{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Transformación pasabanda\n", " \n", "\n", "#### Por Mariano Llamedo Soria" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Resumen \n", "\n", "En este documento presentamos el uso de las siguientes funciones para el análisis de la transformación pasabanda de funciones transferencia:\n", "\n", "\n", "* Análisis de la respuesta en frecuencia: [analyze_sys](https://pytc2.readthedocs.io/en/latest/autoapi/pytc2/sistemas_lineales/index.html#pytc2.sistemas_lineales.analyze_sys), [bodePlot](https://pytc2.readthedocs.io/en/latest/autoapi/pytc2/sistemas_lineales/index.html#pytc2.sistemas_lineales.bodePlot), [pzmap](https://pytc2.readthedocs.io/en/latest/autoapi/pytc2/sistemas_lineales/index.html#pytc2.sistemas_lineales.pzmap), [pretty_print_bicuad_omegayq](https://pytc2.readthedocs.io/en/latest/autoapi/pytc2/sistemas_lineales/index.html#pytc2.sistemas_lineales.pretty_print_bicuad_omegayq), [GroupDelay](https://pytc2.readthedocs.io/en/latest/autoapi/pytc2/sistemas_lineales/index.html#pytc2.sistemas_lineales.GroupDelay)\n", "* De presentación algebraica: [print_latex](https://pytc2.readthedocs.io/en/latest/autoapi/pytc2/general/index.html#pytc2.general.print_latex), [a_equal_b_latex_s](https://pytc2.readthedocs.io/en/latest/autoapi/pytc2/general/index.html#pytc2.general.a_equal_b_latex_s), [pretty_print_SOS](https://pytc2.readthedocs.io/en/latest/autoapi/pytc2/sistemas_lineales/index.html#pytc2.sistemas_lineales.pretty_print_SOS), [pretty_print_lti](https://pytc2.readthedocs.io/en/latest/autoapi/pytc2/sistemas_lineales/index.html#pytc2.sistemas_lineales.pretty_print_lti)\n", "* De manipulación de sistemas lineales: [tf2sos_analog](https://pytc2.readthedocs.io/en/latest/autoapi/pytc2/sistemas_lineales/index.html#pytc2.sistemas_lineales.tf2sos_analog), [parametrize_sos](https://pytc2.readthedocs.io/en/latest/autoapi/pytc2/sistemas_lineales/index.html#pytc2.sistemas_lineales.parametrize_sos)\n" ] }, { "cell_type": "markdown", "metadata": { "jp-MarkdownHeadingCollapsed": true }, "source": [ "## Introducción\n", "\n", "A esta altura del curso, hemos diseñado filtros pasabajo normalizados de orden arbitrario, dependiendo de las restricciones de módulo o retardo impuestas por el problema. Extendemos el problema de diseñar *cualquier* tipo de función transferencia (pasa-alto, pasabanda, etc) al siguiente procedimiento:\n", "\n", "1. Identificar el tipo de filtro requerido por la plantilla original (atenuación o módulo de la transferencia)\n", "2. Convertir la plantilla del filtro, mediante el núcleo de transformación adecuado, a una plantilla pasabajo.\n", "3. Diseñar una función transferencia pasabajo normalizada.\n", "4. Aplicar un núcleo de transformación adecuado.\n", "\n", "Este documento se centra en analizar el comportamiento del núcleo de transformación **pasabanda normalizado**. Para ello recordamos su expresión:\n", "\n", "$$ K_{bp}(s) = Q_{bp} * \\frac{s^2 + 1}{s} $$\n", "\n", "Usamos $p$ como variable compleja en el dominio del prototipo pasabajo (2do paso) solo para señalar que *no* se trata de la misma variable, ni transferencia. Luego al llegar al paso 4, podemos obtener la transferencia pasabanda como\n", "\n", "$$ T_{bp}(s) = T_{Lp}(p)\\Big\\vert_{p = K_{bp}} = (T_{Lp1}(p)\\cdot \\prod_{k=1}^{N} T_{Lp2_k}(p))\\Big\\vert_{p = K_{bp}}$$\n", "\n", "También se sabe que para una transferencia $T(s)$ de orden arbitrario, la misma se puede expresar como el producto de $N$ secciones de segundo orden (SOS), y eventualmente en el caso que el orden fuera impar, una sección de primer orden. Por este motivo en este documento analizaremos el comportamiento del núcleo exclusivamente para secciones de primer y segundo orden. El comportamiento para un orden arbitrario, se podrá deducir del comportamiento para cada sección individual.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Prototipo pasabajos de primer orden\n", "\n", "Sea la función transferencia de un *filtro prototipo pasabajo*\n", "\n", "$$ T_{Lp} = \\frac{k.a}{p + a}, $$\n", "\n", "siendo $a$ un número real que indica la pulsación de corte, y $k$ la ganancia para $p = 0$, entonces \n", "\n", "$$ T_{bp}(s) = T_{Lp}(p)\\Big\\vert_{p = K_{bp}} $$\n", "\n", "$$ T_{bp}(s) = \\frac{a}{ Q_{bp} * \\frac{s^2 + 1}{s} + a} $$\n", "\n", "\n", "$$ T_{bp}(s) = \\frac{s . k . \\frac{a}{Q_{bp}} }{s^2 + s . \\frac{a}{Q_{bp}} + 1} $$\n", "\n", "Como se observa, se llega a un filtro pasabanda normalizado donde se puede apreciar:\n", "\n", "* El centro de la banda de paso se encuentra en $\\omega_0 = 1$\n", "* La ganancia en el centro de la banda de paso depende de $k$\n", "* El Q del pasabanda resultante estará dado por $Q = \\frac{Q_{bp}}{a}$\n", "\n", "En el siguiente ejemplo se mostrará cómo llegar a estos resultados a partir de las herramientas de simulación simbólica y numérica." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# Módulos externos\n", "\n", "import sympy as sp\n", "from sympy.abc import s\n", "\n", "import matplotlib as mpl\n", "import matplotlib.pyplot as plt\n", "\n", "fig_sz_x = 13\n", "fig_sz_y = 7\n", "fig_dpi = 80 # dpi\n", "\n", "fig_font_size = 11\n", "\n", "mpl.rcParams['figure.figsize'] = (fig_sz_x, fig_sz_y)\n", "mpl.rcParams['figure.dpi'] = fig_dpi\n", "plt.rcParams.update({'font.size':fig_font_size})\n", "\n", "import numpy as np\n", "import scipy.signal as sig\n", "from IPython.display import display, Markdown" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# Ahora importamos las funciones de PyTC2\n", "\n", "from pytc2.sistemas_lineales import analyze_sys, parametrize_sos, pretty_print_lti, pretty_print_bicuad_omegayq, tf2sos_analog, pretty_print_SOS\n", "from pytc2.general import print_latex, print_subtitle, a_equal_b_latex_s\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Con todas las herramientas cargadas, se continúa a la definición de las funciones simbólicas con las que se realizarán las primeras pruebas:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/markdown": [ "#### Prototipo de primer orden" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/latex": [ "$\\displaystyle T(s) = \\frac{a k}{a + s}$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/markdown": [ "#### Pasabanda obtenido" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/latex": [ "$\\displaystyle T(s) |_{s = \\frac{Q_{bp} \\left(s^{2} + 1\\right)}{s} }=\\frac{ a k s}{Q_{bp} s^{2} + Q_{bp} + a s}$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Comienzo de la simulación\n", "\n", "Q_bp, a, b, k = sp.symbols(\"Q_bp, a, b, k\", complex = False)\n", "\n", "############################################\n", "# Definicion de las funciones transferencia. \n", "\n", "H1 = k * a/(s + a)\n", "\n", "# nucleo de transformación pasabanda\n", "Kbp = Q_bp * (s**2 + 1) / s\n", "\n", "\n", "# Análisis de la transformación pasabanda para una transferencia de primer orden.\n", "H1bp = sp.simplify(sp.expand(H1.subs(s, Kbp)))\n", "num, den = sp.fraction(H1bp)\n", "num = sp.Poly(num,s)\n", "den = sp.Poly(den,s)\n", "num1_bp, den1_bp, w1_on, Q1_n, w1_od, Q1_d, K1_bp = parametrize_sos(num, den)\n", "\n", "print_subtitle('Prototipo de primer orden')\n", "\n", "print_latex('$ T(s) = ' + sp.latex(H1) + '$')\n", "\n", "print_subtitle('Pasabanda obtenido')\n", "\n", "print_latex(a_equal_b_latex_s('$ T(s) |_{s = ' + sp.latex(Kbp) + ' }', '\\\\frac{ ' + sp.latex(num1_bp.as_expr()) + '}{' + sp.latex(den1_bp.as_expr()) + '}' ))\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "luego de esta pequeña demostración de las capacidades de manejo simbólico se realizará una simulación numérica\n", "\n", "### Análisis numérico\n", "\n", "Ahora se procede a cargar los coeficientes del prototipo pasabajos y se usarán las funciones de transformación provistas en *scipy.signal*. Para ello se define $Q_{bp}$" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "#### Prototipo de primer orden" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/latex": [ "$\\displaystyle T_{lp}(s)=\\frac{1}{s + 1}$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/markdown": [ "#### Pasabanda obtenido para Q=5 (coeficientes de los polinomios)" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "[0.2 0. ]\n", "[1. 