{ "cells": [ { "cell_type": "markdown", "id": "b8fe8bda", "metadata": {}, "source": [ "# readDiag - Versão Gerd - Radiância (AMSUA + ATMS)\n", "\n", "Notebook para gerar resutados das análises do processo de assimilação pelo GSI no SMNA com os arquivos prepBUFR\n", "elaborados por INPE e NCEP.\n", "\n", "\n", "## Utilização da classe `read_diag`\n", "\n", "### Bibliotecas necessárias\n", "\n", "Para iniciar a utilização do `readDiag`, carregue primeiro as bibliotecas necessárias para a sua utilização:\n", "\n", "* `gsidiag`: é a biblioteca que contém as classes `read_diag` e `plot_diag`;\n", "* `pandas`: é a biblioteca que fornece as estruturas de dados tabulados utilizadas pelo `readDiag`;\n", "* `matplotlib`: é a biblioteca a partir da qual são confeccionadas as figuras;\n", "* `datetime`: é a biblioteca utilizada para manipular datas.\n", "\n", "A instrução `%matplotlib inline` é um comando mágico do Jupyter e apenas ajusta o ambiente para que não seja necessário utilizar o comando `plt.show()` sempre que figuras forem mostradas dentro do notebook. Se você estiver utilizando o `readDiag` dentro de um script Python, esta diretiva pode ser suprimida e o comando `plt.show()` deve ser utilizado, a depender da situação." ] }, { "cell_type": "code", "execution_count": null, "id": "36e5dd3a-77f6-47d2-b503-2a0184a245a4", "metadata": {}, "outputs": [], "source": [ "# Descomente a linha a seguir para utilizar este notebook no Google Colab\n", "#!pip install readDiag" ] }, { "cell_type": "markdown", "id": "ac6ebc48", "metadata": {}, "source": [ "### Média de Conjuntos de Tamanhos Diferentes\n", "\n", "**Não se deve fazer a média simples das médias se os conjuntos tiverem tamanhos diferentes ($n_X \\neq n_Y$).** \n", "\n", "Se fizermos a média simples, estaremos dando o mesmo peso para os dois grupos, o que distorce a realidade caso um grupo seja muito maior que o outro. Para encontrar a média global correta, precisamos calcular a **Média Ponderada**.\n", "\n", "---\n", "\n", "#### Fórmula da Média Combinada (Global)\n", "\n", "Dadas as médias $\\bar{X}$ e $\\bar{Y}$, e os tamanhos dos conjuntos $n_X$ e $n_Y$, a média ponderada correta é dada por:\n", "\n", "$$\\bar{X}_{global} = \\frac{n_X \\bar{X} + n_Y \\bar{Y}}{n_X + n_Y}$$\n", "\n", "---\n", "\n", "#### Quando a média simples funciona?\n", "A média simples das médias ($\\frac{\\bar{X} + \\bar{Y}}{2}$) só funciona se, e somente se, os dois conjuntos tiverem **exatamente o mesmo número de elementos** ($n_X = n_Y$).\n" ] }, { "cell_type": "markdown", "id": "f80ab3ea", "metadata": {}, "source": [ "### Variância de Conjuntos de Tamanhos Diferentes\n", "\n", "A variância depende diretamente da **distância de cada dado em relação à nova média global**. Se os conjuntos $X$ e $Y$ tiverem médias diferentes, a dispersão do conjunto unificado será maior do que a simples média de suas variâncias.\n", "\n", "Para combinar as variâncias ou desvios padrão, o cálculo correto depende de uma condição: **os dois conjuntos são do mesmo tamanho (mesmo número de elementos)?**\n", "\n", "---\n", "\n", "### Caso 1: Os conjuntos têm tamanhos diferentes ($n_X \\neq n_Y$)\n", "\n", "Se você tem o número de elementos de $X$ ($n_X$) e de $Y$ ($n_Y$), as médias ($\\bar{X}, \\bar{Y}$) e as variâncias ($s_X^2, s_Y^2$ — que são os desvios padrão ao quadrado), a fórmula da **Variância Combinada** é:\n", "\n", "$$s_{combinada}^2 = \\frac{n_X s_X^2 + n_Y s_Y^2}{n_X + n_Y} + \\frac{n_X n_Y (\\bar{X} - \\bar{Y})^2}{(n_X + n_Y)^2}$$\n", "\n", "* **Parte esquerda da fórmula:** É a média ponderada das variâncias atuais.\n", "* **Parte direita da fórmula:** É o ajuste necessário pela diferença entre as duas médias. Se as médias forem muito distantes, a variância final dispara.\n", "\n", "---\n", "\n", "### Caso 2: Os conjuntos têm exatamente o mesmo tamanho ($n_X = n_Y$)\n", "\n", "Se os dois grupos têm o mesmo número de elementos, a fórmula simplifica bastante. Ainda assim, **não é apenas a média das variâncias**:\n", "\n", "$$s_{combinada}^2 = \\frac{s_X^2 + s_Y^2}{2} + \\frac{(\\bar{X} - \\bar{Y})^2}{4}$$\n", "\n", "### Como encontrar o Desvio Padrão Combinado?\n", "\n", "Basta calcular a variância combinada usando uma das fórmulas acima e, no final, **extrair a raiz quadrada** do resultado:\n", "\n", "$$s_{combinado} = \\sqrt{s_{combinada}^2}$$\n", "\n", "---\n", "\n", "### Resumo prático: Quando a sua simplificação funcionaria?\n", "\n", "Você só poderia tirar a média das variâncias ($s_{combinada}^2 = \\frac{s_X^2 + s_Y^2}{2}$) se duas condições fossem atendidas simultaneamente:\n", "1. Os conjuntos tivessem exatamente o **mesmo número de elementos**.\n", "2. Os conjuntos tivessem exatamente a **mesma média** ($\\bar{X} = \\bar{Y}$).\n" ] }, { "cell_type": "markdown", "id": "e268ce84", "metadata": {}, "source": [ "### Variância Combinada para Três Conjuntos ($X$, $Y$ e $Z$)\n", "\n", "Quando temos três conjuntos com tamanhos diferentes ($n_X, n_Y, n_Z$), médias locais ($\\bar{X}, \\bar{Y}, \\bar{Z}$) e variâncias locais ($s_X^2, s_Y^2, s_Z^2$), o cálculo deve ser feito em duas etapas.\n", "\n", "---\n", "\n", "#### Passo 1: Calcular a Média Global ($\\bar{M}_{global}$)\n", "Primeiro, precisamos encontrar a nova média ponderada de todo o conjunto combinado:\n", "\n", "$$\\bar{M}_{global} = \\frac{n_X \\bar{X} + n_Y \\bar{Y} + n_Z \\bar{Z}}{n_X + n_Y + n_Z}$$\n", "\n", "---\n", "\n", "#### Passo 2: Calcular a Variância Combinada ($s_{combinada}^2$)\n", "A fórmula expandida para três conjuntos é a soma da **média ponderada das variâncias** com o **ajuste de translação das médias**:\n", "\n", "$$s_{combinada}^2 = \\frac{n_X s_X^2 + n_Y s_Y^2 + n_Z s_Z^2}{n_X + n_Y + n_Z} + \\frac{n_X(\\bar{X} - \\bar{M}_{global})^2 + n_Y(\\bar{Y} - \\bar{M}_{global})^2 + n_Z(\\bar{Z} - \\bar{M}_{global})^2}{n_X + n_Y + n_Z}$$\n", "\n", "#### Estrutura Simplificada (Soma dos Quadrados)\n", "Uma forma alternativa e mais limpa de escrever a mesma fórmula é:\n", "\n", "$$s_{combinada}^2 = \\frac{n_X [s_X^2 + (\\bar{X} - \\bar{M}_{global})^2] + n_Y [s_Y^2 + (\\bar{Y} - \\bar{M}_{global})^2] + n_Z [s_Z^2 + (\\bar{Z} - \\bar{M}_{global})^2]}{n_X + n_Y + n_Z}$$\n", "\n", "* **Desvio Padrão Combinado:** Para obter o desvio padrão final, basta extrair a raiz quadrada do resultado: $s_{combinado} = \\sqrt{s_{combinada}^2}$.\n", "\n", "---\n", "\n", "#### Generalização para $k$ Conjuntos\n", "Essa estrutura entre colchetes $[s_i^2 + (\\bar{X}_i - \\bar{M}_{global})^2]$ é muito poderosa porque ela se repete para qualquer quantidade de conjuntos que você queira combinar (4, 5, ou $k$ grupos).\n" ] }, { "cell_type": "code", "execution_count": 1, "id": "7bd343fb", "metadata": { "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_2138433/1165987979.py:1: DeprecationWarning: You are importing the legacy package 'gsidiag'. This interface is deprecated and will be removed in a future major release. Please migrate to 'readDiag.open.open_diagnostic' and the DiagnosticAPI.\n", " import gsidiag as gd\n" ] } ], "source": [ "import gsidiag as gd\n", "\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "from datetime import datetime, timedelta\n", "from gsidiag.datasources import getVarInfo\n", "\n", "import os\n", "import numpy as np\n", "\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 2, "id": "1f8e9a25", "metadata": { "scrolled": true }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:28,821 readDiag INFO read_radiance completed in 0.116s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "['2025100112', '2025100118', '2025100200', '2025100206', '2025100212', '2025100218']\n", "\n", "******************** varName = amsua ********************\n", "\n", "########## varType = metop-b ##########\n", "\n", "['/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_amsua_metop-b_01.2025100112', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_amsua_metop-b_01.2025100118', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_amsua_metop-b_01.2025100200', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_amsua_metop-b_01.2025100206', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_amsua_metop-b_01.2025100212', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_amsua_metop-b_01.2025100218']\n", "\n", "['/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_amsua_metop-b_03.2025100112', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_amsua_metop-b_03.2025100118', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_amsua_metop-b_03.2025100200', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_amsua_metop-b_03.2025100206', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_amsua_metop-b_03.2025100212', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_amsua_metop-b_03.2025100218']\n", "\n", "Aguarde, o tempo total estimado para a leitura dos arquivos é de 2 minutos e 0 segundos.\n", "\n", "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_amsua_metop-b_01.2025100112\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:28,925 readDiag INFO read_radiance completed in 0.099s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_amsua_metop-b_01.2025100118\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:29,593 readDiag INFO read_radiance completed in 0.234s\n", "2026-10-23 20:11:29,690 readDiag INFO read_radiance completed in 0.093s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_amsua_metop-b_01.2025100200\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:30,464 readDiag INFO read_radiance completed in 0.214s\n", "2026-10-23 20:11:30,739 readDiag INFO read_radiance completed in 0.212s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_amsua_metop-b_01.2025100206\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:31,498 readDiag INFO read_radiance completed in 0.213s\n", "2026-10-23 20:11:31,763 readDiag INFO read_radiance completed in 0.202s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_amsua_metop-b_01.2025100212\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:32,479 readDiag INFO read_radiance completed in 0.189s\n", "2026-10-23 20:11:32,739 readDiag INFO read_radiance completed in 0.200s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_amsua_metop-b_01.2025100218\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:33,441 readDiag INFO read_radiance completed in 0.165s\n", "2026-10-23 20:11:33,650 readDiag INFO read_radiance completed in 0.191s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Pronto!\n", "Variable Name : amsua\n", " └── kx => metop-b \n", "\n", "columns ['nchan', 'iuse', 'idqc', 'omf', 'emiss', 'oma', 'tb_obs', 'omf_nbc', 'errinv', 'tlach', 'ts', 'pred1', 'pred2', 'pred3', 'pred4', 'pred5', 'pred6', 'pred7', 'pred8', 'pred9', 'pred10', 'pred11', 'pred12', 'pred13', 'pred14', 'spread', 'end_err', 'lat', 'lon', 'time', 'geometry', 'channel', 'obs', 'omf_nobc', 'inverr']\n", "Série temporal -- ASSIMILADOS mask=idqc==0 & iuse>=1\n", "\n", "\n", " =============================================================================================================\n", " Variable: amsua || type: metop-b || AMSU-A radiances from Metop-B || check: OmF\n", " =============================================================================================================\n", "\n", "chs = [ 7 7 7 ... 13 13 13]\n", "found channels = {7, 8, 9, 10, 11, 12, 13}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-01:12\n", "chs = [ 7 7 7 ... 13 13 13]\n", "found channels = {7, 8, 9, 10, 11, 12, 13}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-01:18\n", "chs = [ 7 7 7 ... 13 13 13]\n", "found channels = {7, 8, 9, 10, 11, 12, 13}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:00\n", "chs = [ 7 7 7 ... 13 13 13]\n", "found channels = {7, 8, 9, 10, 11, 12, 13}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:06\n", "chs = [ 7 7 7 ... 13 13 13]\n", "found channels = {7, 8, 9, 10, 11, 12, 13}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:12\n", "chs = [ 7 7 7 ... 13 13 13]\n", "found channels = {7, 8, 9, 10, 11, 12, 13}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:18\n", "levs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]\n", "zlevs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]\n", "\n", " =============================================================================================================\n", "\n", "channels = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]\n", " Calculating for 2025-10-01:12\n", " Calculating for 2025-10-01:18\n", " Calculating for 2025-10-02:00\n", " Calculating for 2025-10-02:06\n", " Calculating for 2025-10-02:12\n", " Calculating for 2025-10-02:18\n", "\n", " =============================================================================================================\n", "\n", " Making Graphics...\n", " Done!\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:36,323 readDiag INFO read_radiance completed in 0.094s\n", "2026-10-23 20:11:36,423 readDiag INFO read_radiance completed in 0.094s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "########## varType = metop-c ##########\n", "\n", "['/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_amsua_metop-c_01.2025100112', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_amsua_metop-c_01.2025100118', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_amsua_metop-c_01.2025100200', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_amsua_metop-c_01.2025100206', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_amsua_metop-c_01.2025100212', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_amsua_metop-c_01.2025100218']\n", "\n", "['/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_amsua_metop-c_03.2025100112', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_amsua_metop-c_03.2025100118', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_amsua_metop-c_03.2025100200', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_amsua_metop-c_03.2025100206', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_amsua_metop-c_03.2025100212', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_amsua_metop-c_03.2025100218']\n", "\n", "Aguarde, o tempo total estimado para a leitura dos arquivos é de 2 minutos e 0 segundos.\n", "\n", "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_amsua_metop-c_01.2025100112\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:36,983 readDiag INFO read_radiance completed in 0.092s\n", "2026-10-23 20:11:37,083 readDiag INFO read_radiance completed in 0.093s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_amsua_metop-c_01.2025100118\n", "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_amsua_metop-c_01.2025100200\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:37,804 readDiag INFO read_radiance completed in 0.202s\n", "2026-10-23 20:11:37,962 readDiag INFO read_radiance completed in 0.134s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_amsua_metop-c_01.2025100206\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:38,619 readDiag INFO read_radiance completed in 0.180s\n", "2026-10-23 20:11:38,874 readDiag INFO read_radiance completed in 0.178s\n", "2026-10-23 20:11:39,514 readDiag INFO read_radiance completed in 0.140s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_amsua_metop-c_01.2025100212\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:39,719 readDiag INFO read_radiance completed in 0.129s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_amsua_metop-c_01.2025100218\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:40,452 readDiag INFO read_radiance completed in 0.178s\n", "2026-10-23 20:11:40,654 readDiag INFO read_radiance completed in 0.137s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Pronto!\n", "Variable Name : amsua\n", " └── kx => metop-c \n", "\n", "columns ['nchan', 'iuse', 'idqc', 'omf', 'emiss', 'oma', 'tb_obs', 'omf_nbc', 'errinv', 'tlach', 'ts', 'pred1', 'pred2', 'pred3', 'pred4', 'pred5', 'pred6', 'pred7', 'pred8', 'pred9', 'pred10', 'pred11', 'pred12', 'pred13', 'pred14', 'spread', 'end_err', 'lat', 'lon', 'time', 'geometry', 'channel', 'obs', 'omf_nobc', 'inverr']\n", "Série temporal -- ASSIMILADOS mask=idqc==0 & iuse>=1\n", "\n", "\n", " =============================================================================================================\n", " Variable: amsua || type: metop-c || AMSU-A radiances from Metop-C || check: OmF\n", " =============================================================================================================\n", "\n", "chs = [ 7 7 7 ... 13 13 13]\n", "found channels = {7, 9, 10, 11, 12, 13}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-01:12\n", "chs = [ 7 7 7 ... 13 13 13]\n", "found channels = {7, 9, 10, 11, 12, 13}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-01:18\n", "chs = [ 7 7 7 ... 13 13 13]\n", "found channels = {7, 9, 10, 11, 12, 13}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:00\n", "chs = [ 7 7 7 ... 13 13 13]\n", "found channels = {7, 9, 10, 11, 12, 13}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:06\n", "chs = [ 7 7 7 ... 13 13 13]\n", "found channels = {7, 9, 10, 11, 12, 13}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:12\n", "chs = [ 7 7 7 ... 13 13 13]\n", "found channels = {7, 9, 10, 11, 12, 13}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:18\n", "levs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]\n", "zlevs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]\n", "\n", " =============================================================================================================\n", "\n", "channels = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]\n", " Calculating for 2025-10-01:12\n", " Calculating for 2025-10-01:18\n", " Calculating for 2025-10-02:00\n", " Calculating for 2025-10-02:06\n", " Calculating for 2025-10-02:12\n", " Calculating for 2025-10-02:18\n", "\n", " =============================================================================================================\n", "\n", " Making Graphics...\n", " Done!\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:43,380 readDiag INFO read_radiance completed in 0.140s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "******************** varName = atms ********************\n", "\n", "########## varType = npp ##########\n", "\n", "['/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_atms_npp_01.2025100112', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_atms_npp_01.2025100118', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_atms_npp_01.2025100200', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_atms_npp_01.2025100206', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_atms_npp_01.2025100212', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_atms_npp_01.2025100218']\n", "\n", "['/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_atms_npp_03.2025100112', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_atms_npp_03.2025100118', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_atms_npp_03.2025100200', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_atms_npp_03.2025100206', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_atms_npp_03.2025100212', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_atms_npp_03.2025100218']\n", "\n", "Aguarde, o tempo total estimado para a leitura dos arquivos é de 2 minutos e 0 segundos.\n", "\n", "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_atms_npp_01.2025100112\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:43,522 readDiag INFO read_radiance completed in 0.136s\n", "2026-10-23 20:11:44,624 readDiag INFO read_radiance completed in 0.135s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_atms_npp_01.2025100118\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:44,765 readDiag INFO read_radiance completed in 0.134s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_atms_npp_01.2025100200\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:45,926 readDiag INFO read_radiance completed in 0.241s\n", "2026-10-23 20:11:46,141 readDiag INFO read_radiance completed in 0.189s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_atms_npp_01.2025100206\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:47,233 readDiag INFO read_radiance completed in 0.228s\n", "2026-10-23 20:11:47,452 readDiag INFO read_radiance completed in 0.193s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_atms_npp_01.2025100212\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:48,569 readDiag INFO read_radiance completed in 0.217s\n", "2026-10-23 20:11:48,799 readDiag INFO read_radiance completed in 0.178s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_atms_npp_01.2025100218\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:49,945 readDiag INFO read_radiance completed in 0.192s\n", "2026-10-23 20:11:50,172 readDiag INFO read_radiance completed in 0.205s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Pronto!\n", "Variable Name : atms\n", " └── kx => npp \n", "\n", "columns ['nchan', 'iuse', 'idqc', 'omf', 'emiss', 'oma', 'tb_obs', 'omf_nbc', 'errinv', 'tlach', 'ts', 'pred1', 'pred2', 'pred3', 'pred4', 'pred5', 'pred6', 'pred7', 'pred8', 'pred9', 'pred10', 'pred11', 'pred12', 'pred13', 'pred14', 'spread', 'end_err', 'lat', 'lon', 'time', 'geometry', 'channel', 'obs', 'omf_nobc', 'inverr']\n", "Série temporal -- ASSIMILADOS mask=idqc==0 & iuse>=1\n", "\n", "\n", " =============================================================================================================\n", " Variable: atms || type: npp || ATMS radiances from Suomi-NPP || check: OmF\n", " =============================================================================================================\n", "\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-01:12\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-01:18\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:00\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:06\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:12\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:18\n", "levs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22]\n", "zlevs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22]\n", "\n", " =============================================================================================================\n", "\n", "channels = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22]\n", " Calculating for 2025-10-01:12\n", " Calculating for 2025-10-01:18\n", " Calculating for 2025-10-02:00\n", " Calculating for 2025-10-02:06\n", " Calculating for 2025-10-02:12\n", " Calculating for 2025-10-02:18\n", "\n", " =============================================================================================================\n", "\n", " Making Graphics...\n", " Done!\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:54,033 readDiag INFO read_radiance completed in 0.136s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "########## varType = n20 ##########\n", "\n", "['/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_atms_n20_01.2025100112', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_atms_n20_01.2025100118', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_atms_n20_01.2025100200', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_atms_n20_01.2025100206', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_atms_n20_01.2025100212', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_atms_n20_01.2025100218']\n", "\n", "['/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_atms_n20_03.2025100112', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_atms_n20_03.2025100118', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_atms_n20_03.2025100200', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_atms_n20_03.2025100206', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_atms_n20_03.2025100212', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_atms_n20_03.2025100218']\n", "\n", "Aguarde, o tempo total estimado para a leitura dos arquivos é de 2 minutos e 0 segundos.\n", "\n", "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_atms_n20_01.2025100112\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:54,172 readDiag INFO read_radiance completed in 0.134s\n", "2026-10-23 20:11:55,184 readDiag INFO read_radiance completed in 0.135s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_atms_n20_01.2025100118\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:55,324 readDiag INFO read_radiance completed in 0.133s\n", "2026-10-23 20:11:56,394 readDiag INFO read_radiance completed in 0.172s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_atms_n20_01.2025100200\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:56,745 readDiag INFO read_radiance completed in 0.332s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_atms_n20_01.2025100206\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:57,673 readDiag INFO read_radiance completed in 0.185s\n", "2026-10-23 20:11:57,910 readDiag INFO read_radiance completed in 0.213s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_atms_n20_01.2025100212\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:11:59,044 readDiag INFO read_radiance completed in 0.213s\n", "2026-10-23 20:11:59,243 readDiag INFO read_radiance completed in 0.175s\n", "2026-10-23 20:12:00,362 readDiag INFO read_radiance completed in 0.179s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_atms_n20_01.2025100218\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:12:00,554 readDiag INFO read_radiance completed in 0.170s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Pronto!\n", "Variable Name : atms\n", " └── kx => n20 \n", "\n", "columns ['nchan', 'iuse', 'idqc', 'omf', 'emiss', 'oma', 'tb_obs', 'omf_nbc', 'errinv', 'tlach', 'ts', 'pred1', 'pred2', 'pred3', 'pred4', 'pred5', 'pred6', 'pred7', 'pred8', 'pred9', 'pred10', 'pred11', 'pred12', 'pred13', 'pred14', 'spread', 'end_err', 'lat', 'lon', 'time', 'geometry', 'channel', 'obs', 'omf_nobc', 'inverr']\n", "Série temporal -- ASSIMILADOS mask=idqc==0 & iuse>=1\n", "\n", "\n", " =============================================================================================================\n", " Variable: atms || type: n20 || ATMS from NOAA-20 || check: OmF\n", " =============================================================================================================\n", "\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-01:12\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-01:18\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:00\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:06\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:12\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:18\n", "levs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22]\n", "zlevs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22]\n", "\n", " =============================================================================================================\n", "\n", "channels = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22]\n", " Calculating for 2025-10-01:12\n", " Calculating for 2025-10-01:18\n", " Calculating for 2025-10-02:00\n", " Calculating for 2025-10-02:06\n", " Calculating for 2025-10-02:12\n", " Calculating for 2025-10-02:18\n", "\n", " =============================================================================================================\n", "\n", " Making Graphics...\n", " Done!\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:12:04,436 readDiag INFO read_radiance completed in 0.147s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "########## varType = n21 ##########\n", "\n", "['/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_atms_n21_01.2025100112', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_atms_n21_01.2025100118', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_atms_n21_01.2025100200', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_atms_n21_01.2025100206', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_atms_n21_01.2025100212', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_atms_n21_01.2025100218']\n", "\n", "['/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_atms_n21_03.2025100112', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_atms_n21_03.2025100118', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_atms_n21_03.2025100200', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_atms_n21_03.2025100206', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_atms_n21_03.2025100212', '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_atms_n21_03.2025100218']\n", "\n", "Aguarde, o tempo total estimado para a leitura dos arquivos é de 2 minutos e 0 segundos.\n", "\n", "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100112/diag_atms_n21_01.2025100112\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:12:04,579 readDiag INFO read_radiance completed in 0.137s\n", "2026-10-23 20:12:05,641 readDiag INFO read_radiance completed in 0.137s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100118/diag_atms_n21_01.2025100118\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:12:05,785 readDiag INFO read_radiance completed in 0.140s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100200/diag_atms_n21_01.2025100200\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:12:06,913 readDiag INFO read_radiance completed in 0.181s\n", "2026-10-23 20:12:07,123 readDiag INFO read_radiance completed in 0.186s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100206/diag_atms_n21_01.2025100206\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:12:08,268 readDiag INFO read_radiance completed in 0.179s\n", "2026-10-23 20:12:08,465 readDiag INFO read_radiance completed in 0.173s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100212/diag_atms_n21_01.2025100212\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:12:09,608 readDiag INFO read_radiance completed in 0.180s\n", "2026-10-23 20:12:09,850 readDiag INFO read_radiance completed in 0.216s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Reading /mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025/2025100218/diag_atms_n21_01.2025100218\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "2026-10-23 20:12:11,021 readDiag INFO read_radiance completed in 0.198s\n", "2026-10-23 20:12:11,248 readDiag INFO read_radiance completed in 0.200s\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Pronto!\n", "Variable Name : atms\n", " └── kx => n21 \n", "\n", "columns ['nchan', 'iuse', 'idqc', 'omf', 'emiss', 'oma', 'tb_obs', 'omf_nbc', 'errinv', 'tlach', 'ts', 'pred1', 'pred2', 'pred3', 'pred4', 'pred5', 'pred6', 'pred7', 'pred8', 'pred9', 'pred10', 'pred11', 'pred12', 'pred13', 'pred14', 'spread', 'end_err', 'lat', 'lon', 'time', 'geometry', 'channel', 'obs', 'omf_nobc', 'inverr']\n", "Série temporal -- ASSIMILADOS mask=idqc==0 & iuse>=1\n", "\n", "\n", " =============================================================================================================\n", " Variable: atms || type: n21 || ATMS from NOAA-21 || check: OmF\n", " =============================================================================================================\n", "\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-01:12\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-01:18\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:00\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:06\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:12\n", "chs = [ 1 1 1 ... 22 22 22]\n", "found channels = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20, 21, 22}\n", "\n", " Preparing data for: Canais de radiancia 2025-10-02:18\n", "levs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22]\n", "zlevs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22]\n", "\n", " =============================================================================================================\n", "\n", "channels = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22]\n", " Calculating for 2025-10-01:12\n", " Calculating for 2025-10-01:18\n", " Calculating for 2025-10-02:00\n", " Calculating for 2025-10-02:06\n", " Calculating for 2025-10-02:12\n", " Calculating for 2025-10-02:18\n", "\n", " =============================================================================================================\n", "\n", " Making Graphics...\n", " Done!\n", "\n" ] }, { "data": { "image/png": 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qg4NDhQV7STExMQSA7ty5I0zz8/MjTU1NyszMFKYdP36c1NXVKTU1VZh2/fp1oeCSLqerq0vZ2dlCG09PT7K1tZX5R8jR0VHuqaKS63d2dqb8/Hxq0qQJRUREUE5ODhkYGNCVK1fKvI40b968zBvSt99+S126dCGi8k/PWVpa0tKlS2WmderUiaZOnSqzXMl/vgoKCqhp06a0YsWKcvvv7u5OmpqapKenR7q6ugSAHBwcZPaxqtRF0dSvXz8aM2ZMuW3lvRd4eXmRnp4e6enpCc+zqhZNO3fuJF1dXZmiR1o0HThwQG5fShZNu3fvJnV19XKfK9Upmk6dOkW6uroUFBQkM70qRVN+fj75+PiQi4sLZWVlVbi+rVu3koaGBr18+VLhPtbEG3N6LikpCSNGjECzZs0gkUhga2sL4PXh9pLatm0r/C09RCo9fC+dJj2FYWxsjLFjx8LT0xM+Pj7w9/dHenq6UvvVr18/6OvrQ19fH05OThX2VVdXF82aNZPb11u3biEvLw99+vQR8vT19bFjx44KTwcmJyejoKAA3bp1E6ZpamrC1dUV8fHxMm27dOki/G1sbAxHR0ehTcl1TpkyRWhnbW2Nt956SyajuLgYCQkJFe+4GioqKkJQUBBGjx4tTBs9ejQCAwNRXFxcpr23tzdycnJw5swZbNu2DePHj5ebu3TpUmRkZGDTpk1wcnLCpk2b0LJlS8TFxVWpf/Lu96r2uaQ2bdpALBbLTIuKioKPjw+sra1hYGAAd3d3AP8+9uLj4+Hm5iazTMn7WJ6cnBzMmTMHrVq1gpGREfT19REfH1/h80wkEsHc3Fx4rMbGxsLFxUXm0H5JV65cwTfffCPzmJo0aRLS09ORl5eHIUOG4MWLF2jWrBkmTZqEgwcPVuvwvY2NDRo3bizcjo+Ph5WVFaysrIRprVu3hpGRkcxzwdbWFgYGBsJtMzMztG7dGmpqajLTSp8KlUdTUxOjR4/G9u3bsXfvXjg4OMjsOwDIzc1FcnIyJkyYILNPlixZUuFzOzs7G2lpaTLPbQDo1q1bhc9tDQ0NdOzYUWjj5OQkrLNfv35Cu1GjRiE2NhZXrlzB2bNnYW9vj759++L58+eVbndNmJqaQl1dXea0KQA8fPgQ5ubmCuc4ODggKyurzKe3gNenAJOTk+Hg4AAAZU6DKWLLli2IjY1FbGys8Ckyc3Nzuf2WzispJCQEEydOxJ49e2ROe9nb20MkEpW5D6Xi4+PRqFEjNG7cuFr9rkhERAR8fHywdu1ajBkzRmZeedtWersKCgowdOhQpKSk4MSJE5BIJBWu083NDYWFhWUuHVAVjcqbNAw+Pj6wsbFBQEAALC0tUVxcjLfffhv5+fky7TQ1NYW/RSKR3Gkl36C2b9+OadOm4ejRo9i9eze++uornDhxAp07d4aamppw3liqoKCgSv3asmULXrx4UaYf8vpVen7Jvubk5AAA/vzzT5kiBQC0tLTk7jNlKvmpncqeBLXh2LFjePDgAYYNGyYzvaioCGFhYejTp4/MdA0NDXz00Ufw8/PDxYsXcfDgwXKzTUxMMGTIEAwZMgTfffcdXFxc8P333yMoKEjY9qysrDLn6Z89ewZDQ0MA8u/3qva5JD09PZnbubm58PT0hKenJ3bu3InGjRsjNTUVnp6eZZ4TVTFnzhycOHEC33//Pezt7aGjo4PBgwdX+DwDZB+rlb2Q5+TkYPHixfjggw/KzNPW1oaVlRUSEhJw8uRJnDhxAlOnTsWqVasQERFRZr0VKb3PFCVv2yra3sqMHz8ebm5uuHbtmtxiXfrcDggIKFPkqqurV6Xr1RIaGiq8rpW87wwNDWFvbw/g9Rv51q1bYWFhgd27d2PixIkq649YLEaHDh0QFhYmXFNaXFyMsLAwfPrppwrnfPjhh5g3bx5Wr16N1atXy8zbtGkTcnNzMWLECACv/wkICgpCQUGB3MeYWCxGUVGRzLTSr8PA6+J06dKlyMzMRJMmTQBAKBxat24ttAsODsb48eMREhJS5vo2ExMT9OnTBz/99BNmzpwpc59kZGRg586dGDNmDEQiEdq0aYPi4mJERESUud5I2m8AZfouT3h4OPr3748VK1bI/QRqly5dEBYWhhkzZgjTTpw4IVOQSwumpKQknD59GiYmJpWuNzY2FmpqasL+UrU3omh6/PgxEhISEBAQgB49egAAzp49q7R8FxcXuLi4YP78+ejSpQt27dqFzp07o3HjxmUuho6NjRWeVIr0S94Tqzpat24NLS0tpKamCkcUSpP3BGnevDnEYjHOnTsHGxsbAK8f2JcuXZJ58APAhQsXYG1tDQB4+vQpEhMT0apVKwAQXjxLS01NRVpaGiwtLYUMNTU14WJlVdm6dSuGDx+OBQsWyExfunQptm7dKrcAGT9+PL7//nsMGzYMjRo1Umg9YrEYzZs3R25uLgCgRYsWUFNTQ1RUlLA/gdcfEc7KyhL+c5V3v1enz+W5efMmHj9+jOXLlwtHTi5fvizTplWrVjh8+LDMtAsXLlSYe+7cOYwdOxbvv/8+gNdv6FX9D7Bt27bYsmULnjx5IvdoU/v27ZGQkFDuYwp4/ebt4+MDHx8ffPLJJ8LRvvbt21epLyW1atUK9+7dw71794R9duPGDTx79kzmDU3ZnJyc4OTkhKtXr2LkyJFl5puZmcHS0hK3b9/GqFGj5GbIe25LJBJYWlri3LlzMq8J586dg6urq8zyFy5cwDvvvAMAKCwsRFRUlFCAlHwcV0RawEn/GVClWbNmwdfXFx07doSrqyvWrVuH3NxcjBs3TmiTkZGBjIwM3Lp1CwAQFxcnfDDB2NgY1tbWWLlyJWbPng1tbW189NFH0NTUxKFDh/Dll19i9uzZQpH66aef4ocffsDw4cMxf/58GBoa4sKFC3B1dYWjoyNsbW1x7NgxJCQkwMTEBIaGhnKLq759+6J169b46KOPsHLlSmRkZOCrr77CJ598Ivxzu2vXLvj6+sLf3x9ubm7IyMgA8PoxL/2n68cff0TXrl3h6emJJUuWwM7ODtevX8fcuXPx1ltvCR9EsLW1ha+vL8aPH4/169fD2dkZKSkpyMzMxNChQ2FjYwORSIQ//vgD7733HnR0dKCvr1+m36dPn0b//v0xffp0fPjhh0KfxGKx8ByePn063N3dsXr1anh7eyMkJASXL18WPgRSUFCAwYMHIzo6Gn/88QeKioqEHGNjY4jFYkRGRuLixYvw8PCAgYEBIiMjMXPmTIwePVrh1+Qaq5WTgHWsqKiITExMaPTo0ZSUlERhYWHUqVMnmYvl5J3zl3c+t+Q1HLdv36YvvviCzp8/T3fv3qVjx46RiYkJ/fTTT0REdPToURKJRBQUFESJiYm0cOFCkkgkwrUIivRLnsr6JVX6I/0LFiwgExMTCgwMpFu3blFUVBStX79euFj0/v37JBKJKDAwkDIzM4VrW6ZPn06WlpZ05MgRmQvBnzx5ItMfJycnOnnyJMXFxdGAAQPI2tq6wutopBfb9u7dm2JjY+nMmTPk4OBAw4cPL3cZeap6TVNmZiZpamrSkSNHyswLDQ0lLS0t4Xqa0tcZPXr0SOZjvCWvafr9999p1KhR9Pvvv1NCQgLdvHmTVq1aRerq6rRjxw5hmcmTJ5OtrS0dOnSIbt++TREREdS5c2fq3LlzuReQV6XPpcm7niIzM5PEYjHNnTuXkpOT6dChQ+Tg4CDzHEhJSSGxWExz5syhmzdv0s6dO8nc3LzCa5ref/99ateuHcXExFBsbCz5+PiQgYGBzEXB8q7dcnZ2Fq7NevXqFTk4OFCPHj3o7NmzlJycTPv27ROuUTl69ChpaGjQokWL6Nq1a3Tjxg0KDg6mBQsWCH3asmULxcXFUXJyMn311Veko6NT7oXL5V3TVHo4jOLiYmrXrh316NGDoqKi6OLFi3IvBC+9nLz9X/pC6dJK5+Tk5Mg830tf0xQQEEA6Ojrk7+9PCQkJdPXqVdq2bRutXr2aiF5fh6Sjo0NLliyhjIwM4UMea9euJYlEQiEhIXTz5k2aN2+e3AvBra2t6cCBAxQfH0+TJ08mfX19+ueff8rtf8khB9LT0yk2NpY+/PBD0tbWFi74V7UffviBrK2tSSwWk6ura5kL7+UNBQBA5hpFIqJDhw5Rjx49SE9Pj7S1talDhw60bdu2Muu7cuUK9e3bl3R1dcnAwIB69OghXGOamZlJffr0IX19/QqHHCAiunv3LvXr1490dHTI1NSUZs+eTQUFBcJ8d3d3uf0uPRzA3bt3hesZNTU1ycrKij777LMyz4MXL17QzJkzhSEu7O3tZbbvm2++IXNzcxKJROUOOeDr6yu3T6Vfl/fs2UMODg4kFovJycmJ/vzzT2GevCEOpD/S/RUVFUVubm5kaGhI2tra1KpVK/ruu+9q7XomojfoQvATJ05Qq1atSEtLi9q2bUvh4eE1LpoyMjJo0KBBwoPNxsaGFi5cKHPB58KFC8nMzIwMDQ1p5syZ9Omnn8o8kCrrlzzVLZqKi4tp3bp15OjoSJqamtS4cWPy9PSkiIgIoY28J8iLFy/os88+I1NTU9LS0qJu3boJF76W7M/vv/9OTk5OwovUlStXyt2Gkv376aefyNLSkrS1tWnw4MFCMaaoqhZN33//PRkZGcm9+PHVq1dkZGRE/v7+RFT5xdkli6bk5GSaNGkSOTg4kI6ODhkZGVGnTp3KvAi/ePGC/Pz8qGXLlqSjo0N2dnY0efLkCt+EqtLn0sr75M6uXbvI1taWtLS0qEuXLnT48OEyz4Hff/+d7O3tSUtLi3r06CF88qu8ounOnTvk4eFBOjo6ZGVlRT/++GOZAqGyoono9Qv+hx9+SBKJhHR1daljx4508eJFYf7Ro0epa9eupKOjQxKJhFxdXYVPyB08eJDc3NxIIpGQnp4ede7cWeZDE6UpWjQRvS4kBwwYQHp6emRgYEBDhgyRudBfVUVTafI+ULJz505q164dicViatSoEb3zzjsyFwMHBASQlZUVqampyfzjtmjRInrrrbdIU1OTnJ2dZQpz6evirl27yNXVlcRiMbVu3ZpOnTpVbt+k21fyTa9Ro0bk7u5e6XKM1XciolIX3TBWReHh4fDw8MDTp0/r5Cs1AgMDERgYiPDw8FpfN2MN2d27d2FnZ4eYmBilfOURY/91b8yn5xhjjDHGaoKLJsYYY4wxBfDpOfafJx3rRPq1L4wxxpgqcNHEGGOMMaYAPj3HGGOMMaaABj+4ZXFxMdLS0mBgYCCM8M0YY4yxhoWI8Pz5c1haWsp8bZEyNfiiKS0tTea7ohhjjDHWcN27dw9NmzZVSXadFk1nzpzBqlWrEBUVhfT0dBw8eFD4riAAGDt2LIKCgmSW8fT0xNGjRxVeh/SLM+/duyfznWeBgYG4cuUKxowZAxcXF2F6bm4uvvvuOwDAl19+KfP9UzExMdixYwecnZ3LXHTMeZzHeZzHeZzHeXWX9+GHH8Lb21vmC7OVrg4H1qTQ0FBasGABHThwQO4o2L6+vuTl5SUMxZ+enl7l0aKzsrIIgMxoyZs3b6bLly+X+TsnJ4cWLlxIOTk5Mn8TEV2+fFkYcbjk35zHeZzHeZzHeZxX93n+/v4EgLKyskhV6s2n50QikdwjTc+ePcNvv/1W7dzs7GwYGhoiPDwciYmJAF5/4WeHDh2ENgEBAXB0dERYWBg+//xzobrNzc3FypUr0atXLyQkJGDSpEnCMlFRUYiOjuY8zuM8zuM8zuO8epAnfb/PysqSObOkVCorx6oI5RxpMjQ0pMaNG5ODgwNNmTKl3C/dlHr58iVlZWUJP/fu3RMqzylTptCUKVPKLJOTk0OWlpYy38EmFRERQZaWlkLFWxLncR7ncR7ncR7n1Y886ZklVR5pqtdDDnh5eWHHjh0ICwvDihUrEBERgX79+qGoqKjcZZYtWwZDQ0PhR3oReGBgICZOnIiJEyciICBAaC+tZhMTE5GQkICoqChhXlRUFBISEpCYmIiVK1ciNzdXmBcQEMB5nMd5nMd5nMd59ShP5VRWjlUR5BxpKi05OZkAVPiN5eUdaQoPDxfaSM+Jlj5vSvTv+dHS501Lti15DpXzOI/zOI/zOI/z6j5v3rx5Kj/S9J8qmoiITE1NadOmTQrnlne4rq4PI3Ie53Ee53Ee53Ge8vLS0tLe7NNzpd2/fx+PHz+GhYVFlZctedguNzcXYWFhCA4Oxq5du2TaRUVFoX379mjfvr3MoUIA2LVrF4KDgxEWFsZ5nMd5nMd5nMd59Shv7969UDmVlWMKeP78OcXExFBMTAwBoDVr1lBMTAylpKTQ8+fPac6cORQZGUl37tyhkydPUvv27alFixb08uVLhdchPdI0b948ysmpPx+N5DzO4zzO4zzO4zzl5YWHhzfs03OnT58mAGV+fH19KS8vj/r27UuNGzcmTU1NsrGxoUmTJlFGRkaV1iEtmtLS0mj27Nk0e/bsMocEL1++TFOmTJG5w6Q2b95MU6ZMkTmHSvT6juM8zuM8zuM8zuO8+pHX4D89p6amhv79+wun2w4ePAgiQmBgIHR0dHDs2DFkZmYiPz8fXl5eCAgIQHBwcF12mTHGGGNvKpWVYwqobERwqQMHDpCzszNZWlrS2rVrq7QOPj3HeZzHeZzHeZzX8PNq4/RcvR4RHAAePHgANzc3HDt2DN7e3pgxYwZmzJihcK50hNC0tDThiFZ9GLmU8ziP8ziP8ziP85SXFxsbi+nTp7+5I4IXFRWRh4cHrVu3joiIbGxsKj3SVNGI4CX9Vz5CyXmcx3mcx3mcx3k85EClVqxYAQ0NDUybNk3hZcobETwmJkZoU19GLuU8zuM8zuM8zuM85eT5+/tD5VRWjlURSh1punz5MpmZmdGDBw+EaTU50uTv70+XL9efkUs5j/M4j/M4j/M4T3l5tXGkqd4WTWvXriWRSETq6urCDwBSU1MjGxsbhXNLfgSxPh1G5DzO4zzO4zzO4zz+wl6l+Oijj3D16lXExsYKP5aWlpg7dy6OHTtW5byYmJh6NXIp53Ee53Ee53Ee5yk3T+VUVo4poKIRweVR5PRcadLK09/fX5hWHz4ayXmcx3mcx3mcx3nKy/P392/YQw74+/vLHT7A19cXgYGBWLRoEUJCQnDv3j2IxWK8fPkSU6ZMwdq1axVeh3TIgaxz5yDR11di799gjx7VdQ8aHnv7uu5Bg/NQy7quu9CgmD28WtddaHDy7NvWdRcalOzsbFhYGKp0yIE6PT3n4OCABQsW4MCBAwBkRwSXzv/xxx8RFxeHs2fPYtSoUdi2bRv++eefOuw1Y4wxxt5EGnW58n79+qFfv37lzh85cqTM7TVr1mDr1q24evUqevXqperuMcYYY4wJ6u2F4KXl5+dj8+bNMDQ0hLOzc113hzHGGGNvmDo90qSIP/74A8OHD0deXh4sLCxw4sQJmJqaltv+1atXePXqlXA7Ozu7NrrJGGOMsQau3h9p8vDwQGxsLM6fPw8vLy8MHToUmZmZ5bYvb0RwxhhjjLGaqPdFk56eHuzt7dG5c2ds3boVGhoa2Lp1a7nt58+fj6ysLOHn3r17tdhbxhhjjDVU9f70XGnFxcUyp99K09LSgpaWVi32iDHGGGNvgjotmnJycnDr1i3h9p07dxAbGwtjY2OYmJhg6dKlGDBgACwsLPDo0SNs2LABDx48wJAhQ+qw14wxxhh7E9Vp0XT58mV4eHgIt2fNmgXg9eCWmzZtws2bNxEUFIRHjx7BxMQEnTp1wl9//QUnJ6e66jJjjDHG3lB1WjSpqamhf//+iIqKQnp6Og4ePIhBgwYBAAoKCtCiRQskJSXh2bNnAABDQ0O89dZb1VuZtTWgohFC3zhGRnXdgwYnz5RHr1Y2M438uu5Cg5JnwKNXK5vus7S67kKDUvj8ucrXUacXgufm5sLZ2RkbNmwoMy8vLw/R0dH4+uuvER0djQMHDiAhIQEDBgyog54yxhhj7E1Xb0cENzQ0xIkTJ2Sm/fjjj3B1dUVqaiqsrfk/c8YYY4zVnv/Up+eysrIgEolgVMHpIR7ckjHGGGOqUO/HaZJ6+fIl5s2bhxEjRlT47cU8uCVjjDHGVOE/UTQVFBRg6NChICJs3LixwrY8uCVjjDHGVKHen56TFkwpKSk4depUhUeZAB7ckjHGGGOqUa+LJmnBlJSUhNOnT8PExKSuu8QYY4yxN1S9HRHcwsICgwcPRnR0NP744w8UFRUhIyMDAGBsbAyxWFxX3WaMMcbYG0hERFRXKw8PD5cZEVzK19cXixYtgp2dndzlTp8+jZ49eyq0juzsbBgaGuKff7IqPbXHFCMuzKvrLjQ42YW6dd2FBkdS+KSuu9CgPIFxXXehwTEGP0aVKTs7G4Z2dsjKUt37fZ1eCC4dEdzCwgIAcPDgQRARAgMDYWtri/3796NPnz4wNn79ZI2JiQERKVwwMcYYY4wpS70dEVw6v3v37lixYkUt94wxxhhjTFa9HREcAD766CMAwN27d2upR4wxxhhj8tXrT89VB48IzhhjjDFVqNbpuRcvXiAv79+LgVNSUrBu3TocP35caR2rLh4RnDHGGGOqUK2iaeDAgdixYwcA4NmzZ3Bzc8Pq1asxcODASkfsVjUeEZwxxhhjqlCtoik6Oho9evQAAOzbtw9mZmZISUnBjh07sH79eqV2sKq0tLQgkUhkfhhjjDHGaqpaRVNeXh4MDAwAAMePH8cHH3wANTU1dO7cGSkpKUrtIGOMMcZYfVCtC8Ht7e3x22+/4f3338exY8cwc+ZMAEBmZmaVjuxUNCK4tbU1njx5gtTUVKSlpQEAEhISAADm5uYwNzevTtcZY4wxxqqlWiOC79u3DyNHjkRRURF69eolXAC+bNkynDlzBkeOHFEop6IRwQMDAxEYGIhx48aVme/n54dFixYptA7piOBPn/KI4Mqi9oxHsVU6I6O67kHD8+xZXfegQcnT5hHBlU0X/O0KypSdnQ1DCwuVjgherSNNgwcPRvfu3ZGeng5nZ2dheq9evfD+++8rnCMdETwqKgrp6ek4ePAgBg0aJMz39fXF7du3ERAQgGfPnqFbt27YuHEjWrRoUZ1uM8YYY4xVW7VHBDc3N4eLiwvU1P6NcHV1RcuWLRXOqGxE8JUrV2L9+vXYtGkTLl68CD09PXh6euLly5fV7TZjjDHGWLUofKTpgw8+UDj0wIEDCrWraERwIsK6devw1VdfYeDAgQCAHTt2wMzMDL/99huGDx+ucH8YY4wxxmpK4aLJ0NBQlf0o486dO8jIyEDv3r1l+uDm5obIyMhyiyYeEZwxxhhjqqBw0bR9+3ZV9qOMjIwMAICZmZnMdDMzM2GePMuWLcPixYtV2jfGGGOMvXmqfU1TYWEhTp48iZ9//hnPnz8HAKSlpSEnJ0dpnasOHhGcMcYYY6pQrU/PpaSkwMvLC6mpqXj16hX69OkDAwMDrFixAq9evcKmTZtq3DHpOEwPHz6EhYWFMP3hw4do165ductpaWlBS0urxutnjDHGGCupWkeapk+fjo4dO+Lp06fQ0dERpr///vsICwtTSsfs7Oxgbm4uk5ednY2LFy+iS5cuSlkHY4wxxpiiqnWk6a+//sL58+chFotlptva2uLBgwcK51Q2IviMGTOwZMkStGjRAnZ2dvj6669haWkpM5YTY4wxxlhtqFbRVFxcjKKiojLT79+/L3wnnSIuX74sMyL4rFmzAPw7Ivjnn3+O3NxcTJ48Gc+ePUP37t1x9OhRaGtrV7nPL18CpWo8Vk26dd0BxhRRWFjXPWhQqvGyyypTWK23YFYeDdXvz2qdnuvbty/WrVsn3BaJRMjJyYGfnx/ee+89hXN69uwJIirzExgYKOTOnTsXw4cPh5mZGc6dO4exY8fi0qVL1ek2Y4wxxli1VatoWr16Nc6dO4fWrVvj5cuXGDlypHBqbsWKFUrt4MSJE3HixAn88ssviIuLQ9++fdG7d+8qnQZkjDHGGKupan1hL/B6yIGQkBBcvXoVOTk5aN++PUaNGiVzYXhNvXjxAgYGBjh06BC8vb2F6R06dEC/fv2wZMmSSjOkX9ibns5f2Kssui/5C3uVjr+wV/keParrHjQoxaZN6roLDY5aYX5dd6FByc7OhmHjxvXvC3sBQENDA6NHj1ZmX8ooLCxEUVFRmWuYdHR0cPbsWbnL8IjgjDHGGFOFahdNSUlJOH36NDIzM1FcXCwzb+HChTXuGAAYGBigS5cu+Pbbb9GqVSuYmZkhODgYkZGRsLe3l7sMjwjOGGOMMVWo1um5gIAA/O9//4OpqSnMzc0hEon+DRSJEB0drbQOJicnY/z48Thz5gzU1dXRvn17ODg4ICoqCvHx8WXayzvSZGVlxafnlIhPz6kAn55TPj49p1R8ek75+PScctXb03NLlizB0qVLMW/ePGX3p4zmzZsjIiICubm5yM7OhoWFBYYNG4ZmzZrJbc8jgjPGGGNMFar16bmnT59iyJAhyu5LhfT09GBhYYGnT5/i2LFjGDhwYK2unzHGGGNvtmoVTUOGDMHx48eV3Re5jh07hqNHj+LOnTs4ceIEPDw80LJlS4wbN65W1s8YY4wxBlTz9Jy9vT2+/vprXLhwAW3atIGmpqbM/GnTpimlcwCQlZWF+fPn4/79+zA2NsaHH36IpUuXlllnZXQ18qGrweePlYKHBmbsjcPX36gAj1qvXLWwP6tVNG3evBn6+vqIiIhARESEzDyRSKS0oqmoqAhxcXEoLi6GmpoadHV1YWZmxhd0M8YYY6zWVatounPnjrL7IdeKFSuwceNGBAUFwcnJCZcvX8a4ceNgaGio1KNZjDHGGGOVqdffFnj+/HkMHDhQGA3c1tYWwcHB+Pvvv+u4Z4wxxhh701SraCoqKkJgYCDCwsLkDm556tQppXSua9eu2Lx5MxITE+Hg4IArV67g7NmzWLNmTbnL8IjgjDHGGFOFahVN06dPR2BgILy9vfH222/LDG6pTF988QWys7PRsmVLqKuro6ioCEuXLsWoUaPKXYZHBGeMMcaYKlRrRHBTU1Ps2LED7733nir6JAgJCcHcuXOxatUqODk5ITY2FjNmzMCaNWvg6+srd5nyRgTP+ucfvoBcWfgTH8rHn0hUPh4RXLl41Hrl49dSpcrOzoahhUX9GxFcLBaX+91vyjR37lx88cUXGD58OACgTZs2SElJwbJly8otmnhEcMYYY4ypQrUGt5w9ezb8/f1RjYNUVZKXlwc1Ndkuqqurl7mGijHGGGNM1ap1pOns2bM4ffo0jhw5AicnpzIDTR44cEApnfPx8cHSpUthbW0NJycnxMTEYM2aNRg/frxS8hljjDHGFFWtosnIyAjvv/++svtSxg8//ICvv/4aU6dORWZmJiwtLfHxxx9j4cKFVQ/T0Hj9w1h99PJlXfeg4eHrxBhjSlatC8Frk62tLVJSUspMnzp1KjZs2FDp8tnZ2TA0NETW06d8Ibiy8MWLysf7VPl4nyoXF6HKx49Rpaq3F4LXpkuXLqGoqEi4fe3aNfTp0wdDhgypw14xxhhj7E1T7aJp37592LNnD1JTU5GfL/tFjtHR0TXumFTjxo1lbi9fvhzNmzeHu7u70tbBGGOMMVaZan16bv369Rg3bhzMzMwQExMDV1dXmJiY4Pbt2+jXr5+y+yjIz8/Hr7/+ivHjx5c7oOarV6+QnZ0t88MYY4wxVlPVKpp++uknbN68GT/88APEYjE+//xznDhxAtOmTUNWVpay+yj47bff8OzZM4wdO7bcNsuWLYOhoaHwY2VlpbL+MMYYY+zNUa0LwXV1dREfHw8bGxs0adIEJ06cgLOzM5KSktC5c2c8fvxYFX2Fp6cnxGIxfv/993LblDsiOF8Irjx88aLy8T5VPt6nysUXgisfP0aVqjYuBK/WkSZzc3M8efIEAGBtbY0LFy4AAO7cuaOyAS9TUlJw8uRJTJw4scJ2WlpakEgkMj+MMcYYYzVVraLp3XffxeHDhwEA48aNw8yZM9GnTx8MGzZMZeM3bd++HU2aNIG3t7dK8hljjDHGKlKtT89t3rxZ+CqTTz75BCYmJjh//jwGDBiAjz/+WKkdBIDi4mJs374dvr6+0OABKhljjDFWB6p1pElNTU2meBk+fDjWr1+Pzz77DGKxWGmdkzp58iRSU1Nr9PUp3y1fjtwXL5D74gX8Fi9G7osXgJoaomJiELB1a5m/oaaGgK1bERUTU+bvkhlvZN7SpcgtKADEYkTFxSEgKKjM3xCLERAUhKi4uDJ/5xYUCBkl/36j83R1ERUfj4CdOwFdXUBXFwE7dyIqPr7M37lE8FuxArlEMn+Xznjj83bvRlRSEiCRyPydq64Ov9WrkauuLvM3JBJEJSUhYPfuMn+Xzngj8xrS862+5DWk51s9yItJSFBi5VEOqqanT5/SsWPH6JdffqGgoCCZH2W6f/8+jRo1ioyNjUlbW5vefvttunTpksLLZ2VlEQBKS0uj2bNn0+zZsyknJ0emzeXLl2nKlCm0efPmMstv3ryZpkyZQpcvX5aZnpOTw3mcx3mcx3mcx3n1JE/6fp+VlVUmS1mqda7r999/x6hRo5CTkwOJRCIzZpJIJMKYMWOUUtA9ffoU3bp1g4eHB44cOYLGjRsjKSkJjRo1Uko+Y4wxxpjCqlNptWjRgqZPn065ubnKLuJkzJs3j7p3716jDGnlOW/ePMrJyaGcnBxauHChUJ1evnxZqHBL/k30usqVVrgl/y6ZwXmcx3mcx3mcx3l1nxceHq7yI03VGqdJT08PcXFxaNasmfKruBJat24NT09P3L9/HxEREXjrrbcwdepUTJo0qdxlyhunKS0tDRYWFgCA3NxcrFy5Er169UJCQoJMXlRUlPA1MO3bt0eHDh2EeQEBAXB0dERYWBg+//xz6OnpcR7ncR7ncR7ncV49yIuNjcX06dNVOk5TtY40vf/++7R7927llm9yaGlpkZaWFs2fP5+io6Pp559/Jm1tbQoMDCx3GT8/PwJQ5qd05RkREUGWlpZlzq8SEU2ZMoWmTJlSZnpOTg5ZWlpSREREmXmcx3mcx3mcx3mcV3d5aWlpKj/SpPCn5w4fPiz8eHt7Y+7cuVi0aBH2798vM086fpMyFBcXo3379vjuu+/g4uKCyZMnY9KkSdi0aVO5y8yfPx9ZWVnCz7179wAAMTExQpuoqCgkJCQgMTERK1euRG5urjAvICAAEydOxMSJExEQECBMl1aziYmJSEhIQFRUFOdxHudxHudxHufVkzx/f3+onKLVlUgkUuhHTU1NaRWdtbU1TZgwQWbaTz/9RJaWlgpnSK9p8vf3p8uXL5c5b1rynGjJ86ZE/55jLX3elOjfc6ycx3mcx3mcx3mcV/d5tXGkqdpDDtSGESNGlLkQfMaMGdSlSxeFM0p+BLE+HUbkPM7jPM7jPM7jPOXl1caQA1Ua3PLUqVNo3bo1srOzy8zLysqCk5MT/vrrL6UcAQOAmTNn4sKFC/juu+9w69Yt7Nq1C5s3b8Ynn3xS5ayYmBi0b98e7du3lzm0BwC7du1CcHAwwsLCZA4V5ubmIiwsDMHBwdi1a5fMMlFRUZzHeZzHeZzHeZxXj/JUrioVlo+PD61Zs6bc+f7+/jRo0KAaV3IljRgxosxF3Y6OjgovX/L0nFR9+Ggk53Ee53Ee53Ee5ykvz9/fv36dnrO2tqYbN26UOz8+Pp6srKxq3KmS/Pz8yMnJidLT04Wff/75R+Hlyztct3lzwxoJlfM4j/M4j/M4703Oq41xmqo0IvjDhw+hqalZ7nwNDQ38888/1T7qVVGuubm50nMZY4wxxhRWlQqrWbNmdPDgwXLn79+/n+zs7GpayMnw8/MjXV1dsrCwIDs7Oxo5ciSlpKSU2/7ly5eUlZUl/Ny7d49Pz3Ee53Ee53Ee5zXwvNo4PVelEcE/++wzhIeH49KlS9DW1paZ9+LFC7i6usLDwwPr169XWlF35MgR5OTkwNHREenp6Vi8eDEePHiAa9euwcDAoEz7RYsWYfHixWWmh4eHIzExEUD9GLmU8ziP8ziP8ziP85SXl52dDUNDw/ozInhGRgZZWlqSlZUVrVixgn777Tf67bffaPny5WRlZUWWlpaUkZGhmvLu/z19+pQkEglt2bJF7vzyjjTxkAOcx3mcx3mcx3kNN682hhyo8jhNd+/epX79+pGamprMgJb9+vWj27dvq6KPZXTs2JG++OILhdry4Jacx3mcx3mcx3kNP69eD2755MkT+vvvv+nixYv05MkTZfapQs+fP6dGjRrJXKNUEWnRFB4eLkyrD3cu53Ee53Ee53Ee5ykvb968efW3aKots2fPpvDwcLpz5w6dO3eOevfuTaamppSZmanQ8uUdrqvrw4icx3mcx3mcx3mcp7y8evWFvXXl/v37GDFiBBwdHTF06FCYmJjgwoULaNy4cZVy6uPIpZzHeZzHeZzHeZynnLy9e/dC5VRWjqnAsmXLCABNnz5d4WWkR5rmzZtHOTn156ORnMd5nMd5nMd5nKe8vNoY3PI/UzT9/fffZGtrS23btq1W0ZSWllavRi7lPM7jPM7jPM7jPOXl1bsv7K0rOTk5GDVqFAICAtCoUaO67g5jjDHG3kQqK8eUaMyYMTRjxgwiInJ3d6/wSFN54zTx6TnO4zzO4zzO47yGm1cbp+eqNCJ4XQgJCcHSpUuFUch79uyJdu3aYd26dXLblzcieFpaGiwsLADUj5FLOY/zOI/zOI/zOE95ebGxsZg+fXr9GRG8tqWmplKTJk3oypUrwrTqHmniIQc4j/M4j/M4j/Mabt4bP+RAVFQUMjMz0b59e2hoaEBDQwMRERFYv349NDQ0UFRUVGYZLS0tSCQSmR8AiImJkclNSEhAYmIiVq5cKfPxxYCAAEycOBETJ05EQECAMF1azSYmJiIhIUHm45Ccx3mcx3mcx3mcV7d5/v7+UDmVlWNKkJ2dTXFxcTI/HTt2pNGjR1NcXJxCGfw1KpzHeZzHeZzHeQ0/r15/jUpdqez0XGklP4JYnw4jch7ncR7ncR7ncd5/6wt76/XpOWWKiYmpVyOXch7ncR7ncR7ncZ5y81ROZeWYkvz000/Upk0bMjAwIAMDA+rcuTOFhoYqvHzJ03NS9eGjkZzHeZzHeZzHeZynvDx/f38+PXf48GH6888/KTExkRISEujLL78kTU1NunbtmkLLl3e4bvPmhjUSKudxHudxHudx3pucVxvjNGnU7nGtqvPx8ZG5vXTpUmzcuBEXLlyAk5NTHfWKMcYYY28clZVjKlBYWEjBwcEkFovp+vXrctuUN04Tn57jPM7jPM7jPM5ruHm1cXqu3o8IDgBxcXHo0qULXr58CX19fezatQvvvfee3LbljQgeHh6OxMREAPVj5FLO4zzO4zzO4zzOU15ednY2DA0N39wRwaVevXpFSUlJdPnyZfriiy/I1NS0ykeaeMgBzuM8zuM8zuO8hpvHQw78P7FYDHt7e3To0AHLli2Ds7NzuSN/ljcieGBgYL0auZTzOI/zOI/zOI/zlJunciorx1TIw8ODfH19FWorrTzDw8OFadJzoqXPmxL9e3609HnTkm1LnkPlPM7jPM7jPM7jvLrPmzdvHg858MUXX1BERATduXOHrl69Sl988QWJRCI6fvy4QsuXd7iurg8jch7ncR7ncR7ncZ7y8t74L+wFgMzMTIwZMwaOjo7o1asXLl26hGPHjqFPnz5VyqmPI5dyHudxHudxHudxnnLy9u7dC5VTWTmmJN999x117NiR9PX1qXHjxjRw4EC6efOmwstLjzTNmzePcnLqz0cjOY/zOI/zOI/zOE95ebUxuGW9L5o8PT1p+/btdO3aNYqNjaX33nuPrK2t5R7Wk0daNKWlpdWrkUs5j/M4j/M4j/M4T3l5tfHpuXo/IvjRo0dlbgcGBqJJkyaIiorCO++8U0e9YowxxtgbR2XlmIokJSURAIqLi5M7v7xxmvj0HOdxHudxHudxXsPNq43Tc/+JEcGliouLMWDAADx79gxnz56V26a8EcHT0tJgYWEBoH6MXMp5nMd5nMd5nMd5ysuLjY3F9OnTeURwqSlTppCNjQ3du3ev3DYVjQhe0n/lI5Scx3mcx3mcx3mcx0MOVMmnn36KP/74A6dPn0bTpk3LbVfeiOAxMTFCm/oycinncR7ncR7ncR7nKSevvG8KUSqVlWNKUlxcTJ988glZWlpSYmJilZeXXk3v7+9Ply/Xn5FLOY/zOI/zOI/zOE95ebVxpKneF03/+9//yNDQkMLDwyk9PV34ycvLU2j5kh9BrE+HETmP8ziP8ziP8ziPv7BXqTZu3IisrCz07NkTFhYWws/u3burlBMTE1OvRi7lPM7jPM7jPM7jPOXmqZzKyjEliYiIoP79+5OFhQUBoIMHD1Zp+ZKn56Tqw0cjOY/zOI/zOI/zOE95ef7+/nx6LjQ0lBYsWEAHDhyoUdFUeidu3tywRkLlPM7jPM7jPM57k/NqY5ymej8ieL9+/dCvX7+67gZjjDHG3nQqK8dUAAocaSpvnCY+Pcd5nMd5nMd5nNdw82rj9Nx/akRwkUiEgwcPYtCgQeW2KW9E8PDwcCQmJgKoHyOXch7ncR7ncR7ncZ7y8rKzs2FoaMgjgkuhBkeaeMgBzuM8zuM8zuO8hpvHQw5UQ3kjggcGBtarkUs5j/M4j/M4j/M4T7l5KqeyckwFUINPz4WHhwvTpOdES583Jfr3/Gjp86Yl25Y8h8p5nMd5nMd5nMd5dZ83b948HnLg+fPnFBMTQzExMQSA1qxZQzExMZSSkqLQ8s+ePSMAdO/ePZnTdqGhoWRubk5paWky07Oysmj8+PE0fvz4MtPT0tLI3NycQkNDy8zjPM7jPM7jPM7jvLrLS0hIIAD07NkzldUk9f5C8PDwcHh4eJSZ7uvri8DAwEqXv3//PqysrFTQM8YYY4zVN/fu3UPTpk1Vkl3vi6aaKi4uRlpaGgwMDCASieq6O+XKzs6GlZUV7t27p7qr/t8wvE+Vj/epcvH+VD7ep8r1X9qfRITnz5/D0tISamqquWS73g9uWVNqamoqqzhVoeTF60w5eJ8qH+9T5eL9qXy8T5Xrv7I/DQ0NVZrf4D49xxhjjDGmClw0McYYY4wpgIumekJLSwt+fn7Q0tKq6640GLxPlY/3qXLx/lQ+3qfKxftTVoO/EJwxxhhjTBn4SBNjjDHGmAK4aGKMMcYYUwAXTYwxxhhjCuCiiTHGGGNMAVw0qcCGDRtga2sLbW1tuLm54e+//xbmbd68GT179oREIoFIJMKzZ8/KLL906VJ07doVurq6MDIyKjP/ypUrGDFiBKysrKCjo4NWrVrB399fhVtUt1S9PwHg0qVL6NWrF4yMjNCoUSN4enriypUrKtqiulfePn3y5Ak+++wzODo6QkdHB9bW1pg2bRqysrJklk9NTYW3tzd0dXXRpEkTzJ07F4WFhTJtwsPD0b59e2hpacHe3l6hrz36r6qN/fnq1SssWLAANjY20NLSgq2tLbZt21Zr21jbarpPp02bhg4dOkBLSwvt2rUrkx8eHo6BAwfCwsICenp6aNeuHXbu3Fkbm1ZnVL1PAeDYsWPo3LkzDAwM0LhxY3z44Ye4e/euires9nDRpGS7d+/GrFmz4Ofnh+joaDg7O8PT0xOZmZkAgLy8PHh5eeHLL78sNyM/Px9DhgzB//73P7nzo6Ki0KRJE/z666+4fv06FixYgPnz5+PHH39UyTbVpdrYnzk5OfDy8oK1tTUuXryIs2fPwsDAAJ6enigoKFDJdtWlivZpWloa0tLS8P333+PatWsIDAzE0aNHMWHCBGH5oqIieHt7Iz8/H+fPn0dQUBACAwOxcOFCoc2dO3fg7e0NDw8PxMbGYsaMGZg4cSKOHTtWF5usUrWxPwFg6NChCAsLw9atW5GQkIDg4GA4OjrW9ubWipruU6nx48dj2LBhctdx/vx5tG3bFvv378fVq1cxbtw4jBkzBn/88YeqN69O1MY+vXPnDgYOHIh3330XsbGxOHbsGB49eoQPPvhA1ZtXe1T2VcBvKFdXV/rkk0+E20VFRWRpaUnLli2TaXf69GkCQE+fPi03a/v27WRoaKjQeqdOnUoeHh7V6XK9Vhv789KlSwSAUlNThWlXr14lAJSUlFTjbahvFN2nUnv27CGxWEwFBQVERBQaGkpqamqUkZEhtNm4cSNJJBJ69eoVERF9/vnn5OTkJJMzbNgw8vT0VPbm1Lna2J9HjhwhQ0NDevz4sQq3pP6o6T4tyc/Pj5ydnRVa73vvvUfjxo2rVp/ru9rYp3v37iUNDQ0qKioSph0+fJhEIhHl5+fXfCPqAT7SpET5+fmIiopC7969hWlqamro3bs3IiMjVbrurKwsGBsbq3Qdta229qejoyNMTEywdetW5Ofn48WLF9i6dStatWoFW1tbpa2nPqjOPs3KyoJEIoGGxuuvqoyMjESbNm1gZmYmtPH09ER2djauX78utCm5DmkbVT8Paltt7c/Dhw+jY8eOWLlyJd566y04ODhgzpw5ePHihQq3rm4oY59WV0N8HQVqb5926NABampq2L59O4qKipCVlYVffvkFvXv3hqamZo23oz7gokmJHj16hKKiIpkXPwAwMzNDRkaGytZ7/vx57N69G5MnT1bZOupCbe1PAwMDhIeH49dff4WOjg709fVx9OhRHDlypMYvwvVNVffpo0eP8O2338o8tjIyMuQuL51XUZvs7OwG9UZfW/vz9u3bOHv2LK5du4aDBw9i3bp12LdvH6ZOnarsTapzytin1bFnzx5cunQJ48aNq1FOfVRb+9TOzg7Hjx/Hl19+CS0tLRgZGeH+/fvYs2dPjfpfn3DR9B937do1DBw4EH5+fujbt29dd+c/6cWLF5gwYQK6deuGCxcu4Ny5c3j77bfh7e3doN7gqyo7Oxve3t5o3bo1Fi1aVNfd+c+ryf4sLi6GSCTCzp074erqivfeew9r1qxBUFAQP0aV8Bg9ffo0xo0bh4CAADg5OSmvg/9BNdmnGRkZmDRpEnx9fXHp0iVERERALBZj8ODBoAby5SMN69/oOmZqagp1dXU8fPhQZvrDhw9hbm6u9PXduHEDvXr1wuTJk/HVV18pPb+u1db+3LVrF+7evYvIyEioqakJ0xo1aoRDhw5h+PDhSltXXVN0nz5//hxeXl4wMDDAwYMHZQ6tm5uby3yCUbq8dJ70t7x1SCQS6OjoKHWb6lJt7U8LCwu89dZbMDQ0FNq0atUKRIT79++jRYsWSt+2uqKMfVoVERER8PHxwdq1azFmzJga9b2+qq19umHDBhgaGmLlypXCtF9//RVWVla4ePEiOnfuXLMNqQf4SJMSicVidOjQAWFhYcK04uJihIWFoUuXLkpd1/Xr1+Hh4QFfX18sXbpUqdn1RW3tz7y8PKipqUEkEgnTpLeLi4uVtp76QJF9mp2djb59+0IsFuPw4cPQ1taWyejSpQvi4uKETzACwIkTJyCRSNC6dWuhTcl1SNso+3lQ12prf3br1g1paWnIyckR2iQmJkJNTQ1NmzZV5SbWOmXsU0WFh4fD29sbK1asaHCXN5RUW/tU+lpakrq6urC+BqGur0RvaEJCQkhLS4sCAwPpxo0bNHnyZDIyMhI+GZOenk4xMTEUEBBAAOjMmTMUExMj86mYlJQUiomJocWLF5O+vj7FxMRQTEwMPX/+nIiI4uLiqHHjxjR69GhKT08XfjIzM+tkm1WpNvZnfHw8aWlp0f/+9z+6ceMGXbt2jUaPHk2GhoaUlpZWJ9utShXt06ysLHJzc6M2bdrQrVu3ZB5fhYWFRERUWFhIb7/9NvXt25diY2Pp6NGj1LhxY5o/f76wjtu3b5Ouri7NnTuX4uPjacOGDaSurk5Hjx6tq81WmdrYn8+fP6emTZvS4MGD6fr16xQREUEtWrSgiRMn1tVmq1RN9ykRUVJSEsXExNDHH39MDg4OwvNe+onEU6dOka6uLs2fP18mo6F+QrE29mlYWBiJRCJavHgxJSYmUlRUFHl6epKNjQ3l5eXV1aYrFRdNKvDDDz+QtbU1icVicnV1pQsXLgjz/Pz8CECZn+3btwttfH195bY5ffp0hRk2Nja1u6G1RNX7k4jo+PHj1K1bNzI0NKRGjRrRu+++S5GRkbW4lbWrvH0qHbpB3s+dO3eE5e/evUv9+vUjHR0dMjU1pdmzZ5f5aPLp06epXbt2JBaLqVmzZjL3SUNTG/szPj6eevfuTTo6OtS0aVOaNWtWg3kjkqem+9Td3b3CNuW9Lri7u9f+xtYSVe9TIqLg4GBycXEhPT09aty4MQ0YMIDi4+NreUtVR0TUQK7OYowxxhhTIb6miTHGGGNMAVw0McYYY4wpgIsmxhhjjDEFcNHEGGOMMaYALpoYY4wxxhTARRNjjDHGmAK4aGKMMcYYUwAXTYwxxhhjCuCiiTHGGGNMAVw0McYYY4wpgIsmxhhjjDEFcNHEGGOMMaYALpoYY4wxxhTARRNjjDHGmAK4aGKMMcYYUwAXTYwxxhhjCuCiiTHGGGNMARp13YHa8PLlS+Tn59d1NxhjjDGmQmKxGNra2irLb/BF08uXL6GjYwTgVV13hTHGGGMqZG5ujjt37qiscGrwRdPrI0yvAPQGIP7/qerl/FYr9bu8dlVtX958Va2vZPuq9q2y2+X9Fil5GyrbZ4r27/V8jf9/pJf3W129ZvNrM+e/2Oe6yFFD8es/Cgsr/l1UVLP5ysipT32pz+tTMIde35I+Aqr9u7KcograVZZR0bKK9KWqy5fOqe7yVd1Hiu47ZdxnrwCszchAfn4+F001pwFA8///ruobdU3bV7dAUMZ6a6tv9bOdSKT2/79R4W81tYp/S9+oK/td2Ru5Mn7Xxjoawm+Fi6b68FtV2eU9UKXzK3vgS9tV9gSS/q4MkWK/y+tPcbFC/aD/z6lp0VTVN355RVN1lq3put+E5cv7rWp8IThjjDHGmAK4aGKMMcYYUwAXTYwxxhhjCuCiiTHGGGNMAVw0McYYY4wpgIsmxhhjjDEFcNHEGGOMMaYALpoYY4wxxhTARRNjjDHGmAK4aGKMMcYYUwAXTYwxxhhjCuCiiTHGGGNMAVw0McYYY4wpgIsmxhhjjDEFcNHEGGOMMaYALpoYY4wxxhTARRNjjDHGmAK4aGKMMcYYUwAXTYwxxhhjCuCiiTHGGGNMAVw0McYYY4wpQKOuO1B7CvFvjVhczm/p/KL//61eyW+1Ur8ra1fd5WvSvqp9q+x2eb9FSt6GyvaZYv0jUvv/36jwd3Fxxb+L/v8hIRJV/LsylfVDkf6U7lN5vwsLX//W0Kj4t7p6zebX1xw16fNauiPK+116h1V1vjJy6lNfVLm+yn5X9kRU8An0/7fKfaVX9HdlOUUVtKsso6JlFelLVZcvnVPd5au6jxTdd8q4z15B9Rp80SQWi2Fubo6MjJN13RVWh0q/hjPGGGt4zM3NIRaLVZYvIpKW6A3Xy5cvkZ+fr/Tc7OxsWFlZ4d69e5BIJErPry/ehO18E7YR4O1saN6E7XwTthHg7VQWsVgMbW1tpedKNfgjTQCgra2t0p0okUga9INc6k3YzjdhGwHezobmTdjON2EbAd7O+o4vBGeMMcYYUwAXTYwxxhhjCuCiqQa0tLTg5+cHLS2tuu6KSr0J2/kmbCPA29nQvAnb+SZsI8Db+V/xRlwIzhhjjDFWU3ykiTHGGGNMAVw0McYYY4wpgIsmxhhjjDEFcNHEGGOMMaYALpoqsHTpUnTt2hW6urowMjJSaBkiwsKFC2FhYQEdHR307t0bSUlJMm2ePHmCUaNGQSKRwMjICBMmTEBOTo4KtkAxVe3P3bt3IRKJ5P7s3btXaCdvfkhISG1sklzV2e89e/Yssw1TpkyRaZOamgpvb2/o6uqiSZMmmDt3Lgrr8PtaqrqdT548wWeffQZHR0fo6OjA2toa06ZNQ1ZWlky7urw/N2zYAFtbW2hra8PNzQ1///13he337t2Lli1bQltbG23atEFoaKjMfEWep3WhKtsZEBCAHj16oFGjRmjUqBF69+5dpv3YsWPL3GdeXl6q3oxKVWU7AwMDy2xD6cGK6+P9WZVtlPc6IxKJ4O3tLbSpj/flmTNn4OPjA0tLS4hEIvz222+VLhMeHo727dtDS0sL9vb2CAwMLNOmqs/3WkWsXAsXLqQ1a9bQrFmzyNDQUKFlli9fToaGhvTbb7/RlStXaMCAAWRnZ0cvXrwQ2nh5eZGzszNduHCB/vrrL7K3t6cRI0aoaCsqV9X+FBYWUnp6uszP4sWLSV9fn54/fy60A0Dbt2+XaVdyP9S26ux3d3d3mjRpksw2ZGVlCfMLCwvp7bffpt69e1NMTAyFhoaSqakpzZ8/X9WbU66qbmdcXBx98MEHdPjwYbp16xaFhYVRixYt6MMPP5RpV1f3Z0hICInFYtq2bRtdv36dJk2aREZGRvTw4UO57c+dO0fq6uq0cuVKunHjBn311VekqalJcXFxQhtFnqe1rarbOXLkSNqwYQPFxMRQfHw8jR07lgwNDen+/ftCG19fX/Ly8pK5z548eVJbmyRXVbdz+/btJJFIZLYhIyNDpk19uz+ruo2PHz+W2b5r166Ruro6bd++XWhTH+/L0NBQWrBgAR04cIAA0MGDBytsf/v2bdLV1aVZs2bRjRs36IcffiB1dXU6evSo0Kaq+662cdGkgO3btytUNBUXF5O5uTmtWrVKmPbs2TPS0tKi4OBgIiK6ceMGAaBLly4JbY4cOUIikYgePHig9L5XRln9adeuHY0fP15mmiJPotpS3e10d3en6dOnlzs/NDSU1NTUZF7EN27cSBKJhF69eqWUvleFsu7PPXv2kFgspoKCAmFaXd2frq6u9Mknnwi3i4qKyNLSkpYtWya3/dChQ8nb21tmmpubG3388cdEpNjztC5UdTtLKywsJAMDAwoKChKm+fr60sCBA5Xd1Rqp6nZW9vpbH+/Pmt6Xa9euJQMDA8rJyRGm1cf7siRFXh8+//xzcnJykpk2bNgw8vT0FG7XdN+pGp+eU6I7d+4gIyMDvXv3FqYZGhrCzc0NkZGRAIDIyEgYGRmhY8eOQpvevXtDTU0NFy9erPU+K6M/UVFRiI2NxYQJE8rM++STT2BqagpXV1ds27YNVEfDgtVkO3fu3AlTU1O8/fbbmD9/PvLy8mRy27RpAzMzM2Gap6cnsrOzcf36deVvSCWU9fjKysqCRCKBhobs11PW9v2Zn5+PqKgomeeUmpoaevfuLTynSouMjJRpD7y+T6TtFXme1rbqbGdpeXl5KCgogLGxscz08PBwNGnSBI6Ojvjf//6Hx48fK7XvVVHd7czJyYGNjQ2srKwwcOBAmedWfbs/lXFfbt26FcOHD4eenp7M9Pp0X1ZHZc9NZew7VXsjvrC3tmRkZACAzBuo9LZ0XkZGBpo0aSIzX0NDA8bGxkKb2qSM/mzduhWtWrVC165dZaZ/8803ePfdd6Grq4vjx49j6tSpyMnJwbRp05TWf0VVdztHjhwJGxsbWFpa4urVq5g3bx4SEhJw4MABIVfe/S2dV9uUcX8+evQI3377LSZPniwzvS7uz0ePHqGoqEjuPr5586bcZcq7T0o+B6XTymtT26qznaXNmzcPlpaWMm84Xl5e+OCDD2BnZ4fk5GR8+eWX6NevHyIjI6Gurq7UbVBEdbbT0dER27ZtQ9u2bZGVlYXvv/8eXbt2xfXr19G0adN6d3/W9L78+++/ce3aNWzdulVmen27L6ujvOdmdnY2Xrx4gadPn9b4eaBqb1zR9MUXX2DFihUVtomPj0fLli1rqUeqoeh21tSLFy+wa9cufP3112XmlZzm4uKC3NxcrFq1SqlvsqrezpKFQ5s2bWBhYYFevXohOTkZzZs3r3ZuVdXW/ZmdnQ1vb2+0bt0aixYtkplXG/cnq57ly5cjJCQE4eHhMhdJDx8+XPi7TZs2aNu2LZo3b47w8HD06tWrLrpaZV26dEGXLl2E2127dkWrVq3w888/49tvv63DnqnG1q1b0aZNG7i6uspMbwj3ZUPwxhVNs2fPxtixYyts06xZs2plm5ubAwAePnwICwsLYfrDhw/Rrl07oU1mZqbMcoWFhXjy5ImwvDIoup017c++ffuQl5eHMWPGVNrWzc0N3377LV69eqW07x2qre2UcnNzAwDcunULzZs3h7m5eZlPdjx8+BAA/nP35/Pnz+Hl5QUDAwMcPHgQmpqaFbZXxf1ZmqmpKdTV1YV9KvXw4cNyt8fc3LzC9oo8T2tbdbZT6vvvv8fy5ctx8uRJtG3btsK2zZo1g6mpKW7dulUnb7Q12U4pTU1NuLi44NatWwDq3/1Zk23Mzc1FSEgIvvnmm0rXU9f3ZXWU99yUSCTQ0dGBurp6jR8fKlfXF1X9F1T1QvDvv/9emJaVlSX3QvDLly8LbY4dO1bnF4JXtz/u7u5lPmVVniVLllCjRo2q3deaUNZ+P3v2LAGgK1euENG/F4KX/GTHzz//TBKJhF6+fKm8DVBQdbczKyuLOnfuTO7u7pSbm6vQumrr/nR1daVPP/1UuF1UVERvvfVWhReC9+/fX2Zaly5dylwIXtHztC5UdTuJiFasWEESiYQiIyMVWse9e/dIJBLRoUOHatzf6qrOdpZUWFhIjo6ONHPmTCKqn/dndbdx+/btpKWlRY8ePap0HfXhviwJCl4I/vbbb8tMGzFiRJkLwWvy+FA1LpoqkJKSQjExMcLH6WNiYigmJkbmY/WOjo504MAB4fby5cvJyMiIDh06RFevXqWBAwfKHXLAxcWFLl68SGfPnqUWLVrU+ZADFfXn/v375OjoSBcvXpRZLikpiUQiER05cqRM5uHDhykgIIDi4uIoKSmJfvrpJ9LV1aWFCxeqfHvKU9XtvHXrFn3zzTd0+fJlunPnDh06dIiaNWtG77zzjrCMdMiBvn37UmxsLB09epQaN25c50MOVGU7s7KyyM3Njdq0aUO3bt2S+UhzYWEhEdXt/RkSEkJaWloUGBhIN27coMmTJ5ORkZHwicWPPvqIvvjiC6H9uXPnSENDg77//nuKj48nPz8/uUMOVPY8rW1V3c7ly5eTWCymffv2ydxn0ten58+f05w5cygyMpLu3LlDJ0+epPbt21OLFi3qpKCXqup2Ll68mI4dO0bJyckUFRVFw4cPJ21tbbp+/brQpr7dn1XdRqnu3bvTsGHDykyvr/fl8+fPhfdFALRmzRqKiYmhlJQUIiL64osv6KOPPhLaS4ccmDt3LsXHx9OGDRvkDjlQ0b6ra1w0VcDX15cAlPk5ffq00Ab/P3aNVHFxMX399ddkZmZGWlpa1KtXL0pISJDJffz4MY0YMYL09fVJIpHQuHHjZAqx2lZZf+7cuVNmu4mI5s+fT1ZWVlRUVFQm88iRI9SuXTvS19cnPT09cnZ2pk2bNsltW1uqup2pqan0zjvvkLGxMWlpaZG9vT3NnTtXZpwmIqK7d+9Sv379SEdHh0xNTWn27NkyH9WvbVXdztOnT8t9nAOgO3fuEFHd358//PADWVtbk1gsJldXV7pw4YIwz93dnXx9fWXa79mzhxwcHEgsFpOTkxP9+eefMvMVeZ7Whapsp42Njdz7zM/Pj4iI8vLyqG/fvtS4cWPS1NQkGxsbmjRpUr1486nKds6YMUNoa2ZmRu+99x5FR0fL5NXH+7Oqj9mbN28SADp+/HiZrPp6X5b32iHdNl9fX3J3dy+zTLt27UgsFlOzZs1k3j+lKtp3dU1EVEefAWeMMcYY+w/hcZoYY4wxxhTARRNjjDHGmAK4aGKMMcYYUwAXTYwxxhhjCuCiiTHGGGNMAVw0McYYY4wpgIsmxhhjjDEFcNHEGGvQ3nnnHezatauuuyH44osv8Nlnn9V1Nxhj1cBFE2OsSsaOHQuRSIQpU6aUmffJJ59AJBJV+uXCteXw4cN4+PChzDfEA8D58+fx3nvvoVGjRtDW1kabNm2wZs0aFBUV1XidixYtgkgkKvNz8uRJAMCcOXMQFBSE27dv13hdjLHaxUUTY6zKrKysEBISghcvXgjTXr58iV27dsHa2roOeyZr/fr1GDduHNTU/n2pO3jwINzd3dG0aVOcPn0aN2/exPTp07FkyRIMHz4cyviSBCcnJ6Snp8v8vPPOOwAAU1NTeHp6YuPGjTVeD2OsdnHRxBirsvbt28PKygoHDhwQph04cADW1tZwcXGRaVtcXIxly5bBzs4OOjo6cHZ2xr59+4T5RUVFmDBhgjDf0dER/v7+Mhljx47FoEGD8P3338PCwgImJib45JNPUFBQUG4f//nnH5w6dQo+Pj7CtNzcXEyaNAkDBgzA5s2b0a5dO9ja2mLixIkICgrCvn37sGfPHgDA3bt3IRKJsGfPHvTo0QM6Ojro1KkTEhMTcenSJXTs2BH6+vro168f/vnnH5l1a2howNzcXOZHLBYL8318fBASElKFPc4Yqw+4aGKMVcv48eOxfft24fa2bdswbty4Mu2WLVuGHTt2YNOmTbh+/TpmzpyJ0aNHIyIiAsDroqpp06bYu3cvbty4gYULF+LLL78Uihep06dPIzk5GadPn0ZQUBACAwMRGBhYbv/Onj0LXV1dtGrVSph2/PhxPH78GHPmzCnT3sfHBw4ODggODpaZ7ufnh6+++grR0dHQ0NDAyJEj8fnnn8Pf3x9//fUXbt26hYULFyq0z6RcXV1x//593L17t0rLMcbqlkZdd4Ax9t80evRozJ8/HykpKQCAc+fOISQkBOHh4UKbV69e4bvvvsPJkyfRpUsXAECzZs1w9uxZ/Pzzz3B3d4empiYWL14sLGNnZ4fIyEjs2bMHQ4cOFaY3atQIP/74I9TV1dGyZUt4e3sjLCwMkyZNktu/lJQUmJmZyZyaS0xMBACZQqqkli1bCm2k5syZA09PTwDA9OnTMWLECISFhaFbt24AgAkTJpQp3uLi4qCvry/cbt26Nf7++2/htqWlpdBHW1tbuX1hjNU/XDQxxqqlcePG8Pb2RmBgIIgI3t7eMDU1lWlz69Yt5OXloU+fPjLT8/PzZU7jbdiwAdu2bUNqaipevHiB/Px8tGvXTmYZJycnqKurC7ctLCwQFxdXbv9evHgBbW1tufOqct1S27Zthb/NzMwAAG3atJGZlpmZKbOMo6MjDh8+LNzW0tKSma+jowMAyMvLU7gfjLG6x0UTY6zaxo8fj08//RTA68KntJycHADAn3/+ibfeektmnrSQCAkJwZw5c7B69Wp06dIFBgYGWLVqFS5evCjTXlNTU+a2SCRCcXFxuX0zNTXF06dPZaY5ODgAAOLj49G1a9cyy8THx6N169blrlckEsmdVrofYrEY9vb25fbtyZMnAF4Xnoyx/w4umhhj1ebl5YX8/HyIRCLhFFZJrVu3hpaWFlJTU+Hu7i4349y5c+jatSumTp0qTEtOTq5x31xcXJCRkYGnT5+iUaNGAIC+ffvC2NgYq1evLlM0HT58GElJSfj2229rvO7KXLt2DZqamnByclL5uhhjysNFE2Os2tTV1REfHy/8XZqBgQHmzJmDmTNnori4GN27d0dWVhbOnTsHiUQCX19ftGjRAjt27MCxY8dgZ2eHX375BZcuXYKdnV2N+ubi4gJTU1OcO3cO/fv3BwDo6enh559/xvDhwzF58mR8+umnkEgkCAsLw9y5czF48GCZ66hU5a+//hI+kccY++/gT88xxmpEIpFAIpGUO//bb7/F119/jWXLlqFVq1bw8vLCn3/+KRRFH3/8MT744AMMGzYMbm5uePz4scxRp+pSV1fHuHHjsHPnTpnpgwcPxunTp5GamooePXrA0dERa9euxYIFCxASEiKcglOlkJCQci9gZ4zVXyJSxkhujDFWD2VkZMDJyQnR0dGwsbGp6+4AAI4cOYLZs2fj6tWr0NDgg/2M/ZfwkSbGWINlbm6OrVu3IjU1ta67IsjNzcX27du5YGLsP4iPNDHGGGOMKYCPNDHGGGOMKYCLJsYYY4wxBXDRxBhjjDGmAC6aGGOMMcYUwEUTY4wxxpgCuGhijDHGGFMAF02MMcYYYwrgookxxhhjTAFcNDHGGGOMKYCLJsYYY4wxBXDRxBhjjDGmAC6aGGOMMcYUwEUTY4wxxpgCuGhijDHGGFMAF02MMcYYYwrgookxxhhjTAFcNDHGGGOMKYCLJsYYY4wxBXDRxBhjjDGmAC6aGGOMMcYUwEUTY4wxxpgCuGhidWbRokVo165djXMCAwPRs2fPGuewyoWHh0MkEuHZs2cAXu97IyOjOu2TMmzevBlWVlZQU1PDunXr6ro7TAk2bNgAW1tbaGtrw83NDX///bfM/M2bN6Nnz56QSCQyj+nS/vjjD7i7u8PAwAC6urro1KkTAgMDq9SXsWPHYtCgQQq1TU1Nhbe3N3R1ddGkSRPMnTsXhYWFwvwDBw6gT58+aNy4MSQSCbp06YJjx46Vybl37x7Gjx8PS0tLiMVi2NjYYPr06Xj8+LHC/S79fK+o3cCBA2FhYQE9PT20a9cOO3fuLNNu7969aNmyJbS1tdGmTRuEhoYK8woKCjBv3jy0adMGenp6sLS0xJgxY5CWliaTYWtrC5FIJPOzfPlyhbepprhoYgJFnyANyYsXL2BsbAxTU1O8evWqzHzpEzQkJKTMPCcnJ4hEIpkX0CtXrmDAgAFo0qQJtLW1YWtri2HDhiEzMxNAxfvY1tZWoTfsyvpcm4YNG4bExMQ67UNNZWdn49NPP8W8efPw4MEDTJ48ua67hEWLFkEkEsHLy6vMvFWrVkEkElXpH4W7d+9CJBIhNjZWeZ2sQM+ePWXe1MzMzDBkyBCkpKTUyvp3796NWbNmwc/PD9HR0XB2doanp6fwPASAvLw8eHl54csvvyw354cffsDAgQPRrVs3XLx4EVevXsXw4cMxZcoUzJkzR+n9Lioqgre3N/Lz83H+/HkEBQUhMDAQCxcuFNqcOXMGffr0QWhoKKKiouDh4QEfHx/ExMQIbW7fvo2OHTsiKSkJwcHBuHXrFjZt2oSwsDB06dIFT548UWq/z58/j7Zt22L//v24evUqxo0bhzFjxuCPP/6QaTNixAhMmDABMTExGDRoEAYNGoRr164BeH1/REdH4+uvv0Z0dDQOHDiAhIQEDBgwoMz6vvnmG6Snpws/n332mVK3p0LE2P87ffo0AaCnT5/Wyvr8/PzI2dm5xjnbt28nd3f3ai37yy+/UPfu3albt24UEhJSZr6NjQ1ZWVlR3759ZaZHRkaSsbEx6enp0fbt24mIKDMzk0xMTMjX15eio6Pp9u3bdOrUKZoxYwbdvn2biCrexzY2NrR27doa97kyr169qvIyUrX9GKkNcXFxBEC4j+SpyT6rDj8/P7KwsCCxWEz37t2TmdeyZUuytrau0mP+zp07BIBiYmKU29FyuLu706RJkyg9PZ3S0tIoMjKS3NzcqHv37rWyfldXV/rkk0+E20VFRWRpaUnLli0r07a8x3RqaippamrSrFmzyiyzfv16AkAXLlwQpl27do28vb3JwMCA9PX1qXv37nTr1i3y8/MjADI/p0+fltvv0NBQUlNTo4yMDGHaxo0bSSKRVPgYbN26NS1evFi47eXlRU2bNqW8vDyZdunp6aSrq0tTpkwRpr18+ZI+//xzatq0KYnFYmrevDlt2bJFeMyU/PH19S23D6W99957NG7cOOH20KFDydvbW6aNm5sbffzxx+Vm/P333wSAUlJShGmKvk6qyhtzpOno0aPo3r07jIyMYGJigv79+yM5OVmYL/1PbM+ePejRowd0dHTQqVMnJCYm4tKlS+jYsSP09fXRr18//PPPP8Jy4eHhcHV1hZ6eHoyMjNCtWzfhvyl5h2RnzJgh8x9iZf2SR3q04tixY3BxcYGOjg7effddZGZm4siRI2jVqhUkEglGjhyJvLw8Ybni4mIsW7YMdnZ20NHRgbOzM/bt2ydsv4eHBwCgUaNGEIlEGDt2LADg1atXmDZtmnD0pHv37rh06VKZ/vz5559o27YttLW10blzZ+E/iMr8/PPPsLKygq6uLoYOHYqsrCyFllOGrVu3YvTo0Rg9ejS2bt0qt82oUaMQERGBe/fuCdO2bduGUaNGQUNDQ5h27tw5ZGVlYcuWLXBxcYGdnR08PDywdu1a2NnZ1WqfS5I+DpcuXQpLS0s4OjoCAH755Rd07NgRBgYGMDc3x8iRI2X+EweA0NBQODg4QEdHBx4eHrh7967M/NKn55KTkzFw4ECYmZlBX18fnTp1wsmTJ2WWsbW1xXfffYfx48fDwMAA1tbW2Lx5s0yb+/fvY8SIETA2Noaenh46duyIixcvCvMPHTqE9u3bQ1tbG82aNcPixYuFUxhEhEWLFsHa2hpaWlqwtLTEtGnT5O6bwMBAtGnTBgDQrFkziEQi3L17Vzh1vGXLFtjZ2UFbWxvA61MnAwcOhL6+PiQSCYYOHYqHDx8KedLltm3bBmtra+jr62Pq1KkoKirCypUrYW5ujiZNmmDp0qWV3W1o0qQJ+vbti6CgIGHa+fPn8ejRI3h7e5dpv2XLFrRq1Qra2tpo2bIlfvrpJ2Ge9PHn4uIic5SquLgY33zzDZo2bQotLS20a9cOR48eFZaTvi6GhISga9eu0NbWxttvv42IiIhK+6+rqwtzc3NYWFigc+fO+PTTTxEdHV3pcjWVn5+PqKgo9O7dW5impqaG3r17IzIyUuGcffv2oaCgQO4RpY8//hj6+voIDg4GADx48ADvvPMOtLS0cOrUKURFRWH8+PEoLCzEnDlzMHToUHh5eQlHRrp27Sp3nZGRkWjTpg3MzMyEaZ6ensjOzsb169flLlNcXIznz5/D2NgYAPDkyRMcO3YMU6dOhY6Ojkxbc3NzjBo1Crt37wYRAQDGjBmD4OBgrF+/HvHx8fj555+hr68PKysr7N+/HwCQkJCA9PR0+Pv7K7z/srKyhD5Jt63kfSLdtoruk6ysLIhEojKXACxfvhwmJiZwcXHBqlWrZE5fqlydlWu1bN++fbR//35KSkqimJgY8vHxoTZt2lBRURER/fufWMuWLeno0aN048YN6ty5M3Xo0IF69uxJZ8+epejoaLK3txeq9IKCAjI0NKQ5c+bQrVu36MaNGxQYGChUxb6+vjRw4ECZfkyfPl3mP8TK+iWP9D+jzp07y/TL3d2d+vbtS9HR0XTmzBkyMTGh5cuXC8stWbJE2L7k5GTavn07aWlpUXh4OBUWFtL+/fsJACUkJFB6ejo9e/aMiIimTZtGlpaWFBoaStevXydfX19q1KgRPX78WKY/rVq1ouPHj9PVq1epf//+ZGtrS/n5+eVuh5+fH+np6dG7775LMTExFBERQfb29jRy5EjF71iq/pGmW7dukZaWFj158oQeP35M2tradPfuXZk20v9qBgwYQN9++y0REeXm5pJEIqGYmBgyNDQUjjRFRkYSANqzZw8VFxfLXWdNjzQp0ufSfH19SV9fnz766CO6du0aXbt2jYiItm7dSqGhoZScnEyRkZHUpUsX6tevn7BcamoqaWlp0axZs+jmzZv066+/kpmZmUz/t2/fToaGhsIysbGxtGnTJoqLi6PExET66quvSFtbu8x/isbGxrRhwwZKSkqiZcuWkZqaGt28eZOIiJ4/f07NmjWjHj160F9//UVJSUm0e/duOn/+PBERnTlzhiQSCQUGBlJycjIdP36cbG1tadGiRUREtHfvXpJIJBQaGkopKSl08eJF2rx5s9x9k5eXRydPniQA9Pfff1N6ejoVFhYKj00vLy+Kjo6mK1euUFFREbVr1466d+9Oly9fpgsXLlCHDh1kHnt+fn6kr69PgwcPpuvXr9Phw4dJLBaTp6cnffbZZ3Tz5k3atm1bmaMUpUmPwh44cIDs7e2F6RMmTKDp06eXeR359ddfycLCgvbv30+3b9+m/fv3k7GxMQUGBhLRv/+xnzx5ktLT04Xn7po1a0gikVBwcDDdvHmTPv/8c9LU1KTExEQi+vd1sWnTprRv3z66ceMGTZw4kQwMDOjRo0fl9t/d3Z2mT58u3H78+DH5+PiQh4dHucsoy4MHDwiA8HiRmjt3Lrm6upZpX95zcsqUKTKP7dLatm0rPF/mz59PdnZ25b7eyXsvkGfSpElljmrn5uYSAAoNDZW7zIoVK6hRo0b08OFDIiK6cOECAaCDBw/Kbb9mzRoCQA8fPqSEhAQCQCdOnJDbtrpHlnfv3k1isVh4rSEi0tTUpF27dsm027BhAzVp0kRuxosXL6h9+/Zl3g9Wr15Np0+fpitXrtDGjRvJyMiIZs6cWaX+1cQbUzSV9s8//xAAiouLI6J/Xxy2bNkitAkODiYAFBYWJkxbtmwZOTo6EtHrFwIAFB4eLncdihRNlfVLHukD+eTJkzL9AkDJycnCtI8//pg8PT2J6PUhWF1d3TIvJBMmTKARI0bI5JZ8guTk5JCmpibt3LlTmJafn0+Wlpa0cuVKmeVKnip6/Pgx6ejo0O7du8vdDj8/P1JXV6f79+8L044cOUJqamqUnp5e7nKlVbdo+vLLL2nQoEHC7YEDB5Kfn59MG2kh89tvv1Hz5s2puLiYgoKCyMXFhYhIpmiSZmpoaJCxsTF5eXnRypUrZQ6117RoUqTPpfn6+pKZmVmlp5guXbpEAOj58+dE9PqNoHXr1jJt5s2bV2HRJI+TkxP98MMPwm0bGxsaPXq0cLu4uJiaNGlCGzduJCKin3/+mQwMDIQ39tJ69epF3333ncy0X375hSwsLIjo9Yuqg4NDhQV7STExMQSA7ty5I0zz8/MjTU1NyszMFKYdP36c1NXVKTU1VZh2/fp1oeCSLqerq0vZ2dlCG09PT7K1tZX5R8jR0VHuqaKS63d2dqb8/Hxq0qQJRUREUE5ODhkYGNCVK1fKvI40b968zBvSt99+S126dCGi8k/PWVpa0tKlS2WmderUiaZOnSqzXMl/vgoKCqhp06a0YsWKcvvv7u5OmpqapKenR7q6ugSAHBwcZPaxqtRF0dSvXz8aM2ZMuW3lvRd4eXmRnp4e6enpCc+zqhZNO3fuJF1dXZmiR1o0HThwQG5fShZNu3fvJnV19XKfK9Upmk6dOkW6uroUFBQkM70qRVN+fj75+PiQi4sLZWVlVbi+rVu3koaGBr18+VLhPtbEG3N6LikpCSNGjECzZs0gkUhga2sL4PXh9pLatm0r/C09RCo9fC+dJj2FYWxsjLFjx8LT0xM+Pj7w9/dHenq6UvvVr18/6OvrQ19fH05OThX2VVdXF82aNZPb11u3biEvLw99+vQR8vT19bFjx44KTwcmJyejoKAA3bp1E6ZpamrC1dUV8fHxMm27dOki/G1sbAxHR0ehTcl1TpkyRWhnbW2Nt956SyajuLgYCQkJFe+4GioqKkJQUBBGjx4tTBs9ejQCAwNRXFxcpr23tzdycnJw5swZbNu2DePHj5ebu3TpUmRkZGDTpk1wcnLCpk2b0LJlS8TFxVWpf/Lu96r2uaQ2bdpALBbLTIuKioKPjw+sra1hYGAAd3d3AP8+9uLj4+Hm5iazTMn7WJ6cnBzMmTMHrVq1gpGREfT19REfH1/h80wkEsHc3Fx4rMbGxsLFxUXm0H5JV65cwTfffCPzmJo0aRLS09ORl5eHIUOG4MWLF2jWrBkmTZqEgwcPVuvwvY2NDRo3bizcjo+Ph5WVFaysrIRprVu3hpGRkcxzwdbWFgYGBsJtMzMztG7dGmpqajLTSp8KlUdTUxOjR4/G9u3bsXfvXjg4OMjsOwDIzc1FcnIyJkyYILNPlixZUuFzOzs7G2lpaTLPbQDo1q1bhc9tDQ0NdOzYUWjj5OQkrLNfv35Cu1GjRiE2NhZXrlzB2bNnYW9vj759++L58+eVbndNmJqaQl1dXea0KQA8fPgQ5ubmCuc4ODggKyurzKe3gNenAJOTk+Hg4AAAZU6DKWLLli2IjY1FbGys8Ckyc3Nzuf2WzispJCQEEydOxJ49e2ROe9nb20MkEpW5D6Xi4+PRqFEjNG7cuFr9rkhERAR8fHywdu1ajBkzRmZeedtWersKCgowdOhQpKSk4MSJE5BIJBWu083NDYWFhWUuHVAVjcqbNAw+Pj6wsbFBQEAALC0tUVxcjLfffhv5+fky7TQ1NYW/RSKR3Gkl36C2b9+OadOm4ejRo9i9eze++uornDhxAp07d4aamppw3liqoKCgSv3asmULXrx4UaYf8vpVen7Jvubk5AAA/vzzT5kiBQC0tLTk7jNlKvmpncqeBLXh2LFjePDgAYYNGyYzvaioCGFhYejTp4/MdA0NDXz00Ufw8/PDxYsXcfDgwXKzTUxMMGTIEAwZMgTfffcdXFxc8P333yMoKEjY9qysrDLn6Z89ewZDQ0MA8u/3qva5JD09PZnbubm58PT0hKenJ3bu3InGjRsjNTUVnp6eZZ4TVTFnzhycOHEC33//Pezt7aGjo4PBgwdX+DwDZB+rlb2Q5+TkYPHixfjggw/KzNPW1oaVlRUSEhJw8uRJnDhxAlOnTsWqVasQERFRZr0VKb3PFCVv2yra3sqMHz8ebm5uuHbtmtxiXfrcDggIKFPkqqurV6Xr1RIaGiq8rpW87wwNDWFvbw/g9Rv51q1bYWFhgd27d2PixIkq649YLEaHDh0QFhYmXFNaXFyMsLAwfPrppwrnfPjhh5g3bx5Wr16N1atXy8zbtGkTcnNzMWLECACv/wkICgpCQUGB3MeYWCxGUVGRzLTSr8PA6+J06dKlyMzMRJMmTQBAKBxat24ttAsODsb48eMREhJS5vo2ExMT9OnTBz/99BNmzpwpc59kZGRg586dGDNmDEQiEdq0aYPi4mJERESUud5I2m8AZfouT3h4OPr3748VK1bI/QRqly5dEBYWhhkzZgjTTpw4IVOQSwumpKQknD59GiYmJpWuNzY2FmpqasL+UrU3omh6/PgxEhISEBAQgB49egAAzp49q7R8FxcXuLi4YP78+ejSpQt27dqFzp07o3HjxmUuho6NjRWeVIr0S94Tqzpat24NLS0tpKamCkcUSpP3BGnevDnEYjHOnTsHGxsbAK8f2JcuXZJ58APAhQsXYG1tDQB4+vQpEhMT0apVKwAQXjxLS01NRVpaGiwtLYUMNTU14WJlVdm6dSuGDx+OBQsWyExfunQptm7dKrcAGT9+PL7//nsMGzYMjRo1Umg9YrEYzZs3R25uLgCgRYsWUFNTQ1RUlLA/gdcfEc7KyhL+c5V3v1enz+W5efMmHj9+jOXLlwtHTi5fvizTplWrVjh8+LDMtAsXLlSYe+7cOYwdOxbvv/8+gNdv6FX9D7Bt27bYsmULnjx5IvdoU/v27ZGQkFDuYwp4/ebt4+MDHx8ffPLJJ8LRvvbt21epLyW1atUK9+7dw71794R9duPGDTx79kzmDU3ZnJyc4OTkhKtXr2LkyJFl5puZmcHS0hK3b9/GqFGj5GbIe25LJBJYWlri3LlzMq8J586dg6urq8zyFy5cwDvvvAMAKCwsRFRUlFCAlHwcV0RawEn/GVClWbNmwdfXFx07doSrqyvWrVuH3NxcjBs3TmiTkZGBjIwM3Lp1CwAQFxcnfDDB2NgY1tbWWLlyJWbPng1tbW189NFH0NTUxKFDh/Dll19i9uzZQpH66aef4ocffsDw4cMxf/58GBoa4sKFC3B1dYWjoyNsbW1x7NgxJCQkwMTEBIaGhnKLq759+6J169b46KOPsHLlSmRkZOCrr77CJ598Ivxzu2vXLvj6+sLf3x9ubm7IyMgA8PoxL/2n68cff0TXrl3h6emJJUuWwM7ODtevX8fcuXPx1ltvCR9EsLW1ha+vL8aPH4/169fD2dkZKSkpyMzMxNChQ2FjYwORSIQ//vgD7733HnR0dKCvr1+m36dPn0b//v0xffp0fPjhh0KfxGKx8ByePn063N3dsXr1anh7eyMkJASXL18WPgRSUFCAwYMHIzo6Gn/88QeKioqEHGNjY4jFYkRGRuLixYvw8PCAgYEBIiMjMXPmTIwePVrh1+Qaq5WTgHWsqKiITExMaPTo0ZSUlERhYWHUqVMnmYvl5J3zl3c+t+Q1HLdv36YvvviCzp8/T3fv3qVjx46RiYkJ/fTTT0REdPToURKJRBQUFESJiYm0cOFCkkgkwrUIivRLnsr6JVX6I/0LFiwgExMTCgwMpFu3blFUVBStX79euFj0/v37JBKJKDAwkDIzM4VrW6ZPn06WlpZ05MgRmQvBnzx5ItMfJycnOnnyJMXFxdGAAQPI2tq6wutopBfb9u7dm2JjY+nMmTPk4OBAw4cPL3cZeap6TVNmZiZpamrSkSNHyswLDQ0lLS0t4Xqa0tcZPXr0SOZjvCWvafr9999p1KhR9Pvvv1NCQgLdvHmTVq1aRerq6rRjxw5hmcmTJ5OtrS0dOnSIbt++TREREdS5c2fq3LlzuReQV6XPpcm7niIzM5PEYjHNnTuXkpOT6dChQ+Tg4CDzHEhJSSGxWExz5syhmzdv0s6dO8nc3LzCa5ref/99ateuHcXExFBsbCz5+PiQgYGBzEXB8q7dcnZ2Fq7NevXqFTk4OFCPHj3o7NmzlJycTPv27ROuUTl69ChpaGjQokWL6Nq1a3Tjxg0KDg6mBQsWCH3asmULxcXFUXJyMn311Veko6NT7oXL5V3TVHo4jOLiYmrXrh316NGDoqKi6OLFi3IvBC+9nLz9X/pC6dJK5+Tk5Mg830tf0xQQEEA6Ojrk7+9PCQkJdPXqVdq2bRutXr2aiF5fh6Sjo0NLliyhjIwM4UMea9euJYlEQiEhIXTz5k2aN2+e3AvBra2t6cCBAxQfH0+TJ08mfX19+ueff8rtf8khB9LT0yk2NpY+/PBD0tbWFi74V7UffviBrK2tSSwWk6ura5kL7+UNBQBA5hpFIqJDhw5Rjx49SE9Pj7S1talDhw60bdu2Muu7cuUK9e3bl3R1dcnAwIB69OghXGOamZlJffr0IX19/QqHHCAiunv3LvXr1490dHTI1NSUZs+eTQUFBcJ8d3d3uf0uPRzA3bt3hesZNTU1ycrKij777LMyz4MXL17QzJkzhSEu7O3tZbbvm2++IXNzcxKJROUOOeDr6yu3T6Vfl/fs2UMODg4kFovJycmJ/vzzT2GevCEOpD/S/RUVFUVubm5kaGhI2tra1KpVK/ruu+9q7XomojfoQvATJ05Qq1atSEtLi9q2bUvh4eE1LpoyMjJo0KBBwoPNxsaGFi5cKHPB58KFC8nMzIwMDQ1p5syZ9Omnn8o8kCrrlzzVLZqKi4tp3bp15OjoSJqamtS4cWPy9PSkiIgIoY28J8iLFy/os88+I1NTU9LS0qJu3boJF76W7M/vv/9OTk5OwovUlStXyt2Gkv376aefyNLSkrS1tWnw4MFCMaaoqhZN33//PRkZGcm9+PHVq1dkZGRE/v7+RFT5xdkli6bk5GSaNGkSOTg4kI6ODhkZGVGnTp3KvAi/ePGC/Pz8qGXLlqSjo0N2dnY0efLkCt+EqtLn0sr75M6uXbvI1taWtLS0qEuXLnT48OEyz4Hff/+d7O3tSUtLi3r06CF88qu8ounOnTvk4eFBOjo6ZGVlRT/++GOZAqGyoono9Qv+hx9+SBKJhHR1daljx4508eJFYf7Ro0epa9eupKOjQxKJhFxdXYVPyB08eJDc3NxIIpGQnp4ede7cWeZDE6UpWjQRvS4kBwwYQHp6emRgYEBDhgyRudBfVUVTafI+ULJz505q164dicViatSoEb3zzjsyFwMHBASQlZUVqampyfzjtmjRInrrrbdIU1OTnJ2dZQpz6evirl27yNXVlcRiMbVu3ZpOnTpVbt+k21fyTa9Ro0bk7u5e6XKM1XciolIX3TBWReHh4fDw8MDTp0/r5Cs1AgMDERgYiPDw8FpfN2MN2d27d2FnZ4eYmBilfOURY/91b8yn5xhjjDHGaoKLJsYYY4wxBfDpOfafJx3rRPq1L4wxxpgqcNHEGGOMMaYAPj3HGGOMMaaABj+4ZXFxMdLS0mBgYCCM8M0YY4yxhoWI8Pz5c1haWsp8bZEyNfiiKS0tTea7ohhjjDHWcN27dw9NmzZVSXadFk1nzpzBqlWrEBUVhfT0dBw8eFD4riAAGDt2LIKCgmSW8fT0xNGjRxVeh/SLM1esWCEMeX/lyhXhouHc3Fz4+/tj+vTp2Lt3L5ydneHi4gIAiImJwZUrVzBkyBChjfT7qAIDA+Hs7Mx5nMd5nMd5nMd59SAvIyMDjo6OMl+YrXR1OLAmhYaG0oIFC+jAgQNyR8H29fUlLy8vYSj+9PT0Ko8WnZWVRQAoKyuLpkyZQlOmTCnTJicnhywtLWVGxpaKiIggS0tLysnJKTOP8ziP8ziP8ziP8+pHXsn3e1Wp0wvB+/XrhyVLlghf7imPlpYWzM3NhZ/qfilfTEwM2rdvj/bt2yMqKkpm3q5duxAcHIywsDDhi1WB11VwWFgYgoODsWvXLplloqKiOI/zOI/zOI/zOK8e5amcysqxKkI5R5oMDQ2pcePG5ODgQFOmTCn3SzelXr58SVlZWcLPvXv3CIDM93Jt3ryZLl++XObvnJwcWrhwIeXk5Mj8TUR0+fJl4butSv7NeZzHeZzHeZzHeXWf5+/vr/IjTfW6aAoODqZDhw7R1atX6eDBg9SqVSvq1KkTFRYWlptT3jdXl96JmzdvpilTpgg7WyonJ4dmz55Ns2fPLnNI8PLlyzRlyhSZO4zzOI/zOI/zOI/z6j5P+oX3qiya6vWn54YPHy783aZNG7Rt2xbNmzdHeHg4evXqJXeZ+fPnY9asWcLt7Oxs/vQcY4wxxmpOZeVYFUHOkSZ5TE1NadOmTQrnSi8M49NznMd5nMd5nMd5DTevNk7P1ZuvURGJRGWGHCjt/v37sLa2xm+//YYBAwYolJudnQ1DQ0OEh4cjMTERANC+fXt06NBBaBMQEABHR0eEhYXh888/Fz7WmJubi5UrV6JXr15ISEjApEmThGWioqIQHR3NeZzHeZzHeZzHefUgT/p+n5WVBYlEApVQWTmmgOfPn1NMTAzFxMQQAFqzZg3FxMRQSkoKPX/+nObMmUORkZF0584dOnnyJLVv355atGhBL1++VHgdPOQA53Ee53Ee53Few8+rjSEH6rRoOn36tNyLtn19fSkvL4/69u1LjRs3Jk1NTbKxsaFJkyZRRkZGldZR8vTc5cuXyxzaK3kYsORhPqJ/DwOWPlRI9O8hQc7jPM7jPM7jPM6r+7y0tLSGXTRFRERQ//79ycLCotJrmj7++GMCQGvXrq3SOqRFU3h4uDCtPty5nMd5nMd5nMd5nKe8vHnz5jXsoqmyEcGlDhw4QM7OzmRpaVntoqn0Tqzrw4icx3mcx3mcx3mcp7y82jjSVO9HBH/w4AE+++wz7Ny5E5qamtVeV30cuZTzOI/zOI/zOI/zlJO3d+9eqJzKyrEqgpwjTUVFReTh4UHr1q0jIiIbG5tKjzSVNyL4vHnzKCen/nw0kvM4j/M4j/M4j/OUl1cbg1vW66Lpu+++oz59+lBxcTERKVY0lTcieFpaWr0auZTzOI/zOI/zOI/zlJfX4L+wtyJRUVHw9/dHYGAgRCKRwsvNnz8fWVlZws+9e/dU2EvGGGOMvTFUVo5VEUodaVq7di2JRCJSV1cXfgCQmpoa2djYKJwrrTz59BzncR7ncR7ncV7DzauN03P1dkTwx48fIz09XaaNp6cnPvroI4wbNw6Ojo4K5UpHCE1LS4OFhQWA+jFyKedxHudxHudxHucpLy82NhbTp09/M0cEl0eRa5pK4yEHOI/zOI/zOI/zGn5ebQw5UKdHmvz9/TFjxowy0319fREYGIhFixYhJCQE9+7dg1gsxsuXLzFlyhSsXbtW4XVIjzTtjbwFXX0DJfb+zZVdUFDXXWhwiuvHAd8GRU9Do6670KDkFxfXdRcaHLUqXK/LKpeX8xxjujuq9EhTnV4I7uDggAULFuDAgQMAgIMHD4KIEBgYKMz/8ccfERcXh7Nnz2LUqFHYtm0b/vnnnzrsNWOMMcbeRPX2miZ5pEeNTp48iV69eimUy0ealI+PNCkfH2lSPj7SpFx8pEn5+EiTcjX4I01VkZ+fj82bN8PQ0BDOzs513R3GGGOMvWHq/b9if/zxB4YPH468vDxYWFjgxIkTMDU1Lbf9q1ev8OrVK+F2dnZ2bXSTMcYYYw1cvT/S5OHhgdjYWJw/fx5eXl4YOnQoMjMzy22/bNkyGBoaCj9WVla12FvGGGOMNVT1vmjS09ODvb09OnfujK1bt0JDQwNbt24ttz2PCM4YY4wxVaj3p+dKKy4uljn9VpqWlha0tLRqsUeMMcYYexPUadGUk5ODW7duCbfv3LmD2NhYGBsbw8TEBEuXLsWAAQNgYWGBR48eYcOGDXjw4AGGDBlSh71mjDHG2JuoToumy5cvw8PDQ7g9a9YsAK8Ht9y0aRNu3ryJoKAgPHr0CCYmJujUqRP++usvODk51VWXGWOMMfaGqtOiSU1NDf3790dUVBTS09NlxmkqKChAixYtkJSUhGfPngEADA0N8dZbb1VrXaa6Yujr8Wk7ZTAuEtd1FxocHqVJ+dTVeAwcZSos4nGalE3E4zQpVW6x6scQrNMLwXNzc+Hs7IwNGzaUmZeXl4fo6Gh8/fXXiI6OxoEDB5CQkIABAwbUQU8ZY4wx9qar0yNN/fr1Q79+/eTOMzQ0xIkTJ2Sm/fjjj3B1dUVqaiqsra1ro4uMMcYYYwD+Y5+ey8rKgkgkgpGRUblteHBLxhhjjKlCvR+nSerly5eYN28eRowYUeF3yvDglowxxhhThf9E0VRQUIChQ4eCiLBx48YK2/LglowxxhhThXp/ek5aMKWkpODUqVOVfnMxD27JGGOMMVWo10WTtGBKSkrC6dOnYWJiUtddYowxxtgbqt6OCG5hYYHBgwcjOjoaf/zxB4qKipCRkQEAMDY2hljMYwUxxhhjrPaIiKjOxtULDw+XGRFcytfXF4sWLYKdnZ3c5U6fPo2ePXsqtI7s7GwYGhriUkIa9A0qPrXHFFNYxEMxKpuGOg9yx+q3omJ+3isbD26pXDnPs+HW0hJZWVmVXspTXXV6Ibh0RHALCwsAwMGDB0FECAwMhK2tLfbv348+ffrA2NgYABATEwMiUrhgYowxxhhTlno7Irh0fvfu3bFixYpa7hljjDHGmKx6OyI4AHz00UcAgLt379ZSjxhjjDHG5KvXn56rDh4RnDHGGGOqUK3Tcy9evEBeXp5wOyUlBevWrcPx48eV1rHq4hHBGWOMMaYK1SqaBg4ciB07dgAAnj17Bjc3N6xevRoDBw6sdMRuVeMRwRljjDGmCtUqmqKjo9GjRw8AwL59+2BmZoaUlBTs2LED69evV2oHq0pLSwsSiUTmhzHGGGOspqpVNOXl5cHAwAAAcPz4cXzwwQdQU1ND586dkZKSotQOMsYYY4zVB9W6ENze3h6//fYb3n//fRw7dgwzZ84EAGRmZlbpyE5FI4JbW1vjyZMnSE1NRVpaGgAgISEBAGBubg5zc/PqdJ0xxhhjrFqqNSL4vn37MHLkSBQVFaFXr17CBeDLli3DmTNncOTIEYVyKhoRPDAwEIGBgRg3blyZ+X5+fli0aJFC65COCB6bnAEDHhGc1VM8MjCr73hEcOXjZ71yPX+eDRd7c5WOCF6tI02DBw9G9+7dkZ6eDmdnZ2F6r1698P777yucIx0RPCoqCunp6Th48CAGDRokzPf19cXt27cREBCAZ8+eoVu3bti4cSNatGhRnW4zxhhjjFVbtUcENzc3h4uLC9TU/o1wdXVFy5YtFc6obETwlStXYv369di0aRMuXrwIPT09eHp64uXLl9XtNmOMMcZYtSh8pOmDDz5QOPTAgQMKtatoRHAiwrp16/DVV19h4MCBAIAdO3bAzMwMv/32G4YPH65wfxhjjDHGakrhosnQ0FCV/Sjjzp07yMjIQO/evWX64ObmhsjIyHKLJh4RnDHGGGOqoHDRtH37dlX2o4yMjAwAgJmZmcx0MzMzYZ48y5Ytw+LFi1XaN8YYY4y9eap9TVNhYSFOnjyJn3/+Gc+fPwcApKWlIScnR2mdqw4eEZwxxhhjqlCtT8+lpKTAy8sLqampePXqFfr06QMDAwOsWLECr169wqZNm2rcMek4TA8fPoSFhYUw/eHDh2jXrl25y2lpaUFLS6vG62eMMcYYK6laR5qmT5+Ojh074unTp9DR0RGmv//++wgLC1NKx+zs7GBubi6Tl52djYsXL6JLly5KWQdjjDHGmKKqdaTpr7/+wvnz5yEWi2Wm29ra4sGDBwrnVDYi+IwZM7BkyRK0aNECdnZ2+Prrr2FpaSkzlhNjjDHGWG2oVtFUXFyMoqKiMtPv378vfCedIi5fviwzIvisWbMA/Dsi+Oeff47c3FxMnjwZz549Q/fu3XH06FFoa2tXuc9qIhHUeNRlpeDdqHw8IrjyqfEuZfWcOj9GlUqzFnZotU7P9e3bF+vWrRNui0Qi5OTkwM/PD++9957COT179gQRlfkJDAwUcufOnYvhw4fDzMwM586dw9ixY3Hp0qXqdJsxxhhjrNqqVTStXr0a586dQ+vWrfHy5UuMHDlSODW3YsUKpXZw4sSJOHHiBH755RfExcWhb9++6N27d5VOAzLGGGOM1VS1vrAXeD3kQEhICK5evYqcnBy0b98eo0aNkrkwvKZevHgBAwMDHDp0CN7e3sL0Dh06oF+/fliyZEmlGdIv7L16+yF/Ya+S8Jkk5ePTc8rHp+eUq6CIv7BX2fj0nHI9f56Nt+3M6t8X9gKAhoYGRo8ercy+lFFYWIiioqIy1zDp6Ojg7NmzcpfhEcEZY4wxpgrVLpqSkpJw+vRpZGZmori4WGbewoULa9wxADAwMECXLl3w7bffolWrVjAzM0NwcDAiIyNhb28vdxkeEZwxxhhjqlCt03MBAQH43//+B1NTU5ibm8ucWhCJRIiOjlZaB5OTkzF+/HicOXMG6urqaN++PRwcHBAVFYX4+Pgy7eUdabKysuLTc0rEZ5KUj0/PKR+fnlMuPj2nfHx6Trlq4/RctYomGxsbTJ06FfPmzVNFn+TKzc1FdnY2LCwsMGzYMOTk5ODPP/+sdDm+pkn5+P1d+bhoUj4umpSLiybl46JJuWqjaKrWp+eePn2KIUOGKLsvFdLT04OFhQWePn2KY8eOYeDAgbW6fsYYY4y92apVNA0ZMgTHjx9Xdl/kOnbsGI4ePYo7d+7gxIkT8PDwQMuWLTFu3LhaWT9jjDHGGFDNC8Ht7e3x9ddf48KFC2jTpg00NTVl5k+bNk0pnQOArKwszJ8/H/fv34exsTE+/PBDLF26tMw6K6Mm4sP1ysIH6ZWvmiN/sAoU8y5VKn79ZKyaRdPmzZuhr6+PiIgIREREyMwTiURKK5qKiooQFxeH4uJiqKmpQVdXF2ZmZio7V8kYY4wxVp5qFU137txRdj/kWrFiBTZu3IigoCA4OTnh8uXLGDduHAwNDZV6NIsxxhhjrDLVHqepNpw/fx4DBw4URgO3tbVFcHAw/v777zruGWOMMcbeNNUqmoqKihAYGIiwsDC5g1ueOnVKKZ3r2rUrNm/ejMTERDg4OODKlSs4e/Ys1qxZU+4yPCI4Y4wxxlShWkXT9OnTERgYCG9vb7z99tsqG2Pmiy++QHZ2Nlq2bAl1dXUUFRVh6dKlGDVqVLnL8IjgjDHGGFOFag1uaWpqih07duC9995TRZ8EISEhmDt3LlatWgUnJyfExsZixowZWLNmDXx9feUuU96I4Nfu8OCWysIfSmL/BfxhL+Xi573y8WNUuertF/aKxeJyv/tNmebOnYsvvvgCw4cPBwC0+T/27jwsqrJ/A/g9KDOArC5symK5466paP3UXFDJtMXU14rcyqXUUiNbJCtzqTTyNU0zqNdcc8l8XTISzDVBUFFDVNwCtFxA3FD4/v7wnRPDMDDAbMD9ua65YM55zn2e85wZ5uEsz7RogXPnzmHWrFkGO00ajQYajcbsdSMiIqKqpUyDW06ePBmRkZFmH1vm1q1bsLPTrWK1atX0rqEiIiIiMrcyHWnavXs3du7cia1btyIoKEhvoMn169ebpHL9+/fHzJkz4e/vj6CgICQmJmLevHkYMWKESfKJiIiIjFWmTpO7uzueeuopU9dFz4IFC/Dee+9h3LhxuHz5Mnx9ffHKK69g+vTppc6yU6lgxyFtTYKDV1NFwLe7aXGEdbJ1KgtcJVamC8EtKTAwEOfOndObPm7cOCxcuLDE5bOzs+Hm5objZy/DhSOJm4Rtv2KIHmCnybTYaSJbdyM7G0H1PW3vQnBLOnjwIPLy8pTnycnJ6NWrFwYNGmTFWhEREVFVU+ZO0w8//IA1a9bg/PnzyM3N1Zl36NChcldMq06dOjrPZ8+ejYcffhhdu3Y12TqIiIiISlKmu+e++OILDB8+HF5eXkhMTESHDh1Qq1YtnDlzBn379jV1HRW5ublYvnw5RowYYXBAzbt37yI7O1vnQURERFReZeo0ffnll1iyZAkWLFgAtVqNN998Ezt27MCECROQlZVl6joqNm7ciOvXr+Oll14yWGbWrFlwc3NTHn5+fmarDxEREVUdZboQ3MnJCSdOnEBAQAA8PT2xY8cOtGrVCqmpqejUqROuXLlijroiJCQEarUaP/30k8EyhkYE54XgpsMLwaki4IXgpsULwcnWWeJC8DIdafL29sbVq1cBAP7+/ti/fz8AIC0tzWwDXp47dw6//PILRo0aVWw5jUYDV1dXnQcRERFReZWp0/T4449j06ZNAIDhw4fj9ddfR69evTB48GCzjd8UFRUFT09PhIaGmiWfiIiIqDhluntuyZIlyleZjB8/HrVq1cLevXvx5JNP4pVXXjFpBQEgPz8fUVFRCAsLQ/XqNj9KAhEREVVGUgFs375dAEhKSkqpl83KyhIAkpWVJWPGjJExY8bolcnJyRFfX1+Ji4vTmxcXFye+vr6Sk5OjN495zGMe85jHPObZRl7Bz3tzKdPpOQC4fv06fv75ZyxfvhzfffedzsOU/vzzT3z33XeoWbMmWrVqhRYtWiA+Pr7UOdHR0Rg1ahRGjRqFpUuXKtNv3ryJuXPn4uTJk0hJSUFCQoIyLyEhASkpKTh58iTmzp2LmzdvKvOWLl3KPOYxj3nMYx7zbCjP7MrS09q0aZO4uLiISqUSNzc3cXd3Vx4eHh4m69FdvXpVAgIC5KWXXpIDBw7ImTNnZPv27XLq1CmjM7Q9z9jYWGVafHy8LFmyRHJycmT69Ok6vdglS5ZIfHy8UkarYFltGeYxj3nMYx7zmGcbeeHh4WY/0lSmTlPDhg1l4sSJcvPmTVPXR0d4eLg8+uij5cowdLjO2ocRmcc85jGPecxjnuny0tPTbfP03J9//okJEybAycnJlAe99GzatAnt27fHoEGD4OnpiTZt2ugciiuKoRHBCx62u3nzJmJiYrBy5UqsWLFCZ/mEhAS0bdsWbdu21TlUCAArVqzAypUrERMTwzzmMY95zGMe82wob+3atTC7svS0nnrqKVm9erWpO3B6NBqNaDQamTZtmhw6dEi++uorcXBwkOjoaIPLRERECAC9R3h4uOTk5OgdEix4GLDwIcGChwEL/l4wg3nMYx7zmMc85lk/LzY21nZOz/3444/K4+uvvxZ/f3+JiIiQH374QWfejz/+aLLK2dvbS3BwsM601157TTp16mRwmTt37khWVpbyuHDhggCQ9PR0mTx5skyePFnvkGB8fLyMGTNGZ4dpLVmyRMaMGaNzDlXkwY5jHvOYxzzmMY95tpFnibvnjB70aODAgXrTPvjgA71pKpUKeXl5ZTrqVZiPjw+aNWumM61p06ZYt26dwWU0Gg00Go1J1k9ERESkMFt3zASGDh2qdyH4pEmT9I4+FUfb8+TpOeYxj3nMYx7zKm+eJU7PleoLe3/99Ve8+uqr2L9/v953umVlZaFz585YvHgxHnvsMZN06A4ePIjOnTtjxowZeO655/D7779j9OjRWLJkCYYNG2ZURnZ2Ntzc3JCeng4fHx8A/4wN0aNHD6SkpGD06NFK+YSEBBw6dAgA0LZtW7Rr106Zt3TpUjRu3BgxMTF48803UaNGDeYxj3nMYx7zmGcDeUlJSZg4caJZv7C3VEea+vfvL/PmzTM4PzIyUgYOHFjOfpyuoUOH6l3U3bhxY6OX55ADzGMe85jHPOZV/jybG3Lg8OHD6NOnj8H5vXv31rtNsLwaNWqEoKAgZGRkKI/du3eXOicxMVH53VZGLmUe85jHPOYxj3mmyYuMjITZlaaHpdFoJDU11eD81NRUcXBwKHdPrqCIiAhp1apVmZfXHmmKjIyU+HjbGbmUecxjHvOYxzzmmS7PEkeaStVpeuihh2TDhg0G569bt07q169f3jrpiIiIECcnJ/Hx8ZH69evLv/71Lzl37pzB8oaGHOAX9jKPecxjHvOYV3nzbO4Le/v164f33nsPd+7c0Zt3+/ZtRERE4IknnjDJETCtjh07Ijo6Gtu2bcOiRYuQlpaGxx57DDdu3Ciy/KxZs+Dm5qY8/Pz8ADw4PWdLI5cyj3nMYx7zmMc80+aZXWl6WJmZmeLr6yt+fn4yZ84c2bhxo2zcuFFmz54tfn5+4uvrK5mZmebq4ImIyLVr18TV1VW+/vrrIucbOtIUGRmplLGFWyOZxzzmMY95zGOe6fIiIyNt6/SciMjZs2elb9++YmdnJyqVSlQqldjZ2Unfvn3lzJkz5qijnvbt28tbb71lVFlDh+uWLKlcI6Eyj3nMYx7zmFeV8ywxTpPRI4JrBQQEYMuWLbh27RpOnToFEUHDhg3h4eFh6oNgRcrJycHp06fxwgsvWGR9RERERABse0RwEZHJkydLbGyspKWlyZ49e6Rnz55Su3ZtuXz5slHLF7x7TqsiHW5kHvOYxzzmMY95tnF6rlQjglvDkCFDsGvXLly5cgV16tTBo48+ipkzZ+Lhhx82anntiOCxsbE4efIkANsYuZR5zGMe85jHPOaZLk/7eW8zI4Jb26xZswSATJw40ehlCl7TVBFvoWQe85jHPOYxj3kl59nckAPWdPDgQXz11Vdo2bJlmZaPjo62qZFLmcc85jGPecxjnmnzzM5s3TETunHjhjRs2FB27NghXbt2LdORptjYWGWa9pxo4fOmIv+cHy183rRg2YLnUJnHPOYxj3nMY57188LDw21vyAFrePHFF2XSpEkiIiV2moobEbwgax9GZB7zmMc85jGPeabLs7kv7LWGVatW4dChQ5g1a5ZR5Q2NCG6LI5cyj3nMYx7zmMc80+StXbsWZme27pgJnD9/Xjw9PeXw4cPKtLIeaQoPD5ecHNu5NZJ5zGMe85jHPOaZLs8Sg1vadKdpw4YNAkCqVaumPACISqWSatWqyf3790vM0F7TlJ6eblMjlzKPecxjHvOYxzzT5Vni7rlSjwhuST169MDRo0d1pg0fPhxNmjRBeHg4qlWrZqWaERERUZVjtu6YmZT17jmenmMe85jHPOYxr/LmWeL0nM2PCF5Yt27d0Lp1a3z++edGldeOEJqeng4fHx8AtjFyKfOYxzzmMY95zDNdXlJSEiZOnFi1RwT/8ssvpUWLFuLi4iIuLi7SqVMn2bJli9HLGzrHWVFuoWQe85jHPOYxj3kccsAo9erVw+zZs5GQkID4+Hg8/vjjGDBgAI4dO1aqnMTEROV3Wxm5lHnMYx7zmMc85pkmLzIyEmZntu6YGXl4eMjXX39tVFntkabIyEiJj7edkUuZxzzmMY95zGOe6fIscaSpQnWa7t+/LytXrhS1Wi3Hjh0rskxxI4Lb0mFE5jGPecxjHvOYxy/sNbmjR4/C2dkZGo0GY8aMwYYNG9CsWbMiyxoaETwxMdGmRi5lHvOYxzzmMY95ps0zO7N1x0zo7t27kpqaKvHx8fLWW29J7dq1S32kKTIyUiljC7dGMo95zGMe85jHPNPlRUZG8vRcUXr06CEvv/yyUWUNHa5bsqRyjYTKPOYxj3nMY15VzrPEOE0V4vRcYfn5+bh79661q0FERERVidm6Yyby1ltvSVxcnKSlpcmRI0fkrbfeEpVKJT///LNRyxe8e06rIh1uZB7zmMc85jGPebZxes7mRwQfOXIkYmJikJGRATc3N7Rs2RLh4eHo1auXUctrRwSPjY3FyZMnAdjGyKXMYx7zmMc85jHPdHnaz/sqPSL4xx9/LO3btxdnZ2epU6eODBgwQP744w+jly94TVNFvIWSecxjHvOYxzzmlZzHIQcAxMXFYfz48di/fz927NiBe/fuoXfv3jq3JhojOjrapkYuZR7zmMc85jGPeabNMzuzdcfM5PLlywKgyF5pUbQ9z9jYWGWa9pxo4fOmIv+cHy183rRg2YLnUJnHPOYxj3nMY57188LDwznkQGGpqakCQI4ePVrk/OJGBC/I2ocRmcc85jGPecxjnuny+IW9heTn52PSpEno0qULmjdvXmQZQyOC2+LIpcxjHvOYxzzmMc80eWvXroXZma07ZgZjxoyRgIAAuXDhgsEyho40hYeHS06O7dwayTzmMY95zGMe80yXZ4nBLStMp2n8+PFSr149OXPmTKmW017TlJ6eblMjlzKPecxjHvOYxzzT5Vni7rnq5j+WVT4igtdeew0bNmxAbGws6tevb+0qERERUVVktu6YiYwdO1bc3NwkNjZWMjIylMetW7eMWl7b8+TpOeYxj3nMYx7zKm+eJU7P2fyI4CqVqsjpUVFReOmll0pcXjtCaHp6Onx8fADYxsilzGMe85jHPOYxz3R5SUlJmDhxYtUeETwuLk6eeOIJ8fHxEQCyYcOGUi1v6BxnRbmFknnMYx7zmMc85nHIAaPcvHkTrVq1wsKFC8uVk5iYqPxuKyOXMo95zGMe85jHPNPkRUZGwuzM1h0zA5TjSFNkZKTEx9vOyKXMYx7zmMc85jHPdHmWONJU6TpNxY0IbkuHEZnHPOYxj3nMYx6/sNeqDI0InpiYaFMjlzKPecxjHvOYxzzT5pmd2bpjZoByHGmKjIxUytjCrZHMYx7zmMc85jHPdHmRkZE8PVeQMZ2mwgwdrluypHKNhMo85jGPecxjXlXOs8Q4TZXu9BwRERGRWZitO2YiN27ckMTERElMTBQAMm/ePElMTJRz584Ztfz169cFgMyZM0c5ZRcZGSmxsbF6v6enp0t4eLikp6fr/J6VlSWxsbESGRmp9zvzmMc85jGPecyzft6cOXMEgFy/ft1sfRKbHxE8NjYW3bt315seFhaG6OjoEpe/ePGicjE4ERERVW4XLlxAvXr1zJJt852m8srPz0d6ejpcXFwMfiWLLcjOzoafnx8uXLhgvuHfqxi2qemxTU2L7Wl6bFPTqkjtKSK4ceMGfH19YWdnnquPqpsl1YbY2dmZrcdpDq6urjb/wqxo2KamxzY1Lban6bFNTauitKebm5tZ83khOBEREZER2GkiIiIiMgI7TTZCo9EgIiICGo3G2lWpNNimpsc2NS22p+mxTU2L7amr0l8ITkRERGQKPNJEREREZAR2moiIiIiMwE4TERERkRHYaSIiIiIyAjtNZrBw4UIEBgbCwcEBHTt2xO+//67MW7JkCbp16wZXV1eoVCpcv35db/mZM2eic+fOcHJygru7u978w4cPY+jQofDz84OjoyOaNm2KyMhIM26RdZm7PQHg4MGD6NGjB9zd3eHh4YGQkBAcPnzYTFtkfYba9OrVq3jttdfQuHFjODo6wt/fHxMmTEBWVpbO8ufPn0doaCicnJzg6emJqVOn4v79+zplYmNj0bZtW2g0GjRo0MCorz2qqCzRnnfv3sU777yDgIAAaDQaBAYG4ptvvrHYNlpaedt0woQJaNeuHTQaDVq3bq2XHxsbiwEDBsDHxwc1atRA69at8f3331ti06zG3G0KANu3b0enTp3g4uKCOnXq4JlnnsHZs2fNvGWWw06Tia1evRpvvPEGIiIicOjQIbRq1QohISG4fPkyAODWrVvo06cP3n77bYMZubm5GDRoEMaOHVvk/ISEBHh6emL58uU4duwY3nnnHUybNg3//ve/zbJN1mSJ9szJyUGfPn3g7++PAwcOYPfu3XBxcUFISAju3btnlu2ypuLaND09Henp6fj000+RnJyM6OhobNu2DSNHjlSWz8vLQ2hoKHJzc7F37158++23iI6OxvTp05UyaWlpCA0NRffu3ZGUlIRJkyZh1KhR2L59uzU22aws0Z4A8NxzzyEmJgbLli1DSkoKVq5cicaNG1t6cy2ivG2qNWLECAwePLjIdezduxctW7bEunXrcOTIEQwfPhwvvvgiNm/ebO7NswpLtGlaWhoGDBiAxx9/HElJSdi+fTv+/vtvPP300+bePMsx21cBV1EdOnSQ8ePHK8/z8vLE19dXZs2apVNu586dAkCuXbtmMCsqKkrc3NyMWu+4ceOke/fuZamyTbNEex48eFAAyPnz55VpR44cEQCSmppa7m2wNca2qdaaNWtErVbLvXv3RERky5YtYmdnJ5mZmUqZRYsWiaurq9y9e1dERN58800JCgrSyRk8eLCEhISYenOszhLtuXXrVnFzc5MrV66YcUtsR3nbtKCIiAhp1aqVUevt16+fDB8+vEx1tnWWaNO1a9dK9erVJS8vT5m2adMmUalUkpubW/6NsAE80mRCubm5SEhIQM+ePZVpdnZ26NmzJ/bt22fWdWdlZaFmzZpmXYelWao9GzdujFq1amHZsmXIzc3F7du3sWzZMjRt2hSBgYEmW48tKEubZmVlwdXVFdWrP/iqyn379qFFixbw8vJSyoSEhCA7OxvHjh1TyhRch7aMud8Hlmap9ty0aRPat2+PuXPnom7dumjUqBGmTJmC27dvm3HrrMMUbVpWlfHvKGC5Nm3Xrh3s7OwQFRWFvLw8ZGVl4T//+Q969uwJe3v7cm+HLWCnyYT+/vtv5OXl6fzxAwAvLy9kZmaabb179+7F6tWr8fLLL5ttHdZgqfZ0cXFBbGwsli9fDkdHRzg7O2Pbtm3YunVruf8I25rStunff/+NDz/8UOe1lZmZWeTy2nnFlcnOzq5UH/SWas8zZ85g9+7dSE5OxoYNG/D555/jhx9+wLhx40y9SVZnijYtizVr1uDgwYMYPnx4uXJskaXatH79+vj555/x9ttvQ6PRwN3dHRcvXsSaNWvKVX9bwk5TBZecnIwBAwYgIiICvXv3tnZ1KqTbt29j5MiR6NKlC/bv3489e/agefPmCA0NrVQf8KWVnZ2N0NBQNGvWDO+//761q1Phlac98/PzoVKp8P3336NDhw7o168f5s2bh2+//ZavURO8Rnfu3Inhw4dj6dKlCAoKMl0FK6DytGlmZiZGjx6NsLAwHDx4EHFxcVCr1Xj22WchleTLRyrXv9FWVrt2bVSrVg2XLl3SmX7p0iV4e3ubfH3Hjx9Hjx498PLLL+Pdd981eb61Wao9V6xYgbNnz2Lfvn2ws7NTpnl4eODHH3/EkCFDTLYuazO2TW/cuIE+ffrAxcUFGzZs0Dm07u3trXMHo3Z57Tztz6LW4erqCkdHR5NukzVZqj19fHxQt25duLm5KWWaNm0KEcHFixfRsGFDk2+btZiiTUsjLi4O/fv3x/z58/Hiiy+Wq+62ylJtunDhQri5uWHu3LnKtOXLl8PPzw8HDhxAp06dyrchNoBHmkxIrVajXbt2iImJUabl5+cjJiYGwcHBJl3XsWPH0L17d4SFhWHmzJkmzbYVlmrPW7duwc7ODiqVSpmmfZ6fn2+y9dgCY9o0OzsbvXv3hlqtxqZNm+Dg4KCTERwcjKNHjyp3MALAjh074OrqimbNmillCq5DW8bU7wNrs1R7dunSBenp6cjJyVHKnDx5EnZ2dqhXr545N9HiTNGmxoqNjUVoaCjmzJlT6S5vKMhSbar9W1pQtWrVlPVVCta+Er2yWbVqlWg0GomOjpbjx4/Lyy+/LO7u7sqdMRkZGZKYmChLly4VALJr1y5JTEzUuSvm3LlzkpiYKDNmzBBnZ2dJTEyUxMREuXHjhoiIHD16VOrUqSPPP/+8ZGRkKI/Lly9bZZvNyRLteeLECdFoNDJ27Fg5fvy4JCcny/PPPy9ubm6Snp5ule02p+LaNCsrSzp27CgtWrSQU6dO6by+7t+/LyIi9+/fl+bNm0vv3r0lKSlJtm3bJnXq1JFp06Yp6zhz5ow4OTnJ1KlT5cSJE7Jw4UKpVq2abNu2zVqbbTaWaM8bN25IvXr15Nlnn5Vjx45JXFycNGzYUEaNGmWtzTar8rapiEhqaqokJibKK6+8Io0aNVLe99o7En/99VdxcnKSadOm6WRU1jsULdGmMTExolKpZMaMGXLy5ElJSEiQkJAQCQgIkFu3bllr002KnSYzWLBggfj7+4tarZYOHTrI/v37lXkRERECQO8RFRWllAkLCyuyzM6dO4vNCAgIsOyGWoi521NE5Oeff5YuXbqIm5ubeHh4yOOPPy779u2z4FZalqE21Q7dUNQjLS1NWf7s2bPSt29fcXR0lNq1a8vkyZP1bk3euXOntG7dWtRqtTz00EM6+6SysUR7njhxQnr27CmOjo5Sr149eeONNyrNB1FRytumXbt2LbaMob8LXbt2tfzGWoi521REZOXKldKmTRupUaOG1KlTR5588kk5ceKEhbfUfFQileTqLCIiIiIz4jVNREREREZgp4mIiIjICOw0ERERERmBnSYiIiIiI7DTRERERGQEdpqIiIiIjMBOExEREZER2GkiIiIiMgI7TURERERGYKeJiIiIyAjsNBEREREZgZ0mIiIiIiOw00RERERkBHaaiIiIiIzAThMRERGREdhpIiIiIjICO01ERERERqhu7QpYwp07d5Cbm2vtahAREZEZqdVqODg4mC2/0nea7ty5g/r16yMzM9PaVSEiIiIz8vb2Rlpamtk6TpW+05Sbm4vMzEykpl2Ai4srAEAg+N8vBX9AlOfGzdc+R6H5KDS/0GS95Y2dX1L+Pz//mWHsthVed3nbxtLzS6p/vrbNDOTll7C+/ELPlfkG95nu83y9+drl/5df6Hlx8wu/7vJLXKboOmiXy5eiy0EpV2g9haZLoZzCbVU4X395A/UrvH0lrFcKT4fu88LbXbi83vxCyxdeL0qYr7z2jFifXt0NvI4K7xNj625o3f88N64cSswx8FzvfWPcevPzS6pH4Z9ioJy2XQqv19B2lW5+UeVEr3KG6mJo24xfl+507c/8Uj5XXrHlzPnfc703ZilzjK4H/nmel4vM498iNzeXnabycnV1tVinqaydonJ3moqof1m3rbLN1/8w0S1vsFNkZKdJv1MkJczXLv+//ELPi5tfOMPoTpOBD9gSOy8Gly+0vsLTDXSaDK63cH7h7TN2vYba1MB6ytppKry8JTpNJdWlpHWVt9Nk+ufFl1MZ6DQZm1veDogpOk2F5+n98dD7aapyxnY6TNRJKvw830LrKfBc2yTmxAvBiYiIiIzAThMRERGREdhpIiIiIjICO01ERERERmCniYiIiMgI7DQRERERGYGdJiIiIiIjsNNEREREZAR2moiIiIiMwE4TERERkRHYaSIiIiIyAjtNREREREZgp4mIiIjICOw0ERERERmBnSYiIiIiI7DTRERERGQEdpqIiIiIjMBOExEREZER2GkiIiIiMgI7TURERERGYKeJiIiIyAjVrV0BS8nOzobIg98Fyi8Ff5R6vvY5Cs1HofmFJustb+z8kvL/+fnPDGO3rfC6y9s2lp5fUv3ztW1mIC+/hPXlF3quzDe4z3Sf5+vN1y7/v/xCz4ubX/h1l1/iMkXXQbtcvhRdDkq5QuspNF0K5RRuq8L5+ssbqF/h7SthvVJ4OnSfF97uwuX15hdavvB6UcJ85bVnxPr06m7gdVR4nxhbd0Pr/ue5ceVQYo6B53rvG+PWm59fUj0K/xQD5bTtUni9hrardPOLKid6lTNUF0PbZvy6dKdrf+aX8rnyii1nzv+e670xS5ljdD3wz/O8XJhbpe80iQicnZ3RsL6ftatCREREZuTs7Kz3j40pVfpOk0qlQk5ODi5cuABXV1drV8eisrOz4efnVyW3Haja21+Vtx2o2ttflbcdqNrbX5W3Hfhn+1UqldnWUek7TVqurq5V8kUEVO1tB6r29lflbQeq9vZX5W0Hqvb2V+VtNzdeCE5ERERkBHaaiIiIiIxQ6TtNGo0GERER0Gg01q6KxVXlbQeq9vZX5W0Hqvb2V+VtB6r29lflbQcss/0qMedl5kRERESVRKU/0kRERERkCuw0ERERERmBnSYiIiIiI7DTRERERGSECtlpWrhwIQIDA+Hg4ICOHTvi999/L7b82rVr0aRJEzg4OKBFixbYsmWLznwRwfTp0+Hj4wNHR0f07NkTqamp5tyEMivNti9duhSPPfYYPDw84OHhgZ49e+qVf+mll6BSqXQeffr0MfdmlFlptj86Olpv2xwcHHTKVNZ9361bN71tV6lUCA0NVcpUlH2/a9cu9O/fH76+vlCpVNi4cWOJy8TGxqJt27bQaDRo0KABoqOj9cqU9u+ItZR2+9evX49evXqhTp06cHV1RXBwMLZv365T5v3339fb902aNDHjVpRNabc9Nja2yNd9ZmamTrmKsO9Lu+1FvZ9VKhWCgoKUMhVlv8+aNQuPPPIIXFxc4OnpiYEDByIlJaXE5SzxWV/hOk2rV6/GG2+8gYiICBw6dAitWrVCSEgILl++XGT5vXv3YujQoRg5ciQSExMxcOBADBw4EMnJyUqZuXPn4osvvsDixYtx4MAB1KhRAyEhIbhz546lNssopd322NhYDB06FDt37sS+ffvg5+eH3r17488//9Qp16dPH2RkZCiPlStXWmJzSq202w88GBm34LadO3dOZ35l3ffr16/X2e7k5GRUq1YNgwYN0ilXEfb9zZs30apVKyxcuNCo8mlpaQgNDUX37t2RlJSESZMmYdSoUTodh7K8lqyltNu/a9cu9OrVC1u2bEFCQgK6d++O/v37IzExUadcUFCQzr7fvXu3OapfLqXddq2UlBSdbfP09FTmVZR9X9ptj4yM1NnmCxcuoGbNmnrv+Yqw3+Pi4jB+/Hjs378fO3bswL1799C7d2/cvHnT4DIW+6yXCqZDhw4yfvx45XleXp74+vrKrFmziiz/3HPPSWhoqM60jh07yiuvvCIiIvn5+eLt7S2ffPKJMv/69eui0Whk5cqVZtiCsivtthd2//59cXFxkW+//VaZFhYWJgMGDDB1Vc2itNsfFRUlbm5uBvOq0r6fP3++uLi4SE5OjjKtIu17LQCyYcOGYsu8+eabEhQUpDNt8ODBEhISojwvb3taizHbX5RmzZrJjBkzlOcRERHSqlUr01XMAozZ9p07dwoAuXbtmsEyFXHfl2W/b9iwQVQqlZw9e1aZVhH3u4jI5cuXBYDExcUZLGOpz/oKdaQpNzcXCQkJ6NmzpzLNzs4OPXv2xL59+4pcZt++fTrlASAkJEQpn5aWhszMTJ0ybm5u6Nixo8FMayjLthd269Yt3Lt3DzVr1tSZHhsbC09PTzRu3Bhjx47FlStXTFp3Uyjr9ufk5CAgIAB+fn4YMGAAjh07psyrSvt+2bJlGDJkCGrUqKEzvSLs+9Iq6T1vivasSPLz83Hjxg29931qaip8fX3x0EMPYdiwYTh//ryVamh6rVu3ho+PD3r16oU9e/Yo06vSvl+2bBl69uyJgIAAnekVcb9nZWUBgN5ruCBLfdZXqE7T33//jby8PHh5eelM9/Ly0jtnrZWZmVlsee3P0mRaQ1m2vbDw8HD4+vrqvGj69OmD7777DjExMZgzZw7i4uLQt29f5OXlmbT+5VWW7W/cuDG++eYb/Pjjj1i+fDny8/PRuXNnXLx4EUDV2fe///47kpOTMWrUKJ3pFWXfl5ah93x2djZu375tkvdSRfLpp58iJycHzz33nDKtY8eOiI6OxrZt27Bo0SKkpaXhsccew40bN6xY0/Lz8fHB4sWLsW7dOqxbtw5+fn7o1q0bDh06BMA0f0crgvT0dGzdulXvPV8R93t+fj4mTZqELl26oHnz5gbLWeqzvrrRJalCmz17NlatWoXY2Fidi6GHDBmi/N6iRQu0bNkSDz/8MGJjY9GjRw9rVNVkgoODERwcrDzv3LkzmjZtiq+++goffvihFWtmWcuWLUOLFi3QoUMHnemVed/TAytWrMCMGTPw448/6lzX07dvX+X3li1bomPHjggICMCaNWswcuRIa1TVJBo3bozGjRsrzzt37ozTp09j/vz5+M9//mPFmlnWt99+C3d3dwwcOFBnekXc7+PHj0dycrLNXHtVoY401a5dG9WqVcOlS5d0pl+6dAne3t5FLuPt7V1see3P0mRaQ1m2XevTTz/F7Nmz8fPPP6Nly5bFln3ooYdQu3ZtnDp1qtx1NqXybL+Wvb092rRpo2xbVdj3N2/exKpVq4z6g2ir+760DL3nXV1d4ejoaJLXUkWwatUqjBo1CmvWrNE7bVGYu7s7GjVqVOH3fVE6dOigbFdV2Pcigm+++QYvvPAC1Gp1sWVtfb+/+uqr2Lx5M3bu3Il69eoVW9ZSn/UVqtOkVqvRrl07xMTEKNPy8/MRExOjc0ShoODgYJ3yALBjxw6lfP369eHt7a1TJjs7GwcOHDCYaQ1l2Xbgwd0CH374IbZt24b27duXuJ6LFy/iypUr8PHxMUm9TaWs219QXl4ejh49qmxbZd/3wINbcO/evYvnn3++xPXY6r4vrZLe86Z4Ldm6lStXYvjw4Vi5cqXOMBOG5OTk4PTp0xV+3xclKSlJ2a6qsO/j4uJw6tQpo/5RstX9LiJ49dVXsWHDBvz666+oX79+ictY7LO+VJew24BVq1aJRqOR6OhoOX78uLz88svi7u4umZmZIiLywgsvyFtvvaWU37Nnj1SvXl0+/fRTOXHihERERIi9vb0cPXpUKTN79mxxd3eXH3/8UY4cOSIDBgyQ+vXry+3bty2+fcUp7bbPnj1b1Gq1/PDDD5KRkaE8bty4ISIiN27ckClTpsi+ffskLS1NfvnlF2nbtq00bNhQ7ty5Y5VtLE5pt3/GjBmyfft2OX36tCQkJMiQIUPEwcFBjh07ppSprPte69FHH5XBgwfrTa9I+/7GjRuSmJgoiYmJAkDmzZsniYmJcu7cOREReeutt+SFF15Qyp85c0acnJxk6tSpcuLECVm4cKFUq1ZNtm3bppQpqT1tSWm3//vvv5fq1avLwoULdd73169fV8pMnjxZYmNjJS0tTfbs2SM9e/aU2rVry+XLly2+fcUp7bbPnz9fNm7cKKmpqXL06FGZOHGi2NnZyS+//KKUqSj7vrTbrvX8889Lx44di8ysKPt97Nix4ubmJrGxsTqv4Vu3billrPVZX+E6TSIiCxYsEH9/f1Gr1dKhQwfZv3+/Mq9r164SFhamU37NmjXSqFEjUavVEhQUJP/973915ufn58t7770nXl5eotFopEePHpKSkmKJTSm10mx7QECAANB7REREiIjIrVu3pHfv3lKnTh2xt7eXgIAAGT16tM398SioNNs/adIkpayXl5f069dPDh06pJNXWfe9iMgff/whAOTnn3/Wy6pI+157G3nhh3Z7w8LCpGvXrnrLtG7dWtRqtTz00EMSFRWll1tce9qS0m5/165diy0v8mAIBh8fH1Gr1VK3bl0ZPHiwnDp1yrIbZoTSbvucOXPk4YcfFgcHB6lZs6Z069ZNfv31V73cirDvy/K6v379ujg6OsqSJUuKzKwo+72o7Qag8z621me96n8VJCIiIqJiVKhrmoiIiIishZ0mIiIiIiOw00RERERkBHaaiIiIiIzAThMRERGREdhpIiIiIjICO01ERERERmCniaiKO3v2LFQqFZKSkipUdllER0fD3d3dZnKMkZKSAm9vb5v5Jvrc3FwEBgYiPj7e2lUhsjh2mogs7K+//sLYsWPh7+8PjUYDb29vhISEYM+ePUoZlUqFjRs3Wq+SFtStWzeoVCqoVCpoNBrUrVsX/fv3x/r1602+rsGDB+PkyZOlWiYwMBCff/55uXPKatq0aXjttdfg4uKiTMvLy8P8+fPRokULODg4wMPDA3379tV5DZVHYGCgsk+0D+0XpqrVakyZMgXh4eEmWRdRRcJOE5GFPfPMM0hMTMS3336LkydPYtOmTejWrRuuXLli7aqVWW5ubrmWHz16NDIyMnD69GmsW7cOzZo1w5AhQ/Dyyy+bqIYPODo6wtPT02ZySnL+/Hls3rwZL730kjJNRDBkyBB88MEHmDhxIk6cOIHY2Fj4+fmhW7duJutsf/DBB8jIyFAeiYmJyrxhw4Zh9+7dOHbsmEnWRVRhlOmLYYioTK5duyYAJDY21mCZwt8ZGBAQICIip06dkieffFI8PT2lRo0a0r59e9mxY4fesjNnzpThw4eLs7Oz+Pn5yVdffaVT5sCBA9K6dWvRaDTSrl07Wb9+vQCQxMREERG5f/++jBgxQgIDA8XBwUEaNWokn3/+uU5GWFiYDBgwQD766CPx8fGRwMBAo7KL0rVrV5k4caLe9G+++UYA6Gzj+fPnZdCgQeLm5iYeHh7y5JNPSlpamoiIbN++XTQajVy7dk0nZ8KECdK9e3cREYmKihI3NzdlXkltWtT3uBWVIyLy5ZdfykMPPST29vbSqFEj+e6773TmA5ClS5fKwIEDxdHRURo0aCA//vijwXYREfnkk0+kffv2OtNWrVolAGTTpk165Z9++mmpVauW5OTkiIhIRESEtGrVSpYtWyZ+fn5So0YNGTt2rNy/f1/mzJkjXl5eUqdOHfnoo490cgICAmT+/PnF1q179+7y7rvvFluGqLLhkSYiC3J2doazszM2btyIu3fvFlnm4MGDAICoqChkZGQoz3NyctCvXz/ExMQgMTERffr0Qf/+/XH+/Hmd5T/77DO0b98eiYmJGDduHMaOHYuUlBQl44knnkCzZs2QkJCA999/H1OmTNFZPj8/H/Xq1cPatWtx/PhxTJ8+HW+//TbWrFmjUy4mJgYpKSnYsWMHNm/ebFR2aYSFhcHDw0M5TXfv3j2EhITAxcUFv/32G/bs2QNnZ2f06dMHubm56NGjB9zd3bFu3TolIy8vD6tXr8awYcOKXEdJbbp+/XrUq1dP56hLUTZs2ICJEydi8uTJSE5OxiuvvILhw4dj586dOuVmzJiB5557DkeOHEG/fv0wbNgwXL161WAb/Pbbb2jfvr3OtBUrVqBRo0bo37+/XvnJkyfjypUr2LFjhzLt9OnT2Lp1K7Zt24aVK1di2bJlCA0NxcWLFxEXF4c5c+bg3XffxYEDBwzWoygdOnTAb7/9VqpliCo8a/faiKqaH374QTw8PMTBwUE6d+4s06ZNk8OHD+uUASAbNmwoMSsoKEgWLFigPA8ICJDnn39eeZ6fny+enp6yaNEiERH56quvpFatWnL79m2lzKJFi0o8GjR+/Hh55plnlOdhYWHi5eUld+/eVaaVNdvQkSYRkY4dO0rfvn1FROQ///mPNG7cWPLz85X5d+/eFUdHR9m+fbuIiEycOFEef/xxZX7ho09FHSEqrKg2LXzUpXBO586dZfTo0TplBg0aJP369VOeA9A5MpOTkyMAZOvWrQbr0qpVK/nggw90pjVp0kQGDBhQZPmrV68KAJkzZ46IPDjS5OTkJNnZ2UqZkJAQCQwMlLy8PGVa48aNZdasWTrbrFarpUaNGsojMjJSZ12RkZHKEUaiqoJHmogs7JlnnkF6ejo2bdqEPn36IDY2Fm3btkV0dHSxy+Xk5GDKlClo2rQp3N3d4ezsjBMnTugdaWrZsqXyu0qlgre3Ny5fvgwAOHHiBFq2bAkHBwelTHBwsN66Fi5ciHbt2qFOnTpwdnbGkiVL9NbTokULqNVq5bmx2aUhIlCpVACAw4cP49SpU3BxcVGO2NWsWRN37tzB6dOnATy41iY2Nhbp6ekAgO+//x6hoaEG73Qztk1LcuLECXTp0kVnWpcuXXDixAmdaQX3TY0aNeDq6qrsm6Lcvn1bpz21RMTougUGBupcRO7l5YVmzZrBzs5OZ1rhekydOhVJSUnK48UXX9SZ7+joiFu3bhldD6LKoLq1K0BUFTk4OKBXr17o1asX3nvvPYwaNQoRERE6F/wWNmXKFOzYsQOffvopGjRoAEdHRzz77LN6F2Hb29vrPFepVMjPzze6bqtWrcKUKVPw2WefITg4GC4uLvjkk0/0Tt/UqFHD6MyyyMvLQ2pqKh555BEADzo47dq1w/fff69Xtk6dOgCARx55BA8//DBWrVqFsWPHYsOGDcV2Ro1tU1Mp7b6pXbs2rl27pjOtUaNGep0xLe30Ro0aFbtOY+pRu3ZtNGjQwGDdrl69qrQ7UVXBI01ENqBZs2a4efOm8tze3h55eXk6Zfbs2YOXXnoJTz31FFq0aAFvb2+cPXu2VOtp2rQpjhw5gjt37ijT9u/fr7eezp07Y9y4cWjTpg0aNGigHMkpb3ZpfPvtt7h27RqeeeYZAEDbtm2RmpoKT09PNGjQQOfh5uamLDds2DB8//33+Omnn2BnZ4fQ0FCD6zCmTdVqtd6+KKxp06Z6t/vv2bMHzZo1K+VW62rTpg2OHz+uM23IkCFITU3FTz/9pFf+s88+Q61atdCrV69yrdcYycnJaNOmjdnXQ2RL2GkisqArV67g8ccfx/Lly3HkyBGkpaVh7dq1mDt3LgYMGKCUCwwMRExMDDIzM5UjDQ0bNsT69euRlJSEw4cP41//+lepjiABwL/+9S+oVCqMHj0ax48fx5YtW/Dpp5/qlGnYsCHi4+Oxfft2nDx5Eu+9955yMXp5sw25desWMjMzcfHiRezfvx/h4eEYM2YMxo4di+7duwN40BmqXbs2BgwYgN9++w1paWmIjY3FhAkTcPHiRSVr2LBhOHToEGbOnIlnn30WGo3G4HqNadPAwEDs2rULf/75J/7+++8ic6ZOnYro6GgsWrQIqampmDdvHtavX1+uC+EBICQkBPv27dPptA0ZMgRPPfUUwsLCsGzZMpw9exZHjhzBK6+8gk2bNuHrr782+1FA4MFF6r179zb7eohsCTtNRBbk7OyMjh07Yv78+fi///s/NG/eHO+99x5Gjx6Nf//730q5zz77DDt27ICfn5/y3/y8efPg4eGBzp07o3///ggJCUHbtm1Lvf6ffvoJR48eRZs2bfDOO+9gzpw5OmVeeeUVPP300xg8eDA6duyIK1euYNy4cSbJNmTp0qXw8fHBww8/jKeffhrHjx/H6tWr8eWXXyplnJycsGvXLvj7++Ppp59G06ZNMXLkSNy5cweurq5KuQYNGqBDhw44cuSIwbvmtIxp0w8++ABnz57Fww8/bPB01MCBAxEZGYlPP/0UQUFB+OqrrxAVFYVu3boZtf2G9O3bF9WrV8cvv/yiTFOpVFizZg3efvttzJ8/H40bN8Zjjz2Gc+fOITY2FgMHDizXOo2xb98+ZGVl4dlnnzX7uohsiUpKc0UhERFZ1MKFC7Fp0yZs377d2lVRDB48GK1atcLbb79t7aoQWRQvBCcismGvvPIKrl+/jhs3bujcBWctubm5aNGiBV5//XVrV4XI4nikiYiIiMgIvKaJiIiIyAjsNBEREREZgZ0mIiIiIiOw00RERERkBHaaiIiIiIzAThMRERGREdhpIiIiIjICO01ERERERmCniYiIiMgI7DQRERERGYGdJiIiIiIjsNNEREREZAR2moiIiIiMwE4TERERkRHYaSIiIiIyAjtNREREREZgp4mIiIjICOw0ERERERmBnSYiIiIiI7DTRERERGQEdprIat5//320bt263DnR0dHo1q1buXOoZLGxsVCpVLh+/TqAB23v7u5u1TqZwpIlS+Dn5wc7Ozt8/vnn1q4OEdkodppIUfgDsSq4ffs2atasidq1a+Pu3bt68wMDA6FSqbBq1Sq9eUFBQVCpVIiOjlamHT58GE8++SQ8PT3h4OCAwMBADB48GJcvXwZQfBsHBgYa9YFdUp0tafDgwTh58qRV61Be2dnZePXVVxEeHo4///wTL7/8srWrhPfffx8qlQp9+vTRm/fJJ59ApVKV6h+Fs2fPQqVSISkpyXSVLEa3bt2gUqmUh5eXFwYNGoRz585ZZP0AsHDhQgQGBsLBwQEdO3bE77//rjN/yZIl6NatG1xdXYv9u7d582Z07doVLi4ucHJywiOPPKLznjfGSy+9hIEDBxpV9vz58wgNDYWTkxM8PT0xdepU3L9/X5m/fv169OrVC3Xq1IGrqyuCg4Oxfft2vZwLFy5gxIgR8PX1hVqtRkBAACZOnIgrV64YXW9jPxNiY2MxYMAA+Pj4oEaNGmjdujW+//57vXJr165FkyZN4ODggBYtWmDLli3KvHv37iE8PBwtWrRAjRo14OvrixdffBHp6ek6Gdq/yQUfs2fPNnqbyoudJqrS1q1bh6CgIDRp0gQbN24ssoyfnx+ioqJ0pu3fvx+ZmZmoUaOGMu2vv/5Cjx49ULNmTWzfvh0nTpxAVFQUfH19cfPmTYvWuTi5ubkmq4ujoyM8PT1NlmcN58+fx7179xAaGgofHx84OTnplTFlmxnLx8cHO3fuxMWLF3Wmf/PNN/D397d4fUpr9OjRyMjIQHp6On788UdcuHABzz//vEXWvXr1arzxxhuIiIjAoUOH0KpVK4SEhCj/vADArVu30KdPH7z99tsGcxYsWIABAwagS5cuOHDgAI4cOYIhQ4ZgzJgxmDJlisnrnZeXh9DQUOTm5mLv3r349ttvER0djenTpytldu3ahV69emHLli1ISEhA9+7d0b9/fyQmJiplzpw5g/bt2yM1NRUrV67EqVOnsHjxYsTExCA4OBhXr141ab337t2Lli1bYt26dThy5AiGDx+OF198EZs3b9YpM3ToUIwcORKJiYkYOHAgBg4ciOTkZAAP9sehQ4fw3nvv4dChQ1i/fj1SUlLw5JNP6q3vgw8+QEZGhvJ47bXXTLo9xZIqYuvWrdKlSxdxc3OTmjVrSmhoqJw6dUqZn5aWJgBk9erV8uijj4qDg4O0b99eUlJS5Pfff5d27dpJjRo1pE+fPnL58mVluZ07d8ojjzwiTk5O4ubmJp07d5azZ8+KiEhYWJgMGDBApx4TJ06Url27Gl2vouzcuVMAyLZt26R169bi4OAg3bt3l0uXLsmWLVukSZMm4uLiIkOHDpWbN28qy+Xl5cnHH38sgYGB4uDgIC1btpS1a9fqbH/BR1hYmIiI3LlzR1577TWpU6eOaDQa6dKli/z+++969dm8ebO0aNFCNBqNdOzYUY4ePVrsdkREREirVq1k8eLFUq9ePXF0dJRBgwbJ9evXi12usKioKJ02LY1u3brJ4sWLZdGiRdKrVy+9+QEBAfLWW2+JRqOR8+fPK9NHjx4tr732mri5uUlUVJSIiGzYsEGqV68u9+7dM7g+bVtdu3atyHXNnz+/3HUuTPs6/Oijj8THx0cCAwNFROS7776Tdu3aibOzs3h5ecnQoUPl0qVLOsv+97//lYYNG4qDg4N069ZNoqKidOofFRUlbm5uSvlTp07Jk08+KZ6enlKjRg1p37697NixQ287Z86cKcOHDxdnZ2fx8/OTr776SqfMhQsXZMiQIeLh4SFOTk7Srl072b9/vzJ/48aN0qZNG9FoNFK/fn15//33lXbPz8+XiIgI8fPzE7VaLT4+PvLaa68V2Tba7Sn4SEtLU16bS5culcDAQFGpVCIicu7cOXnyySelRo0a4uLiIoMGDZLMzEwlT7vcsmXLxM/PT2rUqCFjx46V+/fvy5w5c8TLy0vq1KkjH330UbH7TJvzxBNP6JTds2eP1K5dW8aOHav3ml+6dKk0adJENBqNNG7cWBYuXKjMK7yN2mXz8vJkxowZUrduXVGr1dKqVSvZunWrspz278LKlSslODhYNBqNBAUFSWxsbLH179q1q0ycOFFn2n/+8x9xcnIqdjlT6dChg4wfP155npeXJ76+vjJr1iy9sobek+fPnxd7e3t544039Jb54osvBIDOazI5OVlCQ0PFxcVFnJ2d5dFHH5VTp05JRESEXvvv3LmzyHpv2bJF7OzsdF5TixYtEldXV7l7967B7W3WrJnMmDFDed6nTx+pV6+e3Lp1S6dcRkaGODk5yZgxY5Rpd+7ckTfffFPq1asnarVaHn74Yfn666+L/UwwRr9+/WT48OHK8+eee05CQ0N1ynTs2FFeeeUVgxm///67AJBz584p04z9O2kuVabT9MMPP8i6deskNTVVEhMTpX///tKiRQvJy8sTkX/+ODRp0kS2bdsmx48fl06dOkm7du2kW7dusnv3bjl06JA0aNBAecHdu3dP3NzcZMqUKXLq1Ck5fvy4REdHKzvYmE5TSfUqivZN3qlTJ516de3aVXr37i2HDh2SXbt2Sa1atWT27NnKch999JGyfadPn5aoqCjRaDQSGxsr9+/fl3Xr1gkASUlJkYyMDKXzMmHCBPH19ZUtW7bIsWPHJCwsTDw8POTKlSs69WnatKn8/PPPcuTIEXniiSckMDBQcnNzDW5HRESE1KhRQx5//HFJTEyUuLg4adCggfzrX/8yfsdK2TtNp06dEo1GI1evXpUrV66Ig4OD0uHV0r5Bn3zySfnwww9FROTmzZvi6uoqiYmJOp2mffv2CQBZs2aN5OfnF7nO8naajKlzYWFhYeLs7CwvvPCCJCcnS3JysoiILFu2TLZs2SKnT5+Wffv2SXBwsPTt21dZ7vz586LRaOSNN96QP/74Q5YvXy5eXl7FdpqSkpJk8eLFcvToUTl58qS8++674uDgoPdHr2bNmrJw4UJJTU2VWbNmiZ2dnfzxxx8iInLjxg156KGH5LHHHpPffvtNUlNTZfXq1bJ3714REdm1a5e4urpKdHS0nD59Wn7++WcJDAyU999/X0RE1q5dK66urrJlyxY5d+6cHDhwQJYsWVJk29y6dUt++eUXASC///67ZGRkyP3795XXZp8+feTQoUNy+PBhycvLk9atW8ujjz4q8fHxsn//fmnXrp3Oay8iIkKcnZ3l2WeflWPHjsmmTZtErVZLSEiIvPbaa/LHH3/IN998o/eBW5i207R+/Xpp0KCBMn3kyJEyceJEvb8jy5cvFx8fH1m3bp2cOXNG1q1bJzVr1pTo6GgR+efD55dffpGMjAzlvTtv3jxxdXWVlStXyh9//CFvvvmm2Nvby8mTJ0Xkn7+L9erVkx9++EGOHz8uo0aNEhcXF/n7778N1r9wp+nKlSvSv39/6d69u8FlTOXu3btSrVo12bBhg870F198UZ588km98obek/PmzRMAkp6eXuQ6nJ2dlW28ePGi1KxZU55++mk5ePCgpKSkyDfffCN//PGH3LhxQ5577jnp06ePZGRkSEZGhsEO0HvvvSetWrXSmXbmzBkBIIcOHSpymby8PPHz85MFCxaIyIO2VqlU8vHHHxdZfvTo0eLh4aH8jXruuefEz89P1q9fL6dPn5ZffvlFVq1aVexngjG6dOkikydPVp77+fnp/X2bPn26tGzZ0mDGjh07RKVSSVZWljItICBAvLy8pGbNmtK6dWuZO3dusf+omlqV6TQV9tdffwkA5WiI9o/D119/rZRZuXKlAJCYmBhl2qxZs6Rx48Yi8uDFCcDgf13GdJpKqldRtG/yX375RadeAOT06dPKtFdeeUVCQkJE5MF/E05OTsoHj9bIkSNl6NChOrkF/3jk5OSIvb29fP/998q03Nxc8fX1lblz5+ost2rVKqXMlStXxNHRUVavXm1wOyIiIqRatWpy8eJFZdrWrVvFzs5OMjIyDC5XWFk7TW+//bYMHDhQeT5gwACJiIjQKaPtyGzcuFEefvhhyc/Pl2+//VbatGkjIqLTadJmVq9eXWrWrCl9+vSRuXPn6vzXWN5OkzF1LiwsLEy8vLyK/U9VROTgwYMCQG7cuCEiItOmTZNmzZrplAkPDy+201SUoKAg5Q+6yIPtfP7555Xn+fn54unpKYsWLRIRka+++kpcXFyUD/bCevToofeB8J///Ed8fHxEROSzzz6TRo0aFdthLygxMVE5wqQVEREh9vb2OkeVf/75Z6lWrZrOEcdjx44pHS7tck5OTpKdna2UCQkJkcDAQJ1/hBo3blzkUY+C62/VqpXk5uaKp6enxMXFSU5Ojri4uMjhw4f1/o48/PDDsmLFCp2MDz/8UIKDg0Xkn79viYmJOmV8fX1l5syZOtMeeeQRGTdunM5yBf/5unfvntSrV0/mzJljsP5du3YVe3t7qVGjhjg5OQkAadSokU4bm8uff/4pAPT+1k2dOlU6dOigV97Qe3LMmDHFvrZbtmyp/JMxbdo0qV+/vsHXXFGfBUUZPXq09O7dW2fazZs3BYBs2bKlyGXmzJkjHh4eylHi/fv3CwC9TqOWtjN46dIlSUlJEQB6R4O1ivt7VZzVq1eLWq1W/kETEbG3t9d7jS5cuFA8PT2LzLh9+7a0bdtW75/ozz77THbu3CmHDx+WRYsWibu7u7z++uulql95VJlrmlJTUzF06FA89NBDcHV1RWBgIIAH1zMU1LJlS+V3Ly8vAECLFi10pmnPi9esWRMvvfQSQkJC0L9/f0RGRiIjI8Ok9erbty+cnZ3h7OyMoKCgYuvq5OSEhx56qMi6njp1Crdu3UKvXr2UPGdnZ3z33Xc4ffq0wfqdPn0a9+7dQ5cuXZRp9vb26NChA06cOKFTNjg4WPm9Zs2aaNy4sVKm4DrHjBmjlPP390fdunV1MvLz85GSklJ8w5VTXl4evv32W51rLJ5//nlER0cjPz9fr3xoaChycnKwa9cufPPNNxgxYkSRuTNnzkRmZiYWL16MoKAgLF68GE2aNMHRo0dLVb+i9ntp61xQixYtoFardaYlJCSgf//+8Pf3h4uLC7p27Qrgn9feiRMn0LFjR51lCu7jouTk5GDKlClo2rQp3N3d4ezsjBMnThT7PlOpVPD29lZeq0lJSWjTpg1q1qxZ5DoOHz6MDz74QOc1pb1+5tatWxg0aBBu376Nhx56CKNHj8aGDRt0LqQ1VkBAAOrUqaM8P3HiBPz8/ODn56dMa9asGdzd3XXeC4GBgXBxcVGee3l5oVmzZrCzs9OZVvD6GkPs7e3x/PPPIyoqCmvXrkWjRo102g4Abt68idOnT2PkyJE6bfLRRx8V+97Ozs5Genq6znsbALp06VLse7t69epo3769UiYoKEhZZ9++fZVyw4YNQ1JSEg4fPozdu3ejQYMG6N27N27cuFHidlc0SUlJeOyxx2Bvb2/0MsX9bTfWihUrMGPGDKxZs0bv2kIRKXH5pKQkVKtWTXnvm8LOnTsxfPhwLF26tMzbde/ePTz33HMQESxatEhn3htvvIFu3bqhZcuWGDNmDD777DMsWLDAYjfFVLfIWmxA//79ERAQgKVLl8LX1xf5+flo3ry53gWeBV/0KpWqyGkFP6CioqIwYcIEbNu2DatXr8a7776LHTt2oFOnTrCzs9N74d67d69U9fr6669x+/ZtvXoUVa/C8wvWNScnBwDw3//+V6eTAgAajabINjOlgnftuLq6mn19Jdm+fTv+/PNPDB48WGd6Xl4eYmJi0KtXL53p1atXxwsvvICIiAgcOHAAGzZsMJhdq1YtDBo0CIMGDcLHH3+MNm3a4NNPP8W3336rbHtWVpberfrXr1+Hm5sbgKL3e2nrXFDBC9aBBx+0ISEhCAkJwffff486derg/PnzCAkJKddFz1OmTMGOHTvw6aefokGDBnB0dMSzzz5b7PsM0H2tOjo6FruOnJwczJgxA08//bTePAcHB/j5+SElJQW//PILduzYgXHjxuGTTz5BXFxcqT7UCreZsYratuK2tyQjRoxAx44dkZycXGRnXfveXrp0qV4nt1q1aqWpepls2bJF+btWcN+5ubmhQYMGAIAGDRpg2bJl8PHxwerVqzFq1Ciz1ad27dqoVq0aLl26pDP90qVL8Pb2NjqnUaNGyMrKQnp6Onx9fXXm5ebm4vTp0+jevTuAkl+zRSnqPe7t7a13l592OwrXfdWqVRg1ahTWrl2Lnj17KtMbNGgAlUqFEydO4KmnntJb74kTJ+Dh4YE6deqUqd7FiYuLQ//+/TF//ny8+OKLOvO8vb2N2ifaDtO5c+fw66+/lvh50bFjR9y/fx9nz55F48aNTbMhxagSR5quXLmClJQUvPvuu+jRoweaNm2Ka9eumSy/TZs2mDZtGvbu3YvmzZtjxYoVAIA6deroHXkq2Hkwpl5169ZFgwYN0KBBAwQEBJS5js2aNYNGo8H58+eVPO1D+5+z9khEXl6estzDDz8MtVqNPXv2KNPu3buHgwcPolmzZjrr2L9/v/L7tWvXcPLkSTRt2hQAdNZX8D+i8+fP69xSun//ftjZ2Zn9xb9s2TIMGTIESUlJOo8hQ4Zg2bJlRS4zYsQIxMXFYcCAAfDw8DBqPWq1Gg8//LBy91zDhg1hZ2eHhIQEnXJnzpxBVlYWGjVqBKDo/V6WOhvyxx9/4MqVK5g9ezYee+wxNGnSRO/IR9OmTfX+gBfcx0XZs2cPXnrpJTz11FNo0aIFvL29cfbs2VLVrWXLlkhKSjJ4h0/btm2RkpKi9zpu0KCBcjTH0dER/fv3xxdffIHY2Fjs27ev1Ef7CmvatCkuXLiACxcuKNOOHz+O69ev670XTCkoKAhBQUFITk7Gv/71L735Xl5e8PX1xZkzZ/Tao379+gCKfm+7urrC19dX570NPNiHxb2379+/j4SEBOW9HRAQoKyv8D9kBWk7cNqOgrmo1Wq0a9cOMTExyrT8/HzlzjFjPfPMM7C3t8dnn32mN2/x4sW4efMmhg4dCuDBa/a3337T+6e4YJ0Ktj1Q9Hs8ODgYR48e1Xkv7tixA66urjr7ZOXKlRg+fDhWrlyJ0NBQndxatWqhV69e+PLLL/XaOjMzE99//z0GDx4MlUqFFi1aID8/H3FxcQbrDUCv7kWJjY1FaGgo5syZU+SwHcHBwTr7RLttBfeJtsOUmpqKX375BbVq1SpxvUlJSbCzs7PYXbxV4kiTh4cHatWqhSVLlsDHxwfnz5/HW2+9Ve7ctLQ0LFmyBE8++SR8fX2RkpKC1NRUpYf9+OOP45NPPsF3332H4OBgLF++HMnJyWjTpo1Z61UUFxcXTJkyBa+//jry8/Px6KOPIisrC3v27IGrqyvCwsIQEBAAlUqFzZs3o1+/fnB0dISzszPGjh2LqVOnombNmvD398fcuXNx69YtjBw5UmcdH3zwAWrVqgUvLy+88847qF27doljkzg4OCAsLAyffvopsrOzMWHCBDz33HOl+o+wtP766y/89NNP2LRpE5o3b64z78UXX8RTTz2Fq1ev6p0eatq0Kf7+++8ib0kHHoznsmrVKgwZMgSNGjWCiOCnn37Cli1blCELXFxcMGrUKEyePBnVq1dHixYtcOHCBYSHh6NTp07o3LmzSetsiL+/P9RqNRYsWIAxY8YgOTkZH374oU4Z7aHvqVOnYtSoUUhISChxfJqGDRti/fr16N+/P1QqFd577z2jj6hoDR06FB9//DEGDhyIWbNmwcfHB4mJifD19UVwcDCmT5+OJ554Av7+/nj22WdhZ2eHw4cPIzk5GR999BGio6ORl5eHjh07wsnJCcuXL4ejo2O5/ukAgJ49e6JFixYYNmwYPv/8c9y/fx/jxo1D165d0b59+3Jll+TXX3/FvXv3DA4kOmPGDEyYMAFubm7o06cP7t69i/j4eFy7dg1vvPEGPD094ejoiG3btqFevXpwcHCAm5sbpk6dioiICDz88MNo3bo1oqKikJSUpDfGzsKFC9GwYUM0bdoU8+fPx7Vr1wyeota6desWMjMzATw4ovDhhx/CwcEBvXv3NkmbFOeNN95AWFgY2rdvjw4dOuDzzz/HzZs3MXz4cKVMZmYmMjMzcerUKQDA0aNH4eLiAn9/f52/dZMnT4aDgwNeeOEF2Nvb48cff8Tbb7+NyZMnK0f2Xn31VSxYsABDhgzBtGnT4Obmhv3796NDhw5o3LgxAgMDsX37dqSkpKBWrVpwc3Mr8qhn79690axZM7zwwguYO3cuMjMz8e6772L8+PHKGYEVK1YgLCwMkZGR6Nixo9LGjo6OypHqf//73+jcuTNCQkLw0UcfoX79+jh27BimTp2KunXrYubMmQAenEoOCwvDiBEj8MUXX6BVq1Y4d+4cLl++jOeee87gZ0JhO3fuxBNPPIGJEyfimWeeUeqkVquVv0kTJ05E165d8dlnnyE0NBSrVq1CfHw8lixZAuBBh+nZZ5/FoUOHsHnzZuTl5Sk5NWvWhFqtxr59+3DgwAF0794dLi4u2LdvH15//XU8//zzRv8jW24Wu3rKynbs2CFNmzYVjUYjLVu2lNjYWJ2L5Yq6ULKoi+AKXviamZkpAwcOFB8fH1Gr1RIQECDTp0/XueBz+vTp4uXlJW5ubvL666/Lq6++qnMBZ0n1KkpJ9dLSXkyqlZ+fL59//rk0btxY7O3tpU6dOhISEiJxcXFKmQ8++EC8vb1FpVIpt5fevn1bXnvtNaldu3axQw789NNPEhQUJGq1Wjp06CCHDx82uA0F6/fll1+Kr6+vODg4yLPPPitXr14tdrnCSnsh+Keffiru7u5FXrR59+5dcXd3l8jISBEp+eLsgheCnz59WkaPHi2NGjUSR0dHcXd3l0ceeUTnQnGRB+0ZEREhTZo0EUdHR6lfv768/PLL8tdff5mkzoUZugh1xYoVEhgYKBqNRoKDg2XTpk1674GffvpJGjRoIBqNRh577DHlzi9DF4KnpaVJ9+7dxdHRUfz8/OTf//633p1URbVpq1atdC5oP3v2rDzzzDPi6uoqTk5O0r59ezlw4IAyf9u2bdK5c2dxdHQUV1dX6dChg3KH3IYNG6Rjx47i6uoqNWrUkE6dOuncNFGYoQvBC9/FJGL8kAMFFdX+Rd2SX5Ch9WsVdUPJ999/L61btxa1Wi0eHh7yf//3f7J+/Xpl/tKlS8XPz0/s7Ox0hhx4//33pW7dumJvb29wyIEVK1ZIhw4dRK1WS7NmzeTXX381WDft9qHAreoeHh7StWvXEpczpQULFoi/v7/y96jw3YpFDQUAQO/9+uOPP8pjjz0mNWrUEAcHB2nXrp188803eus7fPiw9O7dW5ycnMTFxUUee+wx5cacy5cvS69evcTZ2bnYIQdEHrz2+/btK46OjlK7dm2ZPHmyzt1hhdtW+yg8HMDZs2eVm0Ds7e3Fz89PXnvtNb27Hm/fvi2vv/668jnWoEEDne0r6jOhsLCwsCLrVPg1umbNGmnUqJGo1WoJCgqS//73v8q8ooY40D607ZWQkCAdO3YUNzc3cXBwkKZNm8rHH38sd+7cMdiepqYSMeJqMaJixMbGonv37rh27ZpVvlIjOjoa0dHRiI2Ntfi6iSqzs2fPon79+khMTDTJVx4RVXRV4pomIiIiovJip4mIiIjICDw9RxWe9i6yl156ydpVISKiSoydJiIiIiIj8PQcERERkRHYaSIiIiIyQqUf3DI/Px/p6elwcXFRvhaFiIiIKhcRwY0bN+Dr66vzXY+mVOk7Tenp6TpfsElERESV14ULF1CvXj2zZFu107Rr1y588sknSEhIQEZGBjZs2KDztRsvvfQSvv32W51lQkJCsG3bNqPXof228ZSUFCxYsAAA8Pbbb+t8GWdiYiK+++47tGrVSu8OrOjoaBw+fBgvvvii8vUnwIMvPP3444+ZxzzmMY95zGOeDeRlZ2fDz89P+dw3C4uNPV6ELVu2yDvvvCPr168v8qtDwsLCpE+fPpKRkaE8SvsVG1lZWQJAwsPDJScnR3JycmT69OmSk5MjIiLx8fHK1y8U/F1EZMmSJRIfH6/3e8EM5jGPecxjHvOYZ/087deQZWVlibnYzJADKpWqyCNN169fx8aNG8ucm52dDTc3N6Snp8PHxwfAg17q3Llz0aNHD6SkpGD06NFK+YSEBBw6dAjAg29Tb9eunTJv6dKlaNy4MWJiYvDmm28qvVvmMY95zGMe85hn3bykpCRMnDgRWVlZcHV1hVmYrTtWSjBwpMnNzU3q1KkjjRo1kjFjxuh92WBhd+7ckaysLOVx4cKFInuecXFx4uvrq/RQCxozZoyMGTNGb3pOTo74+vrqfMEt85jHPOYxj3nMs35eenq62Y802fSQA3369MF3332HmJgYzJkzB3Fxcejbty/y8vIMLjNr1iy4ubkpD+1F4ImJiUqZhIQEpKSk4OTJk5g7dy5u3rypzFu6dClGjRqFUaNGYenSpcp0bW/25MmTSElJQUJCAvOYxzzmMY95zLORvMjISJid2bpjpYQijjQVdvr0aQEgv/zyi8Eyho40RUZGSnx8vN5504LnRAueNxX55xxr4fOmIv+cY2Ue85jHPOYxj3nWz7PEkaYK1WkSEaldu7YsXrzY6FztheBZWVk2dRiRecxjHvOYxzzmmS6v4Oe9udj06bnCLl68iCtXrigXdJdGYmIi2rZti7Zt2+oc2gOAFStWYOXKlYiJidE5VHjz5k3ExMRg5cqVWLFihc4yCQkJzGMe85jHPOYxz4byzM5s3TEj3LhxQxITEyUxMVEAyLx58yQxMVHOnTsnN27ckClTpsi+ffskLS1NfvnlF2nbtq00bNhQ7ty5Y/Q6tD3PyMhIZZot3BrJPOYxj3nMYx7zTJcXGRlZuU/P7dy5UwDoPcLCwuTWrVvSu3dvqVOnjtjb20tAQICMHj1aMjMzS7UOQ4frlixZImPGjNE5hyryYMdNnjxZJk+erHdIMD4+XsaMGaOzw5jHPOYxj3nMY5718ywxTpNVT8/Z2dnhiSeeUE63bdiwASKC6OhoODo6Yvv27bh8+TJyc3PRp08fLF26FCtXrrRmlYmIiKiqMlt3zAgljQiutX79emnVqpX4+vrK/PnzS7UOnp5jHvOYxzzmMa/y51ni9JxNjwgOAH/++Sc6duyI7du3IzQ0FJMmTcKkSZOMztWOCB4bG4uTJ08CsI2RS5nHPOYxj3nMY57p8rSf91V2RPC8vDzp3r27fP755yIiEhAQUOKRpuJGBK+It1Ayj3nMYx7zmMe8kvOq/JADc+bMQfXq1TFhwgSjlzE0Inh0dLRNjVzKPOYxj3nMYx7zTJtndmbrjpUSCh1pio+PFy8vL/nzzz+VaeU50hQbG6uTvWRJ5RoJlXnMYx7zmMe8qpwXHh5euYccKKhwp2n+/PmiUqmkWrVqygOA2NnZSUBAgNG5hg7XWfswIvOYxzzmMY95zDNdXpX+wt4XXngBR44cQVJSkvLw9fXF1KlTsX379lLn2eLIpcxjHvOYxzzmMc80eWvXroXZma07ZoTiRgQvijGn5wrTHmkKDw+XnBzbuTWSecxjHvOYxzzmmS7PEoNbWnXIgcjIyCKHDwgLC0N0dDTef/99rFq1ChcuXIBarcadO3cwZswYzJ8/3+h1aG9BdACgMl3Vq7R8a1egErpn7QpUQnydmhb/fpoe29S0tF8rYs4hB6x6eq5Ro0Z45513sH79egC6I4Jr5//73//G0aNHsXv3bgwbNgzffPMN/vrrLyvWmoiIiKoimx/csiDtUaNffvkFPXr0MCqXR5pMj//Bmx6PNJkeX6emxb+fpsc2Na1Kf6SpNHJzc7FkyRK4ubmhVatW1q4OERERVTHVrV2BkmzevBlDhgzBrVu34OPjgx07dqB27doGy9+9exd3795VnmdnZ1uimkRERFTJ2fyRpu7duyMpKQl79+5Fnz598Nxzz+Hy5csGyxsaEZyIiIioPGy+01SjRg00aNAAnTp1wrJly1C9enUsW7bMYPlp06YhKytLeVy4cMGCtSUiIqLKyuZPzxWWn5+vc/qtMI1GA41GY8EaERERUVVg1U5TTk4OTp06pTxPS0tDUlISatasiVq1amHmzJl48skn4ePjg7///hsLFy7En3/+iUGDBlmx1kRERFQVWbXTFB8fj+7duyvP33jjDQAPBrdcvHgx/vjjD3z77bf4+++/UatWLTzyyCP47bffEBQUZK0qExERURVl1U6TnZ0dnnjiCSQkJCAjI0NnnKZ79+6hYcOGSE1NxfXr1wEAbm5uqFu3bpnWpQLHxDAVm78QrgJim5qeTQxAV4nw76fp8X1vWgIgz8zrsOo+u3nzJlq1aoWFCxfqzbt16xYOHTqE9957D4cOHcL69euRkpKCJ5980go1JSIioqquQo0IfvDgQXTo0AHnzp2Dv7+/UbnaEcEdwf+UTMUmXjCVDEcENz1z/8dZ1fDvp+nxSJNpaY80mXNE8Ap191xWVhZUKhXc3d0NluHglkRERGQOFaaje+fOHYSHh2Po0KHF9iA5uCURERGZQ4XoNN27dw/PPfccRASLFi0qtiwHtyQiIiJzsPnTc9oO07lz5/Drr7+WeJ6Sg1sSERGROdh0p0nbYUpNTcXOnTtRq1Yta1eJiIiIqiibHRHcx8cHzz77LA4dOoTNmzcjLy8PmZmZAICaNWtCrVZbq9pERERUBVl1yIHY2FidEcG1wsLC8P7776N+/fpFLrdz505069bNqHVohxxQg7fMmgqHHDA9Djlgenydkq2rEBcVVyDyv4c5hxyw6j7Tjgju4+MDANiwYQNEBNHR0QgMDMS6devQq1cv1KxZEwCQmJgIETG6w0RERERkKjY7Irh2/qOPPoo5c+ZYuGZEREREuqx6TVPfvn3Rt29fg/NfeOEFAMDZs2ctVCMiIiKiotn03XNlwRHBiYiIyBzKdHru9u3buHXrlvL83Llz+Pzzz/Hzzz+brGJlxRHBiYiIyBzK1GkaMGAAvvvuOwDA9evX0bFjR3z22WcYMGBAiSN2mxtHBCciIiJzKFOn6dChQ3jssccAAD/88AO8vLxw7tw5fPfdd/jiiy9MWsHS0mg0cHV11XkQERERlVeZOk23bt2Ci4sLAODnn3/G008/DTs7O3Tq1Annzp0zaQWJiIiIbEGZLgRv0KABNm7ciKeeegrbt2/H66+/DgC4fPlyqY7sFDciuL+/P65evYrz588jPT0dAJCSkgIA8Pb2hre3d1mqTkRERFQmZRoR/IcffsC//vUv5OXloUePHsoF4LNmzcKuXbuwdetWo3KKGxE8Ojoa0dHRGD58uN78iIgIvP/++0atgyOCmx5HWja9XGtXgIgsjiOCm5YlRgQv05GmZ599Fo8++igyMjLQqlUrZXqPHj3w1FNPGZ2jHRE8ISEBGRkZ2LBhAwYOHKjMDwsLw5kzZ7B06VJcv34dXbp0waJFi9CwYcOyVJuIiIiozMrc0fX29kabNm1gZ/dPRIcOHdCkSROjM0oaEXzu3Ln44osvsHjxYhw4cAA1atRASEgI7ty5U9ZqExEREZWJ0afnnn76aaND169fX/qKqFQ6R5pEBL6+vpg8eTKmTJkC4MEhNy8vL0RHR2PIkCFG5fL0nOnx9Jzp8fQcUdXD03OmZVOn59zc3MxSAUPS0tKQmZmJnj176tShY8eO2Ldvn8FOE0cEJyIiInMwutMUFRVlznroyczMBAB4eXnpTPfy8lLmFWXWrFmYMWOGWetGREREVU+Zjw7ev38fv/zyC7766ivcuHEDAJCeno6cnByTVa4sOCI4ERERmUOZ7p47d+4c+vTpg/Pnz+Pu3bvo1asXXFxcMGfOHNy9exeLFy8ud8W04zBdunQJPj4+yvRLly6hdevWBpfTaDTQaDTlXj8RERFRQWU60jRx4kS0b98e165dg6OjozL9qaeeQkxMjEkqVr9+fXh7e+vkZWdn48CBAwgODjbJOoiIiIiMVaYjTb/99hv27t0LtVqtMz0wMBB//vmn0TkljQg+adIkfPTRR2jYsCHq16+P9957D76+vjpjORERERFZQpk6Tfn5+cjLy9ObfvHiReU76YwRHx+vMyL4G2+8AeCfEcHffPNN3Lx5Ey+//DKuX7+ORx99FNu2bYODg0Op62wPDjlgKvesXYFKiK9N0+PQGKZVpg8LIgsSAPo9E9Mq0+m53r174/PPP1eeq1Qq5OTkICIiAv369TM6p1u3bhARvUd0dLSSO3XqVAwZMgReXl7Ys2cPXnrpJRw8eLAs1SYiIiIqszJ999zFixcREhICEUFqairat2+P1NRU1K5dG7t27YKnp6fJKjh48GAkJydj0aJF8PX1xfLlyzF//nwcP34cdevWLXF57eCWNcD/5k2FR5pMj4Nbmh6PNJkWjzSRrdMeaTLn4JZl6jQBD4YcWLVqFY4cOYKcnBy0bdsWw4YN07kwvLxu374NFxcX/PjjjwgNDVWmt2vXDn379sVHH31UYgY7TabHTpPpsdNkeuw0mRY7TWTrLNFpKvP7oHr16nj++edNWRc99+/fR15ent41TI6Ojti9e3eRy3BEcCIiIjKHMneaUlNTsXPnTly+fBn5+fk686ZPn17uigGAi4sLgoOD8eGHH6Jp06bw8vLCypUrsW/fPjRo0KDIZTgiOBEREZlDmU7PLV26FGPHjkXt2rXh7e0NleqfE18qlQqHDh0yWQVPnz6NESNGYNeuXahWrRratm2LRo0aISEhASdOnNArX9SRJj8/P56eMyGenjM9np4zPZ6eMy2eniNbZ7PXNAUEBGDcuHEIDw83R52KdPPmTWRnZ8PHxweDBw9GTk4O/vvf/5a4HK9pMj12mkyPnSbTY6fJtNhpIltniU5TmYYcuHbtGgYNGmTquhSrRo0a8PHxwbVr17B9+3YMGDDAousnIiKiqq1MnaZBgwbh559/NnVdirR9+3Zs27YNaWlp2LFjB7p3744mTZpg+PDhFlk/EREREVDGI64NGjTAe++9h/3796NFixawt7fXmT9hwgSTVA54cJht2rRpuHjxImrWrIlnnnkGM2fO1FtnSfLA03NERGVl7pGWqyJ+JpmWJU7Jl6nTtGTJEjg7OyMuLg5xcXE681Qqlck6TXl5eTh69Cjy8/NhZ2cHJycneHl5me1cJREREZEhZeo0paWlmboeRZozZw4WLVqEb7/9FkFBQYiPj8fw4cPh5uZm0qNZRERERCWx6Rsi9u7diwEDBiijgQcGBmLlypX4/fffrVwzIiIiqmrK1GnKy8tDdHQ0YmJiihzc8tdffzVJ5Tp37owlS5bg5MmTaNSoEQ4fPozdu3dj3rx5BpfhiOBERERkDmXqNE2cOBHR0dEIDQ1F8+bNdQa3NKW33noL2dnZaNKkCapVq4a8vDzMnDkTw4YNM7gMRwQnIiIicyjT4Ja1a9fGd999h379+pmjTopVq1Zh6tSp+OSTTxAUFISkpCRMmjQJ8+bNQ1hYWJHLGBoR3AG8U8FU8ksuQqXEwS1Nj4Nbmhb/fpoe29S05H8Pm/vCXrVabfC730xp6tSpeOuttzBkyBAAQIsWLXDu3DnMmjXLYKdJo9FAo9GYvW5ERERUtZRpcMvJkycjMjISZThIVSq3bt2CnZ1uFatVq6Z3DRURERGRuZXpSNPu3buxc+dObN26FUFBQXoDTa5fv94klevfvz9mzpwJf39/BAUFITExEfPmzcOIESNMkk9ERERkrDJ1mtzd3fHUU0+Zui56FixYgPfeew/jxo3D5cuX4evri1deeQXTp083+7qJqGLj9SJk68p0qocM0n5hrzmV6UJwSwoMDMS5c+f0po8bNw4LFy4scfns7Gy4ubnxQnAT4slR0+OF4ERVTzVrV6CS0XaabO5CcEs6ePAg8vL+6TsmJyejV69eGDRokBVrRURERFVNmTtNP/zwA9asWYPz588jN1f3/+RDhw6Vu2JaderU0Xk+e/ZsPPzww+jatavJ1kFERERUkjKdUv3iiy8wfPhweHl5ITExER06dECtWrVw5swZ9O3b19R1VOTm5mL58uUYMWKEwQE17969i+zsbJ0HERERUXmVqdP05ZdfYsmSJViwYAHUajXefPNN7NixAxMmTEBWVpap66jYuHEjrl+/jpdeeslgmVmzZsHNzU15+Pn5ma0+REREVHWU6UJwJycnnDhxAgEBAfD09MSOHTvQqlUrpKamolOnTrhy5Yo56oqQkBCo1Wr89NNPBstwRHDz44XgpscLwYmqHl4IblqWuBC8TEeavL29cfXqVQCAv78/9u/fDwBIS0sz24CX586dwy+//IJRo0YVW06j0cDV1VXnQURERFReZeo0Pf7449i0aRMAYPjw4Xj99dfRq1cvDB482GzjN0VFRcHT0xOhoaFmySciIiIqTplOz+Xn5yM/Px/Vqz+4+W7VqlXYu3cvGjZsiFdeeQVqtdqklczPz0f9+vUxdOhQzJ49u1TLcpwm0+PpOdPj6Tmiqoen50zLEqfnIBXA9u3bBYCkpKSUetmsrCwBIJGRkcq0JUuWSHx8vN7vOTk5Mn36dMnJydH5XUQkPj5elixZovc785jHPOYxj3nMs35eZGSkAJCsrCwxlzJ3mq5duybbt2+X//znP/Ltt9/qPEzp4sWLMmzYMKlZs6Y4ODhI8+bN5eDBg0Yvr+00FW7EJUuWyJgxY5TG1srJyZHJkyfL5MmTlR2mFR8fL2PGjNHZYcxjHvOYxzzmMc/6ebGxsWbvNJVpcMuffvoJw4YNQ05ODlxdXXXGTFKpVHjxxRdNcRAM165dQ5cuXdC9e3ds3boVderUQWpqKjw8PEyST0RERGS0svS0GjZsKBMnTpSbN2+auhOnIzw8XB599NFyZfD0HPOYxzzmMY95lT/PEqfnynQheI0aNXD06FE89NBDpu/FFdCsWTOEhITg4sWLiIuLQ926dTFu3DiMHj3a4DKGxmmKjY3FyZMnAQBt27ZFu3btlDJLly5F48aNERMTgzfffBM1atQAANy8eRNz585Fjx49kJKSorPehIQE5etimMc85jGPecxjnnXztDd+2dyF4E899ZSsXr3atN23Img0GtFoNDJt2jQ5dOiQfPXVV+Lg4CDR0dEGl4mIiBA8uIhe55GVlSVjxoyRMWPG6C2Tk5Mjvr6+EhcXpzcvLi5OfH199c6vigjzmMc85jGPecyzkTxD1zCbktGdph9//FF5fP311+Lv7y8RERHyww8/6Mz78ccfTVY5e3t7CQ4O1pn22muvSadOnQwuc+fOHcnKylIeFy5cUE7PxcfH6x3aK3gYsOBhPpF/DgMWPlQo8s8hQeYxj3nMYx7zmGf9vPT0dNvpNKlUKqMednZ2Jqucv7+/jBw5Umfal19+Kb6+vkZnaHuesbGxyjRb2LnMYx7zmMc85jHPdHnh4eG202myhqFDh+pdCD5p0iS9o0/FMXS4ztqHEZnHPOYxj3nMY57p8ixxpKlUX6Py66+/olmzZsjOztabl5WVhaCgIPz222/lusaqoNdffx379+/Hxx9/jFOnTmHFihVYsmQJxo8fX+qsmzdv6vweExODlStXYsWKFTrlEhIS0LZtW7Rt2xYJCQk681asWIGVK1ciJiaGecxjHvOYxzzm2VDe2rVrYXal6WH1799f5s2bZ3B+ZGSkDBw4sNw9uYKGDh2qd1F348aNjV5ee6QpPDxccnJs59ZI5jGPecxjHvOYZ7o8SwxuWapOk7+/vxw/ftzg/BMnToifn1+5K1VQRESEBAUFSUZGhvL466+/jF5e22lKT0+3qZFLmcc85jGPecxjnunyLHH3XKlGBL906RLs7e0Nzq9evTr++uuvMh/1Ki7X29vb5LlERERERitND+uhhx6SDRs2GJy/bt06qV+/fnk7cjoiIiLEyclJfHx8pH79+vKvf/1Lzp07Z7C8oSEHeHqOecxjHvOYx7zKm2eJ03OlGhH8tddeQ2xsLA4ePAgHBwedebdv30aHDh3QvXt3fPHFFybr1G3duhU5OTlo3LgxMjIyMGPGDPz5559ITk6Gi4uLXvn3338fM2bM0Juenp4OHx8fALYxcinzmMc85jGPecwzXV5SUhImTpxoOyOCZ2Zmiq+vr/j5+cmcOXNk48aNsnHjRpk9e7b4+fmJr6+vZGZmmqd79z/Xrl0TV1dX+frrr4ucb+hIE4ccYB7zmMc85jGv8ubZ3JADXl5e2Lt3L5o3b45p06bhqaeewlNPPYW3334bzZs3x+7du+Hl5WWe3t3/uLu7o1GjRjh16lSR8zUaDVxdXXUeAJCYmKiUSUhIQEpKCk6ePIm5c+fq3L64dOlSjBo1CqNGjcLSpUuV6dre7MmTJ5GSkqJzOyTzmMc85jGPecyzbl5kZCTMrqy9ratXr8rvv/8uBw4ckKtXr5qyI1esGzduiIeHh0RGRhpVXns1Pb9GhXnMYx7zmMe8yptnU1+jYi2TJ0+W2NhYSUtLkz179kjPnj2ldu3acvnyZaOWL3gLoi0dRmQe85jHPOYxj3kV6wt7S3V6zhouXryIoUOHonHjxnjuuedQq1Yt7N+/H3Xq1ClVTmJiok2NXMo85jGPecxjHvNMm2d2ZuuOmcGsWbMEgEycONHoZQqentOyhVsjmcc85jGPecxjnunyIiMjeXpO6/fff5fAwEBp2bJlmTpNhRtxyZLKNRIq85jHPOYxj3lVOc8S4zTZ/Ok5AMjJycGwYcOwdOlSeHh4WLs6REREVBWZrTtmQi+++KJMmjRJRES6du1a7JEmQ+M08fQc85jHPOYxj3mVN88Sp+dKNSK4NaxatQozZ85URiHv1q0bWrdujc8//7zI8oZGBI+NjcXJkycB2MbIpcxjHvOYxzzmMc90ednZ2XBzc7OdEcEt7fz58+Lp6SmHDx9WppX1SBOHHGAe85jHPOYxr/LmVfkhBxISEnD58mW0bdsW1atXR/Xq1REXF4cvvvgC1atXR15ent4yhkYEj46OtqmRS5nHPOYxj3nMY55p88zObN0xE8jOzpajR4/qPNq3by/PP/+8HD161KgMbc8zNjZWmaY9J1r4vKnIP+dHC583LVi24DlU5jGPecxjHvOYZ/288PBwDjlQWEmn5wozdLjO2ocRmcc85jGPecxjnunybO4LeysyWxy5lHnMYx7zmMc85pkmb+3atTA7s3XHTOTLL7+UFi1aiIuLi7i4uEinTp1ky5YtRi+vPdIUHh4uOTm2c2sk85jHPOYxj3nMM12eJQa3tPlO06ZNm+S///2vnDx5UlJSUuTtt98We3t7SU5ONmp5bacpPT3dpkYuZR7zmMc85jGPeabLs8Tdc9XNfyyrfPr376/zfObMmVi0aBH279+PoKAgK9WKiIiIqhyzdcfM4P79+7Jy5UpRq9Vy7NixIssYGqeJp+eYxzzmMY95zKu8eZY4PWfzI4IDwNGjRxEcHIw7d+7A2dkZK1asQL9+/Yosa2hE8PT0dPj4+ACwjZFLmcc85jGPecxjnunykpKSMHHixKo7IrjW3bt3JTU1VeLj4+Wtt96S2rVrl/pIE4ccYB7zmMc85jGv8uZxyIH/UavVaNCgAdq1a4dZs2ahVatWiIyMLLKsoRHBExMTlTK2MnIp85jHPOYxj3nMM02eoX6BSZmtO2ZG3bt3l7CwMKPKaq+mj4yMlPh42xm5lHnMYx7zmMc85pkuzxJHmmy+0/TWW29JXFycpKWlyZEjR+Stt94SlUolP//8s1HLF7wF0ZYOIzKPecxjHvOYxzx+Ya9JXb58GS+++CIaN26MHj164ODBg9i+fTt69epVqpzExESbGrmUecxjHvOYxzzmmTbP7MzWHTORjz/+WNq3by/Ozs5Sp04dGTBggPzxxx9GL1/w9JyWLdwayTzmMY95zGMe80yXFxkZydNzISEhEhUVJcnJyZKUlCT9+vUTf3//Ig/XFcXQ4bolSyrXSKjMYx7zmMc85lXlPEuM02TzI4Jv27ZN53l0dDQ8PT2RkJCA//u//7NSrYiIiKjKMVt3zExSU1MFgBw9erTI+YbGaeLpOeYxj3nMYx7zKm+eJU7PVYgRwbXy8/Px5JNP4vr169i9e3eRZQyNCB4bG4uTJ08CsI2RS5nHPOYxj3nMY57p8rKzs+Hm5sYRwbXGjBkjAQEBcuHCBYNlihsRvCLeQsk85jGPecxjHvNKzuOQAwW8+uqr2Lx5M3bu3Il69eoZLGdoRPDo6GibGrmUecxjHvOYxzzmmTbP7MzWHTOR/Px8GT9+vPj6+srJkydLvby25xkbG6tM054TLXzeVOSf86OFz5sWLFvwHCrzmMc85jGPecyzfl54eDiHHBg7dqy4ublJbGysZGRkKI9bt24Ztbyhw3XWPozIPOYxj3nMYx7zTJfHL39LnhoAACnfSURBVOwFsGjRImRlZaFbt27w8fFRHqtXry5Vji2OXMo85jGPecxjHvNMk7d27VqYndm6YyYSFxcnTzzxhPj4+AgA2bBhQ6mW1x5pCg8Pl5wc27k1knnMYx7zmMc85pkuzxKDW9p8p2nLli3yzjvvyPr168vVaUpPT7epkUuZxzzmMY95zGOe6fIscfeczY8I3rdvX/Tt29fa1SAiIqKqzmzdMTOAEUeaDI3TxNNzzGMe85jHPOZV3jxLnJ6rUCOCq1QqbNiwAQMHDjRYxtCI4Onp6fDx8QFgGyOXMo95zGMe85jHPNPlJSUlYeLEiRwRXAvlONLEIQeYxzzmMY95zKu8eRxyoAwMjQiemJiolLGVkUuZxzzmMY95zGOeafIiIyNhdmbrjpkBynH3XGRkpMTH287IpcxjHvOYxzzmMc90eZY40mTznaYbN25IYmKiJCYmCgCZN2+eJCYmyrlz54xa/vr16wJALly4ICNGjJARI0bonL7LysqS9PR08fb2li1btujN27Jli3h7e0t6errePOYxj3nMYx7zmGcbedrLca5fv262PonNXwgeGxuL7t27600PCwtDdHR0ictfvHgRfn5+ZqgZERER2ZoLFy6gXr16Zsm2+U5TeeXn5yM9PR0uLi5QqVTWro5B2dnZ8PPzw4ULF8x31X8VwzY1PbapabE9TY9taloVqT1FBDdu3ICvry/s7MxzybbND25ZXnZ2dmbrcZpDwYvXyTTYpqbHNjUttqfpsU1Nq6K0p5ubm1nzK93dc0RERETmwE4TERERkRHYabIRGo0GERER0Gg01q5KpcE2NT22qWmxPU2PbWpabE9dlf5CcCIiIiJT4JEmIiIiIiOw00RERERkBHaaiIiIiIzAThMRERGREdhpMoOFCxciMDAQDg4O6NixI37//Xdl3pIlS9CtWze4urpCpVLh+vXresvPnDkTnTt3hpOTE9zd3fXmHz58GEOHDoWfnx8cHR3RtGlTy3y7s5WYuz0B4ODBg+jRowfc3d3h4eGBkJAQHD582ExbZH2G2vTq1at47bXX0LhxYzg6OsLf3x8TJkxAVlaWzvLnz59HaGgonJyc4OnpialTp+L+/fs6ZWJjY9G2bVtoNBo0aNDAqK89qqgs0Z53797FO++8g4CAAGg0GgQGBuKbb76x2DZaWnnbdMKECWjXrh00Gg1at26tlx8bG4sBAwbAx8cHNWrUQOvWrfH9999bYtOsxtxtCgDbt29Hp06d4OLigjp16uCZZ57B2bNnzbxllsNOk4mtXr0ab7zxBiIiInDo0CG0atUKISEhuHz5MgDg1q1b6NOnD95++22DGbm5uRg0aBDGjh1b5PyEhAR4enpi+fLlOHbsGN555x1MmzYN//73v82yTdZkifbMyclBnz594O/vjwMHDmD37t1wcXFBSEgI7t27Z5btsqbi2jQ9PR3p6en49NNPkZycjOjoaGzbtg0jR45Uls/Ly0NoaChyc3Oxd+9efPvtt4iOjsb06dOVMmlpaQgNDUX37t2RlJSESZMmYdSoUdi+fbs1NtmsLNGeAPDcc88hJiYGy5YtQ0pKClauXInGjRtbenMtorxtqjVixAgMHjy4yHXs3bsXLVu2xLp163DkyBEMHz4cL774IjZv3mzuzbMKS7RpWloaBgwYgMcffxxJSUnYvn07/v77bzz99NPm3jzLMdtXAVdRHTp0kPHjxyvP8/LyxNfXV2bNmqVTbufOnQJArl27ZjArKipK3NzcjFrvuHHjpHv37mWpsk2zRHsePHhQAMj58+eVaUeOHBEAkpqaWu5tsDXGtqnWmjVrRK1Wy71790REZMuWLWJnZyeZmZlKmUWLFomrq6vcvXtXRETefPNNCQoK0skZPHiwhISEmHpzrM4S7bl161Zxc3OTK1eumHFLbEd527SgiIgIadWqlVHr7devnwwfPrxMdbZ1lmjTtWvXSvXq1SUvL0+ZtmnTJlGpVJKbm1v+jbABPNJkQrm5uUhISEDPnj2VaXZ2dujZsyf27dtn1nVnZWWhZs2aZl2HpVmqPRs3boxatWph2bJlyM3Nxe3bt7Fs2TI0bdoUgYGBJluPLShLm2ZlZcHV1RXVqz/4qsp9+/ahRYsW8PLyUsqEhIQgOzsbx44dU8oUXIe2jLnfB5ZmqfbctGkT2rdvj7lz56Ju3bpo1KgRpkyZgtu3b5tx66zDFG1aVpXx7yhguTZt164d7OzsEBUVhby8PGRlZeE///kPevbsCXt7+3Jvhy1gp8mE/v77b+Tl5en88QMALy8vZGZmmm29e/fuxerVq/Hyyy+bbR3WYKn2dHFxQWxsLJYvXw5HR0c4Oztj27Zt2Lp1a7n/CNua0rbp33//jQ8//FDntZWZmVnk8tp5xZXJzs6uVB/0lmrPM2fOYPfu3UhOTsaGDRvw+eef44cffsC4ceNMvUlWZ4o2LYs1a9bg4MGDGD58eLlybJGl2rR+/fr4+eef8fbbb0Oj0cDd3R0XL17EmjVrylV/W8JOUwWXnJyMAQMGICIiAr1797Z2dSqk27dvY+TIkejSpQv279+PPXv2oHnz5ggNDa1UH/CllZ2djdDQUDRr1gzvv/++tatT4ZWnPfPz86FSqfD999+jQ4cO6NevH+bNm4dvv/2Wr1ETvEZ37tyJ4cOHY+nSpQgKCjJdBSug8rRpZmYmRo8ejbCwMBw8eBBxcXFQq9V49tlnIZXky0cq17/RVla7dm1Uq1YNly5d0pl+6dIleHt7m3x9x48fR48ePfDyyy/j3XffNXm+tVmqPVesWIGzZ89i3759sLOzU6Z5eHjgxx9/xJAhQ0y2Lmsztk1v3LiBPn36wMXFBRs2bNA5tO7t7a1zB6N2ee087c+i1uHq6gpHR0eTbpM1Wao9fXx8ULduXbi5uSllmjZtChHBxYsX0bBhQ5Nvm7WYok1LIy4uDv3798f8+fPx4osvlqvutspSbbpw4UK4ublh7ty5yrTly5fDz88PBw4cQKdOncq3ITaAR5pMSK1Wo127doiJiVGm5efnIyYmBsHBwSZd17Fjx9C9e3eEhYVh5syZJs22FZZqz1u3bsHOzg4qlUqZpn2en59vsvXYAmPaNDs7G71794ZarcamTZvg4OCgkxEcHIyjR48qdzACwI4dO+Dq6opmzZopZQquQ1vG1O8Da7NUe3bp0gXp6enIyclRypw8eRJ2dnaoV6+eOTfR4kzRpsaKjY1FaGgo5syZU+kubyjIUm2q/VtaULVq1ZT1VQrWvhK9slm1apVoNBqJjo6W48ePy8svvyzu7u7KnTEZGRmSmJgoS5cuFQCya9cuSUxM1Lkr5ty5c5KYmCgzZswQZ2dnSUxMlMTERLlx44aIiBw9elTq1Kkjzz//vGRkZCiPy5cvW2WbzckS7XnixAnRaDQyduxYOX78uCQnJ8vzzz8vbm5ukp6ebpXtNqfi2jQrK0s6duwoLVq0kFOnTum8vu7fvy8iIvfv35fmzZtL7969JSkpSbZt2yZ16tSRadOmKes4c+aMODk5ydSpU+XEiROycOFCqVatmmzbts1am202lmjPGzduSL169eTZZ5+VY8eOSVxcnDRs2FBGjRplrc02q/K2qYhIamqqJCYmyiuvvCKNGjVS3vfaOxJ//fVXcXJykmnTpulkVNY7FC3RpjExMaJSqWTGjBly8uRJSUhIkJCQEAkICJBbt25Za9NNip0mM1iwYIH4+/uLWq2WDh06yP79+5V5ERERAkDvERUVpZQJCwsrsszOnTuLzQgICLDshlqIudtTROTnn3+WLl26iJubm3h4eMjjjz8u+/bts+BWWpahNtUO3VDUIy0tTVn+7Nmz0rdvX3F0dJTatWvL5MmT9W5N3rlzp7Ru3VrUarU89NBDOvuksrFEe544cUJ69uwpjo6OUq9ePXnjjTcqzQdRUcrbpl27di22jKG/C127drX8xlqIudtURGTlypXSpk0bqVGjhtSpU0eefPJJOXHihIW31HxUIpXk6iwiIiIiM+I1TURERERGYKeJiIiIyAjsNBEREREZgZ0mIiIiIiOw00RERERkBHaaiIiIiIzAThMRERGREdhpIiIiIjICO01ERERERmCniYiIiMgI7DQRERERGYGdJiIiIiIjsNNEREREZAR2moiIiIiMwE4TERERkRHYaSIiIiIyAjtNREREREaobu0KWMKdO3eQm5tr7WoQERGRGanVajg4OJgtv9J3mu7cuYP69esjMzPT2lUhIiIiM/L29kZaWprZOk4qERGzJNuI7OxsuLm54cKFC3B1dnowMf++gZ95Jcz/308pqZwN5dhSXUqTZ7Kc/P89R/l+SinLlzFHqW4xz7W/54tumZKWhaH5UvT0kvIKT4eBnFI/l6LnF65/ifXVXczo54V/lrTrjC1fXH5p61pSpqnyyju9IrR9WZ4b0/6Wavvy7gvtTxiYX1J9S1v/8u5LQ9MLysrKgquraxFzyq/SH2nScnV1NaLTVAl/Kr9XK+GntpydgZ/a+Sojf8LIn1LCT0P10f7UflKWtx628bNUnaZSdnJK7AT9r8mk0M/C0ws3sVJem/O/TSrzB5O2fqVdf+Hp2peQkesv7x/v8nwQm6uTUxG23RL1tcb6zbUtqkLTCz83NN3Qc0PLw8BzQ9NLWr5w56bw+gsrPN1Q+cL1NzdeCE5ERERkBHaaiIiIiIzAThMRERGREdhpIiIiIjICO01ERERERmCniYiIiMgI7DQRERERGYGdJiIiIiIjsNNEREREZAR2moiIiIiMwE4TERERkRHYaSIiIiIyAjtNREREREZgp4mIiIjICOw0ERERERmBnSYiIiIiI7DTRERERGQEdpqIiIiIjMBOExEREZER2GkiIiIiMgI7TURERERGqG7tClhKdnY2kH//wRODP/NKmP+/n1JSORvKsaW6FJln4Kfk/+95ST+l+J//+4H8cv60UE7hzS7qeeFNFyOXhaH5UvT0kvIKT4eBnFI/125XoV0JQ7vYQPnCTW3s88I/S9p1xpYvLr+0dS0p01R55Z1eEdq+LM+NaX9LtX1594X2JwzML6m+pa2/uX5aSqXvNIkInJ2d4efnZ+2qEBERkRl5e3tDrVabLb/Sd5pUKhVycnJw4cIFuLq6Wrs6VErZ2dnw8/Pj/quguP8qNu6/iq0q7j+1Wg0HBwez5Vf6TpOWq6trlXnRVEbcfxUb91/Fxv1XsXH/mQ4vBCciIiIyAjtNREREREao9J0mjUaDiIgIaDQaa1eFyoD7r2Lj/qvYuP8qNu4/01OJiKXv2CMiIiKqcCr9kSYiIiIiU2CniYiIiMgI7DQRERERGYGdJiIiIiIjVPpO08KFCxEYGAgHBwd07NgRv//+u7WrVKXMmjULjzzyCFxcXODp6YmBAwciJSVFp8ydO3cwfvx41KpVC87OznjmmWdw6dIlnTLnz59HaGgonJyc4OnpialTp+L+/fs6ZWJjY9G2bVtoNBo0aNAA0dHR5t68Kmf27NlQqVSYNGmSMo37z7b9+eefeP7551GrVi04OjqiRYsWiI+PV+aLCKZPnw4fHx84OjqiZ8+eSE1N1cm4evUqhg0bBldXV7i7u2PkyJHIycnRKXPkyBE89thjcHBwgJ+fH+bOnWuR7avM8vLy8N5776F+/fpwdHTEww8/jA8//BAF79/i/rMwqcRWrVolarVavvnmGzl27JiMHj1a3N3d5dKlS9auWpUREhIiUVFRkpycLElJSdKvXz/x9/eXnJwcpcyYMWPEz89PYmJiJD4+Xjp16iSdO3dW5t+/f1+aN28uPXv2lMTERNmyZYvUrl1bpk2bppQ5c+aMODk5yRtvvCHHjx+XBQsWSLVq1WTbtm0W3d7K7Pfff5fAwEBp2bKlTJw4UZnO/We7rl69KgEBAfLSSy/JgQMH5MyZM7J9+3Y5deqUUmb27Nni5uYmGzdulMOHD8uTTz4p9evXl9u3bytl+vTpI61atZL9+/fLb7/9Jg0aNJChQ4cq87OyssTLy0uGDRsmycnJsnLlSnF0dJSvvvrKottb2cycOVNq1aolmzdvlrS0NFm7dq04OztLZGSkUob7z7IqdaepQ4cOMn78eOV5Xl6e+Pr6yqxZs6xYq6rt8uXLAkDi4uJEROT69etib28va9euVcqcOHFCAMi+fftERGTLli1iZ2cnmZmZSplFixaJq6ur3L17V0RE3nzzTQkKCtJZ1+DBgyUkJMTcm1Ql3LhxQxo2bCg7duyQrl27Kp0m7j/bFh4eLo8++qjB+fn5+eLt7S2ffPKJMu369eui0Whk5cqVIiJy/PhxASAHDx5UymzdulVUKpX8+eefIiLy5ZdfioeHh7I/tetu3LixqTepSgkNDZURI0boTHv66adl2LBhIsL9Zw2V9vRcbm4uEhIS0LNnT2WanZ0devbsiX379lmxZlVbVlYWAKBmzZoAgISEBNy7d09nPzVp0gT+/v7Kftq3bx9atGgBLy8vpUxISAiys7Nx7NgxpUzBDG0Z7mvTGD9+PEJDQ/XamPvPtm3atAnt27fHoEGD4OnpiTZt2mDp0qXK/LS0NGRmZuq0vZubGzp27Kiz/9zd3dG+fXulTM+ePWFnZ4cDBw4oZf7v//5P59vlQ0JCkJKSgmvXrpl7Myutzp07IyYmBidPngQAHD58GLt370bfvn0BcP9ZQ6X9wt6///4beXl5On+oAcDLywt//PGHlWpVteXn52PSpEno0qULmjdvDgDIzMyEWq2Gu7u7TlkvLy9kZmYqZYraj9p5xZXJzs7G7du34ejoaI5NqhJWrVqFQ4cO4eDBg3rzuP9s25kzZ7Bo0SK88cYbePvtt3Hw4EFMmDABarUaYWFhSvsX1fYF942np6fO/OrVq6NmzZo6ZerXr6+XoZ3n4eFhlu2r7N566y1kZ2ejSZMmqFatGvLy8jBz5kwMGzYMALj/rKDSdprI9owfPx7JycnYvXu3tatCRrpw4QImTpyIHTt2wMHBwdrVoVLKz89H+/bt8fHHHwMA2rRpg+TkZCxevBhhYWFWrh2VZM2aNfj++++xYsUKBAUFISkpCZMmTYKvry/3n5VU2tNztWvXRrVq1fTu4rl06RK8vb2tVKuq69VXX8XmzZuxc+dO1KtXT5nu7e2N3NxcXL9+Xad8wf3k7e1d5H7UziuujKurK49SlENCQgIuX76Mtm3bonr16qhevTri4uLwxRdfoHr16vDy8uL+s2E+Pj5o1qyZzrSmTZvi/PnzAP5p/+L+Tnp7e+Py5cs68+/fv4+rV6+Wah9T6U2dOhVvvfUWhgwZghYtWuCFF17A66+/jlmzZgHg/rOGSttpUqvVaNeuHWJiYpRp+fn5iImJQXBwsBVrVrWICF599VVs2LABv/76q94h4Hbt2sHe3l5nP6WkpOD8+fPKfgoODsbRo0d13vg7duyAq6ur8oEQHBysk6Etw31dPj169MDRo0eRlJSkPNq3b49hw4Ypv3P/2a4uXbroDfFx8uRJBAQEAADq168Pb29vnbbPzs7GgQMHdPbf9evXkZCQoJT59ddfkZ+fj44dOypldu3ahXv37illduzYgcaNG/PUTjncunULdna6H9PVqlVDfn4+AO4/q7D2lejmtGrVKtFoNBIdHS3Hjx+Xl19+Wdzd3XXu4iHzGjt2rLi5uUlsbKxkZGQoj1u3billxowZI/7+/vLrr79KfHy8BAcHS3BwsDJfe8t67969JSkpSbZt2yZ16tQp8pb1qVOnyokTJ2ThwoW8Zd1MCt49J8L9Z8t+//13qV69usycOVNSU1Pl+++/FycnJ1m+fLlSZvbs2eLu7i4//vijHDlyRAYMGFDkLett2rSRAwcOyO7du6Vhw4Y6t6xfv35dvLy85IUXXpDk5GRZtWqVODk58Zb1cgoLC5O6desqQw6sX79eateuLW+++aZShvvPsip1p0lEZMGCBeLv7y9qtVo6dOgg+/fvt3aVqhQART6ioqKUMrdv35Zx48aJh4eHODk5yVNPPSUZGRk6OWfPnpW+ffuKo6Oj1K5dWyZPniz37t3TKbNz505p3bq1qNVqeeihh3TWQaZTuNPE/WfbfvrpJ2nevLloNBpp0qSJLFmyRGd+fn6+vPfee+Ll5SUajUZ69OghKSkpOmWuXLkiQ4cOFWdnZ3F1dZXhw4fLjRs3dMocPnxYHn30UdFoNFK3bl2ZPXu22betssvOzpaJEyeKv7+/ODg4yEMPPSTvvPOOztAA3H+WpRIpMLQoERERERWp0l7TRERERGRK7DQRERERGYGdJiIiIiIjsNNEREREZAR2moiIiIiMwE4TERERkRHYaSIqgkqlwsaNG02SFRgYiM8//9wkWbYgNjYWKpVK76tTLC03NxcNGjTA3r17AQBnz56FSqVCUlKSwWVspe62Kjo6Wu/Llyuz3NxcBAYGIj4+3tpVoQqCnSayaSqVqtjH+++/b3BZYz5Ey+PChQsYMWIEfH19oVarERAQgIkTJ+LKlStmWZ81dOvWDZMmTdKZ1rlzZ2RkZMDNzc06lfqfxYsXo379+ujcuTMAwM/PDxkZGWjevLlV62Vqa9euRZMmTeDg4IAWLVpgy5YtJS7z119/4dlnn4WHhwdcXV3RrVs3va9TKcrgwYNx8uRJU1TbJqxfvx69e/dGrVq1ivxboFarMWXKFISHh1unglThsNNENi0jI0N5fP7553B1ddWZNmXKFKvU68yZM2jfvj1SU1OxcuVKnDp1CosXL1a+2/Dq1atWqRcA5OXlKd9NZQ5qtRre3t5QqVRmW0dJRAT//ve/MXLkSGVatWrV4O3tjerVq1utXqa2d+9eDB06FCNHjkRiYiIGDhyIgQMHIjk5udjlwsPDER8fj82bNyMxMRHjx483an2Ojo7w9PQ0RdWNpv3yYHO4efMmHn30UcyZM8dgmWHDhmH37t04duyY2epBlYiVRyQnMlpUVJS4ubkpz/Py8mTGjBlSt25dUavV0qpVK9m6dasyH4W+uqVr164i8uD7uHr27Cm1atUSV1dX+b//+z9JSEjQWRcA2bBhg8G69OnTR+rVq6fzHXoiIhkZGeLk5CRjxoxRpgUEBMgHH3wgQ4YMEScnJ/H19ZV///vfyvz8/HyJiIgQPz8/UavV4uPjI6+99poy/86dOzJ58mTx9fUVJycn6dChg+zcuVOvXX788Udp2rSpVKtWTb766ivRaDRy7do1nfpNmDBBunfvLiIif//9twwZMkR8fX3F0dFRmjdvLitWrFDKhoWF6bVhWlqa7Ny5UwDoZP/www/SrFkzUavVEhAQIJ9++qnOegMCAmTmzJkyfPhwcXZ2Fj8/P53vtbp7966MHz9evL29RaPRiL+/v3z88ccG2//gwYNiZ2cn2dnZyrS0tDQBIImJicq0//73v9KwYUNxcHCQbt26SVRUlF7do6KixM/PTxwdHWXgwIHy6aef6rzOREQ2bdok7du3F41GI7Vq1ZKBAwcarJspPffccxIaGqozrWPHjvLKK68Uu9zIkSN1vlvMWIXfY2FhYTJgwACdMhMnTlTeSyIia9eulebNm4uDg4PUrFlTevToITk5Ocr8pUuXSpMmTUSj0Ujjxo1l4cKFOnmBgYHSsWNH+fLLL+Xq1aulrrMxinptFNS9e3d59913zbJuqlzYaaIKo/Af9Hnz5omrq6usXLlS/vjjD3nzzTfF3t5eTp48KSIPOkcA5JdffpGMjAy5cuWKiIjExMTIf/7zHzlx4oQcP35cRo4cKV5eXjofwMV1mq5cuSIqlcrgh/ro0aPFw8ND8vPzReRBh8HFxUVmzZolKSkp8sUXX0i1atXk559/FpEHHzqurq6yZcsWOXfunBw4cEDn+8FGjRolnTt3ll27dsmpU6fkk08+EY1Go2xnVFSU2NvbS+fOnWXPnj3yxx9/SE5Ojnh5ecnXX3+t5Ny/f19n2sWLF+WTTz6RxMREOX36tFKvAwcOiMiDL/EMDg6W0aNHK1+0fP/+fb1OU3x8vNjZ2ckHH3wgKSkpEhUVJY6OjjrfHRcQECA1a9aUhQsXSmpqqsyaNUvs7Ozkjz/+EBGRTz75RPz8/GTXrl1y9uxZ+e2333Q6cIXNmzdPmjRpojOt8Afj+fPnRaPRyBtvvCF//PGHLF++XLy8vHTqvn//frGzs5M5c+ZISkqKREZGiru7u87rbPPmzVKtWjWZPn26HD9+XJKSknT2/SuvvCI1atQo9lFQSWULdoj8/Pxk/vz5OstPnz5dWrZsabBtRB508uzt7XX+iTBGaTtN6enpUr16dZk3b56kpaXJkSNHZOHChcr3mi1fvlx8fHxk3bp1cubMGVm3bp3UrFlToqOjlbzz58/LzJkzlY7VoEGDZPPmzXL//n29+u3atavE9iv4ZcRaJXWawsPDdTqCRIaw00QVRuE/6L6+vjJz5kydMo888oiMGzdOREr+Q6mVl5cnLi4u8tNPPynTius07d+/v9j58+bNEwBy6dIlEXnQYejTp49OmcGDB0vfvn1FROSzzz6TRo0aSW5url7WuXPnpFq1avLnn3/qTO/Ro4dMmzZNREQ5epKUlKRTZuLEifL4448rz7dv317k0aeCQkNDZfLkycrzwl/OKyJ6naZ//etf0qtXL50yU6dOlWbNminPAwIC5Pnnn1ee5+fni6enpyxatEhERF577TV5/PHHlY5mSQpvm4j+/p42bZpOHUQefDgWrPvQoUOlX79+OmUGDx6s8zoLDg6WYcOGGazLpUuXJDU1tdhHQSWV1b5uRETs7e31Oo8LFy4UT09Pg/U5duyYODs7y6xZs6Ru3bqyZs0aZV58fLwAkL/++qvIZUvbaUpISBAAcvbs2SLzHn74Yb36f/jhhxIcHFxk+QMHDsj48eOldu3a4u3tLZMnT5ajR48q82/dulVi+xX850erpL8FkZGREhgYWOQ8ooIqz8l/qlKys7ORnp6OLl266Ezv0qULDh8+XOyyly5dwrvvvovY2FhcvnwZeXl5uHXrVqmvrZBSfNd1cHCw3nPtHXWDBg3C559/joceegh9+vRBv3790L9/f1SvXh1Hjx5FXl4eGjVqpLP83bt3UatWLeW5Wq1Gy5YtdcoMGzYMnTp1Qnp6Onx9ffH999//f3v3HtPU2ccB/NvWFo6QMy8gncowiigqIEZRQ+r+cAVvhLk4+QMjGiTxmsiyRJ0G3eKMhukkLO5umIppUEfi5iADNcbUQRbQtIZaDKIm3ovRxEvEdd/3D8KJpy1Q3tfF1/n7JCTn9pzznKenPb+e/p4HzJ8/X+sd5ff7sWPHDlRVVeHGjRvo7OzEs2fPMHDgwH60AuDxeJCbm6tblpmZib1798Lv98NkMgGArn4GgwFWqxV3794FACxbtgx2ux3jxo3DnDlzsGDBAmRlZfV4zKdPnyIyMrLPek2fPl23LPB18Hg8WLhwYdA2tbW12vyFCxdQVFTU43GGDRvWrzygxMTEsLf9b2zbtg1z587Fxo0bkZWVBbvdjo6ODqxcuRJutxvjx49HTEzMSzlWWloaZs+ejZSUFGRnZyMrK0tLQH/8+DHa2tpQWFioa7+//vqrx04EGRkZyMjIwJ49e7Bp0ybs2bMH9fX1WgK3oij/SPspioInT5689P2Kfx8JmsQbp6CgAB0dHSgrK0NCQgIiIiIwc+ZMdHZ2hlU+MTERBoMh5A0X6LoRDx48GLGxsWHtLz4+Hl6vF/X19airq8Pq1atRWlqKM2fO4NGjRzCZTGhqatKCj27R0dHatKIoQYnZ06ZNw5gxY+BwOLBq1SpUV1ejoqJCW19aWoqysjLs3bsXKSkpiIqKwvr168Nuh/4ym826eYPBoCWsT5kyBe3t7aipqUF9fT0WL16M9957D0ePHg25r5iYGLjd7n+knoEURel1/cqVK3Ho0KFet3n06JE2/eLrFsqSJUvwzTffAACsVivu3LmjW3/nzh1YrdYey7tcLhQUFADoatfjx48jOzsbPp8PtbW1WL58ea/Hf5HRaAz6cvD8+XNt2mQyoa6uDufOncPvv/+O8vJybN68GY2NjVrw/f333wcFr4HXcjev14uDBw/i0KFDePjwIYqKinTJ/mfPnsXcuXN7rfO3336L/Pz8sM8RAO7fvx/2+1W82SRoEq8lVVUxfPhwOJ1OvPvuu9pyp9OJjIwMAF1PX4CuJyovcjqd2LdvH+bNmwega+gAn88X9rGHDh0Ku92Offv2obi4WHdTvX37NiorK7F06VJdENPQ0KDbR0NDA5KTk7V5RVGQk5ODnJwcrFmzBuPHj4fb7UZ6ejr8fj/u3r0Lm80Wdh275efno7KyEiNHjoTRaMT8+fN17ZCbm4slS5YAAP7++2+0trZiwoQJ2jYWiyWo/QIlJyfD6XTqljmdTiQlJfV4cwxFVVXk5eUhLy8PixYtwpw5c3D//n0MGTIkaNv09HR8/fXXINljL77k5GQcP35ctyzwdUhOTkZjY2Ov26SmpuLkyZM9BhufffZZv3px9jUEhqqq2vTMmTNx8uRJ3bAPdXV1QU/MXjRixAicPXsWmzZtAtD11K+6uhoLFizAkCFDsHbt2rDrGhsbG9RT78KFC7oA2GAwIDMzE5mZmSgpKUFCQgKqq6vx0UcfYfjw4bhy5UqvQYzP54PD4cDBgwfR1NQEu92OnTt34v333w96mjh16tQ+2y8uLi7s8+t28eJFpKen97uceAO94p8HhQhbYL7Fl19+SVVV6XA4eOnSJW7YsEGXCP78+XMqisLt27fz9u3bfPDgAUkyPT2ddrudLS0tbGhooM1mo6IouoRb9NF7rrW1lTExMbTZbDxz5gyvX7/OmpoaTpo0iWPHjtWSzsmufB5VVbVk46+++oomk4m1tbXaef3www90u91sa2vjli1bqCgKfT4fSTI/P5+jRo3SkmkbGxu5Y8cO/vrrryHb5UWXL18mAKamprKwsFC3rri4mPHx8XQ6nWxpaeGKFSuoqqouh6WoqIjTpk1je3s77927R7/fH5TT1NTUpEsEr6ioCJkIHpjQnJaWxq1bt5Lsyus6fPgwPR4PvV4vCwsLabVa6ff7Q56Xz+ej2WzW5bsE5q1cu3aNFouFH3/8MS9dusTKykparVZd3f/44w8ajUaWlpaytbWV5eXlQYngp0+fptFo1BLBXS4Xd+7cGbJeL5vT6eSAAQP4xRdf0OPxcOvWrUHnHaimpoYGg4GrV6+m2+1mc3MzN2/ezOjoaJpMJjocjh7LBl5LtbW1NBgM/Omnn9ja2sqSkhKqqqrlNDU0NPDzzz/nn3/+yWvXrrGqqooWi4W//fYbya6ec4qisKysjF6vly6Xi/v37+fu3bu1Y4wePZoTJkzgrl27ePPmzf+twQJ0dHTw/PnzPHHiBAHQ4XDw/PnzvHXrlm67hIQEHjhw4KUeW/w7SdAkXhuhhhzYtm0bR4wYQbPZHDTkANn1oR0fH0+j0ah90Dc3N3Pq1KmMjIzk2LFjeeTIkaCbel9BE0levXqVBQUFjIuLo9lsZnx8PNetW6cFO90SEhL46aef8sMPP+TAgQNptVpZVlamra+urub06dOpqiqjoqI4Y8YM1tfXa+s7OztZUlLCUaNG0Ww28+233+bChQvpcrlCtkugjIwMAuCpU6d0yzs6Opibm8vo6GgOGzaMW7Zs4dKlS3VBk9fr5YwZM6goSlhDDpjNZr7zzjssLS0NaoPegqbvvvuOkydPZlRUFFVV5ezZs9nc3NzjOZFd3fE3btyozYdK9v3ll1+YmJjIiIgI2mw27t+/P6juP/74I0eOHElFUZiTkxNyyIFjx45x8uTJtFgsjImJ4QcffNBr3V6mqqoqJiUl0WKxcOLEiTxx4kSfZU6dOkWbzUZVVTlo0CAuWrSILS0t3L59OyMjI+l0OkOWC3UtlZSUMC4ujm+99RaLi4u5du1a7b3U0tLC7OxsxsbGMiIigklJSSwvL9eVr6ys1Npu8ODBnDVrFn/++Wdtvcfj6V+D9EN3J4nAv+7rjiTPnTvHQYMGBQ0fIkQoBrIf2axCCPF/wuVywW63o62trc88of6oqKjA+vXr5V+tvCHy8vKQlpaGTz755FVXRbwGZERwIcRrKTU1Fbt27UJ7e/urrop4TXV2diIlJQXFxcWvuiriNSFPmoQQ4gXypEkI0RMJmoQQQgghwiA/zwkhhBBChEGCJiGEEEKIMEjQJIQQQggRBgmahBBCCCHCIEGTEEIIIUQYJGgSQgghhAiDBE1CCCGEEGGQoEkIIYQQIgwSNAkhhBBChOE/UhmFvY4rH1gAAAAASUVORK5CYII=", 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", 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s2aO0L+WLph07dpC+vr7KYk+TounPP/8kExMT2rJli2h6dYqmoqIiGj58OHXr1k20l0mZjRs3koGBgeizVpcazYngaWlpGDduHFq2bAkLCwu4uroCeHGlQnmdO3cWfre3twcAdOrUSTRNfjKhtbU1Jk+eDC8vLwwfPhzBwcHIzs7War+GDRsGMzMzmJmZoUOHDpX21cTEBC1btlTa1/T0dDx58gRDhgwR8szMzLB161ZcvXpVZf+uXr2K4uJi9OvXT5hmaGgIDw8PJCcni9r26dNH+N3a2hpubm5Cm/KP6efnBwBISkrCoEGD1N5W2pKSkoIzZ85g3LhxAAADAwOMGTMGGzduVNp+6tSp2LVrF3JycrBr1y5MnTpVoY2pqSl+++03pKenY/HixTAzM8O8efPg4eGBJ0+eVKt/yrZVdftcXs+ePRWm7dixA/369YODgwPMzMywePFi0XshOTkZvXr1Ei1T/vlVRpP3mKOjIwAIr9PKXhPqvIZnzpyJiIgIdO3aFQsWLMCJEycq7bMqPXr0EN1PTk5Gnz59IJFIhGn9+vVDQUEBbt26pXTd9PX1YWNjo/D5UX59K9OlSxe0adMGv/zyCzZt2oSJEyfCwMBA1ObChQsoLS1F27ZtRdskNja20vd1cnIyDAwMRM+xjY2N6D0LvHidvfzyy8L9du3awcrKCsnJybhx44boMVesWFErJ3lXxdbWFvr6+rhz545o+p07d+Dg4KB2Ttu2bZGbm6tw9RYAFBUV4erVq2jbti0AwNjYuNr9/Pnnn5GUlISkpCThKjIHBwel/ZbPKy8iIgLTpk3Dzp07MXjwYGF669atIZFIFD6f5ZKTk9GkSRPY2dlp1O/KxMbGYvjw4Vi3bh0mTZokmqdq3SquV3FxMUaPHo3MzEwcPnwYFhYWlT5mr169UFJSIrooR5cMqm7SMAwfPhwuLi4IDQ2Fk5MTysrK0LFjRxQVFYnaGRoaCr/LPyArTisrKxPub968GbNnz8bBgwexY8cOLF68GIcPH0bv3r2hp6en8CFSXFxcrX79/PPPePr0qUI/lPWr4vzyfS0oKAAA/Pbbb3jppZdE7WQymdJtpk3lrwyTvwm0/YZV18aNG1FSUgInJydhGhFBJpPhu+++g6Wlpah9p06d0K5dO4wbNw7u7u7o2LGjyivdWrVqhVatWmHatGlYtGgR2rZtix07dmDKlCmwsLBAbm6uwjLyqxXlj6tsW1W3z+WZmpqK7p88eRITJkzAZ599Bi8vL1haWiIiIgJr1qxRmaGOmrzH5K/Tyl4T6ryGhw0bhszMTBw4cACHDx/GoEGDMGvWLHz99dfVWpeK20xdyt6Dla1vVaZOnYoNGzbg8uXLCpfMAy+2ib6+PuLj46Gvry+aZ2ZmVt3uV4uTk5PotWptbQ0rKytYWVnhypUrOn3sykilUvTo0QNRUVHCZf5lZWWIiorCBx98oHbOm2++iYCAAKxZs0bhvfHjjz+isLBQ+Cemc+fO2LJlC4qLixVeA/I+lZaWiqZVfA0DL/4xWb58Oe7evYumTZsCgFA4tG/fXmgXHh6OqVOnIiIiQuFKWhsbGwwZMgTff/895s6dK3pP5eTkYNu2bZg0aRIkEgk6deqEsrIyxMbGigqv8v0GoNB3ZWJiYvDaa69h1apVmDFjhtJ1i4qKEl1RfPjwYdE/Y/KCKS0tDdHR0bCxsanycZOSkqCnpydsL11rFHuaHjx4gJSUFCxevBiDBg2Cu7s7Hj16pLX8bt26YeHChThx4gQ6duyI7du3AwDs7OwU9jyV/5BRp18vvfQSWrdujdatW8PFxUXjPrZv3x4ymQw3btwQ8uQ3Z2dnAMrfIK1atYJUKsXx48eFacXFxTh79qzoTQwAp06dEn5/9OgRUlNT4e7uDgCix5O/uDt37oyoqCiN10kTJSUl2Lp1K9asWSP8l5eUlIRz587ByckJ4eHhSpebOnUqYmJilO5lUsXV1RUmJiYoLCwEALi5ueHWrVsK/20lJCTAyMgIzZs3B6C4rTTtsyonTpyAi4sLFi1ahJ49e6JNmzbIzMwUtXF3d8fp06dF08o/vxVp6z1W2WtCndcw8OJ95+vri//+979Yv349QkJCqt2Pitzd3XHy5EnRP0HHjx+Hubk5mjVrVuN8VcaPH48LFy6gY8eOCu834MVnT2lpKe7evauwTeT/wSv7g+3u7o6SkhLRcyx/Dss/TklJCeLi4oT7KSkpePz4Mdzd3WFgYCB6PGtra+jp6WHs2LHYtm2b0j00BQUFojGHdOWjjz5CaGgotmzZguTkZMycOROFhYWYMmWK0CYnJwdJSUlIT08H8GKvXVJSknA5fvPmzbF69WqsX78eixYtwpUrV3D16lWsXbsWCxYswLx584Q9dR988AHy8vIwduxYxMXFIS0tDf/5z3+QkpIC4MVnwfnz55GSkoL79+8r/PMsN3ToULRv3x4TJ07EuXPncOjQISxevBizZs0S/jHYvn07Jk2ahDVr1qBXr17IyclBTk6O6B+y7777Ds+fP4eXlxeOHj2Kmzdv4uDBgxgyZAheeuklLF++XOiXr68vpk6dir179yIjIwMxMTHYuXMnAMDFxQUSiQT79+/HvXv3hH9cKoqOjoaPjw9mz56NN998U+hT+aEN/P39cfDgQaxZswZXrlzB0qVLERcXJxSyxcXFeOuttxAXF4dt27ahtLRUyJH/43Xy5EmsX78e586dw7Vr17Bt2zbMnTsX77zzDpo0aVKdl4jmauUgYB0rLS0lGxsbeueddygtLY2ioqLo5ZdfFp0sp+y8EmXHc8ufH3Dt2jX65JNP6MSJE3T9+nU6dOgQ2djY0Pfff09ERAcPHiSJREJbtmyh1NRUCgwMJAsLC+GcJnX6pUxV/ZKreA7NokWLyMbGhsLCwig9PZ3i4+Ppm2++obCwMCJ6cQWIRCKhsLAwunv3rnDCqL+/Pzk5OdHvv/8uOhFcfkWTvD8dOnSgI0eO0IULF2jEiBHUvHnzSi+TjY6OJj09PeFE8PPnz4tOXFdHdc9pioyMJKlUqvQqkAULFggnWld8PRQXF9O9e/dEJyyj3DlNQUFBNH/+fIqOjqZr165RQkICTZ48mYyNjenKlStCRocOHWjgwIF0/Phxunr1Ku3atYscHR0pICCgxn1WRtnlub/++isZGBhQeHg4paenU3BwMFlbW4tePxEREWRkZESbNm2ilJQUCgwMrPREcE3fY48ePRJdgp2SkkJSqZRmzpxJ586do+TkZPr++++FE8Greg0vWbKE9u7dS2lpaXTx4kV67bXXlJ7HIqfqnCb5VVFy8hPBZ82aRcnJybR3716lJ4JXXE7Z9q/q/V0x59GjR1RQUCDcr3gi+IQJE8jV1ZV2795N165do9OnT9OKFSto//79RER0/Phx4RzIe/fuCSehjxw5ktq3b09//fUXJSUlkbe3t9ITwT08POjUqVMUFxdHvXv3pt69e6vsO9GL8xnbtWtHzZo1oy1bttClS5coNTWVNm7cSK1bt661IU3kw0lIpVJhHcpTNhQAANq8ebOo3a+//kqvvPIKmZqakpGREfXo0UPpFZnnzp2joUOHkomJCZmbm9Mrr7winGN69+5dGjJkCJmZmVU65AAR0fXr12nYsGFkbGxMtra2NG/ePIWrNJX1u+JwANevXydfX1+yt7cnQ0NDcnZ2pg8//JDu378vavf06VOaO3cuOTo6klQqVbji9PPPPycHBweSSCQqhxyoeCWq/Fbx/N2dO3dS27ZtSSqVUocOHei3334T5im7glt+k2+v+Ph46tWrF1laWpKRkRG5u7vTihUrau18JqJGdCL44cOHyd3dnWQyGXXu3JliYmJqXDTl5OTQqFGjhBebi4sLBQYGiq58CwwMJHt7e7K0tKS5c+fSBx98IHohVdUvZTQtmsrKymj9+vXk5uZGhoaGZGdnR15eXhQbGyu0UfYGefr0KX344Ydka2tb6ZAD//vf/6hDhw7Ch9S5c+dUroPc7t27qWvXriSVSsnW1pbeeOONKpcpr7pF02uvvUavvvqq0nmnT58mAHTu3LkqT86uWDT9+eef9Oabb5KzszNJpVKyt7cnb29v4ao7udu3b5Ovry81b96cjI2NqX379vTll19WepWhun1WRtWYJvPnzycbGxsyMzOjMWPG0Lp16xReP8uXLydbW1syMzMjX19fWrBgQaUngmvyHqtYNBG9uLS/b9++JJPJyMrKiry8vITXelWv4WXLlpG7uzsZGxuTtbU1jRw5kq5du6Z02xCpXzTJ+1XVkAO6KJoqqlg0FRUVUWBgILm6upKhoSE5OjrS66+/TufPnxfa+Pn5kY2NjdIhBywtLcnY2Ji8vLyUDjmwe/duatmyJclkMho8eLBozBxVHj9+TJ988gm1adNGeD8MHjyYIiMjq7zik7H6TEJUD87cY/9oMTExGDhwIB49elTrIw9PnjwZrq6u/FUqjGlZWFgY5syZ02i+IYAxdTSKc5oYY4wxxmqKiybGGGOMMTXw4Tn2j7Z3715YWVlhwIABdd0VxhhjDRwXTYwxxhhjauDDc4wxxhhjamjwI4KXlZUhKysL5ubmoq9AYIwxxljDQUTIz8+Hk5MT9PR0s0+owRdNWVlZotGCGWOMMdZw3bx5U2cj9ddp0XT06FF89dVXiI+PR3Z2NiIjI4XvCgJejMGzZcsW0TJeXl44ePCg2o9hbm4O4MVGLP/Ff2FhYTh37hwmTZqEbt26CdMLCwuxYsUKAMCnn34q+g6qxMREbN26FV26dMHkyZNFj8N5nMd5nMd5nMd5dZf35ptvwsfHR/i7rxN1OLAmHThwgBYtWkR79uxROkqur68veXt7U3Z2tnCTf3WHunJzcwkABQcHC9NCQkIoLi5O4feCggIKDAykgoIC0e9ERHFxcRQSEqLwO+dxHudxHudxHufVfV5wcDABoNzcXNKVenP1nEQiUbqn6fHjx9i7d6/GuXl5ebC0tERMTAxSU1MBAN27d0ePHj2ENqGhoXBzc0NUVBQWLFggVLeFhYVYvXo1Bg0ahJSUFEyfPl1YJj4+HgkJCZzHeZzHeZzHeZxXD/Lkf+9zc3NFR5a0SmflWDVBxZ4mS0tLsrOzo7Zt25Kfn5/Clw1W9OzZM8rNzRVuN2/eFCpPPz8/8vPzU1imoKCAnJycRN/BJhcbG0tOTk6iL8yU4zzO4zzO4zzO47z6kSc/sqTLPU31esgBb29vbN26FVFRUVi1ahViY2MxbNgwlJaWqlxm5cqVsLS0FG7yk8DDwsIwbdo0TJs2DaGhoUJ7eTWbmpqKlJQUxMfHC/Pi4+ORkpKC1NRUrF69GoWFhcK80NBQzuM8zuM8zuM8zqtHeTqns3KsmlDFN38TEV29epUA0JEjR1S2UbWnKSYmRmgjPyZa8bgp0d/HRyseNy3ftvwxVM7jPM7jPM7jPM6r+7yAgACd72n6RxVNRES2trb0448/qp2randdXe9G5DzO4zzO4zzO4zzt5WVlZTXuw3MV3bp1Cw8ePICjo2O1ly2/266wsBBRUVEIDw/H9u3bRe3i4+PRvXt3dO/eXbSrEAC2b9+O8PBwREVFcR7ncR7ncR7ncV49ytu1axd0TmflmBry8/MpMTGREhMTCQCtXbuWEhMTKTMzk/Lz8+njjz+mkydPUkZGBh05coS6d+9Obdq0oWfPnqn9GPI9TQEBAVRQUH8ujeQ8zuM8zuM8zuM87eXFxMQ07MNz0dHRBEDh5uvrS0+ePKGhQ4eSnZ0dGRoakouLC02fPp1ycnKq9RjyoikrK4vmzZtH8+bNU9glGBcXR35+fqInTC4kJIT8/PxEx1CJXjxxnMd5nMd5nMd5nFc/8hr81XN6enp47bXXhMNtkZGRICKEhYXB2NgYhw4dwt27d1FUVARvb2+EhoYiPDy8LrvMGGOMscZKZ+WYGqoaEVxuz5491KVLF3JycqJ169ZV6zH48BzncR7ncR7ncV7Dz6uNw3P1ekRwALh9+zZ69eqFQ4cOwcfHB3PmzMGcOXPUzpWPEJqVlSXs0aoPI5dyHudxHudxHudxnvbykpKS4O/v33hHBC8tLaWBAwfS+vXriYjIxcWlyj1NlY0IXt4/5RJKzuM8zuM8zuM8zuMhB6q0atUqGBgYYPbs2Wovo2pE8MTERKFNfRm5lPM4j/M4j/M4j/O0kxccHAyd01k5Vk2osKcpLi6O7O3t6fbt28K0muxpCg4Opri4+jNyKedxHudxHudxHudpL6829jTV26Jp3bp1JJFISF9fX7gBID09PXJxcVE7t/wliPVpNyLncR7ncR7ncR7n8Rf2asXEiRNx/vx5JCUlCTcnJyfMnz8fhw4dqnZeYmJivRq5lPM4j/M4j/M4j/O0m6dzOivH1FDZiODKqHN4riJ55RkcHCxMqw+XRnIe53Ee53Ee53Ge9vKCg4Mb9pADwcHBSocP8PX1RVhYGJYuXYqIiAjcvHkTUqkUz549g5+fH9atW6f2Y8iHHMiNjYWFmZkWe9+I8XbUvpKSuu5Bg3PHpn1dd6FBsc88U9ddaHDy2nnUdRcalLy8PDg7W+p0yIE6PTzXtm1bLFq0CHv27AEgHhFcPv+7777DhQsXcOzYMUyYMAGbNm3CvXv36rDXjDHGGGuMDOrywYcNG4Zhw4apnD9+/HjR/bVr12Ljxo04f/48Bg0apOvuMcYYY4wJ6u2J4BUVFRUhJCQElpaW6NKlS113hzHGGGONTJ3uaVLH/v37MXbsWDx58gSOjo44fPgwbG1tVbZ//vw5nj9/LtzPy8urjW4yxhhjrIGr93uaBg4ciKSkJJw4cQLe3t4YPXo07t69q7K9qhHBGWOMMcZqot4XTaampmjdujV69+6NjRs3wsDAABs3blTZfuHChcjNzRVuN2/erMXeMsYYY6yhqveH5yoqKysTHX6rSCaTQSaT1WKPGGOMMdYY1GnRVFBQgPT0dOF+RkYGkpKSYG1tDRsbGyxfvhwjRoyAo6Mj7t+/jw0bNuD27dt4++2367DXjDHGGGuM6rRoiouLw8CBA4X7H330EYAXg1v++OOPuHLlCrZs2YL79+/DxsYGL7/8Mv766y906NChrrrMGGOMsUaqTosmPT09vPbaa4iPj0d2djYiIyMxatQoAEBxcTHatGmDtLQ0PH78GABgaWmJl156SbMHe+klwNxcOx1v7Hj0aq3LM3Oq6y40OPZmZXXdhYbFrmdd96DBsbiv+qImpoHn+Tp/iDo9EbywsBBdunTBhg0bFOY9efIECQkJWLJkCRISErBnzx6kpKRgxIgRddBTxhhjjDV29XZEcEtLSxw+fFg07bvvvoOHhwdu3LiB5s2b10YXGWOMMcYA/MOunsvNzYVEIoGVlZXKNjy4JWOMMcZ0od6P0yT37NkzBAQEYNy4cZV+ezEPbskYY4wxXfhHFE3FxcUYPXo0iAg//PBDpW15cEvGGGOM6UK9PzwnL5gyMzPx559/VrqXCeDBLRljjDGmG/W6aJIXTGlpaYiOjoaNjU1dd4kxxhhjjVS9HRHc0dERb731FhISErB//36UlpYiJycHAGBtbQ2pVFpX3WaMMcZYIyQhIqqrB4+JiRGNCC7n6+uLpUuXokWLFkqXi46OxoABA9R6jLy8PFhaWiL33r0qD+0xNRUU1HUPGpyHsK7rLjQ41kZP6roLDcrDZyZ13YUGx/pZVl13oUHJy8+HZbt2yM3N1dnf+zo9EVw+IrijoyMAIDIyEkSEsLAwuLq6Yvfu3RgyZAisrV/8QUlMTAQRqV0wMcYYY4xpS70dEVw+v3///li1alUt94wxxhhjTKzejggOABMnTgQAXL9+vZZ6xBhjjDGmXL2+ek4TPCI4Y4wxxnRBo8NzT58+xZMnf59kmZmZifXr1+OPP/7QWsc0xSOCM8YYY0wXNCqaRo4cia1btwIAHj9+jF69emHNmjUYOXJklSN26xqPCM4YY4wxXdCoaEpISMArr7wCAPjll19gb2+PzMxMbN26Fd98841WO1hdMpkMFhYWohtjjDHGWE1pVDQ9efIE5ubmAIA//vgDb7zxBvT09NC7d29kZmZqtYOMMcYYY/WBRieCt27dGnv37sXrr7+OQ4cOYe7cuQCAu3fvVmvPTmUjgjdv3hwPHz7EjRs3kJX1YgCwlJQUAICDgwMcHBw06TpjjDHGmEY0GhH8l19+wfjx41FaWopBgwYJJ4CvXLkSR48exe+//65WTmUjgoeFhSEsLAxTpkxRmB8UFISlS5eq9RjCiOCPHvGhOm15/Liue9DgFJnxiODaJn3GV85qU5ERf35qm9SgrK670KDk5eXBskkTnY4IrtGeprfeegv9+/dHdnY2unTpIkwfNGgQXn/9dbVz5COCx8fHIzs7G5GRkRg1apQw39fXF9euXUNoaCgeP36Mfv364YcffkCbNm006TZjjDHGmMY0HhHcwcEB3bp1g57e3xEeHh5o166d2hlVjQi+evVqfPPNN/jxxx9x+vRpmJqawsvLC8+ePdO024wxxhhjGlF7T9Mbb7yhduiePXvUalfZiOBEhPXr12Px4sUYOXIkAGDr1q2wt7fH3r17MXbsWLX7wxhjjDFWU2oXTZaWlrrsh4KMjAzk5ORg8ODBoj706tULJ0+eVFk08YjgjDHGGNMFtYumzZs367IfCnJycgAA9vb2oun29vbCPGVWrlyJzz77TKd9Y4wxxljjo/E5TSUlJThy5Ah++ukn5OfnAwCysrJQUFCgtc5pgkcEZ4wxxpguaHT1XGZmJry9vXHjxg08f/4cQ4YMgbm5OVatWoXnz5/jxx9/rHHH5OMw3blzB46OjsL0O3fuoGvXriqXk8lkkMlkNX58xhhjjLHyNNrT5O/vj549e+LRo0cwNjYWpr/++uuIiorSSsdatGgBBwcHUV5eXh5Onz6NPn36aOUxGGOMMcbUpdGepr/++gsnTpyAVCoVTXd1dcXt27fVzqlqRPA5c+bgiy++QJs2bdCiRQssWbIETk5OorGcGGOMMcZqg0ZFU1lZGUpLSxWm37p1S/hOOnXExcWJRgT/6KOPAPw9IviCBQtQWFiIGTNm4PHjx+jfvz8OHjwIIyOjave5qEQPRSUan8LFypFW3YRVU0lJXfeg4eHXqXbx6NU6wN+uoF21cLW8RlXE0KFDsX79euG+RCJBQUEBgoKC8Oqrr6qdM2DAABCRwi0sLEzInT9/PsaOHQt7e3scP34ckydPxtmzZzXpNmOMMcaYxjQqmtasWYPjx4+jffv2ePbsGcaPHy8cmlu1apVWOzht2jQcPnwY//nPf3DhwgUMHToUgwcPrtZhQMYYY4yxmtLoC3uBF0MORERE4Pz58ygoKED37t0xYcIE0YnhNfX06VOYm5vj119/hY+PjzC9R48eGDZsGL744osqM+Rf2Hvvnu6+wK+xkRY8rOsuNDhPjPgLe7XNpIQHttUqM7O67kHDw4fntCovLw+WLVrUvy/sBQADAwO888472uyLgpKSEpSWliqcw2RsbIxjx44pXYZHBGeMMcaYLmhcNKWlpSE6Ohp3795FWZn4BMHAwMAadwwAzM3N0adPHyxbtgzu7u6wt7dHeHg4Tp48idatWytdhkcEZ4wxxpguaHR4LjQ0FDNnzoStrS0cHBwgkUj+DpRIkJCQoLUOXr16FVOnTsXRo0ehr6+P7t27o23btoiPj0dycrJCe2V7mpydnfnwnBbx4Tnt48Nz2seH57SMD89pHx+e06p6e3juiy++wPLlyxEQEKDt/iho1aoVYmNjUVhYiLy8PDg6OmLMmDFo2bKl0vY8IjhjjDHGdEGjq+cePXqEt99+W9t9qZSpqSkcHR3x6NEjHDp0CCNHjqzVx2eMMcZY46ZR0fT222/jjz/+0HZflDp06BAOHjyIjIwMHD58GAMHDkS7du0wZcqUWnl8xhhjjDFAw6KpdevWWLJkCSZPnow1a9bgm2++Ed20KTc3F7NmzUK7du0wadIk9O/fH4cOHYKhoWG1cr7+egWKiwtRXFyI5cuDUFxcCKkUuHAhHlu2hCr8LpUCW7aE4sKFeIXfy2c0xryg4GAUymSAtTXiMzIQunu3wu+wtkbo7t2Iz8hQ+L1QJhMyyv/emPNMTIDk5Hhs2xYKExPAxATYti0UycnxCr8TFWLVqiAQFYp+r5jR2PNCd+xAfFoaYGEh+r1QXx9Ba9agUF9f9DssLBCflobQHTsUfq+Y0SjzEhMBPT0UPn2KoM8+Q+HTp6LfoaeH+MREhG7cqPA79PQQunGjkFH+90ad9w/9vKqveYmZmVqtP5QiDbi6uqq8tWjRQpNIpUpKSmjx4sXk6upKRkZG1LJlS/r888+prKxM7Yzc3FwCQFlZWTRv3jyaN28eFRQUiNrExcWRn58fhYSEKCwfEhJCfn5+FBcXJ5peUFDAeZzHeZzHeZzHefUkT/73Pjc3VyFLWzQ6ETwjI0O7lZsKq1atwg8//IAtW7agQ4cOiIuLw5QpU2BpaYnZs2fXSh8YY4wxxgBotqeptvj4+NDUqVNF09544w2aMGGC2hnyyjMgIIAKCgqooKCAAgMDheo0Li5OqHDL/070osqVV7jlfy+fwXmcx3mcx3mcx3l1nxcTE6PzPU0ajdNUWlqKsLAwREVFKR3c8s8//9RKQbdixQqEhITgjz/+QNu2bXHu3DkMHToUa9euxYQJE5Quo2qcpqysLDg6OgIACgsLsXr1agwaNAgpKSmYPn260D4+Pl4YZ6p79+7o0aOHMC80NBRubm6IiorCggULYGpqynmcx3mcx3mcx3n1IC8pKQn+/v46HadJoz1Ns2bNIlNTUxo9ejT5+/vTnDlzRDdtKS0tpYCAAJJIJGRgYEASiYRWrFhR6TJBQUEEQOFWsfKMjY0lJycnheOrRER+fn7k5+enML2goICcnJwoNjZWYR7ncR7ncR7ncR7n1V1eVlaWzvc0aVQ02djY0G+//abtvigIDw+nZs2aUXh4OJ0/f562bt1K1tbWFBYWpnKZZ8+eUW5urnC7efMmAaCYmBihjXw3YMVde0R/7wasuKuwfNvyuwo5j/M4j/M4j/M4r+7zAgIC6mfR5OjoSCkpKdrui4JmzZrRd999J5q2bNkycnNzUztDfk5TcHBwvXpyOY/zOI/zOI/zOE97efV2T9PXX39N77//frUu/deEtbU1ff/996JpK1asoDZt2qidUf4SxPq0G5HzOI/zOI/zOI/ztJdXG0MOaDS45bFjx7Bt2za0atUKw4cPxxtvvCG6acvw4cOxfPly/Pbbb7h+/ToiIyOxdu1avP7669XOSkxMRPfu3dG9e3fEx8eL5m3fvh3h4eGIiopCYWGhML2wsBBRUVEIDw/H9u3bRcvEx8dzHudxHudxHudxXj3K0zWNrp6r6itMNm/erHGHysvPz8eSJUsQGRmJu3fvwsnJCePGjUNgYCCkUqlaGXl5ebC0tETuo0e6O5u+sSkpqeseMMZqG7/vta7MyKSuu9Cg5OXloUkTS51ePadR0VSbXF1dkalkaPT3338fGzZsqHJ5Lpp0gD88GWt8+H2vdVw0aVdtFE0ajQhem86ePYvS0lLh/sWLFzFkyBC8/fbbddgrxhhjjDU2GhdNv/zyC3bu3IkbN26gqKhINE8+OJU22NnZie5/+eWXaNWqFTw9PbX2GIwxxhhjVdHoRPBvvvkGU6ZMgb29PRITE+Hh4QEbGxtcu3YNw4YN03YfBUVFRfjvf/+LqVOnQiKRKG3z/Plz5OXliW6MMcYYYzWlUdH0/fffIyQkBN9++y2kUikWLFiAw4cPY/bs2cjNzdV2HwV79+7F48ePMXnyZJVtVq5cCUtLS+Hm7Oyss/4wxhhjrPHQ6ERwExMTJCcnw8XFBU2bNsXhw4fRpUsXpKWloXfv3njw4IEu+govLy9IpVL873//U9lG1XfP8YngWsQnhDLW+PD7Xuv4RHDtqo0TwTXa0+Tg4ICHDx8CAJo3b45Tp04BADIyMqCri/EyMzNx5MgRTJs2rdJ2MpkMFhYWohtjjDHGWE1pVDT9+9//xr59+wC8GLNp7ty5GDJkCMaMGaPRwJPq2Lx5M5o2bQofHx+d5DPGGGOMVUajq+dCQkJQVlYGAJg1axZsbGxw4sQJjBgxAu+9955WOwgAZWVl2Lx5M3x9fWFgUO9HSWCMMcZYA6TRniY9PT1R8TJ27Fh88803+PDDD9Ueqbs6jhw5ghs3bmDq1KkaZ6z48ksUPn2KwqdPEfTZZyh8+hTQ00N8YiJCN25U+B16egjduBHxiYkKv5fPaJR5y5ejsLgYkEoRf+ECQrdsUfgdUilCt2xB/IULCr8XFhcLGeV/5zzO47x6nJecDJiYoJAIQatWoZBI9DtMTBCfnIzQbdsUfoeJCUK3bRMyyv/emPOePi3EZ58F4enTQujpAYmJ8di4MVThdz09YOPGUCQmxiv8Xj6jseedO5eoxcpDBU2/tO7Ro0d06NAh+s9//kNbtmwR3bTp1q1bNGHCBLK2tiYjIyPq2LEjnT17Vu3l5V/gl5WVRfPmzaN58+YpfPlfXFwc+fn5ib4tWS4kJIT8/PxE375M9OJLBjmP8ziP8ziP8zivfuTVxhf2anSs63//+x8mTJiAgoICWFhYiMZMkkgkmDRpklYKukePHqFfv34YOHAgfv/9d9jZ2SEtLQ1NmjTRSj5jjDHGmNo0qbTatGlD/v7+VFhYqO0iTiQgIID69+9fowx55RkQEEAFBQVUUFBAgYGBQnUaFxcnVLjlfyd6UeXKK9zyv5fP4DzO4zzO4zzO47y6z4uJidH5niaNxmkyNTXFhQsX0LJlS+1XceW0b98eXl5euHXrFmJjY/HSSy/h/fffx/Tp01Uuo2qcpqysLDg6OgIACgsLsXr1agwaNAgpKSmivPj4eOFrYLp3744ePXoI80JDQ+Hm5oaoqCgsWLAApqamnMd5nMd5nMd5nFcP8pKSkuDv76/TcZo02tP0+uuv044dO7Rbvikhk8lIJpPRwoULKSEhgX766ScyMjKisLAwlcsEBQURAIVbxcozNjaWnJycFI6vEhH5+fmRn5+fwvSCggJycnKi2NhYhXmcx3mcx3mcx3mcV3d5WVlZOt/TpPbVc/v27RNuPj4+mD9/PpYuXYrdu3eL5snHb9KGsrIydO/eHStWrEC3bt0wY8YMTJ8+HT/++KPKZRYuXIjc3FzhdvPmTQBAYuLfZ9XHx8cjJSUFqampWL16NQoLC4V5oaGhmDZtGqZNm4bQ0FBhuryaTU1NRUpKCuLj4zmP8ziP8ziP8zivnuQFBwdD59StriQSiVo3PT09rVV0zZs3p3fffVc07fvvvycnJye1M+TnNAUHB1NcXJzCcdPyx0TLHzcl+vsYa8XjpkR/H2PlPM7jPM7jPM7jvLrPq409TRoPOVAbxo0bp3Ai+Jw5c6hPnz5qZ5S/BLE+7UbkPM7jPM7jPM7jPO3l1caQA9Ua3PLPP/9E+/btkZeXpzAvNzcXHTp0wF9//aWVPWAAMHfuXJw6dQorVqxAeno6tm/fjpCQEMyaNavaWYmJiejevTu6d+8u2rUHANu3b0d4eDiioqJEuwoLCwsRFRWF8PBwbN++XbRMfHw853Ee53Ee53Ee59WjPJ2rToU1fPhwWrt2rcr5wcHBNGrUqBpXcuWNGzdO4aRuNzc3tZcvf3hOrj5cGsl5nMd5nMd5nMd52ssLDg6uX4fnmjdvTpcvX1Y5Pzk5mZydnWvcqfKCgoKoQ4cOlJ2dLdzu3bun9vKqdteFhDSskVA5j/M4j/M4j/Mac15tjNNUrRHB79y5A0NDQ5XzDQwMcO/ePY33elWW6+DgoPVcxhhjjDG1VafCatmyJUVGRqqcv3v3bmrRokVNCzmRoKAgMjExIUdHR2rRogWNHz+eMjMzVbZ/9uwZ5ebmCrebN2/y4TnO4zzO4zzO47wGnlcbh+eqNSL4hx9+iJiYGJw9exZGRkaieU+fPoWHhwcGDhyIb775RmtF3e+//46CggK4ubkhOzsbn332GW7fvo2LFy/C3Nxcof3SpUvx2WefKUyPiYlBamoqgPoxcinncR7ncR7ncR7naS8vLy8PlpaW9WdE8JycHHJyciJnZ2datWoV7d27l/bu3UtffvklOTs7k5OTE+Xk5OimvPt/jx49IgsLC/r555+Vzle1p4mHHOA8zuM8zuM8zmu4ebUx5EC1x2m6fv06DRs2jPT09EQDWg4bNoyuXbumiz4q6NmzJ33yySdqteXBLTmP8ziP8ziP8xp+Xr0e3PLhw4d05swZOn36ND18+FCbfapUfn4+NWnSRHSOUmXkRVNMTIwwrT48uZzHeZzHeZzHeZynvbyAgID6WzTVlnnz5lFMTAxlZGTQ8ePHafDgwWRra0t3795Va3lVu+vqejci53Ee53Ee53Ee52kvr159YW9duXXrFsaNGwc3NzeMHj0aNjY2OHXqFOzs7KqVUx9HLuU8zuM8zuM8zuM87eTt2rULOqezckwHVq5cSQDI399f7WXke5oCAgKooKD+XBrJeZzHeZzHeZzHedrLq43BLf8xRdOZM2fI1dWVOnfurFHRlJWVVa9GLuU8zuM8zuM8zuM87eXVuy/srSsFBQWYMGECQkND0aRJk7ruDmOMMcYaI52VY1o0adIkmjNnDhEReXp6VrqnSdU4TXx4jvM4j/M4j/M4r+Hm1cbhuWqNCF4XIiIisHz5cmEU8gEDBqBr165Yv3690vaqRgTPysqCo6MjgPoxcinncR7ncR7ncR7naS8vKSkJ/v7+9WdE8Np248YNatq0KZ07d06YpumeJh5ygPM4j/M4j/M4r+HmNfohB+Lj43H37l10794dBgYGMDAwQGxsLL755hsYGBigtLRUYRmZTAYLCwvRDQASExNFuSkpKUhNTcXq1atFly+GhoZi2rRpmDZtGkJDQ4Xp8mo2NTUVKSkposshOY/zOI/zOI/zOK9u84KDg6FzOivHtCAvL48uXLgguvXs2ZPeeecdunDhgloZ/DUqnMd5nMd5nMd5DT+vXn+NSl2p6vBcReUvQaxPuxE5j/M4j/M4j/M475/1hb31+vCcNiUmJtarkUs5j/M4j/M4j/M4T7t5OqezckxLvv/+e+rUqROZm5uTubk59e7dmw4cOKD28uUPz8nVh0sjOY/zOI/zOI/zOE97ecHBwXx4bt++ffTbb79RamoqpaSk0KeffkqGhoZ08eJFtZZXtbsuJKRhjYTKeZzHeZzHeZzXmPNqY5wmg9rdr1V9w4cPF91fvnw5fvjhB5w6dQodOnSoo14xxhhjrNHRWTmmAyUlJRQeHk5SqZQuXbqktI2qcZr48BzncR7ncR7ncV7DzauNw3P1fkRwALhw4QL69OmDZ8+ewczMDNu3b8err76qtK2qEcFjYmKQmpoKoH6MXMp5nMd5nMd5nMd52svLy8uDpaVl4x0RXO758+eUlpZGcXFx9Mknn5CtrW219zTxkAOcx3mcx3mcx3kNN4+HHPh/UqkUrVu3Ro8ePbBy5Up06dJF5cifqkYEDwsLq1cjl3Ie53Ee53Ee53GedvN0TmflmA4NHDiQfH191WorrzxjYmKEafJjohWPmxL9fXy04nHT8m3LH0PlPM7jPM7jPM7jvLrPCwgI4CEHPvnkE4qNjaWMjAw6f/48ffLJJySRSOiPP/5Qa3lVu+vqejci53Ee53Ee53Ee52kvr9F/YS8A3L17F5MmTYKbmxsGDRqEs2fP4tChQxgyZEi1curjyKWcx3mcx3mcx3mcp528Xbt2Qed0Vo5pyYoVK6hnz55kZmZGdnZ2NHLkSLpy5Yray8v3NAUEBFBBQf25NJLzOI/zOI/zOI/ztJdXG4Nb1vuiycvLizZv3kwXL16kpKQkevXVV6l58+ZKd+spIy+asrKy6tXIpZzHeZzHeZzHeZynvbzauHqu3o8IfvDgQdH9sLAwNG3aFPHx8fjXv/5VR71ijDHGWKOjs3JMR9LS0ggAXbhwQel8VeM08eE5zuM8zuM8zuO8hptXG4fn/hEjgsuVlZVhxIgRePz4MY4dO6a0jaoRwbOysuDo6Aigfoxcynmcx3mcx3mcx3nay0tKSoK/vz+PCC7n5+dHLi4udPPmTZVtKhsRvLx/yiWUnMd5nMd5nMd5nMdDDlTLBx98gP379yM6OhrNmjVT2U7ViOCJiYlCm/oycinncR7ncR7ncR7naSdP1TeFaJXOyjEtKSsro1mzZpGTkxOlpqZWe3n52fTBwcEUF1d/Ri7lPM7jPM7jPM7jPO3l1caepnpfNM2cOZMsLS0pJiaGsrOzhduTJ0/UWr78JYj1aTci53Ee53Ee53Ee5/EX9mrVDz/8gNzcXAwYMACOjo7CbceOHdXKSUxMrFcjl3Ie53Ee53Ee53GedvN0TmflmJbExsbSa6+9Ro6OjgSAIiMjq7V8+cNzcvXh0kjO4zzO4zzO4zzO015ecHAwH547cOAALVq0iPbs2VOjoqniRgwJaVgjoXIe53Ee53Ee5zXmvNoYp6nejwg+bNgwDBs2rK67wRhjjLHGTmflmA5AjT1NqsZp4sNznMd5nMd5nMd5DTevNg7P/aNGBJdIJIiMjMSoUaNUtlE1InhMTAxSU1MB1I+RSzmP8ziP8ziP8zhPe3l5eXmwtLTkEcHlUIM9TTzkAOdxHudxHudxXsPN4yEHNKBqRPCwsLB6NXIp53Ee53Ee53Ee52k3T+d0Vo7pAGpw9VxMTIwwTX5MtOJxU6K/j49WPG5avm35Y6icx3mcx3mcx3mcV/d5AQEBPORAfn4+JSYmUmJiIgGgtWvXUmJiImVmZqq1/OPHjwkA3bx5U3TY7sCBA+Tg4EBZWVmi6bm5uTR16lSaOnWqwvSsrCxycHCgAwcOKMzjPM7jPM7jPM7jvLrLS0lJIQD0+PFjndUk9f5E8JiYGAwcOFBhuq+vL8LCwqpc/tatW3B2dtZBzxhjjDFW39y8eRPNmjXTSXa9L5pqqqysDFlZWTA3N4dEIqnr7qiUl5cHZ2dn3Lx5U3dn/TcyvE21j7epdvH21D7eptr1T9qeRIT8/Hw4OTlBT083p2zX+8Eta0pPT09nFaculD95nWkHb1Pt422qXbw9tY+3qXb9U7anpaWlTvMb3NVzjDHGGGO6wEUTY4wxxpgauGiqJ2QyGYKCgiCTyeq6Kw0Gb1Pt422qXbw9tY+3qXbx9hRr8CeCM8YYY4xpA+9pYowxxhhTAxdNjDHGGGNq4KKJMcYYY0wNXDQxxhhjjKmBiyYd2LBhA1xdXWFkZIRevXrhzJkzwryQkBAMGDAAFhYWkEgkePz4scLyy5cvR9++fWFiYgIrKyuF+efOncO4cePg7OwMY2NjuLu7Izg4WIdrVLd0vT0B4OzZsxg0aBCsrKzQpEkTeHl54dy5czpao7qnaps+fPgQH374Idzc3GBsbIzmzZtj9uzZyM3NFS1/48YN+Pj4wMTEBE2bNsX8+fNRUlIiahMTE4Pu3btDJpOhdevWan3t0T9VbWzP58+fY9GiRXBxcYFMJoOrqys2bdpUa+tY22q6TWfPno0ePXpAJpOha9euCvkxMTEYOXIkHB0dYWpqiq5du2Lbtm21sWp1RtfbFAAOHTqE3r17w9zcHHZ2dnjzzTdx/fp1Ha9Z7eGiSct27NiBjz76CEFBQUhISECXLl3g5eWFu3fvAgCePHkCb29vfPrppyozioqK8Pbbb2PmzJlK58fHx6Np06b473//i0uXLmHRokVYuHAhvvvuO52sU12qje1ZUFAAb29vNG/eHKdPn8axY8dgbm4OLy8vFBcX62S96lJl2zQrKwtZWVn4+uuvcfHiRYSFheHgwYN49913heVLS0vh4+ODoqIinDhxAlu2bEFYWBgCAwOFNhkZGfDx8cHAgQORlJSEOXPmYNq0aTh06FBdrLJO1cb2BIDRo0cjKioKGzduREpKCsLDw+Hm5lbbq1srarpN5aZOnYoxY8YofYwTJ06gc+fO2L17N86fP48pU6Zg0qRJ2L9/v65Xr07UxjbNyMjAyJEj8e9//xtJSUk4dOgQ7t+/jzfeeEPXq1d7dPZVwI2Uh4cHzZo1S7hfWlpKTk5OtHLlSlG76OhoAkCPHj1SmbV582aytLRU63Hff/99GjhwoCZdrtdqY3uePXuWANCNGzeEaefPnycAlJaWVuN1qG/U3aZyO3fuJKlUSsXFxUREdODAAdLT06OcnByhzQ8//EAWFhb0/PlzIiJasGABdejQQZQzZswY8vLy0vbq1Lna2J6///47WVpa0oMHD3S4JvVHTbdpeUFBQdSlSxe1HvfVV1+lKVOmaNTn+q42tumuXbvIwMCASktLhWn79u0jiURCRUVFNV+JeoD3NGlRUVER4uPjMXjwYGGanp4eBg8ejJMnT+r0sXNzc2Ftba3Tx6httbU93dzcYGNjg40bN6KoqAhPnz7Fxo0b4e7uDldXV609Tn2gyTbNzc2FhYUFDAxefFXlyZMn0alTJ9jb2wttvLy8kJeXh0uXLgltyj+GvI2u3we1rba25759+9CzZ0+sXr0aL730Etq2bYuPP/4YT58+1eHa1Q1tbFNNNcTPUaD2tmmPHj2gp6eHzZs3o7S0FLm5ufjPf/6DwYMHw9DQsMbrUR9w0aRF9+/fR2lpqejDDwDs7e2Rk5Ojs8c9ceIEduzYgRkzZujsMepCbW1Pc3NzxMTE4L///S+MjY1hZmaGgwcP4vfff6/xh3B9U91tev/+fSxbtkz02srJyVG6vHxeZW3y8vIa1B/62tqe165dw7Fjx3Dx4kVERkZi/fr1+OWXX/D+++9re5XqnDa2qSZ27tyJs2fPYsqUKTXKqY9qa5u2aNECf/zxBz799FPIZDJYWVnh1q1b2LlzZ436X59w0fQPd/HiRYwcORJBQUEYOnRoXXfnH+np06d499130a9fP5w6dQrHjx9Hx44d4ePj06D+wFdXXl4efHx80L59eyxdurSuu/OPV5PtWVZWBolEgm3btsHDwwOvvvoq1q5diy1btvBrVAuv0ejoaEyZMgWhoaHo0KGD9jr4D1STbZqTk4Pp06fD19cXZ8+eRWxsLKRSKd566y1QA/nykYb1b3Qds7W1hb6+Pu7cuSOafufOHTg4OGj98S5fvoxBgwZhxowZWLx4sdbz61ptbc/t27fj+vXrOHnyJPT09IRpTZo0wa+//oqxY8dq7bHqmrrbND8/H97e3jA3N0dkZKRo17qDg4PoCkb58vJ58p/KHsPCwgLGxsZaXae6VFvb09HRES+99BIsLS2FNu7u7iAi3Lp1C23atNH6utUVbWzT6oiNjcXw4cOxbt06TJo0qUZ9r69qa5tu2LABlpaWWL16tTDtv//9L5ydnXH69Gn07t27ZitSD/CeJi2SSqXo0aMHoqKihGllZWWIiopCnz59tPpYly5dwsCBA+Hr64vly5drNbu+qK3t+eTJE+jp6UEikQjT5PfLysq09jj1gTrbNC8vD0OHDoVUKsW+fftgZGQkyujTpw8uXLggXMEIAIcPH4aFhQXat28vtCn/GPI22n4f1LXa2p79+vVDVlYWCgoKhDapqanQ09NDs2bNdLmKtU4b21RdMTEx8PHxwapVqxrc6Q3l1dY2lX+Wlqevry88XoNQ12eiNzQREREkk8koLCyMLl++TDNmzCArKyvhypjs7GxKTEyk0NBQAkBHjx6lxMRE0VUxmZmZlJiYSJ999hmZmZlRYmIiJSYmUn5+PhERXbhwgezs7Oidd96h7Oxs4Xb37t06WWddqo3tmZycTDKZjGbOnEmXL1+mixcv0jvvvEOWlpaUlZVVJ+utS5Vt09zcXOrVqxd16tSJ0tPTRa+vkpISIiIqKSmhjh070tChQykpKYkOHjxIdnZ2tHDhQuExrl27RiYmJjR//nxKTk6mDRs2kL6+Ph08eLCuVltnamN75ufnU7Nmzeitt96iS5cuUWxsLLVp04amTZtWV6utUzXdpkREaWlplJiYSO+99x61bdtWeN/Lr0j8888/ycTEhBYuXCjKaKhXKNbGNo2KiiKJREKfffYZpaamUnx8PHl5eZGLiws9efKkrlZdq7ho0oFvv/2WmjdvTlKplDw8POjUqVPCvKCgIAKgcNu8ebPQxtfXV2mb6OjoSjNcXFxqd0Vria63JxHRH3/8Qf369SNLS0tq0qQJ/fvf/6aTJ0/W4lrWLlXbVD50g7JbRkaGsPz169dp2LBhZGxsTLa2tjRv3jyFS5Ojo6Opa9euJJVKqWXLlqLnpKGpje2ZnJxMgwcPJmNjY2rWrBl99NFHDeYPkTI13aaenp6VtlH1ueDp6Vn7K1tLdL1NiYjCw8OpW7duZGpqSnZ2djRixAhKTk6u5TXVHQlRAzk7izHGGGNMh/icJsYYY4wxNXDRxBhjjDGmBi6aGGOMMcbUwEUTY4wxxpgauGhijDHGGFMDF02MMcYYY2rgookxxhhjTA1cNDHGGGOMqYGLJsYYY4wxNXDRxBhjjDGmBi6aGGOMMcbUwEUTY4wxxpgauGhijDHGGFMDF02MMcYYY2rgookxxhhjTA1cNDHGGGOMqYGLJsYYY4wxNRjUdQdqw7Nnz1BUVFTX3WCMMcaYDkmlUhgZGeksv8EXTc+ePYOxsRWA53XdFcYYY4zpkIODAzIyMnRWODX4ounFHqbnAAYDkP7/VH0VP/Uq/FTVrrrtVc3X1eOVb1/dvlV1X9VPiZbXoaptpm7/Xsw3+P9Xuqqf+vo1m1+bOf/EPtdFjh7KXvxSUlL5z9LSms3XRk596kt9fjw1c+jFPfkrQOOfVeWUVtKuqozKllWnL9VdvmKOpstXdxupu+208Zw9B7AuJwdFRUVcNNWcAQDD//+9un+oa9pe0wJBG49bW32rn+0kEr3//4lKf+rpVf5T/oe6qp9V/SHXxs/aeIyG8FPtoqk+/NRVtqoXqnx+VS98ebuq3kDyn1UhUu+nqv6UlanVD/r/nJoWTdX9w6+saNJk2Zo+dmNYXtVPXeMTwRljjDHG1MBFE2OMMcaYGrhoYowxxhhTAxdNjDHGGGNq4KKJMcYYY0wNXDQxxhhjjKmBiybGGGOMMTVw0cQYY4wxpgYumhhjjDHG1MBFE2OMMcaYGrhoYowxxhhTAxdNjDHGGGNq4KKJMcYYY0wNXDQxxhhjjKmBiybGGGOMMTVw0cQYY4wxpgYumhhjjDHG1MBFE2OMMcaYGrhoYowxxhhTAxdNjDHGGGNq4KKJMcYYY0wNBnXdgdpTgr9rxDIVP+XzS///p34VP/Uq/KyqnabL16R9dftW1X1VPyVaXoeqtpl6/SPS+/+fqPRnWVnlP0v//yUhkVT+sypV9UOd/lTsk6qfJSUvfhoYVP5TX79m8+trjp78fS3fEKp+Vtxg1Z2vjZz61BddPl5VP6t6I6r5Bvr/eyo/6dX9WVVOaSXtqsqobFl1+lLd5SvmaLp8dbeRuttOG8/Zc+hegy+apFIpHBwckJNzpK67wupQxc9wxhhjDY+DgwOkUqnO8iVE8hK94Xr27BmKioq0npuXlwdnZ2fcvHkTFhYWWs+vLxrDejaGdQR4PRuaxrCejWEdAV5PbZFKpTAyMtJ6rlyD39MEAEZGRjrdiBYWFg36RS7XGNazMawjwOvZ0DSG9WwM6wjwetZ3fCI4Y4wxxpgauGhijDHGGFMDF001IJPJEBQUBJlMVtdd0anGsJ6NYR0BXs+GpjGsZ2NYR4DX85+iUZwIzhhjjDFWU7yniTHGGGNMDVw0McYYY4ypgYsmxhhjjDE1cNHEGGOMMaYGLpoqsXz5cvTt2xcmJiawsrJSaxkiQmBgIBwdHWFsbIzBgwcjLS1N1Obhw4eYMGECLCwsYGVlhXfffRcFBQU6WAP1VLc/169fh0QiUXrbtWuX0E7Z/IiIiNpYJaU02e4DBgxQWAc/Pz9Rmxs3bsDHxwcmJiZo2rQp5s+fj5I6/L6W6q7nw4cP8eGHH8LNzQ3GxsZo3rw5Zs+ejdzcXFG7unw+N2zYAFdXVxgZGaFXr144c+ZMpe137dqFdu3awcjICJ06dcKBAwdE89V5n9aF6qxnaGgoXnnlFTRp0gRNmjTB4MGDFdpPnjxZ4Tnz9vbW9WpUqTrrGRYWprAOFQcrro/PZ3XWUdnnjEQigY+Pj9CmPj6XR48exfDhw+Hk5ASJRIK9e/dWuUxMTAy6d+8OmUyG1q1bIywsTKFNdd/vtYqYSoGBgbR27Vr66KOPyNLSUq1lvvzyS7K0tKS9e/fSuXPnaMSIEdSiRQt6+vSp0Mbb25u6dOlCp06dor/++otat25N48aN09FaVK26/SkpKaHs7GzR7bPPPiMzMzPKz88X2gGgzZs3i9qV3w61TZPt7unpSdOnTxetQ25urjC/pKSEOnbsSIMHD6bExEQ6cOAA2dra0sKFC3W9OipVdz0vXLhAb7zxBu3bt4/S09MpKiqK2rRpQ2+++aaoXV09nxERESSVSmnTpk106dIlmj59OllZWdGdO3eUtj9+/Djp6+vT6tWr6fLly7R48WIyNDSkCxcuCG3UeZ/Wtuqu5/jx42nDhg2UmJhIycnJNHnyZLK0tKRbt24JbXx9fcnb21v0nD18+LC2Vkmp6q7n5s2bycLCQrQOOTk5ojb17fms7jo+ePBAtH4XL14kfX192rx5s9CmPj6XBw4coEWLFtGePXsIAEVGRlba/tq1a2RiYkIfffQRXb58mb799lvS19engwcPCm2qu+1qGxdNati8ebNaRVNZWRk5ODjQV199JUx7/PgxyWQyCg8PJyKiy5cvEwA6e/as0Ob3338niURCt2/f1nrfq6Kt/nTt2pWmTp0qmqbOm6i2aLqenp6e5O/vr3L+gQMHSE9PT/Qh/sMPP5CFhQU9f/5cK32vDm09nzt37iSpVErFxcXCtLp6Pj08PGjWrFnC/dLSUnJycqKVK1cqbT969Gjy8fERTevVqxe99957RKTe+7QuVHc9KyopKSFzc3PasmWLMM3X15dGjhyp7a7WSHXXs6rP3/r4fNb0uVy3bh2Zm5tTQUGBMK0+PpflqfP5sGDBAurQoYNo2pgxY8jLy0u4X9Ntp2t8eE6LMjIykJOTg8GDBwvTLC0t0atXL5w8eRIAcPLkSVhZWaFnz55Cm8GDB0NPTw+nT5+u9T5roz/x8fFISkrCu+++qzBv1qxZsLW1hYeHBzZt2gSqo2HBarKe27Ztg62tLTp27IiFCxfiyZMnotxOnTrB3t5emObl5YW8vDxcunRJ+ytSBW29vnJzc2FhYQEDA/HXU9b281lUVIT4+HjRe0pPTw+DBw8W3lMVnTx5UtQeePGcyNur8z6tbZqsZ0VPnjxBcXExrK2tRdNjYmLQtGlTuLm5YebMmXjw4IFW+14dmq5nQUEBXFxc4OzsjJEjR4reW/Xt+dTGc7lx40aMHTsWpqamoun16bnURFXvTW1sO11rFF/YW1tycnIAQPQHVH5fPi8nJwdNmzYVzTcwMIC1tbXQpjZpoz8bN26Eu7s7+vbtK5r++eef49///jdMTEzwxx9/4P3330dBQQFmz56ttf6rS9P1HD9+PFxcXODk5ITz588jICAAKSkp2LNnj5Cr7PmWz6tt2ng+79+/j2XLlmHGjBmi6XXxfN6/fx+lpaVKt/GVK1eULqPqOSn/HpRPU9WmtmmynhUFBATAyclJ9AfH29sbb7zxBlq0aIGrV6/i008/xbBhw3Dy5Eno6+trdR3Uocl6urm5YdOmTejcuTNyc3Px9ddfo2/fvrh06RKaNWtW757Pmj6XZ86cwcWLF7Fx40bR9Pr2XGpC1XszLy8PT58+xaNHj2r8PtC1Rlc0ffLJJ1i1alWlbZKTk9GuXbta6pFuqLueNfX06VNs374dS5YsUZhXflq3bt1QWFiIr776Sqt/ZHW9nuULh06dOsHR0RGDBg3C1atX0apVK41zq6u2ns+8vDz4+Pigffv2WLp0qWhebTyfTDNffvklIiIiEBMTIzpJeuzYscLvnTp1QufOndGqVSvExMRg0KBBddHVauvTpw/69Okj3O/bty/c3d3x008/YdmyZXXYM93YuHEjOnXqBA8PD9H0hvBcNgSNrmiaN28eJk+eXGmbli1bapTt4OAAALhz5w4cHR2F6Xfu3EHXrl2FNnfv3hUtV1JSgocPHwrLa4O661nT/vzyyy948uQJJk2aVGXbXr16YdmyZXj+/LnWvneottZTrlevXgCA9PR0tGrVCg4ODgpXdty5cwcA/nHPZ35+Pry9vWFubo7IyEgYGhpW2l4Xz2dFtra20NfXF7ap3J07d1Suj4ODQ6Xt1Xmf1jZN1lPu66+/xpdffokjR46gc+fOlbZt2bIlbG1tkZ6eXid/aGuynnKGhobo1q0b0tPTAdS/57Mm61hYWIiIiAh8/vnnVT5OXT+XmlD13rSwsICxsTH09fVr/PrQubo+qeqfoLongn/99dfCtNzcXKUngsfFxQltDh06VOcngmvaH09PT4WrrFT54osvqEmTJhr3tSa0td2PHTtGAOjcuXNE9PeJ4OWv7Pjpp5/IwsKCnj17pr0VUJOm65mbm0u9e/cmT09PKiwsVOuxauv59PDwoA8++EC4X1paSi+99FKlJ4K/9tproml9+vRROBG8svdpXajuehIRrVq1iiwsLOjkyZNqPcbNmzdJIpHQr7/+WuP+akqT9SyvpKSE3NzcaO7cuURUP59PTddx8+bNJJPJ6P79+1U+Rn14LsuDmieCd+zYUTRt3LhxCieC1+T1oWtcNFUiMzOTEhMThcvpExMTKTExUXRZvZubG+3Zs0e4/+WXX5KVlRX9+uuvdP78eRo5cqTSIQe6detGp0+fpmPHjlGbNm3qfMiByvpz69YtcnNzo9OnT4uWS0tLI4lEQr///rtC5r59+yg0NJQuXLhAaWlp9P3335OJiQkFBgbqfH1Uqe56pqen0+eff05xcXGUkZFBv/76K7Vs2ZL+9a9/CcvIhxwYOnQoJSUl0cGDB8nOzq7Ohxyoznrm5uZSr169qFOnTpSeni66pLmkpISI6vb5jIiIIJlMRmFhYXT58mWaMWMGWVlZCVcsTpw4kT755BOh/fHjx8nAwIC+/vprSk5OpqCgIKVDDlT1Pq1t1V3PL7/8kqRSKf3yyy+i50z++ZSfn08ff/wxnTx5kjIyMujIkSPUvXt3atOmTZ0U9HLVXc/PPvuMDh06RFevXqX4+HgaO3YsGRkZ0aVLl4Q29e35rO46yvXv35/GjBmjML2+Ppf5+fnC30UAtHbtWkpMTKTMzEwiIvrkk09o4sSJQnv5kAPz58+n5ORk2rBhg9IhByrbdnWNi6ZK+Pr6EgCFW3R0tNAG/z92jVxZWRktWbKE7O3tSSaT0aBBgyglJUWU++DBAxo3bhyZmZmRhYUFTZkyRVSI1baq+pORkaGw3kRECxcuJGdnZyotLVXI/P3336lr165kZmZGpqam1KVLF/rxxx+Vtq0t1V3PGzdu0L/+9S+ytrYmmUxGrVu3pvnz54vGaSIiun79Og0bNoyMjY3J1taW5s2bJ7pUv7ZVdz2jo6OVvs4BUEZGBhHV/fP57bffUvPmzUkqlZKHhwedOnVKmOfp6Um+vr6i9jt37qS2bduSVCqlDh060G+//Saar877tC5UZz1dXFyUPmdBQUFERPTkyRMaOnQo2dnZkaGhIbm4uND06dPrxR+f6qznnDlzhLb29vb06quvUkJCgiivPj6f1X3NXrlyhQDQH3/8oZBVX59LVZ8d8nXz9fUlT09PhWW6du1KUqmUWrZsKfr7KVfZtqtrEqI6ugacMcYYY+wfhMdpYowxxhhTAxdNjDHGGGNq4KKJMcYYY0wNXDQxxhhjjKmBiybGGGOMMTVw0cQYY4wxpgYumhhjjDHG1MBFE2OsQfvXv/6F7du313U3BJ988gk+/PDDuu4GY0wDXDQxxqpl8uTJkEgk8PPzU5g3a9YsSCSSKr9cuLbs27cPd+7cEX1DPACcOHECr776Kpo0aQIjIyN06tQJa9euRWlpaY0fc+nSpZBIJAq3I0eOAAA+/vhjbNmyBdeuXavxYzHGahcXTYyxanN2dkZERASePn0qTHv27Bm2b9+O5s2b12HPxL755htMmTIFenp/f9RFRkbC09MTzZo1Q3R0NK5cuQJ/f3988cUXGDt2LLTxJQkdOnRAdna26Pavf/0LAGBrawsvLy/88MMPNX4cxljt4qKJMVZt3bt3h7OzM/bs2SNM27NnD5o3b45u3bqJ2paVlWHlypVo0aIFjI2N0aVLF/zyyy/C/NLSUrz77rvCfDc3NwQHB4syJk+ejFGjRuHrr7+Go6MjbGxsMGvWLBQXF6vs47179/Dnn39i+PDhwrTCwkJMnz4dI0aMQEhICLp27QpXV1dMmzYNW7ZswS+//IKdO3cCAK5fvw6JRIKdO3filVdegbGxMV5++WWkpqbi7Nmz6NmzJ8zMzDBs2DDcu3dP9NgGBgZwcHAQ3aRSqTB/+PDhiIiIqMYWZ4zVB1w0McY0MnXqVGzevFm4v2nTJkyZMkWh3cqVK7F161b8+OOPuHTpEubOnYt33nkHsbGxAF4UVc2aNcOuXbtw+fJlBAYG4tNPPxWKF7no6GhcvXoV0dHR2LJlC8LCwhAWFqayf8eOHYOJiQnc3d2FaX/88QcePHiAjz/+WKH98OHD0bZtW4SHh4umBwUFYfHixUhISICBgQHGjx+PBQsWIDg4GH/99RfS09MRGBio1jaT8/DwwK1bt3D9+vVqLccYq1sGdd0Bxtg/0zvvvIOFCxciMzMTAHD8+HFEREQgJiZGaPP8+XOsWLECR44cQZ8+fQAALVu2xLFjx/DTTz/B09MThoaG+Oyzz4RlWrRogZMnT2Lnzp0YPXq0ML1Jkyb47rvvoK+vj3bt2sHHxwdRUVGYPn260v5lZmbC3t5edGguNTUVAESFVHnt2rUT2sh9/PHH8PLyAgD4+/tj3LhxiIqKQr9+/QAA7777rkLxduHCBZiZmQn327dvjzNnzgj3nZychD66uroq7QtjrP7hookxphE7Ozv4+PggLCwMRAQfHx/Y2tqK2qSnp+PJkycYMmSIaHpRUZHoMN6GDRuwadMm3LhxA0+fPkVRURG6du0qWqZDhw7Q19cX7js6OuLChQsq+/f06VMYGRkpnVed85Y6d+4s/G5vbw8A6NSpk2ja3bt3Rcu4ublh3759wn2ZTCaab2xsDAB48uSJ2v1gjNU9LpoYYxqbOnUqPvjgAwAvCp+KCgoKAAC//fYbXnrpJdE8eSERERGBjz/+GGvWrEGfPn1gbm6Or776CqdPnxa1NzQ0FN2XSCQoKytT2TdbW1s8evRINK1t27YAgOTkZPTt21dhmeTkZLRv317l40okEqXTKvZDKpWidevWKvv28OFDAC8KT8bYPwcXTYwxjXl7e6OoqAgSiUQ4hFVe+/btIZPJcOPGDXh6eirNOH78OPr27Yv3339fmHb16tUa961bt27IycnBo0eP0KRJEwDA0KFDYW1tjTVr1igUTfv27UNaWhqWLVtW48euysWLF2FoaIgOHTro/LEYY9rDRRNjTGP6+vpITk4Wfq/I3NwcH3/8MebOnYuysjL0798fubm5OH78OCwsLODr64s2bdpg69atOHToEFq0aIH//Oc/OHv2LFq0aFGjvnXr1g22trY4fvw4XnvtNQCAqakpfvrpJ4wdOxYzZszABx98AAsLC0RFRWH+/Pl46623ROdR6cpff/0lXJHHGPvn4KvnGGM1YmFhAQsLC5Xzly1bhiVLlmDlypVwd3eHt7c3fvvtN6Eoeu+99/DGG29gzJgx6NWrFx48eCDa66QpfX19TJkyBdu2bRNNf+uttxAdHY0bN27glVdegZubG9atW4dFixYhIiJCOASnSxERESpPYGeM1V8S0sZIbowxVg/l5OSgQ4cOSEhIgIuLS113BwDw+++/Y968eTh//jwMDHhnP2P/JLyniTHWYDk4OGDjxo24ceNGXXdFUFhYiM2bN3PBxNg/EO9pYowxxhhTA+9pYowxxhhTAxdNjDHGGGNq4KKJMcYYY0wNXDQxxhhjjKmBiybGGGOMMTVw0cQYY4wxpgYumhhjjDHG1MBFE2OMMcaYGrhoYowxxhhTAxdNjDHGGGNq4KKJMcYYY0wNXDQxxhhjjKmBiybGGGOMMTVw0cQYY4wxpgYumhhjjDHG1MBFE2OMMcaYGrhoYowxxhhTAxdNjDHGGGNq4KKJMcYYY0wNXDQxxhhjjKmBiybGGGOMMTVw0cT+0SZPnoylS5fWdTcahaVLl6Jr167C/cmTJ2PUqFF11h9tICLMmDED1tbWkEgkSEpKqusuMS3ZsGEDXF1dYWRkhF69euHMmTOi+SEhIRgwYAAsLCwgkUjw+PFjpTn79++Hp6cnzM3NYWJigpdffhlhYWHV6kt13is3btyAj48PTExM0LRpU8yfPx8lJSXC/D179mDIkCGws7ODhYUF+vTpg0OHDink3Lx5E1OnToWTkxOkUilcXFzg7++PBw8eqN3vmJiYSrdN+XYjR46Eo6MjTE1N0bVrV2zbtk2h3a5du9CuXTsYGRmhU6dOOHDggDCvuLgYAQEB6NSpE0xNTeHk5IRJkyYhKytLlOHq6gqJRCK6ffnll2qvU01x0cQE6r5BGoqTJ09CX18fPj4+CvOuX78OiUQCfX193L59WzQvOzsbBgYGkEgkuH79ujA9MjISvXv3hqWlJczNzdGhQwfMmTNHmF+x6Kj4WOr8wa6sz7UtODi42n886puDBw8iLCwM+/fvR3Z2Njp27FjXXcKAAQNU/iHw8fGBRCKp1j8KYWFhsLKy0l4H1ZCXl4dFixYJfyAdHBwwePBg7NmzB0Sk88ffsWMHPvroIwQFBSEhIQFdunSBl5cX7t69K7R58uQJvL298emnn6rM+fbbbzFy5Ej069cPp0+fxvnz5zF27Fj4+fnh448/1nq/S0tL4ePjg6KiIpw4cQJbtmxBWFgYAgMDhTZHjx7FkCFDcODAAcTHx2PgwIEYPnw4EhMThTbXrl1Dz549kZaWhvDwcKSnp+PHH39EVFQU+vTpg4cPH2q13ydOnEDnzp2xe/dunD9/HlOmTMGkSZOwf/9+UZtx48bh3XffRWJiIkaNGoVRo0bh4sWLAF48HwkJCViyZAkSEhKwZ88epKSkYMSIEQqP9/nnnyM7O1u4ffjhh1pdn0oRY/8vOjqaANCjR4/quitq8/X1paCgII2Wfffdd8nf35/MzMzo9u3bonkZGRkEgJydnWnFihWieStXrqTmzZsTAMrIyCAioiNHjpChoSGtXr2arly5QikpKRQZGUnvv/++sFxQUBB16dJFoR/yx0pMTKxRn9Xx/Pnzai8jp6r//2TffvstNW/evNI2NdlmmvD09CRnZ2dyc3MTTb916xbJZDJydHSs1mt+8+bNZGlpqd1OVuLRo0fUoUMHatasGYWFhdGlS5coJSWFQkJCqFWrVrXy+eLh4UGzZs0S7peWlpKTkxOtXLlSoa2qz70bN26QoaEhffTRRwrLfPPNNwSATp06JUy7ePEi+fj4kLm5OZmZmVH//v0pPT2dgoKCCIDoFh0drbTfBw4cID09PcrJyRGm/fDDD2RhYVHp67B9+/b02WefCfe9vb2pWbNm9OTJE1G77OxsMjExIT8/P2Has2fPaMGCBdSsWTOSSqXUqlUr+vnnn4XPpfI3X19flX2o6NVXX6UpU6YI90ePHk0+Pj6iNr169aL33ntPZcaZM2cIAGVmZgrTXFxcaN26dWr3Q9saTdH0+++/U79+/cjS0pKsra3Jx8eH0tPThfnyF8iOHTuof//+ZGRkRD179qSUlBQ6c+YM9ejRg0xNTcnb25vu3r0rLBcdHU0vv/wymZiYkKWlJfXt25euX79ORC/+oI8cOVLUD39/f/L09FS7X8rI3+QHDx6krl27kpGREQ0cOJDu3LlDBw4coHbt2pG5uTmNGzeOCgsLheVKS0tpxYoV5OrqSkZGRtS5c2fatWuXaP2VvUGePXtGH374IdnZ2ZFMJqN+/frRmTNnFPqzf/9+6tSpE8lkMurVqxdduHChyudl37591LNnT5LJZGRjY0OjRo2qcpnyNC2a8vPzyczMjK5cuUJjxoyh5cuXi+bLt8fixYupTZs2onlt27alJUuWiIomf39/GjBgQKWPWdOiqao+K+Pi4kKff/45TZw4kczNzYXndMGCBdSmTRsyNjamFi1a0OLFi6moqEi07MqVK6lp06ZkZmZGU6dOpYCAAFH/K76+1X2P7d69mwYMGEDGxsbUuXNnOnHihOhxjx07Rp6enmRsbExWVlY0dOhQevjwIRFV/homInr48CGNHz+ebG1tycjIiFq3bk2bNm1Sum18fX1Fr3cXFxcielG0zJo1i/z9/cnGxkZ4XmNiYujll18mqVRKDg4OFBAQQMXFxUKep6cnffDBB+Tv709WVlbUtGlTCgkJoYKCApo8eTKZmZlRq1at6MCBA5U+Z56enjRz5kyysbGhY8eOCdOXL19Ow4cPpy5duohe88+ePaN58+aRk5MTmZiYkIeHh/BHWf7eLH+TL/vw4UOaOHEiWVlZkbGxMXl7e1NqaqqQKy+2IiMjqXXr1iSTyWjo0KF048aNSvs/c+ZMMjU1VVrU5+fni7aZLjx//pz09fUpMjJSNH3SpEk0YsQIhfaqiqa1a9cSAMrKylL6GGZmZuTv709ELwpaa2treuONN+js2bOUkpJCmzZtoitXrlB+fj6NHj2avL29KTs7m7Kzs1UWQEuWLFH4jLh27RoBoISEBKXLlJaWkrOzM3377bdERPTgwQOSSCQK/+zJTZ8+nZo0aUJlZWVE9KKYcXZ2pj179tDVq1fpyJEjFBERQSUlJbR7924CQCkpKZSdnU2PHz9WmqlMv379aN68ecJ9Z2dnhWInMDCQOnfurDLj8OHDJJFIKDc3V5jm4uJC9vb2ZG1tTV27dqXVq1fr/DVVXqMpmn755RfavXs3paWlUWJiIg0fPpw6depEpaWlRPT3B3q7du3o4MGDdPnyZerduzf16NGDBgwYQMeOHaOEhARq3bq1UKUXFxeTpaUlffzxx5Senk6XL1+msLAwoSpWp2iqql/KyN/kvXv3FvXL09OThg4dSgkJCXT06FGysbGhL7/8Uljuiy++ENbv6tWrtHnzZpLJZBQTE1PpG2T27Nnk5OREBw4coEuXLpGvry81adKEHjx4IOqPu7s7/fHHH3T+/Hl67bXXyNXVVeEPcXn79+8nfX19CgwMpMuXL1NSUpLKN7oqmhZNGzdupJ49exIR0f/+9z9q1aqV8CFC9Pfr4cyZM2Rra0t//fUXERH99ddfZGdnJ/wHJC+aVq5cSXZ2dpUWijUtmqrqszIuLi5kYWFBX3/9NaWnpwtFzLJly+j48eOUkZFB+/btI3t7e1q1apWw3I4dO0gmk9HPP/9MV65coUWLFpG5uXmlRVN13mP79++nlJQUeuutt8jFxUX40EtMTCSZTEYzZ86kpKQkunjxIn377bd07949Iqr8NUxENGvWLOratSudPXuWMjIy6PDhw7Rv3z6l2+bx48f0+eefU7NmzSg7O1v4Z8jT05PMzMxo/vz5dOXKFbpy5QrdunWLTExM6P3336fk5GSKjIwkW1tb0WvP09OTzM3NadmyZZSamkrLli0jfX19GjZsGIWEhFBqaqpQDJX/Z6YiT09P8vf3p9mzZ9O7774rTG/Tpg1FRkYqFE3Tpk2jvn370tGjRyk9PZ2++uorkslklJqaSs+fP6f169eThYWF8Ac7Pz+fiIhGjBhB7u7udPToUUpKSiIvLy9q3bq18J7dvHkzGRoaUs+ePenEiRMUFxdHHh4e1LdvX5V9Ly0tpSZNmtCMGTNUttG127dvEwCFYnz+/Pnk4eGh0F5V0eTn51fpHrrOnTvTsGHDiIho4cKF1KJFC5Wfd8r+Figzffp0Gjp0qGhaYWEhAVBZbK9atYqaNGlCd+7cISKiU6dOEQCFolFOXgzeuXOHUlJSCAAdPnxYaVtNjz7s2LGDpFIpXbx4UZhmaGhI27dvF7XbsGEDNW3aVGnG06dPqXv37jR+/HjR9DVr1lB0dDSdO3eOfvjhB7KysqK5c+dWq3810WiKporu3btHAIQ/cvIP9J9//lloEx4eTgAoKipKmLZy5Upht/mDBw8IgPCBXZE6RVNV/VJG/kI+cuSIqF8A6OrVq8K09957j7y8vIjoxX+jJiYmCh8k7777Lo0bN06UW/4NUlBQQIaGhrRt2zZhWlFRETk5OdHq1atFy0VERAhtHjx4QMbGxrRjxw6V69GnTx+aMGGCyvnq0LRo6tu3L61fv56IXhS/tra2ol3m5QuZOXPmCLuZp0yZQnPnzqXExERR0VRQUECvvvqqsMdizJgxtHHjRnr27JmQWdOiqao+K+Pi4qLW3ruvvvqKevToIdzv06eP6NAi0Ytd6ZUVTRWp8x67dOkSAaDk5GQiIho3bhz169dPaZ46r+Hhw4eLDglUZd26dcIeJjlPT0/q1q2baNqnn35Kbm5uoiJ1w4YNZGZmJhSFnp6e1L9/f2F+SUkJmZqa0sSJE4Vp2dnZBIBOnjypsk/yoikpKYnMzc2poKCAYmNjqWnTplRcXCwqmjIzM0lfX19hr86gQYNo4cKFRKT88FxqaioBoOPHjwvT7t+/T8bGxrRz505huYqHoJKTkwkAnT59Wmnf79y5QwBo7dq1KtdP1+qiaBo2bBhNmjRJZVtl7xVvb28yNTUlU1NTat++PRFVv2jatm0bmZiYiIoeedG0Z88epX0pXzTt2LGD9PX1VRZ7mhRNf/75J5mYmNCWLVtE06tTNBUVFdHw4cOpW7duor1MymzcuJEMDAxEn7W61GhOBE9LS8O4cePQsmVLWFhYwNXVFcCLKxXK69y5s/C7vb09AKBTp06iafKTCa2trTF58mR4eXlh+PDhCA4ORnZ2tlb7NWzYMJiZmcHMzAwdOnSotK8mJiZo2bKl0r6mp6fjyZMnGDJkiJBnZmaGrVu34urVqyr7d/XqVRQXF6Nfv37CNENDQ3h4eCA5OVnUtk+fPsLv1tbWcHNzE9qUf0w/Pz8AQFJSEgYNGqT2ttKWlJQUnDlzBuPGjQMAGBgYYMyYMdi4caPS9lOnTsWuXbuQk5ODXbt2YerUqQptTE1N8dtvvyE9PR2LFy+GmZkZ5s2bBw8PDzx58qRa/VO2rarb5/J69uypMG3Hjh3o168fHBwcYGZmhsWLF4veC8nJyejVq5domfLPrzKavMccHR0BQHidVvaaUOc1PHPmTERERKBr165YsGABTpw4UWmfVenRo4fofnJyMvr06QOJRCJM69evHwoKCnDr1i2l66avrw8bGxuFz4/y61uZLl26oE2bNvjll1+wadMmTJw4EQYGBqI2Fy5cQGlpKdq2bSvaJrGxsZW+r5OTk2FgYCB6jm1sbETvWeDF6+zll18W7rdr1w5WVlZITk7GjRs3RI+5YsWKWjnJuyq2trbQ19fHnTt3RNPv3LkDBwcHtXPatm2L3Nxchau3AKCoqAhXr15F27ZtAQDGxsbV7ufPP/+MpKQkJCUlCVeROTg4KO23fF55ERERmDZtGnbu3InBgwcL01u3bg2JRKLw+SyXnJyMJk2awM7OTqN+VyY2NhbDhw/HunXrMGnSJNE8VetWcb2Ki4sxevRoZGZm4vDhw7CwsKj0MXv16oWSkhLRRTm6ZFB1k4Zh+PDhcHFxQWhoKJycnFBWVoaOHTuiqKhI1M7Q0FD4Xf4BWXFaWVmZcH/z5s2YPXs2Dh48iB07dmDx4sU4fPgwevfuDT09PYUPkeLi4mr16+eff8bTp08V+qGsXxXnl+9rQUEBAOC3337DSy+9JGonk8mUbjNtKn9lmPxNoO03rLo2btyIkpISODk5CdOICDKZDN999x0sLS1F7Tt16oR27dph3LhxcHd3R8eOHVVe6daqVSu0atUK06ZNw6JFi9C2bVvs2LEDU6ZMgYWFBXJzcxWWkV+tKH9cZduqun0uz9TUVHT/5MmTmDBhAj777DN4eXnB0tISERERWLNmjcoMddTkPSZ/nVb2mlDnNTxs2DBkZmbiwIEDOHz4MAYNGoRZs2bh66+/rta6VNxm6lL2HqxsfasydepUbNiwAZcvX1a4ZB54sU309fURHx8PfX190TwzM7Pqdr9anJycRK9Va2trWFlZwcrKCleuXNHpY1dGKpWiR48eiIqKEi7zLysrQ1RUFD744AO1c958800EBARgzZo1Cu+NH3/8EYWFhcI/MZ07d8aWLVtQXFys8BqQ96m0tFQ0reJrGHjxj8ny5ctx9+5dNG3aFACEwqF9+/ZCu/DwcEydOhUREREKV9La2NhgyJAh+P777zF37lzReyonJwfbtm3DpEmTIJFI0KlTJ5SVlSE2NlZUeJXvNwCFvisTExOD1157DatWrcKMGTOUrltUVJToiuLDhw+L/hmTF0xpaWmIjo6GjY1NlY+blJQEPT09YXvpWqPY0/TgwQOkpKRg8eLFGDRoENzd3fHo0SOt5Xfr1g0LFy7EiRMn0LFjR2zfvh0AYGdnp7DnqfyHjDr9eumll9C6dWu0bt0aLi4uGvexffv2kMlkuHHjhpAnvzk7OwNQ/gZp1aoVpFIpjh8/LkwrLi7G2bNnRW9iADh16pTw+6NHj5Camgp3d3cAED2e/MXduXNnREVFabxOmigpKcHWrVuxZs0a4b+8pKQknDt3Dk5OTggPD1e63NSpUxETE6N0L5Mqrq6uMDExQWFhIQDAzc0Nt27dUvhvKyEhAUZGRmjevDkAxW2laZ9VOXHiBFxcXLBo0SL07NkTbdq0QWZmpqiNu7s7Tp8+LZpW/vmtSFvvscpeE+q8hoEX7ztfX1/897//xfr16xESElLtflTk7u6OkydPiv4JOn78OMzNzdGsWbMa56syfvx4XLhwAR07dlR4vwEvPntKS0tx9+5dhW0i/w9e2R9sd3d3lJSUiJ5j+XNY/nFKSkoQFxcn3E9JScHjx4/h7u4OAwMD0eNZW1tDT08PY8eOxbZt25TuoSkoKBCNOaQrH330EUJDQ7FlyxYkJydj5syZKCwsxJQpU4Q2OTk5SEpKQnp6OoAXe+2SkpKEy/GbN2+O1atXY/369Vi0aBGuXLmCq1evYu3atViwYAHmzZsn7Kn74IMPkJeXh7FjxyIuLg5paWn4z3/+g5SUFAAvPgvOnz+PlJQU3L9/X+GfZ7mhQ4eiffv2mDhxIs6dO4dDhw5h8eLFmDVrlvCPwfbt2zFp0iSsWbMGvXr1Qk5ODnJyckT/kH333Xd4/vw5vLy8cPToUdy8eRMHDx7EkCFD8NJLL2H58uVCv3x9fTF16lTs3bsXGRkZiImJwc6dOwEALi4ukEgk2L9/P+7duyf841JRdHQ0fHx8MHv2bLz55ptCn8oPbeDv74+DBw9izZo1uHLlCpYuXYq4uDihkC0uLsZbb72FuLg4bNu2DaWlpUKO/B+vkydPYv369Th37hyuXbuGbdu2Ye7cuXjnnXfQpEmT6rxENFcrBwHrWGlpKdnY2NA777xDaWlpFBUVRS+//LLoZDll55UoO55b/vyAa9eu0SeffEInTpyg69ev06FDh8jGxoa+//57IiI6ePAgSSQS2rJlC6WmplJgYCBZWFgI5zSp0y9lquqXXMVzaBYtWkQ2NjYUFhZG6enpFB8fT9988w2FhYUR0YsrQCQSCYWFhdHdu3eFE0b9/f3JycmJfv/9d9GJ4PIrmuT96dChAx05coQuXLhAI0aMoObNm1d6mWx0dDTp6ekJJ4KfP39edOK6Oqp7TlNkZCRJpVKlV4EsWLBAONG64uuhuLiY7t27JzphGeXOaQoKCqL58+dTdHQ0Xbt2jRISEmjy5MlkbGxMV65cETI6dOhAAwcOpOPHj9PVq1dp165d5OjoSAEBATXuszLKLs/99ddfycDAgMLDwyk9PZ2Cg4PJ2tpa9PqJiIggIyMj2rRpE6WkpFBgYGClJ4Jr+h579OiR6BLslJQUkkqlNHPmTDp37hwlJyfT999/L5wIXtVreMmSJbR3715KS0ujixcv0muvvab0PBY5Vec0ya+KkpOfCD5r1ixKTk6mvXv3Kj0RvOJyyrZ/Ve/vijmPHj2igoIC4X7FE8EnTJhArq6utHv3brp27RqdPn2aVqxYQfv37yciouPHjwvnQN67d084CX3kyJHUvn17+uuvvygpKYm8vb2Vngju4eFBp06dori4OOrduzf17t1bZd+JXpzP2K5dO2rWrBlt2bKFLl26RKmpqbRx40Zq3bp1rQ1pIh9OQiqVCutQnrKhAADQ5s2bRe1+/fVXeuWVV8jU1JSMjIyoR48eSq/IPHfuHA0dOpRMTEzI3NycXnnlFeEc07t379KQIUPIzMys0iEHiIiuX79Ow4YNI2NjY7K1taV58+YpXKWprN8VhwO4fv06+fr6kr29PRkaGpKzszN9+OGHdP/+fVG7p0+f0ty5c8nR0ZGkUqnCFaeff/45OTg4kEQiUTnkQMUrUeW3iufv7ty5k9q2bUtSqZQ6dOhAv/32mzBP2RXc8pt8e8XHx1OvXr3I0tKSjIyMyN3dnVasWFFr5zMRNaITwQ8fPkzu7u4kk8moc+fOFBMTU+OiKScnh0aNGiW82FxcXCgwMFB05VtgYCDZ29uTpaUlzZ07lz744APRC6mqfimjadFUVlZG69evJzc3NzI0NCQ7Ozvy8vKi2NhYoY2yN8jTp0/pww8/JFtb20qHHPjf//5HHTp0ED6kzp07p3Id5Hbv3k1du3YlqVRKtra29MYbb1S5THnVLZpee+01evXVV5XOO336NAGgc+fOVXlydsWi6c8//6Q333yTnJ2dSSqVkr29PXl7ewtX3cndvn2bfH19qXnz5mRsbEzt27enL7/8stKrDNXtszKqxjSZP38+2djYkJmZGY0ZM4bWrVun8PpZvnw52drakpmZGfn6+tKCBQsqPRFck/dYxaKJ6MWl/X379iWZTEZWVlbk5eUlvNareg0vW7aM3N3dydjYmKytrWnkyJF07do1pduGSP2iSd6vqoYc0EXRVFHFoqmoqIgCAwPJ1dWVDA0NydHRkV5//XU6f/680MbPz49sbGyUDjlgaWlJxsbG5OXlpXTIgd27d1PLli1JJpPR4MGDRWPmqPL48WP65JNPqE2bNsL7YfDgwRQZGVnlFZ+M1WcSonpw5h77R4uJicHAgQPx6NGjWh95ePLkyXB1deWvUmFMy8LCwjBnzpxG8w0BjKmjUZzTxBhjjDFWU1w0McYYY4ypgQ/PsX+0vXv3wsrKCgMGDKjrrjDGGGvguGhijDHGGFMDH55jjDHGGFNDgx8RvKysDFlZWTA3Nxd9BQJjjDHGGg4iQn5+PpycnKCnp5t9Qg2+aMrKyhKNFswYY4yxhuvmzZs6G6m/Toumo0eP4quvvkJ8fDyys7MRGRkpfFcQ8GIMni1btoiW8fLywsGDB9V+DHNzcwDAqlWrhCHvz507h8mTJwMACgsLERwcDH9/f+zatQtdunRBt27dAACJiYk4d+4c3n77baGN/DupwsLC0KVLF87jPM7jPM7jPM6rB3k5OTlwc3MT/u7rRB0OrEkHDhygRYsW0Z49e5SOkuvr60ve3t6UnZ0t3ORf3aGu3NxcAkC5ubnk5+dHfn5+Cm0KCgrIyclJNDK2XGxsLDk5OYm+xkCO8ziP8ziP8ziP8+pHXvm/97pSpyeCDxs2DF988QVef/11lW1kMhkcHByEm6ZfypeYmIju3buje/fuiI+PF83bvn07wsPDERUVJXy5KvCiCo6KikJ4eLjwJbxy8fHxnMd5nMd5nMd5nFeP8nROZ+VYNUHFniZLS0uys7Ojtm3bkp+fn8KXDVb07Nkzys3NFW43b94kABQcHCy0CQkJobi4OIXfCwoKKDAwkAoKCkS/ExHFxcVRSEiIwu+cx3mcx3mcx3mcV/d5wcHBOt/TVK+LpvDwcPr111/p/PnzFBkZSe7u7vTyyy9TSUmJyhxV31xdcSOGhISQn5+fsLHlCgoKaN68eTRv3jyFXYJxcXHk5+cnesI4j/M4j/M4j/M4r+7z5F8SrsuiqV5fPTd27Fjh906dOqFz585o1aoVYmJiMGjQIKXLLFy4EB999JFwPy8vj6+eY4wxxljN6awcqyYo2dOkjK2tLf34449q58pPDOPDc5zHeZzHeZzHeQ03rzYOz9Wbr1GRSCQKQw5UdOvWLTRv3hx79+7FiBEj1MrNy8uDpaUlYmJikJqaCgDo3r07evToIbQJDQ2Fm5sboqKisGDBAuGyxsLCQqxevRqDBg1CSkoKpk+fLiwTHx+PhIQEzuM8zuM8zuM8zqsHefK/97m5ubCwsIBO6KwcU0N+fj4lJiZSYmIiAaC1a9dSYmIiZWZmUn5+Pn388cd08uRJysjIoCNHjlD37t2pTZs29OzZM7Ufg4cc4DzO4zzO4zzOa/h5tTHkQJ0WTdHR0UpP2vb19aUnT57Q0KFDyc7OjgwNDcnFxYWmT59OOTk51XqM8ofn4uLiFHbtld8NWH43H9HfuwEr7iok+nuXIOdxHudxHudxHufVfV5WVlbDLppiY2PptddeI0dHxyrPaXrvvfcIAK1bt65ajyEvmmJiYoRp9eHJ5TzO4zzO4zzO4zzt5QUEBDTsoqmqEcHl9uzZQ126dCEnJyeNi6aKG7GudyNyHudxHudxHudxnvbyamNPU70fEfz27dv48MMPsW3bNhgaGmr8WPVx5FLO4zzO4zzO4zzO007erl27oHM6K8eqCUr2NJWWltLAgQNp/fr1RETk4uJS5Z4mVSOCBwQEUEFB/bk0kvM4j/M4j/M4j/O0l1cbg1vW66JpxYoVNGTIECorKyMi9YomVSOCZ2Vl1auRSzmP8ziP8ziP8zhPe3kN/gt7KxMfH4/g4GCEhYVBIpGovdzChQuRm5sr3G7evKnDXjLGGGOs0dBZOVZNqLCnad26dSSRSEhfX1+4ASA9PT1ycXFRO1deefLhOc7jPM7jPM7jvIabVxuH5+rtiOAPHjxAdna2qI2XlxcmTpyIKVOmwM3NTa1c+QihWVlZcHR0BFA/Ri7lPM7jPM7jPM7jPO3lJSUlwd/fv3GOCK6MOuc0VcRDDnAe53Ee53Ee5zX8vNoYcqBO9zQFBwdjzpw5CtN9fX0RFhaGpUuXIiIiAjdv3oRUKsWzZ8/g5+eHdevWqf0Y8j1Ne05fhamZuRZ733g9el5U111ocPSrcd4eU48eb1OtMtDj7altz0vL6roLDcqTgnxMfqWdTvc01emJ4G3btsWiRYuwZ88eAEBkZCSICGFhYcL87777DhcuXMCxY8cwYcIEbNq0Cffu3avDXjPGGGOsMaq35zQpI99rdOTIEQwaNEitXN7TpH28p0n7eE+T9vGeJu3iPU3ax3uatKvB72mqjqKiIoSEhMDS0hJdunSp6+4wxhhjrJExqOsOVGX//v0YO3Ysnjx5AkdHRxw+fBi2trYq2z9//hzPnz8X7ufl5dVGNxljjDHWwNX7PU0DBw5EUlISTpw4AW9vb4wePRp3795V2X7lypWwtLQUbs7OzrXYW8YYY4w1VPW+aDI1NUXr1q3Ru3dvbNy4EQYGBti4caPK9jwiOGOMMcZ0od4fnquorKxMdPitIplMBplMVos9YowxxlhjUKdFU0FBAdLT04X7GRkZSEpKgrW1NWxsbLB8+XKMGDECjo6OuH//PjZs2IDbt2/j7bffrsNeM8YYY6wxqtOiKS4uDgMHDhTuf/TRRwBeDG75448/4sqVK9iyZQvu378PGxsbvPzyy/jrr7/QoUOHuuoyY4wxxhqpOi2a9PT08NprryE+Ph7Z2dmicZqKi4vRpk0bpKWl4fHjxwAAS0tLvPTSSxo9lo2xFGYmfNhOGyxlhnXdBcYY+8crKasXwyQ2GIVUrPPHqNMTwQsLC9GlSxds2LBBYd6TJ0+QkJCAJUuWICEhAXv27EFKSgpGjBhRBz1ljDHGWGNXp3uahg0bhmHDhimdZ2lpicOHD4umfffdd/Dw8MCNGzfQvHnz2ugiY4wxxhiAf9jVc7m5uZBIJLCyslLZhge3ZIwxxpgu1PtxmuSePXuGgIAAjBs3rtLvlOHBLRljjDGmC/+Ioqm4uBijR48GEeGHH36otC0PbskYY4wxXaj3h+fkBVNmZib+/PPPKr+5mAe3ZIwxxpgu1OuiSV4wpaWlITo6GjY2NnXdJcYYY4w1UvV2RHBHR0e89dZbSEhIwP79+1FaWoqcnBwAgLW1NaRSaV11mzHGGGONkISI6mx0rZiYGNGI4HK+vr5YunQpWrRooXS56OhoDBgwQK3HyMvLg6WlJeJSs2FmXvmhPaaeMh6QTev09CR13YUGh1+n2sVbU/v4Xa9dBfl58GjnhNzc3CpP5dFUnZ4ILh8R3NHREQAQGRkJIkJYWBhcXV2xe/duDBkyBNbW1gCAxMREEJHaBRNjjDHGmLbU2xHB5fP79++PVatW1XLPGGOMMcbE6u2I4AAwceJEAMD169drqUeMMcYYY8rV66vnNMEjgjPGGGNMFzQ6PPf06VM8efJEuJ+ZmYn169fjjz/+0FrHNMUjgjPGGGNMFzQqmkaOHImtW7cCAB4/foxevXphzZo1GDlyZJUjdusajwjOGGOMMV3QqGhKSEjAK6+8AgD45ZdfYG9vj8zMTGzduhXffPONVjtYXTKZDBYWFqIbY4wxxlhNaVQ0PXnyBObm5gCAP/74A2+88Qb09PTQu3dvZGZmarWDjDHGGGP1gUYngrdu3Rp79+7F66+/jkOHDmHu3LkAgLt371Zrz05lI4I3b94cDx8+xI0bN5CVlQUASElJAQA4ODjAwcFBk64zxhhjjGlEoxHBf/nlF4wfPx6lpaUYNGiQcAL4ypUrcfToUfz+++9q5VQ2InhYWBjCwsIwZcoUhflBQUFYunSpWo8hHxH8/LU7MOcRwVk9JeGhgVk9V8ojrLN6Lj8/D11bOeh0RHCN9jS99dZb6N+/P7Kzs9GlSxdh+qBBg/D666+rnSMfETw+Ph7Z2dmIjIzEqFGjhPm+vr64du0aQkND8fjxY/Tr1w8//PAD2rRpo0m3GWOMMcY0pvGI4A4ODujWrRv09P6O8PDwQLt27dTOqGpE8NWrV+Obb77Bjz/+iNOnT8PU1BReXl549uyZpt1mjDHGGNOI2nua3njjDbVD9+zZo1a7ykYEJyKsX78eixcvxsiRIwEAW7duhb29Pfbu3YuxY8eq3R/GGGOMsZpSu2iytLTUZT8UZGRkICcnB4MHDxb1oVevXjh58qTKoolHBGeMMcaYLqhdNG3evFmX/VCQk5MDALC3txdNt7e3F+Yps3LlSnz22Wc67RtjjDHGGh+Nz2kqKSnBkSNH8NNPPyE/Px8AkJWVhYKCAq11ThM8IjhjjDHGdEGjq+cyMzPh7e2NGzdu4Pnz5xgyZAjMzc2xatUqPH/+HD/++GONOyYfh+nOnTtwdHQUpt+5cwddu3ZVuZxMJoNMJqvx4zPGGGOMlafRniZ/f3/07NkTjx49grGxsTD99ddfR1RUlFY61qJFCzg4OIjy8vLycPr0afTp00crj8EYY4wxpi6N9jT99ddfOHHiBKRSqWi6q6srbt++rXZOVSOCz5kzB1988QXatGmDFi1aYMmSJXBychKN5cQYY4wxVhs0KprKyspQWlqqMP3WrVvCd9KpIy4uTjQi+EcffQTg7xHBFyxYgMLCQsyYMQOPHz9G//79cfDgQRgZGVW7z/oSCfT1eNhlxhoLHmWd1XcSfpFqlYGexqdpq02jRxg6dCjWr18v3JdIJCgoKEBQUBBeffVVtXMGDBgAIlK4hYWFCbnz58/H2LFjYW9vj+PHj2Py5Mk4e/asJt1mjDHGGNOYRkXTmjVrcPz4cbRv3x7Pnj3D+PHjhUNzq1at0moHp02bhsOHD+M///kPLly4gKFDh2Lw4MHVOgzIGGOMMVZTGn1hL/BiyIGIiAicP38eBQUF6N69OyZMmCA6Mbymnj59CnNzc/z666/w8fERpvfo0QPDhg3DF198UWWG/At7L2XchbmOvsCPMVb/8JEP7eIv7NU+PjynXfl5eejYomn9+8JeADAwMMA777yjzb4oKCkpQWlpqcI5TMbGxjh27JjSZXhEcMYYY4zpgsZFU1paGqKjo3H37l2UlZWJ5gUGBta4YwBgbm6OPn36YNmyZXB3d4e9vT3Cw8Nx8uRJtG7dWukyPCI4Y4wxxnRBo8NzoaGhmDlzJmxtbeHg4CDaxSiRSJCQkKC1Dl69ehVTp07F0aNHoa+vj+7du6Nt27aIj49HcnKyQntle5qcnZ358BxjjQwf+dAuPjynfXx4Trtq4/CcRkWTi4sL3n//fQQEBOiiT0oVFhYiLy8Pjo6OGDNmDAoKCvDbb79VuRyf08RY48R/j7SLiybt46JJu2qjaNLo6rlHjx7h7bff1nZfKmVqagpHR0c8evQIhw4dwsiRI2v18RljjDHWuGlUNL399tv4448/tN0XpQ4dOoSDBw8iIyMDhw8fxsCBA9GuXTtMmTKlVh6fMcYYYwwAQBpYsWIF2drakq+vL3399dcUHBwsumnTjh07qGXLliSVSsnBwYFmzZpFjx8/Vnv53NxcAkC5ubnk5+dHfn5+Cm0KCgrIycmJYmNjFebFxsaSk5MTFRQUKMzjPM7jPM7jPM7jvPqRV/7vva5otKcpJCQEZmZmiI2NxXfffYd169YJt/IjhddUaWkpLly4gLKyMujp6cHExAT29vYaHasMCwvDtGnTMG3aNISGhgrTCwsLsXr1aqSmpiIlJQXx8fHCvPj4eKSkpCA1NRWrV69GYWGhMC80NJTzOI/zOI/zOI/z6lGezumsHNOC5cuXk42NDe3fv58yMjJo165dZGZmVq29WfLKMyYmRpgWFxdHISEhVFBQQIGBgaIqNiQkhOLi4oQ2cuXbyttwHudxHudxHudxXv3ICwgI0PmepnpdNPn4+NDUqVNF09544w2aMGGC2hmqdtfV9W5EzuM8zuM8zuM8ztNeXlZWVv08PFdaWoqNGzdi/PjxGDx4MP7973+LbtrSt29fREVFITU1FQBw7tw5HDt2DMOGDVO5zPPnz5GXlye6AeLddoWFhYiKikJ4eDi2b98uWj4+Ph7du3dH9+7dRbsKAWD79u0IDw9HVFQU53Ee53Ee53Ee59WjvF27dkHnNKm0Zs2aRaampjR69Gjy9/enOXPmiG7aUlpaSgEBASSRSMjAwIAkEgmtWLGi0mWCgoIIgMItICCACgoKFHYJlt8NWHGXYPndgOV/L5/BeZzHeZzHeZzHeXWfFxMTUz8Pz9nY2NBvv/2m7b4oCA8Pp2bNmlF4eDidP3+etm7dStbW1hQWFqZymWfPnlFubq5wu3nzJgGgrKwsmjdvHs2bN09hl2BcXBz5+fmJnjC5kJAQ8vPzEx1DJXrxxHEe53Ee53Ee53Fe/cirjavnNPruOalUqvK737Rp/vz5+OSTTzB27FgAQKdOnZCZmYmVK1fC19dX6TIymQwymUznfWOMMcZYI6NJpfX111/T+++/T2VlZdou4kSsra3p+++/F01bsWIFtWnTRu0MeeXJh+c4j/M4j/M4j/Mabl5tHJ7T6LvnXn/9dURHR8Pa2hodOnSAoaGhaP6ePXu0UtBNnjwZR44cwU8//YQOHTogMTERM2bMwNSpU7Fq1Sq1MuTfPZeVlQVHR0cAf48NMWjQIKSkpGD69OlC+/j4eOELh7t3744ePXoI80JDQ+Hm5oaoqCgsWLAApqamnMd5nMd5nMd5nFcP8pKSkuDv71//vrC3qq8w2bx5s8YdKi8/Px9LlixBZGQk7t69CycnJ4wbNw6BgYGQSqVqZciLposZd2Buzl/Yy1ijwV+GylijUhtf2KtR0VSbXF1dkZmZqTD9/fffx4YNG6pcnosmxhopLpoYa1Rqo2jS6ETw2nT27FmUlpYK9y9evIghQ4bg7bffrsNeMcYYY6yx0bho+uWXX7Bz507cuHEDRUVFonnyY5LaYGdnJ7r/5ZdfolWrVvD09NTaYzDGGGOMVUWjEcG/+eYbTJkyBfb29khMTISHhwdsbGxw7dq1SkfrrqmioiL897//xdSpUyFRsetd1YjgjDHGGGM1oVHR9P333yMkJATffvstpFIpFixYgMOHD2P27NnIzc3Vdh8Fe/fuxePHjzF58mSVbVauXAlLS0vh5uzsrLP+MMYYY6zx0OhEcBMTEyQnJ8PFxQVN/4+9Ow+LquzfAH4P4Awgm4JsieCKu6amovVTc0El01b1tUJTC/MtLVOyRVpeNVtUKrM0k3pVXFLKzDQlwdwFwRUBFVdAcwNxQ+H7+8N3TgwwMMBswv25rrlgznnOfZ7znBnm4SzPeHpi06ZNaNeuHdLT09G1a1dcunTJFHVFcHAw1Go1fv31V71lbt++jdu3byvPc3Nz4efnxwvBiWoaXghOVKOY40LwSh1p8vb2xuXLlwEADRo0wK5duwAAGRkZMNXNeKdOncLmzZsxZsyYMstpNBq4uLjoPIiIiIiqqlKdpkcffRRr164FcG/Mptdffx19+/bF0KFD8cQTTxi1glqLFy+Gp6cnQkJCTJJPREREVJZK3T23YMECFBYWAgDGjx8Pd3d37NixA48//jhefvllo1YQAAoLC7F48WKEhobCzs7qR0kgIiKi6shkX9BiRBs3bhQAkpqaWuFli37rcVhYmISFhZUok5eXJ76+vhIfH19iXnx8vPj6+pb4ZmYRYR7zmMc85jGPeVaSV/Tz3lQqdXoOAK5evYo//vgDS5YswY8//qjzMKZz587hxx9/RN26ddGuXTu0adMGCQkJFc6JiorCmDFjMGbMGCxcuFCZrv3emrS0NKSmpiIxMVGZl5iYiNTUVKSlpeGTTz7B9evXlXkLFy5kHvOYxzzmMY95VpRncpXpaa1du1acnZ1FpVKJq6uruLm5KY86deoYrUd3+fJl8ff3l5EjR8ru3bvlxIkTsnHjRjl27JjBGdqeZ1xcnDJN+23Kxb8hWeSfb1Mu/o3LRcsW/cZl5jGPecxjHvOYZ/m88PBwkx9pqlSnqWnTpjJhwgS5fv26seujIzw8XB5++OEqZeg7XGfpw4jMYx7zmMc85jHPeHmZmZnWeXru3LlzeO211+Do6GjMg14lrF27Fp06dcIzzzwDT09PPPjggzqH4kqjb0Twooftrl+/jtjYWERHR2PZsmU6yycmJqJDhw7o0KGDzqFCAFi2bBmio6MRGxvLPOYxj3nMYx7zrChv1apVMLnK9LSeeOIJWbFihbE7cCVoNBrRaDQydepU2bdvn3z77bdib28vUVFRepeJiIgQACUe4eHhkpeXV+KQYNHDgMUPCRY9DFj096IZzGMe85jHPOYxz/J5cXFx1nN67pdfflEe3333nTRo0EAiIiLkp59+0pn3yy+/GK1ytWrVkqCgIJ1pr776qnTt2lXvMrdu3ZKcnBzlcebMGQEgmZmZMmnSJJk0aVKJQ4IJCQkSFhams8O0FixYIGFhYTrnUEXu7TjmMY95zGMe85hnHXnmuHvO4EGPhgwZUmLahx9+WGKaSqVCQUFBpY56Fefj44OWLVvqTGvRogVWr16tdxmNRgONRmOU9RMREREpTNYdM4Lhw4eXuBB84sSJJY4+lUXb8+TpOeYxj3nMYx7zqm+eOU7PVegLe//880/8+9//xq5du0p8p1tOTg66deuGb775Bo888ohROnR79+5Ft27d8MEHH+DZZ5/Fnj17MHbsWCxYsAAjRowwKCM3Nxeurq7IzMyEj48PgH/GhujduzdSU1MxduxYpXxiYiL27dsHAOjQoQM6duyozFu4cCECAwMRGxuLKVOmoHbt2sxjHvOYxzzmMc8K8pKTkzFhwgSTfmFvhY40DRo0SGbPnq13fmRkpAwZMqSK/Thdw4cPL3FRd2BgoMHLc8gB5jGPecxjHvOqf57VDTmwf/9+9O/fX+/8fv36lbhNsKqaNWuGVq1aISsrS3ls27atwjlJSUnK79YycinzmMc85jGPecwzTl5kZCRMriI9LI1GI+np6Xrnp6eni729fZV7ckVFRERIu3btKr289khTZGSkJCRYz8ilzGMe85jHPOYxz3h55jjSVKFOU6NGjSQmJkbv/NWrV0vDhg2rWicdERER4ujoKD4+PtKwYUP517/+JadOndJbXt+QA/zCXuYxj3nMYx7zqm+e1X1h78CBA/Hee+/h1q1bJebdvHkTEREReOyxx4xyBEyrS5cuiIqKwoYNGzB//nxkZGTgkUcewbVr10otP3PmTLi6uioPPz8/APdOz1nTyKXMYx7zmMc85jHPuHkmV5EeVnZ2tvj6+oqfn5/MmjVLfv75Z/n555/l448/Fj8/P/H19ZXs7GxTdfBEROTKlSvi4uIi3333Xanz9R1pioyMVMpYw62RzGMe85jHPOYxz3h5kZGR1nV6TkTk5MmTMmDAALGxsRGVSiUqlUpsbGxkwIABcuLECVPUsYROnTrJW2+9ZVBZfYfrFiyoXiOhMo95zGMe85hXk/PMMU6TwSOCa/n7+2P9+vW4cuUKjh07BhFB06ZNUadOHWMfBCtVXl4ejh8/jueff94s6yMiIiICYN0jgouITJo0SeLi4iQjI0O2b98uffr0EQ8PD7lw4YJByxe9e07rfjrcyDzmMY95zGMe86zj9FyFRgS3hGHDhmHr1q24dOkS6tWrh4cffhjTp09H48aNDVpeOyJ4XFwc0tLSAFjHyKXMYx7zmMc85jHPeHnaz3urGRHc0mbOnCkAZMKECQYvU/SapvvxFkrmMY95zGMe85hXfp7VDTlgSXv37sW3336Ltm3bVmr5qKgoqxq5lHnMYx7zmMc85hk3z+RM1h0zomvXrknTpk1l06ZN0qNHj0odaYqLi1Omac+JFj9vKvLP+dHi502Lli16DpV5zGMe85jHPOZZPi88PNz6hhywhBdeeEEmTpwoIlJup6msEcGLsvRhROYxj3nMYx7zmGe8PKv7wl5LWL58Ofbt24eZM2caVF7fiODWOHIp85jHPOYxj3nMM07eqlWrYHIm644ZwenTp8XT01P279+vTKvskabw8HDJy7OeWyOZxzzmMY95zGOe8fLMMbilVXeaYmJiBIDY2toqDwCiUqnE1tZW7t69W26G9pqmzMxMqxq5lHnMYx7zmMc85hkvzxx3z1V4RHBz6t27Nw4ePKgzbdSoUWjevDnCw8Nha2troZoRERFRjWOy7piJVPbuOZ6eYx7zmMc85jGv+uaZ4/Sc1Y8IXlzPnj3Rvn17zJ0716Dy2hFCMzMz4ePjA8A6Ri5lHvOYxzzmMY95xstLTk7GhAkTavaI4F9//bW0adNGnJ2dxdnZWbp27Srr1683eHl95zjvl1somcc85jGPecxjHoccMEj9+vXx8ccfIzExEQkJCXj00UcxePBgHD58uEI5SUlJyu/WMnIp85jHPOYxj3nMM05eZGQkTM5k3TETqlOnjnz33XcGldUeaYqMjJSEBOsZuZR5zGMe85jHPOYZL88cR5ruq07T3bt3JTo6WtRqtRw+fLjUMmWNCG5NhxGZxzzmMY95zGMev7DX6A4ePAgnJydoNBqEhYUhJiYGLVu2LLWsvhHBk5KSrGrkUuYxj3nMYx7zmGfcPJMzWXfMiG7fvi3p6emSkJAgb731lnh4eFT4SFNkZKRSxhpujWQe85jHPOYxj3nGy4uMjOTpudL07t1bXnrpJYPK6jtct2BB9RoJlXnMYx7zmMe8mpxnjnGa7ovTc8UVFhbi9u3blq4GERER1SQm644ZyVtvvSXx8fGSkZEhBw4ckLfeektUKpX88ccfBi1f9O45rfvpcCPzmMc85jGPecyzjtNzVj8i+OjRoxEbG4usrCy4urqibdu2CA8PR9++fQ1aXjsieFxcHNLS0gBYx8ilzGMe85jHPOYxz3h52s/7Gj0i+IwZM6RTp07i5OQk9erVk8GDB8vRo0cNXr7oNU334y2UzGMe85jHPOYxr/w8DjkAID4+HuPHj8euXbuwadMm3LlzB/369dO5NdEQUVFRVjVyKfOYxzzmMY95zDNunsmZrDtmIhcuXBAApfZKS6PtecbFxSnTtOdEi583Ffnn/Gjx86ZFyxY9h8o85jGPecxjHvMsnxceHs4hB4pLT08XAHLw4MFS55c1InhRlj6MyDzmMY95zGMe84yXxy/sLaawsBATJ05E9+7d0bp161LL6BsR3BpHLmUe85jHPOYxj3nGyVu1ahVMzmTdMRMICwsTf39/OXPmjN4y+o40hYeHS16e9dwayTzmMY95zGMe84yXZ47BLe+bTtP48eOlfv36cuLEiQotp72mKTMz06pGLmUe85jHPOYxj3nGyzPH3XN2pj+WVTUigldffRUxMTGIi4tDw4YNLV0lIiIiqolM1h0zknHjxomrq6vExcVJVlaW8rhx44ZBy2t7njw9xzzmMY95zGNe9c0zx+k5qx8RXKVSlTp98eLFGDlyZLnLa0cIzczMhI+PDwDrGLmUecxjHvOYxzzmGS8vOTkZEyZMqNkjgsfHx8tjjz0mPj4+AkBiYmIqtLy+c5z3yy2UzGMe85jHPOYxj0MOGOT69eto164d5s2bV6WcpKQk5XdrGbmUecxjHvOYxzzmGScvMjISJmey7pgJoApHmiIjIyUhwXpGLmUe85jHPOYxj3nGyzPHkaZq12kqa0RwazqMyDzmMY95zGMe8/iFvRalb0TwpKQkqxq5lHnMYx7zmMc85hk3z+RM1h0zAVThSFNkZKRSxhpujWQe85jHPOYxj3nGy4uMjOTpuaIM6TQVp+9w3YIF1WskVOYxj3nMYx7zanKeOcZpqnan54iIiIhMwmTdMSO5du2aJCUlSVJSkgCQ2bNnS1JSkpw6dcqg5a9evSoAZNasWcopu8jISImLiyvxe2ZmpoSHh0tmZqbO7zk5ORIXFyeRkZElfmce85jHPOYxj3mWz5s1a5YAkKtXr5qsT2L1I4LHxcWhV69eJaaHhoYiKiqq3OXPnj2rXAxORERE1duZM2dQv359k2RbfaepqgoLC5GZmQlnZ2e9X8liDXJzc+Hn54czZ86Ybvj3GoZtanxsU+Niexof29S47qf2FBFcu3YNvr6+sLExzdVHdiZJtSI2NjYm63GagouLi9W/MO83bFPjY5saF9vT+NimxnW/tKerq6tJ83khOBEREZEB2GkiIiIiMgA7TVZCo9EgIiICGo3G0lWpNtimxsc2NS62p/GxTY2L7amr2l8ITkRERGQMPNJEREREZAB2moiIiIgMwE4TERERkQHYaSIiIiIyADtNJjBv3jwEBATA3t4eXbp0wZ49e5R5CxYsQM+ePeHi4gKVSoWrV6+WWH769Ono1q0bHB0d4ebmVmL+/v37MXz4cPj5+cHBwQEtWrRAZGSkCbfIskzdngCwd+9e9O7dG25ubqhTpw6Cg4Oxf/9+E22R5elr08uXL+PVV19FYGAgHBwc0KBBA7z22mvIycnRWf706dMICQmBo6MjPD09MXnyZNy9e1enTFxcHDp06ACNRoMmTZoY9LVH9ytztOft27fxzjvvwN/fHxqNBgEBAfj+++/Nto3mVtU2fe2119CxY0doNBq0b9++RH5cXBwGDx4MHx8f1K5dG+3bt8fSpUvNsWkWY+o2BYCNGzeia9eucHZ2Rr169fDUU0/h5MmTJt4y82GnychWrFiBN954AxEREdi3bx/atWuH4OBgXLhwAQBw48YN9O/fH2+//bbejPz8fDzzzDMYN25cqfMTExPh6emJJUuW4PDhw3jnnXcwdepUfPXVVybZJksyR3vm5eWhf//+aNCgAXbv3o1t27bB2dkZwcHBuHPnjkm2y5LKatPMzExkZmbis88+w6FDhxAVFYUNGzZg9OjRyvIFBQUICQlBfn4+duzYgR9++AFRUVGYNm2aUiYjIwMhISHo1asXkpOTMXHiRIwZMwYbN260xCablDnaEwCeffZZxMbGYtGiRUhNTUV0dDQCAwPNvblmUdU21XrxxRcxdOjQUtexY8cOtG3bFqtXr8aBAwcwatQovPDCC1i3bp2pN88izNGmGRkZGDx4MB599FEkJydj48aNuHjxIp588klTb575mOyrgGuozp07y/jx45XnBQUF4uvrKzNnztQpt2XLFgEgV65c0Zu1ePFicXV1NWi9r7zyivTq1asyVbZq5mjPvXv3CgA5ffq0Mu3AgQMCQNLT06u8DdbG0DbVWrlypajVarlz546IiKxfv15sbGwkOztbKTN//nxxcXGR27dvi4jIlClTpFWrVjo5Q4cOleDgYGNvjsWZoz1///13cXV1lUuXLplwS6xHVdu0qIiICGnXrp1B6x04cKCMGjWqUnW2duZo01WrVomdnZ0UFBQo09auXSsqlUry8/OrvhFWgEeajCg/Px+JiYno06ePMs3GxgZ9+vTBzp07TbrunJwc1K1b16TrMDdztWdgYCDc3d2xaNEi5Ofn4+bNm1i0aBFatGiBgIAAo63HGlSmTXNycuDi4gI7u3tfVblz5060adMGXl5eSpng4GDk5ubi8OHDSpmi69CWMfX7wNzM1Z5r165Fp06d8Mknn+CBBx5As2bN8Oabb+LmzZsm3DrLMEabVlZ1/DsKmK9NO3bsCBsbGyxevBgFBQXIycnBf//7X/Tp0we1atWq8nZYA3aajOjixYsoKCjQ+eMHAF5eXsjOzjbZenfs2IEVK1bgpZdeMtk6LMFc7ens7Iy4uDgsWbIEDg4OcHJywoYNG/D7779X+Y+wtalom168eBEfffSRzmsrOzu71OW188oqk5ubW60+6M3VnidOnMC2bdtw6NAhxMTEYO7cufjpp5/wyiuvGHuTLM4YbVoZK1euxN69ezFq1Kgq5Vgjc7Vpw4YN8ccff+Dtt9+GRqOBm5sbzp49i5UrV1ap/taEnab73KFDhzB48GBERESgX79+lq7OfenmzZsYPXo0unfvjl27dmH79u1o3bo1QkJCqtUHfEXl5uYiJCQELVu2xPvvv2/p6tz3qtKehYWFUKlUWLp0KTp37oyBAwdi9uzZ+OGHH/gaNcJrdMuWLRg1ahQWLlyIVq1aGa+C96GqtGl2djbGjh2L0NBQ7N27F/Hx8VCr1Xj66ach1eTLR6rXv9EW5uHhAVtbW5w/f15n+vnz5+Ht7W309R05cgS9e/fGSy+9hHfffdfo+ZZmrvZctmwZTp48iZ07d8LGxkaZVqdOHfzyyy8YNmyY0dZlaYa26bVr19C/f384OzsjJiZG59C6t7e3zh2M2uW187Q/S1uHi4sLHBwcjLpNlmSu9vTx8cEDDzwAV1dXpUyLFi0gIjh79iyaNm1q9G2zFGO0aUXEx8dj0KBBmDNnDl544YUq1d1amatN582bB1dXV3zyySfKtCVLlsDPzw+7d+9G165dq7YhVoBHmoxIrVajY8eOiI2NVaYVFhYiNjYWQUFBRl3X4cOH0atXL4SGhmL69OlGzbYW5mrPGzduwMbGBiqVSpmmfV5YWGi09VgDQ9o0NzcX/fr1g1qtxtq1a2Fvb6+TERQUhIMHDyp3MALApk2b4OLigpYtWypliq5DW8bY7wNLM1d7du/eHZmZmcjLy1PKpKWlwcbGBvXr1zflJpqdMdrUUHFxcQgJCcGsWbOq3eUNRZmrTbV/S4uytbVV1lctWPpK9Opm+fLlotFoJCoqSo4cOSIvvfSSuLm5KXfGZGVlSVJSkixcuFAAyNatWyUpKUnnrphTp05JUlKSfPDBB+Lk5CRJSUmSlJQk165dExGRgwcPSr169eS5556TrKws5XHhwgWLbLMpmaM9U1JSRKPRyLhx4+TIkSNy6NAhee6558TV1VUyMzMtst2mVFab5uTkSJcuXaRNmzZy7NgxndfX3bt3RUTk7t270rp1a+nXr58kJyfLhg0bpF69ejJ16lRlHSdOnBBHR0eZPHmypKSkyLx588TW1lY2bNhgqc02GXO057Vr16R+/fry9NNPy+HDhyU+Pl6aNm0qY8aMsdRmm1RV21REJD09XZKSkuTll1+WZs2aKe977R2Jf/75pzg6OsrUqVN1MqrrHYrmaNPY2FhRqVTywQcfSFpamiQmJkpwcLD4+/vLjRs3LLXpRsVOkwl8+eWX0qBBA1Gr1dK5c2fZtWuXMi8iIkIAlHgsXrxYKRMaGlpqmS1btpSZ4e/vb94NNRNTt6eIyB9//CHdu3cXV1dXqVOnjjz66KOyc+dOM26leelrU+3QDaU9MjIylOVPnjwpAwYMEAcHB/Hw8JBJkyaVuDV5y5Yt0r59e1Gr1dKoUSOdfVLdmKM9U1JSpE+fPuLg4CD169eXN954o9p8EJWmqm3ao0ePMsvo+7vQo0cP82+smZi6TUVEoqOj5cEHH5TatWtLvXr15PHHH5eUlBQzb6npqESqydVZRERERCbEa5qIiIiIDMBOExEREZEB2GkiIiIiMgA7TUREREQGYKeJiIiIyADsNBEREREZgJ0mIiIiIgOw00RERERkAHaaiIiIiAzAThMRERGRAdhpIiIiIjIAO01EREREBmCniYiIiMgA7DQRERERGYCdJiIiIiIDsNNEREREZAB2moiIiIgMYGfpCpjDrVu3kJ+fb+lqEBERkQmp1WrY29ubLL/ad5pu3bqFhg0bIjs729JVISIiIhPy9vZGRkaGyTpO1b7TlJ+fj+zsbKRnnIGzswsAQCD43y9Ff0CU54bN1z5HsfkoNr/Y5BLLGzq/vPx/fv4zw9BtK77uqraNueeXV/9CbZvpySssZ32FxZ4r8/XuM93nhSXma5f/X36x52XNL/66Kyx3mdLroF2uUEovB6VcsfUUmy7Fcoq3VfH8ksvrqV/x7StnvVJ8OnSfF9/u4uVLzC+2fPH1opz5ymvPgPWVqLue11HxfWJo3fWt+5/nhpVDuTl6npd43xi23sLC8upR/KfoKadtl+Lr1bddFZtfWjkpUTl9ddG3bYavS3e69mdhBZ8rr9gq5vzveYk3ZgVzDK4H/nlekI/sIz8gPz+fnaaqcnFxMVunqbKdoip3mkqpf2W3rbrNL/lholteb6fIwE5TyU6RlDNfu/z/8os9L2t+8QyDO016PmDL7bzoXb7Y+opP19Np0rve4vnFt8/Q9eprUz3rqWynqfjy5ug0lVeX8tZV1U6T8Z+XXU6lp9NkaG5VOyDG6DQVn1fij0eJn8YqZ2inw0idpOLPC820niLPtU1iSrwQnIiIiMgA7DQRERERGYCdJiIiIiIDsNNEREREZAB2moiIiIgMwE4TERERkQHYaSIiIiIyADtNRERERAZgp4mIiIjIAOw0ERERERmAnSYiIiIiA7DTRERERGQAdpqIiIiIDMBOExEREZEB2GkiIiIiMgA7TUREREQGYKeJiIiIyADsNBEREREZgJ0mIiIiIgOw00RERERkAHaaiIiIiAxgZ+kKmEtubi5E7v0uUH4p+qPC87XPUWw+is0vNrnE8obOLy//n5//zDB024qvu6ptY+755dW/UNtmevIKy1lfYbHnyny9+0z3eWGJ+drl/5df7HlZ84u/7grLXab0OmiXK5TSy0EpV2w9xaZLsZzibVU8v+TyeupXfPvKWa8Unw7d58W3u3j5EvOLLV98vShnvvLaM2B9Jequ53VUfJ8YWnd96/7nuWHlUG6Onucl3jeGrbewsLx6FP8pespp26X4evVtV8Xml1ZOSlROX130bZvh69Kdrv1ZWMHnyiu2ijn/e17ijVnBHIPrgX+eF+TD1Kp9p0lE4OTkhKYN/SxdFSIiIjIhJyenEv/YGFO17zSpVCrk5eXhzJkzcHFxsXR1zCo3Nxd+fn41ctuBmr39NXnbgZq9/TV524Gavf01eduBf7ZfpVKZbB3VvtOk5eLiUiNfREDN3nagZm9/Td52oGZvf03edqBmb39N3nZT44XgRERERAZgp4mIiIjIANW+06TRaBAREQGNRmPpqphdTd52oGZvf03edqBmb39N3nagZm9/Td52wDzbrxJTXmZOREREVE1U+yNNRERERMbAThMRERGRAdhpIiIiIjIAO01EREREBrgvO03z5s1DQEAA7O3t0aVLF+zZs6fM8qtWrULz5s1hb2+PNm3aYP369TrzRQTTpk2Dj48PHBwc0KdPH6Snp5tyEyqtItu+cOFCPPLII6hTpw7q1KmDPn36lCg/cuRIqFQqnUf//v1NvRmVVpHtj4qKKrFt9vb2OmWq677v2bNniW1XqVQICQlRytwv+37r1q0YNGgQfH19oVKp8PPPP5e7TFxcHDp06ACNRoMmTZogKiqqRJmK/h2xlIpu/5o1a9C3b1/Uq1cPLi4uCAoKwsaNG3XKvP/++yX2ffPmzU24FZVT0W2Pi4sr9XWfnZ2tU+5+2PcV3fbS3s8qlQqtWrVSytwv+33mzJl46KGH4OzsDE9PTwwZMgSpqanlLmeOz/r7rtO0YsUKvPHGG4iIiMC+ffvQrl07BAcH48KFC6WW37FjB4YPH47Ro0cjKSkJQ4YMwZAhQ3Do0CGlzCeffIIvvvgC33zzDXbv3o3atWsjODgYt27dMtdmGaSi2x4XF4fhw4djy5Yt2LlzJ/z8/NCvXz+cO3dOp1z//v2RlZWlPKKjo82xORVW0e0H7o2MW3TbTp06pTO/uu77NWvW6Gz3oUOHYGtri2eeeUan3P2w769fv4527dph3rx5BpXPyMhASEgIevXqheTkZEycOBFjxozR6ThU5rVkKRXd/q1bt6Jv375Yv349EhMT0atXLwwaNAhJSUk65Vq1aqWz77dt22aK6ldJRbddKzU1VWfbPD09lXn3y76v6LZHRkbqbPOZM2dQt27dEu/5+2G/x8fHY/z48di1axc2bdqEO3fuoF+/frh+/breZcz2WS/3mc6dO8v48eOV5wUFBeLr6yszZ84stfyzzz4rISEhOtO6dOkiL7/8soiIFBYWire3t3z66afK/KtXr4pGo5Ho6GgTbEHlVXTbi7t79644OzvLDz/8oEwLDQ2VwYMHG7uqJlHR7V+8eLG4urrqzatJ+37OnDni7OwseXl5yrT7ad9rAZCYmJgyy0yZMkVatWqlM23o0KESHBysPK9qe1qKIdtfmpYtW8oHH3ygPI+IiJB27doZr2JmYMi2b9myRQDIlStX9Ja5H/d9ZfZ7TEyMqFQqOXnypDLtftzvIiIXLlwQABIfH6+3jLk+6++rI035+flITExEnz59lGk2Njbo06cPdu7cWeoyO3fu1CkPAMHBwUr5jIwMZGdn65RxdXVFly5d9GZaQmW2vbgbN27gzp07qFu3rs70uLg4eHp6IjAwEOPGjcOlS5eMWndjqOz25+Xlwd/fH35+fhg8eDAOHz6szKtJ+37RokUYNmwYateurTP9ftj3FVXee94Y7Xk/KSwsxLVr10q879PT0+Hr64tGjRphxIgROH36tIVqaHzt27eHj48P+vbti+3btyvTa9K+X7RoEfr06QN/f3+d6ffjfs/JyQGAEq/hosz1WX9fdZouXryIgoICeHl56Uz38vIqcc5aKzs7u8zy2p8VybSEymx7ceHh4fD19dV50fTv3x8//vgjYmNjMWvWLMTHx2PAgAEoKCgwav2rqjLbHxgYiO+//x6//PILlixZgsLCQnTr1g1nz54FUHP2/Z49e3Do0CGMGTNGZ/r9su8rSt97Pjc3Fzdv3jTKe+l+8tlnnyEvLw/PPvusMq1Lly6IiorChg0bMH/+fGRkZOCRRx7BtWvXLFjTqvPx8cE333yD1atXY/Xq1fDz80PPnj2xb98+AMb5O3o/yMzMxO+//17iPX8/7vfCwkJMnDgR3bt3R+vWrfWWM9dnvZ3BJem+9vHHH2P58uWIi4vTuRh62LBhyu9t2rRB27Zt0bhxY8TFxaF3796WqKrRBAUFISgoSHnerVs3tGjRAt9++y0++ugjC9bMvBYtWoQ2bdqgc+fOOtOr876ne5YtW4YPPvgAv/zyi851PQMGDFB+b9u2Lbp06QJ/f3+sXLkSo0ePtkRVjSIwMBCBgYHK827duuH48eOYM2cO/vvf/1qwZub1ww8/wM3NDUOGDNGZfj/u9/Hjx+PQoUNWc+3VfXWkycPDA7a2tjh//rzO9PPnz8Pb27vUZby9vcssr/1ZkUxLqMy2a3322Wf4+OOP8ccff6Bt27Zllm3UqBE8PDxw7NixKtfZmKqy/Vq1atXCgw8+qGxbTdj3169fx/Llyw36g2it+76i9L3nXVxc4ODgYJTX0v1g+fLlGDNmDFauXFnitEVxbm5uaNas2X2/70vTuXNnZbtqwr4XEXz//fd4/vnnoVaryyxr7fv93//+N9atW4ctW7agfv36ZZY112f9fdVpUqvV6NixI2JjY5VphYWFiI2N1TmiUFRQUJBOeQDYtGmTUr5hw4bw9vbWKZObm4vdu3frzbSEymw7cO9ugY8++ggbNmxAp06dyl3P2bNncenSJfj4+Bil3sZS2e0vqqCgAAcPHlS2rbrve+DeLbi3b9/Gc889V+56rHXfV1R573ljvJasXXR0NEaNGoXo6GidYSb0ycvLw/Hjx+/7fV+a5ORkZbtqwr6Pj4/HsWPHDPpHyVr3u4jg3//+N2JiYvDnn3+iYcOG5S5jts/6Cl3CbgWWL18uGo1GoqKi5MiRI/LSSy+Jm5ubZGdni4jI888/L2+99ZZSfvv27WJnZyefffaZpKSkSEREhNSqVUsOHjyolPn444/Fzc1NfvnlFzlw4IAMHjxYGjZsKDdv3jT79pWlotv+8ccfi1qtlp9++kmysrKUx7Vr10RE5Nq1a/Lmm2/Kzp07JSMjQzZv3iwdOnSQpk2byq1btyyyjWWp6PZ/8MEHsnHjRjl+/LgkJibKsGHDxN7eXg4fPqyUqa77Xuvhhx+WoUOHlph+P+37a9euSVJSkiQlJQkAmT17tiQlJcmpU6dEROStt96S559/Xil/4sQJcXR0lMmTJ0tKSorMmzdPbG1tZcOGDUqZ8trTmlR0+5cuXSp2dnYyb948nff91atXlTKTJk2SuLg4ycjIkO3bt0ufPn3Ew8NDLly4YPbtK0tFt33OnDny888/S3p6uhw8eFAmTJggNjY2snnzZqXM/bLvK7rtWs8995x06dKl1Mz7Zb+PGzdOXF1dJS4uTuc1fOPGDaWMpT7r77tOk4jIl19+KQ0aNBC1Wi2dO3eWXbt2KfN69OghoaGhOuVXrlwpzZo1E7VaLa1atZLffvtNZ35hYaG899574uXlJRqNRnr37i2pqanm2JQKq8i2+/v7C4ASj4iICBERuXHjhvTr10/q1asntWrVEn9/fxk7dqzV/fEoqiLbP3HiRKWsl5eXDBw4UPbt26eTV133vYjI0aNHBYD88ccfJbLup32vvY28+EO7vaGhodKjR48Sy7Rv317UarU0atRIFi9eXCK3rPa0JhXd/h49epRZXuTeEAw+Pj6iVqvlgQcekKFDh8qxY8fMu2EGqOi2z5o1Sxo3biz29vZSt25d6dmzp/z5558lcu+HfV+Z1/3Vq1fFwcFBFixYUGrm/bLfS9tuADrvY0t91qv+V0EiIiIiKsN9dU0TERERkaWw00RERERkAHaaiIiIiAzAThMRERGRAdhpIiIiIjIAO01EREREBmCniYiIiMgA7DQR1XAnT56ESqVCcnLyfZVdGVFRUXBzc7OaHEOkpqbC29vbar6JPj8/HwEBAUhISLB0VYjMjp0mIjP7+++/MW7cODRo0AAajQbe3t4IDg7G9u3blTIqlQo///yz5SppRj179oRKpYJKpYJGo8EDDzyAQYMGYc2aNUZf19ChQ5GWllahZQICAjB37twq51TW1KlT8eqrr8LZ2VmZVlBQgDlz5qBNmzawt7dHnTp1MGDAAJ3XUFUEBAQo+0T70H5hqlqtxptvvonw8HCjrIvofsJOE5GZPfXUU0hKSsIPP/yAtLQ0rF27Fj179sSlS5csXbVKy8/Pr9LyY8eORVZWFo4fP47Vq1ejZcuWGDZsGF566SUj1fAeBwcHeHp6Wk1OeU6fPo1169Zh5MiRyjQRwbBhw/Dhhx9iwoQJSElJQVxcHPz8/NCzZ0+jdbY//PBDZGVlKY+kpCRl3ogRI7Bt2zYcPnzYKOsium9U6othiKhSrly5IgAkLi5Ob5ni3xno7+8vIiLHjh2Txx9/XDw9PaV27drSqVMn2bRpU4llp0+fLqNGjRInJyfx8/OTb7/9VqfM7t27pX379qLRaKRjx46yZs0aASBJSUkiInL37l158cUXJSAgQOzt7aVZs2Yyd+5cnYzQ0FAZPHiw/Oc//xEfHx8JCAgwKLs0PXr0kAkTJpSY/v333wsAnW08ffq0PPPMM+Lq6ip16tSRxx9/XDIyMkREZOPGjaLRaOTKlSs6Oa+99pr06tVLREQWL14srq6uyrzy2rS073ErLUdE5Ouvv5ZGjRpJrVq1pFmzZvLjjz/qzAcgCxculCFDhoiDg4M0adJEfvnlF73tIiLy6aefSqdOnXSmLV++XADI2rVrS5R/8sknxd3dXfLy8kREJCIiQtq1ayeLFi0SPz8/qV27towbN07u3r0rs2bNEi8vL6lXr5785z//0cnx9/eXOXPmlFm3Xr16ybvvvltmGaLqhkeaiMzIyckJTk5O+Pnnn3H79u1Sy+zduxcAsHjxYmRlZSnP8/LyMHDgQMTGxiIpKQn9+/fHoEGDcPr0aZ3lP//8c3Tq1AlJSUl45ZVXMG7cOKSmpioZjz32GFq2bInExES8//77ePPNN3WWLywsRP369bFq1SocOXIE06ZNw9tvv42VK1fqlIuNjUVqaio2bdqEdevWGZRdEaGhoahTp45ymu7OnTsIDg6Gs7Mz/vrrL2zfvh1OTk7o378/8vPz0bt3b7i5uWH16tVKRkFBAVasWIERI0aUuo7y2nTNmjWoX7++zlGX0sTExGDChAmYNGkSDh06hJdffhmjRo3Cli1bdMp98MEHePbZZ3HgwAEMHDgQI0aMwOXLl/W2wV9//YVOnTrpTFu2bBmaNWuGQYMGlSg/adIkXLp0CZs2bVKmHT9+HL///js2bNiA6OhoLFq0CCEhITh79izi4+Mxa9YsvPvuu9i9e7feepSmc+fO+Ouvvyq0DNF9z9K9NqKa5qeffpI6deqIvb29dOvWTaZOnSr79+/XKQNAYmJiys1q1aqVfPnll8pzf39/ee6555TnhYWF4unpKfPnzxcRkW+//Vbc3d3l5s2bSpn58+eXezRo/Pjx8tRTTynPQ0NDxcvLS27fvq1Mq2y2viNNIiJdunSRAQMGiIjIf//7XwkMDJTCwkJl/u3bt8XBwUE2btwoIiITJkyQRx99VJlf/OhTaUeIiiutTYsfdSme061bNxk7dqxOmWeeeUYGDhyoPAegc2QmLy9PAMjvv/+uty7t2rWTDz/8UGda8+bNZfDgwaWWv3z5sgCQWbNmici9I02Ojo6Sm5urlAkODpaAgAApKChQpgUGBsrMmTN1tlmtVkvt2rWVR2RkpM66IiMjlSOMRDUFjzQRmdlTTz2FzMxMrF27Fv3790dcXBw6dOiAqKioMpfLy8vDm2++iRYtWsDNzQ1OTk5ISUkpcaSpbdu2yu8qlQre3t64cOECACAlJQVt27aFvb29UiYoKKjEuubNm4eOHTuiXr16cHJywoIFC0qsp02bNlCr1cpzQ7MrQkSgUqkAAPv378exY8fg7OysHLGrW7cubt26hePHjwO4d61NXFwcMjMzAQBLly5FSEiI3jvdDG3T8qSkpKB79+4607p3746UlBSdaUX3Te3ateHi4qLsm9LcvHlTpz21RMTgugUEBOhcRO7l5YWWLVvCxsZGZ1rxekyePBnJycnK44UXXtCZ7+DggBs3bhhcD6LqwM7SFSCqiezt7dG3b1/07dsX7733HsaMGYOIiAidC36Le/PNN7Fp0yZ89tlnaNKkCRwcHPD000+XuAi7Vq1aOs9VKhUKCwsNrtvy5cvx5ptv4vPPP0dQUBCcnZ3x6aefljh9U7t2bYMzK6OgoADp6el46KGHANzr4HTs2BFLly4tUbZevXoAgIceegiNGzfG8uXLMW7cOMTExJTZGTW0TY2lovvGw8MDV65c0ZnWrFmzEp0xLe30Zs2alblOQ+rh4eGBJk2a6K3b5cuXlXYnqil4pInICrRs2RLXr19XnteqVQsFBQU6ZbZv346RI0fiiSeeQJs2beDt7Y2TJ09WaD0tWrTAgQMHcOvWLWXarl27SqynW7dueOWVV/Dggw+iSZMmypGcqmZXxA8//IArV67gqaeeAgB06NAB6enp8PT0RJMmTXQerq6uynIjRozA0qVL8euvv8LGxgYhISF612FIm6rV6hL7orgWLVqUuN1/+/btaNmyZQW3WteDDz6II0eO6EwbNmwY0tPT8euvv5Yo//nnn8Pd3R19+/at0noNcejQITz44IMmXw+RNWGniciMLl26hEcffRRLlizBgQMHkJGRgVWrVuGTTz7B4MGDlXIBAQGIjY1Fdna2cqShadOmWLNmDZKTk7F//37861//qtARJAD417/+BZVKhbFjx+LIkSNYv349PvvsM50yTZs2RUJCAjZu3Ii0tDS89957ysXoVc3W58aNG8jOzsbZs2exa9cuhIeHIywsDOPGjUOvXr0A3OsMeXh4YPDgwfjrr7+QkZGBuLg4vPbaazh79qySNWLECOzbtw/Tp0/H008/DY1Go3e9hrRpQEAAtm7dinPnzuHixYul5kyePBlRUVGYP38+0tPTMXv2bKxZs6ZKF8IDQHBwMHbu3KnTaRs2bBieeOIJhIaGYtGiRTh58iQOHDiAl19+GWvXrsV3331n8qOAwL2L1Pv162fy9RBZE3aaiMzIyckJXbp0wZw5c/B///d/aN26Nd577z2MHTsWX331lVLu888/x6ZNm+Dn56f8Nz979mzUqVMH3bp1w6BBgxAcHIwOHTpUeP2//vorDh48iAcffBDvvPMOZs2apVPm5ZdfxpNPPomhQ4eiS5cuuHTpEl555RWjZOuzcOFC+Pj4oHHjxnjyySdx5MgRrFixAl9//bVSxtHREVu3bkWDBg3w5JNPokWLFhg9ejRu3boFFxcXpVyTJk3QuXNnHDhwQO9dc1qGtOmHH36IkydPonHjxnpPRw0ZMgSRkZH47LPP0KpVK3z77bdYvHgxevbsadD26zNgwADY2dlh8+bNyjSVSoWVK1fi7bffxpw5cxAYGIhHHnkEp06dQlxcHIYMGVKldRpi586dyMnJwdNPP23ydRFZE5VU5IpCIiIyq3nz5mHt2rXYuHGjpauiGDp0KNq1a4e3337b0lUhMiteCE5EZMVefvllXL16FdeuXdO5C85S8vPz0aZNG7z++uuWrgqR2fFIExEREZEBeE0TERERkQHYaSIiIiIyADtNRERERAZgp4mIiIjIAOw0ERERERmAnSYiIiIiA7DTRERERGQAdpqIiIiIDMBOExEREZEB2GkiIiIiMgA7TUREREQGYKeJiIiIyADsNBEREREZgJ0mIiIiIgOw00RERERkAHaaiIiIiAzAThMRERGRAdhpIiIiIjIAO01EREREBmCniYiIiMgA7DTRfW3kyJF4//33LV2NGuH9999H+/btlecjR47EkCFDLFYfYxARvPTSS6hbty5UKhWSk5MtXSUismLsNJEiLi4OKpUKV69etXRVzGLnzp2wtbVFSEhIiXknT56ESqWCra0tzp07pzMvKysLdnZ2UKlUOHnypDI9JiYGXbt2haurK5ydndGqVStMnDhRmV+801F8XYZ8YJdVZ3OLjIxEVFSUpatRJRs2bEBUVBTWrVuHrKwstG7d2tJVQs+ePaFSqfDxxx+XmBcSEgKVSlWhfxSioqLg5uZmvAoaIDc3F++88w6aN28Oe3t7eHt7o0+fPlizZg1ExCx1mDdvHgICAmBvb48uXbpgz549OvMXLFiAnj17wsXFpcy/e+vWrUOPHj3g7OwMR0dHPPTQQxV+3VfkH4zTp08jJCQEjo6O8PT0xOTJk3H37l1l/po1a9C3b1/Uq1cPLi4uCAoKwsaNG0vknDlzBi+++CJ8fX2hVqvh7++PCRMm4NKlSwbX29DPhLi4OAwePBg+Pj6oXbs22rdvj6VLl5Yot2rVKuU10aZNG6xfv16Zd+fOHYSHh6NNmzaoXbs2fH198cILLyAzM1MnIyAgACqVSudR2nvFVNhpohpr0aJFePXVV7F169YSb0ytBx54AD/++KPOtB9++AEPPPCAzrTY2FgMHToUTz31FPbs2YPExERMnz4dd+7cMXudy5Kfn2+0uri6upr9w9jYjh8/Dh8fH3Tr1g3e3t6ws7MrUcaYbWYoPz+/Eh/M586dQ2xsLHx8fMxen4q4evUqunXrhh9//BFTp07Fvn37sHXrVgwdOhRTpkxBTk6OyeuwYsUKvPHGG4iIiMC+ffvQrl07BAcH48KFC0qZGzduoH///nj77bf15nz55ZcYPHgwunfvjt27d+PAgQMYNmwYwsLC8Oabbxq93gUFBQgJCUF+fj527NiBH374AVFRUZg2bZpSZuvWrejbty/Wr1+PxMRE9OrVC4MGDUJSUpJS5sSJE+jUqRPS09MRHR2NY8eO4ZtvvkFsbCyCgoJw+fJlo9Z7x44daNu2LVavXo0DBw5g1KhReOGFF7Bu3TqdMsOHD8fo0aORlJSEIUOGYMiQITh06BCAe/tj3759eO+997Bv3z6sWbMGqampePzxx0us78MPP0RWVpbyePXVV426PWWSGuL333+X7t27i6urq9StW1dCQkLk2LFjyvyMjAwBICtWrJCHH35Y7O3tpVOnTpKamip79uyRjh07Su3ataV///5y4cIFZbktW7bIQw89JI6OjuLq6irdunWTkydPiohIaGioDB48WKceEyZMkB49ehhcr9Js2bJFAMiGDRukffv2Ym9vL7169ZLz58/L+vXrpXnz5uLs7CzDhw+X69evK8sVFBTIjBkzJCAgQOzt7aVt27ayatUqne0v+ggNDRURkVu3bsmrr74q9erVE41GI927d5c9e/aUqM+6deukTZs2otFopEuXLnLw4MFy98vatWulU6dOotFoxN3dXYYMGVLuMkWFhoZKREREhZYREbl27Zo4OTnJ0aNHZejQoTJ9+nSd+dr2ePfdd6Vp06Y685o1aybvvfeeAJCMjAwRubdfe/bsWeY6IyIipF27diWma9eVlJRUpTqXxt/fXz788EN5/vnnxdnZWdmnU6ZMkaZNm4qDg4M0bNhQ3n33XcnPz9dZdubMmeLp6SlOTk7y4osvSnh4uE79i7++DX2PrV69Wnr27CkODg7Stm1b2bFjh856t23bJj169BAHBwdxc3OTfv36yeXLl0Wk7NewiMjly5flX//6l3h4eIi9vb00adJEvv/++1LbJjQ0VOf17u/vLyIiPXr0kPHjx8uECRPE3d1d2a9xcXHy0EMPiVqtFm9vbwkPD5c7d+4oeT169JB///vfMmHCBHFzcxNPT09ZsGCB5OXlyciRI8XJyUkaN24s69evL3Of9ejRQ8aNGyfu7u6ybds2Zfr06dNl0KBB0q5dO53X/K1bt2TSpEni6+srjo6O0rlzZ9myZYuI/PPeLPrQLnv58mV5/vnnxc3NTRwcHKR///6Slpam5C5evFhcXV0lJiZGmjRpIhqNRvr16yenT58us/7jxo2T2rVry7lz50rMu3btmk6bmUrnzp1l/PjxyvOCggLx9fWVmTNnliirbaMrV67oTD99+rTUqlVL3njjjRLLfPHFFwJAdu3apUw7dOiQhISEiLOzszg5OcnDDz8sx44dk4iIiBL7QLt/ilu/fr3Y2NhIdna2Mm3+/Pni4uIit2/f1ru9LVu2lA8++EB53r9/f6lfv77cuHFDp1xWVpY4OjpKWFiYMu3WrVsyZcoUqV+/vqjVamncuLF89913ZX4mGGLgwIEyatQo5fmzzz4rISEhOmW6dOkiL7/8st6MPXv2CAA5deqUMs3f31/mzJljcD2MrcZ0mn766SdZvXq1pKenS1JSkgwaNEjatGkjBQUFIvLPH/TmzZvLhg0b5MiRI9K1a1fp2LGj9OzZU7Zt2yb79u2TJk2aKC+4O3fuiKurq7z55pty7NgxOXLkiERFRSk72JBOU3n1Ko32Td61a1edevXo0UP69esn+/btk61bt4q7u7t8/PHHynL/+c9/lO07fvy4LF68WDQajcTFxcndu3dl9erVAkBSU1MlKytLrl69KiIir732mvj6+sr69evl8OHDEhoaKnXq1JFLly7p1KdFixbyxx9/yIEDB+Sxxx6TgICAEh/ERa1bt05sbW1l2rRpcuTIEUlOTpYZM2YYvlOl8p2mRYsWSadOnURE5Ndff5XGjRtLYWGhMl/7etizZ494eHjIX3/9JSIif/31l9SrV095M2s7TTNnzpR69eqV2VGsaqepvDqXxt/fX1xcXOSzzz6TY8eOKZ2Yjz76SLZv3y4ZGRmydu1a8fLyklmzZinLrVixQjQajXz33Xdy9OhReeedd8TZ2bnMTlNF3mPr1q2T1NRUefrpp8Xf31/5IE1KShKNRiPjxo2T5ORkOXTokHz55Zfy999/i0jZr2ERkfHjx0v79u1l7969kpGRIZs2bZK1a9eW2jZXr16VDz/8UOrXry9ZWVnKP0M9evQQJycnmTx5shw9elSOHj0qZ8+eFUdHR3nllVckJSVFYmJixMPDQ+e116NHD3F2dpaPPvpI0tLS5KOPPhJbW1sZMGCALFiwQNLS0pTOUNF/Zorr0aOHTJgwQV577TUZPXq0Mr1p06YSExNTotM0ZswY6datm2zdulWOHTsmn376qWg0GklLS5Pbt2/L3LlzxcXFRbKysiQrK0uuXbsmIiKPP/64tGjRQrZu3SrJyckSHBwsTZo0Ud6zixcvllq1akmnTp1kx44dkpCQIJ07d5Zu3brprXtBQYHUqVNHXnrpJb1lTO327dtia2srMTExOtNfeOEFefzxx0uU19dpmj17tgCQzMzMUtfh5OQkEyZMEBGRs2fPSt26deXJJ5+UvXv3Smpqqnz//fdy9OhRuXbtmjz77LPSv39/ZR/o6wC99957Jf5GnDhxQgDIvn37Sl2moKBA/Pz85MsvvxQRkUuXLolKpdL7t3Ts2LFSp04d5W/Hs88+K35+frJmzRo5fvy4bN68WZYvX17mZ4IhunfvLpMmTVKe+/n5lejsTJs2Tdq2bas3Y9OmTaJSqSQnJ0eZ5u/vL15eXlK3bl1p3769fPLJJ2bpiGvVmE5TcX///bcAUD7ktH/Qv/vuO6VMdHS0AJDY2Fhl2syZMyUwMFBE7r04ASh/sIszpNNUXr1Ko32Tb968WadeAOT48ePKtJdfflmCg4NF5N5/E46OjiX+qx89erQMHz5cJ7foH4+8vDypVauWLF26VJmWn58vvr6+8sknn+gst3z5cqXMpUuXxMHBQVasWKF3O4KCgmTEiBF65xuisp2mbt26ydy5c0XkXufXw8ND57+/oh2ZiRMnKv8xjRo1Sl5//XVJSkrS6TTl5eXJwIEDlSMWQ4cOlUWLFsmtW7eUzKp2msqrc2n8/f0NOnr36aefSseOHZXnQUFB8sorr+iU6dKlS5mdpuIMeY8dPnxYAEhKSoqIiAwfPly6d+9eap4hr+FBgwbp/Hdbnjlz5ihHmLR69OghDz74oM60t99+WwIDA3U6qfPmzRMnJyelU9ijRw95+OGHlfl3796V2rVry/PPP69My8rKEgCyc+dOvXXSdpqSk5PF2dlZ8vLyJD4+Xjw9PeXOnTs6naZTp06Jra1tiaM6vXv3lqlTp4rIP0eMikpLSxMAsn37dmXaxYsXxcHBQVauXKksV/xoSkpKigCQ3bt3l1r38+fPCwCZPXu23u0ztXPnzgmAEq+TyZMnS+fOnUuU19dpCgsLK9FuRbVt21YGDBggIiJTp06Vhg0b6v0nsbz3itbYsWOlX79+OtOuX78uAPQeoZw1a5bUqVNHzp8/LyIiu3btEgAlOo1a2s7g+fPnJTU1VQDIpk2bSi2rr23Ks2LFClGr1XLo0CFlWq1atWTZsmU65ebNmyeenp6lZty8eVM6dOgg//rXv3Smf/7557JlyxbZv3+/zJ8/X9zc3OT111+vUP2qosZc05Seno7hw4ejUaNGcHFxQUBAAIB7F90V1bZtW+V3Ly8vAECbNm10pmnPi9etWxcjR45EcHAwBg0ahMjISGRlZRm1XgMGDICTkxOcnJzQqlWrMuvq6OiIRo0alVrXY8eO4caNG+jbt6+S5+TkhB9//BHHjx/XW7/jx4/jzp076N69uzKtVq1a6Ny5M1JSUnTKBgUFKb/XrVsXgYGBSpmi6wwLCwMAJCcno3fv3ga3lbGkpqZiz549GD58OADAzs4OQ4cOxaJFi0ot/+KLL2LVqlXIzs7GqlWr8OKLL5YoU7t2bfz22284duwY3n33XTg5OWHSpEno3Lkzbty4UaH6ldZWFa1zUZ06dSoxbcWKFejevTu8vb3h5OSEd999V+e9kJKSgi5duugsU3T/lqYy7zHt9Tna12lZrwlDXsPjxo3D8uXL0b59e0yZMgU7duwos876dOzYUed5SkoKgoKCoFKplGndu3dHXl4ezp49W+q22drawt3dvcTfj6LbW5Z27dqhadOm+Omnn/D999/j+eefL3HN1cGDB1FQUIBmzZrptEl8fHyZ7+uUlBTY2dnp7GN3d3ed9yxw73X20EMPKc+bN28ONzc3pKSk4PTp0zrrnDFjhtku8rY2ycnJeOSRR1CrVi2Dlynrb7uhli1bhg8++AArV66Ep6enzjxD9kVycjJsbW3Ro0ePSq2/NFu2bMGoUaOwcOHCSm/XnTt38Oyzz0JEMH/+fJ15b7zxBnr27Im2bdsiLCwMn3/+Ob788kvcvn3bGNUvV8mrHqupQYMGwd/fHwsXLoSvry8KCwvRunXrEhd5Fn3Ra/9AFp9WWFioPF+8eDFee+01bNiwAStWrMC7776LTZs2oWvXrrCxsSnxwi1+YXB59fruu+9w8+bNEvUorV7F5xeta15eHgDgt99+K3ERs0ajKbXNjKnonWEuLi4AAAcHB5OvtzSLFi3C3bt34evrq0wTEWg0Gnz11VdwdXXVKd+mTRs0b94cw4cPR4sWLdC6dWu9d7o1btwYjRs3xpgxY/DOO++gWbNmWLFiBUaNGgUXF5dSL4LV3pmiXW9pbVXROhdVu3Ztnec7d+7EiBEj8MEHHyA4OBiurq5Yvnw5Pv/8c70ZhqjKe0z7Oi3rNWHIa3jAgAE4deoU1q9fj02bNqF3794YP348PvvsswptS/E2M1Rp78Gytrc8L774IubNm4cjR46UuPsLuNcmtra2SExMhK2trc48Jyenila/Qnx9fXVeq3Xr1oWbmxvc3Nxw9OhRk667LB4eHrC1tcX58+d1pp8/fx7e3t4G5zRr1gw5OTnIzMzUed8B924OOH78OHr16gWgcn/LSvvb7u3tXWI/a7ejeN2XL1+OMWPGYNWqVejTp48yvUmTJlCpVEhJScETTzxRYr0pKSmoU6cO6tWrZ/S/wfHx8Rg0aBDmzJmDF154QWeet7e3QftE22E6deoU/vzzT+VvoD5dunTB3bt3cfLkSQQGBhpnQ8pQI440Xbp0CampqXj33XfRu3dvtGjRAleuXDFa/oMPPoipU6dix44daN26NZYtWwYAqFevXokjT0X/yBhSrwceeABNmjRBkyZN4O/vX+k6tmzZEhqNBqdPn1bytA8/Pz8AgFqtBnDvDg6txo0bQ61WY/v27cq0O3fuYO/evWjZsqXOOnbt2qX8fuXKFaSlpaFFixYAoLM+7X9Ebdu2RWxsbKW3qTLu3r2LH3/8EZ9//jmSk5OVx/79++Hr64vo6OhSl3vxxRcRFxdX6lEmfQICAuDo6Ijr168DAAIDA3H27NkSfzj27dsHe3t7NGjQAEDJtqpsnfXZsWMH/P398c4776BTp05o2rQpTp06pVOmRYsW2L17t860ovu3OGO9x8p6TRjyGgbuve9CQ0OxZMkSzJ07FwsWLKhwPYpr0aIFdu7cqfNP0Pbt2+Hs7Iz69etXOV+ff/3rXzh48CBat25d4v0G3PvbU1BQgAsXLpRoE+2HkVqt1nlPa7fn7t27OvtYuw+Lrufu3btISEhQnqempuLq1ato0aIF7OzsdNZXt25d2NjYYNiwYVi6dGmpd3fm5eXp3D5vCmq1Gh07dtR5HRUWFip3jhnqqaeeQq1atUr9Z+Kbb77B9evXlSO/bdu2xV9//aX3btnS9kFpf9uDgoJw8OBBnSORmzZtgouLi85+iY6OxqhRoxAdHV1i+BF3d3f07dsXX3/9tdIp08rOzsbSpUsxdOhQqFQqtGnTBoWFhYiPj9dbbwAl6l6auLg4hISEYNasWXjppZdKzA8KCirx3t60aZPOPtF2mNLT07F582a4u7uXu97k5GTY2NiUONJmMmY7EWhBBQUF4u7uLs8995ykp6dLbGysPPTQQzrnfUu7rqS087lFrw84ceKEvPXWW7Jjxw45efKkbNy4Udzd3eXrr78WEZENGzaISqWSH374QdLS0mTatGni4uKiXNNkSL1KU169tIpfQ/POO++Iu7u7REVFybFjxyQxMVG++OILiYqKEpF7FzOqVCqJioqSCxcuKBeMTpgwQXx9feX333/XuRBce0eTtj6tWrWSzZs3y8GDB+Xxxx+XBg0alHnHx5YtW8TGxka5EPzAgQM6F64boqLXNMXExIharS71gsYpU6YoF1oXfz3cuXNH/v77b50LllHkmqaIiAiZPHmybNmyRU6cOCH79u2TkSNHioODgxw9elTJaNWqlfTq1Uu2b98ux48fl1WrVomPj4+Eh4dXuc6lKe1Ok19++UXs7OwkOjpajh07JpGRkVK3bl2d18/y5cvF3t5evv/+e0lNTZVp06aVeSF4Zd9jV65c0bmbKDU1VdRqtYwbN072798vKSkp8vXXXysXgpf3Gn7vvffk559/lvT0dDl06JA89thjpV7HoqXvmibtBb5a2gvBx48fLykpKfLzzz+XeiF48eVKa//y3t/Fc65cuSJ5eXnK8+IXgo8YMUICAgJk9erVcuLECdm9e7fMmDFD1q1bJyIi27dvV66B/Pvvv5WL0AcPHiwtW7aUv/76S5KTk6V///6lXgjeuXNn2bVrlyQkJEjXrl2la9eueusucu96xubNm0v9+vXlhx9+kMOHD0taWposWrRImjRpUuHrYypj+fLlotFoJCoqSo4cOSIvvfSSuLm56dyVlpWVJUlJSbJw4UIBIFu3bpWkpCTlBheRe68PGxsbefvttyUlJUWOHTsmn3/+uWg0Gp2LnC9evCju7u7KheBpaWny448/Ku/96dOnS4MGDeTo0aPy999/67326e7du9K6dWvp16+fJCcny4YNG6RevXrK9WkiIkuXLhU7OzuZN2+ecmF58Yu009LSxMPDQx555BGJj4+X06dPy++//y6tW7eWpk2b6mzjyJEjxc/PT2JiYuTEiROyZcsW5VpUfZ8Jxf3555/i6OgoU6dO1alT0fVs375d7Ozs5LPPPpOUlBSJiIiQWrVqKdc85ufny+OPPy7169eX5ORknRzt58iOHTtkzpw5kpycLMePH5clS5ZIvXr15IUXXijnFWE8NaLTJHLvKvwWLVqIRqORtm3bSlxcXJU7TdnZ2TJkyBDx8fERtVot/v7+Mm3aNJ0736ZNmyZeXl7i6uoqr7/+uvz73//WuRC8vHqVprKdpsLCQpk7d64EBgZKrVq1pF69ehIcHCzx8fFKmQ8//FC8vb1FpVIpt5fevHlTXn31VfHw8ChzyIFff/1VWrVqJWq1Wjp37iz79+/Xuw1aq1evlvbt24tarRYPDw958skny12mqIp2mh577DEZOHBgqfN2794tAGT//v3lXpxdvNP0559/ylNPPSV+fn6iVqvFy8tL+vfvr9x1p3Xu3DkJDQ2VBg0aiIODg7Rs2VI+/vjjMu8yNLTOpdF3e+7kyZPF3d1dnJycZOjQoTJnzpwSr5/p06eLh4eHODk5SWhoqEyZMqXMC8Er8x4r3mkSuXdrf7du3USj0Yibm5sEBwcrr/XyXsMfffSRtGjRQhwcHKRu3boyePBgOXHiRKltI2J4p0lbr/KGHDBFp6m44p2m/Px8mTZtmgQEBEitWrXEx8dHnnjiCTlw4IBSJiwsTNzd3UsdcsDV1VUcHBwkODi41CEHVq9eLY0aNRKNRiN9+vTRuf1bn6tXr8pbb70lTZs2Vd4Pffr0kZiYmHLv+DSWL7/8Uho0aKD8PSp6QbuIlDoUAABZvHixTrlffvlFHnnkEaldu7bY29tLx44dSx3GYv/+/dKvXz9xdHQUZ2dneeSRR5Qbcy5cuCB9+/YVJyenMoccEBE5efKkDBgwQBwcHMTDw0MmTZpU4nVWWr2LDwdw8uRJCQ0NFS8vL6lVq5b4+fnJq6++KhcvXtQpd/PmTXn99deVz7Hiw3SU9plQXPHhO7SP4jc9rVy5Upo1ayZqtVpatWolv/32mzKvtCEOtA9teyUmJkqXLl3E1dVV7O3tpUWLFjJjxgydG25MTSVSQ6/cI6OJi4tDr169cOXKFbMPdjhy5EgEBATwq1SIjCwqKgoTJ06sMd8QQGSIGnFNExEREVFVsdNEREREZACenqP72s8//ww3Nzf07NnT0lUhIqJqjp0mIiIiIgPw9BwRERGRAdhpIiIiIjJAtf8alcLCQmRmZsLZ2Vnne6OIiIio+hARXLt2Db6+vrCxMc0xoWrfacrMzNT5igUiIiKqvs6cOWOyrzeyaKdp69at+PTTT5GYmIisrCzExMRgyJAhyvyRI0fihx9+0FkmODgYGzZsMHgdzs7OAO59Z9KXX34JAHj77bd1vpAzKSkJP/74I9q1a4eRI0fqLB8VFYX9+/fjhRdewIMPPqhMv379OmbMmME85jGPecxjHvOsIC83Nxd+fn7K575JmG3s8VKsX79e3nnnHVmzZk2pXy0QGhoq/fv31/kOGu33nRkqJydHAEh4eLjk5eVJXl6eTJs2Tfkup4SEBFmwYEGJ30VEFixYIAkJCSV+L5rBPOYxj3nMYx7zLJ+n/eqmnJwcMRWrGXJApVKVeqTp6tWr+Pnnnyudm5ubC1dXV2RmZsLHxwfAvV7qJ598gt69eyM1NRVjx45VyicmJmLfvn0AgA4dOqBjx47KvIULFyIwMBCxsbGYMmWK0rtlHvOYxzzmMY95ls1LTk7GhAkTkJOTAxcXF5iEybpjFQQ9R5pcXV2lXr160qxZMwkLCyvxZYPF3bp1S3JycpTHmTNnSu15xsfHi6+vr863h2uFhYVJWFhYiel5eXni6+ur8wW3zGMe85jHPOYxz/J5mZmZJj/SZNVDDvTv3x8//vgjYmNjMWvWLMTHx2PAgAEoKCjQu8zMmTPh6uqqPLQXgSclJSllEhMTkZqairS0NHzyySe4fv26Mm/hwoUYM2YMxowZg4ULFyrTtb3ZtLQ0pKamIjExkXnMYx7zmMc85llJXmRkJEzOZN2xCkIpR5qKO378uACQzZs36y2j70hTZGSkJCQklDhvWvScaNHzpiL/nGMtft5U5J9zrMxjHvOYxzzmMc/yeeY40nRfdZpERDw8POSbb74xOFd7IXhOTo5VHUZkHvOYxzzmMY95xssr+nlvKlZ9eq64s2fP4tKlS8oF3RWRlJSEDh06oEOHDjqH9gBg2bJliI6ORmxsrM6hwuvXryM2NhbR0dFYtmyZzjKJiYnMYx7zmMc85jHPivJMzmTdMQNcu3ZNkpKSJCkpSQDI7NmzJSkpSU6dOiXXrl2TN998U3bu3CkZGRmyefNm6dChgzRt2lRu3bpl8Dq0Pc/IyEhlmjXcGsk85jGPecxjHvOMlxcZGVm9T89t2bJFAJR4hIaGyo0bN6Rfv35Sr149qVWrlvj7+8vYsWMlOzu7QuvQd7huwYIFEhYWpnMOVeTejps0aZJMmjSpxCHBhIQECQsL09lhzGMe85jHPOYxz/J55hinyaKn52xsbPDYY48pp9tiYmIgIoiKioKDgwM2btyICxcuID8/H/3798fChQsRHR1tySoTERFRTWWy7pgByhsRXGvNmjXSrl078fX1lTlz5lRoHTw9xzzmMY95zGNe9c8zx+k5qx4RHADOnTuHLl26YOPGjQgJCcHEiRMxceJEg3O1I4LHxcUhLS0NgHWMXMo85jGPecxjHvOMl6f9vK+xI4IXFBRIr169ZO7cuSIi4u/vX+6RprJGBL8fb6FkHvOYxzzmMY955efV+CEHZs2aBTs7O7z22msGL6NvRPCoqCirGrmUecxjHvOYxzzmGTfP5EzWHasgFDvSlJCQIF5eXnLu3DllWlWONMXFxelkL1hQvUZCZR7zmMc85jGvJueFh4dX7yEHiireaZozZ46oVCqxtbVVHgDExsZG/P39Dc7Vd7jO0ocRmcc85jGPecxjnvHyavQX9j7//PM4cOAAkpOTlYevry8mT56MjRs3VjjPGkcuZR7zmMc85jGPecbJW7VqFUzOZN0xA5Q1InhpDDk9V5z2SFN4eLjk5VnPrZHMYx7zmMc85jHPeHnmGNzSokMOREZGljp8QGhoKKKiovD+++9j+fLlOHPmDNRqNW7duoWwsDDMmTPH4HVob0GsBUBlvKrXaHcsXYFqyCrG/ahm+H43Lr5G6X5hyiEHLHp6rlmzZnjnnXewZs0aALojgmvnf/XVVzh48CC2bduGESNG4Pvvv8fff/9twVoTERFRTWT1g1sWpT1qtHnzZvTu3dugXB5pMj4eaTI+q3gTVjN8vxsXX6N0v6i2R5oqIj8/HwsWLICrqyvatWtn6eoQERFRDWNn6QqUZ926dRg2bBhu3LgBHx8fbNq0CR4eHnrL3759G7dv31ae5+bmmqOaREREVM1Z/ZGmXr16ITk5GTt27ED//v3x7LPP4sKFC3rL6xsRnIiIiKgqrL7TVLt2bTRp0gRdu3bFokWLYGdnh0WLFuktP3XqVOTk5CiPM2fOmLG2REREVF1Z/em54goLC3VOvxWn0Wig0WjMWCMiIiKqCSzaacrLy8OxY8eU5xkZGUhOTkbdunXh7u6O6dOn4/HHH4ePjw8uXryIefPm4dy5c3jmmWcsWGsiIiKqiSzaaUpISECvXr2U52+88QaAe4NbfvPNNzh69Ch++OEHXLx4Ee7u7njooYfw119/oVWrVpaqMhEREdVQFr2mycbGBo899hh8fHwA6A5uaWtri6ZNm6Ju3bqws7vXt3N1dcUDDzxQqXWp+DDag4zP0vu0Oj6IiIzNop2m69evo127dpg3b16JeTdu3MC+ffvw3nvvYd++fVizZg1SU1Px+OOPW6CmREREVNPdVyOC7927F507d8apU6fQoEEDg3K1I4Krwf8+jSXf0hUgIrOzig8KIgOYckTw++ruuZycHKhUKri5uektw8EtiYiIyBSsfpwmrVu3biE8PBzDhw8vswfJwS2JiIjIFO6LTtOdO3fw7LPPQkQwf/78MstycEsiIiIyBas/PaftMJ06dQp//vlnuecpObglERERmYJVd5q0Hab09HRs2bIF7u7ulq4SERER1VBWOyK4j48Pnn76aezbtw/r1q1DQUEBsrOzAQB169aFWq22VLWJiIioBrLokANxcXE6I4JrhYaG4v3330fDhg1LXW7Lli3o2bOnQevQDjlQCxxywFjuWLoC1RBv5yYiMg5TDjlgtSOCBwQEYPXq1ejbty/q1q0LAEhKSoKIGNxhIiIiIjIWqx0RXDv/4YcfxqxZs8xcMyIiIiJdFr2macCAARgwYIDe+c8//zwA4OTJk2aqEREREVHprPruucrgiOBERERkCpU6PXfz5k3cuHFDeX7q1CnMnTsXf/zxh9EqVlkcEZyIiIhMoVKdpsGDB+PHH38EAFy9ehVdunTB559/jsGDB5c7YrepcURwIiIiMoVKdZr27duHRx55BADw008/wcvLC6dOncKPP/6IL774wqgVrCiNRgMXFxedBxEREVFVVarTdOPGDTg7OwMA/vjjDzz55JOwsbFB165dcerUKaNWkIiIiMgaVOpC8CZNmuDnn3/GE088gY0bN+L1118HAFy4cKFCR3bKGhG8QYMGuHz5Mk6fPo3MzEwAQGpqKgDA29sb3t7elak6ERERUeVIJaxatUpq1aolNjY20rdvX2X6jBkzpH///gbnbNmyRXBvMGSdR2hoqIiILF68uNT5ERERBq8jJydHAEgtQNR8GOVR2j7hgw8++OCDD2t45OTkGNxHqKhKHWl6+umn8fDDDyMrKwvt2rVTpvfu3RtPPPGEwTnaEcETExORlZWFmJgYDBkyRJkfGhqKEydOYOHChbh69Sq6d++O+fPno2nTppWpNhEREVGlVXpEcG9vbzz44IOwsfknonPnzmjevLnBGeWNCP7JJ5/giy++wDfffIPdu3ejdu3aCA4Oxq1btypbbSIiIqJKMfgLe5988kmDQ9esWVPxiqhUOkeaRAS+vr6YNGkS3nzzTQD3voTPy8sLUVFRGDZsmEG5/MJe48u3dAWIiIj0MOUX9hp8es7V1dUkFdAnIyMD2dnZ6NOnj04dunTpgp07d+rtNHFEcCIiIjIFgztNixcvNmU9SsjOzgYAeHl56Uz38vJS5pVm5syZ+OCDD0xaNyIiIqp5Kn1N0927d7F582Z8++23uHbtGgAgMzMTeXl5RqtcZXBEcCIiIjKFSt09d+rUKfTv3x+nT5/G7du30bdvXzg7O2PWrFm4ffs2vvnmmypXTDsO0/nz5+Hj46NMP3/+PNq3b693OY1GA41GU+X1ExERERVVqSNNEyZMQKdOnXDlyhU4ODgo05944gnExsYapWINGzaEt7e3Tl5ubi52796NoKAgo6yDiIiIyFCVOtL0119/YceOHVCr1TrTAwICcO7cOYNzyhsRfOLEifjPf/6Dpk2bomHDhnjvvffg6+urM5YTERERkTlUqtNUWFiIgoKCEtPPnj2rfCedIRISEtCrVy/l+RtvvAHg3qCWUVFRmDJlCq5fv46XXnoJV69excMPP4wNGzbA3t6+wnVWgUMOGAvb0fgMGveDKoSvU6KaxRx/Ryt1eq5fv36YO3eu8lylUiEvLw8REREYOHCgwTk9e/aEiJR4REVFKbmTJ0/GsGHD4OXlhe3bt2PkyJHYu3dvZapNREREVGkGD25Z1NmzZxEcHAwRQXp6Ojp16oT09HR4eHhg69at8PT0NFoFhw4dikOHDmH+/Pnw9fXFkiVLMGfOHBw5cgQPPPBAuctrB7dUg/95GgsHtzQ+HmkyPr7fiWoW7d9RUw5uWalOE3BvyIHly5fjwIEDyMvLQ4cOHTBixAidC8Or6ubNm3B2dsYvv/yCkJAQZXrHjh0xYMAA/Oc//yk3g50m42OnyfjYaTI+vt+JahZzdJoqdU0TANjZ2eG5554zZl1KuHv3LgoKCkpcw+Tg4IBt27aVugxHBCciIiJTqHSnKT09HVu2bMGFCxdQWFioM2/atGlVrhgAODs7IygoCB999BFatGgBLy8vREdHY+fOnWjSpEmpy3BEcCIiIjKFSp2eW7hwIcaNGwcPDw94e3tDpfrnQLhKpcK+ffuMVsHjx4/jxRdfxNatW2Fra4sOHTqgWbNmSExMREpKSonypR1p8vPz4+k5I+LpOePj6Tnj4/udqGax2mua/P398corryA8PNwUdSrV9evXkZubCx8fHwwdOhR5eXn47bffyl2O1zQZHztNxsdOk/Hx/U5Us5ij01SpIQeuXLmCZ555xth1KVPt2rXh4+ODK1euYOPGjRg8eLBZ109EREQ1W6U6Tc888wz++OMPY9elVBs3bsSGDRuQkZGBTZs2oVevXmjevDlGjRpllvUTERERAQCkEmbMmCEeHh4SGhoqn332mURGRuo8jGnFihXSqFEjUavV4u3tLePHj5erV68avHxOTo4A0KnXggULJCEhocTveXl5Mm3aNMnLy9P5XUQkISFBFixYUOJ35jGPecxjHvOYZ/m8yMhIASA5OTliKpXqNAUEBOh9NGzY0GiVu3v3rrz77rsSEBAg9vb20qhRI/nwww+lsLDQ4Axtp6l4Iy5YsEDCwsKUxtbKy8uTSZMmyaRJk5QdppWQkCBhYWE6O4x5zGMe85jHPOZZPi8uLs7knaZKDTmQkZFhzINdes2aNQvz58/HDz/8gFatWiEhIQGjRo2Cq6srXnvtNbPUgYiIiAhA5U7PmUtISIi8+OKLOtOefPJJGTFihMEZPD3HPOYxj3nMY171zzPH6blKDTlQUFCAqKgoxMbGljq45Z9//mmUDt2MGTOwYMEC/PHHH2jWrBn279+Pfv36Yfbs2RgxYkSpy+gbpykuLg5paWkAgA4dOqBjx45KmYULFyIwMBCxsbGYMmUKateuDeDeMAeffPIJevfujdTUVIwdO1ZZJjExURmPinnMYx7zmMc85lk2TzvEkCmHHKjUkabx48dL7dq15dlnn5UJEybIxIkTdR7GUlBQIOHh4aJSqcTOzk5UKpXMmDGjzGUiIiIE94Zr0Hnk5ORIWFiYhIWFlVgmLy9PfH19JT4+vsS8+Ph48fX1LXF+VUSYxzzmMY95zGOeleTpu4bZmCrVaXJ3d5fffvvN2HUpITo6WurXry/R0dFy4MAB+fHHH6Vu3boSFRWld5lbt25JTk6O8jhz5oxyei4hIaHEob2ihwGLHuYT+ecwYPFDhSL/HBJkHvOYxzzmMY95ls/LzMy0zk6Tj4+PpKamGrsuJdSvX1+++uornWkfffSRBAYGGpyh7XnGxcUp06xh5zKPecxjHvOYxzzj5YWHh1tnp+mzzz6TV155pUK3/ldG3bp15euvv9aZNmPGDGnatKnBGfoO11n6MCLzmMc85jGPecwzXp45jjRVakTwbdu2YenSpWjcuDEGDRqEJ598UudhLIMGDcL06dPx22+/4eTJk4iJicHs2bPxxBNPVDjr+vXrOr/HxsYiOjoay5Yt0ymXmJiIDh06oEOHDkhMTNSZt2zZMkRHRyM2NpZ5zGMe85jHPOZZUd6qVatgapW6e668rzBZvHhxpStU1LVr1/Dee+8hJiYGFy5cgK+vL4YPH45p06ZBrVYblMEv7DW+O5auQDXEL+wla8e/n2TttHd+mfLuuUp1mswpICAAp06dKjH9lVdewbx588pdnp0m42Onyfis+k1IBP79JOtnjk5TpUYEN6e9e/eioKBAeX7o0CH07dsXzzzzjAVrRURERDVNpTtNP/30E1auXInTp08jPz9fZ5520CljqFevns7zjz/+GI0bN0aPHj2Mtg4iIiKi8lTqQvAvvvgCo0aNgpeXF5KSktC5c2e4u7vjxIkTGDBggLHrqMjPz8eSJUvw4osvQqUq/WDx7du3kZubq/MgIiIiqqpKdZq+/vprLFiwAF9++SXUajWmTJmCTZs24bXXXkNOTo6x66j4+eefcfXqVYwcOVJvmZkzZ8LV1VV5+Pn5maw+REREVHNU6kJwR0dHpKSkwN/fH56enti0aRPatWuH9PR0dO3aFZcuXTJFXREcHAy1Wo1ff/1Vbxl93z3HC8GNhxeCGx8vBCdrx7+fZO3McSF4pY40eXt74/LlywCABg0aYNeuXQCAjIwMmOpmvFOnTmHz5s0YM2ZMmeU0Gg1cXFx0HkRERERVValO06OPPoq1a9cCuDdm0+uvv46+ffti6NChlRp40hCLFy+Gp6cnQkJCTJJPREREVJZKnZ4rLCxEYWEh7Ozu3Xy3fPly7NixA02bNsXLL79s8MCTFVlfw4YNMXz4cHz88ccVWpbjNBkfT88ZH0/PkbXj30+yduY4PVep754zt40bNwqASn1JsPa75yIjI5VpRb/wr+jvRb8UsPiXCRb9AsHiXybIPOYxj3nMYx7zLJsXGRlpnV/YKyJy5coV2bhxo/z3v/+VH374QedhTGfPnpURI0ZI3bp1xd7eXlq3bi179+41eHl9X9i7YMECCQsL0/m2ZJF7O27SpEkyadKkEl8mmJCQIGFhYTo7jHnMYx7zmMc85lk+Ly4uzuSdpkoNbvnrr79ixIgRyMvLg4uLi86YSSqVCi+88IIxDoLhypUr6N69O3r16oXff/8d9erVQ3p6OurUqWOUfCIiIiKDVaan1bRpU5kwYYJcv37d2J04HeHh4fLwww9XKYOn55jHPOYxj3nMq/555jg9V6kLwWvXro2DBw+iUaNGxu/FFdGyZUsEBwfj7NmziI+PxwMPPIBXXnkFY8eO1buMvnGa4uLikJaWBgDo0KEDOnbsqJRZuHAhAgMDERsbiylTpqB27doAgOvXr+OTTz5B7969kZqaqrPexMRE5etimMc85jGPecxjnmXztDd+Wd2F4E888YSsWLHCuN23Umg0GtFoNDJ16lTZt2+ffPvtt2Jvby9RUVF6l4mIiNBeQK/zyMnJkbCwMAkLCyuxTF5envj6+kp8fHyJefHx8eLr61vi/KqIMI95zGMe85jHPCvJ03cNszEZ3Gn65ZdflMd3330nDRo0kIiICPnpp5905v3yyy9Gq1ytWrUkKChIZ9qrr74qXbt21bvMrVu3JCcnR3mcOXNGOT2XkJBQ4tBe0cOARQ/zifxzGLD4oUKRfw4JMo95zGMe85jHPMvnZWZmWk+nSaVSGfSwsbExWuUaNGggo0eP1pn29ddfi6+vr8EZ2p5nXFycMs0adi7zmMc85jGPecwzXl54eLj1dJosYfjw4SUuBJ84cWKJo09l0Xe4ztKHEZnHPOYxj3nMY57x8sxxpKlCX6Py559/omXLlsjNzS0xLycnB61atcJff/1VpWusinr99dexa9cuzJgxA8eOHcOyZcuwYMECjB8/vsJZ169f1/k9NjYW0dHRWLZsmU65xMREdOjQAR06dEBiYqLOvGXLliE6OhqxsbHMYx7zmMc85jHPivJWrVoFk6tID2vQoEEye/ZsvfMjIyNlyJAhVe7JFTV8+PASF3UHBgYavLz2SFN4eLjk5VnPrZHMYx7zmMc85jHPeHnmGNyyQp2mBg0ayJEjR/TOT0lJET8/vypXqqiIiAhp1aqVZGVlKY+///7b4OW1nabMzEyrGrmUecxjHvOYxzzmGS/PHHfPVWhE8PPnz6NWrVp659vZ2eHvv/+u9FGvsnK9vb2NnktERERksIr0sBo1aiQxMTF6569evVoaNmxY1Y6cjoiICHF0dBQfHx9p2LCh/Otf/5JTp07pLa9vyAGenmMe85jHPOYxr/rmmeP0XIVGBH/11VcRFxeHvXv3wt7eXmfezZs30blzZ/Tq1QtffPGF0Tp1v//+O/Ly8hAYGIisrCx88MEHOHfuHA4dOgRnZ+cS5d9//3188MEHJaZnZmbCx8cHgHWMXMo85jGPecxjHvOMl5ecnIwJEyZYz4jg2dnZ4uvrK35+fjJr1iz5+eef5eeff5aPP/5Y/Pz8xNfXV7Kzs03TvfufK1euiIuLi3z33Xelztd3pIlDDjCPecxjHvOYV33zrG7IAS8vL+zYsQOtW7fG1KlT8cQTT+CJJ57A22+/jdatW2Pbtm3w8vIyTe/uf9zc3NCsWTMcO3as1PkajQYuLi46DwBISkpSyiQmJiI1NRVpaWn45JNPdG5fXLhwIcaMGYMxY8Zg4cKFynRtbzYtLQ2pqak6t0Myj3nMYx7zmMc8y+ZFRkbC5Crb27p8+bLs2bNHdu/eLZcvXzZmR65M165dkzp16khkZKRB5bVX0/NrVJjHPOYxj3nMq755VvU1KpYyadIkiYuLk4yMDNm+fbv06dNHPDw85MKFCwYtX/QWRGs6jMg85jGPecxjHvPury/srdDpOUs4e/Yshg8fjsDAQDz77LNwd3fHrl27UK9evQrlJCUlWdXIpcxjHvOYxzzmMc+4eSZnsu6YCcycOVMAyIQJEwxepujpOS1ruDWSecxjHvOYxzzmGS8vMjKSp+e09uzZIwEBAdK2bdtKdZqKN+KCBdVrJFTmMY95zGMe82pynjnGabL603MAkJeXhxEjRmDhwoWoU6eOpatDRERENZHJumNG9MILL8jEiRNFRKRHjx5lHmnSN04TT88xj3nMYx7zmFd988xxeq5CI4JbwvLlyzF9+nRlFPKePXuiffv2mDt3bqnl9Y0IHhcXh7S0NADWMXIp85jHPOYxj3nMM15ebm4uXF1drWdEcHM7ffq0eHp6yv79+5VplT3SxCEHmMc85jGPecyrvnk1fsiBxMREXLhwAR06dICdnR3s7OwQHx+PL774AnZ2digoKCixjL4RwaOioqxq5FLmMY95zGMe85hn3DyTM1l3zAhyc3Pl4MGDOo9OnTrJc889JwcPHjQoQ9vzjIuLU6Zpz4kWP28q8s/50eLnTYuWLXoOlXnMYx7zmMc85lk+Lzw8nEMOFFfe6bni9B2us/RhROYxj3nMYx7zmGe8PKv7wt77mTWOXMo85jGPecxjHvOMk7dq1SqYnMm6Y0by9ddfS5s2bcTZ2VmcnZ2la9eusn79eoOX1x5pCg8Pl7w867k1knnMYx7zmMc85hkvzxyDW1p9p2nt2rXy22+/SVpamqSmpsrbb78ttWrVkkOHDhm0vLbTlJmZaVUjlzKPecxjHvOYxzzj5Znj7jk70x/LqppBgwbpPJ8+fTrmz5+PXbt2oVWrVhaqFREREdU4JuuOmcDdu3clOjpa1Gq1HD58uNQy+sZp4uk55jGPecxjHvOqb545Ts9Z/YjgAHDw4EEEBQXh1q1bcHJywrJlyzBw4MBSy+obETwzMxM+Pj4ArGPkUuYxj3nMYx7zmGe8vOTkZEyYMKHmjgiudfv2bUlPT5eEhAR56623xMPDo8JHmjjkAPOYxzzmMY951TePQw78j1qtRpMmTdCxY0fMnDkT7dq1Q2RkZKll9Y0InpSUpJSxlpFLmcc85jGPecxjnnHy9PULjMpk3TET6tWrl4SGhhpUVns1fWRkpCQkWM/IpcxjHvOYxzzmMc94eeY40mT1naa33npL4uPjJSMjQw4cOCBvvfWWqFQq+eOPPwxavugtiNZ0GJF5zGMe85jHPObxC3uN6sKFC3jhhRcQGBiI3r17Y+/evdi4cSP69u1boZykpCSrGrmUecxjHvOYxzzmGTfP5EzWHTOSGTNmSKdOncTJyUnq1asngwcPlqNHjxq8fNHTc1rWcGsk85jHPOYxj3nMM15eZGQkT88FBwfL4sWL5dChQ5KcnCwDBw6UBg0alHq4rjT6DtctWFC9RkJlHvOYxzzmMa8m55ljnCarHxF8w4YNOs+joqLg6emJxMRE/N///Z+FakVEREQ1jsm6YyaSnp4uAOTgwYOlztc3ThNPzzGPecxjHvOYV33zzHF67r4YEVyrsLAQjz/+OK5evYpt27aVWkbfiOBxcXFIS0sDYB0jlzKPecxjHvOYxzzj5eXm5sLV1ZUjgmuFhYWJv7+/nDlzRm+ZskYEvx9voWQe85jHPOYxj3nl53HIgSL+/e9/Y926ddiyZQvq16+vt5y+EcGjoqKsauRS5jGPecxjHvOYZ9w8kzNZd8xICgsLZfz48eLr6ytpaWkVXl7b84yLi1Omac+JFj9vKvLP+dHi502Lli16DpV5zGMe85jHPOZZPi88PJxDDowbN05cXV0lLi5OsrKylMeNGzcMWl7f4TpLH0ZkHvOYxzzmMY95xsvjF/YCmD9/PnJyctCzZ0/4+PgojxUrVlQoxxpHLmUe85jHPOYxj3nGyVu1ahVMzmTdMSOJj4+Xxx57THx8fASAxMTEVGh57ZGm8PBwycuznlsjmcc85jGPecxjnvHyzDG4pdV3mtavXy/vvPOOrFmzpkqdpszMTKsauZR5zGMe85jHPOYZL88cd89Z/YjgAwYMwIABAyxdDSIiIqrpTNYdMwEYcKRJ3zhNPD3HPOYxj3nMY171zTPH6bn7akRwlUqFmJgYDBkyRG8ZfSOCZ2ZmwsfHB4B1jFzKPOYxj3nMYx7zjJeXnJyMCRMmcERwLVThSBOHHGAe85jHPOYxr/rmcciBStA3InhSUpJSxlpGLmUe85jHPOYxj3nGyYuMjITJmaw7ZgKowt1zkZGRkpBgPSOXMo95zGMe85jHPOPlmeNIk9V3mq5duyZJSUmSlJQkAGT27NmSlJQkp06dMmj5q1evCgA5c+aMvKFOCu0AAChySURBVPjii/Liiy/qnL7LycmRzMxM8fb2lvXr15eYt379evH29pbMzMwS85jHPOYxj3nMY5515Gkvx7l69arJ+iRWfyF4XFwcevXqVWJ6aGgooqKiyl3+7Nmz8PPzM0HNiIiIyNqcOXMG9evXN0m21XeaqqqwsBCZmZlwdnaGSqWydHX0ys3NhZ+fH86cOWO6q/5rGLap8bFNjYvtaXxsU+O6n9pTRHDt2jX4+vrCxsY0l2xb/eCWVWVjY2OyHqcpFL14nYyDbWp8bFPjYnsaH9vUuO6X9nR1dTVpfrW7e46IiIjIFNhpIiIiIjIAO01WQqPRICIiAhqNxtJVqTbYpsbHNjUutqfxsU2Ni+2pq9pfCE5ERERkDDzSRERERGQAdpqIiIiIDMBOExEREZEB2GkiIiIiMgA7TSYwb948BAQEwN7eHl26dMGePXuUeQsWLEDPnj3h4uIClUqFq1evllh++vTp6NatGxwdHeHm5lZi/v79+zF8+HD4+fnBwcEBLVq0MM+3O1uIqdsTAPbu3YvevXvDzc0NderUQXBwMPbv32+iLbI8fW16+fJlvPrqqwgMDISDgwMaNGiA1157DTk5OTrLnz59GiEhIXB0dISnpycmT56Mu3fv6pSJi4tDhw4doNFo0KRJE4O+9uh+ZY72vH37Nt555x34+/tDo9EgICAA33//vdm20dyq2qavvfYaOnbsCI1Gg/bt25fIj4uLw+DBg+Hj44PatWujffv2WLp0qTk2zWJM3aYAsHHjRnTt2hXOzs6oV68ennrqKZw8edLEW2Y+7DQZ2YoVK/DGG28gIiIC+/btQ7t27RAcHIwLFy4AAG7cuIH+/fvj7bff1puRn5+PZ555BuPGjSt1fmJiIjw9PbFkyRIcPnwY77zzDqZOnYqvvvrKJNtkSeZoz7y8PPTv3x8NGjTA7t27sW3bNjg7OyM4OBh37twxyXZZUlltmpmZiczMTHz22Wc4dOgQoqKisGHDBowePVpZvqCgACEhIcjPz8eOHTvwww8/ICoqCtOmTVPKZGRkICQkBL169UJycjImTpyIMWPGYOPGjZbYZJMyR3sCwLPPPovY2FgsWrQIqampiI6ORmBgoLk31yyq2qZaL774IoYOHVrqOnbs2IG2bdti9erVOHDgAEaNGoUXXngB69atM/XmWYQ52jQjIwODBw/Go48+iuTkZGzcuBEXL17Ek08+aerNMx+TfRVwDdW5c2cZP3688rygoEB8fX1l5syZOuW2bNkiAOTKlSt6sxYvXiyurq4GrfeVV16RXr16VabKVs0c7bl3714BIKdPn1amHThwQABIenp6lbfB2hjaplorV64UtVotd+7cERGR9evXi42NjWRnZytl5s+fLy4uLnL79m0REZkyZYq0atVKJ2fo0KESHBxs7M2xOHO05++//y6urq5y6dIlE26J9ahqmxYVEREh7dq1M2i9AwcOlFGjRlWqztbOHG26atUqsbOzk4KCAmXa2rVrRaVSSX5+ftU3wgrwSJMR5efnIzExEX369FGm2djYoE+fPti5c6dJ152Tk4O6deuadB3mZq72DAwMhLu7OxYtWoT8/HzcvHkTixYtQosWLRAQEGC09ViDyrRpTk4OXFxcYGd376sqd+7ciTZt2sDLy0spExwcjNzcXBw+fFgpU3Qd2jKmfh+Ym7nac+3atejUqRM++eQTPPDAA2jWrBnefPNN3Lx504RbZxnGaNPKqo5/RwHztWnHjh1hY2ODxYsXo6CgADk5Ofjvf/+LPn36oFatWlXeDmvATpMRXbx4EQUFBTp//ADAy8sL2dnZJlvvjh07sGLFCrz00ksmW4clmKs9nZ2dERcXhyVLlsDBwQFOTk7YsGEDfv/99yr/EbY2FW3Tixcv4qOPPtJ5bWVnZ5e6vHZeWWVyc3Or1Qe9udrzxIkT2LZtGw4dOoSYmBjMnTsXP/30E1555RVjb5LFGaNNK2PlypXYu3cvRo0aVaUca2SuNm3YsCH++OMPvP3229BoNHBzc8PZs2excuXKKtXfmrDTdJ87dOgQBg8ejIiICPTr18/S1bkv3bx5E6NHj0b37t2xa9cubN++Ha1bt0ZISEi1+oCvqNzcXISEhKBly5Z4//33LV2d+15V2rOwsBAqlQpLly5F586dMXDgQMyePRs//PADX6NGeI1u2bIFo0aNwsKFC9GqVSvjVfA+VJU2zc7OxtixYxEaGoq9e/ciPj4earUaTz/9NKSafPlI9fo32sI8PDxga2uL8+fP60w/f/48vL29jb6+I0eOoHfv3njppZfw7rvvGj3f0szVnsuWLcPJkyexc+dO2NjYKNPq1KmDX375BcOGDTPauizN0Da9du0a+vfvD2dnZ8TExOgcWvf29ta5g1G7vHae9mdp63BxcYGDg4NRt8mSzNWePj4+eOCBB+Dq6qqUadGiBUQEZ8+eRdOmTY2+bZZijDatiPj4eAwaNAhz5szBCy+8UKW6Wytztem8efPg6uqKTz75RJm2ZMkS+Pn5Yffu3ejatWvVNsQK8EiTEanVanTs2BGxsbHKtMLCQsTGxiIoKMio6zp8+DB69eqF0NBQTJ8+3ajZ1sJc7Xnjxg3Y2NhApVIp07TPCwsLjbYea2BIm+bm5qJfv35Qq9VYu3Yt7O3tdTKCgoJw8OBB5Q5GANi0aRNcXFzQsmVLpUzRdWjLGPt9YGnmas/u3bsjMzMTeXl5Spm0tDTY2Nigfv36ptxEszNGmxoqLi4OISEhmDVrVrW7vKEoc7Wp9m9pUba2tsr6qgVLX4le3Sxfvlw0Go1ERUXJkSNH5KWXXhI3NzflzpisrCxJSkqShQsXCgDZunWrJCUl6dwVc+rUKUlKSpIPPvhAnJycJCkpSZKSkuTatWsiInLw4EGpV6+ePPfcc5KVlaU8Lly4YJFtNiVztGdKSopoNBoZN26cHDlyRA4dOiTPPfecuLq6SmZmpkW225TKatOcnBzp0qWLtGnTRo4dO6bz+rp7966IiNy9e1dat24t/fr1k+TkZNmwYYPUq1dPpk6dqqzjxIkT4ujoKJMnT5aUlBSZN2+e2NrayoYNGyy12SZjjva8du2a1K9fX55++mk5fPiwxMfHS9OmTWXMmDGW2myTqmqbioikp6dLUlKSvPzyy9KsWTPlfa+9I/HPP/8UR0dHmTp1qk5Gdb1D0RxtGhsbKyqVSj744ANJS0uTxMRECQ4OFn9/f7lx44alNt2o2GkygS+//FIaNGggarVaOnfuLLt27VLmRURECIASj8WLFytlQkNDSy2zZcuWMjP8/f3Nu6FmYur2FBH5448/pHv37uLq6ip16tSRRx99VHbu3GnGrTQvfW2qHbqhtEdGRoay/MmTJ2XAgAHi4OAgHh4eMmnSpBK3Jm/ZskXat28varVaGjVqpLNPqhtztGdKSor06dNHHBwcpH79+vLGG29Umw+i0lS1TXv06FFmGX1/F3r06GH+jTUTU7epiEh0dLQ8+OCDUrt2balXr548/vjjkpKSYuYtNR2VSDW5OouIiIjIhHhNExEREZEB2GkiIiIiMgA7TUREREQGYKeJiIiIyADsNBEREREZgJ0mIiIiIgOw00RERERkAHaaiIiIiAzAThMRERGRAdhpIiIiIjIAO01EREREBmCniYiIiMgA7DQRERERGYCdJiIiIiIDsNNEREREZAB2moiIiIgMwE4TERERkQHsLF0Bc7h16xby8/MtXQ0iIiIyIbVaDXt7e5PlV/tO061bt9CwYUNkZ2dbuipERERkQt7e3sjIyDBZx0klImKSZCuRm5sLV1dXnDlzBi5OjvcmFt7V87OgnPn/+ynllbOiHGuqS0XyjJZT+L/nqNpPqWD5SuYo1S3jufb3QtEtU96y0DdfSp9eXl7x6dCTU+HnUvr84vUvt766ixn8vPjP8nadoeXLyq9oXcvLNFZeVaffD21fmeeGtL+52r6q+0L7E3rml1ffita/qvtS3/SicnJy4OLiUsqcqqv2R5q0XFxcDOg0VcOfyu+25fzUlrPR81M7X2XgTxj4U8r5qa8+2p/aT8qq1sM6flao01TBTk65naD/NZkU+1l8evEmVsprc/63SZX+YNLWr6LrLz5d+xIycP1V/eNdlQ9iU3Vy7odtN0d9LbF+U22Lqtj04s/1Tdf3XN/y0PNc3/Tyli/euSm+/uKKT9dXvnj9TY0XghMREREZgJ0mIiIiIgOw00RERERkAHaaiIiIiAzAThMRERGRAdhpIiIiIjIAO01EREREBmCniYiIiMgA7DQRERERGYCdJiIiIiIDsNNEREREZAB2moiIiIgMwE4TERERkQHYaSIiIiIyADtNRERERAZgp4mIiIjIAOw0ERERERmAnSYiIiIiA7DTRERERGQAdpqIiIiIDMBOExEREZEB7CxdAXPJzc0FCu/ee6L3Z0E58//3U8orZ0U51lSXUvP0/JTC/z0v76eU/fN/P1BYxZ9myim+2aU9L77pYuCy0DdfSp9eXl7x6dCTU+Hn2u0qtiuhbxfrKV+8qQ19XvxnebvO0PJl5Ve0ruVlGiuvqtPvh7avzHND2t9cbV/VfaH9CT3zy6tvRetvqp/mUu07TSICJycn+Pn5WboqREREZELe3t5Qq9Umy6/2nSaVSoW8vDycOXMGLi4ulq4OVVBubi78/Py4/+5T3H/3N+6/+1tN3H9qtRr29vYmy6/2nSYtFxeXGvOiqY64/+5v3H/3N+6/+xv3n/HwQnAiIiIiA7DTRERERGSAat9p0mg0iIiIgEajsXRVqBK4/+5v3H/3N+6/+xv3n/GpRMTcd+wRERER3Xeq/ZEmIiIiImNgp4mIiIjIAOw0ERERERmAnSYiIiIiA1T7TtO8efMQEBAAe3t7dOnSBXv27LF0lWqUmTNn4qGHHoKzszM8PT0xZMgQpKam6pS5desWxo8fD3d3dzg5OeGpp57C+fPndcqcPn0aISEhcHR0hKenJyZPnoy7d+/qlImLi0OHDh2g0WjQpEkTREVFmXrzapyPP/4YKpUKEydOVKZx/1m3c+fO4bnnnoO7uzscHBzQpk0bJCQkKPNFBNOmTYOPjw8cHBzQp08fpKen62RcvnwZI0aMgIuLC9zc3DB69Gjk5eXplDlw4AAeeeQR2Nvbw8/PD5988olZtq86KygowHvvvYeGDRvCwcEBjRs3xkcffYSi929x/5mZVGPLly8XtVot33//vRw+fFjGjh0rbm5ucv78eUtXrcYIDg6WxYsXy6FDhyQ5OVkGDhwoDRo0kLy8PKVMWFiY+Pn5SWxsrCQkJEjXrl2lW7duyvy7d+9K69atpU+fPpKUlCTr168XDw8PmTp1qlLmxIkT4ujoKG+88YYcOXJEvvzyS7G1tZUNGzaYdXursz179khAQIC0bdtWJkyYoEzn/rNely9fFn9/fxk5cqTs3r1bTpw4IRs3bpRjx44pZT7++GNxdXWVn3/+Wfbv3y+PP/64NGzYUG7evKmU6d+/v7Rr10527dolf/31lzRp0kSGDx+uzM/JyREvLy8ZMWKEHDp0SKKjo8XBwUG+/fZbs25vdTN9+nRxd3eXdevWSUZGhqxatUqcnJwkMjJSKcP9Z17VutPUuXNnGT9+vPK8oKBAfH19ZebMmRasVc124cIFASDx8fEiInL16lWpVauWrFq1SimTkpIiAGTnzp0iIrJ+/XqxsbGR7Oxspcz8+fPFxcVFbt++LSIiU6ZMkVatWumsa+jQoRIcHGzqTaoRrl27Jk2bNpVNmzZJjx49lE4T9591Cw8Pl4cffljv/MLCQvH29pZPP/1UmXb16lXRaDQSHR0tIiJHjhwRALJ3716lzO+//y4qlUrOnTsnIiJff/211KlTR9mf2nUHBgYae5NqlJCQEHnxxRd1pj355JMyYsQIEeH+s4Rqe3ouPz8fiYmJ6NOnjzLNxsYGffr0wc6dOy1Ys5otJycHAFC3bl0AQGJiIu7cuaOzn5o3b44GDRoo+2nnzp1o06YNvLy8lDLBwcHIzc3F4cOHlTJFM7RluK+NY/z48QgJCSnRxtx/1m3t2rXo1KkTnnnmGXh6euLBBx/EwoULlfkZGRnIzs7WaXtXV1d06dJFZ/+5ubmhU6dOSpk+ffrAxsYGu3fvVsr83//9n863ywcHByM1NRVXrlwx9WZWW926dUNsbCzS0tIAAPv378e2bdswYMAAANx/llBtv7D34sWLKCgo0PlDDQBeXl44evSohWpVsxUWFmLixIno3r07WrduDQDIzs6GWq2Gm5ubTlkvLy9kZ2crZUrbj9p5ZZXJzc3FzZs34eDgYIpNqhGWL1+Offv2Ye/evSXmcf9ZtxMnTmD+/Pl444038Pbbb2Pv3r147bXXoFarERoaqrR/aW1fdN94enrqzLezs0PdunV1yjRs2LBEhnZenTp1TLJ91d1bb72F3NxcNG/eHLa2tigoKMD06dMxYsQIAOD+s4Bq22ki6zN+/HgcOnQI27Zts3RVyEBnzpzBhAkTsGnTJtjb21u6OlRBhYWF6NSpE2bMmAEAePDBB3Ho0CF88803CA0NtXDtqDwrV67E0qVLsWzZMrRq1QrJycmYOHEifH19uf8spNqenvPw8ICtrW2Ju3jOnz8Pb29vC9Wq5vr3v/+NdevWYcuWLahfv74y3dvbG/n5+bh69apO+aL7ydvbu9T9qJ1XVhkXFxcepaiCxMREXLhwAR06dICdnR3s7OwQHx+PL774AnZ2dvDy8uL+s2I+Pj5o2bKlzrQWLVrg9OnTAP5p/7L+Tnp7e+PChQs68+/evYvLly9XaB9TxU2ePBlvvfUWhg0bhjZt2uD555/H66+/jpkzZwLg/rOEattpUqvV6NixI2JjY5VphYWFiI2NRVBQkAVrVrOICP79738jJiYGf/75Z4lDwB07dkStWrV09lNqaipOnz6t7KegoCAcPHhQ542/adMmuLi4KB8IQUFBOhnaMtzXVdO7d28cPHgQycnJyqNTp04YMWKE8jv3n/Xq3r17iSE+0tLS4O/vDwBo2LAhvL29ddo+NzcXu3fv1tl/V69eRWJiolLmzz//RGFhIbp06aKU2bp1K+7cuaOU2bRpEwIDA3lqpwpu3LgBGxvdj2lbW1sUFhYC4P6zCEtfiW5Ky5cvF41GI1FRUXLkyBF56aWXxM3NTecuHjKtcePGiaurq8TFxUlWVpbyuHHjhlImLCxMGjRoIH/++ackJCRIUFCQBAUFKfO1t6z369dPkpOTZcOGDVKvXr1Sb1mfPHmypKSkyLx583jLuokUvXtOhPvPmu3Zs0fs7Oxk+vTpkp6eLkuXLhVHR0dZsmSJUubjjz8WNzc3+eWXX+TAgQMyePDgUm9Zf/DBB2X37t2ybds2adq0qc4t61evXhUvLy95/vnn5dChQ7J8+XJxdHTkLetVFBoaKg888IAy5MCaNWvEw8NDpkyZopTh/jOvat1pEhH58ssvpUGDBqJWq6Vz586ya9cuS1epRgFQ6mPx4sVKmZs3b8orr7widerUEUdHR3niiSckKytLJ+fkyZMyYMAAcXBwEA8PD5k0aZLcuXNHp8yWLVukffv2olarpVGjRjrrIOMp3mni/rNuv/76q7Ru3Vo0Go00b95cFixYoDO/sLBQ3nvvPfHy8hKNRiO9e/eW1NRUnTKXLl2S4cOHi5OTk7i4uMioUaPk2rVrOmX2798vDz/8sGg0GnnggQfk448/Nvm2VXe5ubkyYcIEadCggdjb20ujRo3knXfe0RkagPvPvFQiRYYWJSIiIqJSVdtrmoiIiIiMiZ0mIiIiIgOw00RERERkAHaaiIiIiAzAThMRERGRAdhpIiIiIjIAO01EpVCpVPj555+NkhUQEIC5c+caJcsaxMXFQaVSlfjqFHPLz89HkyZNsGPHDgDAyZMnoVKpkJycrHcZa6m7tYqKiirx5cvVWX5+PgICApCQkGDpqtB9gp0msmoqlarMx/vvv693WUM+RKvizJkzePHFF+Hr6wu1Wg1/f39MmDABly5dMsn6LKFnz56YOHGizrRu3bohKysLrq6ulqnU/3zzzTdo2LAhunXrBgDw8/NDVlYWWrdubdF6GduqVavQvHlz2Nvbo02bNli/fn25y/z99994+umnUadOHbi4uKBnz54lvk6lNEOHDkVaWpoxqm0V1qxZg379+sHd3b3UvwVqtRpvvvkmwsPDLVNBuu+w00RWLSsrS3nMnTsXLi4uOtPefPNNi9TrxIkT6NSpE9LT0xEdHY1jx47hm2++Ub7b8PLlyxapFwAUFBQo301lCmq1Gt7e3lCpVCZbR3lEBF999RVGjx6tTLO1tYW3tzfs7OwsVi9j27FjB4YPH47Ro0cjKSkJQ4YMwZAhQ3Do0KEylwsPD0dCQgLWrVuHpKQkjB8/3qD1OTg4wNPT0xhVN5j2y4NN4fr163j44Ycxa9YsvWVGjBiBbdu24fDhwyarB1UjFh6RnMhgixcvFldXV+V5QUGBfPDBB/LAAw+IWq2Wdu3aye+//67MR7GvbunRo4eI3Ps+rj59+oi7u7u4uLjI//3f/0liYqLOugBITEyM3rr0799f6tevr/MdeiIiWVlZ4ujoKGFhYco0f39/+fDDD2XYsGHi6Ogovr6+8tVXXynzCwsLJSIiQvz8/EStVouPj4+8+uqryvxbt27JpEmTxNfXVxwdHaVz586yZcuWEu3yyy+/SIsWLcTW1la+/fZb0Wg0cuXKFZ36vfbaa9KrVy8REbl48aIMGzZMfH19xcHBQVq3bi3Lli1TyoaGhpZow4yMDNmyZYsA0Mn+6aefpGXLlqJWq8Xf318+++wznfX6+/vL9OnTZdSoUeLk5CR+fn4632t1+/ZtGT9+vHh7e4tGo5EGDRrIjBkz9Lb/3r17xcbGRnJzc5VpGRkZAkCSkpKUab/99ps0bdpU7O3tpWfPnrJ48eISdV+8eLH4+fmJg4ODDBkyRD777DOd15mIyNq1a6VTp06i0WjE3d1dhgwZorduxvTss89KSEiIzrQuXbrIyy+/XOZyo0eP1vluMUMVf4+FhobK4MGDdcpMmDBBeS+JiKxatUpat24t9vb2UrduXendu7fk5eUp8xcuXCjNmzcXjUYjgYGBMm/ePJ28gIAA6dKli3z99ddy+fLlCtfZEKW9Norq1auXvPvuuyZZN1Uv7DTRfaP4H/TZs2eLi4uLREdHy9GjR2XKlClSq1YtSUtLE5F7nSMAsnnzZsnKypJLly6JiEhsbKz897//lZSUFDly5IiMHj1avLy8dD6Ay+o0Xbp0SVQqld4P9bFjx0qdOnWksLBQRO51GJydnWXmzJmSmpoqX3zxhdja2soff/whIvc+dFxcXGT9+vVy6tQp2b17t873g40ZM0a6desmW7dulWPHjsmnn34qGo1G2c7FixdLrVq1pFu3brJ9+3Y5evSo5OXliZeXl3z33XdKzt27d3WmnT17Vj799FNJSkqS48ePK/XavXu3iNz7Es+goCAZO3as8kXLd+/eLdFpSkhIEBsbG/nwww8lNTVVFi9eLA4ODjrfHefv7y9169aVefPmSXp6usycOVNsbGzk6NGjIiLy6aefip+fn2zdulVOnjwpf/31l04HrrjZs2dL8+bNdaYV/2A8ffq0aDQaeeONN+To0aOyZMkS8fLy0qn7rl27xMbGRmbNmiWpqakSGRkpbm5uOq+zdevWia2trUybNk2OHDkiycnJOvv+5Zdfltq1a5f5KKq8skU7RH5+fjJnzhyd5adNmyZt27bV2zYi9zp5tWrV0vknwhAV7TRlZmaKnZ2dzJ49WzIyMuTAgQMyb9485XvNlixZIj4+PrJ69Wo5ceKErF69WurWrStRUVFK3unTp2X69OlKx+qZZ56RdevWyd27d0vUb+vWreW2X9EvI9Yqr9MUHh6u0xEk0oedJrpvFP+D7uvrK9OnT9cp89BDD8krr7wiIuX/odQqKCgQZ2dn+fXXX5VpZXWadu3aVeb82bNnCwA5f/68iNzrMPTv31+nzNChQ2XAgAEiIvL5559Ls2bNJD8/v0TWqVOnxNbWVs6dO6czvXfv3jJ16lQREeXoSXJysk6ZCRMmyKOPPqo837hxY6lHn4oKCQmRSZMmKc+LfzmviJToNP3rX/+Svn376pSZPHmytGzZUnnu7+8vzz33nPK8sLBQPD09Zf78+SIi8uqrr8qjjz6qdDTLU3zbREru76lTp+rUQeTeh2PRug8fPlwGDhyoU2bo0KE6r7OgoCAZMWKE3rqcP39e0tPTy3wUVV5Z7etGRKRWrVolOo/z5s0TT09PvfU5fPiwODk5ycyZM+WBBx6QlStXKvMSEhIEgPz999+lLlvRTlNiYqIAkJMnT5aa17hx4xL1/+ijjyQoKKjU8rt375bx48eLh4eHeHt7y6RJk+TgwYPK/Bs3bpTbfkX/+dEq729BZGSkBAQElDqPqKjqc/KfapTc3FxkZmaie/fuOtO7d++O/fv3l7ns+fPn8e677yIuLg4XLlxAQUEBbty4UeFrK6QC33UdFBRU4rn2jrpnnnkGc+fORaNGjdC/f38MHDgQgwYNgp2dHQ4ePIiCggI0a9ZMZ/nbt2/D3d1dea5Wq9G2bVudMiNGjEDXrl2RmZkJX19fLF26FCEhIcrdUQUFBZgxYwZWrlyJc+fOIT8/H7dv34ajo2MFWgFISUnB4MGDdaZ1794dc+fORUFBAWxtbQFAp34qlQre3t64cOECAGDkyJHo27cvAgMD0b9/fzz22GPo16+f3nXevHkT9vb25darS5cuOtOK74eUlBQ88cQTJcps2LBBeZ6cnIyxY8fqXY+np2eFrgNq0qSJwWUr4/3338eAAQPw1ltvoV+/fujbty8uXbqEsLAwHDx4EM2bN4eHh4dR1tWuXTv07t0bbdq0QXBwMPr166dcgH79+nUcP34co0eP1mm/u3fv6r2JoHPnzujcuTNmz56NqVOnYvbs2di8ebNyAbeDg4NJ2s/BwQE3btwwei5VP+w0UY0TGhqKS5cuITIyEv7+/tBoNAgKCkJ+fr5Byzdp0gQqlarUD1zg3gdxnTp1UK9ePYPy/Pz8kJqais2bN2PTpk145ZVX8OmnnyI+Ph55eXmwtbVFYmKi0vnQcnJyUn53cHAocWH2Qw89hMaNG2P58uUYN24cYmJiEBUVpcz/9NNPERkZiblz56JNmzaoXbs2Jk6caHA7VFStWrV0nqtUKuWC9Q4dOiAjIwO///47Nm/ejGeffRZ9+vTBTz/9VGqWh4cHDh48aJJ6Fufg4FDm/LCwMCxZsqTMMnl5ecrvRfdbaZ577jl88803AABvb2+cP39eZ/758+fh7e2td/kDBw4gNDQUwL12Xbt2LYKDg3Hx4kVs2LABo0aNKnP9RdnY2JT45+DOnTvK77a2tti0aRN27NiBP/74A19++SXeeecd7N69W+l8L1y4sETntfhrWSs1NRX//e9/sWTJEuTk5GDs2LE6F/v/9ddfGDBgQJl1/vbbbzFixAiDtxEALl++bPD7lWo2dprovuTi4gJfX19s374dPXr0UKZv374dnTt3BnDv6Atw74hKUdu3b8fXX3+NgQMHArg3dMDFixcNXre7uzv69u2Lr7/+Gq+//rrOh2p2djaWLl2KF154QacTs2vXLp2MXbt2oUWLFspzBwcHDBo0CIMGDcL48ePRvHlzHDx4EA8++CAKCgpw4cIFPPLIIwbXUWvEiBFYunQp6tevDxsbG4SEhOi0w+DBg/Hcc88B+P/27i+kqTaOA/hvs3P0pJxMtK1sTSIHs5oOrAxZNzHqougPxi6CurBuwqBF0D+ZFRaKRYhBECVWGMOoQWUKqRFxSglnzNjcwswuKmhG14Z93wvx0NmmHnkDX99+Hxi4c87DnvN43H6cfZ9Hol+/flEsFqOioiL1GFEUk8Yvkd1uJ0VRNNsURSGbzTbth2MqsiyTx+Mhj8dDFRUVtH37dvr+/Tvl5OQkHet0Oun69esEYNpZfHa7nR49eqTZlvh7sNvt1NfXN+MxDoeDuru7py02Lly4MKdZnLMtgSHLsvrz5s2bqbu7W7Psw7Nnz5LumP0uPz+fXr58SadPnyaiybt+gUCAduzYQTk5OVRVVaW7r3l5eUkz9d6+faspgA0GA5WXl1N5eTn5fD6yWq0UCATo+PHjtGLFCvrw4cOMRUw8Hie/3093796l/v5+crvdVFdXR7t37066m1haWjrr+JlMJt3nN+Xdu3fkdDrn3I79heb560HGdEvMW1y9ehWyLMPv92NoaAgnT57UBMF//vwJSZJQW1uLr1+/4sePHwAAp9MJt9uNcDiM3t5euFwuSJKkCdzSLLPnYrEYcnNz4XK58OLFC3z69AkdHR1Yt24dCgsL1dA5MJnnkWVZDRtfu3YNaWlp6OzsVM/r5s2bGBwcxPDwMKqrqyFJEuLxOABg//79KCgoUMO0fX19uHTpEp48eZJyXH73/v17EBEcDgcqKys1+7xeLywWCxRFQTgcxqFDhyDLsibDcvjwYWzYsAEjIyP49u0bJiYmkjJN/f39miB4S0tLyiB4YqC5uLgYNTU1ACZzXffu3UMkEkE0GkVlZSXMZjMmJiZSnlc8HocgCJq8S2JuZXR0FKIo4sSJExgaGkJrayvMZrOm769fv4bRaERDQwNisRiampqSguDPnz+H0WhUg+ChUAh1dXUp+/WnKYqCRYsW4fLly4hEIqipqUk670QdHR0wGAw4cuQIBgcHEQwGcfbsWWRlZSEtLQ1+v3/atonXUmdnJwwGA27fvo1YLAafzwdZltVMU29vLy5evIg3b95gdHQUbW1tEEURT58+BTA5c06SJDQ2NiIajSIUCqG5uRlXrlxRX2P16tUoKipCfX09Pn/+/O8GLMHY2BgGBgbQ3t4OIoLf78fAwAC+fPmiOc5qteLOnTt/9LXZ/xMXTWzBSLXkwLlz55Cfnw9BEJKWHAAm37QtFguMRqP6Rh8MBlFaWoqMjAwUFhbi/v37SR/qsxVNAPDx40ccPHgQJpMJgiDAYrHg6NGjarEzxWq14vz589i3bx8WL14Ms9mMxsZGdX8gEMCmTZsgyzIyMzNRVlaGrq4udf/4+Dh8Ph8KCgogCAKWL1+OPXv2IBQKpRyXRBs3bgQRoaenR7N9bGwMu3btQlZWFpYtW4bq6mocOHBAUzRFo1GUlZVBkiRdSw4IgoBVq1ahoaEhaQxmKppu3LiBkpISZGZmQpZlbN26FcFgcNpzAian4586dUp9nirs+/jxY6xZswbp6elwuVxobm5O6vutW7ewcuVKSJKEnTt3plxy4MGDBygpKYEoisjNzcXevXtn7Nuf1NbWBpvNBlEUsXbtWrS3t8/apqenBy6XC7IsIzs7GxUVFQiHw6itrUVGRgYURUnZLtW15PP5YDKZsGTJEni9XlRVVal/S+FwGNu2bUNeXh7S09Nhs9nQ1NSkad/a2qqO3dKlS7FlyxY8fPhQ3R+JROY2IHMwNUki8TF13QHAq1evkJ2dnbR8CGOpGIA5pFkZY+w/IhQKkdvtpuHh4VlzQnPR0tJCx44d43+18pfweDxUXFxMZ86cme+usAWAVwRnjC1IDoeD6uvraWRkZL67whao8fFxWr9+PXm93vnuClsg+E4TY4z9hu80Mcamw0UTY4wxxpgO/PUcY4wxxpgOXDQxxhhjjOnARRNjjDHGmA5cNDHGGGOM6cBFE2OMMcaYDlw0McYYY4zpwEUTY4wxxpgOXDQxxhhjjOnARRNjjDHGmA7/ABICP7fEJDDIAAAAAElFTkSuQmCC", 