ind2.mean(axis=1))"
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1\n",
+      " (2, 3)\n",
+      "2\n",
+      " [2.5 3.5 4.5]\n",
+      "3\n",
+      " [2. 5.]\n"
+     ]
+    }
+   ],
+   "execution_count": 33
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.804392Z",
+     "start_time": "2025-03-26T10:33:54.799816Z"
+    }
+   },
    "source": [
-    "# Answer for Ex. 11\n",
-    "\n",
-    "\n"
-   ]
+    "alpha_score = np.array(ridgeCV.cv_values_).mean(axis=0)\n",
+    "print(alpha_score)"
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[113118.88744001 113116.69286852 113113.18556678 113107.58383637\n",
+      " 113098.64598224 113084.40808822 113061.78529489 113025.98539916\n",
+      " 112969.69566328 112882.07537387 112747.79805364 112546.85329372\n",
+      " 112256.56479104 111857.83289663 111346.43126402 110745.49596347\n",
+      " 110109.29600567 109509.30347683 109005.33407911 108617.71404706\n",
+      " 108320.48014704 108060.67952768 107780.11849629 107417.39480475\n",
+      " 106905.47799251 106192.37025218 105279.10514885 104241.95728675\n",
+      " 103226.43288847 102432.84254075 102115.20847976 102611.29155658\n",
+      " 104413.7148642  108209.84634695 114694.63495968 124063.6584143\n",
+      " 135546.04470461 147564.71477358 158507.58752129 167405.12162365\n",
+      " 174048.22918159 178716.25228531 181863.60951865 183928.45859066\n",
+      " 185259.32936241 186107.45677344 186644.07339405 186982.05844378\n",
+      " 187194.33036861 187327.40975748]\n"
+     ]
+    }
+   ],
+   "execution_count": 34
   },
   {
    "cell_type": "markdown",
@@ -1610,17 +2020,55 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.888467Z",
+     "start_time": "2025-03-26T10:33:54.839691Z"
+    }
+   },
    "source": [
-    "# Answer for Exercise 12\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n",
-    "\n"
-   ]
+    "plt.plot(np.log10(alphas), alpha_score)\n",
+    "plt.show()"
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 35
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:54.917915Z",
+     "start_time": "2025-03-26T10:33:54.915253Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "print(\"best alpha for ridge : \", ridgeCV.alpha_)\n",
+    "print(\"ridge coef for the best alpha : \", ridgeCV.coef_)"
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "best alpha for ridge :  132.57113655901108\n",
+      "ridge coef for the best alpha :  [18.60099315 44.83916896 19.65511565 31.2895848  19.53291699 23.82494567\n",
+      " 17.58025351 24.95507189 34.79628953 25.54796552 36.50612186 32.17517034\n",
+      " 17.53213942 56.00516056  0.58648412 -8.49246715]\n"
+     ]
+    }
+   ],
+   "execution_count": 36
   },
   {
    "cell_type": "markdown",
@@ -1635,16 +2083,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:55.011780Z",
+     "start_time": "2025-03-26T10:33:54.966551Z"
+    }
+   },
    "source": [
     "from sklearn.linear_model import LassoCV\n",
     "\n",
     "lassoCV = LassoCV(n_alphas=50)\n",
     "lassoCV.fit(XtrainScaled, Ytrain)\n",
     "lassoCV.mse_path_.shape"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(50, 5)"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 37
   },
   {
    "cell_type": "markdown",
@@ -1659,33 +2123,92 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:55.023571Z",
+     "start_time": "2025-03-26T10:33:55.020025Z"
+    }
+   },
    "source": [
     "alpha_score = lassoCV.mse_path_.mean(axis=1)\n",
     "alpha_score.shape"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(50,)"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 38
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:55.115836Z",
+     "start_time": "2025-03-26T10:33:55.049527Z"
+    }
+   },
    "source": [
     "alphas = lassoCV.alphas_\n",
     "plt.plot(np.log10(alphas), alpha_score)"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x168648310>]"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 39
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:55.145416Z",
+     "start_time": "2025-03-26T10:33:55.142140Z"
+    }
+   },
    "source": [
     "print(\"best alpha for lasso : \", lassoCV.alpha_)\n",
     "print(\"lasso coef for the best alpha : \", lassoCV.coef_)"
-   ]
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "best alpha for lasso :  4.783179587705159\n",
+      "lasso coef for the best alpha :  [-99.92030224 202.5757594   25.01239288   0.          -0.\n",
+      "  32.47945631   0.          -0.           0.          27.91148338\n",
+      " 150.0851833   27.07622842  -0.          86.82862045   0.\n",
+      "  -8.03825832]\n"
+     ]
+    }
+   ],
+   "execution_count": 40
