From e888d2bc203d2b967b7c6d32e70c44d71fb0ab0a Mon Sep 17 00:00:00 2001 From: liaozhaorun Date: Thu, 3 Apr 2025 00:45:25 +0800 Subject: [PATCH] =?UTF-8?q?=E7=96=91=E4=BC=BC=E8=B5=9A=E9=92=B1rank?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- code/train/Rank.ipynb | 433 +++++++++++++++++++++++++----------------- 1 file changed, 256 insertions(+), 177 deletions(-) diff --git a/code/train/Rank.ipynb b/code/train/Rank.ipynb index 44a5187..5c1fdda 100644 --- a/code/train/Rank.ipynb +++ b/code/train/Rank.ipynb @@ -8,8 +8,8 @@ "source_hidden": true }, "ExecuteTime": { - "end_time": "2025-03-31T14:48:00.476292Z", - "start_time": "2025-03-31T14:47:59.982503Z" + "end_time": "2025-04-02T14:12:37.373532Z", + "start_time": "2025-04-02T14:12:36.959182Z" } }, "source": [ @@ -32,8 +32,8 @@ "metadata": { "scrolled": true, "ExecuteTime": { - "end_time": "2025-03-31T14:48:58.450443Z", - "start_time": "2025-03-31T14:48:00.733543Z" + "end_time": "2025-04-02T14:13:37.437375Z", + "start_time": "2025-04-02T14:12:37.383638Z" } }, "source": [ @@ -129,8 +129,8 @@ "id": "cac01788dac10678", "metadata": { "ExecuteTime": { - "end_time": "2025-03-31T14:49:13.957935Z", - "start_time": "2025-03-31T14:48:58.472449Z" + "end_time": "2025-04-02T14:13:49.617975Z", + "start_time": "2025-04-02T14:13:37.783573Z" } }, "source": [ @@ -200,8 +200,8 @@ "source_hidden": true }, "ExecuteTime": { - "end_time": "2025-03-31T14:49:14.289341Z", - "start_time": "2025-03-31T14:49:14.053158Z" + "end_time": "2025-04-02T14:13:49.892104Z", + "start_time": "2025-04-02T14:13:49.635085Z" } }, "source": [ @@ -289,21 +289,100 @@ "id": "a735bc02ceb4d872", "metadata": { "ExecuteTime": { - "end_time": "2025-03-31T14:49:14.359139Z", - "start_time": "2025-03-31T14:49:14.310625Z" + "end_time": "2025-04-02T15:03:19.084540Z", + "start_time": "2025-04-02T15:03:19.044068Z" } }, "source": [ "import numpy as np\n", "import talib\n", "\n", - "\n", "def get_rolling_factor(df):\n", " old_columns = df.columns.tolist()[:]\n", - " # 按股票和日期排序\n", + "\n", + "\n", + " # 按股票和日期排序（如果尚未排序）\n", " df = df.sort_values(by=['ts_code', 'trade_date'])\n", + "\n", " grouped = df.groupby('ts_code', group_keys=False)\n", "\n", + " # 提前计算布尔掩码\n", + " window = 20\n", + " return_threshold = 0.0\n", + "\n", + " df['_is_upside'] = df['pct_chg'] > return_threshold\n", + " df['_is_downside'] = df['pct_chg'] < -return_threshold\n", + " \n", + " # 1. 上行波动率 (20日)\n", + " def rolling_upside_volatility(series, _is_upside, window):\n", + " # 提取正收益\n", + " positive_returns = series.where(_is_upside, np.nan)\n", + " # 计算滚动窗口标准差\n", + " return positive_returns.rolling(window=window, min_periods=2).std()\n", + " \n", + " df[f'upside_volatility_{window}'] = grouped.apply(\n", + " lambda x: rolling_upside_volatility(x['pct_chg'], x['_is_upside'], window)\n", + " ).reset_index(level=0, drop=True)\n", + " \n", + " # 2. 下行波动率 (20日)\n", + " def rolling_downside_volatility(series, _is_downside, window):\n", + " # 提取负收益\n", + " negative_returns = series.where(_is_downside, np.nan)\n", + " # 计算滚动窗口标准差\n", + " return negative_returns.rolling(window=window, min_periods=2).std()\n", + " \n", + " df[f'downside_volatility_{window}'] = grouped.apply(\n", + " lambda x: rolling_downside_volatility(x['pct_chg'], x['_is_downside'], window)\n", + " ).reset_index(level=0, drop=True)\n", + " \n", + " # 3. 上行/下行波动率比率 (20日)\n", + " df[f'volatility_ratio_{window}'] = df[f'upside_volatility_{window}'] / (df[f'downside_volatility_{window}'] + 1e-8)\n", + " \n", + " # 4. 上行半方差 (20日)\n", + " def rolling_upside_semi_variance(series, _is_upside, window, threshold):\n", + " # 提取正收益\n", + " positive_returns = series.where(_is_upside, np.nan)\n", + " # 计算平方偏差\n", + " squared_deviation = (positive_returns - threshold)**2\n", + " # 计算滚动窗口均值\n", + " return squared_deviation.rolling(window=window, min_periods=2).mean()\n", + " \n", + " df[f'upside_semi_variance_{window}'] = grouped.apply(\n", + " lambda x: rolling_upside_semi_variance(x['pct_chg'], x['_is_upside'], window, return_threshold)\n", + " ).reset_index(level=0, drop=True)\n", + " \n", + " # 5. 下行半方差 (20日)\n", + " def rolling_downside_semi_variance(series, _is_downside, window, threshold):\n", + " # 提取负收益\n", + " negative_returns = series.where(_is_downside, np.nan)\n", + " # 计算平方偏差\n", + " squared_deviation = (negative_returns - (-threshold))**2\n", + " # 计算滚动窗口均值\n", + " return squared_deviation.rolling(window=window, min_periods=2).mean()\n", + " \n", + " df[f'downside_semi_variance_{window}'] = grouped.apply(\n", + " lambda x: rolling_downside_semi_variance(x['pct_chg'], x['_is_downside'], window, return_threshold)\n", + " ).reset_index(level=0, drop=True)\n", + "\n", + " # 8. 正负收益天数比率 (20日)\n", + " df[f'positive_negative_days_ratio_{window}'] = grouped['pct_chg'].rolling(window=window, min_periods=2).apply(lambda x: np.sum(x > 0) / (np.sum(x < 0) + 1e-8)).reset_index(level=0, drop=True)\n", + "\n", + " # 9. 正收益幅度均值 (20日)\n", + " def average_positive_return_magnitude(series):\n", + " positive_returns = series[series > return_threshold]\n", + " if positive_returns.empty:\n", + " return 0\n", + " return positive_returns.mean()\n", + " df[f'avg_positive_return_magnitude_{window}'] = grouped['pct_chg'].rolling(window=window, min_periods=2).apply(average_positive_return_magnitude).reset_index(level=0, drop=True)\n", + "\n", + " # 10. 负收益幅度均值 (20日)\n", + " def average_negative_return_magnitude(series):\n", + " negative_returns = series[series < -return_threshold]\n", + " if negative_returns.empty:\n", + " return 0\n", + " return np.abs(negative_returns.mean())\n", + " df[f'avg_negative_return_magnitude_{window}'] = grouped['pct_chg'].rolling(window=window, min_periods=2).apply(average_negative_return_magnitude).reset_index(level=0, drop=True)\n", + "\n", " # df[\"gap_next_open\"] = (df[\"open\"].shift(-1) - df[\"close\"]) / df[\"close\"]\n", "\n", " df['return_skew'] = grouped['pct_chg'].rolling(window=5).skew().reset_index(0, drop=True)\n", @@ -507,7 +586,7 @@ " df[\"br\"] = df[\"br_up\"].rolling(3).sum() / df[\"br_down\"].rolling(3).sum() * 100\n", " df['arbr'] = df['ar'] - df['br']\n", " df.drop(columns=[\"pre_close\", \"br_up\", \"br_down\", 'ar', 'br'], inplace=True)\n", - " \n", + "\n", " df.drop(columns=['weight_std20'], inplace=True, errors='ignore')\n", " new_columns = [col for col in df.columns.tolist()[:] if col not in old_columns]\n", "\n", @@ -595,7 +674,7 @@ " return df, new_columns\n" ], "outputs": [], - "execution_count": 5 + "execution_count": 20 }, { "cell_type": "code", @@ -606,8 +685,8 @@ }, "scrolled": true, "ExecuteTime": { - "end_time": "2025-03-31T14:49:20.203711Z", - "start_time": "2025-03-31T14:49:14.390412Z" + "end_time": "2025-04-02T15:03:25.185749Z", + "start_time": "2025-04-02T15:03:19.095058Z" } }, "source": [ @@ -658,15 +737,15 @@ "industry_df = read_industry_data('../../data/sw_daily.h5')\n" ], "outputs": [], - "execution_count": 6 + "execution_count": 21 }, { "cell_type": "code", "id": "dbe2fd8021b9417f", "metadata": { "ExecuteTime": { - "end_time": "2025-03-31T14:49:20.248588Z", - "start_time": "2025-03-31T14:49:20.244295Z" + "end_time": "2025-04-02T15:03:25.217714Z", + "start_time": "2025-04-02T15:03:25.211561Z" } }, "source": [ @@ -682,19 +761,19 @@ "name": "stdout", "output_type": "stream", "text": [ - "['ts_code', 'open', 'close', 'high', 'low', 'circ_mv', 'is_st', 'up_limit', 'down_limit', 'buy_sm_vol', 'sell_sm_vol', 'buy_lg_vol', 'sell_lg_vol', 'buy_elg_vol', 'sell_elg_vol', 'net_mf_vol', 'his_low', 'his_high', 'cost_5pct', 'cost_15pct', 'cost_50pct', 'cost_85pct', 'cost_95pct', 'weight_avg', 'in_date']\n" + "['ts_code', 'open', 'close', 'high', 'low', 'circ_mv', 'is_st', 'up_limit', 'down_limit', 'buy_sm_vol', 'sell_sm_vol', 'buy_lg_vol', 'sell_lg_vol', 'buy_elg_vol', 'sell_elg_vol', 'net_mf_vol', 'his_low', 'his_high', 'cost_5pct', 'cost_15pct', 'cost_50pct', 'cost_85pct', 'cost_95pct', 'weight_avg']\n" ] } ], - "execution_count": 7 + "execution_count": 22 }, { "cell_type": "code", "id": "85c3e3d0235ffffa", "metadata": { "ExecuteTime": { - "end_time": "2025-03-31T14:49:20.471125Z", - "start_time": "2025-03-31T14:49:20.288287Z" + "end_time": "2025-04-02T15:03:25.263787Z", + "start_time": "2025-04-02T15:03:25.256627Z" } }, "source": [ @@ -705,32 +784,21 @@ "name": "stdout", "output_type": "stream", "text": [ - " ts_code trade_date is_st\n", - "29 000037.SZ 2017-01-03 True\n", - "72 000408.SZ 2017-01-03 True\n", - "95 000504.SZ 2017-01-03 True\n", - "96 000505.SZ 2017-01-03 True\n", - "101 000511.SZ 2017-01-03 True\n", - "... ... ... ...\n", - "8476334 603869.SH 2025-03-28 True\n", - "8476339 603879.SH 2025-03-28 True\n", - "8476386 603959.SH 2025-03-28 True\n", - "8476769 688282.SH 2025-03-28 True\n", - "8476773 688287.SH 2025-03-28 True\n", - "\n", - "[192712 rows x 3 columns]\n" + "Empty DataFrame\n", + "Columns: [ts_code, trade_date, is_st]\n", + "Index: []\n" ] } ], - "execution_count": 8 + "execution_count": 23 }, { "cell_type": "code", "id": "92d84ce15a562ec6", "metadata": { "ExecuteTime": { - "end_time": "2025-03-31T14:53:44.202296Z", - "start_time": "2025-03-31T14:51:08.550768Z" + "end_time": "2025-04-02T15:26:42.881004Z", + "start_time": "2025-04-02T15:03:25.275794Z" } }, "source": [ @@ -742,7 +810,8 @@ " df = df[~df['ts_code'].str.startswith('68')]\n", " df = df[~df['ts_code'].str.startswith('8')]\n", " df = df[df['trade_date'] >= '20180101']\n", - " df = df.drop(columns=['in_date'])\n", + " if 'in_date' in df.columns:\n", + " df = df.drop(columns=['in_date'])\n", " df = df.reset_index(drop=True)\n", " return df\n", "\n", @@ -770,29 +839,26 @@ "text": [ "\n", "Index: 5118212 entries, 0 to 5118211\n", - "Columns: 115 entries, ts_code to mv_momentum\n", - "dtypes: bool(12), datetime64[ns](1), float64(98), int32(1), int64(1), object(2)\n", - "memory usage: 4.0+ GB\n", + "Columns: 123 entries, ts_code to mv_momentum\n", + "dtypes: bool(12), datetime64[ns](1), float64(106), int32(1), int64(1), object(2)\n", + "memory usage: 4.3+ GB\n", "None\n" ] } ], - "execution_count": 10 + "execution_count": 24 }, { "cell_type": "code", "id": "b87b938028afa206", "metadata": { "ExecuteTime": { - "end_time": "2025-03-31T14:53:47.033579Z", - "start_time": "2025-03-31T14:53:45.267610Z" + "end_time": "2025-04-02T15:26:44.711178Z", + "start_time": "2025-04-02T15:26:43.785812Z" } }, "source": [ "from scipy.stats import ks_2samp, wasserstein_distance\n", - "from sklearn.metrics import roc_auc_score\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.preprocessing import StandardScaler\n", "\n", "\n", "def remove_shifted_features(train_data, test_data, feature_columns, ks_threshold=0.05, wasserstein_threshold=0.1,\n", @@ -818,15 +884,15 @@ "\n" ], "outputs": [], - "execution_count": 11 + "execution_count": 25 }, { "cell_type": "code", "id": "f4f16d63ad18d1bc", "metadata": { "ExecuteTime": { - "end_time": "2025-03-31T14:53:47.069023Z", - "start_time": "2025-03-31T14:53:47.064157Z" + "end_time": "2025-04-02T15:26:44.722470Z", + "start_time": "2025-04-02T15:26:44.717192Z" } }, "source": [ @@ -867,15 +933,18 @@ " return df, ret_feature_columns\n" ], "outputs": [], - "execution_count": 12 + "execution_count": 26 }, { "cell_type": "code", "id": "40e6b68a91b30c79", "metadata": { + "jupyter": { + "source_hidden": true + }, "ExecuteTime": { - "end_time": "2025-03-31T14:53:48.018649Z", - "start_time": "2025-03-31T14:53:47.170060Z" + "end_time": "2025-04-02T15:26:45.656660Z", + "start_time": "2025-04-02T15:26:44.774542Z" } }, "source": [ @@ -956,9 +1025,11 @@ " or 'act' in col or 'af' in col]\n", " return remaining_features\n", "\n", + "\n", "import pandas as pd\n", "from sklearn.preprocessing import StandardScaler\n", "\n", + "\n", "def cross_sectional_standardization(df, features):\n", " df_sorted = df.sort_values(by='trade_date') # 按时间排序\n", " df_standardized = df_sorted.copy()\n", @@ -976,23 +1047,14 @@ "\n", " return df_standardized\n", "\n", + "\n", "import numpy as np\n", "import pandas as pd\n", "import statsmodels.api as sm\n", "\n", - "def mad_filter(df, features, n=3):\n", - " \"\"\" 使用中位数绝对偏差（MAD）去极值 \"\"\"\n", - " df = df.copy()\n", - " for col in features:\n", - " median = df[col].median()\n", - " mad = np.median(np.abs(df[col] - median))\n", - " upper = median + n * mad\n", - " lower = median - n * mad\n", - " df[col] = np.clip(df[col], lower, upper) # 截断极值\n", - " return df\n", - "\n", "from concurrent.futures import ProcessPoolExecutor\n", "\n", + "\n", "def neutralize_manual(df, features, industry_col, mkt_cap_col):\n", " \"\"\" 手动实现简单回归以提升速度 \"\"\"\n", "\n", @@ -1016,29 +1078,66 @@ "\n", "import gc\n", "\n", - "gc.collect()" + "gc.collect()\n", + "\n", + "\n", + "def mad_filter(df, features, n=3):\n", + " for col in features:\n", + " median = df[col].median()\n", + " mad = np.median(np.abs(df[col] - median))\n", + " upper = median + n * mad\n", + " lower = median - n * mad\n", + " df[col] = np.clip(df[col], lower, upper) # 截断极值\n", + " return df\n", + "\n", + "\n", + "def percentile_filter(df, features, lower_percentile=0.01, upper_percentile=0.99):\n", + " for col in features:\n", + " # 按日期分组计算上下百分位数\n", + " lower_bound = df.groupby('trade_date')[col].transform(\n", + " lambda x: x.quantile(lower_percentile)\n", + " )\n", + " upper_bound = df.groupby('trade_date')[col].transform(\n", + " lambda x: x.quantile(upper_percentile)\n", + " )\n", + " # 截断超出范围的值\n", + " df[col] = np.clip(df[col], lower_bound, upper_bound)\n", + " return df\n", + "\n", + "\n", + "from scipy.stats import iqr\n", + "\n", + "\n", + "def iqr_filter(df, features):\n", + " for col in features:\n", + " df[col] = df.groupby('trade_date')[col].transform(\n", + " lambda x: (x - x.median()) / iqr(x) if iqr(x) != 0 else x\n", + " )\n", + " return df\n", + "\n", + "\n", + "def quantile_filter(df, features, lower_quantile=0.01, upper_quantile=0.99, window=60):\n", + " df = df.copy()\n", + " for col in features:\n", + " # 计算 rolling 统计量，需要按日期进行 groupby\n", + " rolling_lower = df.groupby('trade_date')[col].transform(lambda x: x.rolling(window=min(len(x), window)).quantile(lower_quantile))\n", + " rolling_upper = df.groupby('trade_date')[col].transform(lambda x: x.rolling(window=min(len(x), window)).quantile(upper_quantile))\n", + "\n", + " # 对数据进行裁剪\n", + " df[col] = np.clip(df[col], rolling_lower, rolling_upper)\n", + " \n", + " return df\n" ], - "outputs": [ - { - "data": { - "text/plain": [ - "0" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 13 + "outputs": [], + "execution_count": 27 }, { "cell_type": "code", "id": "47c12bb34062ae7a", "metadata": { "ExecuteTime": { - "end_time": "2025-03-31T15:05:41.683690Z", - "start_time": "2025-03-31T15:03:24.853004Z" + "end_time": "2025-04-02T15:52:19.994776Z", + "start_time": "2025-04-02T15:47:05.010739Z" } }, "source": [ @@ -1053,13 +1152,13 @@ "df['future_return'] = (df.groupby('ts_code')['close'].shift(-days) - df.groupby('ts_code')['open'].shift(-1)) / \\\n", " df.groupby('ts_code')['open'].shift(-1)\n", "df['future_volatility'] = (\n", - " df.groupby('ts_code')['future_return']\n", - " .transform(lambda x: x.rolling(days).std())\n", + " df.groupby('ts_code')['pct_chg']\n", + " .transform(lambda x: x.rolling(days).std().shift(-days))\n", ")\n", "\n", "df['future_score'] = (\n", - " 0.7 * df['future_return'] +\n", - " 0.3 * df['future_volatility']\n", + " 0.7 * df['future_return']\n", + " # + 0.3 * df['future_volatility']\n", ")\n", "\n", "filter_index = df['future_return'].between(df['future_return'].quantile(0.01), df['future_return'].quantile(0.99))\n", @@ -1083,30 +1182,13 @@ " return np.sign(values) * np.log1p(np.abs(values))\n", "\n", "\n", - "train_data = df[filter_index & (df['trade_date'] <= '2023-01-01') & (df['trade_date'] >= '2000-01-01')]\n", - "test_data = df[(df['trade_date'] >= '2023-01-01')]\n", + "train_data = df[filter_index & (df['trade_date'] <= '2024-03-01') & (df['trade_date'] >= '2000-01-01')]\n", + "test_data = df[(df['trade_date'] >= '2024-03-01')]\n", "\n", "\n", "def select_pre_zt_stocks_dynamic(stock_df):\n", " # 排序数据\n", " stock_df = stock_df.sort_values(by=['trade_date', 'ts_code'])\n", - "\n", - " # avg_vol_3 = stock_df.groupby('ts_code')['vol'].rolling(window=3).mean().reset_index(level=0, drop=True)\n", - " # avg_vol_5 = stock_df.groupby('ts_code')['vol'].rolling(window=5).mean().shift(3).reset_index(level=0, drop=True)\n", - "\n", - " # stock_df = stock_df[\n", - " # (stock_df['cat_up_limit'] == 1) |\n", - " # (stock_df['vol'] > vol_spike_multiplier * stock_df['vol_spike'])\n", - " # ]\n", - " # cd1 = stock_df[\"close\"] > stock_df[\"close\"].shift(1)\n", - "\n", - " # cd2 = stock_df[\"close\"] > stock_df[\"close\"].rolling(window=10).mean()\n", - " #\n", - " # cd3 = (avg_vol_3 > avg_vol_5 * 2)\n", - " #\n", - " # cd4 = stock_df['gap_next_open'] < 0\n", - "\n", - " # stock_df = stock_df[(cd2 & cd4) | cd3]\n", " stock_df = stock_df.groupby('trade_date', group_keys=False).apply(\n", " lambda x: x.nlargest(1000, 'return_20')\n", " )\n", @@ -1114,8 +1196,8 @@ " return stock_df\n", "\n", "\n", - "# train_data = select_pre_zt_stocks_dynamic(train_data)\n", - "# test_data = select_pre_zt_stocks_dynamic(test_data)\n", + "train_data = select_pre_zt_stocks_dynamic(train_data)\n", + "test_data = select_pre_zt_stocks_dynamic(test_data)\n", "\n", "train_data, _ = get_simple_factor(train_data)\n", "test_data, _ = get_simple_factor(test_data)\n", @@ -1154,31 +1236,27 @@ "feature_columns = [col for col in feature_columns if not col.startswith('_')]\n", "print(f'feature_columns size: {len(feature_columns)}')\n", "\n", - "# train_data = train_data.dropna(subset=feature_columns)\n", - "# train_data = train_data.dropna(subset=['label'])\n", - "# train_data = train_data.reset_index(drop=True)\n", - "#\n", - "# # print(test_data.tail())\n", - "# test_data = test_data.dropna(subset=feature_columns)\n", - "# # test_data = test_data.dropna(subset=['label'])\n", - "# test_data = test_data.reset_index(drop=True)\n", - "\n", "numeric_columns = train_data.select_dtypes(include=['float64', 'int64']).columns\n", "numeric_columns = [col for col in numeric_columns if col in feature_columns]\n", "print('去极值')\n", - "train_data = mad_filter(train_data, numeric_columns) # 去极值\n", + "train_data = quantile_filter(train_data, numeric_columns) # 去极值\n", "# print('中性化')\n", "# train_data = neutralize_manual(train_data, numeric_columns, industry_col='cat_l2_code', mkt_cap_col='log(circ_mv)') # 中性化\n", "print('去极值')\n", - "test_data = mad_filter(test_data, numeric_columns) # 去极值\n", + "test_data = quantile_filter(test_data, numeric_columns) # 去极值\n", "# print('中性化')\n", "# test_data = neutralize_manual(test_data, numeric_columns, industry_col='cat_l2_code', mkt_cap_col='log(circ_mv)')\n", + "all_dates = train_data['trade_date'].unique() # 获取所有唯一的 trade_date\n", + "split_date = all_dates[-validation_days] # 划分点为倒数第 validation_days 天\n", + "train_data_split = train_data[train_data['trade_date'] < split_date] # 训练集\n", + "val_data_split = train_data[train_data['trade_date'] >= split_date] # 验证集\n", "\n", - "feature_columns, _ = remove_shifted_features(train_data[train_data['label'] == train_data['label'].max()],\n", - " test_data[test_data['label'] == test_data['label'].max()],\n", - " feature_columns)\n", + "feature_columns, _ = remove_shifted_features(\n", + " train_data_split,\n", + " val_data_split,\n", + " feature_columns)\n", "\n", - "feature_columns = remove_highly_correlated_features(train_data[train_data['label'] == train_data['label'].max()],\n", + "feature_columns = remove_highly_correlated_features(train_data,\n", " feature_columns)\n", "keep_columns = [col for col in train_data.columns if\n", " col in feature_columns or col in ['ts_code', 'trade_date', 'label', 'future_return',\n", @@ -1216,21 +1294,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "feature_columns size: 106\n", + "feature_columns size: 114\n", "去极值\n", "去极值\n", - "检测到 17 个可能漂移的特征: ['vol', 'pct_chg', 'turnover_rate', 'vol_std_5', 'obv', 'log(circ_mv)', 'cov', 'delta_cov', 'alpha_22_improved', 'alpha_003', 'log_close', 'up', 'down', 'mv_turnover_ratio', 'mv_adjusted_volume', 'mv_weighted_turnover', 'nonlinear_mv_volume']\n", - "feature_columns: ['pe_ttm', 'volume_ratio', 'winner_rate', 'return_skew', 'return_kurtosis', 'volume_change_rate', 'cat_volume_breakout', 'turnover_deviation', 'cat_turnover_spike', 'avg_volume_ratio', 'cat_volume_ratio_breakout', 'vol_spike', 'atr_14', 'maobv_6', 'rsi_3', 'return_5', 'return_20', 'std_return_5', 'std_return_90', 'std_return_90_2', 'act_factor1', 'act_factor2', 'act_factor3', 'act_factor4', 'rank_act_factor1', 'rank_act_factor2', 'rank_act_factor3', 'alpha_007', 'alpha_013', 'cat_up_limit', 'cat_down_limit', 'up_limit_count_10d', 'down_limit_count_10d', 'consecutive_up_limit', 'vol_break', 'weight_roc5', 'smallcap_concentration', 'cost_stability', 'high_cost_break_days', 'liquidity_risk', 'turnover_std', 'mv_volatility', 'volume_growth', 'mv_growth', 'arbr', 'momentum_factor', 'resonance_factor', 'cat_vol_spike', 'obv-maobv_6', 'std_return_5 / std_return_90', 'std_return_90 - std_return_90_2', 'cat_af2', 'cat_af3', 'cat_af4', 'act_factor5', 'act_factor6', 'active_buy_volume_large', 'active_buy_volume_big', 'active_buy_volume_small', 'buy_lg_vol_minus_sell_lg_vol', 'buy_elg_vol_minus_sell_elg_vol', 'ctrl_strength', 'low_cost_dev', 'asymmetry', 'lock_factor', 'cat_vol_break', 'cost_atr_adj', 'cat_golden_resonance', 'mv_momentum', 'industry_obv', 'industry_return_5', 'industry_return_20', 'industry__ema_5', 'industry_act_factor1', 'industry_act_factor2', 'industry_act_factor3', 'industry_act_factor4', 'industry_act_factor5', 'industry_act_factor6', 'industry_rank_act_factor1', 'industry_rank_act_factor2', 'industry_rank_act_factor3', 'industry_return_5_percentile', 'industry_return_20_percentile']\n", - "2540320\n", + "检测到 13 个可能漂移的特征: ['vol', 'pct_chg', 'turnover_rate', 'obv', 'log(circ_mv)', 'alpha_003', 'log_close', 'up', 'down', 'mv_turnover_ratio', 'mv_adjusted_volume', 'mv_weighted_turnover', 'nonlinear_mv_volume']\n", + "feature_columns: ['pe_ttm', 'volume_ratio', 'winner_rate', 'upside_volatility_20', 'downside_volatility_20', 'volatility_ratio_20', 'upside_semi_variance_20', 'downside_semi_variance_20', 'positive_negative_days_ratio_20', 'avg_positive_return_magnitude_20', 'avg_negative_return_magnitude_20', 'return_skew', 'return_kurtosis', 'volume_change_rate', 'cat_volume_breakout', 'turnover_deviation', 'cat_turnover_spike', 'avg_volume_ratio', 'cat_volume_ratio_breakout', 'vol_spike', 'vol_std_5', 'atr_14', 'maobv_6', 'rsi_3', 'return_5', 'return_20', 'std_return_5', 'std_return_90', 'act_factor1', 'act_factor2', 'act_factor3', 'act_factor4', 'rank_act_factor1', 'rank_act_factor2', 'rank_act_factor3', 'cov', 'delta_cov', 'alpha_007', 'alpha_013', 'cat_up_limit', 'cat_down_limit', 'up_limit_count_10d', 'down_limit_count_10d', 'consecutive_up_limit', 'vol_break', 'weight_roc5', 'smallcap_concentration', 'cost_stability', 'high_cost_break_days', 'liquidity_risk', 'turnover_std', 'mv_volatility', 'volume_growth', 'mv_growth', 'arbr', 'momentum_factor', 'resonance_factor', 'cat_vol_spike', 'obv-maobv_6', 'std_return_5 / std_return_90', 'std_return_90 - std_return_90_2', 'cat_af2', 'cat_af3', 'cat_af4', 'act_factor5', 'act_factor6', 'active_buy_volume_large', 'active_buy_volume_big', 'active_buy_volume_small', 'buy_lg_vol_minus_sell_lg_vol', 