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", 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", 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", 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4cCAAwNraGn379sWOHTuU2u3ZswdNmjQReq/atWsHZ2dn7N27FwCwa9cupffr2bNnlZYvKCjA8OHDQUTYvHmzWrkxpknW1tbQ19dHSkqK0vSUlBTY2dmpHcfV1RVpaWmlLnAAgPz8fNy7dw+urq4AAGNj40rn+fPPPyM6OhrR0dHCBTt2dnYq81bMKykoKAiffvopgoODlY4wuLi4QCKRICYmRuV6Y2JiUKdOHdSrV69KeZfn9OnTGDRoENavX4+xY8cqzStr217fLsV3Snx8PI4fP67Uy6SKu7s7CgsL8fDhQ1G2oSJvTNE0aNAgpKamYtu2bbh06ZJwiCA/P7/CZQ0NDZWeSyQSldMUh/o6dOiABw8eYNmyZcjJycHw4cPx4YcfAnh11r/ig/L6lXolYyp+rBUxFcR4U2rC9u3bUVhYCHt7exgYGMDAwACbN2/Gb7/9hrS0tErHGz9+PDZt2oT9+/eXOjRXkrm5OQYNGoQVK1bg6tWr6NGjR6lDaOowNTWt9DJAxe+Nsl7HsowePRrOzs4qt8HV1bXcL0JFG+DV65GamgpjY2Ph9Thy5Ah27typlMv27dtx8+ZNoY2BgQFu3bolFFeDBw9Wer+WPNxW3pebnZ1dqUKxsLAQqampNfJ+ZG8uqVSKjh074uTJk8K04uJi4coxdX3wwQcwNDTE2rVrS83bsmULsrKyhP8ktmnTBmfPnkVBQUGZOb1+GkGDBg3g4uICFxcXODs7AwC6du2K69evK312FJ+tFi1aCNP27NkDHx8f7NmzR+lKZQCoW7cu+vbtix9//BE5OTlK8xT/yRwxYgQkEglat26N4uJinD59usy8Aah1CkRoaCi8vLywatUqfPbZZ6Xmd+3aVek1UWxbyddE8Z0SGxuLEydOoG7duhWuNzo6Gnp6erCxsamwrRjeiKLp+fPnuHPnDr7++mv07t1bOKZbUmXeHOqQy+UYMWIEtm3bhr179+K3335DamoqbGxshA+Ki4tLpWKK8abUhMLCQvzyyy9Yu3at0g/s1atXYW9vjz179lQ65scff4zr16+jVatWSl8W5ZFIJGjWrFmZ5wRVRvPmzREWFqbUs3P+/HmYm5vDwcGh2vHLoqenB39/f2zevLnU/5xGjhyJEydOKJ23BLz6QVi/fj1atGiBtm3b4vnz5/jjjz8QFBSk9HpERUXhxYsXQs/n9evXER4ejtDQUKV2oaGhCAsLw+3bt2Fubq70flX8z7SiL7euXbvi5cuXiIiIEKadOnUKxcXFcHd318CeY+z/zZo1C9u2bcPOnTsRExODKVOmICsrq9Q5NtHR0YiLiwPw6vMQHR0tXI7v5OSE1atXY8OGDViwYAFu376Ne/fuYd26dZg7dy5mz54tvJenTZuG9PR0jBw5EuHh4YiNjcWvv/6KO3fuAHg1ttC1a9dw584dPHv2rMziql+/fmjRogXGjBmDq1ev4tixY/j6668xdepUyGQyAK/ObRw7dizWrl0Ld3d3JCcnIzk5Wek/pz/88APy8vLQv39/nDlzBo8ePcLRo0fRt29fNGjQACtWrBDy8vb2xvjx4/H777/jwYMHCA0NRXBwMADA2dkZEokEhw8fxtOnT8scMiQkJAReXl6YMWMGPvjgAyGnkkMb+Pr64ujRo1i7di1u376NxYsXIzw8HNOmTQPw6jvlww8/RHh4OHbt2oWioiIhjqJzIywsDBs2bMDVq1dx//597Nq1CzNnzsTo0aNRp06dyrxFqq5GDgJqWVFREdWtW5dGjx5NsbGxdPLkSercubPSuTUFBQVkbGxMy5cvp+TkZOEqAVXHohXnoJRU8jLItWvX0u7duykmJobu3LlDEyZMIDs7O6XzokpSdT7VixcvlC5NVRwnnj9/vtLl+8+fPxeWOX/+PBkYGNCaNWsoJiaG/Pz8amTIgYMHD5JUKlV5ZcXcuXOpU6dOStNQwTlNCi9evKDMzEzh+etXzw0ePJj27dtHN2/epNjYWPr555/J1NRUOCdIlbLOaXr99Xz8+DGZmJjQ1KlTKSYmhn7//XeytrZW2i8VvQ8q2t7y4vTo0YOMjIyUcs3JySF3d3dydHSk4OBgio+Pp8uXL5cacmD9+vVUv359lefUDR8+nD788EMiIvL19SV3d3eVOXXp0oXmzJmjcl5+fj4NHjyYHBwcKDo6Wun9WPKqIE9PT2rfvj1dunSJzp07R02bNuUhB1iNUQwvIpVKqUuXLkrDAxCRyqEA8L/hUEr6448/qEePHmRqakpGRkbUsWNHpaulFa5evUr9+vUTzrPs0aOHcI7lkydPqG/fvmRmZlbukANERA8fPqQBAwaQsbExWVtb0+zZs0tdtasq79eHA3j48CF5e3uTra0tGRoakqOjI02fPp2ePXum1C4nJ4dmzpxJ9evXJ6lUSi4uLkrbt3TpUrKzsyOJRFLmkAOvX5mseCiuQlcIDg4mV1dXkkql1LJlS/rvf/8rzFM1xIHiodhfERER5O7uThYWFmRkZETNmzenlStX1tj5TERv0JADx48fp+bNm5NMJqM2bdpQaGhoqR+zbdu2kaOjI+np6ZUacqCkin4st27dSu3atSNTU1OSy+XUu3fvMi8XJVKvaBLjTamuyhZN7733Hg0cOFDlvEuXLhEAunr1qjBN3aLpdSWLpqdPn9KMGTOoVatWZGZmRubm5tS6dWtas2ZNmcUpkfpFE5F6Qw5oqmi6cOGC0rAICllZWbRgwQJycXEhQ0NDsrKyog8++ECpMG7dujX961//UrkuxQUEKSkpVLduXVq9erXKdqtWrSIbGxuVJ4iq8+VG9OrS51GjRpGZmRnJ5XLy8fGp1AnmjDGmayRElbwmnNV648aNQ8OGDWvtrVQYY4yxqngjzmlijDHGGKsuLpoYY4wxxtRQevAb9sYbOnSoMLIzY4wxxl7hc5oYY4wxxtTAh+cYY4wxxtSg1cNz/v7+OHDgAG7fvg1jY2N069YNq1atgpubGwAgNTUVfn5++Ouvv5CQkIB69eph6NChWLZsmdo3DiwuLkZiYiLMzc2VbonBGGOMsdqDiJCRkQF7e3ulW5+JSatF0+nTpzF16lR07twZhYWF+Oqrr9CvXz/cunULpqamSExMRGJiItasWYMWLVogPj4ekydPRmJiIvbv36/WOhITE+Ho6KjhLWGMMcaYLnj06JHG7tygU+c0PX36FDY2Njh9+jTeeecdlW327duH0aNHIysrS+VNXF+XlpYGS0tLPNq+HXITE7FTfjM1b67tDGqf/93Yl4knKY0/72J67baWTATtXLO1nUKtkp6RAUdXV7x8+VLto1GVpVNXzynunWNlZVVuG7lcXmbBlJeXh7y8POF5RkYGAEBuYsJFk1jMzbWdQe1TwZ28WeVlFvPnXUwi3NKRvUYu16mf4FpDk6fi6MyJ4MXFxfj888/RvXt3tGrVSmWbZ8+eYdmyZSpvVqvg7+8PCwsL4cGH5hhjjDEmBp0pmqZOnYobN24gKChI5fz09HR4eXmhRYsW5d7eY/78+UhLSxMejx490lDGjDHGGHuT6ETf4LRp03D48GGcOXNG5clbGRkZ8PT0hLm5OQ4ePAhDQ8MyY8lkMshkMk2myxhjjLE3kFZ7mlauXAkbGxv8+OOPyMrKwsyZM3Hnzh2lNhs3bkSDBg1w+fJlnDx5Erm5uVrKljHGGGNvMq32NG3ZsgWZmZnYsWMHHB0d4e/vj969eyM6OhrW1tZIT0/H+vXrYWpqikmTJmHNmjVISUlBbm4u6tWrB319fW2m/+YqLNR2BrUP/2dAdC9f8ongYnr8WNsZ1D4d7F5qO4Xa5X8XfmmSVosmxflGPj4+StPXrl0Lf39/REZGIj4+HgCwZs0aAECzZs0AAA8ePEDDhg1rLlnGGGOMvdG0eniOiJQesbGxAIBPPvkEANCzZ09hXkhICADgxYsXIKIyC6a8vDykp6crPRhjjDHGqktnrp5TZ8gBdfCQA4wxxhjTBJ0pmioackBdPOQAY4wxxjThHzHkQGXwkAOMMcYY0wStFk0rV67Ehg0b8OzZM1haWmLmzJlYtWoV3NzchDa5ubmYPXs2fv31VwDAmDFj8PPPP8O2svfqysgAiorETP/NpcY9/1jl5JuVfesgVjV2dtrOoHZ59kzbGdRC/F0qrhrYn1o9PFdyyIF9+/YhMzMTvXv3xrMSn85Jkybht99+w8SJEwEA9+/fR//+/ZGamqqttBljjDH2BpIQEWlt5WXcVG/evHnw9/dHWloarKysUFxcXKrN119/jWXLllW4jvT0dFhYWCBt61a+Ya9YunbVdga1Tr5DY22nUOtkZmo7g9rlxg1tZ1D7vNPsibZTqFXSMzJg4eKCtLQ0yDV0E3SdHnIgIiICxcXFwjADioeTkxOsrFQfzuAhBxhjjDGmCTpz9ZyqIQeSk5MhlUphaWmp1NbW1hbJyckq4/CQA4wxxhjTBJ0pmnjIAcYYY4zpMq0WTWfOnMGgQYNgamqKLVu2YP78+UpDDshkMuTn58POzg4mJibw9PREbGwsUlJSYFfGpTEymQxyuVzpwRhjjDFWXVq93jEzMxNJSUkwMjJCdna20jACRIRvvvkGEokEM2fOxNChQ7Fu3Tp4eHggKSkJXflkZK1JNOKTlsVmf/SQtlOodWJtB2s7hVqlxEgwTCwPH2o7g9qlBq7+0GpP0+HDhxEXF4cDBw4AeHVfueTkZOTk5CA2Nhbh4eH46KOP8OOPPyIxMRGffvopnj59iiZNmuCtt97SZuqMMcYYe8Notadp8+bNAF7dmBcAxo8fDwAICAhAx44dAQB+fn7YtGkTPvjgA+Tl5cHAwECYp0peXh7y8vKE53z1HGOMMcbEoDNDDgDAwYMHQUQYN24cmjVrBicnJyxevBjLly9HcnIyFi1ahNzcXLx8+bLMmHz1HGOMMcY0QWeunnudoaEhDhw4gLt378LKygomJiYICQnBgAEDoKdXdtp89RxjjDHGNEGnb3zTsWNHREdHIy0tDfn5+ahXrx7c3d3RqVOnMpfhG/YyxhhjTBN0YsgBe3t7AMClS5eU5mdmZmLatGlo2bIlnJyc4OLigitXrmDIkCHaSJcxxhhjbzCt9jQ9e/YMtra2mDNnDmbPno2UlBRER0fDysoKTk5OGDp0KGJiYvDtt98iMzMTX331FYgIubm5lV+ZpSXA954Thb6+tjOoheLitJ1BrdP0bW1nULuUcyopq6pz57SdQe1SldqgkrTa02RlZYXt27dj9uzZAF5dNde+fXssWrQIAHDz5k1kZmZi3LhxWLFiBaZMmYJ27drh8uXL2kybMcYYY28grRZNPXv2VHn1XGBgIABg0KBBcHV1xYMHD/Dw4UO8++67iIuLQ79+/cqMyTfsZYwxxpgm6OzVcwDw/fffo0WLFnBwcIBUKoWnpyc2bdqEd955p8xleMgBxhhjjGmCzhdNFy9exKFDhxAREYG1a9di6tSpOHHiRJnL8JADjDHGGNMEnR1yICcnB1999RUOHjwILy8vAECbNm0QHR2NNWvWoE+fPiqX4yEHGGOMMaYJOjvkQEFBAQoKCvDee+9BIpEIj+3bt+P+/fvaSpkxxhhjbyidHnKga9euSE1NxcqVK+Hg4ICffvoJO3bswJgxYyq/ssREwNhY/I14A9k256JVdFu2aDuDWsdq2jRtp1CrPH4s1XYKtc/QodrOoHbJyAAWLNDoKrRaNCmGHFAICAhAQEAAvL29ERgYiAMHDmD+/PmYPn06UlNTYWBgABcXF3z99ddazJoxxhhjbyKtFk2KIQcAQCKR4ODBgxhaovK2s7NDQEAAACAlJQUODg5YsmQJJBJJmTHz8vKQl5cnPOchBxhjjDEmBp2+eq6knTt3wtzcHMOGDSu3HQ85wBhjjDFN+McUTTt27MAnn3wCIyOjctvxkAOMMcYY0wSdHXKgpLNnz+LOnTvYu3dvhW15yAHGGGOMaQRp0enTp+m9996j+vXrEwCaN29eqTa3bt0iBwcH0tPTIxMTE+rUqRPFx8ervY60tDQCQGlpaUrTt27dSpMnT6bw8HCl6ZmZmTR79myaPXs2ZWZmKs0LDw+nyZMn09atW0uth+NxPI7H8Tgex+N42osXGhqq8vdeTFo9PFdyyAEAwpADCQkJAIB79+6he/fuSElJwbx583Dt2jUsXLiwwkN0jDHGGGOi01g5poaQkBACUOrh7e1NREQjRowgd3d3MjY2ppcvX1ZpHYqepo0bNwrTtm7dKlS4Jf+dmZlJixYtoszMTKV/E72qchUVbsl/czyOx/E4HsfjeBxP+/E2btyo8Z4mCdH/rvnXsteHHCguLoaFhQXmzp2Lc+fOISoqCo0aNcL8+fOVhiV4naohBxwdHREaGoq7d+8CADp06ICOHTsKbbZt2wY3NzecPHkSc+fOhampKQAgKysLq1evRu/evXHnzh1MnDhRWCYiIgKRkZEcj+NxPI7H8Tgex9OBeOnp6bCwsEBaWhrkcjk0oiqVVnZ2NmVlZQnPHz58SOvXr6djx45VuXoDQAcPHhSeJyUlEQAyMTGhdevWUVRUFPn7+5NEIqHQ0NAy4/j5+ansvUpLS6PJkyfT5MmTSy2TmZlJ9vb2dPr06VLzTp8+Tfb29qWOrxIRx+N4HI/jcTyOx/F0JF5Z5zCLqUpFU9++fWnz5s1ERPTixQuytbUlBwcHMjIyoh9//LFqibxWNP39998EgEaNGqXUbtCgQTRy5Mgy4+Tm5lJaWprwePTokXB4Ljw8vFTXXsluwJLdfET/3w34elch0f93CXI8jsfxOB7H43gcT/vxEhMTdbNoqlu3Lt24cYOIiLZt20Zt2rShoqIiCg4OpmbNmqkdp7yr5/Ly8kgikZTqMWrYsCF169ZN7XUoKs+SvVO68OJyPI7H8Tgex+N4HE+8eF9++aVuFk3GxsbCZf8fffQRLV68mIiIEhISyNjYWO04R44coQULFtCBAwdUDjlQr149sre3p6SkJOHh5eVVqvepPGV112m7G5HjcTyOx/E4HsfjeOLFq4mepioNOeDi4oLff/8djx49wrFjx9CvXz8AwJMnTyp18lWPHj3w4YcfolGjRgBKDznQsmVLJCUl4T//+Q8yMzOxf/9+HD16FP/6178qnXNWVpbSv0+ePIk9e/Zg9+7dSu0iIiLQoUMHdOjQAREREUrzdu/ejT179uDkyZMcj+NxPI7H8Tgex9OhePv27YPGVaXS2rdvHxkaGpKenh717dtXmL5y5Ury9PRUO05FQw54e3uTsbEx6evrk0Qiobp169Ivv/xSbsyyzmn68ssvKTNTdy6N5Hgcj+NxPI7H8TieePFqYnDLKo/TlJSURJGRkVRUVCRMu3TpEsXExFQtkddOBCci2rNnD/3xxx907do1OnjwIDVv3pw6d+5MhYWFZcYp6+q5xMREnRq5lONxPI7H8Tgex+N44sWriavnqnzvOTs7O9jZ2SlN69KlS1XDqTRy5Ejh361bt0abNm3QpEkThIaGonfv3iqXmT9/PmbNmiU8V4zTxBhjjDFWLepWV++//77aj6qAip4mVaytrWnLli1qx1VUnnx4juNxPI7H8Tgex6u98Wri8JzaI4L7+PioXYgFBASo1e7MmTP49ttvERERgaSkJMybNw/+/v4q206ePBk//fQTJBIJfv/9dwwePFitdShGCE1MTET9+vUB6MbIpRyP43E8jsfxOB7HEy9edHQ0fH19NToiuFZvo3LgwAEcOXIELVq0wOzZs+Hj44MZM2bAysoKVlZWWLJkCT744ANcvXoVq1evxqNHj2BpaYlHjx5BJpOptQ5F0XTjRhrMzTU0rPobxin5srZTqH0MqnyknJXF2lrbGdQu/B4V340b2s6gVknPyoLFsGEaLZqq/CkoLCxEaGgo7t27h48//hjm5uZITEyEXC6HmZmZWjGsrKywfft24XlAQAACAgLg7e2NzZs349q1awgICMDz589hb28PmUyG6dOnq10wMcYYY4yJpUpFU3x8PDw9PZGQkIC8vDz07dsX5ubmWLVqFfLy8rBlyxa14vTs2ROKjq7Xb9gLAH/++Sf69OmDIUOGwNfXFw0bNoS5uXm5MVXdsJcxxhhjrLqqNLilr68vOnXqhBcvXsDY2FiY/v777+PkyZOiJbdq1SoYGBhgxowZai/j7+8PCwsL4cFXzjHGGGNMDFXqaTp79iwuXLgAqVSqNL1hw4b4+++/RUksIiICGzduRGRkJCQSidrL8ZADjDHGGNOEKvU0FRcXo6ioqNT0x48fV3j4TF1nz57FkydP4OTkBAMDAxgYGCA+Ph6zZ89Gw4YNy1xOJpNBLpcrPRhjjDHGqqtKRVO/fv2wYcMG4blEIkFmZib8/PwwcOBAteOcOXMGgwYNgr29PQDg0qVLwrwxY8Zg8uTJcHR0hKGhIUxMTCCTyfDJJ5/g2LFjVUmbMcYYY6zKqjTkwOPHj9G/f38QEWJjY9GpUyfExsbC2toaZ86cgY2NjVpxyhtywMnJCbt374aNjQ0aN26MnJwcvPXWWygoKMCjR49Qr149tdahGHIgNpaHHBCLrWGqtlOofYyMtJ1BrZMNE22nUKuYGBVrO4Xa5+VLbWdQq6Snp8OiUSPdHKepsLAQQUFBuHbtGjIzM9GhQwd88sknSieGVyQ0NBS9evUqNd3b2xuBgYGlpjs7OyMhIQEnTpwo8zYqr+OiSXxcNGkAF02i46JJXFw0aQAXTaKqiaKpyuM0GRgYYPTo0dVaeUVDDpSUn5+P6dOnY/ny5Wjbtm2ZMXnIAcYYY4xpQpWLptjYWISEhODJkycoLlb+H8iiRYuqnZjC4cOHMXLkSGRnZ6N+/fo4fvw4rMsZ6dff3x9LliwRbf2MMcYYY0AVD89t27YNU6ZMgbW1Nezs7JSGBJBIJMK9YyqVSBk9TVlZWUhKSsKzZ8+wbds2nDp1CpcuXSrzvClVPU2Ojo58eE5EfHhOA/jwnOj48Jy4+PCcBvDhOVHVxOG5Kl09t3z5cqxYsQLJycmIjo5GVFSU8KhMwVTe1XMFBQX48ssv8dZbb6Ft27YYNmwYCgoKAEDp1iuv4yEHGGOMMaYJVTo89+LFC3z00UfVXnlWVhbatm2L8ePHY9iwYUrzsrOzERkZiYULF6Jt27Z48eIFfH19kZiYqNSTpC4DA8DQsNopM4B7RTQhN1fbGdQ6Jvw2FRe/RcWn5n1amZqKNd8bWqWepo8++gh//fVXtVfeo0cPfPjhh2jUqBEAICUlBdHR0UhISICBgQE6d+4MJycnGBkZwdDQELa2tsjPz8fbb79d7XUzxhhjjFVGlXqaXFxcsHDhQly8eBGtW7eG4WtdOOreKy48PFxpyIGAgAAEBATA29sbW7Zswe3bt7Fz5048e/YMdevWFUYC79KlS1XSZowxxhirsiqdCK7oGVIZUCLB/fv3K59IBUMO5Obmonv37mjWrBl27dpVZpyyTgR/8EBzJ4a9aayMsrWdQu3Dh+fEx4eRma4zqPIF7EyF9PR0WNSrp3vjND148EDsPMpVUFCA4cOHg4iwefPmctvykAOMMcYY04QqndNUkxQFU3x8PI4fP15h9Th//nykpaUJj0ePHtVQpowxxhirzarU01RUVITAwECcPHlS5eCWp06dUivOmTNn8O233yIiIgLAqyEHSh6eCw4OxrRp05CamoqioiI8evQIdevWLTemTCaDTCar3AYxxhhjjFWgSkWTr68vAgMD4eXlhVatWikNblkZz549g62tLebMmYPZs2cLV89ZWVmhfv36+Oabb5CXl4cFCxZg6dKlePbsGZKTk2FlZQWpVFqpdRkZ8SkOouHj8OKztNR2Bowx9s9WA79NVToR3NraGr/88gsGDhxYrZWXd8PexYsXl3nCeUhICHr27KnWOhQ37E1K4hPBxWJikK/tFGofLkQZY6xa0tPTYVGnju6dCC6VSuHi4lLtlVd0w17FvIcPH6JRo0aIiopCu3btyo3JN+xljDHGmCZU6UTw2bNnY+PGjahCJ5XG+fv7w8LCQng4OjpqOyXGGGOM1QJV6mk6d+4cQkJC8Oeff6Jly5alBrc8cOCAKMlVxfz58zFr1izhuWKcJsYYY4yx6qhS0WRpaYn3339f7FxEwVfPMcYYY0wTqlQ0BQQEiLLyioYcICL4+fkJA1pOmjQJ//73v9G0aVNR1s8YY4wxpi6tXrJT3pADTk5OWLx4MdavX4/PP/8cy5cvR1FREXr27Inz588L96FTFw85IKJCbSdQ+xTr/jiz7A1XyJ970UkNiituxHRKlYYcAID9+/cjODgYCQkJyM9XvgQ9MjJSrRjlDTkQEBAAS0tLlVe/ffDBB9i/f79a61AMOfDiBQ85IBa9Qh5yQGzFBpUbd4yxmsZFk/i4aBJXTQw5UKX/3n733Xfw8fGBra0toqKi0KVLF9StWxf379/HgAED1I6jGHJAUbcdPHgQRITAwEA8ePAA6enpiIqKEtoQEd555x00aNCgzJh5eXlIT09XejDGGGOMVVeViqYff/wRW7duxffffw+pVIq5c+fi+PHjmDFjBtLS0kRJLDk5GQBga2urNN3W1laYpwoPOcAYY4wxTahS0ZSQkIBu3boBAIyNjZGRkQEAGDNmDPbs2SNedlXAN+xljDHGmCZUqWiys7NDamoqAMDJyQkXL14EADx48EC0AS/t7OwAACkpKUrTU1JShHmqyGQyyOVypQdjjDHGWHVV6eq5d999F4cOHUL79u3h4+ODmTNnYv/+/QgPD8ewYcNESaxRo0aws7PDkSNHEBgYiIMHDyIlJQX5+fno169fpeMVFvKJjGLhU5bZP4Ee+CRbMRUW8hWeYpPyLSf/cap09VxxcTGKi4th8L+bjAYFBeHChQto2rQpJk2aBKlUvZ/VzMxMxMXFAQDat2+PdevWoVevXsKQA6tWrcLChQthZ2eHJUuWYPfu3QgPD0dRURFiYmLKPSFcQXH13NOnfPWcWKTgq+fExlfPiY+LJnFl53LRJDYTI36Piqkmrp6r8pADYihvyIHAwEBkZ2fDzMwMFhYWyMnJwdtvv40ff/wRo0aNwoABA7B8+fIK18FFk/i4aBIfF03i46JJXFw0iY+LJnHVRNFU5c7Bly9f4vLly3jy5AmKi5Vf+LFjx6oVQzHkQFmKiopARNi/fz969+4tTDc2Nsa5c+dULpOXl4e8vDzhOQ85wBhjjDExVKlo+s9//oNPPvkEmZmZkMvlkEgkwjyJRKJ20VQRc3NzdO3aFcuWLUPz5s1ha2uLPXv2ICwsDC4uLiqX8ff3x5IlS0RZP2OMMcaYQpUOz7m6umLgwIFYuXIlTExMNJGX4N69exg/fjzOnDkDfX19dOjQAa6uroiIiEBMTEyp9qp6mhwdHfnwnIj48Jz4+PCc+PjwnLj48Jz4+PCcuHT28Nzff/+NGTNmaLxgKioqQmBgIBISEiCTyWBra4tBgwbhxo0baNy4scplZDIZZDKZRvNijDHG2JunSkVT//79ER4eXmbhIpZVq1Zh8+bN2LlzJ1q2bInw8HCMGzcOxcXF2LBhg0bXzcrBYzeIjv8Pz3SdAfeGii83V9sZ1C41sD/VLpoOHTok/NvLywtffPEFbt26hdatW8PQ0FCp7eDBg0VJ7sKFC+jYsSP09fVBRLCwsICBgQEMDAzg4+MjyjoYY4wxxtShdtE0dOjQUtOWLl1aappEIkFRUVG1klLo1q0b1q9fj88++wwpKSmQy+XIz8/Ht99+W6pQU+Cr5xhjjDGmCWofFVAMaFnRQ6yCCQDmzZuHCRMm4PHjxyguLsbz58+xcOFCTJw4scxl+Ia9jDHGGNOESp1KcerUKbRo0UJl701aWhpatmyJs2fPipZccHAwdu3ahd27dyMyMhI7d+7EmjVrsHPnzjKX4Rv2MsYYY0wTKnUi+IYNGzBx4kSVl/JZWFhg0qRJWLduHXr06CFKcl988QXmzZuHkSNHAgBat26N+Ph4+Pv7w9vbW+UyfPUcY4wxxjShUj1NV69ehaenZ5nz+/Xrh4iIiGonpZCdnY1FixZBIpEIj4ULF+LOnTuYOnWqaOthjDHGGKtIpXqaUlJSyjwBGwAMDAzw9OnTaielMGjQIPz111/49ddf4ebmhuvXr2PWrFlIS0vDRx99VKlYUoNiSA14IDFR5PKQA6LLzNR2BrWPtbW2M6hVpIU8qK3oeMgBcenSkAMA0KBBA9y4caPMW5hcu3YN9evXFyUxAPj++++xcOFCLFiwAE+ePIG9vT1cXV3x/PlzeHh4iLYexhhjjLGKVOrw3MCBA7Fw4ULkqqjmcnJy4Ofnh/fee0+05MzNzbFhwwbEx8cjJycHMTExuH//PiZMmKB0v7uS8vLykJ6ervRgjDHGGKuuSt17LiUlBR06dIC+vj6mTZsGNzc3AMDt27exadMmFBUVITIyEra2thpJNjg4GB9//DESEhJgb2+vss3ixYtV3rA37cULvvecWPhQkvi4m158fHhOXHwnAPHxd6mo0tPTYdGokUbvPVfpG/bGx8djypQpOHbsGBSLSiQS9O/fH5s2bUKjRo00kijw6vYtUqkU//nPf8psU9YNe7loEhF/0MXHRZP4uGgSFxdN4uPvUlHVRNFU6XvPOTs748iRI3jx4gXi4uJARGjatCnq1KmjifwE8fHxOHHiBA4cOFBuOx5ygDHGGGOaUOX7hNapUwedO3dGly5dNFow/f333xg9ejSaNWuG4uJiLFiwAOHh4RpbH2OMMcaYKpXuaapJL168QPfu3dGzZ09YWlpiyJAhGDZsWNWKtGvXADMz8ZN8E/FhD/G9fKntDGqdhFwbbadQqzg56PTPxT/Tw4fazqB2qYHDnVXuaaoJq1atgqOjIz7++GMkJydj1qxZ6NevH5o0aaLt1BhjjDH2htHpounQoUPo1KkTtm3bhnr16mHEiBHYtm1bucvwkAOMMcYY0wSdLpru37+PzZs3o2nTpjh27BimTJmCGTNmlHvDXn9/f1hYWAgPR0fHGsyYMcYYY7VVpYccqElSqRSdOnXChQsXhGkzZszAlStXEBYWpnKZMoccOH0acj6nSRx8TpP4+Jwm0SVYttF2CrWKkwPfhkp00dHazqBWSc/MhIWHh24NOVCT6tevj9zc3FKjfxsYlJ02DznAGGOMMU3Q6aKpe/fuOH/+PFq2bIkTJ04AABYtWoToKlTnT+zbIcecB7cUg238ZW2nUPvExmo7g1pH1od7msSU+lKnz+b4R7Liox//ODr9KZg5cyYeP36M58+fIzMzE6dOncKuXbvg6+ur7dQYY4wx9obR6Z6mzp07Y8SIEQgKCkLTpk1haGiI9u3bo0ePHtpOjTHGGGNvGJ3uaQKAMWPGYO/evbh69Sr+85//QF9fHz169EBGRobK9jzkAGOMMcY0Qad7mgBgwIABwr/btGkDd3d3ODs7Izg4GBMmTCjV3t/fH0uWLKnJFBljjDH2BtD5nqbXWVpawtXVFXFxcSrnz58/H2lpacLj0aNHNZwhY4wxxmqjf1TR9M0330AikeD69euoX7++yjYymQxyuVzpwRhjjDFWXTp/eG7OnDkYNGgQXr58iY0bN8LMzAxFRUUYNWpUpeLYjPWEvJzxnVgl8IBsojsSxOfeie1tY21nULtcvKjtDGqffm/ZaTuF2qUGzmHW+Sri8ePHGDlyJFJSUlC3bl0YGxtj4MCBqFevnrZTY4wxxtgbROcPzwUFBaFfv37w9fXF06dP0aJFC1haWpbZnq+eY4wxxpgm6HxPU1BQECIjI3HlyhW12vPVc4wxxhjTBJ3uaXr06BF8fX2xa9cuGBkZqbUMXz3HGGOMMU3Q6Z6miIgIPHnyBB06dBCmFRUV4cyZM/jhhx+Ql5cHfX19pWX4hr2MMcYY0wSd7mnq3bs3vv76azRu3FgohkxNTdGzZ09ER0eXKpgYY4wxxjRFp3uazM3N0aVLF3Tt2hVNmzYFEaFv3744ffo0JBJJpWI9CAuDuYbyfNM0wURtp1D7eA3Sdga1UGdtJ1DLtNZ2ArXOqFHvazuFWqWgQPPr0OmiCQAGDVL+MWnUqBFSUlJw8eJFtGzZUktZMcYYY+xNo9OH515XVFSEyZMng4jQtWtXlW14yAHGGGOMacI/omi6fv06zMzMIJPJMHnyZBw8eBAtWrRQ2dbf3x8WFhbCw9HRsYazZYwxxlht9I8omtzc3BAdHY1Lly5hypQp8Pb2xq1bt1S25SEHGGOMMaYJOn9OEwBIpVK4uLgAADp27IgrV65g48aN+Omnn0q15SEHGGOMMaYJOt/T5O/vj86dO8Pc3Bw2NjYYOnQoMjMzkZeXp+3UGGOMMfYG0fmepm3btmHEiBFYsWIF0tPT8eWXX+L+/ftYsGBBpeI0Cg6G3MREQ1m+Yd47rO0MGKtQ+/aLtJ0CY+UqLNR2BrVLTexPnS+aevXqhT179mDdunWwsLBAs2bNcP/+fVhYWGg7NcYYY4y9QXS+aNq+fbvS87i4ODRt2hRWVlYq2+fl5SkduuMhBxhjjDEmBp0/p6mk4uJifP755+jevTtatWqlsg0POcAYY4wxTfhHFU1Tp07FjRs3EBQUVGYbHnKAMcYYY5qg84fnzpw5g2+//RanTp1CdnY2tmzZAgcHhzLb85ADjDHGGNMEnS+aMjMzkZSUBCMjI2RnZ8PW1rZKcep+3B8SiVzk7N5M1GyOtlOodRbfvq3tFGqdWy7azqB2efxY2xnUPkH7KnfjeVa+dAC/a3gdOn947vDhw4iLi8OBAwcAAC9evEBycjJycnK0nBljjDHG3iQ6XzRt3rwZaWlp6NmzJwBg/PjxqF+/Pvbu3auyPd+wlzHGGGOaoPNFExEJDwA4ePAgiAjjxo1T2Z6vnmOMMcaYJuh80VRZfPUcY4wxxjRB508Eryy+eo4xxhhjmlDriqbXKQ7rEfG5TWJJLyrSdgq1Dt9+WnwFBfyZFxPfJ018/A4Vl2J/Kn73NUHni6bMzEzExcUJzx88eIDo6GhYWVnBycmpwuUzMjIAAEVFfG6TWCxitZ0BY2r4ne9PyXRbHW0nUEtlZGRo7P60EtJkSSaC0NBQ9OrVq9R0b29vBAYGVrh8cXExEhMTYW5uDolEd8fESE9Ph6OjIx49egS5nMeTEgPvU/HxPhUX70/x8T4V1z9pfxIRMjIyYG9vDz09zZyyrfM9TT179qxWV5uenl65I4jrGrlcrvNvzH8a3qfi430qLt6f4uN9Kq5/yv7UVA+TQq27eo4xxhhjTBO4aGKMMcYYUwMXTTpCJpPBz8+Ph0sQEe9T8fE+FRfvT/HxPhUX709lOn8iOGOMMcaYLuCeJsYYY4wxNXDRxBhjjDGmBi6aGGOMMcbUwEUTY4wxxpgauGjSgE2bNqFhw4YwMjKCu7s7Ll++LMzbunUrevbsCblcDolEgpcvX5ZafsWKFejWrRtMTExgaWlZav7Vq1cxatQoODo6wtjYGM2bN8fGjRs1uEXapen9CQBXrlxB7969YWlpiTp16qB///64evWqhrZI+8rap6mpqZg+fTrc3NxgbGwMJycnzJgxA2lpaUrLJyQkwMvLCyYmJrCxscEXX3yBwtduThYaGooOHTpAJpPBxcVFrRH8/6lqYn/m5eVhwYIFcHZ2hkwmQ8OGDbFjx44a28aaVt19OmPGDHTs2BEymQzt2rUrFT80NBRDhgxB/fr1YWpqinbt2mHXrl01sWlao+l9CgDHjh3DW2+9BXNzc9SrVw8ffPABHj58qOEtqzlcNIls7969mDVrFvz8/BAZGYm2bduif//+ePLkCQAgOzsbnp6e+Oqrr8qMkZ+fj48++ghTpkxROT8iIgI2Njb497//jZs3b2LBggWYP38+fvjhB41skzbVxP7MzMyEp6cnnJyccOnSJZw7dw7m5ubo378/CgoKNLJd2lTePk1MTERiYiLWrFmDGzduIDAwEEePHsWECROE5YuKiuDl5YX8/HxcuHABO3fuRGBgIBYtWiS0efDgAby8vNCrVy9ER0fj888/x6effopjx45pY5M1qib2JwAMHz4cJ0+exPbt23Hnzh3s2bMHbm5uNb25NaK6+1Rh/PjxGDFihMp1XLhwAW3atMFvv/2Ga9euwcfHB2PHjsXhw4c1vXlaURP79MGDBxgyZAjeffddREdH49ixY3j27BmGDRum6c2rOcRE1aVLF5o6darwvKioiOzt7cnf31+pXUhICAGgFy9elBkrICCALCws1Frvv/71L+rVq1dVUtZpNbE/r1y5QgAoISFBmHbt2jUCQLGxsdXeBl2j7j5VCA4OJqlUSgUFBUREdOTIEdLT06Pk5GShzebNm0kul1NeXh4REc2dO5datmypFGfEiBHUv39/sTdH62pif/75559kYWFBz58/1+CW6I7q7tOS/Pz8qG3btmqtd+DAgeTj41OlnHVdTezTffv2kYGBARUVFQnTDh06RBKJhPLz86u/ETqAe5pElJ+fj4iICPTp00eYpqenhz59+iAsLEyj605LS4OVlZVG11HTamp/urm5oW7duti+fTvy8/ORk5OD7du3o3nz5mjYsKFo69EFVdmnaWlpkMvlMDB4davKsLAwtG7dGra2tkKb/v37Iz09HTdv3hTalFyHoo2mPwc1rab256FDh9CpUyesXr0aDRo0gKurK+bMmYOcnBwNbp12iLFPq6o2fo8CNbdPO3bsCD09PQQEBKCoqAhpaWn49ddf0adPHxgaGlZ7O3QBF00ievbsGYqKipS+/ADA1tYWycnJGlvvhQsXsHfvXnz22WcaW4c21NT+NDc3R2hoKP7973/D2NgYZmZmOHr0KP78889qfwnrmsru02fPnmHZsmVK763k5GSVyyvmldcmPT29Vv3Q19T+vH//Ps6dO4cbN27g4MGD2LBhA/bv349//etfYm+S1omxT6siODgYV65cgY+PT7Xi6KKa2qeNGjXCX3/9ha+++goymQyWlpZ4/PgxgoODq5W/LuGi6R/uxo0bGDJkCPz8/NCvXz9tp/OPlJOTgwkTJqB79+64ePEizp8/j1atWsHLy6tW/cBXVnp6Ory8vNCiRQssXrxY2+n841VnfxYXF0MikWDXrl3o0qULBg4ciHXr1mHnzp38HhXhPRoSEgIfHx9s27YNLVu2FC/Bf6Dq7NPk5GRMnDgR3t7euHLlCk6fPg2pVIoPP/wQVEtuPlK7/hutZdbW1tDX10dKSorS9JSUFNjZ2Ym+vlu3bqF379747LPP8PXXX4seX9tqan/u3r0bDx8+RFhYGPT09IRpderUwR9//IGRI0eKti5tU3efZmRkwNPTE+bm5jh48KBS17qdnZ3SFYyK5RXzFH9VrUMul8PY2FjUbdKmmtqf9evXR4MGDWBhYSG0ad68OYgIjx8/RtOmTUXfNm0RY59WxunTpzFo0CCsX78eY8eOrVbuuqqm9ummTZtgYWGB1atXC9P+/e9/w9HREZcuXcJbb71VvQ3RAdzTJCKpVIqOHTvi5MmTwrTi4mKcPHkSXbt2FXVdN2/eRK9eveDt7Y0VK1aIGltX1NT+zM7Ohp6eHiQSiTBN8by4uFi09egCdfZpeno6+vXrB6lUikOHDsHIyEgpRteuXXH9+nXhCkYAOH78OORyOVq0aCG0KbkORRuxPwfaVlP7s3v37khMTERmZqbQ5u7du9DT04ODg4MmN7HGibFP1RUaGgovLy+sWrWq1p3eUFJN7VPFd2lJ+vr6wvpqBW2fiV7bBAUFkUwmo8DAQLp16xZ99tlnZGlpKVwZk5SURFFRUbRt2zYCQGfOnKGoqCilq2Li4+MpKiqKlixZQmZmZhQVFUVRUVGUkZFBRETXr1+nevXq0ejRoykpKUl4PHnyRCvbrEk1sT9jYmJIJpPRlClT6NatW3Tjxg0aPXo0WVhYUGJiola2W5PK26dpaWnk7u5OrVu3pri4OKX3V2FhIRERFRYWUqtWrahfv34UHR1NR48epXr16tH8+fOFddy/f59MTEzoiy++oJiYGNq0aRPp6+vT0aNHtbXZGlMT+zMjI4McHBzoww8/pJs3b9Lp06epadOm9Omnn2prszWquvuUiCg2NpaioqJo0qRJ5OrqKnzuFVcknjp1ikxMTGj+/PlKMWrrFYo1sU9PnjxJEomElixZQnfv3qWIiAjq378/OTs7U3Z2trY2XVRcNGnA999/T05OTiSVSqlLly508eJFYZ6fnx8BKPUICAgQ2nh7e6tsExISUm4MZ2fnmt3QGqLp/UlE9Ndff1H37t3JwsKC6tSpQ++++y6FhYXV4FbWrLL2qWLoBlWPBw8eCMs/fPiQBgwYQMbGxmRtbU2zZ88udWlySEgItWvXjqRSKTVu3FjpNaltamJ/xsTEUJ8+fcjY2JgcHBxo1qxZteaHSJXq7lMPD49y25T1veDh4VHzG1tDNL1PiYj27NlD7du3J1NTU6pXrx4NHjyYYmJianhLNUdCVEvOzmKMMcYY0yA+p4kxxhhjTA1cNDHGGGOMqYGLJsYYY4wxNXDRxBhjjDGmBi6aGGOMMcbUwEUTY4wxxpgauGhijDHGGFMDF02MMcYYY2rgookxxhhjTA1cNDHGGGOMqYGLJsYYY4wxNXDRxBhjjDGmBi6aGGOMMcbUwEUTY4wxxpgauGhijDHGGFMDF02MMcYYY2rgookxxhhjTA0G2k6gJuTm5iI/P1/baTDGGGNMg6RSKYyMjDQWv9YXTbm5uTA2tgSQp+1UGGOMMaZBdnZ2ePDggcYKp1pfNL3qYcoD0AeA9H9T9cv4q/fa37LaVbZ9WfM1tb6S7SubW0XPy/orEXkbKtpn6ub3ar7B/97pZf3V16/e/JqM80/MWRtx9FD86h+FheX/LSqq3nwx4uhSLrq8PjXj0KtnindAlf9WFKeonHYVxShvWXVyqezyr8ep6vKV3Ufq7jsxXrM8AOuTk5Gfn89FU/UZADD8378r+0Nd3fZVLRDEWG9N5aab7SQSvf/9Rbl/9fTK/6v4oa7ob0U/5GL8rYl11Ia/ahdNuvBXU7HLeqMq5lf0xle0q+gDpPhbESL1/paVT3GxWnnQ/+JUt2iq7A+/qqKpKstWd91vwvJl/dU0PhGcMcYYY0wNXDQxxhhjjKmBiybGGGOMMTVw0cQYY4wxpgYumhhjjDHG1MBFE2OMMcaYGrhoYowxxhhTAxdNjDHGGGNq4KKJMcYYY0wNXDQxxhhjjKmBiybGGGOMMTVw0cQYY4wxpgYumhhjjDHG1MBFE2OMMcaYGrhoYowxxhhTAxdNjDHGGGNq4KKJMcYYY0wNXDQxxhhjjKmBiybGGGOMMTVw0cQYY4wxpgYumhhjjDHG1GCg7QRqTiH+v0YsLuOvYn7R//7qV/BX77W/FbWr6vLVaV/Z3Cp6XtZficjbUNE+Uy8/Ir3//UW5f4uLy/9b9L+3hERS/t+KVJSHOvm8nlNZfwsLX/01MCj/r75+9ebrahw9xedasSPK+vv6DqvsfDHi6FIumlxfRX8r+iCq+QH637Myv+nV/VtRnKJy2lUUo7xl1cmlssu/Hqeqy1d2H6m778R4zfKgebW+aJJKpbCzs0Ny8gltp8K06PXvcMYYY7WPnZ0dpFKpxuJLiBQleu2Vm5uL/Px80eOmp6fD0dERjx49glwuFz2+rngTtvNN2EaAt7O2eRO2803YRoC3UyxSqRRGRkaix1Wo9T1NAGBkZKTRnSiXy2v1m1zhTdjON2EbAd7O2uZN2M43YRsB3k5dxyeCM8YYY4ypgYsmxhhjjDE1cNFUDTKZDH5+fpDJZNpORaPehO18E7YR4O2sbd6E7XwTthHg7fyneCNOBGeMMcYYqy7uaWKMMcYYUwMXTYwxxhhjauCiiTHGGGNMDVw0McYYY4ypgYumcqxYsQLdunWDiYkJLC0t1VqGiLBo0SLUr18fxsbG6NOnD2JjY5XapKam4pNPPoFcLoelpSUmTJiAzMxMDWyBeiqbz8OHDyGRSFQ+9u3bJ7RTNT8oKKgmNkmlquz3nj17ltqGyZMnK7VJSEiAl5cXTExMYGNjgy+++AKFWrxfS2W3MzU1FdOnT4ebmxuMjY3h5OSEGTNmIC0tTamdNl/PTZs2oWHDhjAyMoK7uzsuX75cbvt9+/ahWbNmMDIyQuvWrXHkyBGl+ep8TrWhMtu5bds29OjRA3Xq1EGdOnXQp0+fUu3HjRtX6jXz9PTU9GZUqDLbGRgYWGobXh+sWBdfz8pso6rvGYlEAi8vL6GNLr6WZ86cwaBBg2Bvbw+JRILff/+9wmVCQ0PRoUMHyGQyuLi4IDAwsFSbyn7eaxSxMi1atIjWrVtHs2bNIgsLC7WW+eabb8jCwoJ+//13unr1Kg0ePJgaNWpEOTk5QhtPT09q27YtXbx4kc6ePUsuLi40atQoDW1FxSqbT2FhISUlJSk9lixZQmZmZpSRkSG0A0ABAQFK7Uruh5pWlf3u4eFBEydOVNqGtLQ0YX5hYSG1atWK+vTpQ1FRUXTkyBGytram+fPna3pzylTZ7bx+/ToNGzaMDh06RHFxcXTy5Elq2rQpffDBB0rttPV6BgUFkVQqpR07dtDNmzdp4sSJZGlpSSkpKSrbnz9/nvT19Wn16tV069Yt+vrrr8nQ0JCuX78utFHnc1rTKrudH3/8MW3atImioqIoJiaGxo0bRxYWFvT48WOhjbe3N3l6eiq9ZqmpqTW1SSpVdjsDAgJILpcrbUNycrJSG117PSu7jc+fP1favhs3bpC+vj4FBAQIbXTxtTxy5AgtWLCADhw4QADo4MGD5ba/f/8+mZiY0KxZs+jWrVv0/fffk76+Ph09elRoU9l9V9O4aFJDQECAWkVTcXEx2dnZ0bfffitMe/nyJclkMtqzZw8REd26dYsA0JUrV4Q2f/75J0kkEvr7779Fz70iYuXTrl07Gj9+vNI0dT5ENaWq2+nh4UG+vr5lzj9y5Ajp6ekpfYlv3ryZ5HI55eXliZJ7ZYj1egYHB5NUKqWCggJhmrZezy5dutDUqVOF50VFRWRvb0/+/v4q2w8fPpy8vLyUprm7u9OkSZOISL3PqTZUdjtfV1hYSObm5rRz505hmre3Nw0ZMkTsVKulsttZ0fevLr6e1X0t169fT+bm5pSZmSlM08XXsiR1vh/mzp1LLVu2VJo2YsQI6t+/v/C8uvtO0/jwnIgePHiA5ORk9OnTR5hmYWEBd3d3hIWFAQDCwsJgaWmJTp06CW369OkDPT09XLp0qcZzFiOfiIgIREdHY8KECaXmTZ06FdbW1ujSpQt27NgB0tKwYNXZzl27dsHa2hqtWrXC/PnzkZ2drRS3devWsLW1Fab1798f6enpuHnzpvgbUgGx3l9paWmQy+UwMFC+PWVNv575+fmIiIhQ+kzp6emhT58+wmfqdWFhYUrtgVeviaK9Op/TmlaV7XxddnY2CgoKYGVlpTQ9NDQUNjY2cHNzw5QpU/D8+XNRc6+Mqm5nZmYmnJ2d4ejoiCFDhih9tnTt9RTjtdy+fTtGjhwJU1NTpem69FpWRUWfTTH2naa9ETfsrSnJyckAoPQDqniumJecnAwbGxul+QYGBrCyshLa1CQx8tm+fTuaN2+Obt26KU1funQp3n33XZiYmOCvv/7Cv/71L2RmZmLGjBmi5a+uqm7nxx9/DGdnZ9jb2+PatWv48ssvcefOHRw4cECIq+r1VsyraWK8ns+ePcOyZcvw2WefKU3Xxuv57NkzFBUVqdzHt2/fVrlMWa9Jyc+gYlpZbWpaVbbzdV9++SXs7e2VfnA8PT0xbNgwNGrUCPfu3cNXX32FAQMGICwsDPr6+qJugzqqsp1ubm7YsWMH2rRpg7S0NKxZswbdunXDzZs34eDgoHOvZ3Vfy8uXL+PGjRvYvn270nRdey2roqzPZnp6OnJycvDixYtqfw407Y0rmubNm4dVq1aV2yYmJgbNmjWroYw0Q93trK6cnBzs3r0bCxcuLDWv5LT27dsjKysL3377rag/sprezpKFQ+vWrVG/fn307t0b9+7dQ5MmTaoct7Jq6vVMT0+Hl5cXWrRogcWLFyvNq4nXk1XNN998g6CgIISGhiqdJD1y5Ejh361bt0abNm3QpEkThIaGonfv3tpItdK6du2Krl27Cs+7deuG5s2b46effsKyZcu0mJlmbN++Ha1bt0aXLl2UpteG17I2eOOKptmzZ2PcuHHltmncuHGVYtvZ2QEAUlJSUL9+fWF6SkoK2rVrJ7R58uSJ0nKFhYVITU0VlheDuttZ3Xz279+P7OxsjB07tsK27u7uWLZsGfLy8kS771BNbaeCu7s7ACAuLg5NmjSBnZ1dqSs7UlJSAOAf93pmZGTA09MT5ubmOHjwIAwNDcttr4nX83XW1tbQ19cX9qlCSkpKmdtjZ2dXbnt1Pqc1rSrbqbBmzRp88803OHHiBNq0aVNu28aNG8Pa2hpxcXFa+aGtznYqGBoaon379oiLiwOge69ndbYxKysLQUFBWLp0aYXr0fZrWRVlfTblcjmMjY2hr69f7feHxmn7pKp/gsqeCL5mzRphWlpamsoTwcPDw4U2x44d0/qJ4FXNx8PDo9RVVmVZvnw51alTp8q5VodY+/3cuXMEgK5evUpE/38ieMkrO3766SeSy+WUm5sr3gaoqarbmZaWRm+99RZ5eHhQVlaWWuuqqdezS5cuNG3aNOF5UVERNWjQoNwTwd977z2laV27di11Inh5n1NtqOx2EhGtWrWK5HI5hYWFqbWOR48ekUQioT/++KPa+VZVVbazpMLCQnJzc6OZM2cSkW6+nlXdxoCAAJLJZPTs2bMK16ELr2VJUPNE8FatWilNGzVqVKkTwavz/tA0LprKER8fT1FRUcLl9FFRURQVFaV0Wb2bmxsdOHBAeP7NN9+QpaUl/fHHH3Tt2jUaMmSIyiEH2rdvT5cuXaJz585R06ZNtT7kQHn5PH78mNzc3OjSpUtKy8XGxpJEIqE///yzVMxDhw7Rtm3b6Pr16xQbG0s//vgjmZiY0KJFizS+PWWp7HbGxcXR0qVLKTw8nB48eEB//PEHNW7cmN555x1hGcWQA/369aPo6Gg6evQo1atXT+tDDlRmO9PS0sjd3Z1at25NcXFxSpc0FxYWEpF2X8+goCCSyWQUGBhIt27dos8++4wsLS2FKxbHjBlD8+bNE9qfP3+eDAwMaM2aNRQTE0N+fn4qhxyo6HNa0yq7nd988w1JpVLav3+/0mum+H7KyMigOXPmUFhYGD148IBOnDhBHTp0oKZNm2qloFeo7HYuWbKEjh07Rvfu3aOIiAgaOXIkGRkZ0c2bN4U2uvZ6VnYbFd5++20aMWJEqem6+lpmZGQIv4sAaN26dRQVFUXx8fFERDRv3jwaM2aM0F4x5MAXX3xBMTExtGnTJpVDDpS377SNi6ZyeHt7E4BSj5CQEKEN/jd2jUJxcTEtXLiQbG1tSSaTUe/evenOnTtKcZ8/f06jRo0iMzMzksvl5OPjo1SI1bSK8nnw4EGp7SYimj9/Pjk6OlJRUVGpmH/++Se1a9eOzMzMyNTUlNq2bUtbtmxR2bamVHY7ExIS6J133iErKyuSyWTk4uJCX3zxhdI4TUREDx8+pAEDBpCxsTFZW1vT7NmzlS7Vr2mV3c6QkBCV73MA9ODBAyLS/uv5/fffk5OTE0mlUurSpQtdvHhRmOfh4UHe3t5K7YODg8nV1ZWkUim1bNmS/vvf/yrNV+dzqg2V2U5nZ2eVr5mfnx8REWVnZ1O/fv2oXr16ZGhoSM7OzjRx4kSd+PGpzHZ+/vnnQltbW1saOHAgRUZGKsXTxdezsu/Z27dvEwD666+/SsXS1deyrO8OxbZ5e3uTh4dHqWXatWtHUqmUGjdurPT7qVDevtM2CZGWrgFnjDHGGPsH4XGaGGOMMcbUwEUTY4wxxpgauGhijDHGGFMDF02MMcYYY2rgookxxhhjTA1cNDHGGGOMqYGLJsYYY4wxNXDRxBir1d555x3s3r1b22kI5s2bh+nTp2s7DcZYFXDRxBirlHHjxkEikWDy5Mml5k2dOhUSiaTCmwvXlEOHDiElJUXpDvEAcOHCBQwcOBB16tSBkZERWrdujXXr1qGoqKja61y8eDEkEkmpx4kTJwAAc+bMwc6dO3H//v1qr4sxVrO4aGKMVZqjoyOCgoKQk5MjTMvNzcXu3bvh5OSkxcyUfffdd/Dx8YGe3v9/1R08eBAeHh5wcHBASEgIbt++DV9fXyxfvhwjR46EGDdJaNmyJZKSkpQe77zzDgDA2toa/fv3x+bNm6u9HsZYzeKiiTFWaR06dICjoyMOHDggTDtw4ACcnJzQvn17pbbFxcXw9/dHo0aNYGxsjLZt22L//v3C/KKiIkyYMEGY7+bmho0bNyrFGDduHIYOHYo1a9agfv36qFu3LqZOnYqCgoIyc3z69ClOnTqFQYMGCdOysrIwceJEDB48GFu3bkW7du3QsGFDfPrpp9i5cyf279+P4OBgAMDDhw8hkUgQHByMHj16wNjYGJ07d8bdu3dx5coVdOrUCWZmZhgwYACePn2qtG4DAwPY2dkpPaRSqTB/0KBBCAoKqsQeZ4zpAi6aGGNVMn78eAQEBAjPd+zYAR8fn1Lt/P398csvv2DLli24efMmZs6cidGjR+P06dMAXhVVDg4O2LdvH27duoVFixbhq6++EooXhZCQENy7dw8hISHYuXMnAgMDERgYWGZ+586dg4mJCZo3by5M++uvv/D8+XPMmTOnVPtBgwbB1dUVe/bsUZru5+eHr7/+GpGRkTAwMMDHH3+MuXPnYuPGjTh79izi4uKwaNEitfaZQpcuXfD48WM8fPiwUssxxrTLQNsJMMb+mUaPHo358+cjPj4eAHD+/HkEBQUhNDRUaJOXl4eVK1fixIkT6Nq1KwCgcePGOHfuHH766Sd4eHjA0NAQS5YsEZZp1KgRwsLCEBwcjOHDhwvT69Spgx9++AH6+vpo1qwZvLy8cPLkSUycOFFlfvHx8bC1tVU6NHf37l0AUCqkSmrWrJnQRmHOnDno378/AMDX1xejRo3CyZMn0b17dwDAhAkTShVv169fh5mZmfC8RYsWuHz5svDc3t5eyLFhw4Yqc2GM6R4umhhjVVKvXj14eXkhMDAQRAQvLy9YW1srtYmLi0N2djb69u2rND0/P1/pMN6mTZuwY8cOJCQkICcnB/n5+WjXrp3SMi1btoS+vr7wvH79+rh+/XqZ+eXk5MDIyEjlvMqct9SmTRvh37a2tgCA1q1bK0178uSJ0jJubm44dOiQ8FwmkynNNzY2BgBkZ2ernQdjTPu4aGKMVdn48eMxbdo0AK8Kn9dlZmYCAP773/+iQYMGSvMUhURQUBDmzJmDtWvXomvXrjA3N8e3336LS5cuKbU3NDRUei6RSFBcXFxmbtbW1njx4oXSNFdXVwBATEwMunXrVmqZmJgYtGjRosz1SiQSldNez0MqlcLFxaXM3FJTUwG8KjwZY/8cXDQxxqrM09MT+fn5kEgkwiGsklq0aAGZTIaEhAR4eHiojHH+/Hl069YN//rXv4Rp9+7dq3Zu7du3R3JyMl68eIE6deoAAPr16wcrKyusXbu2VNF06NAhxMbGYtmyZdVed0Vu3LgBQ0NDtGzZUuPrYoyJh4smxliV6evrIyYmRvj368zNzTFnzhzMnDkTxcXFePvtt5GWlobz589DLpfD29sbTZs2xS+//IJjx46hUaNG+PXXX3HlyhU0atSoWrm1b98e1tbWOH/+PN577z0AgKmpKX766SeMHDkSn332GaZNmwa5XI6TJ0/iiy++wIcffqh0HpWmnD17VrgijzH2z8FXzzHGqkUul0Mul5c5f9myZVi4cCH8/f3RvHlzeHp64r///a9QFE2aNAnDhg3DiBEj4O7ujufPnyv1OlWVvr4+fHx8sGvXLqXpH374IUJCQpCQkIAePXrAzc0N69evx4IFCxAUFCQcgtOkoKCgMk9gZ4zpLgmJMZIbY4zpoOTkZLRs2RKRkZFwdnbWdjoAgD///BOzZ8/GtWvXYGDAnf2M/ZNwTxNjrNays7PD9u3bkZCQoO1UBFlZWQgICOCCibF/IO5pYowxxhhTA/c0McYYY4ypgYsmxhhjjDE1cNHEGGOMMaYGLpoYY4wxxtTARRNjjDHGmBq4aGKMMcYYUwMXTYwxxhhjauCiiTHGGGNMDVw0McYYY4ypgYsmxhhjjDE1cNHEGGOMMaYGLpoYY4wxxtTARRNjjDHGmBq4aGKMMcYYUwMXTYwxxhhjauCiiTHGGGNMDVw0McYYY4ypgYsmxhhjjDE1cNHEGGOMMaYGLpoYY4wxxtTARRNjjDHGmBq4aGKljBs3DosXL9Z2GhpBRPjss89gZWUFiUSC6OhobafEGNOATZs2oWHDhjAyMoK7uzsuX76sNH/r1q3o2bMn5HI5JBIJXr58qTLO4cOH4eHhAXNzc5iYmKBz584IDAysVC7jxo3D0KFD1WqbkJAALy8vmJiYwMbGBl988QUKCwuF+QcOHEDfvn1Rr149yOVydO3aFceOHSsV59GjRxg/fjzs7e0hlUrh7OwMX19fPH/+XO28Q0NDy903JdsNGTIE9evXh6mpKdq1a4ddu3aVardv3z40a9YMRkZGaN26NY4cOSLMKygowJdffonWrVvD1NQU9vb2GDt2LBITE5ViNGzYEBKJROnxzTffqL1N1cVF0/88fPhQp39ExXhT1oSwsDDo6+vDy8tLmDZu3LhSb/KSj4YNGwIAevbsWeYHwMvLCxKJRKmYe/DgAT7++GPY29vDyMgIDg4OGDJkCG7fvl1mfkePHkVgYCAOHz6MpKQktGrVSrRtryrFdgcFBSlN37Bhg7BvFHJycuDn5wdXV1fIZDJYW1vjo48+ws2bN1XG3rNnD/T19TF16tRyc/D394e+vj6+/fbbCvNV98stNTUVn3zyCeRyOSwtLTFhwgRkZmZWGJ+x6tq7dy9mzZoFPz8/REZGom3btujfvz+ePHkitMnOzoanpye++uqrMuN8//33GDJkCLp3745Lly7h2rVrGDlyJCZPnow5c+aInndRURG8vLyQn5+PCxcuYOfOnQgMDMSiRYuENmfOnEHfvn1x5MgRREREoFevXhg0aBCioqKENvfv30enTp0QGxuLPXv2IC4uDlu2bMHJkyfRtWtXpKamipr3hQsX0KZNG/z222+4du0afHx8MHbsWBw+fFipzahRozBhwgRERUVh6NChGDp0KG7cuAHg1esRGRmJhQsXIjIyEgcOHMCdO3cwePDgUutbunQpkpKShMf06dNF3Z5yESMiogcPHhAAioqK0nYqKq1YsYK+/vprOn/+PMXFxdGGDRtIT0+P/vOf/whtzp8/T/r6+rR69Wq6desWff3112RoaEjXr1+v1Lq8vb3Jz8+vSnlOmDCBfH19yczMjP7++28iInr58iUlJSUJDwAUEBAgPH/y5AkREXl4eJCjoyO5ubkpxXz8+DHJZDKqX7++kFd+fj41adKEBg4cSGFhYfTw4UM6d+4cLViwgMLCwsrM7/vvvycnJ6dytyEvL69K215VHh4eZGRkRE2aNKH8/Hxh+vr168nZ2Vl4npubS926dSMHBwfau3cvPXz4kC5dukRDhw4lU1NTldvdu3dvmjdvHtWpU4dycnLKzMHFxYXmzZtHzZo1qzDfly9fUp8+fWjv3r10+/ZtCgsLoy5dulDHjh2V2nl6elLbtm3p4sWLdPbsWXJxcaFRo0apsUcYq54uXbrQ1KlThedFRUVkb29P/v7+pdqGhIQQAHrx4oXS9ISEBDI0NKRZs2aVWua7774jAHTx4kVh2o0bN8jLy4vMzc3JzMyM3n77bYqLiyM/Pz8CoPQICQlRmfeRI0dIT0+PkpOThWmbN28muVxe7vdSixYtaMmSJcJzT09PcnBwoOzsbKV2SUlJZGJiQpMnTxam5ebm0ty5c8nBwYGkUik1adKEfv75Z+E3seTD29u7zBxeN3DgQPLx8RGeDx8+nLy8vJTauLu706RJk8qMcfnyZQJA8fHxwjRnZ2dav3692nmI7Y0pmv7880/q3r07WVhYkJWVFXl5eVFcXJww//U3h4eHBxG9KiCGDBlCK1asIBsbG7KwsKAlS5ZQQUEBzZkzh+rUqUMNGjSgHTt2CLHy8vJo6tSpZGdnRzKZjJycnGjlypVl5qZ4c/7222/Us2dPMjY2pjZt2tCFCxfK3SYx3pSqVLVoysjIIDMzM7p9+zaNGDGCVqxYobIdADp48GCp6R4eHjRlyhSqW7cunTt3Tpi+YsUKGjRoELVt21bIKyoqigDQw4cP1c7P29tb6TVWFCQeHh40depU8vX1pbp161LPnj2JiCg0NJQ6d+5MUqmU7Ozs6Msvv6SCggKlfKdNm0a+vr5kaWlJNjY2tHXrVsrMzKRx48aRmZkZNWnShI4cOVJuXh4eHuTj40N169alTZs2CdNfL5q++eYbkkgkFB0drbR8UVERderUiVq0aEHFxcXC9Pv375OxsTG9fPmS3N3dadeuXSrXHxoaSg0aNKD8/Hyyt7en8+fPq7U/S3r9y+3WrVsEgK5cuSK0+fPPP0kikQjFNGOakJeXR/r6+qW+Y8aOHUuDBw8u1b6somndunUEgBITE1Wuw8zMjHx9fYno1X/srKysaNiwYXTlyhW6c+cO7dixg27fvk0ZGRk0fPhw8vT0FP6jWFYBtHDhQmrbtq3StPv37xMAioyMVLlMUVEROTo60vfff09ERM+fPyeJRFLmb87EiROpTp06wnfF8OHDydHRkQ4cOED37t2jEydOUFBQEBUWFtJvv/1GAOjOnTuUlJREL1++VBlTle7du9Ps2bOF546OjqWKnUWLFlGbNm3KjHH8+HGSSCSUlpYmTHN2diZbW1uysrKidu3a0erVq5W+lzXtjTk8l5WVhVmzZiE8PBwnT56Enp4e3n//fRQXFwOAcLz7xIkTSEpKwoEDB4RlT506hcTERJw5cwbr1q2Dn58f3nvvPdSpUweXLl3C5MmTMWnSJDx+/BgA8N133+HQoUMIDg7GnTt3sGvXrlKHWVRZsGAB5syZg+joaLi6umLUqFFKx7Jfl5aWBisrK+F5WFgY+vTpo9Smf//+CAsLU3s/VUdwcDCaNWsGNzc3jB49Gjt27AARVSqGVCrFJ598goCAAGFaYGAgxo8fr9SuXr160NPTw/79+1FUVKRW7I0bN2Lp0qVwcHBAUlISrly5IszbuXMnpFIpzp8/jy1btuDvv//GwIED0blzZ1y9ehWbN2/G9u3bsXz5cqWYO3fuhLW1NS5fvozp06djypQp+Oijj9CtWzdERkaiX79+GDNmDLKzs8vNTS6XY8GCBVi6dCmysrJUttm9ezf69u2Ltm3bKk3X09PDzJkzcevWLVy9elWYHhAQAC8vL1hYWGD06NHYvn27yrjbt2/HqFGjYGhoiFGjRpXZrjxpaWmQSCSwtLQE8Oq9aGlpiU6dOglt+vTpAz09PVy6dKnS8RlT17Nnz1BUVARbW1ul6ba2tkhOTlY7zt27d2FhYYH69euXmieVStG4cWPcvXsXwKvzpywsLBAUFIROnTrB1dUVPj4+cHNzg5mZGYyNjSGTyWBnZwc7OztIpVKV60xOTlaZt2KeKmvWrEFmZiaGDx8OAIiNjQURoXnz5irbN2/eHC9evMDTp09x9+5dBAcHY8eOHXj//ffRuHFj9O7dGyNGjIC+vr7w+2JjYwM7OztYWFiosede/RZcuXIFPj4+FW5bWduVm5uLL7/8EqNGjYJcLhemz5gxA0FBQQgJCcGkSZOwcuVKzJ07V628RFFj5ZmOefr0KQEQDl2VdXjO29ubnJ2dqaioSJjm5uZGPXr0EJ4XFhaSqakp7dmzh4iIpk+fTu+++67S//rLo1j3zz//LEy7efMmAaCYmBiVy+zdu5ekUinduHFDmGZoaEi7d+9Wardp0yaysbFRKw+FqvY0devWjTZs2EBERAUFBWRtba2yGxrl9DT5+vpSdHQ0mZubU2ZmJp0+fZpsbGyooKBAqaeJiOiHH34gExMTMjc3p169etHSpUvp3r175eb4eu+NYr3t27dXmvbVV1+Rm5ub0mu4adMmMjMzE94LHh4e9PbbbwvzFe+DMWPGCNMUhyPLO2So2O7c3FxydnampUuXqszVyMhI+J/t6yIjIwkA7d27l4j+/3+fv//+OxG9er9LpVK6f/++0nJpaWlkbGws9F5FRUWRmZkZZWRklJnv63JycqhDhw708ccfC9NWrFhBrq6updrWq1ePfvzxR7VjM1ZZf//9NwEo1VP/xRdfUJcuXUq1L6unafLkyWRhYVHmetq0aUMDBgwgIqIBAwbQ2LFjy2yrOGJRkqenJ5mampKpqSm1aNGCiF71AvXr10+pXVZWFgFQ2WO9a9cuMjExoePHjwvTLl68SADowIEDKnNR9KClpKTQ3r17SV9fX+m0gJLK2jflOXXqFJmYmNDOnTuVplfm9yk/P58GDRpE7du3V+plUmX79u1kYGBAubm5audYHW9MT1NsbCxGjRqFxo0bQy6XCz0/CQkJFS7bsmVL6On9/66ytbVF69athef6+vqoW7eucJLhuHHjEB0dDTc3N8yYMQN//fWX0Hby5MkwMzMTHiW1adNG+LfifzclT1xUCAkJgY+PD7Zt24aWLVuqsfWad+fOHVy+fBmjRo0CABgYGGDEiBFV6rVo27YtmjZtiv3792PHjh0YM2YMDAwMSrWbOnUqkpOTsWvXLnTt2hX79u1Dy5Ytcfz48Uqvs2PHjkrPY2Ji0LVrV0gkEmFa9+7dkZmZKfQoAsqvmeJ9UPK9ofiflarX8XUymQxLly7FmjVr8OzZM5VtSM2eu+PHjyMrKwsDBw4EAFhbW6Nv377YsWOHUrs9e/agSZMmQu9Vu3bt4OzsjL179wIAdu3apfR+PXv2rNLyBQUFGD58OIgImzdvVis3xjTJ2toa+vr6SElJUZqekpICOzs7teO4uroiLS2t1AUOAJCfn4979+7B1dUVAGBsbFzpPH/++WdER0cjOjpauGDHzs5OZd6KeSUFBQXh008/RXBwsNIRBhcXF0gkEsTExKhcb0xMDOrUqYN69epVKe/ynD59GoMGDcL69esxduxYpXllbdvr26X4TomPj8fx48eVeplUcXd3R2FhIR4+fCjKNlTkjSmaBg0ahNTUVGzbtg2XLl0SDhHk5+dXuKyhoaHSc4lEonKa4lBfhw4d8ODBAyxbtgw5OTkYPnw4PvzwQwCvzvpXfFBev1KvZEzFj7UipoIYb0pN2L59OwoLC2Fvbw8DAwMYGBhg8+bN+O2335CWllbpeOPHj8emTZuwf//+UofmSjI3N8egQYOwYsUKXL16FT169Ch1CE0dpqamlV4GqPi9UdbrWJbRo0fD2dlZ5Ta4urqW+0WoaAO8ej1SU1NhbGwsvB5HjhzBzp07lXLZvn07bt68KbQxMDDArVu3hOJq8ODBSu/Xkofbyvtys7OzK1UoFhYWIjU1tUbej+zNJZVK0bFjR5w8eVKYVlxcLFw5pq4PPvgAhoaGWLt2bal5W7ZsQVZWlvCfxDZt2uDs2bMoKCgoM6fXTyNo0KABXFxc4OLiAmdnZwBA165dcf36daXPjuKz1aJFC2Hanj174OPjgz179ihdqQwAdevWRd++ffHjjz8iJydHaZ7iP5kjRoyARCJB69atUVxcjNOnT5eZNwC1ToEIDQ2Fl5cXVq1ahc8++6zU/K5duyq9JoptK/maKL5TYmNjceLECdStW7fC9UZHR0NPTw82NjYVthXDG1E0PX/+HHfu3MHXX3+N3r17C8d0S6rMm0MdcrkcI0aMwLZt27B371789ttvSE1NhY2NjfBBcXFxqVRMMd6UmlBYWIhffvkFa9euVfqBvXr1Kuzt7bFnz55Kx/z4449x/fp1tGrVSunLojwSiQTNmjUr85ygymjevDnCwsKUenbOnz8Pc3NzODg4VDt+WfT09ODv74/NmzeX+p/TyJEjceLECaXzloBXPwjr169HixYt0LZtWzx//hx//PEHgoKClF6PqKgovHjxQuj5vH79OsLDwxEaGqrULjQ0FGFhYbh9+zbMzc2V3q+K/5lW9OXWtWtXvHz5EhEREcK0U6dOobi4GO7u7hrYc4z9v1mzZmHbtm3YuXMnYmJiMGXKFGRlZZU6xyY6OhpxcXEAXn0eoqOjhcvxnZycsHr1amzYsAELFizA7du3ce/ePaxbtw5z587F7NmzhffytGnTkJ6ejpEjRyI8PByxsbH49ddfcefOHQCvxha6du0a7ty5g2fPnpVZXPXr1w8tWrTAmDFjcPXqVRw7dgxff/01pk6dCplMBuDVuY1jx47F2rVr4e7ujuTkZCQnJyv95/SHH35AXl4e+vfvjzNnzuDRo0c4evQo+vbtiwYNGmDFihVCXt7e3hg/fjx+//13PHjwAKGhoQgODgYAODs7QyKR4PDhw3j69GmZQ4aEhITAy8sLM2bMwAcffCDkVHJoA19fXxw9ehRr167F7du3sXjxYoSHh2PatGkAXn2nfPjhhwgPD8euXbtQVFQkxFF0boSFhWHDhg24evUq7t+/j127dmHmzJkYPXo06tSpU5m3SNXVyEFALSsqKqK6devS6NGjKTY2lk6ePEmdO3dWOremoKCAjI2Nafny5ZScnCxcJaDqWLTiHJSSSl4GuXbtWtq9ezfFxMTQnTt3aMKECWRnZ6d0XlRJqs6nevHihdKlqYrjxPPnz1e6fP/58+fCMufPnycDAwNas2YNxcTEkJ+fX40MOXDw4EGSSqUqr6yYO3cuderUSWkaKjinSeHFixeUmZkpPH/96rnBgwfTvn376ObNmxQbG0s///wzmZqaCucEqVLWOU2vv56PHz8mExMTmjp1KsXExNDvv/9O1tbWSvulovdBRdtbXpwePXqQkZGRUq45OTnk7u5Ojo6OFBwcTPHx8XT58uVSQw6sX7+e6tevr/KcuuHDh9OHH35IRES+vr7k7u6uMqcuXbrQnDlzVM7Lz8+nwYMHk4ODA0VHRyu9H0teFeTp6Unt27enS5cu0blz56hp06Y85ACrMYrhRaRSKXXp0kVpeAAiUjkUAP43HEpJf/zxB/Xo0YNMTU3JyMiIOnbsqHS1tMLVq1epX79+wnmWPXr0EM6xfPLkCfXt25fMzMzKHXKAiOjhw4c0YMAAMjY2Jmtra5o9e3apq3ZV5f36cAAPHz4kb29vsrW1JUNDQ3J0dKTp06fTs2fPlNrl5OTQzJkzqX79+iSVSsnFxUVp+5YuXUp2dnYkkUjKHHLg9SuTFQ/FVegKwcHB5OrqSlKplFq2bEn//e9/hXmqhjhQPBT7KyIigtzd3cnCwoKMjIyoefPmtHLlyho7n4noDRpy4Pjx49S8eXOSyWTUpk0bCg0NLfVjtm3bNnJ0dCQ9Pb1SQw6UVNGP5datW6ldu3ZkampKcrmcevfuXeblokTqFU1ivCnVVdmi6b333qOBAweqnHfp0iUCQFevXhWmqVs0va5k0fT06VOaMWMGtWrViszMzMjc3Jxat25Na9asKbM4JVK/aCJSb8gBTRVNFy5cUBoWQSErK4sWLFhALi4uZGhoSFZWVvTBBx8oFcatW7emf/3rXyrXpbiAICUlherWrUurV69W2W7VqlVkY2Oj8gRRdb7ciF5d+jxq1CgyMzMjuVxOPj4+lTrBnDHGdI2EqJLXhLNab9y4cWjYsGGtvZUKY4wxVhVvxDlNjDHGGGPVxUUTY4wxxpgaSg9+w954Q4cOFUZ2ZowxxtgrfE4TY4wxxpga+PAcY4wxxpgatHp4zt/fHwcOHMDt27dhbGyMbt26YdWqVXBzcwMApKamws/PD3/99RcSEhJQr149DB06FMuWLVP7xoHFxcVITEyEubm50i0xGGOMMVZ7EBEyMjJgb2+vdOszMWm1aDp9+jSmTp2Kzp07o7CwEF999RX69euHW7duwdTUFImJiUhMTMSaNWvQokULxMfHY/LkyUhMTMT+/fvVWkdiYiIcHR01vCWMMcYY0wWPHj3S2J0bdOqcpqdPn8LGxganT5/GO++8o7LNvn37MHr0aGRlZam8ievr0tLSYGlpCZ9tpyA1MauwPauYsSEf1RVbclqetlOodUxlfJ2LmPT0uKdebBk5qm+nwqqmICcLv83oh5cvX6p9NKqydOpbRXHvHCsrq3LbyOXyMgumvLw85OX9/w9QRkYGAEBqYsZFk0hkXDSJTlpgWHEjVilSLppExUWT+KQSLpo0QZOn4ujMr19xcTE+//xzdO/eHa1atVLZ5tmzZ1i2bJnKm9Uq+Pv7w8LCQnjwoTnGGGOMiUFniqapU6fixo0bCAoKUjk/PT0dXl5eaNGiRbm395g/fz7S0tKEx6NHjzSUMWOMMcbeJDrRfz1t2jQcPnwYZ86cUXnyVkZGBjw9PWFubo6DBw/C0LDsQxkymQwymUyT6TLGGGPsDaTVnqaVK1fCxsYGP/74I7KysjBz5kzcuXNHqc3GjRvRoEEDXL58GSdPnkRubq6WsmWMMcbYm0yrPU1btmxBZmYmduzYAUdHR/j7+6N3796Ijo6GtbU10tPTsX79epiammLSpElYs2YNUlJSkJubi3r16kFfX1+b6b+xcguLtZ1CraPPJ9mKzkCf96mYCot05kJrxrRGq0WT4nwjHx8fpelr166Fv78/IiMjER8fDwBYs2YNAKBZs2YAgAcPHqBhw4Y1lyxjjDHG3mhaPTxHREqP2NhYAMAnn3wCAOjZs6cwLyQkBADw4sULEFGZBVNeXh7S09OVHowxxhhj1aUzV8+pM+SAOnjIAcYYY4xpgs4UTRUNOaAuHnKAMcYYY5rwjxhyoDJ4yAHGGGOMaYJWi6aVK1diw4YNePbsGSwtLTFz5kysWrUKbm5uQpvc3FzMnj0bv/76KwBgzJgx+Pnnn2Fra1updRkb6vHtP0TyMqdQ2ynUOkaGfCWo2LLzi7SdQq1iJuP3qNj09Pj2SWLKJ83vT61WESWHHNi3bx8yMzPRu3dvPHv2TGgzadIk/Pbbb5g4cSIA4P79++jfvz9SU1O1lTZjjDHG3kASItLa4Btl3VRv3rx58Pf3R1paGqysrFBcXHpcoK+//hrLli2rcB3p6emwsLDA58HhkPENe0XBPU3i09PgDSbfVPlFPJ6YmLinSXw85J248rMzsW10F6SlpUEul2tkHTo95EBERASKi4uFYQYUDycnJ1hZWamMyUMOMMYYY0wTdOYkH1VDDiQnJ0MqlcLS0lKpra2tLZKTk1XG4SEHGGOMMaYJOlM08ZADjDHGGNNlWi2azpw5g0GDBsHU1BRbtmzB/PnzlYYckMlkyM/Ph52dHUxMTODp6YnY2FikpKTAzs5OZUyZTAa5XK70YIwxxhirLq0OOZCZmYmkpCQYGRkhOztbaRgBIsI333wDiUSCmTNnYujQoVi3bh08PDyQlJSErl27ajHzN1sOX8otOkMDnen0ZUylAr5hr+gM+abSoiqqga9RrX5THz58GHFxcThw4ACAV/eVS05ORk5ODmJjYxEeHo6PPvoIP/74IxITE/Hpp5/i6dOnaNKkCd566y1tps4YY4yxN4xWe5o2b94M4NWNeQFg/PjxAICAgAB07NgRAODn54dNmzbhgw8+QF5eHgwMDIR5quTl5SEvL094zlfPMcYYY0wMOjPkAAAcPHgQRIRx48ahWbNmcHJywuLFi7F8+XIkJydj0aJFyM3NxcuXL8uMyVfPMcYYY0wTdPZECkNDQxw4cAB3796FlZUVTExMEBISggEDBkBPr+y0+eo5xhhjjGmCTtywtywdO3ZEdHQ00tLSkJ+fj3r16sHd3R2dOnUqcxm+YS9jjDHGNEEnhhywt7cHAFy6dElpfmZmJqZNm4aWLVvCyckJLi4uuHLlCoYMGaKNdBljjDH2BtNqT9OzZ89ga2uLOXPmYPbs2UhJSUF0dDSsrKzg5OSEoUOHIiYmBt9++y0yMzPx1VdfgYiQm5tb6XXp60mgr8eXd4ohI6dA2ynUOhYmfLdzsckM+V5pYtLeXUprr8w8Hr5FTPk1sD+12tNkZWWF7du3Y/bs2QBeXTXXvn17LFq0CABw8+ZNZGZmYty4cVixYgWmTJmCdu3a4fLly9pMmzHGGGNvIK0WTT179lR59VxgYCAAYNCgQXB1dcWDBw/w8OFDvPvuu4iLi0O/fv3KjMk37GWMMcaYJujs1XMA8P3336NFixZwcHCAVCqFp6cnNm3ahHfeeafMZXjIAcYYY4xpgs4XTRcvXsShQ4cQERGBtWvXYurUqThx4kSZy/CQA4wxxhjTBJ0dciAnJwdfffUVDh48CC8vLwBAmzZtEB0djTVr1qBPnz4ql+MhBxhjjDGmCTo75EBBQQEKCgrw3nvvQSKRCI/t27fj/v372kqZMcYYY28onR5yoGvXrkhNTcXKlSvh4OCAn376CTt27MCYMWMqva6CIoIe36VbFE7WJtpOodbRl/BwGGLjIUbEZajP+1NsL7ILtZ1C7aKv+X4gCZH2Rt8IDQ1Fr169Sk339vZGYGAgkpOTMX/+fPz1119ITU2FgYEB7OzscPfuXUjU/JFJT0+HhYUFZuwNh8zETOxNeCPlFxVrO4Vah4sm8XHRJC4umsTHRZO48rMzsX2sO9LS0iCXyzWyDq32NCmGHAAAiUSCgwcPYujQocJ8Ozs7BAQEAABSUlLg4OCAJUuWlFsw5eXlIS8vT3jOQw4wxhhjTAw6ffVcSTt37oS5uTmGDRtWbjsecoAxxhhjmvCPKZp27NiBTz75BEZGRuW24yEHGGOMMaYJOjvkQElnz57FnTt3sHfv3grb8pADjDHGGNMI0qLTp0/Te++9R/Xr1ycANG/evFJtbt26RQ4ODqSnp0cmJibUqVMnio+PV3sdaWlpBIBCQ0OFaeHh4bR161bKzMykRYsWUWZmpjBv69atFB4eLrRRKNlW0YbjcTyOx/E4HsfjeLoR78svvyQAlJaWRpqi1aLpt99+owkTJtDatWsJAPn4+FBUVJRQFMXFxVGdOnXI0NCQvvrqK4qLi6M//viDUlJS1F6HomjauHGjTr24HI/jcTyOx/E4HscTL15iYmLtLppCQkIIQKmHt7c3ERGNGDGC3N3dydjYmF6+fFmldSiKprS0NJo8eTJNnjy5VJvMzEyyt7en06dPl5p3+vRpsre3V3rBFDgex+N4HI/jcTyOpxvxSv7ea4pWTwRXDDlA/xt24ODBgyAiBAYGori4GP/973/h5eWFHj16oGnTpnB3d8fvv/9ebsy8vDykp6crPQAgKioKHTp0QIcOHRAREaG0zO7du7Fnzx6cPHkSWVlZwvSsrCycPHkSe/bswe7du5WWiYiI4Hgcj+NxPI7H8TieDsXTuKpUWtnZ2ZSVlSU8f/jwIa1fv56OHTtW5eoNAB08eFB4npSURADIxMSE1q1bR1FRUeTv708SiUTp/KTX+fn5qey92rhxo9CmZDdgyX+X7AZ8vUuwZDfg612CHI/jcTyOx/E4HsfTbryNGzfq5uG5vn370ubNm4mI6MWLF2Rra0sODg5kZGREP/74Y9USea1o+vvvvwkAjRo1SqndoEGDaOTIkWXGyc3NpbS0NOHx6NEjlTtx69atNHnyZKVjqESvXrjZs2fT7NmzS3UJhoeH0+TJk5VeMI7H8Tgex+N4HI/jaT9eaGiobh6ei4yMRI8ePQAA+/fvh62tLeLj4/HLL7/gu+++UztOeTfstba2hkQiwZ49e5Ru2Hv9+nUkJCSUGVMmk0Eulys9GGOMMcaqrSqVlrGxsXCF20cffUSLFy8mIqKEhAQyNjZWO86RI0dowYIFdODAAZVDDtSrV4/s7e0pKSlJeHh5eZXqfSpPyavnFP5J3Y0cj+NxPI7H8Tgex9ONw3NVumFvmzZt8Omnn+L9999Hq1atcPToUXTt2hURERHw8vJCcnKyWnEyMzMRFxcHAGjfvj18fHwwY8YMWFlZwcnJCb169cLp06fx008/oVevXjh69Cg+//xzhIaG4u2331ZrHYob9oaGhuLu3bsAgA4dOqBjx45Cm23btsHNzQ0nT57E3LlzYWpqCuDViWirV69G7969cefOHUycOFFYJiIiApGRkRyP43E8jsfxOB7H04F4it97Td6wt0o9Tfv27SNDQ0PS09Ojvn37CtNXrlxJnp6easepaMgBb29vMjY2Jn19fZJIJFS3bl365Zdfyo1Z3jlN/8RLKDkex+N4HI/jcTyOV3G8mhhyoMrjNCUlJVFkZCQVFRUJ0y5dukQxMTFVS+S1E8GJiPbs2UN//PEHXbt2jQ4ePEjNmzenzp07U2FhYZlxyrt6Ljz8nzdYF8fjeByP43E8jsfxKo5X6we3LElV0fS6e/fuEQA6ceJEmW3K6mni26hwPI7H8Tgex+N4tTeeTt1G5f3331f7UaVE1CiaiIisra1py5Ytasctq7tO292IHI/jcTyOx/E4HscTL15N9DSpPeSAhYWF2g91lTfkwOsmT54MiUSC58+fo379+mqvQ0EXRy7leByP43E8jsfxOJ448fbt2wdNq9LVc2I5cOAAjhw5ghYtWmD27NlKV89ZWVlhyZIl+OCDD3D16lWsXr0ajx49gqWlJR49egSZTKbWOhRn0+86fwcmZuYa3qI3gwQSbadQ6+hJeJ+K7WVevrZTqFXkUkNtp1DrFGnv57dWys7MwJi33TR69ZxBVRcsLCxEaGgo7t27h48//hjm5uZITEyEXC6HmZmZWjGsrKywfft24XlAQAACAgLg7e2NzZs349q1awgICMDz589hb28PmUyG6dOnq10wMcYYY4yJpUpFU3x8PDw9PZGQkIC8vDz07dsX5ubmWLVqFfLy8rBlyxa14ihu2AsAEokEBw8exNChQ4X5f/75J/r06YMhQ4bA19cXDRs2hLl5+b1FeXl5yMvLE54rbtjLGGOMMVYdVbqNiq+vLzp16oQXL17A2NhYmP7+++/j5MmToiW3atUqGBgYYMaMGWov4+/vr3R+laOjo2j5MMYYY+zNVaWeprNnz+LChQuQSqVK0xs2bIi///5blMQiIiKwceNGREZGQlKJ8z3mz5+PWbNmCc/T09O5cGKMMcZYtVWpp6m4uBhFRUWlpj9+/LjCw2fqOnv2LJ48eQInJycYGBjAwMAA8fHxmD17Nho2bFjmcnzDXsYYY4xpQpWKpn79+mHDhg3Cc4lEgszMTPj5+WHgwIFqxylvyIExY8Zg8uTJcHR0hKGhIUxMTCCTyfDJJ5/g2LFjVUmbMcYYY6zKqjTkwOPHj9G/f38QEWJjY9GpUyfExsbC2toaZ86cgY2NjVpxyhtywMnJCbt374aNjQ0aN26MnJwcvPXWWygoKMCjR49Qr149tdahGHLg7I3HMDPnXicxaHGUilpLX4+HHBBbfmGxtlOoVfg9Kr7KnHrCKpaZkY4erRw0OuRAlcdpKiwsRFBQEK5du4bMzEx06NABn3zyidKJ4RUJDQ1Fr169Sk339vZGYGBgqenOzs5ISEjAiRMn0Lt3b7XWwUWT+LhoEh//IImPiyZx8XtUfFw0iasmiqYqj9NkYGCA0aNHV2vlFQ05UFJ+fj6mT5+O5cuXo23btmXG5CEHGGOMMaYJVS6aYmNjERISgidPnqC4WPl/dIsWLap2YgqHDx/GyJEjkZ2djfr16+P48eOwtrYus72/vz+WLFki2voZY4wxxoAqHp7btm0bpkyZAmtra9jZ2Sl1MUokEkRGRlY+kTJ6mrKyspCUlIRnz55h27ZtOHXqFC5dulTmeVOqepocHR358JyI+PCc+PjQh/j48Jy4+D0qPj48J66aODxXpavnli9fjhUrViA5ORnR0dGIiooSHpUpmMq7eq6goABffvkl3nrrLbRt2xbDhg1DQUEBACjdeuV1POQAY4wxxjShSofnXrx4gY8++qjaK8/KykLbtm0xfvx4DBs2TGlednY2IiMjsXDhQrRt2xYvXryAr68vEhMTlXqS1GUq04epTL/aOTOAO5rEx7tUfHwTZHEZ6PP+ZLqt0LBK/UCVUqU1fPTRR/jrr7+qvfIePXrgww8/RKNGjQAAKSkpiI6ORkJCAgwMDNC5c2c4OTnByMgIhoaGsLW1RX5+Pt5+++1qr5sxxhhjrDKq1NPk4uKChQsX4uLFi2jdujUMDQ2V5qt7r7jw8HClIQcCAgIQEBAAb29vbNmyBbdv38bOnTvx7Nkz1K1bVxgJvEuXLlVJmzHGGGOsyqp0IriiZ0hlQIkE9+/fr3wiFQw5kJubi+7du6NZs2bYtWtXmXHKOhE8MjaJTwQXCR+eEx/vUvEV8IngouLDc0zXZWako7Obve6N0/TgwQOx8yhXQUEBhg8fDiLC5s2by23LQw4wxhhjTBM0f9ZUNSkKpvj4eBw/frzC6nH+/PlIS0sTHo8ePaqhTBljjDFWm1Wpp6moqAiBgYE4efKkysEtT506pVacM2fO4Ntvv0VERASAV0MOlDw8FxwcjGnTpiE1NRVFRUV49OgR6tatW25MmUwGmUxWuQ1ijDHGGKtAlYomX19fBAYGwsvLC61ataryAF3Pnj2Dra0t5syZg9mzZwtXz1lZWaF+/fr45ptvkJeXhwULFmDp0qV49uwZkpOTYWVlBalUWql1SQ30IDPQ+Y61fwa+lFt0xcV8VpPY+PMuLh7bUnz8qRdXoVTzwwpV6URwa2tr/PLLLxg4cGC1Vl7eDXsXL15c5gnnISEh6Nmzp1rrUNyw98aDFJjzieDi4KJJdFw0MV3HRZP4+FMvroyMdLRuZKt7J4JLpVK4uLhUe+UV3bBXMe/hw4do1KgRoqKi0K5du3Jj8g17GWOMMaYJVeq/nj17NjZu3KiT9yDz9/eHhYWF8HB0dNR2SowxxhirBarU03Tu3DmEhITgzz//RMuWLUsNbnngwAFRkquK+fPnY9asWcJzxThNjDHGGGPVUaWiydLSEu+//77YuYiCr55jjDHGmCZUqWgKCAgQZeUVDTlARPDz8xMGtJw0aRL+/e9/o2nTpqKsnzHGGGNMXVUqmsRS3pADTk5OWLx4MdavX4/PP/8cy5cvR1FREXr27Inz588L96FTl76eHvT1+RJkUejguWz/dBK+NEl0fJEn03X8FhWXQQ186Ks05AAA7N+/H8HBwUhISEB+fr7SvMjISLVilDfkQEBAACwtLVVe/fbBBx9g//79aq1DMeRATPxTmGvoEsQ3DhdNouMRB8THRRPTdfwWFVdGejqaN7TR6JADVep6+e677+Dj4wNbW1tERUWhS5cuqFu3Lu7fv48BAwaoHUcx5ICibjt48CCICIGBgXjw4AHS09MRFRUltCEivPPOO2jQoEGZMfPy8pCenq70YIwxxhirrioVTT/++CO2bt2K77//HlKpFHPnzsXx48cxY8YMpKWliZJYcnIyAMDW1lZpuq2trTBPFR5ygDHGGGOaUKWiKSEhAd26dQMAGBsbIyMjAwAwZswY7NmzR7zsqoBv2MsYY4wxTahS0WRnZ4fU1FQAgJOTEy5evAgAePDggWgDXtrZ2QEAUlJSlKanpKQI81SRyWSQy+VKD8YYY4yx6qrS1XPvvvsuDh06hPbt28PHxwczZ87E/v37ER4ejmHDhomSWKNGjWBnZ4cjR44gMDAQBw8eREpKCvLz89GvX79Kx9OXvHowEfAZtuLjE8FFx+9ScfFbVHx80ay49Gpgh1bp6rni4mIUFxfDwOBVzRUUFIQLFy6gadOmmDRpEqRSqVpxMjMzERcXBwBo37491q1bh169eglDDqxatQoLFy6EnZ0dlixZgt27dyM8PBxFRUWIiYkp94RwBcXVc3cT+Oo5pruK+BdJdPx7JC5+i4qPiyZxZaSnw82pnkavnqvykANiKG/IgcDAQGRnZ8PMzAwWFhbIycnB22+/jR9//BGjRo3CgAEDsHz58grXwUUT+yfgokl8/HskLn6Lio+LJnHVRNFU5cEtX758icuXL+PJkycoLi5Wmjd27Fi1YiiGHChLUVERiAj79+9H7969henGxsY4d+6cymXy8vKQl5cnPOchBxhjjDEmhioVTf/5z3/wySefIDMzE3K5HJIS57hIJBK1i6aKmJubo2vXrli2bBmaN28OW1tb7NmzB2FhYXBxcVG5jL+/P5YsWSLK+hljjDHGFKp0eM7V1RUDBw7EypUrYWJioom8BPfu3cP48eNx5swZ6Ovro0OHDnB1dUVERARiYmJKtVfV0+To6MiH55hO48Nz4uMjH+Lit6j4+PCcuHT28Nzff/+NGTNmaLxgKioqQmBgIBISEiCTyWBra4tBgwbhxo0baNy4scplZDIZZDKZRvNijDHG2JunSkVT//79ER4eXmbhIpZVq1Zh8+bN2LlzJ1q2bInw8HCMGzcOxcXF2LBhQ6ViSSQSpcOIjOkSA35rMh2nxWuGai3+TRKXXg3sT7WLpkOHDgn/9vLywhdffIFbt26hdevWMDQ0VGo7ePBgUZK7cOECOnbsCH19fRARLCwsYGBgAAMDA/j4+IiyDsYYY4wxdahdNA0dOrTUtKVLl5aaJpFIUFRUVK2kFLp164b169fjs88+Q0pKCuRyOfLz8/Htt9+WKtQU+Oo5xhhjjGmC2rdRUQxoWdFDrIIJAObNm4cJEybg8ePHKC4uxvPnz7Fw4UJMnDixzGX4hr2MMcYY04RK3Xvu1KlTaNGihcrem7S0NLRs2RJnz54VLbng4GDs2rULu3fvRmRkJHbu3Ik1a9Zg586dZS7DN+xljDHGmCZU6kTwDRs2YOLEiSov5bOwsMCkSZOwbt069OjRQ5TkvvjiC8ybNw8jR44EALRu3Rrx8fHw9/eHt7e3ymX46jnGGGOMaUKlepquXr0KT0/PMuf369cPERER1U5KITs7G4sWLRKufJNIJFi4cCHu3LmDqVOnirYexhhjjLGKVKqnKSUlpcwTsAHAwMAAT58+rXZSCoMGDcJff/2FX3/9FW5ubrh+/TpmzZqFtLQ0fPTRR6Kth1UOX3osPr70WHz8PhUX700N4PeoqGriM1+poqlBgwa4ceNGmbcwuXbtGurXry9KYgDw/fffY+HChViwYAGePHkCe3t7uLq64vnz5/Dw8BBtPYwxxhhjFanU4bmBAwdi4cKFyM3NLTUvJycHfn5+eO+990RLztzcHBs2bEB8fDxycnIQExOD+/fvY8KECWX+zzwvLw/p6elKD8YYY4yx6qrUvedSUlLQoUMH6OvrY9q0aXBzcwMA3L59G5s2bUJRUREiIyNha2urkWSDg4Px8ccfIyEhAfb29v/X3p3HRVX1fwD/DMsMIAyIbKII7vu+EJqPmgsqmbaYmhaamZqlpraYFVmZmqZZmZUpWKm4pGX+XHJDc00RXBE33BIwNxYXEOb7+8OH+zgwwAAzzACf9+s1r+Hee+6555w7M/fLveeeazDNRx99ZPCBvWcuX+ez50yElz1Mj5fnTI+fU9Nia5oev/WmlZaainpmfvZckR/Ye/HiRYwePRqbN29WfpRUKhWCg4Mxf/581KxZ0ywFBR4+vkWtVuOPP/7IN01+D+xl0GQ6PBiZHoMm0+Pn1LTYmqbHb71plUbQVORnz/n7+2PDhg24desWzp49CxFB3bp1UblyZXOUT3Hx4kVs3boVa9asKTAdhxwgIiIicyhSn6ZHVa5cGW3btkW7du3MGjD9888/GDJkCBo0aACdTocpU6bg0KFDZtseERERkSFFPtNUmm7duoUOHTqgc+fOcHNzQ9++ffHMM88UK0i79yAbdpmme8RLRcbT9KbH0/SmxyueppWt4zff1HgF2bTulMIxvthnmkrDzJkz4efnhxdeeAFJSUmYMGECevTogdq1a1u6aERERFTBWHXQtG7dOrRp0wYLFy6Ep6cnBgwYgIULFxa4DoccICIiInOw6qDp/PnzWLBgAerWrYvNmzdj9OjRGDt2bIEP7J0+fTpcXV2Vl5+fXymWmIiIiMqrIg85UJrUajXatGmDvXv3KvPGjh2LgwcPYt++fQbXyW/IgaPnk+HiwiEHTMFqPzBlGLvfmB77NJkW+zSZnvUefcumtLRUtKzjY11DDpSmqlWr4v79+3nGsLGzy7/YHHKAiIiIzMGqg6YOHTpgz549aNy4MbZu3QoA+PDDDxEbG1vkvO5mZMFGnWXiElZMNvwX3uR0/JfT5DhgqGnZsDlNjmfvTCvjQQW/e+7NN9/ElStXcOPGDaSnp2P79u1YunQpxo0bZ+miERERUQVj1Wea2rZtiwEDBiAyMhJ169aFvb09WrZsiY4dO1q6aERERFTBWPWZJgB48cUXsWLFChw5cgR//PEHbG1t0bFjR6SlpRlMzyEHiIiIyBys+kwTAPTq1Uv5u1mzZggMDIS/vz9WrlyJ4cOH50k/ffp0TJ06tTSLSERERBWA1Z9pys3NzQ316tXD2bNnDS6fPHkyUlJSlNfly5dLuYRERERUHpWpoGnGjBlQqVQ4duwYqlatajCNRqOBVqvVexERERGVlNVfnps0aRL69OmD27dvY968eXB2dkZ2djYGDRpUpHx2X74Bx0qZZiplxcLb400vM4ttamq8Rd603J3sLV2Ecuf6nQeWLkK5cv+O4b7OpmT1QdOVK1cwcOBAJCcno0qVKnB0dETv3r3h6elp6aIRERFRBWL1l+ciIyPRo0cPjBs3Dv/++y8aNWoENze3fNPz7jkiIiIyB6s/0xQZGYnDhw/j4MGDRqXn3XNERERkDlZ9puny5csYN24cli5dCgcHB6PW4d1zREREZA5WfaYpOjoa165dQ6tWrZR52dnZ2LVrF7755htkZGTA1tZWbx0+sJeIiIjMwarPNHXt2hXvv/8+atWqpQRDlSpVQufOnREbG5snYCIiIiIyF6s+0+Ti4oJ27dohKCgIdevWhYige/fu2LlzZ5GfYP7XmVuwd+TtnaYQfSzJ0kUod7Kzzf907oom416GpYtQrrA9Ta+oxzEqmGTeNfs2rDpoAoA+ffroTdesWRPJycnYv38/GjdubKFSERERUUVj1ZfncsvOzsaoUaMgIggKCjKYhkMOEBERkTmUiaDp2LFjcHZ2hkajwahRo7B27Vo0atTIYNrp06fD1dVVefn5+ZVyaYmIiKg8KhNBU/369REbG4sDBw5g9OjRCA0NxcmTJw2m5ZADREREZA5W36cJANRqNerUqQMAaN26NQ4ePIh58+bh+++/z5OWQw4QERGROVj9mabp06ejbdu2cHFxgZeXF/r164f09HRkZPBODiIiIio9KhHrfmR9rVq1MGDAAHTp0gWpqal45513cP78eaxbty7PnXWGpKamwtXVFZqmI6CyVZdCiSuASm6WLkG5U6luE0sXody5c8K4Ry+RkR7wH1WybpKdiYxjC5GSkgKtVmuWbVj95bkuXbpg+fLlmDNnDlxdXdGgQQOcP38erq6uli4aERERVSBWHzQtWrRIb/rs2bOoW7cu3N3dDabPyMjQu3THIQeIiIjIFKy+T9OjdDodxo8fjw4dOqBJE8OXMzjkABEREZlDmQqaxowZg+PHjyMyMjLfNBxygIiIiMzB6i/P7dq1C7NmzcL27dtx9+5dfPfdd6hevXq+6TnkABEREZmD1QdN6enpSExMhIODA+7evQtvb29LF4kyzP9QxIrmThIfgmxyvNuLiEzM6i/PrV+/HmfPnsWaNWsAALdu3UJSUhLu3btn4ZIRERFRRWL14zSpVCqD88PDwzF06NA88w3dPefn58dxmkzJju1och41LF2C8ifprKVLQESlqDTGabL6M00iorwAYO3atRARgwETwLvniIiIyDysPmgqKt49R0REROZg9R3Bi4p3zxEREZE5lLugKbecy3qSnWnhkpQjKqvuBlc2Zd23dAnKH37niSqUnOO8ObtqW33QlJ6ejrNn/9ehMyEhAbGxsXB3d0eNGoV3nk1LSwMAZJ5cYrYyEhERkXVIS0sz2/Nprf7uuaioKHTp0iXP/NDQUERERBS6vk6nw9WrV+Hi4pLvnXjWIOcuv8uXL5ut139FwzY1PbapabE9TY9talplqT1FBGlpafD19YWNjXm6bFv9mabOnTuX6FSbjY1NgSOIWxutVmv1H8yyhm1qemxT02J7mh7b1LTKSnua6wxTjnJ39xwRERGROTBoIiIiIjICgyYrodFoEBYWxuESTIhtanpsU9Nie5oe29S02J76rL4jOBEREZE14JkmIiIiIiMwaCIiIiIyAoMmIiIiIiMwaCIiIiIyAoMmM5g/fz4CAgLg4OCAwMBA/P3338qyH374AZ07d4ZWq4VKpcLt27fzrD9t2jS0b98eTk5OcHNzy7P8yJEjGDRoEPz8/ODo6IiGDRti3rx5ZqyRZZm7PQHg4MGD6Nq1K9zc3FC5cmUEBwfjyJEjZqqR5eXXpjdv3sQbb7yB+vXrw9HRETVq1MDYsWORkpKit/6lS5cQEhICJycneHl54a233kJWVpZemqioKLRq1QoajQZ16tQxagT/sqo02jMjIwNTpkyBv78/NBoNAgICsHjx4lKrY2kraZuOHTsWrVu3hkajQYsWLfLkHxUVhb59+6Jq1aqoVKkSWrRogaVLl5ZG1SzG3G0KAJs3b8Zjjz0GFxcXeHp64tlnn8WFCxfMXLPSw6DJxFasWIEJEyYgLCwMhw8fRvPmzREcHIxr164BAO7evYuePXvivffeyzePzMxM9O/fH6NHjza4PDo6Gl5eXvjll19w4sQJTJkyBZMnT8Y333xjljpZUmm0Z3p6Onr27IkaNWrgwIED2L17N1xcXBAcHIwHDx6YpV6WVFCbXr16FVevXsXs2bNx/PhxREREYNOmTRg+fLiyfnZ2NkJCQpCZmYm9e/diyZIliIiIwIcffqikSUhIQEhICLp06YLY2FiMHz8er7zyCjZv3myJKptVabQnADz//PPYtm0bFi1ahPj4eCxfvhz169cv7eqWipK2aY6XX34ZAwYMMLiNvXv3olmzZvj1119x9OhRDBs2DC+99BLWr19v7upZRGm0aUJCAvr27YsnnngCsbGx2Lx5M65fv45nnnnG3NUrPUIm1a5dOxkzZowynZ2dLb6+vjJ9+nS9dDt27BAAcuvWrXzzCg8PF1dXV6O2+9prr0mXLl2KU2SrVhrtefDgQQEgly5dUuYdPXpUAMiZM2dKXAdrY2yb5li5cqWo1Wp58OCBiIhs2LBBbGxsJCkpSUmzYMEC0Wq1kpGRISIib7/9tjRu3FgvnwEDBkhwcLCpq2NxpdGeGzduFFdXV7lx44YZa2I9StqmjwoLC5PmzZsbtd3evXvLsGHDilVma1cabbpq1Sqxs7OT7OxsZd66detEpVJJZmZmySthBXimyYQyMzMRHR2Nbt26KfNsbGzQrVs37Nu3z6zbTklJgbu7u1m3UdpKqz3r16+PKlWqYNGiRcjMzMS9e/ewaNEiNGzYEAEBASbbjjUoTpumpKRAq9XCzu7hoyr37duHpk2bwtvbW0kTHByM1NRUnDhxQknz6DZy0pj7e1DaSqs9161bhzZt2uDzzz9HtWrVUK9ePUyaNAn37t0zY+0swxRtWlzl8XcUKL02bd26NWxsbBAeHo7s7GykpKTg559/Rrdu3WBvb1/ielgDBk0mdP36dWRnZ+v9+AGAt7c3kpKSzLbdvXv3YsWKFXj11VfNtg1LKK32dHFxQVRUFH755Rc4OjrC2dkZmzZtwsaNG0v8I2xtitqm169fxyeffKL32UpKSjK4fs6ygtKkpqaWqwN9abXn+fPnsXv3bhw/fhxr167Fl19+idWrV+O1114zdZUszhRtWhwrV67EwYMHMWzYsBLlY41Kq01r1qyJP//8E++99x40Gg3c3Nxw5coVrFy5skTltyYMmsq448ePo2/fvggLC0OPHj0sXZwy6d69exg+fDg6dOiA/fv3Y8+ePWjSpAlCQkLK1QG+qFJTUxESEoJGjRrho48+snRxyryStKdOp4NKpcLSpUvRrl079O7dG3PmzMGSJUv4GTXBZ3THjh0YNmwYFi5ciMaNG5uugGVQSdo0KSkJI0aMQGhoKA4ePIidO3dCrVbjueeeg5STh4+Ur3+jLczDwwO2trZITk7Wm5+cnAwfHx+Tb+/kyZPo2rUrXn31Vbz//vsmz9/SSqs9ly1bhgsXLmDfvn2wsbFR5lWuXBm///47Bg4caLJtWZqxbZqWloaePXvCxcUFa9eu1Tu17uPjo3cHY876Octy3g1tQ6vVwtHR0aR1sqTSas+qVauiWrVqcHV1VdI0bNgQIoIrV66gbt26Jq+bpZiiTYti586d6NOnD+bOnYuXXnqpRGW3VqXVpvPnz4erqys+//xzZd4vv/wCPz8/HDhwAI899ljJKmIFeKbJhNRqNVq3bo1t27Yp83Q6HbZt24agoCCTbuvEiRPo0qULQkNDMW3aNJPmbS1Kqz3v3r0LGxsbqFQqZV7OtE6nM9l2rIExbZqamooePXpArVZj3bp1cHBw0MsjKCgIx44dU+5gBIAtW7ZAq9WiUaNGSppHt5GTxtTfA0srrfbs0KEDrl69ivT0dCXN6dOnYWNjg+rVq5uziqXOFG1qrKioKISEhGDmzJnlrnvDo0qrTXN+Sx9la2urbK9csHRP9PImMjJSNBqNREREyMmTJ+XVV18VNzc35c6YxMREiYmJkYULFwoA2bVrl8TExOjdFXPx4kWJiYmRqVOnirOzs8TExEhMTIykpaWJiMixY8fE09NThgwZIomJicrr2rVrFqmzOZVGe8bFxYlGo5HRo0fLyZMn5fjx4zJkyBBxdXWVq1evWqTe5lRQm6akpEhgYKA0bdpUzp49q/f5ysrKEhGRrKwsadKkifTo0UNiY2Nl06ZN4unpKZMnT1a2cf78eXFycpK33npL4uLiZP78+WJrayubNm2yVLXNpjTaMy0tTapXry7PPfecnDhxQnbu3Cl169aVV155xVLVNquStqmIyJkzZyQmJkZGjhwp9erVU773OXckbt++XZycnGTy5Ml6eZTXOxRLo023bdsmKpVKpk6dKqdPn5bo6GgJDg4Wf39/uXv3rqWqblIMmszg66+/lho1aoharZZ27drJ/v37lWVhYWECIM8rPDxcSRMaGmowzY4dOwrMw9/fv3QrWkrM3Z4iIn/++ad06NBBXF1dpXLlyvLEE0/Ivn37SrGWpSu/Ns0ZusHQKyEhQVn/woUL0qtXL3F0dBQPDw+ZOHFinluTd+zYIS1atBC1Wi21atXS2yflTWm0Z1xcnHTr1k0cHR2levXqMmHChHJzIDKkpG3aqVOnAtPk97vQqVOn0q9sKTF3m4qILF++XFq2bCmVKlUST09PeeqppyQuLq6Ua2o+KpFy0juLiIiIyIzYp4mIiIjICAyaiIiIiIzAoImIiIjICAyaiIiIiIzAoImIiIjICAyaiIiIiIzAoImIiIjICAyaiIiIiIzAoImIiIjICAyaiIiIiIzAoImIiIjICAyaiIiIiIzAoImIiIjICAyaiIiIiIzAoImIiIjICAyaiIiIiIzAoImIiIjICHaWLkBpuH//PjIzMy1dDCIiIjIjtVoNBwcHs+Vf7oOm+/fvo2bNmkhKSrJ0UYiIiMiMfHx8kJCQYLbAqdwHTZmZmUhKSsKZhMtwcdECAASC//7x6BtEmTZuec40ci1HruW5ZudZ39jlheX/v/f/LTC2brm3XdK2Ke3lhZVfl9Nm+eSnK2R7ulzTyvJ895n+tC7P8pz1/5t/rumCluf+3OkKXcdwGXLW04nhdFDS5dpOrvmSK5/cbZU7/7zr51O+3PUrZLuSez70p3PXO3f6PMtzrZ97uyhkufLZM2J7ecqez+co9z4xtuz5bft/08alQ6H55DOd53tj3HZ1usLKkftd8kmX0y65t5tfvYq23FA6yVO4/MqSX92M35b+/Jx3XRGnlU9sCfP573SeL2YR8zG6HPjfdHYmkk4uQWZmJoOmktJqtaUWNBU3KCpx0GSg/MWtW3lbnvdgop8+36DIyKApb1AkhSzPWf+/+eeaLmh57jyMDpryOcAWGrzku36u7eWen0/QlO92c+efu37Gbje/Ns1nO8UNmnKvXxpBU2FlKWxbJQ2aTD9dcDpVPkGTsfmWNAAxRdCUe1meH48876ZKZ2zQYaIgKfe0rpS288h0TpOYEzuCExERERmBQRMRERGRERg0ERERERmBQRMRERGRERg0ERERERmBQRMRERGRERg0ERERERmBQRMRERGRERg0ERERERmBQRMRERGRERg0ERERERmBQRMRERGRERg0ERERERmBQRMRERGRERg0ERERERmBQRMRERGRERg0ERERERmBQRMRERGRERg0ERERERmBQRMRERGRERg0ERERERnBztIFKC2pqakQefi3QPnj0bciL8+ZRq7lyLU81+w86xu7vLD8//f+vwXG1i33tkvaNqW9vLDy63LaLJ/8dIVsT5drWlme7z7Tn9blWZ6z/n/zzzVd0PLcnztdoesYLkPOejoxnA5KulzbyTVfcuWTu61y5593/XzKl7t+hWxXcs+H/nTueudOn2d5rvVzbxeFLFc+e0ZsL0/Z8/kc5d4nxpY9v23/b9q4dCg0n3ym83xvjNuuTldYOXK/Sz7pctol93bzq1fRlhtKJ3kKl19Z8qub8dvSn5/zrivitPKJLWE+/53O88UsYj5GlwP/m87OhLmV+6BJRODs7Iy6Nf0sXRQiIiIyI2dn5zz/2JhSuQ+aVCoV0tPTcfnyZWi1WksXp1SlpqbCz8+vQtYdqNj1r8h1Byp2/Sty3YGKXf+KXHfgf/VXqVRm20a5D5pyaLXaCvkhAip23YGKXf+KXHegYte/ItcdqNj1r8h1Nzd2BCciIiIyAoMmIiIiIiOU+6BJo9EgLCwMGo3G0kUpdRW57kDFrn9FrjtQsetfkesOVOz6V+S6A6VTf5WYs5s5ERERUTlR7s80EREREZkCgyYiIiIiIzBoIiIiIjICgyYiIiIiI5TJoGn+/PkICAiAg4MDAgMD8ffffxeYftWqVWjQoAEcHBzQtGlTbNiwQW+5iODDDz9E1apV4ejoiG7duuHMmTPmrEKxFaXuCxcuRMeOHVG5cmVUrlwZ3bp1y5N+6NChUKlUeq+ePXuauxrFVpT6R0RE5Kmbg4ODXpryuu87d+6cp+4qlQohISFKmrKy73ft2oU+ffrA19cXKpUKv/32W6HrREVFoVWrVtBoNKhTpw4iIiLypCnq74ilFLX+a9asQffu3eHp6QmtVougoCBs3rxZL81HH32UZ983aNDAjLUonqLWPSoqyuDnPikpSS9dWdj3Ra27oe+zSqVC48aNlTRlZb9Pnz4dbdu2hYuLC7y8vNCvXz/Ex8cXul5pHOvLXNC0YsUKTJgwAWFhYTh8+DCaN2+O4OBgXLt2zWD6vXv3YtCgQRg+fDhiYmLQr18/9OvXD8ePH1fSfP755/jqq6/w3Xff4cCBA6hUqRKCg4Nx//790qqWUYpa96ioKAwaNAg7duzAvn374Ofnhx49euCff/7RS9ezZ08kJiYqr+XLl5dGdYqsqPUHHo6M+2jdLl68qLe8vO77NWvW6NX7+PHjsLW1Rf/+/fXSlYV9f+fOHTRv3hzz5883Kn1CQgJCQkLQpUsXxMbGYvz48XjllVf0AofifJYspaj137VrF7p3744NGzYgOjoaXbp0QZ8+fRATE6OXrnHjxnr7fvfu3eYofokUte454uPj9erm5eWlLCsr+76odZ83b55enS9fvgx3d/c83/mysN937tyJMWPGYP/+/diyZQsePHiAHj164M6dO/muU2rHeilj2rVrJ2PGjFGms7OzxdfXV6ZPn24w/fPPPy8hISF68wIDA2XkyJEiIqLT6cTHx0dmzZqlLL99+7ZoNBpZvny5GWpQfEWte25ZWVni4uIiS5YsUeaFhoZK3759TV1Usyhq/cPDw8XV1TXf/CrSvp87d664uLhIenq6Mq8s7fscAGTt2rUFpnn77belcePGevMGDBggwcHBynRJ29NSjKm/IY0aNZKpU6cq02FhYdK8eXPTFawUGFP3HTt2CAC5detWvmnK4r4vzn5fu3atqFQquXDhgjKvLO53EZFr164JANm5c2e+aUrrWF+mzjRlZmYiOjoa3bp1U+bZ2NigW7du2Ldvn8F19u3bp5ceAIKDg5X0CQkJSEpK0kvj6uqKwMDAfPO0hOLUPbe7d+/iwYMHcHd315sfFRUFLy8v1K9fH6NHj8aNGzdMWnZTKG7909PT4e/vDz8/P/Tt2xcnTpxQllWkfb9o0SIMHDgQlSpV0ptfFvZ9URX2nTdFe5YlOp0OaWlpeb73Z86cga+vL2rVqoXBgwfj0qVLFiqh6bVo0QJVq1ZF9+7dsWfPHmV+Rdr3ixYtQrdu3eDv7683vyzu95SUFADI8xl+VGkd68tU0HT9+nVkZ2fD29tbb763t3eea9Y5kpKSCkyf816UPC2hOHXP7Z133oGvr6/eh6Znz5746aefsG3bNsycORM7d+5Er169kJ2dbdLyl1Rx6l+/fn0sXrwYv//+O3755RfodDq0b98eV65cAVBx9v3ff/+N48eP45VXXtGbX1b2fVHl951PTU3FvXv3TPJdKktmz56N9PR0PP/888q8wMBAREREYNOmTViwYAESEhLQsWNHpKWlWbCkJVe1alV89913+PXXX/Hrr7/Cz88PnTt3xuHDhwGY5ne0LLh69So2btyY5ztfFve7TqfD+PHj0aFDBzRp0iTfdKV1rLczOiWVaTNmzEBkZCSioqL0OkMPHDhQ+btp06Zo1qwZateujaioKHTt2tUSRTWZoKAgBAUFKdPt27dHw4YN8f333+OTTz6xYMlK16JFi9C0aVO0a9dOb3553vf00LJlyzB16lT8/vvvev16evXqpfzdrFkzBAYGwt/fHytXrsTw4cMtUVSTqF+/PurXr69Mt2/fHufOncPcuXPx888/W7BkpWvJkiVwc3NDv3799OaXxf0+ZswYHD9+3Gr6XpWpM00eHh6wtbVFcnKy3vzk5GT4+PgYXMfHx6fA9DnvRcnTEopT9xyzZ8/GjBkz8Oeff6JZs2YFpq1VqxY8PDxw9uzZEpfZlEpS/xz29vZo2bKlUreKsO/v3LmDyMhIo34QrXXfF1V+33mtVgtHR0eTfJbKgsjISLzyyitYuXJlnssWubm5uaFevXplft8b0q5dO6VeFWHfiwgWL16MF198EWq1usC01r7fX3/9daxfvx47duxA9erVC0xbWsf6MhU0qdVqtG7dGtu2bVPm6XQ6bNu2Te+MwqOCgoL00gPAli1blPQ1a9aEj4+PXprU1FQcOHAg3zwtoTh1Bx7eLfDJJ59g06ZNaNOmTaHbuXLlCm7cuIGqVauapNymUtz6Pyo7OxvHjh1T6lbe9z3w8BbcjIwMDBkypNDtWOu+L6rCvvOm+CxZu+XLl2PYsGFYvny53jAT+UlPT8e5c+fK/L43JDY2VqlXRdj3O3fuxNmzZ436R8la97uI4PXXX8fatWuxfft21KxZs9B1Su1YX6Qu7FYgMjJSNBqNREREyMmTJ+XVV18VNzc3SUpKEhGRF198Ud59910l/Z49e8TOzk5mz54tcXFxEhYWJvb29nLs2DElzYwZM8TNzU1+//13OXr0qPTt21dq1qwp9+7dK/X6FaSodZ8xY4ao1WpZvXq1JCYmKq+0tDQREUlLS5NJkybJvn37JCEhQbZu3SqtWrWSunXryv379y1Sx4IUtf5Tp06VzZs3y7lz5yQ6OloGDhwoDg4OcuLECSVNed33OR5//HEZMGBAnvllad+npaVJTEyMxMTECACZM2eOxMTEyMWLF0VE5N1335UXX3xRSX/+/HlxcnKSt956S+Li4mT+/Plia2srmzZtUtIU1p7WpKj1X7p0qdjZ2cn8+fP1vve3b99W0kycOFGioqIkISFB9uzZI926dRMPDw+5du1aqdevIEWt+9y5c+W3336TM2fOyLFjx2TcuHFiY2MjW7duVdKUlX1f1LrnGDJkiAQGBhrMs6zs99GjR4urq6tERUXpfYbv3r2rpLHUsb7MBU0iIl9//bXUqFFD1Gq1tGvXTvbv368s69Spk4SGhuqlX7lypdSrV0/UarU0btxY/u///k9vuU6nkw8++EC8vb1Fo9FI165dJT4+vjSqUmRFqbu/v78AyPMKCwsTEZG7d+9Kjx49xNPTU+zt7cXf319GjBhhdT8ejypK/cePH6+k9fb2lt69e8vhw4f18iuv+15E5NSpUwJA/vzzzzx5laV9n3Mbee5XTn1DQ0OlU6dOedZp0aKFqNVqqVWrloSHh+fJt6D2tCZFrX+nTp0KTC/ycAiGqlWrilqtlmrVqsmAAQPk7NmzpVsxIxS17jNnzpTatWuLg4ODuLu7S+fOnWX79u158i0L+744n/vbt2+Lo6Oj/PDDDwbzLCv73VC9Aeh9jy11rFf9t4BEREREVIAy1aeJiIiIyFIYNBEREREZgUETERERkREYNBEREREZgUETERERkREYNBEREREZgUETERERkREYNBFVcBcuXIBKpUJsbGyZyrs4IiIi4ObmZjX5GCM+Ph4+Pj5W8yT6zMxMBAQE4NChQ5YuClGpY9BEVMr+/fdfjB49GjVq1IBGo4GPjw+Cg4OxZ88eJY1KpcJvv/1muUKWos6dO0OlUkGlUkGj0aBatWro06cP1qxZY/JtDRgwAKdPny7SOgEBAfjyyy9LnE9xTZ48GW+88QZcXFyUednZ2Zg7dy6aNm0KBwcHVK5cGb169dL7DJVEQECAsk9yXjkPTFWr1Zg0aRLeeecdk2yLqCxh0ERUyp599lnExMRgyZIlOH36NNatW4fOnTvjxo0bli5asWVmZpZo/REjRiAxMRHnzp3Dr7/+ikaNGmHgwIF49dVXTVTChxwdHeHl5WU1+RTm0qVLWL9+PYYOHarMExEMHDgQH3/8McaNG4e4uDhERUXBz88PnTt3Nlmw/fHHHyMxMVF5xcTEKMsGDx6M3bt348SJEybZFlGZUawHwxBRsdy6dUsASFRUVL5pcj8z0N/fX0REzp49K0899ZR4eXlJpUqVpE2bNrJly5Y8606bNk2GDRsmzs7O4ufnJ99//71emgMHDkiLFi1Eo9FI69atZc2aNQJAYmJiREQkKytLXn75ZQkICBAHBwepV6+efPnll3p5hIaGSt++feXTTz+VqlWrSkBAgFF5G9KpUycZN25cnvmLFy8WAHp1vHTpkvTv319cXV2lcuXK8tRTT0lCQoKIiGzevFk0Go3cunVLL5+xY8dKly5dREQkPDxcXF1dlWWFtamh57gZykdE5Ntvv5VatWqJvb291KtXT3766Se95QBk4cKF0q9fP3F0dJQ6derI77//nm+7iIjMmjVL2rRpozcvMjJSAMi6devypH/mmWekSpUqkp6eLiIiYWFh0rx5c1m0aJH4+flJpUqVZPTo0ZKVlSUzZ84Ub29v8fT0lE8//VQvH39/f5k7d26BZevSpYu8//77BaYhKm94pomoFDk7O8PZ2Rm//fYbMjIyDKY5ePAgACA8PByJiYnKdHp6Onr37o1t27YhJiYGPXv2RJ8+fXDp0iW99b/44gu0adMGMTExeO211zB69GjEx8creTz55JNo1KgRoqOj8dFHH2HSpEl66+t0OlSvXh2rVq3CyZMn8eGHH+K9997DypUr9dJt27YN8fHx2LJlC9avX29U3kURGhqKypUrK5fpHjx4gODgYLi4uOCvv/7Cnj174OzsjJ49eyIzMxNdu3aFm5sbfv31VyWP7OxsrFixAoMHDza4jcLadM2aNahevbreWRdD1q5di3HjxmHixIk4fvw4Ro4ciWHDhmHHjh166aZOnYrnn38eR48eRe/evTF48GDcvHkz3zb466+/0KZNG715y5YtQ7169dCnT5886SdOnIgbN25gy5Ytyrxz585h48aN2LRpE5YvX45FixYhJCQEV65cwc6dOzFz5ky8//77OHDgQL7lMKRdu3b466+/irQOUZln6aiNqKJZvXq1VK5cWRwcHKR9+/YyefJkOXLkiF4aALJ27dpC82rcuLF8/fXXyrS/v78MGTJEmdbpdOLl5SULFiwQEZHvv/9eqlSpIvfu3VPSLFiwoNCzQWPGjJFnn31WmQ4NDRVvb2/JyMhQ5hU37/zONImIBAYGSq9evURE5Oeff5b69euLTqdTlmdkZIijo6Ns3rxZRETGjRsnTzzxhLI899knQ2eIcjPUprnPuuTOp3379jJixAi9NP3795fevXsr0wD0zsykp6cLANm4cWO+ZWnevLl8/PHHevMaNGggffv2NZj+5s2bAkBmzpwpIg/PNDk5OUlqaqqSJjg4WAICAiQ7O1uZV79+fZk+fbpendVqtVSqVEl5zZs3T29b8+bNU84wElUUPNNEVMqeffZZXL16FevWrUPPnj0RFRWFVq1aISIiosD10tPTMWnSJDRs2BBubm5wdnZGXFxcnjNNzZo1U/5WqVTw8fHBtWvXAABxcXFo1qwZHBwclDRBQUF5tjV//ny0bt0anp6ecHZ2xg8//JBnO02bNoVarVamjc27KEQEKpUKAHDkyBGcPXsWLi4uyhk7d3d33L9/H+fOnQPwsK9NVFQUrl69CgBYunQpQkJC8r3Tzdg2LUxcXBw6dOigN69Dhw6Ii4vTm/fovqlUqRK0Wq2ybwy5d++eXnvmEBGjyxYQEKDXidzb2xuNGjWCjY2N3rzc5XjrrbcQGxurvF566SW95Y6Ojrh7967R5SAqD+wsXQCiisjBwQHdu3dH9+7d8cEHH+CVV15BWFiYXoff3CZNmoQtW7Zg9uzZqFOnDhwdHfHcc8/l6YRtb2+vN61SqaDT6YwuW2RkJCZNmoQvvvgCQUFBcHFxwaxZs/JcvqlUqZLReRZHdnY2zpw5g7Zt2wJ4GOC0bt0aS5cuzZPW09MTANC2bVvUrl0bkZGRGD16NNauXVtgMGpsm5pKUfeNh4cHbt26pTevXr16eYKxHDnz69WrV+A2jSmHh4cH6tSpk2/Zbt68qbQ7UUXBM01EVqBRo0a4c+eOMm1vb4/s7Gy9NHv27MHQoUPx9NNPo2nTpvDx8cGFCxeKtJ2GDRvi6NGjuH//vjJv//79ebbTvn17vPbaa2jZsiXq1KmjnMkpad5FsWTJEty6dQvPPvssAKBVq1Y4c+YMvLy8UKdOHb2Xq6urst7gwYOxdOlS/PHHH7CxsUFISEi+2zCmTdVqdZ59kVvDhg3z3O6/Z88eNGrUqIi11teyZUucPHlSb97AgQNx5swZ/PHHH3nSf/HFF6hSpQq6d+9eou0a4/jx42jZsqXZt0NkTRg0EZWiGzdu4IknnsAvv/yCo0ePIiEhAatWrcLnn3+Ovn37KukCAgKwbds2JCUlKWca6tatizVr1iA2NhZHjhzBCy+8UKQzSADwwgsvQKVSYcSIETh58iQ2bNiA2bNn66WpW7cuDh06hM2bN+P06dP44IMPlM7oJc07P3fv3kVSUhKuXLmC/fv345133sGoUaMwevRodOnSBcDDYMjDwwN9+/bFX3/9hYSEBERFRWHs2LG4cuWKktfgwYNx+PBhTJs2Dc899xw0Gk2+2zWmTQMCArBr1y78888/uH79usF83nrrLURERGDBggU4c+YM5syZgzVr1pSoIzwABAcHY9++fXpB28CBA/H0008jNDQUixYtwoULF3D06FGMHDkS69atw48//mj2s4DAw07qPXr0MPt2iKwJgyaiUuTs7IzAwEDMnTsX//nPf9CkSRN88MEHGDFiBL755hsl3RdffIEtW7bAz89P+W9+zpw5qFy5Mtq3b48+ffogODgYrVq1KvL2//jjDxw7dgwtW7bElClTMHPmTL00I0eOxDPPPIMBAwYgMDAQN27cwGuvvWaSvPOzcOFCVK1aFbVr18YzzzyDkydPYsWKFfj222+VNE5OTti1axdq1KiBZ555Bg0bNsTw4cNx//59aLVaJV2dOnXQrl07HD16NN+75nIY06Yff/wxLly4gNq1a+d7Oapfv36YN28eZs+ejcaNG+P7779HeHg4OnfubFT989OrVy/Y2dlh69atyjyVSoWVK1fivffew9y5c1G/fn107NgRFy9eRFRUFPr161eibRpj3759SElJwXPPPWf2bRFZE5UUpUchERGVqvnz52PdunXYvHmzpYuiGDBgAJo3b4733nvP0kUhKlXsCE5EZMVGjhyJ27dvIy0tTe8uOEvJzMxE06ZN8eabb1q6KESljmeaiIiIiIzAPk1ERERERmDQRERERGQEBk1ERERERmDQRERERGQEBk1ERERERmDQRERERGQEBk1ERERERmDQRERERGQEBk1ERERERmDQRERERGQEBk1ERERERmDQRERERGQEBk1ERERERmDQRERERGQEBk1ERERERmDQRERERGQEBk1ERERERmDQRERERGQEBk1ERERERmDQRERERGQEBk2Ux9ChQ/HRRx9ZuhhmISJ49dVX4e7uDpVKhdjYWEsXiYiIyggGTf914cIFqz6IRkVFoW/fvqhatSoqVaqEFi1aYOnSpXnSrVq1Cg0aNICDgwOaNm2KDRs2lGo59+3bB1tbW4SEhCjzhg4dCpVKle8rICAAANC5c2eoVCrMmDEjT74hISFQqVR6wVxCQgJeeOEF+Pr6wsHBAdWrV0ffvn1x6tSpfMu3adMmREREYP369UhMTESTJk1MVvfiyql3ZGSk3vwvv/xSaZsc9+7dQ1hYGOrVqweNRgMPDw/0798fJ06cMJj38uXLYWtrizFjxhRYhunTp8PW1hazZs0qtLwPHjzAO++8g6ZNm6JSpUrw9fXFSy+9hKtXr+qlu3nzJgYPHgytVgs3NzcMHz4c6enpheZPZArz589HQEAAHBwcEBgYiL///ltv+Q8//IDOnTtDq9VCpVLh9u3bBvNZv349OnXqBBcXFzg5OaFt27aIiIgoUlmGDh2Kfv36GZX20qVLCAkJgZOTE7y8vPDWW28hKytLWb5mzRp0794dnp6e0Gq1CAoKwubNm/Pkc/nyZbz88svw9fWFWq2Gv78/xo0bhxs3bhhd7qioqALb5tF0JT0+Gfu7EhAQkOcYYuiYYS4MmsqIvXv3olmzZvj1119x9OhRDBs2DC+99BLWr1+vl2bQoEEYPnw4YmJi0K9fP/Tr1w/Hjx8vtXIuWrQIb7zxBnbt2qV82OfNm4fExETlBQDh4eHK9MGDB5X1/fz88vwg/fPPP9i2bRuqVq2qzHvw4AG6d++OlJQUrFmzBvHx8VixYgWaNm1a4Bf83LlzqFq1Ktq3bw8fHx/Y2dnlSZOZmVmCFigeBwcHvP/++3jw4EG+aTIyMtCtWzcsXrwYn376KU6fPo0NGzYgKysLgYGB2L9/f551Fi1ahLfffhvLly/H/fv388178eLFePvtt7F48eJCy3r37l0cPnwYH3zwAQ4fPqy0/1NPPaWXbvDgwThx4gS2bNmC9evXY9euXXj11VcLzZ+opFasWIEJEyYgLCwMhw8fRvPmzREcHIxr164pae7evYuePXvivffeyzefr7/+Gn379kWHDh1w4MABHD16FAMHDsSoUaMwadIkk5c7OzsbISEhyMzMxN69e7FkyRJERETgww8/VNLs2rUL3bt3x4YNGxAdHY0uXbqgT58+iImJUdKcP38ebdq0wZkzZ7B8+XKcPXsW3333HbZt24agoCDcvHnTpOU2xfHJ2N8VAPj444/1jilvvPGGSetTIKkgNm7cKB06dBBXV1dxd3eXkJAQOXv2rLIcgN6rU6dOIiISGhoqffv2lWnTpomXl5e4urrK1KlT5cGDBzJp0iSpXLmyVKtWTRYvXqzklZGRIWPGjBEfHx/RaDRSo0YN+eyzz/ItW0JCggCQX3/9VTp37iyOjo7SrFkz2bt3b4F16t27twwbNkyZfv755yUkJEQvTWBgoIwcObIoTSWhoaESFhZWpHVERNLS0sTZ2VlOnTolAwYMkGnTphlMB0DWrl2bZ36nTp1k9OjRUqVKFdm9e7cyf9q0adKnTx9p3ry5Uq6YmBgBIBcuXDC6fKGhoXr72N/fX9numDFjZNy4cVKlShXp3LmziIhERUVJ27ZtRa1Wi4+Pj7zzzjvy4MEDvfK+/vrrMm7cOHFzcxMvLy/54YcfJD09XYYOHSrOzs5Su3Zt2bBhQ4Hl6tSpkwwbNkyqVKki8+fPV+bPnTtXKaOIyIwZM0SlUklsbKze+tnZ2dKmTRtp1KiR6HQ6Zf758+fF0dFRbt++LYGBgbJ06VKD24+KipJq1apJZmam+Pr6yp49e4xqz0f9/fffAkAuXrwoIiInT54UAHLw4EElzcaNG0WlUsk///xT5PyJiqJdu3YyZswYZTo7O1t8fX1l+vTpedLu2LFDAMitW7f05l+6dEns7e1lwoQJedb56quvBIDs379fmXf8+HEJCQkRFxcXcXZ2lscff1zOnj0rYWFheY4vO3bsMFjuDRs2iI2NjSQlJSnzFixYIFqtVjIyMvKtb6NGjWTq1KnKdM+ePaV69epy9+5dvXSJiYni5OQko0aNUubdv39f3n77balevbqo1WqpXbu2/Pjjj8px6dFXaGhovmXIzRTHp9y/KyIi/v7+MnfuXKPLYWoV5kzTnTt3MGHCBBw6dAjbtm2DjY0Nnn76aeh0OgBQTt1u3boViYmJWLNmjbLu9u3bcfXqVezatQtz5sxBWFgYnnzySVSuXBkHDhzAqFGjMHLkSFy5cgUA8NVXX2HdunVYuXIl4uPjsXTp0jyXWQyZMmUKJk2ahNjYWNSrVw+DBg3SOy2bW0pKCtzd3ZXpffv2oVu3bnppgoODsW/fPqPbqSRWrlyJBg0aoH79+hgyZAgWL14MESlSHmq1GoMHD0Z4eLgyLyIiAi+//LJeOk9PT9jY2GD16tXIzs42Ku958+bh448/RvXq1fOc4VqyZAnUajX27NmD7777Dv/88w969+6Ntm3b4siRI1iwYAEWLVqETz/9VC/PJUuWwMPDA3///TfeeOMNjB49Gv3790f79u1x+PBh9OjRAy+++CLu3r1bYNm0Wi2mTJmCjz/+GHfu3DGYZtmyZejevTuaN2+uN9/GxgZvvvkmTp48iSNHjijzw8PDERISAldXVwwZMgSLFi0ymO+iRYswaNAg2NvbY9CgQfmmK0hKSgpUKhXc3NwAPPwsurm5oU2bNkqabt26wcbGBgcOHChy/kTGyszMRHR0tN5voY2NDbp161ak38LVq1fjwYMHBs8ojRw5Es7Ozli+fDmAh2fD//Of/0Cj0WD79u2Ijo7Gyy+/jKysLEyaNAnPP/88evbsqZwZad++vcFt7tu3D02bNoW3t7cyLzg4GKmpqflegtfpdEhLS1OOBTdv3sTmzZvx2muvwdHRUS+tj48PBg8ejBUrVii/zS+99BKWL1+Or776CnFxcfj+++/h7OwMPz8//PrrrwCA+Ph4JCYmYt68eUa3nymOT7l/V3LMmDEDVapUQcuWLTFr1qwCj5MmZ7FwzcL+/fdfASDHjh0Tkf+d7YmJidFLFxoaKv7+/pKdna3Mq1+/vnTs2FGZzsrKkkqVKsny5ctFROSNN96QJ554Qu+//oLkbPvHH39U5p04cUIASFxcnMF1VqxYIWq1Wo4fP67Ms7e3l2XLlumlmz9/vnh5eRlVjhzFPdPUvn17+fLLL0VE5MGDB+Lh4WHwPyoUcKZp3LhxEhsbKy4uLpKeni47d+4ULy8vefDggd6ZJhGRb775RpycnMTFxUW6dOkiH3/8sZw7d67AMuY+e5Oz3ZYtW+rNe++996R+/fp6+3D+/Pni7OysfBY6deokjz/+uLI853Pw4osvKvMSExMFgOzbty/fMuXU+/79++Lv7y8ff/yxwbI6ODjIuHHjDOZx+PBhASArVqwQkYf/Wfv5+clvv/0mIg8/72q1Ws6fP6+3XkpKijg6Oipnr2JiYsTZ2VnS0tLyLW9u9+7dk1atWskLL7ygzJs2bZrUq1cvT1pPT0/59ttvjc6bqKj++ecfAZDnTP1bb70l7dq1y5M+vzNNo0aNEldX13y306xZM+nVq5eIiEyePFlq1qwpmZmZBtPmXLEozIgRI6RHjx568+7cuSMA8j1jPXPmTKlcubIkJyeLiMj+/fvz/Y0VEZkzZ44AkOTkZImPjxcAsmXLFoNp82ubwpji+GTod0VE5IsvvpAdO3bIkSNHZMGCBeLm5iZvvvlmkcpXEhXmTNOZM2cwaNAg1KpVC1qtVjnzc+nSpULXbdy4MWxs/tdU3t7eaNq0qTJta2uLKlWqKNfLhw4ditjYWNSvXx9jx47Fn3/+qaQdNWoUnJ2dldejmjVrpvyd03/n0WvwOXbs2IFhw4Zh4cKFaNy4sRG1N7/4+Hj8/fffGDRoEADAzs4OAwYMKNZZi+bNm6Nu3bpYvXo1Fi9ejBdffNFg36MxY8YgKSkJS5cuRVBQEFatWoXGjRtjy5YtRd5m69at9abj4uIQFBQElUqlzOvQoQPS09OVM4qA/j7L+Rw8+tnI+Y/R0H7MTaPR4OOPP8bs2bNx/fp1g2nEyDN3W7ZswZ07d9C7d28AgIeHB7p3756nz9Ly5ctRu3Zt5exVixYt4O/vjxUrVgAAli5dqvd5/euvv/TWf/DgAZ5//nmICBYsWGBU2YjKm9jYWHTs2BH29vZGr9OrVy/le1Xc3/Fly5Zh6tSpWLlyJby8vPSWGfNbERsbC1tbW3Tq1KlY2zfEFMengn5XJkyYgM6dO6NZs2YYNWoUvvjiC3z99dfIyMgwRfELVWGCpj59+uDmzZtYuHAhDhw4oFwiMKbTb+4vgkqlMjgv51Jfq1atkJCQgE8++QT37t3D888/j+eeew7Aww5ssbGxyiu/7eQcrHPyzLFz50706dMHc+fOxUsvvaS3zMfHB8nJyXrzkpOT4ePjU2gdS2rRokXIysqCr68v7OzsYGdnhwULFuDXX39FSkpKkfN7+eWXMX/+fKxevTrPpblHubi4oE+fPpg2bRqOHDmCjh075rmEZoxKlSoVeR2g8M9GfvsxP0OGDIG/v7/BOtSrVw9xcXEG18uZX69ePQAP98fNmzfh6Oio7I8NGzZgyZIlemVZtGgRTpw4oaSxs7PDyZMnleDqqaee0vu8Pnq5LeeH7eLFi9iyZQu0Wq2yzMfHJ0+gmJWVhZs3b5bK55EqLg8PD9ja2pb4t7BevXpISUnJc/cW8PC4ce7cOeX7lvsymDF+/PFH5XuVcxdZfr/hOcseFRkZiVdeeQUrV67Uu+xVp04dqFSqAn8rKleuDE9Pz2KVuyCmOD4V9LtiSGBgILKysnDhwgWT1KEwFSJounHjBuLj4/H++++ja9euaNiwIW7duqWXRq1WA4DR/WMKo9VqMWDAACxcuBArVqzAr7/+ips3b8LLywt16tRRXkURFRWFkJAQzJw50+BdSEFBQdi2bZvevC1btiAoKKhEdSlMVlYWfvrpJ3zxxRd6B9gjR47A19dXue5fFC+88AKOHTuGJk2aoFGjRkato1Kp0KBBg3z7BBVFw4YNsW/fPr3/1vbs2QMXFxdUr169xPnnx8bGBtOnT8eCBQvy/AgMHDgQW7du1eu3BDwMyObOnYtGjRqhefPmuHHjBn7//XdERkbq7Y+YmBjcunVLOfN57NgxHDp0CFFRUXrpoqKisG/fPpw6dQouLi56n9ecH9mcH7YzZ85g69atqFKlil6ZgoKCcPv2bURHRyvztm/fDp1Oh8DAQDO0HNFDarUarVu31vst1Ol0yp1jxnr22Wdhb2+PL774Is+y7777Dnfu3FHOrDdr1gx//fVXvne/qtXqPMeWatWqKd8rf39/AA+/N8eOHdP7hyMncHj0d3D58uUYNmwYli9frje8CwBUqVIF3bt3x7fffot79+7pLcs5Mz9gwACoVCo0bdoUOp0OO3fuzLfcgHHHRVMcnwr7XTEkNjYWNjY2ec60mU2pXQi0oOzsbKlSpYoMGTJEzpw5I9u2bZO2bdvqXfd98OCBODo6yqeffipJSUly+/ZtETF8LTqnD8qjHu3R/8UXX8iyZcskLi5O4uPjZfjw4eLj46PXL+pRhvpT3bp1S+8ui+3bt4uTk5NMnjxZEhMTldeNGzeUdfbs2SN2dnYye/ZsiYuLk7CwMLG3t1f6bRmrqH2a1q5dK2q1WmmzR7399tvSpk0bvXkopE9Tjlu3bkl6eroynfvuuaeeekpWrVolJ06ckDNnzsiPP/4olSpVUvoEGZJfn6bc+/PKlSvi5OQkY8aMkbi4OPntt9/Ew8NDr10K+xwUVt+C8unYsaM4ODjolfXevXsSGBgofn5+snLlSrl48aL8/fff0q9fP6lUqZLSb2ru3LlStWpVg33qnn/+eXnuuedERGTcuHESGBhosEzt2rWTSZMmGVyWmZkpTz31lFSvXl1iY2P1Po+P3uHTs2dPadmypRw4cEB2794tdevWlUGDBuXbDkSmEhkZKRqNRiIiIuTkyZPy6quvipubm95daYmJiRITEyMLFy4UALJr1y6JiYnR+02dO3eu2NjYyHvvvSdxcXFy9uxZ+eKLL0Sj0cjEiROVdNevX5cqVarIM888IwcPHpTTp0/LTz/9JKdOnRKRh338atSoIadOnZJ///03375PWVlZ0qRJE+nRo4fExsbKpk2bxNPTUyZPnqykWbp0qdjZ2cn8+fP1vnuP/v6ePn1aPDw8pGPHjrJz5065dOmSbNy4UZo0aSJ169bVq+PQoUPFz89P1q5dK+fPn5cdO3YofSOvXLkiKpVKIiIi5Nq1a/n2dTTF8cmY35W9e/fK3LlzJTY2Vs6dOye//PKLeHp6yksvvVTIJ8J0KkTQJCKyZcsWadiwoWg0GmnWrJlERUXlOZgtXLhQ/Pz8xMbGJs+QA48q7GD5ww8/SIsWLaRSpUqi1Wqla9eucvjw4XzLZkzQlPt2+ZxXTjlzrFy5UurVqydqtVoaN24s//d//1eEVhJlW0UJmp588knp3bu3wWUHDhwQAHLkyBFlnrFBU26PBk3//vuvjB07Vpo0aSLOzs7i4uIiTZs2ldmzZ+cbnIoYHzSJGDfkgLmCpr179+oNi5Djzp07MmXKFKlTp47Y29uLu7u7PPvss3qBcdOmTeW1114zuK2cDprJyclSpUoV+fzzzw2mmzlzpnh5eRn8cTd0K3LO69GO/zdu3JBBgwaJs7OzaLVaGTZsWJE6mBOVxNdffy01atQQtVot7dq10xseQEQMDgUAQMLDw/XS/f7779KxY0epVKmSODg4SOvWrfWGmMlx5MgR6dGjh3JzSseOHZUbU65duybdu3cXZ2fnAoccEBG5cOGC9OrVSxwdHcXDw0MmTpyY53fHULlzDwdw4cIFCQ0NFW9vb7G3txc/Pz9544035Pr163rp7t27J2+++aZUrVpV1Gq11KlTR69+H3/8sfj4+IhKpcp3yAFTHJ+M+V2Jjo6WwMBAcXV1FQcHB2nYsKF89tlncv/+/Xzb09RUIkW8J5zKvaFDhyIgIKDcPkqFiIioOCpEnyYiIiKikmLQRERERGSEvIPfUIXXr1+/PCOwEhERVXTs00RERERkBF6eIyIiIjICgyYiIiIiI1i0T9P06dOxZs0anDp1Co6Ojmjfvj1mzpyJ+vXrA3j4tOawsDD8+eefuHTpEjw9PdGvXz988skncHV1NWobOp0OV69ehYuLi95zxIiIiKj8EBGkpaXB19dX73mxpmTRoGnnzp0YM2YM2rZti6ysLLz33nvo0aMHTp48iUqVKuHq1au4evUqZs+ejUaNGuHixYsYNWoUrl69itWrVxu1jatXr8LPz8/MNSEiIiJrcPnyZbM97sqqOoL/+++/8PLyws6dO/Gf//zHYJpVq1ZhyJAhuHPnDuzsCo/5UlJS4ObmhsvxsdC6uJi6yBWTxtnSJSAq3P3bli5B+aLizdYmZ+9g6RKUK6lpafCr1QC3b982+mpUUVnVtyAlJQUA4O7uXmAarVabb8CUkZGBjIwMZTotLQ0AoHVxgVbLoMkkNGxHKgPUpnn4Nv0XgybTs3e0dAnKJXN2xbGajuA6nQ7jx49Hhw4d0KRJE4Nprl+/jk8++cTgE5RzTJ8+Ha6ursqLl+aIiIjIFKzm8tzo0aOxceNG7N692+C1yNTUVHTv3h3u7u5Yt24d7O3tDeaT+0xTamoq/Pz8kHL1HM80mQrPNFFZcP+WpUtQvvBMk+nxTJNJpaamwtWzmnJFyhys4lvw+uuvY/369di1a5fBgCktLQ09e/aEi4sL1q5dm2/ABAAajQYajcacxSUiIqIKyKKX5z777DN4eXnh22+/xZ07d/Dmm28iPj5eL828efNQrVo1/P3339i2bRvu379vodISERFRRWbRM03fffcd0tPTsXjxYvj5+WH69Ono2rUrYmNj4eHhgdTUVMydOxeVKlXCyJEjMXv2bCQnJ+P+/fvw9PSEra2t8RuTrIcvIqoYdOwIblK2VnFhonzR8ZhkUqXQnhbt05RfD/d3330X06dPR1RUFLp06WIwTUJCAgICAgrdRmpqKlxdXZHyTzz7NJmKQ2VLl4CocHevW7oE5Ystuz2YnG3+XU2o6FJTU+Hq7W/WPk0WvTwnInqvM2fOAAAGDx4MAOjcubOybMeOHQCAW7duQUTyDZgyMjKQmpqq9yIiIiIqqTI15IAxOOQAERERmYPVBE1jxozB8ePHERkZWaJ8Jk+ejJSUFOV1+fJlE5WQiIiIKjKr6NlX2JADRcEhB4iIiMgcrH7Igfv372PMmDF46qmnAAAvvvgikpOTLVFcIiIiqsAsGjQ9OuTAqlWrkJ6ejq5du+L69f/d9TJy5Ej8+uuvGDFiBADg/PnzCA4Oxs2bNy1VbCIiIqqArHrIgZSUFLi7u0On0+VJ8/777+OTTz4pdBsccsAMOOQAlQUccsC0OOSA6XHIAZOq8EMOREdHQ6fTKcMM5Lxq1KgBd3d3g3lyyAEiIiIyB6u5e87QkANJSUlQq9Vwc3PTS+vt7Y2kpCSD+XDIASIiIjIHqwmaOOQAERERWTOLBk27du1Cnz59UKlSJXz33XeYPHmy3pADGo0GmZmZ8PHxgZOTE3r27IkzZ84gOTkZPj4+BvPUaDTQarV6LyIiIqKSsmjQlJ6ejsTERDg4OAB4eNkth4hgxowZUKlUePPNNxETEwN/f3906tQJly5dQlBQkKWKTURERBWQRYOm9evX4+zZs1izZg2Ah8+VS0pKwr1793DmzBkcOnQI/fv3x7fffourV6/ilVdewb///ovatWvjscces2TRiYiIqIKxyiEHwsPD0bp1azRr1gwnTpzA/PnzsXz5cmRkZECn0+Gpp57CihUrDK6bkZGBjIwMZTo1NRV+fn4ccsCUOOQAlQUccsC0OOSA6XHIAZOqUEMOAMDatWshIhg6dCgaNGiAGjVq4KOPPsKnn36KpKQkfPjhh7h//z5u376db568e46IiIjMwWrunsvN3t4ea9aswenTp+Hu7g4nJyfs2LEDvXr1go1N/sXm3XNERERkDlbxwN78tG7dGrGxsUhJSUFmZiY8PT0RGBiINm3a5LsOH9hLRERE5mAVQw74+voCAA4cOKC3PD09Ha+//joaN26MGjVqoE6dOjh48CD69u1rieISERFRBWbRM03Xr1+Ht7c3Jk2ahIkTJyI5ORmxsbFwd3dHjRo10K9fP8TFxWHWrFlIT0/He++9BxHB/fv3LVlsIqKKR7IsXYJyiB3ByxqL3j0XFRWFLl265JkfGhqKiIgIVK1aFXfv3sW9e/dQtWpVvPTSS1i/fj1CQkLw6aefGrUNPrDXDHj3HJUFvHvOtGxsLV2C8sfO0dIlKFfK/d1znTt3Nnj3XEREBACgT58+qFevHhISEnDhwgU88cQTOHv2LHr06JFvnnxgLxEREZmD1d49BwBff/01GjVqhOrVq0OtVqNnz56YP38+/vOf/+S7DoccICIiInOw+qBp//79WLduHaKjo/HFF19gzJgx2Lp1a77rcMgBIiIiMgerHXLg3r17eO+997B27VqEhIQAAJo1a4bY2FjMnj0b3bp1M7gehxwgIiIic7DaIQcePHiABw8e4Mknn4RKpVJeixYtwvnz5y1VZCIiIqqgrHrIgaCgINy8eROfffYZqlevju+//x6LFy/Giy++aMliE5mejrdzmxzb1LR495zpZT+wdAnKl2zzf+etesiBpKQkTJ48GX/++Sdu3rwJOzs7+Pj44PTp0/k+7Dc3DjlgBhxywPR4gDc9DjlgWnbs9mByKqvtIVMmpaamwdW3tlmHHLDoHssZcgAAVCoV1q5di379+inLfXx8EB4eDgBITk5G9erVMXXq1AIDpoyMDGRkZCjTHHKAiIiITMGq75571JIlS+Di4oJnnnmmwHQccoCIiIjMocwETYsXL8bgwYPh4OBQYDoOOUBERETmUCYuqP7111+Ij4/HihUrCk3LIQeIiIjILMSCdu7cKU8++aRUrVpVAMi7776bJ83JkyelevXqYmNjI05OTtKmTRu5ePGi0dtISUkRAHL16lWZOHGiTJw4UdLT0/XSHDp0SEaNGiU//PBDnvV/+OEHGTVqlBw6dEhvfnp6OvNjfsyP+TE/5sf8rCS/nON9SkpKnrxMxaKX5x4dcgCAMuTApUuXAADnzp1Dhw4dkJycjHfffRdHjx7FBx98UOglOiIiIiKTM1s4ZoQdO3YIgDyv0NBQEREZMGCABAYGiqOjo9y+fbtY28iJPN955x1JT0+X9PR0+fDDD5Xo9NChQ0qE++jfIg+j3JwI99G/H82D+TE/5sf8mB/zY36Wzy8qKsrsZ5osOk7To3IPOaDT6eDq6oq3334bu3fvRkxMDGrWrInJkyfrDUuQm6EhB/z8/HD16lVUrVoVAHDnzh18/vnn6Nq1K+Lj4zFixAglfXR0NA4fPgwAaNWqFVq3bq0sW7hwIerXr49t27bh7bffRqVKlZgf82N+zI/5MT/mZwX5xcbGYty4cWYdp6lYZ5ru3r0rd+7cUaYvXLggc+fOlc2bNxc7egMga9euVaYTExMFgDg5OcmcOXMkJiZGpk+fLiqVSqKiovLNJywszODZq9yR586dO8XX1zfP9VURkVGjRsmoUaPyzE9PTxdfX1/ZuXNnnmXMj/kxP+bH/Jgf87NcflevXrXOPk19+/bFTz/9BAC4ffs2AgMD8cUXX6Bv375YsGCBSYI5nU6nbOvNN99EixYt8O677+LJJ5/Ed999l+96+Q05EBMTo6SJjo5GfHw8Tp8+jc8//xx37txRli1cuBCvvPIKXnnlFSxcuFCZnxPNnj59GvHx8YiOjmZ+zI/5MT/mx/yYn5XkN2/ePJhdcSKtKlWqyPHjx0VEZOHChdKsWTPJzs6WlStXSoMGDYzOp6C75zIyMkSlUuU5YxQQECDt27c3ehs5fZrmzZsnhw4dynPd9NFroo9eNxX53zXW3NdNRf53jZX5MT/mx/yYH/NjfpbPrzTONBUraHJ0dFRu++/fv7989NFHIiJy6dIlcXR0NDqfDRs2yJQpU2TNmjUGhxzw9PQUX19fSUxMVF4hISEyaNAgo7fx6C2I1nQakfkxP+bH/Jgf82N+psvPaoccqFOnDn777TdcvnwZmzdvRo8ePQAA165dK1Lnq44dO+K5555DzZo1AeQdcqBx48ZITEzEH3/8gfT0dKxevRqbNm3Ca6+9VuQyx8TEoFWrVmjVqpXeqT0AWLZsGZYvX45t27bpnSq8c+cOtm3bhuXLl2PZsmV660RHRzM/5sf8mB/zY37Mz4ryM7viRFqrVq0Se3t7sbGxke7duyvzP/vsM+nZs6fR+RQ25EBoaKg4OjqKra2tqFQqqVKlivz0008F5nn//n1JSUlRXpcvX1Yuz+WwhlsjmR/zY37Mj/kxP+ZnuvzmzZtnnZfnRB7e3Xb48GHJzs5W5h04cEDi4uKKV5Bcd8+JiCxfvlx+//13OXr0qKxdu1YaNmwobdu2laysrHzzMfbuuR9+KF8joTI/5sf8mB/zY34VOb/SGKep2M+e8/HxgY+Pj968du3aFTc7gwYOHKj83bRpUzRr1gy1a9dGVFQUunbtanCdyZMnY8KECcp0zjhNRERERCVibHT19NNPG/0qDhg402SIh4eHfPfdd0bn++jdcznK0ulG5sf8mB/zY37Mj/lZx+U5o0cEHzZsmNGBWHh4uFHpdu3ahVmzZiE6OhqJiYl49913MX36dINpR40ahe+//x4qlQq//fYbnnrqKaO2kZqaCldXV0RFReH06dMArGPkUubH/Jgf82N+zI/5mS6/nOO9OUcEt+hjVNasWYMNGzagUaNGmDhxIoYNG4axY8fC3d0d7u7umDp1Kp599lkcOXIEn3/+OS5fvgw3NzdcvnwZGo3GqG3kNKItAJV5q1Nh6CxdACIjFLvvARn0wNIFKIfUli5AOSMAMgGzBk3F/l3JyspCVFQUzp07hxdeeAEuLi64evUqtFotnJ2djcrD3d0dixYtUqbDw8MRHh6O0NBQLFiwAEePHkV4eDhu3LgBX19faDQavPHGG0YHTERERESmUqyg6eLFi+jZsycuXbqEjIwMdO/eHS4uLpg5cyYyMjIKfMzJozp37oycE125H9gLABs3bkS3bt3Qt29fjBs3DgEBAXBxcSkwT0MP7CUiIiIqqWINbjlu3Di0adMGt27dgqOjozL/6aefxrZt20xWuJkzZ8LOzg5jx441ep3p06fD1dVVefHOOSIiIjKFYp1p+uuvv7B3716o1fpXZAMCAvDPP/+YpGDR0dGYN28eDh8+DJXK+N5IHHKAiIiIzKFYZ5p0Oh2ys7PzzL9y5Uqhl8+M9ddff+HatWuoUaMG7OzsYGdnh4sXL2LixIkICAjIdz2NRgOtVqv3IiIiIiqpYgVNPXr0wJdffqlMq1QqpKenIywsDL179zY6n127dqFPnz7w9fUFABw4cEBZ9uKLL2LUqFHw8/ODvb09nJycoNFoMHjwYGzevLk4xSYiIiIqtmINOXDlyhUEBwdDRHDmzBm0adMGZ86cgYeHB3bt2gUvLy+j8iloyIEaNWpg2bJl8PLyQq1atXDv3j089thjePDgAS5fvgxPT0+jtpEz5IADOOSAqbhaugDlULH+e6ECVbJ0AcqZFEsXoByytXQByhkdgGSYd8iBYo/TlJWVhcjISBw9ehTp6elo1aoVBg8erNcxvDBRUVHo0qVLnvmhoaGIiIjIM9/f3x+XLl3C1q1b832MSm4MmkyPQZPpMWgyPQZNpsWgyfQYNJmWVQdNpmZoyIFHZWZm4quvvsKnn36Ks2fPwsPDw2A6Q0MO+Pn5MWgyIQZNpsegyfQYNJkWgybTY9BkWqURNBV7cMszZ85gx44duHbtGnQ6/TGiP/zwwxIXLMf69esxcOBA3L17F1WrVsWWLVvyDZiAh0MOTJ061WTbJyIiIgKKeaZp4cKFGD16NDw8PODj46M3JIBKpVKeCVOkguRzpunOnTtITEzE9evXsXDhQmzfvh0HDhzIt98UzzSZH880mR7PNJkezzSZFs80mR7PNJlWaZxpKtZv9aeffopp06YhKSkJsbGxiImJUV5FCZgKunvuwYMHeOedd/DYY4+hefPmeOaZZ/DgwcOnHz366JXcOOQAERERmUOxLs/dunUL/fv3L/HG79y5g+bNm+Pll1/GM888o7fs7t27OHz4MD744AM0b94ct27dwrhx43D16lW9M0nGegCeaTKVa5YuQDnEM02mxzY1LT6w1/R4TDKt0uigXazflf79++PPP/8s8cY7duyI5557DjVr1gQAJCcnIzY2FpcuXYKdnR3atm2LGjVqwMHBAfb29vD29kZmZiYef/zxEm+biIiIqCiKdaapTp06+OCDD7B//340bdoU9vb2esuNfVbcoUOH9IYcCA8PR3h4OEJDQ/Hdd9/h1KlTWLJkCa5fv44qVaooI4G3a9euOMUmIiIiKrZidQTPOTNkMEOVCufPny96QQoZcuD+/fvo0KEDGjRogKVLl+abT34dwW3BU6Gmois8CRURLyWZHtvUtHh5zvR4TDIt+e/L6oYcSEhIMHU5CvTgwQM8//zzEBEsWLCgwLQccoCIiIjMwer/GcsJmC5evIgtW7YUGj1OnjwZKSkpyuvy5culVFIiIiIqz4p1pik7OxsRERHYtm2bwcEtt2/fblQ+u3btwqxZsxAdHQ3g4ZADj16eW7lyJV5//XXcvHkT2dnZuHz5MqpUqVJgnhqNBhqNpmgVIiIiIipEsYKmcePGISIiAiEhIWjSpIne4JZFcf36dXh7e2PSpEmYOHGicvecu7s7qlatihkzZiAjIwNTpkzBxx9/jOvXryMpKQnu7u5Qq9XF2iaVnFU8d6ecybJ0AYiIyrjSODYVqyO4h4cHfvrpJ/Tu3btEGy/ogb0fffRRvh3Od+zYgc6dOxu1jZwH9rIjuOlkW7oA5RADUaKKh8ck08r5HbW6juBqtRp16tQp8cY7d+6MnJjN0N1zOcsuXLiAmjVrIiYmBi1atCgwT0N3zxERERGVVLE6gk+cOBHz5s1DMU5Smd306dPh6uqqvPz8/CxdJCIiIioHinWmaffu3dixYwc2btyIxo0b5xnccs2aNSYpXHFMnjwZEyZMUKZzxmkiIiIiKoliBU1ubm54+umnTV0Wk+Ddc0RERGQOxQqawsPDTbLxwoYcEBGEhYUpA1qOHDkSv/zyC+rWrWuS7RMREREZy6KDWz465ACg/8BeAPjoo48wd+5cjBo1CsDD8aE6d+6MCxcuWKrIREREVEEVa8gBAFi9ejVWrlyJS5cuITMzU2/Z4cOHjcqjoCEHwsPD4ebmZvDut2effRarV682ahsccsD0OOSA6VnfLRVEZG48JplWaQw5UKwzTV999RWGDRsGb29vxMTEoF27dqhSpQrOnz+PXr16GZ1PzpADOXHb2rVrISKIiIhAQkICUlNTERMTo6QREfznP/9BtWrV8s0zIyMDqampei8iIiKikipW0PTtt9/ihx9+wNdffw21Wo23334bW7ZswdixY5GSkmKSgiUlJQEAvL299eZ7e3srywzhkANERERkDsUKmi5duoT27dsDABwdHZGWlgYAePHFF7F8+XLTla4Y+MBeIiIiModiBU0+Pj64efMmAKBGjRrYv38/ACAhIcFkA176+PgAeNg5/FHJycnKMkM0Gg20Wq3ei4iIiKikihU0PfHEE1i3bh0AYNiwYXjzzTfRvXt3DBgwwGTjN9WsWRM+Pj7YsGEDxo8fD39/fzg4OOCvv/6Cl5eXSbZBREREZKxi3T2n0+mg0+lgZ/dwmKfIyEjs3bsXdevWxciRI6FWq43KJz09HWfPngUAtGzZEnPmzEGXLl3g7u6OGjVqYObMmfjggw/g4+ODqVOnYtmyZTh06BCys7MRFxdXYIfwHLx7zvR495zp8e45ooqHxyTTKo2754o95IApFDTkQEREBO7evQtnZ2e4urri3r17ePzxx/Htt99i0KBB6NWrFz799NNCt8GgyfQYNJkegyaiiofHJNMqjaCpWCOCA8Dt27fx999/49q1a9DpdHrLXnrpJaPyyBlyID/Z2dkQEaxevRpdu3ZV5js6OmL37t0G18nIyEBGRoYyzSEHiIiIyBSKdabpjz/+wODBg5Geng6tVguV6n/xskqlUjqJm0L79u2hVquxbNkyeHt7Y/ny5QgNDUWdOnUQHx+fJ/1HH32EqVOn5pnPM02mwzNNpsczTUQVD49JpmW1l+fq1auH3r1747PPPoOTk5M5yqU4d+4cXn75ZezatQu2trZo1aoV6tWrh+joaMTFxeVJb+hMk5+fH4MmE2LQZHoMmogqHh6TTMtqL8/9888/GDt2rNkDpuzsbERERODSpUvQaDTw9vZGnz59cPz4cdSqVcvgOhqNBhqNxqzlIiIiooqnWEFTcHAwDh06lG/gYiozZ87EggULsGTJEjRu3BiHDh3C0KFDodPp8OWXX5p120RERESPMjpoyhmXCQBCQkLw1ltv4eTJk2jatCns7e310j711FMmKdzevXvRunVr2NraQkTg6uoKOzs72NnZYdiwYSbZBhEREZExjO7TZGNj3DiYKpUK2dmm6fXy2WefYe7cuXB0dERycjK0Wi3u3LmDefPmYcSIEQbXYZ8m82OfJtNjnyaiiofHJNMqjT5NRo8InjOgZWEvUwVMAPDuu+9i+PDhuHLlCnQ6HW7cuIEPPvgg34AJ4AN7iYiIyDyK9BiV7du3o1GjRgbHPkpJSUHjxo3x119/maxwK1euxNKlS7Fs2TIcPnwYS5YswezZs7FkyZJ81+EDe4mIiMgcijTkwFNPPYUuXbrgzTffNLj8q6++wo4dO7B27VqTFM7Pzw/vvvsuxowZo8z79NNP8csvv+DUqVNG5cERwU2Pl+dMj5fniCoeHpNMy+rGafL398emTZvQsGFDg8tPnTqFHj164NKlSyYpXJUqVQDA4GCZr732GubPn19oHgyaTI9Bk+kxaCKqeHhMMi2rG6cpOTk5z51yepnZ2eHff/8tcaFy9OnTB3/++Sd+/vln1K9fH8eOHcOECROQkpKC/v37FykvbxTxWiRRKUq3dAHKIfP8ZFZcusKTEFmUDsBVM2+jSEFTtWrVcPz4cdSpU8fg8qNHj6Jq1aomKRgAfP311/jggw8wZcoUXLt2Db6+vqhXrx5u3LiBTp06mWw7RERERIUp0smX3r1744MPPsD9+/fzLLt37x7CwsLw5JNPmqxwLi4u+PLLL3Hx4kXcu3cPcXFxOH/+PIYPH673vLtHZWRkIDU1Ve9FREREVFJF6tOUnJyMVq1awdbWFq+//jrq168P4GFfpvnz5yM7OxuHDx+Gt7e3WQq7cuVKvPDCC7h06RJ8fX0Npsnvgb2+4OU5sl68PGd6vDxnWrw8R9Yu5/Kc1XQEB4CLFy9i9OjR2Lx5M3JWValUCA4Oxvz581GzZk2zFBR4+PgWtVqNP/74I980+Q1uyaCJrBmDJtNj0GRaDJrI2pVG0FTkZ8/5+/tjw4YNuHXrFs6ePQsRQd26dVG5cmVzlE9x8eJFbN26FWvWrCkwHR/YS0REROZQ7JMvlStXRtu2bdGuXTuzBkz//PMPhgwZggYNGkCn02HKlCk4dOiQ2bZHREREZEiRzzSVplu3bqFDhw7o3Lkz3Nzc0LdvXzzzzDPFCtLiLp+EVutihlJWQA5uli5B+aPLsnQJyp/0JEuXoHxRO1u6BOWPja2lS1CupKamwbVafbNuw6q7+cycORN+fn544YUXkJSUhAkTJqBHjx6oXbu2pYtGREREFYxVB03r1q1DmzZtsHDhQnh6emLAgAFYuHBhgetwyAEiIiIyB6sOms6fP48FCxagbt262Lx5M0aPHo2xY8cW+MDe6dOnw9XVVXn5+fmVYomJiIiovCrykAOlSa1Wo02bNti7d68yb+zYsTh48CD27dtncJ38hhxIYZ8m02GfJtNjnybTY58m02KfJtNjnyaTyunTZFVDDpSmqlWr4v79+3lG/7azy7/YHHKAiIiIzMGqL8916NABN27cQOPGjZGYmIjExESMGDECLVu2tHTRiIiIqIKx6qDpzTffxJUrV3Djxg2kp6dj+/btWLp0KcaNG2fpohEREVEFY9WX59q2bYsBAwYgMjISdevWhb29PVq2bImOHTtaumhERERUwVj1mSYAePHFF7FixQocOXIEf/zxB2xtbdGxY0ekpaUZTM8hB4iIiMgcrPpMEwD06tVL+btZs2YIDAyEv78/Vq5cieHDh+dJP336dEydOrU0i0hEREQVgNWfacrNzc0N9erVw9mzZw0unzx5MlJSUpTX5cuXS7mEREREVB6VqaBpxowZUKlUOHbsGKpWrWowjUajgVar1XsRERERlZTVX56bNGkS+vTpg9u3b2PevHlwdnZGdnY2Bg0aZOmiERERUQVi9UHTlStXMHDgQCQnJ6NKlSpwdHRE79694enpaemiERERUQVi9ZfnIiMj0aNHD4wbNw7//vsvGjVqBDc3t3zT8+45IiIiMgerP9MUGRmJw4cP4+DBg0al591zREREZA5Wfabp8uXLGDduHJYuXQoHBwej1uHdc0RERGQOVn2mKTo6GteuXUOrVq2UednZ2di1axe++eYbZGRkwNZW/ynRfGAvERERmYNVn2nq2rUr3n//fdSqVUsJhipVqoTOnTsjNjY2T8BEREREZC5WfabJxcUF7dq1Q1BQEOrWrQsRQffu3bFz506oVCpLF6/isjPuUimRRTlWsXQJyhd7R0uXgKhgajH7Jqw6aAKAPn366E3XrFkTycnJ2L9/Pxo3bmyhUhEREVFFY9WX53LLzs7GqFGjICIICgoymIZDDhAREZE5lImg6dixY3B2doZGo8GoUaOwdu1aNGrUyGDa6dOnw9XVVXn5+fmVcmmJiIioPFKJiPkvApZQZmYmLl26hJSUFKxevRo//vgjdu7caTBwysjIQEZGhjKdmpoKPz8/pFw+Ca3WpTSLXX45+1i6BESFu3fL0iUoX9iniaxcamoqXD2rISUlxWzPnS0TQVNu3bp1Q+3atfH9998XmjY1NRWurq4MmkyJQROVBQyaTItBE1m50giarP7y3PTp09G2bVu4uLjAy8sL/fr1Q3p6ut7ZJCIiIiJzs/q75xYuXIgBAwZg2rRpSE1NxTvvvIPz589jypQpli5axZV139IlKH90WZYuQflz74alS1C+ZDtbugTljw3HGjSpzHSzb8Lqg6YuXbpg+fLlmDNnDlxdXdGgQQOcP38erq6uli4aERERVSBWHzQtWrRIb/rs2bOoW7cu3N3dDaY31BGciIiIqKSsvk/To3Q6HcaPH48OHTqgSZMmBtNwyAEiIiIyhzIVNI0ZMwbHjx9HZGRkvmkmT56MlJQU5XX58uVSLCERERGVV1Z/eW7Xrl2YNWsWtm/fjrt37+K7775D9erV802f82BfIiIiIlOy+jNN6enpSExMhIPDw4fEent7W7hEREREVBFZfdC0fv16nD17FmvWrAEA3Lp1C0lJSbh3756FS0ZEREQVidWPCK5SqQzODw8Px9ChQ/PM52NUSoGDm6VLUP5wnCbTS0+ydAnKFzXHaTI5jtNkUqmpaXCtVr9ijwguIsoLANauXQsRMRgwAbx7joiIiMzD6oOmouLdc0RERGQOVn/3XFHx7jkiIiIyh3IXNOWWc1kvNc38z6SpMDLL3QlKy2OfJtO7w++8SdlbdffXsol9mkwq5zhvzq7aVh80paen4+zZs8p0QkICYmNj4e7ujho1ahS6flpaGgDAr1E7s5WRiIiIrENaWprZnk9r9XfPRUVFoUuXLnnmh4aGIiIiotD1dTodrl69ChcXl3zvxLMGOXf5Xb582Wy9/isatqnpsU1Ni+1pemxT0ypL7SkiSEtLg6+vL2xszHNFxOrPNHXu3LlEp9psbGwKHEHc2mi1Wqv/YJY1bFPTY5uaFtvT9NimplVW2tNcZ5hysHMKERERkREYNBEREREZgUGTldBoNAgLC+NwCSbENjU9tqlpsT1Nj21qWmxPfVbfEZyIiIjIGvBMExEREZERGDQRERERGYFBExEREZERGDQRERERGYFBkxnMnz8fAQEBcHBwQGBgIP7++29l2Q8//IDOnTtDq9VCpVLh9u3bedafNm0a2rdvDycnJ7i5ueVZfuTIEQwaNAh+fn5wdHREw4YNMW/ePDPWyLLM3Z4AcPDgQXTt2hVubm6oXLkygoODceTIETPVyPLya9ObN2/ijTfeQP369eHo6IgaNWpg7NixSElJ0Vv/0qVLCAkJgZOTE7y8vPDWW28hK0v/+XlRUVFo1aoVNBoN6tSpY9QI/mVVabRnRkYGpkyZAn9/f2g0GgQEBGDx4sWlVsfSVtI2HTt2LFq3bg2NRoMWLVrkyT8qKgp9+/ZF1apVUalSJbRo0QJLly4tjapZjLnbFAA2b96Mxx57DC4uLvD09MSzzz6LCxcumLlmpYdBk4mtWLECEyZMQFhYGA4fPozmzZsjODgY165dAwDcvXsXPXv2xHvvvZdvHpmZmejfvz9Gjx5tcHl0dDS8vLzwyy+/4MSJE5gyZQomT56Mb775xix1sqTSaM/09HT07NkTNWrUwIEDB7B79264uLggODgYDx48MEu9LKmgNr169SquXr2K2bNn4/jx44iIiMCmTZswfPhwZf3s7GyEhIQgMzMTe/fuxZIlSxAREYEPP/xQSZOQkICQkBB06dIFsbGxGD9+PF555RVs3rzZElU2q9JoTwB4/vnnsW3bNixatAjx8fFYvnw56tevX9rVLRUlbdMcL7/8MgYMGGBwG3v37kWzZs3w66+/4ujRoxg2bBheeuklrF+/3tzVs4jSaNOEhAT07dsXTzzxBGJjY7F582Zcv34dzzzzjLmrV3qETKpdu3YyZswYZTo7O1t8fX1l+vTpeul27NghAOTWrVv55hUeHi6urq5Gbfe1116TLl26FKfIVq002vPgwYMCQC5duqTMO3r0qACQM2fOlLgO1sbYNs2xcuVKUavV8uDBAxER2bBhg9jY2EhSUpKSZsGCBaLVaiUjI0NERN5++21p3LixXj4DBgyQ4OBgU1fH4kqjPTdu3Ciurq5y48YNM9bEepS0TR8VFhYmzZs3N2q7vXv3lmHDhhWrzNauNNp01apVYmdnJ9nZ2cq8devWiUqlkszMzJJXwgrwTJMJZWZmIjo6Gt26dVPm2djYoFu3bti3b59Zt52SkgJ3d3ezbqO0lVZ71q9fH1WqVMGiRYuQmZmJe/fuYdGiRWjYsCECAgJMth1rUJw2TUlJgVarhZ3dw0dV7tu3D02bNoW3t7eSJjg4GKmpqThx4oSS5tFt5KQx9/egtJVWe65btw5t2rTB559/jmrVqqFevXqYNGkS7t27Z8baWYYp2rS4yuPvKFB6bdq6dWvY2NggPDwc2dnZSElJwc8//4xu3brB3t6+xPWwBgyaTOj69evIzs7W+/EDAG9vbyQlJZltu3v37sWKFSvw6quvmm0bllBa7eni4oKoqCj88ssvcHR0hLOzMzZt2oSNGzeW+EfY2hS1Ta9fv45PPvlE77OVlJRkcP2cZQWlSU1NLVcH+tJqz/Pnz2P37t04fvw41q5diy+//BKrV6/Ga6+9ZuoqWZwp2rQ4Vq5ciYMHD2LYsGElyscalVab1qxZE3/++Sfee+89aDQauLm54cqVK1i5cmWJym9NGDSVccePH0ffvn0RFhaGHj16WLo4ZdK9e/cwfPhwdOjQAfv378eePXvQpEkThISElKsDfFGlpqYiJCQEjRo1wkcffWTp4pR5JWlPnU4HlUqFpUuXol27dujduzfmzJmDJUuW8DNqgs/ojh07MGzYMCxcuBCNGzc2XQHLoJK0aVJSEkaMGIHQ0FAcPHgQO3fuhFqtxnPPPQcpJw8fKV//RluYh4cHbG1tkZycrDc/OTkZPj4+Jt/eyZMn0bVrV7z66qt4//33TZ6/pZVWey5btgwXLlzAvn37YGNjo8yrXLkyfv/9dwwcONBk27I0Y9s0LS0NPXv2hIuLC9auXat3at3Hx0fvDsac9XOW5bwb2oZWq4Wjo6NJ62RJpdWeVatWRbVq1eDq6qqkadiwIUQEV65cQd26dU1eN0sxRZsWxc6dO9GnTx/MnTsXL730UonKbq1Kq03nz58PV1dXfP7558q8X375BX5+fjhw4AAee+yxklXECvBMkwmp1Wq0bt0a27ZtU+bpdDps27YNQUFBJt3WiRMn0KVLF4SGhmLatGkmzdtalFZ73r17FzY2NlCpVMq8nGmdTmey7VgDY9o0NTUVPXr0gFqtxrp16+Dg4KCXR1BQEI4dO6bcwQgAW7ZsgVarRaNGjZQ0j24jJ42pvweWVlrt2aFDB1y9ehXp6elKmtOnT8PGxgbVq1c3ZxVLnSna1FhRUVEICQnBzJkzy133hkeVVpvm/JY+ytbWVtleuWDpnujlTWRkpGg0GomIiJCTJ0/Kq6++Km5ubsqdMYmJiRITEyMLFy4UALJr1y6JiYnRuyvm4sWLEhMTI1OnThVnZ2eJiYmRmJgYSUtLExGRY8eOiaenpwwZMkQSExOV17Vr1yxSZ3MqjfaMi4sTjUYjo0ePlpMnT8rx48dlyJAh4urqKlevXrVIvc2poDZNSUmRwMBAadq0qZw9e1bv85WVlSUiIllZWdKkSRPp0aOHxMbGyqZNm8TT01MmT56sbOP8+fPi5OQkb731lsTFxcn8+fPF1tZWNm3aZKlqm01ptGdaWppUr15dnnvuOTlx4oTs3LlT6tatK6+88oqlqm1WJW1TEZEzZ85ITEyMjBw5UurVq6d873PuSNy+fbs4OTnJ5MmT9fIor3colkabbtu2TVQqlUydOlVOnz4t0dHREhwcLP7+/nL37l1LVd2kGDSZwddffy01atQQtVot7dq1k/379yvLwsLCBECeV3h4uJImNDTUYJodO3YUmIe/v3/pVrSUmLs9RUT+/PNP6dChg7i6ukrlypXliSeekH379pViLUtXfm2aM3SDoVdCQoKy/oULF6RXr17i6OgoHh4eMnHixDy3Ju/YsUNatGgharVaatWqpbdPypvSaM+4uDjp1q2bODo6SvXq1WXChAnl5kBkSEnbtFOnTgWmye93oVOnTqVf2VJi7jYVEVm+fLm0bNlSKlWqJJ6envLUU09JXFxcKdfUfFQi5aR3FhEREZEZsU8TERERkREYNBEREREZgUETERERkREYNBEREREZgUETERERkREYNBEREREZgUETERERkREYNBEREREZgUETERERkREYNBEREREZgUETERERkREYNBEREREZgUETERERkREYNBEREREZgUETERERkREYNBEREREZgUETERERkRHsLF2A0nD//n1kZmZauhhERERkRmq1Gg4ODmbLv9wHTffv30fNmjWRlJRk6aIQERGRGfn4+CAhIcFsgZNKRMQsOVuJ1NRUuLq64vLly9A6Oz2cqcvK5z27kOX/fZfC0llRPtZUlqLkZ7J8dP+dRsnepYjpi5mPUtwCpnP+1ol+msLWRX7LxfD8wvLLPR/55FPkaTG8PHf5Cy2v/mpGT+d+L2zXGZu+oPyLWtbC8jRVfiWdXxbavjjTxrR/abV9SfdFzjvyWV5YeYta/pLuy/zmPyolJQVardbAkpIr92eacmi1WiOCpnL4rvxtW8h7TjqbfN5zlquMfIeR71LIe37lyXnPOVKWtBzW8V6koKmIQU6hQdB/m0xyveeen7uJlfQ5+fy3SsU+MOWUr6jbzz0/5yNk5PZL+uNdkgOxuYKcslD30iivJbZvrrqocs3PPZ3f/Pym81sf+UznN7+w9XMHN7m3n1vu+fmlz11+c2NHcCIiIiIjMGgiIiIiMgKDJiIiIiIjMGgiIiIiMgKDJiIiIiIjMGgiIiIiMgKDJiIiIiIjMGgiIiIiMgKDJiIiIiIjMGgiIiIiMgKDJiIiIiIjMGgiIiIiMgKDJiIiIiIjMGgiIiIiMgKDJiIiIiIjMGgiIiIiMgKDJiIiIiIjMGgiIiIiMgKDJiIiIiIjMGgiIiIiMgKDJiIiIiIj2Fm6AKUlNTUV0GU9nMj3PbuQ5f99l8LSWVE+1lQWg/nl8y66/04X9i4Fv//3DboSvpdSPrmrbWg6d9XFyHWR33IxPL+w/HLPRz75FHk6p165diXy28X5pM/d1MZO534vbNcZm76g/Ita1sLyNFV+JZ1fFtq+ONPGtH9ptX1J90XOO/JZXlh5i1p+c72XlnIfNIkInJ2d4efnZ+miEBERkRn5+PhArVabLf9yHzSpVCqkp6fj8uXL0Gq1li5OhZOamgo/Pz+2vwWw7S2L7W85bHvLsmT7q9VqODg4mC3/ch805dBqtfzyWBDb33LY9pbF9rcctr1llcf2Z0dwIiIiIiMwaCIiIiIyQrkPmjQaDcLCwqDRaCxdlAqJ7W85bHvLYvtbDtvesspz+6tEpLTv2CMiIiIqc8r9mSYiIiIiU2DQRERERGQEBk1ERERERmDQRERERGSEch80zZ8/HwEBAXBwcEBgYCD+/vtvSxepTJk+fTratm0LFxcXeHl5oV+/foiPj9dLc//+fYwZMwZVqlSBs7Mznn32WSQnJ+uluXTpEkJCQuDk5AQvLy+89dZbyMrK0ksTFRWFVq1aQaPRoE6dOoiIiDB39cqUGTNmQKVSYfz48co8tr15/fPPPxgyZAiqVKkCR0dHNG3aFIcOHVKWiwg+/PBDVK1aFY6OjouWtFwAABpQSURBVOjWrRvOnDmjl8fNmzcxePBgaLVauLm5Yfjw4UhPT9dLc/ToUXTs2BEODg7w8/PD559/Xir1s2bZ2dn44IMPULNmTTg6OqJ27dr45JNP8Oi9S2x/09m1axf69OkDX19fqFQq/Pbbb3rLS7OtV61ahQYNGsDBwQFNmzbFhg0bTF7fYpNyLDIyUtRqtSxevFhOnDghI0aMEDc3N0lOTrZ00cqM4OBgCQ8Pl+PHj0tsbKz07t1batSoIenp6UqaUaNGiZ+fn2zbtk0OHTokjz32mLRv315ZnpWVJU2aNJFu3bpJTEyMbNiwQTw8PGTy5MlKmvPnz4uTk5NMmDBBTp48KV9//bXY2trKpk2bSrW+1urvv/+WgIAAadasmYwbN06Zz7Y3n5s3b4q/v78MHTpUDhw4IOfPn5fNmzfL2bNnlTQzZswQV1dX+e233+TIkSPy1FNPSc2aNeXevXtKmp49e0rz5s1l//798tdff0mdOnVk0KBByvKUlBTx9vaWwYMHy/Hjx2X58uXi6Ogo33//fanW19pMmzZNqlSpIuvXr5eEhARZtWqVODs7y7x585Q0bH/T2bBhg0yZMkXWrFkjAGTt2rV6y0urrffs2SO2trby+eefy8mTJ+X9998Xe3t7OXbsmNnbwBjlOmhq166djBkzRpnOzs4WX19fmT59ugVLVbZdu3ZNAMjOnTtFROT27dtib28vq1atUtLExcUJANm3b5+IPPwy2tjYSFJSkpJmwYIFotVqJSMjQ0RE3n77bWncuLHetgYMGCDBwcHmrpLVS0tLk7p168qWLVukU6dOStDEtjevd955Rx5//PF8l+t0OvHx8ZFZs2Yp827fvi0ajUaWL18uIiInT54UAHLw4EElzcaNG0WlUsk///wjIiLffvutVK5cWdkfOduuX7++qatUpoSEhMjLL7+sN++ZZ56RwYMHiwjb35xyB02l2dbPP/+8hISE6JUnMDBQRo4cadI6Fle5vTyXmZmJ6OhodOvWTZlnY2ODbt26Yd++fRYsWdmWkpICAHB3dwcAREdH48GDB3rt3KBBA9SoUUNp53379qFp06bw9vZW0gQHByM1NRUnTpxQ0jyaR04a7itgzJgxCAkJydM+bHvzWrduHdq0aYP+/fvDy8sLLVu2xMKFC5XlCQkJSEpK0ms7V1dXBAYG6rW/m5sb2rRpo6Tp1q0bbGxscODAASXNf/7zH70nswcHByM+Ph63bt0ydzWtVvv27bFt2zacPn0aAHDkyBHs3r0bvXr1AsD2L02l2dbW/ntUboOm69evIzs7W+9gAQDe3t5ISkqyUKnKNp1Oh/Hjx6NDhw5o0qQJACApKQlqtRpubm56aR9t56SkJIP7IWdZQWlSU1Nx7949c1SnTIiMjMThw4cxffr0PMvY9uZ1/vx5LFiwAHXr1sXmzZsxevRojB07FkuWLAHwv/Yr6DcmKSkJXl5eesvt7Ozg7u5epH1UEb377rsYOHAgGjRoAHt7e7Rs2RLjx4/H4MGDAbD9S1NptnV+aaxlX9hZugBUdowZMwbHjx/H7t27LV2UCuHy5csYN24ctmzZAgcHB0sXp8LR6XRo06YNPvvsMwBAy5Ytcfz4cXz33XcIDQ21cOnKv5UrV2Lp0qVYtmwZGjdujNjYWIwfPx6+vr5sf7KYcnumycPDA7a2tnnuJEpOToaPj4+FSlV2vf7661i/fj127NiB6tWrK/N9fHyQmZmJ27dv66V/tJ19fHwM7oecZQWl0Wq1cHR0NHV1yoTo6Ghcu3YNrVq1gp2dHezs7LBz50589dVXsLOzg7e3N9vejKpWrYpGjRrpzWvYsCEuXboE4H/tV9BvjI+PD65du6a3PCsrCzdv3izSPqqI3nrrLeVsU9OmTfHiiy/izTffVM66sv1LT2m2dX5prGVflNugSa1Wo3Xr1ti2bZsyT6fTYdu2bQgKCrJgycoWEcHrr7+OtWvXYvv27ahZs6be8tatW8Pe3l6vnePj43Hp0iWlnYOCgnDs2DG9L9SWLVug1WqVg1JQUJBeHjlpKvK+6tq1K44dO4bY2Fjl1aZNGwwePFj5m21vPh06dMgzvMbp06fh7+8PAKhZsyZ8fHz02i41NRUHDhzQa//bt28jOjpaSbN9+3bodDoEBgYqaXbt2oUHDx4oabZs2YL69eujcuXKZquftbt79y5sbPQPUba2ttDpdADY/qWpNNva6n+PLN0T3ZwiIyNFo9FIRESEnDx5Ul599VVxc3PTu5OICjZ69GhxdXWVqKgoSUxMVF53795V0owaNUpq1Kgh27dvl0OHDklQUJAEBQUpy3Nue+/Ro4fExsbKpk2bxNPT0+Bt72+99ZbExcXJ/Pnzedu7AY/ePSfCtjenv//+W+zs7GTatGly5swZWbp0qTg5Ockvv/yipJkxY4a4ubnJ77//LkePHpW+ffsavA27ZcuWcuDAAdm9e7fUrVtX7zbs27dvi7e3t7z44oty/PhxiYyMFCcnpwp3y3tuoaGhUq1aNWXIgTVr1oiHh4e8/fbbShq2v+mkpaVJTEyMxMTECACZM2eOxMTEyMWLF0Wk9Np6z549YmdnJ7Nnz5a4uDgJCwvjkAOl6euvv5YaNWqIWq2Wdu3ayf79+y1dpDIFgMFXeHi4kubevXvy2muvSeXKlcXJyUmefvppSUxM1MvnwoUL0qtXL3F0dBQPDw+ZOHGiPHjwQC/Njh07pEWLFqJWq6VWrVp626CHcgdNbHvz+uOPP6RJkyai0WikQYMG8sMPP+gt1+l08sEHH4i3t7doNBrp2rWrxMfH66W5ceOGDBo0SJydnUWr1cqwYcMkLS1NL82RI0fk8ccfF41GI9WqVZMZM2aYvW7WLjU1VcaNGyc1atQQBwcHqVWrlkyZMkXvdnW2v+ns2LHD4G99aGioiJRuW69cuVLq1asnarVaGjduLP/3f/9ntnoXlUrkkeFViYiIiMigctuniYiIiMiUGDQRERERGYFBExEREZERGDQRERERGYFBExEREZERGDQRERERGYFBE5EBKpUKv/32m0nyCggIwJdffmmSvKxBVFQUVCpVnse3lLbMzEzUqVMHe/fuBQBcuHABKpUKsbGx+a5jLWW3VhEREXkeAF2eZWZmIiAgAIcOHbJ0UaiMYNBEVk2lUhX4+uijj/Jd15iDaElcvnwZL7/8Mnx9faFWq+Hv749x48bhxo0bZtmeJXTu3Bnjx4/Xm9e+fXskJibC1dXVMoX6r++++w41a9ZE+/btAQB+fn5ITExEkyZNLFouU1u1ahUaNGgABwcHNG3aFBs2bCh0nX///RfPPfccKleuDK1Wi86dO+d5JIwhAwYMwOnTp01RbKuwZs0a9OjRA1WqVDH4W6BWqzFp0iS88847likglTkMmsiqJSYmKq8vv/wSWq1Wb96kSZMsUq7z58+jTZs2OHPmDJYvX46zZ8/iu+++U55tePPmTYuUCwCys7OV53OZg1qtho+PD1Qqldm2URgRwTfffIPhw4cr82xtbeHj4wM7OzuLlcvU9u7di0GDBmH48OGIiYlBv3790K9fPxw/frzA9d555x0cOnQI69evR0xMDMaMGWPU9hwdHeHl5WWKohst5wHI5nDnzh08/vjjmDlzZr5pBg8ejN27d+PEiRNmKweVIxYekZzIaOHh4eLq6qpMZ2dny9SpU6VatWqiVqulefPmsnHjRmU5cj0OoFOnTiLy8Jli3bp1kypVqohWq5X//Oc/Eh0drbctALJ27dp8y9KzZ0+pXr263jP4REQSExPFyclJRo0apczz9/eXjz/+WAYOHChOTk7i6+sr33zzjbJcp9NJWFiY+Pn5iVqtlqpVq8obb7yhLL9//75MnDhRfH19xcnJSdq1ayc7duzI0y6///67NGzYUGxtbeX7778XjUYjt27d0ivf2LFjpUuXLiIicv36dRk4cKD4+vqKo6OjNGnSRJYtW6akDQ0NzdOGCQkJyuMWHs179erV0qhRI1Gr1eLv7y+zZ8/W266/v79MmzZNhg0bJs7OzuLn56f3vKmMjAwZM2aM+Pj4iEajkRo1ashnn32Wb/sfPHhQbGxsJDU1VZmXkJAgACQmJkaZ93//939St25dcXBwkM6dO0t4eHiesoeHh4ufn584OjpKv379ZPbs2XqfMxGRdevWSZs2bUSj0UiVKlWkX79++ZbNlJ5//nkJCQnRmxcYGCgjR44scL3hw4frPfPLWLm/Y6GhodK3b1+9NOPGjVO+SyIiq1atkiZNmoiDg4O4u7tL165dJT09XVm+cOFCadCggWg0Gqlfv77Mnz9fL7+AgAAJDAyUb7/9Vm7evFnkMhvD0GfjUV26dJH333/fLNum8oVBE5UZuX/Q58yZI1qtVpYvXy6nTp2St99+W+zt7eX06dMi8jA4AiBbt26VxMREuXHjhoiIbNu2TX7++WeJi4uTkydPyvDhw8Xb21vvAFxQ0HTjxg1RqVT5HtRHjBghlStXFp1OJyIPAwYXFxeZPn26xMfHy1dffSW2trby559/isjDg45Wq5UNGzbIxYsX5cCBA3rPOHvllVekffv2smvXLjl79qzMmjVLNBqNUs/w8HCxt7eX9u3by549e+TUqVOSnp4u3t7e8uOPPyr5ZGVl6c27cuWKzJo1S2JiYuTcuXNKuQ4cOCAiDx+uGRQUJCNGjFAe1JyVlZUnaDp06JDY2NjIxx9/LPHx8RIeHi6Ojo56z6/z9/cXd3d3mT9/vpw5c0amT58uNjY2curUKRERmTVrlvj5+cmuXbvkwoUL8tdff+kFcLnNmTNHGjRooDcv94Hx0qVLotFoZMKECXLq1Cn55ZdfxNvbW6/s+/fvFxsbG5k5c6bEx8fLvHnzxM3NTe9ztn79erG1tZUPP/xQTp48KbGxsXr7fuTIkVKpUqUCX48qLO2jAZGfn5/MnTtXb/0PP/xQmjVrlm/biDwM8uzt7fX+iTBGUYOmq1evip2dncyZM0cSEhLk6NGjMn/+fOV5Y7/88otUrVpVfv31Vzl//rz8+uuv4u7uLhEREUp+ly5dkmnTpimBVf/+/WX9+vWSlZWVp3y7du0qtP0efaByjsKCpnfeeUcvECTKD4MmKjNy/6D7+vrKtGnT9NK0bdtWXnvtNREp/IcyR3Z2tri4uMgff/yhzCsoaNq/f3+By+fMmSMAJDk5WUQeBgw9e/bUSzNgwADp1auXiIh88cUXUq9ePcnMzMyT18WLF8XW1lb++ecfvfldu3aVyZMni4goZ09iY2P10owbN06eeOIJZXrz5s0Gzz49KiQkRCZOnKhM535AsIjkCZpeeOEF6d69u16at956Sxo1aqRM+/v7y5AhQ5RpnU4nXl5esmDBAhEReeONN+SJJ55QAs3C5K6bSN79PXnyZL0yiDw8OD5a9kGDBknv3r310gwYMEDvcxYUFCSDBw/OtyzJycly5syZAl+PKixtzudGRMTe3j5P8Dh//nzx8vLKtzwnTpwQZ2dnmT59ulSrVk1WrlypLDt06JAAkH///dfgukUNmqKjowWAXLhwwWB+tWvXzlP+Tz75RIKCggymP3DggIwZM0Y8PDzEx8dHJk6cqPd0+7t37xbafo/+85OjsN+CefPmSUBAgMFlRI8qPxf/qUJJTU3F1atX0aFDB735HTp0wJEjRwpcNzk5Ge+//z6ioqJw7do1ZGdn4+7du0XuWyFFeNZ1UFBQnumcO+r69++PL7/8ErVq1ULPnj3Ru3dv9OnTB3Z2djh27Biys7NRr149vfUzMjJQpUoVZVqtVqNZs2Z6aQYPHozHHnsMV69eha+vL5YuXYqQkBDl7qjs7Gx89tlnWLlyJf755x9kZmYiIyMDTk5ORWgFIC4uDn379tWb16FDB3z55ZfIzs6Gra0tAOiVT6VSwcfHB9euXQMADB06FN27d0f9+vXRs2dPPPnkk+jRo0e+27x37x4cHBwKLVdgYKDevNz7IS4uDk8//XSeNJs2bVKmY2NjMWLEiHy34+XlVaR+QHXq1DE6bXF89NFH6NWrF95991306NED3bt3x40bNzBq1CgcO3YMDRo0gIeHh0m21bx5c3Tt2hVNmzZFcHAwevTooXRAv3PnDs6dO4fhw4frtV9WVla+NxG0a9cO7dq1w5w5czB58mTMmTMHW7duVTpwOzo6mqX9HB0dcffuXZPnS+UPgyaqcEJDQ3Hjxg3MmzcP/v7+0Gg0CAoKQmZmplHr16lTByqVyuABF3h4IK5cuTI8PT2Nys/Pzw/x8fHYunUrtmzZgtdeew2zZs3Czp07kZ6eDltbW0RHRyvBRw5nZ2flb0dHxzwds9u2bYvatWsjMjISo0ePxtq1axEREaEsnzVrFubNm4cvv/wSTZs2RaVKlTB+/Hij26Go7O3t9aZVKpXSYb1Vq1ZISEjAxo0bsXXrVjz//PPo1q0bVq9ebTAvDw8PHDt2zCzlzM3R0bHA5aNGjcIvv/xSYJr09HTl70f3myFDhgzBd999BwDw8fFBcnKy3vLk5GT4+Pjku/7Ro0cRGhoK4GG7rlu3DsHBwbh+/To2bdqEYcOGFbj9R9nY2OT55+DBgwfK37a2ttiyZQv27t2LP//8E19//TWmTJmCAwcOKMH3woUL8wSvuT/LOeLj4/Hzzz/jl19+QUpKCkaMGKHX2f+vv/5Cr169Cizz999/j8GDBxtdRwC4efOm0d9XqtgYNFGZpNVq4evriz179qBTp07K/D179qBdu3YAHp59AR6eUXnUnj178O2336J3794AHg4dcP36daO3XaVKFXTv3h3ffvst3nzzTb2DalJSEpYuXYqXXnpJL4jZv3+/Xh779+9Hw4YNlWlHR0f06dMHffr0wZgxY9CgQQMcO3YMLVu2RHZ2Nq5du4aOHTsaXcYcgwcPxtKlS1G9enXY2NggJCRErx369u2LIUOGAAB0Oh1Onz6NRo0aKWnUanWe9sutYcOG2LNnj968PXv2oF69evkeHA3RarUYMGAABgwYgOeeew49e/bEzZs34e7unidty5YtsWDBAohIvnfxNWzYEOvWrdObl3s/NGzYEAcOHCgwTbNmzbBt27Z8g42PP/64SHdxFjYEhlarVf4OCgrCtm3b9IZ92LJlS54zZo+qVq0a/vrrL0yePBnAw7N+a9euxZNPPgl3d3e8/vrrRpfV09Mzz516sbGxegGwSqVChw4d0KFDB3z44Yfw9/fH2rVrMWHCBPj6+uL8+fMFBjHXr19HZGQkfv75Z0RHR6N79+6YMWMG+vXrl+dsYps2bQptP29vb6Prl+P48eNo2bJlkdejCsjClweJjJa7v8XcuXNFq9VKZGSknDp1St555x29juAPHjwQR0dH+fTTTyUpKUlu374tIiItW7aU7t27y8mTJ2X//v3SsWNHcXR01Otwi0Lunjt9+rR4eHhIx44dZefOnXLp0iXZuHGjNGnSROrWrat0Ohd52J9Hq9UqnY2/+eYbsbW1lU2bNin1+vHHH+XYsWNy7tw5ef/998XR0VGuX78uIiKDBw+WgIAApTPtgQMH5LPPPpP169cbbJdHnTlzRgBIs2bNZPjw4XrL3nzzTfHz85M9e/bIyZMn5ZVXXhGtVqvXh2XEiBHStm1bSUhIkH///Veys7Pz9GmKjo7W6wgeERFhsCN47g7NzZs3l7CwMBF52K9r2bJlEhcXJ/Hx8TJ8+HDx8fGR7Oxsg/W6fv262Nvb6/V3yd1v5eLFi6JWq2XSpEly6tQpWbp0qfj4+OiVfd++fWJjYyOzZs2S06dPy9dff52nI/iOHTvExsZG6Qh+9OhRmTFjhsFymdqePXvEzs5OZs+eLXFxcRIWFpan3rlt3LhRVCqVvPbaa3Ls2DE5fPiwTJkyRZydncXW1lYiIyPzXTf3Z2nTpk2iUqlkyZIlcvr0afnwww9Fq9UqfZr2798v06ZNk4MHD8rFixdl5cqVolarZcOGDSLy8M45R0dHmTdvnsTHx8vRo0dl8eLF8sUXXyjbqFWrljRq1EhmzpwpV69eLVmD5XLjxg2JiYmR//u//xMAEhkZKTExMZKYmKiXzt/fX3766SeTbpvKJwZNVGYYGnLgo48+kmrVqom9vX2eIQdEHv5o+/n5iY2NjfJDf/jwYWnTpo04ODhI3bp1ZdWqVXkO6oUFTSIiFy5ckNDQUPH29hZ7e3vx8/OTN954Qwl2cvj7+8vUqVOlf//+4uTkJD4+PjJv3jxl+dq1ayUwMFC0Wq1UqlRJHnvsMdm6dauyPDMzUz788EMJCAgQe3t7qVq1qjz99NNy9OhRg+2SW7t27QSAbN++XW/+jRs3pG/fvuLs7CxeXl7y/vvvy0svvaQXNMXHx8tjjz0mjo6ORg05YG9vLzVq1JBZs2blaYOCgqYffvhBWrRoIZUqVRKtVitdu3aVw4cP51snkYe347/77rvKtKHOvn/88YfUqVNHNBqNdOzYURYvXpyn7IsWLZLq1auLo6Oj9OnTx+CQA7/++qu0aNFC1Gq1eHh4yDPPPFNg2Uxp5cqVUq9ePVGr1dK4cWP5v//7v0LX2b59u3Ts2FG0Wq24ubnJc889JydPnpRPP/1UHBwcZM+ePQbXM/RZ+vDDD8Xb21tcXV3lzTfflNdff135Lp08eVKCg4PF09NTNBqN1KtXT77++mu99ZcuXaq0XeXKleU///mPrFmzRlkeFxdXtAYpgpybJHK/cj53IiJ79+4VNze3PMOHEBmiEilCb1YiIitx9OhRdO/eHefOnSu0n1BRREREYPz48XzUSgUxYMAANG/eHO+9956li0JlAEcEJ6IyqVmzZpg5cyYSEhIsXRQqozIzM9G0aVO8+eabli4KlRE800RE9AieaSKi/DBoIiIiIjICL88RERERGYFBExEREZERGDQRERERGYFBExEREZERGDQRERERGYFBExEREZERGDQRERERGYFBExEREZERGDQRERERGeH/ASmKHodnOQRNAAAAAElFTkSuQmCC", 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", 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "DIRdiag = '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025'\n", "dateIni = '2025100112' \n", "dateFin = '2025100218'\n", "nHour = '6'\n", "\n", "varNames = ['amsua','atms'] \n", "vminOMA = -1.0 \n", "vmaxOMA = 1.0 \n", "vminSTD = 0.0 \n", "vmaxSTD = 2.0 \n", "channel = 6 \n", "\n", "datei = datetime.strptime(str(dateIni), '%Y%m%d%H')\n", "datef = datetime.strptime(str(dateFin), '%Y%m%d%H')\n", "dates = [dates.strftime('%Y%m%d%H') for dates in pd.date_range(datei, datef,freq='6h').tolist()]\n", "\n", "print(dates)\n", "print('')\n", "\n", "lista_satelites = []\n", "OMF_final, stdF_final, Cf_final, OMA_final, stdA_final, Ca_final = [], [], [], [], [], []\n", "\n", "for varName in varNames:\n", " \n", " print('******************** varName = '+varName+' ********************')\n", " print('')\n", " \n", " if varName == 'amsua':\n", " varTypes = ['metop-b', 'metop-c']\n", " # Define a lista de colunas [1, 2, 3, ..., 15] para o dataframe\n", " colunas_canais = []\n", " colunas_canais = list(range(1, 16))\n", " else:\n", " varTypes = ['npp', 'n20', 'n21']\n", " # Define a lista de colunas [1, 2, 3, ..., 22] para o dataframe\n", " colunas_canais = []\n", " colunas_canais = list(range(1, 23))\n", " \n", " colunas_canais.reverse()\n", " ax = None\n", " for varType in varTypes:\n", " \n", " print('########## varType = '+varType+' ##########')\n", " print('')\n", " \n", " paths, pathsc = [], []\n", "\n", " OuterL = '01' \n", " [paths.append(DIRdiag + '/' + dt + '/diag_' + varName +'_'+ varType +'_' + OuterL + '.' + dt) for dt in dates]\n", "\n", " OuterLc = '03'\n", " [pathsc.append(DIRdiag + '/' + dt + '/diag_' + varName +'_'+ varType +'_' + OuterLc + '.' + dt) for dt in dates]\n", "\n", " print(paths)\n", " print('')\n", " print(pathsc)\n", "\n", " read = True\n", "\n", " if read: \n", " gdf_list = []\n", " print('')\n", "\n", " print('Aguarde, o tempo total estimado para a leitura dos arquivos é de ' +\n", " str(int((float(len(paths))*20)/60)) + ' minutos e ' +\n", " str(int((float(len(paths))*20)%60)) + ' segundos.')\n", "\n", " print('')\n", "\n", " for path, pathc in zip(paths, pathsc):\n", " print('Reading ' + path)\n", "\n", " gdf = gd.read_diag(path, pathc)\n", "\n", " gdf_list.append(gdf)\n", "\n", " print('Pronto!')\n", " \n", " tidx = 0\n", " gdf_list[tidx].pfileinfo()\n", " gdf_list[tidx].obsInfo\n", " df = gdf_list[tidx].obsInfo\n", " col = df.columns.tolist()\n", " print('columns', col)\n", " \n", " print('Série temporal -- ASSIMILADOS mask=idqc==0 & iuse>=1')\n", " print('')\n", " channel = None\n", " \n", " lista_satelites.append(varType)\n", " \n", " #OMF, stdF, Cf, OMA, stdA, Ca = \n", " \n", " OMF, stdF, Cf, OMA, stdA, Ca = gd.plot_diag.time_series_radi(gdf_list,\n", " varName=varName, \n", " varType=varType, \n", " mask='idqc==0 & iuse>=1', \n", " dateIni=dateIni, \n", " dateFin=dateFin, \n", " nHour=nHour, \n", " vminOMA=vminOMA, \n", " vmaxOMA=vmaxOMA, \n", " vminSTD=vminSTD, \n", " vmaxSTD=vmaxSTD, \n", " channel=channel, \n", " Clean=False)\n", " # renomear figuras\n", " name_old_OMA = f'hovmoller_{varName}-{varType}_OmA.png'\n", " name_old_OMF = f'hovmoller_{varName}-{varType}_OmF.png'\n", " \n", " name_new_OMA = f'hovmoller_ASSi_{varName}-{varType}_OmA.png'\n", " name_new_OMF = f'hovmoller_ASSi_{varName}-{varType}_OmF.png'\n", " \n", " os.rename(name_old_OMA, name_new_OMA)\n", " os.rename(name_old_OMF, name_new_OMF)\n", " \n", " # Converte o array OMF em DataFrame mapeando as colunas\n", " OMF_df, stdF_df, Cf_df = [], [], []\n", " OMA_df, stdA_df, Ca_df = [], [], []\n", " \n", " OMF_df = pd.DataFrame(OMF, columns=colunas_canais)\n", " stdF_df = pd.DataFrame(stdF, columns=colunas_canais)\n", " Cf_df = pd.DataFrame(Cf, columns=colunas_canais)\n", " OMA_df = pd.DataFrame(OMA, columns=colunas_canais)\n", " stdA_df = pd.DataFrame(stdA, columns=colunas_canais)\n", " Ca_df = pd.DataFrame(Ca, columns=colunas_canais)\n", " \n", " OMF_df['satelite'] = varType\n", " stdF_df['satelite'] = varType\n", " Cf_df['satelite'] = varType\n", " OMA_df['satelite'] = varType\n", " stdA_df['satelite'] = varType\n", " Ca_df['satelite'] = varType\n", " \n", " #print('')\n", " #print(OMF_df)\n", " \n", " OMF_df = OMF_df.replace(-99, np.nan)\n", " stdF_df = stdF_df.replace(-99, np.nan)\n", " Cf_df = Cf_df.replace(-99, np.nan)\n", " OMA_df = OMA_df.replace(-99, np.nan)\n", " stdA_df = stdA_df.replace(-99, np.nan)\n", " Ca_df = Ca_df.replace(-99, np.nan)\n", " \n", " # Concatena os dados de cada satélite na ordem da lista_satelites\n", " OMF_final.append(OMF_df)\n", " stdF_final.append(stdF_df)\n", " Cf_final.append(Cf_df)\n", " OMA_final.append(OMA_df)\n", " stdA_final.append(stdA_df)\n", " Ca_final.append(Ca_df)\n", " \n", " \n", " for file in gdf_list:\n", " file.close()" ] }, { "cell_type": "code", "execution_count": null, "id": "0e02260a", "metadata": {}, "outputs": [], "source": [ "Cf_final\n", "# OMF_df" ] }, { "cell_type": "code", "execution_count": 4, "id": "ec9d345a", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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151413121110987654321satelite
0NaNNaN0.5847260.4288150.3060910.2361980.205760NaN0.219926NaNNaNNaNNaNNaNNaNmetop-c
1NaNNaN0.6813700.4762230.3326730.2412180.207018NaN0.223417NaNNaNNaNNaNNaNNaNmetop-c
2NaNNaN0.6716950.4797350.3073200.2329130.209791NaN0.225216NaNNaNNaNNaNNaNNaNmetop-c
3NaNNaN0.6503260.4827040.3346450.2327500.201473NaN0.216009NaNNaNNaNNaNNaNNaNmetop-c
4NaNNaN0.6259170.4819520.3375550.2550680.227788NaN0.217007NaNNaNNaNNaNNaNNaNmetop-c
5NaNNaN0.6733490.5083150.3339660.2566720.214479NaN0.216508NaNNaNNaNNaNNaNNaNmetop-c