   },
   {
    "cell_type": "markdown",
@@ -1708,10 +2231,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:55.172132Z",
+     "start_time": "2025-03-26T10:33:55.168656Z"
+    }
+   },
+   "source": "XtestScaled = scaler.transform(Xtest)",
    "outputs": [],
-   "source": "XtestScaled = scaler.transform(Xtest)"
+   "execution_count": 41
   },
   {
    "cell_type": "markdown",
@@ -1722,17 +2250,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:33:55.298012Z",
+     "start_time": "2025-03-26T10:33:55.213779Z"
+    }
+   },
    "source": [
     "from sklearn.linear_model import LinearRegression\n",
     "\n",
-    "LinReg = LinearRegression()\n",
-    "LinReg.fit(Xtrain,\n",
+    "linReg = LinearRegression()\n",
+    "linReg.fit(Xtrain,\n",
     "           Ytrain)  # no need to scale for OLS if you just want to predict (unless the solver works best with scaled data)\n",
-    "# the predictions  should not be different with or without standardization (could differ only owing to numerical problems)\n",
-    "hatY_LinReg = LinReg.predict(Xtest)\n",
+    "# the predictions should not be different with or without standardization (could differ only owing to numerical problems)\n",
+    "hatY_LinReg = linReg.predict(Xtest)\n",
     "\n",
     "fig, ax = plt.subplots()\n",
     "ax.scatter(Ytest, hatY_LinReg, s=5)\n",
@@ -1741,7 +2272,30 @@
     "ax.set_ylabel('hatY')\n",
     "ax.set_title('Predicted vs true salaries for OLS estimator')\n",
     "ax.axis('square')"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(-47.125, 2529.625, -84.2876879928325, 2492.4623120071674)"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 42
   },
   {
    "cell_type": "markdown",
@@ -1753,12 +2307,49 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:36:06.843785Z",
+     "start_time": "2025-03-26T10:36:06.753342Z"
+    }
+   },
    "source": [
-    "# Answer for Optional Exercise 1\n"
-   ]
+    "best_ridge = Ridge(fit_intercept=True, alpha=132.57)\n",
+    "best_ridge.fit(Xtrain, Ytrain)\n",
+    "\n",
+    "hatY_ridge = best_ridge.predict(Xtest)\n",
+    "\n",
+    "fig, ax = plt.subplots()\n",
+    "ax.scatter(Ytest, hatY_ridge, s=5)\n",
+    "ax.plot([0, 1], [0, 1], transform=ax.transAxes, ls='--', c='gray')\n",
+    "ax.set_xlabel('Ytest')\n",
+    "ax.set_ylabel('hatY')\n",
+    "ax.set_title('Predicted vs true salaries for Ridge estimator')\n",
+    "ax.axis('square')"
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(-47.125, 2529.625, -66.53302815900629, 2510.2169718409937)"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 54
   },
   {
    "cell_type": "markdown",
@@ -1769,12 +2360,49 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:36:08.861360Z",
+     "start_time": "2025-03-26T10:36:08.776459Z"
+    }
+   },
    "source": [
-    "# Answer for Optional Exercise 2\n"
-   ]
+    "best_lasso = Lasso(fit_intercept=True, alpha=4.78)\n",
+    "best_lasso.fit(Xtrain, Ytrain)\n",
+    "\n",
+    "hatY_lasso = best_lasso.predict(Xtest)\n",
+    "\n",
+    "fig, ax = plt.subplots()\n",
+    "ax.scatter(Ytest, hatY_lasso, s=5)\n",
+    "ax.plot([0, 1], [0, 1], transform=ax.transAxes, ls='--', c='gray')\n",
+    "ax.set_xlabel('Ytest')\n",
+    "ax.set_ylabel('hatY')\n",
+    "ax.set_title('Predicted vs true salaries for Ridge estimator')\n",
+    "ax.axis('square')"
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(-47.125, 2529.625, -86.38826026383923, 2490.361739736161)"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 55
   },
   {
    "cell_type": "markdown",
@@ -1786,17 +2414,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:36:09.772978Z",
+     "start_time": "2025-03-26T10:36:09.765999Z"
+    }
+   },
    "source": [
     "from sklearn.linear_model import LassoLarsIC\n",
     "\n",
     "lassoBIC = LassoLarsIC(criterion='bic')\n",
-    "lassoBIC.fit(Xtrainscaled, Ytrain)\n",
+    "lassoBIC.fit(XtrainScaled, Ytrain)\n",
     "print(\"best alpha chosen by BIC criterion :\", lassoBIC.alpha_)\n",
-    "print(\"best alpha chosen by CV :\", lassoCV.alpha_)"
-   ]
+    "print(\"best alpha chosen by CV :\", lassoCV.alpha_)\n",
+    "\n",
+    "alpha_BIC = lassoBIC.alpha_"
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "best alpha chosen by BIC criterion : 17.81143051916606\n",
+      "best alpha chosen by CV : 4.783179587705159\n"
+     ]
+    }
+   ],
+   "execution_count": 56
   },
   {
    "cell_type": "markdown",
@@ -1807,12 +2451,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:36:12.542833Z",
+     "start_time": "2025-03-26T10:36:12.446849Z"
+    }
+   },
    "source": [
     "lasso.set_params(alpha=alpha_BIC)\n",
-    "lasso.fit(XtrainScaled, Ytrain)\n",