'buy_elg_vol_minus_sell_elg_vol', 'ctrl_strength', 'low_cost_dev', 'asymmetry', 'lock_factor', 'cat_vol_break', 'cost_atr_adj', 'cat_golden_resonance', 'mv_momentum', 'industry_obv', 'industry_return_5', 'industry_return_20', 'industry__ema_5', 'industry_act_factor1', 'industry_act_factor2', 'industry_act_factor3', 'industry_act_factor4', 'industry_act_factor5', 'industry_act_factor6', 'industry_rank_act_factor1', 'industry_rank_act_factor2', 'industry_rank_act_factor3', 'industry_return_5_percentile', 'industry_return_20_percentile']\n", + "1107768\n", "最小日期: 2018-06-04\n", - "最大日期: 2022-12-30\n", - "1252195\n", - "最小日期: 2023-01-03\n", + "最大日期: 2024-03-01\n", + "191955\n", + "最小日期: 2024-03-01\n", "最大日期: 2025-03-28\n" ] } ], - "execution_count": 22 + "execution_count": 42 }, { "cell_type": "code", @@ -1240,8 +1318,8 @@ "source_hidden": true }, "ExecuteTime": { - "end_time": "2025-03-31T14:55:52.421019Z", - "start_time": "2025-03-31T14:55:50.668422Z" + "end_time": "2025-04-02T15:52:20.199221Z", + "start_time": "2025-04-02T15:52:20.184447Z" } }, "source": [ @@ -1287,7 +1365,6 @@ " # 标准化数值特征\n", " scaler = StandardScaler()\n", "\n", - "\n", " # 计算每个 trade_date 内的样本数（LTR 需要 group 信息）\n", " train_groups = train_data_split.groupby('trade_date').size().tolist()\n", " val_groups = val_data_split.groupby('trade_date').size().tolist()\n", @@ -1389,41 +1466,44 @@ " return model, scaler\n" ], "outputs": [], - "execution_count": 15 + "execution_count": 43 }, { "cell_type": "code", "id": "c6eb5cd4-e714-420a-ac48-39af3e11ee81", "metadata": { "ExecuteTime": { - "end_time": "2025-03-31T14:59:05.368441Z", - "start_time": "2025-03-31T14:55:52.438125Z" + "end_time": "2025-04-02T16:43:22.759100Z", + "start_time": "2025-04-02T16:41:20.073261Z" } }, "source": [ "print('train data size: ', len(train_data))\n", "\n", "label_gain = list(range(len(train_data['label'].unique())))\n", - "label_gain = [gain * gain for gain in label_gain]\n", + "label_gain = [gain for gain in label_gain]\n", "light_params = {\n", " 'label_gain': label_gain,\n", " 'objective': 'lambdarank',\n", - " 'metric': 'lambdarank',\n", + " 'metric': 'ndcg',\n", " 'learning_rate': 0.1,\n", " 'num_leaves': 1024,\n", " 'min_data_in_leaf': 128,\n", - " 'max_depth': 16,\n", + " 'max_depth': 8,\n", " 'max_bin': 1024,\n", " 'feature_fraction': 0.7,\n", " 'bagging_fraction': 1,\n", " 'bagging_freq': 5,\n", " 'lambda_l1': 1,\n", " 'lambda_l2': 1,\n", - " # 'boosting': 'dart',\n", + " 'boosting': 'goss',\n", " 'verbosity': -1,\n", " 'extra_trees': True,\n", " 'max_position': 5,\n", " 'ndcg_at': 1,\n", + " 'quant_train_renew_leaf': True,\n", + " 'lambdarank_truncation_level': 1,\n", + " 'lambdarank_position_bias_regularization': 1,\n", " 'seed': 7\n", "}\n", "evals = {}\n", @@ -1450,15 +1530,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "train data size: 2540320\n", - "feature_contri: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]\n", - "原始训练集大小: 2540320\n", - "划分后的训练集大小: 2259332, 验证集大小: 280988\n", - "feature_columns size: 84\n", + "train data size: 1107768\n", + "feature_contri: [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]\n", + "原始训练集大小: 1107768\n", + "划分后的训练集大小: 1017570, 验证集大小: 90198\n", + "feature_columns size: 94\n", "Training until validation scores don't improve for 50 rounds\n", - "[100]\ttrain's ndcg@1: 0.795687\tvalid's ndcg@1: 0.550715\n", "Early stopping, best iteration is:\n", - "[58]\ttrain's ndcg@1: 0.73593\tvalid's ndcg@1: 0.595665\n", + "[26]\ttrain's ndcg@1: 0.527242\tvalid's ndcg@1: 0.572077\n", "Evaluated only: ndcg@1\n" ] }, @@ -1467,7 +1546,7 @@ "text/plain": [ "
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" 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" 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" 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r16hSpQqTJ0/mgw8+4OLFi1SoUEGjnj59+hAREYGrqyuBgYEEBgaq99WuXZvOnTsTEhICgEKh4Msvv2TLli3s3LmTMWPGALBx40ZGjRrF5MmTuXXrFu3bt2f58uVYWFg89Rju3buHhYUFmzZtokOHDurtdevWpX379kyfPh2VSoWTkxOjRo1i9OjRANy5cwd7e3siIiL46KOPntoGQFpaGlZWVlQatZYHBmbPLC8eMtZXMadBLmOP6JOVqyjucF4bkjftSc50I3nTTUnO28VZHZ5ZZsuWLaSnp1O1alWuXr1KaGgof//9N8eOHWPfvn00atSIjz/+mO3bt2NgYICpqSk//fQT3t7eLzzevM/vO3fuYGlp+dSyBi+8dSFeMVevXqVHjx7MmTOHLl26cPfuXfbt20fv3r1JSUkhLS2NFStWAGBtbU16ejodO3akbdu2rF69muTkZIYPH651u+PHjyc8PJyKFStSpkwZwsLCWL16NV999RVubm7s3buXjz/+GFtbW5o0acK6devo2rUriYmJWFpaYmJiolV7ISEhzJo1iwULFmBgYMB3331HUlISGzdu5LfffuPWrVt069aNWbNmMWPGjKfW9eDBA3JzcylVqpTGdhMTE/X80OTkZK5du0abNm3U+62srGjYsCGHDh0qsLORlZVFVlaW+nlaWhoAxnoq9PXlvEdhGeupNP4VhSN5057kTDeSN92U5LwVZkbCo5+37u7u1KlTh8qVK7N27VqcnJwIDg7m1q1bbN26FRsbG3755Re6devGrl27qFGjxkuPN490NsQb7+rVqzx48ID3338fFxcXAPV/OhMTE7KysnBwcFCXj4iIQKlU8u2331KqVCmqV6/OlStXGDx4sFbtTp06lbZt2wIPv2TPnDmTHTt24OXlBUDFihXZv38/y5Yto3nz5lhbWwNgZ2dH6dKltT7Onj170rdvX41tSqWSiIgI9UhGr1692Llz5zM7GxYWFnh5eTFt2jTc3d2xt7fnhx9+4NChQ1SuXBl4eNULAHt7e43X2tvbq/c9LiwsjNDQ0HzbJ3kqMTXNLdyBCrVp9ZTFHcJrSfKmPcmZbiRvuimJeYuOjtbpdXZ2duzcuZM2bdrw1VdfsWjRIu7fv8/ff/9N3bp1cXFxYcKECVp/h3mWzMzMQpeVzoZ449WqVYvWrVtTo0YNfHx88Pb25oMPPqBMmTIFlj9z5gw1a9bUOKuf10HQRr169dQ/X7hwgczMTHXnI092djaenp5a1/2s9vK4urpqTJlydHQkNTW1UPV9//33fPLJJ5QtWxZ9fX3q1KlDjx49nmuhWVBQECNHjlQ/T0tLw9nZmZYtW2JjY6NzvSVNTk4OMTExtG3bFkNDw+IO57UhedOe5Ew3kjfdSN60k56ezo0bN3jnnXfUswaaN2+Ou7u7uswXX3xBuXLl8PX1faFt581MKAzpbIg3nr6+PjExMRw8eJDt27ezePFiJk6cSFxcXJG2a2b2vzUI6enpAGzevJmyZctqlDM2Nn5qPXp6ejy+tKqg4ctH28vz+B9rhUKBUlm4M0aVKlViz549ZGRkkJaWhqOjI927d6dixYoA6tGgf//9F0dHR/Xr/v333yeuazE2Ni7weA0NDeWDRQeSN91I3rQnOdON5E03kreCjR49mk6dOuHi4sI///zDlClT0NfXp2fPnuqZBwEBAYSHh2NjY8PGjRvZsWMHv/322wvPpzb1ydWoRImgUCho3LgxoaGhHDt2DCMjIzZs2ICRkRG5uZrTd9zd3Tl58qTGFZUOHz78XO1Xq1YNY2NjUlJSqFy5ssbD2dkZACMjI4B88dja2nL16lX187S0NJKTk58rHm2YmZnh6OjIrVu32LZtG++99x4AFSpUwMHBgZ07d2rEFhcXp9NIkBBCCCGe7MqVK/To0YOqVavSrVs3bGxsOHz4MLa2thgYGLBp0yZsbW3p1KkTNWvWZNWqVaxcufKFj2poS0Y2xBsvLi6OnTt34u3tjZ2dHXFxcfz333+4u7tz//59tm3bRmJiIjY2NlhZWdGzZ08mTpzIgAEDCAoK4uLFi/muWqUtCwsLRo8ezYgRI1AqlTRp0oQ7d+5w4MABLC0t6dOnDy4uLigUCn777Td8fX0xMTHB3NycVq1aERERQadOnShdujTBwcHo6+u/oOw82bZt21CpVFStWpULFy4wZswY3n77bfW6EIVCQWBgINOnT8fNzY0KFSowefJknJycXpl7lwghhBBviqioqAK35812cHNzeyXuGP446WyIN56lpSV79+5lwYIFpKWl4eLiwty5c2nfvj316tUjNjaWevXqkZ6err707a+//sqgQYPw9PSkWrVqzJ49m65duz5XHNOmTcPW1pawsDD++usvSpcuTZ06dZgwYQIAZcuWJTQ0lPHjx9O3b1969+5NREQEQUFBJCcn07FjR6ysrJg2bdpLGdm4c+cOQUFBXLlyBWtra7p27cqMGTM0hk7Hjh1LRkYGAwcO5Pbt2zRp0oStW7fmu4qVEEIIIUomuc+GEKLY5F2n+/r167JAXAs5OTlER0fj6+sr85q1IHnTnuRMN5I33UjedFMcedPmPhuyZkMIIYQQQghRJKSzIYSWBg0ahLm5eYGPQYMGFXd4hZKSkvLEYzA3NyclJaW4QxRCCCHEG0DWbAihpalTpzJ69OgC9z1rKPFV4eTkxPHjx5+6XwghhBDieUlnQwgt2dnZYWdnV9xhPBcDAwP1ncCFEEIIIYqKTKMSQgghhBBCFAnpbAjxiouNjUWhUHD79u0ibysiIoLSpUurn4eEhDzxbuBCCCFKhlmzZqnvrZSnRYsWKBQKjcfrsm5RvFzS2RBCC2/6l+/u3btz7ty54g5DCCHEKyI+Pp5ly5ZRs2bNfPsGDBjA1atX1Y85c+YUQ4TiVSedDSGEmomJyWu/HkUIIcSLkZ6ejp+fH8uXL6dMmTL59puamuLg4KB+vC4XSREvl3Q2RImjVCqZM2cOlStXxtjYmPLlyzNjxgwAxo0bR5UqVTA1NaVixYpMnjyZnJwc4OEUo9DQUE6cOKEeMo6IiHhqWz179qR79+4a23JycnjrrbdYtWoVAFlZWQwbNgw7OztKlSpFkyZNiI+P1+nYLl26RKdOnShTpgxmZmZUr16d6Oho4H/TsTZv3kzNmjUpVaoU77zzDgkJCerXPz6N6nFJSUlUrFiRgIAAVCoVWVlZjB49mrJly2JmZkbDhg2JjY3VKXYhhBCvlqFDh9KhQwfatGlT4P41a9bw1ltv4eHhQVBQEJmZmS85QvE6kKtRiRInKCiI5cuXM3/+fJo0acLVq1c5e/YsABYWFkRERODk5MSpU6cYMGAAFhYWjB07lu7du5OQkMDWrVvZsWMHAFZWVk9ty8/Pjw8//JD09HTMzc0B2LZtG5mZmXTp0gWAsWPHsm7dOlauXImLiwtz5szBx8eHCxcuYG1trdWxDR06lOzsbPbu3YuZmRmnT59Wt5tnzJgxLFy4EAcHByZMmECnTp04d+7cM+86evLkSXx8fOjXrx/Tp08HICAggNOnTxMVFYWTkxMbNmygXbt2nDp1Cjc3t3x1ZGVlkZWVpX6elpYGQLPZO3hgaKbVsZZkxnoqptWDulO3kqVUFHc4rw3Jm/YkZ7p51fOWEOLzzDJr167l6NGjHDp0iJycHFQqFUqlUn0Crnv37pQvXx5HR0dOnTrFxIkTOXPmDD/99JPOceXVnfevKJziyJs2bSlUKpWqCGMR4pVy9+5dbG1tWbJkCf37939m+fDwcKKiovj999+Bh2s2Nm7c+NR7VDzqwYMHODo6Mm/ePHr16gU8HO1QKpVERUWRkZFBmTJliIiIoGfPnsDD/8Curq4EBgYyZswYYmNjadmyJbdu3XrqqANAzZo16dq1K1OmTMm3L6+eqKgo9WjLzZs3KVeuHBEREXTr1o2IiAgCAwPVi9HzjvfLL7+kY8eOTJw4kVGjRgEPbwxYsWJFUlJSNO7L0aZNGxo0aMDMmTPzxRASEkJoaGi+7ZGRkZiamj47oUIIIYrcf//9x+jRowkNDcXV1RWAiRMnUqFChSd+dp48eZLg4GCWLl2Ko6PjS4xWFIfMzEx69uzJnTt3njl9TkY2RIly5swZsrKyaN26dYH7165dy6JFi0hKSiI9PZ0HDx481xxUAwMDunXrxpo1a+jVqxcZGRls2rSJqKgo4OG0pJycHBo3bqx+jaGhIQ0aNODMmTNatzds2DAGDx7M9u3badOmDV27ds23qM/Ly0v9s7W1NVWrVn1qWykpKbRt25YZM2ZoXInk1KlT5ObmUqVKFY3yWVlZ2NjYFFhXUFAQI0eOVD9PS0vD2dmZ6cf0eGCor82hlmgPz5oqmfy73it51vRVJXnTnuRMN6963p41srFp0ybu3LmjPrkEkJuby+nTp9myZQvp6eno62v+zW7evDnBwcE4Ozvj7e2tU1w5OTnExMTQtm3bZ462i/8pjrzlzUwoDOlsiBLFxMTkifsOHTqEn58foaGh+Pj4YGVlRVRUFHPnzn2uNv38/GjevDmpqanExMRgYmJCu3btnqvOJ+nfvz8+Pj5s3ryZ7du3ExYWxty5c/nss890rtPW1hYnJyd++OEHPvnkE3XnK+/D5ujRo/k+dB6fupXH2NgYY2PjfNv3jmvzxA6KyC8nJ4fo6GiOBreTD2QtSN60JznTzeueNx8fH06dOqWxrW/fvrz99tuMGzeOUqVK5XvNn3/+CYCzs/NzH7OhoeFrmbfi9jLzpk07skBclChubm6YmJiwc+fOfPsOHjyIi4sLEydOpF69eri5uXHp0iWNMkZGRuTm5mrVZqNGjXB2dmbt2rWsWbOGDz/8UP2ftFKlShgZGXHgwAF1+ZycHOLj46lWrZoOR/jwD/2gQYNYv349o0aNYvny5Rr7Dx8+rP751q1bnDt3Dnd39yfWZ2Jiwm+//UapUqXw8fHh7t27AHh6epKbm0tqaiqVK1fWeDg4OOgUuxBCiOJnYWGBh4eHxsPMzAwbGxs8PDxISkpi2rRpHD16lIsXL/LLL7/Qu3dvmjVrVuAlckXJJiMbokQpVaoU48aNY+zYsRgZGdG4cWP+++8//vzzT9zc3EhJSSEqKor69euzefNmNmzYoPF6V1dXkpOTOX78OOXKlcPCwqLAM/WP69mzJ1999RXnzp1j9+7d6u1mZmYMHjyYMWPGYG1tTfny5ZkzZw6ZmZn069dP6+MLDAykffv2VKlShVu3brF79+58HYmpU6diY2ODvb09EydO5K233qJz585PrdfMzIzNmzfTvn172rdvz9atW6lSpQp+fn707t2buXPn4unpyX///cfOnTupWbMmHTp00Dp+IYQQrz4jIyN27NjBggULyMjIwNnZma5duzJp0qTiDk28gqSzIUqcyZMnY2BgQHBwMP/88w+Ojo4MGjSIfv36MWLECAICAsjKyqJDhw5MnjyZkJAQ9Wu7du3K+vXradmyJbdv32bFihX4+/s/s00/Pz9mzJiBi4uLxvoMeHhnVqVSSa9evbh79y716tVj27ZtBV7T/Flyc3MZOnQoV65cwdLSknbt2jF//vx87Q0fPpzz589Tu3Ztfv31V4yMjJ5Zt7m5OVu2bMHHx4cOHToQHR3NihUrmD59OqNGjeLvv//mrbfe4p133qFjx45axy6EEOLV9ehlzZ2dndmzZ0/xBSNeK3I1KiFKCG2uavWypKWlYWVlxfXr12XNhhby5oP7+vrKvGYtSN60JznTjeRNN5I33RRH3vI+vwtzNSpZsyGEEEIIIYQoEtLZEOI5rFmzBnNz8wIf1atXf+HttW/f/ontFXRfCyGEEEKI4iRrNoR4Du+++y4NGzYscF9RDGV+88033Lt3r8B9z7rbeIsWLZBZk0IIIYR4maSzIcRzsLCwwMLC4qW1V7Zs2ZfWlhBCCCHE85JpVEIIIYQQQogiIZ0NIYQQQog33KxZs1AoFAQGBqq3ffrpp1SqVAkTExNsbW157733OHv2bPEFKd5I0tkoJiEhIdSuXfupZS5evIhCoeD48eMvJSZR9GJjY1EoFNy+ffuF1y3vFyGEEAWJj49n2bJl+e7uXbduXVasWMGZM2fYtm0bKpUKb29vcnNziylS8SaSzkYxGT16NDt37lQ/9/f3z3cXZ2dnZ65evYqHh8dLjk47hek4iYcaNWrE1atXsbKyAiAiIuKVuefF48LCwqhfvz4WFhbY2dnRuXNnEhMTNcrcv3+foUOHYmNjg7m5OV27duXff/8tpoiFEEI8Lj09HT8/P5YvX57vZrEDBw6kWbNmuLq6UqdOHaZPn87ly5e5ePFi8QQr3kjS2Sgm5ubmz7yJmb6+Pg4ODhgYFM86/uzs7Jfankql4sGDBy+1zZfNyMgIBwcHFApFcYfyTHv27GHo0KEcPnyYmJgYcnJy8Pb2JiMjQ11mxIgR/Prrr/z000/s2bOHf/75h/fff78YoxZCCPGooUOH0qFDB9q0afPUchkZGaxYsYIKFSrg7Oz8kqITJcErezWqrVu3Mn36dBISEtDX18fLy4uFCxdSqVIlGjVqRNOmTZk9e7a6/H///YeTkxM7d+6kWbNmXL16lf79+7Nr1y4cHByYMWMGEyZMIDAwUGO+4pMoFAq+/PJLfvnlF2JjY3F0dGTOnDl88MEH6jKnTp1i+PDhHDp0CFNTU7p27cq8efMwNzcHHk6ZGTt2LH/++SeGhoZUr16dyMhIXFxcCAkJYePGjRw/fpyQkBBWrlypbhdg9+7duLq6UqFCBY4dO0bNmjUpX748EydOZPDgweoYjh07Rt26dUlOTsbFxYXbt28zevRoNm3aRFZWFvXq1WP+/PnUqlXrmcecF1NAQAAzZszg0qVLKJXKp9YZERFBaGioRuwrVqygRYsW6tjzRj1u375NmTJl2L17Ny1atFDf0To6OppJkyZx6tQptm/fTkhICDVr1qRUqVJ88803GBkZMWjQIEJCQp55DHlxfPXVV/z666/s2rULFxcXvvvuO2xtbenfvz/x8fHUqlWL77//nkqVKgGQlJTEyJEjOXz4MBkZGbi7uxMWFqbxx7kw7ymFQsHy5cvZvHkz27Zto2zZssydO5d3331X/Z7Iu4v38ePH6du3r0bupkyZQkhICAqFgg0bNmiMdpUuXZoFCxbg7+8PwJEjR/j00085c+YMHh4eTJw4MV8uEhISGDNmDPv27cPMzAxvb2/mz5/PW2+99cw8bt26VeN5REQEdnZ2HD16lGbNmnHnzh2+/fZbIiMjadWqFfDwd+/u7s7hw4d55513CvHbeqhh2E4eGJgVunxJZ6yvYk4D8AjZRlbuq99xfVVI3rQnOdNNUeft4qwOhSoXFRXFH3/8QXx8/BPLfPnll4wdO5aMjAyqVq1KTEwMRkZGLypUIV7dzkZGRgYjR46kZs2apKenExwcTJcuXTh+/Dh+fn7MmTNHvdgJYO3atTg5OdG0aVMAevfuzfXr14mNjcXQ0JCRI0eSmpqqVQyTJ09m1qxZLFy4kO+//56PPvqIU6dO4e7uTkZGBj4+Pnh5eREfH09qair9+/cnICCAiIgIHjx4QOfOnRkwYAA//PAD2dnZHDlypMAz2qNHj+bMmTOkpaWxYsUK4OE9E/755x91GT09PXr06EFkZKRGZ2PNmjU0btwYFxcXAD788ENMTEzYsmULVlZWLFu2jNatW3Pu3Lln3ocB4MKFC6xbt47169ejr6//zDq7d+9OQkICW7duZceOHQBYWVlpNZVm/PjxhIeHU7FiRfUQ78qVKxk5ciRxcXEcOnQIf39/GjduTNu2bQtV57Rp05g3bx7z5s1j3Lhx