0.2 1. ]\n" ] } ], "source": [ "# coeficientes de la transferencia de primer orden T1\n", "T1_num = np.array([1])\n", "T1_den = np.array([1, 1])\n", "\n", "# Q de la transformación\n", "Q_bp = 5\n", "\n", "# núcleo LP-BP\n", "num_pbanda, den_pbanda = sig.lp2bp(T1_num, T1_den, bw = 1/Q_bp)\n", "\n", "print_subtitle('Prototipo de primer orden')\n", "\n", "print_latex(a_equal_b_latex_s('$ T_{lp}(s)', sp.latex( 1/(s + 1) )))\n", "\n", "print_subtitle('Pasabanda obtenido para Q={:d} (coeficientes de los polinomios)'.format(Q_bp))\n", "\n", "print(num_pbanda)\n", "print(den_pbanda)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![nada](./img/nada.png)\n", "\"Homero\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Como se observa, la visualización de los coeficientes no solo es complicada de interpretar, sino que tampoco escala bien con la complejidad y orden de la función. Para ello se presenta otra alternativa implementada en *pytc2*" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "#### Como cociente de polinomios" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/latex": [ "$\\displaystyle T_{bp}(s)=\\frac{s \\,\\, 0.2 }{s^2 + s \\,\\, 0.2 + 1 }$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "print_subtitle('Como cociente de polinomios')\n", "\n", "# forma un poco más clara\n", "print_latex(a_equal_b_latex_s('T_{bp}(s)', pretty_print_lti(num_pbanda, den_pbanda, displaystr=False)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![nada](./img/nada.png)\n", "\"Homero\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Esta alternativa está mucho más cerca de la forma matemática en que se suele interpretar, sin embaro, aprovechando las posibilidades algebraicas de *SymPy*, podemos reordenarlo" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "#### Factorizado con $\\omega_0$ y $Q$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/latex": [ "$\\displaystyle T_{bp}(s)=\\frac{s\\, 1\\,\\cdot \\frac{ 1}{ 5}}{s^2 + s \\frac{ 1}{ 5} + 1^2}$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print_subtitle('Factorizado con $\\omega_0$ y $Q$')\n", "\n", "# esta es la que va\n", "print_latex(a_equal_b_latex_s('T_{bp}(s)', pretty_print_bicuad_omegayq(num_pbanda, den_pbanda, displaystr=False)))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "De esta manera la comparación se ve facilitada, si recordamos que al transofrmar una transferencia prototipo de primer orden se obtiene una SOS\n", "\n", "$$ T_{bp}(s) = \\frac{s . k . \\frac{a}{Q_{bp}} }{s^2 + s . \\frac{a}{Q_{bp}} + 1} $$\n", "\n", "\n", "entonces los parámetros serán\n", "\n", "* $ \\omega_0 = 1 $\n", "* $Q = \\frac{Q_{bp}}{a} = Q_{bp} = 5$\n", "* $ K = 1 $\n", "\n", "![nada](./img/nada.png)\n", "\"Homero\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Confirmamos que llegamos a la función transferencia pasabanda de $\\omega_0=1$ y $Q=5$ como se definió en el núcleo de transformación.\n", "\n", "### Análisis de la respuesta en frecuencia\n", "\n", "Continuando con el análisis numérico de este pasabanda, analizaremos la respuesta en frecuencia" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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KvV5f6zomAQ3g7++PjIyMJikrOzsbgYGBTVKWXFgH++Doddi0aROEEJgwYYLcodwSRz8OAOtgL5q6DmFhYXWuc+x0iYiIiBqNSQAREZGTYhJARETkpDgmgIioBTGbzRBCNPq1JpOpiSOyLWergyRJlkdjMAkgImoBKisrcenSJRgMhkaXYTKZUFhY2HRBycAZ6yBJEnx8fBAQENDgqwqYBBARtQCXLl2Cp6cn/Pz8Gv2r0Gg0wsXFsU8LzlgHg8GA7OxspKWloV27dg3al2O/U0REBLPZDIPBAD8/v1s6AZrNZiiVyiaMzPacsQ5KpRKhoaE4e/Zsg+cY4MBAIiIHVz0GoLEtAOT4qo99Q8eDMAkgIiJyUkwCiIic0NLtZ7H5RFa922w+kYWl28/aKCLH0L9/f3zxxRdyh9FkmAQQETmh6EBPPLEysc5EYPOJLDyxMhHRgZ5Nsr9hw4bB1dUVWq0Wnp6eiIuLw86dOy3rExISoFAoLOvbt2+Pt956q9ayUlJSMHnyZAQGBsLHxwdDhw7FoUOHLOsvXLiAMWPG4Pbbb8ekSZOQl5fXJHW4GWfOnMGUKVPg4+MDrVaLgQMHYsuWLY0q65VXXoFKpYJWq7U8du/e3aTxMgkgInJCY7sG4d1ZPWtNBKoTgHdn9cTYrkFNts93330XOp0ORUVFePjhh3HXXXfBaDRa1gcEBECn06GkpARfffUVXn75ZWzevLlGOYWFhbj99ttx4sQJ5OXlYdq0aRg/fjxKS0sBAE8//TSeffZZbNq0CZMnT8Y///nPBsd6bVw36+LFixg4cCCioqJw7tw55OTkYMGCBZg2bRrWr1/f4PIAYOrUqdDpdJbH4MGDG1VOXZgEEBE5qdoSgeZKAK6lUCgwZ84cFBQU4PLly7VuM2jQIHTt2hVJSUk11vXt2xcPPfQQWrduDaVSib/85S8oLS3F6dOnAQCnTp3CwIEDAQADBgzAyZMnAVTNpfD0008jLCwMgYGBmDdvHoqKiizlSpKE//znP+jUqRN8fHwAACtXrkT79u3RqlUrPPXUU/XW65VXXkGfPn3w5ptvonXr1nB3d8d9992H5557Dn/9618b/D7ZApMAIroh9h+3XNcmAs+sTW72BAComgznyy+/RHh4OEJCQmqsF0Jg165dSE5ORu/evW9Y3sGDB2E2mxEVFQUA6Ny5M/bs2QMA2LNnD7p06QIAeP311/Hrr7/iwIEDSElJQX5+Pv785z9blfXDDz9g165duHr1Kk6fPo37778fn376KXJycuDj42PV7XC9LVu2YMaMGTWWz5w5ExcuXMDZs1XfjzvuuAM+Pj61Prp372712vj4ePj5+aFz58544403YDabb/h+NIhwAB988IGIjY0VarVazJw5s95tExISRNeuXYWbm5uIi4sTiYmJNcoKCQkRHh4eYsqUKSI/P/+m4wgNDW1U/LXJyspqsrLkwjrYB1vU4ZfkK6LTi/Hil+QrjVpfn59//lls3LjxVkOUnZyfJaPRKE6ePCmMRmOjy1j0faKI+NtGsej7xBtv3AhDhw4Vbm5uwtvbW2g0GqHRaMSKFSss63fs2CEkSRLe3t6iVatWokuXLmLp0qU3LDc3N1d06NBBvPHGG0IIISorK8X58+fFqFGjxOjRo8Udd9whcnNzhRBCREZGinXr1llee+rUKaFUKoVerxdCCAFAxMfHW9b/3//9n5gyZYrludFoFK1btxbLly+vNRYXFxer11crKysTAMSePXtuWJ/qOgghRHJyssjIyBAmk0kcOnRIREZGin//+9+1vqa+z0B95y6HaAkICQnBiy++iAcffLDe7fLy8jBp0iQ888wzKCgowN13342JEydCr9cDALZu3YqXX34ZGzZswJUrV6BUKrFgwQJbVIHIocnRf0y2s/lEFjYlXcFdvUKwKenKDVt9GmvJkiUoLCxEeXk59u/fj6eeesqqzz8gIACFhYXIz8/HiRMn8Oijj9ZbXlFREcaOHYtx48bhmWeesSz/7rvvYDAYUFlZiZKSEqxbtw4AkJmZibZt21q2a9u2LUwmE7Ky/qhvRESE5e/Lly8jPDzc8rx6Up66tG7dutbujStXrgAA/P39663P9bp27YrQ0FAoFArExsbihRdewKpVqxpUxo04RBIwZcoUTJ48Ga1bt653u7Vr1yIqKgr33XcfNBoN/vrXv8JsNmPbtm0AgC+++ALz589H79694enpiddeew1r16616hMiotrV3X98FM8MCUCQMdtq+9TUVKxZswabNm2yWr5v3z68/fbb+OGHHwD8MbnJli1b8NZbb9XYfuu2bfjiy69w9OhRq+VHjx7Fvn37rP6BU8Ndm8S9OSWmzmSvKUmShB49euC2227Dxo0bG1VGdQLQp08fvPfee1brXnjhBSQkJFgef/rTnwAAoaGhSE1NtWyXmpoKhUKBoKA/ktdrJ1wKCQnBpUuXLM9NJhMyMzPrjGnUqFGWz/W1vv/+e4SHhyMyMhIAMH78eKsR/9c+unbtWmf5CoWi0TeHqkuLmjY4OTkZPXv2tDyXJAndu3dHcnIyJkyYgOTkZIwfP96yPjo6Gmq1GqdPn0a/fv1qlLdkyRIsWbLE8rykpATZ2dk1tmsMs9ncZGXJhXWwD81VByGE1T9EIQQ6elTgueHBePy7oxjZoRV+TSnAy2PCEReshiRJVnG4uLggpnsPCElptTw0NBQTJ06Ei4uL1fKOHTuiXbt2UKvVVsvbR0YiNKI9tBrr7b29vWEymWAwGHAp8wpUSgkKSYJOpwMAuLm5WU29ajQaoVAoGnyDlZsl52ep+q5zRqOxQX3GW0/m4MnVx/H2tO4Y0cEPQgiM6OCHt6d1wxMrj+Ltad0xuktAk8QohLAcLwA4efIkdu/ejb///e8wGAyW0fg3cwOk4uJiTJgwAZ06dcJ7771n9RohRJ1lzJo1C6+++ip69eoFDw8PPPPMM5g+fTokSbK8xmAwWP6ePHky/vWvf2HLli0YNGgQ3n77bRQUFFjV41ovvPACBgwYgCeffBJPPfUU3N3dsXbtWixevBhLly6FyWSCyWS64ZUC1XX46aefMHjwYPj6+uL48eNYvHgx5s2bV+u+qz8DOTk5DfqMt6gkQKfToVWrVlbLfHx8UFJSYllfPeKztvXXW7RoERYtWmR5Xj2itClkZ2c3WVlyYR3sw63UwWAwID8/H1qtFh4eHgCqTpZLlixBTqkJYydNw+je0QCqkuBPPvkEADC603hsSL6KAe39MLyDH7744gtotVr8+c9/tvwDunz5Ms6fTYFWq0WnIUMs+8zNzYVOp4NGo0FgYCAkSYIQAhqNBhUVFVCr1Vb1uZqcjNzcXLhFRFgtX7t2LXJzczFixAiYtD5o7esGVxcFPvnkEwghMG/ePMugs6z8Yixa+g26uFzFggULLOWUlZUhKSkJfn5+aN++/S0lCHJ+lqrvOufi4nLTc85vPpGFJ1cn4d1ZvSzdOAaDASqVCrf3CIXSRdmk3TySJOHJJ5/E3/72NwBVTecPPvggFixYAIVCYbnngUqlumFZGzduxP79+5GUlITVq1dblsfHx6N///51lvHSSy+hvLwcAwYMgMFgwLhx4/D+++9bba9SqSzPu3fvjmXLluHhhx9GYWEh7r//fsTFxUGpVNa6j06dOmHv3r147rnn0KlTJ+h0Ori4uGD58uWYPXv2Tb9X1cdh7dq1WLBgAcrLyxEcHIz58+fj2WefrfUYm0wmKJVKBAQENOi+Ay0qCdBqtTWa9ouKiuDp6XlT64lassrKShgMBsvJ/mqJHiv++xGKiopwxx13IDY2FgAsJxKlZIS+tNjyeg8PDwwcOBCnSzRYeTQPU3uHYVPSFRzLFXj22Wdr7C8kJKTWkd+tW7eutWsvKCjIqlm2WkxMTK31mTJlSo1lZrMZc+bMQUlJiVX/q1lfhg7u5UAl4Ovra1melZWFX375BUqlEmPnPIJOwV7wdFUhNzcXmZmZCAkJaXA/rqM4m11S7wm+uvvnbHZJkyQBCQkJ9a4fNmzYTXftzJ07F3Pnzq11XX0tCRqNBm+//TbefvvtWtfX1tQ+e/bsBp3AO3fubBmDkJ+fj4EDB+LcuXM3/fprffvtt416XUO0qCQgJiYGn376qeW5EALHjx/HI488YlmfmJiIOXPmAADOnTsHvV6PTp06yRIvUXO5vin/559/xqFDh9CnTx/cfvvtAIDvDlyCX0AQioqKaiTHU6dOhbu7u9UJU6FQwBzSDf9ZmWj59Tima2DVr0VJsotBgQqFwtLveq2Q4CD847knUV5ebvULzmw2W345lVaaLO/ZmTNnsG3bNgQFBeHhhx+2bH/16lUAVYmMo9+sZ+GI6BtuM7ZrkF0cV0fl6+uLX375BV9++SWysrJqTXLl5hBJgNFotDzMZjMqKipqbY6ZMmUKnn76aXzzzTeYMWMG/vOf/wCoGqwBAPPmzcPdd9+N2bNnIzo6Gi+++CKmTJkCb29vm9eJqDmcO3cOu3fvhlGhRlT/0Rjesao/V6vVAvhjlDIAPDYyGsXFgVCpJsHNzc2qnGtHUFer7SqAawcLOsLVAdfXMyoqClFRUbWOf/Dw8EBwcLBl2cnLxfh6w29wzTqOXr16YeLEiTaLmxxX27Zt8fLLL8sdRp0c4uqAxYsXw83NDa+99hpWrVoFNzc3y+WC186l7Ofnh3Xr1uFf//oXvL29sWLFCqxfvx4ajQYAMHr0aLzyyiuYMGECgoKCUFlZiY8//li2ehE1lslkQmpqKnbt2mW13Gw249KlS8i8lAp3lz9Oat27d8f8+fNx7733Wm3v5eVV48RYm/ouA6zv8kFHcf2v+kGDBuHJJ5+0tJoAQMcgT4QrCgGgxmViX331FcrLy62SLCJH4BAtAa+88gpeeeWVWtdVjwSuNmzYMCQnJ9dZ1sKFC7Fw4cKmDI/IJq79tXo8NRsrvvoOnopKREf/0awbHh6O2267DW3btkW7tn805bdq1arGoNmGsHX/sT2QJMkyWA0AlAoJCx6omma2+ocFAJSWluLixYsYMGAAlh24isUzqloPTCYTzpw5g8jISKvtieyJQyQBRM5s586dOHHiBIYNG2aZ/lTjpoWndyuEeCqtBjO5urpaur+aEvuPq0iSVOMKIxcXF0yaNAlqtRqPj/tjEGN6ejpWrVoFFxcXPPXUU82aCFQnh019DTk5jupj39CxKkwCiOxI9Qxn1QPyJEnClStXcPXqVZw5c8aSBHQJ8cKLjz8IpVLp8PMcODqNRoOePXsiOzsb/l5/dK0UFBTAxcUFwcHBlgQgKaMI5sJM5F/NRufOnZtsoJhCoYBKpUJeXh78/PwaPWix+lpzR+aMdTAYDMjOzoarq2uDL3NlEkBkJ44cOYL4+HgEBgZC13YIZvZpg2BvN/Tq1QvBwcE1rmJpyLXAZHu9evVCTEyMVZdlSnYJyk4n4sK5syguLsakSZOabH/h4eG4dOkS8vPzG11G9bXmjswZ61DdQhUQ0PCJnZgEEMlACIHMzEyEhoZafrW1bt0aRqMR2dnZePKecLi6ugKomkmvY8eOcoZLjaRSqazGYkyNDcOu0jCUlhSjQ4cOVtuuXr0aISEh6NGjh2Uuh4ZQq9WIioqC2WxudLdATk5Oo04k9sTZ6iBJkuXRGEwCiGxMr9djyX+WobI4F/Pnz7fcoKRNmzaYPn06oqKioFarZY6SmsuQIUMwZMgQqxN1dnY2Tpw4gfXHruBvgW3QNbLhSUC1W5n1UKFQOPyvaNahgfuyyV6InJjBYEBx8R8z72k0Gpw1+sEgFEhLS7MslyQJXbp0YQLgJK795abRaNC/f3/0jvBFVPgfsyxeuHABa9assfqcEDUltgQQNaMjR45g69ataNu2LWbOnGlZ/o/Zg+HqOhp+fn4yRkf2wsfHB2PHjsXY65YfO3YMycnJ0Ol0dU6TS3Qr2BJA1ISqm3grjVV3cnN3d0dFRQUuXLgAvV5v2S40NJQJAN1Qp06dEB4ejri4OABVkzbll1bi4MGDyMnJkTk6agnYEkDUBIxGI/bu3YsjR47g3nvvxfJDuXhgcDt06NABt99+O2JiYjhhDDVY586d0blzZ0tyGeLtBlOFDps2bQIAqzElRI3BJICoCSiVShw7dgxFRUU4dOgQnhr7R8Nunz59ZIyMWoLq8QPdwryRkZEBf39/GAwGhIWFWbapqKiAQqHgmBJqECYBRI2QlZWFq1evolu3bgCq/kkPGjQIhYWFllvyEjWHsLAwPPLII9DpdFZXAuzcuRMHE5MwdsRQJp5005gEEDXQyZMn8e7KzfBRmfF/UVGWG/D06tVL5sjIWUiSBE9PT8tzk8mEpKQk7CtpheFGx54tj2yLAwOJbkAIYTWFZ1RUFALcgFA/T5SUlMgYGVEVpVKJP//5z3hmTDT6xPa2LNfr9di0adMtzSJILRtbAojqceHCBWzbtg0xMTEYOHAggKqZ2Z5cMA8+Pj6NnqWLqKm5u7tjyJAhVssOHTqEgwcP4vjx41i0aBHHC1ANbAkgqkdKSgquXLmCffv2wWw2W5a3atWKCQDZPW9vb/j6+qJfv35QKF1wKLWqRYB3G6RqbAkgukZ+fj5atWqFnBI91h7JxH2DB6OoqAhDhgy5pelYieQQExODLl26wGw2o8xgQkGZASaTCZ9//jk6duyI/v37s3XAyTEJIELVL6Off/4ZR44cweTJk9GtWzfcNyACHhoXq5n+iByNQqGAQqGAlwswuksgDh8+jMuXLyMrKwsxMTGW21aTc2ISQISq0dYGgwFCCCQlJaF79+7w0PDrQS1PTEwMiouLYTQarRKA8vJyGaMiufC/HDklIQTS0tIsl/cBwLBhwxAREYGePXvKFxhRM9NoNBg+fLjVMiEEPli+EtPGD0NeXh6ntHYiTALI6ej1enz33XfYfL4Ubz082bK8VatWVvd+J3IWqampOHmlBEajiS0CToYjncjpqNVqqFQqhCmKYTZzYhWidu3a4e/z74CrRm01FbFer+eVBC0cWwKoxRNCICMjA23atAFQ1f8/fvx43HZbMW/qQ/Q/7du3R3Z2tuW5EAKrV6+G0WjE7bffDn9/fxmjo+bClgBq0UpLS/HFF1/g888/R3p6umW5r68v2rZtK19gRHbu8uXLOHfuHFJTU1FUVCR3ONRMmARQi6YzKiyT/Fy4cEHmaIgcR2hoKO677z4MGDAAJm0glu+5CIATDbU07A6gFqeiogKurq4wmQVWHEjHfZMmobS0FBEREXKHRuRQ2rVrh3bt2gEAogO0AID169dDo9Fg5MiRUKlUcoZHTYBJALUYZrMZe/fuxW+//Yb7778fAQEBWDS6AwCgdevWMkdH5NgUCgmpqalITEwEUNVSUH0rbXJc7A6gFsNsNuPYsWPQ6/XYvXu33OEQtTjh4eEYPXo0OnfujJiYGLnDoSbAlgBqMVxcXDB58mScOHGixmQoRHTrFAoFBg4cCCGE5QZaQghs27UXHdu1QXh4uMwRUkOxJYAcVnFxMVas/AGbj6VZloWGhmLMmDHsqyRqRtfeQTMpJRWfbE3CF198wcG3DogtAeSQhBBYsWIFsrJzcCLXiDHdw3lrXyIZhLb2wri2LlAownjZrQNiEkAOSZIkjB07Fj/++CMmj+/HBIBIJn5+fpg/fz70er3V7bZLSkrg6ekpY2R0M9gdQA6jsLAQFRUVluft27fHY489hsjISBmjIiKlUgl3d3fL8+zsbLz//vvYunUrTCZOzW3PmASQQzh9+jQ+/vhjbNy40WqyEvb9E9mfAwcOwGg04vTpMygpr5Q7HKoHuwPI7gkhkHy5BHq9HpcuXYJOp2MzI5EdmzBhAry8vOAe2Bbrk7Jx34C2codEdWASQHZPCMCoDcTYsWPRvXt3q2ZHIrI/CoUCQ4cOBQD0+d+ykpISJCUlYcCAARzDY0eYBJBdysrKwsWLFzFgwAAoFBJm9Q0HwGuQiRyR0WjEDz/8gIyMDOTl5eHOO++UOyT6HyYBZHeysrLw+eefw2AwwMvLC127dpU7JCK6BQqFAqGhocjMzESXLl3kDoeuwSSA7E5AQAAiIiJQUFCAwMBAucMholukUCgwbtw4xMbGwt/fX+5w6BpMAsguVI/4lyQJCoUCU6dOhRACbm5uMkdGRE3l2gRgxb406C4eRVyHNoiNjZUxKufmEJcIFhYWYsaMGfD09ERISAjefffdWrdbsWIFtFqt5eHh4QFJkrB27VoAQEJCAhQKhdU2r7/+ug1rQrUpKCjAsmXL8Mb6o0jNLQUAuLq6MgEgasEipKu4cuYYNm7ciLS0tBu/gJqFQ7QELFy4EHq9HpmZmUhLS8PIkSPRsWNHjB8/3mq7OXPmYM6cOZbn8fHxmDVrFsaNG2dZFhAQgKysLJvFTvUTQmDdunW4fPkyvEvL0OaOHnKHREQ20K93D2Slp8LV1RURERFyh+O07D4JKC0txapVq3D48GF4eXmhW7duePDBB/H555/XSAKu9/nnn2PmzJm8pMyOSZKEyZMn4/vvv8cdd9wBpVIpd0hEZAMqlcrS7Xcts9lsNf0wNS+7TwJSUlJgNput7l3ds2dPSxN/XfLy8rB+/XokJCTUWB4UFASNRoNx48bhn//8J3x9fWstY8mSJViyZInleUlJCbKzsxtfmWuYzeYmK0suTVmHu+66CwBs/p7wOMiv+iTgyHUAHP84APLXwWg0Qq/Xw93dvdFzCchdh6ZgyzrYfRKg0+ng7e1ttczHxwclJSX1vm7FihWIjIzEgAEDLMs6deqExMREdO7cGZmZmViwYAHmzp2LDRs21FrGokWLsGjRIsvzsLCwJhutnp2d7fAj3xtbh4MHD+L48eO49957oVarmyGym+fMx8FeSJIEIYRD1wFw/OMAyFsHvV6Pd999FxUVFYjsFIN7Zk5tVDk8Dg1j920uWq0WxcXFVsuKiopuOG3s8uXLMX/+fKtlQUFB6Nq1KxQKBdq0aYOlS5di06ZNKCsra/K4qXb5+flYuWkHMjIysHv3brnDISI7odFocPfdd8M/NAJXfTiXgK3YfUtAhw4dIEkSTpw4YZk0JjEx0ap74HpHjx5FcnIy7r333nrLVigUEELU6JOi5uPp7QPvTgPRWXHFMq0oEREAhIeH45E/zbXqCjAajXBxsftTlcOy+5YADw8PTJs2DS+88AJKSkqQnJyMZcuW4f7776/zNcuXL8f48eMRFBRktXzHjh1ITU2FEAJZWVl47LHHMGbMGHh4eDR3NZya2Wy2JFoqpQJ/nzkI06ZN4xebiGq4NgEoLi7Gf/7zHxw/flzGiFo2u08CAODDDz+ESqVCcHAwRo8ejWeffdZyZYBWq7VqVq6srMS3335ba5Jw9OhRDB48GB4eHoiNjUXr1q3x9ddf26wezshoNOL777/Hzp07rZbzBiJEdCM7duxAQUEBNm3ahPLycrnDaZEc4qeYj48PVq1aVes6nU5n9VytViM3N7fWba8f6EfN79ChQ0hJSUFKSgqio6MRGhoqd0hE5CDGjx+PsrIy3HbbbZw8rJk4RBJAjqtv3764fPkywsLCmAAQUYOo1WrcfffdludpeaUI92385YNUE5MAahZ6owlns3WICfXGXXfdxS8tEd0SIQR+Pn4ZIUUn0aZNGO830EQcYkwAOQ6j0Yg1a9bg3MVLyCio6sNjAkBEt0qSJPRyzcWxY4nYuHEjLl++LHdILQJbAqhJbd68GcnJyUhJScFjjz0mdzhE1ILExcXh3LlzCAsLQ3BwsNzhtAhMAqhJDRo0COfPn0f//v156SURNSmVSoXZs2fzHiNNiEkANSlvb28sWLBA9umAiahluj4BOHPmDNRqNdq1aydTRI6NYwLolh0/fhx6vd7ynAkAEdnCqVOn8P333+Ob777nLeIbiUkA3ZJDhw5h5dr1+PLLLzmZBxHZVFhYGLRe3khWtIeXl5fc4TgkdgfQrVGqcMIUhB7entBoNHJHQ0ROxNPTE/fPm4u/eHhApVLJHY5DYhJAtySuVw8sbe2L4OBgKBRsWCIi2/Lx8bF6LoSAXq/nj5KbxP/a1GDX33q5TZs2vBkQEckuPz8fpaWl+P7772E0GuUOxyEwCaAGKSoqwkcffYRt27bJHQoRkZUrV67AbDYjMzOzznvIkDUmAdQg+/fvh06nw5EjRyy3ByYisgddu3aFm5sb5s2bV+NW8lQ7tuFSg4waNQpKpRJRUVGcDpiI7I5KpUJgYCBOXC5Cen4ZxsVwZsH6sCWAbtryPReRW1qJkSNHIiIiQu5wiIjqFOmvRVyED3755RdkZ2fLHY7dYhJAN5SSkoL09HRM6B4Mfy1H3BKR/XNVKfHbr5uxf/9+rFy5EhUVFXKHZJeYBFC9srOzsWbNGnz55ZcoykpnFwAROYyBAwdCo9EgLi6OlwzWgWMCqF5qtRo+Pj4wGAwIDQ2VOxwiopsWEBCAxx57DO7u7nKHYreYBFC9WrVqhT/96U/Q6XT8IhGRw7n+/1ZJSQk8PT1lisb+sDuAanXt5X9qtRq+vr4yRkNEdGuEEPj999/x7nvvIzMzU+5w7AaTAKrh7Nmz+PSzZcjPz5c7FCKiJmEymZCYeAx7ykPw22975A7HbjAJICsGgwE//rQe69KU2Lp1q9zhEBE1CRcXF0yfPg2LhoZi6tQpcodjN5gEkBWVSoVZM6ZjSlsTJkyYIHc4RERNpnXr1hgzZgzvdXINvhNUQ3h4OB544AFeDkhELVpeXh5MJhMCAgLkDkU2bAkgAEBhYaHVYEAmAETUkp05cwaffvopVq1ahcrKSrnDkQ2TAEJpaSn++9//4rvvvqtxm2AiopbIx8cHJpMJBoMBxcXFcocjG3YHEE6dOgWdTof09HQYDAa5wyEianaBgYG4++67ERISAr1Qyh2ObJgEELp07wkPDw8olUp4e3vLHQ4RkU1ERkYCAD745TQWje4AF6XzNY47X43JSoXBhPd/PYfOnTujQ4cOcodDRGRzz4zrBH1FOXbv3m01NsoZsCXASQkhcOnSJURERODZ8Z3kDoeISDalpaX4z3/+g7KyMnh4eKB3795yh2QzbAlwUocOHcIXX3yBdevWwWw2yx0OEZFsPDw80KFDB7i5ucHV1VXucGyKLQFOKi0tDUDVLFoKBXNBInJuY8eOxciRI6HVauUOxaaYBDipqVOnomPHjhwHQEQEOF0LQDX+BHRSkiShW7du0Gg0codCRGRX9Ho9Nm6KR1FRkdyhNDsmAU6ksLAQqf/rBiAiopqEEFj+9Xf4eG8mNmzY0OKvFmAS4EQ2bdqERz79FTt27pY7FCIiuyRJEkYOvQ2DtLmIjIxs8UkAxwQ4Cb1ej9LSUvRXX0Zo8CC5wyEislvR0dF44oknnGKcAJMAJ6HRaPCnP/0J58+fR3R0tNzhEBHZNWdIAAB2BzgVhULBBICIqAGMRiN27dqFq1evyh1Ks3CIJKCwsBAzZsyAp6cnQkJC8O6779a5rSRJ8PDwgFarhVarxfjx463Wr169GpGRkXB3d8fIkSMt18u3VIWFhcjNzZU7DCIih7Rq1Srs2LED8fHxLXJ8gEMkAQsXLoRer0dmZiY2b96M119/HfHx8XVuf/jwYeh0Ouh0OqvtTp06hXnz5uGjjz5CXl4eunfvjhkzZtiiCrKJj4/HRx99hH379skdChGRw+nfvz+USiXCwsKYBMihtLQUq1atwmuvvQYvLy9069YNDz74ID7//PMGl/XNN99g3LhxGDNmDNzc3PDqq6/i2LFjOHHiRDNELr/y8nLk5eXBbDajVatWcodDRORw2rVrhyeeeAIX1e2QU1IpdzhNzu4HBqakpMBsNiMmJsayrGfPnli7dm2drxkxYgRMJhPi4uLw5ptvomvXrgCA5ORk9OnTx7Kdp6cnIiMjkZycbNnmWkuWLMGSJUssz0tKSpCdnd0U1YLZbG6ysurchxC4Y9IUqBQCLi4uTb4/W9ShubEO8qv+deXIdQAc/zgArEN9bo9yh1RRhOyK5p9AyJbHwe6TAJ1OV+Me9z4+PigpKal1+4SEBAwYMAB6vR5vvPEGxowZg1OnTsHLyws6nQ4+Pj43XdaiRYuwaNEiy/OwsDAEBgbeWoX+Jzs7u8nKqovJLJBVXIFQH7dmKd8WdWhurIP8JEmCEMKh6wA4/nEAWIcbMZvNSExMRLt27Zq1ddWWx8HuuwO0Wi2Ki4utlhUVFcHT07PW7YcOHQq1Wg1PT08sXrwYLi4u2Lt3r6Ws66eBrK8sR1VRUYHS0lIoFVKzJQBERM5m5cqV2LBhA3bs2CF3KE3G7pOADh06QJIkq377xMREq+6B+igUCktzY0xMDBITEy3rdDodzp8/f9NlOYrffvsN7733niX5ISKiW9etWzdIkgS1Wt1iBgnafXeAh4cHpk2bhhdeeAFff/010tLSsGzZMixfvrzGtidOnIBer0f37t1RWVmJN998E+Xl5RgwYAAA4J577kGfPn2wbds2DBo0CC+//DK6d+9e63gAR2UymXDixAkYDIYW8yElIrIHMTExCA0Nha+vr9yhNBm7bwkAgA8//BAqlQrBwcEYPXo0nn32Wcv1/1qtFrt3V82Fn5OTg9mzZ8Pb2xvh4eHYt28fNm/ebBkH0LlzZyxfvhwPPfQQfH19cfToUfzwww9yVatZKJVKPPLIIxg9ejT69u0rdzhERC2GJEktKgEAHKAlAKgavLdq1apa1+l0Osvfw4cPx+nTp+sta/r06Zg+fXqTxmdv1Go1Bg4cKHcYREQt1tWSCuRczkCXDpGQJEnucBrNIVoC6OZU6CtRXmmSOwwiohbNYDDgzc9XY9m3a3DmzBm5w7klTAJaiMzMTPzjnY/x9trdMJvNcodDRNRiqVQqxAWp4KOoQHp6utzh3BKH6A6gG9u5cyfU+gIE6c5BkobKHQ4RUYs2evRoDBo0CKGhoXKHckuYBLQQEydOxL59+xAVFeXQ/VNERI6gpQwQZBLQQmi1WowaNUruMIiInJLBYIBKpZI7jAZjEkBERNRIOTk52LZtG3Q6HR588EGHa4nlwEAHl5CQgOPHj8Nk4lUBRES2ZjKZcPbsWVy5cgWXLl2SO5wGY0uAAysoKMCuXbsghIBSqWxRMx8SETmC4OBgDBo0CCcrfOAf5HiDBJkEODBJkqBs0wPepeno3Lmz3OEQETmlkSNHok12CVyUjte4ziTAgWk9vdCvX38M6zABCoXjffiIiFqKDoGOeTdanjkcmItSgVFdAuHiwlyOiEhueXl5+Omnn5CTkyN3KDeNSYADqqysxKVLl3iXQCIiOyGEwOrVq5GYmOhQt3FnEuCAkpKSsHz5cixfvpyJABGRHZAkCf3790dAQAAiIiLkDuemsR3ZAV2+fBkAEBAQ4HDXpBIRtVTdunVD9+7dHer/MpMAB3TnnXeib9++UKvVcodCRET/44gDtB0vYgIABAYGolWrVnKHQURE1zmXo8Py3WdRUFAgdyg3xCTAwRy5VIBj6YVyh0FERHXIOpeEtIQf8Msvv8gdyg0xCXAge/bsweGdW2Asvip3KEREVIeA1n6QzEZkZGRAr9fLHU69OCbAQZjNZhw8eBBFRUVoH9Ia6Botd0hERFSLqKgoTJkyBZ06dbL7OwuyJcBBSJKE8ePHIyoqCrGxsXKHQ0REdVAoFOjWrZvdJwAAWwIchiRJ6NixIzp27Ch3KERE1EIwCSAiImoGRUVFOHr0KMrLyzF+/Hi5w6kVuwMcQGZmJvLy8uQOg4iIGuDKlSvYuXMnDh06hLKyMrnDqRVbAhzA5s2bkZ6ejpEjR2LQoEFyh0NERDchOjoaPoGhOK9sI3codWISYOcqKytxMs8Eg9kN4eHhcodDREQ3SalU4rGH/wS90QxXlVLucGrFJMDOqdVqPPXQPcjLyUabNvabTRIRUU2SJNltAgBwTIBDCPJ2Q9fotg51UwoiIvqD0Wi0y7FdbAkgIiJqRqdPn8ZPP/0EDw8PPProo3b1g45JgB1LSEhASUkJYmNjERISInc4RETUCH5+fqioqEBlZSUKCgrg6+srd0gWTALslBAChw8fhk6nQ+vWrZkEEBE5KH9/f0ydOhXt27eHu7u73OFYYRJgp0wmEwYNGoQzZ86gS5cucodDRES3ICYmRu4QasUkwE65uLigX79+6Nevn9yhEBFREziWXogrRRUYFxMkdygWvDrAThWUVmJXCm8ZTETUUgS6CXiUXMLJkyflDsWCLQF2qKKiAnp9JVq5q+UOhYiImkjiof3Yv38/2rRpYzfdvGwJsEPHjh3Dp0vfxdkDv8odChERNZGOHTvCw8MD/v7+EELIHQ4AtgTYpQsXLkAIAbWaLQFERC1F27Zt8eSTT3KeAKrf9OnTkZqaCk9PT7lDISKiJmJPJ/9qTALskIuLC6KiouQOg4iImkl1d4DciQHHBBAREdmIEAJbt27FBx98gPPnz8sdjmMkAYWFhZgxYwY8PT0REhKCd999t9bt9u3bh7Fjx8LPzw9+fn6YMGECzp49a1mfkJAAhUIBrVZrebz++us2qsWNCSGwb98+ZGRkwGw2yx0OERE1MUmSkJGRgUNXJVy8eFHucByjO2DhwoXQ6/XIzMxEWloaRo4ciY4dO2L8+PFW2xUUFOD+++/HDz/8ADc3N7z00kuYOHEiTp06ZdkmICAAWVlZtq7CTcnPz8fq+B1wlYz461/+DD8/P7lDIiKiJhYXFwejXz569pT/MkG7TwJKS0uxatUqHD58GF5eXujWrRsefPBBfP755zWSgOufP/nkk3jzzTeRl5fnECfU0tJSmDyD4CJK7OoGE0RE1HS6deuGbt3kjqKK3ScBKSkpMJvNVvMu9+zZE2vXrr3ha3fu3ImgoCCrBCAvLw9BQUHQaDQYN24c/vnPf9Z5wl2yZAmWLFlieV5SUoLs7OxbqM0fzGZzjbI0Gg2evfd2AEBOTk6T7Kc51VYHR8M6yK96gJQj1wFw/OMAsA72wpZ1sPskQKfTwdvb22qZj48PSkpK6n3dhQsXsHDhQrz//vuWZZ06dUJiYiI6d+6MzMxMLFiwAHPnzsWGDRtqLWPRokVYtGiR5XlYWBgCAwNvoTZ/yM7ObrKy5MI62AdHr4MkSRBCOHQdAMc/DgDrYGuVlZXQ6XQ1fojasg52nwRotVoUFxdbLSsqKqr3Gvr09HSMGjUKf/vb3zBz5kzL8qCgIAQFVd24oU2bNli6dCmioqJQVlZmd7d3JCKiluvw4cPYtGkTgoKC8OCDD8oWh91fHdChQwdIkoQTJ05YliUmJtZ5W8aMjAyMGDECDz30kNWv+NooFAoIIexi+sbk5GSsXbvWqp5ERNQy+fn5wWw2IycnBwaDQbY47D4J8PDwwLRp0/DCCy+gpKQEycnJWLZsGe6///4a216+fBnDhw/HPffcg2effbbG+h07diA1NRVCCGRlZeGxxx7DmDFj4OHhYYuq1OvMmTNISkrCmTNn5A6FiIiaWVhYGO655x48/fTTUKlUssVh90kAAHz44YdQqVQIDg7G6NGj8eyzz1quBNBqtdi9ezcA4LPPPsO5c+fw1ltvWc0FcOnSJQDA0aNHMXjwYHh4eCA2NhatW7fG119/LVu9rtWxY0fExMSgY8eOcodCRETNzMXFBZGRkbhaZpI1DknYQ1u4gwgLC0NGRkaTlOVIg1fqwjrYB0evw6ZNmyCEwIQJE+QO5ZY4+nEAWAc5vP/rWfxlRJTV9MFNXYf6zl0O0RLgDJbtvoBzOfVf8UBERC2HyWTCXR1ccfDgQdlmibX7qwOcgRACDwxuL3cYRERkQ6Wlpfj8888BAO3atYO/v7/NY2ASYAe+++47FBYWYvDgwehmL9NIERFRs/L09IRWq4VGo0F5ebksMTAJkJkQAhkZGbJ9AIiISB6SJOHxxx+Hi4t8p2ImAXZg5syZuHz5MiIiIuQOhYiIbEjOBABgEiA7SZIQERHBBICIiGyOVwcQERHJxGw248CBA/jpp5+Qn59v8/0zCZDZ1atXZZ0ykoiI5CNJEuIT9uKLg9lNNg9NQ7A7QGZLP1+By2XAU7PHc7ZAIiInI0kS4mI6oHNZuSw3smMSIKOKigoYynXwhAu8vLzkDoeIiGQw4fbbZds3kwAZubq64qW/PYm8vDxZJokgIiLnxiRAZm5ubggLC5M7DCIickJMAoiIiGRkMBiwYcMG5OXlYerUqTbdN5MAGaWmpkKpVMLf3x+urq5yh0NERDJwcXHBmTNnUFlZidzcXHh7e9tu3zbbE9WwefNmZGVlYcyYMRgwYIDc4RARkQwkScLAgQPh4uKC1q1b2/Sycc4TIKPqW0f6+fnJHAkREclp6NChcAnuBF9fX5vuly0BMpr/wENQCDOUSuZiRETOLqOgHP1svE+efWS0+UQWkrN0UCqVcodCREQymxpr+yvF2BIgo0k9Q+UOgYiI7EBOTg6+//576HQ63H///TbbL1sCZGIymXDgwAGkpaXJHQoREclMrVYjPz8flZWVEELYbL9sCZCJwWBAfHw8unTpwtsIExE5OU9PT0ycOBGenp6QJMlm+2USIBNJkhAYGMgrA4iICEqlEr169QIAZGdn22y/TAJkotFosGDBArnDICIiJ8YxAURERHbCYDDYdEwAkwAiIiI7sGHDBkx4ZQX0er3N9skkQAZ6vR6lZRVY9uOvKC8vlzscIiKyA25ubhioSrPMJmsLHBMgg+LiYhiNBpw9th8YN1DucIiIyA7ExcWhS5cuUChs9/ucLQEykCQJapULenZsx7sHEhERAMDHxwchISG8RLCla926NUwmE+6++265QyEiIifGJICIiMgOmEwmFBUVwWw2QwhhkxYBdgcQERHZgby8PHzwwQfQ6XSorKy0yT6ZBMjgxIkTKC8vx65du+QOhYiI7IRarbb8bavLBJkEyCA7OxsGgwHp6elyh0JERHbCy8sL8xY8Bg+tJzw9PW2yTyYBMggPD4darUanTp3kDoWIiOyEQqFAJVxgstF4AIBJgCyioqJQKZSIjY2VOxQiIrIj0YGeUCs5T0CL5+WmkjsEIiKyM+np6TAajSguLrbJ/pgEEJGshBAQAjCbbXfTFCJ7tWbNGpSVlSE1NdUm+2vwPAHbt2/HsWPHUF5ejoCAAIwePRoRERHNEVuL9dNPP6Fbt25ISkpCt27d5A6HSBYnLxdj+Z6L6Pi/JKDLy7/gzu4hmH9bO3QJ8ZI7PCJZeHh4QJIkm90/oMEtAVOnTsX333+P+Ph4vPXWW2jfvj1mzJiBwsLCZgivZcrPz4fJZLJZcw+RvfkpMRNTP9oLjUqBNr7uaO/vgdULBkKjUmDqR3vxU2Km3CESyeLBBx+Ep6cnevbsaZP9NTgJKCgowL59+7B7926cOXMGFy5cAAD8+c9/bvLgrlVYWIgZM2bA09MTISEhePfdd+vcdufOnYiJiYG7uzv69OmDY8eOWa1funQpQkNDodVqMXXqVBQUFDRr7Nfr168fXF1d0a5dO5vul8genLxcjGfXJOHje2OxeHI3aFwUUCokxIR6Y/Hkbvj43lg8uyYJJy8zSSZqbrc8JiAiIgJffvklNm/e3BTx1GnhwoXQ6/XIzMzE5s2b8frrryM+Pr7Gdnl5eZg0aRKeeeYZFBQU4O6778bEiRMtEy9s3boVL7/8MjZs2IArV65AqVRiwYIFzRr79bp06QK1Wo2QkBCb7pfIHizfcxFTY0MxtIN/reuHdvDH1NhQLN9z0caRETkfSQjRqNE4p0+fxquvvoqgoCCcPn0aRUVF2LNnT1PHBwAoLS2Fr68vDh8+jJiYGADACy+8gJSUFKxatcpq288++wyffPIJDh06BKBq0FF4eDg+/vhjTJgwAXPmzEFwcDD+/e9/AwDOnj2LLl26IDc3F97e3vXG0bp1a3z11VdNUidbzQvdnFgH++BIdRBC4EqpQBtfd2hcqn6DlJWVAQDc3d0t2+mNZqTnlyHYQ3KoujlKrHVhHeRnNpst8TdVPR566CFkZGTUuq7RNxAKCQnBwIEDsWnTJly+fBnr169vdIA3kpKSArPZbEkAAKBnz55Yu3ZtjW2Tk5Ot+lIkSUL37t2RnJyMCRMmIDk5GePHj7esj46OhlqtxunTp9GvXz+rspYsWYIlS5ZYLWtkzlSrpixLLqyDfXCUOghR9XBR1P/PzUUhWbYFHKNugOMch/qwDvK69sRvi3o0OAlYt24dJk+eDC8vLyxcuBALFy7E5s2bMXv2bPz222/NESN0Ol2NX+k+Pj4oKSmpddtWrVrVua1Op4OPj89NlbVo0SIsWrTI8jwsLAwTJkxobDUsvl7xHfr164fiwnzExcXdcnlyyc7ORmBgoNxh3BLWwbbMZoEuL/+C1Qt6Iya06judkJAAABg2bJhlu+TMIjy6Yy9O/t84KG6QMNgLRzoOdWEd5Ld69Wr07t0bOp0O3bt3b/b9NXhMwFNPPYXbbrsNX3/9NfLy8gAAbdu2RXJycpMHV02r1dYYSV9UVFTr3MparRZFRUV1bnuj9bZQWVEGSZhsdpcoInuhUEi4s3sIVh68VO92Kw9ewp3dQxwmASBqKtOmTYOHh4dNEgCgEUlAcnIyJk6ciOeeew4BAQHQarXo0qULpk2b1hzxAQA6dOgASZJw4sQJy7LExESr7oFqMTExSExMtDwXQuD48eOWba9ff+7cOej1epvO4z9ixAi4u7ujY8eONtsnkb2Yf1s7rDmciZ0pV2tdvzPlKtYczsT823j1DFFza/TAQCEETp06hczMTPj6+qJ3797NOhhjzpw5KC0txddff420tDSMGjUKy5cvt+rfB6quDoiMjMTSpUsxY8YM/Oc//8GSJUtw9uxZaDQabN26FXfffTe2bt2K6OhoPPDAAxBC4Pvvv79hDGFhYXUOrmgoR2+yAlgHe+GIdfgpMRPPrknC1NhQDNZehYtCwqoNvyDfPQxJimj8a2o3TOoZKneYDeKIx+F6rIN9aOo61HfuuqkxAdu3b8eIESMAAFu2bKmxPi8vD1u3boVarUbbtm3Rtm3bxkdbhw8//BAPPvgggoOD4enpiWeffdaSAGi1WsTHx2Pw4MHw8/PDunXrsHDhQjz44IOIiYnB+vXrodFoAACjR4/GK6+8ggkTJqC4uBhjxozBf//73yaPl4jqNqlnKKIDPLF8z0Wk55dBCODbbQdgzFiOXQePIS4qWO4QiWTx22+/ITw8HFevXoW/f+2X0Talm2oJiImJsfT51zfBjclkQm5uLv7yl7/gjTfeaLoo7URTtwT4+fnBxaXRF2jIjhm3fXD0Ovz8888QAvjtt91444038PwLL+K1xf+QO6wGc/TjALAO9uDf//43Jk2aBIPBgC5dujRJmfWdu25qTMC1g/4uXrxY5+PSpUu4ePEiPvvssyYJvKX66aefUFxcXOtkR0TORpIkSFLVxGNqLz/8++23bXbzFCJ7ExLeDkoXF3h52eb+GU1+F8HAwMBmnTOgJaj+9c+rA4j+EB4eDjetN9w7DcZjf31S7nCIZNF32Bgo1a4ICwuzyf6a5VbCgwYNao5iW4wBAwbA7OKKUaNGyR0Kkd0IDw9HeUE2tLfdi82bN2PHjh1yh0Rkc1EBnnB1aZZTc61styey8PX1hY+7+obTFBM5kzZt2qCyvBSSSg2P/jPw8J8Xwmg0yh0WUYvGJICI7IK3tzfcPLQwFuXAs/dEXM4rxqeffip3WEQ2U1xcjDVr1qCiogIGg8Em+2QSIAOj0Qiz2WyZcZGIqgYIBoWEwViSC8lFBfch9+PZ519Afn6+3KER2YROp0NycjIqKyuhUNjm9MwkQAZnzpyBTqfDl19+KXcoRHalTZs2MBVXzSToFtkHioBovPDiSzJHRWQbbm5uiIuLg1qthlKptMk+mQTIQK1WAwD0er3MkRDZl6h2ETD+LwmQJAkeQ+/Hsv/+t1nvTUJkL1q1aoUJEybA1dXVZvtkEiCDiIgIaLVaPP3003KHQmRX2rdrC2XZH83/Kr820PYcjwWP/sWhbw9LZK+YBMhArVZDoVA49GyBRM0hPDwcKM21PC89/RvMuWnYu3snLl2q/86DRC3Be9vO2nR/TAJkYhYCx9IL5Q6DyK60adMGZdmpKFr3D1z58B7kbXgLU4f2REpKCiIiIuQOj6hZJSQkABd/t+lEckwCZGI2m3Eh7RIKCgrkDoXIbnTr1g0D+/XFM3MnIbp9WwizCSq1K6KiouQOjajZZWVlofDyRZt2fTEJkIm+ogLHf/0RZ86ckTsUIrvh5+eH7du24LnnnsMD8+cCAH5YvRomk0nmyIiaX69evTB8+HCbdhUzCZCJJElQq9X850ZUh+nTpwMACvOu4sCBAzJHQ9T8OnbsiCFDhtjs8kAA4Mg0mbi7u+O5556TOwwiuxUaGoonn34Gnh7uiImJkTscohaJSQAR2a1/v/mG3CEQtWhMAoiIiGSWlZWFL774Ap6enpg2bZrN9ssxATIRQuD48ePYuXMnJ0EhInJyRUVFKKwwoai4xKb7ZUuATIQQ+PHHHwEAsbGx0Gq1MkdE1Dgms4DJ3PhE1mgWEAKoNJqbMKpbp1RIUCokucMgJ9GmTRt4dx+NoeFqm+6XSYBMFAoFyt0CUKpuZdOJIYiaksks8PW+VFwtbvxn+HwaIASQYuOZ0m7E30uNe/u3ZSJANuHu7o7npvQFAGRnZ9tsv0wCZPSvZx6ROwSiW2IyC1wtroS/pwaNvfNprqYqCQj01jRtcLfAbAauFuthMgsmAdSiMQkgolumUAAujcwClBIg0PjXNwcj7Ktrglq+vLw8+Pj42HSOAIBJABERkaz0ej2WLl0KSZLw8MMP23Tf9pN6O6GrV69i8+bN2Lhxo9yhEBGRTPLzq26fLYSAj4+PTffNlgAZlZSUYN++fVAoFLj99tuhsKPmUCIiso2goCA8+eSTKCgogEZj27ExTAJk5O/vjw4dOsDPzw9GoxFqtW0vDSFyNuWVJvyYmImU7BJoXBQYEu2P26Jayx0WOTlJkqDVamW5VJxJgIw8PT1x9913yx0GkdPYcPwyTCYznh3XCYVlBvz3twtordWgY5Cn3KGRk3vzl9N4Zlwnm++X7c8yE0IgPumK3GEQNQuDyYx/bzmD5MyiGute3XgC53J0Noul0mhGUmYRRncNgqtKiSBvV/Rp64vDafk2i4GoNklJSZgQ7S7LXWXZEiAzSZLgprbtJSFEtrL3fB481ErEhHrXWNdaq8GVonK0quV1X+5NRVp+aa1l+rip8djI6AbHkqvTQwiBIC9Xy7JgHzecuFzc4LKImoper8fatWsBAPPnz0d4eLhN988kQGaZmZlI27cNH+8ox4IFC+QOh6jJmIXA7+dzMbpLEACgwmBCcbkBAf87CSslCQZT7dMNzx3Ytsnj0RvNcFVZJ9yuKgX0Rtv/+iKqVlxcDG9vbxQXFyMoKMjm+2cSIDOFQoHU1FQAQFlZGdzd3eUNiKiJXC3Ro7jCaOlvP3KpAGl5Zbi7b9UvHZ3eCK3GBTDaJh6NiwJ6g/UkQBUGMzQubIkj+fj7++OJJ55AeXm5LIPDmQTILCAgALfddhtCQkLg4sLDQS1HcbkBKqVUdaIHkJJdgtbaqsufCsoqkVdaiagALS5frPnaL/ZeRGpuWa3l+rir8MSoDg2Op7VWA0hAdnEFAv/XGnGlqByBXvYzXTE5Lzc3N1n2y7OOzJRKJUaNGiV3GERNzk2thMEkkFNSgcIyA4rLjZa7BcYnZ6FriBd8PdS4XMtr5w1s1+TxqF0UiAnxwpaT2ZgRG4aCcgMOpRZgau+wJt8XkaPg1QFE1CxCfNwQG94KHyWcx/bTObi3fwT0RjP+9cspSADu6hVq85gm9giFUgL+GX8ay3+7iKEd/Hl5IMmmsrISP//8M44cOSLb3WTZEmAnhBAoKiqy+ZSRRM1FIUmYGhuGqbF//NJeMDRSxoiqWidm94uQNQaialeuXMHWA8nwVBxFTEyMLDEwCbAD+fn5+PTTz1BWocezzzzFwYFERE7AxcUFniGRCFVXyDZjLJMAO+Dt7Y2sShVyTR64fPkyoqKi5A6JiIiaWWhoKP7x8DRZY2ASYAeUSiUevftO+Pv7szuAiIhshkmAnYiObvgMaERERLfCIa4OeOmll+Dv7w9vb2888MAD0Ov1tW6Xk5OD2bNnIzQ0FF5eXoiLi8OWLVustpEkCR4eHpY7No0fP94WVSAiIrI4dOgQPv30U/z222+yxmH3ScCyZcuwYsUK7N+/HxcuXMDp06fx97//vdZtdTodevfujQMHDqCwsBDPP/88pkyZgrS0NKvtDh8+DJ1OB51Oh/j4eFtU46aUlJQgKSkJWVlZcodC1CBmM2A0mxv1MAnAJBr/+uZ4mM03rjPRrbh48SKuXLmC3NxcWeOw++6A5cuXY9GiRWjfvj0A4OWXX8acOXPwxhtv1Ni2ffv2eOqppyzPp0yZghdffBGHDh1CRIT9Xxb0448/4uLFi+jfv78sc0gTNZRSIcHfS42rxbW3zt2MIj0gBJBd1PgymoO/lxpKhSR3GNRCDRgwAAEBAQgNtf18GdeShBC138HDTnh7e+Pnn3/GoEGDAABXr15FQEAAsrKyEBgYWO9rL1++jLZt2+L48ePo1KnqPs2SJCE4OBgmkwlxcXF488030bVr11pfv2TJEixZssTyvKSkBCkpKU1SL7PZDIXCuiFGr9ejsrISKpUKrq6udbzSftRWB0fDOtw6k1nAfAv/Rg4fPgIAiI3t3VQhNQmFJDUoCZD7ODQF1sE+NHUdYmNjkZGRUes6u28J0Ol0ViPmq/8uKSmpNwmoqKjAjBkz8MADD1gSAABISEjAgAEDoNfr8cYbb2DMmDE4deoUvLy8apSxaNEiLFq0yPI8LCzshonHzcrOzq5RlsFggFKpdJgPcG11cDSsg/yOJ0oQQiAsJFjuUG6Jox8HgHWwpXe2pmB2v3DLfSyuZcs6yHq2mTZtGiRJqvMBAFqtFkVFRZbXVP/t6Vn3VJ+VlZWYOnUqAgMD8f7771utGzp0KNRqNTw9PbF48WK4uLhg7969zVC7hlOpVMgsrMCy3RfkDoWIiJpJbm4uHhsRWWsCYGuyJgGrV6+GEKLOBwDExMQgMTHR8prExET4+/vXmSVVVlZi+vTpUCqVWLly5Q3vzKdQKGBPPSIhPm64d4D9j18gIqKGM5vN+Pzzz/HGG2/g3Llzcodj/1cHzJs3D++88w4uXryI/Px8vPrqq5g/f36t2xoMBsyYMQN6vR6rVq2CSqWyWn/ixAkcOXIERqMRZWVleOWVV1BeXo4BAwbYoio3pVRXgt92JuCbb76xq+SEiIhu3dWrV1FRUQGDwWAX3RZ2PybggQceQFpaGvr06QODwYBp06bh1VdftawfP348Bg8ejOeffx579+7FTz/9BDc3N/j5+Vm2+eSTTzBnzhzk5OTgkUceQXp6Otzc3BAXF4fNmzfb1Sx9BoPBct1oTk6OXXxIiIioaQQGBuLpp59GRkZGvd3atmL3SYAkSVi8eDEWL15c6/prr/MfOnRovb+ehw8fjtOnTzd5jE3Jz88PnTt3RkBAANzc3OQOh4iImpibm5vdzBJr90mAM5oxY4bcIRARkRNgEkBERGQDJ0+eRElJCTp27Gg33dB2PzDQmRmNRhQXF8sdBhERNYE9v+/HqxuS8fvvv8sdigWTADt14MABzF/8X6zf+LPcoRAR0S0SQiAkKABDfIrQsWNHucOxYHeAnfL09ISfKERqaj6MRuMN5zsgIiL7JUkSJkyYgNtvv13uUKzwzGKnIiMj8adptyMqKooJABFRC1E9G6694NnFTqnVanTr1k3uMIiI6BaZTCZIkmSX94Wxv4iIiIhakGPHjuHdd9/Fzp075Q6lBiYBdq6kpAS///47zpw5I3coRETUCElJSSgpKUFhYaHcodTA7gA7t337diQmJqJt27Z2NaKUiIhuzuTJk5GcnIyICPu7ORxbAuxc9+7d4eHhgaCgIN5QiIjIAX15KAdx/fojLCxM7lBqYBJg59q2bYsnnvgrKgJj7G5UKRER3disvm2gcVHKHUatmATYOUmS4OKihL9WI3coRETUAHl5eTh+/Dh8NPZ7qrXfyMjKwKjWMJvNqKyslDsUIiK6CUeOHMGPP/6Ir776Su5Q6sSBgQ5i//792LNnD7p27YqxY8fKHQ4REd2AQqGAi4sLOnXqJHcodWIS4CBMJhNKSkqQlJSE0aNH2+WkE0RE9IeRI0di4MCBcodRLyYBDqJXr14wGAzo3bs3EwAiIgfh5uYmdwj1YhLgINzc3DB06FC5wyAiohswGAxwcXFxiCu6+JOSiIioCf3666+Y9fq3OJ6UJHcoN8QkwMEYDAa8tWYPdu/eLXcoRER0HaPRiGPHjqG9IRXlZWVyh3ND7A5wMCdPnkTa8d9RodIjLi7O7vubiIiciYuLC+6//34cPnwYPXr0kDucG2JLgIPp0qUL2nsr0L1bDAwGg9zhEBHRdfz9/TFu3Di4urrKHcoNsSXAwahUKjz++ONQKu1zCkoiInIcbAlwQEwAiIjsz65du5CSkuJQN3tjEuDAhBC4dOmSQ33giIhaovz8fCQkJOC7777D2bNn5Q7npjEJcFB6vR6ffvopli9fjkuXLskdDhGRUzObzYiOjoafnx+ioqLkDuemcUyAg9JoNJZBJxcvXkRERITMEREROa8svQqmdgPx0NRgh5rVlUmAAxszZgxOZJWi3MVD7lCIiJxaTKg3Ogd7Qamw/1kCr8UkwIEFBwfDx88EB5iZkoioRSovL0dBQQFCQkIcLgEAOCbA4bmplXBVVV0tYDabZY6GiMi5HDhwAJ999hnWrFkjdyiNwpaAFiAjIwMJCQnw9vbGnXfeKXc4REROIyMjAwDg5+cncySNwySgBbh69SrOnz8PhUKBESNGwMODYwSIiGxh9uzZuHjxIoKDg+UOpVGYBLQA3bt3R0pKCvr27csEgIjIhiRJQvv27eUOo9GYBLQASqUSM2fOlDsMIiKnUVFRgWIDEOBp//cHqA8HBrYwBpMZJjNnECQiai6lpaV4+9338cqXW1BaWip3OLeESUALszzhNP7zzVpkZmbKHQoRUYt05MgRGPXlaFd+Bi4ujt2g7tjRUw0uaftwJT0dv/5aivvuu0/ucIiIWpzbbrsNXl5eAKpmb3VkbAloYYYPHw5fX1/ExsbyxkJERM1AoVCgR48e6NGjh9yh3DK2BLQw7dq1w6OPPupQc1cTETkCIQSkFjZFq0OcKV566SX4+/vD29sbDzzwAPR6fZ3bDhs2DK6urtBqtZbHtZKTk9G/f3+4u7ujS5cu2L59e3OHb3NMAIiImt6aNWuwZcsWlJWVyR1Kk7H7s8WyZcuwYsUK7N+/HxcuXMDp06fx97//vd7XvPvuu9DpdJZHNYPBgDvvvBMTJ05EQUEBXn75Zdx1113Iyclp7mrIQqfTYcuWLTAajXKHQkTk0NLT03HixAn8/vvvllkCWwK7TwKWL1+ORYsWoX379vDz88PLL7+M5cuXN6qshIQElJWV4dlnn4VGo8HMmTMRExODVatWNXHU8jMYDPj444/x+++/Y+/evXKHQ0Tk0Dxa+cMYOQQdO3ZEdHS03OE0GUnY+egxb29v/Pzzzxg0aBCAqilyAwICkJWVhcDAwBrbDxs2DCdOnIDZbEZkZCReeukly3z677zzDn7++Wds27bNsv2jjz4Ks9mMjz76qEZZS5YswZIlSyzPS0pKkJKS0iT1MpvNzd5sr9frUVFpgFqtgZtG1eTl26IOzY11kN+hQ4cAAHFxcTJHcmsc/TgArMMNyxYCChuMCWjqOsTGxtbZemH3AwN1Oh18fHwsz6v/LikpqTUJeOONN9C5c2e4urpi48aNmDVrFnbs2IG+ffvWKKu6vLS0tFr3vWjRIixatMjyPCwsrNZ9NkZ2dnaTlVUXg8GArMIyuLu5wk/b9Jex2KIOzY11kJ8kSRBCOHQdAMc/DgDrYC9sWQdZU75p06ZBkqQ6HwCg1WpRVFRkeU31356enrWW2a9fP3h5eUGtVmPKlCmYNm0a1q5dW2tZ1eXVVZajU6lUaOPv3SwJABGRM9iwYQN27tzZYsdWyZoErF69GkKIOh8AEBMTg8TERMtrEhMT4e/vf9NZkkKhsCorKSkJZrPZqryYmJimq5SdqqioaNEfZCKipnbp0iUcOXIECQkJTdYVbG/svvNn3rx5eOedd3Dx4kXk5+fj1Vdfxfz582vdtrCwEPHx8SgvL4fJZML69evxww8/YOLEiQCqxgu4ubnhzTffhF6vx6pVq5CUlITp06fbsko2ZzQa8fHHHyMhIQG///673OEQETmE4OBgDBkyBJGRkejcubPc4TQLux8T8MADDyAtLQ19+vSBwWDAtGnT8Oqrr1rWjx8/HoMHD8bzzz8Pg8GAl19+GadOnYJCoUBUVBS++uor3HbbbQCqmsfXr1+PBx54AP/3f/+Htm3bYu3atQgICJCrejbh4uKC7t2748CBA3Bzc5M7HCIih6BSqTB8+PAWOUlQNbtPAiRJwuLFi7F48eJa18fHx1v+9vf3x4EDB+otr1u3bti/f3+TxugIBg8ejL59+9aYPImIiKwJIZCaV4ZW7ir4uKtbbAIAOEB3ADUNlUoFrVYLIQTO5ZTIHQ4RkV0SQmDVqlXY9vsRFJZVyh1Os2MS4GSEALafysb27dtRUsJkgIjoWsnJyTh16hQuH9kOqTRP7nCand13B1DTkiRAk7oHu1NTkZOTg5kzZ7bopi4ioobo2LEj4uLiYDQaERERIXc4zY5JgJORJAl9+/ZFeno6wsLC5A6HiMiuqNVqTJgwwWluxc4kwAl17twZjz32GLy8vOQOhYjILlw/Va+ztJByTICTYgJARFSlqKgIS5cuRVJSktO0AFRjEuDkzGYz9uzZg+TkZLlDISKSxeatv+Jyfgm2bt0Kg8Egdzg2xe4AJ7dz507s3LkL0HggPDycLQRE5HS69h2MY3kS7hjeFWq1Wu5wbIotAU6uX79+UHi0gj4wBh4eHnKHQ0Rkc13D/fHaw3ehQ4cOcodic2wJcHLu7u545i8PwdXVVe5QiIhsprKyEkajEe7u7nKHIiu2BFCNBMBkMskUCRGRbcTHx+Pjjz9Gamqq3KHIikkAWQghcPToUSxduhQ6nU7ucIiImkVxcTFOnz6NkpIS5Obmyh2OrJgEkEVFRQW2bduGwsJC/Prrr3KHQ0TULLy8vPDwww9j6NChiI2NlTscWXFMAFm4ublh8uTJOH78OMaNGyd3OE7JZBYwmRt2nbLBZEal0dxMETUdpUKCUuEcE7CQ/SoqM6C4woA2vj4YNmyY3OHIjkkAWYmOjkZ0dDRMZoGz2SWIDvSUOySnYTIL/LjvDMpKG9YVU6orhYc2s5miajruHlrc1b8jEwGSTVJSElR+bZBbakQbX+ceEFiNSQDVqsJgwuG0AvhrTFAoFJw/wAZMZoGyUh3GtroKVQPOk8WqEnh52neyZhDA5oKqOjIJIDkcO3YM69atg7+/P+bOnSt3OHaDSQDVykPjggGBAp999hl8fHwwb948qFQqucNyCioJUClv/kSpUjRse1mYnGsqVrI/QggolUr4+fk5/WWB12ISQHUSQqCiogJFRUUoLCyEv7+/3CERETVKz5494e/vj9atWzvNzYFuBpMAqlPbtm0xZcoUhIWFwdvbW+5wiIgaRAhhdcIPDQ2VMRr7xCSA6tW1a1e5QyAiajAhBNatWwcvLy+MGDGCv/7rwHkC6Kbp9XqsXbsWV69elTsUsgPfppgxc7MJvX8w4em99n+JIjmXkydP4ocjV7Bt9z6cPXtW7nDsFpMAumlr1qzByqPZWP7tDzAajXKHQzILcJPwUFcFpkbyFxbZn86dO2NS3ygMjO2B6OhoucOxW0wC6KaNHDkSnTzKMXbYILi4sCfJ1iqMAuM3mLAtveZI+4FrTPg9y7Yj8Ee1kTAyTEIr57rzKjkIhUKBWXeOwR13TGBXQD34n5xuWmBgIF5ctNDp7rdtL1acFfB1rTr5Xq+tJ5BSKDAgqOa6R3eZcLSOHpwgd2DteGVTh0oki8LCwho3QGMCUD8mAdQg1ycAqampiIiI4BetmZmFwLcpAn/pVvU+l1QKXC0H2ntXPXdRABV13PzxwyE8yVPLV1ZWhm+++Qbjxo3DqVOn0LlzZ7lDcgjsDqBGEUJAr9fjyy+/xJ49e+QOp8W7UAzklANDQqpO+utTBT468Ufzf74e8NXIFR2R/Ewmk6Wb0tPOZ9C0J2wJoEYTouoklJ2dXeN6XGpaOWWAqxLwda16j3dfEWjnWfV3VrmEtBLU2hUAAAt2mnCkju6AEHdg3e1sKSDHpjeaYFBoMG/ePOTn5yMkJETukBwGkwBqFEmS4OrqijvuuAO9e/dGal4Z2rX2kDusFstbU9Xcf6FY4EppVVIAIVBuFPjwlBqjwoAwbe1JwMdDm+ckbzQLmARgFIBZAHqTgEICVLw3ANmIEAKVlZW4WKDH+ZxSTOgeDKWSSW1DsDuAbklsbCwqTWb8eiobAGoMyqGm0bkVMLmdhDlbzfgo2YwPBiugMwAjfzIDEvBKH9t/lT89IRC3yozPTgpsSa/6+5UDvEcA2c7WrVvx3//+F8FuAhO6B8sdjkNiSwDdMo2LEg8Mbo/U1FT89NNPmDVrFgIDA+UOq0VRSBL+0U/CP/r9seyb0VW/eIqLS+Glsf2AgD93U+DP3Wy+WyIAQH5+Pg4ePAij0YjExEQMHTpU7pAcElsCqEmYTCasX78ehYWF+Pnnny3jBYiImoOvry/uvfdexMXFYciQIXKH47DYEkBNQqlUYvbs2di4cSOmTp3KQYJE1CyuHYQcHh6O8PBwmSNybGwJoCbTunVrzJ07l5fnEFGzOHToENZv2MiWxibEJICa1LUtAOXl5fjym++Ql5cnY0RE1BJkZmbih41bsPzAFRw4cEDucFoMJgHUbFb8sAZrT+vw9ddf84ZDRHRLQkJCMGZQX0zr5I7Y2Fi5w2kxOCaAms0dY0ehKHcFxo+/gzccakJCCHyTIvDDOYGsMkDr4oaxEWb8pZsED5Vtx2L8J6nqEkHVNZdmfzREgdgAjgmhpiVJEkaOHAmz2cy5AJoQ/zNTswkKCsJjjz0GlUoldygtyptHBXZkCrzWT4EerYGU7DK8e9odDycILB+psPlkPaPaSHhrIBsVqWkJIbBnzx74+flZ7gMgSRITgCbGby41q2sTACEEtm7diosXL8oYkWO7VCLw7VmBNwZU/dp2UUgI8xB4Z5ACaSVAfBoHTFHLcPjwYfz6669YvXo10tPT5Q6nxWJLANnMgQMHsHfvXuzbtw8PPfQQJxRqhH3ZAgFuQI/W1r/2PVQSBodI2JMFTGxX83U/p5rx2uG6E4SlQxTo7d+4FoTfrggMWmuCryswqZ2E+Z0kKHiJKN0Ck1mgQ6cuOHz4MAIDA3kvgGbkEEnASy+9hI8//hiVlZWYPn06PvzwQ2hqmSHt0qVL6NKli9WysrIyLFy4EO+//z6AquYkd3d3yyj2wYMHIz4+vvkrQejatSsSExMRHBwMg5qXETZGoR4IcKt9XWtX4HRB7Sf6CW0VmNC26eMZEy5haqQEfzfgVAHw9F4zXCRgbicmAdR4B1PzUVBaiblz50Kj0XDekWZk990By5Ytw4oVK7B//35cuHABp0+fxt///vdatw0PD4dOp7M80tPToVarMWPGDKvtDh8+bNmGCYDtaLVazJs3DxMmTMC6o5kwmdl03VA+mqpbCtcmtwJo5Wrbf5ZR3hIC3at++Xf1lfBgFwlb0nlcqeFKS0uxcuVKFBUVoX97P4zvFgxXV1cmAM3M7pOA5cuXY9GiRWjfvj38/Pzw8ssvY/ny5Tf12m+//Rbh4eEYNGhQM0dJN0uj0UCpVGLhiGgoFRLOnTuHjRs3wmw2yx2aQ+gXKCG7DDiWa32iLTUI/HZFoG9A7a/bmGpG39WmOh+Hc5rmxK2QAM7jQg0lhMDKlStx5swZfPfdd/x/YEN23x2QnJyMnj17Wp737NkTV69eRXZ29g37lJcvX4758+fXWD5ixAiYTCbExcXhzTffRNeuXWt9/ZIlS7BkyRLL85KSEmRnZzeuItcxm81NVpZcbrUO1V/0jh07IiMjo9YunuZmT8fBYDKjVFeKYlUJVHWk560ATI1Q45k9SrzYQ4+uPmZklQFvH6hEK5UCg33LUVxc83VDfIFtY+rff22vu5FdWUr09DXBSw2cK5bwSZIrJrQxorjYYF03M1Cqc0dOTjZUSuvKVc/+Zi/HobHs6bPUWHLWYfz48SgrK4ObmxuuXr3a6HJ4HBrG7pMAnU4HHx8fy/Pqv0tKSupNAo4fP47ExESsX7/eanlCQgIGDBgAvV6PN954A2PGjMGpU6fg5eVVo4xFixZh0aJFludhYWFNNpjtZpIYe3erdRBCYPfu3Th+/Djmz58PDw+PJozu5tjTcag0muGhzYSXpydUyrqbQP/eX+CrMwJvnnBDZmnVCbZ/IPDfkQq0dqv5OW5Ou5LNeCNZQG8CWrsBkyMl/KmzC5QK64ELBpOAh8EDAQGBULtYJwGSJEEIYTfHobHs6bPUWLauw7X3AQCAyspKqNXqWyqTx6FhZE0Cpk2bhjVr1tS5XggBrVaLoqIiy7Lqv280P/3y5csxduzYGqNKq283qVarsXjxYnz99dfYu3cvxo0b19hqUCNJkoQhQ4agf//+Vl98k8nEa4HrIUkS5naSMLdT1fPlx8uwMlUDowzN8G9yfgBqBCEEdu3ahYQz2Xj+/qlQuVR93281AaCGk/UbvHr1aggh6nwAQExMDBITEy2vSUxMhL+/f71ZksFgwDfffFNrV8D1FAoFb0Yhs2u/+AknM/HSu59bHXOq39S2RjwSI+HoVX6OyTFcunQJCQkJuJRxGYePHJU7HKdm990B8+bNwxtvvIHbb78d3t7eePXVV294ct+wYQMAYOLEiVbLT5w4Ab1ej+7du6OyshJvvvkmysvLMWDAgGaLnxom6/QRiJJs/PLLL4iOjpali8ARTW7PX+TkOCIiInDbbbehr8GAvnG95Q7Hqdl9EvDAAw8gLS0Nffr0gcFgwLRp0/Dqq69a1o8fPx6DBw/G888/b1m2fPlyzJkzp0bTUk5ODh555BGkp6fDzc0NcXFx2Lx5s9WYA5LXlDvGQmmqQM+ePZkAELUgBQUFaNWqleX5yJEjefmfHbD7JECSJCxevBiLFy+udX1t1/lXtwRcb/jw4Th9+nSTxkdNS61WY/r06VbLjEYjioqK4OfnJ1NURHQrjhw5gp9//hl33nmn5WovJgD2gW2IZNeEENi4cSM+/fRTJCcnyx0OETWQyWTGuQsXYTabcfjwYY7BsjN23xJAzq2srAxpaWmorKzE+as6dDELKGx8lzxbMwgAppv/R2kwV12CZ88M9h0eNaNtp3Pg23kA+ntqMWLECLYA2BkmAWTXPDw88PDDDyMxMRFnRRDKDSZ4aFrmx1apkODuocXmgoa9rlTnDg+D/Y+fcPfQQtnCEziqar07cuQIvL29ERUVhbFdg6pWdOVNgOxRy/xvSi2Kq6sr+vfvj/7XLNu1axc8PDzQu3fvFvPLQqmQcFf/jg2+p0JOTjYCAux/chSlQmIS4AR+++03bN++He7u7liwYMEN53QheTEJIIeTmpqKHTt2AKi6F0FMTIzMETWdxpwoVUpFjVn4iOTSs2dP7Nu3D9HR0bJMBU4NwySAHE5ISAi6d++OwsLCGreOJiLbEkKguLgYXl5ekCQJnp6ebAFwIEwCyOGo1WpMnjwZBoMBCkXVL+D0/DKYinMQFhYGFxd+rIlsoaCgAOvWrcPZPD06DRiD+25rD+DG07qT/eB/S3JIkiRZTQa1cu9ZlB1ZD//Wfpg9ezYngCKyASEErly5AnWlAb29y+QOhxqBHYnUIowOE6juStdqtfIG46RSU1Nx79y5+Oqrr+QOhZrRtdf5+/r64o477sC8eXNb1NgcZ8KWAGoRevbsieDgYAghrLoDKioq4OrqKmNkzmPTpk345quvsGv3Xtx3331yh0NNTAiBAwcOIDk5GfPmzbPc6bN79+4yR0a3gi0B1GIEBgYiKCjI8rywsBDvvfcefv31VxiNRhkjcw4HDx8BAPTs1UPmSKg5ZFzJxsbN25CRkYH9+/fLHQ41ESYB1GL9/vvvqKiowLqDF1BcbpA7nBbvwKHDAID+cbEyR0LNIbVUibCY/ujTpw/i4uLkDoeaCLsDqMUaM2YMPDw8kCO84OX+x/XKRqORVxA0MaPRiLOnTwIAevXqJXM01BTOnDmD48ePY+rUqVAoFBgc7Y9BUZz2t6Xhf0JqsZRKJYYMGWK1rLS0FJ988gliY2Nx2223yRRZy3PmzBkYKisBwHKXOHJceXl5WLlyJQCgffv2iI2tat1hAtDysDuAnMqePXtQUlKCAwcOcJxAEzp69CgAwMfP32pcBjkmPz8/9O7dGx06dED79u3lDoeaEVsCyKkMHz4cKpUKvr6+cHV1RWFREQwmMyRhZhfBLThypCoJ6NadgwIdjRACZ86cwZkzZxDTKw7uFQZ4uqpw++23W64AoJaL//XIqahUKgwfPtzy3Ggy4+djGbiQsBqdO3fGsGHD4ObmJmOEjun3g1WDAgf25aBAR5OdnY3vv/8eABAbGwtPVxUAMAFwEuwOIKemUioQUJGBkpISHDt2zGoiFLo5QggkJx0DwEGBjsJsNlv+DgoKQseOHdGpUyee+J0QWwLI6fXr18/SFeDu7m5ZnpubCx8fH3YT3EBGRgZ0RYUAmATYu6KiIuzYsQN6vR4zZ860LJ82bRpcXFyQnZ0tY3QkB/53I6enVCrRt29fq2VGoxErVqyA0SwwfeoUhIeHyxSd/aseFKhxc0dUVJTM0VB9jp/PwNrD6Yh0yUdmZiZCQ0MBgImuE+ORJ6pFZmYmSkpKsFcfhrla3hGtNt9//z10Oh327dsHAOjcNcZyV0eyD6WlpTCZTPDy8gIA9O3WCSlnziCuyxAEBwfLHB3ZAyYBRLWIiIjAwoULMSk9Ha19W1mWnz17FsXFxejRo4fT/3r62wt/R65OD6OuAEqPVrh4/jzunnMv5s+9F2PGjJE7PKe3d+9e7NixA127dsXkyZMBABqVEn+6e4q8gZFdce7/YkT18PHxsbolsRAC27dvR1ZWFq5cuYI77rhDvuDsgNLFBe6D74Z7ZB+Y9aWoSDuOH7d8BR9vbyYBdkCr1cJoNOLChQswGAxQqVRyh0R2iG13RDfJaDQiNDQULi4u6NOnD0xmgTNZJRBCoLy8XO7wbE7l4gKYTQAAhcYDmvBuMBVfxSMLHpI5MueTmZmJVatWQafT4cV1SRBCICYmBnfeeSf+8pe/MAGgOrElgOgmqVQq3HHHHRg5ciTc3NxQWFaJU1eK4arPx4oVK9CrVy+MHTvWafrFXVxcIEx/zLpYmrQNPXr14q1lbcxkMmHlypXQ6XRo1aoVXr6zan5/SZLQu3dvucMjO+cc/62ImlD1ZEI+7mpM7hWKgwcPwmAw4OrVq06TAABVSVF1S4AQZhiSN+PJx/8ic1Qtn06nw4ULFyzPlUol+vfvj9DQUERERECldJ7PIN06tgQQ3aJJkyYhPDwcrVu3tlr+008/wdvbu2oWNs+Wd4WBSqWCMFe1BFSkHoOLsRxTpnDQWXM6e/Ys3lmxEW1cK/HUk4sszfwDBgzAwIEDeYMfajAmAUS3SKVS1ZhnID8/H1uPpCDf7I5Xw8JabhJgqmoJqEz6BQ8/9CA0Gs0NXkUNUVlZCUmSLCf7sLAwGCUXCIXA1atXERISAgBO1QJFTYtJAFEzcHV1xfQRfXH+wkVERkZall+5cgWnT59G9+7d4efnJ2OEt06lUgHCBGPxVZScPYBHFqyQO6QWZcuWLTh8+DBGjBiBfv36Aajqinr5gSkICgriFL/UJJg+EjUDd3d3DB06FPfPn2fVRHv06FHs2rULa9eulTG6plHVEmBE6bHNGDFqNCIiIuQOyWEJIVBSUgIAuJhbCpNZwGw2o7KyEsePH7faNjQ0lAkANRm2BBDZkK+vL3x9fdG9e3ccuVSAC1dLMS02DLt374a3tzc6deoEtVotd5g3Ra1WQVTooT+xFU9+z1aAxkpPT8f69euh1+vxxBNP4GBqPrzdVIiNjUVQUBA6d+4sd4jUgjEJILKh/v37o1+/fjCbzVAqlegW6o3y8nLs3LkTJpMJ06dPR5cuXeQO86aoXFxQdvo3+Ht7YvTo0XKH4xCEEMjNzYWnpydcXV0BAF5eXsjNzQVQdb3/jLg2VRt7+MPf31+uUMlJMAkgsjFJkizNuSqlAmWVlejcuTPS0tLQoUMHy3ZXsrKxcVM8Yjp3RL9+/exu8JdarUJl1jk88dZbdhebPRJC4L///S9+u1SGx+4ajN7/u+Oit7c37rjjDrRp0wYBAQEyR0nOhkkAkcy8vb0xdepUmM1mq5Pp78dOYcuFCujLDmPAgAGW5eXl5dBoNLKfeNUqNVRqDebPny9rHPaooqIC58+fBwB07doVQFXy5+vrC7dLRUhLz7QkAQAQGxsrS5xETAKI7MT1J/W+XaPgaiqDt7e31fLNmzfjzJkzGDJkiFVyYGteXp6YMXOWw1/l0BSMxj9mTjSYzDh8+DC2bdsGf39/SxIAAIMHD8bgwYNrzClBJBcmAUR2KiwsDGFhYVbLhBA4e/YsKioqoFar8drPJ/FAXNVJOD4+Hr6+vujatSu0Wm2zx/fGP193+lHqeXl5WLduHbKzs/GnP/0JQgi8sv4E/ty3LVQqFfz8/GA0Gi13nGQfP9kbJgFEDkSSJCxYsAAXL15Eu3btENXFFRXF+SgtLcWBAwcAVCUP1UmAXq9Heno6goOD4eHh0ej9Lt1+FtGBnhjbNciy7PoJkDafyMLZ7BIsHBHd6P3Ys+TkZGRmZqJHjx4ICqp6H7RaLTIzMyGEgMlkgiRJeO2ubjCbzXj66ad54x6yexzNQ+RgPD090b17d3h6esLbreokYzQa0atXLwQGBiI4ONiy7ZJNx/DZN9/jnXfegel/s/sBQFlZGUpLS296n9GBnnhiZSI2n8iqdf3mE1l4YmUiogMdf2bEgoICJCUlIS0tzWr5zp078fPeY/h0+2nLMo1Gg3HjxuGee+6xahVRKBRMAMghsCWAqAXw9vbGxIkTaywfHKLE9mSBgIAAq5PUkSNH8OuvvyK6YyfMnDEDSkXVhEb5+flQKpXw8vKymuRobNcgvDurJ55YmYh3Z/W0ahGoTgCuX27viouLLb/iqy/LTMkuwdHdO3D6RBJ69OhhNQFS+/bt4e2dh949rUfwV08ZnZ2dbbvgiZqI3bcE7NixA8OHD4e3t7elCa4+6enpGDNmDDw8PNCuXTusXLnSav3OnTsRExMDd3d39OnTB8eOHWuu0IlkN6hfLF54/jnMmjXLanlWVtUv+iLhhpUHL1mWb926Fe+++y42b95stf3Zs2cRqdHhjcmdrFoEHCEBKCkpwf79+7F9+3YIISzLT58+jR9++AEJCQmWZWezdfBpHQh3d/cav+THjx+Pe+65x2HmcSC6GXbfEuDh4YH7778f99xzD1544YUbbn/33Xeje/fu+Omnn7B//37ceeediImJQUxMDPLy8jBp0iS8//77mDlzJj788ENMnDgRKSkpvPEJtVjVv+yvddddd2HQoEFQKBRW16YXFhYCqJrZsNqL65Lgd/FXFBcXYcqUKZYWgdu7BWH90QzMiqhAbOAf/0oqKytx7tw5aDQatG3b1tICYTabIYRo0GBCg8EAvV4PlUpl9R09efIkKioqEBkZabl6orhEh2++/ho6XQkWLFhgqXNxcTF++eUX6IUSe8sC8eIdVaP1/fz84OrqCnd3dwghIEkSJnQPhskUgDFDeUc+cg523xLQt29f3HvvvVY3YanL2bNnsX//frz22mtwc3PDsGHDMHHiRHz55ZcAgLVr1yIqKgr33XcfNBoN/vrXv8JsNmPbtm3NXQ0iu6JUKhEUFFRjcpoHH3wQjz32GGJiYizL/j6hM1QqF6hUKnh6Vg0OvL1bMNYcyUSEIg8FV1KxNvGPpvDCwkKsWrUK33zzDQwGAwBgx+kcnD1/AYsXL8a///1vq32azWYAwOLX/4Xt27dbrVu2bBnefvtt7Dt8DNtP/7GPDRs2YMOGDZYWDQD49vAVnM8uQnl5uWUefqBqRr7AwED07NIBfx3e1rK8ffv2+Nvf/oZ586zv76BUKpkAkNOQxLXtY3YsISEBs2bNsvrSX+/HH3/E008/jXPnzlmWvfXWW9i+fTvi4+Px+OOPo7S0FMuWLbOsnzBhAoYMGYK//e1vNcpbsmQJlixZYnleUlKClJSUJqnP9RPDOCLWwT7Yug47zxXg7/EXMSK6FbafzcdLo9pgZCd/y4nTbDajrKwMQgjLFQR6oxkKmFFeVgZJkqyuLDh06BAAoEOHjtBo1Fa/+EtLS2EymaDRuELh4gKVUmFZDlQNzKu+/A6oajmonpHR1idyfpbsA+tQU2xsLDIyMmpdZ/fdAQ2h0+ng4+NjtczHx8fyq0Cn06FVq1Z1rr/eokWLsGjRIsvzsLAwBAYGNkms2dnZTVaWXFgH+2DLOmw+kYWXf0nFe3f3wtiuQZYxAa39/TG2a/0xVFRUIF+SYDKZao1XkqruvnjtRDoFBQUAqpbbe5cdP0v2gXVoGFnTpWnTpkGSpDofDaXValFUVGS1rKioyPKr40briahutQ0CvPaqgbouH6zm6uqKkJAQtGnTxmp59Xc9Kiqqxkx6rVq1QqtWrew+ASByVLImAatXr4YQos5HQ8XExCAtLc0yuAkAEhMTLf2bMTExSExMtKwTQuD48eNW/Z9EVFN9VwE0JBEgIvti9x0nZrMZFRUVqKysBFDVpKjX62vdNjo6Gn369MGLL76I8vJy7Nq1C+vXr8fcuXMBAFOmTMHZs2fxzTffoLKyEu+99x4AYNSoUbapDJGDOptdUu9lgNWJwNns2rvWiMg+2f2YgF27dmH48OGW525uboiIiEBqaiqAqmt3Bw8ejOeffx4AsHLlStx///3w8/NDQEAAPvnkE8svfT8/P6xbtw4LFy7Egw8+iJiYGKxfv55NjUQ3cDNTAY/tGmS3cwUQUe3sPgkYNmxYvV0D8fHxVs/btGmDrVu31ltecnJyk8VHRETkqOy+O4CIiIiaB5MAIiIiJ8UkgIiIyEkxCSAiInJSTAKIiIicFJMAIiIiJ8UkgIiIyEkxCSAiInJSTAKIiIicFJMAIiIiJ8UkgIiIyEkxCSAiInJSTAKIiIiclCTqu0UfWdFoNPD392+SsnQ6HbRabZOUJRfWwT6wDvaBdbAPrENNV69ehV6vr3UdkwCZhIWFISMjQ+4wbgnrYB9YB/vAOtgH1qFh2B1ARETkpJgEEBEROSkmATJZtGiR3CHcMtbBPrAO9oF1sA+sQ8NwTAAREZGTYksAERGRk2ISQERE5KSYBBARETkpJgHNZMeOHRg+fDi8vb0RFBR0w+3T09MxZswYeHh4oF27dli5cqXV+p07dyImJgbu7u7o06cPjh071lyhW3nppZfg7+8Pb29vPPDAA3VOOHHp0iVotVqrh0KhwGOPPWbZRpIkeHh4WNaPHz/eruoAAMOGDYOrq6tVPa6VnJyM/v37w93dHV26dMH27dubO3wAN1+HnJwczJ49G6GhofDy8kJcXBy2bNlitY2tjkNhYSFmzJgBT09PhISE4N13361z2xt9vpcuXYrQ0FBotVpMnToVBQUFzRLztW42/n379mHs2LHw8/ODn58fJkyYgLNnz1rWJyQkQKFQWH2mXn/99WaPvyF1AG78uVi9ejUiIyPh7u6OkSNHIi0trZmjr3KzdVixYoXVe+zh4QFJkrB27VoA8h6HpUuXIi4uDhqNBrNmzap3W5t/FwQ1i/3794uvvvpKLFu2TAQGBt5w+9tuu0088sgjoqysTOzYsUNotVqRlJQkhBAiNzdXeHt7iy+//FJUVFSIt99+W4SHh4uKiopmrcNnn30m2rVrJ86fPy9yc3PFbbfdJp555pmbem1+fr7QaDRi9+7dlmUAxKlTp5or3Fo1tA5Dhw4VH330Ua3rKisrRdu2bcVrr70mKioqxMqVK4WXl5fIzs5urvCFEA2rw/nz58Vbb70lMjIyhMlkEmvWrBEeHh4iNTXVso2tjsOcOXPExIkTRVFRkTh+/Ljw9/cXmzZtqrHdjT7fW7ZsEb6+vuLw4cOiuLhYTJ8+XcyYMcNu4t+0aZNYuXKlKCwsFHq9XjzzzDOiU6dOlvU7duy4qf8BzeFm6yBE/Z+LkydPCg8PD7F582ZRVlYmnnjiCdG3b9/mDN2iIXW41qZNm4SXl5coLS0VQsh7HNasWSN+/PFH8eijj4qZM2fWuZ0c3wUmAc3sZj54KSkpwsXFReTn51uWzZ49Wzz11FNCCCE+/fRTERsba1lnNptFWFiY2LhxY/ME/T8DBw4UH3zwgeX5li1bhL+//029dunSpSI6OtpqmRxJQEPrUF8SsGXLFhEQECBMJpNV+UuXLm26gGtxK8dBCCE6d+4sVq9ebXlui+Og0+mEWq22JLJCCPH888+LadOm1dj2Rp/v2bNniyeffNKyvvr7UlhYaBfxXy87O1sAELm5uUII+U4+Da1DfZ+L559/XkydOtXyvLi4WGg0GpGcnNy0QV/nVo7DtGnTxIMPPmh5LmcSUO3ll1+uNwmQ47vA7gA7kJycjIiICLRq1cqyrGfPnkhOTras79mzp2WdJEno3r27ZX1zxnXtfnv27ImrV68iOzv7hq9dvnw55s+fX2P5iBEjEBgYiAkTJuDEiRNNGW6tGlOHl156CX5+fujbty82bNhgVVa3bt2gUPzxtbn2ODWXWzkOly9fxrlz59C1a1er5c19HFJSUmA2mxETE2MVd23v1Y0+39evj46OhlqtxunTp5s87sbEf72dO3ciKCgIfn5+lmV5eXkICgpCREQEHn74YeTn5zdL3NdqTB3q+lxcfww8PT0RGRnZ7J/9xh6HvLw8rF+/vsb/IDmOQ0PI8V1gEmAHdDodfHx8rJb5+PigpKTkptbbKq7qv2+03+PHjyMxMRFz5861Wp6QkIDU1FScO3cOvXr1wpgxY1BcXNzUYVtpaB3eeOMNnD9/HleuXMGzzz6LWbNm4cCBA7WWVV2evR6HiooKzJgxAw888AA6depkWW6L46DT6eDt7W21rK73yh4//w2J/1oXLlzAwoULrfqtO3XqhMTERFy+fBm//fYbMjIyanw3mkND61Df50LOz35jjsOKFSsQGRmJAQMGWJbJdRwaQo7vApOARpg2bRokSarz0VBarRZFRUVWy4qKiuDp6XlT65urDtfvt/rvG+13+fLlGDt2LEJCQqyWDx06FGq1Gp6enli8eDFcXFywd+