+    "lasso.fit(Xtrain, Ytrain)\n",
     "\n",
     "hatY_BIC = lasso.predict(Xtest)\n",
     "\n",
@@ -1823,7 +2470,30 @@
     "ax.set_ylabel('hatY')\n",
     "ax.set_title('Predicted vs true salaries for LassoBIC estimator')\n",
     "ax.axis('square')"
-   ]
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(-47.125, 2529.625, -57.945939257169414, 2518.8040607428306)"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ],
+      "image/png": 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G7KuLFi3Cv/71L6SkpGDUqFFo1aoVhgwZIh0fzMvLgxCi1nUFUG1977nnHvTs2RM9e/bE0KFDsWzZMjzxxBN45513cPr06VrXKygoCACQnp7e5G1z9epVHDt2rNr+4O7uDiGEtE8Y63Ps5eWld9/R0bHOxyv/vyZNmoQPPvgATzzxBLZu3YoDBw7g4MGD8PHxqfPzpWOq/dLmjsGGh4dLo4hrU9PgEG9vb7Rq1Qpbtmyp8TW60xF0IZqdna3366y0tLTaP60q3TGrzMzMOsvVxtvbGwDw/fffSy2emlSuY1U1PVaTTp06oXfv3lizZg2eeuoprFmzBmq1GsOHD9crN3bsWIwdOxZFRUVISUnBsmXLMGnSJISEhCA6Orqhq1ZNTf8jZ2dnFBUVVXu8amB6e3tDoVBAo9HAycmpWvmaHqv6+uXLl2P58uW4ePEifv75Z7zwwgvIycnBli1bkJqait9//x1r165FXFyc9Drd8f66NOW1DRk93dB9A6joyVi9ejWAil6V7777DvHx8SguLsaHH35Y73tVptvXsrKyqj135coVqV46hh4J/tVXXyE0NBTffvut3rJr2k/q21cdHBwwb948zJs3D/n5+dixYwdefPFFjBgxApcuXULLli1hZ2dX67oCqLa+NencuTOEEDh27Bg6duxYY5kRI0bg448/xsaNG/HCCy80dHPo8fb2houLCz777LNan9cx1ue4KbRaLTZt2oTFixfrrbvueHtDmGq/tLkWbFPFxsYiNzcXZWVl0i/OyrcOHToAgDTa9euvv9Z7/XfffVfvgfH27dsjLCwMn332WY1fADq6AKj6S23EiBFwcHDAuXPnaqyj7odFhw4dEBAQgHXr1kEIIb3+woULSEpKatgGQcWIwf3792Pv3r345ZdfEBcXB3t7+1rrPGDAALz55psAUOOo5qrlG/JLtLKQkBDk5ORIrTWgYnDC1q1b9crFxsZCCIHLly/XuI0iIyMb/J5BQUGYPXs2hg0bJp3Yr/swVg3qjz76qN7lNee1dWnovlFV+/bt8fLLLyMyMrJJExdER0fDxcUFX331ld7jmZmZ2LVrV7NHCddHoVBIk17oZGdn1ziKWKch+6qnpycefPBBzJo1Czdu3EBGRgbc3NwQFRWFDRs26O275eXl+Oqrr9CmTRu0b9++3jrrRmv7+vrWWmbs2LGIjIzEsmXLkJqaWmOZrVu34vbt27UuIzY2FufOnUOrVq1q3B9qGpFf27ap7TvJGBQKBYQQ1T4jn376KcrKyqrVt6Z6mWq/tLkWbFNNnDgRX3/9Ne6991787W9/Q+/evaFUKpGZmYmEhASMHTsWDzzwAMLDw/Hoo49i+fLlUCqVGDp0KFJTU/Gvf/2rQV0MK1euxOjRo9GnTx8899xzCAoKwsWLF7F161YptHUBsGLFCsTFxUGpVKJDhw4ICQnBq6++ipdeegnnz5/HyJEj0bJlS1y9ehUHDhyAm5sblixZAjs7O7z22mt44okn8MADD2DGjBnIz89HfHx8g7uIAeCRRx7BvHnz8Mgjj0inyVT2yiuvIDMzE0OGDEGbNm2Qn5+PFStWQKlUYsCAAXUuOzIyErt378Yvv/yCgIAAuLu7Sz9iajNhwgS88sormDhxIp5//nncvXsX//73v6t96Pr27Ysnn3wS06dPx2+//Yb+/fvDzc0NWVlZ2Lt3LyIjI/H000/X+B5arRaDBg3CpEmT0LFjR7i7u+PgwYPYsmULxo0bBwDo2LEjwsLC8MILL0AIAS8vL/zyyy/Yvn17PVu0ea+tS0P3jWPHjmH27Nl46KGH0K5dOzg6OmLXrl04duxYk1pKnp6e+Mc//oEXX3wRU6dOxSOPPILc3FwsWbIEzs7OWLx4cbPWCwB27dpV40QC9957L2JjY7FhwwY888wzePDBB3Hp0iW89tprCAgIQFpamlS2Ifvq6NGjpfPofXx8cOHCBSxfvhzBwcHSiNNly5Zh2LBhGDRoEBYsWABHR0esWrUKqampWLduXbWWUFpamtT9r9VqsWPHDqxevRo9e/bEX//611rX2d7eHj/++COGDx+O6OhoPP300xg0aBDc3Nxw4cIFfP/99/jll1+Ql5dX6zLmzp2LH374Af3798dzzz2Hzp07o7y8HBcvXsS2bdswf/58REVFNWjbhIWFwcXFBV9//TXCw8PRokULqNVqqWvckDw8PNC/f3+8/fbb8Pb2RkhICPbs2YPVq1fD09NTr6zuFKaPP/4Y7u7ucHZ2RmhoKFq1amX0/RKA7Y0irm/EYVxcnHBzc6vxuZKSEvGvf/1LdOnSRTg7O4sWLVqIjh07iqeeekqkpaVJ5YqKisT8+fOFr6+vcHZ2Fn369BHJyckiODi43lHEQlSMch01apRQqVTCyclJhIWFVRuVvGjRIqFWq4WdnV21ZWzcuFEMGjRIeHh4CCcnJxEcHCwefPBBsWPHDr1lfPrpp6Jdu3bC0dFRtG/fXnz22We1jsStzaRJkwQA0bdv32rPbdq0SYwaNUq0bt1aODo6Cl9fX3HvvfcKjUZT73KPHj0q+vbtK1xdXQUAMWDAACFE/f/HzZs3i65duwoXFxdxzz33iA8++KDGUYxCCPHZZ5+JqKgo4ebmJlxcXERYWJiYOnWq+O2332qt1927d8XMmTNF586dhYeHh3BxcREdOnQQixcv1hv5ePLkSTFs2DDh7u4uWrZsKR566CFx8eJFAUAsXrxYKlfTKOKGvla3XteuXatWz9rWub594+rVq2LatGmiY8eOws3NTbRo0UJ07txZvPfee6K0tLTW7VJ5XWr633z66aeic+fOwtHRUahUKjF27Fhx4sQJvTJ1ffbqer/abrpt+sYbb4iQkBDh5OQkwsPDxSeffFJt+zRkX33nnXdETEyM8Pb2Fo6OjiIoKEg8/vjjIiMjQ69eGo1GDB48WNqv+vTpI3755Re9MjWNInZzcxOdOnUSixcvFlqtVq981VHEOvn5+eK1114T3bt3Fy1atBBKpVIEBQWJRx99VOzbt6/ebVhYWChefvll0aFDB+l/ExkZKZ577jnpzIqGfo7XrVsnOnbsKJRKpd6+Wtso4prWB4CYNWuW3mPp6ekCgHj77belxzIzM8X48eNFy5Ythbu7uxg5cqRITU2t9h0rhBDLly8XoaGhwt7evtpIZ2Psl5Up/lwpIiIiMiAegyUiIjICBiwREZERMGCJiIiMgAFLRERkBAxYIiIiI2DAEhERGYGsE00sW7YMGzZswOnTp+Hi4oKYmBi8+eabehMKTJs2DZ9//rne66KioqSTs4GKKbIWLFiAdevW4c6dOxgyZAhWrVqlN6dvXl4enn32Wfz8888AgDFjxuD999+vdmJybcrLy3HlyhW4u7vzwt5ERBZGCIGbN29CrVbXe0lOQ76pbEaMGCHWrFkjUlNTxdGjR8V9990ngoKCRGFhoVQmLi5OjBw5UmRlZUm33NxcveXMnDlTtG7dWmzfvl0cPnxYDBo0SHTp0kXvxPiRI0eKiIgIkZSUJJKSkkRERISIjY1tcF0vXbpU50ntvPHGG2+8mf/t0qVLzQ+vBjKriSauXbsGX19f7NmzB/379wdQ0YLNz8/Hxo0ba3yNVquFj48PvvzyS+lixleuXEFgYCA2b96MESNG4NSpU+jUqRNSUlIQFRUFAEhJSUF0dDROnz5d7xR8uvfx9PTEpUuXDHq1DyIiMp6kpCTs2bMHRUVFeO+995Cfnw+VSmWS9zaruYh11xatermi3bt3w9fXF56enhgwYAD++c9/ShNhHzp0CCUlJXpXcVGr1YiIiEBSUhJGjBiB5ORkqFQqKVyBiuvCqlQqJCUl1RiwRUVFehPu6y7V5eHhwYAlIrIQDg4O0nWP33vvPZMe4jObgBVCYN68eejXr580QTMAjBo1Cg899BCCg4ORnp6Of/zjHxg8eDAOHToEJycnZGdnw9HRES1bttRbnp+fn3Tptezs7BqvTOHr61vr5dmWLVuGJUuWGHANiYjI1IYMGYK2bdtWa7iZgtmMIp49ezaOHTtW7SK+EyZMwH333YeIiAiMHj0a//vf//DHH3/g119/rXN5Qgi9Xyo1/WqpWqayRYsWQavVSrdLly41Ya2IiMjUjh8/jpKSEgAV3/01XXrPFMwiYOfMmYOff/4ZCQkJeiN/axIQEIDg4GDpUlP+/v4oLi6udlmmnJwc+Pn5SWUqXyNU59q1a1KZqpycnKTuYHYLExFZBo1Ggw0bNmD9+vUoLy+XtS6yBqwQArNnz8aGDRuwa9cuhIaG1vua3NxcXLp0CQEBAQCAHj16QKlU6l0vMysrC6mpqYiJiQFQcXFdrVaLAwcOSGX2798PrVYrlSEiIsum0Wiwa9cuABXXQDbZ6Ti1kHUU8TPPPINvvvkGP/30k95AI5VKBRcXFxQWFiI+Ph7jx49HQEAAMjIy8OKLL+LixYs4deoU3N3dAQBPP/00Nm3ahLVr18LLywsLFixAbm4uDh06BHt7ewAVx3KvXLmCjz76CADw5JNPIjg4GL/88kuD6lpQUACVSgWtVsvWLBGRmakcroMHD652wXo5vsNlDdjajn+uWbMG06ZNw507d3D//ffjyJEjyM/PR0BAAAYNGoTXXnsNgYGBUvm7d+/i+eefxzfffKM30UTlMjdu3Kg20cQHH3zQ4IkmGLBEROapvnAFbDBgLQkDlojI/CQlJUmHCGsLV0Ce73CzOU2HiIiosYKDg+Hk5IS+ffvWGq5yYQu2gdiCJSIyTzdv3pTG5NRGju9wszhNh4iIqKGSkpJw+fJl6X594SoXBiwREVkMjUaD7du348svv5SmsDVXDFgiIrIIlUcL9+3b12xbrjoMWCIiMnsNORXH3DBgiYjIrFliuAIMWCIiMmPHjx+3yHAFeB4sERGZsY4dOyIsLAzBwcEWFa4AA5aIiMyYUqnEpEmTZJ+4vyksr8ZERGTVNBoNduzYAd08SJYYrgBbsEREZEYqD2hq27atbBdLNwTL/FlARERWp+poYUsOV4ABS0REZsBST8WpCwOWiIhkZY3hCjBgiYhIRlevXrXKcAU4yImIiGTk5+eHMWPGoLCw0KrCFWDAEhGRDEpKSqBUKgEA3bp1k7k2xsEuYiIiMqnExER88sknuHXrltxVMSoGLBERmUxiYiISEhJw7do1nD59Wu7qGBUDloiITEIXrkDFgKYePXrIXCPjYsASEZHRVQ1XaxvQVBMGLBERGZUthivAgCUiIiMqKirCkSNHANhWuAI8TYeIiIzIyckJcXFx+OOPP9C7d2+5q2NSbMESEZHBXb9+Xfrb09PT5sIVYMASEZGBaTQa/Oc//8HJkyflroqs2EVMREQGU3ni/hs3bshcG3mxBUtERAZR9ao4/fr1k7lG8mLAEhFRs1nrJeeagwFLRETNwnCtGQOWiIiaTAiB/Px8AAzXqjjIiYiImkyhUCA2NhYdO3ZEu3bt5K6OWWELloiIGu3UqVMoKysDUBGyDNfqGLBERNQoGo0G3333HTZs2AAhhNzVMVsMWCIiarDKA5r8/f2hUChkrpH5YsASEVGDcLRw4zBgiYioXgzXxmPAEhFRnfbt28dwbQKepkNERHVSq9VwcHBA//79Ga6NoBAcAtYgBQUFUKlU0Gq18PDwkLs6REQmlZ+fD09PT7mr0WRyfIezi5iIiKpJSUnBtWvXpPuWHK5yYcASEZEejUaDrVu34vPPP8ft27flro7FYsASEZGk8mjhqKgouLq6ylwjy8WAJSIiADwVx9AYsERExHA1AgYsEZGNO3r0KMPVCHgeLBGRjevYsSMOHTqE9u3bM1wNiAFLRGTjnJ2dMW3aNNjb28tdFavCLmIiIhuk0WiQlJQk3We4Gh5bsERENqbygKagoCC0adNG5hpZJ7ZgiYhsSNXRwgxX42HAEhHZCJ6KY1oMWCIiG8BwNT0GLBGRlcvMzGS4yoCDnIiIrFybNm0wbNgwlJWVMVxNiAFLRGSlSktL4eBQ8TUfExMjc21sD7uIiYiskEajwdq1a3H37l25q2KzGLBERFZGN6Dp8uXLOH36tNzVsVkMWCIiK1J1tHDXrl3lrZANkzVgly1bhl69esHd3R2+vr64//77cebMGb0yQgjEx8dDrVbDxcUFAwcOxIkTJ/TKFBUVYc6cOfD29oabmxvGjBmDzMxMvTJ5eXmYMmUKVCoVVCoVpkyZgvz8fGOvIhGRyfBUHPMia8Du2bMHs2bNQkpKCrZv347S0lIMHz4ct27dksq89dZbePfdd/HBBx/g4MGD8Pf3x7Bhw3Dz5k2pzNy5c/Hjjz9i/fr12Lt3LwoLCxEbG4uysjKpzKRJk3D06FFs2bIFW7ZswdGjRzFlyhSTri8RkbEwXM2QMCM5OTkCgNizZ48QQojy8nLh7+8v3njjDanM3bt3hUqlEh9++KEQQoj8/HyhVCrF+vXrpTKXL18WdnZ2YsuWLUIIIU6ePCkAiJSUFKlMcnKyACBOnz7doLpptVoBQGi12mavJxGRId26dUu8/fbbIj4+XiQmJspdHbMkx3e4WR2D1Wq1AAAvLy8AQHp6OrKzszF8+HCpjJOTEwYMGCBdBeLQoUMoKSnRK6NWqxERESGVSU5OhkqlQlRUlFSmT58+UKlUeleTICKyRK6uroiLi8OIESPYcjUjZnMerBAC8+bNQ79+/RAREQEAyM7OBgD4+fnplfXz88OFCxekMo6OjmjZsmW1MrrXZ2dnw9fXt9p7+vr6SmWqKioqQlFRkXS/oKCgiWtGRGQc+fn58PT0BAD4+PjAx8dH3gqRHrNpwc6ePRvHjh3DunXrqj2nUCj07gshqj1WVdUyNZWvaznLli2TBkSpVCoEBgY2ZDWIiEwiMTERK1euxPnz5+WuCtXCLAJ2zpw5+Pnnn5GQkKB36SR/f38AqNbKzMnJkVq1/v7+KC4uRl5eXp1lrl69Wu19r127Vq11rLNo0SJotVrpdunSpaavIBGRASUmJiIhIQGlpaXIysqSuzpUC1kDVgiB2bNnY8OGDdi1axdCQ0P1ng8NDYW/vz+2b98uPVZcXIw9e/ZI03716NEDSqVSr0xWVhZSU1OlMtHR0dBqtThw4IBUZv/+/dBqtbVOH+bk5AQPDw+9GxGR3HThClSMFu7bt6/MNaLayHoMdtasWfjmm2/w008/wd3dXWqpqlQquLi4QKFQYO7cuVi6dCnatWuHdu3aYenSpXB1dcWkSZOkso8//jjmz5+PVq1awcvLCwsWLEBkZCSGDh0KAAgPD8fIkSMxY8YMfPTRRwCAJ598ErGxsejQoYM8K09E1EhVw5UDmsybrAH7n//8BwAwcOBAvcfXrFmDadOmAQAWLlyIO3fu4JlnnkFeXh6ioqKwbds2uLu7S+Xfe+89ODg44OGHH8adO3cwZMgQrF27Fvb29lKZr7/+Gs8++6w02njMmDH44IMPjLuCREQGwnC1PAohhJC7EpagoKAAKpUKWq2W3cVEZFJCCHz//fc4efIkw7WJ5PgON5vTdIiIqGYKhQLjxo1DREQEwsPD5a4ONZBZjCImIqLq0tLSoOtktLe3Z7haGAYsEZEZ0mg0+Oabb7Bp0ybwSJ5lYsASEZmZyhP3e3p61juxDpknBiwRkRnhVXGsBwOWiMhMMFytCwOWiMgM7N27l+FqZXiaDhGRGWjVqhXs7OwwcOBAhquV4EQTDcSJJojI2HJzc9GqVSu5q2GV5PgOZxcxEZFMDhw4gPz8fOk+w9W6MGCJiGSg0Wjwv//9D59//jmKiorkrg4ZAQOWiMjEKo8W7t69O5ycnGSuERkDA5aIyIR4Ko7tYMASEZkIw9W2MGCJiEzg0KFDDFcbw4AlIjKBjh07wsfHh+FqQzjRBBGRCbi5uWHGjBlQKpVyV4VMhC1YIiIj0Wg0OHz4sHSf4Wpb2IIlIjKCygOa1Go1/P39Za4RmRpbsEREBlZ1tDDD1TYxYImIDIin4pAOA5aIyEAYrlQZA5aIyAAyMjIYrqSHg5yIiAwgODgYffv2hZOTE8OVADBgiYiapby8HHZ2dlAoFBg6dKjc1SEzwi5iIqImSkxMxNdff42SkhK5q0JmiAFLRNQEiYmJSEhIwPnz53H69Gm5q0NmiAFLRNRIunAFKgY0RUZGylwjMkcMWCKiRqgarhzQRLVhwBIRNRDDlRqDo4iJiBrg5s2bSEpKAsBwNbXSsnKsTDiHgxk30CvEC7MGhcHB3vzbhwxYIqIGcHd3x5QpU3DhwgXExMTIXR2bsjLhHJbv+AMCwL6z1wEAfxvaTt5KNQADloioDjdv3oS7uzsAoHXr1mjdurXMNbI9BzNuQPz5t/jzviUw/zY2EZFMNBoNVq5cicuXL8tdFZvWK8QLij//Vvx53xKwBUtEVIPKE/dfuHCBLVcZzRoUBgB6x2AtAQOWiKiKqlfF4TFXeTnY21nEMdeq2EVMRFQJLzlHhsKAJSL6E8OVDIkBS0SEiqviXLhwAQDDlQyDx2CJiADY2dlhwoQJOH36NOcWJoNgC5aIbFpGRgaEqDjLUqlUMlzJYBiwRGSzNBoNPv/8c+zcuVPuqpAVYsASkU2qPKDJyclJ5tqQNWLAEpHN4WhhMgUGLBHZFIYrmQoDlohsBsOVTImn6RCRzWjRogUAw4erpV6vlIyLAUtENqNbt25Qq9Xw8/Mz6HIt9XqlZFz8iUVEVu3QoUMoLCyU7hs6XAHLvV4pGRcDloislkajwaZNm/DFF1+gpKTEaO9jqdcrJeNiFzERWaXKA5oiIyOhVCqN9l6Wer1SMi4GLBFZHVOPFrbU65WScbGLmIisCk/FIXPBgCUiq3HgwAGGK5kNBiwRWY327dvD09OT4UpmgcdgichqeHp6YubMmZy8n8wCW7BEZNH27t2LkydPSvcZrmQu2IIlIouVmJiIhIQE2NnZwdfXF97e3nJXiUjCFiwRWSRduALAwIEDGa5kdhiwRGRxKocrBzSRuWLAEpFFYbiSpZA1YBMTEzF69Gio1WooFAps3LhR7/lp06ZBoVDo3fr06aNXpqioCHPmzIG3tzfc3NwwZswYZGZm6pXJy8vDlClToFKpoFKpMGXKFOTn5xt57YjI0NLS0hiuZDFkDdhbt26hS5cu+OCDD2otM3LkSGRlZUm3zZs36z0/d+5c/Pjjj1i/fj327t2LwsJCxMbGoqysTCozadIkHD16FFu2bMGWLVtw9OhRTJkyxWjrRUTG0bZtW3Tv3p3hShZB1lHEo0aNwqhRo+os4+TkBH9//xqf02q1WL16Nb788ksMHToUAPDVV18hMDAQO3bswIgRI3Dq1Cls2bIFKSkpiIqKAgB88skniI6OxpkzZ9ChQwfDrhQRGZwQQurFio2NhUKhqP9FRDIz+2Owu3fvhq+vL9q3b48ZM2YgJydHeu7QoUMoKSnB8OHDpcfUajUiIiKQlJQEAEhOToZKpZLCFQD69OkDlUollalJUVERCgoK9G5EZHoajQbff/+91CvFcCVLYdYBO2rUKHz99dfYtWsX3nnnHRw8eBCDBw9GUVERACA7OxuOjo5o2bKl3uv8/PyQnZ0tlfH19a22bF9fX6lMTZYtWyYds1WpVAgMDDTgmhFRQ+gm7j958iT++OMPuatD1ChmPdHEhAkTpL8jIiLQs2dPBAcH49dff8W4ceNqfZ2uO0mnpl+8VctUtWjRIsybN0+6X1BQwJAlMqGqV8UJDw+XuUZEjWPWLdiqAgICEBwcjLS0NACAv78/iouLkZeXp1cuJycHfn5+UpmrV69WW9a1a9ekMjVxcnKCh4eH3o2ITIOXnCNrYFEBm5ubi0uXLiEgIAAA0KNHDyiVSmzfvl0qk5WVhdTUVMTExAAAoqOjodVqceDAAanM/v37odVqpTJEZD4YrmQtZO0iLiwsxNmzZ6X76enpOHr0KLy8vODl5YX4+HiMHz8eAQEByMjIwIsvvghvb2888MADAACVSoXHH38c8+fPR6tWreDl5YUFCxYgMjJSGlUcHh6OkSNHYsaMGfjoo48AAE8++SRiY2M5gpjIzOTn5yMxMREAw5WsgJBRQkKCAFDtFhcXJ27fvi2GDx8ufHx8hFKpFEFBQSIuLk5cvHhRbxl37twRs2fPFl5eXsLFxUXExsZWK5ObmysmT54s3N3dhbu7u5g8ebLIy8trVF21Wq0AILRabXNXm4jqcP78ebF37165q0FWRo7vcIUQQsiY7xajoKAAKpUKWq2Wx2OJDOz27dtwdXWVuxpkxeT4DreoY7BEZH00Gg1WrVqFa9euyV0VIoNiwBKRbHQDmm7duoVz587JXR0ig2LAEpEsqo4WrnohDyJLx4AlIpPjqThkCxiwRGRSDFeyFQxYIjKZsrIyaU5hhitZO7Oei5iIrIu9vT0mT56M06dPo2vXrnJXh8io2IIlIqPLzMyU/nZ2dma4kk1gwBKRUWk0GqxevRr79u2TuypEJsWAJSKjqTygqby8XObaEJkWA5aIjIKjhcnWMWCJyOAYrkQMWCIyMIYrUQWepkNEBmVvbw+A4VpVaVk5Viacw8GMG+gV4oVZg8LgYM82jjVjwBKRQcXExCAoKAht2rSRuypmZWXCOSzf8QcEgH1nrwMA/ja0nbyVIqPizyciarajR4/i7t270n2Ga3UHM25Ad/Ft8ed9sm4MWCJqlsTERPz000/46quvUFpaKnd1zFavEC8o/vxb8ed9sm7sIiaiJktMTERCQgIAoEOHDnBw4FdKbWYNCgMAvWOwZN34aSCiJqkcrhzQVD8Hezsec7UxjeoiLiwsNFY9iMiCMFyJ6teogI2MjERiYqKx6kJEFiAlJYXhStQAjQrYhx56CEOHDsX8+fNRVFRkrDoRkRkLCwuDm5sbw5WoHgohhKi/2P9LSUnBY489BoVCgS+//BLdu3c3Vt3MSkFBAVQqFbRaLTw8POSuDpGsbt++DVdXV7mrQdRgcnyHN3qQU58+fXDkyBG8/PLL6Nu3L4YNG1Zt5OCGDRsMVkEikt++ffsQEBCAe+65BwAYrkQN0KRRxEVFRcjJyYFCoYBKpeLQfCIrpptb2MHBAbNmzYKnp6fcVSKyCI1Oxm3btuHxxx+HWq3G4cOH0bFjR2PUi4jMQOWJ+/v3789wJWqERg1yeuqppzBmzBjMmDEDSUlJDFciK8ar4hA1T6NasPv27UNSUpLNDGwislUMV6Lma1QL9vDhw+jevTteffVV3L59u9rzd+7cwauvvmqwyhGR6Z06dYrhSmQAjT5NB6i43mNWVhZ8fX31Hs/NzYWvry/KysoMVkFzwdN0yFaUl5djw4YN8PPzY7iS1bCI03QAQAgBhUJR7fHff/8dXl68QgSRJdJ9ru3s7DB+/PgaP+OWgBc2J3PRqIBt2bIlFAoFFAoF2rdvr/cBLCsrQ2FhIWbOnGnwShKRcWk0GuTn5yM2Nlb6jFsqXticzEWjAnb58uUQQuCxxx7DkiVLoFKppOccHR0REhKC6Ohog1eSiIyn8oCmjh07ol07yw4jXticzEWjAjYuLg4AEBoaipiYGCiVSqNUiohMo+poYUsPV6DiQub7zl6HAC9sTvJq0jHYAQMGSH/fuXMHJSUles9zEBCR+bPWU3F4YXMyF00K2Nu3b2PhwoX47rvvkJubW+15axxFTGRNrDVcAV7YnMxHk4bWPf/889i1axdWrVoFJycnfPrpp1iyZAnUajW++OILQ9eRiAwoNzcXu3fvBmB94UpkTpp0HmxQUBC++OILDBw4EB4eHjh8+DDatm2LL7/8EuvWrcPmzZuNUVdZ8TxYsianTp1Cbm4u+vXrJ3dViEzCYs6DvXHjBkJDQwFUHG+9caNilF6/fv3w9NNPG652RGQwd+/ehbOzMwAgPDxc5toQWb8mdRHfc889yMjIAAB06tQJ3333HQDgl19+4dU2iMyQRqPBhx9+iPz8fLmrQmQzmhSw06dPx++//w4AWLRokXQs9rnnnsPzzz9v0AoSUfPoBjRptVr88ccfcleHyGY06RhsVRcvXsRvv/2GsLAwdOnSxRD1Mjs8BkuWyJpHCxM1hsUcgwWAnTt3YufOncjJyUF5ebnec5999lmzK0ZEzcNwJZJXkwJ2yZIlePXVV9GzZ08EBARY9LylRNaI4UokvyYF7Icffoi1a9diypQphq4PETVTSUkJjh8/DoDhSiSnJgVscXExYmJiDF0XIjIApVKJuLg4nD59Gj169JC7OkQ2q0mjiJ944gl88803hq4LETVDdna29LebmxvDlUhmDW7Bzps3T/q7vLwcH3/8MXbs2IHOnTtXu6rOu+++a7gaElkYOS74nZiYiISEBIwePRrdu3c36nsRUcM0OGCPHDmid79r164AgNTUVL3HOeCJbJ2pL/itC1cAuHXrltHeh4gap8EBq/sAE1HdTHnB78rhygFNRObFuP1WRDaoV4gXdP04xrzgN8OVyLw1eaIJIqqZKS74zXAlMn8MWCIDM8UFv0tKSgAwXInMGQOWyAINHjwYYWFhCAkJkbsqRFQLHoMlshDHjx+XWq4KhYLhSmTmGLBEFkCj0WDDhg1Yv359tYtrEJF5YsASmbnKE/eHhITAzo4fWyJLwE8qkRnjVXGILBcDlshMMVyJLBsDlsgMJScnM1yJLBxP0yEyQ8HBwXByckLfvn0ZrkQWStYWbGJiIkaPHg21Wg2FQoGNGzfqPS+EQHx8PNRqNVxcXDBw4ECcOHFCr0xRURHmzJkDb29vuLm5YcyYMcjMzNQrk5eXhylTpkClUkGlUmHKlCnIz8838toRVSgtK8eKHWl49NP9WLEjDaVl9Y8CVqvVmD17NsOVyILJGrC3bt1Cly5d8MEHH9T4/FtvvYV3330XH3zwAQ4ePAh/f38MGzYMN2/elMrMnTsXP/74I9avX4+9e/eisLAQsbGxKCsrk8pMmjQJR48exZYtW7BlyxYcPXoUU6ZMMfr6EQH/f3WdvWevY/mOP7Ay4VyN5ZKSknD58mXpfosWLUxVRSIyAoUQQtRfzPgUCgV+/PFH3H///QAqWq9qtRpz587F3//+dwAVrVU/Pz+8+eabeOqpp6DVauHj44Mvv/wSEyZMAABcuXIFgYGB2Lx5M0aMGIFTp06hU6dOSElJQVRUFAAgJSUF0dHROH36NDp06NCg+hUUFEClUkGr1cLDw8PwG4Cs1qOf7sfePy9bBwD92nrjqyei9MroBjQ5OTlh1qxZcHd3N3U1iayaHN/hZjvIKT09HdnZ2Rg+fLj0mJOTEwYMGICkpCQAwKFDh1BSUqJXRq1WIyIiQiqTnJwMlUolhSsA9OnTByqVSipTk6KiIhQUFOjdiJqivqvrVB4t3LdvX4YrkZUw20FO2dnZAAA/Pz+9x/38/HDhwgWpjKOjI1q2bFmtjO712dnZ8PX1rbZ8X19fqUxNli1bhiVLljRrHYiAuq+uw1NxiKyX2QasjkKh0LsvhKj2WFVVy9RUvr7lLFq0CPPmzZPuFxQUIDAwsKHVJpLUdnUdhiuRdTPbLmJ/f38AqNbKzMnJkVq1/v7+KC4uRl5eXp1lrl69Wm35165dq9Y6rszJyQkeHh56NyJDOX78OMOVyMqZbcCGhobC398f27dvlx4rLi7Gnj17EBMTAwDo0aMHlEqlXpmsrCykpqZKZaKjo6HVanHgwAGpzP79+6HVaqUyRKbWsWNHhIWFMVyJrJisXcSFhYU4e/asdD89PR1Hjx6Fl5cXgoKCMHfuXCxduhTt2rVDu3btsHTpUri6umLSpEkAAJVKhccffxzz589Hq1at4OXlhQULFiAyMhJDhw4FAISHh2PkyJGYMWMGPvroIwDAk08+idjY2AaPICYyFN2hCaVSiUmTJnHifiJrJmSUkJAgAFS7xcXFCSGEKC8vF4sXLxb+/v7CyclJ9O/fXxw/flxvGXfu3BGzZ88WXl5ewsXFRcTGxoqLFy/qlcnNzRWTJ08W7u7uwt3dXUyePFnk5eU1qq5arVYAEFqttjmrTDZsz549Yvv27aK8vFzuqhDZHDm+w83mPFhzx/NgqTkSExORkJAAAJg6dSpCQ0NlrhGRbZHjO9zsRxFbm9KycqxMOKd3yoaDPbsJrVnlcB08eDDDlchGMGBNTDdtngCw78/ZfWo6hYOsQ9Vw5YAmItvBgDWxgxk3oOuTF3/etwW22HJnuBLZNgasifUK8cK+s9chUPO0eeauqUFpay33q1evMlyJbBwD1sTqmjbPEjQ1KG2t5e7n54cxY8agsLCQ4UpkoxiwJlbbtHmWoqlBaekt94YqKSmBUqkEAHTr1k3m2hCRnBiwFkquY5pNDUpLb7k3RGJiIlJTUzF16lRey5WIGLCWSq5jmk0NSktvuVdW04+bpH17pWOuZ86cQY8ePWSuJRHJjQFroeQ6pmlNQdlUVX/c3L2UirsXjwGoGNDEcCUiwIwn+6e61XcRb6pbaVk5VuxIw6Of7seKHWkoLStv8Gsr/7iJdLiiF64c0EREOmzBWihbOKZpTM3pYtcdh450uIIeyisAGK5EVB0D1kKxq7Z5mtPFPmtQGERpCa7/dgIoAwYOHMRwJaJqGLBkMyoPTior//9rXDS2i93B3g5zR3ZCfh81/vjjD/Tu3dsItSUiS8eAJT3WPKVh5W5hBYDoe1rB3k7RqC7269evw9vbGwDg6enJcCWiWjFgSY81T2lYtVvY3k6Br56IavDrNRoNdu/ejfHjx6NTp05GqSMRWQ/raJqQwVjzlIbNGXmt0Wiwa9culJeX48YN/W3SnBHJRGS92IIlPdY8pWFTR17rwhWoGC3cr18/veetudVPRE3HgCU91nz6T1NGXlcN15pGC1tzq5+Imo4BS3p4+s//a0i4Atbd6ieipmPAEtVACAGtVgug/kkkrLnVT0RNpxBCiPqLUUFBAVQqFbRaLTw8POSuDpmAEAJnz55Fu3Zs0RNZOjm+wzmKmKiSU6dOoaysDACgUCgsPlw5wplIPuwiJotkjAkxdMdcO3XqhAcffBAKhaL+F5k5jnAmkg8DliySoYOj8oAmf39/qwhXgCOcieTELmIyGUN2VxoyOBo6WtgS8bKGRPJhC5ZMxpCtTkOdGmPN4QpwhDORnBiwNkqOSf0N2eo0RHDs27fPqsMV4HnNRHJiwNooOQa/GHJCBkMEh1qthoODA/r372+V4UpE8mLA2ig5Br+YW3dlYFAwXLvch4/OFOFwUZpVXZqPiOTHgLVRckzvZw7dlSkpKQgLC4OPjw9WJpzDv/de5iksRGQUDFgbZW6tSVNITExEQkIC3Nzc8Mwzz/AUFiIyKgasjTKH1qQx1DZ4SxeuABAVFQVXV1dO0k9ERsWAJatS0+Ctbo5ZUrhWHi1si614IjIdBixZlardvmePH0R+QRqA6qfiWGsrnojMA4dMklWpPHNRO/vr8K4lXImIjI0tWLIqlbt9e7YJQYvMEnTo0IHhSkQmx4Alq1K127esrCPs7e1lrBER2SoGLJmlyqOBewR7AkKBQxfz6p3WUaPRwM7ODn379gUAhisRyYYBS2ap8mjgvX+OBgbqnhCi8sT9wcHBaNOmjUnqSkRUEw5yIrNUeTRwZbVNCFH1qjgMVyKSGwOWzFLl0cCV1TQhhLVfco6ILBO7iK2IHJegM9Z7Vh4N3C1QhYMZeTidfRPhAR54qn+oVI7hSkTmigFrReS4BJ2x3rPyaOAVO9KwP72iyzjlfC4+SkzH34a2Q2ZmJsOViMwWA9aKyDF5vSnes7b3aNOmDYYNG4aysjKGKxGZHR6DtSKVj1uaavJ6U7xn1ffoGaSSnouJiWG4EpFZYgvWisgxeb0p3rPye0TaZ8HtggZ374bA2dnZ4O9FRGQoCiFETWdDUBUFBQVQqVTQarXw8PCQuzo2qfKAprFjx6Jr167yVoiILIYc3+HsIiaLUHW0MMOViMwdA5bMHk/FISJLxIAls8ZwJSJLxUFOJIuGTFBx+/ZtHDhwAADDlYgsDwPWQskxa5MhNWSCCldXV8TFxeHs2bPo06ePDLUkImo6BqyFkmPWJkOqa4KK/Px8eHp6AgC8vb3h7e1t8vpVZuk/ZohIHvyWsFByzNpkSLVNUKHRaLBy5UqcP39etrpVpfsxs/fsdSzf8QdWJpyTu0pEZAHYgrVQvUK8sO/sdQjUPoOSObe8apqgovKApqysLNxzzz1yVlFi6T9miEgeDFgL1ZAZlMy5G7nyZP5A9dHCffv2NWl96vox0pAfM0REVTFgLVTVgKqJpbS8ajoVx9St77p+jMgxBSURWT4GrBWzhJZXbee5mrr1XdePkYb8mCEiqooBa8XMveUlhMDVq1cBVD/P1dStb0v4MUJEloUBa8XMveWlUCgwbtw4/OUvf0F4eLjec6YOPHP/MUK2xZwHKFLDmfV/LD4+HgqFQu/m7+8vPS+EQHx8PNRqNVxcXDBw4ECcOHFCbxlFRUWYM2cOvL294ebmhjFjxiAzM9PUq2LRSsvKsWJHGh79dD9W7EhDaVl5s5aXlpYG3UWc7OzsqoUrUBF4c4e2R7+23pg7tL3RA0/3Y+SrJ6Lwt6Htmv1lZuhtRraFp4ZZB7Nvwf7lL3/Bjh07pPv29vbS32+99RbeffddrF27Fu3bt8frr7+OYcOG4cyZM3B3dwcAzJ07F7/88gvWr1+PVq1aYf78+YiNjcWhQ4f0lkW1M+Tx0MTERCQkJKBbt24YPXo0FApFjeXMvfVdH3MewU3mz1IGKFLdzLoFCwAODg7w9/eXbj4+PgAqWq/Lly/HSy+9hHHjxiEiIgKff/45bt++jW+++QYAoNVqsXr1arzzzjsYOnQounXrhq+++grHjx/XC22qW10f9sa01HThCgAtW7asNVytAb8gqTlqm4iFLIvZB2xaWhrUajVCQ0MxceJEaYaf9PR0ZGdnY/jw4VJZJycnDBgwAElJSQCAQ4cOoaSkRK+MWq1GRESEVIbqV9eHvaFdWZXD1RYm7ucXJDWHqQ+RkHGYdRdxVFQUvvjiC7Rv3x5Xr17F66+/jpiYGJw4cQLZ2dkAAD8/P73X+Pn54cKFCwCA7OxsODo6omXLltXK6F5fm6KiIhQVFUn3CwoKDLFKFqmuAUANaanZWrgCHDRFzWPph0ioglkH7KhRo6S/IyMjER0djbCwMHz++efS1VWqdjMKIertemxImWXLlmHJkiVNrHnTmePowbo+7PWN9t27d6/RwtUct5UOvyCJyKwDtio3NzdERkYiLS0N999/P4CKVmpAQIBUJicnR2rV+vv7o7i4GHl5eXqt2JycHMTExNT5XosWLcK8efOk+wUFBQgMDDTg2tTM0gbH1NdSa9WqFezs7DBw4ECDt1wtbVsRkW0xj5/7DVRUVIRTp04hICAAoaGh8Pf3x/bt26Xni4uLsWfPHik8e/ToAaVSqVcmKysLqamp9Qask5MTPDw89G6GVNvgIEsbHFPf6S3h4eF45plnjNIt3JhtxdNmiMjUzLoFu2DBAowePRpBQUHIycnB66+/joKCAsTFxUGhUGDu3LlYunQp2rVrh3bt2mHp0qVwdXXFpEmTAAAqlQqPP/445s+fj1atWsHLywsLFixAZGQkhg4dKuu61db6soYZhQ4cOID27dtL13Rt1aqVUd6nMduKrV0iMjWzDtjMzEw88sgjuH79Onx8fNCnTx+kpKQgODgYALBw4ULcuXMHzzzzDPLy8hAVFYVt27ZJ58ACwHvvvQcHBwc8/PDDuHPnDoYMGYK1a9fKfg5sba0vcxoc05RjnLq5hZOSkjBz5kw4OzsbrX6N2VaW1jNARJZPIXRT6lCdCgoKoFKpoNVqDdJdvGJHmtSiUgCYO7S9wVpUhhr809g61jZxvzkw5vYmIvNn6O/whjDrFqw1M2ZL1VDdoY1p9ZlzuALm1TNARLaBASsTY57GYaju0IYe4zT3cAV42gwRmR4D1gI0tsvXUAOlGtLqO3TokNmHKxGRHBiwFqCxXb6G6g5tSKuvY8eO2L9/PyIjI/XC1ZwngSAiMgUGrAVobJevKbtD3dzcMGPGDCiVSr3Hzem0GIY9EcmBAWsBzO3cWI1GAzc3N3Tv3h0AqoUrYF6nxZhT2BOR7WDAWgBzGgFbeUCTWq2Gv79/jeXM6UeBOYU9EdkOBqyZqrlbU95WV9XRwrWFK2BePwrMKeyJyHYwYM2UuXVrNvRUnKo/DNZO7yX78U5zCnsish0MWDNlTt2aVcM1OqYvVuxIq3HQkLn9MAB4DiwRyYMBa6bMpVszIyNDCtfrHu1wuMgfv+08i3/vSqsxRM3phwERkZwYsGbqqf6hSDmfi1NZBQgP8MBT/UNlqUdwcDCc2vwFSen5OHZVBcXVPxDo5VpriJrLDwMiIrkxYGVW2zmaHyWmI+V8LgSAlPO5+Cgx3aTdnOXl5bCzs4NCoUCqCMSxUhcAkIJV8effVUPUnI938nxYIjIlBqzMajtmKWdXq0ajQUZGBiZOnAilUlmtVfpANzXsFHY1hqg5H+80x+PDRGS9GLAyqy1I5epqrTyg6fTp04iMjKyxVWqJLT8eHyYiU2LAyqy2IDVGV2t9XaRVRwtHRkYCMO9WaWPw+DARmRIDVma1BakxQq2uLlJLuORcc5nz8WEisj4MWJmZsnVYWxfpnj2J2L07AQDgHNQF0TF9TVIfU7OWljgRWQbLO5Bm4UrLyrFiRxoe/XQ/VuxIQ2lZeY2PGUOvEC8o/vxb10VaWFiI3Zq9AIBDJa3x4RklViacM8r7ExHZErZgTaymbloAdY5uNdTpJbUNVrro1RPZVy7hRKm/9DwRETUPA9bEauumrWt0q6FOL6ncRXrz5k0ppDu3D8WuiyUAOPiHiMhQGLAmVttI1sqP9Qj21Jvr90B6rkFPL0lMTERSUhKmTJmC1q1bc/APEZERMGBNrK4w0z1WXi6wfOf/t1j73NOq1pmTGisxMREJCRUDmi5cuIDWrVtz8A8RkREwYE2stjCr/Nijn+7Xa7HaKYC5Q9s3u4VZOVwHDx6MmJiYJi2HiIjqx4A1Q1W7kXuHtmp2C7NquFrjea6GxHmLiai5GLBmyFDHRHUhcfb4QXgXpAGoOM/1ozOOOFyUxtCoA+ctJqLmYsDKpK4WUlOPiVZdZnm5wPu7/sBQx6uAPXDNvR1+PaOEwHWThoYltgY5bzERNRcDVibGaCFVXWaglyvKocDO4rYIss9D3k1vCFScjtOY0GhuQFpia5DzFhNRczFgZWKMFlLlZfrZFQDCBQoAZbBDRlkr9AnwkK4x25jQaG5AWmJrkKcuEVFzMWBNTNcavHjjtvSYoVpIulZXpEMWeigvw9HLDi7du+G3C3noFeKFp/qH4qPE9EaHRnMD0hJbgzx1iYiaiwFrYpVbgwAQ5OWK8d3bGKSFNGtQGO5eOoG7Fy8DAGLaB2DAgPZ6ZZoSGs0NSLYGicgWMWBNrHJrEKgIWEO1lJKT9uHuxd8BGPZUnOYGJFuDRGSLGLAmVldrsLSsHO/vSsOPR64AAB7o2hpzhrRt0IAiY17PlQFJRNR4DFgTq6s1uDLhHFbsPCvdX7ErDXZ2inrDzRYulk5EZGkYsCZWV2uwpsFDDRlQ1KJFCwAMVyIic8KANSO9Qrywt9I1YnWP1adbt25Qq9Xw8/MzVtWIiKiRGLAmVtekDbMGhaFclOsdg61tQNGhQ4fQoUMHqfXKcCUiMi8KIYSovxgVFBRApVJBq9XCw8OjyctZsSNNOk1HgYqr5NR3jLW0rBzv7zyLH49WnH5zr08eii4eh4+PD2bMmAGlUtnk+hAR2QJDfYc3BluwJtaUSRtWJpzDil0Vk/V3dshC0Z2KoI2MjGS4EhGZKfOecd0K9QrxguLPvxs6aYMuhDv/OUMTAFz3aMcBTUREZowtWBObNSgM5eVC6u4tF+UoLSuv81zXXiFeKMg4LoXroZLWGBLZy2h1tMSr3xARmRsGrIk52NvBzk6BSzduQwD4986zsFPUPZFDlHse8v8M17MOIRgU08eo0w1a4tVviIjMDQNWBo09DhvesQP2pySje/fuWGyCbmFLvPoNEZG5YcCaSOVu17Jy/YHbZeWizm5ilUqFmTNnwsnJyRRVtcir3xARmRsGrIlU7nZVAGjT0gWZeXcAAMnnc7Ey4ZxeN+zevXvh5eWFTp06AYDJwhXg1W+IiAyBAWsiVbtdC++WVnteRze3sJ2dHXx9feHt7W26ioKT+xMRGQKHhppI1dNzwgM8ajxdp/LE/QMHDjR5uBIRkWGwBWsiVbtdn+ofio8S0/W6YXlVHCIi68GpEhvI2NNsMVyJiIyHUyXaqLS0NIYrEcmCE8sYDwPWxGramdu2bYsePXpApVIxXInIpDixjPEwYE1Mf2e+BqBiZ77vvvugUCjqfjERkYFxYhnjYT+Aiel25s4OVzDQ8TwOplf8YmxIuJaWlWPFjjQ8+ul+rNiRhtKyciPXloisXVMuQEINwxasifUK8cLNjGPorqy4qLqrx50Gv5ZdOURkaJxYxngYsCbWRXkF+X+Gq3NQFzz34MAGv5ZdOURkaJxYxngYsCaUmJiIPbt3A2jaaGHOEUxEZDkYsCaSmJiIhIQEAE0/FYddOUREloMBawL5+fnQaDQAmneeK7tyiIgsBwPWBDw9PTFp0iRcuXIFffv2lbs6RERkAgxYI7p9+zZcXV0BAKGhoQgNDTXp+3OGFiIi+TBgjUSj0WD//v2YOnUqfH19ZakDT+shIpKPTTVnVq1ahdDQUDg7O6NHjx7ScVFD003cf+vWLZw/f94o79EQPK2HiEg+NhOw3377LebOnYuXXnoJR44cwV//+leMGjUKFy9eNOj7VL0qTp8+fQy6/MbgDC1ERPKxmcvVRUVFoXv37vjPf/4jPRYeHo77778fy5Ytq/f1DbnUkbldco7HYImIKvBydUZSXFyMQ4cO4YUXXtB7fPjw4UhKSqrxNUVFRSgqKpLuFxQU1Pke5hauAE/rISKSk000Z65fv46ysjL4+fnpPe7n54fs7OwaX7Ns2TKoVCrpFhgYWOvyy8rK8McffwAwn3AlIiJ52UTA6lS9Yo0Qotar2CxatAharVa6Xbp0qdbl2tvbY/LkyRg7dizDlYiIANhIF7G3tzfs7e2rtVZzcnKqtWp1nJyc4OTkVOdyMzMz0aZNGwCAs7MzunbtapD6EhGR5bOJFqyjoyN69OiB7du36z2+fft2xMTENGmZGo0Gq1evxr59+wxRRSIisjI20YIFgHnz5mHKlCno2bMnoqOj8fHHH+PixYuYOXNmo5dVeUBTeTkvek5ERNXZTMBOmDABubm5ePXVV5GVlYWIiAhs3rwZwcHBjVpOUlIS9u/fD4ADmoiIqHY2cx5sc+nOoXrhhRfg7OzMcCUisiBynAdrE8dgDY3hSkRE9bGZLuLm0jX0e/bsiS5dutQ78QQREZkP3Xe2KTtt2UXcQJmZmXVONkFERObv0qVL0umVxsaAbaDy8nJcuXIF7u7u1SanKCgoQGBgIC5dumSyvn1LwW1TN26funH71I7bpm5Vt48QAjdv3oRarYadnWmOjrKLuIHs7Ozq/dXj4eHBHb0W3DZ14/apG7dP7bht6lZ5+6hUKpO+Nwc5ERERGQEDloiIyAgYsAbg5OSExYsX1zt3sS3itqkbt0/duH1qx21TN3PYPhzkREREZARswRIRERkBA5aIiMgIGLBERERGwIAlIiIyAgZsM61atQqhoaFwdnZGjx49oNFo5K6S0cXHx0OhUOjd/P39peeFEIiPj4darYaLiwsGDhyIEydO6C2jqKgIc+bMgbe3N9zc3DBmzBhkZmaaelUMIjExEaNHj4ZarYZCocDGjRv1njfU9sjLy8OUKVOgUqmgUqkwZcoU5OfnG3ntmq++7TNt2rRq+1OfPn30yljr9lm2bBl69eoFd3d3+Pr64v7778eZM2f0ytjq/tOQbWP2+46gJlu/fr1QKpXik08+ESdPnhR/+9vfhJubm7hw4YLcVTOqxYsXi7/85S8iKytLuuXk5EjPv/HGG8Ld3V388MMP4vjx42LChAkiICBAFBQUSGVmzpwpWrduLbZv3y4OHz4sBg0aJLp06SJKS0vlWKVm2bx5s3jppZfEDz/8IACIH3/8Ue95Q22PkSNHioiICJGUlCSSkpJERESEiI2NNdVqNll92ycuLk6MHDlSb3/Kzc3VK2Ot22fEiBFizZo1IjU1VRw9elTcd999IigoSBQWFkplbHX/aci2Mfd9hwHbDL179xYzZ87Ue6xjx47ihRdekKlGprF48WLRpUuXGp8rLy8X/v7+4o033pAeu3v3rlCpVOLDDz8UQgiRn58vlEqlWL9+vVTm8uXLws7OTmzZssWodTe2qgFiqO1x8uRJAUCkpKRIZZKTkwUAcfr0aSOvleHUFrBjx46t9TW2tH1ycnIEALFnzx4hBPefyqpuGyHMf99hF3ETFRcX49ChQxg+fLje48OHD0dSUpJMtTKdtLQ0qNVqhIaGYuLEiTh//jwAID09HdnZ2XrbxcnJCQMGDJC2y6FDh1BSUqJXRq1WIyIiwuq2naG2R3JyMlQqFaKioqQyffr0gUqlsopttnv3bvj6+qJ9+/aYMWMGcnJypOdsaftotVoAgJeXFwDuP5VV3TY65rzvMGCb6Pr16ygrK4Ofn5/e435+fsjOzpapVqYRFRWFL774Alu3bsUnn3yC7OxsxMTEIDc3V1r3urZLdnY2HB0d0bJly1rLWAtDbY/s7Gz4+vpWW76vr6/Fb7NRo0bh66+/xq5du/DOO+/g4MGDGDx4MIqKigDYzvYRQmDevHno168fIiIiAHD/0alp2wDmv+/wajrNVPXSdUKIao9Zm1GjRkl/R0ZGIjo6GmFhYfj888+lAQZN2S7WvO0MsT1qKm8N22zChAnS3xEREejZsyeCg4Px66+/Yty4cbW+ztq2z+zZs3Hs2DHs3bu32nO2vv/Utm3Mfd9hC7aJvL29YW9vX+0XTk5OTrVfm9bOzc0NkZGRSEtLk0YT17Vd/P39UVxcjLy8vFrLWAtDbQ9/f39cvXq12vKvXbtmddssICAAwcHBSEtLA2Ab22fOnDn4+eefkZCQoHdZTO4/tW+bmpjbvsOAbSJHR0f06NED27dv13t8+/btiImJkalW8igqKsKpU6cQEBCA0NBQ+Pv7622X4uJi7NmzR9ouPXr0gFKp1CuTlZWF1NRUq9t2htoe0dHR0Gq1OHDggFRm//790Gq1VrfNcnNzcenSJQQEBACw7u0jhMDs2bOxYcMG7Nq1C6GhoXrP2/L+U9+2qYnZ7TvNGiJl43Sn6axevVqcPHlSzJ07V7i5uYmMjAy5q2ZU8+fPF7t37xbnz58XKSkpIjY2Vri7u0vr/cYbbwiVSiU2bNggjh8/Lh555JEaTyto06aN2LFjhzh8+LAYPHiwxZ6mc/PmTXHkyBFx5MgRAUC8++674siRI9LpWobaHiNHjhSdO3cWycnJIjk5WURGRpr1aRY6dW2fmzdvivnz54ukpCSRnp4uEhISRHR0tGjdurVNbJ+nn35aqFQqsXv3br1TTW7fvi2VsdX9p75tYwn7DgO2mVauXCmCg4OFo6Oj6N69u94QcmulOw9PqVQKtVotxo0bJ06cOCE9X15eLhYvXiz8/f2Fk5OT6N+/vzh+/LjeMu7cuSNmz54tvLy8hIuLi4iNjRUXL1409aoYREJCggBQ7RYXFyeEMNz2yM3NFZMnTxbu7u7C3d1dTJ48WeTl5ZloLZuuru1z+/ZtMXz4cOHj4yOUSqUICgoScXFx1dbdWrdPTdsFgFizZo1Uxlb3n/q2jSXsO7xcHRERkRHwGCwREZERMGCJiIiMgAFLRERkBAxYIiIiI2DAEhERGQEDloiIyAgYsEREREbAgCUiIjICBiyRFRBCYOjQoRgxYkS151atWgWVSoVXX30Vnp6eBn3f3bt3Q6FQID8/36DLJbIGDFgiK6BQKLBmzRrs378fH330kfR4eno6/v73v2PFihUICgqSsYZEtocBS2QlAgMDsWLFCixYsADp6ekQQuDxxx/HkCFDEBISgunTp0Or1UKhUEChUCA+Ph5AxdVZFi5ciNatW8PNzQ1RUVHYvXu3tNwLFy5g9OjRaNmyJdzc3PCXv/wFmzdvRkZGBgYNGgQAaNmyJRQKBaZNm2b6FScyU7zgOpEViYuLw48//ojp06dj/PjxSE1NRWpqKjw9PbF8+XK88sorOHPmDACgRYsWAIDp06cjIyMD69evh1qtxo8//oiRI0fi+PHjaNeuHWbNmoXi4mIkJibCzc0NJ0+eRIsWLRAYGIgffvgB48ePx5kzZ+Dh4QEXFxc5V5/IrDBgiazMxx9/jIiICGg0Gnz//ffw9fUFAKhUKigUCuki3gBw7tw5rFu3DpmZmVCr1QCABQsWYMuWLVizZg2WLl2KixcvYvz48YiMjAQA3HPPPdLrvby8AAC+vr4GP75LZOkYsERWxtfXF08++SQ2btyIBx54oM6yhw8fhhAC7du313u8qKgIrVq1AgA8++yzePrpp7Ft2zYMHToU48ePR+fOnY1WfyJrwYAlskIODg5wcKj/411eXg57e3scOnQI9vb2es/pupCfeOIJjBgxAr/++iu2bduGZcuW4Z133sGcOXOMUncia8FBTkQ2wtHREWVlZXqPdevWDWVlZcjJyUHbtm31bpW7kgMDAzFz5kxs2LAB8+fPxyeffCItE0C15RIRA5bIZoSEhKCwsBA7d+7E9evXcfv2bbRv3x6TJ0/G1KlTsWHDBqSnp+PgwYN48803sXnzZgDA3LlzsXXrVqSnp+Pw4cPYtWsXwsPDAQDBwcFQKBTYtGkTrl27hsLCQjlXkcisMGCJbERMTAxmzpyJCRMmwMfHB2+99RYAYM2aNZg6dSrmz5+PDh06YMyYMdi/fz8CAwMBVLROZ82ahfDwcIwcORIdOnTAqlWrAACtW7fGkiVL8MILL8DPzw+zZ8+Wbf2IzI1CCCHkrgQREZG1YQuWiIjICBiwRERERsCAJSIiMgIGLBERkREwYImIiIyAAUtERGQEDFgiIiIjYMASEREZAQOWiIjICBiwRERERsCAJSIiMgIGLBERkRH8H3epq7D7oM6uAAAAAElFTkSuQmCC"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 57
   },
   {
    "cell_type": "markdown",
@@ -1834,28 +2504,79 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:36:13.030607Z",
+     "start_time": "2025-03-26T10:36:13.024105Z"
+    }
+   },
    "source": [
-    "# answer for Optional Exercise 3\n"
-   ]
+    "from sklearn.metrics import mean_squared_error\n",
+    "\n",
+    "MSEs = []\n",
+    "for name, estimator in zip([\"LassoCV\", \"LassoBIC\", \"RidgeCV\", \"OLS\"], [lassoCV, lassoBIC, ridgeCV, linReg]):\n",
+    "    y_pred = estimator.predict(Xtest)\n",
+    "    MSE = mean_squared_error(Ytest, y_pred)\n",
+    "    print(f\"MSE for {name} : {MSE}\")\n",
+    "    MSEs.append(MSE)\n",
+    "\n",
+    "print(np.min(MSEs))"
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "MSE for LassoCV : 8747438999.11095\n",
+      "MSE for LassoBIC : 13652129197.771055\n",
+      "MSE for RidgeCV : 34959235357.833115\n",
+      "MSE for OLS : 150074.5486842357\n",
+      "150074.5486842357\n"
+     ]
+    }
+   ],
+   "execution_count": 58
   },
   {
    "cell_type": "markdown",
    "metadata": {},
-   "source": [
-    "**Optional Exercise 4** Display the boxplot of the absolute errors for each estimator.   "
-   ]
+   "source": "**Optional Exercise 4** Display the boxplot of the absolute errors for each estimator."
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-03-26T10:35:27.401569Z",
+     "start_time": "2025-03-26T10:35:27.297762Z"
+    }
+   },
    "source": [
-    "# answer for Optional  Exercise 4\n"
-   ]
+    "# Boxplot the absolute error for LassoCV, LassoBIC, RidgeCV, OLS\n",
+    "ridge_cv_errors = np.abs(Ytest - ridgeCV.predict(Xtest))\n",
+    "lasso_cv_errors = np.abs(Ytest - lassoCV.predict(Xtest))\n",
+    "lasso_bic_errors = np.abs(Ytest - lassoBIC.predict(Xtest))\n",
+    "ols_errors = np.abs(Ytest - linReg.predict(Xtest))\n",
+    "\n",
+    "fig, ax = plt.subplots(figsize=(10, 6))\n",
+    "ax.boxplot([ridge_cv_errors, lasso_cv_errors, lasso_bic_errors, ols_errors],\n",
+    "           labels=['RidgeCV', 'LassoCV', 'LassoBIC', 'OLS'])\n",
+    "ax.set_title('Boxplot of Absolute Errors')\n",
+    "ax.set_ylabel('Absolute Error')\n",
+    "plt.show()"
+   ],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 52
   },
   {
    "cell_type": "markdown",