9OzZk4oVKxIUFET58uX55JNPCAgIYMuWLcDDYWZfX19mzJiBsbExq1atolOnTiQmJlK+fHmg8O+p0NBQ5syZw+eff87ixYvx8/Pj0qVL+fLfqFEjFixYQHBwsHp6Ul5H9VnS09Pp2LEjbdu2ZfXq1SQnJzN8+HCNMrdv36ZVq1b079+f+fPnc+/ePcaNG0e3bt3YtWtXodp51J07d4D/3c/j6NGj5OTkaHTI3n77bcqXL8+hQ4cK7GxkZWWRlZWlfp6WlgaAsZ4KfX25B0hhGeupNP4VhSN5057kTDdFnbecnJxnlrl8+TLDhw8nOjoafX19cnJyUKlUKJVKjdd369aNFi1acO3aNebNm8eHH37Inj17KFWqVJHE/jR5cRXm+MT/FEfetGnrle1sdO3aVeN53pnp06dP061bNwIDA9m/f7+6cxEZGUmPHj1QKBScPXuWHTt2EB8fT7169YCHN0Nzc3PTKoYPP/yQ/v37Aw+/vMbExLB48WK+/PJLIiMjuX//PqtWrcLM7OEZ2SVLltCpUydmz56NoaEhd+7coWPHjuqz5+7u7gW2Y25ujomJCVlZWTg4ODwxHj8/P+bOnUtKSgrly5dHqVQSFRXFpEmTANi/fz9HjhwhNTUVY2NjAMLDw9m4cSM///wzAwcOfOYxZ2dns2rVKmxtbQtdp7m5OQYGBk+N/WmmTp2arxNRs2ZNpkyZAoCbmxtLlixh586dhe5s9O3bl27dugEwbtw4vLy8mDx5Mj4+PgAMHz5cPaoAUKtWLY3Rn2nTprFhwwZ++eUXAgICtHpP+fv706NHDwBmzpzJokWLOHLkCO3atdMoZ2RkhJWVFQqFQuvcRUZGolQq+fbbbylVqhTVq1fnypUrGh3RJUuW4OnpqXFn8e+++w5nZ2fOnTtHlSpVCt2eUqkkMDCQxo0bq9cQXbt2DSMjo3xrTuzt7bl27VqB9YSFhalHwh41yVOJqaksSNTWtHrK4g7htSR5057kTDdFlbfo6Ohnljl8+DCpqak0aNBAvU2pVLJv3z6++OILfvrpJ/VJxTz+/v58/PHHhISE0KxZsxced2HFxMQUW9uvs5eZt8zMzEKXfWU7G+fPnyc4OJi4uDiuX7+OUvnwP2xKSgoeHh54e3uzZs0amjZtSnJyMocOHWLZsmUAJCYmYmBgQJ06ddT1Va5cOd/CqGfx8vLK9zzvSj9nzpyhVq1a6o4GQOPGjVEqlSQmJtKsWTP8/f3x8fGhbdu2tGnThm7duuHo6KhLOgCoXbs27u7uREZGMn78ePbs2UNqaioffvghACdOnCA9PT3fWpB79+6RlJRUqDZcXFzUHY0XVeez5H15f9TjV8xwdHTUamTq0dfb29sDUKNGDY1t9+/fJy0tDUtLS9LT0wkJCWHz5s1cvXqVBw8ecO/ePVJSUgDt3lOPtm1mZoalpaXWo2rPcubMGfVUszyPv19PnDjB7t27CxwtSUpK0qqzMXToUBISEti/f7/uQQNBQUGMHDlS/TwtLQ1nZ2emH9PjgaH+U14pHmWsp2JaPSWTf9cjSylTWwpL8qY9yZluijpvCSE+zyzTtGlT9Um3PAMGDKBq1aqMHj26wIvPZGVloaenR7Vq1fD19X1h8RZWTk4OMTExtG3bFkNDw5fe/uuqOPKWNzOhMF7ZzkanTp1wcXFh+fLlODk5oVQq8fDwUC9a9vPzY9iwYSxevJjIyEhq1Kih8WXyVbBixQqGDRvG1q1bWbt2LZMmTSImJkarueyP8/PzU3c2IiMjadeunbojkJ6ejqOjI7GxsfleV9grHj3aeXqeOvX0Hl57QKX63xDyk4bcHm8TyPefRaFQqDuchfHo6/OmrhW0La/O0aNHExMTQ3h4OJUrV8bExIQPPvhAp0Xyzxt73msezR1oPzyanp6uHml7nDad3oCAAH777Tf27t1LuXLl1NsdHBzIzs7m9u3bGu+Ff//994kjNcbGxuoRskftHdfmmRdMEP+Tk5NDdHQ0R4PbyQeyFiRv2pOc6eZVyJu1tXW+6bvm5ubY2tri6enJX3/9xdq1a/H29sbW1pYrV64wa9YsTExM6NSpU7H+vg0NDeX9poOXmTdt2nklr0Z148YNEhMTmTRpEq1bt8bd3Z1bt25plHnvvfe4f/8+W7duJTIyEj8/P/W+qlWr8uDBA44dO6beduHChXx1PMvhw4fzPc+bCuXu7s6JEyc0rsxz4MAB9PT0qFq1qnqbp6cnQUFBHDx4EA8PDyIjIwtsy8jIqFDXte7ZsycJCQkcPXqUn3/+WeO469Spw7Vr1zAwMKBy5coaj8IsCC5IYeosKPa80ZGrV6+qt73K9384cOAA/v7+dOnShRo1auDg4KBx6b8X9Z563JN+77a2thq5O3/+vMaQpbu7OydPnuT+/fvqbY+/X+vUqcOff/6Jq6trvt9dQR28x6lUKgICAtiwYQO7du2iQoUKGvvr1q2LoaGhxiWcExMTSUlJyTfKIoQQ4tVSqlQp9u3bh6+vL5UrV6Z79+5YWFhw8OBB7Ozsijs88QZ5JTsbZcqUwcbGhq+//poLFy6wa9cujakX8PBseOfOnZk8eTJnzpxRz5GHh4tU27Rpw8CBAzly5AjHjh1j4MCBmJiYaHXJ0Z9++onvvvuOc+fOMWXKFI4cOUJAQADwcIShVKlS9OnTh4SEBHbv3s1nn31Gr169sLe3Jzk5maCgIA4dOsSlS5fYvn0758+ff+K6DVdXV06ePEliYiLXr19/4llsV1dXGjVqRL9+/cjNzVVf5QigTZs2eHl50blzZ7Zv387Fixc5ePAgEydO5Pfffy/0cT+qMHW6urqSnJzM8ePHuX79OllZWZiYmPDOO+8wa9Yszpw5w549e9RrS15Fbm5urF+/nuPHj3PixAl69uypMRrxot5Tj3N1dSU9PZ2dO3dy/fp1dYeiVatWLFmyhGPHjvH7778zaNAgjbMIPXv2RKFQMGDAAE6fPk10dDTh4eEadQ8dOpSbN2/So0cP4uPjSUpKYtu2bfTt27dQHduhQ4eyevVqIiMjsbCw4Nq1a1y7do179+4BDy8E0K9fP0aOHMnu3bs5evQoffv2xcvL67lG74QQQhSN2NhYFixYAICTkxPR0dH8+++/ZGdnc/nyZdasWaNxwlSIF+GV7Gzo6ekRFRXF0aNH8fDwYMSIEXz++ef5yvn5+XHixAmaNm2qvmJQnlWrVmFvb0+zZs3o0qULAwYMwMLCQqurK4SGhhIVFUXNmjVZtWoVP/zwA9WqVQPA1NSUbdu2cfPmTerXr88HH3xA69atWbJkiXr/2bNn6dq1K1WqVGHgwIEMHTqUTz/9tMC28uZR1qtXD1tbWw4cOPDEuPKOu0uXLpiYmKi3KxQKoqOjadasGX379qVKlSp89NFHXLp0Sb1uQVuFqbNr1660a9eOli1bYmtryw8//AA8XIz84MED6tatS2BgINOnT9cphpdh3rx5lClThkaNGtGpUyd8fHw01mfAi3lPPa5Ro0YMGjSI7t27Y2try5w5cwCYO3cuzs7ONG3alJ49ezJ69GhMTU3VrzM3N+fXX3/l1KlTeHp6MnHixHzTpZycnDhw4AC5ubl4e3tTo0YNAgMDKV26tHqa29MsXbqUO3fu0KJFCxwdHdWPtWvXqsvMnz+fjh070rVrV5o1a4aDgwPr16/XOR9CCCGEeLMoVI9PDH9DXblyBWdnZ3bs2EHr1q2fWb6g+xwI8Sht31Miv7S0NKysrLh+/bqs2dBC3nxwX19fmdesBcmb9iRnupG86UbyppviyFve5/edO3ewtLR8atlXdoH489q1axfp6enUqFGDq1evMnbsWFxdXYv1Um7i9SbvKSGEEEII7byS06hehJycHCZMmED16tXp0qULtra26puxrVmzBnNz8wIf1atXL+7Qi0z16tWfeNxr1qwp7vAKpTh/d097T71uUlJSnphHc3Nz9SV/hRBCCCGexxs7suHj46O+gdvj3n33XRo2bFjgvrwvjm/i7LLo6OgnLjzXdU3Hy1aY311Redp76nXj5OT01KuDOTk5vbxghBBCCPHGemM7G09jYWGBhYVFcYfx0rm4uBR3CM+tpP7uXrS8SxkLIYQQQhSlN3YalRBCCCGEEKJ4SWdDCCGEEOIVMGvWLBQKBYGBgept9+/fZ+jQodjY2GBubk7Xrl35999/iy9IIbQknQ0hSojY2FgUCgW3b98u7lCEEEI8Jj4+nmXLllGzZk2N7SNGjODXX3/lp59+Ys+ePfzzzz+8//77xRSlENqTzoYQQgghRDFKT0/Hz8+P5cuXU6ZMGfX2O3fu8O233zJv3jxatWpF3bp1WbFiBQcPHuTw4cPFGLEQhSedDfHaaNGiBZ999hmBgYGUKVMGe3t7li9fTkZGBn379sXCwoLKlSuzZcsWlEol5cqVY+nSpRp1HDt2DD09PS5duvTM9hQKBcuWLaNjx46Ympri7u7OoUOHuHDhAi1atMDMzIxGjRqRlJSk8bqlS5dSqVIljIyMqFq1Kt9///0LqXfTpk3UqVOHUqVKUbFiRUJDQ3nw4IFGvd988w1dunTB1NQUNzc3fvnlFwAuXrxIy5YtAShTpgwKhQJ/f38AXF1dWbBggUZbtWvXJiQk5LljFkII8WxDhw6lQ4cOtGnTRmP70aNHycnJ0dj+9ttvU758eQ4dOvSywxRCJyXyalTi9bVy5UrGjh3LkSNHWLt2LYMHD2bDhg106dKFCRMmMH/+fHr16kVKSgo9evQgMjKSwYMHq1+/Zs0aGjduXOgrc02bNo158+Yxb948xo0bR8+ePalYsSJBQUGUL1+eTz75hICAALZs2QLAhg0bGD58OAsWLKBNmzb89ttv9O3bl3Llyqm/7OtS7759++jduzeLFi2iadOmJCUlMXDgQACmTJmirjc0NJQ5c+bw+eefs3jxYvz8/Lh06RLOzs6sW7eOrl27kpiYiKWlJSYmJlrlXtuYtdEwbCcPDMy0fl1JZayvYk4D8AjZRlauorjDeW1I3rQnOdNNXt4KIyoqij/++IP4+Ph8+65du4aRkRGlS5fW2G5vb8+1a9deQKRCFD3pbIjXSq1atZg0aRIAQUFBzJo1i7feeosBAwYAEBwczNKlSzl58iR+fn7MnTuXlJQUypcvj1KpJCoqSv36wujbty/dunUDYNy4cXh5eTF58mT1/TaGDx9O37591eXDw8Px9/dnyJAhAIwcOZLDhw8THh6u0dnQtt7Q0FDGjx9Pnz59AKhYsSLTpk1j7NixGp0Nf39/evToAcDMmTNZtGgRR44coV27dlhbWwNgZ2eX74OrKHJRkKysLLKystTP09LSADDWU6Gv/+bd26aoGOupNP4VhSN5057kTDd5+XrSva3yXL58meHDhxMdHY2+vj45OTmoVCqUSiU5OTnq0evH61GpVOTm5j6z/tdN3vG8acdV1Iojb9q0JZ0N8Vp5dOGcvr4+NjY21KhRQ70t7+aEqampvPvuu7i7uxMZGcn48ePZs2cPqampfPjhhzq1l1f34+3dv3+ftLQ0LC0tOXPmjHrEIU/jxo1ZuHDhc9V74sQJDhw4wIwZM9RlcnNzuX//PpmZmZiamuar18zMDEtLS1JTUwt9vE+jbcwFCQsLIzQ0NN/2SZ5KTE1zX0icJcm0esriDuG1JHnTnuRMNzExMU/df/jwYVJTU2nQ4H/DIEqlkn379vHFF18wZcoUsrOz+fHHHzE3N1eXuXTpErdu3SI6OrrIYi9Oz8qbKNjLzFtmZmahy0pnQ7xWHr9LuEKh0NimUDwc5lcqH34w+vn5qTsbkZGRtGvXDhsbG53ay6v7ae0VVb3p6emEhoYWeAWSUqVKFVhvXj3Pik1PTw+VSvOsZUFnLF5ELoKCghg5cqT6eVpaGs7OzrRs2VKr30tJl5OTQ0xMDG3bts33OxdPJnnTnuRMN4XNW9OmTdUjxnkGDBhA1apVGT16NM7OzkyfPh0DAwN8fX0BSExM5L///qNv3740bNiwSI/jZZP3m26KI295MxMKQzob4o3Ws2dPJk2axNGjR/n555/56quvirQ9d3d3Dhw4oJ7uBHDgwAGqVav2XPXWqVOHxMTE57rrt5GREfBwRORRtra2XL16Vf08LS2N5ORkndt5GmNjY4yNjfNtNzQ0lA8WHUjedCN5057kTDfPypu1tbV6imsec3NzbG1t8fT0BKBfv36MHTsWOzs7LC0t+eyzz/Dy8qJJkyZFGntxkvebbl5m3rRpRzob4o3m6upKo0aN6NevH7m5ubz77rtF2t6YMWPo1q0bnp6etGnThl9//ZX169ezY8eO56o3ODiYjh07Ur58eT744AP09PQ4ceIECQkJTJ8+vVB1uLi4oFAo+O233/D19cXExARzc3NatWpFREQEnTp1onTp0gQHB6Ovr/9c8QohhHgx5s+fj56eHl27diUrKwsfHx++/PLL4g5LiEKTS9+KN56fnx8nTpygS5cuWl+BSVudO3dm4cKFhIeHU716dZYtW8aKFSto0aLFc9Xr4+PDb7/9xvbt26lfvz7vvPMO8+fPL/RVtQDKli2rXmhub29PQEAA8HBqU/PmzenYsSMdOnSgc+fOVKpU6bniFUIIoZvY2FiNy5GXKlWKL774gps3b5KRkcH69etxcHAovgCF0JJC9fhkbSGEeEnS0tKwsrLi+vXrsmZDCzk5OURHR+Pr6ytTDbQgedOe5Ew3kjfdSN50Uxx5y/v8vnPnzhMvCpNHRjaEEEIIIYQQRUI6G6JEWrNmDebm5gU+qlevXtzhCSGEEEK8EWSBuCiR3n333SdeMlCGboUQQgghXgzpbIgSycLCAgsLi+IOQwghhBDijSbTqIQQQgghhBBFQjobQgghhBA6WLp0KTVr1sTS0hJLS0u8vLzYsmWLev+1a9fo1asXDg4OmJmZUadOHdatW1eMEQvx8klnQwgttWjRgsDAwFeirpCQEOzt7VEoFGzcuPGFxCSEEKJwypUrx6xZszh69Ci///47rVq14r333uPPP/8E4JNPPiExMZFffvmFU6dO8f7779OtWzeOHTtWzJEL8fJIZ0OI19SZM2cIDQ1l2bJlXL16lfbt2z93nREREZQuXfr5gxNCiBKgU6dO+Pr64ubmRpUqVZgxYwbm5uYcOXIEgEOHDvHZZ5/RoEEDKlasyKRJkyhdujRHjx4t5siFeHmksyHEayopKQmA9957DwcHB4yNjYs5ov/Jzc1FqVQWdxhCCPHS5ObmEhUVRUZGhvpqh15eXqxdu5abN2+iVCqJiori/v37tGjRoniDFeIlkqtRCfEcbt26xfDhw/n111/JysqiefPmLFq0CDc3N3WZAwcOMHHiRI4cOYKxsTENGjQgKiqKMmXK5Ktv8+bN9OzZky+//BI/P78nthsSEkJoaCgAenoPzxmoVCri4+OZMGECx44dIycnh9q1azN//nzq1Kmjfu3t27cZN24cGzdu5M6dO1SuXJlZs2Zhbm5O3759AVAoFABMmTKFkJCQZx5nREQEgYGBrFq1ivHjx3Pu3DkuXLiAq6trofLYMGwnDwzMClVWgLG+ijkNwCNkG1m5iuIO57UhedNeSc/ZxVkdnlnm1KlTeHl5cf/+fczNzdmwYQPVqlXj4sWLREZG8vHHH2NjY4OBgQGmpqZs2LCBypUrv4TohXg1SGdDiOfg7+/P+fPn+eWXX7C0tGTcuHH4+vpy+vRpDA0NOX78OK1bt+aTTz5h4cKFGBgYsHv3bnJzc/PVFRkZyaBBg4iMjKRjx45PbXf06NG4urrSt29frl69qt5+9+5d+vTpw+LFi1GpVMydOxdfX1/Onz+PhYUFSqWS9u3bc/fuXVavXk2lSpU4ffo0+vr6NGrUiAULFhAcHExiYiIA5ubmhTpOgMzMTGbPns0333yDjY0NdnZ2+eLOysoiKytL/TwtLQ0AYz0V+voqLbNfchnrqTT+FYUjedNeSc9ZTk7OM8tUrFiR+Ph40tLSWLduHX369GHr1q0ABAcHc+vWLbZu3YqNjQ2//PIL3bp1Y9euXdSoUaOow3/t5OW7MHkX/1McedOmLYVKpSqZf0GE0FGLFi2oXbs2Q4cOpUqVKhw4cIBGjRoBcOPGDZydnVm5ciUffvghPXv2JCUlhf379z+1Ljc3NyZOnMimTZto3rx5oeLYuHEjXbp04Wn/hZVKJaVLl1Z3YLZv30779u05c+YMVapUyVc+b4Ti9u3b6m3nz59/5nFGRETQt29fjh8/Tq1atZ4Yz6MjMo+KjIzE1NS0UMcthBCvsuDgYBwcHOjSpQuDBw9m0aJFlC9fXmO/o6MjgwcPLsYohXg+mZmZ9OzZkzt37mBpafnUsjKyIYSOzpw5g4GBgcadyG1sbKhatSpnzpwB4Pjx43z44YdPrefnn38mNTWVAwcOUL9+/eeK6d9//2XSpEnExsaSmppKbm4umZmZpKSkqOMpV65cgR2NJynMcQIYGRlRs2bNp9YVFBTEyJEj1c/T0tJwdnZm+jE9HhjqFzqmks5YT8W0ekom/65HlrLkTW3RleRNeyU9ZwkhPlq/ZsGCBdja2qpHcZs3b467u7t6/xdffEG5cuXw9fV9YXG+KXJycoiJiaFt27bqUXPxbMWRt7yZCYUhnQ0hipCJickzy3h6evLHH3/w3XffUa9ePfV6CV306dOHGzdusHDhQlxcXDA2NsbLy4vs7OxCx6MrExOTZ8ZubGxc4EL2vePaYGNjU1ShvXFycnKIjo7maHA7+UDWguRNe5KzpwsKCqJ9+/aUL1+eu3fvEhkZyZ49e9i8eTOZmZlUrlyZgIAAwsPDsbGxYePGjezYsYPffvtN8vkUhoaGkh8dvMy8adOOXI1KCB25u7vz4MED4uLi1Ntu3LhBYmIi1apVA6BmzZrs3LnzqfVUqlSJ3bt3s2nTJj777LPniunAgQMMGzYMX19fqlevjrGxMdevX1fvr1mzJleuXOHcuXMFvt7IyCjfepLCHKcQQpREqamp9O7dm6pVq9K6dWvi4+PZtm0bbdq0wcDAgE2bNmFra0unTp2oWbMmq1atYuXKlTKqIUoUGdkQQkdubm689957DBgwgGXLlmFhYcH48eMpW7Ys7733HvDwrFeNGjUYMmQIgwYNwsjIiN27d/Phhx/y1ltvqeuqUqUKu3fvpkWLFhgYGLBgwQKdY/r++++pV68eaWlpjBkzRmM0o3nz5jRr1oyuXbsyb948KleuzNmzZ1EoFLRr1w5XV1fS09PZuXMntWrVwtTUtFDHKYQQJdG3335b4Pa8xbNubm5yx3BR4snIhhDPYcWKFdStW5eOHTvi5eWFSqUiOjpaPbxYpUoVtm/fzokTJ2jQoAFeXl5s2rQJA4P8/fyqVauya9cufvjhB0aNGqVTPN9++y23bt2iTp069OrVi2HDhuW7KtS6deuoX78+PXr0oFq1aowdO1Y9mtGoUSMGDRpE9+7dsbW1Zc6cOYU6TiGEEEKIgsjVqIQQxSYtLQ0rKyuuX78uaza0kDeP3tfXVzp8WpC8aU9yphvJm24kb7opjrzlfX4X5mpUMrIhhBBCCCGEKBLS2RDiFWVubv7Ex759+4o7PCGEEEKIZ5IF4kK8oo4fP/7EfWXLln15gQghhBBC6Eg6G0K8oipXrlzcIQghhBBCPBeZRiWEEEIIIYQoEtLZEEIIIUSJtXTpUmrWrImlpSWWlpZ4eXmxZcsWjTKHDh2iVatWmJmZYWlpSbNmzbh3714xRSzE60U6G0K8ABcvXkShUDx1nYUQQohXT7ly5Zg1axZHjx7l999/p1WrVrz33nv8+eefwMOORrt27fD29ubIkSPEx8cTEBCAnp58hRKiMOR/ihBP4e/vT+fOnYs7DABiY2NRKBTcvn27uEMBICQkBIVCofF4++23izssIYTQSqdOnfD19cXNzY0qVaowY8YMzM3NOXz4MAAjRoxg2LBhjB8/nurVq1O1alW6deuGsbFxMUcuxOtBOhtCFDOVSsWDBw9eaps5OTkvpJ7q1atz9epV9WP//v0vpF4hhCgOubm5REVFkZGRgZeXF6mpqcTFxWFnZ0ejRo2wt7enefPm8rdOCC3I1aiEAH7++WdCQ0O5cOECpqameHp64unpycqVKwFQKBQA7N69mxYtWnDkyBE+/fRTzpw5g4eHBxMnTix0W7GxsbRs2ZLo6GgmTZrEqVOn2L59O82aNWP27Nl8/fXXXLt2jSpVqjB58mQ++OADLl68SMuWLQEoU6YMAH369CEiIgJXV1cCAwMJDAxUt1G7dm06d+5MSEiIOv4vv/ySLVu2sHPnTsaMGQPAxo0bGTVqFJMnT+bWrVu0b9+e5cuXY2FhUahjMTAwwMHBodDH/iQNw3bywMDsuespKYz1VcxpAB4h28jKVRR3OK8NyZv2XvecXZzVoVDlTp06hZeXF/fv38fc3JwNGzZQrVo19ehGSEgI4eHh1K5dm1WrVtG6dWsSEhJwc3MryvCFeCNIZ0OUeFevXqVHjx7MmTOHLl26cPfuXfbt20fv3r1JSUkhLS2NFStWAGBtbU16ejodO3akbdu2rF69muTkZIYPH651u+PHjyc8PJyKFStSpkwZwsLCWL16NV999RVubm7s3buXjz/+GFtbW5o0acK6devo2rUriYmJWFpaYmJiolV7ISEhzJo1iwULFmBgYMB3331HUlISGzdu5LfffuPWrVt069aNWbNmMWPGjELVef78eZycnChVqhReXl6EhYVRvnz5J5bPysoiKytL/TwtLQ0AYz0V+voqrY6nJDPWU2n8KwpH8qa91z1nhR3FrVixIvHx8aSlpbFu3Tr69OnDjh07yM7OBqB///58/PHHAMyZM4cdO3awfPnyJ/6tzGv3RY0ilxSSN90UR960aUs6G6LEu3r1Kg8ePOD999/HxcUFgBo1agBgYmJCVlaWxtn7iIgIlEol3377LaVKlaJ69epcuXKFwYMHa9Xu1KlTadu2LfDwS/jMmTPZsWMHXl5ewMMPv/3797Ns2TKaN2+OtbU1AHZ2dpQuXVrr4+zZsyd9+/bV2KZUKomIiFCPZPTq1YudO3cWqrPRsGFDIiIiqFq1KlevXiU0NJSmTZuSkJDwxJGRsLAwQkND822f5KnE1DRX62Mq6abVUxZ3CK8lyZv2XtecRUdHa/2axo0bs23bNsaOHUvXrl0ByM7O1qjLysqKuLi4Z9YfExOjdftC8qarl5m3zMzMQpeVzoYo8WrVqkXr1q2pUaMGPj4+eHt788EHH6inKz3uzJkz1KxZk1KlSqm35XUQtFGvXj31zxcuXCAzM1Pd+ciTnZ2Np6en1nU/q708rq6uGh0DR0dHUlNTC1Vf+/bt1T/XrFmThg0b4uLiwo8//ki/fv0KfE1QUBAjR45UP09LS8PZ2ZmWLVtiY2NT2EMp8XJycoiJiaFt27YYGhoWdzivDcmb9kpqzhYsWIC9vT3+/v6EhoZiYmKCr6+vev+UKVPw8fHR2Paokpq35yV5001x5C1vZkJhSGdDlHj6+vrExMRw8OBBtm/fzuLFi5k4cSJxcXFF2q6Z2f/WKKSnpwOwefNmypYtq1HuWVc80dPTQ6XSnOJQ0PDmo+3lefyPkkKhQKnU7Qxm6dKlqVKlChcuXHhiGWNj4wKPx9DQUD5YdCB5043kTXtvcs6CgoJo37495cuX5+7du0RGRrJnzx62bduGkZERY8aMYcqUKdSpU4fatWuzcuVKEhMTWbdu3TNz8ibnrShJ3nTzMvOmTTvS2RCCh1+yGzduTOPGjQkODsbFxYUNGzZgZGREbq7m9B53d3e+//577t+/rx7dyFtEqKtq1aphbGxMSkoKzZs3L7CMkZERQL54bG1tuXr1qvp5WloaycnJzxWPLtLT00lKSqJXr14vvW0hhNBVamoqvXv35urVq1hZWVGzZk22bdumHmkODAzk/v37jBgxgps3b1KrVi1iYmKoVKlSMUcuxOtBOhuixIuLi2Pnzp14e3tjZ2dHXFwc//33H+7u7ty/f59t27aRmJiIjY0NVlZW9OzZk4kTJzJgwACCgoK4ePEi4eHhzxWDhYUFo0ePZsSIESiVSpo0acKdO3c4cOAAlpaW9OnTBxcXFxQKBb/99hu+vr6YmJhgbm5Oq1atiIiIoFOnTpQuXZrg4GD09fVfUHaebPTo0XTq1AkXFxf++ecfpkyZgr6+Pj169CjytoUQ4kX59ttvn1lm/PjxjB8//iVEI8SbRzobosSztLRk7969LFiwgLS0NFxcXJg7dy7t27enXr16xMbGUq9ePdLT09WXvv31118ZNGgQnp6eVKtWjdmzZ6sXEupq2rRp2NraEhYWxl9//UXp0qWpU6cOEyZMAKBs2bKEhoYyfvx4+vbtS+/evYmIiCAoKIjk5GQ6duyIlZUV06ZNeykjG1euXKFHjx7cuHFDfcWsw4cPY2trW+RtCyGEEOL1oFA9PtlbCCFekrS0NKysrLh+/bosENdCTk4O0dHR+Pr6yrxmLUjetCc5043kTTeSN90UR97yPr/v3LmDpaXlU8vKHcSFEEIIIYQQRUI6G0K8YIMGDcLc3LzAx6BBg4o7vEJJSUl54jGYm5uTkpJS3CEKIYQQ4jUgazaEeMGmTp3K6NGjC9z3rKHGV4WTkxPHjx9/6n4hhBBCiGeRzoYQL5idnR12dnbFHcZzMTAwoHLlysUdhhBCCCFeczKNSgghhBBCCFEkpLPxCmvRogWBgYHFHYZ4gVxdXVmwYEGR1C3vFyFEUZk9ezb169fHwsICOzs7OnfuTGJiokaZpKQkunTpgq2tLZaWlnTr1o1///23mCIWQrwqpLPxCoiNjUWhUHD79m2N7evXr2fatGnFE1QhXbx4EYVC8dT5/eJ/4uPjGThwoPq5QqFg48aNxRfQE8TGxvLee+/h6OiImZkZtWvXZs2aNfnK/fTTT7z99tuUKlWKGjVqEB0dXQzRCiGK2r59+xg6dCiHDx8mJiaGnJwcvL29ycjIACAjIwNvb28UCgW7du3iwIEDZGdn06lTJ5RKZTFHL4QoTrJm4xVmbW1drO3n5OS81OtcZ2dnY2Rk9NLaKw6vyw3vDh48SM2aNRk3bhz29vb89ttv9O7dGysrKzp27Kgu06NHD8LCwujYsSORkZF07tyZP/74Aw8Pj2I+AiHEi/Tbb79pfB5ERERgZ2fH0aNHadasGQcOHODixYscO3ZMfSGMlStXUqZMGXbt2kWbNm2KK3QhRDEr1pGNrVu30qRJE0qXLo2NjQ0dO3YkKSkJgEaNGjFu3DiN8v/99x+Ghobs3bsXgKtXr9KhQwdMTEyoUKECkZGRWk1TUSgUfPPNN3Tp0gVTU1Pc3Nz45ZdfNMokJCTQvn17zM3Nsbe3p1evXly/fl29/+7du/j5+WFmZoajoyPz58/PN53l+++/p169elhYWODg4EDPnj1JTU0FHo4MtGzZEoAyZcqgUCjw9/cHNKfFTJgwgYYNG+Y7hlq1ajF16lT182+++QZ3d3dKlSrF22+/zZdfflmoXOSNUKxdu5bmzZtTqlQp9Znsp9VZoUIFADw9PVEoFLRo0SJf7Hk6d+6sPjZ4OKVo2rRp9O7dG0tLSwYOHEhERASlS5dm27ZtuLu7Y25uTrt27bh69WqhjsPf35/OnTszc+ZM7O3tKV26NFOnTuXBgweMGTMGa2trypUrx4oVKzReN27cOKpUqYKpqSkVK1Zk8uTJ5OTkaJSZPn06dnZ2WFhY0L9/f8aPH0/t2rXztR0eHo6joyM2NjYMHTpUo55H35+urq4AdOnSBYVCoX6eV8+jAgMD1bmFh2cRe/fujbm5OY6OjsydOzdfLrKyshg9ejRly5bFzMyMhg0bEhsbW6g8TpgwgWnTptGoUSMqVarE8OHDadeuHevXr1eXWbhwIe3atWPMmDG4u7szbdo06tSpw5IlSwrVhhDi9XXnzh3gfyfFsrKyUCgUGBsbq8uUKlUKPT099u/fXywxCiFeDcU6spGRkcHIkSOpWbMm6enpBAcH06VLF44fP46fnx9z5sxh1qxZKBQKANauXYuTkxNNmzYFoHfv3ly/fp3Y2FgMDQ0ZOXKk+kt8YYWGhjJnzhw+//xzFi9ejJ+fH5cuXcLa2prbt2/TqlUr+vfvz/z587l37x7jxo2jW7du7Nq1C4CRI0dy4MABfvnlF+zt7QkODuaPP/7Q+BKak5PDtGnTqFq1KqmpqYwcORJ/f3+io6NxdnZm3bp1dO3alcTERCwtLTExMckXp5+fH2FhYSQlJVGpUiUA/vzzT06ePMm6desAWLNmDcHBwSxZsgRPT0+OHTvGgAEDMDMzo0+fPoXKx/jx45k7dy6enp7qDsfT6jxy5AgNGjRgx44dVK9eXeuRifDwcIKDg5kyZQrwcKg+MzOT8PBwvv/+e/T09Pj4448ZPXp0gdN4CrJr1y7KlSvH3r17OXDgAP369ePgwYM0a9aMuLg41q5dy6effkrbtm0pV64cABYWFkRERODk5MSpU6cYMGAAFhYWjB07Vp3bGTNm8OWXX9K4cWOioqKYO3euurOVZ/fu3Tg6OrJ7924uXLhA9+7dqV27NgMGDMgXZ3x8PHZ2dqxYsYJ27dqhr69f6LyNGTOGPXv2sGnTJuzs7JgwYUK+911AQACnT58mKioKJycnNmzYQLt27Th16hRubm6FbivPnTt3cHd3Vz8/dOgQI0eO1Cjj4+Pz1GlhWVlZZGVlqZ+npaUB0Gz2Dh4YmmkdU0llrKdiWj2oO3UrWUpFcYfz2pC8PVlCiE+B2/NOljx60kSpVDJ8+HAaNWpE1apVycnJoW7dupiZmTFmzBimTZuGSqVi4sSJ5Obm8vfff+c7efOmKyhv4tkkb7opjrxp01axdja6du2q8fy7777D1taW06dP061bNwIDA9m/f7+6cxEZGUmPHj1QKBScPXuWHTt2EB8fT7169YCHZ+C1/RLl7+9Pjx49AJg5cyaLFi3iyJEjtGvXTv0Fe+bMmRoxOjs7c+7cORwdHVm5ciWRkZG0bt0agBUrVuS7B8Enn3yi/rlixYosWrSI+vXrk56ejrm5ufrMkJ2dHaVLly4wzurVq1OrVi0iIyOZPHky8PALcMOGDdWXKJ0yZQpz587l/fffBx6OOpw+fZply5YVurMRGBiofn1h6sybFmRjY4ODg0Oh2nhUq1atGDVqlPr5vn37yMnJ4auvvlJ3qgICAjRGb57F2tqaRYsWoaenR9WqVZkzZw6ZmZlMmDABgKCgIGbNmsX+/fv56KOPAJg0aZL69a6urowePZqoqCh1Z2Px4sX069ePvn37AhAcHMz27dtJT0/XaLtMmTIsWbIEfX193n77bTp06MDOnTsL7Gzk5a506dJa5S49PZ1vv/2W1atXq993K1euVHec4OFN+VasWEFKSor6/Th69Gi2bt3KihUrNN7ThfHjjz8SHx/PsmXL1NuuXbuGvb29Rjl7e3uuXbv2xHrCwsIIDQ3Nt32SpxJT01ytYhIwrZ7MhdeF5C2/Z623iomJUf/81VdfcfToUcLCwjReN2LECL766iuWLFmCQqGgadOmVKxYkStXrpTY9VyP5k0UnuRNNy8zb5mZmYUuW6ydjfPnzxMcHExcXBzXr19XLyJLSUnBw8MDb29v1qxZQ9OmTUlOTubQoUPqLzuJiYkYGBhQp04ddX2VK1emTJkyWsVQs2ZN9c9mZmZYWlqqR0dOnDjB7t27MTc3z/e6pKQk7t27R05ODg0aNFBvt7KyomrVqhpljx49SkhICCdOnODWrVsax1mtWrVCx+rn58d3333H5MmTUalU/PDDD+ozyxkZGSQlJdGvXz+NL7YPHjzAysqq0G3kddxeZJ2FbS+PqampuqMB4OjoqNWIVfXq1dHT+98MQXt7e401BPr6+tjY2GjUuXbtWhYtWkRSUhLp6ek8ePBA4wZ8iYmJDBkyRKOdBg0aqEe4Hm370REKR0dHTp06VejYCyMpKYns7GyNaXXW1tYa77tTp06Rm5tLlSpVNF6blZWFjY2NVu3t3r2bvn37snz5cqpXr/5csQcFBWmMhqSlpeHs7Mz0Y3o8MCz8yE5J9/AMvZLJv+vJGXotSN6e7GkjGzExMbRt2xZDQ0OGDx9OQkIC+/fvzzey6+vry8SJE7l+/ToGBgaULl0aZ2dnmjdvjq+v78s4jFfG43kThSN5001x5C1vZkJhFGtno1OnTri4uLB8+XKcnJxQKpV4eHiQnZ0NPPxyPWzYMBYvXkxkZCQ1atSgRo0aLzSGx38pCoVC3RlIT0+nU6dOzJ49O9/rHB0duXDhwjPrz8jIwMfHBx8fH9asWYOtrS0pKSn4+Pioj7OwevTowbhx4/jjjz+4d+8ely9fpnv37upYAZYvX55vbYc203PMzP43leV56tTT00OlUmlsK2jI7dH28hT0O3m8rqcp6PVP+z0fOnQIPz8/QkND8fHxwcrKSj1NSltPa6ewCpu7p0lPT0dfX5+jR4/m+10V1Hl+kj179tCpUyfmz59P7969NfY5ODjku6zlv//++9RRGmNjY4053Xn2jmujdSeoJMvJySE6Opqjwe3kA1kLkjfdGRgYMGLECDZt2kRsbOxTZxE4OjoCD6e0pqam0qVLlxKbb0NDwxJ77M9D8qabl5k3bdopts7GjRs3SExMZPny5eppUo8vInvvvfcYOHAgW7duJTIyUuPLTtWqVXnw4AHHjh2jbt26AFy4cIFbt269sBjr1KnDunXrcHV1xcAgf6oqVqyIoaEh8fHxlC9fHng4r/3cuXM0a9YMgLNnz3Ljxg1mzZqFs7MzAL///rtGPXnrHHJznz6NpFy5cjRv3pw1a9Zw79492rZtq75Ttb29PU5OTvz111/4+fk934H/v8LU+aTYbW1tNRZ15+bmkpCQoF4M/yo5ePAgLi4uTJw4Ub3t0qVLGmWqVq1KfHy8xnswPj7+uds2NDQsMHcJCQka244fP67+j12pUiUMDQ2Ji4tTv+9u3brFuXPnaN68OfBwwX5ubi6pqanq/1/aio2NpWPHjsyePVvjcr15vLy82Llzp8aFAGJiYvDy8tKpPSHEq2vYsGFERUWxadMmLCws1NMlrays1OsMV6xYgbu7O7a2thw6dIjhw4czYsSIfKP9QoiSpdg6G2XKlMHGxoavv/4aR0dHUlJSGD9+vEYZMzMzOnfuzOTJkzlz5ox6bQXA22+/TZs2bRg4cCBLly7F0NCQUaNGYWJiol5Q/ryGDh3K8uXL6dGjB2PHjsXa2poLFy4QFRXFN998g4WFBX369FFf5cjOzo4pU6agp6enjqF8+fIYGRmxePFiBg0aREJCQr57Z7i4uKBQKPjtt9/w9fXFxMTkiWef/fz8mDJlCtnZ2cyfP19jX2hoKMOGDcPKyop27dqRlZXF77//zq1bt/It5C2sZ9VpZ2eHiYkJW7dupVy5cpQqVQorKytatWrFyJEj2bx5M5UqVWLevHn57iPyqnBzcyMlJYWoqCjq16/P5s2b2bBhg0aZzz77jAEDBlCvXj0aNWrE2rVrOXnyJBUrVnyutl1dXdm5cyeNGzfG2NiYMmXK0KpVKz7//HNWrVqFl5cXq1evJiEhAU9PT+DhyES/fv0YM2YMNjY22NnZMXHiRI2pY1WqVMHPz4/evXurF/z/999/7Ny5k5o1a9KhQ4enxrV79246duzI8OHD6dq1q/qLhZGRkXqN0fDhw2nevDlz586lQ4cOREVF8fvvv/P1118/V06EEK+evCnMj14VDx52MPKuMpiYmEhQUBA3b97E1dWViRMnMmLEiJccqRDiVVNsl77V09MjKiqKo0eP4uHhwYgRI/j888/zlfPz8+PEiRM0bdpUfRY3z6pVq7C3t6dZs2Z06dJFfQWhUqVKvZAYnZycOHDgALm5uXh7e1OjRg0CAwMpXbq0+ovdvHnz8PLyomPHjrRp04bGjRurLxMLD89SR0RE8NNPP1GtWjVmzZpFeHi4Rjtly5YlNDSU8ePHY29vT0BAwBNj+uCDD7hx4waZmZn5Lo/av39/vvnmG1asWEGNGjVo3rw5ERER+ebVauNZdRoYGLBo0SKWLVuGk5MT7733HvBwUXyfPn3o3bs3zZs3p2LFiq/kqAbAu+++y4gRIwgICKB27docPHhQvQg/j5+fH0FBQYwePZo6deqQnJyMv7//c7/X5s6dS0xMDM7OzurOhI+PD5MnT2bs2LHUr1+fu3fv5pvC9Pnnn9O0aVM6depEmzZtaNKkiXqEL8+KFSvo3bs3o0aNomrVqnTu3FljFO5pVq5cSWZmJmFhYTg6Oqofj148oFGjRkRGRvL1119Tq1Ytfv75ZzZu3Cj32BDiDZSdnY1Kpcr3ePRy5rNmzeLatWtkZ2dz7tw5Ro4c+cJO/gkhXl8KlTaT4V9xV65cwdnZmR07dqiv0vOyZWRkULZsWebOnUu/fv2KJQbxcrRt2xYHBwe+//774g7ltZWWloaVlRXXr1+XNRtayFt74OvrK/OatSB5057kTDeSN91I3nRTHHnL+/y+c+eOxgV1CvJa30F8165dpKenU6NGDa5evcrYsWNxdXVVr5d4GY4dO8bZs2dp0KABd+7cUV+iNe8Mv3gzZGZm8tVXX+Hj44O+vj4//PADO3bskMvzCSGEEEI8RbHeQfx55eTkMGHCBKpXr06XLl2wtbVV3+BvzZo1mJubF/h43st3Pi48PJxatWrRpk0bMjIy2LdvH2+99dYLbeN5zZw584n5aN++fXGHV2hPOgZzc3P27dtXZO0qFAqio6Np1qwZdevW5ddff2XdunW0adOmyNosSu3bt39iHrW9B4cQQgghxJO81iMbeZeULci7776b73KteV7kEJOnpydHjx59YfUVlUGDBtGtW7cC9xV0x/JX1fHjx5+4r2zZskXWromJCTt27Ciy+l+2b775hnv37hW4L28BuBBCCCHE83qtOxtPY2FhgYWFRXGH8cqwtrZ+I75E5t0tXTyfouyYCSGEEELkea2nUQkhhBBCCCFeXdLZEEIIId4AYWFh1K9fHwsLC+zs7OjcuTOJiYn5yh06dIhWrVphZmaGpaUlzZo1e+K0SiGEeF7S2RCvDX9//3z3FnlcixYtNO5oLYQQJcWePXsYOnQohw8fJiYmhpycHLy9vcnIyFCXOXToEO3atcPb25sjR44QHx9PQECAxk1BhRDiRXpj12yIohMSEsLGjRufulhbCCHEy7V161aN5xEREdjZ2XH06FH1JeFHjBjBsGHDGD9+vLpc1apVX2qcQoiSRU5lCPECZWdnF3cIQggBwJ07d4D/XWEuNTWVuLg47OzsaNSoEfb29jRv3pz9+/cXZ5hCiDecjGyUUEqlkvDwcL7++msuX76Mvb09n376KRMnTmTcuHFs2LCBK1eu4ODggJ+fH8HBwRgaGhIREUFoaCjw8N4TACtWrMDf3/+p7Z09e5b+/fvz+++/U7FiRRYtWkTbtm3ZsGGDemrUqVOnGD58OIcOHcLU1JSuXbsyb948zM3NC6wzIyODwYMHs379eiwsLBg9enS+MllZWUycOJEffviB27dv4+HhwezZs2nRogXw8MxfYGAga9euJTAwkMuXL9OkSRNWrFiBo6PjM/Po7+/P7du3qV+/Pl988QXGxsYkJydz+fJlRo0axfbt29HT06Np06YsXLgQV1dXAGJjYxk7dix//vknhoaGVK9encjISFxcXABYunQp4eHhXL58mQoVKjBp0iR69eqlblehULB8+XI2b97Mtm3b1Hetf/fddwHIzc1l4MCB7Nq1i2vXrlG+fHmGDBnC8OHD88XepEkT5s6dS3Z2Nh999BELFixQXx46KyuL4OBgIiMjSU1NxdnZmaCgIPr16wdAQkICY8aMYd++fZiZmeHt7c38+fO1vs9Mw7CdPDAw0+o1JZmxvoo5DcAjZBtZuYriDue18Trn7eKsDlqVVyqVBAYG0rhxYzw8PAD466+/gIej0+Hh4dSuXZtVq1bRunVrEhIScHNze+FxCyGEdDZKqKCgIJYvX878+fNp0qQJV69e5ezZs8DDywZHRETg5OTEqVOnGDBgABYWFowdO5bu3buTkJDA1q1b1fedsLKyempbubm5dO7cmfLlyxMXF8fdu3cZNWqURpmMjAx8fHzw8vIiPj6e1NRU+vfvT0BAABEREQXWO2bMGPbs2cOmTZuws7NjwoQJ/PHHH9SuXVtdJiAggNOnTxMVFYWTkxMbNmygXbt2nDp1Sv3BmpmZSXh4ON9//z16enp8/PHHjB49mjVr1hQqlzt37sTS0lJ9N/GcnBz1sezbtw8DAwOmT59Ou3btOHnyJHp6enTu3JkBAwbwww8/kJ2dzZEjR9Sdtw0bNjB8+HAWLFhAmzZt+O233+jbty/lypWjZcuW6nZDQ0OZM2cOn3/+OYsXL8bPz49Lly5hbW2NUqmkXLly/PTTT9jY2HDw4EEGDhyIo6Ojxv1Wdu/ejaOjI7t37+bChQt0796d2rVrM2DAAAB69+7NoUOHWLRoEbVq1SI5OZnr168DcPv2bVq1akX//v2ZP38+9+7dY9y4cXTr1o1du3YVmKusrCyysrLUz9PS0gAw1lOhr68qVL7Fw3w9+q8onNc5bzk5OVqVDwgIICEhgd27d6tfmzfy2r9/fz7++GMA5syZw44dO1i+fDkzZsx4Yrvatl/SSd50I3nTTXHkTZu2FCqV6vX7qyuey927d7G1tWXJkiX079//meXDw8OJiori999/B7Rfs7F161Y6derE5cuXcXBwAGDHjh0aIxvLly9n3LhxXL58GTOzh2e4o6Oj6dSpE//88w/29vbqM/EbN24kPT0dGxsbVq9ezYcffgjAzZs3KVeuHAMHDmTBggWkpKRQsWJFUlJScHJyUsfTpk0bGjRowMyZM4mIiKBv375cuHCBSpUqAfDll18ydepUrl279sxj8/f3Z+vWraSkpGBkZATA6tWrmT59OmfOnFF3ILKzsyldujQbN26kXr162NjYEBsbS/PmzfPV2bhxY6pXr87XX3+t3tatWzcyMjLYvHkz8HBkY9KkSUybNg142FkzNzdny5YttGvXrsBYAwICuHbtGj///LM69tjYWJKSktDX11e3o6enR1RUFOfOnaNq1arExMQUeKf06dOns2/fPrZt26beduXKFZydnUlMTKRKlSr5XhMSEqIeGXtUZGQkpqamBcYthNDO119/TVxcHDNnzsTe3l69/d9//+XTTz8lMDBQPboL8Pnnn6Ovr8/IkSOLIVohxOsoMzOTnj17cufOHSwtLZ9aVkY2SqAzZ86QlZVF69atC9y/du1aFi1aRFJSEunp6Tx48OCZb6SnSUxMxNnZWd3RAGjQoEG+mGrVqqXuaMDDL91KpZLExESND0yApKQksrOzNe4Sb21trbHQ8dSpU+Tm5ub70puVlYWNjY36uampqbqjAeDo6Ehqamqhj69GjRrqjgbAiRMnuHDhQr6bSt6/f5+kpCS8vb3x9/fHx8eHtm3b0qZNG7p166aetnXmzBkGDhyo8drGjRuzcOFCjW01a9ZU/5x3CctH4/7iiy/47rvvSElJ4d69e2RnZ2uM+gBUr15d3dHIO/ZTp04BD+/Wrq+vX2CHKO84d+/eXeA0t6SkpAI7G0FBQRpfaNLS0nB2dmb6MT0eGOrnKy8KZqynYlo9JZN/1yNL+XpNBypOr3PeEkJ8nllGpVIRGBjI8ePH2bt3b75pUSqVitDQUExMTPD19VVvnzJlCj4+Phrb8uTk5BATE0Pbtm3V0yvFs0nedCN5001x5C1vZkJhSGejBDIxMXnivkOHDuHn50doaCg+Pj5YWVkRFRXF3LlzX2KEL0Z6ejr6+vocPXpU4ws1oPEF+fH/mAqFAm0G/B7tIOW1W7du3QKnYdna2gIP17kMGzaMrVu3snbtWiZNmkRMTAzvvPNOodstKG6lUglAVFQUo0ePZu7cuXh5eWFhYcHnn39OXFxcoet42vsk7zg7derE7Nmz8+170noXY2NjjI2N823fO66NRgdQPF1OTg7R0dEcDW4nH8haeNPzNmTIECIjI9m0aRPW1tbcuHEDeDjVNe//85gxY5gyZQp16tShdu3arFy5ksTERNatW/fUnBgaGr6ROStqkjfdSN508zLzpk070tkogdzc3DAxMWHnzp35plEdPHgQFxcXJk6cqN526dIljTJGRkbk5uYWur2qVaty+fJl/v33X/UIRXx8vEYZd3d3IiIiyMjIUH95P3DgAHp6egVelrFSpUoYGhoSFxdH+fLlAbh16xbnzp1Tn4n39PQkNzeX1NRUmjZtWuh4n1edOnVYu3YtdnZ2Tx0R8vT0xNPTk6CgILy8vIiMjOSdd97B3d2dAwcO0KdPH3XZAwcOUK1atULHcODAARo1asSQIUPU25KSkrQ6jho1aqBUKtmzZ0+B06jq1KnDunXrcHV1xcBA/pQIUdyWLl0KoDFFCjQv4hEYGMj9+/cZMWIEN2/epFatWsTExGiM7gohxIskl74tgUqVKsW4ceMYO3Ysq1atIikpicOHD/Ptt9/i5uZGSkoKUVFRJCUlsWjRIjZs2KDxeldXV5KTkzl+/DjXr1/XWPBbkLZt21KpUiX69OnDyZMnOXDgAJMmTQL+d0UrPz8/SpUqRZ8+fdSLGj/77DN69eqVbwoVPByZ6NevH2PGjGHXrl0kJCTg7++vcWOqKlWq4OfnR+/evVm/fj3JyckcOXKEsLAw9dqHouDn58dbb73Fe++9x759+0hOTiY2NpZhw4Zx5coVkpOTCQoK4tChQ1y6dInt27dz/vx53N3dgYdnHiMiIli6dCnnz59n3rx5rF+/vsCrbT2Jm5sbv//+O9u2bePcuXNMnjw5XwfvWVxdXenTpw+ffPIJGzduVB/Hjz/+CMDQoUO5efMmPXr0ID4+nqSkJLZt20bfvn216owKIV4MlUpV4OPxqwWOHz+ey5cvk5GRwcGDB2nSpEnxBCyEKBGks1FCTZ48mVGjRhEcHIy7uzvdu3cnNTWVd999lxEjRhAQEEDt2rU5ePAgkydP1nht165dadeuHS1btsTW1pYffvjhqW3p6+urF3XXr1+f/v37q0dOSpUqBTxcN7Ft2zZu3rxJ/fr1+eCDD2jdujVLlix5Yr2ff/45TZs2pVOnTrRp04YmTZpQt25djTIrVqygd+/ejBo1iqpVq9K5c2fi4+PVoyFFwdTUlL1791K+fHnef/993N3d6devH/fv38fS0hJTU1POnj1L165dqVKlCgMHDmTo0KF8+umnAHTu3JmFCxcSHh5O9erVWbZsGStWrMh3tvJpPv30U95//326d+9Ow4YNuXHjhsYoR2EtXbqUDz74gCFDhvD2228zYMAA9d2InZycOHDgALm5uXh7e1OjRg0CAwMpXbq03I1YCCGEEIBcjUoUkwMHDtCkSRONq0CJkictLQ0rKyuuX78uaza0kLf2wNfXV+Y1a0Hypj3JmW4kb7qRvOmmOPKW9/ktV6MSr4wNGzZgbm6Om5sbFy5cYPjw4TRu3Fg6GkIIIYQQbzCZ6yCe25o1azA3Ny/wUb16deDhvT2GDh3K22+/jb+/P/Xr12fTpk3FHPmzPem4zM3N2bdvX3GHJ4QQQgjxSpORDfHc3n33XY37XTwqbzivd+/e9O7d+2WG9UI87caFZcuWfXmBCCGEEEK8hqSzIZ6bhYVFvhvYvSkqV65c3CEIIYQQQry2ZBqVEEIIIYQQokhIZ0OIV9S1a9do27YtZmZmlC5durjDEUK84sLCwqhfvz4WFhbY2dnRuXNnEhMT85U7dOgQrVq1wszMDEtLS5o1a8a9e/eKIWIhREkgnQ0hXoKQkBBq166t1Wvmz5/P1atXOX78OOfOnXshcbRo0YLAwMAXUtejVCoV7du3R6FQsHHjxhdevxDi2fbs2cPQoUM5fPgwMTEx5OTk4O3trb43DjzsaLRr1w5vb2+OHDlCfHw8AQEBcm8cIUSRkTUbQryikpKSqFu3Lm5ubsUdSj7Z2dkYGRmpny9YsEB9N3ghRPHYunWrxvOIiAjs7Ow4evQozZo1A2DEiBEMGzaM8ePHq8tVrVr1pcYphChZ5FSGEIW0detWmjRpQunSpbGxsaFjx44kJSWp91+5coUePXpgbW2NmZkZ9erVIy4ujoiICEJDQzlx4gQKhQKFQkFERMRT23J1dWXdunWsWrUKhUKBv78/APPmzaNGjRqYmZnh7OzMkCFDSE9P13jtgQMHaNGiBaamppQpUwYfHx9u3bqFv78/e/bsYeHCheo4Ll68CDw8I9qgQQOMjY1xdHRk/PjxPHjwQF1nixYtCAgIIDAwkLfeegsfHx/1vuPHjzN37ly+++6750uwEOKFunPnDgDW1tYApKamEhcXh52dHY0aNcLe3p7mzZuzf//+4gxTCPGGk5ENIQopIyODkSNHUrNmTdLT0wkODqZLly4cP36czMxMmjdvTtmyZfnll19wcHDgjz/+QKlU0r17dxISEti6dSs7duwAwMrK6qltxcfH07t3bywtLVm4cCEmJiYA6OnpsWjRIipUqMBff/3FkCFDGDt2LF9++SXw8It/69at+eSTT1i4cCEGBgbs3r2b3NxcFi5cyLlz5/Dw8GDq1KkA2Nra8vfff+Pr64u/vz+rVq3i7NmzDBgwgFKlShESEqKOaeXKlQwePJgDBw6ot2VmZtKzZ0+++OILHBwcdM5tw7CdPDAw0/n1JY2xvoo5DcAjZBtZuTKiVFivc94uzuqgVXmlUklgYCCNGzfGw8MDgL/++gt4OK0zPDyc2rVrs2rVKlq3bk1CQsIrOYoqhHj9vbDOxu3bt2URq3ijde3aVeP5d999h62tLadPn+bgwYP8999/xMfHq88iPnrZXHNzcwwMDAr9hdzW1hZjY2NMTEw0XvPoegtXV1emT5/OoEGD1J2NOXPmUK9ePfVzQH1jRQAjIyNMTU016vzyyy9xdnZmyZIlKBQK3n77bf755x/GjRtHcHCwei63m5sbc+bM0YhzxIgRNGrUiPfee69Qx5WVlUVWVpb6eVpaGgDGeir09VWFqkM8zNej/4rCeZ3zlpOTo1X5gIAAEhIS2L17t/q12dnZAPTv35+PP/4YePg3Y8eOHSxfvpwZM2Y8sV1t2y/pJG+6kbzppjjypk1bOnU2Zs+ejaurK927dwegW7durFu3DgcHB6Kjo6lVq5Yu1QrxSjt//jzBwcHExcVx/fp1lEolACkpKRw/fhxPT091R6Oo7Nixg7CwMM6ePUtaWhoPHjzg/v37ZGZmYmpqyvHjx/nwww+1qvPMmTN4eXlprLlo3Lgx6enpXLlyhfLlywNQt25djdf98ssv7Nq1i2PHjhW6rbCwMEJDQ/Ntn+SpxNQ0V6u4BUyrpyzuEF5Lr2PeoqOjC13266+/Ji4ujpkzZ3Ly5ElOnjwJwL///gs87HQ8Wp+VlRVxcXFPbSMmJkbHyEs2yZtuJG+6eZl5y8zMLHRZnTobX331FWvWrAEeHlhMTAxbtmzhxx9/ZMyYMWzfvl2XaoV4pXXq1AkXFxeWL1+Ok5MTSqUSDw8PsrOz1dOcitLFixfp2LEjgwcPZsaMGVhbW7N//3769etHdnY2pqamRRqHmZnmNKddu3aRlJSUb0Sza9euNG3alNjY2Hx1BAUFMXLkSPXztLQ0nJ2dadmyJTY2NkUR9hspJyeHmJgY2rZti6GhYXGH89p40/OmUqkIDAzk+PHj7N27N9+0KJVKRWhoKCYmJvj6+qq3T5kyBR8fH41ted70nBUVyZtuJG+6KY685c1MKAydOhvXrl3D2dkZgN9++41u3brh7e2Nq6srDRs21KVKIV5pN27cIDExkeXLl9O0aVMAjUWVNWvW5JtvvuHmzZsFjm4YGRmRm/t8Z+6PHj2KUqlk7ty56qlNP/74o0aZmjVrsnPnzgJHD54Uh7u7O+vWrUOlUqlHNw4cOICFhQXlypV7Yjzjx4+nf//+Gttq1KjB/Pnz6dSpU4GvMTY2xtjYON92Q0ND+WDRgeRNN29q3oYMGUJkZCSbNm3C2tqaGzduAA9HLvJORIwZM4YpU6ZQp04dateuzcqVK0lMTGTdunVPzcmbmrOiJnnTjeRNNy8zb9q0o9PVqMqUKcPly5eBh1foadOmDfDwrMnzfqES4lVUpkwZbGxs+Prrr7lw4QK7du3SOEPfo0cPHBwc6Ny5MwcOHOCvv/5i3bp1HDp0CHi4viI5OZnjx49z/fp1jXULhVW5cmVycnJYvHgxf/31F99//z1fffWVRpmgoCDi4+MZMmQIJ0+e5OzZsyxdupTr16+r44iLi+PixYvqqWBDhgzh8uXLfPbZZ5w9e5ZNmzYxZcoURo4c+dRr7zs4OODh4aHxAChfvjwVKlTQ+viEEM9n6dKl3LlzhxYtWuDo6Kh+rF27Vl0mMDCQoKAgRowYQa1atdi5cycxMTFUqlSpGCMXQrzJdOpsvP/++/Ts2ZO2bdty48YN2rdvD8CxY8c0FsUK8abQ09MjKiqKo0eP4uHhwYgRI/j888/V+42MjNi+fTt2dnb4+vpSo0YNZs2ahb6+PvBwalG7du1o2bIltra2/PDDD1rHUKtWLebNm8fs2bPx8PBgzZo1hIWFaZSpUqUK27dv58SJEzRo0AAvLy82bdqEgcHDQczRo0ejr69PtWrVsLW1JSUlhbJlyxIdHc2RI0eoVasWgwYNol+/fkyaNOk5MiaEeNlUKlWBj7xLZ+cZP348ly9fJiMjg4MHD9KkSZPiCVgIUSLoNI1q/vz5uLq6cvnyZebMmYO5uTkAV69eZciQIS80QCFeFW3atOH06dMa21Sq/13VxsXFhZ9//rnA1xobGz9x35MUdCfuESNGMGLECI1tvXr10njevHlzjcvTPqpKlSrq0ZbHX3PkyJEnxlLQ+ouCPJoPIYQQQgidOhuGhoaMHj063/bHvwQJIYQQQgghSi6d7yD+/fff06RJE5ycnLh06RIACxYsYNOmTS8sOCHeVGvWrMHc3LzAx6P3xRBCCCGEeJ3pNLKxdOlSgoODCQwMZMaMGepF4aVLl2bBggWFvsGXECXVu++++8Qrt8kVOIQQQgjxptCps7F48WKWL19O586dmTVrlnp7vXr1CpxeJYTQZGFhgYWFRXGHIYQQQghRpHSaRpWcnIynp2e+7cbGxmRkZDx3UEIIIYQQQojXn06djQoVKnD8+PF827du3Yq7u/vzxiSEEEKIx4SFhVG/fn0sLCyws7Ojc+fOJCYmapRp0aIFCoVC4zFo0KBiilgIIXScRjVy5EiGDh3K/fv3UalUHDlyhB9++IGwsDC++eabFx2jEEIIUeLt2bOHoUOHUr9+fR48eMCECRPw9vbm9OnTmJmZqcsNGDCAqVOnqp+bmpoWR7hCCAHoOLLRv39/Zs+ezaRJk8jMzKRnz54sXbqUhQsX8tFHH73oGIUoEVq0aEFgYGBxhwHAiRMn6NGjB87OzpiYmODu7s7ChQvzlYuNjaVOnToYGxtTuXJlIiIiXn6wQpQQW7duxd/fn+rVq1OrVi0iIiJISUnh6NGjGuVMTU1xcHBQPywtLYspYiGE0KGz8eDBA1atWkWbNm04f/486enpXLt2jStXrtCvX7+iiFGI1152dvZr1dbRo0exs7Nj9erV/Pnnn0ycOJGgoCCWLFmiLpOcnEyHDh1o2bIlx48fJzAwkP79+7Nt27bnbl8I8Wx37twBwNraWmP7mjVreOutt/Dw8CAoKIjMzMziCE8IIQAdplEZGBgwaNAgzpw5Azw8gyJDtEJoatGiBR4eHhgYGLB69Wpq1KjB4sWLGTNmDPv27cPMzAxvb2/mz5/PW2+9hb+/P3v27GHPnj3qEYTk5GRiY2MJDAzk9u3b6ro3btxIly5d1HfrDgkJYePGjQQEBDBjxgwuXbqEUqlEoVCwfPlyNm/ezLZt2yhbtixz587l3XfffWb8n3zyicbzihUrcujQIdavX09AQAAAX331FRUqVGDu3LkAuLu7s3//fubPn4+Pj49W+WoYtpMHBmbPLigAMNZXMacBeIRsIytXUdzhvDZe9bxdnNWh0GWVSiWBgYE0btwYDw8P9faePXvi4uKCk5MTJ0+eZNy4cSQmJrJ+/fqiCFkIIZ5JpzUbDRo04NixY7i4uLzoeIR4Y6xcuZLBgwdz4MABbt++TatWrejfvz/z58/n3r17jBs3jm7durFr1y4WLlzIuXPn8PDwUM+1trW1LXRbFy5cYN26daxfvx59fX319tDQUObMmcPnn3/O4sWL8fPz49KlS/nOhBbGnTt3NF536NAh2rRpo1HGx8fnqVPBsrKyyMrKUj9PS0sDwFhPhb6+SuuYSipjPZXGv6JwXvW85eTkFLpsQEAACQkJ7N69W+N1ffv2Vf/89ttvY2tri4+PD2fPnqVSpUo6x6RNbELypivJm26KI2/atKVTZ2PIkCGMGjWKK1euULduXY2FaQA1a9bUpVoh3ihubm7MmTMHgOnTp+Pp6cnMmTPV+7/77jucnZ05d+4cVapUwcjISD3XWlvZ2dmsWrUqXwfF39+fHj16ADBz5kwWLVrEkSNHaNeunVb1Hzx4kLVr17J582b1tmvXrmFvb69Rzt7enrS0NO7du4eJiUm+esLCwggNDc23fZKnElPTXK1iEjCtnrK4Q3gtvap5i46OLlS5r7/+mri4OGbOnMnJkyc5efLkE8vev38fgKioqAIvWV9YMTExOr+2JJO86UbyppuXmTdtpmfq1NnIWwQ+bNgw9TaFQoFKpUKhUKjvKC5ESVa3bl31zydOnGD37t2Ym5vnK5eUlESVKlWeqy0XF5cCR0Ie7fibmZlhaWlJamqqVnUnJCTw3nvvMWXKFLy9vZ8rzqCgIEaOHKl+npaWhrOzM9OP6fHAUP8prxSPMtZTMa2eksm/65GlfPWmA72qXvW8JYQ8ffqhSqUiMDCQ48ePs3fvXtzc3J5Z58GDBwHo1KmTTicCc3JyiImJoW3bthgaGmr9+pJK8qYbyZtuiiNveTMTCkOnzkZycrIuLxOiRHl0xC89PZ1OnToxe/bsfOUcHR2fWIeenp56bUaegoYuHx9dzPP4Hx2FQoFSWfizuqdPn6Z169YMHDiQSZMmaexzcHDg33//1dj277//YmlpWeCoBjy88aexsXG+7XvHtcHGxqbQcZV0OTk5REdHczS4nXwga+F1z9uQIUOIjIxk06ZNWFtbc+PGDQCsrKwwMTEhKSmJyMhIfH19sbGx4eTJk4wYMYJmzZppnPzQhaGh4WuZs+ImedON5E03LzNv2rSjU2dD1moIoZ06deqwbt06XF1dMTAo+L+dkZFRvlFBW1tb7t69S0ZGhrpDUdANNYvCn3/+SatWrejTpw8zZszIt9/LyyvftI+YmBi8vLxeSnxClDRLly4FHl6A4lErVqzA398fIyMjduzYwYIFC8jIyMDZ2ZmuXbvmO1EghBAvk06djVWrVj11f+/evXUKRog31dChQ1m+fDk9evRg7NixWFtbc+HCBaKiovjmm2/Q19fH1dWVuLg4Ll68iLm5OdbW1jRs2BBTU1MmTJjAsGHDiIuLeyn3skhISKBVq1b4+PgwcuRIrl27BoC+vr56utagQYNYsmQJY8eO5ZNPPmHXrl38+OOPGus6hBAvzuOjnI9zdnZmz549LykaIYQoHJ06G8OHD9d4npOTQ2ZmpnqBq3Q2hNDk5OTEgQMHGDduHN7e3mRlZeHi4kK7du3Q03t4u5vRo0fTp08fqlWrxr1790hOTsbV1ZXVq1czZswYli9fTuvWrQkJCWHgwIFFGu/PP//Mf//9x+rVq1m9erV6u4uLCxcvXgSgQoUKbN68mREjRrBw4ULKlSvHN998o/Vlb4UQQgjx5lKonnWqpJDOnz/P4MGDGTNmjHzZEEIUSlpaGlZWVly/fl3WbGghb+2Br6+vzGvWguRNe5Iz3UjedCN5001x5C3v8/vOnTtYWlo+tazWdxB/Ejc3N2bNmpVv1EMIIYQQQghRMr2wzgY8vLv4P//88yKrFEIUgUGDBmFubl7gY9CgQcUdnhBCCCHeEDqt2fjll180nqtUKq5evcqSJUto3LjxCwlMCFF0pk6dyujRowvc96zhUCGEEEKIwtKps9G5c2eN5wqFAltbW1q1asXcuXNfRFxCiCJkZ2eHnZ1dcYchhBBCiDecTp0NbW4KJoQQQgghhCiZdFqzMXXqVDIzM/Ntv3fvHlOnTn3uoIQQQojXUVhYGPXr18fCwgI7Ozs6d+5MYmKiev/Nmzf57LPPqFq1KiYmJpQvX55hw4Zx586dYoxaCCGKjk6djdDQUNLT0/Ntz8zMJDQ09LmDEkK8ejZu3EjlypXR19cnMDCwuMMR4pW0Z88ehg4dyuHDh4mJiSEnJwdvb28yMjIA+Oeff/jnn38IDw8nISGBiIgItm7dSr9+/Yo5ciGEKBo6TaNSqVQoFIp820+cOIG1tfVzByWE0F1ISAgbN27k+PHjL7TeTz/9lL59+zJs2DAsLCw09l24cAFPT0/09fW5ffv2C21XiNfJ1q1bNZ5HRERgZ2fH0aNHadasGR4eHqxbt069v1KlSsyYMYOPP/6YBw8eYGCg08eyEEK8srT6q1amTBkUCgUKhYIqVapodDhyc3NJT0+Xy2YK8QZKT08nNTUVHx8fnJycNPbl5OTQo0cPmjZtysGDB4spQiFeTXnTo552Ii7vpljS0RBCvIm0+su2YMECVCoVn3zyCaGhoVhZWan3GRkZ4erqipeX1wsPUoiSRqlUEh4eztdff83ly5ext7fn008/ZeLEiYwbN44NGzZw5coVHBwc8PPzIzg4GENDQyIiItRTGfNOBqxYsQJ/f/+ntjdv3jxWrFjBX3/9hbW1NZ06dWLOnDmYm5sTGxtLy5YtAWjVqhUAu3fvpkWLFgBMmjSJt99+m9atW+vc2WgYtpMHBmY6vbYkMtZXMacBeIRsIys3/yizKNjz5u3irA5alVcqlQQGBtK4cWM8PDwKLHP9+nWmTZvGwIEDtY5HCCFeB1p1Nvr06QNAhQoVaNSokdxKXogiEhQUxPLly5k/fz5NmjTh6tWrnD17FgALCwsiIiJwcnLi1KlTDBgwAAsLC8aOHUv37t1JSEhg69at7NixA0DjpMCT6OnpsWjRIipUqMBff/3FkCFDGDt2LF9++SWNGjUiMTGRqlWrsm7dOho1aqQ+S7tr1y5++uknjh8/zvr165/ZTlZWFllZWernaWlpABjrqdDXV2mdp5LKWE+l8a8onOfNW05OjlblAwICSEhIYPfu3QW+Ni0tDV9fX9zd3Zk4caLW9b8MeTG9irG9yiRvupG86aY48qZNWwqVSvVcn1b3798nOztbY5vcFEwI3d29exdbW1uWLFlC//79n1k+PDycqKgofv/9d+DFrNn4+eefGTRoENevXwfg9u3blClTRmNE48aNG3h6erJ69WqaNWtGREQEgYGBT12zERISUuBFJCIjIzE1NdU5XiFeNV9//TVxcXHMnDkTe3v7fPvv3btHSEgIxsbGTJo0CSMjo2KIUgghdJOZmUnPnj3V00CfRqcJopmZmYwdO5Yff/yRGzdu5Nufm5urS7VCCODMmTNkZWXRunXrAvevXbuWRYsWkZSURHp6Og8ePHjuDv6OHTsICwvj7NmzpKWl8eDBA+7fv09mZuYTOwEDBgygZ8+eNGvWrNDtBAUFMXLkSPXztLQ0nJ2dadmyJTY2Ns91DCVJTk4OMTExtG3bVkaYtfAy8qZSqQgMDOT48ePs3bsXNze3fGXS0tLo0KED9vb2/PLLL690R1vea7qRvOlG8qab4shb3syEwtCpszFmzBh2797N0qVL6dWrF1988QV///03y5YtY9asWbpUKYT4fyYmJk/cd+jQIfz8/AgNDcXHxwcrKyuioqKYO3euzu1dvHiRjh07MnjwYGbMmIG1tTX79++nX79+ZGdnP/GL0K5du/jll18IDw8HHn7JUiqVGBgY8PXXX/PJJ5/ke42xsTHGxsb5thsaGsoHiw4kb7opyrwNGTKEyMhINm3ahLW1tfqEnJWVFSYmJuqORmZmJmvWrOHevXvcu3cPAFtbW/T19Yskrucl7zXdSN50I3nTzcvMmzbt6NTZ+PXXX1m1ahUtWrSgb9++NG3alMqVK+Pi4sKaNWvw8/PTpVohBODm5oaJiQk7d+7MN43q4MGDuLi4MHHiRPW2S5cuaZQxMjLSanTx6NGjKJVK5s6di57ew1vv/Pjjj8983aFDhzTa2bRpE7Nnz+bgwYOULVu20O0L8SZZunQpgHq6YZ68CzX88ccfxMXFAVC5cmWNMsnJybi6ur6MMIUQ4qXRqbNx8+ZNKlasCDxcn3Hz5k0AmjRpwuDBg19cdEKUQKVKlWLcuHGMHTsWIyMjGjduzH///ceff/6Jm5sbKSkpREVFUb9+fTZv3syGDRs0Xu/6f+3deVxU1f/48dewDTsIgYAimCuKIK6RG+aGpLmVppZQprll7ksq4hZqLqC5pH6ETNMW19RINEFFwyRx31ARK9dSEUlkub8//DHfJhZhBEbl/Xw85qFz77nnvO8bdOY959w77u5cvnyZxMREKleujJWVVb6zCbmqV69OZmYmixcvpnPnzsTFxbF8+fInxunh4aH1/MiRIxgYGBR41x0hyoMnXQbp5+f3xDZCCPEi0ekbxF9++WUuX74MQO3atTWfgv7www/Y2tqWWHBClFdTpkxh9OjRBAcH4+HhQa9evbh58yZvvPEGI0eOZNiwYdSvX5+DBw8yZcoUrWN79OiBv78/rVu3xsHBgfXr1xc6lre3NwsWLGDOnDl4enqybt06QkNDS/P0hBBCCFFO6HQ3qoULF2JoaMjw4cPZvXs3nTt3RlEUMjMzWbBgAR9//HFpxCqEeMGkpqZiY2PD7du35QLxYsjMzGTnzp0EBATIuuZikLwVn+RMN5I33UjedKOPvOW+fpfa3ahGjhyp+Xvbtm05e/YsCQkJVK9eHS8vL126FEIIIYQQQrxgdCo2/u3hw4e4ubnh5uZWEvEIIUrYunXr+PDDD/Pd5+bmxqlTp8o4IiGEEEKUFzoVG9nZ2Xz66acsX76cGzducP78eV5++WWmTJmCu7s7/fv3L+k4hRA6euONN2jatGm++2SaWgghhBClSadiY9asWXz55ZfMnTuXAQMGaLZ7enoSFhYmxYYQzxArKyusrKz0HYYQQgghyiGd7ka1Zs0aVqxYQd++fbW+gMjb25uzZ8+WWHBCCCGEEEKI55dOxcYff/yR58uIAHJycsjMzHzqoIQQcP36ddq1a4eFhYXcUlqIZ0RoaCiNGzfGysoKR0dHunbtyrlz57TarFixAj8/P6ytrVGpVNy9e1c/wQohxDNAp2KjTp067N+/P8/277//Hh8fn6cOSogXTUhICPXr1y/WMQsXLuTatWskJiZy/vz5EonDz8+PESNGlEhfAB9++CHVqlXDzMwMBwcHunTpIrOb4oUWGxvL0KFD+eWXX4iOjiYzM5P27dvz4MEDTZv09HT8/f355JNP9BipEEI8G3S6ZiM4OJjAwED++OMPcnJy2LRpE+fOnWPNmjVs3769pGMUoly6ePEiDRs2pEaNGvoOJY9Hjx5hYmJCw4YN6du3L1WqVOHvv/8mJCSE9u3bc/nyZa0llkK8KKKiorSeR0ZG4ujoSEJCAi1btgTQFPQxMTFlHJ0QQjx7ijWzcenSJRRFoUuXLvzwww/s3r0bCwsLgoODOXPmDD/88APt2rUrrViF0KuoqCiaN2+Ora0t9vb2dOrUiYsXL2r2//777/Tu3Rs7OzssLCxo1KgR8fHxREZGMm3aNI4dO4ZKpUKlUhEZGVnoWO7u7mzcuJE1a9agUqkICgoCYMGCBdSrVw8LCwtcXV0ZMmQIaWlpWsfGxcXh5+eHubk5FSpUoEOHDty5c4egoCBiY2MJDw/XxJGcnAw8/rS2SZMmqNVqnJ2dmTBhAllZWZo+/fz8GDZsGCNGjOCll16iQ4cOAAwcOJCWLVvi7u5OgwYNmDlzJlevXtX0K8SL7t69ewDY2dnpORIhhHg2FWtmo0aNGly7dg1HR0datGiBnZ0dJ06coGLFiqUVnxDPjAcPHjBq1Ci8vLxIS0sjODiYbt26kZiYSHp6Oq1ataJSpUps27YNJycnfvvtN3JycujVqxcnT54kKiqK3bt3A2BjY1PoWL/++iv9+vXD2tqa8PBwzMzMADAwMGDRokVUrVqVS5cuMWTIEMaNG8fSpUsBSExMpE2bNrz//vuEh4djZGTE3r17yc7OJjw8nPPnz+Pp6cn06dMBcHBw4I8//iAgIICgoCDWrFnD2bNnGTBgAKampoSEhGhi+vLLLxk8eDBxcXEF5iciIoKqVavi6uqab5uMjAwyMjI0z1NTUwFoOWc3WcYWRfgpCAC1gcKMRtBwehQZOSp9h/PceFLeToZ0KFZ/OTk5fPzxx7z66qvUqlUrzzWLuQV7Zmbmc3s9Y27cz2v8+iJ5043kTTf6yFtxxlIpiqIUtbGBgQHXr1/H0dERAGtraxITE3n55ZeLH6UQz7nbt2/j4ODAiRMnOHjwIGPGjCE5OTnfTzhDQkLYsmULiYmJRe6/a9eu2NraFjoL8v333zNo0CBu374NQJ8+fUhJSeHAgQP5tvfz86N+/fqEhYVptk2aNImNGzdy5swZVKrHb8CWLl3K+PHjuXfvHgYGBvj5+ZGamspvv/2Wp8+lS5cybtw4Hjx4QK1atdixYwfVqlXLd/yQkBCmTZuWZ/vXX3+Nubl5gecpxLNo+fLlJCQkEBoayksvvZRn/4kTJ5gyZQpr167F0tJSDxEKIUTpSE9Pp0+fPty7dw9ra+tC2z7VN4gXo04R4rl34cIFgoODiY+P5/bt2+Tk5ACQkpJCYmIiPj4+pb6UYvfu3YSGhnL27FlSU1PJysri4cOHpKenY25uTmJiIm+99Vax+jxz5gy+vr6aQgOgWbNmpKWl8fvvv1OlShUAGjZsmO/xffv2pV27dly7do158+bRs2dP4uLiMDU1zdN24sSJjBo1SvM8NTUVV1dXZh41IMtYrvEoqsef0Ocw5YiBzGwUw5PyVpyZjY8//piTJ09y4MABqlatmm8bC4vHs3Xt27d/bu8ol5mZSXR0NO3atZMvAS0GyZtuJG+60UfeclcmFEWxio3cdd7/3SZEedC5c2fc3NxYuXIlLi4u5OTk4OnpyaNHjzTLnEpTcnIynTp1YvDgwcyaNQs7OzsOHDhA//79efToEebm5qUaR+4bp/+ysbHBxsaGGjVq8Morr1ChQgU2b95M796987RVq9Wo1eo82/eNb4u9vX2Jx/yiyszMZOfOnSQE+8sLcjGURN4UReGjjz5i69atxMTEFHoDByOjxy+xxsbGz/3P6UU4B32QvOlG8qabssxbccYpVrGhKApBQUGaNwsPHz5k0KBBed6EbNq0qTjdCvHM++uvvzh37hwrV66kRYsWAFpLlby8vFi1ahV///13vrMbJiYmZGdnP1UMCQkJ5OTkMH/+fAwMHt/b4dtvv9Vq4+XlxZ49e/JdqlRQHB4eHmzcuBFFUTQfHsTFxWFlZUXlypWLFaOiKCiKonVdhhAvkqFDh/L111+zdetWrKysuH79OvC46M4t9q9fv87169dJSkoCHi+nsrKyokqVKnIhuRCi3CnW3agCAwNxdHTUfJL5zjvv4OLionme+xDiRVOhQgXs7e1ZsWIFSUlJ/Pzzz1rLgXr37o2TkxNdu3YlLi6OS5cusXHjRg4dOgQ8vrvU5cuXSUxM5Pbt2zq9Ga9evTqZmZksXryYS5cu8dVXX7F8+XKtNhMnTuTXX39lyJAhHD9+nLNnz7Js2TLNNR3u7u7Ex8eTnJysWQo2ZMgQrl69ykcffcTZs2fZunUrU6dOZdSoUZqiJj+XLl0iNDSUhIQEUlJSOHjwIG+99RZmZmYEBAQU+/yEeB4sW7aMe/fu4efnh7Ozs+bxzTffaNosX74cHx8fBgwYAEDLli3x8fFh27Zt+gpbCCH0plgzGxEREaUVhxDPNAMDAzZs2MDw4cPx9PSkVq1aLFq0CD8/P+DxjMGuXbsYPXo0AQEBZGVlUadOHZYsWQJAjx492LRpE61bt+bu3btERERobmdbVN7e3ixYsIA5c+YwceJEWrZsSWhoKP369dO0qVmzJrt27eKTTz6hSZMmmJmZ0bRpU82SpjFjxhAYGEidOnX4559/uHz5Mu7u7uzcuZOxY8fi7e2NnZ0d/fv3Z/LkyYXGY2pqyv79+wkLC+POnTtUrFiRli1bcvDgQc1NJIR40RTlWsWQkBCtO7kJIUR5Vqy7UQkhRElKTU3FxsaG27dvyzUbxZB77UFAQICsay4GyVvxSc50I3nTjeRNN/rIW+7rd1HuRlWsZVRCCCGEEEIIUVRSbAihB+vWrcPS0jLfR926dfUdnhBCCCFEiXiq79kQQujmjTfeoGnTpvnuk6ljIYQQQrwopNgQQg+srKywsrLSdxhCCCGEEKVKllEJIYQQQgghSoUUG0IIIcT/FxoaSuPGjbGyssLR0ZGuXbty7tw5rTYPHz5k6NCh2NvbY2lpSY8ePbhx44aeIhZCiGebFBtCPKOuX79Ou3btsLCwwNbWVt/hCFEuxMbGMnToUH755Reio6PJzMykffv2PHjwQNNm5MiR/PDDD3z33XfExsby559/0r17dz1GLYQQzy4pNoQoAyEhIdSvX79YxyxcuJBr166RmJjI+fPnSyQOPz8/RowYUSJ95fanUqm0HoMGDSqx/oUoa1FRUQQFBVG3bl28vb2JjIwkJSWFhIQEAO7du8f//vc/FixYwGuvvUbDhg2JiIjg4MGD/PLLL3qOXgghnj1ygbgQz6iLFy/SsGFDatSooe9Q8nj06BEmJiYADBgwgOnTp2v2mZub6yssIUrcvXv3ALCzswMgISGBzMxM2rZtq2lTu3ZtqlSpwqFDh3jllVf0EqcQQjyrpNgQooiioqKYOXMmJ0+exNDQEF9fX8LDw6lWrRoAv//+O2PHjuWnn34iIyMDDw8PlixZwpkzZ5g2bRoAKpUKgIiICIKCggocy93dnStXrgCwZs0aAgMDiYyMZMGCBURERHDp0iXs7Ozo3Lkzc+fOxdLSUnNsXFwckyZN4vDhw6jVapo0acKGDRsYOXIksbGxxMbGEh4eDsDly5dxd3cnNjaWsWPHcuzYMezs7AgMDGTmzJkYGT3+L8LPzw9PT0+MjIxYu3Yt9erVY+/evcDj4sLJyempcts0dA9ZRhZP1Ud5ojZUmNsEPEN+IiNbpe9wnhu5eSuqnJwcRowYQbNmzfD09AQeL280MTHJs7SxYsWKXL9+vQSjFUKIF4MUG0IU0YMHDxg1ahReXl6kpaURHBxMt27dSExMJD09nVatWlGpUiW2bduGk5MTv/32Gzk5OfTq1YuTJ08SFRXF7t27AbCxsSl0rF9//ZV+/fphbW1NeHg4ZmZmABgYGLBo0SKqVq3KpUuXGDJkCOPGjWPp0qUAJCYm0qZNG95//33Cw8MxMjJi7969ZGdnEx4ezvnz5/H09NTMRDg4OPDHH38QEBBAUFAQa9as4ezZswwYMABTU1NCQkI0MX355ZcMHjyYuLg4rVjXrVvH2rVrcXJyonPnzkyZMqXA2Y2MjAwyMjI0z1NTUwFQGygYGirF+GmUb2oDRetPUTS5+crMzCxS+2HDhnHy5En27t2rOSYrKyvfPhRFITs7u8h9Py9yz+dFO6/SJnnTjeRNN/rIW3HGUimKIq9WQujg9u3bODg4cOLECQ4ePMiYMWNITk7WLLf4t5CQELZs2UJiYmKR++/atSu2trZERkYW2Ob7779n0KBB3L59G4A+ffqQkpLCgQMH8m3v5+dH/fr1CQsL02ybNGkSGzdu5MyZM5qZl6VLlzJ+/Hju3buHgYEBfn5+pKam8ttvv2n1t2LFCtzc3HBxceH48eOMHz+eJk2asGnTpnzHDwkJ0czy/NvXX38ty6/EM2XFihXEx8fz6aefUrFiRc3248ePExwczNq1a7VmFAcMGEDnzp1544039BGuEEKUqfT0dPr06cO9e/ewtrYutK3MbAhRRBcuXCA4OJj4+Hhu375NTk4OACkpKSQmJuLj45NvoVGSdu/eTWhoKGfPniU1NZWsrCwePnxIeno65ubmJCYm8tZbbxWrzzNnzuDr66spNACaNWtGWloav//+O1WqVAGgYcOGeY4dOHCg5u/16tXD2dmZNm3acPHiRc3ysn+bOHEio0aN0jxPTU3F1dWVmUcNyDI2LFbc5ZnaQGFGoxymHDEgI0eWURVVbt7atWuHsbFxvm0URWHEiBEkJiayb9++PNdMNWvWjBkzZmBkZERAQAAA586d49atW7z33ns0bdq01M+jLGVmZhIdHV1ozkRekjfdSN50o4+85a5MKAopNoQoos6dO+Pm5sbKlStxcXEhJycHT09PHj16pFnmVJqSk5Pp1KkTgwcPZtasWdjZ2XHgwAH69+/Po0ePMDc3L9U4LCyefE1F7hutpKSkfIsNtVqNWq3Os33f+LbY29s/fZDlRGZmJjt37iQh2F9ekIshN2/GxsYF5m3IkCF8/fXXbN26FTs7O/766y/g8dJHMzMzXnrpJfr378+4ceNwdHTE2tqajz76CF9fX5o3b16Wp1OmCsuZKJjkTTeSN92UZd6KM47c+laIIvjrr784d+4ckydPpk2bNnh4eHDnzh3Nfi8vLxITE/n777/zPd7ExITs7OyniiEhIYGcnBzmz5/PK6+8Qs2aNfnzzz+12nh5ebFnz54C+8gvDg8PDw4dOsS/V1TGxcVhZWVF5cqVixVj7jIxZ2fnYh0nxLNi2bJl3Lt3Dz8/P5ydnTWPb775RtNm4cKFdOrUiR49etCyZUucnJwKXDoohBDlnRQbQhRBhQoVsLe3Z8WKFSQlJfHzzz9rLQfq3bs3Tk5OdO3albi4OC5dusTGjRs5dOgQ8PjuUpcvXyYxMZHbt29rXSRdVNWrVyczM5PFixdz6dIlvvrqK5YvX67VZuLEifz6668MGTKE48ePc/bsWZYtW6a5psPd3Z34+HiSk5M1S8GGDBnC1atX+eijjzh79ixbt25l6tSpjBo1CgODgv+LuHjxIjNmzCAhIYHk5GS2bdtGv379aNmyJV5eXsU+PyGeBYqi5Pv4993jTE1NWbJkCX///TcPHjxg06ZNT31HNiGEeFFJsSFEERgYGLBhwwYSEhLw9PRk5MiRfPbZZ5r9JiYm7Nq1C0dHRwICAqhXrx6zZ8/G0PDxdQg9evTA39+f1q1b4+DgwPr164sdg7e3NwsWLGDOnDl4enqybt06QkNDtdrUrFmTXbt2cezYMZo0aYKvry9bt27V3MJ2zJgxGBoaUqdOHRwcHEhJSaFSpUrs3LmTw4cP4+3tzaBBg+jfvz+TJ08uNB4TExN2795N+/btqV27NqNHj6ZHjx788MMPxT43IYQQQryY5G5UQgi9SU1NxcbGhtu3b8s1G8WQe+1BQECArGsuBslb8UnOdCN5043kTTf6yFvu63dR7kYlMxtCCCGEEEKIUiHFhhB6sG7dOiwtLfN91K1bV9/hCSGEEEKUCLn1rRB68MYbbxR4P36ZOhZCCCHEi0KKDSH0wMrKCisrK32HIYQQQghRqmQZlRBCCCGEEKJUSLEhyh0/Pz9GjBih7zCeOTExMahUKu7evavvUIQoVfv376dz5864uLigUqnYsmWL1v4bN24QFBSEi4sL5ubm+Pv7c+HCBf0EK4QQzzkpNoR4AUgBJUTRPXjwAG9vb5YsWZJnn6IodO3alUuXLrF161aOHj2Km5sbbdu25cGDB3qIVgghnm9yzYYQQohyxd/fn86dO+e778KFC/zyyy+cPHlSc2e4ZcuW4eTkxPr16/nggw/KMlQhhHjuycyGKNfu3LlDv379qFChAubm5nTs2FGzXEJRFBwcHPj+++817evXr4+zs7Pm+YEDB1Cr1aSnpz9xrLt37/Lhhx9SsWJFTE1N8fT0ZPv27Zr9GzdupG7duqjVatzd3Zk/f77W8UuXLqVGjRqYmppSsWJF3nzzTQCCgoKIjY0lPDwclUqFSqUiOTn5ifHs3LmTmjVrYmZmRuvWrfM95sCBA7Ro0QIzMzNcXV0ZPny45tPdTz75JN87anl7ezN9+vQnji/EsygjIwMAU1NTzTYDAwPUajUHDhzQV1hCCPHckpkNUa4FBQVx4cIFtm3bhrW1NePHjycgIIDTp09jbGxMy5YtiYmJ4c033+TOnTucOXMGMzMzzp49S+3atYmNjaVx48aYm5sXOk5OTg4dO3bk/v37rF27lmrVqnH69GkMDQ0BSEhIoGfPnoSEhNCrVy8OHjzIkCFDsLe3JygoiCNHjjB8+HC++uorXn31Vf7++2/2798PQHh4OOfPn8fT01PzJt/BwaHQeK5evUr37t0ZOnQoAwcO5MiRI4wePVqrzcWLF/H392fmzJmsXr2aW7duMWzYMIYNG0ZERAR9+/YlNDSUixcvUq1aNQBOnTrF8ePH2bhxY7F+Dk1D95BlZFGsY8oztaHC3CbgGfITGdkqfYfzTEme/fpTHV+7dm2qVKnCxIkT+eKLL7CwsGDhwoX8/vvvXLt2rYSiFEKI8kOKDVFu5RYZcXFxvPrqq8DjL9tzdXVly5YtvPXWW/j5+fHFF18AsG/fPnx8fHByciImJobatWsTExNDq1atnjjW7t27OXz4MGfOnKFmzZoAvPzyy5r9CxYsoE2bNkyZMgWAmjVrcvr0aT777DOCgoJISUnBwsKCTp06YWVlhZubGz4+PgDY2NhgYmKCubk5Tk5ORTr3ZcuWUa1aNc3sSa1atThx4gRz5szRtAkNDaVv376aa0Fq1KjBokWLaNWqFcuWLaNu3bp4e3vz9ddfa+Jet24dTZs2pXr16vmOm5GRofnkGCA1NRUAtYGCoaFSpNjF43z9+0/xfzIzM5+4779tsrKytLZ9++23DBw4EDs7OwwNDWnTpg3+/v4oilJo/y+ignImCid5043kTTf6yFtxxpJiQ5RbZ86cwcjISGspkL29PbVq1eLMmTMAtGrVio8//phbt24RGxuLn5+fptjo378/Bw8eZNy4cU8cKzExkcqVK2sKjfxi6dKli9a2Zs2aERYWRnZ2Nu3atcPNzY2XX34Zf39//P396dat2xNnVAo79/8ugfL19dV6fuzYMY4fP866des02xRFIScnh8uXL+Ph4UHfvn1ZvXo1U6ZMQVEU1q9fz6hRowocNzQ0lGnTpuXZPtknB3PzbJ3OpTyb0ShH3yE8c3bu3PnENtHR0VrPExIS8nyZ5vTp03nw4AFZWVnY2NgwduxYqlevXqT+X0T/zZkoGsmbbiRvuinLvBVl+XguKTaEKES9evWws7MjNjaW2NhYZs2ahZOTE3PmzOHXX38lMzNTMytSGDMzs6eKw8rKit9++42YmBh27dpFcHAwISEh/Prrr9ja2j5V3wVJS0vjww8/ZPjw4Xn2ValSBYDevXszfvx4fvvtN/755x+uXr1Kr169Cuxz4sSJWsVIamoqrq6utG7dGnt7+5I/iRdUZmYm0dHRtGvXTr5xvhgKylvDhg0JCAgo8LgLFy5w8eJFwsLCaNeuXVmE+syQ3zXdSN50I3nTjT7ylrsyoSik2BDlloeHB1lZWcTHx2sKhr/++otz585Rp04dAFQqFS1atGDr1q2cOnWK5s2bY25uTkZGBl988QWNGjXCwuLJ1xp4eXnx+++/c/78+XxnNzw8PIiLi9PaFhcXR82aNTXXdRgZGdG2bVvatm3L1KlTsbW15eeff6Z79+6YmJiQnV30mQEPDw+2bdumte2XX37Ret6gQQNOnz5d4JIogMqVK9OqVSvWrVvHP//8Q7t27XB0dCywvVqtRq1W59lubGwsLyw6kLzpJiMjg/Pnz2ueX716lVOnTmFnZ0eVKlX47rvvcHBwoEqVKpw4cYKPP/6Yrl27FlqQvOjkd003kjfdSN50U5Z5K844cjcqUW7VqFGDLl26MGDAAA4cOMCxY8d45513qFSpktaSJj8/P9avX0/9+vWxtLTEwMCAli1bsm7duiJdrwGPl2O1bNmSHj16EB0dzeXLl/nxxx+JiooCYPTo0ezZs4cZM2Zw/vx5vvzySz7//HPGjBkDwPbt21m0aBGJiYlcuXKFNWvWkJOTQ61atQBwd3cnPj6e5ORkbt++TU5O4ctrBg0axIULFxg7diznzp3j66+/JjIyUqvN+PHjOXjwIMOGDSMxMZELFy6wdetWhg0bptWub9++bNiwge+++46+ffsWKR9C6FNCQgI+Pj6a655GjRqFj48PwcHBAFy7do13332X2rVrM3z4cN59913Wr1+vz5CFEOK5JcWGKNciIiJo2LAhnTp1wtfXF0VR2Llzp1bF3qpVK7Kzs/Hz89Ns8/Pzy7PtSTZu3Ejjxo3p3bs3derUYdy4cZrZiAYNGvDtt9+yYcMGPD09CQ4OZvr06QQFBQFga2vLpk2beO211/Dw8GD58uWsX79e8z0AY8aMwdDQkDp16uDg4EBKSkqhsVSpUoWNGzeyZcsWvL29Wb58OZ9++qlWGy8vL2JjYzl//jwtWrTQvBlzcXHRavfmm2/y119/kZ6eTteuXYucDyH0pVWrViiKkueRW3APHz6cq1ev8ujRI65cucKMGTMwMTHRb9BCCPGcUimKIrczEULoRWpqKjY2Nty+fVuu2SiGzMxMdu7cSUBAgCw1KAbJW/FJznQjedON5E03+shb7uv3vXv3sLa2LrStzGwIIYQQQgghSoUUG0KUgHXr1mFpaZnvI3epU1kaNGhQgfEMGjSozOMRQgghRPkkd6MSogS88cYbeb63Ipc+poKnT5+uubj8v5403SmEEEIIUVKk2BCiBFhZWWFlZaXvMDQcHR0LvQWtEEIIIURZkGVUQgghhBBCiFIhxYYQQogXyr59++jcuTMuLi6oVCq2bNmitT8tLY1hw4ZRuXJlzMzMqFOnDsuXL9dPsEII8YKTYkM8lZCQEOrXr695HhQUJN+18Jz6789SiOfVgwcP8Pb2ZsmSJfnuHzt2LFFRUaxdu5YzZ84wYsQIhg0bxrZt28o4UiGEePFJsSHEc8Dd3Z2wsLAS6y+/T3vHjBnDnj17SmwMIfSlY8eOzJw5k27duuW7/9ChQwQGBuLn54e7uzsDBw7E29ubw4cPl3GkQgjx4pNiQ4gXRHZ2Njk5OTofb2lpKV+sJ8oFX19ftm3bxh9//IGiKOzdu5fz58/Tvn17fYcmhBAvHLkb1Qvm+++/Z9q0aSQlJWFubo6Pjw9bt25l6NCh3L17lyZNmhAeHk5GRgajRo3ik08+YeLEifzvf//D3NycGTNm8N5772n6Gz9+PJs3b+b333/HycmJvn37EhwcXOTbuebk5DBv3jxWrFjB1atXqVixIh9++CGTJk0qUv8hISFs2bKFwYMHM3PmTP766y86derEypUrsbGxKVIMq1evZv78+SQlJWFnZ0ePHj34/PPPAUhJSeGjjz5iz549GBgY4O/vz+LFi6lYsaLW+KNHj2bKlCncuXOHjh07snLlSs3dp550jlevXmX06NHs2rULAwMDWrRoQXh4OO7u7sDjpWd3796lefPmzJ8/n0ePHvH2228TFhaGsbExfn5+XLlyhZEjRzJy5EgAFEUhMjKSESNGsGbNGiZMmMD58+dJSkri1q1bfPLJJxw9epTMzEzq16/PwoULadCgAYBm3NxPfd3c3EhOTtaca2Jioua8Zs6cyYoVK7h16xYeHh7Mnj0bf39/AJKTk6latSobN25k8eLFxMfHU6NGDZYvX46vr2+Rfja5mobuIcvIoljHlGdqQ4W5TcAz5CcyslX6DqdMJc9+/an7CAsLY+jQoVSuXBkjIyMMDAxYuXIlLVu2LIEIhRBC/JsUGy+Qa9eu0bt3b+bOnUu3bt24f/8++/fvR1EUAH7++WcqV67Mvn37iIuLo3///hw8eJCWLVsSHx/PN998w4cffki7du2oXLky8PiWrpGRkbi4uHDixAkGDBiAlZUV48aNK1JMEydOZOXKlSxcuJDmzZtz7do1zp49q9lflP6TkpL49ttv+eGHH0hNTaV///4MGTKEdevWPXH8ZcuWMWrUKGbPnk3Hjh25d+8ecXFxwOM30126dMHS0pLY2FiysrIYOnQovXr1IiYmRtPHxYsX2bJlC9u3b+fOnTv07NmT2bNnM2vWrCeeY2ZmJh06dMDX15f9+/djZGTEzJkz8ff35/jx45iYmACwd+9enJ2d2bt3L0lJSfTq1Yv69eszYMAANm3ahLe3NwMHDmTAgAFa55eens6cOXNYtWoV9vb2ODo6cunSJQIDA1m8eDGKojB//nwCAgK4cOECVlZW/Prrrzg6OhIREYG/vz+Ghob55i48PJz58+fzxRdf4OPjw+rVq3njjTc4deoUNWrU0LSbNGkS8+bNo0aNGkyaNInevXuTlJSEkVHe/14yMjLIyMjQPE9NTQVAbaBgaKg88ecpHlMbKFp/lieZmZnFPiYrK4vMzEzNsYsWLeLQoUNs2rSJKlWqcODAAYYOHYqjoyNt2rQp6ZCfa7k50yXv5ZnkTTeSN93oI2/FGUul5L4TFc+93377jYYNG5KcnIybm5vWvqCgIGJiYrh06RIGBo9Xz9WuXRtHR0f27dsHPF6GY2Njw6pVq3j77bfzHWPevHls2LCBI0eOAOT5NDz3U/otW7Zw//59HBwc+Pzzz/nggw+KdA759T9z5kyuXLlCpUqVAIiKiuL111/njz/+wMnJqdD+KlWqxHvvvcfMmTPz7IuOjqZjx45cvnwZV1dXAE6fPk3dunU5fPgwjRs3JiQkhM8++4zr169rZjLGjRvHvn37+OWXX554jmvXrmXmzJmcOXMGlerxJ9CPHj3C1taWLVu20L59e83P5uLFi5o3/j179sTAwIANGzYAj2cjRowYwYgRIzR9R0ZG8t5775GYmIi3t3eBOcjJycHW1pavv/6aTp06AY+v2di8ebPWxfz//VlWqlSJoUOH8sknn2jaNGnShMaNG7NkyRLNzMaqVavo37+/Vv7OnDlD7dq188QSEhLCtGnT8mz/+uuvMTc3L/AchNBV165dmTBhAq+88grwuODt27cvEyZMoFGjRpp2n3/+OX/99RdTp07VV6hCCPHcSE9Pp0+fPty7d++JXxYsMxsvEG9vb9q0aUO9evXo0KED7du3580336RChQoA1K1bV1NoAFSsWBFPT0/Nc0NDQ+zt7bl586Zm2zfffMOiRYu4ePEiaWlpZGVlFfkbqM+cOUNGRkahnxQWpf8qVapoCg14vN46JyeHc+fOFVps3Lx5kz///LPA8c+cOYOrq6um0ACoU6cOtra2nDlzhsaNGwOP3+j/+wv7nJ2dNTl60jkeO3aMpKSkPF/49/DhQy5evKh5XrduXa0ZBmdnZ06cOFHgueUyMTHBy8tLa9uNGzeYPHkyMTEx3Lx5k+zsbNLT00lJSXlif7lSU1P5888/adasmdb2Zs2acezYMa1t/x7f2dkZeJz7/IqNiRMnMmrUKK1xXF1dmXnUgCzj/GdYRF5qA4UZjXKYcsSAjJzytYzqZEiHYh/TsGFDAgICyMzMZOvWrWRlZdGkSRPNkkCA7du3AxAQEFBisb4IMjMziY6Opl27dkVePiskb7qSvOlGH3nLXZlQFFJsvEAMDQ2Jjo7m4MGD7Nq1i8WLFzNp0iTi4+MB8vwCqlSqfLflXmR86NAh+vbty7Rp0+jQoQM2NjZs2LCB+fPnFykeMzOzQvc/bf9PO35RFZajJ42RlpZGw4YN813y5eDgUKQxCmNmZqaZMckVGBjIX3/9RXh4OG5ubqjVanx9fXn06NET+9PFv2PPjaWg2NVqNWq1Os/2fePbysXpxZCZmcnOnTtJCPaXF+R8pKWlkZSUpHl+9epVTp06hZWVFebm5rRs2ZKJEydiZWWFm5sbsbGxrF27lgULFkg+C2BsbCy50YHkTTeSN92UZd6KM47cjeoFo1KpaNasGdOmTePo0aOYmJiwefNmnfo6ePAgbm5uTJo0iUaNGlGjRg2uXLlS5ONr1KiBmZlZgbdTLWr/KSkp/Pnnn5rnv/zyCwYGBtSqVavQ8a2srHB3dy9wfA8PD65evcrVq1c1206fPs3du3epU6dOUU7xiefYoEEDLly4gKOjI9WrV9d6FPUCd3g8g5GdnV2ktnFxcQwfPpyAgADq1q2LWq3m9u3bWm2MjY0L7c/a2hoXFxfN9S3/7ruouRFCX44cOYKPjw8+Pj4AjBo1Ch8fH80SvrVr19K4cWP69u1LnTp1NNdgDRo0SJ9hCyHEC0lmNl4g8fHx7Nmzh/bt2+Po6Eh8fLzmLkLHjx8vdn81atQgJSWFDRs20LhxY3bs2FGswsXU1JTx48czbtw4TExMaNasGbdu3eLUqVP079+/yP2bmpoSGBjIvHnzSE1NZfjw4fTs2fOJ12vA42sEBg0ahKOjIx07duT+/fvExcXx0Ucf0bZtW+rVq0ffvn0JCwsjKyuLIUOG0KpVK6213E9zjn379uWzzz6jS5