diff --git a/SolidState/GraphenePhonons.ipynb b/SolidState/GraphenePhonons.ipynb
index 20b2d110cd1b3bf95635d2bafcbc52f104c22325..cb92a20c14d1e9f10503d5ef60776cf575d90ced 100644
--- a/SolidState/GraphenePhonons.ipynb
+++ b/SolidState/GraphenePhonons.ipynb
@@ -6,14 +6,16 @@
    "source": [
     "# Fonones en Grafeno\n",
     "\n",
-    "En el presente notebook se presenta una implementación de la teoría de fonones mediante matriz dinámica en el grafeno. Se calculan las bandas de dispersión considerando primeros vecinos de una celda primitiva con dos átomos. La base de la teoría aquí presentada se encuentra en el libro de Kaxiras, E. (2019) Quantum Theory of Materials, capítulo 7."
+    "En el presente notebook se expone una implementación de la teoría de fonones mediante matriz dinámica en el grafeno. Se calculan las bandas de dispersión considerando primeros vecinos de una celda primitiva con dos átomos. La base de la teoría aquí presentada se encuentra en el libro de Kaxiras, E. (2019) Quantum Theory of Materials, capítulo 7.\n",
+    "\n",
+    "---"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Desarrollo analítico"
+    "## 1. Desarrollo analítico"
    ]
   },
   {
@@ -71,7 +73,7 @@
     "\\sum_{j\\beta} D_{i\\alpha,j\\beta}(\\mathbf{K}) u_{j\\beta}(\\mathbf{K}) = \\omega^2 u_{i\\alpha}(\\mathbf{K}),\n",
     "$$\n",
     "\n",
-    "donde $ u_{i\\alpha}(\\mathbf{K}) $ es la amplitud de desplazamiento del átomo $i$ en dirección $\\alpha$ y $ \\omega $ es la frecuencia de vibración."
+    "donde $ u_{i\\alpha}(\\mathbf{K}) $ es la amplitud de desplazamiento del átomo $i$ en dirección $\\alpha$, y $ \\omega $ es la frecuencia de vibración."
    ]
   },
   {
@@ -106,7 +108,7 @@
     "\\mathbf{b}_1 = \\frac{2\\pi}{\\sqrt{3}a} (\\hat{x} - \\sqrt{3} \\hat{y}), \\quad \\mathbf{b}_2 = \\frac{2\\pi}{\\sqrt{3}a} (\\hat{x} + \\sqrt{3} \\hat{y}),\n",
     "$$\n",
     "\n",
-    "el cual es también una red hexagonal de dos sitios, pero rotado $\\pi/2$, de modo que los puntos de alta simetría en la zona de Brillouin son:\n",
+    "los cuales describen también una red hexagonal de dos sitios, pero rotado $\\pi/2$, de modo que los puntos de alta simetría en la zona de Brillouin son:\n",
     "\n",
     "$$\n",
     "\\Gamma = \\vec{0}, \\quad M = \\frac{\\mathbf{b}_1+\\mathbf{b}_2}{2}, \\quad K = \\frac{|\\mathbf{b}_1+\\mathbf{b}_2|}{2} (\\hat{x} + \\frac{1}{\\sqrt{3}} \\hat{y}).\n",
@@ -125,27 +127,61 @@
     "\\hat{r}_{001,010} = \\frac{1}{2} (\\hat{x} + \\sqrt{3} \\hat{y}), \\quad \\hat{r}_{001,100} = \\frac{1}{2} (\\hat{x} - \\sqrt{3} \\hat{y}), \\quad \\hat{r}_{000,001} = \\hat{x}.\n",
     "$$\n",
     "\n",
-    "Con esto en mente podemos calcular la energía potencial $\\Delta U$, tomando las proyecciones y normas de los desplazamientos de los átomos vecinos. De esta forma, se obtiene una energía potencial:\n",
+    "Con esto en mente podemos calcular la energía potencial $\\Delta U$ tomando las proyecciones y normas de los desplazamientos de los átomos vecinos. De esta forma, se obtiene una energía potencial:\n",
     "\n",
     "\\begin{equation*}\n",
     "\\begin{split}\n",
-    "\\Delta U =& \\frac{1}{2} (c_r-c_t) \\; [(S_{000x}-S_{001x})^2 + \\frac{1}{4}(S_{000x}+\\sqrt{3}S_{000y}-S_{0\\bar{1}1x}-\\sqrt{3}S_{0\\bar{1}1y})^2 \\\\\n",
+    "\\Delta U =& \\frac{1}{2} (c_r-c_t) \\; \\Big[(S_{000x}-S_{001x})^2 + \\frac{1}{4}(S_{000x}+\\sqrt{3}S_{000y}-S_{0\\bar{1}1x}-\\sqrt{3}S_{0\\bar{1}1y})^2 \\\\\n",
     "+& \\frac{1}{4}(S_{000x}- \\sqrt{3}S_{000y}-S_{\\bar{1}01x}+\\sqrt{3}S_{\\bar{1}01y})^2 + \\frac{1}{4}(S_{001x}+\\sqrt{3}S_{001y}-S_{010x}-\\sqrt{3}S_{010y})^2\\\\\n",
-    "+& \\frac{1}{4}(S_{001x}-\\sqrt{3}S_{001y}-S_{100x}+\\sqrt{3}S_{100y})^2]\\\\\n",
-    "+& \\frac{1}{2} c_t \\; [(S_{000x}-S_{001x})^2 + (S_{000y}-S_{001y})^2 + (S_{000z}-S_{001z})^2 \\\\\n",
+    "+& \\frac{1}{4}(S_{001x}-\\sqrt{3}S_{001y}-S_{100x}+\\sqrt{3}S_{100y})^2 \\Big]\\\\\n",
+    "+& \\frac{1}{2} c_t \\; \\Big[(S_{000x}-S_{001x})^2 + (S_{000y}-S_{001y})^2 + (S_{000z}-S_{001z})^2 \\\\\n",
     "+& (S_{000x}-S_{\\bar{1}01x})^2 + (S_{000y}-S_{\\bar{1}01y})^2 + (S_{000z}-S_{\\bar{1}01z})^2 \\\\\n",
     "+& (S_{000x}-S_{0\\bar{1}1x})^2 + (S_{000y}-S_{0\\bar{1}1y})^2 + (S_{000z}-S_{0\\bar{1}1z})^2 \\\\\n",
     "+& (S_{001x}-S_{010x})^2 + (S_{001y}-S_{010y})^2 + (S_{001z}-S_{010z})^2 \\\\\n",
-    "+& (S_{001x}-S_{100x})^2 + (S_{001y}-S_{100y})^2 + (S_{001z}-S_{100z})^2].\n",
+    "+& (S_{001x}-S_{100x})^2 + (S_{001y}-S_{100y})^2 + (S_{001z}-S_{100z})^2\\Big].\n",
     "\\end{split}\n",
-    "\\end{equation*}"
+    "\\end{equation*}\n",
+    "\n",
+    "A partir de las segundas derivadas de la energía potencial y los vectores de la red podemos calcular la matriz dinámica $D(\\mathbf{K})$ para el grafeno, la cual se puede diagonalizar numéricamente para obtener las bandas de dispersión del material. La matriz resultante tiene la forma:\n",
+    "\n",
+    "$$\n",
+    "D_{i\\alpha,j\\beta}/m = \\begin{pmatrix}\n",
+    "\\frac{3}{2} (c_r + c_t) & 0 & 0 & D_{xx} & D_{xy} & 0 \\\\\n",
+    "0 & \\frac{3}{2} (c_r + c_t) & 0 & D_{xy} & D_{yy} & 0 \\\\\n",
+    "0 & 0 & 3c_t & 0 & 0 & D_{zz} \\\\\n",
+    "D_{xx}^* & D_{xy}^* & 0 & \\frac{3}{2} (c_r + c_t) & 0 & 0 \\\\\n",
+    "D_{xy}^* & D_{yy}^* & 0 & 0 & \\frac{3}{2} (c_r + c_t) & 0 \\\\\n",
+    "0 & 0 & D_{zz}^* & 0 & 0 & 3c_t\n",
+    "\\end{pmatrix},\n",
+    "$$\n",
+    "\n",
+    "donde tenemos las funciones:\n",
+    "\n",
+    "\\begin{align*}\n",
+    "D_{xx} &= -[c_r + 1/4(c_r+3c_t)(e^{i\\mathbf{K}\\cdot\\mathbf{a}_1} + e^{i\\mathbf{K}\\cdot\\mathbf{a}_2})], \\\\\n",
+    "D_{yy} &= -[c_t + 1/4(3c_r+c_t)(e^{i\\mathbf{K}\\cdot\\mathbf{a}_1} + e^{i\\mathbf{K}\\cdot\\mathbf{a}_2})], \\\\\n",
+    "D_{zz} &= -c_y(1+e^{i\\mathbf{K}\\cdot\\mathbf{a}_1} + e^{i\\mathbf{K}\\cdot\\mathbf{a}_2}), \\\\\n",
+    "D_{xy} &= \\frac{\\sqrt{3}}{4}(c_r - c_t)(e^{i\\mathbf{K}\\cdot\\mathbf{a}_1} - e^{i\\mathbf{K}\\cdot\\mathbf{a}_2}).\n",
+    "\\end{align*}\n",
+    "\n",
+    "### Implementación Numérica\n",
+    "\n",
+    "Ahora que hemos derivado la matriz dinámica para el grafeno, procedemos a implementarla numéricamente. Para ello, utilizaremos la librería `numpy` para determinar los valores propios de la matriz dinámica (`numpy.linalg.eigvalsh`) y `matplotlib` para graficar las bandas de dispersión. Los parámetros utilizados son los siguientes:\n",
+    "\n",
+    "$$\n",
+    "a = 2 \\times 10^{-10} \\, \\text{m}, \\quad c_1 = 4.5 \\times 10^{-17} \\, \\text{N/m}, \\quad c_2 = 12.5 \\times 10^{-17} \\, \\text{N/m}, \\quad c_3 = 2.25 \\times 10^{-17} \\, \\text{N/m}, \\quad m = 2 \\times 10^{-26} \\, \\text{kg},\n",
+    "$$\n",
+    "\n",
+    "donde $a$ es la constante de red (cuyo valor arbitrario no afecta el resultado), $c_1$ y $c_2$ son las constantes de resorte para las interacciones radial y tangencial, respectivamente, $c_3$ es la constante de resorte para la interacción tangencial en la dirección $z$, y $m$ es la masa atómica del carbono. Estos valores ajustan la forma de las bandas de dispersión del grafeno con las presentadas en el libro.\n",
+    "\n",
+    "---"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Desarrollo numérico"
+    "## 2. Desarrollo numérico"
    ]
   },
   {
@@ -162,7 +198,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -183,7 +219,7 @@
     "    # Inicializamos la matriz dinámica con ceros\n",
     "    dinamic = np.zeros((6,6), dtype=complex)\n",
     "\n",
-    "    # Matriz dinámica modelo 1 (descomposición en x y z)\n",
+    "    # Matriz dinámica modelo 1 (descomposición en x y z, aún en desarrollo)\n",
     "    # dinamic[0,0] = 3*c1/m\n",
     "    # dinamic[1,1] = 3*c2/m\n",
     "    # dinamic[2,2] = 3*c3/m\n",
@@ -197,7 +233,7 @@
     "    # dinamic[4,1] = -c2/m*(1+np.exp(1j*np.dot(K,a1))+np.exp(1j*np.dot(K,a2)))\n",
     "    # dinamic[5,2] = -c3/m*(1+np.exp(1j*np.dot(K,a1))+np.exp(1j*np.dot(K,a2)))\n",
     "\n",
-    "    # Matriz dinámica modelo 2 (descomposición en radial y tangencial)\n",
+    "    # Matriz dinámica modelo 2 (descomposición radial y tangencial)\n",
     "    dinamic[0,0] = 3*(c1+c2)/(2)\n",
     "    dinamic[0,3] = -(c1+1/4*(c1+3*c2)*(np.exp(1j*np.dot(K,a1))+np.exp(1j*np.dot(K,a2))))\n",
     "    dinamic[0,4] = np.sqrt(3)/(4)*(c1-c2)*(np.exp(1j*np.dot(K,a1))-np.exp(1j*np.dot(K,a2)))\n",
@@ -227,7 +263,7 @@
     "    # Calculamos la matriz dinámica\n",
     "    dinamic = D(Kx, Ky, Kz, params)\n",