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" ], "text/plain": [ " 15 14 13 12 11 10 9 8 7 6 \\\n", "0 NaN NaN 0.584726 0.428815 0.306091 0.236198 0.205760 NaN 0.219926 NaN \n", "1 NaN NaN 0.681370 0.476223 0.332673 0.241218 0.207018 NaN 0.223417 NaN \n", "2 NaN NaN 0.671695 0.479735 0.307320 0.232913 0.209791 NaN 0.225216 NaN \n", "3 NaN NaN 0.650326 0.482704 0.334645 0.232750 0.201473 NaN 0.216009 NaN \n", "4 NaN NaN 0.625917 0.481952 0.337555 0.255068 0.227788 NaN 0.217007 NaN \n", "5 NaN NaN 0.673349 0.508315 0.333966 0.256672 0.214479 NaN 0.216508 NaN \n", "\n", " 5 4 3 2 1 satelite \n", "0 NaN NaN NaN NaN NaN metop-c \n", "1 NaN NaN NaN NaN NaN metop-c \n", "2 NaN NaN NaN NaN NaN metop-c \n", "3 NaN NaN NaN NaN NaN metop-c \n", "4 NaN NaN NaN NaN NaN metop-c \n", "5 NaN NaN NaN NaN NaN metop-c " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Cf_final[0] #[canais_desejados]\n", "\n", "# OMF_final[0]\n", "\n", "stdF_final[1]\n", "\n", "# OMA_final[0]\n", "# stdF_final[0]\n", "# df_concatenado = df_concatenado.replace(-99, np.nan)\n" ] }, { "cell_type": "code", "execution_count": 5, "id": "3a73c4fc", "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "sat = 0 chan = 4\n", "sat = 1 chan = 4\n", "sat = 0 chan = 5\n", "sat = 1 chan = 5\n", "sat = 0 chan = 6\n", "sat = 1 chan = 6\n", "sat = 0 chan = 7\n", "sat = 1 chan = 7\n", "sat = 0 chan = 8\n", "sat = 1 chan = 8\n", "sat = 0 chan = 9\n", "sat = 1 chan = 9\n", "sat = 0 chan = 10\n", "sat = 1 chan = 10\n", "sat = 0 chan = 11\n", "sat = 1 chan = 11\n", "sat = 0 chan = 12\n", "sat = 1 chan = 12\n", "sat = 0 chan = 13\n", "sat = 1 chan = 13\n", "sat = 0 chan = 14\n", "sat = 1 chan = 14\n", "sat = 0 chan = 15\n", "sat = 1 chan = 15\n", "0 0.009222\n", "1 0.021352\n", "2 0.006309\n", "3 0.045994\n", "4 0.015014\n", "5 0.019150\n", "Name: 8, dtype: float64\n", "\n", "OMF\n", " 4 5 6 7 8 9 10 11 12 \\\n", "0 NaN NaN NaN 0.005555 0.009222 -0.014145 -0.000854 0.000684 0.039182 \n", "1 NaN NaN NaN 0.013189 0.021352 0.042155 0.040007 0.030436 0.063444 \n", "2 NaN NaN NaN 0.018330 0.006309 -0.008517 -0.006020 -0.034859 -0.023790 \n", "3 NaN NaN NaN 0.018740 0.045994 0.037227 0.032890 0.029216 0.010951 \n", "4 NaN NaN NaN 0.018210 0.015014 -0.002063 -0.015649 -0.037810 -0.008447 \n", "5 NaN NaN NaN 0.011056 0.019150 0.024895 0.012863 0.048177 0.051402 \n", "\n", " 13 14 15 \n", "0 0.101535 NaN NaN \n", "1 0.115058 NaN NaN \n", "2 0.073620 NaN NaN \n", "3 -0.046474 NaN NaN \n", "4 0.106549 NaN NaN \n", "5 -0.025861 NaN NaN \n", "\n", "OMA\n", " 4 5 6 7 8 9 10 11 12 \\\n", "0 NaN NaN NaN -0.000305 0.009275 0.006763 0.008581 -0.014476 -0.001475 \n", "1 NaN NaN NaN -0.009512 0.005293 0.001334 0.008440 -0.010369 -0.011077 \n", "2 NaN NaN NaN -0.011838 -0.000971 -0.001684 0.003304 -0.007789 -0.005203 \n", "3 NaN NaN NaN -0.000475 0.005720 -0.002454 0.005006 0.001837 0.006055 \n", "4 NaN NaN NaN -0.001034 0.007274 0.004221 0.005266 -0.002544 0.005569 \n", "5 NaN NaN NaN -0.005355 0.003886 0.003513 -0.001495 -0.007975 -0.010972 \n", "\n", " 13 14 15 \n", "0 0.035602 NaN NaN \n", "1 0.002616 NaN NaN \n", "2 -0.009411 NaN NaN \n", "3 0.011417 NaN NaN \n", "4 0.026938 NaN NaN \n", "5 0.009115 NaN NaN \n", "\n", "stdF\n", " 4 5 6 7 8 9 10 11 12 \\\n", "0 NaN NaN NaN 0.043753 0.050371 0.049099 0.061439 0.096842 0.189180 \n", "1 NaN NaN NaN 0.046135 0.052291 0.048730 0.064149 0.120595 0.234008 \n", "2 NaN NaN NaN 0.046388 0.052014 0.045175 0.056739 0.097291 0.239344 \n", "3 NaN NaN NaN 0.041381 0.049431 0.040299 0.056765 0.109855 0.225896 \n", "4 NaN NaN NaN 0.044923 0.052969 0.056161 0.071714 0.118141 0.242667 \n", "5 NaN NaN NaN 0.044351 0.050830 0.047186 0.069371 0.113266 0.251265 \n", "\n", " 13 14 15 \n", "0 0.355435 NaN NaN \n", "1 0.473352 NaN NaN \n", "2 0.478229 NaN NaN \n", "3 0.415143 NaN NaN \n", "4 0.425608 NaN NaN \n", "5 0.442326 NaN NaN \n", "\n", "stdA\n", " 4 5 6 7 8 9 10 11 12 \\\n", "0 NaN NaN NaN 0.030652 0.035798 0.024178 0.040524 0.054786 0.112247 \n", "1 NaN NaN NaN 0.030865 0.036857 0.023653 0.039020 0.054202 0.109890 \n", "2 NaN NaN NaN 0.031335 0.036147 0.023824 0.038888 0.054356 0.120662 \n", "3 NaN NaN NaN 0.029680 0.035279 0.023619 0.038816 0.056398 0.118446 \n", "4 NaN NaN NaN 0.029934 0.036341 0.024156 0.040263 0.053927 0.113244 \n", "5 NaN NaN NaN 0.029648 0.035388 0.023768 0.040008 0.055034 0.115431 \n", "\n", " 13 14 15 \n", "0 0.217941 NaN NaN \n", "1 0.228295 NaN NaN \n", "2 0.224709 NaN NaN \n", "3 0.218812 NaN NaN \n", "4 0.222937 NaN NaN \n", "5 0.225857 NaN NaN \n", "\n", "qF\n", " 4 5 6 7 8 9 10 11 12 \\\n", "0 0.0 0.0 0.0 17738.0 8851.0 17655.0 17793.0 17776.0 17682.0 \n", "1 0.0 0.0 0.0 17850.0 8875.0 17893.0 17956.0 17935.0 17879.0 \n", "2 0.0 0.0 0.0 18051.0 9012.0 18061.0 18113.0 18080.0 17972.0 \n", "3 0.0 0.0 0.0 18050.0 9049.0 18069.0 18127.0 18110.0 18028.0 \n", "4 0.0 0.0 0.0 18018.0 9024.0 17970.0 18120.0 18080.0 18008.0 \n", "5 0.0 0.0 0.0 17920.0 8969.0 17975.0 18046.0 18042.0 17996.0 \n", "\n", " 13 14 15 \n", "0 17732.0 0.0 0.0 \n", "1 17880.0 0.0 0.0 \n", "2 18017.0 0.0 0.0 \n", "3 18068.0 0.0 0.0 \n", "4 18061.0 0.0 0.0 \n", "5 18026.0 0.0 0.0 \n", "\n", "qA\n", " 4 5 6 7 8 9 10 11 12 \\\n", "0 0.0 0.0 0.0 17738.0 8851.0 17655.0 17793.0 17776.0 17682.0 \n", "1 0.0 0.0 0.0 17850.0 8875.0 17893.0 17956.0 17935.0 17879.0 \n", "2 0.0 0.0 0.0 18051.0 9012.0 18061.0 18113.0 18080.0 17972.0 \n", "3 0.0 0.0 0.0 18050.0 9049.0 18069.0 18127.0 18110.0 18028.0 \n", "4 0.0 0.0 0.0 18018.0 9024.0 17970.0 18120.0 18080.0 18008.0 \n", "5 0.0 0.0 0.0 17920.0 8969.0 17975.0 18046.0 18042.0 17996.0 \n", "\n", " 13 14 15 \n", "0 17732.0 0.0 0.0 \n", "1 17880.0 0.0 0.0 \n", "2 18017.0 0.0 0.0 \n", "3 18068.0 0.0 0.0 \n", "4 18061.0 0.0 0.0 \n", "5 18026.0 0.0 0.0 \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_2138433/645171308.py:41: RuntimeWarning: invalid value encountered in divide\n", " mediaOMF_chan = np.array(somaOMF_chan) / np.array(soma_NF)\n", "/tmp/ipykernel_2138433/645171308.py:42: RuntimeWarning: invalid value encountered in divide\n", " mediaOMA_chan = np.array(somaOMA_chan) / np.array(soma_NA)\n" ] } ], "source": [ "\n", "# Índices dos satélites que você quer combinar (Ex: satélites 0, 1 e 3)\n", "### Sensor AMSU-A\n", "indices_satelites = [0, 1]\n", "\n", "# Canais que você quer calcular (Ex: canais 1, 2, 3 e 4)\n", "canais_desejados = [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]\n", "\n", "df1_OMF, df1_stdF, df1_qF = [], [], []\n", "df1_OMA, df1_stdA, df1_qA = [], [], []\n", "\n", "# Cria o DataFrame vazio apenas com as colunas indicadas\n", "df1_OMF = pd.DataFrame(columns=canais_desejados)\n", "df1_stdF = pd.DataFrame(columns=canais_desejados)\n", "df1_qF = pd.DataFrame(columns=canais_desejados)\n", "\n", "df1_OMA = pd.DataFrame(columns=canais_desejados)\n", "df1_stdA = pd.DataFrame(columns=canais_desejados)\n", "df1_qA = pd.DataFrame(columns=canais_desejados)\n", "\n", "# Calcula a média e variancia dos canais\n", "\n", "for chan in canais_desejados:\n", " \n", " mediaOMF_chan, varOMF_chan, soma_NF = np.zeros(len(dates)), np.zeros(len(dates)), np.zeros(len(dates))\n", " mediaOMA_chan, varOMA_chan, soma_NA = np.zeros(len(dates)), np.zeros(len(dates)), np.zeros(len(dates))\n", " \n", " somaOMF_chan, somaVarF_chan = np.zeros(len(dates)), np.zeros(len(dates))\n", " somaOMA_chan, somaVarA_chan = np.zeros(len(dates)), np.zeros(len(dates))\n", " \n", " \n", " for sat in indices_satelites:\n", " # média\n", " print('sat =', sat,'chan =', chan)\n", " \n", " somaOMF_chan += np.array(OMF_final[sat][chan].fillna(0)) * np.array(Cf_final[sat][chan].fillna(0))\n", " somaOMA_chan += np.array(OMA_final[sat][chan].fillna(0)) * np.array(Ca_final[sat][chan].fillna(0))\n", " \n", " soma_NF += np.array(Cf_final[sat][chan].fillna(0))\n", " soma_NA += np.array(Ca_final[sat][chan].fillna(0))\n", " \n", " mediaOMF_chan = np.array(somaOMF_chan) / np.array(soma_NF)\n", " mediaOMA_chan = np.array(somaOMA_chan) / np.array(soma_NA)\n", " \n", " for sat in indices_satelites:\n", " # variancia\n", " diff1, diff2 = [], []\n", " \n", " diff1 = np.array(OMF_final[sat][chan].fillna(0)) - np.array(mediaOMF_chan)\n", " diff2 = np.array(OMA_final[sat][chan].fillna(0)) - np.array(mediaOMA_chan)\n", " \n", " somaVarF_chan += ( ( np.array( stdF_final[sat][chan].fillna(0) ) ** 2 ) + \n", " ( np.array( diff1 ) ** 2 ) ) * np.array( Cf_final[sat][chan].fillna(0) )\n", " somaVarA_chan += ( ( np.array( stdA_final[sat][chan].fillna(0) ) ** 2 ) + \n", " ( np.array( diff2 ) ** 2 ) ) * np.array( Ca_final[sat][chan].fillna(0) )\n", " \n", " varOMF_chan = np.array(somaVarF_chan) / np.array(soma_NF)\n", " varOMA_chan = np.array(somaVarA_chan) / np.array(soma_NA)\n", " \n", " df1_OMF[chan] = mediaOMF_chan\n", " df1_stdF[chan] = varOMF_chan #* varOMF_chan\n", " df1_qF[chan] = soma_NF\n", " \n", " df1_OMA[chan] = mediaOMA_chan\n", " df1_stdA[chan] = varOMA_chan #* varOMA_chan\n", " df1_qA[chan] = soma_NA\n", "\n", "\n", "# print(OMF_final[0][8])\n", "# print('')\n", "# print('OMF')\n", "# print(df1_OMF)\n", "\n", "# print('')\n", "# print('OMA')\n", "# print(df1_OMA)\n", " \n", "# print('')\n", "# print('stdF')\n", "# print(df1_stdF)\n", "\n", "# print('')\n", "# print('stdA')\n", "# print(df1_stdA)\n", "\n", "print('')\n", "print('qF')\n", "print(df1_qF)\n", "\n", "print('')\n", "print('qA')\n", "print(df1_qA)\n", "\n" ] }, { "cell_type": "code", "execution_count": 6, "id": "e7237dca", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "sat = 2 chan = 5\n", "sat = 3 chan = 5\n", "sat = 4 chan = 5\n", "sat = 2 chan = 6\n", "sat = 3 chan = 6\n", "sat = 4 chan = 6\n", "sat = 2 chan = 7\n", "sat = 3 chan = 7\n", "sat = 4 chan = 7\n", "sat = 2 chan = 8\n", "sat = 3 chan = 8\n", "sat = 4 chan = 8\n", "sat = 2 chan = 9\n", "sat = 3 chan = 9\n", "sat = 4 chan = 9\n", "sat = 2 chan = 10\n", "sat = 3 chan = 10\n", "sat = 4 chan = 10\n", "sat = 2 chan = 11\n", "sat = 3 chan = 11\n", "sat = 4 chan = 11\n", "sat = 2 chan = 12\n", "sat = 3 chan = 12\n", "sat = 4 chan = 12\n", "sat = 2 chan = 13\n", "sat = 3 chan = 13\n", "sat = 4 chan = 13\n", "sat = 2 chan = 14\n", "sat = 3 chan = 14\n", "sat = 4 chan = 14\n", "sat = 2 chan = 15\n", "sat = 3 chan = 15\n", "sat = 4 chan = 15\n", "sat = 2 chan = 16\n", "sat = 3 chan = 16\n", "sat = 4 chan = 16\n", "\n", "qF\n", " 5 6 7 8 9 10 11 12 \\\n", "0 972.0 972.0 29433.0 31566.0 31567.0 31568.0 31565.0 31517.0 \n", "1 813.0 813.0 29254.0 31717.0 31717.0 31716.0 31717.0 31519.0 \n", "2 1003.0 1003.0 30374.0 31748.0 31749.0 31749.0 31746.0 31405.0 \n", "3 1553.0 1554.0 29019.0 31697.0 31697.0 31687.0 31675.0 31211.0 \n", "4 820.0 820.0 29150.0 31661.0 31664.0 31670.0 31663.0 31368.0 \n", "5 998.0 998.0 29044.0 31535.0 31552.0 31542.0 31541.0 31354.0 \n", "\n", " 13 14 15 16 \n", "0 30978.0 31474.0 0.0 0.0 \n", "1 29844.0 31487.0 0.0 0.0 \n", "2 29272.0 31515.0 0.0 0.0 \n", "3 28733.0 31236.0 0.0 0.0 \n", "4 29807.0 31501.0 0.0 0.0 \n", "5 29432.0 31033.0 0.0 0.0 \n", "\n", "qA\n", " 5 6 7 8 9 10 11 12 \\\n", "0 972.0 972.0 29433.0 31566.0 31567.0 31568.0 31565.0 31517.0 \n", "1 813.0 813.0 29254.0 31717.0 31717.0 31716.0 31717.0 31519.0 \n", "2 1003.0 1003.0 30374.0 31748.0 31749.0 31749.0 31746.0 31405.0 \n", "3 1553.0 1554.0 29019.0 31697.0 31697.0 31687.0 31675.0 31211.0 \n", "4 820.0 820.0 29150.0 31661.0 31664.0 31670.0 31663.0 31368.0 \n", "5 998.0 998.0 29044.0 31535.0 31552.0 31542.0 31541.0 31354.0 \n", "\n", " 13 14 15 16 \n", "0 30978.0 31474.0 0.0 0.0 \n", "1 29844.0 31487.0 0.0 0.0 \n", "2 29272.0 31515.0 0.0 0.0 \n", "3 28733.0 31236.0 0.0 0.0 \n", "4 29807.0 31501.0 0.0 0.0 \n", "5 29432.0 31033.0 0.0 0.0 \n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/tmp/ipykernel_2138433/2658986338.py:40: RuntimeWarning: invalid value encountered in divide\n", " mediaOMF_chan = np.array(somaOMF_chan) / np.array(soma_NF)\n", "/tmp/ipykernel_2138433/2658986338.py:41: RuntimeWarning: invalid value encountered in divide\n", " mediaOMA_chan = np.array(somaOMA_chan) / np.array(soma_NA)\n" ] } ], "source": [ "# Índices dos satélites que você quer combinar (Ex: satélites 0, 1 e 3)\n", "### Sensor ATMS\n", "indices_satelites = [2, 3, 4]\n", "\n", "# Canais que você quer calcular (Ex: canais 1, 2, 3 e 4)\n", "canais_desejados = [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]\n", "\n", "df2_OMF, df2_stdF, df2_qF = [], [], []\n", "df2_OMA, df2_stdA, df2_qA = [], [], []\n", "\n", "# Cria o DataFrame vazio apenas com as colunas indicadas\n", "df2_OMF = pd.DataFrame(columns=canais_desejados)\n", "df2_stdF = pd.DataFrame(columns=canais_desejados)\n", "df2_qF = pd.DataFrame(columns=canais_desejados)\n", "\n", "df2_OMA = pd.DataFrame(columns=canais_desejados)\n", "df2_stdA = pd.DataFrame(columns=canais_desejados)\n", "df2_qA = pd.DataFrame(columns=canais_desejados)\n", "\n", "# Calcula a média e variancia dos canais\n", "\n", "for chan in canais_desejados:\n", " \n", " mediaOMF_chan, varOMF_chan, soma_NF = np.zeros(len(dates)), np.zeros(len(dates)), np.zeros(len(dates))\n", " mediaOMA_chan, varOMA_chan, soma_NA = np.zeros(len(dates)), np.zeros(len(dates)), np.zeros(len(dates))\n", " \n", " somaOMF_chan, somaVarF_chan = np.zeros(len(dates)), np.zeros(len(dates))\n", " somaOMA_chan, somaVarA_chan = np.zeros(len(dates)), np.zeros(len(dates))\n", " \n", " for sat in indices_satelites:\n", " # média\n", " print('sat =', sat,'chan =', chan)\n", " \n", " somaOMF_chan += np.array(OMF_final[sat][chan].fillna(0)) * np.array(Cf_final[sat][chan].fillna(0))\n", " somaOMA_chan += np.array(OMA_final[sat][chan].fillna(0)) * np.array(Ca_final[sat][chan].fillna(0))\n", " \n", " soma_NF += np.array(Cf_final[sat][chan].fillna(0))\n", " soma_NA += np.array(Ca_final[sat][chan].fillna(0))\n", " \n", " mediaOMF_chan = np.array(somaOMF_chan) / np.array(soma_NF)\n", " mediaOMA_chan = np.array(somaOMA_chan) / np.array(soma_NA)\n", " \n", " \n", " for sat in indices_satelites:\n", " # variancia\n", " diff1, diff2 = [], []\n", " \n", " diff1 = np.array(OMF_final[sat][chan].fillna(0)) - np.array(mediaOMF_chan)\n", " diff2 = np.array(OMA_final[sat][chan].fillna(0)) - np.array(mediaOMA_chan)\n", " \n", " \n", " somaVarF_chan += ( ( np.array( stdF_final[sat][chan].fillna(0) ) ** 2 ) + \n", " ( np.array( diff1 ) ** 2 ) ) * np.array( Cf_final[sat][chan].fillna(0) )\n", " somaVarA_chan += ( ( np.array( stdA_final[sat][chan].fillna(0) ) ** 2 ) + \n", " ( np.array( diff2 ) ** 2 ) ) * np.array( Ca_final[sat][chan].fillna(0) )\n", " \n", " varOMF_chan = np.array(somaVarF_chan) / np.array(soma_NF)\n", " varOMA_chan = np.array(somaVarA_chan) / np.array(soma_NA)\n", " \n", " \n", " df2_OMF[chan] = mediaOMF_chan\n", " df2_stdF[chan] = varOMF_chan #* varOMF_chan\n", " df2_qF[chan] = soma_NF\n", " \n", " df2_OMA[chan] = mediaOMA_chan\n", " df2_stdA[chan] = varOMA_chan #* varOMA_chan\n", " df2_qA[chan] = soma_NA\n", "\n", " \n", "# print(OMF_final[2][8])\n", "# print('')\n", "# print('OMF')\n", "# print(df2_OMF)\n", "\n", "# print('')\n", "# print('OMA')\n", "# print(df2_OMA)\n", "\n", "# print('')\n", "# print('stdF')\n", "# print(df2_stdF)\n", "\n", "# print('')\n", "# print('stdA')\n", "# print(df2_stdA)\n", "\n", "print('')\n", "print('qF')\n", "print(df2_qF)\n", "\n", "print('')\n", "print('qA')\n", "print(df2_qA)" ] }, { "cell_type": "code", "execution_count": 16, "id": "811e3323", "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "### Plotes\n", "import matplotlib as mpl\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import matplotlib.dates as mdates # Importante para formatar as datas\n", "\n", "### Quantidade total de microondas assimiladas nos canais do sensor\n", "\n", "# Criando um novo DataFrame para armazenar as somas dos canais de mesma frequência\n", "canais_freq = [4, 5, 6, 7, 9, 8, 10, 11, 12, 13, 14] # Canais AMSU-A de mesma frequencia do ATMS: ch_amsua = ch_atms + 1\n", "# canais = list(range(1, 16))\n", "\n", "# Aplique o mesmo índice nos dois\n", "df1_qF.index = pd.to_datetime(dates, format='%Y%m%d%H')\n", "df2_qF.index = pd.to_datetime(dates, format='%Y%m%d%H')\n", "\n", "# df_combinado = pd.to_datetime()\n", "df_combinado = pd.DataFrame(index=pd.to_datetime(dates, format='%Y%m%d%H'))\n", "\n", "# print(\"Índices do df1:\", df1_qF.index)\n", "# print(\"Índices do df2:\", df2_qF.index)\n", "\n", "# O loop vai de 5 até 10 inclusive (range(5, 11))\n", "for c in canais_freq:\n", " nome_canal = f'Ch {c} + {c+1}'\n", " # Soma a coluna 'c' do df1 com a coluna 'c+1' do df2\n", " # Soma tratando eventuais NaN originais como 0\n", " df_combinado[nome_canal] = df1_qF[c].add(df2_qF[c+1], fill_value=0)\n", " #df_combinado[nome_canal] = df1_qF[c] + df2_qF[c+1]\n", " \n", "# 2. Atribuindo o vetor 'dates' como o índice do DataFrame\n", "# Usar pd.to_datetime garante que o matplotlib entenda as datas e permita formatações futuras\n", "# Informe o formato exato: %Y (ano 4 dígitos), %m (mês), %d (dia), %H (hora)\n", "# df_combinado.index = pd.to_datetime(dates, format='%Y%m%d%H')\n", " \n", "df_combinado\n", "\n", "# 3. Criando o Heatmap\n", "fig, ax = plt.subplots(figsize=(14, 6))\n", "\n", "count_max = df_combinado.max().max()\n", "\n", "# Substitui TODOS os zeros por NaN no DataFrame inteiro\n", "df_combinado = df_combinado.replace(0, np.nan)\n", "\n", "ax.add_patch(\n", " mpl.patches.Rectangle(\n", " (-1, -1),\n", " (len(dates) + 1),\n", " (len(canais_freq) + 3),\n", " hatch=\"xxxxx\",\n", " color=\"black\",\n", " fill=False,\n", " snap=False,\n", " zorder=0,\n", " )\n", ")\n", "\n", "# Como o imshow espera uma matriz (linhas = canais, colunas = datas), \n", "# transpomos o DataFrame (.T)\n", "cax = ax.imshow(df_combinado.T, aspect='auto', cmap='gist_heat_r', origin='lower', \n", " vmin=0.0, vmax=np.max(count_max), zorder=1, interpolation='none')\n", "\n", "# Adicionando a barra de cores (colorbar)\n", "cbar = fig.colorbar(cax, ax=ax, orientation='horizontal', pad=0.18, shrink=1.0)\n", "cbar.set_label('Total Observations', fontsize=12)\n", "\n", "# Configurando o eixo Y (Canais)\n", "# Pegamos os nomes das colunas transpostas\n", "ax.set_yticks(range(len(df_combinado.columns)))\n", "ax.set_yticklabels(df_combinado.columns, fontsize=10)\n", "ax.set_ylabel('Channels AMSU-A + ATMS', fontsize=12)\n", "\n", "# Configurando o eixo X (Datas formatadas como mmddhh)\n", "# Como usamos imshow, mapeamos as posições numéricas do índice para as datas reais\n", "ax.set_xticks(range(len(df_combinado.index)))\n", "# ax.set_xticklabels(df_combinado.index.strftime('%m%d%H'), fontsize=10)\n", "ax.set_xticklabels(df_combinado.index.strftime('%d%H'), fontsize=10)\n", "\n", "# Rotaciona as datas para não embolarem\n", "plt.xticks(rotation=45)\n", "\n", "ax.set_xlabel('Date/Hour (MMDDHH)', fontsize=12)\n", "\n", "datefmt1 = dates[0]\n", "datefmt2 = dates[-1]\n", "date1 = datetime.strptime(str(datefmt1), \"%Y%m%d%H\")\n", "date2 = datetime.strptime(str(datefmt2), \"%Y%m%d%H\")\n", "date_title = str(date1.strftime(\"%d%b%Y %H%M\")) + ' - ' + str(date2.strftime(\"%d%b%Y %H%M\")) + ' GMT'\n", "plt.title(date_title, loc=\"right\", fontsize=12)\n", "\n", "\n", "plt.tight_layout()\n", "\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": null, "id": "ae5f8bd5", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 30, "id": "606365b5", "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "### Plotes\n", "import matplotlib as mpl\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import matplotlib.dates as mdates # Importante para formatar as datas\n", "\n", "### Quantidade total de microondas assimiladas nos canais do sensor\n", "\n", "# Criando um novo DataFrame para armazenar as somas dos canais de mesma frequência\n", "canais_freq = [4, 5, 6, 7, 9, 8, 10, 11, 12, 13, 14] # Canais AMSU-A de mesma frequencia do ATMS: ch_amsua = ch_atms + 1\n", "# canais = list(range(1, 16))\n", "\n", "# Aplique o mesmo índice nos dois\n", "df1_OMF.index = pd.to_datetime(dates, format='%Y%m%d%H')\n", "df2_OMF.index = pd.to_datetime(dates, format='%Y%m%d%H')\n", "\n", "# 3. Criando o Heatmap\n", "# fig, ax = plt.subplots(figsize=(14, 6))\n", "fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(14, 12), sharex=True, constrained_layout=True)\n", "\n", "v_max = 0.2 #df_combinado.fillna(0).max().max()\n", "v_min = -0.2 #df_combinado.fillna(0).min().min()\n", "\n", "# Substitui TODOS os zeros por NaN no DataFrame inteiro\n", "# df_combinado = df_combinado.replace(0, np.nan)\n", "\n", "ax1.add_patch(\n", " mpl.patches.Rectangle(\n", " (-1, -1),\n", " (len(dates) + 1),\n", " (len(canais_freq) + 3),\n", " hatch=\"xxxxx\",\n", " color=\"black\",\n", " fill=False,\n", " snap=False,\n", " zorder=0,\n", " )\n", ")\n", "\n", "ax2.add_patch(\n", " mpl.patches.Rectangle(\n", " (-1, -1),\n", " (len(dates) + 1),\n", " (len(canais_freq) + 3),\n", " hatch=\"xxxxx\",\n", " color=\"black\",\n", " fill=False,\n", " snap=False,\n", " zorder=0,\n", " )\n", ")\n", "\n", "# Como o imshow espera uma matriz (linhas = canais, colunas = datas), \n", "# transpomos o DataFrame (.T)\n", "df_combinado = df1_OMF\n", "cax1 = ax1.imshow(df_combinado.T, aspect='auto', cmap='seismic', origin='lower', \n", " vmin=v_min, vmax=np.max(v_max), zorder=1, interpolation='none')\n", "\n", "ax1.set_yticks(range(len(df_combinado.columns)))\n", "ax1.set_yticklabels(df_combinado.columns, fontsize=10)\n", "ax1.set_ylabel('Channels AMSU-A', fontsize=12)\n", "\n", "df_combinado = df2_OMF\n", "cax2 = ax2.imshow(df_combinado.T, aspect='auto', cmap='seismic', origin='lower', \n", " vmin=v_min, vmax=np.max(v_max), zorder=1, interpolation='none')\n", "\n", "ax2.set_yticks(range(len(df_combinado.columns)))\n", "ax2.set_yticklabels(df_combinado.columns, fontsize=10)\n", "ax2.set_ylabel('Channels ATMS', fontsize=12)\n", "\n", "\n", "# -------------------------------------------------------------\n", "# 3. Barra de Cores Compartilhada (abaixo de tudo)\n", "# -------------------------------------------------------------\n", "# Passamos ax=[ax1, ax2] para que o Matplotlib centralize a barra em relação aos dois gráficos\n", "cbar = fig.colorbar(cax2, ax=ax2, orientation='horizontal', pad=0.10, shrink=1.0)\n", "cbar.set_label('Global mean (OmF)', fontsize=12)\n", "\n", "# Configurando o eixo X (Datas formatadas como mmddhh)\n", "# Como usamos imshow, mapeamos as posições numéricas do índice para as datas reais\n", "ax2.set_xticks(range(len(df_combinado.index)))\n", "ax2.set_xticklabels(df_combinado.index.strftime('%d%H'), fontsize=10)\n", "\n", "# Rotaciona as datas para não embolarem\n", "plt.xticks(rotation=45)\n", "\n", "ax2.set_xlabel('Date/Hour (MMDDHH)', fontsize=12)\n", "\n", "datefmt1 = dates[0]\n", "datefmt2 = dates[-1]\n", "date1 = datetime.strptime(str(datefmt1), \"%Y%m%d%H\")\n", "date2 = datetime.strptime(str(datefmt2), \"%Y%m%d%H\")\n", "date_title = str(date1.strftime(\"%d%b%Y %H%M\")) + ' - ' + str(date2.strftime(\"%d%b%Y %H%M\")) + ' GMT'\n", "# plt.title(date_title, loc=\"right\", fontsize=12)\n", "ax1.set_title(date_title, loc=\"right\", fontsize=12)\n", "\n", "\n", "# plt.tight_layout()\n", "\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": 32, "id": "4edcca81", "metadata": {}, "outputs": [ { "data": { "image/png": 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qVGyxxRYxfvz4uOiii6JNmzYR8c0Fn0eMGBH77rtvTJ8+PU4//fTynKlTp8brr78eERG9evWK3r17l98nT548efLkyZMnT548efLkyZMnT548eVXNu+mmm+L//u//KnSW9aJeq+YGqLLrb5SUlCSFhYXJxIkTV1t/4sSJSWFhYXmjv6rBgwcngwcPXm25PHny5MmTJ0+ePHny5MmTJ0+ePHny5FU1b+7cua4ZnA0r2/oZM2bE9OnTY+rUqeX3TZ06NaZPnx4zZsyIESNGxKJFi8rvGzVqVAwaNCgGDRoUo0aNkidPnjx58uTJkydPnjx58uTJkydPnrwa5Y0cOTKyol6r5gZo5ZnBI0eOTEpKKl7HI0n+d72Ob1/HY9V1V72mR5L875of8uTJkydPnjx58uTJkydPnjx58uTJk1fdvGydGZzaMnjcuHE5P/1bnjx58uTJkydPnjx58uTJkydPnjx58iq7tG19SO1lIiZOnBhjx46NMWPGVFg+derU6NWrV/Tq1avCKd4REWPGjImxY8fG+PHjK5zivWjRohg/frw8efLkyZMnT548efLkyZMnT548efLk1SqvXtVr1dwArWzZ586dmyRJUuH07W+fyr3q6dur/ruk5H+neK/6b3ny5MmTJ0+ePHny5MmTJ0+ePHny5Mmrbt7IkSNdJqI+VHbK9WuvvZYMHjy4whdupTvvvDMZPHhw+RdupZKSkmTIkCHJkCFDyr9w8uTJkydPnjx58uTJkydPnjx58uTJk1fdvAkTJrhMBAAAAAAAdaReq+YGyGUi5MmTJ0+ePHny5MmTJ0+ePHny5MmT15DysnWZiEySJEmuC+lsKi4ujoKCgrj44ovjxz/+cUyfPj1OP/308vunTp0ar7/+ekRE9OrVK3r37l1+36hRo2KLLbaI8ePHx0UXXRRt2rSJiG8u+DxixIjYd9995cmTJ0+ePHny5MmTJ0+ePHny5MmTJ69aeUcffXQUFBREUVFR5OfnR72p16q5miZOnJgceOCBSZcuXZKISB599NEK95900klJRFS47b///tXaxsozg8eNG5cUFhaWN/CrGjx4cDJ48ODVlpeUlCSFhYXJxIkTK51dnjx58uTJkydPnjx58uTJkydPnjx58qqbV9n7nNWHBnXN4EWLFsX2228ft9566xrX6d+/f8ybN6/8Nnbs2Bpta+bMmTFjxowYMWJELFq0qHz5qFGjYtCgQTFo0KAYNWpUhdlGjBgRM2bMiOnTp8fUqVPL75s6dWpMnz5dnjx58uTJkydPnjx58uTJkydPnjx58mqVV6/qtWquhVjDmcGHHHJIrXK/3bKXlPzvGh2rXscjSf53zY9V11lp5brfvi6IPHny5MmTJ0+ePHny5MmTJ0+ePHny5FUn7+KLL87KmcGNrgwuKChIOnXqlGy++ebJ4MGDky+++OI7c5YsWZIUFRWV3+bMmbPaJ7akZO04nVyePHny5MmTJ0+ePHny5MmTJ0+ePHmNL2/u3Lnpu0zE9+nfv3/ce++9MX78+Lj22mtj4sSJMWDAgCgtLV3jY4YPHx4FBQXlt65du662zpgxY2Ls2LExfvz4CqdkL1q0KMaPHx9jx46NMWPGVHjM1KlTo1evXtGrV68Kp3jLkydPnjx58uTJkydPnjx58uTJkydPXnXyHn744ciKeq2aayEqOTP42z744IMkIpLnn39+jeus6czgCRMmJEmSVDiVu6Tkf6dvr/rvJEkqnL797VO5V82QJ0+ePHny5MmTJ0+ePHny5MmTJ0+evOrkTZgwwWUivq8MTpIk6dixY3LHHXdUOXflNYNHjhyZDB48uPyTvlJJSUkyZMiQZMiQIeVfuJVee+21ZPDgwRW+cCvdeeed8uTJkydPnjx58uTJkydPnjx58uTJk1ftvG+/z1l9aVSXifi2jz/+OL788svo0qVLrkcBAAAAAGjY6rVqrqaFCxcmb7zxRvLGG28kEZFcf/31yRtvvJF8+OGHycKFC5MLLrggmTJlSjJr1qzk+eefT3r16pVsttlmyZIlS6q8jZUtu8tEyJMnT548efLkyZMnT548efLkyZMnryHkZesyEZkkSZIc99HlJkyYEHvvvfdqy0866aS4/fbb49BDD4033ngjFixYEIWFhdGvX7+48sorY/3116/yNoqLi6OgoCCKiooiPz8/IiJGjRoVW2yxRYwfPz4uuuiiaNOmTUR8c8HnESNGxL777hvTp0+P008/vTxn6tSp8frrr0dERK9evaJ3797l98mTJ0+ePHny5MmTJ0+ePHny5MmTJ09eVfNuuumm+L//+78KnWW9qNequQGq7PobJSUlSWFhYTJx4sTV1p84cWJSWFhY3uivavDgwcngwYNXWy5Pnjx58uTJkydPnjx58uTJkydPnjx5Vc2bO3euawZnw8q2fsaMGTF9+vSYOnVq+X1Tp06N6dOnx4wZM2LEiBGxaNGi8vtGjRoVgwYNikGDBsWoUaPkyZMnT548efLkyZMnT548efLkyZMnr0Z5I0eOjKyo16q5AVp5ZvDIkSOTkpKK1/FIkv9dr+Pb1/FYdd1Vr+mRJP+75oc8efLkyZMnT548efLkyZMnT548efLkVTcvW2cGp7YMHjduXM5P/5YnT548efLkyZMnT548efLkyZMnT568yi5tWx9Se5mIiRMnxtixY2PMmDEVlk+dOjV69eoVvXr1qnCKd0TEmDFjYuzYsTF+/PgKp3gvWrQoxo8fL0+ePHny5MmTJ0+ePHny5MmTJ0+ePHm1yqtX9Vo1N0ArW/a5c+cmSZJUOH3726dyr3r69qr/Lin53yneq/5bnjx58uTJkydPnjx58uTJkydPnjx58qqbN3LkSJeJqA+VnXL92muvJYMHD67whVvpzjvvTAYPHlz+hVuppKQkGTJkSDJkyJDyL5w8efLkyZMnT548efLkyZMnT548efLkVTdvwoQJLhMBAAAAAEAdqdequQFymQh58uTJkydPnjx58uTJkydPnjx58uQ1pLxsXSYikyRJkutCOpuKi4ujoKAgLr744vjxj38c06dPj9NPP738/qlTp8brr78eERG9evWK3r17l983atSo2GKLLWL8+PFx0UUXRZs2bSLimws+jxgxIvbdd1958uTJkydPnjx58uTJkydPnjx58uTJq1be0UcfHQUFBVFUVBT5+flRb+q1am6AVp4ZPG7cuKSwsLC8gV/V4MGDk8GDB6+2vKSkJCksLEwmTpy42n0TJ06UJ0+ePHny5MmTJ0+ePHny5MmTJ0+evGrnVfY+Z/UhtdcMnjlzZsyYMSNGjBgRixYtKl8+atSoGDRoUAwaNChGjRpVvnxlWz9jxoyYPn16TJ06tfy+qVOnxvTp0+XJkydPnjx58uTJkydPnjx58uTJkyevVnn1ql6r5gbo2y17Scn/rtGx6nU8kuR/1/xYdZ2VVq777euCyJMnT548efLkyZMnT548efLkyZMnT1518i6++OKsnBmc+jI4Sdae08nlyZMnT548efLkyZMnT548efLkyZPX+PLmzp3rDeTqw8o3kJs2rSjWWaceL8YMlGvbNtcTQLq0bJnrCSBdlizJ9QSQLtOm5XoCSJd27XI9AaRDSUlx7LZb/b+BXGqvGQwAAAAAkCbKYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACymAAAAAAgBRQBgMAAAAApIAyGAAAAAAgBZTBAAAAAAAp0KDK4JdeeikOOuigKCwsjEwmE4899tga1x08eHBkMpm48cYbszYfAAAAAEBj1aDK4EWLFsX2228ft95663eu9+ijj8bLL78chYWFWZoMAAAAAKBxa5brAVY1YMCAGDBgwHeu88knn8Q555wTzzzzTBxwwAFZmgwAAAAAoHFrUGcGf5+ysrI44YQT4sILL4ytt9461+MAAAAAADQaDerM4O9z7bXXRrNmzeLcc8+t8mOWLl0aS5cuLf+4uLi4PkYDAAAAAGjQGs2ZwVOnTo2RI0fG6NGjI5PJVPlxw4cPj4KCgvJb165d63FKAAAAAICGqdGUwX//+9/js88+i27dukWzZs2iWbNm8eGHH8aQIUOie/fua3zc0KFDo6ioqPw2Z86c7A0NAAAAANBANJrLRJxwwgnRt2/fCsv233//OOGEE+KUU05Z4+Py8vIiLy+vvscDAAAAAGjQGlQZXFJSEu+//375x7NmzYo333wzOnToEN26dYt11123wvrNmzePzp07xxZbbJHtUQEAAAAAGpUGVQa/9tprsffee5d/fP7550dExEknnRSjR4/O0VQAAAAAAI1fgyqD99prr0iSpMrrz549u/6GAQAAAABYizSaN5ADAAAAAKDmlMEAAAAAACmgDAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACymAAAAAAgBRQBgMAAAAApIAyGAAAAAAgBZTBAAAAAAApoAwGAAAAAEgBZTAAAAAAQAoogwEAAAAAUqBZrgfIla7rL4v8/GW5HgMA6tzcL1rkegRIlZYtcz0BpEv37rmeANJlww1zPQGkQ3FxdrbjzGAAAAAAgBRQBgMAAAAApIAyGAAAAAAgBZTBAAAAAAApoAwGAAAAAEgBZTAAAAAAQAoogwEAAAAAUkAZDAAAAACQAspgAAAAAIAUUAYDAAAAAKSAMhgAAAAAIAWUwQAAAAAAKaAMBgAAAABIAWUwAAAAAEAKNKgy+KWXXoqDDjooCgsLI5PJxGOPPVbh/ssvvzy23HLLaNOmTbRv3z769u0br7zySm6GBQAAAABoRBpUGbxo0aLYfvvt49Zbb630/s033zxuueWWeOedd2LSpEnRvXv36NevX3z++edZnhQAAAAAoHHJJEmS5HqIymQymXj00Ufj0EMPXeM6xcXFUVBQEM8//3zsu+++Vcpd+Ziizz+P/Pz8OpoWABqOuV+0yPUIkCotW+Z6AkiXkpJcTwDpsuGGuZ4A0qG4uDjaty+IoqKieu0sm9Vbcj1btmxZ3HnnnVFQUBDbb7/9GtdbunRpLF26tPzj4uLibIwHAAAAANCgNKjLRFTFk08+GW3bto2WLVvGDTfcEM8991x07NhxjesPHz48CgoKym9du3bN4rQAAAAAAA1DoyuD995773jzzTdj8uTJ0b9//zjqqKPis88+W+P6Q4cOjaKiovLbnDlzsjgtAAAAAEDD0OjK4DZt2sSmm24aO++8c9x1113RrFmzuOuuu9a4fl5eXuTn51e4AQAAAACkTaMrg7+trKyswjWBAQAAAABYXYN6A7mSkpJ4//33yz+eNWtWvPnmm9GhQ4dYd9114+qrr46DDz44unTpEl988UXceuut8cknn8SRRx6Zw6kBAAAAABq+BlUGv/baa7H33nuXf3z++edHRMRJJ50Ud9xxR/z73/+Oe+65J7744otYd91140c/+lH8/e9/j6233jpXIwMAAAAANAoNqgzea6+9IkmSNd7/yCOPZHEaAAAAAIC1R6O/ZjAAAAAAAN9PGQwAAAAAkALKYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACymAAAAAAgBRQBgMAAAAApIAyGAAAAAAgBZrlegAgBUpKcj0BpEphu5a5HgEA6k0HP+Ygu77w+xxkQ5OFC7OznaxsBQAAAACAnFIGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACymAAAAAAgBRQBgMAAAAApIAyGAAAAAAgBZTBAAAAAAApoAwGAAAAAEiBOimDly1bFn//+9/joYceirfeeqvGOS+99FIcdNBBUVhYGJlMJh577LHy+5YvXx4XX3xxbLvtttGmTZsoLCyME088MebOnVsHzwAAAAAAYO1W5TL4mWeeiVNPPTW++OKLCsv//e9/xzbbbBN77bVXHHPMMdGrV6844ogjYsWKFdUeZtGiRbH99tvHrbfeutp9ixcvjtdffz0uvfTSeP311+ORRx6J6dOnx8EHH1zt7QAAAAAApE2zqq74xz/+Md5///3o2LFjheXHHXdcvP/++3HSSSfFD3/4wxg3blw8+uijcfPNN8fPf/7zag0zYMCAGDBgQKX3FRQUxHPPPVdh2S233BI77rhjfPTRR9GtW7dqbQsAAAAAIE2qfGbwa6+9Fn379q2w7I033og33ngjjjvuuLj77rvj7LPPjr/97W/Rp0+feOCBB+p82G8rKiqKTCYT7dq1q/dtAQAAAAA0ZlUugz/99NPYdNNNKyx7+umnI5PJxMknn1xh+aGHHhrTp0+vkwHXZMmSJXHxxRfHMcccE/n5+Wtcb+nSpVFcXFzhBgAAAACQNlUug9u2bRuLFy+usGzSpEnRpEmT2GmnnSosb9euXZSWltbNhJVYvnx5HHXUUZEkSdx+++3fue7w4cOjoKCg/Na1a9d6mwsAAAAAoKGqchn8gx/8IP7617+Wfzx//vx46aWXYtddd422bdtWWHfOnDnRuXPnuptyFSuL4A8//DCee+657zwrOCJi6NChUVRUVH6bM2dOvcwFAAAAANCQVfkN5IYMGRKHHHJIDBgwIHbdddd44oknYvHixXHWWWettu7TTz8dPXv2rNNBI/5XBM+cOTNefPHFWHfddb/3MXl5eZGXl1fnswAAAAAANCZVLoMPOuigGDFiRFx11VXxzDPPRKtWreLSSy+No48+usJ6L7/8crz88svxhz/8odrDlJSUxPvvv1/+8axZs+LNN9+MDh06RJcuXeKII46I119/PZ588skoLS2NTz/9NCIiOnToEC1atKj29gAAAAAA0iKTJElSnQeUlpbGF198Eeutt15kMpnV7v/6669j8eLF0a5du2jatGm1hpkwYULsvffeqy0/6aST4vLLL48ePXpU+rgXX3wx9tprrypto7i4OAoKCqLo88+/9xITQB0pKcn1BJAuLVvmegIAANYWfp+DrCheuDAKNt00ioqK6rWzrPKZwSs1bdo01l9//TXe36pVq2jVqlWNhtlrr73iu7rpavbWAAAAAAD8f1Uug7/66qtqh3fo0KHajwEAAAAAoO5VuQzu1KlTtcNLS0ur/RgAAAAAAOpelcvgJEmiVatWccABB8TWW29dnzMBAAAAAFDHqlwGDx06NB588MH485//HDNmzIhjjz02jjnmmOjatWt9zgcAAAAAQB1oUtUVr7766vjggw9i0qRJ0adPn/jd734XPXr0iD322CN+//vf1+iawgAAAAAAZEeVy+CVdt1117jlllti7ty58fjjj0e3bt3iggsuiC5dusRBBx0Ur7zySn3MCQAAAABALVS7DF6padOm8eMf/zjuv//+ePfdd2O33XaLcePGxTPPPFOX8wEAAAAAUAeqfM3gb1u8eHE89thjMXbs2HjuueeiRYsWcdxxx8Whhx5ah+MBAAAAAFAXqlUGr1ixIp566qkYM2ZMPPHEE7FixYro379/3HvvvXHwwQdHy5Yt62tOAAAAAABqocpl8BlnnBF/+ctfori4OPbYY4+48cYb44gjjoh27drV43gAAAAAANSFTJIkSVVWbNKkSbRq1Sr69+8fG2ywwfcHZzIxcuTIWg9Y14qLi6OgoCCKPv888vPzcz0OpENJSa4ngHTxlzoAANQVv89BVhQvXBgFm24aRUVF9dpZVqsMrlZwJhOlpaU1Gqo+KYMhB7x4gOxSBgMAUFf8PgdZka0yuMqXiSgrK6u3IQAAAAAAqF9VLoPvvffe2GOPPaJ79+71OE4WNWv2zQ2od8vadsj1CJAqLZYU53oESJXFzfy1GWRT61ic6xEgXTp2zPUEkA4tWmRlM1W+9sMpp5wSkydPrs9ZAAAAAACoJ1Uug6t4aWEAAAAAABqg6r0rHAAAAAAAjVK1Lpr75ZdfxkcffVTl9bt161btgQAAAAAAqHuZpIrXf2jSpElkMplqhZeWltZoqPpUXFwcBQUFUTR/fuTne7MPyIZlK/wRAmSTN5CD7PIGcpBd3kAOsqxly1xPAKlQXFwcBe3bR1FRUb12ltU6M3jgwIHRq1ev+poFAAAAAIB6Uq0y+IADDohjjz22vmYBAAAAAKCe+NttAAAAAIAUqLcyeP78+fUVDQAAAABANVW5DN5oo42ibdu237nO0qVL4+GHH45DDz00unTpUuvhAAAAAACoG1W+ZvCsWbMqXZ4kSYwfPz4eeOCBePTRR6O4uDg6derk2sIAAAAAAA1Itd5AblVTp06NBx54IB588MH49NNPI5PJxMCBA+NnP/tZ7LzzzpHJZOpyTgAAAAAAaqFaZfB//vOfeOCBB+KBBx6ImTNnxgYbbBDHHXdc7LjjjnH00UfHT37yk9hll13qa1YAAAAAAGqoymXwLrvsEv/85z+jY8eOccQRR8Qf/vCH6NOnT0REfPDBB/U2IAAAAAAAtVflN5B75ZVXonv37nHnnXfGyJEjy4vguvTSSy/FQQcdFIWFhZHJZOKxxx6rcP8jjzwS/fr1i3XXXTcymUy8+eabdT4DAAAAAMDaqMpl8C233BJdunSJww47LDp37hxnnnlmvPjii5EkSZ0Ns2jRoth+++3j1ltvXeP9ffr0iWuvvbbOtgkAAAAAkAZVvkzEWWedFWeddVbMmjUrHnjggRgzZkyMGjUqOnfuHHvvvXdkMplav2ncgAEDYsCAAWu8/4QTToiIiNmzZ9dqOwAAAAAAaVPlM4NX6tGjR/zqV7+Kd999N1599dUYOHBgTJgwIZIkibPOOivOOOOMePLJJ2PJkiX1MW+1LV26NIqLiyvcAAAAAADSptpl8Kp69+4d119/fcyZMyeeffbZ2H///eNPf/pTHHzwwdGxY8e6mrFWhg8fHgUFBeW3rl275nokAAAAAICsq1UZXB7SpEn07ds3Ro8eHf/9739j7Nixse+++9ZFdK0NHTo0ioqKym9z5szJ9UgAAAAAAFlX5WsGV1XLli3j6KOPjqOPPrquo2skLy8v8vLycj0GAAAAAEBO1cmZwQAAAAAANGx1fmZwbZSUlMT7779f/vGsWbPizTffjA4dOkS3bt3iq6++io8++ijmzp0bERHTp0+PiIjOnTtH586dczIzAAAAAEBj0KDODH7ttdeiZ8+e0bNnz4iIOP/886Nnz55x2WWXRUTE448/Hj179owDDjggIiIGDhwYPXv2jDvuuCNnMwMAAAAANAaZJEmSXA+RTcXFxVFQUBBF8+dHfn5+rseBVFi2okH9fydY67VYUpzrESBVFjfzmhKyqXUszvUIkC4tW+Z6AkiF4uLiKGjfPoqKiuq1s9TQAAAAAACkQI3K4DfffDPGjh1bYdkzzzwTe+yxR+y0004xcuTIOhkOAAAAAIC6UaMy+KKLLoo//elP5R/PmjUrDjvssJg1a1ZEfHOt3zvvvLNuJgQAAAAAoNZqVAa/9dZb0adPn/KP77333mjatGm88cYb8corr8QRRxzhTd0AAAAAABqQGpXBRUVFse6665Z/PG7cuNhvv/2iY8eOERGx3377xfvvv183EwIAAAAAUGs1KoO7dOkS7733XkREzJs3L6ZOnRr9+vUrv7+kpCSaNPHedAAAAAAADUWzmjzokEMOiZtvvjmWLFkSr7zySuTl5cVhhx1Wfv9bb70VG2+8cZ0NCQAAAABA7dSoDL7qqqvi888/j/vuuy/atWsXo0ePjvXXXz8iIoqLi+PPf/5znH322XU6KAAAAAAANVejMrht27bxwAMPrPG+jz/+OFq3bl2rwQAAAAAAqDs1KoO/S5MmTaKgoKCuYwEAAAAAqIUqlcG//vWvqx2cyWTi0ksvrfbjAAAAAACoe5kkSZLvW6lJkybVD85korS0tEZD1afi4uIoKCiIovnzIz8/P9fjQCosW1H97yFAzbVYUpzrESBVFjfzmhKyqXUszvUIkC4tW+Z6AkiF4uLiKGjfPoqKiuq1s6zSmcFlZWX1NgAAAAAAAPWvzq8Z3GgsWRLRokWup4BUaNbSG0pCVrVtm+sJIFWcLwVZtiK9v8ZCLpSFv/SEbMjWsVarn6KffPJJvPTSS/HZZ5/FT37yk9hwww2jtLQ0ioqKoqCgIJo2bVpXcwIAAAAAUAs1qpyTJInzzz8/evToEccdd1ycf/75MWPGjIiIKCkpie7du8fNN99cp4MCAAAAAFBzNSqDr7vuuhg5cmRccMEF8dxzz8Wq70FXUFAQhx9+ePzlL3+psyEBAAAAAKidGpXBo0aNihNPPDF+85vfxA477LDa/dttt135mcIAAAAAAORejcrgOXPmxK677rrG+9u0aRPFxcU1HgoAAAAAgLpVozJ4vfXWizlz5qzx/qlTp0a3bt1qPBQAAAAAAHWrRmXw4YcfHnfccUf85z//KV+WyWQiIuLZZ5+N0aNHx5FHHlk3EwIAAAAAUGuZZNV3f6uioqKi2GOPPWLWrFmx++67x9NPPx377bdflJSUxJQpU6Jnz57x0ksvRevWretj5lopLi6OgoKCKJo3L/Lz83M9DqRCWcuG970A1mZNoizXI0CqlNXs/AqghpqsWJbrESBVypq1yPUIkArFxcXRvn1BFBUV1WtnWaNXrgUFBfHyyy/HRRddFJ988km0bNkyJk6cGAsWLIhhw4bF3//+9wZZBAMAAAAApFWNzgxuzJwZDNnnzGDILmcGQ3Y5Mxiyy5nBkF3ODIbsaNBnBgMAAAAA0Lg0q+kD33vvvbj77rvjP//5T8yfPz++fYJxJpOJ8ePH13pAAAAAAABqr0Zl8H333RennHJKNG/ePLbYYoto3779auuk7OoTAAAAAAANWo3K4Msvvzx69uwZTz31VHTs2LHOhnnppZfiuuuui6lTp8a8efPi0UcfjUMPPbT8/iRJYtiwYTFq1KhYsGBB7LbbbnH77bfHZpttVmczAAAAAACsjWp0zeC5c+fGqaeeWqdFcETEokWLYvvtt49bb7210vtHjBgRN910U9xxxx3xyiuvRJs2bWL//fePJUuW1OkcAAAAAABrmxqdGbzddtvF3Llz63qWGDBgQAwYMKDS+5IkiRtvvDF+9atfxSGHHBIREffee2+sv/768dhjj8XAgQPrfB4AAAAAgLVFjc4Mvv766+Ouu+6KyZMn1/U8azRr1qz49NNPo2/fvuXLCgoKYqeddoopU6as8XFLly6N4uLiCjcAAAAAgLSp0ZnB1157bRQUFMTuu+8eW221VXTr1i2aNm1aYZ1MJhN//etf62TIiIhPP/00IiLWX3/9CsvXX3/98vsqM3z48LjiiivqbA4AAAAAgMaoRmXw22+/HZlMJrp16xYlJSXx7rvvrrZOJpOp9XB1YejQoXH++eeXf1xcXBxdu3bN4UQAAAAAANlXozJ49uzZdTzG9+vcuXNERPz3v/+NLl26lC//73//GzvssMMaH5eXlxd5eXn1PR4AAAAAQINWo2sG50KPHj2ic+fOMX78+PJlxcXF8corr8Quu+ySw8kAAAAAABq+Gp0ZvNLChQvjww8/jPnz50eSJKvdv8cee1Qrr6SkJN5///3yj2fNmhVvvvlmdOjQIbp16xbnnXdeXHXVVbHZZptFjx494tJLL43CwsI49NBDa/M0AAAAAADWejUqg7/88sv42c9+Fn/5y1+itLR0tfuTJIlMJlPpfd/ltddei7333rv845XX+j3ppJNi9OjRcdFFF8WiRYvijDPOiAULFkSfPn3i6aefjpYtW9bkaQAAAAAApEYmqeyU3u9x+OGHxxNPPBHnnntu7L777tG+fftK19tzzz1rPWBdKy4ujoKCgiiaNy/y8/NzPQ6kQlnL1rkeAVKlSZTlegRIlbLGc+U1WCs0WbEs1yNAqpQ1a5HrESAViouLo337gigqKqrXzrJGZwY/++yz8fOf/zxGjBhR1/MAAAAAAFAPanQaQ+vWraN79+51PAoAAAAAAPWlRmXw8ccfH48++mhdzwIAAAAAQD2p0WUijjjiiJg4cWL0798/zjjjjOjatWs0bdp0tfV69epV6wEBAAAAAKi9GpXBffr0Kf/3c889t9r9SZJEJpOJ0tLSmk8GAAAAAECdqVEZfPfdd9f1HAAAAAAA1KMalcEnnXRSXc8BAAAAAEA9qtEbyAEAAAAA0LjU6MzgiIglS5bEX/7yl3j99dejqKgoysrKKtyfyWTirrvuqvWAAAAAAADUXo3K4A8//DD23nvvmD17drRr1y6KioqiQ4cOsWDBgigtLY2OHTtG27Zt63pWAAAAAABqqEaXibjwwgujqKgoXn755ZgxY0YkSRJ/+tOfoqSkJK699tpo1apVPPPMM3U9KwAAAAAANVSjMviFF16Is846K3bcccdo0uSbiCRJIi8vLy688MLYd99947zzzqvLOQEAAAAAqIUalcGLFy+O7t27R0REfn5+ZDKZKCoqKr9/l112iUmTJtXJgAAAAAAA1F6NrhncrVu3+Pjjj78JaNYsNthgg3j55Zfj8MMPj4iId999N1q2bFl3U9aHZs2+uQH1bsmSXE8A6dK6gf8IhrXNggW5ngDSpWXLFrkeAVKlpeoE1io1OqT32Wef+Otf/xrDhg2LiIiTTz45hg8fHvPnz4+ysrK477774sQTT6zTQQEAAAAAqLkalcGXXHJJvPrqq7F06dLIy8uLX/ziFzF37tz485//HE2bNo1jjz02rr/++rqeFQAAAACAGsokSZLkeohsKi4ujoKCgij6/PPIz8/P9TiQCotX+FM+yKbWLctyPQKkylcLavQ2HEANNfQrEsLaxjEH2VFcXBzt2xdEUVFRvXaWXrkCAAAAAKRAjS8DPn/+/Bg7dmz85z//ifnz58e3TzDOZDJx11131XpAAAAAAABqr0Zl8DPPPBNHHHFELFq0KPLz86N9+/arrZPJZGo9HAAAAAAAdaNGZfCQIUOic+fO8cgjj8S2225b1zMBAAAAAFDHanTN4Pfffz/OPfdcRTAAAAAAQCNRozJ4s802i4ULF9b1LAAAAAAA1JMalcFXXXVV3HbbbTF79uw6HgcAAAAAgPpQpWsGn3vuuast69SpU/zgBz+I/fbbL7p27RpNmzatcH8mk4mRI0fWzZQAAAAAANRKJkmS5PtWatKk+icQZzKZKC0trdFQ9am4uDgKCgqi6PPPIz8/P9fjQCosXtEi1yNAqrRuWZbrESBVvlpQoz+2A2qoZctcTwDp4piD7CguLo727QuiqKioXjvLKp0ZXFbml0oAAAAAgMas0Z3GsHDhwjjvvPNio402ilatWsWuu+4ar776aq7HAgAAAABo0KpcBi9ZsiQGDx4cN99883eud9NNN8VPf/rTWL58ea2Hq8ygQYPiueeei/vuuy/eeeed6NevX/Tt2zc++eSTetkeAAAAAMDaoMpl8J133hmjR4+OAw444DvXO+CAA+Luu++OP/zhD7Ue7tu+/vrr+Mtf/hIjRoyIPfbYIzbddNO4/PLLY9NNN43bb7+9zrcHAAAAALC2qHIZ/NBDD8VPfvKT2Hjjjb9zvU022SSOPPLIGDt2bK2H+7YVK1ZEaWlptPzW1ctbtWoVkyZNqvPtAQAAAACsLapcBr/zzjvRp0+fKq276667xttvv13jodZknXXWiV122SWuvPLKmDt3bpSWlsb9998fU6ZMiXnz5lX6mKVLl0ZxcXGFGwAAAABA2lS5DF62bFm0aNGiSuu2aNEili5dWuOhvst9990XSZLEBhtsEHl5eXHTTTfFMcccE02aVP5Uhg8fHgUFBeW3rl271stcAAAAAAANWZXL4MLCwpg2bVqV1p02bVoUFhbWeKjvsskmm8TEiROjpKQk5syZE//85z9j+fLla7x8xdChQ6OoqKj8NmfOnHqZCwAAAACgIatyGdy3b9+4995747PPPvvO9T777LO49957Y7/99qv1cN+lTZs20aVLl5g/f34888wzccghh1S6Xl5eXuTn51e4AQAAAACkTZXL4IsvvjiWLFkS++yzT7zyyiuVrvPKK6/EvvvuG0uWLIkLL7ywzoZc1TPPPBNPP/10zJo1K5577rnYe++9Y8stt4xTTjmlXrYHAAAAALA2aFbVFTfeeON46KGH4phjjoldd901Nt5449h2221jnXXWiYULF8a0adPigw8+iNatW8eDDz4Ym2yySb0MXFRUFEOHDo2PP/44OnToED/5yU/i6quvjubNm9fL9gAAAAAA1gaZJEmS6jxg9uzZce2118aTTz4Zn3zySfnywsLCOPDAA+Oiiy5a4/V7G4Li4uIoKCiIos8/d8kIyJLFK6r25pNA3WjdsizXI0CqfLWgyn9sB9SBli1zPQGki2MOsqO4uDjaty+IoqKieu0sq10Gr2rhwoVRXFwc+fn5sc4669TlXPVGGQzZpwyG7FIGQ3YpgyG7FFOQXY45yI5slcFVvkxEZdZZZ51GUwIDAAAAAKSZ0xgAAAAAAFJAGQwAAAAAkALKYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACymAAAAAAgBRolusBcqZZs29uQP1bkesBAKD+eEkJ2dV6RXGuR4BUWbYiP9cjQCqsyFJ34sxgAAAAAIAUUAYDAAAAAKSAMhgAAAAAIAWUwQAAAAAAKaAMBgAAAABIAWUwAAAAAEAKKIMBAAAAAFJAGQwAAAAAkALKYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACjSqMri0tDQuvfTS6NGjR7Rq1So22WSTuPLKKyNJklyPBgAAAADQoDXL9QDVce2118btt98e99xzT2y99dbx2muvxSmnnBIFBQVx7rnn5no8AAAAAIAGq1GVwZMnT45DDjkkDjjggIiI6N69e4wdOzb++c9/5ngyAAAAAICGrVFdJmLXXXeN8ePHx4wZMyIi4q233opJkybFgAED1viYpUuXRnFxcYUbAAAAAEDaNKozgy+55JIoLi6OLbfcMpo2bRqlpaVx9dVXx3HHHbfGxwwfPjyuuOKKLE4JAAAAANDwNKozgx966KF44IEHYsyYMfH666/HPffcE7/97W/jnnvuWeNjhg4dGkVFReW3OXPmZHFiAAAAAICGoVGdGXzhhRfGJZdcEgMHDoyIiG233TY+/PDDGD58eJx00kmVPiYvLy/y8vKyOSYAAAAAQIPTqM4MXrx4cTRpUnHkpk2bRllZWY4mAgAAAABoHBrVmcEHHXRQXH311dGtW7fYeuut44033ojrr78+Tj311FyPBgAAAADQoDWqMvjmm2+OSy+9NM4666z47LPPorCwMM4888y47LLLcj0aAAAAAECDlkmSJMn1ENlUXFwcBQUFUTR/fuTn5+d6HEiFxUsa1RVpoNFr3dLlkyCbikv8nINsyo/iXI8AqbKspe4EsqG4uDg6dSqIoqKieu0svXIFAAAAAEgBZTAAAAAAQAoogwEAAAAAUkAZDAAAAACQAspgAAAAAIAUUAYDAAAAAKSAMhgAAAAAIAWUwQAAAAAAKaAMBgAAAABIAWUwAAAAAEAKKIMBAAAAAFJAGQwAAAAAkALKYAAAAACAFGiW6wGAtV/LlrmeAADqT37bslyPAOlSkusBAKDxcmYwAAAAAEAKKIMBAAAAAFJAGQwAAAAAkALKYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACymAAAAAAgBRQBgMAAAAApECjK4O7d+8emUxmtdvZZ5+d69EAAAAAABqsZrkeoLpeffXVKC0tLf942rRpsd9++8WRRx6Zw6kAAAAAABq2RlcGd+rUqcLH11xzTWyyySax55575mgiAAAAAICGr9FdJmJVy5Yti/vvvz9OPfXUyGQyuR4HAAAAAKDBanRnBq/qscceiwULFsTJJ5+8xnWWLl0aS5cuLf+4uLg4C5MBAAAAADQsjfrM4LvuuisGDBgQhYWFa1xn+PDhUVBQUH7r2rVrFicEAAAAAGgYGm0Z/OGHH8bzzz8fgwYN+s71hg4dGkVFReW3OXPmZGlCAAAAAICGo9FeJuLuu++O9dZbLw444IDvXC8vLy/y8vKyNBUAAAAAQMPUKM8MLisri7vvvjtOOumkaNas0fbZAAAAAABZ0yjL4Oeffz4++uijOPXUU3M9CgAAAABAo9AoT6vt169fJEmS6zEAAAAAABqNRnlmMAAAAAAA1aMMBgAAAABIAWUwAAAAAEAKKIMBAAAAAFJAGQwAAAAAkALKYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACzXI9QM5MmRLRpk2up4BUaLLzzrkeAVLl19e0yPUIkCoXXJDrCSBdJr2cn+sRIFX6dX471yNAKrQoKcnKdpwZDAAAAACQAspgAAAAAIAUUAYDAAAAAKSAMhgAAAAAIAWUwQAAAAAAKaAMBgAAAABIAWUwAAAAAEAKKIMBAAAAAFJAGQwAAAAAkALKYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASIFGVwZ/8skncfzxx8e6664brVq1im233TZee+21XI8FAAAAANCgNcv1ANUxf/782G233WLvvfeOp556Kjp16hQzZ86M9u3b53o0AAAAAIAGrVGVwddee2107do17r777vJlPXr0yOFEAAAAAACNQ6O6TMTjjz8eP/zhD+PII4+M9dZbL3r27BmjRo36zscsXbo0iouLK9wAAAAAANKmUZXB//nPf+L222+PzTbbLJ555pn46U9/Gueee27cc889a3zM8OHDo6CgoPzWtWvXLE4MAAAAANAwNKoyuKysLHr16hW/+c1vomfPnnHGGWfE6aefHnfccccaHzN06NAoKioqv82ZMyeLEwMAAAAANAyNqgzu0qVLbLXVVhWW/eAHP4iPPvpojY/Jy8uL/Pz8CjcAAAAAgLRpVGXwbrvtFtOnT6+wbMaMGbHRRhvlaCIAAAAAgMahUZXBP//5z+Pll1+O3/zmN/H+++/HmDFj4s4774yzzz4716MBAAAAADRojaoM/tGPfhSPPvpojB07NrbZZpu48sor48Ybb4zjjjsu16MBAAAAADRozXI9QHUdeOCBceCBB+Z6DAAAAACARqVRnRkMAAAAAEDNKIMBAAAAAFJAGQwAAAAAkALKYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACymAAAAAAgBRQBgMAAAAApECzXA+QK59ttlt8vU5+rseAVHjgllxPAOkydmyuJ4B02WabXE8A6TJhQq4ngHTZ+artcj0CpEJxcXFWtuPMYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACymAAAAAAgBRQBgMAAAAApIAyGAAAAAAgBZTBAAAAAAApoAwGAAAAAEiBRlcGX3755ZHJZCrcttxyy1yPBQAAAADQoDXL9QA1sfXWW8fzzz9f/nGzZo3yaQAAAAAAZE2jbFGbNWsWnTt3zvUYAAAAAACNRqO7TERExMyZM6OwsDA23njjOO644+Kjjz5a47pLly6N4uLiCjcAAAAAgLRpdGXwTjvtFKNHj46nn346br/99pg1a1bsvvvusXDhwkrXHz58eBQUFJTfunbtmuWJAQAAAAByr9GVwQMGDIgjjzwytttuu9h///1j3LhxsWDBgnjooYcqXX/o0KFRVFRUfpszZ06WJwYAAAAAyL1Gec3gVbVr1y4233zzeP/99yu9Py8vL/Ly8rI8FQAAAABAw9Lozgz+tpKSkvjggw+iS5cuuR4FAAAAAKDBanRl8AUXXBATJ06M2bNnx+TJk+Owww6Lpk2bxjHHHJPr0QAAAAAAGqxGd5mIjz/+OI455pj48ssvo1OnTtGnT594+eWXo1OnTrkeDQAAAACgwWp0ZfCDDz6Y6xEAAAAAABqdRneZCAAAAAAAqk8ZDAAAAACQAspgAAAAAIAUUAYDAAAAAKSAMhgAAAAAIAWUwQAAAAAAKaAMBgAAAABIAWUwAAAAAEAKKIMBAAAAAFJAGQwAAAAAkALKYAAAAACAFFAGAwAAAACkQLNcD5BtSZJERMTChcU5ngTSY8mSXE8A6VJamusJIF0WL871BJAuy5blegJIl2L1CWTFyq5yZXdZXzJJfW+hgfn444+ja9euuR4DAAAAAKCCOXPmxIYbblhv+akrg8vKymLu3LmxzjrrRCaTyfU4VFFxcXF07do15syZE/n5+bkeB9Z6jjnILsccZJdjDrLLMQfZ5ZhrnJIkiYULF0ZhYWE0aVJ/V/ZN3WUimjRpUq/tOvUrPz/fNzLIIsccZJdjDrLLMQfZ5ZiD7HLMNT4FBQX1vg1vIAcAAAAAkALKYAAAAACAFFAG0yjk5eXFsGHDIi8vL9ejQCo45iC7HHOQXY45yC7HHGSXY47vkro3kAMAAAAASCNnBgMAAAAApIAyGAAAAAAgBZTBAAAAAAApoAwGAAAAAEgBZTBrDe+FCNnnuANgbeNnGwBp4OddeimDafRKS0sjIqKsrCwifEOD+jZ//vz46KOPYvbs2ZHJZHI9Dqz1vv1zzc85qD+zZs2Khx9+OIqKinI9CgDUueLi4pg/f358+umnkclkynsU0kUZTKM2Y8aMuPjii+PQQw+NX/3qV/Gvf/1LOQX1aNq0abHffvvFAQccEJtuumncdddduR4J1mrTp0+PYcOGxcknnxx/+MMf4t///rcX7lBP3n777dhxxx3jjTfeiM8//zwiwrEG9ej999+P3/zmN3HSSSfFH/7wh5g9e3auR4K12r/+9a848MADY999943tttsunn322WjSRC2YRpnE6SU0UtOmTYu99torDjrooCgqKoqFCxdGs2bN4p577on11lsv1+PBWmfGjBnRp0+fOO2002L//fePv//97/Hb3/42Pvjgg+jYsWMkSeJ/xkAdevfdd2PXXXeNvn37xrx586K0tDQ++eSTGD16dOy7776OOahDc+bMiT59+sSRRx4Zv/3tb8uXL1u2LFq0aBFlZWV+YYY6NG3atNhnn31i7733jjlz5sSKFSuid+/e8dvf/jbatGmT6/FgrfPvf/87+vTpE6eeemr07NkzJkyYEC+++GK89tprkZ+f73VlyjTL9QBQE3Pnzo0TTjghBg0aFNdcc01ERDzxxBMxZMiQ+OSTT5TBUMeSJIlbbrkl9tprrxg+fHhERHTu3DleeeWVKCkpic8//zw222yzaNbMjxWoC6WlpTF8+PA48MAD4/7774+IiDfffDNuueWW2H///eOvf/1rHHDAAQoqqCOTJ0+OjTfeOH77299GWVlZXHbZZfHBBx/EsmXL4uyzz4599tkn1yPCWmPOnDlx9NFHx2mnnVb+uvK2226L3/3ud1FUVKQMhjq2YsWKGD58eBxwwAExYsSIiIjo1KlTfPHFF1FaWhoff/xxbLjhhjmekmzy2wON0muvvRZdunSJU045pfzP9w466KDIy8uLt99+OyJcUxHqUllZWcyaNSvatWtXvuzPf/5zjB8/Pg4++ODo2bNn/PSnP405c+bkbkhYi5SVlcWcOXOia9eu5ct22GGHGD58eJxxxhlxxBFHxMsvv6wIhjoyZ86cKCgoiIiIPn36xGuvvRatWrWKTCYTffv2jT/+8Y8R4fUl1FaSJPHiiy/G5ptvHoMHDy7/Xe60006LiG/+KgaoWytWrIhZs2bFxhtvXL5s0qRJ8eKLL8Yee+wR22yzTVxxxRWxdOnSHE5JNjmFi0apS5cucfTRR8cWW2wREf97E7kmTZrEokWLIiIq/ImDM6egdpo2bRq77bZbDBs2LDp06BCff/55jBkzJu6///7YeeedY+bMmXHggQdG7969Y/DgwbkeFxq95s2bxzbbbBMTJ06M+fPnR/v27SPim7M4hg4dGp999llceeWVMXbs2MjPz8/xtND4FRYWxssvvxx33XVXtG/fPu67777o0KFDRET85je/iTPPPDN22mmn2HrrrXM8KTRumUwmOnbsGP3794+NNtooIr4piJcvXx5Lly6NBQsW5HZAWAu1bNkyevbsGb/73e+iU6dO8e6778Yf//jH+OMf/xhbbrllvPvuu3H88cfHdtttF4cddliuxyULtGM0KitL3x/96Edx0kknRcQ3RW/Tpk2jadOm0alTpwrrjxw5Mt566y1FMNTQymMuIuL//u//4rLLLotFixbFrFmz4vzzz4+f/OQnUVhYGHvttVfsvffe8fzzzztrCurIHnvsEV9//XXcfffdsXDhwvLlXbt2jYMOOijefPPNKCoqyuGEsPbYbbfdYscdd4zbb789Fi9eHB06dCg/Y3HQoEHRo0eP+Ne//pXjKaFxW/m68sc//nGceeaZERHl1ylt27ZtdO7cOVq0aFG+/r333hszZszIyaywNlj1TVD/7//+L0488cSYMmVKTJkyJX7961/HwIEDY4cddohjjz02dt1113j22WdzOC3Z5MxgGoUvvvgiOnbsGE2bNo0VK1ZUuC7pqkVvkyZNyr/h/epXv4rf/OY38c4772R9XmjsVj3mSktLo2nTptGqVav45S9/GRHfvIjv3LlzRHzzZ0fNmzePiIgtttjCGw9ADcyePTuee+65aNKkSWy44Yax//77x1FHHRV///vf4/e//320atUqjj766PIzFX/0ox9F69atK5TEQNVUdrxttNFGse+++8ZVV11V/ue0PXr0iIiItm3bRrt27SIvLy/Hk0PjtGDBgmjXrl2lv8ut+rqxSZMm5ScV/PKXv4ybb745pk6dmvV5obFbecw1adKk/He5jTfeOG655ZZYsmRJ7LnnnuW/y5WWlkaSJJGXl1f+c4+1n9MlafDee++96Nq1awwaNCgiIpo1a1bhbMWIb/6PcpIksWDBgsjLy4sbbrghfve738Vrr73mz/mgmr59zK0shFe19dZbxy233BLvvfdefPzxx3HFFVfEq6++GieeeGIuRoZG7Z133okf/vCH8cc//jGGDx8eRxxxRJxyyimxcOHCuPnmm2P33XeP2267La688sr44IMP4osvvoh77rknmjRpEuuvv36ux4dGpbLj7dRTT40FCxbE//3f/8Ull1wSLVu2jEMPPTReeeWVmDZtWlx77bXx+eefR69evXI9PjQ67733XvTq1Ssuu+yyiPjmd7lVz1ZcacmSJfHll19GkiRx7bXXxvXXXx8vvvhibLbZZtkeGRq1bx9z3/5drmXLlrHtttvGgw8+GLNnz44FCxbEVVddFdOnT4/DDz88V2OTZZnE3/PSgH3yySdx+OGHx4oVK+LTTz+NAw88MH7/+99HRJT/H65VHXDAAfHaa6/FokWLYsKECfHDH/4wF2NDo1XVY27SpEkxfPjweOqpp2K77baLxYsXx0MPPRQ77LBDDqeHxqekpCT69esXP/zhD+Omm26KTz/9NN5888047rjjomfPnjFmzJhYb7314te//nU8//zzMWnSpOjVq1d88sknMW7cuOjZs2eunwI0Gt91vPXq1Svuvffe6NKlSzzwwANx//33xzPPPBNbbbVVLF26NB566CHHG1TTnDlz4uCDD45FixZFXl5eHHnkkeUF1bff06WsrCz23HPPmD9/fsyaNSsmTpzodzmopqoecw888ECMGjUqpkyZEr169Yq5c+fGY4895udcirhMBA1WkiTxzDPPxIYbbhjnnHNOzJ49Oy655JKIiPj9739f6Z8ZtW7dOpYuXRpTpkyJbbfdNlejQ6NUlWNu+fLl0bx58+jTp0/ce++9MWnSpCgoKIjNN988CgsLc/wMoPFp1qxZLF26NHbbbbeIiOjcuXP0798/pkyZErvttlucdtpp8cQTT8Rll10WgwcPjtdffz3WWWed2GijjWLDDTfM8fTQuHzf8XbmmWfG448/Hscdd1wce+yx8cYbb0R+fn7k5+fHeuutl+PpoXFJkiTGjh0bhYWFcd5558U//vGPGDt2bEREXHbZZRX+fD3im6KqrKws5s6dG1OmTIntttsul+NDo1OVY27l73LHHXdcbL/99vHPf/4z2rVrFz/84Q+jW7duOX4GZJMymAYrk8nEwQcfHAUFBbHXXnvFkiVLIkmSGDp0aCRJEnfeeWf5JSNWvog4/fTT47rrrovu3bvndnhohKpyzDVv3rz8RcS6664bhxxySK7HhkattLQ0/vvf/8b06dPLly1fvjw233zzGD9+fOy6665xxRVXxLBhw2K99daL/v3753BaaNyqc7xlMhmXhYBayGQyceKJJ8b6668f++23X2y//fYRETF27NhIkiSGDRsWTZs2LT9bsVmzZjFo0KDYfffdY9NNN83x9ND4VOWYW/V3uW222Sa22WabHE9NrrhMBA3WyneWXVVJSUn8+c9/jksuuSQOPvjguPPOOyPim3ea7devX/lF0IHqq84xd//998cee+zh/yBDHbjhhhvi+uuvj9tvvz0OPPDAiIjyF+pXX311PPHEEzFu3LjyNwIBaq6qx1v79u29ISrUsXnz5sXvf//7+NOf/hQDBw6MYcOGRUTEI4884lqlUA/WdMw99thjcdBBB6122U3Sw5nBNCgrz/L99jWkVmrbtm385Cc/iYiISy65JDKZTLRt2zZuuOGGmD17dpanhcbPMQfZ9eWXX8bnn38eCxYsiJ133jkiIvbbb7945ZVXYsSIEdGiRYvo169fNG/ePCIiOnbsGMXFxdGyZUtFMFRTbY43RTBUX2XH3KqX9evSpUucccYZERHx4IMPRpIkUVRUFCNHjoyPP/7YJcegmhxz1JQymAZj2rRpcc4558S9994bXbt2XWM5tc4668QRRxwRZWVlMWjQoGjfvn28+uqrzlCEanLMQXa98847MWjQoCgqKor58+fHDjvsEM8880xss802cfrpp8dNN90Ul156aXz11VcxcODAWL58efznP/+J9dZbr8K7QAPfz/EG2fXtY65nz57x9NNPR7Nmzcr/+ixJkigsLIwzzzwzkiSJX//619GuXbt49dVXlVJQTY45asMpJjQIs2fPjsMOOywmTpwY++67b3z88cfRpEmTKCsrq3T9tm3bxqRJk6JNmzbx97//PXr37p3liaFxc8xBdk2fPj322Wef2GeffWL06NFx3333xfvvv1/+Jo377rtvXHzxxdG7d+844YQTYocddog99tgjRo0aFTfeeGOss846OX4G0Hg43iC7KjvmZs6cGb/4xS8iIsrPtF/53y5dusSsWbNinXXWiUmTJnldCdXkmKO2XDOYnFuyZElcffXV8a9//St+9rOfxRVXXBEffvhhTJo0KTbccMNKz1Z89NFH4+c//3n85S9/8Y0MqskxB9lVUlISp512WnTs2DFuvfXWiPjmXdPPO++8+PDDD+Ovf/1rhXWnTZsWzz//fHTq1Cn23Xdfb6QD1eB4g+yqzjG30h/+8Ie48MIL44UXXoiePXtme2Ro1Bxz1AWXiSDnWrZsGVtttVVss802sc8++8Qmm2wSJ5xwQvTp02eN5dQee+wR//jHP2KDDTbI4eTQODnmIPvatGlT/q7OERFNmjSJPn36xIQJE2LZsmWRJEnk5eVFmzZtYueddy6/7htQfY43yK7vO+YymUz5tbkjIg488MDYd999o0ePHrkYFxo9xxy1pQwmZ8rKyqK0tDSaN28exxxzTPnybt26xejRo+OUU06JPn36lBdQS5cujXfffTc222yzWHfddXM4OTROjjnIrrKysigrK4u2bdvGsGHDYqONNoqIKL+O20otWrQo//fixYujTZs2WZ8VGjvHG2RXTY65RYsWRZs2baJz585ZnxcaO8ccdck1g8mJd999N0488cQYMGBADB48OP72t79VuH/jjTeOP/7xj7HRRhvFbrvtFrNmzYohQ4bEGWecEStWrMjR1NB4OeYgu1Yec/3794+zzz47pk2bVn7fyjen+vZ1uocMGRIDBw705lVQTY43yC7HHGSXY466pgwm66ZPnx677rprlJaWxo9+9KN4+eWX4/LLL4+f//znERHl73q5ySabxN133x09evSITTbZJEaPHh233XZbtGvXLrdPABoZxxxk17ePuX/84x8Vjrlmzb75w6zWrVuX/8+WX/ziF3H77bfHL3/5y2jatGnOZofGxvEG2eWYg+xyzFEflMFkVZIkce+998b+++8fY8eOjeHDh8ff//73OPTQQ2PChAlxxhlnRMT/3vVyww03jM6dO0f79u3jn//8Z/zoRz/K5fjQ6DjmILuqesxFRCxdujTat28fv/zlL+N3v/tdTJo0ybVLoRocb5BdjjnILscc9UUZTFZlMpmYO3dufPrpp+XL1llnnTj33HPj+OOPjzfeeCOuvfbaiPjmG9/vf//7ePjhh+P555+PrbbaKldjQ6PlmIPsqsoxd80110RExPLly+OVV16J22+/PSZPnhy9evXK1djQKDneILscc5BdjjnqizKYrEmSJCIievXqFaWlpTF9+vTy+9ZZZ5049dRTo2fPnvH4449HSUlJZDKZ6N69e7z33nvRs2fPXI0NjZZjDrKrqsfcE088EcuWLYvevXtHnz59YuLEidG7d+9cjQ2NkuMNsssxB9nlmKM+ZZKVexhkyQcffBA777xzHHzwwTFy5Mho27Zt+TtgzpkzJzbaaKP429/+FgMGDMj1qLBWcMxBdlXlmBs3blz069cvvv7662jTpk2uR4ZGy/EG2eWYg+xyzFEfmuV6ANJnk002iYceeigGDBgQrVq1issvvzw6duwYERHNmzeP7bbbzhtWQR1yzEF2VeWYy8/PjyZNmnjBDrXkeIPscsxBdjnmqA/KYHJi7733jocffjiOPPLImDdvXhx11FGx3Xbbxb333hufffZZdO3aNdcjwlrFMQfZ9X3HXLdu3XI9Iqw1HG+QXY45yC7HHHXNZSLIqddffz3OP//8mD17djRr1iyaNm0aDz74oOuVQj1xzEF2OeYgexxvkF2OOcguxxx1RRlMzhUXF8dXX30VCxcujC5dupT/yQNQPxxzkF2OOcgexxtkl2MOsssxR11QBgMAAAAApECTXA8AAAAAAED9UwYDAAAAAKSAMhgAAAAAIAWUwQAAAAAAKaAMBgAAAABIAWUwAAAAAEAKKIMBAAAAAFJAGQwAAAAAkALKYAAAqKWysrLYZptt4uqrr871KGuF5cuXR9euXeO2227L9SgAAGsVZTAAwFpo9OjRkclkym8tW7aMwsLC2H///eOmm26KhQsX1jh78uTJcfnll8eCBQtqPec777wTmUwm/vnPf0ZERCaTiZ/97GeVrrvyOb322mu13m5dGzt2bMyZM6fC7Kt+DSZNmrTaY5Ikia5du0Ymk4kDDzywwn0rHzdo0KBKt/fLX/6yfJ0vvviifPnJJ59c4evetm3b2HjjjeOII46Iv/zlL1FWVrZa1l577VW+fpMmTSI/Pz+22GKLOOGEE+K5556rdPvdu3dfbeaVJkyYEJlMJv785z+v9rlY09dur732im222ab84+bNm8f5558fV199dSxZsqTSxwAAUH3KYACAtdivf/3ruO++++L222+Pc845JyIizjvvvNh2223j7bffrlHm5MmT44orrqiTMvhvf/tbrLfeevGjH/2o1lm5dN1118XAgQOjoKBgtftatmwZY8aMWW35xIkT4+OPP468vLxKM1u2bBl/+ctfYtmyZavdN3bs2GjZsmWlj8vLy4v77rsv7rvvvrjhhhvi2GOPjZkzZ8YRRxwR++67bxQXF6/2mA033DDuu+++uPfee+O6666Lgw8+OCZPnhz9+vWLo48+OpYvX/59n4I6d8opp8QXX3xR6ecOAICaUQYDAKzFBgwYEMcff3yccsopMXTo0HjmmWfi+eefj88++ywOPvjg+Prrr3M637hx42LAgAGRyWRyOsd3KSsr+86zU994441466234qijjqr0/h//+Mfx8MMPx4oVKyosHzNmTPTu3Ts6d+5c6eP69+8fxcXF8dRTT1VYPnny5Jg1a1YccMABlT6uWbNmcfzxx8fxxx8fp59+elx11VXx1ltvxfDhw2PChAlx+umnr/aYgoKC8seceeaZcd1118WMGTPirLPOioceeih+9atfrfH515d27dpFv379YvTo0VnfNgDA2koZDACQMvvss09ceuml8eGHH8b9999fvvztt9+Ok08+OTbeeONo2bJldO7cOU499dT48ssvy9e5/PLL48ILL4yIiB49epRfXmD27Nnl69x///3Ru3fvaNWqVXTo0CEGDhwYc+bMWW2OBQsWxOTJk9dYalbVCy+8ELvvvnu0adMm2rVrF4cccki89957FdY5+eSTo3v37qs99vLLL1+tiF55qYoHHnggtt5668jLy4unn356jdt/7LHHokWLFrHHHntUev8xxxwTX375ZYVLLixbtiz+/Oc/x7HHHrvG3A022CD22GOP1c6MfeCBB2LbbbetcFmFqrjkkkuiX79+8fDDD8eMGTO+d/2mTZvGTTfdFFtttVXccsstUVRUVK3t1YX99tsvJk2aFF999VXWtw0AsDZSBgMApNAJJ5wQERHPPvts+bLnnnsu/vOf/8Qpp5wSN998cwwcODAefPDB+PGPfxxJkkRExOGHHx7HHHNMRETccMMN5Zcj6NSpU0REXH311XHiiSfGZpttFtdff32cd955MX78+Nhjjz1Wu6zEM888E5lMJvr161dh+ZIlS+KLL75Y7VZSUrLa83j++edj//33j88++ywuv/zyOP/882Py5Mmx2267VSioq+uFF16In//853H00UfHyJEjKy2SV5o8eXJss8020bx580rv7969e+yyyy4xduzY8mVPPfVUFBUVxcCBA79zjmOPPTaeeOKJ8ue+YsWKePjhh7+zRP4uJ5xwQiRJssZrAX9b06ZN45hjjonFixevdt3j5cuXV/p1+q7SuKioqNLHrOkyFL17944kSWLy5MlVf5IAAKxRs1wPAABA9m244YZRUFAQH3zwQfmys846K4YMGVJhvZ133jmOOeaYmDRpUuy+++6x3XbbRa9evWLs2LFx6KGHVihJP/zwwxg2bFhcddVV8Ytf/KJ8+eGHHx49e/aM2267rcLyv/3tb7Hbbrutdp3du+66K+66664qPY8LL7wwOnToEFOmTIkOHTpERMShhx4aPXv2jGHDhsU999xT5c/JqqZPnx7vvPNObLXVVt+77r///e/YaaedvnOdY489NoYOHRpff/11tGrVKh544IHYc889o7Cw8Dsfd8QRR8TPfvazeOyxx+L444+PZ599Nr744os45phj4u67767Wc4qI8rOJV/261/Qxzz77bPn/BKiqvn37rvG+rbfeerVlG2+8cUREvPvuu2t8wzoAAKpOGQwAkFJt27aNhQsXln/cqlWr8n8vWbIkSkpKYuedd46IiNdffz12333378x75JFHoqysLI466qj44osvypd37tw5Nttss3jxxRfLy+CysrJ4+umnyy85sapDDjkkfvazn622/Nlnn43rrruu/ON58+bFm2++GRdddFF5ERwRsd1228V+++0X48aN+75PwRrtueeeVSqCIyK+/PLLaN++/Xeuc9RRR8V5550XTz75ZPTv3z+efPLJuOmmm743u3379tG/f/8YO3ZsHH/88TFmzJjYddddY6ONNqrSbN/Wtm3biIgKX/eaPmannXaKq666arX133rrrbjgggsqzbr11ltj8803X235kCFDorS0dLXlKz+vq+5PAADUnDIYACClSkpKYr311iv/+KuvvoorrrgiHnzwwfjss88qrFuV68XOnDkzkiSJzTbbrNL7V72Mwquvvhqff/55pdcL3nDDDSs9g/Tjjz+u8PGHH34YERFbbLHFauv+4Ac/iGeeeSYWLVoUbdq0+d7Zv61Hjx7VWn/lZTTWpFOnTtG3b98YM2ZMLF68OEpLS+OII46oUvaxxx4bJ5xwQnz00Ufx2GOPxYgRI6o126pWXm5inXXWqfVjOnbsWOnXqVmzNf+KseOOO8YPf/jD1Za3b9++0sJ35ee1Ib/BIABAY6IMBgBIoY8//jiKiopi0003LV921FFHxeTJk+PCCy+MHXbYIdq2bRtlZWXRv3//KCsr+97MsrKyyGQy8dRTT0XTpk1Xu3/lGaYREePGjYvu3btX+ezb2lpTmVjZ2agRFc+S/j7rrrtuzJ8//3vXO/bYY+P000+PTz/9NAYMGBDt2rWrUv7BBx8ceXl5cdJJJ8XSpUvjqKOOqvJs3zZt2rSIiApf9/p4TF1Z+Xnt2LFj1rcNALA2UgYDAKTQfffdFxER+++/f0R8U7qNHz8+rrjiirjsssvK15s5c+Zqj11TsbrJJptEkiTRo0ePSi8FsKq//e1v8eMf/7im40dElF8qYfr06avd9+9//zs6duxYflZw+/btV3sDu4j/nV1cG1tuuWXMmjXre9c77LDD4swzz4yXX345/vSnP1U5v1WrVnHooYfG/fffHwMGDKhVMXrfffdFJpOJ/fbbr0rrl5aWxpgxY6J169bRp0+fGm+3plZ+Xn/wgx9kfdsAAGujJrkeAACA7HrhhRfiyiuvjB49esRxxx0XEVF+Ju+3L3dw4403rvb4lQXrt8vVww8/PJo2bRpXXHHFajlJksSXX34ZERH//e9/4/XXX6/0EhHV0aVLl9hhhx3innvuqTDLtGnT4tlnn61QNm+yySZRVFQUb7/9dvmyefPmxaOPPlqrGSIidtlll5g2bVosXbr0O9dr27Zt3H777XH55ZfHQQcdVK1tXHDBBTFs2LC49NJLazznNddcE88++2wcffTRa7yUx6pKS0vj3HPPjffeey/OPffcyM/Pr/G2a2rq1KmRyWRil112yfq2AQDWRs4MBgBYiz311FPx73//O1asWBH//e9/44UXXojnnnsuNtpoo3j88cejZcuWERGRn58fe+yxR4wYMSKWL18eG2ywQTz77LOVnvHau3fviIj45S9/GQMHDozmzZvHQQcdFJtssklcddVVMXTo0Jg9e3Yceuihsc4668SsWbPi0UcfjTPOOCMuuOCCGDduXLRs2TL23nvvWj+/6667LgYMGBC77LJLnHbaafH111/HzTffHAUFBXH55ZeXrzdw4MC4+OKL47DDDotzzz03Fi9eHLfffntsvvnm8frrr9dqhkMOOSSuvPLKmDhxYvTr1+871z3ppJNqtI3tt98+tt9++yqtu2LFirj//vsj4ps3Avzwww/j8ccfj7fffjv23nvvuPPOO1d7TFFRUfljFi9eHO+//3488sgj8cEHH8TAgQPjyiuvrNHctfXcc8/FbrvtFuuuu25Otg8AsLZRBgMArMVWXvKhRYsW0aFDh9h2223jxhtvjFNOOWW1NwQbM2ZMnHPOOXHrrbdGkiTRr1+/eOqpp6KwsLDCej/60Y/iyiuvjDvuuCOefvrpKCsri1mzZkWbNm3ikksuic033zxuuOGGuOKKKyIiomvXrtGvX784+OCDI+Kb6wXvvffe1bou75r07ds3nn766Rg2bFhcdtll0bx589hzzz3j2muvrfAmcOuuu248+uijcf7558dFF10UPXr0iOHDh8fMmTNrXQb37t07tttuu3jooYe+twzOhqVLl8YJJ5wQERGtW7eO9dZbL3r37h2XXXZZHHbYYdGkyep/HPjxxx+XP6Zt27bRpUuX2GWXXeL222+v8iUl6lpRUVE8++yzcdttt+Vk+wAAa6NM8n1vfQwAAHVkxYoVse6668bw4cPjrLPOyvU4dea+++6Ls88+Oz766KMqvzEc3+3GG2+MESNGxAcffFAn/+MAAADXDAYAIIu++uqr+PnPfx6HHXZYrkepU8cdd1x069Ytbr311lyPslZYvnx5XH/99fGrX/1KEQwAUIecGQwAAAAAkALODAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACymAAAAAAgBRQBgMAAAAApIAyGAAAAAAgBZTBAAAAAAApoAwGAAAAAEgBZTAAAAAAQAoogwEAAAAAUkAZDAAAAACQAspgAAAAAIAUUAYDAAAAAKSAMhgAAAAAIAWUwQAAAAAAKaAMBgAAAABIAWUwAAAAAEAKKIMBAAAAAFJAGQwAAAAAkALKYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACymAAAAAAgBRQBgMAAAAApIAyGAAAAAAgBZTBAAAAAAApoAwGAAAAAEgBZTAAAAAAQAoogwEAAAAAUkAZDAAAAACQAspgAAAAAIAUUAYDAAAAAKSAMhgAAAAAIAWUwQAAAAAAKaAMBgAAAABIAWUwAAAAAEAKKIMBAAAAAFJAGQwAAAAAkALKYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACjTL9QC5sGTJkli2bFmuxwAAAAAAiIiIFi1aRMuWLet1G6krg5csWRKtWrWLiKW5HgUAAAAAICIiOnfuHLNmzarXQjh1ZfA3ZwQvjYi+UfHpV3bFjKZrSKlseWXLKsus6nZyue3abqc2j61tZmPY9pq2U9fbXtNzrM3XMVv7byZL28nWMVrXx0l19qu634eaVfKTozbLmlay6crWq4/Mqi7L5nbqOrOqc2drO7n82mZrO7n82tbHdurj65itr222vhc0ibLVF65YUbfLIiJKS+s2s6p5DXE7df25yNZ2KsurbWa2tlObz0W2tpPLr219ZK5lX9ukkodW8t2z0mXVWbeul0XUbvbKlq3hq1jn26lq3pqWVzZnXc+4puVV3U5VZ6zOTHX9OY/IzueyPo6d2u5Ddb2sOsdOY/j8fnvZ0oi44dNPY9myZcrg+tEsIpqv8nFDK0pzue1sbSdbhVZD23a2tlOdMnht2q+ytZ1slcG5268ymcr3oUwlXX1tljWpZDOVLavOupUVQLVZtqbl9VHk1XWmbWd/O57j2rvtNS3PWhlc15kNbdvZ2k5atx1Rux+GlWXWxw/xyrZTmxca1V23riWV1BF1vSyi6p/fypaVVfI9rB4+v0klszeWMjiXhVYun2Muy+DafC5zWQav6Tk2hjK4NjNWZztpOHZqm1nfvIEcAAAAAEAKKIMBAAAAAFJAGQwAAAAAkALKYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACymAAAAAAgBRQBgMAAAAApIAyGAAAAAAgBZTBAAAAAAApoAwGAAAAAEgBZTAAAAAAQAoogwEAAAAAUkAZDAAAAACQAspgAAAAAIAUUAYDAAAAAKSAMhgAAAAAIAWUwQAAAAAAKaAMBgAAAABIAWUwAAAAAEAKKIMBAAAAAFJAGQwAAAAAkALKYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACymAAAAAAgBRQBgMAAAAApIAyGAAAAAAgBZTBAAAAAAApoAwGAAAAAEgBZTAAAAAAQAoogwEAAAAAUkAZDAAAAACQAspgAAAAAIAUUAYDAAAAAKSAMhgAAAAAIAWUwQAAAAAAKaAMBgAAAABIAWUwAAAAAEAKKIMBAAAAAFJAGQwAAAAAkALKYAAAAACAFFAGAwAAAACkgDIYAAAAACAFlMEAAAAAACmgDAYAAAAASAFlMAAAAABACiiDAQAAAABSQBkMAAAAAJACymAAAAAAgBRQBgMAAAAApIAyGAAAAAAgBZTBAAAAAAAp0CzXA+TOim99XFkvXraGx1a2vLJllWWWVrKsaRWXVWfdyrZd2bL62E5tHlvbzMaw7TVtp663vabnWJuvY21mrM66mSxtp66/DtXZTl0fY7XdzurLkqTyfShJ6nZZWSXfPitbVp11Syv5VpupZLeq6rLvWl7X6vrzW9XP+ZqW12ZZZV+HypZVZ90V3/7xHRHNKnk1U9my6qzbtJLDpKqPXdO26zozW9upal62tlOdbdfH17Gy5U0qex1Y2c5am2URVT8oqrqsqnkNcTt1/bnI1nbW9E2wrveX+thObT4X2dpOLr+2a8qs62X18UO8Ni8qqrFuZY+u6m/W1Vm3rpdF1G72ypat4Qit8+1UNW9Nyyubs65nXNPyqm6nqjNWZ6a6/pxHZOdzWR/HTm33obpeVp1jpzF8fr+9bOkatlHXUlcGJ0kSbdu2jZKS53M9CkCjVJ3fiQAAAICqadu2bSRr+p9vdSR1ZXAmk4mSkpKYM2dO5Ofn53ociIiI4uLi6Nq1q/2SBsM+SUNkv6Qhsl/S0NgnaYjslzRE9ksampX7ZKae/yw1dWXwSvn5+Q52Ghz7JQ2NfZKGyH5JQ2S/pKGxT9IQ2S9piOyXpI03kAMAAAAASAFlMAAAAABACqSuDM7Ly4thw4ZFXl5erkeBcvZLGhr7JA2R/ZKGyH5JQ2OfpCGyX9IQ2S9paLK1T2aS+n6LOgAAAAAAci51ZwYDAAAAAKSRMhgAAAAAIAWUwQAAAAAAKaAMBgAAAABIgbWuDP7qq6/iuOOOi/z8/GjXrl2cdtppUVJS8p3rn3POObHFFltEq1atolu3bnHuuedGUVFRhfU++uijOOCAA6J169ax3nrrxYUXXhgrVqyo76fDWqK6+2VExJ133hl77bVX5OfnRyaTiQULFqy2Tvfu3SOTyVS4XXPNNfX0LFjb1Nd+WZNciKjZvrNkyZI4++yzY9111422bdvGT37yk/jvf/9bYZ1vf5/MZDLx4IMP1udToRG79dZbo3v37tGyZcvYaaed4p///Od3rv/www/HlltuGS1btoxtt902xo0bV+H+JEnisssuiy5dukSrVq2ib9++MXPmzPp8CqyF6nq/PPnkk1f7vti/f//6fAqshaqzX/7rX/+Kn/zkJ+W/v9x44421zoRvq+t98vLLL1/te+WWW25Zj8+AtVF19stRo0bF7rvvHu3bt4/27dtH3759V1u/Ll5brnVl8HHHHRf/+te/4rnnnosnn3wyXnrppTjjjDPWuP7cuXNj7ty58dvf/jamTZsWo0ePjqeffjpOO+208nVKS0vjgAMOiGXLlsXkyZPjnnvuidGjR8dll12WjafEWqC6+2VExOLFi6N///7xi1/84jvX+/Wvfx3z5s0rv51zzjl1OTprsfraL2uSCxE123d+/vOfxxNPPBEPP/xwTJw4MebOnRuHH374auvdfffdFb5XHnroofX0LGjM/vSnP8X5558fw4YNi9dffz2233772H///eOzzz6rdP3JkyfHMcccE6eddlq88cYbceihh8ahhx4a06ZNK19nxIgRcdNNN8Udd9wRr7zySrRp0yb233//WLJkSbaeFo1cfeyXERH9+/ev8H1x7Nix2Xg6rCWqu18uXrw4Nt5447jmmmuic+fOdZIJq6qPfTIiYuutt67wvXLSpEn19RRYC1V3v5wwYUIcc8wx8eKLL8aUKVOia9eu0a9fv/jkk0/K16mT15bJWuTdd99NIiJ59dVXy5c99dRTSSaTST755JMq5zz00ENJixYtkuXLlydJkiTjxo1LmjRpknz66afl69x+++1Jfn5+snTp0rp7AqyVartfvvjii0lEJPPnz1/tvo022ii54YYb6nBa0qK+9su6+j5M+tRk31mwYEHSvHnz5OGHHy5f9t577yURkUyZMqV8WUQkjz76aL3Nztpjxx13TM4+++zyj0tLS5PCwsJk+PDhla5/1FFHJQcccECFZTvttFNy5plnJkmSJGVlZUnnzp2T6667rvz+BQsWJHl5ecnYsWPr4RmwNqrr/TJJkuSkk05KDjnkkHqZl3So7n65qjX9DlObTKiPfXLYsGHJ9ttvX4dTkja1/b62YsWKZJ111knuueeeJEnq7rXlWnVm8JQpU6Jdu3bxwx/+sHxZ3759o0mTJvHKK69UOaeoqCjy8/OjWbNm5bnbbrttrL/++uXr7L///lFcXBz/+te/6u4JsFaqq/1yTa655ppYd911o2fPnnHddde5fAlVUl/7ZX3v76y9arLvTJ06NZYvXx59+/YtX7bllltGt27dYsqUKRXWPfvss6Njx46x4447xh//+MdIkqR+ngiN1rJly2Lq1KkV9qcmTZpE3759V9ufVpoyZUqF9SO+eY24cv1Zs2bFp59+WmGdgoKC2GmnndaYCauqj/1ypQkTJsR6660XW2yxRfz0pz+NL7/8su6fAGulmuyXucgkPepz/5k5c2YUFhbGxhtvHMcdd1x89NFHtR2XlKiL/XLx4sWxfPny6NChQ0TU3WvLZlVesxH49NNPY7311quwrFmzZtGhQ4f49NNPq5TxxRdfxJVXXlnhz1I//fTTCkVwRJR/XNVc0qsu9ss1Offcc6NXr17RoUOHmDx5cgwdOjTmzZsX119/fa1yWfvV135Zn/s7a7ea7DuffvpptGjRItq1a1dh+frrr1/hMb/+9a9jn332idatW8ezzz4bZ511VpSUlMS5555b58+DxuuLL76I0tLSSl/z/fvf/670MWt6jbhy/1v53+9aB75LfeyXEd9cIuLwww+PHj16xAcffBC/+MUvYsCAATFlypRo2rRp3T8R1io12S9zkUl61Nf+s9NOO8Xo0aNjiy22iHnz5sUVV1wRu+++e0ybNi3WWWed2o7NWq4u9suLL744CgsLy8vfunpt2SjK4EsuuSSuvfba71znvffeq/V2iouL44ADDoitttoqLr/88lrnsXbL1n75Xc4///zyf2+33XbRokWLOPPMM2P48OGRl5dXr9umYWoI+yWsqiHsk5deemn5v3v27BmLFi2K6667ThkMpNbAgQPL/73tttvGdtttF5tssklMmDAh9t133xxOBtBwDBgwoPzf2223Xey0006x0UYbxUMPPVThfaagPlxzzTXx4IMPxoQJE6Jly5Z1mt0oyuAhQ4bEySef/J3rbLzxxtG5c+fVLsK8YsWK+Oqrr77zguAREQsXLoz+/fvHOuusE48++mg0b968/L7OnTuv9u59K9+p/PtyWXtlY7+srp122ilWrFgRs2fPji222KJOs2kccr1fZnN/p3Goz32yc+fOsWzZsliwYEGFs4P/+9//fuf+ttNOO8WVV14ZS5cu9T/OKNexY8do2rRp+Wu8lb5rf+rcufN3rr/yv//973+jS5cuFdbZYYcd6nB61lb1sV9WZuONN46OHTvG+++/rwzme9Vkv8xFJumRrf2nXbt2sfnmm8f7779fZ5msvWqzX/72t7+Na665Jp5//vnYbrvtypfX1WvLRnHN4E6dOsWWW275nbcWLVrELrvsEgsWLIipU6eWP/aFF16IsrKy2GmnndaYX1xcHP369YsWLVrE448/vlrjvssuu8Q777xT4ZfU5557LvLz82Orrbaq+ydMo1Df+2VNvPnmm9GkSZPV/tSa9Mj1fpnN/Z3GoT73yd69e0fz5s1j/Pjx5cumT58eH330Ueyyyy5rnOnNN9+M9u3bK4KpoEWLFtG7d+8K+1NZWVmMHz9+jfvTLrvsUmH9iG9eI65cv0ePHtG5c+cK6xQXF8crr7zynfsorFQf+2VlPv744/jyyy8r/GIJa1KT/TIXmaRHtvafkpKS+OCDD3yvpEpqul+OGDEirrzyynj66acrvJ9KRB2+tqzyW801Ev3790969uyZvPLKK8mkSZOSzTbbLDnmmGPK7//444+TLbbYInnllVeSJEmSoqKiZKeddkq23Xbb5P3330/mzZtXfluxYkWSJN+8e98222yT9OvXL3nzzTeTp59+OunUqVMydOjQnDxHGp/q7pdJkiTz5s1L3njjjWTUqFFJRCQvvfRS8sYbbyRffvllkiRJMnny5OSGG25I3nzzzeSDDz5I7r///qRTp07JiSeemPXnR+NUH/tlVXJhTWqyTw4ePDjp1q1b8sILLySvvfZasssuuyS77LJL+f2PP/54MmrUqOSdd95JZs6cmdx2221J69atk8suuyyrz43G4cEHH0zy8vKS0aNHJ++++25yxhlnJO3atUs+/fTTJEmS5IQTTkguueSS8vX/8Y9/JM2aNUt++9vfJu+9914ybNiwpHnz5sk777xTvs4111yTtGvXLvnrX/+avP3228khhxyS9OjRI/n666+z/vxonOp6v1y4cGFywQUXJFOmTElmzZqVPP/880mvXr2SzTbbLFmyZElOniONT3X3y6VLlyZvvPFG8sYbbyRdunRJLrjgguSNN95IZs6cWeVM+C71sU8OGTIkmTBhQjJr1qzkH//4R9K3b9+kY8eOyWeffZb150fjVN398pprrklatGiR/PnPf67QTy5cuLDCOrV9bbnWlcFffvllcswxxyRt27ZN8vPzk1NOOaXCJ23WrFlJRCQvvvhikiRJ8uKLLyYRUelt1qxZ5Y+bPXt2MmDAgKRVq1ZJx44dkyFDhiTLly/P8rOjsarufpkkSTJs2LBK98u77747SZIkmTp1arLTTjslBQUFScuWLZMf/OAHyW9+8xsv4qmy+tgvq5ILa1KTffLrr79OzjrrrKR9+/ZJ69atk8MOOyyZN29e+f1PPfVUssMOOyRt27ZN2rRpk2y//fbJHXfckZSWlmbzqdGI3HzzzUm3bt2SFi1aJDvuuGPy8ssvl9+35557JieddFKF9R966KFk8803T1q0aJFsvfXWyd/+9rcK95eVlSWXXnppsv766yd5eXnJvvvum0yfPj0bT4W1SF3ul4sXL0769euXdOrUKWnevHmy0UYbJaeffrrCjWqrzn658mf4t2977rlnlTPh+9T1Pnn00UcnXbp0SVq0aJFssMEGydFHH528//77WXxGrA2qs19utNFGle6Xw4YNK1+nLl5bZpIkSap+HjEAAAAAAI1Ro7hmMAAAAAAAtaMMBgAAAABIAWUwAAAAAEAKKIMBAAAAAFJAGQwAAAAAkALKYAAAAACAFFAGAwAAAACkgDIYAIBqufzyyyOTydTosd27d48DDzywzmaZPXt2ZDKZGD16dJ1lNiYlJSWx3nrrxQMPPJDrUaps+fLl0bVr17jttttyPQoAQOoogwEAiFmzZsXPfvaz2HzzzaN169bRunXr2GqrreLss8+Ot99+O9fjsQYjR46MddZZJwYOHLjaff/4xz/isMMOi/XXXz/y8vKie/fuceaZZ8ZHH31UrzONGzcuMplMFBYWRllZ2Wr3N2/ePM4///y4+uqrY8mSJfU6CwAAFSmDAQBS7sknn4xtttkm7rvvvujbt2/ccMMNMXLkyBgwYECMGzcudthhh/jwww9zPSbfsnz58hg5cmQMGjQomjZtWuG+m2++OXbfffd455134pxzzonbbrstjjjiiPjTn/4U2223XUyePLne5nrggQeie/fuMW/evHjhhRcqXeeUU06JL774IsaMGVNvcwAAsLpmuR4AAIDc+eCDD2LgwIGx0UYbxfjx46NLly4V7r/22mvjtttuiyZNnEPQ0Dz55JPx+eefx1FHHVVh+T/+8Y8477zzok+fPvH0009H69aty+/76U9/GrvttlscccQR8a9//Svat29fpzMtWrQo/vrXv8bw4cPj7rvvjgceeCD69u272nrt2rWLfv36xejRo+PUU0+t0xkAAFgzr+oBAFJsxIgRsWjRorj77rtXK4IjIpo1axbnnntudO3a9TtzVqxYEVdeeWVssskm5Zck+MUvfhFLly6tdP1nn302dthhh2jZsmVstdVW8cgjj1S4/6uvvooLLrggtt1222jbtm3k5+fHgAED4q233qrR8xw9enRkMpmYNGlSnHvuudGpU6do165dnHnmmbFs2bJYsGBBnHjiidG+ffto3759XHTRRZEkSYWMsrKyuPHGG2PrrbeOli1bxvrrrx9nnnlmzJ8/v8J6f/3rX+OAAw6IwsLCyMvLi0022SSuvPLKKC0trbDeXnvtFdtss028++67sffee0fr1q1jgw02iBEjRlTpOT322GPRvXv32GSTTSosv/LKKyOTycQ999xToQiOiNhkk01ixIgRMW/evPj9739fvvzkk0+Otm3bxkcffRQHHnhgtG3bNjbYYIO49dZbIyLinXfeiX322SfatGkTG2200RrP6H300Ufj66+/jiOPPDIGDhwYjzzyyBovBbHffvvFpEmT4quvvqrS8wUAoPaUwQAAKfbkk0/GpptuGjvttFOtcgYNGhSXXXZZ9OrVK2644YbYc889Y/jw4ZVey3bmzJlx9NFHx4ABA2L48OHRrFmzOPLII+O5554rX+c///lPPPbYY3HggQfG9ddfHxdeeGG88847seeee8bcuXNrPOc555wTM2fOjCuuuCIOPvjguPPOO+PSSy+Ngw46KEpLS+M3v/lN9OnTJ677f+3db0yV5R/H8c9BDP+A/EntUBQoIPUEEhgNGBJrhaUOm5a5mKi48IGrhBAzigabTQsHtblME5IOoVQ+yD/NitpqbWmZ09pQLKQtFwXBESMROVcPGvfPm4NEBr9+v533a7u3c3+v+77O97oPD9h31773iy+qrq7Odm9BQYGKi4uVnp6u6upqrVq1Si6XS9nZ2erv77euq62tVWBgoAoLC1VdXa2kpCQ999xz2rhxo1c+XV1dmj9/vhISElRZWanbb79dJSUlOnz48F+u5fPPP1diYqIt1tvbq48++kgZGRmaNWvWsPctW7ZMAQEBOnDggC0+MDCg+++/X7feequ2bt2qqKgorVu3TrW1tZo/f76Sk5O1ZcsWBQUFacWKFWptbfWa2+VyKSsrS06nU4888oh6enr03nvvDZtHUlKSjDHj2rICAAAAQxgAAAD4JLfbbSSZxYsXe411dXWZX375xTp6e3utsbKyMnP1v5EnTpwwksyaNWtsczz11FNGkmlqarJikZGRRpJ55513bHmEh4ebuXPnWrFLly6ZgYEB23ytra0mICDAlJeX22KSTE1NzYhrrampMZJMdna28Xg8Vjw1NdU4HA6zdu1aK3blyhUTERFhMjMzrdinn35qJBmXy2Wb9/333/eKX/2sBhUUFJgpU6aYS5cuWbHMzEwjyezZs8eK9fX1GafTaZYsWTLievr7+43D4TBFRUW2+OBv8cQTT4x4f3x8vAkLC7PO8/LyjCSzefNmK9bV1WUmT55sHA6HaWhosOLNzc1GkikrK7PN2d7ebvz9/c3OnTutWFpamsnJyRk2h/PnzxtJZsuWLSPmCgAAgLHDzmAAAAAfdeHCBUlSYGCg19jdd9+tGTNmWMdgu4DhHDp0SJJUWFhoixcVFUmSDh48aIvffPPNevDBB63zadOmacWKFfr666/1008/SZICAgKsPsUDAwPq7OxUYGCg4uLidPz48b+7VEt+fr4cDod1ftddd8kYo/z8fCs2YcIEJScn6/vvv7dijY2NCg4O1r333quOjg7rSEpKUmBgoD7++GPr2smTJ1ufe3p61NHRoYyMDPX29qq5udmWT2BgoHJzc63zG264QSkpKbbvHs6vv/4qY4xXz9+enh5JUlBQ0Ij3BwUFWb//1dasWWN9DgkJUVxcnKZOnWrrSxwXF6eQkBCvHBsaGuTn56clS5ZYseXLl+vw4cNerTQkWbl3dHSMmCsAAADGDi+QAwAA8FGDBcOLFy96je3YsUM9PT1qb2+3FSuH09bWJj8/P8XExNjiTqdTISEhamtrs8VjYmJsBVlJmjNnjiTp3Llzcjqd8ng8qq6u1vbt29Xa2mrrt3vjjTeOfpFD3Hbbbbbz4OBgSfLqiRwcHGwrYLa0tMjtdmvmzJnDzvvzzz9bn7/99luVlpaqqanJq+Dqdrtt5xEREV7PIjQ0VCdPnhzVesyQvsaDv+lgUfhaenp6vArGkyZN0owZM2yx4ODgYXMc+nwk6c0331RKSoo6OzvV2dkpSZo7d64uX76sxsZGPfbYY8PmPnRuAAAAjB+KwQAAAD4qODhY4eHh+uabb7zGBnsInzt3btTzjWVRb/PmzXr22We1evVqVVRUKCwsTH5+fnryySfl8Xiue94JEyaMOn51odXj8WjmzJlyuVzD3j9YRO3u7lZmZqamTZum8vJyRUdHa9KkSTp+/LhKSkq8cr9WPkOLvEOFhYXJ4XB4FWRjYmLk7+8/YjG5r69Pp0+fVnJy8qhyGU2OLS0tOnbsmCQpNjbW61qXy+VVDB7Mffr06dfMFQAAAGOLYjAAAIAPW7BggXbt2qWjR48qJSXluuaIjIyUx+NRS0uL7rjjDive3t6u7u5uRUZG2q4/e/asjDG24vGZM2ckSVFRUZKkt99+W1lZWXr99ddt93Z3d/8rxcPo6Gh9+OGHSk9Pt7WBGOqTTz5RZ2en3n33Xc2bN8+KD/eytX/C399f0dHRXvNOnTpVWVlZampqUltbm9ezl6R9+/apr69PCxcuHLN8XC6XJk6cqLq6Oq/i8WeffaaXX35ZP/zwg21n9mDuV//NAAAAYHzRMxgAAMCHbdiwQVOmTNHq1avV3t7uNf5XO1Ql6YEHHpAkVVVV2eLbtm2T9GfB+Wrnz5/X/v37rfMLFy5oz549uvPOO+V0OiX9uRt16Hc3Njbqxx9//OtFjYOHH35YAwMDqqio8Bq7cuWKuru7Jf1nF+3VuV++fFnbt28f85xSU1P15ZdfesVLS0tljNHKlSv1+++/28ZaW1u1YcMGhYeHq6CgYMxycblcysjI0LJly7R06VLbUVxcLEl66623bPd89dVXcjgcSk1NHbM8AAAAMDJ2BgMAAPiw2NhY1dfXa/ny5YqLi9Ojjz6qhIQEGWPU2tqq+vp6+fn5KSIi4ppzJCQkKC8vT6+99prVJuHo0aN64403tHjxYmVlZdmunzNnjvLz83Xs2DHddNNN2r17t9rb21VTU2Nds3DhQpWXl2vVqlVKS0vTqVOn5HK5NHv27HF7FiPJzMxUQUGBXnjhBZ04cUL33XefJk6cqJaWFjU2Nqq6ulpLly5VWlqaQkNDlZeXp8cff1wOh0N1dXWjKqr/XTk5Oaqrq9OZM2esnsuSNG/ePL300ksqLCxUfHy8Vq5cqfDwcDU3N2vnzp3yeDw6dOiQ18vnrtcXX3yhs2fPat26dcOO33LLLUpMTJTL5VJJSYkV/+CDD5Senv6PekADAADg76EYDAAA4ONycnJ06tQpVVZW6siRI9q9e7ccDociIyO1YMECrV27VgkJCSPOsWvXLs2ePVu1tbXav3+/nE6nnn76aZWVlXldGxsbq1deeUXFxcU6ffq0Zs2apb179yo7O9u6ZtOmTfrtt99UX1+vvXv3KjExUQcPHtTGjRvHfP2j9eqrryopKUk7duzQpk2b5O/vr6ioKOXm5io9PV3Sny+3O3DggIqKilRaWqrQ0FDl5ubqnnvusa1vLCxatEjTp0/Xvn37VFpaahtbv369kpOTVVlZqaqqKrndboWHh+uhhx7SM888M2z7iOs12Ed50aJFI+b6/PPP6+TJk4qPj5fb7daRI0fGZcc0AAAArs1hxmObAgAAAIBxV1FRoZqaGrW0tFzzRW//i6qqqrR161Z99913I/ZgBgAAwNiiZzAAAADwf2r9+vW6ePGiGhoa/u1URq2/v1/btm1TaWkphWAAAID/MnYGAwAAAAAAAIAPYGcwAAAAAAAAAPgAisEAAAAAAAAA4AMoBgMAAAAAAACAD6AYDAAAAAAAAAA+gGIwAAAAAAAAAPgAisEAAAAAAAAA4AMoBgMAAAAAAACAD6AYDAAAAAAAAAA+gGIwAAAAAAAAAPgAisEAAAAAAAAA4AMoBgMAAAAAAACAD/gD/xmaIDX8SSwAAAAASUVORK5CYII=", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "### Plotes\n", "import