9eu6pDv3794OXlBbVajSlTpmDatGmWgUWOdBwqKysxdepUBAYG4v3337da19THoTZarbZGYlHXeyXH5/9GGhJ/tfT0dIwaNQp/+9vfMHPmTMvyoKAgdO3aFQqFAm3atMHSpUuxadMmlJWVNVv8QMPrUN/nQo5jUL3fhh4HoPaWSLmOQ0PI8V1gEtAIq1evhqgaT1Hro6FiYmKQlpaGwsJCy7LExERLE1hMTAwSExMt64QQOH78uFUTWXPU4fr9JiYmwt/fH4GBgXWWazAY8M0339TaFXA9hULRqPeruetQV4wxMTFISkqC2Wy2Ks/ejkNlZSWmT58OpVKJlStXwsXF5abr2FQ6dOgASZKsmpTreq9u9Pm+fv25c+eg1+utWjeaWkPiB4CMjAyMGDECDz300A2nfK1+v5v6Pb9eQ+twves/+9ceA51Oh/Pnz9/SZ/9mNKYOR48eRXJyMu699956y7bVcWgIWb4LjR5NQPUymUyivLxcbN68WQQGBory8vJ6R/MPHDhQPProo6KsrEzs3LlTeHp61rg64OuvvxZ6vV688847ok2bNs1+dcCnn34qIiMjxYULF0ReXp4YPHjwDa8OWLNmjWjdurXQ6/VWy5OTk8Xhw4eFwWAQpaWl4uWXXxaBgYGioKCgGWvQsDoUFBSITZs2ibKyMmE0GsVPP/0k3N3dxW+//SaE+OPqgH/+85+ioqJC/PDDDza5OqAhdaisrBSTJk0SY8eOrfXzYcvjMHv2bDFp0iRRXFwskpKSRGBgYL1XB9T1+d6yZYvw8/MTR44cESUlJWLmzJk2uTrgZuPPzMwUUVFR4pVXXqm1nO3bt4uLFy8Ks9ksrly5IiZOnCjGjh3b3OELIW6+Djf6XFRfHbB161ZRXl4uFi1aZLOrA262DtX+8pe/iDvvvLPGcjmPg8FgEOXl5eKFF14Q06dPF+Xl5aKysrLGdnJ8F5gENJMdO3YIAFaPiIgIy/px48aJ1157zfL80qVLYtSoUcLNzU1ERESIb7/9tkZ5Xbt2Fa6uriIuLk4cPXq02etgNpvFCy+8IPz8/ISXl5e4//77rU4s19dBCCHuuOMO8fjjj9coa/v27aJjx47C3d1d+Pn5ibFjx4rExMTmrkKD6pCTkyP69OkjtFqt8PLyEr1797YaVS+EEMePHxd9+/YVrq6uolOnTmLbtm12VYeEhAQBQLi5uQkPDw/L45tvvhFC2PY4FBQUiGnTpgkPDw8RFBQk3nnnHcs6Dw8PsWvXLsvzG32+P/jgAxEcHCw8PDzEXXfdZXUlTXO52fhfeeUVAcDq/fbw8BBpaWlCCCHefvttERYWJtzc3ERISIi4//77RU5OTrPH35A63Mzn4ocffhDt2rUTbm5uYvjw4VaXndpDHYQQQq/XCz8/P/Hjjz/WKEfO4/Dyyy/XOB/MnTu31jrY+rvAGwgRERE5KY4JICIiclJMAoiIiJwUkwAiIiInxSSAiIjISTEJICIiclJMAoiIiJwUkwAiIiInxSSAiIjISTEJICIiclJMAohIFiaTCYsXL0ZkZCQ0Go3lzolubm4wGo1yh0fkFJgEEJEs/vGPf2DNmjX45ZdfUFxcjDlz5qBv3744fPjwDe98SERNg/cOICKbKy0thb+/P/bu3YuePXsCAH7++WcsWLAA6enp8gZH5ETYEkBENrdz504EBARYEgAAyMvLQ2BgoHxBETkhJgFEZHO5ublo1aqV1bI1a9Zg0qRJMkVE5JyYBBCRzXXr1g0nTpzAvn37UFlZiXfeeQdJSUl47LHH5A6NyKlw9A0R2VyvXr2wePFiTJs2DZWVlRg6dCgSEhLg7e0td2hEToUDA4mIiJwUuwOIiIicFJMAIiIiJ8UkgIiIyEkxCSAiInJSTAKIiIicFJMAIiIiJ8UkgIiIyEkxCSAiInJSTAKIiIicFJMAIiIiJ/X/ceUSsgRX9OEAAAAASUVORK5CYII=", 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "T1_bp = sig.TransferFunction( num_pbanda, den_pbanda )\n", "\n", "# el caracter \"_\" descarta la salida de la función\n", "_= analyze_sys([T1_bp], sys_name='BP 2ºord Q={:d}'.format(Q_bp))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "y con la corroboración numérica se culmina el análisis del primer orden para continuar con los órdenes superiores." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Prototipo pasabajos de segundo orden\n", "\n", "En este caso, la función transferencia *prototipo* será\n", "\n", "$$ T_{lp} = \\frac{k.b}{p^2 + p.a + b}, $$\n", "\n", "siendo $a, b$ y $k$ coeficientes reales y positivos. Procediendo del mismo modo\n", "\n", "$$ T_{bp}(s) = T_{lp}(p)\\Big\\vert_{p = K_{bp}} $$\n", "\n", "llegaremos a una función pasabanda de orden 4, para lo cual utilizaremos las posibilidades que da el análisis simbólico y pondremos foco en los parámetros de sendos pasabanda:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle T_{bp}(s)=\\frac{b k s^{2}}{Q_{bp}^{2} \\left(s^{4} + 1 + \\frac{a s^{3}}{Q_{bp}} + \\frac{a s}{Q_{bp}} + \\frac{s^{2} \\left(2 Q_{bp}^{2} + b\\right)}{Q_{bp}^{2}}\\right)}$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "H2 = k*b/(s**2 + s*a + b)\n", "\n", "H2bp = sp.simplify(sp.expand(H2.subs(s, Kbp)))\n", "\n", "num2_bp, den2_bp = sp.fraction(H2bp)\n", "\n", "num2_bp = sp.Poly(num2_bp, s)\n", "\n", "den2_bp = sp.Poly(den2_bp,s)\n", "\n", "den_bp_lc = den2_bp.LC()\n", "den2_bp = den2_bp.monic()\n", "\n", "#print_latex(sp.latex(num2_bp/den_bp_lc * 1/den2_bp))\n", "\n", "print_latex(a_equal_b_latex_s('T_{bp}(s)', sp.latex(num2_bp/den_bp_lc * 1/den2_bp)))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Análisis de los pasabandas resultantes\n", "\n", "Lamenatablemente no es sencillo ordenar los polinomios como uno está acostumbrado a escribirlos, pero si se presta atención, se notará que existe simetría en los valores de los coeficientes del denominador. Se propondrá entonces la siguiente factorización para intentar llegar a la equivalencia de los coeficientes:\n", "\n", "\n", "$$ T_{bp}(s) = \\frac{s^2.\\frac{k.b}{Q_{bp}^2}}{s^4 + s^3 . \\frac{a}{Q_{bp}} + s^2 . \\frac{2Q^2_{bp}+b}{Q^2_{bp}} + s . \\frac{a}{Q_{bp}} + 1} = \\frac{k_1 \\cdot s\\frac{\\omega_1}{q_1}}{s^2+s\\frac{\\omega_1}{q_1}+\\omega_1^2} . \\frac{k_2 \\cdot s\\frac{\\omega_2}{q_2}}{s^2+s\\frac{\\omega_2}{q_2}+\\omega_2^2} $$\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "#### Se igualan los coeficientes en ambos miembros" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/latex": [ "$\\displaystyle s^{4} + w_{1}^{2} w_{2}^{2} + \\frac{s^{3} \\left(q_{1} w_{2} + q_{2} w_{1}\\right)}{q_{1} q_{2}} + \\frac{s^{2} \\left(q_{1} q_{2} w_{1}^{2} + q_{1} q_{2} w_{2}^{2} + w_{1} w_{2}\\right)}{q_{1} q_{2}} + \\frac{s \\left(q_{1} w_{1}^{2} w_{2} + q_{2} w_{1} w_{2}^{2}\\right)}{q_{1} q_{2}}=s^{4} + 1 + \\frac{a s^{3}}{Q_{bp}} + \\frac{a s}{Q_{bp}} + \\frac{s^{2} \\left(2 Q_{bp}^{2} + b\\right)}{Q_{bp}^{2}}$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "w_o1, w_o2, qq1, qq2 = sp.symbols(\"w_1, w_2, q_1, q_2\", complex = False)\n", "\n", "# planteando la distributiva\n", "den1 = s**2 + s*w_o1/qq1 + w_o1**2\n", "den2 = s**2 + s*w_o2/qq2 + w_o2**2\n", "\n", "den4 = den1 * den2\n", "\n", "den4 = sp.Poly(den4,s)\n", "\n", "den4_coeffs = den4.all_coeffs()\n", "\n", "#print_latex(sp.latex(den4.expr))\n", "\n", "print_subtitle('Se igualan los coeficientes en ambos miembros')\n", "\n", "print_latex(a_equal_b_latex_s(sp.latex(den4.expr), sp.latex(den2_bp.expr)))\n", "\n", "# coef s^0\n", "#print_latex(sp.latex(den4_coeffs[-1]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![nada](./img/nada.png)\n", "\"Homero\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "para luego plantear un sistema de ecuaciones, que describe el comportamiento de la transformación. Comenzamos por el coeficiente de $s^0$, posiblemente el más evidente\n", "\n", "$$ \\omega_1^2 .\\omega_2^2 = 1 $$\n", "\n", "es decir que \n", "\n", "$$ \\omega_1 = \\frac{1}{\\omega_2} $$\n", "\n", "Esta es una primer relación muy importante entre las frecuencias centrales de ambos pasabanda, se encuentran geométricamente centradas respecto a la $\\omega_0=1$ del núcleo de la transformación $K_{bp}(s)$.\n", "\n", "Luego, del mismo modo, analizando las restricciones de los coeficientes de primer y tercer orden surge que\n" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "#### del coeficiente $s^3$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/latex": [ "$\\displaystyle \\frac{a}{Q_{bp}}=\\frac{\\frac{q_{1}}{w_{1}} + q_{2} w_{1}}{q_{1} q_{2}}$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/markdown": [ "#### del coeficiente $s^1$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/latex": [ "$\\displaystyle \\frac{a}{Q_{bp}}=\\frac{q_{1} w_{1} + \\frac{q_{2}}{w_{1}}}{q_{1} q_{2}}$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "c3 = den4_coeffs[1]\n", "\n", "c1 = den4_coeffs[3]\n", "\n", "# substituimos la relación obtenida\n", "c3 = c3.subs(w_o2, 1/w_o1)\n", "c1 = c1.subs(w_o2, 1/w_o1)\n", "\n", "# coef s^3\n", "print_subtitle('del coeficiente $s^3$')\n", "print_latex(a_equal_b_latex_s(r'\\frac{a}{Q_{bp}}', sp.latex(c3)))\n", "\n", "# coef s\n", "print_subtitle('del coeficiente $s^1$')\n", "print_latex(a_equal_b_latex_s(r'\\frac{a}{Q_{bp}}', sp.latex(c1)))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Es decir que la igualdad que debe darse será\n", "\n", "$$ \\frac{ \\frac{q_1}{\\omega_1} + q_2.\\omega_1}{q_1.q_2} = \\frac{ \\frac{q_2}{\\omega_1} + q_1.\\omega_1}{q_1.q_2} = \\frac{a}{Q_{bp}} $$\n", "\n", "$$ \\frac{ \\omega_2 - \\omega_1}{q_1} = \\frac{ \\omega_2 - \\omega_1}{q_2} $$\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Lo cual indica finalmente que $q_1 = q_2 = q$.\n", "\n", "Continuando con el análisis de los coeficientes se puede llegar a expresiones de $q$ y $\\omega_2$ (Ver Schaumann 9.2):\n", "\n", "$$ q^2 = \\frac{Q_{bp}}{a} \\left( \\frac{2Q_{bp}}{a} + \\frac{b}{2aQ_{bp}} \\pm \\sqrt{\\left( \\frac{2Q_{bp}}{a} + \\frac{b}{2aQ_{bp}} \\right)^2 - 1} \\right) $$\n", "\n", "$$ \\omega_2 =\\frac{1}{\\omega_1}= \\frac{a q}{2 Q_{bp}} + \\frac{1}{2} \\sqrt{\\frac{b}{Q_{bp}^2} - \\frac{1}{q^2}}$$\n", "\n", "Si bien no son expresiones sencillas, ni mucho menos prácticas para su memorización, podemos obterner alguna aproximación bajo algunas asunciones del prototipo pasabajo:\n", "\n", "- $ a = \\frac{\\omega_0}{Q_{lp}} = \\frac{1}{Q_{lp}} $ \n", "- $ b = \\omega_0^2 = 1 $\n", "\n", "Esto significa que, si el prototipo pasabajo también está normalizado, el único parámetro libre del prototipo será el $Q_{lp}$. Entonces una aproximación razonable sería:\n", "\n", "$$ q \\approx 2 Q_{bp} Q_{lp}, $$\n", "\n", " luego\n", "\n", "$$ \\omega_2 \\approx 1 + \\frac{1}{2 Q_{bp}}. $$\n", "\n", "De esta manera, solo queda evaluar si esta aproximación es razonable para el filtro bajo diseño. En caso que no sea razonable, resultaría un problema absolutamente numérico, como veremos a continuación.