     "    \n",
-    "    # Calculamos los valores propios de la matriz dinámica\n",
+    "    # Calculamos los valores propios de la matriz dinámica (las frecuencias)\n",
     "    squared = np.linalg.eigvalsh(dinamic)\n",
     "    \n",
     "    # Retornamos la raíz cuadrada de los valores propios\n",
@@ -236,7 +272,7 @@
     "# Definimos la función que calcula la dispersión en el camino Gamma-M-K-Gamma\n",
     "def dispersion(params, b1, b2):\n",
     "    '''\n",
-    "    Esta función calcula la dispersión en el camino Gamma-M-K-Gamma\n",
+    "    Esta función calcula la dispersión en el camino Γ-M-K-Γ\n",
     "    '''\n",
     "    # Definimos los puntos del camino\n",
     "    Gamma = np.array([0,0,0])\n",
@@ -251,12 +287,13 @@
     "    MK = np.array([np.linspace(M[i], K[i], n) for i in range(3)])\n",
     "    KG = np.array([np.linspace(K[i], Gamma[i], n) for i in range(3)])\n",
     "\n",
-    "    # Calculamos los valores propios en cada segmento\n",
+    "    # Calculamos los valores propios en cada segmento. Tomamos la parte real para evitar errores de datatype, pero\n",
+    "    # por ser una matriz hermítica, los valores propios deberían ser reales y positivos (de no ser así habrán NaNs)\n",
     "    GM_eigenvalues = np.array([np.real(eigenvalues(GM[0,i], GM[1,i], GM[2,i], params)) for i in range(n)]).T\n",
     "    MK_eigenvalues = np.array([np.real(eigenvalues(MK[0,i], MK[1,i], MK[2,i], params)) for i in range(n)]).T\n",
     "    KG_eigenvalues = np.array([np.real(eigenvalues(KG[0,i], KG[1,i], KG[2,i], params)) for i in range(n)]).T\n",
     "\n",
-    "    # Cambiamos los nan por ceros\n",
+    "    # Cambiamos los nan por ceros para hacer evidentes los valores propios negativos\n",
     "    GM_eigenvalues = np.nan_to_num(GM_eigenvalues)\n",
     "    MK_eigenvalues = np.nan_to_num(MK_eigenvalues)\n",
     "    KG_eigenvalues = np.nan_to_num(KG_eigenvalues)\n",
@@ -279,7 +316,7 @@
     "\n",
     "    # Graficamos la dispersión para cada uno de los 6 valores propios hallados en cada punto\n",
     "    shifting = 0.1\n",
-    "    colors = 6*['m']\n",
+    "    colors = 6*['m'] #Dar color a cada banda es complicado, por lo que se usará el mismo color para todas\n",
     "    for i in range(6):\n",
     "        plt.plot(np.linspace(0,1+shifting,100), GM[i]*1e-2, str(colors[i])+'.', markersize=2.5)\n",
     "        plt.plot(np.linspace(1+shifting,2-shifting,100), MK[i]*1e-2, str(colors[i])+'.', markersize=2.5)\n",
@@ -294,19 +331,19 @@
     "    plt.xlabel('Camino en el espacio recíproco', fontsize=14)\n",
     "    plt.yticks(np.arange(0, 1700, 200))\n",
     "    plt.ylabel('Frecuencia (cm$^{-1}$)', fontsize=14)\n",
-    "    plt.title('Dispersión en el camino $\\Gamma$-M-K-$\\Gamma$', fontsize=16)\n",
+    "    plt.title('Dispersión del grafeno en el camino $\\Gamma$-M-K-$\\Gamma$', fontsize=16)\n",
     "    plt.grid(alpha=0.5)\n",
     "    plt.show()\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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7t9ubVFlZGTp27Oj2WDabDYBzACWtWvTWW2+pfszYXMEcvyvpGKXjV/PTTz8B8B4cakE6lrKyMtX7HQ6H6kfkoX6dlaQ3d28ZtGDfqP/v//4PjY2NuPXWW/H//t//c7vfte2hP8L52ij3p+V4Cvdz0MuxSK/PuXPn/No+FONHL/RwndqxY4f8aUEgpk2bhg8//BDTpk1DQ0OD372TA91fly5d8PHHH2PEiBH47rvv8Mtf/hIfffSR2x8kwT4Pah7WKFPErVu3DqWlpYiPj8fYsWMD+tmWLVti3LhxePbZZ7F//35069YNJ06cwAcffOC2rfRxqKfbe/ToId8mfUzorceyFgI5flfS8e7du1f1/p9//ll+g1U+t1CQHl9aZc5VSUmJajYsXK8zcOEYv//+e9X7jx49GnQfXanf7LBhw1TvD6Q2WRLO1wYIzXgK93PwJpzH0rt3bwDAtm3b/No+FONHL/RwnTp8+DBEU/MCp3++3HDDDWjZsiWOHj0Kk8mEKVOmhGx/PXv2xEcffYTU1FQUFRXhuuuucyvDCfZ5UPMwUKaIOnLkCH7zm98AaJooddFFFwX9WMnJyejbty8A4OTJk273SwubKDU0NGDp0qUA4BSk33DDDQCaFkHxd7JQc/k6flfS8qp//etf3UoaAOCNN95AfX09OnXqhNzcXG0P1oX02v31r39Vfb3UXnsgvK/zVVddBQD4+9//rpo5lhb+CIa0qp6UGVPav38/1q9fH/BjhnsMhmI8ReI80sOxXH/99QCakgAHDx70uX0oxo9e6Ok6Fajk5GTMnTsXo0ePxvTp09GpU6eQ7u+yyy7DBx98gJYtW+KTTz7BLbfcElC5FoVImLprUAzy1qamrKxMvPTSS3JD/by8PFFRUeHxMZRtimbMmCHWrFkjqqurnbb9/PPP5UVEPv30U/l24EIf5RdffFFuQVRTUyNuv/12AUBkZ2e7Pd7EiRMF0NQA/ttvv3W67/z582LLli1i8uTJoq6uzuk++GgZFOjxe3odHA6HGDhwoAAgRo0a5bRQwocffihatmwpgKbFAVz5OsZAW2I5HA7Rr18/AZUexe+9955ISEjw2Ec52Nc5mD7Kl1xyiQAgxo8f79SKae3atSIxMdFnH2VP/vrXvwoAok2bNuK7776Tbz9w4IDo06ePSExMFEBT72xX3vooh2oMaj2evAnncwjFsQTbR/mGG24QQNNCMl9//bXTfcXFxeJ///d/5f8HO368vUaHDh2S266p2bJli8B/exu78tUezpNwjqtQt4fzRcsFR1x9+umn8u980qRJcu//5j4uBYeBMoWMdMIqVxwbMGCA6Ny5s3yBASBuueUWpwUq1B5DeeG99NJL5f6TvXr1EoMGDZK3AyCmTp3q9BjS7cqV+QYOHChat24tgKZV5D7//HO3ff/888/iqquukn/+4osvFoMHDxZ9+/YVSUlJ8u21tbWq+/Mk0OP39DoI0fSG27FjR7lP6eWXXy4vNABATJs2zevKfJ4EExzs3r1bXsQgKSlJDBgwQH4cbyvzBfs6B3OMypX5kpOTncbjzJkz5cc8evSo08/5er0aGxvFkCFDBNC0ilqvXr1Enz595NXLnn766aAC5VCNQa3Hkzfhfg5aH0uwgXJ5ebkYOnSo/JidO3cWAwYMEBkZGW4BbLDjJxoCZSFCM66MHCgLIcS//vUv+Q/3u+++2+/Xh4Gy9hgoU8gogz/pX8uWLUXHjh3FmDFjxGOPPSb27t3r12MoL7yffvqpeOihh8Tll18u0tLSREJCgujUqZMYN26c+Oc//+lxcQ0hhFi5cqUYOHCgSE5OFikpKWLChAleF/6w2+1i5cqVYty4caJ9+/YiPj5edOjQQQwePFg88sgjbpki1/2pCfT4Pb0OkrKyMjFv3jzRvXt3YbVaRevWrcWIESPEihUrPF5cQxGECCHEjz/+KCZPnizatWsnEhMTRd++fcWf//xn4XA4vD5mMK9zsMdYUlIibr31VqdjfOWVV4QQQv6Ew7Xxvz9viBUVFWLmzJkiKytLxMfHi44dO4p7771XnDx5UrzzzjtBBcpChGYMaj2efAn3c9DyWILdjxBCNDQ0iFdffVUMHz5cpKSkiMTERNGlSxdx8803i/Xr1zttG8z4iZZAWQjtx5XRA2UhhPi///s/YbFYBKC+MEywj0uBMQnBSnAytua0QaLYcebMGbRv3x6pqak4e/ZspA+HiIh0gJP5iIgAvPPOOwA8dx4gIqLYw0CZiGLGf/7zH7z55ptOvZSFECgoKMCCBQsANC2pS0REBAAsvSDDY+kFST777DNceeWVsFgs6NSpE9q1a4cff/xRbhc2ffp0LFmyJMJHSUREesFAmQyPgTJJbDYb/vSnP+Gjjz7CsWPHUFFRgdatW6Nfv3647777MGnSpEgfIhER6QgDZSIiIiIiFaxRJiIiIiJSERfpAzAah8OBkydPolWrVvJH/kRERESkH0II/Pzzz8jKyoLZ7DlvzEBZYydPnkR2dnakD4OIiIiIfDh27Bg6duzo8X4Gyhpr1aoVgKYXvnXr1iHfn91ux8GDB9GtWzdYLJaQ74/ICBobG7F06VKcPn0a8+bNQ2JiYqQPiQyA44ooOJGIZSorK5GdnS3HbZ5wMp/GKisrkZKSIs+mDzW73Y7i4mJ0796dgTKRn6qrq9GyZUsACNu5SsbHcUUUnEjEMv7Ga5zMR0RERESkgoEyEREREZEKBspERERERCoYKBMRERERqWCgTERERESkgoEyEREREZEK9lEmophjtVrxj3/8AydPnoTVao304ZBBcFwRGQ8DZSKKOXFxcfjVr36F4uJixMXxMkja4LgiMh6WXhARERERqWCgTEQxp7GxEcuXL8fatWvR2NgY6cMhg+C4IjIeLmGtMS5hTaR/XGqYQoHjiig4XMKaiIiIiCjKMFAmIiIiIlIRFYHyF198gWuvvRZZWVkwmUxYt26d2zb79u3DhAkTkJKSglatWmHIkCE4evSofH99fT1mzpyJ9u3bo0WLFpgwYQKOHz/u9Bhnz57FtGnTkJKSgpSUFEybNg3nzp0L8bMjIiIiIj2KikC5uroal156KV555RXV+w8ePIgrrrgCPXv2xGeffYZ///vfWLBgARITE+VtZs+ejbVr12LNmjX48ssvUVVVhfHjx8Nut8vbTJ48Gbt27cKmTZuwadMm7Nq1C9OmTQv58yMiIiIi/YmKRo/XXHMNrrnmGo/3P/bYY/jlL3+JxYsXy7d17dpV/r6iogJLly7FihUrMGbMGABAQUEBsrOz8fHHH2PcuHHYt28fNm3ahG3btmHw4MEAgLfeegtDhw7FgQMHkJubG6JnR0RERER6FBWBsjcOhwP/+te/8PDDD2PcuHH47rvv0KVLFzz66KO4/vrrAQA7d+5EY2Mjxo4dK/9cVlYW+vTpg6KiIowbNw5bt25FSkqKHCQDwJAhQ5CSkoKioiKPgXJ9fT3q6+vl/1dWVgJomsGpzFaHit1ux/ny87Db7Wgob0BC2wSPX+21dliSLPJXolilPDfDda6S8XFcEblzjT3UYhRLikWOZcJ2XH7uK+oDZZvNhqqqKjz77LN4+umn8dxzz2HTpk248cYbsWXLFowcORKlpaVISEhAmzZtnH42IyMDpaWlAIDS0lKkp6e7PX56erq8jZpFixZh4cKFbrcfPHhQbhMUSrYxNjhOOHDafBpwoKmYRu1rEoBawHyRGY4TDiRem4jWv28Nc2pT9Y3jnAPmVLP8VdQJmBJNbl+JjOD8+fN4/vnnUVVVhWPHjiEhISHSh0QGwHFFscBTfOAaRzjOOVD5x0rUbaiTYw8pFvEUq5RfVI70j91jsVCoqqrya7uoD5QdDgcA4LrrrsNvf/tbAMBll12GoqIiLFmyBCNHjvT4s0IImEwXgj/l9562cfXoo49izpw58v8rKyuRnZ2Nbt26hbyHZkN5A0pP/DeId8D719r//vdE0w116+tQt74O1s5WAED94XrAAsAOmFuY4ah2wNrZivrD9fLXtClp6PpCV9XsNLPVFG169OiBkpIS5OTksAc5aYbjiozA03v7/tv3o2xVmVt8IMUNUhwhf/0vKfaQYhFPsYrjhAOd2nVCQtvQ/5EpVQD4EvWBcvv27REXF4e8vDyn23v16oUvv/wSAJCZmYmGhgacPXvWKatss9kwbNgweZuffvrJ7fHLysqQkZHhcf9WqxVWq9XtdovFEvKLZFJakjxI3Qanh8Hqqv7whbIRaTtHtcPpPulr2coylK0s8xhIS1/Tp6Yj981cOWBmEE16ZTabw3KuUmzhuKJooRYQH7jvAGwrbe7JslvTULamDIB7fCDFDXK84auqwUOsYu1sRVJakrZP0tMh+Hl+Rn2gnJCQgIEDB+LAgQNOt//www/o1KkTAKB///6Ij4/H5s2bMXHiRADAqVOnsHv3bnkC4NChQ1FRUYGvv/4agwYNAgBs374dFRUVcjCtR4NKBuHAjgPIHZgLe4XdY41yyawSp4EvB7tdrIBwzij74imQlr7aCmywFdiQPjUdEHDarzKIZgBNkXL+/Hm8//77OHXqFLp06cKAhjTBcUV6FUhALHFLlv03SPbKJfB1TaylT01Hzks5qjXKUiyjN1GxhHVVVRVKSkoAAP369cPzzz+PK6+8Em3btsXFF1+MtWvXYtKkSXj11Vdx5ZVXYtOmTZg9ezY+++wzXHHFFQCAX//619iwYQOWLVuGtm3bYt68eThz5gx27twpX8yuueYanDx5Em+88QYA4P7770enTp2wfv16v49Vz0tYeyqoB+A1qHb7aMUTPwNtAF6z0AygKdS41DCFAscV6UUgAXEgpKyy2nu4WgDsbyMBPS9hHRWB8meffYYrr7zS7fY77rgDy5YtAwC8/fbbWLRoEY4fP47c3FwsXLgQ1113nbxtXV0d5s+fj1WrVqG2thajR4/Ga6+9huzsbHmb8vJyzJo1C//85z8BABMmTMArr7yC1NRUv49Vz4FyQI/roT5JLZD2xtrJivoj/merGUBTODCgoVDguKJIcH1v3Dt1r9/v0QB8vj8r34/zVuSFZG4SA+UYYpRA2ed+A6xncuX6cYwv/tZBE/mDAQ2FAscVhYO3919v77v+fjrsLVEVKnoOlKO+RpkiQzphLEkW5BXkIfct9azvXov6X7auJ6mniYESf+qgw3lSExERhYO3wFiirCP2VB4h8fT+6+09NJbfTxkokyaUgbPyq2sQLZ3kEtcAWJJyRQpyduZ4rJeW2ApsTt/bCrxPHCQiItKzQAJjiWt5RMOr/y2TPGzz+D7LwNg/DJQp5NSyz75OfmXGeNiZYW4TAqSfV2aUPT0GA2ciItKr5gbGOS/lyEExALlG2ZWn0kWAgbE3rFHWWKzUKGvBn4uDxNekPn8eQ8LAmVhLSqHAcUWBaO77lnJyvTfR8F7HGmUiFd7qnF1LNDxlh5WP5ekxfGWtGTjHnoSEBCxduhQ//fQTlxkmzXBckSeeEjsSbxljtSSRp6yxp3k7Er6vBY4ZZY0xo6wdtYuJK9d2NWqP4W/WWuKrFQ4Zg5HPHYocjitS8lUqKPEnYePtPTHaO0Exo0wUBH9qmm0FNojzAmVryrz+9Rxsxll6bGadiYjIF7XkjEQ5+Vziz4S6QAJk15+l5mNGWWPMKIeO2gVIrWdkIMFsc/tRerpIkb6dP38eGzduxMmTJ3HXXXfBarVG+pDIADiuYpe/c228lUV4e0y1xzLSe4+eM8oMlDXGQDl8XFchchVMMBvsCkfMNEcXTrqiUOC4ij3+lggGUhYRSwGyhIFyDGGgHBnBXKwCeWx/65xZohEdGNBQKHBcGZ+30gpJsJ84xmKALGGgHEMYKEdWoK3mgt2HrwulhCUa+sSAhkKB48q4gm1jGuhje3tMI2OgHEMYKOuDP8GsVhegQDpqMNOsDwxoKBQ4rown1J9WxnqALGGgHEMYKOtTuALmYEo02IIu/BjQUChwXEU3X72OJc39pJABsjs9B8psD0cxQa3VnES5XHZzLlCBLKDibws6IiIKLX97HTfnE0Ffk8953dcvZpQ1xoxydIjEX/SBtqBjmUboMPNHocBxFV38KasAmveeEEg701jGjDKRzvibYfa26l9z9unUgs6i3oLO2xLb1DwJCQl4+eWXYbPZuNQwaYbjKjr4SpQE0uvYG9fscdmaMjlY5vU8ejCjrDFmlKOTpwtnuC5qgXTSYKZZGzx3KBQ4rvQrnEtAN5Q3oKhdkds+tEy+GImeM8rmsBwNkc5J2d78mnykT0kHAKePyWwFNhQmF2LvtL0h27+n47B2dl7dSzqWrV22ysdkr7UDgPyViIia2Gvt2Dt1LwqTC92C5PSp6civyUfeijzV5aOD3VdRuyL52q3cR3MemyKDpRdECq7lEVJZhMRWYEPOSzlIaBvaj1UDnRDIEo3A2O12fPbZZzhx4gS6du3KzB9pguNKH8LZHlS5T7Vr9LAzw0L+fkGhxdILjbH0wnjUJuFFKhgNtGczW8+p46QrCgWOq8gKx4JTarx1spCyyOSdnksvmFEm8kHK7ua8nCPXnGnVUi7YY1HLNKtNBvTWeo6BMxEZgbdP3CShulY3lDeolnPwUz3jYKBM5KeEtglIn5Iekh7MgfKnZ7OyxpplGkRkNKFcFCSQffN6amwsvdAYSy+MLxpWVXJtbs+ltZ3xI3IKBY6r8PD3GhyKa5mnfbMWuXlYekFkIIH0YI7kMQIIqEzDU6Y5FgJnItK3YFa20/q65W3fDJKNixlljTGjHHuiLcMQSM9mowbOzPxRKHBcaU8vK9t56oush08QjUDPGWX2USZqJk+9j4vaFTn1ONaLQHo2K2ubXXs3Axf6NuvtORJRdFPrfSytbAd47n8cquPw1BeZQbLxsfSCSCN66o4RiEA6aSgD52juqBEfH49nn30Wp0+fRnx8fKQPhwyC46r5fNUf563Ig/3t0F9f2BeZJCy90BhLLwjwXsum14DZlVqJhhQUq30EKvEWOOspgOa5Q6HAcRUcPU2SZl/k8NNz6QUzykQhoPfJfv7w1oJOuWqht6yzcoJgNGaeiSi09BQgSyVk7ItMSswoa4wZZXIVbZP9AuEt6+xLJDPPdrsdO3bswLFjx3DdddchISG6fw+kDxxX/tNbgCwdS/rUdEBA/p4BcnjoOaPMQFljDJTJE08N6pXLTEc7b4GzrwBaLfOstgS3p6+BYHcCCgWOK8/86bYTicBUrcwivyYfgPbt5cgzPQfKLL0gChNPk/2kSXHRUI7hi69yDX8mCnqbMOjpq7estNpXJXutHWh94WNX5Ta+vucbKZF3/nzaFKnMraflp3lekxIDZaIwUy6FrZwUZyuwIeelnKgvx1BSBs7SV18dNtQmDLoG0WpBtVo9tKevLW9tKR/jtsxtSO2cKj+W8s3c1/dpt6ah9+reAQfZREbnqWuEUqQCZC4/TYFg6YXGWHpB/vK0zHQsXrA9ZX9dXxtPXwNVi1r8Er8EAGzERiQhKehjt3ayov6I/0G29PsFGEwbTayXXvhaPU8P1zi1YzPCfJFop+fSCwbKGmOgTMHgqk+e+VNK4Skr7S2jPHDNQABNgXKgGeWEixPQcLSh2c/NVzDNQDq6xGqgHMjqeZEsWfJ0nY32kjcjYKAcQxgoU7DYu7N5/J30Z6+1o85RJwc05aXlaJPRJuDyiT237XGqnwb8C7IDEUxWmiIn1gJlTxPzpGBZT3/s85M7fWOgHEMYKFNzGLmVnJ5oFdC4ThD053vl71frYJoBdGTFSqDs1+p5Oprs6ppJ5vVUf/QcKHMyH5GOKCe7KcsJitoVMQOiofj4eCxYsADl5eXNWmrYdbKiP99Lv1/pNm/BtD+BtPI2aVKj6/ZqATTHkfa0Gld6FUhrNz2ML0+T9hgkUyCYUdYYM8qkJdbUhY7ezx1v2WpPWWl/+OrYoYcAJ5rpfVwFQ2+9j/3BSXvRhRllIgqKspWcxIht5Midt2y1p6y0PwG0dFvZmjJs3brVrWOHWgBNsSkaA2TAc39kXjMpGMwoa4wZZQoF9v3UlsPhwO7du3HkyBFcffXVhvqY3FcG2p+OHcqWdyzb8J9RxlW0Bsi8TkYvPWeUGShrjIEyhRJLMbQRK5OulHx17PArgFbJOjN4viBax5Vel5cOBEstopueA2VzWI6mmb744gtce+21yMrKgslkwrp16zxuO336dJhMJrz44otOt9fX12PmzJlo3749WrRogQkTJuD48eNO25w9exbTpk1DSkoKUlJSMG3aNJw7d077J0QUJKkUQ8lWYENDefN7+pKxWZIscpDTe3Vv5NfkY+ihocivyUd+TT6GHRmGtFvTADQFxGqcyjY6b0VhciG2dmn6uue2PQCagi7XZcJJn+y1duydutfp96hWspBfk4+8FXm6DZJZakGhFBWBcnV1NS699FK88sorXrdbt24dtm/fjqysLLf7Zs+ejbVr12LNmjX48ssvUVVVhfHjx8Nuv3BBnzx5Mnbt2oVNmzZh06ZN2LVrF6ZNm6b58yFqjryCPOTX5MsBs9QVY++0vRE+MoomyhpobwG08g+zhIsvBB5SaYZa8FyYXIi90/Y6Bc0MnvVB+j1IAbIUYKotL633ABloeh5F7YrkP+6Ux02khagrvTCZTFi7di2uv/56p9tPnDiBwYMH48MPP8SvfvUrzJ49G7NnzwbQ9BFYWloaVqxYgUmTJgEATp48iezsbGzcuBHjxo3Dvn37kJeXh23btmHw4MEAgG3btmHo0KHYv38/cnNz/To+ll5QOLE/aHCi9SPySPFWthFsyYb0eEai53Hla/W8aKzp5fXPOPRcemGIrhcOhwPTpk3D/Pnz0bt3b7f7d+7cicbGRowdO1a+LSsrC3369EFRURHGjRuHrVu3IiUlRQ6SAWDIkCFISUlBUVGRx0C5vr4e9fUX/hKvrKwE0PRLV2arQ8Vut8PhcIRlX6Q/lhQL0ianoWxVmZxZTpuShu5LukfFG12kKM+XcJ2rUe2/sYfdbkfPgp7o/lZ3p9rkfVP24fR7p/3qtFG0tQgNR5oCa2msAsaYKKincaWsOy6eXoyyVRcC47I1ZWg/qT1Ov3fa6XqhfP31fk7sv32/fN2rP1yPtClpsKRYdH/cpC4SsYy/+zJEoPzcc88hLi4Os2bNUr2/tLQUCQkJaNOmjdPtGRkZKC0tlbdJT093+9n09HR5GzWLFi3CwoUL3W4/ePCgnFkIJYfDgfLycpSUlMBsjopKGtKYZYEF6TPTYRva9BFq2coylK0sQ+K1iUhdnBrZg9Opmpoa+ftwnatGFvdkHDJ+lwFTogmirulDyooFFajbUAcAMGWZIE423S4FycCFsQoA5ovMcJxwwPpLK9r8qY38OKZEUzifSrPoYVyJOiG/9tJr6irx2kSn39mPx38M+3E2h+OcQw786w/XI31rOsypZhQXF0f4yChYkYhlqqqq/Nou6gPlnTt34qWXXsK3334LkymwC6oQwuln1H7edRtXjz76KObMmSP/v7KyEtnZ2ejWrVvYSi9KSkqQk5PD0osYJyYLp6xR3fo6dF3VFYDxPuJururqavn7cJ2rMWedc8mGr6yzFNDVb6xH+Z7yqMw6R2JcecscuwbJ0fxpk/Q81TLJuQP9K40k/YpELCNVAPgS9YFyYWEhbDYbLr74Yvk2u92OuXPn4sUXX8Thw4eRmZmJhoYGnD171imrbLPZMGzYMABAZmYmfvrpJ7fHLysrQ0ZGhsf9W61WWK3uM8QtFkvYftlmszms+yN96r2yN+x/uVCHmD41HSUzSuTvo6XuMBwSExMxZ84cnDt3DomJiTx3QsTS8sLr2mdNH9jfcV5t0FN/Z09ZZ72vKhjOcaXWM9hVNNYdq5Favylrq+sP17Mm2WDCHcv4u5+on8x35swZnDp1ymmbcePGYdq0abjrrruQm5srT+YrKCjAxIkTAQCnTp1Cx44d3Sbzbd++HYMGDQIAbN++HUOGDOFkPoo6UgBRmFzodDt7Ll/Ac0cffPV39kS5KIqeJguGalz50+tYogyM9fAHRHO4TtiTgmVey4yFk/maqaqqCiUlJfL/Dx06hF27dqFt27a4+OKL0a5dO6ft4+PjkZmZKQe3KSkpuOeeezB37ly0a9cObdu2xbx589C3b1+MGTMGANCrVy9cffXVuO+++/DGG28AAO6//36MHz/e7yCZSC+kN0Yuf016pwzieq/uDfvb/mWdpSAZ8Lwst2vAKO0vGrpuqAXGwWSO9fwcfZEyycrnl7ciTx4jROEQFYHyN998gyuvvFL+v1QTfMcdd2DZsmV+PcYLL7yAuLg4TJw4EbW1tRg9ejSWLVvm9JfLypUrMWvWLLk7xoQJE3z2bibSs7yCPOS+lev0RlvUrijmszEOhwOHDx/GiRMn0K1bN2aUdUTZ3xm4MIal23ytKqgMoG0FNtgKnANM5fdqy3Orfe+vQMeV68qG0lfXAFGi1uvYKJljV8pFRFzLLIz0PEn/oq70Qu9YekF6xZ6jF+i53y35pgwsgcDLNtQ0N5i219pRXV2NlLQUAE3jqkV8C9VAWC1LrCwfce1x7HqM0V5z7IunTDIZF0sviCjipOWvmVmmaOeadQa8l214CoKVPGVupay068+qfV+LWvnntnbYCmuN1S0Q9pQlVpaPSMGyWmBstMyxK2+ZZKJIYKBMFEPyCvKQ83KOnFlmzTIZiaeyDU+ZYGX9c3OCadV2dzUOp/tcv0pcA2jXOlzXwNioQbJalj19ajqvTRRxDJSJYoynzLKRP8ql2KWWffZU/xxsMK0WWJuTzUCNeyDsLUusDIrVjtuopFILCTPJpCcMlIlikFpm2VZgYykGxRxP2dpAgmlljTLSmn5+6KmhXmuU1fYVC0GxK2WphYSZZNITrnlMFKOkzLKSrcCGhvIGDz9BFJssSRanYNbX98qf8/Y11u2duhdF7Ypg7dy0aFf61HTk1+Tzj3XSFQbKRDEsryAP+TX5csAslWLsnbY3wkdGREamNmkvb0Ue/4gg3WHpBVGMsyRZYm6SX1xcHH7961/j3LlziIvjZZC0wXHlH7X2b0a91lD045lMRABiq32c1WrFn//8ZxQXF8NqtUb6cMggOK58Y/s3ijYsvSAiWV5BHoadGSbP4GfNMhFpRa0mmUEy6R0DZSJyopzkp6xZlmb4G4EQAmVlZSgvLwcXJyWtcFx55qkmmUjvGCgTkRu1zHJhcqFhJvnV1NSgQ4cOGD58OGpqaiJ9OGQQHFfqmEmmaMZAmYhUsX0cETUXM8kU7RgoE5FHbB9HRMGw19qZSSZDYKBMRF5J7eNcSzHstXZD1S0TkTb2Tt2LwuRCZpLJEBgoE5FflKUY6VPTceC+A4aqWyai5pH+eOaS1GQkDJSJyG9SKUbum7nymyHrlolIyiIfuP+A0x/UXJKaoh0DZSIKiCXJAkuShXXLRATAecKercCG3Ldy5QCZS1JTtOPKfEQUlGhe9jouLg633347KisrudQwaSYWx5XactQMjslIYuNMJqKQiNZlr61WK95++20uNUyairVxxeWoKRaw9IKImoXLXhPFHrZ+o1jBQJmIms3Tstd6JYRAdXU1ampquNQwaSZWxhUXEaFYwkCZiDQRTZnlmpoapKSkoH///lxqmDQTC+OKmWSKNQyUiUgz0ZZZJiL/MZNMsYiBMhFpKpoyy0TkH2aSKVYxUCYizTGzTGQczCRTLGOgTEQhwcwyUfRjJpliHQNlIgoZZpaJohczyUQMlIkoxJhZJoou9lo7M8lE/8WV+Ygo5PS2gp/FYsFNN92EqqoqWCxcbpe0YYRxJS1JLeGKexTrGCgTUVjkFeQh5+UcFLUrAtCUWc55KScib8CJiYl47733UFxcjMTExLDvn4wp2seVstRCwkwyxTqWXhBR2LBmmUif1Eot8mvyWZNMMY+BMhGFFWuWifTF06Q9S1J0lo8QaYmBMhGFXaQzy9XV1YiLi0OvXr1QXV0dtv2SsUXjuOKkPSLvGCgTUUQws0wUWWz/RuQbA2UiiphIZ5aJYhUzyUT+YaBMRBHFzDJR+Nhr7bDX2plJJvITA2UiijhmlolCb+/UvShMLsSB+w/I5xszyUTeMVAmIl1QyyxL2S8iah5lPbKtwIbct3LZ/o3IDwyUiUg3lJnl9KnpOHDfARQmFzK7TBQkT8tRW5IsbP9G5AeuzEdEupJXkIfct3IBAIXJhQC0X8XPYrHgmmuuQXV1ddQuNUz6o7dxxeWoiZqPgTIR6Y6U6Uqfkg7bSptct5w+NV2Tj4oTExOxfv36qF1qmPRJT+OKy1ETaSMqSi+++OILXHvttcjKyoLJZMK6devk+xobG/HII4+gb9++aNGiBbKysnD77bfj5MmTTo9RX1+PmTNnon379mjRogUmTJiA48ePO21z9uxZTJs2DSkpKUhJScG0adNw7ty5MDxDIlLjqW6ZiDzjctRE2omKQLm6uhqXXnopXnnlFbf7ampq8O2332LBggX49ttv8fe//x0//PADJkyY4LTd7NmzsXbtWqxZswZffvklqqqqMH78eNjtF950J0+ejF27dmHTpk3YtGkTdu3ahWnTpoX8+RGRZ651y0TkGZejJtKWSQghIn0QgTCZTFi7di2uv/56j9vs2LEDgwYNwpEjR3DxxRejoqICaWlpWLFiBSZNmgQAOHnyJLKzs7Fx40aMGzcO+/btQ15eHrZt24bBgwcDALZt24ahQ4di//79yM3N9ev4KisrkZKSgoqKCrRu3brZz9cXu92O4uJidO/eXRc1cUShYq+148B9B2BbaWt2CUZ1dTXS09MhhEBpaWlYzlUyvkiPK6km2drZivrD9ZqVKhGFWiRiGX/jtajIKAeqoqICJpMJqampAICdO3eisbERY8eOlbfJyspCnz59UFRUBADYunUrUlJS5CAZAIYMGYKUlBR5GyKKLGV7q+YuSlJTU4Pa2lotDotIFqlxxeWoiULDcJP56urq8Lvf/Q6TJ0+W/0IoLS1FQkIC2rRp47RtRkYGSktL5W3S090/1k1PT5e3UVNfX4/6+nr5/5WVlQCa/jpSlnWEit1uh8PhCMu+iCIqAUibnIayVWXy5L60KWnoubxnwA+lPF/Cda6S8UViXNlr7SieXiyfF/WH65E2JQ2WFAvHNUWNSMQy/u7LUIFyY2Mjbr31VjgcDrz22ms+txdCwGQyyf9Xfu9pG1eLFi3CwoUL3W4/ePAgWrZs6eeRB8/hcKC8vBwlJSUwmw35AQGRzLLAgvSZ6bANbcqcla0sg+k3JphTAxv7NTU18vfhOlfJ+MI9rs7NP4e6DXXy/+sP1yN9azrMqWYUFxeHdN9EWopELFNVVeXXdoYJlBsbGzFx4kQcOnQIn376qVO9SWZmJhoaGnD27FmnrLLNZsOwYcPkbX766Se3xy0rK0NGRobH/T766KOYM2eO/P/KykpkZ2ejW7duYatRLikpQU5ODmuUKWaIyULOoNmG2gLOLFdXV8vfh+tcJeML57hqKG9A6QbnTzvTpqQhd6B/82mI9CQSsYxUAeCLIQJlKUguLi7Gli1b0K5dO6f7+/fvj/j4eGzevBkTJ04EAJw6dQq7d+/G4sWLAQBDhw5FRUUFvv76awwaNAgAsH37dlRUVMjBtBqr1Qqr1ep2u8ViCdsv22w2h3V/RJHWe2VvNPy5AUXtmuYPlK0sQ/eXu/vdI1Z5rvDcIa2EY1wpJ7UqJ+3lvpnLzhYU1cIdy/i7n6gIlKuqqlBSUiL//9ChQ9i1axfatm2LrKws3Hzzzfj222+xYcMG2O12uaa4bdu2SEhIQEpKCu655x7MnTsX7dq1Q9u2bTFv3jz07dsXY8aMAQD06tULV199Ne677z688cYbAID7778f48eP97vjBRGFj9Q2LhQLkhDpEVfaIwq/qAiUv/nmG1x55ZXy/6VShzvuuANPPvkk/vnPfwIALrvsMqef27JlC0aNGgUAeOGFFxAXF4eJEyeitrYWo0ePxrJly5z+oli5ciVmzZold8eYMGGCau9mItKHvII85LycI2eW/V3q2mw2Y8SIEaitrWVtP2kmlOOKK+0RRUbU9VHWO/ZRJgq/YPrH8tyhUAjFuFIb3yy1ICNhH2UiohDiUtdkVFxpjyiyGCgTkSFwqWsyEnutHXun7kVRuyJYOzdNGGepBVH4MVAmIsPIK8hDfk0+IIDC5ELsnbZXdbvq6mpkZmZi2LBhTi29iJqjueNK+hRk79S9KEwu5Ep7RDrAQJmIDMefpa5Pnz6Ns2fPhvOwKAYEO66k4HjPbXs4aY9IRxgoE5GhWJIscgmG1DbOU2aZSA+Udchla8qQdmsagKYAOb8mn5lkoghioExEhqM2uc9TZpkoUjzVIfde3VsOkDlpjyiyGCgTkSEpJ/cxs6w/Uj2uvdYe8u/93TZcpADZWx0yA2QifYiKBUeIiILhaUESKFadt9fagdYXAipLksXr9wxg1EmvjT+v457b9qBsTZncFxhASL/3Z1upN7Ha8Wr5GknLT7tiHTKRPjFQJiJDU1vquuWtLeX7t2VuQ2rnVL+DrrRb09B7dW+/A2t/vtdr8O1P8Bto4JtwcQIajjaVwUi3hfp7f7a1FdhgK7C5Ha8WAbSvAJmLhxDpFwNlIjI818zymTVnkIum4McMc0BBV9maMmzduhX1R7TLeHoKvkMZYPt6fH+D30ADX2lbALB2smr6Onr63p9tlYINoM1mMwYMGIC6ujqYzWYGyEQGwCWsNcYlrIn0S1oKOH1qOiq+rAgo6FIGhKGgFjQGE2BLkxYT2iY4fR9IEBzscw0k8A1FZt7T9/5sqwxoPQXQHp+34jn1LOiJfR/vg+ldE8pWlbltywCZyJ2el7BmoKwxBspE+iYHTnY7Duw4gJw+OUhomeBX0KV1ba0WwbcyODW3MMNR7Wi6wwLgv3PUlLcHuk9fwW+wga8eA0WtA2glBshEnuk5UGbpBRHFFGWgYk41y/9X3u7p+96re8P+tv+T1qSOCq7ZXeX3u2/ZjdN/O60ahHoKfGEG8N+bpSAWwIVtodjW5XanINlDMC3tv/0t7dHn//q4HbslyeKWrQ3kddRrsKh2jHkFech960KJhfRalMwquVBSofh9uLJ2saL/N/05UY8oSmkSKH/yySf49NNPUVRUhOPHj+P06dNITk5GWloa+vbti5EjR2L8+PHIzMzUYndERM1SU1ODvLw8NNY3Ys+/9yA1PTWgj/T9tf/u/X5noNV4Cnw9BWVOlIG1Jx6Cacnpv57G1i5bPZZNOD2USolDNFN7HlLpDtCUmZf996WrQx3uxJ0AgGVYhkQkov5QPYraFTGjTBSlgi69qKqqwssvv4y33noLR48ehfQwiYmJaNu2LWpra1FRUQGHo+kKEhcXhwkTJuC3v/0thg8frt0z0BmWXhDpm73WjjpHHVq2bOp8sREbA+p64e/3Wtc0+9viLOelnKb9KzLXyuxnIIG61+P5b0lGMO3WIl2SoXW9svRa1KIWv8QvAQBfT/wa1f9X7bYtA2Yid3ouvQgqUF6yZAmefPJJ2Gw2XHrppZg4cSKGDh2KAQMGyG8+ACCEQHFxMbZv346PPvoI//jHP1BdXY3rrrsOf/rTn9ClS5fgnp2OMVAm0i8pI5h8fTIGrxsMoClQTkJSSPcbbHeHYIJNT4INDjWZ5KdBB5DmfB/o8wzkOSmPt7q6GilpKQCAiooKtIhv4bXrBZemJmpiuEA5Pj4eU6ZMwfz589G7d2/fP/BftbW1WL16NRYtWoRp06bhD3/4Q6C71j0GykT61FDeILeHU2b+QpVR1iLwC3fWMZgJjVplqJW0bhvXrMy5jyy58ndUXV0tJ4uU7wGe2sQNOzOMtctEMGCgfPDgQXTr1i3og7Pb7Th+/Dg6deoU9GPoFQNlIv2RMslS0NPy1pYYuGYgAKC8tBxtMtqEtDWZ0bhO4gs2Qx3O9ntqtF6lz1OgLFEGzK6fGhhxnBD5y3CBMnnGQJlIX5SZZKApi9dobfQa0JA2Av3DIlRLWwdTOx0MX4GyxHVMKo+LATPFIj0HymwPR0SG5ZpJTp+ajoS2CWisboz0ocWEQFvFBdN+z5/vvQXBkWhbp1xWXSKtAMjaZSJ9MWv5YGfPnsW7776r5UMSEQWlobxBDkTqD9dj2JlhcgBiMpmQl5eHbt26wWQyRfIwyYWyH7NW37veFiqBjKu8gjzk1+QjfUq60+22Apvcf5uIIk/TQPno0aO46667tHxIIqKA7Z26F0XtimDtbAUAOZMsSU5Oxvfff48NGzYgOTk5UodJBhPouLIkWdwC5vSp6Thw3wEUJhdi77S9DJiJIiyg0oujR496vf/kyZPNOhgiouay19rdMsnsLEB6JgXM0gqAhcmFAFiOQaQHAQXKnTt39vpxkhCCH2MSUcRJ9Z+umWQiPZNKQ9Tql3NeyuFYJoqAgALlNm3a4JlnnsGoUaNU79+3bx9uuukmLY6LiChg0uS99KnpyK/J91iTWlNTg4EDB6K+vh7fffcdWrVqFeYjJSPSalxJ2WVlKzlpGWxmlonCK6BAuX///igrK0Nubq7q/XV1dWC3OSKKBOXkPVuBTW4BpkYIgb1798rfE2lBy3EllWPkvJwjt5JjZpko/AKazPfrX/8anTt39nj/xRdfjHfeeae5x0REFBC1yXvsR0tGILWSAyBnljnJjyh8uOCIxrjgCFF4qS0o4ivj5u/CEESBCOW48rRICUsxyAj0vOCIpu3hiIjCyVcbOCKjUGaWJbYCGxrKw7vsN1GsaXagbLFYfLaNIyLSmlobOGbXyMhcey4rSzGIKDSaHSizcoOIIkW5SAMzyRQLpEl+w84MQ/3hegDMLBOFEksviCjq7J26t2lRBhOQX5MfcCbZZDKhU6dOyMrKYu930kw4x5WnSX5EpC0GykQUVVzbwAUjOTkZBw8exCeffMIlrEkz4R5XzCwThR4DZSKKGmwDR+SMmWWi0GKgTERRgZP3iNQxs0wUOgyUiShqaDV5r7a2FkOGDMEtt9yC2tparQ6PYlwkxxUzy0ShwUCZiHSvuZP3XDkcDnzzzTfYvXs3HA6HRkdJsS7S44qZZSLtNTtQfuyxx5CamqrBoRARudNi8h5RrGBmmUhbzQ6U/+d//ofLvxJRSHDyHlHgmFkm0g5LL4hIlzh5jyh4zCwTaYOBMhHpjr3WDkuShSvvETWDWmbZXmuP8FERRZc4LR/M4XDg+PHjOHHiBBobG1W3GTFihJa7JCKD2Tt1L2wrbUifmo68gjzkvpXLcguiIEmZZemcIqLAaJJRFkJg0aJFyMzMRJcuXXDFFVfgyiuvVP0XjC+++ALXXnutvCzounXr3Pb/5JNPIisrC0lJSRg1ahT27NnjtE19fT1mzpyJ9u3bo0WLFpgwYQKOHz/utM3Zs2cxbdo0pKSkICUlBdOmTcO5c+eCOmYiCpyy3ELKfoUqSG7fvj3atGkTksem2KXHcZVXkIf8mnxAAIXJhSzBIAqAJhnlRx99FIsXL0Z6ejruuusudOjQAXFx2iWrq6urcemll+Kuu+7CTTfd5Hb/4sWL8fzzz2PZsmXo0aMHnn76aVx11VU4cOAAWrVqBQCYPXs21q9fjzVr1qBdu3aYO3cuxo8fj507d8JiaXojnjx5Mo4fP45NmzYBAO6//35MmzYN69ev1+y5EJF3yuxXqILkFi1aoLS0FMXFxWjRokVI9kGxR+/jSvlHaO6buQDAT2uIfBEayMjIED179hQ///yzFg/nFQCxdu1a+f8Oh0NkZmaKZ599Vr6trq5OpKSkiCVLlgghhDh37pyIj48Xa9askbc5ceKEMJvNYtOmTUIIIfbu3SsAiG3btsnbbN26VQAQ+/fv9/v4KioqBABRUVER7FMMyPnz58W+ffvE+fPnw7I/olDZM2WP2IItYs/UPeJ8TejHM88dCgU9jyvlOab8nijSInHe+BuvaZL2raqqwtSpU9GyZUstHi4ghw4dQmlpKcaOHSvfZrVaMXLkSBQVFWH69OnYuXMnGhsbnbbJyspCnz59UFRUhHHjxmHr1q1ISUnB4MGD5W2GDBmClJQUFBUVITc3V3X/9fX1qK+vl/9fWVkJALDb7bDbQz9pwm63w+FwhGVfRKHi2is55/UcIMRDmucOhYKex1Xu8lzkLMkBABS1KgLQdL51eb4LJ8tSREXivPF3X5oEypdddhlOnjypxUMFrLS0FACQkZHhdHtGRgaOHDkib5OQkOBWN5aRkSH/fGlpKdLT3Sc6pKeny9uoWbRoERYuXOh2+8GDB8Pyh4PD4UB5eTlKSkpgNrOJCUWfc/PPoW5DHcwXmeE44UDitYn48fiPId1nXV0d7r//fjQ2NmLp0qVITk4O6f4oNkTTuEocnyifd9vTtyPx2kSkLk6N9GFRjIpELFNVVeXXdpoEyo8//jhuuukmfPvtt7j88su1eMiAmUwmp/8LIdxuc+W6jdr2vh7n0UcfxZw5c+T/V1ZWIjs7G926dQvLQix2ux0lJSXIycmRa62JooW91o6iDU2ZLccJBwbbBocls1VdXY0dO3YAALp06cJFk0gTUTWu1jV9krM9fTsAoG59HTot7cTMMkVEJGIZqQLAF00C5auvvhrLly/HNddcgwkTJuDSSy/1eIG4/fbbtdilLDMzE0BTRrhDhw7y7TabTc4yZ2ZmoqGhAWfPnnXKKttsNgwbNkze5qeffnJ7/LKyMrdstZLVaoXVanW73WKxhO2XbTabw7o/Is1YnCfvJaUlhWe3inOF5w5pJdrGVVJaknz+WTtbsT19e1NbRi7sQxEQ7ljG3/1oEijX19fjH//4B06fPo2lS5cC8Jzh1TpQ7tKlCzIzM7F582b069cPANDQ0IDPP/8czz33HACgf//+iI+Px+bNmzFx4kQAwKlTp7B7924sXrwYADB06FBUVFTg66+/xqBBgwAA27dvR0VFhRxME5F2lP2S82vyOfueKALyCvKQ83IOitpdqFnOfZO9y4kkmgTKc+bMwcqVK3HJJZfg5ptv1rw9XFVVFUpKSuT/Hzp0CLt27ULbtm1x8cUXY/bs2XjmmWfQvXt3dO/eHc888wySk5MxefJkAEBKSgruuecezJ07F+3atUPbtm0xb9489O3bF2PGjAEA9OrVC1dffTXuu+8+vPHGGwCa2sONHz/e40Q+IgqO6+Q9qVUVEYUfFyUh8kyTaPavf/0r+vfvj61bt2oaIEu++eYbp8VKpJrgO+64A8uWLcPDDz+M2tpaPPDAAzh79iwGDx6Mjz76SO6hDAAvvPAC4uLiMHHiRNTW1mL06NFYtmyZU+p95cqVmDVrltwdY8KECXjllVc0fz5EsUzKJFs7W1F/uD6k/ZKJyD/SKpgH7juAwuRClmAQ/ZdJCCGa+yCtW7fGjBkz5DKGWFZZWYmUlBRUVFSEbTJfcXExunfvrvt6OCJ7rR2FyYXy/4edGRaRyUPV1dVyV5pwnatkfNE+rvRyflLsiUQs42+8pkkPjv79+zuVRhAReZI+pemj3fSp6RF9E05OTkZSUngmD1LsiOZxZUmyyOentbMVRe2KuNw1xTxNAuVnnnkGmzZtwoYNG7R4OCIyoL1T9zZlq0xAfk1+RD/WbdGiBSorK/Htt9/qcqlhik5GGFd5BXkYdmYY6g83LaRlK7DBXqu/xVOIwkWTguLNmzdj1KhRuO6663DllVfisssuU01jm0wmLFiwQItdElEUsdfaOXmPKEpwch/RBZoEyk8++aT8/aeffopPP/1UdTsGykSxS/nGy8l7RPrGyX1ETTQJlLds2aLFwxCRAemxX3JdXR1uvPFGVFdXY+PGjVH7MTnpixHHlfKToJyXcji5j2KOJoHyyJEjtXgYIjIYvfZLttvt+OCDD+TvibRgtHElTe6T2jkWtStiZplijiaT+b766ivMmTMHpaWlqveXlpZizpw52LZtmxa7I6IosHfqXhS1K4K1c9MS7yy5IIo+nNxHsU6TQPn555/H+vXrkZmZqXp/ZmYmNmzYgBdeeEGL3RGRzikn79UfrsewM8OYhSKKUtLkPgCc3EcxR5NAeceOHbjiiiu8bjNixAhmlIliiF76JRNR8+UV5CG/Jh8QQGFyIfsrU8zQJFC22Wy46KKLvG6TmZkJm82mxe6ISMf01C+ZiLSlnHPQUN4Q4aMhCj1NAuXU1FQcPXrU6zZHjhyRl/YkImNy7ZdMRMbBlfsoFmkSKA8dOhRr167FsWPHVO8/evQo1q1bh2HDhmmxOyLSMWXJBSfvERkLJ/dRrNEkUJ4zZw5qamowfPhwvPvuuzh16hQA4NSpU1i+fDmGDx+O2tpazJ07V4vdEZEORVPJRYsWLXD+/Hns27fPEL1uSR9iZVxxch/FEk0C5fz8fLz88ss4deoU7rrrLnTs2BFxcXHo2LEj7r77bpSWluKll17CiBEjtNgdEemMa79kIjI2Tu6jWKHJgiMA8OCDD2LkyJF4/fXXsWPHDpw7dw6pqakYNGgQZsyYgT59+mi1KyLSEWnlPWtnK+oP17PkgiiGuC4oxHOfjEazQBkA+vTpg1dffVXLhyQiHVPrlxwNreDq6uowdepUVFVV4f333zf0x+QUPrE2rpQr97EEg4xKk9ILIopd0dgv2W634/3338eHH35oiKWGSR9icVyxBIOMjoEyEQUlmibvEVFoKUsw7LV2dsIgwwgqUB4/fjx27twZ1A5ra2vx//7f/8Prr78e1M8TUeSxXzIRSZT9ldOnpuPAfQeYXSbDCCpQPnbsGAYNGoTRo0dj2bJlqKys9Pkz33zzDWbPno1OnTrhD3/4A9q3bx/Mrokowuy1drc3Rk7gIYptUglG7pu5btllomgW1GS+Xbt24Z133sFTTz2Fu+++G/feey969uyJyy+/HBkZGWjTpg1qa2tRXl6O4uJifPPNN6ioqIDZbMbEiRPxxz/+EZ07d9b4qRBRqEkdLtKnpiOvIA+5b3GWOxE1ka4FnOBHRmISQohgf9jhcOBf//oXli1bhs8//xzl5eVu25jNZlxyySW4/vrrce+99yIrK6tZB6x3lZWVSElJQUVFBVq3bh3y/dntdhQXF6N79+6wWBiwUOjYa+1NNcn/lV+TH7VBcnV1NVq2bAkAYTtXyfg4ri6w19px4L4DF/6w5hwG8iISsYy/8Vqz2sOZzWZce+21uPbaawEA+/btw/Hjx3HmzBkkJSUhLS0NvXv3RkpKSnN2Q0Q6ocwURWuQTEThwR7LZASa9lHu1asXevXqpeVDEpEOKEsuojmTLElOTkZFRQVKSkqQnJwc6cMhg+C4uoA9lsko2B6OiLwy4vLUJpMJLVq0QHJyMkwmU6QPhwyC48oZeyyTETBQJiKP9k7di6J2RbB2tgJghwsiChy7YFA007T0goiMI1qXp/ZHfX097r//flRWVmLlypUx/zE5aYPjyh1LMCjaMaNMRB5F4/LU/jh//jzeffddrFu3DufPn4/04ZBBcFypYwkGRTMGykTkhstTE5HWWIJB0YiBMhE54fLURKQ119U8iaIFA2UicsPlqYlIayzBoGik+WQ+u92O06dPo76+XvX+iy++WOtdEpFGjNYvmYj0R/mJVc5LOYaa/0DGo1lGeefOnRg3bhxatmyJrKwsdOnSxe1f165dtdodEWmMJRdEFGrKEgxrZyuK2hUxs0y6pkmgvGvXLuTn52Pr1q0YO3YshBC45JJLMHbsWLRv3x5CCIwcORLTpk3TYndEFCIsuSCiUMsryMOwM8NQf7jpk2dO7iM90yRQ/p//+R8AwPbt2/GPf/wDAHDDDTfggw8+wOHDhzFjxgzs3r0bTzzxhBa7IyKNxVqXi+TkZJw6dQpfffUVe92SZjiu/JfQNoGT+ygqaBIof/nll5gwYQJ69eol3yaEAAAkJSXhlVdeQVZWFn7/+99rsTsi0lAsllyYTCakpaWhbdu2XGqYNMNxFRhO7qNooEmgXFFR4VR/HB8fj6qqqgs7MZsxatQofPLJJ1rsjog0xpILIooU9lcmPdMkUE5PT8fZs2fl/2dmZqK4uNhpm7q6OtTU1GixOyLSSKyVXEjq6+sxc+ZMPPXUUx479BAFiuMqcOyvTHqnSaCcl5eHAwcOyP8fPnw4PvroI2zbtg0AsG/fPvzf//0fevbsqcXuyIWoaypzkf4SD/QrxaZYLLmQnD9/Hq+//jpWr17NpYYpYMprqPL7+p/rncYVr7X+YQmGMQUai0ixjN5o0kf5V7/6FX7729/i1KlT6NChAx555BGsXbsWw4cPR9u2bXH27Fk4HA7WKIfA/tv3o2xVGc51Pof6w/WwdrYG9DV9ajryVuTBXmuHJckS9FeKTulT0uW+yfw9El0gvXlL1znp+z237UHZmjL5GgpA/r4WtfLPb+2wFdYaq9O1NvfNXF4/vVD+4S69VhRZamPVn7jgwH0HYFtpCzgmcUxxoHdB7wg/a2cmIc26a4bGxkaUl5ejTZs2SEhoahxeVFSEP/7xj/jxxx/RqVMnzJw5E7/61a+afcB6V1lZiZSUFFRUVKB169Yh3Ze91t70sXkzpd2a5nThDybY9vYGwDcD/VEuLBKLb0jV1dVo2bIlAITlXCV9U163AMhv8gCcAuKEixPQcLTB4+PUoha/xC8BABuxEUlIctvG2/Uz1sX6dSkSAgl206emAwJ+BcDNEa7FrvyN1zQJlCPt/PnzePLJJ7Fy5UqUlpaiQ4cOuPPOO/H444/DbG6qLhFCYOHChXjzzTdx9uxZDB48GK+++ip6977wl0t9fT3mzZuH1atXo7a2FqNHj8Zrr72Gjh07+n0s4QyUAWDPlD0oWxV8kCsFyVpQewOQTipvwTQD6fBqKG9AUbsi+f+xuAIfA+XY5itD7A9rJyvqj7hnlKVAeVPyJqeMsi+uwWGsXheVAZr0iSc1XzBZXy0EHJNMSQtbRjmmAuU//vGPeOGFF7B8+XL07t0b33zzDe666y48/fTTeOihhwAAzz33HP74xz9i2bJl6NGjB55++ml88cUXOHDgAFq1agUA+PWvf43169dj2bJlaNeuHebOnYvy8nLs3LkTFot/F6xwB8p2ux0//OcH9OjbA2iAz49D1L5Kf8UHG2wHIpisdKy+YYSC6+86Vt+IGCjHDm/ZYl8ZYsA5o6xMMPRe3dutPKO6uhopaSkAmsZVi/gWPoMSV54SDLHC9ZPSWPxDPlieyiP8HXueBJNR9uc93encTIAcy/gbbzVXSAPlu+++GyaTCc888wwyMjJw9913+/VzJpMJS5cuDXR3Po0fPx4ZGRlOj33TTTchOTkZK1asgBACWVlZmD17Nh555BEATdnjjIwMPPfcc5g+fToqKiqQlpaGFStWYNKkSQCAkydPIjs7Gxs3bsS4ceP8OpZIBMrFxcXo3r17swZXc2qUPZ2EypPKX4GcdBQY1zegYWeGIaFtQgSPKHIYKBuba1DsT2CgzBBL1xvAvUbZ2/XH17jydv30JtYCZpZg+EdtHKkFs74E+r4birlLWsUygQhpoGw2m2EymbBv3z706NFDLm/wxWQywW7Xfvbvs88+iyVLluCjjz5Cjx498O9//xtjx47Fiy++iNtuuw0//vgjunXrhm+//Rb9+vWTf+66665Damoqli9fjk8//RSjR4+Wa60ll156Ka6//nosXLjQr2OJ1kC52cfh5UTR8iMeT3V9zD77xo80L2CgbDxqGWNfvGWIgxHsuPIU6LiKpcCR16sL/ElQ+UPPn+TqOVAOquvFoUOHAAAXXXSR0/8j5ZFHHkFFRQV69uwJi8UCu92OP/7xj7jtttsAAKWlpQCAjIwMp5/LyMjAkSNH5G0SEhKcgmRpG+nn1dTX1zv1y6ysrATQ9EsPxR8Frux2OxwOR1j25VVC07G4ff3vfbnLc5GzJMfjCVk8vdhrrbVE+t5WYIOtwIa0KWmAgNPPpk1JQ/cl3Vm+oSB1R0mbkoZhPw9rek0iPWYiKCEhAQcOHMCRI0eQkJAQ069FNJMCW+n64YnyOiJdHwCXUrX/XrcABD0egh5XLtdIAMhZkuP2vJTXPekaZ1R2u3P7ypzXcwz9fJX8eW+UuAbJwbwnqr53JwR/HgT1nCMQy/i7r6AC5U6dOnn9f7i99957KCgowKpVq9C7d2/s2rULs2fPRlZWFu644w55O9clRYUQPpcZ9bXNokWLVLPNBw8elDMLoeRwOFBeXo6SkhK/M/t6ZFlgQcb8DJgSTRB1wu1rxYIK1G2og/kiMxwnHPLPla288CYiXTDKVpahbGWZvK30NfHaRKQ8leL02LFA1An5zbZsZRnM88wx89y9cTgcSEpKwo8//hjV506skXqtStcEb1zPeQAwJZrw4/EfQ3Z8Wo4r6bro+lyla5zy+RlR4vhE1G2oQ+K1iThYctCwz9Of9zrp/c01MFZ7fwPg9n4ayjGvhUjEMsoVpL3RpI9ypM2fPx+/+93vcOuttwIA+vbtiyNHjmDRokW44447kJmZCQByRwyJzWaTs8yZmZloaGjA2bNnnbLKNpsNw4YN87jvRx99FHPmzJH/X1lZiezsbHTr1i1spRclJSXIycmJaOlFyK1T/ytb7a9niXSRkb7Wra9D3fo6r39lG5G91g7HZIf8evXo2yPSh6QLMXPuGIC/mWPAPWMcbiEZV+vgdN2TSNc0w2aY11143j/1+wlpU9LQc3n0L1zmLWMsUQbJgHvZhNHevyJxPZYqAHzRJFD+6quv8P777+Phhx+Wg1Kl0tJSLF68GBMnTsSQIUO02KWTmpoat79ALBYLHI6mgdalSxdkZmZi8+bNco1yQ0MDPv/8czz33HMAgP79+yM+Ph6bN2/GxIkTAQCnTp3C7t27sXjxYo/7tlqtsFqtbrdbLJaw/bLNZnNY9xcplpYW+Wvvlb1h/4vio6O/+D/D1zXzbOQJg8pJMZw9fkFDQwMeffRRnDt3Dq+88orc/530JdDJbkBkgmNJKMeV8rrn+ppI1zJD1jBb4PSJWM+3ekbV8/PVZUrimikOZKEa6b0x2oU7lvF3P5q0h7vpppvw/fffo7i42OM2PXr0QL9+/fDee+81d3du7rzzTnz88cd444030Lt3b3z33Xe4//77cffdd8uB8HPPPYdFixbhnXfeQffu3fHMM8/gs88+c2sPt2HDBixbtgxt27bFvHnzcObMGd23h9PDZD69ac7kB39XLdQ7tlnyjJP59Es6v6T+xp7oJThWCue48vZHhNEmvyn/4Fdek/XI23uOt3ULjJyw8YfhJvO52rFjB0aPHu11mxEjRmDz5s1a7M7Nn//8ZyxYsAAPPPAAbDYbsrKyMH36dPzhD3+Qt3n44YdRW1uLBx54QF5w5KOPPpKDZAB44YUXEBcXh4kTJ8oLjixbtowBaBSSLi7Kr3kFech9K9dn4KycMCjOC9VVC/V+MZOOiUtUUzRwDY499TfWY3AcKcprmmvAbCuwIeelHMO0f1Reu12DZr3w5z2lbE2Z20q43t5LYn2M64UmGeXExETMmzcPTz/9tMdtHn/8cfzpT39CbW1tc3ena8woR5dg//qX6HEZ2mjKvkQKM8r64Ss4TrstDT2XNtWl6n0cR3JceVpyWC/XJS3o6VOyQHph+/qUkmIgo5yamoqjR4963ebIkSNh6QJBFAhvGWdLkgV7LeqrFkpc29VFOtNsr3VuqWSkN0kyDmly3v679qPsvaY/RpVBsrT4R9qtaei9KjzL2UY76RqW83KOvES92nUpmrl+ShYJ/pTx+coWu34lfdMkUB46dCjWrl2LY8eOITs72+3+o0ePYt26dfjFL36hxe6IQsb1AqYWPHu7UEpvTJEs0WC5BemRrwVBnILj/y7+wfEbuIS2CfI1QKIMmPVUrhAMZblJYXJhyJ+Tt8yxa5DMMgpj0qT0orCwEKNGjcJFF12Ep59+GldddRU6dOiAU6dO4aOPPsLjjz+OU6dO4dNPP8WIESO0OG7dYulF7Aj2o7dQBc5c9tV/LL0IH3/OD6MEx3oaV55edyMsXR+OEoxgM8cUHD2XXmgSKAPAq6++itmzZ8st2UwmE6SHNpvNePHFF/Hggw9qsStdY6Acu7TsrBHMvvVSuxcN9BTQGFGgnSuMMlb1OK481S5H+/wFLSf1eWrh5kmkS+yMKCYCZQDYvXs3Xn/9dezYsQPnzp1DamoqBg0ahBkzZqBPnz5a7UbXGChToC3pvM2CDmSf0r6M8PFqqDkcDuzevRtHjhzB1Vdfjfj4+EgfkmHEcucKPY+rhvIGuXYZuHDdiebrhRYJBn8mcTNzHHoxEygTA2VyF2xnDX+zFiy5CA7PHe2oTc5TiqbOFc2l53ElXStcrzvRXI4RSGbZ33I55R8RzByHBwPlGMJAmXzxd6UmibdsBksugsdzJ3j+BByuk/Nihd7HlafrTjRmlv29/gVabxztZSnRSM+BsiZdL4CmpTvXrVsnl13Y7Xa3bUwmE5YuXarVLomikq/OGp5mVntqQccuF4FraGjA008/jfLycvzv//4vkpKSIn1IUUMqrfBVTmSEyXmBioZxpbzuuLaSi7ZFSny1i2tOp4pYGrfknSYZ5SNHjuCqq67CwYMH4e3hTCaTagBtJMwokxb8yYCYW5jhqHbA2sWK/t/0R0LbhJgLTIKlx0lXeuartEIS6+U/0Tiu1DLL0fY7dJ2jkfum+2qFkmh+nkam54yyJoHyjTfeiHXr1mHatGm4++670bFjR8TFqSerO3Xq1Nzd6RoDZdJSc1vQkbpoDGjCzd++x0aenBeoaB1XrhP9AERVKYba8btivbG+GT5QTk1NxcCBA7F58+bmPlTUY6BMoaQMmKWMsidcLtWzaA1owiGW+h5rLZrHlVpLNL1P8vNnrDJxEB30HChrUqPscDjQr18/LR6KiLxQXuzb39AeOS/loGRWicdVAsV50ezWc2R8wfY95jgyDuWKd9L1pKhdkW4yy8o/yrwFyMqStEF7BnGMUrOZtXiQoUOHYt++fVo8FBF5Ya+1y28OtgIbLEkW5BXkIb8mH0MPDUV+TT7SpzRNalG2gFJOCCxMLsTeaXvlj9alrxRbpN/7ntv2oDC5EEWdilSD5PSp6civyUd+TT7yVuQx8DAw6Xoy7Mwwp2tGQ7l7P+xwsdfasXfqXvm6JX3vGiSnT03HsDPD5E/Z6g95XvCJKBCaZJSfffZZ5Ofn429/+xtuvvlmLR6SiDxQ63Kh/KrsorHXot56TuqgwUxzbFJbFES5OEgs9T0mdwltE+TrTKQyy2pZY1uBewbZ9drlrQsGUTA0qVF+6qmnsGPHDmzcuBEjR45Ev379kJKS4r4zkwkLFixo7u50jTXKFCrBLiwSyITAWJnwEs21pMHy1bkiVvsea8lo48p1klw4apa9XafSp6YDAj6vg1ypNProuUZZk0DZbPavgoPt4bTHQDk2aLmwSKDN940YONvtduzYsQPHjh3Dddddh4QE/U5Yag5/O1dwcp42jDiuwtU+zleArNynr3HKhZiij54DZU1KL7Zs2aLFwxCRF1otLOJanuHPIidGK9GwWCwYOHAgUlNTDfcHpq/gWKIWHEf77zXSjDiu1BYmkRY+0iJTG0iALPE1Tn0tREIUCC5hrTFmlElrwZZcBMqfTLPECK3njHTu+BscA2yXFWpGGldKWrWP86cUTKsxyhKM6KHnjDIDZY0xUCYtReIjRLU3MrXAWeqqEY3Z5oaGBrzwwgs4ffo0nnrqKV0uNexLMMExwKxxKBlhXHmjdk3wNwD15w9xra8hLMGIHjERKJ8/fx5//vOfsXr1auzfvx81NTU4f/48AGDXrl148803MXv2bPTo0UOL3ekWA2XSkh4yImqBs7L1nKtoqGuOtklXyt8BwOBYr6JtXAUrkEl+kV4URPmJHDPK+qXnQFmTGuXa2lqMHTsWRUVFaN++PVq3bo3q6mr5/i5duuCdd95B27Zt8fTTT2uxSyLDU17gI5kJ0bL1nF4DZz1yXQTEVzkMwOCYwsOf9nHeAuRwfgrlOh+D5wUFSpMFR5555hl89dVXWLRoEUpLS3Hvvfc63Z+SkoKRI0fiww8/1GJ3RIbnurCInkhvNJ4WOpG4LnKytctWLnbigfL1UC6woFwExFOQrLYgCIMBCjW1hUlqT9QCgNdFQZTXjHAtYGNJsjgtWkIUCE0yyu+99x5GjRqFhx9+GEBTGzhXXbt2xXfffafF7ohiglZdLkJJLdvsqQ7Rn04asZLxkQJjXxlj5SIgUis3gJlj0gdlZtncwoztHbcjoVMCGo44r+SnljkO57h1TTxEy1wK0gdNAuWjR4/ihhtu8LpN69atUVFRocXuiAxNLyUXwfDWei6YwBnw3TNV77zVFytXxvPWz1rZyg1gcEz6oPxESFo6uuFIA9rf3B6n/3ZaNxN82S6OmkOTQLlVq1YoK1Of2CM5ePAg0tLStNgdkWGpZT6ikae65kACZ0+rcOm1JZ1rQOxPfbGvjLHr89TT86XY5bX+uIsVZuuFqk69jFnlJ16FyYWc3Ed+0yRQHjJkCNavX4+KigrVpauPHz+OjRs34vrrr9did0SGFg0lF4EKJnBW1ma7Zp29lW1oHUgrA19P36sFxL6yxYB/GWOjjAGKfr56H+e8lANLkkVuyWYrsCHnpZyQL3sdCJZgUKA0CZTnz5+PK6+8EmPGjMFLL70kt4WrqanB1q1bMXPmTDQ2NmLOnDla7I7IkKK55CJQ/gTOyoyyRAo4PZVtqAXS0ht1Q3mD/DUxJREff/wxju48CnONGWjd1PIKgLwNAJTMKpH3rwyC/QmI/a0vZsbYOBITm8bViRMnkJiYGOnDabZgFwfx1REjUliCQcHQrI/ykiVLMGvWLNjt7rPYLRYLXnvtNbduGEbEPsoUDDbGd6YMHtWyzv60SnNiAWC/8NXaxYr6o/VNtynvd/0+UB4eRwrYgaZA3J8std5KS8g/Rrgma7E4SCC9lsNND/3pyZme+yhrujLfvn37sGTJEmzfvh3l5eVo3bo1Bg8ejAceeAC9e/fWaje6xkCZgsELt29S4KjMDO/sv7PpTbw5wW2YecpMq32vln329D2Dan2I5muy1ouDSJ+SBbqKX6gxMaE/MRMoEwNlCpyy5II1c+78XVJbSbrf3MLcNBvfJaNs6WzB3478DRDAtbgWcZY41Uyw/PMILMB1/V4LvvajVufMLhnh1djYiCVLlsBms+Gxxx6LmvKLUC4OotfMMq+7+sJAOYYwUKZAMLPhzHUinmtGyhNvk/uUGWjpa6O1UV5quOxQGdp3bq9aoxxImYS375VBSCiDbGUttPIxfGWmY3nMaSnalrD2t/a4uWNEz5llfpKnDwyUYwgDZfKXazAYyxdqtWxx2q1p8qp0rpq7WEkkAppggmx/AmzlZEJ/MBsdOtEQKLted1yFKsOqx8wyExX6oedAWZOuF0899ZRf25lMJixYsECLXRJFNafgWNH1IdaoZbSkIK5sTZkcLPsTGOv99fN0rN6+l8aG9P9A2tN5ykqr9a4uW1OGrVu3BpyNpuihPNfU/ggNdQmCchU/vXTDcO2CwTFNajTJKJvNZq/3m0wmCCFgMplUu2IYCTPK5AuzGP7XROatyAvJAiPRkPkLlNqCJ75KP5qTjXb9o0W5z1gbzxI9jitP55oULIe7RlevmeVYH7uRZviM8pYtW1Rvr6iowLfffouXX34ZY8aMwYMPPqjF7oiiXqxmMYKpiWSPYf+ovU7S994y08Fmo117WCt/jktuR56vcy1vRR7sb4c/MNRrZpklcORJWGqUi4uLcfnll+Mvf/kLJk2aFOrdRRQzyuRNrM60DnTBglDTY+YvkoLJRvvia5EV6Xsj0cO40tu55olrZjmSn6zxU77IM3xG2Zfu3bvjhhtuwLPPPmv4QJnIE3ut3W35VKOLljftWBdMNlqtVZ/TKoVH3LPPgO/6Z46H4ETbuabMLEd6lTy1WmWORZKEJVAGgPT0dBw4cCBcuyPSpVgpudD7m7bVasU//vEPnDx5ElarNWLHES28BdD+lHIoqZVvAMYo24jEuNL7ueaNNIYO3HcAhcmFES17UI5nlmGQUlhKL+rr69G/f3+Ul5fj5MmTod5dRLH0gtTESslFNL1p89wJHddSjkDLN3yVbehlDKkJ17iKpnPNG9eyh0hP7mMZRmQYvvTi3XffVb39/PnzOHHiBNasWYP9+/dj5syZWuyOKKrEQsmFUd60SRuupRy+yjeAwMo2ojnr3FxGO9eUZQ96mNzHlnHkSrP2cCaTye126aFNJhMmTZqEt99+O2qW9AwWM8rkysirP0Xrm3ZjYyNWrFiBn376Cb/97W8Nf13Ss0DKNpS8ZZ0jJZTjKlrPNX/prW0cW8aFl54zypoEysuXL1e93Ww2o02bNrj88suRlZXV3N1EBQbKpGTEkotIreylJT10JyB13so2/On7HMlSjVCMK6MHyEp6W+qatcrhY/hAWQ9OnDiBRx55BB988AFqa2vRo0cPLF26FP379wfQlN1euHAh3nzzTZw9exaDBw/Gq6++it69e8uPUV9fj3nz5mH16tWora3F6NGj8dprr6Fjx45+HwcDZZIYsdZNeuOIxMpeWmKgHF2Czjq7rOgoPUaoaDmuYilAVtJLZtmI128903Og7H1JPT8VFRVhzpw5KC0tVb2/tLQUc+bMwbZt27TYnZuzZ89i+PDhiI+PxwcffIC9e/fiT3/6E1JTU+VtFi9ejOeffx6vvPIKduzYgczMTFx11VX4+eef5W1mz56NtWvXYs2aNfjyyy9RVVWF8ePHG341QQqd9ClNbY+MUOvWUN4gv2lLy0sDTc8tvyYfeSvyov45kj5Zkizy2Oq9ujfya/Ix9NBQ5NfkI78mXz7PXEmBtK3AhsLkQhQmF2LvtL2w19rl4Fv6qgfSseyduheFyYVuQXIsnGtS2zgAcs3y3ml7w34cUq0ygIi3r6PI0iSjfNNNN+H7779HcXGxx2169OiBfv364b333mvu7tz87ne/w1dffYXCwkLV+4UQyMrKwuzZs/HII48AaMoeZ2Rk4LnnnsP06dNRUVGBtLQ0rFixQu71fPLkSWRnZ2Pjxo0YN26cX8fCjDIBxiq5UGa2PC0vHW2YUTaeYDpsqE0ObM54DnZcKc+xaP+0Rit6yiwbdY6Jnug5o6xJ14sdO3Zg9OjRXrcZMWIENm/erMXu3Pzzn//EuHHjcMstt+Dzzz/HRRddhAceeAD33XcfAODQoUMoLS3F2LFj5Z+xWq0YOXIkioqKMH36dOzcuRONjY1O22RlZaFPnz4oKiryGCjX19ejvv7ChbiyshJA0y89HJlou90Oh8PBrLeOuHa5yHk9B4jCX4+91o7i6cUoW3XhTbv+cD0G2wYjoW1C05hLQFSOPeUxh+tcpRD7bwyVuzwXOUtyAFyoUXYdxxIpiC5bU4airUVoONKA9pPao9fKXkF11Ah0XKkdW9maMrSf1B6n3zuNtClp6L6ku3wMsTROLSkWpE1OQ9mqMjmznDYlDT2X9wzrcdjt7tfzWPqDJVwiEcv4uy9NAmWbzYaLLrrI6zaZmZmw2dxrrbTw448/4vXXX8ecOXPw+9//Hl9//TVmzZoFq9WK22+/XS4JycjIcPq5jIwMHDlyBEBTeUhCQgLatGnjto2nkhIAWLRoERYuXOh2+8GDB+XMQig5HA6Ul5ejpKQEZrMmlTTUTKJOIHF8Iuo21CHx2kT8ePzHSB9SwM7NP4e6DXVutydem4gjZ44AZyJwUBqqqamRvw/XuUqRY1lgQcb8put/xYIKeWybskwQJ5s+VG040jRJ8PR7p/FV4VdwnHQAaBrzKU+lNG2f6N7dScnfcSXqhNNxKCVem4i4J+OQ8bsMmBJNUXn90IplgQXpM9NhG/rfkq+VZTDPM/v8PWhNeT0/WHIw7PuPBZGIZaqqqvzaTpNAOTU1FUePHvW6zZEjR0L2ZuRwODBgwAA888wzAIB+/fphz549eP3113H77bfL27m2sBNCqLa1C2SbRx99FHPmzJH/X1lZiezsbHTr1i1spRclJSXIyclh6YUO7L99P8pWlSFtShou//nyqMw8NJQ3oHSD8x+HrpmtaFddXS1/H65zlXRinfPkwH1T9uH0e6edOmpIQTIA1K2vQ936poBWOg+kn3Xla1x5y24b7RzTkpgs5Otqj749wl/yte7C7+6nfj9FJLNtdJGIZaQKAF80CZSHDh2KtWvX4tixY8jOzna7/+jRo1i3bh1+8YtfaLE7Nx06dEBennPdUK9evfD+++8DaMpmA01Z4w4dOsjb2Gw2OcucmZmJhoYGnD171imrbLPZMGzYMI/7tlqtqkuVWiyWsP2yzWZzWPdH6uy1dvkNsGxlGXq+1TOqfieeapGNWBuZnJyMNWvW4NSpU0hOTo6q3xM1n6Xlhd93nzV9YH/H7ldHjbKVZShb2XSOq3XScB1XaLhQ/hGLHSy00ntlb9j/4tyWMuz1wha4X9/5O9NUuGMZf/ejSX57zpw5qKmpwfDhw/Huu+/i1KlTAIBTp05h+fLlGD58OGprazF37lwtdudm+PDhOHDggNNtP/zwAzp16gQA6NKlCzIzM51qpBsaGvD555/LQXD//v0RHx/vtM2pU6ewe/dur4EykVI0drmw19rdZtnXH67HsDPDDDu7Pi4uDjfffDOuvvpqxMVpki+gKBZMRw21ThqmRhNuvvlmjOk1BiV3l6AwuRBbu2yN2Q4WWpL+4FDWCzeUe++prfX+o/H6Ts2nyTtEfn4+Xn75ZcyePRt33XUXgKYyB6mhhtlsxksvvYQRI0ZosTs3v/3tbzFs2DA888wzmDhxIr7++mu8+eabePPNN+VjmT17Np555hl0794d3bt3xzPPPIPk5GRMnjwZAJCSkoJ77rkHc+fORbt27dC2bVvMmzcPffv2xZgxY0Jy3GQcyixHNPXb9LZoSCRXxSKKFG/Lb3vKCiuX2XblmplmBjl4kV7uWhoLXLEvtmi64Mju3bvx+uuvY8eOHTh37hxSU1MxaNAgzJgxA3369NFqN6o2bNiARx99FMXFxejSpQvmzJkjd70ALiw48sYbbzgtOKI8rrq6OsyfPx+rVq1yWnBErZzEE7aHiz3R2pjetf0SEDtv4ufPn8f777+PU6dO4de//rVq+RSRGrU2dPJ9sKMQTdeCfOTDAgvMLcxwVDti5twKh0i3juOKfdrTc3s4w6zMpxcMlGNPtPXZjKVaZE/YR5mC5S1QrkUtfolfAgA2YiOSkCTfF2vnWKhFarnraE2M6J2eA2X2EyNqBqm2FybI9YZ6Fmu1yERakFbyk84ftZpjV+0ntnf6v1TTLNUzU/PkFeRh2JlhTqsvhuN15Yp9sUezQPn8+fN44YUXMGjQILRu3dppgsyuXbvwwAMP4IcfftBqd0QR5zqxRO+US1BLWItM5Ey5tLW/wbE0N2F42XD5tty3clUnAzJg1o5yuetwBq15BXnIr8kHBOTfJRmXJoFybW0trrzySsybNw9HjhxB69atoazo6NKlC9555x28++67WuyOSDeiZRb03ql7UdSuCNbOTbW4yhn3RLFOClj33LbHqVOFP8GxsnOF6zXAkmSRgyoGzKERyaBVmSjh79C4NAmUn3nmGXz11VdYtGgRSktLce+99zrdn5KSgpEjR+LDDz/UYndEERdNJRfKTDJLLYiauAbHRZ2KULamqU+uWg9lwL/gWA0D5tALd9s4touLHZoEyu+99x5GjRqFhx9+GCaTSXUlu65du/pcvY8oGkRDyYX0hquWSWapBcUqb8GxtCofAFg7XeiCEmxwrMbfgFl5rOSbMmiV2saFI7Ms/S7zVuTx92VgmgTKR48excCBA71u07p1a1RUVGixO6KI0nsmQcp277ltj2ommSgWKGuNAf+D47Rb0zD08FDNgmM1vgJm6VhZ++q/SE7uk665/H0ZkyYLjrRq1QplZe5r1ysdPHgQaWlpWuyOKKLstXanxvN6oiyzKFtThrRb01C2poyZZBcJCQlYunQpfvrpJyQk8HUxCmkRCNelqBMuTpCDYtfguP5IPdJuTUPv1b2dFpEI5twOdFxJAXPuW7lyuznpnAWagr2cl3J47vpJmtwnteoMB9dPGNkC0Hg0ySgPGTIE69ev95gxPn78ODZu3BiylfmIwkWZOdDbxVCtzEJakpeZZGfx8fG44447cMMNNyA+Pj7Sh0NBkjpTAN5rjX1ljnuv7g0guOBYKdhxpcww917dW7WMgB/t+yfck/vYLs74NAmU58+fj/LycowZMwZFRUU4f/48AKCmpgaffPIJxo4di8bGRsyZM0eL3RFFhGvmQE9vXJ4m7AHNf/Mn0hO1tm2+yimkPx5DERxrSblstmsZASf8BSack/vYLs7YNCm9GDFiBF599VXMmjUL+fn58u2tWrUCAFgsFrz22mvo37+/Frsjihjlx3p6eIP1tMoeP6r17vz589i4cSNOnjyJLl26cFVLnZJKIbythgf4V07R3LIKf2g5rpRlBBJbgQ22AhtX+fNByvJK18WidkVhWbmPJRjGpOkS1vv27cOSJUuwfft2lJeXo3Xr1hg8eDAeeOAB9O7dW6vd6BqXsDYmablUPb1BScekNOzMMAbJfuAS1vrlqc7YG2kbtVrjcArFuFL+MexKT9cjPWoob0BRuyL5/6G+PirfJ1juFhg9L2GtaaBMDJSNyF5rb+qZ/F/5NfkRf2NyfQMAwItzABgo64eULVYGx8rJd55IQaL0s5EKjpVCOa4YMAdHCl6Vn7iF8jqp9gkG+abnQFmTGmWLxYIpU6Zo8VBEuqSndnBcZY+ilbfloZvb0zjS52WocdGS4IS7bRzbxRmPJjXKrVu3RnZ2thYPRaQryo/S9JJJdp20x1IL0jN/Syl81RkDxg+G/aHWUk7CGmZ14Wwbx3ZxxqNJRnnQoEH497//rcVDEemG3lbg4yp7FA38bdnmyldnCgYbzgJZ5Y/C15mC7eKMR5NAeeHChfj000+xfPlyLR6OKOKkLJheSi68tX8jihQtSymGHtJv2zY98xUwh7o1WrQJR9s4toszFk1KLz766COMGjUKd999N/785z9j0KBByMjIgMlkctrOZDJhwYIFWuySKGScZi7rYAU+tckozCRTuHlq1aZlKQWD4+CplWQoW6OxBCD8beNYgmEMmnS9MJv9S0ybTCbY7caeaMCuF9FNbx0uwt3eKFY0NjZiyZIlsNlseOyxx5CYmBjpQ9IN14A40FZtEr20bAsnPY0rT51xGLC5vzahus6zXZz/9Nz1QpOM8pYtW7R4GCJd0MOiIlxIJLTi4+PxwAMPoLi4OOaXsPYVECtbtakFycptvbVsi4XgTE/jyteCJXkr8mLijxc14Zrcp/xEMlZfayPQJFAeOXKkFg9DFFF66XDhupAIu1uQFpQBsdpKd54CYrUSCsA5O8lSCn3y1h1DnBcoW1MWs9lO5WtTmFwYstdBahfHzHL00mQyH1G000uHC+WkPQkzydqz2+347LPP8PXXXxuuHEzZdUJtkt3WLlvl75VjzdOEO7VuFMo+xgC7Ukj0OK7UJvul3ZomT7SM9Ql/oZ7c5/rewj7X0SfojLLFYsGTTz7pNDlv+/bt2L59O2bNmqXJwRGFU6RLLtQm7bGeMDTq6uowZswYAMD111+PhITo+UNErYZYLUPsqZ7YW3s215pi5ePHUglFsPQ8rpST/SxJFuy17I35CX/hmNyn3If03sIyjOgSdKAshIDrPMBNmzbhqaeeYqBMUUUPJRdcSIQA9/IIfybVBRsQA/7XFPNN3Tik32VeQR5yXs6RJ7XF6mIlaq+D1s/f6Q8UlmFEHU1qlImildoqSuHG9m/G5i0D7Csb7M+kumADYul7pVgJjqiJrwl/sRIwu07uC0XWV3pMtoyLPgyUKaapfSwWLlKwwkxyeLnWCNpr7UBr9cluzf3eVwbYVzbYn0l1DIipOfxZDjsWMp/hyPpG8v2GgsdAmWKavdYekUVFlBdi5YWTQXLzKTO4rl+lYKDlrS3l7bdlbkNq51SfgWyg3/uTAfaVDVZ7bE81xNL3SnwjJn+oLVYisRXYkPNSTkxcm9Syvlo/d7aMiz4MlClmRapWTFmPbCuwIb8mP+Kr/0Ujb4Gwa6DpmrmVZvxL/AlkA/3enwywP/XC/kyq49ghLXB1v/BN8GOtcvQIemU+s9mMnJwc5OTkyLeVlJTg4MGDGDdunPrOTCb861//Cu5IowRX5osOkVqBT60emRdJ//gTEPur5a0tMXDNQADARmwMSUbZ3wywp2wwRZ/q6mq0bNn0aUW43gNCKZZX9wvl6n16WwFWDwy7Ml9JSQlKSkrcbt+0aZPq9iaTqTm7I9JUuGvF2NkiOGqBsUStlhdwL11wbblnt9jx7GXPouxYGfKfykfLti1DUqPsTwY41t8gjSQ+Ph7PPvssTp8+HfGV+bTgz+p+RhXK1ftYqxxdgs4oHzlyJKgddurUKaifixbMKOuf8iOvcGVGmEn2j2s5hesqha48BcKeapSVv2ueOxQKRhxXyj9WlWLhj33lc9f6uu3p2hSLDJlRNnrAS8YUiXZwzCT7ppY1Vq4eJvEnIJa4ZnJj/Y2IKFixXrscqpZurFWODlzCmmKOtIxrOD7y2jt1L4raFcnLALOzhTPl8srKPyaApgl3abemAYC8GMzQQ0NVl09WfvVrv3Y7duzYgf/85z+6WWqYop/Rx5UUMA87M0w+T20FNhQmF2LvtL0RPrrQkMokAGhegsHlraMDu15QzAj3CnzMJHvm6aNcAG7lKfa31TPFzVFXV4ehQ4cCaJp0paelhil6xcq48lS7bNQ2cspsemFyoWbZX9daZdInZpQpJrj+5R5qzCQ7kzIlahlkiVrWGGDJBJEe5RXkIb8mX862SqUYUmbZiNlR5XtIQ3mDj639I72OEDB0Zj6aMVCmmBGukgu1THKs1p4pA+OtXbZ6DZDVyimISL88lWLsuW2PHPQZJWBWlmC4/lGgBZZg6BcDZTI8KVCDCU6ZylDti5lk77XHErUAmYiij1SKAcBpEq7R6pfV/ijQIqh1rYPm9VBfGCiToYWz5IKZZO+lFco/HhggExmLVELQe3VvOeiTaFmqEGnKPwq0rCuWXr+8FXnMKOsMA2UyvHD8pR7rmeRAa48ZIBMZj3Ree6tfNkIQGKq6YqldnJGy8EbAQJkMK1wlF8qsdaxlkv0JkFl7TBR7YqGVnNZ1xWwXp08MlMmQwt3lQpm1NnomWbp4BxIg6018fDwWLFiABx980BBLDZM+cFy5U5YqSIxQihGK/sqsVdanoJewJnVcwlo/wrHiUSSWw44k6fmqrZoXba8Bzx0KBY4rdWqrb0bbNUNNKJa4jsWlrfW8hDUzymRI9lq70+SIUFBO3gtH1jrSlM9XbdU8PWeQiSiyjFyKoXV/ZdYq64shA+VFixbBZDJh9uzZ8m1CCDz55JPIyspCUlISRo0ahT179jj9XH19PWbOnIn27dujRYsWmDBhAo4fPx7mo6fmUl5gwjl5z6hBolSH7Pp8e6/uHbUBssPhwJ49e1BcXAyHwxHpwyGD4LjyzWilGKHor8xaZX0xXKC8Y8cOvPnmm7jkkkucbl+8eDGef/55vPLKK9ixYwcyMzNx1VVX4eeff5a3mT17NtauXYs1a9bgyy+/RFVVFcaPHw+7nYM0WoTjAhMrbeA89UJWPt9oC5AltbW1uPTSSzFhwgTU1tZG+nDIIDiu/GO0rhha91cORf0zBc9QgXJVVRWmTJmCt956C23atJFvF0LgxRdfxGOPPYYbb7wRffr0wfLly1FTU4NVq1YBACoqKrB06VL86U9/wpgxY9CvXz8UFBTgP//5Dz7++ONIPSUKQignQ8RCGzhfnSyM9nyJKPyMVoqhdX9lLm2tH3GRPgAtPfjgg/jVr36FMWPG4Omnn5ZvP3ToEEpLSzF27Fj5NqvVipEjR6KoqAjTp0/Hzp070djY6LRNVlYW+vTpg6KiIowbN051n/X19aivv7DiWGVlJYCmwvRwZKLtdjscDgez3gD2374fZavKkDYlDcN+HtY0GULD18U1kzzYNhgJbRMM89rba+0onl6MslVlbvelTUlD9yXdNX9NI0X5HMJ1rpLxcVwFzpJiQdrkNKfrjq3Ahi7Pd4m6P8pzl+ciZ0kOiqcXozC5EGlT0tBzec+gH89ud/6ENOf1nKj9FM+XSMQy/u7LMIHymjVr8O2332LHjh1u95WWlgIAMjIynG7PyMjAkSNH5G0SEhKcMtHSNtLPq1m0aBEWLlzodvvBgwfRsmXLgJ9HoBwOB8rLy1FSUgKz2VAfEARE1An5Qlu2sgzmeWaYEk2aPf65+edQt6EO5ovMcJxwIPHaRBw5cwQ4o9kuIkbUCVQsqEDdhjq3+xKvTUTKUykwJZrw4/EfI3B0oVFTUyN/H65zlYyP4yo4lgUWZMzPkK9D5ovM2J6+3en6Ey20fi9KHJ+Iug11SLw20VDXYFeRiGWqqqr82s4QgfKxY8fw0EMP4aOPPkJiYqLH7Uwm58EqhHC7zZWvbR599FHMmTNH/n9lZSWys7PRrVu3sLWHKykpQU5OTky3IrLX2uGY7JAzyj369tDssRvKG1C6oemPJccJh5xJjnb+ZpCNqLq6Wv4+XOcqGR/HVTOta7rebk/fDgCoW1+HuvV1zc7MhpvyvahbTrfmXUfXxUa7uEjEMlIFgC+GCJR37twJm82G/v37y7fZ7XZ88cUXeOWVV3DgwAEATVnjDh06yNvYbDY5y5yZmYmGhgacPXvWKatss9kwbNgwj/u2Wq2wWq1ut1sslrD9ss1mc1j3pzfKXsb5NfmaXkikx1b2/UxKS9Ls8SNFel6ujNDX1B/KcyWWzx3SFsdV8yWlJSF9SrrT9alsZRm6v9w9ahIUvVf2hv0vTf2Vi1oVNbu/sqWlJSzrAkRauGMZf/djiM/qR48ejf/85z/YtWuX/G/AgAGYMmUKdu3aha5duyIzMxObN2+Wf6ahoQGff/65HAT3798f8fHxTtucOnUKu3fv9hooU2SFagU+e63dsEtTK2utJeyFTER64a0rBoCo6YyhVX9ltouLLENklFu1aoU+ffo43daiRQu0a9dOvn327Nl45pln0L17d3Tv3h3PPPMMkpOTMXnyZABASkoK7rnnHsydOxft2rVD27ZtMW/ePPTt2xdjxowJ+3Mi36SPoaTsg1ZdLpR/uSsfO1qyGZ4YdWWsYMTHx2POnDk4d+4clxomzXBcaUfqipHzcg6K2hUBaAoSxXmBsjVlus+sKt+bpEA/2GMOxfsc+c+wS1iPGjUKl112GV588UUATbXGCxcuxBtvvIGzZ89i8ODBePXVV50C7Lq6OsyfPx+rVq1CbW0tRo8ejddeew3Z2dl+75dLWIeH68dQWtVu2WvtKEwulP+fX5MPIHr7BQPOAbLSsDPDoj74b45YPXcotDiutCdd79NuTUPZmgtzKqLhGtZQ3iAH+gCaVR5o5FplPS9hbdhAOVIYKIeeWjCr1UVDGVTqPWPhjXQh9VaLHK3PTSuxeO5Q6HFchYbrNS2aPhXTMrFj1FplPQfKhqhRptgTikVFpEU2YIJcrxuNpOex57Y9XmuRY5nD4cDhw4dx4sQJLjVMmuG4Ch3pOh+Ni5RINdd5K/Lk63Mwx8ta5chgoExRJVTBrHKCm5aTAsNN+TzK1pQh7dY0AJys56q2thY5OTkYM2YMlxomzXBchYdyFTxJcyfMhZpUMtGcQJdLW0cGA2WKGqHqcKG2LHW0BZPSstOuz6P36t4MkInIcLx1xtBrplWLQJdLW4cfA2WKGq4XGS0CP9dlqaOtBZwUIBcmF3p8HgyQiciIpM4Y0VSKoVWgyxKM8GGgTFHDXmt3qvVqLrUMrN5nUCu5BsiSaHseRETNEY2lGM3psRyKpBF5xkCZooJyAgQzyb4XDSEiiiW+FinRE2WgG+xxKpNGzCiHFgNl0j2tZ/pGcybZUy0y65CJKNZ5KsXQY2ZZ7TiDmdzXnC4a5B8GyhQVtPqYKVqXpfZVi8wAmYioibIUQ8+T/JTHGczkPraLCw8GyqRroWgHp7wwRUMmmbXI2ouLi8Ovf/1r3HbbbYiLi4v04ZBBcFzpR7RM8mvO5D7WKocHV+bTGFfm047WK/ApVzTS+0pOEtflTwFE1fHrmZHPHYocjit9UVudVG9LXzf3vc4IS1tzZT6iIGn113K0LSjCWmQiouaLhn7Lze2vzFrl0GKgTLqkZclFNC0owlrk8BBCoKysDOXl5eCHaqQVjit9ioZ+y80pwWCtcmgxUCbd0XIFvmhqA8da5PCpqalBhw4dMHz4cNTU1ET6cMggOK70LRr6LQcT8KrVKjNY1g4DZdIlLUouoqkNHPsiExGFnp77LTenBEPZV5llGNpioEy6olXJRTS0gZP+4mctMhFR+Oi533Jzu2CwDEN7DJRJN7QsuQD03QZO+oNgz217WItMRBQBnvotA4h4gBnsEtdsGac9BsqkG1qd4KHovawlZZlF2ZoypN2aBkCfAT0RkZGpZZb33LYnoqULzV3imstba4uBMumGvdbudIIHQ89t4Dy1fOu9urcuA3oioligzCyn3ZqGsjVlACJbjtHcJa7ZMk47DJRJF5QntJaT9/TwsZOvlm8AdHGcRESxSkrS9F7dWzcT/ZqzxDVrlbXDQJkiTosTWq9t4NjyTZ/i4uJw++234/rrr+dSw6QZjqvoJiUs9DTRL9jJfaxV1g7PZNKF9Cnp8vLSgZ7Q0hKl1s5W1B+u100Q6qnlG5efjjyr1Yq3334bxcXFsFqtkT4cMgiOK+OQsrnSe0tRu6KIXr+VySR/jyGvIA+5b+VG/fLWkcaMMkVUcyfe6bENHJefJiKKfnpZza85/ZVZq9x8DJQpYprbDk76C1lPbeC4/HR0EEKguroaNTU1XGqYNMNxZTx6Wc0v2BIM1io3HwNliqhga6iUfyE3t1OGVjyVWkQ6eCd3NTU1SElJQf/+/bnUMGmG48qY9LSaX6BBL2uVm4+BMkVEc0ouXFvARbr2ylepBRERRTc9rOYXbAkG+yo3DwNlCrvmlFzorQUcSy2IiGKHp9X8whWANqcLBmuVg8NAmcIu2I+C9NYCjqUWRESxRw+T/AItwWCtcvAYKFPYBbMCn1omOVIBKUstiIhiWyQn+QVTgtGczhmxjoEyhVUwK/DpqQUcSy2IiAiI7CS/YEowgi3biHUMlClsmvPRjx5awLHUgoiIlCI9yS+Y91SWYASGgTKFVaC1yc1dkEQLLLUwHovFgptuugnjxo2DxcJPAkgbHFexy9Mkv1DSogSDn4T6ZhLsiq6pyspKpKSkoKKiAq1btw75/ux2O4qLi9G9e3ddX5ilZaYDWQK0obwBRe2K5P/n1+SH/aSWjltp2JlhzCIbQLScOxRdOK5im+v7VjjeL+y1dhy474D8HutPAkdqqxrp9qry8UTgvPE3XmNGmUIumHZwkW4DZ6+1Ox23hKUWRETkSaTax7mWU/jaH9vF+Y+BMoVFIB/1RHLynlRmUZhciAP3H3A6bpZaEBGRL+FuH+daTnHgvgM+98d2cf5joEwhFWyNcSQm77l2tLAV2JD7Vq583Hr4eIq0UV1djbi4OPTq1QvV1dWRPhwyCI4rknhqH+dPtjcYUkeL3Ddz/QqAWavsPwbKFDLBllxEYvKep44WliQLLyBERBQw1/Zx/mZ7gyW9X/k7wY9LW/uHgTKFhDRBIJC/WJXBaqBLWweLHS2IiChUpPZxatneULWQC6RfMmuVfWOgTJpTnnT+rsAXicl7XDyEiIjCwTXbG44Wcv6UYLBW2TcGyqQptZNOj5P3uHgIERGFW7gWJ/G3BIO1yr4xUCZNBXvShWvyHkstiIgoksLVQs7fEgzWKnvHQJk0Za+1+11uAYR38h5LLYiISA/C2ULO3y4YrFVWZ4hAedGiRRg4cCBatWqF9PR0XH/99Thw4IDTNkIIPPnkk8jKykJSUhJGjRqFPXv2OG1TX1+PmTNnon379mjRogUmTJiA48ePh/OpRDXlSebvynvhmrzHUgtSslgsuOaaazBixAiunkaa4biiQHhqIadlKYa/JRisVfbMEIHy559/jgcffBDbtm3D5s2bcf78eYwdO9apj+XixYvx/PPP45VXXsGOHTuQmZmJq666Cj///LO8zezZs7F27VqsWbMGX375JaqqqjB+/HjY7RwwvgR6koVr8h5LLUhNYmIi1q9fjzfeeAOJiYmRPhwyCI4rCpRrC7lQTPLzpwSDtcqemYQQItIHobWysjKkp6fj888/x4gRIyCEQFZWFmbPno1HHnkEQFP2OCMjA8899xymT5+OiooKpKWlYcWKFZg0aRIA4OTJk8jOzsbGjRsxbtw4v/bt79rhWonE+uiqxxHAWvMN5Q0oalck/3/YmWEhyezunbrXLYscqn1R9NHLuUPGwnFFwQrle6O91t5U5vhf+TX5qsGwNAHfn4n4WorEeeNvvGaIjLKriooKAEDbtm0BAIcOHUJpaSnGjh0rb2O1WjFy5EgUFTUNyp07d6KxsdFpm6ysLPTp00fehtQFUmeslt0NReDKUgsiIoomnib5aSGQLhisVXYWF+kD0JoQAnPmzMEVV1yBPn36AABKS0sBABkZGU7bZmRk4MiRI/I2CQkJaNOmjds20s+rqa+vR319vfz/yspKAE1/HYWjZMNut8PhcESsPMS15CLn9RzAw6G4toEbbBuMhLYJmh67vdaO4unFKFtVBmtnK+oP1yNtShq6L+ne9Fcyy2gITUsNd+jQAUIInDhxIiyf/pDxcVxRc+Uuz0WXF7pge/p2AE3vq12e76JJkid3eS5yluSgeHoxCpMLkTYlDT2X93TaRu09PRyZ5UjEMv7uy3CB8m9+8xt8//33+PLLL93uM5lMTv8XQrjd5srXNosWLcLChQvdbj948CBatmzp51EHz+FwoLy8HCUlJTCbw/8BgagTSByfiLoNdUi8NhE/Hv/R722PnDkCnNHuWM7NP4e6DXXy/+sP1yN9azrMqWavx0Wxp6amBjU1NQDCd66S8XFckVak90rzRWZsT9+OxGsTkbo4tdmPK+oEylaVAQDKVpbBPM8MU6JzjKN8nz5YctDt/lCIRCxTVVXl13aGCpRnzpyJf/7zn/jiiy/QsWNH+fbMzEwATVnjDh06yLfbbDY5y5yZmYmGhgacPXvWKatss9kwbNgwj/t89NFHMWfOHPn/lZWVyM7ORrdu3cJWo1xSUoKcnJyw18Ptv30/ylaVIW1KGi7/+XKvf3UGsm0wGsobULrBOfOfNiUNuQNzNd0PGYNyom+4zlUyPo4r0sy6pvc1KbNct74OnZZ20iSz7JjskN+Pu+V0c38/Xnfh09mf+v2kmnnWWiRiGakCwBdDBMpCCMycORNr167FZ599hi5dujjd36VLF2RmZmLz5s3o168fAKChoQGff/45nnvuOQBA//79ER8fj82bN2PixIkAgFOnTmH37t1YvHixx31brVZYrVa32y0WS9h+2WazOaz7A5pOIuVfpT3f6ulx/w3lDX5vG+gxSPVUtpU2udQifWo6ct/M5axd8kg5/sJ97pBxcVyRlpLSkpA+JV1+f9uevl2T97feK3vD/pemCfhFrYrUJ+Bb4P6+HeL31HDHMv7uxxCT+R588EEUFBRg1apVaNWqFUpLS1FaWora2loATSUXs2fPxjPPPIO1a9di9+7duPPOO5GcnIzJkycDAFJSUnDPPfdg7ty5+OSTT/Ddd99h6tSp6Nu3L8aMGRPJp6dL/raSCVUbOGmywZ7b9nABESIiMqRQLkziraUr28VdYIiM8uuvvw4AGDVqlNPt77zzDu68804AwMMPP4za2lo88MADOHv2LAYPHoyPPvoIrVq1krd/4YUXEBcXh4kTJ6K2thajR4/GsmXLmBVQIa3Al/uW579sXSfvadXqRtnRomxNGdJuTUPZmjJ2tSAiIsORumEoOznZCmzIeSkn6Pc8KRCWWrqqUb7Hh7tdnJ4Yso9yJMVCH2Wp1MFbv2TXsghfvZX9oezVrCyzkNanj9WTmAJXXV0tT7QK17lKxsdxRaHk7T1Qi8f09Fhavo97PA72USaj8GcFPmUPRmlFoOaeXNJjqpVZAGCQTAExm80YMWIEBg4cGJFuMWRMHFcUSpYki2opRnOXvFa+p7s+Fpe2ZqBMQfBWt6Qsi5BOquYGsVw8hLSWlJSETz/9FO+++y6SkpIifThkEBxXFA5aLkyirEVWeyzWKjNQpgD4WoEvFBP31B5Tiww1ERFRtNIys6z2WMrMsesnw7GWVWagTH5x/fjF2/2uZRHBUmaS2dGCiIjoAi0zy8rHUpvcJ73vxuLy1gyUyW++Pn5R3t+csgh7rV01k8xSC9JKdXU1MjMzMWzYMKdFIoiag+OKws1TNjiYrK+UOYaAajAcq/XKDJTJJ39KLrzdH8y+tM5OE7k6ffo0zp49G+nDIIPhuKJwc80GH7jvgBzoBhPMegqGY7VemYEyeeWr5MJ18l5zcNIeERFR4KRscO6buU7vyYGWSbgGw572I7VljQUMlMkrb39BajV5z1OpBSftERER+ceSZHF6z5YEOtHPVwmGtEZCrNQqM1Amr6QV+FyDVq0m73krtYiVj3WIiIi0Ir1nN3ein6cSjFirVWagTB4p/2IMxeQ9lloQERFpr7mLk3grwYi1WmUGyqTK21+MzZ28x1ILIiKi0GtOCzlvJRixVKvMQJk8UvuLsbmT91hqQXpgNpsxYMAA9OnTh0sNk2Y4rkiPmrs4ibcuGLFQq8wzmdx4yhg3d/IeSy1IL5KSkrBt2zb89a9/5VLDpBmOK9KrYDPLamUWUrAcK7XKDJTJiad2cM2dvMdSCyIiosgJNrOsLLNwnbvkrZWcUTBQJjeeivSDnbzHpaiJiIgirzmZZbUMsq9WckbAQJlk3kouAp28J30Ew6WoSY9qamrQrVs3jB49GjU1NZE+HDIIjiuKBsFmlr1lkI1cgsFAmQB4LrkIZvKeFFjvuW0Pl6ImXRJC4MiRIzh58iSEEJE+HDIIjiuKFp4yy76CXLUMstHbxTFQJgDqBfvBTN5TBtZla8qQdmua/LPMJBMREemDWmbZ3/IJTyUYRmwXx0CZALivwBfo5D1PvZF7r+7NSXtEREQ6pMwsS3yVYngqwTBquzgGyuRxBT5/J+95640MwHAfwxARERlFMEteq5VgGLVdHAPlGKc2sAOZvMfeyERERNEt2CWvXecwGbFWmYFyDLPX2t0+QvE0qU8NeyMTEREZRyDt49RKMIxYq8xAOUYpyy2UH6H4O3mPvZEpmplMJuTl5aFbt24wmUyRPhwyCI4rMoJAMsueumAYqVaZgXIM8lRH5M/kPU+T9lhqQdEkOTkZ33//PTZs2IDk5ORIHw4ZBMcVGUWgC5MoYwrXtrLRnllmoByj1OqIfE3e8zVpj4iIiIxBLbNsr7W7Bb5q7WWNVKvMQDnGqE3U82fyHiftERERxRZlZjl9ajoO3HdAtaTCtQRDGU8wo0xRQ63kwtfkPU+lFpy0R9GspqYGl1xyCcaPH8+lhkkzHFdkRFIQnPtmrluJhSvXeMIItcoMlGOI8uMQqebowP0HPH5E4q3UIto/SqHYJoTA3r17cfDgQS41TJrhuCKjsiRZVGMI5bLXvrpoRWtmmYFyDJFW33OtOcp9K9ctQ8xSCyIiIlLytex1MF209I6BcoxwXX3PNYvsmklmqQURERG58mfZa7VPoplRJt1y/fjD28Q99kcmIiIib7wte62WjIvmWmUGyjFC7a8/JfZHJiIiIn95W/batQtGNNcqM1A2OGXrt2FnhqlO3GN/ZCIiIgqGt8VJ1OY6Rdsn1AyUDcy15KKoXZFbb0PlNhJmksnoTCYTOnXqhKysLC41TJrhuKJY5WlxEmUALWFGmXTFU8mFlEV2bQ/HSXsUC5KTk3Hw4EF88sknXGqYNMNxRbFMLbMsfZrtqUtGNGCgbFBSIFzxVQUAONUdu2aale3hou0jESIiItIHtcwyoJ60i5bMMgNlA1IGwtJgrT9cj8HHB3vsbcgAmYiIiJrLU2Y5vyZfjj2sXaxRE3cwUDYg19VzpK/bO27nhD0iALW1tRgyZAhuueUW1NbWRvpwyCA4roiaeOqGISfvDtWrLoGtRwyUDUj5cUbKFSkYfHywPDglnLBHsczhcOCbb77B7t274XA4In04ZBAcV0QXuGaWt3fc7pS8U3bH0DMGygbj2urNVmBzGpycsEdERETh4JpZrj9cj4HFA926Y+hZXKQPgLSj1upNIpVaMItMRERE4SJllm0rbbB2tmJH9x1O99tr7bAk6LdemRllA/H2VxlLLYiIiCgSXDPLEnMLM4raFWH/HfsjdGS+MVBW8dprr6FLly5ITExE//79UVhYGOlD8mn/7ftR1K4I5hZNv1LpK0stiIiIKNKUNcsSR3VTLX/ZyjKIOhGJw/KJgbKL9957D7Nnz8Zjjz2G7777Dvn5+bjmmmtw9OjRSB+aR6JOoGxVGYALg85R7ZC7WkRLCxYiIiIyrryCPOTX5LsFzHrGQNnF888/j3vuuQf33nsvevXqhRdffBHZ2dl4/fXXI31oHtl/ci+5YKkFkXft27dHmzZtIn0YZDAcV0TeWZIscimGklosoweczKfQ0NCAnTt34ne/+53T7WPHjkVRUZHqz9TX16O+/kLNTWVlJQDAbrfDbg/9L/3L1l9C1Dh/XDHYNhgJbRPCsn+iaJSYmIgTJ06gpKQEiYmJPFdIExxXRP6zpFiQNjmt6RNxC3D66tP4qsVXGF4xPCz79/f8ZKCscPr0adjtdmRkZDjdnpGRgdLSUtWfWbRoERYuXOh2+8GDB9GyZcuQHKfEXmp3C5ITr03EkTNHgDMh3TVR1HM4HCgvL0dJSQnMZn64RtrguCLyn2WBBe1vb4/TV58G0FQ2ur9wPyyZoS8Zraqq8ms7BsoqTCaT0/+FEG63SR599FHMmTNH/n9lZSWys7PRrVs3tG7dOqTHie7A6eTTEDUC5hZmDCkdwnpkIj/Z7XaUlJQgJycHFgvPG9IGxxVRgLoDXyZ/KccyPfN7hmW3UgWALwyUFdq3bw+LxeKWPbbZbG5ZZonVaoXVanW73WKxhOUieUXlFdhfuB8983vyokzkp9raWlx99dWora3Fp59+GvJPfyg2cFwRBScSsYy/+2GgrJCQkID+/ftj8+bNuOGGG+TbN2/ejOuuuy6CR+ZdOD6iIDISh8OBL774Qv6eSAscV0TB02ssw0DZxZw5czBt2jQMGDAAQ4cOxZtvvomjR49ixowZkT40IiIiIgojBsouJk2ahDNnzuCpp57CqVOn0KdPH2zcuBGdOnWK9KERERERURgxUFbxwAMP4IEHHoj0YRARERFRBLF3DRERERGRCgbKREREREQqWHpBRDEpOTkZQgjfGxIFgOOKyFgYKBNRzGnRogUqKytRXFyMFi1aRPpwyCA4roiMh6UXREREREQqGCgTEREREalg6QURxZy6ujrceOONqK6uxsaNG/kxOWmC44rIeBgoE1HMsdvt+OCDD+TvibTAcUVkPCy9ICIiIiJSwUCZiIiIiEgFA2UiIiIiIhUMlImIiIiIVDBQJiIiIiJSwa4XGpOWLq2srAzL/ux2O6qqqlBZWQmLxRKWfRJFu+rqavn7cJ2rZHwcV0TBiUQsI52jvpacNwkuSq+p48ePIzs7O9KHQUREREQ+HDt2DB07dvR4PwNljTkcDpw8eRKtWrWCyWQK+f4qKyuRnZ2NY8eOoXXr1iHfH5FR8NyhUOC4IgpcJM4bIQR+/vlnZGVlwWz2XInM0guNmc1mr3+ZhErr1q15USYKAs8dCgWOK6LAhfu8SUlJ8bkNJ/MREREREalgoExEREREpIKBcpSzWq144oknYLVaI30oRFGF5w6FAscVUeD0fN5wMh8RERERkQpmlImIiIiIVDBQJiIiIiJSwUCZiIiIiEgFA2UiMrxly5bBZDLBZDLhs88+c7tfCIGcnByYTCaMGjUq7MdH0U0aX998843T7adPn8aAAQPQsmVLbN68OUJHR0TNwUA5Cinf9NX+HT58ONKHSKRLrVq1wtKlS91u//zzz3Hw4EG0atUqAkdFRnT8+HHk5+fjxx9/xMcff4yrrroq0odEpDvREM9wZb4o9s4776Bnz55ut3fo0CECR0Okf5MmTcLKlSvx6quvOq3+tHTpUgwdOhSVlZURPDoyiuLiYowZMwaNjY34/PPP0bdv30gfEpGu6TmeYaAcxfr06YMBAwZE+jCIosZtt92GlStXYvXq1Zg+fToAoKKiAu+//z5efvllvPjii5E9QIp6u3btwrhx49CyZUts2bIFXbt2jfQhEemenuMZll4QUcxo3bo1br75Zrz99tvybatXr4bZbMakSZMieGRkBF9++SVGjRqF9PR0fPnllwySiQyAgTIRxZS7774bX3/9Nfbs2QMAePvtt3HLLbewPpma7be//S0A4NNPP9XFR8ZE1HwMlIkopowcORLdunXD22+/jf/85z/YsWMH7r777kgfFhnAhAkTUFFRgdmzZ8Nut0f6cIhIA6xRJqKYYjKZcNddd+Hll19GXV0devTogfz8/EgfFhnAggULcNlll+Gpp56Cw+FAQUEBLBZLpA+LiJqBGWUiijl33nknTp8+jSVLluCuu+6K9OGQgSxcuBBPPPEE1qxZg8mTJ+P8+fORPiQiagZmlIko5lx00UWYP38+9u/fjzvuuCPSh0MG8+STT8JsNuOJJ56AEAKrVq1CXBzfbomiEc9cIopJzz77bKQPgQzsD3/4A8xmMxYsWAAhBFavXs1gmSgK8awlIiIKgccffxxmsxmPPfYYHA4H1qxZg/j4+EgfFhEFwCSEEJE+CArMsmXLcNddd2HHjh26bdBNRERE5E00xDMMlImIiIiIVLDrBRERERGRCgbKREREREQqGCgTEREREalgoExEREREpIKBMhERERGRCgbKREREREQqGCgTEREREalgoExERKRz//znP/Hkk0/iyJEjkT4UopjCQJmIImbUqFEwmUyRPoyo8+STT8JkMuGzzz6L9KHohpHH0tdff41bbrkFp0+fRqdOnSJ9OEQxhYEykQHt3LkT99xzD7p3744WLVogKSkJ3bp1w7Rp07B58+ZIHx4R+am8vBwTJ07Er371K7z88suRPhyimBMX6QMgIu04HA7MmzcPL7zwAuLi4vCLX/wCEyZMQHx8PH788Uf861//QkFBAZ566iksWLAg0oeLd999FzU1NZE+DDIAI44lIQRuv/12XHTRRVi1ahXMZua2iMKNgTKRgTz++ON44YUXcNlll+Fvf/sbunXr5nR/bW0tXnnlFZw5cyZCR+js4osvjvQhkEEYcSyZTCZs2LAh0odBFNP45ymRQZSUlGDx4sVo164dNm3a5BYkA0BSUhLmz5+PhQsXyrf98MMPePjhh3H55ZejXbt2SExMRI8ePfC73/0OVVVVbo8h1YLW19fj97//PS6++GIkJSWhf//++PjjjwEAP//8M2bNmoWLLroIiYmJGDp0KL755huPj6W0bNkymEwmLFu2DJ988gmuuOIKtGjRAu3atcMdd9zhMcjfsGEDrrzySqSkpCApKQmXXXYZXnzxRdjt9oBex0OHDuHee+/FxRdfDKvVig4dOuDOO+9UnURlMpkwatQolJWV4e6770Z6ejqSkpIwZMiQgOuHGxoa8Pzzz+Pyyy9HixYt0KpVK+Tn5+Of//xnQI+jxfP69ttvcfPNN8vbZmRkYOjQoXj22WedtuvcuTM6d+6Ms2fP4r777kNGRgaSkpIwaNAg1eM+efIknnjiCQwZMgTp6emwWq3o3LkzHnjgAdhsNo+vy0svvYRBgwahVatWaNmyJfLy8jBnzhycPXtW3s5TjfL58+fxwgsv4NJLL0VSUhJSUlJw5ZVX4l//+pffr91nn30Gk8mEJ598Elu3bsW4ceOQmprqtD8hBN5++20MHz4crVu3RnJyMgYMGIC3335b9TGFEFi+fDlGjBiB1NRUJCcno3v37pgxYwaOHj0qb3fnnXfCZDLh8OHDqsfzxRdfYOTIkWjZsiXatm2LyZMn4/jx4277k35X586dw6xZs5CdnY24uDgsW7ZM3ibQc+j777/H1KlT0bFjR3lMXX311Vi/fr3Tdlr8DogiRhCRITz22GMCgPj9738f0M8tWrRItG3bVtx0003it7/9rXjooYfE4MGDBQAxZMgQ0dDQ4LT9yJEjBQBx3XXXia5du4oHH3xQ3H333cJqtQqr1Sp27twpBgwYIPr06SNmzZolbrvtNmE2m0Xbtm1FRUWF6mMpvfPOOwKAuPHGG0VCQoK46aabxNy5c8XAgQMFADF8+HC35/Diiy8KAKJt27ZixowZYu7cuaJHjx7y4zgcDr9ei23btomUlBQRFxcnbrjhBjF//nxxyy23iLi4OJGeni4OHjzotD0Acemll4ru3buL/v37i9mzZ4vJkycLi8UiEhISxH/+8x+/9ltXVydGjRolAIh+/fqJmTNnihkzZojs7GwBQPz5z3922v6JJ54QAMSWLVs0f17fffedsFqtIjk5Wdx2223id7/7nZgxY4bIz88XXbt2dXrcTp06iQ4dOojLL79c9OrVS8yfP1/cd999olWrVsJkMomCggKn7VevXi1atGghJkyYIGbNmiXmzp0rfvGLXwgAomvXruLcuXNO29fW1ooRI0YIAKJ79+5i5syZYt68eeK6664TSUlJ4rvvvpO3VRtLDodD3HjjjQKA6NGjh5g7d66YMWOGaNu2rQAgXnrpJb9evy1btggA4qqrrhLx8fFi7NixYv78+WLSpEnyfiZPnizvZ/r06WLmzJmiZ8+eAoCYO3eu23FNmjRJABAXXXSRmDFjhnj44YfFxIkTRWpqqli7dq287R133CEAiEOHDrkdz7hx40RCQoK44YYbxKOPPirGjRsnAIjs7GxRWlrq9rvKzMwU/fr1Ezk5OeLXv/61eOihh8TGjRuFEIGfQ3//+9+F1WoV8fHx4sYbbxSPPvqouOeee0SfPn3Eddddp/nvgChSGCgTGYQUaH388ccB/dzx48dFfX292+0LFy4UANyCHSkgGT58uKiqqpJvX7NmjQAgUlNTxS233CIaGxvl+5577jkBQDz//POqj6UkBcpxcXHiyy+/lG8/f/68/By3bt0q337w4EE54Dt69Kh8e319vfz4K1as8Pk6NDQ0iM6dO4tWrVqJXbt2Od1XWFgoLBaLGD9+vNPtAAQA8cADDwi73S7f/pe//EUAENOnT/e5XyGE+P3vfy8AiCf/f3t3H9PU9f8B/P2T1loeCsRQBOUhjq7DCAMlGwsz5WlkRAU3F6LbFOJcnJhpIm7Zlm2osBkfyowZW3Q6p8tmZhwZEzN0Y4EhA5QVHDorSyCiXaxQoSVQtMjn98c3t+PSC2031G/8fl5/wTn3nnvOPeeGTw/nnm7dKgpIbDYbJSUl0fTp08lkMjnTvQmUvW3X5s2bCQBVVla6lNXb2yv6PSoqigBQenq66APV5cuXSalUUlBQENlsNme62WymgYEBl3KPHDlCAKi0tFSU/sYbbxAAWrVqFY2MjIjy+vv7RWVJjaWjR48SANLpdKIxfu3aNVKr1SSXy6mzs9OlPuMJgSkAOnTokEv+gQMHCAC98soronF/+/ZtWrp0KQGglpYWZ3p5eTkBoIyMDBoaGhKVNTQ0RBaLxfn7ZIEyADp48KDofOG5XbNmjShd6KusrCyXa3r7DJnNZvL39yc/Pz8yGAwu9+PatWvOn6eqDxh7UDhQZuwhIcxeGY3GKSnPYrEQACooKBClC384a2trRekjIyMkl8sJAF29elWU193dTQAoPz9fsqyxhEB59erVLnUS8vbt2+dM2759OwGgnTt3uhzf2NjoDEjcqaioIABUUlIimf/888/TtGnTRLPiAMjPz88l+HM4HCSTyWjBggVur3v37l0KDg6mmJgYyZnv77//3mVW2ZtA2dt2CYHymTNn3JYtBF8NDQ0ueRs2bPD4Q8ro6CipVCpKTU11po2MjJBKpaLAwEC6deuW2zKkxpIwW93c3Oxy/I4dOya9L2MJgWliYqJkfnx8PPn5+ZHdbnfJ+/33311mlefNm0c+Pj7U0dHh9tqTBcpardZlzAwNDVFISAgplUpRYCr01YULF1yu4e0ztGvXLgJA77//vtv6T1UfMPag8Mt8jP2PIyIcPnwYX3zxBS5evAir1YrR0VFn/l9//SV5XmJiouh3Hx8fqNVqDA4OurxYFRYWBgAwmUwe12vBggUuaXPmzAEA9Pf3O9NaW1sB/GeN6njJyclQKpVoa2tze72mpiYAgNFoxNatW13yb9y4gdHRUXR0dCApKcmZrtFo4O/vLzpWJpMhNDRUVM+JXLlyBX19fQgPDxetHRf09PQ46/VPeNuuF154AXv37sWyZcuQl5eHZ555Bk8//fSEL8vJ5XIkJye7pC9atAjl5eVoa2vDyy+/7EyvqKjA/v37YTAY0NfXJ1r/OnasGY1G2Gw2ZGZmIjg4+B+1vbW11blmejxhvHgyNgRS5QwNDaG9vR3h4eEua7gBwOFwAPi7/wYHB/HHH38gJiYGGo3G42tLSUlJcVmXLbwvUF1djY6ODsyfP9+ZN2PGDMTFxbmU4+0zdO7cOQBAVlaW2zpOdR8wdr9xoMzYQ2LWrFkwGo0wmUzQarUen7dx40Z8/PHHiIiIQE5ODsLCwqBQKAAA27Ztw+3btyXPU6lULmkymQyBgYGS6cDfQYMnJitnbHBls9kAAKGhoZLlqNVqjwL0W7duAQC++uqrSY8bHBx0W0+hrp68SChc99KlS7h06ZLH1/WUt+166qmn8PPPP2PHjh04duyY82WvhQsXYvfu3UhLSxOdN3PmTMlty4T+sFqtzjS9Xo8tW7YgJCQEWVlZmDNnDpRKJQBg7969orEmfMiYPXu2F60Vs9lsiIiIkMybNWuWS/3ckRpjfX19ICKYTCbJDzoC4f5ORbsEarV60nqOb5tarZZ84dHbZ8ibNkx1HzB2v3GgzNhDIiUlBbW1taipqUF6erpH59y8eRPl5eWIj49HY2MjfH19nXk3btyY9A//fwshYDebzZLfWnbz5k3JoH6ick6ePIklS5ZMbSU9uO7y5ctx4sSJe1a+N+3S6XTQ6XSw2+1obm7GyZMn8cknn2Dx4sVob28X7ahisVgwOjrqEiybzWYAf3+QGBkZQUlJCcLDw9HW1oaQkBDnsUSEXbt2ic4PCgoC4N1/IcZTqVTOeownpHsyNgRSQaZw/sKFCyV3dhlPuB//pl2CiXYKGX/vBRN9c6G3z9DYvomOjp60jlPdB4zdb7w9HGMPiYKCAvj4+ODAgQPOf9dPRJi56+zsBBEhMzNTFCQDQH19/T2r61QSloBIbcd27tw52O12JCQkuC3nySefBAA0NjZOZfXcio2NhUqlQktLi1cz7p76N+1SKpVITU2FXq/HO++8A7vd7twCUOBwOJzLO8YSxo9w73t7e2G1WpGcnCwKkgGgpaUFdrtdlKbVaqFSqXD+/HnRNnDeSExMhN1udy4VGKuurk5Uv38qICAAsbGxuHz5skdLbYTt7bq6uvDnn3/+q2s3NDSAiERpdrsdv/32G5RKJR599FGPyvH2GRKWUZw5c8ajsu91HzB2L3GgzNhDIiYmBm+++SZ6e3uRnZ2Nrq4ul2OGh4dRVlbmXKsqzB79+uuvonXJ169fx1tvvXVf6v1vvfjii5DJZCgrKxOtcXU4HM42FBQUuC0nNzcXkZGRKCsrwy+//OKS73A4cPbs2Smrt0Amk2H9+vW4evUqtmzZIhksX7x4ccLZQ3e8bVd9fb3zX/FjCbN/wlKJsd577z1RvY1GIz7//HMEBgYiNzcXAJx7TBsMBtE36PX19eH11193KVMmk2HdunWwWq3YtGmTyzIWq9Uquc/3WPn5+QCAt99+W1Q/k8mEsrIyyGQyvPTSS5OW4YmNGzdiaGgIr776quQSma6uLtE+yBs2bMDdu3dRWFjo8gFheHjYuVzGnStXrrjs07x792709PRg5cqVmD59ukflePsM5efnw9/fH3q9XnJ98djZ8vvVB4zdK7z0grGHSGlpKYaHh/HRRx9Bq9UiPT0d8+fPh1wuR1dXF3766SdYLBaUlpYC+M9LdsuXL8e3336LpKQkZGRkwGw2o6qqCunp6ejs7HzALXLvkUcewc6dO1FUVIT4+Hjk5eXBz88PVVVVMBqNyM3NFb1MNhGFQoETJ04gOzsbOp0OGRkZzhehuru7UV9fj5kzZ/7jl+oms23bNhgMBuzbtw+nTp2CTqdDSEgITCYT2tvbceHCBTQ2Nk64JnUy3rZLr9fjxx9/RFpaGubOnYsZM2bAYDCgpqYGMTExeO6550Tlh4WFob+/HwkJCVi8eDGsViuOHTuG4eFhfPbZZwgICAAATJs2DYWFhdDr9Xj88cexdOlS2Gw2/PDDD4iKikJ4eLhL3bdv346mpiZ8+eWXaGpqQnZ2NhQKBTo7O1FdXY2zZ89OOhu5atUqVFRUoLKyEvHx8ViyZAkGBwdx/PhxWCwW6PV6zJ071+t7Ot66devQ1NSEI0eOoKGhAZmZmQgPD4fZbIbRaERzczO+/vpr5zKF9evXo66uDsePH4dGo0FOTg5UKhW6u7tx+vRpHDp0CMuWLXN73aysLBQWFuLUqVN47LHHYDAYcPr0aURERODDDz/0uP7ePkNqtRpHjx7FihUr8MQTTyAnJwdarRa9vb1obm5GdHQ0vvvuOwD3rw8Yu2ce6J4bjLF74vz587RmzRqKiYkhpVJJCoWCoqOjaeXKlS7bfg0MDFBRURFFR0eTQqEgjUZDJSUldOfOHef+p2NJbcMliIqKoqioKMk8T8sStoA7fPiwSxnCtljFxcUueZWVlaTT6SggIIAUCgXFxcWRXq8X7WvrievXr9OmTZtIo9GQQqEglUpFsbGxtHbtWqqpqXHbJsFk90LKyMgI7d+/n1JSUkilUpFCoaDIyEh69tln6dNPPxXtWe3tF454067q6mpavXo1abVaCggIIH9/f5o3bx69++67kvsoR0VFkcViobVr15JarSaFQkFJSUmS+zDfuXOHPvjgA2cdIiMjafPmzTQwMDDh/RoeHqY9e/ZQQkICKZVKZ32Kioqor6/PedxE49LhcNCePXsoLi6OFAoFBQQEkE6nk6zfRCYbd2N98803lJmZScHBwSSXy2n27NmUmppKer2eenp6RMeOjo7SwYMHKTk5mfz8/MjX15c0Gg299tpror2MJ9serri4mOrq6mjRokXk6+tLQUFBtGLFCtH5Ak/Go7fPUGtrK+Xl5VFoaCjJ5XIKCwuj7OxsqqqqEh03FX3A2IPyf0TjFjgxxhhjHhBmSMcuK2D3Xm1tLdLS0lBcXCy55R9jbOrwGmXGGGOMMcYkcKDMGGOMMcaYBA6UGWOMMcYYk8BrlBljjDHGGJPAM8qMMcYYY4xJ4ECZMcYYY4wxCRwoM8YYY4wxJoEDZcYYY4wxxiRwoMwYY4wxxpgEDpQZY4wxxhiTwIEyY4wxxhhjEjhQZowxxhhjTAIHyowxxhhjjEn4f5Ms4vMToqZaAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 800x600 with 1 Axes>"
       ]
@@ -337,18 +374,11 @@
     "#Graficamos la disperción\n",
     "plot_dispersion(disp)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "base",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },