diff --git a/.python-version b/.python-version index e4fba21..24ee5b1 100644 --- a/.python-version +++ b/.python-version @@ -1 +1 @@ -3.12 +3.13 diff --git a/L3/Analyse Matricielle/TP1_Methode_de_Gauss.ipynb b/L3/Analyse Matricielle/TP1_Methode_de_Gauss.ipynb index d27af6e..bb774a4 100644 --- a/L3/Analyse Matricielle/TP1_Methode_de_Gauss.ipynb +++ b/L3/Analyse Matricielle/TP1_Methode_de_Gauss.ipynb @@ -76,24 +76,40 @@ ], "source": [ "import numpy as np\n", + "\n", "%matplotlib inline\n", - "import matplotlib.pyplot as plt\n", "\n", "\n", - "u = np.array([1,2,3,4,5])\n", - "v = np.array([[1,2,3,4,5]])\n", - "su=u.shape\n", - "sv=v.shape\n", + "u = np.array([1, 2, 3, 4, 5])\n", + "v = np.array([[1, 2, 3, 4, 5]])\n", + "su = u.shape\n", + "sv = v.shape\n", "ut = np.transpose(u)\n", "vt = np.transpose(v)\n", - "vt2 = np.array([[1],[2],[3],[4],[5]])\n", - "A = np.array([[1,2,0,0,0],[0,2,0,0,0],[0,0,3,0,0],[0,0,0,4,0],[0,0,0,0,5]])\n", - "B = np.array([[1,2,3,4,5],[2,3,4,5,6],[3,4,5,6,7],[4,5,6,7,8],[5,6,7,8,9]])\n", - "d=np.diag(A)\n", - "dd=np.array([np.diag(A)])\n", - "dt=np.transpose(d)\n", - "ddt=np.transpose(dd)\n", - "Ad=np.diag(np.diag(A))\n", + "vt2 = np.array([[1], [2], [3], [4], [5]])\n", + "A = np.array(\n", + " [\n", + " [1, 2, 0, 0, 0],\n", + " [0, 2, 0, 0, 0],\n", + " [0, 0, 3, 0, 0],\n", + " [0, 0, 0, 4, 0],\n", + " [0, 0, 0, 0, 5],\n", + " ]\n", + ")\n", + "B = np.array(\n", + " [\n", + " [1, 2, 3, 4, 5],\n", + " [2, 3, 4, 5, 6],\n", + " [3, 4, 5, 6, 7],\n", + " [4, 5, 6, 7, 8],\n", + " [5, 6, 7, 8, 9],\n", + " ]\n", + ")\n", + "d = np.diag(A)\n", + "dd = np.array([np.diag(A)])\n", + "dt = np.transpose(d)\n", + "ddt = np.transpose(dd)\n", + "Ad = np.diag(np.diag(A))\n", "\n", "print(np.dot(np.linalg.inv(A), A))" ] @@ -138,11 +154,11 @@ " x = 0 * b\n", " n = len(b)\n", " if np.allclose(A, np.triu(A)):\n", - " for i in range(n-1, -1, -1):\n", - " x[i] = (b[i] - np.dot(A[i,i+1:], x[i+1:])) / A[i,i]\n", + " for i in range(n - 1, -1, -1):\n", + " x[i] = (b[i] - np.dot(A[i, i + 1 :], x[i + 1 :])) / A[i, i]\n", " elif np.allclose(A, np.tril(A)):\n", " for i in range(n):\n", - " x[i] = (b[i] - np.dot(A[i,:i], x[:i])) / A[i,i]\n", + " x[i] = (b[i] - np.dot(A[i, :i], x[:i])) / A[i, i]\n", " else:\n", " raise ValueError(\"A est ni triangulaire supérieure ni triangulaire inférieure\")\n", " return x" @@ -171,7 +187,7 @@ "b = np.dot(A, xe)\n", "x = remontee_descente(A, b)\n", "\n", - "print(np.dot(x - xe, x-xe))" + "print(np.dot(x - xe, x - xe))" ] }, { @@ -263,9 +279,9 @@ " U = A\n", " n = len(A)\n", " for j in range(n):\n", - " for i in range(j+1, n):\n", - " beta = U[i,j]/U[j,j]\n", - " U[i,j:] = U[i,j:] - beta * U[j, j:]\n", + " for i in range(j + 1, n):\n", + " beta = U[i, j] / U[j, j]\n", + " U[i, j:] = U[i, j:] - beta * U[j, j:]\n", " return U" ] }, @@ -282,14 +298,16 @@ " if n != m:\n", " raise ValueError(\"Erreur de dimension : A doit etre carré\")\n", " if n != b.size:\n", - " raise valueError(\"Erreur de dimension : le nombre de lignes de A doit être égal au nombr ede colonnes de b\")\n", - " U = np.zeros((n, n+1))\n", + " raise valueError(\n", + " \"Erreur de dimension : le nombre de lignes de A doit être égal au nombr ede colonnes de b\"\n", + " )\n", + " U = np.zeros((n, n + 1))\n", " U = A\n", " V = b\n", " for j in range(n):\n", - " for i in range(j+1, n):\n", - " beta = U[i,j]/U[j,j]\n", - " U[i,j:] = U[i,j:] - beta * U[j, j:]\n", + " for i in range(j + 1, n):\n", + " beta = U[i, j] / U[j, j]\n", + " U[i, j:] = U[i, j:] - beta * U[j, j:]\n", " V[i] = V[i] - beta * V[j]\n", " return remontee_descente(U, V)" ] diff --git a/L3/Calculs Numériques/DM1.ipynb b/L3/Calculs Numériques/DM1.ipynb index b1388cb..4f9756f 100644 --- a/L3/Calculs Numériques/DM1.ipynb +++ b/L3/Calculs Numériques/DM1.ipynb @@ -9,9 +9,9 @@ "%matplotlib inline\n", "%config InlineBackend.figure_format = 'retina'\n", "\n", - "import numpy as np # pour les numpy array\n", - "import matplotlib.pyplot as plt # librairie graphique\n", - "from scipy.integrate import odeint # seulement odeint" + "import numpy as np # pour les numpy array\n", + "import matplotlib.pyplot as plt # librairie graphique\n", + "from scipy.integrate import odeint # seulement odeint" ] }, { @@ -103,13 +103,14 @@ "source": [ "# Initialisation des variables\n", "T = 130\n", - "t = np.arange(0, T+1)\n", + "t = np.arange(0, T + 1)\n", "\n", - "K = 50 # capacité d'accueil maximale du milieu\n", + "K = 50 # capacité d'accueil maximale du milieu\n", "K_star = 50 # capacité minimale pour maintenir l'espèce\n", - "r = 0.1 # taux de corissance de la capacité d'accueil du milieu.\n", - "t_fl = 30 # la find ed la période de formation.\n", - "K0 = 1 # Valeur initiale de la capacité d'accueil du milieu.\n", + "r = 0.1 # taux de corissance de la capacité d'accueil du milieu.\n", + "t_fl = 30 # la find ed la période de formation.\n", + "K0 = 1 # Valeur initiale de la capacité d'accueil du milieu.\n", + "\n", "\n", "def C(t):\n", " \"\"\"\n", @@ -117,11 +118,12 @@ " \"\"\"\n", " return K_star + K / (1 + (K / K0 - 1) * np.exp(-r * (t - t_fl)))\n", "\n", + "\n", "# On trace le graphique de la solution exacte\n", "plt.plot(t, C(t), label=\"C(t)\")\n", - "plt.hlines(K_star, 0, T, linestyle='dotted', label=\"C = K*\", color='red')\n", - "plt.hlines(K + K_star, 0, T, linestyle='dotted', label=\"C = K + K*\", color='green')\n", - "plt.plot(t_fl, K0 + K_star, 'o', label=\"(t_fl, K0 + K*)\")\n", + "plt.hlines(K_star, 0, T, linestyle=\"dotted\", label=\"C = K*\", color=\"red\")\n", + "plt.hlines(K + K_star, 0, T, linestyle=\"dotted\", label=\"C = K + K*\", color=\"green\")\n", + "plt.plot(t_fl, K0 + K_star, \"o\", label=\"(t_fl, K0 + K*)\")\n", "plt.legend()\n", "plt.xlim(0, 130)\n", "plt.suptitle(\"Courbe de la solution exacte du problème\")\n", @@ -133,14 +135,16 @@ "N0 = 10\n", "r_N = 0.2\n", "\n", + "\n", "def dN(N, t, C_sol):\n", " \"\"\"\n", " Fonction calculant la dérivée de la solution approchée du problème à l'instant t dépendant de N(t) et de C(t)\n", " \"\"\"\n", " return r_N * N * (1 - N / C_sol(t))\n", "\n", + "\n", "t = np.linspace(0, T, 200)\n", - "N_sol = odeint(dN, N0, t, args=(C,)) # On calcule la solution a l'aide de odeint\n", + "N_sol = odeint(dN, N0, t, args=(C,)) # On calcule la solution a l'aide de odeint\n", "\n", "# On trace le graphique de la solution approchée en comparaison à la solution exacte\n", "plt.plot(t, N_sol, label=\"Solution approchée\")\n", @@ -219,42 +223,47 @@ "T, N = 200, 100\n", "H0, P0 = 1500, 500\n", "\n", + "\n", "def F(X, t, a, b, c, d, p):\n", " \"\"\"Fonction second membre pour le système\"\"\"\n", " x, y = X\n", - " return np.array([x * (a - p - b*y), y * (-c - p + d*x)])\n", + " return np.array([x * (a - p - b * y), y * (-c - p + d * x)])\n", "\n", - "t = np.linspace(0, T, N+1)\n", - "sardines, requins = np.meshgrid(\n", - " np.linspace(0.1, 3000, 20),\n", - " np.linspace(0.1, 4500, 30)\n", - ")\n", + "\n", + "t = np.linspace(0, T, N + 1)\n", + "sardines, requins = np.meshgrid(np.linspace(0.1, 3000, 20), np.linspace(0.1, 4500, 30))\n", "fsardines = F((sardines, requins), t, a, b, c, d, 0)[0]\n", "frequins = F((sardines, requins), t, a, b, c, d, 0)[1]\n", - "n_sndmb = np.sqrt(fsardines**2 + frequins**2) \n", + "n_sndmb = np.sqrt(fsardines**2 + frequins**2)\n", "\n", "# On crée une figure à trois graphiques\n", "fig = plt.figure(figsize=(12, 6))\n", - "ax = fig.add_subplot(1, 2, 2) # subplot pour le champ de vecteurs et le graphe sardines vs requins\n", - "axr = fig.add_subplot(2, 2, 1) # subplot pour le graphe du nombre de requins en fonction du temps\n", - "axs = fig.add_subplot(2, 2, 3) # subplot pour le graphe du nombre de sardines en fonction du temps \n", - "ax.quiver(sardines, requins, fsardines/n_sndmb, frequins/n_sndmb)\n", + "ax = fig.add_subplot(\n", + " 1, 2, 2\n", + ") # subplot pour le champ de vecteurs et le graphe sardines vs requins\n", + "axr = fig.add_subplot(\n", + " 2, 2, 1\n", + ") # subplot pour le graphe du nombre de requins en fonction du temps\n", + "axs = fig.add_subplot(\n", + " 2, 2, 3\n", + ") # subplot pour le graphe du nombre de sardines en fonction du temps\n", + "ax.quiver(sardines, requins, fsardines / n_sndmb, frequins / n_sndmb)\n", "\n", "list_p = [0, 0.02, 0.04, 0.06]\n", "for k, pk in enumerate(list_p):\n", - " couleur = (0, k/len(list_p), 1-k/len(list_p))\n", + " couleur = (0, k / len(list_p), 1 - k / len(list_p))\n", " X = odeint(F, np.array([H0, P0]), t, args=(a, b, c, d, pk))\n", - " \n", - " # Tracer la courbe parametrée (H(t),P(t)) \n", + "\n", + " # Tracer la courbe parametrée (H(t),P(t))\n", " ax.plot(X[:, 0], X[:, 1], linewidth=2, color=couleur, label=f\"$p={pk}$\")\n", - " \n", - " # Tracer H en fonction du temps \n", + "\n", + " # Tracer H en fonction du temps\n", " axs.plot(t, X[:, 0], label=f\"Sardines pour p={pk}\", color=couleur)\n", - " \n", + "\n", " # Tracer P en fonction du temps\n", " axr.plot(t, X[:, 1], label=f\"Requins pour p={pk}\", color=couleur)\n", - " \n", - "ax.axis('equal')\n", + "\n", + "ax.axis(\"equal\")\n", "ax.set_title(\"Champ de vecteur du problème de Lotka-Volterra\")\n", "ax.set_xlabel(\"Sardines\")\n", "ax.set_ylabel(\"Requins\")\n", @@ -266,8 +275,8 @@ "axs.set_xlabel(\"Temps t\")\n", "axs.set_ylabel(\"Sardines\")\n", "\n", - "axs.set_title('Evolution des sardines')\n", - "axr.set_title('Evolution des requins')\n", + "axs.set_title(\"Evolution des sardines\")\n", + "axr.set_title(\"Evolution des requins\")\n", "plt.show()" ] }, @@ -309,11 +318,11 @@ "source": [ "def crank_nicolson(y0, T, N, r):\n", " \"\"\"\n", - " schéma de Crank-Nicolson pour le modèle de Malthus \n", - " \n", + " schéma de Crank-Nicolson pour le modèle de Malthus\n", + "\n", " Parameters\n", " ----------\n", - " \n", + "\n", " y0: float\n", " donnée initiale\n", " T: float\n", @@ -325,34 +334,35 @@ "\n", " Returns\n", " -------\n", - " \n", + "\n", " t: ndarray\n", " les instants où la solution approchée est calculée\n", " y: ndarray\n", " les valeurs de la solution approchée par le theta-schema\n", " \"\"\"\n", - " \n", + "\n", " dt = T / N\n", - " t = np.zeros(N+1)\n", - " y = np.zeros(N+1)\n", + " t = np.zeros(N + 1)\n", + " y = np.zeros(N + 1)\n", " tk, yk = 0, y0\n", " y[0] = yk\n", - " \n", + "\n", " for n in range(N):\n", " tk += dt\n", " yk *= (2 + dt * r) / (2 - dt * r)\n", - " y[n+1] = yk\n", - " t[n+1] = tk\n", - " \n", + " y[n + 1] = yk\n", + " t[n + 1] = tk\n", + "\n", " return t, y\n", "\n", + "\n", "def euler_explicit(y0, T, N, r):\n", " \"\"\"\n", - " schéma de d'Euler pour le modèle de Malthus \n", - " \n", + " schéma de d'Euler pour le modèle de Malthus\n", + "\n", " Parameters\n", " ----------\n", - " \n", + "\n", " y0: float\n", " donnée initiale\n", " T: float\n", @@ -364,29 +374,30 @@ "\n", " Returns\n", " -------\n", - " \n", + "\n", " t: ndarray\n", " les instants où la solution approchée est calculée\n", " y: ndarray\n", " les valeurs de la solution approchée par le theta-schema\n", " \"\"\"\n", " dt = T / N\n", - " t = np.zeros(N+1)\n", - " y = np.zeros(N+1)\n", + " t = np.zeros(N + 1)\n", + " y = np.zeros(N + 1)\n", " tk, yk = 0, y0\n", " y[0] = yk\n", - " \n", + "\n", " for n in range(N):\n", " tk += dt\n", " yk += dt * r * yk\n", - " y[n+1] = yk\n", - " t[n+1] = tk\n", - " \n", + " y[n + 1] = yk\n", + " t[n + 1] = tk\n", + "\n", " return t, y\n", "\n", + "\n", "def solution_exacte(t):\n", " \"\"\"\n", - " Fonction calculant la solution exacte du modèle de Malthus à l'instant t \n", + " Fonction calculant la solution exacte du modèle de Malthus à l'instant t\n", " \"\"\"\n", " return y0 * np.exp(r * t)" ] @@ -436,23 +447,25 @@ "# Schéma d'Euler explicite\n", "ax = fig.add_subplot(1, 2, 1)\n", "for n in liste_N:\n", - " t, y = euler_explicit(y0, T, n, r) # On calcule la fonction Euler pour chaque n\n", + " t, y = euler_explicit(y0, T, n, r) # On calcule la fonction Euler pour chaque n\n", " ax.scatter(t, y, label=f\"Solution approchée pour N={n}\")\n", - " \n", - "ax.plot(t_exact, solution_exacte(t_exact), label='Solution exacte')\n", + "\n", + "ax.plot(t_exact, solution_exacte(t_exact), label=\"Solution exacte\")\n", "ax.legend()\n", - "ax.axis('equal')\n", + "ax.axis(\"equal\")\n", "ax.set_title(\"Schéma d'Euler explicite\")\n", "ax.set_xlabel(\"Temps t\")\n", "ax.set_ylabel(\"y\")\n", - " \n", + "\n", "\n", "# Schéma de Crank-Nicolson\n", "ax = fig.add_subplot(1, 2, 2)\n", "for n in liste_N:\n", - " t, y = crank_nicolson(y0, T, n, r) # On calcule la fonction Crank-Nicolson pour chaque n\n", + " t, y = crank_nicolson(\n", + " y0, T, n, r\n", + " ) # On calcule la fonction Crank-Nicolson pour chaque n\n", " ax.scatter(t, y, label=f\"Solution approchée pour N={n}\")\n", - "ax.plot(t_exact, solution_exacte(t_exact), label='Solution exacte')\n", + "ax.plot(t_exact, solution_exacte(t_exact), label=\"Solution exacte\")\n", "ax.legend()\n", "ax.set_title(\"Schéma de Crank-Nicolson\")\n", "ax.set_xlabel(\"Temps t\")\n", @@ -504,7 +517,7 @@ " t, sol_appr = crank_nicolson(y0, T, n, r)\n", " sol_ex = solution_exacte(t)\n", " erreur = np.max(np.abs(sol_appr - sol_ex))\n", - " #erreur = np.linalg.norm(sol_appr - sol_ex, np.inf)\n", + " # erreur = np.linalg.norm(sol_appr - sol_ex, np.inf)\n", " print(f\"Delta_t = {T / N:10.3e}, e = {erreur:10.3e}\")\n", " liste_erreur[k] = erreur\n", "\n", @@ -514,7 +527,7 @@ "ax.scatter(liste_delta, liste_erreur, color=\"black\")\n", "for p in [0.5, 1, 2]:\n", " C = liste_erreur[-1] / (liste_delta[-1] ** p)\n", - " plt.plot(liste_delta, C * liste_delta ** p, label=f\"$p={p}$\")\n", + " plt.plot(liste_delta, C * liste_delta**p, label=f\"$p={p}$\")\n", "ax.set_title(\"Erreur du schéma de Crank-Nicolson\")\n", "ax.set_xlabel(r\"$\\Delta t$\")\n", "ax.set_ylabel(r\"$e(\\Delta t)$\")\n", diff --git a/L3/Calculs Numériques/DM2.ipynb b/L3/Calculs Numériques/DM2.ipynb index d232d8f..85f719a 100644 --- a/L3/Calculs Numériques/DM2.ipynb +++ b/L3/Calculs Numériques/DM2.ipynb @@ -153,22 +153,27 @@ "def M(x):\n", " \"\"\"\n", " Retourne la matrice du système (2)\n", - " \n", + "\n", " Parameters\n", " ----------\n", - " \n", + "\n", " x: ndarray\n", " vecteurs contenant les valeurs [x0, x1, ..., xN]\n", - " \n", + "\n", " Returns\n", " -------\n", - " \n", + "\n", " out: ndarray\n", " matrice du système (2)\n", " \"\"\"\n", - " h = x[1:] - x[:-1] # x[i+1] - x[i]\n", - " return np.diag(2*(1/h[:-1] + 1/h[1:])) + np.diag(1/h[1:-1], k=-1) + np.diag(1/h[1:-1], k=1)\n", - " \n", + " h = x[1:] - x[:-1] # x[i+1] - x[i]\n", + " return (\n", + " np.diag(2 * (1 / h[:-1] + 1 / h[1:]))\n", + " + np.diag(1 / h[1:-1], k=-1)\n", + " + np.diag(1 / h[1:-1], k=1)\n", + " )\n", + "\n", + "\n", "# Test\n", "print(M(np.array([0, 1, 2, 3, 4])))" ] @@ -191,10 +196,10 @@ "def sprime(x, y, p0, pN):\n", " \"\"\"\n", " Retourne la solution du système (2)\n", - " \n", + "\n", " Parameters\n", " ----------\n", - " \n", + "\n", " x: ndarray\n", " vecteurs contenant les valeurs [x0, x1, ..., xN]\n", " y: ndarray\n", @@ -203,18 +208,18 @@ " première valeur du vecteur p\n", " pN: int\n", " N-ième valeur du vecteur p\n", - " \n", + "\n", " Returns\n", " -------\n", - " \n", + "\n", " out: ndarray\n", " solution du système (2)\n", " \"\"\"\n", " h = x[1:] - x[:-1]\n", " delta_y = (y[1:] - y[:-1]) / h\n", - " c = 3 * (delta_y[1:]/h[1:] + delta_y[:-1]/h[:-1])\n", - " c[0] -= p0/h[0]\n", - " c[-1] -= pN/h[-1]\n", + " c = 3 * (delta_y[1:] / h[1:] + delta_y[:-1] / h[:-1])\n", + " c[0] -= p0 / h[0]\n", + " c[-1] -= pN / h[-1]\n", " return np.linalg.solve(M(x), c)" ] }, @@ -273,52 +278,54 @@ "def f(x):\n", " \"\"\"\n", " Retourne la fonction f évaluée aux points x\n", - " \n", + "\n", " Parameters\n", " ----------\n", - " \n", + "\n", " x: ndarray\n", " vecteurs contenant les valeurs [x0, x1, ..., xN]\n", - " \n", + "\n", " Returns\n", " -------\n", - " \n", + "\n", " out: ndarray\n", " Valeur de la fonction f aux points x\n", " \"\"\"\n", " return 1 / (1 + x**2)\n", "\n", + "\n", "def fprime(x):\n", " \"\"\"\n", " Retourne la fonction dérivée de f évaluée aux points x\n", - " \n", + "\n", " Parameters\n", " ----------\n", - " \n", + "\n", " x: ndarray\n", " vecteurs contenant les valeurs [x0, x1, ..., xN]\n", - " \n", + "\n", " Returns\n", " -------\n", - " \n", + "\n", " out: ndarray\n", " Valeur de la fonction dérivée de f aux points x\n", " \"\"\"\n", - " return -2*x/((1+x**2)**2)\n", + " return -2 * x / ((1 + x**2) ** 2)\n", "\n", - "# Paramètres \n", + "\n", + "# Paramètres\n", "xx = np.linspace(-5, 5, 200)\n", "x = np.linspace(-5, 5, 21)\n", "pi = sprime(x, f(x), fprime(-5), fprime(5))\n", "\n", "# Graphique\n", "fig, ax = plt.subplots(figsize=(6, 6))\n", - "ax.plot(xx, fprime(xx), label=f'$f\\'$', color='red')\n", - "ax.scatter(x[1:-1], pi, label=f'$p_i$')\n", + "ax.plot(xx, fprime(xx), label=\"$f'$\", color=\"red\")\n", + "ax.scatter(x[1:-1], pi, label=\"$p_i$\")\n", "ax.legend()\n", - "ax.set_xlabel(f'$x$')\n", - "ax.set_ylabel(f'$f(x)$')\n", - "ax.set_title('Les pentes de la spline cubique')" + "ax.set_xlabel(\"$x$\")\n", + "ax.set_ylabel(\"$f(x)$\")\n", + "ax.set_title(\"Les pentes de la spline cubique\")" ] }, { @@ -363,10 +370,10 @@ "def splines(x, y, p0, pN):\n", " \"\"\"\n", " Retourne la matrice S de taille (4, N)\n", - " \n", + "\n", " Parameters\n", " ----------\n", - " \n", + "\n", " x: ndarray\n", " vecteurs contenant les valeurs [x0, x1, ..., xN]\n", " y: ndarray\n", @@ -375,20 +382,20 @@ " première valeur du vecteur p\n", " pN: int\n", " N-ième valeur du vecteur p\n", - " \n", + "\n", " Returns\n", " -------\n", - " \n", + "\n", " out: ndarray\n", " Matrice S de taille (4, N) tel que la i-ième ligne contient les valeurs a_i, b_i, c_i et d_i\n", " \"\"\"\n", " h = x[1:] - x[:-1]\n", " delta_y = (y[1:] - y[:-1]) / h\n", - " \n", + "\n", " a = y\n", " b = np.concatenate((np.array([p0]), sprime(x, y, p0, pN), np.array([pN])))\n", - " c = 3/h * delta_y - (b[1:] + 2*b[:-1]) / h\n", - " d = 1/h**2 * (b[1:] + b[:-1]) - 2/h**2 * delta_y\n", + " c = 3 / h * delta_y - (b[1:] + 2 * b[:-1]) / h\n", + " d = 1 / h**2 * (b[1:] + b[:-1]) - 2 / h**2 * delta_y\n", " return np.transpose([a[:-1], b[:-1], c, d])" ] }, @@ -412,34 +419,38 @@ }, "outputs": [], "source": [ - "def spline_eval( x, xx, S ):\n", + "def spline_eval(x, xx, S):\n", " \"\"\"\n", " Evalue une spline définie par des noeuds équirepartis\n", - " \n", + "\n", " Parameters\n", " ----------\n", - " \n", + "\n", " x: ndarray\n", " noeuds définissant la spline\n", - " \n", + "\n", " xx: ndarray\n", " abscisses des points d'évaluation\n", - " \n", + "\n", " S: ndarray\n", " de taille (x.size-1, 4)\n", " tableau dont la i-ème ligne contient les coéficients du polynome cubique qui est la restriction\n", " de la spline à l'intervalle [x_i, x_{i+1}]\n", - " \n", + "\n", " Returns\n", " -------\n", - " \n", + "\n", " ndarray\n", " ordonnées des points d'évaluation\n", " \"\"\"\n", - " ind = ( np.floor( ( xx - x[ 0 ] ) / ( x[ 1 ] - x[ 0 ] ) ) ).astype( int )\n", - " ind = np.where( ind == x.size-1, ind - 1 , ind )\n", - " yy = S[ ind, 0 ] + S[ ind, 1 ] * ( xx - x[ ind ] ) + \\\n", - " S[ ind, 2 ] * ( xx - x[ ind ] )**2 + S[ ind, 3 ] * ( xx - x[ ind ] )**3\n", + " ind = (np.floor((xx - x[0]) / (x[1] - x[0]))).astype(int)\n", + " ind = np.where(ind == x.size - 1, ind - 1, ind)\n", + " yy = (\n", + " S[ind, 0]\n", + " + S[ind, 1] * (xx - x[ind])\n", + " + S[ind, 2] * (xx - x[ind]) ** 2\n", + " + S[ind, 3] * (xx - x[ind]) ** 3\n", + " )\n", " return yy" ] }, @@ -472,21 +483,21 @@ } ], "source": [ - "# Paramètres \n", + "# Paramètres\n", "x = np.linspace(-5, 5, 6)\n", - "y = np.random.rand(5+1)\n", + "y = np.random.rand(5 + 1)\n", "xx = np.linspace(-5, 5, 200)\n", "s = splines(x, y, 0, 0)\n", "s_eval = spline_eval(x, xx, s)\n", "\n", "# Graphique\n", "fig, ax = plt.subplots(figsize=(6, 6))\n", - "ax.plot(xx, s_eval, label='spline cubique interpolateur', color='red')\n", - "ax.scatter(x, y, label=f'$(x_i, y_i)$')\n", + "ax.plot(xx, s_eval, label=\"spline cubique interpolateur\", color=\"red\")\n", + "ax.scatter(x, y, label=\"$(x_i, y_i)$\")\n", "ax.legend()\n", - "ax.set_xlabel(f'$x$')\n", - "ax.set_ylabel(f'$f(x)$')\n", - "ax.set_title('Evaluation de la spline cubique')" + "ax.set_xlabel(\"$x$\")\n", + "ax.set_ylabel(\"$f(x)$\")\n", + "ax.set_title(\"Evaluation de la spline cubique\")" ] }, { @@ -525,7 +536,7 @@ } ], "source": [ - "# Paramètres \n", + "# Paramètres\n", "a, b = -5, 5\n", "N_list = [4, 9, 19]\n", "\n", @@ -533,17 +544,17 @@ "fig, ax = plt.subplots(figsize=(15, 6))\n", "\n", "for N in N_list:\n", - " x = np.linspace(a, b, N+1)\n", + " x = np.linspace(a, b, N + 1)\n", " xx = np.linspace(a, b, 200)\n", " s = splines(x, f(x), 0, 0)\n", " s_eval = spline_eval(x, xx, s)\n", - " ax.plot(xx, s_eval, label=f'Spline cubique interpolateur pour N={N}')\n", - " ax.scatter(x, f(x), label=f'f(x) pour N={N}')\n", - " \n", + " ax.plot(xx, s_eval, label=f\"Spline cubique interpolateur pour N={N}\")\n", + " ax.scatter(x, f(x), label=f\"f(x) pour N={N}\")\n", + "\n", "ax.legend()\n", - "ax.set_xlabel(f'$x$')\n", - "ax.set_ylabel(f'$f(x)$')\n", - "ax.set_title('Evaluation de la spline cubique')" + "ax.set_xlabel(\"$x$\")\n", + "ax.set_ylabel(\"$f(x)$\")\n", + "ax.set_title(\"Evaluation de la spline cubique\")" ] }, { diff --git a/L3/Calculs Numériques/DM3.ipynb b/L3/Calculs Numériques/DM3.ipynb index 841a81c..d0af957 100644 --- a/L3/Calculs Numériques/DM3.ipynb +++ b/L3/Calculs Numériques/DM3.ipynb @@ -60,17 +60,20 @@ }, "outputs": [], "source": [ - "def f0(x): \n", + "def f0(x):\n", " return np.exp(x)\n", "\n", + "\n", "def f1(x):\n", - " return 1 / (1 + 16*np.power(x, 2))\n", + " return 1 / (1 + 16 * np.power(x, 2))\n", + "\n", "\n", "def f2(x):\n", - " return np.power(np.abs(x**2 - 1/4), 3)\n", + " return np.power(np.abs(x**2 - 1 / 4), 3)\n", + "\n", "\n", "def f3(x):\n", - " return np.power(np.abs(x+1/2), 1/2)" + " return np.power(np.abs(x + 1 / 2), 1 / 2)" ] }, { @@ -176,10 +179,12 @@ ], "source": [ "for f in [f0, f1, f2, f3]:\n", - " print(f'Calcule de I(f) par la méthode de gauss et par la formule quadratique pour la fonction {f.__name__}')\n", + " print(\n", + " f\"Calcule de I(f) par la méthode de gauss et par la formule quadratique pour la fonction {f.__name__}\"\n", + " )\n", " for n in range(1, 11):\n", " print(f\"Pour n = {n}, gauss = {gauss(f, n)} et quad = {quad(f, -1, 1)[0]}\")\n", - " print('')" + " print(\"\")" ] }, { @@ -211,10 +216,10 @@ "def simpson(f, N):\n", " if N % 2 == 0:\n", " raise ValueError(\"N doit est impair.\")\n", - " \n", + "\n", " h = 2 / (2 * (N - 1) // 2)\n", " fx = f(np.linspace(-1, 1, N))\n", - " \n", + "\n", " return (h / 3) * (fx[0] + 4 * fx[1:-1:2].sum() + 2 * fx[2:-1:2].sum() + fx[-1])" ] }, @@ -270,10 +275,12 @@ ], "source": [ "for f in [f0, f1, f2, f3]:\n", - " print(f'Calcule de I(f) par la méthode de simpson et par la formule quadratique pour la fonction {f.__name__}')\n", + " print(\n", + " f\"Calcule de I(f) par la méthode de simpson et par la formule quadratique pour la fonction {f.__name__}\"\n", + " )\n", " for n in range(3, 16, 2):\n", " print(f\"Pour n = {n}, simpson = {simpson(f, n)} et quad = {quad(f, -1, 1)[0]}\")\n", - " print('')" + " print(\"\")" ] }, { @@ -336,7 +343,7 @@ " elif N == 1:\n", " return x\n", " else:\n", - " return 2 * x * poly_tchebychev(x, N-1) - poly_tchebychev(x, N-2)" + " return 2 * x * poly_tchebychev(x, N - 1) - poly_tchebychev(x, N - 2)" ] }, { @@ -346,7 +353,7 @@ "outputs": [], "source": [ "def points_tchebychev(N):\n", - " k = np.arange(1, N+1)\n", + " k = np.arange(1, N + 1)\n", " return np.cos((2 * k - 1) * np.pi / (2 * N))" ] }, @@ -449,7 +456,7 @@ " lamk = np.zeros(N)\n", " for k in range(N):\n", " s = 0\n", - " for m in range(1, N//2+1):\n", + " for m in range(1, N // 2 + 1):\n", " T = poly_tchebychev(xk[k], 2 * m)\n", " s += 2 * T / (4 * np.power(m, 2) - 1)\n", " lamk[k] = 2 / N * (1 - s)\n", @@ -529,10 +536,12 @@ ], "source": [ "for f in [f0, f1, f2, f3]:\n", - " print(f'Calcule de I(f) par la méthode de fejer et par la formule quadratique pour la fonction {f.__name__}')\n", + " print(\n", + " f\"Calcule de I(f) par la méthode de fejer et par la formule quadratique pour la fonction {f.__name__}\"\n", + " )\n", " for n in range(1, 11):\n", " print(f\"Pour n = {n}, fejer = {fejer(f, n)} et quad = {quad(f, -1, 1)[0]}\")\n", - " print('')" + " print(\"\")" ] }, { @@ -568,26 +577,44 @@ "figure = plt.figure(figsize=(15, 10))\n", "for fi, f in enumerate([f0, f1, f2, f3]):\n", " error_gauss = np.zeros((N,))\n", - " error_simp = np.zeros(((N-1)//2,))\n", + " error_simp = np.zeros(((N - 1) // 2,))\n", " error_fejer = np.zeros((N,))\n", " I_quad, _ = quad(f, -1, 1)\n", - " \n", - " for n in range(1, N+1):\n", + "\n", + " for n in range(1, N + 1):\n", " I_gauss = gauss(f, n)\n", - " error_gauss[n-1] = np.abs(I_gauss - I_quad)\n", + " error_gauss[n - 1] = np.abs(I_gauss - I_quad)\n", " I_fejer = fejer(f, n)\n", - " error_fejer[n-1] = np.abs(I_fejer - I_quad)\n", - " \n", - " for n in range( 3, N+1, 2 ):\n", + " error_fejer[n - 1] = np.abs(I_fejer - I_quad)\n", + "\n", + " for n in range(3, N + 1, 2):\n", " I_simp = simpson(f, n)\n", - " error_simp[(n-2)//2] = np.abs(I_simp - I_quad)\n", - " \n", + " error_simp[(n - 2) // 2] = np.abs(I_simp - I_quad)\n", + "\n", " ax = figure.add_subplot(2, 2, fi + 1)\n", - " ax.scatter(np.arange(1, N+1), np.log10(error_gauss, out = -16. * np.ones(error_gauss.shape), \n", - " where = (error_gauss > 1e-16)), label = 'Gauss', marker=\"+\")\n", - " ax.scatter(np.arange(3, N+1, 2), np.log10( error_simp ), label = 'Simpson', marker=\"+\")\n", - " ax.scatter(np.arange(1, N+1), np.log10(error_fejer, out = -16. * np.ones(error_fejer.shape), \n", - " where = (error_fejer > 1e-16)), label = 'Fejer', marker=\"+\")\n", + " ax.scatter(\n", + " np.arange(1, N + 1),\n", + " np.log10(\n", + " error_gauss,\n", + " out=-16.0 * np.ones(error_gauss.shape),\n", + " where=(error_gauss > 1e-16),\n", + " ),\n", + " label=\"Gauss\",\n", + " marker=\"+\",\n", + " )\n", + " ax.scatter(\n", + " np.arange(3, N + 1, 2), np.log10(error_simp), label=\"Simpson\", marker=\"+\"\n", + " )\n", + " ax.scatter(\n", + " np.arange(1, N + 1),\n", + " np.log10(\n", + " error_fejer,\n", + " out=-16.0 * np.ones(error_fejer.shape),\n", + " where=(error_fejer > 1e-16),\n", + " ),\n", + " label=\"Fejer\",\n", + " marker=\"+\",\n", + " )\n", " ax.legend()\n", " ax.set_title(f\"Erreur de différentes méthodes de quadrature pour {f.__name__}\")\n", " ax.set_xlabel(\"n\")\n", @@ -672,8 +699,13 @@ "def f(x, k):\n", " return x**k\n", "\n", + "\n", "print(\"-----------------------------------------------------------------------\")\n", - "print(\"{:>5s} | {:>7s} {:>9s} {:>9s} {:>9s} {:>9s} {:>9s}\".format(\"N\", \"x^0\", \"x^2\", \"x^4\", \"x^6\", \"x^8\", \"x^10\"))\n", + "print(\n", + " \"{:>5s} | {:>7s} {:>9s} {:>9s} {:>9s} {:>9s} {:>9s}\".format(\n", + " \"N\", \"x^0\", \"x^2\", \"x^4\", \"x^6\", \"x^8\", \"x^10\"\n", + " )\n", + ")\n", "print(\"-----------------------------------------------------------------------\")\n", "\n", "for N in range(1, 11):\n", @@ -683,7 +715,10 @@ " I_exact = 2 / (k + 1) if k % 2 == 0 else 0\n", " approx_error = np.abs(I_approx - I_exact)\n", " approx_errors.append(approx_error)\n", - " print(\"{:5d} | \".format(N) + \" \".join(\"{:.3f} \".format(e) for e in approx_errors))" + " print(\n", + " \"{:5d} | \".format(N)\n", + " + \" \".join(\"{:.3f} \".format(e) for e in approx_errors)\n", + " )" ] }, { @@ -722,8 +757,13 @@ "def f(x, k):\n", " return x**k\n", "\n", + "\n", "print(\"-----------------------------------------------------------------------\")\n", - "print(\"{:>5s} | {:>7s} {:>9s} {:>9s} {:>9s} {:>9s} {:>9s}\".format(\"N\", \"x^0\", \"x^2\", \"x^4\", \"x^6\", \"x^8\", \"x^10\"))\n", + "print(\n", + " \"{:>5s} | {:>7s} {:>9s} {:>9s} {:>9s} {:>9s} {:>9s}\".format(\n", + " \"N\", \"x^0\", \"x^2\", \"x^4\", \"x^6\", \"x^8\", \"x^10\"\n", + " )\n", + ")\n", "print(\"-----------------------------------------------------------------------\")\n", "\n", "for N in range(1, 11):\n", @@ -733,7 +773,10 @@ " I_exact = 2 / (k + 1) if k % 2 == 0 else 0\n", " approx_error = np.abs(I_approx - I_exact)\n", " approx_errors.append(approx_error)\n", - " print(\"{:5d} | \".format(N) + \" \".join(\"{:.3f} \".format(e) for e in approx_errors))" + " print(\n", + " \"{:5d} | \".format(N)\n", + " + \" \".join(\"{:.3f} \".format(e) for e in approx_errors)\n", + " )" ] }, { diff --git a/L3/Calculs Numériques/Interpolation_2.ipynb b/L3/Calculs Numériques/Interpolation_2.ipynb index 977b178..35b979d 100644 --- a/L3/Calculs Numériques/Interpolation_2.ipynb +++ b/L3/Calculs Numériques/Interpolation_2.ipynb @@ -22,8 +22,8 @@ "%matplotlib inline\n", "%config InlineBackend.figure_format = 'retina'\n", "\n", - "import numpy as np # pour les numpy array\n", - "import matplotlib.pyplot as plt # librairie graphique" + "import numpy as np # pour les numpy array\n", + "import matplotlib.pyplot as plt # librairie graphique" ] }, { @@ -72,11 +72,11 @@ " N = len(x)\n", " M = len(xx)\n", " L = np.ones((M, N))\n", - " \n", + "\n", " for i in range(N):\n", " for j in range(N):\n", " if i != j:\n", - " L[:, i] *= (xx - x[j])/(x[i]-x[j])\n", + " L[:, i] *= (xx - x[j]) / (x[i] - x[j])\n", " return L.dot(y)" ] }, @@ -119,7 +119,7 @@ "y = np.random.rand(N)\n", "xx = np.linspace(0, 1, 200)\n", "\n", - "plt.scatter(x,y)\n", + "plt.scatter(x, y)\n", "plt.plot(xx, interp_Lagrange(x, y, xx))" ] }, @@ -155,10 +155,16 @@ "outputs": [], "source": [ "def equirepartis(a, b, N):\n", - " return np.array([a + (b-a) * (i-1)/(N-1) for i in range(1, N+1)])\n", - " \n", + " return np.array([a + (b - a) * (i - 1) / (N - 1) for i in range(1, N + 1)])\n", + "\n", + "\n", "def tchebychev(a, b, N):\n", - " return np.array([(a+b)/2 + (b-a)/2 * np.cos((2*i-1)/(2*N)*np.pi) for i in range(1, N+1)])" + " return np.array(\n", + " [\n", + " (a + b) / 2 + (b - a) / 2 * np.cos((2 * i - 1) / (2 * N) * np.pi)\n", + " for i in range(1, N + 1)\n", + " ]\n", + " )" ] }, { @@ -188,7 +194,7 @@ " L = np.ones_like(xx)\n", " for j in range(N):\n", " if i != j:\n", - " L *= (xx-x[j])/(x[i]-x[j]) \n", + " L *= (xx - x[j]) / (x[i] - x[j])\n", " return L" ] }, @@ -271,16 +277,16 @@ " ax[0].set_title(f\"Points équi-repartis (N={n})\")\n", " xeq = equirepartis(a, b, n)\n", " for i in range(n):\n", - " ax[0].scatter(xeq[i], 0, color='black')\n", - " ax[0].scatter(xeq[i], 1, color='black')\n", + " ax[0].scatter(xeq[i], 0, color=\"black\")\n", + " ax[0].scatter(xeq[i], 1, color=\"black\")\n", " ax[0].plot(xx, Li(i, xeq, xx))\n", " ax[0].grid()\n", - " \n", + "\n", " ax[1].set_title(f\"Points de Tchebychev (N={n})\")\n", " xchev = tchebychev(a, b, n)\n", " for i in range(n):\n", - " ax[1].scatter(xchev[i], 0, color='black')\n", - " ax[1].scatter(xchev[i], 1, color='black')\n", + " ax[1].scatter(xchev[i], 0, color=\"black\")\n", + " ax[1].scatter(xchev[i], 1, color=\"black\")\n", " ax[1].plot(xx, Li(i, xchev, xx))\n", " ax[1].grid()" ] @@ -325,20 +331,20 @@ } ], "source": [ - "f = lambda x: 1/(1+x**2)\n", + "f = lambda x: 1 / (1 + x**2)\n", "a, b = -5, 5\n", "xx = np.linspace(a, b, 200)\n", "\n", - "plt.plot(xx, f(xx), label='Courbe de f')\n", + "plt.plot(xx, f(xx), label=\"Courbe de f\")\n", "for n in [5, 10, 20]:\n", " xeq = equirepartis(a, b, n)\n", " for i in range(n):\n", " plt.scatter(xeq[i], f(xeq[i]))\n", " plt.plot(xx, Li(i, xeq, xx))\n", - " \n", + "\n", "plt.ylim(-1, 1)\n", "plt.legend()\n", - "plt.title('Interpolation de f avec Lagrange pour N points répartis')\n", + "plt.title(\"Interpolation de f avec Lagrange pour N points répartis\")\n", "plt.grid()" ] }, @@ -366,20 +372,20 @@ } ], "source": [ - "f = lambda x: 1/(1+x**2)\n", + "f = lambda x: 1 / (1 + x**2)\n", "a, b = -5, 5\n", "xx = np.linspace(a, b, 200)\n", "\n", - "plt.plot(xx, f(xx), label='Courbe de f')\n", + "plt.plot(xx, f(xx), label=\"Courbe de f\")\n", "\n", "for n in [5, 10, 20]:\n", " xchev = tchebychev(a, b, n)\n", " for i in range(n):\n", " plt.scatter(xchev[i], f(xchev[i]))\n", " plt.plot(xx, Li(i, xchev, xx))\n", - " \n", + "\n", "plt.legend()\n", - "plt.title('Interpolation de f avec Lagrange pour N points de Tchebychev')\n", + "plt.title(\"Interpolation de f avec Lagrange pour N points de Tchebychev\")\n", "plt.grid()" ] }, @@ -437,9 +443,11 @@ "source": [ "N = np.arange(5, 101, 5)\n", "\n", + "\n", "def n_inf(f, p):\n", " return np.max([f, p])\n", "\n", + "\n", "# Norme inf en fct de N\n", "for n in N:\n", " xeq = equirepartis(a, b, n)\n", diff --git a/L3/Calculs Numériques/Point_Fixe.ipynb b/L3/Calculs Numériques/Point_Fixe.ipynb index ab0b6b0..9feb27e 100644 --- a/L3/Calculs Numériques/Point_Fixe.ipynb +++ b/L3/Calculs Numériques/Point_Fixe.ipynb @@ -98,16 +98,16 @@ "\n", "x = np.linspace(-1, 1, 200)\n", "ax = fig.add_subplot(3, 3, 1)\n", - "ax.plot(x, f1(x), label='Courbe f')\n", - "ax.plot(x, x, label=f'$y=x$')\n", + "ax.plot(x, f1(x), label=\"Courbe f\")\n", + "ax.plot(x, x, label=\"$y=x$\")\n", "ax.scatter([i for i in x if f1(i) == i], [f1(i) for i in x if f1(i) == i])\n", "ax.legend()\n", "\n", - "x = np.linspace(-np.pi / 2, 5*np.pi / 2)\n", + "x = np.linspace(-np.pi / 2, 5 * np.pi / 2)\n", "for fk, f in enumerate([f2, f3, f4, f5]):\n", - " ax = fig.add_subplot(3, 3, fk+2)\n", - " ax.plot(x, f(x), label='Courbe f')\n", - " ax.plot(x, x, label=f'$y=x$')\n", + " ax = fig.add_subplot(3, 3, fk + 2)\n", + " ax.plot(x, f(x), label=\"Courbe f\")\n", + " ax.plot(x, x, label=\"$y=x$\")\n", " ax.scatter([i for i in x if f(i) == i], [f(i) for i in x if f(i) == i])\n", " ax.legend()" ] @@ -129,13 +129,13 @@ }, "outputs": [], "source": [ - "def point_fixe(f, x0, tol=1.e-6, itermax=5000):\n", + "def point_fixe(f, x0, tol=1.0e-6, itermax=5000):\n", " \"\"\"\n", " Recherche de point fixe : méthode brute x_{n+1} = f(x_n)\n", - " \n", + "\n", " Parameters\n", " ----------\n", - " \n", + "\n", " f: function\n", " la fonction dont on cherche le point fixe\n", " x0: float\n", @@ -144,10 +144,10 @@ " critère d'arrêt : |x_{n+1} - x_n| < tol\n", " itermax: int\n", " le nombre maximal d'itérations autorisées\n", - " \n", + "\n", " Returns\n", " -------\n", - " \n", + "\n", " x: float\n", " la valeur trouvée pour le point fixe\n", " niter: int\n", @@ -225,14 +225,14 @@ "source": [ "# F1\n", "\n", - "fig, ax = plt.subplots(figsize=(6,6))\n", + "fig, ax = plt.subplots(figsize=(6, 6))\n", "\n", "x, niter, xL = point_fixe(f1, -0.5)\n", "xx = np.linspace(-1, 1, 200)\n", "\n", - "ax.plot(xx, f1(xx), label='Courbe f1')\n", - "ax.plot(xx, xx, label=f'$y=x$')\n", - "ax.scatter(x, f1(x), label='Point Fixe')\n", + "ax.plot(xx, f1(xx), label=\"Courbe f1\")\n", + "ax.plot(xx, xx, label=\"$y=x$\")\n", + "ax.scatter(x, f1(x), label=\"Point Fixe\")\n", "ax.legend()\n", "ax.set_title(f\"Nombre d'itérations : {niter}\")" ] diff --git a/L3/Equations Différentielles/TP1_EDO_EulerExp.ipynb b/L3/Equations Différentielles/TP1_EDO_EulerExp.ipynb index 22f7126..932effe 100644 --- a/L3/Equations Différentielles/TP1_EDO_EulerExp.ipynb +++ b/L3/Equations Différentielles/TP1_EDO_EulerExp.ipynb @@ -103,38 +103,45 @@ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", - "# Fonction f définissant l'EDO\n", - "def f1(t,y):\n", - " return -t*y\n", "\n", - "# Solution exacte \n", - "def uex1(t,y0):\n", - " return y0 * np.exp(-t**2 /2)\n", + "# Fonction f définissant l'EDO\n", + "def f1(t, y):\n", + " return -t * y\n", + "\n", + "\n", + "# Solution exacte\n", + "def uex1(t, y0):\n", + " return y0 * np.exp(-(t**2) / 2)\n", + "\n", "\n", "plt.figure(1)\n", "\n", "## Solutions de l'EDO 1 telles que y(0)=1 et y(0)=2\n", "\n", - "tt=np.linspace(-3, 3, 100) # vecteur représentant l'intervalle de temps\n", - "y1=uex1(tt, 1) # sol. exacte avec y_0=1\n", - "y2=uex1(tt, 2) # sol. exacte avec y_0=2\n", - "plt.plot(tt,y1,label='y(0)=1')\n", - "plt.plot(tt,y2,label='y(0)=2')\n", + "tt = np.linspace(-3, 3, 100) # vecteur représentant l'intervalle de temps\n", + "y1 = uex1(tt, 1) # sol. exacte avec y_0=1\n", + "y2 = uex1(tt, 2) # sol. exacte avec y_0=2\n", + "plt.plot(tt, y1, label=\"y(0)=1\")\n", + "plt.plot(tt, y2, label=\"y(0)=2\")\n", "\n", "##Tracé du champ de vecteurs\n", "\n", - "plt.title('Solution exacte pour y0 et y1')\n", + "plt.title(\"Solution exacte pour y0 et y1\")\n", "plt.legend()\n", - "plt.xlabel('t')\n", - "plt.ylabel('y')\n", + "plt.xlabel(\"t\")\n", + "plt.ylabel(\"y\")\n", "\n", - "t=np.linspace(-5,5,35) # abcisse des points de la grille \n", - "y=np.linspace(0,2.1,23) # ordonnées des points de la grille \n", - "T,Y=np.meshgrid(t,y) # grille de points dans le plan (t,y) \n", - "U=np.ones(T.shape)/np.sqrt(1+f1(T,Y)**2) # matrice avec les composantes horizontales des vecteurs (1), normalisées \n", - "V=f1(T,Y)/np.sqrt(1+f1(T,Y)**2) # matrice avec les composantes verticales des vecteurs (f(t,y)), normalisées \n", - "plt.quiver(T,Y,U,V,angles='xy',scale=20,color='cyan')\n", - "plt.axis([-5,5,0,2.1])" + "t = np.linspace(-5, 5, 35) # abcisse des points de la grille\n", + "y = np.linspace(0, 2.1, 23) # ordonnées des points de la grille\n", + "T, Y = np.meshgrid(t, y) # grille de points dans le plan (t,y)\n", + "U = np.ones(T.shape) / np.sqrt(\n", + " 1 + f1(T, Y) ** 2\n", + ") # matrice avec les composantes horizontales des vecteurs (1), normalisées\n", + "V = f1(T, Y) / np.sqrt(\n", + " 1 + f1(T, Y) ** 2\n", + ") # matrice avec les composantes verticales des vecteurs (f(t,y)), normalisées\n", + "plt.quiver(T, Y, U, V, angles=\"xy\", scale=20, color=\"cyan\")\n", + "plt.axis([-5, 5, 0, 2.1])" ] }, { @@ -185,40 +192,47 @@ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", + "\n", "# Fonction f définissant l'EDO\n", - "def f2(t,y):\n", + "def f2(t, y):\n", " return t * y**2\n", "\n", - "# Solution exacte \n", - "def uex2(t,y0):\n", + "\n", + "# Solution exacte\n", + "def uex2(t, y0):\n", " return y0 / (1 - y0 * t**2 / 2)\n", "\n", + "\n", "plt.figure(1)\n", "\n", "## Solutions de l'EDO 1 telles que y(0)=1 et y(0)=2\n", "\n", - "tt=np.linspace(-3, 3, 100) # vecteur représentant l'intervalle de temps\n", - "y1=uex2(tt, 1) # sol. exacte avec y_0=1\n", - "y2=uex2(tt, 2) # sol. exacte avec y_0=2\n", - "plt.plot(tt,y1,label='y(0)=1')\n", - "plt.plot(tt,y2,label='y(0)=2')\n", + "tt = np.linspace(-3, 3, 100) # vecteur représentant l'intervalle de temps\n", + "y1 = uex2(tt, 1) # sol. exacte avec y_0=1\n", + "y2 = uex2(tt, 2) # sol. exacte avec y_0=2\n", + "plt.plot(tt, y1, label=\"y(0)=1\")\n", + "plt.plot(tt, y2, label=\"y(0)=2\")\n", "\n", "##Tracé du champ de vecteurs\n", "\n", - "plt.title('Solution exacte pour y0 et y1')\n", + "plt.title(\"Solution exacte pour y0 et y1\")\n", "plt.legend()\n", - "plt.xlabel('t')\n", - "plt.ylabel('y')\n", + "plt.xlabel(\"t\")\n", + "plt.ylabel(\"y\")\n", "\n", "xmin, xmax = -2, 2\n", "ymin, ymax = -4, 4\n", "\n", - "t=np.linspace(xmin, xmax,35) # abcisse des points de la grille \n", - "y=np.linspace(ymin, ymax) # ordonnées des points de la grille \n", - "T,Y=np.meshgrid(t,y) # grille de points dans le plan (t,y) \n", - "U=np.ones(T.shape)/np.sqrt(1+f2(T,Y)**2) # matrice avec les composantes horizontales des vecteurs (1), normalisées \n", - "V=f1(T,Y)/np.sqrt(1+f2(T,Y)**2) # matrice avec les composantes verticales des vecteurs (f(t,y)), normalisées \n", - "plt.quiver(T,Y,U,V,angles='xy',scale=20,color='cyan')\n", + "t = np.linspace(xmin, xmax, 35) # abcisse des points de la grille\n", + "y = np.linspace(ymin, ymax) # ordonnées des points de la grille\n", + "T, Y = np.meshgrid(t, y) # grille de points dans le plan (t,y)\n", + "U = np.ones(T.shape) / np.sqrt(\n", + " 1 + f2(T, Y) ** 2\n", + ") # matrice avec les composantes horizontales des vecteurs (1), normalisées\n", + "V = f1(T, Y) / np.sqrt(\n", + " 1 + f2(T, Y) ** 2\n", + ") # matrice avec les composantes verticales des vecteurs (f(t,y)), normalisées\n", + "plt.quiver(T, Y, U, V, angles=\"xy\", scale=20, color=\"cyan\")\n", "plt.axis([xmin, xmax, ymin, ymax])" ] }, @@ -339,33 +353,34 @@ ], "source": [ "# Euler explicite\n", - "def euler_exp(t0,T,y0,h,f):\n", - " t = np.arange(t0, t0+T+h, h)\n", + "def euler_exp(t0, T, y0, h, f):\n", + " t = np.arange(t0, t0 + T + h, h)\n", " y = np.empty(t.size)\n", " y[0] = y0\n", - " N = len(t)-1\n", + " N = len(t) - 1\n", " for n in range(N):\n", - " y[n+1] = y[n] + h * f(t[n], y[n])\n", + " y[n + 1] = y[n] + h * f(t[n], y[n])\n", " return t, y\n", "\n", - "t0=0\n", - "T=1\n", - "y0=1\n", + "\n", + "t0 = 0\n", + "T = 1\n", + "y0 = 1\n", "\n", "for f, uex in zip([f1, f2], [uex1, uex2]):\n", " plt.figure()\n", " t = np.arange(0, 1, 1e-3)\n", " y = uex(t, y0)\n", - " plt.plot(t, y, label='Solution exacte')\n", + " plt.plot(t, y, label=\"Solution exacte\")\n", "\n", - " for h in [1/5, 1/10, 1/50]:\n", + " for h in [1 / 5, 1 / 10, 1 / 50]:\n", " tt, y = euler_exp(t0, T, y0, h, f)\n", - " plt.plot(tt, y, label=f'Solution approchée pour h={h}')\n", - " \n", + " plt.plot(tt, y, label=f\"Solution approchée pour h={h}\")\n", + "\n", " plt.title(f\"Solutions exacte et approchées de la fonction {f.__name__}\")\n", " plt.legend()\n", - " plt.xlabel('t')\n", - " plt.ylabel('y')" + " plt.xlabel(\"t\")\n", + " plt.ylabel(\"y\")" ] }, { @@ -441,12 +456,14 @@ ], "source": [ "# Modèle de Verhulst\n", - "n=1\n", - "d=0.75\n", - "K=200\n", + "n = 1\n", + "d = 0.75\n", + "K = 200\n", + "\n", + "\n", + "def fV(t, P):\n", + " return (n - d) * P * (1 - P / K)\n", "\n", - "def fV(t,P):\n", - " return (n-d)*P*(1-P/K)\n", "\n", "plt.figure()\n", "\n", @@ -455,20 +472,24 @@ "t0, T = 0, 50\n", "\n", "\n", - "for P in range(1, K+100, 15):\n", + "for P in range(1, K + 100, 15):\n", " tt, yy = euler_exp(t0, T, P, h, fV)\n", - " plt.plot(tt, yy, label=f'Solution approchée pour h={h}')\n", - " \n", - "plt.title(f\"Solution approchée du modèle de Verhulst pour la population d'individus\")\n", - "plt.xlabel('t')\n", - "plt.ylabel('y')\n", + " plt.plot(tt, yy, label=f\"Solution approchée pour h={h}\")\n", "\n", - "t=np.linspace(t0, T, 35) # abcisse des points de la grille \n", - "y=np.linspace(0, K+100, 23) # ordonnées des points de la grille \n", - "T,P=np.meshgrid(t,y) # grille de points dans le plan (t,y) \n", - "U=np.ones(T.shape)/np.sqrt(1+fV(T,P)**2) # matrice avec les composantes horizontales des vecteurs (1), normalisées \n", - "V=fV(T,P)/np.sqrt(1+fV(T,P)**2) # matrice avec les composantes verticales des vecteurs (f(t,y)), normalisées \n", - "plt.quiver(T,P,U,V,angles='xy',scale=20,color='cyan')\n", + "plt.title(\"Solution approchée du modèle de Verhulst pour la population d'individus\")\n", + "plt.xlabel(\"t\")\n", + "plt.ylabel(\"y\")\n", + "\n", + "t = np.linspace(t0, T, 35) # abcisse des points de la grille\n", + "y = np.linspace(0, K + 100, 23) # ordonnées des points de la grille\n", + "T, P = np.meshgrid(t, y) # grille de points dans le plan (t,y)\n", + "U = np.ones(T.shape) / np.sqrt(\n", + " 1 + fV(T, P) ** 2\n", + ") # matrice avec les composantes horizontales des vecteurs (1), normalisées\n", + "V = fV(T, P) / np.sqrt(\n", + " 1 + fV(T, P) ** 2\n", + ") # matrice avec les composantes verticales des vecteurs (f(t,y)), normalisées\n", + "plt.quiver(T, P, U, V, angles=\"xy\", scale=20, color=\"cyan\")\n", "plt.legend(fontsize=4)" ] }, @@ -527,29 +548,34 @@ } ], "source": [ - "def fS(t,P):\n", - " return (2-np.cos(t))*P-(P**2)/2-1\n", + "def fS(t, P):\n", + " return (2 - np.cos(t)) * P - (P**2) / 2 - 1\n", "\n", - "P0=5\n", - "t0=0\n", - "T=10\n", - "h=0.1\n", + "\n", + "P0 = 5\n", + "t0 = 0\n", + "T = 10\n", + "h = 0.1\n", "\n", "plt.figure()\n", "tt, yy = euler_exp(t0, T, P0, h, fS)\n", - "plt.plot(tt, yy, label=f'Solution approchée pour h={h}')\n", - " \n", - "plt.title(f\"Solutions approchée du modèle de Verhulst pour une population de saumons\")\n", - "plt.legend()\n", - "plt.xlabel('t')\n", - "plt.ylabel('y')\n", + "plt.plot(tt, yy, label=f\"Solution approchée pour h={h}\")\n", "\n", - "t=np.linspace(t0, T, 35) # abcisse des points de la grille \n", - "y=np.linspace(0, 6, 23) # ordonnées des points de la grille \n", - "T,P=np.meshgrid(t,y) # grille de points dans le plan (t,y) \n", - "U=np.ones(T.shape)/np.sqrt(1+fS(T,P)**2) # matrice avec les composantes horizontales des vecteurs (1), normalisées \n", - "V=fS(T,P)/np.sqrt(1+fS(T,P)**2) # matrice avec les composantes verticales des vecteurs (f(t,y)), normalisées \n", - "plt.quiver(T,P,U,V,angles='xy',scale=20,color='cyan')\n" + "plt.title(\"Solutions approchée du modèle de Verhulst pour une population de saumons\")\n", + "plt.legend()\n", + "plt.xlabel(\"t\")\n", + "plt.ylabel(\"y\")\n", + "\n", + "t = np.linspace(t0, T, 35) # abcisse des points de la grille\n", + "y = np.linspace(0, 6, 23) # ordonnées des points de la grille\n", + "T, P = np.meshgrid(t, y) # grille de points dans le plan (t,y)\n", + "U = np.ones(T.shape) / np.sqrt(\n", + " 1 + fS(T, P) ** 2\n", + ") # matrice avec les composantes horizontales des vecteurs (1), normalisées\n", + "V = fS(T, P) / np.sqrt(\n", + " 1 + fS(T, P) ** 2\n", + ") # matrice avec les composantes verticales des vecteurs (f(t,y)), normalisées\n", + "plt.quiver(T, P, U, V, angles=\"xy\", scale=20, color=\"cyan\")" ] }, { diff --git a/L3/Equations Différentielles/TP2_Lokta_Volterra.ipynb b/L3/Equations Différentielles/TP2_Lokta_Volterra.ipynb index 3664557..00e4a17 100644 --- a/L3/Equations Différentielles/TP2_Lokta_Volterra.ipynb +++ b/L3/Equations Différentielles/TP2_Lokta_Volterra.ipynb @@ -95,53 +95,63 @@ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", + "\n", "# Fonction F définissant l'EDO\n", "def F(Y):\n", - " x=Y[0]\n", - " y=Y[1]\n", - " A=np.array([[0,1],[-2,-3]])\n", - " return np.dot(A,Y)\n", + " x = Y[0]\n", + " y = Y[1]\n", + " A = np.array([[0, 1], [-2, -3]])\n", + " return np.dot(A, Y)\n", "\n", - "# ou \n", - "def F1(x,y):\n", + "\n", + "# ou\n", + "def F1(x, y):\n", " return y\n", "\n", - "def F2(x,y):\n", - " return -2*x-3*y\n", + "\n", + "def F2(x, y):\n", + " return -2 * x - 3 * y\n", + "\n", "\n", "# Solution exacte de Y'=AY, Y(t_0)=Y_0\n", - "def uex(t,t0,Y0):\n", - " U1=np.array([1,-1])\n", - " U2=np.array([1,-2])\n", - " P=np.ones((2,2))\n", - " P[:,0]=U1\n", - " P[:,1]=U2\n", - " C=np.linalg.solve(P,Y0)\n", - " return np.array([(C[0]*np.exp(-(t-t0))*U1[0]+C[1]*np.exp(-2*(t-t0))*U2[0]),(C[0]*np.exp(-(t-t0))*U1[1]+C[1]*np.exp(-2*(t-t0))*U2[1])])\n", + "def uex(t, t0, Y0):\n", + " U1 = np.array([1, -1])\n", + " U2 = np.array([1, -2])\n", + " P = np.ones((2, 2))\n", + " P[:, 0] = U1\n", + " P[:, 1] = U2\n", + " C = np.linalg.solve(P, Y0)\n", + " return np.array(\n", + " [\n", + " (C[0] * np.exp(-(t - t0)) * U1[0] + C[1] * np.exp(-2 * (t - t0)) * U2[0]),\n", + " (C[0] * np.exp(-(t - t0)) * U1[1] + C[1] * np.exp(-2 * (t - t0)) * U2[1]),\n", + " ]\n", + " )\n", "\n", - "## Représentation des solutions pour chaque valeur de la donnée initiale \n", + "\n", + "## Représentation des solutions pour chaque valeur de la donnée initiale\n", "tt = np.linspace(-10, 10, 100)\n", "t0 = tt[0]\n", "for x, y in zip([1, -2, 0, 1, 3], [2, -2, -4, -2, 4]):\n", " sol = uex(tt, t0, [x, y])\n", - " plt.plot(sol[0], sol[1], label=f'$((x0, y0) = ({x}, {y})$')\n", + " plt.plot(sol[0], sol[1], label=f\"$((x0, y0) = ({x}, {y})$\")\n", " plt.scatter(x, y)\n", "\n", - "#Tracé du champ de vecteurs\n", - "x=np.linspace(-5,5,26)\n", - "y=x\n", - "xx,yy=np.meshgrid(x,y)\n", - "U=F1(xx,yy)/np.sqrt(F1(xx,yy)**2+F2(xx,yy)**2)\n", - "V=F2(xx,yy)/np.sqrt(F1(xx,yy)**2+F2(xx,yy)**2)\n", - "plt.quiver(xx,yy,U,V,angles='xy', scale=20, color='gray')\n", - "plt.axis([-5.,5,-5,5])\n", + "# Tracé du champ de vecteurs\n", + "x = np.linspace(-5, 5, 26)\n", + "y = x\n", + "xx, yy = np.meshgrid(x, y)\n", + "U = F1(xx, yy) / np.sqrt(F1(xx, yy) ** 2 + F2(xx, yy) ** 2)\n", + "V = F2(xx, yy) / np.sqrt(F1(xx, yy) ** 2 + F2(xx, yy) ** 2)\n", + "plt.quiver(xx, yy, U, V, angles=\"xy\", scale=20, color=\"gray\")\n", + "plt.axis([-5.0, 5, -5, 5])\n", "\n", - "## Représentation des espaces propres \n", - "plt.plot(tt, -tt, label=f'SEP associé à -1', linewidth=3)\n", - "plt.plot(tt, -2*tt, label=f'SEP associé à -2', linewidth=3)\n", + "## Représentation des espaces propres\n", + "plt.plot(tt, -tt, label=\"SEP associé à -1\", linewidth=3)\n", + "plt.plot(tt, -2 * tt, label=\"SEP associé à -2\", linewidth=3)\n", "\n", "plt.legend(fontsize=7)\n", - "plt.title('Représentation des solutions et champs de vecteurs pour le système (S)')" + "plt.title(\"Représentation des solutions et champs de vecteurs pour le système (S)\")" ] }, { @@ -210,13 +220,15 @@ "source": [ "a, b, c, d = 0.1, 5e-5, 0.04, 5e-5\n", "H0, P0 = 2000, 1000\n", - "He, Pe = c/d, a/b\n", + "He, Pe = c / d, a / b\n", + "\n", "\n", "def F1(H, P):\n", - " return H * (a - b*P)\n", + " return H * (a - b * P)\n", + "\n", "\n", "def F2(H, P):\n", - " return P * (-c + d*H)" + " return P * (-c + d * H)" ] }, { @@ -256,17 +268,17 @@ } ], "source": [ - "xx, yy = np.linspace(0, 3000, 20), np.linspace (0, 4500, 30)\n", - "h,p = np.meshgrid(xx, yy)\n", - "n=np.sqrt(F1(h,p)**2+F2(h,p)**2)\n", - "plt.quiver(h, p, F1(h,p)/n, F2(h,p)/n, angles='xy', scale=20, color='gray')\n", + "xx, yy = np.linspace(0, 3000, 20), np.linspace(0, 4500, 30)\n", + "h, p = np.meshgrid(xx, yy)\n", + "n = np.sqrt(F1(h, p) ** 2 + F2(h, p) ** 2)\n", + "plt.quiver(h, p, F1(h, p) / n, F2(h, p) / n, angles=\"xy\", scale=20, color=\"gray\")\n", "\n", - "plt.vlines(He, 0, 4500, label=f'H=He={He}')\n", - "plt.hlines(Pe, 0, 3000, label=f'P=Pe={Pe}')\n", - "plt.scatter(He, Pe, label=f'(H0, P0) = (He, Pe)')\n", - "plt.scatter(H0, P0, label=f'(H, P)=(H0, P0)=({H0},{P0})', color='red')\n", + "plt.vlines(He, 0, 4500, label=f\"H=He={He}\")\n", + "plt.hlines(Pe, 0, 3000, label=f\"P=Pe={Pe}\")\n", + "plt.scatter(He, Pe, label=\"(H0, P0) = (He, Pe)\")\n", + "plt.scatter(H0, P0, label=f\"(H, P)=(H0, P0)=({H0},{P0})\", color=\"red\")\n", "\n", - "plt.title('Le modèle de Lotka-Volterra')\n", + "plt.title(\"Le modèle de Lotka-Volterra\")\n", "plt.legend(fontsize=7)" ] }, @@ -374,19 +386,20 @@ "outputs": [], "source": [ "a, b, c, d = 0.1, 5e-5, 0.04, 5e-5\n", - "T=200\n", + "T = 200\n", "H0, P0 = 2000, 1000\n", - "He, Pe = c/d, a/b\n", - "p=0.02\n", + "He, Pe = c / d, a / b\n", + "p = 0.02\n", + "\n", "\n", "def voltEE(T, X0, h):\n", - " t = np.arange(0, T+h, h)\n", + " t = np.arange(0, T + h, h)\n", " H = 0 * t\n", " P = 0 * t\n", " H[0], P[0] = X0\n", - " for n in range(len(t)-1):\n", - " H[n+1] = H[n] + h * F1(H[n], P[n])\n", - " P[n+1] = P[n] + h * F2(H[n], P[n])\n", + " for n in range(len(t) - 1):\n", + " H[n + 1] = H[n] + h * F1(H[n], P[n])\n", + " P[n + 1] = P[n] + h * F2(H[n], P[n])\n", " return np.array([t, H, P])" ] }, @@ -438,22 +451,22 @@ ], "source": [ "t, H, P = voltEE(T, [H0, P0], 0.001)\n", - "plt.plot(t, H, label='Population de sardines')\n", - "plt.plot(t, P, label='Population de requins')\n", + "plt.plot(t, H, label=\"Population de sardines\")\n", + "plt.plot(t, P, label=\"Population de requins\")\n", "plt.legend(fontsize=7)\n", "\n", "plt.figure()\n", - "xx, yy = np.linspace(0, 3000, 20), np.linspace (0, 4500, 30)\n", - "h,p = np.meshgrid(xx, yy)\n", - "n=np.sqrt(F1(h,p)**2 + F2(h,p)**2)\n", - "plt.quiver (h, p, F1(h,p)/n, F2(h,p)/n, angles='xy', scale=20, color='gray')\n", + "xx, yy = np.linspace(0, 3000, 20), np.linspace(0, 4500, 30)\n", + "h, p = np.meshgrid(xx, yy)\n", + "n = np.sqrt(F1(h, p) ** 2 + F2(h, p) ** 2)\n", + "plt.quiver(h, p, F1(h, p) / n, F2(h, p) / n, angles=\"xy\", scale=20, color=\"gray\")\n", "\n", - "plt.vlines(He, 0, 4500, label=f'H=He={He}')\n", - "plt.hlines(Pe, 0, 3000, label=f'P=Pe={Pe}')\n", - "plt.scatter(He, Pe, label=f'(H0, P0) = (He, Pe)')\n", - "plt.scatter(H0, P0, label=f'(H, P)=(H0, P0)=({H0},{P0})', color='red')\n", + "plt.vlines(He, 0, 4500, label=f\"H=He={He}\")\n", + "plt.hlines(Pe, 0, 3000, label=f\"P=Pe={Pe}\")\n", + "plt.scatter(He, Pe, label=\"(H0, P0) = (He, Pe)\")\n", + "plt.scatter(H0, P0, label=f\"(H, P)=(H0, P0)=({H0},{P0})\", color=\"red\")\n", "\n", - "plt.title('Le modèle de Lotka-Volterra')\n", + "plt.title(\"Le modèle de Lotka-Volterra\")\n", "plt.legend(fontsize=7)\n", "plt.plot(H, P)" ] @@ -467,25 +480,28 @@ "outputs": [], "source": [ "a, b, c, d = 0.1, 5e-5, 0.04, 5e-5\n", - "T=200\n", + "T = 200\n", "H0, P0 = 2000, 1000\n", - "He, Pe = c/d, a/b\n", - "p=0.02\n", + "He, Pe = c / d, a / b\n", + "p = 0.02\n", + "\n", "\n", "def F1_p(H, P):\n", " return (a - p) * H - b * H * P\n", "\n", + "\n", "def F2_p(H, P):\n", - " return (-c-p) * P + d * H * P\n", + " return (-c - p) * P + d * H * P\n", + "\n", "\n", "def voltEE_p(T, X0, h):\n", - " t = np.arange(0, T+h, h)\n", + " t = np.arange(0, T + h, h)\n", " H = 0 * t\n", " P = 0 * t\n", " H[0], P[0] = X0\n", - " for n in range(len(t)-1):\n", - " H[n+1] = H[n] + h * F1_p(H[n], P[n])\n", - " P[n+1] = P[n] + h * F2_p(H[n], P[n])\n", + " for n in range(len(t) - 1):\n", + " H[n + 1] = H[n] + h * F1_p(H[n], P[n])\n", + " P[n + 1] = P[n] + h * F2_p(H[n], P[n])\n", " return np.array([t, H, P])" ] }, @@ -535,22 +551,22 @@ ], "source": [ "t, H, P = voltEE_p(T, [H0, P0], 0.001)\n", - "plt.plot(t, H, label='Population de sardines')\n", - "plt.plot(t, P, label='Population de requins')\n", + "plt.plot(t, H, label=\"Population de sardines\")\n", + "plt.plot(t, P, label=\"Population de requins\")\n", "plt.legend(fontsize=7)\n", "\n", "plt.figure()\n", - "xx, yy = np.linspace(0, 3000, 20), np.linspace (0, 4500, 30)\n", - "h,p = np.meshgrid(xx, yy)\n", - "n=np.sqrt(F1(h,p)**2 + F2(h,p)**2)\n", - "plt.quiver (h, p, F1(h,p)/n, F2(h,p)/n, angles='xy', scale=20, color='gray')\n", + "xx, yy = np.linspace(0, 3000, 20), np.linspace(0, 4500, 30)\n", + "h, p = np.meshgrid(xx, yy)\n", + "n = np.sqrt(F1(h, p) ** 2 + F2(h, p) ** 2)\n", + "plt.quiver(h, p, F1(h, p) / n, F2(h, p) / n, angles=\"xy\", scale=20, color=\"gray\")\n", "\n", - "plt.vlines(He, 0, 4500, label=f'H=He={He}')\n", - "plt.hlines(Pe, 0, 3000, label=f'P=Pe={Pe}')\n", - "plt.scatter(He, Pe, label=f'(H0, P0) = (He, Pe)')\n", - "plt.scatter(H0, P0, label=f'(H, P)=(H0, P0)=({H0},{P0})', color='red')\n", + "plt.vlines(He, 0, 4500, label=f\"H=He={He}\")\n", + "plt.hlines(Pe, 0, 3000, label=f\"P=Pe={Pe}\")\n", + "plt.scatter(He, Pe, label=\"(H0, P0) = (He, Pe)\")\n", + "plt.scatter(H0, P0, label=f\"(H, P)=(H0, P0)=({H0},{P0})\", color=\"red\")\n", "\n", - "plt.title('Le modèle de Lotka-Volterra')\n", + "plt.title(\"Le modèle de Lotka-Volterra\")\n", "plt.legend(fontsize=7)\n", "plt.plot(H, P)" ] @@ -697,46 +713,49 @@ } ], "source": [ - "gamma=0.5\n", - "a=0.004\n", - "lm=10\n", + "gamma = 0.5\n", + "a = 0.004\n", + "lm = 10\n", + "\n", "\n", "def fphi(d):\n", - " return (gamma/d)*np.log(d/a)\n", + " return (gamma / d) * np.log(d / a)\n", + "\n", "\n", "def F(X):\n", - " (n,m)=np.shape(X)\n", - " Y=np.zeros((n,m))\n", - " Y[0,:]=X[1,:]\n", - " Xaux=np.zeros(m+2)\n", - " Xaux[-1]=1\n", - " Xaux[1:-1]=X[0,:]\n", - " Y[1,:]=fphi(Xaux[2:]-Xaux[1:-1])-fphi(Xaux[1:-1]-Xaux[0:-2])-lm*X[1,:]\n", + " (n, m) = np.shape(X)\n", + " Y = np.zeros((n, m))\n", + " Y[0, :] = X[1, :]\n", + " Xaux = np.zeros(m + 2)\n", + " Xaux[-1] = 1\n", + " Xaux[1:-1] = X[0, :]\n", + " Y[1, :] = fphi(Xaux[2:] - Xaux[1:-1]) - fphi(Xaux[1:-1] - Xaux[0:-2]) - lm * X[1, :]\n", " return Y\n", "\n", - "h=0.0002\n", - "T=15\n", - "N=100\n", "\n", - "t=np.arange(0,T+h,h)\n", - "Nt=np.size(t)\n", - "X=np.zeros((2,N,Nt))\n", - "R0=-1+2*np.random.rand(N)\n", - "X0=np.arange(1/(N+1),1,1/(N+1))+0.1*R0*(1/(N+1))\n", + "h = 0.0002\n", + "T = 15\n", + "N = 100\n", "\n", - "X[0,:,0]=X0\n", - "X[1,:,0]=X0\n", + "t = np.arange(0, T + h, h)\n", + "Nt = np.size(t)\n", + "X = np.zeros((2, N, Nt))\n", + "R0 = -1 + 2 * np.random.rand(N)\n", + "X0 = np.arange(1 / (N + 1), 1, 1 / (N + 1)) + 0.1 * R0 * (1 / (N + 1))\n", + "\n", + "X[0, :, 0] = X0\n", + "X[1, :, 0] = X0\n", + "\n", + "plt.figure(1, figsize=(24, 18))\n", + "for n in range(Nt - 1):\n", + " Y = F(X[:, :, n])\n", + " X[:, :, n + 1] = X[:, :, n] + (h / 2) * Y + (h / 2) * F(X[:, :, n] + h * Y)\n", "\n", - "plt.figure(1,figsize=(24,18))\n", - "for n in range(Nt-1):\n", - " Y=F(X[:,:,n])\n", - " X[:,:,n+1]=X[:,:,n]+(h/2)*Y+(h/2)*F(X[:,:,n]+h*Y)\n", - " \n", "for i in range(N):\n", - " plt.plot(t,X[0,i,:],'k')\n", - "plt.xlabel('t')\n", - "plt.ylabel('$x_i$')\n", - "plt.title('position x_i des globules rouges au cours du temps')\n" + " plt.plot(t, X[0, i, :], \"k\")\n", + "plt.xlabel(\"t\")\n", + "plt.ylabel(\"$x_i$\")\n", + "plt.title(\"position x_i des globules rouges au cours du temps\")" ] }, { diff --git a/L3/Equations Différentielles/TP3_Convergence.ipynb b/L3/Equations Différentielles/TP3_Convergence.ipynb index fead81c..533d281 100644 --- a/L3/Equations Différentielles/TP3_Convergence.ipynb +++ b/L3/Equations Différentielles/TP3_Convergence.ipynb @@ -76,14 +76,15 @@ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", + "\n", "## Question 1\n", "def mon_schema(t0, T, y0, h, f):\n", " t = np.arange(t0, t0 + T + h, h)\n", " y = 0 * t\n", " y[0] = y0\n", - " for n in range(len(t)-1):\n", - " yn1 = y[n] + h * f(t[n] + h / 2, y[n] + h/2 * f(t[n], y[n]))\n", - " y[n+1] = y[n] + h / 2 * (f(t[n], y[n]) + f(t[n+1], yn1))\n", + " for n in range(len(t) - 1):\n", + " yn1 = y[n] + h * f(t[n] + h / 2, y[n] + h / 2 * f(t[n], y[n]))\n", + " y[n + 1] = y[n] + h / 2 * (f(t[n], y[n]) + f(t[n + 1], yn1))\n", " return t, y" ] }, @@ -140,25 +141,27 @@ "## Question 2\n", "\n", "# f second membre de l'EDO\n", - "def f(t,y):\n", + "def f(t, y):\n", " return y + np.sin(t) * np.power(y, 2)\n", "\n", + "\n", "# sol. exacte de (P)\n", "def yex(t):\n", - " return 1 / (1/2 * np.exp(-t) + (np.cos(t)-np.sin(t)) / 2)\n", + " return 1 / (1 / 2 * np.exp(-t) + (np.cos(t) - np.sin(t)) / 2)\n", + "\n", "\n", "t0, T = 0, 0.5\n", "N = 100\n", "y0 = 1\n", - "t, y_app = mon_schema(t0, T, y0, T/N, f)\n", + "t, y_app = mon_schema(t0, T, y0, T / N, f)\n", "y_ex = yex(t)\n", "\n", "plt.figure(1)\n", - "plt.plot(t, y_ex, label='Solution exacte', lw=3)\n", - "plt.plot(t, y_app, '+ ', label=f'Solution approchée pour N={N}')\n", - "plt.title('Solutions approchées pour mon_schema')\n", - "plt.xlabel(f'$t$')\n", - "plt.ylabel(f'$y$')\n", + "plt.plot(t, y_ex, label=\"Solution exacte\", lw=3)\n", + "plt.plot(t, y_app, \"+ \", label=f\"Solution approchée pour N={N}\")\n", + "plt.title(\"Solutions approchées pour mon_schema\")\n", + "plt.xlabel(\"$t$\")\n", + "plt.ylabel(\"$y$\")\n", "plt.legend(fontsize=7)" ] }, @@ -212,15 +215,17 @@ "# Question 3\n", "plt.figure(2)\n", "\n", - "for s in range(2,11):\n", - " h=(1/2)/(2**s)\n", + "for s in range(2, 11):\n", + " h = (1 / 2) / (2**s)\n", " t, y_app = mon_schema(t0, T, y0, h, f)\n", - " plt.plot(t, y_app, label=f'h={h}')\n", + " plt.plot(t, y_app, label=f\"h={h}\")\n", "\n", "plt.legend(fontsize=7)\n", - "plt.xlabel(f'$t$')\n", - "plt.ylabel('$y^n$')\n", - "plt.title('Solutions approchées de (P) obtenus avec mon_schema pour différentes valeurs du pas h')" + "plt.xlabel(\"$t$\")\n", + "plt.ylabel(\"$y^n$\")\n", + "plt.title(\n", + " \"Solutions approchées de (P) obtenus avec mon_schema pour différentes valeurs du pas h\"\n", + ")" ] }, { @@ -252,23 +257,25 @@ } ], "source": [ - "E=[]\n", - "H=[]\n", + "E = []\n", + "H = []\n", "\n", "plt.figure(3)\n", - "for s in range(2,11):\n", - " h=(1/2)/(2**s)\n", + "for s in range(2, 11):\n", + " h = (1 / 2) / (2**s)\n", " t, y_app = mon_schema(t0, T, y0, h, f)\n", " y_ex = yex(t)\n", " err = np.max(np.abs(y_app - y_ex))\n", - " plt.plot(t, np.abs(y_app - y_ex), label=f'h={h}')\n", + " plt.plot(t, np.abs(y_app - y_ex), label=f\"h={h}\")\n", " E.append(err)\n", " H.append(h)\n", - " \n", + "\n", "plt.legend()\n", - "plt.xlabel(f'$t$')\n", - "plt.ylabel('$|y(t_n) - y^n|$')\n", - "plt.title('différence en valeur absolue entre sol. exacte et sol. approchée par mon_schema, pour différentes valeurs du pas h')" + "plt.xlabel(\"$t$\")\n", + "plt.ylabel(\"$|y(t_n) - y^n|$\")\n", + "plt.title(\n", + " \"différence en valeur absolue entre sol. exacte et sol. approchée par mon_schema, pour différentes valeurs du pas h\"\n", + ")" ] }, { @@ -304,13 +311,13 @@ "\n", "H, E = np.array(H), np.array(E)\n", "\n", - "plt.plot(T/H, E/H, label=f'$E_h / h$')\n", - "plt.plot(T/H, E/H**2, label=f'$E_h / h^2$')\n", + "plt.plot(T / H, E / H, label=\"$E_h / h$\")\n", + "plt.plot(T / H, E / H**2, label=\"$E_h / h^2$\")\n", "\n", "plt.legend()\n", - "plt.xlabel('N')\n", - "plt.ylabel('Erreur globale')\n", - "plt.title('Erreur globale en fonction de N')" + "plt.xlabel(\"N\")\n", + "plt.ylabel(\"Erreur globale\")\n", + "plt.title(\"Erreur globale en fonction de N\")" ] }, { @@ -344,14 +351,16 @@ "source": [ "plt.figure(5)\n", "\n", - "plt.plot(np.log(H), np.log(E), '+-', label='erreur')\n", - "plt.plot(np.log(H), np.log(H), '-', label='droite pente 1')\n", - "plt.plot(np.log(H), 2*np.log(H), '-', label='droite pente 2')\n", + "plt.plot(np.log(H), np.log(E), \"+-\", label=\"erreur\")\n", + "plt.plot(np.log(H), np.log(H), \"-\", label=\"droite pente 1\")\n", + "plt.plot(np.log(H), 2 * np.log(H), \"-\", label=\"droite pente 2\")\n", "\n", "plt.legend()\n", - "plt.title('Erreur pour la méthode mon_schema en echelle logarithmique : log(E) en fonction de log(h)')\n", - "plt.xlabel(f'$log(h)$')\n", - "plt.ylabel(f'$log(E)$')" + "plt.title(\n", + " \"Erreur pour la méthode mon_schema en echelle logarithmique : log(E) en fonction de log(h)\"\n", + ")\n", + "plt.xlabel(\"$log(h)$\")\n", + "plt.ylabel(\"$log(E)$\")" ] }, { @@ -444,24 +453,26 @@ " t = np.arange(t0, t0 + T + h, h)\n", " y = 0 * t\n", " y[0] = y0\n", - " for n in range(len(t)-1):\n", - " y[n+1] = y[n] + h * f(t[n+1], y[n+1])\n", + " for n in range(len(t) - 1):\n", + " y[n + 1] = y[n] + h * f(t[n + 1], y[n + 1])\n", " return t, y\n", "\n", + "\n", "def crank(t0, T, y0, h, f):\n", " t = np.arange(t0, t0 + T + h, h)\n", " y = 0 * t\n", " y[0] = y0\n", - " for n in range(len(t)-1):\n", - " y[n+1] = y[n] + h/2 * (f(t[n], y[n]) + f(t[n+1], y[n+1]))\n", + " for n in range(len(t) - 1):\n", + " y[n + 1] = y[n] + h / 2 * (f(t[n], y[n]) + f(t[n + 1], y[n + 1]))\n", " return t, y\n", "\n", + "\n", "def adams(t0, T, y0, h, f):\n", " t = np.arange(t0, t0 + T + h, h)\n", " y = 0 * t\n", " y[0] = y0\n", - " for n in range(1, len(t)-1):\n", - " y[n+1] = y[n] + h/2 * (3* f(t[n], y[n]) - f(t[n-1], y[n-1]))\n", + " for n in range(1, len(t) - 1):\n", + " y[n + 1] = y[n] + h / 2 * (3 * f(t[n], y[n]) - f(t[n - 1], y[n - 1]))\n", " return t, y" ] }, @@ -474,39 +485,41 @@ "outputs": [], "source": [ "def euler_explicite(t0, T, y0, h, f):\n", - " N = int(T/h)\n", + " N = int(T / h)\n", " n = len(y0)\n", - " t = np.linspace(t0, t0 + T, N+1)\n", - " y = np.zeros((N+1, n))\n", + " t = np.linspace(t0, t0 + T, N + 1)\n", + " y = np.zeros((N + 1, n))\n", " y[0,] = y0\n", " for n in range(N):\n", - " y[n+1] = y[n] + h * f(t[n], y[n])\n", + " y[n + 1] = y[n] + h * f(t[n], y[n])\n", " return t, y\n", "\n", + "\n", "def heun(t0, T, y0, h, f):\n", - " N = int(T/h)\n", + " N = int(T / h)\n", " n = len(y0)\n", - " t = np.linspace(t0, t0 + T, N+1)\n", - " y = np.zeros((N+1, n))\n", + " t = np.linspace(t0, t0 + T, N + 1)\n", + " y = np.zeros((N + 1, n))\n", " y[0,] = y0\n", " for n in range(N):\n", " p1 = f(t[n], y[n])\n", " p2 = f(t[n] + h, y[n] + h * p1)\n", - " y[n+1] = y[n] + h/2 * (p1 + p2)\n", + " y[n + 1] = y[n] + h / 2 * (p1 + p2)\n", " return t, y\n", "\n", + "\n", "def runge(t0, T, y0, h, f):\n", - " N = int(T/h)\n", + " N = int(T / h)\n", " n = len(y0)\n", - " t = np.linspace(t0, t0 + T, N+1)\n", - " y = np.zeros((N+1, n))\n", + " t = np.linspace(t0, t0 + T, N + 1)\n", + " y = np.zeros((N + 1, n))\n", " y[0,] = y0\n", " for n in range(N):\n", " p1 = f(t[n], y[n])\n", - " p2 = f(t[n] + h/2, y[n] + h/2 * p1)\n", - " p3 = f(t[n] + h/2, y[n] + h/2 * p2)\n", - " p4 = f(t[n] + h, y[n] + h* p3)\n", - " y[n+1] = y[n] + h/6 * (p1 + 2*p2 + 2*p3 + p4)\n", + " p2 = f(t[n] + h / 2, y[n] + h / 2 * p1)\n", + " p3 = f(t[n] + h / 2, y[n] + h / 2 * p2)\n", + " p4 = f(t[n] + h, y[n] + h * p3)\n", + " y[n + 1] = y[n] + h / 6 * (p1 + 2 * p2 + 2 * p3 + p4)\n", " return t, y" ] }, @@ -624,13 +637,16 @@ "# Question 1\n", "a, b, c = 0.1, 2, 1\n", "\n", + "\n", "# f second membre de l'EDO\n", - "def f1(t,y):\n", - " return c * y * (1 - y/b)\n", + "def f1(t, y):\n", + " return c * y * (1 - y / b)\n", + "\n", "\n", "# sol. exacte de (P1)\n", "def yex1(t):\n", - " return b / (1 + (b-a)/a * np.exp(-c*t))\n", + " return b / (1 + (b - a) / a * np.exp(-c * t))\n", + "\n", "\n", "t0, T = 0, 15\n", "h = 0.2\n", @@ -639,25 +655,27 @@ "plt.figure()\n", "for schema in [euler_explicite, heun, runge]:\n", " t, y_app = schema(t0, T, y0, h, f1)\n", - " plt.plot(t, y_app.ravel(), '+ ', label=f'Solution approchée par {schema.__name__}')\n", + " plt.plot(t, y_app.ravel(), \"+ \", label=f\"Solution approchée par {schema.__name__}\")\n", "\n", - "t = np.arange(t0, t0+T+h, h)\n", + "t = np.arange(t0, t0 + T + h, h)\n", "y_ex = yex1(t)\n", - "plt.plot(t, y_ex, label='Solution exacte', lw=1)\n", - "plt.title(f'Solutions approchées pour le schema {schema.__name__}')\n", - "plt.xlabel(f'$t$')\n", - "plt.ylabel(f'$y$')\n", + "plt.plot(t, y_ex, label=\"Solution exacte\", lw=1)\n", + "plt.title(f\"Solutions approchées pour le schema {schema.__name__}\")\n", + "plt.xlabel(\"$t$\")\n", + "plt.ylabel(\"$y$\")\n", "plt.legend(fontsize=7)\n", "\n", "plt.figure()\n", - "for schema in [euler_explicite, heun, runge]: \n", + "for schema in [euler_explicite, heun, runge]:\n", " t, y_app = schema(t0, T, y0, h, f1)\n", - " plt.plot(t, np.abs(y_app.ravel() - yex1(t)), label=f'Schema {schema.__name__}')\n", - " \n", + " plt.plot(t, np.abs(y_app.ravel() - yex1(t)), label=f\"Schema {schema.__name__}\")\n", + "\n", "plt.legend()\n", - "plt.xlabel(f'$t$')\n", - "plt.ylabel('$|y(t_n) - y^n|$')\n", - "plt.title(f'différence en valeur absolue entre sol. exacte et sol. approchée, pour différents schemas')" + "plt.xlabel(\"$t$\")\n", + "plt.ylabel(\"$|y(t_n) - y^n|$\")\n", + "plt.title(\n", + " \"différence en valeur absolue entre sol. exacte et sol. approchée, pour différents schemas\"\n", + ")" ] }, { @@ -696,24 +714,26 @@ " Z[1] = -Y[0] + np.cos(t)\n", " return Z\n", "\n", + "\n", "def yexF(t):\n", - " return 1/2 * np.sin(t) * t + 5 * np.cos(t) + np.sin(t),\n", + " return (1 / 2 * np.sin(t) * t + 5 * np.cos(t) + np.sin(t),)\n", + "\n", "\n", "t0, T = 0, 15\n", "h = 0.2\n", - "Y0 = np.array([5,1])\n", + "Y0 = np.array([5, 1])\n", "\n", "plt.figure()\n", "for schema in [euler_explicite, heun, runge]:\n", " t, y_app = schema(t0, T, Y0, h, F)\n", - " plt.plot(t, y_app[:,0], '+ ', label=f'Solution approchée par {schema.__name__}')\n", + " plt.plot(t, y_app[:, 0], \"+ \", label=f\"Solution approchée par {schema.__name__}\")\n", "\n", - "t = np.arange(t0, t0+T+h, h)\n", + "t = np.arange(t0, t0 + T + h, h)\n", "y_ex = yexF(t)\n", - "plt.plot(t, y_ex[0], label='Solution exacte', lw=3)\n", - "plt.title('Solutions approchées par differents schemas')\n", - "plt.xlabel(f'$t$')\n", - "plt.ylabel(f'$y$')\n", + "plt.plot(t, y_ex[0], label=\"Solution exacte\", lw=3)\n", + "plt.title(\"Solutions approchées par differents schemas\")\n", + "plt.xlabel(\"$t$\")\n", + "plt.ylabel(\"$y$\")\n", "plt.legend(fontsize=7)" ] }, @@ -730,16 +750,19 @@ "import matplotlib.pyplot as plt\n", "# Question 3\n", "\n", + "\n", "# f second membre de l'EDO\n", - "def f3(t,y):\n", - " return (np.cos(t) - y) / (1+t)\n", + "def f3(t, y):\n", + " return (np.cos(t) - y) / (1 + t)\n", + "\n", "\n", "# sol. exacte de (P1)\n", "def yex3(t):\n", - " return (np.sin(t) - 1/4) / (1 + t)\n", + " return (np.sin(t) - 1 / 4) / (1 + t)\n", + "\n", "\n", "t0, T = 0, 10\n", - "y0 = np.array([-1/4])" + "y0 = np.array([-1 / 4])" ] }, { @@ -793,15 +816,17 @@ "plt.figure()\n", "for schema in [euler_explicite, heun, runge]:\n", " plt.figure()\n", - " for s in range(2,11):\n", - " h=1/(2**s)\n", + " for s in range(2, 11):\n", + " h = 1 / (2**s)\n", " t, y_app = schema(t0, T, y0, h, f3)\n", - " plt.plot(t, y_app, label=f'h={h}')\n", + " plt.plot(t, y_app, label=f\"h={h}\")\n", "\n", " plt.legend(fontsize=7)\n", - " plt.xlabel(f'$t$')\n", - " plt.ylabel('$y^n$')\n", - " plt.title(f'Solutions approchées de (P) obtenus avec {schema.__name__} pour différentes valeurs du pas h')" + " plt.xlabel(\"$t$\")\n", + " plt.ylabel(\"$y^n$\")\n", + " plt.title(\n", + " f\"Solutions approchées de (P) obtenus avec {schema.__name__} pour différentes valeurs du pas h\"\n", + " )" ] }, { @@ -846,22 +871,24 @@ "for schema in [euler_explicite, heun, runge]:\n", " H, E = [], []\n", " plt.figure()\n", - " for s in range(2,11):\n", - " h=1/(2**s)\n", + " for s in range(2, 11):\n", + " h = 1 / (2**s)\n", " t, y_app = schema(t0, T, y0, h, f3)\n", " E.append(np.max(np.abs(yex3(t) - y_app.ravel())))\n", " H.append(h)\n", - " \n", + "\n", " H, E = np.array(H), np.array(E)\n", - " plt.plot(np.log(H), np.log(E), '+-', label='erreur')\n", - " plt.plot(np.log(H), np.log(H), '-', label='droite pente 1')\n", - " plt.plot(np.log(H), 2*np.log(H), '-', label='droite pente 2')\n", - " plt.plot(np.log(H), 3*np.log(H), '-', label='droite pente 3')\n", - " \n", + " plt.plot(np.log(H), np.log(E), \"+-\", label=\"erreur\")\n", + " plt.plot(np.log(H), np.log(H), \"-\", label=\"droite pente 1\")\n", + " plt.plot(np.log(H), 2 * np.log(H), \"-\", label=\"droite pente 2\")\n", + " plt.plot(np.log(H), 3 * np.log(H), \"-\", label=\"droite pente 3\")\n", + "\n", " plt.legend()\n", - " plt.title(f'Erreur pour la méthode {schema.__name__} en echelle logarithmique : log(E) en fonction de log(h)')\n", - " plt.xlabel(f'$log(h)$')\n", - " plt.ylabel(f'$log(E)$')" + " plt.title(\n", + " f\"Erreur pour la méthode {schema.__name__} en echelle logarithmique : log(E) en fonction de log(h)\"\n", + " )\n", + " plt.xlabel(\"$log(h)$\")\n", + " plt.ylabel(\"$log(E)$\")" ] }, { @@ -943,19 +970,20 @@ "a = 5\n", "t0, T = 0, 20\n", "H = [0.1, 0.05, 0.025]\n", - "Y0 = np.array([1/10, 1])\n", + "Y0 = np.array([1 / 10, 1])\n", + "\n", "\n", "def P(t, Y):\n", - " return np.array([Y[1], (a - Y[0]**2) * Y[1] - Y[0]])\n", + " return np.array([Y[1], (a - Y[0] ** 2) * Y[1] - Y[0]])\n", + "\n", "\n", "for schema in [euler_explicite, heun, runge]:\n", " plt.figure()\n", " for h in H:\n", " t, y_app = schema(t0, T, Y0, h, P)\n", - " plt.plot(t, y_app[:,0], '+ ', label=f'Solution approchée pour h={h}')\n", + " plt.plot(t, y_app[:, 0], \"+ \", label=f\"Solution approchée pour h={h}\")\n", " plt.legend()\n", - " plt.title(f'Solutions approchees pour differents pas h par {schema.__name__}')\n", - " " + " plt.title(f\"Solutions approchees pour differents pas h par {schema.__name__}\")" ] }, { diff --git a/L3/Méthodes Numériques/TP1_Equation_de_Poisson.ipynb b/L3/Méthodes Numériques/TP1_Equation_de_Poisson.ipynb index ae0b733..c0d6abe 100644 --- a/L3/Méthodes Numériques/TP1_Equation_de_Poisson.ipynb +++ b/L3/Méthodes Numériques/TP1_Equation_de_Poisson.ipynb @@ -240,22 +240,25 @@ "outputs": [], "source": [ "import numpy as np\n", + "\n", "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "\n", + "\n", "def A(M):\n", " return 2 * np.eye(M) - np.eye(M, k=-1) - np.eye(M, k=1)\n", "\n", + "\n", "def solution_approchée(f, M, a=0, b=1, ua=0, ub=0):\n", - " X = np.linspace(a, b + 1 if b == 0 else b, M+2)\n", - " U = np.zeros(M+2)\n", + " X = np.linspace(a, b + 1 if b == 0 else b, M + 2)\n", + " U = np.zeros(M + 2)\n", " U[0], U[-1] = ua, ub\n", - " \n", - " h = (b-a)/(M+1)\n", + "\n", + " h = (b - a) / (M + 1)\n", "\n", " delta = np.zeros(M)\n", - " delta[0], delta[-1] = ua/np.power(h, 2), ub/np.power(h, 2)\n", - " \n", + " delta[0], delta[-1] = ua / np.power(h, 2), ub / np.power(h, 2)\n", + "\n", " U[1:-1] = np.linalg.solve(A(M), h**2 * (f(X)[1:-1] + delta))\n", " return X, U" ] @@ -290,22 +293,25 @@ ], "source": [ "M = 50\n", - "h = 1/(M+1)\n", + "h = 1 / (M + 1)\n", + "\n", "\n", "def f1(x):\n", - " return (2 * np.pi)**2 * np.sin(2 * np.pi * x)\n", + " return (2 * np.pi) ** 2 * np.sin(2 * np.pi * x)\n", + "\n", "\n", "def u1(x):\n", " return np.sin(2 * np.pi * x)\n", "\n", + "\n", "x, U_app = solution_approchée(f1, M)\n", "plt.figure()\n", - "plt.scatter(x, U_app, label=f\"$A_M U_h = h² F$\")\n", - "plt.plot(x, u1(x), label='Solution exacte', color='red')\n", + "plt.scatter(x, U_app, label=\"$A_M U_h = h² F$\")\n", + "plt.plot(x, u1(x), label=\"Solution exacte\", color=\"red\")\n", "plt.legend()\n", - "plt.ylabel('f(x)')\n", - "plt.xlabel('x')\n", - "plt.title(f\"$-u''=f(x)$\")" + "plt.ylabel(\"f(x)\")\n", + "plt.xlabel(\"x\")\n", + "plt.title(\"$-u''=f(x)$\")" ] }, { @@ -340,21 +346,23 @@ "H, E = [], []\n", "for k in range(2, 12):\n", " M = 2**k\n", - " h = 1/(M+1)\n", - " \n", + " h = 1 / (M + 1)\n", + "\n", " x, U_app = solution_approchée(f1, M)\n", - " \n", + "\n", " e = np.abs(u1(x) - U_app)\n", - " plt.plot(x, e, label=f'{h}')\n", + " plt.plot(x, e, label=f\"{h}\")\n", " E.append(np.max(e))\n", " H.append(h)\n", "\n", - "H, E = np.array(H), np.array(E) \n", + "H, E = np.array(H), np.array(E)\n", "\n", - "plt.xlabel('$h$')\n", - "plt.ylabel('$\\max_{j=0,\\dots,M+1}|u(x_j)-u_j|$')\n", + "plt.xlabel(\"$h$\")\n", + "plt.ylabel(\"$\\max_{j=0,\\dots,M+1}|u(x_j)-u_j|$\")\n", "plt.legend(fontsize=7)\n", - "plt.title('Différence en valeur absolue entre la solution exacte et la solution approchée')" + "plt.title(\n", + " \"Différence en valeur absolue entre la solution exacte et la solution approchée\"\n", + ")" ] }, { @@ -387,12 +395,12 @@ ], "source": [ "plt.figure()\n", - "plt.plot(H, E/H, label=f'$E_h / h$')\n", - "plt.plot(H, E/H**2, label=f'$E_h / h^2$')\n", + "plt.plot(H, E / H, label=\"$E_h / h$\")\n", + "plt.plot(H, E / H**2, label=\"$E_h / h^2$\")\n", "plt.legend()\n", - "plt.xlabel('$h$')\n", - "plt.ylabel('Erreur globale')\n", - "plt.title('Erreur globale en fonction de $h$')" + "plt.xlabel(\"$h$\")\n", + "plt.ylabel(\"Erreur globale\")\n", + "plt.title(\"Erreur globale en fonction de $h$\")" ] }, { @@ -425,13 +433,15 @@ ], "source": [ "plt.figure()\n", - "plt.plot(np.log(H), np.log(E), '+-', label='erreur')\n", - "plt.plot(np.log(H), np.log(H), '-', label='droite pente 1')\n", - "plt.plot(np.log(H), 2*np.log(H), '-', label='droite pente 2')\n", + "plt.plot(np.log(H), np.log(E), \"+-\", label=\"erreur\")\n", + "plt.plot(np.log(H), np.log(H), \"-\", label=\"droite pente 1\")\n", + "plt.plot(np.log(H), 2 * np.log(H), \"-\", label=\"droite pente 2\")\n", "plt.legend()\n", - "plt.xlabel(f'$log(h)$')\n", - "plt.ylabel(f'$log(E)$')\n", - "plt.title('Erreur pour la méthode mon_schema en echelle logarithmique : log(E) en fonction de log(h)')" + "plt.xlabel(\"$log(h)$\")\n", + "plt.ylabel(\"$log(E)$\")\n", + "plt.title(\n", + " \"Erreur pour la méthode mon_schema en echelle logarithmique : log(E) en fonction de log(h)\"\n", + ")" ] }, { @@ -509,27 +519,31 @@ ], "source": [ "import numpy as np\n", + "\n", "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "\n", - "ua, ub = 1/2, 1/3\n", + "ua, ub = 1 / 2, 1 / 3\n", "a, b = 1, 2\n", "M = 49\n", "\n", + "\n", "def f2(x):\n", - " return -2/np.power((x+1), 3)\n", + " return -2 / np.power((x + 1), 3)\n", + "\n", "\n", "def u2(x):\n", - " return 1/(x+1)\n", + " return 1 / (x + 1)\n", + "\n", "\n", "x, U_app = solution_approchée(f2, M, a, b, ua, ub)\n", "plt.figure()\n", - "plt.scatter(x, U_app, label=f\"$A_M U_h = h² F$\")\n", - "plt.plot(x, u2(x), label='Solution exacte', color='red')\n", + "plt.scatter(x, U_app, label=\"$A_M U_h = h² F$\")\n", + "plt.plot(x, u2(x), label=\"Solution exacte\", color=\"red\")\n", "plt.legend()\n", - "plt.ylabel('f(x)')\n", - "plt.xlabel('x')\n", - "plt.title(f\"$-u''=f(x)$\")" + "plt.ylabel(\"f(x)\")\n", + "plt.xlabel(\"x\")\n", + "plt.title(\"$-u''=f(x)$\")" ] }, { @@ -565,19 +579,21 @@ "H, E = [], []\n", "for k in range(2, 12):\n", " M = 2**k\n", - " h = (b-a)/(M+1)\n", - " \n", + " h = (b - a) / (M + 1)\n", + "\n", " x, U_app = solution_approchée(f2, M, a, b, ua, ub)\n", - " \n", + "\n", " e = np.abs(u2(x) - U_app)\n", - " plt.plot(x, e, label=f'{h}')\n", + " plt.plot(x, e, label=f\"{h}\")\n", " E.append(np.max(e))\n", " H.append(h)\n", - " \n", - "plt.xlabel('$h$')\n", - "plt.ylabel('$\\max_{j=0,\\dots,M+1}|u(x_j)-u_j|$')\n", + "\n", + "plt.xlabel(\"$h$\")\n", + "plt.ylabel(\"$\\max_{j=0,\\dots,M+1}|u(x_j)-u_j|$\")\n", "plt.legend(fontsize=7)\n", - "plt.title('Différence en valeur absolue entre la solution exacte et la solution approchée')" + "plt.title(\n", + " \"Différence en valeur absolue entre la solution exacte et la solution approchée\"\n", + ")" ] }, { @@ -609,14 +625,14 @@ } ], "source": [ - "H, E = np.array(H), np.array(E) \n", + "H, E = np.array(H), np.array(E)\n", "plt.figure()\n", - "plt.plot(H, E/H, label=f'$E_h / h$')\n", - "plt.plot(H, E/H**2, label=f'$E_h / h^2$')\n", + "plt.plot(H, E / H, label=\"$E_h / h$\")\n", + "plt.plot(H, E / H**2, label=\"$E_h / h^2$\")\n", "plt.legend()\n", - "plt.xlabel('$h$')\n", - "plt.ylabel('Erreur globale')\n", - "plt.title('Erreur globale en fonction de $h$')" + "plt.xlabel(\"$h$\")\n", + "plt.ylabel(\"Erreur globale\")\n", + "plt.title(\"Erreur globale en fonction de $h$\")" ] }, { @@ -649,13 +665,15 @@ ], "source": [ "plt.figure()\n", - "plt.plot(np.log(H), np.log(E), '+-', label='erreur')\n", - "plt.plot(np.log(H), np.log(H), '-', label='droite pente 1')\n", - "plt.plot(np.log(H), 2*np.log(H), '-', label='droite pente 2')\n", + "plt.plot(np.log(H), np.log(E), \"+-\", label=\"erreur\")\n", + "plt.plot(np.log(H), np.log(H), \"-\", label=\"droite pente 1\")\n", + "plt.plot(np.log(H), 2 * np.log(H), \"-\", label=\"droite pente 2\")\n", "plt.legend()\n", - "plt.xlabel(f'$log(h)$')\n", - "plt.ylabel(f'$log(E)$')\n", - "plt.title('Erreur pour la méthode mon_schema en echelle logarithmique : log(E) en fonction de log(h)')" + "plt.xlabel(\"$log(h)$\")\n", + "plt.ylabel(\"$log(E)$\")\n", + "plt.title(\n", + " \"Erreur pour la méthode mon_schema en echelle logarithmique : log(E) en fonction de log(h)\"\n", + ")" ] }, { @@ -732,22 +750,25 @@ ], "source": [ "def An(M, h):\n", - " mat = 2*np.eye(M) - np.eye(M, k=1) - np.eye(M, k=-1)\n", - " mat[0,0] = 1\n", + " mat = 2 * np.eye(M) - np.eye(M, k=1) - np.eye(M, k=-1)\n", + " mat[0, 0] = 1\n", " mat[-1, -1] = 1\n", " return mat + h**2 * np.eye(M)\n", "\n", + "\n", "def f3(x):\n", - " return (np.power(2 * np.pi, 2) + 1 ) * np.cos(2*np.pi * x)\n", + " return (np.power(2 * np.pi, 2) + 1) * np.cos(2 * np.pi * x)\n", + "\n", "\n", "def u3(x):\n", - " return np.cos(2*np.pi * x)\n", + " return np.cos(2 * np.pi * x)\n", + "\n", "\n", "def solution_neumann(f, M, a, b):\n", - " X = np.linspace(a, b, M+2)\n", - " U = np.zeros(M+2)\n", - " h = 1/(M+1)\n", - " \n", + " X = np.linspace(a, b, M + 2)\n", + " U = np.zeros(M + 2)\n", + " h = 1 / (M + 1)\n", + "\n", " U[1:-1] = np.linalg.solve(An(M, h), h**2 * f3(X[1:-1]))\n", " U[0], U[-1] = U[1], U[-2]\n", " return X, U\n", @@ -759,12 +780,14 @@ "for M in [49, 99, 499]:\n", " x, U_app = solution_neumann(f3, M, a, b)\n", "\n", - " plt.scatter(x, U_app, marker='+', s=3, label=\"$h^2({A_N}_h + I_M)U = h^2F$ pour M={M}\")\n", - "plt.plot(x, u3(x), label='Solution exacte', color='red')\n", + " plt.scatter(\n", + " x, U_app, marker=\"+\", s=3, label=\"$h^2({A_N}_h + I_M)U = h^2F$ pour M={M}\"\n", + " )\n", + "plt.plot(x, u3(x), label=\"Solution exacte\", color=\"red\")\n", "plt.legend(fontsize=8)\n", - "plt.ylabel('f(x)')\n", - "plt.xlabel('x')\n", - "plt.title(f\"$-u''(x) + u(x)=f(x)$\")" + "plt.ylabel(\"f(x)\")\n", + "plt.xlabel(\"x\")\n", + "plt.title(\"$-u''(x) + u(x)=f(x)$\")" ] }, { @@ -800,19 +823,21 @@ "H, E = [], []\n", "for k in range(2, 12):\n", " M = 2**k\n", - " h = (b-a)/(M+1)\n", - " \n", + " h = (b - a) / (M + 1)\n", + "\n", " x, U_app = solution_neumann(f3, M, a, b)\n", - " \n", + "\n", " e = np.abs(u3(x) - U_app)\n", - " plt.plot(x, e, label=f'{h}')\n", + " plt.plot(x, e, label=f\"{h}\")\n", " E.append(np.max(e))\n", " H.append(h)\n", - " \n", - "plt.xlabel('$h$')\n", - "plt.ylabel('$\\max_{j=0,\\dots,M+1}|u(x_j)-u_j|$')\n", + "\n", + "plt.xlabel(\"$h$\")\n", + "plt.ylabel(\"$\\max_{j=0,\\dots,M+1}|u(x_j)-u_j|$\")\n", "plt.legend(fontsize=7)\n", - "plt.title('Différence en valeur absolue entre la solution exacte et la solution approchée')" + "plt.title(\n", + " \"Différence en valeur absolue entre la solution exacte et la solution approchée\"\n", + ")" ] }, { @@ -845,13 +870,15 @@ ], "source": [ "plt.figure()\n", - "plt.plot(np.log(H), np.log(E), '+-', label='erreur')\n", - "plt.plot(np.log(H), np.log(H), '-', label='droite pente 1')\n", - "plt.plot(np.log(H), 2*np.log(H), '-', label='droite pente 2')\n", + "plt.plot(np.log(H), np.log(E), \"+-\", label=\"erreur\")\n", + "plt.plot(np.log(H), np.log(H), \"-\", label=\"droite pente 1\")\n", + "plt.plot(np.log(H), 2 * np.log(H), \"-\", label=\"droite pente 2\")\n", "plt.legend()\n", - "plt.xlabel(f'$log(h)$')\n", - "plt.ylabel(f'$log(E)$')\n", - "plt.title('Erreur pour la méthode mon_schema en echelle logarithmique : log(E) en fonction de log(h)')" + "plt.xlabel(\"$log(h)$\")\n", + "plt.ylabel(\"$log(E)$\")\n", + "plt.title(\n", + " \"Erreur pour la méthode mon_schema en echelle logarithmique : log(E) en fonction de log(h)\"\n", + ")" ] }, { @@ -959,7 +986,11 @@ "outputs": [], "source": [ "def v(x):\n", - " return 4*np.exp(-500*np.square(x-.8)) + np.exp(-50*np.square(x-.2))+.5*np.random.random(x.shape)" + " return (\n", + " 4 * np.exp(-500 * np.square(x - 0.8))\n", + " + np.exp(-50 * np.square(x - 0.2))\n", + " + 0.5 * np.random.random(x.shape)\n", + " )" ] } ], diff --git a/L3/Projet Numérique/Segregation.ipynb b/L3/Projet Numérique/Segregation.ipynb index 408bb60..2df9548 100644 --- a/L3/Projet Numérique/Segregation.ipynb +++ b/L3/Projet Numérique/Segregation.ipynb @@ -2,19 +2,15 @@ "cells": [ { "cell_type": "code", + "execution_count": 1, "id": "8311f569-6f93-4a3a-ab5f-917c4badc2e0", "metadata": { - "tags": [], "ExecuteTime": { "end_time": "2024-09-17T20:41:31.731363Z", "start_time": "2024-09-17T20:41:14.008637Z" - } + }, + "tags": [] }, - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import itertools" - ], "outputs": [ { "name": "stderr", @@ -24,18 +20,24 @@ ] } ], - "execution_count": 1 + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import itertools" + ] }, { "cell_type": "code", + "execution_count": 3, "id": "78b05b39-bad1-4d1c-897f-153e9697f477", "metadata": { - "tags": [], "ExecuteTime": { "end_time": "2024-09-17T20:41:49.263556Z", "start_time": "2024-09-17T20:41:49.253326Z" - } + }, + "tags": [] }, + "outputs": [], "source": [ "class ModeleSchelling:\n", " def __init__(self, M, p, L):\n", @@ -47,9 +49,11 @@ "\n", " def initialisation_grille(self):\n", " grille = np.zeros((self.M, self.M), dtype=int)\n", - " occupes = np.random.choice(self.M * self.M, size=int((1 - self.p) * self.M * self.M), replace=False)\n", + " occupes = np.random.choice(\n", + " self.M * self.M, size=int((1 - self.p) * self.M * self.M), replace=False\n", + " )\n", " self.Ntot = len(occupes)\n", - " \n", + "\n", " for occupe in occupes:\n", " i, j = divmod(occupe, self.M)\n", " grille[i, j] = np.random.choice([-1, 1])\n", @@ -57,7 +61,7 @@ " return grille\n", "\n", " def afficher_grille(self, title):\n", - " color = plt.imshow(self.grille, cmap='coolwarm', interpolation='nearest')\n", + " color = plt.imshow(self.grille, cmap=\"coolwarm\", interpolation=\"nearest\")\n", " plt.colorbar(color)\n", " plt.title(title)\n", " plt.show()\n", @@ -66,42 +70,51 @@ " groupe = self.grille[agent[0], agent[1]]\n", " count_similaires = 0\n", " count_differents = 0\n", - " \n", + "\n", " voisins = []\n", - " for (i,j) in list(itertools.product([x-1, x, x+1], [y-1, y, y+1])):\n", + " for i, j in list(itertools.product([x - 1, x, x + 1], [y - 1, y, y + 1])):\n", " if 0 <= i < self.M and 0 <= j < self.M and (i, j) != (x, y):\n", " voisins.append((i, j))\n", - " \n", + "\n", " for voisin in voisins:\n", " i, j = voisin\n", " case = self.grille[i, j]\n", - " if case == 0: pass\n", + " if case == 0:\n", + " pass\n", " else:\n", " if case == groupe:\n", " count_similaires += 1\n", - " else: \n", + " else:\n", " count_differents += 1\n", - " \n", - " if count_similaires+count_differents == 0:\n", + "\n", + " if count_similaires + count_differents == 0:\n", " return False\n", " else:\n", - " return float(count_similaires/(count_similaires+count_differents)) >= self.L\n", - " \n", + " return (\n", + " float(count_similaires / (count_similaires + count_differents))\n", + " >= self.L\n", + " )\n", + "\n", " def clusters(self):\n", " visited = np.zeros_like(self.grille, dtype=bool)\n", " clusters = []\n", "\n", - " def dfs(i, j, groupe, cluster): # Depth-First Search \n", + " def dfs(i, j, groupe, cluster): # Depth-First Search\n", " stack = [(i, j)]\n", "\n", " while stack:\n", " i, j = stack.pop()\n", "\n", - " if 0 <= i < self.M and 0 <= j < self.M and not visited[i, j] and self.grille[i, j] == groupe:\n", + " if (\n", + " 0 <= i < self.M\n", + " and 0 <= j < self.M\n", + " and not visited[i, j]\n", + " and self.grille[i, j] == groupe\n", + " ):\n", " visited[i, j] = True\n", " cluster.add((i, j))\n", "\n", - " for (di, dj) in [(-1, 0), (1, 0), (0, -1), (0, 1)]:\n", + " for di, dj in [(-1, 0), (1, 0), (0, -1), (0, 1)]:\n", " stack.append((i + di, j + dj))\n", "\n", " added_clusters = set()\n", @@ -111,94 +124,110 @@ " for i, j in indices:\n", " current_cluster = set()\n", " dfs(i, j, groupe, current_cluster)\n", - " \n", + "\n", " if current_cluster and frozenset(current_cluster) not in added_clusters:\n", " clusters.append((groupe, len(current_cluster)))\n", " added_clusters.add(frozenset(current_cluster))\n", "\n", " return clusters\n", - " \n", + "\n", " def coef_segregation(self):\n", " S = 0\n", " clusters = self.clusters()\n", " for i in range(len(clusters)):\n", - " S += int(clusters[i][1])**2\n", + " S += int(clusters[i][1]) ** 2\n", " return S * 2 / (self.Ntot**2)\n", "\n", " def simuler(self, T=400, move_satisfaits=True):\n", - " for t in range(1, int((1-self.p)*self.M**2 * T)):\n", - " agents = [(i, j) for i, row in enumerate(self.grille) for j, val in enumerate(row) if val != 0]\n", + " for t in range(1, int((1 - self.p) * self.M**2 * T)):\n", + " agents = [\n", + " (i, j)\n", + " for i, row in enumerate(self.grille)\n", + " for j, val in enumerate(row)\n", + " if val != 0\n", + " ]\n", " agent = agents[np.random.randint(0, len(agents) - 1)]\n", - " \n", + "\n", " while not move_satisfaits and self.satisfaisante(agent[0], agent[1], agent):\n", " agents.remove(agent)\n", " if len(agents) == 0:\n", " break\n", " agent = agents[np.random.randint(0, len(agents) - 1)]\n", - " \n", - " cases_non_occupees = [(i, j) for i, row in enumerate(self.grille) for j, val in enumerate(row) if val == 0]\n", - " nouvelle_case = cases_non_occupees[np.random.randint(0, len(cases_non_occupees) - 1)]\n", - " \n", + "\n", + " cases_non_occupees = [\n", + " (i, j)\n", + " for i, row in enumerate(self.grille)\n", + " for j, val in enumerate(row)\n", + " if val == 0\n", + " ]\n", + " nouvelle_case = cases_non_occupees[\n", + " np.random.randint(0, len(cases_non_occupees) - 1)\n", + " ]\n", + "\n", " while not self.satisfaisante(nouvelle_case[0], nouvelle_case[1], agent):\n", " cases_non_occupees.remove(nouvelle_case)\n", " if len(cases_non_occupees) == 0:\n", " break\n", - " nouvelle_case = cases_non_occupees[np.random.randint(0, len(cases_non_occupees) - 1)]\n", - " \n", - " self.grille[nouvelle_case[0]][nouvelle_case[1]] = self.grille[agent[0]][agent[1]]\n", + " nouvelle_case = cases_non_occupees[\n", + " np.random.randint(0, len(cases_non_occupees) - 1)\n", + " ]\n", + "\n", + " self.grille[nouvelle_case[0]][nouvelle_case[1]] = self.grille[agent[0]][\n", + " agent[1]\n", + " ]\n", " self.grille[agent[0]][agent[1]] = 0\n", " cases_non_occupees.append(agent)\n", - " self.afficher_grille(f'Configuration Finale de T={T} pour (M, p, L) = ({self.M},{self.p},{self.L})')\n" - ], - "outputs": [], - "execution_count": 3 + " self.afficher_grille(\n", + " f\"Configuration Finale de T={T} pour (M, p, L) = ({self.M},{self.p},{self.L})\"\n", + " )" + ] }, { "cell_type": "code", + "execution_count": null, "id": "2d3b256a-9934-45bf-b865-815618d9350e", "metadata": { - "tags": [], + "ExecuteTime": { + "start_time": "2024-09-17T20:41:52.787394Z" + }, "jupyter": { "is_executing": true }, - "ExecuteTime": { - "start_time": "2024-09-17T20:41:52.787394Z" - } + "tags": [] }, + "outputs": [ + { + "data": { + "image/png": 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85bYBoKSkBImJiR7PJSYmoqKiAj/88AP+85//oK6uzucx//rXvyzpgy+WDwBkRzLV1dUedc/rIxIbHKlo5vAeOT5x3QqPP8/ee6/wdRHRufrXRP0wOrZH4TbX/0+Zc1JwpHFbDfXBqB33PgBAUdoYv9ox6pPK/barLaN21j7aocHX3O+LlX3SE32PVb7jMn0wIvqOy9wX/f3W/wxY9d7113H/LPXff6OfQ1Ef9Nzb1n9/9GTum6gfRvdJpk/uVPrnfv8rKytx9c9+jpYtW5puz0hNTQ3+gzpsiu2CZgrL2c7BiQmVX6G4uNi1BToAy/71H8wsHwCcPn1aaiSTl5fnKunprpkjAs0c3lt+RjVprjsuUvi6iOhcX9c2e6z7D0FUkwqpPvnbB6N29D+I7q8b3TNRn1Tut11tGbUj+qVk5fdJRPQ9VvmOy/TBiOg7LnNf9Pdb/zNg1XsXfceN+iAi8/Nt5Xdc1A+j+yTTJ3cq/fP1cxWIMG4z+P67wm//XQUXFxfnMQCwUlJSktdmaqWlpYiLi0PTpk0RGRmJyMhIn8ckJSXZ0icgCOoA5OTkYNasWa4/V1RUICUlBU9ct8LnlzHn1Sni9gSv512/1u9+9S7a5fHnz3r4vxOb/jo57uca9EGmj3ru792rnRknPP/s9rrRPdWT6aOoT39a/hPPg936aNQnUR+Mzv3s1YbbyYH/ZO+b6Nw8ic9D+DlbSNQPmffufr8BuXvs9fkI3vtvdN9x9+vof36t6oO+baNjZT47/bnuv5NydO9H+DtHR+U7o/+Zdb/n7vfhnKY+Le8vR5QDEQoDDYdm/yAlIyMDr7zyisdze/fudW2xHh0djbS0NOTn57sWEzqdTuTn5yM7O9u2flk+AGjbtq3USMbKhRZERBReHE0i4PARLvb7fBOJcJWVlTh69Kjrz8eOHcPhw4fRunVrdOzYETk5OThx4gQ2b94MALj77rvx9NNP48EHH8Rvf/tb7Nu3D3/5y1+wa9f/BnWzZs3ChAkTMHDgQAwaNAjLly9HVVWV3xuUmWH5AKCxRjJERBR+IiIdiIgw/6/4CKf8ue+//77H9ub1s9gTJkzAxo0bcfLkSY+txVNTU7Fr1y7MnDkTTz31FC655BL83//9H7KyslzH3Hrrrfjuu+8wb948lJSUoH///ti9e7dXON1KtoQAAjmSkZkilCGaTjQiMz2qn1KTCTWo9EF0b6wKQxi1pb/H7oxCMKL3Z3SuaLrdaApXxGxoRP9no3Y8vjO6e6jSf/19E30+MmS+EzLnyrQr+51WCe+IKIWu3L7H+s9KNOWvP1b/nRF99/R9+g38+317obYK2GPN77JgNGTIEIhK6Piq8jdkyBB8+OGHwnazs7MD+g9lWwYAjTGSISKi8ONo4oBDYQbAYWIG4MfCtkWAgR7JEBFR+ImICnwI4MeCewEQERGFoUZPA2zI7L33unI73WNLMrEvK6nExUXnqsT8ZdY/iFLu9Ixike6fgSi+btSuzH2RihvrzhV9Z4xinirrBayKSYtSr4yuKfN5iGL+KnF8mXQ3mf6L2jE6VyXGr5JOLPq5k0k99vqsRH0SxPwBuRRUrzVLrzZwYAAxBGBe0A4AiIiIjEREOhARqRACqAvfAQBDAERERGGIMwBERBSyHJEOOBRmABwI3xmAkBgAuMel9DEnURzWylKtenbl0cvkcavE1I1KEot4xKAV+qTnHl/U5xvrKb13QTsyVGLOMp+z/l6I7pOofCwgvhcqNSlkSnCrlBh2b0um7K6KQNVSkInrq9SnUFm/Eag1VzKUQwBhPABgCICIiCgMhcQMABERkS+OCMUsgABsBhSsQmIA4D4NJZPOJmoHUJu2VNnVy6pj9dzvjUoanZ5MuqG+/x59MkgZ+kywa2KgSrPaVfpXhuHuc2730ahEtUwZZNGUv1H6rahdlfCHyufjTmVqXqb/XiXEA/R9EvXJKLRjV+gqUByREXBEKmwGBPnNgH4sQmIAQERE5AvXAJjHNQBERERhiDMAREQUshwOVgI0K2gHAE9ctwJRTZoDEKcB6mOgMrFIGY21TawMq9K2jI4V3WOZtDOVlEGjtswSlVA2SrlT+Zw97ptBfNrslriyPK5j8N2SWRciuo6oXa8+SXzmRrF5u9ZzqJBJyxSmkRpsba6yBiMY7psjEkohAEf4LgFgCICIiCgcBe0MABERkRHlSoBMAyQiIgo9jogIOCIU0gAVzg11Dk3TgioCUlFRgfj4eAzK2uVaAyBiVxzZrni0nXm0ZuOjRjnSVsa6zbajch2V69r1nbBrTYlo62D9daxcm2L2uydqBxDHwVXqCeiJ1mQYra0x+72QvU/BEG/39x5fqK3CoT0jUF5ejri4OFv6Uv93xf6rB6FFlPl/y1ZeuIAhBw7Z2tdgxRkAIiIKWcqVABXODXUcABARUchSLgQUxmsAwjf4QUREFMaCdgZg9t570cwRCUAu77kx8vNVttuUYRQfFeWPC/vUSDF/UbxaNndcJpdcJFC1Caz6nor2CQDgtaeC2Vi9yhayeoHaplelXoJdWyG7U9mfQE+mZoDKz4q/557T6nCrsCXrMARgXtAOAIiIiIw4HIpZAI7wnQjnAICIiEIWZwDMC7kBgJ1TkaLjGytcIFPiU0RlitCq+6RvR1Ra185p5ECke+rJvB+VY/Wfs1EJX3cq28LKUAlp2BXqEZEpby1zHdnS0qK2ZO6Tnky562AsBUzmhdwAgIiIqJ5yFgA3AyIiIgo9DAGYF76rH4iIiMJYyJUClolB2bUNqf51lfUBKvF2mTKpKn2SYWVpY3dWllC2qhRwoPog0yez7fhiV8qg6HurEm9XKQ1sVRlhK9v195pGbVv5u8zf3xWBLAV86MYhaNFEoRRw7QUM2rmfpYCJiIhCCUMA5jEEQEREFIY4A0BERCGLMwDmhdwaAD2ZcrIq8XYZKnF8u7ZvVTlXJS4r6kNjrT2wKrZtZ2xV5rpWHStD9N5l197YVf9BZYtiu/Lb3X/eVbYZDlS5brPXCeQagMLRQ5XXAKT9LT8s1wAwBEBERBSGOAAgIqKQdTEEEKHwMBcCWLVqFTp37ozY2Fikp6fj0KFDDR47ZMgQOBwOr8eIEf+bBZo4caLX68OHDzfVN3+FxBoA0RShfhotx+3/7UqxM6JSwjNH97rH9LtB6V+Z3ef00/ruvMqB6t67VVOTVk1b6tuyq0SvnWVQRf23q8StSppsY5H5nK0Kfxj9LpBJufMIUUr2yexna2X4T1RaurG+L44ItUqAjjr5c1944QXMmjULa9asQXp6OpYvX46srCwUFRWhffv2Xse/+OKLqKmpcf35+++/R79+/TBmzBiP44YPH44NGza4/hwTEyPdNxmcASAiopBVvwhQ5SFr2bJlmDx5MiZNmoTevXtjzZo1aNasGdavX+/z+NatWyMpKcn12Lt3L5o1a+Y1AIiJifE4rlWrVqbuib84ACAiorBXUVHh8aiurvZ5XE1NDQoLC5GZmel6LiIiApmZmSgoKPDrWs8++yzGjh2L5s09F7rv378f7du3R48ePTB16lR8//335t+QHzgAICKikKUW/7/4AICUlBTEx8e7Hnl5eT6vd/r0adTV1SExMdHj+cTERJSUlBj299ChQ/j0009x5513ejw/fPhwbN68Gfn5+ViyZAnefPNNXH/99airqzN5Z4yFxBoAs/FdlRihPjYv6pPsdc1Sia97bbMqKBussi2pXWlodm0PbNW2wr5YVXLYKFVUpk/urCxtHKitnEXsSpM1Wv8js/ZGhtfaA7ffSVZuxyyz5bjsuoVAsKoOQHFxsUcaoF3x92effRaXXXYZBg0a5PH82LFjXf9/2WWXoW/fvujatSv279+PoUOH2tIXzgAQEVHYi4uL83g0NABo27YtIiMjUVpa6vF8aWkpkpKShNeoqqrC1q1bcccddxj2p0uXLmjbti2OHj3q/5uQxAEAERGFrEAvAoyOjkZaWhry8/NdzzmdTuTn5yMjI0N47rZt21BdXY3bb7/d8Dr//ve/8f3336NDhw5S/ZPBAQAREYUsq9YAyJg1axbWrVuHTZs24ciRI5g6dSqqqqowadIkAMD48eORk6MPmFyc/h81ahTatGnj8XxlZSUeeOABvPvuu/j666+Rn5+PkSNHolu3bsjKyjJ3Y/wQEmsARPR5qqJSwEbMbqFp9hr+XAeCvGE789JF15FhNr/dytK5IqLvjyqZuLhUDDpAtRVEx4q+x0bHqpxrlpXrWkRtqxxrWBZc2LJ/11Tl7307p9XhVsuuGnxuvfVWfPfdd5g3bx5KSkrQv39/7N6927Uw8Pjx44jQDSyKiopw4MABvPbaa17tRUZG4uOPP8amTZtQVlaG5ORkDBs2DAsXLrS1FkDIDwCIiCh8NdZmQNnZ2cjOzvb52v79+72e69GjBxraeqdp06bYs2ePqX6o4ACAiIhCltlpfPfzw1XI7Qaoknpl1VQ24DldJ9rBT3+uzO5/VvZJhcy0rMwucaLpd5nUN19tN9QHo/Os3KnOrl0HRcca9UnmOiq76ckw+zNrZRqjiMp1GissF4jvnq/j6wVyN8DPJo9Ey+gmpts5W1OL3uv+Hpa7AXIGgIiIQpfDcfGhcn6Y4gCAiIhClsOhuAaAAwAiIqLQwzUA5oXcGgC9xor7mU0ZtCrGZkQm3m7UB/25ojLCoq1T7SwR695H0XatRgIVcxbdN6P+W/Wdt/LzkFnrobKdrlXpn3oq6x9k+m+2D/70oyFWrvXw9/0Ecg3Av6aORssYhTUA1bXoufpvXANAREQUShorDfDHgAMAIiIKWQwBmBe+75yIiCiMBe0MwOy996KZIxKAdfF2K1kVh9XHR72Y3PpVVFJY9twcwXao+nZ+A911LYqlGjG7vbGVcXyVegke982m9SeyfRKtq9B/b3NEaz0kStp6/TwIvv92rWGQPVemHavWC8i8d5lt0WXvQ6B+34o4ItSm8R1h/M/goB0AEBERGeEaAPPCeOxDREQUvjgDQEREoSsi4uJD5fwwFbQDgCeuW+GzDkCg6n9bmZMrivt99qpBPwSvWVlLX8SqugbB8tn5+5qvtsz2w+uz0q+VEJDpv6VrGiTi+qK1Hl51AHTfeffj9fdF9H5kth22c62E2W2VrYyZe9XfcLvHMtcRtROsHA6HUjW/cK4EGL5DHyIiojAWtDMARERERlgHwLygHQD4mwYoU+LWyjQbUZ+s3L5VlIql/7N7uEBmilmW2ftoZclkK0usWkXU7p90f7ar9KxRn6zaNlnP/Xvq9d2TSAO0MiykEj6wKg1Qpk8yjNJvcwTHivqo/51idN3GSv1zxywA84J2AEBERGTIobgIMIwLAYTvOyciIgpjUgOAvLw8XHHFFWjZsiXat2+PUaNGoaioyOOY8+fPY/r06WjTpg1atGiB0aNHo7S01NJOExERAQD+GwIw+wBDAP558803MX36dFxxxRW4cOECfve732HYsGH47LPP0Lz5xZS9mTNnYteuXdi2bRvi4+ORnZ2NW265BW+//bZUx9zTAEXpVKI4uEo8TiUGrRJL1RPF5FTibx4xW8kUQbNpT0avub8ffToSljdcelZP5nO3c7tW99dVtii2cntpq/ogSjP1+uz0ljdc/tooBm3V1rV2lQm2cutgu+LtgdhS+ZxWh1tNtyTH4YiAQ2EaX+XcUCc1ANi9e7fHnzdu3Ij27dujsLAQP//5z1FeXo5nn30WW7ZswbXXXgsA2LBhA3r16oV3330XV155pVeb1dXVqK6udv25oqLCzPsgIiIiCUpDn/LycgBA69atAQCFhYWora1FZmam65iePXuiY8eOKCgo8NlGXl4e4uPjXY+UlBSVLhERUTipn8ZXeYQp0wMAp9OJGTNm4KqrrkKfPn0AACUlJYiOjkZCQoLHsYmJiSgpKfHZTk5ODsrLy12P4uJis10iIqIwU18HQOURrkynAU6fPh2ffvopDhw4oNSBmJgYxMTEeD3vXgfAnVe82sJ4u1VEsTujNQwqcUuZ9+ueNywba5SJw4rqGOi5t6UvQerVJ1FMWvcdEcVW7dyiWOZ4j/4brHdwv6eitRBGfVAppavPO3fvv0wc36tPEsdauU5HVALXa72DjTU2RAJRm0D2Gg39bjt79iww4HKptijwTA0AsrOz8fLLL+Ott97CJZdc4no+KSkJNTU1KCsr85gFKC0tRVJSknJniYiI3LEQkHlScx+apiE7Oxvbt2/Hvn37kJqa6vF6WloamjRpgvz8fNdzRUVFOH78ODIyMqzpMRERUT2H42IxH9OP8B0AODRN0/w9eNq0adiyZQv+/ve/o0ePHq7n4+Pj0bRpUwDA1KlT8corr2Djxo2Ii4vDPffcAwB45513/LpGRUUF4uPj8UJEV58hAD2VUqde036C3c8aIyVHfx0rU4xERPdFVmOkYskcaxSSEbWrZ+VOfKJ2hSWHDXaBtGoaORCpZFa3rXJdO8j8PtIfL5NCKCqXbiWvNEDnlygvL0dcXJwt16v/u+L4wrsQF+sdRva7nfPV6Dj3j7b2NVhJhQBWr14NABgyZIjH8xs2bMDEiRMBAE8++SQiIiIwevRoVFdXIysrC88884wlnSUiInLHEIB5UgMAfyYLYmNjsWrVKqxatcp0p4iIiPwSobgXALMAiIiIQo/D4YBDIY6vcm6oC4kBgNk4slHcUrSFphG7ysnKkCkRK8MrbqzQJ492FLZgldkG2qhP7m2pvFeZz9LK9QFmS2Pr21JaW9BIqXDuVLaXNiIqSy36rqmUyTZKfRW1LUpjlFkHYvRzFYzbAZN5ITEAICIi8onbAZvGAQAREYUsLgI0L3yHPkRERGEsaGcAGtoO2Ep2bevp73n+kNn61Ww8TibGqaeyHa0Mr+vo8/VNxrZl4sgqpZiNPhuzpXSNSgFbFReXWVtgtB2wSq0Fj/uki5lLxcgNSnB7rBNRWO+gsj5IqqaJwnU9jlWoG+HezoXaKmCP+fohUuoL+qicb8KqVavw2GOPoaSkBP369cPKlSsxaNAgn8du3LgRkyZN8nguJiYG58+fd/1Z0zTk5uZi3bp1KCsrw1VXXYXVq1eje/fupvrnD84AEBFR6GqE3QBfeOEFzJo1C7m5ufjggw/Qr18/ZGVl4dSpUw2eExcXh5MnT7oe33zzjcfrS5cuxYoVK7BmzRocPHgQzZs3R1ZWlscgwWocABAREUlYtmwZJk+ejEmTJqF3795Ys2YNmjVrhvXr1zd4jsPhQFJSkuuRmJjoek3TNCxfvhwPP/wwRo4cib59+2Lz5s349ttvsWPHDtveR9CGANx3AzSbXhWo8p6yJT1V2hYRTe+KpvllS4OKwh8y6Xmi1DLZkrBmd72zq3yvbJ/009lW9UHleKvSSmWm2424f59kUjaN0j1VwmlW3Sc9md97ojCFnd/xhq5zTqvDraavKsfhiIBDIQRQf25FRYXH8w3tVFtTU4PCwkLk5PzvWxQREYHMzEwUFBQ0eJ3Kykp06tQJTqcTl19+OR555BFceumlAIBjx46hpKQEmZmZruPj4+ORnp6OgoICjB071vT7E+EMABERhS6LQgApKSmIj493PfLy8nxe7vTp06irq/P4FzwAJCYmoqSkxOc5PXr0wPr16/H3v/8dzz33HJxOJwYPHox///vfAOA6T6ZNKwTtDAAREVGgFBcXe2wG5Otf/2ZlZGR47Ig7ePBg9OrVC3/84x+xcOFCy64jiwMAIiIKWY6ICDgUCgHVnxsXF+fXboBt27ZFZGQkSktLPZ4vLS1FUlKSX9ds0qQJBgwYgKNHjwKA67zS0lJ06NDBo83+/fv71aYZQTsAcE8DNEslNm9lzNOdlfE4UbzdsOyxRNxSfx1R6pnXexfE22XSq6zcJlYmtdKqPll5rMxnJ/N+vL5PgjUZovtmtJ7BqnU7Ku/d6HM3249AbWdsZUqwXd+ngHE4Lj5UzpcQHR2NtLQ05OfnY9SoUQAAp9OJ/Px8ZGdn+9VGXV0dPvnkE9xwww0AgNTUVCQlJSE/P9/1F35FRQUOHjyIqVOnSvVPRtAOAIiIiAxFOBR3A5QfPMyaNQsTJkzAwIEDMWjQICxfvhxVVVWuXP/x48fjJz/5iWsdwYIFC3DllVeiW7duKCsrw2OPPYZvvvkGd955J4CLGQIzZszAokWL0L17d6SmpmLu3LlITk52DTLswAEAERGRhFtvvRXfffcd5s2bh5KSEvTv3x+7d+92LeI7fvw4ItwGJf/5z38wefJklJSUoFWrVkhLS8M777yD3r17u4558MEHUVVVhSlTpqCsrAxXX301du/ejdjYWNveBwcAREQUugIcAqiXnZ3d4JT//v37Pf785JNP4sknnzTohgMLFizAggULTPXHjKAdALjXAXDntf2pRP60US6wXfnhKiViReeK4u0yMUKj+KFVW+ZaGbOVuY5KfNSqUq52bfts1AejtjwIysCq3FOVbXvN1neQFajPWXSsyj2WeU1Yu8OgJkigSn/LsGoRYDgK33dOREQUxoJ2BoCIiMhQI20G9GPAAQAREYUuh7kNfTzOD1MOTdO0xu6Eu4qKCsTHx+OFiK5+7QWg5x6TkqlLD3jWCdAfK7NlrqjegJXbAft7nq9zVeLtMtex6lyjPQfc77H+NT3RZ6eSOy6icv9V9pZQ+TzMtiv73ZNZj2KWlXtLGJ1rVZ9kqHweIirbAR/aMwLl5eV+Fdcxo/7vipJ18xDXzPxK+Ypz55E0eYGtfQ1WnAEgIqKQZdVmQOGIAwAiIgpdEYohAJVzQ9yPegAgSpMzPN4oFU40NbbccwpalGZjFFqwKjVRNIUu9d50fZIpEyxqB/C+F+706Z6i1ESjKXJRGmOg0vVExxqWcTbbQQMy08ii92b0nVBJAzT786AyxS8bSrSqT6JQlsoW43bdt8baDpjM+1EPAIiI6EeOWQCmcQBAREShq5EqAf4YcABAREShKyJCcTMgzgAEtUCVJDV7rlfMViLNzKuUsUVlUg1j2YI+ysTBjWKRMvdUVNbZru1PjV6zKw3NbFlX1euKWNWnPxm8rlLK2K40TWFbBut2zKb5GvVPtDYnUGWPzbZ7obYK2GN+nQIFRkgMAIiIiHziGgDTOAAgIqLQxTRA08J36ENERBTGQmIGwD0fVibP3IhKjrFVW4Aa5VeLagjIxNdlWBlvd4+X6tcLWLn1q13rROziFUd2W/+gslZFrzHeu9EW3VaVrZXpr+h+y7atP9fs+5H9XdAY5X5VvnsB43AohgDCdwYgJAYAREREPjEN0DSGAIiIiMJQSMwAqOymJ6IyjSx6TTRtJj1VZ3LnOr3GmvY2W7JUNqVLFCayKj1MZZc7L/rPVfAdsXIqWPQdFx0r2n1Rf66V4Sc9symEotLRZvrhL7umzANVBtnsZxnQUsCsA2BaSAwAiIiIfGIIwLTwHfoQERGFMc4AEBFR6GIhINOCdgDwxHUrENWkOQBxHEq0na6V2+eqxPKs7IeI2Ti/lXFKUazY6DoypWiFW+ZKvB+jrV5l0j2tLAPr77myMXOZ74hoy2hRyWpZVqVwito1SgO0atthPZn4u9E6C5k1GaJrWrX2ydfx9QJaCtihuAaAAwAiIqIQxDUApoXv0IeIiCiMcQaAiIhCF9cAmBa0A4DZe+9FM0ckAHE8TrSdrlG8UBQXVNl6V+VYmRinPg4oKpOsUgdAKjav64OolHGg1iUIy7rq46wS7Vi5/ayI6Dp2ri+xaj2NSk0N0esyazJUSohbWepbZm2B6Lr6LZcbY9tq0bkBrQPAEIBp4Tv0ISIiCmNBOwNARERkiJUATQvaAYB7GqCIytSXTOqMUbqYWUbT+KIpQ30f/iRI27IqnVC2Lfd7rJ9et3JXO/dwjv69WxWisTJ8o0LlvpndmVJ0vwG5nyU9u6av3cmke8q0a3SsSvhMlM7qdb8lriNiVRpgIGkOBzSFaXyVc0Nd+A59iIiIwljQzgAQEREZcjgUswDCdwaAAwAiIgpdTAM0LWgHAO5pgCJ2pSd5xbYUSsSKtqr1SmMUMLqOR1zQxthcIEreyqbceZQClmzLKjIpX8GQQihzrlH6rUqaqft6An1sW6a0tMz2yyqxej2z6wek+m9AJd1QZitto+tSaAnaAQAREZERLgI0L3znPoiIKPTVhwBUHiasWrUKnTt3RmxsLNLT03Ho0KEGj123bh1+9rOfoVWrVmjVqhUyMzO9jp84cSIcDofHY/jw4ab65i8OAIiIKHTVVwJUeUh64YUXMGvWLOTm5uKDDz5Av379kJWVhVOnTvk8fv/+/bjtttvwxhtvoKCgACkpKRg2bBhOnPAMTQ0fPhwnT550Pf785z+buiX+cmiaptl6BUkVFRWIj4/HCxFd/SoFLBN7tDL2K8o7N+qHiEoeunssT5SXLdsHPZXtaO0SiK2QZb9PMvdJdB09q8o6N9bPklVrJezaOtjoXJmfu1AoKW72eyo690JtFQ7tGYHy8nLExcVJtemv+r8rTr66EXHNm5lvp+ocOlw/Uaqv6enpuOKKK/D0008DAJxOJ1JSUnDPPfdgzpw5hufX1dWhVatWePrppzF+/HgAF2cAysrKsGPHDtPvRRZnAIiIKHTVVwJUeeDigML9UV1d7fNyNTU1KCwsRGZmplsXIpCZmYmCggK/unzu3DnU1taidevWHs/v378f7du3R48ePTB16lR8//33Jm+KfzgAICKikFW/CFDlAQApKSmIj493PfLy8nxe7/Tp06irq0NiYqLH84mJiSgpKfGrzw899BCSk5M9BhHDhw/H5s2bkZ+fjyVLluDNN9/E9ddfj7q6OpN3xhizAIiIKOwVFxd7hABiYmJsuc6jjz6KrVu3Yv/+/YiNjXU9P3bsWNf/X3bZZejbty+6du2K/fv3Y+jQobb0JWgHAD0Kt6Fly5YAPHNTrYw96snE/UR552av4es6/r4GqMX9ZZj9DGRinKL8b5U+6Fm5RqGx6g3Yxap4u9G+Gu45+jJb/AYLUW2CYGD0WdmxpiSw2wFbUwgoLi7OrzUAbdu2RWRkJEpLSz2eLy0tRVJSkvDcxx9/HI8++ihef/119O3bV3hsly5d0LZtWxw9etS2AQBDAEREFLI0R4TyQ0Z0dDTS0tKQn5/ves7pdCI/Px8ZGRkNnrd06VIsXLgQu3fvxsCBAw2v8+9//xvff/89OnToINU/GRwAEBERSZg1axbWrVuHTZs24ciRI5g6dSqqqqowadIkAMD48eORk/O//U+XLFmCuXPnYv369ejcuTNKSkpQUlKCyspKAEBlZSUeeOABvPvuu/j666+Rn5+PkSNHolu3bsjKyrLtfQRtCKAobYwrDdBjylBhm1s9lakvK7fXtaodmSlbf9sx6od+W1hRSqRUCEaw1bGv10Xv3ap0MNF2ubKsmsZX+W7JTLdbWnJbF875k8k0OjvDgaLyxHoy/fAKf7gzSCeW+TysStU1m5p4obYK2BOYkKTZXH6P8yXdeuut+O677zBv3jyUlJSgf//+2L17t2th4PHjxxER8b9/X69evRo1NTX41a9+5dFObm4u5s+fj8jISHz88cfYtGkTysrKkJycjGHDhmHhwoW2rUUAgngAQEREZESD/DS+/nwzsrOzkZ2d7fO1/fv3e/z566+/FrbVtGlT7Nmzx1Q/VHAAQEREoasRZgB+LJTWADz66KNwOByYMWOG67nz589j+vTpaNOmDVq0aIHRo0d7rZYkIiKixmV6BuC9997DH//4R69UhpkzZ2LXrl3Ytm0b4uPjkZ2djVtuuQVvv/226U7KbHNr1xasVm3famfcWGZbT5m4nz7O79H2ckFME+LPQx8PFaV76tcWqKRLilj5HRG1oxLbtmo9h0zsWua+SKfbun22ObpjVba59bcdX6+LUvtUvl8yKYNWre+wMw2woWMDmwboUEwD5AyAlMrKSowbNw7r1q1Dq1atXM+Xl5fj2WefxbJly3DttdciLS0NGzZswDvvvIN3333XZ1vV1dVeJRiJiIj8YVUlwHBkagAwffp0jBgxwqOMIQAUFhaitrbW4/mePXuiY8eODdZIzsvL8yi/mJKSYqZLREREJEF6ALB161Z88MEHPuskl5SUIDo6GgkJCR7Pi2ok5+TkoLy83PUoLi6W7RIREYWr+kqAKo8wJbUGoLi4GPfddx/27t3rUcNYRUxMjM88xyeuW4GoJs2V2rZyy0xR21auJVApqSoTt5TJb/cqeyzI19fz2DZZ344+ri9syZNVOeBWfh4yrweqnK+eqIaDKN9dZb2AEbP1K+zajlnUjq+27NqiWIXovolqdzTW91KFBgc0mJ/GVzk31EkNfQoLC3Hq1ClcfvnliIqKQlRUFN58802sWLECUVFRSExMRE1NDcrKyjzO86dGMhEREQWO1AzA0KFD8cknn3g8N2nSJPTs2RMPPfQQUlJS0KRJE+Tn52P06NEAgKKiIhw/flxYI5mIiMgMM/X89eeHK6kBQMuWLdGnTx+P55o3b442bdq4nr/jjjswa9YstG7dGnFxcbjnnnuQkZGBK6+8Uqpjs/fe6yoFLEM0HSdKO9MfLzN1Z2WakMy5XqlxJq8pm3YmM40pM71oV+lZlevI7FhoFA5pqA+A57SsUQqnqH9mPxtA/P0xuo5M6VwZKmWc/X0tkNdxfz1QO14alWJ2D+lZVTY4sKWArdkNMBxZXgnwySefREREBEaPHo3q6mpkZWXhmWeesfoyREREpEB5AKCveRwbG4tVq1Zh1apVqk0TEREJqebyh3MdAO4FQEREIYtrAMxzaJqmNXYn3FVUVCA+Ph4vRHR1rQGwKhamUhrYqm1JZfsgE6+26z7pY5WBSBtSSSWTacvKbZ2tWrdgV2qo6Jr+tC1i1zoFq9LoVH527CrjbOc2vWa/TzJ9EF3nnFaHW51fory8HHFxcX5fT0b93xXH3tmNuBbmU8YrKquQOni4rX0NVuE79CEiIgpjDAEQEVHoUgwBMAuAiIgoBLESoHlBuwZgUNYuVylgq7Y0NWL2OjIlVY3IxBdVSrmK8raN7qn+umb7IGrXaPtfu7bt1ZOpA2Dl5+5OpXSrVaV1rYyDi4jeq2yfRMcaMfsdsbM8scy5Mj9L7qyqaRLINQBfFexFS4U1AGcrq9Al47qwXAPAGQAiIgpZzAIwjwMAIiIKXQ4AKrn84RsBCI0BgGgHM5myqSpEU2HC3fIUid6PzHS7vv+fver/sXpe79f9XOGZumONdh10o1LeV6VsrahdK0veujO6L3alXqqki7mHQ4x+JkXX8bqnNqUMWrk7oEwfVMIUMt9xUehE9HmE4m6AZF5IDACIiIh80RABTSGjXeXcUMcBABERhSyWAjYvfIc+REREYSxoZwAa2g7YKx6qez1QKYNmY3kqW+8GS+y3MeKEKml+wpi6wbFWfZZWlZ3Wv25VqVzVc91jzn8y2CbZqq21jY6V+c6opPLatW2v0XqnYNDQew/kdsDMAjAvaAcARERERlgIyDwOAIiIKGRxBsC88H3nREREYSwkZgDMxsHtjIfKlOWU6YcorqlSetaqEp9WthuMcXG7ysmqlK21avtZoz5ZtX7GKJc/UN8Rd17lq3XrEuyq6SDDsP6DRe3K1CYwIio5HCjMAjAvJAYAREREvnANgHkMARAREYUhzgAQEVHI4iJA80JuO2A7c9RV4rKBILv1ayDYFdvWr3cwii/atSWrTJ8C9d0TnaeyfkB/rvv7ldkyurF+VqxcF2L2PsluY20Vu9bEiN4r4Pm9cG/3Qm0VDu0ZEZDtgD/94BBatmhhup2zlZXoc/mgsNwOOHyHPkRERGGMIQAiIgpZGhRDAGH87+CgHQC4lwJujKltr9KgrzZwoGRbMtvPAnJTkWbTq+wsBWy2HK7+PulToFSmoGXeu8efDcIQKp+d6DW7tm81vE4D07tG58qmhlqVLunvNfy5jszvHJn0N7vCRCL6aXv991j0PfW6pv5cUz2yFrMAzAvfoQ8REZFJq1atQufOnREbG4v09HQcOnRIePy2bdvQs2dPxMbG4rLLLsMrr7zi8bqmaZg3bx46dOiApk2bIjMzE1988YWdb4EDACIiCl0XCwFFKDzkZwBeeOEFzJo1C7m5ufjggw/Qr18/ZGVl4dSpUz6Pf+edd3DbbbfhjjvuwIcffohRo0Zh1KhR+PTTT13HLF26FCtWrMCaNWtw8OBBNG/eHFlZWTh//rzpe2OEAwAiIgpZ9SEAlQdwMavA/VFdXd3gNZctW4bJkydj0qRJ6N27N9asWYNmzZph/fr1Po9/6qmnMHz4cDzwwAPo1asXFi5ciMsvvxxPP/30xfegaVi+fDkefvhhjBw5En379sXmzZvx7bffYseOHZbfs3pBuwbAX/pYvXv5TDvT5mRSszxihJLX9IjfGWyrana9gErM367Ytux1rNo22cp2zX6/rCx7bNXPh52fXSC2ubZyXYvK+hO71gOJGK2naega/vSpoe/IOa0Ot/rdQzVWlQJOSUnxeD43Nxfz58/3Or6mpgaFhYXIyfnfnYyIiEBmZiYKCgp8XqOgoACzZs3yeC4rK8v1l/uxY8dQUlKCzMxM1+vx8fFIT09HQUEBxo4da+atGQr5AQAREZGq4uJijzoAMTExPo87ffo06urqkJiY6PF8YmIi/vWvf/k8p6SkxOfxJSUlrtfrn2voGDtwAEBERCFL0xzQNIUZgP+eGxcXx0JAREREoSPiYi0Akw/Zvwbbtm2LyMhIlJaWejxfWlqKpKQkn+ckJSUJj6//r0ybVgiJGQBR7EsmB1cqD12X929VPM6IaEtQK3OkTefCG7Stcp9k4u2itlRy1s1e09d1/H1N9liZtkSlaa1cA2PVd1HmOjLlolXWMMi2JSKK++vfT45E+WURo23EVdZ6eJRBdvtddaG2CtjT+Fss2yE6OhppaWnIz8/HqFGjAABOpxP5+fnIzs72eU5GRgby8/MxY8YM13N79+5FRkYGACA1NRVJSUnIz89H//79AVxclHjw4EFMnTrVtvcSEgMAIiIiXxqjENCsWbMwYcIEDBw4EIMGDcLy5ctRVVWFSZMmAQDGjx+Pn/zkJ8jLywMA3HfffbjmmmvwxBNPYMSIEdi6dSvef/99rF17cdDkcDgwY8YMLFq0CN27d0dqairmzp2L5ORk1yDDDhwAEBFRyGqMAcCtt96K7777DvPmzUNJSQn69++P3bt3uxbxHT9+HBER/wstDB48GFu2bMHDDz+M3/3ud+jevTt27NiBPn36uI558MEHUVVVhSlTpqCsrAxXX301du/ejdjYWNPvzUhIDADs2tlKJY3OqrQzu1IRZa5jZwhD5fOx6joyn7M+bc6dUdqWSGOlPIpKWqt8VipT6DLnisrYyoT/ZPskIvPZiV73CvcZlNkV7kyJhq9r1K6I0edq5WcQarKzsxuc8t+/f7/Xc2PGjMGYMWMabM/hcGDBggVYsGCBVV00FBIDACIiIl+4F4B5HAAQEVHI4gDAPKYBEhERhaGgnQF44roViGrSHIB16VUqaTZWpot59MGm2KldayP0rwcqfUqFTP+F6Z+SW8qKjhVRuU9eMX+JtDOj7Y7dWVn6V/h5SJSxlWH0eXikt9kU55bdotj9dZntso22NhetLZBZ99JopYAtKgQUjoJ2AEBERGSEIQDzOAAgIqKQxQGAeVwDQEREFIYcmqZpjd0JdxUVFYiPj8egrF2uNQDu7NzCVCaGazZGKFsW1Wyc38otVlWu436fRCVI9W0Z5eeLYpNWbqdrF69tek1+h1S+08HCqu+qlWslRDF0mZLDInaWYrZqC2+zfbxQW4VDe0agvLzctg126v+ueOeDL9CiZUvT7VSePYvBl3e3ta/BiiEAIiIKWRoUFwEyBEBEREThJCRmAOyYopK9jp7ZaUDZNBu7Sg7LTCPrybw/j/skUSZVTyZ8oHKfVMIFUt8fQelWI1alq8pMg8uwMq3Uql04Vd6raEdFI1aG6US7WNpVnthIQ8cHMg3QCQecCv+KVzk31IXEAICIiMgXZgGYxxAAERFRGOIMABERhSxWAjQv5NIA9VRKAavE9kTpbaI4v0r5Tz1RqlxjbdPZGPFdmT7Initi1K7M+zFbjtXK1NZApZXqycSg7eqj6J4bfR52lQ02vdYG4u+eVSmC+uO9SgE7vwxIGuD+wmNo0cL8NSorKzAkLTUs0wAZAiAiIgpDDAEQEVHIYgjAPA4AiIgoZDELwLwf3RqAYCh9amVs1WvLVjcq8UartiG2MlYfiC1YrWRlXQYZMms99Pnv7ozWwDRGyWSZ68iUh9ZTqeFg1JZIMG7/bfaaIoFcA5D/3nHlNQBDr+jINQBEREQUHhgCICKikKUBcCqeH644ACAiopDFRYDmhfwAwMpYntl29ceq5F7rX3eP03r1QaG+v11xS9G5Rvcpxz2GK5E3D8itH3CPHcvEjb3ywV8VHy+Koatsbyz8Tujo9xzwOD5A62Vkcsllfu689lNQ+F1gV70Er3x9mF9XEYh9QVTbqnehtgrY4//PFjWOkB8AEBFR+GIWgHkcABARUchiCMC8oB0AzN57L5o5IgGYTzkSlcoF5EoBq2w96n4d2fdidhrTa4pZN11tVUhDpk8yZKdHPxOED7zCKu7TsBJ98vq+6F6X2qZXH6aw6DuuZ1e6Z6C26Bb+DCuU8tZTOdcjpKT7OdOHdkTft0CVoW6s9FUKPkE7ACAiIjLCEIB50nUATpw4gdtvvx1t2rRB06ZNcdlll+H99993va5pGubNm4cOHTqgadOmyMzMxBdffGFpp4mIiADAqak/wpXUAOA///kPrrrqKjRp0gSvvvoqPvvsMzzxxBNo1aqV65ilS5dixYoVWLNmDQ4ePIjmzZsjKysL58+ft7zzREREZI5UKeA5c+bg7bffxj/+8Q+fr2uahuTkZMyePRv3338/AKC8vByJiYnYuHEjxo4da3gNX6WAzW6raueWsmZT7qzcVlUltmfVtqp2bTVqtAWrVaV0jdIAVcrhmk03tDNF0+z7sTNuLPpZMlq3EwiNVb7Xqt8jVv4eFLXdWNsB73r3JJorlAKuqqzAiCs7sBSwkZdeegkDBw7EmDFj0L59ewwYMADr1q1zvX7s2DGUlJQgMzPT9Vx8fDzS09NRUFDgs83q6mpUVFR4PIiIiPxRnwWg8ghXUgOAr776CqtXr0b37t2xZ88eTJ06Fffeey82bdoEACgpKQEAJCYmepyXmJjoek0vLy8P8fHxrkdKSoqZ90FERGFI09Qf4UpqAOB0OnH55ZfjkUcewYABAzBlyhRMnjwZa9asMd2BnJwclJeXux7FxcWm2yIiIiL/SKUBdujQAb179/Z4rlevXvjb3/4GAEhKSgIAlJaWokOHDq5jSktL0b9/f59txsTEICYmxut5f+sAqGxhKiwnqy8zKiB7HRGZc+3KxZaJTcq8N5n75BXrtTDfXVTC18qcaY+SvQbXEZGJ1RvF0KFQk0LErvUDXmsnArSGQaqmg8nriLZqBgAs120FLlj/YFWcPxTz/J1wwKmQyqdybqiTmgG46qqrUFRU5PHc559/jk6dOgEAUlNTkZSUhPz8fNfrFRUVOHjwIDIyMizoLhER0f9wDYB5UgOAmTNn4t1338UjjzyCo0ePYsuWLVi7di2mT58OAHA4HJgxYwYWLVqEl156CZ988gnGjx+P5ORkjBo1yo7+ExERBaUzZ85g3LhxiIuLQ0JCAu644w5UVlYKj7/nnnvQo0cPNG3aFB07dsS9996L8vJyj+McDofXY+vWrdL9k0oDBICXX34ZOTk5+OKLL5CamopZs2Zh8uTJrtc1TUNubi7Wrl2LsrIyXH311XjmmWfw05/+1K/261M7Xojo6jMEIJOWokJl9zwryaRIuU+XBmo3QJXrqIRvrGLlfbEqBczO9x6IVFE7f1asSjO1kl2plTKpx6K2VcpFm/0sL9RW4dCeEQFJA9x+4JRyGuDNV7e3pa/XX389Tp48iT/+8Y+ora3FpEmTcMUVV2DLli0+j//000+Rm5uLiRMnonfv3vjmm29w9913o2/fvvjrX//qOs7hcGDDhg0YPny467mEhATExsZK9U+6FPAvf/lL/PKXv2zwdYfDgQULFmDBggWyTRMREUkJ1lLAR44cwe7du/Hee+9h4MCBAICVK1fihhtuwOOPP47k5GSvc/r06eNaUwcAXbt2xeLFi3H77bfjwoULiIr631/ZCQkJrnV3ZkmXAiYiIvqx0dejqa6uVmqvoKAACQkJrr/8ASAzMxMRERE4ePCg3+3Uz0y4/+UPANOnT0fbtm0xaNAgrF+/HpKT+QC4GRAREYUw1Xr+9efqa9Dk5uZi/vz5ptstKSlB+/btPZ6LiopC69atG6yLo3f69GksXLgQU6Z4hmkWLFiAa6+9Fs2aNcNrr72GadOmobKyEvfee69UH4N2APDEdStcpYCtopJOFajyvjJE5WWN+mS2HK7RdexKRxKtd9Afb+Xn7E5fntgoVdTsFtKiNEVZVsV3rUx1FbUt83On/07kKJSLtqpkr12lsWV5fFct3Pbc39+D57Q63OpPR62gupL/v+cWFxd7rAHwlZ4OXCyJv2TJEmGTR44cMd+f/6qoqMCIESPQu3dvr4HI3LlzXf8/YMAAVFVV4bHHHvvxDACIiIgCJS4uzq9FgLNnz8bEiROFx3Tp0gVJSUk4deqUx/MXLlzAmTNnDGP3Z8+exfDhw9GyZUts374dTZo0ER6fnp6OhQsXorq6usGBiy8cABARUchSLecre267du3Qrl07w+MyMjJQVlaGwsJCpKWlAQD27dsHp9OJ9PT0Bs+rqKhAVlYWYmJi8NJLL/m1sv/w4cNo1aqV1F/+AAcAREQUwoK1EmCvXr0wfPhwV7n82tpaZGdnY+zYsa4MgBMnTmDo0KHYvHkzBg0ahIqKCgwbNgznzp3Dc88957FBXrt27RAZGYmdO3eitLQUV155JWJjY7F371488sgjrh14ZQTtAMC9FLA7u0qoGlHJyZXpk1054F7XEcT9VWKTdm3falQa2Ko4rEx5YpnPyui+iMoGC0tWG9xfq9ZvGK7JEKxbUPlOiz4P/TVV3qvX+g73z8PC2iMqa4dk1rl4rJEx+I5bxb3dC7VVwB7/t8BWEegZABnPP/88srOzMXToUERERGD06NFYsWKF6/Xa2loUFRXh3LlzAIAPPvjAlSHQrVs3j7aOHTuGzp07o0mTJli1ahVmzpwJTdPQrVs3LFu2zKMej7+CdgBAREQUylq3bt1g0R8A6Ny5s0f63pAhQwzT+YYPH+5RAEgFBwBERBSyVOv5h/NeACExALArDc2qtJvGSgNU2TlQNI1s1Q54+raMPptAlXy2K4VT9F0U7WpnRBi+UUjbUgmVyKRhGrGqBLRKyp0+pVPmeyuTUmvV7pl2/Z6TDf8Fw06CVtUBCEesBEhERBSGQmIGgIiIyJdgXgQY7DgAICKikBWsmwGFgpAYAJiN7elTe/QlMWWopMZZlfZkJfdYpT7tTIZKGmOgyqbKpHCqbFGsf10l3mvXeValr8qQucd2fR5WljIWrh+wcetms9950fofwLpU3UYrBUymhcQAgIiIyBcnFBcBWtaT0MMBABERhSyuATCPWQBERERhKGhnAKzYDli2TKpVOeuBiuOrlJ61ag2DynsXleHV999o/YbZPhrFR92vK7veoTHqQ8jkrBttn2t2TYbMz47sdfx9zZ/X/T1XJRdeZk2MTO0Lme+eVxlnXbvu3wn974lQ2BadMwDmBe0AgIiIyIhTc8CpUM1P5dxQxwEAERGFLM4AmMc1AERERGEoaGcA3LcDNhs3s7ImuehYPdFWqYGKE8vk9lpZ/9uqXH59bXYjZvPbvY5VyImWiY9amVcvw/178SfdegejNQEi7msnVNYWGBHFq82uJfD1ulVxfT27ft5l2hX9blD5vcftgENP0A4AiIiIjGiKmwGF8wCAIQAiIqIwFBIzAFZN78pMbav0STQFamXanFSfbAqVyLzmlZqom+b3eF0ybdHstLhKmpaVpYDd6VMR9d8nmXNF29O6h6YAyVQyfZhLcB2V9DY9q0pYG32Wou+BSolxlTTAQH0e7qz8/WQXTXNAU1jJr3JuqAuJAQAREZEvXANgHkMAREREYYgzAEREFLKciosAVc4NdUE7ADBbClgpBcwm7vE5fdxVJS1IJR1Jhdk+62P++nbc740+vmtX+qTKPbMytu3RD31M2aLysbJEpZm9UvBMX8W+rbVF11BJ3RN9j2XW6RiRWS/g1SeT1zS6jmjtgftalUBuB8wQgHkMARAREYWhoJ0BICIiMsIZAPM4ACAiopDFNQDmBe0AYO2jHdCyZUsA4pxWK2P+ZuNzMrnLdpYCNpujKxsflalrYPY6svdFFIcN1NoIuz5bmfsmUwLa6Doe7UqUZpa933bF0FXace+HYc69bl1PQ+3oz1X5rFRYWbpY9Ls5UDgDYB7XABAREYWhoJ0BICIiMuJ0XnyonB+ugnYAMGXOSUQ1qbj4B4umrGR29TIqrWnVrndGzKaS6fuvstOb2RLJKsfK3kOrpvlFn7vK56oytW229LLsdVTalkoZtClsJEOlXVEKpFG7Hr9HLPyO2/V7zyh11517ieSzZ88CAy5v8FgrMQRgHkMAREREYShoZwCIiIiMcAbAPA4AiIgoZDmhmAZoWU9CT9AOAGbvvRfNHJEAxHFw/daconQlme1cRak9RkRpQoHaDthoq1eZdmW2ibUqrm9lPFTmul5bFLt9v4y25VVZ/yD6jtsVB7crPdIrNUxhvYlVqaJe2yQrlOS2K820sdYOCX/vSby3z3SlgCn4Be0AgIiIyIimadAU5vFVzg11HAAQEVHI4hoA85gFQEREFIZCfgZAJd6oZ1W80avEp01bFFsVR7Yyx14Ux7Sy7LGee9v6eO+fdMe6xzmN3ptMGWqrtpz1ildLlFu1cutXd1aW3FZZUyIq0Sv8jhvUwVCp/+D+ecnUPAjUz12gyis3Fk2xEJBm4yrAM2fO4J577sHOnTsRERGB0aNH46mnnkKLFi0aPGfIkCF48803PZ676667sGbNGtefjx8/jqlTp+KNN95AixYtMGHCBOTl5SEqSu6v9JAfABARUfgK5hDAuHHjcPLkSezduxe1tbWYNGkSpkyZgi1btgjPmzx5MhYsWOD6c7NmzVz/X1dXhxEjRiApKQnvvPMOTp48ifHjx6NJkyZ45JFHpPrHAQAREYWsYN0N8MiRI9i9ezfee+89DBw4EACwcuVK3HDDDXj88ceRnJzc4LnNmjVDUlKSz9dee+01fPbZZ3j99deRmJiI/v37Y+HChXjooYcwf/58REdH+93HoB0APHHdCkQ1aW54nJWpM1btpidzDaPpOdHuYSrvXWW6V2YaUzQ9KtMn/bQ4BG0ZTcPKkAmrmG0XMNglTmF6V8TKnxW7Qld67vfJyp3oROV99bzeq+C7qJJ+a9fvFaNyv+GqoqLC488xMTGIiYkx3V5BQQESEhJcf/kDQGZmJiIiInDw4EHcfPPNDZ77/PPP47nnnkNSUhJuvPFGzJ071zULUFBQgMsuuwyJiYmu47OysjB16lT885//xIABA/zuY9AOAIiIiIxYFQJISUnxeD43Nxfz58833W5JSQnat2/v8VxUVBRat26NkpKSBs/7f//v/6FTp05ITk7Gxx9/jIceeghFRUV48cUXXe26/+UPwPVnUbu+cABAREQhS3Nq0BTm8evPLS4uRlxcnOv5hv71P2fOHCxZskTY5pEjR0z3Z8qU/83mXHbZZejQoQOGDh2KL7/8El27djXdri8cABARUdiLi4vzGAA0ZPbs2Zg4caLwmC5duiApKQmnTp3yeP7ChQs4c+ZMg/F9X9LT0wEAR48eRdeuXZGUlIRDhw55HFNaWgoAUu0CQTwAaKgUsBGrYvV6MmlCMoxid+6xSZm0Ibu2FjVqR3+uTP+F7Uqke6psmyxaP6CS9iezTawo/mwlmfUnoji3nsr6AMO4uODnTv9Zuqd/GsW5VcpSi1hZbln08210L9yprJHxN93wQm0VsMe6NRoigV4E2K5dO7Rr187wuIyMDJSVlaGwsBBpaWkAgH379sHpdLr+UvfH4cOHAQAdOnRwtbt48WKcOnXKFWLYu3cv4uLi0Lt3b6n3wkJAREQUsurXAKg87NCrVy8MHz4ckydPxqFDh/D2228jOzsbY8eOdWUAnDhxAj179nT9i/7LL7/EwoULUVhYiK+//hovvfQSxo8fj5///Ofo27cvAGDYsGHo3bs3fvOb3+Cjjz7Cnj178PDDD2P69OnSixY5ACAiIrLB888/j549e2Lo0KG44YYbcPXVV2Pt2v/NlNTW1qKoqAjnzp0DAERHR+P111/HsGHD0LNnT8yePRujR4/Gzp07XedERkbi5ZdfRmRkJDIyMnD77bdj/PjxHnUD/BW0IQAiIiIjTqcGp0IMQOVcI61btxYW/encubPHZkQpKSleVQB96dSpE1555RXl/jm0INsKqaKiAvHx8Tj84Qdo2bIlALl8X/d8cf15duVMW5UDbeV1rdxWVVSa1sr3Hqh7bNV1ZK8biHZU1onIfM52lY+18jqiGhRGaz9k+mD287HyZ9+qn3ejtQRGtTzqXaitwqE9I1BeXu7Xwjoz6v+umLv+DGKbmb/G+XMVWPjb1rb2NVgxBEBERBSGGAIgIqKQFcx7AQQ7DgCIiChkOTUNToW/xVXODXVBuwbghYiuftUBsDJOZjYfVqZd2biw2ffXWLHsQOVMW7Ulq8x1rPq+GF1HpS0r77/ZtmTfq1VrWWQo1c6XyKO3sg6A2e+iTB9k32tDvwfPaXW41fllQNYA5Kz9XnkNQN6UNlwDQEREROGBIQAiIgpZGjSoTGRrCKpJ8IAK2gGA2e2A3aew9OVjjbaUtWt6UfSalWlPdpX3VSHTJ/c/i1LSfLXr8VkHqP9WMpu+KpuiZte0vkpbMlteu7MrPKBv+7NXdS/qriNTgltEVG5cfx0jZstdY/muhl+T7EOgaE7A6VQ7P1wxBEBERBSGpAYAdXV1mDt3LlJTU9G0aVN07doVCxcu9Jh+0TQN8+bNQ4cOHdC0aVNkZmbiiy++sLzjREREmqYpP8KV1ABgyZIlWL16NZ5++mkcOXIES5YswdKlS7Fy5UrXMUuXLsWKFSuwZs0aHDx4EM2bN0dWVhbOnz9veeeJiCi81e8GqPIIV1JrAN555x2MHDkSI0ZcjE117twZf/7zn107GWmahuXLl+Phhx/GyJEjAQCbN29GYmIiduzYgbFjx5rqpEz6i3u8TmVLWVEf9Owq1ao/PlAlba1kOrXSIP7pFS/Vx2lNUlkrYRTDFfGIy9pYIlZ0rOh1K8sri35m/6Rb+yEqPWtnCW6zx+rXroi+x6L7IHtdEX/L9wJ+rLUJgTUB5D+pGYDBgwcjPz8fn3/+OQDgo48+woEDB3D99dcDAI4dO4aSkhJkZma6zomPj0d6ejoKCgp8tlldXY2KigqPBxERkT80p6b8CFdSMwBz5sxBRUUFevbsicjISNTV1WHx4sUYN24cAKCkpAQAkJiY6HFeYmKi6zW9vLw8/OEPfzDTdyIiCnMsBWye1AzAX/7yFzz//PPYsmULPvjgA2zatAmPP/44Nm3aZLoDOTk5KC8vdz2Ki4tNt0VERET+kSoFnJKSgjlz5mD69Omu5xYtWoTnnnsO//rXv/DVV1+ha9eu+PDDD9G/f3/XMddccw369++Pp556yvAavkoBu7MyJuVvWUsgOLdKFWmsegNG/TDbjp5MvF2lZLJVn6XMegG7tojWnxuo7bEba+tgu95foFi1HsioXZl2/O1TILcDnvFUKWKamr9G9Q8VWH5fIksBGzl37hwiIjxPiYyMhPO/VRhSU1ORlJSE/Px81+sVFRU4ePAgMjIyLOguERHR/zAN0DypNQA33ngjFi9ejI4dO+LSSy/Fhx9+iGXLluG3v/0tAMDhcGDGjBlYtGgRunfvjtTUVMydOxfJyckYNWqUHf0nIqIwpjnVqvmFcyVAqQHAypUrMXfuXEybNg2nTp1CcnIy7rrrLsybN891zIMPPoiqqipMmTIFZWVluPrqq7F7927ExsZKdczfUsAiRlOCUlNsCmU5/b2mbLtW7apm1I5+utornVJwrl3llUUpU6ISw0bt2pXWZNR/d1aFN1TJtOUeIhN9PwC1nffc2fmzY1VZbaOS1naR+XmwI2x6TqvDrX63So1FagDQsmVLLF++HMuXL2/wGIfDgQULFmDBggWqfSMiIhJyahqcCtP4KueGuqDdDIiIiMiIahw/nNcAcDMgIiKiMCSVBhgI9akdg7J2udYAWLWFqT6+KCJTPtOqWLxqW1a1a8RsGp3MNWViwfrj9ceK2rIzXdKqdlXK7srex4bIpoeJzrUqvm7UB5W0OZk1MmbZmWpo1RbFonZFApkGOHXpCeU0wNUP/iQs0wAZAiAiopDFSoDmMQRAREQUhjgDQEREIUvT1Db0CbIoeEAF7QBg9t57XaWAzcbj9Mf+BtbF283Gs436YHRdfwVLjrTZz84rX1piS9kcXVsy91xUAlolh9vK0tIyn6VdefQyufxGWzUHYk2J0f0XrRvR9z9Q2zHrid671/omk2s9rCqNHcg6AJpiGmA4DwAYAiAiIgpDQTsDQEREZERzKoYAFM4NdUE7AHAvBWy2lKt+ms+oRKloik00NWY0beY+vaufnm6sXfqsYjTda9X0rl1pc0Y8poatTK3UT9Ha9NnJlBWWIbqn+pCL0X3z+Dk1OXUtS38fhGEji3a/BOTS82S+T6L3Y/TzoFLGWbQbIPYEpuwxBwDmBe0AgIiIyIhTu/hQOT9ccQ0AERFRGOIMABERhSyGAMwL2gGA2TRA99eN0o9E7CoRa+f2rSJ2pQV6pZkJ3l+gSsIaMXtd2ZRNs2syZN670TWNPh9/25ZJTZT97ERrZPztnyqV9D2zqX5WpdzJ9klPJgU1UL+vZHAzIPMYAiAiIgpDHAAQEVHIcjoBp1NTeNjXtzNnzmDcuHGIi4tDQkIC7rjjDlRWVjZ4/Ndffw2Hw+HzsW3bNtdxvl7funWrdP+CNgRARERkJJhDAOPGjcPJkyexd+9e1NbWYtKkSZgyZQq2bNni8/iUlBScPHnS47m1a9fisccew/XXX+/x/IYNGzB8+HDXnxMSEqT7F3IDAKO4mah0q0zMTaaGgJU56ypk6hjI5OfL1lNo6LpG8USZz07mHqv0X8SqLZWN2rVyTYBHiVuDexyILXGNriNzrMq6Fpk1DSrrH8yuq/CnbdG5/r4m225Da3wCWQo4WB05cgS7d+/Ge++9h4EDBwIAVq5ciRtuuAGPP/44kpOTvc6JjIxEUlKSx3Pbt2/Hr3/9a7Ro0cLj+YSEBK9jZTEEQEREIas+C0DlAQAVFRUej+rqaqV+FRQUICEhwfWXPwBkZmYiIiICBw8e9KuNwsJCHD58GHfccYfXa9OnT0fbtm0xaNAgrF+/3tRMRsjNABAREdWzKg0wJSXF4/nc3FzMnz/fdLslJSVo3769x3NRUVFo3bo1SkpK/Grj2WefRa9evTB48GCP5xcsWIBrr70WzZo1w2uvvYZp06ahsrIS9957r1QfOQAgIqKwV1xcjLi4ONefY2JifB43Z84cLFmyRNjWkSNHlPvzww8/YMuWLZg7d67Xa+7PDRgwAFVVVXjsscd+PAMA970A3BnFwUQ1vGW2udXHiUXbt1qZ364Sq3d/XV8DXp8PLlVbwcJtcEVU6tRLbS0swey6ED19/4y2ozXbruHPh2BvAz2z+zjoqbxXs9tuA9bte2CkMdb8WLmPgNk9UESvB3IvACfUtgN24uK5cXFxHgOAhsyePRsTJ04UHtOlSxckJSXh1KlTHs9fuHABZ86c8St2/9e//hXnzp3D+PHjDY9NT0/HwoULUV1d3eDAxZegHQAQEREZCXQlwHbt2qFdu3aGx2VkZKCsrAyFhYVIS0sDAOzbtw9OpxPp6emG5z/77LO46aab/LrW4cOH0apVK6m//AEOAIiIKIQFaxpgr169MHz4cEyePBlr1qxBbW0tsrOzMXbsWFcGwIkTJzB06FBs3rwZgwYNcp179OhRvPXWW3jllVe82t25cydKS0tx5ZVXIjY2Fnv37sUjjzyC+++/X7qPITEAsGqbWFG7+rYNpy1Npv6IQglGfZJJE/LaklXArrQg1bZlyExXu5OZnpbdKtXjXN198do2WaLdQJSp9ed1v8+zcItf4e8CQVpjoMoGW1ky2arfBSp9MhuCOXv2LPrv8fvUH63nn38e2dnZGDp0KCIiIjB69GisWLHC9XptbS2Kiopw7tw5j/PWr1+PSy65BMOGDfNqs0mTJli1ahVmzpwJTdPQrVs3LFu2DJMnT5buX0gMAIiIiHzR/lvRT+V8u7Ru3brBoj8A0LlzZ58zEI888ggeeeQRn+cMHz7cowCQCg4AiIgoZHE3QPNYCIiIiCgMObQg2wuxoqIC8fHxeCGiq8/tgO0kKpOq5x47NkprsmsLTatiw3beX7u2Tbbq/ah8NiqpcVbG6kXtBOo7opIyKDreqtS+QH1WjXWuXT/DZlOcz2l1uNX5JcrLy/1KrTOj/u+KX834DE1iWppup7b6LP66vLetfQ1WDAEQEVHI0pxOaApb+qmcG+oYAiAiIgpDnAEgIqKQ5VTMAlA5N9SFxBoAd1J52xaWy5Rt219G78eu9QNWaaw4pSg2bGWtiECtJ5ARqDUx7oxKS4uolMq2Kr/dyj7pmc2jl825F9UTUfk9KNMHf9sO5BqAUdM/Vl4DsGNV37BcA8AQABERURhiCICIiEIW6wCYF7QDAPfdAN2nmbxK5+rOE01hWZlOZXbK0KhMqlVTiDJTqUbliRtjytmo/6J0MJXQj/7cxiilKzNla3SfRFP3MtfRl5a2ssStWSpla1XSGkXfkUCFFb2+/xK/91Q+u8b4XWCEAwDzgnYAQEREZMQJJ5ya+VQ+J5gGSERERGGEMwBERBSyNKfaNL7C5EHIC7k0QCtZtSZAJaZpFH8XlRzWX9f9WJlSxioxfyu3/7XqPpotFwtYl6KmZ1e6p9H9llkDYFd5ZSvj7Val3OlZVQbZiFU/HzLrdgJV7tr92Au1VTi0Z0RA0gBvuKMQTaJbmG6ntqYSrzybxjRAIiIiCg8MARARUcjSNA0qE9lBNgkeUBwAEBFRyHI6nXAqbOijcm6o+1GvAbCzJKxM3FKmXbu2Pw2GMqky56psKSuTGy9T0taIVe/Hrpg5ILfltYhdP1sq6yz8vYYsozLIZj93o591q9YLqJQYNupTMJQCzpp4SHkNwJ6Ng8JyDQBnAIiIKGSxEJB5HAAQEVHI0jQnNIVcPpVzQ11IDADMprTITifaVXbXnX7aL0c3xfbZqw2eqsSuMqlG54qmIq2cRha1q+cxramwm6GVZVMDlbZlVVt27fAnw8r3KuqjUflxUZ9E7XqFEgz6ZPY6esLfZRaFhS7UVgF7zLdFgRESAwAiIiJfGAIwjwMAIiIKXYoDAHAAQEREFHqcmuJmQGG8BiBo0wAHZe1ybQcsYlcZXpn0PCtj5jLnyrQls4ZBZXtg0XVkUhxlY5xWpWWK+qESy7ZrvYPKdWTKExu1K1OyWk9m/YPoOjKsTHUVUSmhLNOWVSWfZTX02QUyDfDasf9AlEIa4IWaSuzb+jOmARIREYUSrgEwjwMAIiIKWZrmhKZQzS+c0wC5GRAREVEYCtoZgNl773WVAhbFvpS2MNXHEAWxSFF+vpXxXK84ueC6KrE8YXxXovynzHa0KqVO9fFq/Wcn8x0JFLO5/So53jLfH5lYvVH/rSyp7M7rvQpi2ypE99jKOL7ZLZaN2vb6nC2q+2F27U0g6wAwBGBe0A4AiIiIjLASoHkMARAREYUhzgAQEVHIcjoBp8I0fhjvBhwadQDs2ipVhkoc0K4cYz2ZXGyZfOpA5dHLkKlrINMnf8+TZVftfKN6FaLPVrb+QyDYtW2yEZmaID/muhIya3qAhusNBLIOwFU37fWrZkxDLtRW4e2XrgvLOgAMARAREYUhhgCIiChkMQvAvJAfAFg1FWx0vEo5X5U+SE2hC6Z7ZY5VmUIXTUnrU5Ws2mJZ1D9fbVl1rkwfVaZ3Ra8bpqvKpEcabE8rPFfAypCY2e+IbEqw6L2rsOu7KDpXpcSw0ffrT+6hRDRSGmAQZwEsXrwYu3btwuHDhxEdHY2ysjI/+qMhNzcX69atQ1lZGa666iqsXr0a3bt3dx1z5swZ3HPPPdi5cyciIiIwevRoPPXUU2jRQq4kMkMAREQUsupnAFQedqmpqcGYMWMwdepUv89ZunQpVqxYgTVr1uDgwYNo3rw5srKycP78edcx48aNwz//+U/s3bsXL7/8Mt566y1MmSK/DiTkZwCIiIiC0R/+8AcAwMaNG/06XtM0LF++HA8//DBGjhwJANi8eTMSExOxY8cOjB07FkeOHMHu3bvx3nvvYeDAgQCAlStX4oYbbsDjjz+O5ORkv/sXdAOA+qSEugvnXM+d0+pc/3+htsrjePfX9K/rX9MzastfMn0yIvN+ZNqVIXPfjPp09uxZW9qVuRcq99Tsd8+I6F5Y1Y5sWzJtW/Wdlrmm/lyVz86IzOduFaM+Bur3oKhdPfefb/d26n9/ByLJ7ELNWaW9AOouXOx3RUWFx/MxMTGIiYlR6pusY8eOoaSkBJmZma7n4uPjkZ6ejoKCAowdOxYFBQVISEhw/eUPAJmZmYiIiMDBgwdx8803+39BLcgUFxdrAPjggw8++AjxR3FxsW1/V/zwww9aUlKSJf1s0aKF13O5ubmW9XXDhg1afHy84XFvv/22BkD79ttvPZ4fM2aM9utf/1rTNE1bvHix9tOf/tTr3Hbt2mnPPPOMVL+CbgYgOTkZxcXF0DQNHTt2RHFxcdjlZsqoqKhASkoK75MB3if/8D75h/dJTNM0nD17Vmo6WlZsbCyOHTuGmpoa5bY0TYPD4fB4rqF//c+ZMwdLliwRtnfkyBH07NlTuV92C7oBQEREBC655BLXdExcXBx/wPzA++Qf3if/8D75h/epYfHx8bZfIzY2FrGxsbZfx93s2bMxceJE4TFdunQx1XZSUhIAoLS0FB06dHA9X1paiv79+7uOOXXqlMd5Fy5cwJkzZ1zn+yvoBgBERETBql27dmjXrp0tbaempiIpKQn5+fmuv/ArKipw8OBBVyZBRkYGysrKUFhYiLS0NADAvn374HQ6kZ6eLnU9pgESERHZ4Pjx4zh8+DCOHz+Ouro6HD58GIcPH0ZlZaXrmJ49e2L79u0AAIfDgRkzZmDRokV46aWX8Mknn2D8+PFITk7GqFGjAAC9evXC8OHDMXnyZBw6dAhvv/02srOzMXbsWOmQS9DOAMTExCA3NzfgqzBDDe+Tf3if/MP75B/eJ/LHvHnzsGnTJtefBwwYAAB44403MGTIEABAUVERysvLXcc8+OCDqKqqwpQpU1BWVoarr74au3fv9gh1PP/888jOzsbQoUNdhYBWrFgh3b+g2wyIiIiI7McQABERURjiAICIiCgMcQBAREQUhjgAICIiCkMcABAREYWhoB0ArFq1Cp07d0ZsbCzS09Nx6NChxu5So8nLy8MVV1yBli1bon379hg1ahSKioo8jjl//jymT5+ONm3aoEWLFhg9ejRKS0sbqcfB4dFHH3Xl1dbjfbroxIkTuP3229GmTRs0bdoUl112Gd5//33X65qmYd68eejQoQOaNm2KzMxMfPHFF43Y48Crq6vD3LlzkZqaiqZNm6Jr165YuHChxwY3vE8U0qR2DgiQrVu3atHR0dr69eu1f/7zn9rkyZO1hIQErbS0tLG71iiysrK0DRs2aJ9++ql2+PBh7YYbbtA6duyoVVZWuo65++67tZSUFC0/P197//33tSuvvFIbPHhwI/a6cR06dEjr3Lmz1rdvX+2+++5zPc/7pGlnzpzROnXqpE2cOFE7ePCg9tVXX2l79uzRjh496jrm0Ucf1eLj47UdO3ZoH330kXbTTTdpqamp2g8//NCIPQ+sxYsXa23atNFefvll7dixY9q2bdu0Fi1aaE899ZTrGN4nCmVBOQAYNGiQNn36dNef6+rqtOTkZC0vL68RexU8Tp06pQHQ3nzzTU3TNK2srExr0qSJtm3bNtcxR44c0QBoBQUFjdXNRnP27Fmte/fu2t69e7VrrrnGNQDgfbrooYce0q6++uoGX3c6nVpSUpL22GOPuZ4rKyvTYmJitD//+c+B6GJQGDFihPbb3/7W47lbbrlFGzdunKZpvE8U+oIuBFBTU4PCwkKP/ZAjIiKQmZmJgoKCRuxZ8KivGtW6dWsAQGFhIWpraz3uWc+ePdGxY8ewvGfTp0/HiBEjPO4HwPtU76WXXsLAgQMxZswYtG/fHgMGDMC6detcrxvtSR4uBg8ejPz8fHz++ecAgI8++ggHDhzA9ddfD4D3iUJf0JUCPn36NOrq6pCYmOjxfGJiIv71r381Uq+Ch9PpxIwZM3DVVVehT58+AICSkhJER0cjISHB49jExESUlJQ0Qi8bz9atW/HBBx/gvffe83qN9+mir776CqtXr8asWbPwu9/9Du+99x7uvfdeREdHY8KECa574etnMJzu05w5c1BRUYGePXsiMjISdXV1WLx4McaNGwcAvE8U8oJuAEBi06dPx6effooDBw40dleCTnFxMe677z7s3bs34FuEhhKn04mBAwfikUceAXCxPvmnn36KNWvWYMKECY3cu+Dxl7/8Bc8//zy2bNmCSy+9FIcPH8aMGTOQnJzM+0Q/CkEXAmjbti0iIyO9VmaXlpZK73X8Y5OdnY2XX34Zb7zxBi655BLX80lJSaipqUFZWZnH8eF2zwoLC3Hq1ClcfvnliIqKQlRUFN58802sWLECUVFRSExM5H0C0KFDB/Tu3dvjuV69euH48eMAPPckdxdu9+mBBx7AnDlzMHbsWFx22WX4zW9+g5kzZyIvLw8A7xOFvqAbAERHRyMtLQ35+fmu55xOJ/Lz85GRkdGIPWs8mqYhOzsb27dvx759+5CamurxelpaGpo0aeJxz4qKinD8+PGwumdDhw7FJ5984tpy8/Dhwxg4cCDGjRvn+n/eJ+Cqq67ySiP9/PPP0alTJwCee5LXq9+TPJzu07lz5xAR4fkrMjIyEk6nEwDvE/0INPYqRF+2bt2qxcTEaBs3btQ+++wzbcqUKVpCQoJWUlLS2F1rFFOnTtXi4+O1/fv3aydPnnQ9zp075zrm7rvv1jp27Kjt27dPe//997WMjAwtIyOjEXsdHNyzADSN90nTLqZIRkVFaYsXL9a++OIL7fnnn9eaNWumPffcc65jHn30US0hIUH7+9//rn388cfayJEjwy69bcKECdpPfvITVxrgiy++qLVt21Z78MEHXcfwPlEoC8oBgKZp2sqVK7WOHTtq0dHR2qBBg7R33323sbvUaAD4fGzYsMF1zA8//KBNmzZNa9WqldasWTPt5ptv1k6ePNl4nQ4S+gEA79NFO3fu1Pr06aPFxMRoPXv21NauXevxutPp1ObOnaslJiZqMTEx2tChQ7WioqJG6m3jqKio0O677z6tY8eOWmxsrNalSxft97//vVZdXe06hveJQplD09zKWhEREVFYCLo1AERERGQ/DgCIiIjCEAcAREREYYgDACIiojDEAQAREVEY4gCAiIgoDHEAQEREFIY4ACAiIgpDHAAQERGFIQ4AiIiIwhAHAERERGHo/wNgGdR1K/tDzAAAAABJRU5ErkJggg==", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "M = 100\n", - "p = 5/100\n", - "L = 1/2\n", + "p = 5 / 100\n", + "L = 1 / 2\n", "\n", "modele = ModeleSchelling(M, p, L)\n", "modele.afficher_grille(\"Configuration Initiale\")\n", "\n", "for T in [1, 10, 100, 400]:\n", " modele.simuler(T, True)" - ], - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ], - "image/png": 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" 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NZrdhio8//hiNGjXCP/7xD+uy6OhoDB8+3O5piOxxtJgzZw7+/PNP1fXUrrs3Bg0aZPfd/cc//oFGjRrh448/xiOPPOLV/eapfv36oUGDBqrrnTlzBkII1KlTR3G9e++9F7Nnz8aePXtQp04d7NmzB9OmTfOqba7YJr1bwo7r16/HJ5984vIprl4s53369GnF9dq1a4fNmzd7tM+EhATF9y33vNo1V3Lu3DmXgwIs95HlaZvlv2rruhtgoLa92shMpcR/x+1t0wqAS/dw586dMXDgQLz88suKifqy5wnAabTL0KFDcdttt2Hu3LkYNWoUrrzySrv369Sp4/ETlkDjcSfEEoM7e/asR+v/8ssvCAkJQfPmze2WJyQkoHbt2vjll1/sltvGzizq1Knj0Y+2q2MDcDp23bp1pb5swKVOiCuff/45srOzkZeX5xRm8KYTYjmHq666yum9li1bYseOHXbLIiMjnX7otVy/mjVruowLK/HkMzt37hymT5+OZcuW4cSJE3ax1eLiYrf7PnToEIBLQ7LdKS4udvt5/vLLL2jevLlTLovj9ZQ9jhapqanS+/BWixYt7P5sMpnQvHlza26O1vtNC3ffGXeESvy9Q4cOaNmyJVatWoXatWsjISEBt9xyi9ftsxUSEoKmTZvaLbOMSPB1HSLLeavV5KlTp47m76qnx/ZGVFSUy1yr8+fPW9+3/a8n67o7jtL2Sttatq+oqHD5nifb33vvvRg7diw++eQTxU6I7Hm6YjKZ8Nhjj2HTpk3Ytm0b7rvvPrv3hRA+r+XkK5o6IYmJiZoL6nh6YdwNfZL5cnjCXfvcJXS6unmOHDmC7t27o2XLlpg7dy6SkpIQHh6Ojz/+GC+++KJqXFYPng4d88cxbT+zUaNGYdmyZRg9ejTS09OtReYGDBigeF0s782aNcuad+PIduict/x1HODSv/Td/QjaioqK0txp9SeTyeTye6nlO+NK3bp1YTKZPOo433vvvVi0aBFq1aqF/v376/KkymiW865fv77iehUVFThz5oxH+2zQoIHib0O9evWsx3b817WnGjVqhK1btzr9RXjy5EkAfz3ZswxmsCy3dfLkSdStW1fx6YDa9mpPEBs1aoSqqiqcOnUKDRs2tC6vqKjAH3/84dETyKSkJNVrL3ueSscG4PL4f/75p+p9E6g01Qm5/fbb8eqrryIvLw/p6emK6zZp0gRmsxmHDh2yS1gqLCxEUVGRdaSLL1j2ffjwYbt/hf3xxx9OP3CWf+EWFRWhdu3a1uWOT2qUfPjhh7hw4QI++OADu6cDW7dudVrX006Z5RwOHjzo9K+8gwcP+vT66emdd97B4MGDMWfOHOuy8+fPqyY6WsI8sbGxXv2rr0mTJvj222+dfhgPHjyo63G0uOuuu7B9+3bV9QYPHqx7QTvLEx8LIQQOHz5srWGi5X6rU6eOyzCplu+MK2FhYWjWrBmOHj2quu69996LiRMn4uTJkx6HHD1hNpvx008/2dVj+PHHHwFAsViXHo4ePYqQkBCnWhCOdu7caRfKVtunUrtbtmxpXa9NmzYet9VW+/bt8Z///AcHDhxA69atrct37dplfR8ArrjiCjRo0MBl4bbdu3e7/UeAxTXXXIOwsDDs3bsX//znP63LKyoqsH//frtl7toJXAp19+rVy7p87969MJvNqscXQuDnn39Ghw4dFNeTPU93LN85V6HNo0ePol27dl7t12ia/vnw5JNPombNmnjwwQddZgkfOXLEmsFr+ZAdR7DMnTsXAHTJZHene/fuCAsLcxoi+9JLLzmta/lL6NNPP7UuKysrw+uvv+7x8Sz/0nAMNSxbtsxp3Zo1a3o00qBTp05o2LAhFi9ebPdYb8OGDThw4IBPr5+eQkNDnf7VvGDBAtWhw6mpqWjWrBlmz57tcrSIWuXBXr164bfffsM777xjXVZeXu40Wkj2OFrMmTMHmzdvVn25GsEja8WKFXah1HfeeQcnT57EbbfdBkDb/dasWTP88MMPdtfmq6++0iU7Pz09XbG6qG0bcnJyMH36dOsoDL3Y/k4IIfDSSy+hRo0a6N69u67HcZSfn4+rr75a9SmYJSfEk5daTkhqairCw8M9uubu9OnTBzVq1MDLL79sXSaEwOLFi3HFFVfYjabs168fPvroI7vh4bm5ufjxxx9x9913Kx4nLi4OGRkZeOONN+zu5ZUrV6K0tNRu+/Lycvzwww92+TW33HIL6tat6/T3wqJFixAdHW13j7v63i9atAi///47evbsqdhOLedZWVmJH374we6pyZkzZ5x+HysrK/HCCy8gPDzcqQNaXFyMI0eOeDxqNdBoehLSrFkzrFq1Cv3790erVq3sKqbu3LkTa9eutdbgaNeuHQYPHoxXX30VRUVF6Nq1K3bv3o3XX38dffv29bgn7434+Hg8+uijmDNnDu6880707NkTX331FTZs2ID69evb/cu4R48eaNy4MR544AE88cQTCA0NxdKlS9GgQQMcO3bMo+P16NED4eHhuOOOO/Dvf/8bpaWlWLJkCRo2bOj0SC41NRWLFi3C888/j+bNm6Nhw4Yu49k1atTAjBkzMHToUHTt2hX33HMPCgsLMW/ePCQnJ+Oxxx6Tu0h+cvvtt2PlypWIi4tD69atkZeXh08++cT6GNidkJAQ/Oc//8Ftt92Gq6++GkOHDsUVV1yBEydOYOvWrYiNjcWHH37odvthw4bhpZdewqBBg5Cfn49GjRph5cqViI6O1vU4WnibE/Lpp59aO8m///47ysrK8PzzzwO4NGT1pptuUt1H3bp10aVLFwwdOhSFhYXIyclB8+bNMWzYMADa7rd//etfmDt3LjIzM/HAAw/g1KlTWLx4Ma6++mrV4aVq+vTpg5UrV+LHH39UfSLgmDzoTrdu3bB9+3aPQruRkZHYuHEjBg8ejLS0NGzYsAHr16/H008/bfcv0CFDhuD1119XfdJgsXTpUqcaOpZzqFWrFiorK7F9+3anZHpX9MwJiYyMRI8ePfDJJ59g8uTJdu99/fXX1gTJw4cPo7i42HrftWvXDnfccQeAS9WWR48ejVmzZqGyshLXXnst1q1bh88++wxvvvmmXTjo6aefxtq1a3HzzTfj0UcfRWlpKWbNmoU2bdpg6NChdse3XFfbXJypU6fi+uuvR9euXTF8+HD8+uuvmDNnDnr06GHXOdi9ezduvvlmZGdnWwcjREVFYcqUKRg5ciTuvvtuZGZm4rPPPsMbb7yBqVOn2g0db9KkCfr37482bdogMjISO3bswOrVq9G+fXv8+9//tmunq/vL0/M8ceIEWrVqZff084MPPsDzzz+Pf/zjH0hJScGZM2ewatUqfPvtt5g2bZpTx/KTTz6BEAJ9+vRx/SEHOm+G1Pz4449i2LBhIjk5WYSHh4tatWqJG264QSxYsMBu6FFlZaV47rnnREpKiqhRo4ZISkoS48ePdxqe5K46nONQQE+H6AohxMWLF8WECRNEQkKCiIqKErfccos4cOCAqFevnnjooYfsts/PzxdpaWkiPDxcNG7cWMydO9ftEF13Vew++OAD0bZtWxEZGSmSk5PFjBkzxNKlS532UVBQIHr37i1q1aolAFjPz10lzzVr1ogOHTqIiIgIUbduXTFw4EDx66+/2q0zePBgUbNmTac2uRt+7EitYqq7IbquhkI2adLEbojpn3/+KYYOHSrq168vYmJiRGZmpvjhhx+c1nN3/l9++aW46667RL169URERIRo0qSJ+Oc//ylyc3NVz+uXX34Rd955p4iOjhb169cXjz76qNi4caPux7HwVcVUy/V39crOzlbc1nJd33rrLTF+/HjRsGFDERUVJXr37m1XzdHCk/tNCCHeeOMN0bRpUxEeHi7at28vNm3a5HaIrpYKxxcuXBD169cXU6ZMcXkN1IbJurovU1NTVYdvCvHX9+jIkSOiR48eIjo6WsTHx4vs7GxrxVqLfv36iaioKPHnn38q7tPyO+Ludfz4cSGEEBs2bBAAxKFDh1Tbqbd3331XmEwmcezYMY/b7jiMvKqqSkybNk00adJEhIeHi6uvvlq88cYbLo/37bffWq9v7dq1xcCBA0VBQYHTevXr1xfXXXed0/LPPvtMXH/99SIyMlI0aNBAjBw50m74uRB/3feuvh+vvvqquOqqq0R4eLho1qyZePHFF+2G5wshxIMPPihat24tatWqJWrUqCGaN28unnrqKafjCOH+/vLkPC3fEdvruXfvXnHHHXeIK664QoSHh4uYmBjRpUsXu3IDtvr37++y4m2w8KoTEqz+/PNPAUA8//zzRjeFyC8sP8Zr1641uikemzx5skhJSbEr9+2tkpISERYWJl566SXVdd115l1p2LChePzxx2WbZ9WnTx+nukb+cvHiRfG3v/1NPPvss4Yc35XvvvtOABAfffSR0U1RpOX+8oWTJ0+KyMhIsW7dOkOOr4fgTyl3w9WYcUt+yuU+CylRMHvsscdQWlqK1atXS+/r008/xRVXXGENO+nhu+++w7lz51xOeOaNAwcO4KOPPsKUKVN02Z9WoaGhmDx5MhYuXOiTar3e2Lp1K9LT0wM+980X95cWOTk5aNOmTfCGYgCYhPDxGFiDLF++HMuXL0evXr0QExODHTt24K233kKPHj2wadMmo5tH5Bfbtm3DzTffjLVr19oVbiNnQ4YMwTvvvBMwfxETVQeaElODSdu2bREWFoaZM2eipKTEmqxqSawiIiIiY1224ZiOHTvik08+wenTp1FRUYHjx48jJydHt8JTRMGgW7duEELwKYgHli9fzqcgFDQ+/fRT3HHHHUhMTITJZMK6detUt9m2bRs6duyIiIgING/e3GU9ooULFyI5ORmRkZFIS0vTdRJPVy7bTggREdHlqqysDO3atbObqV3J0aNH0bt3b9x8883Yv38/Ro8ejQcffNAuPWHNmjUYM2YMsrOzsW/fPrRr1w6ZmZk4deqUr07j8s0JAS716GbNmoWCggK0a9cOCxYs0L2wERERkZFMJhPee+899O3b1+06Tz31FNavX2839cqAAQNQVFRkrWGTlpaGa6+91lqwz2w2IykpCaNGjVKcL0fGZZsTYunRLV68GGlpacjJyUFmZiYOHjxoN2+AO2azGb/99htq1aoVtBMDERFVV0IInD17FomJiT6dW+j8+fMezQnlCeFiIrqIiAiv5ppxlJeX51TkLjMzE6NHjwZwqfx9fn4+xo8fb30/JCQEGRkZyMvLkz6+O5dtJ2Tu3LkYNmyYtTrd4sWLsX79eixdutSjHt1vv/1mnTCIiIiC0/Hjx72enE/N+fPnkRgVgz+hPA2Fp2JiYpzykmyrvsooKChAfHy83bL4+HiUlJTg3Llz+PPPP1FVVeVynR9++EH6+O5clp0Qb3p0Fy5csJszwxKlWmZKQbTJuRc959b5dn8eu/kRt+1xXNeR0ra+omebHPf16guNrP8/fJzzTJLujqO1TVflr3W7rtJxHfejdFyZz0bLPaK2rRIj7h9AuY229wAAHExVnhfE2+M40vPz0ovMb4On+5ERKL9Pel//qovlyM+9G7Vq1dJ1v7YqKirwJ6rwemRTREumWJbDjMGlP+H48eOIjY21LtfjKUgguyw7IadPn9bco5s+fTqee+45p+XRphBEm5ynwg6rUdNhPffTZTuu63wM99v6ip5tctyX7Zc+rIbyXCK2x9HaJqUfF6XjOu5H6bgyn42We0RtWyVG3D+AchsdPxs9r6MSfx1HC5nfBk/3IyNQfp98df39EU6Phuu/JzT5/+zM2NhYu06IXhISEpwmni0sLERsbCyioqIQGhqK0NBQl+uoTYQo47LshHhj/PjxGDNmjPXPJSUlSEpKwpxb51u/HOM3DP9rfZv/lzX9tlfdvqfncXzFsY3fb7D5g8K5qe3HkdN1Gn3C7borc66wb9NVf1VeVLreWjnuy1f3iLtjyNJy7+l53bRQOl/HNtn+2ZffHdt9++u6KN1rWtf1VZtl2hjMTGEmhEh2dkzCt52l9PR0fPzxx3bLNm/ejPT0dABAeHg4UlNTkZuba01wNZvNyM3NRVZWls/adVl2QurXr6+5R6dX8g8REVUvphohMLkI22vah8aBqqWlpTh8+LD1z0ePHsX+/ftRt25dNG7cGOPHj8eJEyewYsUKAMBDDz2El156CU8++ST+9a9/YcuWLXj77bexfv166z7GjBmDwYMHo1OnTujcuTNycnJQVlbmNMOxni7LTohRPToiIqp+QkJNCAmRe5IRYta2/d69e3HzzTdb/2x5kj948GAsX74cJ0+exLFjx6zvp6SkYP369Xjssccwb948XHnllfjPf/6DzMxM6zr9+/fH77//jokTJ6KgoADt27fHxo0bnVIb9HTZ1glZs2YNBg8ejFdeecXao3v77bfxww8/eHRBS0pKEBcXh86Z613GKtUe9bY++Ffv8n6FsIGrffkjPKP2KFQpnGF7bo7vOXJc1/FaGPG41vHclD6fYAiHOQrEx9yO19H2vlC6fxzJnJtR4SUt95CWcIYjpWuq53XTi9K5am2vqzaWiyr0Nx9BcXGxT3IsgL/+nnivfkvUDJHLCSkzV+Hvp3/waXsD0WX5JAQwpkdHRETVj6mGCSbJJyEmjU9CLheXbScEALKyshh+ISIinwoJ83845nLBuWOIiIjIEJdtTogs2ZwQW1rjm7Y5C2r5JHpRitkD2uL2trScu9bYs14xfcccEVtaz9tfQ0TdHdMoRuXOqOUceUvLcHEt+WHefo8cj+lPMkOBtdD7u+PPnJAPm16tS07IHT99x5wQIiIi8lxIqAkhoZLhmCqGY4iIiIj8hk9CiIiIJJhCTTBJPgkxoXo+CWFOiBuWWN+akGYu5wTQK2fCFaXYqK/yIPRsv5YaKbb8VY5cC5k8FT1zBXx1PnrF9PXMDZBhRD2My+HcbSnlSAH232mZXDJfXTfLfi9WlmH3pt5+yQnZeHVb1AyVzAmpqkLP776udjkhDMcQERGRIRiOISIikmAK0aFYmY8nsAtU7IR4yV9D7Rwfb2qZOVYpFOJUPt3jFqmzvTYy+5V5tOvI2/LwWh8Za3mkrOUesv1sZUpyB8JwXn/xV5l2PcMvMve8UhhFS1hUZpiz0u+K47mNV7iPtc6obXvuK///v2fPnkX7TSoN1okpNASmUMkJ7FA9MyPYCSEiIpKgyxDdapqYypwQIiIiMgSfhBAREUkwmTiBnbfYCVEx59b51rLtSuXUlYa8asnrUDuOI9vY6f3QL+btyyHInlI7pl0bHWPRBg2T1ItT/oLt+emY2+B0325QaIOG/SDHmPtHaTp4PUux6zUUW/FzBuw+a8fjaMkBk5lmQq/jqN0DMuXhXf32XawsUzyenkyhkA7HmKpnSgjDMURERGQMPgkhIiKSoEvFVA7RJSIiIq1MISEwhUgO0ZXcPlixbLsblnK8nTPXW3NCbOlZrjgQBEMOhZbrJhMD10LvUtOe0BKjd6TXVOv+pFQjxVe05JMEStl2f/HXFAJK6zr+3rr6DvizbPu2Lp0REyb3b/rSixfRbcfuale2nU9CiIiIJOhSMVVy+2DFTggREZEEXYqVVdOckOoZhCIiIiLD8UmITrTEqrVMp65lThSZ8f0ytMRylbbVc64Pf+UvyOQDeNtGmc/RX/kLWqaDV2P73dLzc1Wq7aNFMOaA+Op7p0TmOKr1VAzGcIz32AkhIiKSYDLpMDrGVD0DE+yEEBERSeCTEO9xiK4bakN01WgZ0uevsImWY2ppvxJ/Pep1pBQOMKIEvSveDsvVUspf6zG1hAKDjcw9bxSlku968eUQddt96/k758nvij+H6O7s0QUxNSSH6FZexPX/28EhukREROQ5XUbHcAI7IiIi0orhGO9Vz0wYIiIiMhyfhGigJS6vxJNpqF0dU/a4tpziyypxYW9ju74cUql0XH/Fz/2VR2B7PuM1bqvlM7Arh61jbpLSZ6clr0CGP3Kt9GbX5gCYXkBmX2q/OcGcj8S5Y7zHTggREZEEhmO8Vz27XkRERGQ4PgkhIiKSwCch3mMnRAMtMWW9yiL7aiy91twG2/eVcli0tEErf9V10FKGXq8cEZlz0TN+bhu3X6kyXbqWNn+/wf7PWvNa3AmU6+btcYyqo2NEG2S+K4FwnZSwE+I9hmOIiIjIEOyEEBERSbj0JCRE8qX9ScjChQuRnJyMyMhIpKWlYffu3W7X7datG0wmk9Ord++/nn4OGTLE6f2ePXt6dU08xbLtbljK8e7/ch9q1aoFQDk0oleZc628nXFXhp7HkSkB7y09Pw9fhQP03K/SPeJ4HNshulpCgUaVPG/tEDLSa2i2luukdkxvr6kMpfYCym2W+X776/vsyT3uz7LtX/a/FbXCa0jt62xFJTqs2exxe9esWYNBgwZh8eLFSEtLQ05ODtauXYuDBw+iYcOGTuufOXMGFRUV1j//8ccfaNeuHf7zn/9gyJAhAC51QgoLC7Fs2TLrehEREahTp47UuSnhkxAiIiIJlpwQ2ZcWc+fOxbBhwzB06FC0bt0aixcvRnR0NJYuXepy/bp16yIhIcH62rx5M6Kjo3H33XfbrRcREWG3ni87IAA7IURERAGjpKTE7nXhwgWndSoqKpCfn4+MjAzrspCQEGRkZCAvL8+j47z22msYMGAAata0n6B127ZtaNiwIa666iqMGDECf/zxh9wJqWAnhIiISIJ8PshfFVeTkpIQFxdnfU2fPt3peKdPn0ZVVRXi4+PtlsfHx6OgoEC1vbt378a3336LBx980G55z549sWLFCuTm5mLGjBnYvn07brvtNlRVVUlcHWUcoqti+LiTCKtR4rRcZniZFmqxaaWhwHryVV6LlpwWLbkOWsqEB8JQTbV19brfVIcY2+YKBNgwSFe05Dbomr+jpZy6hlwyX+UJKV0nx3yRlQ7vO+axaPnNsX3fKS9lg+Pa7nnzO1guqtDf80NI0XOI7vHjx+1yQiIiIqT268prr72GNm3aoHPnznbLBwwYYP3/Nm3aoG3btmjWrBm2bduG7t27694OgE9CiIiIAkZsbKzdy1UnpH79+ggNDUVhYaHd8sLCQiQkJCjuv6ysDKtXr8YDDzyg2pamTZuifv36OHz4sLaT0ICdECIiIgn+TkwNDw9HamoqcnNzrcvMZjNyc3ORnp6uuO3atWtx4cIF3HfffarH+fXXX/HHH3+gUaNGHrdNK3ZCiIiIJOiZE+KpMWPGYMmSJXj99ddx4MABjBgxAmVlZRg6dCgAYNCgQRg/3rk28WuvvYa+ffuiXr16dstLS0vxxBNP4IsvvsDPP/+M3Nxc9OnTB82bN0dmZqb3F0cFc0ICkF4l343ibZ6KTMzbcVvH0vK2OSJOJcR9dI31/Kx8lSsQDPeXXveTr+ro6HkNDamFo7F2iZY8Llta6qk4rqsl96S66N+/P37//XdMnDgRBQUFaN++PTZu3GhNVj127BhCHDo2Bw8exI4dO/C///3PaX+hoaH4+uuv8frrr6OoqAiJiYno0aMHpkyZ4pO8FAt2QoiIiCQYNXdMVlYWsrKyXL63bds2p2VXXXUV3NUnjYqKwqZNmzS3QRY7IURERBK8Cae42kd1xE6Il/Qc/ufI231paZNM+5WGv6odR8t+1R7faglR2IZntMzgGgyhDj2HcWsp8e4r/hgOrue+tFz/y4GW+0nLurbfd5l7z7ZsOzbpU8affIedECIiIhkm06WX7D6qIXZCiIiIJJhMOuSEsBNCREREWjEnxHvshOhEzynF9ZpO3VfTnDu2SUuOiBKt7VOKywfCMEkZepbz9tWwT0OGk+pI6fuh5Z4OlBwQfw3t93aYtJb7R0uuCQU3dkKIiIgkGDVE93LATggREZEEhmO8Vz3PmoiIiAzHJyE6kcm3UJwm3IGWeKxeOSCOxzUqvqxlP/6KGfsq70YLmToVMrkPvmqTzHG1tEHps3K8Dlpq7sjQK+/GX7VL9MzzCGamEPlwiqmaPhJgJ4SIiEgCc0K8V037XkRERGQ0PgkhIiKSERJy6SW7j2qInRA/0LNmhR5zKmjdTq1N329wWMFH8Wa1dni7X6W8CC3zXejJMddkvMK8Go68nVNHjZb9+mouIjVKbQyE/AWZmi5q7be9jr7MTVK6xjI5Urb71TqPlNFMJpN0xdPqWjG1ena9iIiIyHB8EkJERCSBdUK8ZxJCCKMbEYhKSkoQFxeHNSHNEG0KBaAcztDyGNJxXZnHz7bUHvUqlYP31eNno8orK30+ug6nlmiTXtdGLZxh+77avablkb63U7prJTM0WK/9OtIytYKvvltafnMCocy5nlMROHK1r4uVZdi9qTeKi4sRGxuraX+esvw9cXTc/agVES61r7MXKpDywkqftjcQ8UkIERGRDJMOianVtFBI9TxrIiIiMlxQdkKmT5+Oa6+9FrVq1ULDhg3Rt29fHDx40G6d8+fPY+TIkahXrx5iYmLQr18/FBYWGtRiIiK6bP1/sTKZF6ppsbKgDMds374dI0eOxLXXXouLFy/i6aefRo8ePfD999+jZs2aAIDHHnsM69evx9q1axEXF4esrCzcdddd+Pzzz70+rlKc0jEeqxjvdFh3vMP7viqprFQO3lfTtPuLUUNpHWnJv9CrFL7TuTnsS6kdisOTVY7r7ZTuQGDkKMiwvU56DjFW4vQddfjcteSp2O1H4rsuM4xeZjhyoDGZQmCSDKfIbh+sgrITsnHjRrs/L1++HA0bNkR+fj5uuukmFBcX47XXXsOqVatwyy23AACWLVuGVq1a4YsvvsB1113ntM8LFy7gwoUL1j+XlJT49iSIiIiqucui61VcXAwAqFu3LgAgPz8flZWVyMjIsK7TsmVLNG7cGHl5eS73MX36dMTFxVlfSUlJvm84EREFP0s4RfZVDQV9J8RsNmP06NG44YYbcM011wAACgoKEB4ejtq1a9utGx8fj4KCApf7GT9+PIqLi62v48eP+7rpRER0GbDUCZF9VUdBXydkxIgR2LBhA3bs2IErr7wSALBq1SoMHTrULrwCAJ07d8bNN9+MGTNmqO7XVZ0QWzL1CPQqbaz1uFrG5es5hl+Jv+pHeMtXNV0A39W/0FLy2l91NZRoySvwV20MLXkeWtb1V25DIHyuelL73I2uE/LLpGGIjZSrE1JyvgJNJi1hnZBgkpWVhY8++giffvqptQMCAAkJCaioqEBRUZHd05DCwkIkJCQY0FIiIrpcWUe4SO6jOgrK5z9CCGRlZeG9997Dli1bkJKSYvd+amoqatSogdzcXOuygwcP4tixY0hPT/d3c4mI6HJmMl0qNib1qp6dkKAMxzz88MNYtWoV3n//fVx11VXW5XFxcYiKigJwKUzz8ccfY/ny5YiNjcWoUaMAADt37vToGGrhGLXH9IH42FWJTNltX4UV1Bgxg7DSftXodVyt11CvocB6DuX01Wfnq6G/vhpiHAyhEF/Rcxiuq3ukXFShv/mIX8Ixx6b8G7GREXL7On8BjSe8wnBMMFi0aBEAoFu3bnbLly1bhiFDhgAAXnzxRYSEhKBfv364cOECMjMz8fLLL/u5pUREdLljOMZ7QdkJ8eThTWRkJBYuXIiFCxf6oUVERFRthegwd0w1HR0TlJ0QIiKiQGEymWCSzOmQ3T5YsRPiJcchYmolrpXIxEb1ivf7aihqIOSAaHlP63G0MKoUte1x1YaTaik7r4VReUN6kRne7qvy5P4aRu8rwdBG8j12QoiIiGSYdAjHcO4YIiIi0oqJqd6rnl0vIiIiMlxQ1gnxB8v4786Z6xFWoyYA72OYwTAtta/qRxiVE6JEJifEqDoUMnkFeuUOKJXO1ppT5G0uk6/qdai1SUsp/EBgVN6TUjv8XePFn2XbT8wejdgoyToh5y7gisdzNLV34cKFmDVrFgoKCtCuXTssWLAAnTt3drnu8uXLMXToULtlEREROH/+vPXPQghkZ2djyZIlKCoqwg033IBFixahRYsW3p+YCj4JISIikmHALLpr1qzBmDFjkJ2djX379qFdu3bIzMzEqVOn3G4TGxuLkydPWl+//PKL3fszZ87E/PnzsXjxYuzatQs1a9ZEZmamXUdFb+yEEBERBZm5c+di2LBhGDp0KFq3bo3FixcjOjoaS5cudbuNyWRCQkKC9RUfH299TwiBnJwcPPvss+jTpw/atm2LFStW4LfffsO6det8dh5MTFUxdvMj1rLt3pb+DsTwiyNfPuauTowI5ajRaxi3UghCaaivq/e9bYdj2Ge8B7OpWteVuMedpmXweMvA5KvpBgLhd8OubLufjmkyhcAkObrFsn1JSYnd8oiICERE2Id6KioqkJ+fj/Hj/7oTQ0JCkJGRgby8PLfHKC0tRZMmTWA2m9GxY0dMmzYNV199NQDg6NGjKCgoQEZGhnX9uLg4pKWlIS8vDwMGDJA6P3f4JISIiEiGjuGYpKQkxMXFWV/Tp093Otzp06dRVVVl9yQDAOLj41FQUOCyiVdddRWWLl2K999/H2+88QbMZjOuv/56/PrrrwBg3U7LPvXAJyFEREQB4vjx43aJqY5PQbyVnp5uN4v89ddfj1atWuGVV17BlClTdDmGN9gJISIikmAKCYFJsliZZfvY2FjV0TH169dHaGgoCgsL7ZYXFhYiISHBo+PVqFEDHTp0wOHDhwHAul1hYSEaNWpkt8/27dt7ehqasROiYs6t861DdG0FyrBbX01R720bfNkOvY4jkxugtq23MXG9Sver7VuvIblqfDVEVy03wzYXRa29eg1l1jIcVuvQWdvPwF/DgmVyQIzKLTM8785kuvSS3YeHwsPDkZqaitzcXPTt2xcAYDabkZubi6ysLI/2UVVVhW+++Qa9evUCAKSkpCAhIQG5ubnWTkdJSQl27dqFESNGaDoVLdgJISIikhFi0mEWXW2dmDFjxmDw4MHo1KkTOnfujJycHJSVlVlrgQwaNAhXXHGFNadk8uTJuO6669C8eXMUFRVh1qxZ+OWXX/Dggw8CuDRyZvTo0Xj++efRokULpKSkYMKECUhMTLR2dHyBnRAiIqIg079/f/z++++YOHEiCgoK0L59e2zcuNGaWHrs2DGE2HSM/vzzTwwbNgwFBQWoU6cOUlNTsXPnTrRu3dq6zpNPPomysjIMHz4cRUVF6NKlCzZu3IjIyEifnQc7IURERDL8HI6xyMrKcht+2bZtm92fX3zxRbz44osqTTBh8uTJmDx5sua2eIudEB+xjeVqiY8DyjF8pRisr6YFV6PlOEr1I7TGk7XEy/WKTfurnLqeU8d7e484XlM981a8/TzUjmnbZn/lK+iZJ+S0ru1vh0G5V0ol6/W6p7UyPAfEgZ6JqdVN9TxrIiIiMhyfhBAREckwhVx6ye6jGmInhIiISIZJ+wR0LvdRDZmEEMLoRgQiyxTNnTPXu6wT4hgndaSU66Bl2nO1OTi00GsOEaX9Ou5bzynqvW2D2royjMrD0Yu/6oY48tXcJVqOqWe9GL0YcT/JnIue97Dtb53WPDpXbbpYWYbdm3qjuLhYtfiXtyx/TxQsmYjYaLkRJCXl55EwbLJP2xuI+CSEiIhIgp4T2FU37IQQERHJCNEhHCO7fZBiOMYNy2O2NSHNEG0KBaDf406jHmH6ikwoxHZdpaGArvYbaMP0AP3K6PtrOKOeIRYtjAgdOFI6dy3l1YPtGjry5X2q9PukFGpWC0N7Ut6+XFShv/mIX8IxhUuf0yUcE/+vbIZjiIiISAOOjvEaOyFEREQyDKqYejlgJ4SIiEhGSIgOE9hVzychzAlxw1VOiC09y5z7q3y0XvvWUtbZl8NQvY1l+zK3xFfDPLXsVy23xlt6XjelXCCl+L+We89ftOSP+HIIrrdD8NXaoGWqCC379vVUEX7NCVkxTZ+ckEFPMyeEiIiINGBOiNfYCSEiIpLBIbpeq55dLyIiIjIcc0LcMDInxDbOrSXG7auYsb8YVUbb27omarSU3Ncal1fa1l/1VGRqoiidj5Y8D5ny/HpNIeCvKQP89Z3Vct1k1vX1ferXnJBVMxEbHSW3r/JziL/3SeaEEBERkQYcous1hmOIiIjIEHwSYgC1x6reDjNUe9yp1+NcvR6Xa11Xaebi7zd4fBipNmkJscjMBKqF2vn4Y0ZhPR+ty9xP/gp3KB0nGEIuWjiWpR/v5e+TXvvx9Dhnz54FOnT0yTGcsE6I19gJISIiksFwjNeqZ9eLiIiIDMcnIURERDJYrMxr7ISomHPrfITVqOm0XEtugBp/TUmv1xBdPUtja2mT43Hthv/p1iJlalOK+yr/Qqb8tbdDvmXapGVbtfbb5RJIfM+U2qDWDpnrr+U6ybTJ2++0Wvv0umecvjsK68rkGFnaWy6qPN5GmkmHnBB2QoiIiEgz5oR4rXp2vYiIiMhwfBJCREQkgzkhXmMnxEsyuQG+IhNH9VVJZV+VgJZpk54Csa6DI9t71V+5M1poyUlY6VBrQmZaA8fjBmJ5e9t8Hj3rzuhZv8dTWn5j9JgG4GJlGbDJN7VInDAc47Xq2fUiIiIiw/FJCBERkQxWTPUaOyFeCoTwiwy1x516PdrVchzHss5qj58d17el9JheyyzGMkOvHSk9fpaZAVlLGEttWyNmSNWyrsxw0UCe8dUdu1CajscMhFCmzL0XaITJBCEZTpHdPlhVz64XERERGY5PQoiIiGSYTDqMjqmeT0LYCSEiIpLBIbpeMwkhhNGNCEQlJSWIi4tD58z11rLtSuWvZfIi/JVPotcU4/6K1+p5XbzNcQmUz05JMMTPZfJujDg/mZwWLfTMLfP2Oul5DytNZ6Hnd8mTcy0XVehvPoLi4mLExsZ6vG8tLH9PFHz0H8TWjJbbV1k5Em5/0KftDUR8EkJERCSBianeq57Pf4iIiPRiCcfIvjRauHAhkpOTERkZibS0NOzevdvtukuWLMGNN96IOnXqoE6dOsjIyHBaf8iQITCZTHavnj17am6XFuyEEBERybBUTJV9abBmzRqMGTMG2dnZ2LdvH9q1a4fMzEycOnXK5frbtm3DPffcg61btyIvLw9JSUno0aMHTpywD4f27NkTJ0+etL7eeustry+LJ5gT4oYl1rcmpBmiTaGq6/srN0Ap5qpGKY7qWHNDqR6Dv2omKOURAPqduwy949ieHEdLnRNAv6nYlWi5f9QEQo5UoOR52DLic1WjZ+6MTH0eV8f1Z07IyQ3LdckJaXTbEI/bm5aWhmuvvRYvvfQSAMBsNiMpKQmjRo3CuHHjVLevqqpCnTp18NJLL2HQoEEALj0JKSoqwrp166TORQs+CSEiIpJhqZgq+8Kljo3t68KFC06Hq6ioQH5+PjIyMmyaEIKMjAzk5eV51OTy8nJUVlaibt26dsu3bduGhg0b4qqrrsKIESPwxx9/SFwYdeyEEBERSbAkpsq+ACApKQlxcXHW1/Tp052Od/r0aVRVVSE+Pt5ueXx8PAoKCjxq81NPPYXExES7jkzPnj2xYsUK5ObmYsaMGdi+fTtuu+02VFVVSVwdZRwdQ0REFCCOHz9uF46JiIjQ/RgvvPACVq9ejW3btiEyMtK6fMCAAdb/b9OmDdq2bYtmzZph27Zt6N69u+7tANgJ8ZqeuQBaaijIzGViG7d32o/Dn5WmfHeKTW/wukmKHK/b/fBProDtdQqEuDugfA85vuerz0NJoFwnJf6a78lX+SSO31ml76iWuYhk6Dkfj9JvW8DXwtGxWFlsbKxqTkj9+vURGhqKwsJCu+WFhYVISEhQ3Hb27Nl44YUX8Mknn6Bt27aK6zZt2hT169fH4cOHfdYJYTiGiIhIgjCF6PLyVHh4OFJTU5Gbm2tdZjabkZubi/T0dLfbzZw5E1OmTMHGjRvRqVMn1eP8+uuv+OOPP9CoUSOP26YVOyFERERBZsyYMViyZAlef/11HDhwACNGjEBZWRmGDh0KABg0aBDGj//redmMGTMwYcIELF26FMnJySgoKEBBQQFKS0sBAKWlpXjiiSfwxRdf4Oeff0Zubi769OmD5s2bIzMz02fnwXCMj2gZDrvS4X27R9sSj1W1PO7UQuaxcCAOM3RkV2ra4T2ZYcN6DW3WOhxWZkoBT2kNQQRCKXYlMsPBtVC7Dt5ONyBDz1Cz7fsy7fNXWQCveVHnw+U+NOjfvz9+//13TJw4EQUFBWjfvj02btxoTVY9duwYQkL+es6waNEiVFRU4B//+IfdfrKzszFp0iSEhobi66+/xuuvv46ioiIkJiaiR48emDJlik/yUizYCSEiIpIgoC2c4m4fWmVlZSErK8vle9u2bbP7888//6y4r6ioKGzatElzG2SxE0JERCTDgCchl4ugzwl54YUXYDKZMHr0aOuy8+fPY+TIkahXrx5iYmLQr18/pyxiIiIiMlZQPwnZs2cPXnnlFadhRo899hjWr1+PtWvXIi4uDllZWbjrrrvw+eef63ZsteFmSkPTtORByAwrVNpWz/1qWddxmK1SPokaLWWelc7dkZY4tq9yBZTI5ICorRvouRpayEwd73iN1XKDlI6rtG4gTJfgyzL5ev3m+KssgNdMJh2G6PJJSFApLS3FwIEDsWTJEtSpU8e6vLi4GK+99hrmzp2LW265BampqVi2bBl27tyJL774wu3+Lly44FQul4iISI2eFVOrm6DthIwcORK9e/e2KzkLAPn5+aisrLRb3rJlSzRu3Fixpv706dPtSuUmJSX5rO1EREQUpJ2Q1atXY9++fS5r6hcUFCA8PBy1a9e2W65WU3/8+PEoLi62vo4fP653s4mI6HJkqZgq+6qGgi4n5Pjx43j00UexefNmu5r3siIiIlyOhZ5z63yE1agJwPsx71pjuYrl1RX2LVNTQEubtOS0qF0nmRoWRuRjOMamHXnbJpkp0WVyA/TKDdK6H1/mIXh7DKXvt6++W1pyGwKxpogavfJWArGekC0BEwTkwimy2weroOt65efn49SpU+jYsSPCwsIQFhaG7du3Y/78+QgLC0N8fDwqKipQVFRkt50nNfWJiIjIf4LuSUj37t3xzTff2C0bOnQoWrZsiaeeegpJSUmoUaMGcnNz0a9fPwDAwYMHcezYMcWa+kRERN7QOveLu31URyYhhDC6EbK6deuG9u3bIycnBwAwYsQIfPzxx1i+fDliY2MxatQoAMDOnTs93mdJSQni4uKwJqQZok2hUu3TOqOlXsPaHCkNadVzaKZewxf15KtH1VrCJt7uR42vjuPLmViNuMaBsF+tArHkvhLHNmkJLevtYmUZdm/qjeLiYtVZab1l+Xvil88+QmxMTbl9lZahyY23+7S9gSjonoR44sUXX0RISAj69euHCxcuIDMzEy+//LLRzSIiIiIbl0UnxLFGfmRkJBYuXIiFCxca0yAiIqo29KjzUV3rhFwWnRAiIiKjMCfEe+yEaKBX7FQtL8I2d0PP8sS2MVmtZZC9HQqstB81RuWPKHGa4t2xDL2X10ZmSKivchBkpiZQo9cU71ruEV9NgaAnvYb+G/VdcTquzW+OzGelxlUJgXJRhf6a9iKBE9h5rXp2vYiIiMhwfBJCREQkQ4dwDCumEhERkWasmOq9y6JOiC+o1QlRyuMA5MbEe1u/wCnPQ2JacCNqT/irDVra5C9q94+eeR9K/PW5+6osvRGfpcx3X88pHPzFV7knet/j5aIK/c1H/FIn5Ke8zaglWSfkbGkZmqbfyjohRERE5DmOjvEeOyFEREQyTNBhdIwuLQk67ISocDeLruOjQ6chrj56LKwUsnB6XCsx3E8vWkp/q62rJdwUCLQMxdaT7SN8IDCuk8yQY2+nMfDXsFq10JlSSEUt9OSrEIy/pnBwd0xA3/vS21m+yXjshBAREUkQCIGQrHghu32wYieEiIhIAsu2e696dr2IiIjIcHwSomLs5kdcDtFV46shiErHkRkGqbRfx/WNKhOuV6xXZniy2rpaPg/Hku96cYrx2/x/IOaLaCFT1lyGlntEqXS5GsfPZ7zC5+O4ri21XBKl97X8jgTK1Ap25/P/bbhYWQZs8s/9zdEx3mMnhIiISAKLlXmPnRAiIiIJfBLivep51kRERGQ4PgnRwNupp/XMAdFCJj6r1Ga1vAJvj+sU43aIW/sqn0HL56MWs9eUK6CBUh0Etetml3ej02elxl8l9/3FX7kOMvk8erVRS30bLXVMtNQx0nMaDH/g6BjvsRNCREQkgTkh3mM4hoiIiAzBJyFEREQSmJjqPZMQQhjdiEBkmaK5c+Z669wxWmjJK/BVboOvqMXwjagVIJNX4KucHaNqJjhSyufRa9p5mXNVm1MkUK6jp2RqZ/gqF8Koeh563TNq18VVfZ6LlWXYvak3iouLERsb6/GxtLD8PfHtvt2oFRMjta+zpaW4pmNnn7Y3EFXPrhcREREZjuEYIiIiCQI6hGOq6TMBhmPcsDxmWxPSzFq23V/DDr2dllrm8abaI3At5ciV2qH0WFVpCnTHdV2tr9QGXw0D9fZcA5Vtm2XChFrCPjKhAl+FGfRskxaBECZxZMRwaz2ugz/DMV/vy0etWpLhmLOlaNsxleEYIiIiCnwLFy5EcnIyIiMjkZaWht27dyuuv3btWrRs2RKRkZFo06YNPv74Y7v3hRCYOHEiGjVqhKioKGRkZODQoUO+PAV2QoiIiGRcKlYWIvnSVidkzZo1GDNmDLKzs7Fv3z60a9cOmZmZOHXqlMv1d+7ciXvuuQcPPPAAvvzyS/Tt2xd9+/bFt99+a11n5syZmD9/PhYvXoxdu3ahZs2ayMzMxPnz56WujxJ2QoiIiCRYipXJvoBLIR7b14ULF1wec+7cuRg2bBiGDh2K1q1bY/HixYiOjsbSpUtdrj9v3jz07NkTTzzxBFq1aoUpU6agY8eOeOmlly6dgxDIycnBs88+iz59+qBt27ZYsWIFfvvtN6xbt84n1w1gTohbajkhWuL9wVCmXU/+GsppSyZfxJG/2q+UDxMon6UtX+UROJLJpTEi90dLG/TMVdIyjYS/jqtErzw5wLPf23JRhf7mI37JCfly/37UqlVLal9nz55Fh/btnZZnZ2dj0qRJdssqKioQHR2Nd955B3379rUuHzx4MIqKivD+++877adx48YYM2YMRo8ebbfvdevW4auvvsJPP/2EZs2a4csvv0R7m3Z07doV7du3x7x586TOzx2OjiEiIgoQx48ft+s0RUREOK1z+vRpVFVVIT4+3m55fHw8fvjhB5f7LSgocLl+QUGB9X3LMnfr+AI7IURERBKEMEEIyblj/n/72NhYjo4hIiIiT4VcqhUi8dLy13H9+vURGhqKwsJCu+WFhYVISEhwuU1CQoLi+pb/atmnHvgkxEtqcepAiE3LxNaVtjWq/oVi3ofDdZHJSbDdVs/PUek6+etzNSr3REubZc7H2xo7gPLnruW6abmmjusq5T05no/Sud8P332u3tYMkslLcbwnlO4n27Lt2KTPlBiBJjw8HKmpqcjNzbXmhJjNZuTm5iIrK8vlNunp6cjNzbXLCdm8eTPS09MBACkpKUhISEBubq41J6SkpAS7du3CiBEjfHYu7IQQERFJsB3dIrMPLcaMGYPBgwejU6dO6Ny5M3JyclBWVoahQ4cCAAYNGoQrrrgC06dPBwA8+uij6Nq1K+bMmYPevXtj9erV2Lt3L1599VKnzWQyYfTo0Xj++efRokULpKSkYMKECUhMTLRLftUbOyFEREQSjOiE9O/fH7///jsmTpyIgoICtG/fHhs3brQmlh47dgwhIX+FeK6//nqsWrUKzz77LJ5++mm0aNEC69atwzXXXGNd58knn0RZWRmGDx+OoqIidOnSBRs3bkRkZKTUuSnhEF03tJZtD4TwixZa26tXiMKostTeDq+WOY6/aJnVWGYGZJkhunpdJ38Nd3ckM/uwLa3XwR/DorXMUKtnG5SuhdYpHFzxZ9n2vV9+hxjJIbqlZ8+iU4erq13Zdj4JISIikmDEk5DLBTshREREEtgJ8R6H6BIREZEhmBPihiXW1zlzPcJq1HR6/3Irxe4YF5aZxt2Wnu3XEkOWaZPSEEQ9+es43tKz9LcRuU16lipX4sup7n2V56FE5nPXklPkmOeh5TfHcVtX+/Fn2fZd+37QJSckrWNL5oQQERGR5xiO8R47IURERBLYCfEec0KIiIjIEMwJcUMtJ0TPHAotsVGZegV61nnQi0z9EV/lhMiwvS8CsZy6nsfRUr5brzobvuTtPSRzTdWOaVeKXeWaKd17Mm3Ukl/iq9+YQK8TsnPfIV1yQq7v2II5IUREROQ5AR1m0WU4hoiIiMh/GI5xQ+sQXSNKugPKj2uNKnGthRHXzajQgFEhFyXBMDRYaWZcXw0B1/MeCYQwqJbvmV4hOi1t0NomT6ZlOHv2LNp36OiXcMxn+44gJkYyHFN6Fjd2bMZwDBEREXmOo2O8x3AMERERGYJPQoiIiCQIoUNiquT2wYo5IW6o5YT4kl5DBWXoFZv2Zdl2peN4EjO2CMThoo60DIfVwlf5MVryDGSGu8vcX0r3gdo1NSoHzFP++t75qx3e/Cb6c4jutvyjiImRO0ZpaQm6paZUu5wQhmOIiIjIEAzHEBERSWA4xnvshBAREUng6BjvMSfEDVc5Id6W5HakZ0lrX7VJhrf1AJSm5waUcwX0rG3gr9oZWj47LZ+PlmkAgqFOiBaBUO7eqJwQb793Wq+ZXrVA9DqmO+WiCv3NR/ySE5K755guOSHdr23MnBAiIiIif2A4hoiISIIAYNZhH9UROyFEREQSmJjqPeaEuKFnnRBf5hx4G9vVGmPVa+pyLfSs5yETAzeCUTk6Sm2QyYPw1ZwoWo6pJy33kxE5Imp5Qb6q36FXbpbW+8XVcf1ZJ2Tz7uOoKZkTUlZagls7J1W7nBA+CSEiIpLA0THeYyeEiIhIAsMx3mM4xg3LY7Y1Ic0QbQoFoK30txHD2PTkq/b76/GtXmTCVv46rpYh3mr3rV5Dvh3J3E++ms7eX2FFX4VjfDW1gpbfNn/9lnnzWfkzHLNp1wldwjGZaVcwHENERESeYzjGe0FbJ+TEiRO47777UK9ePURFRaFNmzbYu3ev9X0hBCZOnIhGjRohKioKGRkZOHTokIEtJiKiy5FZ6POqjoKyE/Lnn3/ihhtuQI0aNbBhwwZ8//33mDNnDurUqWNdZ+bMmZg/fz4WL16MXbt2oWbNmsjMzMT58+cNbDkRERFZBGVOyLhx4/D555/js88+c/m+EAKJiYkYO3YsHn/8cQBAcXEx4uPjsXz5cgwYMED1GK6G6Ho7LM+oHAo9t1Xiq9i0TJu07NtfMXslgViq3F+MKoluxHXT2n7bfB+l8vt6CsT7KdCH6K7/4qQuOSG9r2tU7XJCgvJJyAcffIBOnTrh7rvvRsOGDdGhQwcsWbLE+v7Ro0dRUFCAjIwM67K4uDikpaUhLy/P5T4vXLiAkpISuxcREZEay+gY2Vd1FJSdkJ9++gmLFi1CixYtsGnTJowYMQKPPPIIXn/9dQBAQUEBACA+Pt5uu/j4eOt7jqZPn464uDjrKykpybcnQURElwUh9HlVR0HZCTGbzejYsSOmTZuGDh06YPjw4Rg2bBgWL17s9T7Hjx+P4uJi6+v48eM6tpiIiIgcBeUQ3UaNGqF169Z2y1q1aoX//ve/AICEhAQAQGFhIRo1amRdp7CwEO3bt3e5z4iICERERDgtH7v5EZd1Qhz5quaA2hh+b+PEepbZdnxPKY4tc12CofS3bZv8VYdCCy1tUrvX9Crlr+d1kWmTXlMgyJyPUs2X8SrbKp27rwRb3R9fMcMEs+QQW9ntg1VQPgm54YYbcPDgQbtlP/74I5o0aQIASElJQUJCAnJzc63vl5SUYNeuXUhPT/drW4mI6PLGnBDvBWUn5LHHHsMXX3yBadOm4fDhw1i1ahVeffVVjBw5EgBgMpkwevRoPP/88/jggw/wzTffYNCgQUhMTETfvn2NbTwREZEfnTlzBgMHDkRsbCxq166NBx54AKWlpYrrjxo1CldddRWioqLQuHFjPPLIIyguLrZbz2QyOb1Wr16tqW1BGY659tpr8d5772H8+PGYPHkyUlJSkJOTg4EDB1rXefLJJ1FWVobhw4ejqKgIXbp0wcaNGxEZGanpWHNune9yFl0jZsYEXJRQ1rCtljbLlA1XChEFYojCV9TOza5EOvwTatJyvdVCfTKPz70t464WkpNpk5b1bT+77zfYv6fl3BzXdbzmvvp+y1C6xnrNfC3zO2Fpw9mzZ9F+k1eH10yPxFJfJqYOHDgQJ0+exObNm1FZWYmhQ4di+PDhWLVqlcv1f/vtN/z222+YPXs2WrdujV9++QUPPfQQfvvtN7zzzjt26y5btgw9e/a0/rl27dqa2haUnRAAuP3223H77be7fd9kMmHy5MmYPHmyH1tFRETVTSCXbT9w4AA2btyIPXv2oFOnTgCABQsWoFevXpg9ezYSExOdtrnmmmusOZYA0KxZM0ydOhX33XcfLl68iLCwv7oOtWvXtuZheiMowzFERESXI8d6VRcuXJDaX15eHmrXrm3tgABARkYGQkJCsGvXLo/3YymiZtsBAYCRI0eifv366Ny5M5YuXQqt9U+D9kkIERFRINBj7hfL9o41qrKzszFp0iSv91tQUICGDRvaLQsLC0PdunXd1s1ydPr0aUyZMgXDh9uHySZPnoxbbrkF0dHR+N///oeHH34YpaWleOSRRzxuHzshPqIUN/VXOXV/UcodUMsX8bYUvuO+9RwKrIXSZ6kWH/c2Xq4npTaqfXaBWPbcrs06Xl+l66Rl6Kzae0rnpyX3Sgs9c2f0uqe1/hbYrm+5LuWiSpe2eESP0S3/v/3x48ftyra7Kh0BXJq+ZMaMGYq7PHDggFybcOnJTO/evdG6dWunztCECROs/9+hQweUlZVh1qxZ7IQQEREFo9jYWI/mjhk7diyGDBmiuE7Tpk2RkJCAU6dO2S2/ePEizpw5o5rLcfbsWfTs2RO1atXCe++9hxo1aiiun5aWhilTpuDChQtuO0+O2AkhIiKSYMTomAYNGqBBgwaq66Wnp6OoqAj5+flITU0FAGzZsgVmsxlpaWlutyspKUFmZiYiIiLwwQcfeDSydP/+/ahTp47HHRCAnRAiIiIpgVwxtVWrVujZs6d1apPKykpkZWVhwIAB1pExJ06cQPfu3bFixQp07twZJSUl6NGjB8rLy/HGG2/YTeraoEEDhIaG4sMPP0RhYSGuu+46REZGYvPmzZg2bZp15npPmYTWVNZqwjJFc+fM9S7rhDjyV76ClpwQPadEN6IktJ70uha++uy0xsD1apOW4/jquFpqS6jlU/mr9Lde3wFva5MAzr8rtr85TvWEJNobiLV8PPk+XKwsw+5Nva2jOnzB8vfE6m1/IDpG7hjlpSUY0K2eT9p75swZZGVl4cMPP0RISAj69euH+fPnIyYmBgDw888/IyUlBVu3bkW3bt2wbds23HzzzS73dfToUSQnJ2Pjxo0YP348Dh8+DCEEmjdvjhEjRmDYsGEICfF84C2fhBAREV3G6tat67YwGQAkJyfbDa3t1q2b6lDbnj172hUp8xY7IURERBL0mPulus4dw3CMG5bHbPu/3IdatWoB0PaYWInMo3d/8dVwwEAQiKEPLdfbl+E8LWE3Xz2m99f9r1f79fzuK4Vc9BzKrxQuVuOPkgIyvz9GhGPe3HJGl3DMwFvq+rS9gYgVU4mIiMgQDMcQERFJCPQJ7AIZOyFEREQSAnkCu0DHnBA31Iboqg0VtJvqW+MQ3UDICQk2Wspfy8S0ZUrwK5b+lsjV8Nf9pGU4rMz3Q498AK1tAHxXRt9fw4b1oufvj145Rt60qVxUob/5iF9yQlbm/qlLTsj93etUu5wQPgkhIiKSYIYOE9jp0pLgw04IERGRBOaEeI+jY4iIiMgQfBLiJbXYrq+m2ZapSaBXrNcxZq9X/RStx7Hdt9bcDU+pfc5aYvxacg60TP9uFJk2Kn0/nD5nH7VBS2lzmWvur3oq/rovtOR5+OuaGp1Hxych3mMnhIiISIJZmGCWrHgqu32wYieEiIhIAp+EeI85IURERGQI1glxQ61OiNq02v6iJT7rbjut26rtS2m/vpojxYgp6AH/1ZpQ4qt4uL9yDPSco8b289BzOnstbdIzV0OmFovSulroNY+UL+vZuNq3P+eOWbKxCNE1JeuElJVgWM/arBNCREREnhNCvk5IdX0cwHAMERERGYLhGDcsj9n2f7kPtWrVAuC7oah60XM4r5Zwk0w5by1kHjf7Y/pxrcdRIhPm8VWZdhm+up8cBXpoSs/71Jft8JTMdAm+/qz8GY555eNiREmGY86VleDfveIYjiEiIiLPcXSM9xiOISIiIkPwSQgREZEEsw6JqbLbByt2QlQMH3cSYTVKfHoMvYa4ysRYHbf9foP32xpRVlxLroCWUuyBkOujxinfwuGz02s6dU1tcMj5uB8O+/X2nvfTEGg972Gla+74fVY6P5nvma/uYy379eUQaVdTOJSLKvTX7YjKGI7xHsMxREREZAg+CSEiIpLAJyHeYyeEiIhIAnNCvMdOiE601DZwjJ9riXM7xtq9zV/QqxSzK97Gfh3bpFYbQ0tNAr3i5/6qdaClJo1a/o7t/ea4rpacBCVO7dUxX8Hu3tSwX1/mJulVC8fpe6fQZrXzUSpZr4WW4yj9HgHefz+MqgfjLT4J8R5zQoiIiMgQfBJCREQkwWy+9JLdR3XEsu1uqM2iq8b2caFamEFp6J2eJcRlyl/7aoZOpXNVe7Rre12NmsVYSbCV4Hbkr3CGke2ornx1zyiFeWVKvDvypP3logr9zUf8UrZ97n/1Kds+pl/1K9vOcAwREREZguEYIiIiCUxM9R47IURERBLM0GGIri4tCT7MCXHDEuvb/+U+1KpVC4DcsDdbRg2lDfQcBa3t83aYpC+H2foqn8eWr/KEZNrkOOxcz+HV3tKaY6Tn+XnLH9dF63F8dR/LCLSckFnvFCMqWjInpLwET/yj+uWE8EkIERGRBCEEZP89X12fB7ATQkREJIE5Id7j6BgiIiIyBHNC3LDE+taENEO0KdTpfS3xZT2nTw/E+gr+qhMiQ69S8jI5OVpqKMjw15Tv/iqFb3vdfJWL4XhcLefmmC+idI/oWY7cX7kzaut72yYteTZarrGFP3NCXlhdhEjJnJDz5SUYN6C2T9p75swZjBo1Ch9++CFCQkLQr18/zJs3DzExMW636datG7Zv32637N///jcWL15s/fOxY8cwYsQIbN26FTExMRg8eDCmT5+OsDDPgywMxxAREUkI9HDMwIEDcfLkSWzevBmVlZUYOnQohg8fjlWrViluN2zYMEyePNn65+joaOv/V1VVoXfv3khISMDOnTtx8uRJDBo0CDVq1MC0adM8bhs7IURERBICeRbdAwcOYOPGjdizZw86deoEAFiwYAF69eqF2bNnIzEx0e220dHRSEhIcPne//73P3z//ff45JNPEB8fj/bt22PKlCl46qmnMGnSJISHh3vUPoZj3HBVtj0QymP7awifI6UZOv01o6W/rpMRM3QGSmlyf4QkZMgMs3Xkr7CVEWTuJ7UwSbCEhP0Zjpm6Sp9wzDP31sbx48ft2hsREYGIiAiv97t06VKMHTsWf/75p3XZxYsXERkZibVr1+Lvf/+7y+26deuG7777DkIIJCQk4I477sCECROsT0MmTpyIDz74APv377duc/ToUTRt2hT79u1Dhw4dPGofn4QQERFJ0DMck5SUZLc8OzsbkyZN8nq/BQUFaNiwod2ysLAw1K1bFwUFBW63u/fee9GkSRMkJibi66+/xlNPPYWDBw/i3Xffte43Pj7ebhvLn5X264idECIiIgnCLCAk4ymW7V09CXFl3LhxmDFjhuI+Dxw44HV7hg//6+lSmzZt0KhRI3Tv3h1HjhxBs2bNvN6vI3ZCiIiIAkRsbKxH4aOxY8diyJAhius0bdoUCQkJOHXqlN3yixcv4syZM27zPVxJS0sDABw+fBjNmjVDQkICdu/ebbdOYWEhAGjaLzshKsZufsTlEF1HSrFqmTLIeg7vVdqv4/BRxziw7Z+1tEnPEvVahkHrVfbcl/kjRgyxVPvcv9/gfl0l98PhHvd4S23U2uSrXA299iszNYHMdlqOKzMM2l85II55K8hxHsZ9sbIM2OSb3CRHRiSmNmjQAA0aNFBdLz09HUVFRcjPz0dqaioAYMuWLTCbzdaOhScsuR+NGjWy7nfq1Kk4deqUNdyzefNmxMbGonXr1h7vl8XKiIiIJFhyQmRfvtCqVSv07NkTw4YNw+7du/H5558jKysLAwYMsI6MOXHiBFq2bGl9snHkyBFMmTIF+fn5+Pnnn/HBBx9g0KBBuOmmm9C2bVsAQI8ePdC6dWvcf//9+Oqrr7Bp0yY8++yzGDlypKZEWnZCiIiILmNvvvkmWrZsie7du6NXr17o0qULXn31r6dWlZWVOHjwIMrLywEA4eHh+OSTT9CjRw+0bNkSY8eORb9+/fDhhx9atwkNDcVHH32E0NBQpKen47777sOgQYPs6op4guEYIiIiCWazgFkyHiO7vZK6desqFiZLTk62m0AvKSnJqVqqK02aNMHHH38s1TbWCXFDrWy7DF9NJe/LeKyv6pPolVOhpQS0UWX0g6Fsuy212h965d048tf3Q+n8jJrO3lf1Vnz12yBzjzjytkaNOxcry7B7U2+/1AmZsPSMLnVCpvyrrk/bG4gYjiEiIiJDMBxDREQkIdDnjglk7IQQERFJMAsBs2QvQnb7YMVOiIqr8teiVq1aALTVylCiFrPXqzaAv3IQlNqh5ThqdUKU9uWYA+KvuUyUOH2uEm2wvaZq10lpWy2fh6/2q8ZfOVJOeUMazsFX3x+neVo0tEHpumnJmdJC5ho60lL3R6+8J70I86WX7D6qI+aEEBERkSH4JISIiEiCgIDsQFOB6hmO4RBdNyxDrzpnrkdYjZqq6/tqemujpkhX4q9pzNXaZHtttEw3LvNoV89z12v4or+mVjeqRL23n6XRj+j14O1n68th6L66rnr/rpSLKvQ3H/HLEN2nFp9GRJTcMS6cK8GMh+pziC4RERGRPwRlJ6SqqgoTJkxASkoKoqKi0KxZM0yZMsXucZgQAhMnTkSjRo0QFRWFjIwMHDp0yMBWExHR5UgIocurOgrKTsiMGTOwaNEivPTSSzhw4ABmzJiBmTNnYsGCBdZ1Zs6cifnz52Px4sXYtWsXatasiczMTJw/f97AlhMR0eXGMouu7Ks6CsrE1J07d6JPnz7o3ftSfkRycjLeeust6wyAQgjk5OTg2WefRZ8+fQAAK1asQHx8PNatW4cBAwZ4dVwj4s1qQ/Zsh2s65os4DuVUGmKsZUicr8pqa2V7Pk65Mxsc1/6LTIxby7nL5P44fu62n6XMUN9gpCXXwZbWz9kf3+9AG1rqSjC00ZG39wgZLyifhFx//fXIzc3Fjz/+CAD46quvsGPHDtx2220AgKNHj6KgoAAZGRnWbeLi4pCWloa8vDyX+7xw4QJKSkrsXkRERGqEWejyqo6C8knIuHHjUFJSgpYtWyI0NBRVVVWYOnUqBg4cCAAoKCgAAMTHx9ttFx8fb33P0fTp0/Hcc8/5tuFERHTZYdl27wXlk5C3334bb775JlatWoV9+/bh9ddfx+zZs/H66697vc/x48ejuLjY+jp+/LiOLSYiIiJHQVknJCkpCePGjcPIkSOty55//nm88cYb+OGHH/DTTz+hWbNm+PLLL9G+fXvrOl27dkX79u0xb9481WPoWSdESyzacX2ZGhCBUNPCkdaS4962yV+1M7QcVylHRy0nxF+lzLUcUykfSc/8C2/rwehJ5h5Rar+aQMxv8PZa+Ptc/FknZPS8Ql3qhOQ8Gs86IcGgvLwcISH2TQ8NDYXZfKn4fkpKChISEpCbm2t9v6SkBLt27UJ6erpf20pERJc3DtH1XlDmhNxxxx2YOnUqGjdujKuvvhpffvkl5s6di3/9618AAJPJhNGjR+P5559HixYtkJKSggkTJiAxMRF9+/Y1tvFERHRZ4QR23gvKcMzZs2cxYcIEvPfeezh16hQSExNxzz33YOLEiQgPDwdwqWeanZ2NV199FUVFRejSpQtefvll/O1vf/PoGGrhGD3LIivt26gy246U2qGltLyWEEogzpwp0wa9Pg9fhrR89cjc8Tjehij8VTrel99vbwVDaEYmtKwU3vOGP8Mxj8wt0CUcM39MQrULxwTlk5BatWohJycHOTk5btcxmUyYPHkyJk+e7L+GERFRtWMWAmbJf8/Lbh+sgrITQkREFCj0yOkIwqCELoIyMZWIiIiCH5+EqBi7+RFEm0L9eky94s1KcXitMVelPBWlfTnmL0Ah/q923jLTtnubg+A0dBbG56n4alizJ+/bksld0jpU1VP+ytXwdii2L3NNvJ0mQOv9ZHd+Dp+jTPu1tCNQpo6wMJsFzJIVT2W3D1bshBAREUlgxVTvMRxDREREhuCTECIiIglCyE9AV10TU4OyTog/WMZ/rwlp5lFOiJb8C7V4pm3M1TF2rlbe21NGxVBlprd35G1uh0w+gq+um1PujANf5oEEE5maNL6q8WLUdAlafjfUtlU6pp5TUviTP+uEDJ9+HOGRcseoOF+CV8cnVbs6IQzHEBERkSEYjiEiIpIgzDqEYzg6hlyZc+t8a9l2pUeLju99v8H9PtUeUdo9YnZ43BmIoQQlMqEAPYdx+qs0uLeCYXhiIJTN16Oct4VeM1Rr2Y/Wkvta9m27r/Eeb0V6YCfEe+yEEBERSTCLSy/ZfVRHzAkhIiIiQ/BJCBERkQSGY7zHTogKb8u26zUtdSBMHa+VlmGFWtaVaUMg5MPode7BmAMiM7Tc2/Lwel4nLWXa9cxb0UsglLP31fcB0O/31lucwM57DMcQERGRIdgJISIikmA2/zWJnfcv37XvzJkzGDhwIGJjY1G7dm088MADKC0tdbv+zz//DJPJ5PK1du1a63qu3l+9erWmtjEcQ0REJCHQwzEDBw7EyZMnsXnzZlRWVmLo0KEYPnw4Vq1a5XL9pKQknDx50m7Zq6++ilmzZuG2226zW75s2TL07NnT+ufatWtrahvLtruhtWy7nnwV31Tar54lrvVi9PTcriiV5wfsr6tReSkyn5W3+RfBQO36256vUevqdRw9KZWHV/t98lWblKZ0sLTJn2Xb73/2J4RH1pLaV8X5s1j5fFPd23vgwAG0bt0ae/bsQadOnQAAGzduRK9evfDrr78iMTHRo/106NABHTt2xGuvvWZdZjKZ8N5776Fv375et4/hGCIiIgmW0TGyL+BSx8b2deHCBam25eXloXbt2tYOCABkZGQgJCQEu3bt8mgf+fn52L9/Px544AGn90aOHIn69eujc+fOWLp0qeYnOgzHEBERSdBziG5SUpLd8uzsbEyaNMnr/RYUFKBhw4Z2y8LCwlC3bl0UFBR4tI/XXnsNrVq1wvXXX2+3fPLkybjlllsQHR2N//3vf3j44YdRWlqKRx55xOP2sRNCREQUII4fP24XjomIiHC53rhx4zBjxgzFfR04cEC6PefOncOqVaswYcIEp/dsl3Xo0AFlZWWYNWsWOyF6sp07xpbMvBOqbGooyMwB4XRchf2q5YAYkSsQCLU+HGtAjHeIgcvMERSIvK3VECj5I0r3qeNnqVSrRM/zMaquiy0966sEQh0Ux8/ONkfE8jmfPXsW6NDRL+0xQ8AsmV5pxqXtY2NjPcoJGTt2LIYMGaK4TtOmTZGQkIBTp07ZLb948SLOnDmDhIQE1eO88847KC8vx6BBg1TXTUtLw5QpU3DhwgW3nSdH7IQQERFJMKJiaoMGDdCgQQPV9dLT01FUVIT8/HykpqYCALZs2QKz2Yy0tDTV7V977TXceeedHh1r//79qFOnjscdEICdECIiIimBPES3VatW6NmzJ4YNG4bFixejsrISWVlZGDBggHVkzIkTJ9C9e3esWLECnTt3tm57+PBhfPrpp/j444+d9vvhhx+isLAQ1113HSIjI7F582ZMmzYNjz/+uKb2sROiwtuy7XrRc+islsfCWsqG+yp041TqG54fR7fQgeMj+wAIEWllex21lEt35KsQhZ77tQu5OJyrzLk70nLvaRnS6hgycrr/fMCXw4b9FcZ19dlerCzz2fGCzZtvvomsrCx0794dISEh6NevH+bPn299v7KyEgcPHkR5ebnddkuXLsWVV16JHj16OO2zRo0aWLhwIR577DEIIdC8eXPMnTsXw4YN09Q2dkKIiIgkiP+veiq7D1+pW7eu28JkAJCcnOzyScy0adMwbdo0l9v07NnTrkiZt9gJISIiksBZdL3HYmVERERkCD4JCTJaYsb+yldwKl1uM2xVJodFLYavtC+lOL1am3yVQ2HUUE3bXBqZ6dONGoarJa/ALudCZV29ppKXGa7vlPfkcL/56p6RabMRQ7UD5V50J5ATUwMdOyFEREQShNkMITkNruz2wYrhGCIiIjIEn4QQERFJMOswOkZ2+2BlEtU1EKXCMkXzmpBm1johTvkYNmRKGfsqJ0EmnhwIJdPVeFsjRa+p7mXJTPGuxzFd8bYdgRajd0Xt3PT6PIyYvh7w/rdCS90fNUrn7pQ7pvCbqcd3tFxUob/5CIqLiz0qg+4Ny98TfUd+jRoRtaT2VXnhLNYtbOvT9gYihmOIiIjIEAzHEBERSWCdEO+xE6KBv2aP1LO8tKcut/CLXtuqXQfHEJ2We0QpRKQ2dFOJzLbehiQCfQilJ7QMPfVXOXLb4yhNWwAAK23uRW8/c1f71YvT8GOFdugZIvIHdkK8x04IERGRBDPMMAu5IbZmcIguERERkd/wSQgREZEEYZYPp0g+SAla7IQEICPKhvuqjLOMQCgTrsZXeUIyn7tjm2xj74GYq6Eln0RLvoue96WW746W8u+OOUWO56NpagKbz10p30JWaw25J1p+y/T+fbpYWQZs8k8eH3NCvMdwDBERERmCT0KIiIgkcAI777ETQkREJMFsNsMsOQGd7PbBip0QDWxjoXrmAihNva5lW7W4r17tV4tr2+5bzxLp/pom3JbWOiC2bdQyTbuWXAGZOiBq/FV/QUv8X0sOggylOhVa7gOl+9bpHjagJhCgnKuhlvOl5TOwXdff91a5qEJ/vxyRZLATQkREJIGJqd5jJ4SIiEiCEGYIyTG2stsHK86i64ZldsTOmesRVqMmgMCZ6dRTSo+UZcIxWh5N+6uktVFkzs/2kbiWMI+etMxsqkRr+7SEwJQe/xs1ZFdJMAwt1zKM2Nv9yOxLJhxmO0R396befplF99b781AjPEZqX5UVpdi8Mr3azaLLJyFEREQSGI7xHjshREREMnTohICdECIiItLKLHSYwI45IWTLVU6IEpl4s5YYsr9KpMvkk2iZDl7L9N1aeDstu1qb1PblLS25GXrloagdR4ae95PSfrXQ87vjr2HDSvTM3dCyX2/L6vs7h6tcVKG/+YhfckJuGfAZwiRzQi5WlGLL6huZE0JERESeY06I99gJISIikiCEGUKy4ml1HaLLCeyIiIjIEMwJccMS61sT0gzRplAA+sVV9Rxb7y2ZNmgtZa7luN7yV06OFjI5LjLxfiPqp8jUCfFV+315Xby9Z3x5n3q7b7Xvs17TMlzOOSFd+21FWA3JnJDKUmz/783MCSEiIiLPsWKq9xiOISIiIkPwSQgREZEEsxkwS45ukcxrDVrshGigFMd25K9YqZY5IPTKfTAqB0Sv62TUnDN6fR5a7z0t+Rf+mvfEH5+Hv3JA/D1FvR7srr/K91nL9z0Q5nMygjDrMDqmmvZCGI4hIiIiQ/BJCBERkQQWK/Meh+i64apsu5Zht7bli7WWdfbVlNxGlLz25TFt961nOfJAGEasJaSiJ5n7Vi9aSrz7K0ziOEzV23LkMsOGjRqKreW4Mp+HlikclO4Ry2dzsbIMuzf19ssQ3fTeGz2a3kPJxcoy5K3v6ZP2Tp06FevXr8f+/fsRHh6OoqIi1W2EEMjOzsaSJUtQVFSEG264AYsWLUKLFi2s65w5cwajRo3Chx9+iJCQEPTr1w/z5s1DTIznw5UZjiEiIpJgeRIi+/KViooK3H333RgxYoTH28ycORPz58/H4sWLsWvXLtSsWROZmZk4f/68dZ2BAwfiu+++w+bNm/HRRx/h008/xfDh2jrHDMcQERFdxp577jkAwPLlyz1aXwiBnJwcPPvss+jTpw8AYMWKFYiPj8e6deswYMAAHDhwABs3bsSePXvQqVMnAMCCBQvQq1cvzJ49G4mJiR4di50QNyxRqqqL5dZl5aLK7foXK8vs/nz27Fm376lROo7acZX2o7Ud3rbJX8e03bft9fZkW0/3qyeZz9V2W1+1D5C7b/XieJ1s26Tlnpa5Bxw53l+2x9Xrc/XltjK0HFfm81C6pmptcHXfWn67/ZFxcLHirPTolqqLl9pdUlJitzwiIgIRERFS+9bq6NGjKCgoQEZGhnVZXFwc0tLSkJeXhwEDBiAvLw+1a9e2dkAAICMjAyEhIdi1axf+/ve/e3YwQS4dP35cAOCLL7744iuIX8ePH/fZ3xPnzp0TCQkJurU1JibGaVl2drZu7V22bJmIi4tTXe/zzz8XAMRvv/1mt/zuu+8W//znP4UQQkydOlX87W9/c9q2QYMG4uWXX/a4TXwS4kZiYiKOHz8OIQQaN26M48ePV6t6/lqVlJQgKSmJ10kFr5M6XiPP8DopE0Lg7NmzHocFvBEZGYmjR4+ioqJCl/0JIWAymeyWuXsKMm7cOMyYMUNxfwcOHEDLli11aZuvsBPiRkhICK688krro7HY2Fh+0T3A6+QZXid1vEae4XVyLy4uzufHiIyMRGRkpM+P42js2LEYMmSI4jpNmzb1at8JCQkAgMLCQjRq1Mi6vLCwEO3bt7euc+rUKbvtLl68iDNnzli39wQ7IUREREGmQYMGaNCggU/2nZKSgoSEBOTm5lo7HSUlJdi1a5d1hE16ejqKioqQn5+P1NRUAMCWLVtgNpuRlpbm8bE4RJeIiOgyduzYMezfvx/Hjh1DVVUV9u/fj/3796O0tNS6TsuWLfHee+8BAEwmE0aPHo3nn38eH3zwAb755hsMGjQIiYmJ6Nu3LwCgVatW6NmzJ4YNG4bdu3fj888/R1ZWFgYMGKApBMYnISoiIiKQnZ3t9+zkYMPr5BleJ3W8Rp7hdSJPTZw4Ea+//rr1zx06dAAAbN26Fd26dQMAHDx4EMXFxdZ1nnzySZSVlWH48OEoKipCly5dsHHjRrvQ05tvvomsrCx0797dWqxs/vz5mtrGiqlERERkCIZjiIiIyBDshBAREZEh2AkhIiIiQ7ATQkRERIZgJ4SIiIgMwU6IgoULFyI5ORmRkZFIS0vD7t27jW6SoaZPn45rr70WtWrVQsOGDdG3b18cPHjQbp3z589j5MiRqFevHmJiYtCvXz8UFhYa1OLA8MILL1jH3VvwOl1y4sQJ3HfffahXrx6ioqLQpk0b7N271/q+EAITJ05Eo0aNEBUVhYyMDBw6dMjAFvtfVVUVJkyYgJSUFERFRaFZs2aYMmWK3cRsvE4UtDyeZaaaWb16tQgPDxdLly4V3333nRg2bJioXbu2KCwsNLpphsnMzBTLli0T3377rdi/f7/o1auXaNy4sSgtLbWu89BDD4mkpCSRm5sr9u7dK6677jpx/fXXG9hqY+3evVskJyeLtm3bikcffdS6nNdJiDNnzogmTZqIIUOGiF27domffvpJbNq0SRw+fNi6zgsvvCDi4uLEunXrxFdffSXuvPNOkZKSIs6dO2dgy/1r6tSpol69euKjjz4SR48eFWvXrhUxMTFi3rx51nV4nShYsRPiRufOncXIkSOtf66qqhKJiYli+vTpBrYqsJw6dUoAENu3bxdCCFFUVCRq1Kgh1q5da13nwIEDAoDIy8szqpmGOXv2rGjRooXYvHmz6Nq1q7UTwut0yVNPPSW6dOni9n2z2SwSEhLErFmzrMuKiopERESEeOutt/zRxIDQu3dv8a9//ctu2V133SUGDhwohOB1ouDGcIwLFRUVyM/PR0ZGhnVZSEgIMjIykJeXZ2DLAoulul7dunUBAPn5+aisrLS7bi1btkTjxo2r5XUbOXIkevfubXc9AF4niw8++ACdOnXC3XffjYYNG6JDhw5YsmSJ9f2jR4+ioKDA7jrFxcUhLS2tWl2n66+/Hrm5ufjxxx8BAF999RV27NiB2267DQCvEwU3lm134fTp06iqqkJ8fLzd8vj4ePzwww8GtSqwmM1mjB49GjfccAOuueYaAEBBQQHCw8NRu3Ztu3Xj4+NRUFBgQCuNs3r1auzbtw979uxxeo/X6ZKffvoJixYtwpgxY/D0009jz549eOSRRxAeHo7Bgwdbr4Wr72F1uk7jxo1DSUkJWrZsidDQUFRVVWHq1KkYOHAgAPA6UVBjJ4S8MnLkSHz77bfYsWOH0U0JOMePH8ejjz6KzZs3GzLFd7Awm83o1KkTpk2bBuDSfBbffvstFi9ejMGDBxvcusDx9ttv480338SqVatw9dVXY//+/Rg9ejQSExN5nSjoMRzjQv369REaGuo0WqGwsBAJCQkGtSpwZGVl4aOPPsLWrVtx5ZVXWpcnJCSgoqICRUVFdutXt+uWn5+PU6dOoWPHjggLC0NYWBi2b9+O+fPnIywsDPHx8bxOABo1aoTWrVvbLWvVqhWOHTsGANZrUd2/h0888QTGjRuHAQMGoE2bNrj//vvx2GOPYfr06QB4nSi4sRPiQnh4OFJTU5Gbm2tdZjabkZubi/T0dANbZiwhBLKysvDee+9hy5YtSElJsXs/NTUVNWrUsLtuBw8exLFjx6rVdevevTu++eYb63TZ+/fvR6dOnTBw4EDr//M6ATfccIPTEO8ff/wRTZo0AQCkpKQgISHB7jqVlJRg165d1eo6lZeXIyTE/qc6NDQUZrMZAK8TBTmjM2MD1erVq0VERIRYvny5+P7778Xw4cNF7dq1RUFBgdFNM8yIESNEXFyc2LZtmzh58qT1VV5ebl3noYceEo0bNxZbtmwRe/fuFenp6SI9Pd3AVgcG29ExQvA6CXFp+HJYWJiYOnWqOHTokHjzzTdFdHS0eOONN6zrvPDCC6J27dri/fffF19//bXo06dPtRt6OnjwYHHFFVdYh+i+++67on79+uLJJ5+0rsPrRMGKnRAFCxYsEI0bNxbh4eGic+fO4osvvjC6SYYC4PK1bNky6zrnzp0TDz/8sKhTp46Ijo4Wf//738XJkyeNa3SAcOyE8Dpd8uGHH4prrrlGREREiJYtW4pXX33V7n2z2SwmTJgg4uPjRUREhOjevbs4ePCgQa01RklJiXj00UdF48aNRWRkpGjatKl45plnxIULF6zr8DpRsDIJYVN2j4iIiMhPmBNCREREhmAnhIiIiAzBTggREREZgp0QIiIiMgQ7IURERGQIdkKIiIjIEOyEEBERkSHYCSEiIiJDsBNCREREhmAnhIiIiAzBTggREREZ4v8AvUNVkDwW/3sAAAAASUVORK5CYII=" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": null + ] }, { "cell_type": "code", @@ -610,8 +639,8 @@ "source": [ "M = 50\n", "T = 100\n", - "p_list = [2/100, 6/100, 12/100, 18/100]\n", - "L_list = [1/5, 2/7, 1/3, 5/7, 3/4]\n", + "p_list = [2 / 100, 6 / 100, 12 / 100, 18 / 100]\n", + "L_list = [1 / 5, 2 / 7, 1 / 3, 5 / 7, 3 / 4]\n", "\n", "for p in p_list:\n", " for L in L_list:\n", @@ -631,20 +660,20 @@ "evalue": "name 'random' is not defined", "output_type": "error", "traceback": [ - "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[0;31mNameError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[0;32mIn[6], line 8\u001B[0m\n\u001B[1;32m 4\u001B[0m L \u001B[38;5;241m=\u001B[39m \u001B[38;5;241m2\u001B[39m\u001B[38;5;241m/\u001B[39m\u001B[38;5;241m7\u001B[39m\n\u001B[1;32m 6\u001B[0m S \u001B[38;5;241m=\u001B[39m []\n\u001B[0;32m----> 8\u001B[0m modele \u001B[38;5;241m=\u001B[39m \u001B[43mModeleSchelling\u001B[49m\u001B[43m(\u001B[49m\u001B[43mM\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mp\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mL\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 9\u001B[0m modele\u001B[38;5;241m.