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Conclusiones para prototipos de segundo orden\n", "\n", "Podemos concluir entonces que para un *prototipo pasabajo de segundo orden* \n", "\n", "* se obtendrá una función transferencia pasabanda de orden 4 normalizada ($\\omega_0 = 1$).\n", "* la transferencia podrá entenderse como la cascada de dos pasabandas de segundo orden.\n", "* cada pasabanda tendrá pulsaciones recíprocas $\\omega_1 = \\frac{1}{\\omega_2}$\n", "* ambos pasabanda tendrán igual factor de selectividad Q, es decir $q_1 = q_2 = q$\n", "\n", "Estas observaciones se pueden expresar matemáticamente como\n", "\n", "$$ T_{bp}(s) = \\frac{s^2.k.b}{s^4 + s^3 . \\frac{a}{Q_{bp}} + s^2 . \\frac{2Q^2_{bp}+b}{Q^2_{bp}} + s . \\frac{a}{Q_{bp}} + 1} $$\n", "\n", "Luego si la pulsación natural del prototipo es unitaria $b=1$, \n", "\n", "$$ T_{bp}(s) = \\frac{k_1 \\cdot s\\frac{\\omega_1}{q}}{s^2+s\\frac{\\omega_1}{q}+\\omega_1^2} . \\frac{k_2 \\cdot s\\frac{1}{q.\\omega_1}}{s^2+s\\frac{1}{q.\\omega_1}+\\frac{1}{\\omega^2_1}} $$\n", "\n", "\n", "las siguientes aproximaciones son válidas:\n", "\n", "\n", "* $ q \\approx 2 Q_{bp} Q_{lp} $\n", "* $ \\omega_2 \\approx 1 + \\frac{1}{2 Q_{bp}} $\n", "* $ k_1 \\cdot k_2 \\approx 4 \\cdot Q_{lp}^2 $\n", "\n", "![nada](./img/nada.png)\n", "\"Homero\n", "\n", "A continuación finalizaremos la explicación mediante la simulación numérica" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Análisis numérico\n", "\n", "Se comienza como en el caso anterior, cargando los coeficientes del prototipo pasabajo. Luego de definir los parámetros de la transformación pasabanda, que serán los mismos para poder comprararlos, se procede a la transformación numérica del prototipo." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/markdown": [ "#### Prototipo de segundo orden" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/latex": [ "$\\displaystyle T_{lp}(s)=\\frac{1}{s^{2} + \\sqrt{2} s + 1}$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/markdown": [ "#### Pasabanda obtenido (coeficientes de los polinomios)" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "[0.04 0. 0. ]\n", "[1. 0.28284271 2.04 0.28284271 1. ]\n" ] } ], "source": [ "# coeficientes de la transferencia de primer orden T1\n", "T2_num = np.array([1])\n", "T2_den = np.array([1, np.sqrt(2), 1])\n", "\n", "# Q de la transformación\n", "Q_bp = 5\n", "\n", "# núcleo LP-BP\n", "num_pbanda, den_pbanda = sig.lp2bp(T2_num, T2_den, bw = 1/Q_bp)\n", "\n", "print_subtitle('Prototipo de segundo orden')\n", "\n", "print_latex(a_equal_b_latex_s('$ T_{lp}(s)', sp.latex( 1/(s**2 + s * sp.sqrt(2) + 1) )))\n", "\n", "#display(Markdown('### Filtro pasabanda cuarto orden normalizado Q ={:d}'.format(Q_bp) ))\n", "\n", "print_subtitle('Pasabanda obtenido (coeficientes de los polinomios)')\n", "\n", "print(num_pbanda)\n", "print(den_pbanda)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![nada](./img/nada.png)\n", "\"Homero\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "misma observación que en el caso anterior, con los coeficientes no podemos extraer la información que necesitamos con facilidad. Le damos una vuelta algebraica y se obtiene" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "#### Pasabanda visto como cociente de polinomios" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/latex": [ "$\\displaystyle T_{bp}(s)=\\frac{s^2 \\,\\, 0.04 }{s^4 + s^3 \\,\\, 0.2828 + s^2 \\,\\, 2.04 + s \\,\\, 0.2828 + 1 }$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "print_subtitle('Pasabanda visto como cociente de polinomios')\n", "\n", "# forma un poco más clara\n", "#pretty_print_lti(num_pbanda, den_pbanda)\n", "print_latex(a_equal_b_latex_s('T_{bp}(s)', pretty_print_lti(num_pbanda, den_pbanda, displaystr=False)))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![nada](./img/nada.png)\n", "\"Homero\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "que en el caso de órdenes mayores a dos tampoco es lo suficientemente claro. Por ello se enfatiza la necesidad de factorizar y parametrizar para ganar una mejor perspectiva del funcionamiento del filtro" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "#### Pasabanda factorizado en secciones bicuadráticas (SOS)" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/latex": [ "$\\displaystyle T_{bp}(s)= \\frac{s \\,\\, 0.1565 }{s^2 + s \\,\\, 0.1514 + 1.152 } . \\frac{s \\,\\, 0.2555 }{s^2 + s \\,\\, 0.1314 + 0.8679 }$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# esta es la que va\n", "\n", "print_subtitle('Pasabanda factorizado en secciones bicuadráticas (SOS)')\n", "\n", "sos_pbanda = tf2sos_analog(num_pbanda, den_pbanda)\n", "\n", "# la visualizamos de algunas formas, la tradicional\n", "#pretty_print_SOS(sos_pbanda)\n", "print_latex(a_equal_b_latex_s('T_{bp}(s)', pretty_print_SOS(sos_pbanda, displaystr=False)))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "como se puede observar, la factorización ayuda, pero no es suficiente" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "#### Pasabanda factorizado en SOS parametrizadas $\\omega_0$ y $Q$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/latex": [ "$\\displaystyle T_{bp}(s)= \\frac{s\\,1.034\\,\\cdot \\frac{1.073}{7.089}}{s^2 + s \\frac{1.073}{7.089} + 1.073^2} . \\frac{s\\,1.944\\,\\cdot \\frac{0.9316}{7.089}}{s^2 + s \\frac{0.9316}{7.089} + 0.9316^2}$" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print_subtitle('Pasabanda factorizado en SOS parametrizadas $\\omega_0$ y $Q$')\n", "\n", "#pretty_print_SOS(sos_pbanda, mode='omegayq')\n", "print_latex(a_equal_b_latex_s('T_{bp}(s)', pretty_print_SOS(sos_pbanda, mode='omegayq', displaystr=False)))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "![nada](./img/nada.png)\n", "\"Homero\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nuevamente se enfatiza la similitud con la expresión original de la transferencia pasabanda general\n", "\n", "$$ T_{bp}(s) = \\frac{s . k . \\frac{\\omega_0}{Q_{bp}} }{s^2 + s . \\frac{\\omega_0}{Q_{bp}} + \\omega_0^2} $$\n", "\n", "Para luego identificar los parámetros de cada SOS\n", "\n", "#### SOS1\n", "\n", "* $ \\omega_0 = 1.073 $\n", "* $ Q = 7.09 $\n", "* $ K = 1.03 $\n", "\n", "#### SOS2\n", "\n", "* $ \\omega_0 = 0.932 $\n", "* $ Q = 7.09 $\n", "* $ K = 1.94 $\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Análisis de la respuesta en frecuencia\n", "\n", "Procedemos finalmente a analizar la transferencia pasabanda completa de forma numérica" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "T1_bp = sig.TransferFunction( num_pbanda, den_pbanda )\n", "\n", "# el caracter \"_\" descarta la salida de la función\n", "_ = analyze_sys(T1_bp, sys_name='pasabanda 4to orden Q={:d}'.format(Q_bp))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notar en el diagrama de polos y ceros las observaciones que se hicieron más arriba:\n", "\n", "* $ \\omega_1 = 1.073 $ y $ q_1 = 7.09 $\n", "* $ \\omega_2 = 0.932 $ y $ q_2 = 7.09 $\n", "* $ \\omega_1 = \\frac{1}{\\omega_2} $\n", "\n", "Se deja para quien lea y tenga interés, verificar en el diagrama de módulo el ancho de banda del filtro implementado:\n", "\n", "$$ \\mathrm{BW} = \\frac{1}{Q_{bp}} = 0.2 $$\n", "\n", "Como observación final, revisamos los resultados que arrojan las aproximaciones propuestas\n", "\n", "* $ q_1 = q_2 = \\approx 2 Q_{bp} Q_{lp} = 2 . 5 . \\frac{\\sqrt{2}}{2} = 7.07 $\n", "* $ \\omega_2 \\approx 1 + \\frac{1}{2 Q_{bp}} = 1.1$\n", "* $ \\omega_1 \\approx \\frac{1}{1.1} = 0.9$\n", "* $ k_1 \\cdot k_2 \\approx 4 \\cdot Q_{lp}^2 = 2$\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ahora te toca a vos campeón, andá a diseñar un pasabanda.\n", "\n", "![nada](./img/messi_campeon.jpg)\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.12.3" }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "window_display": false } }, "nbformat": 4, "nbformat_minor": 4 }