matplotlib as mpl\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import matplotlib.dates as mdates # Importante para formatar as datas\n", "\n", "### Quantidade total de microondas assimiladas nos canais do sensor\n", "\n", "# Criando um novo DataFrame para armazenar as somas dos canais de mesma frequência\n", "canais_freq = [4, 5, 6, 7, 9, 8, 10, 11, 12, 13, 14] # Canais AMSU-A de mesma frequencia do ATMS: ch_amsua = ch_atms + 1\n", "# canais = list(range(1, 16))\n", "\n", "# Aplique o mesmo índice nos dois\n", "df1_OMA.index = pd.to_datetime(dates, format='%Y%m%d%H')\n", "df2_OMA.index = pd.to_datetime(dates, format='%Y%m%d%H')\n", "\n", "# 3. Criando o Heatmap\n", "# fig, ax = plt.subplots(figsize=(14, 6))\n", "fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(14, 12), sharex=True, constrained_layout=True)\n", "\n", "v_max = 0.2 #df_combinado.fillna(0).max().max()\n", "v_min = -0.2 #df_combinado.fillna(0).min().min()\n", "\n", "# Substitui TODOS os zeros por NaN no DataFrame inteiro\n", "# df_combinado = df_combinado.replace(0, np.nan)\n", "\n", "ax1.add_patch(\n", " mpl.patches.Rectangle(\n", " (-1, -1),\n", " (len(dates) + 1),\n", " (len(canais_freq) + 3),\n", " hatch=\"xxxxx\",\n", " color=\"black\",\n", " fill=False,\n", " snap=False,\n", " zorder=0,\n", " )\n", ")\n", "\n", "ax2.add_patch(\n", " mpl.patches.Rectangle(\n", " (-1, -1),\n", " (len(dates) + 1),\n", " (len(canais_freq) + 3),\n", " hatch=\"xxxxx\",\n", " color=\"black\",\n", " fill=False,\n", " snap=False,\n", " zorder=0,\n", " )\n", ")\n", "\n", "# Como o imshow espera uma matriz (linhas = canais, colunas = datas), \n", "# transpomos o DataFrame (.T)\n", "df_combinado = df1_OMA\n", "cax1 = ax1.imshow(df_combinado.T, aspect='auto', cmap='seismic', origin='lower', \n", " vmin=v_min, vmax=np.max(v_max), zorder=1, interpolation='none')\n", "\n", "ax1.set_yticks(range(len(df_combinado.columns)))\n", "ax1.set_yticklabels(df_combinado.columns, fontsize=10)\n", "ax1.set_ylabel('Channels AMSU-A', fontsize=12)\n", "\n", "df_combinado = df2_OMA\n", "cax2 = ax2.imshow(df_combinado.T, aspect='auto', cmap='seismic', origin='lower', \n", " vmin=v_min, vmax=np.max(v_max), zorder=1, interpolation='none')\n", "\n", "ax2.set_yticks(range(len(df_combinado.columns)))\n", "ax2.set_yticklabels(df_combinado.columns, fontsize=10)\n", "ax2.set_ylabel('Channels ATMS', fontsize=12)\n", "\n", "\n", "# -------------------------------------------------------------\n", "# 3. Barra de Cores Compartilhada (abaixo de tudo)\n", "# -------------------------------------------------------------\n", "# Passamos ax=[ax1, ax2] para que o Matplotlib centralize a barra em relação aos dois gráficos\n", "cbar = fig.colorbar(cax2, ax=ax2, orientation='horizontal', pad=0.10, shrink=1.0)\n", "cbar.set_label('Global mean (OmA)', fontsize=12)\n", "\n", "# Configurando o eixo X (Datas formatadas como mmddhh)\n", "# Como usamos imshow, mapeamos as posições numéricas do índice para as datas reais\n", "ax2.set_xticks(range(len(df_combinado.index)))\n", "ax2.set_xticklabels(df_combinado.index.strftime('%d%H'), fontsize=10)\n", "\n", "# Rotaciona as datas para não embolarem\n", "plt.xticks(rotation=45)\n", "\n", "ax2.set_xlabel('Date/Hour (MMDDHH)', fontsize=12)\n", "\n", "datefmt1 = dates[0]\n", "datefmt2 = dates[-1]\n", "date1 = datetime.strptime(str(datefmt1), \"%Y%m%d%H\")\n", "date2 = datetime.strptime(str(datefmt2), \"%Y%m%d%H\")\n", "date_title = str(date1.strftime(\"%d%b%Y %H%M\")) + ' - ' + str(date2.strftime(\"%d%b%Y %H%M\")) + ' GMT'\n", "# plt.title(date_title, loc=\"right\", fontsize=12)\n", "ax1.set_title(date_title, loc=\"right\", fontsize=12)\n", "\n", "\n", "# plt.tight_layout()\n", "\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "id": "343ba77a", "metadata": {}, "outputs": [], "source": [ "# verifica se o calculo do std combinando da celula anterior esta correto\n", "# para fazer a conferencia setar apenas dois satelites na lista de satelites e o canal 7\n", "\n", "aux1 = np.array( OMF_final[0][7] ).tolist()\n", "aux2 = np.array( OMF_final[1][7] ).tolist()\n", "\n", "# mf1 = 0.005588\n", "# mf2 = 0.005522\n", "\n", "mf1 = aux1[0]\n", "mf2 = aux2[0]\n", "\n", "# std1 = 0.197798\n", "# std2 = 0.219926\n", "\n", "aux1 = np.array( stdF_final[0][7] ).tolist()\n", "aux2 = np.array( stdF_final[1][7] ).tolist()\n", "\n", "std1 = aux1[0]\n", "std2 = aux2[0]\n", "\n", "print('std1 =', std1, 'std2 =', std2)\n", "\n", "aux1 = np.array( Cf_final[0][7] ).tolist()\n", "aux2 = np.array( Cf_final[1][7] ).tolist()\n", "\n", "# n1 = 8856.0\n", "# n2 = 8882.0\n", "\n", "n1 = aux1[0]\n", "n2 = aux2[0]\n", "\n", "m = ((0.005588*8856.0) + (0.005522*8882.0))/(8856.0 + 8882.0)\n", "\n", "m = ( (mf1*n1) + (mf2*n2) ) / (n1 + n2)\n", "\n", "diff1 = mf1 - m\n", "diff2 = mf2 - m\n", "\n", "soma = (n1 * ( (std1**2) + (diff1**2) ) ) + (n2 * ( (std2**2) + (diff2**2) ) )\n", "\n", "std = soma / (n1+n2)\n", "\n", "# print('soma NF =', soma_NF)\n", "\n", "# print('diff1 =', diff1)\n", "# print('diff2 =', diff2)\n", "\n", "print('')\n", "print('std combinado de omf no primeiro data em relação ao primeiro e segundo satelites:')\n", "print(std)\n", "\n", "print('valor obtido na celula anterior:')\n", "print(df_stdF[7][0])" ] }, { "cell_type": "code", "execution_count": null, "id": "f8673a05", "metadata": { "scrolled": false }, "outputs": [], "source": [ "# Para uso em máquina local (neste caso, o diretório remoto deverá ser montado localmente com o comando sshfs)\n", "# Exemplo: \n", "# $ sshfs username@egeon.cptec.inpe.br:/pesq/share/das/dist/joao.gerd/EXP18/GSI/dataout /extra2/EGEON_EXP18_GSI_dataout\n", "# ou\n", "# $ sshfs username@itapemirim.cptec.inpe.br:/share/das/dist/joao.gerd/EXP18/GSI/dataout /extra2/EGEON_EXP18_GSI_dataout\n", "# DIRdiag = '/extra2/EGEON_EXP18_GSI_dataout'\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepbufr_amsua_INPE/')\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepbufr_amsua_NCEP/')\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepbufr_conv_NCEP/')\n", "# dateIni = '2025082012' \n", "# dateFin = '2025082012'\n", "# nHour = '6'\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/IBIS/ATMS_AMSUA/gsi_dataout/SMNA_v3.0.0.t11889-atms-amsu/SMG/datainout/gsi/dataout/')\n", "# dateIni = '2025050906' #'2025082012' \n", "# dateFin = '2025050906' #'2025082012'\n", "# nHour = '6'\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepINPE_press')\n", "# # DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepNCEP_press')\n", "# dateIni = '2025090412' \n", "# dateFin = '2025090412'\n", "# nHour = '6'\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepINPE/i79') # Eduardo\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepINPE/DIMNT') # Sergio\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepNCEP') # NCEP\n", "# dateIni = '2025090412' \n", "# dateFin = '2025090412'\n", "# nHour = '6'\n", "\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP22/gsi/dataout/MELISSA/ATMS_AMSUA') # EXP22\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP22/gsi/dataout/MELISSA/AMSUA') # EXP22\n", "# dateIni = '2025080112' \n", "# dateFin = '2025080312'\n", "# nHour = '24'\n", "\n", "# dateIni = '2025102818' \n", "# dateFin = '2025102818'\n", "# nHour = '06'\n", "\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/Exps_DISSM_ATMS/2026041906_controle') # NCEP\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/Exps_DISSM_ATMS/2026041906_GTS-H5')\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/Exps_DISSM_ATMS/2026041906_DISSM-H5')\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/Exps_DISSM_ATMS/2026041906_atmsPYT_i95')\n", "# dateIni = '2026041906' \n", "# dateFin = '2026041906'\n", "# nHour = '6'\n", "\n", "# DIRdiag = '/mnt/beegfs/luiz.sapucci/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout'\n", "# DIRdiag = '/mnt/beegfs/ioper/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout'\n", "# dateIni = '2026090100' \n", "# dateFin = '2026090100'\n", "# nHour = '6'\n", "\n", "DIRdiag = '/mnt/beegfs/caroline.viezel/SMNA_v3.0.0.t12717/SMG/datainout/gsi/dataout/ATMS_SRF_warm-OCT-NOV2025'\n", "dateIni = '2025100112' \n", "dateFin = '2025100118'\n", "nHour = '6'\n", "\n", "\n", "varNames = ['amsua','atms'] #'amsua' , 'atms'] \n", "# varNames = ['atms'] #'amsua' , 'atms'] \n", "vminOMA = -1.0 \n", "vmaxOMA = 1.0 \n", "vminSTD = 0.0 \n", "vmaxSTD = 2.0 \n", "channel = 6 \n", "\n", "datei = datetime.strptime(str(dateIni), '%Y%m%d%H')\n", "datef = datetime.strptime(str(dateFin), '%Y%m%d%H')\n", "dates = [dates.strftime('%Y%m%d%H') for dates in pd.date_range(datei, datef,freq='6h').tolist()]\n", "\n", "print(dates)\n", "print('')\n", "\n", "for varName in varNames:\n", " \n", " print('******************** varName = '+varName+' ********************')\n", " print('')\n", " \n", " if varName == 'amsua':\n", " varTypes = ['metop-b', 'metop-c']\n", " else:\n", " varTypes = ['npp', 'n20', 'n21']\n", " \n", " ax = None\n", " for varType in varTypes:\n", " \n", " print('########## varType = '+varType+' ##########')\n", " print('')\n", " \n", " paths, pathsc = [], []\n", "\n", " OuterL = '01' \n", " [paths.append(DIRdiag + '/' + dt + '/diag_' + varName +'_'+ varType +'_' + OuterL + '.' + dt) for dt in dates]\n", "\n", " OuterLc = '03'\n", " [pathsc.append(DIRdiag + '/' + dt + '/diag_' + varName +'_'+ varType +'_' + OuterLc + '.' + dt) for dt in dates]\n", "\n", " print(paths)\n", " print('')\n", " print(pathsc)\n", "\n", " read = True\n", "\n", " if read: \n", " gdf_list = []\n", " print('')\n", "\n", " print('Aguarde, o tempo total estimado para a leitura dos arquivos é de ' +\n", " str(int((float(len(paths))*20)/60)) + ' minutos e ' +\n", " str(int((float(len(paths))*20)%60)) + ' segundos.')\n", "\n", " print('')\n", "\n", " for path, pathc in zip(paths, pathsc):\n", " print('Reading ' + path)\n", "\n", " gdf = gd.read_diag(path, pathc)\n", "\n", " gdf_list.append(gdf)\n", "\n", " print('Pronto!')\n", " \n", " tidx = 0\n", " gdf_list[tidx].pfileinfo()\n", " gdf_list[tidx].obsInfo\n", " df = gdf_list[tidx].obsInfo\n", " col = df.columns.tolist()\n", " print('columns', col)\n", "\n", " \n", " print('')\n", " print('Distribuição espacial channel -- dates')\n", " print('')\n", " if varName == 'amsua':\n", " channel = 7\n", " else:\n", " channel = 8\n", " \n", " print('Channel = ', channel)\n", " print('')\n", " param = 'obs' #'obs'\n", " minVal = 180 #180 #-1.0\n", " maxVal = 260 #250 #1.0\n", " #ax = None\n", " #area=[-120, -20, -60, 40] # sul america GEOPANDAS\n", " #area=[-100, -65, 5, 35] # Melissa GEOPANDAS\n", " area=None\n", " \n", " #atms_n20 14 1 0.800 0.800 2.000 10.000 \n", " #amsua_metop-b 13 1 0.800 0.800 4.500 10.000 \n", " #atms_n21 13 1 0.550 0.550 1.000 10.000\n", "\n", " forplot = 'Channel ='+str(channel)\n", " varInfo = getVarInfo(varType, varName, 'instrument')\n", " if varInfo is not None:\n", " #instrument_title = varInfo + \" | \" + str(param)\n", " instrument_title = varName + \" | \" + str(param)\n", " else:\n", " instrument_title = str(varName) + '-' + str(varType) + ' | ' + 'Unknown instrument' + \" | \" + str(param)\n", "\n", " for tidx in range(len(dates)):\n", " ax = gd.plot_diag.plot(gdf_list[tidx], \n", " varName=varName, \n", " varType=varType, \n", " param=param, \n", " minVal=minVal, \n", " maxVal=maxVal, \n", " mask=\"(nchan==\"+str(channel)+\")\", # & (iuse >= 1 & idqc == 0)\", # \"(nchan==\"+str(channel)+\")\", # (iuse >= 1 & idqc == 0)\", \n", " markersize=5.80,\n", " ax = ax,\n", " area = area, \n", " title = instrument_title, \n", " legend='true')\n", " \n", " \n", " \n", " for file in gdf_list:\n", " file.close()\n", " \n", "if ax != None:\n", " datefmt1 = dates[0]\n", " datefmt2 = dates[-1]\n", " date1 = datetime.strptime(str(datefmt1), \"%Y%m%d%H\")\n", " date2 = datetime.strptime(str(datefmt2), \"%Y%m%d%H\")\n", " #date_title = str(date1.strftime(\"%d%b%Y %H%M\")) + ' - ' + str(date2.strftime(\"%d%b%Y %H%M\")) #+ ' GMT'\n", " date_title = str(date1.strftime(\"%d%b%Y %H%M\")) + ' - ' + str(date2.strftime(\"%H%M\")) #+ ' GMT'\n", " ax.annotate(date_title, xy=(0.75, 1.015), xytext=(0, 0), xycoords='axes fraction', textcoords='offset points', \n", " fontsize=10, horizontalalignment='left', verticalalignment='center')\n", " plt.title(date_title, loc='right', fontsize=10)\n", " #plt.title(instrument_title, loc='left', fontsize=9)\n", " ax.annotate(forplot, xy=(0.65, 1.075), xytext=(0, 0), xycoords='axes fraction', textcoords='offset points', \n", " color='gray', fontweight='bold', fontsize='12',horizontalalignment='left', verticalalignment='center')\n", "\n", " #figname=varName+\"_\"+str(varType)+\"_\"+param+\"_\"+\"CH\"+str(channel)+\"_\"+\"SulAmerica_dates_ALL\"+\"_\"+\"plot.png\"\n", " #figname=varName+\"_\"+str(varType)+\"_\"+param+\"_\"+\"CH\"+str(channel)+\"_\"+\"Melissa_dates_ALL\"+\"_\"+\"plot.png\"\n", " figname=varName+\"_\"+str(varType)+\"_\"+param+\"_\"+\"CH\"+str(channel)+\"_\"+\"word_dates_ALL\"+\"_\"+\"plot.png\"\n", " plt.tight_layout()\n", " plt.savefig(figname)" ] }, { "cell_type": "code", "execution_count": null, "id": "c524c794", "metadata": { "scrolled": false, "tags": [] }, "outputs": [], "source": [ "# Para uso em máquina local (neste caso, o diretório remoto deverá ser montado localmente com o comando sshfs)\n", "# Exemplo: \n", "# $ sshfs username@egeon.cptec.inpe.br:/pesq/share/das/dist/joao.gerd/EXP18/GSI/dataout /extra2/EGEON_EXP18_GSI_dataout\n", "# ou\n", "# $ sshfs username@itapemirim.cptec.inpe.br:/share/das/dist/joao.gerd/EXP18/GSI/dataout /extra2/EGEON_EXP18_GSI_dataout\n", "# DIRdiag = '/extra2/EGEON_EXP18_GSI_dataout'\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepbufr_amsua_INPE/')\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepbufr_amsua_NCEP/')\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepbufr_conv_NCEP/')\n", "# dateIni = '2025082012' \n", "# dateFin = '2025082012'\n", "# nHour = '6'\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/IBIS/ATMS_AMSUA/gsi_dataout/SMNA_v3.0.0.t11889-atms-amsu/SMG/datainout/gsi/dataout/')\n", "# dateIni = '2025050906' #'2025082012' \n", "# dateFin = '2025050906' #'2025082012'\n", "# nHour = '6'\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepINPE_press')\n", "# # DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepNCEP_press')\n", "# dateIni = '2025090412' \n", "# dateFin = '2025090412'\n", "# nHour = '6'\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepINPE/i79') # Eduardo\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepINPE/DIMNT') # Sergio\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepNCEP') # NCEP\n", "# dateIni = '2025090412' \n", "# dateFin = '2025090412'\n", "# nHour = '6'\n", "\n", "\n", "DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP22/gsi/dataout/MELISSA/ATMS_AMSUA') # EXP22\n", "# dateIni = '2025080112' \n", "# dateFin = '2025080312'\n", "# nHour = '24'\n", "\n", "dateIni = '2025102800' \n", "dateFin = '2025102818'\n", "nHour = '06'\n", "\n", "\n", "varNames = ['amsua','atms'] #'amsua' , 'atms'] \n", "vminOMA = -1.0 \n", "vmaxOMA = 1.0 \n", "vminSTD = 0.0 \n", "vmaxSTD = 2.0 \n", "channel = 6 \n", "\n", "datei = datetime.strptime(str(dateIni), '%Y%m%d%H')\n", "datef = datetime.strptime(str(dateFin), '%Y%m%d%H')\n", "dates = [dates.strftime('%Y%m%d%H') for dates in pd.date_range(datei, datef,freq='6h').tolist()]\n", "\n", "print(dates)\n", "print('')\n", "\n", "for varName in varNames:\n", " \n", " print('******************** varName = '+varName+' ********************')\n", " print('')\n", " \n", " if varName == 'amsua':\n", " varTypes = ['metop-b', 'metop-c']\n", " else:\n", " varTypes = ['npp', 'n20', 'n21']\n", " \n", " ax = None\n", " for varType in varTypes:\n", " \n", " print('########## varType = '+varType+' ##########')\n", " print('')\n", " \n", " paths, pathsc = [], []\n", "\n", " OuterL = '01' \n", " [paths.append(DIRdiag + '/' + dt + '/diag_' + varName +'_'+ varType +'_' + OuterL + '.' + dt) for dt in dates]\n", "\n", " OuterLc = '03'\n", " [pathsc.append(DIRdiag + '/' + dt + '/diag_' + varName +'_'+ varType +'_' + OuterLc + '.' + dt) for dt in dates]\n", "\n", " print(paths)\n", " print('')\n", " print(pathsc)\n", "\n", " read = True\n", "\n", " if read: \n", " gdf_list = []\n", " print('')\n", "\n", " print('Aguarde, o tempo total estimado para a leitura dos arquivos é de ' +\n", " str(int((float(len(paths))*20)/60)) + ' minutos e ' +\n", " str(int((float(len(paths))*20)%60)) + ' segundos.')\n", "\n", " print('')\n", "\n", " for path, pathc in zip(paths, pathsc):\n", " print('Reading ' + path)\n", "\n", " gdf = gd.read_diag(path, pathc)\n", "\n", " gdf_list.append(gdf)\n", "\n", " print('Pronto!')\n", " \n", " tidx = 0\n", " gdf_list[tidx].pfileinfo()\n", " gdf_list[tidx].obsInfo\n", " df = gdf_list[tidx].obsInfo\n", " col = df.columns.tolist()\n", " print('columns', col)\n", " \n", "# print('Série temporal -- ASSIMILADOS mask=idqc==0 & iuse>=1')\n", "# print('')\n", "# channel = None\n", "# gd.plot_diag.time_series_radi(gdf_list,\n", "# varName=varName, \n", "# varType=varType, \n", "# mask='idqc==0 & iuse>=1', \n", "# dateIni=dateIni, \n", "# dateFin=dateFin, \n", "# nHour=nHour, \n", "# vminOMA=vminOMA, \n", "# vmaxOMA=vmaxOMA, \n", "# vminSTD=vminSTD, \n", "# vmaxSTD=vmaxSTD, \n", "# channel=channel, \n", "# Clean=False)\n", "# # renomear figuras\n", "# name_old_OMA = f'hovmoller_{varName}-{varType}_OmA.png'\n", "# name_old_OMF = f'hovmoller_{varName}-{varType}_OmF.png'\n", " \n", "# name_new_OMA = f'hovmoller_ASSi_{varName}-{varType}_OmA.png'\n", "# name_new_OMF = f'hovmoller_ASSi_{varName}-{varType}_OmF.png'\n", " \n", "# os.rename(name_old_OMA, name_new_OMA)\n", "# os.rename(name_old_OMF, name_new_OMF)\n", " \n", "# print('Série temporal -- REJEITADOS mask=idqc!=0 & iuse>=1')\n", "# print('')\n", "# channel = None\n", "# gd.plot_diag.time_series_radi(gdf_list,\n", "# varName=varName, \n", "# varType=varType, \n", "# mask='idqc!=0 & iuse>=1', \n", "# dateIni=dateIni, \n", "# dateFin=dateFin, \n", "# nHour=nHour, \n", "# vminOMA=vminOMA, \n", "# vmaxOMA=vmaxOMA, \n", "# vminSTD=vminSTD, \n", "# vmaxSTD=vmaxSTD, \n", "# channel=channel, \n", "# Clean=False)\n", "# # renomear figuras\n", "# name_old_OMA = f'hovmoller_{varName}-{varType}_OmA.png'\n", "# name_old_OMF = f'hovmoller_{varName}-{varType}_OmF.png'\n", " \n", "# name_new_OMA = f'hovmoller_REJEi_{varName}-{varType}_OmA.png'\n", "# name_new_OMF = f'hovmoller_REJEi_{varName}-{varType}_OmF.png'\n", " \n", "# os.rename(name_old_OMA, name_new_OMA)\n", "# os.rename(name_old_OMF, name_new_OMF)\n", " \n", "# print('Série temporal -- MONITORADOS-ASS mask=idqc==0 & iuse==-1')\n", "# print('')\n", "# channel = None\n", "# gd.plot_diag.time_series_radi(gdf_list,\n", "# varName=varName, \n", "# varType=varType, \n", "# mask='idqc==0 & iuse==-1', \n", "# dateIni=dateIni, \n", "# dateFin=dateFin, \n", "# nHour=nHour, \n", "# vminOMA=vminOMA, \n", "# vmaxOMA=vmaxOMA, \n", "# vminSTD=vminSTD, \n", "# vmaxSTD=vmaxSTD, \n", "# channel=channel, \n", "# Clean=False)\n", "# # renomear figuras\n", "# name_old_OMA = f'hovmoller_{varName}-{varType}_OmA.png'\n", "# name_old_OMF = f'hovmoller_{varName}-{varType}_OmF.png'\n", " \n", "# name_new_OMA = f'hovmoller_MASSi_{varName}-{varType}_OmA.png'\n", "# name_new_OMF = f'hovmoller_MASSi_{varName}-{varType}_OmF.png'\n", " \n", "# os.rename(name_old_OMA, name_new_OMA)\n", "# os.rename(name_old_OMF, name_new_OMF)\n", " \n", "# print('Série temporal -- MONITORADOS-REJE mask=idqc!=0 & iuse==-1')\n", "# print('')\n", "# channel = None\n", "# gd.plot_diag.time_series_radi(gdf_list,\n", "# varName=varName, \n", "# varType=varType, \n", "# mask='idqc!=0 & iuse==-1', \n", "# dateIni=dateIni, \n", "# dateFin=dateFin, \n", "# nHour=nHour, \n", "# vminOMA=vminOMA, \n", "# vmaxOMA=vmaxOMA, \n", "# vminSTD=vminSTD, \n", "# vmaxSTD=vmaxSTD, \n", "# channel=channel, \n", "# Clean=False)\n", "# # renomear figuras\n", "# name_old_OMA = f'hovmoller_{varName}-{varType}_OmA.png'\n", "# name_old_OMF = f'hovmoller_{varName}-{varType}_OmF.png'\n", " \n", "# name_new_OMA = f'hovmoller_MREJEi_{varName}-{varType}_OmA.png'\n", "# name_new_OMF = f'hovmoller_MREJEi_{varName}-{varType}_OmF.png'\n", " \n", "# os.rename(name_old_OMA, name_new_OMA)\n", "# os.rename(name_old_OMF, name_new_OMF)\n", " \n", " \n", "# print('Distribuição espacial channel -- ASSIMILADOS mask=idqc==0 & iuse>=1')\n", "# print('')\n", "# channel = 12\n", "# print('Channel = ', channel)\n", "# print('')\n", "# param = 'oma'\n", "# minVal = None #200.0\n", "# maxVal = None #250.0\n", "\n", "# forplot = 'Channel ='+str(channel)\n", "# varInfo = getVarInfo(varType, varName, 'instrument')\n", "# if varInfo is not None:\n", "# instrument_title = varInfo\n", "# else:\n", "# instrument_title = str(varName) + '-' + str(varType) + ' | ' + 'Unknown instrument'\n", "\n", "# ax = gd.plot_diag.plot(gdf_list[tidx], \n", "# varName=varName, \n", "# varType=varType, \n", "# param=param, \n", "# minVal=minVal, \n", "# maxVal=maxVal, \n", "# mask=\"(nchan==\"+str(channel)+\") & (iuse >= 1 & idqc == 0)\", \n", "# markersize=4.80, \n", "# legend='true')\n", "\n", "\n", "# if ax != None:\n", "# datefmt = dates[tidx]\n", "# date = datetime.strptime(str(datefmt), \"%Y%m%d%H\")\n", "# date_title = str(date.strftime(\"%d%b%Y - %H%M\")) + ' GMT'\n", "# plt.title(date_title, loc='right', fontsize=10)\n", "# #plt.title(instrument_title, loc='left', fontsize=9)\n", "# ax.annotate(forplot, xy=(0.75, 1.015), xytext=(0, 0), xycoords='axes fraction', textcoords='offset points', \n", "# color='gray', fontweight='bold', fontsize='10',horizontalalignment='left', verticalalignment='center')\n", "\n", "# figname=varName+\"_\"+str(varType)+\"_\"+param+\"_\"+\"CH\"+str(channel)+\"_\"+dates[tidx]+\"_\"+\"plot.png\"\n", "# plt.tight_layout()\n", "# plt.savefig(figname)\n", " \n", " \n", "# print('Distribuição espacial channel -- ASSIMILADOS mask=idqc==0 & iuse>=1')\n", "# print('')\n", "# channel = 13\n", "# print('Channel = ', channel)\n", "# print('')\n", "# param = 'obs'\n", "# minVal = 200.0\n", "# maxVal = 250.0\n", "\n", "# forplot = 'Channel ='+str(channel)\n", "# varInfo = getVarInfo(varType, varName, 'instrument')\n", "# if varInfo is not None:\n", "# instrument_title = varInfo\n", "# else:\n", "# instrument_title = str(varName) + '-' + str(varType) + ' | ' + 'Unknown instrument'\n", "\n", "# ax = gd.plot_diag.plot(gdf_list[tidx], \n", "# varName=varName, \n", "# varType=varType, \n", "# param=param, \n", "# minVal=minVal, \n", "# maxVal=maxVal, \n", "# mask=\"(nchan==\"+str(channel)+\") & (iuse >= 1 & idqc == 0)\", \n", "# markersize=4.80, \n", "# legend='true')\n", "\n", "# if ax != None:\n", "# datefmt = dates[tidx]\n", "# date = datetime.strptime(str(datefmt), \"%Y%m%d%H\")\n", "# date_title = str(date.strftime(\"%d%b%Y - %H%M\")) + ' GMT'\n", "# plt.title(date_title, loc='right', fontsize=10)\n", "# #plt.title(instrument_title, loc='left', fontsize=9)\n", "# ax.annotate(forplot, xy=(0.75, 1.015), xytext=(0, 0), xycoords='axes fraction', textcoords='offset points', \n", "# color='gray', fontweight='bold', fontsize='10',horizontalalignment='left', verticalalignment='center')\n", "\n", "# figname=varName+\"_\"+str(varType)+\"_\"+param+\"_\"+\"CH\"+str(channel)+\"_\"+dates[tidx]+\"_\"+\"plot.png\"\n", "# plt.tight_layout()\n", "# plt.savefig(figname)\n", "\n", " \n", " print('')\n", " print('Distribuição espacial channel -- dates')\n", " print('')\n", " channel = 9\n", " print('Channel = ', channel)\n", " print('')\n", " param = 'omf' #'obs'\n", " minVal = -1.0 #200 #180 #180 #-1.0\n", " maxVal = 1.0 #230 #260 #250 #1.0\n", " #ax = None\n", " area=[-120, -20, -60, 40] # sul america GEOPANDAS\n", " #area=[-100, -65, 5, 35] # Melissa GEOPANDAS\n", " \n", " #atms_n20 14 1 0.800 0.800 2.000 10.000 \n", " #amsua_metop-b 13 1 0.800 0.800 4.500 10.000 \n", " #atms_n21 13 1 0.550 0.550 1.000 10.000\n", "\n", " forplot = 'Channel ='+str(channel)\n", " varInfo = getVarInfo(varType, varName, 'instrument')\n", " if varInfo is not None:\n", " #instrument_title = varInfo + \" | \" + str(param)\n", " instrument_title = varName + \" | \" + str(param)\n", " else:\n", " instrument_title = str(varName) + '-' + str(varType) + ' | ' + 'Unknown instrument' + \" | \" + str(param)\n", "\n", " for tidx in range(len(dates)):\n", " ax = gd.plot_diag.plot(gdf_list[tidx], \n", " varName=varName, \n", " varType=varType, \n", " param=param, \n", " minVal=minVal, \n", " maxVal=maxVal, \n", " mask=\"(nchan==\"+str(channel)+\") & (iuse >= 1 & idqc == 0)\", \n", " markersize=4.80,\n", " ax = ax,\n", " area = area, \n", " title = instrument_title, \n", " legend='true')\n", " \n", " if ax != None:\n", " datefmt1 = dates[0]\n", " datefmt2 = dates[-1]\n", " date1 = datetime.strptime(str(datefmt1), \"%Y%m%d%H\")\n", " date2 = datetime.strptime(str(datefmt2), \"%Y%m%d%H\")\n", " #date_title = str(date1.strftime(\"%d%b%Y %H%M\")) + ' - ' + str(date2.strftime(\"%d%b%Y %H%M\")) #+ ' GMT'\n", " date_title = str(date1.strftime(\"%d%b%Y %H%M\")) + ' - ' + str(date2.strftime(\"%H%M\")) #+ ' GMT'\n", " ax.annotate(date_title, xy=(0.75, 1.015), xytext=(0, 0), xycoords='axes fraction', textcoords='offset points', \n", " fontsize=10, horizontalalignment='left', verticalalignment='center')\n", " #plt.title(date_title, loc='right', fontsize=10)\n", " #plt.title(instrument_title, loc='left', fontsize=9)\n", " ax.annotate(forplot, xy=(0.65, 1.075), xytext=(0, 0), xycoords='axes fraction', textcoords='offset points', \n", " color='gray', fontweight='bold', fontsize='12',horizontalalignment='left', verticalalignment='center')\n", "\n", " figname=varName+\"_\"+str(varType)+\"_\"+param+\"_\"+\"CH\"+str(channel)+\"_\"+\"SulAmerica_dates_ALL\"+\"_\"+\"plot.png\"\n", " #figname=varName+\"_\"+str(varType)+\"_\"+param+\"_\"+\"CH\"+str(channel)+\"_\"+\"Melissa_dates_ALL\"+\"_\"+\"plot.png\"\n", " plt.tight_layout()\n", " plt.savefig(figname)\n", " \n", " \n", "# print('')\n", "# print('Distribuição espacial channel -- dates - ASSIMILADOS')\n", "# print('')\n", "# channel = 13\n", "# print('Channel = ', channel)\n", "# print('')\n", "# param = 'oma'\n", "# minVal = -1.0\n", "# maxVal = 1.0\n", "# ax = None\n", "\n", "# forplot = 'Channel ='+str(channel)\n", "# varInfo = getVarInfo(varType, varName, 'instrument')\n", "# if varInfo is not None:\n", "# instrument_title = varInfo + \" | \" + str(param)\n", "# else:\n", "# instrument_title = str(varName) + '-' + str(varType) + ' | ' + 'Unknown instrument' + \" | \" + str(param)\n", "\n", "# for tidx in range(len(dates)):\n", "# ax = gd.plot_diag.plot(gdf_list[tidx], \n", "# varName=varName, \n", "# varType=varType, \n", "# param=param, \n", "# minVal=minVal, \n", "# maxVal=maxVal, \n", "# mask=\"(nchan==\"+str(channel)+\") & (iuse >= 1 & idqc == 0)\", \n", "# markersize=4.80,\n", "# ax = ax,\n", "# title = instrument_title, \n", "# legend='true')\n", " \n", "# if ax != None:\n", "# datefmt1 = dates[0]\n", "# datefmt2 = dates[-1]\n", "# date1 = datetime.strptime(str(datefmt1), \"%Y%m%d%H\")\n", "# date2 = datetime.strptime(str(datefmt2), \"%Y%m%d%H\")\n", "# date_title = str(date1.strftime(\"%d%b%Y %H%M\")) + ' - ' + str(date2.strftime(\"%d%b%Y %H%M\")) #+ ' GMT'\n", "# plt.title(date_title, loc='right', fontsize=10)\n", "# #plt.title(instrument_title, loc='left', fontsize=9)\n", "# ax.annotate(forplot, xy=(0.55, 1.015), xytext=(0, 0), xycoords='axes fraction', textcoords='offset points', \n", "# color='gray', fontweight='bold', fontsize='12',horizontalalignment='left', verticalalignment='center')\n", "\n", "# figname=varName+\"_\"+str(varType)+\"_\"+param+\"_\"+\"CH\"+str(channel)+\"_\"+\"dates_ASS\"+\"_\"+\"plot.png\"\n", "# plt.tight_layout()\n", "# plt.savefig(figname)\n", " \n", " \n", "# print('')\n", "# print('statcount --- Teste!')\n", "# print('')\n", "# channel = 13\n", "# print('Channel = ', channel)\n", "# # dateIni = '2024020100'\n", "# # dateFin = '2024020118'\n", "\n", "# gd.plot_diag.statcount(gdf_list, \n", "# varName=varName, \n", "# varType=varType, \n", "# noiqc=False, \n", "# dateIni=dateIni, \n", "# dateFin=dateFin, \n", "# nHour=nHour, \n", "# channel=channel, \n", "# figTS=True, \n", "# figMap=True, \n", "# markersize=4.80)\n", " \n", " \n", " for file in gdf_list:\n", " file.close()\n", " " ] }, { "cell_type": "code", "execution_count": null, "id": "56d768cc", "metadata": {}, "outputs": [], "source": [ "# Para uso em máquina local (neste caso, o diretório remoto deverá ser montado localmente com o comando sshfs)\n", "# Exemplo: \n", "# $ sshfs username@egeon.cptec.inpe.br:/pesq/share/das/dist/joao.gerd/EXP18/GSI/dataout /extra2/EGEON_EXP18_GSI_dataout\n", "# ou\n", "# $ sshfs username@itapemirim.cptec.inpe.br:/share/das/dist/joao.gerd/EXP18/GSI/dataout /extra2/EGEON_EXP18_GSI_dataout\n", "# DIRdiag = '/extra2/EGEON_EXP18_GSI_dataout'\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepbufr_amsua_INPE/')\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepbufr_amsua_NCEP/')\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepbufr_conv_NCEP/')\n", "# dateIni = '2025082012' \n", "# dateFin = '2025082012'\n", "# nHour = '6'\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/IBIS/ATMS_AMSUA/gsi_dataout/SMNA_v3.0.0.t11889-atms-amsu/SMG/datainout/gsi/dataout/')\n", "# dateIni = '2025050906' #'2025082012' \n", "# dateFin = '2025050906' #'2025082012'\n", "# nHour = '6'\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepINPE_press')\n", "# # DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepNCEP_press')\n", "# dateIni = '2025090412' \n", "# dateFin = '2025090412'\n", "# nHour = '6'\n", "\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepINPE/i79') # Eduardo\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepINPE/DIMNT') # Sergio\n", "# DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP_OBS/prepNCEP') # NCEP\n", "# dateIni = '2025090412' \n", "# dateFin = '2025090412'\n", "# nHour = '6'\n", "\n", "\n", "DIRdiag = os.path.join(os.getcwd(), '../../Exp_SMNA/data/EXP22/gsi/dataout') # EXP22\n", "dateIni = '2025081018' \n", "dateFin = '2025081112'\n", "nHour = '06'\n", "\n", "\n", "varNames = ['amsua'] #['amsua' , 'atms'] \n", "vminOMA = -1.0 \n", "vmaxOMA = 1.0 \n", "vminSTD = 0.0 \n", "vmaxSTD = 5.0 \n", "channel = 6 \n", "\n", "datei = datetime.strptime(str(dateIni), '%Y%m%d%H')\n", "datef = datetime.strptime(str(dateFin), '%Y%m%d%H')\n", "dates = [dates.strftime('%Y%m%d%H') for dates in pd.date_range(datei, datef,freq='6h').tolist()]\n", "\n", "print(dates)\n", "print('')\n", "\n", "for varName in varNames:\n", " \n", " print('******************** varName = '+varName+' ********************')\n", " print('')\n", " \n", " if varName == 'amsua':\n", " varTypes = ['metop-b', 'metop-c']\n", " else:\n", " varTypes = ['npp', 'n20', 'n21']\n", " \n", " for varType in varTypes:\n", " \n", " print('########## varType = '+varType+' ##########')\n", " print('')\n", " \n", " paths, pathsc = [], []\n", "\n", " OuterL = '01' \n", " [paths.append(DIRdiag + '/' + dt + '/diag_' + varName +'_'+ varType +'_' + OuterL + '.' + dt) for dt in dates]\n", "\n", " OuterLc = '03'\n", " [pathsc.append(DIRdiag + '/' + dt + '/diag_' + varName +'_'+ varType +'_' + OuterLc + '.' + dt) for dt in dates]\n", "\n", " print(paths)\n", " print('')\n", " print(pathsc)\n", "\n", " read = True\n", "\n", " if read: \n", " gdf_list = []\n", " print('')\n", "\n", " print('Aguarde, o tempo total estimado para a leitura dos arquivos é de ' +\n", " str(int((float(len(paths))*20)/60)) + ' minutos e ' +\n", " str(int((float(len(paths))*20)%60)) + ' segundos.')\n", "\n", " print('')\n", "\n", " for path, pathc in zip(paths, pathsc):\n", " print('Reading ' + path)\n", "\n", " gdf = gd.read_diag(path, pathc)\n", "\n", " gdf_list.append(gdf)\n", "\n", " print('Pronto!')\n", " \n", " tidx = 0\n", " gdf_list[tidx].pfileinfo()\n", " gdf_list[tidx].obsInfo\n", " df = gdf_list[tidx].obsInfo\n", " col = df.columns.tolist()\n", " print('columns', col)\n", " \n", " \n", " # Construção dataframe\n", " df0 = gdf_list[tidx]\n", " df0 = gdf_list[tidx].obsInfo[varName].loc[varType] #cria o dataframe (tabela)\n", " df0['amf'] = df0['omf'] - df0['omA'] # cria uma nova coluna na tabela que é a subtração oma-omf\n", " \n", " # Construção malha\n", " dx = 10.0\n", " dz = 10.0\n", " long_x = np.arange(0.0, 360.0+dx, dx)\n", " lat_z = np.arange(-90.0, 90.0+dz, dz)\n", " \n", " print('')\n", " print('Coordenadas vértices células')\n", " print('')\n", " print('long_x = ', long_x)\n", " print('')\n", " print('lat_z = ', lat_z)\n", " \n", " \n", " \n", " \n", " " ] }, { "cell_type": "code", "execution_count": null, "id": "403c4517", "metadata": {}, "outputs": [], "source": [ "dx = 10.0\n", "dz = 10.0\n", "long_x = np.arange(0.0, 360.0+dx, dx)\n", "lat_z = np.arange(-90.0, 90.0+dz, dz)\n", "\n", "print('')\n", "print('Coordenadas vértices células')\n", "print('')\n", "print('long_x = ', long_x)\n", "print('')\n", "print('lat_z = ', lat_z)\n", "\n", "\n", "# rng = np.random.default_rng() # Uses PCG64 by default\n", "\n", "# rngx=rng.uniform(size=(1, 5), low=0, high=360)\n", "# rngy=rng.uniform(size=(1, 5), low=-90, high=90)\n", "\n", "# rngx=rngx[0]\n", "# rngy=rngy[0]\n", "\n", "# valx = rngx.random()\n", "# valy = rngy.random()\n", "\n", "rngx = [92.78325182, 345.13029357, 228.54029907, 308.66783948, 146.4931305 ]\n", "\n", "rngy = [-6.71192731, 65.86833908, 29.59440363, 82.04119412, -46.98245988]\n", "\n", "print('')\n", "print('rngx = ', rngx)\n", "print('')\n", "print('rngy = ', rngy)\n", "\n", "for z in lat_z:\n", " for x in long_x:\n", " if any(elemento > 2 for elemento in minha_lista)\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "id": "655590bb", "metadata": { "tags": [] }, "outputs": [], "source": [ "gdf_list" ] }, { "cell_type": "markdown", "id": "28e3569a-1b5d-451d-9e15-720a9153e6b7", "metadata": {}, "source": [ "Fazendo `tidx = 0`, obtemos o primeiro objeto da lista `gdf_list`:" ] }, { "cell_type": "code", "execution_count": null, "id": "88d8af81", "metadata": { "tags": [] }, "outputs": [], "source": [ "tidx = 0\n", "gdf_list[tidx]" ] }, { "cell_type": "markdown", "id": "f4ad8170-bffd-4c93-a51a-5747b88478b1", "metadata": { "tags": [] }, "source": [ "### Obtendo informações dos arquivos\n", "\n", "Utilize a função `pfileinfo()` para obter uma lista das observações e seus respectivos tipos (`kx`) que estão contidos dentro do arquivo:" ] }, { "cell_type": "code", "execution_count": null, "id": "83af7ed8", "metadata": { "tags": [] }, "outputs": [], "source": [ "gdf_list[tidx].pfileinfo()" ] }, { "cell_type": "code", "execution_count": null, "id": "fb0af990", "metadata": {}, "outputs": [], "source": [ "gdf_list[tidx].obsInfo\n", "df = gdf_list[tidx].obsInfo\n", "col = df.columns.tolist()\n", "print('columns', col)\n", "mask = 'nchan == 6'\n", "df.query(mask).oma" ] }, { "cell_type": "markdown", "id": "baaf3d6a", "metadata": {}, "source": [ "## Utilização da classe `plot_diag`\n", "\n", "Observações: na tabela dos convencionais o `iuse` é `iusev` (mudar no mask)" ] }, { "cell_type": "markdown", "id": "ef2f11f6", "metadata": {}, "source": [ "### Série temporal\n", "\n", "\n", "A seguir são apresentadas as opções de figuras com a função `time_series_radi()` (nova função), incluída na classe `plot_diag`. Inicialmente é gerada uma figura com os parâmetros já fixados nesta seção. Em seguida são apresentadas figuras alterando o parâmetro `channel`.\n", "\n", "Plotando uma série temporal do OmA e OmF para os dados do canal setado na célula de definição das variáveis:" ] }, { "cell_type": "code", "execution_count": null, "id": "363f269f", "metadata": { "scrolled": false }, "outputs": [], "source": [ "channel = None\n", "# channel = [7, 8, 9, 10, 11, 12, 13, 14, 15]\n", "\n", "gd.plot_diag.time_series_radi(gdf_list,\n", " varName=varName, \n", " varType=varType, \n", " mask='idqc==0 & iuse>=1', \n", " dateIni=dateIni, \n", " dateFin=dateFin, \n", " nHour=nHour, \n", " vminOMA=vminOMA, \n", " vmaxOMA=vmaxOMA, \n", " vminSTD=vminSTD, \n", " vmaxSTD=vmaxSTD, \n", " channel=channel, \n", " Clean=False)" ] }, { "cell_type": "markdown", "id": "a04f193a", "metadata": {}, "source": [ "### Distribuição espacial" ] }, { "cell_type": "code", "execution_count": null, "id": "a6297ca3", "metadata": { "scrolled": false }, "outputs": [], "source": [ "varNames = ['ps','t','q','uv','gps']\n", "\n", "for varName in varNames:\n", " print('varName: ', varName)\n", " try:\n", " varTypes = var_kxs[varName]\n", " print('varTypes: ', varTypes)\n", " print('')\n", " \n", " # Todas as obs da variável\n", " idschar = '_'.join([str(item) for item in varTypes])\n", " gd.plot_diag.ptmap(gdf_list[tidx], varName=varName, varType=varTypes)\n", " figname = varName + '_' + idschar + '_' + 'ptmap.png'\n", " plt.tight_layout()\n", " plt.savefig(figname)\n", " \n", " # Todas as obs assimiladas\n", " varNames = [varName]\n", " idschar = '_'.join([str(item) for item in varNames])\n", " gd.plot_diag.pvmap(gdf_list[tidx], varName=varNames, mask='iuse==1')\n", " figname = idschar + '_pvmap.png'\n", " plt.tight_layout()\n", " plt.savefig(figname)\n", " \n", " except:\n", " print('warning --- not kx varName ', varName)\n", " print('')" ] }, { "cell_type": "code", "execution_count": null, "id": "6c16f7d1", "metadata": { "tags": [] }, "outputs": [], "source": [ "param = 'iuse'\n", "tidx = 0\n", "\n", "gd.plot_diag.plot(gdf_list[tidx], \n", " varName=varName, \n", " varType=varType, \n", " param=param, \n", " mask='iuse >= -1', \n", " legend='true')" ] }, { "cell_type": "markdown", "id": "f82df541", "metadata": {}, "source": [ "Para salvar a figura, defina o seu nome (`figname`) e execute os comandos a seguir:" ] }, { "cell_type": "code", "execution_count": null, "id": "84169c19", "metadata": { "tags": [] }, "outputs": [], "source": [ "figname = varName + '_' + param + '_' + 'plot.png'\n", "\n", "plt.tight_layout()\n", "plt.savefig(figname)" ] }, { "cell_type": "markdown", "id": "2a240e9d-3d2a-48e3-a76a-f09fc6331a1d", "metadata": {}, "source": [ "Gerando a mesma figura, mas considerando vários tipos diferentes (`kx`) da observação selecionada:" ] }, { "cell_type": "code", "execution_count": null, "id": "0be7a398", "metadata": { "tags": [] }, "outputs": [], "source": [ "# varTypes = [254,242,221,220,257,258,281,280]\n", "##### PrepBufr - INPE\n", "# # varTypes = [244, 260, 255, 281, 253, 243, 254, 220, 252, 242, 250, 245, 246, 240, 247]\n", "# varTypes = [244, 260, 255, 281, 220, 253, 243, 254, 280, 230, 252, 242, 250, 245, 247, 246, 240]\n", "# varName = 'uv'\n", "# # varTypes = [269, 267, 42, 3, 66, 755, 753, 5, 751, 44, 43, 825]\n", "# varTypes = [267, 269, 3, 5, 66, 753, 751, 754, 750, 755, 44, 42, 43, 825]\n", "# varName = 'gps'\n", "# # varTypes = [120]\n", "# varTypes = []\n", "# varName = 'q'\n", "# # varTypes = [181, 120]\n", "# varTypes = [181, 120, 180, 130]\n", "# varName = 't'\n", "# # varTypes = [181, 120]\n", "varTypes = [181, 180]\n", "varName = 'ps'\n", "#### PrepBufr - NCEP\n", "# # varTypes = [244, 260, 255, 281, 253, 243, 254, 220, 287, 280, 284, 221, 230, 252, 242,\n", "# # 250, 210, 245, 246, 240, 247, 224, 232]\n", "# varTypes = [244, 260, 255, 281, 253, 243, 254, 287, 280, 284, 221, 220, 252, 242, 250,\n", "# 210, 245, 247, 246, 240, 230, 224, 232]\n", "# varName = 'uv'\n", "# # varTypes = [269, 267, 42, 3, 66, 755, 753, 5, 751, 44, 43, 825]\n", "# varTypes = [267, 269, 3, 5, 66, 753, 751, 754, 750, 755, 44, 42, 43, 825]\n", "# varName = 'gps'\n", "# # varTypes = [181, 120, 187, 180, 183, 132, 182]\n", "# varTypes = [181, 187, 180, 183, 120, 132]\n", "# varName = 'q'\n", "# # varTypes = [181, 120, 187, 180, 183, 130, 126, 132, 182]\n", "# varTypes = [181, 187, 180, 183, 120, 130, 132, 126]\n", "# varName = 't'\n", "# # varTypes = [181, 180, 120, 187, 183, 132, 182]\n", "# varTypes = [181, 180, 187, 183, 120]\n", "# varName = 'ps'\n", "idschar = '_'.join([str(item) for item in varTypes])\n", "\n", "gd.plot_diag.ptmap(gdf_list[tidx], varName=varName, varType=varTypes)\n", "\n", "figname = varName + '_' + idschar + '_' + 'ptmap.png'\n", "\n", "plt.tight_layout()\n", "plt.savefig(figname)" ] }, { "cell_type": "markdown", "id": "fb0eaa77-fca0-4be6-8d82-1ef7794bab0b", "metadata": {}, "source": [ "Gerando uma figura com diferentes variáveis, considerando a máscara `iuse==1`:" ] }, { "cell_type": "code", "execution_count": null, "id": "8bdc6d6a", "metadata": { "tags": [] }, "outputs": [], "source": [ "varNames = ['t'] #['uv','ps','t']\n", "idschar = '_'.join([str(item) for item in varNames])\n", "\n", "gd.plot_diag.pvmap(gdf_list[tidx], varName=varNames, mask='iuse==1')\n", "\n", "figname = idschar + '_pvmap.png'\n", "\n", "plt.tight_layout()\n", "plt.savefig(figname)" ] }, { "cell_type": "markdown", "id": "a48cf904-ad49-4d2e-9415-6bec88ab48cc", "metadata": {}, "source": [ "### Histograma\n", "\n", "Utilize a função `pcount()` da classe `plot_diag` para obter um histograma com a contagem do número de observações para uma determinada variável:" ] }, { "cell_type": "code", "execution_count": null, "id": "078f84a8", "metadata": { "tags": [] }, "outputs": [], "source": [ "varName = 't'\n", "gd.plot_diag.pcount(gdf_list[tidx], varName)" ] }, { "cell_type": "markdown", "id": "368a57ec-9e04-4394-a9d7-4cb4bba1b0a3", "metadata": {}, "source": [ "Utilize a função `vcount()` da classe `plot_diag` para obter um histograma com a contagem do número de observações para todos os tipos de variáveis:" ] }, { "cell_type": "code", "execution_count": null, "id": "b1d44398", "metadata": { "tags": [] }, "outputs": [], "source": [ "gd.plot_diag.vcount(gdf_list[tidx])\n", "\n", "idschar = 'All_varNames'\n", "figname = idschar + '_vcount.png'\n", "\n", "plt.tight_layout()\n", "plt.savefig(figname)" ] }, { "cell_type": "markdown", "id": "f50747e4-44c9-48d3-a150-ec640573cb18", "metadata": {}, "source": [ "De forma semelhante, utilize a função `kxcount()` da classe `plot_diag` para obter um histograma com a contagem do número de observações por tipo:" ] }, { "cell_type": "code", "execution_count": null, "id": "46deda00", "metadata": { "tags": [] }, "outputs": [], "source": [ "gd.plot_diag.kxcount(gdf_list[tidx])" ] }, { "cell_type": "markdown", "id": "deb35f54", "metadata": {}, "source": [ "### Série temporal\n", "\n", "\n", "A seguir são apresentadas as opções de figuras com a função `time_series()`, incluída na classe `plot_diag`. Inicialmente é gerada uma figura com os parâmetros já fixados nesta seção. Em seguida são apresentadas figuras alterando os parâmetros `Level`, `Lay` e `SingleL`.\n", "\n", "Plotando uma série temporal do OmA e OmF:" ] }, { "cell_type": "code", "execution_count": null, "id": "241bc9fc", "metadata": { "tags": [] }, "outputs": [], "source": [ "gd.plot_diag.time_series(gdf_list,\n", " varName=varName, \n", " varType=varType, \n", " dateIni=dateIni, \n", " dateFin=dateFin, \n", " nHour=nHour, \n", " vminOMA=vminOMA, \n", " vmaxOMA=vmaxOMA, \n", " vminSTD=vminSTD, \n", " vmaxSTD=vmaxSTD, \n", " Level=Level, \n", " Lay=Lay, \n", " SingleL=SingleL,\n", " Clean=False)" ] }, { "cell_type": "markdown", "id": "905097b2", "metadata": {}, "source": [ "No caso anterior, o parâmetro `Level` estava fixo em 1000 hPa com `SingleL` igual a `All`, ou seja, toda a atmosfera foi considerada como uma única camada e o valor 1000 hPa funciona apenas como uma flag para indicar que não existe variação em altura. Ainda com `Level=1000`, pode-se usar `SingleL='OneL'` para uma única camada em torno do valor de `Level`, neste caso 1000 hPa, variando entre `Level-Lay` e `Level+Lay` (na definição de variáveis, `Lay` foi fixado com 15 hPa; no caso de ser `None`, o valor padrão de 50 hPa é utilizado)." ] }, { "cell_type": "code", "execution_count": null, "id": "565623bd", "metadata": { "tags": [] }, "outputs": [], "source": [ "SingleL = 'OneL'\n", "Lay = 15\n", "\n", "gd.plot_diag.time_series(gdf_list,\n", " varName=varName, \n", " varType=varType, \n", " dateIni=dateIni, \n", " dateFin=dateFin, \n", " nHour=nHour, \n", " vminOMA=vminOMA, \n", " vmaxOMA=vmaxOMA, \n", " vminSTD=vminSTD, \n", " vmaxSTD=vmaxSTD, \n", " Level=Level, \n", " Lay=Lay, \n", " SingleL=SingleL,\n", " Clean=False)" ] }, { "cell_type": "markdown", "id": "8771f5b9", "metadata": {}, "source": [ "Observe como no exemplo acima a quantidade de dados diminui, uma vez que agora está sendo utilizada uma camada entre 1015 e 985 hPa.\n", "\n", "Agora vamos alterar para não fixar em um único nível ou camada, ou seja, altear a variável `Level` para `None` ou `Zlevs`. A opção `None` busca os dados em cada nível existente nos arquivos e faz a figura para todos esses níveis, porém os valores no eixo y (ordenada) são apenas dos níveis padrão. É importante esclarecer que os chamados níveis padrão estão definidos na classe `read_diag` e podem ser acessados utilizando o método `zlevs` da seguinte forma:" ] }, { "cell_type": "code", "execution_count": null, "id": "269a1812", "metadata": { "tags": [] }, "outputs": [], "source": [ "gdf_list[tidx].zlevs" ] }, { "cell_type": "markdown", "id": "29f63a5f-8d2c-4e8d-a292-89a484740c06", "metadata": {}, "source": [ "Dessa forma, pode-se utilizar o parâmetro `Level='Zlevs'` para produzir uma série temporal por níveis:" ] }, { "cell_type": "code", "execution_count": null, "id": "7b8695b3", "metadata": { "tags": [] }, "outputs": [], "source": [ "Level = 'Zlevs'\n", "Lay = 15\n", "\n", "gd.plot_diag.time_series(gdf_list,\n", " varName=varName, \n", " varType=varType, \n", " dateIni=dateIni, \n", " dateFin=dateFin, \n", " nHour=nHour, \n", " vminOMA=vminOMA, \n", " vmaxOMA=vmaxOMA, \n", " vminSTD=vminSTD, \n", " vmaxSTD=vmaxSTD, \n", " Level=Level, \n", " Lay=Lay, \n", " SingleL=SingleL,\n", " Clean=False)" ] }, { "cell_type": "markdown", "id": "168e33f3", "metadata": {}, "source": [ "Se `Lay=None`, então as camadas são preenchidas variando entre o valor médio considerando as camadas inferiores e superiores. Por exemplo, para o nível de 700 hPa é construída uma camada entre 750 e 650 hPa, uma vez que os níveis inferiores e superiores são 800 e 600 hPa, respectivamente. Para o nível de 1000 hPa a camada varia entre 1050 e 950 hPa.\n", "\n", "O mesmo exemplo anterior, mas considerando `Level='Zlevs'`:" ] }, { "cell_type": "code", "execution_count": null, "id": "369095b9", "metadata": { "tags": [] }, "outputs": [], "source": [ "Level = 'Zlevs'\n", "Lay = None\n", "\n", "gd.plot_diag.time_series(gdf_list,\n", " varName=varName, \n", " varType=varType, \n", " dateIni=dateIni, \n", " dateFin=dateFin, \n", " nHour=nHour, \n", " vminOMA=vminOMA, \n", " vmaxOMA=vmaxOMA, \n", " vminSTD=vminSTD, \n", " vmaxSTD=vmaxSTD, \n", " Level=Level, \n", " Lay=Lay, \n", " SingleL=SingleL,\n", " Clean=False)" ] }, { "cell_type": "markdown", "id": "f65d75eb", "metadata": {}, "source": [ "Finalmente, existe a opção de se considerar todos os níveis, ou seja, `Level=None`. Esta opção traz certa dificuldade na visualização da informação na figura por conta da grande quantidade de níveis e distribuição dos dados em todos os níveis:" ] }, { "cell_type": "code", "execution_count": null, "id": "c4a84f15", "metadata": { "tags": [] }, "outputs": [], "source": [ "Level = None\n", "\n", "gd.plot_diag.time_series(gdf_list,\n", " varName=varName, \n", " varType=varType, \n", " dateIni=dateIni, \n", " dateFin=dateFin, \n", " nHour=nHour, \n", " vminOMA=vminOMA, \n", " vmaxOMA=vmaxOMA, \n", " vminSTD=vminSTD, \n", " vmaxSTD=vmaxSTD, \n", " Level=Level, \n", " Lay=Lay, \n", " SingleL=SingleL,\n", " Clean=False)" ] }, { "cell_type": "markdown", "id": "64ddd69e-cecb-458b-b25f-27820feaa636", "metadata": {}, "source": [ "Finalizado o uso dos arquivos, feche-os para liberar a memória utilizada:" ] }, { "cell_type": "code", "execution_count": null, "id": "9e95c31d-1cff-4047-a53e-5d5b11534aa2", "metadata": { "tags": [] }, "outputs": [], "source": [ "for file in gdf_list:\n", " file.close()" ] }, { "cell_type": "markdown", "id": "ab17d898", "metadata": {}, "source": [ "O `readDiag` é um pacote em desenvolvimento e em constante atualização. Novas funcionalidades serão adicionadas e demonstradas por meio deste notebook." ] }, { "cell_type": "code", "execution_count": null, "id": "eefbad7e-cccf-4a99-be5f-aa4d5c2dd642", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "readDiagGerd", "language": "python", "name": "readdiaggerd" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.14" } }, "nbformat": 4, "nbformat_minor": 5 }