\u001B[39mafficher_grille(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mConfiguration Initiale\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n\u001B[1;32m 11\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m t \u001B[38;5;129;01min\u001B[39;00m T:\n", - "Cell \u001B[0;32mIn[5], line 7\u001B[0m, in \u001B[0;36mModeleSchelling.__init__\u001B[0;34m(self, M, p, L)\u001B[0m\n\u001B[1;32m 5\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mL \u001B[38;5;241m=\u001B[39m L\n\u001B[1;32m 6\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mNtot \u001B[38;5;241m=\u001B[39m \u001B[38;5;241m0\u001B[39m\n\u001B[0;32m----> 7\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mgrille \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43minitialisation_grille\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\n", - "Cell \u001B[0;32mIn[5], line 16\u001B[0m, in \u001B[0;36mModeleSchelling.initialisation_grille\u001B[0;34m(self)\u001B[0m\n\u001B[1;32m 14\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m occupe \u001B[38;5;129;01min\u001B[39;00m occupes:\n\u001B[1;32m 15\u001B[0m i, j \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mdivmod\u001B[39m(occupe, \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mM)\n\u001B[0;32m---> 16\u001B[0m grille[i, j] \u001B[38;5;241m=\u001B[39m \u001B[43mrandom\u001B[49m\u001B[38;5;241m.\u001B[39mchoice([\u001B[38;5;241m-\u001B[39m\u001B[38;5;241m1\u001B[39m, \u001B[38;5;241m1\u001B[39m])\n\u001B[1;32m 18\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m grille\n", - "\u001B[0;31mNameError\u001B[0m: name 'random' is not defined" + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[6], line 8\u001b[0m\n\u001b[1;32m 4\u001b[0m L \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m2\u001b[39m\u001b[38;5;241m/\u001b[39m\u001b[38;5;241m7\u001b[39m\n\u001b[1;32m 6\u001b[0m S \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m----> 8\u001b[0m modele \u001b[38;5;241m=\u001b[39m \u001b[43mModeleSchelling\u001b[49m\u001b[43m(\u001b[49m\u001b[43mM\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mL\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 9\u001b[0m modele\u001b[38;5;241m.\u001b[39mafficher_grille(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConfiguration Initiale\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 11\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m T:\n", + "Cell \u001b[0;32mIn[5], line 7\u001b[0m, in \u001b[0;36mModeleSchelling.__init__\u001b[0;34m(self, M, p, L)\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mL \u001b[38;5;241m=\u001b[39m L\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mNtot \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[0;32m----> 7\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgrille \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minitialisation_grille\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "Cell \u001b[0;32mIn[5], line 16\u001b[0m, in \u001b[0;36mModeleSchelling.initialisation_grille\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m occupe \u001b[38;5;129;01min\u001b[39;00m occupes:\n\u001b[1;32m 15\u001b[0m i, j \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mdivmod\u001b[39m(occupe, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mM)\n\u001b[0;32m---> 16\u001b[0m grille[i, j] \u001b[38;5;241m=\u001b[39m \u001b[43mrandom\u001b[49m\u001b[38;5;241m.\u001b[39mchoice([\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m1\u001b[39m])\n\u001b[1;32m 18\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m grille\n", + "\u001b[0;31mNameError\u001b[0m: name 'random' is not defined" ] } ], "source": [ "M = 50\n", "T = [1, 10, 100, 400]\n", - "p = 5/100\n", - "L = 2/7\n", + "p = 5 / 100\n", + "L = 2 / 7\n", "\n", "S = []\n", "\n", @@ -654,7 +683,7 @@ "for t in T:\n", " modele.simuler(t, True)\n", " S.append(modele.coef_segregation())\n", - " \n", + "\n", "plt.scatter(T, S, label=\"Coefficient de Segrégation\")\n", "plt.plot(T, S)\n", "plt.legend()\n", @@ -684,19 +713,19 @@ "evalue": "", "output_type": "error", "traceback": [ - "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[0;31mKeyboardInterrupt\u001B[0m Traceback (most recent call last)", - "Cell \u001B[0;32mIn[95], line 12\u001B[0m\n\u001B[1;32m 10\u001B[0m modele \u001B[38;5;241m=\u001B[39m ModeleSchelling(M, p, L)\n\u001B[1;32m 11\u001B[0m modele\u001B[38;5;241m.\u001B[39mafficher_grille(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mConfiguration Initiale\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n\u001B[0;32m---> 12\u001B[0m \u001B[43mmodele\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msimuler\u001B[49m\u001B[43m(\u001B[49m\u001B[43mT\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43;01mTrue\u001B[39;49;00m\u001B[43m)\u001B[49m\n\u001B[1;32m 13\u001B[0m S\u001B[38;5;241m.\u001B[39mappend(modele\u001B[38;5;241m.\u001B[39mcoef_segregation())\n\u001B[1;32m 15\u001B[0m plt\u001B[38;5;241m.\u001B[39mscatter(L, S, label\u001B[38;5;241m=\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mCoefficient de Segrégation\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n", - "Cell \u001B[0;32mIn[94], line 95\u001B[0m, in \u001B[0;36mModeleSchelling.simuler\u001B[0;34m(self, T, move_satisfaits)\u001B[0m\n\u001B[1;32m 93\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21msimuler\u001B[39m(\u001B[38;5;28mself\u001B[39m, T\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m400\u001B[39m, move_satisfaits\u001B[38;5;241m=\u001B[39m\u001B[38;5;28;01mTrue\u001B[39;00m):\n\u001B[1;32m 94\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m t \u001B[38;5;129;01min\u001B[39;00m \u001B[38;5;28mrange\u001B[39m(\u001B[38;5;241m1\u001B[39m, \u001B[38;5;28mint\u001B[39m((\u001B[38;5;241m1\u001B[39m\u001B[38;5;241m-\u001B[39m\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mp)\u001B[38;5;241m*\u001B[39m\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mM\u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39m\u001B[38;5;241m2\u001B[39m \u001B[38;5;241m*\u001B[39m T)):\n\u001B[0;32m---> 95\u001B[0m agents \u001B[38;5;241m=\u001B[39m [(i, j) \u001B[38;5;28;01mfor\u001B[39;00m i, row \u001B[38;5;129;01min\u001B[39;00m \u001B[38;5;28menumerate\u001B[39m(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mgrille) \u001B[38;5;28;01mfor\u001B[39;00m j, val \u001B[38;5;129;01min\u001B[39;00m \u001B[38;5;28menumerate\u001B[39m(row) \u001B[38;5;28;01mif\u001B[39;00m val \u001B[38;5;241m!=\u001B[39m \u001B[38;5;241m0\u001B[39m]\n\u001B[1;32m 96\u001B[0m agent \u001B[38;5;241m=\u001B[39m agents[random\u001B[38;5;241m.\u001B[39mrandint(\u001B[38;5;241m0\u001B[39m, \u001B[38;5;28mlen\u001B[39m(agents) \u001B[38;5;241m-\u001B[39m \u001B[38;5;241m1\u001B[39m)]\n\u001B[1;32m 98\u001B[0m \u001B[38;5;28;01mwhile\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m move_satisfaits \u001B[38;5;129;01mand\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39msatisfaisante(agent[\u001B[38;5;241m0\u001B[39m], agent[\u001B[38;5;241m1\u001B[39m], agent):\n", - "Cell \u001B[0;32mIn[94], line 95\u001B[0m, in \u001B[0;36m\u001B[0;34m(.0)\u001B[0m\n\u001B[1;32m 93\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21msimuler\u001B[39m(\u001B[38;5;28mself\u001B[39m, T\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m400\u001B[39m, move_satisfaits\u001B[38;5;241m=\u001B[39m\u001B[38;5;28;01mTrue\u001B[39;00m):\n\u001B[1;32m 94\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m t \u001B[38;5;129;01min\u001B[39;00m \u001B[38;5;28mrange\u001B[39m(\u001B[38;5;241m1\u001B[39m, \u001B[38;5;28mint\u001B[39m((\u001B[38;5;241m1\u001B[39m\u001B[38;5;241m-\u001B[39m\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mp)\u001B[38;5;241m*\u001B[39m\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mM\u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39m\u001B[38;5;241m2\u001B[39m \u001B[38;5;241m*\u001B[39m T)):\n\u001B[0;32m---> 95\u001B[0m agents \u001B[38;5;241m=\u001B[39m [(i, j) \u001B[38;5;28;01mfor\u001B[39;00m i, row \u001B[38;5;129;01min\u001B[39;00m \u001B[38;5;28menumerate\u001B[39m(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mgrille) \u001B[38;5;28;01mfor\u001B[39;00m j, val \u001B[38;5;129;01min\u001B[39;00m \u001B[38;5;28;43menumerate\u001B[39;49m\u001B[43m(\u001B[49m\u001B[43mrow\u001B[49m\u001B[43m)\u001B[49m \u001B[38;5;28;01mif\u001B[39;00m val \u001B[38;5;241m!=\u001B[39m \u001B[38;5;241m0\u001B[39m]\n\u001B[1;32m 96\u001B[0m agent \u001B[38;5;241m=\u001B[39m agents[random\u001B[38;5;241m.\u001B[39mrandint(\u001B[38;5;241m0\u001B[39m, \u001B[38;5;28mlen\u001B[39m(agents) \u001B[38;5;241m-\u001B[39m \u001B[38;5;241m1\u001B[39m)]\n\u001B[1;32m 98\u001B[0m \u001B[38;5;28;01mwhile\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m move_satisfaits \u001B[38;5;129;01mand\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39msatisfaisante(agent[\u001B[38;5;241m0\u001B[39m], agent[\u001B[38;5;241m1\u001B[39m], agent):\n", - "\u001B[0;31mKeyboardInterrupt\u001B[0m: " + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[95], line 12\u001b[0m\n\u001b[1;32m 10\u001b[0m modele \u001b[38;5;241m=\u001b[39m ModeleSchelling(M, p, L)\n\u001b[1;32m 11\u001b[0m modele\u001b[38;5;241m.\u001b[39mafficher_grille(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConfiguration Initiale\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 12\u001b[0m \u001b[43mmodele\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msimuler\u001b[49m\u001b[43m(\u001b[49m\u001b[43mT\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 13\u001b[0m S\u001b[38;5;241m.\u001b[39mappend(modele\u001b[38;5;241m.\u001b[39mcoef_segregation())\n\u001b[1;32m 15\u001b[0m plt\u001b[38;5;241m.\u001b[39mscatter(L, S, label\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCoefficient de Segrégation\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "Cell \u001b[0;32mIn[94], line 95\u001b[0m, in \u001b[0;36mModeleSchelling.simuler\u001b[0;34m(self, T, move_satisfaits)\u001b[0m\n\u001b[1;32m 93\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msimuler\u001b[39m(\u001b[38;5;28mself\u001b[39m, T\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m400\u001b[39m, move_satisfaits\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[1;32m 94\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m1\u001b[39m, \u001b[38;5;28mint\u001b[39m((\u001b[38;5;241m1\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mp)\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mM\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m2\u001b[39m \u001b[38;5;241m*\u001b[39m T)):\n\u001b[0;32m---> 95\u001b[0m agents \u001b[38;5;241m=\u001b[39m [(i, j) \u001b[38;5;28;01mfor\u001b[39;00m i, row \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgrille) \u001b[38;5;28;01mfor\u001b[39;00m j, val \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(row) \u001b[38;5;28;01mif\u001b[39;00m val \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 96\u001b[0m agent \u001b[38;5;241m=\u001b[39m agents[random\u001b[38;5;241m.\u001b[39mrandint(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;28mlen\u001b[39m(agents) \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m1\u001b[39m)]\n\u001b[1;32m 98\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m move_satisfaits \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msatisfaisante(agent[\u001b[38;5;241m0\u001b[39m], agent[\u001b[38;5;241m1\u001b[39m], agent):\n", + "Cell \u001b[0;32mIn[94], line 95\u001b[0m, in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 93\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msimuler\u001b[39m(\u001b[38;5;28mself\u001b[39m, T\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m400\u001b[39m, move_satisfaits\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[1;32m 94\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m t \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m1\u001b[39m, \u001b[38;5;28mint\u001b[39m((\u001b[38;5;241m1\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mp)\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mM\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m2\u001b[39m \u001b[38;5;241m*\u001b[39m T)):\n\u001b[0;32m---> 95\u001b[0m agents \u001b[38;5;241m=\u001b[39m [(i, j) \u001b[38;5;28;01mfor\u001b[39;00m i, row \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgrille) \u001b[38;5;28;01mfor\u001b[39;00m j, val \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28;43menumerate\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mrow\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mif\u001b[39;00m val \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m 96\u001b[0m agent \u001b[38;5;241m=\u001b[39m agents[random\u001b[38;5;241m.\u001b[39mrandint(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;28mlen\u001b[39m(agents) \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m1\u001b[39m)]\n\u001b[1;32m 98\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m move_satisfaits \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msatisfaisante(agent[\u001b[38;5;241m0\u001b[39m], agent[\u001b[38;5;241m1\u001b[39m], agent):\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " ] } ], "source": [ "M = 50\n", "T = 400\n", - "p_list = [2/100, 6/100, 12/100, 18/100, 25/100]\n", + "p_list = [2 / 100, 6 / 100, 12 / 100, 18 / 100, 25 / 100]\n", "L_list = range(0, 1, 4)\n", "\n", "S = []\n", @@ -707,13 +736,15 @@ " modele.afficher_grille(\"Configuration Initiale\")\n", " modele.simuler(T, True)\n", " S.append(modele.coef_segregation())\n", - " \n", + "\n", " plt.scatter(L, S, label=\"Coefficient de Segrégation\")\n", " plt.plot(T, S)\n", " plt.legend()\n", " plt.xlabel(\"L\")\n", " plt.ylabel(\"S\")\n", - " plt.title(f\"Evolution du coefficient de ségrégation S en fonction de la tolérance L = {L} pour p = {p}\")" + " plt.title(\n", + " f\"Evolution du coefficient de ségrégation S en fonction de la tolérance L = {L} pour p = {p}\"\n", + " )" ] }, { @@ -725,8 +756,8 @@ "source": [ "M = 30\n", "T = 400\n", - "p = 5/100\n", - "L = 2/7\n", + "p = 5 / 100\n", + "L = 2 / 7\n", "\n", "modele = ModeleSchelling(M, p, L)\n", "modele.afficher_grille(\"Configuration Initiale\")\n", @@ -763,8 +794,8 @@ "source": [ "M = 20\n", "T = 100\n", - "p = 5/100\n", - "L = 2/7\n", + "p = 5 / 100\n", + "L = 2 / 7\n", "\n", "modele = ModeleSchelling(M, p, L)\n", "modele.afficher_grille(\"Configuration Initiale\")\n", diff --git a/L3/Statistiques/TP1.ipynb b/L3/Statistiques/TP1.ipynb index 681d9f8..be58569 100644 --- a/L3/Statistiques/TP1.ipynb +++ b/L3/Statistiques/TP1.ipynb @@ -48,10 +48,10 @@ "nb_repl = 100000\n", "sample = np.random.exponential(lam, nb_repl)\n", "intervalle = np.linspace(0, 5, 100)\n", - "plt.hist(sample, bins=intervalle, density=True, label='Echantillon')\n", + "plt.hist(sample, bins=intervalle, density=True, label=\"Echantillon\")\n", "\n", "densite = stats.expon().pdf\n", - "plt.plot(intervalle, densite(intervalle), label='Fonction densité')\n", + "plt.plot(intervalle, densite(intervalle), label=\"Fonction densité\")\n", "plt.legend()" ] }, @@ -86,15 +86,15 @@ ], "source": [ "np_repl = 10000\n", - "sampleX, sampleY = 2*np.random.rand(np_repl)-1, 2*np.random.rand(np_repl)-1\n", + "sampleX, sampleY = 2 * np.random.rand(np_repl) - 1, 2 * np.random.rand(np_repl) - 1\n", "\n", "intervalle = np.linspace(-2, 2, 100)\n", - "plt.hist(sampleX + sampleY, bins=intervalle, density=True, label='Echantillon')\n", + "plt.hist(sampleX + sampleY, bins=intervalle, density=True, label=\"Echantillon\")\n", "\n", "densite = stats.uniform(-1, 2).pdf\n", - "plt.plot(intervalle, densite(intervalle), label='Fonction densité')\n", + "plt.plot(intervalle, densite(intervalle), label=\"Fonction densité\")\n", "\n", - "plt.plot(intervalle, 1/4 * np.maximum(2 - np.abs(intervalle), 0), label='Fonction')\n", + "plt.plot(intervalle, 1 / 4 * np.maximum(2 - np.abs(intervalle), 0), label=\"Fonction\")\n", "plt.legend()" ] }, @@ -130,10 +130,22 @@ "source": [ "lam = 1\n", "nb_repl = 10000\n", - "sampleX, sampleY, sampleZ = np.random.exponential(lam, nb_repl), np.random.exponential(lam, nb_repl), np.random.exponential(lam, nb_repl)\n", + "sampleX, sampleY, sampleZ = (\n", + " np.random.exponential(lam, nb_repl),\n", + " np.random.exponential(lam, nb_repl),\n", + " np.random.exponential(lam, nb_repl),\n", + ")\n", "intervalle = np.linspace(-5, 5, 100)\n", - "plt.hist(sampleX - sampleY/2, bins=intervalle, density=True, alpha=.7, label='Echantillon de X - Y/2')\n", - "plt.hist(sampleZ/2, bins=intervalle, density=True, alpha=.7, label='Echantillon de Z')\n", + "plt.hist(\n", + " sampleX - sampleY / 2,\n", + " bins=intervalle,\n", + " density=True,\n", + " alpha=0.7,\n", + " label=\"Echantillon de X - Y/2\",\n", + ")\n", + "plt.hist(\n", + " sampleZ / 2, bins=intervalle, density=True, alpha=0.7, label=\"Echantillon de Z\"\n", + ")\n", "plt.legend()" ] }, @@ -157,15 +169,17 @@ } ], "source": [ - "p = 1/2\n", + "p = 1 / 2\n", "nb_repl = 1000\n", "\n", "plt.figure(figsize=(18, 5))\n", "for i, k in enumerate([10, 100, 1000]):\n", - " plt.subplot(1, 3, i+1)\n", + " plt.subplot(1, 3, i + 1)\n", " sample = np.random.binomial(k, p, nb_repl)\n", " intervalle = np.linspace(np.min(sample), np.max(sample), 100)\n", - " plt.hist(sample, bins=intervalle, density=True, label=f'Echantillon de X pour n={k}')\n", + " plt.hist(\n", + " sample, bins=intervalle, density=True, label=f\"Echantillon de X pour n={k}\"\n", + " )\n", " plt.legend()" ] }, @@ -179,7 +193,7 @@ "outputs": [], "source": [ "def sample_uniforme(N):\n", - " return 2*np.random.rand(N) - 1" + " return 2 * np.random.rand(N) - 1" ] }, { @@ -218,7 +232,7 @@ "\n", "for _ in range(nb_lgn):\n", " liste_Sn.append(np.mean(sample_uniforme(nb_repl)))\n", - " \n", + "\n", "nb_bins = 100\n", "intervalles = np.linspace(np.min(liste_Sn), np.max(liste_Sn), nb_bins)\n", "plt.hist(liste_Sn, density=True, bins=intervalles)\n", @@ -256,12 +270,14 @@ "liste_Sn = []\n", "\n", "for _ in range(nb_lgn):\n", - " liste_Sn.append(np.mean(np.sqrt(3*nb_repl) * np.tan(np.pi/2 * sample_uniforme(nb_repl))))\n", + " liste_Sn.append(\n", + " np.mean(np.sqrt(3 * nb_repl) * np.tan(np.pi / 2 * sample_uniforme(nb_repl)))\n", + " )\n", "\n", - "#nb_bins = 100\n", - "#intervalles = np.linspace(np.min(liste_Sn), np.max(liste_Sn), nb_bins)\n", - "#plt.hist(liste_Sn, density=True, bins=intervalles)\n", - "#plt.show()\n", + "# nb_bins = 100\n", + "# intervalles = np.linspace(np.min(liste_Sn), np.max(liste_Sn), nb_bins)\n", + "# plt.hist(liste_Sn, density=True, bins=intervalles)\n", + "# plt.show()\n", "\n", "plt.figure()\n", "densite = stats.norm(scale=1).pdf\n", diff --git a/L3/Statistiques/TP2.ipynb b/L3/Statistiques/TP2.ipynb index 35872c4..30f0a78 100644 --- a/L3/Statistiques/TP2.ipynb +++ b/L3/Statistiques/TP2.ipynb @@ -27,7 +27,12 @@ "source": [ "def f(L, z):\n", " x, y = L[0], L[1]\n", - " return np.power(z*x, 2) + np.power(y/z, 2) - np.cos(2 * np.pi * x) - np.cos(2 * np.pi * y)" + " return (\n", + " np.power(z * x, 2)\n", + " + np.power(y / z, 2)\n", + " - np.cos(2 * np.pi * x)\n", + " - np.cos(2 * np.pi * y)\n", + " )" ] }, { @@ -123,17 +128,17 @@ "source": [ "plt.figure(figsize=(18, 5))\n", "for i, nb_repl in enumerate([100, 1000, 10000]):\n", - " plt.subplot(1, 3, i+1)\n", + " plt.subplot(1, 3, i + 1)\n", " sample_X1 = np.random.normal(0, 1, nb_repl)\n", " sample_X2 = np.random.normal(3, np.sqrt(5), nb_repl)\n", - " sample_e = np.random.normal(0, np.sqrt(1/4), nb_repl)\n", + " sample_e = np.random.normal(0, np.sqrt(1 / 4), nb_repl)\n", " Y = 5 * sample_X1 - 4 * sample_X2 + 2 + sample_e\n", "\n", " intervalle = np.linspace(np.min(Y), np.max(Y), 100)\n", - " plt.hist(Y, bins=intervalle, density=True, label='Echantillon de Y')\n", + " plt.hist(Y, bins=intervalle, density=True, label=\"Echantillon de Y\")\n", "\n", " densite = stats.norm(-10, np.sqrt(105.25)).pdf\n", - " plt.plot(intervalle, densite(intervalle), label='Fonction densité')\n", + " plt.plot(intervalle, densite(intervalle), label=\"Fonction densité\")\n", "\n", " plt.title(f\"Graphique de la somme de gaussiennes pour N={nb_repl}\")\n", " plt.legend()" @@ -151,8 +156,9 @@ "def theta_hat(Y):\n", " return np.mean(Y)\n", "\n", + "\n", "def sigma_hat(Y):\n", - " return 1/nb_repl * np.sum(np.power(Y - theta_hat(Y), 2))" + " return 1 / nb_repl * np.sum(np.power(Y - theta_hat(Y), 2))" ] }, { @@ -166,7 +172,11 @@ "source": [ "def log_likehood_gauss(X, Y):\n", " theta, sigma_2 = X[0], X[1]\n", - " return 1/2*np.log(2*np.pi) + 1/2*np.log(sigma_2) + 1/(2*nb_repl*sigma_2) * np.sum(np.power(Y - theta, 2))" + " return (\n", + " 1 / 2 * np.log(2 * np.pi)\n", + " + 1 / 2 * np.log(sigma_2)\n", + " + 1 / (2 * nb_repl * sigma_2) * np.sum(np.power(Y - theta, 2))\n", + " )" ] }, { @@ -191,9 +201,9 @@ "nb_repl = 5000\n", "sample_X1 = np.random.normal(0, 1, nb_repl)\n", "sample_X2 = np.random.normal(3, np.sqrt(5), nb_repl)\n", - "sample_e = np.random.normal(0, np.sqrt(1/4), nb_repl)\n", + "sample_e = np.random.normal(0, np.sqrt(1 / 4), nb_repl)\n", "Y = 5 * sample_X1 - 4 * sample_X2 + 2 + sample_e\n", - " \n", + "\n", "mk = {\"method\": \"BFGS\", \"args\": Y}\n", "res = opt.basinhopping(log_likehood_gauss, x0=(-1, 98.75), minimizer_kwargs=mk)\n", "print(res.x)\n", @@ -211,12 +221,12 @@ "outputs": [], "source": [ "def simule(a, b, n):\n", - " X = np.random.gamma(a, 1/b, n)\n", + " X = np.random.gamma(a, 1 / b, n)\n", " intervalle = np.linspace(0, np.max(X), 100)\n", - " plt.hist(X, bins=intervalle, density=True, label='Echantillon de X')\n", + " plt.hist(X, bins=intervalle, density=True, label=\"Echantillon de X\")\n", "\n", - " densite = stats.gamma.pdf(intervalle, a, 0, 1/b)\n", - " plt.plot(intervalle, densite, label='Fonction densité Gamma(2, 1)')\n", + " densite = stats.gamma.pdf(intervalle, a, 0, 1 / b)\n", + " plt.plot(intervalle, densite, label=\"Fonction densité Gamma(2, 1)\")\n", " plt.legend()" ] }, @@ -254,8 +264,13 @@ "source": [ "def log_likehood_gamma(X, sample):\n", " a, b = X[0], X[1]\n", - " n = len(sample) \n", - " return -n*a*np.log(b) + n * np.log(sp.gamma(a)) - (a-1) * np.sum(np.log(sample)) + b * np.sum(sample)" + " n = len(sample)\n", + " return (\n", + " -n * a * np.log(b)\n", + " + n * np.log(sp.gamma(a))\n", + " - (a - 1) * np.sum(np.log(sample))\n", + " + b * np.sum(sample)\n", + " )" ] }, { @@ -296,7 +311,7 @@ "nb_repl = 1000\n", "a, b = 2, 1\n", "\n", - "sample = np.random.gamma(a, 1/b, nb_repl)\n", + "sample = np.random.gamma(a, 1 / b, nb_repl)\n", "mk = {\"method\": \"BFGS\", \"args\": sample}\n", "res = opt.basinhopping(log_likehood_gamma, x0=(1, 1), minimizer_kwargs=mk)\n", "print(res.x)" diff --git a/M1/Numerical Methods/TP1.ipynb b/M1/Numerical Methods/TP1.ipynb index 54906b1..d8e9517 100644 --- a/M1/Numerical Methods/TP1.ipynb +++ b/M1/Numerical Methods/TP1.ipynb @@ -122,7 +122,7 @@ " y = np.zeros(N + 1)\n", " y[0] = y0\n", " for n in range(N):\n", - " y[n + 1] = np.power(h + np.sqrt(h ** 2 + y[n]), 2)\n", + " y[n + 1] = np.power(h + np.sqrt(h**2 + y[n]), 2)\n", " return t, y" ] }, @@ -158,7 +158,7 @@ "\n", "plt.scatter(t, sol_appr, label=\"Approximation with EI\")\n", "plt.plot(x, f_exact(x, T), label=\"Exact solution\", color=\"red\")\n", - "plt.plot(x, x ** 2, label=\"Square function\", color=\"green\")\n", + "plt.plot(x, x**2, label=\"Square function\", color=\"green\")\n", "plt.legend()\n", "plt.show()" ] @@ -297,9 +297,9 @@ "\n", "sol = odeint(F, y0, t, args=(a, r))\n", "\n", - "plt.plot(t, sol[:, 0], label='S(t)')\n", - "plt.plot(t, sol[:, 1], label='I(t)')\n", - "plt.plot(t, sol[:, 2], label='R(t)')\n", + "plt.plot(t, sol[:, 0], label=\"S(t)\")\n", + "plt.plot(t, sol[:, 1], label=\"I(t)\")\n", + "plt.plot(t, sol[:, 2], label=\"R(t)\")\n", "plt.legend()\n", "plt.show()" ] @@ -336,7 +336,9 @@ "\n", "def calculate_errors(sol_exact, sol_appr):\n", " return np.max(\n", - " np.power(np.abs(sol_appr - sol_exact), 2)[np.isfinite(np.power(np.abs(sol_appr - sol_exact), 2))]\n", + " np.power(np.abs(sol_appr - sol_exact), 2)[\n", + " np.isfinite(np.power(np.abs(sol_appr - sol_exact), 2))\n", + " ]\n", " )\n", "\n", "\n", @@ -356,8 +358,8 @@ "plt.plot(errors_EE, label=\"Euler Explicit\")\n", "plt.plot(errors_H, label=\"Heun\")\n", "plt.plot(errors_RK4, label=\"Runge Kutta order 4\")\n", - "plt.yscale('log')\n", - "plt.xscale('log')\n", + "plt.yscale(\"log\")\n", + "plt.xscale(\"log\")\n", "plt.legend()\n", "plt.show()" ] @@ -431,23 +433,23 @@ "# Plot the real parts\n", "plt.figure(figsize=(12, 6))\n", "plt.subplot(1, 2, 1)\n", - "plt.plot(t, np.real(x_appr_EI), label='Numerical Solution by EI')\n", - "plt.plot(t, np.real(x_appr_EE), label='Numerical Solution by EE')\n", - "plt.plot(t, np.real(x_exact), label='Exact Solution', linestyle='--')\n", - "plt.xlabel('Time')\n", - "plt.ylabel('Real Part')\n", + "plt.plot(t, np.real(x_appr_EI), label=\"Numerical Solution by EI\")\n", + "plt.plot(t, np.real(x_appr_EE), label=\"Numerical Solution by EE\")\n", + "plt.plot(t, np.real(x_exact), label=\"Exact Solution\", linestyle=\"--\")\n", + "plt.xlabel(\"Time\")\n", + "plt.ylabel(\"Real Part\")\n", "plt.legend()\n", - "plt.title('Real Part of the Solution')\n", + "plt.title(\"Real Part of the Solution\")\n", "\n", "# Plot the imaginary parts\n", "plt.subplot(1, 2, 2)\n", - "plt.plot(t, np.imag(x_appr_EI), label='Numerical Solution by EI')\n", - "plt.plot(t, np.imag(x_appr_EE), label='Numerical Solution by EE')\n", - "plt.plot(t, np.imag(x_exact), label='Exact Solution', linestyle='--')\n", - "plt.xlabel('Time')\n", - "plt.ylabel('Imaginary Part')\n", + "plt.plot(t, np.imag(x_appr_EI), label=\"Numerical Solution by EI\")\n", + "plt.plot(t, np.imag(x_appr_EE), label=\"Numerical Solution by EE\")\n", + "plt.plot(t, np.imag(x_exact), label=\"Exact Solution\", linestyle=\"--\")\n", + "plt.xlabel(\"Time\")\n", + "plt.ylabel(\"Imaginary Part\")\n", "plt.legend()\n", - "plt.title('Imaginary Part of the Solution')\n", + "plt.title(\"Imaginary Part of the Solution\")\n", "\n", "plt.show()" ] diff --git a/M1/Numerical Methods/TP2.ipynb b/M1/Numerical Methods/TP2.ipynb index b995c7f..9ab7be0 100644 --- a/M1/Numerical Methods/TP2.ipynb +++ b/M1/Numerical Methods/TP2.ipynb @@ -1,8 +1,9 @@ { "cells": [ { - "metadata": {}, "cell_type": "markdown", + "id": "c897654e0a140cbd", + "metadata": {}, "source": [ "# Automatic Differentiation\n", "\n", @@ -11,42 +12,18 @@ "Loss function: softmax layer in $\\mathbb{R}^3$\n", "\n", "Architecture: FC/ReLU 4-5-7-3" - ], - "id": "c897654e0a140cbd" + ] }, { + "cell_type": "code", + "execution_count": 33, + "id": "70a4eb1d928b10d0", "metadata": { "ExecuteTime": { "end_time": "2025-03-24T15:16:27.015669Z", "start_time": "2025-03-24T15:16:23.856887Z" } }, - "cell_type": "code", - "source": [ - "import numpy as np\n", - "from sklearn.neural_network import MLPClassifier\n", - "from sklearn.datasets import make_classification\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.metrics import accuracy_score\n", - "\n", - "accuracies = []\n", - "\n", - "for _ in range(10):\n", - " X, y = make_classification(n_samples=1000, n_features=4, n_classes=3, n_clusters_per_class=1)\n", - "\n", - " X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)\n", - " model = MLPClassifier(hidden_layer_sizes=(5, 7), activation='relu', max_iter=10000, solver='adam')\n", - " model.fit(X_train, y_train)\n", - "\n", - " y_pred = model.predict(X_test)\n", - " accuracies.append(accuracy_score(y_test, y_pred))\n", - "\n", - "print(f'Mean Accuracy: {np.mean(accuracies) * 100:.0f}%')\n", - "print(f'STD Accuracy: {np.std(accuracies) * 100:.0f}%')\n", - "print(f\"Max accuracy: {np.max(accuracies) * 100:.0f}%\")\n", - "print(f\"Min accuracy: {np.min(accuracies) * 100:.0f}%\")" - ], - "id": "70a4eb1d928b10d0", "outputs": [ { "name": "stdout", @@ -59,20 +36,47 @@ ] } ], - "execution_count": 33 + "source": [ + "import numpy as np\n", + "from sklearn.neural_network import MLPClassifier\n", + "from sklearn.datasets import make_classification\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import accuracy_score\n", + "\n", + "accuracies = []\n", + "\n", + "for _ in range(10):\n", + " X, y = make_classification(\n", + " n_samples=1000, n_features=4, n_classes=3, n_clusters_per_class=1\n", + " )\n", + "\n", + " X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)\n", + " model = MLPClassifier(\n", + " hidden_layer_sizes=(5, 7), activation=\"relu\", max_iter=10000, solver=\"adam\"\n", + " )\n", + " model.fit(X_train, y_train)\n", + "\n", + " y_pred = model.predict(X_test)\n", + " accuracies.append(accuracy_score(y_test, y_pred))\n", + "\n", + "print(f\"Mean Accuracy: {np.mean(accuracies) * 100:.0f}%\")\n", + "print(f\"STD Accuracy: {np.std(accuracies) * 100:.0f}%\")\n", + "print(f\"Max accuracy: {np.max(accuracies) * 100:.0f}%\")\n", + "print(f\"Min accuracy: {np.min(accuracies) * 100:.0f}%\")" + ] }, { + "cell_type": "code", + "execution_count": null, + "id": "96b6d46883ed5570", "metadata": { "ExecuteTime": { "end_time": "2025-03-24T14:37:53.507776Z", "start_time": "2025-03-24T14:37:53.505376Z" } }, - "cell_type": "code", - "source": "", - "id": "96b6d46883ed5570", "outputs": [], - "execution_count": null + "source": [] } ], "metadata": { diff --git a/M1/Numerical Methods/TP2_DANJOU_Arthur.ipynb b/M1/Numerical Methods/TP2_DANJOU_Arthur.ipynb index 14b3e8f..396fee8 100644 --- a/M1/Numerical Methods/TP2_DANJOU_Arthur.ipynb +++ b/M1/Numerical Methods/TP2_DANJOU_Arthur.ipynb @@ -51,17 +51,18 @@ " \"\"\"\n", " return S0 * np.exp((mu - 0.5 * sigma**2) * t + sigma * W)\n", "\n", + "\n", "def euler_maruyama(mu, sigma, T, N, X0=0.0):\n", " \"\"\"\n", " Simulation d'une EDS de Black-Scholes par la méthode d'Euler-Maruyama\n", - " \n", + "\n", " Paramètres :\n", " mu (float) : drift\n", " sigma (float) : volatilité\n", " T (int) : temps final\n", " N (int) : nombre de pas de temps\n", " X0 (float) : valeur initiale\n", - " \n", + "\n", " Retourne :\n", " t (array-like) : tableau des temps\n", " X (array-like) : tableau des valeurs de l'EDS\n", @@ -70,17 +71,18 @@ "\n", " t = np.linspace(0, T, N + 1)\n", " X = np.zeros(N + 1)\n", - " \n", + "\n", " X[0] = X0\n", "\n", " dW = np.random.normal(0, np.sqrt(dt), N)\n", - " \n", + "\n", " for i in range(N):\n", " St = S(t[i], X[i], mu, sigma, dW[i])\n", " X[i + 1] = X[i] + mu * St * dt + sigma * St * dW[i]\n", - " \n", + "\n", " return t, X\n", "\n", + "\n", "def plot_brownien(t, X, B=None):\n", " \"\"\"\n", " Plot la simulation d'Euler-Maruyama\n", @@ -90,15 +92,15 @@ " X (array-like) : tableau des valeurs de l'EDS\n", " B (float) : barrière (optionnelle)\n", " \"\"\"\n", - " plt.plot(t, X, alpha=0.5, label='Euler-Maruyama')\n", - " plt.title('Simulation d\\'Euler-Maruyama pour une EDS')\n", - " \n", + " plt.plot(t, X, alpha=0.5, label=\"Euler-Maruyama\")\n", + " plt.title(\"Simulation d'Euler-Maruyama pour une EDS\")\n", + "\n", " if B is not None:\n", - " plt.axhline(B, label='Barrière', color='red', linestyle='--')\n", - " \n", + " plt.axhline(B, label=\"Barrière\", color=\"red\", linestyle=\"--\")\n", + "\n", " plt.legend()\n", - " plt.xlabel('Temps')\n", - " plt.ylabel('X(t)')\n", + " plt.xlabel(\"Temps\")\n", + " plt.ylabel(\"X(t)\")\n", " plt.grid()" ] }, @@ -165,10 +167,11 @@ "\n", "np.random.seed(333)\n", "\n", + "\n", "def plot_convergence(S0, mu, sigma, T):\n", " \"\"\"\n", " Plot la convergence du schéma d'Euler-Maruyama\n", - " \n", + "\n", " Paramètres :\n", " S0 (int) : valeur initiale\n", " mu (float) : drift\n", @@ -176,26 +179,27 @@ " T (int) : temps final\n", " \"\"\"\n", " errors = []\n", - " \n", + "\n", " for N in N_list:\n", " dt = T / N\n", " dW = np.random.normal(0, np.sqrt(dt), N)\n", - " \n", + "\n", " exact = S(T, S0, mu, sigma, dW)\n", " _, X = euler_maruyama(mu=mu, sigma=sigma, T=T, N=N, X0=S0)\n", - " \n", + "\n", " errors.append(np.max(np.abs(X[1:] - exact)))\n", - " \n", - " plt.plot(np.log(h_list), np.log(errors), 'o-', label='Erreur numérique')\n", - " plt.plot(np.log(h_list), 0.5 * np.log(h_list), '--', label='Ordre 1/2')\n", - " plt.plot(np.log(h_list), np.log(h_list), '--', label='Ordre 1')\n", - " plt.plot(np.log(h_list), 2*np.log(h_list), '--', label='Ordre 2')\n", - " plt.xlabel('log(h)')\n", - " plt.ylabel('log(Erreur)')\n", - " plt.title('Convergence du schéma d\\'Euler-Maruyama')\n", + "\n", + " plt.plot(np.log(h_list), np.log(errors), \"o-\", label=\"Erreur numérique\")\n", + " plt.plot(np.log(h_list), 0.5 * np.log(h_list), \"--\", label=\"Ordre 1/2\")\n", + " plt.plot(np.log(h_list), np.log(h_list), \"--\", label=\"Ordre 1\")\n", + " plt.plot(np.log(h_list), 2 * np.log(h_list), \"--\", label=\"Ordre 2\")\n", + " plt.xlabel(\"log(h)\")\n", + " plt.ylabel(\"log(Erreur)\")\n", + " plt.title(\"Convergence du schéma d'Euler-Maruyama\")\n", " plt.legend()\n", " plt.grid(True)\n", "\n", + "\n", "plt.figure(figsize=(10, 5))\n", "plot_convergence(S0, r, sigma, T)\n", "plt.show()" @@ -269,6 +273,7 @@ "plot_brownien(t, X, B=B)\n", "plt.show()\n", "\n", + "\n", "def is_barrier_breached(X, B):\n", " \"\"\"Renvoie True si la barrière est franchie, False sinon\n", " La barrière est franchie si X >= B\n", @@ -282,7 +287,12 @@ " \"\"\"\n", " return any(X >= B)\n", "\n", - "print(\"La barrière a été franchie\" if is_barrier_breached(X, B) else \"La barrière n'a pas été franchie\")" + "\n", + "print(\n", + " \"La barrière a été franchie\"\n", + " if is_barrier_breached(X, B)\n", + " else \"La barrière n'a pas été franchie\"\n", + ")" ] }, { @@ -299,18 +309,19 @@ " trajectories (list of tuples): Liste des trajectoires avec le temps et les valeurs\n", " B (float): Valeur de la barrière\n", " \"\"\"\n", - " for (t, X) in trajectories:\n", - " col = 'pink' if is_barrier_breached(X, B) else 'lime'\n", + " for t, X in trajectories:\n", + " col = \"pink\" if is_barrier_breached(X, B) else \"lime\"\n", " plt.plot(t, X, alpha=0.5, color=col)\n", - " plt.title('Simulation d\\'Euler-Maruyama pour une EDS')\n", - " \n", - " plt.axhline(B, label='Barrière', color='red', linestyle='--')\n", - " \n", + " plt.title(\"Simulation d'Euler-Maruyama pour une EDS\")\n", + "\n", + " plt.axhline(B, label=\"Barrière\", color=\"red\", linestyle=\"--\")\n", + "\n", " plt.legend()\n", - " plt.xlabel('Temps')\n", - " plt.ylabel('X(t)')\n", + " plt.xlabel(\"Temps\")\n", + " plt.ylabel(\"X(t)\")\n", " plt.grid()\n", - " \n", + "\n", + "\n", "def payoff(X, B, K):\n", " \"\"\"Calcule le payoff d'une option en fonction des trajectoires.\n", "\n", @@ -324,9 +335,10 @@ " \"\"\"\n", " if not is_barrier_breached(X, B):\n", " return max(X[-1] - K, 0)\n", - " else: \n", + " else:\n", " return 0\n", - " \n", + "\n", + "\n", "def call_BS(x):\n", " \"\"\"Calcul du prix d'une option d'achat européenne selon le modèle de Black-Scholes en fonction de x.\n", "\n", @@ -336,27 +348,34 @@ " Retourne:\n", " float: Le prix de l'option d'achat européenne.\n", " \"\"\"\n", - " d1 = (np.log(x/K) + (r + 0.5 * sigma**2) * T) / (sigma * np.sqrt(T))\n", + " d1 = (np.log(x / K) + (r + 0.5 * sigma**2) * T) / (sigma * np.sqrt(T))\n", " d2 = d1 - sigma * np.sqrt(T)\n", " return x * stats.norm.cdf(d1) - K * np.exp(-r * T) * stats.norm.cdf(d2)\n", - " \n", + "\n", + "\n", "def compute_payoff_BS():\n", " \"\"\"Calcul du prix d'une option d'achat Up-and-Out selon le modèle de Black-Scholes en fonction de la barrière.\n", - " \n", + "\n", " Retourne:\n", " float: Le prix de l'option d'achat Up-and-Out.\n", " \"\"\"\n", " lam = (r + 0.5 * sigma**2) / sigma**2\n", - " return call_BS(S0) - call_BS(S0) * (S0/B)**(2 * lam) + (S0/B)**(lam - 1) * (call_BS(B**2/S0) - (S0/B)**2 * call_BS(B**2/S0))\n", - " \n", + " return (\n", + " call_BS(S0)\n", + " - call_BS(S0) * (S0 / B) ** (2 * lam)\n", + " + (S0 / B) ** (lam - 1)\n", + " * (call_BS(B**2 / S0) - (S0 / B) ** 2 * call_BS(B**2 / S0))\n", + " )\n", + "\n", + "\n", "def compute_payoff(trajectories, B, K):\n", " \"\"\"Calcule le payoff d'une option en fonction des trajectoires.\n", - " \n", + "\n", " Paramètres:\n", " trajectories (list of tuples): Liste des trajectoires avec le temps et les valeurs.\n", " B (float): Valeur de la barrière.\n", " K (float): Prix d'exercice de l'option.\n", - " \n", + "\n", " Retourne:\n", " float: Valeur du payoff de l'option.\n", " \"\"\"\n", @@ -390,7 +409,13 @@ ], "source": [ "N_trajectories = 1000\n", - "trajectories = [(t, X) for (t, X) in [euler_maruyama(mu=r, sigma=sigma, T=T, N=1000, X0=S0) for _ in range(N_trajectories)]]\n", + "trajectories = [\n", + " (t, X)\n", + " for (t, X) in [\n", + " euler_maruyama(mu=r, sigma=sigma, T=T, N=1000, X0=S0)\n", + " for _ in range(N_trajectories)\n", + " ]\n", + "]\n", "plt.figure(figsize=(10, 6))\n", "plot_browniens(trajectories, B=B)\n", "plt.show()\n", @@ -431,28 +456,35 @@ "\n", "np.random.seed(333)\n", "\n", + "\n", "def plot_payoff_errors():\n", " \"\"\"Trace l'erreur de convergence du payoff actualisé en fonction de N.\"\"\"\n", " errors = []\n", - " \n", + "\n", " for N in N_list:\n", - " trajectories = [(t, X) for (t, X) in [euler_maruyama(mu=r, sigma=sigma, T=T, N=N, X0=S0) for _ in range(N_trajectories)]]\n", + " trajectories = [\n", + " (t, X)\n", + " for (t, X) in [\n", + " euler_maruyama(mu=r, sigma=sigma, T=T, N=N, X0=S0)\n", + " for _ in range(N_trajectories)\n", + " ]\n", + " ]\n", " payoff_BS = compute_payoff_BS()\n", " payoffs = compute_payoff(trajectories, B, K)\n", - " \n", + "\n", " errors.append(np.max(np.abs(payoffs - payoff_BS)))\n", - " \n", - " \n", - " plt.plot(np.log(N_list), np.log(errors), 'o-', label='Erreur numérique')\n", - " plt.plot(np.log(N_list), 0.5 * np.log(N_list), '--', label='Ordre 1/2')\n", - " plt.plot(np.log(N_list), np.log(N_list), '--', label='Ordre 1')\n", - " plt.plot(np.log(N_list), 2*np.log(N_list), '--', label='Ordre 2')\n", - " plt.xlabel('log(h)')\n", - " plt.ylabel('log(Erreur)')\n", - " plt.title('Convergence de l\\'erreur du payoff actualisé')\n", + "\n", + " plt.plot(np.log(N_list), np.log(errors), \"o-\", label=\"Erreur numérique\")\n", + " plt.plot(np.log(N_list), 0.5 * np.log(N_list), \"--\", label=\"Ordre 1/2\")\n", + " plt.plot(np.log(N_list), np.log(N_list), \"--\", label=\"Ordre 1\")\n", + " plt.plot(np.log(N_list), 2 * np.log(N_list), \"--\", label=\"Ordre 2\")\n", + " plt.xlabel(\"log(h)\")\n", + " plt.ylabel(\"log(Erreur)\")\n", + " plt.title(\"Convergence de l'erreur du payoff actualisé\")\n", " plt.legend()\n", " plt.grid(True)\n", "\n", + "\n", "plt.figure(figsize=(10, 5))\n", "plot_payoff_errors()\n", "plt.show()" diff --git a/M1/Numerical Methods/TP_DANJOU_Arthur.ipynb b/M1/Numerical Methods/TP_DANJOU_Arthur.ipynb index 1d74d4c..13e99e1 100644 --- a/M1/Numerical Methods/TP_DANJOU_Arthur.ipynb +++ b/M1/Numerical Methods/TP_DANJOU_Arthur.ipynb @@ -28,8 +28,9 @@ "k = np.arange(1, 12 + 1)\n", "m = np.power(2, k)\n", "\n", + "\n", "def f(x):\n", - "\treturn 1 / np.sqrt(x)" + " return 1 / np.sqrt(x)" ] }, { @@ -39,19 +40,23 @@ "outputs": [], "source": [ "a, b = 1, 2\n", + "\n", + "\n", "def compute_I(f, a, b, m):\n", " h_list = (b - a) / m\n", " I = []\n", " errors = []\n", " sol_exact = quad(f, a, b)[0]\n", - " \n", + "\n", " for h in h_list:\n", " t = np.arange(a, b, h)\n", - " y = np.array([3/4 * h * f(t[i] + h/3) + h/4 * f(t[i] + h) for i in range(len(t))])\n", + " y = np.array(\n", + " [3 / 4 * h * f(t[i] + h / 3) + h / 4 * f(t[i] + h) for i in range(len(t))]\n", + " )\n", " I_approx = np.sum(y)\n", " I.append(I_approx)\n", " errors.append(np.abs(I_approx - sol_exact))\n", - " \n", + "\n", " return I, h_list, errors" ] }, @@ -84,12 +89,12 @@ "print(f\"I1 = {I1}\")\n", "\n", "plt.figure(figsize=(10, 5))\n", - "plt.plot(np.log(h_list), np.log(errors1), 'o-', label='Erreur numérique')\n", - "plt.plot(np.log(h_list), 2*np.log(h_list), '--', label='Ordre 2')\n", - "plt.plot(np.log(h_list), 4*np.log(h_list), '--', label='Ordre 4')\n", - "plt.xlabel('log(h)')\n", - "plt.ylabel('log(Erreur)')\n", - "plt.title('Convergence de la méthode d\\'intégration')\n", + "plt.plot(np.log(h_list), np.log(errors1), \"o-\", label=\"Erreur numérique\")\n", + "plt.plot(np.log(h_list), 2 * np.log(h_list), \"--\", label=\"Ordre 2\")\n", + "plt.plot(np.log(h_list), 4 * np.log(h_list), \"--\", label=\"Ordre 4\")\n", + "plt.xlabel(\"log(h)\")\n", + "plt.ylabel(\"log(Erreur)\")\n", + "plt.title(\"Convergence de la méthode d'intégration\")\n", "plt.legend()\n", "plt.grid(True)\n", "plt.show()" @@ -116,12 +121,12 @@ "I2, h_list, errors2 = compute_I(f, a, b, m)\n", "\n", "plt.figure(figsize=(10, 5))\n", - "plt.plot(np.log(h_list), np.log(errors2), label='Approximation de l\\'intégrale')\n", - "plt.plot(np.log(h_list), np.log(h_list), '--', label='h')\n", - "plt.plot(np.log(h_list), 2*np.log(h_list), '--', label='h^2')\n", - "plt.xlabel('h')\n", - "plt.ylabel('Approximation de l\\'intégrale')\n", - "plt.title('Approximation de l\\'intégrale par la méthode de Simpson')\n", + "plt.plot(np.log(h_list), np.log(errors2), label=\"Approximation de l'intégrale\")\n", + "plt.plot(np.log(h_list), np.log(h_list), \"--\", label=\"h\")\n", + "plt.plot(np.log(h_list), 2 * np.log(h_list), \"--\", label=\"h^2\")\n", + "plt.xlabel(\"h\")\n", + "plt.ylabel(\"Approximation de l'intégrale\")\n", + "plt.title(\"Approximation de l'intégrale par la méthode de Simpson\")\n", "plt.legend()\n", "plt.show()" ] @@ -146,19 +151,19 @@ "metadata": {}, "outputs": [], "source": [ - "def RKI(f, y0, vt, tol = 1e-6, itmax = 20):\n", - "\tN, T = len(vt), vt[-1]\n", - "\tyn = np.zeros((len(y0), N))\n", - "\tyn[:, 0] = y0\n", - "\th = T / N\n", + "def RKI(f, y0, vt, tol=1e-6, itmax=20):\n", + " N, T = len(vt), vt[-1]\n", + " yn = np.zeros((len(y0), N))\n", + " yn[:, 0] = y0\n", + " h = T / N\n", "\n", - "\tfor n in range(N-1):\n", - "\t\tp1 = f(vt[n], yn[:, n])\n", - "\t\tF1 = lambda p2: f(vt[n] + h/3, yn[:, n] + h/6 * (p1 + p2)) - p2\n", - "\t\tp2 = newton(F1, yn[:, n], fprime=None, tol=tol, maxiter=itmax)\n", - "\t\tF2 = lambda yn1: yn[:, n] + h/4 * (3 * p2 + f(vt[n+1], yn1)) - yn1\n", - "\t\tyn[:, n + 1] = newton(F2, yn[:, n], fprime=None, tol=tol, maxiter=itmax)\n", - "\treturn yn" + " for n in range(N - 1):\n", + " p1 = f(vt[n], yn[:, n])\n", + " F1 = lambda p2: f(vt[n] + h / 3, yn[:, n] + h / 6 * (p1 + p2)) - p2\n", + " p2 = newton(F1, yn[:, n], fprime=None, tol=tol, maxiter=itmax)\n", + " F2 = lambda yn1: yn[:, n] + h / 4 * (3 * p2 + f(vt[n + 1], yn1)) - yn1\n", + " yn[:, n + 1] = newton(F2, yn[:, n], fprime=None, tol=tol, maxiter=itmax)\n", + " return yn" ] }, { @@ -194,14 +199,18 @@ "source": [ "a, b = [0, 2]\n", "\n", + "\n", "def f(t, y):\n", " return t * np.power(y, 3) - t * y\n", - " \n", + "\n", + "\n", "y0 = [0.5]\n", "\n", + "\n", "def sol_exact(t):\n", " return 1 / np.sqrt(1 + 3 * np.exp(np.power(t, 2)))\n", "\n", + "\n", "x_fine = np.linspace(a, b, 1000)\n", "y_fine = sol_exact(x_fine)\n", "\n", @@ -212,13 +221,13 @@ "y_exact_interp = np.interp(vt, x_fine, y_fine)\n", "\n", "plt.figure(figsize=(10, 5))\n", - "plt.plot(x_fine, y_fine, label='Solution exacte')\n", - "plt.scatter(vt, y, label='Solution numérique', color='red')\n", + "plt.plot(x_fine, y_fine, label=\"Solution exacte\")\n", + "plt.scatter(vt, y, label=\"Solution numérique\", color=\"red\")\n", "plt.legend()\n", "plt.show()\n", "\n", "error = np.max(np.abs(y - y_exact_interp))\n", - "print(f\"Error with h={h}: {error}\")\n" + "print(f\"Error with h={h}: {error}\")" ] }, { @@ -246,7 +255,7 @@ ], "source": [ "k = np.arange(1, 10 + 1)\n", - "h_list = 1/np.power(2, k)\n", + "h_list = 1 / np.power(2, k)\n", "\n", "errors = []\n", "for h in h_list:\n", @@ -258,14 +267,14 @@ "log_h = np.log(h_list)\n", "log_errors = np.log(errors)\n", "order = np.polyfit(log_h, log_errors, 1)[0]\n", - " \n", + "\n", "plt.figure(figsize=(10, 5))\n", - "plt.plot(log_h, log_errors, 'o-', label=f'Erreur (ordre {order:.2f})')\n", - "plt.plot(log_h, log_h, '--', label='h')\n", - "plt.plot(log_h, 2*log_h, '--', label='h^2')\n", - "plt.plot(log_h, 4*log_h, '--', label='h^4')\n", - "plt.xlabel('log(h)')\n", - "plt.ylabel('log(error)')\n", + "plt.plot(log_h, log_errors, \"o-\", label=f\"Erreur (ordre {order:.2f})\")\n", + "plt.plot(log_h, log_h, \"--\", label=\"h\")\n", + "plt.plot(log_h, 2 * log_h, \"--\", label=\"h^2\")\n", + "plt.plot(log_h, 4 * log_h, \"--\", label=\"h^4\")\n", + "plt.xlabel(\"log(h)\")\n", + "plt.ylabel(\"log(error)\")\n", "plt.legend()\n", "plt.grid(True)\n", "plt.show()\n", @@ -306,11 +315,14 @@ "source": [ "def F(t, Y):\n", " x, y, z = Y\n", - " return np.array([\n", - " 1 + np.power(x, 2) * y - (z + 1) * x,\n", - " x * z - np.power(x, 2) * y,\n", - " - x * z + 1.45\n", - " ])\n", + " return np.array(\n", + " [\n", + " 1 + np.power(x, 2) * y - (z + 1) * x,\n", + " x * z - np.power(x, 2) * y,\n", + " -x * z + 1.45,\n", + " ]\n", + " )\n", + "\n", "\n", "h = 0.025\n", "y0 = np.array([1, 1, 1])\n", @@ -320,20 +332,20 @@ "y = RKI(F, y0, t)\n", "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(15, 5))\n", "\n", - "ax1.scatter(y[0], y[1], label='Solution numérique', color='red')\n", - "ax1.plot(sol_exact[:, 0], sol_exact[:, 1], label='Solution exacte', color='blue')\n", + "ax1.scatter(y[0], y[1], label=\"Solution numérique\", color=\"red\")\n", + "ax1.plot(sol_exact[:, 0], sol_exact[:, 1], label=\"Solution exacte\", color=\"blue\")\n", "ax1.legend()\n", - "ax1.set_title('x vs y')\n", + "ax1.set_title(\"x vs y\")\n", "\n", - "ax2.scatter(y[1], y[2], label='Solution numérique', color='red')\n", - "ax2.plot(sol_exact[:, 1], sol_exact[:, 2], label='Solution exacte', color='blue')\n", + "ax2.scatter(y[1], y[2], label=\"Solution numérique\", color=\"red\")\n", + "ax2.plot(sol_exact[:, 1], sol_exact[:, 2], label=\"Solution exacte\", color=\"blue\")\n", "ax2.legend()\n", - "ax2.set_title('y vs z')\n", + "ax2.set_title(\"y vs z\")\n", "\n", - "ax3.scatter(y[0], y[2], label='Solution numérique', color='red')\n", - "ax3.plot(sol_exact[:, 0], sol_exact[:, 2], label='Solution exacte', color='blue')\n", + "ax3.scatter(y[0], y[2], label=\"Solution numérique\", color=\"red\")\n", + "ax3.plot(sol_exact[:, 0], sol_exact[:, 2], label=\"Solution exacte\", color=\"blue\")\n", "ax3.legend()\n", - "ax3.set_title('x vs z')\n", + "ax3.set_title(\"x vs z\")\n", "\n", "plt.tight_layout()\n", "plt.show()" @@ -357,14 +369,15 @@ ], "source": [ "def R(z):\n", - " return (1 + 3/4 * z * (1 + z/6)/(1 - z/6)) / (1 - z/4)\n", + " return (1 + 3 / 4 * z * (1 + z / 6) / (1 - z / 6)) / (1 - z / 4)\n", + "\n", "\n", "x = np.linspace(-15, 5, 100)\n", "y = np.linspace(-7.5, 7.5, 100)\n", "X, Y = np.meshgrid(x, y)\n", - "Z = R(X + 1j*Y)\n", + "Z = R(X + 1j * Y)\n", "plt.figure(figsize=(10, 7))\n", - "plt.contour(X, Y, np.abs(Z), levels=[1], cmap='rainbow')\n", + "plt.contour(X, Y, np.abs(Z), levels=[1], cmap=\"rainbow\")\n", "plt.grid()\n", "plt.show()" ] diff --git a/M1/Numerical Optimisation/ComputerSession1.ipynb b/M1/Numerical Optimisation/ComputerSession1.ipynb index 131b49e..75c9485 100644 --- a/M1/Numerical Optimisation/ComputerSession1.ipynb +++ b/M1/Numerical Optimisation/ComputerSession1.ipynb @@ -16,18 +16,18 @@ }, { "cell_type": "code", + "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:16:34.054857Z", "start_time": "2025-02-18T16:16:33.430974Z" } }, + "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt" - ], - "outputs": [], - "execution_count": 2 + ] }, { "cell_type": "markdown", @@ -47,17 +47,14 @@ ] }, { + "cell_type": "code", + "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:16:34.991206Z", "start_time": "2025-02-18T16:16:34.987118Z" } }, - "cell_type": "code", - "source": [ - "A = np.array([[4, 6, -2, 3], [2, -1, 0, 1], [-7, 0, 1, 12]])\n", - "print(A)" - ], "outputs": [ { "name": "stdout", @@ -69,7 +66,10 @@ ] } ], - "execution_count": 3 + "source": [ + "A = np.array([[4, 6, -2, 3], [2, -1, 0, 1], [-7, 0, 1, 12]])\n", + "print(A)" + ] }, { "cell_type": "markdown", @@ -79,17 +79,14 @@ ] }, { + "cell_type": "code", + "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:16:35.419774Z", "start_time": "2025-02-18T16:16:35.416576Z" } }, - "cell_type": "code", - "source": [ - "print(A[0,])\n", - "print(A[:, 1])" - ], "outputs": [ { "name": "stdout", @@ -100,7 +97,10 @@ ] } ], - "execution_count": 4 + "source": [ + "print(A[0,])\n", + "print(A[:, 1])" + ] }, { "cell_type": "markdown", @@ -111,20 +111,14 @@ ] }, { + "cell_type": "code", + "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:16:35.744187Z", "start_time": "2025-02-18T16:16:35.737424Z" } }, - "cell_type": "code", - "source": [ - "Ac = A.copy().astype(float)\n", - "Ac[0,] = 2 * Ac[0,]\n", - "Ac[1,] = 2 * Ac[1,]\n", - "Ac[:, 3] = Ac[:, 3] / 3\n", - "print(Ac)" - ], "outputs": [ { "name": "stdout", @@ -136,7 +130,13 @@ ] } ], - "execution_count": 5 + "source": [ + "Ac = A.copy().astype(float)\n", + "Ac[0,] = 2 * Ac[0,]\n", + "Ac[1,] = 2 * Ac[1,]\n", + "Ac[:, 3] = Ac[:, 3] / 3\n", + "print(Ac)" + ] }, { "cell_type": "markdown", @@ -147,17 +147,14 @@ ] }, { + "cell_type": "code", + "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:16:36.073319Z", "start_time": "2025-02-18T16:16:36.070480Z" } }, - "cell_type": "code", - "source": [ - "B = np.array([[4, 5, 6], [5, 10, 15], [1, 1, 1]])\n", - "print(B)" - ], "outputs": [ { "name": "stdout", @@ -169,7 +166,10 @@ ] } ], - "execution_count": 6 + "source": [ + "B = np.array([[4, 5, 6], [5, 10, 15], [1, 1, 1]])\n", + "print(B)" + ] }, { "cell_type": "markdown", @@ -180,17 +180,14 @@ ] }, { + "cell_type": "code", + "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:16:36.494442Z", "start_time": "2025-02-18T16:16:36.491672Z" } }, - "cell_type": "code", - "source": [ - "C = A.copy()[:3, :3]\n", - "print(C)" - ], "outputs": [ { "name": "stdout", @@ -202,7 +199,10 @@ ] } ], - "execution_count": 7 + "source": [ + "C = A.copy()[:3, :3]\n", + "print(C)" + ] }, { "cell_type": "markdown", @@ -215,20 +215,14 @@ ] }, { + "cell_type": "code", + "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:16:37.059366Z", "start_time": "2025-02-18T16:16:37.055617Z" } }, - "cell_type": "code", - "source": [ - "D = B.dot(A)\n", - "print(D)\n", - "\n", - "E = B * C\n", - "print(E)" - ], "outputs": [ { "name": "stdout", @@ -243,7 +237,13 @@ ] } ], - "execution_count": 8 + "source": [ + "D = B.dot(A)\n", + "print(D)\n", + "\n", + "E = B * C\n", + "print(E)" + ] }, { "cell_type": "markdown", @@ -255,18 +255,14 @@ ] }, { + "cell_type": "code", + "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:16:37.430599Z", "start_time": "2025-02-18T16:16:37.427671Z" } }, - "cell_type": "code", - "source": [ - "print(np.sum(E))\n", - "Y = np.sum(D, axis=1)\n", - "print(Y)" - ], "outputs": [ { "name": "stdout", @@ -277,7 +273,11 @@ ] } ], - "execution_count": 9 + "source": [ + "print(np.sum(E))\n", + "Y = np.sum(D, axis=1)\n", + "print(Y)" + ] }, { "cell_type": "markdown", @@ -312,23 +312,14 @@ ] }, { + "cell_type": "code", + "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:16:37.862027Z", "start_time": "2025-02-18T16:16:37.763126Z" } }, - "cell_type": "code", - "source": [ - "def f(x):\n", - " return x ** 2 * np.cos(10 * x)\n", - "\n", - "\n", - "xx = np.linspace(-np.pi, np.pi, 1000)\n", - "\n", - "plt.plot(xx, f(xx), color='green')\n", - "plt.axis('equal')" - ], "outputs": [ { "data": { @@ -345,16 +336,25 @@ }, { "data": { + "image/png": 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", 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" + ] }, "metadata": {}, "output_type": "display_data" } ], - "execution_count": 10 + "source": [ + "def f(x):\n", + " return x**2 * np.cos(10 * x)\n", + "\n", + "\n", + "xx = np.linspace(-np.pi, np.pi, 1000)\n", + "\n", + "plt.plot(xx, f(xx), color=\"green\")\n", + "plt.axis(\"equal\")" + ] }, { "cell_type": "markdown", @@ -367,39 +367,39 @@ ] }, { + "cell_type": "code", + "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:16:38.611125Z", "start_time": "2025-02-18T16:16:38.445164Z" } }, - "cell_type": "code", + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def g(x, n):\n", - " return x ** 2 * np.cos(x * n)\n", + " return x**2 * np.cos(x * n)\n", "\n", "\n", "xx = np.linspace(-np.pi, np.pi, 1000)\n", "nn = np.arange(0, 11, 1)\n", "for N in nn:\n", " plt.plot(xx, g(xx, N), label=f\"n = {N}\")\n", - "plt.plot(xx, f(xx), color='black')\n", + "plt.plot(xx, f(xx), color=\"black\")\n", "plt.legend()\n", "plt.show()" - ], - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ], - "image/png": 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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 11 + ] }, { "cell_type": "markdown", @@ -427,38 +427,38 @@ ] }, { + "cell_type": "code", + "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:16:39.454689Z", "start_time": "2025-02-18T16:16:39.302487Z" } }, - "cell_type": "code", - "source": [ - "def f(x, y):\n", - " return np.exp(-x ** 2) * np.sin(np.pi * x - y)\n", - "\n", - "\n", - "bound = np.linspace(-4, 4, 100)\n", - "Z = [[f(x, y) for x in bound] for y in bound]\n", - "\n", - "plt.contour(bound, bound, Z, 20, cmap='inferno')\n", - "plt.colorbar()\n", - "plt.show()" - ], "outputs": [ { "data": { + "image/png": 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", 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" + ] }, "metadata": {}, "output_type": "display_data" } ], - "execution_count": 12 + "source": [ + "def f(x, y):\n", + " return np.exp(-(x**2)) * np.sin(np.pi * x - y)\n", + "\n", + "\n", + "bound = np.linspace(-4, 4, 100)\n", + "Z = [[f(x, y) for x in bound] for y in bound]\n", + "\n", + "plt.contour(bound, bound, Z, 20, cmap=\"inferno\")\n", + "plt.colorbar()\n", + "plt.show()" + ] }, { "cell_type": "markdown", @@ -486,19 +486,19 @@ ] }, { + "cell_type": "code", + "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:16:42.719040Z", "start_time": "2025-02-18T16:16:42.715677Z" } }, - "cell_type": "code", + "outputs": [], "source": [ "def f(A, b, x):\n", " return 1 / 2 * np.dot(A, x).dot(x) - b.dot(x)" - ], - "outputs": [], - "execution_count": 13 + ] }, { "cell_type": "markdown", @@ -512,13 +512,44 @@ ] }, { + "cell_type": "code", + "execution_count": 16, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:17:09.781325Z", "start_time": "2025-02-18T16:17:09.636938Z" } }, - "cell_type": "code", + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/tp/_ld5_pzs6nx6mv1pbjhq1l740000gn/T/ipykernel_32447/1819267217.py:28: RuntimeWarning: divide by zero encountered in log\n", + " plt.plot(np.log(np.linalg.norm(xk - x_star, axis=1)), 'blue')\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "d = 2\n", "M = np.random.rand(d, d)\n", @@ -540,47 +571,16 @@ "\n", "\n", "xk, k_list, x_star = GD(x0, tau, n_iter)\n", - "plt.plot([f(A, b, x) for x in xk], 'red')\n", - "plt.scatter(n_iter, f(A, b, np.linalg.solve(A, b)), c='blue')\n", - "plt.xlabel('Iteration')\n", - "plt.ylabel('Function value')\n", - "plt.title('Convergence of Gradient Descent')\n", + "plt.plot([f(A, b, x) for x in xk], \"red\")\n", + "plt.scatter(n_iter, f(A, b, np.linalg.solve(A, b)), c=\"blue\")\n", + "plt.xlabel(\"Iteration\")\n", + "plt.ylabel(\"Function value\")\n", + "plt.title(\"Convergence of Gradient Descent\")\n", "plt.show()\n", "\n", - "plt.plot(np.log(np.linalg.norm(xk - x_star, axis=1)), 'blue')\n", + "plt.plot(np.log(np.linalg.norm(xk - x_star, axis=1)), \"blue\")\n", "plt.show()" - ], - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ], - "image/png": 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" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/tp/_ld5_pzs6nx6mv1pbjhq1l740000gn/T/ipykernel_32447/1819267217.py:28: RuntimeWarning: divide by zero encountered in log\n", - " plt.plot(np.log(np.linalg.norm(xk - x_star, axis=1)), 'blue')\n" - ] - }, - { - "data": { - "text/plain": [ - "
" - ], - "image/png": 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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 16 + ] }, { "cell_type": "markdown", @@ -591,42 +591,41 @@ ] }, { + "cell_type": "code", + "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2025-02-18T16:17:12.752200Z", "start_time": "2025-02-18T16:17:12.592610Z" } }, - "cell_type": "code", - "source": [ - "lim_inf, lim_sup = -5, 5\n", - "X = Y = np.linspace(lim_inf, lim_sup, 100)\n", - "xx, yy = np.meshgrid(X, Y)\n", - "Z = np.array(\n", - " [[f(A, b, np.array([x, y])) for x in X] for y in Y])\n", - "\n", - "plt.contour(xx, yy, Z, levels=10, cmap='inferno')\n", - "plt.colorbar()\n", - "plt.plot(xk[:, 0], xk[:, 1], 'red')\n", - "plt.scatter(x_star[0], x_star[1], c='blue')\n", - "plt.xlabel('x1')\n", - "plt.ylabel('x2')\n", - "plt.title('Level Sets and Gradient Descent Path')\n", - "plt.show()" - ], "outputs": [ { "data": { + "image/png": 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", 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" + ] }, "metadata": {}, "output_type": "display_data" } ], - "execution_count": 17 + "source": [ + "lim_inf, lim_sup = -5, 5\n", + "X = Y = np.linspace(lim_inf, lim_sup, 100)\n", + "xx, yy = np.meshgrid(X, Y)\n", + "Z = np.array([[f(A, b, np.array([x, y])) for x in X] for y in Y])\n", + "\n", + "plt.contour(xx, yy, Z, levels=10, cmap=\"inferno\")\n", + "plt.colorbar()\n", + "plt.plot(xk[:, 0], xk[:, 1], \"red\")\n", + "plt.scatter(x_star[0], x_star[1], c=\"blue\")\n", + "plt.xlabel(\"x1\")\n", + "plt.ylabel(\"x2\")\n", + "plt.title(\"Level Sets and Gradient Descent Path\")\n", + "plt.show()" + ] }, { "cell_type": "markdown", @@ -650,12 +649,22 @@ }, { "cell_type": "code", + "execution_count": 240, "metadata": { "ExecuteTime": { "end_time": "2025-02-04T18:12:28.620072Z", "start_time": "2025-02-04T18:12:28.615982Z" } }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[2. 2.]\n" + ] + } + ], "source": [ "import numpy as np\n", "\n", @@ -669,21 +678,16 @@ "\n", "\n", "def gradient(F, x, d, delta=1e-05):\n", - " return np.array([(F(x + delta * e(i, d)) - F(x - delta * e(i, d))) / (2 * delta) for i in range(d)])\n", + " return np.array(\n", + " [\n", + " (F(x + delta * e(i, d)) - F(x - delta * e(i, d))) / (2 * delta)\n", + " for i in range(d)\n", + " ]\n", + " )\n", "\n", "\n", "print(gradient(F, np.array([1, 1]), 2))" - ], - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[2. 2.]\n" - ] - } - ], - "execution_count": 240 + ] }, { "cell_type": "markdown", @@ -695,13 +699,23 @@ ] }, { + "cell_type": "code", + "execution_count": 224, "metadata": { "ExecuteTime": { "end_time": "2025-02-04T17:55:42.711021Z", "start_time": "2025-02-04T17:55:42.705568Z" } }, - "cell_type": "code", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[array([1, 1]), array([0.8, 0.8]), array([0.64, 0.64]), array([0.512, 0.512]), array([0.4096, 0.4096]), array([0.32768, 0.32768]), array([0.262144, 0.262144]), array([0.2097152, 0.2097152]), array([0.16777216, 0.16777216]), array([0.13421773, 0.13421773]), array([0.10737418, 0.10737418]), array([0.08589935, 0.08589935]), array([0.06871948, 0.06871948]), array([0.05497558, 0.05497558]), array([0.04398047, 0.04398047]), array([0.03518437, 0.03518437]), array([0.0281475, 0.0281475]), array([0.022518, 0.022518]), array([0.0180144, 0.0180144]), array([0.01441152, 0.01441152]), array([0.01152922, 0.01152922]), array([0.00922337, 0.00922337]), array([0.0073787, 0.0073787]), array([0.00590296, 0.00590296]), array([0.00472237, 0.00472237]), array([0.00377789, 0.00377789]), array([0.00302231, 0.00302231]), array([0.00241785, 0.00241785]), array([0.00193428, 0.00193428]), array([0.00154743, 0.00154743]), array([0.00123794, 0.00123794]), array([0.00099035, 0.00099035]), array([0.00079228, 0.00079228]), array([0.00063383, 0.00063383]), array([0.00050706, 0.00050706]), array([0.00040565, 0.00040565]), array([0.00032452, 0.00032452]), array([0.00025961, 0.00025961]), array([0.00020769, 0.00020769]), array([0.00016615, 0.00016615]), array([0.00013292, 0.00013292]), array([0.00010634, 0.00010634]), array([8.50705917e-05, 8.50705917e-05]), array([6.80564734e-05, 6.80564734e-05]), array([5.44451787e-05, 5.44451787e-05]), array([4.3556143e-05, 4.3556143e-05]), array([3.48449144e-05, 3.48449144e-05]), array([2.78759315e-05, 2.78759315e-05]), array([2.23007452e-05, 2.23007452e-05]), array([1.78405962e-05, 1.78405962e-05]), array([1.42724769e-05, 1.42724769e-05]), array([1.14179815e-05, 1.14179815e-05]), array([9.13438523e-06, 9.13438523e-06]), array([7.30750819e-06, 7.30750819e-06]), array([5.84600655e-06, 5.84600655e-06]), array([4.67680524e-06, 4.67680524e-06]), array([3.74144419e-06, 3.74144419e-06]), array([2.99315535e-06, 2.99315535e-06]), array([2.39452428e-06, 2.39452428e-06]), array([1.91561943e-06, 1.91561943e-06]), array([1.53249554e-06, 1.53249554e-06]), array([1.22599643e-06, 1.22599643e-06]), array([9.80797146e-07, 9.80797146e-07]), array([7.84637717e-07, 7.84637717e-07]), array([6.27710174e-07, 6.27710174e-07]), array([5.02168139e-07, 5.02168139e-07]), array([4.01734511e-07, 4.01734511e-07]), array([3.21387609e-07, 3.21387609e-07]), array([2.57110087e-07, 2.57110087e-07]), array([2.0568807e-07, 2.0568807e-07]), array([1.64550456e-07, 1.64550456e-07]), array([1.31640365e-07, 1.31640365e-07]), array([1.05312292e-07, 1.05312292e-07]), array([8.42498333e-08, 8.42498333e-08]), array([6.73998667e-08, 6.73998667e-08]), array([5.39198933e-08, 5.39198933e-08]), array([4.31359147e-08, 4.31359147e-08]), array([3.45087317e-08, 3.45087317e-08]), array([2.76069854e-08, 2.76069854e-08]), array([2.20855883e-08, 2.20855883e-08]), array([1.76684706e-08, 1.76684706e-08]), array([1.41347765e-08, 1.41347765e-08]), array([1.13078212e-08, 1.13078212e-08]), array([9.04625697e-09, 9.04625697e-09]), array([7.23700558e-09, 7.23700558e-09]), array([5.78960446e-09, 5.78960446e-09]), array([4.63168357e-09, 4.63168357e-09]), array([3.70534686e-09, 3.70534686e-09]), array([2.96427748e-09, 2.96427748e-09]), array([2.37142199e-09, 2.37142199e-09]), array([1.89713759e-09, 1.89713759e-09]), array([1.51771007e-09, 1.51771007e-09]), array([1.21416806e-09, 1.21416806e-09]), array([9.71334446e-10, 9.71334446e-10]), array([7.77067557e-10, 7.77067557e-10]), array([6.21654046e-10, 6.21654046e-10]), array([4.97323236e-10, 4.97323236e-10]), array([3.97858589e-10, 3.97858589e-10]), array([3.18286871e-10, 3.18286871e-10]), array([2.54629497e-10, 2.54629497e-10]), array([2.03703598e-10, 2.03703598e-10])]\n" + ] + } + ], "source": [ "def gradient_algo(x0, tau, n_iter, F, d):\n", " x = x0\n", @@ -713,17 +727,7 @@ "\n", "\n", "print(gradient_algo(np.array([1, 1]), 0.1, 100, F, 2))" - ], - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[array([1, 1]), array([0.8, 0.8]), array([0.64, 0.64]), array([0.512, 0.512]), array([0.4096, 0.4096]), array([0.32768, 0.32768]), array([0.262144, 0.262144]), array([0.2097152, 0.2097152]), array([0.16777216, 0.16777216]), array([0.13421773, 0.13421773]), array([0.10737418, 0.10737418]), array([0.08589935, 0.08589935]), array([0.06871948, 0.06871948]), array([0.05497558, 0.05497558]), array([0.04398047, 0.04398047]), array([0.03518437, 0.03518437]), array([0.0281475, 0.0281475]), array([0.022518, 0.022518]), array([0.0180144, 0.0180144]), array([0.01441152, 0.01441152]), array([0.01152922, 0.01152922]), array([0.00922337, 0.00922337]), array([0.0073787, 0.0073787]), array([0.00590296, 0.00590296]), array([0.00472237, 0.00472237]), array([0.00377789, 0.00377789]), array([0.00302231, 0.00302231]), array([0.00241785, 0.00241785]), array([0.00193428, 0.00193428]), array([0.00154743, 0.00154743]), array([0.00123794, 0.00123794]), array([0.00099035, 0.00099035]), array([0.00079228, 0.00079228]), array([0.00063383, 0.00063383]), array([0.00050706, 0.00050706]), array([0.00040565, 0.00040565]), array([0.00032452, 0.00032452]), array([0.00025961, 0.00025961]), array([0.00020769, 0.00020769]), array([0.00016615, 0.00016615]), array([0.00013292, 0.00013292]), array([0.00010634, 0.00010634]), array([8.50705917e-05, 8.50705917e-05]), array([6.80564734e-05, 6.80564734e-05]), array([5.44451787e-05, 5.44451787e-05]), array([4.3556143e-05, 4.3556143e-05]), array([3.48449144e-05, 3.48449144e-05]), array([2.78759315e-05, 2.78759315e-05]), array([2.23007452e-05, 2.23007452e-05]), array([1.78405962e-05, 1.78405962e-05]), array([1.42724769e-05, 1.42724769e-05]), array([1.14179815e-05, 1.14179815e-05]), array([9.13438523e-06, 9.13438523e-06]), array([7.30750819e-06, 7.30750819e-06]), array([5.84600655e-06, 5.84600655e-06]), array([4.67680524e-06, 4.67680524e-06]), array([3.74144419e-06, 3.74144419e-06]), array([2.99315535e-06, 2.99315535e-06]), array([2.39452428e-06, 2.39452428e-06]), array([1.91561943e-06, 1.91561943e-06]), array([1.53249554e-06, 1.53249554e-06]), array([1.22599643e-06, 1.22599643e-06]), array([9.80797146e-07, 9.80797146e-07]), array([7.84637717e-07, 7.84637717e-07]), array([6.27710174e-07, 6.27710174e-07]), array([5.02168139e-07, 5.02168139e-07]), array([4.01734511e-07, 4.01734511e-07]), array([3.21387609e-07, 3.21387609e-07]), array([2.57110087e-07, 2.57110087e-07]), array([2.0568807e-07, 2.0568807e-07]), array([1.64550456e-07, 1.64550456e-07]), array([1.31640365e-07, 1.31640365e-07]), array([1.05312292e-07, 1.05312292e-07]), array([8.42498333e-08, 8.42498333e-08]), array([6.73998667e-08, 6.73998667e-08]), array([5.39198933e-08, 5.39198933e-08]), array([4.31359147e-08, 4.31359147e-08]), array([3.45087317e-08, 3.45087317e-08]), array([2.76069854e-08, 2.76069854e-08]), array([2.20855883e-08, 2.20855883e-08]), array([1.76684706e-08, 1.76684706e-08]), array([1.41347765e-08, 1.41347765e-08]), array([1.13078212e-08, 1.13078212e-08]), array([9.04625697e-09, 9.04625697e-09]), array([7.23700558e-09, 7.23700558e-09]), array([5.78960446e-09, 5.78960446e-09]), array([4.63168357e-09, 4.63168357e-09]), array([3.70534686e-09, 3.70534686e-09]), array([2.96427748e-09, 2.96427748e-09]), array([2.37142199e-09, 2.37142199e-09]), array([1.89713759e-09, 1.89713759e-09]), array([1.51771007e-09, 1.51771007e-09]), array([1.21416806e-09, 1.21416806e-09]), array([9.71334446e-10, 9.71334446e-10]), array([7.77067557e-10, 7.77067557e-10]), array([6.21654046e-10, 6.21654046e-10]), array([4.97323236e-10, 4.97323236e-10]), array([3.97858589e-10, 3.97858589e-10]), array([3.18286871e-10, 3.18286871e-10]), array([2.54629497e-10, 2.54629497e-10]), array([2.03703598e-10, 2.03703598e-10])]\n" - ] - } - ], - "execution_count": 224 + ] }, { "cell_type": "markdown", @@ -750,13 +754,15 @@ ] }, { + "cell_type": "code", + "execution_count": 225, "metadata": { "ExecuteTime": { "end_time": "2025-02-04T17:55:48.068018Z", "start_time": "2025-02-04T17:55:48.065662Z" } }, - "cell_type": "code", + "outputs": [], "source": [ "alpha0 = 3\n", "alpha1 = 2\n", @@ -768,9 +774,7 @@ "\n", "def E(A):\n", " return np.mean(np.abs(Yi - (A[0] + A[1] * Xi)) ** 2)" - ], - "outputs": [], - "execution_count": 225 + ] }, { "cell_type": "markdown", @@ -780,37 +784,37 @@ ] }, { + "cell_type": "code", + "execution_count": 226, "metadata": { "ExecuteTime": { "end_time": "2025-02-04T17:55:53.451076Z", "start_time": "2025-02-04T17:55:53.293559Z" } }, - "cell_type": "code", + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "bound = np.linspace(-10, 10, 100)\n", "Z = [[E(np.array([x, y])) for x in bound] for y in bound]\n", "\n", - "plt.contour(bound, bound, Z, 20, cmap='inferno')\n", - "plt.scatter(x_star[0], x_star[1], c='blue')\n", + "plt.contour(bound, bound, Z, 20, cmap=\"inferno\")\n", + "plt.scatter(x_star[0], x_star[1], c=\"blue\")\n", "plt.colorbar()\n", "plt.show()" - ], - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ], - "image/png": 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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 226 + ] }, { "cell_type": "markdown", @@ -822,36 +826,14 @@ ] }, { + "cell_type": "code", + "execution_count": 232, "metadata": { "ExecuteTime": { "end_time": "2025-02-04T17:57:18.424095Z", "start_time": "2025-02-04T17:57:18.364818Z" } }, - "cell_type": "code", - "source": [ - "tau_list = np.linspace(0.01, 1, 20)\n", - "\n", - "\n", - "def gradient_algo(x0, tau, n_iter, F, d):\n", - " x = x0\n", - " history = [x]\n", - " for _ in range(n_iter):\n", - " x = x - tau * gradient(F, x, d)\n", - " history.append(x)\n", - " return history\n", - "\n", - "\n", - "list_tau_y = []\n", - "for tau in tau_list:\n", - " history = gradient_algo(np.array([2, 3]), tau, 100, E, 2)\n", - " x, y = history[-1]\n", - " list_tau_y.append((tau, y))\n", - " print(f\"tau = {tau}, x = {x}, y = {y}\")\n", - "\n", - "best_tau = max(list_tau_y, key=lambda x: x[1])\n", - "print(best_tau)" - ], "outputs": [ { "name": "stdout", @@ -881,7 +863,29 @@ ] } ], - "execution_count": 232 + "source": [ + "tau_list = np.linspace(0.01, 1, 20)\n", + "\n", + "\n", + "def gradient_algo(x0, tau, n_iter, F, d):\n", + " x = x0\n", + " history = [x]\n", + " for _ in range(n_iter):\n", + " x = x - tau * gradient(F, x, d)\n", + " history.append(x)\n", + " return history\n", + "\n", + "\n", + "list_tau_y = []\n", + "for tau in tau_list:\n", + " history = gradient_algo(np.array([2, 3]), tau, 100, E, 2)\n", + " x, y = history[-1]\n", + " list_tau_y.append((tau, y))\n", + " print(f\"tau = {tau}, x = {x}, y = {y}\")\n", + "\n", + "best_tau = max(list_tau_y, key=lambda x: x[1])\n", + "print(best_tau)" + ] }, { "cell_type": "markdown", @@ -893,35 +897,35 @@ }, { "cell_type": "code", + "execution_count": 231, "metadata": { "ExecuteTime": { "end_time": "2025-02-04T17:57:15.047877Z", "start_time": "2025-02-04T17:57:14.971370Z" } }, - "source": [ - "best_A = gradient_algo(np.array([2, 3]), best_tau[0], 100, E, 2)[-1]\n", - "\n", - "plt.scatter(Xi, Yi, label='Data')\n", - "plt.plot(Xi, best_A[0] + best_A[1] * Xi, color='red', label='Fitted line')\n", - "plt.xlabel('Xi')\n", - "plt.ylabel('Yi')\n", - "plt.legend()\n", - "plt.show()" - ], "outputs": [ { "data": { + "image/png": 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", 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" + ] }, "metadata": {}, "output_type": "display_data" } ], - "execution_count": 231 + "source": [ + "best_A = gradient_algo(np.array([2, 3]), best_tau[0], 100, E, 2)[-1]\n", + "\n", + "plt.scatter(Xi, Yi, label=\"Data\")\n", + "plt.plot(Xi, best_A[0] + best_A[1] * Xi, color=\"red\", label=\"Fitted line\")\n", + "plt.xlabel(\"Xi\")\n", + "plt.ylabel(\"Yi\")\n", + "plt.legend()\n", + "plt.show()" + ] }, { "cell_type": "code", diff --git a/M1/Numerical Optimisation/ComputerSession2.ipynb b/M1/Numerical Optimisation/ComputerSession2.ipynb index 2b2a265..7a6fdc3 100644 --- a/M1/Numerical Optimisation/ComputerSession2.ipynb +++ b/M1/Numerical Optimisation/ComputerSession2.ipynb @@ -308,7 +308,6 @@ } ], "source": [ - "import numpy as np\n", "\n", "u = lambda x: np.sqrt((6 - x) ** 2 + 4)\n", "\n", @@ -364,7 +363,9 @@ "# Run Newton's method\n", "optimal_point_newton, iterations_newton = newton_method(initial_guess_newton)\n", "print(f\"Optimal point (Newton): {optimal_point_newton}\")\n", - "print(f\"Objective function value at optimal point (Newton): {objective_function(optimal_point_newton)}\")\n", + "print(\n", + " f\"Objective function value at optimal point (Newton): {objective_function(optimal_point_newton)}\"\n", + ")\n", "print(f\"Number of iterations (Newton): {iterations_newton}\")\n", "\n", "# Initial interval for dichotomy method\n", @@ -373,7 +374,9 @@ "# Run dichotomy method\n", "optimal_point_dichotomy, iterations_dichotomy = dichotomy_method(aL, aR)\n", "print(f\"Optimal point (Dichotomy): {optimal_point_dichotomy}\")\n", - "print(f\"Objective function value at optimal point (Dichotomy): {objective_function(optimal_point_dichotomy)}\")\n", + "print(\n", + " f\"Objective function value at optimal point (Dichotomy): {objective_function(optimal_point_dichotomy)}\"\n", + ")\n", "print(f\"Number of iterations (Dichotomy): {iterations_dichotomy}\")" ] }, @@ -564,9 +567,7 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": [ - "\n" - ] + "source": [] } ], "metadata": { diff --git a/M1/Numerical Optimisation/ComputerSession3.ipynb b/M1/Numerical Optimisation/ComputerSession3.ipynb index dbd35ad..42c1108 100644 --- a/M1/Numerical Optimisation/ComputerSession3.ipynb +++ b/M1/Numerical Optimisation/ComputerSession3.ipynb @@ -42,20 +42,24 @@ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", + "\n", "def generate_thetas(n):\n", " random_steps = np.random.random(n)\n", - " return np.concatenate(([0], np.cumsum(random_steps / np.sum(random_steps) * (2*np.pi))))\n", + " return np.concatenate(\n", + " ([0], np.cumsum(random_steps / np.sum(random_steps) * (2 * np.pi)))\n", + " )\n", + "\n", "\n", "n = 4\n", "thetas = generate_thetas(n)\n", - "thetas_inf = np.linspace(0, 2*np.pi, 1000)\n", + "thetas_inf = np.linspace(0, 2 * np.pi, 1000)\n", "\n", "plt.figure(figsize=(7, 7))\n", - "plt.plot(np.cos(thetas), np.sin(thetas), label='polygon')\n", - "plt.scatter(np.cos(thetas), np.sin(thetas), color='red', label='vertices')\n", - "plt.plot(np.cos(thetas_inf), np.sin(thetas_inf), 'k--', label='unit circle', alpha=0.5)\n", + "plt.plot(np.cos(thetas), np.sin(thetas), label=\"polygon\")\n", + "plt.scatter(np.cos(thetas), np.sin(thetas), color=\"red\", label=\"vertices\")\n", + "plt.plot(np.cos(thetas_inf), np.sin(thetas_inf), \"k--\", label=\"unit circle\", alpha=0.5)\n", "plt.legend()\n", - "plt.title(f'Polygon with {n} sides')\n", + "plt.title(f\"Polygon with {n} sides\")\n", "plt.grid(True)\n", "plt.xlim(-1.1, 1.1)\n", "plt.ylim(-1.1, 1.1)\n", @@ -207,58 +211,61 @@ } ], "source": [ - "from cProfile import label\n", "import numpy as np\n", "from scipy.optimize import minimize\n", "import matplotlib.pyplot as plt\n", "\n", + "\n", "def polygon_perimeter(theta, n):\n", " points = np.array([[np.cos(t), np.sin(t)] for t in theta])\n", " perimeter = 0\n", - " for i in range(n-1):\n", - " perimeter += np.sqrt(np.sum((points[i+1] - points[i])**2))\n", - " perimeter += np.sqrt(np.sum((points[0] - points[-1])**2))\n", + " for i in range(n - 1):\n", + " perimeter += np.sqrt(np.sum((points[i + 1] - points[i]) ** 2))\n", + " perimeter += np.sqrt(np.sum((points[0] - points[-1]) ** 2))\n", " return -perimeter\n", "\n", + "\n", "def constraint_increasing(theta):\n", - " return np.array([theta[i+1] - theta[i] for i in range(len(theta)-1)])\n", + " return np.array([theta[i + 1] - theta[i] for i in range(len(theta) - 1)])\n", + "\n", "\n", "def optimize_polygon(n):\n", " theta0 = generate_thetas(n)\n", - " \n", + "\n", " constraints = [\n", - " {'type': 'ineq', 'fun': constraint_increasing},\n", - " {'type': 'eq', 'fun': lambda x: x[0]},\n", - " {'type': 'ineq', 'fun': lambda x: 2*np.pi - x[-1]}\n", + " {\"type\": \"ineq\", \"fun\": constraint_increasing},\n", + " {\"type\": \"eq\", \"fun\": lambda x: x[0]},\n", + " {\"type\": \"ineq\", \"fun\": lambda x: 2 * np.pi - x[-1]},\n", " ]\n", "\n", " result = minimize(\n", " lambda x: polygon_perimeter(x, n),\n", " theta0,\n", " constraints=constraints,\n", - " method='SLSQP'\n", + " method=\"SLSQP\",\n", " )\n", - " \n", + "\n", " return result.x\n", "\n", + "\n", "def plot_perimeter(n):\n", " optimal_angles = optimize_polygon(n + 1)\n", " plt.figure(figsize=(7, 7))\n", - " t = np.linspace(0, 2*np.pi, 100)\n", - " plt.plot(np.cos(t), np.sin(t), 'k--', alpha=0.5, label='unit circle')\n", + " t = np.linspace(0, 2 * np.pi, 100)\n", + " plt.plot(np.cos(t), np.sin(t), \"k--\", alpha=0.5, label=\"unit circle\")\n", "\n", " points = np.array([[np.cos(t), np.sin(t)] for t in optimal_angles])\n", " points = np.vstack([points, points[0]])\n", - " plt.plot(points[:, 0], points[:, 1], 'b-', linewidth=2, label='optimal polygon')\n", - " plt.scatter(points[:-1, 0], points[:-1, 1], color='red', label='vertices')\n", + " plt.plot(points[:, 0], points[:, 1], \"b-\", linewidth=2, label=\"optimal polygon\")\n", + " plt.scatter(points[:-1, 0], points[:-1, 1], color=\"red\", label=\"vertices\")\n", "\n", " plt.legend()\n", - " plt.axis('equal')\n", + " plt.axis(\"equal\")\n", " plt.grid(True)\n", - " plt.title(f'Optimal {n}-sided Polygon Inscribed in Unit Circle')\n", - " plt.xlabel('x')\n", - " plt.ylabel('y')\n", - " plt.axis('equal')\n", + " plt.title(f\"Optimal {n}-sided Polygon Inscribed in Unit Circle\")\n", + " plt.xlabel(\"x\")\n", + " plt.ylabel(\"y\")\n", + " plt.axis(\"equal\")\n", " plt.grid(True)\n", " plt.show()\n", "\n", @@ -266,6 +273,7 @@ " print(f\"Maximum perimeter: {-polygon_perimeter(optimal_angles, n)}\")\n", " print(f\"2 * pi = {2 * np.pi}\")\n", "\n", + "\n", "for n in np.arange(3, 10, 1):\n", " plot_perimeter(n)" ] @@ -316,9 +324,11 @@ "source": [ "x0 = np.array([2, -1, 3, 0, -5])\n", "\n", + "\n", "def K(x):\n", " return np.minimum(x, 0)\n", "\n", + "\n", "print(f\"Initial point: {x0}\")\n", "print(f\"Projection of x0 onto K: {K(x0)}\")" ] diff --git a/M1/Portfolio Management/TP-Project.ipynb b/M1/Portfolio Management/TP-Project.ipynb index 843e152..1cd5cc6 100644 --- a/M1/Portfolio Management/TP-Project.ipynb +++ b/M1/Portfolio Management/TP-Project.ipynb @@ -1,8 +1,9 @@ { "cells": [ { - "metadata": {}, "cell_type": "markdown", + "id": "81049114d821d00e", + "metadata": {}, "source": [ "# Project - Portfolio Management\n", "\n", @@ -11,52 +12,36 @@ "### Time period studied from 2017-01-01 to 2018-01-01\n", "\n", "### Risk-free rate: 2%" - ], - "id": "81049114d821d00e" + ] }, { "cell_type": "code", + "execution_count": 51, "id": "initial_id", "metadata": { - "collapsed": true, "ExecuteTime": { "end_time": "2024-11-25T13:43:46.298758Z", "start_time": "2024-11-25T13:43:46.293696Z" - } + }, + "collapsed": true }, + "outputs": [], "source": [ "import yfinance as yf\n", "import pandas as pd\n", "import numpy as np" - ], - "outputs": [], - "execution_count": 51 + ] }, { + "cell_type": "code", + "execution_count": 52, + "id": "9f9fc36832c97e0", "metadata": { "ExecuteTime": { "end_time": "2024-11-25T13:43:47.318911Z", "start_time": "2024-11-25T13:43:47.198820Z" } }, - "cell_type": "code", - "source": [ - "# Data Extraction\n", - "Tickers = [\"^RUT\", \"^IXIC\", \"^GSPC\", \"XWD.TO\"]\n", - "start_input = \"2017-01-01\"\n", - "end_input = \"2018-01-01\"\n", - "S = pd.DataFrame()\n", - "for t in Tickers:\n", - " S[t] = yf.Tickers(t).history(start=start_input, end=end_input)[\"Close\"]\n", - "\n", - "S = S.interpolate(method=\"pad\")\n", - "\n", - "# Show the first five and last five values extracted\n", - "display(S.head())\n", - "display(S.tail())\n", - "print(S.shape)" - ], - "id": "9f9fc36832c97e0", "outputs": [ { "name": "stderr", @@ -72,15 +57,6 @@ }, { "data": { - "text/plain": [ - " ^RUT ^IXIC ^GSPC XWD.TO\n", - "Date \n", - "2017-01-03 00:00:00+00:00 1365.489990 5429.080078 2257.830078 38.499630\n", - "2017-01-04 00:00:00+00:00 1387.949951 5477.000000 2270.750000 38.553375\n", - "2017-01-05 00:00:00+00:00 1371.939941 5487.939941 2269.000000 38.481716\n", - "2017-01-06 00:00:00+00:00 1367.280029 5521.060059 2276.979980 38.517544\n", - "2017-01-09 00:00:00+00:00 1357.489990 5531.819824 2268.899902 38.383186" - ], "text/html": [ "
\n", "
LinearRegression()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + ], + "text/plain": [ + "LinearRegression()" ] }, "execution_count": 16, @@ -609,7 +610,9 @@ "output_type": "execute_result" } ], - "execution_count": 16 + "source": [ + "lin_reg.fit(X, y)" + ] }, { "cell_type": "markdown", @@ -620,32 +623,34 @@ }, { "cell_type": "code", + "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:38:57.098642Z", "start_time": "2025-01-22T09:38:56.937883Z" } }, - "source": "lin_reg.fit(x, y) # we used x instead of X", "outputs": [ { "ename": "ValueError", "evalue": "Expected 2D array, got 1D array instead:\narray=[-4.9263773 -4.77287927 -4.69182165 -4.56196234 -4.41697258 -4.36182744\n -4.12350081 -4.09952139 -4.05822652 -3.85469926 -3.81994098 -3.71886367\n -3.70078495 -3.60247516 -3.60203002 -3.47687897 -3.45710508 -3.38728221\n -3.3302708 -3.10528641 -3.05361292 -3.00091798 -2.85415327 -2.73090651\n -2.72761278 -2.66060514 -2.18616108 -2.11671896 -2.06406242 -1.98487911\n -1.96049902 -1.87633359 -1.74174642 -1.45474032 -1.38187389 -1.29540294\n -1.29201976 -1.18978774 -1.12521621 -0.93613139 -0.91471356 -0.63282611\n -0.62848081 -0.6112156 -0.56585801 -0.53843724 -0.49614062 -0.41084224\n -0.3812277 -0.33278996 -0.30444189 -0.28903794 -0.24295074 0.01044775\n 0.53579401 0.54584787 0.57032152 0.59207161 0.65236106 0.68741196\n 1.30282593 1.31664399 1.3471832 1.4386512 1.61916515 1.6431354\n 1.64850857 1.68402962 1.69813995 1.82495504 1.83048953 1.96320375\n 1.97368029 2.00265102 2.05165379 2.22359351 2.44762156 2.5808774\n 2.61139702 2.64998857 2.73956049 2.78383497 2.80729031 2.83898209\n 2.86064305 2.86924378 3.04764357 3.14020385 3.22761613 3.27631172\n 3.32259801 3.32678196 3.53403073 3.5859792 3.93121121 4.26764989\n 4.61897665 4.67509732 4.70698024 4.75622352].\nReshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.", "output_type": "error", "traceback": [ - "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[0;31mValueError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[0;32mIn[17], line 1\u001B[0m\n\u001B[0;32m----> 1\u001B[0m \u001B[43mlin_reg\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mfit\u001B[49m\u001B[43m(\u001B[49m\u001B[43mx\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43my\u001B[49m\u001B[43m)\u001B[49m \u001B[38;5;66;03m# we used x instead of X\u001B[39;00m\n", - "File \u001B[0;32m/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/sklearn/base.py:1389\u001B[0m, in \u001B[0;36m_fit_context..decorator..wrapper\u001B[0;34m(estimator, *args, **kwargs)\u001B[0m\n\u001B[1;32m 1382\u001B[0m estimator\u001B[38;5;241m.\u001B[39m_validate_params()\n\u001B[1;32m 1384\u001B[0m \u001B[38;5;28;01mwith\u001B[39;00m config_context(\n\u001B[1;32m 1385\u001B[0m skip_parameter_validation\u001B[38;5;241m=\u001B[39m(\n\u001B[1;32m 1386\u001B[0m prefer_skip_nested_validation \u001B[38;5;129;01mor\u001B[39;00m global_skip_validation\n\u001B[1;32m 1387\u001B[0m )\n\u001B[1;32m 1388\u001B[0m ):\n\u001B[0;32m-> 1389\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mfit_method\u001B[49m\u001B[43m(\u001B[49m\u001B[43mestimator\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n", - "File \u001B[0;32m/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/sklearn/linear_model/_base.py:601\u001B[0m, in \u001B[0;36mLinearRegression.fit\u001B[0;34m(self, X, y, sample_weight)\u001B[0m\n\u001B[1;32m 597\u001B[0m n_jobs_ \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mn_jobs\n\u001B[1;32m 599\u001B[0m accept_sparse \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mFalse\u001B[39;00m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mpositive \u001B[38;5;28;01melse\u001B[39;00m [\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mcsr\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mcsc\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mcoo\u001B[39m\u001B[38;5;124m\"\u001B[39m]\n\u001B[0;32m--> 601\u001B[0m X, y \u001B[38;5;241m=\u001B[39m \u001B[43mvalidate_data\u001B[49m\u001B[43m(\u001B[49m\n\u001B[1;32m 602\u001B[0m \u001B[43m \u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[43m,\u001B[49m\n\u001B[1;32m 603\u001B[0m \u001B[43m \u001B[49m\u001B[43mX\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 604\u001B[0m \u001B[43m \u001B[49m\u001B[43my\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 605\u001B[0m \u001B[43m \u001B[49m\u001B[43maccept_sparse\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43maccept_sparse\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 606\u001B[0m \u001B[43m \u001B[49m\u001B[43my_numeric\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43;01mTrue\u001B[39;49;00m\u001B[43m,\u001B[49m\n\u001B[1;32m 607\u001B[0m \u001B[43m \u001B[49m\u001B[43mmulti_output\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43;01mTrue\u001B[39;49;00m\u001B[43m,\u001B[49m\n\u001B[1;32m 608\u001B[0m \u001B[43m \u001B[49m\u001B[43mforce_writeable\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43;01mTrue\u001B[39;49;00m\u001B[43m,\u001B[49m\n\u001B[1;32m 609\u001B[0m \u001B[43m\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 611\u001B[0m has_sw \u001B[38;5;241m=\u001B[39m sample_weight \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m\n\u001B[1;32m 612\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m has_sw:\n", - "File \u001B[0;32m/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/sklearn/utils/validation.py:2961\u001B[0m, in \u001B[0;36mvalidate_data\u001B[0;34m(_estimator, X, y, reset, validate_separately, skip_check_array, **check_params)\u001B[0m\n\u001B[1;32m 2959\u001B[0m y \u001B[38;5;241m=\u001B[39m check_array(y, input_name\u001B[38;5;241m=\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124my\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39mcheck_y_params)\n\u001B[1;32m 2960\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m-> 2961\u001B[0m X, y \u001B[38;5;241m=\u001B[39m \u001B[43mcheck_X_y\u001B[49m\u001B[43m(\u001B[49m\u001B[43mX\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43my\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mcheck_params\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 2962\u001B[0m out \u001B[38;5;241m=\u001B[39m X, y\n\u001B[1;32m 2964\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m no_val_X \u001B[38;5;129;01mand\u001B[39;00m check_params\u001B[38;5;241m.\u001B[39mget(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mensure_2d\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;28;01mTrue\u001B[39;00m):\n", - "File \u001B[0;32m/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/sklearn/utils/validation.py:1370\u001B[0m, in \u001B[0;36mcheck_X_y\u001B[0;34m(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_writeable, force_all_finite, ensure_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, estimator)\u001B[0m\n\u001B[1;32m 1364\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(\n\u001B[1;32m 1365\u001B[0m \u001B[38;5;124mf\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;132;01m{\u001B[39;00mestimator_name\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m requires y to be passed, but the target y is None\u001B[39m\u001B[38;5;124m\"\u001B[39m\n\u001B[1;32m 1366\u001B[0m )\n\u001B[1;32m 1368\u001B[0m ensure_all_finite \u001B[38;5;241m=\u001B[39m _deprecate_force_all_finite(force_all_finite, ensure_all_finite)\n\u001B[0;32m-> 1370\u001B[0m X \u001B[38;5;241m=\u001B[39m \u001B[43mcheck_array\u001B[49m\u001B[43m(\u001B[49m\n\u001B[1;32m 1371\u001B[0m \u001B[43m \u001B[49m\u001B[43mX\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1372\u001B[0m \u001B[43m \u001B[49m\u001B[43maccept_sparse\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43maccept_sparse\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1373\u001B[0m \u001B[43m \u001B[49m\u001B[43maccept_large_sparse\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43maccept_large_sparse\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1374\u001B[0m \u001B[43m \u001B[49m\u001B[43mdtype\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mdtype\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1375\u001B[0m \u001B[43m \u001B[49m\u001B[43morder\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43morder\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1376\u001B[0m \u001B[43m \u001B[49m\u001B[43mcopy\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mcopy\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1377\u001B[0m \u001B[43m \u001B[49m\u001B[43mforce_writeable\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mforce_writeable\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1378\u001B[0m \u001B[43m \u001B[49m\u001B[43mensure_all_finite\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mensure_all_finite\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1379\u001B[0m \u001B[43m \u001B[49m\u001B[43mensure_2d\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mensure_2d\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1380\u001B[0m \u001B[43m \u001B[49m\u001B[43mallow_nd\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mallow_nd\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1381\u001B[0m \u001B[43m \u001B[49m\u001B[43mensure_min_samples\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mensure_min_samples\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1382\u001B[0m \u001B[43m \u001B[49m\u001B[43mensure_min_features\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mensure_min_features\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1383\u001B[0m \u001B[43m \u001B[49m\u001B[43mestimator\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mestimator\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1384\u001B[0m \u001B[43m \u001B[49m\u001B[43minput_name\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mX\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\n\u001B[1;32m 1385\u001B[0m \u001B[43m\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 1387\u001B[0m y \u001B[38;5;241m=\u001B[39m _check_y(y, multi_output\u001B[38;5;241m=\u001B[39mmulti_output, y_numeric\u001B[38;5;241m=\u001B[39my_numeric, estimator\u001B[38;5;241m=\u001B[39mestimator)\n\u001B[1;32m 1389\u001B[0m check_consistent_length(X, y)\n", - "File \u001B[0;32m/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/sklearn/utils/validation.py:1093\u001B[0m, in \u001B[0;36mcheck_array\u001B[0;34m(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_writeable, force_all_finite, ensure_all_finite, ensure_non_negative, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator, input_name)\u001B[0m\n\u001B[1;32m 1086\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[1;32m 1087\u001B[0m msg \u001B[38;5;241m=\u001B[39m (\n\u001B[1;32m 1088\u001B[0m \u001B[38;5;124mf\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mExpected 2D array, got 1D array instead:\u001B[39m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;124marray=\u001B[39m\u001B[38;5;132;01m{\u001B[39;00marray\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m.\u001B[39m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;124m\"\u001B[39m\n\u001B[1;32m 1089\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mReshape your data either using array.reshape(-1, 1) if \u001B[39m\u001B[38;5;124m\"\u001B[39m\n\u001B[1;32m 1090\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124myour data has a single feature or array.reshape(1, -1) \u001B[39m\u001B[38;5;124m\"\u001B[39m\n\u001B[1;32m 1091\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mif it contains a single sample.\u001B[39m\u001B[38;5;124m\"\u001B[39m\n\u001B[1;32m 1092\u001B[0m )\n\u001B[0;32m-> 1093\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(msg)\n\u001B[1;32m 1095\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m dtype_numeric \u001B[38;5;129;01mand\u001B[39;00m \u001B[38;5;28mhasattr\u001B[39m(array\u001B[38;5;241m.\u001B[39mdtype, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mkind\u001B[39m\u001B[38;5;124m\"\u001B[39m) \u001B[38;5;129;01mand\u001B[39;00m array\u001B[38;5;241m.\u001B[39mdtype\u001B[38;5;241m.\u001B[39mkind \u001B[38;5;129;01min\u001B[39;00m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mUSV\u001B[39m\u001B[38;5;124m\"\u001B[39m:\n\u001B[1;32m 1096\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(\n\u001B[1;32m 1097\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mdtype=\u001B[39m\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mnumeric\u001B[39m\u001B[38;5;124m'\u001B[39m\u001B[38;5;124m is not compatible with arrays of bytes/strings.\u001B[39m\u001B[38;5;124m\"\u001B[39m\n\u001B[1;32m 1098\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mConvert your data to numeric values explicitly instead.\u001B[39m\u001B[38;5;124m\"\u001B[39m\n\u001B[1;32m 1099\u001B[0m )\n", - "\u001B[0;31mValueError\u001B[0m: Expected 2D array, got 1D array instead:\narray=[-4.9263773 -4.77287927 -4.69182165 -4.56196234 -4.41697258 -4.36182744\n -4.12350081 -4.09952139 -4.05822652 -3.85469926 -3.81994098 -3.71886367\n -3.70078495 -3.60247516 -3.60203002 -3.47687897 -3.45710508 -3.38728221\n -3.3302708 -3.10528641 -3.05361292 -3.00091798 -2.85415327 -2.73090651\n -2.72761278 -2.66060514 -2.18616108 -2.11671896 -2.06406242 -1.98487911\n -1.96049902 -1.87633359 -1.74174642 -1.45474032 -1.38187389 -1.29540294\n -1.29201976 -1.18978774 -1.12521621 -0.93613139 -0.91471356 -0.63282611\n -0.62848081 -0.6112156 -0.56585801 -0.53843724 -0.49614062 -0.41084224\n -0.3812277 -0.33278996 -0.30444189 -0.28903794 -0.24295074 0.01044775\n 0.53579401 0.54584787 0.57032152 0.59207161 0.65236106 0.68741196\n 1.30282593 1.31664399 1.3471832 1.4386512 1.61916515 1.6431354\n 1.64850857 1.68402962 1.69813995 1.82495504 1.83048953 1.96320375\n 1.97368029 2.00265102 2.05165379 2.22359351 2.44762156 2.5808774\n 2.61139702 2.64998857 2.73956049 2.78383497 2.80729031 2.83898209\n 2.86064305 2.86924378 3.04764357 3.14020385 3.22761613 3.27631172\n 3.32259801 3.32678196 3.53403073 3.5859792 3.93121121 4.26764989\n 4.61897665 4.67509732 4.70698024 4.75622352].\nReshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample." + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[17], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mlin_reg\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# we used x instead of X\u001b[39;00m\n", + "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/sklearn/base.py:1389\u001b[0m, in \u001b[0;36m_fit_context..decorator..wrapper\u001b[0;34m(estimator, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1382\u001b[0m estimator\u001b[38;5;241m.\u001b[39m_validate_params()\n\u001b[1;32m 1384\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[1;32m 1385\u001b[0m skip_parameter_validation\u001b[38;5;241m=\u001b[39m(\n\u001b[1;32m 1386\u001b[0m prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[1;32m 1387\u001b[0m )\n\u001b[1;32m 1388\u001b[0m ):\n\u001b[0;32m-> 1389\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfit_method\u001b[49m\u001b[43m(\u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/sklearn/linear_model/_base.py:601\u001b[0m, in \u001b[0;36mLinearRegression.fit\u001b[0;34m(self, X, y, sample_weight)\u001b[0m\n\u001b[1;32m 597\u001b[0m n_jobs_ \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mn_jobs\n\u001b[1;32m 599\u001b[0m accept_sparse \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpositive \u001b[38;5;28;01melse\u001b[39;00m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcsr\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcsc\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcoo\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[0;32m--> 601\u001b[0m X, y \u001b[38;5;241m=\u001b[39m \u001b[43mvalidate_data\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 602\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 603\u001b[0m \u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 604\u001b[0m \u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 605\u001b[0m \u001b[43m \u001b[49m\u001b[43maccept_sparse\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maccept_sparse\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 606\u001b[0m \u001b[43m \u001b[49m\u001b[43my_numeric\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 607\u001b[0m \u001b[43m \u001b[49m\u001b[43mmulti_output\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 608\u001b[0m \u001b[43m \u001b[49m\u001b[43mforce_writeable\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m 609\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 611\u001b[0m has_sw \u001b[38;5;241m=\u001b[39m sample_weight \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 612\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m has_sw:\n", + "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/sklearn/utils/validation.py:2961\u001b[0m, in \u001b[0;36mvalidate_data\u001b[0;34m(_estimator, X, y, reset, validate_separately, skip_check_array, **check_params)\u001b[0m\n\u001b[1;32m 2959\u001b[0m y \u001b[38;5;241m=\u001b[39m check_array(y, input_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124my\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mcheck_y_params)\n\u001b[1;32m 2960\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 2961\u001b[0m X, y \u001b[38;5;241m=\u001b[39m \u001b[43mcheck_X_y\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mcheck_params\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2962\u001b[0m out \u001b[38;5;241m=\u001b[39m X, y\n\u001b[1;32m 2964\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m no_val_X \u001b[38;5;129;01mand\u001b[39;00m check_params\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mensure_2d\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mTrue\u001b[39;00m):\n", + "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/sklearn/utils/validation.py:1370\u001b[0m, in \u001b[0;36mcheck_X_y\u001b[0;34m(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_writeable, force_all_finite, ensure_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, estimator)\u001b[0m\n\u001b[1;32m 1364\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 1365\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mestimator_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m requires y to be passed, but the target y is None\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1366\u001b[0m )\n\u001b[1;32m 1368\u001b[0m ensure_all_finite \u001b[38;5;241m=\u001b[39m _deprecate_force_all_finite(force_all_finite, ensure_all_finite)\n\u001b[0;32m-> 1370\u001b[0m X \u001b[38;5;241m=\u001b[39m \u001b[43mcheck_array\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1371\u001b[0m \u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1372\u001b[0m \u001b[43m \u001b[49m\u001b[43maccept_sparse\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maccept_sparse\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1373\u001b[0m \u001b[43m \u001b[49m\u001b[43maccept_large_sparse\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maccept_large_sparse\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1374\u001b[0m \u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1375\u001b[0m \u001b[43m \u001b[49m\u001b[43morder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43morder\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1376\u001b[0m \u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcopy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1377\u001b[0m \u001b[43m \u001b[49m\u001b[43mforce_writeable\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mforce_writeable\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1378\u001b[0m \u001b[43m \u001b[49m\u001b[43mensure_all_finite\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mensure_all_finite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1379\u001b[0m \u001b[43m \u001b[49m\u001b[43mensure_2d\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mensure_2d\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1380\u001b[0m \u001b[43m \u001b[49m\u001b[43mallow_nd\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mallow_nd\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1381\u001b[0m \u001b[43m \u001b[49m\u001b[43mensure_min_samples\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mensure_min_samples\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1382\u001b[0m \u001b[43m \u001b[49m\u001b[43mensure_min_features\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mensure_min_features\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1383\u001b[0m \u001b[43m \u001b[49m\u001b[43mestimator\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mestimator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1384\u001b[0m \u001b[43m \u001b[49m\u001b[43minput_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mX\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1385\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1387\u001b[0m y \u001b[38;5;241m=\u001b[39m _check_y(y, multi_output\u001b[38;5;241m=\u001b[39mmulti_output, y_numeric\u001b[38;5;241m=\u001b[39my_numeric, estimator\u001b[38;5;241m=\u001b[39mestimator)\n\u001b[1;32m 1389\u001b[0m check_consistent_length(X, y)\n", + "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/sklearn/utils/validation.py:1093\u001b[0m, in \u001b[0;36mcheck_array\u001b[0;34m(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_writeable, force_all_finite, ensure_all_finite, ensure_non_negative, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator, input_name)\u001b[0m\n\u001b[1;32m 1086\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1087\u001b[0m msg \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 1088\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExpected 2D array, got 1D array instead:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124marray=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00marray\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1089\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mReshape your data either using array.reshape(-1, 1) if \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1090\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124myour data has a single feature or array.reshape(1, -1) \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1091\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mif it contains a single sample.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1092\u001b[0m )\n\u001b[0;32m-> 1093\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(msg)\n\u001b[1;32m 1095\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m dtype_numeric \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(array\u001b[38;5;241m.\u001b[39mdtype, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mkind\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;129;01mand\u001b[39;00m array\u001b[38;5;241m.\u001b[39mdtype\u001b[38;5;241m.\u001b[39mkind \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUSV\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 1096\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 1097\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdtype=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnumeric\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m is not compatible with arrays of bytes/strings.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1098\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConvert your data to numeric values explicitly instead.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 1099\u001b[0m )\n", + "\u001b[0;31mValueError\u001b[0m: Expected 2D array, got 1D array instead:\narray=[-4.9263773 -4.77287927 -4.69182165 -4.56196234 -4.41697258 -4.36182744\n -4.12350081 -4.09952139 -4.05822652 -3.85469926 -3.81994098 -3.71886367\n -3.70078495 -3.60247516 -3.60203002 -3.47687897 -3.45710508 -3.38728221\n -3.3302708 -3.10528641 -3.05361292 -3.00091798 -2.85415327 -2.73090651\n -2.72761278 -2.66060514 -2.18616108 -2.11671896 -2.06406242 -1.98487911\n -1.96049902 -1.87633359 -1.74174642 -1.45474032 -1.38187389 -1.29540294\n -1.29201976 -1.18978774 -1.12521621 -0.93613139 -0.91471356 -0.63282611\n -0.62848081 -0.6112156 -0.56585801 -0.53843724 -0.49614062 -0.41084224\n -0.3812277 -0.33278996 -0.30444189 -0.28903794 -0.24295074 0.01044775\n 0.53579401 0.54584787 0.57032152 0.59207161 0.65236106 0.68741196\n 1.30282593 1.31664399 1.3471832 1.4386512 1.61916515 1.6431354\n 1.64850857 1.68402962 1.69813995 1.82495504 1.83048953 1.96320375\n 1.97368029 2.00265102 2.05165379 2.22359351 2.44762156 2.5808774\n 2.61139702 2.64998857 2.73956049 2.78383497 2.80729031 2.83898209\n 2.86064305 2.86924378 3.04764357 3.14020385 3.22761613 3.27631172\n 3.32259801 3.32678196 3.53403073 3.5859792 3.93121121 4.26764989\n 4.61897665 4.67509732 4.70698024 4.75622352].\nReshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample." ] } ], - "execution_count": 17 + "source": [ + "lin_reg.fit(x, y) # we used x instead of X" + ] }, { "cell_type": "markdown", @@ -656,25 +661,13 @@ }, { "cell_type": "code", + "execution_count": 20, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:39:52.478784Z", "start_time": "2025-01-22T09:39:52.472388Z" } }, - "source": [ - "a = np.arange(6).reshape(2, 3)\n", - "# 3 ways to reshape the array a into a 3 x 2 array \n", - "b = a.reshape(3, 2)\n", - "b2 = a.reshape(3, -1) # -1 means \"guess\" the number\n", - "b3 = a.reshape(-1, 2) # same\n", - "# obviously reshape(4,-1) would not work here as 2 X 3=6 is not\n", - "# divisible by 4...\n", - "print(a)\n", - "print(b)\n", - "print(b2)\n", - "print(b3)" - ], "outputs": [ { "name": "stdout", @@ -694,7 +687,19 @@ ] } ], - "execution_count": 20 + "source": [ + "a = np.arange(6).reshape(2, 3)\n", + "# 3 ways to reshape the array a into a 3 x 2 array\n", + "b = a.reshape(3, 2)\n", + "b2 = a.reshape(3, -1) # -1 means \"guess\" the number\n", + "b3 = a.reshape(-1, 2) # same\n", + "# obviously reshape(4,-1) would not work here as 2 X 3=6 is not\n", + "# divisible by 4...\n", + "print(a)\n", + "print(b)\n", + "print(b2)\n", + "print(b3)" + ] }, { "cell_type": "markdown", @@ -713,29 +718,20 @@ }, { "cell_type": "code", + "execution_count": 52, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:50:01.091807Z", "start_time": "2025-01-22T09:50:00.964206Z" } }, - "source": [ - "y_predict = lin_reg.predict(X)\n", - "plt.plot(X, y_predict, color='r', label='Regression')\n", - "plt.scatter(X, y, label='Sample')\n", - "plt.legend()\n", - "plt.show()\n", - "\n", - "y_1 = lin_reg.predict([[1]])\n", - "print(\"The estimated value for x=1 is\", y_1)" - ], "outputs": [ { "data": { + "image/png": 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", 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" + ] }, "metadata": {}, "output_type": "display_data" @@ -748,7 +744,16 @@ ] } ], - "execution_count": 52 + "source": [ + "y_predict = lin_reg.predict(X)\n", + "plt.plot(X, y_predict, color=\"r\", label=\"Regression\")\n", + "plt.scatter(X, y, label=\"Sample\")\n", + "plt.legend()\n", + "plt.show()\n", + "\n", + "y_1 = lin_reg.predict([[1]])\n", + "print(\"The estimated value for x=1 is\", y_1)" + ] }, { "cell_type": "markdown", @@ -759,13 +764,13 @@ }, { "cell_type": "code", + "execution_count": 30, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:42:26.316701Z", "start_time": "2025-01-22T09:42:26.312959Z" } }, - "source": "print(\"The estimated coefficients are a=\", lin_reg.coef_, \", b=\", lin_reg.intercept_)", "outputs": [ { "name": "stdout", @@ -775,7 +780,9 @@ ] } ], - "execution_count": 30 + "source": [ + "print(\"The estimated coefficients are a=\", lin_reg.coef_, \", b=\", lin_reg.intercept_)" + ] }, { "cell_type": "markdown", @@ -786,13 +793,13 @@ }, { "cell_type": "code", + "execution_count": 31, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:42:50.448815Z", "start_time": "2025-01-22T09:42:50.445550Z" } }, - "source": "print(np.sum((y - y_predict) ** 2))", "outputs": [ { "name": "stdout", @@ -802,7 +809,9 @@ ] } ], - "execution_count": 31 + "source": [ + "print(np.sum((y - y_predict) ** 2))" + ] }, { "cell_type": "markdown", @@ -813,15 +822,13 @@ }, { "cell_type": "code", + "execution_count": 32, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:42:57.691432Z", "start_time": "2025-01-22T09:42:57.686810Z" } }, - "source": [ - "lin_reg.score(X, y)" - ], "outputs": [ { "data": { @@ -834,11 +841,13 @@ "output_type": "execute_result" } ], - "execution_count": 32 + "source": [ + "lin_reg.score(X, y)" + ] }, { - "metadata": {}, "cell_type": "markdown", + "metadata": {}, "source": "The output is the $R^2$ coefficient. It is far from 1, which means that the model is not perfect." }, { @@ -864,16 +873,13 @@ }, { "cell_type": "code", + "execution_count": 36, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:44:45.265060Z", "start_time": "2025-01-22T09:44:45.261420Z" } }, - "source": [ - "X2 = np.array([x ** 2, x]).T\n", - "print(X2.shape)" - ], "outputs": [ { "name": "stdout", @@ -883,7 +889,10 @@ ] } ], - "execution_count": 36 + "source": [ + "X2 = np.array([x**2, x]).T\n", + "print(X2.shape)" + ] }, { "cell_type": "markdown", @@ -894,22 +903,16 @@ }, { "cell_type": "code", + "execution_count": 37, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:45:05.543859Z", "start_time": "2025-01-22T09:45:05.532828Z" } }, - "source": [ - "poly2_reg = LinearRegression()\n", - "poly2_reg.fit(X2, y)" - ], "outputs": [ { "data": { - "text/plain": [ - "LinearRegression()" - ], "text/html": [ "
LinearRegression()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + ], + "text/plain": [ + "LinearRegression()" ] }, "execution_count": 37, @@ -1334,7 +1340,10 @@ "output_type": "execute_result" } ], - "execution_count": 37 + "source": [ + "poly2_reg = LinearRegression()\n", + "poly2_reg.fit(X2, y)" + ] }, { "cell_type": "markdown", @@ -1353,31 +1362,20 @@ }, { "cell_type": "code", + "execution_count": 50, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:49:38.985508Z", "start_time": "2025-01-22T09:49:38.910274Z" } }, - "source": [ - "# Answer for Exercise 11\n", - "y2_predict = poly2_reg.predict(X2)\n", - "plt.scatter(x, y, label='Sample')\n", - "plt.plot(x, y2_predict, color='r', label='Regression')\n", - "\n", - "plt.legend()\n", - "plt.show()\n", - "\n", - "y2_1 = poly2_reg.predict([[1, 1]])\n", - "print(\"The estimated value for x=1 is\", y2_1) #add your code" - ], "outputs": [ { "data": { + "image/png": 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", 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atm1rmTBhgs1jWCz5/L+LiEheTz5pnKO6dHH7oQs6f1/Nt3pEypUzeic8cVwHde3alXnz5nHhwgVmzZpFqVKl6NevH7t27eLixYt5egQyMjJo1aoVAHv37qVt27a5Xm/Xrl2eY5QpU4bmza+sF//tt9/IysqiQYMGubZLT0+ncmWjAvETTzzBsGHD+Oqrr+jevTv9+vXL3sewYcPo168fO3bs4NZbb6Vv37784x//sPn5fv/9dzp27IjJdCW67tSpE+fPn+fo0aPUqlULIFf7ACIiIjh58mT+X5yIiB/JMluK1muRmgpvvWXct9Fj7k18KxAxmYo1ROJO5cuXp169egAsWrSIFi1a8N///jd71cnnn39OzZo1c70nKCjIoWOULVs2VyBw/vx5AgMD2b59O4FXlX62Dr88/PDD9OzZk88//5yvvvqKmJgYXn31VUaOHMltt93GoUOHWLt2LevWraNbt24MHz6cV155xeHPb1W6dOlcj00mk0sn1YqIlBSx8YlMW7O7aPVgFiwwgpFGjeD2213c0uLxrcmqJVRAQABPP/00kydPzjWxtF69erlukZGRADRs2JCffvop1z5+/PHHQo/TqlUrsrKyOHnyZJ59h4eHZ28XGRnJY489xscff8y4ceNYsGBB9mtVq1Zl0KBBLF26lNdee423337b5rEaN25MXFwclhwTebds2UJISAjXXnutQ9+PiIi/iY1PZNjSHUWrB5OZCa+9ZtwfN85YMePFvLt1fuSf//wngYGBvPXWW4wfP54xY8awZMkSDhw4wI4dO5gzZw5LliwB4NFHH2XPnj1MmDCBP/74gw8//JDFixcD5OoBuVqDBg24//77efDBB/n4449JSEhg27ZtxMTE8PnnnwMwevRovvzySxISEtixYwfffPMNjRs3BuDZZ59l9erV7N+/n127dvHZZ59lv3a1xx9/nCNHjjBy5Ej27NnD6tWrmTp1KmPHjiXAy38pREQ8KctsYdqa3UWvB/Phh8ZE1erVYeBAVzXTaXxraKYEK1WqFCNGjODll18mISGBqlWrEhMTw59//knFihVp3bo1Tz/9NABRUVGsXLmScePGMXv2bDp27MgzzzzDsGHDCh2+eeedd3jxxRcZN24cx44do0qVKnTo0IFevXoBRr6R4cOHc/ToUUJDQ4mOjmbWrFmAMedk0qRJHDx4kLJly3LjjTeyfPlym8epWbMma9eu5cknn6RFixZUqlSJIUOGMHnyZCd+ayIivmdbwpk8PSE55awH07Fu5atetIB1uHzkSAh2X4bUojJZcvade5nU1FTCwsJISUkhNDQ012tpaWkkJCQQFRVFcAn4ol3t3//+N/Pnz+fIkSOebopL6f9dRHzd6p3HGLV8Z6Hbzb63JX1a5p5LyNdfQ48exiKKw4ehcmXbb3axgs7fV1OPSAn15ptv0rZtWypXrsyWLVuYMWMGI0aM8HSzRESkmOyt82JzO2tvyL/+5bEgxFEKREqoffv28eKLL3LmzBlq1arFuHHjmDRpkqebJSIixdQuqhIRYcEkpaTZnCdiwsiCmqcezK+/wpdfGpNTx4zJ874iLwV2MQUiJdSsWbOy526IiIjvsNaDGbZ0BybIFYwUWA9m5kzj33794Lrrcr1UrKXALqblCyIiIl7G4Xowx47BsmXG/XHjcr1UrKXAblDkQCQmJoa2bdsSEhJCtWrV6Nu3L3v37s21zc0335xd7t56e+yxx4rd6Jy8eK6tuID+v0XEX0Q3i+C7CbfwwdAOzL63JR8M7cB3E26x3YPx+utG/pAbb4T27bOfLvZSYDco8tDMpk2bGD58OG3btuXy5cs8/fTT3HrrrezevZvyObKbDh06lOeffz77cbkipEO3xZqR8+LFi5QtW9Yp+xTvd/HiRSBvRlYREV8UGGDKu0T3aqmpMH++cf+qdO7FWgrsJkUORGJjY3M9Xrx4MdWqVWP79u3cdNNN2c+XK1cuV9ZOZwkMDKRixYrZdUnKlStXYDIvKdksFgsXL17k5MmTVKxYMU+KehERv/Xf/xrBSMOG8HdOKKuT5/IPQoqynSs4bbJqSkoKAJUq5Z7F+/7777N06VLCw8Pp3bs3U6ZMybdXJD09nfT09OzHqampBR7TGuCoSJr/qFixoksCWxGREqmQdO7FWgrsJk4JRMxmM6NHj6ZTp07ZRdsA7rvvPmrXrk2NGjX49ddfmTBhAnv37uXjjz+2uZ+YmBimTZtm93FNJhMRERFUq1aNzMzMYn8O8W6lS5dWT4iISE4ffWQkLqtWDR54IM/LRV4K7EZOyaw6bNgwvvjiC7777rsCC5pt2LCBbt26sX//furWrZvndVs9IpGRkXZlZhMREfErFgu0aQM//wzPPw9TptjczLpqBmwvBba5CqeYHMmsWuzluyNGjOCzzz7jm2++KbSqavu/Z/Lu37/f5utBQUGEhobmuomIiIgN33xjBCFly8KwYflu5vBSYDcr8tCMxWJh5MiRrFq1io0bNxIVFVXoe3bu3AlARIRnP7SIiEiJZ03n/tBDUKWKzU2s2VTTL5t5pX8LMMHp8+m+kVl1+PDhLFu2jNWrVxMSEkJSUhIAYWFhlC1blgMHDrBs2TJuv/12KleuzK+//sqYMWO46aabaN68udM+gIiIiN+Jj4cvvgCTCcaOtblJQdlUPbVU15YizxHJb6nsO++8w+DBgzly5AgDBw4kPj6eCxcuEBkZyZ133snkyZPtHnJxZIxJRETEbzz0ECxebKRzX7kyz8vWeSFXn+BdOS8kJ0fO306ZrOoqCkRERESucvw41KljLN2Ni4MOHXK9nGW20Hn6hnwTmVlXynw34RaXDc24dbKqiIiIuNGcOUYQ0qlTniAEHMum6g0UiIiIiJQU585dSef+5JM2NykJ2VRzUiAiIiJSUixaBGfPQv360Lu3zU1KQjbVnBSIiIiIlASXL8OsWcZ9G+ncrazZVPOb/WHCWD3jyWyqOSkQERERKQlWroRDh4ycIQ8+mO9mgQEmpvZuApAnGLE+ntq7iVfkEAEFIiIiIt7PYoEZM4z7I0YY2VQL4O3ZVHPS8l0RERFvt3EjdO0KwcFw5Ei+mVSvZs2sevJcmluzqTpy/nZK9V0RERFxIWtvSAHp3G0JDDB5VRZVWzQ0IyIi4s127YK1a4107mPGeLo1TqdARERExJvNnGn827evsWzXxygQERER8VaJibB0qXF//HjPtsVFFIiIiIh4q1degYwM+Mc/jJsPUiAiIiLijU6dupLOffJkz7bFhRSIiIiIeKNZs+DiRWjTBqKjPd0al1EgIiIi4m3OnIE33jDuT55srJjxUQpEREREvM3rrxuVdq+/Hu64w9OtcSkFIiIiIt4kNRVmzzbuT56cb3E7X+Hbn05ERKSkeeMNOHsWGjWCfv083RqXUyAiIiLiLc6fv5LA7JlnIDDQs+1xAwUiIiIi3uKttyA5GerWhXvv9XRr3EKBiIiIiDe4dOlKcbtJk6CUf9SlVSAiIiLiDRYuhBMnoFYteOABT7fGbRSIiIiIeFp6OkyfbtyfOBHKlPFse9xIgYiIiIinLV4Mx45BjRrw0EOebo1bKRARERHxpMxMeOkl4/5TT0FwsGfb42YKRERERDzp/ffh4EGoVg2GDvV0a9xOgYiIiIinZGXBf/5j3B83DsqV82x7PECBiIiIiKesWAH79kGlSjBsmKdb4xEKRERERDzBbIZ//9u4P2YMhIR4tj0eokBERETEEz7+GHbvhrAwGDnS063xGAUiIiIi7maxwIsvGvefeMIIRvyUAhERERF3++wz+OUXqFABRo3ydGs8SoGIiIiIO1ks8MILxv3HH4fKlT3bHg/zj4o6V8kyW9iWcIaT59KoFhJMu6hKBAaYPN0sERHxB199BT/+CGXLGkt2/ZzfBSKx8YlMW7ObxJS07OciwoKZ2rsJ0c0iPNgyERHxeTl7Qx591Ehi5uf8amgmNj6RYUt35ApCAJJS0hi2dAex8YkeapmIiPiFjRthyxYICoInn/R0a7yC3wQiWWYL09bsxmLjNetz09bsJstsawsREREnsK6UGTLEKHAn/hOIbEs4k6cnJCcLkJiSxraEM+5rlIiI+I/vv4cNG6B0aZgwwdOt8Rp+E4icPJd/EFKU7URERBxinRsyaBDUquXZtngRvwlEqoXYV1bZ3u1ERETs9uOPEBsLgYEwcaKnW+NV/GbVTLuoSkSEBZOUkmZznogJCA8zlvKKiIh/c3qaB+vckPvug7p1ndNIH1HkHpGYmBjatm1LSEgI1apVo2/fvuzduzfXNmlpaQwfPpzKlStToUIF+vXrx4kTJ4rd6KIIDDAxtXcTwAg6crI+ntq7ifKJiIj4udj4RDpP38CABVsZtXwnAxZspfP0DUVfWfnLL/Dpp2AywdNPO7exPqDIgcimTZsYPnw4W7duZd26dWRmZnLrrbdy4cKF7G3GjBnDmjVr+Oijj9i0aRPHjx/nrrvuckrDiyK6WQTzBrYmPCz38Et4WDDzBrZWHhERET/nkjQP1gq7d98NjRo5oZW+xWSxWJyyXvXUqVNUq1aNTZs2cdNNN5GSkkLVqlVZtmwZ/fv3B2DPnj00btyYuLg4OnTokGcf6enppKenZz9OTU0lMjKSlJQUQkNDndFMQJlVRUQkryyzhc7TN+S7wtI6hP/dhFvsP2fs3AmtWhn3f/0Vrr/eKW31dqmpqYSFhdl1/nbaZNWUlBQAKlUy5lhs376dzMxMunfvnr1No0aNqFWrFnFxcTb3ERMTQ1hYWPYtMjLSWc3LJTDARMe6lenTsiYd61ZWECIiIq5J8/DMM8a/997rN0GIo5wSiJjNZkaPHk2nTp1o1qwZAElJSZQpU4aKFSvm2rZ69eokJSXZ3M+kSZNISUnJvh05csQZzRMRESmU09M8fPcdrF1rrJR5/vlitMy3OWXVzPDhw4mPj+e7774r1n6CgoIICgpyRpNcTsM7IiK+xalpHiwWmDTJuD9kCNSvX4yW+bZiByIjRozgs88+Y/PmzVx77bXZz4eHh5ORkcHZs2dz9YqcOHGC8PDw4h62eC5fhiVLoG1baN7c4bercJ6IiO9xapqH2FijRyQoCJ591tlN9SlFHpqxWCyMGDGCVatWsWHDBqKionK93qZNG0qXLs369euzn9u7dy+HDx+mY8eORW+xMzz1FDz8cJGWUalwnoiIb3Jamgez+cr5ZcQIqFnTqe30NUVeNfP444+zbNkyVq9eTcOGDbOfDwsLo2zZsgAMGzaMtWvXsnjxYkJDQxk5ciQA33//vV3HcGTWrUP27zeWUGVlGRFrp052vc0lM6pFRMSrFLvXe8UKY3JqSAhZ+w+w7VyA3w3jO3L+LnIgYjLZ/iLfeecdBg8eDBgJzcaNG8cHH3xAeno6PXv25M0337R7aMZlgQjAI4/AggXQpQt8842RaKYQcQeSGbBga6HbfTC0Ax3rVnZGK0VExAOKPA8wMxOaNoV9+9j3+HgevDbaL4fx3RKIuINLA5EjR4zJQ+np8NVX0KNHoW9ZvfMYo5bvLHS72fe2pE9LdcWJiPidBQvgkUdIr1SZNg/O43xQuVwvW0MZX0+i6ZE8IiVOZCQMG2bcf/ppY4ZzIVQ4T0RE8pWWBtOmATCv4915ghAgexLstDW7yTJ7bT+AW/lvIALG0qry5eGnn2D16kI3t86ozq9zzoTR7abCeSIifujNN+HYMdIjajKvUf697EVKjObD/DsQqVYNRo827k+ebExeLYAK54mIiE2pqfCf/wCwe+ho0kuVKfQtdidG83H+HYgAjB8PFSvCrl3wwQeFbq7CeSIiksfMmZCcDA0bknbfA3a9RcP4Bv+drJrTSy8ZwzTXXQd79kDp0oW+RZlVRUQEgNOnISoKzp+HDz8kq19/Ok/fUGhiNF9O9aDJqo4aORKqV4c//4RFi+x6iwrniYgIADExRhDSqhX066dhfAcpEAFjwqq1QuILL8ClS55tj4iIuESW2ULcgWRW7zxG3IHk4q9cOXIE5s417v/nPxBgnFY1jG8/Dc1YpadDgwZw+DC8+iqMHeva44mIiFu5pE7Y0KGwcCHcdBNs3JgnOaa/DuMroVlRLVpkVEmsUsUYpgkJcf0xRUTE5ax1wq4+4RUrwdgff0CTJsaKyy1b4B//cEZTfYLmiBTVgw8avSKnT8OsWZ5ujYiIOEGW2cK0NbttThwtVoKxZ581gpBevRSEFIMCkZxKlTLmiAC88ooRkIiISIm2LeFMvsVKoYgJxn7+2ShuB/Dii8VroJ9TIHK1/v2Nmc/nzsG//+3p1oiISDHZmzjMoQRj1gUOAwZAixZFaJVYKRC5WkAATJ9u3H/zTTh0yLPtERGRYnF6nbBvv4UvvjB60Z9/vhgtE1AgYluPHtCtG2RkGGOAIiJSYjm1TpjFYiTABGNxQ716zmqm31Igkp+XXjL+fe89+PVXz7ZFRESKzKkJxr74wlghExwMU6Y4tZ3+SoFIfm64Ae6+24h+n37a060REZFicEqCMbP5yvlgxAioWdMFLfU/yiNSkH37jDXily/Dpk1GwhoRESmxipVgbPlyY3JqaKiRa6pyZdc2tgRTHhFnqV/fyJoH8NRTRu+IiIiUWEWuE5aZeWUoZvx4BSFOpECkEFmTp5BVrjz88AN/zFlU/LoEIiJS8ixeDPv3Q9WqMHq0p1vjUxSIFCA2PpHOS3Yzu3VfAIKmTqbrv2OJjU/0bMNERMR9Ll2CadOM+08/rfIfTqZAJB/WugSJKWksbNuXk+WvofbZJLpvXMWwpTsUjIiI+Is334RjxyAyEh57zNOt8TkKRK6SZbawZd9pJv7vt+waBBfLlGVm5/sBGPn9ckLSzhetLoGIiJQsKSkQE2Pcf+45Y9muOJUCkRxi4xPpPH0D9//3B85eysz12kfNe/BH5Vpck3aOx+M+tKsuQZbZQtyBZFbvPEbcgWQFLiIiJU1MDCQnQ6NGRmFUcbpSnm6At8ivRLRVVkAgMV0f4p2V03ho+xrea92rwLoEsfGJTFuzO1ehpYiwYKb2buJ4qWkRESlUsZbm2nLoEJbXXsMEbB02EcuhlOLvU/JQIELBJaJz+ua6G/i+VnP+cfhXxm9+l2rj77C5XX5BTVJKGsOW7rA/eY6IiNjFFRd/x0aMo2Z6OnG1rmfAscqwYKsuKF1AQzMUXiI6m8nEf7r+C4A7d2+k3ZmEPJsUFNRYn9P8EhER58m5uCAn68VfURYXfP/hl9T87H8A/LvrEDCZir1PsU2BCI6Vft4VXo9PmtwMQOCEvEnOCgtqLGDX/BIRESmcKy7+srLMlJ3wFACfNOlCfPiVwna6oHQ+BSI4UPoZoy5BxVkvQ5ky8M03sHZtrtftDWocCX5ERMQ2V1z87Z//Lq0O/sqlUkFM7zLYKfuU/CkQofAS0QAVy5bm/Yfb892EW7j51rbwxBPGC08+aaT+/Zu9QY0jwY+IiNjm9Iu/tDSujZkKwNvt7iIxtGrx9ykFUiBC4SWiTcBL/a6nU70qV2ZLP/MMVKkCv/8Ob72VvX1hQY0JYwJVu6hKTv4UIiL+x+kXf7NnU/7YYZIqVGJ++37O2acUSIHI3xwuEV2xIjz/vHF/6lT46y+g8KAGYGrvJlr+JSLiBE69+EtKgn//G4C3bhtKWhnbgYYuKJ3LZLF4b0lZR8oIO4tD69AvX4aWLWHXLqMI0qxZ2S8pj4iIiHtYV80AuSatWv9y250yYehQWLgQ2rYlduEqhi3bWfx9+ilHzt8KRIpr3Tq49VYoVQri46Fhw+yXnJ5cR0REbCr2xd/OndC6tbEScssW+Mc/dEFZDApE3K13b/jsM+jVC9as8XRrRET8UpEv/iwW6NoVNm2Ce++FDz4o/j79nAIRd9u7F5o1M4ZqvvoKevTwdItERMReq1bBXXcZBe327IHatT3dohLPkfO3Jqs6Q8OGMHy4cX/sWCMgERER75eeDuPHG/fHj1cQ4gEKRJzl2WehUiVjnsjChZ5ujYiI2OP11+HPPyEiAiZM8HRr/JICEWepVAmmTTPuT5kCKSmebY+IiBTsxAl44QXjfkwMVKjg2fb4KQUizvToo9CoEZw+DS++6OnWiIhIQZ59Fs6dgzZt4IEHPN0av6VAxJlKl4aZM437s2fD/v2ebY+IiNj2yy9XhtFfew0CdDr0lCJ/85s3b6Z3797UqFEDk8nEJ598kuv1wYMHYzKZct2io6OL216vl9Uzmr9u6gaZmZx5dISqM4qIeBuLBcaMAbMZ7r4bOnf2dIv8WpEDkQsXLtCiRQvmzp2b7zbR0dEkJiZm3z7IsTbbF8XGJ9J5+gb6N+hPZkAglTZ8yfghLxEbn+jppomIiNWnnxrV04OCYPp0T7fG75Uq6htvu+02brvttgK3CQoKIjw8vKiHKFGsKYYtAJUjWdymN0N//IQRn77JbVUa8/qg9srEJyLiaTmX644dC3XqeLQ54uI5Ihs3bqRatWo0bNiQYcOGkZycXOD26enppKam5rqVBFlmC9PW7M5Vj+D1TgM4Va4idc8cZdD2NUxbs1vDNCIinvbaa8b8verVYdIkT7dGcGEgEh0dzbvvvsv69euZPn06mzZt4rbbbiMrKyvf98TExBAWFpZ9i4yMdFXznGpbwplctQgAzgWV5+UugwB4YssHZB09xraEM55onoiIX8oyW4g7kMzqnceIO5BM1pGjV5brvvwyhIR4toECOCnFu8lkYtWqVfTt2zffbf7880/q1q3L119/Tbdu3Wxuk56eTnp6evbj1NRUIiMjvT7F++qdxxi1fGee500WMx+/9yStEveyunEXWPY+fVrWdH8DRUT8jK2CdW/FzqTnLxugY0f47jutlHEhr0zxft1111GlShX2F7CkNSgoiNDQ0Fy3kqBaSLDN5y2mACbfOowsUwB9ft9Evd+2ubllIiL+xzpnL2cQ0vZIPD1/2YAZE9+PmqogxIu47X/i6NGjJCcnExHhexM220VVIiIsGFv1GHeF12Npq9sBaPLvSZCR4d7GiYj4EVtz9gLNWTy/bj4AK1rcyrg/S2nOnhcpciBy/vx5du7cyc6dOwFISEhg586dHD58mPPnz/Pkk0+ydetWDh48yPr16+nTpw/16tWjZ8+ezmq71wgMMDG1dxOAPMGICXj1xoGkV66Kae9eePVVt7dPRMRf2JqzN/DntTQ+dZC/gkN4+aYHSUxJ05w9L1LkQOSnn36iVatWtGrVCoCxY8fSqlUrnn32WQIDA/n111+54447aNCgAUOGDKFNmzZ8++23BAUFOa3x3iS6WQTzBrYmPCz3ME14WDAvP3wTQa/9nXH1hRfg0CEPtFBExPedPJc7CKly4S/GfbsUgFdueoC/yoXZ3E48p8h5RG6++WYKmuf65ZdfFnXXJVZ0swh6NAlnW8IZTp5Lo1pIMO2iKhEYYIKm9xvphDdtglGj4KpMtCIiUnxXz9mbuHExoekX+K16XT5o0TPf7cRzihyIiG2BASY61q2c9wWTCebOhZYtYfVq+Owz6NXL7e0TEfFmWWZL9sVclfJBYILT59NzX9gVwDpnLykljRuOxNM/fj0Az/YYhjkgEBNGT3W7qEpu+DRiDwUi7tS0qVHfYMYMeOIJ6NYNypb1dKtERLyCrSW3OUWEBTO1d5PsLNU5g5acgcrU3k0YuWQbL3w1D4BlLXryc81G2XP4pvZuUmhAI+6jQMTdnn0WPvgAEhIgJgaef97TLRIR8bhcZTLykZSSxrClO5g3sDVAnqAlZ6Cyhp9pdPoQZ8qGZieXDL8qkBHv4JSEZq7iSEKUEuV//4P+/aFMGYiPh/r1Pd0iERGPyTJb6Dx9Q749ITmZgLBypUm5mJknaLH2cSzqEUHXvl3g/HkO/Oc14m/rb/fQjjiHVyY0kxzuuguio42cIiNGGCWpRUT8lK0lt/mxAGdtBCHW1wCyxoyF8+ehY0fqThhJn5Y16Vi3soIQL6VAxBNMJpgzxyhB/dVXsHKlp1skIuIxzlxK2zlhB91/24QlIADefFMZVEsA/Q95Sr16MHGicX/MGDh3zrPtERHxEGctpQ26nMHz64wJqn/e+5CxSlG8ngIRT5owAa67Do4d06RVEfFbBZXJcMTjcR8S9VciSRUqkfzkZKe0TVxPgYgnlS1rDNEAzJplTFwVEfFRWWYLcQeSWb3zGHEHkrPrvRRUJiMn62sVy5XOs13d00cYttUY5p59xwjaNK/t3MaLy2jVjDe46y5YtQpuvNHIvGqy/7ogv3X0IiLexFaOkKvzgtibRwRg2NIdwN8TVC0WVnwwifZH4llfty2Zqz4h+voaLv08UjBHzt8KRLzB4cPQuDFcvAhLlsCDD9r1Nnt+sUVEPC2/HCHWS6Z5A1vbTFJWUGbVnH///vnrOmZ8MZtLpYPZtmYTXXq2c9+HE5sUiJRE06fDxIlkVqrCuo+/4ZprIwrs3XDkF1tExFMKyxFiTbn+3YRbHO7NzTJb2LF9H81v7UDQ2b8wv/wyAU8+6YRWS3Epj0gJ9OWt95JQtRalz5wm5YlxDFiwlc7TNxAbn5hn2yyzhWlrdhe4jn7amt3Z468iIp5SWI4QC5CYksa2hDMO7zswwETbuf8h6Oxf0Lw5AaNHF72h4jEKRLxAbHwij62I58lbhwMw4NevaH/4t+x0xlcHI678xRYRcSZ7c4QUKZfI118bw9kmE7z1FpQu7fg+xOMUiHhYzt6Nn65tyrIW0QD858u5lLmcAeTt3XDpL7aIiBPZmyPE4VwiFy7A0KHG/ccfhw4dHGyZeAsFIh52de/GSzcP5mT5a6h75iiPx31os3fDZb/YIiJOVliOEBPGJPt2UZUc2/GUKXDwINSqZRQQlRJLgYiHXd1rkRpcgandHwVg2NaVNDx1MM92LvvFFhFxsoJyhFgfT+3dxLGJqlu3wmuvGfffegtCQorbTPEgBSIeZqvX4ouGnfiqfgfKmC8zY+1rBJqzcm3nkl9sEREXiW4WwbyBrQkPy/33Ljws2PEVfhkZ8PDDRrHQBx4wCog6IL+kauI5Wr7rYdalbUkpablWwVQ9f4avFw4jLP0Cc3s+zGNr384TWCiPiIiUJE5JwDhtGjz3HFStCr//DpUr233sNzbs550tCZy9lJn9vP5muobyiJQw1pwgQK5gpN9v63l17SyyygQR+MtOaNQoz3uVWVVE/EZ8PLRuDZmZsGIF3H23XW+LjU9k4se/cfZiZp7XlHvJNZRHpITJr9vy+063c6rzLQRmpMO//gVZWXneGxhgomPdyvRpWZOOdSsrCBGREs/m8ElWljEkk5kJd9wB//ynXfuKjU/ksaU7bAYhoNxL3qCUpxsghuhmEfRoEp63d+OBhtC0KcTFweuvw5gxnm6qiIjL5DfkvOjsFhr/8AOEhsKbb9pVk8uaHqEwOVcndqxr31CPOI96RLyIzd6NyEh45RVjg2eegf37PdtIEREXsQ5TX52wsfShg9Se9R/jwSuvQM2adu2vsOSPV1PuJc9QIFISDB0K3brBpUtG16TZ7OkWiYg4VZbZwnOf2ihdYbHwn9g5lMtM56frWpL1ryF279PRwEK5lzxDgYiXKHBJmckECxZA+fKwaRPMn++5hoqIuMAbG/aRlJo3cPjnb+vofOgX0kqVYVz3x9l28C+79+lIYKHcS56jOSJewK5luFFR8NJLMHIkPPUU3H471KmT7z61mkZESorY+ERmfb0vz/NVz59h8ob/AvBq54EcuqaGQ70c1uSPV6dHuJoJ5V7yJPWIeFh+Y6I2C949/jjceKNRY+GRR4yEPvnss/P0DQxYsJVRy3cWWMlXRMST8p1QarHwny/nEpZ+gV/D67GobR/AsV6OgpI/Wl1TrrSW7nqYAhEPylnw7mo2l5QFBMB//wvBwbBuHSxalOd9DgU2IiIelt+E0r67N9Jj/w9kBJTiydtHkxUQWKThk/zSI1QsW5ox3evz0+QeCkI8TEMzHlTYjG6bS8rq14cXX4Tx42HsWOjZE669Fig8sDFhBDY9moSrC1JEvIKtoZZq55J57uu3AHi9073srVoHKPrwSb7pEfR30CuoR8SD7B3rTEq5lPuJ0aOhfXtITYVHH80eonEksBER8QZ5hlosFmK+fIOKaef5Nbwe89v3B2BM9wbF6rlQ8kfvpUDEg+wd63zh899zD6kEBhrDMmXKwNq18N57gP2BjdbKi4i3uLqa+D9/+5puB34kPbAU424fw+XAUoSHBjHilnoebae4jgIRD7r6FzA/f13IyDu/o0kTzFOnApA5fCTbv/uNKhWC7Dqu1sqLiLfIOaG0ZupJpqxfAMCszgPZX7U2JuC5O5qqB8OHKRDxoJy/gAWxNXE1Nj6Rm8w3sDOiAaXPp3LhgUGMW/EzFcuVzjewMaG18iLifaKbRTDvvpbM/nIOoRkX2V6jEW+3u5NrypfmX53qEFa2jOrA+DAFIh5mndFdqXzpArfLOb/DujLm6PlMxv3fGNJKleGmgz/TY9Mqzl7MzJ6YmpP1sdbKi4g3it74P27482eyypYj7tlXqRhSljMXMvnvloNKQeDjFIh4gehmEUzp1dSubZNSLuVaGXOgciQvdRkMwNPfLKJu8lEqlitN9dDcwy/hYcFaKy8iHmcri3TW73swPzUBgM0PP8mrCRbOXMjI9T6lIPBdWr7rJcJD7Zu3ceZCRp6VMUva9KLb/m3ceGgnr37+Kv3vn8HcRzoREGDSUjUR8Rq2skhXCTKxZOEYmqansblOKx4qe4PN9yoFge9Sj4iXKGziqnV+RyUbE1ItpgDG/99ozgZXoGXiPkbEreD0hfRcS9WA/GvZiIi4WH7JFh9c9y5Nj//B2eAKPHn7KKO2Vj6UgsA3KRDxEgWlIs45vyO/npMTIVWYfOvjAIz4fgXXHdiV/ZpSvouIJ+WXbLH10d8ZvvUjAJ7uOYITIVXs2p9SEPgWBSJeJL9UxDnndxTUc/JZ45v4pEkXSlnMNJs4HC5cUMp3EfG4rX8m5/kbVD79IrM+f5VAi5n/Ne3K2kad7d6fUhD4FpPFkk/lNC+QmppKWFgYKSkphIaGero5blNY5VxrcAHkusIwAaFp59m6fAxlTyRifuQROtW5O99sqyaMIOe7CbdovFVEXCI2PpGJ//uNs5cycz0/fe1s7vltHUdDq3Hbv+ZwLqh8ofvS36ySw5Hzt3pEvFBhqYgL6jmZ/vBNlF22FICAt9+myfZN+R7HFeOttmbEi4h/sl40XR2E9Pzje+75bR1mTIztNdbuIASUgsAXFXnVzObNm5kxYwbbt28nMTGRVatW0bdv3+zXLRYLU6dOZcGCBZw9e5ZOnToxb9486tev74x2+72CizhFwLhx8OqrvLx2NtH/eoNTFfJPYuas8VZbM+IjwoKZ2ruJlg2L+Jn85oVUP3eal76YA8Bb7fuxLbKZXfsL198Sn1XkHpELFy7QokUL5s6da/P1l19+mddff5358+fzww8/UL58eXr27ElamiYZOUuBPSf//jcXGl9P5UupzPxsJiaLOd/9OGO8VXNRRCQnW0U4TRYzr34+i2vSzvFb9brMvPF+m++1/iUb070+s+9tyQdDO/DdhFsUhPioIveI3Hbbbdx22202X7NYLLz22mtMnjyZPn36APDuu+9SvXp1PvnkE+69916b70tPTyc9PT37cWpqalGbJ0FBBK9cwaWWrbnx0E6GblvF2+375drEOt5a3JTv+V35gNb+i/grWz2tj2z7mM6HfuFi6SBG9X6SzMDSlCsTSJlSAZy9eGX4Rr0f/sUlCc0SEhJISkqie/fu2c+FhYXRvn174uLi8g1EYmJimDZtmiua5JcCmzTmwDMv0Oy5J3ly87vE1WrObxHG0Jgzx1ttXfnklHMuijWniYj4tqt7Wpsn/sH4zUal8GndHuHPytcCsOCBG+hQt3KBE/TFt7lksmpSUhIA1atXz/V89erVs1+zZdKkSaSkpGTfjhw54orm+ZVmz44jqUcvSpuzeH3Ny5RPvwg4N+W7vXNMtPZfxH/kTDVQIf0ir386g9LmLD5v2IkVzW/NTtLY4e9h5YIm6Itv86oU70FBQQQF2VfKXuxkMhG+4l0sLVsSdfgwXxz4iGOz5jn1isPeOSZa+y/iP6xJGoe9t52Y2DnUOZvI0dCqTIoeienv7KlaASPgoh6R8PBwAE6cOJHr+RMnTmS/Jm50zTWYli6FgABqrfmIjnFfOPWX39709MWdiyIiJUt0swjWlN1D7z3fctkUwBN3PEVqcAUV4ZRcXBKIREVFER4ezvr167OfS01N5YcffqBjx46uOKQU5sYb4dlnjfuPPQZ79mS/VNzcH/amp9eVj4if+e03mk2fAsCxJyczaNwArYCRPIo8NHP+/Hn279+f/TghIYGdO3dSqVIlatWqxejRo3nxxRepX78+UVFRTJkyhRo1auTKNSJuNnkybNoE33wDd98NP/xA7IGzTsn9YU2ydvW+NPtdxE9duGD8nUlLg+hoasdMpXaAcmhKXkVO8b5x40a6du2a5/lBgwaxePHi7IRmb7/9NmfPnqVz5868+eabNGjQwO5j+GuKd5dKSoKWLeHECY70u5+b6g3Is+zW2m9RlK7TwtLTi0jxlJjfsYcegsWLoUYN2LkTqlb1dIvEjRw5f6vWjD9avx5Ljx6YLBZG9RrH6qZ5A0rVdBDxPiUme/G778KgQRAQABs2QJcunm6RuJlqzUjBunXj6PBxAPzny7lcl3w0zybW3B+LtySoboyIFygx2Yv37oXHHzfuT52qIEQKpR4RP3F1d27SXxcI79eLjod/4/eqdej7wKukly546bRXXnmJ+IEss4XO0zd4fyXtixehY0f49Vfo2hXWrYPAQM+1RzzGkfO3V+UREdew1Z1bqXxpAns/ydp3nqDxqYNMXf82T0ePLHA/1isvLbsTca8Skb3YYoFHHjGCkGrV4P33FYSIXTQ04+Py6849cyGTUxUqMabXOMyYuO+XL7kzfkOB+7J2nU1bs1vDNCJuVCKyF7/xxpXg48MPIUIXK2IfBSI+rKBidFbfRbVizj+M2j//+XIujU4mFLjPnFdeIuIeXp+9+LvvYOxY4/6MGZoXIg5RIOLDCuvOtXrv1gfZXKcVZS+nM++T/xCadr7Q96hujIj7eHX24uPH4Z//hMuX4d57YfRo97dBSjQFIj7M3mDhmd7NKPvhci6G1yTqr0ReWfsaJou5wPeoboyI+3ht9uKMDCMISUqCZs1g4UIwabm/OEaBiA+zN1gIDytL27YNKLfmEyxlynDrvq0M27rS5raqGyPiGdbsxeFhuX+vPVq3ZexY+P57CAuDVaugfHn3t0FKPK2a8WHW7tyklDSb80SsS/6yg4obbsA0dy4MHcq4b5fyW3h9vo1qlWt7UN0YEU+JbhZBjybh3pFZ9d13Ye5c4/7SpVCvnvvbID5BPSI+rEjduQ8/DEOGEGgx88aal7n2bFL2S6qYKeJ5gQEmOtatTJ+WNelYt7JngpCff4ZHHzXuT50KvXq5vw3iM5TQzA84nBY6LQ1uugl+/JELjZvxzX9XUbnaNd5b00JE3Cc5GW64AQ4ehNtvhzVrjFTuIjmo1ozk4XChrCNHoE0bOHUK7rvP6HrVJDQR/5aVZQQfX30FdevCjz/CNdd4ulXihZRZVfKwdufaLTISPvoIunWDZcugaVN4+mnXNfAqJabCqIg/mTrVCELKloWPP1YQIk6hQERyyRUAXNuM9rNfJ2DEcHjmGWjUCO66y+VtKDEVRkX8ySefwL//bdxfuBCaN/doc8R3aGhGsuUXACyPX0btZYugXDn49lto3dqlbRi2dEeeVT7WvhBNlhVxDod6HffsgXbt4Nw5I2HZrFlubauUPJojIg4rKAAINGcR9/0sqm7ZCDVqGOPCNWo4vQ0lpsKoSAnnUK/j6dPQoQMcOGBMYv/6ayhd2s0tlpLGkfO3pjpLgTVpLEBWQCADuo3G0rixkc65Tx+j3LeTOVJhVESKJr9CmNbq2rHxiVeeTE83hmMPHICoKFi5UkGIOJ0CER+UZbYQdyCZ1TuPEXcgudBKufYEAPvTS/HzG+9C5crw008weDCYzUU6Xn5KRIVRkRKssIsOyFFd22IxcoV8+y2EhsJnn0HVqu5srvgJTVb1MUWZ6Gnvif1IpQhar1plrKT56CNo1IjYu4c5bWKp11cYFSnhHOl17Pjh27BkCQQGGr/vTZq4r6HiV9Qj4kMc6nLNwaEA4MYb4e23jSdeeIEvnp7p8PHy49UVRkW8lCM9kvZedAR+vPLKcv05c+DWW53RVBGbFIj4CIe6XK/icAAweDDm8eMBeHntbFod2+PQ8fLjtRVGRbxUbHwinadvYMCCrYxavpMBC7bSefqGYl10NE/8gxumjDYejBoFw4Y5scUieSkQ8RHFmehZlADgh6FPsq5ee4KyMnl71YvUSD1p9/EK4pUVRkW8UFF6QAu76KiZepJFq14kID3NyKD66qsuaLlIbgpEfERxJ3o6GgCcvJjJqN7j2V0tiqoXzvLflc9TPj3vSpqiTCyNbhbBdxNu4YOhHZh9b0s+GNqB7ybcoiBE5G9F7QEt6KKjQvpFFq58nirnzsD118Py5cb8EBEX02RVH+GMiZ6OlBivFhLMxTJlebjfFFa/O5bGpw7y2mev8uidT2MOCMy1XVE4nJJexI84NOn0qt8j60VHzknmAeYs5sfOpPGpg1C9urFCJiTEhZ9A5AoFIj7C2uWalJJm8yrJmgyssIme9gYA1uMlUo1H7pzM8g8m0WP/DzzzzSJe6DbU7uOJiOO+3p1k13Zb9p+yeVGR66Ij9RLtXnueiD1bITgYVq+GWrVc2XyRXDQ04yPcPdEz5/F21mzE+NtHAzDkp9UM+fETpx9PRAyx8Yn8d8tBu7Z945sD+U5itV509Fm/nIh3FxhPvvsutG9f5LY5K6eQ+BelePcxjuYRKW6V25zHe+SH//H0xncA2DljPi3HP1r8DyQi2Qorg1AQ62/13PtacU35IE6eS6PxprU0GP2I8cLMmTBmTJHbpmKVkpNqzfg5e4MLZ/3hyD5e6iXazZpGxHsLoUwZiI2Frl2d8plEBOIOJDNgwdZi7SPABGYLdDz0C0s+nEoZ82UODhxKnffeLvI+VaxSrqZaM34uu8u1ZU061q2cbxBSlORnBR6v1bVEvDPfqE2RkcHlO/rwzYp16qItYdS97r2cUd7AbIGmJw7w9scvUsZ8mc8a3cgtNXo7nIDQqjg5jERAk1X9UmF/OEwYfzh6NAl3fI5HYCBfPf0KVXfsp9XBX2k65B76DZzB5dp11EVbAqh73bs5o7xB1JljLPnwWUIyLhFX63rG/t9YLKaAIv/OF2cFjwioR8QvubLKbWx8Io9+tJtBfZ7m96p1qHbhL5aumIz56LEipX0X93FmL5m4RmEJyQoTkXqK91ZMpsrFFH6rXpdH7ppMRqnS2b/zs9b94XAvmIpVSnEpEPFDrvrDkbOnJTW4Ag/e/TwHK0ZQ+2wS762YQsVLqeqi9VLqXi8Z7FkdV7FcaZuBSqWLKby3YgrXpp7iQKVrGXT385wLKp9rmze+2V9omvirqVilFJcCET/kqj8cV/e0nKpQiYH3vkhihco0SD7M4g+ncu7kmXx7Wjw5N8Hf50W4spdMnKugLMjzB7bmpbuuB3IHKhXSL7L4o6nUO3OUYyFVeeCe5zlTLizfYzjSC6ZilVJcmiPih5yV/OxqtnpQjoZVZ+A9L/Lhsgm0SNrHf//3PCfvaQVXjRXHxify3Ke7SUq9so/w0GCeu8P1cxM0L0Ld6yVNYVmQc2ZODcpMZ+H/nqd50n6Sy4bywD0vcDy0WoH7d2SumLWXZtjSHZgg198UFasUe6hHxA+5KvlZfj0oB6pE8uDdz5Naphztj8TTedIwyMjIfj02PpHHlu7IFYQAJKWm8ZiL5yZoXoRB3eslT0Gr46z1mpYPbsPGn+bT4Ug8meUrMOju50mofK1d+3ekF0zFKqU4FIj4KVf84Sioi3ZXeD0e7v8saaWDuGbj1/DAA5CVRZbZwsSPfytwv5M+/s0lQyWaF3GFutd9UFYWdSeMIGLzOsxBwQR89hkjxt+d53e+MPb2gqlYpRSVhmb8mCNF7uxRWBftj5HNiH99ETc8MRg+/BBCQ9n61H84ezGzwP3+dTGTrX8m06lelSK1Kz9adniFutd9S+wvRzE/9C9u/3kdmQGBPNrrKX6Pu8zU3vDdhFvYlnCGLftP8cY3BwrdlyO9YCpWKUWhHhE/Z0/yM0cU1tNyw2P3wfvvQ0AALFxI+bGjwI7kvnEHkovVLls0LyI3da/7hthfj5H6wEPc/vM6LpsCeKL3k2yo1y57uHHd7iQ61q3MmB4N7e4F8/fJ3OJa6hERpyu0p+Wf/4SLF+Ghh2j52Qc8fyyVZ3s8BqaCgiDn/+HTvIi8nN1LJu6VdTmL9CFDufu3r8kyBTC693i+aNQZyD0B9ZZG1dl+6C9uaxbOoi0HC+wFW7c7ye8nc4trKRARlyi0i3bQILBYsPzrXzz48+dYTDC1e/7BSMfrnDssA65bPVTS+UP3enGLPXoli4VTgx6mz09fkGUKYEyvsXzW+Kbcm2AMN3aIWc+ZC1cmjJtMuTsmw/8ONACbNWSsvSvqKRNncGkg8txzzzFt2rRczzVs2JA9e/a48rBSUgwejCXLjGXowwza8TkWTDzX/dE8wUjFcqXp4IITo+ZF+CefXK5tscATTxC+bDFmTIz7vzF82uTmfDfPGYSAUX8GYEinOnRvEp4dfHeevsE1pSBEcnD5HJGmTZuSmJiYffvuu+9cfUgpQQKG/Itd017BjInBOz5j6vq388wZeemu6532h+7qse4eTcI1L8KP+ORybYsFxoyBN97AYjLx5O2j+aSp41WvTcDa+KTs3iEluRN3cfnQTKlSpQgPD3f1YaQEu37KWH4Drn92HA9tXwPAtG6PEB4WzHN3NHVaMFDQlbB1JYFPddVLLi4t9ugpZjM88QTMnQuA5e0FfH+qDqZ8hhsLcvUqMU3mFndxeY/Ivn37qFGjBtdddx33338/hw8fznfb9PR0UlNTc93EP1w/ZSzmtxcA8ND2Nfxw+CO2PNXVqUFIQVfC1pUEzlo9JN7H567wzWZ47DEjCDGZYMECAh4ekm+yQntZAwtN5hZ3cWkg0r59exYvXkxsbCzz5s0jISGBG2+8kXPnztncPiYmhrCwsOxbZGSkK5snXiZg6MOwaBGYTFRf/i6B/3oILl8u9n6VuEzAx5ZrX75sTPhesMBYCr94MTz8MJD/MuxK5UvbtWtrYKEkd+IuJovFjiQOTnL27Flq167NzJkzGTJkSJ7X09PTSU9Pz36cmppKZGQkKSkphIaGuquZ4mkffJCdeZX+/eG99yC46FddcQeSGbBga+GHHdrBp1aL+OTKkGLwmZ+DS5fgvvvgk08gMBCWLoV7782z2dX//21qX0OXGd8Uukrsuwm3ZP+cWHsSwfZkbs2jkvykpqYSFhZm1/nbrct3K1asSIMGDdi/f7/N14OCgggKCnJnk8QbDRgAZcvCPffAypVw/DisWgXVCi7UlR+fuhK2k0+uDCkmn1iuffYs9OkDmzdDUBCsWGE8tsHWMmxHV4lZe1eu/lkK9/OfJXEut2ZWPX/+PAcOHCAiQj+8Uoi+fWHtWqhYEb7/Htq1g/j4Iu3K38a6fXJliBO4qtij2yQmQpcuRhASGgpffplvEJKfomTPVQ0ZcTWXDs2MHz+e3r17U7t2bY4fP87UqVPZuXMnu3fvpmrVqoW+35GuHfFRe/dCr16wfz+EhMDy5XD77Q7tIstsofP0DQ51SZdU1s+a36RMX/qsRVUie4v27YOePSEhAapXh9hYaNmyyLvTsJ24mtcMzRw9epQBAwaQnJxM1apV6dy5M1u3brUrCBEBoGFD2LrVmCuycSP07g2vvgqjRhWSEv4Kf0pcpkJ+hStxaex37IDoaDh1CurWha++guuuK9Yu/SF7rpQcLg1Eli9f7srdi7+oXNnohh4+HBYuNJI3/f47vPEGlLZvJYC/jHX743yYoigxJ+ING4xhynPnoFUr+OILo0dExIeo1oyUDGXKwNtvQ+PGMH68cX//fvjoI6hk3+TCEnclXAT+Nh/Gp61cCfffDxkZ0LWrsUpGQ9TigxSIiNsVeXzaZIKxY6F+fWP54oYN0KEDfPYZNGhg17FLzJVwEfnEyhCBefOMHkCLBfr1M5boFmMJu4g3UyAibuWUiYK9e8OWLca/+/YZwcjKlXDLLQ61xRcn7PnTfBhn8pqfhawsmDDBmAcFRubUN94w8oWI+Ci3JjRzlFbN+BbrstKrf+CKnBzpxAlj/HzrVihVCt58E4YOtbstJW7lhAN8/fM5k9d8VxcuGEMxq1cbj59/HiZPtntStog3ceT8rUBE3MJly0rT0uBf/zKysYIxkXXGjAKvIJ0eEHkpr7nK92Je87Nw7BjccYexQiYoyEjZbiNbqkhJ4cj5260JzcR/uazgWHAwvP++cfUIMGuWkeQpn4KJ/lR3xjofRoX8bPOan4UdO6B9e+PfqlXhm28UhIhfUSAibuHSZaUmE0yZYqS7Dg6Gzz+HTp3g4ME8m/pcBVYpMq/4WVixAjp3NnpEGjeGH36Ajh3temuW2cKWfad55cs9vPLlXrbsP+0TAbT4H01WFbdwy7LSu++GqCijizs+3rjKXLUK/vGP7E2UZ0OsPPqzkJpqrAD773+Nx7ffDsuWQViYXW+PjU9k4se/cfZiZvZzb3yzn4rlSvPSXdf7xNCi+A/1iIhbuK2keNu28OOPRvrrkyeN/Avvv5/9svJsiJXHfhbWr4frrzeCEJMJJk6ETz91KAh5bOmOXEGI1dmLmTzmx/WEpGRSICJu4daCY9deC999Z6yoyciAgQONoRuz2X0BkXg9t/8snD8Pjz8O3bvD4cNGmvZNmyAmxu7luVlmC899uqvQ7XxlnpP4BwUi4jZFqfxZZOXLw//+Z1xtArz4ItxzD4Fpl0p2BVZxGrcGx5s3Q4sWRqIyMAKSX36BG290aDfbEs6QlJpe6Haa5yQlieaIiFu5Nc16QIBxtdmwITzyiJH07OBBolev9ou6M1I4l9cgungRnnkGZs82sqTWqgWLFkG3bkXanSPzVTTPSUoKBSLidm5Psz54sFG19M474aefoF07oj/9lB4TblGeDXFdcBwXZ/zs/fGH8fjhh42MqcXIieTIfBXNc5KSQoGI+Icbb4Rt26BXL6Ny7403EjhnDh0fekiZK8W5wXFaGkydCq+8AmYz1KhhVI2+7bZcm+WXcK6gRHTtoioRHhpU6PCM5jlJSaJARPzHddcZV6n33guxsTBkiPHvW2/BNdd4unU+we+zuf70EwwaBLt3G48ffBBeey3Pz1d+aeXvaBHBp78k5ptuPjDAxHN3NOWxpTsKbIbmOUlJohTv4n/MZuNq9Zln4PJliIyE996DLl083bISzWtqtnhCRga88IIxJykrC6pXh7ffNnLaXCW/tPL5sZVu3lYeEYBrypUmRnlExAuo1oyIPX78Ee67D/bvN4Znxo41Vtd4oNx6Se9J8JqaLZ7wyy9GL8gvvxiP773XqJhbOe9QT2E1l/JjqxZTltnC1gPJxP15GjCGljpcp1T+4h0UiIjY69w5IwBZuNB43LSpUXDshhvc1gRX9CS4M7BxWUFDb5eZCS+9ZNQ5unwZqlQxluf275/vW+IOJDNgwdYiH/KDoR3cO9FbpIgcOX9rjoj4t5AQWLAAeveGoUNh1y7o0AGefNKYcOji3pH8ehKSUtIYtnRHkXoS3D1E4kjNFp85ie7aZfSCbN9uPL7zTpg/H6pVK/BtxV1SqyW54ouU0EwEjLH8XbuMbvWsLONKt3VrowiZi7ii+qs1sLk6MLAGNq5I/e1X9XuysuDll42fje3bjUmo779vJM8rJAiB4i+p1ZJc8UUKRESsqlSBDz64clL5/XejEurIkZCS4vTDObv6q6fK2pfk+j1ZZgtxB5JZvfMYcQeSC/5u9u41KuVOmGBMTv2//zOKK953n91LwAtLK58flR4QX6ZARORqd91lLL984AEjG+Ybbxgl2j/80HjsJM7uSfBUWfuSWr8nNj6RztM3MGDBVkYt38mABVvpPH1D3l4js9lYgtuyJWzdaiQkW7QI1qwxcoQ4oKC08vlR6QHxdQpERGypXBnefRfWrYP69SExEe65B6KjYd8+pxzC2T0JnhoicWvNFiexewjrwAG4+WYYM8ZIVHbrrUYvSDES4eVXc8nq6q/JJbWYRLyIAhGRgnTvDr/+Cs89B2XKwFdfGStrxo2Ds2eLtWtn9yR4cojErQUNi8meIaznV8djnjsXmjeHb781iijOn28kwIuMLHYboptFMOX/mth8zTo6NKRTHT4Y2oHvJtziVd+fiLNp+a6IvfbtgyeeME5GYPSaPP+8UVCvVNEWoFmvzIFcJ8ai5N+wLqNNSkmzeZJ1xzLakpAPpbAltDVTTjL9i9l0PvR3XpCbbzaGYqKinNYGv13yLH7DkfO3ekRE7FW/PnzxhXFr3BiSk2H4cKO8uzU4cZAzexK8YYjEWrOlT8uadKzrncm18h2asli455cviV00nM6HfuFycDC8/jqsX+/UIAQ8N59HxBspj4iIo6KjjSGbt94yco3s3m0UNOvRAyZPNgrsOTB/oCjVX/PreXB5WXsfUKVCUJ7nmibtZ9LGd7J7QX6q2ZjAJYtp1a2dS9rgV0ueRQqhQESkKEqVMnpD7rvPqDEyZ44xsXXdOvjHP+Dpp+H22+0OSByp/lpYwjKXlbX3AbHxiTz36a7sx/VPHWL0lmX8394tAKQHluaVmx5gbbd72Ny1rcvaUZKXPIs4m+aIiOTDofkOf/5pJLp65x0jxwQYEx0nTYJ//hMCA53SJnfUdCkJ8zyKIud3V+/0YZ74fjm9fv+WACyYMfFJ05t5rfP9HKkY7vIJtmt/Pc6ID34mv7QlmiMiJZ1qzYgUkyNp0nOeuGte/IvWHy8m4K234Px5Y4O6dY0kWA8+CEF5hwXs5Y4Jjr5aQTfLbKHzS+upvudXhm77mNv2fk/A3+Hc2gb/4LXO9/FH1Tpu+az2VN814eOFAsXnKRARKQZHeh3yO3G/eFME3Tb8D2bPNia1gpH8atw4Y5VNhQoOt8vegmlFLYzmsxV09+3jyBsLyVj6PnXPHMt++sv6HZjd6T52V78u+7n3h7SnU/0qLmuKPdV3A0zwxoDW3N68BH7XIn/TqhmRInIkTXpBSbEeXpNA7J0Pw6FDMGsW1KwJx48bgUjt2jBtGpxxbEWEKyc4Fva5LcDE//3Glv2nnZ4i3iVOnDCCwHbtoEEDIl9/mbpnjnGpVBAfN+3Krf96g0fvmpwrCAE4fSHdpc0qbLUMGHlErilfxqXtEPEmCkREcrB3WeXWA8n2BSxly8Ho0UaGzoULjSXAZ84YCdJq1TICk/377WqbKyc42nOCPHspk/sX/mA7Dbo3OHfOyIbbs6fR+zR6NPz4IwQEcLZzV8b+3xhuGPEeY3uN44+qdWzuwtWTQ7VaRiQvBSIiOdh7Aoj787RjeSCCgmDIEKOQ3ooVRt2SCxdg5kwjOLnlFqPgXlr++3RlTRdHTnyFVfJ1qJBccWVkGDVf7r0XqleHQYOM7Ldms9EbMns2HD9OyKb1xHX6Py4GlbO5G3fVw9FqGZG8tHxXJAf7TwD2TQbNc4IPDIS77zZW0sTGGst+Y2Phm2+MW1iY8drAgUY+koAr1wrWhGXDlu7AhO1MrEVNWObIic/y9/GmrdlNjybhuY7nlsmuZjNs2QLvvw8ffZR7iKtBA7j/fhgwwAjw/hYILvvuHGENJgvLfuttBQJFXEk9IiI52NvrYO9k0HxP8CaTkQRt7Vo4eNBIjBYZCSkpxhDOzTeTfm0t9j/4GPEfriXrchbgupoujpant5X50+5CckUVH28sh46KgptuMhLKnTkD4eFXhmH27IFnn80VhFj1aBLO6O4NCCtbOtfz7qyH4w3Zb0W8jVbNiFwlv/ovVkM61eGWRtUZ99EvnEh1Yl0Xsxk2b+bInLe55vPVVEi/mP1ScoVruHBbL2oNuR9uvpms0mWcnuujsM9ty+x7W9KnZU3XLS0+fNgYslq2zCg+aBUSAv36GQnlbrml0DwttnpqKpYtzUOd6jDilvpuP/H76jJpESst3xUpJlsnigATuRJQVSxXmrMXM/Pt6i/KVbY1GChzOYOuB34k+o/vuWX/j4RmXAlKKFfOKMQWHQ1duhjVgJ2YMO3qz10Q61Jhpy4tPnMGVq40hl42b77yfOnSRrba+++HXr2gbFm72uity5J9NXGcCDh2/tYcEREbejQJJySoNHF/nubAqQt8EZ+UJwtmysVMAML+DkisilrXJecS2vRSZYht2InYhp0onZVJx0O/0nNfHLce+JGq55KNIZ21a403hoQYEzM7djRuHTpApaLNMbCmh996IJnhy3Zw9lKmze2unstQ5NUgFgskJsIvvxi377835sxk5jhuly5Gz0f//g5/rsKWJec318UdHEnrL+LLFIiIXMXeXgHriSy4VADvP9ye0+fTi3Vlm98S2szA0my+rg2br2vDMxYLq28MocXuH4y6Nlu3GstW1683blYNG14JTFq0MHKXVKuWa/JrfgIDTHSqX4WX+l1vc6jG1lwGeya7Bl3OoM7hP2DnOmOYxRp8WBO+5dS8+ZVJp5GRhe47P45UuVVQIOIZCkREcrAn/XZOFiApNZ0Ak4k+LWsW69h29SqYTBy8th4tenWBp56CrCxjEmdc3JXbvn2wd69xW7z4yntLlzbya1x7bf638HCjoB84VMn3rwvpBGAhOCONKhfOUv18MhHnTnNtykkanD5E45MJ1E0+SqlXzXk/U0CAETi1aGHcevWCZs2K+jXmorwdIt7P5YHI3LlzmTFjBklJSbRo0YI5c+bQrp1rSmuLFEdB3fiFccaJrEg5JgIDr5zAH3vMeO70aaOnJC4Otm2D3buN4Y/MTCPT66FD+e88IAAiIoxMsKGhRAcF0bNMEMnpWaRfNhMUGEDloABMmy8ZOU8uXeJc8llaJ53i90vnCMqyPZRjdTa4AlnXN6fyP9oavR4tWkCTJnbP93CU8naIeD+XBiIrVqxg7NixzJ8/n/bt2/Paa6/Rs2dP9u7dS7Vq1Vx5aBGH2ZNdND/OOJE5LcdElSpGr0KvXleey8yEpCQ4etT27dgx43b58pX7OY5bUPWVkL9vVpdKBXGywjUcD63K8ZAqHKgcye/Vovi9ahQnQioTXrGs26rKKm+HiPdzaSAyc+ZMhg4dykMPPQTA/Pnz+fzzz1m0aBETJ07Ms316ejrp6VdqPaSmprqyeSK5FKVXw5knMlcmLKN0aWOuRUHzLcxmOHnySmBy/rzR65GebgwBgZH/pHRpCA6GsmXZ81cG0zYe5lxQec6WDeGv4BAulClrbJcPd87JcOl3KiJO4bJAJCMjg+3btzNp0qTs5wICAujevTtxcXE23xMTE8O0adNc1SSRAjnaq+GKE5kj8zKcLiDAmCMSHg433GDXW/buPEZcwk6HD+XOORke/U5FpFAuC0ROnz5NVlYW1atXz/V89erV2bNnj833TJo0ibFjx2Y/Tk1NJbIYM+ZFHFFYN/7VXHUisy6h9fYcE1lmC6fPFa1arbvnZJSU71TEH3nVqpmgoCCCgoI83QzxU4V141uAMd3rU6dKeZefyLw9x4Sjic+sPDknw9u/UxF/5bJApEqVKgQGBnLixIlcz584cYLw8HBXHVakWNSNXzhHlzhbaU6GiNjiskCkTJkytGnThvXr19O3b18AzGYz69evZ8SIEa46rEixqRs/f44scb46Jb6CORGxxaVDM2PHjmXQoEHccMMNtGvXjtdee40LFy5kr6IR8VbqxrfN3iXOU/6vMQ90rMP2Q38pmBORArk0ELnnnns4deoUzz77LElJSbRs2ZLY2Ng8E1hFpGSwd7VLlZAgypQKUDAnIoVy+WTVESNGaChGxEfYu9rl4OmLhW8kIgIUXgFLRORv7aIqER5a+Mq25T8eJuvqcsUiIjYoEBEpIbLMFuIOJLN65zHiDiS7/USfZbawLeEMrWpVLHRba/ZUEZHCeFUeERGxzVbejgg3rkIpSt4QVbQVEXuoR0TEy1nzdlwdBCSlpDFs6Q5i4xM9cvzCOJo91dM9PiLiGeoREfEA6zBHYUtbC8rbYcFIEjZtzW56NAl3ydJYR/KGWBUle6qne3xExHMUiIi4mSMn3cLydlhwTTVba6C0Zf8ph3pCipI9Nb9MrdYen3kDWysYEfFhCkRE3MjRk6698yycOR+jqHVkwPHsqZ7u8RERz1MgIuImRTnp2jvPwlnVbItaR2ZE13p0qlfF4eypnurxERHvoUBExE0cOem2i6rEtoQzJKVcolL5Mvx1IcNmcODMarbFmQ8ypkeDIvVYuLPHx955OSLiXgpERNzE3pPput1JjP1wZ6FDI86uZmtvHRlnHt9dPT6aDCvivbR8V8RN7D2ZLtpy0K6AIDws2KkTOR3tdXDG8dtFVSIiLJj8whgTRsBQnB4fTy9/FpGCqUdExE2sJ92klLR8hz8CTFBQ+oxK5UszpVdTwkOdP7Rgb6BU1PkgtgQGmJjauwnDlu7ABLm+F2f0uGgyrIj3U4+IiJtYT7pAnh4A6+PCcniduZBJeGgwHetWdvqJ097eiTE9Gjj1+NHNIpg3sDXhYbkDIWf0uDgyL0dEPEM9IiJuZD3pXj1fITwsmNubhfPfLQcL3YerUqe7uneiINHNIujRJNzpk0k9sfxZRByjQETEzfI76W5LOGNXIOKspbr5tS2/QMnVEzsDA0xOX6Lr7uXPIuI4BSIiHmDrpFvYHBJnLtUtiKt6JzzBW75TEcmf5oiIeAl75pC4amjEVls61q1Mn5Y1XTIfxV286TsVEdsUiIh4EVdO3PRX+k5FvJvJYrF4ba3t1NRUwsLCSElJITQ01NPNEXEbZQF1Pn2nIu7jyPlbc0REvJArJm76O32nIt5JQzMiIiLiMQpERERExGMUiIiIiIjHKBARERERj1EgIiIiIh6jQEREREQ8RoGIiIiIeIwCEREREfEYJTQTkXwpG6mIuJoCERGxKTY+kWlrdpOYkpb9XERYMFN7N1F9FhFxGg3NiEgesfGJDFu6I1cQApCUksawpTuIjU/0UMtExNcoEBGRXLLMFqat2Y2tapjW56at2U2W2WvrZYpICaJARERy2ZZwJk9PSE4WIDEljW0JZ9zXKBHxWQpERCSXk+fyD0KKsp2ISEEUiIhILtVCgp26nYhIQRSIiEgu7aIqEREWTH6LdE0Yq2faRVVyZ7NExEcpEBGRXAIDTEzt3QQgTzBifTy1dxPlExERp1AgIiJ5RDeLYN7A1oSH5R5+CQ8LZt7A1sojIiJOo4RmImJTdLMIejQJV2ZVEXEpBSIikq/AABMd61b2dDNExIe5bGimTp06mEymXLeXXnrJVYcTERGREsilPSLPP/88Q4cOzX4cEhLiysOJiIhICePSQCQkJITw8HBXHkJERERKMJeumnnppZeoXLkyrVq1YsaMGVy+fLnA7dPT00lNTc11ExEREd/lsh6RJ554gtatW1OpUiW+//57Jk2aRGJiIjNnzsz3PTExMUybNs1VTRIREREvY7JYLHaX0Jw4cSLTp08vcJvff/+dRo0a5Xl+0aJFPProo5w/f56goCCb701PTyc9PT37cWpqKpGRkaSkpBAaGmpvM0VERMSDUlNTCQsLs+v87VAgcurUKZKTkwvc5rrrrqNMmTJ5nt+1axfNmjVjz549NGzY0K7jOfJBRERExDs4cv52aGimatWqVK1atUiN2rlzJwEBAVSrVq1I7xcRERHf45I5InFxcfzwww907dqVkJAQ4uLiGDNmDAMHDuSaa65xxSFFRESkBHJJIBIUFMTy5ct57rnnSE9PJyoqijFjxjB27FiH9mMdNdLqGRERkZLDet62Z/aHQ3NE3O3o0aNERkZ6uhkiIiJSBEeOHOHaa68tcBuvDkTMZjPHjx8nJCQEk8l/C21ZVw8dOXJEk3bdRN+5++k7dz995+7nL9+5xWLh3Llz1KhRg4CAglOWeXXRu4CAgEIjKX8SGhrq0z+43kjfufvpO3c/fefu5w/feVhYmF3buTSzqoiIiEhBFIiIiIiIxygQKQGCgoKYOnVqvhlpxfn0nbufvnP303fufvrO8/LqyaoiIiLi29QjIiIiIh6jQEREREQ8RoGIiIiIeIwCEREREfEYBSIiIiLiMQpESqj09HRatmyJyWRi586dnm6Ozzp48CBDhgwhKiqKsmXLUrduXaZOnUpGRoanm+Zz5s6dS506dQgODqZ9+/Zs27bN003yWTExMbRt25aQkBCqVatG37592bt3r6eb5VdeeuklTCYTo0eP9nRTPE6BSAn11FNPUaNGDU83w+ft2bMHs9nMW2+9xa5du5g1axbz58/n6aef9nTTfMqKFSsYO3YsU6dOZceOHbRo0YKePXty8uRJTzfNJ23atInhw4ezdetW1q1bR2ZmJrfeeisXLlzwdNP8wo8//shbb71F8+bNPd0U72CREmft2rWWRo0aWXbt2mUBLD///LOnm+RXXn75ZUtUVJSnm+FT2rVrZxk+fHj246ysLEuNGjUsMTExHmyV/zh58qQFsGzatMnTTfF5586ds9SvX9+ybt06S5cuXSyjRo3ydJM8Tj0iJcyJEycYOnQo7733HuXKlfN0c/xSSkoKlSpV8nQzfEZGRgbbt2+ne/fu2c8FBATQvXt34uLiPNgy/5GSkgKgn2s3GD58OP/3f/+X6+fd33l19V3JzWKxMHjwYB577DFuuOEGDh486Okm+Z39+/czZ84cXnnlFU83xWecPn2arKwsqlevnuv56tWrs2fPHg+1yn+YzWZGjx5Np06daNasmaeb49OWL1/Ojh07+PHHHz3dFK+iHhEvMHHiREwmU4G3PXv2MGfOHM6dO8ekSZM83eQSz97vPKdjx44RHR3NP//5T4YOHeqhlos41/Dhw4mPj2f58uWebopPO3LkCKNGjeL9998nODjY083xKqo14wVOnTpFcnJygdtcd9113H333axZswaTyZT9fFZWFoGBgdx///0sWbLE1U31GfZ+52XKlAHg+PHj3HzzzXTo0IHFixcTEKAY3lkyMjIoV64cK1eupG/fvtnPDxo0iLNnz7J69WrPNc7HjRgxgtWrV7N582aioqI83Ryf9sknn3DnnXcSGBiY/VxWVhYmk4mAgADS09NzveZPFIiUIIcPHyY1NTX78fHjx+nZsycrV66kffv2XHvttR5sne86duwYXbt2pU2bNixdutRv/1i4Uvv27WnXrh1z5swBjOGCWrVqMWLECCZOnOjh1vkei8XCyJEjWbVqFRs3bqR+/fqebpLPO3fuHIcOHcr13EMPPUSjRo2YMGGCXw+LaY5ICVKrVq1cjytUqABA3bp1FYS4yLFjx7j55pupXbs2r7zyCqdOncp+LTw83IMt8y1jx45l0KBB3HDDDbRr147XXnuNCxcu8NBDD3m6aT5p+PDhLFu2jNWrVxMSEkJSUhIAYWFhlC1b1sOt800hISF5go3y5ctTuXJlvw5CQIGISIHWrVvH/v372b9/f55gT52JznPPPfdw6tQpnn32WZKSkmjZsiWxsbF5JrCKc8ybNw+Am2++Odfz77zzDoMHD3Z/g8SvaWhGREREPEYz7kRERMRjFIiIiIiIxygQEREREY9RICIiIiIeo0BEREREPEaBiIiIiHiMAhERERHxGAUiIiIi4jEKRERERMRjFIiIiIiIxygQEREREY/5f/7aXHaT46BdAAAAAElFTkSuQmCC" + ] }, "metadata": {}, "output_type": "display_data" @@ -1390,7 +1388,18 @@ ] } ], - "execution_count": 50 + "source": [ + "# Answer for Exercise 11\n", + "y2_predict = poly2_reg.predict(X2)\n", + "plt.scatter(x, y, label=\"Sample\")\n", + "plt.plot(x, y2_predict, color=\"r\", label=\"Regression\")\n", + "\n", + "plt.legend()\n", + "plt.show()\n", + "\n", + "y2_1 = poly2_reg.predict([[1, 1]])\n", + "print(\"The estimated value for x=1 is\", y2_1) # add your code" + ] }, { "cell_type": "markdown", @@ -1401,16 +1410,13 @@ }, { "cell_type": "code", + "execution_count": 45, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:48:21.636481Z", "start_time": "2025-01-22T09:48:21.632962Z" } }, - "source": [ - "print(\"The estimated coefficients are a=\", poly2_reg.coef_[0], \", b=\", poly2_reg.coef_[1], \"and c=\",\n", - " poly2_reg.intercept_)" - ], "outputs": [ { "name": "stdout", @@ -1420,7 +1426,16 @@ ] } ], - "execution_count": 45 + "source": [ + "print(\n", + " \"The estimated coefficients are a=\",\n", + " poly2_reg.coef_[0],\n", + " \", b=\",\n", + " poly2_reg.coef_[1],\n", + " \"and c=\",\n", + " poly2_reg.intercept_,\n", + ")" + ] }, { "cell_type": "markdown", @@ -1431,13 +1446,13 @@ }, { "cell_type": "code", + "execution_count": 46, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:48:26.904691Z", "start_time": "2025-01-22T09:48:26.902199Z" } }, - "source": "print(\"Quadratic error for the 2nd degree polynomial regression\", np.sum((y - y2_predict) ** 2))", "outputs": [ { "name": "stdout", @@ -1447,7 +1462,12 @@ ] } ], - "execution_count": 46 + "source": [ + "print(\n", + " \"Quadratic error for the 2nd degree polynomial regression\",\n", + " np.sum((y - y2_predict) ** 2),\n", + ")" + ] }, { "cell_type": "markdown", @@ -1469,12 +1489,33 @@ }, { "cell_type": "code", + "execution_count": 53, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:51:54.357008Z", "start_time": "2025-01-22T09:51:54.285099Z" } }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0. 1.05815835 1.00300147] 0.45741832011044625\n", + "The estimated coefficients are a= 1.0030014670964105 , b= 1.0581583492954199 and c= 0.45741832011044625\n" + ] + } + ], "source": [ "from sklearn.preprocessing import PolynomialFeatures\n", "\n", @@ -1492,69 +1533,37 @@ "\n", "# Plotting the estimated polynomial\n", "plt.scatter(x, y)\n", - "plt.plot(x, poly2_bis_reg.predict(X2_bis), color='r')\n", + "plt.plot(x, poly2_bis_reg.predict(X2_bis), color=\"r\")\n", "plt.show()\n", "\n", "# estimated coefficients (Pay attention to the order)\n", "print(poly2_bis_reg.coef_, poly2_bis_reg.intercept_)\n", - "print(\"The estimated coefficients are a=\", poly2_bis_reg.coef_[2], \", b=\", poly2_bis_reg.coef_[1], \"and c=\",\n", - " poly2_bis_reg.intercept_)" - ], - "outputs": [ - { - "data": { - "text/plain": [ - "
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aZk7+fQlx0ST1bU7vlgkmjkxEREJewdmQBx80ipiFubBamklOTWPw3I2FghCA9MwcBs/dSHJqmkkjExGRsLBiBaxZA1FR8PjjZo8mKIRNIJJnszNh8WbsTh5z3Ddh8WbybM6OEBER8QHHTpmBA40GdxI+gci6nUeLzIQUZAfSMnNYt/No4AYlIiLh44cfYPlyKF8eRo82ezRBI2wCkUPZroMQb44TERHxiCM3pH9/qF/f3LEEkbAJRGrFuNdW2d3jRERE3LZ+PSQnQ2QkjBlj9miCStjsmumYWI2EuGjSM3Oc5olYgPg4YyuviIiEN5+XeXDkhtx5JzRq5JtBhgivZ0QmTZpEhw4diImJoVatWtxwww1s3bq10DE5OTkMGTKE6tWrU6VKFW6++WYOHjxY6kF7IzLCQlLf5oARdBTkuJ3Ut7nqiYiIhLnk1DS6TV7OHTPX8tj8Tdwxcy3dJi/3fmflL7/AF1+AxQJPPunbwYYArwORlStXMmTIENauXcvSpUvJzc3l6quv5sSJE/nHDB8+nMWLF/PJJ5+wcuVKDhw4wE033eSTgXujd8sEZvRrR3xc4eWX+LhoZvRrpzoiIiJhzi9lHhwddm+9FZo29cEoQ4vFbrf7ZL/q4cOHqVWrFitXruSyyy4jMzOTmjVrMm/ePG655RYAtmzZQrNmzUhJSaFz585FXsNqtWK1WvNvZ2VlUa9ePTIzM4mNjfXFMAFVVhURkaLybHa6TV7ucoelYwl/9egr3T9nbNoEbdsa13/9FS6+2CdjDXZZWVnExcW5df72WbJqZmYmANWqGTkWGzZsIDc3lx49euQf07RpU+rXr09KSorT15g0aRJxcXH5l3r16vlqeIVERljo0qg617c5ny6NqisIERER/5R5eOop47+33x42QYinfBKI2Gw2hg0bRteuXWnZsiUA6enpVKhQgapVqxY6tnbt2qSnpzt9nbFjx5KZmZl/2bt3ry+GJyIiUiKfl3lYvRqWLDF2ykycWIqRhTaf7JoZMmQIqamprF69ulSvExUVRVRUlC+G5Hda3hERCS0+LfNgt8PYscb1gQOhceNSjCy0lToQGTp0KF9++SWrVq2ibt26+ffHx8dz+vRpjh07VmhW5ODBg8THx5f2bUvnzBl47z3o0AFatfL46WqcJyISenxa5iE52ZgRiYqC8eN9PdSQ4vXSjN1uZ+jQoSxcuJDly5eTmJhY6PH27dtTvnx5li1bln/f1q1b2bNnD126dPF+xL7wxBNw//1ebaNS4zwRkdDkszIPNtvZ88vQoXD++T4dZ6jxetfMww8/zLx581i0aBFNmjTJvz8uLo6KFSsCMHjwYJYsWcKcOXOIjY3lkUceAeCHH35w6z08ybr1yPbtxhaqvDwjYu3a1a2n+SWjWkREgkqpZ70XLDCSU2NiyNu+g3XZEWG3jO/J+dvrQMRicf5Bvvvuu9x7772AUdBs5MiRfPTRR1itVnr16sWbb77p9tKM3wIRgAcegJkz4fLL4bvvjEIzJUjZkcEdM9eWeNxHgzrTpVF1X4xSRERM4HUeYG4utGgB27ax7eFR3FO3d1gu4wckEAkEvwYie/cayUNWK3z7LfTsWeJTFm3az2PzN5V43LTb23B9G03FiYiEnZkz4YEHsFarTvt7ZnA8qlKhhx2hTKgX0TSljkiZU68eDB5sXH/ySSPDuQRqnCciIi7l5MCECQDM6HJrkSAEyE+CnbB4M3m2oJ0HCKjwDUTA2FpVuTL89BMsWlTi4Y6MaleTcxaMaTc1zhMRCUNvvgn792NNOJ8ZTV3PsntVGC2EhXcgUqsWDBtmXB83zkheLYYa54mIiFNZWfD88wBsHjQMa7kKJT7F7cJoIS68AxGAUaOgalX4/Xf46KMSD1fjPBERKeLVVyEjA5o0IefOu916ipbxDeGbrFrQCy8YyzQNG8KWLVC+fIlPUWVVEREB4MgRSEyE48fh44/Ju/kWuk1eXmJhtFAu9aBkVU898gjUrg1//gmzZ7v1FDXOExERACZNMoKQtm3h5pu1jO8hBSJgJKw6OiQ++yycOmXueERExC/ybHZSdmSwaNN+UnZklH7nyt69MH26cf355yHCOK1qGd99WppxsFrhootgzx545RUYMcK/7yciIgHllz5hgwbBrFlw2WWwYkWR4pjhuoyvgmbemj3b6JJYo4axTBMT4//3FBERv3P0CTv3hFeqAmP/+x80b27suFyzBv7xD18MNSQoR8Rb99xjzIocOQJTppg9GhER8YE8m50Jizc7TRwtVYGx8eONIKRPHwUhpaBApKBy5YwcEYCXXzYCEhERKdPW7TzqslkpeFlg7OefjeZ2AM89V7oBhjkFIue65RYj8zk7G/7v/8wejYiIlJK7hcM8KjDm2OBwxx3QurUXoxIHBSLnioiAyZON62++Cbt3mzseEREpFZ/3Cfv+e/j6a2MWfeLEUoxMQIGIcz17wlVXwenTxhqgiIiUWT7tE2a3GwUwwdjccOGFvhpm2FIg4soLLxj//eAD+PVXc8ciIiJe82mBsa+/NnbIREfD00/7dJzhSoGIK5dcArfeakS/Tz5p9mhERKQUfFJgzGY7ez4YOhTOP98PIw0/qiNSnG3bjD3iZ87AypVGwRoRESmzSlVgbP58Izk1NtaoNVW9un8HW4apjoivNG5sVM0DeOIJY3ZERETKLK/7hOXmnl2KGTVKQYgPKRApQd64p8mrVBl+/JH/vT679H0JRESk7JkzB7Zvh5o1Ydgws0cTUhSIFCM5NY1u721mWrsbAIhKGkf3/0smOTXN3IGJiEjgnDoFEyYY1598Uu0/fEyBiAuOvgRpmTnM6nADhyqfxwXH0umxYiGD525UMCIiEi7efBP274d69eChh8weTchRIHKOPJudNduOMOY/v+X3IDhZoSKvdrsLgEd+mE9MznHv+hKIiEjZkpkJkyYZ1595xti2Kz6lQKSA5NQ0uk1ezl3//pFjp3ILPfZJq578r3p9zsvJ5uGUj93qS5Bns5OyI4NFm/aTsiNDgYuISFkzaRJkZEDTpkZjVPG5cmYPIFi4ahHtkBcRyaTuA3j30wkM2LCYD9r1KbYvQXJqGhMWby7UaCkhLpqkvs09bzUtIiIlKtXWXGd278Y+dSoWYO3gMdh3Z5b+NaUIBSIU3yK6oO8aXsIP9Vvxjz2/MmrV+9QadZ3T41wFNemZOQyeu9H94jkiIuIWf3z52z90JOdbraTUv5g79leHmWv1hdIPtDRDyS2i81ksPN/9PgBu3LyCjkd3FjmkuKDGcZ/yS0REfKfg5oKCHF/+vNlc8MPH33D+l/8B4P+6DwSLpdSvKc4pEMGz1s+/x1/I582vACBydNEiZyUFNXZwK79ERERK5o8vf3l5NiqOfgKAz5tfTmr82cZ2+kLpewpE8KD1M0ZfgqpTXoQKFeC772DJkkKPuxvUeBL8iIiIc/748rf9rfdpu+tXTpWLYvLl9/rkNcU1BSKU3CIaoGrF8nx4fydWj76SK67uAI8+ajzw+ONG6d+/uRvUeBL8iIiIcz7/8peTQ91JSQC80/Em0mJrlv41pVgKRCi5RbQFeOHmi+l6YY2z2dJPPQU1asAff8Dbb+cfX1JQY8FIoOqYWM3HP4WISPjx+Ze/adOovH8P6VWq8Vanm33zmlIsBSJ/87hFdNWqMHGicT0pCf76Cyg5qAFI6ttc279ERHzAp1/+0tPh//4PgLevGUROBeeBhr5Q+pbFbg/elrKetBH2FY/2oZ85A23awO+/G02QpkzJf0h1REREAsOxawYolLTq+MvtdsmEQYNg1izo0IHkWQsZPG9T6V8zTHly/lYgUlpLl8LVV0O5cpCaCk2a5D/k8+I6IiLiVKm//G3aBO3aGTsh16yBf/xDXyhLQYFIoPXtC19+CX36wOLFZo9GRCQsef3lz26H7t1h5Uq4/Xb46KPSv2aYUyASaFu3QsuWxlLNt99Cz55mj0hERNy1cCHcdJPR0G7LFrjgArNHVOZ5cv5WsqovNGkCQ4YY10eMMAISEREJflYrjBplXB81SkGICRSI+Mr48VCtmpEnMmuW2aMRERF3vPYa/PknJCTA6NFmjyYsKRDxlWrVYMIE4/rTT0NmprnjERGR4h08CM8+a1yfNAmqVDF3PGFKgYgvPfggNG0KR47Ac8+ZPRoRESnO+PGQnQ3t28Pdd5s9mrClQMSXypeHV181rk+bBtu3mzseERFx7pdfzi6jT50KETodmsXrT37VqlX07duXOnXqYLFY+Pzzzws9fu+992KxWApdevfuXdrxBr28Xr3567KrIDeXow8OVXdGEZFgY7fD8OFgs8Gtt0K3bmaPKKx5HYicOHGC1q1bM336dJfH9O7dm7S0tPzLRwX2Zoei5NQ0uk1ezi0X3UJuRCTVln/DqIEvkJyaZvbQRETE4YsvjO7pUVEwebLZowl75bx94jXXXMM111xT7DFRUVHEx8d7+xZliqPEsB2gej3mtO/LoPWfM/SLN7mmRjNe699JlfhERMxWcLvuiBHQoIGpwxE/54isWLGCWrVq0aRJEwYPHkxGRkaxx1utVrKysgpdyoI8m50JizcX6kfwWtc7OFypKo2O7qP/hsVMWLxZyzQiImabOtXI36tdG8aONXs0gh8Dkd69e/P++++zbNkyJk+ezMqVK7nmmmvIy8tz+ZxJkyYRFxeXf6lXr56/hudT63YeLdSLACA7qjIvXt4fgEfXfETevv2s23nUjOGJiISlPJudlB0ZLNq0n5QdGeTt3Xd2u+6LL0JMjLkDFMBHJd4tFgsLFy7khhtucHnMn3/+SaNGjfjvf//LVVdd5fQYq9WK1WrNv52VlUW9evWCvsT7ok37eWz+piL3W+w2PvvgcdqmbWVRs8th3odc3+b8wA9QRCTMOGtY93byq/T6ZTl06QKrV2unjB8FZYn3hg0bUqNGDbYXs6U1KiqK2NjYQpeyoFZMtNP77ZYIxl09mDxLBNf/sZILf1sX4JGJiIQfR85ewSCkw95Uev2yHBsWfngsSUFIEAnY/4l9+/aRkZFBQkLoJWx2TKxGQlw0zvox/h5/IXPbXgtA8/8bC6dPB3ZwIiJhxFnOXqQtj4lL3wJgQeurGflnOeXsBRGvA5Hjx4+zadMmNm3aBMDOnTvZtGkTe/bs4fjx4zz++OOsXbuWXbt2sWzZMq6//nouvPBCevXq5auxB43ICAtJfZsDFAlGLMArl/bDWr0mlq1b4ZVXAj4+EZFw4Sxnr9/PS2h2eBd/Rcfw4mX3kJaZo5y9IOJ1IPLTTz/Rtm1b2rZtC8CIESNo27Yt48ePJzIykl9//ZXrrruOiy66iIEDB9K+fXu+//57oqKifDb4YNK7ZQIz+rUjPq7wMk18XDQv3n8ZUVP/rrj67LOwe7cJIxQRCX2HsgsHITVO/MXI7+cC8PJld/NXpTinx4l5vK4jcsUVV1Bcnus333zj7UuXWb1bJtCzeTzrdh7lUHYOtWKi6ZhYjcgIC7S4yygnvHIlPPYYnFOJVkRESu/cnL0xK+YQaz3Bb7Ub8VHrXi6PE/N4HYiIc5ERFro0ql70AYsFpk+HNm1g0SL48kvo0yfg4xMRCWZ5Nnv+l7kalaPAAkeOWwt/sSuGI2cvPTOHS/amckvqMgDG9xyMLSISC8ZMdcfEagH4acQdCkQCqUULo7/BSy/Bo4/CVVdBxYpmj0pEJCg423JbUEJcNEl9m+dXqS4YtBQMVJL6NueR99bx7LczAJjXuhc/n980P4cvqW/zEgMaCRwFIoE2fjx89BHs3AmTJsHEiWaPSETEdIXaZLiQnpnD4LkbmdGvHUCRoKVgoLKYn2l6ZDdHK8bmF5eMPyeQkeDgk4Jm/uJJQZQy5T//gVtugQoVIDUVGjc2e0QiIqbJs9npNnm5y5mQgixAXKXyZJ7MLRK0OOY4ZvdMoPsNl8Px4+x4fiqp19zi9tKO+EZQFjSTAm66CXr3NmqKDB1qtKQWEQlTzrbcumIHjjkJQhyPAeQNHwHHj0OXLjQa/QjXtzmfLo2qKwgJUgpEzGCxwOuvGy2ov/0WPv3U7BGJiJjGl1tpu+3cSI/fVmKPiIA331QF1TJA/4fMcuGFMGaMcX34cMjONnc8IiIm8dVW2qgzp5m41EhQ/fP2AcYuRQl6CkTMNHo0NGwI+/craVVEwlZxbTI88XDKxyT+lUZ6lWpkPD7OJ2MT/1MgYqaKFY0lGoApU4zEVRGREJVns5OyI4NFm/aTsiMjv99LcW0yCnI8VrVS+SLHNTqyl8FrjWXuadcNpX2rC3w7ePEb7ZoJBjfdBAsXwqWXGpVXLe5/L3C1j15EJJg4qxFybl0Qd+uIAAyeuxH4O0HVbmfBR2PptDeVZY06kLvwc3pfXMevP48Uz5PztwKRYLBnDzRrBidPwnvvwT33uPU0d/5hi4iYzVWNEMdXphn92jktUlZcZdWCf//+9etSXvp6GqfKR7Nu8Uou79UxcD+cOKVApCyaPBnGjCG3Wg2WfvYd59VNKHZ2w5N/2CIiZimpRoij5Prq0Vd6PJubZ7OzccM2Wl3dmahjf2F78UUiHn/cB6OW0lIdkTLom6tvZ2fN+pQ/eoTMR0dyx8y1dJu8nOTUtCLH5tnsTFi8udh99BMWb85ffxURMUtJNULsQFpmDut2HvX4tSMjLHSY/jxRx/6CVq2IGDbM+4GKaRSIBIHk1DQeWpDK41cPAeCOX7+l057f8ssZnxuM+PMftoiIL7lbI8SrWiL//a+xnG2xwNtvQ/nynr+GmE6BiMkKzm78VLcF81r3BuD5b6ZT4cxpoOjshl//YYuI+JC7NUI8riVy4gQMGmRcf/hh6NzZw5FJsFAgYrJzZzdeuOJeDlU+j0ZH9/FwysdOZzf89g9bRMTHSqoRYsFIsu+YWM2zF376adi1C+rXNxqISpmlQMRk585aZEVXIanHgwAMXvspTQ7vKnKc3/5hi4j4WHE1Qhy3k/o29yxRde1amDrVuP722xATU9phiokUiJjM2azF10268m3jzlSwneGlJVOJtOUVOs4v/7BFRPykd8sEZvRrR3xc4b938XHRnu/wO30a7r/faBZ6991GA1EPuCqqJubR9l2TOba2pWfmFNoFU/P4Uf47azBx1hNM73U/Dy15p0hgoToiIlKW+KQA44QJ8MwzULMm/PEHVK/u9nu/sXw7767ZybFTufn362+mf6iOSBnjqAkCFApGbv5tGa8smUJehSgif9kETZsWea4qq4pI2EhNhXbtIDcXFiyAW29162nJqWmM+ew3jp3MLfKYai/5h+qIlDGupi1/6Hoth7tdSeRpK9x3H+TlFXluZISFLo2qc32b8+nSqLqCEBEp85wun+TlGUsyublw3XXwr3+59VrJqWk8NHej0yAEVHspGJQzewBi6N0ygZ7N44vObtzdBFq0gJQUeO01GD7c7KGKiPiNqyXn2cfW0OzHHyE2Ft58062eXI7yCCUpuDuxSyP3lnrEdzQjEkSczm7Uqwcvv2wc8NRTsH27uYMUEfETxzL1uQUby+/exQVTnjduvPwynH++W69XUvHHc6n2kjkUiJQFgwbBVVfBqVPG1KTNZvaIRER8Ks9m55kvnLSusNt5Pvl1KuVa+alhG/LuG+j2a3oaWKj2kjkUiASJYreUWSwwcyZUrgwrV8Jbb5k3UBERP3hj+TbSs4oGDv/6bSnddv9CTrkKjOzxMOt2/eX2a3oSWKj2knmUIxIE3NqGm5gIL7wAjzwCTzwB114LDRq4fE3tphGRsiI5NY0p/91W5P6ax48ybvm/AXilWz92n1fHo1kOR/HHc8sjnMuCai+ZSTMiJnO1Juq04d3DD8Ollxo9Fh54wCjo4+I1u01ezh0z1/LY/E3FdvIVETGTy4RSu53nv5lOnPUEv8ZfyOwO1wOezXIUV/zR4bxK5bV112QKRExUsOHduZxuKYuIgH//G6KjYelSmD27yPM8CmxEREzmKqH0hs0r6Ln9R05HlOPxa4eRFxHp1fKJq/IIVSuWZ3iPxvw0rqeCEJNpacZEJWV0O91S1rgxPPccjBoFI0ZAr15Qty5QcmBjwQhsejaP1xSkiAQFZ0sttbIzeOa/bwPwWtfb2VqzAeD98onL8gj6OxgUNCNiInfXOtMzTxW+Y9gw6NQJsrLgwQfzl2g8CWxERIJBkaUWu51J37xB1Zzj/Bp/IW91ugWA4T0uKtXMhYo/Bi8FIiZyd63z2a/+KLykEhlpLMtUqABLlsAHHwDuBzbaKy8iweLcbuL/+u2/XLVjPdbIcoy8djhnIssRHxvF0CsvNHWc4j8KREx07j9AV/46cbpofkfz5tiSkgDIHfIIG1b/Ro0qUW69r/bKi0iwKJhQen7WIZ5eNhOAKd36sb3mBViAZ65roRmMEKZAxEQF/wEWx1nianJqGpfZLmFTwkWUP57Fibv7M3LBz1StVN5lYGNBe+VFJPj0bpnAjDvbMO2b14k9fZINdZryTscbOa9yee7r2oC4ihXUByaEKRAxmSOju1rl8sUeVzC/w7EzZt/xXEb+czg55Spw2a6f6blyIcdO5uYnphbkuK298iISjHqv+A+X/PkzeRUrkTL+FarGVOToiVz+vWaXShCEOAUiQaB3ywSe7tPCrWPTM08V2hmzo3o9Xrj8XgCe/G42jTL2UbVSeWrHFl5+iY+L1l55ETGdsyrSeX9swfbEaABW3f84r+y0c/TE6ULPUwmC0KXtu0EiPta9vI2jJ04X2RnzXvs+XLV9HZfu3sQrX73CLXe9xPQHuhIRYdFWNREJGs6qSNeIsvDerOG0sOawqkFbBlS8xOlzVYIgdGlGJEiUlLjqyO+o5iQh1W6JYNQ/h3Esugpt0rYxNGUBR05YC21VA1z3shER8TNXxRbvWfo+LQ78j2PRVXj82seM3louqARBaFIgEiSKK0VcML/D1czJwZgajLv6YQCG/rCAhjt+z39MJd9FxEyuii222/cHQ9Z+AsCTvYZyMKaGW6+nEgShRYFIEHFVirhgfkdxMydfNruMz5tfTjm7jZZjhsCJEyr5LiKmW/tnRpG/QZWtJ5ny1StE2m38p0V3ljTt5vbrqQRBaLHY7S46pwWBrKws4uLiyMzMJDY21uzhBExJnXMdwQVQ6BuGBYjNOc7a+cOpeDAN2wMP0LXBrS6rrVowgpzVo6/UequI+EVyahpj/vMbx07lFrp/8pJp3PbbUvbF1uKa+14nO6pyia+lv1llhyfnb82IBKGSShEXN3My+f7LqDhvLgAR77xD8w0rXb6PP9ZbnWXEi0h4cnxpOjcI6fW/H7jtt6XYsDCizwi3gxBQCYJQ5PWumVWrVvHSSy+xYcMG0tLSWLhwITfccEP+43a7naSkJGbOnMmxY8fo2rUrM2bMoHHjxr4Yd9grvolTAowcCa+8wotLptH7vjc4XMV1ETNfrbc6y4hPiIsmqW9zbRsWCTOu8kJqZx/hha9fB+DtTjezrl5Lt14vXn9LQpbXMyInTpygdevWTJ8+3enjL774Iq+99hpvvfUWP/74I5UrV6ZXr17k5CjJyFeKnTn5v//jRLOLqX4qi1e/fBWL3ebydXyx3qpcFBEpyFkTTovdxitfTeG8nGx+q92IVy+9y+lzHX/JhvdozLTb2/DRoM6sHn2lgpAQ5fWMyDXXXMM111zj9DG73c7UqVMZN24c119/PQDvv/8+tWvX5vPPP+f22293+jyr1YrVas2/nZWV5e3wJCqK6E8XcKpNOy7dvYlB6xbyTqebCx3iWG8tbcl3V998QHv/RcKVs5nWB9Z9Rrfdv3CyfBSP9X2c3MjyVKoQSYVyERw7eXb5RrMf4cUvBc127txJeno6PXr0yL8vLi6OTp06kZKS4jIQmTRpEhMmTPDHkMJSZPNm7HjqWVo+8ziPr3qflPqt+C3BWBrz5Xqrs28+BRXMRXHUNBGR0HbuTGurtP8xapXRKXzCVQ/wZ/W6AMy8+xI6N6pebIK+hDa/JKump6cDULt27UL3165dO/8xZ8aOHUtmZmb+Ze/evf4YXlhpOX4k6T37UN6Wx2uLX6Sy9STg25Lv7uaYaO+/SPgoWGqgivUkr33xEuVteXzVpCsLWl2dX6Sx89/LysUl6EtoC6oS71FRUURFudfKXtxksRC/4H3sbdqQuGcPX+/4hP1TZvj0G4e7OSba+y8SPhxFGgd/sIFJya/T4Fga+2JrMrb3I1j+rp6qHTACfpoRiY+PB+DgwYOF7j948GD+YxJA552HZe5ciIig/uJP6JLytU//8btbnr60uSgiUrb0bpnA4opb6Lvle85YInj0uifIiq6iJpxSiF8CkcTEROLj41m2bFn+fVlZWfz444906dLFH28pJbn0Uhg/3rj+0EOwZUv+Q6Wt/eFueXp98xEJM7/9RsvJTwOw//Fx9B95h3bASBFeL80cP36c7du359/euXMnmzZtolq1atSvX59hw4bx3HPP0bhxYxITE3n66aepU6dOoVojEmDjxsHKlfDdd3DrrfDjjyTvOOaT2h+OImvnvpay30XC1IkTxt+ZnBzo3ZsLJiVxQYRqaEpRXpd4X7FiBd27dy9yf//+/ZkzZ05+QbN33nmHY8eO0a1bN958800uuugit98jXEu8+1V6OrRpAwcPsvfmu7jswjuKbLt1zFt4M3VaUnl6ESmdMvNvbMAAmDMH6tSBTZugZk2zRyQB5Mn5W71mwtGyZdh79sRit/NYn5EsalE0oFRPB5HgU2aqF7//PvTvDxERsHw5XH652SOSAFOvGSneVVexb8hIAJ7/ZjoNM/YVOcRR+2POmp3qGyMSBMpM9eKtW+Hhh43rSUkKQqREmhEJE+dO56b/dYL4m/vQZc9v/FGzATfc/QrW8sVvnQ7Kb14iYSDPZqfb5OXB30n75Eno0gV+/RW6d4elSyEy0rzxiGk8OX8HVR0R8Q9n07nVKpcnsu/jLHn3UZod3kXSsnd4svcjxb6O45uXtt2JBFaZqF5st8MDDxhBSK1a8OGHCkLELVqaCXGupnOPnsjlcJVqDO8zEhsW7vzlG25MXV7sazmmziYs3qxlGpEAKhPVi99442zw8fHHkKAvK+IeBSIhrLhmdA6rE9vy+j+M3j/PfzOdpod2FvuaBb95iUhgBH314tWrYcQI4/pLLykvRDyiQCSElTSd6/DB1fewqkFbKp6xMuPz54nNOV7ic9Q3RiRwgrp68YED8K9/wZkzcPvtMGxY4McgZZoCkRDmbrDwVN+WVPx4PifjzyfxrzReXjIVi91W7HPUN0YkcIK2evHp00YQkp4OLVvCrFlg0XZ/8YwCkRDmbrAQH1eRDh0uotLiz7FXqMDV29YyeO2nTo9V3xgRcziqF8fHFf53bWrflhEj4IcfIC4OFi6EypUDPwYp87RrJoQ5pnPTM3Oc5ok4tvzlBxWXXIJl+nQYNIiR38/lt/jGfJ/YttDxoL4xImbp3TKBns3jg6Oy6vvvw/TpxvW5c+HCCwM/BgkJmhEJYV5N595/PwwcSKTdxhuLX6TusfT8h9QxU8R8kREWujSqzvVtzqdLo+rmBCE//wwPPmhcT0qCPn0CPwYJGSpoFgY8LgudkwOXXQbr13OiWUu++/dCqtc6L3h7WohI4GRkwCWXwK5dcO21sHixUcpdpAD1mpEiPG6UtXcvtG8Phw/DnXcaU69KQhMJb3l5RvDx7bfQqBGsXw/nnWf2qCQIqbKqFOGYznVbvXrwySdw1VUwbx60aAFPPum/AZ6jzHQYFQknSUlGEFKxInz2mYIQ8QkFIlJIoQCgbks6TXuNiKFD4KmnoGlTuOkmv4+hzHQYFQknn38O//d/xvVZs6BVK1OHI6FDSzOSz1UAMD91HhfMmw2VKsH330O7dn4dw+C5G4vs8nHMhShZVsQ3PJp13LIFOnaE7GyjYNmUKQEdq5Q9yhERjxUXAETa8kj5YQo116yAOnWMdeE6dXw+hjLTYVSkjPNo1vHIEejcGXbsMJLY//tfKF8+wCOWssaT87dSnaXYnjR2IC8ikjuuGoa9WTOjnPP11xvtvn3Mkw6jIuIdV40wHd21k1PTzt5ptRrLsTt2QGIifPqpghDxOQUiISjPZidlRwaLNu0nZUdGiZ1y3QkAtlvL8fMb70P16vDTT3DvvWCzefV+rpSJDqMiZVhJXzqgQHdtu92oFfL99xAbC19+CTVrBnK4EiaUrBpivEn0dPfEvrdaAu0WLjR20nzyCTRtSvKtg32WWBr0HUZFyjhPZh27fPwOvPceREYa/96bNw/cQCWsaEYkhHg05VqARwHApZfCO+8Ydzz7LF8/+arH7+dKUHcYFQlSnsxIuvulI/KzT89u13/9dbj6al8MVcQpBSIhwqMp13N4HADcey+2UaMAeHHJNNru3+LR+7kStB1GRYJUcmoa3SYv546Za3ls/ibumLmWbpOXl+pLR6u0/3HJ08OMG489BoMH+3DEIkUpEAkRpUn09CYA+HHQ4yy9sBNRebm8s/A56mQdcvv9ihOUHUZFgpA3M6Alfek4P+sQsxc+R4Q1x6ig+sorfhi5SGEKREJEaRM9PQ0ADp3M5bG+o9hcK5GaJ47x708nUtladCeNN4mlvVsmsHr0lXw0qDPTbm/DR4M6s3r0lQpCRP7m7QxocV86qlhPMuvTidTIPgoXXwzz5xv5ISJ+pmTVEOGLRE9PWozXionmZIWK3H/z0yx6fwTNDu9i6pev8OCNT2KLiCx0nDc8LkkvEkY8Sjo959+R40tHwSTzCFsebyW/SrPDu6B2bWOHTEyMH38CkbMUiIQIx5RremaO029JjmJgJSV6uhsAON4vjVo8cOM45n80lp7bf+Sp72bz7FWD3H4/EfHcfzenu3Xcmu2HnX6pKPSlI+sUHadOJGHLWoiOhkWLoH59fw5fpBAtzYSIQCd6Fny/Tec3ZdS1wwAY+NMiBq7/3OfvJyKG5NQ0/r1ml1vHvvHdDpdJrI4vHdcvm0/C+zONO99/Hzp18npsvqopJOFFJd5DjKd1RErb5bbg+z3w4394csW7AGx66S3ajHqw9D+QiOQrqQ1CcRz/qqff2ZbzKkdxKDuHZiuXcNGwB4wHXn0Vhg/3emxqVikFqddMmHM3uPDVH47898s6RccpE0j4YBZUqADJydC9u09+JhGBlB0Z3DFzbaleI8ICNjt02f0L732cRAXbGXb1G0SDD97x+jXVrFLOpV4zYS5/yrXN+XRpVN1lEOJN8bNi369tXRLefcvoTXH6NGeuu57vFizVFG0Zo+n14OWL9gY2O7Q4uIN3PnuOCrYzfNn0Uq6s09fjAoQOpalhJAJKVg1LJf3hsGD84ejZPN7zHI/ISL598mVqbtxO212/0mLgbdzc7yXOXNBAU7RlgKbXg5sv2hskHt3Pex+PJ+b0KVLqX8yIf47Abonw+t98aXbwiIBmRMKSP7vcJqem8eAnm+l//ZP8UbMBtU78xdwF47Dt2+9V2XcJHF/Okol/lFSQrCQJWYf5YME4apzM5LfajXjgpnGcLlc+/9/8lKX/83gWTM0qpbQUiIQhf/3hKDjTkhVdhXtunciuqglccCydDxY8TdVTWZqiDVKaXi8b3NkdV7VSeaeBSrWTmXyw4GnqZh1mR7W69L91ItlRlQsd88Z320ssE38uNauU0lIgEob89Yfj3JmWw1Wq0e/250irUp2LMvYw5+Mksg8ddTnTYmZuQrjnRfhzlkx8q7gqyG/1a8cLN10MFA5UqlhPMueTJC48uo/9MTW5+7aJHK0U5/I9PJkFU7NKKS3liIQhXxU/O5ezGZR9cbXpd9tzfDxvNK3Tt/Hv/0zk0G1t4Zy14uTUNJ75YjPpWWdfIz42mmeu839ugvIiNL1e1pRUBblg5dSoXCuz/jORVunbyagYy923PcuB2FrFvr4nuWKOWZrBczdigUJ/U9SsUtyhGZEw5K/iZ65mUHbUqMc9t04kq0IlOu1NpdvYwXD6dP7jyalpPDR3Y6EgBCA9K4eH/JyboLwIg6bXy57idsc5+jXNv7c9K356i857U8mtXIX+t05kZ/W6br2+J7NgalYppaFAJEz54w9HcVO0v8dfyP23jCenfBTnrfgv3H035OWRZ7Mz5rPfin3dsZ/95pelEuVFnKXp9RCUl0ej0UNJWLUUW1Q0EV9+ydBRtxb5N18Sd2fB1KxSvKWlmTDmSZM7d5Q0Rbu+XktSX5vNJY/eCx9/DLGxrH3ieY6dzC32df86mcvaPzPoemENr8blirYdnqXp9dCS/Ms+bAPu49qfl5IbEcmDfZ7gj5QzJPWF1aOvZN3Oo6zZfpg3vttR4mt5MgumZpXiDc2IhDl3ip95oqSZlkseuhM+/BAiImDWLCqPeAzcKO6bsiOjVONyRnkRhWl6PTQk/7qfrLsHcO3PSzljieDRvo+z/MKO+cuNSzen06VRdYb3bOL2LFi4J3OLf2lGRHyuxJmWf/0LTp6EAQNo8+VHTNyfxfieD4GluCDI93/4lBdRlK9nySSw8s7kYR04iFt/+y95lgiG9R3F1027AYUTUK9sWpsNu//impbxzF6zq9hZsKWb08M+mVv8S4GI+EWJU7T9+4Pdjv2++7jn56+wWyCph+tgpEtD3y7LgP92D5V14TC9Xtpmj0HJbudw//u5/qevybNEMLzPCL5sdlnhQzCWGztPWsbRE2cTxi2WwhOT8X8HGoDTHjKO2RXNlIkv+DUQeeaZZ5gwYUKh+5o0acKWLVv8+bZSVtx7L/Y8G/ZB99N/41fYsfBMjweLBCNVK5Wnsx9OjMqLCE8huV3bbodHHyV+3hxsWBj5z+F80fwKl4cXDELA6D8DMLBrA3o0j88PvrtNXu6fVhAiBfg9R6RFixakpaXlX1avXu3vt5QyJGLgffw+4WVsWLh345ckLXunSM7ICzdd7LM/dOeudfdsHq+8iDASktu17XYYPhzeeAO7xcLj1w7j8xaed722AEtS0/Nnh1TkTgLF70sz5cqVIz4+3t9vI2XYxU+P4Dfg4vEjGbBhMQATrnqA+Lhonrmuhc+CgeK+CTt2EoTUVL0U4tdmj2ax2eDRR2H6dADs78zkh8MNsLhYbizOubvElMwtgeL3GZFt27ZRp04dGjZsyF133cWePXtcHmu1WsnKyip0kfBw8dMjsL0zE4ABGxbz455PWPNEd58GIcV9E3bsJPDV7iEJPiH3Dd9mg4ceMoIQiwVmziTi/oEuixW6yxFYKJlbAsWvgUinTp2YM2cOycnJzJgxg507d3LppZeSnZ3t9PhJkyYRFxeXf6lXr54/hydBJmLQ/TB7Nlgs1J7/PpH3DYAzZ0r9uipcJhBi27XPnDESvmfONLbCz5kD998PuN6GXa1yebde2hFYqMidBIrFbnejiIOPHDt2jAsuuIBXX32VgQMHFnncarVitVrzb2dlZVGvXj0yMzOJjY0N1DDFbB99lF95lVtugQ8+gGjvv3Wl7MjgjplrS37bQZ1DardISO4MKYWQ+T04dQruvBM+/xwiI2HuXLj99iKHnfv/v/0F53H5S9+VuEts9egr839PHDOJ4DyZW3lU4kpWVhZxcXFunb8Dun23atWqXHTRRWzfvt3p41FRUURFRQVySBKM7rgDKlaE226DTz+FAwdg4UKoVXyjLldC6puwm0JyZ0gphcR27WPH4PrrYdUqiIqCBQuM204424bt6S4xx+zKub9L8WH+uyS+FdDKqsePH2fHjh0kJOiXV0pwww2wZAlUrQo//AAdO0JqqlcvFW5r3SG5M8QH/NXsMWDS0uDyy40gJDYWvvnGZRDiijfVc9VDRvzNr0szo0aNom/fvlxwwQUcOHCApKQkNm3axObNm6lZs2aJz/dkakdC1Nat0KcPbN8OMTEwfz5ce61HL5Fns9Nt8nKPpqTLKsfP6iopM5R+Vm+VydmibdugVy/YuRNq14bkZGjTxuuX07Kd+FvQLM3s27ePO+64g4yMDGrWrEm3bt1Yu3atW0GICABNmsDatUauyIoV0LcvvPIKPPZYCSXhzwqnwmVq5FeyMlfGfuNG6N0bDh+GRo3g22+hYcNSvWQ4VM+VssOvgcj8+fP9+fISLqpXN6ahhwyBWbOM4k1//AFvvAHl3dsJEC5r3eGYD+ONMnMiXr7cWKbMzoa2beHrr40ZEZEQol4zUjZUqADvvAPNmsGoUcb17dvhk0+gmnvJhWXum7AXwi0fJqR9+incdRecPg3duxu7ZLRELSFIgYgEnNfr0xYLjBgBjRsb2xeXL4fOneHLL+Gii9x67zLzTdhLIbEzRGDGDGMG0G6Hm282tuiWYgu7SDBTICIB5ZNEwb59Yc0a47/bthnByKefwpVXejSWUEzYC6d8GF8Kmt+FvDwYPdrIgwKjcuobbxj1QkRCVEALmnlKu2ZCi2Nb6bm/cF4XRzp40Fg/X7sWypWDN9+EQYPcHkuZ2znhgVD/+XwpaD6rEyeMpZhFi4zbEyfCuHFuJ2WLBBNPzt8KRCQg/LatNCcH7rvPqMYKRiLrSy8V+w3S5wFRkAqab/lBLGh+F/bvh+uuM3bIREUZJdudVEsVKSs8OX8HtKCZhC+/NRyLjoYPPzS+PQJMmWIUeXLRMDGc+s448mHUyM+5oPld2LgROnUy/luzJnz3nYIQCSsKRCQg/Lqt1GKBp582yl1HR8NXX0HXrrBrV5FDQ64Dq3gtKH4XFiyAbt2MGZFmzeDHH6FLF7eemmezs2bbEV7+Zgsvf7OVNduPhEQALeFHyaoSEAHZVnrrrZCYaExxp6Ya3zIXLoR//CP/ENXZEAdTfxeysowdYP/+t3H72mth3jyIi3Pr6cmpaYz57DeOnczNv++N77ZTtVJ5Xrjp4pBYWpTwoRkRCYiAtRTv0AHWrzfKXx86ZNRf+PDD/IdVZ0McTPtdWLYMLr7YCEIsFhgzBr74wqMg5KG5GwsFIQ7HTubyUBj3E5KySYGIBERAG47VrQurVxs7ak6fhn79jKUbmy1wAZEEvYD/Lhw/Dg8/DD16wJ49Rpn2lSth0iS3t+fm2ew888XvJR4XKnlOEh4UiEjAeNP502uVK8N//mN82wR47jm47TYic06V7Q6s4jMBDY5XrYLWrY1CZWAEJL/8Apde6tHLrNt5lPQsa4nHKc9JyhLliEhABbTMekSE8W2zSRN44AGj6NmuXfRetCgs+s5Iyfzeg+jkSXjqKZg2zaiSWr8+zJ4NV13l1ct5kq+iPCcpKxSISMAFvMz6vfcaXUtvvBF++gk6dqT3F1/Qc/SVqrMh/guOU1KM373//c+4ff/9RsXUUtRE8iRfRXlOUlYoEJHwcOmlsG4d9OljdO699FIiX3+dLgMGqHKl+DY4zsmBpCR4+WWw2aBOHaNr9DXXFDrMVcG54grRdUysRnxsVInLM8pzkrJEgYiEj4YNjW+pt98OyckwcKDx37ffhvPOM3t0ISHsq7n+9BP07w+bNxu377kHpk4t8vvlqqz8da0T+OKXNJfl5iMjLDxzXQsemrux2GEoz0nKEpV4l/BjsxnfVp96Cs6cgXr14IMP4PLLzR5ZmRY0PVvMcPo0PPuskZOUlwe1a8M77xg1bc7hqqy8K87KzTurIwJwXqXyTFIdEQkC6jUj4o716+HOO2H7dmN5ZsQIY3eNCe3Wy/pMQtD0bDHDL78YsyC//GLcvv12o2Nu9aJLPSX1XHLFWS+mPJudtTsySPnzCGAsLXVuqFL+EhwUiIi4KzvbCEBmzTJut2hhNBy75JKADcEfMwmBDGz81tAw2OXmwgsvGH2OzpyBGjWM7bm33OLyKSk7Mrhj5lqv3/KjQZ0Dm+gt4iVPzt/KEZHwFhMDM2dC374waBD8/jt07gyPP24kHPp5dsTVTEJ6Zg6D5270aiYh0EsknvRsCZmT6O+/G7MgGzYYt2+8Ed56C2rVKvZppd1Sqy25EopU0EwEjLX83383ptXz8oxvuu3aGU3I/MQf3V8dgc25gYEjsPFH6e+w6t+Tlwcvvmj8bmzYYCShfvihUTyvhCAESr+lVltyJRQpEBFxqFEDPvro7Enljz+MTqiPPAKZmT5/O193fzWrrX1Z7t+TZ7OTsiODRZv2k7Ijo/jPZutWo1Pu6NFGcuo//2k0V7zzTre3gJdUVt4VtR6QUKZARORcN91kbL+8+26jGuYbbxgt2j/+2LjtI76eSTCrrX1Z7d+TnJpGt8nLuWPmWh6bv4k7Zq6l2+TlRWeNbDZjC26bNrB2rVGQbPZsWLzYqBHigeLKyrui1gMS6hSIiDhTvTq8/z4sXQqNG0NaGtx2G/TuDdu2+eQtfD2TYNYSSUB7tviI20tYO3bAFVfA8OFGobKrrzZmQUpRCM9VzyWHcz8mv/RiEgkiCkREitOjB/z6KzzzDFSoAN9+a+ysGTkSjh0r1Uv7eibBzCWSgDY0LCV3lrAmLkrFNn06tGoF339vNFF86y2jAF69eqUeQ++WCTz9z+ZOH3OsDg3s2oCPBnVm9egrg+rzE/E1bd8Vcde2bfDoo8bJCIxZk4kTjYZ65bzbgOb4Zg4UOjF6U3/DsY02PTPH6Uk2ENtoy0I9lJK20J6feYjJX0+j2+6/64JccYWxFJOY6LMxhO2WZwkbnpy/NSMi4q7GjeHrr41Ls2aQkQFDhhjt3R3BiYd8OZMQDEskjp4t17c5ny6NgrO4lsulKbud2375huTZQ+i2+xfOREfDa6/BsmU+DULAvHwekWCkOiIinurd21iyeftto9bI5s1GQ7OePWHcOKPBngf5A950f3U18+D3tvYhoEaVqCL3tUjfztgV7+bPgvx0fjMi35tD26s6+mUMYbXlWaQECkREvFGunDEbcuedRo+R1183EluXLoV//AOefBKuvdbtgMST7q8lFSzzW1v7EJCcmsYzX/yef7vx4d0MWzOPf25dA4A1sjwvX3Y3S666jVXdO/htHGV5y7OIrylHRMQFj/Id/vzTKHT17rtGjQkwEh3HjoV//QsiI30ypkD0dCkLeR7eKPjZXXhkD4/+MJ8+f3xPBHZsWPi8xRVM7XYXe6vG+z3BdsmvBxj60c+4KluiHBEp69RrRqSUPCmTXvDEff7Jv2j32Rwi3n4bjh83DmjUyCiCdc89EFV0WcBdgUhwDNUOunk2O91eWEbtLb8yaN1nXLP1ByL+DueWXPQPpna7k//VbBCQn9Wd7rsWQrxRoIQ8BSIipeDJrIOrE/dzlyVw1fL/wLRpRlIrGMWvRo40dtlUqeLxuNxtmOZtY7SQ7aC7bRt735jF6bkf0ujo/vy7v2ncmWld72Rz7Yb59304sBNdG9fw21Dc6b4bYYE37mjHta3K4Gct8jftmhHxkidl0osrinX/4p0k33g/7N4NU6bA+efDgQNGIHLBBTBhAhz1bEeEPxMcS/q57cCY//zGmu1HfF4i3i8OHjSCwI4d4aKLqPfaizQ6up9T5aL4rEV3rr7vDR68aVyhIATgyAmrX4dV0m4ZMOqInFe5gl/HIRJMFIiIFODutsq1OzLcC1gqVoJhw4wKnbNmGVuAjx41CqTVr28EJtu3uzU2fyY4unOCPHYql7tm/ei8DHowyM42quH26mXMPg0bBuvXQ0QEx7p1Z8Q/h3PJ0A8Y0Wck/6vZwOlL+Ds5VLtlRIpSICJSgLsngJQ/j3hWByIqCgYONBrpLVhg9C05cQJefdUITq680mi4l+P6Nf3Z08WTE19JnXw9aiRXWqdPGz1fbr8dateG/v2N6rc2mzEbMm0aHDhAzMplpHT9JyejKjl9mUD1w9FuGZGitH1XpAD3TwDuJYMWOcFHRsKttxo7aZKTjW2/ycnw3XfGJS7OeKxfP6MeScTZ7wqOgmWD527EgvNKrN4WLPPkxGf/+/0mLN5Mz+bxhd4vIMmuNhusWQMffgiffFJ4ieuii+Cuu+COO4wA72+R4LfPzhOOYLKk6rfB1iBQxJ80IyJSgLuzDu4mg7o8wVssRhG0JUtg1y6jMFq9epCZaSzhXHEF1rr12X7PQ6R+vIS8M3mA/3q6eNqe3lnlT7cbyXkrNdXYDp2YCJddZhSUO3oU4uPPLsNs2QLjxxcKQhx6No9nWI+LiKtYvtD9geyHEwzVb0WCjXbNiJzDVf8Xh4FdG3Bl09qM/OQXDmb5sK+LzQarVrH39Xc476tFVLGezH8oo8p5nLimD/UH3gVXXEFe+Qo+r/VR0s/tzLTb23B9m/P9t7V4zx5jyWrePKP5oENMDNx8s1FQ7sorS6zT4mympmrF8gzo2oChVzYO+Ik/VLdJizho+65IKTk7UURYKFSAqmql8hw7metyqt+bb9mOYKDCmdN037Ge3v/7gSu3ryf29NmghEqVjEZsvXvD5Zcb3YB9WDDt3J+7OI6twj7dWnz0KHz6qbH0smrV2fvLlzeq1d51F/TpAxUrujXGYN2WHKqF40TAs/O3ckREnOjZPJ6YqPKk/HmEHYdP8HVqepEqmJkncwGI+zsgcfC2r0vBLbTWchVIbtKV5CZdKZ+XS5fdv9JrWwpX71hPzewMY0lnyRLjiTExRmJmly7GpXNnqOZdjoGjPPzaHRkMmbeRY6dynR53bi6D17tB7HZIS4NffjEuP/xg5MzkFnjfyy83Zj5uucXjn6ukbcmucl0CwZOy/iKhTIGIyDncnRVwnMiiy0Xw4f2dOHLcWqpvtq620OZGlmdVw/asatiep+x2Fl0aQ+vNPxp9bdauNbatLltmXByaNDkbmLRubdQuqVWrUPKrK5ERFro2rsELN1/sdKnGWS6DO8muUWdO02DP/2DTUmOZxRF8OAq+FdSq1dmk03r1SnxtVzzpcqugQMQcCkRECnCn/HZBdiA9y0qExcL1bc4v1Xu7NatgsbCr7oW07nM5PPEE5OUZSZwpKWcv27bB1q3GZc6cs88tX96or1G3rutLfLzR0A886uT71wkrEdiJPp1DjRPHqH08g4TsI9TNPMRFR3bT7NBOGmXso9wrtqI/U0SEETi1bm1c+vSBli29/RgLUd0OkeDn90Bk+vTpvPTSS6Snp9O6dWtef/11Onb0T2ttkdIobhq/JL44kXlVYyIy8uwJ/KGHjPuOHDFmSlJSYN062LzZWP7IzTUqve7e7frFIyIgIcGoBBsbS++oKHpViCLDmof1jI2oyAiqR0VgWXXKqHly6hTZGcdol36YP05lE5XnfCnH4Vh0FfIubkX1f3QwZj1at4bmzd3O9/CU6naIBD+/BiILFixgxIgRvPXWW3Tq1ImpU6fSq1cvtm7dSq1atfz51iIec6e6qCu+OJH5rMZEjRrGrEKfPmfvy82F9HTYt8/5Zf9+43LmzNnrBd63uO4rMX9fHE6Vi+JQlfM4EFuTAzE12FG9Hn/USuSPmokcjKlOfNWKAesqq7odIsHPr4HIq6++yqBBgxgwYAAAb731Fl999RWzZ89mzJgxRY63Wq1YrWd7PWRlZflzeCKFeDOr4csTmT8LllG+vJFrUVy+hc0Ghw6dDUyOHzdmPaxWYwkIjPon5ctDdDRUrMiWv04zYcUesqMqc6xiDH9Fx3CiQkXjOBcCmZPh189URHzCb4HI6dOn2bBhA2PHjs2/LyIigh49epCSkuL0OZMmTWLChAn+GpJIsTyd1fDHicyTvAyfi4gwckTi4+GSS9x6ytZN+0nZucnjtwpkToapn6mIlMhvgciRI0fIy8ujdu3ahe6vXbs2W7ZscfqcsWPHMmLEiPzbWVlZ1CtFxryIJ0qaxj+Xv05kji20wV5jIs9m50i2d91qA52TUVY+U5FwFFS7ZqKiooiKijJ7GBKmSprGtwPDezSmQY3Kfj+RBXuNCU8LnzmYmZMR7J+pSLjyWyBSo0YNIiMjOXjwYKH7Dx48SHx8vL/eVqRUNI1fMk+3ODsoJ0NEnPFbIFKhQgXat2/PsmXLuOGGGwCw2WwsW7aMoUOH+uttRUpN0/iuebLF+dyS+ArmRMQZvy7NjBgxgv79+3PJJZfQsWNHpk6dyokTJ/J30YgEK03jO+fuFuen/9mMu7s0YMPuvxTMiUix/BqI3HbbbRw+fJjx48eTnp5OmzZtSE5OLpLAKiJlg7u7XWrERFGhXISCOREpkd+TVYcOHaqlGJEQ4e5ul11HTpZ8kIgIUHIHLBGRv3VMrEZ8bMk72+av30Peue2KRUScUCAiUkbk2eyk7Mhg0ab9pOzICPiJPs9mZ93Oo7StX7XEYx3VU0VEShJUdURExDlndTsSArgLxZu6IepoKyLu0IyISJBz1O04NwhIz8xh8NyNJKemmfL+JfG0eqrZMz4iYg7NiIiYwLHMUdLW1uLqdtgxioRNWLyZns3j/bI11pO6IQ7eVE81e8ZHRMyjQEQkwDw56ZZUt8OOf7rZOgKlNdsPezQT4k31VFeVWh0zPjP6tVMwIhLCFIiIBJCnJ1138yx8mY/hbR8Z8Lx6qtkzPiJiPgUiIgHizUnX3TwLX3Wz9baPzNDuF9L1whoeV081a8ZHRIKHAhGRAPHkpNsxsRrrdh4lPfMU1SpX4K8Tp50GB77sZluafJDhPS/yasYikDM+7ubliEhgKRARCRB3T6ZLN6cz4uNNJS6N+Lqbrbt9ZHz5/oGa8VEyrEjw0vZdkQBx92Q6e80utwKC+LhonyZyejrr4Iv375hYjYS4aFyFMRaMgKE0Mz5mb38WkeJpRkQkQBwn3fTMHJfLHxEWKK58RrXK5Xm6TwviY32/tOBuoORtPogzkREWkvo2Z/DcjVig0OfiixkXJcOKBD/NiIgEiOOkCxSZAXDcLqmG19ETucTHRtOlUXWfnzjdnZ0Y3vMin75/75YJzOjXjvi4woGQL2ZcPMnLERFzaEZEJIAcJ91z8xXi46K5tmU8/16zq8TX8FfpdH/PThSnd8sEejaP93kyqRnbn0XEMwpERALM1Ul33c6jbgUivtqq62psrgIlfyd2RkZYfL5FN9Dbn0XEcwpEREzg7KRbUg6JL7fqFsdfsxNmCJbPVERcU46ISJBwJ4fEX0sjzsbSpVF1rm9zvl/yUQIlmD5TEXFOgYhIEPFn4ma40mcqEtwsdrs9aHttZ2VlERcXR2ZmJrGxsWYPRyRgVAXU9/SZigSOJ+dv5YiIBCF/JG6GO32mIsFJSzMiIiJiGgUiIiIiYhoFIiIiImIaBSIiIiJiGgUiIiIiYhoFIiIiImIaBSIiIiJiGgUiIiIiYhoVNBMRl1SNVET8TYGIiDiVnJrGhMWbScvMyb8vIS6apL7N1Z9FRHxGSzMiUkRyahqD524sFIQApGfmMHjuRpJT00wamYiEGgUiIlJIns3OhMWbcdYN03HfhMWbybMFbb9MESlDFIiISCHrdh4tMhNSkB1Iy8xh3c6jgRuUiIQsBSIiUsihbNdBiDfHiYgUR4GIiBRSKybap8eJiBRHgYiIFNIxsRoJcdG42qRrwdg90zGxWiCHJSIhSoGIiBQSGWEhqW9zgCLBiON2Ut/mqiciIj6hQEREiujdMoEZ/doRH1d4+SU+LpoZ/dqpjoiI+IwKmomIU71bJtCzebwqq4qIXykQERGXIiMsdGlU3exhiEgI89vSTIMGDbBYLIUuL7zwgr/eTkRERMogv86ITJw4kUGDBuXfjomJ8efbiYiISBnj10AkJiaG+Ph4f76FiIiIlGF+3TXzwgsvUL16ddq2bctLL73EmTNnij3earWSlZVV6CIiIiKhy28zIo8++ijt2rWjWrVq/PDDD4wdO5a0tDReffVVl8+ZNGkSEyZM8NeQREREJMhY7Ha72y00x4wZw+TJk4s95o8//qBp06ZF7p89ezYPPvggx48fJyoqyulzrVYrVqs1/3ZWVhb16tUjMzOT2NhYd4cpIiIiJsrKyiIuLs6t87dHgcjhw4fJyMgo9piGDRtSoUKFIvf//vvvtGzZki1bttCkSRO33s+TH0RERESCgyfnb4+WZmrWrEnNmjW9GtSmTZuIiIigVq1aXj1fREREQo9fckRSUlL48ccf6d69OzExMaSkpDB8+HD69evHeeed54+3FBERkTLIL4FIVFQU8+fP55lnnsFqtZKYmMjw4cMZMWKER6/jWDXS7hkREZGyw3Hedif7w6MckUDbt28f9erVM3sYIiIi4oW9e/dSt27dYo8J6kDEZrNx4MABYmJisFjCt9GWY/fQ3r17lbQbIPrMA0+feeDpMw+8cPnM7XY72dnZ1KlTh4iI4kuWBXXTu4iIiBIjqXASGxsb0r+4wUifeeDpMw88feaBFw6feVxcnFvH+bWyqoiIiEhxFIiIiIiIaRSIlAFRUVEkJSW5rEgrvqfPPPD0mQeePvPA02deVFAnq4qIiEho04yIiIiImEaBiIiIiJhGgYiIiIiYRoGIiIiImEaBiIiIiJhGgUgZZbVaadOmDRaLhU2bNpk9nJC1a9cuBg4cSGJiIhUrVqRRo0YkJSVx+vRps4cWcqZPn06DBg2Ijo6mU6dOrFu3zuwhhaxJkybRoUMHYmJiqFWrFjfccANbt241e1hh5YUXXsBisTBs2DCzh2I6BSJl1BNPPEGdOnXMHkbI27JlCzabjbfffpvff/+dKVOm8NZbb/Hkk0+aPbSQsmDBAkaMGEFSUhIbN26kdevW9OrVi0OHDpk9tJC0cuVKhgwZwtq1a1m6dCm5ublcffXVnDhxwuyhhYX169fz9ttv06pVK7OHEhzsUuYsWbLE3rRpU/vvv/9uB+w///yz2UMKKy+++KI9MTHR7GGElI4dO9qHDBmSfzsvL89ep04d+6RJk0wcVfg4dOiQHbCvXLnS7KGEvOzsbHvjxo3tS5cutV9++eX2xx57zOwhmU4zImXMwYMHGTRoEB988AGVKlUyezhhKTMzk2rVqpk9jJBx+vRpNmzYQI8ePfLvi4iIoEePHqSkpJg4svCRmZkJoN/rABgyZAj//Oc/C/2+h7ug7r4rhdntdu69914eeughLrnkEnbt2mX2kMLO9u3bef3113n55ZfNHkrIOHLkCHl5edSuXbvQ/bVr12bLli0mjSp82Gw2hg0bRteuXWnZsqXZwwlp8+fPZ+PGjaxfv97soQQVzYgEgTFjxmCxWIq9bNmyhddff53s7GzGjh1r9pDLPHc/84L2799P7969+de//sWgQYNMGrmIbw0ZMoTU1FTmz59v9lBC2t69e3nsscf48MMPiY6ONns4QUW9ZoLA4cOHycjIKPaYhg0bcuutt7J48WIsFkv+/Xl5eURGRnLXXXfx3nvv+XuoIcPdz7xChQoAHDhwgCuuuILOnTszZ84cIiIUw/vK6dOnqVSpEp9++ik33HBD/v39+/fn2LFjLFq0yLzBhbihQ4eyaNEiVq1aRWJiotnDCWmff/45N954I5GRkfn35eXlYbFYiIiIwGq1FnosnCgQKUP27NlDVlZW/u0DBw7Qq1cvPv30Uzp16kTdunVNHF3o2r9/P927d6d9+/bMnTs3bP9Y+FOnTp3o2LEjr7/+OmAsF9SvX5+hQ4cyZswYk0cXeux2O4888ggLFy5kxYoVNG7c2Owhhbzs7Gx2795d6L4BAwbQtGlTRo8eHdbLYsoRKUPq169f6HaVKlUAaNSokYIQP9m/fz9XXHEFF1xwAS+//DKHDx/Ofyw+Pt7EkYWWESNG0L9/fy655BI6duzI1KlTOXHiBAMGDDB7aCFpyJAhzJs3j0WLFhETE0N6ejoAcXFxVKxY0eTRhaaYmJgiwUblypWpXr16WAchoEBEpFhLly5l+/btbN++vUiwp8lE37nttts4fPgw48ePJz09nTZt2pCcnFwkgVV8Y8aMGQBcccUVhe5/9913uffeewM/IAlrWpoRERER0yjjTkREREyjQERERERMo0BERERETKNAREREREyjQERERERMo0BERERETKNAREREREyjQERERERMo0BERERETKNAREREREyjQERERERM8/9H4RQTG6VJjwAAAABJRU5ErkJggg==" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[0. 1.05815835 1.00300147] 0.45741832011044625\n", - "The estimated coefficients are a= 1.0030014670964105 , b= 1.0581583492954199 and c= 0.45741832011044625\n" - ] - } - ], - "execution_count": 53 + "print(\n", + " \"The estimated coefficients are a=\",\n", + " poly2_bis_reg.coef_[2],\n", + " \", b=\",\n", + " poly2_bis_reg.coef_[1],\n", + " \"and c=\",\n", + " poly2_bis_reg.intercept_,\n", + ")" + ] }, { "cell_type": "code", + "execution_count": 61, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:56:27.580084Z", "start_time": "2025-01-22T09:56:27.504624Z" } }, - "source": [ - "# Answer for Exercise 13 ($3^{rd}$ degree)\n", - "poly3 = PolynomialFeatures(degree=3)\n", - "poly3.fit(X)\n", - "X3_bis = poly3.transform(X)\n", - "\n", - "poly3_reg = LinearRegression()\n", - "poly3_reg.fit(X3_bis, y)\n", - "\n", - "plt.scatter(x, y, label='Sample')\n", - "plt.plot(x, poly3_reg.predict(X3_bis), color='r', label='Regression')\n", - "plt.legend()\n", - "plt.show()\n", - "\n", - "print(poly3_reg.coef_, poly3_reg.intercept_)\n", - "print(\"The estimated coefficients are a=\", poly3_reg.coef_[3], \", b=\", poly3_reg.coef_[2], \", c=\", poly3_reg.coef_[1],\n", - " \"and d=\", poly3_reg.intercept_)" - ], "outputs": [ { "data": { + "image/png": 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", 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" + ] }, "metadata": {}, "output_type": "display_data" @@ -1568,7 +1577,32 @@ ] } ], - "execution_count": 61 + "source": [ + "# Answer for Exercise 13 ($3^{rd}$ degree)\n", + "poly3 = PolynomialFeatures(degree=3)\n", + "poly3.fit(X)\n", + "X3_bis = poly3.transform(X)\n", + "\n", + "poly3_reg = LinearRegression()\n", + "poly3_reg.fit(X3_bis, y)\n", + "\n", + "plt.scatter(x, y, label=\"Sample\")\n", + "plt.plot(x, poly3_reg.predict(X3_bis), color=\"r\", label=\"Regression\")\n", + "plt.legend()\n", + "plt.show()\n", + "\n", + "print(poly3_reg.coef_, poly3_reg.intercept_)\n", + "print(\n", + " \"The estimated coefficients are a=\",\n", + " poly3_reg.coef_[3],\n", + " \", b=\",\n", + " poly3_reg.coef_[2],\n", + " \", c=\",\n", + " poly3_reg.coef_[1],\n", + " \"and d=\",\n", + " poly3_reg.intercept_,\n", + ")" + ] }, { "cell_type": "markdown", @@ -1586,16 +1620,13 @@ }, { "cell_type": "code", + "execution_count": 62, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:57:11.033033Z", "start_time": "2025-01-22T09:57:11.029811Z" } }, - "source": [ - "XX = np.arange(6).reshape(3, 2)\n", - "print(XX)" - ], "outputs": [ { "name": "stdout", @@ -1607,20 +1638,20 @@ ] } ], - "execution_count": 62 + "source": [ + "XX = np.arange(6).reshape(3, 2)\n", + "print(XX)" + ] }, { "cell_type": "code", + "execution_count": 63, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:57:11.899363Z", "start_time": "2025-01-22T09:57:11.893990Z" } }, - "source": [ - "poly2 = PolynomialFeatures(2)\n", - "poly2.fit_transform(XX)" - ], "outputs": [ { "data": { @@ -1635,20 +1666,20 @@ "output_type": "execute_result" } ], - "execution_count": 63 + "source": [ + "poly2 = PolynomialFeatures(2)\n", + "poly2.fit_transform(XX)" + ] }, { "cell_type": "code", + "execution_count": 64, "metadata": { "ExecuteTime": { "end_time": "2025-01-22T09:57:12.753351Z", "start_time": "2025-01-22T09:57:12.748167Z" } }, - "source": [ - "poly2_bis = PolynomialFeatures(2, interaction_only=True)\n", - "poly2_bis.fit_transform(XX)" - ], "outputs": [ { "data": { @@ -1663,11 +1694,14 @@ "output_type": "execute_result" } ], - "execution_count": 64 + "source": [ + "poly2_bis = PolynomialFeatures(2, interaction_only=True)\n", + "poly2_bis.fit_transform(XX)" + ] }, { - "metadata": {}, "cell_type": "markdown", + "metadata": {}, "source": [ "### Answer for Exercise 14\n", "The output of PolynomialFeatures(2) corresponds to $[1, x_1, x_2, x_1^2, x_1x_2, x_2^2]$\n", @@ -1676,11 +1710,11 @@ ] }, { - "metadata": {}, "cell_type": "code", - "outputs": [], "execution_count": null, - "source": "" + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/M1/Statistical Learning/TP2_KNN.ipynb b/M1/Statistical Learning/TP2_KNN.ipynb index e092724..e75342f 100644 --- a/M1/Statistical Learning/TP2_KNN.ipynb +++ b/M1/Statistical Learning/TP2_KNN.ipynb @@ -60,24 +60,45 @@ }, { "cell_type": "code", + "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T11:00:08.826606Z", "start_time": "2025-03-19T11:00:08.811426Z" } }, - "source": "import numpy as np", "outputs": [], - "execution_count": 7 + "source": [ + "import numpy as np" + ] }, { + "cell_type": "code", + "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:17.854652Z", "start_time": "2025-02-07T16:32:17.851755Z" } }, - "cell_type": "code", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9.0\n", + "4.0\n", + "10.000000000000002\n", + "5.000000000000001\n", + "2.0000000000000004\n", + "2.9999999999999996\n", + "The nearest neighbor is the observation [4]\n", + "The predicted value is [4]\n", + "The nearest neighbor is the observation [4 5 1]\n", + "The predicted value is [4 5 1]\n" + ] + } + ], "source": [ "X0 = np.array([0, 0, 0])\n", "X1 = np.array([0, 3, 0])\n", @@ -98,30 +119,11 @@ " near = np.argsort(distances)[:k]\n", " print(f\"The nearest neighbor is the observation {near}\")\n", " print(f\"The predicted value is {near}\")" - ], - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "9.0\n", - "4.0\n", - "10.000000000000002\n", - "5.000000000000001\n", - "2.0000000000000004\n", - "2.9999999999999996\n", - "The nearest neighbor is the observation [4]\n", - "The predicted value is [4]\n", - "The nearest neighbor is the observation [4 5 1]\n", - "The predicted value is [4 5 1]\n" - ] - } - ], - "execution_count": 2 + ] }, { - "metadata": {}, "cell_type": "markdown", + "metadata": {}, "source": "## 1. K-NN classification for `Iris` " }, { @@ -165,21 +167,21 @@ }, { "cell_type": "code", + "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T11:00:12.701811Z", "start_time": "2025-03-19T11:00:12.595101Z" } }, + "outputs": [], "source": [ "from sklearn import datasets\n", "\n", "iris = datasets.load_iris()\n", "X = iris.data\n", "y = iris.target" - ], - "outputs": [], - "execution_count": 8 + ] }, { "cell_type": "markdown", @@ -190,17 +192,13 @@ }, { "cell_type": "code", + "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:18.569068Z", "start_time": "2025-02-07T16:32:18.566479Z" } }, - "source": [ - "# Answer for Exercise 2\n", - "print(np.shape(X))\n", - "print(np.shape(y))" - ], "outputs": [ { "name": "stdout", @@ -211,7 +209,11 @@ ] } ], - "execution_count": 4 + "source": [ + "# Answer for Exercise 2\n", + "print(np.shape(X))\n", + "print(np.shape(y))" + ] }, { "cell_type": "markdown", @@ -222,19 +224,21 @@ }, { "cell_type": "code", + "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:18.644913Z", "start_time": "2025-02-07T16:32:18.609906Z" } }, + "outputs": [], "source": [ "from sklearn.model_selection import train_test_split\n", "\n", - "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)" - ], - "outputs": [], - "execution_count": 5 + "X_train, X_test, y_train, y_test = train_test_split(\n", + " X, y, test_size=0.33, random_state=42\n", + ")" + ] }, { "cell_type": "markdown", @@ -247,19 +251,13 @@ }, { "cell_type": "code", + "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:18.656592Z", "start_time": "2025-02-07T16:32:18.654009Z" } }, - "source": [ - "#Answer for Exercise 3 \n", - "print(np.shape(X_train))\n", - "print(np.shape(X_test))\n", - "print(np.shape(y_train))\n", - "print(np.shape(y_test))" - ], "outputs": [ { "name": "stdout", @@ -272,7 +270,13 @@ ] } ], - "execution_count": 6 + "source": [ + "# Answer for Exercise 3\n", + "print(np.shape(X_train))\n", + "print(np.shape(X_test))\n", + "print(np.shape(y_train))\n", + "print(np.shape(y_test))" + ] }, { "cell_type": "markdown", @@ -292,18 +296,18 @@ }, { "cell_type": "code", + "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:18.668040Z", "start_time": "2025-02-07T16:32:18.666273Z" } }, + "outputs": [], "source": [ "def euc_dis(sample1, sample2):\n", " return np.linalg.norm(sample1 - sample2, axis=1) ** 2" - ], - "outputs": [], - "execution_count": 7 + ] }, { "cell_type": "markdown", @@ -327,28 +331,13 @@ }, { "cell_type": "code", + "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:18.698079Z", "start_time": "2025-02-07T16:32:18.695117Z" } }, - "source": [ - "# np.argsort \n", - "\n", - "distance_ex = np.array([4, 4, 4, 3, 3, 3, 2, 2, 2, 1, 1, 0.5, 0.2])\n", - "print(\"The indices where the 4 smallest digits are located are \\n\", np.argsort(distance_ex)[:4])\n", - "print(\"The 4 smallest digits are \", distance_ex[np.argsort(distance_ex)[:4]])\n", - "\n", - "print(\"\\n\")\n", - "\n", - "# counter.most_common()\n", - "\n", - "from collections import Counter\n", - "\n", - "print(\"In 'aabbbbccccccc', the frequencies of the letters are : \\n\", Counter('aabbbbccccccc').most_common())\n", - "print(\"In 'aabbbbccccccc', The letter that repeats the most is \", Counter('aabbbbccccccc').most_common()[0][0])" - ], "outputs": [ { "name": "stdout", @@ -365,16 +354,42 @@ ] } ], - "execution_count": 8 + "source": [ + "# np.argsort\n", + "\n", + "distance_ex = np.array([4, 4, 4, 3, 3, 3, 2, 2, 2, 1, 1, 0.5, 0.2])\n", + "print(\n", + " \"The indices where the 4 smallest digits are located are \\n\",\n", + " np.argsort(distance_ex)[:4],\n", + ")\n", + "print(\"The 4 smallest digits are \", distance_ex[np.argsort(distance_ex)[:4]])\n", + "\n", + "print(\"\\n\")\n", + "\n", + "# counter.most_common()\n", + "\n", + "from collections import Counter\n", + "\n", + "print(\n", + " \"In 'aabbbbccccccc', the frequencies of the letters are : \\n\",\n", + " Counter(\"aabbbbccccccc\").most_common(),\n", + ")\n", + "print(\n", + " \"In 'aabbbbccccccc', The letter that repeats the most is \",\n", + " Counter(\"aabbbbccccccc\").most_common()[0][0],\n", + ")" + ] }, { "cell_type": "code", + "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:18.727024Z", "start_time": "2025-02-07T16:32:18.725108Z" } }, + "outputs": [], "source": [ "from collections import Counter\n", "\n", @@ -383,9 +398,7 @@ " distances = euc_dis(X_train, x_new)\n", " nearest_neighbors = np.argsort(distances)[:K]\n", " return Counter(y_train[nearest_neighbors]).most_common(1)[0][0]" - ], - "outputs": [], - "execution_count": 9 + ] }, { "cell_type": "markdown", @@ -413,16 +426,13 @@ }, { "cell_type": "code", + "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:18.747162Z", "start_time": "2025-02-07T16:32:18.743867Z" } }, - "source": [ - "a = np.array([[1, 2], [3, 4]])\n", - "a" - ], "outputs": [ { "data": { @@ -436,19 +446,20 @@ "output_type": "execute_result" } ], - "execution_count": 10 + "source": [ + "a = np.array([[1, 2], [3, 4]])\n", + "a" + ] }, { "cell_type": "code", + "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:18.803162Z", "start_time": "2025-02-07T16:32:18.798675Z" } }, - "source": [ - "a.sum()" - ], "outputs": [ { "data": { @@ -461,19 +472,19 @@ "output_type": "execute_result" } ], - "execution_count": 11 + "source": [ + "a.sum()" + ] }, { "cell_type": "code", + "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:18.862775Z", "start_time": "2025-02-07T16:32:18.859640Z" } }, - "source": [ - "a.sum(axis=1)" - ], "outputs": [ { "data": { @@ -486,19 +497,19 @@ "output_type": "execute_result" } ], - "execution_count": 12 + "source": [ + "a.sum(axis=1)" + ] }, { "cell_type": "code", + "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:18.936458Z", "start_time": "2025-02-07T16:32:18.932745Z" } }, - "source": [ - "a.sum(axis=0)" - ], "outputs": [ { "data": { @@ -511,7 +522,9 @@ "output_type": "execute_result" } ], - "execution_count": 13 + "source": [ + "a.sum(axis=0)" + ] }, { "cell_type": "markdown", @@ -523,16 +536,13 @@ }, { "cell_type": "code", + "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:18.973366Z", "start_time": "2025-02-07T16:32:18.970454Z" } }, - "source": [ - "b = np.arange(8).reshape(2, 2, 2)\n", - "b" - ], "outputs": [ { "data": { @@ -549,17 +559,20 @@ "output_type": "execute_result" } ], - "execution_count": 14 + "source": [ + "b = np.arange(8).reshape(2, 2, 2)\n", + "b" + ] }, { "cell_type": "code", + "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:19.006689Z", "start_time": "2025-02-07T16:32:19.003910Z" } }, - "source": "b.sum(axis=0), b.sum(axis=1), b.sum(axis=2), b.sum()", "outputs": [ { "data": { @@ -578,7 +591,9 @@ "output_type": "execute_result" } ], - "execution_count": 15 + "source": [ + "b.sum(axis=0), b.sum(axis=1), b.sum(axis=2), b.sum()" + ] }, { "cell_type": "markdown", @@ -599,18 +614,18 @@ }, { "cell_type": "code", + "execution_count": 16, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:19.039310Z", "start_time": "2025-02-07T16:32:19.037538Z" } }, + "outputs": [], "source": [ "def euc_dis_mat(sample1, sample2):\n", " return np.linalg.norm(sample1 - sample2, axis=1) ** 2" - ], - "outputs": [], - "execution_count": 16 + ] }, { "cell_type": "markdown", @@ -633,21 +648,21 @@ }, { "cell_type": "code", + "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:19.076151Z", "start_time": "2025-02-07T16:32:19.073174Z" } }, + "outputs": [], "source": [ "def knn_class_2(X_train, y_train, x_new, K):\n", " X_new = np.tile(x_new, (len(X_train), 1))\n", " distances = euc_dis_mat(X_train, X_new)\n", " k_neighbors = np.argsort(distances)[:K]\n", " return Counter(y_train[k_neighbors]).most_common()[0][0]" - ], - "outputs": [], - "execution_count": 17 + ] }, { "cell_type": "markdown", @@ -665,19 +680,13 @@ }, { "cell_type": "code", + "execution_count": 18, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:19.114434Z", "start_time": "2025-02-07T16:32:19.109526Z" } }, - "source": [ - "predictions = [knn_classifier(X_train, y_train, data, 3) for data in X_test]\n", - "predictions2 = [knn_class_2(X_train, y_train, data, 3) for data in X_test]\n", - "\n", - "print(f\"The accuracy rate of our classifier is {np.sum(predictions == y_test) / len(predictions) * 100}%\")\n", - "print(f\"The accuracy rate of our classifier is {np.sum(predictions2 == y_test) / len(predictions2) * 100}%\")" - ], "outputs": [ { "name": "stdout", @@ -688,7 +697,17 @@ ] } ], - "execution_count": 18 + "source": [ + "predictions = [knn_classifier(X_train, y_train, data, 3) for data in X_test]\n", + "predictions2 = [knn_class_2(X_train, y_train, data, 3) for data in X_test]\n", + "\n", + "print(\n", + " f\"The accuracy rate of our classifier is {np.sum(predictions == y_test) / len(predictions) * 100}%\"\n", + ")\n", + "print(\n", + " f\"The accuracy rate of our classifier is {np.sum(predictions2 == y_test) / len(predictions2) * 100}%\"\n", + ")" + ] }, { "cell_type": "markdown", @@ -706,19 +725,19 @@ }, { "cell_type": "code", + "execution_count": 19, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:19.215397Z", "start_time": "2025-02-07T16:32:19.148514Z" } }, + "outputs": [], "source": [ "from sklearn.neighbors import KNeighborsClassifier\n", "\n", "knn_classifier_2 = KNeighborsClassifier(n_neighbors=3)" - ], - "outputs": [], - "execution_count": 19 + ] }, { "cell_type": "markdown", @@ -729,19 +748,16 @@ }, { "cell_type": "code", + "execution_count": 20, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:19.233667Z", "start_time": "2025-02-07T16:32:19.227889Z" } }, - "source": "knn_classifier_2.fit(X_train, y_train)", "outputs": [ { "data": { - "text/plain": [ - "KNeighborsClassifier(n_neighbors=3)" - ], "text/html": [ "
KNeighborsClassifier(n_neighbors=3)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + ], + "text/plain": [ + "KNeighborsClassifier(n_neighbors=3)" ] }, "execution_count": 20, @@ -1166,7 +1185,9 @@ "output_type": "execute_result" } ], - "execution_count": 20 + "source": [ + "knn_classifier_2.fit(X_train, y_train)" + ] }, { "cell_type": "markdown", @@ -1177,13 +1198,13 @@ }, { "cell_type": "code", + "execution_count": 21, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:19.260546Z", "start_time": "2025-02-07T16:32:19.254828Z" } }, - "source": "knn_classifier_2.score(X_test, y_test)", "outputs": [ { "data": { @@ -1196,7 +1217,9 @@ "output_type": "execute_result" } ], - "execution_count": 21 + "source": [ + "knn_classifier_2.score(X_test, y_test)" + ] }, { "cell_type": "markdown", @@ -1242,29 +1265,39 @@ }, { "cell_type": "code", + "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T11:00:20.853667Z", "start_time": "2025-03-19T11:00:20.714184Z" } }, + "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "from itertools import product\n", "from sklearn.neighbors import KNeighborsClassifier" - ], - "outputs": [], - "execution_count": 9 + ] }, { "cell_type": "code", + "execution_count": 23, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:19.575414Z", "start_time": "2025-02-07T16:32:19.570441Z" } }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(200, 2) (200,)\n" + ] + } + ], "source": [ "rng = np.random.default_rng(seed=12)\n", "num_observations = 100\n", @@ -1276,30 +1309,17 @@ "Y2 = np.hstack((np.zeros(num_observations), np.ones(num_observations)))\n", "\n", "print(X2.shape, Y2.shape)" - ], - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(200, 2) (200,)\n" - ] - } - ], - "execution_count": 23 + ] }, { "cell_type": "code", + "execution_count": 24, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:19.693282Z", "start_time": "2025-02-07T16:32:19.599201Z" } }, - "source": [ - "plt.figure(figsize=(8, 6))\n", - "plt.scatter(X2[:, 0], X2[:, 1], c=Y2, alpha=0.4)" - ], "outputs": [ { "data": { @@ -1313,16 +1333,19 @@ }, { "data": { + "image/png": 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", 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" + ] }, "metadata": {}, "output_type": "display_data" } ], - "execution_count": 24 + "source": [ + "plt.figure(figsize=(8, 6))\n", + "plt.scatter(X2[:, 0], X2[:, 1], c=Y2, alpha=0.4)" + ] }, { "cell_type": "markdown", @@ -1333,12 +1356,14 @@ }, { "cell_type": "code", + "execution_count": 25, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:19.710747Z", "start_time": "2025-02-07T16:32:19.706881Z" } }, + "outputs": [], "source": [ "nb_neighbors = [1, 3, 5, 7, 9, 11]\n", "\n", @@ -1348,9 +1373,7 @@ " knn_classifier_k = KNeighborsClassifier(n_neighbors=k)\n", " knn_classifier_k.fit(X2, Y2)\n", " KNNs.append(knn_classifier_k)" - ], - "outputs": [], - "execution_count": 25 + ] }, { "cell_type": "markdown", @@ -1361,12 +1384,25 @@ }, { "cell_type": "code", + "execution_count": 26, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:20.615872Z", "start_time": "2025-02-07T16:32:19.741060Z" } }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "x_min, x_max = X2[:, 0].min() - 1, X2[:, 0].max() + 1\n", "y_min, y_max = X2[:, 1].min() - 1, X2[:, 1].max() + 1\n", @@ -1374,7 +1410,9 @@ "xx, yy = np.meshgrid(np.arange(x_min, x_max, 0.1), np.arange(y_min, y_max, 0.1))\n", "f, axarr = plt.subplots(2, 3, sharex=\"col\", sharey=\"row\", figsize=(15, 12))\n", "\n", - "for idx, clf, tt in zip(product([0, 1, 2], [0, 1, 2]), KNNs, [f\"KNN (k={k})\" for k in nb_neighbors]):\n", + "for idx, clf, tt in zip(\n", + " product([0, 1, 2], [0, 1, 2]), KNNs, [f\"KNN (k={k})\" for k in nb_neighbors]\n", + "):\n", " Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n", " Z = Z.reshape(xx.shape)\n", "\n", @@ -1382,21 +1420,8 @@ " axarr[idx[0], idx[1]].scatter(X2[:, 0], X2[:, 1], c=Y2, s=20, edgecolor=\"k\")\n", " axarr[idx[0], idx[1]].set_title(tt)\n", "\n", - "plt.show()\n" - ], - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ], - "image/png": 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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 26 + "plt.show()" + ] }, { "cell_type": "markdown", @@ -1435,19 +1460,19 @@ }, { "cell_type": "code", + "execution_count": 27, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:23.064353Z", "start_time": "2025-02-07T16:32:20.623241Z" } }, + "outputs": [], "source": [ "from sklearn.datasets import fetch_openml\n", "\n", - "mnist = fetch_openml('mnist_784')" - ], - "outputs": [], - "execution_count": 27 + "mnist = fetch_openml(\"mnist_784\")" + ] }, { "cell_type": "markdown", @@ -1458,60 +1483,16 @@ }, { "cell_type": "code", + "execution_count": 28, "metadata": { "ExecuteTime": { "end_time": "2025-02-07T16:32:23.107290Z", "start_time": "2025-02-07T16:32:23.095904Z" } }, - "source": [ - "mnist.data" - ], "outputs": [ { "data": { - "text/plain": [ - " pixel1 pixel2 pixel3 pixel4 pixel5 pixel6 pixel7 pixel8 pixel9 \\\n", - "0 0 0 0 0 0 0 0 0 0 \n", - "1 0 0 0 0 0 0 0 0 0 \n", - "2 0 0 0 0 0 0 0 0 0 \n", - "3 0 0 0 0 0 0 0 0 0 \n", - "4 0 0 0 0 0 0 0 0 0 \n", - "... ... ... ... ... ... ... ... ... ... \n", - "69995 0 0 0 0 0 0 0 0 0 \n", - "69996 0 0 0 0 0 0 0 0 0 \n", - "69997 0 0 0 0 0 0 0 0 0 \n", - "69998 0 0 0 0 0 0 0 0 0 \n", - "69999 0 0 0 0 0 0 0 0 0 \n", - "\n", - " pixel10 ... pixel775 pixel776 pixel777 pixel778 pixel779 \\\n", - "0 0 ... 0 0 0 0 0 \n", - "1 0 ... 0 0 0 0 0 \n", - "2 0 ... 0 0 0 0 0 \n", - "3 0 ... 0 0 0 0 0 \n", - "4 0 ... 0 0 0 0 0 \n", - "... ... ... ... ... ... ... ... \n", - "69995 0 ... 0 0 0 0 0 \n", - "69996 0 ... 0 0 0 0 0 \n", - "69997 0 ... 0 0 0 0 0 \n", - "69998 0 ... 0 0 0 0 0 \n", - "69999 0 ... 0 0 0 0 0 \n", - "\n", - " pixel780 pixel781 pixel782 pixel783 pixel784 \n", - "0 0 0 0 0 0 \n", - "1 0 0 0 0 0 \n", - "2 0 0 0 0 0 \n", - "3 0 0 0 0 0 \n", - "4 0 0 0 0 0 \n", - "... ... ... ... ... ... \n", - "69995 0 0 0 0 0 \n", - "69996 0 0 0 0 0 \n", - "69997 0 0 0 0 0 \n", - "69998 0 0 0 0 0 \n", - "69999 0 0 0 0 0 \n", - "\n", - "[70000 rows x 784 columns]" - ], "text/html": [ "
\n", "
LogisticRegression(penalty=None)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + ], + "text/plain": [ + "LogisticRegression(penalty=None)" ] }, "execution_count": 34, @@ -266,7 +270,11 @@ "output_type": "execute_result" } ], - "execution_count": 34 + "source": [ + "# Answer for Exercise 3\n", + "reg_log = LogisticRegression(penalty=None, fit_intercept=True)\n", + "reg_log" + ] }, { "cell_type": "markdown", @@ -277,24 +285,21 @@ }, { "cell_type": "code", + "execution_count": 35, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:31:44.569660Z", "start_time": "2025-03-19T09:31:44.555547Z" } }, - "source": [ - "# Answer for Exercise 4\n", - "reg_log.fit(X, y)" - ], "outputs": [ { "data": { - "text/plain": [ - "LogisticRegression(penalty=None)" - ], "text/html": [ "
LogisticRegression(penalty=None)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + ], + "text/plain": [ + "LogisticRegression(penalty=None)" ] }, "execution_count": 35, @@ -302,7 +307,10 @@ "output_type": "execute_result" } ], - "execution_count": 35 + "source": [ + "# Answer for Exercise 4\n", + "reg_log.fit(X, y)" + ] }, { "cell_type": "markdown", @@ -315,20 +323,13 @@ }, { "cell_type": "code", + "execution_count": 36, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:31:45.551736Z", "start_time": "2025-03-19T09:31:45.548903Z" } }, - "source": [ - "# Answer for Exercise 5 (1)\n", - "a1, a2 = reg_log.coef_[0]\n", - "b = reg_log.intercept_[0]\n", - "\n", - "print(\"The coefficients are : \", a1, \",\", a2)\n", - "print(\"The intercept is : \", b)" - ], "outputs": [ { "name": "stdout", @@ -339,11 +340,18 @@ ] } ], - "execution_count": 36 + "source": [ + "# Answer for Exercise 5 (1)\n", + "a1, a2 = reg_log.coef_[0]\n", + "b = reg_log.intercept_[0]\n", + "\n", + "print(\"The coefficients are : \", a1, \",\", a2)\n", + "print(\"The intercept is : \", b)" + ] }, { - "metadata": {}, "cell_type": "markdown", + "metadata": {}, "source": [ "We have $w^T * x + b = 0$\n", "\n", @@ -354,36 +362,43 @@ }, { "cell_type": "code", + "execution_count": 37, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:31:46.940096Z", "start_time": "2025-03-19T09:31:46.727016Z" } }, - "source": [ - "# Answer for Exercise 5 (2)\n", - "plt.figure(figsize=(8, 8))\n", - "plt.scatter(X[:, 0], X[:, 1], c=y, alpha=0.3, cmap=mcolors.ListedColormap([\"steelblue\", \"tomato\"]), label=\"Sample\")\n", - "\n", - "x1 = np.linspace(-4, 4, 100)\n", - "x2_learn = -(a1 * x1 + b) / a2 # Cf above\n", - "plt.plot(x1, x2_learn, label='Logistic Regression', c='green')\n", - "plt.legend()\n", - "plt.show()" - ], "outputs": [ { "data": { + "image/png": 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", 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/P173utfhhRdeWNjXWq2GP/7jP8aXv/xl6LqOn/3Zn8V//a//FV/5ylcu+BgqKCgoKAColjmVaWaSkUuGQSV3eCdVXYVrGtcV8azZNSQ+mliXdVceqCAeurCeynPhz//8zzE8PIw/+7M/g6Zp2Lt3LyYmJvD+978fH/zgB1GtVvGlL30Jf/VXf4VXv/rVAIAvfOELGBgYWHWZZ8+eRV9fH17zmtfAsixs2bIFd911FwCWjQ3DQDKZRF/f6r+w/+N//A+87W1vw4c//OGF12655ZZz7kuxWEQikeADQY0PBD/5kz+JvXv3AgA+9rGP4ad/+qcX1MPdu3fjU5/6FF7+8pfj05/+NEZGRvDd734Xjz/+OO68804AwOc//3ns3r172bp++qd/Gv/5P//nhX//3M/9HD7wgQ/g53/+5wEAO3bswEc+8hG8733vw4MPPnjOY3L27FnE43G84Q1vQDKZxNatW3HbbbetuI+ScD7yyCN4yUteAgD4yle+guHhYXzjG9/AW97yFgAs/3/mM5/Bzp3MonvnO9+J3/3d3z3n8VNQUFBQWIJaFXj+IJCb5VSmRBpwbf67lAf23c4RoQrXLFSp/RrD4cOHcc899yxST++9915UKhWMjY3h1KlTsG17gSQBQDqdxg033LDqMt/ylregXq9jx44duP/++/H1r399Ucn5QvD0008vEN0LRTKZxNNPP42DBw8ukK7PfOYzC+8fPHgQX/ziF5FIJBZ+7rvvPnieh9OnT+Po0aMwTRO33377wnd27dqFbDa7bF2SmLYv+3d/93cXLfv+++/H5OQkarXaOY/Ja1/7WmzduhU7duzAz/3cz+ErX/nKAnFeisOHD8M0Tdx9990Lr3V2duKGG27A4cOHF16LxWILpBMA+vv7V1RuFRQUFBTOgYkRjvrsGeTcecPgFKauPpbbTx8BLvL+pnB1cV0pnjErhsoDlXVb91rA9/1lJXvf9wGwl7H97yt9ZiUMDw/j6NGj+M53voPvfve7+LVf+zV87GMfw/e///0LdmdHoxc/qkzXdezatQsAsHfvXkxNTeGtb30rHn74YQCA53n4lV/5lUW9lRJbtmxZ1AvajpX2damD3/M8fPjDH16xDzUSiZzzmCSTSTz55JN46KGH8E//9E/44Ac/iA996EN4/PHHl/W9rnbcl57Hpce5/VwqKCgoKFwA7BYD5hOplfNH0x1AbgYozgOdvVd/+xQuCNeV4qlpGuKh+Lr8rEV/JwDs378fjz766CJS8uijjyKZTGJwcBA7d+6EZVn48Y9/vPB+qVRaZGZZCdFoFD/5kz+JT33qU3jooYfw2GOP4dChQwCAUCgE13XP+f2bb74Z3/ve9y5jz4D3vOc9eOaZZ/D1r38dAHD77bfj+eefx65du5b9hEIh7N27F47j4KmnnlpYxokTJ1AoFM67rttvvx1Hjx5dcdm6+B/WuY6JaZp4zWtegz/6oz/Cs88+i5GREfzzP//zsvXs378fjuPgRz/60cJr8/PzOHbsGPbt23c5h0tBQUFBoR2OzZ9QeOX3DRPwfRJUhWsW15XiuZFQLBbx9NNPL3qto6MDv/Zrv4Y/+ZM/wW/8xm/gne98J44ePYoHH3wQ733ve6HrOpLJJH7+538ev/3bv42Ojg709PTgwQcfhK7rq5LfL37xi3BdF3fffTdisRi+/OUvIxqNYuvWrQDogH/44Yfxtre9DeFwGF1dXcuW8eCDD+LVr341du7cibe97W1wHAd///d/j/e9730XvM+pVAq//Mu/jAcffBD/4T/8B7z//e/Hi1/8Yvz6r/867r//fsTjcRw+fBjf+c538Kd/+qfYu3cvXvOa1+Ad73gHPv3pT8OyLPzWb/0WotHoeYn+Bz/4QbzhDW/A8PAw3vKWt0DXdTz77LM4dOgQfu/3fu+cx+Rb3/oWTp06hZe97GXIZrP49re/Dc/zVmxn2L17N974xjfi/vvvx//6X/8LyWQSH/jABzA4OIg3vvGNF3xsFBQUFBTOA9PiT6sFhFeowrkOAI2fUbhmcV0pnhsJDz30EG677bZFPx/84AcxODiIb3/72/jxj3+MW265Bb/6q7+KX/qlX8J//+//feG7n/jEJ3DPPffgDW94A17zmtfg3nvvxb59+xCJrDzLNpPJ4HOf+xzuvffeBeXyb//2b9HZ2QkA+N3f/V2MjIxg586d6O7uXnEZr3jFK/C1r30N3/zmN3HrrbfiVa961SKV70Lx7ne/G4cPH8bXvvY13Hzzzfj+97+P48eP46UvfSluu+02/H//3/+H/v7+hc//5V/+JXp7e/Gyl70M//E//kfcf//9SCaTq+6rxH333Ydvfetb+M53voMXvehFePGLX4xPfOITC2T7XMckk8ngb/7mb/CqV70K+/btw2c+8xn8n//zf1YNvv/CF76AO+64A294wxtwzz33wPd9fPvb31Yh8woKCgprCSsE9A0B1dLK8UnFPMPxM51XfdMULhyafw03mpVKJaTTaRSLRaRSqUXvNRoNnD59Gtu3bz8vCbneUa1WMTg4iI9//OP4pV/6pfXenCuKsbExDA8P47vf/e5Fm502CtS1raCgoLAKalXg0ONAfg5IZ6l8OjYd7YYJ7L8N6B1c763cdDgXX1sKVWrfgHjqqadw5MgR3HXXXSgWiwuxPNdjafef//mfUalUcNNNN2FychLve9/7sG3bNrzsZS9b701TUFBQULjaiMU5Z/7McWB2EigXAdMEsl3Alp1Ad//5l6GwrlDEc4Pij//4j3H06FGEQiHccccd+MEPfrBib+ZGh23b+J3f+R2cOnUKyWQSL3nJS/CVr3xFlbEVFBQUNisSSeDA7QySbzU5AjSZXtnprnDNQRHPDYjbbrsNBw8eXO/NuCq47777cN999633ZigoKCgoXGuIJ/lzLcN1gbrIgY7FSJI3ORTxVFBQUFBQUFBYS3guMDkKjJ8BKiW+lkgDQ1uBvuFNrc5ueOJ5DXujFBQuCeqaVlBQUNjA8Dzg1BHg5BEgFGJrAABUi8BzB2mQ2rkPWKP8742GDUs8ZY9frVa7pKk6CgrXKlothh8bhirJKCgoKGw4FHPAmROMdoq2TdULRYBaBTh7Aujq3bSxTxuWeBqGgUwmszDvOhaLrdn0IAWF9YLneZidnUUsFoNpbthfTwUFBYXNi9kpRjxF44DvBSYoaEA8wffmphTxvFIYHx/H+9//fvz93/896vU69uzZg7/4i7/AHXfccdnL7uvrA4AF8qmgcD1A13Vs2bJFPUgpKCgobETUq4AV5p8TZ4ByiQTU9znu0zSBnoH13sp1wxUlnvl8Hvfeey9e+cpX4u///u/R09ODkydPIpPJrMnyNU1Df38/enp6YNv2mixTQWG9EQqFFubJKygobEJ4HlCYpypWLQPhCPMps90kLQrXNkKCdM5OAvUKEE/zvPk+lc+ZcaCzl//ehALDFb2C//AP/xDDw8P4whe+sPDatm3b1nw9hmGofjgFBQUFhY0PzwVOHmaPoOvSnOI4wNgI0D8M7L2FoyMVrl109QHP/AgoFYGubkATQoKmAYYBRBNAow5UikAys66buh64orLKN7/5Tdx55514y1vegp6eHtx222343Oc+t+rnm80mSqXSoh8FBQUFBYVNg8lROqLjKY5+zHYLtbMLGB8BTh9d7y1UOB+yXRzfaTeAZpPKpu8DjRonLfUOAKYBFHLrvaXrgitKPE+dOoVPf/rT2L17N/7xH/8Rv/qrv4p3vetd+Mu//MsVP//Rj34U6XR64Wd4ePhKbp6CgoKCgsK1A9elshmKANHY4vesENWxqTGWcRWuXeg6ezh7B6lgF+f543lA3xAwsJVB8q673lu6LtD8KxgaGAqFcOedd+LRRx9deO1d73oXHn/8cTz22GPLPt9sNtFsNhf+XSqVMDw8fEFD5xUUFBQUFDY0KmXgx//CoPFQePn7vs/+wNv/DdDdd/W3T+HC8cyP2OOZyrCsDgCRKB8qPBeYmQRuvZth8tcBSqUS0un0BfG1K6p49vf3Y//+/Yte27dvH86ePbvi58PhMFKp1KIfBQUFBQWFzQMNwGp60OY0o2xI9A1R4fR9IJXlTyjC9/LzQDoDdPSs6yauF66ouejee+/F0aOL+1GOHTuGrVu3XsnVKigoKCgobDzEYlQ7K0WgI7L8/WoFiMSA5CYTZWoV/mg6kEjR5X+to7sP2LKTJjHTAmJxltarZbZR7Dqwsqq9CXBFied73vMevOQlL8Hv//7v4z/9p/+EH//4x/jsZz+Lz372s1dytQoKCgoKChsPusFZ3s8dJNGKJYL3Wg0S0l37ST43A5oNGq2mJ4BmjWpvLAEMbgO27KJD/FqFbgB7bgTSHczyrJbZ+7llJ9MJNml4PHCFezwB4Fvf+hYeeOABHD9+HNu3b8d73/te3H///Rf03YvpGVBQUFBQUNjw8Dw6188cB+wWYFiAa5PIDG4Fdt+4OeKU7BYJ+PQYy9TROMvWlRJJ+c69VA03QuuB53F/dP26PXcXw9euOPG8HCjiqaCgoKCwprBbQG6WBEbTgGT62gtm932glAfmpoF6jSXZzh4g20kCuhkwcRY49GNmYhpLzk29yuNy50tp3lFYd1wMX7uGftMUFBQUFBSuIIp54OizQH42eE3TafLYewuQSK7ftrVD01iiTXes95asH6bH2Ru5lHQCVD+LOZ7HyyGejph4aFqXvgyFi4YingoKCgoK1z8adeDwU0C5AHT1B/2BrsPRlEd84Ja7N14ptFIG5qeoApohhpdfD8pos37uc6HpwKWOys7NMqhfPoBkOulC7+zdGKX7DQ5FPBUUFBQUrn/MTXFSTO9AMMIQoKLW1Q/MTQLzMyQg64VWE8jNkCTrBhXPVGZlMuT7wNhpmm/qVe6H5wK6CfQPATfcvDJxs1sk26Z1bSt98SSn/KwE3wd899Lc7eMjwNFD7JuNCvPW5CgV1l0HgK27LnmTFS4MingqKCgoKFz/mJ8BLGsx6ZQwDL5emF8/4jk7CZx4HigWGOUJkDj2D5MQLSWRc1PAsUOAFQZ6hwJy2mqSkJoW2wckahW6q6fGOPs9FGJ4+cCWa9Ml3zNIQthqLo8dqpRIGju6L26ZlTJw8jD7edu/m0gxMeD0Eaqf6ezlb7/CqriiAfIKCgoKCgrXBDyXruLVoOv8zHqgmAMOPw3UakBPP4lk7xCjg86cIFlqh+/TfON5yxXRUJgu8KkxEi2ARO3ZHwMnXmA2fSRG8nn0EJ3j1+IIzq5eYGgby+HFHJXaZoMPEM0asG0PVdGLwdwUCXhqBWKZSHP5sxNrsvkKq0MRTwUFBQWF6x/pDhKLleB7NJokM1d1kxYwOUry19mzuDczEuN2T40GJBLgfhRzVOpWQjTOz1REqXrkGNXc3kG6+CNRkq/eAZKxs6eu3L5dKgwD2HMzVdtQmL251TKPx413Mg/zYlEtsw92NYTCq5f3FdYMqtSuoKCgoHD9o7ufJejC/PLw7vwcCVlX79XfLscm+Yufg0QWc0Ap1+a69wHPR1CTXwJNjt0UuZdzU0C6c3mbgW5Q6ZseY29jJLo2+7RWME1g624Gxtdr3P5Y7NKNU7IPdjW47sYzl21AKMVTQUFBQeH6RzLN8HVoJFrFHEno9BjJxp6bSfKuNnyfJfPztQG0R26HIkAqxbLxSmjU2fsZS1L5bDZXJ5XRGPsoV1ODrwWYFs9fInl5bv2OLv7prOCGd122H3Suw8PHJoNSPBUUFBQUNgf6h9k3OTsBzM9SGdyyk2poMr0+2yRJ1fzs4hGZEnaLSl+7AUjXgf6twNwMS/TthNl1gMIcVcJkmgTbMAIn+1I4NpXAa3n85Fqho4fnenqM5qKQcMW3moxY6upbH9V7k0ERTwUFBQWFzYN0lj/XSmqOppEQz04Bjdpigul7NNd09jKbsx29g0C1BIwcB0oFRgs5NlW7nn7OdNc09q2mOjgJqaNn+fpLBRKuizXqbESYJrDvFpLsuSmgJR4+DJNpBns2yTjSdYYingoKCgoKCuuJngFg22462CslIBylQtmosR91943LS8y6DuzYRzI5M0kjUShMRa+rl+X1uSmqpYNbgKMF9rKmsoECWsgxYmrLjs0TnB6J0ZxUyvNYAyTd6Y5ztzsorBkU8VRQUFBQUFhP6AazOjOdjEEqFwErxsig3oHVe091nSXj9kzKehU49hxzQZsN+o8iURIuuwXMT1NJ1XRGMe3Yu/n6GnWdx3qpyUzhqkARTwUFBQUFhfWGrlP57Bk4v9loNTQbwPNPcQpTuoPGoZkpYPQUR1B2DwLD26mKprNApovl54tFq8k8zXqV25nKApmOjT+mU+GqQBFPBQUFBQWFawmXWvKdmSDp7B6gunnmBNXTWIJl+FIemI1Q8ezpvzTSOT8DvPCUyB6tMJ4omgS27QJuvefai2RSuOagGhoUFBQUFBQ2OnyfZDAcZQ/n7BR7GLOdLLPHU4CukYSWCsCpo4sjmi4ElRLw9GPA8ecY6O4DMCygnAeefAR47HtUaxUUzgFFPBUUFBQUFDY6fA+wm3RltxpAcZ69oTI0XpqHPJdh8rnZwFxzoZgc5RQkIJhpnkwLV3wKOPI0cPbE4u80GyzJu+s0jlThmoMqtSsoKCgoKFwPaLU4w933WXLP9rDEruskpgAVynCE+Z6t5oUv2/eBM8dYwu/qW94OkMpwutLIcZqiCvPA+BmamTyP/aYDWxkdtVKeqMKmgSKeCgoKCgoKGxmuy/J3bgbITbOcXqsDrTGgkaVrvVFnGT6ZFqHxxsWHxter/NNYhTpYIRLamQngyDP8fCINhEyOvHz+IAnpvlsV+dzEUMRTQUFBQUFhvdBskIw5NolbtuviQ8wnzgBnjlNRNEwagBJxoN5gVmezwdL4wBYue26aLvRU5sLXoWlAIgPYx1Z+33MB+CSUJw9Tfe0dCt6PRAE7yW3t6OZkJYVNCUU8FRQUFBQULgaOTQVP04FY/NJc6L5PEnb6KFApA57D0PdEErjhFo7yvKBtcYDxEaqZ0TgwvINl7clRoD5GAmiFgP4tjD3KzVDp3Lr74uOPhncAh5/ixKR4avG+lIuAESKhLRdWzga1QpwhP3mW26MC2zclFPFUUFBQUFC4EDg2MDZC4lSvknims8DgdsYTXcz0n8lR4PDTJF+uyxJ1vc5lj5wAbr8XuOWu85ek61WgVuFoTICKZ+8Q+zAHt9LdPj9DYgiQfG7bwyzPi8X2PcDO/Szrt5oku74f9IoObqViWymtXo6PREnaXQfQ1XjKzQhFPBUUFBQUFM4HxwGOPssw9micRM9zgdwcHeJ7bwGGtl/4skZPkrhWShxtGYkB2Q4AHRyB+fRjJGn7biU5dRzObc/P8e+JFEdjSrK7NBrJMJnn2dHDbd57K8lxKnvx+Z21KuDaVCv/zb+lOWn0JAmvYQCROInsgdv5+bOnuD0rEXHH5rapsPlNC0U8FRQUFBSuHzhixjm0Sy+Dr4S5KaqdHcIpLhGOMpj91BGgs2f18ZbtKBeYpWlaJK3JzGJls6MbqJYZXdQ/zP04/AzHYAKCiNo0Ee3Yx97LSnHx6EyJWpUEdfseEkbHAabH+VOvkvD2DlAhXaquFvPA2ClgdpqtAKbFyUq33kOinZuhWpvM8PuJJNcXi3P7E6nFy/M9ktXdN168sUnhuoEingoKCgoKGx+y13HyLMmNnEU+uA3oHeRnCvPA9ASJn2lSpevuJyE7H6bHSZbaSadEMgNMj5FEDl4A8fRcRgzJHM2lhE/XRQneofrZrHP57eTQ91meP/Ec0DcMFOZI9uLJYDmNOvsx99zEfbRbVG3HzwT7Ui5yPnzfENVVuX+FeeC5J7jMVBawkjQpjRzjeze+iN9Zilicyu/x50g0Eymei1aT25juWPl7CpsGingqKCgoKFzbKOZI/OZnAA0kYD2DgSvbdYFjz7LEG4kywsf3SZDysyRgvkcjj22ThHkul9nRDey7jTFD50K1vDpB1TSSq+YF5mKGo0A4zO1bqeTcELFFpsntr5aptLYTVE2jU316nPuya78YkVng51yhUG7dDWzZxe+MngLGTtP447oktFYIiFkk7LE41UjPA04fo3rZMxiUzE2Ln5keZ6l9360r79+23fzO2AiJM3yW17v62CPaTo4VNh0U8VRQUFBQuHYxcRY4dogkKRonoTx2iEHlsq9yflqUwbuAUBs5DEeo6D33BBXEdAcJnITnAbMTXN5t95y77zAcYel5NfjehfdOJlIkYaOnWTIHqAjWq9zeYh7IZKnc1qpUIbv6Vl5WLAHk54G7bwa6+0jO6zV+p7OHaqUuFMfJUe7H9BhjluwWAJ/HLBKlYjy8k8pmfpYO9aV9mppOhXd2kuX7SGz5NukGsP0GOteLeRLjSJTHXznZNz0U8VRQUFBQuHx4LglQboaEJhIjWUqmL87t3Y5yETjxPL/fO0RCND9D0lQuAmdOAne9jIqmri8mnRKJFHDyecb/DGxd/J6uk4jmZrjtnT3Lvy/RN0Sy5TokX06Lf1ohEsRIlI7udkhD0Owktz0qTDjZLhKzmQng2R+TnLUaARmMJwBoVAmrFW5fd//K/aOaBkAYeZKZwN2+FPUqy+7lEteTSJC0AiJLNEdl9aYXkdzb9srHE2ibfNRamXhKRKL8uRqQkU7lAh8oYnEg06V6Sa9BKOKpoKCgoHB5sFtUDSfOkoAaJpW8MyeArbsY33MpStfsJBW/viGSy7MnSJyiUZaZc7OchuO4dGyvBM8jsUp1rPy+FeJnapVzE8/ufr5/4nnAdoIRlKZJ8nXTnYvL9XaL03smR0kKTYv7M3qaeZi7DzAyaXwEOHUYsF0eo55+Ljs/x2O3ZTdw6MfM/NyxbzmJr1dEcPz5CJbGY5mf5bFrjzuKRAFdo4moVCAxNgzuw0ph9naL379Yd/yVQqsJHH+eLQB2E4DGY5ntBvbceHFB+QpXHNfIVaOgoKCgsGFx+hj7Bzu6F6tk1TKn2MTiNMBcLMqFwOwyO0EzTraDSiNAxS4apwo6M07H9VJooBp2LuLrr/7WAgwTCIWARoNlf7lcgORsad/i6WMklZ29i8lbo06DTjwhIo/6SYqPPQt4PmBZjC3qjHHDLJMl9Kkx4XBvW0+lyGVcyLGNJ6nWtlorZ2zaNhCyBEnPsMxeyNMR3w7fJzkd3BoopusJz+NDz9hpEuqIcPY7NseHvtACbrn7wtIGFK4KFPFUUFBQULh01KvA1ChLvEtLs/Ekidb4GZpULlb11A0qqM0Gy9GxeEA6ASqDhkHiNXJ0uasb4HfT2dXL/c0GyZ7vkzwDK5dpZyeB6Ulg3y0kiK0GlxmNs8R76gjL9uEI45ymRmlyMi0SxGKex8I0+b2zJ6iUWiEeu3wfTUe6KN9rOlXPagXYuof7NjXOnk3D4PrDEWDXgZVjlJbCNNljOT3B7WsvkTfrJKSZbh5v3eA6K09wvGY6y21qNVlijyeo2l4LKOUDk1j79WdaJPXT42xp2Lp7/bZRYREU8VRQUFBQuHRUSiSfK6mNALMdywWSnYtVyDp7SFpbTSpY7aqV5wVxPYk0DTPT4yzLSxNStcQS+p5buA35OWGYEeTVbpFQ+h7jf2ybSqZukMjsuSkon0+NLe4jjUT5PbslDD6zLP33D5Mk1mtCqRyls9tzhdvcZX9oYZ4lcivE9Rkmf9rVURmpZBg0UW2/geTVcYBUmsQqvUoLwUoY3Cb6VF0eC13ndlkhoH+I+y6PcXcfcOAOzoAv5LgdVogK6LY9F7fey4Xn8XjlZngtRGJUklMZbpuzSj+qppPMT08q4nkNQRFPBQUFBYU1wGoGIo2l7KWTdS4Enb10qk+N8d9yzKLrkEhKM43r0kHd1QNUKnwPGpW53TcyTmh+muRyepxEz/eoPDo21cBkOiAvjs3AeMcBbn0xCVe1HBhlPI+ZlPOzouyukYD2T5B4ymORn+f6IrHFUUytBglgIsXtT2VJnou5gND5fkAKS3katXYduDxXeO8gyaphkfw6Lf49mea+uvbi0rrsay0VRCleqLNX05nuODxv4yOChJv8c+Q4e2DP1ydhGNwvhWsGingqKCgoKFw6YgkgHKPquZKiWSsD8fS53c+rIRxhxqamsY9zepwKqqaTrA1uJxHJz5GY3f4SMbu8Su6XzASEr3eQJeP5GZJIGZ108jDVzXal0bQ4bnJmnARxaDvL8bUqCevECGegmyYQigLwuNwTL1D57ehmuf7MCa5naf5nq0Xji2FSCbab3P5qmSQznqSyZ1j8bCxG8ny5hC/TSbJ26ij3N5UNlGHPo+FpqSteN/i99cLZE1Rds11ULyVqFZ47qbR73srHp1nnA4zCNQNFPBUUFBQULh3xJEcunjlOI1B7yHm9RuK0Z8ulx9ok08Bt91IJfO5xqptdfUC6kyQwNyMMNgNUxWRZO53ltrSTvkiM5WaJEy+ABp4VnNu6zv2RxLN3CDj8FPs756a53/J7zQaJUTwJnHwByL6M2/jsj5eTtmaDCtzgLgbOJzOc9x6JUrWdET2Jngt0D3I523ez9H250HVg5z4+IEycJeEEgGwnMLAtmPB0KbBbQj22Vj6el4Jmg60W8dRi0glwH5p1kvVYkgp0e0YrwIcQ3eD1eS3AcynQbvKIJ0U8FRQUFBQuDzv2UqGbHqMaaVpCsTOAHTeI8vNlwDTZb5nt4vShYp6EUNeo2nX1MkB+eoKkzvepgKWzwA23AFt2rmwu8tzFZqWl0A2WegGSl+kx4NATJDTwgyqv75GY9g5wG+angeHtVNoqRZbWpVHKsIDeYZqXZieAHXtIpsdHqOL1DNIx3tVPIpjpXE5UalXuf26G/852k5ieayLQ0pzVzh6qn4m0iFO6RDW1WmbU0/Q4j1UoRLPXwJZLU7nbURE9ut2rRGXFUzy+O/YCZ0/y/MSS3Jdahar3tj3LCenVRqnAXt/ZKQA+H6J6h3jdXmrG7QaGIp4KCgoKCpeHcIRGlL5h9ka2GkA0wUzKTOfa9AQ2G1QbB7aS0MXiVCQTaeCpx+gqd53AIOSDbvNqmarpSs7vWEKoUN7KBLRZD6KKIjGu+5HvAOU8FTaA6l7PoCAROolEq0lStOcmYOwUP1MpA54DRGMcl1kusEUh1cH2gf4tNA5Jg89qx2x+hvmg5ULQkzo9DoymOMlpJWVUzmifPCuipQyqk5EYpw/JkZoXi3KROaqFefarRmLc96OHaLQ6cPtlxhgJZr9q+7B4o7OXDyVT48CcMIv1DPDcdfet77Sk2Ung8NNBK4qmM9t1epxmse03bDryqYingoKCgsKlw24Fc8F7B9a+rOl5jDkaPUkSuRAO3sX55KU8VdB6jYpfIk3iUa8CpSLL6fEU8KqfXB543tVLwlTILZ86VC2TMMr9qZRpaEllApVQ0wBDB2p1GqC2CLOLYfC9wW1UP0v5oJezVqUq6tjAzXeRdALctsQ5FEuAyzj6DPetdyggLL5PV/3RZ2ioWtpre/Iwcy47eoJcVIBq4fHngUj84s+b7zOPtJijMiuJeyTK/ZiZAM6eAm646eKW245YgkS9WuF5WopqOchylXFRO/dhYTb8ehO6ZgM49hzPde9Q8HoixW0/fZTbfK7BBdchFPFUUFBQULh4VMtU0KbGODkoZIkS69a1HZM4epIKWiRGw4+uk+zm54DnnyTZLM6z5B6O8L35aWEE8ulyf+pREsu9tyyeLhSJ0fV++BlRphWKVL3K9ezYRxKZm2UpvFLkJKHRk/ysVNJMiwQsN8vw94wgsT393L5jz3E50ZiY6W6RDNeqVIhXm8O+FHNislDv4GJSpWnseT19BPjXfyE5jsap9kViQf5nO+kESKAbdZbKe/ovjqhVSiLjs2O5WqwbQcTV1l2Xfj1ExeCBU4d5btt7R5t1bvvOfYsfKK6VaUoAr8NyceWosXiSPbYzE4p4KigoKCgoLED2BlbLJCbxJNWkw0+xxBpPAZEIS6zHDtEoc+PtK/f3eR5JYn6ey+joIkE5V7j72VNcVvvYQytEsjY9zm1otUhuPJdkqFYhaZHKo+uSIPsecMuLFxuOegf576lxEgXfExOCEiSTp4+SzI6dYml7aDvJaynHfbdC7NusVdizees9AbltNbnuPTcBvkszkWkAiQxVwblpOt/DURKm85WlS3mS1qVEr17lKM8zJ0h8h7azFWHsNBXQWhmI97G/s5jjNsUSJI3xJHtmm/WL68lsNbh/S5ViiUiU56bZuLwHke17uG3to0ftJqAZwLbdfNC5VlGrcptXK/WHozwfmwyKeCooKCgorIxKmaMc52dI6gCqWdUyidLgtrYSa4xEbHaCpfHdNy5e1uwkezHPngQa1SCmZ9cBYP/ti8vMnkc1a2aCqtBKbmtNY8lyagyAD7geCUqtsliNdB0Sus5ekuL56eVkJdPJH89lH2m1BBx6nMQhnSWZm50IjDS9QyRApQLJY0uobz2DVLeaDfaAzkySHG/dtdzpbTe5vLMnqHqGY8whHdp+7viipXmo9Rrw3BMi4N7gHHu7CRRbPAaFeZKb8TPcr3A0mLY0N03imExdfM6qYQa9ou1JBhKOE4TiXw6sECO1egdpzmk2SKq7+7nt69m/eT4YBs6ZM+p515ZCe5Ww+fZYQUFB4XqA6wY3/SsRz9JqAkeeJlHr6AmIUzFPo0p3H8lKu1hpiBLr1Dj7HaWyODsJPPwPLM0nU0BmmISwkAeefoyE8c6XkrxOjzMns1Rg7+XcFEvEmRVIhiH6IlNZ9jj6fqAw+T57IqFR2YtEgJpFsrWaSqYbgOaTHNcqLO1LNTaVJZmyW1Q7h3YC9hGqiWYYiIopQw99C4DO7M1qiUTVaXGikizB2y3gzEmW5ttV5PEzwpRzx8rl10wXFWCZWel7VGLnp0UIvM19TWV5/uamqUyePcm80WQKcEokptlukp6xU8DeW5fHFZ0PyQxJeSm/smu8lCdZjK/BPHfTJKFfbTrWtYp0B6CbPBdL2xx88aC0c9/6bNs6QhFPBQUFhY2EhjCyTJ4lgbFEb2X/8OXH17RjbpqEpqt/MbGVrmtp3sksGZ0YEeVDOUvcddmjOT9NZ7ksJxsm0N3LsvvIMTH7W+OUGl2nepp0SdxOHwP669zH9jJzs051sKuXCmV+XpBNkHgaJlXR/mExllKQw3OhVhFEbsl890wn1UNNpxI8dop9jp29PBaROD9z+iiJ4Z4bgfQ2frZWI2HUDZLC3AwJfCTKYxRNiB7QOEn6qSPM1qzXRCyV2I/OHq5jbor7XKtSWTVE7FM4EhiLrBBQKXD9PuikjyW4T806VexsJ8+Prl+8cmgYjKl64Un228oZ8o7N8y/bEtbb4LOeyHTQtDV+hte+fBBzbD4oZTrXJp91g0ERTwUFBYWNgnoVeP4pYG6CZCUUJvk88iyJ4oE7WIZcC8xPi1LpEjVVN/ia5wLVFYinY/N9ORmomKPJxDCWE2NN5/bWKiSchuhzlA7mUJiqY3GeZetkJuifdGySzJ37mN2Ym+fxqdeo3skA+J7+QD1sNoKRlI5DRdL3uc52UuA4QHJJaTyVoYI3NUbSUC5wfyolfr9/iH2Ick58bg7Y0UVyMT/DKKW5aZK/3ByVasdm3mX7Mc528Xj9+Pt8yLAF8cx0kujtu5XxPDOTLJeXS0Czxe3r6gvK3q0me199n6amREpkWwqSWS0C0IAtO/hvx7n4sm/fEJd/6jAwcpREGD5J8YEb18Y0U6sEpirD4PHp7Fm7kPorCd0AbriZ5Ht2kgRdQ5DKsOfmy4yb2phQxFNBQUFho+DMSeYUdg8GZEUStZkJ4Mwx9sOtBSSBXIponORpfppq2VJI17VU3uwWSY1urKx+mRYAjWQsmVpcttV1EjpblI2nx0g4GjX+9AwGsTR2k6pbMQ/UKyz19w7wNd1g6Tciej3HTvOnUgqIWf8WEjsrFATgR9tvkRr3y7S4T406S+TZTjrKnRaJbzLN41Kvcpv6hris3BzJRzRGIm2I+Kml5hzHocpbq1IxTGV4LnKz3IcDd3A06PwMldFaGUi1uN3txF4am3yfoe79w9zmWpWqbzjMbeno5nG+VGUyneXyNY3XhmVRYT1zgmT+cqYhTU/QsFYtAWaIDztnT/Ac7r31/PFT1wLCEeDGO3nuSgWW2GMJMTJ1c04wUsRTQUFBYSOgUeM4xWRmZRUylQWmJ4Gtu1eemX6xSGXZb7kUhhE4yh2b5MYwRM/mPEuswztIRCol4TzPiV5Iiz1/7eVyxxY9ixpNPEuRSDNkW9eBRoPkKRLla1WRrZlIUTkc3Eaic/x53ui7e1lqrlepfu65kYT5xPPczkwnt6VWYeRRrSIITYql9J4hkrMFUiYc8rsO8Hy0Z2mWm6LHVAfgYsFUEo5yek4yw95V3eDfM51skVh6LmengHod2DMQqGEhccznp0my73gpiWQyQxJcLlEFbzWCUHnfZ0ldPpj4Pv+UanKjThJUq9I57rlUi80VlOnV4Lmc5HTmuCCgES7ftNgO8OSjwI13kNRfrJpaKjCX1HUXH2fX5cPX0WeYULARzDma6DNOd5z/s5sAG+CMKSgoKCigUWepeLXxf7Ls26ivDfHs7qc7vVwgwWmHrtOpncyICCKfr6WyHJHZ0U1F8eRhhn/rGsvC9Rrf6+wlYfA9ksdIlKSxXFx5W6QrvauXpWYzRFXz1BESnvZyZfcA2xBOHwGqVaAzxm2VauXBH7B/tH28ZFIEwp86wnJotUx1cvwM1zuwhcS1mCdx3rGPRFVOowGoOFpCDW02hPoXDt6LJxmrdMdLqQaOHF3eV2m3OFoxnRU5j2X+eC7XHxPRR8Ucj2MiSfJaP8zropgneYZGVRUaH0TCESqmyUxA1Jp1Hg/T5N9/9C8szZsm93lo23Ki5Pt8UJDl+kNPAE89QvW2UgbgcztDYX5ufhoozALb91K9Hdh64b2kM+NBUH47DEMkFMzwXG3CHsmNDkU8FRQUFDYCDCNQFlcq0bkOb+prVb5LZdg/efw5koBYgiJercIy7YteTiJYmA9mdKc7SVzmplgiNUMkbYkkScusiBdyncAkYzdJnsolmoOicRJYgMTU87mO8RGSmaYoX9stEqaVciRjCRLNSJzbCbBPcuwUVdPMCt+xW9y2/ByD5hNpKpSzUyR6w9uB4Z1UczOdfO3McZIs0xJZo1n2eVohoLN7caRTpQTs3k8FdXArkJtmRFOmk0qh67B87rRIwifO0jjkOliYARqJkczarWC7d+5lRujEKI9xvcr3t+6m2moYwf4W5rmcljh2W3bRcDU1RjKeSPEYj50iUb3xDh5fz2Mrx+Qo90PXeF5OH+FyO7o4RMB1gdkxoFwOXPweqA6/8CQJ+Y69F1bWn5teXXk1LW5TpaiI5waEIp4KCgoKGwHxFBWo/DwJ31KUC2Lud3r5e5eK4R1U3qZGhTFCYx9k/3CQNdndv/g7vk+C4rpAR4avpbJUKuMJEqS56UAJ7R4ABrbx7806Z38PbAumAc0JE01XH0nU3CQwflqEwy9RzzyPSlhulj/NOglrKstj5rT4maXwfZLragVo1oBDP6Y6a4WonvouSeyBOwIyuWMv+yjHzwhFUvQ5WiH+XTdI0ltNEq++QRJXgArrgTuAU0dpVLLnuC+JJI95pcR9TqYCE43v8bVCTqiaCAjoDbcAnX3A1FkSwHQGGNrB9194kscikeaypOP8pjv5cHH2NGOK5ANLKEzyPzcFnDwC3Ho3t3PkGPc9Gic5Pfosj5fnAu44y/zNBrctJAYKRGIktplOfnb0JM1eSxX0FeFvbkf8dQxFPBUUFBQ2AnSdpKSYIwlMC9OM57IfzvPoUF5rw0JHN39cVzhyz7N8Oc6yvZQNkGzsv4Nl1xMvkJAMblusPibSwLM/IlmKRoMw91CUhObEYb7ug/sMAP1bSfR8L1AoAR4nX/xZKZKEtoS5prtvsSu6VmFbwPwMyU4ozPc9n+XzaJR9ozv3UkkEeDzCEQBCkW3UA4KdzgDFAo9FNE7luHdwcZZjugO45W4+MMjIpFQWeO4g8PC3GOfkuoDpkZRqejC5Z0Ioj4Ucz7/dBGyheMNnf2uryWN9y4uF0izmw+/YS6KZTAOPf59kd+k1o2kiPmqOPbRnj/P8RYUCWSnymBdtPkR09/K9epXb06qTUFumyEwVWaVThaDkfz509LCfVarf7XAdQdRXmN+ucM1DEU8FBQWFjYKeAbrWTx8hwZKCUCJF48zlOIjPhwsltOeagKNpwVQhGQpvN9mbWMqTqNXrJH3bbqDCl0gDrs2weccGMllO+dE19koefpLkSk7iiYtRlHaL6mw4AszP0g3d0c2/jxwFdt/EbWo1gBeeAibFSE3DIImvV9kqUHOBWhgwC8Cj3yWhlEYvx+H6TAvwKlQcc9PsKd12A0c6hiPLybrdAmybpLa9j7JS5nKLBf6EI+zrTCQBaCKgPwW88AQwvIt/n5umCz4UpompZ5Dbd+YEyfCNd7K/cmj74m2olllyXy3g3QqR+E6cJYGPtpW9PY/qpq5xH1pNbqcPlvc1sHWio2fxFCbd4GcvBL2DXHcxt/gYeV6QCZvtvrBlKVxTUMRTQUFBYSOhf5hl49wcS8emxT68pZNR1guhMFWquamVTU6VAolmZw/jkXIzJJW6xv7Nwjz7RMtFYWLRgFKFCm+9QsUymmA/aTpPBe3sSZItuyWUwDn2HUIjobRtwJaObx84+hyVyN4hfndqlOsxwpw047RIurwmiVW1xJGch54gefZ99jymsiR+piliiQwSpUKepWlNY46jRK1Ckjg1Fkyd6hsKJik9f5BqcWc3YIS4L6U8VVHp2B87zW3s6uX+1spsd/Bd9oymMixxN5tUT4t5Lr+rlyRQtgrIiVe2HTjh2yGD9htVHqtGTYzfFGpqXvSfJtM8drUK98luBVMiU1m2iEhIk9SFIN3BY3f8OR6vUJjfdxye2xtu3hiOdoVlUGdNQUFBYaPBCjED8lqEppEcz05SVZMld98jwTt9jOSzWSOpaDX5GcsiqbRb/Oz8LJBKcxmGIYxTFlU8iXSGJCyRIoEFSEZSWaph0xN8LZkCqqAa190LnD5BNa1e5wQoK0TiWCwCTjMoazdqgGNR3bNMqqNz0yRwPQMsdedmqG7KmeTxFL8XjrLXdXArS8uVsiCWs/xMNMF9P/EC9zUa53sDW/j9mMgIdR0el1CIxK5WZg+sYZL82XbQ15ufIzl0p4G5GRLmkeNsMzh7gj2mu/bzeIYjbDk4eyKYaNSOUoEk1ge3q5jjsQ+FeS5aTe5TMsXtsUJAfgaYnyMB7+5brKbWKjwmHRehUvYPk9jOTpKA6wYfWDp7g8B/hQ0HRTwVFBQUrgc0G6Lv0SepWc9w7Z4B9jWOHKNqFwpTIZwYIXmMJ6lElovcXrsVkIl6jWqja3NZjRqNPQAJqSxbtxokO6kOlpgTSarAsQQn6VTKJGqyD9AHVcG5GSpntSqXFRJB6qaIBKo3BLGyWTJutajoJTIs885Ocnm9g0HCQLUUTIyyLKBqkwDXKiSnyQwd8Pk5lsKl6hiOiGMhejYHtnB7k2kqi+msMCtFxJjNHLcnkSJRdJzFhNG0qA7CJ7m1LBLUngEqwwd/SPI/sIVmrcHtQbB9ppPHwnV4HbkOj2ulRLNVWOaeivX1DAKN4yypt5o87uku9prKWCU5QrNS4vW5c9/Fm9/as0cVrgso4qmgoKCwkeE4VK3Gz7AU7ftUlnoHaC6JRK/+NmkaA947ujnaMT8rJgHFSY6sEGeX201B+Iokm4kER0tG4oH7PBylymdZ/ExcKIXVCh3S0kU+JEhUJEoiOT9C0uUK802jCkyUSS5DIQAe/7TtwLSTzgrFsC3CCD7L3oYuytMmSWtLOOStUBDGrunChKWLSU26ILkV9uSms8tzLHXhZh8fEbPoNbYANBtUDy2TxG12iu9FIiTxjsOwd98TwfUa96VeodprhbidkRjL87PTwPwU+1tTGR7jPQdILudFEoAjDErJNE1UfUNUqDVNRFu5gbIbiXIZuiCivsdzM/AizqafHuXy8vNURXfuo/qrnOqbHop4KigoKGxU+D5LtSPHqJx19wPQ2swlDWYxXo251r4fEDbTDJzRmU7mY558gWadTAdL4L5HMqkbQMsV7u5GMK+92SD327EPeOEgS9zhCD9jt0ioWqLHNdPFbNGePhLdRFoE7tfJHesiVF2D6A/N8hhVq0AsCphh9oW2hNoJg3mZrk1nuwYqoZmsyDP1hNs+zGW3T1yqVbhtnsP1W2Hui91g68DC8fLExCZD9MJ6PAa1MpXRZhPwbGBmmsQ5kQS27BYz1kEjk8wAbdR4bJwmVcZIlEqj7/HP/AyvBd/n+tKdPIaHniARf9HL+aDQbPLcpbPBzHfPZc5qq8kHBF88EBgW+05rIkR/z01cdr3K/XrRy5kTaprBNCMFBSjiqaCgoLBxUcqzfJ3pWBy2HY0H5e25ISppVwoyGH5ylCVaXWPZvG8ocDTbTaBUpNLWbLBvMxojQWk1SW48ERbvOyxP+z4VtO4BoHeYfaGZLpLDVguoz1NJTXcBD32LZMkw+L35GRKraolkyPe5Dg1CERVl8VSaaqJ0nns+36sU+X1NCxRjXSOJleMnrRDbAlotIGXxu5UclxeNAs/NcLkjJ9hXqptUAGFTBSzMUR21LBJlwwSef4I5nKbF0r0PHp9QhORvxw2cJlWYp7O/mOf2TY2TaGc7qMxWKzRIZTrE5COf2xoTarEV4n7oOk1gp44Ad/wbIG3wHI6dpqveskiew2EG6FfKPP6aRgIfCvHBp1mn01xeezv2kshejQcehQ0HRTwVFBQU1htSndN19uZd6FjB/Fyg/i2FYfJnevzKEE+7RYI3coxO7ViCvYy+R7V1ahzYdwt7IQ0rcDo36iRxphXECukmYEBMZrKBpk0C5bokjC96KYn0wR8CxZpQ0EySqokR4MjTJGC9gzwWxXn2MXpDVEo1jYTJ10iCy3lua0cPCa+mU6mLJ+imHjvF19MZksJKmWqkaYpQeeGIHznG7apV2Tvp2JzUY5j83uBWrmtihPs1NyXU0irJnGlRiRw5HvS2hiNcT6PGddouiaN0wQ9v53Gan2GQvhkSuaNiWbUykPU5f90KCfW0IQLtqzyustodFe73+RkG8+dmGQw/MymOl9gX06TZKZkG0K7a+iT8218cjHJNJBePMFVQWAJFPBUUFBTWCw3hNp4aIwEwdBKf4R00hJwPdmv59J52WMKRvdaYGuVUm+kxYGyEZCkpVLuuPpKu/Bxd6+kOOpHTaSq0hhUEonseSbYnCKYrzTIaEE1S4QxFSB77h7msoR0kSidfAErCaa2LPkjTDMrJ4Rh7TGtl9hw6NkkuRF9mZ09gLuoeIIm1QmL7U1TwrBC3U/ZmarqY155iiX3LTpJi3wdOHAHGTnIbs13BtJ7ZqSBgviEC1rfsYmuE6wYxRI7DVoFwjEpto8Hvuy4QCTPf8+QLXOfgdn4mEqOyvP0GKqXTZ4FTx6g+h0J8GKjXeNybDeGAT/ChICmc9brOtoATL7DPtFzk97p6eR7ys9yHZ38E3HpPkFLgujQ8pTJ0y8cukWx6HgD//IMJFK4bKOKpoKCgsB5oNti7KHsSO7p4M8/P072877bzK5WRGImMNJcsRau58njNy8HMJPDj77Mkm58jAYuIPsPxkSDyRvZyzk+zF/DGFwGPfJfkq9ngtmkaKBEK4mGJGdymSVUuP834H7vByUJWiMrwmeOBQuxrQiVtkJDKsn2rSdIJEf1Tr/FP3WApfXZaZH0iiIAKR0kKXYf7MjsVbA9AIts/TEd3uoPHVjquG3UgGmGbgWGSLB97lkSu0WB8lK6TSI+PcHsiUSqgsRS3y7aB/i4qms2m6FUVBiHfo4GsMM9jMzcjjlmIRHPyLM+J71PVHTtDMijD9CNRxjMlUiS5uTnAKnF/XIfntVGnWtmev9rZy2NQKwch/FIyTXcAe2++NNJZKfGBa0b0+6ayJNGdvReu+CtsSCjiqaCgoLAemBrlzb67bU62IYLBC/OcTtTZc+7A7Wy36EksiTJoG1pC6bwQ5fRC4bosd4+eCgiMLsLedROIxViyzXSQPDTqHHtYr1Ep23Mjo46KeW6fNJxIscswAcugwui0gEqFBDORonoaibJXtFElgSvmsaBg2rbohwzz7/k5lo4Ng8QykRLu9rogXrMkzfE0idXum3jcS3mSoOEdPLZTYwxmD8eAA7dzLvrSeB/f53ZG48JJ7wBHniL50zUajDyPoyTl1KZYgo7yYg7wJ0meHUGgZd9pJArM2iSu4RC3fyLH1+0W+d/po+I4CjOXafF8tBoiRcAE45USJLK6DoSEG75SBPxBYQqqcxujK7RtSHNQupMPAtIQ1dF9aX2cuVmORa2UgklWU2NU0LeL/lBFPq9bKOKpoKCgcLXhuVSpIrGVR1GmMlTb8nPnHoOZSJK8HD9EopFIsRxcE4Rtyy6S17XC1CjVxmSGRLdaAXND4yR0tRpL6XLiztgpKmXVCklOpcTlxBLsX3Ra/HxMTMaxwsIYFSIR08W+5OeonDo2lUDbBkyd/w6L7EnZA9mo833HCXI/DZ1kLRwT889FhFOjwmN94DZg6x7u3/HnWNZuNUmGqmXub98Qz0mjwXns7UHomka1tJjjv6fHqU6GLDFKUjj+LQvQDC6zXiW5tCxuXzjK3lSpBsuSdkRkm9pCAY0neRx1na0I1VIQzi6JvCX6Pp0me11LRarGhTkeAxkTZYlQ+t5Bnlf4K7duyEB9w6DJybTYr3r4ae5XuoOJCksfflaC3QKOHeJ56h0KlPpEmsdEzmfv7ruYK1NhA0ERTwUFBYWrDccJ1LmVoBtYCFY/H7bsJKkaP81SqyfUrZ37gP4ta9s7NzNJoiJLq/EESY/vkURVS1QjZydJFiMxbp/jkszVBNm68U4SmCcfCQhmOELSaYVJQn2QZM1McJ1d/SRszSkAHpAvBD2hMn+y1RQEz+SIS02n4ud6JL8xj9mTsbgIre8B+rbyc7MTJFC33kOzz1OP8tjtuYlKYjQuHPPTwNFngNv/zeLpOX1D3G/X4TbbLRIogK+FQgDEuM1qnere9Bhfcx0RUp8i+ZKtE54bTGZynCDLVAbPA0AoSmXYsINtcW1u89yMcOrHqELbTRJbw2R/p6Ez/3TbHpb/PeH+b79m7Bb3q1nndj36XRJhXRM5njqJ9ugpYPeNJLrnQm6WSnVX3/L2EKneT48p4nkdQxFPBQUFhasNQ7ijW82V3/c8Eq8LyT7UNCpW3f2CtIBEdC3nWDsO1bzJs9y2Sonl8FgSiBRFdmWcBM9xxBxvF+gf4LacPMLt6hvicupVErpygb2bmgFovohRAglRVz9LybUKFdJQCMjXaXZxXeEgF39CHCsZcB4S2Zm+sNIbgtylsmK8o0lnud0EJke47nCEP71DJNT9wyTHEnaLhDgUFi7wKfauSvQM8LvTYyRWpii5ez7NO8k0z9XsVGAympviNuZmSX537We5PzfL91tNqq09/YHyWq+x7K7pwOhp4WgPBaNGW02SVd2g2iyJqt5BMhqJsZ1DluSHd9KR3r+V/aCVUkCYW00q8zIFoLOX/y7MAX1b2CYiyXcxRyVTJgOshnoNDOVf5YEoImKipPFM4bqDIp4KCgoKVxuGQWJz5GkSkqWqZLnAMnq268KXqeuBCrZWqFWo/h16nA7yYp6qZSnPUmlXLwnv/Aw/Wy4Aepbl8OHtjBOqVUk0ZRk2EiPh8T0SrUqJ77fEPugG991pkcBmu4SaKoxCkRjJi98i0TV0AB63RwOPrWHyO4bob/Q8vm6FuR2uC+TPkPRlu0jcTBH5dOY4lyW313Op6MlYIoB/RmIkm7LH0QoB+2+janfyCAmnJM3xDLellOexcRwgpJFkypaAVp2udcPCAjEb3kESNzclCGsNgAb07meLwPwMt8tp8fhMjXE7sl0kgprOcn80RvKqGyJnNEayGUuQTJomo6+K83S316tUhWenea7SWRLURJJh9P1b+Ho7+U53CBV3/NzEU9eCB4KV4Ll8MFATjq5bKOKpoKCgcDlo1IPRjxeTX9g3TDIxM0GFKSr6D0sF3nx33bq4lHuxuFzFqJjnjO7DzwJOg7PKbYdEUtO53c06yVcqzW3u6acxJDfLbS8XBbFqi8uRhML3qcD1DAInn6filhJ9o8V5zkqPRjhf3TBoJnJzVFntFqAnSMQMHYAGOFU63KNxqqyaLkw/TUATfZ2S8JTzJGC2TQV15ChV12gUSGbZMpDt5LmVvamxOAkYwPM2cZaZl/tuC9S7cIQu73qFgfeuK85pnuqnjEcCOO5S03hcCgWqoI0aSZsP/r2YF/tqCJd/jj2flSKNXJ29bH+olEke5SSk3Cx7flMiBkqX/bCCkI+f4TYcuIMEFuB67/23JKMvHKSyWatyHTv389zmZgMlPhonce7pDyY3ReNMMhjcxs+sdP2msoEivfR93yfpHd6hiOd1DEU8FRQUFC4FlTIwepL9b45NRau7jzfNZOb8349EeeMfOQrMTJFM6EbgqO4buvhtatSoOE2Pi8zGFJfT3XdxvZ6eCxx/nnmPugb0DJG8RGJU1wo5Opxbdap6VphqWFxM9SkXWaY1hHLVrAdEuNkgiTMtQYo0kcNZAOYmxNz0ENDRyWWMjQgvzLSIC3KDFgTXIZEzdCqFrhOEpWc6+W+7CUC0NRgGVdmzp6gUAkA8LgLkK1R1Z8Q2TI9xTrnvsz+yd0AE2vsANB7XybMsr7f3I3pu4DIvzAfkMxTicuXYzq5ekuKGiFlKZkkyu3p5HI88w23ZspMqZjzF/eno4nUnz3GjRoUwmeH5sW3uo+vRALVzP18vzIsyN0hSB7ext1MSPNclIW02aLTqqgBnj1NFX9T3Kch7KCTIe4vnv9Xk9spcUsPgQ8ngtsWmo3QHW0NGTwk1Oxqcy9wsifC5DHUKGx6KeCooKChcLCol4LknSMCSaSo9douEoDDPzEqpJJ0LsTiw/3ZgW0UEoeskEKv1v51vm55/kgpeJEbSNztJgjK8gz2VF7rcQo7L0UCSoospQvDZ1+fYdEybllAUdfYTVsrA0DYaR+oV7kulJMLZ53ms7BaQHibhnJsiufNsoO6RLHmCTE5UhFmpJggsRLndp6HGc2ii0Qwg1QHERISSpgXO8Y5unofpCcABCZnnUlXTwDgqyxLbZwWKm3Sp2y0S5tkpkbeaIElOpkmwQmHuQzvxPPgI8OQPqeaFIqLkrQWkLxojkY/Faehx7KDdolEHJkb5GbvJ7TENYNcBMd5yEjh5lAQ8FOJ+9g5yH0sFAB4Je8ji8rr6SPwMk8plq8n9LszxvXZFfOw0I7wyXXwoqpb5MGRFaAxzbe5Pe2KApnMbWg1Oq5o4Q7NSPMHPjRxjyPyBO4Lyu6bRhASIFgaRS6ppfJjZc+Pat4woXFNQxFNBQUHhYnHmBAlm72AQPyNHKc5OMBLm5rsuvFwYSwSh3b5PElHK8+/RGMnAucxCnkeFsjDH0rUkFMk0FayzJ0lO2s0wqy7LZa9gfp6kz26RPFQrQa9kLMH9bjZIwAxBPuJpqla6SQWyVAhUztOHASMkguXHSVLmp/m+EQIyWaAs+z2bADQS6EadpfGwMEw5DsvSuk710UAw9SidFQ77cBCkXimR5A5u4/dzc0I5Bb/jC0OUaYhSvHCTt5tmoAMQYytTGR6HsdNcX7syPXoKePJREr0tO8X4zRFhFKpzv2JxobzmqQS7Qk2sV7n8RpWEVtNJ9iZHgYGtbEXo6CGJjqeAapHrSWW4jc0a0GyRhA9tF+fLFQpzguuMxoSD3lyc12m3eD5kmwLA7Ywlg3M/N0O1tVLi8Uum2d8bibLtYHqc2zewlQQ1FOF6ZyeAU0eBW18c/D6EwnzgGtoetJZE43xQuBBDncKGhiKeCgoKmwPNBlU8WQLOdi2e0HKhqFWpgKWyyzMPNY03/tzsyqHu54PdAk48D0yOiRIxgrzGPTeubtoo5Unist3L+zoN0es4elrEK52j77OYo7lk5DgzOCtloDBLEpHKsETseSSlrWYQ7l5wqSa2RIRQJEqlzIqSdMzPcn+kk7/ZIAEyDBKcSpkKWVOEntcqVNwiERJDaIHi6tgiJkmExsMX8Usigki67V1btAFEqNLWysCUIGiOA8DjeTJF36NUW3nQeY1II0zIDExEqQxJcLMOTNepJANibOYLJOCS4Hsex10mMsJBP8o+Tc8XxLjFdZbyPC5RkTUaCgVtCrpBspnuIDk1TCqCOnhcZycD4mw7NChJ41A0tvjhRzroM528ViTk8c50Bq9pOgl8blYorxbPdTjKB5l6lb9D02OiJJ+gmazZIJmULQXpDv7elQpBjywgzlXHuY1I50KtrUqQSK9tioPCFYU6UwoKCtc/psYY21Mp8YboeSQ4wzuAbbsvrv/RbpIwJFMrvx8Ok8BdSAZnO3wfOPYcb+rZTiAiiIEjDDAvPAXccvfKZLlWFX2Ebbmg9RrVqmKOJGniDNXG7TesbPqolINpMvEk11sXZphmQxiFXO6355HoGgZJXjVHVaxZpxLc1c/3GjV+NhYDjBQJUaUojC4RlntnJkge5qd5blyTx04Sb8MMSu2GCbSE+tgUy4ZGkpRIiUB6g8RXT4o+R5EMMF0UxC5Cgmzbov/SEX2KIb7uCUe5JcLopRs+FOL6XJfLLzepMLpiZGmtwvMUCguHf5H7WixwXaEoCaLmBz2fhiHGUVZF0H1IhL9HgnzSZIafKebFFCYEBLQ4z31LZfh5uyWOTYPnv2+IhM9xRItBjQauPTeen6i5Dj+f7SIpLheCtoGePl4LURHNVC3zmjl7UpT8IQxIMZJZKxRM0rpc1KrAmWPAtMgW1Q0xL34HkyKUKemahyKeCgoK1zfmpzlhBWBpUBcKYLXM8rRukHxeKAyLN21bGIqWwrbFNJqL/N9rKU/1qKPNcAHwBt7VR6PPzAQNIUuhtznFNU3M1T7Jm3Q0RnWw1aAiVy2z5y4SXbyMqVGSm84e4NQRMS9dC0ZNOjb/nJ7gFBzHEU5zWxiCTJav6zWWl3WNZCQpJtLEIgB8QVRFP2hXH0ma3SJRc11Ay5EkaRAlZ6H6eR7VT88jedOMoDfQsVl6tiKcnmSF2XYAjUR75Bj/HhZTgOSMeE/suyuUTt8Tx9AUuaBVnm9NqJNmiO836vxsKMS+0oM/JDGbHCM5KxZogtINksVKCUCJxyrbw2vDEfPTDXEtaWL/ojGuwxDh95ZFIjl6ktfFzATQ0du2fDNogXAdKsihKHtPh7aLyUUFGpCGd7A9ZGkPZSzB16rlQIGsVnhuuvpY/g9HeT5adR4Tz+M10y0eMp4/yOMSCvN3TKq5jbpQXtcgk7NR58PRnKg4pDO8ZsoFOvFdh/uocE1DEU8FBYXrF75PEuTYvEFKSELluZz40z984dFFcTGjenp8OXkDSDw6uy++zF7MUVnqWGHEpabz5j01vjLxTHXwfZkbOTXOm3Smk/tazFGZSqaZMQlQPV1wh4usyliSBLBWoWGmIsw8AElsrUyly3VIipp1lnhDER7jVlOUrD1+z3NJQByHoyZbTS5OEpLRU2L2ekWQQF+875G42nJ5rjA4eUFpPBKlC73Z4mc9j2Q0HBZKoijBT40B81NcRq1C8ue5WOjl1E0sTBTSDACiv7PZDPZTN6iG+h7gxflavBeYHSMRjwqXvqYFfauxhJg+JHpIa0I97rKEcckgyXccmoxqNSBi8xgDLM9nOoJA+WiMZMv1SLTqNV7DukFluuEEiqzvcf2pDHDTi8Sx0Ugsc6I8b4W4/kiMfx/YChx+itsWiYpjBKGUiqQAeCS98sGrWmR/56nDbCEYbJuU5Xk0h7muOAbCqFXMiQEDDtfd2RtMwjofpsZIOnsGgvWYOtsGSnm2iPQMXF4MmcIVhyKeCgoK1y8aNd7kEquQwESaTuFS4cJH9GkajSNFEb2T6aTKY7f4mhUGtu6++AxNSQ5Wg2GQsElVsx2xOGN9Tj5PdVGWy+EH/ZOlQmAYys/wc7v2M0/Uc0UMkElSI3so4ykqb7WKUAoNZms2xUx2qVwaYsSl53OdviCedWGokTFRliC6zQbgiMBzqTZKYqlpWAh9r1XZ3+oKJ/XCsbCEIik/L4ijbA2ARtWvlKfa2WoGZFjTeL48n+sDgvYL0wqMPbVS0ENqt7h/DoJ57Bq4Tdt280HE90X7hRbsc0K4+G1R2jd0/tnRAwwcEIqxQ7J09Dm65mXfY+9g0EtrWcDgdq5H0/jwMPUUiVsyJZ4NNBLNrj6STtnCAHAfTh6mIapRDwgxRE9sKkvC3jPAvtFijueoWhIjWOM8/+mOQLmUim00yoeHaJTLDkeF6l7iQ0xTqMMHH+HvijRR6QavuViC1+HA1vP8frhUWKPxlVtjkmnuc3528cQphWsOingqKChcv5Dq22oxQtIZ7Xsrv78asl2cNz5ylC5p12HJM9NBRbKz9+K3NRJFoMKtsL2NOnv2lpJOqVYWcySBM0dJuDr7SFh0ncuslEms7Bbd4089xhGHL3oFsPcWKmqlIpfv+yRFlgHk5lmmd0VpvVETuZzVQL209eB7ui6Op3hNE1FMjQqAeNCvibaeRNMKlDGpsAKihF4WvY2C1Gog8bWbgNv2WV8QTtk32SgFJMkwxHIF4ZITiKRirZnA4DCNPR1dJDCT4wE5kvPkDVH2njgjph51kszNTHKfJ0dFeTzEbS/laPgxDfZWahrQ1cNjXa0wgSASJclsNpiFunU3j3NuBpg6y2Od7SZBjMb43v5b2ZYxNcb1WiYQjgvDVSsI3e8a4P6dOUnimUgLIi9U1okz/PvQDjFm1aIyHkuQxMvAfUeo1vJ4+h6J6MAW0R8rDE/hCIlluUjFOBymGm+GOBHq9FFGQ0li6Pu8Vo88w++e6/fGdUUbS2jl9zUxSMC2V1+GwjUBRTwVFBSuX0QivFnXq4uNNxKyJy0SW/5eOzyX2ZYy4zHVQfUp08kbp+zrTGUuzqjUjo4efj8/t/wGXK/yz6Wh8q4LHHuWJWvDops6HAGOPkNCMbiVBKYgshIlOZU9robB8Ppijt+dnyGxgVQutcC97muB61uWwyHK0wu9kYLIhyMkCNUqqEYKc4zj8PjIYHdJUB179TGKniBRfhspd11RChckQ6qeukaSVBbbGU+IzEkXcGQZGkGQu1Q84yGqfs0GzTxSWTQtklDZ0ynnwkPj+zLPtaML6NsqyuQ+zVTNBpcfT5FQGiZ7QOs1RiMV5mkOCg/y77v2kRjOjLNVYnqCZeVQmMpxpcTrrbOH10pHN89tOMq/6zqPazHHUvqem4Dtu7gd46fpMJe9nTMTnMve2RMY03oGuG2zk8CNdwA33MQe0eefBI6/QLXWFa0T9Qqv1c4eltqlGapviIpps0l1NBxlf6jjcv8jISqSnT28PqSzfXaSy+noWV31N0xxLKorG+w8cQ2uRkw3GXzfx2RlEgPJgfXelGVQxFNBQeH6hWkxQujI07xZtd+UPI83/v4t5+7HLBWA48+xN84TDuZIFOjbAuzcuziC5nIQCgO7D9C9Pj3G7dUNlrkBYPseEpOpMaEyCfXt7CnRY2hwf4d3kEDkZ0kwZMm1XiOBkTE5GriMSgl49LvAPa9iuXP0FMnktCBJ0Shv9tIV7YheQoDHwhUEVNcC0p3MCKNQVaiFBn8cB7BrJKdOU54IUB3VhWq5BK5DE49jc4ymJWKUZOampgVqq+8HzvSQxbaHcDQgV67bNitcD4hkpUT1Vzf5mhUSfa4DVLFrVZLD9v5TX7QDOKKNIZYUMU5eMOYynqI6Lg1Qhk7Cf+RpkulqhcQ+28XRm7E41cJQmGQuLmapuy7Jf7XMzxdzXPfwDpLi+anA8OMJ1/0td3MZc1NcT1Y+JLWokEvTWRTBcmMJLm/sDFs3Yklum9MCJib5e5JM872efi4/KnJJpXGrWuY2SGW8XucyDIOqbTHP453tCs5xPMkHrlZz9f5MXafC+vxBwE0vN++V8mw7aF/uJsWjo4/it7/z25iqTOHwrx9GyLi2yLgingoKCtc3Breyb3HibDA/WgZ1d/QBO/atrrLUq3TRlvJiyo10NddYZvc9lqnXKsKlqw+49R72ss1Ocfk9A1SSHJsTccolQbQ8lktbLd64fdGjmM6SLDWqwPhZ3sxT6cC8ZBgkEs0qUNJ5PEoAnngYePkb6HhPnACee1wEt8ewoFpKGDrgaYJ0ShIKMf0HgXNcElE5Lzwa43GsFIFCE4uwEumUaDYF6Yfo15R9oaboewW3UZclf2GAKhdFqLxPkmWYJHFy8o4sy0N8XxpwrDDXJ6OoZM+mpXN/XRHnJNXepphaFYtz+a0mD4hpksi1mlQnmw2h3vo8n80WsG0ny8/pLPDMj1gSd22uNxILHnRaGpcVT5I4+hqwXfSXTo/RSW8YVA3l8QZY6p+f5k+zIXp851lSN0MBafeE4pxI8vxMj7M8XsixFC8fujRNGMraKgjZLj4UTY/z2tX0wHxmmMwyhRbMnHeWlMPbHxzOhZ4BEumpcTExTATil4p8GNh+46Y2Fh2ZO4IHvvcAvnHkGwCAqBnFwYmDuGf4nvXdsCVQxFNBQeH6hhUC9t0qyoKjJGSRKBXE3sFzl9mnJ5ZPKNI0qjyaRjdvoy5KfCL2qKv38sp9qQx/du4X5MhkD+HRZ3nj7hkgqcjNBvO6h3eQuNg2PxtP0iw1eorLmBWZh2aY5U5bTK+xbZK0RIKk5OTzJBE33CxCv4t0Def9oJwuyYfsm/XdYH65jDvyzSAOyRcGoJ5+YPs+4dKeCcrcwPl7bF1BLjVR/pdYCHwHiYeGoGfX04M8TlMQRCssxn06gpyJHk7pPI/E6C5PaIw9ys+yfB6KijYC0cvrNNtinBy+r+tUZmtVMR1IC9Q92+Zno3GqilIdTHdyf0aOsd/yiR8EbRCex9iqRp3kEsKwE0uIcP2YGIKQBIZ3AVv14LqbmxLk2icRzM/RAZ/O8jOlPH9cV/RmipxSXuDcz5Mv8FyZFh/AIlFuc6vJ4QK+z2MRjgB3v5IRXHaTn5N9lpkunnfXoVEpmeZ5XNqOUqsC2Y6V22HaEY5w4lEiJaZrzfG4ZztJjnuvvbLy1cBUZQofeuhD+PyTn4fru9A1Hb902y/hQ6/4kCq1KygoKKwLTEuMHdwiyq1titBS2K1gxvnzT/K1SFz0b7a5hIs5zhmvlEkGXQcYP8Nw7b23XXhEjONQYfI8kolYnDf6uWmWSHWNy3VcoEdELfkeyYVhssRaq4ieuojIlpznNkYTQFznTdoKkxS4gpAYVuAU9wRxDkdJpnWD2zK8nWpxJEpiardIwHRBMuWsblML9kUXxMV2SXIiMb7uiEid8TMkd8K8fl7I7W0/l9DblEoELnzfA3yHpDAsytW1Kj9v6IGxyBcxSp4nxnsaVOgMncc/HKVKPD9Nkh4W/aWOK4xWXltklE9Sr2kifskSIfBhEqT8PAmb7/J7jSq3NxIPRnyeOsLvxUQsU6vJ42iaTF2oFAMDVq3G9SbSJKWTZ6l66zqv0Wx3MP+9lCd57hmkeu2DxyUS498rBZ6rvpuC0nW1DEBjP2qjynNnhXh8Uec+Og5J9a0vZhRZKsP1DG6nyjw/zYewREoE9je4vNkJku1EKjh39RqX2b/1wpIgwhHOet+yi+qtrrOl4WJTJK4DlJtlfPyxj+OPH/1jVG32gf/7Pf8ef/CaP8D+7v3rvHWrQxFPBQWFzQMZdL4aGnVmGU5PBATAbrKs3tlDA45uAIU8lSQrJMYPir4y1yVpNZ47/6x2zyNpGD3F8rnvkvBYIVGebZAM1Cscd9ndzxK6nIxTr5JkFOZJplqNgORVy9w+GREE0fvXagRkT075iQoFrXeI+zF2muuQiuv0eNDXaZgkWp5wr0vVU7q4HRuACDWXIeKuyzge1wFOHObxWSiPXwCWfk6aSOT59KXCKUxIstweT3MfZZncc7DgetaNoJwuz5EliB3A7Y6lAvd5tczgdFssw/cClVbmfMpIqmiSQfZSYa1XgvVoQhl2HKBe5sNFMsN1DG4jGW80xLSqucDQ5HpB+bqrl4SwmOO12tlLMua5XN7UGE1BnT1CEW8BW3eyF7g4z22yQkxj8H0gJQxLgFA0xWz3uUk+zCQzwbFPpEhmAaqLu8UEJNlDu30Pt/PMcRJQeWwNSyQTiN+/SomksdXg52X14WIQjmzasrrt2vj8k5/Hh77/IcxUZwAAdw3ehY+99mN42daXrfPWnR+KeCooKChInD7Cm3V3P8lTpUhiF0+y5zISYwm7MEdCFAotLg8aBsnb/DRv0OeaQz16kiMyTYulQsOgq/y5gzRJ7L1NlG7LwNwMlzdxBti6K+hRTGdJQkpFoSraNBNVSiQiW/dwW+0W4OaBVg2ALsLORc+lLrIlu3qpolXLgSLVM8DMyGZdBIpLwicUY9Pkeg2TfYnJdDAppzAvPit6E6UxSfODsHXbvoAoqzbmKSNzIMrq7a9Ho4CvA74wUGU6uJ5ynvtcq3K+uWGKzFIDgClyMkX/Z7NBUh+J0wleqzIZoSGC7yH7ENu2yfOCXklP9HtCo+Lna1gYwSmNP7oo/0PjuZmMBmM4rRCNQo1q0NpghoCQRmVZqvGGIY6nTFPoCBQ/qeiHIoFCHYrwuikKBVQ+NNSqVFZLeaqmhgHs2CumU9nL3eOaRiI6O8H1y4lZmviP71NR3bKTBLhUEE5/jYT3jnvZrzw3xeV395FwZrs3pWJ5sfB9H18/8nU88L0HcGz+GABgV8cu/P6rfh9v3v9maBtkXKgingoKCgoACdf0BMmiLDtmu0igPI8EMzfL2J1qmSQqkVzuiA9FAHt+8fjBdnguCebRZ/nZdld8s0Gi4zjMgOzqE3FPokRezFMdMwwsZFamOngTb9aDqTDhKEnp7v3AsedpxjB15m3aTkCAyiUAHvfBMrldzQb3WfbvuS4JXESn6gdRpgf4nmEAns2Sde8QSdv0OP+MCKVTKseOLZQ7S8QZuYt7Pc8HWS4HBNETBND3uF+GyNDURRRSsw4kszxndoMEvjZFgmQ3g2lJcsqSzIqMp0hApfpsGEC2FyjMiFGQWGzKsQUx9T0qnE6L2yPzTw1BqnTh/tY0vt9o8JpLZkRfqE6TUKPGc1gp8HjVG6J3VbRlWKHA3V8pswWgo5v9lMkMtzk/xwclqeJaIT5cdPUGpPbMCRLFTCcfrrr6+PfJUWFoai7vu9R1vt4e5B6OstyeE+sMR5lHWhd5q/UaH6IO3E4yq8ZaXjQeOfsIfvs7v43Hxh4DAHTHuvHBl38Q77jjHdeca/18UMRTQUFBASDRaNYXk8VUhurn7KQIJa+TlJULJI39W4Kxk4uwQh3Z96kCjZ9m2XN8JDB8dHSLMmaBN3TXpTIlDUOxBEkhhKO+oyeYre05nPyS7WLeoilC4we38jtzkyQKji2Imgc4PoA2BbNWZ6C855G4OKKPr1KiESgUAtAkcfXdIOPS94RaaFC1CoVIZpqCsMjys5wcpJtBULzsE71gaAscEUAwwtH3hFtaY/yQjI2S89lNQY40nWS31cCCA94UBN51qfhJwci1+VDRPcCWhcmzgCvIo2ECujRbITBcLUxS0rks2xEtBR4PNcBzUK8JpVkLnOK9Azzv0ZgobfvChCOMPS3hhjcMPiDowhnfqAKJrUGWp5z+U6uIyKJOLrdSXDy9S9OpRJomcMMtVCjbDXHRuGgBKPO4yvd8j8sNhYLyPCCut228ViqlQDGPxoLYqP6tK+dvKpwTS53qMSuG9774vfjte38bqXDq3F++RqGIp4KCgsLCGEqt7e/gDbp/C00f0xMknKYJbNlNVWslRbNRIyldqoSePcHSuiy71kTv4PhpKmx9g7xBxxLcjrnpYF6455EUVyokeLEEb+ozEyQJnWLajGUBdp0GDtflRBjXbSt/z3HfmiK83TQDgljKc7slKSwXSFyLee6rKfo2JTuT0390Q4xOjHOfamVumyeyJx0nKPlKJVkXfY7eCgR9NcjQd6lqwhfbFaGiWa+JiTkNYQQCt9XWxLQkXRBhnyX3cJTLcNv6PKEx/7OjB+jfJlopRB9hpRiM2TR0YU4CFtRSqUBLR3fIAprSdS+vKZEdWq2w5UCWrnfuF1OKBBnOdtEFXquI8ZJ6QGA9HzC8gOgWcpyWVRARSZUyWzIcW7jmXSCX4zlPpLicsdMsdyfS7LudmSBpHdrOfejuo2odTwTOfKnwRqNUtvuHF5+fngFg143sh54eE+0XYmDAlh3MvFW4YGw0p/rFQBFPBQWFzYlahTfcqXEqU7EECUS1tNhQoeske64L7NgD3PoSkrJnfiRCqzMBcbFbdDFv2bFYYaqUgdPHScg0nWqm3QpMSZUSJ7406sJ00RLEoQOIJIO4H0O4wV2HZdHB7fy8JLGaxnidoR105MuSbanA/WqKki1E32FMxEI1GiRMZogl2lKO29kQfYSex3JuNE4y1hTlZ0fE8WzfC0yeIakJhem8dloBmZeKpOsIN7sgaxpEPNK5CKgWhMSjrbfUc4O+QEkK7VabiiqW6/kAHEE8hRPd14KpVdIIpel8WHBaLM/rGo+FnM0eFlOwinlhsHJIYGWUVLvL3rBEvJNQZWVfquwRdZ0gFSAaE1mrooWj1aLKmZ9vK9Wb4oEIXJ5mBjmftSoV3kaNwwdKBW5rKstj1moGh6NaYhm9WuIDVf9WkuhKCTj8NFspdt1IlT/bxWV39FBZ9fwgl7R3iK8vOk0a59Z3dvOBRbYqdPRQeb3UiV6bDCs51X/yhp/ER1/90WvaqX4xUMRTQUFh86Ewz2D4Yh4L5ESORszPUUGSZUHfJ7EBaNYJhakw7rmJMTjTY0J9ckkkBrYwELy90T8/y5t37xBLwLUaicr0GDmX3aJiZxo0MZkGHcNREcmke4GjubsfuP1eEsLcHBXGWJxEd+c+xiE1GywRN8SoRUeoj7Lfzxcld08s1zCYvdmsC9c4aHCSU3gkL6xVgJYZTIFqNaiUHbidJLwgjCueI8rzQmU0zSAEHrog0QYAQ0QTteVxLoMga7rJ45zJch21mihzIyCCcnqPL9sIlpgtJCmVozo9l+RRkjpHhNTXysCpIl3gjQbJqDTO+GJ7F2bLg+fd90k0o3ESv4boa2y2RS9pbdmnErUyMDHCY5rp5J+HHudnojEx8chgaL3nBeqnvOZqFV5HrQYw5fL6HNouXN9REek0y/PVO0QyuXPf4vzatEhLGD0tpjV1Mvv26DPsOZVJAa7DZey9ZfV0iGRm8YObwgVhozvVLwaKeCooKGwuODZL3jOTJFXVChZCznXRnydnZEtCEYuTaPaIEpfj8P1YMiiHdvUyW7CzN4gZkmiK2JhqGRg5ToKn61y355CQ6DqQ6AZmp0lwSgUSx1qFamQ6S2WxXAKOHiJpblQDl7Y+BfQNsAT65CNUZYHAjQ2IvkpwnxxBWqIxYYaxg5KxrvG9pRmars0f3wc6+4CuNN3jukZVCz5QOS1c9xBCnxGotAA4+cdjwLt0Q6+KNjU0HBXubZ8Kn66TpPngcXDBYHevjdTJ73oAtDYl1DSC/QrHeD4aTcAtAhBxQJEYvy/HY7aawPwcCVdEZK16or9Ursey+L4mXOOGcO+3GoKoirK+Lvo1I3Euo1xiu0VhDhgQ5W7Zq7tA8HzRpyraHRIpthbISUm+z77Uzj5ez2dOsO9TPkzUqzzH4cjKQxOicT48zM+QeHZ0A7f/GyY0lEs8DukOvr5iX7PCpeB6capfDBTxVFBQ2FzIz3F8ZrnAG3I8GZRuq8JgFI4Be28KbtSdPYECarfYOzk5ShIRjpK45edJHpaWIAExStLjxJfcLP/dqAfft22RxdliiTSRIKkwTcbQZLIkMdNjXFe1TKJnhoLQ8nCYM7aHd5CghcLcH9PCwtjFOoLMS9mbWK9jIecTgHC1YGGizyIIImg3geIc0CmUM0OEpsuWAHmcoAG6uySKSRA5ac6xQiRYcvxmO9HVtaBSPbyTDwCjJ7kMxwlK1s1GG7FdCW3L1DSW2nWDpE3OFvc8oQj7gCfySg2dx98wAU1kklrRwGzTrLcRe9njKR5mNA2IiH3VDbFOQbbDETHfXJiMKiUeU9Oi6cx1gZ4hlr5lj2wkJVIB5PET57Kjh+YkaQxLpqminnwBmEryegL4IJOb5XFcDTJSSiIcCQxLCmuO68mpfjFQxFNBQWFzoVZh6VHTFpuDdIM37WadN/8Dt/HGG08GJW+AiuX4CJXNdidws0GVKZZgZmI7st0spZ8+KkLW/YBEuD5v+NEYy6um6J2Ez8lB0TYncK0CnB2lgtaocZ1OiyRW14FkhyBDHnv4zh5niVoXbmi7BbTaVExJXpa6yxephu1oI4+Ow1J06g5B2sucStSSRiLh2naXzOWW6zYEGZMqq+YDMMS2tG2Prglia3Jf66Lf0BIPC65zHtK5ZL0QbQauHyjcEERYmpAWpi95IoBeD5bRbAbRRr4gqzIiynEEMRSk2nV47TRqgNsUxiiLDwHJDM95YZ7nZW6aJLHV4HvZrmC2e7HA7TAsXjd2U0RZmVS4d+2nyahaprN8/IxosbD5YJDMAHGhjI6PsD94pfB11+G2KVxRrDRT/bfu+a0N7VS/GCjiqaCgsLnQbDBrsbNv+Xuuwx64cgF4/GEqbKEIXb67RGP/6CkxnnGJIUaaTybOMMqovRwZjZMcVqskss2aKLlaQTi7DAUPhUgg4klBQNtgt6iClUQ8jszcbFSFYnqEZCTTASQyLHNLZdUVET9OOxGUfYPa4pL8atDaS/U2iUytzF7TmQmSTAMkt8vU0qXHWhAnV/R9mqI0bTdJSA3R02mK8vXEWfbaui5VYtehUuyuRpJXgY+AYLZkMHxb76ch3PeeeECQzntTuLQ9l+QXCEriUlX2RI9oOCKyTr2gXSEaFe0bGs9tMh1MfPKESaujR/QUF1ji1oUhqqMbaFSASpXHOBzlOU5naXaLirzOkWPcp1aD15ymUemslLi+bXuA44fYR5zOcr1WKCDH1pKYJIU1xVRlCh9+6MP43JOfW3Cq/+db/zM+/MoPb3in+sVAEU8FBYXNhVgyiNZph+8xYLyYY4xMRzcV0UaN8TPVCsukxw6RkE4ZvHnLKCOAf5byJCbtBovCHEvhXX1BzFCrEbi1NV24gC0glCLBLJe4rEQqIDtySpDn0ik/OyEm1Ziin7BFAloqiozQDjElpiWUQaEuLiKYokwcbpt0s1SlXPhou1IqyvSnj1Ftm5ngvhgW4DUv7FwszHtH0P8IYSSCUB1bnnD5t9rW7zKLVBP9mrYXKI3nXylL3PADhVKamzxfKKB20NsZkoYiLzAyaTLTU/SKys95XlBGjya4zaFIoD7qwpUfT/I8FnMk04boG83N8tqThqpGncdYq5AcplJAK8Jyed9gMPEICMxOji2INYBQlNtTzPHa7OwBRuPA80/w2rCsgOAn08D+24LSvN0KzGuaxvczXcv7lxXOi0qrgo8/+nF87NGPbaiZ6lcKV414fvSjH8Xv/M7v4N3vfjf+5E/+5GqtVkFBYSPB86jgzUwy8iUUptq4tKx9OejsoXmimBMlXKFM1qpAboqkMtMZTGyJxIC0Dxz6MUmEBt7sPZ/l0XKRpiIZmt1uBvA8Esxint/pHeANvbuXCt70mFDt7CB8vFygkzoiCEtulsQgGufP2ZMklhVh/oknSDocEYckFcnxsyTGcnKQaZJM6cIN7YvmSemQlgTGE8af1UicNFzBJzmemyFB8n2uQxq1lirCixcSzDiXBiQZ7C7NSPBZDvcdsZ1inT6EEcoL3Na6dp5MUI3XjyuIZrMWxErJbM9FHo42pdMVzneZ2QlRovdcMS1JbJum08DUagI9g0w3aNRoSsvP8/qpiGt6fpqjNZs10ccbATDHY9c3BGy7gbPic7NAvAWU5ml+SiY5EejuV5EEHnmK10siRQLbOwjMjJMwGgYJteMwCcEKMZvTabEXOZnmteiI6yPTwe9rGn83jh5iS4qErgNd/cANN/N3ROG8sF0bf/HUX+BDD30I09VpANevU/1icFWI5+OPP47PfvazuPnmm6/G6hQUFDYiPI9RQCPHRQkwTKIwcYY38n23rk3/WTQG3HgXcPD7VHNkDJIkook0iW60zfmbnycxzXSKXkPRuxcKU5WcHgPie9nz2GwBP3qI0TTVEsui4QiVtI4ulsWjcU56mZ+l+qlpXFamI5i5LuNrBrZwglKlzDJ/q0H+U68KBU6Uf1vSlQ7hwm6Jv0OMphRZlqGwmLHtByTVdbld0l1vmFQVVypjtxNS36Hq6gvV1LLE/PXznQShNurCECMD+j3R39muKkp1tR0LeZzisyuW9duU3QU1VAtUS8sKHOEy6kjzlxNY16ZjXtNJ7CHMQnL2OnTA1Pig4Lokl/BJ5uNJlthrYSqMlRLbPBrCNGSGqEpGolxWKMzrpTDP/t50lmpytosk9s6XATe/KHgosveRIE6OClIbIaksFblMTeSnhiPsTZ0R52rPAZb1pZEoHKEyPjVGgvrCU3yg6uoLQv/tFkktfOCmu1aPU1KA7/v4xpFv4APf+8CmcapfDK74lVOpVPAzP/Mz+NznPoff+73fu9KrU1BQ2KiYGmMuZjK7mPS5DoldKAQcuGNt1tXVC2S66ZA2dK4zluBNWio/UgJzbJbKo3GSso4emjcMi9sUT/KmP3GWozBbDapPMipJOrcNg2pTKkuVcG5SOOtF+Vz2/8XiLMtXK8HEGJn56TokoY06UM5xGxtVLIxeNCzRdyhIYLMhlERZoha5nHJ6EhDE80iiZujcXt8LIoPOhfae0aooJ5+feWJBbaxV2LfqSyURq5ueFr66xP0uobUrtf7iz7salUuptsZTwpzlBORdO0cZ2TB4vqUZSRN9qXI9kuiHwjzPxRyV8EqZ5y6RBPbfSqPQ/DTPiy6mFPUOUV2U0V6NKs/T4DZei57HmKOOrsWz0we3UZEfPcVBCFLZjkS5fVGhzM+KsalWiNOMalXAHhfl+zRJciJN8m9aJLt9gwH5B0T/Zy+XlZ+liqqwDI+cfQTv++778OjoowDoVH/w5Q/iHXe8A5ahYqiAq0A8f/3Xfx2vf/3r8ZrXvOa8xLPZbKLZDHqDSqXSld48BYWNDcdhPFCrIcK1O1d2q17r8Fwqm6a1mHQCJGXpTt7w2udAXyrGR4Djz/EG3TfEKT2lPAlUNM6QeLkNnsfjW8iRCHR2s9zo2GI6S4nkIT9HxaguejerJREmHuP7dpM3/tGTwSz2ZgMLQeaaTlKT7uD5k/2EpRyD4HWD5XrTokpWz9GAI4+d5wXTbTw3mHhjmksImnRcm0Gfq+aLGeBhYYjyga4eGpvOnLz443s+oroUdhOQ3HWpmWo1LCOdGhYmIq0IXbjmdTEJyKCKqreposByZbV9+e0mIgBICLd4bk6U7kWPqmXxNSssQtlP0TSW7uCPj+BhQvb4xuI0AVmWMJalqFACgUlN1xa3cUh0dIvv5xjz1WzS3FYp8e+GIXqCS9yPeIqKKsBrIZZk4Lwl5sJPj/MabCedEqbF7S/mFfFcgutxpvqVwhUlnl/96lfx5JNP4vHHH7+gz3/0ox/Fhz/84Su5SQoK1w/mpoCTR6isyDJiPEGVZWh7EAGzEdBo8MYYS678fjTGG2u1vJh4ui7VyPw8SXg8QVXG80j+ACqS8jvFPHD8eRK5oe18zbFZHp6d5E+9yvXVKiTDxRyQm+YyY3HefPu3sMeuVCCpmJ/hMkIhfs/zgZAgnLEEoEeY6VjI8Tud3SQtFbGNoTD7JR2HimtIZEUms8DQNqpkplh2VvSnhiweN8mbJPmUWZoaAvUQED2IkmiJ9gLDItnShMoZT3CbxkcAGMt9SNcqNLBP0m5heRao6EmVPZ2S9JVLPF/n60XVhRrsuTzHhuhNNUNB7mcoQnNQyBKRSE0qiPlZfmdoB1X2WpXvecLtHksIxbfJa6tSEq0D7uLf33qVami9RtKYyrJF4/jzHHU5cYYkszjP79k9XH88xYcqmXRQKVExl78PvsfrcewUe6kjMSwMUlj1kMgILAVgZaf69TJT/UrhihHP0dFRvPvd78Y//dM/IRK5MAXmgQcewHvf+96Ff5dKJQwPD1+pTVRQ2LjIz7EPq9WiWUYSjkoROPosbw7DO9Z7Ky8cmvjPaiRA9hC2O0CaDSo8MxOBO7rVIDmNxALlNxzhxKGd+9mP2BSzpiWkkjW8neT2zHHgzDHekAHepOMpkZOZIeEH6CyOJ6meyj7BRpXLt0Tp3LFJFqIJEjxpwMkIlapeZS9dq0m1r1oRxyEnPtfBz5bLDGy37aAcK/sM5TGTfYwy09LXxbjLtjK7PIaex7+aOgCTaqAcDVqvs1SsL1VLr1HIXkNPKJia6MFdmFrUrsDK60jsb712Hie8JKziuvM9IJ5h2bxY4AOAY1N1HNpOQij7c/uG+fdkmqR0ZhyYHOP1o+skodLs5Ipro1ljD6hlif7hAjBylKkKVojn8+xJXjszE3xdXqdS2dQAVIsktKkMVf1wlA9H0HmOF4xwOj+Tm+P673oFl3HqyCqHQ7Q/xFd5QNxEqLQq+ONH//i6nql+pXDFiOfBgwcxMzODO+4IerJc18XDDz+MP/uzP0Oz2YSxJJYhHA4jHA4vXZSCgsJSjI/wptk7GLym67zxFXMs6fYNrZ0T/EojHAXSGd4cl5bamw32fxbmgWPP8s/uPh6DybOB491zeVOenWZv256bqPrUqywZ2zZ7I0OrPAhXy4L4IZiDHgqRGGzZRUJZF8ag3KwYMVhgvJLjcPJOq87tNS3AEjmVtogC8sRN2wpxH7v7hVo7C0CElju2iFUKcV2uAzz891xGMYeF4HZTROCEI/yOJDC6uXg05QJvbCNb0lQklUFJvDUARhjQGsFrns/8zyuGNZBUdTNQ4RaMRudYpiEMVCtFap1rMw2ThM0MiZGgHq8pmbVZLtCs1myyxzI/R4XREPPomzVhZhI9tobBVIRwVJiynCDTMzcLPPUYszvrdV7HHd28Rlst/p5Ui3w9liARdF1e3wCnK2U7qGgP7+Q1ZhgkmabF36FYQrSBiFD+bCenFDXrJLTlwvKZ67m5wHy3SbGZZqpfKVwx4vnqV78ahw4dWvTaL/7iL2Lv3r14//vfv4x0KigoXCAaorSbyqz8fiJN80IxR1fqRoCuAwPbuF8VcUMFeKM9fZQ36L4h3uBHjnIcYK3Cm6ok15USb6g9A7wpF+a5nGhcRMmMiUzGFUhJq8Gbrd0Ctt9AAhpP8uZcLZM4DmzlcZ2eoGo1foY37EaDCpQcC6mLPsJGXUwjAomKZYGlW1HyrtfoRJdqtcyz9KXDXKMSWpgnIamUuR4NQuVa0icozTpLca5oI88FPCOI1ZHrNCwSqFV7HtcKa6Co2q2gl9Y5n4IpXO22A2juyn2MK0E3xKz2GV4TybSIUALXlxcPENKoFQqTpFbLPHeOLfptIR4UXD7UWCFe757Lh4hsF5VTzeBDVqsFbNnJqoYmCO7EGaCSp0Jer4prQhqmkmwnsRsi99UFTh6mYaxR54PpwBaW38tFLs80+RC0ZScJcyQK7DrAMv70GH9/fJ/Li6eAG27alNONVnKq78zuxB+85g/wU/t+atM71S8GV4x4JpNJ3HjjjYtei8fj6OzsXPa6goLCRUAGRRur/PrKUGv3Ik0e642efmD3AQaST43xZnr2BG/42/fwhmyYNGiMnuRNsW8oKKmXikEpOxwRjnFX9ONZQY+jHCnZTjpKBZazZT9opUhSYAnDT0H0kEbidDKHIySjpkl1VRp5mm5A8pqNIOwdBm/+nsvllAskKgWhnOoG+/NcSSTF5JxGA9BKQRnWbpLUyBK6zMwERL/hSvFH7f8QBFU3xP57i+OC5DIlgdU3gEAgVWTfA+rnuebbWzqk6nkhkP2h8Hn9mAYWDEeaznNbq/L8WCEAnuit1HldVMtASxNz6cVYUDk1yTRJHnfs5cNNMsN2j0wXx1+GRUxTvSxyYcWQgFCY2yKHFwD8e2Ge5NNx2HJSLvLBqpTneM1sF02IrSbPs2Gxh7m7rR9xaDt/F6bGWVXwPG7b1t2MeNpkWMmpvhlmql8pqCAuBYWNhlCYcTuN2uJoFYlWQ8yD3mDudk3jja2jh8rS+AhvfjfcxJtxO0mIxknS8rlAHXVFb121zJus51GZTAunv2HyxhyKUEHt6AmmsBTzQLMKdGwh8YwmeNOX22UYVDsbouxZLopopA4APhUvOfvdFdmcnk+DkyHC332NZVXPp1q7MC7SAfwWX4/G+XqrIfr+HKDqiYB0LwhN1zWqWdIos3AM28LdF7Dk77rIdlwwH8ke0PNkdl7LqNdEn+15IF3/ms7pRa4NyM4E3RAEc4V99kVepyT5tsM+z1KR70XjJJmuOP62zWtAN3jOjTYl1DABLcLPmCJdoLMX2HMz1dD8HK9/XeN78zO8/mzR8lAuij5fcHn1mijRi4cIqbzL9gMNLKN7Lq/hoR3BwxnAB6B4iu0r7dC0IIrLc/i75Drid7T74s7PBoVyql8ZXFXi+dBDD13N1SkoXJ+wQjQuHDsUjN6T8D3RAzmwvD9royCZFqVMYZZKdSz/TETMvS7lAH8bFsZOzkwGZcVYAhgb4c22fxtv3NkulhWPPCtMQoJ0VYqcbS5V1Wwn+y+bjeAGXS3zJl4XN/l4CgtzuWUcTiTGZczP8Lu6Hqiyc1P8u5yvbrdYaodN8hKJAtAApylC2NsJoSjTA+I9QUChLc6uvBCi6HkiPikURPZILMrBxMqxRQtTgq4R45HsobzQ7fF95nm6LU5GWthnv21C0UrwWALXjIBIauADgO0EAf6y4ir7bWXgv962HqksSyJcLbF1o5TjtTs7KcyCBaqoHT0iZ1ast1ziwwvAB1BPkMNmIyDFsTgJ7ZZdQfbr0WfYqtLZw+U0G0wyuOGmxYahYg547gmquOlsoLLPTpH43njn+pHP9ulm9QofJLv7eIzWKNR+qjKFDz30IXz+yc8rp/oVgFI8FRQ2Iga3kehMjQoHd5SqR7VE1W3nvo0Vp7QSFtS7FRBPkqjNzwQjJUsF3hz1CBWongH+WS0Bp4/QiJXuoJK4dSffl6Xq/i3s8ZTGo2Sa70+P8cZer/F4Ojb7CZMZ9ujl5wA9JtzMDtdvmkGw/NB2thCcPsry5vBOkpGZCRGB0yDxME2uu1zg+3J2OMBj4Ai1S0bduKJVQJaLF+awLz1eOhZKxAsv6cF0Iq+6+OPn64+0RGm51Tx37+hSyAgi11nDKB7Z1yoU4QvBQnldmLQMA4AY8ynNX8tWowV/ys9pehCcr0H0yjokraYoqcvJRrL/1nUAWydxldstlcp6DZg8Q3KZ6eRn56dpLIImTG7i91mW5kt5ks9oAmhVxHXgijJ+g4S4d5DXMcD/TwxsY6xTKMJt6Ojmg1h7RJnv06RXrfC7cv9DIh1iZkK0AnRe/f/HeKJn9cyJoE/WcVgd6R0E9t5yWTnG5WYZH3/s48qpfoWhiKeCwkZEOALsv403jokzwhBiALv2A31bqHisNRxHuGlLgYM+03Fl+gDtVuC2Lea4LnkD9H061ytFlhaff0KoRhUqM60mHfLSUe6D+ZmRGPD0v5LsNRu8gfcMADfdSSWyUuTNvrOX6+od4ndOHSWRCEe43/3DvNFpOglvvcrPxeJUQR2bpfvOPs5mz83wuMWTXO/sJA1K1XKQ5+i6gD3X5khfBb4ffMYDcyNlFM+K88qXEikNC5JcdQnpPBdkwL2mcx1GW4+o42BB/VuNiErCuabxTFIR9s9/3CQ8H9DaIqhcMbZShrS3WktaDtpaFxbmsfuBqct1A7URmuD5fkDINHG85XkxhFrqipxO3SBBzIvJWHUxu92weFzlMS/meP14fhAX5guHvCzpy2SDeILtIIkkH8baVftQiOairbtXP0bVCn8P0m2/c+3IdASO/dUMjlcKk6P8fUxlF6dfODaJezhC8nmRUE71qwtFPBUUNipCYTpRB7fxf7yGEdxA1xpTY8DBH7B07YmycKqTpp99t/CmuRbwPJK60ZMs6RXmWYLsHWKQejTOEtuJ5/j3m+7mvp8+yvJjNA7s3Bq4cD2h/tgNtiZMnuV7ITFV5uwJqicv+3fADbewFDk9RjLSarI8roGqpSQAoTBv7IV5lvemRTajK4xM8zO86Q+Lsr3rUUHNzfJmXS6I4HdX9OpK8nmR/ZS+A9QdkhTPFede9vXpQWRSO3QNMLTg++eDJEe6KM37PjNKbeGw1kyWlD2puJ5rey+CdEridrFTkM6LdgIp1ONQWJi+Wjw+7pLPC8GSCrPoA3VF9NHC6E6hSjqiF9QRMUtWmJ/1vSAXtVoOTEVWGDBcMW2qCVgeiWSrSQNTMs3rwnGYagCwZ7mzm0MTCvPcvmhclMNFZFhYjF9t1Pl7FBbh+roR9ESvBtdmuT65imnGCgVO/asJ1wXGz/I4L41cMy225EyP8/+J7Yarc8D3fXz9yNfxwPceUE71qwhFPBUUNjpkJuCVwvQ48J2v04SQ6eKNp9UQs6WF4/qWu9emv2r0JHD0EG+U3f3syRw5zpaCwizQM0jyGEtQ3ZV9rI4dTJgJhTkysNkARk+LudcizkiWP5ueKGt2cf9+/BDwitcDt72ExqPJsywnhiMs4cUSLLnPTgLPP8lwftcJyuWtJknE9DiPRzJNAjo7xW2vV0kC6lW+b5iiN9e/fBXQtYNjoOlBCd5zsTCeUTOCmCfPD0jK+foipRHJExmRpsXSri5MXK4nRny6CBja5UCcQ0n8ryRMM1CyGw0ABhAWCrLdCgi8YZBYa0YwFEAeP12UzYHgwc9xgmiqUFj0gYrfTznnHeA6XPHwke6i+t5q8D25Ta4gpfEkr8N4nAQrP0fSGY5QoZfKo8y8bTWFQq+xR9R1qLz3DLJ/+VywQvxdaTWB6Aq/062WyKm9ynPHGzX+/2a18PponA911fIFEc9Hzj6C3/7Ob+OxsccAKKf61YQingoKCqvDcYCnHuWNbnBbUFaPRHnjLBfZP7llx+XPbm7U2FsmeygBjp3cdYCl8NFTJGudPcCWPbxhS0SigSpXzPPzjRrL56GwyNEU5eFEgmStVKAyme0kQRw7TdPE0PZgLGHPQNBbFwrz/cNPMvJpVpTLNRGZ4zr8t2kCM9NAss4b4fyM6Cc0aUDRRYlWF8RvLVW9hR5FQZjMUDCC0dAZEB+J8e9OK3BKr4aFHlI3CNOXYfhyfS3Rh7gmZXShMLZPHroSkKYe3w+US90PxmtaISAWI7l0HMATCqmsLKSF4c1uirxToUrKkapyEtWWnVzmkWd43FwnUE9lqd5u8eFIhrtLVMu8Rl2b7R2D24L3TJPrTaQWl8PDEfZwjo9wuZUSfx8MkwacG24+f2tMLBEsQ47QbD9uxRxJ8PmU0yuFVS+LC7telFN9/aGIp4KCwuoozFGxS2WW37CkMlLMk5heLvHMz9NF27NkObKfdHgHy42JDElns0EFRCp94Qj/HYqSVBRy/G65QPdr3QdCTf49GicJqNf4vVCI5fJGjYRhfprKkqaz9Cnnr5sG56ePn6WquWMvb/CTo/yOdKPPjpOYSvOSL0qo8IPqd7vJZqmb/LIhlENHbM+ivkxflISFIueKUv/SG7emk1x4wrWt+UI59oMysee2hd+vEfn0/QtrA7i8lYjpQ0KpDpnM2XQcnmNNmIDCFuCLSVKSlMq+5kaN6tvWPUGLSL0KRJNA7zCP0dadDGLXxcNJOCZIrjg/raYYDlDiA0r7JDL5+xUOB4MELKEE12sko77HnkwZswXwO129/J2xW8CeG/kw1dF94a04W3fRvDQzzuVIV3sxzx7SrbtW7v+8kojG+DtXyq9sIKqJqWKJlcmjmql+7UARTwUFhdXRqJOkrDapJBTmzba1BmMVJflZLdTbtETZ2GcpXPZMNuv8rmGQGMUcks78LAlxbpb7oYEErFHjzQvgDTuVJbH2PO5rS5TOE2mW0nOzvNHXqySglRJJ7+BWOn2nx6lOGWJ0o90MnOeACIh3AK+xOjFb67xMaXaRy5VOdtdhm4EmhgyYomcxFApimgCeAyskehkdEqW6iIcyLB5zx8aCUUlO8dlocB1GFkViPAbhCPl3rSL2UVyTpjDt9Ahi6Lt8QLIsPogU52nGaTWAco6xSNCooreaQVi77okBBGLakCuNWT4wcZbrl6XkUoHfufuVVFgnR6maxlMctBCOAIefAo49xz7jRCoYF9rRzX3atpu9yxfrPk9mgJtexDaXibM8FuEojUlbdgaK79WEblD1zc/x96295N5q8gFzx75l/eZqpvq1B0U8FRQUVoeui7J6E8AKvVXSUZ28jLJbtcyfcpHkx3VX7lltNlgWLxaAE8+yjFyvieB4HWiU6dTu6qHik58Dzp4KZmzXq0K9k1N/fCo4lRKV0kwHyYfrkOSOj1DFDAljRqshooQaJF0yvqkwy+O0sFyQwEo3dFPMz9Y0wF+LPsgLgSaczl7w91aL+weQOPkeSaicqNS+aTKSRxLYhdK3RkLvieUuqF7+1dmtVXGJx1W2PdQqQQSSLKnLUaS6SbI3vIvnslxgyTrbzT7gqTFeW4bJ/tdKEQsTslqN4Pj6PjNaPYPrjET5AGCJBxY5+rXZCIj8jXexvUPXqfh7bvCAA3B9Xf3Ac48zzN6y+MCU7SZJ3H7DpUceyQlp0jwFBIas9ULvII/1mRM8D2aIv/+6weOzfc/CR23Xxl889Rf40EMfwnR1GoByql8rUMRTQUFhdaQ62FM5eVaUEdvUBN9nebxvkLFBF4tWEzh1hGP5pGo5O0kCuufGxcH4js0b8o69JJvQaAKKRKnsOCIWJ65xm1otmi5cm/tQE9OMWk0u1wdJVSnPZdTKgth2AXe8lPt2+hiVnbowNVhhoFUWkTt+oIDKEGupKvr+4kgeR9wYdX3xBJorDUOQGkdsi++IMY2e4Gi+IFnuYnLRjoVgdj9oB1gQZ9fAGHUuXHD7gYh1uhQs9KoK4txsiB5WnyVuKxxEIk2Pc1WVCtMdTItmn5lxbkO1TDXdMESFwCd5k25/XYTPuy4f5DQEJirTEv2ZfWJ4QR7IZIGb7wyInry+2pFIMlZt7y1B+Lym80HwAp3dKyI/xwD5eo0PZLLEPz5Cwnfjiy7vYfNSoesk0529fCisVVl16ezhcdONFWeq7+rYhY+++qPKqX6NQBFPBQWF1ZFIMoy+mGN/ZatBkuW6LC9G48Dt95L8XQwch4aLiRESQzn/WdOBU4eB5w8COw9QwWnU2Mc2sIXlNdchQZQlYNsWZEEopcU88K/fC+Zi5+cC5daxg/KxBpLQcES85wAP/wPw3EHu5+QZ9n3KCCFfqFgyaLyYB0wdaDRF/6eINVro3VwkIQriATGr21/78no7pGIpJw2ZJuDrgcGo2QjULDn1aaXt8aViqge7crWkTd9bsl2aCLAXCq7jiGD9NTiOmh5cP4YFaG3ZpADQrPFBZXA7yWMxx95NeLzOEhk+NKU6hNFIONabzWDClN0MEgd8BOV3HzQvlfPA5Bh/l/qGgF37lk8fs1tiKpbI7sx0UOHUdSY0rAU8Dxg5RhLb0/ZAGTW5bTNjNAEeuH1t1nex0DT+/2KFmfFqpvrGgCKeCgoK58aOvSRWJ1+gylAuAtCAoZ3ArS9mH9nFIj/LEmVnX1BiBGiYiER5YyvMspQYiTArdGArFcaWmPbSN0RCVSpweVaYpWRdTMkpF3mDjsR5w6+WSSrgALow11gWb9iRKONmZiao6iRSolRtk3D7Pnv8wkJd9UUZstkKooa0hlATNSwjQ9JZLtUWXQfMsBinKNXGcxC6SzbuCGORLYi2L6cHtW3fstnuKyxDMxZPU7paaCfDusHc1GiUma3l0uUvX54PQz4MiOO10EYg8jnlwIH5aRJIuxnE97ieeIAJBwkKjRqvCYDHLhYDSi3uj+z99RG0lcTiJJnJNLD/Vv4eLDXzzU2R7JbyWOjfDUf52V371y7Dt1zkw9oKxA6axp7WuanlFZB1hHKqbywo4qmgoHBumBaw92aaaUp5qoaRGMtbl3qzm5te3NfWjmwXCVnfFqqt4XDwOd8nEW01eJMHWAY3LJLHVpNkMiRMIvPTYh9MKn9WCCwRG4ETOCJGVRbzomQvMjZlUL7dIsGU/W3JFPtCbSfoRV0gnKBRZCmP07Q257FPchyOBLmN5yR+2uWLjLK87l1iNuaFTga6kvA9EV8lIp1ME/CscweZL4xdXc3UhcB0Zug8LyY4w90wuE6ZX+p5wdQu2aubzJCklQrcjmSGqvz8FJcv3eyuI8Ln29PphdJshNi+oemsMMjWDIlmg3Ffh5/i8rr7g/frVRqAoPF3dC3gtFhFkONjlyIUFg+ArXUnnsqpvjGhiKeCgsKFIZm+/L4u2RtZzJ1bwTMtEsWloz/DEWB4G3D6MG9+ckRmNCEUyCaJYTzO+JWZcZJEywJiSZIIu0nCYYYEOZ0JguVlVqVh8qZaKVG8tCzeaHWDy/E9EpZF03r8RX8sgmEE6poliEa9urKS2T4adNUFbjLoIt7INESwvB70yp5LDV6Is2p/USiZWltfqy+c/uEwz7XdEukEVnA9yFB2Oea0mCOptFskrHY9aLdoNbEwylOPid5Pcbv12tT2SCzo3fRc9ic/d5BkMxon0Z2d5mCFwhxnrYcjQYZmNM71TI0yMmktRuWaFver1Qwe7tphywD59Stdq5nqGxuKeCooKFwd5OcYLzM/IyYR5ajudPUtv8FJVXV+hjc6y+KoQNMEtuwGdowAh54gOW21AL3OG3cszs+ksixDjp6kQWJhzF+LSiU0cdPXSAB18b9Cy2Ip3xJmj8I8Ca4ujTU+VdFmMyA7miHMRCuUy+XUoHBEbIPD5fHNlbMQr6RhZ6PC8wB4LK8vxFa1TQE6F9qPp6aJMZbC1b8QHyXURzlD3RS5lTJv0xbh782GeIiJ83waJhAWvcYAP2PboAsJwchWRyjGGoJg/2hUTIEyeA1WSsDYycCYNjXG/RvexeXE07weKyVGGqVEKVyW/Eu5tSGeyQyNOvOzy7N5fZ9Vj6HtPAZXGXKm+oe//+EFp/rdg3fjY6/9GF669aVXfXsULg2KeCooKFx5zE9z1GSjzhtb/zB7yUZPkoht2RWQz1qFN/jx0zQ5eCJwO5mho7V3EHjJa3nDffpfqUxZIbp4w2GW6jt6AmXG90SWoujB1HXe3OXow1YLSCcEaWiJ8rnP8qZrB8qm5wJeBXBCgbFJF2MvdWP5BKKFPFKfZGQhF1JARuwslIPFZzWd221f4ZGRGxGyP/W8famrIBwh8WzUAE+QSs8LDF9yVGYkItRN8BpwRX9uJEwjEcD1R0QgvOcBiS5AD5MEeh7fq1XENaWLcr5oTTEtXs/hKK9Lu0UiZ5jMqpSjTTWNSqfc9rBoC5kaC/qQZezTxTywtJp8qKuWxYCGDCOYDJG+sHUPe5tnJ9nraYX4sFXKUW0d3nnxx/4ysNJMdeVU37hQxFNBQeHKwnWBk0d5s5Mu2WgUGNrBmKapMd5QewZ4sysXSNBs4V43raC0+fyTQZ/b3a8Edt8I/OCfgNw0Q7NjCSqcZ46LcZXT/LdpiGgcnaMqWy4JhSmCvGMxOpebDpCKkxTLmeaeTxJo6IweatZJIKwI4Lba4omWQKppPri+Zcdlad+k6CFd76zEax2XlAYgyJnMidV0XhNyhKV098uHhEU5mb3BdKFwTJTdhYoZjZM8Oi0g3QP0DdOc5o8GiQm1EntGNT94iApHgnSIiiB/usibTaT4wBWLCaJZFGM4G0HAfLlI0pjMkLRq2oUnS+RmgWOHWHGQ+6wbrDzsvZn71NkDHLgDOHuClQrHpkrbO0QzoZwNfxWw2kz1X7njV2BJIq+woaCIp4KCwpVFYZ7RS9n2uBeNrvRwhMrmzARJY6ojKKN29wUfN0yqmHPTDI/u7OHNsrMHeMW/Y+ZgKUe3bSEPwKdLHRAKpiASpsEbv6YDIdGnpjtUYjNdgFUmiWg1SQzqNZISM8wSfr1KQuy0FnZj7eALM7wP+ErtXFNouujphCing9dCPBkMFQgLI5ndIMmzLF4jW7ZT7ZubpomoXBAkMEq1XE5xCpeAM8f4UNI7RLVQAxBJBPFWtsPlWhYfpIBgWeEwJ+8YIipKlvKlslopibaTEK9Jx+FyC3NAVuRYng/VMnD4aSqxPW0mJcfm9CMAuPkubkNnD39nKyW+b4WWz4a/gjg6dxQf+N4HFjnVf+ue38J/fcl/VU71DQ5FPBUUFAjfD5QUgDflZPribjTlAkt40viT7eaN2feWO+A1TdwsfRLG3gExfjDHfELf53LKBd7gTYuGofwct1OO7ct0AvvvAH7wD8DRZwMFsilKmPEUiaLv80ZugOtsCGf83lt4U5W9cgcf5XcbNS4nGud21qtAU+NN2RWl+ss1/izLzxTL84CFDE7vEsvKCm3wAOii/UH0i3o6UK8DcOksN8wgZ1XXWVJuVIETR1kGT4uMzskxES2lAy0xjlWep5gwtVWrImEhBPg2EEsDZQ2ISme7KI23moGzPp3lw5cwTdm2DRsGdNuFGU/AjMaBuUnxvYYYelDndu0+sDx+aSXMTvIa7x1a/HttWlQ856ZIZDt7+bosw19FKKf69Q9FPBUUFHjzPPE8MDMZRPyEIlRFdh1YfVa7hO9TiRw5StJmyAiZYyL0XahK9aoI1dZYusvPsJfScTje0nWAuRneSPNz3B7HJtnzRIlUOow9j2rq1Bi3/dCPWSZNpvnZSknkZzpcht0SU4/8oB/TsEQfWwe/OzvJz8tsTVMYWaoVLtMSOY3yT3+FEvpawLJYevVsQVQU8bwsyBGU4TCvQdcDNDmxCYCliXnkMSBs8bPZTqCk89op5pgVq2lB5qau8zvNhugRFQ9XkXhQPjd1INvHcn0xT4V/5BgNOu1z2eFzHU88DCfThWqhiGa1hnyiG2GngWrcRravF71bEzDGR/j7k+4EhraxReVCpxTNTFE9XelhUjryi/mAeF5FrDRT/d/v+ff4g9f8gXKqX2dQxFNBYbPDcTgpaOIsbzgd3Xy9UaML3XE4L9o8x/8uZiaAE8/xpts+QaXV5HulvCjlaYEZo1TgjT+WpLloYCuJ5IkXgMcfZrRRtntxhFO1zBv0+Bkud+Ist3FuisuTphDTYn+n6wB1N5g5Lu+3crRlKAT0DJFUTE+wtNrVx+3VdGGqEOqSFQ5C4OVM97XI11wJjgP4V2m05maB5wZqPiDK7+J1u8lrRBJIzeC1KB9QNI3nJBJl+dn3xOQkYVCDz78X5vlwUysL45kHDHdSPW02+ZlYnORvcCuv/XqVvzv5ebiJNApaBQXPQrZVR//cKVT6tiEXTmBkugg/7GCgbwja3lv4+yIfxi7mGJyzgnGpgwouHWqm+uaDIp4KCpsZ5SLwwpPAU4+xpFyrAB1dJHyRGNBlkeDlZhaPz2uH59GEUCrwZ/w0CVkkKpy3Gg0NvscImESWStHMJG/4kRjVpZkJEkjP4yjNhXGB3Sxf+h4/39krSG6MipFucD2VEr9bKQCpTrE/Vb5mWAC8oBwpsxjrNaqu0JiZ6MUZFXPaBirFoOyqaSTRstdN1y7R5HIutMUxXclxmgqE5wXTieRcdRmX5LaAUpF/jyfEg4Av0hZGSCI98UBjhkQKgTCaRVtiEIEPQKjzrsM/mzU+wBgmjUuhMMlqLAnUKnCaDbjNOcQ6++BlOuFVCtABdDYKaHo+JpFAbOsBZE0LOPQ4f990nf3QfcPnL4t3dFFxXfF4CAU4fhkz3i8Caqb65oUingoKmxXFHJXOEy9QNZFTekZPs1Q4vIM3VE1j3+ZqxLOY59z1eo0Er1yg4uN5vInpFlDOAftu5w24UmQfme+R4IYjVCfnZ3gj7h3k3x3x2VaDn/M8Es3uAeDI02wBcAWB9EV/Xa3G1xo13oTnZ0CzjiiJ+4Jg+GJSjQbmFeoatz8UISkY2gacPkoi7vnsMXUdkfXoUY3024jimkCV068u/BXUPUH4peu8WgrOu2OTOBqmGM0qzGetpmgvMfj74ggDUTzJ7xbmgilddguo5fm5uWkanMoltnqEwmiU6/A0C14siUpyCzxNh+46KG67EW4khjN1DZ2z88iOTHKZ0TgJ4+mjbDnZfxsV+9XQ2cOWllI+yAEFeBxys+yt7uhZ8yO9FKvNVFdO9c0BRTwVFDYjPI+z1ytlcQPSSPpCYTG3fI43zp4Bqn7nGkt45hiVl0ynGDtpB8afWhVo1dg/Wa8Ce24GWnWqRqUib4S5Gf7bMKkkyZu9HuINv14DrBJnxnf0APUKzUJyRCbAG71hMYKmUuZ6Mx18vemTLOoaI5Q8H7CE4uSL72o6CYOMOOrqI/E4fZR9n64whOjCFe+5WDaPfU0gDUVK8VwzSFVzQUU+xwODbVORDMleUHcxaXQ8OuKjieBa8X1RevdEed3mw1Kjzt8hOXIzngImz7Dcn+kSD2EFKvUGs1tdy0c10wtncBeg6dBcB6FKAU4sBSeeQjJ3Bub8CWDrAKsAEskMH96OP8/f56UDGYp5EtO5ST4UTuZJWrt6uf2NOh/U9ty08rSiNcLRuaN44HsP4OtHvg5AzVTfrFDEU0FhM6KYI7nMdpFE5WaD9wyTJoz8LG9MdnN180KxwGkrVkgYk5rsyZQ5lKZJBTSWoHo4NxlkFxbn+b35Wb4n52J7LhVLK0wSFk3wxh2OAvBJKi0x+UUXZiPDBLQiPwtNBHcLV7GcHNSoBcqUHPfnOVy2DM5uNYPSeiJJxXYOYsqiICy+F4xKvBxoop9wEQnyrwyf3axYUCFdPnwAQdi6JgYASPOWfK1lA75Q7C0xVlWOWzVFokGlJFo/WovbIqQpzfM5QjMUAqwsr5+ZCRLbbDcfmiLi+q1VRVk/BN2KohLNICL6NjWRnBCq5GA2a8DkCVhRbTHplMh28XcwN8Oyu4Sc816vcj86e7mfpQIJaf8wBzP09F+4SekioZzqCu1QxFNBYTOi2eAN1ApRIZmdIjGTIdShMFWbQo43yJXKd/k54OAjwOkTwY1Vhp8nksEEHtchMaxX6T6XjmDXAU4+z1gjOa8aACBijyDibop5lgZ1nQTSbjJ6RpbyUxkS50SKPavwRWneJbEwEMzglpOBDIskU9MCw0UyzVJquURVKj9PJdYVLnYrxG1w7EBpvVQYpohS0oSauoR8KpwfphWMvlwNrgdgyWfa/66BDxGeyweBeJzXnCfOeTjMHs7uPlEyF1Ovmk3wIWFJqoEno5nEJCTd5PXteOyvTCT5e9ao8xqzQvxdK+aBSBTGnhtQt7IwHA+WoSE+cwaa50NzHLQcFx3TZ5Du7QQq3bze26Eb3J9GPXit1WQ/tG0zQkkiLkxN1RJJZ/c5yvOXAeVUV1gJingqKGxGGEbg6I0l2Fc5OcobaiRKYloXWYT7biHRa0e5CLzwFHswZc5lrUoymp8laY3GSdJSWZK+Uh7o6GVJHmLd+fkgD9MQ/zvSDSAS4vodMY+7URczsMFlReIsLfYO0R3suVRxTZPrmZ8VTnaQnOTneYM3QoGyKud2l4vcxs5ehtCPn+b3mg32dvo+YOkBOV4L04PrijxRhYuHmDokpxGdk6f7bK9Am4lo4S0/eNjxASQSnNZz5hgV0q4ePtyYISY9hMKiFG9xWfLho31cpS9aMEJCKXVsrr9WAnr6+AA3dpoPSo0a20Zcl8tMpBHbuRs9FQ/TcyX05kdh1fKo9G7DfCSLlgfs6SghUq8Ao6c4QSi6ZF56+z4B7HEuFZfPXAf43UqJaRNrTDxXmqmunOoKEop4KihsRqQ72HMmg9i7+6km5kTZu1rmzaizm6StXguilgwDGDtFgtm3JZit3tEdKFC2TQJrJNjPlp8PnO2NGkuRter/z96fB8mWpuld4O/7zurH99gj7r7knlVZVd1VrV60tmgkDGlYmjHBDAZIMxpGkrHUoIaWGNEtA5UEAjSAgY1JAgQzDUJCzbA0rdbWrd67qrKWzMr97jd2D9/dz36++eM9Hh5xb9zMm1mZWTer/DELuzfC3Y8fDz8e3/M97/s8rygvrSWJRSoK6as0SH5lnpfz0LU8p+tIj2hh4N47spjv3RelytJCEi1rHgTuleptMpj3sWktRLsSSMaiG8j5aC0Ta9CAEuUzCoHS+ZwkUlbVpWqaf7v5neaMkZkLPB4KmbNuCk6Zgyz7vee4n5ppXqrNriebnfaKqN71tnwu8gyMhmarzOcspwd5ZX9nXj6XZc3bLgwnDGyFkNNaQ679ShUuPQXXnpXP1mggn5NKICprOMQaDblMQd2JCPOE/cYW48oKgWtzvllhqXYOdecd2WR1DuDClflri0J5LbP+apBrGx49gtWvyEbteGTot4eFU32Bx8GCeC6wwPciXA8uXhM3+rAnOYPNJSFlh3uiHFYC6QN1SqfuvRuyMLsV+Pqvi8o4ncjCOxqKeuhXZBFP43LkoC+EdNiVvrOlVVGFLC3GIs8vpxEdyeKdZ3JumRHSCRwThH5XVNlwIhE0eS7kM4ql5B5UReHpdUozkTUvsdtlrI0p+/aeflFe68GOzHkP6qLejnplbFJJHB4qg8/KtIty+McCbUlbRFoONZi1cjzILXW5lNmWzEU3BXND0Yk7z/pqFaJkuq5swFxXjGsHO1JuB9l8BYEohv2efD5GfdloWVb5uYjlswHz80qTMrZLlbmfy/IZO9iVr5lz/KR7fH9b5qRvXsDKUtaGfbKaR7u5hrI0FQV2d09U/smgzAodS5+zVxFiO+jCxavzysHxOb1bK0Iun8EPgRCe5VT/d37nv8Mf/b4/unCqL3AKC+K5wALfqzh3WZSOu++Uo/iYq4ueLwrnyVLe0QG8/Ovzec1e6SqPy7J1UZK98VBGDc5I56TM17x0vSyLlypitwOTNyBO5kpRUJV/i7zM37TKRdyIIenNbwipjEunfGtZvvodIa8mFyKgLSETWSrHCWrQrMCwNIVkqbzm/pEQldFATBlRKGX8miNE9yGCuXD+fGzQ5XtflKrkrO0hn4Wmnyyb54BV9hWr+fsO8jPXk8fNejJNGfg+i0raeg42z8s17nhCZJNYrrlwCo0laceo1iHri+quy7J2YUQJV6b8v5pffyvrciyvItfY134FNi8KiV1eE9I76Mrn7fzlE20oBbZl0aj6cp73ygqDH0hw/MGOXJ+/8Q9kcxXUpB1mMoaXf1USIM5fOY5pkqlMD0wfm1UfLj/9bb1Nb3Te4Cf/3k+emqm+cKov8G5YEM8FFvhehdaieq6fk0Usz0QNvPm6LJoz0mkK6f3c3y7zCzW41XkZ0auIErS2CVsXRXG8d1NIY/dQ1MRqaaowZh7inpejCKOJLNpJqZLOsgnjcpa6VY6tjCNRqsKpPNarlMHcUWn4CefHnvVj6rJXdDoGqzl//CzwO8tEDQ0nQjrzMhQ8KR42jnwn8dBM9+9yzDYys02KmSnPZV/ng4lIxoDJIMnmrRazO/iBfMWhvOfHk37K4zuObFpmG4247N0Mp2WCgSvKfrMtpNEuBwgsr4tK3juSayecyLnZbmlWa8m13+/I+fgV2dREIfTfkfaS1Q3pU37q+TnpBCGi1slxnR05VpHLdb20XkaAJfLZeuH7xGRnEIL75jflGCsb8vm+d1NGbM7c8FkqRLa59Oh83vfAx+FUL4whLwy2Vosy/XcRFsRzgQW+1+H5sF4uFLMMzGp9Pgu9dyjq5NGeuMUnQ1mAZ+af2eSW6USUlqN9WdCuPCUlfG2JgeHeTVksrzwjRHVvW/o2B0npVk/LBbzsATXll23LMSajchxmOQfeD2QxH/XLiCVnrooVWemWL8lKmsgCboyc73gIhzvyfOeuwdFuGUA/lmNkybcfl/Rh4nuBdFrlrPAHezeNOUEyzbyntyhNaQ/iwd7ZkwHvli1GMduVxyax/GzUl2vOtssxqWEZ6eVS+BVy28FMphRLG3ib51H3b8n1t3ZOcl737pVjN8uEhKAG9YZkZoIQzkogJHDrknzO+kdy/b70hXmYexLL9K69bWl52b0v8U6ToZxjlspLjiMZD3vucrkRK3NmFUJAD3eF2K5sSDan1nLMQXfertBehadelOv+feDjcKpP4pTtown3jyYkWUHg2VxcqbG1FODaC1feJx0L4rnAAgs8jKKAnTuygB33jClRU5IYNi9JGbGzL7cbI7mAN14XFejqc7L4zsqiF6/Jgrd3X9SifhcOtuVYbukS1hP5N09LJ3npQJ+pXzB3tivKmJqsdLyX/aFFqVQWOZCWETOzyCRk0bYsKX9qB+x0HpGUpUIe8uJ7g+g9SdC6HEOqS6XvDOPVcW9nAen7UKNnRLTI5fqx7bmSajvSwzlTJJUCinIKlyYzEE0n9Jtb2IDa3Sdbu8BKtYk36Mlmp9EUc17/CG6+Ic+zVJbRp6N5C4lXETW/3pKvtS1p9winQjzDCbzyFfmMFIVsgO7dkI2c40tFwbZLE50tZfXpZK6MnkStIecTR/K6nv2MlN6H/bL1pCqmP+vRJC4vDIeDkJ3ehGmc4TiGf7D9N/hLX/7SR+pUH4YJL9845HAYUfVtHMtiMI358o0plwZ1PnNleUE+P+FYEM8FFlhgjiCQRWvnjpT3qvV52LrtlL1ymZiFnv6ULKSdfVnQXFccwCYXM8XO3TLX0JaFdW1TiENzSdSXMJSFzw9kwZ+MgVItSmNxGWtLFu9oKmpnkpSl8KSMsyldynkG2CfKqCVOlsvzfO7uTSIxkVi2zIUfDUTlepLK699LKAooSoW5eERJ1fVK8jgjpaWaTUkWHwum7EXWcr0qLSq348pxZiNRbZc8T0mKHJXH+PUU7bukyiKcTtmrrLFWd6m0V4V4ehX53EzLbM5aXQxqk6Fc++1lIdMny+kz0pfEcg6/8rfhxhtyfU9G0iNda0rfaTgpBzpsSCyT0mK0G/bkM/oggZy592cbqFnpv956rN9Smhe8cueI24djiqLga0d/l//69b/AzlSixq61r/Pnf++H71Q3xvDG/T6dUcS5pSq6NBjWKw5pVnD7cESr6vL01uO9jgWeTCyI5wILPIkwRsrBSSyLSqM171/8KKEtMQB94zdk7rm2hNR55ZSVyUiUziiSmc95KipSFsP156XPctCTRbNaK6NmUlFtZoaj3qGonXkm5T7HkePO+tcsDYmRxzVrooRZthDRO++IQqR0qaaauRo6C6p/t5GIhRF19PabQgQKU2aFsiCdTwzOeO+UFhOapR5Qo98lOulMlEQ1z0XxNvm8H1SVxylyCschy1JUnsvwIwqM0Si/Qt0qONIudy+9xDOr1bmyuLYlX90D2Ti5lXkfZpLIxqvePHHqZStJmsBXfhneerX8LEyl7SDLZMO1tCqfD6XnAx+SRExFk5Golw+GyU/HYoh60FD0mLi5P+TG3pC99FX+8qv/Hq90vgxAy1vmn7z8x/lXf/CP8dKl9Q907HfDYJqw35+yXPePSecMjq2p+Q53O2Mur9UXqucnGAviucACTxpGfbj9tiiJM+LZWoKL1z+wEeCxkaWiZs5GWg6PSleuJwuf54lSdLAn6k5jSaJugrqoL3dvCBE8GVjteqKW3r9VljAtOb625PjVhjxvUJ3PxrYdIaBKSR/b4Z48Ztb7WWQn5pmfIB55hmRxPoqMmBNleTMP0V/gycaMbH7b0afltYMjG5q0mDvktXUcoVVoixyFZQrAwiBKee76uJMB6sIlbtYvcu7pi9RU2ZfqlaX6/W2ZeDXsi/LZO4LzVyWQ/qQiPxlJxWBUhrgHVdlsKS0qpjHSk+mUc97DifxtCFflc6htaTOpt2RDN0M4FdK6dfHR+Z3vgiTL+ZWbX+evfuvP8+t7fxsA36rwh579l/k/P/fHSBOXvV7CM1s5vvPhkr9pnBFnOavu2YS56tkMpwlRmi+I5ycYC+K5wAJPEsZDePWrQuKaS1Kay1JREV/9KrxgxKDwUcAYeOc1uPW2qCz1BhKmHorTt70sgfL374jKs7YlxG15XcxGWSojMWdRNfaJ7L7RQMqOSSzlwnqznKeelgHWzGeux6Goqk+9KCXxyRiJU+qLemTZ8vNH4j3KrqYoRynOyrQncCpgfIHvPpRqeF6WwVXZA5yXPZV2Ieql1uTawTEJuVJY8ZS8UsOdDknqLcZXPoXdP8S8cgBFJNfv0spc9Vzbkv7LcAJvvzo3BrmWbJgmQ7n+Lz4lJrfZMIfS0CSnWuaAhlP5O6CQ8+yV42GX146jm/LOHuPUMB6OyY3CXLxOs75C633+dvbGe/zk3/0z/Dff/C8pSqf6H7j6z/FHXvw3WA1kulFuFez3Q8ZheibxLIyhM4zYH0yJkpzAs9loBbRrHvo9yvKicirywmDph++bFwatFdbC4f6JxoJ4LrDAk4TtO0Iy17fm6ojjCrnrHsDtt+T/9kfw0R0NpC+ztSLk7v5N+b8qy5u9I1mcw4mck1eRFoCNC6Lc9Lsy9WU6kr601vK8J7R7IAuuH4hymWdSjkzL6JpZxTTP5D+VQMKxL1wRMr4bSM/cqMwEtewyM5FSBT1BNmeL0mwayyOJpHn4tgXpfPLxbW0OZpFM5X9dZ75Rykq1UStUFOGbkNzxmK6cJ621yf0AYzv0r3wK9+A+54528I6MXO/TsTx2rXSRP/WikMNaXcjjjdfLEvyRPHG1Lvdrr8qI1uaSfGayHJwTpCqozzdsqxty7psXhHTmOWxdJD53jds37tHrj4jdZeL2GgPTpPLWAc9utbm20XjPPsxRPOI//PX/8JRT/Ye2/hH+xGf+bbaC6wzDhL3+FNvSVD37we3aMdK84NW7XW4fDMkLg2NZZHnOO7tDrm00eO58+0xCOUO76tGouAynCe2a99Dt/UnM1nKVwFtQl08yFu/eAgs8KYgj6X2sNR42yYAsTrMJJctrD9/+7aJ/JAvc0qqUuXvlc9WaUh6PpvD6PVEblzekh7N3JD+/cE2mxnieLOrNtqiZ4ViOmcZCJvtdUTRtR/rYlBYiG5d9m3Zp8hgN4NWX4ZlPS2/n5kWJlbn9VmmksOY9oUpLz+mx0jkrtZ9BLBf4BKNki7PS+PtKHlDzMHrPl8+PWynNQN58olUSQw7KNZg8p9c+T3rxOQrLJvcDJmsXsadDONimXrVx44GUyJdW5RofDYVkJgl8+vOli70Jn/6CKPuzsa3NJTmP8Ug2kZYtJLSzV46+LEvns9vS0kjn+fLYpJyY9NSLfKtocaPls365gmdbeEAD6Zd85W6XwLPZWjo7Mmk2U/2nfumnOJgcAPD5rS/wz177CZ5qfJ8QyXtdoiQ/1Tl9bqlKI3h4GtE7ewPe2R2w2vDx3Tm9mMYZb2z3CTybq+uPDpX3HItrG3W+fruDnioaFQelRAHtjWMcW3Nltb7I9PyEY0E8F1jgSUGWymJSrZ19+2wW9YPRKR8WZpFDIAvfxevibp+VADt7QgxXt6QU7leE2PUO4fWvQa0l5DUMJT6ptSLRSp19IZyH+6W7tikLM5T9aCmg5fXluZBXv3TL9/4+XL4O118opwxl82xPEHJ7PBaxhCkzDRf47sNsFKXWpfGtfO/1IyKYjmHmGZteRXqQex3ZRK1tyWbGIK0chUErhSmgu/Uiu8vXqNUDTGuZNAqpv/EKFc9lNRkIsfTLfkTXBzcWk9LevbkpTykhpqsbp13tIJ/19qr0hW6eF+X05uuifvq+kNDmMmycl8+htuTzUm/D+csMmutsv77LUt17qOexGbhM44y7nTGb7eAUWTPG8LNv/Cw/+fd+8nim+rX2Nb70o1/ix5//cW7uD/l7r2zTG0fUfJflmodSijDJOBiGjKOUo1HMZjs4PmaU5tw5GFOvOKdIJ0Dg2YRJxu2DERdXatjWo3tPr6w3yArDjb0h97sTVEl5m4HHc+dbrLeCRz52gU8GFsRzgQWeFDhuGYIenzYLzJCVmZOzHrAPglnOpbYeNh7MHLCzuJlKFa48K6rQnXfEDHHhmqgu3UNZcONQfj7owRqiZGZDePs1aLXAKFngD7aFVDbaUKkBE8iscupQIg7jopDFVpWPUUgZ/cYbcO/WfLoSQJKfyHU8ywXN+zM7L/DkwS7bKWDe7qFVKWwbUDZQjmm1Sxf4u77xRlo9Wm257oZ92eBsXRLVMgrLcasKXA/vcI9LG03G15/jYDDF6Ryytf065wZ3qAUe3ngghNB154kTng/drnzG9rbhqRfklA624X4Dnn1JepxnUAouXC0HNRzBlaehVhNz4XAgfwfOXZLHPPcZ+fz5leMIpWFnTJzmrDbONuM0Kg7dcUyc5sdk8Ffv/ip/8u/8SX79/q8DsBKsHM9Udy3523J+uYbvWmQ5hGlGmhXkpsDWFk9vtvBsxc39AeutynHf5nCaMIlTNh9BDOsVh944ZhyltKoPl9Fn0ErxzFaLZsVhpzfFGEO75uE7NpOZcuparLWCD93ctMDHgwXxXGCBJwWuJwvZO69Jb9eDxLB/JOpHc+n9HzspR17u3hWjkOOK63X9nCyWIKpMrSnPs7QqP9NaflYUYoBYOycl9dFAFspRTwilH4hbuNYQpXT7FrzzuiijjiNqaDiRBXk6loUziU8Yi7Tkd/rlolXkQgTGA3HNK0vKjSf7+45ncT/Q86e13L/IFqX2TzLycgNkytGWlCYgkO9ncURKlX29qpxoNBuzyXwAgbKEyC6viRt8OplnX/Y7sqmbjKT0DWKsC0NqjQZfuL7K8NZNJndvkkQ9YqOJw4JmHOMe7OLEcTmTXUtiQr8jG6x6XdIotCXn2T2UUZbV+nwcLchn7YXPwc035bNnO3Dpqfltq5vSbtJefihS7T2vbgUYg+HhmeoVu8IXf/CL/MQP/8RDM9VHYUrNc/jc1WXGcUaS5biWRbPqUvcd4jSnO4oZhSnN4NvYCJ+BYZjw1k6f3d6UOC0wxjC6fYRWisCzj2OWGoHLpy4un1JdF/hkYEE8F1jgScLWZVmgDrYlJsWvzJ3fng9Xn37XaSNnIo7gtZeFeHoVIbjRFL71MhzswoufE8Ln+VLSfv3r8vzVhiym04ncv70sAfFhmcd5/5Yok34AGCmhn7sihqNhSUg3zpcEciTK6WQs+aB5JmRUlyX2oC7nNSMKs/nrWVaO+OMEiXwXVWtWgn2v+y3w5MMUopifFZs1g2XJz9NUSCeUG7byvTflpsQqI7o8Xz5T47Fs4IpCpnPdvVlOtLLkoUcH8m+SUIQhw1e+zmE/JKtusBGGqDRmlFmQKZb6PdxZlmb/SJ7fr8jXbPM4K7fv35cWkgtXT7+OlQ0pufePZINlO1KWtx/uozyJRsXBsy2mcXam4WYUptjuiH/9F77EX3n5rxzPVP/Dn/nD/PTv/ulHzlQvjKEw0Kp6tGsPV18sS5MbQ1HM35NGxaHqOYyis8noKEypV1yq/qNf0yRK+eqNQzrDiOW6z3JN887ekHudMYHv8Ey9xVqzQlEYOqOIr93q4DlrLJ1xjgs8uVgQzwUWeJIQVOHF75c8zIMdIXaWLcrkhatzJfL94M47UvZb2zwx/hIhtoc7UtZ79iX52fqWlA5378LRoRDE5hJ85gelx3PQk4zCJJI+szQpw9wTWF2Xr15pUmotizkpnMj37VUhpFkmiqlXkfskpbPdKknGLGYpCjk2CM2ULuAhAmJKw8msDSGOpFy6wBOGd9sInHGb0kK8kjNyVlU5ZcgppxllablBKcljloPKZdSktmTQQZGXTnYftpakxaPXge5ApiEtrcjmJ0vL5AQH7t+g67fo7Xew188RODYmW6ZytIPtaJLplLGtaY76WFapygc1eXxrlVO9xkpJj3T/6GHiCUJ836dpsBm4bC4F3Nof4drBqd7Jw3Gf/+6t/5z/9e5fZfo+Z6r7rkXFFUJ7FlGcxhm+Y1NxrROPsbmwUuO1e118x8I7UQYPk4wwyXj2XAvnXfo773bGHA4jzpdTiyZRSn+SsNmukmQ5290J7aqHY2vWmhXuH02435ksiOcnDAviucACTxqCmhDBy08JibIcIYODnpgWHE8I2+Mon1EoKku9eZp0gjy+3hKCe/G6kF4oy3orQiqL0u0bTmS6ypvflIW7tQIcwdgXpclbEkfvaDgvf87yR5vteXmfQhRPpeT5vbLXK8+FZPQ6MqEGCfJ+bCjkvLIEIasnQ+QXyueTgXd7Dx64bWY0SyJOv3+qvGaUXE9BXd7z6Viun7wcLGBbZTh8eZ3ZtiiSfmksUkpK615QElhHPmsztFdgdRMzHjJ581sopXAc+fxkFSGWTjjBi8aYrKAIh1iWLZ/dJBEC2TqrJcZ8qBPIlFK8cGGJNCvY6U6lDK0yfu72f8ffvPGf0k86wPufqd6ouGy0A27uDfFd+1QEUpYXDKYJL1xoP2QiemqzQZSk3OlMwBgcW5OkBVornt5qcXmt/sjnzPKCe0djGhXnuJw+jjLSLKcZuDi2pjeOGYYJy3UhmvWKw15/yvN5+10NSws8WVgQzwUWeFLhB6IK7t6DO2+LSjiLk2kuw7VnJNPz3RBNJWpoaeXs24OqTAWKpnPiCbLo97uiWOa55BG2y2MUufSxRaEoSXVZpJkMZNpRa1kW9kFPFvz2Sqly9iFolGMqy3GAWSal+bTsQU3ieT/f+yGLRSHRTUoL0VCl6gWlIWVBPJ94nOzVnZnIgGPX+uy99QJJLmityuSrLJsTzrycIjQrmxvk/34g12LvaJ6s4HpSep8NaXBcIaf1pvQ1ux5FFEKvS9XzUb0DnGiM2z8gty3GW1exwjHW4R4WGc5kJK0ls2lbDxLMopBzbT/gbP82UXFtvv/6Gvu9Kf/9q3+T/+Tlf5d7oxsAXF+6zp/7PX+OH3/+x993BNGzWy3GYcp2d0LNt3FtiyjNmcYZ55erXDsjFsm1LT5zZZVzyzX2+1PCJKfq26w3A1Ya/rsGyGd5QZabU4Yhg8GUD9FKSdTvic+yLqOWikUv9ycKC+K5wAJPMvbuS3+mZQvJtMo4lf6R9Gh+6vNzQngWtCWKZJ4/rHhCObNanzYyRVN445tShi9K9XJG7EoliCQuDRMHMJEyHo4nPZwbF+ah3PUyk3Q2ZWU4kNsqgShMtg1pDlEsKqWyENvyB1xITAFZASfFj5lLf/b/BZ4M6HKKD0auTaXnJfMHMzoLI6VzPVPKq3I9TqeiVno+UKrss7GrWsv+xfOlYlBOJBIT0VCuU5Db/KqEv9ebpzN0ixwnmqLDIfakizMdodOItNoiqVfI3QrGcclbK3Ju0URSG+7fluEHM/JZ5NLb2Vo6c7NojCHNCyytsD7AmMvf2v51fuLv/gS/du/XAFgNVvkzv/PPnHKqv19UfYcvPLXGvc6Y+0cTkiyn6tk8d67N+eXqqVL6SVhasdEK2HifsUe2pfFKcjvrV/UdG600WV6glJJuhRPK5iRK2WgH71q+X+DJw4J4LrDAk4osg7vvyEJ7klzajpgRDnbE4DNTGM9CrS6K4qB/dv/YqC/l9lpTvi8KePMVKemvbMzNDaYQl/rhLpy/IspQmoiSdLQn0TSTkSi0Rwdw6bqQy917UB2XvXe2EAG7jIzSGihVqUZT1NWZQ/nbVTBMcZq7HquoCzwZmL0Xs4SCnHno/xnvU+nOJi9VzbzsEzaliui4kp85y3nVlrReaEuIZFArExWmonQur8/zX6dT+XxV66dJZxRiDQcElQb37SYbUReKgqTWwspSgv1bkKZEXh373BWwlWzaXE+uZZDPAJQ9n8sSieTN+xHzomC7O+VuZ8Q4zNBawtnPL9ceyy3+oFM9cAK++Nu+yJ/84T/5kFP9g6Di2jy91eLaRpO8KLAt/Z5jLz8obEtzYaXKN24f0QwcLK1pVByagUN/GmNpTdVzaFTkb9IkTjHAheXaIlD+E4YF8VxggScVw558LT3CcFBvCskLHyiTn4S2JPuv/2VZDOuteUTNaCAL9YWr80D2/pGQy6W1045apSXgevcOvPWKLOpJGW9UrQpJdT248oyUEuNIzmvnrjjnLS2l+ZmzWCHfT6dlDqIt5zYsyUQ+IyIfEGdOtVmU454oFCd6eI0BZt+Xm4TZdTqLTZrdbzKSSVeznkw9GyhQJiSkqRDUIpOxq61l2STFkbR0JOWX0jLsIKjOHfEz5Jko/srgPfU8aeRwtGfYHHax0hhVFNiTEROvChcu4QX+vCd544K0orRWZbOnlGz+VtZPZfDmRcErd7rc2BtiW5rAs8mLgtfu9dg+mvC5q6usNM42zeyN9/jpX/xp/vLLf/nYqf5HPvtH+Knf9VOPdKp/OxAl9qPPzLy4UmN/ELLdndIKXCrlnPejYcQ4TVjZ8BlHKZM4w1KKp7eabC4t4pQ+aVgQzwUWeFKR5/O55GfBdsT0c6of7gysbEgI9RvfgHs3ZfGrVqG5As+8JLOfZxiXZNQ9I+DZL6ew3HxDguVrdTm/3hH03xZHfBLDW6+K8tlcktzPG68JWXA9iWMaDiUovt6az36v1sUoksRQpEIwThKTBT5hUGeXzN/rMSc3B8WDLRdlJFKWinFopprOMl9dV1zjxsh1NBtHqRCiipZkBb8imyLLkmlC156Xa3Tnjhj5MORpRqQdsuXz0F7lcmHYzc/RHQ8wWmElCTUvxG20qLXLSWNZKp9V25Ee7CKHa88+cuDDdnfKjb0hy3XvlEmnGbjs9UNevXfEjzy7eaq0fNZM9T/4zB/kSz/6pfd0qn8S4Ls2339tVaYWHU04GkVYWvH5p9YIXIsoLUjzgsurNc4t1Vg7EWC/wCcHC+K5wAJPKjx/Hg90ojxHkUuP2uGukMS9e7LI184oraUJvP2qKI+uJ0pQlsh6fu7Sw7EuZ5W4ZwpkrysK6vKaqFGjvihGozIi6eigNBQ5MobQcYBCxgJOy5nt3Y70gYYe1BIhDHEoz+uXSlVeLILfP/F4L9J51vtr5HFaAbocfVqSLlMIgbQ0smyV96WYT69KYtnInCS8/b70INcaojpW62Wupy3mszyDZz4Fz70EN98g39/maBRxz2oxwaLZ22V6v0cj8NjaWsVKtzCDI2hUCZhgV10UWo45HQuR9Xx5/iiSz82scDBLe0B6Ou92RtiWfsgZrpRiteGzPwjpDCM22sGZM9Xfr1P9k4KKa/PixSWubzSI0hytFXXfWZTTv4uwIJ4LLPCkot6UkvfBdhkBU05G2b4tBG7cl5/feF2I5dVnHyaSt96UTND26nxUnzFCGm+/Jarj6okRfkFNFseZito7klnscQxH+0ISrzwtBophT1SlpVU5/vYdQElJsdcRl7pfgfaaENJwMs9aTCIYlyQ4ics52pp5jNKCeH6y8UFNXGaeQGBLf2ZeFJBLmoNVFLKhscrpQ5QGIsV8HOzxD8rjZakML5hNNfJ82YRNx3IsreUaXlrlxk6fV+52qXo2q/GAZtLFdjWDSUyS5TyzdZ5ApdLTnKeikKZlnFNQZdxYodcdUxx1UEGA25uwmu5gHezINW874HhkeUHlbpeNehvtb5H7p1tlbEtjjGESp/zs6z/Lv/X3/q3jmerXl67zpR/9Ev/0c//0J4KMDacJe/0pvUmMpRRrzQrrreCR5qQZfNd+iJQv8N2Bxbu6wAJPKpQSMhmOhcTVmvLv/raUFLcuw6Vr4iYf9UXZ9IM5kZyOxdxTb51WTJWSkX6dPSkvrqzPzUltWYA52BbFptcR1dW2RWUd9qQP0/eEjBYZrJ6T40VlcPtoIOTx6AAuXoWDe/JYpSGdyr/KktDuvJyNneUQjsRYovUDZfaSrBbv0VKwwHcRChG+LYvCKJTSFNqhUBpdbWIZI+pmEp+hrJ4YKDC7jtJU+oltV+4flkkMeSY5t7v3iCZTuocxy81V/PYamb9EUm9THfWwqy36wyFHXoPg0nW4d1uu7yiENMWsrLNnN7l3GJMlCY3JkEOnjf9L/5AkG7C5sYyTp3DvBkzG6KUVqkUdens4g12GF54hbs/d7sYYXu99lT//zf+Ir+79JvDhONU/btw9HPHqvR7jKMV3LIrCcPtwxGqjwmevrND4kMdtLvDJwIJ4LrDAk4xGCz71BSGId24IWaw1pJ9yaW3eP1ZvSel9796cSI4G4rJdO/fwceNIFu1bb4qjd/PCnGA+/WkhrLfekLGWBunRnAznU4Y8DzAS9n7nbXlejEyKUUqUzFFfjjPozo0iupxGMxrKfZSeE4fZhBptcarfT/E+ewUX+ERC6+O4qxygKDDkFI6HNgVFGbcUZwWVZFqGmr+LMj4zJekyDiwKhYjOAuhdTzZSr30NGm2mUUFlt8PacJdJdoXJ5lUmaxepHNxleftt6jmYPZt8rYW1tAI/+gdFyU8iem6De50pVVJqRUp47iIbGLxBj7tOizy1uTLck2t/8wLWeEAzsLnhttjKpjTuvkHXr5JXatwevs1/9vK/y6/u/m3gXWaqZ+VGzH4yl/GjUcQ378qM9YsrteOf54VhtzflG3eO+MGn1x87+H04TZjGGUrJKM/3UkwXeHLxZF6xCyzwSUeWSYn66FBKfbW6RLjUm+//WLUGPP0pUTOjKWxdPNtwVK2LQpnE8z4zOB21ZAqJYersC5nMUlkMt2/B1efEELR9WwhjEguhzDIhg+GU4wV70JUSIxpMBv2JBHtXqhIhU/jQLR3ySktJclqqnknKMWEwpUnkVITSCTJxHK/0/n9tC3zCcBwMro5HrKNBaU2ubXSeoRWo6ZhCGSzflxJ8ljxsRDJFmQs7+yqAMnrJ8+Wz0j+Sa7jRhNVN0kHIZGoROAX17XcwSuP3DzGWTbh8jiKcQJLIs9iOmJI8n2L7NkevvoWbxrjNOoOVcyRBg6V3vkbeaFNTLuODDkkywF1ekfPxKrTTIbVKg/2ixsb0iPH+6/ynh3+D/9+N/y/Fu81U7x6KSts9lF9Se0WC65fWHh2r9h3AdndCnOScW66d+rmlFeutCocneljfDZM45Y37PXbLQHqtFHXf5fJ6jWvrzVNTlRb4ZGBBPBdY4MNGFIqD/GBHvteWLI5+Fa4/JzmYHwR2OTrzUS73BxedoC4qZhRKv9ywL4H0nb1yMosvZfXNC0Ikf+3vAEqI5/52qRgVEjczmYhapG0hrXkqSstshropMxjzQhb0egscGwaj+bmjpEf0oRD3kjDMSqOmDAkvinnv3gKfAKh53uYHgjwup2ScWmO0i9GawqmgzASVZbh5TqEtcktjBQFEWoLbH0JRkk7m2Z6OK+c56yOuNaFzAK1VXFuUt9StYCUhzduvgtJMVy+C1gzDhIqtOX9xWT5Dd96Gz/0Q4dUXeGdYJbAVcVDBWDbe4BCdxiS1Fj6QTsckGtxZTqjr44cTri17fKs/4s9v/8/8t3d+ntBIReF3XfhH+X/9Y3+RT2+8ePol7dwlevVlJsMpiR+gtaI5vIm/vw3XX4CL1z7g7/7DhTGGg35IcMacdwDH0hTGMIpSNs68hyBKc16+2WG3N2W57rFSr5AXhmGY8M3bXbLc8Pz59kfzIhb4yLAgngss8GHCGOm1fDCAHYT4vfWKKILvNeryJGZTgoJq6XIPJa7oQUxGctxZFFJdlBzefKXM1ZxI2Ptx2bGQ6Srbt0VJvXdbCGpQEyf6ZCxEczSQ/s0kBpUI6TTIbSabk88iL/M5p9JfGk7nQe6uK2ro0d4DJ63mIy1NWWqfEegHQ+AXeMJhPoT3SxTuAnG2G6VQWYJVFChTUFgOhaXReS49nrMkhzQ+HSumNeKIL81qx3uyMmQ+iaQ3euuiXKfdAxp+lSUTMhylOK5HbecG463r2PEEa9in0e+z3q5iVZKyunAkpfagSWG75K6NsWymccZgFKOnCaETEVTO6GM0BSk5/5/Dn+enbvw3HCQ9AF5a+z6+9KN/gd//9I8+/JDxkIOvfoX9wZShXUNNhOB5jse5PGPjxuvo5hI0nwwiNvMKPgqPsz/Z6U7Y6005txQcT3SytKJd9bC15tb+kPPLVRpn/Y4XeGKxIJ4LLPBhYtiX8nJ75TTpBOnXPNyVMvbjEM9eR9zq3YNyzGRVFtTuocQVnVQ+p2O5z9bFOXFTSsxCnT0xQmgt5DOoCTlMEjmXNIGDPTExFYUQ5qODspSu5r1khRGiWRSiHvmVEyQ2k7L9oCvnFdREETV+OZKzVH1PlFPFBAJST83npGWR3/nJgmWfnUTwgSZQSV+mRmGMwYozjAajcwrbo/B9Eq9GkWfUw4E425WSNo9kKuNSZ854zQm1XMv9XF+UeNsVR3utIZ+Pd76FFdS5mOQchAVTLLIkxoz6OMMeeZbSqlWp60ymhQVlS0kSU2nZNAOXo1FEdxyx25uSx4YisVD7B+xV6qxqF0dPpG9VKf6nzm/wbw3+N95K9gG47m3w5z7/E/z4s/8kan8bfu3vEto+R9UV+sEStuOg7r5DvHNItrrFimcf/37DNOf2VONGfVY6ex878Uzzgs4wIkwyLK1YqvnUKw5rzQpvbvdpVx/OBE6zAsvS1CtnK6Iz3OuM8V3rzDGigau5dzTiG7eOuLhaO37eBZ58LIjnAgt8mBgPhNAtnaFIghCyXtlb5rjzueuzXsvGkhzjndck1BpgZVMUltFAyGGWC4G1y1iZJJZF9NpzonAen8sIXv5VUXSWVsRIkcYwKcuOK+vzUZK2LQvp4b48znJKwmlkkY6jUlGajTgs5HUGNfl5lM9LmpYl56UtoBxh2F4VAn2MkwR0kdv5icZDQe8lvq33VB5rlKKwXArHQWmH1KtAEqNqDZSrZTNjOWDnotaniVzjWSYK+rF5zcjnpd4Uhb1Sk+u91xHVcnkdmm0CYH08Id6+RxLFeEd7FNU6rfVVGoGDrcrMzv6RJDWAmGdW67x+v0tnlNAKXOrNGmlxibXdt9ibTOgHFWKvylcOv8pPDH6OX4tuAbDqtvgz5/8Z/ui5348btOCVr4Dj0k0Mu/v3SZPXGLc32Vu7TvHWLdbighXHPrW5rLgy8agzNbT6vY91UT8YhHzrXpfuOMYYI4UZz+byWp2NVsDdwzFHo4ilmncc/ZQXBfuDKRvtgNVHTGYCKIwhznJc+2ET0TBMuHs45t7RmDiV41Vcm0urNZ49135sw9IC3xksiOcCC3zYeM9e93JB3t8WV/mwPx8NOB2JWnN0UDpwK7B7F9Y2Yf2cENDuAZy/Ko9JS+PS6ubpme1FDm9+Q0Zcrq5DtVGqsB6MuqJQaS0LdBzNnRyuK+51XZJRTEmmY06TC1NOg0HUTssW8mtKojrLScSURquDUrFV88DvWUySVZ7HQun8ZMKyoFDy/ln2e0/Seq/DKYtcK4rCoEyOUorCCzAGItvDNopaFqNrdSGNxoiSqdJ5lmdB2cJRKulKSWvIdAKNhvRax1E5ZcsXlbDsv6w4FpW1VbLuIaaIyFYvYtkW1slKwux1lq91vVXBd22MiQmTlDQv6DnLjOvnuBx16GQ3+Gd2f5ZfiL4BQKBcvnjuD/In1/9xGktb8pk5OoC1TYZJwTv9PtSXaNjQHnZw4yY3tU2WpBwOpmy2g1M93YHrEHcTJpnhA9gXPxB645iXbx4SpTnrzcpx9ug4ynj9fg+F4qXLy7x6t8v9owmubVEYQ1YUbLQCPn1p+UwlcwatFDXP4XAYnppbP00ybu4NmcQpVc/m3FKV1YbPJM54434fA3zq4vLH8BtY4INiQTwXWODDRLU09CSRLIYPIpwISex1JMbFGJkEZNnSa7lzTwihUkI0lZaezr17QuZmM9TzDF76gUefR+9IFrJqo+x3Q87Hc6FbjvabjIX4zTIPk0hc7dOJRM6kiRDUJJHHW5ac76x8meeiplar8/vZlhDiWdi860tJfjoRknxMOkH67dL5iO4FPpkwRjZIaSwEynbkejBFmdOqAfWYGwsFrouFwQBFbpNaDqFVQVHgUuCuruAMOtJ37AeyARoPxNCmyyELtl2a4Sw5H6VlFGuqJV7s8tOy6dOW3DeO5PqdjiBNyYM60XhMXGgmd++T+HX8aoWWZ1Er4rKNZeV4XvxomlL1HD5zZZlRmBImGbblUSxv8Rff/uv8z3f+B3LKmerXf5yfeuaPsFVZkfzbah1e+bK04lg2h8MhaVawXJe/H2mlStDdJfHbVFyL/jQirnl4J8LVlclRRU7WXvuw391H4m5nxDhKOX/Cta6Uol5xMEhe5+98fpMffnaTvf6E/iTB0orVRoX1VuVMJfNBnF+psdObkJxQPjvDSHJBXQulFM3ARSlFrTQy3TkccWm1vuj7fIKxIJ4LLPBhorkkZbvdu0IwT/ZhjoeyYG2cl5npeTafJpQl0h+5vCoRTOEU1ktFw6sIaTs6EFXTD+RYRTEnlQ9iOpaFv9mWx1WqZXD8Euxuy+2jcprLsFSNbEdc7t0DmFpCHqJQSpYzgjrry5zFIGnkcUki97NKF71lQ6VS9oVSTnhJ5Th56YA/jklalNmfTLxHTuYMs/SDWk2UxiQWMmfZx8Ts8UmnJ9dqHGE7Lrm2sJIptqtQloelwfJcua6isTyPH8hAAsuWz4PjlNdZNnezV4J5GX44kMSJQReWV6SVJQ6PBx/kQZ1OprBiiW9yKdBZSNYZc6Qt8vUlaucvopIQXaqkhRGi3Kp6LNV8pumEn3njP+dn3vgvCDOpDHx+7ffyl/6xf58fuvTZ0y/76EA+72ubZIVhME0ITpDK3Avwoy4mqNKvLlMd7BPXPTxXCJ/KUtTRPll7FX9ri/eCMebbnniUZDm7vfAUucsLQ5hkYniyNcNpTHccc2GlRr3S+kDPs9UOuLxW59b+iKrvELgWe70JSV7g5Jor6/VTeZ4136E3jumO4gXxfIKxIJ4LLPBhQil4+kVR8g735opKEov6d+15UQAHXVE7Zginskg327LwDrrzPE6Qx4RTmRaUZ+BWH006T6K1LOpqNJUF2tKiSk5zWYSVJ+eapGDGMnfdFNIDZ4yU0VXpPD82kMwmw5Ru9JO5odqS/3uVkrhO56aibKZEZZKxqPU8WD47UZ79IKaUD2RkWeBdMXt/3wuzOeqrWzDoc3x9uL5cG2n8mM+n52p/ucGxHAemBdZ0IAYiyxbD3XQscWH1BrRW5NrqHcm1nudQK5V2rUWFnZXG+x0hrGlaqvyJqKXDvqRCrG4xrrQ46k9ZqzehKFCOQ9FYIq0vsz+MeSVx2DiIaSRj7EuKjTij6tsErs1gOuUf7PxN/uqrf5FudAjA88uf5V989if59Mpv43NnEcPZ56swGAVxmpPmBUlW4DqaQOVYtqbVqnKjuMxWVvBUOKSSS1RZhsWuv0T7xe+jWqs+fHwgTDJ2ulPuH41JspxG4HF+ucpGK3goB3MSpWx3J+z1Q/JClNetdpWVE/2YRWEojMGxpbzeGUXs9UOmUUphwHXk52GcMY5SpnGGVopW1X1f/Ze2pfn0pWUaFZe7nTG9SUyY5LQCl8trdZZqD1eVlFLkj3PdLvAdw4J4LrDAh41KVaYNHe3P3eG1hiigjXZpJsoedr3PEFTnJXbvgT+sRSFk7srTDz8uCmVakDHzCUGuDxsXJL8z7MhzF7mcU1ATshCOoYIQ3+lQ8kaX10Adyv0MQKl6ziKTQNQthTzPhauwe7/sD9VigCryudFDKzFQnVSmirKv9Tjkm7mqerKk/zhYEM8PH2f9/s9SqXWpbkZTIXVxLIQ1Duf9kMeK54morJPf244olbYjGyG/DBXPU+k7zjLIR/LzPJN/28uysVpeF/J4XHYfynH8QP5Nywgwyypd7R7cflP+H9RKNb7c+BxsEzsjHLdGEdTJlEJnKVY4YdteopvbZHGElfYZrJ7j9pFhNd/ns1dXeGP0i/wHv/VT7E7FOHS+doX/+0t/ih/Z/MfYH4RcXKnhnzVtp96EWpNk0ONu4tAZRgzDhMCzsbRmLR9RW11haX2VI4Z8K7uGamnWrZQsLxjbPsvntrh27ewy+zBM+NrNDvuDkMC1sS3FTnfC9tGYq+sNPnVp6bjX8mgU8fLNDv1JTMWz0Urx1s6AOwcjnr/Q5tqGdJC6jkXVsxmGCcNpwp3DsfRk+g5KKSZRyl5/wi++ts1GMyApDJaCZuBxdb3BxdUa+jFVV9e2eHqrxeW1OmGc0ai4jML0TNKZ5QVKQcVdTDV6krEgngss8FHAcYXwbVx4+DbXk684FJIKQjBdT8ifUtLvFUdCJj1f/m/bUhZfWpE4pRmyDO68NVeCyj45phP5fuOCLLB794QMO54Q4eaSzEePY/kZpUmj2ZZeUmPmYzdRpTpZuta1LYs5MoWFi9cl5mmQifqEEjWpKERlTWdRSum87852S/JZgJkR3A8YFr8Imf8IcEap/SxyX+TzqVZ+RYxGINeH58q13D2UkHdTyHV+cmNhjGxKtAWWkWtrpprGYXkqulTNy/7kZlsIZ2tZrsdGC3pd2LwId29Iab1al/Mq8jKZIZTn9nxwKzAZiPI56EpvpxeQK00Qd7GDJtOLzxC316gc3kd19nDGhq1alTCHcP0c9jOf5pzj8w9u/TL/6i/9B3yz82UAGs4Sf+ipf4V//Or/iSK3ORiGXFqtc22jcerXNpwmdMcxhTHUautMb3yFo9xhuV4lNwbPVgTJlOk0Zlu1WUVR9Vw+c3WdlaZPGGX4nsWnlmtstoMzeyaNMbx2t8vhMOTcUvVY3WxVIUoy3tkb0Kp6XF6rk2Q537xzxChMOL9cPS7HL9U8BtOEb9w+Yhxlx4psmhUc9KeMowzX0lTLHkuDIcxyLMvi7uGYRsXj4mqNojD0pwkv3+qQ5QXXN9+fDcq1LVzb4qmtFl9++4AoyfBPtCQYY+gMxUG/2nxEqsgCTwQWxHOBBT5uVEsX+r2bQtp0WZZsr0iuZlHAhWuiAHUPhSyOhjKfvb0Mz39uTliNgXe+BbffEjK5tiWLdDiR0mGcQGdXVB1tycJr26VDvgZ33oHAEaJcrUnJMc/Eca+0LNJpDJSK4ox4mHw+zjJL4P5tebxti3o0M3b4npTxT0buFGUJHnjsPsIFHolHhBkB8Hi6z6Peg3d7X/T89pnanOdyLWgt5rSwvFuaiAEtS8r0gqJ8zGzwQPlcWSyn4lekjB7PNjwI6ZyOwarI5+T8FdlMHb8ELRuc9opM1vIDuQ5Hg7KyUE7aqtTkupyOxJyUpvLZUBriCO14YFmkjouVRBSWzXDjCpNpQbd9CRotdnOXjUvnCeNt/ovf+nP80v2fA2Sm+r/2A/86/9xzf4z+UBMmGdWqw/mVGu2ax15vyiTOKEqCNJgmxFmOAqZTC5W2ecka0Ei6BCZl1I8JbY+j1Su8lQRs7fR5arPJ566u0gjcx+rV7E1i9gcRK43KQyV137XxHIs7hyMurNQ4HEQcjWI225WHjuvamm/uDbl/NObSah1LayZxysEw4nAYcmG5hk4UeVleL3Lp86z6LpM4lcKIpVmp+/QnMW/vDdhaqhJ475+CnFsK6G40uLE3xLFTAs8mLwyjMKHmu7xwYQlnEaf0RGNBPBdY4DuBS09JSfBgW5znrisqTZZAWJbM6y1RIidDaLbmCs7dd2Q0Xr0lCujOHVF8DOJUnxk0Ni+KieLidSGxnbLsn5Yudc+X57ZtWZzDUpHqHomKVG/Kgmy7pVGjJAx5JiXzWS/eeCSlyxkBSePSUFTM+0QfiQXp/HbwXpadnMchnx/kPSjm77dlSd+w65fXBqWpqIzoCmch7xUgLOOOTpjOdGlYm/UHO44Y02o1IbN+ILffv10OJShzNGeGuZNotEThH3bls5Imc4NRtS6bt4M9OYegJiS1uSSfvzRBFQUWFsPqCvUsxh0eMXWrHNbWODz/HAmao+iA//WtP8vP3f4Z8nKm+u/e+nH+/R/79/jcxetyHufmJp69/pTffGuf3iRGGdjpTeiMIs4v1Xj2fAvXtriZDXmzskkWbPJCvaCiClSqGOqAiXGphzEbrYDf9vT6scr3OAahSZSR5vnZJX6g6jmMo5TuOOKNnR73DkeEiZSz2zX3OALp9sGIKMup+TbrLWmDWMEnSjL6kwRbK3IjEUgXVmt0BiGFAVtrkqyQjprydBuBy3Z3QmcYcnG1/r6uOgBLaz51aYmlmsfdzphRlGIpxTPnWlxYrtE6I7B+gScLC+K5wALfCdTq8KnPw85t6b8cDsRN3liCBkLe9u5IGXxlAy4/IypSEsvklEEXXvy8PKazJ4t4NJVF1vFEGV3dFBKaJvDC5+D8WBbkWUl+eb3sgSvNH/0jGX8Zh/LzYW9e4i8KUEVpgpgFvpdZnCYX8mlyUU51WRYtCsij79iveAFB+S59ezjVQ3siz1KVvcQz9TEsY8Rm/b25VW5cytxYywGMmD8UFGVvYeFXsFDYtpbrMo7kxP2KXKtJaapLE2guSyVgllubl/Q7z0VdX9uU6UTd2aAGT65by5bN2v7u3PBncvB9uX3Yky4Vk+P7DsM0p9Y9wG2tcVS/yEE45u/v/zX+4eF/S5yLYv8j536M/9un/hQVc4Gtxump40op+pOYr9/qEKcF59pVMfn0pqw3A4Zhwu2DMdc3pQTfqnocFYY7Xp0LKzVs4Hz51RlFtAL3VGn5cTDro3yUOloYw3Ca8htvHnDvaMQgSlFacdCfUq+4XFmvUxjoTxJqno31gJLYqvr4jkWz6nJ1vXkc03s0jHE0JFlB4Nmn9gdaKRRy2weFpTUXV+ucX6mR5QVaqUVo/CcIC+K5wALfKfgVWWS1hndel38vP1UqQwZuvilqJsxNGpUyPuZgW0rsd96WWeyVqqiXFV/MQv2OLKSrW7KI9zoSlt3vwsEuDI6E8Aa1Mog+EZKrKE0epQvYsuflU7scfxmF83PKSzKqSgUrL/vprHJRSRIWquZHg8eNPy34gCX3k6MwtS0kbdaX6TqieueZEE1bw3hcXkezGnuBTK4qhHDGIRSGXFsYk5IriwJF6vqkdkDh+rSiPk6SSDXAskX5L8oNjevJscKJfL31ahnZVZTZs2WfdL0Jn/khUTzfemWeT5vGEjjvlhu4eAquR25ZFF6ArmZYvQ6WUqxZGaMoIkwLbjXW+dnhL/O3b/+/GWdHgDjV/8Rn/gyfXftBepMYS+kzR0NudyeMwpQLK0LMx5GEyzcDH9ex6I0jxlEF37HIC/Adi6NxxLnl6inzTZTkNFfn8UBRmnM4CEmyAsdSLDd8qt7DZsVWzSXwHEZR+kD0UcEkyrh1MCJKMqp+nStrDeK0oO47aK3oTWJuHYxYrnkURYEB2rXTr7EZODQqDofDiGsbTbQWN7tra0ZhSlEYVldPl+5n0VPuI1TY9wOt1GPlgS7wZGFBPBdY4DuBcCKEsbMni+z9m0Ioty04d1kUw/FQMgYnIyGKldLpq8q8w6/+qiieRSGLdGe3DK73xDzRPRSS+cL3wbdeFuevbUsJM42l/208LI0bRekE9qDWFEJR9YQEjwdyDijpicvzclpNSTpn0BZgpNdOW/P7L9zmnwzYTmkMQ4im5wt5M+b0uFRMORmokM2TH8CgM9+QAKdo8YkeUKMtMsvB5IbCq5A1l8i8AI1h4jVx4gnV/hHOdAhGzZ9PKTmf9QvSutHvlMle5eCC2ZjWuzekP/qSLWX3a8/Jz4pC+kZ7h3LNak1aQJIWjA/6GAx2kePVlvCDAG9tAydL+B+KW/zp+/8GNwfvALAZXOaPfeZP8aMX/wAgBqFplPGpy0un8iRBCNZud0rtxPzwkyk/rqUZ5AWTKKVV9fDdKVGaEcxMfCVZG0cpjqXZbElf993OmDfu9xiGpYkPQ9V3uL7REPJ3guRVPYdLqzVev9fD0oqq59AZRex0JxwMQnrjCK00gWdxfqVOu+ZyNIxoVT1aVY/eOMKyFKMoZbUZHIfaz+C7NmvNCve7EzrDmKWah6UVgWdx+3DE5dU6Sw+Q1f4koe67rL3LuEyY54IqOHbYL/DdgQXxXGCBjxtZCm98Qww8M/d4UJcy4KAri+TKhiywrgO5L0rl+nlZjIpC+jX7HVEsXV/MElkmamNaLkjTkSg8SSRZh/WGlMQ3LsDGRSGeo76U2KOpHKfREmI5yxSdkY7xUMjqrD80RxZ625Ly5jFKslkJyvgktRA8PymYkU4QPjMbUJCb02LobOMT1ESNHPUfIJ0PHjeT+3qQ+RUmuYXt59hFipXE5F6FuL6MrtRIux5ZNEFbNiaJMWiUUihTYMWxXNPako2VXxF1s9ESRRMjm7md27C2Idd5a5kkz5nev09xcIQzGeLYDjRXuNe6jL99kyCdkleqTL0W0WjA1Cp4Y/9r/Kne/8SvZfcAWA1W+Ve+/9/ks61/gjASJdMYqHo2z19sc239YYd2XhiGkcQN9ScxrqUpzOwjbNBaHXPywLO5sFzjm3dEcR2GKVluGMcprqV57kKb5brHbm/K1252sC3FVruK1qoslye8cqeLrTVX1k+755/ZapHnhjuHI27uDdnuTUmzHKvsvwzjlF9764DanS7PnW8TeA7DMJHjhpLLGXg255eqp4LtZ6h4Np+9soJnW3RGEcYY6hWXF863MciIy6oSA1B/kmAwfObyyiPbBvLCcK8z5s7hiGGYoJS0IVxerXNuqfpYva0LPNlYEM8FFvi4cXQIh7vzyUYzRdC2pcdz2BUSOBmLm32WaxiWodnTUgH1gzKsHVFObbt0tE/nJqPmkpDKvftwL5HeT9uW0nxrSb48X5RTbUup3xg5Xq8jx8pz6ZMrcjjmmKXDPS+kzA6iUCnmzvlZsPgTg1n597sDH+mrOTGHXNRPT64DpWRz4zrys045GvXd0gm0FvJZa5BW6mRhgvY8TDSlUIq02iarNrHHfSytiZRFnuW4cUpmexSl+c1ybdzCYI26Urq3bTh3qWxNQa63eksU+u070F7hKFHcGVmE7gZVz6UxnJJ5NUxnQlR14OnPYPV2sCcj6pMjbqb7/Nt8hZ+PROEMlMsX134ff/JH/k0a7S3iOKHrw7TaxvJ9Vhr+8ajGk8jygtfuddk+mnA4jFiqeuSmELKX5PRNTCOQzMsZAWsEDltLQiZfu98jTnIC3+bqeoNGxSVKc75++5BhmHBptYYuqw0SzO6RF4ab+yPOr9ROubptS8w4W0sBf+cb91mqekzjjHGUEKU5eVka708SXr3T5fpWg41WFcfSHAxDntlq4js2u70paV4cH9sYQ28S4zkW339tjVbVZTBNMAYqnoWlNTf2BtzryO9AK8VS3ePqWoOtpeDMS6Uwhtfud3lre4DraOq+c9wzejCIePFCxtNbrfdzJT+EvCg4GsWMo/Q41H42dnOBjwcL4rnAAh83eodl/Ev58XO9UgYpI4jSVHo3o1AURoUQvJtvykI762lrLYmqiBLHrqIc+5cJUaw2ROXs7Jc5mqXjOE2FNCytyeNsW3ro+l0huvUGLK2LyjkZz00ds2lEM6dwkSHdg6UKO+MeriuxNrNpTKhyTOZ3eij7dw/phMfn9N92B1yRyYbDC8rNUbuM6xrPFfB3G39a5GX+psY4PtZkijONKSwbK4nwentY4RBnMoZozIHdoGnFuGmITUFuKSIvIM4L1GiIZZXnNMuDnUFpUUBHPYhDxp0jbkYuxsCmmlIb7aJtw2Fjic54n83uDn7YpevW6E56/JX07/Az7hvkorPyL1U+z09Wf5TWXkj83/8Mt7au01xfZb3qohstuPoc+Ge7st/ZG/DW7oBzSwFJmmNbilbFJ0pyJnFKnBXc6UxYqftYGvb7U5Jc+isLY1jeaFItTTm9ccLPffUOjqW5dzTGtS2GYcpqw2erHRybapqBy8EgpD+JWW2czrGcTfNxbI3vWkxiUTLrFZdpnBK4DralidOc4TTFc2KePdcGBc9stVmu+3zjdofd3lSCDLQizQtqFYeXLi0dTzV6sBT/woUlrq7VGYZC8pYb/ruWzDvDiHd2h7Rr3qmopYprM5wmvLXbZ61Z+cDO9f4k5pW7XQ6HEXlRoAx4rsW5pSovXlxa9It+TFgQzwUW+LiR5+WEnhL1piiZo4EQwWFPVKJzFyXXMwphZV3I3p13SqOFC+evivlo1C+VT18MQrYrfZZu6SY2ZcnUrQpb8crYm6N9IYbdQ+FkcSixSMsbkgmqLVFMex0pqdcacv8Z2Tju/QNxt5fELg4lD7QwZTmeUsEdlUR5gQ8LFh8mnT9DtZxNlCqMvPdWVd5D25H7Ow7ExYlJRI86URscH9vRFLZHYTJUkWMsC5VlqDQlrdbp64BOpU077xFbCp0l6DTBy0IyyyUqbKxqFWfYlQ2b9cAS5pU9p3HEsDckdZZYs2LqOzcgzxmdu04YLLOfBOwlMUvjO/y14h/wN9TfI3Ik3eF38RR/IvgDfKp6idHBPmYUEmQhvZ1dvlq0OL8a8Dk7xH396/L6l9dPnUKU5tw+GJHnBeM0Z5rm7PSmOLZmqeajjCLJc66s1vEczU53KjPhbSGE1zYaVFwh1IUxJHnIXn+K1hrftWkFLmluuHs4Ik5zrq3X0VpjW5rCGIpHjIvMcsM4yphEabmXLWgELklWEKUZjqVJFKRZzjhMubk34KnNJuutCq5t8fnraxwOIzqjkCwvqPsu662AeuVhxRdEEd3tTbnbGdOfSBbwWtPnwkrtIWI8w25vQm6KM/M9G4HLvc6Yg0H4WMTTGCntR2mOpRWuo3n5ZofeJGKtEeDY8jd4Gmfc2BtijOGzV1cXvaQfAxbEc4EFPm7U6tJPNzMQWGXJ8N5N6fscDSTgPUmkdNgoy+VxLP2al58RRbESSGD8oCsO3VmG5kyddL2y37Iqj9VKRlmaQn7WPZSvWhNWVqFWlZ7Qzt7ctNRoIYYhV8hk8qi52ycWu3BaRtUwL83q2VhM/d4k5f1iNn7zexSPIp8K0MfE8XF+P7NAeEvaJwozn50+e9/SZF5yN8W7pBaUbRezNpI8hTTCyX1UvUkvqdFMBmTVFv2Lz9PcfpOp5dFPY1ouqEST+wEqQlzwWpNXaoSZwnYcMIpUO1hZgTcjEEnK6LBH31rBDkd0dw6oNFKCpIcyBaNzTxG3VnHGE/ywx8+Of4m/Zf42fTME4AXrIj/J7+a68yzDMGdnMuBcOsGtVjC5y4pKGBQR7+xrPHeJz9ZSyRZdWjuVJzqYxNzcHxIlOVorVuviOO+OQjqjkOWaz1or4LnzLQ4GETpJqbg2b+8NmITZcZ+m51iMw5T9fshaq8JgnFAUhjQrqPoOrq05HIYs132Wah6TOMV3LSqPCGV3HSGmYZwxDFPitMDSOXVfsjwncYoxikkklZH1VoWXLq8cq4C2pdlsB2y2zy6Tn7qSjOGNnT5v3O8DUPMdDIZbB0O2uxNeurzCxZXaQ48bhSm+82ha4lgSXP9e6E9i3tjus98PSfMCrRVhnDKJMl642D4eEQrSv6qVz/2jKZfX4odU2wU+fCyI5wILfNxY3hCzxbAnauewJ2Xu49GDyO2tFSkpHh2I6pjEsuhv34anXhTFcmUTLj8NX/0V6O+IOjpzAE/LQHi/IsplZ78s35ekcNiX49ebQl6vPC1h8/vbsHNPlMvQFfKahPKv6wlpzk9meZ6Bwsxvz/OyD/Ajchl9D5POGR5ZIDQFUKYMFO9HG1WyUXFccYzPRlzarpjODndlKta7tHYek05lyTGyDK00zaoPgzFpmjOyKgyNhZVBbnKcao26iSi0jVIZabWBFY6xwzEqSxm5DbbVEvXaKro3JGIHt15HZyndwx5d4zCqeKR+jW84W9Qsi9+hcxrnL2CCOpX9O/xa71f5s6Of447qAnBRLfEvV/8J/kB+FTdLOELJOEaVElCQWBXsPKTQNu0ipFdpcPtgxDNLSwSzPuigevyyu+OYw0HEWssnKJXLimuzXPMYxylpmgOKW4cjlmo+a60KRWHY6U2PDTpaa57abNCfJuRFgW97jK2MwLWYxDm+ax33WvbGEc3ApTuKubpePxWbdBKtqkeWF9w9GsseNTdEaYZtaXzbIi8sHK2oVhwuLFf59KWVh+KTHhedUcRb2wPqFedUD2yj4nI0injtXo/lmnc8ZnMGz7FI3yXfMyvMe5bDh2HCV2+IsrlS9/Fdmywv+PI7QyZxxvowYL11WnH1XZvDYUR3vCCeHwcWxHOB7z3MAtCt71A/T60O11+A116Gb/6WqJnampfFqzVRNG0bbt2UyUWuJ+rnZCwl6/s3hHQOukIoZzOoZ0HvKFEt8wKuPgObF+Zl9iyHUUeCuRVCbP0A7t4UN3BrSQjqUSH3tx15nllPXZYBeUk6HmQeqgwKt+S5i4yPjHAu8HgwBWgJbodC3kdjHq08z1oztD3/9zhmScmGJwqFUGobiuSsg8z/63nSahGGMOziKGj7FrHdZrqyStVzqNerVCy4bdUZ7/ZxRoe4WUThuFimQGcZoVNhWDgEacjk+kvYRU6wc5P+7oSjTBN5dar1KkuOy97adeKkxuE44nK6y8Uw4+7RL/Kl3v/Il/O7oKBpqvxf9e/kj6bXmOgr2HGfOCsolJE4W62gMOiioNCK1PFRpmDJyhj3hgz2MoK6i8kzkjTHAJ6tGUeJONbP6MK1lOJWd4IxYzbaVXzHxnM0nm1hW4osk17N3iRmEmckpfvclGa+tWaFUZRKQLutyXNDZxTj2hPWmhWeOdd+5GVwrzPCthSBaxMmmXTjWBZhmtEdxQSeRtkOWimitCBwP/jfx93ulCwvzjReLdU87h1N2B+EXH3g9s12wJ3D8SkT0wyzkvnae8xhv9cZczSOOH8iC9W2NBXXJs0LdnoTlmrecal9BqWktWGBjx4L4rnA9w7GI9i/L2Mki1xKzBsXYHVDFtiPE1sX5Vx27sh5WNa8r3L3niiOWSIqpx9I6dwYWfg3zsv5x6GMzhz14Oqz8rpGfVE6i1weMx0JafQroqC+8Hkhsl/5ZSl/Oh6g5FiHO3C0J2rrhWtlIHcZ5TSLcZr1aM7K6LPg+GOcmGz0YZfUF/gAUHOiOdsjGN4jW9XIhsJxwK/KdeL5onhnqcw4t8twebdso0jOmlBVbkIcV3qUux3pE00SLM8nyGIuEkJdkY8rjLbvo5kQJjmF36I1PaI+6mOpgjSoc9ddQhmFcVymYcLw6qeprV+h9+YbdHsj6pUqYWOZUW2JQmu+L9nh9jTiZrzDf3b/b/D3i9cA8JXDH7J+B/9H8yNseBXiYkCYJEzsGuemO+hqlf5UYbSNKgxOMiGstlEUeOGIjXjMZBLi391nWg24y69zb/kKmVOhXfM4HISsNHzGkfRN2pamwDCcJOz2JvQnMRXXwhi4sTc4nhC0Uq9wYzKgWhGFbhpneLZV5lnmuI7FUl3K9O1qxMEwYhylrDR9PnNlmfPLNSqPiChKspxb+2PWmwH+NZtv3DniaBQxCBP5mBpDUUC9YmNpTV4U3NwfstKoHBuH3g960xj/EcRVKYWtFePw4ZL5eivg/FLA3aMJy6XByACTKKU3ibm+0XxXRTLJcu4fTWgG7kO9mjXfYRynhHHGKEpYqs2PM+uLrXwIofYLvDcWxHOB7w30OvDa14SYBTVZjA925OvSU3D9+Y+XfEahuMavPjcv0+lyEsxkBDdel3OtVKXPssjlMZ4/N/lEkfRjVsvva3WZzx5OhCxORnK83qEs/JeuC8ndvSO3WeVMbM+T126QTM9wKoaJWUC81gihzCCZlWtnhPNBAlOSzYVy8JHiZNFcIdFKZ0LrssQ+DyTHPEbJXSHXXaUqLRnRVNRuy4GkD1FJGmyrPIEH+myVkk2L1hSWRawdjGVjTafo3hG6WsWqt2QT9I3fJB6NsIYD1uttDutrdJVck0bbFFFEmtocxppuY53Cb7IynBC/8xbfuvgS3dWXmDpDWoHN807IuZ03aA726GZd/rr5df6mfoVcGbRR/FP+D/DHK7+PNd0kTzNWCJmsb6Bsj3BpA3tfsTwaMMoSHKNIbRelDKl2CMIB2nIJlUNQpKhpzJ5yMTffZC1K6Fz+FDvdCTf2BqgyRH27OyFKc8JyprnvWLRqHjVPJv54rkVvHHP7YMT1jQbtmkd3FJPm8rsU809OmuVc22weE8v1VkCj4tCqevzIs+tstuel/rMwnKYMpzGrzQpLJaG7sTfkrb0eo2mK42iMgqpvc3G1wUrd5U5nzMEw4jOXl9loBaw2/VO9kY9ClOb0RjF3DkfcORyLexxpN2hWXZZqPoUxMh71ATiW5jNXVvBcm53uhF5pSqp6Ns+fb/P0VutdzT9Zbsjy4kwCvlz36QwjwjSTka0n0BlFNAOPtdZ7968u8O1jQTwX+O5HlsLbrwohm4WwgxC4aCrRRc22GHreC9OxlJpdT1TEKBRSm6Wi7LRXhBw+CnEkpe3Oniib56+UU35KzCKU0liIaRwJEXRdUSyXN+R50hRUNu/pHA2gUp/HMlEaQ4IaRFpuH/TEZPT2a6KkWvbcCDQzg8z6Md95HVbWyizOUiozhfBMbZ2Y3f1uTX4LfNg4izLOgqrK7cFpqBPvz/t5m/IMDvZE9VSUc86bct2HkzImy8hG5KwhAUY2JnFrlUkYk23v4CdTMDl5HKHCCXYY4ShDjsJECblbQWPYGO3ScCqYaMoEm06wToQmcXzSWpu8MHSdGpvxiHc6HQ5TD+0GPDW4w1a6B2GHv6R+i7+qf40QaQP4vdkl/mz2/TzlPYXjBXh2Ri+N6NtVWL9IEA2h0WRn/fegX/0tLHp0Uk1U9VkfH1Cb9sSFnxfUwiN8xyJya7h5TsWEFPs3CFfOsW3qjKOM3d6ERtUlScXYUpQGF2NgGqU0fAlpX3cDWlWX3jhhmmRcW29wkyG7vSl7/Sm2VjQqLlqBb1skWY5CJglN4pSnNpqsNd+bLBXGyDWiFUopNtoBjcAhLwrirCin3xpevLhEXhhu7I2YJimdYYSlFDf3h5xfrvHS5eWHJjSdxChM+dqtDgeDkN2+lNujNMe1LHmdk5jtriiSK49QLn1XAumvbTQYheLAb1bdM0eCPgjX1niORZTmDznjm1WX9bbPm9tD+uMY37EpjGEUpgSezYsXl/AXiufHggXxXOC7H72OKIDLp92ngJSxjw7gG79ZltwtWFqV//sn/qAPuuI67+zLomw7cqwkFiI6I2L1Blx5VkrpD2LnLtx8XdTGcCKl9mgqvZob54S83r8px9y6JIu7bUvUUpmDSBKJKjkeyjnUW3LsNJb73r8vZiXbgUoNMBLRVBRCUpdW5VhFAY4tBDZN52TVGOkBHXTLXNBROdXIKxlOqXTNelIXpPNjw3vplGfOZD82FKkT6udjwpQxSV4g1xBIW4cuNymUm5yTE41OKN2ZKeikmik+a8UUZWkiO8COp+g0h/EQbdsUfoApctwsJK430FlKNQ2ZeC59d4nMrpCOJjRURmgrjLYI4wwTjXm6eog1zHDikJVkj79ufYW/nP9djpgA8IK+wB9TP8Y/o1ssNWysZgtW18B2aF2q0Q8VvaigOppyz0u5lThU1l7i4sqA6f37HMYpN1rPcT7scHX/dTAxptGG1WW6hUuj6kM8xRkcMnnjVQ7WX2K9VaE/SeiNYlpVF8+2mZJiKUWUpiitORyF2NoiyQrOLVUBwzTOaQYetq1ZawX4tiYrYLnhgIEwyciN9G/XfIenNpe5stbAOjG2dhKn7PWmbJc9lu2ax7mlKoFrEbg2kyg7jj8yKDzHZqluk6SygdBKcbszxnctNoMqnVHEcsOn5tvcPhzh2JrPXlmRxxvDJM4oCoPvWtiW5lt3jzgYTLm0WuPO4YhpZlhr+OSFnH/Vt2WKk229p0moUXEfaZR6FGxLc3GlxtdvH9GoOMcZpyBB+77j8KmLS2y0K4zCDK3g6c0m51eqOJZFZxhhW4rGGaX6BT48LIjnAt/9CKeygFq2kLnpWL53PFEX97YhjeaRP7t3xQX+3GegtSzE9dWvyuMaLVEc97eFRDba8MynhaQWhZC+N74uJHBta34OnT35ubbk50Uh5zIewf49IZWWLaS0tSLHaa1IWdQPZFHvHEjAu+cJAdRKiGhRyPFnhNEqTUBRKIRxc0PIgeOA78N0WEYuefJasom40ItsThx0OQEpnAix1ta8Z7MQV+6CdH58eNxu2ZwHyOcxETxmhzzW+2aXbvYsmeevWo5ca0ki18KDeZEnSGcOFEWOP+5huz5YNhO/iWUMxrYhSaSDw3OxMRilsJOIpMgpvApqPEDFUyx3mSw3OAq0JSMeHUdzMTygPdyn6ljkseLr41/mLzi/yB3TB+Acy/xf9I/x280LtAKPwJ5gmVRe/uoG1JpUgKeNYXhwSNc0mdSWqbsOy+sbTPJ1JiuXuX80JTcFK4evYiZ13M3zrLTrHE1idNmjmLkVkjij2N9l1HyeSZyRF2IK8hwhWvuD8Fi9bFRERa76Dp1hRJzlWErRHUakeUEYCzncbFeplI7swTRhmuRcWWtwcaVO1bcfIm79SczLNzscjSIqro2l0RsezgABAABJREFUFTf3B9w5HPHMuRZb7Qpv7Q6plCTR0vJnJ84ywiTn4mqN7iRGKQjK59VlP6ZrWwSuxat3u/iOhdbQG8V0xhFFIWX0RsXhfnfCaqNCbxJT8x18z2Ia5RhjmMYZWsU8e66JbVkcDqe0qu+PWD4OLq7UOBiG7HSnNCoOgSemov44oeJafO7aKuvNisQsKcU0znh7t89ePyROc2xLs9Lwub7RfE8j0wIfDAviucB3P2bGmN27om6mZfZgVs4gdz1RQ5fX5/mEnX2Zp/6ZH4Rbb4rqNyvF57ksxs0lOcbRoeRwai1EtbMnyuVKaVoyRkb45blk/oH8xV9aL53lWp4vy2A8huFAiOX6lhDQ3pEs/OFEyGNamj0uXINzl+H1l8W4EU7l/B1HyIEuY2wmI3m9L78Ff/9/lueggEEqJhKthShnJwPhjZDXcFzmNman1bKZ4mXMPAx/YSb6SPDhBMTP1JvH3CxkCeR63mqRZbIxUszsv2ccS8n1VmaH5saiUBpLK4b+Ml4eoXOpDmSOJ5eOUbhZCJZNZgw6TYiCJqGdwPiI6mCfHW+DVh4zra0xSXNagw7Lo3t0/Ba/ag/4a+HPcMO/AcBS4fMvpD/E79E/BMYidw0rDV9mjGdl/3S3A47LNM4YHHToTyK+bm9yd6pokHFrPyXN5bfuuTZ5UXB1vcH62GUS+IyTnDjNiRJxs3cnMe4gYmBPuLPXx7YdxlFCo+LiOpY4pY2ocY6tmSQZaW5oV30urfoMw5jAc7i+1cS2NLs9uLRaP+XIXq77qHHMfj/kmXPth0hnXhR8884RvUnEuRNu7jYe4yjlzft9XrqyzPmlKtvdCb5bKo4K9vshV9ebLNd89vu943ns4yilVnHwHIub+0OOhhGHo5DOMGQa51R9m2e2mtQDh2mc8fXbHSZRykYrYBymVDwJuw+TnCST35ltay6tNehPErrjR2UCf3vwXZvvv7rKrdqIu50xvXGCbSkurNS4ut44NkvJBKiEr9w45GgUsVTzaFU90rxgvx/SG8d837VVNhZ9nx86FsRzge9+tJakv3HQg0YTgiVZPI/2hXg6Lly4Mi/DKy1E9GAX7r4jimdzaX68cCKEsdYUEtvvwPqmqEQgqujM3FNvCmntdeT+J7GyJgv8wa5MJEoiWeiDuhiFhgNRROOozNwso3AuXIHz12DzvBDHXrfsxQvmIypn5dDJSErzWSrnkZ+gMTMzSJ6LsnqSR2SZzLwu8hO9nMwd0jAnmgvC+ZHhQyGdM0OI7Zwwhz0GTr6veamG2xbgzcdgzp9kPuHIdzAoVJJgmRzyDANYSYyTxSR+jdyx0XGIzoXYOpZFqG2ccEKRGuw4JMNQi4ZciyO2nRY3Qo1SI86P7/NNa8xftH+JbwxeAcDD4V/MPse/MrhMo7Dpe0e4QRX8hmi8RY5aWoXlVWgtM+kNuHM0pqcDRuuXuTtxGYYJ947GrNR9LizXsC1NmGTc3B/xvx9M+LFuxGi6S+JUyLKCSZxiaY2dRig0U7eKQgkvR6bEbh+NSbOCZtXFLkviFccmzRK644h21SXPDU9vtvjhZzf45dd2aVe9M8u8rcBltz/laBSV5fk5OsOIzihmrRmc6eYeThMOBxHff32VrW6Ve0djwiTjqY0WSzUfW6tjw01eFPQnGUopNtsBdztj9vtT6hXps8yKgoqryfKCnd6UpzdbtGsy//3+0YSjUXyq60IpSPOCSZyhU8VwmpDnxUc6G913bZ473+bqeoO4jGEKPPuh57y9P5Lf5wmybmmLzXbAXn/Km9t9VhuVU+0MC3z7WBDPBb77oTTH5piZMQbERDMLxzYP/GHRlizY/a4ssO6JIGVTxgVpXaqCiaiQM+KpLSF1M2J3nBv6gItTacnX1Br27otCagysbgqZ3bkrBNcpMzqNKcvuZRl8776U06djaC7L7QfbQiKLcvJMNJ2fa1FmlxZnRB0VJ7IbTfkai3w+MnG2irxXj+D3+BShJw9Kpk7pUgnP83mf7uPCGMlkTWLIrdNjUmcmNm1znNWUZSgMCoObRqg8wckiVJFj5zmpWyF2qlTNGCeNQYNTqZJql3TQR6djHHJCXUGl0fEgJTcJSewxfz74Jf43+5sUFCgUP6B+mJ+s/RifP9zFcabYaUzmKshjqmGX6CAkXV/CQ8H15yme+wzffOUOh0HEylqbYppS3DrCGFiqeoRJLhN0XEuc3YOYfhLwKbdJKwnJw4iJsVHGYGcxWmumdsBOsEauNHGcUfMc4jRHKdm0ubaYa6IkZxhJhNEkSdkdhDQrLk+fa6KALC/wHxGJJOYkcW0/iHGUUhTmoezLGWoVh94kRivF5bU6l9fqFMagleJoFPHWTp+DQUiU5kRxztZywGa7iqUVnWFEK/DITSEjOXPFSsvHYOiOY3qTuJyf7lJxbe4fjbmwXGW3N+FgGNKfyMSlKM2oeg5v7gxQCl68uPxYl19hDL1xzCSSVgnH1jjawrU19YrzrgTWc6xHmqGiJGO7N6FVPbufc6nmcTSK6I3jDxQptcCjsSCeC3z3Y9AVFbJal7L1ZCQLcTiRyJf2ipSUTXF6hroxUoLW9on51AgRdNz5+MhZYPoM0bScGV1mb2aleaffg7XN0+dmECW23oRnPiW5nr1DIZWmkD7POJTFXmv5/96OkLtaQ5zxk2FZAi0zE11fyO+wW4a9Gymjo949w3EWj3TSpfx+1cwF6fzQ8ME7aJWUxfNUrl/fn6cuGGCafwCVutyIFJmQ0BnJVOVUJL/shSvK++UZCkXoVpn6dYIiwSgLPx7hJBMaSYSdZzh5hLElLzOIBvS8Cpl2SCybIxVQRBGvVTZJkyF/zf9NfkP9AinyuXtRvcT/wf6nuKDWuBgfEbsBuQE/y7CShFA7uEVKbTLEtGti+LvyDN1Jxl6sWV5po7WFVhlxlpPmOVXPpzApe4MpSV5wNJCRi2O7ysvZBs+nuyhbYychloKBVSVWFqFT4bZuAgZLKxqBQ3ccE6eSBGGVcWXGGNJMCKKtNCYvOLdcZbVewbGlJzRKszNnlc96LrWCne6EwpgyGknIlzGGSZSSG4Nr6VMEtijMsaN9hhnZWq77/MDT6wwmCRdX6rx694j1dkCjIrPRC1OgNIzGKVXfIc2K8rEKR0sc1FqzQuDZrDZ89gYh1zcaKBT3jka0AlFwq9phc6nKNE7JC8MwfO9S+3Ca8Oq9LgeDkNE04bDsiW1UXM4tV9loBzz1Htmej0KSFaRZQRCc3WfqlhmqSfbhNLssMMeCeC7w3Y+iEGPE1iVRFScjIV+1Ngw6klU4UzFnf5dnJemNC3PTzvK6/MyvSPzSwa5IMStbQvZACOJoCE89L0rkG9+QeeidMkJpPJAFcOaYzxKZMLS8Jl9pCvduCcGsVEsTUiw/N0XpptcywciypYw+6Mv3tbqQi3wW9B1y3Id5/Ls4qzevhEJum6m96VkTaRb4dvGoZezBOKTHJZ4nGiGwZipkPlOrT7yPjRaMxmVLR/nI7BHq54MjNh1vHrdllWeaZRhjKIoCE4cYZWNsG600Wmu0bZM3l9jz12iGXSp5SmYM1UkPbTImQQNd2KgC9GSMU6RYvoe1tEIYtMmOhoyUxf9ifYNfqPyvDNUYgKv5Of5Q+o+y4X8Wy6oQhH2KfMxudRk/VVQcSC0XJ4noG03sN/AuXodPfx4qVaad8XFZOUwyDIasMIynGRUnpygMRyOJEXJtMTS5jsUrxRaqyFmL+9h2jbRQWJZhbPvcrl9g6rdJ8zLuKBRVOEozNIoCw63DFK2gWfXYaPqESU5vmjCJRF21tObCSpVv3D6iUSlOObIBDgYRR6OI/+Urd+iNEwyGdtXjhYtt2oHHvaMxdw7GaEvyMJfqPlvtgIprM45SnjnXemTJWCtFu+bRrLr4nsVb2wOG0zGdUSSRRgpWGxXqFYdbByOMMSil5M9EqcAqpVhrBjKNNxQzFCh6kwTXUrSrHnGa0ap6rDZ8DgYRkzh9ZEzSNM746s1DjkYxgWsxjjIKCgLXZlrmomaZmIY+f331fZNP15ae2yTLz1RF06zAKo1VC3y4WBDPBb774fnlolkImauU/VH1FqShkLe1zXkvXJHLBJ9ZrJJty3jLzr4QTseF9rIQzySRjM3pWPor41AmC1Ub8MqXpSTeXJI56BoZddk9LL+35HHVhpTXUfJcbqlaWo4oTDNDxyxrM5qKQnu4W5bDlRDeNOU4NieNy9vMGc7mR8AwD5LXWloHsgX5/DDxbtpJOVX9mETqx7y/QaF48D0uby1yuaYwMsUqqEqaQVo600eDM6YOzUxCal5WV+XPXF8eW+TluRlMkWMKAyrHpImUYx0Hq92m2W6wWmsx6Ftkwy7VJKGGwbEUjmUoKg1MlhIhPYOpcsisCnma8ovpN/lPnF9hm0MAtooW/2T++/nH00tsJEOO8ruM9RpRkTGOMxKV4FkW91efYlRpEicpMZpznsHBJfADGZnYnXBjt8/NfZmeE6a5GI3ChLQoMMZgjMGxLeIClFYSN2S5vLX0NPemPVbzEWQ5fVwOnCapU8VV4u4Ok4xplBJnBZbWbLUD8sIwmCZUHAtjDOMoI8kLtpaquI7FncMRL1xY4uJqnc4w4n53cuzIznIhwrcPRnTHMTXfpl3zURj604T//eV7VD2LmueSFTntQMrgu90Jk1Am9AS+w/ml2nten1opnt1qsdaoSI7ozoAozXhqo4nvWkxjiVAbJxl1zyHJc1bK3OKiVAd/+3ObeI5Fb5JwbilAa4XWGtfWVD2bVuBhWYqd7oTR9NHEc7s7pjOM2GoH3DyQXNGVegWFIkpzhtOEC8tV+tOEt3f6LD29/r76Rn3XZqsd8NbugKrvPFRuPxpHLNX8DzyvfoFHY0E8F/juR3tFYo96h0I2jRFy51dg7bwsvnnpZJ/1Y7ZX4NlPC8lc25KF987b0vOZ59Iv9+LnIQhEQU1TmbF+/Xkhq6++LET0ZCj91edFNb31ppiNLl6X+3cP4e4NUUP3t8VQlJcl8rzsvZzlKCZloHyRg1OO/bRL4msQUjDrs7QcSDMeO0LHD+S1p5Eoq+kiLunDxOMU7M7M4nwE5gTVnP2YWeC/U8ZvTUNR5yuBtH1k8XwMalHGi2WzqKTixDOUSQ/Y8w1OmSdpUORKorYKNNoYMq0JlYdWHg3LZlkl2K5iurRC1skoUhfLsUkay8RelWQ8xgon6Cwhywy/efhV/nzly3zDuQdAnRp/OPlt/FPxc3y9+jQ7DZ9stMfK5JDVwR1Cp4KThYwi6DaW6VSWSFFMCsN6K2DVSzmcZEx2Bry12+ebd7rcPRySZPIa6p6NVUYIGSME0bM1lqXxbI0xhjBJCVwHbJsDt8l23qCwDQZDmhXYsZTHmxUXp5ytruMUrTSuY+FYmkbgEc+mGE1TLixXeenyMq5tca8z4fpGE9+x+NzVFdo175Qj23ctJnHKatNn+cSoR8+16E8SdvshP/RMA2MU3VFEVra83O1McByLH35u87EJlFKK5brPct3n4kqdX/j6Pe51xmS5IS0KxlHGwSCiXhLjds0nTDKORhGrDZ+LqzXywrDZCqgH7pmh7KbcDL/bX5j7RxMCzybOC/qTmLrvospr0ncsxmHCKExZrnkcDCMG04RW9f2RxCvrDY5GMTvdCe2ah+9I9FJvHOPamme2Hq0SL/DBsSCeC3z3w3FFvXzndXjrFVlgfV/Un6AOX/hd0F6VXkmtxaizsl72xBmJNAqnUgpvLktJO6hLX+YslDvPpfSttSio/Y5EK52EZUmckleRxf7TXxDyqzW8/CsyY73elBD60VCIaBRKiRQlBieFqJ1ORcizUhIEz8xxrMoonLyccJQIm3k3U5BSZW+oK7+TYV9K8un7NKHMjgWP7iNd4D0xe6cspd+1F3NeXj8D2ponEERTUT2rdflqLcv1NRjJ//NUNl/pCeXzhIEob7bLSVlgaYlUysMQKMjRxLaLbXKM5WBMTqZELTW9Dv2iILX6+ChcpWDahTxj6NWJWpv0c01Uq7HkDOlM3ubPul/hF+xbADg4/H7v9/HP51/g6d59vuGtYnsuhdLcC9bpuzU2kh7NdEJcqXHgLjMNVtAokrRgpe5zebVGc9zhq9QZv7UnJXBjcG2L/UEoQnCsaVRccmNQCiquGFKWah5hLLFJlpbeyrQwpHlRzvZWWFqRKTHAjMOULJfybJYbmhWPVs0jL8TRXfMdPEeT5Yq0dHXvdCc0AiGrcSol35kj+9pGgygRR/YvfWsHY3iIWIWJKJCupdnrhfzQM+ustyrHZqOtpYJGxWW5/sFUu5mZaX8Q4buaZuDiWIppJEH1l1brjKKENLO4uFLn2fMtqp5MRGoEkhTgOw9nYY6jlMBzaARnq52Fkd+zbYkSnuUFVf80XVFKST+rY5GO43Ij8f7QqLh837XVMsdzymCSYGnNerPC9c1FjudHhQXxXOC7H9u34f4tKZMHVYlQiiJRJFc24LnPnj3mMk3grVcl/zNL56Sq0YanPzUvzc8W+ZOPyzMhc2fB9aQknyZCPCcjMQq5vhBNrcu56EmZ31nmc05HokTZpUs5DKW3c2ZgGiQn3PdGiLDtQJKdfR4z2KX6OzOfJLEopVqBeXfy8xBOEk5l8VhzwRc4E7mhvLbKHM0z8Eh11NKywTGFkEbLgkpFNiTTsaieIJskpXko/wbIjRjNQmMTBzWU1rgmoxJPwUrEa6QdHJOjlCKxHBK7hhtPqOQRCRbdFGqNhhhbpmPcNMQ2BYdulaOwoKBgak/5j/N/wN+q/IbMVEfxeyq/k98e/aM8M1W8NHgLr8j4THSPMDtk4NTY95cJ/TrT9XXc8QH3Yk0lCamrHOO6rDR8tqoObv+Ae8rnqyOXlhcSxzmH45CjYYStJbEhzgp60wTX1viOzaUVCYhXUKqEBqUhSgrCJCHPDY5jYZVGnzwHy1JorbAtzUarIopfu4rvWAwmCYGXY2tFf5qgtUXgyvzxJCt4c7uPY2mev9DmGb99rLCdnO4zjFIcW2M9UA7Oc3nPHNsiSjMKA83ApVkaZsIkYxKnpFnxgXoVbx0M0VrxhadW6QxjRmGCQvHM+RZFYVhtVvi+q6vUfIdm4B6Xui2tubxW5ys3DphEYkqaIcly+pPkmKSeBa0kbH+vN6VRdYWAZgarvHthDAbp00zSHMeSUv4HQTNw+f5rawzDhCQtFpOLPgYsiOcC392IpnDzTSFhF67Kz7K0jFAyokz2DsVEdBJFAV/5ZXjzG+Jqd1whrvW2EMXXvgaf+YH5yMqTsB15TJqcTT7TRO7jOHKsuzfluLYtRLJVRiNNZewfkzHH4wktS+6X5kJGZhNkZsH30XTuNC4KiYk6FYn0gBJ5PIe9PK9uR8iiep/jFR88pjFCmBa88wPDYCiUjZWlaE5PL3pPCpGX+atFUSrZddnsrG/Kxumd1+eGOFPIJmYWOWYg1xZZeRwnHFK4HrFfZVAAUYSvbVJsQtvDQ0wkqSPEQyPX3cCpYww48RijbexojDKG3HLA9enEU/5H9av89eiXZaa6gt9TXOWL5/8lnnM3OLp1h2rYp6kSMtvGReFlU9pFxIoJyWpbVNc2cL0Gd8wye4Mxn/ZDlqwprtL0uwV3CXjV36KXa6ww4c7hWFq9XQun0FiWRZJm5IWh4jo4tmZzqUpmDHlRsNGqoBTEWY4xMI4yHFvR8GyaNYlHyouEiytVlhsVfNvi05eXeXt3QFoqcIHv0LBcjkYRWkG76pJkBZYlmZa9UYxRhr/99ft0RhFPb7UeCi2vOBJkP4tAOr4OLHGqp3mGa/voB8rCSVbgWBbOByBlYZJx72iC51hUXJtrG64EGmCwLU2eGzqjEN+xzyxxX1ipMY5S3tkd0p/EOLZFWs6Fv7Je55mt1rs+/4XlGjvdCcpAM/A4HE1xHb80b8l89Wbgclj2gTYf4U5/XDQqLiwEzo8FHynx/NKXvsTf+lt/izfeeINKpcIP/dAP8Rf+wl/gmWee+SifdoEF5ugeCrlbPzG+0j6xy9a2RBKdJJ7GwLdehq//upDDoCIL+N596c08f0XUx/3ts4lnsw3tJekHXdk4fZsx8/ikV74ifaNvvypEzw+kT9T1Re30y0B4U0bhWOUf93Hpyi8zArFLZTNLS9NIXoZ5KyF/RSEKmGGeaZqfiNQxZk5ULEvI6skZ3O8XpjSimFmf4KLs/rg4dqiXKqQyOUX5U0shG4r8PRRspeR+nidqp+OWprRkPrJ1957cri1JXFAGKqX5JMso8pxU29h2js5SdJbiJSGeKsPRLRujDIXSRF5A4vigNFaWoJwKuaO5WbvIqpVS6AydpaTaIWyu0TPwPxW/xV/it+gq2Vx9Wp3j/5H+dl5c+W2kP/AHGW+/g3XYZWQ71Mc52rZRlk+cZFRNSstReExIBvtgOQS1NjvNC2TnKiR5yK3DEW/1E+KgSW+a0QigUfHIipFkZToOxhg0BsfW2OXvPcsK7h673hUHo5AwzY5jkVbqLlvt2jHhq3pCwtaaAVXfFrKpYLXhc2t/yDQ1nGtXqfkOtw6GksFpclxH0xlGjKOUasXhXCsgznPuHY4ZhSnfd3WVjfacfD57vsUrd48YhSnNwMWUlrKKa6GVIkoylqouB4OQwhhcW9PwXYbThOcvnJ50NIlT+pMEYwxVz6FVdR8y5eRFwTu7A9643xMlV2tqFYe1ZoXlmicbDFu9a9yQVornz7dZbwbsD6aMoxTPsdhoBqw2fYmYehdstAOurje4sT/EsRW20ux0J1haU3Ft1poVDocRVc/mqc3WRxpIv8CHi4+UeP7SL/0Sf/yP/3E+//nPk2UZf/pP/2l+7Md+jNdee41qtfreB1hggW8XSTzPuDwLni/K4ixAHYRcvvXNcoLRCeIYVKUXbvcurJ6Dgx24+uzpMjvI95eehvFXJUKp0RYCG0fymEEP7r0jBHI0kC/XFbUyDktX/aGQUD+QHrzmMmCEzFLmKBqE4Fn2nDzOT0LI5iws/rhxECmBq1zuM8v+tMr4HLfMJ33feZxq3u9KIc+RLwjnSTyoWp4FpTSZ7ZEFVYztYY/7mCzDVgbLFKfzlh4FQ9lm4ZaRWqYclmDLZsn1yqEIfjnNKpur4kCulEQkeWWqgc7JgjqjS8/hDTs4yiLv7OCYAmUyhsZhqirYFASqQGvNwK1xd/kKeWBRVKA3ScnCkFf7f5f/WP1D7ugeAOdMm3/N/kf4QeszVAILc+15DmKwd7qoxGKNgp7XoBoOwcuxbYsMi5ZOKbTGP7jPzup13PV1vlAP6E1S3hhlvNGxiFJHpiOVaRCWinC0Is8hKwy5MYzijKKQ7E1LF8LP04xLq3XOL1V5e3dAf5SQZDlJXmApzSBK2Wj6eI4mTg013+F+d4ylFRXHZjCJWa553O9aTMYxttY4lpClwSQhUwV5bEjyjJWGz2o9EBPNKKJZjmx8e2/AanM+MefSqiiEX37ngPtHEoyuyg3JJE7xbIv73QndSYKlpYfUGHjufItLq2JMzPKCN3cG3D0cMYklAcO1NeutgBcutKmV5fC8MLx6t8vr93rEJak0heFgELLTnfDUZpNLq3WSLH/PuCGlFCsN/wMFsFta8alLS7SqYrSyteJgGIORvlXX0qw2Kzy1+cFyPBf4zuEjJZ4///M/f+r7/+q/+q9YW1vjq1/9Kr/jd/yOh+4fxzFxPA+VHQ6HH+XpLfBJgTGiXB5sC2mzHXGLr27M8zAfhRkpexSyRJzhJ3ff+9tSxvbOaMiv1YX8hWPwXCF2Z3Ha1Q341PfPnfBZKoQgKns70dLXOeiKKjkZyeOicB5MH47LzERbyOnMNDSLVdKlqjhzJZ8qjRtRTU9OHyoKyAogl+d0fbmfsuS4s+ik2XM8tlJZ3vfk8x+T4AX5nOFxOGNuO+SVGplfBTS2baNMjsnKzcYZU2sehpE4rVEPKJVuv1ImINiwfWfeX5xm89aImeptINcaY3uYLIM8Jw/qTDavErXXafAt7N5huaExNCZdauGA0PYZOhXGVp20tcFS3ScrcrYjeC25wX87+Rm+Yd0BoG18/tnsd/K7g9+D01rH8kGrgm/lNV5/Y5dPdY6oKoWdp4zdJibLqUYT6oGHG/iYUUg6GmIcD3XhCp9/9jxrrQqv3euJslgUJTlTx72Vg0ks0T5KMYlSrHJMZJYbcgtIRaxf1zIqcq83Za8/pVXzOL9SpTOKGEwS+pOILMtZaVaORz8WhUzX8R2L33z7gAvLNa5vNMTxHWeMwoS673BxuUbVt7l1MKLiBjTLcPWZy1spmZjTGUb0J/ExodIK1ho+gWez1w+Z9sPSoCSq5UYrYLnuk+VGZqJbCs+xMQbiNKfq2bx2v8eb232aVZetJRkRGSYZdzsj4jTnC9dX8V2bw0HIjf0RvmdjCtjrT6lXHEDRHcV8LeoQuDZ5YViuVz7SuKFZr+jF1ZpMgkLaB5KswLE1jQcmFyVZzuEwIklzXNtiueGf6apf4DuLj7XHczAYALC0tHTm7V/60pf46Z/+6Y/zlBZ40lEUcPstuPmGEBs/kIlDnT2JPHr+s2eXu2dor8wNPLNIohnyXFTI6y+c/vmgK/cd9kURclwhsDA3YowH0jNqv8tHaHld3PKjgahK27clDimJxfhx5y0huLUWFD0xfbiVeeB3lMn31aooVrN8xVlJfNYykM/ibZjnfRbF6VK6tpnrbUYIc1yallQyvx+z3M9vs2xl2+XYzmzhcJ9BKSxjRHzWGsnZnJfNjbIoHJ/cr5BXaqiiIGIJd9DBMtn7M2qVpeK8vQpphLZslF+Vcno0gYOyr/nSM/DyL0NnnzyNKSyPTGlSpSiSGKfIKWyX1KtSOdrFPrhHPBxyp34J12QEZKLIpjGp7dKrrXE/WOOanvD9yTa/1b3Df5z+Ar+k3wLAMzZ/OPk0/7z5bSy5Vey0Sxwp9vMGX/E3eXUvYRrFnJ+m5HnEIMvJKhmx1yRUDnE8YcvNqfk26cYmLK2x9f0voJsBhTGMwgRba5K0IM1zLEvURt/RhLEhSsXkI+5zTVZIJBKFojAGBdR9iQC6ezSh5jvUfOkdrPsugWsTZxmHg4jpQYrvSpZlmhU4lqbmOyigOwp59lwTz9asN+qstypstCrc705oBR77/RDH0kyijMIY4jTDtjWBZ5cTc4rjYHaAl292ePlWB9+x8B0NxqJVlTGV94+mpYkok9B5Jdmurq3ZH0y5fTDC0oo7ByOW6t4pQ0/FtdlqV9npTtjpTbm63mC7NyEqA9o912K57hOlGRXXouJq9vohv/n2AV+4vsozW82PJW5IK0WlnMTkP6KV825nzJvbfQbTWfawoV5xeWarxaXV2qIU/wThYyOexhi++MUv8iM/8iO8+OKLZ97nJ3/yJ/niF794/P1wOOTChQtn3neB7xF09uDm62KOCE4EIBcF7N+H3/xFIXhZmaO5tiWRRTMFs9aQnswbbwjRrDXktnAqIyVXNuQxJxGGMk1o2JOQ9lpdQt4bpQEoTSSE/kFD0lnQWno+8xxe/7qoT/2O9N71juR40aQUDQv5/4mcRKoBeIEQVMcVN/7MSDQbo5mfIJ0nDUSzXr88e/R8bmNKQvNgIfj9kMUH76vkR7YtfaaLCUiyYam3YTrEmrV1WDZkEgmTKU0e1EkayyhTYLQm96q4SUyuLVxLw3u0dp5EjiFHM84h89riJh8O0dO3QGtUmlMkhnz1PLXP/jD5l/8h2aCHSVO0yXELQxGHFFoRtzaI2mtMsYgyh3v1axzisWamNMM+TjzF9gxNK6c4f5V6sES08xv8P/s/z3+dvUyuDdoo/unoOv9C/MMMg2vcq1Sw3IxGHmFXPL7sXuaeCYiSFMuyuWe1eD4ZMSwsmklEXqkzcWv0tU9iDM+srxOcu0CxssFQe6TDkDQz3NwfcvdwyDBMsDRYBeXMdEXg2STThEksym6cFbiWpuo5FECc5Di2ZhilvLXTJ81zGhWPKM3J84IozXEdBUbMLXlh8BIZ37hS9/Ec6bdMsoK7h2N2+yGrjQqurbm4Wuf7rq7gOzH7gymdUUSUSFTTJE7JCukLrXsO7bqPrTVeWcK+2xnxy6/vEqcZSSbB9jXfIc0LhlGGbZXP2Rmz3gy4uCJtbDIZKeZrtw6puBZRmrN6RjyQpSUndLs74ep6g3GUEicZ0zhjte7TrLgcjSMZx1nOgzfGcHG1znrrPSpOJzCOUg4HIUkuv/eVchLSh4Gd7oSv3exgWaJWW1pU6P404eu3OmituLjy3gH6C3w8+NiI55/4E3+Cb37zm/zKr/zKI+/jeR7eWeXNBb43YYyYIFCnSScImRoP5fZL12U6UL8js84vlMHss/npV5+VMPXtW0IkMdLbee4yXH3udJTS4Z4cZ2YM6nfEVT7rxwyqolg+/YKU0x8XeSbtArv3pF0AVY61nMp5BtW5IWQ0LF3GRUk4cyFvaVr23Ckhm8V75Gwa8+je1ofwIc5Y1zMDU8rZfQjfgzCFZMd6nijqWQq6EHJuSf6qyRLsUQ+NIaqvoPKUNM1Q7Q2C3v1S2X6PDYFS5JaUQSM0RmkS26WfwUBV0FioAhrhEfluhyJ/Gb2yhrV8hVpuEUz62ElKZtlEtk/XqXOw8gxrtoe+e4M8zomXN8hjQ8eqMmzUcPOYMM5YtVLadsrfOfov+cvTnyM00l/9u5OL/Kvh57msN8h8n3B5lZHyuOnZqLxgbTrAcgtqvvRHhmnOLd1g065SLWJMEoqyaHvoNKeYRgxMiyxTvJPWuPf6AXlRkBUFv/XWAfvDEJNnBOGEDTOmQUKoXfZUDW1VUcoc50NGRU6YFFRci1bVxbY10zhlf2goCiPz1jPJ7ZzGGUpBUfz/2fvzGE3yNL8P+/yOON4776y7uvqcmZ2dmeXucpeXtRIpyxRhyaAEmjbMA5BtUKJXtgwJkCHDNmCTFgVQImABNAlYNGRzYVmCeNjGwjRFLo/lLrmzs3P19Ez3dFd115V3vndcv8N/PPFmZnVVdffM9Mz29OYDVHdmvvFGxBsRmfGN5/kegdRqGh/o5wnGKIyWbue7hzOWlYBBozU3tnpUtefNR2PmRc3v+8xV3jucMVnWTJYVCkVq1BkAu3s44629CS9fGbGsHVlt+OrdY8rKsTHMedh2Ya1W2BA5nhU0LlDUMk4/nC5RCta6Gb3cMuyk7E9KjucVH9TwS4ymqqWjnlvDuLWXUkqRJYZr6z0q5/EhMl5UrH0PdkMxRr67N+Gtx1MWZXP2fNzLLC9fHfHy1dEPZF0UYuSdgymRyNbgHFhrrdjoZxxOC+7uT7m+0f1QQdNl/WjqRwI8f/EXf5G//bf/Nv/wH/5Dbty48aPY5GV9Gso7mI3PIy4v1uP7AgQvmmKDcCTvvSldyusvyM+0kYjKa7dkfTHKOvvDJ9fpHLz9hngc7l6TrujOdelCzqYwHwvn8ku/B77wc0/yQj+slgsBnkTY2BULpyRtuZ9K8tiNlU5hp9vyNtv3TsdCFVjxNIGPzMH87Yi8DOF89+L30Kb7tNf0VGgfRiOu4x5cJfnqNkErjfcBrxTlcknqCtLU0u3lmHmGL8tnHk/FCt4rfJLhlMFbhe72CHmPZdCc9LcJSktEYarJR5vMdEYSYD4tmCxStnvXWFMZnXJOg6JBs1Apg8dvY47eJq2WrEXp1mZ6QLG2gzYWSCCp+RuzX+a/fveXOUEy1T8Xr/Fnqn+Of67oM0uHPEj6rPslvWZB0enQuID3keP5krFZ8niZUftIUTnmpPxTe52Zg8+6fW4uxozw1NqySHu8qwbU2TX24pCuBmM0D/bmvHs8x9UNX3T7vFAfYbyn1oaN6NkNcD/b5Lujm0StsS3HE8AopHPYBMrGYYBl47FG000sVRQ7pRCFX9i4gFYw7GVoYFbUzMqa04Xws61OqBvHZCERokYrvvngFKM1w27K529t8LW7RyitWeskpInhdFHx4HhBJzW8dzTnH7z+iDwx7I+X9DoJzgd8CNQNnNYO5wNF7ZguagIRq7WwgIqGZSUG7Z3UkFlNUTki4L1nWjrKWhLNermlnycUtef6hjyAX93o4UN4imyTWUPlPN00of89dCrvH835xnun9DLLjc0equW0zoqGb753QmoNL+wMPnxFz6lZ0XAyq56bWrTWzTialYwX9aUI6RNSP1TgGWPkF3/xF/kbf+Nv8Cu/8ivcuXPnh7m5y/rUlaJtMTz547Idk/f65x6Xq8o7UGQioLhy87zrCdLZzD6gSzk+EnCw3XodPrwnXVUQkJrlwhn9Xb//SUumj1JHj2XfghO18WIi4/fWxJqqELFP3jlPQLJWhD+hOvNXFI9OLep07wS0fuJM2lcimEtu5xNVlecJVzGCOxdgGd+gklwa1N5zde8t4YTmOSaU+KogxqfBgLxbTAsMEbzDGyOXz3xMqCqSdMj6AJZVQLtAz3lUf0DsrdEsZ9xfe5EvD69xdWj4ufv/jLWg8UnOMslZn+6zUY5JyoA2Bqsig3rOLd1wOAmcrl3jN5rf5JcW/wWP/R4At+Ia/1b4Bf6A+QJkkMwfcLU8ZhhKXIB6coLN1pg7Ra4jszKwGBiG/YzoC2wzZ+hLIvB6coXvpLtcNyXbumGwPmKe9tCbO6Sqj59VLI/mHE4LDiYi+rnlTnip3GNse8x0cmbZm9HwQnlInWTc7V0nTyxZm51eu0DlArkx1E4zKRp8DKTBiCmAk46qUtD40KYcGbz3hAjL2klntAWZtfNUzvPN947RRqgSVeP4J9/Z4ydvbzDsZtzeHRJCZF42nCwq5kVDYjQ3N/tkiaQnTZY1h9OSUVc8QxdVQ9NEjBGLI4X4bWqjSYzCGkWvIx3R03nJstR85sYandSwKBW/8faRGF1E4bYmWtPLEwadhOub8oC/OchY7+d8/d4xs7KRaMw8wbnIomro55ZZ4ZgWNcezkvV+9tyOpQ+BuwczEqOe8NlUSkzaax94Z3/Kjc2e8FO/j/Ih4EPEPodraozwd1cPGZf1218/VOD5Z//sn+WXfumX+Ft/628xGAzY25M/TKPRiE7n0qn1sj6krBX+5rtvie/lqqpSFNtpLgCw+76OaLcvHcJy+bSg6IOqrmGV+NPtyxh+MZXtqdYuSJknwexHrb2HbSfTyTqHG3B8IOpjWlCpWz/OqpDPnnVbg3jfKtg5t4ZaRaasQOfZH37F00lDP0QvTWXO/USfECdd/pF/qlYOBE31jNcisS5EhS1yF4Ky1FqjI2jnxIDgw7bhPSbUaAfRWpJywW65JMyPGFvx2rTBE/yS1DXEYs6kidzu3GA8G9BfTnB5jyLrsTXdZ7MaU5qExhi6waFcwVoxxq1d493yG/ylk/8z34r3AFiLHf6n7uf5o9XnKEbXIDHo4PEmoVed0nUFjU7R0eMONaq/Teprvqu6HKkuw2LO5yZ3GRYnmNYVoVGGfTvg7f5N3u50udLpoTT0Sui1o/zJsmJ/XDAvGlTwvFAdM4+WeUzODlgESp0wjjk3qxPu2k0anZNZ4WUSI1XlWURHP7csykinVXVXLpx3ACMoFHmiUSiOZxWJEaW8IraXvsKFQOU8pfN0U4tLDDFEGu95eLJkWjTsDHP6eUrZON47nJNbEZxl1px1BbeGOfcOZiilKJ2jqEQctfIhbXyQ7WvN8bxivZsyW1Y0PhJjxCTCdexkliZEpsuabiZAUyuYlQ3vHs747M11tocdZkXDV+8dYbUiSQyPTpfosSJLNBstwNw7beikhvtHc45nJdc2evzk7c1nqseny4bxonqu8n3UTTmaFkyW3383spNa8tSwrJ2YwL+visqRtyb4l/XJqB/qmfjLf/kvA/ALv/ALT/z8r/21v8af/tN/+oe56cv6tNTVm2JvdHII65vnqvLVGH776tOj+Bg/2LvzeWXbTtQK6Bkjnc9VzSYC+Fael+MTUbdDO+7fehqUNjXce0tU+fOpdE1Da1uze01M6U0is9LeSFTvWUd+Vi5WH+h8f1ZqdRfO+X5aSxc1eAE2F2t1DL4fZfnKbP4D39umI1kr5+R79v/8HVYrxwDFuRhspXQHglLoKCBGRy9+jL4g+oA+e/J49vnwSkRdJjagLHU+QBXztlvuyX1FZXLKpEOiFNo3TG2XQqe8sHzMeH6EIVBrQ96UDKsp3lgqlQh4qiOKjO+YGX+h+ev8cnIPIuTR8sfr38Ufq3+W21VJ1DWNqylCwnY1JteBIuvRrZcQA8dmQFYteM3NeDPb5Z3eDZz3XDt9m51yzIHpsdAyUUij40YzZlDC17KXOZkVdLME5wLzyjFbNiwqEb2EGOnFmq4vmZhu29lrn+kQ5spc52zHGX2/ZFwnpDYQY2RZe0kZTQy9zKKU4sZGj8my5mReoa2mqD15oulmCVXjyFPDeFHjgoyhQ2sWEaOnCWCtJrUGqxUaGd0nVrMoG0II9LKEfi6/yj5GupllUcl434dwNpZf66csy5pUG7qZZVk5TpcViVaUtaeTJe343zFZCpjMUs2wkzEvHe8dL3jtuvwd+5mXtzmclsyKmhhh0Em5tdVHRTiaFry9P2V/vOSlKyO2R13efDRmuqxY1p69ccGwk3Bjs8/LV0cMOyll47l7IFZwP/3S9lOdzxDjWdqSC4HJQo5n4zxZalnvpfgP+xPzIdVJZYT/xoMxvcw+weP0LU/3xSvDj03IdFk/eP3QR+2XdVk/UI024LNfknSfg0eAEnAWvNgoXb3FU6z5+RQ2t2Vs/b3U2qZ4Hc4mst2LFYN0Kl/+nIh8Xv+KCJFWdjjawMY2vPZF4ZeCgLC3vgnvvQ3DkYDQ9S3Z/8VMtjHclM5s0YLMphGzeZR0QGdj2bbS55nbad4q1YWndaYgV6mAQN9wBla7XUCfA+SPXKtW0Yf8DsconMW800Z8ftLG/p+wShKhIah4AT+eH2MdA1EbUAYVPMbXhDbBSLXLST95BUBV+5VCrzrd2uKSDB2dKORDAGNQMaK8p+z3iWlCp5hymq2z7G9QlzUbp49wSUrqG1JfQYw4hDeYGM2RnvMfdr/JX0++I5nqUfGvh8/xL6s/QkivkNkpNjxirVmweXqX02yAbSoK20UbT+JrXNQ47ymVIRrDUb5GPdzi6vKE3WrCAzPAKyOc1Qi1suwnI66WY/r2hMlgh9OFCGW6mcX5SN2cX3O2vWwDioAATsWT0jnXmqtXPpDUDVliha/ZSQlAmlgSY/AxkiUWqxuub/YoalGfl7VnUTaUdWjtTwMaRS+1xNicBYVliZVtRwFAtZcc8EXVsKwdWitG3US63THSeMke1xqMNgy7CZkVYc+37p+SWsNLV0YUleNoXjJb1JIBAQw6CfNSOpP9jj2LthTjfMXrD07YHXbZ6Oes9zJqJ4A7sQajFfeP57yzP+VwUrC71sUa6XB+8YVNTucVdw+mzMuG21sDPnNjnaztbuaJYXfU4eHJgjs7w6eM4nuZpZMmjBc1x/OKo+kSrTTWiLfqe4dztgYZWfKDiX5evjJisqx5dLKkm1nyxFC5wLxs2B11PjSe87J+tHXZe76sT37tXBOQdrwv4MZaEQ7tP3zStDzGlpMZ4drt7038A5Lo8sIrYnt0egTDNRm7VwWMjwWYbl+Db/+WgM6NnfMsdteI9ZMPkuGeZvKeh+8JIA1B9n0+FWBqEwG4W9vCR+0PhF8aW8C4ti6vvftdWC5FJBTb7uJq/L6yXFJKjMCtln+s/kWom/NoxO8pe/0jtiFsIt3ZYvHhUY6/Y+tClzL49jysHpbiBah+psiSRW2KigGXZFAWpIqz9zqTEJUiKoXyARNF7GK0FrDoHMY3rPqkiSsxEVLdYIoxrlQ455kkOxQBlsGwraGIFm8zbs8OwTdkwdEkiv+YL/N/GrzOQsk5/oPuFv9e/fMkG7+b75p11pcnDCeHqKbiyHTo+IpROSFzJbPoGZPxUPXZz9Z4K91G24Se8timRhG5yoKowInU6syOVgcIWuO1ZqueMmWb0LYxx4uapP0db4InBIUjZaYzBqHkxPTODrOKss6+L5npjIXpiBm5D9RO0n5ijAy6Kf08YVE1nLaK9rLxHM1KrNFnSvSNfkq/k/L4dMmibCTL/OqQk2nJ/rRgUTbEEPARApEYIDOaTmZJjWaybJiXDd9875R+x3IyK7HWsDXIqV3g1lb/zG9z2E158cqQg0nBoqrJk4SbGz2atS4Pj+f4KIC7qJyYxre/+8vSszXM+dKdLd54cEq/Xd9KqX6xjFJMlvWZXdKqOqmls2E5npVc3+ihjX7qvVliaHzgdFE9BTzz1HJzq8ff/dpDysaxNcjPuJw+BPYnBWUjpu+DZ4zJP2p1UsvPvLjN/dGc+0cLKudJreZLL2xyY7NPN7uEOp+kujwbl/XjUVkuYHJVN+7AW6+LfdL4+NyvMu/BK59/2pvzo9a123KHeu9t4WC6tsu4c1WM5pdLONoXqyVz4dfHJjL2P3wsr1+7JV6gwbUJQe0+P7wnI3pjpOupFXz+Z8Ea+Ae/DP2+dEW7A7FwGqy13p2c342r6gIojAKwo4fGn+OWFneedUjrRgzjQdaxynD/fmq1HzGIQCbJoHJc8jqfVxeOi7/AyX0mFxdUgGAUUWmCNvh8gA8a5x15rAlao4gEk+CVRuHxMaIjGBQqSWS0HMArDd6hGocloqJDVUuiTkBp+okiM5pSB5ZJRvANUWd4bTDU/N+zt/gPB29woIWX+ruTm/y5zX+Nn747Z5IO+Xo6wI9nDBcHzExOHh2VSqiDYqksO0pRe8V+0ifVnsNsDZ/1GPYyNlRN1XiqOuCriiYq0RJGuTxX1GGFfI4kBiIKo6GqHWUTKZUcTx9BEfEY3ks3+VJxn45KKPQ5mMm8YxQKXk+usVCS6rPqTqJkNL7Ry1iUDf08YXOQ8eh4SVF5YohMqwrnA93UkibmzBu0n1uubvS5sdll2EnpdyxvPp7iXCASJVs8N2z0cxEwpRqjpaP47tGceVmDUjS1Y142bA7ys5x25wOzouFnX96hajxfeeeI3VFOmgjH8mBcsFxWHBS1DD4STT+Vjt/JomZjkLE1kMSj43nFSxeuthAi06LmdF7x6HTJ9iAXbnH7t2WyqDmalSwrx/0j4Zk+L5ddXXjf++vqWhdjFL4SIVVixLi/8YGr613WehnvHsy4tdX/vgVGICD3latrvLg7wrXd5Uv7pE9mXQLPy/rxLJvAa18QDujJoQiDul3pQr7fJulZFXw7urYi9jjcE9DoPaxtyAhfW+lixijWSscHMJ0g86tn/OroNjf9uAWedfXkcsN1ERhNx9L9zDoCaH/+n5fP8PpvSlLRmZBqIuvwTkRJsRU+WSv7frGMFfAZaD0+L0RllsvWxP1CRy1+/7555xzaFjwV8+9/Xb9T6ynQCU8MhLVBxYBCYXyFB1T7oGCiRwVP4h2NNtQ2RxmgdnhrMIA2Fm81uqlbWrQiaENUlspkFHmfTmhY90uumhrylLjUvG03+OL0Hr9s3uY/Wf8N7hqhaNzxff5c+N388Y0/gAopPivgzkss5zm95oiuCkzzAcsq0KvmRDxzemSqIQ2OtWbGfmeLqjMi04ZEK3qu5DRbx0XFgc/YDI7Y4oQVINTtJZsHxyTN8SGQZ1Z4knAmuLrIfL2XbNINNS/WR6yHJQ2GJHoiinfSbd7OdmRogHhygiaEyKJyLKuGTpZwc7tPDBHnIsezikkhnc5uZnlhd9imE5V0UsuwK9ZJR9OSLDFsDjpcKx1HM6EEGKXo5rZ9VoyUTeDqWpdunvDZTMb6N7d6PDpZsqglXvOdvRk7azmL0nF9o8eLOwMqFzicFCwqR57C/aMFtXP0O6lkr0eFqz3HdWCQJww7Cev9jNNFRdl4ZkXNW4/HXNvokyeaewczDiYls7Ims4Zl49gbL1vApnh8upRuuVaUzrN/WrCsHBqw1mAU9PJE1OoRus8R79QusD3MuLXV42hWUTeefmrYGkrcZgiRybKWLjFwMq/wIdJJDTujzgdmwT+rjFYYfRmT+UmuS+B5WT++pbWMv1cenh+lqlIEPY/fE1DXVNJZ1G12ujby2uGejL9vvCi8vKqEb39N/p99gPrSmHOBT959WuyTZKLU30Sy56/dlnG91gJM5zMBiVqLVVRdyvuUaSforbgqS6FRAi6dg1RDksvXwbWRiUh3VPFENCPwHODzPdQqFclddjqfXRegUCv68UpBkhF9g/Ke9x+31XdBJ+jWLN5lHYKP5LEh6kilUjSRNFaEGFpgE9FoggKtNd45nLJ4FUiaBtXGlmrAxobNWBKiIljLUjt6ixN28jUWwzVerx/yV+J/yRv6PgAbIeffjz/Dn0l/itQklAd7NIMNwtWXWfY3iHPHIJTk2pO4BU0Qlq8GEiUUgF6omacD9gZXSTo5VdmwGE841Q2vd3t4AvP+JtEfs9EsGRvp9q3A4SgULFXCIz0UcFg7LjberBGma+NXbgCa17Nr7NkRu25CN9SUOmHfDjkyfVH2G0WWitJcKcUwt2RpQuUDg1bcc/9owdG0xGrQ2lI2DUXjeHd/SpoYjNZsDyWx6GBSsD8uuLLeZbKosFpjtKJxnkXtmZfC/exkhhe2+6z1MmKE0SChbDw7a122Rx0OpyWPjhccTJbsjHK++MImt7YHEpWZwu96cZtv3j/mjQennC5KfIBBx3Bzq8+ibMhsQuM9WSI2SeN5xWRZM11UDDsp33085d2DOf1OwrysWy5nzos7AwbdlKr2/NO39okBBt2U1GrKxrMsHTEE9sZLjqYl28Oc7VGHk3nJW3Xgzu6AndH538XaeYrat5d+xGgBmjujLjHGJ+Iry+AJMfLGgzGHs4KyfR/AWi/jJ25ucHX9oyckXdYnvy6B52X9zqmqhG995dzaKEng3rsy+t69LqPyLJeOpW8EtBGlM5l1RLn+5jeEp7l742lR02obo40WkAEnRxKNOVoXYNkbyPvKpQC37auyXH8oZvVmX7if86n8SzsQxtLh7fXEYqlcynZ2b8ByJtzQJD8HmCYRcpyWRBy0Ot+fj6tibDmdl6DzqWqB5lm1oDMoTYF4YSb4MzbE6ioKOqHIuqTBo1yJDgHlalLXYBRUSY5WiuA9ZZKLgMZmGGvwaU6+OEUFT0BBU2NjICoRrsi1qglKY3xDVF18t4+ez9ld3OW3Ntb5T9Wv8Hr966AhVSn/qv0X+B+7n+anN3qUjee0KPEKvpXe5kFyjdvvvEMsPDvVKRt+Tm0zomvIomPPjniQbXE/3eC1+oAq7dCjoZiO2Yk1pVe80bvK/dij9oFFp8ODtZtc2X+b63HChJQQFYNQ4logeWq6pO2hNVrU4CBsD2uiOIzF83MwSfqM0/7Zclw41lopciuZ7oXzLBpN4WrMEhZFzdF0yfGsRmtFP0/QWp1lqk9czZ3BkJubfXq58CYTozmel7x2bcTpvOaNR6d0U8PUC6jyPqCUJsRInlpCDHQzib00rZm9NYZbW32utpnun7+9wa2tJ+3gtoY5P//KLgfjgjs7Qw4nBaOWl/rwZIFSirUk5WRecjIv2ex36OWGKxt9Pnd9ROkC33084bt7U3ZGOS/sDNnq5/Q7AoCNFgukxgesNeyNl1SNZ62bsj7ImJXujBt7PC9Z72V0UkNsObfrfcW9gxnvHs6lO6phkCdnlIFRN30qM33adjvfbWZsDXK2hyIK9SFyPCv5rbtHpHbn0vz9U1SXwPOyfufU/XcEdO5cldH0+ERG0tduygh9/6F0I2cTGG2KSf3+wxYsttna21fhve+Kwn77Sgvu2pqOpcs5Woev/GN4cFdA4mIGJ/uQ92HniuS+NxXceU34nCCWUNduy9h6uC4AOQYRKSWpjM+dg9DmuhsjI/eqav0/rSy/smaqSkhToQ48yzfyB61Lx4rnVzz7T9uBE+GKB1SMmJUbQatNX5Uxim50NMayzDexTYElYpWGPCeWDbaYo4OnTnN8kuIxzHWHWb7O1byLnY9FWEQgxoD2nqDa7qlJCdYQjSXkfYLNeGDG/EXzZf4f9bcJyGj/D2e/nz+5+yfYtOs8Pl3yGzay2YUwjFTjCYu1XeKVFzhZnPCZh7/OVj0mjSKaKkzGo3SDyiuGruCdfJeHecKDdBPtHeAoh1e5p4c8Ul18HQgxMCtrvsaAtzt3uNGcsuXmaCLvphs8SNY5sMOzpFha/ufq2K0yJi5ekUpBkmhMGwW56oaulnE+cLqoz963jA1rvRTnI4/HJXnSsDHI2Ozn9PKEECJl7ZmVgfVeyrJ2HEwLOkVDvyMA8oXtAZ00YW034/F4QVN7EmNITY1Sik4qIpy7B3M2+il3dgYsKsfuWqcFoAqlFNZoEiM80Pd3BwHGy5qDSUndeJRW3D9a0Elta7VUM13WLGtHNzUYLcbqL2z36WQJnQxevbbG4bTkxmafF7bPge2DoznLyrMz6rCsHIlVJEaz1ktpXEQRubbe43hWEELkdF6RWc3tGxso4N7BlHcPNfcOZwzyhPV+KhGby5rxsmZa1LxydfSEn+asqFlUDSHCRnusz34ftGJn1OHB8Zz7R/NL4PkpqkvgeVm/M6quYO++dBZXvMu6aHmTiYDL6akAuPGx3LmKheSqhyAgs9uXSM7lHN55A959U1Tuow1RndtUwOSX/zF891uiJjdGMrpBQO5774gl0+d/RvipF8nvu9dE1PSNfwb7DwTUKnOuFk/TNmazVcjvPxQwaq1sYzFvozbbFo/35xzRy/rhltbnx121FIjgCcqc2SFFpUmiw8TQpg3JcioGgk4w2qK1Iut1Sdc2Ud5jjvagafDOoduwAaUiUWuatIt1DZkr2FO7TLd2MVHTrRak5Zw6H0Ka0ZsfobynSTr4vEdhc1wa+Uvp1/gr+d+nUEIHeaX3B/gTyb/CHzJdlnaj/ViK/SKwtrnG0aRk3c7IhiOulCdcd0ckKvIw3WDTL+iGmiUpiyRlkWRsuSmv1AdMbrzKO50XuD8uyaxhs5+ybDyq9jTeSfM8RLyPFHbAoR0IjxVw6vzBLrRgU0eIWpTcPkq3MbRUAh8jPogtkWnH3caIhdP7mtBno/zVul2IWCtpQDFGRt2Mfi7iJKMViVE4FxkvasZLiWlUSqE13Nzs8ZnrI8YLocYMO+lZJ/NgUrA3XrJsRGntG8fe6ZKTWcXmMEcrzXQhCUG7azKKni5rvnbviDfuG9b7Kdc3++yMOsyLhq/fO2Ze1mSJ4aXdIafzmoPpkvGiYthNGHUsR/OCXma5sztis+1oFrWjcYFl5citZlY0Z36hy8pxuqgYdFKmyxqfGkbdDAUMOxnHM+GCDruKEORZd5AnNC7y6GSBVop52TDqZlxZf5KX2UktRsPj05KjaYlSYLVk3eep4ep6j8PJkn7+bDgy7KbsjQtq579nvudlfTLrEnhe1u+MqgoBYYO1Cz+80ElIM/G6fPxAOpfDkajBtRZh0dtvCJioK1HO37gjyx08ECD6+Z8RQdE734G3vyUCof4QiNKVXM6ku5m2CR57D6UD2+nBlRsCWl7/TXjz66KKLwv5mdbyV977VtiEgOVVF3MFXGcTqOpWhNQKi8riB+dy/ljWSrXf9riMleNcLp/m3H7QOj4qjWBlBA/t+ZDryqOIMeBNigkBEx0qtDLtGAhIGlXUFqc0aVOjnUaHCbapYXNHrkGliHWJDc1K945xDUm5kI+XZWzYyMPYYaf2YqSgUpoAybIgazyJBp92KLo9fil8lf+o+VWOXAEKfsLv8j/s/DGqrX+NK52IPnkTUy4YR9tmfEeWlSdZTIjdAY1Nubb3Jh1fsxxs8KhJ2PdrbLkZm27OrfKAfTvCRkfT6bC3+yrrWA7mNTFGHk9KIOKcRB0mVqHaY3X2zKSeDzBWmrnEaBItqvzQ0gmq2qFaJXk/T8hTy2QhhuU6no/i/YVTqxV0UoNVirr2GKMoXeDu/oRRN6ObJhgNtfcYI76m1kjCUEDG7/cP51RNZHeUM+gYDqeV5L47x+msavV4kdBySkMMLOuGkRMRkFIyqn48XjIvHdvDnN01cCFw71Asgl69vkbjPKeLiitrHd7am7KsPFmqub01YFk3JMZwY6tLVQ9QKnJ7e8Cycry9NxHj9jbKdrysnzgGZeNpXGA4SLFWQ+NJtGpdYiXHvvGBo1lBjLDey/ExkLQWUHvjgrf2Jvz0na1ngsPNQYey8rx6dUSSGKrG0csSdkYdxouao2nxVGd3VUYpfAxntPXL+vGvS+B5WZ/eWi5EnKPNeeSl97Ca5nR75+IcrWQ8DTLqXnEYRxsCIh/cFc7l1o5YNV25If/cZ+DwkYzYQ4SHd4Un2h+e2w7lHVFAnJ5Id3Ixle5nbyDrvPum2EJNTsQ/1DXS6XR1G4sZ2m7aGYHt/DOGAKFpAefFZX4nAs5VRc4kzyDnsVy0c9oPL9+uQ1iRbZ1FlsanbahWwFPrttPZpkqpFUyMNCbBBIdufTg14LWiwWJ1JIkBHSMERzAGXSxQk7E8YFgLRSGbtymRiDIWazRpU1LbHlk1J33wFk1T4zt9OsUYZTTT/gbHfotNN+GXkwf8H5t/zHfVGBS8EEf82+YP8Qdm11jGEbPyPU53Psubyx16j95hUTkqUmIMHEyOCEnCvdFt1qen2HpJk3ZJzAIbNB7LgV5nnvZZLyecZgMWMeFRssXe0lHUNQBZoum0Y+ejWYkxmrJx+HYU/mGlkV8zqxUuRFSEpfeEIBzPiHTYVuAntZI0NC3OgZY+O8fnBvMgYHTZOEKQrukyeJwvOUbU6t3UnuWh9zuZ/L556GYJ87Lhnf0J949mpIl087YGOYk1Z7nrZSOiP50aEqvZHXWYFY79lqfpQuDx6RKrFbe3tjBakSaGtdbi6ZvvndA4z7yUnHTnA/vjZfucpehmBucjw27Cz7y4w1t7EyaLineP5swKsYjq5wneRx7GJcezkv1JybX17tmxKxtHYsXqyYVI1Xi0lmQo5wMLH0VpnhimhWetJylPpr3sG//ss6iVQmlNN0945eroiddWNIPndTRFxW94eDwnRDmnO6POZQTmj3FdnrnL+vTVci7G6wePWksjI7xLbSQJaJVo1BsIsDw9kmWaRr5XiN9mRLpkD9+FybF0FCNitzQ5EUBjrKxnv+18xijbnJ4KEElzGbnbVH4WnHiAbmyLYCl4uPemdEm1hWqxijo5Nxt/Kvv8fX/cVfwhcy6/h+7fJ6bet78fQVz1fofCiGI1oDWrGFWbyHVysZO8AqIRMeGMUXCvTXFElLI0SoMH5eRcRgyl7eCiIvGFRGQSCVrTmAQdG8x8Ig8e1oJrBAQrD8pgg0Mpjc9yKh/Rp0dY0+Pd/i4Hoxu8kOxxpZkQkw7/ZDDmL8/+33yVBwBsxZz/7eAP8qeu/RF06XiYjXmQ7jJanHL09rf5R+oq68ktbutT8nJOHSLftevct+skTZefPX2bsdIM0gzbNPTSnIghhEiWZAQbCDGBqDnWXY4mlQhqQsSHwNZaT1TeERKjWJYffHVdvPqigkQLBaBsxCdTKzBKzldiFVc3uoxyy/5UPCqXVfPEilbprmc/A4raUTX+DDhFVs8SGqUiy9pR1GIlRGJYFPWZkX3jA5ULaBXp5ylFXVM1geMonztLNFopOqllvKjAK9Z7KTe3+hzNSkbdlF6eUNaabmapGsc37p/QyxJSq1nvZ9zY6FE1ju88HGONdHPXuil1U3C6qClrh4/QTQ3XN/vkmeHKKOfL7xxR1I7tYecsznLpxaIp+Mhbj8d479FaU9aeqvG8tDsCIl9/94TTRcXBtBBBkQukVjHIE4q6IbEivJoWNXli2ehlnCyezSePbTpT8gyfzo2+KOT3x0uurveeiN1cVg33j+YMOimTRS3PchH6nZTP3ljj9gWO6mX9+NQl8LysT1cVC/jmV0TMM1yXCEzvRFleLORucnIoANMY4VkuZjA+khF1VQjASCUthpNDAS3zqSxflwJKy+J8m1kuYLZcynbGJwIyTSLv6Q0kBakuQCciLlqN3MfHYu/kPPhCQI3WbXcuPmdUvvrDHM9H7erCzz7uvPSzsfX3UEkiaUqrffqE19OgU2IXV7dJv/IG1AYSJZ3Ip8B+lNxpbYFACIFFZ0TZ3ySp54TZBK/BttZWyjkyAjqs4jAVWIuzKUkAE1zLHRURiQ+gvUcRCGlKsAlLk2MWE2K0HA63edS9wryBe8kG9/0e/7fqb/J3mrcByVT/Rf+T/Jn099MbvIhdLMkTzdXPvMpxmTM5GdM7PWHY36Rc3+W36k10V7iEtUqYLCs6tUdpzXLZMFN91oIhKeaMTQerNdoFrI90Y8W0s8VBNqIJEVc1hBhpHOyNC/qZwRoRz6y6Zc+ri0dZKzBG430k0aC0REz20oROZuhmhsZFhr2czbUeR5OCo1nJ0WTZ8jjlt8eqgFs9z2npyMV2/Uq1y7WMDZRCRXAxYpREcVbOY5Smdp7Gyxg4ywx5qtE6Q6maynlq7xmSYrWm9p7EGsrK0csT8kSM3q+u9bi+2eMb7x2zKKW7uGzV40UFB5OCu/tTQoi8vTcltYZBx+JC5Hha0oRIokWUFCIcnC75279xj599SVKeaucZL0Sh3zhPlhhubPbIreH+0YJBJ2W9n5GnhsNJSZZoHp0WrPVS+pnl8aSgqh29HBal4+Hpgl6esDXImZfie3prq8fBpOB0Xp/xRi/WrGzoZvaZAiGjFZ+/uUHdBB4cL+jnFtvyTvfGS3wIXFnLGXTSlqYQGS8qvnr3mNSaS6ulH8O6BJ6X9emqR+8J6Ny5fg7KjJEu48mhAIYsE8skpGPBrZfgJ383vPeWdC1V+76rPZidCpisEhmB378rd8kbd87HqtNTWXenK+B2Y1s6q52eAMfpWABrsRSD+80deW+McHwoP29av83VuNYg+3cx5lK377mgmn7ijm1sK/FtP3P0Hw8I/X7WkXVB1/K5PmnkLJucUxh4drp8az5E0BYVgpi3h5ZDm5hW5OWeOD8esUxyNhErpOip0w7T2pN5TdckmNjQRKF+KAI6tKGWShOVIhgrl2XWbd0JCqhLtE0xTd1i3UBEU+d9yrJm4BzzdMB8sE2v3+d0ecxfrf4mv27+EYGAjop/Uf0s/2bvD/PTdY1PO8xmS8ZZl/XhJtujAT/RjXzT9Znv76OqghkZtfN0swwSg17ljBcN95M+n2v2eTjPObGb3KwO2Y5zVCoencliwmn3Kt/p36TQHfqZJUSYNGJP5mPEKMlYb1z4yKSQFfUhhNjaHKWkiaFxnk5q8RHKJqJCxPnI7/vsDu8ezvnq3QOOphqtINVRzOmtIVZefp2CPA9WjYDg1a+WbRk6idY4E6CJJFaTWX32++scpNYI/QFxL7Aa1nsZVWvaPi0ajFGkxmC1PstWdy3tIks1VePZHxcsS0cgklrxCS2aRkRAPtLLDZ6A0ppF2TAuamIQrmtUYnHUhMDJsuJoVnI6K+lklq1Bh16e4EMgRMvprOKb750S2uWH3YSr611+4XNXuXc45x996zF7pwtGvZQ0Nbx8ZcQgF9/Pt/enDDuWO9sj8kyU9GvdlCwxzIuG0U7Kw5Mlm4OMXpbgW3P4onJ87tY6g07yzHO71sv4uVd2eHiy4MHxAhcCG/2MsvEMOwnDbna2rFaKjX7O3umSewdTrqx1nssPvaxPZl0Cz8v69JRrpHvYHTw7p320LulDL362Ha3XAtbWt6RrubkNX/016VjmndZPc94KUwQAoLR4c27sSCdT6xYQIgCyP5QROgoWEwFdMcrYPyKG9GuiGBav0As57Ge2Sc2q1fLk/n8YAIxRAJVaCVj0k2N4pc69Zz5q6fe3oz7i2L2uWqrAhyx7UZjzo6rV2P1D8usVYEIgaE1EEYJHEyCaC8dUlC5hJWRSCuM9KIhpzjBUOGDRBHpKMc/X0E1N4irS6DHt+YkKXN6lHmywTHvkuZJzuT+X1VqNsl2CD3jnMHWBHR/RqA7OJKhuzu7sbf6K/zb/T/cPqJCR5++Jr/G/8r+HrPNZrm7voKoxzdoORMj338N9++tU9wzDbofrLmXSNPS6GbrfYVbUZNZSO4/Wio1+xnhRc5gMmaQDNuYnnGRrPO500KaiX8/IygXfzq/wD/ufZRL7WFZja+nohhjoJwnGaKA5szn6KNXPDPmZbZBjvZ9S1YHCR1yI9POE2gVMonhwvOAb7x4z6CSEqBj1MpZlg9GKZSXqbulqS5VNO2Jvf12sBmsMtQvoRNFJLCG4lgfpEXcBhQe8D6SJKOhX17NSiq1Rl41Bh9myYtDJ2OilmNY7dFY2HE6lu3jvwGC14mhW0IRAlhgSo5iVYo3kQ0QpOJ55hnlKL03YGy+pm0CWaKzR1D7gQ8AaTeM8vSylbDxpYjieF2wMMkLQvP7ghNN5RZ5YlIKq8ZwsSr71YExROX7i9iY7a2MGHenIJlYz7KbkiREOZmJ4fLJkZ73LVtu9DDGyPy7YGnb40gubvHc04/F4yem8QivFoJPy6gub3Nn94ES5Xp7w6rU1Xrk6IkQ4nBYczkrWetkzlx92U47nJYvK0c+fDWgv65NZl8Dzsj495RoBk/lzRi/Gnt9ZnpXlvnNNxvPvfFvA42wiXcymkS6ZSQSE1pUoz/OOgE2l5eeulhH+5AQ6nfb1hYDWrCv+oRtb5x1VpdvcdQQIo9rko7rNXf8eAdkKRK0AKO/jfioNiQW0dNI+SiWp7FdTcQaEnwCiz9rHlar8Akh9AuRpzm75vy3c1FW3+Pmg82xJpVFKctPjannveML5XRmiUeAbsU0yAreavEfTHbCgRxZOKOmwf/U1qAp2j+4yqudYH4heE5SlGmxx2t+il1msm0O9BGWh34EsxyQZxjn85IToNYZIHj0+NfzX9pv8x/bLolQHXtW3+Xeq38fPVdvUeY/p1hWyboY9fcBwdoKpKpJiShENpc6w0dE9nnIjZKyrhmA1szYXPU8My1psj0bdjLVBxre5w/XqLW7pRZstr5mmI7493OG30qsce0uoPZ1UPDPlUgzULrCsHUnQT3lrftiZ9CEw7FqsMYyXNZNlQ9n41iRATNpjjFhj8D7y4GTBy7tDfIgM84Sydu1oPOJDxFxgkFy8UlIDNjFnNk/OB2xrIB98JETV8krj2XNl8JEsE8BYR+GdagX9TsKVtQ6dxLKsG2Zlg9aKk1mFVrA7GqCV4r2jOYeTUmyJiobGBRmNe49CUbR+p1fWcuGdGgT4tpZQViucj+TWUDWe2lVoDaNuSlkH3no0wYdIVXu2Bh0So1lUDZ3EUjmh9Tw4WbIxyIVX2us9Jd5Jrdg3jecVe6cLXMtbaFxgrZfxxRc22R512B51xEu0cmitWOul35MNklJKOLtRQK3Wz1G7ayW6y0tP4R+7ugSel/XpKZu03MLqXEB0sVbdwES8+aQrF8Qfc8XrfOXzcO8t6VCuoiuzXFKCVnGYTRRwmeWwvimpR4/vw6wWg/nRBpwcCOezN5Axf4xw/baM4Jdz8QQ1VpT1wYsIyTUtYLzA1/x+6mwkv0JHF8byzks7xyTScX2ingHUYvszpb8HP9D4bDHPGfh8xudS+jl81idrBRWfUJx/0H78oBU9ykNcpUCddZNDS7VYzWo1AY2OERUcCkU2H2Pqkn7WkCCq7s3lEVXUHA53ue+uoGLgxnyPbTdFLaasGcvAa/Ri0rosBOngWyMPMM4Lfy7LccWSv5u8y/9u+C3e0WMAbvsB/071c/wRf4foAipMWaQpwywQun0WV++w81v/Ddo1LDZvsHSRSRNYNpJ41DGR2yfvMB3tthY6EaMVVeNZVg2JtbgQOC017/Ze5rW0oh9rQFFlHb61sCydgDUFEBWNCyRGkxrNsg6ilFaR1Gq0itQu8BwxtJznFiAm1lLUIuKJEZaVo248sTXor51HK+Ex7qx1SbVmWtSSq76oCCFSu4g1gNKSQKtaEGoU3gvI0UbhW0SaGC0G87XDtN1tUXHLMlpDahTGGAICwtZ7GUTxtUyMYqPfRyuYFNJpNFrxe1/bpfGR2VIM1H0IYgivJF6ych7vA85HOplFHI4UeWKZlg2ZMdQmonWkkxiWZUMMovQ3RhHa7uS8cixLx8OyYb2fYVorqnkpaVg7o1yA8LxiZ9DheFaSJ5ai9s9UjWeJ4cXdIa9cG525lW30M3bXunSz8+WH3ZRhN/2BfvW6mXBgl5V7Yt2rWlQN3Sy5VLf/GNblGbusT0/ZBK7clFjL3vDpcfv0RKyRiPD6V4TnGSP0+nD1lrx3fUv+P5+KaXyaCSj0TgBjXcnyaUd8O6+/INt59215vVjIOtY3oa5bJUMi2e8vvCLL3L8rvFCUjNaNlZG4MSLIiSvg9gOoyVcm5qtRdoznXdWV3c+Tb3j2tlx1bgulDPCs965W0YJH1YpwuAB8V6rws2UuAM0VVeED9uNZ4p/Vz36YltKq3RcdPMYaOXZKg1Z4BdC2nGKQMXxrCi80XOGGDpZjVPAsdEZnfEDSGdBs3SQGRVXXzMsJ625OriM2N5gsF0/Z5Zy2pXNOk/AeVORXOxP+vdFv8GvJMQDrscP/0v0Mf6J4kW5dk7gTjpMBVW+NTr/H6PQhVShpuiNA0WjDfDxpleFwahOO1ZAE2Jjuszw4gN4GZdNQu8CikgeJfmZY72U4L0DvcdplrZviYqSfWSgnhNqdNb3FwSxQ1I66za4MERaVx2pNajUuBHneekatrgStxEezWQaMEs/PopH1Je2I2/tIFUXg5VwgpOKNeTwrKRsnzmMtRzq04+uoIEkUo24OMTIrHSEEGh9QCozWuEa+7mZGrrsYGXVSysZRtcfPOY8Lga1+n6vrPeZFTWJF8LM3XgCw1kuZF46i8fgI1za67Gs4mJT4VqDkfWR3lJCuOqTLhkgkSy2mjd/s5wnTZY1WEeehcZ6mBcF5YnHeUzYiIgox0gTPrKyxWpGnBms8vcyy3s/o5wkhSgqRj4HaB25t9fnqvWOGnQR7QYUeY+RoWnJ1o8cXbovd0w+zhh3hnt7dn5El3ScES7XzLCrHK1dHz1TKX9Ynuy6B52V9vLWci5gmRhlTD9efzbf8YdW1WwIoDx4JpzPrSCdxOpa712BNQGddtuDUyEj96MtiwZR1YHIER3tQDmX8rhXoVEDobAw3XgCUdDaXc7FbOnws4+vXf1OA5GhD9mVtQ5Tro3XpfCapdEjvvyNgtduV5d7+9rk9E0jnVpm2m6Zk3P/EaFidd3hXFAM4Fy2tQKc20pltGgm4jkHA81P1PICrxObJ2HYb6vmdzxjOt3e2yvrCqlYcuGeo5M/w5oeDzme9/jzweXEi/rwyH7KNgEYbDSaFKNxV/wT4bnmaKJzSJK4BIj7JUVoRbYd541Ex0PEVyzohLBf4tEfPVWxaz2L9Cja3ZKuHg9axwDeO2DStoXrku2rC/3r0Bn8zewyIUv2/638P/7r7PdyMgU79SHLFk4RmuEn3xk3mdaBIFJ3JMWGxYOkVxzFn3wzQGXTzlEInHC09iatYd3Oa+ZxTuiglwpfY+prWbeb2ej/hdK6onYC0rB2ljroZi9JJN7MFUq61UYoRcqtJraJqAkkifxda+/jnXoE+yhGp6iAZ7W3XWUaxEJF9MEp4gt3UcjQv2Z8UpFbG7r0saU3SPS6KPMtqRWIMm/2MxkfSxOBDpGzAxwDolrsrSTtFI1xX5yMnvhIeZCbXc9E4jFIYrZkua9Z6KZ/fkkjMtPXsjMDX3z0mTQwPjubc25/SySyp0SitSRPNrPBMy4atxNLPUxofKaqG1Bg2+h3KxnN7e0hZNdLB9QGtxZnUaOHQzouGJNFcWesw6GRkVjNZ1BKilllubPZwPjBe1hxOS3EVaDvI/Tzh9vaAk1nJe8cL+nlyFvU5WdSMuimfu7H+QwedIJ3lz15fp6g9D0+W4qNqNWXtcCFyZ2fACzsfzBu9rE9mXQLPy/p4yjWS2vP4vZb3qAQUbezAyz8B/R+R31qnBz/x0zIuP9yTzpGxAgCv3JCc9RhE9X72no6Ax6/8quSlX70tSvb7dwVYrm/JSDzLBYguF/KeshAAORvLa8VCko+Mlm0fPRY7p1svwxd/4txCKURRwa/snIwVi6bx6bmZvbUCLG0LeJczKMtzE0Jj5TVroEQ6p7oFmyuKgDHSIauW8rrKzgFplkHxYclG7c3FOTm/cdXRaxXzz6oYzzu9ZtX1pAWcoUWCSvbbrSIm9XNFTx/Owny6Pug9ZwD1I472AXSaYfJM9s9o/FI6WAJNIKJRBEnMieItiTZEmxDQFN0hZVFBU9FpZiRuCrpHlTSslcf4JKHYvgm+oqsrOX+dHiUKc3pEiIFHiePPd7/FX8vv4VVER/gfVC/zPzL/EtpeoSFSVjPmJMy6W2wWJ/gkZdlIROKsiGwER1OfoGpHow2TtIPWimXQNK0nponiMeptK9aIkW6mKWoBkY2PlLUjYtEqUjjPZFmzM+pwOq+BKGbptXTsfYyEVmyjlHg5+iidt8xqZpWcrU4qY/jn1YoLarXGe+EWZkZ6zCtQ20kt672MsnYsK0flhPPZsQYXDSGEVugUsErG1qNeyvWNHkfTksaHM5sjFxLy1FBU0tX0MVI3jroOoCFGTdmIKn6tl7I5yOgkCX/oi9fYHnXZGXbYnyx58/GEYSfl3aM5k0XF3YMZVd1Q+0jjAq9dWyMxCqMUW/2cshYD+0XVkCWGjhV/1BAjm4OMiKJsHFEperllzWiqJlA7j/eRRemwiebmVp9BR0bdIUCWWnq5ZNE/OlngfGxz4RXz0tE0gU5q2ernZInhp17cZmOQc/9owbJyGK159dqI29uD54p9fhjVyxN+9qVtHp4suX88o3aB7WGHG1t9rq13n+jIXtaPT10Cz8v6wStGeOt1ePct6SjuXhcgUZdirF7X8IWffTbv8odRvQH8xO8S0Fi1yUWDoXRBZ1PhYV6s5UKAYJrJfveHEoGZpnDYxldevQVbu7K+4wMB0qcHUMzPO6FJIlZJ5VzM5otCuKFpKvu0qvtvyyi/P4IH94QPOlxrwR0CPJQWkdQK6C5mAnYjQBDQGT2szLG1ku9tBmQyul9ZBjUtFKurc7smtTJDf7bhs1R8hgAnPh90gmxvlRB0sTMaOQd6kSdBplqJjX4AagHIuLXtRLYDctT7zHrOuqPvA53mwuvvL7OKIM07UNdEUxB8a4MET2xDEfFoyWiPChUCma9JjZf4yajIY8VmNUZlGaE35FRpOrMxeTMHLaEBripxtWfc7fCfZq/zl/I3WSg5nn+4uML/YfIqt5IbPLp1kzIoXFkyLEsKm7Ovu6zbKWuZxuUi7NgbL3kwdwzwZMq05u2gtGZeOrFdQrHWzHiQrLGn+wxSy+GkoPaRYSehmxq6bZ72yg+y8YF52bAoHY335GcxiBURqBtP2Y6qV2IdHSJZZtFaY3UQC9uPmCoVQ0ArRUBM+rNEUzYR58Tk3U0kDz5ESI10KWe1o68VidY0SsQ6pvW9zK2ln6WEfuRkUXNjo8ekqNkfL+mkYuZeN54meBHyRMTDX0VSpTBErFFcWevQ72S8sDPipSsiaPrGe8c0LvDmwzHzqmY8rzmalixKmQJYo3l0Ip6YTQj0Ogm9bKX4F46jQoznXcsB3Rp2aLwnsxrnDUrBsJuQWEVReSrn2RzkrHcleaisHUrB9qBDnmrGi4rDacNaL6OTGnxLK+h3LKnVnMwrbu8MyBLDq9fWeHF3SOWEFpElvz056XlqeenKkJeuDEVsdGmd9GNfl8Dzsn7wmo6l07m2+aSiPM0F5B08klH0zRd/tPvV7cu/VZWSEf009/NUlOT9kQiCYpD3vfoFGN4Xb9ByKQC0P4DPfFE6qP/4/ydAtCwhyYT7qbSM1YslLKfCKV3M5PPfelnA8L035Zg9uAsHjwXsVpWISNJMgKZuR+mh3RdtIM8EnK7G1KHlgobQKq0jqOZ83G7Mk6HUq7u/TduvV0Kmj6orfs5yz7Ml+kDe5oXv4w8OOsOKU9qO6xWaYDTqIwKaVZ3dWrWV7PAY8c5DUWCqEmLEpT2ic+imJGjQ4SLw1BiEE6p8TegPGVUTqqrBY7FGob1CdbrkHXnQ6U2P8c5B1xL6A3TTUC5m/Gf62/z5/hvsG3k4+NlmnT83+zw/U+9A8GjXMJoe0Ml6LI1h3lvDzxeEpmGRDRhoQ1otMFlXYhfnEzo47nev0KnnDMspY5URg8bGwJZf4LThK707OAzL0hGjKLcXy4okljTTQLQJRdbDGo3zkdiCL2stWgu/Umux0bFa8/B0jnPibxmipA6lVuNDoGzc2XPRRykfpOmvguSYD2wime9EMX13nk6qybSmcRHVUgRijPQ7lvVBxmRRCUj1QiFARbTWdDPhRNaN2C2dzEpq5ymdF8C5utYQjmhZObSKLCvLsJOyPeowWa4e5CRucu90QeUCx7Oak1lBnmicM8yrRiIpncc0YvHU7yRc3ehKhzVE1roZvUxApw8i8mq853RekSWWtV6GNZpOYpgWAv6NBhcRWgDQzy3dLCECw9xyNC3ppglawcm8QgGb/ZzP3RSPzcenC14tR/RaeyJr9Ceqq3gJOj8ddQk8L+sHr8mxdNM2dp5+bcX523vwowee7y9zwX/xYlWlqLyDP7cPAgF8d16T/R+swWd/SgBnkgqYLBZtd1KddxLhHAhOx/DWN6WDWlXy/fhYfjbaPFfSGy0dU0XrLWpkFF6Vop7vDWXcL6oI6EfpqK7EJyupKlHuzLFV7+u267mqVfRmVUDdfsanUomeBwA/ABg+z5ZIqycz05+9kKz7KYX991ZKCx9PgKAjai1WRDytov8gTujZMgrq7gjvA8Y1YqnkHEorVPBEFYnWtt1dAZ4RMfIOKGwM4GrSYo5vKoxK0FmGrioSAr1qDguD15a0mDIl4VT1qSr4lfJ1/je9X+MtOwfgRd/nf7/8Sf7VcIcaxSJLODF9BrrB+oYT0+Fds05MAjfnb7EWSr7bvUE/63LdzRj5KWa6ZEPVfKd3g3/Wf4nrp/d4cfaQkV8y8AEdA1Pb5evDl3izcwMQUUoEdt2UV6oDtsICEzyNthzaPm8mu0yTHnli6WWatV7OsnIs6oZF5agb8ZYsW26mMZqu1YQYOZ7XrYfp93aeV5eTVhofQxtzeW5CH2JkXjo6qWkBsaH2ntp5lqVj1D/PTZ8VDqUKUqMZ9TOujLrMi4ay9iRGk1gxpw/xPNEoRLBKiclDlD5xnhqubfQJMWLbh1oRwigOZxVGQVE1ZKklMUZG9KXYTB1MC9a6wuUcdhJeuTJib1wwXlStq4Bn/3RJ7duHoCDbuLKeMOxkEkUJvHxlyNffO2FaOnZH+VlCUACWRcOV9S7rvZS7Bxm3tgdkiezfqJuyNcxIjCHGyMOTJfOyOQOel3VZP4y6BJ6X9YOXa4HO88ok5+KX385a2xDxULEQLuiqjBGg6IKMti9+FqXPO7fbV+RnTS0m88d7cHoiIHEFvkKQtKP5vFVxKwGpew9EeNTUAiiXCxEggXRL8845NxOkK+mcAEetpZs8Wpex/WBNOKGHe7LfNpG8+dU+LGacseKSVEBdCPL6itt4JhfWF0zi1Tkv9IM6lB9UFw3hnyMWerICT3nptLY155ZQ79sTbSVGshWkKEBlcvxUXV0QWEWiVqiPnJykhMPZKoxrZTBZgut0qWyXpJyRuRodHY6MxC/aMftK+x5RURifEbH8oSrbhwAYVHMcimnWxwTPcLxPAyx1RswS/ll2yl9s/r98OWkz1X3Kf7D8LP9G9TIq66Giw4aaJungtObe9qts+iXL2tPLhEZxkG3QUw30+iz7I94KI17MPYvmMfu9a/y9/GU6oxFf0x2+k+xwuz4hlkuOVId7ySandoBuVfpNjGzUU36qeJcsBk6TLrWypK7hSj2h70p+Q71Akw7opQmzspERexApUtV4nA+tbyZ0MkW/kxBjpJyWhBjppAbj2uP9PE+l95WPsd0GLCp31o3ULU24joE8kXF77bz8zEeOXUUgihl8u6my9uyNlyxqx6ibstnP6ecJ1hr6mWWyKM/Fae3l6ImYqNBKIj8XVcPxvGRZezb6GQ+O5+yMOqz3M+qm3T+tMDGyKJs20164m9Zq+nlK7TzWGE4XErU56CQQIw+Ol0wWNU0I0k32oq4/GBdUzrMz7HD/cM53Ho3xITBbNhxNC3ZHnTOLo2ubPa5v9Lh/NGdjkPHq1SGd7GlgeW6ecNlVvKwfbl0Cz8v6wSvPOcueU88Yy9QlrF9/+uc/6uqPRDx099vnI+yqFMX30T5cuXaeKrQq18hn22y7ubMJfPtrwgn1Xsb0eUfWk6Sy3mU7rldKlptPW/Bh5T1pKttbzGU83+2fK8+9E+HT5k7LAx3K69duwe2X4Sv/BO6+KUC2qcQ1YHtXwOZyLiIo1wJNhQDt6YQzDuVFa6TgzgHnalT9TND5PdyIjKWdt34kg3apZwBPrcBYdF0RnuBjSrTkao/UaptEorFEalQUD0n1zBnu6p3P+IxKtbGXAp5zVzHvblPZHOsqfN5l7jPWFsfY2LQ6KU0gomIgKEWMGr3alwghBnSSyn4DMe1Qrl2lDmCnp3SqGV/twn80+FV+tf4GAJ1o+LfKz/Bvz1/liot4PCUN1tdEpXAoTmyf02TACRkLH3iw/VnQmgddz4vNMV+yc0blqSTklJa9/Cq/6jY4qjXXXCCalEfZJu8l6yyNO8P+KspNIWpwdeDl6oA0BvaTIVorDFDrhEdqxHU35sX6kG8mXQ5mRau9UngVKVpAmBiNNWJ/5L3Y9rRnkTRN6KWGReVpvOSaf5RasScM7fNFezZXn0FH2szz9jOp82eYadGwbPctTzSm5YG6aUVROw6n8jmG3ZTxomZZi0H9yrczttvMjHBEi9JxOq/49e/s8eKVEQfTkqNZxdYwY9hJydOERdlQNR4fIkXtsa3tkQ+SfpQnhjwVvubpvGJWNmz0Uw6mBYfTEm2UKLoT4WiWtccFoTiczMQHVCu4ut5hkFkqHzieVSRW89q1XfLUsj8u2Bx0WO9lzEr3TOA5XdYMOylrvR/Mf/OyLuvD6hJ4XtYPXhs7ApAmp9KZu1hVIX+pdz8BwFMpeOmzMpp+7214+1sC7ryT106PhXd562XpIpZLGY1v7gpn8yv/BN55QzqTt16B174gncuqAj8XLqvS0lFd3US9iEXIO/K1b8B2BZjOJvJa1pGRe5wKaOz1n0wyyrsCcP/Gfy77G9ouaNqR1+tKwOy8zWY3VnLFW0/Js9IX4NoToLC9K1srYPQJUKZan1Fa/8/wXAU6IICz25f2ycUO6zPPx/Nei2evqQsT/qgMdSJm/waF8Q5lNaY/kn1KcyqdklQLjBcV/hnMXHlrGksCwul94jO2NAzvBMhoQxE1j82Arek+Wb3AhIDXhuA9iVZ4pYXWEGPb41Rn5pVNbx3lGky1IGgLacY0JhgF2juiTrlrPP/Z8Lf4pfy7eC9Z3/89vsi/a34/u1mHsjxl2RyRBIehorYJlUp4HDt8S28wO6kZNXNKnfBbJ4HUQi+1HGzc4uF2h0k1572DCcfeEPtrnJ4uRJdmZD+NVsSoxDzdyUG27WVXNZENX7DhFxybrgA1V9GNjVjvqJRSWb5Q3GfbzdFFyqEdctzd4MR0znz2tZZ+sAttClDwxBjJEuEmFk3TmsI/+xL5oPIIUWPVsF9dtcLBlK9ty+QgglHgfGw9PDVBRWECJZZeKrzLujW73+hnnBa1AE4tHFGlBOyGCHUj5u6+BeqNjxilWO9ldDMRc82LhlHXtr6gnoNJQZoYenlCajSzoiEgHdPEmtamKucP/uQ18sTwd7/+iCzRGGPatKfQqtEjVSnWUD5ENnoZxmgUmjwzvLLV42hasT9ZcjKvuLGV8Lmb69zc7DNZ1vzG24dMljXDTnLW3ZyXDYuq4QsvbH5PKUOXdVnfT10Cz8v6wSvvwMufgze+JuCrP2wB2FxA2u1XRBH+SShr4YXXJG8978kIfbAmwO3d70oC0XQsQDnvwsa22BG98VUBovsP5fPeexOu3oBbL8l7EitdyLJYeexIh3MFCtNcQMq0lrviaB2Oj6RTGaKA4bwr6vemFjESWoDmvbfk+xBhMAAUTMYC2qplC3gR9wA/ke6ld/L+upY7ru20yUXNBV5nC0pj2x31kkF9JmoKrYdoksgHqkrOwGxqZd1PVZTO69m3HyDueX+c5ypNKQZBFSEA8VxxrjWJtURtMb4GHzEhnMWWWteQ2AQXcqK1VL0N8tkR2jWUnSFN3mMQKuHTXqwV6tGm3WWx/FGu4cbJu2IDZFN88Oi6QvmGYC0KfcaxQ1mCTbHREZVGB4dPUpySDm1lexQ+YuqSR7Mpf7XzTX6p/xWKVqn+0/Gz/EH1R/mX5jVaee7qBKUHLLoJNjjGpkOlLD1fcS/fZqZzjFZ0fM13zSbzqsE2CqMy+lnKUaN4FHp8u2rIrKbrAtYYGufEu9EoytrR76QieAnS8XIx4lfG7Hhs62Bwpz5iw83JWt2/aT1JlYpMTZeyjrzcPOJ2c8xXs6sUdl1yELx01Fc8ydQomjbeclY0rTWTdBTfTzdeeR1crNb6Ex/bZxtAB57qX6+qTXXEGsleB+FKxhhIjRHfAx/wQTw480RRNp7psqaTGOrE0PiIc+GMyq3jucAIYK2bYjW8vTfmeFby2vV1rqx12BsvKWrP4aSgm1mMEg/QqgmEAINuilGKLNF0s4T98ZJ+Zng8Ljmdl4yXknUeQ2BZNaRWSxc9CI1jXjRorfExkmpF4wOb3ZzMWq5tSPpRr5PwL3z++plAaNBJqBrPm4/GPDheiENAjOSp4bM31nlpd/ScI3lZl/Xx1SXwvKyPp67cFHD16F0ZL4coY+Brt8Q/U/8InqLLpYywT4/k+7VN4WW+P7v95EA6mS+8Iu85OZCuZZLKOLtYymu71+HN12V0vntNAGa3L6Dx9Aje/OZ5ROZ0fG4XFbxsM0lFtR6DgB3TGsIvZq3PppY88ystr/TkWNa1sSPHce9dAbLVUo5ft9dyBo10NKu65YWuxucI0F11LxNzniuepvKvWEpX0irhlrpGqBCrHPvQdk2VOgeodXmBbxnlri9oq/UV9e8DmM8YY2v1pKXSE8u1d3SJAKI1SuQJQZOWzo9pKohVK6pqj+cqdz7k2I6FJCGUDXY5RcxzIHUFaTIg0R1YTHnCi3RFS1CRoDQRj4oOvEWHiuPuBok1dH1BqBuxHnIN8UI3OWiNtoaAdE6brEs93GZe1qTjQ0xVELThl7Lv8Be73+BYyz6/7K/yP2n+eX53vEmfgqxZMGjmVMqyVCn3BtfpWcWwWTAJCUZp5qaLAtbrGWWac5yvkVuNVopZ2XD3cMrLV0e8ezCjrD3rvYxBnjDqpOyNl8zKBtWq1YlipN4E8XFsnKdoOcCVsngUr1T7rIeCmcqZq5wkOu64Y4ah4Nj0OTY9Sp1yDGw1C15tHnLaz5knPUIIdFLT5oGv+IOK0kVwDqtEOe1bMLUqHQNrvkATqXXCwmbEIF6dWkHZeFkHPNEVf3+trirngejFbL29trLEoJUowBd1PDNX8N5zuqi4tdXnxlaf+0dzpkUNQQy6PPFsjK+B00UNEVKrmZWe00XNoGPxIXJ1vccLOwNOFjW9XHiw87IhsYoQLaNuxu3tAXuTgsoHjNEYBUfTkvGyRrUHxblw1o2VSzbgAhgkFaqTWpRSOB/YHxdkicEoRVX7JzibSilevjpid63L4bSgakRItTXMGXXTS37nZf1I6hJ4XtbHVxvbbYewBSpp9qNLLTo5hO98Tcb9tuUoPbwn/pif+ZLs16qO9gSw7D8QT06QLt9ydh6JGILYJD1+TyyRTo/OaQPHB9KJnE/ls/YGAg67A1jfln3Y2ZWuavBtzCEQWv6jd7JMmgngG4yk27d7U7rE3/66CJRUa1MUlURpzmfn4E8budm6puWWtiP9FdfWNU8mG8UooFkp4ZZ2egKUi4Usp7WM/kE+uzWiCl8p45+YvuvzzHX3YWp0dW5s/8yoTXU+3z2L8vQCaCNC6Esy6SiHIPtUtyKsJJNj2VSybPBoV2OMxRDFaF0DNkUbg5oc44JHBQcqYliN+gW5+BDR+Bb+KrQKVDqlwKCrCtMsUdHh0ZiVnEi3lk3Bo+pS1PRoXJJRd/scFAs2leFX0nf58/lv8raZAnDLD/mT5X+LK+r3sh0KygS0Tlikmth2ehc6oesqZsOrpEvPrdkBx6pDx1fkfsHU5DzefBGnhviiIWogRk7mFXf3pixrEalYoziYFEyWFXUjQkD5fBJ7Oa5lZLsCLqtzPdEdnDLcbMa8l2wQWqDdCw0mBgoSNIEsesrVr5bpcaM5ZbuacKo6GANV41sTeajceW4AiLWS1RqtxDKIGLnpTrlTHbEelugYKbXlsV3jXm8XZRK00mRA7R0xPhdzApAaKNvLtwmQaqE0rEQ0Lka8F2P7VUUUtYvcP17QTQUIaoT3Ck+yTFYq+xihdoE08fTzDsvKMS0aNgc5P/3SNu/sTXlwIgC7cR7nxcJp1Es5mlWczipG3ZTtYUdU+kFG900INC6cbcf5eP4M1+5L3QgP1QXpIivl8CGwKBtubPaemTI06CQiYLqsy/ptqEvgeVkff60iE39UVRYCOuez1rz+wgj5+AC+/VX4qd97rmRvagFZ07GAPnvhD7B3kj703W8JKHxwD/r99s5ViZI8y2Vdg9G5ldJ8KuKgKzfkbnB0BMWsXemKpBjbWZ2R/9el8DmTTERN2spYfXwsYKzTle4crSI9XIyqbLuSMch6VkpwANo7U7GA+gL4nJwImO32BXSG1sdTKemUrsRRGgHCSsn7vH+f7VLgubf7M4X8quIHi4xWEZqKJ4Gpb8Gvbju1IYoRvrmgFHG1xFgmQPAiDKoqIhVeWxqdkDZOrI8aT6kTCIpucCh0S/qLGOLZR4tAQDPXudA1iWw0M2KITFROzzpUNPjgJKVIGyaddQqV0FWefjUFFMY3lGXJ1/w9/vLo7/EVsw/Aesj5U/XP8wfi7+OBGdFr5mgCD+w6vr9GXTVk6Yxr9Sl5U3KlGVMeL3EYxjpjRgLe8Xa6zTvdKyR2QFM7SQjyAqYUkfGyJk80i7Kh8YFFWdP4c0/LEFb2PNA44cJaq4haMs8jEJVipjMqZVkPS2Y6w6MZhIJObDi2PUqVMPJLJuY8HKJUCethKc9FnjMvTS5cQkatxuWRJoSzVKHbzQlfLO/j0RyZPh5NN9a8XB+yoWu+mdyh0hlGSydbXbjcniUbK9936dVtl1QD86qGqIgxYlFULS0gtVqGB43krydGk6UWrRRF3QglWIFdCY7aDQZgVjqO5pVwQUNkXoo9U7+TSJZ842mCRIxeXeuSWcN39yakVjNMUqxWHE0rAqHdh/CE6YNVwpVdsV2s0iil0Vqx1k3R7d++ZdMQSjne40X1I00buqzL+rC6BJ6X9eNfR3vSQbwIOkG+3twRXubR/rmPaJbLeL07kHFtuZQRtA/SWfNexEejNQF/a1vyvumJgNu6Fm/NYiJgtCpkHU0Dp4dtJ+5EwJGx56bvOp57fCapgLsbL8lofTaGvYeyX00NofUFXaX/rCyf5IOJ/PhsxNjeclfNu6T1lwwtZxPks7g2PrOpW6snBJQupueg2JjWezWVz9nmjkvSUUuXCPF8TH3xNq+k23fej/mQWo31/PsFTQigboIco6qU70OUtpNqxUBJCkkOvsaXJcE76T4ag05SMlfiY6AJcqDyWFGZjOiVqNCdRyslN/aW6xZRRKUpTI7RkdTXVMowTvsUKuGWKfCuQvsK5St8kqN7fWqnSZYTapsz37jGd/0Bf67+L/k72XcAyKPhT1Zf5L/vfp4lI8ZJTtc3nJg+wS/Z8yl52YjVUDok9oeo2Zis2GOtXvBW7wZ7dkjjAt1mwXYz4Sisc1p3aVzAGi1ioRCJSuNCAGWonaOoG0lRUgoIxBZsrbp0Son6XGsxkm8unItaJ9xLt7A4Rr7AxogmSrfVjuiGhuR9eU+agOf893BFmlhdqRf7b20KKT5AFhperfapleXUnNudLVRGoRJulGM2zTHvdXcBg1VyicQL2/nAy+3CMjJ+F6KoR8RBQvKIVNFjjYivBMgrkkRMsqYtq6OTSMCAa4GnbkEoEcqqIaLwITAtGn79rX2qxjMrJAYzxbCsHA9O5tzY6DHqSrqU0YrTRcXpoqKs2ujVCzut4ExZ3zGKjUHOdNFQVA1FLUr9GDzzylHUnpd2h/Qyy8OTxSXwvKxPVF0Cz8v6+KuuZPRdVzIyXd960jfz467xsXQtn2XlpLQAlPHxOfDsDdvxcYTjQwF9MQBagGRdgErg9qvi1RnCeadyOJQR/FGbA98bAkr+v1J8rzqQSSodzfkcfCsq0i0oCwFGQ+mmHu0JwLWifpYuoxMwLB9CgOZZtfPFeOGWu/paGQGYqxGySQQk1o1YSS2mcLiHJ1AnXdTkFB0iSmu0D2DAKCP8UVefcy2NadXyAZQ/U3NfONCtKv7Z3dBn9zx1ayL+AZDBu5U0mpU3J0rL+e61QqtlLapj71tHTQOuEXChDKVJqUzKlpuThlp4gzYjdcIV1e3xEz6gIhhLrgI6OLG3N5aYpBgfxHzeGNAJtbUsbE6zrGhsTmUSHqSav6j+Pv+V+So+Sgzlv8KX+J8XX8CEbWqb0HMNs6bm6/kLVBh+ungPj6JqZF+0jixqTSdAEwJH6Rqnwx1Kp6iUZ6pS1usZry4e8M9MD5Q5E4nECImVdU0W1dnpizGSGk1oAVEIslzt5D3S2Qu839FopjMarblndujYBk1k6EvuNEc4DJaSkvOJgYqRNHoO7OCJ9QTk0l91KFeXc0TiMiOw5ecMQskju/bUZRCUZqYzrtXHvJ1sUjWh7U5/9FpdZZ1EyXNZCzpXYHg1kV4p8FOrMCGiDCRn1yAXnvMEnHokS331OcvaY4yIfh4dLzBGcWd3SGY1WWKJMZIYAaonswqlVesHGvEhcDAp25hKddZV1YgBvw8BDSTWkFmD1g5rDXUTeHy6FCFZlvDZGwM+e2OdovUp/dyN9d/x/M0QI8ezUugIiGXWej+7TEP6bahL4HlZH2/t3Yd3vi3ekas/1N2eWBTdeukH53zOpwIivRMboo1tnuyhPKPej2tG69IJffie8Dp7A8k4r2sZ63onYiOCRGROT0UoFZFtaisCoSSVn4/WBZgd7olwp9OV7mhdi91S9ALajJX1u7YTGRFB0fXbIkZaAbs0g7LtjK4shwI82bO5UKrtMp55qV4YXwcv+1ssRHXf6+GNwU8mOFthQy1WQ2H1fgU+CIdRG7DxnEymLpLzLnZg21rZLb2vnjdojzHgo/qQFKEVUL/wvUKOc1XCaBNfLHBKo0yCIYjPZ3A0KiOqiNeGJDrJeW6BsYuKqBMyX50BjxVkDtpgVBSroeAYVDNiCNQ+YHWgpzxOa2a6wzjm+MRygOL/1f06/5f06yyj8F7/cO8L/Gn/B7lxaimC4jQa3sxu4rVjo5pwrR7zVrolKeneU60EKypSOs/VaoYOgYW2FF6dmQxkqeHE97jiJqw1Ux4la+0IO9JJhC9r2m7gymYowhN+qEKfjU+Mp59le7pvR7xUH9GNNUstXbNKJaz7BVfchKVOGVsR75kY2HVTjk2PPTt8al2ry3S1vdXV3E6/SaJwFeNFMcz5W6iVJfEeHQNB6yc6gR+hv362rFJKmvdGU3uPiufqd6VU67gKPojYZ2eUA4rEaE5nFahIYjWxcRIUFjlLNQIxuLdK1Pa1FxHQ4bREK+kwr7LrFZFxUbHV7xCioqwctQsUVYOP0EkMmY0kq99BwAdJftJaU7tIYg3rg4wXd4aEELizO2R72DlLHqoa/0xjiRWn9XcKGJ0VDd9475j9cYELQbrYRnN1vcvnb23QzS6h0I+yLo/2ZX18dbQH3/qq/BXeuSYgMwYZT7/5DQFn329spnMCaB/ebZXdLYAdjqTb6BzPNLBvowuf8BftDeHaCy0Qa7tmzgnvcTCS0TxKOo437wjPc3oiI+piKV1DH2B9U5CA98Kb7A+FbzqdCjDt9AVMrnw5F4tWuNOO82etOCl4AatNI93OTsu/LFrhjrHg25z5i6V1e7d7VtdQBodnGe7QiqEKPAoPWNVSAQDtG0KS4rCkGszKJTGEtruJEMxWDw5xtf1wvr3w/i7o80En0HYnYxth+SzznLZWgq/VyF+3CnznhdrgGmmEKkWdD1BRbIuUClQmI0SNX43UQ6BRCXmQm3ulM7LosLS2SFEU61WaMUv7bJenqBhI6pJUQxIiVYwsTUJhEpTy/BfZW/wV8084UdKh/oK9xb+vfoGftD+JLia8mxi0L/BBOH4uKPbtiBt+zH02ODY9Nv2C/RashQg6RLq+RKvIgepRuEhqDXmi5ZTkoOaQuRqsCE5WpuAhSlSkj4EQw5nJ+vsDnFZ2RB9UR6bHW+k2n6n26YWamc5QwFxnrGlLoRLW/JJ1vySgODY9vta5QaWfkYwTnryC3++/WSsrl1UMZ0Kmi5VFR6kS6qjPQLjVkFlN5SLuIyRUaQVGaSof6KaafidhWTbEFnVLTKWkT4UYUVpRNoFRN2V31OHdwxnLKqAQGygX4lOpsKZ1mVCq9f40ivGiRKNJWv6oax8mlYIibVjWAWMUG52ME8AHj4+KPLOS0e4CZe1wrehItfvaVYa1bsrWION0WdNJkyfiLhel4+WrwzOAeThZ8sbDMQ+PlygNd3YGvHxldBax+WmsqvF89d4R++MlO6POmU9p2XjePZzhQ+BnX975RGXSf9rrEnhe1sdTMQpA804shlaltIC54OH+2yK+Sb7HZIwQ4Gu/Bt/4sqwv7wiQHK4JEJzPBdgdH0gn8/3iouHaedwlyLLrm7LcxpaAveVMxDvT8bmJe1UKyHnxMzKOPz2Go0MBnd2+cES1FtHObCLd0Zc+A+++Bctp2yWNMnovW3JY4yBU5/nqi5mo75OsHbWnAkCTBCrDOXS72NdR511NQvt/Lry2+gPadkqUkg6l0XitCXVDNIkkv7TLR23RLmB1A43DR48JcEYcNVrA+Vnefdvm0YlwP1cCog9VuT/3JH/wy1qBaoVGSSo0DleB95LTbix4SKolKgjYSnwg+gjakgaxEEIbbPSo4DGAjR5DIGj5XFHm0nTrBc7CvumzNDk6TegMBoy9oloWrFdjfjW+wV/ofo27rVL9dhzyb5o/zB9JvkBHBR4taraUIk1SOvWCR3pwLmLSiipadsKc7+RX+FLxHtebU8ami0PTCzXDWDLROUd2gFKQp5rcJm2qaYKpNd1uSqKNdMEUpNacqdOLqnzSjID2eeF7ahEqvp1dZW5ybtcnDENBBB6k6/zT7h0qDKNYoWJkZnIO7ACnnt3Dfr/4Z9UpXD2rHJk+U91hzS85sf0nltUx0AsVb+Y7ZzZWq2euog4f+eMkRpEl7ZjcKBrnqVw4s0cKBEmUbXPkY4CqdsROig8iyhIMJz3bZ1k5hRBRNmLaXPozCkcIhCjipeAVSkeWtdgvrfVSskQM3fPU4opA1QQGHYPWCmU1RQ1Wa7JEk1pDYhS7Gz22Rx0mRY1WimXdACL0Gi8qUqu5viHH8uvvHvP3vv6A00VNakXy9dbjCV+/d8If+uJ17uw83aX+NNT+eMn+eMnV9S7mwsQtTwxX1rs8Pl1yOC25ut79gLVc1sdZl8Dzsj6eWs5hfCQg81nVHwlfcjo+j598f8UovEnXim96A/nZG78FX/7HgILBUDqPD+7K6zdflA7kaEPAz/4jAXAgIGi0Dq998Wkvz5X/5tFjAa72wq9C2toTNRUQhU+43tpE9XqSzV5XIijqtOst5tLx7HTFzunqLQGQwcmyIbQCoVZoZPOWN9qOq7t9Abt5V8DoYiZgMYTznPu8I6DS2PNOpmvaEb2/IATSQNt9XOXFJ2IKH5H4QhMDaiVWVwoVPTp4VFDElVXS+YmRfTZI93M1X7S29SvNOEtievJdH1rCrH1ft3Nlv3SRcBiRUb82cOc1oQ7sP4QQ0UkCSYd6sUC5EuNqCBETPLmrMSphYXIWvTWS0DCsZjJWXeW9nyUoabw2+AhZcPTdksN0m4N0hElS1pzHKctXshP+r92/w1etKNVHscu/0f2X+RPh8wyXM5ZxweHGNYpqTu0DV5KGetjHhTWSWuHaEXeIChUjB3bAb3Re4HZzzK6b0iVQqoTfzG6xERYsg2I3T9js52Splbzv5Ryf5NiNHbacZV47cmvIUsN82TBeVmcj7ItUAuAs2/yDqLVPnEeluJ9s8NCukbc0gkKlZyPx/Y+2mqceLc4y1rVwPmtt+U6+y5eK++y4KWPdxStNN9SshSWP7BoPkvUPXOeH7kOI1E4U6XXtzxTqK9JIXFET2mNTe48PItL62r1jahfppgYXxFT+/cfQqPZhLir6nZSJLwlRjPOdUmTWII83qh0aKCrnyazltWtD8eY0iiOtWoGT+LNWzjPsJFRNwBpFP7fc2h7w+ZsbZInh7b0pD04WdDPL0axkUTZoDa9dW2O9n/LweMHf+ep9isZza6uPNZpIpKg8e+MF/83XH/LHfm/OsPvpi8vcGxet+O7pjmZixJT/aFZcAs8fYV0Cz8v6eGqVdGOec0mtOmXPi1o8OZTkoNPDc9X35q6Ay+98Q4DI1u55N6/bl07jo3eli1qV8MWfl87k+FiWWduU9+RdAW/TUxnP5q0d0krMc33r3Lsy78q23vuu+F3Oxq1ZXi2dzN5QTObHJ3DvO3L3HIwEyMYotIKqbEf0dwWcrgzKvZPuZJbK9ou5bG/l7QkCHnevy/HIWp/Kw/0zYIT3Qh1IcxnlFwvZ37V12H/cKuLduf1R8HLslWLlvRm0xdZlm74DaItqt69CGzOpW4DrWnHPij+qU+l+aiXnqNOFmy/LNt99Sx4svH+GqfwzLhmT4NHo0HCmho8tRUC3UucVfDVaus9p3iYVKTnunQEsJqQh4LOUWdahU87Jl1NWkZkqijF8oRK0Qbw5laUTagyBBLEVEumN0A+qoKl1wiYllQnci5Z7/pj/PP37/CP7JgBJTPgX8/8Of8r9HDeDJeYpU53iooh2stjQLafM7TaPetv4JkG7ikQpsVXF8V3dFaqv7XFie+ShJomB2iSkwfEzy7vs1mOWs8ip1rhpgSkWbFByuHWb0OvTqVwbb6+YLyvGy4YQI8mKCaF4wpIHWobIRwSetl22F2quuAkboaCJiiM7YN8OnjlW/6ileDKh6H6ygUfzQn3Epl+giZQq4Y3sCm+n2z/QtgDqAKF2AgSDnHcfaQU7kkTlfDzbHx9gXtZMl7WYLOhzGyjVDh5ShCMaaBOYtAi4auexxlC7QONFUNTJLFXtWDaNdOWNIk8TjFFkiaVvZB9CjJSVY146roxy1m3K/qSg9pGtYYfPXF/jzs7wDCi+dHWIUnBlvUdZO9m21tw7mHM6r3lwNGO8rHlpd3BmuaRQdDPLlurw6HTBO/tTvnRn6wc6vp/EakLAfoC2QDrf3+sjzGX9IHUJPC/r46m8c25I/qxRerkU0JB3nn7t5BC++WUZR4822lFqKaByfCx3zyR9kr+plERdzsay7iSXu8L2VUlLWiUlxSij7PfeFuDZNALE+sPWuzI7Fwetqq6ky5nlAjAPWtV5bwg37gig3dwRLubRXquytjKKV0jnsq7lWKxvwWQiFkd1DX55DgJDhF5XgGQILciN0jksi/OOK+G8y4mSjPb1rZZTuhQ6QQjCd10uZH2+5UVq1RrEG+gOUEmGKU+IrQ9iDAGUIxjbCm/kfWowkmN+UfG/yojfviLnsizkX57LsjvXxFdzegLOoeqSD6wIyiig7exa8agUrujqRtDOMkOANJHjeLjXquwNlPvgPSbr0Ol1MVVDVIrapiSuAhTapHRwbBQnTLIR884mu9WxgNW8T6yXuCAJOaVpbWeMInUl3WZJVTzirw++xS+n38CriIqK/3b4En+8/H3crocM9Ew4dOkWdzdexK9vwXSMswOKaGhIOFFdUuPRWlE3gbVmzlwlPLZPTghKneJanF9rw1c6t/h8+YidakbnZIEPgcKmvNG7wntqi3RRk6WGZSUZ6PPKoVRkvZvR+EDlxIw8IVC7VYeZD0z7eX+5CNeaMT9ZPmQQSiqVoIjcaY44MgO+2rn5hI/n++uDNhVpG+gXfvYoWeOxHTEMJSYGljqh1B9fJ84HqGKkk2rK1o8pIIIbrVRLTY9n+1e2z4SalsrAudGFigprFTZCWQcZDCiJCl1UDaNuRpYEJsuGxkcmiwrnxYbJaIXSImZqnBjFKwWHk4JOYrAolpVnUjRk1vDK7ohuntDLLC9fHZ1xEmvnOZ5VfO7mOt3M8vbelI1+Tr/lep4uKr5y91j8SZ8hJuqkQtV4cDz/VALPtW7Ko5PFM1+LUY79sPPp6/R+kusSeF7Wx1NJKrGZ3/mGdCMvmrIHLwDu+m0BSxcrBMk9LwsBLqvK25H13TcvJO7MzkfMxkrXMCKWSL0+/NavyWt5R0bdV25IjvkbvyUWSFUlXUbXwFuvC7i9fke6dKbt8K3M5UFA6nADCOdekqvSBq6/IOB3fCzd0SSRn+09gPvvyP6POtL9W8zP+Y/Oy4h9xelMEvkc02Pp6iWpdBBXHWS9Eii12e+uftLTM3goKgFl128LdWA+kTuja7uJayKEMkcHxOhoTIKKARtjm/yjWiG8QlmL6XSl26m07G/Sjr9DEHCLPs88P3gk+1y23NUVee8ZFYxF+0CwBh8VbrCBzRPpdLf8yrP3rx4G2phF0lSuq7VN/GJONAY9LdB1BcZiOj06cYnPEpndOo3WhiR4ok6obYf+cMRy8ypqT6FPH+FtQkmPufKU0aK1EtufGHBxyV8YvMdfHbx5lqn+e8Ir/C+Kn+N3FZaZdRTUVElCEgPZ5JDrp8e80XyB4+uf4SFzNsuEn2ke8+L8IbN8SDcJVOWMmTJ8K7vGIuk8NS8+G/cCE9Pl17ovshWWbCaeykVOdZdZSImTitw6Xrk24sUrAx4eL5gWtYxxW26hBqzVhCj58TFIl8191Dk7MPJLvlA+QMfIfbt+dm51DFx1E75QPODXei8+l9v5fhHRE5/1OduMSn0gmP1+ynB+Ka1MHFYs6gjUPmJURGt15i26Ktte1j5E0kSj/KohH3Gt8MtadXbiMmtBSSJSP7NnHp5KqTN+Zt04ChcomkBaN4wXFctalO231oWXeWu7z4tXhkwXDWlq+Imb6zw6WXD3YMZkWbGoHIlW3NkdsdnPeePhKZuDnE56fmvfHOTkiWFS1JS1f+I1kN95MYv4dCrcr653eWd/ynRZP0UlOF3U9POE3bXLMfuPsi6B52V9fHXzRQFte/dlhJ3mAuTKBWxcEZHO+wHJajR+UXW+qqYWcDabCAAaH0hnc5UZl+UCwibH0uVc2xQAtJjD678Jh49FyV0sWwsmL2A1zQXA7T+C0Ra8+Kpso6kF7FSlCIOshY3N1hDeS0fz7pvwUz/PmYhntCH81be+KaCorgSYzSYQGki7ss3p5DzaMQbOvHMmJwJiXSPbz7SYvC8XcsfuDVpv0VI6rkki3y+m0vX0TsDv1ZuyvyaBHS2f9+RQjr0P8v8gnFAVPBYRPDhj0S4StYy+E1+jtZJj4FoD+RAECJtE7r7TSctv7UF/re1wK9mn2ViOVZaDdxgvqToR8MoCRuxSTYaylmxthOsOCdMJxIjKLCY0qKr1ELWJdJuD8DurvMciGEzRdomzIV03xpQLdHvuzMocvz+UY1gWWJOg0w5ZtSCZHxM7Peqij66WaOexUTPAEbBMk5T/yn6Hv7T5DQ5NBcBL/hp/2v0hfp6bvFy8R+4L7vav45PszDx8FjzrbsoXZne5568wOnqbdH5CESoGtmFjVhKSIXfXbvCO63IY0zPF+QqAKZ52AghKc5L0WViL1wHnz8UwlQu8vT9lo5fRSxMUBS7AZFljtCIQwUOWWLLEtIbxikSLWXrzESaM15sxvVA/za9Umj07YtdNeaE+ptTSCZ3pnLHunP+uxw/uev6oyrf7Qsu5TKxBG02o5KHCtaP0VaLTqhTCBWx8wIWAdudau5XOrmw8mTUYo6kaj3eOiMI1Fa6TtBZOmswqenkKEerE0MylA1rVgYNJQTez3NjskRjNonLcujJk1M0YdTMeHi8YLyqurXe5fzTHaM3OsNOeV8+vvbmPMYqr6096Jhut2BrlHE5LpmX9BPD0MTBdNixKhzaKRdk8oYr/NNRGP+ez19d5/f4Js7KRqNAI07Ims4Yv3t68jA/9Edcl8Lysj6+SFD73U8KrfPSeJPrkHXjhVbhy/WmBD7SAqxGguqrlXEbY07EAx70HAgTT/AIHUEl++mwifMrrL4qqHAQQuUbsl6pCOp3ByzpWNIC1TRFD7d+HF16WfYxRuq8r0NXtndsHGQO3XxKAef8d6e4mqYCst78lIqUXPycAeCXyOT2SfY9RAOnqzhs5t3/yvgXoVSsCys73N8tlXWnW+oFOW8ERAlJPDqQbuXNV9nW0eX6zrwrZ9ywXM/jJuN2mxwQxKve9IS7v4UPEFgusipimAP8+fqdqgb5rLjgGxNZHdUvOUZq9L+lI6Ad+tWzL14wxEpUiiQ0aQ3V8RDmeoXSOdSXWuzNjbrOiIxgDvQGV85RHx0QjXpVNd8gy61NEzfrimKSp0ahzrm6M8lCiFEmS0utkFIsSN5uQLcbQ1GIS7xs6GCpl+P+k9/nzg6/zjpW405tuwP9s8dP8/uY1QpLjU4ePiirJGfVS5tFIpGIi3b71JGe4HJM++joPYmCvN+LbhecdIjumZBCcdC/9BBMcUxLumTXeikO8Ms8FZ67lJq66dedATgzgj2cVIZZiNi4mkWL101r2OC+elBqx4UmtpWocTf3hyHPHzVg8Z9StiFxvTlm7EJvZKMNjO+Jb+dUz70+tpfv6SaDSSeqqmLVbo0kTQ+MCWok/pnfhLIF2RQNofDj7viaIoXz7QCUsEE2eik9E7VpP1Cjm81XjCSFwOq+wRrGohHKRaM1aN2Fe1iRWczKvmFeSG7U1yLi5NWB7dN71HfVS7u7PsFqxOch56co5TSPEyK+9uQ8RXtwJT1gDaaW4vTXgnb0pR9OSzV6ONZpl5Xg0XrB3umTQSTmdlvyDbz3mzs6AV6+NninG+XGtl64M6XcSHhzPOZpWKAUv7Y64sdlje/jxdtYv68PrEnh+mqpYtEAmexLI/SgrSSUhZzAS8OhaoUvTwLOs4mybJV5XLcCai8ioXIh4pteO5qvyHAQuZrJ8VchduKnh7rfFNmnnmgBPY2V8//a3BLjkXRH+9PrnndHRBjy+D/sPYOuKgKa9R/J9MZP9eefbMj5/4TWJzty+Kusan5wryZdzAa7Xbsr+Zfk5jzRJ5bzYRLiQVSkATSnpUEbOE4JsG99JOJ9NKlrz+bbFosO5dREKdq89qXwH+bqqhId6tA/1rFW/G8BAU6EC2KrA5h1JT6qW+LJoM78dYTLGBC+G2jGgYrigktfyGeYT4ZVaKyC7WrbcWgWNgCC8F/CphGsabUKtDMY3LQ+0Rq110J0B6fEc7WqcSYjagpIYSMoCXztqZbCuIa8DTWdA1evR846YplRLg8KQWiX7UC7l+ljlzDc1+ekhCRFnU8gzwuYmpBnV/Xf5zXif/2D4Br+enQKw6VP+3dlr/NHyM+zZLdCiVp6qlGAs3ugzE+r1fsa0kON/WBuy8QnzpeIbyS2iCgQfKFEcO8W1xT5XzGP2d16ksV3Wy5Jr1SPW3Iwvp9dxyjy3Oxg4f2H1uguSKd60SqHEKlbSEb8SwCB57I0P2PZXqHKe8iOiwPicEayKkRfqY7b9nFPT46FdA6XIQ8Pt5oQ0Or7ceYFa27OE19+uWo3OV8d2pVyX0bfG+0ATW8MJKwDdtUlVKwcArRWJEYN4f0Ekaa1mo5+hlKKsHaGNzkwtdNKkfViIRBfxPhJCJE8NIcC8EgHSi7t9JosGFyNGQ5pYtgdPpupopTiZVww7CVc3nuxqaqXYHuS8vTdlsqyf8uXcXetwa2vAeFnx6HRBjHAwLagbz9aww8+9ssPuqMOsaHj9/gko+Oz1JzvcP86llOLKWpcra11c286+9O387atL4PlpqPGxKKiPD2T0mmbCb7xx59ldxh9mBQ/vfEe6glVxbgmU55Je9MKrT6YXDdZkZHy4J6Du8LGAhlE7eq8K8dxECYhaKalVq+x2tQBMY6QDWCzg9isCiiYn7fh6KCNr5wQwuv8/e38eJFmWZvdhv3vf7rt77BG5Z21d3VXVPd0904PBDDQAhiAkowQziAJlEmkSIYqLjCYZCALgBgGkjEYDjJTJKJkWiKQE0SguoAiRMAgEiQEwGAxm6732zMo19s1397fde/XH9zwiMyurKqu6urq6O45ZVlaGh7u/92Lx4+f7zjmFPFetIqHTiRDQnbvw9rfOzUVFRSpPj+BoF77ye4TUbl4VBXJ4Io+1CHK/9bqQsjAW4jfsi4I5GcnxLSzGiz70xS5naeTfOjhXGPNcskDL6gXE86HblZH7vFKSv/yzovT+zt+V48lTUSGLXGKbtHfewOQH1fPZcynHOlGVs5SyzDFKo3Qgo/hCMiBL5eFpLaHVDlCemLHKvLo+UzkWV0UdLfYyixKnHBYP7ao907LA+QHECfMyIjWwVIyI8lRadarXWA8rZg/PF9IYJjDuEzqwcUOc986iHRgvxDXrTIzFhj5hOqxMXpUi2+rK8RkDJwd4xuB1E2xcI6u1+E5+zJ9v/yZ/I7gPQOI8/leTG/yJ4XVCVWfi+eQ6ZNzs0nAlvfkYVZYUzmdYWJJYolhmmaEWeWiTUc5T7uEzxxB68vW0xrKZ9zHWMlWKvUlBkSQsNZcYMeWF4oTjMuF2sPKxR9L5I/b0vKzqFatgABzn4/SK/EnA/Pm/P+r5DvwmX8z2HutPB2jalBUzZqQjTv36mdqe6oBd1WazHLJmRjzUvbP7/ChG7tVaJ1TPvQh8MNbRjgNK50hzg1JiOJIwCAmP93Hn7U/OEQU+xlqcc/haEQaabj1CVyP2vBTjkDQZqWpfVJMbaSCyTkb8vXpEWliy0lQkNWCl4wOKXiNiOM1572BMtx6ilLjP88JQlIZW7en1w8vNmNv7Q8bz9xPPopRWoysrdd7ZGfD6g1OywrDeSXhhs0Onep7FDuS9gzFXlhvUo5+8EfQF4fzR44J4/rjj9Ej2GWdTUfz8hhCx228KyfrSVz9b8rlzH957SxTP7iMOyekYbr8hauDWtfOPay1EcTwU8nx6KOSuyCXUParyLtNU6jGdFXITxnLb0a4QVVMKWR2cyHh7NhGCmtSFjIaVCllrCNGMZaeQS9dFGdRalFazqLf0zs1AxsCDu/IcnVV5vKQhz799T843is8bivxAyOZkJOeg1HlMk37kcQMf/ES+dlHMWT1mZZbBlNWOZTWOV0pc461IruGV5+XjW9ck/un4QNYcjK32Qqv92rI8zyYtS8BVgewe2BKTZ+RhTKYjatkUh8MZgy4ytHMYFAQx/kIr8j2ImvJ9Nh3LtZ5OhNQaiW9ySY08L9A2xau6463ysUGMUgqvMrcUQYTGYr0AtE9Rj/GyuezARQm+LSGbi+LkHFYryrCOiRL8bE5eb+OVOcP1m5ysbNI5fUf2TJU6j/YqCrmuSQ3mc8x0ysO0z78+/2/4y/7bmMChHfxP5tf4U/MvsWVrFL5lqgICHJfLAbfKFn3l0XJgrSHXPra09KcZoe/hKYUpHcHomLHz2fdaOBSFtWhr2SxGbGWnTLwQVxrKvCTzDafTjNJpojDmatbnrr+EVVqc0c/A0BYk6lFYqvcBT7mtsBBoS+mEYFWLK2cq4NOwF3S4VpywVE448c4JZqec0TYzHgRLstP56DEoTa48NooBD4OerGW7H82e52IcvsBif7MwlmlmqEU+7SRgVhh6jYR5XjLNCupBQF4Y0sJIEhyQFpIs4SkIQ49f/MIGWiveOxBDolKSEQqikDonWaDWWHQV7J8W5VmvQxxI9eU4FbKYlYa3twfM85L5dkmnFlKLfOLAJw491ju1D/Lt0a6HdGoRJ5OMpWZ+tqs5nheMZjk31lvVWohPIw7PTEcPjyccDlKurDRYacU0k4Cd0xkn4+wnknhe4EePC+L54wxrZBScziX7cYEgFIJ1uCtE8OYXPpvjWQS7x4k8/6OoN4VQbd+FtUuPB7b3VuCVr8Ob3xaldHEOvVUhju9+XxS8dg/GfUCdu+O1J68ss5mYfJK6qKZQje9jIbUHO+crCErLtXnuCxDVhLj99t+V44+Tah/TiZnGlkLgrIW7t2BpKHLSRiLPPRsJuRv14dQXZdcPquikQjrgS9nNI6xuy+ZVqLwTx7pS1Y5kKo50XRFU3HmEkrXyHLUmLG9IiHpYqRqd5UpZHcquqat2MtO5fI8EkdwvSzkPna8U18xi/YBZ0Kj6p2fYsEaZNPBHJ4SzEedh7g6w8oamXhc1cTIWZdH3YJZW7UYJViucEhevQ6G0hwljbBCKYmkK6nmGpwGtcQsV3A/A5Djr0HkBSQhhJOakQmKfFqH41tNEoxPKIBb12Q+ZqpC4uyoh8tOJfE1r9Sp6KWViUv5C/B7/TvIu08qp/ofTdf6VyWu8YNpYoFSKsZeQq4B6OaNtp7SzEfOqw/0o7mE8n0Y2ovQjUaqNo2FTMut4GKyilSLwFI1sxlZxwmo5pleMqRXSJ39iOpyEXTH/KBg5n4ad09QlY8L3EcanQfF0crnAB+V0yrqufezfH/Z0Qy/he/ElvpTucqkckCsPjWPVjJjohHvh0lMrLkvlETnzocfyWeFpSwXWwjjNmRc57VrEiytNuo2IB0cTZllBVkjAvNYKa93Z5kst9GjVQi4v13npcofBJOPe4QhfP9Kt4CnCwCPwNf1pJvd3ch0ktH2GpzW1yMc6x2hekAQBhSnZG8xI8wLf82jFIdNU8jyXGlJXOprl9Brv31uyFi6vNFhtJ8zSsooQUjTigC9e7lGLPL5155h2EtJrROITnOeM05K9dMbBcMblpQYr7QStZCXgAhf4YeCCeP44Y3AqY8WnOcI9T8w2+w/hys2PX1P5STAdCxHpPSULLkuFbB3uiBp66Yb8rZSQlbIQxbbVEVK5siFkdRG3NDiFeLFxVZ1fngmBzTPZJ41CiTBaEDjlhKTVm0I0K/UMgPqajHBXt0QZO96vQgWrrMqiAJdXeZuc9wzWGqKc7T2UY9t9KPfxPTmWpC5kcT4RlXYx6vVl14syk+M15SOvUtWOa1k99yLwPYxkpO0FVZRQCJeuShNTd0XOY9SHu2+J2z9ORPWtt+ScvvMPIJidrzsszsFZqWopJdvOag+rfQgCbBDhnEOVBbrK0/TKTMihH6C0X6Vqj+W845p8vUanleEoElNFluHU4teLw1ZrBH42R9kS5xS59tCuxBlDMB09kt+pwJoq4xMIQlRRUCqPImkRZlPJGrWOzClOrEc6m3K41iEcDdmazIgin2BlXa4fisJZ/r3kDn8u/D4HWpzqXzYr/Lns6/yhoU+mAnIcRnl4tsAENSZeTK48lsoxnnIMgyZTLyb2NHthh5uzfXrliJqxmNJw4iV8u3WdoYp4br6H1nAtPyJQlqlfo25yrHVkOmS5nOBlQ3aDdtWiZCkdGKc+tN/+UTiebtb5qF3KxX0WI+hnoRe7QYehl7BWDKWXXWmO/AaX8j4z9fTfLYnN2fY7z/DoPxpYREU3VjOa5YS+x1avzlo3YX84w5UOrRyhL2N0BbSSgBe3OnTrEddW2xz0Z7y7O+R0klNai6kyOsERBR5pbrBWIpo0ClvKSsksL/GUphbJKksrDljryKg8CjS1MGKSlYzmQjJroUcYeMyygpoKuXswYrkZk0Q+fuW43x/M2Fqq83PPr5IWhvG8kGOuhcSBx2++e4DWimYtwNOK+0cTrLMkYUDSTJhlBbm13D8ak0Q+UXAxkr7ADwcXxPPHGUUOznwwqYzic9XnsyCerlLEHpsFORkBH+xIrFE6g3dfh/0duHQN1i7LbuTpIWc1lQ/vyDFvXROit7opOY+DEyFXZX6+C2pKcW1nVeRQ5XhGKVGBF+P5pCb3X5hirJX4p+e+CNvvVRmeWXWtIog9+Vzn4Oz3rzo3KqHg7e8IuewsC6GdTyuV0Vak0gjZXQTRO1d9Hdx5iKAtATHSiGlIiaIaRqLGOld1zW8IOW505GPTkXxt3/6OkMDuckVqq4am1UvisJ/PRCXO5ueZnAtqsshDtZZkNqCsbzDvbVA72sYf99FlvjhrsE66zj1PiG2RwzyVW08Pz0P+HeB5aGsIVdUK4wcYL8RECcoYTNzEGIeZpxhnKVo9/HyOykr8+RSjPUo/IvaqZ9cabQpU3CRFU7RWKbvLzApLeXxIMjyiFjfoFQf42uLKjJlzBF6GVYq/VrzJnw2+ya14BMD1ss6fzr7OH7XXsDrAqWMim4MOcNaisdTLOaHokYyCJrfrWwzjDitmzMR6fDu5zFFnC39wRE/lpDrkMOzwoIgIXUEtm/LVyX1im3MStohdSeDEILUbtPG1pj0/5dhvkCuPKJtyx+syU8EPPI9+1rsvFLwPU00fxVRH3InO624bJqVlUjp2zsB7fJ2nZjNK5bEftJ/5uH8UyIyjFmhCTzFJC77/4JRWLeSVK0vs9adM5jnT3JAEPq0kYKkVYS2cTnKurFi+e/+E+4eTam9Wn/3qKy1M0qJqMtJY6zDOohXV6FxTWshyS6vuc2WlwTw3jOYFka/JCkvsy760dY7COvb6MwbTnLV2zGCWM54XhL5mqRFzeanO1dUWr11dwtOaeqQfG5PnpWE4k8xKrRRR4DFJC5aaEUG18+hQeMh70rwwYuy7wAV+CLggnj/O8GUZHVM+vapy0dLzQTWWnzZqDYjrsvPXqF5wBn1pDlrkMdbrsldZ5LKHertynS+vy3E22pKVebAjKuDzX5IRe9KAmhIVd/uukK7FrmcQChlcmHaiqlUnqvbOVBWg3miLEjlIhJQ+97I8nvKkA37h3PYWzgtxYguRLED559dy4cCHSo30q9igyuleq8t9vMoFrpSQzCKvmJwTBbO7LIQSOOsPVJ78z6IP3dPyGLMJvPM9ceprLSYj35dzWdus1g6cEPL778oxdpaEpAIElZKqqBRdoNlBByF2llMqDxfVcJ4nbl5TgPaxKJSuHOaLIPd0JvuhWYpVHjZuoJVGz0Yy5vZ8vMDHOMdMJQRY/CzFeD5p1MSfDqlri3M+E7+Ol7RpFCVePif3Q9TKJn46lHMeD9FKE8cxebPNadgmKxXewS71bEysLWWzgcqmxIc7+EWGSef8vfIB/9vW9/mt6BiAJRvxL89e5o/NbuLVu3g2JcgzlDVoU6KcpowaTJWPb8uzPyb0aOuStdlDuvMBd/0eN8o77MfLbOs1kkDhex5dl3Ij3aeXj4jLuURDKUVcZlilued3qbsCrRVz5VPL5wTpGM9ZJs7jfrD0mY+kF+Tzk2DixbwVbfBqus1GMWTkxTgUDZviO8s70RrHXuOjH+gzxuJ8VUW4S2PRSqMcnE5SssLQiAKMsYznJdZBFGhKZ9npz2lGBUrBf/YbQ4qyEPXeOlEukwClCtLcSgSWdSjtzgYOSahZaSUEnuZ0mjFKC+LIw/c047lUnc5zg7GOVi1EIQalVhIwTXPuH09I85K1boxSIfNqpB6HPr/4xcYHZnAqpVBKnY3PrXO0agHz3FBoS+BLFuhgVrDWTkgij9NJxmr70/MHuGqv+2ntSRf46cIF8fxxRrsn4+rR4HEjDwgBGQ/ERR49Lcfoh4Aoho1LQibjmpC00wO5LYxFedu8KmTOD0Qpe3gHvvx7zgldowXXn4eDapx9911YWoHrLwhZ8gNR8VAy2te+kNJGS5TMKJZzfvf78nyDUwnuO5N0nOyOdpY4ayLqLMnxhrEohkXlal+06JgqPD2KqoRpI8dgqtijhVkorFRlvyXPk87l+HBVrmTl3K415fiDqpYzrglJTarVg1rznEDmGZyeVuRVi8M/SsS0NBpUGZuuMhBVjnJj5JgfPBRy22jJ58+q6+ZX5qmkCT/3y3inB+g772FnU/yypIxrBNMxTmmKIEY7S4gT4pxKDBKmxFjptS4KQ4FPntSpR4aomBNYg1dv4ddE2bRFTu4FFHGNMoyJWk2idIwd9mmQk+clWa2F6q6QhAFRMUMZI6kHCuit44U+XT+kFsRM9/Zx2Ql5exlXb0EQkU1nkGW8y4Q/33mdv57sAuJU/9/MnuOf46sU8SpHgYeq1WmWc8IiZeTXac5OmUYN5l6McRApMQXleIRFys3BXcaEPAg67HoN1rMBK/kQL9li11tjKT/l5elD4nzORAWElISUTAnY9jqc+A0y5XPZDLjpz+iYjKScsZSNuB8u8b1klRP/R0PSfpBVvvvhEqkOuJyfsmQmaODYb/Aw6LHjd3AfQDJ+YHe7c0ROdnRz5b/veT7q8dUjvxKMFbWyFnoMZgWlsez0J0xS2c2Oqjeio1mBsQ5rLaGnmWbyc+8paYPSyuGUZrWdcDqRViFrZeMnDjyi0CP0FEVpsDiSUBqMAk/Tn2SM5rKKYayjEfskgU9ayOJFVlrmuURz5cay2qoRVAkSaVly0J/zm+8c8g//THRWlfkoAk+z3km4vTeiVZMd4rVOgnOK0SxjmhX4nub6apNLy42q2vPTeRc0mGbs9mfs9ac4C8utmK2L/MyfalwQzx9n+IE4wt/8loyiW92qVjEVwtXqSIXiZ4mrz4tLe+9BFWFzKIRpMoSlNRkZL+CckMk8fbzDvdGWvcwogU4PXvlZ2Z28/y785q+ej6TDSNTORUzQ0moVXB4IOZrNhNBNRpXSqOWaBNF5hiYIsV3ZlOdy9ryD3FS1lUEAna4QU+2J+700FSnNJcPSD4TgLXJL01SOa6E4ezm4qsJyPhcCC3IcUQKTvNrFNHKtFrFRaSrGmTyTrvKlFanxrDVkdcAPYDySa93uChmfz+TfeS7HWavyUNVEXnGTmijT7S60OuiVVZLJBLW3Q1GkzMIaqtah5gb4ZUbgSZwSRgESH2VKsM6SRXVMe4loNgQNaVgXB6+d4zlL4BxePqPsrOCWN/GjiKjbI7AljIZ4a5u00jllNaZPlzbp65DgYBvVXSJ+5Ss0Ql9Mcv0jmIyIRscwH3DUXiN/4csoW6LvvsXB5ID/Q/y7/Cf1NzDKoZ3iH8tu8q+mr3I5aJH21pm5iFMX0+9dphFqtNbU771FM2xQBDFeNkN5Hs6ro42hLEqC2Zix8/lW/SqToIZxmrFXo22mvJjuMyXkxXwH35Y8qNp9tLMc+lM65YR1MzqLG9oNu1BfYtnOqGV1fse/whveMnMn+Z0LQXpBihbfoov3Tp9Hu8eB3+LAaxK5EoUjU8EHEs4FfpDzWCtHXMlP6JkpGhh4yfuI7oc9vqv+szhCY6WvW0cBtdCTfxeGJPJpxD5Kyw7owqE+zQxeIk1ECiiNw5YOYwwUhryQUoHAky52paBV8wl9H4UUKOAgCXy63ZC8NFxergMNrHPsns6gcsBba4n8kDQvmGUFgS+GpMI4qs4CYt+nHgfsnk7Y6095fqPz1PO+tNRg52TK0WhO7Gsmc0evEZEEmv7UY7NX5/mNNs45TsfufdWanwT7/RnfvnfMZC6NSFrBewcjHhxP+OLl7mMh+Bf46cEF8fxxx8ZlebW6f+vxXbuVqqKy2flsj2fRXrS6KQRt0Tq0vCbHssh5hPM539N6o5WWeKJ6UwgSiJN7+64Q2L0HoubFiZA1r+o4HxzLjmNZiEKZVDFKURVnlKWiJBYtuWZf/KqQt5dehYe3hVz2j4TwOcnYo90Tt3qjLarmyZEQzE5XVEdrZDFqEVi+QG9Zjn/Qlx3UIBCiuSCkSgnx1sjIv9U9X5swpdw2OJH/T5Tsq2ZZde6BXLysItfTkfyZTaqKz6pnvd0TkptnQmzD8Fw5rTeFaDe7+K98lSSdEkyn6GaLsrWEd7pDeLQjFZSNlhBaZ3BhRDka4YqcQDnyeoPS5ATpFNfsUhjDzPep1Rp4CnSnR3jpBqG1VSNVtce6vgVrW6jTQ9ThPuOdbQ7yiFFrhdnWVzjuXaKWJby41ObGVy+hTo/kDUGeYm69w/48JApCZvmYv1z+Ov+P+LeYVU71P5Rt8ieyn+f5cIOTdptTXVCfz2nFmry2Shx42DwnmPYZEjJMVhkmberhmCXPkqPJoiYNM0Pt3edI1xkFDRyOssrmmega62Wf59J96mbOvt+ibWYkVpSwmfZpKI+6zVh2M/Y9KXUYlZrLsc9J6xpvztbIjDRJdV1Ku5ihnGVEyLHfwKjFnt/nk3SeQSky9cOP3rman/Bquo3n3Nlof7mcsF6MaEdrvBltnJFPT324sx/k14+nFYUxTNKCRhJwMpqD8ol8xTiVUPeskOxO6xxanfe0O6qhg5XWI99XZ7/OtNKEvqKwjjjwqUVSnSku9pzSOJ7fajOeFaSF5bm1FjunE+4fTZhlEkQfBJow9JjMCpRSdOvVTuYT5xV4Gucch4P5BxLPpWbMl68v8/rDU0prGUxz0sJQCwMuLdW5uiLNb4PZor/8B1Mk53nJ9x6cUJSWy8vnan6nHjGc5by53adTj96XOXqBn3xcEM8fdygl5HNlQwjXIkC+2Xk8qP2zhB9IgP3y+rmC+FTnfTU+Xoyon0SWCnFaQHuifCot4/JR//GGpsWO5emxKHzOQv9UiKvnVWQuk/H21edkj/TSdVlT2LgMX/yaEFvzfFUxWQjZKlLZu6zXIc2EAOJEIT3Yq1RdV4Wze/K8cU3WA0Z9IbHdJVEgg+rFOYrl45OhnEPSqOQuLSRdK7h3G+IIwo5cIy+QkXk6qzI6Z0JOu0tCwpU+d/uP+vIcSa2qzUyrnd+gUnZBxv2hOP7vvIWXpXgmJzq8B/O+7I66sjJlpfJ1RMZ91jiU76NMSXKyD7bEq9qTjB9gSocpDd7ahrxRiBMh1Iv1hUvXZa9WaVje4PB4zO7yC5QvfQXdWSIOIy4hY7rvP+xTe36NjWsvyLUbj0jee4vVwX3+g9Hf598t/jYnSvZtX7Nr/Iuzn+WXZw3mfsKp0oyLFOUyjuKEQbhG6CztfIDzfWYra+yHBZ3RHicm4NDrsuN7GOfI54ab0xE9B8aPCCp3s3zrSq2nKT1WzATfWZ7PDmnbOfoRVhBSEtuCjbzPyKsRULJuLCeuw9+dtZgVlsCVvJLvcqkYEjrptrdOcew1eD3ZpO/VP9+k8zNCw6R8IdsjVz4D/3z3cKZDajbjufyIQ7/Jkd+UEH1P6i8/CqWxaDRpUVY97Y7JvGCiCkoDoS+5nYUDhcIYR5YbAl9hUZiixNeqajbSeJ6HVhCFHvO0JPAVmbGookQpRVYYPKVo1kI0imurDRpxwFs7A0azAk9pSiyBr1DAYJJRi8TcpD1F4GsC//Hf7aW1JKH31NioR7HZq9NrxuwPZrzx4JSHJxPatZDVVkJWGo5GKVopXru29NSR/cfBwWDOcJqztfT+wPt2LWT7ZMJef3ZBPH8KcUE8f1Lg+xUh+hzB92Wn881vQd54nCSaUkjiyrqQu+SJ/bbhqYyIHx3Nay0d6W9/Rwjp8PS8ahNkpD48lcagRkuUSIWQJj8SUra6ed4aNJvK53aX5WM3vyDkajaR46baszzcByyMxxLZtHZF1Mw4gUs3YfuOuOxPDoVYhgm88EqVD/p35DjiuozBFyN8rc4zOoNISG5a7YXmc3njEFah9LOJXKvDnSoTVInKWe1aMp9BwxdX/XwCeVH1qivZk42q/FKthBxnqdyn1hCCeut1uQ61phxn/0CU3DwXFXbjspD0IoUwxkYJOT6hKdBljioyTFTDeT5OeQTTEaXSlMtbhC98Uc5lOhZF9gtflmMcVk5750jzkn2vyfRLXyTq9R578WzXQk4ORvzOrUNeudqjFXt0tm/zV3f+Nn/m9K9x250CcNm0+NOzn+HnvVcpy5KdSHGvsQlOY8qCiZlzq3ad18PrrKmMr8YZy/mAYDJiI5uhB4ds+nMGy5dIogiH43A0Z16I8agfNogCjyjwKI0lLw2lcWhryB1cz09xWtHXdUyVaek5Q89YCmWZqQDfGUo8vh+ucd+2ObEByjm+lO5yLT/i2Gswr8w4vjOslmN+Zv6A36zdYKp/RBW4nyOsmjENm/HQ777vtpmO6Nk5l+yQI5pYwBh7VpX5YVBI1WhWOqwzOIR8WidGmEUblK8USkNmHYU11IOIeVrIXiYQYskBV1g8rYQIOug1QoyV8brD0alHrHdq1EOf4/GcV672+OLlHn/j2w/pNSLqccDJOKWVhISBVLPOMgm1H85yNjr1Myc6SCuRAiLfY7n10SQuDjyurTS5vNRg+0QU1vE8RwEb3RrXVpqsd39wU9E4zcXV/wFrF0noczJJf+DnucCPHy6I5wV+uNi8Kqre9j0hQlEsyluZy/7p6hbcfUf60aNEPiedyWj8hS+JeepRrG0KATs9EsLYPxYVsCiE/Fkjj3PpGhwdgKrijRYx2dOxqGzT8WJGdv7YvRV4pVI9jw/FTBPE8NVfEML7zb8v5K3Zlud9eFeIWzYXNW95A77y81Vu6A6cHIi6NxpwtleQp6K6VjFB1JuQJBKJpJSQRD+sxuuJKKezqRDFPKvqQqtdUVM1GuUpjKtevwXZXmR3Lhz5ZXFuUDrcqxYJjRjBnJXdUV2ZjpbWJTVgdCrXaWVdiLwXQLONCiOyUUowOqzC7jXKSfuQLgu8Msf4McHJLnxvKsrv1vXK8DaEV3+WYtjndPeA02nObhjyTi3iRlQntIZoMsAbHDEbjNidOw5dnTtRk0mWc3j09/gPb/1bfDO9DUCXGn88+BX+kew5Xkz3UHafiYoYhg1W8hFHfpPjsAkq5qCxSmEccTHGnmxzGvjMwjrTPGJJJdyYH9I5zbnfusSsUPjzCSGOiZcw1AnaSStNUVrSwhKYkgLN2ItoknFf9c5IJ4BRHie6zrXyhNejLb5duyJ5qEpTlNW3nJ2xWfQ58pqk+lxhKpXHnt/mUtlnoxhwO1r7dH8uf4Tw4JmzSh9F3WYUeE/EtZ0jVT49l58Zi0z1I/9hUEr6FhYmnigMSFNLUUXzhr6mNK767eEkLU7Lj1WeF2TGUVq5zVoHpSUJNO1aTCsJ8HXJUlNG1r7WNBKfehhQWsc0K2jGIc+tt5llJVGg+drNVaxz3Dsccziao1D4nmKSSuJGPfJJi5LSWTSKeV4yy0tqoc9au8Zm9+l1mgvkpeFomDKYZSilaNdCfvb5VYy1KIQsf1quc12tFXwQFhFUF/jpwwXxvMCniywVMmarcXOrI4HnS+tCLqdjITFrW6JmhpGol0d75yHuW1fF7NN+v7JBUoeXvyqRQsf7ovpNRpBPJMLouS8KKaQy0SzMNoyFWBYFYCXiqdZ4f51oZ0n+zBdVk9F5KkB3SQjldCTB8dOR7FwuqijnM9nV/IVfgde+IeR4cAJHu5gsxxiH0x4eHkpr0ApvOpb7dpdF6cwLuLIhY/j9h6LQJnXZXfX9qpISub6eV5myqp3JpCYEFs7bhhotIawgx1p1h5PU5PwnY3msYV9WI5QWwu1XpHg2kWuxuiG5oP1T/DAi8lIKNPgRusjxsjlFvY2fzSiUj+drfKUkWeH1bwrp3LoGh3vMR2O+11ecDhW+ium7gP2ZwTw85UvFLrXBHv3hlKOZwRYFl3yPN5uK/2P/v+YfHPxNACIV8k80/yH+pP+zNGcZJj/E8xSeseRhzHa0RGBLtiZ7NHXC7/a+wLZJiMoZ19M9xipgbBNCoxgXcByuM/USrswOifN9ch0xUQG/XbtB10xZz4cMbA2KnNViRs1kBM7wZrJJjsdIxXTcnL5LsNVepnKWjpsz0RFWKXJVGdoeXQM2MyJXPkY6F3BKMdURl37CiOfTSOezZIkWePgfMkz2naX0fMnBrEbsXkUSo0DjaU2al2eP4CkF2sl7NQVx6KNR1JKAYipmIqUgCT0hpg6ccviVCjrNpQbT10KwrDt3sNcinyDw8HJDMw4JfI2noV2LyApDPfToNSPatYheM+bhsayKLILmb6w16TUiTicZaWFY79RpJQGXlut8871j7h9O8LXkcTZin8tLDb58fZl27YPzmvuTjO/eP+ZkJL8PHNIpv9JKeO3aMu3axx+tO+c4GWfsDaaMZmJ+Wu/UWO8kLDVitFIUxj6m0AJnsVHrn2Jc0wV+fHBBPH+SMRmfh6o321UN4w8JxohZ594tIXt+FT+0tCZ5mWub8udpaLblz42Xnu25Gk149WdFPUtn8rF3vievMO2ekMWd+3K+82m166rPW4lWtuTj1j7upn8UyVOUg43Lcn5Hu+eu8aSqY5xPhfgWObz1HfjqL8KLr8LxAem928zKCSUhjVSahGyVq4eyeNZU6wCBvPoaI2amWqNy4AfQ7IpKOa/2OqHKRa3anTxfrvPdtyvyqaqmIuT+RSFrANbIbmWjJe1H45EosOORXK9FAH9VS4murttkApvX5LbxiHo2IXcl8yDB8zS+KcnCBJummEadRqBRnobWkpDme7coGl0m4xlv/eqvMxlN2Qwt9TjgshcS5AllqsgO7vMdasyok2GYx2P+f/lf5e8PfgOrROX5HzR+H7/s/xF+duMavhkT3vkefjmnMBYDJDZjNRsw1SFDHTPzY3bCHrl1rGUjgjzlNJaRfhR45IWlKCzbfhsSxZGq8b14i5mOyLVPUKR8ZXqfbwzv0CtnOKUYq4iJF9EyM7SDh2GXhsnoubnEwcqVYqRjJjrC8PSfPeUs9kOSNEs0Hhbl3Ec6xT8OfuA4o08RCvHXfdR+4onfoMw1oS3J9eMvXdpZfGfYVg0ePbNFR7u1DqUcTonpCAf1KKAwhswajBMyFHiaZhKSFYaiMOSFo9DSPhR4mjDQzNIqRkkvFFEAR2Etgdb4vhBPax2ls5xOUp7baDFNDVtLdZpxgLGO3f6MG2tN4sDD0+qxr4fWml4zplftP56MU2qRz+99aYMvXu5xZ3/M8TglCjSb3Rob3TqtDyGdaV7y7bvHDKYZ690Er9r/L6vGo+/cPebnX1wj9J/9NcI6xzu7A97dGVIaQxT4lMby4GjMerfGq1d6rHdrbJ9MWe8kZ49dGsvhcM5yM2bjUxjpX+DHDxfE8/OOIoejfTGAZKmQm7UtIXTeB/ySmIzh3juiCC7czJ0eXH7ug8nfD4rv/RZ897dkRBxEQjrrLUjvitL26tdlr3LRE+7/gA5Ypc4rNitTy1k708qGfOzuO+c5nFlFwJdW5RiaHSF3o/77M1A/CMvrck733hEC6Acyxk6nQnaX12Xsns5FUe0ukc5TjlVCUgyItagsJqnjFRmUBdbJ7M7LUgjb4vR+/ouy89p9IGQeJ1/3ZlvI7mwspNMLqnrQkbxye1qItLFChP3wvElp0Zbk+3Luvl+94mugygId9UVhrTJVjSkp0ZSlxfX75Lv71OKAuFbDbzRw9SbzzjrZ4T5lkeKUj242qXka/9Fo8iimmKfsvH2L6WDELFdMGsv0dY1GGbIRKq7M9jCnx9wqYyZegIkK/iZ/k1/N/yYZGSj4Gf0K//zaP87XolW+N9ZwvI8a7cLxAcZajB+grUEZQ+gyjqI679U3WXFTmmbOvovReUZm5BJ5niItDFlRVjWHMDQaPEPfq8u3qdIkWcG1/IiWTUm9AKs0Ey/mQbiERbOe98H3eTtZp1XOqVlRlGY6ZKgSNsyQoRc/1WU90/I9q519at953eY8CLufKumET5d0/qAk1gHlMzzAiVfnYdDlRn7MCXWp6lSK2BasmAm7fpsHuoWzTlILnKU0DuOgtA5fy8c9BWlhMVhpE9KKyFOUxlFax3ieY6zcTysreZlaoTUkgUdeGClGa8ubrrQomaYl2kgWVl5IS1C3HnF9pcVgmnLnYCxk1hi6jYh66HN1tcXNtRYgjvMklDahWuQzmhUMZ5mohb5mnhl+zwurKKXoNWJ6z308Q87+YM7JOGWrV0c/0kjke5qNbo29/oyDwfwx9/lHYe90xlvbA5pxQDM5fwNfGsvu6YzQ83j1ag8N7A1mmKrvXivFUjPitavL1KILCvLTiIuv+ucZ6VzUs8NdIQp+IORg7yFcvg7Pv1K1Fz2C2QRe/x0Z8bZ78qcsZZQ6+l1wX5F9xU8T927B7/6aSBbtrpCZRS97dxn2H8gMyhj5uOcJeV6/IurlDwqvMgulc1EJtSc7heNBtdppRR3trcrxtHsyNp9OROl7VugqhmhtSxRVPxAC3F2R8whjIbyeJ889mzKc54zCBnF3CTU4BqVQzmHiGtaBNxvj+yFeoyXk1fdFxQxj6WUf9+VrV4zk7ziR81gYyQ52pJK01a3U0Fwc8M0O4EThXKwDFAUEMTYIKYylKCFA4c/GeKYAfLlWZUE5GmImI4zysGGEUzAeTTmItlhe7rKycZXgcIeldg8zO8UaH60VnpdIhiycmb6MtZzmYLbvkuuEh8kllIpQuSUtUwoTcBnHysl9xq7Gb9Zv8R/a32CgpUv+mr7OP578j/jGrIOdtailh/RmPmp+jMnGKFNShDFWeRROMSRG4eiZOcNyjOf7RNWLbaE9rDGU1gjhMee5jg4x9Ry7GtZZAjyi+Zifn9ziWnnKbtBlpkN8LHWbc7M45k64zFRHLNmMFZ2x79U58c7V8p6ZMtYRh37rqdE+h36TgVdj2Uw49FuP3VazOU7B7qfcd+5V7zM+2u/9bPislFOrNK9HWxg0m+WArpFpR6587gU93ow3Zc2jUi/jwKPU1T6up/G8qn1LKUKnpFfdSJB7pxZwOM6ZzPOz6CpVxSYZ44gDTRwGzLISHKy1YzZ7Up2bFgUHLmWel6KeI8r8RrdOFCj2hzMGgzlZYTgeiXJ5bbXJV26sEFdZme1ayLWVJq8/7DM+yBnPc/nV5WA0y2nXQgmkd+4DzTofhsPhjNDXj5HOBTwtawjH42cnns45HhyP0UAzeVxE8D3Naitmrz/juY0WX39+jZNxynCW45yjEQestJP3jd8v8NODC+L5ecbdt2UvcmXj8drLPIX774n6duXm4/fZvS+kc21L9vVASNnSmuRT3n1XlLkfVHFcoMjhjW8Kody8dv7xoMrYPD4UhfFgR+ovo1j+fftNUXK/+FVRLX8QaE9MTG98S1RBz5dXjXpLFELPFxPTzS/IuHlxXcbDD1aNPwhx1TTU6grZ1N7jbv1FjiqAH3CqEnxP4/yIot7GeR5enmKCWEheIcHxQb0hxHlBOq0RU9LV58Ql//Z3qhrQuCL33rlJ6cpz52P+ZqdiFaW48Gt1OR7twckBZZExOz4h9SLKSUaQGerWERUF2ljUsI/Jc1yWgtLowEM7i1E+nXwI4xoPGsuEy13a/SPYfYC3vIY3GojaG8ZC0K3BlAXl1FKOp8wyRYlm1mijolo1ipTWlfzwADXf4W/5d/g36t/lgTcEYNO0+UfNH+KF+Je4NuqzNttjYHJq0Zyv7NwjMDl+4IN1+POcXAdM/QYjF9AwGdpzLBcj+rrN2PmUzopzHA+Vpcy8EF/pM8+VMgbfGnbjjhhGCsON/JRVM2aiIqZKQu4LNFM/pmEy1vMBd70uyoJvDJfKAWMVYYGGS0lVwJvxFmPv6QpVoXxejzf5yvwhl4pTxjrBoqi7DBzcilY5eIKQ/qAwTgTyH0fk2ue7yWXumBXado7CMdYxA52cmY686u/CWMLAp3QlgdaVBi+9576nyAshoVpp8tLhjKVcXBut8LXGKIkqmuWgtaFdD5lWqmTgeygU86IkiXwCXzOcZnieYrkZkwQet/aHHPRnlKUjCjS+pzDWcvdgxP/3d+7SrodnhqCXtrrcP5rw5sNTnBNlMPQ9rq42WW0n3D0c02vGZ3mbIAT7ZJxyMk4pjZiPVjvJYz3t8nkfXlWp1PlawrMgLQwn44xG/HQKEYc+x+OMybyg14hZbSesti+aii4guCCen1dMx5IRuWgjehRhLKRu935VQVndXuQS2F5vnZOrR9HqSuTP4ETI56eB/rEQuCdNOlC1KGWy43f1eVEaF7/8Gi0xFL33Frz2cz945ujaFhzviWO70a7yKxNRHhttuU5Pxjk59/EjqBotuX6nR3LuYSTkrtU572X3PFFeceRJk8gPsYVPWGTgHMqWRONTZC9MocpCSGRcE0V1976o3JORqNPtTiW/lHI+07Gcm6eFhH7j94uS++Y3hczfuyVSXhhKdFGjDVGMOTmiyA2OOUE9wI9qmEaDmfbwTh7iK/DGQ3CO0gtRno+yDuuBZ0tMWdKanTA/ihjrjPbaljy274vaWqUKmOU1Ji4gPznGn/RJnWboEtKlVVStgYemtOIQb2jL9uzb/BvBr/J6aweAlqvxj9nfx6+kr9EzOaXZYamc0CdiXjpyl9GyJZEr0GlO5vngFE4r8CXKprQKrWDJzLjnlnnoYhSKoU64GyzxYnbAxJSM/ARXQmJzembKw6DLvi9JCr4puWqHzHVEsxqfL1AYGBLQs3MaquDYa/BmcokNM2YpG2Ot43awyl7Y4egj+soP/Ra/WbvBVtFnsxiicOz6bXaCLnt++1Mfs+McXTNlsxzQNnMy5XPgt9n3W+/bnfy8YuzFH0jmS+cIUOSlRSlLuxay0owZzjLmuSEC6kmIsQ5PKaaZBKmjNdpZtNby3s1BKw6IAs00K1ltJ/z8i2v8t9/bxVhIs5IkCs46MDytZEW7cAznBaOdPg+PxmSlIfJ92vUIhSMtLGle8P37p/y9N3f5Y7/wPADTrOpdDzxZ/XCypl2W5+ac+0cTLi018LQiLw3fu3/Cw+MppVl83ztaScjLl7tceUS9bCY+b2+nxIFHHHqP7XI658hLS6f+0ZFdaWHYOZly52DI2zt94tDj8lKDXiN+X7bo52eL+AKfN/x4/Jb5acRsKq00T3N2Q+VIrsw1jUoRKatsx+QDFra9apS6MKd8GljskCpddZE/8svHGtmtdPY8KmkBpaGzLG1Lo/7TA+Y/DqJY3O6N90Ql7stYm5VNyUV5VFUtciHgq+tCPMcD+fes2tXsrcjxPEmGZ1PYfVAFxSP7nYRy/OOhZG6ubMrn+QP45t9nbTDiJC9QpsCfjQjSKWUQYbWHskbIUq0u+5paw1vflSxSz4flVbl+t948VzuVku8L54TMf+UbcPmm3Pe1b0hb1O59yKo92jiRV9B0Tpo0MfMZAYZSOXLPwysydOCT1XukSEi3K3Kc8lC+TxkmWM/DaQ9XKcl+GHLn8mtsfeUmKgzl2h3uwe/+GubkkEHhSAfHJMUc12gxKQOKtMClcxplSn2pwago2NeH/JXxf8Q/iL4HQOx8/qfpK/wB+/sJdR00ePmMbjZkHDbIcXRnp0x1jqq1wWbo2ZgZVQyU9uiaFBUGZK5AW8gbHaYbz7GkGiilOBrOeMttkCmfq/kJa/lQPFs64N1wlXeidYrKle5j8JxhGiSYciI5nOqRF2ylwTmads69eJmjoMUw6VJGhsI4LOpsnP1Re5BDL2HoJbwdraNwZ41Fnzqc48XsgBfyA3wsKT5dLFeKUw78Nt9OLn+uMkM1Z0FozwzrRO2UUbWlHgVVP7nDuYKNXo0k9BnNMhpxSH/isdefoXDUokCc787hex612K/G8xrf06y1E1bb8VnrT1aFhKZ5yTwvUQp6jYg40OwNpswKsZXVY5+8tBhrqzG+Yjwv+Bvf3uZnbqzy3HqL79w94sHxhM2lOrVAXpqtlZajW7tDus2IvdMpcajZ7NbZ7c+4fzhmpZ0QB4uGKyfu9XvHJKFHrxFx92DMe/tjdk6nPDyZ0GsmrLRiNrs1fE9zNEpp10LWux+uSM6ykm/dPWL3dEYSejTikMPRjKyw9BoZN9dbZ4RW4qG8DzU8XeCnFxfE8/MKVf1nkenxJJyrSN4jt/mBjJLzTIjekzClkNP+cRVqngj5+7jj5kfh+UKCy0wIV/2RnU1jJCJIe5IT+STCSIhy9imFCMeJZH9euSljX60lpO/296Xm0lZBLrraMX3+i5LZef+WHENZConMc8mufOXr8nkLpXT7jpDCL31V4pTu3YLJoGrjseftSKYi9vUmrajJYarIHxwT1pqUUR2vmFPGdYZREy+us+7lVf6mE2PY8oY4z4tcjq3ZFrNWOodWW1RGT4thbP3yOUHuLMk1ODqQxiFT7XVaSxFGvHec0Tm4x8rOm+g8xVcT0AoT1Ug7K+jjPWKdoIenlDqUNzQOtCkp47o4sJVHMB9jk7oQZqWkpWr9Ejz3MqNf/1XG3/pdWpSYdg8TRExTeNOvo/yAVwe3aLtv8v/Sv8V/ZX/nrFP9Dxav8k8XvwfftYlMjqcmoHxaZkbDpNzSa/QoiIMIr8gY2BCvLAh1iK81mRdilIfT4movlOI4aHHYvsZpe50Nz6ewltEsw1jLbda4H/Ro2RSNY6Kj9xGuXPmkKiDCMvASlsyUvq6dmYC0tQS2JPN9doIupQFrDRbQnsI9khv0rMTpaQajTxOb5ZAvZPuMvPix89XOslkO+FKq+e3k+qevsn5CfFzS+dgdkezMpWbEUititRWftUL1pyl5ackKi1aaWugzy0vSwkh7kQHnZJzcTgI69RCtFOO05OVLPWZZwcOTKWlRUpT27Hf0Vq/OS5e6KMSJ7iFj5yw3RCF4SjMvSkorFZynk5T/9O/f5hdeWuf+8YQk9EiC89/HWiui0OP27oid/pQk9Knvjnh3d8jhYMZzm+0z0gkL407M7umUB0djDgZz3t7pU4sCvnSlx4OjCYNJysloztFInOXtWsirV5feN55/Erf2Buydzs4Iq+9Jk5fS5677qytN8tJwMk65sd56JhX1Aj99uCCen1c0O6KgTUdP71ufDIVo1B6J/QlCISK3XhcC+Gh8kjHw7usVIfOErGhPRrvPffGTK46dnpAhhShfw9PzkPPZRMjo5etPf/xFgN6nHfMUJ4/HJL328zLun4zOdz+7S3CwK7umSV1kkqP988zL996SndgXXpW2nSCUPdVGW1Ydrj0Paxti7JmM5FysE1WyuX42wq9FcKlXI71XUqQZJmmAF1Gi8P2AXqzxVSjO+PYK9NaEaBojJrJ0Ll/rWqNS9apYpaKAB7dlb/XyjfM4q1tvyD4oSkhzswV+iNUeRRAzufQ8jbRPkbRwQYSJauTtJfJak3ie0podo20JXogqMpTnUyR1TJTgV9FUpbVs+sX7d8Zqde5c+TLew0OCokMe1jjKNQ+0pu8Mzk74d4Pf5j/mW8xcCQp+Mb/Kvzp8mRW2eKu2wr1wmcSkLNkZgTX4KmYahEziNs+pvrhgB4q58plon67S+M6glLiORyokwtLvrHEQdPiev8bJJCcOLVluxNClPQLPUhBw9Eh+5pOqZKE89oIerxU77ARdPOfo2hkGqUrsmRkDL+G342vse01w5651+5TH+6QInGGlHFdmI0VfJ1Kj+XHJoXNcKvo4pZg/QbKt0hx6LdbKMV0z5dR/dnfzpw2vOi1TjZoXkVfOuWcOnl9cf4VjNCt4fqPN5aUG43lBEvnsnE4ZTnPGaYZzkJWiUiscfhV1q5A3EsOpZV6UXF6qs3My5aWtDl+5vszdwzF3D0Yyfj6dUJaOOAqYzAvSwmCsQ2lN4EnuZ+hglOaUVpqQrHN4KI4nKb/73hHGSrxYmhuSynRUGMv+YI7FYoxirZ1wfbXB4TDl3VnBfn9Opxa9LwapmQTcO5qAQ1z0FalsxAEnk4yTccp4XvDqlRqvXVv+SGVymhXsnM7o1KOz0PduPeLaaoOHxxPSwnBnf4TFEflCQL94ufehj3mBn15cEM/PK6JY9hJvvS6xOIvxuXNCdJyVQO4nx8GbV0TdO9ytIoMSUfJuvyG7iTdfroxH6lz9fPNb8Oo3PpnDPKkL8bn1OqysCVGaTqSZqCiEoC1vPJ1cjofynJ2P8QvKOXn8Re5lo/XR+6GeJ+aqpUdCuG0VIr84rp17lWu9ilZKauc1lVoLwVuYd0Diiganciwoydkcnsi1XpxPkcPRHr03v43pP8SWhqKYUtaaBLYkmM3xvdZ56oC1sns7n8oO6eGOkPeikPNO6nIscdV0tP9QwtmX1+G3/ja8+W1RW00hpHr7jtxn8xp+ELA8NRReyHz5MnmrR9ZeOVNqTFky7mywpiUeSvkxk6COnySoIDgzLKV+jKu3WW89XclIp3Pavs90+QYHM8thPsfFJb89/Tv8dfNXGcYSlP2S3eCPp7+Pr+TrLKkRVmlyfKzWjEmYBbUqFqkk8BShB3lhKTNDrTToIKKvEnwyYqXxTYFvDEqVTKMG3qWr7Ko1HmYNbEUCrJV6ThT4nodSlvSRLu+nkcR3vS6dcsSWG3EYtui7Gt1iSsum3A96/L3689yJ3q/mf2Kl7gkslxO+lO7QszOUc9IAqzx2gjavR1tkTwme/yCEztA1Mwm0f8rtufbxjaFpM075eMTzk4zEPwjGgV8RP+egKCVnM3iG+stHITFNjv4kZTwruPxine/eO2UtCSjbCfeTkL3+lMm8ZJLmZwH2xgjhdUjEEkA2L7h/PGW1XeNkkvFbtw6JAo+lVix5ndax2U2YpCV3D8YoDI0k4HSaMc1KtJbay9Las8B5UPieGJLqoY+nNb16wnCe4XuawJPd0nlWkvg+s6JkpRWjtUYpRSP2OBql1KMJG936Y9FESimGs4wk8B9TMutxQD0OuLLcYPd0Kh3wzzAOn2UlaV7S6Ty+xrXWqdGshRyPUg4GM64uNbm53mK5FZ9lhV7gAk/ignh+nnHlOSEdO3eF1GhPlLWkLlFKa1vvv09Sl1Hwg9tCPk+PhWBaK67y1UdyPP1ASMvBtvxpfOGTHefV54UQPbwDyquczZ603axtwp0qU7S7fL5nOh7KePvGS+cucDjfvzw9lFeAelNc/c227GLeuyVVlHkuppbuslynpdWPd8zzaUV8W1UDUi5rBwtE8Xlf/OmRXGvty7WcT2VEv3BxKyXGptMjIbdKCzF+cAce3ILhKZ6zeJ4iUCAsqoT+oRDIKJLPP9oTdbPReVwJjiJ5FZ1NRQVN6lWo+xje+rasB+zclevUaMuxDAcy9k/nMDjCu/I83eE+p5MRo5e+Tn18RO3gvuxsplPS6YzEFQTpBC9JSIKIEp9ZaXCFIc4mZNpjvrrG8qUNWr3OUy9rEkqItDaWk3HKr01+k/90/p+xb/dBwbrt8E/nv5cN/5cY+QHvJJrLTFka7rFV9DmNO0yVJigzls2Uu9EKEYblbMaktGTAhtPUtCP3FJOgzkO/Ts9MCbQiC2Lubr3C5OpX2T2ac60jmYiDaYbJM5JcAuDLuEYceo8Rz6ch1QG/HV3hpj7hStmntJr9oMV3/UvcC5Z+qMpg06R8ef6QusvY81pnY/jIFlzPTwD4Vnz1mZVPV5EpPqTGUFTajz9md4hS+Sx5nM+CRx+nqL5E+ccgnR7yq8hTHnlpeGd3wB/+mcvEgebN7T5vb/c5GM6ZplI5+b7WJCctRQrpZ9dy8ejWI8aznO/cPSYvDb1GTBz4HI3nHA5n+FrL9km3RqsWMprnHI9SCuPwlMXXmsJIFzyVmluWjv3BnDj0uLLaYLVd43g8B6A/SZkXJRrFejdhvVPDOccsKzgaZaR5yWRecDrJ6NYjtpbqJKHPJC2IAo8o+OBpUhR4zLJn05B1VXhhrHtfJJPUdSZEvsfLl7sX4/ULfCQuiOfnGb4vO4vrl0SZPHM+r3y4Olmrw0uvSRRPnsmIWLnHSecCSgm5OtiWTu1PMvbWWsjn+uXzuswoFhe91nLM770thHLxoldrSLPP1rXzx5lN4e1vy8hbe1Vk0D0hcJtX4GRfIobaPWj1hCweH8jHvvTVxxXNj8IiJA8nBDR8cie2+uW6cOaXpSi6924JAS6Lx4lqWYoaOhkJeRycCHkGIdZBJG8a/ECOtyyEtC4C7utNuU77DyHNhFAvwug9CTWXfNAhJE2oxRKZVG/CvXeFxG9dE+I+ncqovyzkWAen0BuS3HgedTphdnxMmI9pjQ7xZiN0NqemPJJuB2/jEhwd4PePaEUxde1T4FG0OugbL3K5lhBduiJf26dgbX2ZB3Gdb+79Fv/myV/hjnsPgBYN/qnyG/yK/Rqh1nyLiNL3iZoJA6/FPLdszA+5nJ8wIWRmFXf8HreSTeou57XpfZbMKS1TMsOnPRvha80wqNMqZtTNHBMm+LUGNZNxevc26xs36HUa3Ht4SGe8zdL0CDtPMUpzNG/wMF5mpJtPVf8ebdJJdcgb0Qa3ghUiV2CUdxb8/sPEZjGgbeds+53H9rwzHXBIk61iyN3g2cfihfI59utczU+ZPMURnticTPsMvWePvdFKCGdhPz3S+dhj60eyVp/1fgjJxkk3eWks97IR/8+/8zae9rhzMGQ4K7DW4aqqyydhAe3AKoeHplkLiEOP7ZMpaWGY5RIafzrJWGvXmOUFD48nbHRrfGFLfjYaccD1tTazzDCZFzgFxlUh6hoaUUC3EVIah68VWWG4dzDmH3rtEsvNiP5UXPjGiDnp5Us9PE9zMJixN5gReppUQT3y8JRi53TKLC+51KtjrePKUoP94fwDr1NWGGrdZ6MA7VpIpx4ynOUst97/vTOc5XQbEc3kwkx0gY/GBfH8vEMpcbZ/kLv9w5DU5c+w//R4pQU8X8ii/QED/qJYVLcFslRUwLKQ/vVL1wEn5KuzdN6BDvL8735fSOfy+uMRUqM+/M7flXO5/uL5i3BYPd/xvuSTdpefnTgv6ianVbf5ky9teVY1MCWicIIc/9134HAf1isSb4yMwwGe+4I40B/clocLQlFmrZVjnwzk40VZmZH8qnXJiapZq5+XBGglRjHPk+dQ5tzAVOZi5opr8ubEOQh8Ib1RIqP2WrNSl4H5HpQFQb3GpoLundtsL93gKExY2r9N0OpSj0MiV8r3wPIalAVeNscLQ8JmCzauQrMm4fXPvfx0wxtwarf5k0f/J35j8GsABIT8fu8P8o+Y38dX8gMakaPfXsZOQwIg8D2shdN6l9LzeKd+ibGK2E2hrxI8pZh5Ib/duMGgaPFz83vUsgk7qkZdOzaLIc5Y9oIWd5MNZskqTQdXJ9uossHvHORcOniHXn7KjvM49er4zrBZDFk2E74TX2Y36LzvPJ62o5lrn/yz+pXpHJvlkKkOn3qtMx0QmAldO/9YY/GHQY/Ncki3MkotHjtwJctmwp1whaF+tlYcD4gDicb6WCGQzwjnQCFrFoV9nCDq6ovztGe1nP8aM84JIXbw7fdOaNQCfK1x1uF5iuIRtqyo8iyr3VK/iifytPSvR77m3tG4MgZJMUJpHUVpqYUes6xkrz/lynLjbLy91Ai5stzg/pE0F3lVA1IziWjGPsZCGPhEvqIWKZx1vHcwYrVdY6WdMM9LHuSG62stlpoxeWnYOZ0R+R5XVhq8uT3gaJxyMs0oCsub26csNxN+4aV11jo1+pOMSVrQiB9fycgKUToXGaIfBd/T3Fxr8bt3pHazVROzlXWO4TTHWseNtaYkAFzgAh+BC+L504A4Oc+BfDITFCSDcWnlB3O3PwrnJNLn7jsVsateJepNIY6rm+9/MR2eVuP4FTlGY4TwLVz944EQwacRnnZPFMbR4NlNUp4nZPiNbwlZGxxX2ZvIdZpOhFxWMT00W/I8W9dkhWE+l/5yrYTkrW7Ic49HsH1PPt7sCFk0ZfUYnWpEPjzfsfV8MTuFCfRPhOmYypGOks/zg4rEpvL4zsnqgfbkftoDtBxzICHn8rkDIb7Oyt8P7hAMTwk8j+dfuIx9cAcvuITf6cljbt8VZf3mS0I+D3blvBcVoM7K1/BgB5wjTxocDOYcjuYcTvb5y2//7/nP3v7LGGdQKH7BfI0/WvwyHW+ZulfiAfMgYdpex5uPMMYSZVMa5ZxocsKJV2fH1TlyIak+/1bKDYy8Gm/Xb7DduUI0OmatGPIVNSBgwkFjjeOgycHc0dAB9V6dhDoc7+CPDmlOjrmrWwytwSoolce+Dlkux7yQ7XPkN88ilB77Nn6276QfChSgsdiPeCeoPmRs/jQc+U2+F13iC9kel8s+hfLwqr74e8ESb0QbH/im4snjUxrmhX2qYvhJ8OiZWipjUehRC3ymaUFaGhabER/1nEJahXgqOKsrnWWGerx4JlWtFciDuUfuB+B7qjICKRzihp/nsq8ZeJooCChKqdy0Tnrb57lh93RKryHkPQ59fuGlNdY6MW887JMWltjX1CKf0jpC36dd85nMSza6NZYaEZeW6jLWNo6ba23qUUgtlj73/rQgzUu6jYjD4YzAUwS+x2iWkRaSQTpJc+4ejnFAEnoMJhlZYWglofwqTQsmacGNtRar7Wev3ry83KAwllt7Q3ZPqzfjDhpJyGvXltjqPRuJvcAFLojnTwO6yzIa7R+/Pzg+S2UEvHH5mV5wngkH2/D2d4UwrW7KK5S1QoTe+o6QrfVLj99nMqp63kMZUR8fiJLonPwZjyGqybE+qWoGodz3yXxSY86NWHHy/pD7jStC1t79/nnd5GLfdGlFrtXJgUQrLcbqnSUZ+ze7573zi5pOOFemjw+E/DlXdcNXIfNFIeNylCi+fnBOTpWSdQrn5NibbSF+1grJzVKZPdbqEvGUzSWuKophdCrnuGikGp7Ic3ieXLfldQmU370HSYPAGTC5NDGBPFZR7c0W1RpArX4ey5WllSpu4dbrpPfv8L3aFd4pHH/t/r/Hf3nv/05aVRjeSH4Pv9j5Z0kGDQ7SAWOb4YKI/foG18sTwnRGoh29+QlX8il1k1GWJanT/OzkNt9XS9wKV6tWmepyOMcsM5jQx9bX2DfLbBa3GXlt+q5GNjdiHiqllvAER3RyxGpWcOzHDHLzWKYmSPf3ejliqZywH7Sf4Rv7s4NTir5X40p++tTRt3YWp9QnGvk/CHuc+HXWyhF1m1Hicew3OPHqzxzn5ICPWI/92Hjy4QJPoVAyNteqqop8NpbrEKLpVe/dPE9jSouxjvEsE1XTWXDu7HvMPXJfGdMLqbbOEYe+xGMpudH3PHR1j8j3MFaaiYyxNJKQ5zfbaKVoJgGh71Eax2iaM80Mk6wAB804JAo0o1lBHHg8t9HCWsfVlRY31+X/Pa3YH8z57r1jHh5PmGYl06yktI7BLKdTi4T4Wsd6R0Lx89JgrKUoJQng0lKdWW44maRVZWXIK1d63FxvfywDkFKKm+ttNrp1jkZzitIS+pqVdnLmwr/ABZ4FF98tPw0IQjEWvfktIYWLqKX5TEjRlZsSfP5pwBh4cFfIZvsRt7qu/n16KDubqx/gdD/eF3XN88Uoo6tYpvkEjhFSFD1xv6KqxQwq0uWcnOeDu9J1ns7Pye6Lr54nBHieZHkurwlRvvO2EMDOknzO4ET2Rl947VwNbnUl7D2MHs8sBSGQWQqvfh32tkXFXd6Ad74n+5jak2MPfMgLeZwiB78uamirKwqxVrLDWxNHOoc7si6hK8ORrrJTO0tyvRd5qOMRxHXZlR2PRElNZ0I66w25hp4v5HQykccpqvioogCcnOdCRcvnQkhbXSHfxkKjhWn3uP/W2/x/Tv9z/tLkv+I0OwbgWuMVXg3/OGvBlwm1R9EyHDc75KUlzWS94ACfr6UjvmoOaRQnpF7IwK/zIGrxwNZp5mN+b3GbrXLAYdhlFDYYRg2skrGoMfICr5QhthqjFNpTUAoB8LWiMIa8tJSzjMCWjFVd9uqqMeoZwVCiZUWu/Ljf5Z8JdoIul4o+dZs9njHqHKtmzKmuceR/giQKYKoj7oQfs7XrM0ZWOqwrKa2hLF3lBP94UIDva2kCAnAO4xYOfHfmnFdPeK4cVc0kEPiaJNCkzhJoTWGdKKgVMQx8jTaOojSoyrG+0jp/s7A47pevLLF3OuFkklfqqJDIdj3iS5d7rLYS9gczapGPXnxfAxvdGvVonZ3+lHd2BhwMNd2GBOK3Yp/t0xm1MEArRWZKQl9MRZO0YKkZYx383i+sM01LHNKV/mT80sfBIq/zAhf4pLggnj8tWFqVZpu9h+J6LguJ/dm4Io7tT2vMPhmK+vYo6XwUzU7V9DN6fG+1USl7B7syUn80n7TelNtnUyFgqxuPP+ZRVZO5UFZ37wuRzDMh19OxELDbb8Cdt+AX/pC47UGI7dIq/MKvwJe/IcR3NJDr0VuV2x513XeXRMXdeyC3L8LlTSnmqXZ1TaNE4o0abTF63fq+PLZSQjg9K6TPD+TrYI0Q5LCKzqq3xCQ0OBV3Rb0px2GtEOXVjcdXEsJIzvHBLcgy+f90LuR0eU1IME6IdFnCbCznsn3n/FqbEoJYniebyy5qFMl+ajqXPgPg/33/b/Gv3P8/8yDfBWCrcY0//vKfoZX/HA9PJvSnGY3IJ/BkRKplbkyYp6RWMSw1N0xOsrHJNFnipAyZzy0roz7rps9yOWLZzrhvJtjcZz/o8kbtEqXyKMqS0mhqocfEC+mVU46Mj7GOONTSWOMco8mcHoqMAG1KnBei3ON7m4sx9dPG7J8HHHhN3gnXeTHfp2XmzHSExlK3OUOd8P1463N77J8GHJw5wB99w/Ao1COf+zQYBxh7toLqkGpLh6NKNDojn49GQkWewteKOPLp1GOOxuIaX27FbJ9MyEopp0hCjbWSc1mUhtDTTOY5g2lGHHjkpWUwy1luJbx2bYm7ByP+zhvyc9NrxnRrIRvdOvXYZ38wZ6kZs/IU806rFtKqhdxca1GPAnZOJwSe7Nda6/A9jXWOwliWmglR4JGVhnrkM5jJDmYzCcg/bZn6Ahf4BLggnj9NaHXkz82X5Det5//gHelPwtpzE8zTsIiEck/8Amz3znctN68+fttsIrfX6nDvHVEDo0QI5YPbQoqW1+Gbvy4E7fRIRtKjvpCyWlM+XmTw8C781q/CL/7D55mdC9Sb71cxn3b8L74qBPJwVwi8UlUF6BK8+IoQtY1Ebrt/W0jh9ZeEIBeZZJvmmaiiRdX4pJXkv2xek/9P6nIe6VTU0tWt83Py/UrF9eTvk0MhwS+8LP+/fVc+HidU/XyyKtDpibL59ndEad28IiP5RUVnUUCtdd44FcZyHADZnL8fDfhT/+D/wm+cfh+AJa/J//LqP8kf/tq/wCyD1x+cCMlEkRtD6PtM0pJZXrCVD3hptk1H5awnmrbLUWXGC3XDldVVjgZT0ncfMCsgra2i0jmDoEXuFFv5MYWDbyVXsICvHGHgc9d2aWV9Ah1gtc84LbDW4ilopyNOvAb7QZMv5nuMdIJ9YpWkY2eMdcyJ9zndTVOKd6I1Bn6NrWJA10wpCLgbLbMbdD6wq/wnCYuR+Yfd/pH3t/KjY608lqvG6+oRmXPxY+JpJaVg9Ygk8Lmy0mSrW+P2wYjhNCOOJW8zK0p8rZmkJcYVGGuJfI8k9Ekin5NxSqsWEHg+L1/qcGWlSSsJ6TYi4sjn7e0+1jra9YjcWPonU9q1iFeuLH2oGhn6Hi9tddjtTxnPcxqJj3WOrDRkRUkzCWkmAVlpzlYTSmO5vT9kfzAnKwy+p9nq1bmy0qB14UK/wI8AF8TzpxF+8NGf80kRJ5UTfPZ0EpfO5Pb4ib01rcU1fu8d2QVVVbNSWVTE7QV5kTjal8cYnIg66oysCiytipK3fUfML53lqut+6Xx3NUokZuhwT1zw7d4nI95xAl/6mhC28UCOq9YQY5Tvn5/P1edFHe1XWap+VUPpB3JMv/W3RZkNQumTX94Qcni0L6Sz3pRjzHM55yAQ0huEcv7Wyt5qUoPrVVD/8oY4/e/dkscaDeScL9+U41oE3Cslx9XqCvEdDWRMn2eifG5cEVV6NuGd/m3+zMl/yV+dVZ3qOuKPdf/7/AutX0ZdeoWJF6JVga81cegDWbW3ZtEaNr2c1/IdjHIcRD2WWh4xllMVk5yeslaLaPgB29pyHNUJlUXh0DiMF3CsmmwWA+7Hy5zqBq2aTxh6TKMVZklJ7+A+RamZeSGUhlo541THvBFvMVUBa2bCphlwquvMdYjnDB0zJ8Dw3fjSWQj7R6lnPxIoxYHf4sBvoaoonk9tF/unBI+ST+x5YkHoiSnIWEfoaTQQBEIeb6w2eW5T9hkDrVnr1PjWnSOi0Gc8zRnNC+a5wVqLVmLwWesmrDYTrq+18DzNy5d6XFpqPJalqZXi5UtdlpsxOycTTicZfqC5vtZjq1d/JiJ4ebnB7/3COqNZzmiaUxpLbgwrraRqFlIMpiVXVpoMpjnz3PBGLqQ0CX0KY3lru8/+YMbXbq5c5G5e4DPHBfG8wKeLpC5k6+47QooeVT5NKUTt+kvvN/qAmGnWLwuxm46FWGlPiFWciJP8xktSYXn7TVHtLt04fw7PFyL18J6MwjevvP9F2g8AK6ahyUgU4E+CRcvRk6rp065H8hRFzVpZcTjaFbWy0To38kSJkO37t+TfgQ+pk3NdWsEpxbS9SlEY/INtanENr/dIgH6zI6R1NJDHGQ/PzUunh9Jede0FUTsnY7nmSU1I59vfhf0dGA/YcRP+XP+/5j+wr2OwaDT/441/mD9943/G9EiRlGPGtTbKlNQDJU0tE1290Eubi3Gwlg+omZx+c4WW7zFXUOBTU5aBrlE/OcFXEDdq5IcZKp9TKB8bxmjrSF3AkpvQMSlZo8NKs8ZglkPs87q3hYsVW9kxdZtROHg9WOeB32XoJWjg27XLvJAesGZG9IoZFhh4CXfCLR4E5+seTxLOZ7eyfDb4vPSnfxYIql3JD1M7nwWLr+EZ+Xzki6qqDFJrFkamKk2g2t8cTHL64wylFa6KTjo5mTArDM45VOW697Qm8DWe1lxdbXJpWdIejscZN9Za7zsmrRTrnRrrnRq2ct2/r372I3Bzrc3vf3WLb793TLMeMsuKMwJ5OsmoRz6BrzkazNCe5mavdVZ1CVKpuduf8vZ2n597Ye1jP/8FLvCD4IJ4XuDTx7XnZYfwYFcITRAKSZzPpN/86nNPv19vRYigMULKDndlp/Pk4Nwd/vVfEhf3bCyf/+RI3/chCuG0IltPoiyE2FlTZWj+CDAawHtvyvU5PZbz7K6KUrm8JuQ4rsFLXxaFE+Tz0zmzWc72KGMwSWE+oXO6R6xD4syxEknTCkEo6vH2XVldAFF5lZJ1gC+8Vu2iXj4/psNd+J1fg8EJE5vyFye/xr+d/zZTJUkBv9T8Ov/s6j/BpeAS/lSzkh0yMB7JwX1aD9/GKVBhl0HhoVA040B2LkvLejnCJUn1YuhhfM3Qa1IfHNInJpjO8W3JwCXEGDyT8zBcpqi2NmQ0qmiEHo3VFkrBySSlKC2FUuzrNu9FDeqeIrOW1OizLEcLTLyEbyZXadqU2BUYNAMvofwJ3o/8cYZXMcBH6zEXcUjPAl8LkZSWIEtWilIsEVCKRqBxKDylGGfF2RslGbMrjLXcORgxTgte3OgwyQre2x+hgG4j5KVWm53+nKPRnCT0WG4lNOOgcrFLvmUrCTgZp2SFqaYAT0dpLHv9GdsnE+aZ1Gxu9epsdGuPEcWn4aXNLr7W3Nod8O7ekIfHU1CWZhJSiwJ8pajHAUvN+H2PpZViuZlwMEzpT7Oz+KcLXOCzwAXxvMCnj7gGX/warOzCzn0heHFN+s5XN0UtPDk4D1ZvVKpAFEvO5+u/KzWbZX5uqplNZOfwoOqgL4pzd/qjqLdkp/NoT0bUdc57460V08zyWjXe/iGuHHwQJmN445sy5k7qMo4/2hOCODgWY1atMlO99Op5IH+tTvrm99i+dZd5ltMNfXS9QXrji+RH++xuH2M3l1hfdCnXm7LLe/92Fbz/gqjBy2vnhijEFHGwf4L3q3+N4OAO/3H4Ln9h9rc4MCNQ8DNqg39d/RKvtH8JSw2TnTIalNRrHl0Mo8N9ZlENzzmS4/f4BS/CRKvcp0FWWDytCD1NoH3wPNpJiHGWHa9L4ka00hFJYCm0RzQ5oefF3I277KsmyjqsswQYSgdFHPPcSrPKKHRM0pxZbsitxTnFsATr5AVWLf7jhLAopRh6CUOevZXnR6V2ft6U1h8GPmitQdS/89sXH/M8jS3tM12XJPIJtCYrDQpxYedFiac1oa8IA5/SGAlRdxB4GuNk9O6cIysdcSCB8GlZ0p/mRIEkJmSl40anRi0OSUIPB6y1E5ZbMaeTjNEsZ6kZn+2PftjxpnnJt+8es306JfI9Ql+zP5ixfTLl6kqD1659+L6npxUvbna4stzgtavLHI/nzPKSJAxoJQFJ6PPNO0cfGHUUBx7HxpDmz1abeYELfFq4IJ4X+OEgiuHyDQlcPwuud2Lu2b4L0yoIPYyFZG1ePR+1H+xI7/tCKQ1C2LoukT6zidyGk9uiJ4hEGMHGJekuPz06d7bnVU5lqyMff/E1eb7PGjt3ZQ0BRGUEWT7rLouLfD6DL31drtujtaidJe5uvcJ7kzqXapqp51HU25gooeN9l/b+Q3ZPQnrNmHChbqSpKJuvfUOu3RM4HqV8++4x6r03ubfzN/g37d/jbhWNdEUv8yeb/wh/JHmN+vEOw7jB5NLzgKKYzpgc3OPqjUu0dMRwlmGsoxatkUxOcad9iqBN7gUMZznzosm18ohZIyAKfQaTjNPCouobNFZWcJNDTlTCdHrMjm7ywG9Rr84hL+CSm9KPuwyjNoNZxmCaodGUzmIXdmf3eA6k4/3xOAsstJ/Pq7/3J510Au/LznwUznEef1TB2A8mnY/Wm2rE5T0rSkprUShi31U99Y7SKlwhu5mFsQSeIgw0pbHUwoBZVkosEqKCvrc/ojCW1XaMNTCa58yyksjXQlitZZKWLDUdXqWwAoznBcut6EO70t/ZHfDwZMrmE+pmXhruHo5oJgEvbXU/8P4LJKHP5ZUGl1ceb7CaZgWeVpTGPvU4SiP7qR+lrF7gAp82LojnBX640BoWIdd33oZbb4hSubwumZfbdyVfNE6EqC6tCTG88QX5PGuFTC4ijZodUQg7PVEN683314H6lQnn/m0JTI+rPctWTx5v2D+XVj5L5Dl8/3ckIqndk3MBUWHns0qNDKHVltrLw13mBk69GgWat/dHxMtrpE+MxcaXX6BpCrz9XWZ+Stiq9jXD+Dyn9AmkheG794/5nb1/wH9++1/lW+ZdAJZ0g386+hX+QPEzXE3aKN/DhDHBZMB04wYAjfe+R1EaTJiwnIQsN2Mcjt3TGe9lIYyPaDeG+Emdl9OHLM13WZsdYfIRR811UhKMhfVOQo0JD1af57/VlyG/y9XJDlt2xNQGYA2JK8nqHR62r+ObgunDh6xYR5+QvVKjtTrLYPT1s4Waf14J508TTBVfpDnPV118XXxPo5WitNJTbnl87P4kLPK1X7zRyAqLw2EsaBx5YVGuqt20BufJKoa1oDxFUVpQMmKPAw+FRDg5J6qo1oost8zykvFcOtqbnYR6LON0zxiMhaI0JKFEiBlrubLcrJzlj2Mwzbh7MOLX394n9D3iwKNTD8/UzdD3aCYhD4+n3FhrfeLMzXoUsNZJuH84oR6/f7oznOW0axGd+oWz/QKfLS6I5wU+G0zHEhy/yOScT8U8M5+KuWY2lt3O431RRS/fkB3OJ7FwofdWqqD4HXGux7E4tkd9IZQvvCr7n7NL4trmEXW11RHyORo8niX6w4RzsP9AVM5m+/Gc0qQujvfTI1Fw3/g2Bjg6GXM6yxj7NU66l3grq9FrxkSBTy06/9E1cZ3hc19mGPRYaxho+PIcKxsyXn/Ki98/uPtd/uVf/5f47cO/CUCNgP9F8w/wzzT/IKENeXg0YZ6VRL6H0x7aFmdJ2/5kQB4ljz3s6STj4fGEKPRZbtd4pTwlufNt2tmIzCo8HPXhAbXhIXFjlUO/jS40byUdXnddigTm9SUy7dMtZ0TpiBnwfdViotpsnuzxQtmnSYmnFRN8bts6b3irGCUvqj+EuvAL/JAR+JpAS15nHHnUI5+lZkwUeNw9GDOZ52TVJFhX/3H2caVUIePy0PcojCF7pMZTaVmzOMsCdeBpR2EcFiGpnqcIPEVuHGVpUEpUR19pGnGAp2VX0jrH8Shl+2RCtx6y2kqY5gVpZjgczVFO3tBN0oKXLnXZWnq/qfDe4Zg3Hp5yOJxzOs1oJQG39oZnGZ2Ln+tGFHAySZll5Q8U9n5tpcXhMGV/MGOpGVcqrWM4y8hLyxcvf3Jie4ELfFJcEM8LfDYYnEgm5VpVlXlyIKRzEXdUVlWSz31RRun720Kcnow7WrCLZkcif+69K2R13BcHfKcHl5+D/YcS3n71BYkiWvSlJzV5Ndp/KIrpD5t4OicK7d5DaTA6PZYROKpSayv2FgSiAB/vQxSxHa/wkAaNVpOlcsrK8A5Db4vbww6e0ryw2X5sfFZqn3F3HffiBnSfsvtaYX+yz5//O3+ev/Stv4RxBq00f3T5D/Fn+9fpNF8C7WGVIw6l+aRTC/HKjGnz6tmxTo2i7itqoRA+h+NolFbd0D5BkfKF4zvkZcZx3GLmNOOyZCWKcPM58XTEoN7lVvc629RJTvs8b+8S5xPywjD2Eu5Eq8w6a5xMUr48e8DV/Jh5UOcoaFAYR93lPDc/xPcLvhlfJnPeT8WI+icJFshKCx4orVEotPbISsdWL+FwkGKNxWQlpUWqM6sff4WonAuCWQs9Vnt1do+nlMahcJRGlFJn7ZmaugilPysyWnzcOZyzlRlJPrvAcDCY4YDQTwk8jacUp9OM1x+e8tx6m8T36NRCAs9js1vjxa0Om706y4s9z0dwPEr5/oMTfE+z2avTn2a0ayEKxekk5e7hmJe2OniVo1/xg09kllsxP3Njmbe3+xyNUqwVF30zCXn5eo+rT4znL3CBzwIXxPMCH4zxEPpHMiIOoyr25xNWpZXFQn6Q0PRhH5LGOfHy/XMX+tZ1uPX60+OOxgM5hu6y7JF+6Wti2MlTUTibbSGY996V8bxST48z0t55XeQPEw/ek3NZzAFbHVFaD3ZEte08kjM67IOzTNevc7A7ohn5RKFPSUQwGfB8eshevUV/knIyjtjsnZ/XyTijW49Zaj49k2+ST/i3f+Pf5i/+xl9kWkwB+NrKH+BPfP3P8oK3xvKv/xd4wyOy1gra80gCj3lW4AYnGC9gcul5nHMMZzk26vLy5AEn4zlJ5BP6HtO0IAk9dJERjE8Jsin5+nXaKNQ043QCD1ydwDkiXTIPa9z1OvROHnJ9/BDP9xn5CblTJPMxP1NO2PZLvDJiIz0hby9htIfJDIV1DFwAYZtLWZ+HXoeHfueH9zW8wA8VmQFtLPUoIPBgmpa8ud1nkhZoT+NVAZxaKUy1GJpEHp0kYjhLKQzkxvHgUFR6rR+nbE8K4YsfRcUiWN5RuAVZPX/7Uo88SuvICsM0LWkkPhu9OrbqSb+1O+DySpOv3Vjlhc0Om73aY2TTWEd/kpFWYfPbpxPywrLSSqqdUp9ZZmjGAd267EqP5nn1/zndRkTzUwh4X+/UWG7GZy5739NnqvIFLvCjwAXx/ElHWUqNpTEyxn0W4miNuMq374g6p5TMt+KaRCFdff7jB68HFSFyVo7JGBl9L1AU0ieuNaysyW7m0a78O6lXGaBDuf9zLwvpXKDRBJ44r1pdSOqHnWP0Q44QGQ+qPNNE1NeykI9FEZyeyPn5Ve/7dCyB91dfYJRb8tLSqp2/6BS1Ft30kMtBzpup5sHxmKVmhLGyMxYGmhe3Ou8bmxWm4N/75l/iz/3dP8fB7AiAn13/Kn/yG/87mD7PZrNGoTUHN3+G7pu/iX+yD0FIo3CsetKNfm/9BXa8HvPDMcNZTj3psT8+JH7nPbLWEs1GQmEsYVngT0/J04yZ9RlOc/LSkhfmLArHxHWibEB9eMS06PBausNEhaS6hqcUudPMoxAdGC5P96gHLTqJz4HymGeGtDRY40BBEkXYTLNejtn2OxeK548xHDDPCgpj8DTMc1Hj27UALxdlMwg0iVJYnKQUzDOmmRWjEqJiiiNe6jAfq0d95LmUBlWxUa2qHWGEvKIgqD45DHzSwpz1pstjKlCObiOkV495aavDSjtmMJM3sSvtmND3OBmnvLnd53iUYqyQ2ocnE5abCc5JxeVaJ+HuwZi5ViShj3Uwy8pqv9VxfbWJpz+dPXR5vg+ehFzgAp8lLojnTyqck3H1g9swGlZEK5Lx9fUXpWnng7B9D957S/YhO48EpE9GYg6K4vfXWj4KY0QpnU0AJSpkd1mI5bAvf3tVK9FC6TTleRi7Q1zdK5vifj89lM9vd2X3c3Xzo89/dUvG23n2WHzQ2XnENVFwf5g4ORTjUKdaL2h1ZOxeqyo/D3YkPqm7IuS53YPNq4tVysehNZ6Ga72ESV7nZJJy/3DCvCipxwFbvTbNRwwEzjn+6tt/lT/z3/wp3u3fBuBmtMa/tvbH+MXaz3HwwONbbsTu6YRmLSTV67TWvsLm0R3qsyGNKGDj5hZcfQGzeoPY+by90yfwFI16i9PoZZb3b9OYD8iHR+jCMg1CdqMODXtMu5xzMs6YVc5aUNRCj8xZ8jSjCCxLxZigLNgP6lAaVClGE89pxi6kXk5o5CfMQx+tNfVYU0wtKEdpYZaWhEoT2vyCdP6YwwGzwqIKe0YYPWXIS5848HGuwFqHF3qUxpBn5ZkhyTkIKgKplcJaJ13s1WMvHPQg43nP0ygfitJWeZ8K5WnK0uD7nsQgOWhE3tmjNOIAa6HbiFAaIt9DOcfrD/pnsWEOx0or4dpqk7d3BkzTguWWENHSWO4ejnlwPKGZhKx1EtbaNUrj2B/MmIzmjGY5hwOfZNXn1Ss9Lj1lR/QCF/hJwAXx/EnF7n146ztC2LpLEmeUzsS4M53CK199+gi6yGHnnqh0T1ZeNloynt6+J7uaT+tjHw/hne8L8bSVK8DzhfBuXYe7b1dj9hqcHIl7O8+l8rLdk88fnMjnf+XnZYSezmU03mjK38+C5TUhrw/fk/OsNeTVZzKS53z+S+f5oZ8UWSrH5wdPv5bTCXiPuElrTXHz728LGV7dgKgGa5vyWEEAQUBQufSlHUUYqDLCyrw4oaEDeRH2FE1f8gTvH084Gad84VKXvfx1/sX/5l/kNx7+hlwKv8WfffF/zn+v84c4PMk4yef0pvd5pV3y16ZthtsDVtsJaecKR401WuWMVhKQXdvgCy9eJj2a8O6DPt+7d0pWGvxKoYEtaq7JUlziEs2BCymDiFfUDl5+gjEzDH7lEJbMoyIvUaZkr96l4XJStMTqLBQqDR7VCzsRSVmAKat4G1GC5bEUubH4pmT85BuLC/xYY5HjmcQSwZYbcZ076xjPc4qFWrn4fISoLvY2rXtc8XROyCdAFPioqpko8j08T+FQJL7H3Dp8LXucga8wVcYnSORQXu2Xe0phjaN0llYSsN5NCH0PYy17gxl3D0fEgc/VlfhhXW8AAQAASURBVMbZz6/vaS4tN7i9O2C3P6XXjAg8zeXlBkvNmOPxnNNxxteeW+GlrS6Np7jQL3CBnxRcEM+fRGSpjHiD8JzMgZCjhdK2vy3K55OYjOTP0xzlICPj8UBGw0/uX2YpvPVtMe0srZ0HtOeZVFhaCy9/Bfa2ZdzeryobN69IfmdRwPFB1T3+oozZ49rT6zU/Cp4HL74i5Hnv/rnbvdGBS9dg/dLHf8wFZhNx6B/uiGqrfVkPuHTjcbNSEIB9pD1JKTnPIILTA+l69wMhxc+9LNfk1uu0e01qoc94XpyN28NJn7zeYRQ22NkfUI99Li83Hhutf//gTf6N/+Lf4jcPxKmeeDF/Yu2/y5967Z/BlhFv7/SJIp+k2UVlMUvjI67FTY6TGkppVloJ7Xr7LF7ldn/Gwet7jNOCw+GccVoQepqssPQnU+LQY+w3eFBInExeGubZnFnW5veZPYJiitYhLkhQSlGkGav5gEOvwRvBOlv5KT5GHMWlMAUFlEbC4S9FMG+uoKYjitGIsY6BhTHEkpicAs1B2P7cZ3Ne4HF8WEi+0gpjHPOshNA7I4lZUZ6RTvXI46AkTN2W8uZmMS1YkE919nmiSpalleaiahe0Hvu0k5DSWIrSoH0PrTSFccxzQxR4GGMx1pIWhtUkZpaX1MKAKJDKTABPa5YbCW9vD3huvXVGOo21DGcFs7wgN5Z7h2PW2jGbPZk6hb5GKcWr15b4yvWVT228foELfF5xQTx/EjGoCN3TRtJay6h7/yFcee79qqVzskf5ZDbmo/e3VZfhkzjeF9f2op1ogTASpe94T6ocX/s5cbRPRtIL3j8+J2Hrlz44Sunjwg+kvnPrquRkKkR1fJpS+6yYjuH1b4qi2+wImS8LySPtH4vZqbMkn9tbkSzRRQg+VDus69Dpiqr8xa/KzmwQCnEfnhAe7HE1DrkzLBmdTGnbOVkYs9O6zG5/TuBrbqw2JT6mtOyMdvmP3viL/PXtv4LBoFH8kxv/EH+++QfZbGyCV+O9/hRr3VmLiY0S8oN9GnpEsnmD00lGpxGy0joP5B/Ocnb7M756c4WdkwnOWZpJxPE4pTCOwMBSM6SMHHunEwbTHGMcw/Ya296Ea+M9aiZHF2O0teiyYKAjfrX2IgOdEPhNnsuOUEWBUz7nr7cObQ1pVvBWcwk/jFkf3qXnzcmjBqkyhNmcCMMb4SqHqoFX+dYWIvsFfjRYZHJ+FD7oUxxgjAy4SyvxRK6SLfNS7qWpTEFUv4YcVRC6Iy8cnqdxzqKRrR+qHc5AQ1YarAWtHNYpPOXhe4rBNDsb3dfjgMD3cFkhHe2lY+agkfi8uNmhMKK8F6Xh8nLjCaIoxzjP5Q1nVhjuHY44mWQ4JwT6YJDyu+8d8/ysoF0Lsc6x0a3x6tWlC9J5gZ8KXBDPn0SUhbwCfJABaNEIVBbvJ2G1uiiMs8nTR9HTiZCtp42Wj/bksZ/2vH4gr0iDYyFe9ab8WduS58oz+ZxHI4Y+LQThOfH7QfHwrpDO1a3z8wxCuWZHe6I0v/YNua27Isrv7TfkutYacn7OyZuDK8+fk06Q3dkvfg3ad+ntP8S3Y05nmsNgg1Fvk2BphRueYvtkShT43Do44D959//Kf7vz75O5FIBf8l/mX/P+O/zyfAlv7y40jmE6JnMtoujxvd7SgWdhlBYMJil3D+V82rUQ39OM5zmB5+EpMXt4WpPmhry0xL6iP03JSkMcegynhWQfeh4jFfOd5g0GKmZpekSznEkuadzgu/EWDwJR4Y+8Bg/CDtfzE069OlMXEvrQVoZLXsaDcJl7ZczEhqzVHTfdgE0vZ1YWHKiYe0GPB0EXpxSlPR+9XuBHh2chnR+FRx+ilFbLx5qMFqUBqlrctAhB9bXCOog8hcbH9xVpUWLMI++jrVRjhoFH6GmurTaphz7vHY5ZrgVMM8MkKwhKS16W1WNbYkqaccLpJGU8z8kKw/W1FsvNxw2KvqcJPEWaW6xz3D+acDRK6dYjfE8akgJPU4995nnBzfUWN9faZ6akC1zgpwEXxPMnEX64kA6eru5lqahtT+sqj2syDr7z5vs/p8gl6P2FV95v2AEZFX+Ymqj10ytIao0PNzt9XpDOZbze7LyfXCslGaInhxIE31sWBXgykN3a4/3KTBUI8X7pNcksnY7ltulYCOjSupDRKzdpZRktT7PuRRgn/dEPj6fcPx7w73/n/8ZfufPvMi5PAHjZv8Y/E/8Rfu+ohp8k2M1NiaEZ9mHYp5WPyLqXIK5WAay0uTycGcbHQ8LRKd5McTRIOGwvsb7RY55buksx1lHFJmkmWcEkLUiLkrywzLIS6xxZYStlyaBwHKqQHf8ycdIjtiW5Uwy8BM/3oFIlrdK8mVzCaJ+NfEDHzPAsBLU6p0uXOWleol3AydGEB0GHQ79HgxwXQN9oUvP4G5RHv7MSm7NRDtkohnjO0vdr7Pkdjr36Z99YdYFPhEDLQP5sp1PJmwvn3JnauaCjpXFopYgDTRz4ZEWJtYpuPaY0jtEsQ2lFM/bp1GOaNZ9ePSQrLOO84MXNDkorNPD2zoDBLJM8UCWj8LV2nW4jYpqWTOYFSejTTEKOxymeVrSSgDj08bSiEYegYDjL6E9S2hXpdM4xSnOWWjFf2Oqy15/RSsKnBs3/uMFYx/FozsFgLobHyGetU2OpGT+1vekCP924IJ4/iegtQ7Mle43d5cdvM6UQoesvfDBJvPqcjML3HlZxP6EoksaIYefyjaffr92VYPinwVl57vqPAcH8IBSZkMenkeQilyrM+++eO+mHp0JSv/R1IfvzqfwxhYz89x5K3miRy96nKWVkv3ZJiGkVfbXQVJxz/Nr2X+dP/8afYX9+D4CNcIt/PvrDfKPzy6yd3GPu50x1RGYsQWdZiKcpaXqK/vAY1+2glCIYnXCqE0xpePX4DRrZjI4JCVLF4DTk6HQT4hVq1YtppxYymeccDcV96+lFRbpDa8lZtA7ywmGMwfdkF3OsE0aaszgl7RSekhd066BQAd+LL3ErWKFt5gQawnYbv95BWcW8KDCLwG9nKb0QBRTGfOCeYNvM+Mr8IUtmQqpCjFIs5VOu5Se8Fa1zO1y9IJ8/FliY685H7L6nKKyYh5wkG7HIlS+NJU4CaqFHtx4Shz4vbrY5GMwZTDOG85xrK/IzNZzn3DuakhaGWVZwqWdZasWstmJe2OowmucMJxmNWkheGLqNiCT0eW6zzf7plDe3B3z/3gnNWgg4osBno1vD14qrK01qkce7e0NG85xa5DPPS6ZZQRIGXF5qoLWikQQcDucYa8/2RD8IaV7Sn+ZY56hHvgTPf06+h/PS8P0Hp9w/knWcwPPIS8vt/RE311u8fKl3sUJwgcdwQTx/EhGEcOMlePM7oqY1O0Iy07lkeq5uiKr5QYhiMQGtbooRKZ2JSWltS3Y1/Q/4tlnZEMf7ZCgmpEcxOJXR/VN6wz/3mI4rB3sGaCGKjyrBeSbu+f6xzAbDSKoxjw9g08m1S2ryhxUxZ739HXHot3uPxTqVec749i1298fsb75EPQrY6tW5O/kO/9Kv/ukzp3rN6/BHrv5z/A+j38Olo/sUJkNlc8qwQRRoZmlJo1WXOKzxgKjVozE+YfdhQi+ASRBzHHf5yuku49mcfrOH166jcejJiO7uuzSfi5jTxTlpQDkZzwF15gr2tCIOA5xzlEaL4xzZzZNUGoeriINy4PsKT2k8HMY5rKk6sYGpjpjqSOoP59CwMxyKKFAStF2UEh5u7dmu39PgOcMr6Q5dM2XH71bPD32gYVK+kO0z8hIO/R8w0eACPzA8df6G5EloKke5UjhnKOxie0jhK1kzt1ZYp3Xy+b1GyAubXRpJcNaZXo8DWjVDHPqgFc0k4NbeiElaEIfeGSk8HM3oTzPy0rDRqTOa53QaEUVhmWYlnqc5GWekhUEpSXVIIh/nHKGvmWUF3717zHMbbX7ltct0GxHOwek4I80N2lOsd2qsdWpnjvVHXfcfBGMtt/aG3DucME0LHLInutap8fLlz4f7/dbeiDv7I1bbyWOh9LOs5O2dAfUo4Mbaxc/bBc5xQTx/UrF+WWKMtu+Ke9xWAfI3vwCXb350eHoQwsZl+fOs6CwJ4X3vTQlHj+vyW3U+led+/ktP3w39vGI6hnu3ZHczT4UojvrQd3DjC+eq2dHeuTmqvSS5pfvbMlIf9WU8f/nm+ePWmvDu94XEP6KeFsby3smM4cwjGu/gWpt882iP//Xf+gvnnepBjT9685/i5fgfJVB1ZsNd0sIwNzltY1lKSoJsijoZg+pgajVGBPSNjytmTOYZ77LKnu6yPtqjrg12YwtPK4qKOEaNNg1fUZsdsK+v8PB4wnIrppWEFFWXNUAcePgalJKO7NIIkfD1eSTOwoumNTTjgNyIWUN9gF65GKempbhCanHMasfncAiTrKycyx+M5XLCSjnh0G+dkc4FJl5Ms0i5VAwuiOfnAB/2lQwDRRz6KKXwNehCMjZDX+NpjXWOeV6eqeH1yOPqapOtXh3fE/VwlhU4pKu9MJZ2LeTu4ViqYOshWsnjxIHENmWF4WAw51KvjjWOeWEYzjICTxNVo/L39ke0agFLjZjray0UYsKrRQFLzZhuI2KpGRH6Hq9cXaI/yWjVQ+LAe98O5zgtuLrSODve910f53hre8Bb231atZCNXg2tFPO85P7xmKw0fP3mipDqHxH+/+z9aYxkWZ7dB/7uvW+13czXcI81MyMzq7KqurZeis2lmy02RUxzCEGkOBsFkE2QAr8MWUS3uj+IrCIgVg+alBqzNIckCEEzHwYEIS4SxAGnSKopqUviUntVVuUeu4evttvb7jIf7nMPjwiP3CMzssoOkIgMN3PbLd555/8/52Sl5ubBjE4jeqgJyZP6gGt7Uy6uPvp5LvHjhyXx/FHG2jlvbplP/dE/Sd//th5rvQKolCdeF5/2yubdW95AA3D5Wdjcvj/a6UlHNofvf8Pva3b7/j+tfSD8nev+Osdk8nDPryGEdTYndWJ1EHiSOR7CeubJN/hRe5E/FBN1ZzjnYJzT7/VYHL7M3/7Bl/hHt/4hxhkEkj/+3P+J3/rffIWDw5gf3B7SiAOKsCSY3WJNWtbdnHA6I7OCOAlhLyNfLLjbv4IerJFsXKTz3E+S5bD/2m0GB2Pa22usdTo455gVFdNFyXSaMRtPOXf3BqmRTFvnuDkfIKQiCCSJVTjn42PCOgpGFOI+R7NEYIVXNAMlSUJJtxGxO859PinikUpPM4mYl5pICaZZQV5KBI7oOHbpTdBypa8+FGevkcxlzEDPkM5iH5XcsMQHA+fd6cc5rsfvbCQ9aQmU/0C1WjHzwmCtIwyVbybCG3XA0QwU3UZEJ40ZLXzlpKhXQdpJyHheYqxlrR3z6t0JaSiRwhPJWVZhrEUbf9I1mhUczgoqYzic5iSRYqWVEocB2jqUEAgnGM1LWnHAoJ1wfGpurK3H+iXr3ZSVdsK5QZOd4Zxm//4T7smiJJCCCyuPXj0aL0re2JvQb8X3KZtpFLDVb3L7aM6d4eJDVROnWcWsqNjqnx15105DhrOyJvvLvN0lPD4Q4vnbv/3b/OZv/iY7Ozu88MIL/NZv/Ra/7/f9vg/irpeQ0itw7ze0ht1bcOeGJ2lS+tH8uQs+DH5lvc62eRN3/ZOMnZu+MWl9G3A+GF9XtRP/IszHMD70jvzJCLO2CRvbqO7AP+8ohqLwimY2h7IkV14xVIsFqQoQQeDNWsZSIDmYZIig4m/t/AP+q7v/DQvna/g+s/Lz/NL2X+SZ/vPEDNjsO17bHdNOQhpbm+jJOv3Xvw5aU0mFiRvErRidL1hYSbuY4oqE4cWriKTBZgLBVpfimuHWKKeaGKZZ6esB8wUX8gPaJqPvcqLd6/TyEbN5F/fspzjY6rFzNKeRhAi8MpmXXgU9/s9aH1tzvIPmKwIVjcg75HPjR+3gFc5jXbLOmEdbU1dtWpQEHUi0cW+qkB3DR8s/GgKHFRL3ptda4oOAxVdXnhamFZ50WguZNjSTgM1eE6Ukw1lOVhryylvd4zAgChyr7QQHXFhtkpWG0bxgUfrx+KzQrHYS2mlIUfnMWIdgXlQs8opcG9I4pN+IKIxlb5zx+u4EVfdoDhoJaeRPYkrtP4/HHRbmgTOnYyXW1j9XUvDJSwO0sdwZzonq3vm81MSh4oULA9a7KY/C4bQgK819EWf37kuQRoqbB7MnY4z9Vl+8JZY4hcdOPP/+3//7/MW/+Bf57d/+bX72Z3+Wv/23/zZ/5I/8EV588UUuXrz4uO9+iccBreGlb/sxfhR75c5oHyW0d8dnU/ZX337L0JMGrX3OaaPt91V3bnrySC3LhJFXMy8/x6SC+bRiT3QxQ0crG7PWSegNVhE33wChKOdzDl+7xpELyVREms/oVwG9V1+ikURgLYWx/Lejf81vF1/lQI8BeKr5An946y/xbPsnsc7x2t0xv/P9O/z01XVW2wn/44s77E9yVuaCPzgzJDZhkE/plRmBaFEEEbO0R7ecMwnPk61sA343bmykbxXaH1I1OmSVwVUlT813abicRZjSThIO2xuYIOaynpO98SKffurT7I4WlNowaCXoucM5TRIFzHNdK6EQSEmgBLbOXxzOCvJSn8TinG6bEXCSw+mArLQnyqlwUFT2kbuAD2IkUyqhiG1FIR/ef2vZgh/Gmw+N4Zf4YPBg0L+rf5ZEikEr8vvDDpSQpJEPZ7+y3iaNAg5mMeN5hXUWIQRxqFjkFbuTjCQMkFLQbXiCGYeKy+tttvoNjHPcPlzw0u0jjHFEEnTtjF/vpgxaMXEY+KiwytKIAsrK0kwDDmYZ40wShV5ClVIihaDbiKj0/Qkd8+Le3ugxOmnETz+7we5owe5oQWUcvfU2m7Xj+82greXNPDmhkpTa3Ndw9kGjk4a04pBp7jNJH8Q0q/x1noBd1CWeHDx24vlf/Bf/Bb/8y7/Mn/2zfxaA3/qt3+Kf/bN/xt/6W3+Lr3zlK4/77pd4HNi95Ulnf+3+WKVmx7vaX/k+fPZnH21CetKhK9+ipCtPOq3xqrFU3p2fZbB/l8M7O/zr1jP0VI/uYortJhxMMo6mOef7TbYbTfRL3yMrKsrGgoGEAEfR7DJxAWJ8hN1Y56vBNf7Tvb/PK9UeAJfUKv/71T/N6rn/A4M6jqQyFiFAa8vXXrrLvNCM5iVCQIOSu2GPSdBgW2ZcCCtECoQxRWaZdzbRaRtXG6KG84K9uSYdbNO/9UPGugEI+iajqTNGUZN1V3Ake4i0QV4aRt0BzfE+W3bKhdUm37k+ZG+cgYMw8GNzpUDVI/jKWKyTJJEiCfx+ZlH5bEMhIA4EZVXH4tQvexwocm3Qp1jm2yWcxxiqJneCLperQ+6KDpXwn0HhHKtmxlxG3A577+njscS7QxpKTH1GEYWSOFRY69DWsd1v8KlLq3QbEfuTBZV2JHFAIwrotyJCpTiY5ZTaMM0rlBA0k5BuI0JKn7X56s4YgaCdRlw91+XCaotbhzOmWUUjDnh2u8edUcZsUdFthQxaMZ303r9fs6Jia9CkEStevDkkjQPSSDEvNLPM0W1GXFht1sY6eR/ZM9ZxNC14aqNNJ72fgCWh4tJam0trD1QQvwXiwK+0WOfOjCTKS8Nmv/GhutuTKODiaovv3zwiDhXJA+airDR8/Hx/ud+5xH14rMygLEu+/vWv82u/9mv3/fwXf/EX+drXvvbQ9YuioCiKk79PJpPH+fCWeDew1tdfhvHDWZ5CeIPRcN8Hxa9ufjiP8b3iOELqzg3vWO8N7iVQCwlJSiUV+69dw338EulTV2m8/h2Sakra7JJpy93dIYPJETqIOUhWSVttXCCZx02a+7cIkib/v67l/3b3/8q/M35ndECDL4ov8Etrf4x/tfEFWq17GXhZoWkmIecGDX73BzvklWWz30BrS5BJnxPYaPK6SdlPIi4OGlxdb3G4v0AFJeJUdNbBJEMg2GmsEfRGbBeHDLWiX01oCENoFszjJtdlh2ReECvFrDRUheXgB6/RvvgCVze7/PDOiEWlaYmATiOkrDRhoNDWooxAV75msLIO4e7lMXpzursvd9NYP7a39r3VXjoh+F6yhcSxpX2Gp0GgcIxlwveSbcbqXVSw/pjhzRznbxcPthg55wgDRSihmUZY61joCmuglUQM5wUb/ZRPX1k7UfGKynA4K5jnmv1xThoFdNKAvLLM84rdkY8pSuKAbhDTb4Z0GjF3hnO+ff2Q8ytNntm8t2r0e5/b5HdevMPeKGez50fY2hhGixIpBFc22oznJaudBOMcK+2E7X5Akii0Nr7C1gmvXmrDJCuptM+z3ew3eH67/+DL8K6x3k1ppxGjecGgdb86WlQG4xznn4AM0KtbXfJKc31/hq3jlCptCJTk+e0eF98h4V7iRx+PlXgeHBxgjGFj4/4InY2NDe7evfvQ9b/yla/w5S9/+XE+pCXeK3QFi7k3KU3H3lgkhM/njBJP2pzz5pmPKpTy6ua1lz25nk3882t2/PNezFgkXYqyYlPmFL0NxpdfoHXndZLRHilQ7u6QuYzd7U9SdAboSOGEJMjnvHzwff7zyX/D/1e/CEAqIv7i2r/Pn23/IuMsZG4lwhiU9DaKrDRU1nKx22ZeaHJtyStNoiWjeclm2qaRhlSRYm4kWVFx7WDO1kqLZhpSHBwgLl0FITDWsSgMSgnGFaiNq0wmPdrDO6w5TWHhWthnFnbQLsJkFXMqRouC5nxB7nKmWUW3GfHMpjclldqrsZU2dNKQGwdzjHFo59CV8VWEx6Pz+iV+kFwexzC9H8hlxL9LL7Fi5gz0HIVlLmN2gza5fJ8arH7E8Z5JJ359Qjmfu3nclQ6+P0Abd1JlKQSMM+8eP5zkrLZThBBMspLXdye8dHuEEtBrJT483klAMC81B5OCUPl9y8NJjrWOQSumnYYcTgsakcKud5D1zPr8aouffW6Dr37nNgeznKIyUI/On9/uYR3M8ortQRMhJGHgM2yVlBhr2ZtkDFoJP/3sRu3aNjTigOe3e2wPmu+rw7wRB3z8fI9vXTtkZ7io1V3BPK9YlJqnNjqce4Sp54NEqCQ/cXmV8yst7o4W5KU/Sd7oNhi042WA/BIP4QOZhT44CnjUTsqv//qv88UvfvHk75PJhAsX3kGczxKPB87BZORVzDzz2Z6zSb2UV1tS48Qbita2/N8/qvudznnCuXvHj9jzRU2kM+9Ob7YgbTHrbyAOxsjaSJCvbFF0VomnRwhdEOUVO0HAojmgEQQ4Kdmvjvh/3v6v+Pvzf4nBIhH8Yuvn+eLl/5hVtcLQOgqZk+3vM50tqMIE6xxxqLi42mKtm7A/zsE5rPXOWOtgTza4I1q0j3YZig6VdTAv+V9e2uWzayE6jLgpOyR55Q9cZcVsUeJwHBZwEK1ykKRcqBKe0ze5E3SJCRDGIqWiqAyLuaZjK1ob68h2Ql5pXx2o/U7cPK9YFIbJvCQrNEqKk2gkc6pDXb4DJe3EdPQW71dInR96ysluhWQ/aLMfLNWWdwNfCfDucZxP6XAn0VqRklTWEqCgDn9vJyG23uO9eThnUWl/EmMcNw9m3DycYa2jlYTcHS0IpGSjl+Kc3wN2zrIofXqCFH7n8fZwQSsLCJXk+sGcS2sZG717BO3KRpefuVpx83DG1a0eaRiw0UsJpOTb1w+9cSlQnF9t+eD5hQ9ux0FZWbYHTf7gJ7cJlTzJs31c4+6La22iUHFtb8rhNMc6RysOeX67z6W11lsGz39QUFKw3k3f1Cy1xBLHeKzEc3V1FaXUQ+rm3t7eQyooQBzHxPEycuGJgtbw2g/g9ht+7FyVPttyNvHRScfNSHnmR/CLuQ+JPx2dpCsfrl4WXk3srfpopycRwwNvkuoNfIPT6Mgbp7TxKq4KqJ76OOOJY1I5rFVE1iCsxQUh+WATrMUmrxIHslYW5/x/dv+Jd6pbrwT/vHuGP5n+hzhzldGeorXiO89joymjmCiJOddvkEQB3WZEo1ZSlPLGCCUFu+OMKPAHnq/ZVa6WU9b0AVYFyCAgPhzzWtWm9YlPs37pPPvjDOMcG50G81zTjAJK493jQil2khXOF4f0qxmzsIsEJlkFwIqZoxstbNe/30IIpJAczRZE3RTr/K7eNNO+rfWU4/e0+fedKGnHjTRnwjk29YQL1RF9kwGwH7S4FfaXZPM9QAJxWO/o1i/+oxqi3gzHxrFj85gPt5AEuFoFg0VpqIwlrwxmYdHWMVrk3NibUtTydxoFNJOAfjMmDhXjRckrOyOyQmOsI68s2lpy6SO70iig1JbxoqQVhxhTcjDN7yOeAP12UictBKy2fU+6NoaDScb+JKedhBjn6DQiNvsNktAbncaLkue3eyeZnIF6/GreZq/BRjdlUXrzXhKq5c7kEh9pPFbiGUURn/vc5/jqV7/Kf/Af/AcnP//qV7/KH/tjf+xx3vUS7xduvOqJ2HHDzs4N34Qk8FmdYej/nqRQZv5nz30SGvXu0f6OJ66TEd4V7rxb/OJTPgfzrc7YZxPvLHf4aKJO7/HWHe7d8UR5sO7jocrSPxcHFsvh7hEvvbzLdLbgThVRfv27XFUZW70E1e6QrWyx6K0zDVtsqDH/cPZV/ssb/2+OzAiAq+HT/CV+nj+cdfi622ZcB2KPFyWNKGUgcuzFizjdIK80l9baJ2NC5xyVtrTjiP18QVZogjqiaWwTZp1nGORjztkpgzRk0e5Q9jfI5gl/qt/khQsDrHMczXLu/u7Ch8YvSmZFRSsJOKwSXmxc4IXFTdYXh+gwQQhBR1bYtMnrvUu0XUTTOUazEgR0GzFHc6+8RnV2ooV3zlTOwCNvwjmulnt8rNhBOJipGOHgcnnAth7x7eQ8N8OPUGbsEwSLVx9PE/53+1Yek05X38g8LwmUZJpVtWmmPumRAhBoY5HC+b1gYwikREnBItccTHMGrZhSG0bzkspYIiWw1mLq4vYMH7nVjENsBZX1Svj+JDtRJsHvFwsHP/3sOtO8YnfoyebeeMH+JGdeVESBZHeUcXeU0YwDPn6hz0Yv8cQvCrh9OKcyljhUJ4HxjxNCCJrx0hm+xI8GHvuo/Ytf/CJ/6k/9KT7/+c/zhS98gb/zd/4ON27c4D/5T/6Tx33XS7xXFDncvu6zK9OGn5eOjrzDu9vzl+3veEUQvOGoF91TO4/24fvf9JevrPsmJWc9mXzpu34c/6je97LwDUi7t+/ti4aRD8V/5uMnDUjOOaZ5RaUtYSBpJ+F7G3uNju4FvQ/WYT7zKmgUc2tcMNkbEUUVjcE5NkVFcXCDnTAl05bnTEV7uM+osc7/GrzMn331v+SV/A4A2+Em/3H3f8fn1ee4lO0zLA4Jy4ztbps4kWTTCSY7oDy3CeefYmvi8zFvD+eEyke4FJWhnYY8fa7N9b0JDsd4XlBUPveyQDBSPa4FfdJAsapSPtHrsz/K+OGdIb/wyfOAH9GvdRJK7Q0avgXG72mOWyt8r9HgXDXhY6k/wN+WLY4aK9wsFGsHMx9jU2iasSKQEYuioqwsRaXf/et+Bh5FeAZmznPFLnMRMwvumS6mKqFv5nw83+FINZnL5fTk3eB9WrUF7r2HSkAcKkptGM4KkkjRTiOM1USBIK/891fKuiK18L8bhZKismSl5nDqm3IE3kVe2HsKuqyD6IvS73REgUQ6r7yXlcU5HzR5HPI+aCc8vdEhDhXDecHtozk3D6f0mr6BRwlBIw7Q1jLJSr517YBnN7usdRt87/oh07w6UXJ7jcTveD4BRp8llvgo4LETzz/5J/8kh4eH/LW/9tfY2dnhE5/4BP/0n/5TLl269Ljveon3iskIspkne3BckOxdA3EK56/AbASbF73i2Wj5tqLjvc/b13zV5PrWvdsU0iuk1vp+883znlCehjXw0nf873cHfjQPfpx/+5pXJD/xeY4Ky6s7E3bHC+/uDiQb3QZXz3Xpt94l6QgCyOpD73ETU7vLbOcO+8MZDSWpti6hhKSv4HarT5VVXJtpTByyJ1/hb9/+z/lG8SoAq0GHXzv3H/ILyc9ze3dGag45SLvsPPUs0XzMhsyQiwlKSa43Nli78HGCtMWKLbAOPn6+x/7E73b1mzHr3ZT//uvXfFag8LV787xWkPB7c044Frlh12RUbxjajZij6b20CCEErSRko9eoo40UQSC4czSn1A4jQm7YDkUvJas0o3mBKAW51oznBRbvsu+3Yn+AF76/PVDSJ4K7dzeefbvY1BMiNPvq4ZH6UDY4r0ds6AmvR2uP6RH86OBxvk+nkUSSC6st9sYZWeWNc4tCc5zkGUiQQp2o+0r6pINKO6JAYIxjvCjRxme6OgtIUMJnxVYGwKEAk2tMpFjtJCgpWRQlO8M5sk6mWOnE/MSlVSrjuH00ZZ5XvHRnxOGkYHulhcOxN86YF37NJJCCg0nOeiehlUTI1DcHSemJ7NGs4Btv7KPqPvYllljizfGBmIv+wl/4C/yFv/AXPoi7WuL9hLOeQB5HCSkFcVy72lP/9yj1e55J6pVNIfz/5ws43H90a1K7Cwe7vuP8wdil4YEf2Q/W749sSlJPgvd2GN24yb+dRkyzkkErIW55ZeTG4ZTRvOTzz6w+FEHytrC+BQd3/XMX0qu0q5vcWIS83gi42NeMe+dYPbjOrDWgLyWtNOJbR6/zfxn+Xf7X/N8CkMqYL37hi/zqx/40ndGE4Z0dZoVEnjuP6G/QthHXdieIxIHVjDXs5YKn54KB8JV97TTi8nqHy+v3mkn2xhmH05Kt2kH7yt0x00WJcd457MPYBXG97zbJKmaFZpGXJ7fRbUQ0k5Cs0Gz2GkwW/rJASgqrEUrSShVCOPbHGUVliJSgk0QgBM5YKm25O1z48Z9wFKWum1vqjw5e5bLu/Sc2PZuR84ixoxBUQtEyxdmXL3Efjt+bs4xc79VgdHI7EgSCrNBo4zDGEkiJc36HM1A+bSEQnDQLSamorA9HT8IQoyz5vCTXGmcdUgpEXTogT0VwGfBKp3VEStFIAn7iyiofv+CnMJ00otuM2B1mvHp3zCyvCJTkuzeOOJhmtNKQjW7KhZUWi0JTaYOQgjCQzDNNEqv7/l1RUrLWSdkZLnhjd8JGN/1QczWXWOKjgI9owvcSHwgabe9Wz+Z+tC2kD40/ro8sck8Go1qxHB5Ap++JaJF75VI94iMmlSe15oxD29G+J34P5oQCqACnJHdfeZ1p96k69sT/Q9+IJWnU5PZwzqs7E37ymfidHwTWNn0W6cFd/1zr0PUiy+lUc6brl9AqRDiHk4qhHvL/Gv4D/unsn2OxSCR/ZvsP86XL/0e2/8Cf8GruNtjzCw46dxm0E9JA0clKgkAxRDDOffh0ZSzR4Yy7owWVsfzip84/9PCG84IoUEyzEovz/dWBd/NKAao2HTTikDhQVMZQactwXrI/yVhpJzTigIurbV68eUS3GZEEAa/tTWg3IqSUjLOCrIDRvDgZxadxQq8ZEShFXunaSFTg8ITBxyHd/14a513sj+pkf7eokKg3oUSBM+hlD/s7wlmNh+/1bTuJzrIwLwxSebXcOW8skoA1jnYzIlICKX01qi8kECwKi3GOeaG9smn9510gaMTe7DPNq/s+CQJQSqCEoDSWxMJnr6xxdavLrcM5Nw6m3PzhnDf2JvQaMVc22vSaMW/shhzNFKN5gRReuTzdxDOcFcxKTf8RfeO9ZsTBNGeaVw8FyC+xxBL3Y0k8l3g0Wm0fj3TzNU8CVeBJ2WwCe7f9HublZ70COp94cnr1hXtZnknilc+zCGSRe2NScoYqWVVvGseUG8lkMmflfPIQsRRCMGgm7I4X7+4gkDbhY5+Bl7/rg/DrtYFmtWC3uYZYf5r2YsTCZfzXR3+ffzD+78id30H96fSz/L2f+cu8IAb+8Z8iP1EcIITgtbsTzq80acQBg1bEt68fUVaaIJBs9lLWOymHswLnYHecsyj0fRV82tiTwOuy8sqjkhIpTR1h4wiVRAnBoqzICkMYSG4ezvgX37nNpbUW24MmUSBpJgF3hwtKo8lLTV5UCCkIpPQB0EKeVBEqAaV2KAlJGLA9CBgvAo6mBY1mjHXlfRWCpysx3y1Ov7Onb2Y36HKxOkI6i32AYIbOB1UdBq13f8c/pnjwrXqvxPO0miql8AY0JamkwRoQUmBwGG2QSiKFP3lpqJCiNCghyPKKqa09iE4ghTjJ1FT1ZxVnsbWTSQq/35nGPk5ppR2BcLx484iX7oxRUpwo/HmleeXOmCsbHfqtBPamxPVJ3bGLHvx3zlhLKwkf6SYPpDwhxkssscSbY0k8l3hzPP2839PcvePVuzD0Kmh3BcLA73U6B5euwrmL0K2bO8IIti7BD77trxOcGo066zNBN857hfRBNFpeUX0ETJ6RhX3iRzhJ49ArF2Vl4d2kNnX78Jnf4xXcbAZC0qxCbn9jlzDX/M74n/GPh/8Pjqxv1no2epo/Hv1H/Knnfx/Pt3uelD/1PAQB2li+f/OI79444truhL1JzneuHbLeS4kCwWiWUWhLoCRB3QM9aCdcXGsxnpfsDBc8vXlv1K615WBWsNZJmOYV+2Nv6AnqTEFjHYH09X/GOqJQstpOaMYhaaT4+mv7/M8/vMtmr0ES+ddPSn8dJQU7owxtLN1mTCNW7IwWfgdUCUIl6DRCVupR47U934JUVRrr3ImLWXKPdLybw/Dx7x+vDjyobd4NOuwGXc7pMftBm7KuxUxsxZqZciMcsK+WxPO94vh9eM/Kp4A69Yu8sn4/Ex/bFEiJFYK8qNDGn9gcTS1Cwlo3ISs0FgilAunIC7/Ok5UVRWVrUit9Vmi9r9xIQgbNmDRSrHVS7g4zjmYF/WZMoCS3D+f0WzFpGDDJSm4czLi42qCbRswKbxrKK0MUSAptGc3zk1ilB08Ej7EoNXEY3FcZucQSS5yNJfFc4s2RNOATn4eNnXsO8/4qfPb3wGDV51sq9bBBCDzxHB3B3Zt+JzRJvZq5mHrl9Onnz45GWt2ApAnTkTcincZihowiynQdqw3pGU0hpfYq33HG5Zmw1ofCg39sD8Y6BYEfu9fYMJbZi/+Uv/3dr3BY+orL83KV/7j1J3hO/BTnBi0uDRq+q77Zgc0LOOf41hsH/A/fv0NR+ce00U3ZHWd858YhAkEnUWz1OwSBJ45RoLiy3qaZhBSV4c5wfh/xLIwlDiRxGNBtxIRSMssqtHUkoTdadBsxeenH4UoI8tIipWCaVWSVodKGUEkurLTIS83tozk7owVrnYROGhB3U4RzTDJP3rVxDJp+bWE4L1FSMskK9iYZSgjCUNFtRIznBdqAVF7v1ObRL/+bwdtN/L4e4A0jp99fGfCt5DwvFHfY0FNC59XeUgS8Hq3y/XjrISV0iXeO98vdbh1U1hE4R2V8oHyspD8xjCQRDiEk2laAN6g1VYB1DiEF3SSgnUY457h9tCAOJGGgGM4KrHMo63wGbihJwpCtlQabvSZZWaGk4HDqJxKNOKDU5r61gnYScjgrMBZeuDjge9ePGC4KjqY5pbZ1gUPA559aIwgEtw7nJGHzxAQFXhEdL0peuNB/X5uLlljiRxXLb8kSb41j9XLrjCSCN/sERTG88FkfpXTnhid6KoCrn4BzF7yyeRZaHU9KX/6u37Vs1u7l+QycJb36PG0z4PZwwfbg4QdwNC04v9qinZ5hQLHWZ3XeuQaTsf9Zu+uf28b2mbmiX7v5NX7lq7/C125+DYBm0OfnBn+G/y2f42Ix4lya80wvIZ0eekL9zMeh3WU8L/jXr+4xnBcEUrIofKyLc45OEpJXhiQKeWqzg6jduYfTgv1JTjMJUVKiT+3AOufjk57a6Ph9sqyk34rZXmnyxt4U6yCp9zpLbQgCn4NonGVRVLy2O2GtmyAIOZzlKAk7wwV3hxmzRYW13sHbFRKtDVVlqSpDVhmcdT6c21p2jua+j11IkJJKW3qNGK0t44VXrqR4WCl7W01E9eWnieZZ/HWmEv5NeoWBmdO2OQ7BWKWMZPp4c16XeFcwFma5qWOVJHGoMA7aSUQnDaiMQ9sYbRzW+Gilae5PqFRhycqcQvtsT+tgo50g8cqkL1BzNKKQq1s91joJ2lgKAVEYeL9jTQgDJWnEiulCk4R+NUcApbZcXm+jBLxyd8JKy4/aB62Eq1tdrp7rklc+4uzW0Zx2GnpFtDLMcs3WoMFTG503fQ2WWGIJjyXxfBKhKzjc8yYbXXlitLrpCdlHDWHkszq3L3m1UwVeTXwrnL/iFdI7N7zz3TlYWYNzFxHrW1ydl4wWFbeP5qy0YqLQVzseTQuaScgzNZm7D8d1mK/9wBPMY0I7OvKvdTaHK8+dEJeXDl7i1//Fr/OPfviPAEiDlL/0M3+JP/fp/zPzLMAaWA1K1l2OdNY/3v7ayfO7sT/j2u4E4xyNyI/hSmPIK4NEoIRkmpVo5wiF319rxgGHs5ytQYOs0Gz1U0bzwpsulD9IdtKI1XbC4Sz3JHulhRKSO8M5o0VZ7755g0WgJFuDBp0k4ubRnFYSEAeKu6MFNw/mZFXFPNckcUBeaax1zIqKRhwQKa8sFcayKDTG+nYZrS1SSaKAkxzEo1lBGEjiejx5vOp2MjYX94xGx9FP7xVOCA6DFocsx+ofFZj6/Q+kpBUHdNIIJQSdhs/MPJzmjHKNLhxGe3U0TH3OZ1EZrKp3mANBXK+KRKE3JW3UDT/OOYazAikFT621KI09aeCSQrDWSRnNx+SVJgkDn8AgBc45pJT8/Ce2eW6rCwhaSXBCWqNA8ZPPrHPjcMatgzlFZUnCgKvnulxYaS3VziWWeJtYflOeNCzm8MNvwv6uP1or5bMr01e9krZ9+cN+hO8OUkH8DvafhPDRSaub3sTknFdQa0VypZ3w+afXeHVnxP4kp5wVREqyvdLk6rkuK+0zTEuToa/7bLTukU7w6wSLmSelgzXuBhVf/p0v83e/8XcxziCF5Jc/88t86ee+xFZ76+HbfQTujheMs4rNXkp8TLbrKJkoVJQLP+I7muZsdH3+XxRIZoVmOCvIK8Pdcc7NA9+SEgaSrDTkpebZrR7NJOT8Ssszu6fgO9cP+Tev7pOGkkWp6TcTNvspq52E3VHGLKt4Y3cCwucSttOQThrW5iHfHFNZQ1b68XoUSlzdTpRGiv1JRllZwkCAs+Slj8axzpNRayxOQBQKKl3vfNYuo6B2Gmvr0O+kN3OJDxWB9Ep19SZnCu80C1Rby7zUdBoRgfI950Eg2DsqyEuDNg6HH5/PCs3BtEDVJ12FNgghKCrLejclDhTGOaaLgnlRcX1/QqEtnTTi00+t8hNX1rg7WvDvXts/aS9aaSdkpeHO0ZzhvMAYr5zeGS7Y7Df49OUVmsm9aUle+uYkbRxxqHhms8vVzS66/k4+KX3pSyzxUcGSeD5JsNaPl/fvesJ1OopoMvRtP2kTBj9GwdhCeDPTGVjtJKy0NxgvfMNOqCTdRvToCKWDXaiKs1+/RovZaIe/+S//Cr/5w/+aeTUH4I8++0f5jX/vN/j42sff8UNflBXW+sd1DCkEiNo04xwS4XM296Yn8S3zouJoliOEYJ6XdJsxotCM6kikSVYRKMHl9c7J7ZXaE9LzKw22Bg2u7c7qZiLNcDZmf5rXj8dgbG0CEsKrr8fGjFAyzSzGOrJSY5x3t0eBQkk/phRC0E5C5oXGGENWWUIpCQJFpb1bOQx8ALgzfr9PCv/RduJe//cSHw0IvNLntPHpZ+7hy0//SOHV7OOfHa9CnjZ7Vwac8yscIEgixXBSkhWaVhKQVdoPRyJRq+QO5zxBVUIQSJ9nGyrJ0xsdJouS4bxAAqWxrHdSPvv0Kj99dYMoUGz1vRK6M5yz1kmJQ8X2oEEgJTcPp3SbEZfX22wPmmz2Giduduscb+xOeGVnwiwv66YiQb8Z87Hzfc71l2HxSyzxbrAknk8Sxkf38iMfzL/s9L1bevfWjxfxfAsIIeg9IlvvISxmEDxsgqqs5u9d/2/50g/+LrvVCICf2v4pfvMP/Sa//9Lvf9ePbaUV04hDJouSXtOT5ygQRIFivCiZ55p2GpIEkkWh2RnOEELwyUsDBq2EvNR0mwkv3R769iLray2nWcWLN4do42inEdpYdscZw3nJ4STnYJJTGYvWlv3J4qRmECGY5holfHB3GgVkZYWxXoWqtPGRN4HyTmQhqBCUlWViK/rNmKLSZJUfu0eBJCus3/eUwhdbAVrfTz6sA4k7k7gs8WTD1rWToZKUdVzWMdmUAtLQm+Jy7d9Yy/0xWFJw39pFMxYURmCMZZZVjOY+6F9KQRqq2tku0cKQFdqrodKr8d50JsicRgjJ7njBOCvJS0OoBC9cGPDsVtdfNsr4/s0hn7o0IIkCPvPUKt+/ccTuODu5rUYU8HMvbPGx8/0zu9av7U349rVD0vheU5E2dVPR6/v81NV11jr3YjPmRcXd4YI7wwXaWAatmK1Bk9X2w7FvSyzx44wl8XySMJv49p+zci/Bj4iP9sHUTvIl3hnC+F6vPF5J+cc7/4pf/8Hf4qXZDQCebl3gK//+3+SPf/yPv+eDxUq7wfmVJneOFgznBc06y1Mbw2RRIiWc6zfYHrSotGVvssA6x6XVFkczn0H69Vf3uDNc+JGe8HtogfKmBpxje9Dg7jhjUVTIOkZJCt93nVWaWVb5Ckvpg4kakd9pyytbj/M1pbZIAZWxJ7E0aRT4rQYhUbLOD7UWoSSm8upXVo9FEd48UkcqnpiBTqth7jE0GC3x+GGd/y+Q3NdKJfEKeRgopHU4ZyiMwwGB8CcYSnpV3Tof8dVrhAQqQGmvaLo6rEkIicDvc87LirIyBMqnMVj8bQSBJA4Ued3FHiiJQFBpX7+ZRgHzomJ3nHN1q0vLhby+O2Gtk3B+pUUnjfjpZzc4mvqRvD9hjR6Z81tqw2t3pySRui80PlCS9W7K7aM5b+xOT0jlcFbwzTcOOJzmJJEPt391Z8K1vRkfO9/j6rnuknwusUSNJfH8SKH+h+v9roL5ccHKOtx8FaqSr01/yK98///O146+C8Bq1OWvbv1x/twf/s+INs9w778LrHdSntns0oxD7gwXjOvg6qIy9FsRUSBpRCGH0xwlBef6TZpJwP60oNKWw+mCm0czuo2YJFCImnhmpWZWVkyyinYc8vXDAx+ZVBNOBxSlYZFpnAMZCBIVYJwhjkKsMWRlyXxa1Uoo4EDX5NFYQzsN6TVib8xYlAjhnb/NWJEJ/xyO6zClA4urx/f3VM3TWZ7LT+xHC8cnDQ6w1uKEuC8QXikfW7AoDGG9hlEZ45XuWuW0Fk8ogWYc0IhDprkmCRWBksRBgHOWorIYZ8lLQxoH4KCq1f1WFJBEqt799Cq7VyuVT2FQPqLMOh+SNJwXHE5yNnoNnHXcOJj5PWg8gV3tJKzy1lW6w1nBJCvZ7J0dBNxrRuxPMp/fGSi+c/2Q0bxge6Xp118AWjGTrOQHt4Z0GxEbyx73JZYAlsTzyUKz7UfsVXl2LmY2g63Lb88VvsTDGKzxUtPy6//Lr/CPhv8GgFTFfPHif8ivDn6RzoXnYXXbxxbVo3CEP8g040d0g7/Z3bVjnt7soK1ls59SaMtsUXJtb0YaBVxcb7HRSX1AtvJNQtY6ru9Psc5xbW8GDoxxzExFIAVxqLzKJDV3Rwv+u29c5429KZ00RBtHIw5xDnbmc38wFmC1I04kURAQh4r9SYVzvnpQSUESBRjrnevWglLON8QI30WtrSOvDJ1EkUYBd0fZCek8DngX7pi0vp9v2BIfJo7Jp7aga7lT4JXMY8Sh9DuYCJQSBMIRCN+9fkxcQylIk5BFaXx0UWWJI1UTRj+6Nsb6+kvrjWjGCVTgsM5RVF5t19aRBIpeI2TQjpmXhlBKGnFIZQyTrCQrKvZHCzrNCBDsjBac6zc4v9K6b9f6rWCsjz17lHHINxVpjHXsT3IOpznr3fQe6azRSSNmWcWtw9mSeC6xRI0lg3mS0FvxpqK7t7yj+/Q4fTrypHTz4f7uJd4ad2d373eqI/kz6z/Pl87/R2y3t2FjC576GHPj+MH1fXaGC4rKbyo245CLa02e3eq/o4OXFH7vLIkCru/NEHmJiUNaacjl9TYXVs84GEqIQoXRlp3hAmOdH4FTH8SVRCnfcHQwzSm1P0BKgXfeWks7DggCSeIUTkClHUnk8wxlXYfpO94VoZIESuCcJ5nKWZJQMS/qAHrpDR5YCEPJLK9OSIWsI5K0vUdQPki8X806S9yPQHjyV1nH6U9nOw2w1pvZtPXJB9b5tQxtHZU2dJKIfium0oZ5qclKQ1FZRrMcEEgpaMQBzsF44SOPBq2Ec72U13YnTPOSftOfjAVCsD/NMdZ5l3lNBAMpMFbQS2Pyyn+WJ4uSg2mBtn79I50oBIJeK+J/fPEOHz8/4Ccur5y5y3kW0iggVIq81GfGJC3qnyehYneU+XWCR/zb0KxD6q1zDxHTJZb4ccSSeD5JkBKe/YR3Zxzc9X9XyiugcQrPftKPiz8sWFNncar7KzCfYMzKGX/ja3+Dv/G1v3HiVP+lZ3+J3/g9/xkvJNv+Ss0OtNqU2vDNV/fYGS5YaSWsdXx7yjyvePHWiEo7PnV55R0dPAIleW6rx+W1NpOspKgM33rjgEDJM0nsPK9oRgEz58OztbW0VICxjkWlGU4LnHCkYYBSgiQUHM0sh1M/xl8UmkWhkfV9SyCpValKu5NaToTPyQkDSSMOMKECKrQRaAutVLHaTokjyTyr2McxzzRZ6d29wbG6WbuMtf1g6Z/0d73cOnlM8C1aPmtzUWiaSUi3GXN3tCDL/Q4mQKUN3TTwlaoyopkEbPaaXFhtkVeaO0dzru1NfY6ms7TikItrbQ5nOYvS7yAnUUBWarTxl4eBojKWbjMirOPFcI55rsnKiqwUNNOQ1U6Du8OMw1nOZFFQVBrjfNFBO4mY5RVZYbhztPDtW63kvhawN0OvGbHRS7l1OGNr0LzvO6+NZZpVfPLSgChQZ5YlnIZ1jnDZpLXEEidYEs8nDY0W/MRP+erFw1MB8mubD9dHflCoSq/CnrQPKd/ys3kRWu23/v0PAZWp+Hvf/Ht86Xe+xO58F4Cf3PpJfvMP/SZ/4PIfOPN3doYLdoYLzvUaJ+qFFIJ2GhEoyfX9GRdWW2dnhJ7CZFGyKDRCQK/pG1DiULEW+n2xaV7x3etHPqT9lAKjjWU4L9nuN5gXmqfW29w+mjOcl97Y4zxfLEpLXhWkUcDBLGeWa5SsFUshKCqNFJLK+ED4c70mSaQwNZGtjEVKyVonpt9MCKRAKsF4XnDrYO7zPI2l0IZCG8pKEwaKrCq9qinvjdapTSFKfLCOdevveonHAFObieJQkVcOY2GeG6a5X/1Q0o/SBZ6g7k1yumnI5Y0Oo1kJAirtw9Wf2ujSSSO+ff2IOPQtV6NFyWReMi81oRJoberAdz/CVlLSa0YkUUBlLBSevAWBAKFopxF5ZZksKtIoYGc0J6/MCVluxj6MvteMiUJfKRsqyWt3x1xaaz1SmTwNIQTPb/dYFJrbh76pKFSSvDLMC83FlSZX1j2J7TZiwtrwF5/R1T7LKz5+vr9UO5dYosaSeD6JCCPYvOD/+7BRlfDiN2Hnhg9ajxNPhl990eeNvvA56PQ+7Ed5Aucc//iH/5hf+xe/xsuHLwPwdP9pvvILX3lLp/rtozmRUmcemNIo4GCaczDJHkk850XFD28N2RktyEtzknl5eaPN0xtdVB1q+PRGh+mi4sbBlFD5+sBSe6K3PWiQhAF5Zbiy2WFeaAqtCZVCO6jqikDlBO0k8uYhCXlpiUKIlKLQBm39/NsCw0VOrgOccxSVoTKWVqpoRCGtJEDWaoxNHEmckzhFpPwYPgokk0XJLK98DE0dmaQE99zsS+XxI4nj9Y3T6QPHanYoJVlhkKLO0hS+SQghiJQgCgIq69DHEVyhIq8s46wiHOcUlaGdhAxaCYU2NCJFIwnYG2ccTjMWhTe+aQHOWRpJyHonZXecsTNa0EoCWnHIPK9Ya6eEoWB/7PvTu42IrNLcOprTSUOcc1jr0NbRqE14aajoNGOc8yUHRWXYn2S+dvPU99tYS14ZlBAPjdR7zZifurrOjYMZtw5nFNqSRgHPb/c4v9I6IZmDdsxWv8n1/SkbvfTkZNJax8E0p5WEbA+aj/39XGKJjwqWxHOJN8ft617pXNu8f7ze6sD+jq+f/ImfPrPj/IPG125+jV/96q/yuzd/F4DVxip/5ff/Ff785/88kTo7NuU0isoQBo9+HkoIqkfIenll+MbrB9wdLug2ImwAe5MF1/YmfOf6IZ97eo3f+7FzNZlTfOapVfqtmB/cOuJgkpPGirVOgrGOb1874ObhnEE7xjhLGoUIYLgokdLXYIaBYrUTszfOScOAUvsRuHYWJQRhKP3B2FjmuWGe+xiaY969yCt2Rwu09YHbUsIkq6gqQyOJ2OinDJoxu+OMeVGhpCCv7lVderdz3au+JJ0fSZxOHbi3Q+wD3QGC2nyWFRpZ7zAKAaVxpKGg1QiZlxpnHZV1DKd5rTj6/crDWcFoUXI0K5gXmqwyBFL4z3NNaCvjP6PWOoQQbPQSru1qZrlmUWoKbWklikXuiWwYStbaKYU23D6ckZealVZKnvjcz/VuQhQERIEEhFdM8Vmk2jpU/QWojOXmwYzr+1O/miIE672US6ttVjv3TixbScjHz/d59lwXbeu6Tnn/yauss3ctjp3DObre5bTO0W1EfOriytvPGl5iiR8DLInnEo+GrrzS2Wg+vNMpJPRW4WjPtyr1Vj6cx8jZnepf/MIX+dWf/VU68dvvt+80Io5mU+Dhg4RzDmP9/thZ2Dmac3e4YLWTcH1/ysE0J1SKJAqYZ5r/6cUdyspyZaNNXhr2pzmH0wznIIkUh5OCH94a0W/HrLdT0iinqgyFtrTTEGOdjzNKQrLCu+0jpbDWEUhBJ42Y55oAQZiEdBoRo1nOaGHrLmo/Og2V9GP0yjAvKszIMs8qHDBelFjriJ3j9uGCV+6MsfXupsHXGJ4WgyVL0vmjgroAqzYJWcJA0YwDrLXMAa0dSeh3LKx1jPMSXX8nQiVJAolDEAV+HJ0gfNXkLD9JRxBAt5lwNC/AwUo7RUnBcJ7TTEK2Bw0qYzmcFMSRoqg0RWWIlKSVBPRa/nspheAzV1ZZacV1sYJjVlRMlSRU6r71lVIb0shPFFbbCUkUoI3lO9cOeH1vShoFNGO/Q31tb8LucMFnnlp7qJUoUJI38yWlUcBPPr3O4XrO0TTHOEcrCdnopssO9yWWeADLb8QSj0ZZQJ5Bs3X25VHsjVBF/sE+rhoPOdWF5M98+s/w5Z//8jvqVD/Gdr/J9f1ZHcbuHQNRoJBSMF6UNJOQjUfk+t04mJFEit1hxsEkZ9CKT6JYWnHIG3sTfuf7t3l1t0U7Cbm2N0VIOD9osjVosTvOCAPF/jjzUUdCeLUnDigqS68Z+ZzO2Ks5QgiyUoMQmFphkdLnJbbTiKh22x7XYfqRqSBWgiTwRNa7hAW5NljnWG3HNJOI4bxglpW+keZUSffxLqiro2aWnPNHAwKIlcQ4H1+kjcU6R6QExkEooXQ+UktJURvVYGxK3yokBUqGbPWbIHyEkTELKu1PVtIopKoMrUZIrxl5g1ChT3YikyggDMTJGoySgkEz5vJ6h2B3wkorJoqUby0qvXL68s6Iu0c+NikKA3aG8zoOzNFtCuJAUhmHsRZtBM045IULAwDuHM15Y2/Kel2feYxWErI3zvj+zSNW2vHbdsAfQ0nBejdlvXv2vxFLLLGEx5J4LvFoSOWNRFrDWZNqa+rS7w+2Reksp/p76VQ/xlo3oZeGfPONA0ptiQNvCkrCgEE74tOXV2klD7v5rXOU2uCc43Dmd7pO5/9llWa8KEkihdaWsrK0GyGdNOJwWjBZaMaLAm29W3Y8L+k1Y6Z5RV5WVMZXChaV3xtd76Y005CdoznJomJR+bGkCgRx5B3BB5OcvKxbmiR1Y5Jl7hzG6ZODfK+VUJRez/zY+T5v7E2ZZiVlZWuN8x60dYQCT3atu69/Gx7u7V7iycTpGkuB39eVUuKcJVY+0zUvDeNFWY/XBeK+jVA/ku80QiptMQbiQIGATiOgEbU5mOYczQqiwCvsQSBJooBS21oBLJjmJaVRBFIynpe8sjMG578vUaBY68TsT8K6ctXf76LUzPOKSvud0Wc2u7SSkFAJXrx5xDgr65Ys/wTTOCCOAr7w7DqX19s457hxOCOqv9sPYqUdszPM2B/nbK8s9zKXWOJxYEk8l3g0ktTHN9265t32D2I69lFE3f4H8nDOcqq/H53qx7i2N2WUlfSbcZ0/qH0odam5stHi0vrZDn4pBK0kZHfkzQv91v2j+lG94xYFkpd3xjjn6LUiAinpNWNe2534PveGz0Cc55pBK6HXjLl9NGe0yCm1od+MiALFoB2jtaOdhlxcaXNnOOelOyOMtcwyjZR+t+3Y8CMdSCVOXMg44UfnzjLPK4rKkkSKl+6MGc2Kmoj4HU7JA3udziF4uP9S4n/ng87y/HHHu4qU8h4hAgGi7jmtjAYERhgq47D49z8KBEmoyHGU2icvKOWzN0MlEaIis444lIxmBdpY4jBASlmPp71D3Vn/HYlDibWWUEkWha5P0DzRrXSGcd4tvzNcMGgnrHUSduruc6WE/7xqSxQoNntN+q2YQEpeuDCg14j55hv7gF+bacQBG92UT1wcnKid2jpmmSaNzj5ZPj5hzCt95uVLLLHEe8eSeC7x5ti+DId7cLAL/RUfYu8sTCd+xH7luUd3y79POMup/szgGf76H/zr70unOsAkK3np9ohGFLB1oYkx9qSRZJKV/OtX9lBS8KlLqw8RS4DzKy1e2ZlgjMVZ52UlwDjLzcM5Rak5qltYHD6T8HBScH61xTyvKLWhUbcjeW3JGxNCJbkzlPRbMYNWzJ2jBW/sTmnEASvthE4zpNvqU2rNa3cn5JUhVOJE8RF1xmClDVKKWg2yVLVYfdzN7qxjd5xhrSGNQkIFVoIwlvLUIqeuXewP8ktR1yaCH9eeVkMldRytYYn3Ge8mTUAqMMa/h9JZBHU8knA450fpx6i0IQgk7YbPxZznBuUcRakpT+KPHKNFSaUdhbZcWovoNiLyoqLUFucESezTFi6vt3AOKuu4czgD4U1tUeCbu5LQlx804oBX747Z6jXYqLvRF3OfHxqHiisbHbb6DYKaKEaB5MpGm14zJCsNn316DSUEg1bsw+drKCkIA1GXQ5z1eh7vMn/4ZskllvhRxZJ4LvHm6K3Axz8Dr/7AE9Djg1KjBc99Cs5feax3/7s3fpdf/ee/ytdufg3wTvW/+gf+Kn/uc3/ubTnV3y72xxnzQnN+pYlzjp3RgluHcxyOJAxYlJpvvnHIvDB85srqifnAOce88ArK5fUWtw5n7E1y1toJ1jn2pxnTrEIIgbHQbQQIIdF1TuYrd0ZYZ2nGEYXWKOFds8fh8lHoncQ/+fQal9b8CHN/kjOaFYSB73ev6rWAi6s+pF4KQV4ZZllFXb4EgHhgNi4FaG0JA0GlveHIAa70/dvOCV+Hyf0C51lZ8daCxlKvjt5/P8cVQ0u8L3gvjU1KghISJzzxctSjduVb1SvrczuVqIsHBGSl352MlMSEjmYS0Ekj2o2ISEr2pzlHs5ysNGjrSWgzVjgEcd3uYx00o4DR3BcdFJXm/GqbRV6h6g71ThrRa8YEyn9+B01vHjo3aPB7nt+k30yY5RWv7U64uHr23rkQgnYacmm1deYJqRSC7UGT71w/OtmbPo1ZXtGIgrfM6l1iiSXePZbEc4m3xuqmd7APD6DMverZX/WZno8JZznV//IX/jK/8rO/8o6c6qdxbJxQ8uFIlEWpUdIbHMaLktuHc5JQnbjYjYtIQr//9t0bh/SbEdO84vXdKfuTBcZ4NeX8SoMb+3MOp7mvqXSCZqxORu2dNMZYy86oxBrLojIY44njztGcOArY7DX8eLMmj+005Fzft8EgBNOsOgmE35/kvLIzojSW58/3Gc4KRouCg0mOUpLK3lN2HiQqUajot2KGs4JpVtVqqB+nOifA2bc9Oj++bQkcDymPCat74O9LvDMcf1KPX7skklgLpbYPKc9vhnt5q45W4sPZtanrT+uTHWMshfNB7Bv9BpVxZEVFICVr3Qa7oznGOlY7KXGgOJr5zM5ASQJpsdayP15QNCLWOgkWn5U5zzWXV1v0WzEv3xmjpOL8oMms0DSjgHYaIpVA4mOI8sqwtdKkkQR86tLqSePQ3jjj9uGMUpszzT/zvOLqVu9NpyAXVlrcOVpw52jOWm0wss4xzSqmWcnHzg9opx+NZrYllvgoYkk8l3h7CAKf5fmYcZZT/Zc/88t86ee+9K6c6uAzNm8fzri+f++AdX7FE7ljYhkqia2lusOJ74dWSjCr6ydLbWknkpV2wvW9Kf/8u7d5fWdMVhnWuymrnaQeAwZc2WghhXcET7MS60ApPz5MY8XR/DicSPgubCmIAoU2PsrGAXfqvbYwkLSTEAS8dnfMt64dkpWaUltmWcXuJOPO4ZxACXqNmF4zpp2GzLPKO/Lx+YW6ZoDH5DJWgiT09ZnaOgIlTjrYrQP7LnKSHiSpJzmR9omIef1IQsB9EVbGQlZaBH5Uflxd+lbvViA97bcW0lBxeaPDeF7WDnTvYjfGnexYRkpSVI4kkIRp5JVRJer8Vp/pOc19P3orCYhCVZcZCLqNqN7n9PvI++OcyaLEAd1mzM9/coubh3M2ugkv3ZmgBPeFuts6b1MKcZL3eYyVdsJGv8Hto/l9DWPOOY5mBUkUcP4tTEHNJOSzT63y4q0he+MMXWd9tpKQFy4OePZc9229N0ssscS7w5J4LvFE4HE51bNS8/XX97lztKAZB3UNoOZb1w65O8r43FOrNJOQ1XZKoCR5qRktvAJ4NC9q9c+Tt14zIis01/enjOYF7Xo0OJwXjBcl24Mm24MGd4YZT2+26TWS+jH4LMFFoRnOS6aLkjRQVNLh8NmaSkme2mhRVJow8IpWoLyTPVSSb7y+z8HEm4zKyvqu60KTlYZSG/IKXtudsNVv0m1EJy57JyRSWFIlkdLH0RgLlXMsSl8HKOq6TSndSW7n+w3rlt3q7xa2bos6vbFw/Odbkc6o3q2VQhCFPve1Xde4KukD4o3x5C5QCuWsvz9rKbVGioBmrE72j4+jvm7sT5mXFRKojCQrDY04QNXpCbGSJ674dhqw2h7wc5/YRAjJ7tC3F+2OFoRSkhtzXz7uvNA0kpBACgIpaaX372h+6tIKxjp2R5lv8ZKCUltaacgnLgwYtN56EtNrxvzMsxsMZ4UPkJeCfjOmES8PiUss8bix/JYt8aHi7Xaql9pw52jB7aMZeWl8Dd1Kk81TqsdZeO3umDtHC29EOLleSLfhuH005+WdMZ+5ssqgHXNprc1Lt4fcOZozySr6zRgVesKYBIqDSc7htGA4K/xIvDY3tAjJS82twxmN2I8Nj6Yln7q0inUb3DyYESqBtYrD+kDXSkN6aYSSgnYSsNZJyUrDvDDMJzkXV9ogFKvtlKfPdTkYL3jx5pB+K6IRh2SlRVtHXmry0pPjo2lOIAXTrGSSawIpsNbipMTiKGtDhajlMu0clTMnbUbH5qC3o6A9Cqdd8MdY9qq/e5xeVThWOH3Q+8N7nsfRSNadTiIQ9QmFJVIBpbUs8oob+zOySoOFOJQEUhJHAdb5NIR5UTHLdZ0ZG5LWUUhPb3Q5nPqJQKQCIiWRUhIqb1JKYkUzDpFK4kpNKwnpNiK2Bg2OpiV3xxlJqFjrpLy2M/EnQs7vUTfjgHmhsc6x3k05mOZs9ZsP7Vu2kpCfvrrO/jhnb5JhraPTCNnsNd/RiFwKwUo7YeXssIollljiMWFJPJf4UPBOOtWzUvPN1w+4czQnChVRINkZevPP5fUWn7q8emLGOY2s1Nw6nNNrRA+RUyVF7RKfc/WczwJ84UKfg0lOZSzGOrJSEynJoBWz1kkZLwpu7M9opxFxIE8ctQBJFDArKnaGcy6utrwyqQ3bgybtJOLfvrqHkJ4UlNownjsmc5/tqUSKttCIfauKEpJWI2Stk7LSjknCgNvaoY0fh+6OFhxN8xMVUSqotCWvHMNZzqETWGfrUHlBGgaMsqpup/GuZcu9PMdjkVO5e4aTd4tlmtJb4yxy/o5+XwiU8OsTp/dmpfDpAs6c2q+1Dil8w9Q0LxFIIufV76K0xIEgCFRtLtM4oBEFJIFkXhimixIlJf1mxAsX+wxaEd98/RAp4GhegqNWKx3XD6YscseVtQ6tNGB/4gsP1nt+mrAzyk5OAFfbCY0o4Mb+jNf3JryxO6GRhLTqk7Cy1Kz3Gnzi0uAhAxD4YoftleYya3OJJT6CWBLPJT5wfO3m1/iVr/7K23aq//D2yO90nVYtm75b/fXdKe004tmt3kO/l5V+FL3WOXv01ogDxovSK5BJSBQokkjxqUsr7AwXDOcFzSSkEYdY6/fj5oVmo98gDgTGeZKojWWclRxOC+6OMoazgn4zYVFoH8Q9L5DSjyCLylCUBovBWUepFSvtBOssh1MfBP/cdp+fuLRyH/kutUEpWJSG3XEOztGIQ2Q9apwavzU6L6o6zkhQaL+vNy+MJ6n1bTk8SZHinhEI/NhWivduAlqaiM6GxOdiFvrdvzragpB+J9dqdx+BPV5lOI7JOj6xOFawnQElLNO88isaxuCcoCWFb/ixDuF80oG2XkVP44B+M2Ktl3Jlvcv+eMFz2z12xxmjRcm89BFHlbH0m7HfxxQwnBUoqXh2q8vltTbfu3HEoBWffH99L3vDx4S1YxaF5vxKizCQtJKQzV6Dzb432S2xxBI/WlgSzyU+MJzlVP9LP/OX+E9/73/6SKf6NKu4czS/76B1jDhUNJOQGwczLq+3H3K5HtdEGuvO7Fk2xldNHjvcnfOj6zQOSKKAapKxczSvI2cEQSBJQ8XF1RazrGKWVSgp2RtnLMoKgSCQgqwyJJVXaffHGYUx/NQzK/zw9oThvMThe9eDQJBEfkx/MM2ROKaLioNRRlbqk706oG5nkXVri6WVBCemi0D6yCVrIdeu7k/35MZxb6/yQbrjHqCIzmfLv+ddzCXpvIfTfT8OTgxccH+D0Nu5DahTA2xdBCBAHJ9Q1J+FJPJNQJXxoezHZjKAQHljUVFZSu1PRoxwZNr4vE3rr1MZ/7gCKWmnflS+N8r5V9+/TRxIPvOUz7LtJCEv3hxSacugndBJQ+alZqvXpLKGj20P+NzTq+xPchblw8UK4JXLi2ttjqY5X3hug17z8WYCL7HEEh8+lsRziceOR3Wqf+nnvsR2Z/tNf3deVGSlZnDGQQuglQQMZyVZ+XC8SqcRsdKOOZzmbPQaD/3uaFHQa/qwa+DEQfvqzphQSa5udim1pdKW0ljmRYk2lkAI0ijgjd2pbzYqKhpJiHWWfitmo9vgmXMd7hwt+MGtIf1mhK9VFwyaEfvWYq1DSklpNJMMDmcFqibJr94dk2nDpy+vcGmtTaAk3WZEGodMsso74p07MT3llcZZR6gEp1oyUdLnMj4ICTRihU9aMifB7sdtNUu8Pwikr5KstEHXBqHTYQHv1Md1rEZ7Q40kkPiWIeeIA19tGSnlG6SMv551fu/T/75PWjD1WYUUnmQaY0Hc+ztAGPjUg91RzmhW+XG68EHtK52Eq+d6PLXZZdBOuHEwY5ZXTPOKeaGRq/DZy2s8V8ca3VNfvVv9QfjwevGmEUhLLLHEjw6WxHOJx4ZZOeNvfu1v8ptf+80Tp/ovPftL/MYv/AYvrL/wtm7jOFLl9AEUIC+1HxkWut7JfJgxSSG4stHhcFpwOM3pNWOUFFjrGC9KtHE8vdm9T0kNlGSaVVxabREG6j4yeziDLDdcP5giEKRxwN5oTlYZZoUGAWkUstFNoDZo7I0zKmOotGOSlUSBREqIwwBtDFlhMaby6m0a0YoV+xMfP/PNNw4pteXquS5pKOmmIXkRssg1eWXIK69olcZgrKVy8oTMSHlvpP5Qp7qASCm0sJT6/uscvxJL/vneoASEwmeicqrp6d2EBkjA1L8bqTpiSPoqSykNlfYVlP1WDE4wLypfmcqpDNX6pMY6zyzDQNb1qX68Dj5FQSCptMFZqLRXZxelL0gotR/T/9tX9ljvNug2fKpDK/EnRDtHC57ejPiFT56n17y3MtNtRHQaEeNFeabjfLIo6bdi4lAynBUI4RX+NzMNLrHEEh9dLInnEu873q5T/e2g24hoJxHTrKTXjDHWcedozu44o6gM07yiFQd8+41DXrg4YL2b3vf724Mm5orlh7fH7AznJz9vJRGfvrzChVPmBFdXWm70GowWJWkckIY+qH04L6i0o9+K0Qacs0yygsp5EpmEkrQ2B3399X3aaUSlfT7i4aRgUVQ+ZFtAWVm0NlTWURmHkJJYQKwk3YbviQ+kZJwVfOO1ffbGGe0koN+KKbTl7miBsQ6tLUIIvwYQBuSlOfVcqJXRh19T43xDy7GD/ZjQW+5VbP44zcvfSxPQWVD4k57KOqRwvItIVB/2DiekMFQghfT5nc6htWNmLb1GRLMTMp75k5rKODKtqeo7vRfB5E72P3Fe5RRCkAQK4/z+Ms7hsEgpaiOcIw7ryxE+T7ZWNr99/YCfenqDpO48N9ay1k343NNr95FO8OP0K+ttvnXtkMmipJ2G9cmkPwGsjEUK+J9/cJdZXiGAdhpxeb3NpbX2Q2UPSyyxxEcbS+K5xPsG5xz/5KV/wq/981/jpcOXAO9U/+u/8Nf5Ex//E+9qlBaHvoryO9cPCZRkOC+4cTAljQLiUKJExJWNNuNFyTdeP+Bnnl1/aE/s4lqbjV6Dg0lOoX0u5lonIYnu//g7AAFX1tosSs3+JOfuKKvDr72ZZ5qVxKFiu99gUWpWWjFRqGgnIVIKDicZO8MM5+DSeoujWcE0KxFCMi80hfZNRXllTwhJVVkWTjMNSqT0TmCBYJaXHOWa8aIE4SsHP3ahz7NbPV7dGWOsQ0qBNc630Nh7I9QH8x4fhDYOJf04+HT8zrshST8KeD8zRpXCG3V4eLz+dnE8VvcRSoI0ViAExriTbFkhBKudFCUF80yjDSShopvGVFV+qoWKE3PZseLqHISBV/gljkBKrPWfybIy1EN9wO96WmexSO94jxV5abi+P6GZREgp6DUintvqsT0422V+ZaNDZSyv351w63B+spPajEMaUcDtozmtJGKlleDwLULfeP2ARaF54UJ/OYZfYokfISyJ50cdtj5IfMjVMGc51f/K7/8r/PnP//n33Kn+9KY/aP3w1pAf3h76rmmnSaOAS+vNE5Xz9tGcG/uzMw0KcajeMnpFCkG34SOWLqy2SOOARVF5521tbnplZ0SpLdcP56y0E9ppyME0Z1b4sf/RrKAy9kSlGbR9ReYs1xjrTlpi/P1505LBYfG7eoeznDQK6DbCE+JghCBQMM39wfjSeptuM6IYZRSlqY1F96xCJ2PztzhWG7scqR8bc97P3HxXN0QJARKBFPV7497+63287yuloN+K/K6x8eHunpD6lIRbB1MaUUgaKRqRqlVWX3/pXev3zE1wL8rJm84cjVjhnCDX+uQkRlCbloTfB42VRCAwxtKIQ1aaMZv9Bp+4uMJmr0EYyDPNf6chheD57T7bgxYHkwxtHaHyprhvvLbPeie970Rwpa2YFxWv3Z1wrt9YdqcvscSPEJbE86MI5+BwF3Zvw+jIH1XWt2BjG9q9D/ShnOVU/+IXvsiv/uyvvutO9QehpOTj5/sI4GCS1/tgim4juu9g1Ukj7gwXPH++d2aP89vB+ZUmtw9nzPOKg0mGlIK1jie2o3lBpxFjrWNvnJHlFc0kZJZVlNrU0UUVEsHh1HdYP73ZoZtGTBYllVHM8wopIQ0UDkdRJ4Ef751KIZguSkZzQamd77DGE2KpBLOs5M7RnKIyRKEkjUOs9Tt+i1IzK3wzEbw5mfpxJ5wnEG/fXf52UVlP8FpJgJSSRVHV74lDOb+veRYC6XcxnXOkkaLQFuMca52UO8MFtl6fqKxvmPJB74ZCO7b6KUkcUC5KJllJUWmqU2/ysaJ7svOJNwoVlalrODUCiCOFACrrc2ATGdYmNksUBHWurEIKwVonecc5mu00vC/k/dvXDrC4h6YP4NXQ4axgd5wtiecSS/wIYUk8P2pwDq69DK//EIyBRtNLV6/9AO7cgI9/BlY/nE71P/3pP82Xf+7Lb+lUfzcQQni1pZNwfqV15nWUEujKvu3aR2/OcUSBOlEoz/UbXN3q8u1rh9w6mNNtRHU1pSaOFM+sNrm+NyVQgvGiJNeWdup3UMeLAvDGDSl9N3szCRnOSpSAXiP0+5QCkjDAOoesay8dfr/0mBlk1XETjabbjJFSIBGEtUt6XmpaYcBKJ2VRavrNmFleYY5mzIpHUZuleegYpxVAP8Z9f3cMLJCXhij0rm1jawX0VHr86SD54zF4UH8+cm39TrBzaOs7zvPhnMpYcIJASRwOWSuRe+OCcVbSqjNn9WnSefxn/TSjQBBJSRIFFPUJkxKCMPRxYcZYrAFVq6ahUvSTkPOrLZpxiDaW1XbK4H0gg/NCv+lJYqgkWaEfefkSSyzx0cOSeH7UMDyAN16CpAHNU11vnT4c7sHL3/WqZ/x4FIJHdap/5Re+8rad6u8WjdgrSJW2hMHDY71FoemkEeFbqJ37k4wb+1P2JjnWOlppyKXVNhdWm7W6OsA52B0tEMeEdNBk0IrJS02pLeN5ySSr6Ka+OnNeiNpk5AllJ41oREHdtS7ItCUvNVJI4kDRTAKUlDi82nRsyj9NgfxlhkBVNOMAqRQ4cE5gtKUKHGVlkHXMzUY3pREpXtkZsSjtyRg5DiRRIP1o3VmMxSutTyg8GXz8+6bHawnCuffcJnQWCuMozD3SdLxr+SAkPj9TCImxfidT4thea4ATlJVGCH/S4Run/EjcIWgmIaXWGGOpKslhWVBoczJePyadSvj8z1AJ0kj5+8GyUhvWmgkkoSRUijhSFKXF4upayZiNXoNISeb16skz57o04oDDaU5eGQIp6Lfitz1pOK7AfX13zK3DBVv9kpV2TL8ZIU+tDVXGnRiYllhiiR8NLInnRw27t0FXMFh/+LL+Kuzd8QR06+L7erdnOdV/avun+M0/9Jv8/ku//329r0dhpR2z1knYH2ec6zfuMxwUlaGoDJcu3u+Cdc470vfHGaXxhHFnuEBJQacRIQPBZFHy717bYzTv8vSmj1+a5xWtJKDfTNjsN1BS8MbulN3xgiQK2OylzIqK4aKiNHNv9GjFOCEYz0uSKCAKfbh8qCRRoHw3No6y0hxOrXf3Hj/OB/48hqljme6OPGnIKgPOV2QaYzmc57STCOtcTTgcvWaEoILjsW3i3flHswJTNxw9ybDUyt9jfJiB8iTQWU8IpfzgM0xP1E7pSSd45dEKHwRfGUuoFEr5kXgSBj4twfiTmGYS0opDDmYZc22wRmOdQODH9tqe+lzVd+bwbURZaek2Yp7e7BAqSV5/f57abJMXhh/cHtXKqSUrDK/uTEgixcfO9/m9z59jrRPztZfucjDJ0cae7Ec/c67DxdXWm5qBFoXmm2/ss3O0AOdbk3ZHCw6mGRvdlMvrbZSUZKVGSfFQUsUSSyzx0caSeH7UMD7yaudZkNJLRdn87MvfBd5Jp/rjRqUtnSTkezeOeG13wko7YaXlx9BFZbiy3ub8qZ0zYy0/uDXi9d3JyVj91Z0xQgiubnnFRgrvIs9LzTffOOCl2yOk9KPMrLTcPjpille004jdcUa3ERMof7B8IRqwN1qQlYZCG5SSpJGi14jIS83hLKeoLL1mhJKCtVaD0mgiKZmXBpxjUVRvSXgqAzqvwIGSIKXAAUWlSaMQpY7bmQRKSpRStBuCOFAYHJNFQV5orHXeyPToSfwTg8ctyAruVYba9zNL6RE4VnFPt0i5+ufO+gah4/OlNAq4sNak0o5mrGglIdf3Z/WKhsQ6R6D8n6NF6TNshcM5gcPHFD3o0BeijnlCnDQarbYTVtue1CXaE89BM+H1+ZROGvHJiys+W3NRoOsihc1+k5V2zLfeOGKal6y2E+JQoY1ltCj55usHAFxaa/Mo/OD2kDtHi/tOHu+OFgRScudoThIommnINKu4eq57st+Zl5q7o4xp7nehB62EtU6yzPtcYomPGJbE86OGIIBs8SZXcO+bw/2ddqo/TowXJd98fZ/9Sc6gDoLfOZqzP17w9GaXzz+9zvmV5n0Hodd2J3z/5hHNOGStkzDNKpIooBEpbh7MiANFJw2pjGWWV1zfn9JOQn7muQ2UlHTSkB/eGfLa7gRtLGkcUBlDWZPJbjdiNM+RUlLMPLFd66SkUUBlLJMbFXEoKEpLHEhWOym744zJwiuP06wkr+x9nOd4B9Q8QLyOiYS1/mQgDCRK+rrPUEl6zZBQBby2O6YZh6yv+/ua5xVJoBhXFcbakxCEd0K0HrP4+KGgPIN8v9/j9gdvr5kEXkU0ljQJfZ6r8W51Qd3gA+Ach5OcQPnczrU6rH1vnOGco6pZubP+5Eprn8MpJDhrz3wOAhBSnGR2ppH0NZl1LFNWGtpJwKzQzAuvpkahZNBOTnY5rXPcPprzrTcOmRcV24PmCXEMlGS1nXA4zXllZ8y5fuPMsfskK9kZ3l+Be3m9TRz64oTxwvLq7oSfuLzCJy8NeGazixSC3dGC71w/YjwvvPve+TWAjV6DT19eoZmED93XEkss8WRiSTw/alg7Bwe7/qgjHiCYZQEygO7gPd3Fg071Rtjgiz/zRX7lZ3/lfXOqvxNoY/nO9UMOpjnbgyayloaMtQxnBdY6mklwH+lcFBX/5uU99sYZqj6Al9qQlYaVdsy80Hzn+gGNKGC0KDmY5MxyzWo75tWdCecGDTppxNVzPcaLihdvHNGIQ5pJQBQq8sqQhookDJnZEgHcPlowzSu6jaiO0fGj7kJrug3vxD+/0uKmg1lWEDpJZS26JkGC+pzhEc7n451NpQTtNCSQEuccR7OcUhuU9Pd5aa1NGAiyomKWlUxyr3b6PUFxskf4dsnkjxrpfBRU/dqf9dqcJt/Hu5NvRlID6U8exKnrS3w8kXWOUAqazYjSGOa5BgeFNtjaYe7w7T3TrOT6/pQLgyb7U58rq5REa0sUKpJAYgJJVlUkQno13FhU4Bu66nIi4F6sUlifBC1K493sUtQB8CkH0xytLZ1WfGKsm2YlxvqTHa0t16dTnt7onjnt6DUjdkcZR7OCzTNqaue5Ji8tK617h55ASS6sttjopYznJdO84nNPrbFWj9iPW7yKyrC10kTW91sZy53hHAH89LPrqA85Um6JJZZ4e1gSz48a1re8e/3grt/zVPVbWOZwtA/nLkLv3RHPR3Wqf/nnv8xWe+t9fBJvE9bAZMTR0ZTJ3TEbG2snpBN8zNJqJ+X24Zzbh/OT2CNjLf/rK3u8vDNmtR3TiL3hZzjP2RlmaGNZFJpFUdFKIx+cbfzwc15obh/NmRUVT290Gc0LAinoNGM2uinbgyYH05w7RzOkiFjvNsj3Ndq4e073ytBJQ29ecrBS1wGO5gVHs4JQSbZXWtw5WiAFTPN7EUhvRvKU9GNYY21NUiUX15rMF5p+K6aZBvSbMfNck1Wapza7hIFkkpU450PjZT3ulR+AeedJxjGRVNwj+dWbMEn34P8LCOqszQcVayn9CcfxdY8JX14aDP71L7TDYeqyAH8eqY1B1iYjJTyxcs4h84qdcUYaBlSxoar8bRvr47iMcT6KSfo6TXGsnHLvfZbSm5Ladc2lzxq1XNufstJKubTeop2GvL47wVrHuX6D20dz9uqGsONSgkVhvAnpDHMf+O+kddTfpzNe9/qBHeecAicpFFGgaKWhXyk4Fa90ezhnmpWcX2neR3ZDJdnsNrg7ztif5GcS3SWWWOLJw5J4ftSQNn1k0kvf9SaiY9dAEML2ZXj2kyDfmQv0rE71P/rsH+U3/r3f4ONrH3+fn8DbxP5duP4KjA4RwxnnJiWNxRbzc1eoWr37rtpMAvYn2cn47e4w4+bBjFYc0EkjhBDMiopKO/JS8/KdkT9wCr8rudlrkJcG7RRRIOvqTMPru2O08Q71fiOqd+ccw1mOEJL9se9U18ax0k4YtGPyyninfBKwP8pO3OZhoFgUvg5QG0tWarS1KKkIpcU5i3WcqJ8P4vhwa51DST8mldIT0H4r5vnzXXrNhOv7U0aLkkDCD28N2R0vWBT61M6ku+/23g6Oyer9t/DRxvFzeDfrrqGEKPSfFWMc01zfe01qgv/ga+SAyjofqSQExhoqIylK6zvUrTvZzwykI44CQuU/M0mo2B/nGGv43FNrzArNneGCeaaR0p9oKaHq0TkoKWrSyqk3ul7JaIScHzTZm2Y044DVTkIYCPYnGYfT/MR0l5X+BKyZhHRSv1ajrWW6mLGwlv1xxoXVh2PNvPLuCxvOQq8R1d3uvqXrcJozmpcAdNIQ5+DKRptmcu/QdHe48AT9DIXVd85bxotySTyXWOIjgiXx/CiiO4DP/iwM92Ex8yP3Ts9HKr2DcdP72an+vmJ/B77/ddAaugMq1aEo9hkMdwnyGaOnfgLdvDfy98dXcXKMvX00Jwm9QeE4I3PnaI42fjfzztGCADCVoQzqgG8cSvhImHmh6TUjDqc5Ugg2eymtNEQJyWu7E/bHOWHoSevdUYZxjm4aEscKhTh5PKvdBlmpGc1LkkgxnBfM8hIpFbOiwlrfRBMEEuMsmLPHt/diccRJ1SXOj26Ppjkg2OilTLKKr7+2S1aa2qVsKSp9plHnHZHHdzCW/3FAZYHKEErpczVP4c2IrKlzOqWAvLSEytYpA5AV+kSBNtYnMcSBNxZp46iMj+VSUnJptc1Wv8HRtODW0Zyi0jgcQb3vK6Vknlf+RAkIlKgJZEhROW4ezTDGcmF7wKAZcW1/iraW7V6TXsOfvFzbn3JptUUa+kOEtY7xvGR7pUVRaW4czNgaNB4abx9Mcta6Kf3Ww+1h4JXMy+st/qcXd04KE5JQ4QRc25tiHVw91z0Zp8OxOvroUyWvGC8/oUss8VHBknh+VBEEft/zXeBxdKq/b7AGrr3ipb86CL8RA2HMLG3RmuzR2LvB5MonTn5lnlc8t32vz3mal3QaEUWp+d6tYd0iZGkmikYYoCSYutbSGMdwXrLWSam08RmZ1vhebAtOOMaZvzwKJHeGcywOrKTQhsrYk/1SZx1JHHAwy8lLTRIGJ7t7k6ykMj5DU0pHXhiCQJBEvrJQCkGlDaW2dUPNPag6rEAIHxZujN+LG2cV40XJaifh9nDOeF5y62iBsY5GrTg9aFJ6MwQSlPC93KejeN4Pw8373Q70YaOy1C1R96ubjzJiyZpw4vyep5ISIQQSfJ3q6dsQXjW1VhMqiYWahAZMs4peMyZUiiDwKQrnV1rcHS5IIlWr5paFEKRRQFgbcdpJ5I1JxjCdlFw91+WpjTY39mestD1J1M6x2U8ROG4dzrg7WnjHfH3a004jntpok2sfr3Rtf8ZKKz4x043mBa0k4vnt3n2RZg9is9cAwUkeb14ZrHP0mjGdRsT+NGM0L06qb1c7Ca/cGcEZZNavnQja6QdrdlxiiSXePZbE88cMj7NT/X3BeOgjo04ZpNppSL8VczAtCNMO8XgfVWToKOFwWtCIAs4P7sUoJaFid7jg9d0Ze6MF01yjBJSV4cgVWAfnBw2CUJ50aJ/rpZTGsjfOyEvDLK8ojcEYy1on4eJaixv7My6uNWlMAhaFprKGJFK04gAhFbOsRAroN2MmWYlxlrzyTvpes0GlLaNFjhA+0qadRieqmcVSVs4H1pt7O3pxAGEYYIx3Q9v68bo6AHy1nRKHilsHCwpdkUaenMwKjXuHXezWgqjzLcUD43V4e6aas3DcynNMvJ7c6Pp3Bv0Akz4mnQ9ms4YSGklIWfkTlTgIfCtQpZkV5oR0SiAOBEopTxKtIys1aayIA0WvmRAGkrujBXGoOJjkBFIgpUApyaCVIAUczgq6jQht7Um9pZCCRU2UO42Ipza6zPIKbS0rLe9aP5jmHE5zOs2ICytNqCOL0iigmYb0GhGBkshScHG1yeW1NvsTv26ilOTKRocr620GrTcvr9ifZHTTmCtrbaZZ5XvbA0mvrsC9eThjZ7g4IZ7bg6ZfITlFRsGvneyOMgbtmLXuslJziSU+KlgSzx8TvHz4Mr/+L36df/iDfwj4TvW//IW//KE51R8JrcFoCO+RYCUEl9c7WCYMxzPixYK9wwnzyNR5g4P7Rntbgyb//ddvMF4UnBs0Ccd57e51VNayyDWBEqy3E47mBeDzDwet5CQqKVSS84PmSYZgUB+420lEqBRv7E4otfVRRYuKQGpK7dDW8cy5FCHgcJLX3dt+706GAoTfa8NBJ4lAQlsIxgvhm45Kw6LSSCHqrEY/5owC//e80jjnaMUhK520JhYwzXKmWeVJrHXvyjhkAWssUvjna61Dv43dTnWKUJ4mpsdE7EQ5PXUDH7WIprcTtXSf67029fgkAlFnbfrLjfE7vc45nPD/CN/rUhdEgT8hCqxlXmjmuSZqKUbznCgQTDPNvKyYLSoaUUCaBFxea7PWSdgdZ1Ta+oUP55BC1s0/jn4zJlSClXZCKw3YnxSkp0w8SagYzUtvVEsi8kozaCcPBbjPc82glfCpyyve4FRZAiXuu603w944Y1FWNHVApxE9tL+ZhIpRXT8LsNJO+OTFFb5385CbhzOUEAznOUdTr7BeWGmSV+ZttyYtscQSHy6WxPNHHLuzXb78r77M3/n63zlxqv/yZ36ZL/3clz4cp/pbIQy9UaosILpHJpNQ8dy5HuPQsFiAPNen3euy0Utpxvdn+FnrTUShUoTKH3iPlajKWGIlWVQGU1clzsuKyhiGM0sSB6y0Y9pJxGefWqURB3zj9QPuDBd1zI2fgyslPTETFiEEpbEICWGgmGYlgRQU2tFvRgzaCeN5yXBeYIzP9DROMFoUGAtbgwbPn+/TSgLuDhdcP5hRVYZmGjFdlOTGUlm/H6iEd9ivd1LmZcXuuMBY50PsS+MrFd/jW+BF17Np4Vk/PU1ylazbgB5x3WOEddzPE9zceR/OajY6Js/1yu19qwmxBOFEvfHrDUW6NgKa2mSEEEh8GLwQoLUF/MmLdZZK+yD4JPKNRYfTnJ2hD17f6CXcPJhR1RmeT2+2ubTW4fy8QCm4O8wAwVY/pdOI6TVjhLPcHeeEgaxJYn7mWk0rCek1Q17bzU8c58coKkNeaV640PdlBZJ3VJP50p0R379xxO2jBYdTn/DQb8VcXG2dGJKMdQ/tjl5eb9NphLx4c8g33zggKzSrnYRuM+KN/RmHs4JPXVph69TkY4kllngysSSeP6J4Ip3qbwedPvRX4HD/oR1WJRwDmzF4/lnOP3fhkTcxnJekkTdmzAvvOJ7lFa0kpFuPC2e5pptGLApDGsE0q0hjxUarwfagydVzXc6veNfuTz+7zs2DGZOsZDKv2OylGOfIi4o0DnBOMF4UGAetOGS68Ld19VwLYxx55Xc340DSa0YkYcA0LwmlZLgoSWPFZ66sUmrD7jBjvKiI6uPuVr9ZP37fDR/Hio9td7k7LjiaFn5v1PhYnWOK8F6VRCl8LE9Zs0IJBIGg1Gff8nFmpePen2+FSt9bJzi5X57cMfyDBPm4+cjWZzTC+dfBeo/Yibp7bCjSxhNJ6wDlENLvGy+KsiZwol5HEEjh26qE8AR9vZuw0o5pRN65vjfOWe0mxGGIEIZm4veE41Cx2WvwhWfP8Y3X95FC8JmnVmnFAVJKDqc5r+9N2Wo26TdjjqYFw1lxYiDKK8N2JzkJZt+b5AznBWEgCZWvsNTG8dRG50xH+5vBOsf3bhzx6t0xvVbMNC/pNyO0ceyNFmhjeaY2FWlj2TyjJjONArLS+MzPbnofad6fZHzn+hHtNKKdLsPkl1jiScaSeP6I4UnoVH9PkBKuPA/zue+l7/S9CloWMBlBbwUuPPXmNyG8Irk5aFJVlrXSsDdZUNbjuFIbwIfO/9TVNZ7f7hMqSRwqokDRa0b3hdF30ojLa22ml1f5zvUjv1MnBCudBlnlx51C+ut1GxHaWI7mBV94botQCf6H792mDCVbgwbN2DfC3DmaM5p5Y1AoJN+6dsDuMOP6wRThHE5IxouSWVYRR37Hr52GhIFCSEUzVifNMwjqWJ33aYTtHELey4D0qt69W33wPqS45+Y+K3j9rJ+fpYg+qaTzNI6rL71iK8DZe7u0tg6VsMeZoHWWp4PK1Cqng0hJBq2YRhSyay2FNoRCEQaSQAkGzYR5oam0IY0Un7i44j8r7RRrHbvjDCUF21tNjqYFofQnPlmpT1YvVtsJSknG85Kysljn90U3+02acYgQgtVOwuGsIKu0D6QPJCutBGMds7ziJ59eY7PfYGe4oNKWtU7K+dUWW/3GO66pPJoW3DiYsd5JCQJ/4nc0zek1Y/qthOGsYH/sI9HWuw02zohG2h1ljBbFfY1Jx1htJ9w6nLMznNNOe+/8jV1iiSU+MCyJ548InqRO9feM/ip88vNw83U43IW59mP3S8/Ahaeh+egeaPAqYTMOGc9L+k3fGNRMAiaLgvFCM1nkrHZiPvPUGlfWO3QajzZVGet4+c6IN/amzHLfi/3KzoyjWcFKO6HSjiwvWO0krHcTjPWd0s0oZHulwUor4RtvHGAcDFoxqm4b6qQR44XP9bw7ypiXFUJAIwxYW03Q1nE0Lfxo38K5XoOnN9t8440DilKThqHPBLXupJnp3ZDOev0PyynV0gFOIKQD439W6Hu/8+B9VObez47piKyzHK115KeS2UNV137y5LrcI+lTAyzOZ3LWD19JaDciFrlGG7/XGAhFUb8AlnvjeMG9NIIklLRqV/nRvKSdRjTiCJwjDr2KN6k/C1IKjMkwxtFuhnz6yhrrdaNQoARCSda7KZWxPHuuy6hTcmN/xsE05+bBjDQKaMQBv/dj51irK1pH8wIlBZu9Bo1Y8YNbI3aGc6QUtJKAO0dzAiW5vNYmKzXjecF6r8FnrqzSTkOe2+ph6z3ld4uDid89PQ6Gf2q9jRJwNCuxzjLNNDf2p/zk1Q0+eWlwZg7o0SwnlPK+qKVjCOETIg6nxUOXLbHEEk8WlsTzRwBPUqf6+4beine2L2becBRFPjz/bWCz3+DZ7S7feO2AUEmaSeDDs1sJlVmw3kv5pc9d4icur77lbb2yM+L7N4/oNCIurLS4uNrm/Djjay/tYIzlua0uUkryUpMVliDwY8okClhpJfSaMVc3u3z3+iEHk5ys1JTaopTg8loLIQTfGx+QRoqVdsosrwiUJCsrHF6lCpXk9nBOI/FETklBVmofYG6d72B33Ec+TxPBQPkmHVnvnR5D4duPJIIwgHlu0K5WOeuoGyfsier5KJy+7JhipqFk0EyY5uV9xLN6m4ntj8t89Cjn+fGeppK+krSZBAgEWWWQEkIpmeUVi6LEIrzKLHzb0PE67PHoXQKNWKGkRFtLUO8rRqGiFSsCJZgucmaFptK10Yhj8u+oco2S0HEh692ESEkCKam0JQr8Z0AKn+m50WsQKkm3GfETl1dopxGrneQk9H2187Dbu9uI2R1n7E8ytvu+69xaKIwhUopz/Qab/QZJTf6EEN5A9h5QanufSppEAVe3ekyzikXhY8FW2gk/8+zGIwmuEOLNP4fuXhvSEkss8eRiSTw/wniwUz0NUr74hS/yqz/7q0+WU/3dQoi3VDdPY15U3Dmac/NgjkTQa8bsDBfIWsHSxtKMQ37+hS0++9TaW97eotBc25vSTqOTAznAWjflhQsrvLwzopmEPLPZpdDGVxcqwcEk51y/caKkXl7v8NLtIaNFwcG0oKw02jqu708pK0tpDCuthFYcMssr9ic5VX17PjoJRrOCF28MQUC3GfngciEIA4Wx5sTJ7lWze2N3r7r5yB0hIJD3DD1pLDEOKm2w7v4jtgWK9+D8mReWSi/eVGl/1E7nWb/xTojoMb15kICHgUTiG3iODVEnpFH6ukcpHNr4liFnfatQHCjSSFFWhsI6ZG2gOt6rVQqagURbKCqLlJ7cKSWYLCryygCadpJi45B5XjEvDc7a2mAkULI2EoWKZhqhtSarDF97eY8/9Mltuo2Qo2lBvyVYlJrtQbNOPXAsSs0LFwdv60QKvBJ9cbXFxXe4p/le0EwCdF0BevyZkELQbfj1FOfg/ErrTVXVlXbCa3fHtfnogc+r87vUDzrwl1hiiScPS+L5EcRZnep/+tN/mi//3JfZ7mx/2A/vQ8FwVvA//WCHN/Ym5KWPk7HO0W1GdNOQfr1L9vz5HluD5pnjurNuc5ZXZzplz/UbHEwzru1NWWuntFKftbk/zmkmIVfP9ZgsSl7bnfAvv3eL775xSFFZwlAiHOTa1Lt/BoFgb5JRVgZtnTfxCIdAoGs1M5CC4bxAKcnrd6ec6zdqxVMTKN+dXZResZR+QO8VNHccsn1vxA2eyBkrfL0iluIMs8+7QSA4iWDy3fAP10ce41G09vT1lYBQCSyCJBTklfMq4Zs8BiXv37lUQpDGikadcVqYOlNUCGzNQLUFW8/UrYMsrwjDgDCQNOOQwtRqsLZEkSIIJVmhPcl1EoPAOD9+D2tC2IkjklCRFYbSVBzNMgrtvOItweK73kvriXESKdIopBEqitqQdDTNeHlnxCcvrTDJKq7tzei3YvqtiHleMayzLZ/Z7L69N+hDwlo3pRkHjBe+3MErnRofIOW1+q3+m1debnRTVtsJu6MFG73GCfk83nsdtOJlbeYSS3wEsCSeHyGc5VT/pWd/id/4hd/ghfUXPuRH9+FBG8v//IMdvnv9kDiUdNIIJQV5ZZjlJYVW/J7nN9leeWcKj6nLrs8iqV7p7HFjf8qiqFiUfkQ+aMd00pBvXzvgO9cP2Rlm3BnOyEvvbM9KfdK3LmU9HHfe7Xw4LUBAGinyyuKsV4eiwJO3JFKESlEZg7aWS2ttXrs7YV6UJGFAFCrCmmjqU5VFofRVm6chxXF2pB/bGtx9RPA4i9K9xZj9QWjnR/i2/v0H9zjf6QhdSr8OkASSOJBUpoJA4Kyj3wyZ5pq88reohB+TH+8HCmBRv97C+Yagqq6FMg6EOLV2UD/X49egMH4fNY0Vi0ozzSq/5qCEDzyXXlFXwmerKikwwqvKpbEsSu1H1FIQhpIojDicFrTTsB4HCyaLkqIyWOFOVPlA+bF0GgfkpcY5eH13wma/yUorphUHNJKARWGIAseVjQ7PbHZppyGjeYF1jkYUnOxSPinopBHPbff4+uv7/PDW0KvFrk5jsI7ntntv+ZjjUPHpK6t8640Dv6Napy8Ya32u6KUVGvGT9byXWGKJh7H8ln4E8MR2qj8h2Bkt+MHtIUkY3LfTFoeKRhxw42DGt64dPpJ4WueYZhXG2vsO2mmkUFJQ6ofDqbNSczTLWekkfPxCj24z5u5wwa3DOTf3Z7y8M6qrOg1aW9qpN5Esco21+NEqoq409KNbK7y6aVxNFp2r+7YdSRiSxgESh7aKaebjoZJIkmufU5pGAXHgqxgPJhlF6cPgQyWx1pzE/vgwfW8W0cY7nh8khEo+HCH0tnFM4s4gre90b9NYSEJBpBRZZRD1OLqoDKUG5wSh8icISnr9LJBecTSnHkBWGR91VPeXO7hvN1Mpb/rCulNRSP5EwdRLro04QEmJcX6vNlCSKJAEKiCrLKWxVMa/X0VlKSuNFJI4lFg8SRq0UwLpTWF+vxNc5XvYHa5ujXJIBFGgaCf+ff/kxT6bvSaDVkRWWipjiANFMwm5czTnuzcOOZr6TFdfo9nk6c3uW4a63x0t+OGtIUfzglgpnj7X4cp650xzz3vFhdUWL94aURlHFPhd17U4oNeMMNbxneuH/PTV9TfNBe01Y37P85vcHWWMZt5812vGfq/6MTzmJZZY4v3Hkng+wTh2qv/6v/j1J69T/QnCrYM581xzae1hYhkqSSMOeGNvQmUs4QMxMDvDBa/vjjk8ddDeXmnyzGaXQSthrZuwN8rY7De8Mmgdt+vYlsNpzvnVFt+7OcRar65t9hrEkUQbRyuNyHVOoQ25NoDABzl54pEqiZQ+ABzhCKWk1D78XklJoBTNQBKEEqV8WLdE0UwVwsHFldb/n70/+ZEsS7P8wN998yCziI5marO7R7iHx5xZmVUcMslmIbsXvWiAQC1qUSCK4IYrrlggQFSCIIoAiysSIFgb/gdscNnsZpFFJIs1ZEbG4BHhk7nNOsssb37v3l7cp2JqZqru5u7m8/sBmR7upjLoUzGVI9/9zjmUpaLtZTon1DZBCYpSm1ZkrSbPjqYtUx8tn9WEFkVF8VzL0dle6GdxnD//avy0d3FWqelakJb69s7ZHmNRrkPXy1JiCEE7sJGRIikUliHq3nRtyPIcc232UQCy3pe9QAybQtRudIVvaxOPYegDYNsUhJ5DlOX651ZJhKHbqFZJQTe0yUqp6yefy1JNCoWgIs4rTAMCx9R7owhUpfcUDUMgDNbPrawktmlRSf09OpbBVjfg9d0eXp232fZNQGdVPjxd8dcfna4F2FnD1u8ez5jFOT+/vXmhIJNK8c/fPeSfv3fIMin0a0PCL+6dcmenw5/95Br98MVu9M/DySIlL0v+6PXNOjlBC1DD0FPLg2nM4Sz5xN1Tx/ryd1QbGhpeHY3w/Jryte9U/xqhzTEvtp2cYVuCvKiopBaelZScLFI+OJjz3pMZjm1wddDCsQzirOT3j2fM45yf39rgrasDouSI3z2a4tkG0yjndJHi2gZ3drrc2u4gpeIvPzwhKyt2+wGni4ysrLQISHKKsyB2IdaxO0pCKfUEzzRNbEOHtEtVUkktwlqeRdtziPOCqqqIU4VlSfKyoh04tAOXzW5JUpQYhsFmx2OySpmsSir08fF5J3BR1ke6hr4GSghkPfY7m3iaxtNp5afFMvWE8rPUdcLZFBZ81yavitpNL5HKxERhmSZZXlBJhWcb6xWCslIUlaod/HpSmxey/h7BFgLbMkjO5z6dwzC0EDOE7jz3HZuiqigqReA6+n8XEsOoJ5yWnqouk5J5VCCl3tkUlha/sh6pKp6mClToI/QnEx1jdOZOr+pg+RyFWermLEdJ8kow6tggBG9d669F53myouK9JzMsUzBsPzXVnNVQ7k9invRW3L5g//OdhxP+2W/3sS2TW1ttDKE3g1dpybuPpziWyf/zD2688EHt83CySBBoQ9zzEe+moZ37x7O4EZQNDd9yGuH5NeNb71T/AuiFDqZ58ZE4QJJVXBmG2KbBIs51WPss4YODOWUlafs2Ram4udlev2kfTGIedXUuYlZKsqJifxJxPI/xHYtroz63tjpYhkFclHUEUslvH044midMo4yilCSFxDR0F7whhHYyo0VJXuqjcMfS4eFt39bHv0pnXyZ5qc0npd7ZdG0DH2sdgv/gZE6UVizinN1BiFSCsgJh6CP8SukKT0Pox6I6CzvXkznPNnEs7fZ3LZOyqkjr41/jgv3MT+Jlo5IAHFOQn1OoBuA6Wtidz8KUSlAWFYahBbTjmGSZTgU4nCV6F7a+Dwnklb66RVWt78Ow9bWwDINS6e9P8DT0XgiBVae7B46N7xisMkDoGtQ809FSldK1j0JYdZwRZEWJaRq0XYs0r4jP4pVE7a5X6Gm2EAih46+UUijTQCrtmj+jUroHvcxLRj0fyzB4Y7fHz25f7FY/XaTM44yd/ovmN8s0CF2LBycrbmx2nnGBl5XkV/dOqaTi6jkXuEDQ9mzK0uPDgzmH04i90cunSnwSVfWiG/08Z/uzDQ0N324a4fk1oXGqf3ZubHXYbOuw7O061xD0FGsR5yil+N6VPo9OI/7X3zzmaJbgmII0L7kybGGb2lW+THNu1YHygWvxmwcTTEPnJf745ojxMuXdJ1N8x2SeFExW2Tq+JS8rlknByTJlGLoYQpCVlRZFtRCp5ItCQwiQUiIwiNMS1zaxTINWIIiSnLKSZGWpA90RdH0b0zR1eH0Fx4sY17YopTa0VEqCUliWSVVUGAJC10LKHKUEVaUoqCec9f4nKALPAmGRzRJA74J+Fs5HJH2ckaiSCruOfTIMbZwKHBvLNIjTfD19dW2DopIYSu9IBnUCfVpo+fxJAnkt8Gt3+1nnumMaJOslVi2IbMvEq/d6PUuvM+SFpKgkRal/dpZh1FNjE8uoyJDISpKVkrzSWalnT+jsmL+SWlQXlcKop/JFJcnycv3YUp5NowFhkJeSH90Y8X//6bVnorzOk9evr8vEnGvrDyiVlJjG0w9kiyTnYBbTvaQ4oeXbTMcZ+9P4lQrPtm+v27YuWhNK84pu2JzmNDR822mE51fMN7ZT/WtEx3f44ze2+d/eecLJIqnzGgWFlEipeONKHyEU//SdJzw8WTHqeiyjgkmUrfcIk6LkybhgEekg66COfrkyCNkb6YgWIfSRYMd3WSQ5h9OYfssFdMXgKsvp+S7DjsfxQjfG2ObZ8auOFhKm7qE8G/YZ9T5lWlQEjkXoWrR8hyuDkMNZzN3DBZYwsCy9e3i8SAldG1BkecUkzrmz3ebaRoffP56S5hXCEHi2iSUEhdQ7j2kpOWd01y04Skc3uZbJZjcgzUtWTqH77b/gHc+qnqoaQoezowRFVVJWBmkh1/uV1GYhPaXUxqCzPnMhDBQSUw9zP/axqgpknZUJOsvz7Pnq/FVwLZO0KHVCgKPD2ZOsrOOoBJapf1ZZIYmrp275UkGUlEjQR/G2qKOr9HQThDYd1ZPWolSkqkLVrVOhrfMsTcOg33KRSjFd5cR1BeZl2JZRx2TVgvc58lLi2eYLKyhSnoWtXyxYDYNPH2fwEmz3A+4eLphGGYPWs8H2sygjcC12mjikhoZvPY3w/IponOqvlh/eGODYBr99OGG8TJFK0bMdrm+12er6vLc/RylFP3TpeA4o8GOTk0WCUrDd9Wl5No6lK/nuHS/Iy4of7PXXj+FYJobQTvDAsdifRqRFySIueHy6JCkklmni2Sbb/ZDJKiVK9c6mlAphGliGIHRNhAFJXuHZJp5loBBIKVkmBe3AZbbSu6SgMEyBZQoypfcWk7zEMsGzbVzT4HSe0vYdHMPANAxatn6es1VGnuasUvnC3mVVKRaJNuwUleDDwzlSu5zwaoNN+Sl3PRU6SunMNf5JlFJP+AopSUuJyJ7N9kwKRYCk33bXLvE0r+pdUJOs1DubZ/rpk6KazsSpWccZ2YYO/M8rvc4QiRLPsuh2HYZtjzev9lmmBf/83QPGy6x2wivy4mlUUlEnBZwd22f1+oQQZ2H++kg9L/W01LF1ZFKca+Xd9R16oYtAO+9Nw6DlmCR5xeOTFcfzhKuXpDGM2h4tz2EW5wxazxqBzvrW72x3XpiIhp5OfzicJhdOPeO0wrGsVx7G3vEd3trr86sHY56MI1q+3vRcpTm2afL2tQG9V2xoamho+PrRCM8vmcuc6t/ITvWvEaZh8NbegBubbaarM4e6xaDl8i8/OMIyDGzTQNRvwjpmRpCXUu8Voo+ylQLXMbEMg1RWZIWkVb//tj2bTuAwjzIqJdmfxpwuMwRacORFxdEs4ddM2O4G9FsepshJy4qiqOi3PXr1Mf54lWKIgkHdJR/XmY2OZRA4Jqs0xxCC3WGLKNHrAvG8nkSqilms6AW6OjPOS8Txkl6op2Vpqms246J8JjT+jPPzLz3BUwhZgRAUVYVjGXRCh2VSaiHF5WHvz6O9+y8nPM8ijepNBC3W1NM/Ay2gskLi2RamIVimBUUdvr8Wxc/d5jLO/mYJoVMFLANavktRlpimiWua3Nlp8yc/2OXxJGbY8XTNpW8zi3Is06AoK0xLT2il0u53XZ35NAf1zFykQ/r1f9VRT4o0l3VMl4GUZ7fXH2YsQ2CZxnqqi9DZo5fhORZv7Hb55f0xJ4vkGVf7eJWx1fXZu8Co4zsWb17tsz+JmEQp/cBd/97Jq4rDecz3r/QuvO3n5dpGm8C1eTxecbxIQMHNzQ5Xh62mdaih4TtCIzy/RL6VnepfM0LXro+iNVlRsUgKXdknJcdzvcNomzqQXCAoSkle6jd4IRSTZcpmz0fN4HiRMKyzQQ1DcH2jxTtJxvtPFiRZhdfWItWxTAahh2kK5klO27PZ7Pj0Wy55XvFkGtMPHQLHZpUVRGnJ3qjFTjcgyku8rKAbuFimwdE8Jsmq9bHrfpQTZSVFpXRAudC935NVRpprY9Miztno+lwZhNw/XnC8SDCE0FWPybOy8fmgeAWklcIytArMCklW5Hq1QJztoX7ytTd4KiA/aVJ61v0tRH10bugjaISemp61H2nhWWAaBr1AV4VWlaxrQS9vRXqes5goJevHMwWWISjKin7b562rfbZ6gW58UtotP11lPDpdabNVPa0uBKhKUSp9VB84FpVSlEn5sYLbMESds2pimwYmdUtVocsAslKb3GzTICtKDAG9wOFjvDgA3NhsY5oGdw/nnC4SKgW+bXJ7u8P3dnuX5nj+5NYGk2XKL+6Pmcc5nmVRVLq+9fpGm3/vR3vPdKu/SkYdj1HHq/edL0+jaGho+HbSCM8vgcap/tWhB0favNEPXQ4ci2Wa0/YcXNuk29L1fYukwBTgOhYj12GnHyClYh5nehpVvwm3PJt+6CGVwrUN2p6NZQocO6CqJG1fT48s0+BHN4bcO1ryIF4S1MenoEVQN3QQCh6OI4rajW+InOkqI8oKSqnFyjTKWKbF0x3G+lg3ySpidD6kYSjmccH7T2a8uTeg7Tv1bZRuX6rV0EXC6Py/C8C09BQyr8794Seou7p/CQDLqs07xrOu9fXXnWVrqnqXEG2OkWeGE6memZqW9US2kjlVpSOqhi2XWb2f+0mcPaZl6lxOwxLYhrEO2g88iz9+fYvb2x1A8MHBjH/x/jFRlpNkOnR/px+wSgvGy6w2e53VmOr1i7Mp8Vk0lay/N1FP1IXQlaeDlkNR6uinwLPII53/6Tkmbc+h4+sYp3mij85HneATj56FEFwbtdjtB8zjfD3pb/vPBxY9i2eb/Hs/3uPmdkevp6wyAsfi9d0eb+31aV9iaHqVmMb5V05DQ8N3hUZ4foEcrY7483/25/yTv/ona6f6f/Dj/4A//9M/Z7e9+1U/va8FZ/EypiG+kDUDxzLZ7vncPVxwZRhyfaPF/eMl42VCJaEsKlxDYFoGLdchqJ3AHx0uKaqKq4OQ/WlM6Fq1S1hyNI9p+TZXBiH9wMMQel9zfxqxSgsd25To2KZFnFNISdt3SIsK19bRSQ9PVkRpWcfyCBzbYBblzOKcJCtRKBZRRlbqvUvTUOsmofPGH9syabkWaVmRVzr2aXcY0g8dHpyuUEof7xbVUzPNZYKtkGBIMD9lAczZTqdAu70zpWsQz7OeOJ47FrfONQZVdT2oIWq3P9p4pM4yMZUiKSosU2C41ku3KtVpRmeLFKAURSUppX7NeY5FlOZ8dKQn2ONVglTg2RbH85SWZ/HR4RKAfstlGee1U1x3jCd5iWsbeLZBXrcRWUZdSWpqY5So1zyUEri2dvBXldSRUqWOzvIdyXiVopSgH7rs9ENubrYYtr2P/wZrLNN46a89w7FM3rw64M2rg0ud5g0NDQ2vmkZ4fgFc5lT/R//uP/pOd6qfZ5HkPB5HPBmvkAo6vq2Pnvvhx2b9fRb2Rq06gzNh1PZw62Pq/HhJXumMRt8xaflWXeVnsIgz5nHBTi/gzZ0uJ4uERZLjWCa3tzpkRUVg2+vneubIPVpEPDyOWaYFpiEIXV3BaZmCrcBnvEw5XWYUVUXXt7EtE6UUpwttEPJdXYcplSIvpO48R62Pps/knKA+rpaSoq5vFAimqwzHEhjCqAWUiW0LfXR9wb7n80jARmAK9amD4G1T4NoGpZTkF9z2+WD6Sol1hadh1OfgAoz6a86+tlQKE1FnpVZkRYZt6d3IvJSfuH8q6smqqKW3rqfUhq+sqHg8jnHsjPEypRs4bHZ9Or7D4SymkoooyzEMY20CKipJnBXaYGQamKapJ7m5JFdqvSZg1R+oXNMg8CyGLRffszDQYe3UHfSbXZ841x9CeqHLTi/g5mabH94YvfK/C5deo0Z0NjQ0fEk0wvMVcpFT/Q+v/CH/9b/3X/NvXf+3vuJn98kUlc7Ys03jC30jGi9T/uruKfM4o+Vr8XY0T9ifxry23eWta4NX+oY7bHv85NYG7zycsD/VHwRMIXhjt4uSko+OlggElcyI0oI4KzENwVbP5739GdNVRq/lErg2Uio8RweIx3lJ4Oq/QkopsrJiGZdEdcC5bZl1E45JUSoeLFc6KN0WhK5L98xotNQmi8kqw7MNHEuQFhXnTtcvnPBVCmSlKBI9ZTVMwSzSfeQChYGeJPYDh6JMKV7Sop7VLUCfHlU/hkCIp9FFZ8fmZ5PMs2mmZemRZlmp9TH1eWENZ5FLot431XWZAL6rxaNZ14BehHH253UfpWmZeLbBKtWtSHpqHVBKicoVnmMyq+O0Bi2XjY5HkkumZOv81TvbXW5utvnl/VOipERJSVFAUeku+NC1UAgCx2TQ9oiygskyw1eK0LM5C4VKshLHNHhtp8drO11e3+2S5joovxe6DNt6kh5lBUqxNiQ1NDQ0fNNphOcrQCnF//ze/8x/+v/7T7+Rneqni5RHYx3dopQ+Utwbhuz0g1f+3MtK8puHY1ZpztVhuL7/ju+Q5CUfHM71479CR61UOjZndxDg2gYobXAoSskH+3N2BgGmYTCPcu2gdkw8y2QQupwsUx5NIpZZwRs7fVqeXTvSBUezGMc0tNM9znkyiZhFGUKAaxkMQptVWvE4jjANUR/RahGx2XXIyopZlOme76rSrUPYGIZB9QktQOv1S6Unn5UCUUkqQ62zIvX3rgVbL3A4XWYvnc/5WSIc80r/P0MI3DqmqG4J1UHxsA5wP1OWlbq4YvO8AJVSUVaCSBb6ewLyUqFqc9Flph5D6D3MvAQlBIbQHw7yujrUMU2yUmIaBsu8wKrd7k/G0fpoPHBNeqFbZ2IamIag5bnc3OxwNEuYJzl5pfNildJTXM8S9EJPV2XKs052vX5RH/hTSclW1+f6Rsg8zgk9mxubT/e9D6YxD06W62iwlmdzfaPNtVHrCzP9NDQ0NHwZNMLzc/JNd6o/Hq/45f1T0qKi4zkYhmB/ErE/ifje1R7f2+29UvF5ukiZLHXjz/P36zsWlpHz6HT1jCj9PKR5ya8fTHg8XjGNMuZRTlJUhJ6lw7mFYKPjEzhWbfLxaPs2SV5yMI1JCsneKKTl2kyilJ2Bz96whSHggydzpquU40XCPM4oSr0n59dO51msw9ircwJMSUlRVVRKsdXxMYyn00Cp9ISrqvSR85mgPOMygVUpdPe1EKzyEic1+BtvbPHe4zlRXlBVCseyCL2KOC3XR9gvEz/0aQVoWSlCz6SUElMp2r6DZZlkeVlHDimklGSF3j0VgkvjmnQepsC2BC1Pm2WSrCTKK8rqqejk3D+ff75FpbAMgevoKX5ZSmxLMGh7+LbJNNJRVWmhW6N6oUdR56ku04zJMqco9fRZCO34LytFN7T5t9/c4d2DGSeLlDTXP2fQH6KcOgv1bOqqiwccBLBMSwxTi9i7RyvirGBvFNILXWzT4P7xkl/dHyOVols721dZyS8+OmEe5/zw+qCZfjY0NHxjaYTnZ+T98fv8g//1H/A//f5/Ar6ZTvUoK3jn4RSB4Org6YSx7dusUu2SHra8V5qvF2VlPYG8+I0zcG0WSaGPqs3PJzylUvz6wYR7xwvKSosJYUA3sDmZa8E4bLsUpY6xqaTe1UzykkVScDJPMEyDQerQcm2itCTOStq+w3Yv0ALEt3kyjfjwUNIPXFZZwWSZc7KIyQoJqPVOIUpRCp0VGiUFRjfg6rCFlCuOl7ruUpaCSql6OvjsMbI4M9ucQx/dG9iG3uu0TYVj67rH13Y7PDhZYddNRoHX4/7xgnvHKx1oz8eHvRtnYlm9nAA1AKM+2paVXtmoFBhSYVuCKCuQtWX9/MTWACxTO7+l1LulQundTCFqIWcaFFJnYFZSUki1dvoLdP3n+ZpPIaDlWQhD4NomRaVwTEGnFzBdprQcCwQ4tkFWpw20PZtB6DCNclZZTlkplklOVlY4poHV0okFri1YxAXv7s8RQvDadofHkwgpYacX6F55pXQDkmXwzqMJeVHpaKtSYVmCluswaLkU9erABwdzbNPgzk6Xd59MsS3jmVB4z7FIi4p7Rws269ishoaGhm8ijfD8lFzkVP+mdqofz7Rh5urwxTexlmczj3MOptErFZ6mIT6hXeZpKPfzTFYpB9OY02WKgd7B3Or5tDznwp3QyTLjySTCtU32JxGBa68rCE1DMFmlFKWkKDNcWzfMzOOSZVqC0t3cnqMNLAezGN8x1+01k1XGveMlo7aLaZj4tkU3sEnyimWak+RaYDumue4TF4YBqgKlsC2DySrDMA3mcUaWawFiCEW9Jrk2FJ014TxfC2lQt/YoyCtF4GpBIyX8/smMtm8jK0mFwTTOifIK44I55kUTR9vU0VJpVlK8hOo829s0BDgGZFJ/j1JKklJnkNZFQwj1NMT+TEwrCY5tYbv6eid1oL6e+kpKJXAsk0oI2r4OVs+VRJ1NTGtxLAQ4phb3pikYtQNub7X51YMJTn1UXiqI84rAs7AEzPMSpRSuY7I/jSkqvW5R1v9U6GB/gEHLIc4r5nFOUUl+cnPI3rDFySJllZYkRcnVQQv3XNXlRsfneB6zMwg4nWe0fZuWZyOVqmtZW+wNQ+4frygrxSIpLvw76dkmQgiejKNGeDY0NHxjaYTnS/JtdKqvsgKrbk65CL82W7wMul8643CWkOYlnmOy1Q0YtN1n7n/QcvEdkygtarPFU5RSLNOC71/pv3CUeP94yTuPxiR5hW9r5/df3T1GIbi20eLOtm4/OR8pM40ySinXeYzne68d08R3LQQCzzGYRxnH82RtLJJKj916gUs3cJnHGatURxKdLFLuHs7Ji4ph26fj2+xPV/z2yYyiFk1S6fijSla1iNaCTwitIl3LxDBgf7wkSnX4+Nlxrqr3HoWsJ59CoIRaxwtJtNg6m0YWldSCvo4Kcm0TFMyjTBucDIFvmhgIIlQdvq6vw9lU8/lPA5WEspQ6k9RQuvddqRfE77OvAShLRaWXVZFST7azSuo9y/rrzq7vWXe5sY5ZUmx1AyqpmKxSlkmJYehJqGMamKbAMkx6oY0kg7RYP64JyDrU3TB02LtjWWz1fALPJnDNuv+8ohc4nEXPV+gwfqUUcVqRlxWhZ1NViijVx++hazNqexiGDmWK0pJh28M2DTq+yyzOiTJtSssLXURwbdTGNo36/iw2CHh0GpMWJZsdj1VWkGQlncDh6ijEcyxMU6+ZmOLj/04u05f7O9nQ0NDwdaQRnp/At7lT3TYMHTB+CWWlsKxP3iWrpOR3j6d8dLigqCS2aVBWkg8O5tza6vDW3lMh2Qkcrg3bvHcwA1iLz7KSOlLIc16Y9kxWKe88GmMaBntDn4NpxPEireseSx6drCgqyeNxxI9uDNfd1krpjNAoLfCsZ1/qlmnQ8W3tJEcLj7yS+ljVMjGFwLcMkqKiqJ0+tmmwTAqO5wlFJRl2tPvZNLSJREmFUvKZKkfJWSyQwrUMHFPouKFKUmVqLYod88x08vTnUaqzaZ4WflLo2kWltEANXBOhFJUSmIb+eWWiohPoUHzftdjseCzigv1JpHdI02Jdo3nW5HORllQKSqk76UulEFLnbsZ5dWEr0fk5aoXeOS2kosp1V/3zZiHE01xPWSvpog6Ir5TOJ7Utfd0tw9RCUemGo81eSCVhJgSea+ma0KKkKOQ6oH7Ydrm91cUyBJMowzYNbNsgqMPVo6wkyXQuqGUY5JUkzkqGLYc7V/pkuRaQnm2SV5Ju6FJJqfvFDcFmx+N4nvBovCIvK1zLorQhyUsenKwoSkm/5WGbZ2ssCtM0uHe0qDvqBdc322y0Pby6XcizTU6TYj1dvYiikut914aGhoZvIo3wvITLnOrfpk71QdvDEoKsDjY/j5TaAXyl/8lHeveOlrz3ZMag5a3jhQDirOT9/RmebfL6bm/937+/10eheHi6YrLKEELH7wxaHm/tDV5oazmYxqR5xdWhzzIpeHQaIaVEoid8s1lEJ3RwLIN//eEJ40VKUlRMVxmzVU5RVReaMTzbZLMb8MHBTNdE5hVSKtJcCxLXtojSgoenFXvDkNB3OF2knC5SvDq307EMTuYptmUQuDb7kxzHFAjbYlE97dk+OxbXuY8GaaH7xk0D3RNumaR5hURiClX3iVP3dmtBKtEZl1qYKJQE37XJy4qkkJiGwsFkkeR1QLnNu/szVkmh902Fvk3dTPmxi5tCgGkYul5SKoQpcCyDrKxQteP+/M2f3xU9m9g+f0x/XoCe0+c6u1MITlcppjCIs1JHXNWi0rFM8qpis+Ppvc/AAUPQDxzSQrJIcmaljqOqFPRDD9+1yPIKUwhC36aoFLe3O9iWqZ3yUrvR96eRnm46Jp3QJXQsAttklRbrkH/PNslKyAttGErzikWc49kmu4MWQgiO5zEtz2SRlIyXKXlZcXOrA0LR8hxubendb51VywuvyaKS67SFKCueqX4F/QEvLar1B6uGhoaGbyKN8LyAi5zq//m/9Z/zH/38P/pGONVflmHb48qwxYOTJaOOt+51zsuK43nKZsdnu/fx+515WXH/ZEng2s+ITtBGnayweXCy4sZmG8fS4tY2DX50Y8SNzQ6TOi7Gdyw2uj72Baaj00W6fm7TVcoszshLSVFW2IZBVkg+OprT8RwWac7RLObKMCQvdRvMMiloeRaha60/MCR5iW2aBK4gyXTfeehaBK4OkY/SnFlcYpkC29ITxONFiu+YSAWvtXSI/O8eTzmYxoyXGUVZrnMp89o0ctbYY5n6eF3UQl8IqOojctswdBwPCtMU2EIHi8/TAoEWmnlZHyObAtsEy7LJ8pI4q+ppoMISBkLAItbi997Rot571M6b8wHu53M1zzi/62mKs6B1vftom7qPXtd+VvWUV39AOVsBKM+JTMvUge9aTF/M2VG7adQZnZUiySs2uw6mqc1SoHceHctkdxBimfDodMXesMXt7S7zOCcrKoZtlyPHJCvqliahp+Fn97mqQ/mP5wk3Nzu4nolUijgr2ej4DEKlo4vqCySEIHRtjmcJo46H55ossxyk4nCeUFS6Z/3KIKCsJB1fR2odTiIsy1xPJadRztE84e29IZsdj3uuRV5WL0wtz0TlD/YGLNOC9/ZnVJWi5ds6MzbTYna7H7DdDy65og0NDQ1ffxrheY7vWqe6aQh+eGOIacD+JGa8TNH1jLqf+u1rg/Ux4GWs0oJlUjDqXFzX1/ZtTuYJy6Rg2H52qtoNHLrBJwt5UTvBQYfPz+Mc3zbp+HoyWkiJZ1sczGKqShHs2Gx0tGAOXYt/+cExR7OEsu5rL6oKUxiMuj6/fThBCMGd7Q5pLpmsMhQS27YwDF2N6NXCL8kKeoFDXkrefTyjlIrtvk+al4xXCcs4X3d4KyXrf+p9SakUUhZYhrZqO6ZJQUVRKVRZUdXTT9c0QehVgLrcBuqjdaeekGWlIiuLOoQdBAamoUVgWpQoqUgqqXM0AerjecM4l6PJs1PHs13Ls93RVuAQOhbzJMc2Td7Y7fFkEhE4Zr0XKjCQZFKtJ7NnWEKb0wop1+anizjbVw1tY/0629to8fpOl/FCh/YXlWS6zMgrxVbXx7Z0TJHvWHzvSo9lWjBbZSR5RT90uXe84PE4YrxMeXCyJCu0YO8ENq5lMlmmjDoeq1RfGd/V92MIwV/ePSErK04Wid6rRXFlGGIYguNZwtEsxrPNtRNdh9GXPJlE7PYDHENQSkVgmZimFouebXJnu4NC8WQac2urw+8fT9di1TDEOmR+ZxCwMwjZM/Tx/8PTJfuTGFC4tsmNzTZvXu0/s6vc0NDQ8E2jEZ41Sin+7v/77/KX+3+57lT/h3/yD79xTvVPi2eb/PTWBre3c2Z1pmHLtxm0vJdqDzozhVz2lev8yk8bCHmO7Z7P49MVRVVxr+5Z32gHGKLCMrUwlVLhWCZxVRJnxfq2vdDlb31vi18/mFCUklVSELgWncDBt3U0T9t3MAwDzxFYpmC6KrAsk8CxmcYZsyhn0HEZdfRR/yLRfeqmIZjHGYFroaS+AlquCC3MhI4JKkoFdRe965gEjoUCbNNlvEwQhkAVElMYCENQlhWrslpPKA1TYFG3SQlQ9URPSl3J2Q1cVkmuPzhIvfu5TAosA4TQovks89IyjHpN4VnhaQhdKWmagsCxGLU9krzCMU32Ri1+dntEWUlWaYEoJFlR6ozRCyKepIK8qkjz6tJw+PO3qSp9m1HH442dHqFnM48KXEuvIPiOxSzKuLnV1lFRQnC60Eawju/Q8fWHl6IoeffJFJRiukqRSh+Rn72OpVIkRUmUFfz05oaecns2SikOZwl/8tYuizjn4ThiEDqMuj6hoz/Q/ObBGARcGYaEns3xLOXxRBcDLNOCu0cLpFTc2Ggz6nrkhSTKS753pcdGx2eV6j3bf+P729imwb3jJfvTGADPMbi11eZ750Tlm3t9bm61mUU5UipCz6IbON+KFZ+GhobvNo3wrBFC8F/+O/8l/92/+u/4r/5v/xVvbrz5VT+lLw1Rd0Q/v1v5MuhoGIdlWtC/4Pb6mNuh7X92Q0To2ZwsUiarlKyoUFLf7yorMAVs9vy6IeZsj/LZN+fA0UJ6o+0SejaGIRi1Pfotj/vHC7JCkpdSCx1b34luEpIUpcR2DDqeQ5RXrNJCPwehDVFZJknzEtsyAe1Yr+rj57KeBrquhWXoqW3bd7AMgygruDbyqJQkSktK42w6qOsjKynXHeNSngXM6+N4eZZzKfQ+qiFy8qLSZipBfXt9W8M4d9AtQRm6xamoQ+0N9fR43bX1A5qGdm4rdBambQh+cW+MQh+hO7ZBWuqM0TNBe15fSiBKq0s/jJxxtvfqObVTXervXQie2QEQAuKs4u7RgqpSLJIMKeH9/TmDtq4eraTi0emKvJT4no1Z6MB2XbcpyIoSENimRZRWzOMC1zZYpgWWEFwbhrx9Y4ghBL97NGF/GhOlpTam2SbXN9ps9QJGHQ9DCPaGBQjFyTzFs3X0Usu32R2GuKbJuEjxLJMoLSnKiLZnE9eGptd3e1zbaDOLdJNUWH8Qeh7fsdYrJg0NDQ3fFprfauf427f/Nn/79t/+qp/GNwrHMrm20eI398f4jvXMMWBaVCyTgrevD14wL70slZTcPZzTazm4tiDKcgxTkJXa9OHYBm3P0VE5WYnvWLTOmTKysuL+8ZJ7R3Oi1Ge7HyKVIiskvdBlsxtwOEvIy5KsKFnEhc4SxSCvKhTQCW2EEKS5Fp1lpfTeZe1gzyuJUnrSuErLtagDkEpPY9NSh58LtDHFcyy2+gGOZXP/ZEF15qg3DW0mUnXUkayd7kpR1RFNaxQs4kJ3j0t9VB/YekpoW/oYv3pWd2IisE2BVNpQVpQVeaXFnWVqxSeEIPAsBi2XXuAy6rj8yw+OsWo39/40xliXP2qebw563mz0PCZgWwaWCYFn4domjmWR5BVtX5t4srLCtUxOFymzSGetdnwbJzfZHPpUlSIrtCHMtQ1sU2AKQZQWdDznGfOOY+v9VNsUuJbg9k6HXuBiCNbd6GeT0Z/d3uROnLNK9ORcCPjLuyd1i5D+mtCzeWtvwPvWDEvo/vezCKkn84jTRUondNifRutYKesspgt90rDda3Y1Gxoavns0wrPhc3N7q0Ocldw7Xq7D0YtSghDc3u5we7v7me/7pHaR39rqgALLNPngYKYbbqR2Ah/PExzLxLFMBi1nPT2SSnH/eMXRNKbl2VwbtfFdCyUVq7TgVw/GXN9s8+HhAiklx4uEOC9QaJc9tfhbxAVJVlGWFVLp43jftbEriZISw9ACTtQTT716oA/dDUPncJ458OO8oOM7XNvoECXaPd+q25KyoiQppY5Ikrq5RymglPUk84ILVAfNS/QuaZyXmKbAt01EPcs8MzoZ9UQ1rWOHlALXsnBtXW3ZD11WaYFtG5jCwDYNdgchrmUwbHlaCNqWDmtXkvOmbN38pMgvOlt/DsuoA/UFKCWwTYObGx1msc6xXCUF8zhfN0udzFN6ocNG22Me57R8h2ujNo5lsD+N6YY2SS45WqSUUpFkJYZhgGBt6BIIykoSuBamaTIMPV7bvfx1eX7/OMoKHTx/lpFaM2i53Nrs8uh0RZLr9Yz7R0sKqd3pO32/NkjpSLBZXHC6TNhtwt8bGhq+wzTCs+FzY5kGP7w+ZLcfcDiLierJ404/YKPjv9Su6GWskoJKqbXb/fZ2Zx3S7tomizgHoeshf/9ohm2adOpj/VVSMF4mOmBcCB6NI/JSHwH7roVS8Ad3RvzoRp///Z0DlNJO/5NZSlLneW6EHoukYJEWUNcgerZFKaXeizQMXNsgL6raiGNgu3qCt24vsgSObZHWfeWhZ6NkxTStmNYZk4FtkrsWtmkSZyVlXmEonYkpebYO8jx23dJjWQJZu4aUEniuSakKHdkkoagNQGdH2YFjYZi6atMyDXZ6AUX93GxLu9FD12ZvFHL3cMGw45MVJYOWFqerpACpMA2BWd9HkpW13P5kzo7YTcPgtZ0ut7Y7/OWHJ4xXGQh9nVdpwfv7M0xhsN3zGa/0Pu3NzfY6QaGSkn/x/jG3tzsMQpey1Nc0zXKUVAhfYFsGZVVRKUXgmDiWQct/+V99oWuz1fO5f7x8pvRACN2epZRks+ez2fX4Z787oIVgtx8ghFhHIyV5xe4gYH+S8PpO+YmmvYaGhoZvK81vv4ZXgmkItnoBW6/4+FCcuZNqfMfi5laH+ycLVmmBROkaSCl4+9oQgINZgmMZHM9iJqtMV11K3ezTroVDnJfMo5x3Hkz5f/xsj/1JwuEsZh7nGAaEls1m16frOwgilnUcD7YWTHFekZUVlmlQlAph6LGjbs0xdDNR/fwrqQhcC1n/M3AsplHB6TIjK0pC32KeFJjCwLEM4kyLQ3VuB/OSYSdlpduQzLodScc0VXi2jUCQlxVSyrU73rL0fqtnmyyTksCzMQ1By3dQtfmmKHXM09Ei4d7xkjQvkVLXO+alxDT1BFfHQZkopaeqEvVCn7zgaTvS2S6odv4buoWo5XB9o83j00jnyVoGq6RktiqwTMGg5ZPlJWE9se6FznrqKJViHuVkhWTQ8pFSt1WNOj6ny5SykszjjJZvYwpB19PX5Ppm+1O/Tm9udjiZpxzO4nVrUSUV8zhDIfgbr23QD13uHs6ZxwWHs4RVlrNKdJZrO7DJC8mTyZJpNGCnEZ4NDQ3fUZrffpeQlxVpUWEZxgv5lA1fHr06GD4tqvX+aC90eNPtM4tyHhwv2Nto8we3N9no6vDtw1nCwTRiGed4loGSikHXw7Of/hw7vkNZKQ7nMYuk5Oow5K29Pg+OdYSNbRss4py40NNby4S8hKKsiJIS09Ld4UpJFrHu+nZsk7Zvk5c60Ny1Tbq+3ls0TYNO7UqerDI6vo1rCfICJouMqm6JqpSeWJ7P3LwskeipJlc6xse1MIC81ILMtXVu6WY34PZWh+NlilnXTyZFhVPq2KONjoeUipNlRpZXdEK9H6mUYn+yIs4qjmcxSSG5OgjZ6YUcTWMOFylVJckVGLV56iyb8/yup2mIdcf92X/zbJ05en3UwrENHpwu1w1D2oAldDlAnJOXuj1qo6NrK89I84pZnNHyLExDT6uHbY8oLcgKW+d4Sj0tV0KAIdjqB/wb39u+tJLyMoZtj5/eGvH7J1OO5wmrpCDOS3zH5M52l2HbRSrY7ARsdrXxSaWw1fPpBvo1HGUlB9OcR6cROy9RzNDQ0NDwbaRRVM+R5iX3TpY8OonIyhLTMNjq+dzcbDNoXZxV2fDF0W+57PRDHpws2er56xB6y9TC5fZOjz9+fYt+SzvqDSFIC70jWFSS00VGVZuAhm2XSsIyzinqzMu2ZzGNUhzbpKh0iLdh6hger6uzQJOsJM5LjhcpRVGRGRWhaeE6FrahhSJoQSyEwHes+thbHzyvkgrPN3EdG6duOIqSglLqY2nHMkhVpY/vAccSFBXrqsmLRKeB3qssKlnveAo8yyR0LdJS0g2c9QrAn7x1hdev9Pnreyd4tsl4mbFKc8ZWxnYvoB3Y7I8jkqwk9CwswyAtS3qhiwJOFkkdnm+RlRWH84StXsg0yslKWYvks+B1LT4t4+nos6zd75apj/h1LqmWp1Fe8i/eO+LxOKbtW/QCh9B76vD2HYu7h3M+Olzyg70hSV4xjVIqqSO85lHOtVEL09BZpne2u1imwDCWnC5SFrVwHbZ9fnCtz7/x/R2ujdqf6bW41Qto+zb//L0jHdJvGfiOxf40ZpWWvL7TIfRsHp7qXefbW91n1kw8WxG4Jk+mK5J80DjWGxoavpM0v/nOkeYlf/nRCfuTmI5v0/Edikpy72jByTzhZ7c31sHkDV8OhhC8fX2ARLE/ifWxsdBVil3f4QfXBmvRCfDukym/fzKjF7i8vtvl4WnEZJWyzApOFtqE5FomldKOaEMIPtifc2e7y7/68JiDacwizvFdC0NoB/jpIkUp2Ox6TFc5jiUQhiDLS7zAZrvnE7gWb+4NOJjESHRQfVUp5kmmI6UCvb85aLn6ddXRYni/inQskSrrsHmFqKsqz46uz5uKzqaJCpCVXIe5O6ah9yyLipbnsNMPyMuK3qDFz+5sEGd6Ynx12OLKIKSSivf2Z8yjnEpKlklB6On8zoNpjASSvGAe6/Ykz7HY7PoIAUVRkeQlo7bL6VJHAhWVxDBELYbrJFNDrCeLSsGwo4+oz5p7Rm2PjbbPg2xJVUkEguC5Rh/HMmn5FpNVxj/77RMC16bl2ZRSMVmmJHlFmukoKSEEgWvxvSt9rg5bHM9jZlHBH762wfVRm1HHu7A69dPwwcGcySrj5mZ7vacplWK6yvjt4ymbXZ/DetXjvOg8u8a7g4CqVJzME65tfDYB3NDQ0PBNphGe57h/oo9Zd/uBbo4BXFvX3x1MY37/eMbgey8XrN7w6vAdiz+4vcnpRsJklVFJRcvTho/zU6NFkvPgZEU/dNeVhFeHoTbDxDnLpGDQdrFNLQqubbTIi4rTZUboxSyTgqLSTnTPMYmSggcnEXmpuDoIQYBjlQSuzbDlYpmCpKjY7Qd4tsVuP6ATODw4WTJZpQgE8zjHtgTbvQAlWb+u7Dq8PCsq8qICFIXUDmrDEBiGwEQfT6+P3IWedCL0NLSo8zwNoRAWFFIR2CZbXQ/PsbRByLP51f0xRSXZn8aYCDzPou3Z3Nhs89HRkvEiYRbnun1KCDZ7Ab5trpt6wpZua+qFDnkhWZU5EnAsi1FHC8koKbAsA9cyyEudN2oAaSX19RYGw9BlnhTs9kM2uwFvXOnSC11Cz+RolpAWJVlZ4Vn6Z6pQrNKcOJOUUnIwS+n4Jau0YNBy2R2GxGnJ+wdzhl2Pra7e2zSEoOXazC2LP3q9z89vb76S1+EiyXk8jhi03GfMQYYQDNseTyYRlZQMQofxKmOyynAsg1Iqiqpi2Pa4NmpzskgozudcNTQ0NHyHaIRnTVFJHp1GtH17LQ7OM2p7nC4SJqu0mXp+BVxmXlomBcfzmNNFysky5WAa8f0rvfWf7/YDjuYxZSWRSq1rMzuBg1F3hPdDh/eezHhjp0tUlPz+8ZTTeUpWd8Gbjq6TtEyD29tdyqpCCMF2P6AsFW/t9fEck8eTmF7g8MZuj8kyZbzMCDxdyWibJoskY5VUBA5USpKV5dplbgmDSuoge1FP70wDUDr70TwXjF/WVZhnhp2zdcXANukFDlLBZJGy0fO4vtkizSseHi+5e7Tgw4MZm10fyzDot1xC18K2dTtQN9BidBC6OoReKVzL5Hgek+QVD46XSBSmYaxNWkalu+c916LjayHtOHqvNslLZKEokQgLHk9jyqqqXesmTyaRbkeyTALXZplkzKMcp2tgYDCLMsbLDNAh62/sdnFsg+N5wmSlW7YUunLyL353wE9vb7LV9cnLikVSsNHxeH336Wvh8zKLcpK8XD/3LK8wTUE30O1J3cBhFuVc3+wQuDpNIc1LAtdg2G4zaLn1jqpYpzQ0NDQ0fNdohGdNXlRkZUnoXtywY1sGUummmIavBw9PlvyrD495PNYGmHmsj7WXccGPbgwJPZte6DCsj497oYttmQw6np7SpSVX+iGOZRKlBS3fZnsQstnx+euPTnk4XmEIQZKXRGnJ9c02mx0fYQimq5SrwxaVVHRbLm9d7dMJdE/4LMqwTJPvXe1za6uN75j85d1T5nFGkhfrSstplDEIXYpKEWclrq2FZFpWZIU+ivcsLUBD317HSNmWgScEhtBC2rH0Efq1UYuiqrh7uKgrT03eezxjmRaYhsGtzQ4fHC54PNYrC/kT3Y7kWiaeY3G6SOn5LqOWh1SKopTMVhmrtMBzdEd5y7MAQZxVOLbBlX5Ikpfrak3bMsjykqO5jtVq+xa+bZOVUmejSsEyKbl/os1EHd/Gdy0cS6cBSKV0k1OlXfSeY2HUwewtz9a7pEqnEoy6LqOWj2cbHM1SHp0uEcCg7fL2tQHXRq1n4o8+L0pKThcpB9OYvKgw6+e7P4kZdjw2ux4guD5qsYhzds6dnJwxXWXa0NVtPrw2NDR8N2mEZ41p6je+opJc9JZQSQmCZlLxNeFkkfAX7x7yeLzCEFps+I5JWiy5ezgnzSv+zTe3sS2TvWHIk0lElJZAxSLOCBybG5sddno+j8cRCIGo9//avsOo64GAOCs5WSR0fJetbrBesxBCsIr18XLbs/Ecix9cG3Bnu0NU97i3fWf99T+/vUHLs/nlvRMejfVz8SyLQc9lfxqR5hW+a+KaJn6lG59cW6w/6EipKCu932oZOt9TGAahbXBlGDJq+2z2fMaLFAUkRYmUktNlyniZMmp7uLaJIaATOCipOF2mgH5NZ3lJksK/XB7zaBLx4xsDkrzkySTSk9Y6rH+V6vzUQkrytEIJxRu7PQ6nMcsk113mrsU0ytnpW2x1PcbLFMsyKCvJySIldG095TUMjucppqmnpklRIQzBVtfXYfhZQdu3KCtdRlBUFY/HenrtmAbLuGAYetiWydVhiGdrcezbJmmhp55nWaGvgiivOFmkdAKH0blTj6KSHM9ilnHOj24Oub7ZZrLKeDyJ6IUOoWvV0Us5VaX44Y1hYyxqaGj4zvKF/fa7f/8+/8V/8V/wT//pP+Xw8JDd3V3+7t/9u/xn/9l/huO82Ev8VePZJjv9gPf357Q9u3bdPmUW5XR8l0H70/eZN7x67h8veXy6wrHMtbnIMU36YcEyzTmcJzw8XXF7u0s3cNns+EyMlNd2enWUkm7vmUU5cVoSOBaOqSdYq7RgHhUUpa7VXMQ5hqibf86xSguujFps958e/3uOdWE4+LDt8Tff2OKNKz3uHy35P363T1ZUtAOHq4ZAsWKZaJe4ZQAopDLwHD2xMw2dB9oLLWzLJMlK+i0X09CtQqFr8fBkxTzOCV0L17bWE7lB6BJlJafLtDZNgTIEHd9hFme6v14I3ScPHM1j/vd3Uk6XKWlRETgWpmngOSZKKuK0wDD17a+P2lwbtfjtoylxVjCLtItcoeiHDggd1j8IXR5PYlzLxBSCtCh15WVZ0bEdvEBff9Mw2J/E+LYWjC1Pu/OPpgn3j1YskhzbMohqc9iVQVg3FQmivCTJSlzHxFykfHS04NqoxY9uDNdpCJ8VpRTzKKPtWeswerP+HWGbOrd1ssoYtjx8x+Int0a0fJsnk4ijWYJpCHqhy82tDnvDJkqpoaHhu8sXJjzfffddpJT8D//D/8CdO3d45513+A//w/+QKIr4x//4H39RD/u5uL7R5miWsj+N1xOiSsr6zVTy1t7gc7+BNXx+ykpy/3hBKRXD4OlRqll3iUspOUoSPjpastnxSAptcOn6+gPPw9MVaa6zN9OyQinY6PgczuK1eJpGGZNVStvVDmrbMpjGGb6tg+Bncc6w5fHm1T4d/+U+SAmhw9tHba/eKdZNOHcPF7x5dUBZSpZJzniZUlWKbugyaru4toVlCh4cLwl9m17gMlmlBI5FUlQEroVtGcyiHMsAgajd7golFZZlYkvFONPTyrzQO6RFpQPwTWHg2AZFUbEzDFimBcs4wzQE2z2fqtLB7FV9HRQQWia9sx1Ry2TY8fi3r+3i2xb3jxf86sGYQeBhmLA/jdch9x3fYZnkRFmJZxsEjkValHhYbHR8/viNTe6fRiyiHNMQ7I1CjmYJrqPXIWzLIHRt4qwgK0oenC7xbBNDaGHnmAbDlkvo2eRlxf3jJb5j8oO6XOCzkhYV01XGa7s9DqYxk1WKbRgIoas0BdAPXUJP/0r1HYsfXh9yZ7tLkpcYQtAJ7Fc2fW1oaGj4pvKFCc8/+7M/48/+7M/W/37r1i3ee+89/vv//r//2grPXujy8zsjfvd4yukiradi2jzw1t6A6xutr/opNqBNNXml+3ys597IQ8/myiAkLaXuRi8kg5be+bt7tOBfvH+ElIrQtVBA27Npew4SxfsHM/JCstn12er5JEXJMtU7mYO2RydwiJKCRZJzfdji3/nhFfaGn+01sTcK2Z9EzOOMoqp0L7gLLd9imeWMOj6v7XSZx1qApXmF51jI+sjbNk3d0tP2CVybJCsopWTU9lmkEW3LRKDIS0lWSCxTT0z1nqZNWlTklcQyDQxDrM1Ki7hASqlrPZOSTuAipWKVFeRpiaUUncChKCuOZwkHs4Qkr7h/siTLK7b7AXe2O0il1xSUUhzMYp1FKqDrO7X5JwchyEpZi0a9ixt6Dm9eddifxBgCZlHGMi24Mgg5XiQ8Po1YJjlV/TOMMz2tbvs6Q9WyDGw9MsaxTHqhw6PTiJtbnUv3t1/qNadXS/Edi6vDFqWUPBlHlFLR8WyubbSxTN0Jf57AtZoCioaGhoZzfKm/EefzOYPB4NI/z7KMLMvW/75YLL6Mp/UMg5bH33xjm+kqq5uLBP2W20w6v0bYpsEg9Hi/mCOVeqGFxjQN+qHDra0O/84PdrWIUooHJ0te3+nqrEmpxVsvdPAdi3cfT5GV4sZWi1VSoiRsd30Sv8IQMI8yBi29anFnp8PPb28ybH/2QoHtXsDeqMX/9s4+QiikUigFp4uMOK3Y6vvkpXa5j1ou3cDRge25nvT5jgVCxy5JpYjzCt8xKaSi7Vks4pxVkhPnBVGmX8dJXrLRdmm5NnGmqzGDwMa1DNKixDQFcaZLE2QlCTyLojY6Ba6lJ8RFpbvkK4ljmfz6/glFqWgHDkUp+fBwzi/unnB9s61zUC0D2zABhSEMirLCsvR6QCdwSIuKjm/TDhy6obs24yglMUyD3z2akpUVbd/Bd3Uz1CopGHY8dvqBNiJJLTKXSc7VUeuZv6uhZ7M/0ZWnn0d4eo5+rTw41usMUVaw3Q8whd5PfTRe6fB7t/k90dDQ0PBxfGnC8+7du/y3/+1/y3/z3/w3l37NP/pH/4g///M//7Ke0qWc5fI1fH1582qPX94/ZbJKGbWfGj2kVNpVbhh8/2qfdn0MPl5lTKOc7X5w4YcIHdwOe4MWlmWilFo3A01WGfePl9imwR/c2WS7F3zuKZZlGvz45pCPjhbcP14wjbL1EblpCpK0ZBEXxPUk88ZGizev9vhgf840zuiHru6jnyc8Hq/ohVqcVkqx0fE5WSRUShEKh7LSMUCm0I1ItqU73E1DELqWdrBXilHoMl7o8PMCgW8ZGCacLNI6ukiTFxVKwCzOKSvFZlevHDiWSSUVk1XKu4+nvHVtgEAb82ZxTlFVzKKCQVsHuVdS4timrvoUgo3671ycFRxME7qBzbDjEWXaKDVb5RiGYHcY0vIsPNsiSgqSomS6Emx0fbZ7T18LZSV1hmtakOTl5/p5GUJwZRDyf757iFSK7V6wnm46lkmcx6RFxTItGTS58A0NDQ2X8qnfPf/hP/yHnygO//W//tf8/Oc/X//7/v4+f/Znf8a//+//+/z9v//3L73dP/gH/4D/5D/5T9b/vlgs2Nvb+7RPseE7wLWNNn/jzib/57uHPMxWdAIb6txEDMH3d3vcONcMI5WeKl6U0Xr257riknUnPGiBeGVgYQrBja02t7Y6r+x7cCyTP3xtUxuAWi5CwMOTFQ8nK71H6VoIAYPQZbLK8GwT2zZwbRPXNrEtk9CzKUtJJ3D4/tUBj8crHpwsuLHZBvQ0Lk4LxlGKY5oskrwOi/eZrBImy4xWYNMPHSzDICslHd/Gs8EwtKFon5hCKr3TaEPLtzHQx/+5kHi1i3y81GsDtqnrR0/mCf+vP7rNlVHI//HOPss0Ryk4niXkda7qlUGIUzcq9UL9IeGjoyV5WXFne4RrmxzOEtq+/vnGWYFhGIw6HpNlhkTvjQ47Hne2u7i2iZSKw1nM8TxhusqQSvHrBxNWacFrO71nfr6f9ufV9mySomKyzLAtg6rSeafbvYCWZ/FkHHFt1HrBnNjQ0NDQoPnUwvM//o//Y/7O3/k7H/s1N27cWP/v/f19/vRP/5Q//uM/5p/8k3/ysbdzXRfXbVzj30XKSkf/RGlZO4B1IPdlb+BCCP7tH+zSa7n88v6Y41lMnJegYND2sG29A+m7FrapO7V92yTOynWr0XlM00CgLpyGKqUoKknrcxzVXsZOP2C7FzCNdMxQlJVrF3pRVXQCl3ZgIxC8+2RGWUn++PUtuqFLVa8LtD2baZSh0AL2YGquqy4VCsex+OFoxG4/WHfeh57DB/sz7h1rkVdJ3TY0bLlkpeS1nQ5xXvHodIUwYBB4OvwdaHkOlik4mqcElmC6ynl4stL7okIQq5K8rLh7tCTJCzzLYnfYYncQEmcli7RgGefrSep2z2ej7ZHkFZNlyiotuDZq49gmw7bH6SJDSoXvWFiWYLbK6fi69/72TocbG21+93hSH/8bPB6veDyOEIbANAS3NnWW6u8fz4iykp/d2vhMsWhpUTHqeHRqc1eaV+sg/l7okOQ6wqmo1xAaGhoaGl7kUwvP0WjEaDR6qa998uQJf/qnf8rPfvYz/sf/8X/EaByd3zqSvORwGnOy0E0tg5bLdj94aac3wGSV8psHE8bLdB0Q7jome8MWb+71L30TNw2Dn97a4Oog5C/ePWS8yugGDr16d/Bff3jMjc02P7oxouXZ7AxCPjiY4zvWCz3aBtBv6b1K97mJ2DTK64rOgFdJlBUcTmNt1JmnjJczlmlON3CIMu08b3kWRSG10SnJ6bdcrgxaawPNGb3Q4XCWYFsG37vaxzQEeaH709u+XU9PBd3AZbsf8uMbI/7N7++wiDPuHi05nGkzj2+bHC90vueo7bOIdQ3pMtHH3L3AYdB2MYTgcBaTV5JK6inx+RipOMs5XWa8tz/Te6pt7wXBH6cF7zyakpWSaZRhmQY7dTVpL9QfQLuBw9VRyOPTiDhP8SyTVVbweBJxa7PLT24NGbY9FPDB/pwn04hHJxHCUPi2xe4w5MqghVV/+Hh8uuJKP2Rv9OlNYYYQUJsNu8GLr+9K6rrTplK3oaGh4XK+sB3P/f19/uRP/oRr167xj//xP+bk5GT9Z9vb21/UwzZ8iYyXKb+6P2a8THEsEyHg0emKj44WvH19yJXBJ+cVLpOCv7p7yjLJ2ej660lUlBW8fzBHAT++Mbx08imV4u7RAql0deWZ0agDOk7naEk/9Li93eH13S6rtODJJKLlWTiWqY+is5LbOx3avsP9oyWrtKDta0PSMimwTYO3rw/1ce8rYrJK+euPxkxWKZ5jrjvlFzGMWh5vXR2SlSWTZU6p9GRz0NZNPc+LTtCu63mkMzzjvORObaJ6nryShOf2UzuBy09uPnvKMFmlvPtkxsk8ZaPj0Qt17ulm12e3F+C5Fsu4QErqo3nnhRWGvFR0fJsnpxG+a71QMyuVIq8UjmWwTAquj1rsDlrsDQP+4l1tfAI92d7tB4SuxXiZMo9zhBJcHYbc3GpRVYpFnPO93S5bXZ+/vHvC6TxldxjSC1w6vl3XVGpTmmUaPJlEn0l4Dlq6pGCVFi+I6LPXypt7/SYyqaGhoeFj+MKE5//yv/wvfPjhh3z44YdcvXr1mT9TSl1yq4ZvCllR8esHY2ZRxpVhuBZ8SulGnF8/GNP2bDoXTIbO82SyYhZlXB2Gz4jL0NXHy49OV9zYaK9D4p9nuso4nidsdPwX3O2OZeK7Fg9PltzYbBG6Nq9td4izgg8PFpSVZNj2eOtan+9f6ePaJpsdn0fjiOkqBQTXN1rsjdpsnqs4TPOStKiwTeMzVTIWldTXLn7+2kGelyR5heeYbPV8rgwUsj4GX8Q5zgX7ieNlyv3jJSeLhK2uz9EiYZHk3NrqMGp76+s6izJC12Kr+/GT20HL449e32IWZaySgm7gcjiLkVIR5SVRnUs5bLs8Oi0JbPPclE+RFCVZWfH6TpdS6jWF80gpeXgacTCNiPMCx9R1nafLjOkqY6vr8/snM7qBo6Oe6iljJRXjZUohK377cMo7D6Z0Q5udXsDOoMUbu12uDkOitGD3kg89rqXXLT4LncDh2qjNe09mAGvxedbI1Akcrn7GeK2GhoaG7wpfmPD8e3/v7/H3/t7f+6LuvuFLYJloRzDoI8/zTu6jecJ4mbLTD58RfEIINjo+j05XPJlGHys8lVI8mUSEnnXhRDNwLcarlMkqu1R4nkX7PH88fv4+oqwgLSpmq4RfPRgTZQXXNlpIqeOBDmcJ272QnX7A7kD/80wsnT/mj7KCj44WPBlH62zMza7Pra3Op0pBOK6v3VY3eObadUOHfttnXNdcdgNduWnWUUj9llvnccr1VO14HvPB/pxVVnJlEPL9vT790xUfHM751f0x37vSo99yWcQFQsDb1waf+GEA9LHyoOUxaHkYhuCv7p7WgfMCQ+jsz9CzWSQFeSUZr1IsQ9diKmBv1OK1Kz32x9oodT726niR8mSyWmdv9gKHK8MWeVnx4GTJ9Y0WGx2P/WnEsK2bgA6mEb9/PGOZ5NiWWU8vBXFaMV5l5KVklRSMuh6lvPyDbVZUnyux4vtX+wA8PF0yW2W6alXoaegPrg0uPIJvaGhoaHhKk2zcsCZKCw5nCSeLmMfjiKyom20MQejaXNsIeX23j20azOMMQ1y+z+a7FqfzFK5c/ngKHWN02dFkJSXLuOC9/RnzOKPjO2z1gmeOvA1DoBAX5nlydv/CIE4LfvNwjFTqhdD3k0XCr+6P6fg2YV2X+vxeaZQV/OWHJxzNE3qBQ7/lUFSSBydLTpcpP7u18cxU9OOI0gKleOF42rVM9kah3qs8XjJqe1imwSrV9Z0/v71R96frfcx5nPHekzmLpKAXOnoaqrTjP/RsPjyY8+h0hWfpOtjrG+1n4oZeliuDEKn0DuUsziiVxBRwZ6tDy7OYrnJmUUYhJa5lcmXQYm+kjUQ7fX3b6Spj2PaopOR4luBYJgYCKdW69/ws8P10mfHTWyMenqw4msUcTGPuHS1wbJO+6eI79lrgFZVkHudsdn3Gq5S2bxG6Foskf2HPOC911eXLrIBchm0a/PD6kBsbuo+9korAtRh1vM9kWGpoaGj4rtEIzwYAnkwifvNgwizKOJzGTKIU37bY6Hrc2upQSsXvHs3ICsmPb44QdfTQpeh0oo/FqM0u+5PohUlRVlTcPZrz4GQFKPKi0s5yz+atvT7X6qikQcul5dksk+LCadM8zrix0WYa5SyTgqsX9GSP2h6PxxGHs4Tb2xcfnd8/XnI0T7gyCNdi27FMQtfmYBrz3v6snizmHM8TsrLCt022esEL7vyPi9rZ6Pjc2CxZpTmVUpT1pPPaqMXVYYuirPirj075F+8fMYsysrJiu+fR8hxO5gkouL3dYaPj0/EdjuYxP7m9wW4/+MwRP0IIro1a7PQDJsuUslI4tsGg5XH3cM6vH4x5fbeLbRlYht6jjNKCJK/46a0Rtmnwy/un7E8iHMtkkRSYBszLnO2e/8w0u+XpfnOAP7izwTzOeX9/rh3lLZcPj+a0zn3wsE0DA8FkldXpADnXN1u8/2ROVlTra79KC1ZJwc2tNlufQXw/TydwXmpyDHoqfzSLdVargGHbZ6vrXzqlb2hoaPg20wjPbwCqzqA0hPhC8gFnUcav7o+ppKTl6UDxswzMaZRx/2TJ93Z7OKbBg5MVeyOduagUzxz7nn++cV7y+m73Ex97b6irI+OsXB/ly7pl6OHJiq2ex+u7PSzTQCnFNMr41YMxgWsz6uhj2JtbbX7zYIwQugITYJHkPDqNkEpxfaPDk3GEa5sXXj894TSYRtkLfwZ6UvZ4HK2Pvp9n2HY5msX8X+8eMo0yikpiGTp83juYc2enyxu7vfVEths4mEKHuF/k2DdNwd/63g43tzoopXDrLnIAZer2n+ujFq/vdnnvyYxBy8M0BKWUnCwSOoHDTj/AsQwMw8A2jQu/71mUcTCLWSUFjmWw0fHZ7PqXZp3apvGCs//2doe0qLh3tKSIc/19S4ljmnz/ao/rG21MQ+DaJvePlzwar8jLim7ocGUQstHxnrmm+sOMjmYXdf96x7fp+g7CECglMF/Y5TVI8wrHMoizkusbbdqew/3jJdNVjlSKlmfz9vUBt7Y6l35/XwRHs5hfPRgzj3JsU/fc3z1cMGp7/PjmaO3eb2hoaPiu0AjPrzFFJdmfRDwar4jTEscy2BvpPETfeXU/uieTiCgr2Bu2+GB/Xh+h6zfnXugyiwrmSUE/dKmWGSeLlDvbHUYdl4NZzE7v6RRQKsXJPKXjO+z0P/lIc6vns93zeOfhdP14Uik+Ol7Qa7nc2uquhYKo9w4fT1Y8Gq8YdfSu3p3tLlIq7h0teHiy4niZMlmm2KZgZ9Dio6MFJ3MdNbTR8S4UYVLBZSk4WSHJy+rSiCjHMjmeJ8yinNvbnWd+Nsuk4J0HE0whuL3dwTQMhm1d9/hwvGKnF65d6lIqThYpbc9hdxBeGHR+utQ7r8OOp9uIDEFaloSOjWXocPmTecJW1yMpKjxbh8CfRynF3cMF7+5PSbIK1zYpK8mHhwuu9AN+dHP00q8v0zD4wbWB7lKfJ6RFiedYbHV9+qG7vtabXZ+Njsf3r/Z1V3xeXhhPtUy0Y/z8NNG2DGTdJCXEix92Sqnw3DPxaeLZFtc3HK4OQ5aJXmsI6xSDL5NlUvDX98ZkRfWMiaySisNZxC/vn/I339huMj8bGhq+UzTC82tKXlb88t6Yh6fL+s3UJMpKfvHRKY/HET+7vXFhEPpn4XAWr3usi6rCNJ8qMMswkEoSZyX90MUyBFlR4lgmP74x4pf3TjmYRpiGFgVFKekGDj+68cnxQ1lR8c6jCcfzFEMIplHG8TxFoSN/3t4bXOgab9fHymUl1zuo37/aZ2/U4q/unjCLMt682menH6xFa1lJ3n0yY6vnv+DqrqSiknK9a/g8timwTIO8lJimYBHlrNKy3r0skQruHS/5Xu2MPyPJS6arjPsnCx6PV1zfaDFoadF5ZdhCAoezBCklhhBUStELXN6+/qxJJc7K9fH9k9MVD46XHMxiilIyi3LiacnVOj7ItgySouJoHvPgZEXo2vz1R6dcHYbs9EMC1+JwlvDOowm+YzEa+evrM1ll/PLBmGmU8W++uUPLe7mj5LOK2U8y7QihM0W/d6XHv/7gmHmU0w2fPkaalyzinLf2Bs8I32Hbw3NMDEG9VlGuW44qqShKST90WKYFP7o+WO9amobxlU4UD6YRiyRn77nEBtMQbPcCDqYJx/OkccI3NDR8p2iE59eU+8dL7p8s2O492y3eCxX704h3n0z5+e3NT32/RSVZxE+PH8/e4M/eFn3XYhbnz9xGPHf7M5HaC13++I3t2uGeoBT0Q5etl+gyV0rxzsMxd4+WbHQ8tnoBSimysuL9/Tmni3Sdv/g8upHnRWzTICsk1zbb9J8THFeHIQfTiPeezBmE3nrKWFaSw1nMqOOxdYk5yHMsdnoBv3kwJi0q5nHOeJmyTAstGKWkkopplPLgZMm1UYu0qPjwYMEyyRFCsD+NmUUZUkHHt7m52eXKMOSnt0YkWUklFW3fZqvrPxPE/vBkye8e62D5qpK8fzDn8XjF1UHIziDANQMenC75YH9O23coq4pFkvP+wYxRy2NvGLJMC/7qo1NG7RU/uTnk4ekKpViL22mU8eh0tTYx/avpCXFe8YNrA+5sd19pIPrxPOFkkbDKCj46XuBYJqOOh2frUP87O11ee25Foxs43Nzs8O6TKV3fIctjTpcJjmkS5yWha5PkFXuj1nr39+vA8TwhcC5ObDj7oDaNcq4Ov4In19DQ0PAV0QjPrxilFLMo52ShJ1quZTJouTw8XdHynBeO4UxDMGx5HExj5nH+0vEtlVTcP15w/3jFIslQSkcN7Y1a9AKX+8cL+i2XfuhyOE20o90SrJKSaZQTLhKSrMBz7Wfc265tcmUQ4FoG8zgnr3QLjW0ZH+vynawyHo9jNuo9TdATMc+2uDZq8WQScTiLubn5Yjf6Mi24vtF6YVdvHucs05ztC45wHcvk+1f6/P7xlAcny/XxsxDa0PPjm6OPNXvsDEL+j98dcLpM8eqj31HbJSskszjHMU1Cx2Z/EuPUTvQo1Yanx+OIrJTc2Gzh2zaTVUpWljwerxBCm2gucvYfzmJ+eX+MZQquDEJO5gmuZdAPXCZRTuDabHR8ro1a/P7JlP1phECLmlHHwXdN4lyy1XcYtFz2pxG/vD8mzsv1NHqZ5Hx0qDNNe4GLaQhOFgl5UfHOgwkCeH23d+l1+TTcO1rwm4cTiqpiuxfQ9R0O5vp1vLMb8MMbuoXo+XQCIQTfv9rDsQzuHS9Jy4rxMmWVFbQ9nbZwddTmxkb7M/ewfxGoTzDY1Vu7X86TaWhoaPia0AjPr5BKKt59MuWjwwVpWWEKse7MnkU5r+9cbM4JXIvJKiPOypcWnu/vz/jdoymeY7LR8RFCEKUFv3s0pRc6WJZ2BvdCbUx5cLJkHmfMoxzXNjmeJRxIxY2tdh3foyeKq7Tg1/fHHM4TKilrU4g+Hv3R9dHHBr/nZYXvvDhl7PgOo7bL/eMle8NnBea8NrA8H4kEWsSrj9nVbPk2N7c6fP9qf23W6gQOm+caky4jzUu6oYPnmLy/P9c1m8LAdSzudDwejSOWaU7o2jyexEgpafs2caYnpP3Awa+neoFjMY8L3rgSsD+NOVmkL4hlpRT3T5ZUUrHZ9VFK73/6js1G19AT8eMlUioWaU5RScqqwjJNQs+kGziEns3RLNZ1of2AzY7P4SwBpXDbWqAdz5MXsy0FhJ7uQv/oSE9wvc+5UzyLMn73eIpjGesPLt3AYWcQMlllZKWOYrooEgu0mH59t8e1jTbzKKtD9fXr72iecDSNOZzG9EOHaxvtz+Xif1WMuh6HsxguGMJWUhsGu0FjLmpoaPhu0QjPr5B7Rwt+93jKIHTZODdFPFmkvPdkRtd3uL754rtWJRVCXC6wnmce53x4OKcTOM/sXXYCB9+xOJrH7I1ajBcpT8YRnmNSVFJ3lLs2Wz2fQcvV7UAG/Or+KYFj0Q0dfnn/lINpzHY3eOb4+nie8Nf3TvnjN7YuNKoouHQaZBiCa6M2D8cr9qcxTh3TkxQlnm3y1l5/LV6irGCy1HmKSik8x2CVlhful67Skk7gcHu786kNHSfzhK7v4HVNxsuUtmdjGAaeY2AKg1mUM40yur7DPM5B6Aag/WmMUope6Kynmq5tsqrbc6SSnF4gPOO8ZLxI6QR2/XWKvJRkZVUf3ysWccm7+zNWaYEpBL5jEng2oeswXqZE9XU4mSdsdj1dawo4tskyKaik5MHJSqcFrDK9HiHANk0CxyJwLfanMZNVxu7g8/2qOJjFxFnJdj9YH7cXpcSxTUZtT/fWz+JPjCjybBOvvlZ3D+f8/vEUqaDt2wjgaJZwMEt482qPN3Z7X6n4vNIP141S5xukpFIczWKG7cvXOxoaGhq+rTTC8ysiLyvunywJXfsFA82o7dINHR6cLLk6Cl84hl3EOW3PeWnjxMk8IS2qF/qyQTuGdVQR/M3vbXMwi3l4sqLtOfzJW10dTG6Zz0T6nLnK89LnaJaw0wuemUpapsF2P+DJOOJwGnNz68Xj8sCxEOj9yLJSTFYZ0zhDVYp2YJOXkp/f2uDKIORwllBIyc2gzU4/YNDyqKTig/0p946XRGmhJ62GwTLOSfKIaxstAtfCs/VLPCsqorTgzo3hZ3IRS6XW9Y2ubRJ69jPTuV7gsEgKHk2WLKMCx7EwhSDOSnqh+4yJppIKQ4ApBKYwKKV84fGU0o95Fh0khKAoK46msa727IV4jt77TPMK3zHwbAvftrBNA9e2WKYFItM/46KUmI4BArZ7Ab+6f8q4rhu1TINFXGCY+jm9ttNFCD2lXCb5Z66YPM8izjGE4O7BnNNlpj9MmIJlnDNdZViGweki5fXdl7u/eZzz7pMZrm0+8/cgrDNd39+fs9HxP1dL0eelEzj88PqQ3zwY87iO81IK8qpi2PL44fVhk+XZ0NDwnaMRnl8Ri7hgGefPTDrPEEJwY6PNrx6M2R/HOorFECilWKYFcVbyoxsv/6aVldWlR5jwtL+6F7r0QhfXMi8NW4enrnIhFFzQwAPa6ezaJoez5ELhudH1GLRcHhyvWCY5y7TQEzkBx4uYqlK8tt3l2kb7QsPI+wcz3nk4oePr6CFDCE7mCUfziJN5yqNTXcU5bLt0QxfHNLi13bnwubwMvdDlwcmKXuDg2RZJVq4/MORlxfEiwbMtpBTYtkVZSt1jPwi0G148vUZRVjBseziWrphsX+Ae9x2TlmezynQ80VmGa1ZWdEMXKRWWIagqCF0L0xSUStH2bOK8xLX11HKVFrRc3cYUZQVeLZpVPW42DC1wLVOQ5fp1crpMmccFSa5D4NueQyklr+10L22Z+iQs0+BgFpPm5Tp3FABXT8gfnKw4XiQvfX9Hs5g4Ly9cuWj7NvM442Aaf6XCE3TrU8d3OJhGTFYZRr1TvN0PXmkkWkNDQ8M3heY331eE3uS8vMVm0PK40m9hmoIn0wgDkOhJ4ZvX+p9KQHm2SfUJ/dWDc7uYSlE/u4sRop7ISXWp8xz0kXl1wTQPtNnnjSs9fvNwzHiZsdH1sIRBWlZ4tkW363A0izldpOu8zjOirOD+0ZKu/7Q9ZrJKuX+yxDZNei2XQctDoE1MtmnyB2/tcGOz/ZmF03Y/4O7RgmVasNn1uH+8Wk+LH5wsyUrFds9BKriz3UFK+PXDMYskx7G0+1oL+hyrDmKfRjlt376wxtI0DK5vtPnFRyekRYUh9N5nN3RYJjmVVLR8m1JKlNDizXNMfM8iryRxVuA7FkleEbgWlZSMlxm3tjqMlym7g4DbWx0+PJxz73hJ27MJewFHs5gn44g7211sS+8De47g/3z3kHceTNjsBYSexZV+yEbXf2nHe9uzmUYpg5b7wm2EANcWpFlFWlQvZRBapcXH7uW6tskieZrOoJRimRRkZYVtGnQC52M/jL1K2r5N2+99KY/V0NDQ8HWnEZ5fEW3PJnBtorS4cK9tlRZcHbb4o9c3mMUFWaHfMIdt7xPzMZ9no+N/fH+1VFw5N91s+zaWcXmzziopuLbRoh963D1cXtqTnmQltz5GIAv0WsFmx2ce5yhFvUvq0QtdDiYxTyarF4TnZJkRZSW7A73rV0nJ49MIKRWDloeblSgFb98YYCB4PIn01PEzik7Qhqe3rw349f3xOvroeJGyiLK1GDWEwZWhX5u3ANHnt49mFKXkaBYD0G+5bHZ9lmmOa5m8vTe8MKsU4NqoxSzKuHe8pKz0fmfLtVlUOaapUwPKShG6JiiBYegWn+1ewNE85mieUFQVKFgmJbe3O+wNQ/6v947pt/QKxQ+uDQhcm5N5rGsuixKBzlQddnx2+iHHC503uT+JUUJgLuDByYpbm21+cG3wUk1ALc/Gty3irMS1rLVoLCo9Gd7sBViWIK6nsp+EXU+LL6OsFG69czxdZXxwMOdorrNPTcNgo+txZ7v7TEJDQ0NDQ8MXTyM8vyI8x2JvFK6d5ucFXlZULJOCt68P6AQunc/pfD0z1Pz20ZS8lHR8vZ+4SgsWScHNzfYz5hZtegjYn0bs9MNnJlSLOMc0BFeHLTq+QzdwOF2kL7yBTyNtVtm5INrojFVa4NoWV4ctZO1IP/9YoWdxMk9RSj0zGa6kQvBU7C6SglVW0Kuvk2lo4SElWJag49s8Ol19JlPRea4OW+su8aNZzE7fZ7zUe5K3tjp0Q4e2Z6+f606/hSFMiqrixkaH8SqlrCS2qZ3dV4ettaiOsoIo1U1EncDBNvU09Uc3hmx1Ax6eLjieJ1SV4nuv9/EdvS94/2TJMtK97sfzlFVS4DkmLc/CELDdC/nTt3fZ6OhOdJ0l+vTaWabBra023cDmr++dYgqBQrAzCLm52eZolnAyT9ns+EyjDMsQ7PQD0qLig8M5Lc/mziXpC+dxbZOrwxarTK+YPP156zapnX5AksuXnkJutH0+EPMLPxyVlc5V3eoFzKKMv7x7wjzJGIQeXsskrySH05hZlPPz2xuN+GxoaGj4EmmE51fIaztdorTk0ekKwxC4tg5Al0pxa6v9sdPCT8vruz082+Le8YLJSsfRlFKLoPEy5S/ePWC3H3JlEBJ6Nj+4PtCVndMIxzQwTYO0Pi5+c6/PVldHMr19fcgv75/yaKxbcgTake1YBm9fG14apwR6zUDVJ/qGEC+43KUCYby4juA7JqLuQtdTPwnnRGtWSALXwqobmFxb77AWlXxBpCySnMNpzDIpME3BRttns3d5vNLZHuxbewMA3tuf8ev7Y/ZGF7fPuLZB6Fr87PZIG4QqHTllGILTRcov751y72TBIiqwLQPfMekGLre2OlzbaGEaBleGIVeGIVvdgF/cO6Ufuuv93luG4P0nM06WKXe221wZtigquQ5W/xuvbT7TjBO6NoGrdz/PTDlWLYS3uj6hY+G5Fre3OihgvExpeRbWWV1l/QPzbJPQtXhwsuL6ZvsT46jOYqvC1GJv2FoblkLXouXbjJcpvdB56Wn+RtfjyrDFg5Mlo7a3LixI8pLTRcqVQchm1+c3DyfM4oyrg6ftQZ5hsjsIOZjGvL8/Y9R5MTu0oaGhoeGLoRGeXyGOZfLTWyOuDEKeTCKSvGSjY7E7CNnu+Z/raPh5DCG4sdnm6jBkHud8cDDncd1gAxClJb+6P+bRacRPb+n8zT96fYvDWczRLKaoFL16MjpoueemegG+s8V+naOoUFwZdrkyCD/R2NENnPWRPmjBKAT4js67jLKCG5uDF243bHsMWk4dQ+Q/FUV1NmJeVVzvtNZiIi91tebz4ujhyZJ3Hk2J0gLHMqik4sODOdv9gJ/cGF16BK6UYrxM2Z/EHM5jplHGqOPjOxesJWQFt7e66+tlm4auQ/3olHtHCz2xTApcy6QbOlwZhCR5yS8+OiEvq2fC269ttJnFOfeOllimwHcs3STl2ZiGoBd6FJWeZl4dtHhtp/tCHaNrm1zbaPGbBxMC92l/+Zlb/2iWsLfRxrVNZlFGWlQMWy6y3vq1z70mW57NdJUTnROxl2GbBre2OvzioxNc22S759cfPBTzOKeoFDe3Oi/9mjcNPQ22TMH+JGKySgGBY+nd2Leu9fWKwzRmcK4z/jyDlst4mTKLMgatr9aE1NDQ0PBdoRGeXzGW+XSi9WU9XlZUHExjei33mb73fktxOI35zcMxf+t727i2yfWNNtc/oYbwbAr45tX+p3ouZ/3ev7o/BvTxuCEEgatXDza6Hrv9F4/qLdPgrb0Bf3X3lCeTiKB2dR/OYhzbYKsbMKyPsKVSzOOMt/YGz0w7Txcpv3owxjQMrp7r0i4rycEkxhJj/vD1rRcmYVlR8s9+e8A7Dycs00IHuCc5D0+W/OFrm2ye64FfxDm2YXJl8OzP9rePpnx0tEQgMITBjY0OhqFzRh+eRryx2yP0DD48XKwn0Gff9w+vDxl1fB7XFZe+Y/G3vrfNdj8gKyryQmKZgkHbu3QKeXurwzIueHi6wjK14MwLiQLaocPo3AeGs3rSKC3xHXvdkQ6sP7S8bFbmtY0WWVlx92DOk3GEqu+75dn88NqAvU/4O1BJRVnp7880DDzb5Ge3Nri91WFR17y2fYde6CCEYBZlFJWkfUk2qGvrvNq8vHxXtKGhoaHh1dIIz+8gj8YRwDOiE/RUdKPrczJPLmzTedVUUoudNK/IqwrHNFDANEpxbZM3druXTtI2Oj5/9PomD09XOjan5VOUEf3Q5cowwKjjgybLjI2O/4J4fjxekReSK8Nn9/vOjp0PZgnjZfpC9un/91eP+VcfntDxbd2Og2C8Snl0uuKf/faAP7izSce3Ga/StcM9PNdbv4hznkxWDFsu946X2KaxXhFoe/p2J4uEO9sdHo0jThbpM5NXyzS4NmpxbdSq25PEU+H3kquKZ5P2nX7Ak0lElOlqz7evDzhZJDw6WZHVu5OGITicxgSuzY3N1jMRXoskpxc6tLyX+zViCMEbuz12+yGni4S80m1FGx3v0uky6Naoh6erunpU18peHYbsjVr4jrX+4PM8Z7WtZ8a85zn774716k4WGhoaGho+nkZ4fgOZx/p4UwhBP3Q+VZ1hWbuIw0vEgm0aSAVRWryqp3spB9OYk0XCH762QZRVrNIcKfVRuzBgGunv8zJRciY4vnelh5SK02XKveMlk2XKVOa4tjbOvLbbe0ZkV1JxvEhoXbJP6NomlZQs4uIZ4fnodMVvHk4YtBz64dOp4HYvoOVZfHS44GC6YhE7FJUi9Ez2JxGLpODGRpvXdrrM4pw0rxiE3npH9TyBo9MHzqa/xcc4tz/PKoZlGuyNWi/spl4btRi1PR6crIjSgpZvUVaSvVHI1rnYp2WSU5TyM0VU6Xihl9vljLKCX3yk27FanoVrmaRFyS/vjzmaJ/z01ojQvfi+Qtdmux/w0dGC0LVemMyOlylbPf+lixgaGhoaGj4/jfD8BhFlBb9/POVgGpMVei+y5Tlc32zx2nb3pWJthBAIoTM4L+N5F/kXxaPxqm5FsnBt67ksUXXhxO8izo7Qrw5b7PRD5rGu0HRt84X4qPreX+LZnR0yP+Xe0Zw4K9ntv3gk3PIcem2PySpnpx+y3QvwHAupFKuk4LePJlRS0akFl2HofcQofbYVSAhQUldpKtQnmnZeNZZpcHu7y/WNNnFeoqTujL9/rNuqLMNYZ4Z+f69/qanqVfHhwZyDacyVQbAWuCE23UDyZBLxwb7Nj2+OLr397e0uk1XG40nEoOXi2SZ5KZnUFaGv7/YaY1FDQ0PDl0gjPL8hZEW1nvyM2h4bHR9Zh2L/9uGEspL8YG/wiYLRrONw3nsyu3DSk9StN/0veAokldKZjpdkNurvQ3E4i7FNA9syGLTcTxTXpiE+0ShiGgajtse94wXdC/b/8rLCNPS+4HnivPrYwPSyqFjEWniefV+G0PFIhiG4d7zg7WtDbNNcV5jOojmVfJoxmuYVncAhykpans1G96sxvVimsRbtbwcOV4ctjhcJeVHhOxabXZ9u4HyhH1CirODJJKYfui9MVU3DoB967E9jXtu5fCreDRx+fnuDu4dzDmcJiyjHsgyuDELubHdfyIhtaGhoaPhiaYTnN4SD2jV+fvJjCLF2ht8/XrI3bL3UseHesMXjccTxPGHU9tbtQ2lRcbJIub3VfsZE8kVgCO3Knq6yC/98skq5d7RkHhc8HkcYhqAfOLx+pfeCWeezcLW+BrMoe+aaVVJyPE/Y7b/oym/7Nkpx4RG5QjGJMp3BecHOoHaAZ1RSstX3eXS6YrPjMWq7nCwyAlcLVV1vCnkhefv64NJj5FdBmpcczZO6GUkwbLv0L3CA6z/zvvT6yTSvSPOS7gXNTgCBa3E0i0ny6mOn4r3Q5We3N1kmBXndXNT27S9lqt/Q0NDQ8CyN8PyG8Hi8wnPMC/fpQs9msso4XaQvJTx7octPbox459GE/ak2GimlW29ubbX5wbXhl/KmvDdscTSNa6fy0+9rFuW883BCKRXXN3RQfVnp49FffHSCIfTU9vOw2fV5+9qA3z2e8uhUX9uq0tmmW72At68PX5hu3tnu8S/DI06XCVu9AONc8GicFZRScW3UQqAnx2ff17qTW+hs0h/sDdZRP23foZCSo5kOh9/s+dzY7HBrq8PVLzDp4Mk44rePJtoNLvRSgWPqqKW39vqfK2j/VWEa2r1eVoqLBt16Uqwbm14GvVf6xQn5hoaGhoZPphGe3xDS/GJn7hlCQPkxe5vPs90P6LVcjucJSV5iCMGg5dJvuV/aztvuIODKMOTROKIfOoSu7h7/4GBKnJW8fW2wPu49c5sfzWI+PJyz+Sl6wi/j5laHfsvlYBYzj3IsQ7DZC9ju+RcKr42uxx/c2eQvfn/Ik3GkG6AMwTIpSPKKGxttPNvkg4MF8zijrBSWKeiH7tqY49omLc/mD+9scjiLtSO/4+mw/dBl1PHoBi/2mZ8nzkoOpjEH04hKKvqhy+4gZNi+OK/yeU4XKb+8f4pSsDsM1z/vJC/58GCOKQQ/vDH8jFf11dH2nXXb0kXtQrMop9dy6X7OZq+GhoaGhi+PRnh+Q2gHDvuTiN4FQzCpFGWlWCU5v/johDgr8V2L3X7IZte71HXs2SbXvmBzyMfhWCY/uamD2p+MIw5nMVkhyXLJm3t9di44Uu+3XCbLlHn8akK/L4viuQhDCP7o9W0C1+adB2MO5wlVJekGLn94p0c3dPj//PWjWmx6hK52pR/OYw5mMa9td9isdwpfNiP1eaarjL++d8p4mdYTcMHJIuX+yZLvX+1xZ7v7ieLzwemStCi5Mnj2Z+87Fv2Wy6PxiptbnZd2nn9RmIbg9laHv7x7XDcbaUEupWJaV3/e3up87g8gDQ0NDQ1fHo3w/IZwdRDyeLwiK6oXDDlnQuyDwzmuZeLYJsfzhAfHS65vtHj7+vBrcXR6EZ5j8cPrQ25vd4izknmcY1uC7V5w4eTVMg0KqYX2V4FtGvzs1gbfv9JnUXeOdwKH0LX45+8e0vIcikqSFRVCmIDAEIJlWuC71qeKvnqespL8+sGYWZRx5dykctDS+aC/ezSjG7gf2z2elxUn8+QSt7+usJxFGdMo+8qFJ8CVYUgpR7z3ZM7BNOIsbaDjO7y1N3gl+74NDQ0NDV8ejfD8hrDd97m52ebu0YLAsQg9W7fmxDnH8xiBYPecmxq0E/6joyWBZ/P9K5+uVejLJnTtdY/4+/s2aVHRumC1IM0rXEu31nyVBK617gcHmEUZ41XGD671WaUFx/OUtCgRQjBq+9zcaOupdFq8ENz/spwsUsbLlM2u/4Io7wQOqzTi0Xj1scJTKv1/9iVT0bNpqVJfjbC/iOsbuqr1dJGS18H2w473lb8GGhoaGho+PY3w/IZgGrousRu4PDxZskxyhIBB29W1gL79wiTUtU3avs3DkxU3Nztf6Rt1WlQkWYlhCNq+fekeaejqRqAPDuYEjrV23INeKZisUq5vtL8W07jz5KUkryQbrv5QMOr4FJVEwLoH/qQWTp/V4LJKC8pKskgKFlFOKSW+a9EPXYL6ccfLFKnUpdfXsQw6vjajXeQEz4oKyzS+UDf9Z8G1zS+tVrahoaGh4YujEZ7fIHS4d4frGy2SXMfuJHnJeJleOkVr+zZHs4RVUnwlwjMtKu4eLnh0uiItnpqYbm522B0EF+4j3tnpMosyHk9WdAO37hKvmMc5w7bH67u9r10Ujm0a2IZBXkpc26wd2U+vd15W2JbANj/7zyAvKx6drhCGtqGbhqCYSQ5sk71RG8c2sD7huhhCcG2jzdE8Ic7KZ6a2shbHu4OAQbsx7DQ0NDQ0vHoa4fkNxDIN2r4+hs7KChCXdvEopbfivgqdlpcVv/zohIfjiG7gMGx7VFIxXmacLo/5cTXixuaL5pqWZ/MHdza5f7Lk0WnEMsmxTZPvXe1xfaN96X7iV0k3dBh1XI7n6QtRT6qe1F4btV+61/x5lFIcTGIWScFOP3ga0QSssoL7J0u6vs0fvLb5iakEVwYhs50udw8XzCLd4FNWiiQv2eh4/GBv0LT5NDQ0NDR8ITTC8xtO23fo+A7LJL/Q5b1ICtqB85UcTe9PYh6PI3b6wToKyjbB6/lMVhnvPpmx3fMvNNyEns1bewPubHfJS4n9Ndjr/DgMIXhtp8c8PuFgGjNouTiWQVZUjJcZLc/hzk7nM09qp1HGKi3YG4bMkhzbNNbZp6Fj8XC8wq0beT4J0xD84NqAjY7P4/GKeZTjOwbfv9pnd/CsqG1oaGhoaHiVNO8w33Bs0+DGZotf3DvFtYtndvPirCTOCl7fGX3prnalFA9OlriOeWH+aC902J/EHC/Sj410cm3z0lrN82RFtTaf2JbBqON/6UJ1s+vz89sbfHAw43SRUUiJYxpcGYa8ttP9XPFPi7iglJLXdnvcP14wWWV6mi1ASmh7Nr161/NlOAvh/zRB/IskZ38ScTRPQMFG12e3H7x0HFVDQ0NDQ0MjPL8F3NjskOR6l3KyyrANoxY9Jm9c6XFz69NlRb4KKqlIL4h+OsOou9jzovrcj/XwZMl7+3PmcYZCrxa0fYc3dntc32h9qfugm12fUcdjHuUUlcSxjFfaae7aJnd2eiyTnGVSIJXCd6x1y88XxeE05pf3xyyTfC1ujxcJ948W/PDGkKvDry4PtqGhoaHhm0MjPL8FmIbgrT19THo0T0jzEs+x2Oz4DFov12bzWamkXMf8SKVoew5bPT1tdC2DVVZeeDupFAou7DX/NDyZRPz1vTGWKdjph+uA8Vmsg9ZNQ7D3JYfkG0LQb73aKWDbt7FNY53j+nzw/f4k4urQ/9h2q89KlBX8+sGYvKyeuZZDYLxM+c2DCR3foRN8/XZvGxoaGhq+XjTC81uCEIJBy3slbT4vS5yV/Or+KQfTeB3hU0lFN3B4+/qQvVGbv/rohCqUL0zjlklBy7UZdT7785VKce9oASiG7afZlYahr8XJIuGjowW7g+ALnQZ+GfRbLlu9gEenK3b6wTPd9os4xzSE7on/Aj5kHM8S5nF+YZzRsO3x8HTFwTRqhGdDQ0NDwyfSCM+Gz0QlFb++f8rjccR2L1hPLqVS6y7wn94csdMP2J/E9FsuoWtRScU8zsmKirevDz5XXuQizhkvs0t3DHuBy+kyZRbpGKZvMoYQvH1tQCklh9MYyzAwTUFaVHi2yZt7/XUf/KtmGmXYpnGp0913TMar7At57IaGhoaGbxeN8Gz4TExWKQezhK2e/8xxuSEEm12fR6crTpcpP7014v39OfuTiFmcYwLd0OWtvQHXNj7fEXglFVLJS7u6TVMglUJ+jVp4Pg+hZ/OHdzY5miUczWLyuid+p+/TD7+4lQrDEB97DaUEq+lLb2hoaGh4CRrh2fCZmNXNOZe55VuezcEk5s2rfX5yc8RrO13iTAfId0PnlewiBnX3eZyXF2Z7xlmJZ5vfqnggxzLZG7W+1L3VYcvjAzWnkhKpAAWWKRBCC9K8rNjofDHT1oaGhoaGbxffnnfkhi+dj5txCQEKtXaZtzz7M3eUX4bvWFwdhvz+8QzXMkgLWf93E9MwmKwyXtvpvvLH/a6x1fNxLZN/9cEJlikwDEHLtRi0XbJCMmx7bH+KWKaGhoaGhu8ujfBs+Ey0PN23XlbyGaPLGaus4PZW9zM34Oi2n4zjeUJSu/S3uj79lvvMfd7cbPP7x1P+4veHKLTD3zQFvm3x1l6f13e6n/VbbKg5mMakRUkpJWlRoRSczBM+Olry+m6XH90YfKumyg0NDQ0NXxzNu0XDZ2Kj4zFsexzPE7b7wTNicB7n2Ib5Ui06F1FJxe8fT7l7uCCvKmzToKwkH+wb3Nzq8NZeH/P/396dxsZVHmocf845s3sWj5fYMbZjY5ZcRAOXhOYGUbUpKBRVLSAVCQnR0AXJKEWJkAoNlQofWqWqkCo13UCVAqJL6KIkQipV8gFCJYQgJRbcULglJDiJEydeZ/NsZ879YGIwHidOgs8Z2/+fNB88M/E8eeXl8Tvv+x7TVMVx9MFgWnbFUXtjnSYKtspORaWyI8s0FPRbCgVq92pHC0EmX9I7x0YVDQW07uoWpbLFj47Imlzz6TPNybffAQCYA4onLorPMrVqRaMOHpnc2R4OWDINQxPFsoJ+S9d2JrUscXHr/o6eTunfJ0bVEA2qLvjx58gVyvq/gTGF/JauaqvXaKagI4NptSQiigR9qlQc2ZXJ0lmuVDQ4NlH12umYu8GxCWXyJbU31k0e2RULqeET1yM4MZzVyZEcazwBAHNC8cRFS0aD+p+rWnRqLKeTo1mVK45WNEe1PFl30ccXleyKjp7OKBLwzThqKRL0qVDy68MzGXUti+n0+IRKtq3IR+XUNCfXH0pSwJyc6RwYzVI8L0E2X5LPMmfdMR8KWBrPFV1OBQBYqCieuCSRoE+Xt8R1eUv8M/l86Ymi0vmiGmc5CD8e8WtwbEKpXEn5Ulm+cxwMH/BbmpjlykmYG8syZFcqsz5etp1LvvoUAGDpoHii5jhnt8JX9fEDoYBPJXv2UlQs26pzYUe7XXF0enxCJ0YySuVKCvpNXdYQVWsyotAs16pfKJrjYb1njKlYtmccnWVXKiraNjPKAIA5o3iippw9dimTLylZ5YpEmXxJkaBf0bBfpin9x28pmy/NKJj5ki3JmPdSZFcq+t/+ER0+lZI0ecRTJl/SwEhOrcmIbuhucqX8zpfGWEjtjVF9eCatxlhIkeDkj4xCydbp1IRa6yNqrad4AgDmhuKJmhLwWVrRHNVbR4cVDvimzRgWSrbGcwV9rrNRIb+loM9UT2tc7x4fU75kKxb2yzAMZSZKyuRLumJ5Yt43vRwbyuo/J8fVFAsp9IkjhexKRQMjOb3jH9WanuZ5u6rQfLNMQ6u6GmVZhgZGshrO5GVI8lumOhrqdO2KRgUX+KwuAMA9FE/UnMtb4soWyjpyOi3JUcCyVCzbkqSelrh6WifXkxqGoZWXJRUJ+HT0dFqjmYIcSXVBv67ratTlLfFZL6f5WbArFX14Jq2Q3zetdEqSZZpqjIV0aiyn8Vxx1uvJLwQhv6UbupvU0xLXeK4ox5FiYf+MM1UBADgfiidqztmjmpYnIzo5mlOuUFY4YKktWafmREjWJzYUWaah7pa4OpqiSk+UJEl1Id+sl/L8LOWLttL54qxvpUeCPo1kCsrmywu6eEqTJb++Lrjg/x8AAG9RPFGTLNO4oPWDPstUMupuKTIMQ4aMyc1QVVScjy5szqQgAACSJM5BAS5SOGCpMRaa9RzLzEebnqptkgIAYCmieAIXyTAMrWiOyTSMyfWln5j6zBXKGs8W1dkUm9oJvlg4jqP0REkjmbyy+ZLXcQAAC8ji+o0IzEGxbOv0+ITGspMzlYlIQC314YtaF7o8GdF1XY3694lRHRvOyjIN2RVHQZ+lq9oSuqot8VnH99RwOq/Dp1I6ncqpVHYU9JlqTUZ0RWtC8UjA63gAgBpH8cSSMpYtqO/okIZSBZ3dkF1xHDXHQrquq+mi1ol2LYupOR7S6fEJTZRs+S1TjbGgknXBBXuMUjXD6bzeeP+MMvmiGqIhBSKm8iVbh0+lNJop6sYrmimfAIBzonhiyciXbPUdGdJwJq/lycjU7ni7UtGp0QkdPDKkm65umXE00lzUhfzqXsAHxZ9PxXH03sCYsoWS2hujU/dHLVORoE8nhrM6PJjSf3c3eZgSAFDrWOOJJeP0WE5D6byW19d96kgmU8uTEY2k8zo1NuFhwto1ni3qzHhejbHQjMdMw1AyGtTJ0ZyyBdZ8AgBmR/HEknEmnZfPNGVWOVTeNA35fKbOpCie1RTLtkp2ZdZrzwf9k4f8F0sVl5MBABYSiieWjErF0bmWXJqGMW1nOj7m95nyWcbUFaQ+rVieXNvq9/EjBQAwO35LYMloiIZULFeqlkvHcVQo2a4fQr9Q1NcF1RgLaSRdmPGY4zgazRTUUh9WdBGvcwUAXDqK5xJVsiuzzl4tVq31YcUjAZ1J5Wc8NpTOKxYOaHmyzoNktc80DF21PCG/z9TJ0ZwKJVuO4yhfLGtgJKdYOKCelsV1dBQA4LPHrvYlZnAsp2PDGQ2lJmeumuJBtTdG1ZIIL6qjf6qpC/l13YpG9R0dVv9QRpGATzKkiUJZsbBfq1Y0MGN3Di31Ea3padZ/To5rOJ1XqeIoYJm6rLFOVy5PMFsMADgviucScmQwpbc+HFG5UlEs7Jchqf9MRieGc7q2M6mGaEinxnIazxXlMw0tq4+o9SIPVq9VrcmIbgr5dHIkq9OpvORIPa1xXZas4wzKOWipj6g5EdZYtqCy7SjgM5WIBBb9Hy0AgM8GxXOJGMsW9M7xUQX9plrqwlP3x8IBjeeKeuWdAdWF/DIMQyG/Jdt2dPRMWi31EV3f1aRYePHMBMbDAcUvC+jqy7xOsjCZhqGG6MxjlQAAOB/WeC4Rp8ZyyhXKqq+b+Xao4zj6cCirbKGsjsaomuNhtSYjWp6MaHAsp7f7h1VhtzcAALhEFM8lIj1RUnCWMxiHUnmZmpzJ+iTLNLUsEdbg2ISG0zM35AAAAFwIiucS4bNMle2Zh3vblYpSEyX5LVNWlYPVAz5L5UpFqRxXpAEAAJeG4rlELEuEVXGcquWz4lRUcRwlq7wNfxZ7RwAAwKWieC4RyxJhtSXrdHI0p3zp4/M7S7ajku0oGLCUqLKru1CyFbDMqo8BAABcCHa1LxF+y9R13Y2yLFOnRnMasm05jhTwmbqmI6n0REmpiZKSdR8fjVOyKxocz6mzOcYZjQAA4JJRPJeQuqBfN17RrNFMQemJkhzHUTwSUDIa1LGhjA4dG9Xx4awCPlN2xZEjqb0hqs91NszYeAQAAHChKJ5LjGkYaoyF1Bibfg7jio9mNU+N5pSeKMlnGWqKh7UsEZbfYkUGAAC4dBRPTImHA4qHWcsJAADmB1NZAAAAcAXFEwAAAK6geAIAAMAVFE8AAAC4guIJAAAAV1A8AQAA4AqKJwAAAFxB8QQAAIArKJ4AAABwBcUTAAAArqB4AgAAwBUUTwAAALiC4gkAAABXUDwBAADgCoonAAAAXEHxBAAAgCsongAAAHAFxRMAAACuoHgCAACaSaxAAAALxElEQVTAFa4Uz0KhoOuvv16GYaivr8+NlwQAAECNcaV4PvLII2pra3PjpQAAAFCj5r14vvjii9q7d6+efPLJ8z63UCgolUpNuwEAAGBxmNfiOTg4qAceeEDPPfecIpHIeZ+/bds2JRKJqVtHR8d8xgMAAICL5q14Oo6j+++/X729vVqzZs2c/s3WrVs1Pj4+dTt27Nh8xQMAAIDLLrh4PvHEEzIM45y3AwcOaPv27UqlUtq6deucP3cwGFQ8Hp92AwAAwOJgOI7jXMg/GBoa0tDQ0Dmf09XVpXvuuUcvvPCCDMOYut+2bVmWpXvvvVfPPvvseV8rlUopkUhofHycEgoAAFCDLqSvXXDxnKv+/v5pm4MGBgZ022236a9//avWrl2r9vb2834OiicAAEBtu5C+5puvEJ2dndM+jkajkqSenp45lU4AAAAsLly5CAAAAK6YtxnPT+vq6tI8vasPAACABYAZTwAAALiC4gkAAABXUDwBAADgCoonAAAAXEHxBAAAgCsongAAAHAFxRMAAACuoHgCAADAFRRPAAAAuILiCQAAAFe4dslMXLpcoazhdF52xVHQb6kpHpLf4m8HAACwMFA8F4CK4+j9k+P6YDCldL4kQ4YMQ2qIBvVf7Um11ke8jggAAHBeTJctAB+cSunt/mFJ0mUNdWpvrFNLIqxUrqg3PxjScDrvcUIAAIDzo3jWuHzJ1uHBlCJBv+rrgjINQ5Lks0y11EeUK5Z09Eza45QAAADnR/GscaOZgjITJSXCgaqP10eCOj02oXyx7HIyAACAC0PxrHF2pSJHkmkaVR/3mYZspyK74rgbDAAA4AJRPGtcOOCTzzJUKNlVH88Vywr7/Qr6LZeTAQAAXBiKZ41LRoNaFg9rKD2hijN9VrNUriiTL6uzuU4+jlUCAAA1juOUapxpGLqmI6lcsazjwxnFwwH5LVMTRVsTxbJWNMe0ojnmdUwAAIDzonguAPV1QX3+ymU6PpzV8eGMiuWKoiGfrulIqr2xTgEfb7MDAIDaR/FcIOLhgK5pD+iq5QnZFUc+y5Q1y4YjAACAWkTxXGB8likmOAEAwELEjhQAAAC4guIJAAAAV1A8AQAA4AqKJwAAAFxB8QQAAIArKJ4AAABwBcUTAAAArqB4AgAAwBUUTwAAALiC4gkAAABXUDwBAADgCoonAAAAXEHxBAAAgCsongAAAHAFxRMAAACuoHgCAADAFRRPAAAAuILiCQAAAFdQPAEAAOAKiicAAABc4fM6wLk4jiNJSqVSHicBAABANWd72tnedi41XTzT6bQkqaOjw+MkAAAAOJd0Oq1EInHO5xjOXOqpRyqVigYGBhSLxWQYxry/XiqVUkdHh44dO6Z4PD7vr7eQMDbVMS6zY2yqY1xmx9hUx7jMjrGpzu1xcRxH6XRabW1tMs1zr+Ks6RlP0zTV3t7u+uvG43G+gGfB2FTHuMyOsamOcZkdY1Md4zI7xqY6N8flfDOdZ7G5CAAAAK6geAIAAMAVFM9PCAaDevzxxxUMBr2OUnMYm+oYl9kxNtUxLrNjbKpjXGbH2FRXy+NS05uLAAAAsHgw4wkAAABXUDwBAADgCoonAAAAXEHxBAAAgCsongAAAHAFxXMOCoWCrr/+ehmGob6+Pq/jeO7rX/+6Ojs7FQqFtHz5ct13330aGBjwOpbnjh49qu985zvq7u5WOBxWT0+PHn/8cRWLRa+jee4nP/mJbrrpJkUiEdXX13sdx1O//vWv1d3drVAopNWrV+uf//yn15E898orr+hrX/ua2traZBiGdu/e7XWkmrBt2zbdeOONisViWrZsme6880699957Xsfy3G9+8xutWrVq6qo869at04svvuh1rJqzbds2GYahLVu2eB1lGornHDzyyCNqa2vzOkbNWL9+vf785z/rvffe09/+9jcdPnxY3/jGN7yO5bl3331XlUpFTz31lA4dOqSf//zn+u1vf6vHHnvM62ieKxaLuvvuu/Xggw96HcVTzz//vLZs2aIf/vCHOnjwoL7whS/o9ttvV39/v9fRPJXNZnXdddfpl7/8pddRasr+/fu1adMmvfbaa9q3b5/K5bI2bNigbDbrdTRPtbe366c//akOHDigAwcO6Mtf/rLuuOMOHTp0yOtoNeONN97Q008/rVWrVnkdZSYH5/T3v//dWblypXPo0CFHknPw4EGvI9WcPXv2OIZhOMVi0esoNednP/uZ093d7XWMmrFjxw4nkUh4HcMzn//8553e3t5p961cudL5wQ9+4FGi2iPJ2bVrl9cxatLp06cdSc7+/fu9jlJzksmk87vf/c7rGDUhnU47V155pbNv3z7ni1/8orN582avI03DjOc5DA4O6oEHHtBzzz2nSCTidZyaNDIyoj/84Q+66aab5Pf7vY5Tc8bHx9XQ0OB1DNSAYrGof/3rX9qwYcO0+zds2KBXX33Vo1RYSMbHxyWJnymfYNu2du7cqWw2q3Xr1nkdpyZs2rRJX/3qV3Xrrbd6HaUqiucsHMfR/fffr97eXq1Zs8brODXn0UcfVV1dnRobG9Xf3689e/Z4HanmHD58WNu3b1dvb6/XUVADhoaGZNu2Wlpapt3f0tKiU6dOeZQKC4XjOHr44Yd1880369prr/U6jufefvttRaNRBYNB9fb2ateuXbrmmmu8juW5nTt36s0339S2bdu8jjKrJVc8n3jiCRmGcc7bgQMHtH37dqVSKW3dutXryK6Y67ic9f3vf18HDx7U3r17ZVmWvvnNb8pZpFdfvdCxkaSBgQF95Stf0d13363vfve7HiWfXxczLpAMw5j2seM4M+4DPu173/ue3nrrLf3pT3/yOkpNuPrqq9XX16fXXntNDz74oDZu3Kh33nnH61ieOnbsmDZv3qzf//73CoVCXseZ1ZK7VvvQ0JCGhobO+Zyuri7dc889euGFF6b9QrBtW5Zl6d5779Wzzz4731FdNddxqfbFfPz4cXV0dOjVV19dlG91XOjYDAwMaP369Vq7dq2eeeYZmebi/PvuYr5mnnnmGW3ZskVjY2PznK72FItFRSIR/eUvf9Fdd901df/mzZvV19en/fv3e5iudhiGoV27dunOO+/0OkrNeOihh7R792698sor6u7u9jpOTbr11lvV09Ojp556yusontm9e7fuuusuWZY1dZ9t2zIMQ6ZpqlAoTHvMKz6vA7itqalJTU1N533eL37xC/34xz+e+nhgYEC33Xabnn/+ea1du3Y+I3piruNSzdm/XQqFwmcZqWZcyNicOHFC69ev1+rVq7Vjx45FWzqlS/uaWYoCgYBWr16tffv2TSue+/bt0x133OFhMtQqx3H00EMPadeuXXr55ZcpnefgOM6i/R00V7fccovefvvtafd961vf0sqVK/Xoo4/WROmUlmDxnKvOzs5pH0ejUUlST0+P2tvbvYhUE15//XW9/vrruvnmm5VMJvXBBx/oRz/6kXp6ehblbOeFGBgY0Je+9CV1dnbqySef1JkzZ6Yea21t9TCZ9/r7+zUyMqL+/n7Ztj11Hu4VV1wx9b21FDz88MO67777tGbNGq1bt05PP/20+vv7l/w64Ewmo/fff3/q4yNHjqivr08NDQ0zfhYvJZs2bdIf//hH7dmzR7FYbGotcCKRUDgc9jiddx577DHdfvvt6ujoUDqd1s6dO/Xyyy/rH//4h9fRPBWLxWas/z27F6Om1gV7tp9+gTly5AjHKTmO89Zbbznr1693GhoanGAw6HR1dTm9vb3O8ePHvY7muR07djiSqt6Wuo0bN1Ydl5deesnraK771a9+5axYscIJBALODTfcwNE4juO89NJLVb8+Nm7c6HU0T83282THjh1eR/PUt7/97anvoebmZueWW25x9u7d63WsmlSLxyktuTWeAAAA8MbiXYAGAACAmkLxBAAAgCsongAAAHAFxRMAAACuoHgCAADAFRRPAAAAuILiCQAAAFdQPAEAAOAKiicAAABcQfEEAACAKyieAAAAcMX/A7ncFofchbBCAAAAAElFTkSuQmCC" + ] }, "metadata": {}, "output_type": "display_data" } ], - "execution_count": 37 + "source": [ + "# Answer for Exercise 5 (2)\n", + "plt.figure(figsize=(8, 8))\n", + "plt.scatter(\n", + " X[:, 0],\n", + " X[:, 1],\n", + " c=y,\n", + " alpha=0.3,\n", + " cmap=mcolors.ListedColormap([\"steelblue\", \"tomato\"]),\n", + " label=\"Sample\",\n", + ")\n", + "\n", + "x1 = np.linspace(-4, 4, 100)\n", + "x2_learn = -(a1 * x1 + b) / a2 # Cf above\n", + "plt.plot(x1, x2_learn, label=\"Logistic Regression\", c=\"green\")\n", + "plt.legend()\n", + "plt.show()" + ] }, { "cell_type": "markdown", @@ -410,12 +425,25 @@ }, { "cell_type": "code", + "execution_count": 38, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:31:48.554831Z", "start_time": "2025-03-19T09:31:48.474934Z" } }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def sigmoid(x):\n", " return 1 / (1 + np.exp(-x))\n", @@ -425,20 +453,7 @@ "plt.plot(x, sigmoid(x), label=\"Sigmoid Function\")\n", "plt.legend()\n", "plt.show()" - ], - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ], - "image/png": 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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 38 + ] }, { "cell_type": "markdown", @@ -451,19 +466,19 @@ }, { "cell_type": "code", + "execution_count": 39, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:31:48.891615Z", "start_time": "2025-03-19T09:31:48.884879Z" } }, + "outputs": [], "source": [ "def cost_log_likelihood(X, y, w, b):\n", " h = sigmoid(np.dot(X, w) + b)\n", " return -np.sum(y * np.log(h) + (1 - y) * np.log(1 - h))" - ], - "outputs": [], - "execution_count": 39 + ] }, { "cell_type": "markdown", @@ -485,12 +500,14 @@ }, { "cell_type": "code", + "execution_count": 40, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:31:49.482987Z", "start_time": "2025-03-19T09:31:49.479349Z" } }, + "outputs": [], "source": [ "def GD_training(X, y, num_steps, learning_rate):\n", " w, b = np.zeros(2), 0\n", @@ -506,12 +523,13 @@ "\n", " if step % 300 == 0:\n", " print(\"In step \", step, \", the parameters are \", w, b, \";\")\n", - " print(\"and the value of the cost function is \", cost_log_likelihood(X, y, w, b))\n", + " print(\n", + " \"and the value of the cost function is \",\n", + " cost_log_likelihood(X, y, w, b),\n", + " )\n", "\n", " return w, b" - ], - "outputs": [], - "execution_count": 40 + ] }, { "cell_type": "markdown", @@ -522,17 +540,13 @@ }, { "cell_type": "code", + "execution_count": 41, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:31:52.538272Z", "start_time": "2025-03-19T09:31:51.682437Z" } }, - "source": [ - "w_GD, b_GD = GD_training(X, y, num_steps=3000, learning_rate=5e-5)\n", - "\n", - "print(\"The parameters are : \", w_GD, b_GD)" - ], "outputs": [ { "name": "stdout", @@ -562,44 +576,54 @@ ] } ], - "execution_count": 41 + "source": [ + "w_GD, b_GD = GD_training(X, y, num_steps=3000, learning_rate=5e-5)\n", + "\n", + "print(\"The parameters are : \", w_GD, b_GD)" + ] }, { "cell_type": "code", + "execution_count": 42, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:31:52.801878Z", "start_time": "2025-03-19T09:31:52.597175Z" } }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "plt.figure(figsize=(8, 8))\n", - "plt.scatter(X[:, 0], X[:, 1], c=y, alpha=0.3, cmap=mcolors.ListedColormap([\"steelblue\", \"tomato\"]))\n", + "plt.scatter(\n", + " X[:, 0],\n", + " X[:, 1],\n", + " c=y,\n", + " alpha=0.3,\n", + " cmap=mcolors.ListedColormap([\"steelblue\", \"tomato\"]),\n", + ")\n", "\n", - "# Plot the decision boundaries \n", + "# Plot the decision boundaries\n", "# blue : the decision boundary using Sklearn\n", - "# rouge : the decision boundary using GD \n", + "# rouge : the decision boundary using GD\n", "x1 = np.linspace(-4, 4, 100)\n", "x2_GD = -(w_GD[0] * x1 + b_GD) / w_GD[1]\n", "\n", "plt.plot(x1, x2_GD, c=\"tomato\", label=\"GD\")\n", "plt.plot(x1, x2_learn, c=\"steelblue\", label=\"Sklearn\")\n", "plt.legend()\n", - "plt.show()\n" - ], - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ], - "image/png": 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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 42 + "plt.show()" + ] }, { "cell_type": "markdown", @@ -646,18 +670,13 @@ }, { "cell_type": "code", + "execution_count": 43, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:32:02.484670Z", "start_time": "2025-03-19T09:32:02.480673Z" } }, - "source": [ - "a = np.arange(10)\n", - "rng = np.random.default_rng(seed=42)\n", - "rng.shuffle(a) # shuffle in place\n", - "a" - ], "outputs": [ { "data": { @@ -670,16 +689,23 @@ "output_type": "execute_result" } ], - "execution_count": 43 + "source": [ + "a = np.arange(10)\n", + "rng = np.random.default_rng(seed=42)\n", + "rng.shuffle(a) # shuffle in place\n", + "a" + ] }, { "cell_type": "code", + "execution_count": 58, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:51:37.764449Z", "start_time": "2025-03-19T09:51:37.744068Z" } }, + "outputs": [], "source": [ "def mini_batch_SGD(X, y, learning_rate, batch_size, epochs):\n", " \"\"\"\n", @@ -691,7 +717,7 @@ " learning_rate (float): Learning rate for gradient descent.\n", " batch_size (int): Size of each mini-batch.\n", " epochs (int): Number of epochs to train.\n", - " \n", + "\n", " Returns:\n", " w (numpy.ndarray): Final weight vector of shape (d,).\n", " b (float): Final bias term.\n", @@ -712,8 +738,8 @@ "\n", " # Mini-batch processing\n", " for i in range(0, n, batch_size):\n", - " X_batch = X_shuffled[i:i + batch_size]\n", - " y_batch = y_shuffled[i:i + batch_size]\n", + " X_batch = X_shuffled[i : i + batch_size]\n", + " y_batch = y_shuffled[i : i + batch_size]\n", "\n", " # Compute predictions\n", " h = sigmoid(np.dot(X_batch, w) + b)\n", @@ -736,19 +762,17 @@ " costs_SGD.append(current_cost)\n", "\n", " return w, b, costs_SGD" - ], - "outputs": [], - "execution_count": 58 + ] }, { "cell_type": "code", + "execution_count": 64, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:56:51.427407Z", "start_time": "2025-03-19T09:56:46.160169Z" } }, - "source": "w_SGD, b_SGD, cost_SGD = mini_batch_SGD(X, y, learning_rate=5e-5, batch_size=50, epochs=1000)\n", "outputs": [ { "name": "stdout", @@ -40757,29 +40781,21 @@ ] } ], - "execution_count": 64 + "source": [ + "w_SGD, b_SGD, cost_SGD = mini_batch_SGD(\n", + " X, y, learning_rate=5e-5, batch_size=50, epochs=1000\n", + ")" + ] }, { "cell_type": "code", + "execution_count": 55, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:47:35.522758Z", "start_time": "2025-03-19T09:47:35.500853Z" } }, - "source": [ - "# when n//batch_size=0\n", - "x = np.array(['a', 'b', 'c', 'd', 'e', 'f'])\n", - "indices = np.array([0, 1, 2, 3, 4, 5])\n", - "n = len(x)\n", - "np.random.default_rng().shuffle(indices)\n", - "batch_size = 2\n", - "x_shuffled = x[indices]\n", - "j = 0\n", - "for i in range(0, n, batch_size):\n", - " print(f\"batch number {j}\", x_shuffled[i:i + batch_size])\n", - " j += 1" - ], "outputs": [ { "name": "stdout", @@ -40791,29 +40807,29 @@ ] } ], - "execution_count": 55 - }, - { - "cell_type": "code", - "metadata": { - "ExecuteTime": { - "end_time": "2025-03-19T09:47:36.146264Z", - "start_time": "2025-03-19T09:47:36.142238Z" - } - }, "source": [ - "#when n//batch_size different from zero. \n", - "x = np.array(['a', 'b', 'c', 'd', 'e', 'f', 'g'])\n", - "indices = np.array([0, 1, 2, 3, 4, 5, 6])\n", + "# when n//batch_size=0\n", + "x = np.array([\"a\", \"b\", \"c\", \"d\", \"e\", \"f\"])\n", + "indices = np.array([0, 1, 2, 3, 4, 5])\n", "n = len(x)\n", "np.random.default_rng().shuffle(indices)\n", "batch_size = 2\n", "x_shuffled = x[indices]\n", "j = 0\n", "for i in range(0, n, batch_size):\n", - " print(f\"batch number {j}\", x_shuffled[i:i + batch_size])\n", + " print(f\"batch number {j}\", x_shuffled[i : i + batch_size])\n", " j += 1" - ], + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": { + "ExecuteTime": { + "end_time": "2025-03-19T09:47:36.146264Z", + "start_time": "2025-03-19T09:47:36.142238Z" + } + }, "outputs": [ { "name": "stdout", @@ -40826,7 +40842,19 @@ ] } ], - "execution_count": 56 + "source": [ + "# when n//batch_size different from zero.\n", + "x = np.array([\"a\", \"b\", \"c\", \"d\", \"e\", \"f\", \"g\"])\n", + "indices = np.array([0, 1, 2, 3, 4, 5, 6])\n", + "n = len(x)\n", + "np.random.default_rng().shuffle(indices)\n", + "batch_size = 2\n", + "x_shuffled = x[indices]\n", + "j = 0\n", + "for i in range(0, n, batch_size):\n", + " print(f\"batch number {j}\", x_shuffled[i : i + batch_size])\n", + " j += 1" + ] }, { "cell_type": "markdown", @@ -40844,17 +40872,13 @@ }, { "cell_type": "code", + "execution_count": 66, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:57:02.992900Z", "start_time": "2025-03-19T09:57:02.961126Z" } }, - "source": [ - "w_SGD, b_SGD, costs_SGD = mini_batch_SGD(X, y, learning_rate=5e-4, batch_size=1000, epochs=30)\n", - "\n", - "print(\"The parameters computed by stochastic gradient descent are: \", w_SGD, b_SGD)\n" - ], "outputs": [ { "name": "stdout", @@ -40924,19 +40948,44 @@ ] } ], - "execution_count": 66 + "source": [ + "w_SGD, b_SGD, costs_SGD = mini_batch_SGD(\n", + " X, y, learning_rate=5e-4, batch_size=1000, epochs=30\n", + ")\n", + "\n", + "print(\"The parameters computed by stochastic gradient descent are: \", w_SGD, b_SGD)" + ] }, { "cell_type": "code", + "execution_count": 67, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T09:57:05.419724Z", "start_time": "2025-03-19T09:57:05.033915Z" } }, + "outputs": [ + { + "data": { + "image/png": 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AkThQrwHlwoZu5kbhmhLPL3/5y7j77rvx9re/Hd3d3bjjjjvwJ3/yJyu+v9FooFgsLvi6ETEzM4P3vve92LZtG0KhEHp7e/G6170OTz755EZvmoKCgoLCRmJylOXZWBLoGaDK2dXHyTzjI8D5kxu9hQproa2T4zutOtBoUNn0PKBeJSHt6QdMA8hnN3pLNwTXlHieO3cOf/zHf4w9e/bgG9/4Bv71v/7X+I3f+A187nOfW/b9H//4x5FKpea/hoaGruXmbRje+ta34rnnnsOjjz6KU6dO4ctf/jJ+6qd+Ctns5rkIm031VK2goKBwXeE4wNgI3c+R6MLXAkEgkQamxljGVdi80HWgu58PDq4DFDL8cl2gdxDoH2aQvONs9JZuCK4p8XRdF3feeSc+9rGP4Y477sB73/tevOc978Ef//EfL/v+D37wgygUCvNfo6Oj13LzNgT5fB7f//738cgjj+A1r3kNhoeHce+99+KDH/wgXv/61y/7mY985CPo6enBs88+u+zrhUIBv/qrv4ru7m4kk0m89rWvxXPPPTf/+tmzZ/GmN70JPT09iMfjuOeee/D4448vWMb27dvx0Y9+FO9617uQSqXwnve8B5/97GeRTqfxjW98A/v370c8Hsc/+Sf/BJOTk1fteCgoKCgoCNSqQKW48jSeaJyks1y6vtulcGnQdSDdTtf6noPArgP82nNQkE4d8ACEwxu9pRuCa0o8+/r6cODAgQU/279/Py5evLjs+0OhEJLJ5IKvS4Hneag37Q358jxvXdsYj8cRj8fx2GOPodForLk/73//+/E//+f/xPe//33cfvvty77n9a9/PaampvDVr34VR44cwZ133okHH3xwXkEtl8v42Z/9WTz++OM4evQoXve61+GNb3zjkvPw3/7bf8OhQ4dw5MgR/M7v/A4AoFqt4vd///fx+c9/Hk888QQuXryI3/qt31rXviooKCgoXCo0kJUsh5vTjLIl0TtIhdPz2OeZbKOSDQC5DJBKA+3dG7qJG4Vrao+7//77cfLkwn6UU6dOYXh4+Jqsr2E5eNMj37gmy14LX/rt1yEcXPtwmqaJz372s3jPe96DT33qU7jzzjvxwAMP4B3veAduu+22+ffZto13vvOdePrpp/GDH/wAg4ODyy7v29/+Nl544QXMzMwgFAoBAH7/938fjz32GP76r/8av/qrv4rDhw/j8OHD85/56Ec/ii9+8Yv48pe/jF//9V+f//lrX/vaBaTy+9//PizLwqc+9al5Q9iv//qv4yMf+cilHRwFBQUFhbURjXKsYrkAtC+jhlXKQDgKJC5NlNnyqJb5pelAPEmX/2ZHVy+wbRdjlMwAEI2xtF4psY1i90G6329CXFPF8zd/8zfxox/9CB/72Mdw5swZ/K//9b/w6U9/Gu973/uu5Wo3Pd761rdiYmICX/7yl/G6170O3/nOd3DnnXfis5/97Px7fvM3fxNPPvkkvve9761IOgHgyJEjKJfL6OjomFdT4/E4zp8/j7NnzwIAKpUKPvCBD+DAgQNIp9OIx+M4ceLEEsXz7rvvXrL8aDS6IIWgr68PMzMzV3gEFBQUFBSWQDc4y9u2SLRa0ayTkPZvI/m8GdCoA8efBX7yBHDk+8CR7wFPfZcGq83eH6kbwN5DwG33suxuNQF4JKO33UvD2E2Ka6p43nPPPfjiF7+ID37wg/jIRz6CHTt24JOf/CR+8Rd/8ZqsLxQw8KXfft01WfZ61n0pCIfDePjhh/Hwww/jwx/+MH7lV34Fv/u7v4t3vetdAICHH34Yf/mXf4lvfOMbqx4v13XR19eH73znO0tek3mp/+7f/Tt84xvfwO///u9j9+7diEQieNvb3rbEQBSLxZYsIxAILPi3pmnrbitQUFBQULhE9A6x1/PCaaCUB4wA4FgkMtt2AcN7NnoLrw+sJvDSUWB6jGXqVBvL1uUicPIFkvPdBzd364FuAH1DNBlZTfZ2BoIbvVUbjmueRPuGN7wBb3jDG671agCQFK2n3L0ZceDAgQXZnf/0n/5TvPGNb8Q//+f/HIZh4B3veMeyn7vzzjsxNTUF0zSxffv2Zd/zve99D+9617vwlre8BQB7PkdGRq7yHigoKChsAVhNf3KMpgGJ1OYKZtd1YOc+zvKemyYJDYaAjm6grYNk5mbA7BSD1rv6GE0E8Hwl00AgAIyeB3oG+e/NDl3fGu0B1wmb5Dft5kEmk8Hb3/52vPvd78Ztt92GRCKBp59+Gr/3e7+HN73pTQve+5a3vAWf//zn8cu//MswTRNve9vblizvoYcewstf/nK8+c1vxiOPPIJbbrkFExMT+OpXv4o3v/nNuPvuu7F792787d/+Ld74xjdC0zT8zu/8DlzXvV67rKCgoLA5UMgBJ58HcrP+zzSdJo99h4H4Cm7y6w1NA1Lt/LpZMT3O3khjGZoSiQGFLM/jlRBP2+L/zcDq71O4qlDE8zojHo/jvvvuwyc+8QmcPXsWlmVhaGgI73nPe/ChD31oyfvf9ra3wXVd/PIv/zJ0XcfP/dzPLXhd0zR89atfxX/4D/8B7373uzE7O4ve3l68+tWvRk9PDwDgE5/4BN797nfjFa94BTo7O/Hbv/3bN2w4v4KCgsKyqNc4+aeUBzr7OEEGAByboylPeMDh+7ZeKbRcAjJTjFkygwwvvxGU0UZt9XOh6YBlXd6ys7MM6pcPIOkOutA7ejZ36f4GgeZt4oa9YrGIVCqFQqGwJFqpXq/j/Pnz2LFjB8I3aRbWZoQ6LwoKCpsSY+eBF49waoy2yFfrOMDcJHD4ZSQgG4VmA8jOkCTrBhXPZHp5MuR53KdzJ0g6DZNh5boJ9A0Ct9y2PHGzmiTbZmBzK30vPMWw/OVMOJ4HTI8CB+8GhnZe2nLHR9gj6lgcXQnw+Ok6e0aHd1/xpt+MWI2vLYZSPBUUFBQUbnxkZtgbuJh0AlQ/NZ1z0TeKeM5OAmeOcb635JmBIM0puw8uJZFzU8CpF4BAiL2Okpw2GySkZoDtAxLVMjBxgWTOtoFgkEamzeqS7x6gKtlsLI0dKhdJGtu7Lm2Z5RJw9jj7eVs/G08yMeD8CaqfqbYr336FFXFN45QUFBQUFBQ2BVyHqtZK0HW+ZyNQyDI2qFoFuvtIJHsGOanowhmSpVZ4HjBxkQHlixXRYIgu8Kkxf8JRuQg8/xPgzEtiYk6U5PPkC1SBN+MIzs4eYHA7y+GFLJXaRp0PEI0qsH3vyhOeVsLcFAl4chliGU9x+bMTV2XzFVaGIp4KCgoKCjc+Uu0kFsvBc2k0SaSv6ybNY3KU5K+je2FvZjjK7Z4aXTgms1EnGYuvUNKMxPiecoH/HjlFNbdngC7+cITkq6efZOziuWu3b5cLwwD23kbVNhhib26lxONx6G5GS10qKiX2wa6EYAgoFS57kxXWB1VqV1BQUFC48dHVxxJ0PsNyaitycyRknT3Xf7tsi+QvtgqJLGSBYrbFde8Brge/Jr8Imhy7KXIv56aAVMfSNgPdoNI3PcbexnDk6uzT1YJpMrd0YDtjpTSd050u1zgl+2BXguNsPXPZFsSWVzw3sTfqpoQ6HwoKCpsSiRSw5xAAjUSrkCUJnR4j2dh7G0ne9YbnsWS+VhtA69/WYBhIJpdON5Ko19j7GU1Q+Ww0ViaVkSj7KFdSgzcDzADPXzxxZW799k7+317GDe84bD/o2ICHj5sMW5Z4yok61Wp1g7dEoRVyGpJhbPEoDwUFhRsPfUPAHS8Hdu1nGTsaJxm9/eWcrb0RkKSqukKfpdWk0tdqANJ1oG+Y7vTF/ZmODeTnuD+JFEvWhsGfLwfbohJ4M/zNbu+m8j03xRGkEs0GzV2dvRujet9k2LKldsMwkE6n5+eGR6NRaCp/a0Phui5mZ2cRjUZhbpYpIAoKCgqtSInxi5slNUfTSIhnp4B6dSHB9Fyaazp6mM3Zip4BoFIERk4DxTwn49gWVbvuPmD3ATGZKQ0k24FijsRrMYp5Eq5LNepsRZgmsP8wSfbcFNCc5TEyTKYZ7D2kSu3XAVuaHfT28glVkk+FjYeu69i2bZt6CFBQUFBYL7r7ge176GAvF4FQhAplvcp+1D2HlpaYdR3YuZ9kcmaSRqJgiIpeZw/L63NTVEsHtgEn8+xlTbb5Cmg+y4ipbTtvnuD0cJTmpGKOxxog6U61r97uoHDVsGUD5FvhOA6sy51goHBVEQwGoatfXgUFBYVLg+uSKE6N0VktVbie/kvrPa1VgHMnWTpu1Ok/Ckfo5paRRJ5LQppMcy58d/+12iuFmwQ3XYC8YRiqp1BBQUFBYetC10kAu/vXNhuthEYdOHaUU5hS7TQOzUwBo+c4grJrABjaQVU01QakO1l+vlQ0G8zTlBN/km1Aun3rj+lUuC64IYingoKCgoLCDYPLrRrNTJB0dvVT3bxwhuppNM4yfDEHzIapeHb3XR7pzMwALx0V2aNlxhNFEsD23TRpbbZIJoVNB1UTVVBQUFBQ2OrwPJLBUIQ9nLNT7GFs62BfYywJ6BpJaDHPcvyldtqVi8CzTwKnX2SguwfACAClHPDMD4Anv0W1VkFhFSjiqaCgoKCgsNXhuYDVoCu7WQcKGfaGytB4aR5yHYbJZ2d9c816MTnKKUiAP9M8kRKu+CRw4lng4pmFn2nUWZJ3NmgcqcKmgyq1KygoKCgo3AhoNjnD3fNYcm/rZold10lMASqUoTAD9JuN9S/b84ALp1jC7+xd2g6QTHO60shpzlHPZ4DxC0BmmipoJAr0DzM6ygxctV1W2HpQxFNBQUFBQWErw3FY/s7OANlpltOrNaA5BtTbmANar7EMn0iJ0Hjj0kPjZVi9sQJ1CARJaGcmgBPP8f3xFBA0OfLy2BES0v23K/J5E0MRTwUFBQUFhY1Co04yZlskbm2dlx5iPnEBuHCaiqJh0gAUjwG1OrM6G3WWxvu3cdlz03ShJ9PrX4emAfE0YJ1a/nXXAeCRUJ49TvW1Z9B/PRwBrAS3tb2L89cVbkoo4qmgoKCgoHApsC0qeJoORGOX50L3PJKw8yeBcglwbYa+xxPALYeBbbvWuS02MD5CNTMSA4Z2sqw9OQrUxkgAA0Ggbxtjj7IzVDqH91x6/NHQTuD4UU5MirVkNXqeyB4NktCW8svPPA8EOUN+8iK3R2U+35RQxFNBQUFBQWE9sC1gbITEqVYh8Uy1AQM7GE90KdN/JkeB48+SfDkOS9S1Gpc9cga4837g8L1rl6RrFaBa5mhMgIpnzyD7MAeG6W7PzJAYAiSf2/cyy/NSsWMvsOsAy/rNBsmu5/m9ogPDVGzLxZXL8eEISbtjA7oaT3kzQhFPBQUFBQWFtWDbwMnnGcYeiZHouQ6QnaNDfN9hYHDH+pc1epbEtVzkxKJwFGhrB9DOEZjPPkmStv92klPb5tz23By/jyc5GlOS3cXRSIbJPM/2bm7zvttJjpNtl57fWa0AjkW18pU/TXPS6FkSXsMAwjES2YN38v0Xz3F7liPitsVtU2HzNy0U8VRQUFBQuHFgixnn0C6/DL4c5qaodrYLp7hEKMJg9nMngI7u9Y23LOWZpWkGSFoT6YXKZnsXUCkxuqhviPtx/DmOwQQEEbVoItq5n72X5QI/txjVCgnqjr0kjLYNTI/zq1Yh4e3pp0K6WF0t5ICxc8DsNFsBzAAnK93+chLt7AzV2kSan48nuL5ojNsfXzQ60XNJVvccunRjk8INA0U8FRQUFBS2PmSv4+RFkhs5i3xgO9AzwPfkM8D0BImfaVKl6+ojIVsL0+MkS62kUyKRBqbHSCIH1kE8XYcRQzJHczHh03VRgrepfjZqXH4rOfQ8lufPvAj0DgH5OZK9WMJfTr3Gfsy9t3IfrSZV2/EL/r6UCpwP3ztIdVXuXz4DvPg0l5lsAwIJmpRGTvG1Q/fwM4sRjVH5Pf0iiWY8yXPRbHAbU+3Lf07hpoEingoKCgoKmxuFLIlfZgbQQALWPeC7sh0HOPU8S7zhCCN8PI8EKTdLAua5NPJYFkmY63CZ7V3A/jsYM7QaKqWVCaqmkVw11pmLGYoAoRC3b7mSc13EFpkmt79SotLaSlA1jU716XHuy+4DYkRmnu9zhEI5vAfYtpufGT0HjJ2n8cdxSGgDQSAaIGGPxqhGui5w/hTVy+4Bv2RuBvie6XGW2vffvvz+bd/Dz4yNkDjDY3m9s5c9oq3kWOGmgyKeCgoKCgqbFxMXgVMvkCRFYiSUp15gULnsq8xMizJ4JxBsIYehMBW9F5+mgphqJ4GTcF1gdoLLu+Plq/cdhsIsPa8Ez11/72Q8SRI2ep4lc4CKYK3C7S3kgHQbldtqhSpkZ+/yy4rGgVwGuO82oKuX5LxW5Wc6uqlW6kJxnBzlfkyPMWbJagLweMzCESrGQ7uobOZm6VBf3Kep6VR4ZydZvg9Hl26TbgA7bqFzvZAjMQ5HePyVk/2mhyKeCgoKCgpXDtchAcrOkNCEoyRLidSlub1bUSoAZ47x8z2DJESZGZKmUgG4cBa499VUNHV9IemUiCeBs8cY/9M/vPA1XScRzc5w2zu6l35eoneQZMuxSb7sJv8fCJIghiN0dLdCGoJmJ7ntEWHCaeskMZuZAJ7/CclZs+6TwVgcgEaVsFLm9nX1Ld8/qmkAhJEnkfbd7YtRq7DsXipyPfE4SSsgskSzVFZvvYfk3rKWP55Ay+Sj5vLEUyIc4df1gIx0KuX5QBGNAelO1Uu6CaGIp4KCgoLClcFqUjWcuEgCaphU8i6cAYZ3M77ncpSu2Ukqfr2DJJcXz5A4RSIsM2dnOQ3HdujYXg6uS2KVbF/+9UCQ76mWVyeeXX18/cwxwLL9EZSmSfJ1690Ly/VWk9N7JkdJCs0A92f0PPMw9xxkZNL4CHDuOGA5PEbdfVx2bo7Hbtse4IWfMPNz5/6lJL5WFsHxaxEsjccyN8tj1xp3FI4AukYTUTFPYmwY3IflwuytJj9/qe74a4VmAzh9jC0AVgOAxmPZ1gXsPXRpQfkK1xyb5KpRUFBQUNiyOH+K/YPtXQtVskqJU2yiMRpgLhWlvG92mZ2gGaetnUojQMUuEqMKOjNOx/ViaKAathrx9VZ+aR6GCQSDQL3Osr9cLkBytrhv8fwpksqOnoXkrV6jQScWF5FHfSTFp54HXA8IBBhb1BHlhgVMltCnxoTDvWU95QKXsZ5jG0tQrW02l8/YtCwgGBAkPc0yez5HR3wrPI/kdGDYV0w3Eq7Lh56x8yTUYeHsty2OD32pCRy+b31pAwrXBYp4KigoKChcPmoVYGqUJd7FpdlYgkRr/AJNKpeqeuoGFdRGneXoaMwnnQCVQcMg8Ro5udTVDfCzqbaVy/2NOsme55E8A8uXaWcngelJYP9hEsRmncuMxFjiPXeCZftQmHFOU6M0OZkBEsRCjsfCNPm5i2eolAaCPHa5XpqOdFG+13SqnpUyMLyX+zY1zp5Nw+D6Q2Fg98HlY5QWwzTZYzk9we1rLZE3aiSk6S4eb93gOstPc7xmqo3b1GywxB6LU7XdDCjmfJNY6/VnBkjqp8fZ0jC8Z+O2UWEBFPFUUFBQULh8lIskn8upjQCzHUt5kp1LVcg6uklamw0qWK2qlev6cT3xFA0z0+Msy0sTUqXIEvrew9yG3JwwzAjyajVJKD2X8T+WRSVTN0hk9t7ql8+nxhb2kYYj/JzVFAafWZb++4ZIEmtVoVSO0tntOsJt7rA/NJ9hiTwQ5PoMk1+t6qiMVDIMmqh23ELyattAMkVilVqhhWA5DGwXfaoOj4Wuc7sCQaBvkPsuj3FXL3DwLs6Az2e5HYEgFdDtey9tvVcK1+Xxys7wWghHqSQn09w2e4V+VE0nmZ+eVMRzE0ERTwUFBQWFq4CVDEQaS9mLJ+usBx09dKpPjfHfcsyiY5NISjON49BB3dkNlMt8DRqVuT2HGCeUmSa5nB4n0fNcKo+2RTUwkfLJi20xMN62gdtfRsJVKflGGddlJmVmVpTdNRLQvgkST3kschmuLxxdGMXUrJMAxpPc/mQbyXMh6xM6z/NJYTFHo9bug1fmCu8ZIFk1AiS/dpPfJ1LcV8daWFqXfa3FvCjFC3X2ejrTbZvnbXxEkHCT/x85zR7YtfokDIP7pbBpoIingoKCgsLlIxoHQlGqnsspmtUSEEut7n5eCaEwMzY1jX2c0+NUUDWdZG1gB4lIbo7E7M5XiNnlFXK/RNonfD0DLBlnZkgiZXTS2eNUN1uVRjPAcZMz4ySIgztYjq9WSFgnRjgD3TSBYASAy+WeeYnKb3sXy/UXznA9i/M/m00aXwyTSrDV4PZXSiSZsQSVPSPA90ajJM9XSvjSHSRr505yf5NtvjLsujQ8LXbF6wY/t1G4eIaqa1sn1UuJapnnTirtrrv88WnU+ACjsGmgiKeCgoKCwuUjluDIxQunaQRqDTmvVUmc9m67/FibRAq4434qgS8+RXWzsxdIdZAEZmeEwaafqpgsa6fauC2tpC8cZblZ4sxLoIFnGee2rnN/JPHsGQSOH2V/59w091t+rlEnMYolgLMvAW2v5jY+/5OlpK1RpwI3sJuB84k0572HI1RtZ0RPousAXQNczo49LH1fKXQd2LWfDwgTF0k4AaCtA+jf7k94uhxYTaEeB5Y/npeDRp2tFrHkQtIJcB8aNZL1aIIKdGtGK8CHEN3g9bkZ4DoUaG/yiCdFPBUUFBQUrgw791Ghmx6jGmkGhGJnADtvEeXnK4Bpst+yrZPThwo5EkJdo2rX2cMA+ekJkjrPowKWagNuOQxs27W8uch1FpqVFkM3WOoFSF6mx4AXniahgedXeT2XxLSnn9uQmQaGdlBpKxdYWpdGKSMA9AzRvDQ7AezcSzI9PkIVr3uAjvHOPhLBdMdSolKtcP+zM/x3WxeJ6WoTgRbnrHZ0U/2Mp0Sc0mWqqZUSo56mx3msgkGavfq3XZ7K3Yqy6NHtWiEqK5bk8d25D7h4lucnmuC+VMtUvbfvXUpIrzeKefb6zk4B8PgQ1TPI6/ZyM263MBTxVFBQUFC4MoTCNKL0DrE3slkHInFmUqY7rk5PYKNOtbF/mIQuGqMiGU8BR5+kq9yxfYOQB7rNKyWqpss5v6NxoUK5yxPQRs2PKgpHue4f/ANQylFhA6judQ8IEqGTSDQbJEV7bwXGzvE95RLg2kAkynGZpTxbFJLtbB/o20bjkDT4rHTMMjPMBy3l/Z7U6XFgNMlJTsspo3JG++RFES1lUJ0MRzl9SI7UvFSUCsxRzWfYrxqOct9PvkCj1cE7rzDGSDD7FduHxQsdPXwomRoH5oRZrLuf566rd2OnJc1OAsef9VtRNJ3ZrtPjNIvtuOWmI5+KeCooKCgoXD6spj8XvKf/6pc1XZcxR6NnSSLnw8E7OZ+8mKMKWqtS8YunSDxqFaBYYDk9lgRe+0+XBp539pAw5bNLpw5VSiSMcn/KJRpakmlfJdQ0wNCBao0GqG3C7GIYfG1gO9XPYs7v5axWqIraFnDbvSSdALctvopiCXAZJ5/jvvUM+oTF8+iqP/kcDVWLe23PHmfOZXu3n4sKUC08fQwIxy79vHke80gLWSqzkriHI9yPmQng4jngllsvbbmtiMZJ1CtlnqfFqJT8LFcZF7VrP+Znw280oWvUgVMv8lz3DPo/jye57edPcptXG1xwA0IRTwUFBQWFS0elRAVtaoyTg4IBUWIdvrpjEkfPUkELR2n40XWS3dwccOwZks1ChiX3UJivZaaFEcijy/3oD0ks9x1eOF0oHKXr/fhzokwrFKlahevZuZ8kMjvLUni5wElCo2f5XqmkmQESsOwsw9/TgsR293H7Tr3I5USiYqZ7gGS4WqFCvNIc9sWYE5OFegYWkipNY8/r+RPAj75NchyJUe0LR/38z1bSCZBA12sslXf3XRpRKxdFxmf7UrVYN/yIq+Hdl389RMTggXPHeW5be0cbNW77rv0LHyg2yzQlgNdhqbB81FgswR7bmQlFPBUUFBQUFOYhewMrJRKTWIJq0vGjLLHGkkA4zBLrqRdolDl05/L9fa5LkpjLcBntnSQoq4W7XzzHZbWOPQwESdamx7kNzSbJjeuQDFXLJC1SeXQcEmTPBQ6/bKHhqGeA/54aJ1HwXDEhKE4yef4kyezYOZa2B3eQvBaz3PdAkH2b1TJ7Nm9/uU9umw2ue++tgOfQTGQaQDxNVXBums73UISEaa2ydDFH0rqY6NUqHOV54QyJ7+AOtiKMnacCWi0BsV72dxay3KZonKQxlmDPbKN2aT2ZzTr3b7FSLBGO8Nw06lf2ILJjL7etdfSo1QA0A9i+hw86mxXVCrd5pVJ/KMLzcZNBEU8FBQUFheVRLnGUY2aGpA6gmlUpkSgNbG8psUZJxGYnWBrfc2jhsmYn2Yt58SxQr/gxPbsPAgfuXFhmdl2qWTMTVIWWc1trGkuWU2MAPMBxSVCq5YVqpGOT0HX0kBRnppeSlXQHv1yHfaSVIvDCUyQOqTaSudkJ30jTM0gCVMyTPDaF+tY9QHWrUWcP6MwkyfHw7qVOb6vB5V08Q9UzFGUO6eCO1eOLFueh1qrAi0+LgHuDc+ytBlBo8hjkMyQ34xe4X6GIP21pbprEMZG89JxVw/R7RVuTDCRs2w/FvxIEgozU6hmgOadRJ6nu6uO2b2T/5lowDKyaM+q6m0uhvU64+fZYQUFB4UaA4/g3/WsRz9JsACeeJVFr7/aJUyFHo0pXL8lKq1hpiBLr1Dj7HaWyODsJPPF1luYTSSA9REKYzwHPPknCePerSF6nx5mTWcyz93JuiiXi9DIkwxB9kck29jh6nq8weR57IqFR2QuHgWqAZGsllUw3AM0jOa6WWdqXamyyjWTKalLtHNwFWCeoJpohICKmDH3n7wDozN6sFElU7SYnKskSvNUELpxlab5VRR6/IEw5dy1ffk13UgGWmZWeSyU2My1C4C3ua7KN529umsrkxbPMG00kAbtIYtrWRdIzdg7Yd/vSuKK1kEiTlBdzy7vGizmSxdhVmOdumiT0K03H2qxItQO6yXOxuM3BEw9Ku/ZvzLZtIBTxVFBQUNhKqAsjy+RFEpiA6K3sG7ry+JpWzE2T0HT2LSS20nUtzTvpRaMTw6J8KGeJOw57NDPTdJbLcrJhAl09LLuPnBKzvzVOqdF1qqcJh8Tt/Cmgr8Z9bC0zN2pUBzt7qFDmMoJsgsTTMKmK9g2JsZSCHK6GalkQuUXz3dMdVA81nUrw2Dn2OXb08FiEY3zP+ZMkhnsPAantfG+1SsKoGySF2RkS+HCExygSFz2gMZL0cyeYrVmrilgqsR8d3VzH3BT3uVqhsmqI2KdQ2DcWBYJAOc/1e6CTPhrnPjVqVLHbOnh+dP3SlUPDYEzVS8+w31bOkLctnn/ZlrDRBp+NRLqdpq3xC7z25YOYbfFBKd1xdfJZtxgU8VRQUFDYKqhVgGNHgbkJkpVgiOTzxPMkigfvYhnyaiAzLUqli9RU3eDPXAeoLEM8bYuvy8lAhSxNJoaxlBhrOre3WibhNESfo3QwB0NUHQsZlq0Tab9/0rZIMnftZ3ZjNsPjU6tSvZMB8N19vnrYqPsjKW2biqTncZ2tpMC2gcSi0ngyTQVvaoykoZTn/pSL/HzfIPsQ5Zz47Byws5PkIjPDKKW5aZK/7ByVatti3mXrMW7r5PH6yXf5kGEJ4pnuINHbfzvjeWYmWS4vFYFGk9vX2euXvZsN9r56Hk1N8aTIthQks1IAoAHbdvLftn3pZd/eQS7/3HFg5CSJMDyS4oOHro5pplr2TVWGwePT0X31QuqvJXQDuOU2ku/ZSRJ0DX4qw97brjBuamtCEU8FBQWFrYILZ5lT2DXgkxVJ1GYmgAun2A93NSAJ5GJEYiRPmWmqZYshXddSebOaJDW6sbz6ZQYAaCRjieTCsq2uk9BZomw8PUbCUa/yq3vAj6WxGlTdCjmgVmapv6efP9MNln7Dotdz7Dy/ykWfmPVtI7ELBP0A/EjrLVLjfpkB7lO9xhJ5Wwcd5XaTxDeR4nGpVbhNvYNcVnaO5CMSJZE2RPzUYnOObVPlrVaoGCbTPBfZWe7Dwbs4GjQzQ2W0WgKSTW53K7GXxibPY6h73xC3uVqh6hsKcVvau3icL1eZTLVx+ZrGayMQoMJ64QzJ/JVMQ5qeoGGtUgTMIB92Lp7hOdx3+9rxU5sBoTBw6G6eu2KeJfZoXIxMvTknGCniqaCgoLAVUK9ynGIivbwKmWwDpieB4T3Lz0y/VCTb2G+5GIbhO8pti+TGMETPZoYl1qGdJCLlonCeZ0UvZIA9f63lctsSPYsaTTyLEU8xZFvXgXqd5Ckc4c8qIlsznqRyOLCdROf0Md7ou3pYaq5VqH7uPUTCfOYYtzPdwW2plhl5VC0LQpNkKb17kORsnpQJh/zugzwfrVmapYboMdUBOJg3lYQinJ6TSLN3VTf4fbqDLRKLz+XsFFCrAXv7fTUsKI55Zpok+65XkUgm0iTBpSJV8GbdD5X3PJbU5YOJ5/H/Uk2u10iCqhU6x12HarG5jDK9ElyHk5wunBYENMzlmwG2AzzzQ+DQXST1l6qmFvPMJXWchcfZcfjwdfI5JhRsBXOOJvqMU+1rv/cmwBY4YwoKCgoKqNdYKl5p/J8s+9ZrV4d4dvXRnV7Kk+C0Qtfp1E6kRQSRx58l2zgis72LiuLZ4wz/1jWWhWtVvtbRQ8LguSSP4QhJY6mw/LZIV3pnD0vNZpCq5rkTJDyt5cqufrYhnD8BVCpAR5TbKtXKI99j/2jreMmECIQ/d4Ll0EqJ6uT4Ba63fxuJayFH4rxzP4mqnEYDUHEMCDW0URfqX8h/LZZgrNJdr6IaOHJyaV+l1eRoxVSbyHks8ct1uP6oiD4qZHkc4wmS19pxXheFHMkzNKqq0PggEgpTMU2kfaLWqPF4mCa///G3WZo3Te7z4PalRMnz+KAgy/UvPA0c/QHV23IJgMftDIb4vsw0kJ8Fduyjets/vP5e0plxPyi/FYYhEgpmeK5uwh7JrQ5FPBUUFBS2AgzDVxaXK9E5Nm/qV6t8l0yzf/L0iyQB0ThFvGqZZdp7HiARzGf8Gd2pDhKXuSmWSM0gSVs8QdIyK+KFHNs3yVgNkqdSkeagSIwEFiAxdT2uY3yEZKYhytdWk4RpuRzJaJxEMxzjdgLskxw7R9U0vcxnrCa3LTfHoPl4igrl7BSJ3tAOYGgX1dx0B3924TRJlhkQWaNt7PMMBIGOroWRTuUisOcAFdSBYSA7zYimdAeVQsdm+dxukoRPXKRxyLExPwM0HCWZtZr+du/ax4zQiVEe41qFrw/vodpqGP7+5jNcTlMcu227abiaGiMZjyd5jMfOkageuovH13XZyjE5yv3QNZ6X8ye43PZODhFwHGB2DCiVfBe/C6rDLz1DQr5z3/rK+nPTKyuvZoDbVC4o4rkFoYingoKCwlZALEkFKpch4VuMUl7M/U4tfe1yMbSTytvUqDBGaOyD7Bvysya7+hZ+xvNIUBwHaE/zZ8k2KpWxOAnS3LSvhHb1A/3b+X2jxtnf/dv9aUBzwkTT2UsSNTcJjJ8X4fCL1DPXpRKWneVXo0bCmmzjMbObfM9ieB7JdaUMNKrACz+hOhsIUj31HJLYg3f5ZHLnPvZRjl8QiqTocwwE+b1ukKQ3GyRevQMkrgAV1oN3AedO0qhkzXFf4gke83KR+5xI+iYaz+XP8lmhasInoLccBjp6gamLJICpNDC4k6+/9AyPRTzFZUnH+a138+Hi4nnGFMkHlmCI5H9uCjh7Arj9Pm7nyCnueyRGcnryeR4v1wGccZb5G3VuW1AMFAhHSWzTHXzv6FmavRYr6MvCu7kd8TcwFPFUUFBQ2ArQdZKSQpYkMCVMM67DfjjXpUP5ahsW2rv45TjCkbvG8uU4y9ZSNkCyceAull3PvERCMrB9ofoYTwHP/5hkKRLxw9yDERKaM8f5cw/cZwDoGybR81xfoQR4nDzx/3KBJLQpzDVdvQtd0dUy2wIyMyQ7wRBfdz2WzyMR9o3u2kclEeDxCIUBCEW2XvMJdioNFPI8FpEYleOegYVZjql24PB9fGCQkUnJNuDFI8ATf8c4J8cBTJekVNP9yT0TQnnMZ3n+rQZgCcUbHvtbmw0e68MvE0qzmA+/cx+JZiIFPPVdkt3F14ymifioOfbQXjzN8xcRCmS5wGNesPgQ0dXD12oVbk+zRkIdMEVmqsgqncr7Jf+10N7NflapfrfCsQVRX2Z+u8KmhyKeCgoKClsF3f10rZ8/QYIlBaF4ksaZK3EQr4X1EtrVJuBomj9VSIbCWw32JhZzJGq1Gknf9luo8MVTgGMxbN62gHQbp/zoGnsljz9DciUn8cTEKEqrSXU2FAYys3RDt3fx+5GTwJ5buU3NOvDSUWBSjNQ0DJL4WoWtAlUHqIYAMw/88HESSmn0sm2uzwwAbpmKY3aaPaXbb+FIx1B4KVm3moBlkdS29lGWS1xuIc+vUJh9nfEEAE0E9CeBl54Ghnbz+7lpuuCDIZqYuge4fRfOkAwfupv9lYM7Fm5DpcSS+0oB74Egie/ERRL4SEvZ23Wpbuoa96HZ4HZ6YHlfA1sn2rsXTmHSDb53PegZ4LoL2YXHyHX9TNi2rvUtS2FTQRFPBQUFha2EviGWjbNzLB2bAfbhLZ6MslEIhqhSzU0tb3Iq50k0O7oZj5SdIanUNfZv5jPsEy0VhIlFA4plKry1MhXLSJz9pKkcFbSLZ0m2rKZQAufYdwiNhNKyAEs6vj3g5ItUInsG+dmpUa7HCHHSjN0k6XIbJFaVIkdyvvA0ybPnsecx2UbiZ5oilsggUcrnWJrWNOY4SlTLJIlTY/7Uqd5Bf5LSsSNUizu6ACPIfSnmqIpKx/7YeW5jZw/3t1piu4PnsGc0mWaJu9GgelrIcfmdPSSBslVATryyLN8J3woZtF+v8FjVq2L8plBTc6L/NJHisauWuU9W058SmWxji4iENEmtB6l2HrvTL/J4BUP8vG3z3N5y29ZwtCssgTprCgoKClsNgSAzIDcjNI3keHaSqposuXsuCd75UySfjSpJRbPB9wQCJJVWk+/NzALJFJdhGMI4FaCKJ5FKk4TFkySwAMlIso1q2PQEf5ZIAhVQjevqAc6foZpWq3ECVCBI4lgoAHbDL2vXq4AdoLoXMKmOzk2TwHX3s9SdnaG6KWeSx5L8XCjCXteBYZaWyyVBLGf5nkic+37mJe5rJMbX+rfx81GREerYPC7BIIldtcQeWMMk+bMsv683N0dy6EwDczMkzCOn2WZw8Qx7THcf4PEMhdlycPGMP9GoFcU8SawHblchy2MfDPFcNBvcp0SS2xMIArkZIDNHAt7Vu1BNrZZ5TNovQaXsGyKxnZ0kAdcNPrB09PiB/wpbDop4KigoKNwIaNRF36NHUrOR4drd/exrHDlF1S4YokI4MULyGEtQiSwVuL1W0ycTtSrVRsfisupVGnsAElJZtm7WSXaS7SwxxxNUgaNxTtIpl0jUZB+gB6qCczNUzqoVLisogtRNEQlUqwtiZbFk3GxS0YunWeadneTyegb8hIFK0Z8YFQgAFYsEuFomOU2k6YDPzbEULlXHUFgcC9Gz2b+N25tIUVlMtQmzUliM2cxye+JJEkXbXkgYzQDVQXgkt4EACWp3P5XhI98n+e/fRrPWwA4/2D7dwWPh2LyOHJvHtVyk2Sokc0/F+roHgPppltSbDR73VCd7TWWskhyhWS7y+ty1/9LNb63Zowo3BBTxVFBQUNjKsG2qVuMXWIr2PCpLPf00l4Qj13+bNI0B7+1dHO2YmxWTgGIkR4EgZ5dbDUH4CiSb8ThHS4Zjvvs8FKHKFwjwPTGhFFbKdEhLF/mgIFHhCIlkZoSkyxHmm3oFmCiRXAaDAFz+37J8006qTSiGLRFG8Fj2NnRRnjZJWpvCIR8I+mHsmi5MWLqY1KQLkltmT26qbWmOpS7c7OMjYha9xhaARp3qYcAkcZud4mvhMEm8bTPs3XNFcL3GfamVqfYGgtzOcJTl+dlpIDPF/tZkmsd470GSy4xIArCFQSmRoomqd5AKtaaJaCvHV3bDES5DF0TUc3lu+u/hbPrpUS4vl6Equms/1V/lVL/poYingoKCwlaF57FUO3KKyllXHwCtxVxSZxbj9Zhr7Xk+YTNN3xmd7mA+5tmXaNZJt7ME7rkkk7oBNB3h7q7789obdXK/nfuBl46wxB0K8z1Wk4SqKXpc053MFu3uJdGNp0Tgfo3csSZC1TWI/tA2HqNKBYhGADPEvtCmUDthMC/Tsehs10AlNN0m8kxd4bYPcdmtE5eqZW6ba3P9gRD3xaqzdWD+eLliYpMhemFdHoNqicpoowG4FjAzTeIcTwDb9ogZ66CRSWaA1qs8NnaDKmM4QqXRc/n/3AyvBc/j+lIdPIYvPE0ifs8DfFBoNHjuUm3+zHfXYc5qs8EHBE88EBgB9p1WRYj+3lu57FqF+3XPA8wJNU1/mpGCAhTxVFBQUNi6KOZYvk63LwzbjsT88vbcIJW0awUZDD85yhKtrrFs3jvoO5qtBlAsUGlr1Nm3GYmSoDQbJDeuCIv3bJanPY8KWlc/0DPEvtB0J8lhswnUMlRSU53Ad/6OZMkw+LnMDIlVpUgy5HlchwahiIqyeDJFNVE6z12Pr5UL/Lym+YqxrpHEyvGTgSDbAppNIBngZ8tZLi8SAV6c4XJHzrCvVDepAMKiCpifozoaCJAoGyZw7GnmcJoBlu498PgEwyR/O2/hNKl8hs7+Qo7bNzVOot3WTmW2UqZBKt0uJh953NaoUIsDQe6HrtMEdu4EcNcrgZTBczh2nq76QIDkORRigH65xOOvaSTwwSAffBo1Os3ltbdzH4ns9XjgUdhyUMRTQUFBYaMh1TldZ2/eescK5uZ89W8xDJNf0+PXhnhaTRK8kVN0akfj7GX0XKqtU+PA/sPshTQCvtO5XiOJMwN+rJBuAgbEZCYLaFgkUI5DwnjPq0ikj3wfKFSFgmaSVE2MACeeJQHrGeCxKGTYx+gOUinVNBImTyMJLuW4re3dJLyaTqUuFqebeuwcf55KkxSWS1QjTVOEygtH/Mgpble1wt5J2+KkHsPk5waGua6JEe7X3JRQSyskc2aASuTIab+3NRTmeupVrtNySBylC35oB49TZoZB+mZQ5I6KZVVLQJvH+euBoFBP6yLQvsLjKqvdEeF+z8wwmD87y2D4mUlxvMS+mCbNTokUgFbV1iPh3/Eyf5RrPLFwhKmCwiIo4qmgoKCwUagLt/HUGAmAoZP4DO2kIWQtWM2l03taERCO7KuNqVFOtZkeA8ZGSJYSQrXr7CXpys3RtZ5qpxM5laJCawT8QHTXJcl2BcF0pFlGAyIJKpzBMMlj3xCXNbiTROnsS0BROK110Qdpmn45ORRlj2m1xJ5D2yLJhejL7Oj2zUVd/SSxgaDY/iQVvECQ2yl7MzVdzGtPssS+bRdJsecBZ04AY2e5jW2d/rSe2Sk/YL4uAta37WZrhOP4MUS2zVaBUJRKbb3OzzsOEA4x3/PsS1znwA6+JxylsrzjFiql0xeBc6eoPgeDfBioVXncG3XhgI/zoSAhnPW6zraAMy+xz7RU4Oc6e3gecrPch+d/DNz+cj+lwHFoeEqm6ZaPXibZdF0A3tqDCRRuGCjiqaCgoLARaNTZuyh7Ets7eTPPZehe3n/H2kplOEoiI80li9FsLD9e80owMwn85LssyebmSMDCos9wfMSPvJG9nJlp9gIeugf4weMkX406t03TQIlQEI+AmMFtmlTlctOM/7HqnCwUCFIZvnDaV4g9TaikdRJSWbZvNkg6IaJ/alX+XzdYSp+dFlmf8COgQhGSQsfmvsxO+dsDkMj2DdHRnWrnsZWO63oNiITZZmCYJMunnieRq9cZH6XrJNLjI9yecIQKaDTJ7bIsoK+TimajIXpVhUHIc2kgy2d4bOZmxDELkmhOXuQ58TyqumMXSAZlmH44wnimeJIkNzsHBIrcH8fmea3XqFa25q929PAYVEt+CL+UTFPtwL7bLo90lot84JoR/b7JNpLojp71K/4KWxKKeCooKChsBKZGebPvapmTbYhg8HyG04k6ulcP3G7rEj2JRVEGbUFTKJ3rUU7XC8dhuXv0nE9gdBH2rptANMqSbbqd5KFe49jDWpVK2d5DjDoq5Lh90nAixS7DBAIGFUa7CZTLJJjxJNXTcIS9ovUKCVwhh3kF07JEP2SI3+fmWDo2DBLLeFK422uCeM2SNMdSJFZ7buVxL+ZIgoZ28thOjTGYPRQFDt7JueiL4308j9sZiQknvQ2cOEryp2s0GLkuR0nKqU3ROB3lhSzgTZI824JAy77TcASYtUhcQ0Fu/0SWP7ea5H/nT4rjKMxcZoDno1kXKQImGK8UJ5HVdSAo3PDlAuANCFNQjdsYWaZtQ5qDUh18EJCGqPauy+vjzM5yLGq56E+ymhqjgr5D9Icq8nnDQhFPBQUFhesN16FKFY4uP4oymabalptbfQxmPEHycvoFEo14kuXgqiBs23aTvF4tTI1SbUykSXQrZTA3NEZCV62ylC4n7oydo1JWKZPklItcTjTO/kW7yfdHxWScQEgYo4IkYrrYl9wclVPbohJoWYCp898hkT0peyDrNb5u237up6GTrIWiYv65iHCql3msD94BDO/l/p1+kWXtZoNkqFLi/vYO8pzU65zH3hqErmlUSwtZ/nt6nOpkMCBGSQrHfyAAaAaXWauQXAYC3L5QhL2pUg2WJe2wyDa1hAIaS/A46jpbESpFP5xdEvmA6Pu0G+x1LRaoGufneAxkTFRAhNL3DPC8wlu+dUMG6hsGTU5mgP2qx5/lfqXamaiw+OFnOVhN4NQLPE89g75SH0/xmMj57F29l3JlKmwhKOKpoKCgcL1h2746txx0A/PB6mth2y6SqvHzLLW6Qt3atR/o23Z1e+dmJklUZGk1Fifp8VySqEqRauTsJMliOMrtsx2SuaogW4fuJoF55gc+wQyFSToDIZJQDyRZMxNcZ2cfCVtjCoAL5PJ+T6jMn2w2BMEzOeJS06n4OS7Jb9Rl9mQ0JkLru4HeYb5vdoIE6vaX0+xz9Ic8dntvpZIYiQnH/DRw8jngzlcunJ7TO8j9dmxus9UkgQL4s2AQgBi3WalR3Zse488cW4TUJ0m+ZOuE6/iTmWzbzzKVwfMAEIxQGTYsf1sci9s8NyOc+lGq0FaDxNYw2d9p6Mw/3b6X5X9XuP9brxmryf1q1LhdP3ycRFjXRI6nTqI9eg7Yc4hEdzVkZ6lUd/YubQ+R6v30mCKeNzAU8VRQUFC43jCEO7rZWP511yXxWk/2oaZRserqE6QFJKJXc461bVPNm7zIbSsXWQ6PJoBwQWRXxkjwbFvM8XaAvn5uy9kT3K7eQS6nViGhK+XZu6kZgOaJGCWQEHX2sZRcLVMhDQaBXI1mF8cRDnLxf4hjJQPOgyI70xNWekOQu2SbGO9o0lluNYDJEa47FOZXzyAJdd8QybGE1SQhDoaEC3yKvasS3f387PQYiZUpSu6uR/NOIsVzNTvlm4zmpriN2VmS390HWO7PzvL1ZoNqa3efr7zWqiy7azowel442oP+qNFmg2RVN6g2S6Kqt5OMhqNs55Al+aFddKT3DbMftFz0CXOzQWVepgB09PDf+TmgdxvbRCT5LmSpZMpkgJVQq4Kh/Cs8EIVFTJQ0ninccFDEU0FBQeF6wzBIbE48S0KyWJUs5VlGb+tc/zJ13VfBrhaqZap/LzxFB3khR9WymGOptLOHhDczw/eW8oDexnL40A7GCVUrJJqyDBuOkvB4LolWucjXm2IfdIP7bjdJYNs6hZoqjELhKMmL1yTRNXQALrdHA4+tYfIzhuhvdF3+PBDidjgOkLtA0tfWSeJmisinC6e5LLm9rkNFT8YSAfx/OEqyKXscA0HgwB1U7c6eIOGUpDmW5rYUczw2tg0ENZJM2RLQrNG1bgQwT8yGdpLEzU0JwloFoAE9B9gikJnhdtlNHp+pMW5HWyeJoKaz3B+JkrzqhsgZjZJsRuMkk6bJ6KtChu72WoWq8Ow0z1WqjQQ1nmAYfd82/ryVfKfahYo7vjrx1DX/gWA5uA4fDNSEoxsWingqKCgoXAnqNX/046XkF/YOkUzMTFBhioj+w2KeN9/dty8s5V4qrlQxKuQ4o/v484Bd56xyyyaR1HRud6NG8pVMcZu7+2gMyc5y20sFQaxa4nIkofA8KnDdA8DZY1TckqJvtJDhrPRImPPVDYNmIidLldVqAnqcRMzQAWiAXaHDPRKjyqrpwvTTADTR1ykJTylHAmZZVFBHTlJ1jUSARBtbBto6eG5lb2o0RgIG8LxNXGTm5f47fPUuFKbLu1Zm4L3jiHOao/op45EAjrvUNB6XfJ4qaL1K0uaB3xdyYl8N4fLPsuezXKCRq6OH7Q/lEsmjnISUnWXPb1LEQOmyH1YQ8vEL3IaDd5HAAlzv/T9NMvrSESqb1QrXsesAz2121lfiIzES5+4+f3JTJMYkg4HtfM9y12+yzVekF7/ueSS9QzsV8byBoYingoKCwuWgXAJGz7L/zbaoaHX18qaZSK/9+XCEN/6Rk8DMFMmEbviO6t7BS9+mepWK0/S4yGxMcjldvZfW6+k6wOljzHvUNaB7kOQlHKW6ls/S4dysUdULhKiGxcRUn1KBZVpDKFeNmk+EG3WSODMgSJEmcjjzwNyEmJseBNo7uIyxEeGFmRZxQY7fguDYJHKGTqXQsf2w9HQH/201AIi2BsOgKnvxHJVCAIjFRIB8marujNiG6THOKfc89kf29ItAew+AxuM6eZHl9dZ+RNfxXeb5jE8+g0EuV47t7OwhKa6LmKVEG0lmZw+P44nnuC3bdlHFjCW5P+2dvO7kOa5XqRAm0jw/lsV9dFwaoHYd4M/zGVHmBknqwHb2dkqC5zgkpI06jVadZeDiaaroC/o+BXkPBgV5b/L8NxvcXplLahh8KBnYvtB0lGpna8joOaFmR/xzmZ0lEV7NUKew5aGIp4KCgsKlolwEXnyaBCyRotJjNUkI8hlmVkolaTVEY8CBO4HtZRGErpNArNT/ttY2HXuGCl44StI3O0mCMrSTPZXrXW4+y+VoIEnRxRQheOzrsy06ps2AUBR19hOWS8DgdhpHamXuS7kowtkzPFZWE0gNkXDOTZHcuRZQc0mWXEEmJ8rCrFQVBBai3O7RUOPaNNFoBpBsB6IiQknTfOd4exfPw/QEYIOEzHWoqmlgHFUgILYv4Ctu0qVuNUmYZ6dE3mqcJDmRIsEKhrgPrcTzyA+AZ75PNS8YFiVvzSd9kSiJfDRGQ49t+e0W9RowMcr3WA1uj2kAuw+K8ZaTwNmTJODBIPezZ4D7WMwDcEnYgwEur7OXxM8wqVw2G9zv/Bxfa1XEx84zwivdyYeiSokPQ4EwjWGOxf1pTQzQdG5Ds85pVRMXaFaKxfm+kVMMmT94l19+1zSakADRwiBySTWNDzN7D139lhGFTQVFPBUUFBQuFRfOkGD2DPjxM3KU4uwEI2Fuu3f95cJo3A/t9jySiGKO30eiJAOrmYVclwplfo6la0koEikqWBfPkpy0mmFWXJbDXsFchqTPapI8VMp+r2Q0zv1u1EnADEE+YimqVrpJBbKY91XO88cBIyiC5cdJUjLTfN0IAuk2oCT7PRsANBLoeo2l8ZAwTNk2y9K6TvXRgD/1KNUmHPYhP0i9XCTJHdjOz2fnhHIKfsYThijTEKV44SZvNc1AByDGVibTPA5j57m+VmV69BzwzA9J9LbtEuM3R4RRqMb9isaE8pqjEuwINbFW4fLrFRJaTSfZmxwF+ofZitDeTRIdSwKVAteTTHMbG1Wg0SQJH9whzpcjFOY41xmJCge9uTCv02ryfMg2BYDbGU34535uhmprucjjl0ixvzccYdvB9Di3r3+YBDUY5npnJ4BzJ4HbX+b/PgRDfOAa3OG3lkRifFBYj6FOYUtDEU8FBYWbA406VTxZAm7rXDihZb2oVqiAJduWZh5qGm/82dnlQ93XgtUEzhwDJsdEiRh+XuPeQyubNoo5kri2rqV9nYbodRw9L+KVVun7LGRpLhk5zQzOcgnIz5JEJNMsEbsuSWmz4Ye75x2qiU0RIRSOUCkLREg6MrPcH+nkb9RJgAyDBKdcokLWEKHn1TIVt3CYxBCar7jalohJEqHx8ET8koggkm57xxJtAGGqtNUSMCUImm0DcHmeTNH3KNVWHnReI9IIEzR9E1EyTRLcqAHTNSrJgBib+RIJuCT4rstxl/G0cNCPsk/T9QQxbnKdxRyPS0RkjQaDfpuCbpBsptpJTg2TiqAOHtfZSZ84WzYNStI4FIkufPiRDvp0B68VCXm80x3+zzSdBD47K5TXAM91KMIHmVqFv0PTY6IkH6eZrFEnmZQtBal2/t4V836PLCDOVfvqRqTVUG2pEsRTVzfFQeGaQp0pBQWFGx9TY4ztKRd5Q3RdEpyhncD2PZfW/2g1SBgSyeVfD4VI4NaTwdkKzwNOvcibelsHEBbEwBYGmJeOAofvW54sVyuij7AlF7RWpVpVyJIkTVyg2rjjluVNH+WSP00mluB6a8IM06gLo5DD/XZdEl3DIMmrZKmKNWpUgjv7+Fq9yvdGo4CRJCEqF4TRJcxy78wEyUNmmufGMXnsJPE2TL/UbphAU6iPDbFsaCRJ8aQIpDdIfPWE6HMUyQDTBUHswiTIliX6L23Rpxjkz13hKA+IMHrphg8GuT7H4fJLDSqMjhhZWi3zPAVDwuFf4L4W8lxXMEKCqHl+z6dhiHGUFRF0HxTh72E/nzSR5nsKOTGFCT4BLWS4b8k03281xbGp8/z3DpLw2bZoMajSwLX30NpEzbH5/rZOkuJS3m8b6O7ltRAR0UyVEq+Zi2dFyR/CgBQlmQ0E/UlaV4pqBbhwCpgW2aK6IebF72RShDIlbXoo4qmgoHBjIzPNCSsAS4O6UAArJZandYPkc70wArxpW8JQtBiWJabRXOKf12KO6lF7i+EC4A28s5dGn5kJGkIWQ29ximuamKt9ljfpSJTqYLNORa5SYs9dOLJwGVOjJDcd3cC5E2JeuuaPmrQt/n96glNwbFs4zS1hCDJZvq5VWV7WNZKRhJhIEw0D8ARRFf2gnb0kaVaTRM1xAC1LkqRBlJyF6ue6VD9dl+RNM/zeQNti6TkQ5vSkQIhtB9BItEdO8fuQmAIkZ8S7Yt8doXR6rjiGpsgFrfB8a0KdNIN8vV7je4NB9pUe+T6J2eQYyVkhTxOUbpAslosAijxWbd28NmwxP90Q15Im9i8S5ToMEX4fCJBIjp7ldTEzAbT3tCzf9FsgHJsKcjDC3tPBHWJyUZ4GpKGdbA9Z3EMZjfNnlZKvQFbKPDedvSz/hyI8H80aj4nr8prpEg8Zx47wuARD/B2Tam69JpTXq5DJWa/x4WhOVBxSaV4zpTyd+I7NfVTY1FDEU0FB4caF55EE2RZvkBKSULkOJ/70Da0/uigmZlRPjy8lbwCJR0fXpZfZC1kqS+3LjLjUdN68p8aXJ57Jdr4ucyOnxnmTTndwXwtZKlOJFDMmAaqn8+5wkVUZTZAAVss0zJSFmQcgia2WqHQ5NklRo8YSbzDMY9xsiJK1y8+5DgmIbXPUZLPBxUlCMnpOzF4vCxLoidddEldLLs8RBifXL42HI3ShN5p8r+uSjIZCQkkUJfipMSAzxWVUyyR/roP5Xk7dxPxEIc0AIPo7Gw1/P3WDaqjnAm6MP4v1ALNjJOIR4dLXNL9vNRoX04dED2lVqMedAWFcMkjybZsmo2oVCFs8xgDL8+l2P1A+EiXZclwSrVqV17BuUJmu274i67lcfzIN3HqPODYaiWVWlOcDQa4/HOX3/cPA8aPctnBEHCMIpVQkBcAl6ZUPXpUC+zvPHWcLwUDLpCzXpTnMccQxEEatQlYMGLC57o4efxLWWpgaI+ns7vfXY+psGyjm2CLS3X9lMWQK1xyKeCooKNy4qFd5k4uvQALjKTqFi/n1j+jTNBpHCiJ6J91Blcdq8meBEDC859IzNCU5WAmGQcImVc1WRGOM9Tl7jOqiLJfD8/sni3nfMJSb4ft2H2CeqOuIGCCTpEb2UMaSVN6qZaEUGszWbIiZ7FK5NMSIS9fjOj1BPGvCUCNjogKC6DbqgC0Cz6XaKImlpmE+9L1aYX+rI5zU88ciIBRJ+X5BHGVrADSqfsUc1c5mwyfDmsbz5XpcH+C3X5gB39hTLfo9pFaT+2fDn8eugdu0fQ8fRDxPtF9o/j7HhYvfEqV9Q+f/27uB/oNCMbZJlk6+SNe87HvsGfB7aQMBYGAH16NpfHiYOkrilkiKZwONRLOzl6RTtjAA3Iezx2mIqtd8QgzRE5tsI2Hv7mffaCHLc1QpihGsMZ7/VLuvXErFNhLhw0MkwmWHIkJ1L/IhpiHU4SM/4O+KNFHpBq+5aJzXYf/wGr8fDhXWSGz51phEivucm104cUph00ERTwUFhRsXUn1bKUZIOqM9d/nXV0JbJ+eNj5ykS9qxWfJMt1OR7Oi59G0NR+CrcMtsb73Gnr3FpFOqlYUsSeDMSRKujl4SFl3nMsslEiurSff40Sc54vCenwL2HaaiVixw+Z5HUhQwgGyGZXpHlNbrVZHLWfHVS0v3P6fr4niKn2kiiqleBhDz+zXR0pNoBnxlTCqsgCihl0RvoyC1Gkh8rQbgtLzXE4RT9k3Wiz5JMgyxXEG45AQiqVhrJjAwRGNPeycJzOS4T47kPHlDlL0nLoipRx0kczOT3OfJUVEeD3Lbi1kafkyDvZWaBnR281hXykwgCEdIMht1ZqEO7+Fxzs4AUxd5rNu6SBAjUb524Ha2ZUyNcb0BEwjFhOGq6Yfud/Zz/y6cJfGMpwSRFyrrxAV+P7hTjFkNUBmPxkniZeC+LVRreTw9l0S0f5vojxWGp1CYxLJUoGIcClGNN4OcCHX+JKOhJDH0PF6rJ57jZ1f7vXEc0cYSXP51TQwSsKyVl6GwKaCIp4KCwo2LcJg361plofFGQvakhaNLX2uF6zDbUmY8JtupPqU7eOOUfZ3J9KUZlVrR3s3P5+aW3oBrFf5/cai84wCnnmfJ2gjQTR0KAyefI6EYGCaByYusRElOZY+rYTC8vpDlZzMzJDaQyqXmu9c9zXd9y3I4RHl6vjdSEPlQmAShUgHVSGGOsW0eHxnsLgmqba08RtEVJMprIeWOI0rhgmRI1VPXSJJKYjtjcZE56QC2LEPDD3KXimcsSNWvUaeZRyqLZoAkVPZ0yrnw0Pi6zHNt7wR6h0WZ3KOZqlHn8mNJEkrDZA9orcpopHyG5qDQAL/fvZ/EcGacrRLTEywrB0NUjstFXm8d3bxW2rt4bkMRfq/rPK6FLEvpe28Fduzmdoyfp8Nc9nbOTHAue0e3b0zr7ue2zU4Ch+4CbrmVPaLHngFOv0S11hGtE7Uyr9WObpbapRmqd5CKaaNBdTQUYX+o7XD/w0Eqkh3dvD6ks312kstp715Z9TdMcSwqyxvsXHENrkRMbzJ4nodsuYGOxOZrO1DEU0FB4caFGWCE0IlnebNqvSm5Lm/8fdtW78cs5oHTL7I3zhUO5nAE6N0G7Nq3MILmShAMAXsO0r0+Pcbt1Q2WuQFgx14Sk6kxoTIJ9e3iOdFjaHB/h3aSQORmSTBkybVWJYGRMTkauIxyEfjh48DLX8ty5+g5kslpQZIiEd7spSvaFr2EAI+FIwiorvmkO5EWRqGKUAsNftk2YFVJTu2GPBGgOqoL1XIRHJsmHtviGM2AiFGSmZua5qutnuc704MBtj2EIj65cpyWWeG6TyTLRaq/usmfBYKiz7WfKna1QnLY2n/qiXYAW7QxRBMixsn1x1zGklTHpQHK0En4TzxLMl0pk9i3dXL0ZjRGtTAYIpmLiVnqjkPyXynx/YUs1z20k6Q4M+Ubflzhuj98H5cxN8X1tMmHpCYVcmk6i8BfbjTO5Y1dYOtGNMFts5vAxCR/TxIpvtbdx+VHRC6pNG5VStwGqYzXalyGYVC1LeR4vNs6/XMcS/CBq9lYuT9T16mwHjsCOKml5r1ijm0Hrcu9SXFsNIvPPH4Cc5Uq/vT/ei0CxlUwdl1FKOKpoKBwY2NgmH2LExf9+dEyqLu9F9i5f2WVpVahi7aYE1NupKu5yjK757JMfbUiXDp7gdtfzl622Skuv7ufSpJtcSJOqSiIlstyabPJG7cnehRTbSRL9QowfpE382TKNy8ZBolEowIUdR6PIoCnnwAeeAMd7/EzwItPieD2KOZVSwlDB1xNkE5JQiGm/8B3jksiKueFR6I8juUCkG9gAZYjnRKNhiD9EP2asi/UFH2v4DbqsuQvDFClggiV90iyDJMkTk7ekWV5iM9LA04gxPXJKCrZsxnQub+OiHOSam9DTK2Kxrj8ZoMHxDRJ5JoNqpONulBvPZ7PRhPYvovl51Qb8NyPWRJ3LK43HPUfdJoalxVLkDh6GrBD9JdOj9FJbxhUDeXxBljqz0zzq1EXPb4ZltTNoE/aXaE4xxM8P9PjLI/nsyzFy4cuTROGspYKQlsnH4qmx3ntarpvPjNMZplC82fO24vK4a0PDquhu59EempcTAwTgfjFAh8Gdhy6qY1FF+fK+LN/PIEfnpwGALhmE8cnM7htsGuNT15fKOKpoKBwYyMQBPbfLsqCoyRk4QgVxJ6B1cvs0xNLJxRpGlUeTaObt14TJT4Re9TZc2XlvmSaX7sOCHJksofw5PO8cXf3k1RkZ/153UM7SVwsi++NJWiWGj3HZcyKzEMzxHKnJabXWBZJWjxOUnL2GEnELbeJ0O8CXcM5zy+nS/Ih+2Y9x59fLuOOPNOPQ/KEAai7D9ixX7i0Z/wyN7B2j60jyKUmyv8S84HvIPHQ4Pfsurqfx2kKghgIiXGftiBnoodTOs/DUbrL4xpjj3KzLJ8HI6KNQPTy2o2WGCebr+s6ldlqRUwH0nx1z7L43kiMqqJUB1Md3J+RU+y3fPp7fhuE6zK2ql4juYQw7ETjIlw/KoYgJICh3cCw7l93c1OCXHskgrk5OuBTbXxPMccvxxG9mSKnlBc49/PsSzxXZoAPYOEIt7nZ4HABz+OxCIWB+17DCC6rwffJPst0J8+7Y9OolEjxPC5uR6lWgLb25dthWhEKc+JRPCmma83xuLd1kBz39K/++RsU2XIdn//uaXz96EVe/pqD8dv/AaMP/DXKib8BoIingoKCwvWFGRBjB7eJcmuLIrQYVtOfcX7sGf4sHBP9my0u4UKWc8bLJZJBxwbGLzBce98d64+IsW0qTK5LMhGN8UY/N80Sqa5xubYDdIuoJc8luTBMllirZdFTFxbZkhluYyQOxHTepAMhkgJHEBIj4DvFXUGcQxGSad3gtgztoFocjpCYWk0SMF2QTDmr29T8fdEFcbEckpxwlD+3RaTO+AWSO2FeXxNye1vPJfQWpRK+C99zAc8mKQyJcnW1wvcbum8s8kSMkuuK8Z4GFTpD5/EPRagSZ6ZJ0kOiv9R2hNHKbYmM8kjqNU3ELwVECHyIBCmXIWHzHH6uXuH2hmP+iM9zJ/i5qIhlajZ4HE2TqQvlgm/Aqla53niKpHTyIlVvXec12tblz38v5kieuweoXnvgcQlH+X05z3PVe6tfuq6UAGjsR61XeO4CQR5f1LiPtk1SffvLGEWWTHM9AzuoMmem+RAWT4rA/jqXNztBsh1P+ueuVuUy+4bXlwQRCnPW+7bdVG91nS0Nl5oicQOg2rDxNz86h7968iwaFn8fZvb8GGcefBRv7XoNvoYfYxu2bfBWLoUingoKCjcPZND5SqjXmGU4PeETAKvBsnpHNw04ugHkc1SSAkExflD0lTkOSavx4tqz2l2XpGH0HMvnnkPCEwiK8mydZKBW5rjLrj6W0OVknFqFJCOfIZlq1n2SVylx+2REEETvX7Pukz055SciFLSeQe7H2HmuQyqu0+N+X6dhkmi5wr0uVU/p4rYtACLUXIaIOw7jeBwbOHOcx2e+PL4OLH6fNJHI8+lJhVOYkGS5PZbiPsoyuWtj3vWsG345XZ6jgCB2ALc7mvTd55USg9MtsQzP9VVamfMpI6kiCQbZS4W1VvbXowll2LaBWokPF4k01zGwnWS8XhfTquZ8Q5Pj+uXrzh4SwkKW12pHD8mY63B5U2M0BXV0C0W8CQzvYi9wIcNtCgSZxuB5QFIYlgChaIrZ7nOTfJhJpP1jH0+SzAJUF/eICUiyh3bHXm7nhdMkoPLYGgGRTCB+/8pFksZmne+X1YdLQSh805bVbcfF146O4vNPnEShQnW50H8Spx76U9w3PIRH8RXchts2eCtXhiKeCgoKChLnT/Bm3dVH8lQukNjFEuy5DEdZws7PkRAFgwvLg4ZB8paZ5g16tTnUo2c5ItMMsFRoGHSVv3iEJol9d4jSbQmYm+HyJi4Aw7v9HsVUG0lIsSBURYtmonKRRGR4L7fVagJODmhWAegi7Fz0XOoiW7KzhypapeQrUt39zIxs1ESguCR8QjE2Ta7XMNmXmEj5k3LyGfFe0ZsojUma54etW9Y6oqxamKeMzIEoq7f+PBIBPB3whIEq3c71lHLc52qF880NU2SWGgBMkZMp+j8bdZL6cIxO8GqFyQh1EXwP2YfYsk2u6/dKuqLfExoVP0/D/AhOafzRRfkfGs/NZMQfwxkI0ihUr/itDWYQCGpUlqUabxjieMo0hXZf8ZOKfjDsK9TBMK+bglBA5UNDtUJltZijamoYwM59YjqVtdQ9rmkkorMTXL+cmKWJ/3geFdVtu0iAi3nh9NdIeO+6n/3Kc1NcflcvCWdb102pWF4qPM/DD05M4U//8QTGs1UAQKV9Amde8ygG99fx19p/x2vx2g3eyrWhiKeCgoICQMI1PUGyKMuObZ0kUK5LgpmdZexOpUQSFU8sdcQHw4CVWTh+sBWuQ4J58nm+t9UV36iT6Ng2MyA7e0XckyiRF3JUxwwD85mVyXbexBs1fypMKEJSuucAcOoYzRimzrxNy/YJUKkIwOU+BExuV6POfZb9e45DAhfWqfpBlOkBvmYYgGuxZN0zSNI2Pc7/h4XSKZVj2xLKXUDEGTkLez3XgiyXA4LoCQLoudwvQ2Ro6iIKqVEDEm08Z1adBL46RYJkNfxpSXLKksyKjCVJQKX6bBhAWw+QnxGjILHQlGMJYuq5VDjtJrdH5p9KV7Eu3N+axtfrdV5zibToC9VpEqpXeQ7LeR6vWl30roq2jEDQd/eXS2wBaO9iP2UizW3OzfFBSaq4gSAfLjp7fFJ74QyJYrqDD1edvfx+clQYmhpL+y51nT9vDXIPRVhuz4p1hiLMI62JvNValQ9RB+8kmVVjLS8Zx0az+JPHj+P4WB4A0IzmcfbVX0DgzpP4pPER/Dx+Hjq2BnlXxFNBQUEBINFo1BaSxWSa6ufspAglr5GUlfIkjX3b/LGTC7BMHdnzqAKNn2fZc3zEN3y0d4kyZp43dMehMiUNQ9E4SSGEo76925+t7dqc/NLWybxFU4TGDwzzM3OTJAq2JYiaC9gegBYFs1pjoLzrkrjYoo+vXKQRKBgE0CBx9Rw/49JzhVpoULUKBklmGoKwyPKznBykm35QvOwTXTe0eY4IwB/h6LnCLa0xfkjGRsn57KYgR5pOstusY94BbwoC7zhU/KSK6lh8qOjqZ8vC5EXAETd1wwR0abaCb7ian6Skc1mWLVoKXB5qgOegVhVKs+Y7xXv6ed4jUVHa9oQJRxh7msINbxh8QNCFM75eAeLDfpannP5TLYvIog4ut1xYOL1L06lEmiZwy2EqlK2GuEhMtACUeFzla57L5QaDfnkeENfbdl4r5aKvmEeifmxU3/Dy+ZsKq2KxU90J1DFy32MoveI7+I+hD+C9+BsEsbWySxXxVFBQUJgfQ6m1fA/eoPu20fQxPUHCaZrAtj1UtZZTNOtVktLFSujFMyyty7JrVfQOjp+nwtY7wBt0NM7tmJv254W7LklxuUyCF43zpj4zQZLQIabNBAKAVaOBw3E4EcZxWsrfc9y3hghvN02fIBZz3G5JCkt5EtdCjvtqir5Nyc7k9B/dEKMTY9ynaonb5orsSdv2S75SSdZFn6O7DEFfCTL0Xaqa8MR2halo1qpiYk5dGIHAbbU0MS1JF0TYY8k9FOEynJY+T2jM/2zvBvq2i1YK0UdYLvhjNg1dmJOAebVUKtDS0R0MAA3pupfXlC6c8GW2HMjS9a4DYkqRIMNtnXSBV8tivKTuE1jXAwzXJ7r5LKdl5UVEUrnElgzbEq55B8hmec7jSS5n7DzL3fEU+25nJkhaB3dwH7p6qVrH4r4zXyq8kQiV7b6hheenux/YfYj90NNjov1CDAzYtpOZtwrrxkpO9fEH/hb/JvFu/DscQxLJtRe0CaGIp4KCws2Japk33KlxKlPROAlEpbjQUKHrJHuOA+zcC9z+CpKy534sQqvTPnGxmnQxb9u5UGEql4Dzp0nINJ1qptX0TUnlIie+1GvCdNEUxKEdCCf8uB9DuMEdm2XRgR18vySxmsZ4ncGddOTLkm0xz/1qiJItRN9hVMRC1eskTGaQJdpilttZF32ErstybiRGMtYQ5WdbxPHs2AdMXiCpCYbovLabPpmXiqRjCze7IGsaRDzSagRU80Pi0dJb6jp+X6AkhVazRUUVy3U9ALYgnsKJ7mn+1CpphNJ0PizYTZbndY3HQs5mD4kpWIWcMFjZJLAySqrVZW8ERLyTUGVlX6rsEXVsPxUgEhVZq6KFo9mkypnLtJTqTfFABC5PM/2cz2qFCm+9yuEDxTy3NdnGY9Zs+IejUmQZvVLkA1XfMEl0uQgcf5atFLsPUeVv6+Sy27uprLqen0vaM8ifLzhNGufWd3TxgUW2KrR3U3m93IleNxmWdarv/RHOvfbP8Y6un8bv4in0Y52xUfXq2lPZNgCKeCooKNx8yGcYDF/IYZ6cyNGIuTkqSLIs6HkkNgDNOsEQFca9tzIGZ3pMqE8OiUT/NgaCtzrac7O8efcMsgRcrZKoTI+Rc1lNKnamQROTadAxHBGRTLrrO5q7+oA77ychzM5RYYzGSHR37WccUqPOEnFdjFq0hfoo+/08UXJ3xXINg9mbjZpwjYMGJzmFR/LCahlomv4UqGadStnBO0nC88K44tqiPC9URtP0Q+ChCxJtADBENFFLHucSCLKmmzzO6Tauo1oVZW74RFBO7/FkG8GiVAFJSuWoTtcheZSkzhYh9dUScK5AF3i9TjIqjTOe2N752fLgefc8Es1IjMSvLvoaGy3RS1pL9qlEtQRMjPCYpjv4/xee4nsiUTHxyGBovev66qe85qplXkfNOjDl8Poc3CFc3xER6TTL89UzSDK5a/9CQpISaQmj58W0pg5m3558jj2nMinAsbmMfYdXTodIpBc+uCmsC6s51R8Y3oO/xNewD+tUjUfPAV/6HKs0//mPRZvJKgkb1xmKeCooKNxcsC2WvGcmSaoqZcyHnOuiP0/OyJaEIhoj0ewWSoNt8/Vowi+HdvYwW7Cjx48ZkmiI2JhKCRg5TYKn61y3a5OQ6DoQ7wJmp0lwinkSx2qZamSqjcpiqQicfIGkuV7xXdr6FNDbzxLoMz+gKgv4bmxA9FWC+2QL0hKJCjOM5ZeMdY2vLc7QdCx+eR7Q0Qt0puge1zWqWvCA8nnhuocQ+gxfpQXAyT8uA96lG3pFtKihoYhwb3tU+HSdJM0Dj4MDBru7LaROftYFoLUooabh71coyvNRbwBOAYCIAwpH+Xk5HrPZADJzJFxhkbXqiv5SuZ5AgK9rwjVuCPd+sy6Iqijr66JfMxzjMkpFtlvk54B+Ue6WvbrzBM8TBEK0O8STbC2Qk5I8j32pHb28ni+cYd+nfJioVXiOQ+HlVbBIjA8PmRkSz/Yu4M5XMqGhVORxSLXz58v2NStcDlZzqu/a7+Er2v+H+3H/+hY2PQ586fPAU98VD0I6J2HtPngN9+DSoYingoLCzYXcHMdnlvK8IccSfum2IgxGoSiw71b/Rt3R7SugVpO9k5OjJBGhCIlbLkPysLgECYhRki4nvmRn+e96zf+8ZYksziZLpPE4SYVpMoYm3UYSMz3GdVVKJHpm0A8tD4U4Y3toJwlaMMT9MQOYH7tYg595KXsTazXM53wCEK4WzE/0WQBBBK0GUJgDOoRyZojQdNkSII8TNEB3FkUxCSInzTmBIAmWHL/ZSnR1za9UD+3iA8DoWS7Dtv2SdaPeQmyXQ8syNY2ldt0gaZOzxV1XKMIe4Iq8UkPn8TdMQBOZpIGIb7Zp1FqIvezxFA8zmgaExb7qhlinINuhsJhvLkxG5SKPqRmg6cxxgO5Blr5lj2w4KVIB5PET57K9m+YkaQxLpKiinn0JmErwegL4IJOd5XFcCTJSSiIU9g1LClcdKznVo3eewx8bH8Wb8WZoqz6YCWRnga/8BfCDb/q/s3e/GnjTLy/txd0EUMRTQUHh5kK1zNKjpi00B+kGb9qNGm/+B+/gjTeW8EveABXL8REqm61O4EadKlM0zszEVrR1sZR+/qQIWfd8EuF4vOFHoiyvmqJ3Eh4nB0VanMDVMnBxlApavcp12k2SWF0HEu2CDLns4bt4miVqXbihrSbQbFExJXlZ7C5foBq2ooU82jZL0cm7BGkvcSpRUxqJhGvbWTSXW67bEGRMqqyaB8AQ29KyPbomiK3Jfa2JfsOAeFhw7DVI56L1QrQZOJ6vcEMQYWlCmp++5IoAet1fRqPhRxt5gqzKiCjbFsRQkGrH5rVTrwJOQxijAnwISKR5zvMZnpe5aZLEZp2vtXX6s90LeW6HEeB1YzVElJVJYrH7AE1GlRKd5eMXRIuFxQeDRBqICWV0fIT9wcuFrzs2t03hmmKJU92sY+Rlj6H2iu/jw6F/j3+FfwVzPfSskAO+9r+B7/y9+LsCDq548ztZfdmkUMRTQUHh5kKjzqzFjt6lrzk2e+BKeeCpJ6iwBcN0+e4+wPeMnhPjGRcZYqT5ZOICo4xay5GRGMlhpUIi26iKkmvAD2eXoeDBIAlELCEIaAusJlWwoojHkZmb9YpQTE+QjKTbgXiaZW6prDoi4sduJYKyb1BbWJJfCVprqd4ikamW2Gs6M0GSaYDkdolauvhYC+LkiL5PU5SmrQYJqSF6Ok1Rvp64yF5bx6FK7NhUip2VSPIK8OATzKYMhm/p/TSE+94VDwjSeW8Kl7brkPwCfklcqsqu6BENhUXWqeu3K0Qion1D47lNpPyJT64wabV3i57iPEvcujBEtXcB9TJQrvAYhyI8x6k2mt0iIq9z5BT3qVnnNadpVDrLRa5v+17g9AvsI061cb2BoE+OA4tikhSuKrLlOv78idP42jOtTvXHMfnAY/jNxHvwb/EpxLCOUbuVEvCNvwEe/6JvHrvlNuAt7/L/Tm1iKOKpoKBwcyGa8KN1WuG5DBgvZBkj095FRbReZfxMpcwy6akXSEinDN68ZZQRwP8XcyQmrQaL/BxL4Z29fsxQs+67tTVduIADQDBJglkqclnxpE925JQg16FTfnZCTKoxRT9hkwS0WBAZoe1iSkxTKINCXVxAMEWZONQy6WaxSjn/1lalVJTpz5+i2jYzwX0xAoDbWN+5mJ/3Dr//EcJIBKE6Nl3h8m+2rN9hFqkm+jUt11ca114pS9zwfIVSmptcTyiglt/bGZSGItc3Mmky01P0isr3ua5fRo/Euc3BsK8+6sKVH0vwPBayJNOG6BvNzvLak4aqeo3HWCuTHCaTQDPMcnnvgD/xCPDNTrYliDWAYITbU8jy2uzoBkZjwLGneW0EAj7BT6SAA3f4pXmr6ZvXNI2vpzuX9i8rrIla08bfPHkO/2fRTPVzD34e7+x6A34HT6Mb6yD89Rrw+GPAN/+Gfy8APkz83LuA/XdsKgPRarhuxPPjH/84PvShD+H9738/PvnJT16v1SooKGwluC4VvJlJRr4EQ1QbF5e1rwQd3TRPFLKihCuUyWoFyE6RVKY7/Ikt4SiQ8oAXfkISoYE3e9djebRUYFlLhma3/vF3XRLMQo6f6ennDb2rhwre9JhQ7Sw/fLyUp5M6LAhLdpbEIBLj18WzJJZlYf6JxUk6bBGHJBXJ8YskxnJykGmSTOnCDe2J5knpkJYExhXGn5VInDRcwSM5npvhDdHzuA5p1FqsCC9ciD/jXBqQZLC7NCPBYzncs8V2inV6EEYo13db69oamaAarx9HEM1G1Y+VktmeC+7ZLUqnI5zvMrMTokTvOmJakuYbOTRRmu8eYLpBvUpTWi7D66csrunMNEdrNqqijzcMYI7HrncQ2H4LZ8VnZ4FYEyhmaH5KJDgR6L7XkgSeOMrrJZ4kge0ZAGbGSRgNg4TatpmEEAjSfGI32YucSPFatMX1kW7n5zWNvxsnX2BLioSuA519VNai61DlFGA7Lr7+7Cg+992lTvWHhw/ir/AP2I11lMStJsvpX/0C/94ADOx/878Abn/ZliGcEteFeD711FP49Kc/jdtuu+16rE5BQWErwnUZBTRyWpQAQyQKExd4I99/+9XpP4tEgUP3Ake+SzVHxiBJIhpPkehGWpy/uQyJabpD9BqK3r1giKrk9BgQ28eex0YT+PF3GE1TKbIsGgpTSWvvZFk8EuONIzNL9VPTuKx0uz9zXcbX9G/jBKVyiWX+Zp38p1YRCpwo/zalKx3Chd0U30OMphRZlsGQmLHt+STVcbhd0l1vmFQVlytjtxJSz6bq6gnVNBAQ89fXOglCbdSFIUYG9Luiv7NVVZTqaivm8zjFe5ct67cou/NqqOarloGA7wiXUUeat5TAOhYd85pOYg9hFpKz16EDpsYHBcchuYRHMh9LsMReDVFhLBfZ5lEXpiEzSFUyHOGygiFeL/kM+3tTbVST2zpJYu9+NXDbPf5DkbWfBHFyVJDaMEllscBlaiI/NRRmb+qMOFd7D7KsL41EoTCV8akxEtSXjpLgdPb6of9Wk6QWHnDrvSvHKSnA8zz88OQ0PvOt45hY5FQ/sD+Ib2h/hntwz9oLsm3gh/9A41Bujj/r7qdp6J5Xb9ls1Gt+5ZTLZfziL/4i/uRP/gQf/ehHr/XqFBQUtiqmxpiLmWhbSPocm8QuGAQO3nV11tXZA6S76JA2dK4zGudNWio/UgKzLZbKIzGSsvZumjeMALcpluBNf+IiR2E261SfZFSSdG4bBtWmZBtVwrlJ4awX5XPZ/xeNsSxfKfsTY2Tmp2OThNZrQCnLbaxXMD960QiIvkNBAht1oSTKErXI5ZTTkwA/nkcSNUPn9nquHxm0Glp7RiuinLw288S82lgts2/Vk0oiVjY9zX90kftdQmtVar2F73c0KpdSbY0lhTnL9sm7tsqN3DB4vqUZSRN9qXI9kugHQzzPhSyV8HKJ5y6eAA7cTqNQZprnRRdTinoGqS7KaK96hedpYDuvRddlzFF758LZ6QPbqciPnuMgBKlshyPcvohQ5mfF2NRAkNOMqhXAGhfl+xRJcjxF8m8GSHZ7B3zyD4j+zx4uKzdLFVVhCZZ3qv8lUneO4k+Nj+Nn8DNrO9Vdl5FIj32OxxvgdfLGXwRe8fCWJ/3XfOvf97734fWvfz0eeuihNYlno9FAo+H3BhWLxWu9eQoKWxu2zSfhZl2Ea3cs71bd7HAdKptmYCHpBEjKUh38A9w6B/pyMT4CnH6Rf7x7Bzmlp5gjgYrEGBIvt8F1eXzzWRKBji6WG21LTGcpkjzk5qgY1UTvZqUowsSjfN1q8MY/etafxd6oYz7IXNNJalLtPH+yn7CYZRC8brBcbwaoktWyNODIY+e6/nQb1/En3pjmIoImHdem3+eqeWIGeEgYojygs5vGpgtnL/34rkVUF8NqAJK7LjZTrYQlpFPD/ESkZaEL17wuJgEZVFH1FlUUWKqsti6/1UQEAHHhFs/OidK96FENBPizQEiEsp+jaSzVzi8P/sOE7PGNxmgCCgSEsSxJhRLwTWq6tnxJtb1LfD7LmK9Gg+a2cpHfG4boCS5yP2JJKqoAr4VogoHzATEXfnqc12Ar6ZQwA9z+Qk4Rz0VYaaa6/Yof47+E/gN+Cb8EA2solJ4HPPsj4LFH+XcKYEvE6/8Z8MDPXr12ow3GNSWeX/jCF/DMM8/gqaeeWtf7P/7xj+M//+f/fC03SUHhxsHcFHD2BJUVWUaMxamyDO7wI2C2Aup13hijieVfj0R5Y62UFhJPx6EamcuQhMfiVGVcl+QPoCIpP1PIAaePkcgN7uDPbIvl4dlJftUqXF+1TDJcyALZaS4zGuPNt28be+yKeZKKzAyXEQzyc64HBAXhjMYBPcxMx3yWn+noImkpi20MhtgvadtUXIMiKzLRBgxup0pmimW3if7UYIDHTfImST5llqYGXz0E4E8v8QCI9gIjQLKlCZUzFuc2jY8AMJb6kDYrNLBP0mpiaRao6EmVPZ2S9JWKPF9r9aLqQg12HZ5jQ/SmmkE/9zMYpjkoGBCRSA0qiLlZfmZwJ1X2aoWvucLtHo0LxbfBa6tcFK0DzsLf31qFamitStKYbGOLxuljHHU5cYEks5Dh56xurj+W5EOVTDooF6mYy98Hz+X1OHaOvdThKOYHKax4SLRV4rZuPizvVP8HzD7wd/h3iV/Dr+PTiGCNFiHPY3vDY48ycg3gtfG6twEPvumGi7i6ZsRzdHQU73//+/HNb34T4fD6FJgPfvCD+Lf/9t/O/7tYLGJoaPOFnyoobDhyc/xD1WzSLCMJR7kAnHyeN4ehnRu9leuHJv6zEgmQPYStJapGnQrPzITvjm7WSU7DUV/5DYXZF7XrAPsRG2LWtIRUsoZ2kNxeOA1cOMUbMsCbdCwpcjLTJPwAncWxBNVT2SdYr3D5AVE6ty2ShUicBE8acNJCpapV2EvXbFDtq5TFcciK97XzvaUSA9styy/Hyj5DecxkH6PMtPR0Me6ypcwuj6Hr8ltTB2BSDZSjQWs1lor1xWrpJoUsO7pCwdRED+781KJWBVZeR2J/a9U1nPCSsIrrznOBWJpl80KeDwC2RdVxcAcJoezP7R3i94kUSenMODA5xutH10lCpdnJEddGo8oe0EBA9A/ngZGTTFUIBHk+L57ltTMzwZ/L61QqmxqASoGENpmmqh+K8OEIOs/xvBFO53uyc1z/vT/FZZw7scLhEO0PsRUeEG8i1Jo2/vrJc/irJ8+gYfFam9n7I4y89n/hX3W9BR/CEbSjfY2lADjzEvDFz/LvNsC/Vw++GXjdW2/Y43zNiOeRI0cwMzODu+7ye7Icx8ETTzyBP/qjP0Kj0YCxKJYhFAohFAotXpSCgsJijI/wptkz4P9M13njK2RZ0u0d3DqlmVAESKV5c1xcam/U2f+ZzwCnnuf/u3p5DCYv+o531+FNeXaavW17b6XqU6uwZGxZ7I0MrvAgXCkJ4gd/DnowSGKwbTcJZU0Yg7KzYsRgnvFKts3JO80at9cMAAGRU2mJKCBX3LQDQe5jV59Qa2cBiNBy2xKxSkGuy7GBJ77GZRSymA9uN0UETijMz0gCo5sLR1PO88YWsiVNRVIZlMRbA2CEAK3u/8z1mP95zXAVJFXd9FW4eaPRKss0hIFquUit1TbTMEnYzKAYCerympJZm6U8zWqNBhWq3BwVRkPMo29UhZlJ9NgaBlMRQhFhyrL9TM/sLHD0SWZ31mq8jtu7eI02m/w9qRT482icBMVxeH0DnK7U1k5Fe2gXrzHDIMk0A/wdisZFG4gI5W/r4JSiRo2EtpRfOnM9O+eb725SyJnqn3viBIoV/q7Rqf5neMPwHXgM/4hhDK+9oItnqXA+/xP+2wwAP/V64Gd+gaayGxjXjHg++OCDeOGFFxb87F/+y3+Jffv24bd/+7eXkE4FBYV1oi5Ku8n08q/HUzQvFLJ0pW4F6DrQv537VRY3VIA32vMneYPuHeQNfuQkxwFWy7ypSnJdLvKG2t3Pm3I+w+VEYiJKZkxkMi5DSpp13mytJrDjFhLQWII350qJxLF/mMd1eoKq1fgF3rDrdSpQciykLvoI6zUxjQgkKoEAWLoVJe9alU50qVbLPEtPOsw1KqH5DAlJucT1aBAq16I+QWnWWYzVoo1cB3ANP1ZHrtMIkECt2PN4tXAVFFWr6ffS2mspmMLVbtmA5izfx7gcdEPMap/hNZFIiQglcH058QAhjVrBEElqpcRzZ1ui3xbiQcHhQ00gyOvddfgQ0dZJ5VQz+JDVbALbdrGqoQmCO3EBKOeokNcq4pqQhqkE20msush9dTir29B5PSbbmJJQzFFpd11+rquP6wkLh/3ugyzjT4/x98fzuLxYErjl1huu9Lse+E71lzCRJcGvtk3g9GsfxeH9cXxb+3McxuG1FzQ5ynnqTz/Bf+s6cP9PA2/45zdNeP81I56JRAKHDh1a8LNYLIaOjo4lP1dQULgEyKBoY4VfXxlq7VyiyWOj0d0H7DnIQPKpMd5ML57hDX/HXt6QDZMGjdGzvCn2Dvol9WLBL2WHwsIx7oh+vIDf4yhHSraSjmKe5WzZD1oukBQEhOEnL3pIwzE6mUNhklHTpLoqjTwNxyd5jbof9g6DN3/X4XJKeRKVvFBOdYP9eY4kkmJyTr0OaEW/DGs1SGpkCV1mZgKi33C5+KPWfwiCqhti/92FcUFymZLAboW4Fqkiey5QW+Oab23pkKrneiD7Q+Hx+jENzBuONJ3ntlrh+QkEAbiit1LndVEpAU1NzKUXY0Hl1CTTJHncuY8PN4k02z3SnRx/GRIxTbWSyIUVQwKCIW6LHF4A8Pt8huTTttlyUirwwaqY43jNtk6aEJsNnmcjwB7mrn5/OYM7+LswNc6qguty24b33PBq3HJYaaZ6153T+Avj43gQD669kLkp4Mt/ATz5Lf/39p4HGI3UWrm6CbC1PfkKCjcjgiHG7dSrC6NVJJp1MQ96i7nbNY03tvZuKkvjI7z53XIrb8atJCESI0nLZX111BG9dZUSb7Kuyz/2KeH0N0zemINhKqjt3f4UlkIOaFSA9m0knpE4b/pyuwyDamddlD1LBRGN1A7Ao+IlZ787IpvT9WhwMkT4u6exrOp6VGvnx0XagNfkzyMx/rxZF31/NlBxRUC664em6xrVLGmUmT+GLeHu81j0vS6yHefNR7IHdI3Mzs2MWtUfHbgapOtf0zm9yLEA2ZmgG4JgLrPPnsjrlCTfstnnWSzwtUiMJNMRx9+yeA3oBs+50aKEGiaghfkeU6QLdPQAe2+jGpqb4/Wva3wtM8PrzxItD6WC6PMFl1erihK9eIiQyrtsP9DAMrrr8Boe3Ok/nAF8AIol2b7SCk3zo7hcm79Lji1+R7su7fxsUazkVMcrjuCR0O/gF/AL0LHGw0s+A/z9F9gyI9tgbn8556lLg+NNhutKPL/zne9cz9UpKNyYCARpXDj1gj96T8JzRQ9k/9L+rK2CREqUMoVZKrlMg35YzL0uZgFvO+bHTs5M+mXFaBwYG+HNtm87b9xtnSwrnnhemIQE6SoXONtcqqptHey/bNT9G3SlxJt4TdzkY0nMz+WWcTjhKJeRmeFndd1XZeem+L2cr241WWqHRfISjgDQALshQthbCaEo0wPiNUFAoS3MrlwPUXRdEZ8U9CN7JBbkYGL52KL5KUGbxHgkeyjXuz2exzxPp8nJSPP77LVMKFoOLkvgmuETSQ18ALBsP8Bf+t9kv60M/Ndb1iOVZUmEK0W2bhSzvHZnJ4VZME8Vtb1b5MyK9ZaK/sjEupjC5Nq8tiQpjsZIaLft9rNfTz7HVpWObi6nUWeSwS23LjSyFLLAi09TxU21+Sr77BSJ76G7N458tk43q5X5INnVy2N0lfIts+U6Pv/d0/ja0Ys8VcKpnn3ga/j3iX+Df43PIIQ1/CjlIvD1vwL+8cv+Q9H+O4C3/Auq2zcxlOKpoLAVMbCdRGdqVDi4I1Q9KkWqbrv2b604peUwr94tg1iCRC0z44+ULOZ5c9TDVKC6+/n/ShE4f4LlrFQ7lcThXXxdlrz6trHHUxqPEim+Pj3GG3utyuNpW+wnTKTZo5ebA/SocDPbXL9p+sHygzvYQnD+JMubQ7tIRmYmRAROncTDNLnuUp6vy9nhAI+BLdQuGXXjiFYBWS6en8O++HjpmC8Rz/9I96cTuZWFb1+rPzIgSsvNxuq9o4shI4gc+ypG8ci+VqEIrwfz5XVh0jIMAGLMpzR/LVmN5v9fvk/T/eB8DaJX1iZpNUVJXU42kv23jg1YOomr3G6pVNaqwOQFkst0B9+bmaaxCJowuYnfZ1maL+ZIPiNxoFkW14Ejyvh1EuKeAV7HAP9O9G9nrFMwzG1o7+KDWGtEmefR+FIp87Ny/4MiHWJmQrQCdFz/vzGu6Fm9cMbvk7VtVkd6BoB9h68ox7jasPE3PzqH//PkGTRbnOqjr/3feG/X2/EBHEEKqdUXUqsA//BF4B/+lucV4N/jt7yL26egiKeCwpZEKAwcuIM3jokLwhBiALsPAL3bqHhcbdi2cNMWfQd9uv3a9AFaTd9tW8hyXfIG6Hl0rpcLLC0ee1qoRmUqM80GHfLSUe6B+ZnhKMOZG3XhPDd5I731biqR5QJv9h09XFfPID9z7iSJRCjM/e4b4o1O00l4axW+LxqjCmpbLN139HI2e3aGxy2W4HpnJ2lQqpT8PEfHAay5Fkf6CvA8/z0umBspo3iWnVe+mEhpmJfkKotI52qQAfeaznUYLT2ito159W8lIioJ51WNZ5KKsLf2cZNwPUBriaByxNhKGdLebC5qOWhpXZifx+75pi7H8dVGaILnez4h08TxlufFEGqpI3I6dYMEMScmY9XE7HYjwOMqj3khy+vH9fy4ME845GVJXyYbxOJsB4kn+DDWqtoHgzQXDe9Z+RhVyvw9SLX8zrUi3e479lcyOF4rTI7y9zHZtjD9wrZI3EPhyyJ3KznVTz/0Wfzc8H34O3wbA1ijD7PZAL79FeBr/8fP5x3aSYXz1nuXP5Y3KRTxVFDYqgiG6EQd2M4/vIbh30CvNqbGgCPfY+naFWXhZAdNP/sP86Z5NeC6JHWjZ1nSy2dYguwZZJB6JMYS25kX+f2t93Hfz59k+TESA3YN+y5cV6g/Vp2tCZMX+VpQTJW5eIbqyat/BrjlMEuR02MkI80Gy+MaqFpKAhAM8caez7C8Ny2yGR1hZMrM8KY/JMr2jksFNTvLG1IpL4LfHdGrK8nnJfZTejZQs0lSXEece9nXp/uRSa3QNcDQ/M+vBUmOdFGa9zxmlFrCYa2ZLCm7UnFdbXsvgXRK4napU5DWRCuBFOpxMCRMX00eH2fR+4VgSYVZ9IE6IvpofnSnUCVt0Qtqi5ilQIjv9Vw/F7VS8k1FgRBgOGLaVAMIuCSSzQYNTIkUrwvbZqoBwJ7lji4OTchnuH2RmCiHi8iwkBi/Wq/x9ygkwvV1w++JXgmOxXJ9YoUotkDQd+pfTzgOMH6Rx3lx5JoZYEvO9Dj/JrYarlaB53n4wYkpfOYfj2NykVP93v0d+FPtCziAA6svxLaA730D+Lv/xb8PANXXN/8L4K5Xbv3K0zWAIp4KClsdMhPwWmF6nKWj3CydtoEgyVxuluqn5wGH77s6/VWjZ4GTL/BG2dXHnsyR02wpyM8C3QMkj9E41V3Zx2pb/oSZYIgjAxt1YPS8mHst4oxk+bPhirJmJ/fvJ99hht4dr6DxaPIiy4mhMG8i0ThL7rOTwLFnqGQ4tl8ubzZIIqbHeTwSKRLQ2Slue61CElCr8HXDFL253pWrgI7lHwNN90vwroP58Yya4cc8uZ5PUtbqi5RGJFdkRJoBlnZ1YeJyXDHi04HP0K4E4hxK4n8tYZq+kl2vAzCAkFCQraZP4A2DxFoz/KEA8vjpomwO+A9+tu1HUwVDog9U/H7KOe8A1+GIh49UJ9X3Zp2vyW1yBCmNJXgdxmIkWLk5ks5QmAq9VB5l5m2zIRR6jT2ijk3lvXuA/curIRDk70qzAUSW+Z1uNkVO7TV6yF0J9Sr/3qwUqh6J8aGuUloX8Tw2msWnH38JJ8YKAHyn+sCdWfy18QheiVeuvgDXAX70beDLf+4PlejoBt74S8DLH7y2f5O3OBTxVFBQWBm2DRz9IW90A9v9sno4whtnqcD+yW07r3x2c73K3jLZQwlw7OTugyyFj54jWevoBrbt5Q1bIhzxVblCju+vV1k+D4ZEjqYoD8fjJGvFPJXJtg4SxLHzNE0M7vDHEnb3+711wRBfP/4MI59mRblcE5E5js1/myYwMw0karwRZmZEP6FJA4ouSrS6IH5XU9Wb71EUhMkM+iMYDZ0B8eEov7ebvlN6Jcz3kDp+mL4Mw5fra4o+xKtSRhcKY+vkoWsBaerxPF+51D1/vGYgCESjJJe2DbhCIZWVhZQwvFkNkXcqVEk5UlVOotq2i8s88RyPm2P76qks1VtNPhzJcHeJSonXqGOxvWNgu/+aaXK98eTCEm4ozB7O8REut1zk74Nh0oBzy21rt8ZE4/4y5AjN1uNWyJIEr6WcXiuseFms73q5OFfGn/7jCTy5yKluvuI5fDL0n/AWvAVa64S0JavxgGd+ADz2OT6gAmxLeP0/A171T7bO0I4NhCKeCgoKKyM/R8UumV56w5LKSCFHYnqlxDOXoYu2e9FyZD/p0E6WG+Npks5GnQqIVPpCYf47GCGpyGf52VKe7teaBwQb/D4SIwmoVfm5YJCqRb1KwpCZprKk6Sx9yvnrpsH56eMXqWru3Mcb/OQoPyPd6LPjJKbSvOSJEio8v/rdarJZ7Ca/Ygjl0Bbbs6Av0xMlYaHIOaLUv/jGrekkF65wbWueUI49v0zsOi3h91eJfHre+toArmwlYvqQUKqDJnM2bZvnWBMmoFAA8MQkKUlKZV9zvUr1bXiv3yJSqwCRBNAzxGM0vItB7Lp4OAlFBckV56fZEMMBinxAac1zlL9foZA/SCAglOBalWTUc9mTKWO2AH6ms4e/M1YT2HuID1PtXetvxRneTfPSzDiXI13thRx7SId3X/+exUiUv3PF3PIGoqqYKtZqlGqBnKn+1WcWOtULD/wD/mPi/8a/wp8igFWOj+fR6f/FR9miA5Ck/8wvAK994xWZmm42KOKpoKCwMuo1kpSVJpUEQ7zZNq/CWEVJflYK9TYDomzsUWmQPZONGj9rGCRGUZukMzdLQpyd5X5oIAGrV3nzAnjDTraRWLsu97UpSufxFEvp2Vne6GsVEtBykaR3YJhO3+lxqlOGGN1oNXznOSAC4m3Ara9MzK52XqY0u8jlSie7Y7PNQBNDBkzRsxgM+jFNAM9BICh6GW0SpZqIhzICPOa2hXmjkpzis9Xg2IwsCkd5DEJh8u9qWeyjuCZNYdrpFsTQc/iAFAjwQaSQoerVrAOlLGORoFFFbzb8sHbdFQMIxLQhRxqzPGDiItcvS8nFPD9z32uosE6OUjWNJTloIRQGjh8FTr3IPuN40h8X2t7Ffdq+h73Ll9pnmEgDt97DNpeJizwWoQiNSdt2+Yrv9YRuUPXNzfH3rbXk3mzwAXPn/iX95nKm+mKn+vhr/wq/3vXP8W/xNOJYozR/6gXOUz99jP8ORYCf/jng4Z+jyq1wSVDEU0FBYWXouiirNwAs01slHdWJKyi7VUr8KhVIfhxn+f6oRp1l8UIeOPM8y8i1qgiO14F6iU7tzm4qPrk54OI5f8Z2rSLUOzn1x6OCUy5SKU23k3w4Nknu+AhVzKAwZjTrIkqoTtIl45vyszxO88sFCax0QzfE/GxNA7yr0Qe5HmjC6ez63zeb3D+AxMlzSULlRKXWTZORPJLAzpe+NRJ6Vyx3XvXyrs9urYjLPK6y7aFa9iOQZEldjiLVTZK9od08l6U8S9ZtXewDnhrjtWWY7H8tFzA/IatZ94+v5zGj1TW4znCEDwAB8cAiS7SNuk/kD93L9g5dp+LvOv4DDsD1dfYBLz7FMPtAgA9MbV0kiTtuuXxzi5yQJs1TgG/I2ij0DPBYXzjD82AG+fuvGzw+O/bOv9V2XHz92VE8+t2FTvWzDz2Kdwy/Gr+DJ9CNNUZUjpwi4Tz2DP8dCAKveSPwMz9/ZX/zbnIo4qmgoLAyku3sqZy8KMqILU/3nsfyeO8AY4MuFc0GcO4Ex/JJ1XJ2kgR076GFwfi2xRvyzn0iG0+jCSgcobJji1icmMZtajZpunAs7kNVTDNqNrhcDyRVxRyXUS0JYtsJ3PUq7tv5U1R2asLUEAgBzZKI3PF8BVSGWEtV0fMWRvLY4sao6wsn0FxrGILU2GJbPFuMaXQFR/MEyXIWkotWzAeze347wLw4exWMUath3e0HItbpcjDfqyqIc6Muelg9lrgDIT8SaXqcqyqXme5gBmj2mRnnNlRKVNMNQ1QIPJI36fbXRfi84/BBToNvojIDoj+zVwwvyAHpNuC2u32iJ6+vVsQTjFXbd9gPn9d0kqJ1OruXRW6OZeValQ9kssQ/PkLCd+iejSFeuk4y3dHDh8JqhVWXjm4eN92Yn6n+J986hskszVqV9gmcec2jeNX+fvy59jfYjd2rr2d8hD2cR3/IfxsG8Mp/Arzhn/FvhMIVQRFPBQWFlRFPMPy4kGV/ZbNOkuU4LC9GYsCd95P8XQpsm4aLiRESQzn/WdOBc8eBY0eAXQep4NSr7GPr38bymmPzj78sAVuWIAtCKS3kgB99y5+LnZvzlVvb8svHGkhCQ2Hxmg088XXgxSPcz8kL7PuUEUKeULFk0HghB5g6UG+I/k8RazTfu7lAQhTEA2JWt3f1y+utkIqlnDRkmoCn+wajRt1Xs+TUp+W2x5OKqe7vyvWSNj130XZpIsBeKLi2LYL1r8Jx1HT/+jECgNaSTQoAjSofVAZ2kDwWsqLs6vI6i6f50JRsF0Yj4VhvNPwJU1bDTxzw4JffPdC8VMoBk2P8XeodBHbvXzp9zGqKqVgiuzPdToVT15nQcDXgulT66jU/fB6gwz0cBWbGaAI8eOfVWd+lQtP492KZmfErOdV33lnBl43/B/fi3tWXPTNBl/qPv+3/btz3Gs5Tv9IedoV5KOKpoKCwOnbuI7E6+xJVhlIBgAYM7gJufxn7yC4VuVmWKDt6F7pA+4ZIAi+eZQk7EufM+f2Hgf5hKoxNMe2ld5CEqpjn8gIhlpJ1MSWnVOANOhzjDb9SIqmADejCXBMI8IYdjjBuZmaCakc8KUrVFgm357HHLyTUVU+UIRtNP2pIqws1UcMSMiSd5bJEquuAGRLjFKXauAqhu2zjjjAWWYJoe3J6UMv2LZntvswyNGPhNKXrhVYyrBvMTY1EmNlaKl758uX5MOTDgDhe820EGq8pOXAgM00CaTX8+B7HFQ8wIT9BoV7lNQHw2EWjQLHJ/ZG9vx78tpJojCQzkQIO3M7fg8Vmvrkpkt1iDvP9u6EI37v7wNXL8C0V+LC2DLGDprGndW5qaQVkA0Gn+nE8eXIGgO9Uj77iOP449J/xs/jZ1Z3q2Vng7/8S+P43fIX6zvtJOFvTBBSuChTxVFBQWB1mANh3G800xRxVw3CU5a3LvdnNTS/sa2tFWycJWe82qq2hkP8+zyMRbdZ5kwdYBjcCJI/NBslkUJhEMtNiH0wqf4EgWCI2fCdwWIyqLOREyV5kbMqgfKtJgin72xJJ9oVatt+LOk84QaPIYh6naS3OY4/kOBT2cxtXJX7alYuMsrzuXmY25nonA11LeK6IrxKRTqYJuIHVg8znx66uZOqCbzozdJ4XE5zhbhhcp8wvdV1/apfs1U2kSdKKeW5HIk1VPiNyHaWb3bFF+HxrOr1Qmo0g2zc0nRUG2Zoh0agz7uv4US6vq89/vVahAQgaf0evBuwmqwhyfOxiBEPiAbC54cRzJad69YFv48OJ/x/eic/CwCrxUaU88NX/DXz77/zr6OBdHG95OQ/UCuuCIp4KCgrrQyJ15X1dsjeykF1dwTMDJIqLR3+GwsDQduD8cd785IjMSFwokA0Sw1iM8Ssz4ySJgQAQTZBEWA0SDjMoyOmMHywvsyoNkzfVcpHiZSDAG61ucDmeS8KyYFqPt+B/C2AYvroWEESjVlleyWwdDbriAm8y6CLeyDREsLzu98qupgbPx1m1/lAomVpLX6snnP6hEM+11RTpBAH/epCh7HLMaSFLUmk1SVitmt9u0WxgfpSnHhW9n+J267ao7eGo37vpOuxPfvEIyWYkRqI7O83BCvk5zloPhf0MzUiM65kaZWTS1RiVawa4X82G/3DXCksGyG9cXuVKM9WnXvu3+L+73onfwFOIYIUkDoB/O775N8A/POab//YcIuHce+iab//NDkU8FRQUrg9yc4yXycyISURZqgydvUtvcFJVzczwRhcIcFSgaQLb9gA7R4AXniY5bTYBvcYbdzTG9yTbWIYcPUuDxPyYvyaVSmjipq+RAOriT2EgwFJ+QJg98hnepHRprPGoijYaPtnRDGEmWqZcLqcGhcJiG2wujy8un4V4LQ07WxWuC8BleX0+tqplCtBqaD2emibGWApX/3x8lFAf5Qx1U+RWyrxNS4S/N+riISbG82mYQEj0GgN8j2WBLiT4I1ttoRhr8IP9IxExBcrgNVguAmNnfWPa1Bj3b2g3lxNL8XosFxlplBSlcFnyL2avDvFMpGnUycwu7Wv0PFY9BndsSIyQP1P9OIoVHqf8wAmcf+jz+OVtD+JDeAIdWGUyU6MOfOtLwNf/yv89HN7DeeoH77r+2aQ3KRTxVFBQuPbITDOSpF7jja1viL1ko2d5A9i22yef1TJvEOPnaXJwReB2Ik1Ha88A8IqHecN99kdUpgJBunhDIZbq27t9ZcZzRZai6MHUdd7c5ejDZhNIxQVpaIryucfypmP5yqbrAG4ZsIO+sUkXYy91Y+kEovk8Uo9kZD4XUkBG7MyXg8V7NZ3bbV3jkZFbEbI/dc2+1BUQCpN41quAK0il6/qGLzkqMxwW6iZ4DTiiPzccopEI4PrDIhDedYF4J6CHSAJdl69Vy+Ka0kU5X7SmmAFez6EIr0urSSJnmOwplKNNNY1Kp9z2kGgLmRrz+5Bl7NOlPLA0G3yoq5TEgIY0I5gMkb4wvJe9zbOT7PUMBPmwVcxSbR3adenH/gogZ6r/yT++hKlFTvWH9u/A/9Yew3ZsX3kBVhN44mvA33/Bz/Dt3wa86Z3s5VSE87pCEU8FBYVrC8cBzp7kzU66ZCMRYHAnY5qmxnhD7e7nza6UJ0GzhHvdDPilzWPP+H1u972G5bHvfRPITjM0OxqnwnnhtBhXOc1/m4aIxtE5qrLpkFCYIsg7GqVzuWEDyRhJsZxp7nokgYbO6KFGjQQiEAacZks80SJINc0D17fkuCzumxQ9pBudlbjZcVlpAIKcyZxYTec1IUdYSgezfEhYkJPZ408XCkVF2V2omJEYyaPdBFLdQO8QzWneqJ+YUC2yZ1Tz/IeoUNhPhygL8qeLvNl4kg9c0aggmgUxhrPuB8yXCiSNiTRJlaatP1kiO8tA9HzW32fdYOVh323cp45uKoAXz7BSYVtUaXsG2fsoZ8NfBxwbzeL/e/wYTo7RTCad6vvvtPF1449wO25f+cOOAzz5OPDlv6B5EODfjn/6S8B9P7X2+FCFawJFPBUUFK4t8hlGLy3Iv9PoSg+FqWzOTJA0Jtv9MmpXr/92w6SKOTfN8OiObt40OrqBn/oZZg4Ws3Tb5nMAPP9GYxiY7+UzDd74NR0Iij413aYSm+4EAiWSiGaDxKBWJSkxQyzh1yokxHZzfjeuHjxhhvcAT6mdVxWaLno6Icrp4LUQS/hDBULCSGbVSfICAV4j23ZQ7ZubpomolBckMEK1XE5xChWBC6f4UNIzSLVQAxCO+/FWls3lBgJ8kAL8ZYVCnLxjiKgoWcqXymq5KNpOgrwmbZvLzc8BbSLHci1USsDxZ6nEdreYlGyL048A4LZ7uQ0d3fydLRf5eiC4dDb8NcToXBn/c7FT/WVfROrlZ/Gnof+Ch/DQyh92XeDpJ4AvfZ75qwD35Q3/DLj/dfxdVtgwqKOvoKBAeJ6vpAC8KSdSl3ajKeVZwpPGn7Yu3pg9d6kDXtPEzdIjYezpF+MHs8wn9Dwup5TnDd4M0DCUm+N2yrF96Q7gwF3A974OnHzeVyAbooQZS5Ioeh5v5Aa4zrpwxu87zJuq7JU78kN+tl7lciIxbmetAjQ03pQdUaq/UuPPkvxMsTwXmM/gdC+zrKzQAheALtofRL+oqwO1GgCHznLD9HNWdZ0l5XoFOHOSZfCUyOicHBPRUjrQFONY5XmKClNbpSISFoKAZwHRFFDSgIh0tovSeLPhO+tTbXz4EqYpy7JgwYBuOTBjcZiRGDA3KT5XF0MPatyuPQfXp97NTvIa7xlc+HttBqh4zk2RyHb08OeyDH8d4TvVL8DztHmneuOB7+EjiQ/gHXgHdKxQEfA84LkfA489yn5ygOfxZ38e+Kk3LG+WUrjuUMRTQUGBN88zx4CZST/iJximKrL74Mqz2iU8j0rkyEmSNkNGyJwSoe9CVapVRKi2xtJdboa9lLbN8ZaODczN8Eaam+P22BbJnitKpNJh7LpUU6fGuO0v/IRl0kSK7y0XRX6mzWVYTTH1yPP7MY2A6GNr52dnJ/l+ma1pCiNLpcxlBkROo/y/t0wJ/WogEGDp1bUEUVHE84ogR1CGQrwGHRfQ5MQmAAFNzCOPAqEA39vWARR1XjuFLLNiNc3P3NR1fqZRFz2i4uEqHPPL56YOtPWyXF/IUeEfOcU+w9a57PC4jqefgJ3uRCVfQKNSRS7ehZBdRyVmoa23Bz3DcRjjI/z9SXUAg9vZorLeKUUzU1RPl3uYlI78Qs4nntcRcqb6/37yNP1Z0DCz58eYffAx/FbXu/F/4fcRwirE8fizHG957gT/HYkCP/1W4OG3XPqAC4VrCkU8FRRudtg2JwVNXOQNp72LP69XqRrYNudFr1aempkAzrzIm27rBJVmg68Vc6KUp/lmjGKeN/5oguai/mESyTMvAU89wWijtq6FEU6VEm/Q4xe43ImL3Ma5KS5PmkLMAPs7HRuoOf7McXm/laMtg0Gge5CkYnqCpdXOXm6vpgtThVCXAiE/BF7OdL8a+ZrLwbYB7zqN1rxZ4Dq+mg+I8rv4udXgNSIJpGbwWpQPKJrGcxKOsGTruWJykjCoweP3+QwfbqolYTxzgaEOqm6NBt8TjZEIDQzz2q9V+LuTy8CJp5DXysi7AbQ1a+ibO4dy73ZkQ3GMTBfghWz09w5C23eYvy/yYexSjsGqFYzLHVRw+ZAz1T/73eMoCad6of8kRh76C7x7+HX4bXwPKawS43buBAnn8Wf572AIePBNwOvefnVc/gpXHYp4KijczCgVgJeeAY4+yZJytQy0d5LwhaNAZ4AELzuzcHxeK1yXJoRinl/j50nIwhHhvNVoaPBcRsDE26gUzUzyhh+OUl2amSCBdF2O0pwfF9hF9cJz+f6OHkFyo1SMdIPrKRf52XIeSHaI/anwZ0YAgOuXI2UWY61K1RUaMxPdGKNizltAueCXXTWNJFr2uunaZZpcVkNLHNO1HKepQLiuP51IzlWXcUlOEygW+H0sLh4EPJG2MEIS6YoHGjMoUgiE0SzSFIMIPABCnXds/r9R5QOMYdK4FAyRrEYTQLUMu1GH05hDtKMXbroDbjkPHUBHPY+G62EScUSHD6LNDAAvPMXfN11nP3Tv0Npl8fZOKq7LHg+hAMeuYMb7JUDOVP/0t17EVJY9zZX2CZx9zefws/tvwd9oX8YABlZewOg5ltSf+zH/bZjAAz8LvP4dfhuOwqaEIp4KCjcrClkqnWdeomoip/SMnmepcGgnb6iaxr7NlYhnIce567UqCV4pT8XHdXkT0wNAKQvsv5M34HKBfWSeS4IbClOdzMzwRtwzwO9t8d5mne9zXRLNrn7gxLNsAXAEgfREf121yp/Vq7wJZ2ZAs44oiXuCYHgeXeoamFeoa9z+YJg3sMHtwPmTJOKuxx5TxxZZjy7VSK+FKF4VqHL69YW3jLonCL90nVeK/nm3LRJHwxSjWYX5rNkQ7SUGf19sYSCKJfjZ/Jw/pctqAtUc3zc3TYNTqUiiFAyhXqrB1QJwowmUE9vgajp0x0Zh+yE44Sgu1DR0zGbQNjLJZUZiJIznT7Ll5MAdVOxXQkc3W1qKOT8HFOBxyM6yt7q9+6of6cVYyal++E4DjxufwkEcXPnDU2PAlz8P/OS7/LemA/c/BLzxFzekRUDh0qGIp4LCzQjX5ez1ckncgDSSvmBIzC2f442zu5+q32pjCS+covKS7hBjJy1fcahWgGaV/ZO1CrD3NqBZo2pULPBGmJ3hvw2TSpK82etB3lRqVSBQ5Mz49m6gVqZZSI7IBHijNwKMoCmXuN50O3/e8EgWdY0RSq4HBITi5InPajoJg4w46uwl8Th/kn2fjjCE6MIV7zpYMo/9qkAaipTiedUgVc15FXmVBwbLoiIZlL2gzkLSaLt0xEfi/rXieaL07oryusWHpXqNv0Ny5GYsCUxeYLk/3SkewvJU6g1mtzoBD5V0D+yB3YCmQ3NsBMt52NEk7FgSiewFmJkzwHA/qwASiTQf3k4f4+/zYhNNIUfCNjfJh8LJHElrZw+3v17jg9reW6+pAWdZp/p9j6HzFRfw56GP4tV49cofzswAX/kL4If/4P9+3PMA8KZfotqrsGWgiKeCws2IQpbksq2TJCo7679mmDRh5GZ5Y7IaK5sXCnlOWwkEhTGpwZ5MmUNpmlRAo3Gqh3OTfnZhIcPPZWb5mpyL7TpULAMhkrBInDfuUASAR1IZEJNfdGE2MkxAK/C90ERwt3AVy8lB9aqvTMlxf67NZcvg7GbDL63HE1Rs5yCmLArC4rn+qMQrgSb6CReQIO/a8NmbFfMqpMOHD8APW9fEAABp3pI/a1qAJxT7gBirKsetmiLRoFwUrR/NhW0R0pTmehyhGQwCgTZePzMTJLZtXXxoCovrt1oRZf0g9EAE5UgaYdG3qYnkhGA5C7NRBSbPIBDRFpJOibZO/g5mZxYSMTnnvVbhfnT0cD+LeRLSviEOZujuW79J6RKxklPdfeBJPJL4IH4OPwdtpWyyQg746heA737VfwC+7T7gze/kBCeFLQdFPBUUbkY06ryBBoJUSGanSMyk+zMYomqTz/IGuVz5LjcHHPkBcP6Mf2OV4efxhD+Bx7FJDGsVus+lI9ixgbPHGGsk51UDAETsEUTcTSHH0qCuk0BaDUbPyFJ+Mk3iHE+yZxWeKM07JBYG/BnccjKQESDJ1DTfcJFIsZRaKlKVymWoxDrCxR4Ichtsy1daLxeGKaKUNKGmLiKfCmvDDPijL1eC4wJY9J7W7zXwIcJ1+CAQi/Gac8U5D4XYw9nVK0rmYupVowE+JCxKNXBlNJOYhKSbvL5tl/2V8QR/z+o1XmOBIH/XCjkgHIGx9xbUAm0wbBcBQ0Ns5gI014Nm22jaDtqnLyDV0wGUu3i9t0I3uD/1mv+zZoP90JbFCCWJmDA1VYoknV2rlOevACs51bMPfgX/vutX8Sv4fxBAYPkPl0vAN/6KIy7l79u+wxxvuevANdlehesDRTwVFG5GGIbv6I3G2Vc5OcobajhCYloTWYT7D5PotaJUAF46yh5MmXNZrZCM5mZJWiMxkrRkG0lfMQe097AkD7HuXMbPwzTEnyPdAMJBrt8W87jrNTEDG1xWOMbSYs8g3cGuQxXXNLmezKxwsoPkJJfhDd4I+sqqnNtdKnAbO3oYQj8u8v8adfZ2eh4Q0H1yfDUCtB1H5IkqXDrE1CE5jWhVnu6xvQItJqL5lzz/YccDEI9zWs+FU1RIO7v5cGMGmfQQDIlSfIDLkmSodVylJ1owgkIptS2uv1oEunv5ADd2ng9K9SrbRhyHy4ynEN21B91lF9NzRfTkRhGo5lDu2Y5MuA1NF9jbXkS4VqaxZvse/o4t2N2WfQJYni4Wls5cB/jZcpFpE1eZeMqZ6o8+8RJKFRL9Qv9JXHzoL/Grw/9/9v47SJI0Pe8Ef649PHSkztKqq3X3aMxggMEAIEhCEaBYGiVI49rZrXHteIvdEzzSeMuzs8PS1uzudm9Jwy6XC4LkEgSWAAZaD9RggMFM94iWVV06K3XoCA/X/t0fr0dGVlVWd3VPd091TzxmaVWZEeHhkeGR3/M97/s87/fxX/GHVLiPuhpO4Lc/A7/xs/I3AKTN5od/BB77wNt6nnN8YzAnnnPM8c2Iekt6zqZB7EtroiZ2i7K3P5LFaGFJSFswmUUtGQbcviYEc/XkbLZ6a2mmQCWJEFijIv1svc7M2R5OpBQ58UV5abQkFinPpa9SIfmVWVbMQ9flOW1LekRzBRtXZDHfuS1KlaELSTSMWRC4U6i38WDWx6brQrRLnmQs2p6cj67LxBp0QBPlMwyAwvkcx1JW1QvVNPt68zvVESMz53gw5DJnXeXcYQ4yzDee437HTPNCbbYd2ew0F0X1rjblc5GloHSoN4p8zmJ6kFP0d2bFcxnGrO1CccjAlgs5rdTk2i+V4dQFOPeofLZGA/mclDxRWYMhxmjIaXKqVkiQxezW1hmXFvFsk+P1Eq3KMbSbV2ST1d6DE2dmry0M5LUcdnSHE/n3fiNY3ZJs1A5Ghn59mDrV/8ffeZHdQ071a5/+t/zQY0/xC9ovs8J9DEBJDL/7y/BrP11ULpC59T/8d+CZj83nqb+PMCeec8zxzQjbkf6oV78qC0+lLguWV5Gyu2nKgthtixqTprBxVRZmuwRf+WNRGSe+LLyjoaiHbkkW8SQqRg66QkiHXek7ay2JKmToYixy3GIaUUcWniyVc0uVkE7ggCD0u6LKBr5E0GSZkM8wkpK7VxaFp9cuzETGrMRuFrE2qujbe+RJea17WzLn3auKejvqFbFJBXG4pww+LdPOy+HvCnRD2iKSYqjBtJXjbm6pF0uZachcdJUzMxQduvO0r1ZDlEzblg2YbYtxbW9Lyu0gmy/PE8Ww35PPx6gvGy3DKD4XkXw2YHZeSVzEdmlF7ueCfMb2tuVr6hw/7B7f3ZQ56WsnMNKE5WGftOLQrC+jGTolDczujqj8/qDICh1Ln7NTEmI76MLJs7PKwcE5vV4rQiafwbeB1L200eXHf/tFLt+WrFRxqv8UH/2gx08Y/4oLXDj6gWkKf/Sb8Mv/Xj67IBWYv/C34MPffn/SPMd7FnPiOccc36w4dlqUjltXilF8zNRFxxWF83Apr7MHz//xbF6zU7jKo6JsnRdkbzyUUYNT0ukX+Zqnzhdl8UJF7LbBfxWieKYUeWX5N8+K/E2jWMSV9Hxd+qqQyqhwyjcW5KvfFvKqMlnIdEPIRJrIcbwK1EswLEwhaSKvud8RojIaiCkjDKSMX7GE6N5DMOfOn3cNevHe54UqOW17yKah6YfL5hlgFH3F2ux9B/mZ7cjjpj2Zqgh8n0YlrT8Ga8flGrccIbJxJNdcMIFaS9oxylVI+6K660VZO1eihGuq+L82u/4WV+RYTkmusS9/DtZOColdWBbSO+jK5+346UNtKDmmYVAru3KeG0WFwfUkOH5vS67PP/ld2Vx5FWmH8cfw/B9Jafr4mYOYJpnKdNf0sWn14fQjX9fbdKs95l999mX+5JIYFKdO9WOf2OF/c/6ffIyPHf3APJNIpF/4t5IcAfL34gf+Bnziz8hnf473JebEc445vlmh66J6rhyTRSxLRQ289oosmlPSqXLp/dzdLPILdbDLszKiUxIlaHkN1k+KarFxTRaO7r6oieXCVKHULMQ9K0YRhr4s2nGhkk6zCaNilrpRjK2MQlGqgok81ikVwdxhYfgJZsee9mPqRa/oZAxGffb4aeB3mooaGvhCOrMiFDzO7zWOfCNxz0z39zmmG5npJkVNleeir/PuRCSlQKUQp7NWi+kdXE++okDe84NJP8XxLUs2LdONRlT0bgaTIsHAFmW/3hTSaBYDBBZWRCXvdeTaCXw5N9MuzGoNufb7bTkftySbmjCA/hVpL1lalT7lC4/PSCcIETUOj+tsy7HyTK7r1koRARbLZ+uJD4nJTiEE99LX5BiLq/L53rgmIzanbvg0ESJbb90/n/cN0B2H/Ns/uMyvPX/rDqe68akv8d9V/zHfy/ce7VRXCr78efjMv4Gtm/KzakOC3z/1vbPECSBXiixXmLqGNi+1v28wJ55zzPHNDseFlWLxmWZglquzWei9fVEnOzviFveHsgBPzT/TyS0TX5SWzq4saGcuSAlfN8TAsHFNFsszF4Wo7mxK3+YgLtzqSbGAFz2gqvgyTTmGPyrGYRZz4F1PFvNRv4hYsmaqWJ4WbvmCrCSxLOBKyfmOh7C/Jc937Bx0tosA+rEcI42//riktxPfDKTTKGaF3927qdQhkqlmPb15YUq7G3f3zh4OeDdMMYqZtjw2juRno75cc6ZZjEkNikgvm9wtkZkWyp+Qt1Zx1o6j3b4u19/yMVHrdjaKsZtFQoJXgWpNMjNBCGfJExK4fko+Z/2OXL/PfHQW5h5HMr1rZ1NaXrZvS7yTP5RzTBN5yVEo42GPnS42YkXOrIYQ0P1tIbaLq5LNqetyzEF31q7QXIILT8p1/yZwP6f68Lt+jX+09J/xI/x/MY5yziklU9J+/idn05O8Cvy5vwzf9UPy2S7gRwmbHZ/bHZ84zfEck5OLFdZbHrY5V0Lf65gTzznmmONe5LmoEfvbh3rGNFFT4gjWTkkZsb0rtysluYBXXxEV6OxjsqhMy6Inz8mCt3Nb1KJ+F/Y25Vh24RLWffk3SwoneeFAn6pfMHO2axQxNWnheC/6Q/NCqcwzICkiZqaRSciibRhS/tQtMJNZRFKaCHnI8m8OovcwQdeLMaR6ofQdYbw66O3MIXkTavSUiOaZXD+mOVNSTUt6OKeKpKYBeTGFSydVEE58+vV1TEDb3iVdPsFiuY4z6Mlmp1YXc16/I3PD80z6N8sF8Zy2kDglUfOrDflaXpd2j2AixDPw4YUvyWckz2UDtHFVNnKWKxUF0yxMdKaU1Sf+TBk9jEpNzicK5XU9+qyU3of9ovWkLKa/1ylnZ7lifxCw1fOZRCm2pfPa1pCf+9IVxoec6pvf/TP8/VM/xD/gDyhROvpgr70ohPPyC/K948J3/xD82b98T3boMIh5/uo++8OQsmtiGQaDScQXr044Najy7JmFOfl8j2NOPOeYY44ZPE8Wra2bUt4rV2elL9MqeuVSMQs98pQspO1dWdBsWxzAKhMzxdatItfQlIV1eU2IQ70l6ksQyMLnerLg+2OgUIuSSFzGuiGLdziRxSqOi1J4XMTZFC7lLAXMQ2XUAofL5Vk2MyrEoZhIDFPmwo8GonI9TOX1bybkOeSFwpzfp6RqOwV5nJLSQs2mIIsPBFX0IutyvWq6qNyWLceZjkQ1bbIsIc4ztCzCrSbork2iGQSTCTulZZarNqXmkhBPpySfm0mRzVmpikHNH8q131wQMn24nD4lfXEk5/C534Crr8r17Y+kR7pSl77TwC8GOqxKLJOmi9Fu2JPP6N0Ecuren26gpqX/auOBfktJlvPCzQ439sfkec5md8IfXNpg7IvC7Le2uPHp/5W/8tgH+cfar7DAwtEHuvka/Py/gRe/KN+bFnz6++HP/9Uj58orpXj1dp/2KORYq4xeGAyrJYskzbmxP6JRtnlk/cFexxwPJ+bEc445HkYoJeXgOJJFpdaY9S++k9ANMQB99U9k7rluCKlziikr/kiUzjCUmc9ZIipSGsH5x6XPctCTRbNcKaJmElFtpoaj3r6onVkq5T7LkuNO+9cMHWIlj6tXRAkzTCGiN6+IQqTphZqqZmroNKj+9UYi5krU0RuXhAjkqsgKZU46Hxoc8d5pupjQDO0uNfp1opOOREFUs0wUb5XN+kG14jh5Rm5ZpGmClmUy/IgcpXQ0t0TVyOnoNrdOPcPFpfJMWVxel6/unmyc7NKsDzOOZeNVrR869aKVJInhS38Il18sPgsTaTtIU9lwtZbk86Hps4EPcSymIn8k6uXdYfKTsRii7jYUPSCu7Q65ujMkSjN++6VbbLel73U6U/3pi2U+V/vXnOb00QfYuimmoec+J9/rOnzyz8L3/3V5PffBYBKz25+wUHUPSOcUlqlTcS1utcecXq7OVc/3MObEc445HjaM+nDjNVESp8Sz0YKT59+yEeCBkSaiZk5HWg47hSvXkYXPcUQp2tsRdafWkqgbryrqy62rQgQPB1bbjigdt68XJUxDjq8bcvxyTZ7XK89mY5uWEFBNkz62/R15zLT3M08PzTM/RDyyFMnivB8ZUYfK8moWoj/Hw40p2fy6o0+LawdLNjRJPnPI68ZBhFauG2RoGCoHDBSilGe2i+0P0E6c4lr1JMceOUlFK/pSnaJUv7spE6+GfVE+ex04flYC6Q8r8v5IKgajIsTdK8tmS9NFxVRKejKtYs574MvfhmBJPoe6KW0m1YZs6KYIJkJa10++pSiiOM348rU2v/vKbW7sSID71KneemaH//Pe/5EL155m9Yl17hk6tL8Dv/jv4E8+O2uT+eh3wA/+rVkf+etgEqVEacaSfTRhLjsmw0lMmGRz4vkexpx4zjHHw4TxEF58TkhcvSWluTQRFfHF5+AJJQaFdwJKwZWX4fprokpUa0iYeiBO3+aCBMrfvikqz/K6ELeFFTEbpYmMxJxG1ZiHVqXRQMqOcSTlwmq9mKeeFAHWzGauR4GoqheelJK4P0bilPqiHhmm/Py+eIOyq8qLUYrTMu0h3BEwPsf7D4UanhVlcK3oAc6KnkozF/VS18l0C0vFZJqGEU3IShXsyZC42mB85inM/j7qhT3IQ7l+W4sz1XN5XfovA1/6G6fGINuQDZM/lOv/5AUxuU2HORSGJjnVIgc0mMjfAQ05z14xHnZh+SC6KWvvME4U4+GYTGmok+epVxdpvMnfTncc8i9/52U++8IWHHKqq295nv9D+A/4aPtTZOTshgHjIMG1CvLX78Av/xT84a8f9NQOLn6YjU/+RbTjp1n1PJpKob+BM11UTo0sVxj6vffNcoWuaxhzh/t7GnPiOcccDxM2bwrJXFmfqSOWLeSuuydu0IUVMRm83RgNpC+zsSjk7vY1+b9WlDd7HVmcA1/OySlJC8DqCVFu+l2Z+jIZSV9aY2HWE9rdkwXX9US5zFIpRyZFdM20Ypql8p+SJ+HYJ84IGd/2pGduVGSCGmaRmUihgh4im9NFaTqN5b5EUt1725x0Pvz4ujYH00im4r+2NdsopYXaqGtoYYirAjLLYbJ4nKTSJHM9lGnRP/MU9t5tjnW2cDpKrvfJWB67XLjILzwp5LBSFfJ49ZWiBN+RJy5X5X7NJRnRWm/JZybNwDpEqrzqbMO2tCrnvnZCSGeWwfpJomPnuHF1g15/RGQvEDWXGag6pct7PLre5Nxq7Q2jiCZRyn/8k6v89B+/RpoI+du78AV6n/p1/mb2t/nIjf8ClWu0jZCyY862a6MB/PrPwGd/6SAFYnjmSZ5/+ntpL57CMgzS2z2ubA85t1rjsePNIwnlFM2yQ61kM5zENCvOPbf3/Yj1hTKeM6cu72XM37055nhYEIXS+1ip3WuSAVmcphNKFpbvvf3rRb8jC1xrScrcveK5KnUpj4cTeGVD1MaFVenh7HXk5yfOydQYx5FFvd4UNTMYyzGTSMhkvyuKpmlJH5umC5GNir5NszB5jAbw4vNw8Wnp7Vw7KbEyNy4XRgpj1hOq6dJzeqB0TkvtRxDLOd7DKNjitDT+ppIHtFkYvePK58cuFWYgZzbRKo4gA81WqCyj1zxOcvIxcsMkcz385ZOYkyHsbVItm9jRQErkrSW5xkdDIZlxDE9/pHCx1+Hpj4qyPx3bWm/JeYxHsok0TCGh7Z1i9GVROp/elhRGOseVx8bFxKQLT/JS3uBqw2XldAnHNHCAGtIv+cKtLp5jst46OjJpOlP9J/7gJXxfSPlg/RIbn/4Z/rz13XzPxk+y3824Eo/u6Jw+XdFp/s5Pw+/8wmws5/nHufltf4k/1VZZqrkct2f0YhKlvLrZx3NMzq7U7j6NAziWwbnVKl+50UafaNRKFpomCmhvHGGZOmeWqvNMz/c45sRzjjkeFqSJLCblytG3T2dR3x2d8nZhGjkEsvCdPC8mgWkJsL0jxHBpXUrhbkmIXW8fXvkyVBpCXoNA4pMaixKt1N4Vwrm/W7hr67IwQ9GPlgC6vL4sE/LqFm753mfh9Hk4/0QxZSidZXuCkNuDsYgFVJFpOMf7D9NRlLpeGN+K916/TwTTAdQsY9MpSQ9yry2bqOV12cwopJUjl5KwyqG7/iTbC+eoVD1UY4EkDKi++gIlx2YpHgixdIt+RNsFOxKT0s7GzJSnaUJMl1bvdLWDfNabS9IXunZclNNrr4j66bpCQusLsHpcPoe6IZ+XahOOn2ZQX2HzlW1aVeeense6ZzOJUm61x6w1vTvImlKKP3p1h//xsy+w15W/J5PmFje+86f4G499jL+699N88Ws+18cBFddmoeKgaRrJZMLpl36PT974Q4y4IJwnz8EP/Qjhox/klZe2qaJw7TupheeYBHHKjb0RJxcrmMb9e0/PrNRIc8XVnSG3u34RQq+oew6PHW+w0vBe532e472AOfGcY46HBZZdhKBHd5oFpkiLzMlDkz3eNKY5l7pxr/Fg6oCdxs2UynDmUVGFbl4RM8SJc6K6dPdlwY0C+fmgB8uIkpkO4bWXodEApckCv7cppLLWhFIF8CE1iqlDsTiM81wWW614jIaU0a++ChvXZ9OVAOLsUK7jUS5o3pzZeY6HD2bRTgGzdg9dK4RtBZoJFGNazcIF/rpvvJJWj0ZTrrthXzY466dEtQyDYtyqBraDs7/DqdU64/OPsTeYYLX3Wd98hWODm1Q8B2c8EEJo27PECceFblc+YzubcOEJOaW9Tbhdg0efkR7nKTQNTpwtBjV04MwjUKmIuXA4kL8Dx07JYx57Vj5/bukgQmnYHhMlGUu1o804tZJFdxwRJdkBGXxpo8u/+O2vceW2GIdib8C1b/8PfNcHl/kp499wnONErYwX7CukGQRJShbHPH7jC3z88mcpRxKKP2mt4f4nfxf9g58EXWc4CPCjhLX7EMNqyaI3jhiHCY3yvWX0KXRN4+J6g3rJYqs3QSlFs+LgWib+VDm1DZYb3qzHdI73FObEc445HhbYjixkV16W3q67iWG/I+pHvfXmjx0XIy+3b4lRyLLF9bpybDYxpLUkZfV+ZxZ5ouvyszwXA8TyMSmpjwayUI56QihdT9zClZoopZvX4corooxalqihgS8L8mQsC2ccHTIW6ZLf6RaLVp4JERgPxDWvGVJuPNzfdzCL+66eP12X++fpvNT+XkZWbIBUMdqSwgQE8v00jkjTir5erZhoNB2zycxZrRlCZBeWxQ0+8WfZl/22bOr8kZS+QYx1QUClVuOj55cYXr+Gf+sacdgjUjpRkFOPIuy9bawoKmay69Ln2G/LBqtalTQK3ZDz7O7LKMtydTaOFuSz9sQH4dol+eyZFpy6MLttaU3aTZoL90SqveHVrQFKoZCZ6v/ysy/yp5c68us1Q25+y2e4+AmfX3H+XzzJkwcPGwUJFcfiQ6cbtF76PI9/+VepjLsAhPVFrn/sB7l66kN82+MnqL8F5/zrYRjEXN7qs92bECU5SilGNzromobnmAcxSzXP5qmTC6w15wroew1z4jnHHA8T1k/LArW3KTEpbmnm/HZcOPvI604bORJRKKPqdjdF1bQdKZ2/9DzsbcOTHxTC57hS0n7lK/L85ZosphNf7t9ckID4oMjjvH1dlEnXA5SU0I+dEcPRsCCkq8cLAjkS5dQfSz5olgoZ1YsSu1eV85oShen89TQtRvxxiES+jqo1LcG+0f3mePihclHMj4rNmsIw5OdJIqQTig1b8d6rYlNiFBFdjiufqfFYNnB5LtO5bl0rJloZ8tDOnvwbx+RBwPCFr7DfD0jLq6wGAVoSMUoNSDVa/R72NEuz35Hnd0vyNSVl03L77m1pITlx9s7XsbgqJfd+RzZYpiVl+cPJEEegVrJwTINJlB5puBkFCZ5t8uO/9RK/8eWNQzPVf5vqp17if67+Ez7Fp+55XJ5lrF17nme+8it43W0A4nKDzU/8IHtPf4oYnXQUkuez96RWsig7FqMwoe7dW5UZBQnVkk3Zvf9r8sOE567u0x6GLFRdFio6V3aGbLTHeK7FxWqD5XqJPFe0RyFfvt7GsZZpVY6oEM3x0GJOPOeY42GCV4YnPyx5mHtbQuwMU5TJE2dfN3z5vrh5Rcp+y2uHxl8ixHZ/S8p6jz4jP1tZl9Lh9i3o7AtBrLfg2Y9Lj+egJxmFcSh9ZklchLnHsLQiX73CpNRYEHNS4Mv3zSUhpGkqiqlTkvvEhbPdKEjGNGYpDDgwCE2VLuAeAqIKw8m0DSEKpVw6x0OG19sIHHGbpgvxio/IWdWKKUNWMc0oTYoNSkEe0wy0TEZN6oYMOsizwsnuwnpLWjx6begOZBpSa1E2P2lSJCdYcPsqXbdBb7eNuXIMzzJR6QKlzhampRNPJoxNnfqoj2EUqrxXkcc3lrij11jTpEe637mXeIIQ3zdpGqx7Nmstj+u7I2zTu6N3sjsO+cJre3x1Y5/skFM9+q7P8k+X/gF/mf+u6J88BKXghS+y8HP/muXb1wBI3DJbH/t+dj/4XeSWlMgnkxjXMinZs02wa5ucWKzw8kYX1zJwDpXBgzgliFMePdbAep3+zlvtMfvDkOPF1CI/TOj7MWvNMnGasdn1aZYdLFNnuV7idsfndtufE8/3GObEc445HjZ4FSGCpy8IiTIsIYODnpgWLEcI24Mon2EgKku1fifpBHl8tSEE9+R5Ib1QlPUWhVTmhds38GW6yqWvycLdWAQ6MHZFaXJa4ugdDWflz2n+aL05K++Ti+KpafL8TtHrlWVCMnptmVCDBHk/MDTkvNIYIauHQ+TnyufDgdd7D+66bWo0i0PufP+04prR5HryqvKeT8Zy/WTFYAHTKMLhi+vMNEWRdAtjkaZJad3xCgJryWdtiuYiLK2hxkP8Sy+haRqWJZ+ftCTE0gp8nHCMSnPyYIhhmPLZjWMhkI2jWmLU2zqBTNM0njjRIklztroTdF1D0+BrNzv86fVtkkjU38H6JXa/++f4r079Nf53/C7WPcnvyGf75/41XH0ZAwnLf/Xx72T0bT8giRQF0ixnMIl54kTzHhPRhbUaYZxws+2DUlimTpzk6LrGI+sNTi9X7/ta0ixnozOmVrIOyunjMCVJM+qejWXq9MYRwyBmoSpEs1qy2OlPeDxrvq5haY6HC3PiOcccDytcT1TB7Q2ZeTwacBAnU1+Acxcl0/P1EE4kaqi1ePTtXlmmjYSTGfEEWfT7XVEss0zyCJvFMfJM+tjCQJSkqizS+AOZdtRYkIV90JMFv7lYqJx98GrFmMpiHGCaSmk+KXpQ42jWz/dmyGKeS3STpgvR0ArVCwpDypx4PvQ43Ks7NZEBB6716XvreJJc0FiSyVdpOiOcWTFFaFo2V8j/XU+uxV5nlqxgO1J6nw5psGwhp9W69DXbDnkYQK9L2XHRentY4Ri7v0dmGozXz2IEY4z9HQxSLH8krSXTaVt3E8w8l3Nt3meu+VtEyTb58PlldnsTPvvSJr/05asMRwrQ8VtbbHz6p/mRx76V/5P2a1Q5gvhdvwSf+UlpvQH5PXznDxB++odp78bsDgIqWYhtGoRJxiRKOb5Q5twRsUi2afDsmSWOLVTY7U8I4oyya7JS91isua8bIJ9mOWmm7jAMKRSqeIiuaRL1e+izrBdRS/m8l/s9hTnxnGOOhxk7t6U/0zCFZBpFnEq/IwvFUx+ZEcKjoBuiSGbZvYonFDOr9TuNTOEEXv2alOHzQr2cErtCCSKOCsPEHvjijsVypIdz9cQslLtaZJJOp6wMB3JbyROFyTQhySCMRKXUDMS2/BYXEpVDmsNh8WPq0p/+f46HA3oxxQcl16amz0rmd2d05kpK5/pUKS/L9TiZiFrpuEChsk/Hruq67F8cVyoGxUQiMREN5ToFuc0tS/h7tX5nhm6eYYUT9GCI6XexJiP0JCQpN4irJTK7hLJsssainFvoS2rD7Rsy/GBKPvNMejsbrSM3i0opkizH0DWMt2DWubzV51/89le5clsijmKvz/Vv/2n+3AeP8x+Nf8cqq/c+aPMGfObfwJc/L98bJnz7n4Pv+2vQWKAMfLSWstEec7vjE6cZZcfksWNNji+U7yilH4aha6w2PFbfZOyRaeg4Bbmd9qu6lomu6aRZjqaJmntY2fTDhNWm97rl+zkePsyJ5xxzPKxIU7h1RRbaw+TStMSMsLclBp+pwngUKlVRFAf9o/vHRn0pt1fq8n2ew6UXpKS/uDozN6hcXOr723D8jChDSSxKUmdHomn8kSi0nT04dV7I5fYGlMdF750pRMAsIqN0HShUqVpd1NWpQ/nrVTBUfid3PVBR53g4MH0vpgkFGbPQ/yPep8KdTVaomlnRJ6wKFdGyJT9zmvOqG9J6oRtCJL1KkagwEaVzYWWW/zqZyOerXL2TdIYBxnCAV6px26yzGnYhz4krDYw0wdu9DklC6FQxj50BU5NNm+3ItQyzEnWey+f0sWdnKRJAludsdifcao8YBym6DsdaZY4vVI406NyNW+0x/9NnX+CLl+T5pjPVn/5Ewo87/y0XuXjvg3a34Bf/Lfzp7836oz/+nfADf7OYjjRDyTZ5ZL3BudU6WZ5jGvobjr18qzANnROLZb56o0PdszB0nVrJou5Z9CcRhq5TdixqJfmb5EcJCjixUJkHyr/HMCeec8zxsGLYk6/WfQwH1bqQvOCuMvlh6IZk//W/KIthtTGLqBkNZKE+cXYWyN7vCLlsLd/pqNV0CbjevgmXX5BFPS7ijcplIam2A2cuSikxCuW8tm6Jc97QpTQ/dRZryPeTSZGDaMq5DQsykU2JyFvEkVNt5uW4hwr5oR5epYDp98UmYXqdTmOTpvfzRzLpatqTqU8HChQJCUkiBDVPZexqY0E2SVEoLR1x8aXpMuzAK88c8VNkqSj+msK58DhJaNHZUawNuxhJhJbnmP4I3ynDiVM4njvrSV49Ia0ojSXZ7GmabP4WV+7I4M3ynBdudrm6M8Q0dDzHJMtzXt7osdnx+eDZJRZrR5tmuuOQn/yDV/mN528fcqr/FgufusK/rf4TPs7Hj3jQPvzyv4fP/cZM+f/wt8EP/i2JVnsdiBL7zmdmnlyssDsI2OxOaHg2JcdkteHRGYaMk5jFVZdxmOBHKYam8ch6nbXWPE7pvYY58ZxjjocVWTabS34UTEtMP3f0wx2BxVUJoX71q7BxTRa/chnqi3DxGZn9PMW4IKP2EQHPbjGF5dqrEixfqcr59TrQf00c8XEEl18U5bPektzPqy8LWbAdiWMaDiUovtqYzX4vV8UoEkeQJ0IwDhOTOd5j0I4umb/RYw5vDqZl+MO3m5aU05NDCvY089W2xTWulFxH03GUGkJU0SVZwS3JpsgwROE797hco1s3xciHIktSQt0iXTgOzSVO54rt7Bjd8QClaxhxTMUJsGsNKs1i0liayGfVtKQHO8/g3KP3Hfiw2Z1wdWfIQtW5w6RT92x2+gEvbnT45KNrd5SWj5yp/sifkH/n5/hvln6U7+e/v9epPuzDr/40/N4vz6aePfUR+KG/PcsLfUjg2iYfPrckU4s6Pp1RiKFrfOTCMp5tECY5SZZzeqnCsVaF5UbpHVNg53jnMCeec8zxsMJxZ/FAh8pz5Jn0qO1vC0nc2ZBFvnLEDOQkhtdeFOXRdkQJSmNZz4+dujfW5agS91SB7HVFQV1YFjVq1BfFaFREJHX2CkORJWMILQvIZSzgpJjZ3m1LH2jgQCUWwhAF8rxuoVRl+Tz4/T2PNyKdR72/Sh6na4BejD4tSJfKhUAaOrJsFfcln02viiPZyBwmvP2+9CBXaqI6lqtFrqcp5rMshYtPwWPPwLVXyXY36YxCNowGPgb13jaT2z1qnsP6+hJGso4adKBWxsPHLNto6HLMyViIrOPK84ehfG6mhYNp2gPS03mrPcI09Huc4ZqmsVRz2R0EtIchq03vYKb6//IHLzLx5fc7WL9E57t/kf/rqb/Fj/B/x7x7OfdH8Bs/C7/zmZk6/MhT8MN/RyYqPaQo2SZPnmxxfrVGmGToukbVtebl9PcR5sRzjjkeVlTrUvLe2ywiYIrJKJs3hMCN+/Lzq68IsTz76L1E8volyQRtLs1G9SklpPHGZVEdD/d1eRVZHKcqaq8js9ijCDq7QhLPPCIGimFPVKXWkhx/8yagSUmx1xaXuluC5rIQ0sCfZS3GIYwLEhxHxRxtnVmM0px4vrfxVk1capZAYEp/ZpbnkEkvopHnsqExiulDFAYijdk42IMfFMdLExleMJ1q5LiyCZuM5Vi6Ltdwa4mrW31euNWl7JgsRQPqcRfT1hn4EXGacXH9OJ6WiIqYJaKQJkWck1dmXFuk1x2Td9ponofd81lKtjD2tuSaNy2wHNIsp3Sry2q1ie6uk7l3tsqYho5SCj9K+KNXd/gXv/MV2l2pAPitLTY//TP8p499mv9C+1U87io1hwH8zi/Ab/xHOS+QaLYf/jvw+Afv3w/+DmE4idnpT+j5EYamsVwvsdLw7mtOmsK1zXtI+RzvD8zf1TnmeFihaUImg7GQuEpd/t3dlJLi+mk4dU7c5KO+KJuuNyOSk7GYe6qNOxVTTZORfu0dKS8urswWo6YswOxtimLTa4vqapqisg570ofpOkJG8xSWjsnxwiK4fTQQ8tjZg5NnYW9DHqvpkEzkX82Q0O6smI2dZhCMxFii63eV2Quymr9BS8Ec7yPkInwbBrnS0DSdXLfINR29XMdQStTNODpCWT00UGB6HSWJ9BObttw/KJIYslRybrc3CP0J3f2IhfoSbnOZ1G0RV5uURz3McoP+cEjHqeGdOg8bN+T6DgNIEtTiCjtmnY39iDSOqflD9q0m7u//AXE6YG11AStLYOMq+GP01iLlvAq9HazBNsMTF4maM7e7Uort3oRfe/GL3N6RAQux1+fGt/8Mf+GD5/iM8VMscleaRRLD7/8q/Mp/kL8HIHPof+hvwwc+8a4TToBb+yNe3OgxDhNcyyDPFTf2RyzVSnzgzCK1BzBQzfH+w5x4zjHHw4xaA576qBDEm1eFLFZq0k/ZWp71j1UbUnrf2ZgRydFAXLbLx+49bhTKon39kjh6107MCOYjTwthvf6qjLVUSNnOH86mDDkOoCTs/eZr8rwomRSjaaJkjvpynEF3ZhTRi2k0o6HcR9NnxGE6oUY3uKPfT+NN9grO8Z6Erh+YXjKAPEeRkVsOusrJi7ilKM0pxRMM/Q2yXqemJL2IAwsDIaLTAHrbkY3Uy1+GWpNJmFPabrM83MZPz+CvncVfPklp7xYLm69RzUDtmGTLDYzWInzXD4qSH4f07Bob7QllEip5QnDsJKsonEGPW1aDLDE5M9yRa3/tBMZ4QN0zuWo3WE8n1G69Stctk5Uq7A8Dfvkr17ixHcjvopip/qFPaPwr5//DWYqqRnpoI/b534Jf+l9lowhSCfkLfws++qm3NbD+zaAzCvnaLZmxfnKxcvDzLBdS/dWbHT7+yMoDB78PJzGTKEXToFF23lAxnePhxZx4zjHHO4E0lRJ1Z19KfZWqRLhU62/+WJWa9Ga5nhDJ9ZNHG47KVVl44mjWZwZ3Kh0qlxim9q6QyTSRxXDzOpx9TAxBmzeEMMaREMo0lcUrmHCwYA+6orCgg0qh70uwd6ksETK5C93CIa/pUpKcFKpnnHBAGFRhErkjQukQmTiIV3rzv7Y53mM4CAbXDkaso4Om62S6iZ6l6BpokzG5pjBcV0rwaXyvEUnlRS7s9CsHiuglx5XPSr8j13CtDktrJIMAf2LgWTnVzSsoTcft76MMk2DhGHngQxzLs5iWmJIcl3zzBp0XL2MnEXa9ymDxGLFXo3Xly2S1JhXNZrzXJo4H2AuLcj5OiWYypFKqsZtXWJ10iPd2+KV9+PK1Hhyaqb72qZv8h+o/4UN8SF5bd19U2s6eGP2+9qfyWkA2kd//1+Fbv2eWVPENwmbXJ4ozji1U7vi5oWusNErsH+phfT34UcKrt3tsF4H0uqZRdW1Or1Q4t1IvNiBzvJcwJ55zzPF2IwzEQb63Jd/rhiyObhnOPyY5mG8FZjE6834u97tLaV5VVMwwkH65YV8C6ds7xWQWV8rqayeESH7+twBNiOfuZqEY5RI34/uiFummkNYskYVtOkNdFRmMWS6LYLUBlgmD0ezc0aRH9J4Q94IwTEujqggJz/NZ794c7wFos7zNtwR5XEbBOHUdpdsoXSe3SmjKR0tT7Cwj1w0yQ8fwPAh1CW6/B3lBOplle1q2nOe0j7hSh/YeNJawTVHeEruEEQfUb7wIms5k6SToOsMgpmTqHD+5IJ+hm6/BBz9BcPYJrgzLeKZG5JVQhokz2EdPIuJKAxdIJmNiHexpTqjt4gY+5xYcXu1n/PRWmd/fbJNnJtOZ6tp3/jH/7+X/iu/he2ZO9a1bhC88R3zlEqWrX8MaFnmhTgk+9b3wwz9yXxf9uwmlFHv9AM89YjQnYBk6uVKMwuSoaPsDhEnG89fabPcmLFQdFqslslwxDGK+dqNLmikeP958Z17EHO8Y5sRzjjneTiglvZZ3B7CDEL/LL4gi+EajLg9jOiXIKxcu90AWmrvhj+S40yikqig5XHqhyNX0Jez9oOyYy3SVzRuipG7cEILqVcSJ7o+FaI4G0r8ZR6DFQjoVcptKZ+Qzz4p8zon0lwaTWZC7bYsa2tm566S12UhLVZTapwT67hD4OR5yqLfh/RKFO0ec7UrT0NIYI8/RVE5uWOSGjp5l0uM5TXJIojtjxXQdccQXZrWDPVkRMh+H0hu9flKu0+4eNbdMSwUMRwmW7VDZusp4/Txm5GMM+9T6fVaaZYxSXFQXOlJq9+rkpk1mmyjDZBKlDEYR+iQmsEK80hFEUOWkwO+1Nf7V9ZQgElVwsH6J3nf9Cv/49N/hb/Bfox8awaVGA/q/9hmcF79AbSQKZ2ra7Jx5FuORJ1hplNEnPtS/8cQTZl7B++FB9idbXZ+d3oRjLe9gopOhazTLDqauc313yPGFMrWjfsdzPLSYE8855ng7MexLebm5eCfpBOnX3N+WMvaDEM9eW9zq3b1izGRZFtTuvsQVHVY+J2O5z/rJGXHTNDELtXekLKfrQj69ipDDOJZzSWLY2xETU54LYe7sFaV0bdZLlishmnku6pFbOkRiUynbD7pyXl5FFFHlFiM5C9X3UDlVTCAg9dRsRlrm+Z3vLRjm0UkEb2kClfRl6mgopTCiFKWD0jNy0yF3XWKnQp6lVIOBONs1Tdo84omMS50643UOqeW63M92RYk3bXG0V2ry+bjyEoZX5WScsRfkTDBI4wg16mMNe2RpQqNSpqqnMi3MK1pK4ohSw6Tu2XRGId1xyHZvQhYp8thA291jp1RlSbexdF/6VjWdz3c0/rm/TidIARO/tcX2p/43/rPjH+U/v/6PcLdyAvPzdMqL9L0W1e3rLP3qv6a5cx2A3DDpnXuWzoUP4WsWQZRitfsstneg/u4qgEmW0x6GBHGKoWu0Ki7VksVyvcSlzT7N8r2ZwEmaYxg61dLRiugUG+0xrm0cOUbUs3U2OiO+er3DyaXKwfPO8fBjTjznmOPtxHgghK51hCIJQsh6RW+ZZc/mrk97LWstOcaVlyXUGmBxTRSW0UDIYZoJgTWLWJk4kkX03GOicB6cywie/yNRdFqLYqRIIvCLsuPiymyUpGnKQrq/K48zrIJwKlmko7BQlKYjDnN5nV5Ffh5ms5KmYch56QZQjDBsLgmBPsBhAjrP7XxP456g9wJf13sqj1WaRm7Y5JaFplskTgniCK1SQ7N12cwYFpiZqPVJLNd4moqCfmBeU/J5qdZFYS9V5HrvtUW1XFiBehMPWBn7RJsbxGGE09khL1dprCxR8yxMrcjs7HckqQHEPLNU5ZXbXdqjmIZnU61XSPJTLG9fZsf36XslIqfMlf2A/8FvcW0ijvTY63Pzkz/DX1p2+L+1/3OafxKDNaYbK7Z3b2P2Ps/63jVa+zfkV63p9E4/Rfexjx5EMJWQKUjtiaLR772ri/reIOCljS7dcYRSSgozjsnp5SqrDY9b+2M6o5BWxTnI4czynN3BhNWmx9J9JjMB5EoRpRm2ea+JaBjE3Nofs9EZEyVyvJJtcmqpwqPHmg9sWJrjG4M58Zxjjrcbb9jrXizIu5viKh/2Z6MBJyNRazp7hQO3BNu3YHkNVo4JAe3uwfGz8pikMC4trd05sz3P4NJXZcTl0gqUa4UK68CoKwqVrssCHYUzJ4dti3tdL8goqiDTEXeSC1VMg0HUTsMU8qsKojrNSUQVRqu9QrHVZoHf05gkoziPudL53oRhQK7J+2eYbzxJ640OpxlkukaeKzSVoWkaueOhFISmg6k0KmmEXqkKaVRKlEwtmWV55hQtHIWSrmnSGjLxoVaTXusoLKZsuaISFv2XJcugtLxE2t1H5SHp0kkM08A4XEmYvs7ita40Sri2iVIRQZyQZDk9a4Fx9RinwzaTNOKf7Dd4ZSLmwswKufmxz/Ctp/b4N92/zYn94/KZX15jGOfcvn2dY1e+yMLOVUAI+LWlR9iqrpOeOM+ac6chx7Mtom6Mnyregn3xLaE3jnj+2j5hkrFSLx1kj47DlFdu99DQeOb0Ai/e6nK742ObBrlSpHnOasPj6VMLRyqZU+iaRsWx2B8Gd8ytn8Qp13aG+FFC2TE51iqzVHPxo5RXb/dRwFMnF96F38AcbxVz4jnHHG8nyoWhJw5lMbwbgS8ksdeWGBelZBKQYUqv5daGEEJNE6Kp6dLTubMhZG46Qz1L4ZmP3f88eh1ZyMq1ot8NOR/Hhm4x2s8fC/GbZh7GobjaJ75EziSxENQ4lscbRjHKsihfZpmoqeXy7H6mIYR4GjZvu1KSn/hCkg9IJ0i/XTIb0T3HexNKyQYpiWTTYVpyPai8yGnVAe0BNxYa2DYGCgXkmUliWARGCY0cmxx7aRFr0Ja+Y9eTDdB4IIY2vRiyYJqFGc6Q89F0GcWa6BIvdvoR2fTphtw3CuX6nYwgSci8KuF4TJTr+LduE7tV3HKJhmNQyaOijWXxYCLQaJJQdiyePbPAKEgI4hTTcDAXn+AXr9zmy7dGoPSDmeqnP3SFn5/8XZ60PwLnqvDCF6UVxx/DH/wWT914Ga3Y6I1Wz7B95gP8iXuac53XmExCooqDcyhcXVMZWp6RNpff7nf3vrjVHjEOE44fcq1rmka1ZKGQvM5PPb7Gtz66xk7fp+/HGLrGUq3ESqN0pJJ5N44vVtjq+cSHlM/2MJRcUNtA0zTqno2maVQKI9PN/RGnlqrzvs+HGHPiOcccbyfqLSnbbd8Sgnm4D3M8lAVr9bjMTM/S2TShNJb+yIUliWAKJrBSKCxOSUhbZ09UTdeTY+X5jFTejclYFv56Ux5XKhfB8S3Y3pTbR8U0l2GhGpmWuNy7ezAxhDyEgZQspwR12pc5jUHSkcfFsdzPKFz0hgmlUtEXSjHhJZHjZIUD/iAmaV5mfzjxBjmZU0zTDyoVURrjSMicYc5GNT4w6XTkWo1CTMsm0w2MeIJpa2iGg6GD4dhyXYVjeR7Xk4EEhimfB8sqrrN05mYvebMy/HAgiRODLiwsSitLFBwMPsi8Ku1Uw4gkvskmR08D0vaYjm6QrbSoHD+JFgfohUqaKyHKjbJDq+ISJRmfu7TF5y5tkacGoLP3yJ9gfupL/PPV/wvfwXfMXnZnTzaiNy6jXnqOWrGxG62dpf34x4krTYxBF1Uq0y8vUB7sElUdHFsIn5YmaJ1d0uYS7vr6A7xd6usePxmnGdu94A5yl+WKIE5RSuGYOsNJRHcccWKxQrXUeEvPs970OL1c5fruiLJr4dkGOz2fOMuxMp0zK9U78jwrrkVvHNEdRXPi+RBjTjznmOPthKbBI0+Kkre/M1NU4kjUv3OPiwI46Mq0nymCiSzS9aYsvIPuLI8T5DHBRKYFZSnY5fuTzsNoLMiiFk5kgTZ0USUnmSzCmiPnGiegxjJ3XeXSA6eUlNG1wnl+YCCZToYp3OiHc0N1Q/7vlAriOpmZitKpEpVKxqKuz4LlD4dhvxVTylsysszxupi+v2+E6Rz1pXUY9Dm4PmxXro0kesDn02dqf7HBMSwLJjnGZCAGIsMUw91kLHFh1Ro0FuXa6nXkWs8yqBRKu66LCjstjffbQliTpFD5Y1FLh31JhVhaZ1xq0OlPWK7WIc/RLIu81iKpLrA7jHghtljdi6jFY8xTGqtRStk18WyT4STm8vaA33z5OklgAAaD9Uu0P/Wr/FXzL/KPF36J0uFldzyCX/sZ+MNfgyxDA/qtY1w/+xHihXVsS8fLMwxTp9EoczU/zXqacyEYUsokqizFYNtt0XzyQ5Qr5SN+sRDEKVvdCbc7Y+I0o+Y5HF8os9rw7snB9MOEza7PTj8gy3MWqi7rzTKLh/ox81yRK4VlSnm9PQrZ6QdMwoRcgW3Jz4MoZRwmTKIUXdNolO031X9pGjpPn1qgVrK51R7T8yOCOKPh2ZxertKq3FtV0jSN7EGu2zm+YZgTzznmeLtRKsu0oc7uzB1eqYkCWmsWZqL0Xtf7FF55VmJ37vrDmudC5s48cu/jwkCmBSk1mxBku7B6QvI7g7Y8d57JOXkVIQvBWBwKUSgh725Zyv/avtxPARSq5zQyCUTd0pDnOXEWtm8X/aG6GKDybGb00DUxUB1WpvKir/Ug5JuZqnq4pP8gmBPPtx9H/f6PUqn1Qt0MJ0LqokgIaxTM+iEPFM9DUVmHvzctUSpNSzZCbtHDmCXSd5ymkI3k51kq/zYXZGO1sCLk8aDsPpTjuJ78mxQRYIZRuNoduHFJ/u9VCjW+2PjsbRJZIyy7Qu5VSTUNPU0wAp9Ns0U3M0mjECPpM1g6xo2OYinb5QNnF+mOI37muVcJxzpgFE71n+X7W9/Gt9z8//HsiVVKVrHkhhP4rZ+H3/zZYjAD5AsrbD/xSZ6PawyDGK/nY+g6y9mIytIirZUlOgx5KT2H1tBZMRLSLGdsuiwcW+fcuaPL7MMg5svX2uwOAjzbxDQ0tro+m50xZ1dqPHWqddBr2RmFPH+tTd+PKDkmuqZxeWvAzb0Rj59ocm5VOkhty6DsmAyDmOEk5ub+WHoyXQtN0/DDhJ2+z++9vMlq3SPOFYYGdc/h7EqNk0sV9AdUXW3T4JH1BqeXqwRRSq1kMwqSI0lnmuVoGpTs+VSjhxlz4jnHHO8ELFsI3+qJe2+zHfmKAiGpIATTdoT8aZr0e0WhkEnHlf+bppTFW4sSpzRFmsLNyzMlqOiTY+LL96snZIHd2RAybDlChOstmY8eRfIzCpNGvSm9pErNxm6iFepk4VrXTVnMkSksnDwvMU+DVNQnNFGT8lxU1mQapZTM+u5MuyCfOagpwX2LYfHzkPl3AEeU2o8i93k2m2rllsRoBHJ9OLZcy919CXlXuVznhzcWSsmmRDfAUHJtTVXTKChORS9U86I/ud4UwtlYkOux1oBeF9ZOwq2rUlovV+W88qxIZgjkuR0X7BL4A1E+B13p7XQ8Mk3Hi7qYXp3JyYtEzWVK+7fR2jtYY8V6pUyQQbByDPPi0xyzXL58fZ9/9bkX2NvPAL1wqv8sHzt2kr+/899i3fQ4uVjl3GpNFODf/WVROccDAKLVUwQf+S76Q5/d3Gah6pAphWNqePGEySRiU2uyhEbZsXn27AqLdZcgTHEdg6cWKqw1vSN7JpVSvHyry/4w4FirfKBuNsoQxilXdgY0yg6nl6vEacbXbnYYBTHHF8oH5fhWxWEwifnqjQ7jMCVKMpIsJ0lz9voTxmGKbeiUix5LhSJIMwzD4Nb+mFrJ4eRShTxX9Ccxz19vk2Y559fenA3KNg1s0+DCeoMvvrZHGKe4h/pclVK0h+KgX6rfJ1VkjocCc+I5xxzvNsqFC33jmpA2vShLNhclVzPP4cQ5UYC6+0IWR0OZz95cgMc/OCOsSsGVl+DGZSGTy+uySAe+lA6jGNrbourohiy8plk45Ctw8wp4lhDlckVKjlkqjntNl0U6iYBCUZwSD5XNxlmmMdy+IY83TVGPpsYO15Ey/uHInbwowQMP3Ec4x31xnzAjAB5M97nfe/B674s+u32qNmeZXAu6Lua0oLhbEosBLY2L9IK8eMx08EDxXGkkp+KWpIweTTc8COmcjMEoyefk+BnZTB28BF02OM1FmazlenIdjgZFZaGYtFWqyHU5GYk5KUnks6HpEIXolgOGQWLZGHFIbpgMV8/gT3K6zVNQa7Cd2ayeOo4eafzKcy9xbUP6WDMz5Na3/AIf+kCJf7D/Tyh3FihXLI4vVmi6OuNf/wzV3/mPWKMeAOP6Mi988PvZPPMBJkGK1r3MM8aAWtzFUwmjfkRgOnSWznA59ljf6nNhrc4Hzy5R8+wH6tXs+RG7g5DFWumekrprmziWwc39EScWK+wPQjqjiLVm6Z7j2qbO13aG3O6MObVUxdB1/ChhbxiyPww4sVBBjzWyoryeZ9LnWXZt/CiRwoihs1h16fsRr+0MWG+V8Zw3T0GOtTy6qzWu7gyxzATPMclyxSiIqbg2T5xoYc3jlB5qzInnHHN8I3DqgpQE9zbFeW7botKkMQRFybzaECXSH0K9MVNwbl2Bk+fk9mEPtm6K4qMQV+zUoLF2UkwUJ88LiW0XZf+kcKk7rjy3acriHBSKVLcjKlK1LguyaRdGjYIwZKmUzKe9eOORlC6nBCSJCkNRPusTvS/mpPPrwRtZdjIehHy+lfcgn73fhiF9w7ZbXBsUpqIioiuYhryXgKCIOzpkOtMLw9q0P9iyxJhWqQiZdT25/faNYihBkaM5NcwdRq0hCv+wK5+VJJ4ZjMpV2bzt7cg5eBUhqfWWfP6SGC3PMTAYlhepphH2sMPELrNfWWb/+GPE6IzChFevbPHSjcEhp/pvc/Lje/zSwj/lIhehUZh4VE7/s7+O8as/RXXYBmBYavDZ059i/4lPcvHkAsdNg2u7Qy6V1ki9NZ6o5pS0HC3RGOoevrKpBhGrDY9veWTlQOV7EIOQH6YkWYZrHX0VlB2LcZjQHYe8utVjY39EEEs5u1mxDyKQbuyNCNOMimuy0pA2iEVcwjil78eYukamJALpxFKF9iAgV2DqOnGaS0dNcbo1z2az69MeBpxcqr6pqw7A0HWeOtWiVXG41R4zChMMTePisQYnFio0jgisn+Phwpx4zjHHNwKVKjz1Edi6If2Xw4G4yWstqCHkbeemlMEXV+H0RVGR4kgmpwy68ORH5DHtHVnEw4ksspYjyujSmpDQJIYnPgjHx7IgT0vyCytFD1xh/uh3ZPxlFMjPh71ZiT/PQcsLw8k08L3I4lSZkE+ViXKqF2XRPIcs/Ib9iucQFO/S14c7emgP5VlqRS/xVH0MihixaX9vZhQblyI31rAAJeYPDfKitzB3SxhomKYu12UUyom7JblW48JUl8RQX5BKwDS3Nivod5aJur68JtOJutNBDY5ct4Ypm7Xd7ZnhT2XgunL7sCddKirDdS2GSUalu4fdWKZTPUknSLmy3+dme4SaOtUvfAHtW7/EXx/8Xf6e8X2sUvSmKoX2/B+R/fxP0tjZACD2alz/yPfx2/WnwZJpQzf2xpxfk7GfjbJDJ1fcdKqcWKxgAseLr/YopOHZd5SWHwTTPsr7qaO5UgwnCX9yaY+NzohBmKDpGnv9CdWSzZmVKrmCvh9TcUyMu5TERtnFtQzqZZuzK/WDmN7OMMLSIU5zPMe8Y3+gazJ5Pk7fenuMoeucXKpyfLFCmuXomjYPjX8PYU4855jjGwW3JIusrsOVV+Tf0xcKZUjBtUuiZsLMpFEq4mP2NqXEfvM1mcVeKot6WXLFLNRvy0K6tC6LeK8tYdn9Luxtw6AjhNerFEH0sZBcjcLkUbiADXNWPjWL8ZdhMDunrCCjWqFgZUU/nVEsKnHMXNV8Z/Cg8ac5b7HkfngUpm4KSZv2ZdqWqN5ZKkTT1GE8Lq6jaY09RyZX5UI4owByRaYbKJWQaQY5Gontkpgeue3SCPtYcSzVAMMU5T8vNjS2I8cKfPm6/GIR2ZUX2bNFn3S1Ds9+QhTPyy/M8mmTSALn7WIDF03AdsgMg9zx0MspRq+NoWksGymjMCRIcm7UjvGnwzKXbt9ExRZTp/rgU7/J3y39NZ7c+3uYmiGjIZWCl56Dn/9JuPkaBhDbHjsf/352PvDdbE8ywp0hi66FbRn0xiHjsIRrGWQ5uJZBZxxybKF8h/kmjDPqS7N4oDDJ2B8ExGmOZWgs1FzKzr1mxUbFxnMsRmFyV/RRjh+mXN8bEcYpZbfKmeUaUZJTdS10XaPnR1zfG7FQccjzHAU0K3eqiXXPolay2B+GnFuto+viZrdNnVGQkOeKpaU7S/fT6Cn7Pirsm4GuaQ+UBzrHw4U58Zxjjm8EAl8IY3tHFtnb14RQbhpw7LQohuOhZAz6IyGKpUJN0Yq8w+f+SBTPPJdFur1dBNc7Yp7o7gvJfOJD8NLzYmYwTSlhJpH0v42HhXEjL5zADlTqQijKjpDg8UDOAU164rKsmFZTkM4pdANQ0munG7P7z93m7w2YVmEMQ4im4wp5U+rOcamoYjJQLpsn14NBe7YhAe6gxYd6QJVukBoWKlPkTom03iJ1PHQUvlPHinzK/Q7WZAhKmz2fpsn5rJyQ1o1+u0j2KgYXTMe03roq/dGnTCm7n3tMfpbn0jfa25drVtdJcoiTnPFeH4XCzDOcSgvX83CWV7HShN/LV/jxbcWwPwQs/NYWO9/+C/zlpU/zfYP/mWBfMQoTnjpdx7n+Cvz8v4bXXpSzdkpcf/q7uPrMd1NtSXRa7k8Ofi22oTPIcvwwoVF2cO0JYZLiTU18BVkbhwmWobPWkL7uW+0xr97uMQwKEx+KsmtxfrUm5O8QySs7FqeWKryy0cPQNcqORXsUstX12RsE9MYhuqbjOQbHF6s0KzadYUij7NAoO/TGIYahMQoTluoeC9U7neSubbJcL3G769MeRrQqDoau4TkGN/ZHnF6q0rqLrPb9mKprs/w64zJhlguqwYHDfo73B+bEc4453m2kCbz6VTHwTN3jXlXKgIOuLJKLq7LA2hZkriiVK8dlMcpz6dfst0WxtF0xS6SpqI1JsSBNRqLwxKFkHVZrUhJfPQGrJ4V4jvpSYg8ncpxaQ4jlNFN0SjrGQyGr0/7QDFnoTUPKmwcoyGbJK+KTtLng+V7BlHSC8JnpgIJM3SmGTjc+XkXUyFH/LtJ593FTua8DqVvCzwxMN8PME4w4InNKRNUF9FKFpOuQhj66YaLiCIWOpmloKseIIrmmdUM2Vm5J1M1aQxRNlGzmtm7A8qpc540F4ixjcvs2+V4Hyx9imRbUF9lonMbdvIaXTMhKZSZOg3A0YGLk7OyF/PNxhZuhLJGx1+f2J3+eTxw7x/9+88dwr3vsqIiyY/JBs8fp//C/wEtfktdrWvDpHyD9s3+Fr1zqMZzEOHtDbEMnV9OPsELXtQNO7jkmJxYqfO2mKK7DICHNFOMowTZ0HjvRZKHqsN2b8OVrbUxDY71ZRte1olwe88LNLqauc2aldsev/+J6gyxT3NwfcW1nyGZvQpJmGEX/ZRAlfP7yHpWbXR473sRzLIZBLMcNJJfTc0yOt8p4R5T6S47JB84s4pgG7VGIUopqyeaJ400UMuKyrIkBqO/HKBTPnl68b9tAlis22mNu7o8YBjGaJm0Ip5eqHGuVH6i3dY6HG3PiOccc7zY6+7C/PZtsNFUETVN6PIddIYH+WNzs01zDoAjNnhQKqOsVYe2IcmqahaN9MjMZ1VtCKnduw0YsvZ+mKaX5Rku+HFeUU92UUr9ScrxeW46VZdInl2dwwDELh3uWS5kdRKHSmDnnp8HiDw2m5d/3B97RV3NoDrmon45cB5ommxvbkp+1i9Gor5dOoOtCPis1klKVNIjRHQcVTsg1jaTcJC3XMcd9DF0n1AyyNMOOElLTIS/Mb4ZtYucKY9SV0r1pwrFTRWsKcr1VG6LQb96E5iKdWOPmyCCwVyk7NrXhhNSpoNo+YdmCR57F6G1h+iOqfoedxOTHnVO82pa4sswK2fjoL/BnntD4mfwfUguqdGswKddwB/us/N6/w/zqH8vzGwZ88s/B9/810lqLlze6bHZ89ochrbJDpnIhe3FGX0XUPMm8nBKwmmex3hIy+fLtHlGc4bkmZ1dq1Eo2YZLxlRv7DIOYU0sV9KLaIMHsDlmuuLY74vhi5Q5Xt2mIGWe95fFbX71Nq+wwiVLGYUyYZGRFabzvx7x4s8v59RqrjTKWobM3DLi4Xse1TLZ7E5IsPzi2UoqeH+FYBh8+t0yjbDOYxCgFJcfA0HWu7gzYaMvvQNc0WlWHs8s11lt3zpqfIleKl293ubw5wLZ0qq510DO6Nwh58kTKI+uNt3hRC7I8pzOKGIfJQaj9dOzmHO8O5sRzjjnebfT2i/iX4uNnO4UMUkQQJYn0boaBKIwaQvCuXZKFdtrT1miJqogmjl2NYuxfKkSxXBOVs71b5GgWjuMkEdLQWpbHmab00PW7QnSrNWitiMrpj2emjuk0oqlTOE+R7sFChZ1yD9uWWJvpNCa0YkzmN3oo+/uHdMKDc/qvuwMuT2XD4XjF5qhZxHWNZwr4640/zbMif1NHWS6GP8GaROSGiRGHOL0djGCI5Y8hHLNn1qgbEXYSYJKTGRqh4xFlOdpoiGEU5zTNg51C00UBHfUgChi3O1wLbZSCNW1CZbSNbir2ay3a413Wulu4QZeuXcGfwK+pM/xx6QykxsFM9cdOfoV/9rsXOPlZj/H6H2KsLLGiQvTXXoJrr8xK4h/7NPzg3zzI172y2ePy9oBjLY84yTANjUbJJYwz/CghSnNutn0Wqy6GDrv9CXEm/ZW5Uiys1ikXppzeOOZXn7uJZehsdMbYpsEwSFiquaw3vQNTTd2z2RsE9P2IpdqdOZbTaT6WqePaBn4kSma1ZDOJEjzbwjR0oiRjOElwrIhHjzVBg4vrTRaqLl+90Wa7N5EgA10jyXIqJYtnTrUOphrdXYp/4kSLs8tVhoGQvIWa+7ol8/Yw5Mr2kGbFuSNqqXQwFarPcr30lp3rfT/ihVtd9ochWZ6jKXBsg2OtMk+ebM37Rd8lzInnHHO828iyYkJPgWpdlMzRQIjgsCcq0bGTkusZBrC4IovczSuF0cKG42fFfDTqF8qnKwYh05Y+S7twE6uiZGqXha04RexNZ1eIYXdfOFkUSCzSwqpkguqGKKa9tpTUKzW5/5RsHPT+gbjbC2IXBZIHmquiHE+h4I4KojzH2wWDt5POH6FaTidK5Uree6Ms76Fpyf0tC6L80CSi+52oCZaLaenkpkOuUrQ8QxkGWpqiJQlJuUpf92iXmjSzHpGhoacxehLjpAGpYRPmJka5jDXsyobNuGsJc4qe0yhk2BuSWC2WjYjq1lXIMkbHzhN4C+zGHjtxxNJ4j99hhS+a51GZBQr2HvkT3Ec/y//j8sc593PfTmXUIUlHjDdukd+8QqN7bfZ6n/ww/JX/VPqyC4RJxo29EVmWM04yJknGVm+CZeq0Ki6a0oizjDNLVRxLZ6s7kZnwphDCc6s1SrYQ6lwp4ixgpz9B13Vc26Th2SSZ4tb+iCjJOLdSRdd1TEMnV4r8PuMi00wxDlP8MCn2sjk1zyZOc8IkxTJ0Yg2SNGMcJFzbGXBhrc5Ko4RtGnzk/DL7w5D2KCDNcqquzUrDo1o6egKbUort3oRb7TF9X7KAl+suJxYr9xDjKbZ7PpnKj8z3rHk2G+0xe4PggYinUlLaD5MMQ9ewLZ3nr7Xp+SHLNQ/LlL/Bkyjl6s4QpRQfOLs07yV9FzAnnnPM8W6jUpV+uqlaYhQlw41r0vc5GkjAexxL6bBWlMujSPo1T18URbHkicIy6IpDd5qhOVUnbafotyzLY3VNRlmqXH7W3ZevSh0Wl6BSlp7Q9s7MtFRrIIYhW8hkfL+524cWu2BSRNUwK83q07GY+huTlDeL6fjNb1Lcj3xqgH5AHB/k9zMNhDekfSJXs9np0/ctiWcld5W/TmpB0XYxbSPJEkhCrMxFq9bpxRXq8YC03KB/8nHqm5eYGA79JKJhgxbrZK6HFiIueF0nK1UIUg3TskBpJLqFkeY4UwIRJ4z2e/SNRcxgRHdrj1ItwYt7aCpndOwCUWMJa+xTCoZ8wXf4knmeLBKVbrB+ieBDn+HvXj7H47/w57FzRTnp4LoW1dGA1f1X0IvXOlw6Se3ZD8Ojz8D6qTte+cCPuLY7JIwzdF1jqSqO8+4ooD0KWKi4LDc8HjveYG8QoscJJdvktZ0BfpAe9Gk6lsE4SNjtByw3SgzGMXmuSNKcsmthmzr7w4CFqkur4uBHCa5tULpPKLttCTENopRhkBAlOYaeUXUly9OPEpTS8EOpjKw0SjxzevFABTQNnbWmx1rz6DL5HVeSUry61efV230AKq6FQnF9b8hm1+eZ04ucXKzc87hRkOBa96clliHB9W+Evh/x6maf3X5AkuXoukYQJfhhyhMnmwcjQkH6V3XN5XZnwunl6B7Vdo63H3PiOccc7zYWVsVsMeyJ2jnsSZn7YPQgcntjUUqKnT1RHeNIFv3NG3DhSVEsF9fg9CPw3OegvyXq6NQBPCkC4d2SKJft3aJ8X5DCYV+OX60LeT3ziITN727C1oYol4Et5DUO5F/bEdKcHc7yPAK5mt2eZUUf4DvkMvomJp1T3LdAqHKgSBnI34w2qslGxbKld3E64tK0xXS2vy1TsV6ntfOAdGqGHCNN0TWdetmFwZgkyRgZJYbKwEghUxlWuUJVheS6iaalJOUaRjDGDMZoacLIrrGptahWltB7Q0K2sKtV9DShu9+jqyxGJYfErfBVa52KYfDtekbt+AmUV6W0e4vXehk/kTTwVR0S8Ftb7H/Lz/K3d6r8xV/7FH29QjsOqaiAlfEelUkfvdgsjb0Gz538GN3qKn92tYU37YP2ygcvuzuO2B+ELDdcvEK5LNkmCxWHcZSQJBmgcX1/RKvistwokeeKrd7kwKCj6zoX1mr0JzFZnuOaDmMjxbMN/CjDtY2DXsveOKTu2XRHEWdXqnfEJh1Go+yQZjm3OmPZo2aKMEkxDR3XNMhyA0vXKJcsTiyUefrU4j3xSQ+K9ijk8uaAasmi4s4U0VrJpjMKeXmjx0LFORizOYVjGSSvk++Z5uoNy+HDIOa5q6JsLlZdXNskzXK+eGWIH6WsDD1WGncqrq5tsj8M6Y7nxPPdwJx4zvHNh2kAuvEN6uepVOH8E/Dy8/C1PxU1UzdmZfFyRRRN04Tr12Ryke2I+umPpWR9+6qQzkFXCOV0BvU06B1NVMssh7MXYe3ErMyeZjBqSzC3hhBb14Nb18QN3GgJQe3kcn/TkueZ9tSlKZAVpONu5qEVQeGGPHee8o4RzjkeDCoHXYLbIZf3Uan7K8/T1gzdnP17ELOkyYYnDIRQ6ibk8VEHmf3XcaTVIghg2MXSoOkaRGaTyeISZceiWi1TMuCGUWW83cca7WOnIbllY6gcPU0JrBLD3MJLAvzzz2DmGd7WNfrbPp1UJ3SqlKtlWpbNzvJ5orjC/jjkdLLNySBl2N3jJ32P7bAFiFN981t+lr806PJDf/S91Me+kB4j5fx4kwv+JqYSsh6bDvutU7QXT6JqC1i9DoOdFK9qo7KUOMlQgGPqjMNYHOtHdOEamsb1ro9SY1abZVzLxLF0HNPANDTSVHo1e36EH6XEhftcFWa+5XqJUZhIQLupk2WK9ijCNn2W6yUuHmve9zLYaI8wDQ3PNgniVLpxDIMgSemOIjxHRzMtdE0jTHI8+63/fdzuTkiz/A7SOUWr4rDR8dkdBJy96/a1psfN/fEdJqYppiXz5TeYw77RHtMZhxw/lIVqGjol2yTJcrZ6Pq2Kc1Bqn0LTpLVhjncec+I5xzcPxiPYvS1jJPNMSsyrJ2BpVRbYdxPrJ+Vctm7KeRjGrK9ye0MUxzQWldP1pHSulCz8q8fl/KNARmeOenD2UXldo74onXkmj5mMhDS6JVFQn/iIENkv/aGUPy0H0ORY+1vQ2RG19cS5IpC7iHKaxjhNezSnZfRpcPwBDk02ertL6nO8BWgzojndIyjeIFtVyYbCssAty3XiuKJ4p4nMODeLcHm7aKOIj5pQVWxCLFt6lLtt6RONYwzHxUsjThJAVSMblxht3kbHJ4gzcrdBY9KhOupjaDmJV+WW3UJTGsqymQQxw7NPU1k5Q+/Sq3R7I6qlMkFtgVGlRa7rfCje4sYkZDfS+M39nGvRGiAz1Tc++ot8wN7iv37uEyx0E0YlRVf3uNh7mdqki5XJdZ4YFqNyk17zOErTcMIxq7GP7we4t3aZlD1u8cdsLJwhtUo0Kw77g4DFmss4lL5J09DJUQz9mO2eT9+PKNkGSsHVncHBhKDFaomr/oBySRS6SZTimEaRZ5lhWwatqpTpm+WQvWHIOExYrLs8e2aB4wsVSveJKIrTjOu7Y1bqHu45k6/e7NAZhQyCWD6mSpHnUC2ZGLpOludc2x2yWCsdGIfeDHqTCPc+xFXTNExdYxzcWzJfaXgcb3nc6vgsFAYjBfhhQs+POL9af11FMk4zbnd86p59T69mxbUYRwlBlDIKY1qV2XGmfbGltyHUfo43xpx4zvHNgV4bXv6yEDOvIovx3pZ8nboA5x9/d8lnGIhr/OxjszKdXkyC8Udw9RU511JZ+izzTB7juDOTTxhKP2a5+L5SlfnsgS9k0R/J8Xr7svCfOi8kd/um3GYUM7EdR167QjI9g4lMVJoGxOs6QihTiKfl2inhvJvAFGRzrhy8ozhcNNeQaKUjoetFiX0WSI56gJK7hlx3pbK0ZIQTUbsNC+I+hAVpMI3iBO7qs9U02bToOrlhEOkWyjAxJhP0Xge9XMaoNmQT9NUvEI1GGMMBK9Um+9Vluppck0o3ycOQJDHZj3S6tRVyt87i0Ce6cpmXTj5Dd+kZJtaQhmfyuBVwbOtV6oMd/FTxp9ZxnucEKHGqbz3zO5w79gL//KvfxkrvKRYJ8JebNHu7LG6/hhOOAQh1m+3qKnqpjKZDYth4wQDdsAk0Cy9P0CYRO5qNunaJ5TCmffoptro+V3cGaEWI+mbXJ0wygmKmuWsZNCoOFUcm/ji2QW8ccWNvxPnVGs2KQ3cUkWTyuxTzT0aSZpxbqx8Qy5WGR61k0Sg7fPLRFdaas1L/URhOEoaTiKV6iVZB6K7uDLm802M0SbAsHaVB2TU5uVRjsWpzsz1mbxjy7OkFVhseS3X3jt7I+yFMMnqjiJv7I27uj8U9jrQb1Ms2rYpLrpSMR70LlqHz7JlFHNtkq+vTK0xJZcfk8eNNHllvvK75J80UaZYfScAXqi7tYUiQpDKy9RDao5C657DceOP+1Tm+fsyJ5xzvf6SJTBMJ/FkIOwiBCycSXVRviqHnjTAZS6nZdkRFDAMhtWkiyk5zUcjh/RCFUtpu74iyefxMMeWnwDRCKYmEmEahEEHbFsVyYVWeJ0lAS2c9naMBlKqzWCYKY4hXgVCX2wc9MRm99rIoqYY5MwJNzSDTfswrr8DicpHFWUhlKheeqRuHZne/XpPfHG83jqKM06CqYntwJ7RD78+beZuyFPZ2RPXUKOac1+W6D/wiJkvJRuSoIQFKNiZRYwk/iEg3t3DjCaiMLArRAh8zCLE0RYaGCmMyu4SOYnW0Tc0qocIJPiZtb4UQndhySSpNslzRtSqsRSOutNvsJw667XFhcJP1ZAczGPOz1gk+a6yiMul33LvwBRbP/jr//GtP8ezmn8cxNXoqIPNHnLj5Eo7fByAuVdleOsu+XaOTmlTKbtHn2RMXfpZTCTq4lkFoV7CzjJIKyHevEiweY1NVGYcp2z2fWtkmTsTYkhcGF6VgEibUXAlpX7E9GmWb3jhmEqecW6lxjSHbvQk7/QmmrlEr2egauKZBnGZoyCQhP0q4sFpnuf7GZClXSq4RXUPTNFabHjXPIstzojQvpt8qnjzZIssVV3dGTOKE9jDE0DSu7Q45vlDhmdMLOK+jCo6ChC9fb7M3CNjuS7k9TDJsw5DX6UdsdkWRXLyPcunaEkh/brXGKBAHfr1sHzkS9G7Ypo5jGYRJdo8zvl62WWm6XNoc0h9HuJZJrhSjIMFzTJ482cKdK57vCubEc473P3ptUQAXlmekcwrXEyL41S8UJXcDWkvyf/fQH/RBV1zn7V1ZlE1LjhVHQkSnRKxagzOPSin9bmzdkuw/fySL9+5tIb6L6u6gkgABAABJREFUa7B6TMjr7WtyzPVTsribpkQtFTmIxKGokuOhnEO1IcdOIrnv7dtiVjItKFUAJRFNeS4ktbUkx8pzsEwhsEkyI6tKSQ/ooFvkgo6KqUZOwXAKpWvakzonne8a3kinPHIm+4GhSDukfj4gVBGT5HhyDYG0dejFJoVik3N4otEhpTtVOe1EZ4LLcj5BM3RC08OMJuhJBuMhummSux4qz7DTgKhaQ08TykmA79j07RapWSIZ+dS0lMDUULpBEKWocMwj5X2MYYoVBSwl+/yh2eA3jNMkiXx2B+uXiJ79Jf7JS0v84O9/J0a9CctL0NljZftV9H5HztW0uXz+4/zeI38WO404mQ+Y3L7NfpRwtfEYx4M2Z3dfARWhak1YWqCb29TKLkQTrME+/qsvsrfyDCuNEn0/pjeKaJRtHNNkQoKhaYRJgqbr7I8CTN0gTnOOtcqAYhJl1D0H09RZbni4pk6aw0JNYp6COCVT0r9dcS0urC1wZrmGcWhsrR8l7PQmbBY9ls2Kw7FWGc828GwTP0wP4o8UGo5l0qqaxIlsIHRN40Z7jGsbrHll2qOQhZpLxTW5sT/CMnU+cGZRHq8UfpSS5wrXNjANnZduddgbTDi1VOHm/ohJqliuuWS5nH/ZNen7EbZpvKFJqFay72uUuh9MQ+fkYoWv3OhQK1kHGacgQfuuZfHUyRarzRKjIEXX4JG1OscXy1iGQXsYYhoatSNK9XO8fZgTzzne/wgmsoAappC5yVi+txxRF3c2IQlnkT/bt8QF/tiz0FgQ4vric/K4WkMUx91NIZG1Jlx8Wkhqngvpe/UrQgKLMGlAFM5XvyKEbXld7huFRd/phpBKwxRS2liU4zQWpSzqerKot/ck4N1xhADqmhDRPJfjTwmjUZiAwkAI49qqkAPLAteFybCIXHLktaS+uNDzdEYc9GICUuALsdaNWc9mLq7cOel89/Cg3bIZd5HPAyJ4wA55oPfNLNzsaTzLXzUsudbiWK6Fu/MiD5HODMjzDHfcw7RdMEx8t46hFMo0IY6lg8OxMVEoTcOMQ+I8I3dKaOMBWjTBsBdIM4WlgW7IiEfL0jkZ7NEc7lK2DLJIZ8uP+ZfVE0xSMdf4rS06H/lZ/vKtJn/h976Xx8wJhpXI5+r6q7C/jQ4oyyZ85Bm2l8/zwuJTeLbHQrWJn63gL57mdmdCpnIW919E+VXsteMsNqt0/Ai96FFM7RJxlJLvbjOqP44fpWS5mIIcS4jW7iA4UC9rJVGRy65FexgSpRmGptEdhiRZThAJOVxrlikVjuzBJGYSZ5xZrnFysUrZNe8hbn0/4vlrbTqjkJJtYuga13YH3NwfcfFYg/VmicvbQ0oFSTR0+bMTpSlBnHFyqULXj9A08Irn1Yt+TNs08GyDF291cS0DXYfeKKI9DslzKaPXSha3uz5LtRI9P6LiWriOwSTMUEoxiVJ0LeLRY3VMw2B/OKFRfnPE8kFwcrHC3jBgqzuhVrLwHDEV9ccxJdvgg+eWWKmXJGZJ05hEKa9t99npB0RJhmnoLNZczq/W39DINMdbw5x4zvH+x9QYs31L1M2kyB5MixnktiNq6MLKLJ+wvSvz1J/9OFy/JKrftBSfZbIY11tyjM6+5HDquhDV9o4ol4uFaUkpGeGXZTItCOQvfmulcJbr8nxpCuMxDAdCLFfWZaHsdWThD3whj0lh9jhxToKrX3lejBvBRM7fsoQc6EWMjT+S1/v8ZfjsL8pzkMMgEROJrgtRTg8Hwishr8G4yG1M71TLpoqXUrMw/LmZ6B3B2xMQP1VvHnCzkMaQ6bNWizSVjZHG1P57xLE0ud6K7NBMGeSajqFrDN0FnCxEz6Q6kFqOXDpKw04DMExSpdCTmNCrE5gxjDuUB7tsOas0sohJZRk/yWgM2iyMNmi7DV4y1/msUkzyOqTiVN/62H/kO7sJ3/PLH6FsOCytl/AiXxIiBl05VcMkefQDdFbO0kvgK6xwa6JRI+X6bkKSyW/dsU2yPOfsSo2VsY3vuYzjjCjJCGNxs3f9CHsQMjB9bu70MU2LcRhTK9nYliFOaSVqnGXq+HFKkimaZZdTSy7DIMJzLM6v1zENne0enFqq3uHIXqi6aOOI3X7AxWPNe0hnlud87WaHnh9y7JCbu4nDOEy4dLvPM2cWON4qs9n1ce1CcdRgtx9wdqXOQsVlt987mMc+DhMqJQvHMri2O6QzDNkfBbSHAZMoo+yaXFyvU/UsJlHKV2608cOE1YbHOEgoORJ2H8QZcSq/M9PUObVco+/HdMf3ywT++uDaJh8+u8T1yohb7TG9cYxpaJxYrHB2pXZglpIJUDFfurpPZxTSqjg0yg5JlrPbD+iNIz50bonVed/n24458Zzj/Y9GS/obBz2o1cFryeLZ2RXiadlw4sysDK/pQkT3tuHWFVE8663Z8QJfCGOlLiS234aVNVGJQFTRqbmnWhfS2mvL/Q9jcVkW+L1tmUgUh7LQe1UxCg0HoohGYZG5WUThnDgDx8/B2nEhjr1u0YvnzUZUTsuh/khK82ki55EdojFTM0iWibJ6mEekqcy8zrNDvZzMHNIwI5pzwvmO4W0hnVNDiGkdMoc9AA6/r1mhhpsG4MzGYM6eZDbhyLVQaGhxjKEyyFIUYMQRVhoRuxUyy0SPAvRMiK1lGAS6iRX45InCjAJSFJVwyLkoZNNqcDXQ0bQRx8e3uWo0+OnKeXqjmpyeFbL54V/ku6KX+RefOUum1rC9EFtLWLr0Glp/V05T0+GRp5icf5obE0VP8xitrHHLtxkGMRudMYtVlxMLFUxDJ4hTru2O+LU9n+/phowm28RWiTTN8aMEQ9cxkxANnYldRkMTXo5Mid3sjEnSnHrZxixK4iXLJEljuuOQZtkmyxSPrDX41kdX+cOXt2mWnSPLvA3PZrs/oTMKi/L8DO1hSHsUsVz3jnRzDycx+4OQD59fYr1bZqMzJohTLqw2aFVcTF07MNxkeU7fT9E0jbWmx632mN3+hGpJ+izTPKdk66RZzlZvwiNrDZoVmf9+u+PTGUV3dF1oGiRZjh+l6InGcBKTZfk7OhvdtU0eO97k7EqNqIhh8hzznue8sTuS3+chsm7oBmtNj53+hEubfZZqpTvaGeb4+jEnnnO8/6HpHJhjpsYYEBPNNBxb3fWHRTdkwe53ZYG1DwUpqyIuSNcLVTAWFXJKPHVDSN2U2B3kht7l4tR0ydfUddi5LQqpUrC0JmR265YQXKvI6FSqKLsXZfCd21JOn4yhviC3720KicyVfIWT2bnmRXZpfkTUUX4ou1EVrzHPZiMTp6vIG/UIfpNPEXr4oMnUKb1QwrNs1qf7oFBKMlnjCDLjzjGpUxObbnKQ1ZSmaCg0FHYSomUxVhqi5RlmlpHYJSKrTFmNsZIIdLBKZRLdJhn00ZMxFhmBXkJLwoNBSnYcgGnx041HeEU7gZboMlP9md/m/Molfuq3VzneeQIziRg7CY3uDcrR6KC5QDt+Fv7MD5N/y6f56gs32R+GLC43yScJ+fUOSkGr7BDEmUzQsQ1xdg8i+rHHU3adRhyQBSG+MtGUwkwjdF1nYnpsectkmk4UpVQciyjJ0DTZtNmmmGvCOGMYSoSRHydsDwLqJZtHjtXRgDTLce8TiSTmJHFt341xmJDn6p7syykqJYueH6FrGqeXq5xerpIrha5pdEYhl7f67A0CwiQjjDLWFzzWmmUMXaM9DGl4DpnKZSRnprHYcFEouuOInh8V89NtSrbJ7c6YEwtltns+e8OAvi8Tl8IkpexYXNoaoGnw5MmFB7r8cqXojSP8MJEpraaOpRvYpk61ZL0ugXUs475mqDBO2ez5NMpH93O2Kg6dUUhvHL2lSKk57o858Zzj/Y9BV1TIclXK1v5IFuLAl8iX5qKUlFV+5wx1paQErZuH5lMjRNCyZ+Mjp4HpU4STYmZ0kb2ZFuadfg+W1+48N4UosdU6XHxKcj17+0IqVS59nlEgi72uy/93toTcVWrijPeHRQm0yEy0XSG/w24R9q6kjI72+hmO03ikwy7lN6tmzknn24a33kGrSVk8S+T6dd1Z6oICJtlbUKmLjUieCgmdkkytmIrkFr1weXG/LEVDI7DLTNwqXh6jNAM3GmHFPrU4xMxSrCxEmSZarvDCAT2nRKpbxIZJR/PIw5CXS2vkccLvVk6yq1fRMgtNyUx17ewX+Ctf/jg/9OK304h6JPqQStyjPukdNBfEVgl14Qmcb/1uePJDdP2UnUhnYbGJrhvoWkqUZiRZRtlxyVXCzmBCnOV0BjJycWyWeT5d5fFkG83UMeMAQ4OBUSbSDAKrxA29DigMXaPmWXTHEVEiSRBGEVemlCJJhSCamo7Kco4tlFmqlrBM6QkNk/TIWeXTnktdg62uT65UEY0k5EsphR8mZEphG/odBDbP1YGjfYop2VqounzskRUGfszJxSov3uqw0vSolWQ2eq5yNB1G44Sya5GkefFYDUuXOKjlegnPMVmquewMAs6v1tDQ2OiMaHii4JZ1i7VWmUmUkOWKYfDGpfbhJObFjS57g4DRJGa/6ImtlWyOLZRZbXpceINsz/shTnOSNMfzju4ztYsM1Th9e5pd5phhTjzneP8jz8UYsX5KVEV/JOSr0oRBW7IKpyrm9O/ytCS9emJm2llYkZ+5JYlf2tsWKWZxXcgeCEEcDeHC46JEvvpVmYfeLiKUxgNxvE8d82ksE4YWluUrSWDjuhDMUrkwIUXyc5UXbnpdJhgZppTRB335vlIVcpFNg74DDvowD34XR/XmFdCQ26Zqb3LURJo5vl7cbxm7Ow7pQYnnoUYIjKm+l03V6kPvY60Bo3HR0lE8Mr2P+nn3iE3LmcVtGcWZpilKKfI8R0UBSjNRpomu6ei6jm6aZPUWO+4y9aBLKUtIlaLs99BViu/V0HMTLQfdH2PlCYbrYLQWCbwmaWfIWHN4zl7hkldBpR5aJk71yZO/zHe99CwXPvtXqQZ99HgbJ+qxMtg6mKc+NkrslVpolRorjzwNT38ESmUm7fFBWTmIUxSKNFeMJyklKyPPFZ2RxAjZphiabMvghXwdLc9YjvqYZoUk1zAMxdh0uVE9wcRtkmRF3FEgqnCYpOho5Ciu7yfoGtTLDqt1lyDO6E1i/FDUVUPXObFY5qs3OtRK+R2ObIC9QUhnFPJLX7pJbxyjUDTLDk+cbNL0HDY6Y27ujdENycNsVV3Wmx4l22QcJlw81rhvyVjXNJoVh3rZxnUMLm8OGE7GtEehRBppsFQrUS1ZXN8boZRC0zT5M1EosJqmsVz3ZBpvIGYo0Oj5Mbah0Sw7RElKo+ywVHPZG4T4UXLfmKRJlPLctX06owjPNhiHKTk5nm0yKXJR01RMQx85v/SmyadtSs9tnGZHqqJJmmMUxqo53l7Miecc7384brFo5kLmSkV/VLUBSSDkbXlt1guXZzLBZxqrZJoy3rK9K4TTsqG5IMQzjiVjczKW/sookMlC5Rq88EUpiddbMgddR0ZddveL7w15XLkm5XU0eS67UC0NSxSmqaFjmrUZTkSh3d8uyuGaEN4k4SA2J4mK29QRzub7QDELktd1aR1I5+Tz7cTraSfFVPUDEqk/4P0VGhp3v8fFrXkm1xRKplh5ZUkzSApn+mhwxNShqUlIm5XVteJntiuPzbPi3BQqz1C5Ai1DJbGUYy0Lo9mk3qyxVGkw6Bukwy7lOKaCwjI0LEORl2qoNCFEegYTzSI1SmRJykuZx89VThDHNUhh0txi/8M/z3/yqscP/4dH6VomkbfH6f51Lo43MIrX3i01eWH9A2xbdSJ0jjkKCxvP9WRkYtfn6nafa7syPSdIMiZRyiCISfIcpRRKKSzTIMpB0zWJGzJsLrceYWPSYykbQZrRx2bPqpNYZWxN3N1BnDIJE6I0x9B11pseWa4YTGJKloFSinGYEmc5660ytmVwc3/EEydanFyq0h6G3O76B47sNBMifGNvRHccUXFNmhUXDUV/EvNrz29Qdgwqjk2aZzQ9KYNvd338QCb0eK7F8VblDa9PXdN4dL3Bcq0kOaJbA8Ik5cJqHdc2mEQSoTaOU6qORZxlLBa5xXmhDn7bY2s4lkHPjznW8tB1DV3XsU2dsmPS8BwMQ2Or6zOa3J94bnbHtIch602Pa3uSK7pYLaGhESYZw0nMiYUy/UnMa1t9Wo+svKm+Udc2WW96XN4eUHate8rtnXFIq+K+5Xn1c9wfc+I5x/sfzUWJPertC9lUSsidW4Ll47L4ZoWTfdqP2VyER58Wkrm8Lgvvzdek5zPLpF/uyY+A54mCmiQyY/3840JWX3xeiOjhUPqzj4tqev2SmI1Onpf7d/fh1lVRQ3c3xVCUFSXyrOi9nOYoxkWgfJ6BVYz9NAviqxBSMO2zNCxIUh44Qsf15LUnoSiryTwu6e3EgxTsjszivA9mBFUd/Zhp4L9VxG9NAlHnS560faTRbAxqXsSLpdOopPzQMxRJD5izDU6RJ6nQyDSJ2srR0ZUi1XUCzUHXHGqGyYIWY9oak9YiaTslT2wMyySuLRA5ZeLxGCPw0dOYNFVcak/4yeYFutYixBB7A7Y/+rP8wPaI9d/4PuqlMjveJk/0X2O99yJm0TYwNEpcWbzA5eXHSTQdP0xYaXgsOQn7foq/NeDydp+v3exya39InMprqDomRhEhpJQQRMfUMQwdx9RRShHECZ5tgWmyZ9fZzGrkpkKhSNIcM5LyeL1kYxWz1fUoQdd0bMvAMnRqnkM0nWI0STixUOaZ0wvYpsFG2+f8ah3XMvjg2UWaFecOR7ZrG/hRwlLdZeHQqEfHNuj7Mdv9gE9crKGURncUkhYtL7faPpZl8K2PrT0wgdI0jYWqy0LV5eRild/8ygYb7TFppkjynHGYsjcIqRbEuFlxCeKUzihkqeZycqlClivWGh5Vzz4ylF0Vm+HX+wtzu+PjOSZRltP3I6qujVZck65lMA5iRkHCQsVhbxgymMQ0ym+OJJ5ZqdEZRWx1fZoVB9eS6KXeOMI2dS6u318lnuOtY04853j/w7JFvbzyClx+QRZY1xX1x6vCR78DmkvSK6nrYtRZXCl64pREGgUTKYXXF6Sk7VWlL3Mayp1lUvrWdVFQ+22JVjoMw5A4Jacki/3THxXyq+vw/Odkxnq1LiH0o6EQ0TCQEimaGJw0RO20SkKeNU2C4Jk6jrUiCicrJhzFwmZezxSkaUVvqC2/k2FfSvLJmzShTI8F9+8jneMNMX2nDE1/3V7MWXn9COjGLIEgnIjqWa7KV2NBrq/BSP6fJbL5Sg4pn4cMRFm9WUzKAkOXSKUsCICcDJ3ItDFVhjIslMpINVFLVa9NP89JjD4uGramwaQLWcrQqRI21uhnOmGlQssaEvgB/1P9PFezUxDJTPXbH/llPqy1+bFfWuY17VkmVZvHeld4tvMKpVx6BCeGw63KOi9UzzCpLaFrOnGSs1h1Ob1UoT5u8xxVxpd3pASuFLZpsDsIRAiOdGolm0wpNA1KthhSWhWHIJLYJEOX3sokVyRZXsz21jB0jVQTA8w4SEgzKc+mmaJecmhUHLJcHN0V18KxdNJMIylc3Vtdn5onZDVKpOQ7dWSfW60RxuLI/v2XtlCKe4hVEIsCaRs6O72AT1xcYaVROjAbrbdyaiWbhepbU+2mZqbdQYhr69Q9G8vQmIQSVH9qqcoojElSg5OLVR493qDsyESkmidJAa51bxbmOEzwHIuad7TamSv5PZuGKOFpllN276QrmqZJP6tlkIyjYiPx5lAr2Xzo3FKR4zlh4McYus5KvcT5tXmO5zuFOfGc4/2PzRtw+7qUyb2yRCiFoSiSi6vw2AeOHnOZxHD5Rcn/TJMZqao14ZGnZqX56SJ/+HFZKmTuKNiOlOSTWIinPxKjkO0K0dT1Yi56XOR3Fvmck5EoUWbhUg4C6e2cGpgG8SH3vRIibFoQp0efxxRmof5OzSdxJEqproF6ffJzDw4TTs3ggeaCz3EkMkVxbRU5mkfgvuqoocsGR+VCGg0DSiXZkEzGonqCbJI0nXvyb4BMidEsUCaRV0HTdWyVUoomYMTiNdItLJWhaRqxYRGbFezIp5SFxBh0E6jUamJsmYyxkwBT5ezbZTpBTk5OZjr8S/MsL+hLkMlM9e1nfodm/Sr/5ec/wHds6zhZwvH8FZa6Qxwlv4uBVebKiQ/iO2U2YoNSHFDVMpRts1hzWS9b2P09NjSX50Y2DScgijL2xwGdYYipS2JDlOb0JjG2qeNaJqcWJSBeg0IlVGg6hHFOEMdkmcKyDIzC6JNlYBgauq5hGjqrjZIofs0yrmUw8GM8J8PUNfqTGF038GyZPx6nOZc2+1iGzuMnmlx0mwcK2+HpPsMwwTJ1jLvKwVkm75llGoRJSq6g7tnUC8NMEKf4UUKS5m+pV/H63hBd1/johSXaw4hREKOhcfF4gzxXLNVLfOjsEhXXou7ZB6VuQ9c5vVzlS1f38EMxJU0Rpxl9Pz4gqUdB1yRsf6c3oVa2hYCmCqO4e64UCunTjJMMy5BS/ltB3bP58LllhkFMnOTzyUXvAubEc473N8IJXLskJOzEWflZmhQRSkqUyd6+mIgOI8/hS38Il74qrnbLFuJabQpRfPnL8OzHZiMrD8O05DFJfDT5TGK5j2XJsW5dk+OaphDJRhGNNPHl/v6Yg/GEhiH3SzIhI9MJMtPg+3AycxrnucRE3RGJdJcSeTCHvTivblvIovYmxyvefUylhDDNeedbhkKRayZGmqBz5/SiN6QQWZG/mueFkl2Vzc7KmmycrrwyM8SpXDYx08gxBZlukBbHsYIhue0QuWUGORCGuLpJgklgOjiIiSSxhHjoyHU3sKooBVY0RukmZjhGU4rMsMB26cWKz1stvhgt3TFTfe3ic/z317+VymdrlMc9ltMh5XiCWWxiEs1g21ti7/hjeBceoz7ocFMtsDMY87Qb0DIm2JpOv5tzC48X3XV6mY4RxNzcH0urt21g5TqGYRAnKVmuKNkWlqmz1iqTKkWW56w2SmgaRGmGUjAOUyxTo+aY1CsSj5TlMScXyyzUSrimwdOnF3hte0BSKHCea1EzbDqjEF2DZtkmTnMMQzIte6MIpSl+4yu3aY9CHllv3BNaXrIkyH4agXRwHRjiVE+yFNt00e8qC8dpjmUYWG+BlAVxykbHx7EMSrbJuVVbAg1QmIZOlinaowDXMo8scZ9YrDAOE65sD+n7EZZpkBRz4c+sVLm43njd5z+xUGGr66MpqHsO+6MJtuUW5i2Zr173bPaLPtD6fdzpD4payYa5wPmu4B0lnj/2Yz/Gz/3cz/Hqq69SKpX4xCc+wT/7Z/+MixcvvpNPO8ccM3T3hdytHBpfaR7aZeumRBIdJp5KwUvPw1f+WMihV5IFfOe29GYePyPq4+7m0cSz3oRmS/pBF1fvvE2pWXzSC1+SvtHXXhSi53rSJ2q7ona6RSC8KqJwjOKP+7hw5RcZgZiFspkmhWkkK8K8NSF/eS4KmGKWaZoditRRakZUDEPI6uEZ3G8WqjCiqGmf4Lzs/qA4cKgXKqSmMvLip4aGbCiyN1CwNU3u5ziidlp2YUqLZyNbtzfkdt2QxAVNQakwn6QpeZaR6CammaGnCXqa4MQBjlaEoxsmSlPkmk7oeMSWC5qOkcZoVonM0rlWOcmSkZDrKXqakOgWQX2ZgTL5vNbi583TZIkY/Qbrl9Af/xX+yxvPcsH4Hyi5r1FWv8Wav4WXTOS0dIO90iKRWwHbYV0LiAe7YFh4lSZb9ROkx0rEWcD1/RGX+zGRV6c3Sal5UCs5pPlIsjItC6UUOgrL1DGL33ua5tw6cL1r7I0CgiQ9iEVarNqsNysHhK/sCAlbrnuUXVPIpgZLNZfru0MmieJYs0zFtbi+N5QMTpVhWzrtYcg4TCiXLI41PKIsY2N/zChI+NDZJVabM/L56PEGL9zqMAoS6p6NKixlJdtA1zTCOKVVttkbBORKYZs6NddmOIl5/MSdk478KKHvxyilKDsWjbJ9jykny3OubA949XZPlFxdp1KyWK6XWKg4ssEwtdeNG9I1jcePN1mpe+wOJozDBMcyWK17LNVdiZh6Haw2Pc6u1Li6O8QyNUxNZ6vrY+g6JdtkuV5ifxhSdkwurDXe0UD6Od5evKPE8/d///f5+3//7/ORj3yENE35R//oH/E93/M9vPzyy5TL5Tc+wBxzfL2Io1nG5VFwXFEWpwHqIOTy8teKCUaHiKNXll647VuwdAz2tuDso3eW2UG+P/UIjJ+TCKVaUwhsFMpjBj3YuCIEcjSQL9sWtTIKClf9vpBQ15MevPoCoITMUuQoKoTgGeaMPM5OQsjmNCz+oHEQKYFrmdxnmv1pFPE5dpFP+qbzOLVZvyu5PEc2J5yHcbdqeRQ0TSc1HVKvjDIdzHEflaaYmsJQ+Z15S/eDomizsItILVUMSzBls2Q7xVAEt5hmlc5UcSDTNIlIcopUAz0j9aqMTj2GM2xjaQZZewtL5WgqZagsJloJkxxPy9F1nYFd4dbCGTLPIC9Bz09Ig5CdwYifKR0nTJoHTvXRh36Bv3lriU//0ffAxQ8QX32Fk7//72mM28X56PTdOt3aCqluYQANPSHXddy922wtncdeWeGjVY+en/DqKOXVtkGYWDIdqUiDMLQQS9fIMkhzRaYUoyglzyV709Bz4edJyqmlKsdbZV7bHtAfxcRpRpzlGJrOIExYrbs4lk6UKCquxe3uGEPXKFkmAz9ioeJwu2vgjyNMXccyhCwN/JhUy8kiRZylLNZclqqemGhGIfViZONrOwOW6rOJOaeWRCH84pU9bnckGF0rNiR+lOCYBre7Pl0/xtClh1QpeOx4g1NLYkxMs5xLWwNu7Y/wI0nAsE2dlYbHEyeaVIpyeJYrXrzV5ZWNHlFBKlWu2BsEbHV9LqzVObVUJU6zN4wb0jSNxZr7lgLYDV3jqVMtGmUxWpm6xt4wAiV9q7ahs1QvcWHtreV4zvGNwztKPH/913/9ju9/4id+guXlZZ577jm+/du//Z77R1FEFM1CZYfD4Tt5enO8V6CUKJd7m0LaTEvc4kurszzM+2FKyu6HNBZn+OHd9+6mlLGdIxryK1Uhf8EYHFuI3VGcdmkVnvrwzAmfJkIIwqK3E136OgddUSX9kTwuDGbB9MG4yEw0hZxOTUPTWCW9UBWnruQ7SuNKVNPD04fyHNIcyOQ5bVfupxly3Gl00vQ5HlipLO57+PkPSPCcfE7xIJwxMy2yUoXULQM6pmmiqQyVFpuNI6bW3AslcVqjHlAo3W6pSEAwYfPmrL84SWetEVPVW0Gm6yjTQaUpZBmZV8VfO0vYXKHGS5i9/WJDo6j5XSrBgMB0GVolxkaVpLFKq+qS5hmbIWzFNr+Vm/TM05CIU333wz/Pdw9svuMrf4l1R6dq7VH73M+x2rkBQKoZdCpL3GiexY1GlGOfhqdhey5qFJCMhijLQTtxho88epzlRomXN3qiLOZ5Qc60g97KgR9JtI+m4YcJRjEmMs0UmQEkItav6DIqcqc3Yac/oVFxOL5Ypj0KGfgxfT8kTTMW66WD0Y95LtN1XMvgC6/tcWKhwvnVmji+o5RREFN1LU4uVCi7Jtf3RpRsj3oRrj51eWuaTMxpD0P6fnRAqHQNlmsunmOy0w+Y9IPCoCSq5WrDY6HqkmZKZqIbGo5lohRESUbZMXn5do9Lm33qZZv1loyIDOKUW+0RUZLx0fNLuLbJ/iDg6u4I1zFROez0J1RLFqDRHUV8OWzj2SZZrliolt7RuKFpr+jJpYpMgkLaB+I0xzJ1andNLorTjP1hSJxk2KbBQs090lU/xzcW72qP52AwAKDVah15+4/92I/xT//pP303T2mOhx15Djcuw7VXhdi4nkwcau9I5NHjHzi63D1Fc3Fm4JlGEk2RZaJCnn/izp8PunLfYV8UIcsWAgszI8Z4ID2j5ut8hBZWxC0/GoiqtHlD4pDiSIwfNy8Lwa00IO+J6cMuzQK/w1S+L5dFsZrmK05L4tOWgWwab8Ms7zPP7yyl6yYzvU0JYY4K05IWz+7HNPfz6yxbmWYxtjOdO9yn0DQMpUR81nUkZ3NWNleaQW65ZG6JrFRBy3NCWtiDNoZK35xRqygVZ80lSEJ0w0Rzy1JOD33YK/qaT12E5/8Q2rtkSURuOKSaTqJp5HGElWfkpk3ilCl1tjH3NoiGQ25WT2GrFI9UFNkkIjFtepVlbnvLnNN9Phxv8mI35aesJpvxcUCc6tsf+iW+O7rN3/uDpynnNpp5nXr7JgsjmaeeaAaveMe54q2xpEJSpTFx6gSaRRT5rNsZFdckWV2D1jLrH34Cve6RK8UoiDF1cbUnWYZhiNroWjpBpAgTMfmI+1wnzSUSiVwjVwoNqLoSAXSr41NxLSqu9A5WXRvPNonSlP1ByGQvwbUlyzJJcyxDp+JaaEB3FPDosTqOqbNSq7LSKLHaKHG769PwHHb7AZah44cpuVJESYpp6niOWUzMyQ+C2QGev9bm+ettXMvAtXRQBo2yjKm83ZkUJqJUQuc1yXa1TZ3dwYQbeyMMXePm3ohW1bnD0FOyTdabZba6Plu9CWdXamz2fMIioN2xDRaqLmGSUrINSrbOTj/gC6/t8dHzS1xcr78rcUO6plEqJjG592nlvNUec2mzz2AyzR5WVEs2F9cbnFqqzEvxDxHeNeKplOJHf/RH+eQnP8mTTz555H3+4T/8h/zoj/7owffD4ZATJ04ced85vknQ3oFrr4g5wjsUgJznsHsbvvB7QvDSIkdzeV0ii6YKZqUmPZlXXxWiWanJbcFERkourspjDiMIZJrQsCch7ZWqhLzXCgNQEksI/d2GpKOg69LzmWXwyldEfeq3pfeu15HjhX4hGuby/0M5iZQ9cDwhqJYtbvypkWg6RjM7RDoPG4imvX5Zev/53EoVhObuQvCbIYt331eTH5mm9JnOJyDJhqXahMkQY9rWYZiQSiRMqulkXpW4toCmcpSukzll7Dgi0w1sQ4c3aO08jAxFhs44g9Rpipt8OESfXAZdR0sy8liRLR2n8oFvJfviH5AOeqgkQVcZdq7Io4Bc14gaq4TNZSYYhKnFRvUc+zgsqwn1oI8VTTAdRd3IyI+fpeq1UFuX+PHA4084BnHhVH/6t3nS+gp/9U8/SV09BQxY6l6l5neKc9b4w9ZT/NLqJ3DHAx4PNhjmBvU4JCtV8e0Kfd0lVoqLKyt4x06QL64y1B2SYUCSKq7tDrm1P2QYxBg6GDnFzHQNzzGJJzF+JMpulObYhk7ZsciBKM6wTJ1hmHB5q0+SZdRKDv9/9v48RpM8T+/DPr8jjvfOO+uurupreu7l7pLUSrJoSjJgGJAtwRYMyLBoQIYgk4QAw4AgA4YN/yPYhi1DEEQBskFLgClLoERySXFJcUXuRe4990zP9FXVXVfe+d5x/Q7/8Y03M6urqrtnp2e2Zza/QHVn5htvRLwRkRlPPN/v8zxl4/E+UDaeNFEQRdziQySrJb5xa5CTJTJvWbvAB4dznowLtocdUqu5tT3g5+9ukScV+5MlR7OSsharpkXV4ILMhQ6yhPVBjtWarG1hf3A04zfffELVOGonxvb9PKHxgWnpsKbd5tGc3VGXW1syxibJSBVfv3dIJzWUjWf7OfZARotP6KOTBXd3h8zLhqp2LCvH9iBn1Ek5npcSx9nmwccYubU9YHftYzpOF2peNhxOCmovx32rTUL6NOrxyYKvv3eEMcJWGy0s9HhZ8417R2ituLX18Qb6l/WTqZ8Y8PxLf+kv8a1vfYvf+q3feuEyWZaRPa+9eVl/MitGEUGgngadIGBqPpXXb78i6UDjI8k6v9kas6/y0+9+TszUH90TIEmU2c7rL8HdN562Ujrck/WshEHjI1GVr+Yxuz1hLF/7grTTP2l5J+MCTx7IuACqjbVcyn52e+eCkNm0VRmHFnB6AW9N087cKQGb4WN8NmN88WzrM/UpZqzrlYCp4flzCH8CKwbxjs0yYdRdAzoIODfivxpdjZ2doomUgy2Ub2gah1q/Qvf0Yctsf8wDgVJ4I23QEk1UmtqmjB1MVAeNQQUYFsf4J0cE/zX01g5m8w59b+guxti6wRlLaXNOkgEHW6+zYzP0B+/iK0+1eQVfRY5Mj+mwT+orisqxbRq2rOG3pxP+UX0XWqX64au/y/WdX+P/+tsvsTP/0+yPtnj16G1eHt9HrNbh+1uv89/c/Rf5VpFTNJ5ER67aHr1QEetCmEWboRtPWJZM4hrOKd5p+jx48wAfAi4Efu+tA/anBdE7usWCK3HOkJpCp+ypPtr0UCqe+UOWwVPUgU5qWOulWKtZVg3700gIUfLWnfh2LiuHUhBCILWaxgf6eYIxCqOF7Xz/cMayEjBotObGVo+q9rz1eMy8qPmnP3eVDw5nTJY1k2WFQpEadQbA7h3OeHtvwitXRixrR1YbvnHvmLJybAxzHrUsrNUKGyLHs4LGBYpa2umH0yVKwVo3o5dbhp2U/UnJ8bziowi/xGiqWhj13BrGrb2UUoosMVxb71E5jw+R8aJi7YewG4ox8s7ehLefTFmUzdnzcS+zvHJ1xCtXRz+SdVGIkfcOpkQiW4NzYK21YqOfcTgtuLc/5fpG92MFTZf1k6mfCPD8y3/5L/PLv/zL/MZv/AY3btz4SWzysn4WyjuYjc8jLi/WkwcCBC+aYoPMSN5/S1jK6y/Jz7SRiMprt2R9Mco6+8On1+kcvPumeBzuXhNWdOe6sJCzKczHMnP51X8Kvvxnnp4L/bhaLgR4EmFjVyyckrSd/VSSx26sMIWdbju32b53OpZRgdWcJvCJZzD/OCIvQzjfvfhD0HQ/6zU9lbEPoxHXcQ+uknx1m6CVxvuAV4pyuSR1BWlq6fZyzDzDl+Vzj6diBe8VPslwyuCtQnd7hLzHMmhO+tsEpSWiMNXko01mOiMJMJ8WTBYp271rrKmMTjmnQdGgWaiUwZN3MUfvklZL1qKwtZkeUKztoI0FEnQS+O1lxR/sJYSLSvXXf4V/958Mufa1P02hU67N3+fnDr97lqf+weA63+9e4ze3v8qDqkvtPUXlmJPyu/Y6MwdvuH1uLsaM8NTaskh7vK8G1Nk19uKQrgZjNA/35rx/PMfVDV9x+7xUH2G8p9aGjejZDfAg2+Sd0U2i1th2xhPAKIQ5bAJl4zDAsvFYo+kmliqKnVKIMl/YuIBWMOxlaGBW1MzKmtOFzGdbnVA3jslCIkSNVnzn4SlGa4bdlC/e2uCb945QWrPWSUgTw+mi4uHxgk5q+OBozq9/9zF5YtgfL+l1EpwP+BCoGzitHc4HitoxXdQEIlZrmQIqGpaVGLR3UkNmNUXliID3nmnpKGtJNOvlln6eUNSe6xvyAH51o4cP4Zlhm8waKufppgn9H4KpfHA059sfnNLLLDc2e6h2pnVWNHzngxNSa3hpZ/DxK3pBzYqGk1n1wtSitW7G0axkvKgvRUifkfqxAs8YI3/5L/9l/sbf+Bv82q/9Gnfu3Plxbu6yfuZK0VIMT/+4bNvkvf65x+Wq8g4UmQgortw8Zz1BmM3sI1jK8ZGAg+3W6/DRfWFVQUBqlsvM6J/6Z562ZPokdfRE9i04URsvJtJ+b02sqQoR++Sd8wQka0X4E6ozf0Xx6NSiTvdOQOtnzqR9JYK5nO18qqryPOEqRnDnAizjG1SSC0HtPVf33paZ0DzHhBJfFcT4LBiQd4tpgSGCd3hj5PKZjwlVRZIOWR/AsgpoF+g5j+oPiL01muWMB2t3+YPhNa4ODX/mwe+xFjQ+yVkmOevTfTbKMUkZ0MZgVWRQz7mlGw4ngdO169xzlt90BtfI7P5y/THLr/4t/vV3NvmFX/0lto7eZ8fdY+iWZ4Bzr7fL72x9iVlvA3e4zyIYhv2M6AtsM2foSyLw3eQKP0h3uW5KtnXDYH3EPO2hN3dIVR8/q1gezTmcFhxMRPRzy53wcrnH2PaY6eTMsjej4aXykDrJuNe7Tp5YsjY7vXaBygVyY6idZlI0+BhIgxFTACeMqlLQ+NCmHBm894QIy9oJM9qCzNp5Kuf5zgfHaCOjElXj+Cc/2ONLtzcYdjNu7w4JITIvG04WFfOiITGam5t9skTSkybLmsNpyagrnqGLqqFpIsaIxZFC/Da10SRGYY2i1xFG9HResiw1n7uxRic1LErF7797JEYXUWZbE63p5QmDTsL1TXlg2BxkrPdzvnX/mFnZSDRmnuBcZFE19HPLrHBMi5rjWcl6P3shY+lD4N7BjMSop3w2lRKT9toH3tufcmOzJ/Opf4TyIeBDxL5g1tQYmd9dPWRc1h9//ViB51/8i3+Rv/bX/hp/62/9LQaDAXt7ewCMRiM6nUun1sv6mLJW5jfff1t8L1dVlaLYTnMBgN0PMaLdvjCE5fJZQdFHVV3DKvGn25c2/GIq21OtXZAyT4PZT1p7j1om08k6hxtwfCDqY1pQqVs/zqqQz551W4N43yrYObeGWkWmrEDn2R9+xbNJQz9GL01lzv1EnxInXf6Rf6ZWDgRN9ZzXIrEuRIXdtp+DstRaoyNo58SA4OO24T0m1GgH0VqScsFuuSTMjxhb8dq0wRP8ktQ1xGLOpInc7txgPBvQX05weY8i67E13WezGlOahMYYusGhXMFaMcatXWNcOv7L0jMv1gFRqh///N/kX30455d+7ZfoacW1xQdcK/cFFAOVSniQb3K/f4vSZvSWp7yjuhypLsNizucn9xgWJxh/bha/bwe827/Ju50uVzo9lIZeCb0oVmmTZcX+uGBeNKjgeak6Zh4t85icHbAIlDphHHNuVifcs5s0OiezMpdJjFSVZxEd/dyyKCOdVtVduXDOAEZQKPJEo1AczyoSI0p5RWwvfYULgcp5SufpphaXGGKINN7z6GTJtGjYGeb085SycXxwOCe3IjjLrDljBbeGOfcPZiilKJ2jqEQctfIhbXyQ7WvN8bxivZsyW1Y0PhJjxCQy69jJLE2ITJc13UyAplYwKxveP5zxxs11tocdZkXDN+4fYbUiSQyPT5fosSJLNBstwNw7beikhgdHc45nJdc2enzp9uZz1ePTZcN4Ub1Q+T7qphxNCybLPzob2UkteWpY1k5M4D9UReXIWxP8y/ps1I/1TPyVv/JXAPhzf+7PPfXzv/pX/yp/4S/8hR/npi/rZ6Wu3hR7o5NDWN88V5Wv2vDbV59txcf40d6dLyrbMlEroGeMMJ+rmk0E8K08L8cnom6Htt2/9SwobWq4/7ao8udTYU1Da1uze01M6U0ivdLeSFTvWUd+Vi5WH+h8f1ZqdRfO5/20FhY1eAE2F2t1DP4oyvKV2fxHvrdNR7JWzskP7f/5J6xWjgGKczHYSukOBKXQUUCMjl78GH1B9KFlC1/8EOGViLpMbEBZ6nyAKuYtW+7JfUVlcsqkQ6IU2jdMbZdCp7y0fMJ4foQhUGtD3pQMqyneWCqVCHiqI4qMh3bE/zu7wnvqDhSiVN/7+b/DPzd7zP/6b14jDUM6yQdcnz0mbVX7lbYUOmOmcz7IdsiqBa+7GW9lu7zXu4Hznmun77JTjjkwPRZaOgppdNxoxgxK+Gb2Ciezgm6W4FxgXjlmy4ZFJaKXECO9WNP1JRPTbZm99pkOmVyZ65ztOKPvl4zrhNQGYowsay8po4mhl1mUUtzY6DFZ1pzMK7TVFLUnTzTdLKFqHHlqGC9qXJA2dGjNImL0NAGs1aTWYLVCI637xGoWZUMIgV6W0M/lV9nHSDezLCpp7/sQztrya/2UZVmTakM3sywrx+myItGKsvZ0sqRt/zsmSwGTWaoZdjLmpeOD4wWvX5e/Y7/wyjaH05JZURMjDDopt7b6qAhH04J396fsj5e8fGXE9qjLW4/HTJcVy9qzNy4YdhJubPZ55eqIYSelbDz3DsQK7udf3n6G+QwxnqUtuRCYLOR4Ns6TpZb1Xor/uD8xH1OdVFr4bz4c08vsU3Ocvp3TvXtl+KkJmS7rR68fe6v9si7rR6rRBrzxVUn3OXgMKAFnwYuN0tVbPDM1P5/C5ra0rX+YWtsUr8PZRLZ7sWIQpvKVz4vI57tfEyHSyg5HG9jYhte/IvOlICDs7e/AB+/CcCQgdH1L9n8xk20MN4WZLVqQ2TRiNo8SBnQ2lm0rfZ65neatUl3mtM4U5CoVEOgbzsBqtwvoc4D8iWtFFX3M73CMMrOYd9qIz89a2/8zVkkiYwgqXsCP58dYx0DUBpRBBY/xNaFNMFLtcsInrwCoar9S6BXTrS0uydDRiUI+BDAGFSPKe8p+n5gmdIopp9k6y/4GdVmzcfoYl6SkviH1FcSIQ+YGE6OZ6YT/ZOuL/GF8FdUq1fe+9N/xuc67/Ct/+E/zxvIWV93bbJVjTDugXGvLk84O86TDWjXBRY3znlIZojEc5WvUwy2uLk/YrSY8NAO8MjKzGqFWlv1kxNVyTN+eMBnscLoQoUw3szgfqZvza862l21AERDAqXhaOudac/XKB5K6IUuszGt2UgKQJpbEGHyMZInF6obrmz2KWtTnZe1ZlA1lHVr704BG0UstMTZnQWFZYmXbUQBQ7SUHfFE1LGuH1opRNxG2O0YaL9njWoPRhmE3IbMi7Pneg1NSa3j5yoiichzNS2aLWjIggEEnYV4KM9nv2LNoSzHOV3z34Qm7wy4b/Zz1XkbtBHAn1mC04sHxnPf2pxxOCnbXulgjDOdXXtrkdF5x72DKvGy4vTXgczfWyVp2M08Mu6MOj04W3NkZPmMU38ssnTRhvKg5nlccTZdopbFGvFU/OJyzNcjIkh9N9PPKlRGTZc3jkyXdzJInhsoF5mXD7qjzsfGcl/WTrUvu+bI++7VzTUDa8b6AG2tFOLT/6GnT8hjbmcwI127/cOIfkESXl14V26PTIxiuSdu9KmB8LMB0+xp8/+sCOjd2zrPYXSPWTz5IhnuayXsefSCANATZ9/lUgKlNBOBubcs8an8g86WxBYxr6/La++/Acikiodiyi6v2+8pySSkxArda/rH6F6FuzqMRf6js9U9IQ9hE2Nli8fFRjn9i6wJLGXx7HlYPS/ECVD9TZMmiNkXFgEsyKAtSxdl7nUmIShGVQvmAiSJ2MVoLWHQO4xtWPGniSkyEVDeYYowrFc55JskORYBlMGxrKKLF24zbs0PwDVlwhKTL/ze/zt/rv0H0GQpRqr+8/Rv8G9//7zFZ/k/4yun3+MrpW2St+KlBM097hBiJChoXeKT67GdrvJ1uo21CT3lsU6OIXGVBVOBEanVmR6sDBK3xWrNVT5myTWhpzPGiJml/x5vgCUHhSJnpjEEoOTG9s8Osoqyz70tmOmNhOmJG7gO1k7SfGCODbko/T1hUDaetor1sPEezEmv0mRJ9o5/S76Q8OV2yKBvJMr865GRasj8tWJQNMQR8hEAkBsiMppNZUqOZLBvmZcN3Pjil37GczEqsNWwNcmoXuLXVP/PbHHZT7l4ZcjApWFQ1eZJwc6NHs9bl0fEcHwVwF5UT0/j2d39ZeraGOV+9s8WbD0/pt+tbKdUvllGKybI+s0taVSe1dDYsx7OS6xs9tNHPvDdLDI0PnC6qZ4BnnlpubvX41W8+omwcW4P8bJbTh8D+pKBsxPR98Jw2+SetTmr5hbvbPBjNeXC0oHKe1Gq++tImNzb7dLNLqPNZqsuzcVk/HZXlAiZXdeMOvP1dsU8aH5/7VeY9ePWLz3pzftK6dlvuUB+8KzOYrmUZd66K0fxyCUf7YrVkLvz62ETa/odP5PVrt8QLNLg2Iajd50f3pUVvjLCeWsEXfxGsgV//Fej3hRXtDsTCabDWendyfjeuqgugMArAjh4af45bWtx5xpDWjRjGg6xjleH+R6nVfsQgApkkg8pxOdf5orpwXPyFmdznzuKCChCMIipN0AafD/BB47wjjzVBaxSRYBK80ig8PkZ0BINCJYm0loPETeIdqnFYIio6VLUk6gSUpp8oMqMpdWCZZATfEHWG1waL5+8PXuI/H30V5wbgRam++aVf5z/6zYQr3/lTHFrFy3u/woYTxr5RhifpBqcqZ2ESdtyc2iv2kz6p9hxma/isx7CXsaFqqsZT1QFfVTRRiZYwyuW5Gh1WyOdIYiCiMBqq2lE2kVLJ8fQRFBGP4YN0k68WD+iohEKfg5nMO0ah4LvJNRZKUn1W7CRKWuMbvYxF2dDPEzYHGY+PlxSVJ4bItKpwPtBNLWlizrxB+7nl6kafG5tdhp2Ufsfy1pMpzgUiUbLFc8NGPxcBU6oxWhjF94/mzMsalKKpHfOyYXOQn+W0Ox+YFQ2/+MoOVeP52ntH7I5y0kRmLA/GBctlxUFRS+Mj0fRTYfxOFjUbg4ytgSQeHc8rXr5wtYUQmRY1p/OKx6dLtge5zBa3f1smi5qjWcmycjw4kjnTF+Wyqwvv+3BdXetijMJXIqRKjBj3Nz5wdb3LWi/j/YMZt7b6f2SBEQjIffXqGnd3R7iWXb60T/ps1iXwvKyfzrIJvP5lmQE9ORRhULcrLOSHbZKeV8G3rWsrYo/DPQGN3sPahrTwtRUWM0axVjo+gOkE6V8951dHt7npxy3wrKunlxuui8BoOhb2M+sIoP2z/335DN/9Q0kqOhNSTWQd3okoKbbCJ2tl3y+WsQI+A63H54WozHLZmrhfYNTiH90373yGtgVPxfyPvq4/qfUM6ISnGsLaoGJAoTC+wgOqfVAw0aOCJ/GORhtqm6MMUDu8NRhAG4u3Gt3U7Vi0ImhDVJbKZBR5n05oWPdLrpoa8pS41LxrN/jK9H1+N9niv9z5Jcp68yxTnS/9Tf5vh7v8s3/wp/EHPyCWj3hpISMcjTK807/Ownbp1EtM8MzJyFRDGhxrzYz9zhZVZ0SmDYlW9FzJabaOi4oDn7EZHLHFCStAqNtLNg+OSZrjQyDPrMxJwpng6uLk6/1kk26ouVsfsR6WNBiS6Iko3ku3eTfbkaYB4skJmhAii8qxrBo6WcLN7T4xRJyLHM8qJoUwnd3M8tLusE0nKumklmFXrJOOpiVZYtgcdLhWOo5mMhJglKKb2/ZZMVI2gatrXbp5whuZtPVvbvV4fLJkUUu85nt7M3bWchal4/pGj7s7AyoXOJwULCpHnsKDowW1c/Q7qWSvR4WrPcd1YJAnDDsJ6/2M00VF2XhmRc3bT8Zc2+iTJ5r7BzMOJiWzsiazhmXj2BsvW8CmeHK6FLZcK0rn2T8tWFYODVhrMAp6eSJq9QjdF4h3ahfYHmbc2upxNKuoG08/NWwNJW4zhMhkWQtLDJzMK3yIdFLDzqjzkVnwzyujFUZfxmR+lusSeF7WT29pLe3vlYfnJ6mqFEHPkw8E1DWVMIu6zU7XRl473JP29427MpdXlfD9b8r/s49QXxpzLvDJu8+KfZJMlPqbSPb8tdvSrtdagOl8JiBRa7GKqkt5nzJtB70VV2UpNErApXOQakhy+Tq4NjIRYUcVT0UzAi8APj9ErVKR3CXT+fy6AIVa0Y9XCpKM6BuU93z4uK2+CzpBt2bxLusQfCSPDVFHKpWiiaSxIsTQApuIRhMUaK3xzuGUxatA0jSoNrZUAzY2bMaSEBXBWpba0VucsJOvsRiu8bAe8Ou9HotyF2pRqk//1N/kf3dU8S//k9dRpye45dewrfCt0ZZ3sh2KvE9tc3zjSJFLNVEyAtALNfN0wN7gKkknpyobFuMJp7rhu90ensC8v0n0x2w0S8ZG2L4VOByFgqVKeKyHAg5rx0XizRqZdG38yg1A893sGnt2xK6b0A01pU7Yt0OOTF+U/UaRpaI0V0oxzC1ZmlD5wKAV9zw4WnA0LbEatLaUTUPRON7fn5ImBqM120NJLDqYFOyPC66sd5ksKqzWGK1onGdRe+alzH52MsNL233WehkxwmiQUDaenbUu26MOh9OSx8cLDiZLdkY5X3lpk1vbA4nKTOFP3d3mOw+OefPhKaeLEh9g0DHc3OqzKBsym9B4T5aITdJ4XjFZ1kwXFcNOyjtPprx/MKffSZiXdTvLmXN3Z8Cgm1LVnt99e58YYNBNSa2mbDzL0hFDYG+85Ghasj3M2R51OJmXvF0H7uwO2Bmd/12snaeofXvpR4wWoLkz6hJjfCq+sgyeECNvPhxzOCso2/cBrPUyvnBzg6vrnzwh6bI++3UJPC/rT05VJXzva+fWRkkC99+X1vfudWmVZ7kwlr4R0EYUZjLriHL9rW/LnObujWdFTattjDZaQAacHEk05mhdgGVvIO8rlwLctq/Kcv2hmNWbfZn9nE/lX9qBMBaGt9cTi6VyKdvZvQHLmcyGJvk5wDSJDMdpScRBq/P9+bQqxnam8xJ0PlMt0DyrFnQGpSkQL8wEfzYNsbqKgk4osi5p8ChXokNAuZrUNRgFVZKjlSJ4T5nkIqCxGcYafJqTL05RwRNQ0NTYGIhKhCtyrWqC0hjfEFUX3+2j53N2F/d4a/NL/NfdNZbLNXCiVN//+V/hXyzH/Dvf+yrpZEZ8co+8EF9bpwwP1m7xtc5trswecaWaUfua6Bqy6NizIx5mWzxIN3i9PqBKO/RoKKZjdmJN6RVv9q7yIPaofWDR6fBw7SZX9t/lepwwISVExSCUuBZInpouaXtojRY1OMi0hzVRHMbi+TmYJH3Gaf9sOS4ca60UuZVM98J5Fo2mcDVmCYui5mi65HhWo7Winydorc4y1Seu5s5gyM3NPr1c5iYTozmel7x+bcTpvObNx6d0U8PUC6jyPqCUJsRInlpCDHQzib00rZm9NYZbW32utpnuX7y9wa2tp+3gtoY5f/bVXQ7GBXd2hhxOCkbtXOqjkwVKKdaSlJN5ycm8ZLPfoZcbrmz0+fz1EaULvPNkwjt7U3ZGOS/tDNnq5/Q7AoCNFgukxgesNeyNl1SNZ62bsj7ImJXubDb2eF6y3svopIbYztyu9xX3D2a8fzgXdlTDIE/ORgZG3fSZzPRpy3a+38zYGuRsD0UU6kPkeFby9XtHpHbn0vz9Z6gugedl/cmpB+8J6Ny5Kq3p8Ym0pK/dlBb6/iNhI2cTGG2KSf3+oxYsttna21fhg3dEYb99pQV3bU3HwnKO1uFrvwUP7wlIXMzgZB/yPuxckdz3poI7r8s8J4gl1LXb0rYergtAjkFESkkq7XPnILS57sZIy72qWv9PK8uvrJmqEtJURgee5xv5o9alY8WLK579p2XgRLjiARUjZuVG0GrTV2WMohsdjbEs801sU2CJWKUhz4llgy3m6OCp0xyfpHgMc91hlq9zNe9i52MRFhGIMaC9J6iWPTUpwRqisYS8T7AZh1bxV4c3+Za7iZq0SvUv/0O+ujPh377354kPTokH32J9/BAQtfh7V97gn/z8v4J98C6fe/d32KrHpFFEU4XJeJxuUHnF0BW8l+/yKE94mG6ivQMc5fAq9/WQx6qLrwMhBmZlzTcZ8G7nDjeaU7bcHE3k/XSDh8k6B3Z4lhRLO/+5OnarjImLV6RSkCQa00ZBrtjQ1TLOB04X9dn7lrFhrZfifOTJuCRPGjYGGZv9nF6eEEKkrD2zMrDeS1nWjoNpQado6HcEQL60PaCTJqztZjwZL2hqT2IMqalRStFJRYRz72DORj/lzs6AReXYXeu0AFShlMIaTWJkDvTD7CDAeFlzMCmpG4/SigdHCzqpba2WaqbLmmXt6KYGo8VY/aXtPp0soZPBa9fWOJyW3Njs89L2ObB9eDRnWXl2Rh2WlSOxisRo1nopjYsoItfWexzPCkKInM4rMqu5fWMDBdw/mPL+oeb+4YxBnrDeTyVic1kzXtZMi5pXr46e8tOcFTWLqiFE2GiP9dnvg1bsjDo8PJ7z4Gh+CTx/huoSeF7Wn4yqK9h7IMziau6yLtq5yUTA5fRUANz4WO5cxUJy1UMQkNntSyTncg7vvQnvvyUq99GGqM5tKmDyD34L3vmeqMmNkYxuEJD7wXtiyfTFX5D51IvD77vXRNT07d+D/YcCapU5V4unaRuz2Srk9x8JGLVWtrGYt1GbLcXj/fmM6GX9eEvr8+Ou2hGI4AnKnNkhRaVJosPE0KYNyXIqBoJOMNqitSLrdUnXNlHeY472oGnwzqHbsAGlIlFrmrSLdQ2ZK9hTu0y3djFR060WpOWcOh9CmtGbH6G8p0k6+LxHYXNIM/6zwUv8mtoGt1Kq/x7rN97i3/vBV1nf+zJ37v8uVw7eOYPID7fusr95i0cv/2mGynPdHZGoyKN0g02/oBtqlqQskpRFkrHlprxaHzC58RrvdV7iwbgks4bNfsqy8aja03gn5HmIeB8p7IBDO5A5VoRZXVVowaaOELUouX0UtjG0owQ+RnwQWyLTtruNEQunD5HQZ6381bpdiFgraUAxRkbdjH4u4iSjFYlROBcZL2rGS4lpVEqhNdzc7PG56yPGCxmNGXbSMybzYFKwN16ybERp7RvH3umSk1nF5jBHK810IQlBu2vSip4ua755/4g3HxjW+ynXN/vsjDrMi4Zv3T9mXtZkieHl3SGn85qD6ZLxomLYTRh1LEfzgl5mubM7YrNlNIva0bjAsnLkVjMrmjO/0GXlOF1UDDop02WNTw2jrlwXw07G8UxmQYddRQjyrDvIExoXeXyyQCvFvGwYdTOurD89l9lJLUbDk9OSo2mJUmC1ZN3nqeHqeo/DyZJ+/nw4Muym7I0Laud/6HnPy/ps1iXwvKw/GVUVAsIGaxd+eIFJSDPxunzyUJjL4UjU4FqLsOjdNwVM1JUo52/ckeUOHgoQ/eIviKDovR/Au98TgVB/CERhJZczYTfTNsFj75EwsJ0eXLkhoOW7fwhvfUtU8WUhP9Na/sp73wqbELC8YjFXwHU2gapuRUitsKgsfvRZzp/KWqn2W47LWDnO5fLZmduPWscnHSNYGcFDez7kuvIoYgx4k2JCwESHCq1MOwYCkkYVtcUpTdrUaKfRYYJtatjckWtQKWJdYkOz0r1jXENSLuTjZRkbNvIodtipvRgpqJQmQLIsyBpPosGnHcruiL9vNvjr3MJP+oAo1dNXf5NfOvyf8kvv/jy/8PbfZfv419DtZ3pvcIODz/1ZJqWn181obMq1vbfo+JrlYIPHTcK+X2PLzdh0c26VB+zbETY6mk6Hvd3XWMdyMK+JMfJkUgIR5yTqMLEK1R6rs2cm9WKAsdLMJUaTaFHlh3acoKodqlWS9/OEPLVMFmJYruN5K95fOLVaQSc1WKWoa48xitIF7u1PGHUzummC0VB7jzHia2qNJAwFpP3+4HBO1UR2RzmDjuFwWknuu3OczqpWjxcJ7UxpiIFl3TByIgJSSlrVT8ZL5qVje5izuwYuBO4fikXQa9fXaJzndFFxZa3D23tTlpUnSzW3twYs64bEGG5sdanqAUpFbm8PWFaOd/cmYtzeRtmOl/VTx6BsPI0LDAcp1mpoPIlWrUus5Ng3PnA0K4gR1ns5PgaS1gJqb1zw9t6En7+z9VxwuDnoUFae166OSBJD1Th6WcLOqMN4UXM0LZ5hdldllMLHcDa2flk//XUJPC/rZ7eWCxHnaHMeeek9rLo53d65OEcraU+DtLpXM4yjDQGRD+/JzOXWjlg1Xbkh/9zn4PCxtNhDhEf3ZE60Pzy3Hco7ooA4PRF2cjEV9rM3kHXee0tsoSYn4h/qGmE6Xd3GYoaWTTsbYDv/jCFAaFrAeXGZP4mAc1WRM8kzyHksF22f9uPLt+uQqci2ziJL47M2VCvgqXXLdLapUmoFEyONSTDBoVsfTg14rWiwWB1JYhCgFxzBGHSxQE3G8oBhLRSFbN6mRCLKWKzRpE1JbXtk1Zz04ds0TY3v9OkUY5TRTPsbHPstNt2U3+lc5f+T3qYsRYy3XH9M+NLf5d/6esZrf+91dtXvc/vwHUwrRHuUbfJbg9c4TAZsPTohJAn3R7dZn55i6yVN2iUxC2zQeCwHep152me9nHCaDVjEhMfJFntLR1HXAGSJptO2nY9mJcZoysbh21b4x5VGfs2sVrgQURGW3hOCzHhGhGFbgZ/UStLQtDgHWvrsHJ8bzIOA0WXjCEFY02XwOF9yjKjVu6k9y0PvdzL5ffPQzRLmZcN7+xMeHM1IE2HztgY5iTVnuetlI6I/nRoSq9kddZgVjv12TtOFwJPTJVYrbm9tYbQiTQxrrcXTdz44oXGeeSk56c4H9sfL9jlL0c0MzkeG3YRfuLvD23sTJouK94/mzAqxiOrnCd5HHsUlx7OS/UnJtfXu2bErG0dixerJhUjVeLSWZCjnAwsfRWmeGKaFZ60nKU+mvewb//yzqJVCaU03T3j16uip11ZjBi9iNEXFb3h0PCdEOac7o85lBOZPcV2eucv62avlXIzXDx63lkZG5i61kSSgVaJRbyDA8vRIlmka+V4hfpsRYckevQ+TY2EUI2K3NDkRQGOsrGe/ZT5jlG1OTwWIpLm03G0qPwtOPEA3tkWwFDzcf0tYUm2hWqyiTs7Nxp/JPv/QH3cVf8wzlz8E+/eZqQ/t7ycQV33YoTCiWDVozSpG1SZynVxkkldANCImnDEK7rUpjohSlkZp8KCcnMuIobQdXFQkvpCITCJBaxqToGODmU/kwcNacI2AYOVBGWxwKKXxWU7lI/r0CGt6vN/f5WB0g5eSPa40E2LS4dvDK/zXwTJdXoFSlOrLn//b/Dtxh//BW/8M1eM3GY2/jW0DBt7q3eAfbHyVmGbk5RztA+/YdR7YdZKmyy+evstYaQZphm0aemlOxBBCJEsygg2EmEDUHOsuR5NKBDUh4kNga60nKu8IiVEsy4++ui5efVFBokFrRdmIT6ZWYJScr8Qqrm50GeWW/al4VC6r5qkVrdJdz34GFLWjavwZcIqsniU0SkWWtaOoxUqIxLAo6jMj+8YHKhfQKtLPU4q6pmoCx1E+d5ZotFJ0Ust4UYFXrPdSbm71OZqVjLopvTyhrDXdzFI1jm8/OKGXJaRWs97PuLHRo2ocP3g0xhphc9e6KXVTcLqoKWuHj9BNDdc3++SZ4coo5w/eO6KoHdvDzlmc5dKLRVPwkbefjPHeo7WmrD1V43l5dwREvvX+CaeLioNpIYIiF0itYpAnFHVDYkV4NS1q8sSy0cs4WTx/njy26UzJc3w6N/qikN8fL7m63nsqdnNZNTw4mjPopEwWtTzLReh3Ut64scbtCzOql/XTU5fA87J+tqpYwHe+JmKe4bpEYHonyvJiIXeTk0MBmMbInOViBuMjaVFXhQCMVNJiODkU0DKfyvJ1KaC0LM63meUCZsulbGd8IiDTJPKe3kBSkOoCdCLiolXLfXws9k7Ogy8E1GjdsnPxBa3y1R/meN5qVxd+9mnnpZ+1rX+IShJJU1rt02e8ngWdIqRZ3Sb9yhtQG0iUMJHPgP0oudPaAoEQAovOiLK/SVLPCbMJXoNtGUXlHBkBHVZxmAqsxdmUJCDMo5ZZUaUVPoD2HkUgpCnBJixNjllMiNFyONzmcfcK8wbuJxsce8PfSYc8mt+Qz2BLTn7uv+F/URzxP//+P8P2/gfYJ/+IfgvKJ90NvjV6mb+x/U/RdAYS69iVWcJaJUyWFZ3ao7RmuWyYqT5rwZAUc8amg9Ua7QLWR7qxYtrZ4iAb0YSIqxpCjDQO9sYF/cxgjYhnVmzZi+riUdYKjNF4H0k0KC0Rk700oZMZupmhcZFhL2dzrcfRpOBoVnI0WbZznPLbY1XArZ7ntDBysV2/Uu1y7cQGSqEiuBgxSqI4K+cxSlM7T+OlDZxlhjzVaJ2hVE3lPLX3DEmxWlN7T2INZeXo5Ql5IkbvV9d6XN/s8e0PjlmUwi4uW/V4UcHBpODe/pQQIu/uTUmtYdCxuBA5npY0IZJoESWFCAenS3759+/ziy9LylPtPOOFKPQb58kSw43NHrk1PDhaMOikrPcz8tRwOCnJEs3j04K1Xko/szyZFFS1o5fDonQ8Ol3QyxO2BjnzUnxPb231OJgUnM7rs7nRizUrG7qZfa5AyGjFF29uUDeBh8cL+rnFtnOne+MlPgSurOUMOmk7phAZLyq+ce+Y1JpLq6WfwroEnpf1s1WPPxDQuXP9HJQZIyzjyaEAhiwTyySEseDWy/ClPw0fvC2spWrfd7UHs1MBk1UiLfAH9+QueePOeVt1eirr7nQF3G5sC7Pa6QlwnI4FsBZLMbjf3JH3xgjHh/LzpvXbXLVrDbJ/F2MudfueC6rpp+7YxrYS3/YzR//pgNA/yjqyLuhaPtdnbTjLJucjDDw/Xb41HyJoiwpBzNtDO0ObmFbk5Z46Px6xTHI2ESuk6KnTDtPak3lN1ySY2NBEGf1QBHRoQy2VJipFMFYuy6zbuhMUUJdom2KausW6gYimzvuUZc3AOebpgPlgm16/z7II/D2jOQ43UYUo1fe/9A/5M90n/JU/vMHmNGN4/JtYL0xgHK1TfPHP8t30OvvvvIeqS2Yqp3aebpZBYtCrnPGi4UHS5/PNPo/mOSd2k5vVIdtxjkrFozNZTDjtXuUH/ZsUukM/s4QIk0bsyXyMGCUZ640Ln3goZDX6EEJsbY5S0sTQOE8ntfgIZRNRIeJ85J9+Y4f3D+d8494BR1ONVpDqKOb01hArL79OQZ4Hq0ZA8OpXy7YTOonWOBOgiSRWk1l99vvrHKTWyPgD4l5gNaz3MqrWtH1aNBijSI3Ban2Wre7asYss1VSNZ39csCwdgUhqxSe0aBoRAflILzd4AkprFmXDuKiJQWZdoxKLoyYETpYVR7OS01lJJ7NsDTr08gQfAiFaTmcV3/nglNAuP+wmXF3v8uc+f5X7h3N+83tP2DtdMOqlpKnhlSsjBrn4fr67P2XYsdzZHpFnoqRf66ZkiWFeNIx2Uh6dLNkcZPSyBN+awxeV4/O31hl0kuee27Vexp95dYdHJwseHi9wIbDRzygbz7CTMOxmZ8tqpdjo5+ydLrl/MOXKWueF86GX9dmsS+B5WT875RphD7uD5+e0j9YlfejuG21rvRawtr4lrOXmNnzjt4WxzDutn+a8FaYIAEBp8ebc2BEmU+sWECIAsj+UFjoKFhMBXTFK2z8ihvRrG7I/vo2xXOWwn9kmNSuq5en9/zgAGKMAKrUSsOin2/BKnXvPfNLSH6ajPmHbva7aUYGPWfaiMOcnVau2+8fk1yvAhEDQmogiBI8mQDQXjqkoXcJKyKQUxntQENOcYahwwKIJ9JRinq+hm5rEVaTRY9rzExW4vEs92GCZ9shzJedyfy6rtRpluwQf8M5h6gI7PqJRHZxJUN2ca7PH/PU05VtuF1WmKODold/jjY3f49/8zi/yZ5oBVz74NrYNJWjSnPlgi87GJt3FmOuTJZOmodfN0P0Os6Ims5baebRWbPQzxouaw2TIJB2wMT/hJFvjSaeDNhX9ekZWLvh+foXf6L/BJPaxrNrWwuiGGOgnCcZooDmzOfok1c8M+ZltkGO9n1LVgcJHXIj084TaBUyieHi84NvvHzPoJISoGPUylmWD0YplJepuYbWlyqZtsbe/LlaDNYbaBXSi6CSWEFw7B+kRdwGFB7wPpIko6FfXs1KKrVGXjUGH2bJi0MnY6KWY1jt0VjYcToVdvH9gsFpxNCtoQiBLDIlRzEqxRvIhohQczzzDPKWXJuyNl9RNIEs01mhqH/AhYI2mcZ5ellI2njQxHM8LNgYZIWi++/CE03lFnliUgqrxnCxKvvdwTFE5vnB7k521MYOOMLKJ1Qy7KXliZAYzMTw5WbKz3mWrZS9DjOyPC7aGHb760iYfHM14Ml5yOq/QSjHopLz20iZ3dj86Ua6XJ7x2bY1Xr44IEQ6nBYezkrVe9tzlh92U43nJonL08+cD2sv6bNYl8Lysn51yjYDJ/AWtF2PP7yzPy3LfuSbt+fe+L+BxNhEWs2mEJTOJgNC6EuV53hGwqbT83NXSwp+cQKfTvr4Q0Jp1xT90Y+ucUVW6zV1HgDCqTT6q29z1HxKQrUDUCoDyodlPpSGxgBYm7ZNUksp+NRVnQPgpIPq8fVypyi+A1KdAnubslv/HMpu6YotfDDrPllQapSQ3Pa6W946nnN+VIRoFvhHbJCNwq8l7NN0BC3pk4YSSDvtXX4eqYPfoHqN6jvWB6DVBWarBFqf9LXqZxbo51EtQFvodyHJMkmGcw09OiF5jiOTRE9KUf9S7wt/KXiMsBihEqb52+x/xf/7dLV77w5e4Vr5Jr5zJ7tuEYrRDsAk1VnLcFzO6x1NuhIx11RCsZtbmoueJYVmL7dGom7E2yPg+d7hevc0tvWiz5TXTdMT3hzt8Pb3KsbeE2tNJxTNTLsVA7QLL2pEE/Yy35sedSR8Cw67FGsN4WTNZNpSNb00CxKQ9xog1Bu8jD08WvLI7xIfIME8oa9e2xiM+RMyFCZKLV0pqwCbmzObJ+YBtDeSDj4So2rnSePZcGXwkywQw1lHmTrWCfifhylqHTmJZ1g2zskFrxcmsQivYHQ3QSvHB0ZzDSSm2REVD44K0xr1HoShav9Mra7nMnRoE+LaWUFYrnI/k1lA1ntpVaA2jbkpZB95+PMGHSFV7tgYdEqNZVA2dxFI5Get5eLJkY5DLXGmv94x4J7Vi3zSeV+ydLnDt3ELjAmu9jK+8tMn2qMP2qCNeopVDa8VaL/2hbJCUUjKzGwXUav0CtbtWoru89BT+qatL4HlZPztlk3a2sDoXEF2sFRuYiDefsHJB/DFXc52vfhHuvy0M5Sq6MsslJWgVh9lEAZdZDuubknr05AHMajGYH23AyYHMfPYG0uaPEa7flhb8ci6eoMaKsj54ESG5pgWMF+Y1/yh11pJfoaMLbXnnhc4xiTCuT9VzgFpsf6b0D+EHGp8v5jkDn8/5XEq/YJ716VpBxacU5x+1Hz9qRY/yEFcpUGdscmhHLVa9Wk1Ao2NEBYdCkc3HmLqknzUkiKp7c3lEFTWHw10euCuoGLgx32PbTVGLKWvGMvAavZi0LgtBGHxr5AHGeZmfy3JcUfD73V3+k+2foy43oRGlunn97/C//6blF74+ZLM6JItyLlyaM7n9BbLjx2hXU4x2WLrIpAksG0k86pjI7ZP3mI52WwudiNGKqvEsq4bEWlwInJaa93uv8Hpa0Y81oKiyDt9bWJZOwJoCiIrGBRKjSY1mWQdRSqtIajVaRWoXeIEYWs5zCxATaylqEfHECMvKUTee2Br0186jlcwx7qx1SbVmWtSSq76oCCFSu4g1gNKSQKtaEGoU3gvI0UbhW0SaGC0G87XDtOy2qLhlGa0hNQpjDAEBYeu9DKL4WiZGsdHvoxVMCmEajVb80uu7ND4yW4qBug9BDOGVxEtWzuN9wPlIJ7OIw5EiTyzTsiEzhtpEtI50EsOybIhBlP7GKELLTs4rx7J0PCob1vsZprWimpeShrUzygUIzyt2Bh2OZyV5Yilq/1zVeJYY7u4OefXa6MytbKOfsbvWpZudLz/spgy76Y/0q9fNZAZ2Wbmn1r2qRdXQzZJLdftPYV2escv62SmbwJWbEmvZGz7bbp+eiDUSEb77NZnzjBF6fbh6S967viX/n0/FND7NBBR6J4CxrmT5tCO+nddfku28/668XixkHeubUNetkiGR7PeXXpVlHtyTuVCUtNaNlZa4MSLIiSvg9iOoyVcm5qtWdoznrOrK7ufpNzx/W646t4VSBnjee1eraMGjakU4XAC+K1X42TIXgOZqVOEj9uN54p/Vz36cltKq3RcdPMYaOXZKg1Z4BdBSTjFIG741hZcxXJkNHSzHqOBZ6IzO+ICkM6DZukkMiqqumZcT1t2cXEdsbjBZLp6yyzktpXM+JuE9qMi3elf597Zf46S8daZUL778t/m335nyP/wbXfrNAhslT91rQ7F1g9M7X6QebrF7skejDfPxpFWGw6lNOFZDEmBjus/y4AB6G5RNQ+0Ci0rAaz8zrPcynBeg9yTtstZNcTHSzyyUE0LtzkhvcTALFLWjbrMrQ4RF5bFak1qNC0Get55TqytBK/HRbJYBo8Tzs2hkfUnb4vY+UkUReDkXCKl4Yx7PSsrGifNYOyMd2vZ1VJAkilE3hxiZlY4QAo0PKAVGa1wjX3czI9ddjIw6KWXjqNrj55zHhcBWv8/V9R7zoiaxIvjZG8t5WOulzAtH0Xh8hGsbXfY1HExKfCtQ8j6yO0pIVwzpsiESyVKLaeM3+3nCdFmjVcR5aJynaUFwnlic95SNiIhCjDTBMytrrFbkqcEaTy+zrPcz+nlCiJJC5GOg9oFbW32+cf+YYSfBXlChxxg5mpZc3ejx5dti9/TjrGFHZk/v7c/Iku5TgqXaeRaV49Wro+cq5S/rs12XwPOyPt1azkVME6O0qYfrz5+3/HHVtVsCKA8ey0xn1hEmcTqWu9dgTUBnXbbg1EhL/egPxIIp68DkCI72oBxK+10r0KmA0NkYbrwEKGE2l3OxWzp8Iu3r7/6hAMnRhuzL2oYo10frwnwmqTCkD94TsNrtynLvfv/cngmEuVWmZdOUtPufag2rc4Z3NWIA56KlFejURpjZppGA6xgEPD9TLwK4SmyejG23oV7MfMZwvr2zVdYXVrWagXuOSv4Mb3486Hze6y8Cnxc74i8q8zHbCGi00WBSiDK76p8C3+2cJgqnNIlrgIhPcpRWRNth3nhUDHR8xbJOCMsFPu3RcxWb1rNYv4LNLdnq4aB1LPCNIzZNa6geeax7/F9ufpV71eegFKX60Vf+Hn/+dMq//vc3eWM6Iw2zdr8Vsyt3eLxxm04no7OY4quapVccx5x9M0Bn0M1TCp1wtPQkrmLdzWnmc07popQIX2Lra1q3mdvr/YTTuaJ2AtKytpU66mYsSidsZgukXGujFCPkVpNaRdUEkkT+LrT28S+8An2UI1LVQTLaW9ZZWrEQkX0wSuYEu6nlaF6yPylIrbTde1nSmqR7XBR5ltWKxBg2+xmNj6SJwYdI2YCPAdDt7K4k7RSNzLo6HznxlcxBZnI9F43DKIXRmumyZq2X8sUticRMW8/OCHzr/WPSxPDwaM79/SmdzJIajdKaNNHMCs+0bNhKLP08pfGRompIjWGj36FsPLe3h5RVIwyuD2gtzqRGywztvGhIEs2VtQ6DTkZmNZNFLSFqmeXGZg/nA+NlzeG0FFeBlkHu5wm3tweczEo+OF7Qz5OzqM/JombUTfn8jfUfO+gEYZbfuL5OUXsenSzFR9VqytrhQuTOzoCXdj56bvSyPpt1CTwv69Mp10hqz5MP2rlHJaBoYwde+QL0f0J+a50efOHnpV1+uCfMkbECAK/ckJz1GET1fvaejoDHr/1jyUu/eluU7A/uCbBc35KWeJYLEF0u5D1lIQByNpbXioUkHxkt2z56InZOt16Br3zh3EIpRFHBr+ycjBWLpvHpuZm9tQIsbQt4lzMoy3MTQmPlNWugRJhT3YLN1YiAMcKQVUt5XWXngDTLoPi4ZKP25uKcnN+4YvRaxfzzKsZzptesWE9awBlaJKhkv1sG7GyfniN6+vgpzGfro95zBlA/YWsfQKcZJs9k/4zGL4XBEmgCEY0iSGJOFG9JtCHahICm6A4piwqaik4zI3FT0D2qpGGtPMYnCcX2TfAVXV3J+ev0KFGY0yNCDBynA/6DK5/ja/5LqEqU6kdf+If8s9zjX/7tV3njZM5u9V67X4pF0uXx9l389jXmpWM8rdkIjqY+QdWORhsmaQetFcugaVpPTBPFY9TbVqwRI91MU9QCIhsfKWtHxKJVpHCeybJmZ9ThdF4DUczSa2HsfYyEVmyjlHg5+ijMW2Y1s0rOVieVNvyLajULarXGe5ktzIxwzCtQ20kt672MsnYsK0flZOazYw0uGkIIrdApYJW0rUe9lOsbPY6mJY0PZzZHLiTkqaGohNX0MVI3jroOoCFGTdmIKn6tl7I5yOgkCf/CV66xPeqyM+ywP1ny1pMJw07K+0dzJouKewczqrqh9pHGBV6/tkZiFEYptvo5ZS0G9ouqIUsMHSv+qCFGNgcZEUXZOKJS9HLLmtFUTaB2Hu8ji9JhE83NrT6DjrS6Q4AstfRyyaJ/fLLA+djmwivmpaNpAp3UstXPyRLDz93dZmOQ8+BowbJyGK157dqI29uDF4p9fhzVyxN+8eVtHp0seXA8o3aB7WGHG1t9rq13n2JkL+unpy6B52X96BUjvP1deP9tYRR3rwuQqEsxVq9r+PIvPn/u8sdRvQF84U8JaKza5KLBUFjQ2VTmMC/WciFAMM1kv/tDicBMUzhs4yuv3oKtXVnf8YEA6dMDKObnTGiSiFVSORez+aKQ2dA0lX1a1YN3pZXfH8HD+zIPOlxrwR0CPJQWkdQK6C5mAnYjQBDQGT2szLG1ku9tBmTSul9ZBjUtFKurc7smtTJDf77hs1R8jgAnvhh0gmxvlRB0kRmNnAO9yNMgU63ERj/CaAFIu7VlItsGOepDZj1n7OiHQKe58PqHy6wiSPMO1DXRFATf2iDBU9tQRDxaMtqjQoVA5mtS4ykqR4yKPFZsVmNUlhF6Q06VpjMbkzdz0BIa4KoSV3tm3Q3+042X+Afmy+ByFHD8yu/xS8mv8r/9x7us+RFrs++cfeZx0ufbo5d5yZ3S72a4XIQde+MlD+eOAZ5Mmda8HZTWzEtHIKBRrDUzHiZr7Ok+g9RyOCmofWTYSeimhm6bp73yg2x8YF42LEpH4z35WQxiRQTqxlO2reqVWEeHSJZZtNZYHcTC9hOmSsUQ0EoREJP+LNGUTcQ5MXl3E8mDDxFSIyzlrHb0tSLRmkaJWMe0vpe5tfSzlNCPnCxqbmz0mBQ1++MlnVTM3OvG0wQvQp6IePirSKoUhog1iitrHfqdjJd2Rrx8RQRN3/7gmMYF3no0Zl7VjOc1R9OSRSldAGs0j0/EE7MJgV4noZetFP8y46gQ43nXzoBuDTs03pNZjfMGpWDYTUisoqg8lfNsDnLWu5I8VNYOpWB70CFPNeNFxeG0Ya2X0UkNvh0r6HcsqdWczCtu7wzIEsNr19a4uzukcjIWkSV/PDnpeWp5+cqQl68MRWx0aZ30U1+XwPOyfvSajoXpXNt8WlGe5gLyDh5LK/rm3Z/sfnX78m9VpWREPzv7eSpK8v5IBEExyPte+zIMH4g3aLkUANofwOe+Igzqb/0DAaJlCUkms59KS1u9WMJyKjOli5l8/luvCBi+/5Ycs4f34OCJgN2qEhFJmgnQ1G0rPbT7og3kmYDTVZs6tLOgIbRK6wiqOW+3G/N0KPXq7m/T9uuVkOmT6opfsNyLbIk+cm7zwvfxRwedYTVT2rbrFZpgNOoTAppVnd1atZXs8BjxzkNRYKoSYsSlPaJz6KYkaNDhIvDUGGQmVPma0B8yqiZUVYPHYo1Ce4XqdMk78qDTmx7jnYOuJfQH6KahWiz5671r/BeDP0VohuBFqX539+/y//ythLvHa6RxiWIJwGlvk/f711hUgWXQLLIBA21IqwUm60rs4nxCB8eD7hU69ZxhOWWsMmLQ2BjY8gucNnytdweHYVk6YhTl9mJZkcSSZhqINqHIelijcT4SW/BlrUVrma/UWmx0rNY8Op3jnPhbhiipQ6nV+BAoG3f2XPRJygch/VWQHPOBTSTznSim787TSTWZ1jQuotoRgRgj/Y5lfZAxWVQCUr2MEKAiWmu6mcxE1o3YLZ3MSmrnKZ0XwLm61pAZ0bJyaBVZVpZhJ2V71GGyXD3ISdzk3umCygWOZzUns4I80ThnmFeNRFI6j2nE4qnfSbi60RWGNUTWuhm9TECnDyLyarzndF6RJZa1XoY1mk5imBYC/o0GF5GxAKCfW7pZQgSGueVoWtJNE7SCk3mFAjb7OZ+/KR6bT04XvFaO6LX2RNbozxSreAk6fzbqEnhe1o9ek2Nh0zZ2nn1tNfO39/AnDzw/XOaC/+LFqkpReQd/bh8EAvjuvC77P1iDN35OAGeSCpgsFi07qc6ZRDgHgtMxvP0dYVCrSr4fH8vPRpvnSnqjhTFVtN6iRlrhVSnq+d5Q2v2iioB+FEZ1JT5ZSVWJcmeOrXpft6znqlbRm1UBdfsZn0klehEA/Ahg+CJbIq2ezkx//kKy7mcU9j9cKS3zeAIEHVFrsSLiWRX9R82Eni2joO6O8D5gXCOWSs6htEIFT1SRaG3L7grwjIiRd0BhYwBXkxZzfFNhVILOMnRVkRDoVXNYGLy2pMWUKQmnqk9VKb7mu/zHV/55qmrnTKk+fOVv8x9+zfPF3++TuRLVcrNF2uOd3c/xZvcmMQZuHrzNWih5p3uDftblupsx8lPMdMmGqvlB7wa/13+Z66f3uTt7xMgvGfiAjoGp7fKt4cu81bkBiCglArtuyqvVAVthgQmeRlsObZ+3kl2mSY88sfQyzVovZ1k5FnXDonLUjXhLlu1spjGartWEGDme162H6Q93nleXk1YaH0Mbc3luQh9iZF46OqlpAbGh9p7aeZalY9Q/z02fFQ6lClKjGfUzroy6zIuGsvYkRpNYMacP8TzRKESwSonJQxSeOE8N1zb6hBix7UOtCGEUh7MKo6CoGrLUkhgjLfpSbKYOpgVrXZnlHHYSXr0yYm9cMF5UrauAZ/90Se3bh6Ag27iynjDsZBJFCbxyZci3PjhhWjp2R/lZQlAAlkXDlfUu672UewcZt7YHZIns36ibsjXMSIwhxsijkyXzsjkDnpd1WT+OugSel/Wjl2uBzovKJOfilz/OWtsQ8VCxkFnQVRkjQNEFaW1f/CxKnzO321fkZ00tJvPHe3B6IiBxBb5CkLSj+bxVcSsBqXsPRXjU1AIolwsRIIGwpXnnfDYThJV0ToCj1sImj9albT9Yk5nQwz3Zb5tI3vxqHxYzzqbiklRAXQjy+mq28UwurC+YxKvzudCPYig/qi4awr9ALPR0BZ7x0mlta84toT60J9pKjGQrSFGAyuT4qbq6ILCKRK1Qnzg5SckMZ6swrpXBZAmu06WyXZJyRuZqdHQ4MhK/aNvsK+17REWZ+IyI5Q9V2T4EwKCa41BMsz4meIbjfRpgqTNilvC9zjb/abrOdH4NKlGq+y/8Lf4P3zvkz/3tNZKqPgOcU9vl7atfJElTjhvoBRmjOMg26KkGen2W/RFvhxF3c8+iecJ+7xr/MH+FzmjEN3WHHyQ73K5PiOWSI9XhfrLJqR2gW5V+EyMb9ZSfK94ni4HTpEutLKlruFJP6LuS31cv0aQDemnCrGykxR5EilQ1HudD65sJnUzR7yTEGCmnJSFGOqnBuPZ4v8hT6UPlY2y3AYvKnbGRuh0TrmMgT6TdXjsvP/ORY1cRiGIG326qrD174yWL2jHqpmz2c/p5grWGfmaZLMpzcVp7OXoiJiq0ksjPRdVwPC9Z1p6NfsbD4zk7ow7r/Yy6afdPK0yMLMqmzbSX2U1rNf08pXYeawynC4naHHQSiJGHx0smi5omBGGTvajrD8YFlfPsDDs8OJzzg8djfAjMlg1H04LdUefM4ujaZo/rGz0eHM3ZGGS8dnVIJ3sWWJ6bJ1yyipf1461L4HlZP3rlOWfZc+o5bZm6hPXrz/78J139kYiH7n3/vIVdlaL4PtqHK9fOU4VW5Rr5bJstmzubwPe/KTOh3kubPu/IepJU1rts2/VKyXLzaQs+rLwnTWV7i7m057v9c+W5dyJ82txp50CH8vq1W3D7FfjaP4F7bwmQbSpxDdjeFbC5nIsIyrVAUyFAezrhbIbyojVScOeAc9Wqfi7o/CFuRMbS9ls/kUG71HOAp1ZgLLquCE/NY0q05GqP1GqbRKKxRGpUFA9J9dwe7uqdz/mMSrWxlwKec1cx725T2RzrKnzeZe4z1hbH2Ni0OilNIKJiIChFjBq92pcIIQZ0ksp+AzHtUK5dpQ5gp6d0qhlvda/x/7p+h9PJDahFqT790q/wbz58h//lf93DhvSspe6UZq+zxfd7Nzkd3kQ3NQsfeLj9BmjNw67nbnPMV+2cUXkqCTmlZS+/yj92GxzVmmsuEE3K42yTD5J1lsadYX8V5aYQNbg68Ep1QBoD+8kQrRUGqHXCYzXiuhtztz7kO0mXg1nRaq8UXkWKFhAmRmON2B95L7Y97VkkTRN6qWFReRovueafpFbTE4b2+aI9m6vPoCNt5nn7mdT5M8y0aFi2+5YnGtPOgbppRVE7DqfyOYbdlPGiZlmLQf3KtzO228yMzIgWpeN0XvE7P9jj7pURB9OSo1nF1jBj2EnJ04RF2VA1Hh8iRe2xre2RD5J+lCeGPJV5zdN5xaxs2OinHEwLDqcl2ihRdCcyo1nWHhdkxOFkJj6gWsHV9Q6DzFL5wPGsIrGa16/tkqeW/XHB5qDDei9jVrrnAs/psmbYSVnr/Wj+m5d1WR9Xl8Dzsn702tgRgDQ5FWbuYlWF/KXe/QwAT6Xg5TekNf3Bu/Du9wTceSevnR7L3OWtV4RFLJfSGt/clZnNr/0TeO9NYSZvvQqvf1mYy6oCP5dZVqWFUV3dRL2IRcg78rVvwHYFmM4m8lrWkZZ7nApo7PWfTjLKuwJw/8Z/JvsbWhY07cjrdSVgdt5msxsrueKtp+RZ6Qtw7SlQ2N6VrRUw+hQoU63PKK3/Z3ihAh0QwNntC31ykWF97vl40Wvx7DV1ocMflaFOxOzfoDDeoazG9EeyT2lOpVOSaoHxosI/g5krb01jSUBmep/6jO0YhncCZLShiJonZsDWdJ+sXmBCwGtD8J5EK7zSMtYQY8txqjPzyqa3jnINploQtIU0YxoTjALtHVGnPDID/otbL/Om+wJqslKq/xr/I+7zv/m1AdvjLrZlOD2aRdJhbjq8Z9b5nt5gdlIzauaUOuHrJ4HUQi+1HGzc4tF2h0k154ODCcfeEPtrnJ4uRJdmZD+NVsSoxDzdyUG27WVXNZENX7DhFxybrgA1V9GNjVjvqJRSWb5cPGDbzdFFyqEdctzd4MR0znz2tRY+2IU2BSh4YoxkicwmFk3TmsI//xL5qPLIoMaKsF9dtTKDKV/bdpKDCEaB87H18NQEFWUSKLH0Upm7rFuz+41+xmlRC+DUMiOqlIDdEKFuxNzdt0C98RGjFOu9jG4mYq550TDq2tYX1HMwKUgTQy9PSI1mVjQEhDFNrGltqnL++S9dI08Mv/qtx2SJxhjTpj2FVo0eqUqxhvIhstHLMEaj0OSZ4dWtHkfTiv3JkpN5xY2thM/fXOfmZp/Jsub33z1ksqwZdpIzdnNeNiyqhi+/tPlDpQxd1mX9UeoSeF7Wj155B175PLz5TQFf/WELwOYC0m6/Korwz0JZCy+9LnnreU9a6IM1AW7vvyMJRNOxAOW8CxvbYkf05jcEiO4/ks97/y24egNuvSzvSaywkGWx8tgRhnMFCtNcQMq0lrviaB2Oj4SpDFHAcN4V9XtTixgJLUDz/tvyfYgwGAAKJmMBbdWyBbyIe4CfCHvpnby/ruWOazttclFzYa6zBaWxZUe9ZFCfiZpC6yGaJPKBqpIzMJtaWfczFYV5Pfv2I8Q9H47zXKUpxSCoIgQgnivOtSaxlqgtxtfgIyaEs9hS6xoSm+BCTrSWqrdBPjtCu4ayM6TJewxCJfO0F2uFerRpd1ksf5RruHHyvtgA2RQfPLquUL4hWItCn83YoSzBptjoiEqjg8MnKU4JQ1vZHoWPmLpkf1bz/9ve5Zsbr6KaVqn+8u+zPXyH/+TXNF+c1GRxH4BSJRykQ95PN6l0Qs9X3M+3mekcoxUdX/OO2WReNdhGYVRGP0s5ahSPQ4/vVw2Z1XRdwBpD45x4NxpFWTv6nVQEL0EYLxcjfmXMjse2DgZ36iM23JysBcKm9SRVKjI1Xco68krzmNvNMd/IrlLYdclB8MKor+YkU6No2njLWdG01kzCKH543HjldXCxWutPfGyfbQAdeIa/XlWb6og1kr0OMisZYyA1RnwPfMAH8eDME0XZeKbLmk5iqBND4yPOhbNRbh3PBUYAa90Uq+HdvTHHs5LXr69zZa3D3nhJUXsOJwXdzGKUeIBWTSAEGHRTjFJkiaabJeyPl/Qzw5Nxyem8ZLyUrPMYAsuqIbVaWPQgYxzzokFrjY+RVCsaH9js5mTWcm1D0o96nYQ//8XrZwKhQSehajxvPR7z8HghDgExkqeGN26s8/Lu6AVH8rIu69OrS+B5WZ9OXbkp4Orx+9JeDlHawNduiX+m/gk8RZdLaWGfHsn3a5syl/nh7PaTA2EyX3pV3nNyIKxlkko7u1jKa7vX4a3vSut895oAzG5fQOPpEbz1nfOIzOn43C4qeNlmkopqPQYBO6Y1hF/MWp9NLXnmV9q50pNjWdfGjhzHvfcFyFZLOX7dXjszaITRrOp2LnTVPkeA7oq9TMx5rniayr9iKaykVTJb6hoZhVjl2IeWNVXqHKDW5YV5yyh3fUFbra+o/xDAfE4bW6unLZWeWq69o0sEEK1RIk8JmrQwP6apIFatqKo9nqvc+ZBjOxaShFA22OUUMc+B1BWkyYBEd2Ax5Skv0tVYgooEpYl4VHTgLTpUHHc3SKyh6wtC3Yj1kGuIF9jkoDXaGgLCnDZZl3q4zbysSceHmKog6pS/uX6Dv939EtRDFDC5+hZbV36Lf/93OvziwYQ8iMiqQfM4WePra6/RTTTDZsEkJBilmZsuClivZ5RpznG+Rm41WilmZcO9wymvXB3x/sGMsvas9zIGecKok7I3XjIrG1SrVieKkXoTxMexcZ6inQGulMWjeLXaZz0UzFTOXOUk0XHHHTMMBcemz7HpUeqUY2CrWfBa84jTfs486RFCoJOaNg98NT+oKF0E57BKlNO+BVOr0jGw5gs0kVonLGxGDOLVqRWUjZd1wFOs+IdrdVU5D0QvZuvttZUlBq1EAb6o45m5gvee00XFra0+N7b6PDiaMy1qCGLQ5YlnbXwNnC5qiJBazaz0nC5qBh2LD5Gr6z1e2hlwsqjp5TIHOy8bEqsI0TLqZtzeHrA3Kah8wBiNUXA0LRkva1R7UJwLZ2ysXLIBF8AgqVCd1KKUwvnA/rggSwxGKaraPzWzqZTilasjdte6HE4LqkaEVFvDnFE3vZzvvKyfSF0Cz8v69Gpju2UIW6CSZj+51KKTQ/jBN6Xdb9sZpUf3xR/zc1+V/VrV0Z4Alv2H4skJwvItZ+eRiCGITdKTD8QS6fTofGzg+ECYyPlUPmtvIOCwO4D1bdmHnV1hVYNvYw6B0M4/eifLpJkAvsFI2L7dm8ISf/9bIlBSrU1RVBKlOZ+dgz9t5Gbrmna2tG3pr2ZtXfN0slGMApqVktnSTk+AcrGQ5bSW1j/IZ7dGVOErZfxT3Xd9nrnuPk6Nrs6N7Z8btanO+7tnUZ5eAG1EBvqSTBjlEGSf6laElWRyLJtKlg0e7WqMsRgiXkmMIDZFG4OaHOOCRwUHKmJYtfoFufgQ0fgW/iq0ClQ6pcCgqwrTLFHR4dGYlZxIt5ZNwaPqUtT0aFySUXf7HBQLNpXlD/pb/Gejz9OU21CLUt3e/W/5N/5wwP/s9wKjIA9LtbIc2gEntsfEZHR8zWx0lXTpuTU74Fh16PiK3C+Ympwnm3dxaogvGqIGYuRkXnFvb8qyFpGKNYqDScFkWVE3IgSUzyexl+NaWrYr4LI61xPdwSnDzWbMB8kGoQXavdBgYqAgQRPIoqdc/WqZHjeaU7arCaeqgzFQNb41kYfKnecGgFgrWa3RSiyDiJGb7pQ71RHrYYmOkVJbntg17vd2USZBK00G1N4R4wsxJwCpgbK9fJsAqY6SlNSKaFyMeC/G9quKKGoXeXC8oJsKENTI3Cs8PWWyUtnHCLULpImnn3dYVo5p0bA5yPn5l7d5b2/KwxMB2I3zOC8WTqNeytGs4nRWMeqmbA87otIP0rpvQqBx4Ww7zsfzZ7h2X+pG5lBdEBZZKYcPgUXZcGOz99yUoUEnEQHTZV3WH0NdAs/L+vRrFZn4k6qyENA5n7Xm9RdayMcH8P1vwM/90rmSvakFZE3HAvrshT/A3kn60DvfE1D48D70++2dqxIleZbLugajcyul+VTEQVduyN3g6AiKWbvS1ZBibHt1Rv5flzLPmWQiatJW2urjYwFjna6wc7SK9HAxqrJlJWOQ9ayU4AC0d6ZiAfUF8Dk5ETDb7QvoDK2Pp1LClK7EURoBwkrJ+7z/kO1S4IW3+zOF/KriR4uMVhGaiqeBqW/Br26Z2hDFCN9cUIq4WmIsEyB4EQZVFZEKry2NTkgbJ9ZHjafUCQRFNzgUuh36ixji2UeLQEAz17mMaxLZaGbEEJmonJ51qGjwwUlKkTZMOusUKqGrPP1qCiiMbyjLkndUxr93+0+zWNw8y1Sv3vgV/sIPHP/jX4Zd9xgQdvEbm5/ja52XME3BtfqUvCm50owpj5c4DGOdMSMB73g33ea97hUSO6CpnSQEeQFTish4WZMnmkXZ0PjAoqxp/LmnZQgrex5onMzCWquIWjLPIxCVYqYzKmVZD0tmOsOjGYSCTmw4tj1KlTDySybmPByiVAnrYSnPRZ4zL00uXEJGrdrlkSaEs1Sh280JXykf4NEcmT4eTTfWvFIfsqFrvpPcodIZRguTrS5cbs+TjZUfuvTqliXVwLyqISpijFgUVTsWkFotzYNG8tcTo8lSi1aKom5kJFiBXQmO2g0GYFY6juaVzIKGyLwUe6Z+J5Es+cbTBIkYvbrWJbOGd/YmpFYzTFKsVhxNKwKh3YfwlOmDVTIru5p2sUqjlEZrxVo3Rbd/+5ZNQyjleI8X1U80beiyLuvj6hJ4XtZPfx3tCYN4EXSCfL25I3OZR/vnPqJZLu317kDateVSWtA+CLPmvYiPRmsC/ta25H3TEwG3dS3emsVEwGhVyDqaBk4PWybuRMCRseem7zqee3wmqYC7Gy9La302hr1Hsl9NDaH1BV2l/6wsn+SDifz4rMXY3nJX5F3S+kuGdmYT5LO4Nj6zqVurJwSULqbnoNiY1ns1lc/Z5o5L0lE7LhHieZv64m1eCdt3zsd8TK3aev7DgiYEUDdBjlFVyvchCu2kWjFQkkKSg6/xZUnwTthHY9BJSuZKfAw0QQ5UHisqkxG9EhW682il5MbezrpFFFFpCpNjdCT1NZUyjNM+hUq4ZQq8q9C+QvkKn+ToXp/aaZLlhNrmzDeu8Sgk/AedXQ6aO7Bolepf/Pv8a4/3+Nd+OWHLSexmjeF72RX+wfALqE5XmLd0SOwPUbMxWbHHWr3g7d4N9uyQxgW6zYLtZsJRWOe07tK4gDVaxEIhEpXGhQDKUDtHUTeSoqQUEIgt2FqxdEqJ+lxrMZJvLpyLWifcT7ewOEa+wMaIJgrbakd0Q0PyobwnTcBz/nu4GppYXakX+bc2hRQfIAsNr1X71Mpyas7tzhYqo1AJN8oxm+aYD7q7gMEquUTihe185OV2YRlpv8ugqEfEQTLkEamixxoRXwmQVySJmGRN26mOTiIBA64FnroFoUQoq4aIwofAtGj4nbf3qRrPrJAYzBTDsnI8PJlzY6PHqCvpUkYrThcVp4uKsmqjVy/stIIzZX3HKDYGOdNFQ1E1FLUo9WPwzCtHUXte3h3SyyyPThaXwPOyPlN1CTwv69OvupLWd11Jy3R962nfzE+7xsfCWj7PyklpASjj43Pg2Ru27eMIx4cC+mIAtADJugCVwO3XxKszhHOmcjiUFvxRmwPfGwJK/r9SfK8YyCQVRnM+B9+KinQLykKA0VDY1KM9AbhW1M/CMjoBw/IhBGieVdtfjBduuauvlRGAuWohm0RAYt2IldRiCod7eAJ10kVNTtEhorRG+wAGjDIyP+rq81lLY1q1fADlz9TcFw50q4p/Phv6fM5TtybiHwEZvFtJo1l5c6K0nO9eK7Ra1qI69r511DTgGgEXylCalMqkbLk5aahlbtBmpE5mRXV7/GQeUBGMJVcBHZzY2xtLTFKMD2I+bwzohNpaFjanWVY0NqcyCQfpBv/x2nXenb2MmopS/eTzv86/tHiTf+vvdthuaqDGo/iN3qv8N70v8Fp9wFKn2Eb2RevIotZ0AjQhcJSucTrcoXSKSnmmKmW9nvHa4iG/Z3qgzJlIJEZIrKJqApNFdXb6YoykRhNaQBSCLFc7eY8we4EPOxrNdEajNffNDh3boIkMfcmd5giHwVJSct4xUDGSRs+BHTy1noBc+iuGcnU5RyQuMwJbfs4glDy2a89cBkFpZjrjWn3Mu8kmVRNadvqT1+oq6yRKnsta0LkCw6uO9EqBn1qFCRFlIDm7BrnwnCfg1CNZ6qvPWdYeY0T08/h4gTGKO7tDMqvJEkuMkcQIUD2ZVSitWj/QiA+Bg0nZxlSqM1ZVIwb8PgQ0kFhDZg1aO6w11E3gyelShGRZwhs3BrxxY52i9Sn9/I31P/HzmyFGjmeljCMgllnr/ewyDemPoS6B52V9urX3AN77vnhHrv5Qd3tiUXTr5R995nM+FRDpndgQbWzzNIfynPowrhmtCxP66AOZ6+wNJOO8rqWt652IjQgSkTk9FaFURLaprQiEklR+PloXYHa4J8KdTlfY0boWu6XoBbQZK+t3LRMZEUHR9dsiRloBuzSDsmVGV5ZDAZ7mbC6UalnGMy/VC+3r4GV/i4Wo7ns9vDH4yQRnK2yoxWoorN6vwAeZYdQGbDwfJlMXh/MuMrBtreyWPlQvarTHGPBRfUyK0AqoX/heIce5KmG0iS8WOKVRJsEQxOczOBqVEVXEa0MSneQ8t8DYRUXUCZmvzoDHCjIHbTAqitVQcAyqGTEEah+wOtBTHqc1M91hHHN8Yjmhy69eucrvxzdQU1Gqn77yB/xC/7v8u7/qubkIwAKP4ludm3wn2eVRss6p6UhKuvdUK8GKipTOc7WaoUNgoS2FV2cmA1lqOPE9rrgJa82Ux8la28KOdBKZlzUtG7iyGYrwlB+qjM/Gp9rTz7M93bcjXq6P6MaapRbWrFIJ637BFTdhqVPGVsR7JgZ23ZRj02PPDp9Z1+oyXW1vdTW33W+SKLOK8aIY5vwt1MqSeI+OgaD1U0zgJ+DXz5ZVSgl5bzS196h4rn5XSrWOq+CDiH12RjmgSIzmdFaBiiRWExsnQWGRs1QjEIN7q0RtX3sRAR1OS7QShnmVXa+IjIuKrX6HEBVl5ahdoKgafIROYshsJFn9DgI+SPKT1praRRJrWB9k3N0ZEkLgzu6Q7WHnLHmoavxzjSVWM61/UsDorGj49gfH7I8LXAjCYhvN1fUuX7y1QTe7hEI/ybo82pf16dXRHnzvG/JXeOeagMwYpD391rcFnP1RYzOdE0D76F6r7G4B7HAkbKNzPNfAvo0ufMpftDeEay+1QKxlzZyTucfBSFrzKGEcb96ROc/pibSoi6Wwhj7A+qYgAe9lbrI/lHnT6VSAaacvYHLly7lYtMKdtp0/a8VJwQtYbRphOzvt/GXRCneMBd/mzF8srdu73fNYQ2kcnmW4QyuGKvBI/o1V7SgAoH1DSFIcllSDWbkkhtCym8iA2erBIa62H863Fz7Mgr4YdAItOxnbCMvnmee0tRJ8rVr+ulXgOy+jDa4RIlQp6nyAimJbpFSgMhkhavyqpR4CjUrIg9zcK52RRYeltUWKoliv0oxZ2me7PEXFQFKXpBqSEKliZGkSCpNglOKXN67w6+ou1AMUML36Fq9c+8f8R7+TcPfx9AwYfZCs88vDr3Koe5gYueHHPGCDY9Nj0y/Yb8FaiKBDpOtLtIocqB6Fi6TWkCdaTkkOag6Zq8GK4GRlCh6iREX6GAgxnJmsfzjAaWVH9FF1ZHq8nW7zuWqfXqiZ6QwFzHXGmrYUKmHNL1n3SwKKY9Pjm50bVPo5yTjh6Sv4w/6btbJyWcVwJmS6WFl0lCqhjvoMhFsNmdVULuI+QUKVVmCUpvKBbqrpdxKWZUNsUbfEVEr6VIgRpRVlExh1U3ZHHd4/nLGsAgqxgXIhPpMKa1qXCaVa70+jGC9KNJqknR917cOkUlCkDcs6YIxio5NxAvjg8VGRZ1Yy2l2grB2uFR2pdl+7yrDWTdkaZJwuazpp8lTc5aJ0vHJ1eAYwDydL3nw05tHxEqXhzs6AV66MziI2fxarajzfuH/E/njJzqhz5lNaNp73D2f4EPjFV3Y+U5n0P+t1CTwv69OpGAWgeScWQ6tSWsBc8PDgXRHfJD9kMkYI8M3fhm//gawv7wiQHK4JEJzPBdgdHwiT+WFx0XDtPO4SZNn1TVluY0vA3nIm4p3p+NzEvSoF5Nz9nLTjT4/h6FBAZ7cvM6Jai2hnNhF29OXPwftvw3LasqRRWu9lOxzWOAjVeb76Yibq+yRrW+2pANAkgcpwDt0u8jrqnNUktP/nwmurP6AtU6KUMJRG47Um1A3RJJL80i4ftUW7gNUNNA4fPSbA2eCo0QLOz/LuW5pHJzL7uRIQfazK/YUn+aNf1gpUKzRKUhnjcBV4LzntxoKHpFqigoCtxAeij6AtaRALIbTBRo8KHgPY6DEEgpbPFaUvTbde4Czsmz5Lk6PThM5gwNgrqmXBejXh61mP/3zzS/hCUq2W648ZvPyP+I/+sOGrv7NgFaR50NnkcbrB1+0ux6Ynp0UrqmjZCXN+kF/hq8UHXG9OGZsuDk0v1AxjyUTnHNkBSkGeanKbtKmmCabWdLspiTbCgilIrTlTpxdV+bQZQXsF6R+KIlR8P7vK3OTcrk8YhoIIPEzX+d3uHSoMo1ihYmRmcg7sAKeez2F/WPyzYgpXzypHps9Ud1jzS05s/6lldQz0QsVb+c6ZjdXqmauowyf+OIlRZEnbJjeKxnkqF87skQJBEmXbHPkYoKodsZPig4iyBMMJZ/s8K6cQIspGTJtLfzbCEQIhingpeIXSkWUt9ktrvZQsEUP3PLW4IlA1gUHHoLVCWU1Rg9WaLNGk1pAYxe5Gj+1Rh0lRo5ViWTeACL3Gi4rUaq5vyLH81vvH/MNvPeR0UZNakXy9/WTCt+6f8C985Tp3dp5lqX8Wan+8ZH+85Op6F3Oh45YnhivrXZ6cLjmcllxd737EWi7r06xL4HlZn04t5zA+EpD5vOqPZF5yOj6Pn/xwxShzk64V3/QG8rM3vw5/8FuAgsFQmMeH9+T1m3eFgRxtCPjZfywADgQEjdbh9a886+W58t88eiLA1V74VUhbe6KmAqLME663NlG9nmSz15UIijrteou5MJ6drtg5Xb0lADI4WTaEViDUCo1s3s6Ntu3qbl/Abt4VMLqYCVgM4TznPu8IqDT2nMl0Tdui9xeEQBpo2cdVXnwipvARiS80MaBWYnWlUNGjg0cFRVxZJZ2fGNlng7Cfq/6ita1facZZEtPT7/rYksnaD7GdK/uliwOHEWn1awN3XpfRgf1HECI6SSDpUC8WKFdiXA0hYoIndzVGJSxMzqK3RhIahtVM2qqrvPezBCWN1wYfIQuOvltymG5zkI4wScqa8zhl+X5vk79z/XXKxS0oVpnq/x3/x++e8uf/q+KsVXuUr3MyvELTX2vnKNdIaoVrW9whKlSMHNgBv995idvNMbtuSpdAqRL+MLvFRliwDIrdPGGzn5OlVvK+l3N8kmM3dthylnntyK0hSw3zZcN4WZ21sC+OEgBn2eYfNVr71HlUigfJBo/sGnmUB4tCpWct8f1PtppnHi3OMta1zHzW2vKDfJevFg/YcVPGuotXmm6oWQtLHts1HibrH7nOj92HEKmdKNLr2p8p1FdDI3E1mtAem9p7fBCR1jfvH1O7SDc1uCCm8h8+hka1D3NR0e+kTHxJiGKc75QiswZ5vFFt00BROU9mLa9fG4o3p1EcadUKnMSftXKeYSehagLWKPq55db2gC/e3CBLDO/uTXl4sqCbWY5mJYuyQWt4/doa6/2UR8cL/ttvPKBoPLe2+lijiUSKyrM3XvDffesR/+ov5Qy7P3txmXvjohXfPctoJkZM+Y9mxSXw/AnWJfC8rE+nVkk35gWX1Iope1HU4smhJAedHp6rvjd3BVz+4NsCRLZ2z9m8bl+YxsfvC4talfCVPyvM5PhYllnblPfkXQFv01Npz+atHdJKzHN969y7Mu/Ktj54R/wuZ+PWLK8WJrM3FJP58Qnc/4HcPQcjAbIxylhBVbYt+nsCTlcG5d4JO5mlsv1iLttbeXuCgMfd63I8stan8nD/DBjhvYwOpLm08ouF7O/aOuw/aRXx7tz+KHg59kqx8t4M2mLrsk3fAbRFtdtXoY2Z1C3Ada24ZzU/qlNhP7WSc9Tpws1XZJvvvy0PFt4/x1T+OZeMSfBodGg4U8PHdkRAt1LnFXw1WtjnNG+TipQc984AFhPSEPBZyizr0Cnn5Mspq8hMFcUYvlAJ2iDenMrSCTWGQILYCon0RsYPqqCpdcImJZUJ3I+WvZjzy1trTGZ3z5Tq4y/+Gv/mw8f8r/6r8izlZ5YPee/K5xlHy7XlAXXUPO5t45sE7SoSpcRWFcc7uiujvrbHie2Rh5okBmqTkAbHLyzvsVuPWc4ip1rjpgWmWLBByeHWbUKvT6dybby9Yr6sGC8bQowkq0kIxVOWPNBOiHxC4GnbZXuh5oqbsBEKmqg4sgP27eC5bfVPWoqnE4oeJBt4NC/VR2z6BZpIqRLezK7wbrr9I20LoA4QaidAMMh595FWsCNJVM7Hs/3xAeZlzXRZi8mCPreBUm3jIUVmRANtApMWAVftPNYYahdovAiKOpmlqh3LphFW3ijyNMEYRZZY+kb2IcRIWTnmpePKKGfdpuxPCmof2Rp2+Nz1Ne7sDM+A4stXhygFV9Z7lLWTbWvN/YM5p/Oah0czxsual3cHZ5ZLCkU3s2ypDo9PF7y3P+Wrd7Z+pOP7WawmBOxHaAuE+f5hH2Eu60epS+B5WZ9O5Z1zQ/LntdLLpYCGvPPsayeH8J0/kHb0aKNtpZYCKsfHcvdM0qfnN5WSqMvZWNad5HJX2L4qaUmrpKQYpZX9wbsCPJtGgFh/2HpXZufioFXVlbCcWS4A86BVnfeGcOOOANrNHZnFPNprVdZWWvEKYS7rWo7F+hZMJmJxVNfgl+cgMETodQVIhtCC3CjMYVmcM66Ec5YTJRnt61vtTOlSxglCkHnX5ULW59u5SK1ag3gD3QEqyTDlCbH1QYwhgHIEY1vhjbxPDUZyzC8q/lcZ8dtX5FyWhfzLc1l255r4ak5PwDlUXfKRFUEZBbTMrhWPSpkVXd0I2l5mCJAmchwP91qVvYFyH7zHZB06vS6maohKUduUxFWAQpuUDo6N4oRJNmLe2WS3OhawmveJ9RIXJCGnNK3tjFGkrqTbLAnlkl+5fYUnxeuoWatUf+M3+JdOv8+/87cDWfswtcwHfOP2n+Hxna/CbIJbzCmioSHhRHVJjUdrRd0E1po5c5XwxD7dISh1imtxfq0NX+vc4ovlY3aqGZ2TBT4ECpvyZu8KH6gt0kVNlhqWlWSgzyuHUpH1bkbjA5UTM/KEQO1WDDMfmfbz4XIRrjVjvlQ+YhBKKpWgiNxpjjgyA77RufmUj+eH66M2FWkJ9As/e5ys8cSOGIYSEwNLnVDqT4+J8wGqGOmkmrL1YwqI4EYr1Y6mx7P9K9tnQk07ysC50YWKCmsVNkJZB2kMKIkKXVQNo25GlgQmy4bGRyaLCufFhslohdIiZmqcGMUrBYeTgk5isCiWlWdSNGTW8OruiG6e0Mssr1wdnc0k1s5zPKv4/M11upnl3b0pG/2cfjvrebqo+Nq9Y/EnfY6YqJPKqMbD4/nPJPBc66Y8Plk897UY5dgPOz97TO9nuS6B52V9OpWkEpv5g28LG3nRlD14AXDXbwtYulghSO55WQhwWVXetqzvvXUhcWd23mI2VljDiFgi9frw9d+W1/KOtLqv3JAc8ze/LhZIVSUso2vg7e8KuL1+R1g60zJ8K3N5EJA63ADCuZfkqrSB6y8J+B0fCzuaJPKzvYfw4D3Z/1FH2L/F/Hz+0Xlpsa9mOpNEPsf0WFi9JBUGccUg65VAqc1+d/XTnp7BQ1EJKLt+W0YH5hO5M7qWTVwTIZQ5OiBGR2MSVAzYGNvkH9UK4RXKWkynK2yn0rK/Sdv+DkHALfo88/zgsexz2c6urob3nlPBWLQPBGvwUeEGG9g8Eaa7na88e//qYaCNWSRN5bpa28Qv5kRj0NMCXVdgLKbToxOX+CyR3q3TaG1IgifqhNp26A9HLDevovYU+vQx3iaU9JgrTxktWiux/YmBGAP//q0v8Pvm59BLUaqf3P0D/hy/y//pH3h6Tj7j0mQ86l+l6o2w0xMWh0ccX/8cj5izWSb8QvOEu/NHzPIh3SRQlTNmyvC97BqLpPNMv/is3QtMTJff7t5lKyzZTDyVi5zqLrOQEicVuXW8em3E3SsDHh0vmBa1tHHb2UINWKsJUfLjYxCWzX3SPjsw8ku+XD5Ex8gDu352bnUMXHUTvlw85Ld7d1842/lhEdFTn/UF24xKfSSY/aOU4fxSWpk4rKaoI1D7iFERrdWZt+iqbHtZ+xBJE43yK0I+4lrhl7Xq7MRl1oKSRKR+Zs88PJVSZ/OZdeMoXKBoAmndMF5ULGtRtt9al7nMW9t97l4ZMl00pKnhCzfXeXyy4N7BjMmyYlE5Eq24sztis5/z5qNTNgc5nfT81r45yMkTw6SoKWv/1Gsgv/NiFvGzqXC/ut7lvf0p02X9zCjB6aKmnyfsrl222X+SdQk8L+vTq5t3BbTtPZAWdpoLkCsXsHFFRDofBiSr1vhF1fmqmlrA2WwiAGh8IMzmKjMuywWETY6F5VzbFAC0mMN3/xAOn4iSu1i2FkxewGqaC4DbfwyjLbj7mmyjqQXsVKUIg6yFjc3WEN4Lo3nvLfi5P8uZiGe0IfOrb39HQFFdCTCbTSA0kHZlm9PJebRjDJx550xOBMS6RrafaTF5Xy7kjt0btN6ipTCuSSLfL6bCenon4PfqTdlfk8COls97cijH3gf5f5CZUBU8FhE8OGPRLhK1tL4TX6O1kmPgWgP5EAQIm0TuvtNJO9/ag/5ay3Ar2afZWI5VloN3GC+pOhHwygJG7FJNhrKWbG2E6w4J0wnEiMosJjSoqvUQtYmwzUHmO6u8xyIYTNGyxNmQrhtjygW6PXdmZY7fH8oxLAusSdBph6xakMyPiZ0eddFHV0u089ioGeAIWOZJh1/e2Obvd74C1QjtRKl+d/03+U9/o+DKQoQlhU55Z3iLvd4uLkIaPetuypdn97jvrzA6epd0fkIRKga2YWNWEpIh99Zu8J7rchjTM8X5CoApnnUCCEpzkvRZWIvXAefPxTCVC7y7P2Wjl9FLExQFLsBkWWO0IhDBQ5ZYssS0hvGKRItZevMJOozXmzG9UD87X6k0e3bErpvyUn1MqYUJnemcse6c/67Hj2Y9f1Ll232hnblMrEEbTajkIc61rfRVotOqFDIL2PiACwHtzrV2K51d2XgyazBGUzUe7xwRhWsqXCdpLZw0mVX08hQi1ImhmQsDWtWBg0lBN7Pc2OyRGM2icty6MmTUzRh1Mx4dLxgvKq6td3lwNMdozc6w055Xz2+/tY8xiqvrT3smG63YGuUcTkumZf0U8PQxMF02LEqHNopF2Tyliv9ZqI1+zhvX1/nugxNmZSNRoRGmZU1mDV+5vXkZH/oTrkvgeVmfXiUpfP7nZK7y8QeS6JN34KXX4Mr1ZwU+0AKuRoDqqpZzaWFPxwIc9x4KEEzzCzOASvLTZxOZp7x+V1TlIIDINWK/VBXCdAYv61iNAaxtihhq/wG89IrsY4zCvq5AV7d3bh9kDNx+WQDmg/eE3U1SAVnvfk9ESnc/LwB4JfI5PZJ9j1EA6erOGzm3f/K+BehVKwLKzvc3y2Vdadb6gU5bwRECUk8OhI3cuSr7Oto8v9lXhex7losZ/GTcbtNjghiV+94Ql/fwIWKLBVZFTFOA/9B8p2qBvmsuOAbE1kd1S85Rmn0o6UjGD/xq2XZeM8ZIVIokNmgM1fER5XiG0jnWlVjvzoy5zWocwRjoDaicpzw6Jhrxqmy6Q5ZZnyJq1hfHJE2NRp3P6sYoDyVKkSQpvU5GsShxswnZYgxNLSbxvqGDoVKWX13b4a9tfFWU6pUo1beu/T3+w9+e8Oqp/Ll0aCZpn/eufp4ZKbnRZImwfetJznA5Jn38LR7GwF5vxPcLz3tEdkzJIDhhL/0EExxTEu6bNd6OQ7wyLwRnrp1NXLF150BODOCPZxUhlmI2LiaRYvXTWvY4L56UGrHhSa2lahxN/fHIc8fNWLyg1a2IXG9OWbsQm9kowxM74nv51TPvT62Fff0sjNJJ6qqYtVujSRND4wJaiT+md+EsgXY1BtD4cPZ9TRBD+faBSqZANHkqPhG1az1Ro5jPV40nhMDpvMIaxaKSkYtEa9a6CfOyJrGak3nFvJLcqK1Bxs2tAdujc9Z31Eu5tz/DasXmIOflK+djGiFGfvutfYhwdyc8ZQ2kleL21oD39qYcTUs2eznWaJaV4/F4wd7pkkEn5XRa8uvfe8KdnQGvXRs9V4zz01ovXxnS7yQ8PJ5zNK1QCl7eHXFjs8f28NNl1i/r4+sSeP4sVbFogUz2NJD7SVaSSkLOYCTg0bVCl6aB51nF2TZLvK5agDUXkVG5EPFMr23NV+U5CFzMZPmqkLtwU8O974tt0s41AZ7GSvv+3e8JcMm7Ivzp9c+Z0dEGPHkA+w9h64qApr3H8n0xk/157/vSPn/pdYnO3L4q6xqfnCvJl3MBrtduyv5l+fkcaZLKebGJzEJWpQA0pYShjJwnBNk2vpNw3ptUtObzLcWiw7l1EQp2rz2tfAf5uqpkDvVoH+pZq343gIGmQgWwVYHNO5KeVC3xZdFmfjvCZIwJXgy1Y0DFcEElr+UzzCcyV2qtgOxq2c7WKmgEBOG9gE8ls6bRJtTKYHzTzoHWqLUOujMgPZ6jXY0zCVFbUBIDSVnga0etDNY15HWg6Qyoej163hHTlGppUBhSq2QfyqVcH6uc+aYmPz0kIeJsCnlG2NyENKN68D7fSTr832/8PIvFnTOlenb37/D/+PpjfvEbOWBplOHt7jXS6NDWgjIkWrPez5gWcvwPa0M2/v+z9+cxkmVplh/2u/fttpv57h77kmtlZlVX7zUjcggMSQ0pCaQECaAgARJEUCAESJBACBLJAbgJ5EggIWoBSFCUCOkPcUYURGmWnp6anq7eu2vJWnKPyNh9dze33d5279Uf3zP3iMjIzMiqrKysKj9AZGS4uZm993yxY+f7zjl9JjPFj4JLOGWxxpKiOC4Vm9N91r1d9levUfg1umnKZrZDpxzznXCLUnkfqw5azm5Y3F5a6RQvKqdQ4CsW1hGzMMAgfeyFsfjVj1BWGtLnZIHuY0awyjmu5MesmAknXp1tvwNKEduCy0Wf0JV8J7lCrv3ThtefFRaj88W1dSw2OiTeyBhL4arACV8Ielk1VS0SALRWBJ4ExJvHTJK+r+k1IpRSpHmJraozQx+SMKjeLDhc6TDGYa0jDj2shUkmBqRraw2G04LSOTwNYeCz0nyyVUcrRX+S0UoCNnpPqppaKVaaMR/ujRjO8o/kcq51Ei4tNxnMMnZOpjgHB6M5eWFYbiX8xs1V1toJ43nB2w/7oODlrScV7p9nKKVY79RY79QoKzn7PLfzZ4dz4vmLgMGxOKiPD2T0Gkay33jh6rNVxp8mrIE774sqmM3PIoHiWNqLrrzwZHtRsyMj48M9IXWHu0Ia2tXoPZtL5iZKSNTCSa0qZ3eZC8H0PFEA51O4fFNI0bBfja9bMrIuSyGMZSHPVatI6HQiBHT7Lrz3vTNzUVGRyv4hHO7A135bSO3mZVEgh8fyWIsg91tvCSkLYyF+wxNRMCcjOb6FxXjRh77Y5SyN/FsHZwpjnksWaFm9gHg+dLsycp9XSvJXf12U3m9/S44nT0WFLHKJbdLeWQOTH1TPZ8+kHOtEVc5SyjLHKI3SgYziC8mALJWHp7WEVjtAeWLGKvPq+kzlWFwVdbTYyyxKnHJYPLSr9kzLAucHECfMy4jUwFIxIspTadWpXmM9rJg9PF9IY5jA+ITQgY0b4rx3Fu3AeCGuWWdiLDb0CdNhZfKqFNlWV47PGDjexzMGr5tg4xpZrcU7ZcD/7vqvcTx+6dSpnr/49/lff/AO//TfaQAxJZo79U0OaiuoLGUt61NgGRaWJJYolllmqEUe2mSU85R7+MwxhJ58Pa2xbOYnGGuZKsXupKBIEpaaS4yY8kJxzFGZcDtY+cwj6fwxe3peVvWKVTAAjrNxekX+JGD+7N+f9nz7fpNXs90n+tMBmjZlxYwZ6Yi+Xz9V21MdsKPabJZD1syIh7p3ep+fxci9WuuE6rkXgQ/GOtpxQOkcaW5QSgxHEgYh4fE+7qz9yTmiwMdYi3MOXyvCQNOtR+hqxJ6XYhySJiNV7YtqciMNRNbJiL9Xj0gLS1aaiqQGrHR8QNFrRAynOR/uj+nWQ5QS93leGIrS0Ko9u354uRlze2/IeP5R4lmU0mp0aaXO+9sD3nrQJysM652EFzY7dKrnWexA3tsfc2m5QT36xRtBnxPOnz3OiefPO/qHss84m4ri5zeEiN1+R0jWV77+xZLP7fvw4buieHYfc0hOx3D7bVEDt66cfVxrIYrjoZDn/oGQuyKXUPeoyrtMU6nHdFbITRjLbYc7QlRNKWR1cCzj7dlECGpSFzIaVipkrSFEM5adQi5cFWVQa1FazaLe0jszAxkDD+7Kc3RW5fGShjz/o3tyvlF81lDkB0I2JyM5B6XOYpr0Y48b+OAn8rWLYk7rMSuzDKasdiyrcbxS4hpvRXINL92Uj29dkfino31ZczC22gut9mvL8iybtCwBVwWye2BLTJ6RhzGZjqhlUxwOZwy6yNDOYVAQxPgLrcj3IGrK99l0LNd6OhFSayS+ySU18rxA2xSv6o63yscGMUopvMrcUgQRGov1AtA+RT3Gy+ayAxcl+LaEbC6Kk3NYrSjDOiZK8LM5eb2NV+YM169zvLJJp/++7JkqdRbtVRRyXZMazOeY6ZT91PFvN1a5nb2GSsWpPn7x9/kXD77L/+DvxigaWGCmI/b8Nh8km5RoWi7FWkOufWxpOZlmhL6HpxSmdASjI8bOZ89r4VAU1qKtZbMYsZX1mXghrjSUeUnmG/rTjNJpojDmcnbCXX8Jq7Q4o5+DoS1I1OOwVO8DnnFbYSHQltIJwaoWV05VwGdhN+hwpThmqZxIAH5FMDvljLaZ8SBYkp3Ox49BaXLlsVEMeBj0ZC3b/Wz2PBfj8AUW+5uFsUwzQy3yaScBs8LQayTM85JpVlAPAvLCkBZGkuCAtJBkCU9BGHr85Zc30Frx4b4YEpWSjFAQhdQ5yQK1xqKrYP+0KE97HeJAqi/HqZDFrDS892jAPC+ZPyrp1EJqkU8c+MShx3qn9nG+Pdr1kE4t4niSsdTMT3c1x/OC0Szn2nqLwJO++EYcnpqOHh5NOBikXFppsNKKaSYB2/0Zx+PsF5J4nuNnj3Pi+fMMa2QUnM4l+3GBIBSCdbAjRPD6y1/M8SyC3eNEnv9x1JtCqB7dhbULTwa291bgtV+Dd94UpXRxDr1VIY4f/EgUvHYPxieAOnPHa09eWWYzMfkkdVFNoRrfx0Jq97fPVhCUlmtz42WIakLc/uJbcvxxUu1jOjHT2FIInLVw9xYsDUVO2kjkuWcjIXejE+j7ouz6QRWdVEgHfCm7eYTVbdm8CpV34lhXqtqRTMWRriuCijuLULJWnqPWhOUNCVEPK1Wjs1wpq0PZNXXVTmY6l++RIJL7ZSlnofOV4ppZrB8wCxpV//QMG9Yokwb+6JhwNuIszN0BVt7Q1OuiJk7Goiz6HszSqt0owWqFU+LidSiU9jBhjA1CUSxNQT3P8DSgNW6hgvsBmBxnHTovIAkhjMScVEjs0yIU33qaaHRMGcSiPvshUxUSd1clRH46ka9prV5FL6XMLfyNC1f44/Lrp53qw6vf5r+e/yH/yjc9ApNUbvKEg6BNZDIadk47GzGvOtwP4x7G82lkI0o/EqXaOBo2JbOOh8EqWikCT9HIZmwVx6yWY3rFmFohffLHpsNx2BXzj4KR82nYOU1dMib8CGF8FhTPJpcLfFxOp6zr2if+/UlPN/QSfhhf4CvpDhfKAbny0DhWzYiJTrgXLj2z4rJUHlGVbfq8maE/LTxrqcBaGKc58yKnXYt4caVJtxHx4HDCLCvICgmY11phrTvdfKmFHq1ayMXlOi9d7DCYZNw7GOHrx7oVPEUYeAS+5mSayf2dXAcJbZ/haU0t8rHOMZoXJEFAYUp2BzPSvMD3PFpxyDSVPM+lhtSVjmY5vcZH95ashYsrDVbbCbO0rCKEFI044NWLPWqRx/fuHNFOQnqNSHyC85xxWrKbztgfzri41GClnaCVrASc4xw/DZwTz59nDPoyVnyWI9zzxGyz9xAuXf/sNZU/DqZjISK9Z2TBZamQrYNtUUMvXJO/lRKyUhai2LY6QipXNoSsLuKWBn2IFxtX1fnlmRDYPJN90iiUCKMFgVNOSFq9KUSzUs8AqK/JCHd1S5Sxo70qVLDKqiwKcHmVt8lZz2CtIcrZ7kM5tp2Hch/fk2NJ6kIW5xNRaRejXl92vSgzOV5TPvYqVe24ltVzLwLfw0hG2l5QRQmFcOGyNDF1V+Q8Ridw911x+8eJqL71lpzT9/8UgtnZusPiHJyVqpZSsu2s9rDahyDABhHOOVRZoKs8Ta/MhBz6AUr7Var2WM47rsnXa9SvDEeRmCqyDKcWv14ctloj8LM5ypY4p8i1h3YlzhiC6eix/E4F1lQZn0AQooqCUnkUSYswm0rWqHVkTnFsPdLZlIO1DuFoyNZkRhT5BCvrcv1QlGj+0/U2/4X+GqRtFDDe+IBfa3yTf/sPM5pZIO9fdEiqfY7CDkMvIdQhS+UYTzmGQZOpFxN7mt2ww/XZHr1yRM1YTGk49hLebF1lqCJuzHfRGq7khwTKMvVr1E2OtY5MhyyXE7xsyE7QrlqULKUD49Qn9ts/DsezzTqftku5uM9iBP089GInkOuxVgyll11pDv0GF/ITZurZv1sSm/PI7zzHo/9sYBEV3VjNaJYT+h5bvTpr3YS94QxXOrRyhL6M0RXQSgJe3OrQrUdcWW2zfzLjg50h/UlOaS2myugERxR4pLnBWolo0ihsKSsls7zEU5paJKssrThgrSOj8ijQ1MKISVYymgvJrIUeYeAxywpqKuTu/ojlZkwS+fiV435vMGNrqc5v3FwlLQzjeSHHXAuJA48/+2AfrRXNWoCnFfcPJ1hnScKApJkwywpya7l/OCaJfKLgfCR9jp8OzonnzzOKHJz5eFIZxWeqzxdBPF2liD0xC3IyAt7fllijdAYfvAV723DhCqxdlN3I/gGnNZUP78gxb10Rore6KTmPg2MhV2V+tgtqSnFtZ1XkUOV4RilRgRfj+aQm91+YYqyV+Kcbr8KjD6sMz6y6VhHEnnyuc3D6+1edGZVQ8N73hVx2loXQzqeVymgrUmmE7C6C6J2rvg7uLETQloAYacQ0pERRDSNRY52ruuY3hBw3OvKx6Ui+tu99X0hgd7kitVVD0+oFcdjPZ6ISZ/OzTM4FNVnkoVpLMhtQ1jeY9zaoHT7CH5+gy3xx1mCddJ17nhDbIod5Krf2D85C/h3geWhrCFXVCuMHGC/ERAnKGEzcxBiHmacYZylaPfx8jspK/PkUoz1KPyL2qmfXGm0KVNwkRVO0Vim7y8wKS3l0QDI8pBY36BX7+NriyoyZcwRehlWa3wlj/tP4VczsrFP90vrf4//2JydsjCLAx6CY+TFzPHws9XJOKHoko6DJ7foWw7jDihkzsR5vJhc57GzhDw7pqZxUhxyEHR4UEaErqGVTvj65T2xzjsMWsSsJnBikdoI2vta0532O/Aa58oiyKXe8LjMV/MTz6Oe9+0LB+yTV9HFMdcSd6KzutmFSWialY+cMvCfXeWo2o1Qee0H7uY/7Z4HMOGqBJvQUk7TgRw/6tGohr11aYvdkymSeM80NSeDTSgKWWhHWQn+Sc2nF8oP7x9w/mFR7s/r0V19pYZIWVZORxlqHcRatqEbnmtJClltadZ9LKw3muWE0L4h8TVZYYl/2pa1zFNaxezJjMM1Za8cMZjnjeUHoa5YaMReX6lxebfHG5SU8ralH+okxeV4ahjPJrNRKEQUek7RgqRkRVDuPDoWHvCfNCyPGvnOc46eAc+L58wxfltEx5bOrKhctPR9XY/l5o9aAuC47f43qBWdwIs1BizzGel32Kotc9lBvV67z5XU5zkZbsjL3t0UFvPkVGbEnDagpUXEf3RXStdj1DEIhgwvTTlS16kTV3pmqAtQbbVEiB4mQ0huvyOMpTzrgF85tb+G8ECe2EMkClH92LRcOfKjUSL+KDaqc7rW63MerXOBKCcks8orJOVEwu8tCKIHT/kDlyf8s+tA9LY8xm8D7PxSnvtZiMvJ9OZe1zWrtwAkhv/+BHGNnSUgqQFApqYpK0QWaHXQQYmc5pfJwUQ3neeLmNQVoH4tC6cphvghyT2eyH5qlWOVh4wZaafRsJGNuz8cLfIxzzFRCgMXPUoznk0ZN/OmQurY45zPx63hJm0ZR4uVzcj9ErWzip0M55/EQrTRxHJM32/TDNlmp8PZ3qGdjYm0pmw1UNiU+2MYvMkw658/8kP9w4w3m4yswE6d648rf4d//3iNe/X4CRBQ6wALKGpx1lFHMVPn4tjz9Y0KPti5Zmz2kOx9w1+9xrbzDXrzMI71GEih8z6PrUq6le/TyEXE5l2gopYhLIcD3/C51V6C1Yq58avmcIB3jOcvEedwPlr7wkfSCfP44mHgx70YbvJ4+YqMYMvJiHIqGTfGd5f1ojSOv8ekP9AVjcb6qItylsWilUQ76k5SsMDSiAGMs43mJdRAFmtJZtk/mNKMCpeBv/cmQoixEvbdOlMskQKmCNLcSgWUdSrvTgUMSalZaCYGn6U8zRmlBHHn4nmY8l6rTeW4w1tGqhSjEoNRKAqZpzv2jCWlestaNUSpkXo3U49DnL7/a+NgMTqUUSqnT8bl1jlYtYJ4bCm0JfMkCHcwK1toJSeTRn2Sstj8/f4Cr9rqf1Z50jl8unBPPn2e0ezKuHg2eNPKAEJDxQFzk0bNyjH4KiGLYuCBkMq4JSevvy21hLMrb5mUhc34gStnDO/DV3z4jdI0WXL0J+9U4++4HsLQCV18QsuQHouKhZLSvfSGljZYomVEs5/zBj+T5Bn0J7juVdJzsjnaWOG0i6izJ8YaxKIZF5WpftOiYKjw9iqqEaSPHYKrYo4VZKKxUZb8lz5PO5fhwVa5k5dyuNeX4g6qWM64JSU2q1YNa84xA5hn0+xV51eLwjxIxLY0GVcamqwxElaPcGDnmBw+F3DZa8vmz6rr5lXkqacJv/BW8/j76zofY2RS/LCnjGsF0jFOaIojRzhLihDinEoOEKTFWeq2LwlDgkyd16pEhKuYE1uDVW/g1UTZtkZN7AUVcowxjolaTKB1jhyc0yMnzkqzWQnVXSMKAqJihjJHUAwX01vFCn64fUgtiprt7uOyYvL2Mq7cgiMimM8gy7vpN/saNl+lPvgJjcarbF/4+f/299/krfy8BEiZRk2FrFac93HxOc9ZnGjWYezHGQaTEFJTjERYp1wd3GRPyIOiw4zVYzwas5EO8ZIsdb42lvM8r04fE+ZyJCggpCSmZEvDI63DsN8iUz0Uz4Lo/o2MyknLGUjbifrjED5NVjv2fDUn7SVb57odLpDrgYt5nyUzQwJHf4GHQY9vv4D6GZPzE7nbniJwEv+fK/8jzfNrjq8d+JRgramUt9BjMCkpj2T6ZMEllNzuq3oiOZgXGOqy1hJ5mmsnPvaekDUorh1Oa1XZCfyKtQtbKxk8ceEShR+gpitJgcSShNBgFnuZkkjGayyqGsY5G7JMEPmkhixdZaZnnEs2VG8tqq0ZQJUikZcn+yZw/e/+Af/pXotOqzMcReJr1TsLt3RGtmuwQr3USnFOMZhnTrMD3NFdXm1xYblTVnp/Pu6DBNGPnZMbuyRRnYbkVs3Wen/lLjXPi+fMMPxBH+Dvfk1F0q1vVKqZCuFodqVD8InH5pri0dx9UETYHQpgmQ1hak5HxAs4JmczTJzvcG23Zy4wS6PTgtV+X3cn7H8Cf/d7ZSDqMRO1cxAQtrcpz+YGQo9lMCN1kVCmNWq5JEJ1laIIQ25VNeS5nzzrITVVbGQTQ6Qox1Z6430tTkdJcMiz9QAjeIrc0TeW4Foqzl4OrKizncyGwIMcRJTDJq11MI9dqERuVpmKcyTPpKl9akRrPWkNWB/wAxiO51u2ukPH5TP6d53KctSoPVU3kFTepiTLd7kKrg15ZJZlMULvbFEXKLKyhah1qboBfZgSexClhFCDxUaYE6yxZVMe0l4hmQ9CQhnVx8No5nrMEzuHlM8rOCm55Ez+KiLo9AlvCaIi3tkkrnVNWY/p0aZMTHRLsP0J1l4hf+xqN0BeT3MkhTEZEoyOYDzhsr5G/8FWULdF33+V4mvF/vniNB6NXURNxqk9vfot/ee+7/At/L0KRkEZ13ute58Ot12lEHlpr6vfepRk2KIIYL5uhPA/n1dHGUBYlwWzM2Pl8r36ZSVDDOM3Yq9E2U15M95gS8mK+jW9LHlTtPtpZDvwpnXLCuhmdxg3thF2oL7FsZ9SyOt/2L/G2t8zcSX7nQpBekKLFt+jivdOX0e6x77fY95pErkThyFTwsYRzgZ/kPNbKEZfyY3pmigYGXvIRovtJj++q/yyO0Fjp69ZRQC305N+FIYl8GrGP0rIDunCoTzODl0gTkQJK47ClwxgDhSEvPAJPE3jSxa4UtGo+oe+jkAIFHCSBT7cbkpeGi8t1oIF1jp3+DCoHvLWWyA9J84JZVhD4YkgqjKPqLCD2fepxwE5/wu7JlJsbnWee94WlBtvHUw5Hc2JfM5k7eo2IJNCcTD02e3VubrRxztEfu49Ua/442DuZ8ea9IyZzaUTSCj7cH/HgaMKrF7tPhOCf45cH58Tz5x0bF+XV6v6tJ3ftVqqKymbniz2eRXvR6qYQtEXr0PKaHMsi5xHO5nzP6o1WWuKJ6k0hSCBO7kd3hcDuPhA1L06ErHlVx/ngSHYcy0IUyqSKUYqqOKMsFSWxaMk1e/XrQt5eeh0e3hZyeXIohM9Jxh7tnrjVG21RNY8PhWB2uqI6WiOLUYvA8gV6y3L8gxPZQQ0CIZoLQqqUEG+NjPxb3bO1CVPKbYNj+f9Eyb5qllXnHsjFyypyPR3Jn9mkqvisetbbPSG5eSbENgzPlNN6U4h2s4v/2tdJ0inBdIputihbS3j9bcLDbamgbLSE0DqDCyPK0QhX5ATKkdcblCYnSKe4ZpfCGGa+T63WwFOgOz3CC9cIra0aqao91vUtWNtC9Q9QB3uMtx+xn0eMWivMtr7GUe8CtSzhxaU2175+AdU/lDcEeYq59T5785AoCMnygv9Hq8Xb3ovooTjVR1e/zX8r/UP+p//Qw7cxeRCTNpeYddbYq10gDn1snhNMTxgSMkxWGSZt6uGYJc+So8miJg0zQ+3e51DXGQUNHI6yyuaZ6Brr5Qk30j3qZs6e36JtZiRWlLCZ9mkoj7rNWHYz9jwpdRiVmouxz3HrCu/M1siMNEl1XUq7mKGcZUTIkd/AqMWe35eTdJ5CKTL104/euZwf83r6CM+509H+cjlhvRjRjtZ4J9o4JZ+e+mRnP8ivH08rCmOYpAWNJOB4NAflE/mKcSqh7lkh2Z3WObQ662l3VEMHK61Hvq9Of51ppQl9RWEdceBTi6Q6U1zsOaVx3NxqM54VpIXlxlqL7f6E+4cTZpkE0QeBJgw9JrMCpRTderWT+dR5BZ7GOcfBYP6xxHOpGfPVq8u89bBPaS2DaU5aGGphwIWlOpdXpPltMFv0l/9kiuQ8L/nhg2OK0nJx+UzN79QjhrOcdx6d0KlHH8kcPccvPs6J5887lBLyubIhhGsRIN/sPBnU/kXCDyTAfnn9TEF8pvO+Gh8vRtRPI0uFOC2gPVE+lZZx+ejkyYamxY5l/0gUPmfhpC/E1fMqMpfJePvyDdkjvXBV1hQ2LsKrvyrE1tysKiYLIVtFKnuX9TqkmRBAnCik+7uVquuqcHZPnjeuyXrA6ERIbHdJFMigenGOYvn4ZCjnkDQquUsLSdcK7t2GOIKwI9fIC2Rkns6qjM6ZkNPukpBwpc/c/qMTeY6kVtVmptXOb1ApuyDj/lAc/3fexctSPJMTHdyD+YnsjrqyMmWl8nVExn3WOJTvo0xJcrwHtsSr2pOMH2BKhykN3tqGvFGIEyHUi/WFC1dlr1ZpWN7g4GjMzvILlC99Dd1ZIg4jLiBjuh89PKF2c42NKy/ItRuPSD58l7XBI/4zSr41v4xO30AD4/UP+Eb8u/wbf1JSywMyHfBBbY25H0NQYxCtEzpLOx/gfJ/Zyhp7YUFntMuxCTjwumz7HsY58rnh+nREz4HxI4LK3SzfulLraUqPFTPBd5ab2QFtO0c/xgpCSmJbsJGfMPJqBJSsG8ux6/CtWYtZYQlcyWv5DheKIaGTbnvrFEdeg7eSTU68+pebdH5BaJiUl7NdcuUz8M92D2c6pGYzbuSHHPhNDv2mhOh7Un/5aSiNRaNJi7LqaXdM5gUTVVAaCH3J7SwcKBTGOLLcEPgKi8IUJb5WVbORxvM8tIIo9JinJYGvyIxFFSVKKbLC4ClFsxaiUVxZbdCIA97dHjCaFXhKU2IJfIUCBpOMWiTmJu0pAl8T+E/+bi+tJQm9Z8ZGPY7NXp1eM2ZvMOPtB30eHk9o10JWWwlZaTgcpWileOPK0jNH9p8F+4M5w2nO1tJHA+/btZBHxxN2T2bnxPOXEOfE8xcFvl8Roi8RfF92Ot/5HuSNJ0miKYUkrqwLuUue2m8b9mVE/PhoXmvpSH/v+0JIh/2zqk2QkfqwL41BjZYokQohTX4kpGx186w1aDaVz+0uy8euvyzkajaR46baszzYAyyMxxLZtHZJ1Mw4gQvX4dEdcdkfHwixDBN44bUqH/T35TjiuozBFyN8rc4yOoNISG5a7YXmc3njEFah9LOJXKuD7SoTVInKWe1aMp9BwxdX/XwCeVH1qivZk42q/FKthBxnqdyn1hCCeustuQ61phznyb4ouXkuKuzGRSHpRQphjI0ScnxCU6DLHFVkmKiG83yc8gimI0qlKZe3CF94Vc5lOhZF9uWvyjEOK6e9c6R5yZ7XZPqVV4l6vSdePNu1kOP9Ed++dcBrl3u0Yo/Oo9v8f/pH/CfFMnayggZmnV1urPxd/safDViZhOQq5Dvta9xLNiiNoW7m3Kpd5a3wKmsq4+txxnI+IJiM2Mhm6MEBm/6cwfIFkijC4TgYzZkXBm1KTsIGUeARBR6lseSloTQObQ25g6t5H6cVJ7qOqTItPWfoGUuhLDMV4DtDicePwjXu2zbHNkA5x1fSHa7khxx5DeaVGcd3htVyzK/MH/BntWtM9c+oAvdLhFUzpmEzHvrdj9w20xE9O+eCHXJIEwsYY0+rMj8JCqkazUqHdQaHkE/rxAizaIPylUJpyKyjsIZ6EDFPC9nLBEIsOeAKi6eVEEEHvUaIsTJedzg69Yj1To166HM0nvPa5R6vXuzxO28+pNeIqMcBx+OUVhISBhqFYpZJqP1wlrPRqZ860UFaiRQQ+R7LrU8ncXHgcWWlycWlBo+ORWEdz3MUsNGtcWWlyXr3JzcVjdNcXP0fs3aRhD7Hk/Qnfp5z/PzhnHie46eLzcui6j26J0QoikV5K3PZP13dgrvvSz96lMjnpDMZjb/wFTFPPY61TSFg/UMhjCdHogIWhZA/a+RxLlyBw31QVbzRIiZ7OhaVbTpezMjOHru3Aq9VqufRgZhpghi+/g0hvN/9YyFvzbY878O7Qtyyuah5yxvwtd+qckO34Xhf1L3RgNO9gjwV1bWKCaLehCSRSCSlhCT6YTVeT0Q5nU2FKOZZVRda7YqaqtEoT2Fc9fotyPYiu3PhyC+LM4PSwW61SGjECOas7I7qynS0tC6pAaO+XKeVdSHyXgDNNiqMyEYpweigCrvXKCftQ7os8Moc48cExzvww6kov1tXK8PbEF7/dYrhCf2dffrTnJ0w5P1axLWoTmgN0WSANzhkNhixM3ccuDp3oiaTLOfk5C6/8+gB+bGUIuS1Ie1Lf4//43cfcvMHMZaII6/Oo2SZSVDH4TgKm6Bi9hurFMYRF2Ps8SP6gc8srDPNI5ZUwrX5AZ1+zv3WBWaFwp9PCHFMvIShTtBOWmmK0pIWlsCUFGjGXkSTjPuqd0o6AYzyONZ1rpTHvBVt8WbtkuShKk1RVt9ydsZmccKh1yTVZwpTqTx2/TYXyhM2igG3o7XP9+fyZwgPnjur9HHUbUaB91Rc2xlS5dNz+amxyFQ/8p8EpaRvYWHiicKANLUUVTRv6GtK46rfHk7S4rT8WOV5QWYcpZXbrHVQWpJA067FtJIAX5csNWVk7WtNI/GphwGldUyzgmYccmO9zSwriQLNr15fxTrHvYMxB6M5CoXvKSapJG7UI5+0KCmdRaOY5yWzvKQW+qy1a2x2n12nuUBeGg6HKYNZhlKKdi3k12+uYqxFIWT583Kd62qt4OOwiKA6xy8fzonnOT5fZKmQMVuNm1sdCTxfWhdyOR0LiVnbEjUzjES9PNw9C3Hfuixmn/ZHlQ2SOrzydYkUOtoT1W8ygnwiEUY3XhVSSGWiWZhtGAuxLArASsRTrfHROtHOkvyZL6omo7NUgO6SEMrpSILjpyPZuVxUUc5nsqv5jb8Kb/ymkOPBMRzuYLIcYxxOe3h4KK1BK7zpWO7bXRalMy/g0oaM4fceikKb1GV31ferSkrk+npeZcqqdiaTmhBY4LRtqNESwgpyrFV3OElNzn8ylscanshqhNJCuP2KFM8mci1WNyQX9KSPH0ZEXkqBBj9CFzleNqeot/GzGYXy8XyNr5QkK7z1XSGdW1fgYJf5aMwPTxT9ocJXMScuYG9mMA/7fKXYoTbY5WQ45XBmsEXBBd/jdmeN/2dakj1YATYxfgo3v8m/8867/Pbfj7EkTIOE3GmO4h4P4xUCW7I12aWpE77Te5lHJiEqZ1xNdxmrgLFNCI1iXMBRuM7US7g0OyDO98h1xEQF/EXtGl0zZT0fMrA1KHJWixk1kxE4wzvJJjkeIxXTcXNOXIKt9jKVs3TcnImOsEqRq8rQ9vgasJkRufIJ0rmAU4qpjrjwC0Y8n0U6nydLtKgyVj8OvrOUni85mNWI3atIYhRoPK1J8/L0ETylQDt5r6YgDn00iloSUEzFTKQUJKEnxNSBUw6/UkGnudRg+loIlnVnDvZa5BMEHl5uaMYhga/xNLRrEVlhqIcevWZEuxbRa8Y8PJJotkXQ/LW1Jr1GRH+SkRaG9U6dVhJwYbnOdz884v7BBF9LHmcj9rm41OCrV5dp1z4+r/lkkvGD+0ccj+T3gUM65VdaCW9cWaZd++yjdeccx+OM3cGU0UzMT+udGuudhKVGjFaKwtgnFFrgNDZq/XOMazrHzw/OiecvMibjs1D1ZruqYfwpwRgx69y7JWTPr+KHltYkL3NtU/48C822/Ln20vM9V6MJr/+6qGfpTD72/g/lFabdE7K4fV/Odz6tdl31WSvRypZ83Non3fSPI3mGcrBxUc7vcOfMNZ5UdYzzqRDfIod3vw9f/8vw4utwtE967zazckJJSCOVJiFb5eqhLJ411TpAIK++xoiZqdaoHPgBNLuiUs6rvU6oclGrdifPl+t8972KfKqqqQi5f1HIGoA1slvZaEn70XgkCux4JNdrEcBf1VKiq+s2mcDmFbltPKKeTchdyTxI8DyNb0qyMMGmKaZRpxFolKehtSSk+d4tikaXyXjGu7/3R0xGUzZDSz0OuOiFBHlCmSqy/ft8nxoz6mQY8kTxx60p834LNRCn+vzmH/A/e/hd/pu/E2F1nVm7R1lacuPAFCQ2YzUbMNUhQx0z82O2wx65daxlI4I8pR/LSD8KPPLCUhSWR34bEsWhqvHDeIuZjsi1T1CkfG16n98c3qFXznBKMVYREy+iZWZoBw/DLg2T0XNziYOVK8VIx0x0hOHZP3vKWewnJGmWaDwsyrlPdYp/FvzEcUafIxTir/u0/cRjv0GZa0JbkusnX7q0s/jO8Eg1ePzMFh3t1jqUcjglpiMc1KOAwhgyazBOyFDgaZpJSFYYisKQF45CS/tQ4GnCQDNLqxglvVBEARyFtQRa4/tCPK11lM7Sn6Tc2GgxTQ1bS3WacYCxjp2TGdfWmsSBh6fVE18PrTW9Zkyv2n88HqfUIp+/9NIGr17scWdvzNE4JQo0m90aG906rU8gnWle8ubdIwbTjPVuglft/5dV49H37x7xWy+uEfrP/xphneP9nQEfbA8pjSEKfEpjeXA4Zr1b4/VLPda7NR4dT1nvJKePXRrLwXDOcjNm43MY6Z/j5w/nxPPLjiKHwz0xgGSpkJu1LSF03sf8kpiM4d77oggu3MydHly88fHk7yfFD/8cfvDnMiIOIiGd9Rakd0Vpe/3XZK9y0RPu/4QOWKXOKjYrU8tpO9PKhnzs7vtnOZxZRcCXVuUYmh0hd6OTj2agfhyW1+Wc7r0vBNAPZIydToXsLq/L2D2di6LaXSKdpxyphKQYEGtRWUxSxysyKAusk9mdl6UQtsXpffNV2XntPhAyj5Ove7MtZHc2FtLpBVU96EheuT0tRNpYIcJ+eNaktGhL8n05d9+vXvE1UGWBjk5EYa0yVY0pKdGUpcWdnJDv7FGLA+JaDb/RwNWbzDvrZAd7lEWKUz662aTmafzHo8mjmGKesv3eLaaDEbNcMWksc6JrNMqQjVBxabaL6R9xq4yZeAFEHn+6NOd4cAHveFMqLq98h39h8of8y9/0cCTsrVwlr7eoH++gnMX4AdoalDGELuMwqvNhfZMVN6Vp5uy5GJ1nZEYukecp0sKQFWVVcwhDo8EznHh1+TZVmiQruJIf0rIpqRdglWbixTwIl7Bo1vMT8H3eS9ZplXNqVhSlmQ4ZqoQNM2Toxc90Wc+0fM9qZ5/Zd163OQ/C7udKOuHzJZ0/KYl1QPkcD3Ds1XkYdLmWH3FMXao6lSK2BStmwo7f5oFu4awjDjyss5TGYRyU1uFr+binIC0sBittQloReYrSOErrGM9zjJX7aWUlL1MrtIYk8MgLI8VobXnTlRYl07REG8nCygtpCerWI66utBhMU+7sj4XMGkO3EVEPfS6vtri+1gLEcZ6E0iZUi3xGs4LhLBO10NfMM8Nvv7CKUopeI6Z347MZcvYGc47HKVu9OvqxRiLf02x0a+yezNgfzJ9wn38advsz3n00oBkHNJOzN/Clsez0Z4Sex+uXe2hgdzDDVH33WimWmhFvXF6mFp1TkF9GnH/Vv8xI56KeHewIUfADIQe7D+HiVbj5WtVe9BhmE3jr2zLibffkT1nKKHX0HXBfk33FzxP3bsF3/kAki3ZXyMyil727DHsPZAZljHzc84Q8r18S9fInhVeZhdK5qITak53C8aBa7bSijvZW5XjaPRmbTyei9D0vdBVDtLYliqofCAHursh5hLEQXs+T555NGc5zRmGDuLuEGhyBUijnMHEN68CbjfH9EK/REvLq+6JihrH0so9P5GtXjOTvOJHzWBjJ9relkrTVrdTQXBzwzQ7gROFcrAMUBQQxNggpjKUoIUDhz8Z4pgB8uVZlQTkaYiYjjPKwYYRTMB5N2Y+2WF7usrJxmeBgm6V2DzPrY42P1grPSyRDFk5NX8Za+jmYR3fJdcLD5AJKRajckpYphQm4iGPl+D4T1+I7F7v8iBfwjjbwgMnaLf5K8Lv8a39cEJYBk+4G32vdoFZO6U3GNExJEcZY5VE4xZAYhaNn5gzLMZ7vE1UvtoX2sMZQWiOEx5zlOjrE1HPkalhnCfCI5mN+a3KLK2WfnaDLTIdSqWlzrhdH3AmXmeqIJZuxojP2vDrH3pla3jNTxjriwG89M9rnwG8y8GosmwkHfuuJ22o2xynY+Zz7zr3qfcan+72fD1+UcmqV5q1oC4NmsxzQNTLtyJXPvaDHO/GmrHlU6mUceJS62sf1NJ5XtW8pReiU9KobCXLv1AIOxjmTeX4aXaWq2CRjHHGgicOAWVaCg7V2zGZPqnPTomDfpczzUtRzZP9yo1snChR7wxmDwZysMByNRLm8strka9dWiKuszHYt5MpKk7cenjDezxnPc/nV5WA0y2nXQgmkd+5jzTqfhIPhjNDXT5DOBTwtawhH4+cnns45HhyN0UAzeVJE8D3Naitm92TGjY0Wv3ZzjeNxynCW45yjEQestJOPjN/P8cuDc+L5Zcbd92QvcmXjydrLPIX7H4r6dun6k/fZuS+kc21L9vVASNnSmuRT3v1AlLmfVHFcoMjh7e8Kody8cvbxoMrYPDoQhXF/W+ovo1j+ffsdUXJf/bqolj8JtCcmpre/J6qg58urRr0lCqHni4np+ssybl5cl/Hw41Xjj0NcNQ21ukI2tfekW3+RowrgB/RVgu9pnB9R1Ns4z8PLU0wQC8krJDg+qDeEOC9IpzViSrp8Q1zy732/qgGNK3LvnZmULt04G/M3OxWrKMWFX6vL8WgPjvcpi4zZ0TGpF1FOMoLMULeOqCjQxqKGJ5g8x2UpKI0OPLSzGOXTyYcwrvGgsUy43KV9cgg7D/CW1/BGA1F7w1gIujWYsqCcWsrxlFmmKNHMGm1UVKtGkdK6kh/so+Y7fHOpxd9qvIGaruEB884uL/f+Lv/unw3pzgP6QYfvrd3gWh1e3v4RgcnxAx+sw5/n5Dpg6jcYuYCGydCeY7kYcaLbjJ1P6aw4x/FQWcrMC/GVPvVcKWPwrWEn7ohhpDBcy/usmjETFTFVEnJfoJn6MQ2TsZ4PuOt1URZ8Y7hQDhirCAs0XEqqAt6Jtxh7z1aoCuXzVrzJ1+YPuVD0GesEi6LuMnBwK1pl/ylC+pPCOBHIfx6Ra58fJBe5Y1Zo2zkKx1jHDHRyajryqr8LYwkDn9KVBFpXGrz0nvueIi+EhGqlyUuHM5ZycW20wtcaoySqaJaD1oZ2PWRaqZKB76FQzIuSJPIJfM1wmuF5iuVmTBJ43Nobsn8yoywdUaDxPYWxlrv7I/7Lb9+lXQ9PDUEvbXW5fzjhnYd9nBNlMPQ9Lq82WW0n3D0Y02vGp3mbIAT7eJxyPE4pjZiPVjvJEz3t8nmfXFWp1NlawvMgLQzH44xG/GwKEYc+R+OMybyg14hZbSests+bis4hOCeeX1ZMx5IRuWgjehxhLKRu535VQVndXuQS2F5vnZGrx9HqSuTP4FjI5+eBkyMhcE+bdKBqUcpkx+/yTVEaF7/8Gi0xFH34LrzxGz955ujaFhztimO70a7yKxNRHhttuU5Pxzk599kjqBotuX79Qzn3MBJy1+qc9bJ7niivOPKkSeSH2MInLDJwDmVLonEf2QtTqLIQEhnXRFHduS8q92Qk6nS7U8kvpZzPdCzn5mkhob/5T4iS+853hczfuyVSXhhKdFGjDVGMOT6kyA2OOUE9wI9qmEaDmfbwjh/iK/DGQ3CO0gtRno+yDuuBZ0tMWdKaHTM/jBjrjPbaljy274vaWqUKmOU1Ji4gPz7Cn5yQOs3QJaRLq6haAw9NacUh3tCWXTfg/7p2FTu8jJqKU31l6+/yH313hys/CDkIl3mn2WHHazEn5kI6pGVLIleg05zM88EpnFbgS5RNaRVawZKZcc8t89DFKBRDnXA3WOLFbJ+JKRn5Ca6ExOb0zJSHQZc9X5IUfFNy2Q6Z64hmNT5foDAwJKBn5zRUwZHX4J3kAhtmzFI2xlrH7WCV3bDD4af0lR/4Lf6sdo2t4oTNYojCseO32Q667Prtz33MjnN0zZTNckDbzMmUz77fZs9vfWR38suKsRd/LJkvnSNAkZcWpSztWshKM2Y4y5jnhgioJyHGOjylmGYSpI7WaGfRWst7NwetOCAKNNOsZLWd8FsvrvHNH+5gLKRZSRIFpx0Ynlayol04hvOC0fYJDw/HZKUh8n3a9QiFIy0saV7wo/t9/vCdHf4737gJwDSretcDT1Y/nKxpl+WZOef+4YQLSw08rchLww/vH/PwaEppFt/3jlYS8srFLpceUy+bic97j1LiwCMOvSd2OZ1z5KWlU//0yK60MGwfT7mzP+S97RPi0OPiUoNeI/5ItuiXZ4v4HF82/Hz8lvllxGwqrTTPcnZD5UiuzDWNShEpq2zH5GMWtr1qlLowp3weWOyQKl11kT/2y8ca2a109iwqaQGlobMsbUujk2cHzH8WRLG43Rsfikp8ImNtVjYlF+VxVbXIhYCvrgvxHA/k37NqV7O3IsfzNBmeTWHnQRUUj+x3Esrxj4eSubmyKZ/nD+C7f8zaYMRxXqBMgT8bEaRTyiDCag9ljZClWl32NbWGd38gWaSeD8urcv1uvXOmdiol3xfOCZn/2m/Cxety3zd+U9qidu5DVu3Rxom8gqZz0qSJmc8IMJTKkXseXpGhA5+s3iNFQrpdkeOUh/J9yjDBep50mldKsh+G3Ln4Bltfu44KQ7l2B7vwnT/AHB8wKBzp4IikmOMaLSZlQJEWuHROo0ypLzUYFQVHoeMfhBNyfh2G0qnuX/0H/G/feZ9ffTfiIFjme0kH5SxjlZBbR3fWZ6pzVK0NNkPPxsyoYqC0R9ekqDAgcwXaQt7oMN24wZJqoJTicDjjXbdBpnwu58es5UPxbOmAD8JV3o/WKSpXuo/Bc4ZpkGDKieRwqsdesJUG52jaOffiZQ6DFsOkSxkZCuOwqNNx9qftQQ69hKGX8F60jsKdNhZ97nCOF7N9Xsj38bGk+HSxXCr67Ptt3kwufqkyQzWnQWjPDetE7ZRRtaUeBVU/ucO5go1ejST0Gc0yGnHIycRj92SGwlGLAnG+O4fvedRivxrPa3xPs9ZOWG3Hp60/WRUSmuYl87xEKeg1IuJAszuYMivEVlaPffLSYqytxviK8bzgd958xK9cW+XGeovv3z3kwdGEzaU6tUBemq2VlqNbO0O6zYjd/pQ41Gx26+yczLh/MGalnRAHi4YrJ+71e0ckoUevEXF3f8yHe2O2+1MeHk/oNRNWWjGb3Rq+pzkcpbRrIevdT1YkZ1nJ9+4estOfkYQejTjkYDQjKyy9Rsb19dYpoZV4KO8TDU/n+OXFOfH8skJV/1lkejwN5yqS99htfiCj5DwTovc0TCnk9OSoCjVPhPx91nHz4/B8IcFlJoSr/tjOpjESEaQ9yYl8GmEkRDn7nEKE40SyPy9dl7Gv1hLSd/tHUnNpqyAXXe2Y3nxVMjvv35JjKEshkXku2ZWv/Zp83kIpfXRHSOFXvi5xSvduwWRQtfHYs3YkUxH7epNW1OQgVeQPjghrTcqojlfMKeM6w6iJF9dZ9/Iqf9OJMWx5Q5znRS7H1myLWSudQ6stKqOnxTC2fvGMIHeW5Boc7kvjkKn2Oq2lCCM+PMro7N9jZfsddJ7iqwlohYlqpJ0V9NEusU7Qwz6lDuUNjQNtSsq4Lg5s5RHMx9ikLoRZKWmpWr8AN15h9Ee/x/h736FFiWn3MEHENIV3/DrKD3h9cIuuusXfWm1xfPQSyq3hlCG7/gf8Kw++xz/7zZATr8N362ucBG2Wsj4Nk3JLr9GjIA4ivCJjYEO8siDUIb7WZF6IUR5OQ2IzCqU4CloctK/Qb6+z4fkU1jKaZRhruc0a94MeLZuicUx09BHClSufVAVEWAZewpKZcqJrpyYgbS2BLcl8n+2gS2nAWoMFtKdwj+UGPS9xepbB6PPEZjnk5WyPkRc/cb7aWTbLAV9JNX+RXP38VdYfE5+VdD5xRyQ7c6kZsdSKWG3Fp61QJ9OUvLRkhUUrTS30meUlaWGkvciAczJObicBnXqIVopxWvLKhR6zrODh8ZS0KClKe/o7eqtX56ULXRTiRPeQsXOWG6IQPKWZFyWllQrO/iTlb/7xbb7x0jr3jyYkoUcSnP0+1loRhR63d0Zsn0xJQp/6zogPdoYcDGbc2Gyfkk5YGHdidvpTHhyO2R/MeW/7hFoU8JVLPR4cThhMUo5Hcw5H4ixv10Jev7z0kfH807i1O2C3PzslrL4nTV5Kn7nuL680yUvD8Tjl2nrruVTUc/zy4Zx4flnR7IiCNh09u299MhSiUXss9icIhYjceksI4OPxScbAB29VhMwTsqI9Ge3eePXHVxw7PSFDClG+hv2zkPPZRMjoxavPfvxFgN7nHfMUJ0/GJL3xWzLun4zOdj+7S7C/I7umSV1kksO9s8zLD9+VndgXXpe2nSCUPdVGW1YdrtyEtQ0x9kxGci7WiSrZXD8d4dciuNCrkd4rKdIMkzTAiyhR+H5AL9b4KhRnfHsFemtCNI0RE1k6l691rVGpelWsUlHAg9uyt3rx2lmc1a23ZR8UJaS52QI/xGqPIoiZXLhJIz2hSFq4IMJENfL2EnmtSTxPac2O0LYEL0QVGcrzKZI6Jkrwq2iq0lo2/eKjO2O1OncufRXv4QFB0SEPaxzmmgdac+IM2pb8ny72uDd7HX0onerTS9/hvz/6I/7Ff6gZeB3+ZucVtr0WS25OYA2+ipkGIZO4zQ11Ii7YgWKufCbap6s0vjMoJa7jkQqJsJx01tgPOvzQX+N4khOHliw3YujSHoFnKQg4fCw/82lVslAeu0GPN4pttoMunnN07QyDVCX2zIyBl/AX8RX2vCa4M9e6fcbj/bgInGGlHFdmI8WJTqRG87OSQ+e4UJzglGL+FMm2SnPgtVgrx3TNlL7//O7mzxtedVqmGjUvIq+cc88dPL+4/grHaFZwc6PNxaUG43lBEvls96cMpznjNMM5yEpRqRUOv4q6VcgbieHUMi9KLi7V2T6e8tJWh69dXebuwZi7+yMZP/cnlKUjjgIm84K0MBjrUFoTeJL7GToYpTmllSYk6xweiqNJync+PMRYiRdLc0NSmY4KY9kbzLFYjFGstROurjY4GKZ8MCvYO5nTqUUfiUFqJgH3DifgEBd9RSobccDxJON4nDKeF7x+qcYbV5Y/VZmcZgXb/RmdenQa+t6tR1xZbfDwaEJaGO7sjbA4Il8I6KsXe5/4mOf45cU58fyyIoplL/HWWxKLsxifOydEx1kJ5H56HLx5SdS9g50qMigRJe/227KbeP2VynikztTPd74Hr//mj+cwT+pCfG69BStrQpSmE2kmKgohaMsbzyaX46E8Z+cz/IJyTh5/kXvZaH36fqjniblq6bEQbluFyC+Oa/te5VqvopWS2llNpdZC8BbmHZC4okFfjgUlOZvDY7nWi/MpcjjcpffOm5iTh9jSUBRTylqTwJYEszm+1zpLHbBWdm/nU9khPdgW8l4Uct5JXY4lrpqO9h5KOPvyOvz5P4J33hS11RRCqh/dkftsXsEPApanhsILmS9fJG/1yNorp0qNKUvGnQ3WtMRDKT9mEtTxkwQVBKeGpdSPcfU2661nKxnpdE7b95kuX2N/ZjnI5xDDD6IDHkxW8UeX0cB07QP+Sf1N/ld/UmBsxL2ww7fqL/AoXsJax0zXq1ikksBThB7khaXMDLXSoIOIE5XgkxErjW8KfGNQqmQaNfAuXGZHrfEwa2ArEmCt1HOiwPc8lLKkj3V5P4skfuB16ZQjttyIg7DFiavRLaa0bMr9oMcf1m9yJ/qomv9jK3VPYbmc8JV0m56doZyTBljlsR20eSvaIntG8PzHIXSGrplJoP0zbs+1j28MTZvR57MRzx9nJP5xMA78ivg5B0UpOZvBc9RfPg6JaXKcTFLGs4KLL9b5wb0+a0lA2U64n4TsnkyZzEsmaX4aYG+MEF6HRCwBZPOC+0dTVts1jicZf37rgCjwWGrFktdpHZvdhElacnd/jMLQSAL604xpVqK11F6W1p4GzoPC98SQVA99PK3p1ROG8wzf0wSe7JbOs5LE95kVJSutGK01SikascfhKKUeTdjo1p+IJlJKMZxlJIH/hJJZjwPqccCl5QY7/al0wD/HOHyWlaR5Safz5BrXWqdGsxZyNErZH8y4vNTk+nqL5VZ8mhV6jnM8jXPi+WXGpRtCOrbvCqnRnihrSV2ilNa2PnqfpC6j4Ae3hXz2j4RgWiuu8tXHcjz9QEjL/iP503j5xzvOyzeFED28A8qrnM2etN2sbcKdKlO0u3y2Zzoeynj72ktnLnA427/sH8grQL0prv5mW3Yx792SKso8F1NLd1mu09LqZzvm+bQivq2qASmXtYMFovisL75/KNda+3It51MZ0S9c3EqJsal/KORWaSHGD+7Ag1sw7OM5i+cpAgXCoko4ORACGUXy+Ye7om42Ok8qwVEkr6KzqaigSb0KdR/Du2/KesD2XblOjbYcy3AgY/90DoNDvEs36Q736E9GjF76NerjQ2r792VnM52STmckriBIJ3hJQhJElPjMSoMrDHE2IdMe89U1li9s0Op1nnlZk1BCpLWxHI8z/kSd8P15HX98Ex9xqr/e/h3+N38+wBUN/rD9CrNal95oj61yQF91mSpNUGYsmyl3oxUiDMvZjElpyYANp6lpR+4pJkGdh36dnpkSaEUWxNzdeo3J5a+zczjnSkcyEQfTDJNnJLkEwJdxjTj0niCez0KqA/4iusR1fcyl8oTSavaCFj/wL3AvWPqpKoNNk/LV+UPqLmPXa52O4SNbcDU/BuB78eXnVj5dRab4hBpDUWk/+5jdIUrl8+RxPg8ef5yi+hLln4F0esivIk955KXh/Z0B/9VfuUgcaN55dMJ7j07YH86ZplI5+ZHWJCctRQrpZ9dy8ejWI8aznO/fPSIvDb1GTBz4HI7nHAxn+FrL9km3RqsWMprnHI1SCuPwlMXXmsJIFzyVmluWjr3BnDj0uLTaYLVd42g8B+BkkjIvSjSK9W7CeqeGc45ZVnA4ykjzksm8oD/J6NYjtpbqJKHPJC2IAo8o+PhpUhR4zLLn05B1VXhhrPtIJJPUdSZEvscrF7vn4/VzfCrOieeXGb4vO4vrF0SZPHU+r3yyOlmrw0tvSBRPnsmIWLknSecCSgm52n8kndo/zthbayGf6xfP6jKjWFz0Wssxf/ieEMrFi16tIc0+W1fOHmc2hffelJG39qrIoHtC4DYvwfGeRAy1e9DqCVk82pePfeXrTyqan4ZFSB5OCGj49E5s9ct14cwvS1F0790SAlwWTxLVshQ1dDIS8jg4FvIMQqyDSN40+IEcb1kIaV0E3Nebcp32HkKaCaFehNF7Emou+aBDSJpQiyUyqd6Eex8Iid+6IsR9OpVRf1nIsQ760BuSXLuJ6k+YHR0R5mNaowO82Qidzakpj6Tbwdu4AIf7+CeHtKKYuvYp8ChaHfS1F7lYS4guXJKv7TOwtr7Mg7jOtweP+M+LEK9/BR/IkyEbG7/D3/juNiuThD9qvM53l66y1G4QeopZ4diYH3AxP2ZCyMwq7vg9biWb1F3OG9P7LJk+LVMyw6c9G+FrzTCo0ypm1M0cEyb4tQY1k9G/e5v1jWv0Og3uPTygM37E0vQQO08xSnM4b/AwXmakm89U/x5v0kl1yNvRBreCFSJXYJR3Gvz+08RmMaBt5zzyO0/seWc64IAmW8WQu8Hzj8UL5XPk17mc95k8wxGe2JxM+wy954+90UoIZ2E/P9L5xGPrx7JWn/d+CMnGSTd5aSz3shH/2e+/h6c97uwPGc4KrHW4quryaVhAO7DK4aFp1gLi0OPR8ZS0MMxyCY3vTzLW2jVmecHDowkb3Rovb8nPRiMOuLrWZpYZJvMCp8C4KkRdQyMK6DZCSuPwtSIrDPf2x/yTb1xguRlxMhUXvjFiTnrlQg/P0+wPZuwOZoSeJlVQjzw8pdjuT5nlJRd6dax1XFpqsDecf+x1ygpDrft8FKBdC+nUQ4aznOXWR793hrOcbiOimZybic7x6Tgnnl92KCXO9o9zt38Skrr8GZ48O15pAc8Xsmh/woC/KBbVbYEsFRWwLKR//cJVwAn56iyddaCDPP8HPxLSubz+ZITU6AS+/S05l6svnr0Ih9XzHe1JPml3+fmJ86Juclp1mz/90pZnVQNTIgonyPHffR8O9mC9IvHGyDgc4MbL4kB/cFseLghFmbVWjn0ykI8XZWVG8qvWJSeqZq1+VhKglRjFPE+eQ5kzA1OZi5krrsmbE+cg8IX0RomM2mvNSl0G5rtQFgT1GpsKundu82jpGodhwtLebYJWl3ocErlSvgeW16As8LI5XhgSNluwcRmaNQmvv/HKsw1vwJEd8e9kfYrta3iIUz25/E3+vbc/4NX3Y44al/iLm6/wvXkTDQS+h7XQr3cpPY/36xcYq4idFE5UgqcUMy/kLxrXGBQtfmN+j1o2YVvVqGvHZjHEGctu0OJussEsWaXp4PLkEaps8O39nAv779PL+2w7j75Xx3eGzWLIspnw/fgiO0HnI+fxrB3NXPvkX9SvTOfYLIdMdfjMa53pgMBM6Nr5ZxqLPwx6bJZDupVRavHYgStZNhPuhCsM9fO14nhAHEg01mcKgXxOOAcKWbMo7JMEUVdfnGc9q+Xs15hxTgixgzc/PKZRC/C1xlmH5ymKx9iyosqzrHZL/SqeyNPSvx75mnuH48oYJMUIpXUUpaUWesyykt2TKZeWG6fj7aVGyKXlBvcPpbnIqxqQmklEM/YxFsLAJ/IVtUjhrOPD/RGr7Ror7YR5XvIgN1xda7HUjMlLw3Z/RuR7XFpp8M6jAYfjlONpRlFY3nnUZ7mZ8I2X1lnr1DiZZEzSgkb85EpGVojSucgQ/TT4nub6Wovv3JHazVZNzFbWOYbTHGsd19aakgBwjnN8Cs6J5y8D4uQsB/LpTFCQDMallZ/M3f44nJNIn7vvV8SuepWoN4U4rm5+9MV02K/G8StyjMYI4Vu4+scDIYLPIjztniiMo8Hzm6Q8T8jw298TsjY4qrI3kes0nQi5rGJ6aLbkebauyArDfC795VoJyVvdkOcej+DRPfl4syNk0ZTVY3SqEfnwbMfW88XsFCZwcixMx1SOdJR8nh9UJDaVx3dOVg+0J/fTHqDlmAMJOZfPHQjxdVb+fnCHYNgn8DxuvnAR++AOXnABv9OTx3x0V5T16y8J+dzfkfNeVIA6K1/D/W1wjjxpsD+YczCaczgd8X//8I84fKuLchdxymCu/gH/y3s/4K/8o5Bbjev8oFPDtLqMuxfwshHGWKJsSqOcE02OOfbqbLs6hy4k1WffSrmBkVfjvfo1HnUuEY2OWCuGfE0NCJiw31jjKGiyP3c0dEC9VyehDkfb+KMDmpMj7uoWQ2uwCkrlsadDlssxL2R7HPrN0wilJ76Nn+876acCBWgs9lPeCapPGJs/C4d+kx9GF3g52+VieUKhPLyqL/5esMTb0cbHvql4+viUhnlhn6kY/jh4/EwtlbEo9KgFPtO0IC0Ni82IT3tOIa1CPBWc1pXOMkM9XjyTqtYK5MHcY/cD8D1VGYEUDnHDz3PZ1ww8TRQEFKVUblonve3z3LDTn9JrCHmPQ59vvLTGWifm7YcnpIUl9jW1yKe0jtD3add8JvOSjW6NpUbEhaW6jLWN4/pam3oUUoulz/1kWpDmJd1GxMFwRuApAt9jNMtIC8kgnaQ5dw/GOCAJPQaTjKwwtJJQfpWmBZO04Npai9X281dvXlxuUBjLrd0hO/3qzbiDRhLyxpUltnrPR2LPcY5z4vnLgO6yjEZPjj4aHJ+lMgLeuPhcLzjPhf1H8N4PhDCtbsorlLVChN79vpCt9QtP3mcyqnreQxlRH+2Lkuic/BmPIarJsT6tagah3PfpfFJjzoxYcfLRkPuNS0LWPvjRWd3kYt90aUWu1fG+RCstxuqdJRn7N7tnvfOLmk44U6aP9oX8OVd1w1ch80Uh43KUKL5+cEZOlZJ1Cufk2JttIX7WCsnNUpk91uoS8ZTNJa4qimHUl3NcNFINj+U5PE+u2/K6BMrv3IOkQeAMmFyamEAeq6j2ZotqDaBWP4vlytJKFbdw6y3S+3f4Ye0St4qQv3v05+y/X8crliUT8+J3+R8O/oR/4fc1f954hf9w/TrTuEU3gKvlMWE6I9GO3vyYS/mUuskoy5LUaX59cpsfqSVuhatVq0x1OZxjlhlM6GPra+yZZTaL24y8NieuRjY3Yh4qpZbwGEd0fMhqVnDkxwxy80SmJkj393o5YqmcsBe0n+tb+4uCU4oTr8alvP/M0bd2FqfUjzXyfxD2OPbrrJUj6jajxOPIb3Ds1Z87zskBn7Ie+5nx9MMFnkKhZGyuVVUV+Xws1yFE06veu3mexpQWYx3jWSaqprPg3On3mHvsvjKmF1JtnSMOfYnHUnKj73no6h6R72GsNBMZY2kkITc322ilaCYBoe9RGsdomjPNDJOsAAfNOCQKNKNZQRx43NhoYa3j8kqL6+vy/55W7A3m/ODeEQ+PJkyzkmlWUlrHYJbTqUVCfK1jvSOh+HlpMNZSlJIEcGGpziw3HE/SqrIy5LVLPa6vtz+TAUgpxfX1NhvdOoejOUVpCX3NSjs5deGf4xzPg/Pvll8GBKEYi975npDCRdTSfCak6NJ1CT7/PGAMPLgrZLP9mFtdV//uH8jO5urHON2P9kRd83wxyugqlmk+gSOEFEVP3a+oajGDinQ5J+f54K50nafzM7L74utnCQGeJ1mey2tClO+8JwSwsySfMziWvdEX3jhTg1tdCXsPoyczS0EIZJbC678Gu49ExV3egPd/KPuY2pNjD3zIC3mcIge/LmpoqysKsVayw1sTRzoH27IuoSvDka6yUztLcr0XeajjEcR12ZUdj0RJTWdCOusNuYaeL+R0MpHHKar4qKIAnJznQkXL50JIW10h38ZCo4Vp93j47m3+pr3N9/fX8GZLeMBs9RZ/zf1D/ud/WvDtpV/hX3/tt+gHTfLSkmayXrCPz6+mI75uDmgUx6ReyMCv8yBq8cDWaeZj/lJxm61ywEHYZRQ2GEYNrJKxqDHyAq+UIbYaoxTaU1AKAfC1ojCGvLSUs4zAloxVXfbqqjHqKcFQomVFrvzs3+dfALaDLheKE+o2ezJj1DlWzZi+rnHo/xhJFMBUR9wJP2Nr1xeMrHRYV1JaQ1m6ygn+2aAA39fSBATgHMYtHPju1DmvnvJcOaqaSSDwNUmgSZ0l0JrCOlFQK2IY+BptHEVpUJVjfaV19mZhcdyvXFpitz/heJJX6qiQyHY94isXe6y2EvYGM2qRj158XwMb3Rr1aJ3tkynvbw/YH2q6DQnEb8U+j/ozamGAVorMlIS+mIomacFSM8Y6+EsvrzNNSxzSlf50/NJnwSKv8xzn+HFxTjx/WbC0Ks02uw/F9VwWEvuzcUkc25/XmH0yFPXtcdL5OJqdquln9OTeaqNS9vZ3ZKT+eD5pvSm3z6ZCwFY3nnzMw6omc6Gs7twXIplnQq6nYyFgt9+GO+/CN/4pcduDENulVfjGX4Wv/qYQ39FArkdvVW573HXfXRIVd/eB3L4IlzelmKfa1TWNEok3arTF6HXrR/LYSgnh9KyQPj+Qr4M1QpDDKjqr3hKT0KAv7op6U47DWiHKqxtPriSEkZzjg1uQZfL/6VzI6fKakGCcEOmyhNlYzuXRnbNrbUoIYnmebC67qFEk+6npXPoMgP/L/m3+5pHBG97AA9LOLr/S+Pv8W98e8m77Df61m7+BWdqQhpa0kH08DWGeklrFsNRcMznJxibTZInjMmQ+t6yMTlg3JyyXI5btjPtmgs199oIub9cuUCqPoiwpjaYWeky8kF455dD4GOuIQy2NNc4xmszpocgI0KbEeSHKPbm3uRhTP2vM/mXAvtfk/XCdF/M9WmbOTEdoLHWbM9QJP4q3vrTH/nnAwakD/PE3DI9DPfa5z4JxgLGnK6gOqbZ0OKpEo1Py+XgkVOQpfK2II59OPeZwLK7x5VbMo+MJWSnlFEmosVZyLovSEHqayTxnMM2IA4+8tAxmOcuthDeuLHF3f8Tvv70DQK8Z062FbHTr1GOfvcGcpWbMyjPMO61aSKsWcn2tRT0K2O5PCDzZr7XW4Xsa6xyFsSw1E6LAIysN9chnMJMdzGYSkH/eMvU5zvFj4Jx4/jKh1ZE/11+S37Se/5N3pD8Na89MMM/CIhLKPfULsN0727XcvPzkbbOJ3F6rw733RQ2MEiGUD24LKVpeh+/+kRC0/qGMpEcnQspqTfl4kcHDu/Dnvwd/+Z8+y+xcoN78qIr5rON/8XUhkAc7QuCVqipAl+DF14SobSRy2/3bQgqvviQEucgk2zTPRBUtqsYnrST/ZfOK/H9Sl/NIp6KWrm6dnZPvVyquJ38fHwgJfuEV+f9Hd+XjcULVzyerAp2eKJvvfV+U1s1LMpJfVHQWBdRaZ41TYSzHAZDN+WYr4T948z3KvU08IK8NuLT6u/x7391Grf46/6/f/sf4YVHneJLTNIbQ95mkJbO8YCsf8NLsER2Vs55o2i5HlRkv1A2XVlc5HExJP3jArIC0topK5wyCFrlTbOVHFA6+l1zCAr5yhIHPXdullZ0Q6ACrfcZpgbUWT0E7HXHsNdgLmrya7zLSCfapVZKOnTHWMcfel3Q3TSnej9YY+DW2igFdM6Ug4G60zE7Q+diu8l8kLEbmn3T7p97fyo+OtfJYrhqvq8dkzsWPiaeVlILVI5LA59JKk61ujdv7I4bTjDiWvM2sKPG1ZpKWGFdgrCXyPZLQJ4l8jscprVpA4Pm8cqHDpZUmrSSk24iII5/3Hp1graNdj8iN5eR4SrsW8dqlpU9UI0Pf46WtDjsnU8bznEbiY50jKw1ZUdJMQppJQFaa09WE0lhu7w3ZG8zJCoPvabZ6dS6tNGidu9DP8TPAOfH8ZYQffPrn/LiIk8oJPns2iUtncnv81N6a1uIav/e+7IKqqlmpLCri9oK8SBzuyWMMjkUddUZWBZZWRcl7dEfML53lqut+6Wx3NUokZuhgV1zw7d6PR7zjBL7yq0LYxgM5rlpDjFG+f3Y+l2+KOnpSZan6VQ2lH8gx/fk/EmU2CKVPfnlDyOHhnpDOelOOMc/lnINASG8QyvlbK3urSQ2uVkH9yxvi9L93Sx5rNJBzvnhdjmsRcK+UHFerK8R3NJAxfZ6J8rlxSVTp2YQfTfv8GwbGb18ExKneuPhN/v23bnFp8AL3/rl/i73ORYYP+8TDGZBVe2sWrWHTy3kj38Yox37UY6nlEWPpq5ik32etFtHwAx5py1FUJ1QWhUPjMF7AkWqyWQy4Hy/T1w1aNZ8w9JhGK8ySkt7+fYpSM/NCKA21ckZfx7wdbzFVAWtmwqYZ0Nd15jrEc4aOmRNg+EF84TSE/dPUs58JlGLfb7Hvt1BVFM/ntov9S4LHySf2LLEg9MQUZKwj9LSkLARCHq+tNrmxKfuMgdasdWp8784hUegznuaM5gXz3GCtRSsx+Kx1E1abCVfXWnie5pULPS4sNZ7I0tRK8cqFLsvNmO3jCf1Jhh9orq712OrVn4sIXlxu8JdeXmc0yxlNc0pjyY1hpZVUzUKKwbTk0kqTwTRnnhvezoWUJqFPYSzvPjphbzDjV6+vnOdunuMLxznxPMfni6QuZOvu+0KKHlc+TSlE7epLHzX6gJhp1i8KsZuOhVhpT4hVnIiT/NpLUmF5+x1R7S5cO3sOzxci9fCejMI3L330RdoPACumoclIFOAfB4uWo6dV02ddj+QZipq1suJwuCNqZaN1ZuSJEiHb92/JvwMfUifnurSCU4ppe5WiMPj7j6jFNbzeYwH6zY6Q1tFAHmc8PDMv9Q+kverKC6J2TsZyzZOakM73fgB72zAe8FAp/rUAdvffQDkPpwzu8h/yr979IV9/c53Rlb/K7V//a+StHnWHNLVMdPVCL20uxsFaPqBmck6aK7R8j7mCAp+asgx0jfrxMb6CuFEjP8hQ+ZxC+dgwRltH6gKW3ISOSckaHVaaNQazHGKft7wtXKzYyo6o24zCwVvBOg/8LkMvQQNv1i7yQrrPmhnRK2ZYYOAl3Am3eBCcrXs8TTif38ryxeDL0p/+RSCodiU/Se18Hiy+hqfk87EvqqoySK1ZGJmqNIFqf3MwyTkZZyitcFV00vHxhFlhcM6hKte9pzWBr/G05vJqkwvLkvZwNM64ttb6yDFppVjv1Fjv1LCV6/4j9bOfgutrbf6J17d488MjmvWQWVacEsj+JKMe+QS+5nAwQ3ua673WadUlSKXmzsmU9x6d8BsvrH3m5z/HOX4SnBPPc3z+uHJTdgj3d4TQBKGQxPlM+s0v33j2/XorQgSNEVJ2sCM7ncf7Z+7wX/uviIt7NpbPf3qk7/sQhdCvyNbTKAshdtZUGZo/A4wG8OE7cn36R3Ke3VVRKpfXhBzHNXjpq6Jwgnx+Omc2y3k0yhhMUphP6PR3iXVInDlWImlaIQhFPX50V1YXQFRepWQd4OU3ql3Ui2fHdLAD3/4DGBwzcY5/PTH86PANvEI61bML3+VfOv5T/tnv9Th55b/G4cWIgfVJ9u/TevgeToEKuwwKD4WiGQeyc1la1ssRLkmqF0MP42uGXpP64IATYoLpHN+WDFxCjMEzOQ/DZYpqa0NGo4pG6NFYbaEUHE9SitJSKMWebvNh1KDuKTJrSY0+zXK0wMRL+G5ymaZNiV2BQTPwEspf4P3In2d4FQN8vB5zEYf0PPC1EElpCbJkpSjFEgGlaAQah8JTinFWnL5RkjG7wljLnf0R47TgxY0Ok6zgw70RCug2Ql5qtdk+mXM4mpOEHsuthGYcVC52ybdsJQHH45SsMMSf4PgujWX3ZMaj4wnzTGo2t3p1Nrq1J4jis/DSZhdfa27tDPhgd8jDoykoSzMJqUUBvlLU44ClZvyRx9JKsdxM2B+mnEyz0/inc5zji8A58TzH54+4Bq/+KqzswPZ9IXhxTfrOVzdFLTzePwtWb1SqQBRLzudb35GazTI/M9XMJrJzuF910BfFmTv9cdRbstN5uCsj6jpnvfHWimlmea0ab/8UVw4+DpMxvP1dGXMndRnHH+4KQRwciTGrVpmpXnr9LJC/Vid954c8unWXeZbTDX10vUF67VXywz12Hh1hN5dYX3Qp15uyy3v/dhW8/4KowctrZ4YoxBSxv3eM93t/m2D/Pv/xRswfDW/iDdp4wHz1Fv+N8vf4n7wZMLz62xx8dZNRaljyNV1jGB3sMYtqeM6RHH3IN7wIE61ynwZZYfG0IvQ0gfbB82gnIcZZtr0uiRvRSkckgaXQHtHkmJ4XczfusqeaKOuwzhJgKB0UccyNlWaVUeiYpDmz3JBbi3OKYQnWyQusWvzHCWFRSjH0EoY8fyvPz0rt/LIprT8NfNxag6h/Z7cvPuZ5Glva57ouSeQTaE1WGhTiws6LEk9rQl8RBj6lMRKi7iDwNMbJ6N05R1Y64kAC4dOy5GSaEwWSmJCVjmudGrU4JAk9HLDWTlhuxfQnGaNZzlIzPt0f/aTjTfOSN+8e8ag/JfI9Ql+zN5jx6HjK5ZUGb1z55H1PTyte3OxwabnBG5eXORrPmeUlSRjQSgKS0Oe7dw4/NuooDjyOjCHNn6828xzn+LxwTjzP8dNBFMPFaxK4fhpc78Tc8+guTKsg9DAWkrV5+WzUvr8tve8LpTQIYeuqRPrMJnIbTm6LniISYQQbF6S7vH945mzPq5zKVkc+/uIb8nxfNLbvyhoCiMoIsnzWXRYX+XwGX/k1uW6P16J2lri79RofTupcqGmmnkdRb2OihI73A9p7D9k5Duk1Y8KFupGmomy+8Zty7Z7C0SjlzbtHqA/f4e35Pf5/yQ28B2uVU32HX6/9A/76D1NUssbOr3+DycUXAUUxnTHZv8flaxdo6YjhLMNYRy1aI5n0cf0TiqBN7gUMZznzosmV8pBZIyAKfQaTjH5hUfUNGisruMkBxyphOj1iWzd54LeoV+eQF3DBTTmJuwyjNoNZxmCaodGUzmIXdmf3ZA6k46PxOAsstJ8vq7/3F510Ah/JznwcznEWf1TB2I8nnY/Xm2rE5T0rSkprUShi31U99Y7SKlwhu5mFsQSeIgw0pbHUwoBZVkosEqKCfrg3ojCW1XaMNTCa58yyksjXQlitZZKWLDUdXqWwAoznBcut6BO70t/fGfDweMrmU+pmXhruHoxoJgEvbXU/9v4LJKHPxZUGF1eebLCaZgWeVpTGPvM4SiP7qZ+mrJ7jHJ83zonnOX660BoWIdd33oNbb4tSubwumZeP7kq+aJwIUV1aE2J47WX5PGuFTC4ijZodUQg7PVEN682P1oH6lQnn/m0JTI+rPctWTx5veHImrXyRyHP40bclIqndk3MBUWHns0qNDKHVltrLgx3mBvpejQLNe3sj4uU10qfGYuOLL9A0Bd7eDjM/JWxV+5phfJZT+hTSwvCD+0f86fG7/PHhHTj+xqlT/ery7/Jvfv+QqPcKw69cIRocEExHTDeuAdD48IcUpcGECctJyHIzxuHY6c/4MAthfEi7McRP6rySPmRpvsPa7BCTjzhsrpOSYCysdxJqTHiwepNv6ouQ3+XyZJstO2JqA7CGxJVk9Q4P21fxTcH04UNWrOOEkN1So7U6zWD09fOFmn9ZCecvE0wVX6Q5y1ddfF18T6OVorTSU255cuz+NCzytV+80cgKi8NhLGgceWFRrqrdtAbnySqGtaA8RVFaUDJijwMPhUQ4OSeqqNaKLLfM8pLxXDram52EeizjdM8YjIWiNCShtCwZa7m03Kyc5U9iMM24uz/ij97bI/Q94sCjUw9P1c3Q92gmIQ+Pplxba/3YmZv1KGCtk3D/YEI9/uh0ZzjLadciOvVzZ/s5vlicE89zfDGYjiU4fpHJOZ+KeWY+FXPNbCy7nUd7oopevCY7nE9j4ULvrVRB8dviXI9jcWyPToRQvvC67H/OLohrm8fU1VZHyOdo8GSW6E8TzsHeA1E5m+0nc0qTujje+4ei4L79JgY4PB7Tn2WM/RrH3Qu8m9XoNWOiwKcWnf3omrjO8MZXGQY91hoGGr48x8qGjNef8eL3+/fe5z948w/g/kXgIiZIaW99k3/7nQesTF7gne5Neu06Ha1x2kPb4jRp258MyKPkiYftTzIeHk2IQp/ldo3Xyj7JnTdpZyMyq/Bw1If71IYHxI1VDvw2utC8m3R4y3UpEpjXl8i0T7ecEaUjZsCPVIuJarN5vMsL5QlNSjytmOBz29Z521vFKHlR/SnUhZ/jp4zA1wRa8jrjyKMe+Sw1Y6LA4+7+mMk8J6smwbr6j7NPKqUKGZeHvkdhDNljNZ5Ky5rFaRaoA087CuOwCEn1PEXgKXLjKEuDUqI6+krTiAM8LbuS1jmORimPjid06yGrrYRpXpBmhoPRHOXkDd0kLXjpQpetpY+aCu8djHn7YZ+D4Zz+NKOVBNzaHZ5mdC5+rhtRwPEkZZaVP1HY+5WVFgfDlL3BjKVmXKm0juEsIy8tr1788YntOc7x4+KceJ7ji8HgWDIp16qqzON9IZ2LuKOyqpK88aqM0vceCXF6Ou5owS6aHYn8ufeBkNXxiTjgOz24eAP2Hkp4++UXJIpo0Zee1OTVaO+hKKY/beLpnCi0uw+lwah/JCNwVKXWVuwtCEQBPtqDKOJRvMJDGjRaTZbKKSvDOwy9LW4PO3hK88Jm+4nxWal9xt113Isb0H3G7muFh5M+/+of/JfsfW/ptFNdX/pD/vqdt3jj9k0mV/5JZp5P2J8ySQs6tRCvzJg2L58e69Qo6r6iFgrhczgOR2nVDe0TFCkvH90hLzOO4hYzpxmXJStRhJvPiacjBvUut7pXeUSdpH/CTXuXOJ+QF4axl3AnWmXWWeN4kvLV2QMu50fMgzqHQYPCOOou58b8AN8v+G58kcx5vxQj6l8kWCArLXigtEah0NojKx1bvYSDQYo1FpOVlBapzqx+/BWici4IZi30WO3V2TmaUhqHwlEaUUqdtadq6iKU/rTIaPFx53DOVmYk+ewCw/5ghgNCPyXwNJ5S9KcZbz3sc2O9TeJ7dGohgeex2a3x4laHzV6d5cWe52M4GqX86MExvqfZ7NU5mWa0ayEKRX+ScvdgzEtbHbzK0a/4yScyy62YX7m2zHuPTjgcpVgrLvpmEvLK1R6XnxrPn+McXwTOiec5Ph7jIZwcyog4jKrYnx+zKq0sFvKDhKYPTyBpnBEv3z9zoW9dhVtvPTvuaDyQY+guyx7pV35VDDt5Kgpnsy0E894HMp5X6tlxRto7q4v8aeLBh3IuizlgqyNK6/62qLadx3JGhyfgLNP1q+zvjGhGPlHoUxIRTAbcTA/Yrbc4maQcjyM2e2fndTzO6NZjlprPzuQb5XP+9T/9f/P2n8Z4xSoKyLe+y7/U/w7/+Pgvo1q/TW4LnJIxZxJ4zLMCNzjGeAGTCzdxzjGc5dioyyuTBxyP5ySRT+h7TNOCJPTQRUYw7hNkU/L1q7RRqGlGfwIPXJ3AOSJdMg9r3PU69I4fcnX8EM/3GfkJuVMk8zG/Uk545Jd4ZcRGekzeXsJoD5MZCusYuADCNheyEx56HR76nZ/mV/EcP0VkBrSx1KOAwINpWvLOoxMmaYH2NF4VwKmVwlSLoUnk0UkihrOUwkBuHA8OJsyzUtYvHnv8p4XwxY+iYhEs7yjcgqyevX2pRx6ldWSFYZqWNBKfjV4dW/Wk39oZcHGlya9eW+WFzQ6bvdoTZNNYx8kkI63C5h/1J+SFZaWVVDulPrPM0IwDunXZlR7N8+r/c7qNiObnEPC+3qmx3IxPXfa+p09V5XOc42eBc+L5i46ylBpLY2SM+zzE0RpxlT+6I+qcUjLfimsShXT55mcPXg8qQuSsHJMxMvpeoCikT1xrWFmT3czDHfl3Uq8yQIdy/xuvCOlcoNEEnjqvWl1I6iedY/RTjhAZD6o800TU17KQj0UR9I/l/Pyq9306lsD7yy8wyi15aWnVzl50ilqLbnrAxSDnnVTz4GjMUjPCWNkZCwPNi1udj4zNCmP4d7/3/+VbfzjHm3bEOLR6i3+++BZ/7eRXOfnH/z3utXokt35A950/wz/egyCkUThWPelGv7f+Attej/nBmOEsp5702BsfEL//IVlriWYjoTCWsCzwp33yNGNmfYbTnLy05IU5jcIxcZ0oG1AfHjItOryRbjNRIamu4SlF7jTzKEQHhovTXepBi07is6885pkhLQ3WOFCQRBE206yXYx75nXPF8+cYDphnBYUxeBrmuUErTbsW4OWibAaBJlEKi5OUgnnGNLNiVEJUTHHESx3mE/Wojz2X0qAqNqpVtSOMkFcUBNUnhxS5F2AAAQAASURBVIFPWpjT3nR5TAXK0W2E9OoxL211WGnHDGbyJnalHRP6HsfjlHcenXA0SjFWSO3D4wnLzQTnpOJyrZNwd3/MXCuS0Mc6mGVltd/quLraxNOfzx66PN/HT0LOcY4vEufE8xcVzsm4+sFtGA0rohXJ+Prqi9K083F4dA8+fFf2ITuPBaRPRmIOiuKP1lo+DmNEKZ1NACUqZHdZiOXwRP72qlaihdJpyrMwdoe4ulc2xf3eP5DPb3dl93N189PPf3VLxtt59kR80Ol5xDVRcH+aOD4Q41CnWi9odWTsXqsqP/e3JT6puyLkud2DzcuLVconoTWehiu9hEle53iScv9gwrwoqccBW702zccMBM45/pP3/xH/+Tcf4J2s4BGStXf5reib/C/2ujx46b/L7ybXKfdymqM+qV6ntfY1Ng/vUJ8NaUQBG9e34PILmNVrxM7nve0TAk/RqLfoR6+wvHebxnxAPjxEF5ZpELITdWjYI9rlnONxxqxy1oKiFnpkzpKnGUVgWSrGBGXBXlCH0qBKMZp4TjN2IfVyQiM/Zh76aK2px5piakE5SguztCRUmtDm56Tz5xwOmBUWVdhTwugpQ176xIGPcwXWOrzQozSGPCtPDUnOQVARSK0U1jrpYq8ee+GgBxnPe55G+VCUtsr7VChPU5YG3/ckBslBI/JOH6URB1gL3UaE0hD5Hso53npwchob5nCstBKurDZ5b3vANC1YbgkRLY3l7sGYB0cTmknIWidhrV2jNI69wYzJaM5olnMw8ElWfV6/1OPCM3ZEz3GOXwScE89fVOzch3e/L4StuyRxRulMjDvTKbz29WePoIsctu+JSvd05WWjJePpR/dkV/NZfezjIbz/IyGetnIFeL4Q3q2rcPe9asxeg+NDcW/nuVRetnvy+YNj+fyv/ZaM0NO5jMYbTfn7ebC8JuT14YdynrWGvPpMRvKcN79ylh/64yJL5fj84NnXcjoB7zE3aa0pbv69R0KGVzcgqsHapjxWEEAQEFQufWlHEQaqjLAyL05o6EBehD1F05c8wftHE47HKS9f6PJOfpv/wz/4Lm57E48VimTIjd7v8tf3E44a/xR3r8W0pgNe8/f429M2w0cDVtsJaecSh401WuWMVhKQXdng5Rcvkh5O+ODBCT+81ycrDX6l0MAWNddkKS5xiWbfhZRBxGtqGy8/xpgZBr9yCEvmUZGXKFOyW+/ScDkpWmJ1FgqVBo/qhZ2IpCzAlFW8jSjB8liK3Fh8UzJ++o3FOX6uscjxTGKJYMuNuM6ddYznOcVCrVx8PkJUF3ub1j2peDon5BMgCnxU1UwU+R6ep3AoEt9jbh2+lj3OwFeYKuMTJHIor/bLPaWwxlE6SysJWO8mhL6HsZbdwYy7ByPiwOfySuP059f3NBeWG9zeGbBzMqXXjAg8zcXlBkvNmKPxnP4441dvrPDSVpfGM1zo5zjHLwrOiecvIrJURrxBeEbmQMjRQmnbeyTK59OYjOTPsxzlICPj8UBGw0/vX2YpvPummHaW1s4C2vNMKiythVe+BruPZNx+UlU2bl6S/M6igKP9qnv8RRmzx7Vn12t+GjwPXnxNyPPu/TO3e6MDF67A+oXP/pgLzCbi0D/YFtVW+7IecOHak2alIAD7WHuSUnKeQQT9fel69wMhxTdekWty6y3avSa10Gc8L07H7eHkhLzeYRQ22N4bUI99Li43nhitf+f4Q/73f/9vw/0rwCbGz+ht/EP+3X7Byso/w9vNkCjwaIY+KotZGh9yJW5ylNRQSrPSSmjX26fxKrdPZuy/tcs4LTgYzhmnBaGnyQrLyWRKHHqM/QYPComTyUvDPJszy9r8Y2aXoJiidYgLEpRSFGnGaj7gwGvwdrDOVt7Hx4ijuBSmoIDSSDj8hQjmzRXUdEQxGjHWMbAwhlgSk1Og2Q/bX/psznM8iU8KyVdaYYxjnpUQeqckMSvKU9KpHnsclISp21Le3CymBQvyqU4/T1TJsrTSXFTtgtZjn3YSUhpLURq076GVpjCOeW6IAg9jLMZa0sKwmsTM8pJaGBAFUpkJ4GnNciPhvUcDbqy3TkmnsZbhrGCWF+TGcu9gzFo7ZrMnU6fQ1yileP3KEl+7uvK5jdfPcY4vK86J5y8iBhWhe9ZIWmsZde89hEs3PqpaOid7lE9nYz5+f1t1GT6Noz1xbS/aiRYII1H6jnalyvGN3xBH+2QkveAnR2ckbP3Cx0cpfVb4gdR3bl2WnEyFqI7PUmqfF9MxvPVdUXSbHSHzZSF5pCdHYnbqLMnn9lYkS3QRgg/VDus6dLqiKr/6ddmZDUIh7sNjwv1dLschd4Ylo+MpbTsnC2O2WxfZOZkT+Jprq02JjyktDyYH/K2732J26wrKXcEpQ3Dhj/g3Dx7wG+o34R/7NT48mmJns9MWExsl5Pt7NPSIZPMa/UlGpxGy0joL5B/OcnZOZnz9+grbxxOcszSTiKNxSmEcgYGlZkgZOXb7EwbTHGMcw/Yaj7wJV8a71EyOLsZoa9FlwUBH/F7tRQY6IfCb3MgOUUWBUz5nr7cObQ1pVvBucwk/jFkf3qXnzcmjBqkyhNmcCMPb4SoHqoFX+dYWIvs5fjZYZHJ+Gj7uUxxgjAy4SyvxRK6SLfNS7qWpTEFUv4YcVRC6Iy8cnqdxzqKRrR+qHc5AQ1YarAWtHNYpPOXhe4rBNDsd3dfjgMD3cFkhHe2lY+agkfi8uNmhMKK8F6Xh4nLjKaIoxzjP5Q1nVhjuHYw4nmQ4JwR6f5DynQ+PuDkraNdCrHNsdGu8fnnpnHSe45cC58TzFxFlIa8AH2cAWjQClcVHSVitLgrjbPLsUfR0ImTrWaPlw1157Gc9rx/IK9LgSIhXvSl/1rbkufJMPufxiKHPC0F4Rvx+Ujy8K6RzdevsPINQrtnhrijNb/ym3NZdEeX39ttyXWsNOT/n5M3BpZtnpBNkd/bVX4X2XXp7D/HtmP5McxBsMOptEiytcM1TPDqeEgU+Hxwc8l/s/T7T2xt4xXVRCze/x/+4/wP++e0tvKInbwZuvUXmWkTRk3u9pQPPwigtGExS7h7I+bRrIb6nGc9zAs/DU2L28LQmzQ15aYl9xck0JSsNcegxnBaSfeh5jFTM95vXGKiYpekhzXImuaRxgx/EWzwIRIU/9Bo8CDtczY/pe3WmLiT0oa0MF7yMB+Ey98qYiQ1ZqzuuuwGbXs6sLNhXMfeCHg+CLk4pSns2ej3Hzw7PQzo/DY8/RCmtlk80GS1KA1S1uGkRguprhXUQeQqNj+8r0qLEmMfeR1upxgwDj9DTXFltUg99PjwYs1wLmGaGSVYQlJa8LKvHtsSUNOOE/iRlPM/JCsPVtRbLzScNir6nCTxFmlusc9w/nHA4SunWI3xPGpICT1OPfeZ5wfX1FtfX2qempHOc45cB58TzFxF+uJAOnq3uZamobc/qKo9rMg6+885HP6fIJej9hdc+atgBGRV/kpqo9bMrSGqNTzY7fVmQzmW83ux8lFwrJRmixwcSBN9bFtI3Gchu7dFeZaYKhHi/9IZklk7Hctt0LAR0aV3I6KXrtLKMlqdZ9yKMk/7oh0dT7h+N+I9u/x22P0gIZlfxgGzlFv9c8Wf8M+/3mHffwL6whbf/QPZphye08hFZ9wLE1SqAlTaXhzPD+GhIOOrjzRSHg4SD9hLrGz3muaW7FGMdVWySZpIVTNKCtCjJC8ssK7HOkRW2UpYMCseBCtn2LxInPWJbkjvFwEvwfA8qVdIqzTvJBYz22cgHdMwMz0JQq9Nfushx8wLtAo4PJzwIOhz4PRrkuABOjCY1T75Befw7K7E5G+WQjWKI5ywnfo1dv8ORV//iG6vO8WMh0DKQP93pVPLmwjl3qnYu6GhpHFop4kATBz5ZUWKtoluPKY1jNMtQWtGMfTr1mGbNp1cPyQrLOC94cbOD0goNvLc9YDDLJA9UySh8rV2n24iYpiWTeUES+jSTkKNxiqcVrSQgDn08rWjEISgYzjJOJintinQ65xilOUutmJe3uuyezGgl4TOD5n/eYKzjaDRnfzAXw2Pks9apsdSMn9nedI5fbpwTz19E9Jah2ZK9xoVTfAFTChG6+sLHk8TLN2QUvvuwivsJRZE0Rgw7F689+37trgTDPwvOynPXfw4I5sehyIQ8PoskF7lUYd7/4MxJP+wLSf3KrwnZn0/ljylk5L/7UPJGi1z2Pk0pI/u1C0JMq+irhabinOO/2Pl9/s73DgmGGwRA1t7lG9G3+G8PbxLwGsNmQeHFZMYSdJaFeJqSpqc4GR7huh2UUgSjY/o6wZSG14/eppHN6JiQIFUM+iGH/U2IV6hVL6adWshknnM4FPetpxcV6Q6tJWfROsgLhzEG35NdzLFOGGlO45S0U3hKXtCtg0IF/DC+wK1ghbaZE2gI2238egdlFfOiwCwCv52l9EIUEhP1cXuCbTPja/OHLJkJqQoxSrGUT7mSH/NutM7tcPWcfP5cYGGuOxux+56isGIecpJsxCJXvjSWOAmohR7dekgc+ry42WZ/MGcwzRjOc66syM/UcJ5z73BKWhhmWcGFnmWpFbPainlhq8NonjOcZDRqIXlh6DYiktDnxmabvf6Udx4N+NG9Y5q1EHBEgc9Gt4avFZdXmtQijw92h4zmObXIZ56XTLOCJAy4uNRAa0UjCTgYzjHWnu6JfhzSvORkmmOdox75Ejz/JfkezkvDjx70uX8o6ziB55GXltt7I66vt3jlQu98heAcT+CceP4iIgjh2kvwzvdFTWt2hGSmc8n0XN0QVfPjEMViAlrdFCNSOhOT0tqW7Gr6H/Nts7IhjvfJUExIj2PQl9H9M3rDv/SYjisHewZoIYqPK8F5Ju75kyOZDYaRVGMe7cOmk2uX1OQPK2LOeu/74tBv956IdSrznPHtW+zsjdnbfIl6FLDVq/MX4x/yH//DH8DuJQLWKJIhN5e+xX9vfIW4+A2m3Trd/TuUYYMo0MzSkkarLnFY4wFRq0djfMzOw4ReAJMg5iju8rX+DuPZnJNmD69dR+PQkxHdnQ9o3oiY08U5aUA5Hs8BdeoK9rQiDgOcc5RGi+Mc2c2TVBqHq4iDcuD7Ck9pPBzGOaypOrGBqY6Y6kjqD+fQsDMciihQErRdlBIebu3prt+z4DnDa+k2XTNl2+9Wzw8nQMOkvJztMfISDvyfMNHgHD8xPHX2huRpaCpHuVI4ZyjsYntI4StZM7dWWKd18vm9RsgLm10aSXDamV6PA1o1Qxz6oBXNJODW7ohJWhCH3ikpPBjNOJlm5KVho1NnNM/pNCKKwjLNSjxPczzOSAuDUpLqkEQ+zjlCXzPLCn5w94gbG23+6hsX6TYinIP+OCPNDdpTrHdqrHVqp471x133HwdjLbd2h9w7mDBNCxyyJ7rWqfHKxS+H+/3W7og7eyNW28kTofSzrOS97QH1KODa2vnP2znOcE48f1GxflFijB7dFfe4rQLkr78MF69/enh6EMLGRfnzvOgsCeH98B0JR4/r8lt1PpXnvvmVZ++GflkxHcO9W7K7madCFEcncOLg2stnqtnh7pk5qr0kuaV7j2SkPjqR8fzF62ePW2vCBz8SEv+YeloYy4fHM4Yzj2i8jWtt8seDA373T96Ehy8AlzBByvLGt/jn5xfY6fyPuO8fcun4Q+Y2p20sS0lJkE1Rx2P4/7P351GWZftdH/jZe5/xzjfmjJyzKmt49eZZT8NDTwNGDALZxsAybdOYodXt1Tb2siRsg0G45dV40fJqLFt0u2kJY8CmLQkQjawWCJCEkHjze1WvXlVWzhEZ053PPePeu//YJyIjMyOzqrKGV/Xe/a5VKysibtz5xvme7+/3/X5FD91oMMFnqD1sOWeW5nydNbZln43JNk2pMadOo6SgrIlj2OrS8gSN+Q535Dlu7s9Y6UR04oCy7rIGiHyFJ0EI15FdaUckPHk3EufQiyYltCOfQjuzhniIXnk4Ts0q5wppRBFrPY/dMczyqnYuPxwr1YzVasau1zkinYeYqYh2mXGmHC2I5zsAj3olA18QBR5CCDwJsnQZm4EnUVJirCUtqiM1vBkqzq+1Ob3UxFNOPZznJRbX1V5qQ7cRcHV36qpgmwFSuOuJfBfblJeanVHKmaUmRlvSUjOe5/hKEtaj8it3JnQaPsutiIvrHQTOhNcIfZbbEf1WyHI7JPAU7zu/zHCW02kGRL56YIdzmpWcX20d3d8Hnh9reeHWiBduDek0Ak4tNZBCkBYV1/en5JXmY0+sOlL9DUJaVNzcn9FpBA80ITlS73Ftd8q5lYc/zgW+9bAgnt/MWD3lzC3J1B39o/jNb+sxximASjnide4Jp2zeueUMNAAXnoKN0/dGO73TkSbw1c+5fc1u3/1XVS4Qfuu6u8whmTzYdWsIfp3NSZ1Y7XmOZI6HsJY68g1u1J5nD8REbQ0T9scZ/V6PweQqP3X1HzB75RmEfQorNOGZ3+C/2DhDeOlH+OpeyhOhR75n8Wa3WJWGNZvgT2ekRhBGPuymZPM5d/oXqZZWidbP0Xn6Y6QZ7F25zdL+mPbpVVY7Hay1zPKS6bxgOk2ZjaecunODWEumrVPcTJYQUuF5ksgorHXxMX4dBSNycY+jWSIwwimanpJEvqTbCNgZZy6fFPFQpacZBSRFRaAE0zQnKyQCS3AYu/QItGzhqg/FyWskiQxZqmZIazAPS25Y4O2Bde70wxzXw1c2kI60eMq9oVqtkCTXGGPxfeWaiXBGHbA0PUW3EdCJQ0ZzVzkp6lWQduQzTgq0May2Q16+MyH2JVI4IjlLS7QxVNqddI1mOQeznFJrDqYZUaBYbsWEvkdlLEoIhBWMkoJW6LHUjjg8NdfG1GP9grVuzHI74tRSk+1hQrN/7wn3ZF7gScHZ5YevHo3nBVd3J/Rb4T3KZhx4bPab3B4kbA3n31A1cZqWzPKSzf7JkXft2Gc4K2qyv8jbXcDhbSGeP/VTP8Vf/st/me3tbZ577jl+8id/ku/8zu98O256ASmdAvdmo6pg5xZs3XAkTUo3mj911oXBL6/V2TaPcNe/k7F90zUmrZ0GrAvGr8raiX8OkjGMD5wjfzJCr27A+mlUd8k97iCEPHeKZppAUZAppxiq+ZxYeQjPc2YtbciR7E9SqkDzf519lts3n0GV593+2qnP8/tEwuqpP8SFTz2DNpaXhtu0I5/G5gbVZI3+K5+FqqKUCh02CFshVTZnbiTtfIrNI4bnLiOiBhsReJtd8muaW6OMcqKZpoWrB8zmnM32aeuUvs0Idq7Ty0bMki72qfezv9lje5DQiHwETpnMCqeCHv5njIutOdxBcxWBikbgHPKZdqN2cArnoS5ZZ8xTGV1XbRqUhMqTVNo+UiE7hIuWfzgEFiMk9pGXWuDtgMFVVx4XphWOdBoDaaVpRh4bvSZKSYazjLTQZKWzuoe+R+BZVtoRFji70iQtNKMkZ1648fgsr1jpRLRjn7x0mbEWQZKXzLOSrNLEoU+/EZBrw+445ZWdCaru0VxqRMSBO4kpKvd+POyw0PedOR0qsab+vpKC951fotKGrWFCUPfOZ0VF6CueO7vEWjfmYTiY5qSFvifi7O5tCeJAcXN/9s4YY7/aB2+BBY7hLSeef+fv/B3+g//gP+Cnfuqn+PZv/3Z++qd/mt/1u34Xzz//POfOnXurb36BtwJVBS9+0Y3xg9Apd7pyUUK7Wy6bsr/y2luG3mmoKpdz2mi7fdXtm448UssyfuDUzAtPMykhmZbsii56aGmlY1Y7Eb2lFcTNqyAURZJwcOUaA+uTqoA4m9EvPXovv0gjCsAYUmP5GW+fr+y/F3/+IRRQrLzMd0XXOdX+15kHLV4YFvhf3eITl9dYaUf8s+e32ZtkLCeCz8w0kYlYyqb0ihRPtMi9gFnco1skTPwzpMunAbcbN9bStQrtDSkbHdJSY8uCS8kODZsx92PaUcRBex3thVyoEtKrz/PBSx9kZzSnqDRLrYgqsVhbEQUeSVbVSih4UuIpganzF4eznKyojmJxjrfNCDjK4bRAWpgj5VRYyEvz0F3A+zGSMaVQhKYklw/uv7VMztfCjQfG8Au8Pbg/6N/W34sCxVIrcPvDFpSQxIELZ7+41iYOPPZnIeOkxFiDEILQV8yzkp1JSuR7SCnoNhzBDH3FhbU2m/0G2lpuH8x58fYArS2BhKp2xq91Y5ZaIaHvuaiw0tAIPIrS0Iw99mcp41QS+E5ClVIihaDbCCirexM6kvzu3ughOnHAJ55aZ2c0Z2c0p9SW3lqbjdrx/ShUxvAoT46vJEWl72k4e7vRiX1aoc80c5mk92Oalu4y74Bd1AXeOXjLiedf+St/hT/+x/84/96/9+8B8JM/+ZP80i/9Ev/df/ff8RM/8RNv9c0v8FZg55Yjnf3Ve2OVmh3nan/pq/Dhb3+4Cemdjqp0LUpV6Uin0U41lsq589MU9u5wsLXNv2w9SU/16M6nmG7E/iRlMM04029yutGkevErpHlJ0ZizJMHDkje7TKyHGA/Q62v89e6En98+gz9+Bh8oOtt8vPN5LjR+iGj1d7pwbG0QAqrK8Bsv3iHJK0ZJgRDQoOCO32PiNTgtU876JSIG/JA8NSSdDaq4ja0NUcMkZzepiJdO07/1NcZVAxD0dUqzShkFTdZszkD2EHGDrNCMuks0x3tsmilnV5p86fqQ3XEKFnzPjc2VAlWP4EttMFYSBYrIc/uZeemyDYWA0BMUZR2LUz/toafIKk11jGW+VsJ5iKFqsuV1uVAecEd0KIV7DwprWdEzEhlw2++9wTfIAo+D2Jfo+owi8CWhrzDGUhnL6X6D959fodsI2JvMKStLFHo0Ao9+K8BXiv1ZRlFpplmJEoJm5NNtBEjpsjZf3h4jELTjgMunupxdaXHrYMY0LWmEHk+d7rE1SpnNS7otn6VWSCe++/drlpdsLjVphIrnbw6JQ484UCR5xSy1dJsBZ1eatbFO3kP2tLEMpjmX1tt04nsJWOQrzq+2Ob96XwXxqyD03EqLsfbESKKs0Gz0G99Qd3sUeJxbafHVmwNCXxHdZy5KC817zvQX+50L3IO3lBkURcFnP/tZfvRHf/Se73//938/v/Ebv/HA5fM8J8/zo68nk8lbefcWeBwY4+ov/fDBLE8hnMFouOeC4lc2vjH38Y3iMEJq64ZzrPeW7iZQCwlRTCkVe1euYd9znvjSZRqvfImonBI3u6SV4c7OkKXJgMoL2Y9WiFttrCdJwibNvVt4UZP/5XTIL6QS9bWP4QNlPObZ3j/jT2bn+af9P0bYbh0dcNK8ohn5nFpq8OsvbJOVho1+g6oyeKl0OYGNJq/omL0o4NxSg8trLQ725iivQByLztqfpAgE241VvN6I0/kBw0rRLyc0hMbXc5KwyXXZIUpyQqWYFZoyN+y/cIX2uee4vNHla1sj5mVFS3h0Gj5FWeF7isoYlBZUpasZLI1F2Lt5jM6cbu/J3dTGje2NeWO1l1YIvhJtIrFsVi7DUyNQWMYy4ivRacbqMSpYv8XwKMf5a8X9LUbWWnxP4UtoxgHGWOZVidHQigKGSc56P+aDF1ePVLy81BzMcpKsYm+cEQcendgjKw1JVrIzcjFFUejR9UL6TZ9OI2RrmPDF6wecWW7y5MbdVaPveHqDX31+i91RxkbPjbArrRnNC6QQXFxvM04KVjoR2lqW2xGn+x5RpKgq7SpsrXDqZaWZpAVl5fJsN/oNnjndv/9peGysdWPaccAoyVlq3auO5qVGW8uZd0AG6OXNLllZcX1vhqnjlMpK4ynJM6d7nHudhHuBb368pcRzf38frTXr6/dG6Kyvr3Pnzp0HLv8TP/ET/IW/8Bfeyru0wBtFVcI8cSal6dgZi4Rw+ZxB5Eibtc48826FUk7dvPZ1R65nE/f4mh33uOcz5lGXvCjZkBl5b53xhedobb1CNNolBoqdbVKbsnP6feSdJapAYYXEyxJ+a/4y/60fom9+HAVoL+fU5q/zo2aZovowiS8RWqOks1GkhaY0hnPdNklekVWGrKyIKskoKdiI2zRinzJQJFqS5iXX9hM2l1s0Y598fx9x/jIIgTaWea5RSjAuQa1fZjLp0R5usWorcgPX/D4zv0NlA3RaklAymuc0kzmZzZimJd1mwJMbzpRUVE6NLStNJ/a5sZ+gtaWylqrUrorwcHReP8X3k8vDGKY3A5kM+FfxeZZ1wlKVoDAkMmTHa5PJN6nB6pscb5h04tYnlHW5m4dd6eD6Ayptj6oshYBx6tzjB5OMlXaMEIJJWvDKzoQXb49QAnqtyIXHWwkIkqJif5LjK7dveTDJMMay1Appxz4H05xGoDBrHWQ9sz6z0uLbn17nl790m/1ZRl5qqEfnz5zuYSzMspLTS02EkPiey7BVUqKNYXeSstSK+MRT67VrW9MIPZ453eP0UvNNdZg3Qo/3nOnxhWsHbA/ntborSLKSeVFxab3DqYeYet5O+ErygQsrnFlucWc0JyvcSfJ6t8FSO1wEyC/wAN6WWej9o4CH7aT82I/9GH/mz/yZo68nkwlnz76OOJ8F3hpYC5ORUzGz1GV7zib1Ul5tSQ0jZyha3XRfv1v3O611hHNny43Ys3lNpFPnTm+2IG4x668j9sfI2kiQLW+Sd1YIpwNElRNkJduex7y5RMPzsFJyo9jhp6dXmAy+A2mVc6qf/i3+VNTndPzdZMaSZxnp3h7T2ZzSjzDWEvqKcystVrsRe+MMrMUY54w1FnZlgy3Roj3YYSg6lMZCUvAvXtzhw6s+lR9wU3aIstIduIqS2bzAYjnIYT9YYT+KOVtGPF3dZMvrEuIhtEFKRV5q5klFx5S01teQ7YisrFx1YOV24pKsZJ5rJklBmlcoKY6ikfSxDnX5OpS0I9PRq7xePnV+6DEnuxGSPa/NnrdQWx4HrhLg8XGYT2mxR9FagZKUxuChoA5/b0c+pt7jvXmQMC8rdxKjLTf3Z9w8mGGMpRX53BnN8aRkvRdjrdsDttYwL1x6ghRu5/H2cE4r9fCV5Pp+wvnVlPXeXYJ2cb3LJy+X3DyYcXmzR+x7rPdiPCn54vUDZ1zyFGdWWi54fu6C27FQlIbTS00+877T+Eoe5dm+VePuc6ttAl9xbXfKwTTDWEsr9HnmdJ/zq61XDZ5/u6CkYK0bP9IstcACh3hLiefKygpKqQfUzd3d3QdUUIAwDAnDReTCOwpVBVdegNtX3di5LFy25WziopMOm5Gy1I3g54kLiT8enVSVLly9yJ2a2Ftx0U7vRAz3nUmqt+QanEYDZ5yqtFNxlUd56T2MJ5ZJaTFGERiNMAbr+WRLG2AMJnqZ0JMoJTjIR/y/xl/l9u0PocpPOIPFxhf4wWyI2nuWtB2SKdd5HuqKIggJopBT/QZR4NFtBjRqJUUpZ4xQUrAzTgk8d+D5DbPC5WLKarWPUR7S8wgPxlwp27Te+0HWzp9hb5yirWW90yDJKpqBR6Gde1woxXa0zJn8gH45Y+Z3kcAkLQFY1glVo4XputdbCIEUksFsTtCNMdbt6k3TyrW1HnP8Hjf/vh4l7bCR5kRYy0Y14Ww5oK9TAPa8Frf8/oJsvgFIIPTrHd36yX9YQ9SjcGgcOzSPuXALiYetVTCYF5pSG7JSo+eGylhG84wbu1PyWv6OA49m5NFvhoS+YjwveGl7RJpXaGPJSkNlDJl0kV1x4FFUhvG8oBX6aF2wP83uIZ4A/XZUJy14rLRdT3qlNfuTlL1JRjvy0dbSaQRs9BtEvjM6jecFz5zuHWVyeuqtV/M2eg3WuzHzwpn3Il8tdiYXeFfjLSWeQRDwkY98hF/+5V/mD/yBP3D0/V/+5V/mB3/wB9/Km17gzcKNlx0RO2zY2b7hmpAELqvT993XUQxF6r739PugUe8e7W074joZ4Vzh1rnFz11yOZivdsY+mzhnucVFE3V6b23d4e6WI8pLay4eqijcY7FgMBzsDHjx6ztMZ3O2yoDis1/mskrZ7EWodod0eZN5b42p32JZHPDX0i/ypTvP4c8/hQLK5Sv8a+Il/o3rPp9tXWTsy6MDWiOIWRIZ5tw5bNUgKyvOr7aPxoTWWsrK0A4D9rI5aV7h1RFNYxMx6zzJUjbmlJmyFPvM2x2K/jppEvFH+02eO7uEsZbBLOPOr89daPy8YJaXtCKPgzLi+cZZnpvfZG1+QOVHCCHoyBITN3mld562DWhay2hWgIBuI2SQOOU1qLMTDbx+pnICHnoV1nK52OXZfBthYaZChIULxT6nqxFfjM5w038XZca+g2Bw6uNxwv+4L+Uh6bT1lSRZgack07SsTTP1SY8UgKDSBims2wvWGk9KlBTMs4r9acZSK6SoNKOkoNSGQAmMMei6uD3FRW41Qx9TQmmcEr43SY+USXD7xcLCJ55aY5qV7Awd2dwdz9mbZCR5SeBJdkYpd0YpzdDjPWf7rPciR/wCj9sHCaU2hL46Cox/KyGEoBkunOELfHPgLR+1/5k/82f4o3/0j/LRj36Ub/u2b+Ov/bW/xo0bN/jTf/pPv9U3vcAbRZ7B7esuuzJuuHnpaOAc3t2e+9netlMEwRmOesFdtXOwB1/9vPv58pprUrLGkckXv+zG8Q/rfS9y14C0c/vuvqgfuFD8J99z1IBkrWWalZSVwfck7ch/Y2Ov0eBu0PvSGiQzp4IGIbfGOZPdEUFQ0lg6xYYoyfdvsO3HpJXhaV3SHu4xipb5FT7Lr985gz/+jtqpfocPLb3Ep2bv4WJ2iaE6wC9STnfbhJEknU7Q6T7FqQ04c4nNicvHvD1M8JWLcMlLTTv2eeJUm+u7EyyWcZKTly73MkcwUj2ueX1iT7GiYt7b67M3Svna1pDved8ZwI3oVzsRReUMGq4Fxu1pjlvLfKXR4FQ54dnYHeBvyxaDxjI3c8Xq/szF2OQVzVDhyYB5XlKUhrysHv95PwEPIzxLOuHpfIdEhMy8u6aLqYro64T3ZNsMVJNELqYnj4M3adUWuPsaKgGhrygqzXCWEwWKdhygTUXgCbLSfX6lrCtSc/e7gS/JS0NaVBxMXVOOwLnIc3NXQZd1EH1euJ2OwJNI65T3ojRY64ImD0Pel9oRT6x3CH3FMMm5PUi4eTCl13QNPEoIGqFHZQyTtOAL1/Z5aqPLarfBV64fMM3KIyW314jcjuc7wOizwALvBrzlxPPf+rf+LQ4ODviLf/Evsr29zXvf+17+4T/8h5w/f/6tvukF3igmI0hnjuzBYUGycw2EMZy5CLMRbJxzimej5dqKDvc+b19zVZNrm3evU0inkBrj+s03zjhCeRxGw4tfcr/fXXKjeXDj/NvXnCL53o8yyA0vb0/YGc+du9uTrHcbXD7Vpd96TNLheZDWh97DJqZ2l9n2FnvDGQ0lKTfPo4Skr+B2q0+ZllybVehAccP/Kr8w28Db//iRU/39p7/Ev22fZWfnPLEesh932b70FEEyZl2myPkEpSTXG+usnn0PXtxi2eQYC+8502Nv4na7+s2QtW7ML372mssKFK52L8lqBQm3N2eFZZ5pdnRKeVXTboQMpnfTIoQQtCKf9V6jjjZSeJ5ga5BQVBYtfG6YDnkvJi0rRkmOKARZVTFOcgzOZd9vhe4AL1x/u6ekSwS3jzeefa3YqCYEVOypB0fqQ9ngTDVivZrwSrD6Ft2Dbx68la/TcUSB5OxKi91xSlo649w8rzhM8vQkSKGO1H0lXdJBWVkCT6C1ZTwvqLTLdLUGkKCEy4otNYB1Zr3MfRZXOhFKSuZ5wfYwQdbJFMudkA+cX6HUltuDKUlW8uLWiINJzunlFhbL7jglyd2aiScF+5OMtU5EKwqQsWsOktIR2cEs53NX91B1H/sCCyzwaLwt5qIf/uEf5od/+Iffjpta4M2ENY5AHkYJKQVhWLvaY/d1ELs9zyh2yqYQ7v+zORzsPbw1qd2F/R3XcX5/7NJw343sl9bujWyKYkeCd7cZ3bjJb08DpmnBUisibDll5MbBlFFS8NEnVx6IIHlNWNuE/TvusQvpVNqVDW7MfV5peJzrV4x7p1jZv86stURfSlqRz0uzz/Pfqyb29nfh4ZzqZ59+kZ/46O9lY/o0w61tstxDnjqD6K/TNgHXdiaIyIKpGFewmwmeSARLwlX2teOAC2sdLqzdbSbZHaccTAs2awftS3fGTOcF2jrnsAtjF4T1vtskLZnlFfOsOLqObiOgGfmkecVGr8Fk7n7mSUluKoSStGKFEJa9cUpeagIl6EQBCIHVhrIy3BnO3fhPWPKiqptb6rcOTuUy9s0nNj2TkvGQsaMQlELR0vnJP1/gHhy+NicZud6owejoeiQIBGleUWmL1gZPSqx1O5yecmkLnuCoWUhKRWlcOHrk+2hlyJKCrKqwxiKlQNSlA/JYBJcGp3QaS6AUjcjjAxdXeM9ZN4XpxAHdZsDOMOXlO2NmWYmnJF++MWB/mtKKfda7MWeXW8zzirLSCCnwPUmSVkShuufvipKS1U7M9nDO1Z0J6934G5qrucAC7wa8SxO+F3hb0Gg7t3qauNG2kC40/rA+Ms8cGQxqxXK4D52+I6J55pRL9ZC3mFSO1OoTDm2DPUf87s8JBVAeVknuvPQK0+6lOvbE/aFvhJI4aHJ7mPDy9oSPPRm+/oPA6obLIt2/4x5rHbqepxmdMmG6dp5K+QhrsUIyTV7kZ4IZyeRTyLFzqrfPf5EfP32R93znf3Sk5pozc/Y7d1hqR8SeopMWeJ5iiGCcufDpUhuCgxl3RnNKbfj+95954O4Nk5zAU0zTAoN1/dWec/NKAao2HTRCn9BTlFpTVoZhUrA3SVluRzRCj3MrbZ6/OaDbDIg8jyu7E9qNACkl4zQnzWGU5Eej+DiM6DUDPKXIyqo2EuVYHGFwcUj3vpbaOhf7wzrZHxclEvUISuRZTbXoYX9dOKnx8I2+bEfRWQaSXCOVU8utdcYiCRhtaTcDAiWQ0lWjukICwTw3aGtJ8sopm8a93wWCRujMPtOsvOedIAClBEoICm2IDHz44iqXN7vcOki4sT/l5tcSru5O6DVCLq636TVDru74DGaKUZIjhVMujzfxDGc5s6Ki/5C+8V4zYH+aMc3KBwLkF1hggXuxIJ4LPByttotHunnFkUDlOVI2m8DubbeHeeEpp4AmE0dOLz93N8szipzyeRKBzDNnTIpOUCXL8pFxTJmWTCYJy2eiB4ilEIKlZsTOeP54B4G4Cc9+CL7+ZReEX68NNMs5O81VxNoTtOcj8vw2fz3+OndG344qYyRgT32VH3tmk++2H3P3/xj5CUIPIQRX7kw4s9ykEXostQK+eH1AUVZ4nmSjF7PWiTmY5VgLO+OMeV7dU8FXaXMUeF2UTnlUUiKlriNsLL6SKCGYFyVprvE9yc2DGb/ypducX21xeqlJ4Emakced4ZxCV2RFRZaXCCnwpHQB0EIeVREqAUVlURIi3+P0ksd47jGY5jSaIcYW91QIHq/EfFwcf2WPX82O1+VcOUBag7mPYPpWY5AceK3Hv+FvUdz/Ur1R4nlcTZVSOAOakpRSYzQIKdBYdKWRSiKFO3lpKJ+80CghSLOSqak9iFYghTjK1FT1exVrMLWTSQq33xmHLk5puR2AsDx/c8CLW2OUFEcKf1ZWvLQ15uJ6h34rgt0pYX1Sd+iiB/eZ08bQivyHusk9KY+I8QILLPBoLIjnAo/GE8+4Pc2dLafe+b5TQbvL4Htur9NaOH8ZTp2Dbt3c4QeweR5e+KK7jHdsNGqNywRdP+MU0vvRaDlF9SHQWUrq9wkf4iQNfadcFKWBx0lt6vbhQ59yCm46AyFplj63P7fDqZ2r/G/6H/M1+3H8230UUC1f5YPRmD+x/mGeafYcKb/0DHgelTZ89eaAL98YcG1nwu4k40vXDljrxQSeYDRLySuDpyRe3QO91I44t9pinBRsD+c8sXF31F5Vhv1ZzmonYpqV7I2docerMwW1sXjS1f9pYwl8yUo7ohn6xIHis1f2+LWv3WGj1yAK3PMnpbuMkoLtUUqlDd1mSCNUbI/mbgdUCXwl6DR8lutR47Vd14JUlhXG2iMXs+Qu6Xicw/Dh7x+uDtyvbd7xOux4XU5VY/a8NkVdixmZklU95Ya/xJ5aEM83isPX4Q0rnwLq1C+y0rj9TFxskyclRgiyvKTS7sRmMDUICavdiDSvMIAvFUhLlrt1nrQoyUtTk1rpskLrfeVG5LPUDIkDxWon5s4wZTDL6TdDPCW5fZDQb4XEvsckLbixP+PcSoNuHDDLnWkoKzWBJ8krwyjJjmKV7j8RPMS8qAh9757KyAUWWOBkLIjnAo9G1ID3fhTWt+86zPsr8OFPwdKKy7dU6kGDEDjiORrAnZtuJzSKnZo5nzrl9IlnTo5GWlmHqAnTkTMiHcd8hgwCingNU2niE5pCisqpfIcZlyfCGBcKD+6+3R/r5Hlu7F5j9cbLzJOf5Wcm7yUY/U5nHOrc4X1LN/nwwQU2WxucX2q4rvpmBzbOYq3lC1f3+Sdf3SIv3X1a78bsjFO+dOMAgaATKTb7HTzPEcfAU1xca9OMfPJSszVM7iGeuTaEniT0PbqNEF9KZmlJZSyR74wW3UZIVrhxuBKCrDBIKZimJWmpKSuNryRnl1tkRcXtQcL2aM5qJ6ITe4TdGGEtk9SR90pblppubWGYFCgpmaQ5u5MUJQS+r+g2AsZJTqVBKqd3VvrhT/+j4Owmbl8PcIaR46+v9PhCdIbn8i3Wqym+dWpvITxeCVb4arj5gBK6wOvHm+VuNxZKY/GspdQuUD5U0p0YBpIAixCSypSAM6g1lYexFiEF3cijHQdYa7k9mBN6Et9TDGc5xlqUsS4D15dEvs/mcoONXpO0KFFScDB1qRiN0KOo9D1rBe3I52CWow08d26Jr1wfMJznDKYZRWXqAgePj15axfMEtw4SIr95ZIICp4iO5wXPne2/qc1FCyzwzYrFp2SBV8eherl5QhLBo95BQQjPfdhFKW3dcERPeXD5vXDqrFM2T0Kr40jp17/sdi2btXs5mYE1xJefoa2XuD2cc3rpwTswmOacWWnRjk8woBjjsjq3rsFk7L7X7rrHtn76QQK6s8XP/up/w/97uI6/9zsJgDKe0Dl7mx8anuH8wTqn4ownexHx9MAR6iffA+0u4yTnX768yzDJ8aRknrtYF2stncgnKzVR4HNpo4Oo3bkH05y9SUYz8lFSUh3bgbXWxSddWu+4fbK0oN8KOb3c5OruFGMhqvc6i0rjeS4HUVvDPC+5sjNhtRsh8DmYZSgJ28M5d4Yps3mJMc7B2xWSqtKUpaEsNWmpsca6cG5j2B4kro9dSJCSsjL0GiFVZRjPnXIlxYNK2WtqIqp/fpxonsRfZyrit+KLLOmEtsmwCMYqZiTjtzbndYHHgjYwy3QdqyQJfYW20I4COrFHqS2VCam0xWgXrTTN3AmVyg1pkZFXLtvTWFhvR0icMukK1CyNwOfyZo/VTkSlDbmAwPec37EmhJ6SNELFdF4R+W41RwBFZbiw1kYJeOnOhOWWG7UvtSIub3a5fKpLVrqIs1uDhHbsO0W01Myyis2lBpfWO498DhZYYAGHBfF8J6Iq4WDXmWyq0hGjlQ1HyN5t8AOX1Xn6vFM7lefUxFfDmYtOId264Zzv1sLyKpw6h1jb5HJSMJqX3B4kLLdCAt9VOw6mOc3I58mazN2DwzrMKy84gnlIaEcD91ynCVx82hGXwR6//Ct/lf96ImHru/BxTvULH9rmRz72b1CmPkbDilewZjOkNe7+9lePHt+NvRnXdiZoa2kEbgxXaE1WaiQCJSTTtKCyFl+4/bVm6HEwy9hcapDmFZv9mFGSO9OFcgfJThyw0o44mGWOZC+3UEKyNUwYzYt6980ZLDwl2Vxq0IkCbg4SWpFH6CnujObc3E9Iy5Ikq4hCj6ysMMYyy0saoUegnLKUa8M8r9DGtctUlUEqSeBxlIM4mOX4niSsx5OHq25HY3Nx12h0GP30RmGF4MBrccBirP5uga5ff09KWqFHJw5QQtBpuMzMg2nGKKuocouunDrqxy7nMy81RtU7zJ4grFdFAt+Zktbrhh9rLcNZjpSCS6stCm2OGrikEKx2YkbJmKysiHzPJTBIgbUWKSXf/d7TPL3ZBQStyDsirYGn+NiTa9w4mHFrPyEvDZHvcflUl7PLrYXaucACrxGLT8o7DfMEvvZ52NtxR2ulXHZl/LJT0k5f+Ebfw8eDVBC+jv0nIVx00sqGMzFZ6xTUWpFcbkd89IlVXt4esTfJKGY5gZKcXm5y+VSX5fYJpqXJ0NV9Nlp3SSe4dYL5zJHSIORLv/W/8OfG+yS373aq9567xo9/7w/xdPtBp/nDcGc8Z5yWbPRiwkOyXUfJBL6imLsR32Casd51+X+BJ5nlFcNZTlZq7owzbu67lhTfk6SFJisqntrs0Yx8ziy3HLO7BF+6fsBvvbxH7EvmRUW/GbHRj1npROyMUmZpydWdCQiXS9iOfTqxX5uHXHNMaTRp4cbrgS+xdTtRHCj2JilFafA9AdaQFS4ax1hHRo02WAGBLyireuezdhl5tdO4Mpbq9fRmLvANhSedUl0+4kzh9WaBVsaQFBWdRoCnXM+55wl2BzlZoam0xeLG57O8Yn+ao+qTrrzSCCHIS8NaNyb0FNpapvOcJC+5vjchrwydOOCDl1b4wMVV7ozm/Ksre0ftRcvtiLTQbA0ShkmO1k453RrO2eg3+OCFZZrR3WlJVrjmpEpbQl/x5EaXyxtdqvoz+U7pS19ggXcLFsTznQRj3Hh5744jXMejiCZD1/YTN2HpWygYWwhnZjoBK52I5fY647lr2PGVpNsIHh6htL8DZX7y86cUW8//Kj9y/ZfY3vluVPkcEvAuvcKPfv9n+M7V3/e67/q8KDHG3a9DSCFA1KYZa5EIl7O5Oz2Kb0nyksEsQwhBkhV0myEirxjVkUiTtMRTggtrnaPrKypHSM8sN9hcanBtZ1Y3E1UMZ2P2pll9fzTa1CYgIZz6emjM8CXT1KCNJS0qtHXu9sBTKOnGlEII2pFPkldorUlLgy8lnqcoK+dW9j0XAG612++Twr21rbjb/73AuwMCp/TZSrv0M/vgz49/S+HU7MPvHa5CHjd7lxqsdSscIIgCxXBSkOYVrcgjLSs3HAlErZJbrHUEVQmBJ12era8kT6x3mMwLhkmOBAptWOvEfPiJFT5xeZ3AU2z2nRK6PUxY7cSEvuL0UgNPSm4eTOk2Ay6stTm91GSj1zhysxtruboz4aXtCbOsqJuKBP1myLNn+pzqL8LiF1jgcbAgnu8kjAd38yPvz7/s9J1beufWtxbxfBUIIeg9JFvvAcxn4N1ngioLpl/5Nf5Tc4Uv599NMHROdbNxiz/xfc/xBy/8+49935ZbIY3QZzIv6DUdeQ48QeApxvOCJKtoxz6RJ5nnFdvDGUII3nd+iaVWRFZUdJsRL94euvYi42otp2nJ8zeHVNrSjgMqbdgZpwyTgoNJxv4ko9SGqjLsTeZHNYMIwTSrUMIFd8eBR1qUaONUqLLSLvLGU86JLAQlgqI0TExJvxmSlxVp6cbugSdJc+P2PaVwxVZAVd1LPowFiT2RuCzwzoapayd9JSnquKxDsikFxL4zxWWVe2EN98ZgScE9axfNUJBrgdaGWVoySlzQv5SC2Fe1s11SCU2aV04NlU6Nd6YzQWorhJDsjOeM04Ks0PhK8NzZJZ7a7LqfjVK+enPI+88vEQUeH7q0wldvDNgZp0fX1Qg8fsdzmzx7pn9i1/q13QlfvHZAHN5tKqp03VT0yh4fv7zGaudubEaSl9wZztkazqm0YakVsrnUZKX9YOzbAgt8K2NBPN9JmE1c+89JuZfgRsSDPdC1k3yB1wc/vNsrryuqr/w2P5F9ll8pvotw9AECoOru8vu+Z41//z1/4qhi73Gx3G5wZrnJ1mDOMMlp1lmeldZM5gVSwql+g9NLLcrKsDuZY6zl/EqLwcxlkH725V22hnM30hNuD81TztSAtZxeanBnnDLPS2QdoySF67tOy4pZWroKS+mCiRqB22nLSlOP8yuKyiAFlNocxdLEgee2GoREyTo/1BiEkujSqV9pPRZFOPNIHal4ZAY6robZt6DBaIG3Hsa6/zzJPa1UEqeQ+55CGou1mlxbLOAJd4KhpFPVjXURX72Gj6c8VOUUTVuHNQkhEbh9zqQoKUqNp1wag8Fdh+dJQk+R1V3snpIIBGXl6jfjwCPJS3bGGZc3u7Sszys7E1Y7EWeWW3TigE88tc5g6kby7oQ1eGjOb1FprtyZEgXqntB4T0nWujG3BwlXd6ZHpHI4y/n81X0OphlR4MLtX96ecG13xrNnelw+1V2QzwUWqLEgnu8q1H+43uwqmG8VLK/B9a9jv/wv+R/Gv8nf9D9GsPuHCYEqnvCJJ2/y5z75h4g2zr0pN7fWiXlyo0sz9NkazhnXwdV5qem3AgJP0gh8DqYZSgpO9Zs0I4+9aU5ZGQ6mc24OZnQbIZGnEDXxTIuKWVEySUvaoc9nD/ZdZFJNOC2QF5p5WmEtSE8QKQ9tNWHgY7QmLQqSaVkroYCFqiaP2mjasU+vETpjxrxACOf8bYaKVLjHcFiHKS0YbD2+v6tqHs/yXLxj3104PGmwgDEGK8Q9gfBKudiCea7x6zWMUmundNcqpzE4Qgk0Q49G6DPNKiJf4SlJ6HlYa8hLg7aGrNDEoQcWylrdbwUeUaDq3U+nsju1UrkUBuUiyox1IUnDJOdgkrHea2CN5cb+zO1B4wjsSidihVev0h3OciZpwUbv5CDgXjNgb5K6/E5P8aXrB4ySnNPLTbf+AtAKmaQFL9wa0m0ErC963BdYAFgQz3cWmm03Yi+Lk3Mx0xlsXnhtrvAF7oUxcOV5/uFX/y7/t94zyOG/TYBzqj/xzDX+L+E6y6c/DSubLraoHoUj3EGmGT6kG/wRWGqHPLHRoTKGjX5MXhlm84JruzPiwOPcWov1TuwCspVrEjLGcn1virGWa7szsKC1ZaZLPCkIfeVUJllxZzTn73/uOld3p3Rin0pbGqGPtbCdJO5gLMBUljCSBJ5H6Cv2JiXWuupBJQVR4KGNc64bA0pZ1xAjXBd1ZSxZqelEijjwuDNKj0jnYcC7sIek9c192Rb4xuGQfFYGqlruFDgl8xChL90OJgKlBJ6weMJ1rx8SV18K4shnXmgXXVQawkDVhNGNrrU2rv7SOCOatgLlWYy15KVT2ytjiTxFr+Gz1A5JCo0vJY3Qp9SaSVqQ5iV7ozmdZgAItkdzTvUbnFlu3bNr/WrQxsWePcw45JqKKrSx7E0yDqYZa934Lums0YkDZmnJrYPZgngusECNBYN5J6G37ExFd245R/fxcfp05Ejpxmt3VS+AU4e/+C/53D/5a/z5/jLZ/I8gE+dUX770dX68v8aT8dOwvgmXniXRlheu77E9nJOXblOxGfqcW23y1Gb/dR28pHB7Z1HgcX13hsgKdOjTin0urLU5u3LCwVBC4Ct0ZdgeztHGuhE49UFcSZRyDUf704yicgdIKXDOW2Nohx6eJ4mswgooK0sUuDxDWddhuo53ha8knhJY60imsobIVyR5HUAvncEDA74vmWXlEamQdURSZe4SlLcTb1azzgL3whOO/JXGcvzd2Y49jHFmtsq45ANj3VpGZSxlpelEAf1WSFlpkqIiLTR5aRjNMkAgpaARelgL47mLPFpqRZzqxVzZmTDNCvpNdzLmCcHeNEMb61zmNRH0pEAbQS8OyUr3Xp7MC/anOZVx6x/xRCEQ9FoB/+z5Ld5zZokPXFg+cZfzJMSBh68UWVGdGJM0r78f+YqdUerWCR7yt6FZh9Qbax8gpgss8K2IBfF8J0FKeOq9zp2xf8d9rZRTQMMYnnqfGxd/o2B0ncWp7q3AfKfihS9w8x/9ND/SE+zkP4B303Wqh0/e5se+/eN8W/gRd7lmB1ptikrz+Zd32R7OWW5FrHZce0qSlTx/a0RZWd5/Yfl1HTw8JXl6s8eF1TaTtCAvNV+4uo+n5IkkNslKmoHHzLrw7MoYWspDG8u8rBhOc6ywxL6HUoLIFwxmhoOpG+PP84p5XjlHvpJIIKpVqbKyR7WcCJeT43uSRuihfQWUVFpQGWjFipV2TBhIkrRkD0uSVqSFc/d6h+pm7TKuzNtL/6S76cXWyVsE16LlsjbneUUz8uk2Q+6M5qSZ28EEKCtNN/ZcpaoMaEYeG70mZ1daZGXF1iDh2u7U5WhaQyv0Obfa5mCWMS/cDnIUeKRFRaXdz31PUWpDtxng1/FiWEuSVaRFSVoImrHPSqfBnWHKwSxjMs/JywptXdFBOwqYZSVprtkazF37Viu6pwXsUeg1A9Z7MbcOZmwuNe/5zFfaME1L3nd+icBTJ5YlHIexFn/RpLXAAkdYEM93Ghot+MDHXfXiwbEA+dWNB+sj3y6UhVNhj9qHlGv52TgHrfar//7bjSsvMP77/0/+bHuf5833Edzquzf6qTv8qe97Hz90/nef+Gvbwznbwzmneo0j9UIKQTsO8JTk+t6MsyutkzNCj2EyL5jnFUJAr+kaUEJfseq7fbFpVvLl6wMX0n5Mgam0YZgUnO43SPKKS2ttbg8ShknhjD3W8cW8MGRlThx47M8yZlmFkrViKQR5WSGFpNQuEP5Ur0kUKHRNZEttkFKy2gnpNyM8KZBKME5ybu0nLs9TG/JKk1eaoqzwPUVaFk7VlHdH69SmECXeXse6cTe9wFsAXZuJQl+RlRZtIMk008ytfijpRukCR1B3Jxnd2OfCeofRrAABZeXC1S+td+nEAV+8PiD0XcvVaF4wSQqSosJXgqrSdeC7G2ErKek1A6LAo9QGckfePE+AULTjgKw0TOYlceCxPUrISn1ElpuhC6PvNUMC31XK+kpy5c6Y86uthyqTxyGE4JnTPeZ5xe0D11TkK0lWapK84txyk4trjsR2GyF+bfgLT+hqn2Ul7znTX6idCyxQY0E834nwA9g46/77RqMs4PnPw/YNF7QeRo4Mv/y8yxt97iPQ6X2j76XDzVcof+6v85eCF/mn6nsJtz7j9jh7B/zQ95zi//Ds//6RztLbg4RAqRMPTHHgsT/N2J+kDyWeSV7ytVtDtkdzskIfZV5eWG/zxHoXVYcaPrHeYTovubE/xVeuPrCoHNE7vdQg8j2yUnNxo0OSV+RVha8UlYWyrghUVtCOAmcekpAVhsCHQCnySlMZN/82wHCekVUe1lryUlNqQytWNAKfVuQdufdNZInCjMgqAuXG8IEnmcwLZlnpYmjqyCQluOtmXyiP70ocrm8cTx84VLN9KUlzjRR1lqZwTUIIQaAEgedRGkt1GMHlK7LSME5L/HFGXmrakc9SKyKvNI1A0Yg8dscpB9OUee6Mb5UAaw2NyGetE7MzTtkezWlFHq3QJ8lKVtsxvi/YG7v+9G4jIC0rbg0SOrGPtRZjLJWxNGoTXuwrOs0Qa13JQV5q9iapq9089vnWxpCVGiXEAyP1XjPk45fXuLE/49bBjLwyxIHHM6d7nFluHZHMpXbIZr/J9b0p67346GTSGMv+NKMV+Zxear7lr+cCC7xbsCCeCzwat687pXN1497xeqsDe9uufvIDn3iw4/ztxJ1b2F/4WX46/U3+VuPTRDv/Tu1Un/Lt3+Xzn37kjxDen4t6AvJS43sPfxxKCMqHyHpZqfncK/vcGc7pNgKMB7uTOdd2J3zp+gEfeWKV73j2VE3mFB+6tEK/FfLCrQH7k4w4VKx2IrSxfPHaPjcPEpbaIdoa4sBHAMN5gZSuBtP3FCudkN1xRux7FJUbgVfWoITA96U7GGtDkmmSzMXQHPLueVayM5pTGRe4LSVM0pKy1DSigPV+zFIzZGeckuQlSgqy8m7VpXM7173qC9L5rsTx1IG7O8Qu0B3Aq81naV4h6x1GIaDQltgXtBo+SVFhjaU0luE0qxVHt195MMsZzQsGs5wkr0hLjSeFez/XhLbU7j1qjEUIwXov4tpOxSyrmBcVeWVoRYp55ois70tW2zF5pbl9MCMrKpZbMVnkcj/XuhGB5xF4EhBOMcVlkVbGouoPQKkNN/dnXN+butUUIVjrxZxfabPSuXti2Yp83nOmz1OnulSmruuU9568yjp712DZPkio6l1OYy3dRsD7zy2/9qzhBRb4FsCCeC7wcFSlUzobzQd3OoWE3goMdl2rUm/57b9/Bzvw9/8mf2/7V/hvNj6Gt/uniKZgvJynPjnnv/zUD9ELX7uTtNMIGMymwIMHCWst2rj9sZOwPUi4M5yz0om4vjdlf5rhK0UUeCRpxT9/fpuiNFxcb5MVmr1pxsE0xVqIAsXBJOdrt0b02yFr7Zg4yChLTV4Z2rGPNtbFGUU+ae7c9oFSGGPxpKATByRZhYfAj3w6jYDRLGM0N3UXtRud+kq6MXqpSfISPTIkaYkFxvMCYyyhtdw+mPPS1hhT725qXI3hcTFYsiCd3yyoC7Bqk5DB9xTN0MMYQwJUlSXy3Y6FMZZxVlDVnwlfSSJPYhEEnhtHRwhXNTnLjtIRBNBtRgySHCwst2OUFAyTjGbkc3qpQakNB5OcMFDkZUVeagIlaUUevZb7XEoh+NDFFZZbYV2sYJnlJVMl8ZW6Z32lqDRx4CYKK+2IKPCotOFL1/Z5ZXdKHHg0Q7dDfW13ws5wzocurT7QSuQpyaN8SXHg8bEn1jhYyxhMM7S1tCKf9W686HBfYIH7sPhELPBwFDlkKTRbJ/88CJ0RKs/e3vs1HsAv/m1++8Vf5L+49CyF/lN4t5xTffWD+/ylT/8eLrZfvwnrdL/J9b1ZHcbuHAOBp5BSMJ4XNCOf9Yfk+t3YnxEFip1hyv4kY6kVHkWxtEKfq7sTfvWrt3l5p0U78rm2O0VIOLPUZHOpxc44xfcUe+PURR0J4dSe0CMvDb1m4HI6Q6fmCCFIiwqEQNcKi5QuL7EdBwS12/awDtONTAWhEkSeI7LOJSzIKo2xlpV2SDMKGCY5s7RwjTTHSroPd0FtHTWz4JzfHBBAqCTauviiShuMtQRKoC34EgrrIrWUFLVRDca6cK1CUqCkz2a/CcJFGGk9p6zcyUoc+JSlptXw6TUDZxDKq6OdyCjw8D1xtAajpGCpGXJhrYO3M2G5FRIEyrUWFU45/fr2iDsDF5sU+B7bw6SOA7N0m4LQk5Taoo2h0oJm6PPc2SUAtgYJV3enrNX1mYdoRT6745Sv3hyw3A5fswP+EEoK1roxa92T/0YssMACDgviucDDIZUzElUVnFTwYXRd+v02tSjNpvBL/wtXf/t/5UeePctB/Mfwbjinenx5mz/7Pd/Nx1efeOyrX+1G9GKfz1/dp6gMoedMQZHvsdQO+OCFFVrRg25+Yy1FpbHWcjBzO13H8//SsmI8L4gCRVUZitLQbvh04oCDac5kXjGe51TGuWXHSUGvGTLNSrKipNSuUjAv3d7oWjemGftsDxKiecm8dGNJ5QnCwDmC9ycZWVG3NEnqxiRDYi3aVkcH+V4rIi+cnvnsmT5Xd6dM04KiNLXGeReVsfgCR3aNvad/Gx7s7V7gnYnjNZYCt68rpcRaQ6hcpmtWaMbzoh6vC8Q9G6FuJN9p+JSVQWsIPQUCOg2PRtBmf5oxmOUEnlPYPU8SBR5FZWoFMGeaFRRa4UnJOCl4aXsM1n1eAk+x2gnZm/h15aq73XlRkWQlZeV2Rp/c6NKKfHwleP7mgHFa1C1Z7gHGoUcYeHzbU2tcWGtjreXGwYyg/mzfj+V2yPYwZW+ccXp5sZe5wAJvBRbEc4GHI4pdfNOta85tfz+mYxdF1O2/tfcjm8Mv/xyDf/Y/82Pv6fL1tT9EcMM51cXmLv/H730/v/chTvXXg2u7U0ZpQb8Z1vmDlQulLiourrc4v3ayg18KQSvy2Rk580K/de+oflTvuAWe5OvbY6y19FoBnpT0miFXdiauz73hMhCTrGKpFdFrhtweJIzmGUWl6TcDAk+x1A6pKks79jm33GZrmPDi1ghtDLO0Qkq323Zo+JEWpBJHLmSscKNza0iykrw0RIHixa0xo1leExG3wym5b6/TWgQP9l9K3O+83Vme3+p4rEgp5xHCEyDqntNSV4BAC02pLQb3+geeIPIVGZaicskLSrnsTV9JhChJjSX0JaNZTqUNoe8hpazH086hbo37jIS+xBiDryTzvKpP0BzRLasUbZ1bfns4Z6kdsdqJ2K67z5US7v1aGQJPsdFr0m+FeFLy3Nkleo2Qz1/dA9zaTCP0WO/GvPfc0pHaWRnLLK2Ig5NPlg9PGLOyeqzXY4EFFnh1LIjnAo/G6QtwsAv7O9BfdiH21sB04kbsF59+eLf8G0WRw6/+A/Jf+lv8hacFv37+dxPdOu2c6v0Bf/AzZ/gTz/67b0oH8iQtePH2iEbgsXm2idbmqJFkkhb8y5d2UVLw/vMrDxBLgDPLLV7anqC1wRrrZCVAW8PNg4S8qBjULSwWl0l4MMk5s9IiyUqKStOo25GctuSMCb6SbA0l/VbIUitkazDn6s6URuix3I7oNH26rT5FVXHlzoSs1PhKHCk+os4YLCuNlKJWgwxlLVYfdrNbY9kZpxijiQMfX4GRILShOLbIWdUu9vv5pahrE8GNa4+roZI6jlazwJuMx0kTkAq0dq+htAZBHY8kLNa6UfohykrjeZJ2w+ViJplGWUteVBRH8UeW0bygrCx5ZTi/GtBtBGR5SVEZrBVEoUtbuLDWwloojWXrYAbCmdoCzzV3Rb4rP2iEHi/fGbPZa7Bed6PPE5cfGvqKi+sdNvsNvJooBp7k4nqbXtMnLTQffmIVJQRLrdCFz9dQUuB7oi6HOOn5PNxlXuRuLrDAW4UF8Vzg0egtw3s+BC+/4Ajo4UGp0YKn3w9nLr75t1lV8Ou/hPnF/4m/enbC3336dxDvPEME6MaM7/qukB/98B8hUG/eiH9vnJLkFWeWm1hr2R7NuXWQYLFEvse8qPj81QOSXPOhiytH5gNrLUnuFJQLay1uHczYnWSstiOMtexNU6ZpiRACbaDb8BBCUtU5mS9tjTDW0AwD8qpCCeeaPQyXD3znJP7YE6ucX3UjzL1JxmiW43uu372s1wLOrbiQeikEWamZpSV1+RIA4r7ZuBRQVQbfE5SVMxxZwBauf9ta4eowuVfgPCkr3hioMNSro/fezmHF0AJvCt5IY5OSoITECke8LPWoXblW9dK43E4l6uIBAWnhdicDJdG+pRl5dOKAdiMgkJK9acZglpEWmso4EtoMFRZBWLf7GAvNwGOUuKKDvKw4s9JmnpWoukO9Ewf0miGecu/fpaYzD51aavCpZzboNyNmWcmVnQnnVk7eOxdC0I59zq+0TjwhlUJweqnJl64Pjvamj2OWlTQC71WzehdYYIHHx4J4LvDqWNlwDvbhPhSZUz37Ky7T882E0fAv/wn8vb/J3+1t89++5xMENz9OjHOqP/vJjB//1B+gGz7e8v6hcULJByNR5kWFks7gMJ4X3D5IiHx15GLXNiDy3f7bl28c0G8GTLOSV3am7E3maO3UlDPLDW7sJRxMM1dTaQXNUB2N2jtxiDaG7VGB0YZ5qdHaEcftQUIYeGz0Gm68WZPHduxzqu/aYBCCaVoeBcLvTTJe2h5RaMMzZ/oMZzmjec7+JEMpSWnuKjv3E5XAV/RbIcNZzjQtazXUjVOtFWDNax6dH163BA6HlIeE1d739QKvD4fv1MPnLgokxkBRmQeU50fhbt6qpRW5cPZK1/Wn9cmO1obcuiD29X6DUlvSvMSTktVug51RgjaWlU5M6CkGM5fZ6SmJJw3GGPbGc/JGwGonwuCyMpOs4sJKi34r5OtbY5RUnFlqMssrmoFHO/aRSiBxMURZqdlcbtKIPN5/fuWocWh3nHL7YEZR6RPNP0lWcnmz98gpyNnlFluDOVuDhNXaYGSsZZqWTNOCZ88s0Y7fBc1sCyzwLsWCeC7w2uB5LsvzrYC18Llfh1/4WX5NXuMvved96Ot/gOCmwgrDxgcP+Euf/r2caz9eZFNWusy/63t3D1hnlh2ROySWvpKYWqo7mLh+aKUEs7p+sqgM7Uiy3I64vjvl//fl27yyPSYtNWvdmJVOVI8BPS6ut5DCOYKnaYGxoJQbH8ahYpAchhMJ14UtBYGnqLSLsrHAVr3X5nuSduSDgCt3xnzh2gFpUVFUhllasjNJ2TpI8JSg1wjpNUPasU+Sls6Rj8svrGoGeEguQyWIfFefWRmLp8RRB7uxYB4jJ+l+knqUE2m+sTGv72YIuCfCShtIC4PAjcoPq0tf7dXypKP9xkDsKy6sdxgnRe1Ady52re3RjmWgJHlpiTyJHwdOGVWizm91mZ7TzPWjtyKPwFd1mYGg2wjqfU63j7w3zpjMCyzQbYZ89/s2uXmQsN6NeHFrghLcE+pu6rxNKcRR3uchltsR6/0GtwfJPQ1j1loGs5wo8DjzKqagZuTz4UsrPH9ryO44paqzPluRz3PnlnjqVPc1vTYLLLDA42FBPBf4xsFa+Opn4ed/hq9PXuDH3vcko9t/Eu+ac6o3L+/wn33PZ/jw6oXHvom0qPjsK3tsDeY0Q6+uAaz4wrUD7oxSPnJphWbks9KO8ZQkKypGc6cADpK8Vv8cees1A9K84vrelFGS065Hg8MkZzwvOL3U5PRSg61hyhMbbXqNqL4PLktwnlcMk4LpvCD2FKW0WFy2plKSS+st8rLC95yi5SnnZPeV5HOv7LE/cSajojSu6zqvSAtNUWmyEq7sTNjsN+k2giOXvRUSKQyxkkjp4mi0gdJa5oWrAxR13aaU9ii3882GsYtu9ceFqduijm8sHP77aqQzqHdrpRAEvst9bdc1rkq6gHitHbnzlEJZ427PGIqqQgqPZqiO9o8Po75u7E1JihIJlFqSFppG6KHq9IRQySNXfDv2WGkv8Tveu4EQkp2hay/aGc3xpSTT+p583CSvaEQ+nhR4UtKK793RfP/5ZbSx7IxS1+IlBUVlaMU+7z27xFLr1ScxvWbIJ59aZzjLXYC8FPSbIY1wcUhcYIG3GotP2QLfGLz0Ffi5n2Hv1hf4kY9ucHX/3yW45pzqanOf/9P3fpAfOOZULyrN1mDO7cGMrNCuhm65ycYx1eMkXLkzZmswd0aEo8v5dBuW24OEr2+P+dDFFZbaIedX27x4e8jWIGGSlvSbIcp3hDHyFPuTjINpznCWu5F4bW5o4ZMVFbcOZjRCNzYcTAvef34FY9e5uT/DVwJjFAf1ga4V+/TiACUF7chjtROTFpok1ySTjHPLbRCKlXbME6e67I/nPH9zSL8V0Ah90sJQGUtWVGSFI8eDaYYnBdO0YJJVeFJgjMFKicFS1IYKUctllbWUVh+1GR2ag16LgvYwHHfBH2LRq/74OL6qcKhwuqD3B/c8D6ORjD2eRCDqEwpDoDwKY5hnJTf2ZqRlBQZCX+JJSRh4GOvSEJK8ZJZVdWasT1xHIT2x3uVg6iYCgfIIlERKia+cSSkKFc3QRyqJLSpakU+3EbC51GAwLbgzTol8xWon5sr2xJ0IWbdH3Qw9krzCWMtaN2Z/mrHZbz6wb9mKfD5xeY29ccbuJMUYS6fhs9Frvq4RuRSC5XbE8slhFQsssMBbhAXxXODtxfWX4Od+lvRrv8mf/1iX32z8m8TXnVPd9of8oc+c5489+wP37GilRcXnX9lna5AQ+IrAk2wPnfnnwlqL919YOTLjHEdaVNw6SOg1ggfIqZKidoknXD7lsgCfO9tnf5JRaoM2lrSoCJRkqRWy2okZz3Nu7M1oxwGhJ48ctQBR4DHLS7aHCedWWk6ZrDSnl5q0o4DffnkXIR0pKCrNOLFMEpftqURMZaARulYVJSSths9qJ2a5HRL5HrcrS6XdOHRnNGcwzY5URKmgrAxZaRnOMg6swFhTh8oLYt9jlJZ1O41zLRvu5jkeipzK3jWcPC4WaUqvjpPI+ev6fSFQwq1PHN+blcKlC1h9bL/WWKRwDVPTrEAgCaxTv/PCEHoCz1O1uazCAo3AI/IkSa6ZzguUlPSbAc+d67PUCvj8KwdIAYOkAEutVlqu70+ZZ5aLqx1ascfexBUerPXcNGF7lB6dAK60IxqBx429Ga/sTri6M6ER+bTqk7CiqFjrNXjv+aUHDEDgih1OLzcXWZsLLPAuxIJ4LvD2YOs6/MLfQH/un/OTH/b4+Y/8azS2niHGOdU/810t/uMP/+ETnepfuz1yO13HVcum61Z/ZWdKOw54arP3wO+lhRtFr3ZOHr01Qo/xvHAKZOQTeIooULz//DLbwznDJKcZ+TRCH2PcflySV6z3G4SeQFtHEittGKcFB9OcO6OU4Syn34yY55UL4k5ypHQjyLzU5IXGoLHGUlSK5XaEsYaDqQuCf/p0nw+cX76HfBeVRimYF5qdcQbW0gh9ZD1qnGq3NZrkZR1nJMgrt6+X5NqR1Pq6LI6kSHHXCARubCvFGzcBLUxEJ0PicjHz6vGfncqAkG4n11T2HgJ7uMpwGJN1eGJxqGBbDUoYplnpVjS0xlpBSwrX8GMswrqkg8o4FT0OPfrNgNVezMW1LnvjOU+f7rEzThnNC5LCRRyV2tBvhm4fU8BwlqOk4qnNLhdW23zlxoClVnj0+XW97A0XE9YOmecVZ5Zb+J6kFfls9Bps9J3JboEFFvjmwoJ4LvDWYu8O/L3/Efubv8Lfekbz09/xbUQ3Pk4DMF7Bez9R8he//ffTDk/OAp2mJVuD5J6D1iFCX9GMfG7sz7iw1n7A5XpYE6mNPbFnWWtXNXnocLfWja7j0CMKPMpJyvYgqSNnBJ4niX3FuZUWs7RklpYoKdkdp8yLEoHAk4K01ESlU2n3xim51nz8yWW+dnvCMCmwuN51zxNEgRvT708zJJbpvGR/lJIW1dFeHVC3s8i6tcXQirwj04UnXeSSMZBVtu5Pd+TGcnev8n66Y++jiNZly7/hXcwF6byL430/Fo4MXHBvg9BruQ6oUwNMXQQgQByeUNTvhShwTUCldqHsh2YyAE85Y1FeGorKnYxoYUkr7fI2jbtMqd398qSkHbtR+e4o459+9TahJ/nQJZdl24l8nr85pKwMS+2ITuyTFBWbvSal0Tx7eomPPLHC3iRjXjxYrABOuTy32mYwzfi2p9fpNd+iTOAFFljgHYMF8VzgrcHoAP7B34J//o/41TMZ/+XveD9c/R1EN5xT/fQHx/z4d/0eznR6j7yaJC9Ji4qlEw5aAK3IYzgrSIsH41U6jYDldsjBNGO913jwLs5zek0Xdg0cOWhf3h7jK8nljS5FZSgrQ6ENSV5QaYMnBHHgcXVn6pqN8pJG5GOsod8KWe82ePJUh63BnBduDek3A1ytumCpGbBnDMZYpJQUumKSwsEsR9Uk+eU7Y9JK88ELy5xfbeMpSbcZEIc+k7R0jnhrj0xPWVlhjcVXgmMtmSjpchnvhwQaocIlLemjYPfDtpoF3hx40lVJlpWmqg1Cx8MCXq+P61CNdoYaiSdxLUPWEnqu2jJQyjVIaXc5Y93ep/t9l7Sg67MKKRzJ1NqAuPs1gO+51IOdUcZoVrpxunBB7cudiMunelza6LLUjrixP2OWlUyzkiSvkCvw4QurPF3HGt1VX51b/X648HrxyAikBRZY4JsHC+K5wJuL6Rj+0f8M//jv83w34c9++gmmN74f7xWXvdm+vM9//pnP8IG1s6/p6g4jVY4fQAGyonIjw7yqdzIfZExSCC6udziY5hxMM3rNECUFxljG84JKW57Y6N6jpHpKMk1Lzq+08D11D5k9mEGaaa7vTxEI4tBjd5SQlppZXoGAOPBZ70ZQGzR2xyml1pSVZZIWBJ5ESgh9j0pr0tygdenU2zigFSr2Ji5+5vNXDygqw+VTXWJf0o19stxnnlVkpSYrnaJVaI02htLKIzIj5d2R+gOd6gICpaiEoajuvczhM7Hgn28MSoAvXCYqx5qeHic0QAK6/t1A1RFD0lVZSqkpK1dB2W+FYAVJXrrKVI5lqNYnNcY6Zul7sq5PdeN1cCkKAklZaayBsnLq7LxwBQlF5cb0v/3SLmvdBt2GS3VoRe6EaHsw54mNgO953xl6zeDo/ncbAZ1GwHhenOg4n8wL+q2Q0JcMZzlCOIX/UabBBRZY4N2LBfFc4M3BPIFf/l/hl3+ObW/Cj3zHBjd2/iDhFedU9zYP+D9/70f5/tfZqd5tBLSjgGla0GuGaGPZGiTsjFPyUjPNSlqhxxevHvDcuSXWuveGy59eaqIvGr52e8z2MDn6fisK+OCFZc4eMyfYutJyvddgNC+IQ4/Yd0HtwySnrCz9VkilwVrDJM0prSORkS+Ja3PQZ1/Zox0HlJXLRzyY5Mzz0oVsCyhKQ1VpSmMptUVISSggVJJuw/XEe1IyTnM+d2WP3XFKO/Lot0LyynBnNEcbS1UZhBBuDcD3yAp97LFQK6MPPqfauoaWQwf7IaE33K3Y/Faal7+RJqCToHAnPaWxSGF5jEhUF/YOR6TQVyCFdPmd1lJVlpkx9BoBzY7PeOZOakptSauKsr7RuxFM9mj/E+tUTiEEkafQ1u0vYy0Wg5SiNsJZQr/+OcLlydbK5hev7/PxJ9aJ6s5zbQyr3YiPPLF6D+kEN06/uNbmC9cOmMwL2rFfn0y6E8BSG6SAX3vhDrOsRADtOODCWpvzq+0Hyh4WWGCBdzcWxHOBN4Y8g3/89+Ef/c/MyiH/+Sc6fHb2bxK/coYQoD/ij3z3Rf537/mBxxqlhb6rovzS9QM8JRkmOTf2p8SBR+hLlAi4uN5mPC/43Cv7fPKptQf2xM6ttlnvNdifZOSVy8Vc7UREwb1vfwsg4OJqm3lRsTfJuDNK6/BrZ+aZpgWhrzjdbzAvKpZbIYGvaEc+UgoOJinbwxRr4fxai8EsZ5oWCCFJ8oq8ck1FWWmOCElZGua2YuoVSOmcwALBLCsYZBXjeQHCVQ4+e7bPU5s9Xt4eo41FSoHR1rXQmLsj1PvzHu9HpS1KunHw8fidxyFJ3wx4MzNGlcIZdXhwvP5acThWdxFKgjhUIARa26NsWSEEK50YJQVJWlFpiHxFNw4py+xYCxVH5rJDxdVa8D2n8EssnpQY496TRamph/qA2/U01mCQzvEeKrJCc31vQjMKkFLQawQ8vdnj9NLJLvOL6x1KbXjlzoRbB8nRTmoz9GkEHrcHCa0oYLkVYXEtQp97ZZ95XvHc2f5iDL/AAt9EWBDPdztMfZB4u6thqhL+2f8XfvFvUU0P+Msf9fhF+bto3nBOddNI+L7v7PIffuQPnxh19HrwxIY7aH3t1pCv3R66rmlbEQce59eaRyrn7UHCjb3ZiQaF0FevGr0ihaDbcBFLZ1daxKHHPC+d87Y2N720PaKoDNcPEpbbEe3YZ3+aMcvd2H8wyym1OVJpltquInOWVWhjj1pi3O0505LGYnC7egezjDjw6Db8I+KghcBTMM3cwfj8WptuMyAfpeSFro1Fd61CR2PzVzlWa7MYqR8ac97M3HxbN0QJARKBFPVrY1/783247yuloN8K3K6xduHujpC6lIRb+1MagU8cKBqBqlVWV3/pXOt3zU1wN8rJmc4sjVBhrSCrqqOTGEFtWhJuHzRUEoFAa0Mj9Fluhmz0G7z33DIbvQa+J080/x2HFIJnTvc5vdRif5JSGYuvnCnuc1f2WOvE95wILrcVSV5y5c6EU/3Gojt9gQW+ibAgnu9GWAsHO7BzG0YDd1RZ24T109DuvbW3rTX85q84p/rBDj/zPsv/sPQpGtc+RhPnVP/AJw1//lM/+FCn+uuFkpL3nOkjgP1JVu+DKbqN4J6DVScO2BrOeeZM78Qe59eCM8tNbh/MSLKS/UmKlILVjiO2oySn0wgxxrI7TkmzkmbkM0tLikrX0UUlEsHB1HVYP7HRoRsHTOYFpVYkWYmUEHsKiyWvk8AP906lEEznBaNEUFTWdVjjCLFUgllasDVIyEtN4Evi0McYt+M3LypmuWsmgkeTqW91wnkE8drd5a8VpXEErxV5SCmZ52X9mliUdfuaJ8GTbhfTWkscKPLKoK1ltROzNZxj6vWJ0riGKRf0rskry2Y/Jgo9innBJC3Iy4ry2It8qOge7XzijEJ5qesazgoBhIFCAKVxObCR9GsTmyHwvDpXViGFYLUTve4czXbs3xPy/sVr+xjsA9MHcGrocJazM04XxHOBBb6JsCCe7zZYC9e+Dq98zZHARtNJV1degK0b8J4Pwcpb0KluDHz21+AXfhbu3OJ/u1jyX33og6iXP01j4pzqZz8w5cc//bvZ7HTf9JsXQji1pRNxZrl14mWUElSlec21j86cYwk8daRQnuo3uLzZ5YvXDri1n9BtBHU1ZUUYKJ5caXJ9d4qnBON5QVYZ2rHbQR3Pc8AZN6R03ezNyGc4K1ACeg3f7VMKiHwPYy2yrr20uP3SQ2aQlodNNBXdZoiUAonAr13SSVHR8j2WOzHzoqLfDJllJXowY5Y/jNoszEOHOK4AujHum7tjYICs0AS+c21rUyugx9LjjwfJH47Bvfr9kVXG7QRbS2Vcx3k2TCi1ASvwlMRikbUSuTvOGacFrTpztjpOOg//rR9m4AkCKYkCj7w+YVJC4PsuLkxrg9GgatXUV4p+5HNmpUUz9Km0YaUds/QmkMEkrx55kugrSZpXD/35Agss8O7Dgni+2zDch6svQtSA5rGut04fDnbh6192qmf4JikE1sKXfwt+7mfh5hW+tF7wZ7/vKdKr34v/klMCu5cH/LnPfA/vXdt8c27zIWiETkEqK4PvPTjWm+cVnTjAfxW1c2+ScmNvyu4kwxhLK/Y5v9Lm7EqzVleXsBZ2RnPEISFdarLUCsmKiqIyjJOCSVrSjV11ZpKL2mTkCGUnDmgEXt21LkgrQ1ZUSCEJPUUz8lBSYnFq06Ep/zgFcj/TeKqkGXpIpcCCtQJdGUrPUpQaWcfcrHdjGoHipe0R88IcjZFDTxJ40o3WrUEbnNL6DoUjg2/9vunhWoKw9g23CZ2EXFtyfZc0He5a3g+Jy88UQqKN28mUWE6vNsAKirJCCHfS4Rqn3EjcImhGPkVVobWhLCUHRU5e6aPx+iHpVMLlf/pKEAfK3Q6G5dqw1owg8iW+UoSBIi8MBlvXSoas9xoESpLUqydPnurSCD0OphlZqfGkoN8KX/Ok4bAC95WdMbcO5mz2C5bbIf1mgDy2NlRqe2RgWmCBBb45sCCe7zbs3Hb7lUtrD/6svwK7W46Abp5747f1tS/Cz/0MXHmem92SH/m+TbZu/07CrzunerA54D/83o/zmfNPv/Hbeg1YboesdiL2ximn+o17DAd5qclLzflz97pgrXWO9L1xSqEdYdwezlFS0GkESE8wmRf8qyu7jJIuT2y4+KUkK2lFHv1mxEa/gZKCqztTdsZzosBjoxczy0uG85JCJ87o0QqxQjBOCqLAI/BduLyvJIGnXDc2lqKsOJga5+49vJ/3/XsIXccy3Rk50pCWGqyryNTacJBktKMAY21NOCy9ZoCghMOxbeTc+YNZjq4bjt7JMNTK31t4Nz3lSKA1jhBK+fZnmB6pndKRTnDKoxEuCL7UBl8plHIj8cj3XFqCdicxzcinFfrsz1KSSmN0hbECgRvbV+bY+6q+MYtrI0oLQ7cR8sRGB19Jsvrzc2mjTZZrXrg9qpVTQ5prXt6eEAWKZ8/0+Y5nTrHaCfmNF++wP8motDnaj37yVIdzK61HmoHmecXnr+6xPZiDda1JO6M5+9OU9W7MhbU2SkrSokJJ8UBSxQILLPDuxoJ4vtswHji18yRI6aSiNDn5568Vr7wIP/8z8PznmIQVf/a7e3xx9P00vn66dqqP+Xc+c5k//OzjOdUfF2Vl6EQ+X7kx4MrOhOV2xHLLjaHzUnNxrc2ZYztn2hheuDXilZ3J0Vj95e0xQggubzrFRgrnIs+Kis9f3efF2yOkdKPMtDDcHgyYZSXtOGBnnNJthHjKHSyfC5bYHc1JC01eaZSSxIGi1wjIioqDWUZeGnrNACUFq60Gha4IpCQpNFjLPC9flfCUGqqsBAtKgpQCC+RlRRz4KHXYziRQUqKUot0QhJ5CY5nMc7K8whjrjEwPn8S/Y/BWC7KCu5Wh5s3MUnoIDlXc4y1Stv6+Na5B6PB8KQ48zq42KStLM1S0Ip/re7N6RUNirMVT7t/RvHAZtsJircDiYorud+gLUcc8IY4ajVbaESttR+qiyhHPpWbEK8mUThzwvnPLLltznlPVRQob/SbL7ZAvXB0wzQpW2hGhr6i0YTQv+Pwr+wCcX23zMLxwe8jWYH7PyeOd0RxPSrYGCZGnaMY+07Tk8qnu0X5nVlTcGaVMM7cLvdSKWO1Ei7zPBRZ4l2FBPN9t8DxI54+4gH18h/utq/DzPwtf+BeUyvBffcrnH9nvp/XK067ispHwu75rmX//w7/rDTvVXy/G84LPv7LH3iRjqQ6C3x4k7I3nPLHR5aNPrHFmuXnPQejKzoSv3hzQDH1WOxHTtCQKPBqB4ub+jNBTdGKfUhtmWcn1vSntyOeTT6+jpKQT+3xta8iVnQmVNsShR6k1RU0mu92AUZIhpSSfOWK72omJA49SGyY3SkJfkBeG0JOsdGJ2ximTuVMep2lBVpp7OM/hDqi+j3gdEgljnIrrexIlXd2nryS9po+vPK7sjGmGPmtr7raSrCTyFOOyRBtzFILweojWWyw+fkNQnEC+3+xx+/3X14w8pyJqQxz5Ls9VO7e6oG7wAbCWg0mGp1xu52od1r47TrHWUtas3Bp3clVVLodTSLDGnPgYBCCkOMrsjAPpajLrWKa00LQjj1lekeROTQ18yVI7OtrlNNZye5DwhasHJHnJ6aXmEXH0lGSlHXEwzXhpe8ypfuPEsfskLdge3luBe2GtTei74oTx3PDyzoQPXFjmfeeXeHKjixSCndGcL10fME5y5763bg1gvdfggxeWaUb+A7e1wAILvDOxIJ7vNqyegv0dd9QR95G/IgfpQXfp9V3nzhb8vb8Bv/WrWGv4f3zI8LP976B55aO0AOPnfOQTiv/sU7+fVhi86tW92ai04UvXD9ifZpxeaiJraUgbw3CWY4ylGXn3kM55XvJbX99ld5yi6gN4UWnSQrPcDknyii9d36cReIzmBfuTjFlWsdIOeXl7wqmlBp044PKpHuN5yfM3BjRCn2bkEfiKrNTEviLyfWamQAC3B3OmWUm3EdQxOm7UnVcV3YZz4p9ZbnHTwizN8a2kNIaqJkGC+pzhIc7nw51NpQTt2MeTEmstg1lGUWmUdLd5frWN7wnSvGSWFkwyp3a6PUFxtEf4WsnkNxvpfBhU/dyf9NwcJ9+Hu5OPIqmedCcP4tjlJS6eyFiLLwXNZkChNUlWgYW80pjaYW5x7T3TtOD63pSzS032pi5XVilJVRkCXxF5Eu1J0rIkEtKp4dqgPNfQVZcTAXdjlfz6JGheaOdml6IOgI/Zn2ZUlaHTCo+MddO0QBt3slNVhuvTKU+sd0+cdvSaATujlMEsZ+OEmtokq8gKw3Lr7qHHU5KzKy3WezHjpGCalXzk0iqr9Yj9sMUrLzWby01kfbulNmwNEwTwiafWUG93pNwCCyzwWFgQz3cb1jade33/jtvzVPVLWGQw2INT56D3GonnYA/+wf8Ev/ZLYAz/4Kmc//qJj+G/8B00B86pfuGDc/7ip3+AjfbDR2dvGYyGyYjBYMrkzpj19dUj0gkuZmmlE3P7IOH2QXIUe6SN4Tdf2uXr22NW2iGN0Bl+hknG9jCl0oZ5XjHPS1px4IKztRt+JnnF7UHCLC95Yr3LKMnxpKDTDFnvxpxearI/zdgazJAiYK3bINurqLS963QvNZ3Yd+YlC8t1HeAoyRnMcnwlOb3cYmswRwqYZncjkB5F8pR0Y1htTE1SJedWmyTzin4rpBl79JshSVaRlhWXNrr4nmSSFljrQuNlPe6Vb4N5552MQyKpuEvyy0cwSXv//wvw6qzN+xVrKd0Jx+FlDwlfVmg07vnPK4tF12UB7jyy0hpZm4yUcMTKWovMSrbHKbHvUYaasnTXrY2L49Lauigm6eo0xaFyyt3XWUpnSmrXNZcua9RwbW/Kcivm/FqLduzzys4EYyyn+g1uDxJ264aww1KCea6dCekEcx+4z6Sx1J+nE573+o4d5pwCRykUgadoxb5bKTgWr3R7mDBNC84sN+8hu76SbHQb3Bmn7E2yE4nuAgss8M7Dgni+2xA3XWTSi192JqJD14Dnw+kL8NT7QL6KC3Qygn/4t+FXfxGqkn91OuM///B7KV74HYTPO/LWvzziz3/P9/Ls6vpb+nAeir07cP0lGB0ghjNOTQoa802SUxcpW717LtqMPPYm6dH47c4w5eb+jFbo0YkDhBDM8pKysmRFxde3Ru7AKdyu5EavQVZoKqsIPFlXZ2pe2RlTaedQ7zeCenfOMpxlCCHZG7tO9UpbltsRS+2QrNTOKR957I3SI7e57ynmuasDrLQhLSoqY1BS4UuDtQZjOVI/78fh4dZYi5JuTCqlI6D9VsgzZ7r0mhHX96aM5gWehK/dGrIznjPPq2M7k/ae63stOCSr917DuxuHj+Fx1l19CYHv3itaW6ZZdfc5qQn+/c+RBUpjXaSSEGijKbUkL4zrUDf2aD/Tk5Yw8PCVe89EvmJvnKGN5iOXVpnlFVvDOUlaIaU70VJC1aNzUFLUpJVjL3S9ktHwObPUZHea0gw9VjoRvifYm6QcTLMj011auBOwZuTTid2UozKG6XzG3Bj2xilnVx6MNXPKuytsOAm9RlB3u7uWroNpxigpAOjEPtbCxfU2zejuoenOcO4I+gkKq+ucN4znxYJ4LrDAuwQL4vluRHcJPvztMNyD+cyN3Ds9F6n0qHFTMoVf+v/Ar/w85BlX+zk/8p2X2H35uwm/5Jzq4eaI/+h7P8Gnzz/5Nj2YE7C3DV/9LFQVdJcoVYc832NpuIOXzRhd+gBVs3N0cXd8FUfH2NuDhMh3BoXDjMztQUKl3W7m1mCOB+hSU3h1wDcWJVwkTJJX9JoBB9MMKQQbvZhW7KOE5MrOhL1xhu870npnlKKtpRv7hKFCIY7uz0q3QVpUjJKCKFAMk5xZViClYpaXGOOaaDxPoq0BffL49m4sjjiqusS60e1gmgGC9V7MJC357JUd0kLXLmVDXlYnGnVeF3l8HWP5bwWUBig1vpQuV/MYHkVkdZ3TKQVkhcFXpk4ZgDSvjhRobVwSQ+g5Y1GlLaV2sVxKSs6vtNnsNxhMc24NEvKywmLx6n1fKSVJVroTJcBToiaQPnlpuTmYobXh7OkllpoB1/amVMZwutek13AnL9f2ppxfaRH77hBhjGWcFJxebpGXFTf2Z2wuNR4Yb+9PMla7Mf3WyeURUeBxYa3FP39++6gwIfIVVsC13SnGwuVT3aNxOhyqow8/VXKK8eIdusAC7xYsiOe7FZ7n9j1fC7IUfuUX4Jf+LsxnDOOSH/s9G3x169M0vuic6qI/4Y9999P8wcfsVH/TYDRce8lJf3UQfiME/JBZ3KI12aWxe4PJxfce/UqSlTx9+m6f8zQr6DQC8qLiK7eGdYuQoRkpGr6HkqDrWkutLcOkYLUTU1baZWQa7XqxDVhhGafu54En2RomGCwYSV5pSm2O9kutsUShx/4sIysqIt872t2bpAWldhmaUlqyXON5gihwlYVSCMpKU1Smbqi5C1WHFQjhwsK1dntx47RkPC9Y6UTcHiaMk4JbgznaWBq14nS/SelR8CQo4Xq5j0fxvBmGmze7HegbjdJQt0Tdq24+zIgla8KJdXueSkqEEEhwdarHr0M41dSYCl9JDNQk1GOalvSaIb5SeJ5LUTiz3OLOcE4UqFo1N8yFIA48/NqI044CZ0zSmumk4PKpLpfW29zYm7HcdiSxspaNfozAcutgxp3R3Dnm69Oedhxwab1NVrl4pWt7M5Zb4ZGZbpTktKKAZ0737ok0ux8bvQYIjvJ4s1JjrKXXDOk0AvamKaMkP6q+XelEvLQ1ghPIrFs7EbTjt3/3fIEFFng8LIjnNzPKAv7pP4Rf/NswHZF7hr/0O7v84+m30fqyc6rbxpzf/Z2r/PBH3n6n+okYD11k1DGDVDv26bdC9qc5ftwhHO+h8pQqiDiY5jQCjzNLd2OUIl+xM5zzys6M3dGcaVahBBSlZmBzjIUzSw08Xx51aJ/qxRTasDtOyQrNLCsptEZrw2on4txqixt7M86tNmlMPOZ5RWk0UaBohR5CKmZpgRTQb4ZM0gJtDVnpnPS9ZoOyMozmGUK4SJt2HBypZgZDUVoXWK/v7uiFHvi+h9bODW3q+2vrAPCVdkzoK27tz8mrkjhw5GSWV9jX2cVuDIg631LcN16H12aqOQmHrTyHxOudG13/+lDdx6QPSef92ay+hEbkU5TuRCX0PNcKVFbMcn1EOiUQegKllCOJxpIWFXGoCD1Frxnhe5I7ozmhr9ifZHhSIKVAKclSK0IKOJjldBsBlTFH9ZZCCuY1Ue40Ai6td5llJZUxLLeca31/mnEwzeg0A84uN6GOLIoDj2bs02sEeEoiC8G5lSYXVtvsTdy6iVKSi+sdLq61WWo9urxib5LSjUMurraZpqXrbfckvboC9+bBjO3h/Ih4nl5quhWSY2QU3NrJzihlqR2y2l1Uai6wwLsFC+L5zYiqgt/4ZWccGuxhhOW//3TE/xh8hPbXPuKc6l7BJz7p86Of+sFviFP9oagq0BX4d++TEoILax0ME4bjGeF8zu7BhCTQdd7g0j2jvc2lJr/42RuM5zmnlpr446x291pKY5hnFZ4SrLUjBkkOuPzDpVZ0FJXkK8mZpeZRhqBXH7jbUYCvFFd3JhSVcVFF8xJPVhSVpTKWJ0/FCAEHk6zu3nZ7d9IXINxeGxY6UQAS2kIwngvXdFRo5mWFFKLOanRjzsBzX2dlhbWWVuiz3IlrYgHTNGOalo7EGvtYxiEDGG2Qwj1eYyzVa9jtVMcI5XFiekjEjpTTY1fwbotoei1RS/e43mtTj0siEHXWpvu51m6n11qLFe6P8N0udUHguRMizxiSvCLJKoKWYpRkBJ5gmlYkRclsXtIIPOLI48Jqm9VOxM44payMW/iwFilk3fxj6TdDfCVYbke0Yo+9SU58zMQT+YpRUjijWhSQlRVL7eiBAPckq1hqRbz/wrIzOJUGT4l7rutR2B2nzIuSZuXRaQQP7G9GvmJU188CLLcj3nduma/cPODmwQwlBMMkYzB1CuvZ5SZZqV9za9ICCyzwjcWCeH4zwRj47X8Kv/A3XIMR8HMf9fkrp54j+vKnaFvnVH/igxl/4dM/wFq7+SpX+A2A7zujVJFDcJdMRr7i6VM9xr5mPgd5qk+712W9F9MM783wM8aZiHyl8JU78B4qUaU2hEoyLzW6rkpMipJSa4YzQxR6LLdD2lHAhy+t0Ag9PvfKPlvDeR1z4+bgSklHzIRBCEGhDUKC7ymmaYEnBXll6TcDltoR46RgmORo7TI9tRWM5jnawOZSg2fO9GlFHneGc67vzyhLTTMOmM4LMm0ojdsPVMI57Nc6MUlRsjPO0ca6EPtCu0rFN/gSONH1ZFp40nePk1wl6zagh1z2EH4d9/MObu68Byc1Gx2S53rl9p7VhFCCsKLe+HWGoqo2AuraZIQQSFwYvBBQVQZwJy/GGsrKBcFHgWssOphmbA9d8Pp6L+Lm/oyyzvB8YqPN+dUOZ5IcpeDOMAUEm/2YTiOk1wwR1nBnnOF7siaJ2YlrNa3Ip9f0ubKTHTnOD5GXmqyseO5s35UVSF5XTeaLWyO+emPA7cGcg6lLeOi3Qs6ttI4MSdrYB3ZHL6y16TR8nr855PNX90nzipVORLcZcHVvxsEs5/3nl9lcegf+TVtggQXuwYJ4fjPAWvjib7p6y9vXAPgXzyj+3Hufwnzh22nsOcVi+fKEP/8938vTq6vfwDv7Kuj0ob8MB3sP7LAqYVkyKUvPPMWZp88+9CqGSUEcOGNGkjvH8SwraUU+3XpcOMsqunHAPNfEAUzTkjhUrLcanF5qcvlUlzPLzrX7iafWuLk/Y5IWTJKSjV6MtpYsL4lDD2sF43mOttAKfaZzd12XT7XQ2pKVbncz9CS9ZkDke0yzAl9KhvOCOFR86OIKRaXZGaaM5yVBfdzd7Dfr+++64cNQ8ezpLnfGOYNp7vZGtYvVOaQIb1RJlMLF8hQ1K5SA5wmK6uRrPsystNz999VQVnfXCY5ul3fuGP5+gnzYfGTqMxph3fNgnEfsSN09NBRV2hFJYwFlEdLtG8/zoiZwol5HEEjh2qqEcAR9rRux3A5pBM65vjvOWOlGhL6PEJpm5PaEQ1+x0WvwbU+d4nOv7CGF4EOXVmiFHlJKDqYZr+xO2Ww26TdDBtOc4Sw/MhBlpeZ0JzoKZt+dZAyTHN+T+MpVWFbacmm9c6Kj/VEw1vKVGwNevjOm1wqZZgX9ZkClLbujOZU2PFmbiipt2DihJjMOPNJCu8zPbnwPad6bpHzp+oB2HNCOF2HyCyzwTsaCeL7b8cLnHeF85WsAvHxG8p985yUGX/wk4W/3kUC8OeY//t5v4zvOX/zG3tfXAinh4jOQJK6XvtN3KmiRuxio3jKcvfToqxBOkdxYalKWhtVCszuZU9TjuKLSgAud//jlVZ453cdXktBXBJ6i1wzuCaPvxAEXVttML6zwpesDt1MnBMudBmnpxp1Cust1GwGVNgySnG97ehNfCf7JV25T+JLNpQbN0DXCbA0SRjNnDPKF5AvX9tkZplzfnyKsxQrJeF4wS0vCwO34tWMf31MIqWiG6qh5BkEdq/MmjbCtRci7GZBO1bt7rfffhhR33dz33/b9+44c+/r+771TSedxHFZfOsVWgDV3d2lNHSphDjNB6yxPC6WuVU4LgZIstUIagc+OMeSVxhcK35N4SrDUjEjyirLSxIHiveeW3XulHWOMZWecoqTg9GaTwTTHl+7EJy2qo9WLlXaEUpJxUlCUBmPdvuhGv0kz9BFCsNKJOJjlpGXlAuk9yXIrQhvLLCv52BOrbPQbbA/nlJVhtRNzZqXFZr/xumsqB9OcG/sz1joxnudO/AbTjF4zpN+KGM5y9sYuEm2t22D9hGiknVHKaJ7f05h0iJV2xK2DhO1hQjvuvf4XdoEFFnjbsCCe71Zced4Rzq99EYC9PvzID1zgpec/TOM3nFNd9qf88c88y7/+Nneqv2H0V+B9H4Wbr8DBDiSVG7uffxLOPgHNR4fZb9YH13FS0G+6xqBm5DGZ54znFZN5xkon5EOXVrm41qHTePiOqzaWr2+NuLo7ZZa5XuyXtmcMZjnL7YiysqRZzkonYq0boY3rlG4GPqeXGyy3Ij53dR9tYakVouq2oU4cMJ67XM87o5SkKBECGr7H6kpEZSyDae5G+wZO9Ro8sdHmc1f3yYuK2PddJqixR81Mj0M66/U/DMdUSwtYgZAWtPteXt39nftvo9R3v3dIR2Sd5WiMJTuWzO6ruvaTd67LPZAuNcBgXSZnffeVhHYjYJ5VVNrtNXpCkddPgOHuOF5wN40g8iWt2lU+SAracUAjDMBaQt+peJP6vSClQOsUrS3tps8HL66yVjcKeUoglGStG1Nqw1Onuow6BTf2ZuxPM27uz4gDj0bo8R3PnmK1rmgdJTlKCjZ6DRqh4oVbI7aHCVIKWpHH1iDBU5ILq23SomKc5Kz1Gnzo4grt2OfpzR6m3lN+XOxP3O7pYTD8pbU2SsBgVmCsYZpW3Nib8rHL67zv/NKJOaCDWYYv5T1RS4cQwiVEHEzzB362wAILvLOwIJ7vNty4Aj//M/Cl3wJgHkv+wg+d4Z9fe4b2r911qv/gd53iT34DOtXfNPSWnbN9PnOGoyBw4fmvARv9Bk+d7vK5K/v4StKMPBee3Yoo9Zy1Xszv+ch5PnBh5VWv66XtEV+9OaDTCDi73OLcSpsz45TfeHEbrQ1Pb3aRUpIVFWlu8Dw3powCj+VWRK8Zcnmjy5evH7A/yUiLiqIyKCW4sNpCCMFXxvvEgWK5HTPLSjwlSYsSi1OpfCW5PUxoRI7IKSlIi8oFmBvrOtgt95DP40TQU65JR9Z7p4dQuPYjicD3IMk0la1VzjrqxgpzpHo+DMd/dkgxY1+y1IyYZsU9xLN8jYntb5X56GHO88M9TSVdJWkz8hAI0lIjJfhSMstK5nmBQTiVWbi2ocN12MPRuwQaoUJJSWUMXr2vGPiKVqjwlGA6z5jlFWVVG404JP+WMqtQEjrWZ60bESiJJyVlZQg89x6QwmV6rvca+ErSbQZ84MIy7ThgpRMdhb6vdB50e3cbITvjlL1Jyum+6zo3BnKtCZTiVL/BRr9BVJM/IYQzkL0BFJW5RyWNAo/Lmz2mack8d7Fgy+2ITz61/lCCK4R49PvQ3m1DWmCBBd65WBDPdwu2bzrT0L/6ZwBUHvzff+gcf2d0lu6vfZg2YL2Cb/tkxH/yqd//gOHmXQkhXlXdPI4kL9kaJNzcT5AIes2Q7eEcWStYlTY0Q5/vfm6TD1969T3XeV5xbXdKOw6ODuQAq92Y584u8/XtEc3I58mNLnmlXXWhEuxPMk71G0dK6oW1Di/eHjKa5+xPc4qyojKW63tTitJQaM1yK6IV+syykr1JRllfn4tOgtEs5/kbQxDQbQYuuFwIfE+hjT5ysjvV7O7Y3aluLnJHCPDkXUNPHEq0hbLSGHvvEdsA+Rtw/iS5oazmj1TaH7bTedJvvB4iekhv7ifgvieRuAaeQ0PUEWmUru5RCkulXcuQNa5VKPQUcaAoSk1uLLI2UB3u1SoFTU9SGchLg5SO3CklmMxLslIDFe0oxoQ+SVaSFBprTG0wEihZG4l8RTMOqKqKtNT8xtd3+b73nabb8BlMc/otwbyoOL3UrFMPLPOi4rlzS6/pRAqcEn1upcW517mn+UbQjDyqugL08D0hhaDbcOsp1sKZ5dYjVdXldsSVO+PafHTf+9W6Xer7HfgLLLDAOw8L4vlOx/4d+Ht/E/7Fr7h9MgF/+/ed46+KFRq/9Um6tVP98gdK/vyn/zXWOt+atXHDWc4///+z96cxsm15dh/22/vMcWKOnO/NO7+5Xs3VXd3NZo+UyrQsSKZoUbAM9AcSNgQaMASbNEXJEkHABATKhiHABCVAlGXLsmXIkqmBEiU12VSTbLKrq2t4VfXmO+ccc5z5nL39YZ+Mm/fezPfum+q9VxXrQ726mRkRJ05EZqyz/v+11o/3uX00I81NnIzSmk7o0gkcevUu2YuXu+z0w3PHdefd5yItznXKbvcanMwT7hzNWW8FNAOTtXk8TQl9h+e2u8zinHcOZ/z2aw/4we0hWaFwHInQkJZVvftXIRAczRLyoqJU2ph4hEYgKGs105aCcZRhWZJ3D+Zs9xq14lliW6Y7O8uNYinNgN4oaPo0ZPvRiBsMkauUMPWKKLJzzD4fBrZgGcFkuuGfro88xUW09uzPWwIcS6AQ+I4gLbRRCd/jGCz5+M6lJQSBZ9GoM06zqs4UFQJVM9BSgapn6kpDkhY4jo1jS0LPIatqNbhUuK6F7UiSrDQkV0sqBJU243enJoRtz8V3LJKsIq8KRouErNRG8ZagMF3vuTLE2HctAteh4VhktSFpNE94c3/Cq1cHzJKCO0cLek2PXtMlSgvGdbblra3Os71AnxLWOwGhZzONTbmDUTpLTICU0ep3eu/9t2uzE7DW8jmcxGx2G0vyebr32m96q9rMFVb4HGBFPD+rmAxN8Pvf+1sm1xL4nT92lb+01kb8/s/TLMyV/fpzC/71X/9NntsYfJpH+6mirBS/++N9fnB3iOdI2oGLJQVpUbFIc7LS4hdf3OLS4IMpPFVddn0eSTVKZ5d7x3PirCDOzYi83/JoBw7fu3PC9+8O2R8n7I0XpLlxtid5uexbl7Iejmvjdh7OMxAQuBZpodDKqEOubcib71o4lkVRVZRKcXW9xTsHM6Isx3dsXMfCqYlmeaayyJGmavMspDjNjjRj2wr9GBE8zaLU7zNmfxKlNiN8Vd/+yT3ODzpCl9KsA/i2xLMlRVWALdBK0wsd5mlJWph7tIQZk5/uBwogrs+30KYhqKhroSoNQpxZO6if6+k5yCqzjxp4FnFRMk8Ks+ZgCRN4Lo2ibgmTrWpJQSWMqpxXijgvzYhaChxH4jouw3lGK3DqcbBgFudkRYUSeqnK25YZSweeTZqXaA3vHs7Y6oUMmh5Nz6bh28RZhWtrrm+2ubXVoRU4TKIMpTUN117uUn5W0A5cXrjU5Q/ePeb1B2OjFus6jUFpXrjUfd9j9hyLL19f47u3T8yOap2+UCllckWvDmh4n63nvcIKKzyN1W/pZw2LGfzX/x/47b9pnNzAj3/hGn/+pZDZ730F780eAI2dOf+73/wFfvHq1U/zaD8T2J/E/PjhGN+xH9tp8xyLhmdz72TBd+8MLySeSmvmSUGl1GMf2oFrYUlBXj4dTp3kJaNFyqDt8/Jul07ocTCOeTCMuH+84M39SV3VWVGWilZgTCRxWqIUZrSKqCsNzehWCaNuVromi1rXfdsa33EIPBuJplQW88TEQ/muJC1NTmng2ni2qWI8mSVkuQmDdyyJUtUy9seE6RuzSFkZx/OThNCST0cIPTNOSdw5pPWD7m1WCnxH4FoWSVEh6nF0VlTkJWgtcCxzgWBJo5/Z0iiO1ZkDSIrKRB3V/eUaHtvNtCxj+kLpM1FI5kKhqpdcG56NJSWVNnu1tiVxbYlt2SSFIq8URWVer6xQ5EWJFBLPkSgMSeq3AmxpTGFmvxN0YXrYNbpujdJIBK5t0fLN6/7qlR5b3ZB+0yXJFUVV4dkWoe+wN4r4wb0ho7nJdDU1miE3tzrvG+p+MIl5/cGYUZThWRY3t9tc32ifa+75qNhda/KjBxOKSuPaZtd13bPphi6V0nz/7pCff27jPXNBu6HHL764xcEkYbIw5rtu6Jm96k/gmFdYYYWPHyvi+VlBEsF/95/B3/5PIIkB2H/1Cn/+l9q8+4+fI/zvL+MBVm/Bn/m1V/hnXn7l8+VU/wTx4CQiSkuurj9NLB1L0vBsbh/NKCr1lNlqfxzz7uGU4ZkP7UuDkFtbHfpNn/WOz9EkYavXMMqg0jysY1uG85TLa01euz9GKaOubXUbeK6krDTNwCUtU7KyIi0rQGCCnAzxCCyJlCYAHKFxpCQvTfi9JSW2ZRHaEtuRWJYJ65ZYhIGF0HBl0KQsNS0/MzmhjgVaUJTGtKJqNnk6mrYtM1oW1BE/RUXxRMvR6V7oh3GcP/lu/KB3cVqp6dmQlub27ukeY1EuQ9fLUiGFoNVwUJEmKTS2FHVvujFk+a61NPtoAFXvy55Dhi0haje6JnCMiUdKMwB2LEHou0RZbl63SiGkaaNaJAWd0CErlamffCJLNSk0goo4r7AkNFzL7I0i0JXZU5RSICTLYysrhWPZVMo8R9eWbHYaPL/Txa/zNluBBZgd7nsnC/7w3ZMlATtt2PrRgwmTOOfrNzfOJWRKa/7B6wf8gzcOmCeFeW8o+M7tE25tt/nWV67QC5/uRv8oOJ6l5GXJN5/fqJMTDAGV0qiW++OYg0nyvrunrv2T31FdYYUVPj6siOenjTyDv/NfwN/6fxu1E5jfvMy//sf7/MPvbNH+Wy8QAjQS/plf3uFPf1Y61T9DMOaYp9tOTuHYgryoqJQhnpVSHM9S3tqf8sbDCa4judxv4tqSOCv58YMJ0zjn6zfWeeVynyg55Ef3x/iOZBzlnMxSPEdya7vDja02Smm+/fYxWVmx02twMsvIysqQgCSnOA1iF2IZu6MVlMooeJZl4UgT0q50SaUMCWv6Ni3fJc4LqqoiTjW2rcjLilbDpdXw2OiUJEWJlJKNts9okTJalFSY8fFZJ3BR1iNdac6BFgJVy36niqclH6mVHxS2ZRTKD1PXCacqLASeQ14VtZteobSFhca2LLK8oFIa35HLFYKy0hSVrh38RqnNC1U/R3CEwLElydncpzOQ0hAxKUzneeA6FFVFUWkanmv+f6GQslY4baOqzpOSaVSglNnZFLYhv6qWVDWPUgUqzAj94cjEGJ2606s6WD5HY5WmOcvVirwSrLUdEIJXrvSWpPMssqLijYcTbEswaD0y1ZzWUO6NYh52F9w8Z//ztXsjfueHezi2xY3NFlKYzeBFWvL6gzGubfFPf+Pax/q35niWIDCGuCetj5Y0zv2jSbwilCus8FOOFfH8tFAW8Lt/2/SpT4YAFDs7/J/+xDb/3zc8un/za7QBbRf80jcb/G9/8Z/46XCqfwLohi6Wdf5IHCDJKi4NQhxLMotzE9Y+SXhrf0pZKVqBQ1Fqrm+0lh/a+6OY+x2Ti5iViqyo2BtFHE1jAtfmylqPG5ttbCmJi7KOQCr54b0Rh9OEcZRRlIqkUFjSdMFLIYyTGUNK8tKMwl3bhIe3AseMf7XJvkzy0phPSrOz6TmSAHsZgn/3eEqUVszinJ1+iNKCsgIhzQi/0qbCUwrzWFSnYedGmfMdC9c2bn/PtiirirQe/8pz9jPfD88alQTgWoL8DEOVgOcaYnc2C1NpQVlUSGkItOtaZJlJBTiYJGYXtr4PBeSVObtFVS3vQzrmXNhSUmrz/ASPQu+FENh1unvDdQhcySIDhKlBzTMTLVVpU/sohF3HGUFWlFiWpOXZpHlFfBqvJGp3vcao2UIghIm/0lqjLYnSxjV/ikqbHvQyL1nrBthS8sJOl6/dPN+tfjJLmcYZ272nzW+2JQk9m7vHC65ttB9zgZeV4nu3T6iU5vIZF7hA0PIdytLn7f0pB+OI3bVnT5V4P1TV0270szjdn11hhRV+urEinj9pqAp+7+/A3/x/GMc6oAfr/N//1HP8tb2U5n/+83Rrp/qLX1L8a7/yT7LeXkWEvBeubbbZaJmw7K061xCMijWLc7TWvHipx/2TiP/+Bw84nCS4liDNSy4NmjiWcZXP05wbdaB8w7P5wd0RljR5iV++vsZwnvL6wzGBazFNCkaLbBnfkpcV86TgeJ4yCD2kEGRlZUhRTUQq9TTREAKUUggkcVriORa2JWk2BFGSU1aKrCxNoDuCTuBgWZYJr6/gaBbjOTalMoaWSivQGtu2qIoKKSD0bJTK0VpQVZqCWuGs9z9B0/BtEDbZJAHMLuiHwdmIpPcyElVK49SxT1Ia41TDdbAtSZzmS/XVcyRFpZDa7Eg26gT6tDD0+f0I8pLg1+72085115IkyyVWQ4gc28Kv93p926wz5IWiqBRFaV47W8paNbawZUWGQlWKrFTklclKPT2g0zF/pQypLiqNrFX5olJkebl8bKVO1WhASPJS8aVra/yPvnrlsSivs8jr99dFZM5zzAVKpRSWfHRBNkty9icxnQuKE5qBw3iYsTeOP1bi2QqcZdvWeWtCaV7RCS8uc1hhhRV+OrAinj8paA3f+fvw//sPYO+e+Vq7x3/3p77MX45PsP+bl2nXTvWt52L+D7/xm9xc732KB/z5QTtw+YUXtvg7rz3keJbUeY2CQimU0rxwqYcQmt9+7SH3jhesdXzmUcEoypZ7hElR8nBYMItMkHWjjn651A/ZXTMRLUKYkWA78JglOQfjmF7TA0zF4CLL6QYeg7bP0cw0xjjW6fjVRAsJy/RQnop9st6nTIuKhmsTejbNwOVSP+RgEvPOwQxbSGzb7B4ezdJa+dZkecUozrm11eLKepsfPxiT5hVCCnzHwhaCQpmdx7RUnDG6mxYcbaKbPNtio9MgzUsWbmH67T/hHc+qVlWlMOHsaEFRlZSVJC3Ucr+S2ixkVEpjDDrtMxdColFYRsx9z8eqKlB1ViaYLM/T4zX5q+DZFmlRmoQA14SzJ1lZx1EJbMu8VlmhiKtHbvlSQ5SUKDCjeEfU0VVG3QRhTEe10lqUmlRX6Lp1KnRMnqUlJb2mh9Ka8SInriswL4Jjyzomqya8TyAvFb5jPbWCotRp2Pr5hFVKPnicwTNgq9fgnYMZ4yij33w82H4SZTQ8m+1VHNIKK/zUY0U8P2loDT/8A1Nvefct87VGk+/9iW/yFxpHxP/DJfzoCwCEOwv+3G/+It+8uvspHvDnE1+81sd1JD+8N2I4T1Fa03Vcrm622OwEvLE3RWtNL/Ro+y5oCGKL41mC1rDVCWj6Dq5tKvluH83Iy4ov7D4i/65tIYVxgjdcm71xRFqUzOKCBydzkkJhWxa+Y7HVCxktUqLU7GwqpRGWxJaC0LMQEpK8wncsfFuiESilmCcFrYbHZGF2SUEjLYFtCTJt9haTvMS2wHccPEtyMk1pBS6ulFhS0nTMcU4WGXmas0jVU3uXVaWZJcawU1SCtw+mKONywq8NNuUH3PXUmCilU9f4+6FURuErlCItFSJ7PNszKTQNFL2Wt3SJp3lV74JaZKXZ2TzlT+8X1XRKTq06zsiRJvA/r8w6QyRKfNum03EZtHxevtxjnhb8g9f3Gc6z2gmvyYtHUUlFnRRwOrbP6vUJIU7D/M1IPS+NWuo6JjIpzg3z7gQu3dBDYJz3lpQ0XYskr3hwvOBomnD5gjSGtZZP03eZxDn95uNGoNO+9Vtb7acU0dA36Q8H4+Rc1TNOK1zb/tjD2NuByyu7Pb53d8jDYUQzMKtDizTHsSxevdKn+zEbmlZYYYXPHlbE85PEmz+A//Tfh7d+aP7tBdz/p36FP3/liHu/0yIcvoQH2L2I/+Wvv8r/5KUXV071DwlLSl7Z7XNto8V4cepQt+k3Pf7RW4fYUuJYElF/CJuYGUFeKrNXiBllaw2ea2FLSaoqskLRrD9/W75Du+EyjTIqrdgbx5zMMwSGcORFxeEk4fuM2Oo06DV9LJGTlhVFUdFr+XTrMf5wkSJFQb/uko/rzEbXljRci0WaI4VgZ9AkSsy6QDytlUhdMYk13YapzozzEnE0pxsatSxNTc1mXJSPhcaf4qz+ZRQ8jVAVCEFRVbi2pB26zJPSECkuDnt/Esa7/2zE8zTSqN5EMGRNP/oeGAKVFQrfsbGkYJ4WFHX4/pIUP3Gbi3D6myWESRWwJTQDj6IssSwLz7K4td3iV7+ww4NRzKDtm5rLwGES5diWpCgrLNsotEob97upznyUg3pqLjIh/earJupJk+aqjumSKHV6e3MxY0uBbcmlqosw2aMXwXdtXtjp8N07Q45nyWOu9uEiY7MTsHuOUSdwbV6+3GNvFDGKUnoNb/l3J68qDqYxL13qnnvbj4or6y0ansOD4YKjWQIarm+0uTxorlqHVljhZwQr4vlJ4M6bRuH84R+Yf9sOk3/yN/nXvjTm93+novPtXyIERCPlT/zRXX7r89yp/hlD6DmPmbCyomKWFKayTymOpmaH0bFMILlAUJSKvDQf8EJoRvOUjW6AnsDRLGFQZ4NKKbi63uS1JOPNhzOSrMJvGZLq2hb90MeyBNMkp+U7bLQDek2PPK94OI7phS4N12GRFURpye5ak+1Ogygv8bOCTsPDtiSH05gkq5Zj170oJ8pKikqbgHJher9Hi4w0N8amWZyz3gm41A+5czTjaJYghTBVj8njtPHJoHgNpJXGloYFZoUiK3KzWiBO91Df/9xLHhHI91NKT7u/hahH59KMoBFGNT1tPzLEs8CSkm7DVIVWlaprQS9uRXoSpzFRWtWPZwlsKSjKil4r4JXLPTa7DdP4pI1bfrzIuH+yMGarWq0uBOhKU2ozqm+4NpXWlEn5noRbSlHnrFo4lsSibqkqTBlAVhqTm2NJsqJECug2XN7DiwPAtY0WliV552DKySyh0hA4Fje32ry4070wx/MrN9YZzVO+c2fINM7xbZuiMvWtV9db/LEv7T7Wrf5xYq3ts9b2633ni9MoVlhhhZ9OrIjnx4mHd0yf+nf+vvm3ZZH90d/g3/yViv/8H0zo/YffoINxqv/KN9v8b1ZO9U8cRjgy5o1e6LHv2szTnJbv4jkWnaap75slBZYAz7VZ81y2ew2U0kzjzKhR9Ydw03fohT5KazxH0vIdbEvgOg2qStEKjHpkW5IvXRtw+3DO3XhOox6fgiFBndBFaLg3jChqN74UOeNFRpQVlMqQlXGUMU+LRzuM9Vg3ySpiTD6klJppXPDmwwkv7/ZpBW59G23al2o2dB4xOvtvAVi2USHz6sw334fd1f1LANh2bd6Rj7vWlz93mq2p611CjDlGnRpOlH5MNS1rRbZSOVVlIqoGTY9JvZ/7fjh9TNsyuZzSFjhSLoP2G77NLzy/yc2tNiB4a3/C7715RJTlJJkJ3d/uNVikBcN5Vpu9TmtMzfrFqUp8Gk2l6ucmakVdCFN52m+6FKWJfmr4Nnlk8j9916Llu7QDE+M0TczofK3deN/RsxCCK2tNdnoNpnG+VPpbwXv/XfEdiz/25V2ub7XNesoio+HaPL/T5ZXdHq0LDE0fJyx59p2zwgor/KxgRTw/DhzvG5f67/326dY+6pu/yr/3x9v8u394h/a//0v0aqf6K18W/MVf+SdZa63GSsAyXsaS4hNZM3Bti61uwDsHMy4NQq6uN7lzNGc4T6gUlEWFJwWWLWl6Lo3aCfzuwZyiqrjcD9kbx4SeXbuEFYfTmGbgcKkf0mv4SGH2NffGEYu0MLFNiYltmsU5hVK0Ape0qPAcE51073hBlJZ1LI/AdSSTKGcS5yRZiUYzizKy0uxdWlIvm4TOGn8c26Lp2aRlRV6Z2KedQUgvdLl7skBrM94tqkdmmosIW6FAKrA+YAHM6U6nwLi9M21qEM9iqTieGYvbZxqDqroeVIra7Y8xHun6zrXWJEWFbQmkZz9zq1KdZnS6SAFaU1SKUpn3nO/aRGnOu4dGwR4uEpQG37E5mqY0fZt3D+YA9Joe8zivneKmYzzJSzxH4juSvG4jsmVdSWoZY5So1zy0FniOcfBXlTKRUqWJzgpcxXCRorWgF3ps90KubzQZtPz3foI1bEs+88+ewrUtXr7c5+XL/Qud5iussMIKHzdWxPOjYHwC/8V/BL/7XxvbLMDX/gj/5T97jf/jG9/B/7/dpFtcAWDnuZR/9dd/g5sb3U/veD9DmCU5D4YRD4cLlIZ24JjRcy98z6y/D4PdtWadwZmw1vLx6jF1fjQnr0xGY+BaNAO7rvKTzOKMaVyw3W3w8naH41nCLMlxbYubm22yoqLhOMtjPXXkHs4i7h3FzNMCSwpCz1Rw2pZgsxEwnKeczDOKqqITODi2hdaak5kxCAWeqcNUWpMXynSeo5ej6VM6J6jH1UpR1PWNAsF4keHaAilkTaAsHEeY0fU5+55PQgEOAkvoDxwE71gCz5GUSpGfc9sng+krLZYVnlLWc3ABsv6Z058ttcZC1FmpFVmR4dhmNzIv1fvun4paWRU19Tb1lMbwlRUVD4YxrpMxnKd0Gi4bnYB24HIwiamUJspypJRLE1BRKeKsMAYjS2JZllFyc0Wu9XJNwK4vqDxL0vBtBk2PwLeRmLB26g76jU5AnJuLkG7osd1tcH2jxRevrX3svwsXnqMV6VxhhRV+QlgRzw+D+QT+q/8Y/u5/AUVuvvaFr/Ptf+4b/CuHf4/8/3mNZvQbALR2Yv78b/4S37i68+kd7zOiqEzGnmPJT/SDaDhP+YN3TpjGGc3AkLfDacLeOOa5rQ6vXOl/rB+4g5bPV26s89q9EXvjCDCZji/sdNBK8e7hHIGgUhlRWhBnJZYUbHYD3tibMF5kdJseDc9BKY3vmgDxOC9peOZXSGtNVlbM45KoDjh3bKtuwrEoSs3d+cIEpTuC0PPonBqN5sZkMVpk+I7EtQVpUXFmun6uwldpUJWmSIzKKi3BJDJ95AKNxCiJvYZLUaYUz2hRz+oWoA8OXT+GQIhH0UWnY/NTJfNUzbRtI2mWlV6Oqc8SaziNXBL1vqmpywQIPEMerboG9DzI0+/XfZSWbeE7kkVqWpGMat2gVAqda3zXYlLHafWbHuttnyRXjMmW+au3tjpc32jx3TsnREmJVoqigKIyXfChZ6MRNFyLfssnygpG84xAa0Lf4TQUKslKXEvy3HaX57Y7PL/TIc1NUH439Bi0jJIeZQVaszQkrbDCCit83rEinh8EcWS61P/b/xQyY1LhuVe4/c/9Jn+u+Lvs/819wuGv4wFOL+Z/9Wtf5H/88vOfeTXhZJZyf2iiW7Q2I8XdQch2r/GxH3tZKX5wb8gizbk8CJf33w5ckrzkrYOpefyP0VGrtInN2ek38BwJ2hgcilLx1t6U7X4DS0qmUW4c1K6Fb1v0Q4/jecr9UcQ8K3hhu0fTd2pHuuBwEuNa0jjd45yHo4hJlCEEeLakHzos0ooHcYQlRT2iNSRio+OSlRWTKDM931VlWodwkFIuBfSLsFy/1Eb5rDSISlFJvcyKNM/dELZuw+Vknj1zPueHiXDMK/M/Ugi8Oqaobgk1QfGwDHA/ZZaVPr9i8ywBVUpTVoJIFeY5AXmp0bW56CJTjxRmDzMvQQuBFObiIK+rQ13LIisVlpTM8wK7drs/HEbL0XjDs+iGXp2JKbGkoOl7XN9oczhJmCY5eWXyYrU2Kq5vC7qhb6oy1Wknu1m/qAf+VEqx2Qm4uh4yjXNC3+HaRnt57PvjmLvH82U0WNN3uLre4spa8xMz/aywwgor/CSwIp7PgiyF3/6b8Lf+Y4gX5mtXbjH8k/8MfzH8Xb773/+IzoM/unSq/8/+6FX+F1/96ufCqf5guOC7d05Ii4q27yKlYG8UsTeKePFylxd3uh8r+TyZpYzmpvHnyfsNXBtb5tw/WTxGSj8K0rzk+3dHPBguGEcZ0ygnKSpC3zbh3EKw3g5ouHZt8vFpBQ5JXrI/jkkKxe5aSNNzGEUp2/2A3UETKeCth1PGi5SjWcI0zihKsycX1E7nSWzC2KszBEwrRVFVVFqz2Q6Q8pEaqLRRuKrKjJxPCeUpLiJYlcZ0XwvBIi9xU8nPv7DJGw+mRHlBVWlc2yb0K+K0XI6wnyV+6IMS0LLShL5FqRSW1rQCF9u2yPKyjhzSKKXICrN7KgQXxjWZPEyBYwuavjHLJFlJlFeU1SPSyZn/Pnm8RaWxpcBzjYpflgrHFvRbPoFjMY5MVFVamNaobuhT1Hmq8zRjNM8pSqM+C2Ec/2Wl6YQOv/LyNq/vTziepaS5eZ3BXES5dRbqqepqigdcBDBPS6RlSOw7hwvirGB3LaQbejiW5M7RnO/dGaK0plM72xdZyXfePWYa53zxan+lfq6wwgqfW6yI53uhyOHv/S34L/9fMBubr21fIfln/3n+ypXv8rf+zv9A//WfWzrVf/2bPf7XnyOnepQVvHZvjEBwuf9IYWwFDovUuKQHTf9jzdeLsrJWIM//4Gx4DrOkMKNq66MRT6U137874vbRjLIyZEJI6DQcjqeGMA5aHkVpYmwqZXY1k7xklhQcTxOkJemnLk3PIUpL4qykFbhsdRuGgAQOD8cRbx8oeg2PRVYwmuccz2KyQgF6uVOI1pTCZIVGSYHsNLg8aKLUgqO5qbtUpaDSulYHHx8ji1OzzRmY0b3EkWav07E0rmPqHp/baXP3eIFTNxk1/C53jmbcPlqYQHveO+xdnpJl/WwEVAKyHm2ryqxsVBqk0ji2IMoKVG1ZP6vYSsC2jPNbKbNbKrTZzRSiJnKWpFAmA7NSikLppdNfYOo/z9Z8CgFN30ZIgedYFJXGtQTtboPxPKXp2iDAdSRZnTbQ8h36ocs4yllkOWWlmSc5WVnhWhK7aRILPEcwiwte35sihOC5rTYPRhFKwXa3YXrltTYNSLbktfsj8qIy0ValxrYFTc+l3/Qo6tWBt/anOJbk1naH1x+OcWz5WCi879qkRcXtwxkbdWzWCiussMLnESvieR6qCv7hfwd/8z+E0ZH52toW1T/9L/DXv/CQv/G7/zXd/+qX6ddO9Ve/ZPG//xx2qh9NjGHm8uDpD7Gm7zCNc/bH0cdKPC0p3qdd5lEo95MYLVL2xzEn8xSJ2cHc7AY0fffcndDRPOPhKMJzLPZGEQ3PWVYQWlIwWqQUpaIoMzzHNMxM45J5WoI23dy+awws+5OYwLWW7TWjRcbtozlrLQ9LWgSOTafhkOQV8zQnyQ3Bdi1r2ScupARdgdY4tmS0yJCWZBpnZLkhIFJo6jXJpaHotAnnyVpISd3aoyGvNA3PEBql4McPJ7QCB1UpKiTjOCfKK+Q5OuZ5iqNjmWipNCspnoF1nu5tSgGuhEyZ56iUIilNBmldNITQj0LsT8m0VuA6No5nzndSB+ob1VdRaoFrW1RC0ApMsHquFfpUMa3JsRDgWobcW5ZgrdXg5maL790d4daj8lJDnFc0fBtbwDQv0VrjuRZ745iiMusWZf1fjQn2B+g3XeK8YhrnFJXiK9cH7A6aHM9SFmlJUpRc7jfxzlRdrrcDjqYx2/0GJ9OMVuDQ9B2U1nUta5PdQcidowVlpZklxbm/k75jIYTg4TBaEc8VVljhc4sV8TwLpeDb/4PpUz98aL7WHaD/qX+B//TnS/7Nf/xfEf5ff5l+8asAXH4u51/99V/n+kbn0zvmj4BFVmDXzSnnIajNFs8C0y+dcTBJSPMS37XY7DTot7zH7r/f9AhciygtarPFI2itmacFL13qPTVKvHM057X7Q5K8InCM8/sP3jlCI7iy3uTWlmk/ORspM44ySqWWeYxne69dyyLwbAQC35VMo4yjabI0FiltZLduw6PT8JjGGYvURBIdz1LeOZiSFxWDVkA7cNgbL/jhwwlFTZqUNvFHlapqEm0InxCGRXq2hZSwN5wTpSZ8/HScq+u9R6Fq5VMItNDLeCGFIVunamRRKUPo66ggz7FAwzTKjMFJCgLLQiKI0HX4ujkPp6rmk1cDlYKyVCaTVGrT+671U+T38fcAlKWmMsuqKGWU7axSZs+y/rnT83vaXS6XMUuazU6DSmlGi5R5UiKlUUJdS2JZAltadEMHRQZpsXxcC1B1qLuUJuzdtW02uwEN36HhWXX/eUW34XIaPV9hwvi11sRpRV5WhL5DVWmi1IzfQ89hreUjpQllitKSQcvHsSTtwGMS50SZMaXlhSkiuLLWwrFkfX826zS4fxKTFiUbbZ9FVpBkJe2Gy+W1EN+1sSyzZmKJ9/6dnKfP9ju5wgorrPBZxIp4nsX/+V+BH3/X/P9mG/74P88/+KPr/Ks//E9Qf+0bdKJ/AoD2TsKf/81f4utXtz+9Y/0Y4EhpAsYvQFlpbPv9d8kqpfjRgzHvHswoKoVjScpK8db+lBubbV7ZfUQk2w2XK4MWb+xPAJbks6yUiRTy3afUntEi5bX7Qywp2R0E7I8jjmZpXfdYcv94QVEpHgwjvnRtsOy21tpkhEZpgW8//la3LUk7cIyTHEM88kqZsaptYQlBYEuSoqKonT6OJZknBUfThKJSDNrG/WxJYyLRSqO1eqzKUXEaC6TxbIlrCRM3VCmqTC9JsWudmk4evR6lPlXzDPFTwtQu1lGxNDwLoTWVFljSvF6ZqGg3TCh+4NlstH1mccHeKDI7pGmxrNE8bfI5j0tqDaUynfSl1ghlcjfjvDq3leisjlphdk4Lpaly01X/pFkI8SjXU9VMuqgD4itt8kkd25x3W1qGKGrTcLTRDakUTITA92xTE1qUFIVaBtQPWh43NzvYUjCKMhxL4jiSRh2uHmUlSWZyQW0pyStFnJUMmi63LvXIckMgfccirxSd0KNSyvSLS8FG2+domnB/uCAvKzzbpnQgyUvuHi8oSkWv6eNYp2ssGsuS3D6c1R31gqsbLdZbPn7dLuQ7FidJsVRXz0NRqeW+6worrLDC5xEr4nkWr3zN1F3+E3+CN/7YK/y5O/8Bw3/vecKhIZxuL+Ff+vUv862Xbn7mnerPgn7LxxaCrA42PwuljAP4Uu/9R3q3D+e88XBCv+kv44UA4qzkzb0JvmPx/E53+fWXdntoNPdOFowWGUKY+J1+0+eV3f5TbS3745g0r7g8CJgnBfdPIpRSKIzCN5lEtEMX15b8/tvHDGcpSVExXmRMFjlFVZ1rxvAdi41Og7f2J6YmMq9QSpPmhpB4jk2UFtw7qdgdhISBy8ks5WSW4te5na4tOZ6mOLak4TnsjXJcSyAcm1n1qGf7dCxuch8laWH6xi2J6Qm3LdK8QqGwhK77xKl7uw0hVZiMS0NMNFpB4DnkZUVSKCypcbGYJXkdUO7w+t6ERVKYfVNhblM3U77n4qYQYElp6iWVRlgC15ZkZYWuHfdnb/7kruipYvvkmP4sAT3Dz012pxCcLFIsIYmz0kRc1aTStS3yqmKj7Zu9z4YLUtBruKSFYpbkTEoTR1Vp6IU+gWeT5RWWEISBQ1Fpbm61cWzLOOWVcaPvjSOjbroW7dAjdG0ajsUiLZYh/75jkZWQF8YwlOYVszjHdyx2+k2EEBxNY5q+xSwpGc5T8rLi+mYbhKbpu9zYNK51k1XLU+/JolLLtIUoK57aFa+UIi2q5YXVCiussMLnESvieRa//k9z+Mtf5S+M/j1++B/t033wG4SAbGT88798nf/51770uXCqPysGLZ9LgyZ3j+estf1lr3NeVhxNUzbaAVvd997vzMuKO8dzGp7zGOkEY9TJCoe7xwuubbRwbUNuHUvypWtrXNtoM6rjYgLXZr0TnHt+T2bp8tjGi5RJnJGXiqKscKQkKxTvHk5p+y6zNOdwEnNpEJKXpg1mnhQ0fZvQs5cXDEle4lgWDU+QZKbvPPRsGp4JkY/SnElcYlsCxzYK4tEsJXAtlIbnmiZE/kcPxuyPY4bzjKIsl7mUeW0aOW3ssS0zXhc10RcCqnpE7khp4njQWJbAESZYfJoWCAzRzMt6jGwJHAts2yHLS+KsqtVAjS0kQsAsNuT39uGs3ns0zpuzAe6nTvqzl09ndz0tcRq0bnYfHcv00Zvaz6pWec0FyukKQHmGZNqWCXw3ZPp8nI7aLVlndFaaJK/Y6LhYljFLgdl5dG2LnX6IbcH9kwW7gyY3tzpM45ysqBi0PA5di6yoW5qEUcNP73NRh/IfTROub7TxfAulNXFWst4O6IfaRBfVJ0gIQeg5HE0S1to+vmcxz3JQmoNpQlGZnvVL/QZlpWgHJlLrYBRh29ZSlRxHOYfThFd3B2y0fW57NnlZPaVanpLKL+z2macFb+xNqCpNM3BMZmxmyOxWr8FWr3HBGV1hhRVW+OxjRTxraDT/yuz/wn/72xGDN36RLoBd8JvfHPAv/eI3PzdO9Q8CSwq+eG2AJWFvFDOcp5h6RtNP/eqV/nIMeBEWacE8KVhrn1/X1wocjqcJ86Rg0HpcVe00XDqN9++EFrUTHEz4/DTOCRyLdmCU0UIpfMdmfxJTVZrGtrM0eoWezT9664jDSUJZ97UXVYUlJGudgB/eGyGE4NZWmzRXjBYZGoXj2EhpqhH9mvglWUG34ZKXitcfTCiVZqsXkOYlw0XCPM6XHd5aq/q/Zl9SaY1SBbY0Vm3XsiioKCqNLiuqWv30LAuEWQWoy22gHq27tUKWlZqsLOoQdhBILGlIYFqUaKVJKmVyNAHq8byUZ3I0eVx1PN21PN0dbTZcQtdmmuQ4lsULO10ejiIarlXvhQokikzppTJ7ClsYc1qh1NL8dB5O91VDRy7fZ7vrTZ7f7jCcmdD+olKM5xl5pdnsBDi2iSkKXJsXL3WZpwWTRUaSV/RCj9tHMx4MI4bzlLvHc7LCEPZ2w8GzLUbzlLW2zyI1ZybwzP1IIfj2O8dkZcXxLDF7tWguDUKkFBxNEg4nMb5jLZ3oJoy+5OEoYqfXwJWCUmkatoVlGbLoOxa3ttpoNA/HMTc22/z4wXhJVqUUy5D57X6D7X7IrjTj/3snc/ZGMaDxHItrGy1evtx7bFd5hRVWWOHzhhXxPIWGH/xn2wz2+2ih+PKXXf7cH/2NCwnVTwt8x+KrN9a5uZUzqTMNm4FDv+k/U3vQqSnkop9c5ld+0EDIM9jqBjw4WVBUFbfrnvX1VgMpKmzLEFOlNK5tEVclcVYsb9sNPX7pxU2+f3dEUSoWSUHDs2k3XALHRPO0AhcpJb4rsC3BeFFg2xYN12EcZ0yinH7bY61tRv2zxPSpW1IwjTMano1W5gwYuiIMMRMmJqgoNdRd9J5r0XBtNOBYHsN5gpACXSgsIRFSUJYVi7JaKpTSEtjUbVICdK3oKWUqOTsNj0WSmwsHZXY/50mBLUEIQ5pPMy9tKes1hceJpxSmUtKyBA3XZq3lk+QVrmWxu9bkazfXKCvFIi0QhSIrSpMxek7Ek9KQVxVpXl0YDn/2NlVlbrPW9nlhu0voO0yjAs82KwiBazOJMq5vtkxUlBCczIwRrB24tANz8VIUJa8/HIPWjBcpSpsR+en7WGlNUpREWcFXr68bldt30FpzMEn41Vd2mMU594YR/dBlrRMQuuaC5gd3hyDg0iAk9B2OJikPRqYYYJ4WvHM4QynNtfUWax2fvFBEecmLl7qstwMWqdmz/SMvbeFYkttHc/bGMQC+K7mx2eLFM6Ty5d0e1zdbTKIcpTShb9NpuD8VKz4rrLDCzzZWxLOGEII/+2tf4z/5/bf4i7/xa1xbb7//jX5KIOqO6Cd3K58FJhrGZZ4W9M65vRlzu7SCD68Yh77D8SxltEjJigqtzP0usgJLwEY3qBtiTvcoH/9wbriGSK+3PELfQUrBWsun1/S5czQjKxR5qQzRccydmCYhRVEqHFfS9l2ivGKRFuYYhDFEZZkizUsc2wKMY72qx89lrQZ6no0tjWrbClxsKYmygitrPpVWRGlJKU/VQVMfWSm17BhX6jRg3ozj1WnOpTD7qFLk5EVlzFSC+vbmtlKeGXQr0NK0OBV1qL3Uj8brnmMe0JLGua0xWZiOFHzn9hCNGaG7jiQtTcboKaE9yy8VEKXVhRcjpzjde/Xd2qmuzHMXgsd2AISAOKt453BGVWlmSYZS8ObelH7LVI9WSnP/ZEFeKgLfwSpMYLup2xRkRQkIHMsmSiumcYHnSOZpgS0EVwYhr14bIIXgR/dH7I1jorQ0xjTH4up6i81ug7W2jxSC3UEBQnM8TfEdE73UDBx2BiGeZTEsUnzbIkpLijKi5TvEtaHp+Z0uV9ZbTCLTJBXWF0JPInDt5YrJCiussMJPC1Z/1c7gWzdf5ls3X/60D+NzBde2uLLe5Ad3hgSu/dgYMC0q5knBq1f7T5mXnhWVUrxzMKXbdPEcQZTlSEuQlcb04TqSlu+aqJysJHBtmmfWIrKy4s7RnNuHU6I0YKsXorQmKxTd0GOj0+BgkpCXJVlRMosLkyWKJK8qNNAOHYQQpLkhnWWlzd5l7WDPK4XWRmlcpOWS1AEobdTYtDTh5wJjTPFdm81eA9d2uHM8ozp11FvSmIl0HXWkaqe71lR1RNMSGmZxYbrHlRnVNxyjEjq2GeNXj/NOLASOJVDaGMqKsiKvDLmzLcP4hBA0fJt+06Pb8Fhre/yjt46wazf33jhGLssfDZ5sDnrSbPQkLMCxJbYFDd/Gcyxc2ybJK1qBMfFkZYVnW5zMUiaRyVptBw5ubrExCKgqTVYYQ5jnSBxLYAlBlBa0ffcx847rmP1UxxJ4tuDmdptuw0MKlt3op8ro125ucCvOWSRGORcCvv3Ocd0iZH4m9B1e2e3zpj3BFqb//TRC6uE04mSW0g5d9sbRMlbKPo3pwkwatrqrXc0VVljhZw8r4rnCR8bNzTZxVnL7aL4MRy9KBUJwc6vNza0Pn3N6XLvIb2y2QYNtWby1PzENN8o4gY+mCa5t4doW/aa7VI+U1tw5WnA4jmn6DlfWWgSejVaaRVrwvbtDrm60ePtghlKKo1lCnBdojMuemvzN4oIkqyjLCqXNOD7wHJxKoZVCSkPgRK14mtUDM3SX0uRwnjrw47ygHbhcWW8TJcY936zbkrKiJCmViUhSprlHa6BUtZJ5zgmqg+YVZpc0zkssSxA4FqLWMk+NTrJWVNM6dkhr8GwbzzHVlr3QY5EWOI7EEhLHkuz0QzxbMmj6hgg6tglr14qzpmzT/KTJz5utPwFb1oH6ArQWOJbk+nqbSWxyLBdJwTTOl81Sx9OUbuiy3vKZxjnNwOXKWgvXluyNYzqhQ5IrDmcppdIkWYmUEgRLQ5dAUFaKhmdjWRaD0Oe5nYvfl2f3j6OsMMHzpxmpNfpNjxsbHe6fLEhys55x53BOoYw7fbsX1AYpEwk2iQtO5gk7q/D3FVZY4WcYK+K5wkeGbUm+eHXATq/BwSQmqpXH7V6D9XbwTLuiF2GRFFRaL93uN7fay5B2z7GYxTkIUw/54/sTHMuiXY/1F0nBcJ6YgHEhuD+MyEszAg48G63hG7fW+NK1Hn/3tX20Nk7/40lKUud5roc+s6RglhZQ1yD6jk2plNmLlBLPkeRFVRtxJI5nFLxle5EtcB2btO4rD30HrSrGacW4zphsOBa5Z+NYFnFWUuYVUptMTMXjdZBn4dQtPbYtULVrSGuB71mUujCRTQqK2gB0OspuuDbSMlWbtiXZ7jYo6mNzbONGDz2H3bWQdw5mDNoBWVHSbxpyukgKUBpLCqz6PpKsrOn2++N0xG5JyXPbHW5stfn228cMFxkIc54XacGbexMsIdnqBgwXZp/2+kZrmaBQKcXvvXnEza02/dCjLM05TbMcrTQiEDi2pKwqKq1puBauLWkGz/6nL/QcNrsBd47mj5UeCGHas7RWbHQDNjo+v/OjfZoIdnoNhBDLaKQkr9jpN9gbJTy/Xb6vaW+FFVZY4acVq79+K3wssKRgs9tg82MeH4pTd1KNwLW5vtnmzvGMRVqg0KYGUglevTIAYH+S4NqSo0nMaJGZqktlmn1aNXGI85JplPPa3TF//Gu77I0SDiYx0zhHSghth41OQCdwEUTM6zgeHEOY4rwiKytsS1KUGiGN7Ghac6RpJqqPv1Kahmej6v82XJtxVHAyz8iKkjCwmSYFlpC4tiTODDnUZ3YwLxA7KSvThmTV7UgmpqnCdxwEgrysUEot3fG2bfZbfcdinpQ0fAdLCpqBi67NN0VpYp4OZwm3j+akeYlSpt4xLxWWZRRcEwdlobVRVRX6qT55waN2pNNdUOP8l6aFqOlydb3Fg5PI5MnakkVSMlkU2Jag3wzI8pKwVqy7obtUHZXWTKOcrFD0mwFKmbaqtXbAyTylrBTTOKMZOFhC0PHNObm60frA79PrG22OpykHk3jZWlQpzTTO0Ah+/rl1eqHHOwdTpnHBwSRhkeUsEpPl2mo45IXi4WjOOOqzvSKeK6ywws8oVn/9LkBeVqRFhS3lU/mUK/zk0K2D4dOiWu6PdkOXl70ekyjn7tGM3fUW37i5wXrHhG8fTBL2xxHzOMe3JVpp+h0f33n0OrYDl7LSHExjZknJ5UHIK7s97h6ZCBvHkczinLgw6q1tQV5CUVZESYllm+5wrRWz2HR9u45FK3DISxNo7jkWncDsLVqWpF27kkeLjHbg4NmCvIDRLKOqW6IqbRTLs5mbFyUSPeLk2sT4eDYSyEtDyDzH5JZudBrc3GxzNE+x6vrJpKhwSxN7tN72UUpzPM/I8op2aPYjtdbsjRbEWcXRJCYpFJf7IdvdkMNxzMEspaoUuQZZm6dOsznP7npaUiw77k+/5jsmc/TqWhPXkdw9mS8bhowBS5hygDgnL0171Hrb1FaeIs0rJnFG07expFGrBy2fKC3ICsfkeCqjlmshQAo2ew3+yItbF1ZSXoRBy+erN9b48cMxR9OERVIQ5yWBa3Frq8Og5aE0bLQbbHSM8UmnsNkN6DTMezjKSvbHOfdPIrafoZhhhRVWWOGnEStG9QTSvOT28Zz7xxFZWWJJyWY34PpGi37zpzta6bOIXtNjuxdy93jOZjdYhtDbliEuN7e7/MLzm/SaxlEvhSAtzI5gUSlOZhlVbQIatDwqBfM4p6gzL1u+zThKcR2LojIh3tIyMTx+x2SBJllJnJcczVKKoiKTFaFl47k2jjREEQwhFkIQuHY99jaD50VS4QcWnuvg1g1HUVJQKjOWdm1JqiszvgdcW1BULKsmzyOdErNXWVSq3vEU+LZF6NmkpaLTcJcrAL/6yiWev9TjD28f4zsWw3nGIs0Z2hlb3QathsPeMCLJSkLfxpaStCzphh4aOJ4ldXi+TVZWHEwTNrsh4ygnK1VNkk+D1w35tOUj6bOs3e+2ZUb8JpfU0NMoL/m9Nw55MIxpBTbdhkvoP3J4B67NOwdT3j2Y84XdAUleMY5SKmUivKZRzpW1JpY0Waa3tjrYlkDKOSezlFlNXAetgC9c6fFHXtrmylrrQ70XN7sNWoHDP3jj0IT025LAtdkbxyzSkue324S+w70Ts+t8c7Pz2JqJ72gansXD8YIk768c6yussMLPJFZ/+c4gzUu+/e4xe6OYduDQDlyKSnH7cMbxNOFrN9eXweQr/GQgheDVq30Umr1RbMbGwlQpdgKXL1zpL0knwOsPx/z44YRuw+P5nQ73TiJGi5R5VnA8MyYkz7aotHFESyF4a2/Kra0O//jtI/bHMbM4J/BspDAO8JNZitaw0fEZL3JcWyCkIMtL/IbDVjeg4dm8vNtnfxSjMEH1VaWZJpmJlGqY/c1+0zPvq7Yhw3tVZGKJdFmHzWtEXVV5Oro+ayo6VRM1oCq1DHN3LWn2LIuKpu+y3WuQlxXdfpOv3VonzoxifHnQ5FI/pFKaN/YmTKOcSinmSUHom/zO/XGMApK8YBqb9iTftdnoBAgBRVGR5CVrLY+TuYkEKiqFlKImw3WSqRRLZVFrGLTNiPq0uWet5bPeCribzakqhUDQeKLRx7UtmoHNaJHxOz98SMNzaPoOpdKM5ilJXpFmJkpKCEHDs3nxUo/LgyZH05hJVPBzz61zda3FWts/tzr1g+Ct/SmjRcb1jdZyT1NpzXiR8cMHYzY6AQf1qsdZ0nl6jnf6DapSczxNuLL+4QjwCiussMLnGSvieQZ3js2YdafXMM0xgOeY+rv9ccyPH0zov/hsweorfHwIXJtv3NzgZD1htMiolKbpG8PHWdVoluTcPV7QC71lJeHlQWjMMHHOPCnotzwcy5CCK+tN8qLiZJ4R+jHzpKCojBPddy2ipODucUReai73QxDg2iUNz2HQ9LAtQVJU7PQa+I7NTq9Bu+Fy93jOaJEiEEzjHMcWbHUbaMXyfeXU4eVZUZEXFaAplHFQSymQUmBhxtPLkbswSifCqKFFnecphUbYUChNw7HY7Pj4rm0MQr7D9+4MKSrF3jjGQuD7Ni3f4dpGi3cP5wxnCZM4N2UJQrDRbRA41rKpJ2yatqZu6JIXikWZowDXtllrGyIZJQW2LfFsSV6avFEJpJUy51tIBqHHNCnY6YVsdBq8cKlDN/QIfYvDSUJalGRlhW+b11SjWaQ5caYolWJ/ktIOShZpQb/psTMIidOSN/enDDo+mx2ztymFoOk5TG2bbz7f4+s3Nz6W9+EsyXkwjOg3vcfMQVIIBi2fh6OISin6octwkTFaZLi2pFSaoqoYtHyurLU4niUUZ3OuVlhhhRV+hrAinjWKSnH/JKIVOEtycBZrLZ+TWcJoka5Uz08BF5mX5knB0TTmZJZyPE/ZH0e8dKm7/P5Or8HhNKasFErrZW1mu+Ei647wXujyxsMJL2x3iIqSHz8YczJNyeoueMs1dZK2Jbm51aGsKoQQbPUalKXmld0evmvxYBTTbbi8sNNlNE8ZzjMavqlkdCyLWZKxSCoaLlRakZXl0mVuC0mlTJC9qNU7SwLaZD9aZ4Lxy7oK89Swc7qu2HAsug0XpWE0S1nv+lzdaJLmFfeO5rxzOOPt/QkbnQBbSnpNj9CzcRzTDtRpGDLaDz0TQq81nm1xNI1J8oq7R3MUGkvKpUlLVqZ73vds2oEh0q5r9mqTvEQVmhKFsOHBOKasqtq1bvFwFJl2JNui4TnMk4xplON2JBLJJMoYzjPAhKy/sNPBdSRH04TRwrRsaUzl5O/+aJ+v3txgsxOQlxWzpGC97fP8zqP3wkfFJMpJ8nJ57FleYVmCTsO0J3UaLpMo5+pGm4Zn0hTSvKThSQatFv2mV++oimVKwworrLDCzxpWxLNGXlRkZXlhJ7tjS5Q2TTErfDZw73jOP377iAdDY4CZxmasPY8LvnRtQOg7dEOXQT0+7oYejm3Rb/tGpUtLLvVCXNsiSguagcNWP2SjHfCH755wb7hACkGSl0RpydWNFhvtACEF40XK5UGTSmk6TY9XLvdoN0xP+CTKsC2LFy/3uLHZInAtvv3OCdM4I8mLZaXlOMrohx5FpYmzEs8xRDItK7LCjOJ92xDQMHCWMVKOLfGFQApDpF3bjNCvrDUpqop3DmZ15anFGw8mzNMCS0pubLR562DGg6FZWcgfmnYkz7bwXZuTWUo38Fhr+iitKUrFZJGxSAt813SUN30bEMRZhetILvVCkrxcVms6tiTLSw6nJlarFdgEjkNWKpONqgTzpOTOsTETtQOHwLNxbZMGoLQ2TU6VcdH7ro2sg9mbvmN2SbVJJVjreKw1A3xHcjhJuX8yRwD9lserV/pcWWs+Fn/0UaGV4mSWsj+OyYsKqz7evVHMoO2z0fEBwdW1JrM4Z/vM5OQU40VmDF2d1cXrCius8LOJFfGsYVnmg6+oFOd9JFRKgWClVHxGcDxL+N3XD3gwXCCFIRuBa5EWc945mJLmFb/88haObbE7CHk4iojSEqiYxRkN1+HaRpvtbsCDYQRCIOr9v1bgstbxQUCclRzPEtqBx2ansVyzEEKwiM14ueU7+K7NF670ubXVJqp73FuBu/z5r99cp+k7fPf2MfeH5lh826bf9dgbR6R5ReBZeJZFUJnGJ88RywsdpTRlZfZbbWnyPYWUhI7k0iBkrRWw0Q0YzlI0kBQlSilO5inDecpay8dzLKSAdsNFK83JPAXMezrLS5IU/tH8iPujiC9f65PkJQ9HkVFa67D+RWryUwulyNMKLTQv7HQ5GMfMk9x0mXs24yhnu2ez2fEZzlNsW1JWiuNZSug5RuWVkqNpimUZ1TQpKoQUbHYCE4afFbQCm7IyZQRFVfFgaNRr15LM44JB6OPYFpcHIb5jyHHgWKSFUT1Ps0I/DkR5xfEspd1wWTsz9SgqxdEkZh7nfOn6gKsbLUaLjAejiG7oEnp2Hb2UU1WaL14brIxFK6ywws8sPrG/fnfu3OEv/+W/zG//9m9zcHDAzs4O/+K/+C/yF//iX8R1n+4l/rThOxbbvQZv7k1p+U7tun2ESZTTDjz6rQ/eZ77Cx487R3MenCxwbWtpLnIti15YME9zDqYJ904W3Nzq0Gl4bLQDRjLlue1uHaVk2nsmUU6cljRcG9cyCtYiLZhGBUVpajVncY4UdfPPGSzSgktrTbZ6j8b/vmufGw4+aPn84gubvHCpy53DOX/vR3tkRUWr4XJZCjQL5olxidsSQKO0xHeNYmdJkwfaDW0c2yLJSnpND0uaVqHQs7l3vGAa54SejefYS0WuH3pEWcnJPK1NU6CloB24TOLM9NcLYfrkgcNpzN99LeVknpIWFQ3XxrIkvmuhlSZOC6Rlbn91rcWVtSY/vD8mzgomkXGRazS90AVhwvr7oceDUYxnW1hCkBalqbwsK9qOi98w59+Skr1RTOAYwtj0jTv/cJxw53DBLMlxbElUm8Mu9cO6qUgQ5SVJVuK5FtYs5d3DGVfWmnzp2mCZhvBhobVmGmW0fHsZRm/VfyMcy+S2jhYZg6ZP4Np85cYazcDh4SjicJJgSUE39Li+2WZ3sIpSWmGFFX528YkRz9dffx2lFH/9r/91bt26xWuvvcaf+TN/hiiK+Kt/9a9+Ug/7kXB1vcXhJGVvHC8Vokqp+sNU8cpu/yN/gK3w0VFWijtHM0qlGTQejVKtuktcKcVhkvDu4ZyNtk9SGINLJzAXPPdOFqS5yd5MywqtYb0dcDCJl+RpHGWMFiktzzioHVsyjjMCxwTBT+KcQdPn5cs92sGzXUgJYcLb11p+vVNsmnDeOZjx8uU+ZamYJznDeUpVaTqhx1rLw3NsbEtw92hOGDh0Gx6jRUrDtUmKioZn49iSSZRjSxCI2u2u0Upj2xaO0gwzo1bmhdkhLSoTgG8JietIiqJie9BgnhbM4wxLCra6AVVlgtmr+jxoILQtuqc7orbFoO3zK1d2CBybO0czvnd3SL/hIy3YG8fLkPt24DJPcqKsxHckDdcmLUp8bNbbAb/wwgZ3TiJmUY4lBbtrIYeTBM816xCOLQk9hzgryIqSuydzfMdCCkPsXEsyaHqEvkNeVtw5mhO4Fl+oywU+LNKiYrzIeG6ny/44ZrRIcaRECFOlKYBe6BH65k9q4Np88eqAW1sdkrxECkG74Xxs6usKK6ywwucVnxjx/Na3vsW3vvWt5b9v3LjBG2+8wV/7a3/tM0s8u6HH12+t8aMHY05maa2KGfPAK7t9rq43P+1DXAFjqskr0+djP/FBHvoOl/ohaalMN3qh6DfNzt87hzN+781DlNKEno0GWr5Dy3dRaN7cn5AXio1OwGY3IClK5qnZyey3fNoNlygpmCU5VwdNfv2Ll9gdfLj3xO5ayN4oYhpnFFVlesE9aAY28yxnrR3w3HaHaWwIWJpX+K6NqkfejmWZlp5WQMNzSLKCUinWWgGzNKJlWwg0eanICoVtGcXU7Gk6pEVFXilsSyKlWJqVZnGBUsrUeiYl7YaHUppFVpCnJbbWtBsuRVlxNEnYnyQkecWd4zlZXrHVa3Brq43SZk1Ba83+JDZZpAI6gVubf3IQgqxUNWk0u7ih7/LyZZe9UYwUMIky5mnBpX7I0SzhwUnEPMmp6tcwzoxa3QpMhqptSxwjGePaFt3Q5f5JxPXN9oX728/0njOrpQSuzeVBk1IpHg4jSqVp+w5X1lvYlumEP4uGZ68KKFZYYYUVzuAn+hdxOp3S7/cv/H6WZWRZtvz3bDb7SRzWY+g3fX7xhS3Gi6xuLhL0mt5K6fwMwbEk/dDnzWKK0vqpFhrLkvRClxubbX79CzuGRGnN3eM5z293TNakMuStG7oErs3rD8aoSnNts8kiKdEKtjoBSVAhBUyjjH7TrFrc2m7z9ZsbDFofvlBgq9tgd63J33ltDyE0Smu0hpNZRpxWbPYC8tK43NeaHp2GawLbc6P0Ba4NwsQuKa2J84rAtSiUpuXbzOKcRZIT5wVRZt7HSV6y3vJoeg5xZqoxGw0Hz5akRYllCeLMlCaoStHwbYra6NTwbKMQF5Xpkq8Urm3x/TvHFKWm1XApSsXbB1O+884xVzdaJgfVljjSAjRSSIqywrbNekC74ZIWFe3AodVw6YTe0oyjtUJakh/dH5OVFa3AJfBMM9QiKRi0fbZ7DWNEUoZkzpOcy2vNx35XQ99hb2QqTz8K8fRd8165e2TWGaKsYKvXwBJmP/X+cGHC773V34kVVlhhhffCT4x4vvPOO/zb//a/zb/1b/1bF/7MX/krf4W/9Jf+0k/qkC7EaS7fCp9dvHy5y3fvnDBapKy1Hhk9lNLGVS4lL13u0arH4MNFxjjK2eo1zr2IMMHtsNtvYtsWWutlM9BokXHnaI5jSb5xa4OtbuMjq1i2Jfny9QHvHs64czRjHGXLEbllCZK0ZBYXxLWSeW29ycuXu7y1N2UcZ/RCz/TRTxMeDBd0Q0NOK61ZbwcczxIqrQmFS1mZGCBLmEYkxzYd7pYUhJ5tHOyVZi30GM5M+HmBILAl0oLjWVpHFxnkRYUWMIlzykqz0TErB65tUSnNaJHy+oMxr1zpIzDGvEmcU1QVk6ig3zJB7pVSuI5lqj6FYL3+nYuzgv1xQqfhMGj7RJkxSk0WOVIKdgYhTd/Gd2yipCApSsYLwXonYKv76L1QVspkuKYFSV5+pNdLCsGlfsjff/0ApTVb3cZS3XRtiziPSYuKeVrSX+XCr7DCCitciA/86flv/Bv/xvuSw9///d/n61//+vLfe3t7fOtb3+JP/sk/yZ/+03/6wtv9hb/wF/iX/+V/efnv2WzG7u7uBz3EFX4GcGW9xc/f2uDvv37AvWxBu+FAnZuIFLy00+XamWYYpY2qeF5G6+n3TcUly054MATxUt/GEoJrmy1ubLY/tufg2hY/99yGMQA1PYSAe8cL7o0WZo/SsxEC+qHHaJHhOxaOI/EcC8+xcGyL0HcoS0W74fLS5T4PhgvuHs+4ttECjBoXpwXDKMW1LGZJXofFB4wWCaN5RrPh0AtdbCnJSkU7cPAdkNIYivaIKZQ2O40ONAMHiRn/50Lh1y7y4dysDTiWqR89nib8T795k0trIX/vtT3maY7WcDRJyOtc1Uv9ELduVOqG5iLh3cM5eVlxa2sNz7E4mCS0AvP6xlmBlJK1ts9onqEwe6ODts+trQ6eY6GU5mASczRNGC8ylNZ8/+6IRVrw3Hb3sdf3g75eLd8hKSpG8wzHllSVyTvd6jZo+jYPhxFX1ppPmRNXWGGFFVYw+MDE88/+2T/Ln/pTf+o9f+batWvL/7+3t8ev/dqv8Qu/8Av8O//Ov/Oet/M8D89bucZ/FlFWJvonSsvaAWwCuS/6ABdC8Ctf2KHb9PjunSFHk5g4L0FDv+XjOGYHMvBsHMt0ageORZyVy1ajs7AsiUCfq4ZqrSkqRfMjjGovwnavwVa3wTgyMUNRVi5d6EVV0W54tBoOAsHrDyeUleIXnt+kE3pU9bpAy3cYRxkaQ2D3x9ay6lKjcV2bL66tsdNrLDvvQ9/lrb0Jt48MyauUaRsaND2yUvHcdps4r7h/skBI6Dd8E/4ONH0X2xIcTlMatmC8yLl3vDD7okIQ65K8rHjncE6SF/i2zc6gyU4/JM5KZmnBPM6XSupWN2C95ZPkFaN5yiItuLLWwnUsBi2fk1mGUprAtbFtwWSR0w5M7/3N7TbX1lv86MGoHv9LHgwXPBhGCCmwpODGhslS/fGDCVFW8rUb6x8qFi0tKtbaPu3a3JXm1TKIvxu6JLmJcCrqNYQVVlhhhRWexgcmnmtra6ytrT3Tzz58+JBf+7Vf42tf+xp/42/8DeTK0flThyQvORjHHM9MU0u/6bHVazyz0xtgtEj5wd0Rw3m6DAj3XIvdQZOXd3sXfohbUvLVG+tc7of87usHDBcZnYZLt94d/P23j7i20eJL19Zo+g7b/ZC39qcErv1Uj7YEek2zV+k9oYiNo7yu6GzwcSLKCg7GsTHqTFOG8wnzNKfTcIky4zxv+jZFoYzRKcnpNT0u9ZtLA80puqHLwSTBsSUvXu5hSUFemP70VuDU6qmg0/DY6oV8+doav/zSNrM4453DOQcTY+YJHIujmcn3XGsFzGJTQzpPzJi723DptzykEBxMYvJKUSmjEp+NkYqznJN5xht7E7On2vKfIvxxWvDa/TFZqRhHGbYl2a6rSbuhuQDtNFwur4U8OImI8xTftlhkBQ9GETc2OnzlxoBBy0cDb+1NeTiOuH8cIaQmcGx2BiGX+k3s+uLjwcmCS72Q3bUPbgqTQkBtNuw0nn5/V8rUna4qdVdYYYUVLsYntuO5t7fHr/7qr3LlyhX+6l/9qxwfHy+/t7W19Uk97Ao/QQznKd+7M2Q4T3FtCyHg/smCdw9nvHp1wKX+++cVzpOCP3jnhHmSs94JlkpUlBW8uT9FA1++NrhQ+VRa887hDKVNdeWp0agNJk7ncE4v9Lm51eb5nQ6LtODhKKLp27i2ZUbRWcnN7TatwOXO4ZxFWtAKjCFpnhQ4luTVqwMz7v2YMFqk/OG7Q0aLFN+1lp3ysxjWmj6vXB6QlSWjeU6pjbLZb5mmnidJJxjX9TQyGZ5xXnKrNlE9ibxShGf2U9sNj69cf3zKMFqkvP5wwvE0Zb3t0w1N7ulGJ2Cn28D3bOZxgVLUo3n3qRWGvNS0A4eHJxGBZz9VM6u0Jq80ri2ZJwVX15rs9JvsDhr87uvG+ARG2d7pNQg9m+E8ZRrnCC24PAi5vtmkqjSzOOfFnQ6bnYBvv3PMyTRlZxDSbXi0A6euqTSmNNuSPBxFH4p49pumpGCRFk+R6NP3ysu7vVVk0gorrLDCe+ATI55/+2//bd5++23efvttLl++/Nj3tNYX3GqFzwuyouL7d4dMooxLg3BJ+LQ2jTjfvzuk5Tu0z1GGzuLhaMEkyrg8CB8jl6Fnxsv3TxZcW28tQ+KfxHiRcTRNWG8HT7nbXdsi8GzuHc+5ttEk9Bye22oTZwVv788oK8Wg5fPKlR4vXerhORYb7YD7w4jxIgUEV9eb7K612DhTcZjmJWlR4VjyQ1UyFpUy5y5+8txBnpckeYXvWmx2Ay71Naoeg8/iHPec/cThPOXO0ZzjWcJmJ+BwljBLcm5stllr+cvzOokyQs9ms/Peym2/6fPN5zeZRBmLpKDT8DiYxCilifKSqM6lHLQ87p+UNBzrjMqnSYqSrKx4frtDqcyawlkopbh3ErE/jojzAtcydZ0n84zxImOzE/DjhxM6DddEPdUqY6U0w3lKoSp+eG/Ma3fHdEKH7W6D7X6TF3Y6XB6ERGnBzgUXPZ5t1i0+DNoNlytrLd54OAFYks/TRqZ2w+Xyh4zXWmGFFVb4WcEnRjx/67d+i9/6rd/6pO5+hZ8A5olxBIMZeZ51ch9OE4bzlO1e+BjhE0Kw3g64f7Lg4Th6T+KptebhKCL07XMVzYZnM1ykjBbZhcTzNNrnyfH42fuIsoK0qJgsEr53d0iUFVxZb6KUiQc6mCRsdUO2ew12+ua/p2Tp7Jg/ygrePZzxcBgtszE3OgE3NtsfKAXhqD53m53GY+euE7r0WgHDuuay0zCVm1YdhdRrenUep1qqakfTmLf2piyykkv9kJd2e/ROFrx1MOV7d4a8eKlLr+kxiwuEgFev9N/3YgDMWLnf9Ok3faQU/ME7J3XgvEAKk/0Z+g6zpCCvFMNFii1NLaYGdteaPHepy97QGKXOxl4dzVIejhbL7M1uw+XSoEleVtw9nnN1vcl622dvHDFomSag/XHEjx9MmCc5jm3V6qUgTiuGi4y8VCySgrWOT6kuvrDNiuojJVa8dLkHwL2TOZNFZqpWhVFDv3Clf+4IfoUVVlhhhUdYJRuvsESUFhxMEo5nMQ+GEVlRN9tIQeg5XFkPeX6nh2NJpnGGFBfvswWezck0hUsXP57GxBhdNJqslGIeF7yxN2EaZ7QDl81u47GRt5QCjTg3z5PT+xeSOC34wb0hSuunQt+PZwnfuzOkHTiEdV3qk3ulUVbw7bePOZwmdBsuvaZLUSnuHs85mad87cb6Y6roeyFKC7TmqfG0Z1vsroVmr/JozlrLx7Yki9TUd3795nrdn272MadxxhsPp8ySgm7oGjVUG8d/6Du8vT/l/skC3zZ1sFfXW4/FDT0rLvVDlDY7lJM4o9QKS8CtzTZN32a8yJlEGYVSeLbFpX6T3TVjJNrumduOFxmDlk+lFEeTBNe2kAiU0sve89PA95N5xldvrHHveMHhJGZ/HHP7cIbrWPQsj8B1lgSvqBTTOGejEzBcpLQCm9CzmSX5U3vGeWmqLp9lBeQiOJbki1cHXFs3feyV0jQ8m7W2/6EMSyussMIKP2tYEc8VAHg4ivjB3RGTKONgHDOKUgLHZr3jc2OzTak0P7o/ISsUX76+hqijhy6ESSd6T8ja7LI3ip5SirKi4p3DKXePF4AmLyrjLPcdXtntcaWOSuo3PZq+wzwpzlWbpnHGtfUW4yhnnhRcPqcne63l82AYcTBJuLl1/uj8ztGcw2nCpX64JNuubRF6DvvjmDf2JrWymHM0TcjKisCx2Ow2nnLnv1fUzno74NpGySLNqbSmrJXOK2tNLg+aFGXFH7x7wu+9ecgkysjKiq2uT9N3OZ4moOHmVpv1dkA7cDmcxnzl5jo7vcaHjvgRQnBlrcl2r8FonlJWGteR9Js+7xxM+f7dIc/vdHBsiS3NHmWUFiR5xVdvrOFYku/eOWFvFOHaFrOkwJIwLXO2usFjanbTN/3mAN+4tc40znlzb2oc5U2Ptw+nNM9ceDiWRCIYLbI6HSDn6kaTNx9OyYpqee4XacEiKbi+2WLzQ5DvJ9FuuM+kHINR5Q8nsclqFTBoBWx2ggtV+hVWWGGFn2asiOfnALrOoJRCfCL5gJMo43t3hlRK0fRNoPhpBuY4yrhzPOfFnS6uJbl7vGB3zWQuas1jY9+zxxvnJc/vdN73sXcHpjoyzsrlKF/VLUP3jhdsdn2e3+liWxKtNeMo43t3hzQ8h7W2GcNe32zxg7tDhDAVmACzJOf+SYTSmqvrbR4OIzzHOvf8GYVTMo6yp74HRil7MIyWo+8nMWh5HE5i/uHrB4yjjKJS2NKEz/v7U25td3hhp7tUZDsNF0uYEPfzHPuWJfilF7e5vtlGa41Xd5EDaMu0/1xda/L8Toc3Hk7oN30sKSiV4niW0G64bPcauLZESoljyXOf9yTK2J/ELJIC15astwM2OsGFWaeOJZ9y9t/capMWFbcP5xRxbp63UriWxUuXu1xdb2FJgedY3Dmac3+4IC8rOqHLpX7Iett/7JyaixkTzS7q/vV24NAJXIQUaC2wntrllaR5hWtL4qzk6nqLlu9y52jOeJGjtKbpO7x6tc+NzfaFz++TwOEk5nt3h0yjHMcyPffvHMxYa/l8+fra0r2/wgorrPCzghXx/AyjqBR7o4j7wwVxWuLakt01k4cYuB/fS/dwFBFlBbuDJm/tTesRuvlw7oYek6hgmhT0Qo9qnnE8S7m11Wat7bE/idnuPlIBldYcT1Pagct27/1HmpvdgK2uz2v3xsvHU1rz7tGMbtPjxmZnSRREvXf4YLTg/nDBWtvs6t3a6qCU5vbhjHvHC47mKaN5imMJtvtN3j2ccTw1UUPrbf9cEqY0XJSCkxWKvKwujIhybYujacIkyrm51X7stZknBa/dHWEJwc2tNpaUDFqm7vHecMF2N1y61JXSHM9SWr7LTj88N+j8ZG52Xgdt37QRSUFaloSugy1NuPzxNGGz45MUFb5jQuDPQmvNOwczXt8bk2QVnmNRVoq3D2Zc6jX40vW1Z35/WVLyhSt906U+TUiLEt+12ewE9EJvea43OgHrbZ+XLvdMV3xenhtPNU+MY/ysmujYElU3SQnx9MVOqTS+d0o+LXzH5uq6y+VByDwxaw1hnWLwk8Q8KfjD20OyonrMRFYpzcEk4rt3TvjFF7ZWmZ8rrLDCzxRWxPMzirys+O7tIfdO5vWHqUWUlXzn3RMeDCO+dnP93CD0D4ODSbzssS6qCst6xMBsKVFaEWclvdDDloKsKHFtiy9fW+O7t0/YH0dY0pCColR0Gi5fuvb+8UNZUfHa/RFH0xQpBOMo42iaojGRP6/u9s91jbfqsXJZqeUO6kuXe+yuNfmDd46ZRBkvX+6x3WssSWtZKV5/OGGzGzzl6q6UplJquWv4JBxLYFuSvFRYlmAW5SzSst69LFEabh/NebF2xp8iyUvGi4w7xzMeDBdcXW/SbxrSeWnQRAEHkwSlFFIIKq3pNjxevfq4SSXOyuX4/uHJgrtHc/YnMUWpmEQ58bjkch0f5NiSpKg4nMbcPV4Qeg5/+O4Jlwch272QhmdzMEl47f6IwLVZWwuW52e0yPju3SHjKOOXX96m6T/bKPm0Yvb9TDtCmEzRFy91+f23jphGOZ3w0WOkecksznllt/8Y8R20fHzXQgrqtYpy2XJUKU1RKnqhyzwt+NLV/nLX0pLyU1UU98cRsyRn94nEBksKtroN9scJR9Nk5YRfYYUVfqawIp6fUdw5mnPneMZW9/Fu8W6o2RtHvP5wzNdvbnzg+y0qxSx+NH48/YA//VgMPJtJnD92G/HE7U9Jajf0+IUXtmqHe4LW0As9Np+hy1xrzWv3hrxzOGe97bPZbaC1Jisr3tybcjJLl/mLT8I08jwNx5JkheLKRoveE4Tj8iBkfxzxxsMp/dBfqoxlpTiYxKy1fTYvMAf5rs12t8EP7g5Ji4ppnDOcp8zTwhBGpaiUZhyl3D2ec2WtSVpUvL0/Y57kCCHYG8dMogyloR04XN/ocGkQ8tUbayRZSaU0rcBhsxM8FsR+73jOjx6YYPmqUry5P+XBcMHlfsh2v4FnNbh7MuetvSmtwKWsKmZJzpv7E9aaPruDkHla8AfvnrDWWvCV6wPunSzQmiW5HUcZ908WSxPTPx4fE+cVX7jS59ZW52MNRD+aJhzPEhZZwbtHM1zbYq3t4zsm1P/WdofnnljR6DRcrm+0ef3hmE7gkuUxJ/ME17KI85LQc0jyit215nL397OAo2lCwz0/seH0Qm0c5VwefAoHt8IKK6zwKWFFPD9laK2ZRDnHM6NoebZFv+lx72RB03efGsNZUjBo+uyPY6Zx/szxLZXS3DmacedowSzJ0NpEDe2uNek2PO4czeg1PXqhx8E4MY52W7BISsZRTjhLSLIC33Mec297jsWlfgPPlkzjnLwyLTSOLd/T5TtaZDwYxqzXe5pgFDHfsbmy1uThKOJgEnN94+lu9HlacHW9+dSu3jTOmac5W+eMcF3b4qVLPX78YMzd4/ly/CyEMfR8+frae5o9tvshf+9H+5zMU/x69LvW8sgKxSTOcS2L0HXYG8W4tRM9So3h6cEwIisV1zaaBI7DaJGSlSUPhguEMCaa85z9B5OY794ZYluCS/2Q42mCZ0t6DY9RlNPwHNbbAVfWmvz44Zi9cYTAkJq1tkvgWcS5YrPn0m967I0jvntnSJyXSzV6nuS8e2AyTbsND0sKjmcJeVHx2t0RAnh+p3vhefkguH044wf3RhRVxVa3QSdw2Z+a9/H2ToMvXjMtRE+mEwgheOlyF9eW3D6ak5YVw3nKIito+SZt4fJai2vrrQ/dw/5JQL+Pwa7e2v3JHMwKK6ywwmcEK+L5KaJSmtcfjnn3YEZaVlhCLDuzJ1HO89vnm3Mans1okRFn5TMTzzf3Jvzo/hjftVhvBwghiNKCH90f0w1dbNs4g7uhMabcPZ4zjTOmUY7nWBxNEvaV5tpmq47vMYriIi34/p0hB9OESqnaFGLGo1+6uvaewe95WRG4T6uM7cBlreVx52jO7uBxgjmtDSxPRiKBIfH6PXY1m4HD9c02L13uLc1a7YbLxpnGpIuQ5iWd0MV3Ld7cm5qaTSHxXJtbbZ/7w4h5mhN6Dg9GMUopWoFDnBmFtNdwCWpVr+HaTOOCFy412BvHHM/Sp8iy1po7x3MqpdnoBGht9j8D12G9I40ifjRHKc0szSkqRVlV2JZF6Ft0Gi6h73A4iU1daK/BRjvgYJKA1ngtQ9COpsnT2ZYCQt90ob97aBRc/yPuFE+ijB89GOPacnnh0mm4bPdDRouMrDRRTOdFYoEh08/vdLmy3mIaZXWovnn/HU4TDscxB+OYXuhyZb31kVz8HxfWOj4HkxjOEWErZQyDncbKXLTCCiv8bGFFPD9F3D6c8aMHY/qhx/oZFfF4lvLGwwmdwOXqxtOfWpXSCHExwXoS0zjn7YMp7Yb72N5lu+ESuDaH05jdtSbDWcrDYYTvWhSVMh3lnsNmN6Df9Ew7kITv3Tmh4dp0Qpfv3jlhfxyz1Wk8Nr4+mib84e0TfuGFzXONKhouVIOkFFxZa3FvuGBvHOPWMT1JUeI7Fq/s9pbkJcoKRnOTp6i1xncli7Q8d790kZa0Gy43t9of2NBxPE3oBC5+x2I4T2n5DlJKfFdiCckkyhlHGZ3AZRrnIEwD0N44RmtNN3SXqqbnWCzq9hylFSfnEM84LxnOUtoNp/45TV4qsrKqx/eaWVzy+t6ERVpgCUHgWjR8h9BzGc5Tovo8HE8TNjq+qTUFXMdinhRUSnH3eGHSAhaZWY8Q4FgWDdem4dnsjWNGi4yd/kf7U7E/iYmzkq1eYzluL0qF61istXzTWz+J3zeiyHcs/PpcvXMw5ccPxigNrcBBAIeThP1JwsuXu7yw0/1UyeelXrhslDrbIKW05nASM2hdvN6xwgorrPDTihXx/JSQlxV3jueEnvOUgWat5dEJXe4ez7m8Fj41hp3FOS3ffWbjxPE0IS2qp/qywTiGTVQR/OKLW+xPYu4dL2j5Lr/6SscEk9vWY5E+p67yvAw4nCRsdxuPqZK2JdnqNXg4jDgYx1zffHpc3nBtBGY/sqw0o0XGOM7QlabVcMhLxddvrHOpH3IwSSiU4nqjxXavQb/pUynNW3tjbh/NidLCKK1SMo9zkjziynqThmfjO+YtnhUVUVpw69rgQ7mIldbL+kbPsQh95zF1rttwmSUF90dz5lGB69pYQhBnJd3Qe8xEUymNFGAJgSUkpVJPPZ7W5jFPo4OEEBRlxeE4NtWe3RDfNXufaV4RuBLfsQkcG8eSeI7NPC0QmXmNi1JhuRIEbHUbfO/OCcO6btS2JLO4QFrmmJ7b7iCEUSnnSf6hKybPYhbnSCF4Z3/KyTwzFxOWYB7njBcZtpSczFKe33m2+5vGOa8/nOA51mO/B2Gd6frm3pT1dvCRWoo+KtoNly9eHfCDu0Me1HFeWkNeVQyaPl+8Olhlea6wwgo/c1gRz08Js7hgHuePKZ2nEEJwbb3F9+4O2RvGJopFCrTWzNOCOCv50rVn/9DKyurCESY86q/uhh7d0MOzrQvD1uGRq1wIDec08IBxOnuOxcEkOZd4rnd8+k2Pu0cL5knOPC2MIifgaBZTVZrntjpcWW+daxh5c3/Ca/dGtAMTPSSF4HiacDiNOJ6m3D8xVZyDlkcn9HAtyY2t9rnH8izohh53jxd0Gy6+Y5Nk5fKCIS8rjmYJvmOjlMBxbMpSmR77fsO44cWjcxRlBYOWj2ubisnWOe7xwLVo+g6LzMQTnWa4ZmVFJ/RQSmNLQVVB6NlYlqDUmpbvEOclnmNUy0Va0PRMG1OUFfg1ada13CylIbi2Jchy8z45madM44IkNyHwLd+lVIrntjsXtky9H2xLsj+JSfNymTsKgGcU8rvHC45myTPf3+EkJs7Lc1cuWoHDNM7YH8efKvEE0/rUDlz2xxGjRYasd4q3eo2PNRJthRVWWOHzgtVfvk8JZpPz4habftPnUq+JZQkejiMkoDBK4ctXeh+IQPmORfU+/dX9M7uYWlMf3fkQolbklL7QeQ5mZF6do+aBMfu8cKnLD+4NGc4z1js+tpCkZYXv2HQ6LoeTmJNZuszrPEWUFdw5nNMJHrXHjBYpd47nOJZFt+nRb/oIjInJsSy+8co21zZaH5o4bfUavHM4Y54WbHR87hwtlmrx3eM5WanZ6rooDbe22igF3783ZJbkuLZxXxtCn2PXQezjKKcVOOfWWFpScnW9xXfePSYtKqQwe5+d0GWe5FRK0wwcSqXQwpA337UIfJu8UsRZQeDaJHlFw7OplGI4z7ix2WY4T9npN7i52ebtgym3j+a0fIew2+BwEvNwGHFrq4Njm31g3xX8/dcPeO3uiI1ug9C3udQLWe8Ez+x4b/kO4yil3/Seuo0Q4DmCNKtIi+qZDEKLtHjPvVzPsZglj9IZtNbMk4KsrHAsSbvhvufF2MeJVuDQCro/kcdaYYUVVvisY0U8PyW0fIeG5xClxbl7bYu04PKgyTefX2cSF2SF+cActPz3zcd8Euvt4L37q5Xm0hl1sxU42PLiZp1FUnBlvUkv9HnnYH5hT3qSldx4D4IsMGsFG+2AaZyjNfUuqU839NgfxTwcLZ4inqN5RpSV7PTNrl+lFA9OIpTS9Js+XlaiNbx6rY9E8GAUGdXxQ5JOMIanV6/0+f6d4TL66GiWMouyJRmVQnJpENTmLUD0+OH9CUWpOJzEAPSaHhudgHma49kWr+4Ozs0qBbiy1mQSZdw+mlNWZr+z6TnMqhzLMqkBZaUJPQu0QErT4rPVbXA4jTmcJhRVBRrmScnNrTa7g5B/+MYRvaZZofjClT4Nz+F4Gpuay6JEYDJVB+2A7V7I0czkTe6NYrQQWDO4e7zgxkaLL1zpP1MTUNN3CBybOCvxbHtJGovKKMMb3Qa2LYhrVfb94NRq8UUoK41X7xyPFxlv7U85nJrsU0tK1js+t7Y6jyU0rLDCCius8MljRTw/Jfiuze5auHSanyV4WVExTwpevdqn3fBof0Tn66mh5of3x+Sloh2Y/cRFWjBLCq5vtB4ztxjTQ4O9ccR2L3xMoZrFOZYUXB40aQcunYbLySx96gN8HBmzyvY50UanWKQFnmNzedBE1Y70s48V+jbH0xSt9WPKcKU0gkdkd5YULLKCbn2eLGmIh1Jg24J24HD/ZPGhTEVncXnQXHaJH05itnsBw7nZk7yx2aYTurR8Z3ms270mUlgUVcW19TbDRUpZKRzLOLsvD5pLUh1lBVFqmojaDRfHMmrql64N2Ow0uHcy42iaUFWaF5/vEbhmX/DO8Zx5ZHrdj6Ypi6TAdy2avo0UsNUN+bVXd1hvm050kyX66NzZluTGZotOw+EPb59gCYFGsN0Pub7R4nCScDxN2WgHjKMMWwq2ew3SouKtgylN3+HWBekLZ+E5FpcHTRaZWTF59HqbNqntXoMkV8+sQq63At4S03MvjsrK5KpudhtMooxvv3PMNMnohz5+0yKvFAfjmEmU8/Wb6yvyucIKK6zwE8SKeH6KeG67Q5SW3D9ZIKXAc0wAutKaG5ut91QLPyie3+niOza3j2aMFiaOplSGBA3nKb/7+j47vZBL/ZDQd/jC1b6p7BxHuJbEsiRpPS5+ebfHZsdEMr16dcB375xwf2hacgTGke3aklevDC6MUwKzZqDrib4U4imXu9Ig5NPrCIFrIeoudKP6KThDWrNC0fBs7LqByXPMDmtRqadIyizJORjHzJMCyxKstwI2uhfHK53uwb6y2wfgjb0J378zZHft/PYZz5GEns3Xbq4Zg1BlIqekFJzMUr57+4TbxzNmUYFjSwLXotPwuLHZ5sp6E0tKLg1CLg1CNjsNvnP7hF7oLfd7b0jBmw8nHM9Tbm21uDRoUlRqGaz+889tPNaME3oODc/sfp6acuyaCG92AkLXxvdsbm620cBwntL0bezTusr6BfMdi9CzuXu84OpG633jqE5jq8LUZnfQXBqWQs+mGTgM5ynd0H1mNX+943Np0OTu8Zy1lr8sLEjykpNZyqV+yEYn4Af3RkzijMv9R+1BvrTY6Yfsj2Pe3Juw1n46O3SFFVZYYYVPBivi+SnCtS2+emONS/2Qh6OIJC9Zb9vs9EO2usFHGg0/CSkE1zZaXB6ETOOct/anPKgbbACitOR7d4bcP4n46g2Tv/nN5zc5mMQcTmKKStOtldF+0zuj6jUI3E326hxFjebSoMOlfvi+xo5Ow12O9MEQRiEgcE3eZZQVXNvoP3W7Qcun33TrGKLgESmqsxHzquJqu7kkE3lpqjWfJEf3jue8dn9MlBa4tqRSmrf3p2z1Gnzl2tqFI3CtNcN5yt4o5mAaM44y1toBgXvOWkJWcHOzszxfjiVNHeq7J9w+nBnFMinwbItO6HKpH5LkJd9595i8rB4Lb7+y3mIS59w+nGNbgsC1TZOU72BJQTf0KSqjZl7uN3luu/NUHaPnWFxZb/KDuyMa3qP+8lO3/uEkYXe9hedYTKKMtKgYND1UvfXrnHlPNn2H8SInOkNiL4JjSW5stvnOu8d4jsVWN6gvPDTTOKeoNNc328/8nrekUYNtS7A3ihgtUkDg2mY39pUrPbPiMI7pn+mMP4t+02M4T5lEGf3mp2tCWmGFFVb4WcGKeH7KsK1HitZP6vGyomJ/HNNteo/1vfeamoNxzA/uDfmlF7fwHIur6y2uvk8N4akK+PLl3gc6ltN+7+/dGQJmPC6FoOGZ1YP1js9O7+lRvW1JXtnt8wfvnPBwFNGoXd0HkxjXkWx2GgzqEbbSmmmc8cpu/zG182SW8r27QywpuXymS7usFPujGFsM+bnnN59SwrKi5Hd+uM9r90bM08IEuCc5947n/NxzG2yc6YGfxTmOtLjUf/y1/eH9Me8ezhEIpJBcW28jpckZvXcS8cJOl9CXvH0wWyrQp8/7i1cHrLUDHtQVl4Fr80svbrHVa5AVFXmhsC1Bv+VfqELe3GwzjwvunSywLUM480KhgVbosnbmguG0njRKSwLXWXakA8uLlmfNyryy3iQrK97Zn/JwGKHr+276Dl+80mf3fX4HKqUpK/P8LCnxHYuv3Vjn5mabWV3z2gpcuqGLEIJJlFFUitYF2aCeY/Jq8/LiXdEVVlhhhRU+XqyI588g7g8jgMdIJxhVdL0TcDxNzm3T+bhRKUN20rwirypcS6KBcZTiORYv7HQuVNLW2wHffH6DeycLE5vTDCjKiF7ocWnQQNbxQaN5xno7eIo8PxguyAvFpcHj+32nY+f9ScJwnj6Vffrffu8B//jtY9qBY9pxEAwXKfdPFvzOD/f5xq0N2oHDcJEuHe7hmd76WZzzcLRg0PS4fTTHseRyRaDlm9sdzxJubbW5P4w4nqWPKa+2Jbmy1uTKWrNuTxKPiN8zriqeKu3bvQYPRxFRZqo9X73a53iWcP94QVbvTkopOBjHNDyHaxvNxyK8ZklON3Rp+s/2Z0QKwQs7XXZ6ISezhLwybUXrbf9CdRlMa9S9k0VdPWpqZS8PQnbXmgSuvbzweRKnta2nxrwncfp11/74JgsrrLDCCiu8N1bE83OIaWzGm0IIeqH7geoMy9pFHF5AFhxLojREafFxHe6F2B/HHM8Sfu65daKsYpHmKGVG7ULCODLP8yJScko4XrzURSnNyTzl9tGc0TxlrHI8xxhnntvpPkayK6U5miU0L9gn9ByLSilmcfEY8bx/suAH90b0my698JEquNVt0PRt3j2YsT9eMItdikoT+hZ7o4hZUnBtvcVz2x0mcU6aV/RDf7mjehYN16QPnKq/xXs4tz/KKoZtSXbXmk/tpl5Za7LW8rl7vCBKC5qBTVkpdtdCNs/EPs2TnKJUHyqiysQLPdsuZ5QVfOdd047V9G082yItSr57Z8jhNOGrN9YIvfPvK/QctnoN3j2cEXr2U8rscJ6y2Q2euYhhhRVWWGGFj44V8fwcIcoKfvxgzP44JivMXmTTd7m60eS5rc4zxdoIIRDCZHBehCdd5J8U7g8XdSuSjefYT2SJ6nMVv/NwOkK/PGiy3QuZxqZC03Osp+Kj6nt/hqM7HTI/wu3DKXFWstN7eiTc9F26LZ/RIme7F7LVbeC7NkprFknBD++PqJSmXRMuKc0+YpQ+3gokBGhlqjQ1+n1NOx83bEtyc6vD1fUWcV6ilemMv3Nk2qpsKZeZoS/t9i40VX1ceHt/yv445lK/sSS4IQ6dhuLhKOKtPYcvX1+78PY3tzqMFhkPRhH9pofvWOSlYlRXhD6/010Zi1ZYYYUVfoJYEc/PCbKiWio/ay2f9XaAqkOxf3hvRFkpvrDbf1/CaNVxOG88nJyr9CR1603vE1aBlNYm0/GCzEbzPDQHkxjHkji2pN/03pdcW1K8r1HEkpK1ls/toxmdc/b/8rLCkmZf8CzivHrPwPSyqJjFhniePi8pTDySlILbRzNevTLAsaxlhekkmlKpRxmjaV7RbrhEWUnTd1jvfDqmF9uSS9L+asPl8qDJ0SwhLyoC12ajE9BpuJ/oBUqUFTwcxfRC7ylV1ZKSXuizN455bvtiVbzTcPn6zXXeOZhyMEmYRTm2LbnUD7m11XkqI3aFFVZYYYVPFivi+TnBfu0aP6v8SCGWzvA7R3N2B81nGhvuDpo8GEYcTRPWWv6yfSgtKo5nKTc3W4+ZSD4JSGFc2eNFdu73R4uU24dzpnHBg2GElIJew+X5S92nzDofBpfrczCJssfOWaUUR9OEnd7TrvxW4KA1547INZpRlJkMznN2Bo0DPKNSis1ewP2TBRttn7WWx/Eso+EZomrqTSEvFK9e7V84Rv44kOYlh9OkbkYSDFoevXMc4OZ7/k+8fjLNK9K8pHNOsxNAw7M5nMQkefWeqng39PjazQ3mSUFeNxe1AucnouqvsMIKK6zwOFbE83OCB8MFvmudu08X+g6jRcbJLH0m4tkNPb5ybY3X7o/YGxujkdam9ebGZosvXBn8RD6UdwdNDsdx7VR+9LwmUc5r90aUSnN13QTVl5UZj37n3WOkMKrtR8FGJ+DVK31+9GDM/RNzbqvKZJtudhu8enXwlLp5a6vLPwoPOZknbHYbyDPBo3FWUCrNlbUmAqMcnz6vZSe3MNmkX9jtL6N+WoFLoRSHExMOv9ENuLbR5sZmm8ufYNLBw2HED++PjBtcmKUC1zJRS6/s9j5S0P7HBUsa93pZac4Tuo1SbBqbngVmr/STI/IrrLDCCiu8P1bE83OCND/fmXsKIaB8j73NJ7HVa9BtehxNE5K8RApBv+nRa3o/sZ23nX6DS4OQ+8OIXugSeqZ7/K39MXFW8uqV/nLce+o2P5zEvH0wZeMD9IRfhOubbXpNj/1JzDTKsaVgo9tgqxucS7zWOz7fuLXB7/74gIfDyDRAScE8KUjyimvrLXzH4q39GdM4o6w0tiXohd7SmOM5Fk3f4edubXAwiY0jv+2bsP3QY63t02k83Wd+FnFWsj+O2R9HVErTCz12+iGD1vl5lU/iZJby3TsnaA07g3D5eid5ydv7Uywh+OK1wYc8qx8fWoG7bFs6r11oEuV0mx6dj9jstcIKK6ywwk8OK+L5OUGr4bI3iuieI4IprSkrzSLJ+c67x8RZSeDZ7PRCNjr+ha5j37G48gmbQ94Lrm3xlesmqP3hMOJgEpMViixXvLzbY/uckXqv6TGap0zjjyf0+6IonvMgheCbz2/R8BxeuzvkYJpQVYpOw+PnbnXphC7/zR/er8mmT+gZV/rBNGZ/EvPcVpuNeqfwWTNSn8R4kfGHt08YztNaARccz1LuHM956XKXW1ud9yWfd0/mpEXJpf7jr33g2vSaHveHC65vtp/Zef5JwZKCm5ttvv3OUd1sZAi5UppxXf158//f3p3GxlWebwO/zjZn9vHMeI9XnISUJfCHAC+Iqk1BUFS1gFQkJEShC1IQRSCkQqFS4UOrVBVSpdINVCkgukAXBYRUKvKBpX8hRFOSN7xshSzYidcZe/aZc86c87wfxjExnnFsJz5nbF8/yR8y49h3Hox9+Znnue+O6Bn/AkJERO5h8FwjehIhHE8XYFj2ggs5J4PYx+NZ6KoCn6ZgMlvGp5N59LeFcWF/sileOq3H71OxvT+Joc4oSkYV2ZIJTZXQ2RKsu/OqKjIspxa0vaApMi49pw1f2BRHbnbmeDToQ0hX8eaH4wj7fbBsB4ZlQ5IUABJkSUK+YiGgq8tqffV5VdvBoU/TyBQNbDplpzIRrvUHfX8kg1hQX3T2uFm1MZUtN7jtXxthmSkamCkangdPANiUDKHqtOKjE1mMzRRxsttANODD+b2Js3Lel4iI3MPguUZ0xgMYbI/g8EQOQZ+KkF+rTc0pmZjMliBBQvcpt6mB2k34IxN5BP0avrBpeVOF3BbStbk54v8d1VCxbITrHC2omDZ0tTa1xktBXZ2bDw4AmaKBdMHABX1xFCoWJrMVVKwqJElCaySAwbZIbVe6Yi1o3L9UU7kK0vkK2mOBBaE8GvShUCliJF1YNHg6ovamNdgVPblbKoQ3wb6e/rbaqNZUrgJztrF9Mur3/GuAiIiWj8FzjVDk2rjEWFDH8FQe+bIJSQISEb02FjCgLdgJ1TUFkYCG4akCBtujnv6grlg2ykYVsiwhEtAaniMN6bWJQB+PZRH0qXM37oHakYLpQgX9bZGm2I07lVl1YNoO2vTaLwWt0QAs24EEzM2Bn5oNTiu94FKoWKjaDnJlC7miiarjIKCriId0BGc/bzpfgSNEw/X1qTKigdpltHo3wQ3LhqrIq3qbfiV0TXFtrCwREa0eBs81pNbcO4r+tjDKZq3tTtmsIp2vNNxFiwQ0TGTKKJQtT4JnxbJxeDyHkVQBFeuzS0yD7VF0J4J1zyNu7oohUzRwfLqAWFCfnSVuI1sykYz4sbW7pela4WiKDE2WYVYd6JoyeyP7s/U2qzY0VYKmrPy/gVm1MZIqQJJr19AVWYKVcTCmKehtjcCnyVBPsy6yJKGvLYKJbBklozpv19aZDcfdiSASEV7YISKis4/Bcw1SFRmRQO1laKNqA5AazuIRonYqzoucZlZtHDwyheF0EbGgD8mIH7YjkM4bSOUncbHdioH2hZdrwn4Nl21ux7GpPEZSReTLJjRFwbaeFvS3RRqeT/RSLORDa1THZLayoNWTmN2p7WuNLHmu+ecJITA2XUKubKErHvysRROAgmHh2FQesYCGy7a0n7YrwaZECJmuGA6P55Ap1ib4VG2BsllFW9SPC3oTnOZDRESrgsFzjYsEfIgGfMiXzbq3vHNlC5Ggz5OXpkenSzieLqIrHpxrBaUpgL8lgOmCgQ9PZNDZEqh74Sbk13B+bwKbO2Mwqw60JjjXuRhZkrClqwXZ0hTGZkpIhHX4VBmGZSOdNxD2+7C5K7rindqZooFCxUJvMoRM2YSmyHO9T0M+FcPpAvTZiTyno8gSLuhLoC0awPF0AdmiiYBPxhd64uhOzA+1REREZxN/wqxxmiJjoD2Md46moGvWvLN5JaOKkmFha1er67fahRD4dCoP3afU7T/aEvJhdLqEyVxl0ZZOuqY0HKt5KsOy5y6faKqM1mjA9aDaHgtgx1AbPh7LIJUzYDkOfIqMTckQtnTFzqj9U65koeo42NLdgmOTOUwXjNputgQ4DhDxa2iZPeu5FCeb8C+nEX+ubGJ0uoiJbBkQQFssgO54cMntqIiIiBg814GB9ijKZu0s5XTBgCbLs6FHwbmbWjDYsbxekWeD7QhU6rR+OkmencVuWvYZf67hqTw+Gs0iWzIgUDtaEAn4cG53C/rbwq6eB22PBdAa9SNbNGHZDnyqfFZnmuuags1dLciXTeTLFhwhEPCpc1N+Vsv4TAkHj6WRL5tz4XYyV8axiRy2DyTRk/SuHywREa0dDJ7rgCJLOL+39jLpRLaMilmF36eiPRpAIry0aTYrZTvOXJsfRwhE/D50tNR2G3VVRsGo1v17jhAQQN255stxYrqIA0fTUBUJXfHQXIPxTKnWaF2RJfS63CRfliTEw2d3FzAS0KAp8lwf1883vh+dLqInGVh0utVKFQ0Lhz5Nw6za89YyCSCdr+DdT6cRDfgQDTbf2VsiImouDJ7rhCRJSIT9Z2Waz1KVjCr+77EUxmZKcy18bEcgFvThwv4kelsj+M+RKdghZ8FuXL5sIaxraI2uvF5HCBydyAEQSEY+610py7W1mMqVcWQih+5EcFV3A90QD+voaAliJFVAVzw4b7Z9rmRCkaXanPhV+CVjMlNGtmTWbWdYtbniAAAXcklEQVSUjPgxnCpgbKbI4ElERKfF4EkrYjsCh46lcDxdRGdLcG7n0hFibhb4JYOt6IoHMTpdQjysI6SrsB2BbMmEYdm4sD9xRv0icyUT6bzR8IxhS1BHKl9Bplhrw7SWyZKEC/sSqDoOxmdKUGUZiiKhYtnwawrO643PzYM/22aKBjRFbnjTPeBTkC4Yq/K5iYhofWHwpBWZLlQwlimjoyUw7+VyWZLQHgtgJFVAKl/BJee04r+jWYxOF5EpmVAAxEI6zu9NoK/tzF4Ctx0BRzgNZ3UrigRHCDhNNIXnTIT8Gi7f3I6JTBkTmRLM2TnxXfEA4qHVO1Ihy9Kia+g4gMp56UREtAQMnrQimdnJOY1uy4f9GsamSzivJ47/GWzFlq4YSkatgXws5DsrZxGDs7PPS2a1bm/PklGFX1PWVXsgn6qgtzXs6rnVZNiPj0UWtuPAEQAEoCoSJKkWSM2qjbbo6uy2EhHR+rJ+fiKT6xbb45IkQEDM3TIP+7UVzyhvJOBT0ZMM4YPjGeiqjIrlzD6uQJFlTBcMbOmKnfXPu9F0tASgqwre/ngKqiJBliWEdRWJiA7DcpCM+NG5jLZMRES0cTF40oqE/bV561XbmXfR5aSCYWGoI7biCTi1aT8GJrNllGdv6XfEAoiH9Xkfc7A9gg+Oz+B/PxiHQO2Gv6JICGgqzu+NY2tXbKX/RJo1NlNCxaqi6jioWDaEAKayZRyZyGNrdwwXDSTW1a4yERGtHv60oBVpi/qRjPgxmS2jMx6cFwazJROarCxpik49tiPwwfEZHB7PwbRtaIqMqu3g41EZgx1RnN8bhyLLcITAkYk8bEegJxlC2bBRFQ6sqoAiS9A1BX5f8047WgsKFQvvj8wg7PfhynM7kCuasy2yamc+VVmuvfxORES0BAyetCKqImN7fxIHjtZutgd8CmRJQtmsQtcUXNAXR3tsZef+jk3m8MGJGSTCOkL6Zx+jZFTx39EM/JqCrd0tmCkYODqRR0csiKCuwnEEbKcWOquOg4lMue7sdFq6iUwZhYqFnmSo1rIr4kfilHkEJ9JFjE2XeMaTiIiWhMGTViwe1vF/tnZgPFPC2EwRVUegvy2Mrnhoxe2LLNvBsckCgj51QauloK7CsDR8OlXAQHsEk9kyLNtGcDacynLt/CEA+OTaTufoTJHB8wwUKxZURW54Y97vU5AtmS5XRUREaxWDJ52RoK7inI4ozumInpWPly+byFdMJBs0wo8GNUxkysiVLFSsKtRFGsP7NAXlBpOTaGkURYLtOA2fr9rijKdPERHRxsHgSU1HnLwKX9dnT/h9Kiy7cSgyqzZCLtxotx2ByWwZJ6YLyJUs6JqMTYkwOuNB+BvMql8r2qIBfCRlYFbtBa2zbMeBadvcUSYioiVj8KSmcrLtUqFiIV5nIlGhYiGoawgHNMgy8LGmoFixFgTMimUDkFY9FNmOg/83PI3D4zkAtRZPhYqF0ekSOuNBXDLY6kr4XS3JiB89yTA+ncojGfEjqNe+ZRiWjclcGZ0tQXS2MHgSEdHSMHhSU/GpCvrbwjh0LI2AT523Y2hYNrIlAxf2JeHXFOiqjKHOKD48nkHFshEJaJAkCYWyhULFwuau2KpfehlJFfHxWBatET/8p7QUsh0Ho9MlvK/NYMdQ26pNFVptiixh+0ASiiJhdLqIdKECCYCmyOhNhHBBfxL6Gt/VJSIi9zB4UtM5pyOKolHF0ck8AAGfosCs2gCAoY4ohjpr50klScK2TXEEfSqOTeYxUzAgAIR0DRcNJHFOR7ThOM2zwXYcfDqVh19T54VOAFBkGcmIH+OZErIls+E8+bXArym4ZLAVQx1RZEsmhAAiAW1BT1UiIqLTYfCkpnOyVVNXPIixmRJKRhUBn4LueAhtMT+UUy4UKbKEwY4oelvDyJctAEDIrzYc5Xk2VUwb+YrZ8KX0oK5iumCgWKmu6eAJ1EJ+S0hf8/8OIiLyFoMnNSVFlpZ1flBVZMTD7oYiSZIgQapdhqrDEbODzbkpSEREBABgHxSiFQr4FCQj/oZ9LAuzl57qXZIiIiLaiBg8iVZIkiT0t0UgS1LtfOkpW58lo4ps0URfa2TuJvh6IYRAvmxhulBBsWJ5XQ4REa0h6+snItESmFUbk9kyMsXaTmUs6ENHS2BF50K74kFcNJDEBydmMJIuQpEl2I6ArirY2h3D1u7Y2S7fU+l8BYfHc5jMlWBVBXRVRmc8iM2dMUSDPq/LIyKiJsfgSRtKpmjg4LEUUjkDJy9kO0KgLeLHRQOtKzonOtAeQVvUj8lsGWXLhqbISEZ0xEP6mm2jVE86X8G/P5lCoWIiEfbDF5RRsWwcHs9hpmDiss1tDJ9ERLQoBk/aMCqWjYNHU0gXKuiKB+dux9uOg/GZMg4cTeGqczsWtEZaipBfw+AabhR/Oo4Q+Gg0g6JhoScZnns8rMgI6ipOpIs4PJHD/wy2elglERE1O57xpA1jMlNCKl9BV0vocy2ZZHTFg5jOVzCeKXtYYfPKFk1MZStIRvwLnpMlCfGwjrGZEooGz3wSEVFjDJ60YUzlK1BlGXKdpvKyLEFVZUzlGDzrMas2LNtpOHte12pN/k3LcbkyIiJaSxg8acNwHIHFjlzKkjTvZjp9RlNlqIo0N0Hq88xq7WyrpvJbChERNcafErRhJMJ+mFWnbrgUQsCwbNeb0K8VLSEdyYgf03ljwXNCCMwUDHS0BBBex+dciYjozDF4blCW7TTcvVqvOlsCiAZ9mMpVFjyXylcQCfjQFQ95UFnzkyUJW7ti0FQZYzMlGJYNIQQqZhWj0yVEAj4Mdayv1lFERHT28Vb7BjORKWEkXUAqV9u5ao3q6EmG0RELrKvWP/WE/Bou6k/i4LE0hlMFBH0qIAFlo4pIQMP2/gR37BbR0RLEjqE2fDyWRTpfgeUI+BQZm5IhbOmKcbeYiIhOi8FzAzk6kcOhT6dRdRxEAhokAMNTBZxIl3BBXxyJsB/jmRKyJROqLKG9JYjOFTZWb1ad8SCu8qsYmy5iMlcBBDDUGcWmeIg9KJegoyWItlgAmaKBqi3gU2XEgr51/0sLERGdHQyeG0SmaOD94zPQNRkdocDc45GAD9mSiTfeH0XIr0GSJPg1BbYtcGwqj46WIC4eaEUksH52AqMBH6KbfDh3k9eVrE2yJCERXthWiYiI6HR4xnODGM+UUDKqaAktfDlUCIFPU0UUjSp6k2G0RQPojAfRFQ9iIlPCu8NpOLztTURERGeIwXODyJct6A16MKZyFcio7WSdSpFltMcCmMiUkc4vvJBDREREtBwMnhuEqsio2gube9uOg1zZgqbIUOo0VvepCqqOg1yJE2mIiIjozDB4bhDtsQAcIeqGT0c4cIRAvM7L8Cfx7ggRERGdKQbPDaI9FkB3PISxmRIq1mf9Oy1bwLIFdJ+CWJ1b3YZlw6fIdZ8jIiIiWg7eat8gNEXGRYNJKIqM8ZkSUrYNIQCfKuO83jjyZQu5soV46LPWOJbtYCJbQl9bhD0aiYiI6IwxeG4gIV3DZZvbMFMwkC9bEEIgGvQhHtYxkirgvZEZHE8X4VNl2I6AANCTCOPCvsSCi0dEREREy8XgucHIkoRkxI9kZH4fxv7ZXc3xmRLyZQuqIqE1GkB7LABN4YkMIiIiOnMMnjQnGvAhGuBZTiIiIlod3MoiIiIiIlcweBIRERGRKxg8iYiIiMgVDJ5ERERE5AoGTyIiIiJyBYMnEREREbmCwZOIiIiIXMHgSURERESuYPAkIiIiIlcweBIRERGRKxg8iYiIiMgVDJ5ERERE5AoGTyIiIiJyBYMnEREREbmCwZOIiIiIXMHgSURERESuYPAkIiIiIlcweBIRERGRKxg8iYiIiMgVrgRPwzBw8cUXQ5IkHDx40I1PSURERERNxpXg+eCDD6K7u9uNT0VERERETWrVg+fLL7+MV155BY8//vhp39cwDORyuXlvRERERLQ+rGrwnJiYwF133YVnn30WwWDwtO+/e/duxGKxubfe3t7VLI+IiIiIXLRqwVMIgTvvvBO7du3Cjh07lvR3Hn74YWSz2bm3kZGR1SqPiIiIiFy27OD52GOPQZKkRd/279+PJ554ArlcDg8//PCSP7au64hGo/PeiIiIiGh9kIQQYjl/IZVKIZVKLfo+AwMDuPXWW/HSSy9BkqS5x23bhqIouO222/DMM8+c9nPlcjnEYjFks1mGUCIiIqImtJy8tuzguVTDw8PzLgeNjo7i+uuvx9/+9jdcccUV6OnpOe3HYPAkIiIiam7LyWvqahXR19c378/hcBgAMDQ0tKTQSURERETrCycXEREREZErVm3H8/MGBgawSq/qExEREdEawB1PIiIiInIFgycRERERuYLBk4iIiIhcweBJRERERK5g8CQiIiIiVzB4EhEREZErGDyJiIiIyBUMnkRERETkCgZPIiIiInIFgycRERERucK1kZl05kpGFel8BbYjoGsKWqN+aAp/dyAiIqK1gcFzDXCEwCdjWRyZyCFfsSBBgiQBibCOL/TE0dkS9LpEIiIiotPidtkacGQ8h3eH0wCATYkQepIhdMQCyJVMvHMkhXS+4nGFRERERKfH4NnkKpaNwxM5BHUNLSEdsiQBAFRFRkdLECXTwrGpvMdVEhEREZ0eg2eTmykYKJQtxAK+us+3BHVMZsqomFWXKyMiIiJaHgbPJmc7DgQAWZbqPq/KEmzhwHaEu4URERERLRODZ5ML+FSoigTDsus+XzKrCGgadE1xuTIiIiKi5WHwbHLxsI72aACpfBmOmL+raVUdFCpV9LWFoLKtEhERETU5tlNqcrIk4bzeOEpmFcfTBUQDPmiKjLJpo2xW0d8WQX9bxOsyiYiIiE6LwXMNaAnpuHxLO46nizieLsCsOgj7VZzXG0dPMgSfypfZiYiIqPkxeK4R0YAP5/X4sLUrBtsRUBUZSoMLR0RERETNiMFzjVEVGdzgJCIiorWIN1KIiIiIyBUMnkRERETkCgZPIiIiInIFgycRERERuYLBk4iIiIhcweBJRERERK5g8CQiIiIiVzB4EhEREZErGDyJiIiIyBUMnkRERETkCgZPIiIiInIFgycRERERuYLBk4iIiIhcweBJRERERK5g8CQiIiIiVzB4EhEREZErGDyJiIiIyBUMnkRERETkCgZPIiIiInIFgycRERERuUL1uoDFCCEAALlczuNKiIiIiKiekzntZG5bTFMHz3w+DwDo7e31uBIiIiIiWkw+n0csFlv0fSSxlHjqEcdxMDo6ikgkAkmSVv3z5XI59Pb2YmRkBNFodNU/31rCtamP69IY16Y+rktjXJv6uC6NcW3qc3tdhBDI5/Po7u6GLC9+irOpdzxlWUZPT4/rnzcajfILuAGuTX1cl8a4NvVxXRrj2tTHdWmMa1Ofm+tyup3Ok3i5iIiIiIhcweBJRERERK5g8DyFrut49NFHoeu616U0Ha5NfVyXxrg29XFdGuPa1Md1aYxrU18zr0tTXy4iIiIiovWDO55ERERE5AoGTyIiIiJyBYMnEREREbmCwZOIiIiIXMHgSURERESuYPBcAsMwcPHFF0OSJBw8eNDrcjz3jW98A319ffD7/ejq6sLtt9+O0dFRr8vy3LFjx/Dd734Xg4ODCAQCGBoawqOPPgrTNL0uzXM//elPcdVVVyEYDKKlpcXrcjz1m9/8BoODg/D7/bj00kvxr3/9y+uSPPfGG2/g61//Orq7uyFJEl544QWvS2oKu3fvxmWXXYZIJIL29nbcdNNN+Oijj7wuy3O//e1vsX379rmpPFdeeSVefvllr8tqOrt374YkSbj//vu9LmUeBs8lePDBB9Hd3e11GU1j586d+Mtf/oKPPvoIf//733H48GF885vf9Losz3344YdwHAdPPvkk3nvvPfziF7/A7373OzzyyCNel+Y50zRxyy234O677/a6FE89//zzuP/++/GjH/0IBw4cwBe/+EXccMMNGB4e9ro0TxWLRVx00UX41a9+5XUpTeX111/HPffcg7feegv79u1DtVrFddddh2Kx6HVpnurp6cHPfvYz7N+/H/v378dXvvIV3HjjjXjvvfe8Lq1p/Pvf/8ZTTz2F7du3e13KQoIW9Y9//ENs27ZNvPfeewKAOHDggNclNZ0XX3xRSJIkTNP0upSm8/Of/1wMDg56XUbT2LNnj4jFYl6X4ZnLL79c7Nq1a95j27ZtEz/84Q89qqj5ABB79+71uoymNDk5KQCI119/3etSmk48Hhe///3vvS6jKeTzebFlyxaxb98+8aUvfUncd999Xpc0D3c8FzExMYG77roLzz77LILBoNflNKXp6Wn88Y9/xFVXXQVN07wup+lks1kkEgmvy6AmYJom/vOf/+C6666b9/h1112HN99806OqaC3JZrMAwO8pp7BtG8899xyKxSKuvPJKr8tpCvfccw++9rWv4dprr/W6lLoYPBsQQuDOO+/Erl27sGPHDq/LaToPPfQQQqEQkskkhoeH8eKLL3pdUtM5fPgwnnjiCezatcvrUqgJpFIp2LaNjo6OeY93dHRgfHzco6porRBC4IEHHsDVV1+NCy64wOtyPPfuu+8iHA5D13Xs2rULe/fuxXnnned1WZ577rnn8M4772D37t1el9LQhguejz32GCRJWvRt//79eOKJJ5DL5fDwww97XbIrlrouJ/3gBz/AgQMH8Morr0BRFHzrW9+CWKfTV5e7NgAwOjqKr371q7jlllvwve99z6PKV9dK1oUASZLm/VkIseAxos/7/ve/j0OHDuHPf/6z16U0hXPPPRcHDx7EW2+9hbvvvht33HEH3n//fa/L8tTIyAjuu+8+/OEPf4Df7/e6nIY23Kz2VCqFVCq16PsMDAzg1ltvxUsvvTTvB4Jt21AUBbfddhueeeaZ1S7VVUtdl3pfzMePH0dvby/efPPNdflSx3LXZnR0FDt37sQVV1yBp59+GrK8Pn+/W8nXzNNPP437778fmUxmlatrPqZpIhgM4q9//Stuvvnmucfvu+8+HDx4EK+//rqH1TUPSZKwd+9e3HTTTV6X0jTuvfdevPDCC3jjjTcwODjodTlN6dprr8XQ0BCefPJJr0vxzAsvvICbb74ZiqLMPWbbNiRJgizLMAxj3nNeUb0uwG2tra1obW097fv98pe/xE9+8pO5P4+OjuL666/H888/jyuuuGI1S/TEUtelnpO/uxiGcTZLahrLWZsTJ05g586duPTSS7Fnz551GzqBM/ua2Yh8Ph8uvfRS7Nu3b17w3LdvH2688UYPK6NmJYTAvffei7179+K1115j6FyEEGLd/gxaqmuuuQbvvvvuvMe+/e1vY9u2bXjooYeaInQCGzB4LlVfX9+8P4fDYQDA0NAQenp6vCipKbz99tt4++23cfXVVyMej+PIkSP48Y9/jKGhoXW527kco6Oj+PKXv4y+vj48/vjjmJqamnuus7PTw8q8Nzw8jOnpaQwPD8O27bl+uJs3b577f2sjeOCBB3D77bdjx44duPLKK/HUU09heHh4w58DLhQK+OSTT+b+fPToURw8eBCJRGLB9+KN5J577sGf/vQnvPjii4hEInNngWOxGAKBgMfVeeeRRx7BDTfcgN7eXuTzeTz33HN47bXX8M9//tPr0jwViUQWnP89eRejqc4Fe3affo05evQo2ykJIQ4dOiR27twpEomE0HVdDAwMiF27donjx497XZrn9uzZIwDUfdvo7rjjjrrr8uqrr3pdmut+/etfi/7+fuHz+cQll1zC1jhCiFdffbXu18cdd9zhdWmeavT9ZM+ePV6X5qnvfOc7c/8PtbW1iWuuuUa88sorXpfVlJqxndKGO+NJRERERN5YvwfQiIiIiKipMHgSERERkSsYPImIiIjIFQyeREREROQKBk8iIiIicgWDJxERERG5gsGTiIiIiFzB4ElERERErmDwJCIiIiJXMHgSERERkSsYPImIiIjIFf8ffajjsU+q2hAAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "plt.figure(figsize=(8, 8))\n", - "plt.scatter(X[:, 0], X[:, 1], c=y, alpha=0.3, cmap=mcolors.ListedColormap([\"steelblue\", \"tomato\"]))\n", + "plt.scatter(\n", + " X[:, 0],\n", + " X[:, 1],\n", + " c=y,\n", + " alpha=0.3,\n", + " cmap=mcolors.ListedColormap([\"steelblue\", \"tomato\"]),\n", + ")\n", "\n", "x1 = np.linspace(-4, 4, 100)\n", "x2_SGD = -(w_SGD[0] * x1 + b_SGD) / w_SGD[1]\n", @@ -40946,20 +40995,7 @@ "plt.plot(x1, x2_learn, c=\"steelblue\", label=\"Sklearn\")\n", "plt.legend()\n", "plt.show()" - ], - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ], - "image/png": 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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 67 + ] }, { "cell_type": "markdown", @@ -40978,27 +41014,13 @@ }, { "cell_type": "code", + "execution_count": 75, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T10:06:51.624736Z", "start_time": "2025-03-19T10:06:51.611049Z" } }, - "source": [ - "from sklearn.model_selection import train_test_split\n", - "from sklearn import datasets\n", - "\n", - "iris = datasets.load_iris(as_frame=True)\n", - "\n", - "X, y = iris.data, iris.target\n", - "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=5)\n", - "\n", - "log_reg = LogisticRegression(fit_intercept=True)\n", - "\n", - "log_reg.fit(X_train, y_train)\n", - "y_pred = log_reg.predict(X_test)\n", - "log_reg.score(X_test, y_test)" - ], "outputs": [ { "data": { @@ -41011,7 +41033,23 @@ "output_type": "execute_result" } ], - "execution_count": 75 + "source": [ + "from sklearn.model_selection import train_test_split\n", + "from sklearn import datasets\n", + "\n", + "iris = datasets.load_iris(as_frame=True)\n", + "\n", + "X, y = iris.data, iris.target\n", + "X_train, X_test, y_train, y_test = train_test_split(\n", + " X, y, test_size=0.33, random_state=5\n", + ")\n", + "\n", + "log_reg = LogisticRegression(fit_intercept=True)\n", + "\n", + "log_reg.fit(X_train, y_train)\n", + "y_pred = log_reg.predict(X_test)\n", + "log_reg.score(X_test, y_test)" + ] }, { "cell_type": "markdown", @@ -41043,29 +41081,29 @@ }, { "cell_type": "code", + "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T10:58:43.985209Z", "start_time": "2025-03-19T10:58:19.396703Z" } }, + "outputs": [], "source": [ "import tensorflow as tf\n", "\n", "(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data()" - ], - "outputs": [], - "execution_count": 1 + ] }, { "cell_type": "code", + "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T10:58:46.374251Z", "start_time": "2025-03-19T10:58:46.365605Z" } }, - "source": "type(x_train)", "outputs": [ { "data": { @@ -41078,19 +41116,19 @@ "output_type": "execute_result" } ], - "execution_count": 2 + "source": [ + "type(x_train)" + ] }, { "cell_type": "code", + "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T10:58:47.207411Z", "start_time": "2025-03-19T10:58:47.204291Z" } }, - "source": [ - "x_train.shape, y_train.shape" - ], "outputs": [ { "data": { @@ -41103,17 +41141,19 @@ "output_type": "execute_result" } ], - "execution_count": 3 + "source": [ + "x_train.shape, y_train.shape" + ] }, { "cell_type": "code", + "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T10:58:47.828676Z", "start_time": "2025-03-19T10:58:47.823536Z" } }, - "source": "28 * 28", "outputs": [ { "data": { @@ -41126,7 +41166,9 @@ "output_type": "execute_result" } ], - "execution_count": 4 + "source": [ + "28 * 28" + ] }, { "cell_type": "markdown", @@ -41137,23 +41179,25 @@ }, { "cell_type": "code", + "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T10:58:51.690085Z", "start_time": "2025-03-19T10:58:51.651012Z" } }, + "outputs": [], "source": [ - "# definition of the model \n", + "# definition of the model\n", "tf.random.set_seed(4)\n", "model = tf.keras.Sequential()\n", "model.add(tf.keras.layers.Input(shape=[28, 28])) # we specify the input shape\n", "model.add(tf.keras.layers.Flatten()) # we flatten the data\n", - "model.add(tf.keras.layers.Dense(10, activation=\"softmax\")) # 10 labels (figures from 0 to 9)\n", - "#activation=\"softmax\" as it is a multiclass problem" - ], - "outputs": [], - "execution_count": 5 + "model.add(\n", + " tf.keras.layers.Dense(10, activation=\"softmax\")\n", + ") # 10 labels (figures from 0 to 9)\n", + "# activation=\"softmax\" as it is a multiclass problem" + ] }, { "cell_type": "markdown", @@ -41183,114 +41227,116 @@ }, { "cell_type": "code", + "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T10:59:00.281294Z", "start_time": "2025-03-19T10:59:00.274306Z" } }, - "source": [ - "model.compile(loss=\"sparse_categorical_crossentropy\",\n", - " optimizer=\"sgd\",\n", - " metrics=[\"accuracy\"])" - ], "outputs": [], - "execution_count": 6 + "source": [ + "model.compile(\n", + " loss=\"sparse_categorical_crossentropy\", optimizer=\"sgd\", metrics=[\"accuracy\"]\n", + ")" + ] }, { "cell_type": "code", + "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T10:59:27.035193Z", "start_time": "2025-03-19T10:59:00.493936Z" } }, - "source": "history = model.fit(x_train, y_train, epochs=30)", "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 398us/step - accuracy: 0.8051 - loss: 468.3519\n", + "\u001b[1m1875/1875\u001b[0m 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\u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 405us/step - accuracy: 0.8861 - loss: 222.4019\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 405us/step - accuracy: 0.8861 - loss: 222.4019\n", "Epoch 17/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 404us/step - accuracy: 0.8842 - loss: 224.2069\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 404us/step - accuracy: 0.8842 - loss: 224.2069\n", "Epoch 18/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 429us/step - accuracy: 0.8847 - loss: 226.9697\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 429us/step - accuracy: 0.8847 - loss: 226.9697\n", "Epoch 19/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 400us/step - accuracy: 0.8861 - loss: 224.0267\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 400us/step - accuracy: 0.8861 - loss: 224.0267\n", "Epoch 20/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 445us/step - accuracy: 0.8860 - loss: 224.9942\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 445us/step - accuracy: 0.8860 - loss: 224.9942\n", "Epoch 21/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 498us/step - accuracy: 0.8869 - loss: 223.2416\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 498us/step - accuracy: 0.8869 - loss: 223.2416\n", "Epoch 22/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 403us/step - accuracy: 0.8864 - loss: 225.3823\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 403us/step - accuracy: 0.8864 - loss: 225.3823\n", "Epoch 23/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 399us/step - accuracy: 0.8864 - loss: 220.9412\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 399us/step - accuracy: 0.8864 - loss: 220.9412\n", "Epoch 24/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 397us/step - accuracy: 0.8884 - loss: 219.2184\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 397us/step - accuracy: 0.8884 - loss: 219.2184\n", "Epoch 25/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 392us/step - accuracy: 0.8845 - loss: 226.9767\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 392us/step - accuracy: 0.8845 - loss: 226.9767\n", "Epoch 26/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 391us/step - accuracy: 0.8869 - loss: 222.8797\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 391us/step - accuracy: 0.8869 - loss: 222.8797\n", "Epoch 27/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 397us/step - accuracy: 0.8884 - loss: 220.8678\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 397us/step - accuracy: 0.8884 - loss: 220.8678\n", "Epoch 28/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 394us/step - accuracy: 0.8875 - loss: 223.3590\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 394us/step - accuracy: 0.8875 - loss: 223.3590\n", "Epoch 29/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 394us/step - accuracy: 0.8878 - loss: 221.2637\n", + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 394us/step - accuracy: 0.8878 - loss: 221.2637\n", "Epoch 30/30\n", - "\u001B[1m1875/1875\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m1s\u001B[0m 392us/step - accuracy: 0.8867 - loss: 223.8463\n" + "\u001b[1m1875/1875\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 392us/step - accuracy: 0.8867 - loss: 223.8463\n" ] } ], - "execution_count": 7 + "source": [ + "history = model.fit(x_train, y_train, epochs=30)" + ] }, { "cell_type": "code", + "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T10:59:30.147983Z", "start_time": "2025-03-19T10:59:29.891625Z" } }, - "source": "model.evaluate(x_test, y_test)", "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "\u001B[1m313/313\u001B[0m \u001B[32m━━━━━━━━━━━━━━━━━━━━\u001B[0m\u001B[37m\u001B[0m \u001B[1m0s\u001B[0m 470us/step - accuracy: 0.8769 - loss: 261.1911\n" + "\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 470us/step - accuracy: 0.8769 - loss: 261.1911\n" ] }, { @@ -41304,7 +41350,9 @@ "output_type": "execute_result" } ], - "execution_count": 8 + "source": [ + "model.evaluate(x_test, y_test)" + ] }, { "cell_type": "markdown", @@ -41315,27 +41363,27 @@ }, { "cell_type": "code", + "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T10:59:36.402820Z", "start_time": "2025-03-19T10:59:35.043905Z" } }, + "outputs": [], "source": [ "(X_train, y_train), (X_test, y_test) = tf.keras.datasets.cifar10.load_data()" - ], - "outputs": [], - "execution_count": 9 + ] }, { "cell_type": "code", + "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T10:59:46.827470Z", "start_time": "2025-03-19T10:59:46.824193Z" } }, - "source": "len(np.unique(y_test)) # 10 labels", "outputs": [ { "data": { @@ -41348,19 +41396,19 @@ "output_type": "execute_result" } ], - "execution_count": 12 + "source": [ + "len(np.unique(y_test)) # 10 labels" + ] }, { "cell_type": "code", + "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2025-03-19T10:59:47.663176Z", "start_time": "2025-03-19T10:59:47.658204Z" } }, - "source": [ - "X_train.shape, y_train.shape" - ], "outputs": [ { "data": { @@ -41373,7 +41421,9 @@ "output_type": "execute_result" } ], - "execution_count": 13 + "source": [ + "X_train.shape, y_train.shape" + ] }, { "cell_type": "code", diff --git a/M1/Statistical Learning/TP4_Ridge_Lasso_and_CV.ipynb b/M1/Statistical Learning/TP4_Ridge_Lasso_and_CV.ipynb index adc0181..7fefe71 100644 --- a/M1/Statistical Learning/TP4_Ridge_Lasso_and_CV.ipynb +++ b/M1/Statistical Learning/TP4_Ridge_Lasso_and_CV.ipynb @@ -43,7 +43,7 @@ "source": [ "import warnings\n", "\n", - "warnings.filterwarnings('ignore')" + "warnings.filterwarnings(\"ignore\")" ] }, { @@ -434,7 +434,7 @@ ], "source": [ "import numpy as np\n", - "import pandas as pd # dataframes are in pandas \n", + "import pandas as pd # dataframes are in pandas\n", "import matplotlib.pyplot as plt\n", "\n", "hitters = pd.read_csv(\"data/Hitters.csv\", index_col=\"Name\")\n", @@ -895,9 +895,13 @@ ], "source": [ "# Hint for Question (4) :\n", - "ex = pd.DataFrame(dict(nom=['Alice', 'Nicolas', 'Jean'],\n", - " age=[19, np.NaN, np.NaN],\n", - " exam=[15, 14, np.NaN]))\n", + "ex = pd.DataFrame(\n", + " dict(\n", + " nom=[\"Alice\", \"Nicolas\", \"Jean\"],\n", + " age=[19, np.NaN, np.NaN],\n", + " exam=[15, 14, np.NaN],\n", + " )\n", + ")\n", "\n", "print(\"data : \\n\", ex)\n", "print(\"First result : \\n\", ex.isnull())\n", @@ -1080,10 +1084,10 @@ ], "source": [ "# We remove the players for whom Salary is missing\n", - "hitters.dropna(subset=['Salary'], inplace=True)\n", + "hitters.dropna(subset=[\"Salary\"], inplace=True)\n", "\n", "X = hitters.select_dtypes(include=int)\n", - "Y = hitters['Salary']\n", + "Y = hitters[\"Salary\"]\n", "\n", "# check-point\n", "print(Y.isnull().sum()) # should be 0\n", @@ -1109,7 +1113,7 @@ }, "outputs": [], "source": [ - "#Answer for Exercise 4\n", + "# Answer for Exercise 4\n", "from sklearn.model_selection import train_test_split\n", "\n", "Xtrain, Xtest, Ytrain, Ytest = train_test_split(X, Y, test_size=0.3, random_state=42)" @@ -1697,8 +1701,8 @@ } ], "source": [ - "#the values of alphas chosen by defaults are also on a logarithmic scale\n", - "plt.plot(np.log10(alphas_lasso), '.')" + "# the values of alphas chosen by defaults are also on a logarithmic scale\n", + "plt.plot(np.log10(alphas_lasso), \".\")" ] }, { @@ -1735,8 +1739,8 @@ "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')" + "ax.set_xlabel(\"log10(alpha)\")\n", + "ax.set_ylabel(\"Lasso coefficients\")" ] }, { @@ -1792,7 +1796,7 @@ "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" + "print(\"4. Le nombre de 0 de chaque ligne est : \\n\", (ind == 0).sum(axis=1))" ] }, { @@ -2294,18 +2298,19 @@ "from sklearn.linear_model import LinearRegression\n", "\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", + "linReg.fit(\n", + " Xtrain, Ytrain\n", + ") # 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", "\n", "fig, ax = plt.subplots()\n", "ax.scatter(Ytest, hatY_LinReg, 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 OLS estimator')\n", - "ax.axis('square')" + "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 OLS estimator\")\n", + "ax.axis(\"square\")" ] }, { @@ -2355,11 +2360,11 @@ "\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')" + "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\")" ] }, { @@ -2408,11 +2413,11 @@ "\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')" + "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\")" ] }, { @@ -2445,7 +2450,7 @@ "source": [ "from sklearn.linear_model import LassoLarsIC\n", "\n", - "lassoBIC = LassoLarsIC(criterion='bic')\n", + "lassoBIC = LassoLarsIC(criterion=\"bic\")\n", "lassoBIC.fit(XtrainScaled, Ytrain)\n", "print(\"best alpha chosen by BIC criterion :\", lassoBIC.alpha_)\n", "print(\"best alpha chosen by CV :\", lassoCV.alpha_)\n", @@ -2499,11 +2504,11 @@ "\n", "fig, ax = plt.subplots()\n", "ax.scatter(Ytest, hatY_BIC, 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 LassoBIC estimator')\n", - "ax.axis('square')" + "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 LassoBIC estimator\")\n", + "ax.axis(\"square\")" ] }, { @@ -2539,7 +2544,9 @@ "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", + "for name, estimator in zip(\n", + " [\"LassoCV\", \"LassoBIC\", \"RidgeCV\", \"OLS\"], [lassoCV, lassoBIC, ridgeCV, linReg]\n", + "):\n", " y_pred = estimator.predict(Xtest)\n", " MSE = mean_squared_error(Ytest, y_pred)\n", " print(f\"MSE for {name} : {MSE}\")\n", @@ -2584,10 +2591,12 @@ "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", + "ax.boxplot(\n", + " [ridge_cv_errors, lasso_cv_errors, lasso_bic_errors, ols_errors],\n", + " labels=[\"RidgeCV\", \"LassoCV\", \"LassoBIC\", \"OLS\"],\n", + ")\n", + "ax.set_title(\"Boxplot of Absolute Errors\")\n", + "ax.set_ylabel(\"Absolute Error\")\n", "plt.show()" ] }, diff --git a/M1/Statistical Learning/TP5_Naive_Bayes.ipynb b/M1/Statistical Learning/TP5_Naive_Bayes.ipynb index 2003b23..bed1cbc 100644 --- a/M1/Statistical Learning/TP5_Naive_Bayes.ipynb +++ b/M1/Statistical Learning/TP5_Naive_Bayes.ipynb @@ -32,7 +32,7 @@ "metadata": {}, "outputs": [], "source": [ - "import pandas as pd \n", + "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt" ] @@ -226,7 +226,7 @@ } ], "source": [ - "sms = pd.read_csv(\"data/spam.csv\", encoding='latin')\n", + "sms = pd.read_csv(\"data/spam.csv\", encoding=\"latin\")\n", "\n", "sms.head()" ] @@ -244,7 +244,7 @@ "metadata": {}, "outputs": [], "source": [ - "sms.rename(columns={'v1':'Label', 'v2':'Text'}, inplace=True)" + "sms.rename(columns={\"v1\": \"Label\", \"v2\": \"Text\"}, inplace=True)" ] }, { @@ -644,7 +644,7 @@ } ], "source": [ - "sms['Labelnum']=sms['Label'].map({'ham':0,'spam':1})\n", + "sms[\"Labelnum\"] = sms[\"Label\"].map({\"ham\": 0, \"spam\": 1})\n", "\n", "sms.head()" ] @@ -674,13 +674,13 @@ } ], "source": [ - "# Hint 1 for Exercise 1 \n", - "a=np.array([0,1,1,1,0])\n", - "print (len(a))\n", - "print (a[a==0])\n", - "print (len(a[a==0]))\n", - "print (a[a==1])\n", - "print (len(a[a==1]))" + "# Hint 1 for Exercise 1\n", + "a = np.array([0, 1, 1, 1, 0])\n", + "print(len(a))\n", + "print(a[a == 0])\n", + "print(len(a[a == 0]))\n", + "print(a[a == 1])\n", + "print(len(a[a == 1]))" ] }, { @@ -881,8 +881,8 @@ } ], "source": [ - "# Hint 2 for Exercise 1 \n", - "sms[sms.Labelnum==0].head()" + "# Hint 2 for Exercise 1\n", + "sms[sms.Labelnum == 0].head()" ] }, { @@ -1083,8 +1083,8 @@ } ], "source": [ - "# Hint 3 for Exercise 1 \n", - "sms[sms.Labelnum==1].head()" + "# Hint 3 for Exercise 1\n", + "sms[sms.Labelnum == 1].head()" ] }, { @@ -1104,8 +1104,8 @@ ], "source": [ "print(len(sms))\n", - "print(sms[sms.Label == 'ham'].shape)\n", - "print(sms[sms.Label == 'spam'].shape)" + "print(sms[sms.Label == \"ham\"].shape)\n", + "print(sms[sms.Label == \"spam\"].shape)" ] }, { @@ -1136,8 +1136,8 @@ ], "source": [ "# Hint 1 for Exercise 2\n", - "print (sms.loc[0, 'Text']) \n", - "print (\"--> The length of the first sms is\", len(sms.loc[0, 'Text']))" + "print(sms.loc[0, \"Text\"])\n", + "print(\"--> The length of the first sms is\", len(sms.loc[0, \"Text\"]))" ] }, { @@ -1160,10 +1160,13 @@ ], "source": [ "plt.figure(figsize=(10, 6))\n", - "plt.hist(sms.loc[:, 'Text'].apply(len), bins='stone',)\n", - "plt.title('Histogram of SMS Lengths')\n", - "plt.xlabel('Length')\t\n", - "plt.ylabel('Frequency')\n", + "plt.hist(\n", + " sms.loc[:, \"Text\"].apply(len),\n", + " bins=\"stone\",\n", + ")\n", + "plt.title(\"Histogram of SMS Lengths\")\n", + "plt.xlabel(\"Length\")\n", + "plt.ylabel(\"Frequency\")\n", "plt.show()" ] }, @@ -1222,30 +1225,41 @@ } ], "source": [ - "Example = pd.DataFrame([['iphone gratuit iphone gratuit',1],['mille vert gratuit',0],\n", - " ['iphone mille euro',0],['argent gratuit euro gratuit',1]],\n", - " columns=['sms', 'label'])\n", + "Example = pd.DataFrame(\n", + " [\n", + " [\"iphone gratuit iphone gratuit\", 1],\n", + " [\"mille vert gratuit\", 0],\n", + " [\"iphone mille euro\", 0],\n", + " [\"argent gratuit euro gratuit\", 1],\n", + " ],\n", + " columns=[\"sms\", \"label\"],\n", + ")\n", "vec = CountVectorizer()\n", "X = vec.fit_transform(Example.sms)\n", "\n", "# 1. Displaying the vocabulary\n", "\n", - "print (\"1. The vocabulary of Example is \", vec.vocabulary_)\n", + "print(\"1. The vocabulary of Example is \", vec.vocabulary_)\n", "\n", "# 1 bis :\n", "\n", - "print('The vocabulary arranged in alphabetical order : ', sorted(list(vec.vocabulary_.keys())))\n", + "print(\n", + " \"The vocabulary arranged in alphabetical order : \",\n", + " sorted(list(vec.vocabulary_.keys())),\n", + ")\n", "\n", - "# 2. Displaying the vectors : \n", + "# 2. Displaying the vectors :\n", "\n", - "print (\"2. The vectors corresponding to the sms are : \\n\", X.toarray())# X.toarray because \n", - "# X is a \"sparse\" matrix. \n", + "print(\n", + " \"2. The vectors corresponding to the sms are : \\n\", X.toarray()\n", + ") # X.toarray because\n", + "# X is a \"sparse\" matrix.\n", "\n", - "# 3. For a new data x_0=\"iphone gratuit\", \n", - "# you must also transform x_0 into a numerical vector before predicting. \n", + "# 3. For a new data x_0=\"iphone gratuit\",\n", + "# you must also transform x_0 into a numerical vector before predicting.\n", "\n", - "vec_x_0=vec.transform(['iphone gratuit']).toarray() # \n", - "print (\"3. The numerical vector corresponding to (x_0=iphone gratuit) is \\n\", vec_x_0 )" + "vec_x_0 = vec.transform([\"iphone gratuit\"]).toarray() #\n", + "print(\"3. The numerical vector corresponding to (x_0=iphone gratuit) is \\n\", vec_x_0)" ] }, { @@ -1267,7 +1281,7 @@ ], "source": [ "#'sparse' version (without \"to_array\")\n", - "v = vec.transform(['iphone iphone gratuit'])\n", + "v = vec.transform([\"iphone iphone gratuit\"])\n", "v" ] }, @@ -1309,8 +1323,8 @@ } ], "source": [ - "# \"(0,2) 1\" means : the element in row 0 and column 2 is equal to 1. \n", - "# \"(0,3) 2\" means : the element in row 0 and column 3 is equal to 2. \n", + "# \"(0,2) 1\" means : the element in row 0 and column 2 is equal to 1.\n", + "# \"(0,3) 2\" means : the element in row 0 and column 3 is equal to 2.\n", "print(v)" ] }, @@ -1340,8 +1354,8 @@ } ], "source": [ - "vec_x_1 = vec.transform(['iphone vert gratuit']).toarray()\n", - "vec_x_2 = vec.transform(['iphone rouge gratuit']).toarray()\n", + "vec_x_1 = vec.transform([\"iphone vert gratuit\"]).toarray()\n", + "vec_x_2 = vec.transform([\"iphone rouge gratuit\"]).toarray()\n", "print(vec_x_1)\n", "print(vec_x_2)" ] @@ -1372,8 +1386,8 @@ "outputs": [], "source": [ "vectorizer = CountVectorizer()\n", - "X = vectorizer.fit_transform(sms['Text'])\n", - "y = sms['Labelnum']" + "X = vectorizer.fit_transform(sms[\"Text\"])\n", + "y = sms[\"Labelnum\"]" ] }, { @@ -1400,10 +1414,12 @@ "source": [ "from sklearn.model_selection import train_test_split\n", "\n", - "X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.30,random_state=50)\n", + "X_train, X_test, y_train, y_test = train_test_split(\n", + " X, y, test_size=0.30, random_state=50\n", + ")\n", "\n", - "print (\"size of the training set: \", X_train.shape[0])\n", - "print (\"size of the test set :\", X_test.shape[0])" + "print(\"size of the training set: \", X_train.shape[0])\n", + "print(\"size of the test set :\", X_test.shape[0])" ] }, { @@ -1906,7 +1922,7 @@ "from sklearn.metrics import accuracy_score\n", "\n", "y_pred = sms_bayes.predict(X_test)\n", - "print (\"The accuracy score on the test set is \", accuracy_score(y_test, y_pred))" + "print(\"The accuracy score on the test set is \", accuracy_score(y_test, y_pred))" ] }, { @@ -1969,10 +1985,17 @@ } ], "source": [ - "my_sms = vectorizer.transform(['free trial!', 'Iphone 15 is now free', 'I want coffee', 'I want to buy a new iphone'])\n", + "my_sms = vectorizer.transform(\n", + " [\n", + " \"free trial!\",\n", + " \"Iphone 15 is now free\",\n", + " \"I want coffee\",\n", + " \"I want to buy a new iphone\",\n", + " ]\n", + ")\n", "\n", "pred_my_sms = sms_bayes.predict(my_sms)\n", - "print (pred_my_sms)" + "print(pred_my_sms)" ] }, { @@ -1999,7 +2022,7 @@ "from sklearn.naive_bayes import BernoulliNB\n", "\n", "# Load the MNIST dataset\n", - "mnist = fetch_openml('mnist_784', version=1, parser='auto')\n", + "mnist = fetch_openml(\"mnist_784\", version=1, parser=\"auto\")\n", "X, y = mnist.data, mnist.target" ] }, @@ -2036,7 +2059,9 @@ "source": [ "X_copy = (X.copy() >= 127).astype(int)\n", "\n", - "X_train, X_test, y_train, y_test = train_test_split(X_copy, y, test_size=0.25, random_state=42)\n", + "X_train, X_test, y_train, y_test = train_test_split(\n", + " X_copy, y, test_size=0.25, random_state=42\n", + ")\n", "\n", "ber_bayes = BernoulliNB()\n", "ber_bayes.fit(X_train, y_train)\n", @@ -2059,6 +2084,7 @@ "outputs": [], "source": [ "from keras.datasets import cifar10\n", + "\n", "(x_train, y_train), (x_test, y_test) = cifar10.load_data()" ] }, @@ -2077,7 +2103,7 @@ } ], "source": [ - "# reminder : the output is an RGB image 32 x 32 \n", + "# reminder : the output is an RGB image 32 x 32\n", "print(x_train.shape)\n", "print(y_train.shape)" ] diff --git a/M1/Statistical Learning/TP6_keras_intro.ipynb b/M1/Statistical Learning/TP6_keras_intro.ipynb index b1fd7aa..b25f52b 100644 --- a/M1/Statistical Learning/TP6_keras_intro.ipynb +++ b/M1/Statistical Learning/TP6_keras_intro.ipynb @@ -1,2207 +1,2266 @@ { - "cells": [ - { - "cell_type": "markdown", - "id": "ced704ec-0d0d-45c3-9b55-2368396e5c77", - "metadata": { - "id": "ced704ec-0d0d-45c3-9b55-2368396e5c77" - }, - "source": [ - "# TP6 A short introduction to neural networks with Keras" - ] - }, - { - "cell_type": "markdown", - "id": "cd455d57-9a48-4a1c-82d6-2894f99cdb6d", - "metadata": { - "id": "cd455d57-9a48-4a1c-82d6-2894f99cdb6d" - }, - "source": [ - "We will use the Keras library, which serves as a high-level API for TensorFlow.\n", - "\n", - " Keras is a\n", - "deep-learning framework for Python that provides a convenient way to define and\n", - "train almost any kind of deep-learning model. Keras was initially developed for\n", - "researchers, with the aim of enabling fast experimentation.\n", - "Keras has the following key features:\n", - "- It allows the same code to run seamlessly on CPU or GPU.\n", - "- It has a user-friendly API that makes it easy to quickly prototype deep-learning\n", - "models.\n", - "- It has built-in support for convolutional networks (for computer vision), recurrent\n", - "networks (for sequence processing), and any combination of both.\n", - "- It supports arbitrary network architectures: multi-input or multi-output models,\n", - "layer sharing, model sharing, and so on.\n", - "\n", - "Extracted from the book \"Deep Learning with Python \", author : François Chollet.\n", - "\n", - "Remark : \n", - "\n", - " - PyTorch is more popular among researchers and academic practitioners for its flexibility and ease of use.\n", - "\n", - " - TensorFlow is preferred by industry professionals for large-scale applications and production deployment.\n" - ] - }, - { - "cell_type": "markdown", - "id": "ahhFpKIMWSxI", - "metadata": { - "id": "ahhFpKIMWSxI" - }, - "source": [ - "This tutorial uses the Fashion MNIST dataset which contains 70,000 grayscale images in 10 categories. The images show individual articles of clothing at low resolution (28 by 28 pixels). We will only use an MLP." - ] - }, - { - "cell_type": "markdown", - "id": "cT3zmP9N-Gfb", - "metadata": { - "id": "cT3zmP9N-Gfb" - }, - "source": [ - "Remark : in colab, try using the GPU instead of the CPU (Click on the \"Runtime\" menu at the top.\n", - "Select \"Change runtime type.\"\n", - "In the dialog box that appears, choose \"GPU\" under the Hardware accelerator dropdown menu.\n", - "Click \"Save.\" \n", - "\n", - "(GPU access is available with free Colab, but it comes with usage and performance limitations compared to the paid options)." - ] - }, - { - "cell_type": "markdown", - "id": "48a02457-d8ec-4c0a-b11f-7d4819c75e8d", - "metadata": { - "id": "48a02457-d8ec-4c0a-b11f-7d4819c75e8d" - }, - "source": [ - " Fashion MNIST is a slightly more challenging problem than regular MNIST. Both datasets are relatively small and are used to verify that an algorithm works as expected.\n", - "\n", - "Here, 60,000 images are used to train the network and 10,000 images to evaluate how accurately the network learned to classify images. You can access the Fashion MNIST directly from TensorFlow" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "5260add2-2092-4849-b39b-0b4416d60275", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "5260add2-2092-4849-b39b-0b4416d60275", - "outputId": "654e42f5-eb10-449a-f110-d62b0e81fc0a" - }, - "outputs": [], - "source": [ - "import tensorflow as tf\n", - "import numpy as np\n", - "tf.keras.utils.set_random_seed(42)\n", - "fashion_mnist = tf.keras.datasets.fashion_mnist\n", - "(X_train, y_train), (X_test, y_test) = fashion_mnist.load_data()" - ] - }, - { - "cell_type": "markdown", - "id": "1003ff8e-552e-425e-81df-85d623b062e3", - "metadata": { - "id": "1003ff8e-552e-425e-81df-85d623b062e3" - }, - "source": [ - "Let us take a look at the shape and the datatype of the training set :" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "cf702fe0-4b88-441e-a6c1-73fd5c57111f", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "cf702fe0-4b88-441e-a6c1-73fd5c57111f", - "outputId": "4f1ec97c-59a0-4eb7-ed01-8423374eb1e5" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "((60000, 28, 28), dtype('uint8'))" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "X_train.shape, X_train.dtype" - ] - }, - { - "cell_type": "markdown", - "id": "oXlaIKYNYQIl", - "metadata": { - "id": "oXlaIKYNYQIl" - }, - "source": [ - "We will need a validation set during training. As the dataset is already shuffled, we will just use the last rows of the dataset for the validation set :" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "aoanwQnmYa3K", - "metadata": { - "id": "aoanwQnmYa3K" - }, - "outputs": [], - "source": [ - "X_val, y_val = X_train[-5000:], y_train[-5000:]\n", - "X_train, y_train = X_train[:-5000], y_train[:-5000]" - ] - }, - { - "cell_type": "markdown", - "id": "100d1fdb-d769-4dc7-aada-69d816b099aa", - "metadata": { - "id": "100d1fdb-d769-4dc7-aada-69d816b099aa" - }, - "source": [ - "Neural networks process inputs using small weight values, and inputs with large integer values can disrupt or slow down the learning process. As such it is good practice to normalize the pixel values. We do not really know the best way to scale the pixel values for modeling, but we know that some scaling will be required.\n", - "\n", - "A good starting point is to normalize the pixel values of grayscale images, e.g. rescale them to the range [0,1]. This involves first converting the data type from unsigned integers to floats, then dividing the pixel values by the maximum value.\n", - "\n", - "\n", - "\n", - "(If we used the sigmoid or tanh activation for the first layer, it would be even more important not to have too big input values, as they could cause saturation).\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "d5d925c1-6a53-4a9d-99ee-4ebb1a9c9026", - "metadata": { - "id": "d5d925c1-6a53-4a9d-99ee-4ebb1a9c9026" - }, - "outputs": [], - "source": [ - "X_train01, X_val01, X_test01 = X_train/255.0, X_val/255.0, X_test/255.0" - ] - }, - { - "cell_type": "markdown", - "id": "0d393d58-bb7b-4a0b-90d2-2d1895300aa4", - "metadata": { - "id": "0d393d58-bb7b-4a0b-90d2-2d1895300aa4" - }, - "source": [ - "Remarks :\n", - " Normalizing the inputs and initializing the weights properly are particularly important in the context of deep learning (see e.g. the vanishing gradient problem or the exploding gradient problem). Here we have a shallow network, but the size of the inputs and of the weights matter anyway, we just have fewer problems.\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "2e31918c-b394-410a-b879-474f95b25035", - "metadata": { - "id": "2e31918c-b394-410a-b879-474f95b25035" - }, - "source": [ - "Here are the class names (they are not included with the dataset) : " - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "731ad9e7-57ae-47c5-b50d-5d77c28216bd", - "metadata": { - "id": "731ad9e7-57ae-47c5-b50d-5d77c28216bd" - }, - "outputs": [], - "source": [ - "class_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat',\n", - " 'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']" - ] - }, - { - "cell_type": "markdown", - "id": "7e3a55f3-d4b6-450e-93a2-2d6fb339c3b5", - "metadata": { - "id": "7e3a55f3-d4b6-450e-93a2-2d6fb339c3b5" - }, - "source": [ - "Q1. What does the first image of the training set represent ?" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "WDW-zdxKxv13", - "metadata": { - "id": "WDW-zdxKxv13" - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# answer Q1\n", - "import matplotlib.pyplot as plt\n", - "\n", - "plt.figure(figsize=(10, 10))\n", - "plt.imshow(X_train[0], cmap='gray')\n", - "plt.xlabel(class_names[y_train[0]])\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "244eb6d5-a902-41a6-ac33-c3d97036780a", - "metadata": { - "id": "244eb6d5-a902-41a6-ac33-c3d97036780a" - }, - "source": [ - "Let us display the first 25 images in the training set :" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "b2e30200-0700-435f-89cb-98e0ad0440bc", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 826 - }, - "id": "b2e30200-0700-435f-89cb-98e0ad0440bc", - "outputId": "ce7d30ed-d045-4673-b567-bf9699df5db6" - }, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "plt.figure(figsize=(10,10))\n", - "for i in range(25):\n", - " plt.subplot(5,5,i+1)\n", - " plt.xticks([])\n", - " plt.yticks([])\n", - " plt.grid(False)\n", - " plt.imshow(X_train[i], cmap=plt.cm.binary)\n", - " plt.xlabel(class_names[y_train[i]])\n", - "plt.show()\n" - ] - }, - { - "cell_type": "markdown", - "id": "f18ae0cd-588e-4087-add7-9d32b727f6e1", - "metadata": { - "id": "f18ae0cd-588e-4087-add7-9d32b727f6e1" - }, - "source": [ - "Now let us build the neural network. Here we will build a classification MLP (multi layer perceptron). " - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "ed84911d-a6d5-484d-9ba6-97570069a4fb", - "metadata": { - "id": "ed84911d-a6d5-484d-9ba6-97570069a4fb" - }, - "outputs": [], - "source": [ - "model = tf.keras.Sequential([\n", - " tf.keras.layers.Input(shape=[28,28]),\n", - " tf.keras.layers.Flatten(),\n", - " tf.keras.layers.Dense(300,activation=\"relu\", kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(100,activation=\"relu\",kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(10,activation=\"softmax\"),\n", - "])" - ] - }, - { - "cell_type": "markdown", - "id": "d18862c4-b4b6-4aec-9312-8c2ee7644117", - "metadata": { - "id": "d18862c4-b4b6-4aec-9312-8c2ee7644117" - }, - "source": [ - "Q2.\n", - " a) What does the `Flatten` layer do ?\n", - "\n", - " b) What do the numbers 300, 100 and 10 represent ?\n", - "\n", - " c) How many hidden layers are there ?\n", - "\n", - " d) Why do we use the softmax activation function in the output layer and what do the outputs of the last layer represent ?\n", - "\n", - " e) What does \"sequential\" mean ?" - ] - }, - { - "cell_type": "markdown", - "id": "491ab5d1", - "metadata": {}, - "source": [ - "**Answer**:\n", - "\n", - "a) The flatten layer transforms the 2D input (28×28 pixels) into a 1D vector of size 784. This is necessary before feeding the data into fully connected (Dense) layers.\n", - "\n", - "b) They are the number of neurons in each Dense (fully connected) layer:\n", - "- 300 neurons in the first hidden layer\n", - "- 100 neurons in the second hidden layer\n", - "- 10 neurons in the output layer (one for each class, e.g., digits 0–9)\n", - "\n", - "c) There are 2 hidden layers (those with 300 and 100 neurons). The final layer is the output layer.\n", - "\n", - "d) Softmax turns the raw scores into probabilities that sum to 1. Each output represents the model’s confidence that the input belongs to a specific class (e.g., digit 0–9 in MNIST).\n", - "\n", - "e) It means the model’s layers are arranged in a linear sequence: each layer feeds directly into the next, with no branching or multiple inputs/outputs.\n", - "\n", - "f) A Dense layer (also called a fully connected layer) is a layer where every neuron is connected to all the neurons in the previous layer." - ] - }, - { - "cell_type": "markdown", - "id": "cf344a37-1423-4295-bcc9-7effe7a6e2b1", - "metadata": { - "id": "cf344a37-1423-4295-bcc9-7effe7a6e2b1" - }, - "source": [ - "The model's summary() method displays all the model's layers :" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "b7d520b6-738e-413d-bf00-a47cc71c1c93", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 265 - }, - "id": "b7d520b6-738e-413d-bf00-a47cc71c1c93", - "outputId": "42afbab3-c5a5-4f85-ee83-85b9898ebdae" - }, - "outputs": [ - { - "data": { - "text/html": [ - "
Model: \"sequential\"\n",
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\n" - ], - "text/plain": [ - "\u001b[1mModel: \"sequential\"\u001b[0m\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
-              "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
-              "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
-              "│ flatten (Flatten)               │ (None, 784)            │             0 │\n",
-              "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-              "│ dense (Dense)                   │ (None, 300)            │       235,500 │\n",
-              "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-              "│ dense_1 (Dense)                 │ (None, 100)            │        30,100 │\n",
-              "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
-              "│ dense_2 (Dense)                 │ (None, 10)             │         1,010 │\n",
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 Total params: 266,610 (1.02 MB)\n",
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 Trainable params: 266,610 (1.02 MB)\n",
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\n" - ], - "text/plain": [ - "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m266,610\u001b[0m (1.02 MB)\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
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\n" - ], - "text/plain": [ - "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "model.summary()" - ] - }, - { - "cell_type": "markdown", - "id": "c8dbecd7-0695-4eda-a03e-ad3cedaf24a1", - "metadata": { - "id": "c8dbecd7-0695-4eda-a03e-ad3cedaf24a1" - }, - "source": [ - "Q3. a) What does 235,500 correspond to ?\n", - "\n", - "b) What is a \"non trainable\" parameter ?" - ] - }, - { - "cell_type": "markdown", - "id": "b86437d9", - "metadata": {}, - "source": [ - "**Answer**: \n", - "\n", - "a) `235 000` represents the total number of parameters (weights + biais) for the first layer ($(784+1)*300=235 500$).\n", - "b) The parameter is not modified by back-propagation" - ] - }, - { - "cell_type": "markdown", - "id": "mSmqvW3tBvey", - "metadata": { - "id": "mSmqvW3tBvey" - }, - "source": [ - "Q4. Display the weights and the biases of the first hidden layer." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "Khr8wuf_DKW-", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "Khr8wuf_DKW-", - "outputId": "18d2cb28-ec1b-4ba5-ffbf-a27c4a8d558f" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[-0.02708957, -0.01657043, -0.02541305, ..., -0.0117284 ,\n", - " -0.07759066, -0.04104815],\n", - " [ 0.03956839, 0.03968426, 0.11159597, ..., 0.00709551,\n", - " 0.10016222, 0.00951595],\n", - " [ 0.0368086 , -0.00992455, 0.00582458, ..., -0.05939534,\n", - " 0.00859205, 0.04936637],\n", - " ...,\n", - " [ 0.0014246 , -0.04466628, 0.00846922, ..., -0.05190999,\n", - " 0.03495238, 0.05571212],\n", - " [ 0.00618674, 0.00718611, -0.04097459, ..., -0.04273593,\n", - " 0.03054574, -0.05612838],\n", - " [ 0.02281788, 0.00126068, -0.07944933, ..., 0.08006408,\n", - " -0.02017345, 0.07210501]], shape=(784, 300), dtype=float32)" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Answer for Q4.\n", - "weights, biaises = model.layers[1].get_weights()\n", - "weights" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "S__6iEM6NwHA", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "S__6iEM6NwHA", - "outputId": "e78e4fc9-64e4-497b-b944-b3e31408b614" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", - " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "biaises" - ] - }, - { - "cell_type": "markdown", - "id": "w0aWN8LMwFS2", - "metadata": { - "id": "w0aWN8LMwFS2" - }, - "source": [ - "Q5.\n", - "\n", - "a) **Why don't we initialize all the weights to zero (as is done with the biases) ?**\n", - "\n", - "b) **What happens if we initialize all the weights and the biases of a layer with the same value ?**\n", - "\n", - "**Answer**: \n", - "\n", - "a) If all weights are initialized to zero, every neuron in the layer learns the same thing. Specifically:\n", - "\n", - "During forward propagation, all neurons in the same layer produce the same output.\n", - "\n", - "During backpropagation, they also receive the same gradients.\n", - "\n", - "As a result, they remain identical throughout training — this is called the symmetry problem.\n", - "\n", - "By contrast, biases can safely be initialized to zero because they are scalars per neuron and don’t affect symmetry in the same way — they don’t control how inputs are mixed.\n", - "\n", - "b) Same problem: no diversity in computation.\n", - "\n", - "All neurons in the layer will compute the same output (same weights + same bias).\n", - "\n", - "The network loses its capacity to learn different features, which defeats the purpose of having multiple neurons.\n", - "\n", - "The gradients with respect to each parameter are also the same → weights evolve identically, maintaining this symmetry forever.\n", - "\n", - "Thus, random initialization (usually with small values) breaks this symmetry and allows different neurons to specialize.\n", - "\n", - "----\n", - "\n", - "The initialization is usually random : the weights are sampled from a normal distribution or a uniform distribution, usually independently. In particular in the context of deep learning, the variances of these normal distributions are important to keep a relatively constant scale (in the neurons from layer to layer and in the gradients when doing the backpropagation).\n", - "\n", - "Remarks : when you create a multilayer perceptron (MLP) using Keras, each dense layer by default uses the Glorot Uniform initializer for its weight matrix and initializes the biases to zeros.\n", - "You can always override these defaults by specifying a different initializer in the layer's constructor if needed. Actually here, as we used a ReLU activation, we used the \"He\" intializer (it does not matter that much to use \"He\" or \"Gloriot\" here as the network is shallow. However, even for a shallow network, it is important for the weights not to be far too small or far too big.)\n", - "\n", - "See also :\n", - "\n", - "https://www.deeplearning.ai/ai-notes/initialization/index.html\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "b0bd0771-3463-46b8-bdef-5bcadbc07052", - "metadata": { - "id": "b0bd0771-3463-46b8-bdef-5bcadbc07052" - }, - "source": [ - "Now we need to \"compile the model\" : it means we will specify the loss function and the optimizer we use. Optionally, you can specify a list of extra metrics to compute during training and evaluation. " - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "3fcfe918-d745-4c66-8350-dd89e34ac93c", - "metadata": { - "id": "3fcfe918-d745-4c66-8350-dd89e34ac93c" - }, - "outputs": [], - "source": [ - "model.compile(loss=\"sparse_categorical_crossentropy\",\n", - " optimizer=\"adam\",\n", - " metrics=[\"accuracy\"])" - ] - }, - { - "cell_type": "markdown", - "id": "5d06aed8-0611-461c-979c-9d14e3fe895f", - "metadata": { - "id": "5d06aed8-0611-461c-979c-9d14e3fe895f" - }, - "source": [ - "We used the `sparse_categorical_crossentropy` loss because we have \"sparse labels\" : for each instance, there is just a target class index : from 0 to 9. If instead we had one-hot vectors ( e.g. [0,0,1,0,0,0,0,0,0,0] to represent class 2), then we woud need to use the \"categorical_cross_entropy\" loss instead.\n", - "\n", - "Since it is a classifier, it is useful to measure its accuracy during training and evaluation, which is why we set `metrics=[\"accuracy\"]`. You can find the list of metrics proposed by keras here : https://www.tensorflow.org/api_docs/python/tf/keras/metrics\n", - "\n", - "Q6. What loss would we have chosen if we had a binary classification problem ? See : https://www.tensorflow.org/api_docs/python/tf/keras/losses\n", - "\n", - "Q7. What basic loss could we use for a regression problem ?\n" - ] - }, - { - "cell_type": "markdown", - "id": "813aff4b", - "metadata": {}, - "source": [ - "**Answer**:\n", - "\n", - "Q6) BinaryCrossentropy\n", - "\n", - "Q7) MeanSquareError or MeanAbsoluteError" - ] - }, - { - "cell_type": "markdown", - "id": "63c7c396-cd50-4822-bbf0-abcb0361fa01", - "metadata": { - "id": "63c7c396-cd50-4822-bbf0-abcb0361fa01" - }, - "source": [ - "Now the model is ready to be trained. For this we simply need to call its `fit` method :" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "e784cc36-b04c-4aca-abfc-9fc081fd726b", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "e784cc36-b04c-4aca-abfc-9fc081fd726b", - "outputId": "2b3ac988-ef08-4d0f-ece5-feb82c59c986" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - accuracy: 0.7850 - loss: 0.6068 - val_accuracy: 0.8392 - val_loss: 0.4062\n", - "Epoch 2/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8627 - loss: 0.3769 - val_accuracy: 0.8496 - val_loss: 0.3903\n", - "Epoch 3/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8785 - loss: 0.3303 - val_accuracy: 0.8546 - val_loss: 0.3747\n", - "Epoch 4/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8869 - loss: 0.3037 - val_accuracy: 0.8564 - val_loss: 0.3778\n", - "Epoch 5/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8955 - loss: 0.2810 - val_accuracy: 0.8696 - val_loss: 0.3513\n", - "Epoch 6/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9019 - loss: 0.2642 - val_accuracy: 0.8624 - val_loss: 0.3813\n", - "Epoch 7/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9075 - loss: 0.2505 - val_accuracy: 0.8692 - val_loss: 0.3840\n", - "Epoch 8/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9107 - loss: 0.2379 - val_accuracy: 0.8690 - val_loss: 0.3768\n", - "Epoch 9/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9154 - loss: 0.2250 - val_accuracy: 0.8708 - val_loss: 0.3813\n", - "Epoch 10/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9199 - loss: 0.2152 - val_accuracy: 0.8698 - val_loss: 0.4006\n", - "Epoch 11/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9217 - loss: 0.2051 - val_accuracy: 0.8742 - val_loss: 0.3909\n", - "Epoch 12/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9261 - loss: 0.1969 - val_accuracy: 0.8716 - val_loss: 0.4219\n", - "Epoch 13/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9292 - loss: 0.1890 - val_accuracy: 0.8752 - val_loss: 0.4213\n", - "Epoch 14/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9312 - loss: 0.1828 - val_accuracy: 0.8738 - val_loss: 0.4402\n", - "Epoch 15/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9324 - loss: 0.1763 - val_accuracy: 0.8736 - val_loss: 0.4419\n", - "Epoch 16/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 3ms/step - accuracy: 0.9362 - loss: 0.1691 - val_accuracy: 0.8732 - val_loss: 0.4577\n", - "Epoch 17/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9379 - loss: 0.1626 - val_accuracy: 0.8760 - val_loss: 0.4588\n", - "Epoch 18/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - 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accuracy: 0.9673 - loss: 0.0903 - val_accuracy: 0.8754 - val_loss: 0.7853\n", - "Epoch 49/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9678 - loss: 0.0856 - val_accuracy: 0.8808 - val_loss: 0.7499\n", - "Epoch 50/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9682 - loss: 0.0821 - val_accuracy: 0.8824 - val_loss: 0.7406\n", - "Epoch 51/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9691 - loss: 0.0808 - val_accuracy: 0.8826 - val_loss: 0.7655\n", - "Epoch 52/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9710 - loss: 0.0757 - val_accuracy: 0.8822 - val_loss: 0.8760\n", - "Epoch 53/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9696 - loss: 0.0804 - val_accuracy: 0.8860 - val_loss: 0.7731\n", - "Epoch 54/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9731 - loss: 0.0747 - val_accuracy: 0.8806 - val_loss: 0.8113\n", - "Epoch 55/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9705 - loss: 0.0768 - val_accuracy: 0.8864 - val_loss: 0.8137\n", - "Epoch 56/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9703 - loss: 0.0798 - val_accuracy: 0.8814 - val_loss: 0.8953\n", - "Epoch 57/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9689 - loss: 0.0814 - val_accuracy: 0.8794 - val_loss: 0.8376\n", - "Epoch 58/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9722 - loss: 0.0756 - val_accuracy: 0.8806 - val_loss: 0.8223\n", - "Epoch 59/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9736 - loss: 0.0702 - val_accuracy: 0.8868 - val_loss: 0.8391\n", - "Epoch 60/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9720 - loss: 0.0726 - val_accuracy: 0.8838 - val_loss: 0.8715\n" - ] - } - ], - "source": [ - "history = model.fit(X_train01, y_train, epochs = 60, validation_data=(X_val01, y_val))" - ] - }, - { - "cell_type": "markdown", - "id": "pft_8LriRFk6", - "metadata": { - "id": "pft_8LriRFk6" - }, - "source": [ - "Remark : if you call the fit method again, keras continues the training where it left off.\n" - ] - }, - { - "cell_type": "markdown", - "id": "xkoeO0kLF3fp", - "metadata": { - "id": "xkoeO0kLF3fp" - }, - "source": [ - "Q8. Can you recall what is an \"epoch\" ?\n", - "\n", - "**Answer**: An epoch in training a neural network is one complete pass through the entire training dataset.\n", - "\n", - "During an epoch, the model sees every training example once and updates its weights accordingly.\n", - "\n", - "Usually, data is split into mini-batches, so multiple updates happen within a single epoch (this is mini-batch gradient descent).\n", - "\n", - "Training typically involves multiple epochs so the model can gradually improve.\n", - "\n", - "Think of an epoch as one full cycle through the training data to learn patterns and adjust weights." - ] - }, - { - "cell_type": "markdown", - "id": "eSKrY64nFqdj", - "metadata": { - "id": "eSKrY64nFqdj" - }, - "source": [ - "Q9. The `fit()` method also has the two arguments `class_weight` and `sample_weight` (not used here). When can these arguments be useful ?\n", - "\n", - "- `class_weight` is used to give more importance to underrepresented classes.\n", - "- `sample_weight` assigns weights to individual samples, useful for noisy data or time-sensitive importance." - ] - }, - { - "cell_type": "markdown", - "id": "a-6IJhqnMcnm", - "metadata": { - "id": "a-6IJhqnMcnm" - }, - "source": [ - "The `fit()` method returns a History object containing in particular a dictionary (`history.history`) containing the loss and extra metrics it measured at the end of each epoch on the training set and on the validation set (if any). Let us display the learning curves." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "_UQsOj8JPc3q", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 470 - }, - "id": "_UQsOj8JPc3q", - "outputId": "8f1d6388-d46b-4891-d73f-793ccf3b9d32" - }, - "outputs": [ - { - "data": { - "image/png": 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5WwKeatDAKz6ZaEMRyf+3g6WC7KBL3MJONIMGhfoohRBCCBFiJD6FSdj54ANgwwZg40YzKC5tvCVrPrLoOGFWt7VY0spJ62SFCkg45xz8Hh+PyldckbTIeaAxlEIIIYTIEkh8xjrsp81OOqxfyaQeu+zaFejTxxub6a+oOEsBUUAWLeq9jxbLefOMRZOxlqcThk7Fx2P95Mk4r3nzUB2ZEEIIIaIQic9YgBZKdtuhG7xsWXPfli2myw5d59aC6YalgiwUkj16GKFph+2w41tKiMXJ3SWHhBBCCCGCQOIz2upezphh3OPuQTc561xSQI4cabYtVcq4xyk8WVqIRc8Zt2lHrVre/bIVo/0/IYQQQohMROIz0qCIXLPGlCjiYJKOLVDO+pVs6ejPkkkL5f793tvs9U33OJN+/FkwhRBCCCHCgMRnuKGgZLylFZu0Yvq2dLTik4KyRQvTvpFucfegSKUF002jRqE7DiGEEEKIAJD4DAUHDgDLlwPLlpnBYuhDh5rHWMNy9Gjgn3+S1rGsWdOMhg2T7uunn0I7dyGEEEKIDETiM7Ng955ffjFik3GZblg4fcgQryv88ceNCKXYZPcePi6EEEIIEYNIfKaXXbuMNXL9euC557z3f/UVMGuW9zbrYdarB1x4oRmM27Ti88EHQz9vIYQQQogwIPEZLCdOmESeH38Epk4Fli4191NIsuUjk3tIz56m048Vm8WLh3XaQgghhIg+1q0DWrUC7rsP6NsXMYHEZzC8+qrp9MOMdDd16gBXXmn6nVtuuSXk0xNCCCFEbPHuuyYtZMAAU1GR/V2inWzhnkDE9jWnZZNZ5n/+6b2fsZgUnkwIuvVW4JNPgG3bTDIRhWksvCOEEEIIETEFcb74witNBg9GTCDLpzt28/vvgW+/NcKTLScJSxg9+qhZ79jRxG2yQDsThIQQQggRu+zda4xQTBym+mN3QCYGs9tfWjl0CFi8GFi4ENi3z+yPHlQ2gPEpmTh3rrFxUXJQiNIK+uSTQJEiyFyYl/LHHybMkOPff4EyZUz+yjnnJB2FCgW9e4lPvqFoxfz116TF22nFvPpq4KKLvPexx7m7z7kQQgghMh9+Px87ZsLbqMKSG9zu+HHkpUGJgilvXiBHDjOyZ0+6zlwNbr99u1dgupcc7uYtFgrE2rWB+vXNoFGK1WpYi9tfZ0LW8KbQXLDALNes8d8shoK2enUjRE+PCePYzjofunY1xXO4KwrQp57K4Nf36FEjiKl2reDcsyew/y1Y0CtE2V0xALKe+OQblz8jqN7J2WebM8o3AhOD2rc3g28mWTdFVmTLFlMmjL/w2ZZV3bFiG3p5Zs40CZQMIeJ5b90auOwyU5M42uC1fMUK46ucONF8qV5+uYnLv+IKb1JoNEAxRevTokVGGHBJ4cKWyfTK+Y4KFYCyZY2wSu61Yd1pWvMoLOygwOL3HUUVBRCXya3zudk5L7nnCBTO5a+/TNLupk1mDpzbwYNm6W+48ypSgDbJKwPZkMfM69upUylvR4tf5crmmDlfzoXngyPxSXMar6j1jv79txGb3J7vQV/KlzeNYCjWVq4071keO5ccAE4hG77AFkd8dl79LFqXKI9b0BODXzqCh4tMQL4yRUwyM8+JXbotp3yN+dwMF7SDn3e7zuNYssQITc7T9/WlmGat8WbNgEqVjEhn8CkHvye45HmjJXftWjMCJOuIT36Iv/zSdBPKk8e80HzjsVsQL1L8lUHVLkRWhReRl18G3nrLuJcIPxNs6Uoxwi/uzLb800rACyG/EHjRo9UiK8GLvz+LSEbC/f/2mxGbHPyhwdfdMmeOqUPML9Pmzc2556ClJzN/iFgBkBZRw2PiNZ3Xcg53rD6huBk50syf4oCpwxSjTZv6t1a54WvD/6cI/P13ZFu/HrX++Qdx//1nPhMBWnoCFmNWZHJJYUBB4u+z6tsNz0KrHo0rFKP88UBxacUml6kJrUDg55IWOoos92A+hL/3CI+N1kSeIx4TB9fpcs4o+H1+Wkx6smVDwqlTyObxIC6l46UusP9L4U6ByY6B7iVFF3WC+1j42ttjsMfDY+FtWwHHTeHC5nrWuLERnI0anZkjwv1SsFrxuWIF5i7IjW3/lkFh7EerpQORDQnohxbYdKQSRt6/GL1wulmNrxWS87UCM5jrCY1xFJr8XHDQIOfbOdEXillamK0o5efkxRdTfao4jyezr3Tp5+DBgyhcuDB2796N4sGWLOLh8QL79NPeNwX3wS+4qlUzZb5Zkfj4eEyePBlt27ZFzvTEwtgLwtat5kLMdX6YGFPCJQd/PITLGscvHM6Ngx84LmlJ50W+ShXznuIymIAcHiO/3Pjr147Vq42LKX9+7+BzuG/b+/h+Zlkv/jpPyzli+bBhw4Dnn/e6WRh7xDlZEWov0Lx4WjHaoEH6rR+Exzltmvlx+M033i8kzpHPwRazHLwYRoPVil92fE0pWrjk4DHSDbhjB7Bzp/8lx549OFq8OHL17o3s995rLBkZwe7d5jXmtZAx7XzPuqEli+eVX5AUPlOmmPPv+8VEwcZzT/GW0rngdZfva4ppvod4jLSa8Hm5dK/bJbfh+4lf+u7Pkl3Souf+3PM5KNAmTDCC0z1fCso2bYAbbjCvIY+dg58tN/ySvuQSc1wU2nzvnRaZiUvuNyUBQxF26aXGUswlBVhq0OLEz7h70OrM8+RP6FEE8Nzw88AfARSkvD76js2bk/6QSA4et7WWcfBHJV9P93s2uXW+T/l+9gffE1aI8rzxtaMwo3eRx+wLP+M8Hl5vOAeKNPfgdd/3NsWQS2gmLpO71lGM2/ciB8/l6fX4Y6cwdGReXNMlHyqdn4rISgkrHK0Q5fnkDwCKTF4z+f5Ngyf1gQfM78DubXfiow6TnNd+2Izzcd+MG1A+z078Weta5Ny/y1y3+d5NSc7xfeT7XcIlvVu8tlJ00hqbzu9Wq9cOHDiAQinEgsa2+KTAZFGs2bPNbb7QTB565JE0BciK07hN7Bxr1sCzbh0OHT+OApUrIxtFEH/V8cvKveSgKOObmxdPXpj4C5LDvc6LqFv0+MIvKCtErSjlB8lekHyHvUDZYeN+fON/7Lq9zYsUvxjdYtPfBdQfrIzg7wuUF2cWbbMikwE8vFD5lu8KFh4jrTAs8XXttX7f32eIT370+cXNz4i1ovBCxMoNFLP8guFnh0KEosXXpcIvL4oQXrh4fBy0HgQiSPlrefJk04yBiX42wc++djwHvgLJzs+KUQ6KJnux5BcM50w3E38kcOle5xeojQlLKWaMX0ycD9/nHHyv2nXfwf26v5ztc2QE/LLo3h146CHz5Rws/BxR0FOY0f3nvtRTfLRo4bVq0sLjK+xoPeR55/mfMcO8jhZuy8+z/SJ3faEn3s5oOGfOk+8zvvc4L4ot9+vVtq0RnFzyuuAL31NsCmLFKEVvoM99+nN8qlIl/L1qFc7dvBlxvmKW8FxRiHJQeFCs8TNuP+scvJb4g59LeuEoMq3YpLjl5yEQ7DWL557XVL4/rcB0u2f5Az6t8DloxXT/WObg+yUlOcEfBP7iJFOzrGWiMYS/uVk7k5cx/iaLJE6dMo4nvkV5ieRbmvASR6M231Yffwx06+b6B1rEad3mZ9UtMvn+zQhDQQBs2nQQlSplZfHJoFl+Odk3/f33my/ZzLSc8IPON3qgF4rMnAd/BbkH35TudX558GLNwTeme+le55cpxdJpkeks3X3og4XngvtOzd3CDwp/hfH1tAIgvQIto+D8aYWhyOaguKYotZaSQL/QfF8XXzcWP7i+MTr+brO7Fn9oWXjeOnSAE6FOYXH64pvkgswEu8ceM8HvhEKCNWxZRC659y+/6K2rll/gyVkykrNc8XX77jsjOLkPt/WEV9lOnczg55Y/EvjlSRewHf7iiWwYAN/zyVljwg3fyzy/vPbQKkY3bTLL+MKFsXLQIFw4cybiTsd9OdCK9/DD5lsyJcsERQEFJ39UuOPRCL/4rdWaVo7U3M1u+GOQ11T7Q4Ru+2DguefnxP1D1N86n4efo0Ctj9wvE0Ovv958O/OLNlD41UdBSBFK5UGLL8+D7/uWg5/z0697ks8Rr0sMW2DMLAdfl0C/UnkNYZazbavMzzzPUTDnJZKg4OF3hBWjPHe8hluxyetber1iGSw++bbhx4UvOb+SIinKZ9Ys8/uF9hoKTbdGf+UVk/HO3+J8C0dKegovPw0bHsS+fVlZfPKweIHlh/rZZ70JRpkBxRlj5T791Fz86Hpp2dJYoviBC8aMTasJ3032YsYLPsVGSpY8O3hx5icoJathRsEvCr7zOapXx8nKlbFwwQI0Kl8eOehe9Oda880a5Jcx42k4aMGy6xwUI74iiK+N2yLlHhRh/rIefe/ja5SMC+YM6w1fUx6nFZlWcPIDldI55Xz8fYFyyfPD4/ONlaJFJz0/WvjlPHasqT1LMep+jTt3diyi8fXqYfaIEbh86lRkY0kxwvdrnz7GGxBMcglfH1rT+KVtv2g4gnnvUaRed50ZtPCkdgWlS5Ii24pRiqvkXIz8wnH/mOJwu+tSG3wt3KEeyQ0+R3KJGVxyBGFxSPzSbNMGOXmsLOrHUAR7meb1hCKUFm77TcnX3bqe6d608Dh4LeI3LMvEpRKWERT2M22Pz9dr4F635yI9+MRdOp6IJk2MmE7vvjNS2NDq5Baj/AFBQcvvIbfQ5HnM9Fo5WZdAxCc/UvzdZyMd+BuEX9uRQq9ewNChwG23AaNGJX2Mv3mo6/n7nzl1/HiHG3698yO5bh1jlLOS+KQo6d/fxHbaOClesDLzlxYvLC+9ZC78yb2MFC8UoVaM+opgCiF+eduLFd2cvIClF170eXGjZcgu7bAXPX+uSd/7KLJoATgtMhMFp0/iSUC/NGmZ4k84nit+cvy5xWIdirbMtIzbxIsxY4DPPjOvt32oQgV4tmxBNr7n+P64807zmcmo5gjcL63ivoLbWq547PzypdikhZOiOz3xRXyPcv8Uer4W+xC5mDIav58jujPfecckzNjwBF4H+TrSgu22QvK4mdltBWcg8Yci8+LbM/vzLtJ8jhj9wMuR5YkngIEDERGcOmVsHbx8MzqJjg9fKHUoPxidQTtAOIuSUGoxUosCvkyZg9i6NXXxGTufCtqg+TPB1qfimcgs4UlX5QsvmIL0Fro56dbnhWb6dOOW5C9gWghoEeUgFHIUobT00apJsenrgqY1iq5HG8BOl1RK1jw7aOmwQpPCLtJK5DDOiDGBWZnM/iLiObdurtdeM+9FCtGvvkLc33+D74iEq69GNsZ18kdERsL3H39UcPiaEHh14s/1YBMGU4Iik27KWIdWcVYgYFjEhx8Cb79tkhvef98rOHlNYawjr0OMmRWRgYRnxEK3NqFM4OWJX9mRwi+/GOHJr3J+tP3BUPBBg0y0yM8/J79dZkNJ8uCDRnhSuowfb3L3UiM2Phl85Sk8CS/QmSW6KBQpOvkqEz7PjTeaaq/uL0F+8dOVSUvf/PnmXU0RwHcJrUAcbujis2KTg4HYIYqNETH+xWcTSoYNw8kpUzB30yY0ffhhZAv1+4vPl5HCMyvCbF+GR/BK//XX5rpCswcFp15bIdIkPukAYtF2OoyYNB4JH6UJE8ySzovk8rEYMtCzp8mGZ9RfuMQnnTLDhxs5xMivQO0B0S8+6Ya64w6zfvfdJiA/o2U9xSZFJ3+OWEsDuyLR2lqtWsqWPrrAOFj3ikERfMfzS4PuSXZPktgUoaBAAXg6dMB++nBE9P+osLGyQog0fa0zyo106WK+lumGZ1EHRqyE2+X+xele7rRtpQRzRin8rG2Lv0VDCb9Oevc263SmXXON/7K0sSk+aWFkWQm6c+lmDLSmIpN6aNdOLiPcfZ8tncKfILffbp6TbvNgoUucVgoOIYQQQoQc5mSyrCztQyzFySghik/ahcItPmfPNnNLyeVuoey5+WZg9Ghj/WQhkVDBVBUKd8oj2v9YxTIYckS9u52FughjoXwTWJgBbdtW2cHbzEYOBiYx0KrKV5dRwEIIIYSIapc7nY8ss0TxybDqSIj7nHDa5c5yzYE4RJkoRfHJrHdWo8voUH5/0G7HLuSUUnTeMmwh2GjHHFFtN2erTMJOICyYzJQvusit0Eyu6C0tmMzcZua5OwvcX2Y4B8vVZEIhXCGEEEKEFutyZz6vXTKajnUq6RhNi2Mzo1zuX34ZmMvdQinD2NBJk0z9z48+ytQpOqksfD7mPLIELuebFnkUveKTMpsFqxl3SWskayawwK0vLCPDjhEcjITlknGairEUQgghshS0R1nLJ612hE5TWkFZgIbxk0zkCafLvVgxY08LFBbaofhkUR3mXLPgSGa9dow8ZIU32uUowdLaATg6xSfrIjDSlXXv2HfKdr5g6RXaghl1awUnU8KEEEIIkeWhQ5T9EWitY/dTC13vFJ90vYdLfH7+eXAudwvjVilWGYn4+uumGltm8Pzzpnw0cx6ZFMXKkWklQpoyBQgDGh54wLjBafdl5w8KT76D3nvPvKNYZIopYMx6l/AUQgghxGms1ZOywd1O05YmpuXT5hiHkpMng3e5+1o/yQcfAGwymNGMG2d6khCm2gRjmY168ZmTlUtZ1Iq5/HzXUGQyRY024LvuMnXwhBBCCCFSiPe0LncLxShLbrPdprtpWChd7rt2mTqjrM4YLMyMZ5diNn5j8lRGwnLlbPNJmHedEZbhqBKfHnfvZ1o9WVqJ0bZCCCGEEAHGe9pkIwvd3Pa+cGS9f55Gl7s7DcZaP2mjY/51eqGQfeYZ87ocP26iGpnUlBFElfhMdKP36nVm+z4hhBBCiGRgJjv7u1DcNWly5uNWVoRafJ5Mp8vdwmjEWrWAAwdMAhVrgDIrPS388ANQo4bpj8M0m6uvNglNrAqQ5cRnHPukV6oEDBwY7qkIIYQQIgpd7kzQYfnu5MQnXeC09IWKWbOMuz+tLncLncM//mhc5LSEMjmIxX1YFIiCNBD+/Re44QagbVsj1s85xwhjOpt9S6lnGfHpMGqU6V4vhBBCCBEgybncLbT0nXWWcTczlSTULvdOnUwmeXpgdUnKpCVLjJCliKarvHJlUwyeVlZ/8H7Gip5/vslkp4XzkUdMBUvOK9gi8jElPk8xqeiSS8I9DSGEEELEmPikwAq16/3kSW9bzPS43H258EKTuU+LJa2ftKzef79xy7M+p7v/zsKFxhr88MPA4cPGZU/x+sYbGWvtjFrxmfD00+GeghBCCCGijL/+MvGPtOg1bZr8dqEWnzNnGmHICpK+GfjphWKaSULsKs4kJD7HunXmPh7nL78YQUqxuWyZafDIqpWsd8oy6ZlJVIlPuduFEEIIkVarJ3vQsKRSSiWLrDUw0DjJSHG5JwcTrCgyWWC/Tx9TYJ8F6elIpiueVtBbbwXWrzdVK92FhTKL6BKfQgghhBAZ7HK3lCtn3NQsNG8TlKLN5Z4cLIXO+E9aPzt3NvfxWClER48ObV8eiU8hhBBCxDSBis9Qut5nzAD27AFKlgxsXhnFueeajkVbtwKrVqUvwz6tRGdvdyGEEEKIANiyBdi40cR7NmsWmPgcOjTjxOeJE6Z70Y4dwM6d3uWkSZnvck+Js89G2JD4FEIIIUTMWz3r1QMKFUp9eyb+MO6R7mkWpWety0ChJbNfP9P524rMfftS/p8uXZDlkPgUQgghRMwSjMudMOubiUlsUclyRd27B/Z/TNzp1g2YPPnMx2h1ZUwlx1lneZfMKg+lyz1SSFPM59ChQ1GxYkXkyZMHjRs3xkKmhaXA4MGDUa1aNeTNmxflypVD7969cezYsbTOWQghhBAiU8RnWuM+6aqn8MydGxg50sR00gLKUkp0vTPGcvlyYOpU4JNPgNdfN1nmGV3APSbF5/jx4/HII4+gf//+WLp0KerUqYPWrVtjJ23Lfhg7diyefPJJZ/u1a9fiww8/dPbx1FNPZcT8hRBCCCH8QsH3xx/GjX7xxYH/ny25RPHpLsieHEzceewxs/7aa0CPHsZ9X726aZsZivJF0UTQL8egQYNw5513okePHqhevTqGDx+OfPnyYSRlvh/mzZuHZs2a4eabb3aspVdeeSVuuummVK2lQgghhBAZYfWsW9e40wOlSRMgb15g+3bTYjIl6Mi96SbTypI90Xv1St+cswJBxXyeOHECS5YsQd++fRPvy5YtG1q2bIn58+f7/Z+mTZtizJgxjths1KgRNm7ciMmTJ+NW2pqT4fjx486wHDx40FnGx8c7Q0Qe9rzo/EQuOkeRj85R5KNzFF3naMYM2tiyo3nzU4iPTwh4H4zRvPji7Jg2LRumTj2FqlWT/9/HH8+GVauyo1QpD95//2Sy/dOzAvEBfi6CEp+7d+/GqVOncBajZF3w9jqmhfmBFk/+38UXXwyPx4OTJ0/innvuSdHt/vLLL2PAgAFn3D9jxgzHyioil2nTpoV7CiIVdI4iH52jyEfnKDrO0eTJLQAURP78izF58vag/r9MmcoAauCzz3bhvPMW+N1myZJSGDKkibN+992/YvFi/yGIWYX//vsvoO3iPFSEAbJ161aULVvWcaU3oU36NH369MGsWbOwgKlhPsycORNdunTBCy+84CQn/fnnn3jooYcc130/1iMI0PLJRKVt27ahOIMnRET+2uEHvVWrVsjJXl4i4tA5inx0jiIfnaPoOUe1arXCeeflQ1ycB9u3n0TRosHth/3OGzfOiQIFPNix46TTptINSynVr58DO3fGoVevUxg0KHDLaqxCvVaiRAkcOHAAhVKoaxWU5ZM7zJ49O3bwFXfB26VLl/b7PxSYdLH37NnTuV2rVi0cOXIEd911F55++mnHbe9L7ty5neELP+j6sEc2OkeRj85R5KNzlLXO0a+/Avv3A1ddlSG7E6f59ddczrJ27TiUKhX8uWrQwCQL7dkTh2XLciYpUE+z3d13mzqetWoxySg7cubMjqxOzgA/E0ElHOXKlQv169fHdBa+Ok1CQoJz220J9TXB+gpMClgShNFVCCGEiDmOHAFatQLatQM2bAj3bGKLX34xNYyYdZ4WKF3cWe9uhgzxllUaOxbIkye9s81aBJ3tzjJLI0aMwMcff+yUTrr33nsdSyaz30m3bt2SJCS1b98ew4YNw7hx47Bp0ybHFE5rKO+3IlQIIYTIivz4I3D4MA05jFFETLB+PfDgg8DixeGdx6xZRuKkp4i7v3qfK1cyyciss1ZnzZrpmmaWJOgOR507d8auXbvw7LPPYvv27ahbty6mTJmSmIS0efPmJJbOZ555BnFxcc7y33//RcmSJR3h+eKLL2bskQghhBBRxtdfe9cpcO65B1ELnZnDhwOPPgocPWosgoybLFcu9HM5cCAX1q41ls/mzdMvPhkaceiQ6cFuyyrRWn3//Rk04SxGmtpr9urVyxn+YIJRkifIkcMpMM8hhBBCCANL8nz7rff2zz8Dp06ZMj/RButh3nGHt7UkC9Owz/kNNwCzZzNsL7TzWb3aJCfTKlmiRNr3c+65QKVKwMaN5jimTDFdi2hvY3nzrNidKCNQzX0hhBAiDMyZA+zda5JamBi8b59pvxiN1lsm3dgYyMGDgd9+M0XdWQSHltBQs2pViXTFe/qzfj73nIn1JB99ZPqzi7Qh8SmEEEKEgUmTzLJ9e69ICqaXeLhhrOpddwEdO5r+5XXqsO4l8NBDwHnnmf7lhIJt3LjwWD7TE+/pKz5tDCuPT5UJ0ofEpxBCiCwNqwcydo89wEMZH2nFZ4cO3qxqVzGZiIYxkBdeCIwYYVzPTMChlbNGDe82V18N2H4yrLaYWpvKjILu/r//LuysX3JJ+vd3+eVe93rt2sDAgenfZ1ZH4lMIIUSW5o03gHffNRnaoWLFCgok0z/8yiu91rVffjG9wiM5TpUNCC++GPjzT5NMxFjVV181Lndf/vc/oEULU1LquutM0k5mM2eOUYoXXODJENc4Y0ZpnWZ4xKefqqxSRiDxKYQQIkszf7637NHWraHNcqfwZHLOBRcAZ59thKedT6TBOqQUnYx9ZGLUzTeb2M6U4iqZPPXZZ2xVCbAL9513GqtvZjJ7thGfl1yScR2HaKX+91+VVcooJD6FEEJkWeLjTZwiYa3NMWNC87zW5c54SUK3bnIFzSPldeL86FovXNhYADmYVJQatD5OmGDKFI0f703ayQwYe/rdd0baNG+ecSqX58efZVekDYlPIYQQWZZVq0xNSguzmDPbMvfXXyarnSWxGReZUkHzSOHLL02YAEsM0dpJq2cwNG3KFpRmndnvmWHd3bzZWGY3bYpD4cLH0aqVuihGKhKfQgghsiy05JHGjU0s39q1md+Zx7rcWfzcXYPSWj75/Oz1Hkm8845Z3nsvUL582vbBLHHW/aQV9cYbgV27Mm5+TGaiwGV3pXLlPHjhhTkoWjTj9i8yFolPIYQQWRZmbdvYy06dvNbPULrcLeecA1SrZtz/Pv1awgrDEubNA3LmBO6+O32u6w8/NMf4zz/GesrY0fRCKyotnozJZOzszJknUa7c4fTvWGQaEp9CCCGyLG7L5223mXUmyLB9YmaVAWJGuy2x5EskllyyVk9aLUuXTt++ChY0LnwmWTG8gJnz6eGHH0y4Agv0X3SReW3D0c5TBIfEpxBCiCwJXdvMwCaNGpmSQGXLGiHjbnuZkXz/vbH2sV4kWzf6Emlxnzt3GjFOMqoUFWuBsj4oef55b0vOYGHC0zXXAP/9Z4q+8zVjOSQR+Uh8CiGEyJIsWmSW7N1dsqQpC9Stm7nv449D63K3sGwRE5EoiulGDjcUiSdOAA0bGutwRkGX+333eS2qtDrTisl40EBgC89bbjF1R7t2Bb75BsifP+PmJzIXiU8hhBDI6i53S/fuZkkhxM5HGQktdFOmpCw+mSRTv35kuN4pBFl8n2RGAf5Bg4zY5utCsd+2rXHrs2Unj91fPCgrEbBrUu/e3iSm0aNNPKqIHiQ+hRBCZOlkI7f4ZDIMYwcpfOjWzUjoFmZZJ2aL162b/HaR4nqfONEU3WedTlonMxrWzaTInD3btDfl8+zda6ytfA0YAtGrl4njZBIWrZwsUv/yy+b/X3oJePNNYykW0YVOmRBCiCwHLWjW8kmx6cZaP0eNytian7bEEq2etle4P9xJR5ldczQl3n7bLO+5J/MKrFM4suQUC88zzICCmwKzWDFjeR461PRnp2DndsyW5/9QoPbtm/LrKCIXiU8hhBBZjk2bTDecXLnOtEJ27mzEFgvQL1uWMc9HSyrjElNyuVuaNTM1R2l1tAlRoWbpUmDuXNOVKD3llYKBz0Xh/f77wPbtJhGJPwQKFTLClJZqnhdmy/fsGZo5icxB4lMIIUSWw1o9KTx9rXqMu7QCMaMSj1gnk2KX+6YFLyUoPClAwxn36S6vxL7soYYxnG3amJqrtIAyUYsu+J9/Tl28i8hH4lMIIUSWw1+ykT/XO+M+me2dUVnubKdJC19qhDPuk52HbHmlBx5A2KEYZ01UCmJ2MRLRj8SnEEKILIe/ZCM3rVoBZ59tisKntQ6lhXGbqZVYSk58zphhEm1CCeMpWWS/QYMz42GFyAgkPoUQQmQpKKxsLGdy4orWSdaRzIh2m4wd3bjRWPBatw7sfy68EChSBDh40LS3DGV5pWHDvFZPJfSIzEDiUwghRJZixQrjSi9RwhSYTw7remdXIrqi05vlTmtqoIXQWfCeHZdC7XqnhZZ911n2iIlXQmQGEp9CCCGyZLwnW2qmZNljG0i6nun2Hjs27c8XrMs9nH3ebaIRC71nVnklISQ+hRBCZClSSzZyw7aP6cl637LFuM1Zm7J9++D+18Z9suQRuwAF4zq/8UbTEnP+/MD/b/lyU9CdIQes7SlEZiHxKYQQIksRjPjs0sXUAmWMKN31aXW5s3QS+8cHQ5UqwDnnmBCBOXMC/7/HHgMmTAAWLwYuvhh4+unAMvat1fO660x3ISEyC4lPIYQQWQbW2vzzT6/bPTWKF/daLNNi/bQud5YKChaGBFjrZ6Cu9zFjvJ2JrrzStKVkG0oe68qVKb8utp1oJJRXErGNxKcQQogsw8KF3h7uLPgeCNb1TnFGl3ag7NsHzJqVdvEZbL1PWmfZmpL06wdMnQp88YUR0LTaMn71tddMtyVfPvjAVAGoV0+1NEXmI/EphBAiamDNzN9+8y+gMtrlbmF5JGZ/79xJQRd47SHWB2WyUs2aQOXKaZgsvBnvFJasOZocfKxTJ+DYMaBtW+C557wudJZ6YnF7ut779AEuv9y0F7Vwju++a9ZVXkmEAolPIYQQUcOzzwJ16gD9+4dOfLLVo635+ckn2TI9y90NC90z656imwXn/UEhftNNwF9/AeedZ1zvTHCylC5t+srTulmggEkqql0b+PBDs1/GpTIxiqWnGOMqRGYj8SmEECIqWLoUePllsz5kCHD4cHD/z/hH63YPRny6a35+910cDh7Mmer2tED+8INZT28v8tRKLjGhaNo0IF8+YOJE/+EEtGbecYexGrO3PF+7nj2Ba64BXn3VW16JhfCFyGwkPoUQQkQ8jLW8/Xavu/3AAWD06OD28ccfJg6TAouWv2Dg9uw6FB8fhzlzzkm8n5ZDJuuwnNJXXwFvvgk8/LBJUjpyxGSrM44yPaQU98mYzldeMeu0ZNaqlfK+zj3XWFAZ+8ks/u++M4KcRe3vvTd98xQiUHIEvKUQQggRJiiWmDRTrBhw//3A88+b0kCsR+l2MQficqcYpCs9WJh4xNjLr76qjM2bs2PzZuDvv43ITA66sdMbQ3nppUYcMkufz1ehgrl/zRpvMtSjjwbuMue+WI7pqqtMOAFfV/4vhbIQoUDiUwghRESzbh0wYIBZf+stkznOJe+nuznQfulWfCbXzz01GFf52GMe7N6dD1OmJH3srLOAihWNMLSDrTutyzw9FCpkSiWxYDxd77QA0/JLdz6FL5OSBg4Mfr9MhKLVkzVEleEuQonEpxBCiIiFbnbGKjJTm1ncXbsaSyIF2ODBRoQGKz6Djfe0sEj8F1+cwqefbkCLFuehUqUcjsgsXz7zYyXpeqf4pOud1s5bbzVhBHzuceNMV6K0QNe7zagXIlQo5lMIIUTEwhJA8+aZLO3hw70u7F69zDqTen7/PfX9HD3q7VCUVvFJ2rTx4Oab1+H22z1o1QqoWjU0STrupCOGHHz7rem9zjjTYDsnCRFuJD6FEEJEJCwd1LevWWdGdrly3sdYUoi1K91tIVOCsZqsZ0n3OK2F0QZDBZjNzlqjtoYnxXj9+uGemRDBI/EphBAi4mAWOUv/MKbxkkuAu+8+c5sHHzTLjz4yMZAp8euvXqtnNBZRp5WTJZIs993nTTYSItqQ+BRCCBFxsI86k4no0h4xwn9GO13R1aubmpWjRmVuslEkYHvMMzmIJZ2EiFYkPoUQQkQU27cDvXubdWa5M67SH7RgWusnXe8ptdxMb7JRJEDrL+ty/vijSRQSIlqR+BRCCBFRMJlo/34Tz/jIIylvyzqV7OizcaPppe6PHTtMfUyK1QYNELUwo71dOyB//nDPRIj0IfEphBAiYvjySzMotNixJ7USQhRibBNJ3n47ZasnXfSsmSmECC8Sn0IIISKCvXtN9yLy5JNAnTqB/R//hzGhrIG5enXKyUZCiPAj8SmEECIiYItIusjPPx945pnA/4+F3tntJ7myS7EQ7ylELCHxKYQQIuxMnWpKJjEuc+RIU1ooGB56yCxHjzYWVAuTkBYtiv5MdyFiCYlPIYSIMn77zbRXtO7kaOf4ceCee8w6s9ebNAl+H6yBSTc9OxkxVtTC/u+HDpnY0Bo1Mm7OQoi0I/EphBBRJtRuuAEYM8b05J4yBVEPLZ7sZlSmDPDCC2nbBy2m1vo5ZIjpZuR2uTPLPXv2DJqwECJdSHwKIUQU8cor3l7mtPJdcw0wYQKilhMngJde8iYZsYd7WrnpJqBECWDzZuCbb8x9ivcUIvKQ+BRCiCjhjz+8Qo2xjZ07A/HxQJcuwAcfICrhcVAsli7tLZmUVtgNybbhfOsts1SmuxCRh8SnEEJESa9z9vOm2/3KK01x9U8/Nf3PExKAO+8EXn8dUQWFsxXTTzwB5M2b/n3ee6+pDTp7NjB3LrBqlblf4lOIyEHiUwghooDPPjN1LJkF/u67JsaRMYzDhxvhRh5/HHjqKSNUowHGrW7aBJQqZUR0RlC2LHD99WadgpzC/JxzzP1CiMhA4lMIISKcffu8vc5Z//K887yPUYQOHAi8/LK5zSWLrlN0RTJMCHrxRa9ozpcv4/ZtE4/WrjVLWT2FiCwkPoUQIsKhNXPnTlN8nULNH0zWGTbMiFEuWYqJbu1ItuRu2GAShOgqz0goNhs2THpbCBE5SHwKIUQEw4SZ994z6xSVKRVfZ61MxoEy5nHsWKBTJ5MRH2mw8LstqfTYY6YGZ0biLrtEJD6FiCwkPoUQIoJd0xSUjOHs3h247LLAyg1NmmQyv7/7DmjTBjh4EBHF+PGmXFSxYiaJKjNgLVQWlWfrTbcVVAgRfnKEewJCCCH88/bbwIoVRqS99lrg/9eunWlXefXVwKxZpowRM8mZoJQtm1n6Wy9UCOjXD2jfPjRWT/ZyL1gwc54nVy5g8WJjBQ22VacQInOR+BRCiAiEtS+ffdasv/oqULJkcP9/ySXAzJlA27bAjh2Bu987dDA1Mh94AJnCl1+aRKAiRYBevZCp0PorhIg8JD6FECICYczikSNAs2ZAjx5p20e9eqZt5d9/G4sjB7Pgk1tnvOiIEaa/+saNpm5oRrak5HP8739mndn7tLQKIbIeEp9CCBFhfPttnBO3ycQh1vGkSzw91r9q1QK3llaubOqGDh5sRCtrcWZUGaSJE4HVq4HChY3AFUJkTZRwJIQQEcTRo9nx8MPZE2Mia9YM3XMzPrJPH2DcOBMzSbHYooUp85SRVk9adel2F0JkTSQ+hRAik9m9Gzh2LLBtx4+vhi1b4lCxojfmM9SwZ/z06SbRacECoEkTYP369O3zm2+A334zCUbuMkhCiKyH3O5CCJGJpZLYNnLUKHP77LOBSpWAc881w73O9o8UZ998Y9oXDRmSsV1/guXii4F580zCEuM/mzY1JZyaNw9+XywVZa2eTGSiqBVCZF0kPoUQIhOgpZMWRFr8LNu2mTF37pnb58zJ+MwcSEiIw7XXJqBdu/A7phgryiL311xjli1bAh9/DHTpEtx+vv8eWLbMFJN/5JHMmq0QIlqQ+BRCiAyGRd1ZsoiljlhjcsIEYzmkBXHTJjPsOpdM7GErzPj4OOTLF4833uBewi8+CUs8/fwzcMstwFdfmSL2zKBnUhJjRAOxeg4YYNZZWql48UyfshAiwpH4FEKIDGTXLtNVaMkSE99Iy6ftTETh5a/bDksd/fsv8McfJ7Fhwwycc87liCRYoP7zz00y0qBBQN++wPz5Jhmpdm0zkhOVU6aYYu8MIWAClRBCSHwKkUViD+++OztOnarsxPCJzGHLFuDKK4F164ASJYzwql8/9f9jLc3y5RkT6sHhwxHYjP30HGmRZXwqE4Yoqt0hBWXKAHXqeMUoB9321urJNprBFsoXoeXUqVOIpwk+yuEx5MiRA8eOHXOOSWQcOXPmRPYMKP4r8SlEFmD2bCa9ZEO2bBdgyJBTTnyhOBO6lV9+2Vgu2VOdgipQ2Ku8VSvTmahcOeDHH4Hzz0fMQdd5o0bA5MkmQYrtPxk6sHWrGT/84N2W7zNqGdYafeyxcM5apITH48H27duxf/9+xMrxlC5dGlu2bEFcILEhIiiKFCnivL7peW0lPoXIArC/N0lIyIaVKxOc+EORFIpFJtJQLNFNTBF63XUmO5uvV0rXWSbTtG5tXO5VqwLTphlLZqxC8clhOXQIWLXKCFEKUjt4P+FreNZZYZuuSAUrPEuVKoV8+fJFvWBLSEjA4cOHUaBAAWRLT4cGcYao/++//7DzdOHfs1m+I5Tic+jQoXjttdecN2ydOnXwzjvvoJH7SuQD39RPP/00vvrqK+zduxcVKlTA4MGD0Vb+PyFCKj7JsmVxEp8+LFoEdOpkhCetnhRNc+aw5qYZF15oBBSTbXz7hf/yC3D11SbJiNvR1V6qFLIUjG1lLVAOd1F5JlIxFEHvt8iFbmkrPIvHSDYYxeeJEyeQJ08eic8MJi8DwMHGEzud90xaXfBBn5Xx48fjkUceQf/+/bF06VJHfLZu3TpRCfvCN0CrVq3w119/4YsvvsD69esxYsQIlGVROyFESEr+sEyOZenS6LZqZDR0l/N3MPuos5QQa1lSUC5dCtx+uxGbtGxy/ZxzTLINXeu2hBBjPCk82ZpyxoysJzyTg9/5jA/l68I2oSIysTGetHgKEQj2vZKe+OCgxeegQYNw5513okePHqhevTqGDx/uTGTkyJF+t+f9tHZOmjQJzZo1Q8WKFXHppZc6olUIkfksXAgcPx574vPECSP23McWLIxRpHhkByImBjHmk20lCa2YH34I/PMPMHCgcaPv2WPWKaquugro2NGIe1o+afFkz3IhopFod7WL6HqvBPV7lFbMJUuWoC9/+p+GJu2WLVtiPutu+OGbb75BkyZNcP/99+Prr79GyZIlcfPNN+OJJ55I1lx7/PhxZ1gO0qxwWmXHQiZeLGLPi85P5DF9On9jZkfDhqewaFF2rF4NHD4c79SfjGa6d8+OceOyoUYND0aOPOmIxWBgbkXr1jnw999xqFzZg6+/PulYOX3fwoUKmcLoDz4IfPddHN59NxtmzsyGqVPN4zffnIARI0451r30vv31OYp8Yu0c8TgYy0dXNUcswOOxy1g5pkiCrylfW753fHVcoJ+LoMTn7t27nfiQs3wix3l7HWuL+GHjxo34+eef0bVrV0yePBl//vkn7rvvPmeCdN374+WXX8YAW5/DxYwZM+QaiHCmMdNCRBQTJzLgriQuvHAV1q27AIcO5cJ7781F5coHEK2sW1cU48Zd4qyvXs0Y1uy4/vrfnZEzp/niSYnjx7NhwIAmWLOmBIoWPYbHH/8Fixf/l+r/0Sr68MPAtdcWxLRpFVCkyHF06vSHk2CUkehzFPnEyjliSSJmLjNBhwamWOKQzXgTGQrfJ0ePHsXs2bNxknX8XDAhKRDiPPYnQgBs3brVidWcN2+eY8209OnTB7NmzcKCBQvO+J+qVas6tbY2bdqUqJDpumfC0jb2mQvQ8lmuXDln+1gJiI41+GOCF2PG97IOmIgM+F1SsmQOHD0ah0WLjqJnz0NYsaIU3n33JHr2DPijH1HwitW8eXYsXJgNN9xAaw3w5ZcmgqhOHQ8++OCkU28yOVj2r3Pn7Pjmm2woVMiD6dNT3j6U6HMU+cTaOeL3M0sSMSSOCTqxAGUNhWfBggUVTpBJ7xnm8VCX+b5nqNdKlCiBAwcOoBDdRhlh+eQOKSB37NiR5H7e5i8nfzAV37co6QUXXOBkylM957IBVi5y587tDF+4n1j4sMcyOkeRF+959KgpeF67dg6cd94BR3wuX54jamt9jhtnjot9wt96KxtY7YPdd1jEfMUKWkFz4tlnTftH32OkcGWdShZH5yXmm2/i0KBB5L0Q+hxFPrFyjujNpEBjCF2sZIZbV7s9rlD+MImF90Rq8DXla+vvMxDo8Qd1VigU69evj+nTpyc5ybzttoS6YZIRXe3uuIvff//dEaX+hKcQIuNLLF16qalTed55pog0M7mjEQppikry5JP8cWvWb7yR7neTAMSQo379TNkf3ueGkT7vv28ysceONa+LECI6mTJlCi6++GKn6Dm9oldffTU2bNiQ+Pg///yDm266CcWKFUP+/PnRoEGDJB7ab7/9Fg0bNnSsdzSuXXvttYmPUVwxUdoNn+ejjz5y1mn54zasAMQkau7j008/xZ49e5znpJeYYYK1atXCZ599lmQ/CQkJePXVV1G5cmXH0Fa+fHm8+OKLzmMtWrRAL/5CdrFr1y5HL7m1V7QT9E8CllliqaSPP/4Ya9euxb333osjR4442e+kW7duSRKS+Diz3R966CFHdH7//fd46aWXnAQkIUToxCex4pMFwKMxvGvwYG8HId8+4QxFZ7b6mDFA0aKmt3q9esArr5j2okOHAs8/b7Z9911T11MIkQKsP5bcYJmHQLflr8bUtk3T9I44mmTx4sWOMKNFjgLSFpm//PLL8e+//zqJzytWrHBCBK0hjFqE27Le+LJly5z/T6leeXI8+eSTjr6hHmLZSbqkaaTj/letWoW77roLt956KxbSXXOavn37YuDAgejXrx/WrFmDsWPHJubS9OzZ07ntDj0cM2aMI2YpTGMGTxp45513POXLl/fkypXL06hRI8+vv/6a+Nill17q6d69e5Lt582b52ncuLEnd+7cnkqVKnlefPFFz8mTJwN+vgMHDjA4zbN79+60TFeEgBMnTngmTZrkLEVkwFORPz8dzR7PihXmHE2cOMlTpEiCc9/SpaGby9GjHs+cOR7PqVNp38f27R5PgQLmeMaMSXnbf//1eNq1M9ty1Kzp8cTFmfUBAzwRiz5HkU+snaOjR4961qxZ4yzPwH6A/I22bZNumy9f8tteemnSbUuUOHObDGDXrl2OVlixYoXnzTff9BQsWNCzZ88ev9s2adLE07Vr12T3xf1MnDgxyX2FCxf2jBo1ylnftGmTs83gwYNTnVe7du08jz76qLN+8OBBRwuNGDHC77Y8D0WLFvWMHz8+8b7atWt7nnvuOU80vGesXuMyJdJU+pcmYV+zsGXmzJln3EeX/K/uKtdCiEyHrnUaFIoVA2rWNIk2dL1feKEHM2bEOY8HW54oLTDhlMXb+cP/lluAjz82bu9gYRzn4cNAw4am01BKsCf7t9+a53roIdP6kdx7r3HJCyGinz/++APPPvus40pnNR5r1dy8eTNWrlyJCy+80HG5+2P58uVOzfL0Qle+bwwtvbuff/65Y3VlbgutmLZSDy2kx48fxxVXXOF3f3Tf01LKGuk33nij08yHFlRab2MJ9Z0QIsZd7s2bG7FH8UmM+DRu6TvuyNw50Nt2zTVGeBK6xJmb+Nprwe1n5Urggw/M+qBBgYlXCu3bbjPC96mnTOchuuCV/CpEgPDXXnL41ulOpsuhg+8H9q+/kBG0b9/eadfNUMAyZco44rNmzZqO4LNtIJMjtccZz+lbDMhfDUvGkrphJZ+33nrLaSHOeE8+/vDDDyeWsUrtea3rvW7duk7M6qhRoxx3O48zloiN1DYhRKrxnpZ69cwFleIzM+G19vrr6Q0xvb8pAMnrrxsBGSi8/rPIO40aN9wAXHxxcPNgS8zRo83zprENsRBZEwqr5IZvWaaUtvUVXP62CRIm9rBd9zPPPONYEVlFZ9++fYmP16hRw7FuMufEH7Vr104xgYcNcdzlIGllDaSG5dy5c9GhQwfccsstTifHSpUqOfkulipVqjgCNKXnpmilRZWimvGft7O3b4wh8SlEDMIEG/Yn9yc+afkkK1akvyNPSs9PF/vkyeZ7hz3QmczJ1pSEyUKffhrYvn74AfjpJ1Pg3f6/ECJrU7RoUSfD/f3333cq6rCZDZOPLNddd51TArJjx46OIGTDmy+//DKxGyOb3DALnUu6wummf4WukdPQ2jhkyBAnGYkJTffcc09AZYQoLlkHlvXQud+77747SXlKutWfeOIJJ/lp9OjRTnY+wxI/ZC9fH+snk5JofXVn4ccKEp9CxCDLl5tYS/Ya9y2gft55pmUkkynXrs3456aFkqFUEyYYwThxonH9kz59TAwmoUv8xx9T3hfFsc1q5/9VqpTx8xVCRB/MbB83bpzT8puu9t69ezsubwtLE7EUU6lSpZyMdloTKeZszfHLLrsMEyZMcGIp6eKm2HRnpL/xxhtOEfXmzZs7LcEfe+yxgDos0hJbr149J/Odz2EFsJt+/frh0UcfdeJVabHt3LkzdvqELbBcE7tPcRkrxf/dKOZTiBiP9/R1NTP8iiWI6A6n67127Yx7XrrIKRJZCo/Py4LwrVt7H2e8JV3uNATwMZY74jx8YvYTGTGCrTRNkfynn864eQohop+WLVs6pYrc2H7u7LTDOMkvvvgi2f/v1KmTM/zBGNKpU6cmuW//flOqjrAjlL8GkUxw8q0P6k84P/30085IDiZQsWzTHZkdmB8mZPkUIgvFe1rq10emxH0+8wwwZIhZpwD15y2i+OVjTPZkNn7btoynOnM7XueZ4U7+9z9jxRVCiFgmPj7e6QBJC+pFF13kWFFjEYlPIWIMZrUnF+9psdezjBSfjMd86SVvEXfGfCYHW1uyIDxLPe3aZayj27cn3YYxonv2sB2vceMLIUSsM3fuXKcD5KJFizB8+PBwTyfTkNtdiBiDZYloNWSGeXJ1PK3lk0lHTA7Kkc4rAa2dtrHZq6+aepqpwbhTJhM1bQps3Ai0aWMstryfHfLeftts98Yb6Z+fEEJEA5dddplfd36sIcunEDHqcm/WLHnRVqUKUKCAqcPJmMr0QBf6Aw+YdRZwf/zxwP+XHeUYVsUanEySopueiVDs285STVdeCVx1VfrmJ4QQIrKQ+BQii8V72rhLaxVNj+udsfw2Hv7hh4EBA4LfR+XKxgJKMfzzzyYWlPvlHGn1VFF4IYSILSQ+hYghWOZo9uzUxafb9c42m2nh33+Brl3Nc1KAMos9rUKRMagsycQyenPnmvsY58m2oEIIIWILiU8hYojVq02SDsvRJVe+KKMy3seONa7xRo2A995Lv4WSbTDZiYgw7jMtVlQhhBCRj8L4hYjReM/UmnFY8blsmcmQD7b1JPu0E3Z+y6i2lV26AOeea8Qn40GFEELEHrJ8CpHF4j0tVaualspsV7x+fXDPs2oV8NtvRuCy33pG0rixKa8khBAiNpH4FCJGYHWOQOM9Ca2VdeumLe7T9mVngfhixYKdqRBCZExZooeZ6SiiDolPIWIElkxie2C2AW7YMLD/SUvcJxOMGO9JmHAkhBBCBIPEpxARxuHDwDXXAL17G2tmsC73Jk1MB6HMEp9z5gCbN5si9ldfHfj/CSGEEETiU4gI44UXgG+/BQYPBp5/PnPiPX3bbDLpiBbNYFzu118P5M0b+HMJIURmsW/fPnTr1g1FixZFgQIFcP311+OPP/5IfPzvv/9G+/btncfz58+PGjVqYPLkyYn/27VrV5QsWRJ58+ZFlSpVMGrUqDAeTeyjbHchIggm/rBepqV/f6B6dSP0UoIW0rSIz/PPNwKS1lZep6tVS3l7dh+aMMGsy+UuRGxz5EjKMeMM8QlkWzaMcP9Q9bctkx/Tw2233eaIzW+++cYRn48//jiuvvpqrFmzBjlz5sT999+PEydOYPbs2Y745P3cjvTr18+5/cMPP6BEiRL4888/cZTt30SmIfEpRIRAAck2lfHxJpGH2ei0fnbrBlSq5LVS+uPPP4Ft24BcuUy2eKCw/SaTjubPN6731MQnOxHt2wecfTaD/QN/HiFE9HFam/mF16jvv/feZotcVs7wB38Qz5zpvV2xIrB7d9Jt0tPO3IrOuXPnomnTpkhISMD777+PmjVrYtKkSbjhhhuwefNmXHfddahVq5bzP5V4UT0NH7vwwgvR4HRx5IqcoMhU5HYXIkL46itg2jQjIN96C3jtNdPXnD/AGQNKcZkc9sJO4RmsK9yK2kDiPq3L/eabM662pxBCpIe1a9ciR44caOz65V2sWDFUq1bNeYw8+OCDeOGFF9CsWTP0798fv7FW3GnuvfdejBs3DnXr1kWfPn0wb968sBxHVkLiU4gIgG4oJhiRPn1Mv3NaJceNMzUv2cqyY0cjRP1hXe5psUYG2mbzwAETi0rkchci9mE4TnLjyy+TbstKG8ltS4+Jm7/+OnObzKZnz57YuHEjbr31VqxcudKxcr7zzjvOY23atHFiQnv37o2tW7fiiiuuwGOPPZb5k8rCSHwKEQG89BKwZQtQoQLQt6/3/sKFgW++MbU0Fy40PdR93VNpjff0Jz5TSjrilw1jPimGbX1QIUTswjjM5IY73jO1bX29Mf62SQ8XXHABTp48iQULFiTet3fvXqxfvx7VGTR/mnLlyuGee+7BV199hUcffRQjRoxIfIzJRt27d8eYMWMwePBgx20vMg+JTyHCDBN9Xn/drL/5punL7oZW0C++MJbQzz4zQtXNpk3AP/+YbkMssxQsvDbzi+TgQWDDhtRd7rR6prePuxBCZBTMTu/QoQPuvPNOzJkzBytWrMBdd92FsmXLOvcTFqOfOnUqNm3ahKVLl2LGjBmOaCXPPvssvv76ayfRaPXq1fjuu+8SHxOZg8SnEGGEVsuHHgJOnABatzaudX9cfjkwZIhZf+YZEx9qsVZPFpb3Fa6BQFFbu3bKcZ90+8+Y4Y33FEKISIKlkerXr+9kuDOuk1BEMtOdnDp1ysl4p6i86qqrULVqVbz77rvOY7ly5ULfvn1Ru3ZtXHLJJciePbsTAyoyD2W7CxFG6FJnPBSvj2+/nbJF8e67gdWrAYYp3XqryYCn+zs9Lne3651ufbreu3Q583FehymUeU0/99y0P48QQmQUM10p9KzfOXr0aGed2e4HDx5EoUKFEh+38Z3+eOaZZ5whQocsn0KECSYP2bbEjG1naaXUYA3QVq1MSRNmwG/fnnHiMyXL55gxZqlEIyGEEOlF4lOIMDFwoMn6POcc4OmnA3eRjx9vhCoTlChEuQ+WPWraNO1zseWWaPn0TWhaswZYvtw89403pv05hBBCCCLxKUQYYGLPK694rZnBZHsWLWpKHhUpAqxa5bVcstd6WqlRw9QX3b/fJDD5SzRq0wYoXjztzyGEEEIQiU8hwgDd7SxbdMUVqbfO9Actn2xzaQu9p7fbEIWnv6Qjll5yZ7kLIYQQ6UXiU4gQ8913ZtCNzRj4tJYtatkS+Ogj4KKLWEA5/fPyF/fJRh9//22squ3bp/85hBBCCGW7CxFCjh0zpZUIOxqlt5TcLbeYkRH4a7NprZ6dOqWtjJMQQgjhi8SnECGE/do3bgTKlAH69UNE4e50xKSj+Hjg88/NfXK5CyGEyCgkPoUIEcxKt92J3ngjfQlCmUHNmqbe6N69xtX+229mvXRpoEWLcM9OCCFErKCYTyFCADsY3XabcbuzW1Hnzog4cucGatXyut6ty/2mm7yJTUIIIUR6kfgUIpOhC/uuu0wxeFo72dEtUnuj27hPNg5h9yUil7sQIhapWLEiBg8eHO5pZEkkPoXIZOhq//hjYz1kDOX55yNisXGfI0YYK221al5BKoQQQmQEEp9CZCLsRmRbBrOs0lVXIaKx4pM1SAkz6SPVSiuEEFmVU6dOOT3soxWJTyEyCdbI7N7dW1bp3nsR8TDmk/VHLTffHM7ZCCGEf95//32UKVPmDAHWoUMH3HHHHdi0aRM6duyIs846CwUKFEDDhg3x008/pfn5Bg0ahFq1aiF//vwoV64c7rvvPhw+fDjJNnPnzsVll12GfPnyoWjRomjdujX27dvnPMZ5vvrqq6hcuTJy586N8uXL48UXX3QemzlzJuLi4rCfLeZOs3z5cue+v5ipCtZ0/ghFihTBN998g+rVqzv72Lx5MxYtWoRWrVqhRIkSKFy4MC699FIsZckSF9zv3Xff7bwWefLkQc2aNfHdd9/hyJEjKFSoEL744osk20+aNMk5zkOHDiGziCrxefRouGcgRGCwnFKHDsaCeM01psRSNJAnj2m1SZo0ASpVCveMhBBhCVQ/ciT0g88bIDfccAP27NmDGTNmJN63d+9eTJkyBTfffLMjDNu0aYPp06dj2bJluOqqq9C+fXtHsKWFbNmy4e2338bq1avx8ccf4+eff0afPn2SiMUrrrjCEYbz58/HnDlznOejhZL07dsXAwcORL9+/bBmzRqMHTvWEYPB8N9//+GVV17BBx984MyjVKlSjkDs3r2783y//vorqlSpgrZt2yYKR4pevg4UxmPGjHGem/PInj27IzC7dOmCUaNGJXke3r7++utRMDNLsniigAMHDvAd6fn22z3hnopIhhMnTngmTZrkLLM6+/Z5POefz6uox1Ovnsdz+LAnqs7RE0+YuY8eHbKpidPocxT5xNo5Onr0qGfNmjXOMhFetIwUDO0I8mLZoUMHz+233554+7333vOUKVPGEx8f79m3b5/n1KlTSbavUaOG55133km8XaFCBc+bb76ZptdtwoQJnuLFiyfevummmzzNmjXzu+3Bgwc9uXPn9owYMcLv4zNmzHA0DudsWbZsmXPfpk2bnNujRo1ybi9fvjzFefGYCxYs6Pn222+d21OnTvVky5bNs379er/bL1iwwJM9e3bP1q1bnds7duzw5MiRwzNz5szg3jM+eo3LlIgqy+fChQo+E5ENC7OzV/u6dcA55wDffgvkz4+oYsAAYOVK4NZbwz0TIYRInq5du+LLL7/E8dNB6p9++qljyaOVkpbPxx9/HBdccIHjrqbrfe3atWm2fNJlT8tm2bJlHYvgrbfe6lheaY10Wz79weflHJN7PFBy5cqF2rVrJ7lvx44duPPOOx2LJ93udKPz2O1xcl7nnHMOqlat6nefjRo1Qo0aNRxrLqF1tEKFCrjkkkuQmURVkfkFCyQ+ReTCn+6M65w+HShQwPRvZyejaIP1PllwXgiRRWEvXZ94xpA9bxDQre3xePD99987MZ2//PIL3nzzTecxurdnz56N119/3YmzzJs3r+NKPsGiy0HCuMurr74a9957rxOnWaxYMcfNzdhS7o8xntx/cqT0GKFYJjwWSzwtGX72wzhQN3S5UwS/9dZbjmhkLGiTJk0SjzO15yY9e/bE0KFD8eSTTzou9x49epzxPFlafC5aFOd8wSv7VkQir74KfPghLyQmy71OnXDPSAgh0gC/ZKPAZcPkmU6dOjkWzz///BPVqlVDvXr1nDjHBQsWOMLs2muvdbalNdAm7wTLkiVLnH2+8cYbiULxc9t7+DS0SDK+dABdRz7QKkkRyMcp9HwpWbKks9y2bZuTqGQtloHAWM53333XifMkW7Zswe7du5PM659//sHvv/+erPXzlltuceJXGdPKmFC+bplNVLnd9+2Lw++/h3sWQpwJkwWffNKsv/UWcPo6IIQQIpNd77R8jhw50lm3nHfeeZg4caIj4lasWOEkIaW1NBEtp7REvvPOO9i4cSM++eQTDB8+PMk2TChi5jmz4H/77TesW7cOw4YNc4QgRfITTzzhCLzRo0djw4YNTnLQh7RWnN4/M+ife+45/PHHH87xUOgGAoUt50PXPgU3XwO3tZPZ73ShX3fddZg2bZpTBeCHH35wErMsFLwU8QxTuPLKKx03fWYTVeIT8GDVqnDPQYikLFjgjY984AGgV69wz0gIIbIGLVq0cNzg69evdwSmhe5xiqqmTZs67nmWPaJVNC3UqVPHKbXETHOWKaKl9eWXX06yDa2KP/74oyN0GUdJ1/fXX3+NHKdr1zEM4NFHH8Wzzz7rxKF27twZO3fudB7LmTMnPvvsM0ew0lLJ53nhhRcCmhsFLMs58dgYh/rggw86WfBuGBfLsISbbrrJycanCLZZ+BYbQnD77bcjFMQx6wgRzsGDB51A2k2bdqNixeLhno7wA38VTp482TH984MU7bC3+Zdf8r2XenWQAweAkyeBdu2Ar7+O3D7osXaOYhGdo8gn1s7RsWPHHGvYueee61joYgFaOKkbmHxj3eQiZWg97d27N7Zu3eokNqX1PWP12oEDB5zXPyZiPjOz5JQQZPt24KmnWOcsuP9jTczPPotc4SmEEEL4wmx9xpqy9icL0acmPDOKqBKfQmQWrNTBWE16OmxTB5ZMYh92xt2nNipUUCKcEEJEI3SjU3j5gxnkLOgeq7z66qtOiALjQhm3GiqiSnwOG5YNP/zA2InI75EtogMGnbAk0iOPAH/+ae5r1MgI0YsuCvfshBBCZDbXXHMNGjdu7PexWAitSAkmOXGEmqgSn2vXxjn9smfNkvgU6WfNGtNz/ccfze3SpYFXXmHZCVMuSQghROzDovGZ2kpSnEFUfcU2bmzKJFCACpFW9u0DHnqI9c+M8GSIC8sksYxXt24SnkIIIURmElWWz0aNTGL+woUAi/eHKC5WRKErnVno+/efOf7+G2ADjD17zLYdOwKvv86acOGetRBCCJE1iCrxWbkyULy4EQ7LltESGu4ZiXDDmsFDh7JMBLB3r1dk+pQwO4MaNYDBg4GWLUM1UyGEEEJEnfhkNnHTpsC33xrXu8Rn1mbzZqBHD+Dnn/0/ztq+7FRWpEjS0aIFe9max4UQQggRWqLu69eKz7lzTbKIyJpu9TFjTCchFoHPl8+USOKPEbfIZIcxlT8SQgghIouoE5/NmgElSwLFioV7JiIc7N4N3HOP6T5EKDjpcq9SJdwzE0IIIUQgZItG8bljB/D+++GeiQg1338P1KxphCdd5rR2zpkj4SmEECJ4KlasiMEM/g+AuLg4TJo0KdPnlFWIOsunyuBkPQ4fBh591PuDo3p1Y+2sVy/cMxNCCCFEsGSL5rg/ZjWL2IaJZXXreoUn43wXL5bwFEIIIaKVqBSfv/4KlC0LXHZZuGciguWrr4ArrjAZ5+xSdc01pof6zTcDt90G3HWXSSRiu8vbbweaNwc2bADKlTNZ7YMGmUQiIYQQmVsrOdSDzxso77//PsqUKYME1ttz0aFDB9xxxx3YtGkTOnbsiLPOOgsFChRAw4YN8dNPP2XYa7Ry5Uq0aNECefPmRfHixXHXXXfhMN10p5k5cyYaNWqE/Pnzo0iRImjWrBn+ZqFpACtWrMDll1/udFUqVKgQ6tevj8W0qmQhos7tTipUALZtM7GfzHYuVCjcMxKBMHkycMMNpjZnMLDr0NtvA4ULZ9bMhBBCWP77DyhQIPTPS+2WP39g295www144IEHMGPGDFxBiwZY63kvpkyZgu+++84Rgm3atMFLL72E3LlzY/To0Wjfvj3Wr1+P8uXLp2ueR44cQevWrdGkSRMsWrQIO3fuRM+ePdGrVy989NFHOHnypCN877zzTnz22Wc4ceIEFi5c6MSNkq5du+LCCy/EsGHDkD17dixfvjzme8jHhPg8+2zg3HOBTZuMFfTKK8M9I5EaS5YAN95ohGeXLvx1arpUpTTi442VtG3bcM9eCCFEJFG0aFFHXI4dOzZRfH7xxRcoUaKEY1Wk+KS1MdvpRJHnn38eEydOxDfffOOIxPTA5zx27JgjaGnZJEOGDHHE7SuvvOIIyQMHDuDqq6/Geafb511wwQWJ/79582Y8/vjjOP/8853bVbJg1mxUik9b75PikzGBEp+RDc9Tu3bGrdKqFTB6NJDFfuQJIUTUwNrJLg9ySJ83GGhBpHXx3Xffdaybn376Kbp06eIITopPCs7Jkydj27ZtjjXy6NGjjvBLL2vXrkWdOnUShSeh0GUIAC2rl1xyCW677TbHOtqqVSu0bNkSN954I86m5QwMK3vEsZR+8sknzmO04lqRmlWIyphPW3KJsNi8iFzY8rJNGxMiUbs2f5lKeAohRCRD7zB1VahHsE1BaGn0eDz4/vvvsWXLFvzyyy+OICX9+vVzSiPR7c776dquVauW4wIPBaNGjcL8+fPRtGlTjB8/HlWrVsWvdNUCeO6557B69Wq0a9cOP//8M6pXr+5YZbMSUS8+eS5T6+MtwsOxY8a9vn49cM45JuZT8blCCCEygjx58qBTp06OxZOxldWqVUO906VQFixYgO7du+Paa691RGfp0qXx119/Zcjz0oXOpCHGflrmzp3rWFw5BwvjOvv27Yt58+ahZs2ajrveUrVqVfTu3Rs//vijcwwUq1mJNInPoUOHOsVZeeIbN27sBNIGwrhx45yAWwbipoWTJ73rNWoYIUPXwMqVadqdyEQY29m9uykCz/NE4ckKBUIIIURGQUsnLZ8jR45MtHoSurFpTaTFk0Lx5ptvPiMzPj3PSf1Dcbtq1Son6YnJT7feequTXc9Me4pOWj6Z4U6B+ccffziila7/Xr16OdnwfIyilUlL7pjQrEDQ4pPmY8Yr9O/fH0uXLnXiHhjXwGyvlOAvjsceewzNWTsnjbRokQMzZ5r17NlNKR7WfSxYMM27FJnEE08An39uXOz0JtSqFe4ZCSGEiDVY7qhYsWJOrCUFpuXFF190kpLo9qZ7njrFWkXTS758+TB16lQnu54lnK6//non6YlJR/bxdevW4brrrnMsnCzDdP/99+Puu+92stv37NmDbt26OY8xFpSJUwMGDEBWIuiEo0GDBjkBvj169HBuDx8+PPFXx5NPPun3f06dOuX8UuCLy9iL/WmsDr9mTRwuv9zUhXztNeDNN9O0GxEgixYBLIt29dXBiUd+/l5/3ayPHGlqegohhBAZDV3dW7duPeN+llNiXU+b7U4oAN0E44ZnbKkbuvIZr+kPWj+Ti+HMlSuXEyKQ1QlKfDJQd8mSJY452cITy2wtmpeT43//+x9KlSrlFH6l+EyN48ePO8NykMU8wSLk8Rg92oMvvojDd9958MgjCXj88YSA64KJwMMbXnopG15+ORtOnYrDU0+xp7oHXbokOMNfibR41kVyisgn4MEH+SGNw//+dwqdOyc4JZNE+LHnyC5F5KFzFPnE2jnicVBY0SWdUW7pcGOFoj0ukbHwNeVry/cOLbluAv1cBCU+d+/e7Vgxqerd8DZNzP6YM2cOPvzwQyfuIlBefvllvyboK6/8EXXrlsYHH9TEqlUl8dJL2TF8+AlcccVmtG+/AYUKxcbFIJxs25Yfb75ZD7//Xsy5fd55+/H33wWxalV2PPOMGdWr78all/6Dpk23omBB72u+fn1R9OuXAx5PHK688i/UqrXCifUUkcW0adPCPQWRCjpHkU+snKMcOXI4yTgsTRSqTPBQcejQoYC2+/zzz51wQn+UK1cuReNaVuTEiRNO7Ors2bOdElZu/mOHggCI8/jaklOApu2yZcs6mVus7G/p06cPZs2a5WSX+Z742rVrOzW4GNNAWPuKbneWQAjG8sk3AGt1sY0VZzxxYhyeeCI7/v7b1GaoVs2D0aNP4sILAz0a4Yav6ccfx6F37+w4ciQOhQt7MGQILZce7NtHi2YcPvssG2bP9rowcub0oHVrD266KQGVK8ejVatsOHgwN9q0ScCXX55CjqitIhub8BcpvzBZdy6rddOIFnSOIp9YO0csls4yRTaJOBagrKH+YPtK21UoJbjtDtYD9APPcQW2VRRJ3jMMWaAu833PUK+x0D+L7LN1aHIEJQ+4Q5pYfU8Sb/OXky8bNmxwJshgX4s1gfPXFgOE/RVWZbFYDn9vAvth79zZ9AVnDCg17/r1cbjoopy44w7ghRdojQ3myLI2e/aYnursu04uvZSF4ONQvrx5e5QqBdxzjxlbtrBqAfDpp+xPy/AHDgpSs229egn4/PNsyJs3aqt4xTzuz5GITHSOIp9YOUf0ZlKgMYTOHR8ZzVidYY8rNQoXLuwMERh8Tfna+vsMBPqZCOqdxkDZ+vXrY/r06UlOMm+7LaEWto5auXKl43K345prrnFaX3Gdqjk95M0LPPSQWS9WzFjvPviArapMQpLLeCqSgZ4jJhNRePI988orAE9vcq1vecoefxxgFMWqVQDDf+2PwlKljmDSpFNh6QkshBAi7Sg2UoTyvRK0Y5RxEaxt1aBBAzRq1AiDBw92Cq3a7HeWD6BrnnGbNMeysKqbIkWKOEvf+9PTZpMwJ4mZ2Szxwz7iffoA770HvPGGsZAG2zkhEjh61HQGolE5o70hLABP4Th4sLnNFrO0ZgZTiYK1Vl96yViaFy+Oxx9/zELp0q0ydqJCCCEyDRqVbMZ4yZIlnduBuKojXRwxLpHu4Vix5kZKOANf1127djmvK98rIROfnTt3dp742Wefxfbt21G3bl1MmTIlMQmJfVNDebJpoWPx8n//NbU/We+evcMprDZsAFjP/oorTFmmSKk1SQstKzxwzqwQsW1b0qVdtxWpKDzZ0allSzMY1+qTYBYUK1YAt97qLc5/333GUhxsX10LTzfntG2bEr6EECKa4Pf1ueee6+RU+CtZFK0iiQkxefPmjXohHYmwjilLWaVH66UpJYTV+Tn8war9KfHRRx8hI+H7itbPCROAefOAyy5jUhNw3XXAwIHG8kk3ct26Jq7xf/8DSpZE2GAy4Q03AN98E9j2TNqhlZLHwEFRTeMxa2dSVFOMMszA9/NFgcu6/2vWmLF6tXd91y4kxnKyDme7dhl/nEIIIaIDWrAoJpi5zBjQWEgKYyb2JZdcEhNxuZEE836Ys5NeUR8T+ci0ClJ8zp3rvY9dj158EejZ07jgv/iCBfEB1nbt35/FZvmBSyoKaYlkQs3mzUmXjENmLCT7k6cHhklQGFN40nLJWMkyZYCzz066dK/zuVnFiiEFFJ8zZhiLKGM0bYIQ4zApROkG//NPr9jcuzf5udAizNdDiVlCCCGSSyCJVoFEIc3Qv1g4nlgkJsRn27bG9cssbV/OPdcI01mzgIcfNokyLOdF4VW7tldkbt9urIXJwTJfbGZQsWLa5sh98/kpfmnN/P571i0N7H/Z8pXjgQdMAXjGtFKMctDay2PwZ1DmD5NKlYDq1b2DApXxnSrML4QQQohwEBPik25njpSgMF282Ig0duz5/Xcz3LC6E62bjCOlNdHGkzIecuNGsw8KUD/VoVKFiTnvvGPWGZMaqPD0hcK1cWMznn6aBV1ZyN8I0U2bgKpVvUKzWrW0x3EKIYQQQmQGMSE+A4WubtYBZcwlBSBDW9xCk7Gg/sIYWKaUMZYUq5dcYgQohV2gjBgBPPOMWX/rLeCmmzLumCguKWTTKmaFEEIIIUJJzIhPus3pyqZ4vP32lLdl0f1k8qX8Qusn3fZM7mEsJS2gtDQGUi1q4kRTnJ3Q4vrgg4E/rxBCCCFErBEzBbAYB8nkIiYGZQastclknzp1TO1NdlZKrV09BSutnEw04txYD1MIIYQQIisTM+LTNliia9yWEspo6Jany71BA2D3buOKZxypPyhMWdyeXZaYWT5sWHQWuhdCCCGEyEhiRnyyvaYtIv/665n7PHS5U+zu22dKHDET3g2Tk666ynRdYozo2LEmUUgIIYQQIqsTM+KTsIA8YXY6Xd6ZBWtvTp1qhCUFZqtWwOzZ5jG65Jn8wyVLOX39telBL4QQQgghYkx80r3NbHbW1OzWzdueMjNgEfsffjBJSEeOGEsnk4vatDFtPVlfdMoU041ICCGEEELEoPgkgwebOpwsHM/s8syEZY6+/dYIzqNHgU6dgGXLTGwoLaPsUiSEEEIIIWJYfBYoAIwZA1x7LfDcc5n/fHnyGItnhw5eiygtnqkVvRdCCCGEyIrEZBrMRRd5+56HAnZGYgvPTz4BGjUKrP6nEEIIIURWJOYsn/748UfTzSgzyZnTFLeX8BRCCCGEyMLi8777gNatgTfeCPdMhBBCCCFEzItPFoQn7K3OZCAhhBBCCBE+Yl589uhhko/i44GuXYH//gv3jIQQQgghsi4xLz7Z0vL9903Zo7VrgSeeCPeMhBBCCCGyLjEvPkmJEsCoUWZ9yBBTHF4IIYQQQoSeLCE+CZOOHnzQrLMLktzvQgghhBChJybrfCbHwIHAmjXAY4+Z7kRCCCGEECK0ZCnxmTcvMG1auGchhBBCCJF1yTJud38sXmySkYQQQgghRGjIUpZPN1u3AlddBezZA+zaBTz1lMmMF0IIIYQQmUeWtXyy9NK993oL0D/6KJCQEO5ZCSGEEELENllWfNLK+fzzwJtvmttcMgv+5Mlwz0wIIYQQInbJsuLT8vDDwEcfAdmzm+UNNwDHjoV7VkIIIYQQsUmWF5+ke3fgq6+A3LmBSZOAl14K94yEEEIIIWITic/TXHMNMGUK0LYt8OST4Z6NEEIIIURskmWz3f1x2WVmWDweYN8+oFixcM5KCCGEECJ2kOUzBZ59FqhbF1i/PtwzEUIIIYSIDSQ+k+HwYeDzz4EtW4CLLwZ++incMxJCCCGEiH4kPpOhQAFgzhygfn1g927gyitNLGh8fLhnJoQQQggRvUh8pkDJksDs2cDdd5v4z1deAZo1AzZsCPfMhBBCCCGiE4nPVMiXDxg+HPjyS6BoUWDRIuCSS1QLVAghhBAiLUh8BkinTsCKFUDz5sDAgUCePOGekRBCCCFE9KFSS0FQrhwwcyaQzSXZGRfK4vQNG4ZzZkIIIYQQ0YEsn0HiFp5MROrcGWjaFHjtNSAhIZwzE0IIIYSIfCQ+00GOHEZ4njwJ9OkDXHUVsHVruGclhBBCCBG5SHymgyJFTC3QESOAvHmBadOAqlWB/v2BQ4fCPTshhBBCiMhD4jOdxMUBPXsCS5YAjRsDR44A//sfUKUKsH9/uGcnhBBCCBFZSHxmEBdcAMyfD0yYYITnFVcYy6gQQgghhPAi8ZnBVtDrrwdWrwaGDPHev3GjadE5Y0Y4ZyeEEEIIEX4kPjOBnDlNQXrL888Dc+cCLVoAbdoAv/0WztkJIYQQQoQPic8QwLacvXqZ7PgpU4C6dYFu3YC//w73zIQQQgghQovEZwgoVQp45x1g7VrgxhtNn/hPPjGZ8c88E+7ZCSGEEEKEDonPEFK5MjB+PLBwoUlIOnHCuOiFEEIIIbIKaq8ZBtiK86efzGB5JsusWcDy5cA995iWnUIIIYQQsYYsn2GkZUugYEGzTlf8Y48BDz8MVKsGjB4NnDoV7hkKIYQQQmQsEp8RAvvC33knUKaMSUTq3t0kJn37rRGmQgghhBCxgMRnhJA9O3DXXcAff5jseBaoX7UKuOYaoH59kyUvhBBCCBHtSHxGGPnyAX36mML0ffuanvHLlgFHj3q3kSVUCCGEENGKxGeEwiL1L70EbNkCvPUW0L699zHe364dMHmycdcLIYQQQkQLEp8RTvHiwIMPmgL1hGJz+HAjPClAWSv0jTeAvXvDPVMhhBBCiNSR+IwysmUDfv4Z6N3bxIVu2GCy5M85xyQsMWZUCCGEECJSkfiMQqpUAQYNAv75B3j/faBOHRMT+sEHwHPPhXt2QgghhBDJI/EZxeTPb6ydTEj65Rfg6quBp5/2Ps6STWvWhHOGQgghhBBJkfiMAeLigIsvNjVBq1f33t+/P1Czpuknv3JlOGcohBBCCGGQ+IxRmJhEVzzLMk2YANSuDVx3nWnfKYQQQggRLiQ+Yzgxafx4YMUK4IYbjHX0q6+ACy8EOnYEliwJ9wyFEEIIkRWR+IxxaPH8/HPjdu/SxYjQr782MaKWEyfUR14IIYQQoUHiM4tQowbw2WcmAemOO4wL3vLJJ0C5csADDxhRqsL1QgghhMgsJD6zGOefb0oyUWxavv8e2LYNGDIEuOQSUzNUQlQIIYQQmYHEp8C4ccB33wHduwOFCycVohUqAIcPh3uGQgghhIgVJD4FcuUyrTo/+gjYuTOpEGX7zgIFvNsyaYnbCCGEEEKkhdMdw4VIKkQ5mIjkFpq0iDJznpn0bdoA3boB7dsDuXOHc8ZCCCGEiHnL59ChQ1GxYkXkyZMHjRs3xsKFC5PddsSIEWjevDmKFi3qjJYtW6a4vYgsIcr4T8v27UD9+sDJk6agPYXo2WcD990HLFgQ59QUFUIIIYTIUPE5fvx4PPLII+jfvz+WLl2KOnXqoHXr1tiZjC925syZuOmmmzBjxgzMnz8f5cqVw5VXXol///032KcWYYY1Qvm7YfVq4IkngLJlgX37gGHDgObNc2DevDLhnqIQQgghYk18Dho0CHfeeSd69OiB6tWrY/jw4ciXLx9Gjhzpd/tPP/0U9913H+rWrYvzzz8fH3zwARISEjB9+vSMmL8IA2zhOXCg6R3/44/ALbcAhQp5ULv2rsRt3nkH6NQJGDUK2LEjrNMVQgghRLTGfJ44cQJLlixB3759E+/Lli2b40qnVTMQ/vvvP8THx6NYsWLJbnP8+HFnWA4ePOgs+X8cInK47DIzDh+Ox+zZ3vMzblx2zJuXDRMnmu0aNkxAu3YetG2bgDp1TLF7EVrsudFnKHLROYp8dI4iH52j8BHoax7n8QQeqbd161aULVsW8+bNQ5MmTRLv79OnD2bNmoUFCxakug9aQadOnYrVq1c7MaP+eO655zBgwIAz7h87dqxjZRWRz4YNhbFoUWlnbNhQJMlj5codxNtvz5AAFUIIIWIIGhhvvvlmHDhwAIUKFYqMbPeBAwdi3LhxThxocsKT0LLKuFK35ZOxopdffjmKFy8eotmKYH/tTJs2Da1atULOnDmTPLZ1azx++CEO33+fDdOnx6FOnQJo165t4uOdOmVH1aoetGzpQbNmHuTNG4YDyOLnSEQGOkeRj85R5KNzFD6spzo1ghKfJUqUQPbs2bHDJ4iPt0uXLp3i/77++uuO+Pzpp59Qmw3HUyB37tzO8IVvIr2RIht/54iF6u+5x4yjR4E9e+KQM6cJN9640dQVJYMGmbJNF18MtGplRt26prSTyDj0OYp8dI4iH52jyEfnKPQE+noH9bWeK1cu1K9fP0mykE0ecrvhfXn11Vfx/PPPY8qUKWjQoEEwTyliDFo13eWbSpZkUhpw220me56hvnx7PfmkKevkMoALIYQQIgYI2qZEdzhrd3788cdYu3Yt7r33Xhw5csTJfifdunVLkpD0yiuvoF+/fk42PGuDbt++3RmH1bNRAChYELj5ZpMVv2ULsGYN8Pbbpng9Oyu1aOHddvFiU/x++HDgn3/COWshhBBCpJWgYz47d+6MXbt24dlnn3VEJEso0aJ51llnOY9v3rzZyYC3DBs2zMmSv/7665Psh3VCmVgkhIUJSBdcYMYDD5gOS+6kpEmTgMmTzbj3XlN3lCKVo149ueeFEEKIaCBNCUe9evVyhj+YTOTmr7/+StvMRJaHHZbcsJ0nraHsrsTKXsuWmfG//wH87cN1dlwiBw4Yq6oEqRBCCBFZ6KtZRA1Vq5pY0LlzTatPuupZyD5/fuDIESNALXffzcL3QLNmwP33A++/b7oz/fdfOI9ACCGEECEttSRERlGqlElS4mCS0rp1Sa2cvE1BOm+eGRZuw2ILixYBOfTuF0IIIUKOvn5F1MPyTOya5IbJSX/8ASxfnnTs3GkedwvPDh2MKG3a1Axm2adQhlYIIYQQ6UDiU8QkFJc2eemmm7z3b90K7PK2oMexY8APP7AosUlosrGmFKAUoi1bAlddFfr5CyGEELGKxKfIUpQpY4ZbpM6aZeJI6Z7nktZRJjRxbNrkFZ9sRPvee0aYsvi9ahcLIYQQwSPxKbI0FJ/sj2B7JFBgUnBaIcqEJQvvZ4knWyyf/RLs/557rimeb7u/njoFnDxprKjqYS+EEEJ4kfgUwgWFYqVKZtxyS9LHmCnftq2xiO7bB/zyixmWN98EHn7YrC9Y4BWujB+1o2hR4NprgdtvB847L4QHJoQQQkQIEp9CBEjNmsD337OlLPD7717X/K+/Art3A4ULJ40lda/b2ywRtXatsZw+80zoj0EIIYQINxKfQgQJM+PPP9+M011lz+DSS4H9+43oZCkoK0BZAuqjj4Du3b3bfvONSXbivi6+WG56IYQQsY3EpxCZQPbsxhLqtoYS1hi98cak97FXPTPuWTS/ShVTu5TdnBhDKoQQQsQa6nAkRJh5+mlj9WSnJtYm5e0KFYyb/447km5Lt//06cDq1cCePSZBSgghhIgmJD6FCDNMTBo50tsytHlzE1dKgblhQ9Jte/Y0tUcpTEuUMAX2y5cHLrkE6NMn6basZ8r9CCGEEJGE3O5CRAgFCnhbhv79t7GCUlxaaOWsVQsoVswI1b17TXH8LVvMoKvfDbs+0TpKKypLQVWokA0nT56HXLniUK8ecNZZIT9EIYQQQuJTiEiEgpHDDRORfvzRe5uJTCyI/++/pgZpwYJJH2MGPsUpRSwHQHVa07Gu0to6Z453+/HjgYoVgRo1jAgWQgghMguJTyGiFFpFy5Uz46KLznyMdUmtMOX4449TmDFjB3bvPht16nhT6rkdW5Da+FHWOK1e3VhYCxUyGfidO3uL5zM5ivfbwY5RrGEqhBBCBILEpxAx3L3JWlAvu4xW0AQ0brwIbdu2RY4c3t6gLJjPONKVK407f+NGMywnTnjF56FDQPv2SZ+HXZzoxmenJxbh576EEEKI5JD4FCIL4q4lWras153PJCWKULrpDx4EDhwwbUTdQrRhQ3M/H7e1TFlon4NWVCs+ue2wYUaU1q1rRKoQQggh8SmESKRkSaBFCzP8UaoUsHCh9zZd9bSS2m5PtHxali3zthulW/7CC4GzzwaKFzejQwdvuMCRI8A//5j72YLUN3lKCCFE7CDxKYRIlwWVPeo5brnlzE5QV18NzJtnMvMpTt0wHMCKTwpaK3i5T8abUuhyMCufdVCvuso8Tqsry1DZx9yJVkIIISIfiU8hRKZA9/y33xrrKN34y5ebDHyWf+KgJdRy9KjpBkVhye3tNmvXmsfdltilS5PeZsITE6Ts4GPsFCWEECIykfgUQmQqtGRWrWpGctBdz/hRloailZQilWWkOHbsMBn3lpMnTUY+Hzt8GNi61YyffjKPM87Uis81a4ChQ00JKRbjtxn6FLp2ycQsIYQQoUOXXSFExJAzp3Glc1Aw+qNVK2/nJ1pK160zItMOZt5bFiwA3n03+ef77DOgSxezPm0a8NRTxuXPAv203DZqZESrO0FLCCFE+pD4FEJELbRcNm5shj/YEeqJJ4woZRkpm8HPJTPzaf20sCbq4sVm3V3Mn0lYFKL9+p1ZT1UIIUTwSHwKIWIWlolyl4pyQxe/26JJiypjVClSlywBFi0CVqww5acmTzZWUcukScDYsaaEVLVqwPnnA5UrJ22HKoQQwj8Sn0KILOvid8N6pxykZ0+zZA1TClAKUXeCFONLJ0www53dzxalFKJDhgDnnuutd2qfi+uMU+VgeSku69f3lpaaOTMOM2acg3z54pxqAJxP/vyZ+CIIIUQYkPgUQohkYH1Sf279224zbU1Z8okxp+vXG1e+7Q7lFoy0mDLulJZWJkv5wg5TRYqY9fHjs+HDD+vjrbe8j7Pu6TnnGCH64Ycmu5/weSiOKVLTKlBZZYDJWiyV5Y6TZRIW416VjCWEyAx0aRFCiHS681keiln5FKEsK8U4UcvvvxuR54bu+QIFzDh+3Ht/o0YJWLx4N44dK4l//41zLKMUpxzsPJUvn3fb1183mf2ExflpdbXtVDlYG9XGtLIyAMtWWaHMJcdffwElSpjHLU8/DUyfbgQtY1ybNTPVBriumqpCiIxA4lMIIdIJY0dLlzbj0kuTPvb55yaZiVZUik2KuuQsij16eHDWWfPRtm1b5MyZ07GmsvMTB/fBBCsL92Fro9q6qIxVtXTv7l3v2tVbisoXWmQPHfIKS1pa7X4pQjlsWMEllwAzZnj/l+KYx6NqAEKIYJD4FEKITISi0+3WDgZaLm3xfF/eftsM1kf9+++kg1ZY68on/H+66RmPahOk7KCV1i0eGcd66pSpEDBnDjB3rhm0kvomVDH0gJZbtk31HTVrAu3be7el9ZZCNVeutL0WQojYQeJTCCGiGIpMDsZoJsfgwUgSR5oaTIBimSqOe+819zE2lNZQC+NNKXyJjXV107p1UvHJmFWGH1DA0srKQXHNZZMmwKuverft08fExzJRy3ew7mrnzoEfixAi8pD4FEKIGCcj3OJMdLLJTtaiy4x9lqbati3poFCtXdu7LS2pNu6VllIOdrGy+MaSsisV67D6o3nzpOKTsai0prIpgXuUKpX+YxZCZA4Sn0IIIdIEE6DY6pQjNUuqLTPFOFbGmHLYdSZMuaHlk2KV8ai+w92mldssXGgSvn75Jek+mEh13XXA8OHe+0aMMNZWdrFibCuXHLyPMa2WhARgyxYzN87ZzpfjwIFs2LbtbKclrIVhCRTADCuwg/G9tPIqHlaIM5H4FEIIkenQZU7Bx5Ea/fsHtk8KvqVLTckr92AIAC2r7ioDFK533eV/PxSerO363nvebVk9wD/Z0aBBefzvf957WrY0YQi+MCmM4Qfffee9jwlcbB9Lwe6uXiBEVkLiUwghRFRCiyq7THG4ocuepaTcCVJ09XfsCOzda5Kf7JLb0tLJJC23qKXl0lYosDGqplpBAooW3cUCV862/F82FLCNAzhs+SzGrbrnQAvtNdd4QwqYmMXOWExIo0WXsa+XXZaJL5gQEYLEpxBCiJiCFsV69ZLeR+E4ceKZ29JiSRHKuFQLXeV0sfsjPv4UJk9mdtX5iVZTVgZwQ9FJEcoELfd+GWbAygN//mmStWyMrA0ZYIKWFZ8Uqk88YUQp42cZx5pSMwFuT9HL5+Dgc3MOPD5WJbjgAu8cPvnE3M/tuWRIBAU3Xzd28qK1lnDuU6cCefN6B8MUmDzmDlMQIlgkPoUQQmRZaN2kBTIjsTVY3XVZCW+zVSuh5XXDBiNEOWipbdrUuy0TuV57LakgppWU4pXWVsaz2lqu/F8KVIYL+OPhh4E33/SKz169kp87ww+s+KQ1t127M7ehNZfW2uuvBwYM8N7PclzsxqXOWCI19BYRQgghQoxNdmrYMPltHn0U+O03MxgWwO5ZHKRKFe92tIi6hactY8X7aa10i2s+dsMNRkBSeHNJqyetnwwHYEcrtwW3fn1zP+NnOdjMgBZTWnt3MfrgNLQUM/yAsb1cMqaVc+C++RwtWgA332y25f7YoYuP2cftOgdFtn1dKLSZVMb7uW8+t50LBysw2G15DCzZdfhwNvzzTxUUKBDnHA+PM1TQ2rx5szl+37q4wovEpxBCCBFhUDBSoFkoPtli1cayuuNcKcAoeCj2GF7AWNjkoPWVXbcCgVUIFi9Oeh8FKZ+L1lp3OSt24eK8KA7ZUpbDDUWwFZ+0vqaUVHbbbcCoUV6hyljY5OA+P/3Ue7tfP/7lC1DduZ9zatzYdOdihYKU9hWIsGQVBDv4OnDJWri23e6XXxqLNF+7W24Bbr89admxjCQhwYRt8EeGbSrBygvvv89WvaYtLps9pPR+CBcSn0IIIUSEwwx5DmbW+0JxwbjOUECXur/yWowppVBkG1gKU1YcoGWSYpQWSXcMLgXhPfd4H7NLu+7u6MW4Uz6XfZwWUHcMqrt7GC2jrGiQK9cpLFu2HX/+WQY7dsRh9mw4g6EMVnxSRP/4o7H0WhHHYevWtmlj4mzJt98Ct96atMmCG9aateKTTRA4D1qI2diBg49RhN50U9LOY4HCyg1sa8vXlaENHJs2mW5mfE0oNu+802xLC/jo0WYQ/iDh/HicHFxPKXY4VEh8CiGEECLdMAmJIpjj8suT347ltoYNC2yftNQyNjYQGBfLclnx8QmYPHkx2rRpi7/+yukIz1mzksavLlvmP57V/bxWfFKsWeFJMWeP0Q4rPAkTxii6KWxHjgS+/tpYjzkeeQRYsSJprVpfGMrAuGCW+rIinP97443+t+cPD8YPW2hlpVV5/nwzaGXmXDgILcq0LBMKZMb1UjCHuh6txKcQQgghYg4KKgo9DiZSuaFgY2wprYmEFkmGOtjhrvNKt/3ateZ+3ySy5AQhLaccFJNjxgAffmisku5Y3SlTjCV3+XIT18pBiybp2xd46SWzzphWDlqXOS/G1HLJ4ZvgxTji557zWo0ZqkFXPMecOUljemkdpSAuWdIIaD6HXZYunfpx7txp4pFZuYHJZ8Eg8SmEEEKILAUz+pm8xTJbdN+nlJREy+f5prJW0FDY9e5tKg5QiFoL49Gjxg1P4eYLn8vtnmf8KIVpeurg3n+/tySXhW1wKVw5rx9+MMPCclo//+y10jLBjA0dKDZpveWSIQqEolziUwghhBAiAALpuJURUHS6E7R27ADq1DHxm6ytygQhDloeA7GupmceFpbyYqcuCkm6+une55JWXs7PHUfMpCqGL/juizG3PA7G6gaT3S/xKYQQQggRQipWBGbODPcsjNWXYQUcFsaBsqoCH7PYxCwKTcaVcsmYWFZXSAsSn0IIIYQQwoGC0p1ERWz8aUahBllCCCGEECJkSHwKIYQQQoiQIfEphBBCCCFChsSnEEIIIYQIGRKfQgghhBAiZEh8CiGEEEKIkCHxKYQQQgghQobEpxBCCCGECBkSn0IIIYQQImRIfAohhBBCiJAh8SmEEEIIIUKGxKcQQgghhAgZEp9CCCGEECJkSHwKIYQQQoiQIfEphBBCCCFChsSnEEIIIYQIGRKfQgghhBAiZEh8CiGEEEKIkCHxKYQQQgghQobEpxBCCCGECBkSn0IIIYQQIrLF59ChQ1GxYkXkyZMHjRs3xsKFC1PcfsKECTj//POd7WvVqoXJkyendb5CCCGEECIric/x48fjkUceQf/+/bF06VLUqVMHrVu3xs6dO/1uP2/ePNx000244447sGzZMnTs2NEZq1atyoj5CyGEEEKIWBafgwYNwp133okePXqgevXqGD58OPLly4eRI0f63f6tt97CVVddhccffxwXXHABnn/+edSrVw9DhgzJiPkLIYQQQogoIkcwG584cQJLlixB3759E+/Lli0bWrZsifnz5/v9H95PS6kbWkonTZqU7PMcP37cGZYDBw44y7179wYzXRFC4uPj8d9//2HPnj3ImTNnuKcj/KBzFPnoHEU+OkeRj85R+Dh06JCz9Hg8GSc+d+/ejVOnTuGss85Kcj9vr1u3zu//bN++3e/2vD85Xn75ZQwYMOCM+6tWrRrMdIUQQgghRBhEaOHChTNGfIYKWlbd1tL9+/ejQoUK2Lx5c4oHI8LHwYMHUa5cOWzZsgWFChUK93SEH3SOIh+do8hH5yjy0TkKH7R4UniWKVMmxe2CEp8lSpRA9uzZsWPHjiT383bp0qX9/g/vD2Z7kjt3bmf4QuGpN1Jkw/OjcxTZ6BxFPjpHkY/OUeSjcxQeAjESBpVwlCtXLtSvXx/Tp09PvC8hIcG53aRJE7//w/vd25Np06Ylu70QQgghhIhdgna70x3evXt3NGjQAI0aNcLgwYNx5MgRJ/uddOvWDWXLlnXiNslDDz2ESy+9FG+88QbatWuHcePGYfHixXj//fcz/miEEEIIIURsic/OnTtj165dePbZZ52kobp162LKlCmJSUWMy2QGvKVp06YYO3YsnnnmGTz11FOoUqWKk+les2bNgJ+TLnjWFfXniheRgc5R5KNzFPnoHEU+OkeRj85R5BPnSS0fXgghhBBCiAxCvd2FEEIIIUTIkPgUQgghhBAhQ+JTCCGEEEKEDIlPIYQQQggRMiJefA4dOhQVK1ZEnjx50LhxYyxcuDDcU8rSzJ49G+3bt3e6F8TFxTmVC9wwf42VEM4++2zkzZsXLVu2xB9//BG2+WY1WOKsYcOGKFiwIEqVKoWOHTti/fr1SbY5duwY7r//fhQvXhwFChTAddddd0YjCJF5DBs2DLVr104sgM2axz/88EPi4zo/kcfAgQOd693DDz+ceJ/OU3h57rnnnHPiHueff37i4zo/kU1Ei8/x48c7dUVZMmHp0qWoU6cOWrdujZ07d4Z7alkW1nTleeCPAn+8+uqrePvttzF8+HAsWLAA+fPnd84ZLwQi85k1a5Zzwf3111+dZg7x8fG48sornfNm6d27N7799ltMmDDB2X7r1q3o1KlTWOedlTjnnHMcMbNkyRKn5nGLFi3QoUMHrF692nlc5yeyWLRoEd577z3nB4MbnafwU6NGDWzbti1xzJkzJ/ExnZ8IxxPBNGrUyHP//fcn3j516pSnTJkynpdffjms8xIGvn0mTpyYeDshIcFTunRpz2uvvZZ43/79+z25c+f2fPbZZ2GaZdZm586dznmaNWtW4vnImTOnZ8KECYnbrF271tlm/vz5YZxp1qZo0aKeDz74QOcnwjh06JCnSpUqnmnTpnkuvfRSz0MPPeTcr/MUfvr37++pU6eO38d0fiKfiLV8njhxwrEM0G1rYfF63p4/f35Y5yb8s2nTJqfxgPucsccrwyV0zsLDgQMHnGWxYsWcJT9TtIa6zxFdVeXLl9c5CgOnTp1yur7RMk33u85PZEEvAjvzuc8H0XmKDBjSxRCwSpUqoWvXrk6TG6LzE4MdjkLF7t27nQuz7Zxk4e1169aFbV4ieSg8ib9zZh8ToSMhIcGJUWvWrFliRzGeh1y5cqFIkSJJttU5Ci0rV650xCbDURiPNnHiRFSvXh3Lly/X+YkQ+KOA4V50u/uiz1H4oVHjo48+QrVq1RyX+4ABA9C8eXOsWrVK5ycKiFjxKYRIv9WGF2J3HJSIDPiFSaFJy/QXX3yB7t27O3FpIjLYsmULHnroISdumsmuIvJo06ZN4jrjcSlGK1SogM8//9xJdhWRTcS63UuUKIHs2bOfkZ3G26VLlw7bvETy2POicxZ+evXqhe+++w4zZsxwElwsPA8Madm/f3+S7XWOQgutMpUrV0b9+vWdCgVM4nvrrbd0fiIEum2Z2FqvXj3kyJHDGfxxwGRKrtOCpvMUWdDKWbVqVfz555/6HEUB2SL54swL8/Tp05O4EXmb7ioReZx77rnOB9t9zg4ePOhkveuchQbmgVF40o37888/O+fEDT9TOXPmTHKOWIqJsVI6R+GD17bjx4/r/EQIV1xxhRMaQeu0HQ0aNHDiCu26zlNkcfjwYWzYsMEp86fPUeQT0W53llmiO4of9EaNGmHw4MFOYH6PHj3CPbUs/QHnL0t3khEvxkxoYTA3YwxfeOEFVKlSxRE+/fr1cwLCWW9ShMbVPnbsWHz99ddOrU8b38TEL7qiuLzjjjuczxbPGetMPvDAA84F+aKLLgr39LMEffv2dVyG/LwcOnTIOV8zZ87E1KlTdX4iBH52bJy0hWXjWDPS3q/zFF4ee+wxp+Y0Xe0so8SSjPSW3nTTTfocRQOeCOedd97xlC9f3pMrVy6n9NKvv/4a7illaWbMmOGUq/Ad3bt3Tyy31K9fP89ZZ53llFi64oorPOvXrw/3tLMM/s4Nx6hRoxK3OXr0qOe+++5zyvvky5fPc+2113q2bdsW1nlnJW6//XZPhQoVnGtayZIlnc/Ijz/+mPi4zk9k4i61RHSewkvnzp09Z599tvM5Klu2rHP7zz//THxc5yeyieOfcAtgIYQQQgiRNYjYmE8hhBBCCBF7SHwKIYQQQoiQIfEphBBCCCFChsSnEEIIIYQIGRKfQgghhBAiZEh8CiGEEEKIkCHxKYQQQgghQobEpxBCCCGECBkSn0IIEUXExcVh0qRJ4Z6GEEKkGYlPIYQIkNtuu80Rf77jqquuCvfUhBAiasgR7gkIIUQ0QaE5atSoJPflzp07bPMRQohoQ5ZPIYQIAgrN0qVLJxlFixZ1HqMVdNiwYWjTpg3y5s2LSpUq4Ysvvkjy/ytXrkSLFi2cx4sXL4677roLhw8fTrLNyJEjUaNGDee5zj77bPTq1SvJ47t378a1116LfPnyoUqVKvjmm29CcORCCJExSHwKIUQG0q9fP1x33XVYsWIFunbtii5dumDt2rXOY0eOHEHr1q0dsbpo0SJMmDABP/30UxJxSfF6//33O6KUQpXCsnLlykmeY8CAAbjxxhvx22+/oW3bts7z7N27N+THKoQQaSHO4/F40vSfQgiRBWM+x4wZgzx58iS5/6mnnnIGLZ/33HOPIyAtF110EerVq4d3330XI0aMwBNPPIEtW7Ygf/78zuOTJ09G+/btsXXrVpx11lkoW7YsevTogRdeeMHvHPgczzzzDJ5//vlEQVugQAH88MMPij0VQkQFivkUQogguPzyy5OIS1KsWLHE9SZNmiR5jLeXL1/urNMCWqdOnUThSZo1a4aEhASsX7/eEZYUoVdccUWKc6hdu3biOvdVqFAh7Ny5M93HJoQQoUDiUwghgoBiz9cNnlEwDjQQcubMmeQ2RSsFrBBCRAOK+RRCiAzk119/PeP2BRdc4KxzyVhQusotc+fORbZs2VCtWjUULFgQFStWxPTp00M+byGECBWyfAohRBAcP34c27dvT3Jfjhw5UKJECWedSUQNGjTAxRdfjE8//RQLFy7Ehx9+6DzGxKD+/fuje/fueO6557Br1y488MADuPXWW514T8L7GTdaqlQpJ2v+0KFDjkDldkIIEQtIfAohRBBMmTLFKX/khlbLdevWJWaijxs3Dvfdd5+z3WeffYbq1as7j7E00tSpU/HQQw+hYcOGzm1mxg8aNChxXxSmx44dw5tvvonHHnvMEbXXX399iI9SCCEyD2W7CyFEBsHYy4kTJ6Jjx47hnooQQkQsivkUQgghhBAhQ+JTCCGEEEKEDMV8CiFEBqEoJiGESB1ZPoUQQgghRMiQ+BRCCCGEECFD4lMIIYQQQoQMiU8hhBBCCBEyJD6FEEIIIUTIkPgUQgghhBAhQ+JTCCGEEEKEDIlPIYQQQgiBUPF/MpBiIK+9RLMAAAAASUVORK5CYII=", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import pandas as pd\n", - "pd.DataFrame(history.history).plot(\n", - " figsize=(8,5),xlim=[0,59],ylim=[0,1],grid=True, xlabel=\"Epoch\",\n", - " style=[\"r--\", \"b--\", \"r\", \"b\"]\n", - ")\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "L2qi9QymVrXy", - "metadata": { - "id": "L2qi9QymVrXy" - }, - "source": [ - "Q10. 4 values are displayed : \"accuracy\", \"loss\", \"val_accuracy\" and \"val_loss\". Can you tell precisely what each value represents ?\n", - "\n", - "**Answer**: \n", - "\n", - "- `accuracy`: Correct prediction rate on the training set.\n", - "- `loss`: Loss function value on the training set.\n", - "- `val_accuracy`: Correct prediction rate on the validation set.\n", - "- `val_loss`: Loss function value on the validation set." - ] - }, - { - "cell_type": "markdown", - "id": "04TFG3NsRH0N", - "metadata": { - "id": "04TFG3NsRH0N" - }, - "source": [ - "Q11. Comment the curves.\n", - "\n", - "Remark : if we kept increasing the number of epochs, we would end up with a training loss close to zero and a training accuracy close to 100%. More precisely, after about 150 epochs, we get the following values\n", - "- validation loss : about 1.4\n", - "- training loss : about 0.03\n", - "- validation accuracy : about 89%\n", - "- training accuracy : about 99%\n", - "\n", - "**Answer**: There is overfitting (not so grave). This is due to the large number of parameters in the neural network (aobut 260k) while the number of parameters of the dataset is smaller (about 50k)" - ] - }, - { - "cell_type": "markdown", - "id": "nBnufjfFXqiI", - "metadata": { - "id": "nBnufjfFXqiI" - }, - "source": [ - "Q12. a) Find the indices, for the first 200 rows of the validation set, where the model (that we trained for 60 epochs) gets wrong.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "MUnWm1MfyBBk", - "metadata": { - "id": "MUnWm1MfyBBk" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step \n" - ] - } - ], - "source": [ - "probas_val_60 = model.predict(X_val01[:200])\n", - "classif_val_60 = probas_val_60.argmax(axis=1)\n", - "wrong_classif_val_60 = (classif_val_60 != y_val[:200])" - ] - }, - { - "cell_type": "markdown", - "id": "vJ3wYKSDr2-L", - "metadata": { - "id": "vJ3wYKSDr2-L" - }, - "source": [ - "b) Now let us train the model for only 10 epochs and call this model `model_10`." - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "DBsp72CAqRef", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "DBsp72CAqRef", - "outputId": "ab6e22c3-19c2-4610-d028-02a4e940b209" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1/10\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7866 - loss: 0.5999 - val_accuracy: 0.8326 - val_loss: 0.4162\n", - "Epoch 2/10\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8624 - loss: 0.3776 - val_accuracy: 0.8512 - val_loss: 0.3772\n", - "Epoch 3/10\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8763 - loss: 0.3341 - val_accuracy: 0.8502 - val_loss: 0.3915\n", - "Epoch 4/10\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 1ms/step - accuracy: 0.8875 - loss: 0.3049 - val_accuracy: 0.8592 - val_loss: 0.3675\n", - "Epoch 5/10\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8936 - loss: 0.2835 - val_accuracy: 0.8720 - val_loss: 0.3465\n", - "Epoch 6/10\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9017 - loss: 0.2663 - val_accuracy: 0.8752 - val_loss: 0.3437\n", - "Epoch 7/10\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9065 - loss: 0.2499 - val_accuracy: 0.8752 - val_loss: 0.3545\n", - "Epoch 8/10\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9102 - loss: 0.2404 - val_accuracy: 0.8810 - val_loss: 0.3369\n", - "Epoch 9/10\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9145 - loss: 0.2271 - val_accuracy: 0.8740 - val_loss: 0.3714\n", - "Epoch 10/10\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9161 - loss: 0.2195 - val_accuracy: 0.8816 - val_loss: 0.3601\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model_10 = tf.keras.Sequential([\n", - " tf.keras.layers.Input(shape=[28,28]),\n", - " tf.keras.layers.Flatten(),\n", - " tf.keras.layers.Dense(300, activation=\"relu\", kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(100, activation=\"relu\", kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(10, activation=\"softmax\"),\n", - "])\n", - "\n", - "model_10.compile(loss=\"sparse_categorical_crossentropy\",\n", - " optimizer=\"adam\",\n", - " metrics=[\"accuracy\"])\n", - "\n", - "model_10.fit(X_train01, y_train, epochs=10, validation_data=(X_val01, y_val))" - ] - }, - { - "cell_type": "markdown", - "id": "jowzB0kI6a4t", - "metadata": { - "id": "jowzB0kI6a4t" - }, - "source": [ - "So the accuracy on the validation set is almost the same with 10 epochs as with 60 epochs (stagnant val accuracy, and close to the training accuracy) but the validation loss is much better (and rather close to the training loss). If we want to understand better the situation, let us look at some values for the predicted probabilities." - ] - }, - { - "cell_type": "markdown", - "id": "ESbfJeBnsOHl", - "metadata": { - "id": "ESbfJeBnsOHl" - }, - "source": [ - "c) Find the indices, for the first 200 rows of the validation set, where `model_10` (that we trained for 10 epochs) gets wrong." - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "7w49W7ecsb42", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "7w49W7ecsb42", - "outputId": "2cef9214-3a2c-4631-c8f2-6275baae3fbf" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 5ms/step \n" - ] - } - ], - "source": [ - "probas_val_10 = model_10.predict(X_val01[:200])\n", - "classif_val_10 = probas_val_10.argmax(axis=1)\n", - "wrong_classif_val_10 = (classif_val_10 != y_val[:200])\n", - "\n", - "indices = np.where(wrong_classif_val_10 * wrong_classif_val_60)[0]" - ] - }, - { - "cell_type": "markdown", - "id": "T3uLsznrwP-c", - "metadata": { - "id": "T3uLsznrwP-c" - }, - "source": [ - "d) Display the estimated probabilities of the two models for the right class and for the indices where both models gets wrong (among the first 200 rows of the validation set). (Round to 3 decimal places) \n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "Hf7QyWqMFnUs", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "Hf7QyWqMFnUs", - "outputId": "55185cf2-1517-49b2-f1a2-82cf1820dca8" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([0.001, 0.393, 0.343, 0. , 0. , 0.001, 0.023, 0.189, 0. ,\n", - " 0. , 0. , 0.001, 0.11 , 0.002, 0. , 0.005, 0.006, 0.021],\n", - " dtype=float32)" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "probas_val_60[indices, y_val[indices]].round(3)" - ] - }, - { - "cell_type": "markdown", - "id": "qrUnU77H7FAx", - "metadata": { - "id": "qrUnU77H7FAx" - }, - "source": [ - " We see that most of the time, in the overfitting situation (60 epochs), for an instance that the model does not classify correctly, the probability for the correct label tends to be lower : the model gets wrong for those instances and is \"overly confident while it is wrong\" (it indicates a high probability for a wrong label so the probability for the correct label gets lower making the loss increase).\n", - "\n", - "\n", - "\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "71vLRKp0TZeo", - "metadata": { - "id": "71vLRKp0TZeo" - }, - "source": [ - " An idea to prevent this overfitting is to use **Early stopping** :" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "vYe04DM5cu4r", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "vYe04DM5cu4r", - "outputId": "825bd44c-888d-4820-ca98-4fe2274b7d27" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7864 - loss: 0.5990 - val_accuracy: 0.8298 - val_loss: 0.4282\n", - "Epoch 2/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8627 - loss: 0.3785 - val_accuracy: 0.8450 - val_loss: 0.3963\n", - "Epoch 3/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8772 - loss: 0.3354 - val_accuracy: 0.8544 - val_loss: 0.3724\n", - "Epoch 4/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8889 - loss: 0.3041 - val_accuracy: 0.8632 - val_loss: 0.3656\n", - "Epoch 5/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8957 - loss: 0.2829 - val_accuracy: 0.8686 - val_loss: 0.3534\n", - "Epoch 6/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9019 - loss: 0.2651 - val_accuracy: 0.8746 - val_loss: 0.3442\n", - "Epoch 7/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9071 - loss: 0.2491 - val_accuracy: 0.8844 - val_loss: 0.3403\n", - "Epoch 8/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9088 - loss: 0.2387 - val_accuracy: 0.8840 - val_loss: 0.3357\n", - "Epoch 9/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9157 - loss: 0.2245 - val_accuracy: 0.8834 - val_loss: 0.3541\n", - "Epoch 10/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9198 - loss: 0.2157 - val_accuracy: 0.8714 - val_loss: 0.4132\n", - "Epoch 11/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9220 - loss: 0.2063 - val_accuracy: 0.8770 - val_loss: 0.4210\n", - "Epoch 12/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9256 - loss: 0.1986 - val_accuracy: 0.8768 - val_loss: 0.4228\n", - "Epoch 13/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9291 - loss: 0.1875 - val_accuracy: 0.8738 - val_loss: 0.4382\n" - ] - } - ], - "source": [ - "early_stopping_cb = tf.keras.callbacks.EarlyStopping(patience=5, restore_best_weights=True)\n", - "\n", - "model = tf.keras.Sequential([\n", - " tf.keras.layers.Input(shape=[28,28]),\n", - " tf.keras.layers.Flatten(),\n", - " tf.keras.layers.Dense(300,activation=\"relu\", kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(100,activation=\"relu\",kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(10,activation=\"softmax\"),\n", - "])\n", - "\n", - "model.compile(loss=\"sparse_categorical_crossentropy\",\n", - " optimizer=\"adam\",\n", - " metrics=[\"accuracy\"])\n", - "\n", - "history2 = model.fit(X_train01, y_train, epochs = 60, validation_data=(X_val01, y_val), callbacks=[early_stopping_cb])" - ] - }, - { - "cell_type": "markdown", - "id": "MwTfIPcAeH6R", - "metadata": { - "id": "MwTfIPcAeH6R" - }, - "source": [ - "Q13. a) Explain what the previous cell does (first and last line).\n", - "\n", - " Hint : https://www.tensorflow.org/api_docs/python/tf/keras/callbacks/EarlyStopping\n", - "\n", - "b) Can you name another way to prevent overfitting ? (mentioned in the lecture notes).\n", - "\n", - "**Answer**: \n", - "\n", - "a) *First Line*: This creates a callback to stop training early if the validation loss doesn't improve for 5 consecutive epochs (patience=5). With restore_best_weights=True, the model will roll back to the weights from the epoch with the best validation loss, preventing overfitting.\n", - "*Last Line*: This trains the model on X_train01 and y_train for up to 60 epochs. It uses the validation set (X_val01, y_val) to monitor performance. The training may stop early thanks to the early_stopping_cb, and training history is saved in history2.\n", - "\n", - "b) We can use Dropout. It randomly \"drops\" (i.e. sets to zero) a fraction of the neurons during training, which helps the model generalize better by preventing co-adaptations of neurons. Example:\n", - "\n", - "```{python}\n", - "tf.keras.layers.Dropout(rate=0.5)\n", - "```\n", - "This can be inserted between dense layers to regularize the model.\n" - ] - }, - { - "cell_type": "markdown", - "id": "Anus7RlTV_bL", - "metadata": { - "id": "Anus7RlTV_bL" - }, - "source": [ - "Remark : if you are not satisfied with the performance of your model, you should tune the hyperparameters. There are a lot of hyperparameters that you can tune : learning rate, optimizer, number of hidden layers, number of neurons, batch size etc.\n", - "If you want to fine tune the hyperparameters, you can use the Keras Tuner library : https://www.tensorflow.org/tutorials/keras/keras_tuner" - ] - }, - { - "cell_type": "markdown", - "id": "qZ-0xPXzcglX", - "metadata": { - "id": "qZ-0xPXzcglX" - }, - "source": [ - "Now let us see the performance of our model on the test set." - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "q6BXm1YJUmKK", - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "q6BXm1YJUmKK", - "outputId": "6c7f3f57-fd81-4727-8422-a4480be423af" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 547us/step - accuracy: 0.8669 - loss: 55.3559\n" - ] - }, - { - "data": { - "text/plain": [ - "[58.230831146240234, 0.864799976348877]" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.evaluate(X_test,y_test)" - ] - }, - { - "cell_type": "markdown", - "id": "MexBSb7NCYCP", - "metadata": { - "id": "MexBSb7NCYCP" - }, - "source": [ - "**Optional 1** Train a logistic regression model : this model has far fewer parameters : you should not see the same overfitting problem when increasing the number of epochs." - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "GUZldkyGyYwF", - "metadata": { - "id": "GUZldkyGyYwF" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 464us/step - accuracy: 0.7328 - loss: 0.7938 - val_accuracy: 0.8340 - val_loss: 0.4826\n", - "Epoch 2/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 430us/step - accuracy: 0.8391 - loss: 0.4794 - val_accuracy: 0.8422 - val_loss: 0.4516\n", - "Epoch 3/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 425us/step - accuracy: 0.8498 - loss: 0.4464 - val_accuracy: 0.8442 - val_loss: 0.4396\n", - "Epoch 4/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 425us/step - accuracy: 0.8539 - loss: 0.4302 - val_accuracy: 0.8468 - val_loss: 0.4333\n", - "Epoch 5/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 428us/step - accuracy: 0.8566 - loss: 0.4200 - val_accuracy: 0.8476 - val_loss: 0.4295\n", - "Epoch 6/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 427us/step - accuracy: 0.8587 - loss: 0.4128 - val_accuracy: 0.8486 - val_loss: 0.4271\n", - "Epoch 7/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 428us/step - accuracy: 0.8605 - loss: 0.4072 - val_accuracy: 0.8470 - val_loss: 0.4256\n", - "Epoch 8/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 461us/step - accuracy: 0.8622 - loss: 0.4028 - val_accuracy: 0.8486 - val_loss: 0.4246\n", - "Epoch 9/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 427us/step - accuracy: 0.8629 - loss: 0.3992 - val_accuracy: 0.8488 - val_loss: 0.4239\n", - "Epoch 10/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 427us/step - accuracy: 0.8634 - loss: 0.3960 - val_accuracy: 0.8482 - val_loss: 0.4236\n", - "Epoch 11/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 427us/step - accuracy: 0.8641 - loss: 0.3933 - val_accuracy: 0.8480 - val_loss: 0.4235\n", - "Epoch 12/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 428us/step - accuracy: 0.8648 - loss: 0.3910 - val_accuracy: 0.8476 - val_loss: 0.4235\n", - "Epoch 13/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 428us/step - accuracy: 0.8659 - loss: 0.3889 - val_accuracy: 0.8484 - val_loss: 0.4236\n", - "Epoch 14/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 423us/step - accuracy: 0.8665 - loss: 0.3870 - val_accuracy: 0.8490 - val_loss: 0.4238\n", - "Epoch 15/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 424us/step - accuracy: 0.8671 - loss: 0.3852 - val_accuracy: 0.8486 - val_loss: 0.4241\n", - "Epoch 16/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 423us/step - accuracy: 0.8677 - loss: 0.3837 - val_accuracy: 0.8486 - val_loss: 0.4244\n", - "Epoch 17/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 466us/step - accuracy: 0.8683 - loss: 0.3822 - val_accuracy: 0.8482 - val_loss: 0.4248\n", - "Epoch 18/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 439us/step - accuracy: 0.8689 - loss: 0.3809 - val_accuracy: 0.8486 - val_loss: 0.4252\n", - "Epoch 19/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 429us/step - accuracy: 0.8694 - loss: 0.3797 - val_accuracy: 0.8476 - val_loss: 0.4256\n", - "Epoch 20/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 424us/step - accuracy: 0.8698 - loss: 0.3785 - val_accuracy: 0.8472 - val_loss: 0.4260\n", - "Epoch 21/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 429us/step - accuracy: 0.8701 - loss: 0.3774 - val_accuracy: 0.8468 - val_loss: 0.4264\n", - "Epoch 22/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 426us/step - accuracy: 0.8704 - loss: 0.3764 - val_accuracy: 0.8468 - val_loss: 0.4269\n", - "Epoch 23/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 425us/step - accuracy: 0.8705 - loss: 0.3755 - val_accuracy: 0.8468 - val_loss: 0.4274\n", - "Epoch 24/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 426us/step - accuracy: 0.8705 - loss: 0.3746 - val_accuracy: 0.8470 - val_loss: 0.4278\n", - "Epoch 25/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 453us/step - accuracy: 0.8707 - loss: 0.3737 - val_accuracy: 0.8468 - val_loss: 0.4283\n", - "Epoch 26/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 448us/step - accuracy: 0.8708 - loss: 0.3729 - val_accuracy: 0.8470 - val_loss: 0.4288\n", - "Epoch 27/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 443us/step - accuracy: 0.8709 - loss: 0.3721 - val_accuracy: 0.8464 - val_loss: 0.4292\n", - "Epoch 28/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 443us/step - accuracy: 0.8709 - loss: 0.3714 - val_accuracy: 0.8464 - val_loss: 0.4297\n", - "Epoch 29/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 462us/step - accuracy: 0.8710 - loss: 0.3707 - val_accuracy: 0.8464 - val_loss: 0.4302\n", - "Epoch 30/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 453us/step - accuracy: 0.8711 - loss: 0.3700 - val_accuracy: 0.8468 - val_loss: 0.4307\n", - "Epoch 31/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 420us/step - accuracy: 0.8710 - loss: 0.3693 - val_accuracy: 0.8462 - val_loss: 0.4311\n", - "Epoch 32/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 418us/step - accuracy: 0.8714 - loss: 0.3687 - val_accuracy: 0.8458 - val_loss: 0.4316\n", - "Epoch 33/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 417us/step - accuracy: 0.8716 - loss: 0.3681 - val_accuracy: 0.8456 - val_loss: 0.4321\n", - "Epoch 34/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 420us/step - accuracy: 0.8721 - loss: 0.3675 - val_accuracy: 0.8452 - val_loss: 0.4326\n", - "Epoch 35/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 415us/step - accuracy: 0.8724 - loss: 0.3670 - val_accuracy: 0.8448 - val_loss: 0.4331\n", - "Epoch 36/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 420us/step - accuracy: 0.8726 - loss: 0.3665 - val_accuracy: 0.8450 - val_loss: 0.4335\n", - "Epoch 37/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 418us/step - 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accuracy: 0.8760 - loss: 0.3533 - val_accuracy: 0.8412 - val_loss: 0.4514\n", - "Epoch 78/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 421us/step - accuracy: 0.8761 - loss: 0.3531 - val_accuracy: 0.8412 - val_loss: 0.4518\n", - "Epoch 79/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 457us/step - accuracy: 0.8759 - loss: 0.3529 - val_accuracy: 0.8408 - val_loss: 0.4522\n", - "Epoch 80/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 420us/step - accuracy: 0.8761 - loss: 0.3527 - val_accuracy: 0.8406 - val_loss: 0.4526\n", - "Epoch 81/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 418us/step - accuracy: 0.8761 - loss: 0.3526 - val_accuracy: 0.8408 - val_loss: 0.4529\n", - "Epoch 82/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 418us/step - accuracy: 0.8763 - loss: 0.3524 - val_accuracy: 0.8404 - val_loss: 0.4533\n", - "Epoch 83/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 421us/step - accuracy: 0.8763 - loss: 0.3522 - val_accuracy: 0.8402 - val_loss: 0.4537\n", - "Epoch 84/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 421us/step - accuracy: 0.8763 - loss: 0.3520 - val_accuracy: 0.8400 - val_loss: 0.4541\n", - "Epoch 85/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 464us/step - accuracy: 0.8764 - loss: 0.3518 - val_accuracy: 0.8398 - val_loss: 0.4544\n", - "Epoch 86/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 421us/step - accuracy: 0.8765 - loss: 0.3516 - val_accuracy: 0.8398 - val_loss: 0.4548\n", - "Epoch 87/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 420us/step - accuracy: 0.8764 - loss: 0.3514 - val_accuracy: 0.8396 - val_loss: 0.4552\n", - "Epoch 88/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 450us/step - accuracy: 0.8764 - loss: 0.3513 - val_accuracy: 0.8394 - val_loss: 0.4555\n", - "Epoch 89/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 456us/step - accuracy: 0.8765 - loss: 0.3511 - val_accuracy: 0.8392 - val_loss: 0.4559\n", - "Epoch 90/90\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 419us/step - accuracy: 0.8765 - loss: 0.3509 - val_accuracy: 0.8390 - val_loss: 0.4563\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "reg_log = tf.keras.Sequential([\n", - " tf.keras.layers.Input(shape=[28,28]),\n", - " tf.keras.layers.Flatten(),\n", - " tf.keras.layers.Dense(10,activation=\"softmax\"),\n", - "])\n", - "reg_log.compile(loss=\"sparse_categorical_crossentropy\",\n", - " optimizer=\"adam\",\n", - " metrics=[\"accuracy\"])\n", - "reg_log.fit(X_train01, y_train, epochs=90, validation_data=(X_val01, y_val))" - ] - }, - { - "cell_type": "markdown", - "id": "GR2JJnwv3zUS", - "metadata": { - "id": "GR2JJnwv3zUS" - }, - "source": [ - "**Optional 2** : Train the model on the un-normalized dataset (use only 30 epochs as it takes time)." - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "zv-yV-xQyVd8", - "metadata": { - "id": "zv-yV-xQyVd8" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.6586 - loss: 7.7191 - val_accuracy: 0.7086 - val_loss: 0.7708\n", - "Epoch 2/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7257 - loss: 0.7339 - val_accuracy: 0.7668 - val_loss: 0.5891\n", - "Epoch 3/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7667 - loss: 0.6082 - val_accuracy: 0.7880 - val_loss: 0.5681\n", - "Epoch 4/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 1ms/step - accuracy: 0.8169 - loss: 0.5174 - val_accuracy: 0.7946 - val_loss: 0.5648\n", - "Epoch 5/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 1ms/step - accuracy: 0.8377 - loss: 0.4704 - val_accuracy: 0.8270 - val_loss: 0.5107\n", - "Epoch 6/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8448 - loss: 0.4490 - val_accuracy: 0.8330 - val_loss: 0.4713\n", - "Epoch 7/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8521 - loss: 0.4277 - val_accuracy: 0.8534 - val_loss: 0.4069\n", - "Epoch 8/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8628 - loss: 0.3925 - val_accuracy: 0.8542 - val_loss: 0.4263\n", - "Epoch 9/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8668 - loss: 0.3824 - val_accuracy: 0.8584 - val_loss: 0.4099\n", - "Epoch 10/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8705 - loss: 0.3706 - val_accuracy: 0.8496 - val_loss: 0.4153\n", - "Epoch 11/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8745 - loss: 0.3588 - val_accuracy: 0.8550 - val_loss: 0.4377\n", - "Epoch 12/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8766 - loss: 0.3548 - val_accuracy: 0.8652 - val_loss: 0.4027\n", - "Epoch 13/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8786 - loss: 0.3448 - val_accuracy: 0.8562 - val_loss: 0.4194\n", - "Epoch 14/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8769 - loss: 0.3622 - val_accuracy: 0.8440 - val_loss: 0.4315\n", - "Epoch 15/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8831 - loss: 0.3358 - val_accuracy: 0.8530 - val_loss: 0.4754\n", - "Epoch 16/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8853 - loss: 0.3256 - val_accuracy: 0.8578 - val_loss: 0.4148\n", - "Epoch 17/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8865 - loss: 0.3263 - val_accuracy: 0.8510 - val_loss: 0.4600\n", - "Epoch 18/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8854 - loss: 0.3193 - val_accuracy: 0.8552 - val_loss: 0.4512\n", - "Epoch 19/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8879 - loss: 0.3197 - val_accuracy: 0.8530 - val_loss: 0.4577\n", - "Epoch 20/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8876 - loss: 0.3229 - val_accuracy: 0.8572 - val_loss: 0.4659\n", - "Epoch 21/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8892 - loss: 0.3099 - val_accuracy: 0.8506 - val_loss: 0.4705\n", - "Epoch 22/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8880 - loss: 0.3213 - val_accuracy: 0.8626 - val_loss: 0.4255\n", - "Epoch 23/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8911 - loss: 0.3110 - val_accuracy: 0.8508 - val_loss: 0.4534\n", - "Epoch 24/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8951 - loss: 0.2982 - val_accuracy: 0.8580 - val_loss: 0.4383\n", - "Epoch 25/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8930 - loss: 0.3023 - val_accuracy: 0.8578 - val_loss: 0.4875\n", - "Epoch 26/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8929 - loss: 0.3012 - val_accuracy: 0.8634 - val_loss: 0.4421\n", - "Epoch 27/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8950 - loss: 0.2971 - val_accuracy: 0.8592 - val_loss: 0.4446\n", - "Epoch 28/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8946 - loss: 0.2928 - val_accuracy: 0.8622 - val_loss: 0.4505\n", - "Epoch 29/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8993 - loss: 0.2810 - val_accuracy: 0.8548 - val_loss: 0.5223\n", - "Epoch 30/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8961 - loss: 0.2942 - val_accuracy: 0.8574 - val_loss: 0.4575\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model_ter = tf.keras.Sequential([\n", - " tf.keras.layers.Input(shape=[28,28]),\n", - " tf.keras.layers.Flatten(),\n", - " tf.keras.layers.Dense(300,activation=\"relu\", kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(100,activation=\"relu\",kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(10,activation=\"softmax\"),\n", - "])\n", - "model_ter.compile(loss=\"sparse_categorical_crossentropy\",\n", - " optimizer=\"adam\",\n", - " metrics=[\"accuracy\"])\n", - "model_ter.fit(X_train, y_train, epochs=30, validation_data=(X_val, y_val))" - ] - }, - { - "cell_type": "markdown", - "id": "bsTVF2Dy6cGo", - "metadata": { - "id": "bsTVF2Dy6cGo" - }, - "source": [ - "**Optional 3** : Train the model on the dataset with a different normalization : divide by 25000 so that the inputs are much smaller (use only 30 epochs as it takes time). Compare with the case where you normalize by dividing by 255.0 (you can also try dividing by 2500.0, you should not see such a big difference with the case where we divide by 255.0. Remember that we have a shallow network here)." - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "1-KComPFy1wS", - "metadata": { - "id": "1-KComPFy1wS" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.6645 - loss: 0.9781 - val_accuracy: 0.8202 - val_loss: 0.4931\n", - "Epoch 2/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8294 - loss: 0.4769 - val_accuracy: 0.8336 - val_loss: 0.4414\n", - "Epoch 3/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8493 - loss: 0.4246 - val_accuracy: 0.8432 - val_loss: 0.4204\n", - "Epoch 4/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8587 - loss: 0.3927 - val_accuracy: 0.8468 - val_loss: 0.4029\n", - "Epoch 5/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8652 - loss: 0.3678 - val_accuracy: 0.8494 - val_loss: 0.3902\n", - "Epoch 6/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8718 - loss: 0.3475 - val_accuracy: 0.8546 - val_loss: 0.3777\n", - "Epoch 7/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8785 - loss: 0.3303 - val_accuracy: 0.8578 - val_loss: 0.3656\n", - "Epoch 8/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8828 - loss: 0.3153 - val_accuracy: 0.8598 - val_loss: 0.3589\n", - "Epoch 9/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8879 - loss: 0.3020 - val_accuracy: 0.8626 - val_loss: 0.3541\n", - "Epoch 10/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8918 - loss: 0.2908 - val_accuracy: 0.8648 - val_loss: 0.3486\n", - "Epoch 11/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8953 - loss: 0.2805 - val_accuracy: 0.8674 - val_loss: 0.3464\n", - "Epoch 12/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8993 - loss: 0.2703 - val_accuracy: 0.8688 - val_loss: 0.3441\n", - "Epoch 13/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9020 - loss: 0.2616 - val_accuracy: 0.8708 - val_loss: 0.3416\n", - "Epoch 14/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9050 - loss: 0.2533 - val_accuracy: 0.8732 - val_loss: 0.3379\n", - "Epoch 15/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9088 - loss: 0.2455 - val_accuracy: 0.8752 - val_loss: 0.3380\n", - "Epoch 16/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9120 - loss: 0.2377 - val_accuracy: 0.8758 - val_loss: 0.3348\n", - "Epoch 17/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9158 - loss: 0.2304 - val_accuracy: 0.8762 - val_loss: 0.3331\n", - "Epoch 18/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9181 - loss: 0.2232 - val_accuracy: 0.8756 - val_loss: 0.3341\n", - "Epoch 19/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9216 - loss: 0.2164 - val_accuracy: 0.8782 - val_loss: 0.3340\n", - "Epoch 20/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9231 - loss: 0.2097 - val_accuracy: 0.8802 - val_loss: 0.3352\n", - "Epoch 21/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9264 - loss: 0.2034 - val_accuracy: 0.8824 - val_loss: 0.3378\n", - "Epoch 22/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9279 - loss: 0.1971 - val_accuracy: 0.8824 - val_loss: 0.3412\n", - "Epoch 23/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9308 - loss: 0.1910 - val_accuracy: 0.8812 - val_loss: 0.3456\n", - "Epoch 24/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9327 - loss: 0.1850 - val_accuracy: 0.8844 - val_loss: 0.3487\n", - "Epoch 25/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9347 - loss: 0.1800 - val_accuracy: 0.8840 - val_loss: 0.3529\n", - "Epoch 26/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9370 - loss: 0.1740 - val_accuracy: 0.8836 - val_loss: 0.3559\n", - "Epoch 27/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9393 - loss: 0.1683 - val_accuracy: 0.8836 - val_loss: 0.3620\n", - "Epoch 28/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9410 - loss: 0.1630 - val_accuracy: 0.8830 - val_loss: 0.3677\n", - "Epoch 29/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9425 - loss: 0.1580 - val_accuracy: 0.8828 - val_loss: 0.3725\n", - "Epoch 30/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9439 - loss: 0.1531 - val_accuracy: 0.8850 - val_loss: 0.3794\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model_5 = tf.keras.Sequential([\n", - " tf.keras.layers.Input(shape=[28,28]),\n", - " tf.keras.layers.Flatten(),\n", - " tf.keras.layers.Dense(300,activation=\"relu\", kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(100,activation=\"relu\",kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(10,activation=\"softmax\"),\n", - "])\n", - "model_5.compile(loss=\"sparse_categorical_crossentropy\",\n", - " optimizer=\"adam\",\n", - " metrics=[\"accuracy\"])\n", - "\n", - "X_train_far_too_small, X_val_far_too_small = X_train/25500.0, X_val/25500.0\n", - "\n", - "model_5.fit(X_train_far_too_small, y_train, epochs=30, validation_data=(X_val_far_too_small, y_val))" - ] - }, - { - "cell_type": "markdown", - "id": "kH6PsYnL9Tmz", - "metadata": { - "id": "kH6PsYnL9Tmz" - }, - "source": [ - "**Optional 4** : try using the sigmoid activation for the hidden layers instead of the ReLU. First train the model on normalized data then on un-normalized data." - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "dShxjtDny8HD", - "metadata": { - "id": "dShxjtDny8HD" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7407 - loss: 0.7888 - val_accuracy: 0.8360 - val_loss: 0.4605\n", - "Epoch 2/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8553 - loss: 0.3999 - val_accuracy: 0.8386 - val_loss: 0.4300\n", - "Epoch 3/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8715 - loss: 0.3539 - val_accuracy: 0.8498 - val_loss: 0.4042\n", - "Epoch 4/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8813 - loss: 0.3239 - val_accuracy: 0.8580 - val_loss: 0.3892\n", - "Epoch 5/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8894 - loss: 0.3013 - val_accuracy: 0.8626 - val_loss: 0.3787\n", - "Epoch 6/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8959 - loss: 0.2828 - val_accuracy: 0.8678 - val_loss: 0.3787\n", - "Epoch 7/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9021 - loss: 0.2669 - val_accuracy: 0.8678 - val_loss: 0.3790\n", - "Epoch 8/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9069 - loss: 0.2533 - val_accuracy: 0.8710 - val_loss: 0.3780\n", - "Epoch 9/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9120 - loss: 0.2399 - val_accuracy: 0.8704 - val_loss: 0.3782\n", - "Epoch 10/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9176 - loss: 0.2273 - val_accuracy: 0.8710 - val_loss: 0.3808\n", - "Epoch 11/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9214 - loss: 0.2158 - val_accuracy: 0.8726 - val_loss: 0.3805\n", - "Epoch 12/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9257 - loss: 0.2049 - val_accuracy: 0.8694 - val_loss: 0.3859\n", - "Epoch 13/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9304 - loss: 0.1945 - val_accuracy: 0.8720 - val_loss: 0.3934\n", - "Epoch 14/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9336 - loss: 0.1846 - val_accuracy: 0.8716 - val_loss: 0.4023\n", - "Epoch 15/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9372 - loss: 0.1754 - val_accuracy: 0.8676 - val_loss: 0.4147\n", - "Epoch 16/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9404 - loss: 0.1666 - val_accuracy: 0.8676 - val_loss: 0.4186\n", - "Epoch 17/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9441 - loss: 0.1582 - val_accuracy: 0.8696 - val_loss: 0.4338\n", - "Epoch 18/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9460 - loss: 0.1509 - val_accuracy: 0.8670 - val_loss: 0.4443\n", - "Epoch 19/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9500 - loss: 0.1429 - val_accuracy: 0.8706 - val_loss: 0.4454\n", - "Epoch 20/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9526 - loss: 0.1362 - val_accuracy: 0.8686 - val_loss: 0.4618\n", - "Epoch 21/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9554 - loss: 0.1292 - val_accuracy: 0.8656 - val_loss: 0.4863\n", - "Epoch 22/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9577 - loss: 0.1220 - val_accuracy: 0.8662 - val_loss: 0.4932\n", - "Epoch 23/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - accuracy: 0.9597 - loss: 0.1170 - val_accuracy: 0.8658 - val_loss: 0.5143\n", - "Epoch 24/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9599 - loss: 0.1135 - val_accuracy: 0.8648 - val_loss: 0.5415\n", - "Epoch 25/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9629 - loss: 0.1068 - val_accuracy: 0.8620 - val_loss: 0.5629\n", - "Epoch 26/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9644 - loss: 0.1021 - val_accuracy: 0.8590 - val_loss: 0.6076\n", - "Epoch 27/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9667 - loss: 0.0971 - val_accuracy: 0.8640 - val_loss: 0.6027\n", - "Epoch 28/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9673 - loss: 0.0953 - val_accuracy: 0.8594 - val_loss: 0.6309\n", - "Epoch 29/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9688 - loss: 0.0910 - val_accuracy: 0.8630 - val_loss: 0.6526\n", - "Epoch 30/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9710 - loss: 0.0864 - val_accuracy: 0.8640 - val_loss: 0.6396\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# sigmoid activation, normalized data (scale : [0,1])\n", - "model_sig_norm = tf.keras.Sequential([\n", - " tf.keras.layers.Input(shape=[28,28]),\n", - " tf.keras.layers.Flatten(),\n", - " tf.keras.layers.Dense(300,activation=\"sigmoid\", kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(100,activation=\"sigmoid\",kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(10,activation=\"softmax\"),\n", - "])\n", - "model_sig_norm.compile(loss=\"sparse_categorical_crossentropy\",\n", - " optimizer=\"adam\",\n", - " metrics=[\"accuracy\"])\n", - "model_sig_norm.fit(X_train01, y_train, epochs=30, validation_data=(X_val, y_val))" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "1O32YLVuy8k3", - "metadata": { - "id": "1O32YLVuy8k3" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.6551 - loss: 1.0137 - val_accuracy: 0.6920 - val_loss: 0.7548\n", - "Epoch 2/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7053 - loss: 0.7489 - val_accuracy: 0.7290 - val_loss: 0.7050\n", - "Epoch 3/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7162 - loss: 0.7261 - val_accuracy: 0.7220 - val_loss: 0.7043\n", - "Epoch 4/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7244 - loss: 0.6950 - val_accuracy: 0.7410 - val_loss: 0.6906\n", - "Epoch 5/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7329 - loss: 0.6854 - val_accuracy: 0.7522 - val_loss: 0.6677\n", - "Epoch 6/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7434 - loss: 0.6751 - val_accuracy: 0.7538 - val_loss: 0.6704\n", - "Epoch 7/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7419 - loss: 0.6836 - val_accuracy: 0.7470 - val_loss: 0.6619\n", - "Epoch 8/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7357 - loss: 0.6719 - val_accuracy: 0.7456 - val_loss: 0.6474\n", - "Epoch 9/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7386 - loss: 0.6690 - val_accuracy: 0.7386 - val_loss: 0.6632\n", - "Epoch 10/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7397 - loss: 0.6665 - val_accuracy: 0.7442 - val_loss: 0.6630\n", - "Epoch 11/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7473 - loss: 0.6595 - val_accuracy: 0.7466 - val_loss: 0.6551\n", - "Epoch 12/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7376 - loss: 0.6605 - val_accuracy: 0.7662 - val_loss: 0.6222\n", - "Epoch 13/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7563 - loss: 0.6315 - val_accuracy: 0.7732 - val_loss: 0.5941\n", - "Epoch 14/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7706 - loss: 0.6042 - val_accuracy: 0.7624 - val_loss: 0.6283\n", - "Epoch 15/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7615 - loss: 0.6226 - val_accuracy: 0.7598 - val_loss: 0.6130\n", - "Epoch 16/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7657 - loss: 0.6080 - val_accuracy: 0.7798 - val_loss: 0.5883\n", - "Epoch 17/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7628 - loss: 0.6154 - val_accuracy: 0.7702 - val_loss: 0.6045\n", - "Epoch 18/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7724 - loss: 0.5999 - val_accuracy: 0.7810 - val_loss: 0.5828\n", - "Epoch 19/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7839 - loss: 0.5758 - val_accuracy: 0.7930 - val_loss: 0.5618\n", - "Epoch 20/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7901 - loss: 0.5718 - val_accuracy: 0.7860 - val_loss: 0.5895\n", - "Epoch 21/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7845 - loss: 0.5713 - val_accuracy: 0.7808 - val_loss: 0.5898\n", - "Epoch 22/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7779 - loss: 0.5845 - val_accuracy: 0.7874 - val_loss: 0.5695\n", - "Epoch 23/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7872 - loss: 0.5686 - val_accuracy: 0.7676 - val_loss: 0.5934\n", - "Epoch 24/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7815 - loss: 0.5739 - val_accuracy: 0.7920 - val_loss: 0.5528\n", - "Epoch 25/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7892 - loss: 0.5618 - val_accuracy: 0.7928 - val_loss: 0.5675\n", - "Epoch 26/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7882 - loss: 0.5590 - val_accuracy: 0.7988 - val_loss: 0.5464\n", - "Epoch 27/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7866 - loss: 0.5598 - val_accuracy: 0.7764 - val_loss: 0.5784\n", - "Epoch 28/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7838 - loss: 0.5673 - val_accuracy: 0.7848 - val_loss: 0.5651\n", - "Epoch 29/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7886 - loss: 0.5563 - val_accuracy: 0.8008 - val_loss: 0.5436\n", - "Epoch 30/30\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7971 - loss: 0.5387 - val_accuracy: 0.8010 - val_loss: 0.5349\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model_sig_un_norm = tf.keras.Sequential([\n", - " tf.keras.layers.Input(shape=[28,28]),\n", - " tf.keras.layers.Flatten(),\n", - " tf.keras.layers.Dense(300,activation=\"sigmoid\", kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(100,activation=\"sigmoid\",kernel_initializer=\"he_normal\"),\n", - " tf.keras.layers.Dense(10,activation=\"softmax\"),\n", - "])\n", - "model_sig_un_norm.compile(loss=\"sparse_categorical_crossentropy\",\n", - " optimizer=\"adam\",\n", - " metrics=[\"accuracy\"])\n", - "model_sig_un_norm.fit(X_train, y_train, epochs=30, validation_data=(X_val, y_val))" - ] - }, - { - "cell_type": "markdown", - "id": "z9Tmg3PRUXCe", - "metadata": { - "id": "z9Tmg3PRUXCe" - }, - "source": [ - "**Optional 5** Use the ReLU again and try initializing the weights with normally distributed and independent weigths but with a high variance." - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "p5nkk6t8zIzz", - "metadata": { - "id": "p5nkk6t8zIzz" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Epoch 1/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.6039 - loss: 86.8092 - val_accuracy: 0.7452 - val_loss: 19.3635\n", - "Epoch 2/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7728 - loss: 14.7505 - val_accuracy: 0.7648 - val_loss: 8.7317\n", - "Epoch 3/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7867 - loss: 6.8569 - val_accuracy: 0.7916 - val_loss: 3.7573\n", - "Epoch 4/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7893 - loss: 3.0035 - val_accuracy: 0.7756 - val_loss: 1.6859\n", - "Epoch 5/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7805 - loss: 1.3666 - val_accuracy: 0.7798 - val_loss: 1.0656\n", - "Epoch 6/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7814 - loss: 0.9145 - val_accuracy: 0.7768 - val_loss: 0.9132\n", - "Epoch 7/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7917 - loss: 0.7225 - val_accuracy: 0.7832 - val_loss: 0.8141\n", - "Epoch 8/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7993 - loss: 0.6555 - val_accuracy: 0.7934 - val_loss: 0.7410\n", - "Epoch 9/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8125 - loss: 0.5778 - val_accuracy: 0.7986 - val_loss: 0.6734\n", - "Epoch 10/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8231 - loss: 0.5296 - val_accuracy: 0.8092 - val_loss: 0.6434\n", - "Epoch 11/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8347 - loss: 0.4960 - val_accuracy: 0.8220 - val_loss: 0.6397\n", - "Epoch 12/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8415 - loss: 0.4696 - val_accuracy: 0.8220 - val_loss: 0.6570\n", - "Epoch 13/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8482 - loss: 0.4438 - val_accuracy: 0.8270 - val_loss: 0.6685\n", - "Epoch 14/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8525 - loss: 0.4270 - val_accuracy: 0.8238 - val_loss: 0.6539\n", - "Epoch 15/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8581 - loss: 0.4113 - val_accuracy: 0.8290 - val_loss: 0.6831\n", - "Epoch 16/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8640 - loss: 0.3913 - val_accuracy: 0.8298 - val_loss: 0.7134\n", - "Epoch 17/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8691 - loss: 0.3778 - val_accuracy: 0.8262 - val_loss: 0.7223\n", - "Epoch 18/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8705 - loss: 0.3728 - val_accuracy: 0.8280 - val_loss: 0.7357\n", - "Epoch 19/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8743 - loss: 0.3598 - val_accuracy: 0.8288 - val_loss: 0.7622\n", - "Epoch 20/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8787 - loss: 0.3488 - val_accuracy: 0.8250 - val_loss: 0.7780\n", - "Epoch 21/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8801 - loss: 0.3455 - val_accuracy: 0.8354 - val_loss: 0.7774\n", - "Epoch 22/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8834 - loss: 0.3304 - val_accuracy: 0.8282 - val_loss: 0.7972\n", - "Epoch 23/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8846 - loss: 0.3250 - val_accuracy: 0.8316 - val_loss: 0.8399\n", - "Epoch 24/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8864 - loss: 0.3191 - val_accuracy: 0.8364 - val_loss: 0.8428\n", - "Epoch 25/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8881 - loss: 0.3186 - val_accuracy: 0.8266 - val_loss: 0.9485\n", - "Epoch 26/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8901 - loss: 0.3106 - val_accuracy: 0.8376 - val_loss: 0.9145\n", - "Epoch 27/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8923 - loss: 0.3062 - val_accuracy: 0.8310 - val_loss: 0.9605\n", - "Epoch 28/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8931 - loss: 0.3016 - val_accuracy: 0.8420 - val_loss: 0.9259\n", - "Epoch 29/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8948 - loss: 0.2966 - val_accuracy: 0.8424 - val_loss: 0.9897\n", - "Epoch 30/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8977 - loss: 0.2851 - val_accuracy: 0.8406 - val_loss: 1.0251\n", - "Epoch 31/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8985 - loss: 0.2840 - val_accuracy: 0.8340 - val_loss: 1.0227\n", - "Epoch 32/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8979 - loss: 0.2931 - val_accuracy: 0.8336 - val_loss: 1.0029\n", - "Epoch 33/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9007 - loss: 0.2807 - val_accuracy: 0.8366 - val_loss: 1.0235\n", - "Epoch 34/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9013 - loss: 0.2741 - val_accuracy: 0.8410 - val_loss: 0.9453\n", - "Epoch 35/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9049 - loss: 0.2732 - val_accuracy: 0.8376 - val_loss: 1.0164\n", - "Epoch 36/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9045 - loss: 0.2665 - val_accuracy: 0.8408 - val_loss: 1.0273\n", - "Epoch 37/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9060 - loss: 0.2627 - val_accuracy: 0.8380 - val_loss: 1.0743\n", - "Epoch 38/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9054 - loss: 0.2668 - val_accuracy: 0.8386 - val_loss: 1.0879\n", - "Epoch 39/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9070 - loss: 0.2561 - val_accuracy: 0.8424 - val_loss: 1.0748\n", - "Epoch 40/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9097 - loss: 0.2540 - val_accuracy: 0.8308 - val_loss: 1.1934\n", - "Epoch 41/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9112 - loss: 0.2570 - val_accuracy: 0.8412 - val_loss: 1.0743\n", - "Epoch 42/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9100 - loss: 0.2514 - val_accuracy: 0.8400 - val_loss: 1.1461\n", - "Epoch 43/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9093 - loss: 0.2524 - val_accuracy: 0.8370 - val_loss: 1.1910\n", - "Epoch 44/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9118 - loss: 0.2487 - val_accuracy: 0.8394 - val_loss: 1.1850\n", - "Epoch 45/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9132 - loss: 0.2391 - val_accuracy: 0.8398 - val_loss: 1.2205\n", - "Epoch 46/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9142 - loss: 0.2433 - val_accuracy: 0.8356 - val_loss: 1.3211\n", - "Epoch 47/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9157 - loss: 0.2344 - val_accuracy: 0.8372 - val_loss: 1.2488\n", - "Epoch 48/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9160 - loss: 0.2348 - val_accuracy: 0.8420 - val_loss: 1.2971\n", - "Epoch 49/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9162 - loss: 0.2360 - val_accuracy: 0.8468 - val_loss: 1.2902\n", - "Epoch 50/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9179 - loss: 0.2328 - val_accuracy: 0.8336 - val_loss: 1.2355\n", - "Epoch 51/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9202 - loss: 0.2245 - val_accuracy: 0.8302 - val_loss: 1.4387\n", - "Epoch 52/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9182 - loss: 0.2329 - val_accuracy: 0.8346 - val_loss: 1.3602\n", - "Epoch 53/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9196 - loss: 0.2244 - val_accuracy: 0.8370 - val_loss: 1.2779\n", - "Epoch 54/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9206 - loss: 0.2242 - val_accuracy: 0.8444 - val_loss: 1.3331\n", - "Epoch 55/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9234 - loss: 0.2143 - val_accuracy: 0.8542 - val_loss: 1.2873\n", - "Epoch 56/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9205 - loss: 0.2204 - val_accuracy: 0.8406 - val_loss: 1.3728\n", - "Epoch 57/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9207 - loss: 0.2259 - val_accuracy: 0.8414 - val_loss: 1.3721\n", - "Epoch 58/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9237 - loss: 0.2151 - val_accuracy: 0.8474 - val_loss: 1.3719\n", - "Epoch 59/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9228 - loss: 0.2189 - val_accuracy: 0.8414 - val_loss: 1.3527\n", - "Epoch 60/60\n", - "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9254 - loss: 0.2101 - val_accuracy: 0.8394 - val_loss: 1.4407\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model_high_variance = tf.keras.Sequential([\n", - " tf.keras.layers.Input(shape=[28,28]),\n", - " tf.keras.layers.Flatten(),\n", - " tf.keras.layers.Dense(300,activation=\"relu\"),\n", - " tf.keras.layers.Dense(100,activation=\"relu\"),\n", - " tf.keras.layers.Dense(10,activation=\"softmax\"),\n", - "])\n", - "model_high_variance.layers[1].set_weights([200*np.random.randn(28*28,300)/100, np.zeros(300)])\n", - "model_high_variance.layers[2].set_weights([200*np.random.randn(300,100)/100, np.zeros(100)])\n", - "\n", - "model_high_variance.compile(loss=\"sparse_categorical_crossentropy\",\n", - " optimizer=\"adam\",\n", - " metrics=[\"accuracy\"])\n", - "\n", - "model_high_variance.fit(X_train01, y_train, epochs=60, validation_data=(X_val01, y_val))" - ] - } - ], - "metadata": { - "accelerator": "GPU", - "colab": { - "gpuType": "T4", - "provenance": [] - }, - "kernelspec": { - "display_name": ".venv", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.9" - } + "cells": [ + { + "cell_type": "markdown", + "id": "ced704ec-0d0d-45c3-9b55-2368396e5c77", + "metadata": { + "id": "ced704ec-0d0d-45c3-9b55-2368396e5c77" + }, + "source": [ + "# TP6 A short introduction to neural networks with Keras" + ] }, - "nbformat": 4, - "nbformat_minor": 5 + { + "cell_type": "markdown", + "id": "cd455d57-9a48-4a1c-82d6-2894f99cdb6d", + "metadata": { + "id": "cd455d57-9a48-4a1c-82d6-2894f99cdb6d" + }, + "source": [ + "We will use the Keras library, which serves as a high-level API for TensorFlow.\n", + "\n", + " Keras is a\n", + "deep-learning framework for Python that provides a convenient way to define and\n", + "train almost any kind of deep-learning model. Keras was initially developed for\n", + "researchers, with the aim of enabling fast experimentation.\n", + "Keras has the following key features:\n", + "- It allows the same code to run seamlessly on CPU or GPU.\n", + "- It has a user-friendly API that makes it easy to quickly prototype deep-learning\n", + "models.\n", + "- It has built-in support for convolutional networks (for computer vision), recurrent\n", + "networks (for sequence processing), and any combination of both.\n", + "- It supports arbitrary network architectures: multi-input or multi-output models,\n", + "layer sharing, model sharing, and so on.\n", + "\n", + "Extracted from the book \"Deep Learning with Python \", author : François Chollet.\n", + "\n", + "Remark : \n", + "\n", + " - PyTorch is more popular among researchers and academic practitioners for its flexibility and ease of use.\n", + "\n", + " - TensorFlow is preferred by industry professionals for large-scale applications and production deployment.\n" + ] + }, + { + "cell_type": "markdown", + "id": "ahhFpKIMWSxI", + "metadata": { + "id": "ahhFpKIMWSxI" + }, + "source": [ + "This tutorial uses the Fashion MNIST dataset which contains 70,000 grayscale images in 10 categories. The images show individual articles of clothing at low resolution (28 by 28 pixels). We will only use an MLP." + ] + }, + { + "cell_type": "markdown", + "id": "cT3zmP9N-Gfb", + "metadata": { + "id": "cT3zmP9N-Gfb" + }, + "source": [ + "Remark : in colab, try using the GPU instead of the CPU (Click on the \"Runtime\" menu at the top.\n", + "Select \"Change runtime type.\"\n", + "In the dialog box that appears, choose \"GPU\" under the Hardware accelerator dropdown menu.\n", + "Click \"Save.\" \n", + "\n", + "(GPU access is available with free Colab, but it comes with usage and performance limitations compared to the paid options)." + ] + }, + { + "cell_type": "markdown", + "id": "48a02457-d8ec-4c0a-b11f-7d4819c75e8d", + "metadata": { + "id": "48a02457-d8ec-4c0a-b11f-7d4819c75e8d" + }, + "source": [ + " Fashion MNIST is a slightly more challenging problem than regular MNIST. Both datasets are relatively small and are used to verify that an algorithm works as expected.\n", + "\n", + "Here, 60,000 images are used to train the network and 10,000 images to evaluate how accurately the network learned to classify images. You can access the Fashion MNIST directly from TensorFlow" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "5260add2-2092-4849-b39b-0b4416d60275", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "5260add2-2092-4849-b39b-0b4416d60275", + "outputId": "654e42f5-eb10-449a-f110-d62b0e81fc0a" + }, + "outputs": [], + "source": [ + "import tensorflow as tf\n", + "import numpy as np\n", + "\n", + "tf.keras.utils.set_random_seed(42)\n", + "fashion_mnist = tf.keras.datasets.fashion_mnist\n", + "(X_train, y_train), (X_test, y_test) = fashion_mnist.load_data()" + ] + }, + { + "cell_type": "markdown", + "id": "1003ff8e-552e-425e-81df-85d623b062e3", + "metadata": { + "id": "1003ff8e-552e-425e-81df-85d623b062e3" + }, + "source": [ + "Let us take a look at the shape and the datatype of the training set :" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "cf702fe0-4b88-441e-a6c1-73fd5c57111f", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "cf702fe0-4b88-441e-a6c1-73fd5c57111f", + "outputId": "4f1ec97c-59a0-4eb7-ed01-8423374eb1e5" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "((60000, 28, 28), dtype('uint8'))" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "X_train.shape, X_train.dtype" + ] + }, + { + "cell_type": "markdown", + "id": "oXlaIKYNYQIl", + "metadata": { + "id": "oXlaIKYNYQIl" + }, + "source": [ + "We will need a validation set during training. As the dataset is already shuffled, we will just use the last rows of the dataset for the validation set :" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "aoanwQnmYa3K", + "metadata": { + "id": "aoanwQnmYa3K" + }, + "outputs": [], + "source": [ + "X_val, y_val = X_train[-5000:], y_train[-5000:]\n", + "X_train, y_train = X_train[:-5000], y_train[:-5000]" + ] + }, + { + "cell_type": "markdown", + "id": "100d1fdb-d769-4dc7-aada-69d816b099aa", + "metadata": { + "id": "100d1fdb-d769-4dc7-aada-69d816b099aa" + }, + "source": [ + "Neural networks process inputs using small weight values, and inputs with large integer values can disrupt or slow down the learning process. As such it is good practice to normalize the pixel values. We do not really know the best way to scale the pixel values for modeling, but we know that some scaling will be required.\n", + "\n", + "A good starting point is to normalize the pixel values of grayscale images, e.g. rescale them to the range [0,1]. This involves first converting the data type from unsigned integers to floats, then dividing the pixel values by the maximum value.\n", + "\n", + "\n", + "\n", + "(If we used the sigmoid or tanh activation for the first layer, it would be even more important not to have too big input values, as they could cause saturation).\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "d5d925c1-6a53-4a9d-99ee-4ebb1a9c9026", + "metadata": { + "id": "d5d925c1-6a53-4a9d-99ee-4ebb1a9c9026" + }, + "outputs": [], + "source": [ + "X_train01, X_val01, X_test01 = X_train / 255.0, X_val / 255.0, X_test / 255.0" + ] + }, + { + "cell_type": "markdown", + "id": "0d393d58-bb7b-4a0b-90d2-2d1895300aa4", + "metadata": { + "id": "0d393d58-bb7b-4a0b-90d2-2d1895300aa4" + }, + "source": [ + "Remarks :\n", + " Normalizing the inputs and initializing the weights properly are particularly important in the context of deep learning (see e.g. the vanishing gradient problem or the exploding gradient problem). Here we have a shallow network, but the size of the inputs and of the weights matter anyway, we just have fewer problems.\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "2e31918c-b394-410a-b879-474f95b25035", + "metadata": { + "id": "2e31918c-b394-410a-b879-474f95b25035" + }, + "source": [ + "Here are the class names (they are not included with the dataset) : " + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "731ad9e7-57ae-47c5-b50d-5d77c28216bd", + "metadata": { + "id": "731ad9e7-57ae-47c5-b50d-5d77c28216bd" + }, + "outputs": [], + "source": [ + "class_names = [\n", + " \"T-shirt/top\",\n", + " \"Trouser\",\n", + " \"Pullover\",\n", + " \"Dress\",\n", + " \"Coat\",\n", + " \"Sandal\",\n", + " \"Shirt\",\n", + " \"Sneaker\",\n", + " \"Bag\",\n", + " \"Ankle boot\",\n", + "]" + ] + }, + { + "cell_type": "markdown", + "id": "7e3a55f3-d4b6-450e-93a2-2d6fb339c3b5", + "metadata": { + "id": "7e3a55f3-d4b6-450e-93a2-2d6fb339c3b5" + }, + "source": [ + "Q1. What does the first image of the training set represent ?" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "WDW-zdxKxv13", + "metadata": { + "id": "WDW-zdxKxv13" + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# answer Q1\n", + "import matplotlib.pyplot as plt\n", + "\n", + "plt.figure(figsize=(10, 10))\n", + "plt.imshow(X_train[0], cmap=\"gray\")\n", + "plt.xlabel(class_names[y_train[0]])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "244eb6d5-a902-41a6-ac33-c3d97036780a", + "metadata": { + "id": "244eb6d5-a902-41a6-ac33-c3d97036780a" + }, + "source": [ + "Let us display the first 25 images in the training set :" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "b2e30200-0700-435f-89cb-98e0ad0440bc", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 826 + }, + "id": "b2e30200-0700-435f-89cb-98e0ad0440bc", + "outputId": "ce7d30ed-d045-4673-b567-bf9699df5db6" + }, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "plt.figure(figsize=(10, 10))\n", + "for i in range(25):\n", + " plt.subplot(5, 5, i + 1)\n", + " plt.xticks([])\n", + " plt.yticks([])\n", + " plt.grid(False)\n", + " plt.imshow(X_train[i], cmap=plt.cm.binary)\n", + " plt.xlabel(class_names[y_train[i]])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "f18ae0cd-588e-4087-add7-9d32b727f6e1", + "metadata": { + "id": "f18ae0cd-588e-4087-add7-9d32b727f6e1" + }, + "source": [ + "Now let us build the neural network. Here we will build a classification MLP (multi layer perceptron). " + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "ed84911d-a6d5-484d-9ba6-97570069a4fb", + "metadata": { + "id": "ed84911d-a6d5-484d-9ba6-97570069a4fb" + }, + "outputs": [], + "source": [ + "model = tf.keras.Sequential(\n", + " [\n", + " tf.keras.layers.Input(shape=[28, 28]),\n", + " tf.keras.layers.Flatten(),\n", + " tf.keras.layers.Dense(300, activation=\"relu\", kernel_initializer=\"he_normal\"),\n", + " tf.keras.layers.Dense(100, activation=\"relu\", kernel_initializer=\"he_normal\"),\n", + " tf.keras.layers.Dense(10, activation=\"softmax\"),\n", + " ]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "d18862c4-b4b6-4aec-9312-8c2ee7644117", + "metadata": { + "id": "d18862c4-b4b6-4aec-9312-8c2ee7644117" + }, + "source": [ + "Q2.\n", + " a) What does the `Flatten` layer do ?\n", + "\n", + " b) What do the numbers 300, 100 and 10 represent ?\n", + "\n", + " c) How many hidden layers are there ?\n", + "\n", + " d) Why do we use the softmax activation function in the output layer and what do the outputs of the last layer represent ?\n", + "\n", + " e) What does \"sequential\" mean ?" + ] + }, + { + "cell_type": "markdown", + "id": "491ab5d1", + "metadata": {}, + "source": [ + "**Answer**:\n", + "\n", + "a) The flatten layer transforms the 2D input (28×28 pixels) into a 1D vector of size 784. This is necessary before feeding the data into fully connected (Dense) layers.\n", + "\n", + "b) They are the number of neurons in each Dense (fully connected) layer:\n", + "- 300 neurons in the first hidden layer\n", + "- 100 neurons in the second hidden layer\n", + "- 10 neurons in the output layer (one for each class, e.g., digits 0–9)\n", + "\n", + "c) There are 2 hidden layers (those with 300 and 100 neurons). The final layer is the output layer.\n", + "\n", + "d) Softmax turns the raw scores into probabilities that sum to 1. Each output represents the model’s confidence that the input belongs to a specific class (e.g., digit 0–9 in MNIST).\n", + "\n", + "e) It means the model’s layers are arranged in a linear sequence: each layer feeds directly into the next, with no branching or multiple inputs/outputs.\n", + "\n", + "f) A Dense layer (also called a fully connected layer) is a layer where every neuron is connected to all the neurons in the previous layer." + ] + }, + { + "cell_type": "markdown", + "id": "cf344a37-1423-4295-bcc9-7effe7a6e2b1", + "metadata": { + "id": "cf344a37-1423-4295-bcc9-7effe7a6e2b1" + }, + "source": [ + "The model's summary() method displays all the model's layers :" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "b7d520b6-738e-413d-bf00-a47cc71c1c93", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 265 + }, + "id": "b7d520b6-738e-413d-bf00-a47cc71c1c93", + "outputId": "42afbab3-c5a5-4f85-ee83-85b9898ebdae" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
Model: \"sequential\"\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1mModel: \"sequential\"\u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ flatten (Flatten)               │ (None, 784)            │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense (Dense)                   │ (None, 300)            │       235,500 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_1 (Dense)                 │ (None, 100)            │        30,100 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_2 (Dense)                 │ (None, 10)             │         1,010 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
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 Total params: 266,610 (1.02 MB)\n",
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 Trainable params: 266,610 (1.02 MB)\n",
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\n" + ], + "text/plain": [ + "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m266,610\u001b[0m (1.02 MB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Non-trainable params: 0 (0.00 B)\n",
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\n" + ], + "text/plain": [ + "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "model.summary()" + ] + }, + { + "cell_type": "markdown", + "id": "c8dbecd7-0695-4eda-a03e-ad3cedaf24a1", + "metadata": { + "id": "c8dbecd7-0695-4eda-a03e-ad3cedaf24a1" + }, + "source": [ + "Q3. a) What does 235,500 correspond to ?\n", + "\n", + "b) What is a \"non trainable\" parameter ?" + ] + }, + { + "cell_type": "markdown", + "id": "b86437d9", + "metadata": {}, + "source": [ + "**Answer**: \n", + "\n", + "a) `235 000` represents the total number of parameters (weights + biais) for the first layer ($(784+1)*300=235 500$).\n", + "b) The parameter is not modified by back-propagation" + ] + }, + { + "cell_type": "markdown", + "id": "mSmqvW3tBvey", + "metadata": { + "id": "mSmqvW3tBvey" + }, + "source": [ + "Q4. Display the weights and the biases of the first hidden layer." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "Khr8wuf_DKW-", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Khr8wuf_DKW-", + "outputId": "18d2cb28-ec1b-4ba5-ffbf-a27c4a8d558f" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[-0.02708957, -0.01657043, -0.02541305, ..., -0.0117284 ,\n", + " -0.07759066, -0.04104815],\n", + " [ 0.03956839, 0.03968426, 0.11159597, ..., 0.00709551,\n", + " 0.10016222, 0.00951595],\n", + " [ 0.0368086 , -0.00992455, 0.00582458, ..., -0.05939534,\n", + " 0.00859205, 0.04936637],\n", + " ...,\n", + " [ 0.0014246 , -0.04466628, 0.00846922, ..., -0.05190999,\n", + " 0.03495238, 0.05571212],\n", + " [ 0.00618674, 0.00718611, -0.04097459, ..., -0.04273593,\n", + " 0.03054574, -0.05612838],\n", + " [ 0.02281788, 0.00126068, -0.07944933, ..., 0.08006408,\n", + " -0.02017345, 0.07210501]], shape=(784, 300), dtype=float32)" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Answer for Q4.\n", + "weights, biaises = model.layers[1].get_weights()\n", + "weights" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "S__6iEM6NwHA", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "S__6iEM6NwHA", + "outputId": "e78e4fc9-64e4-497b-b944-b3e31408b614" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "biaises" + ] + }, + { + "cell_type": "markdown", + "id": "w0aWN8LMwFS2", + "metadata": { + "id": "w0aWN8LMwFS2" + }, + "source": [ + "Q5.\n", + "\n", + "a) **Why don't we initialize all the weights to zero (as is done with the biases) ?**\n", + "\n", + "b) **What happens if we initialize all the weights and the biases of a layer with the same value ?**\n", + "\n", + "**Answer**: \n", + "\n", + "a) If all weights are initialized to zero, every neuron in the layer learns the same thing. Specifically:\n", + "\n", + "During forward propagation, all neurons in the same layer produce the same output.\n", + "\n", + "During backpropagation, they also receive the same gradients.\n", + "\n", + "As a result, they remain identical throughout training — this is called the symmetry problem.\n", + "\n", + "By contrast, biases can safely be initialized to zero because they are scalars per neuron and don’t affect symmetry in the same way — they don’t control how inputs are mixed.\n", + "\n", + "b) Same problem: no diversity in computation.\n", + "\n", + "All neurons in the layer will compute the same output (same weights + same bias).\n", + "\n", + "The network loses its capacity to learn different features, which defeats the purpose of having multiple neurons.\n", + "\n", + "The gradients with respect to each parameter are also the same → weights evolve identically, maintaining this symmetry forever.\n", + "\n", + "Thus, random initialization (usually with small values) breaks this symmetry and allows different neurons to specialize.\n", + "\n", + "----\n", + "\n", + "The initialization is usually random : the weights are sampled from a normal distribution or a uniform distribution, usually independently. In particular in the context of deep learning, the variances of these normal distributions are important to keep a relatively constant scale (in the neurons from layer to layer and in the gradients when doing the backpropagation).\n", + "\n", + "Remarks : when you create a multilayer perceptron (MLP) using Keras, each dense layer by default uses the Glorot Uniform initializer for its weight matrix and initializes the biases to zeros.\n", + "You can always override these defaults by specifying a different initializer in the layer's constructor if needed. Actually here, as we used a ReLU activation, we used the \"He\" intializer (it does not matter that much to use \"He\" or \"Gloriot\" here as the network is shallow. However, even for a shallow network, it is important for the weights not to be far too small or far too big.)\n", + "\n", + "See also :\n", + "\n", + "https://www.deeplearning.ai/ai-notes/initialization/index.html\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "b0bd0771-3463-46b8-bdef-5bcadbc07052", + "metadata": { + "id": "b0bd0771-3463-46b8-bdef-5bcadbc07052" + }, + "source": [ + "Now we need to \"compile the model\" : it means we will specify the loss function and the optimizer we use. Optionally, you can specify a list of extra metrics to compute during training and evaluation. " + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "3fcfe918-d745-4c66-8350-dd89e34ac93c", + "metadata": { + "id": "3fcfe918-d745-4c66-8350-dd89e34ac93c" + }, + "outputs": [], + "source": [ + "model.compile(\n", + " loss=\"sparse_categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "5d06aed8-0611-461c-979c-9d14e3fe895f", + "metadata": { + "id": "5d06aed8-0611-461c-979c-9d14e3fe895f" + }, + "source": [ + "We used the `sparse_categorical_crossentropy` loss because we have \"sparse labels\" : for each instance, there is just a target class index : from 0 to 9. If instead we had one-hot vectors ( e.g. [0,0,1,0,0,0,0,0,0,0] to represent class 2), then we woud need to use the \"categorical_cross_entropy\" loss instead.\n", + "\n", + "Since it is a classifier, it is useful to measure its accuracy during training and evaluation, which is why we set `metrics=[\"accuracy\"]`. You can find the list of metrics proposed by keras here : https://www.tensorflow.org/api_docs/python/tf/keras/metrics\n", + "\n", + "Q6. What loss would we have chosen if we had a binary classification problem ? See : https://www.tensorflow.org/api_docs/python/tf/keras/losses\n", + "\n", + "Q7. What basic loss could we use for a regression problem ?\n" + ] + }, + { + "cell_type": "markdown", + "id": "813aff4b", + "metadata": {}, + "source": [ + "**Answer**:\n", + "\n", + "Q6) BinaryCrossentropy\n", + "\n", + "Q7) MeanSquareError or MeanAbsoluteError" + ] + }, + { + "cell_type": "markdown", + "id": "63c7c396-cd50-4822-bbf0-abcb0361fa01", + "metadata": { + "id": "63c7c396-cd50-4822-bbf0-abcb0361fa01" + }, + "source": [ + "Now the model is ready to be trained. For this we simply need to call its `fit` method :" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "e784cc36-b04c-4aca-abfc-9fc081fd726b", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "e784cc36-b04c-4aca-abfc-9fc081fd726b", + "outputId": "2b3ac988-ef08-4d0f-ece5-feb82c59c986" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - accuracy: 0.7850 - loss: 0.6068 - val_accuracy: 0.8392 - val_loss: 0.4062\n", + "Epoch 2/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8627 - loss: 0.3769 - val_accuracy: 0.8496 - val_loss: 0.3903\n", + "Epoch 3/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8785 - loss: 0.3303 - val_accuracy: 0.8546 - val_loss: 0.3747\n", + "Epoch 4/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8869 - loss: 0.3037 - val_accuracy: 0.8564 - val_loss: 0.3778\n", + "Epoch 5/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8955 - loss: 0.2810 - val_accuracy: 0.8696 - val_loss: 0.3513\n", + "Epoch 6/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9019 - loss: 0.2642 - val_accuracy: 0.8624 - val_loss: 0.3813\n", + "Epoch 7/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9075 - loss: 0.2505 - val_accuracy: 0.8692 - val_loss: 0.3840\n", + "Epoch 8/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9107 - loss: 0.2379 - val_accuracy: 0.8690 - val_loss: 0.3768\n", + "Epoch 9/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9154 - loss: 0.2250 - val_accuracy: 0.8708 - val_loss: 0.3813\n", + "Epoch 10/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9199 - loss: 0.2152 - val_accuracy: 0.8698 - val_loss: 0.4006\n", + "Epoch 11/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9217 - loss: 0.2051 - val_accuracy: 0.8742 - val_loss: 0.3909\n", + "Epoch 12/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9261 - loss: 0.1969 - val_accuracy: 0.8716 - val_loss: 0.4219\n", + "Epoch 13/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9292 - loss: 0.1890 - val_accuracy: 0.8752 - val_loss: 0.4213\n", + "Epoch 14/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9312 - loss: 0.1828 - val_accuracy: 0.8738 - val_loss: 0.4402\n", + "Epoch 15/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9324 - loss: 0.1763 - val_accuracy: 0.8736 - val_loss: 0.4419\n", + "Epoch 16/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 3ms/step - accuracy: 0.9362 - loss: 0.1691 - val_accuracy: 0.8732 - val_loss: 0.4577\n", + "Epoch 17/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9379 - loss: 0.1626 - val_accuracy: 0.8760 - val_loss: 0.4588\n", + "Epoch 18/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - 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accuracy: 0.9673 - loss: 0.0903 - val_accuracy: 0.8754 - val_loss: 0.7853\n", + "Epoch 49/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9678 - loss: 0.0856 - val_accuracy: 0.8808 - val_loss: 0.7499\n", + "Epoch 50/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9682 - loss: 0.0821 - val_accuracy: 0.8824 - val_loss: 0.7406\n", + "Epoch 51/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9691 - loss: 0.0808 - val_accuracy: 0.8826 - val_loss: 0.7655\n", + "Epoch 52/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9710 - loss: 0.0757 - val_accuracy: 0.8822 - val_loss: 0.8760\n", + "Epoch 53/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9696 - loss: 0.0804 - val_accuracy: 0.8860 - val_loss: 0.7731\n", + "Epoch 54/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9731 - loss: 0.0747 - val_accuracy: 0.8806 - val_loss: 0.8113\n", + "Epoch 55/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9705 - loss: 0.0768 - val_accuracy: 0.8864 - val_loss: 0.8137\n", + "Epoch 56/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9703 - loss: 0.0798 - val_accuracy: 0.8814 - val_loss: 0.8953\n", + "Epoch 57/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9689 - loss: 0.0814 - val_accuracy: 0.8794 - val_loss: 0.8376\n", + "Epoch 58/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9722 - loss: 0.0756 - val_accuracy: 0.8806 - val_loss: 0.8223\n", + "Epoch 59/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9736 - loss: 0.0702 - val_accuracy: 0.8868 - val_loss: 0.8391\n", + "Epoch 60/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9720 - loss: 0.0726 - val_accuracy: 0.8838 - val_loss: 0.8715\n" + ] + } + ], + "source": [ + "history = model.fit(X_train01, y_train, epochs=60, validation_data=(X_val01, y_val))" + ] + }, + { + "cell_type": "markdown", + "id": "pft_8LriRFk6", + "metadata": { + "id": "pft_8LriRFk6" + }, + "source": [ + "Remark : if you call the fit method again, keras continues the training where it left off.\n" + ] + }, + { + "cell_type": "markdown", + "id": "xkoeO0kLF3fp", + "metadata": { + "id": "xkoeO0kLF3fp" + }, + "source": [ + "Q8. Can you recall what is an \"epoch\" ?\n", + "\n", + "**Answer**: An epoch in training a neural network is one complete pass through the entire training dataset.\n", + "\n", + "During an epoch, the model sees every training example once and updates its weights accordingly.\n", + "\n", + "Usually, data is split into mini-batches, so multiple updates happen within a single epoch (this is mini-batch gradient descent).\n", + "\n", + "Training typically involves multiple epochs so the model can gradually improve.\n", + "\n", + "Think of an epoch as one full cycle through the training data to learn patterns and adjust weights." + ] + }, + { + "cell_type": "markdown", + "id": "eSKrY64nFqdj", + "metadata": { + "id": "eSKrY64nFqdj" + }, + "source": [ + "Q9. The `fit()` method also has the two arguments `class_weight` and `sample_weight` (not used here). When can these arguments be useful ?\n", + "\n", + "- `class_weight` is used to give more importance to underrepresented classes.\n", + "- `sample_weight` assigns weights to individual samples, useful for noisy data or time-sensitive importance." + ] + }, + { + "cell_type": "markdown", + "id": "a-6IJhqnMcnm", + "metadata": { + "id": "a-6IJhqnMcnm" + }, + "source": [ + "The `fit()` method returns a History object containing in particular a dictionary (`history.history`) containing the loss and extra metrics it measured at the end of each epoch on the training set and on the validation set (if any). Let us display the learning curves." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "_UQsOj8JPc3q", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 470 + }, + "id": "_UQsOj8JPc3q", + "outputId": "8f1d6388-d46b-4891-d73f-793ccf3b9d32" + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "pd.DataFrame(history.history).plot(\n", + " figsize=(8, 5),\n", + " xlim=[0, 59],\n", + " ylim=[0, 1],\n", + " grid=True,\n", + " xlabel=\"Epoch\",\n", + " style=[\"r--\", \"b--\", \"r\", \"b\"],\n", + ")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "L2qi9QymVrXy", + "metadata": { + "id": "L2qi9QymVrXy" + }, + "source": [ + "Q10. 4 values are displayed : \"accuracy\", \"loss\", \"val_accuracy\" and \"val_loss\". Can you tell precisely what each value represents ?\n", + "\n", + "**Answer**: \n", + "\n", + "- `accuracy`: Correct prediction rate on the training set.\n", + "- `loss`: Loss function value on the training set.\n", + "- `val_accuracy`: Correct prediction rate on the validation set.\n", + "- `val_loss`: Loss function value on the validation set." + ] + }, + { + "cell_type": "markdown", + "id": "04TFG3NsRH0N", + "metadata": { + "id": "04TFG3NsRH0N" + }, + "source": [ + "Q11. Comment the curves.\n", + "\n", + "Remark : if we kept increasing the number of epochs, we would end up with a training loss close to zero and a training accuracy close to 100%. More precisely, after about 150 epochs, we get the following values\n", + "- validation loss : about 1.4\n", + "- training loss : about 0.03\n", + "- validation accuracy : about 89%\n", + "- training accuracy : about 99%\n", + "\n", + "**Answer**: There is overfitting (not so grave). This is due to the large number of parameters in the neural network (aobut 260k) while the number of parameters of the dataset is smaller (about 50k)" + ] + }, + { + "cell_type": "markdown", + "id": "nBnufjfFXqiI", + "metadata": { + "id": "nBnufjfFXqiI" + }, + "source": [ + "Q12. a) Find the indices, for the first 200 rows of the validation set, where the model (that we trained for 60 epochs) gets wrong.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "MUnWm1MfyBBk", + "metadata": { + "id": "MUnWm1MfyBBk" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 4ms/step \n" + ] + } + ], + "source": [ + "probas_val_60 = model.predict(X_val01[:200])\n", + "classif_val_60 = probas_val_60.argmax(axis=1)\n", + "wrong_classif_val_60 = classif_val_60 != y_val[:200]" + ] + }, + { + "cell_type": "markdown", + "id": "vJ3wYKSDr2-L", + "metadata": { + "id": "vJ3wYKSDr2-L" + }, + "source": [ + "b) Now let us train the model for only 10 epochs and call this model `model_10`." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "DBsp72CAqRef", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "DBsp72CAqRef", + "outputId": "ab6e22c3-19c2-4610-d028-02a4e940b209" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/10\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7866 - loss: 0.5999 - val_accuracy: 0.8326 - val_loss: 0.4162\n", + "Epoch 2/10\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8624 - loss: 0.3776 - val_accuracy: 0.8512 - val_loss: 0.3772\n", + "Epoch 3/10\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8763 - loss: 0.3341 - val_accuracy: 0.8502 - val_loss: 0.3915\n", + "Epoch 4/10\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 1ms/step - accuracy: 0.8875 - loss: 0.3049 - val_accuracy: 0.8592 - val_loss: 0.3675\n", + "Epoch 5/10\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8936 - loss: 0.2835 - val_accuracy: 0.8720 - val_loss: 0.3465\n", + "Epoch 6/10\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9017 - loss: 0.2663 - val_accuracy: 0.8752 - val_loss: 0.3437\n", + "Epoch 7/10\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9065 - loss: 0.2499 - val_accuracy: 0.8752 - val_loss: 0.3545\n", + "Epoch 8/10\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9102 - loss: 0.2404 - val_accuracy: 0.8810 - val_loss: 0.3369\n", + "Epoch 9/10\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9145 - loss: 0.2271 - val_accuracy: 0.8740 - val_loss: 0.3714\n", + "Epoch 10/10\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9161 - loss: 0.2195 - val_accuracy: 0.8816 - val_loss: 0.3601\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_10 = tf.keras.Sequential(\n", + " [\n", + " tf.keras.layers.Input(shape=[28, 28]),\n", + " tf.keras.layers.Flatten(),\n", + " tf.keras.layers.Dense(300, activation=\"relu\", kernel_initializer=\"he_normal\"),\n", + " tf.keras.layers.Dense(100, activation=\"relu\", kernel_initializer=\"he_normal\"),\n", + " tf.keras.layers.Dense(10, activation=\"softmax\"),\n", + " ]\n", + ")\n", + "\n", + "model_10.compile(\n", + " loss=\"sparse_categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"]\n", + ")\n", + "\n", + "model_10.fit(X_train01, y_train, epochs=10, validation_data=(X_val01, y_val))" + ] + }, + { + "cell_type": "markdown", + "id": "jowzB0kI6a4t", + "metadata": { + "id": "jowzB0kI6a4t" + }, + "source": [ + "So the accuracy on the validation set is almost the same with 10 epochs as with 60 epochs (stagnant val accuracy, and close to the training accuracy) but the validation loss is much better (and rather close to the training loss). If we want to understand better the situation, let us look at some values for the predicted probabilities." + ] + }, + { + "cell_type": "markdown", + "id": "ESbfJeBnsOHl", + "metadata": { + "id": "ESbfJeBnsOHl" + }, + "source": [ + "c) Find the indices, for the first 200 rows of the validation set, where `model_10` (that we trained for 10 epochs) gets wrong." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "7w49W7ecsb42", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "7w49W7ecsb42", + "outputId": "2cef9214-3a2c-4631-c8f2-6275baae3fbf" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m7/7\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 5ms/step \n" + ] + } + ], + "source": [ + "probas_val_10 = model_10.predict(X_val01[:200])\n", + "classif_val_10 = probas_val_10.argmax(axis=1)\n", + "wrong_classif_val_10 = classif_val_10 != y_val[:200]\n", + "\n", + "indices = np.where(wrong_classif_val_10 * wrong_classif_val_60)[0]" + ] + }, + { + "cell_type": "markdown", + "id": "T3uLsznrwP-c", + "metadata": { + "id": "T3uLsznrwP-c" + }, + "source": [ + "d) Display the estimated probabilities of the two models for the right class and for the indices where both models gets wrong (among the first 200 rows of the validation set). (Round to 3 decimal places) \n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "Hf7QyWqMFnUs", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Hf7QyWqMFnUs", + "outputId": "55185cf2-1517-49b2-f1a2-82cf1820dca8" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.001, 0.393, 0.343, 0. , 0. , 0.001, 0.023, 0.189, 0. ,\n", + " 0. , 0. , 0.001, 0.11 , 0.002, 0. , 0.005, 0.006, 0.021],\n", + " dtype=float32)" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "probas_val_60[indices, y_val[indices]].round(3)" + ] + }, + { + "cell_type": "markdown", + "id": "qrUnU77H7FAx", + "metadata": { + "id": "qrUnU77H7FAx" + }, + "source": [ + " We see that most of the time, in the overfitting situation (60 epochs), for an instance that the model does not classify correctly, the probability for the correct label tends to be lower : the model gets wrong for those instances and is \"overly confident while it is wrong\" (it indicates a high probability for a wrong label so the probability for the correct label gets lower making the loss increase).\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "71vLRKp0TZeo", + "metadata": { + "id": "71vLRKp0TZeo" + }, + "source": [ + " An idea to prevent this overfitting is to use **Early stopping** :" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "vYe04DM5cu4r", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "vYe04DM5cu4r", + "outputId": "825bd44c-888d-4820-ca98-4fe2274b7d27" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7864 - loss: 0.5990 - val_accuracy: 0.8298 - val_loss: 0.4282\n", + "Epoch 2/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8627 - loss: 0.3785 - val_accuracy: 0.8450 - val_loss: 0.3963\n", + "Epoch 3/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8772 - loss: 0.3354 - val_accuracy: 0.8544 - val_loss: 0.3724\n", + "Epoch 4/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8889 - loss: 0.3041 - val_accuracy: 0.8632 - val_loss: 0.3656\n", + "Epoch 5/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8957 - loss: 0.2829 - val_accuracy: 0.8686 - val_loss: 0.3534\n", + "Epoch 6/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9019 - loss: 0.2651 - val_accuracy: 0.8746 - val_loss: 0.3442\n", + "Epoch 7/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9071 - loss: 0.2491 - val_accuracy: 0.8844 - val_loss: 0.3403\n", + "Epoch 8/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9088 - loss: 0.2387 - val_accuracy: 0.8840 - val_loss: 0.3357\n", + "Epoch 9/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9157 - loss: 0.2245 - val_accuracy: 0.8834 - val_loss: 0.3541\n", + "Epoch 10/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9198 - loss: 0.2157 - val_accuracy: 0.8714 - val_loss: 0.4132\n", + "Epoch 11/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9220 - loss: 0.2063 - val_accuracy: 0.8770 - val_loss: 0.4210\n", + "Epoch 12/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9256 - loss: 0.1986 - val_accuracy: 0.8768 - val_loss: 0.4228\n", + "Epoch 13/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9291 - loss: 0.1875 - val_accuracy: 0.8738 - val_loss: 0.4382\n" + ] + } + ], + "source": [ + "early_stopping_cb = tf.keras.callbacks.EarlyStopping(\n", + " patience=5, restore_best_weights=True\n", + ")\n", + "\n", + "model = tf.keras.Sequential(\n", + " [\n", + " tf.keras.layers.Input(shape=[28, 28]),\n", + " tf.keras.layers.Flatten(),\n", + " tf.keras.layers.Dense(300, activation=\"relu\", kernel_initializer=\"he_normal\"),\n", + " tf.keras.layers.Dense(100, activation=\"relu\", kernel_initializer=\"he_normal\"),\n", + " tf.keras.layers.Dense(10, activation=\"softmax\"),\n", + " ]\n", + ")\n", + "\n", + "model.compile(\n", + " loss=\"sparse_categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"]\n", + ")\n", + "\n", + "history2 = model.fit(\n", + " X_train01,\n", + " y_train,\n", + " epochs=60,\n", + " validation_data=(X_val01, y_val),\n", + " callbacks=[early_stopping_cb],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "MwTfIPcAeH6R", + "metadata": { + "id": "MwTfIPcAeH6R" + }, + "source": [ + "Q13. a) Explain what the previous cell does (first and last line).\n", + "\n", + " Hint : https://www.tensorflow.org/api_docs/python/tf/keras/callbacks/EarlyStopping\n", + "\n", + "b) Can you name another way to prevent overfitting ? (mentioned in the lecture notes).\n", + "\n", + "**Answer**: \n", + "\n", + "a) *First Line*: This creates a callback to stop training early if the validation loss doesn't improve for 5 consecutive epochs (patience=5). With restore_best_weights=True, the model will roll back to the weights from the epoch with the best validation loss, preventing overfitting.\n", + "*Last Line*: This trains the model on X_train01 and y_train for up to 60 epochs. It uses the validation set (X_val01, y_val) to monitor performance. The training may stop early thanks to the early_stopping_cb, and training history is saved in history2.\n", + "\n", + "b) We can use Dropout. It randomly \"drops\" (i.e. sets to zero) a fraction of the neurons during training, which helps the model generalize better by preventing co-adaptations of neurons. Example:\n", + "\n", + "```{python}\n", + "tf.keras.layers.Dropout(rate=0.5)\n", + "```\n", + "This can be inserted between dense layers to regularize the model.\n" + ] + }, + { + "cell_type": "markdown", + "id": "Anus7RlTV_bL", + "metadata": { + "id": "Anus7RlTV_bL" + }, + "source": [ + "Remark : if you are not satisfied with the performance of your model, you should tune the hyperparameters. There are a lot of hyperparameters that you can tune : learning rate, optimizer, number of hidden layers, number of neurons, batch size etc.\n", + "If you want to fine tune the hyperparameters, you can use the Keras Tuner library : https://www.tensorflow.org/tutorials/keras/keras_tuner" + ] + }, + { + "cell_type": "markdown", + "id": "qZ-0xPXzcglX", + "metadata": { + "id": "qZ-0xPXzcglX" + }, + "source": [ + "Now let us see the performance of our model on the test set." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "q6BXm1YJUmKK", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "q6BXm1YJUmKK", + "outputId": "6c7f3f57-fd81-4727-8422-a4480be423af" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 547us/step - accuracy: 0.8669 - loss: 55.3559\n" + ] + }, + { + "data": { + "text/plain": [ + "[58.230831146240234, 0.864799976348877]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.evaluate(X_test, y_test)" + ] + }, + { + "cell_type": "markdown", + "id": "MexBSb7NCYCP", + "metadata": { + "id": "MexBSb7NCYCP" + }, + "source": [ + "**Optional 1** Train a logistic regression model : this model has far fewer parameters : you should not see the same overfitting problem when increasing the number of epochs." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "GUZldkyGyYwF", + "metadata": { + "id": "GUZldkyGyYwF" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 464us/step - accuracy: 0.7328 - loss: 0.7938 - val_accuracy: 0.8340 - val_loss: 0.4826\n", + "Epoch 2/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 430us/step - accuracy: 0.8391 - loss: 0.4794 - val_accuracy: 0.8422 - val_loss: 0.4516\n", + "Epoch 3/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 425us/step - accuracy: 0.8498 - loss: 0.4464 - val_accuracy: 0.8442 - val_loss: 0.4396\n", + "Epoch 4/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 425us/step - accuracy: 0.8539 - loss: 0.4302 - val_accuracy: 0.8468 - val_loss: 0.4333\n", + "Epoch 5/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 428us/step - accuracy: 0.8566 - loss: 0.4200 - val_accuracy: 0.8476 - val_loss: 0.4295\n", + "Epoch 6/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 427us/step - accuracy: 0.8587 - loss: 0.4128 - val_accuracy: 0.8486 - val_loss: 0.4271\n", + "Epoch 7/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 428us/step - accuracy: 0.8605 - loss: 0.4072 - val_accuracy: 0.8470 - val_loss: 0.4256\n", + "Epoch 8/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 461us/step - accuracy: 0.8622 - loss: 0.4028 - val_accuracy: 0.8486 - val_loss: 0.4246\n", + "Epoch 9/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 427us/step - accuracy: 0.8629 - loss: 0.3992 - val_accuracy: 0.8488 - val_loss: 0.4239\n", + "Epoch 10/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 427us/step - accuracy: 0.8634 - loss: 0.3960 - val_accuracy: 0.8482 - val_loss: 0.4236\n", + "Epoch 11/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 427us/step - accuracy: 0.8641 - loss: 0.3933 - val_accuracy: 0.8480 - val_loss: 0.4235\n", + "Epoch 12/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 428us/step - accuracy: 0.8648 - loss: 0.3910 - val_accuracy: 0.8476 - val_loss: 0.4235\n", + "Epoch 13/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 428us/step - accuracy: 0.8659 - loss: 0.3889 - val_accuracy: 0.8484 - val_loss: 0.4236\n", + "Epoch 14/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 423us/step - accuracy: 0.8665 - loss: 0.3870 - val_accuracy: 0.8490 - val_loss: 0.4238\n", + "Epoch 15/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 424us/step - accuracy: 0.8671 - loss: 0.3852 - val_accuracy: 0.8486 - val_loss: 0.4241\n", + "Epoch 16/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 423us/step - accuracy: 0.8677 - loss: 0.3837 - val_accuracy: 0.8486 - val_loss: 0.4244\n", + "Epoch 17/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 466us/step - accuracy: 0.8683 - loss: 0.3822 - val_accuracy: 0.8482 - val_loss: 0.4248\n", + "Epoch 18/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 439us/step - accuracy: 0.8689 - loss: 0.3809 - val_accuracy: 0.8486 - val_loss: 0.4252\n", + "Epoch 19/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 429us/step - accuracy: 0.8694 - loss: 0.3797 - val_accuracy: 0.8476 - val_loss: 0.4256\n", + "Epoch 20/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 424us/step - accuracy: 0.8698 - loss: 0.3785 - val_accuracy: 0.8472 - val_loss: 0.4260\n", + "Epoch 21/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 429us/step - accuracy: 0.8701 - loss: 0.3774 - val_accuracy: 0.8468 - val_loss: 0.4264\n", + "Epoch 22/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 426us/step - accuracy: 0.8704 - loss: 0.3764 - val_accuracy: 0.8468 - val_loss: 0.4269\n", + "Epoch 23/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 425us/step - accuracy: 0.8705 - loss: 0.3755 - val_accuracy: 0.8468 - val_loss: 0.4274\n", + "Epoch 24/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 426us/step - accuracy: 0.8705 - loss: 0.3746 - val_accuracy: 0.8470 - val_loss: 0.4278\n", + "Epoch 25/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 453us/step - accuracy: 0.8707 - loss: 0.3737 - val_accuracy: 0.8468 - val_loss: 0.4283\n", + "Epoch 26/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 448us/step - accuracy: 0.8708 - loss: 0.3729 - val_accuracy: 0.8470 - val_loss: 0.4288\n", + "Epoch 27/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 443us/step - accuracy: 0.8709 - loss: 0.3721 - val_accuracy: 0.8464 - val_loss: 0.4292\n", + "Epoch 28/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 443us/step - accuracy: 0.8709 - loss: 0.3714 - val_accuracy: 0.8464 - val_loss: 0.4297\n", + "Epoch 29/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 462us/step - accuracy: 0.8710 - loss: 0.3707 - val_accuracy: 0.8464 - val_loss: 0.4302\n", + "Epoch 30/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 453us/step - accuracy: 0.8711 - loss: 0.3700 - val_accuracy: 0.8468 - val_loss: 0.4307\n", + "Epoch 31/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 420us/step - accuracy: 0.8710 - loss: 0.3693 - val_accuracy: 0.8462 - val_loss: 0.4311\n", + "Epoch 32/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 418us/step - accuracy: 0.8714 - loss: 0.3687 - val_accuracy: 0.8458 - val_loss: 0.4316\n", + "Epoch 33/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 417us/step - accuracy: 0.8716 - loss: 0.3681 - val_accuracy: 0.8456 - val_loss: 0.4321\n", + "Epoch 34/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 420us/step - accuracy: 0.8721 - loss: 0.3675 - val_accuracy: 0.8452 - val_loss: 0.4326\n", + "Epoch 35/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 415us/step - accuracy: 0.8724 - loss: 0.3670 - val_accuracy: 0.8448 - val_loss: 0.4331\n", + "Epoch 36/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 420us/step - 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accuracy: 0.8760 - loss: 0.3536 - val_accuracy: 0.8410 - val_loss: 0.4510\n", + "Epoch 77/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 420us/step - accuracy: 0.8760 - loss: 0.3533 - val_accuracy: 0.8412 - val_loss: 0.4514\n", + "Epoch 78/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 421us/step - accuracy: 0.8761 - loss: 0.3531 - val_accuracy: 0.8412 - val_loss: 0.4518\n", + "Epoch 79/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 457us/step - accuracy: 0.8759 - loss: 0.3529 - val_accuracy: 0.8408 - val_loss: 0.4522\n", + "Epoch 80/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 420us/step - accuracy: 0.8761 - loss: 0.3527 - val_accuracy: 0.8406 - val_loss: 0.4526\n", + "Epoch 81/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 418us/step - accuracy: 0.8761 - loss: 0.3526 - val_accuracy: 0.8408 - val_loss: 0.4529\n", + "Epoch 82/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 418us/step - accuracy: 0.8763 - loss: 0.3524 - val_accuracy: 0.8404 - val_loss: 0.4533\n", + "Epoch 83/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 421us/step - accuracy: 0.8763 - loss: 0.3522 - val_accuracy: 0.8402 - val_loss: 0.4537\n", + "Epoch 84/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 421us/step - accuracy: 0.8763 - loss: 0.3520 - val_accuracy: 0.8400 - val_loss: 0.4541\n", + "Epoch 85/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 464us/step - accuracy: 0.8764 - loss: 0.3518 - val_accuracy: 0.8398 - val_loss: 0.4544\n", + "Epoch 86/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 421us/step - accuracy: 0.8765 - loss: 0.3516 - val_accuracy: 0.8398 - val_loss: 0.4548\n", + "Epoch 87/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 420us/step - accuracy: 0.8764 - loss: 0.3514 - val_accuracy: 0.8396 - val_loss: 0.4552\n", + "Epoch 88/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 450us/step - accuracy: 0.8764 - loss: 0.3513 - val_accuracy: 0.8394 - val_loss: 0.4555\n", + "Epoch 89/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 456us/step - accuracy: 0.8765 - loss: 0.3511 - val_accuracy: 0.8392 - val_loss: 0.4559\n", + "Epoch 90/90\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 419us/step - accuracy: 0.8765 - loss: 0.3509 - val_accuracy: 0.8390 - val_loss: 0.4563\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "reg_log = tf.keras.Sequential(\n", + " [\n", + " tf.keras.layers.Input(shape=[28, 28]),\n", + " tf.keras.layers.Flatten(),\n", + " tf.keras.layers.Dense(10, activation=\"softmax\"),\n", + " ]\n", + ")\n", + "reg_log.compile(\n", + " loss=\"sparse_categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"]\n", + ")\n", + "reg_log.fit(X_train01, y_train, epochs=90, validation_data=(X_val01, y_val))" + ] + }, + { + "cell_type": "markdown", + "id": "GR2JJnwv3zUS", + "metadata": { + "id": "GR2JJnwv3zUS" + }, + "source": [ + "**Optional 2** : Train the model on the un-normalized dataset (use only 30 epochs as it takes time)." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "zv-yV-xQyVd8", + "metadata": { + "id": "zv-yV-xQyVd8" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.6586 - loss: 7.7191 - val_accuracy: 0.7086 - val_loss: 0.7708\n", + "Epoch 2/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7257 - loss: 0.7339 - val_accuracy: 0.7668 - val_loss: 0.5891\n", + "Epoch 3/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7667 - loss: 0.6082 - val_accuracy: 0.7880 - val_loss: 0.5681\n", + "Epoch 4/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 1ms/step - accuracy: 0.8169 - loss: 0.5174 - val_accuracy: 0.7946 - val_loss: 0.5648\n", + "Epoch 5/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 1ms/step - accuracy: 0.8377 - loss: 0.4704 - val_accuracy: 0.8270 - val_loss: 0.5107\n", + "Epoch 6/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8448 - loss: 0.4490 - val_accuracy: 0.8330 - val_loss: 0.4713\n", + "Epoch 7/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8521 - loss: 0.4277 - val_accuracy: 0.8534 - val_loss: 0.4069\n", + "Epoch 8/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8628 - loss: 0.3925 - val_accuracy: 0.8542 - val_loss: 0.4263\n", + "Epoch 9/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8668 - loss: 0.3824 - val_accuracy: 0.8584 - val_loss: 0.4099\n", + "Epoch 10/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8705 - loss: 0.3706 - val_accuracy: 0.8496 - val_loss: 0.4153\n", + "Epoch 11/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8745 - loss: 0.3588 - val_accuracy: 0.8550 - val_loss: 0.4377\n", + "Epoch 12/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8766 - loss: 0.3548 - val_accuracy: 0.8652 - val_loss: 0.4027\n", + "Epoch 13/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8786 - loss: 0.3448 - val_accuracy: 0.8562 - val_loss: 0.4194\n", + "Epoch 14/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8769 - loss: 0.3622 - val_accuracy: 0.8440 - val_loss: 0.4315\n", + "Epoch 15/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8831 - loss: 0.3358 - val_accuracy: 0.8530 - val_loss: 0.4754\n", + "Epoch 16/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8853 - loss: 0.3256 - val_accuracy: 0.8578 - val_loss: 0.4148\n", + "Epoch 17/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8865 - loss: 0.3263 - val_accuracy: 0.8510 - val_loss: 0.4600\n", + "Epoch 18/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8854 - loss: 0.3193 - val_accuracy: 0.8552 - val_loss: 0.4512\n", + "Epoch 19/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8879 - loss: 0.3197 - val_accuracy: 0.8530 - val_loss: 0.4577\n", + "Epoch 20/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8876 - loss: 0.3229 - val_accuracy: 0.8572 - val_loss: 0.4659\n", + "Epoch 21/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8892 - loss: 0.3099 - val_accuracy: 0.8506 - val_loss: 0.4705\n", + "Epoch 22/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8880 - loss: 0.3213 - val_accuracy: 0.8626 - val_loss: 0.4255\n", + "Epoch 23/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8911 - loss: 0.3110 - val_accuracy: 0.8508 - val_loss: 0.4534\n", + "Epoch 24/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8951 - loss: 0.2982 - val_accuracy: 0.8580 - val_loss: 0.4383\n", + "Epoch 25/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8930 - loss: 0.3023 - val_accuracy: 0.8578 - val_loss: 0.4875\n", + "Epoch 26/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8929 - loss: 0.3012 - val_accuracy: 0.8634 - val_loss: 0.4421\n", + "Epoch 27/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8950 - loss: 0.2971 - val_accuracy: 0.8592 - val_loss: 0.4446\n", + "Epoch 28/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8946 - loss: 0.2928 - val_accuracy: 0.8622 - val_loss: 0.4505\n", + "Epoch 29/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8993 - loss: 0.2810 - val_accuracy: 0.8548 - val_loss: 0.5223\n", + "Epoch 30/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8961 - loss: 0.2942 - val_accuracy: 0.8574 - val_loss: 0.4575\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_ter = tf.keras.Sequential(\n", + " [\n", + " tf.keras.layers.Input(shape=[28, 28]),\n", + " tf.keras.layers.Flatten(),\n", + " tf.keras.layers.Dense(300, activation=\"relu\", kernel_initializer=\"he_normal\"),\n", + " tf.keras.layers.Dense(100, activation=\"relu\", kernel_initializer=\"he_normal\"),\n", + " tf.keras.layers.Dense(10, activation=\"softmax\"),\n", + " ]\n", + ")\n", + "model_ter.compile(\n", + " loss=\"sparse_categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"]\n", + ")\n", + "model_ter.fit(X_train, y_train, epochs=30, validation_data=(X_val, y_val))" + ] + }, + { + "cell_type": "markdown", + "id": "bsTVF2Dy6cGo", + "metadata": { + "id": "bsTVF2Dy6cGo" + }, + "source": [ + "**Optional 3** : Train the model on the dataset with a different normalization : divide by 25000 so that the inputs are much smaller (use only 30 epochs as it takes time). Compare with the case where you normalize by dividing by 255.0 (you can also try dividing by 2500.0, you should not see such a big difference with the case where we divide by 255.0. Remember that we have a shallow network here)." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "1-KComPFy1wS", + "metadata": { + "id": "1-KComPFy1wS" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.6645 - loss: 0.9781 - val_accuracy: 0.8202 - val_loss: 0.4931\n", + "Epoch 2/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8294 - loss: 0.4769 - val_accuracy: 0.8336 - val_loss: 0.4414\n", + "Epoch 3/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8493 - loss: 0.4246 - val_accuracy: 0.8432 - val_loss: 0.4204\n", + "Epoch 4/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8587 - loss: 0.3927 - val_accuracy: 0.8468 - val_loss: 0.4029\n", + "Epoch 5/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8652 - loss: 0.3678 - val_accuracy: 0.8494 - val_loss: 0.3902\n", + "Epoch 6/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8718 - loss: 0.3475 - val_accuracy: 0.8546 - val_loss: 0.3777\n", + "Epoch 7/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8785 - loss: 0.3303 - val_accuracy: 0.8578 - val_loss: 0.3656\n", + "Epoch 8/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8828 - loss: 0.3153 - val_accuracy: 0.8598 - val_loss: 0.3589\n", + "Epoch 9/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8879 - loss: 0.3020 - val_accuracy: 0.8626 - val_loss: 0.3541\n", + "Epoch 10/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8918 - loss: 0.2908 - val_accuracy: 0.8648 - val_loss: 0.3486\n", + "Epoch 11/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8953 - loss: 0.2805 - val_accuracy: 0.8674 - val_loss: 0.3464\n", + "Epoch 12/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8993 - loss: 0.2703 - val_accuracy: 0.8688 - val_loss: 0.3441\n", + "Epoch 13/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9020 - loss: 0.2616 - val_accuracy: 0.8708 - val_loss: 0.3416\n", + "Epoch 14/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9050 - loss: 0.2533 - val_accuracy: 0.8732 - val_loss: 0.3379\n", + "Epoch 15/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9088 - loss: 0.2455 - val_accuracy: 0.8752 - val_loss: 0.3380\n", + "Epoch 16/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9120 - loss: 0.2377 - val_accuracy: 0.8758 - val_loss: 0.3348\n", + "Epoch 17/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9158 - loss: 0.2304 - val_accuracy: 0.8762 - val_loss: 0.3331\n", + "Epoch 18/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9181 - loss: 0.2232 - val_accuracy: 0.8756 - val_loss: 0.3341\n", + "Epoch 19/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9216 - loss: 0.2164 - val_accuracy: 0.8782 - val_loss: 0.3340\n", + "Epoch 20/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9231 - loss: 0.2097 - val_accuracy: 0.8802 - val_loss: 0.3352\n", + "Epoch 21/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9264 - loss: 0.2034 - val_accuracy: 0.8824 - val_loss: 0.3378\n", + "Epoch 22/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9279 - loss: 0.1971 - val_accuracy: 0.8824 - val_loss: 0.3412\n", + "Epoch 23/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9308 - loss: 0.1910 - val_accuracy: 0.8812 - val_loss: 0.3456\n", + "Epoch 24/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9327 - loss: 0.1850 - val_accuracy: 0.8844 - val_loss: 0.3487\n", + "Epoch 25/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9347 - loss: 0.1800 - val_accuracy: 0.8840 - val_loss: 0.3529\n", + "Epoch 26/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9370 - loss: 0.1740 - val_accuracy: 0.8836 - val_loss: 0.3559\n", + "Epoch 27/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9393 - loss: 0.1683 - val_accuracy: 0.8836 - val_loss: 0.3620\n", + "Epoch 28/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9410 - loss: 0.1630 - val_accuracy: 0.8830 - val_loss: 0.3677\n", + "Epoch 29/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9425 - loss: 0.1580 - val_accuracy: 0.8828 - val_loss: 0.3725\n", + "Epoch 30/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9439 - loss: 0.1531 - val_accuracy: 0.8850 - val_loss: 0.3794\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_5 = tf.keras.Sequential(\n", + " [\n", + " tf.keras.layers.Input(shape=[28, 28]),\n", + " tf.keras.layers.Flatten(),\n", + " tf.keras.layers.Dense(300, activation=\"relu\", kernel_initializer=\"he_normal\"),\n", + " tf.keras.layers.Dense(100, activation=\"relu\", kernel_initializer=\"he_normal\"),\n", + " tf.keras.layers.Dense(10, activation=\"softmax\"),\n", + " ]\n", + ")\n", + "model_5.compile(\n", + " loss=\"sparse_categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"]\n", + ")\n", + "\n", + "X_train_far_too_small, X_val_far_too_small = X_train / 25500.0, X_val / 25500.0\n", + "\n", + "model_5.fit(\n", + " X_train_far_too_small,\n", + " y_train,\n", + " epochs=30,\n", + " validation_data=(X_val_far_too_small, y_val),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "kH6PsYnL9Tmz", + "metadata": { + "id": "kH6PsYnL9Tmz" + }, + "source": [ + "**Optional 4** : try using the sigmoid activation for the hidden layers instead of the ReLU. First train the model on normalized data then on un-normalized data." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "dShxjtDny8HD", + "metadata": { + "id": "dShxjtDny8HD" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7407 - loss: 0.7888 - val_accuracy: 0.8360 - val_loss: 0.4605\n", + "Epoch 2/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8553 - loss: 0.3999 - val_accuracy: 0.8386 - val_loss: 0.4300\n", + "Epoch 3/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8715 - loss: 0.3539 - val_accuracy: 0.8498 - val_loss: 0.4042\n", + "Epoch 4/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8813 - loss: 0.3239 - val_accuracy: 0.8580 - val_loss: 0.3892\n", + "Epoch 5/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8894 - loss: 0.3013 - val_accuracy: 0.8626 - val_loss: 0.3787\n", + "Epoch 6/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.8959 - loss: 0.2828 - val_accuracy: 0.8678 - val_loss: 0.3787\n", + "Epoch 7/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9021 - loss: 0.2669 - val_accuracy: 0.8678 - val_loss: 0.3790\n", + "Epoch 8/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9069 - loss: 0.2533 - val_accuracy: 0.8710 - val_loss: 0.3780\n", + "Epoch 9/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9120 - loss: 0.2399 - val_accuracy: 0.8704 - val_loss: 0.3782\n", + "Epoch 10/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9176 - loss: 0.2273 - val_accuracy: 0.8710 - val_loss: 0.3808\n", + "Epoch 11/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9214 - loss: 0.2158 - val_accuracy: 0.8726 - val_loss: 0.3805\n", + "Epoch 12/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9257 - loss: 0.2049 - val_accuracy: 0.8694 - val_loss: 0.3859\n", + "Epoch 13/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9304 - loss: 0.1945 - val_accuracy: 0.8720 - val_loss: 0.3934\n", + "Epoch 14/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9336 - loss: 0.1846 - val_accuracy: 0.8716 - val_loss: 0.4023\n", + "Epoch 15/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9372 - loss: 0.1754 - val_accuracy: 0.8676 - val_loss: 0.4147\n", + "Epoch 16/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9404 - loss: 0.1666 - val_accuracy: 0.8676 - val_loss: 0.4186\n", + "Epoch 17/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9441 - loss: 0.1582 - val_accuracy: 0.8696 - val_loss: 0.4338\n", + "Epoch 18/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9460 - loss: 0.1509 - val_accuracy: 0.8670 - val_loss: 0.4443\n", + "Epoch 19/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9500 - loss: 0.1429 - val_accuracy: 0.8706 - val_loss: 0.4454\n", + "Epoch 20/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9526 - loss: 0.1362 - val_accuracy: 0.8686 - val_loss: 0.4618\n", + "Epoch 21/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9554 - loss: 0.1292 - val_accuracy: 0.8656 - val_loss: 0.4863\n", + "Epoch 22/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9577 - loss: 0.1220 - val_accuracy: 0.8662 - val_loss: 0.4932\n", + "Epoch 23/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 2ms/step - accuracy: 0.9597 - loss: 0.1170 - val_accuracy: 0.8658 - val_loss: 0.5143\n", + "Epoch 24/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9599 - loss: 0.1135 - val_accuracy: 0.8648 - val_loss: 0.5415\n", + "Epoch 25/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9629 - loss: 0.1068 - val_accuracy: 0.8620 - val_loss: 0.5629\n", + "Epoch 26/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9644 - loss: 0.1021 - val_accuracy: 0.8590 - val_loss: 0.6076\n", + "Epoch 27/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9667 - loss: 0.0971 - val_accuracy: 0.8640 - val_loss: 0.6027\n", + "Epoch 28/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9673 - loss: 0.0953 - val_accuracy: 0.8594 - val_loss: 0.6309\n", + "Epoch 29/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9688 - loss: 0.0910 - val_accuracy: 0.8630 - val_loss: 0.6526\n", + "Epoch 30/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9710 - loss: 0.0864 - val_accuracy: 0.8640 - val_loss: 0.6396\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# sigmoid activation, normalized data (scale : [0,1])\n", + "model_sig_norm = tf.keras.Sequential(\n", + " [\n", + " tf.keras.layers.Input(shape=[28, 28]),\n", + " tf.keras.layers.Flatten(),\n", + " tf.keras.layers.Dense(\n", + " 300, activation=\"sigmoid\", kernel_initializer=\"he_normal\"\n", + " ),\n", + " tf.keras.layers.Dense(\n", + " 100, activation=\"sigmoid\", kernel_initializer=\"he_normal\"\n", + " ),\n", + " tf.keras.layers.Dense(10, activation=\"softmax\"),\n", + " ]\n", + ")\n", + "model_sig_norm.compile(\n", + " loss=\"sparse_categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"]\n", + ")\n", + "model_sig_norm.fit(X_train01, y_train, epochs=30, validation_data=(X_val, y_val))" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "1O32YLVuy8k3", + "metadata": { + "id": "1O32YLVuy8k3" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.6551 - loss: 1.0137 - val_accuracy: 0.6920 - val_loss: 0.7548\n", + "Epoch 2/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7053 - loss: 0.7489 - val_accuracy: 0.7290 - val_loss: 0.7050\n", + "Epoch 3/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7162 - loss: 0.7261 - val_accuracy: 0.7220 - val_loss: 0.7043\n", + "Epoch 4/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7244 - loss: 0.6950 - val_accuracy: 0.7410 - val_loss: 0.6906\n", + "Epoch 5/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7329 - loss: 0.6854 - val_accuracy: 0.7522 - val_loss: 0.6677\n", + "Epoch 6/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7434 - loss: 0.6751 - val_accuracy: 0.7538 - val_loss: 0.6704\n", + "Epoch 7/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7419 - loss: 0.6836 - val_accuracy: 0.7470 - val_loss: 0.6619\n", + "Epoch 8/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7357 - loss: 0.6719 - val_accuracy: 0.7456 - val_loss: 0.6474\n", + "Epoch 9/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7386 - loss: 0.6690 - val_accuracy: 0.7386 - val_loss: 0.6632\n", + "Epoch 10/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7397 - loss: 0.6665 - val_accuracy: 0.7442 - val_loss: 0.6630\n", + "Epoch 11/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7473 - loss: 0.6595 - val_accuracy: 0.7466 - val_loss: 0.6551\n", + "Epoch 12/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7376 - loss: 0.6605 - val_accuracy: 0.7662 - val_loss: 0.6222\n", + "Epoch 13/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7563 - loss: 0.6315 - val_accuracy: 0.7732 - val_loss: 0.5941\n", + "Epoch 14/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7706 - loss: 0.6042 - val_accuracy: 0.7624 - val_loss: 0.6283\n", + "Epoch 15/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7615 - loss: 0.6226 - val_accuracy: 0.7598 - val_loss: 0.6130\n", + "Epoch 16/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - 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accuracy: 0.7882 - loss: 0.5590 - val_accuracy: 0.7988 - val_loss: 0.5464\n", + "Epoch 27/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7866 - loss: 0.5598 - val_accuracy: 0.7764 - val_loss: 0.5784\n", + "Epoch 28/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7838 - loss: 0.5673 - val_accuracy: 0.7848 - val_loss: 0.5651\n", + "Epoch 29/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7886 - loss: 0.5563 - val_accuracy: 0.8008 - val_loss: 0.5436\n", + "Epoch 30/30\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.7971 - loss: 0.5387 - val_accuracy: 0.8010 - val_loss: 0.5349\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_sig_un_norm = tf.keras.Sequential(\n", + " [\n", + " tf.keras.layers.Input(shape=[28, 28]),\n", + " tf.keras.layers.Flatten(),\n", + " tf.keras.layers.Dense(\n", + " 300, activation=\"sigmoid\", kernel_initializer=\"he_normal\"\n", + " ),\n", + " tf.keras.layers.Dense(\n", + " 100, activation=\"sigmoid\", kernel_initializer=\"he_normal\"\n", + " ),\n", + " tf.keras.layers.Dense(10, activation=\"softmax\"),\n", + " ]\n", + ")\n", + "model_sig_un_norm.compile(\n", + " loss=\"sparse_categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"]\n", + ")\n", + "model_sig_un_norm.fit(X_train, y_train, epochs=30, validation_data=(X_val, y_val))" + ] + }, + { + "cell_type": "markdown", + "id": "z9Tmg3PRUXCe", + "metadata": { + "id": "z9Tmg3PRUXCe" + }, + "source": [ + "**Optional 5** Use the ReLU again and try initializing the weights with normally distributed and independent weigths but with a high variance." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "p5nkk6t8zIzz", + "metadata": { + "id": "p5nkk6t8zIzz" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - 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accuracy: 0.9142 - loss: 0.2433 - val_accuracy: 0.8356 - val_loss: 1.3211\n", + "Epoch 47/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9157 - loss: 0.2344 - val_accuracy: 0.8372 - val_loss: 1.2488\n", + "Epoch 48/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9160 - loss: 0.2348 - val_accuracy: 0.8420 - val_loss: 1.2971\n", + "Epoch 49/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9162 - loss: 0.2360 - val_accuracy: 0.8468 - val_loss: 1.2902\n", + "Epoch 50/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9179 - loss: 0.2328 - val_accuracy: 0.8336 - val_loss: 1.2355\n", + "Epoch 51/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9202 - loss: 0.2245 - val_accuracy: 0.8302 - val_loss: 1.4387\n", + "Epoch 52/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9182 - loss: 0.2329 - val_accuracy: 0.8346 - val_loss: 1.3602\n", + "Epoch 53/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9196 - loss: 0.2244 - val_accuracy: 0.8370 - val_loss: 1.2779\n", + "Epoch 54/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9206 - loss: 0.2242 - val_accuracy: 0.8444 - val_loss: 1.3331\n", + "Epoch 55/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9234 - loss: 0.2143 - val_accuracy: 0.8542 - val_loss: 1.2873\n", + "Epoch 56/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9205 - loss: 0.2204 - val_accuracy: 0.8406 - val_loss: 1.3728\n", + "Epoch 57/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9207 - loss: 0.2259 - val_accuracy: 0.8414 - val_loss: 1.3721\n", + "Epoch 58/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9237 - loss: 0.2151 - val_accuracy: 0.8474 - val_loss: 1.3719\n", + "Epoch 59/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9228 - loss: 0.2189 - val_accuracy: 0.8414 - val_loss: 1.3527\n", + "Epoch 60/60\n", + "\u001b[1m1719/1719\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 2ms/step - accuracy: 0.9254 - loss: 0.2101 - val_accuracy: 0.8394 - val_loss: 1.4407\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model_high_variance = tf.keras.Sequential(\n", + " [\n", + " tf.keras.layers.Input(shape=[28, 28]),\n", + " tf.keras.layers.Flatten(),\n", + " tf.keras.layers.Dense(300, activation=\"relu\"),\n", + " tf.keras.layers.Dense(100, activation=\"relu\"),\n", + " tf.keras.layers.Dense(10, activation=\"softmax\"),\n", + " ]\n", + ")\n", + "model_high_variance.layers[1].set_weights(\n", + " [200 * np.random.randn(28 * 28, 300) / 100, np.zeros(300)]\n", + ")\n", + "model_high_variance.layers[2].set_weights(\n", + " [200 * np.random.randn(300, 100) / 100, np.zeros(100)]\n", + ")\n", + "\n", + "model_high_variance.compile(\n", + " loss=\"sparse_categorical_crossentropy\", optimizer=\"adam\", metrics=[\"accuracy\"]\n", + ")\n", + "\n", + "model_high_variance.fit(X_train01, y_train, epochs=60, validation_data=(X_val01, y_val))" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "gpuType": "T4", + "provenance": [] + }, + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 } diff --git a/M1/Statistical Learning/TP7_Kmeans.ipynb b/M1/Statistical Learning/TP7_Kmeans.ipynb index 0dee34c..a263e2f 100644 --- a/M1/Statistical Learning/TP7_Kmeans.ipynb +++ b/M1/Statistical Learning/TP7_Kmeans.ipynb @@ -46,23 +46,23 @@ "\n", "\n", "np.random.seed(12)\n", - "num_observations=400\n", + "num_observations = 400\n", "\n", - "center1=[0,0]\n", - "center2=[1,4]\n", - "center3=[-3,2]\n", + "center1 = [0, 0]\n", + "center2 = [1, 4]\n", + "center3 = [-3, 2]\n", "\n", - "x1=np.random.multivariate_normal(center1,[[1,0],[0,1]], num_observations)\n", - "x2=np.random.multivariate_normal(center2,[[1,0],[0,1]], num_observations)\n", - "x3=np.random.multivariate_normal(center3,[[1,0],[0,1]], num_observations)\n", + "x1 = np.random.multivariate_normal(center1, [[1, 0], [0, 1]], num_observations)\n", + "x2 = np.random.multivariate_normal(center2, [[1, 0], [0, 1]], num_observations)\n", + "x3 = np.random.multivariate_normal(center3, [[1, 0], [0, 1]], num_observations)\n", "\n", - "X= np.vstack((x1, x2, x3)).astype(np.float32)\n", + "X = np.vstack((x1, x2, x3)).astype(np.float32)\n", "\n", - "plt.figure(figsize=(8,6))\n", - "plt.plot(X[:,0], X[:,1],\".b\",alpha=0.2)\n", - "plt.plot(center1[0], center1[1], '.', color='red', markersize=10)\n", - "plt.plot(center2[0], center2[1], '.', color='red', markersize=10)\n", - "plt.plot(center3[0], center3[1], '.', color='red', markersize=10)\n", + "plt.figure(figsize=(8, 6))\n", + "plt.plot(X[:, 0], X[:, 1], \".b\", alpha=0.2)\n", + "plt.plot(center1[0], center1[1], \".\", color=\"red\", markersize=10)\n", + "plt.plot(center2[0], center2[1], \".\", color=\"red\", markersize=10)\n", + "plt.plot(center3[0], center3[1], \".\", color=\"red\", markersize=10)\n", "plt.show()" ] }, @@ -540,10 +540,12 @@ } ], "source": [ - "plt.figure(figsize=(8,6))\n", - "plt.plot(X[:,0], X[:,1],\".b\",alpha=0.2)\n", + "plt.figure(figsize=(8, 6))\n", + "plt.plot(X[:, 0], X[:, 1], \".b\", alpha=0.2)\n", "for center in kmeans1.cluster_centers_:\n", - " plt.plot(center[0], center[1], '.', color='red', markersize=10, label='Cluster center')\n", + " plt.plot(\n", + " center[0], center[1], \".\", color=\"red\", markersize=10, label=\"Cluster center\"\n", + " )\n", "plt.legend()\n", "plt.show()" ] @@ -585,11 +587,11 @@ "# Hint: An example for plotting the Voronoi partition\n", "from scipy.spatial import Voronoi, voronoi_plot_2d\n", "\n", - "points_generer_voronoi = np.array([[0,0],[1,4],[-3,2]])\n", + "points_generer_voronoi = np.array([[0, 0], [1, 4], [-3, 2]])\n", "\n", "vor = Voronoi(points_generer_voronoi)\n", "\n", - "fig, ax = plt.subplots(1,1,figsize=(4,4)) \n", + "fig, ax = plt.subplots(1, 1, figsize=(4, 4))\n", "\n", "fig = voronoi_plot_2d(vor, ax=ax, show_vertices=False)" ] @@ -614,14 +616,16 @@ "# Answer for Exercise 3\n", "\n", "\n", - "fig, ax = plt.subplots(1,1,figsize=(8,6)) \n", - "plt.plot(X[:,0], X[:,1], \".b\", alpha=0.2)\n", + "fig, ax = plt.subplots(1, 1, figsize=(8, 6))\n", + "plt.plot(X[:, 0], X[:, 1], \".b\", alpha=0.2)\n", "\n", "vor = Voronoi(kmeans1.cluster_centers_)\n", "fig = voronoi_plot_2d(vor, ax=ax, show_vertices=False)\n", "\n", "for center in kmeans1.cluster_centers_:\n", - " plt.plot(center[0], center[1], '.', color='red', markersize=10, label='Cluster center')\n", + " plt.plot(\n", + " center[0], center[1], \".\", color=\"red\", markersize=10, label=\"Cluster center\"\n", + " )\n", "plt.legend()\n", "plt.show()" ] @@ -1233,10 +1237,10 @@ } ], "source": [ - "print (\"1:\", compress_model.labels_)\n", - "print (\"2:\", compress_model.labels_.shape)\n", - "print (\"3:\", compress_model.cluster_centers_)\n", - "print (\"4:\", compress_model.cluster_centers_.shape)" + "print(\"1:\", compress_model.labels_)\n", + "print(\"2:\", compress_model.labels_.shape)\n", + "print(\"3:\", compress_model.cluster_centers_)\n", + "print(\"4:\", compress_model.cluster_centers_.shape)" ] }, { @@ -1275,13 +1279,13 @@ "metadata": {}, "outputs": [], "source": [ - "color_new=np.zeros_like(colors)\n", + "color_new = np.zeros_like(colors)\n", "\n", - "labels=compress_model.labels_\n", - "centers=compress_model.cluster_centers_\n", + "labels = compress_model.labels_\n", + "centers = compress_model.cluster_centers_\n", "\n", "for i in range(len(colors)):\n", - " color_new[i]= centers[labels[i]]" + " color_new[i] = centers[labels[i]]" ] }, { @@ -1336,11 +1340,12 @@ ], "source": [ "import matplotlib.image as mpimg\n", + "\n", "mpimg.imsave(\"assets/zelda_new.png\", zelda_new)\n", "\n", "plt.figure(figsize=(8, 6))\n", "plt.imshow(zelda_new)\n", - "plt.show()\n" + "plt.show()" ] }, { @@ -1363,13 +1368,13 @@ "source": [ "import os\n", "\n", - "size_new=os.path.getsize('assets/zelda_new.png')\n", - "size_old=os.path.getsize('assets/zelda.png')\n", + "size_new = os.path.getsize(\"assets/zelda_new.png\")\n", + "size_old = os.path.getsize(\"assets/zelda.png\")\n", "\n", - "print (\"The original size is \", size_old, \"bytes.\")\n", - "print (\"The compressed size is \", size_new, \"bytes.\")\n", + "print(\"The original size is \", size_old, \"bytes.\")\n", + "print(\"The compressed size is \", size_new, \"bytes.\")\n", "\n", - "print (f\"The compression factor is {size_old/size_new : .3f}\")" + "print(f\"The compression factor is {size_old / size_new: .3f}\")" ] }, { @@ -1407,8 +1412,8 @@ } ], "source": [ - "partiel=plt.imread(\"assets/partiel.png\")\n", - "plt.figure(figsize = (20,10))\n", + "partiel = plt.imread(\"assets/partiel.png\")\n", + "plt.figure(figsize=(20, 10))\n", "plt.imshow(partiel)" ] }, @@ -1426,7 +1431,7 @@ } ], "source": [ - "print (partiel.shape)" + "print(partiel.shape)" ] }, { @@ -1472,23 +1477,23 @@ } ], "source": [ - "partiel_new=np.zeros_like(partiel)\n", + "partiel_new = np.zeros_like(partiel)\n", "\n", - "noir_rgb=np.array([0,0,0])\n", - "blanc_rgb=np.array([1,1,1])\n", + "noir_rgb = np.array([0, 0, 0])\n", + "blanc_rgb = np.array([1, 1, 1])\n", + "\n", + "epsilon = 0.5 # threshold\n", "\n", - "epsilon=0.5 # threshold\n", - " \n", "distances = np.linalg.norm(partiel - noir_rgb, axis=2)\n", "partiel_new = np.zeros_like(partiel)\n", "partiel_new[distances <= epsilon] = noir_rgb\n", "partiel_new[distances > epsilon] = blanc_rgb\n", - " \n", + "\n", "mpimg.imsave(\"assets/partiel_new.png\", partiel_new)\n", "\n", - "plt.figure(figsize=(20,10))\n", + "plt.figure(figsize=(20, 10))\n", "plt.imshow(partiel_new)\n", - "plt.show()\n" + "plt.show()" ] }, { @@ -1531,16 +1536,20 @@ "mnist = tf.keras.datasets.mnist\n", "(X_train, y_train), (X_test, y_test) = mnist.load_data()\n", "\n", - "X_train = X_train.reshape(-1, 28*28)\n", + "X_train = X_train.reshape(-1, 28 * 28)\n", "\n", "kmeans2 = KMeans(n_clusters=10)\n", "clusters = kmeans2.fit_predict(X_train)\n", "\n", + "\n", "def map_clusters_to_labels(clusters, true_labels):\n", - " return np.array([mode(true_labels[clusters == i], keepdims=True).mode[0] for i in range(10)])\n", + " return np.array(\n", + " [mode(true_labels[clusters == i], keepdims=True).mode[0] for i in range(10)]\n", + " )\n", + "\n", "\n", "cluster_to_label = map_clusters_to_labels(clusters, y_train)\n", - "print(\"Cluster to label mapping:\", cluster_to_label)\n" + "print(\"Cluster to label mapping:\", cluster_to_label)" ] }, { diff --git a/M1/Statistical Learning/neural_network.ipynb b/M1/Statistical Learning/neural_network.ipynb index e4cd942..43fe91b 100644 --- a/M1/Statistical Learning/neural_network.ipynb +++ b/M1/Statistical Learning/neural_network.ipynb @@ -6,7 +6,7 @@ "metadata": {}, "outputs": [], "source": [ - "import numpy as np \n", + "import numpy as np\n", "import pandas as pd\n", "import tensorflow as tf\n", "import matplotlib.pyplot as plt" @@ -178,16 +178,21 @@ "outputs": [], "source": [ "def build_model():\n", - " model = tf.keras.models.Sequential([\n", - " tf.keras.layers.Dense(16, activation='relu', input_shape=(X.shape[1],), kernel_regularizer=tf.keras.regularizers.l2(0.01)),\n", - " tf.keras.layers.Dense(8, activation='relu', kernel_regularizer=tf.keras.regularizers.l2(0.01)),\n", - " tf.keras.layers.Dense(1, activation='sigmoid')\n", - " ])\n", - " model.compile(\n", - " optimizer='adam',\n", - " loss='binary_crossentropy',\n", - " metrics=['accuracy']\n", + " model = tf.keras.models.Sequential(\n", + " [\n", + " tf.keras.layers.Dense(\n", + " 16,\n", + " activation=\"relu\",\n", + " input_shape=(X.shape[1],),\n", + " kernel_regularizer=tf.keras.regularizers.l2(0.01),\n", + " ),\n", + " tf.keras.layers.Dense(\n", + " 8, activation=\"relu\", kernel_regularizer=tf.keras.regularizers.l2(0.01)\n", + " ),\n", + " tf.keras.layers.Dense(1, activation=\"sigmoid\"),\n", + " ]\n", " )\n", + " model.compile(optimizer=\"adam\", loss=\"binary_crossentropy\", metrics=[\"accuracy\"])\n", " return model" ] }, @@ -291,10 +296,7 @@ "histories = []\n", "\n", "early_stopping = EarlyStopping(\n", - " monitor='val_loss',\n", - " patience=10,\n", - " restore_best_weights=True,\n", - " verbose=1\n", + " monitor=\"val_loss\", patience=10, restore_best_weights=True, verbose=1\n", ")\n", "\n", "for fold, (train_idx, val_idx) in enumerate(skf.split(X, y), 1):\n", @@ -305,29 +307,28 @@ " scaler = StandardScaler()\n", " X_train_scaled = scaler.fit_transform(X_train)\n", " X_val_scaled = scaler.transform(X_val)\n", - " \n", + "\n", " model = build_model()\n", "\n", - " model.compile(\n", - " optimizer='adam',\n", - " loss='binary_crossentropy',\n", - " metrics=[\"f1_score\"]\n", - " )\n", + " model.compile(optimizer=\"adam\", loss=\"binary_crossentropy\", metrics=[\"f1_score\"])\n", "\n", " # EarlyStopping\n", - " callback = tf.keras.callbacks.EarlyStopping(monitor='val_loss', patience=10, restore_best_weights=True)\n", + " callback = tf.keras.callbacks.EarlyStopping(\n", + " monitor=\"val_loss\", patience=10, restore_best_weights=True\n", + " )\n", "\n", " # Entraînement\n", " history = model.fit(\n", - " X_train_scaled, y_train,\n", + " X_train_scaled,\n", + " y_train,\n", " epochs=50,\n", " batch_size=8,\n", " validation_data=(X_val_scaled, y_val),\n", " callbacks=[callback],\n", " verbose=0,\n", - " class_weight={0: 1.0, 1: 2.0}\n", + " class_weight={0: 1.0, 1: 2.0},\n", " )\n", - " \n", + "\n", " histories.append(history.history)\n", "\n", " # Prédiction & F1\n", @@ -360,9 +361,9 @@ "axes = axes.flatten() # Flatten to easily iterate\n", "\n", "for i, (hist, ax) in enumerate(zip(histories, axes)):\n", - " ax.plot(hist['loss'], label='Train loss', alpha=0.6)\n", - " ax.plot(hist['val_loss'], label='Val loss', linestyle='--', alpha=0.6)\n", - " ax.set_title(f\"Fold {i+1}\")\n", + " ax.plot(hist[\"loss\"], label=\"Train loss\", alpha=0.6)\n", + " ax.plot(hist[\"val_loss\"], label=\"Val loss\", linestyle=\"--\", alpha=0.6)\n", + " ax.set_title(f\"Fold {i + 1}\")\n", " ax.set_xlabel(\"Epochs\")\n", " if i % 2 == 0:\n", " ax.set_ylabel(\"Binary Crossentropy\")\n", @@ -436,7 +437,9 @@ "import tensorflow as tf\n", "import numpy as np\n", "\n", - "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42, stratify=y)\n", + "X_train, X_test, y_train, y_test = train_test_split(\n", + " X, y, test_size=0.2, random_state=42, stratify=y\n", + ")\n", "\n", "scaler = StandardScaler()\n", "X_train_scaled = scaler.fit_transform(X_train)\n", @@ -444,21 +447,21 @@ "\n", "model = build_model()\n", "\n", - "model.compile(\n", - " optimizer='adam',\n", - " loss='binary_crossentropy'\n", + "model.compile(optimizer=\"adam\", loss=\"binary_crossentropy\")\n", + "\n", + "callback = tf.keras.callbacks.EarlyStopping(\n", + " monitor=\"val_loss\", patience=10, restore_best_weights=True\n", ")\n", "\n", - "callback = tf.keras.callbacks.EarlyStopping(monitor='val_loss', patience=10, restore_best_weights=True)\n", - "\n", "history = model.fit(\n", - " X_train_scaled, y_train,\n", + " X_train_scaled,\n", + " y_train,\n", " epochs=50,\n", " batch_size=8,\n", " validation_split=0.2,\n", " callbacks=[callback],\n", " verbose=0,\n", - " class_weight={0: 1.0, 1: 2.0}\n", + " class_weight={0: 1.0, 1: 2.0},\n", ")\n", "\n", "\n", @@ -486,11 +489,11 @@ ], "source": [ "plt.figure(figsize=(8, 5))\n", - "plt.plot(history.history['loss'], label='Loss (train)')\n", - "plt.plot(history.history['val_loss'], label='Loss (val)', linestyle='--')\n", - "plt.xlabel('Epochs')\n", - "plt.ylabel('Binary Cross-Entropy Loss')\n", - "plt.title('Courbe d\\'apprentissage')\n", + "plt.plot(history.history[\"loss\"], label=\"Loss (train)\")\n", + "plt.plot(history.history[\"val_loss\"], label=\"Loss (val)\", linestyle=\"--\")\n", + "plt.xlabel(\"Epochs\")\n", + "plt.ylabel(\"Binary Cross-Entropy Loss\")\n", + "plt.title(\"Courbe d'apprentissage\")\n", "plt.legend()\n", "plt.grid(True)\n", "plt.tight_layout()\n", diff --git a/pyproject.toml b/pyproject.toml index f0d07e4..ad3f2cc 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -11,7 +11,6 @@ dependencies = [ "opencv-python>=4.11.0.86", "pandas>=2.2.3", "scikit-learn>=1.6.1", - "tensorflow==2.19.0", ] [dependency-groups] @@ -19,3 +18,55 @@ dev = [ "ipykernel>=6.29.5", "uv>=0.6.16", ] + +[tool.ruff.lint] +# Activer les règles de linting courantes +select = [ + "E", # pycodestyle errors + "W", # pycodestyle warnings + "F", # Pyflakes + "I", # isort + "B", # flake8-bugbear + "C4", # flake8-comprehensions + "UP", # pyupgrade +] + +# Désactiver certaines règles +ignore = [ + "E501", # line too long, géré par le formatter +] + +# Longueur de ligne +line-length = 88 + +# Exclure certains fichiers ou répertoires +exclude = [ + ".bzr", + ".direnv", + ".eggs", + ".git", + ".hg", + ".mypy_cache", + ".nox", + ".pants.d", + ".pytype", + ".ruff_cache", + ".svn", + ".tox", + ".venv", + "__pypackages__", + "_build", + "buck-out", + "build", + "dist", + "node_modules", + "venv", +] + +# Permettre à Ruff de corriger automatiquement certaines erreurs +fixable = ["ALL"] +unfixable = [] + +# Formatage des imports +[isort] +known-third-party = ["pydantic", "django"]