cuTJ8+ncqVK3PlyhU2bdrEuHHjNBfiP4m7uzv79u3j7bffRq1W89JLLxXYtkaNGnz11Vc0atSI1NRUxo4dm2cGJrcIa9asGWq1WrPU7t/Gjh3L1KlTqVatGvXr1yciIoLExMQiXZgvhD75+fmR3+WIuTNCTk5ORERE6CEyIYQof2Rm4wVibW3Nvn37CAgIoGbNmkyePJn58+fTsWNHnfp74403GDlyJMOGDaN+/focPHiQKVOmFKuPKVOmMHr0aIKDg/Hw8KBXr16a6x2K2n/16tXp3r07AQEBtG/fHi8vL5YuXVqk8QMDAwkLC2Pp0qXUrVuXTp06ceHCBeDxLNDWrVupUKECLVu2pG3btrz88st88803JXaO5ubm7Nu3jypVqtC9e3c8PDzo378/Dx8+LPK1LwDTp08nOTmZatWqaS2/ys///vc/7ty5Q4MGDXj33XcZPnw4jo6OWm3mz59PdHQ0rq6umk9//2v48OGMGjWK0aNHU69ePaKioti2bZvWnaiEEEIIIQojd6MSz7T/3iFJvFhSU1OxsbHh9u3bcs1GMeR+Qh8QECDrmotB8lZ8kjPdSN50I3nTjT7ylvv6XZS7UcnMhhBCCCGEEKJUSLEhnmuWlpYFPvbv36/v8IQQQgghyjW5QFw800JCQggJCSlwf2HLq/793RxCCCGEEKLsSbEhnmvVq1fXdwhCCCGEEKIAsoxKCCGEEEIIUSqk2BBCCPFC2bdvH507d8bFxQWVSsWWLVu09qelpTFs2DAqV66MmZkZderUYfny5foJVgghXnBSbAihg/zewLzoQkJCqF+/vr7DEOKJHjx4gLe3N0uWLMl3/9ixY4mKimLt2rWcOXOGESNGMGzYMLZt21bGkQohxItPig0hRB75FVNjxoxhz549+glIiGLo2LEjM2fOpFu3bvnuP3ToEIGBgfj5+eHu7s7AgQPx9vbm8OHDZRypEEK8+KTYEKKcyM7OJicnR+fjLS0t5Yv3xAvB19eXbdu28ccff6AoCnv37uX8+fO0b99e36EJIcQLR+5GJcqdFStWEBISwu+//46Bwf/V2126dMHe3p7Vq1ezbNky5s2bx9WrV6latSqTJ0/m3Xffzbe/mJgYWrduzZ07d7C1tQUe35LXx8eHy5cv4+7uTmRkJCNGjGDt2rWMHj2aq1evEhAQwJo1a/juu++YOnUq9+7d491332XhwoUYGhoCkJGRwaRJk1i/fj13797F09OTOXPm4Ofn98TzzB1zzZo1TJgwgfPnz5OUlMStW7f45JNPOHr0KJmZmdSvX5+FCxfSoEEDANzd3QE0nwq7ubmRnJyc59vcc3JymDlzJitWrODWrVt4eHgwe/Zs/P39i/0zaRq6hywji2IfV16pDRXmNgHPkJ/IyFbpO5wylTz79afuIywsjKFDh1K5cmWMjIwwMDBg5cqVtGzZsgQiFEII8W9SbIhy56233uKjjz5i7969tGnTBoC///6bqKgodu7cyebNm/n4448JCwujbdu2bN++nffee4/KlSvTunVrncdNT09n0aJFbNiwgfv379O9e3e6deuGra0tO3fu5NKlS/To0YNmzZrRq1cvAIYNG8bp06fZsGEDLi4ubN68GX9/f06cOEGNGjWKNOacOXNYtWoV9vb2ODo6cunSJQIDA1m8eDGKojB//nwCAgK4cOECVlZW/Prrrzg6OhIREYG/v7+m8Pmv8PBw5s+fzxdffIGPjw+rV6/mjTfe4NSpUwXGlpGRQUZGhuZ5amoqAGoDBUNDpbgpLbfUBorWn+VJZmZmsY/JysoiMzNTc+yiRYs4dOgQmzZtokqVKhw4cIChQ4fi6Oio+T9BPJabM13yXp5J3nQjedONPvJWnLGk2BDlToUKFejYsSNff/215o3F999/z0svvUTr1q1p0aIFQUFBDBkyBIBRo0bxyy+/MG/evKcqNjIzM1m2bBnVqlUD4M033+Srr77ixo0bWFpaUqdOHVq3bs3evXvp1asXKSkpREREkJKSgouLC/D4uomoqCgiIiL49NNPizTm0qVL8fb21mx77bXXtNqsWLECW1tbYmNj6dSpEw4ODgDY2tri5ORUYN/z5s1j/PjxvP322wDMmTOHvXv3EhYWVuCFuaGhoUybNi3P9sk+OZibZz/xfIS2GY10Xxb3vNq5c2exj0lISMDY2Bh4XPBOnTqVCRMmYGBgwO+//467uzuvvPIKn3zyCVOnTi3pkF8I0dHR+g7huSR5043kTTdlmbf09PQit5ViQ5RLffv2ZcCAASxduhS1Ws26det4++23MTAw4MyZMwwcOFCrfbNmzQgPD3+qMc3NzTWFBkDFihVxd3fH0tJSa9vNmzcBOHHiBNnZ2dSsWVOrn4yMjCJfO2FiYoKXl5fWths3bjB58mRiYmK4efMm2dnZpKenk5KSUuRzSU1N5c8//6RZs2Za25s1a8axY8cKPG7ixImMGjVKqx9XV1dat24t14MUQ2ZmJtHR0bRr107zJloUrGHDhgQEBJCZmcnWrVvJysqiSZMmWkv+tm/fDkBAQIC+wnwmye+abiRvupG86UYfectdmVAUUmyIcqlz584oisKOHTto3Lgx+/fvZ+HChTr1lXvdh6L835KW/KYX//sfgEqlyndb7kXcaWlpGBoakpCQkGcp078LlMKYmZmhUmmv6Q8MDOSvv/4iPDwcNzc31Go1vr6+PHr0qEh9Pg21Wo1arc6z3djYWF5YdCB5y19aWhpJSUma51evXuXUqVNYWVlhbm5Oy5YtmThxIlZWVri5uREbG8vatWtZsGCB5LMA8rumG8mbbiRvuinLvBVnHCk2RLlkampK9+7dWbduHUlJSdSqVUtzgbSHhwdxcXEEBgZq2sfFxVGnTp18+8pddnTt2jUqVKgAoLmI+mn4+PiQnZ3NzZs3adGixVP3lysuLo6lS5dqPsG9evUqt2/f1mpjbGxMdnbBy5qsra1xcXEhLi6OVq1aafXdpEmTEotVCF0cOXJEa8lj7mzau+++S48ePVi7di3BwcH07duXv//+Gzc3N2bNmsWgQYP0FbIQQrywpNgQ5Vbfvn3p1KkTp06d4p133tFsHzt2LD179sTHx4e2bdvyww8/sGnTJnbv3p1vP9WrV8fV1ZWQkBBmzZrF+fPnmT9//lPHV7NmTfr27Uu/fv2YP38+Pj4+3Lp1iz179uDl5cXrr+t2V54aNWrw1Vdf0ahRI1JTUxk7dixmZmZabdzd3dmzZw/NmjVDrVZriqh/Gzt2LFOnTqVatWrUr1+fiIgIEhMTWbdunU5xCVFS/Pz8tGYac2VmZrJz506cnJyIiIjQQ2RCCFH+yPdsiHLrtddew87OjnPnztGnTx/N9q5duxIeHs68efOoW7cuX3zxBREREQXebtbY2Jj169dz9uxZvLy8mDNnDjNnziyRGCMiIujXrx+jR4+mVq1adO3alV9//ZUqVaro3Of//vc/7ty5Q4MGDXj33XcZPnw4jo6OWm3mz59PdHQ0rq6u+Pj45NvP8OHDGTVqFKNHj6ZevXpERUWxbdu2It0lSwghhBDlg0rJ7+MfIYQoA6mpqdjY2HD79m25QLwYcj+hDwgIkHXNxSB5Kz7JmW4kb7qRvOlGH3nLff2+d+8e1tbWhbaVmQ0hhBBCCCFEqZBiQ4jnVMeOHbG0tMz3UZTv4BBCCCGEKG1ygbgQz6lVq1bxzz//5LvPzs6ujKMRQgghhMhLig0hnlOVKlXSdwhCCCGEEIWSZVRCCCGEEEKIUiHFhhCixAQFBdG1a1d9hyHKgX379tG5c2dcXFxQqVRs2bJFa79KpcrzMDExYfPmzfoJWAghyikpNkS55+fnx4gRI/QdxjMrOTkZlUpVIt+KLkRJefDgAd7e3ixZsiTf/deuXdN6rF69GpVKha+vbxlHKoQQ5ZtcsyFECXj06BEmJib6DqNAmZmZcs9y8ULp2LEjHTt2LHC/k5OT1vOtW7fi5+eXZ7sQQojSJTMbolwLCgoiNjaW8PBwzVKLyMhIbG1ttdpt2bIFlUqleR4SEkL9+vVZtWoVVatWxdTUFHi8dGPVqlV069YNc3NzatSowbZt27T6io2NpUmTJqjVapydnZkwYQJZWVkArFixAhcXF3JycrSO6dKlC++//77m+datW2nQoAGmpqa8/PLLTJs2TdNHbhzLli3jjTfewMLCglmzZhWahzt37tC3b18cHBwwMzOjRo0aREREAFC1alUAfHx8UKlUmm9Sz87OZtSoUdja2mJvb8+4ceOQ7wgVz6IbN26wY8cOgoKC9B2KEEKUOzKzIcq18PBwzp8/j6enJ9OnTwdgx44dRTo2KSmJjRs3smnTJgwNDTXbp02bxty5c/nss89YvHgxffv25cqVK9jZ2fHHH38QEBBAUFAQa9as4ezZswwYMABTU1NCQkJ46623+Oijj9i7dy9t2rQB4O+//yYqKoqdO3cCsH//fvr168eiRYto0aIFFy9eZODAgQBMnTpVE0dISAizZ88mLCwMI6PC/6lPmTKF06dP8+OPP/LSSy+RlJSkua3u4cOHadKkCbt376Zu3bqaGZz58+cTGRnJ6tWr8fDwYP78+WzevJnXXnutwHEyMjLIyMjQPE9NTQWg5ZzdZBlbFCnvAtQGCjMaQcPpUWTkqJ58wHPkZEgHnY7LysoiMzMz332rV6/GysqKTp06sX///gLbibxycyU5Kx7Jm24kb7rRR96KM5YUG6Jcs7GxwcTEBHNzc83yin8XDoV59OgRa9aswcHBQWt7UFAQvXv3BuDTTz9l0aJFHD58GH9/f5YuXYqrqyuff/45KpWK2rVr8+effzJ+/HiCg4OpUKECHTt25Ouvv9YUG99//z0vvfQSrVu3Bh4XMxMmTCAwMBCAl19+mRkzZjBu3DitYqNPnz689957RTqXlJQUfHx8aNSoEQDu7u6afbnnZ29vr7UEJSwsjIkTJ9K9e3cAli9fzk8//VToOKGhoUybNi3P9sk+OZibZxcpVvF/ZjTKeXKj50xuUV1cCQkJBS4VXLJkCb6+vuzfvx+A6OhoneMrryRnupG86UbyppuyzFt6enqR20qxIYSO3Nzc8hQaAF5eXpq/W1hYYG1tzc2bNwE4c+YMvr6+WkuymjVrRlpaGr///jtVqlShb9++DBgwgKVLl6JWq1m3bh1vv/02BgaPVz0eO3aMuLg4raVR2dnZPHz4kPT0dMzNzQE0hUNRDB48mB49evDbb7/Rvn17unbtyquvvlpg+3v37nHt2jWaNm2q2WZkZESjRo0KXUo1ceJERo0apXmempqKq6srM48akGVctCJP5M5s5DDliIHMbPx/DRs2JCAgIM/2AwcO8Mcff7Blyxbq1KlDdHQ07dq1k2uYiigzM1NypgPJm24kb7rRR95yVyYUhRQbQvyHgYFBnjfM+U0XWljkv+znv//QVSpVnmswCtO5c2cURWHHjh00btyY/fv3s3DhQs3+tLQ0pk2bpplR+Lfca0cKiy8/HTt25MqVK+zcuZPo6GjatGnD0KFDmTdvXpH7KAq1Wo1arc6zfd/4ttjb25foWC+yzMxMdu7cSUKwv7wg/39GRkb55uLLL7+kYcOGNGrUSPPv2NjYWPJWTJIz3UjedCN5001Z5q0448gF4qLcMzExITv7/5bwODg4cP/+fR48eKDZVlK3ffXw8ODQoUNaxUxcXBxWVlZUrlwZeFwwdO/enXXr1rF+/Xpq1apFgwYNNO0bNGjAuXPnqF69ep5H7uyHLhwcHAgMDGTt2rWEhYWxYsUKAM01Gv/OkY2NDc7OzsTHx2u2ZWVlkZCQoPP4QhRHWloaiYmJmn+bly9fJjExkZSUFE2b1NRUvvvuOz744AM9RSmEEEJmNkS55+7uTnx8PMnJyVhaWtK0aVPMzc355JNPGD58OPHx8URGRpbIWEOGDCEsLIyPPvqIYcOGce7cOaZOncqoUaO0CoW+ffvSqVMnTp06xTvvvKPVR3BwMJ06daJKlSq8+eabGBgYcOzYMU6ePMnMmTN1iis4OJiGDRtSt25dMjIy2L59Ox4eHgA4OjpiZmZGVFQUlStXxtTUFBsbGz7++GNmz55NjRo1qF27NgsWLODu3bs650aI4jhy5IjmOiZAszwvMDBQ8+91w4YNKIqiuYZKCCFE2ZOZDVHujRkzBkNDQ+rUqYODgwOpqamsXbuWnTt3Uq9ePdavX09ISEiJjFWpUiV27tzJ4cOH8fb2ZtCgQfTv35/JkydrtXvttdews7Pj3Llz9OnTR2tfhw4d2L59O7t27aJx48a88sorLFy4EDc3N53jMjExYeLEiXh5edGyZUsMDQ3ZsGED8Hh5yqJFi/jiiy9wcXGhS5cuAIwePZp3332XwMBAfH19sbKyolu3bjrHIERx+Pn5oShKnse/PxgYOHAg6enp2NjY6C9QIYQo51SK3BhfCKEnqamp2NjYcPv2bblmoxhyr9kICAiQdc3FIHkrPsmZbiRvupG86UYfect9/b537x7W1taFtpWZDSGEEEIIIUSpkGJDiHJg0KBBWFpa5vsYNGiQvsMTQgghxAtKLhAXohyYPn06Y8aMyXffk6Y/hRBCCCF0JcWGEOWAo6Mjjo6O+g5DCCGEEOWMLKMSQgghhBBClAopNoQQQjxz9u3bR+fOnXFxcUGlUrFly5Y8bc6cOcMbb7yBjY0NFhYWNG7cWOtL/YQQQuifFBtClBB3d3fCwsL0HUaZiYmJQaVSyRf5iVLx4MEDvL29WbJkSb77L168SPPmzalduzYxMTEcP36cKVOmYGpqWsaRCiGEKIxcsyFEAZKTk6latSpHjx6lfv36ZTauu7s7I0aMYMSIEWU25pP4+flRv379clVMCf3q2LEjHTt2LHD/pEmTCAgIYO7cuZpt1apVK4vQhBBCFIPMbAjxlB49elTmY2ZnZ5OTk1Pm4wrxLMjJyWHHjh3UrFmTDh064OjoSNOmTfNdaiWEEEK/ZGZDlHs5OTnMmzePFStWcPXqVSpWrMiHH37I5MmTAfDx8QGgVatWxMTEEBQUxN27d2ncuDFLlixBrVZz+fLlIo+nKArTpk1j9erV3LhxA3t7e958800WLVqEn58fV65cYeTIkYwcOVLTPjIykhEjRrBmzRomTJjA+fPnSUpKwtnZmUmTJrF+/Xru3r2Lp6cnc+bMwc/PD0Bz3DfffMOIESO4evUqzZs3JyIiAmdnZwCysrIYNWoUa9aswdDQkA8++IDr169z7949tmzZQlBQELGxscTGxhIeHg6gdb4JCQmMHz+e06dPU79+fSIiIqhVq1axfgZNQ/eQZWRRrGPKM7Whwtwm4BnyExnZKn2HU2zJs19/quNv3rxJWloas2fPZubMmcyZM4eoqCi6d+/O3r17adWqVQlFKoQQ4mlJsSHKvYkTJ7Jy5UoWLlxI8+bNuXbtGmfPnuXw4cM0adKE3bt3U7duXUxMTDTH7NmzB2tra6Kjo4s93saNG1m4cCEbNmygbt26XL9+nWPHjgGwadMmvL29GThwIAMGDNA6Lj09nTlz5rBq1Srs7e1xdHRk2LBhnD59mg0bNuDi4sLmzZvx9/fnxIkT1KhRQ3PcvHnz+OqrrzAwMOCdd95hzJgxrFu3DoA5c+awbt06IiIi8PDwIDw8nC1bttC6dWsAwsPDOX/+PJ6enkyfPh0ABwcHkpOTgcfLWebPn4+DgwODBg3i/fffJy4uLt9zz8jIICMjQ/M8NTUVALWBgqGhUuxclldqA0Xrz+dNZmZmsY/JysrSHJf7O9S5c2eGDRsGQN26dTlw4ABLly7l1VdfLXRcXcYvryRnupG86Ubypht95K04Y0mxIcq1+/fvEx4ezueff05gYCDweN138+bNNW+m7e3tcXJy0jrOwsKCVatWaRUgRZWSkoKTkxNt27bF2NiYKlWq0KRJEwDs7OwwNDTEysoqz5iZmZksXboUb29vTT8RERGkpKTg4uICwJgxY4iKiiIiIoJPP/1Uc9zy5cs169mHDRumKRoAFi9ezMSJE+nWrRsAn3/+OTt37tTst7GxwcTEBHNz8zwxAcyaNUvzSfKECRN4/fXXefjwYb4X6oaGhjJt2rQ82yf75GBunl3EDIpcMxo9n0vp/v37VVQJCQkYGxsDj3+nDQ0NMTQ01OrLxMSE48ePP7F/XT4kKO8kZ7qRvOlG8qabssxbenp6kdtKsSHKtTNnzpCRkUGbNm2KdVy9evV0KjQA3nrrLcLCwnj55Zfx9/cnICCAzp07Y2RU+D9HExMTvLy8NM9PnDhBdnY2NWvW1GqXkZGBvb295rm5ubnWhbPOzs7cvHkTgHv37nHjxg1NsQNgaGhIw4YNi3xNyL9jyl2adfPmTapUqZKn7cSJExk1apTmeWpqKq6ursw8akCWsWGRxhOPZzRmNMphyhEDMnKev2VUJ0M6FPuYhg0bEhAQoHneuHFjAK1tq1evxtvbW2vbv2VmZhIdHU27du00hYsonORMN5I33UjedKOPvOWuTCgKKTZEuWZmZqbTcRYWul9f4Orqyrlz59i9ezfR0dEMGTKEzz77jNjY2EL/kzAzM0Ol+r83lmlpaRgaGpKQkIChofYbdUtLS83f/9unSqVCUUpu+c2/+8+Nr6BCRa1Wo1ar82zfN76tVoEkCpeZmcnOnTtJCPZ/YV+Q09LSSEpK0jy/evUqp06dws7OjipVqjBu3Dh69eqFn58frVu3Jioqih07dhATE/PEnBgbG7+weSstkjPdSN50I3nTTVnmrTjjyN2oRLlWo0YNzMzM2LNnT559uTMX2dklv7zHzMyMzp07s2jRImJiYjh06BAnTpzQjFuUMX18fMjOzubmzZtUr15d65Hfcqf82NjYULFiRX799VfNtuzsbH777TetdkWNSYiScuTIEXx8fDQ3aBg1ahQ+Pj4EBwcD0K1bN5YvX87cuXOpV68eq1atYuPGjTRv3lyfYQshhPgPmdkQ5ZqpqSnjx49n3LhxmJiY0KxZM27dusWpU6cIDAzEzMyMqKgoKleujKmpKTY2Nk89ZmRkJNnZ2TRt2hRzc3PWrl2LmZkZbm5uwOPv2di3bx9vv/02arWal156Kd9+atasSd++fenXrx/z58/Hx8eHW7dusWfPHry8vHj99aLd8eejjz4iNDSU6tWrU7t2bRYvXsydO3e0ZlHc3d2Jj48nOTkZS0tL7OzsnjoPQhTGz8/viTNw77//Pu+//34ZRSSEEEIXMrMhyr0pU6YwevRogoOD8fDwoFevXty8eRMjIyMWLVrEF198gYuLC126dCmR8WxtbVm5ciXNmjXDy8uL3bt388MPP2iWEU2fPp3k5GSqVauGg4NDoX1FRETQr18/Ro8eTa1atejatSu//vprvtdLFGT8+PH07t2bfv364evri6WlJR06dNC6wHvMmDEYGhpSp04dHBwcSElJ0e3khRBCCFGuqJSSXLwthHju5eTk4OHhQc+ePZkxY0apjpWamoqNjQ23b9+WazaKIfeajYCAAFnXXAySt+KTnOlG8qYbyZtu9JG33Nfve/fuYW1tXWhbWUYlRDl35coVdu3aRatWrcjIyODzzz/n8uXL9OnTR9+hCSGEEOI5J8uohChh69atw9LSMt9H3bp19R1eHgYGBkRGRtK4cWOaNWvGiRMn2L17Nx4eHvoOTQghhBDPOZnZEKKEvfHGGzRt2jTffc/itLCrq2uB3/gthBBCCPE0pNgQooRZWVlhZWWl7zCEEEIIIfROllEJIYQQQgghSoUUG0IIIcrcvn376Ny5My4uLqhUKrZs2aK1PygoCJVKpfXw9/fXT7BCCCF0JsWGEC+Q5ORkVCoViYmJT93Xpk2baN++Pfb29k/sU1EUOnbsmO+bRiHy8+DBA7y9vVmyZEmBbfz9/bl27ZrmsX79+jKMUAghREmQazaEKIcePXqEiYlJoW0ePHhA8+bN6dmzJwMGDCi0bVhYmNY3jgvxJB07dqRjx46FtlGr1Tg5OZVRREIIIUqDzGwI8ZyJioqiefPm2NraYm9vT6dOnbh48SIAVatWBcDHxweVSoWfnx/weElK165dmTVrFi4uLtSqVeuJ47z77rsEBwfTtm3bQtslJiYyf/58Vq9e/XQnJsR/xMTE4OjoSK1atRg8eDB//fWXvkMSQghRTDKzIcRz5sGDB4waNQovLy/S0tIIDg6mW7duJCYmcvjwYZo0acLu3bupW7eu1uzFnj17sLa2Jjo6usRiSU9Pp0+fPixZsuSpPoFuGrqHLCOLEovrRac2VJjbBDxDfiIj+9mbUUqe/fpT9+Hv70/37t2pWrUqFy9e5JNPPqFjx44cOnQIQ0PDEohSCCFEWZBiQ4jnTI8ePbSer169GgcHB06fPo2DgwMA9vb2ed78W1hYsGrVqicunyqOkSNH8uqrr9KlS5citc/IyCAjI0PzPDU1FQC1gYKhoVJicb3o1AaK1p/PmszMzGIfk5WVpXXcv3/Pa9eujYeHB7Vr12b37t289tprTxWXLvGVV5Iz3UjedCN5040+8lacsaTYEOI5c+HCBYKDg4mPj+f27dvk5OQAkJKSQp06dQo8rl69eiVaaGzbto2ff/6Zo0ePFvmY0NBQpk2blmf7ZJ8czM2zSyy28mJGoxx9h5CvnTt3FvuYhISEJ37ppbW1NVu3buXhw4e6hgZQorN75YXkTDeSN91I3nRTlnlLT08vclspNoR4znTu3Bk3NzdWrlyJi4sLOTk5eHp68ujRo0KPs7Ao2WVKP//8MxcvXsTW1lZre48ePWjRogUxMTF5jpk4cSKjRo3SPE9NTcXV1ZXWrVtjb29fovG9yDIzM4mOjqZdu3bP5LfS66Jhw4YEBAQUuP/333/n/v37tG3bttB2hXkR81baJGe6kbzpRvKmG33kLXdlQlFIsSHEc+Svv/7i3LlzrFy5khYtWgBw4MABzf7cmYvs7NKfJZgwYQIffPCB1rZ69eqxcOFCOnfunO8xarUatVqdZ7uxsbG8sOjgec5bWloaSUlJmudXr17l1KlT2NnZYWdnx7Rp0+jRowdOTk5cvHiRcePGUb16dV5//fWnPufnOW/6IjnTjeRNN5I33ZRl3oozjhQbQjxHKlSogL29PStWrMDZ2ZmUlBQmTJig2e/o6IiZmRlRUVFUrlwZU1NTbGxsdBrr77//JiUlhT///BOAc+fOAeDk5KT1+K8qVapo7oolREGOHDlC69atNc9zZ7wCAwNZtmwZx48f58svv+Tu3bu4uLjQvn17ZsyYkW+xKoQQ4tklxYYQzxEDAwM2bNjA8OHD8fT0pFatWixatEhzi1sjIyMWLVrE9OnTCQ4OLnA5U1Fs27aN9957T/P87bffBmDq1KmEhIQ85ZmI8s7Pzw9FKfgC959++qkMoxFCCFFapNgQ4jnTtm1bTp8+rbXt32/aPvjggzzLmyIjI4s9TlBQEEFBQcU6prA3j0IIIYQof+RL/YQQQgghhBClQooNIcqh/fv3Y2lpWeBDCCGEEKIkyDIqIcqhRo0akZiYqO8whBBCCPGCk2JDiHLIzMyM6tWr6zsMIYQQQrzgZBmVEEIIIYQQolRIsSGEEKLE7du3j86dO+Pi4oJKpWLLli0Fth00aBAqlYqwsLAyi08IIUTZkGKjEMnJyahUKlnb/gIICgqia9eu+g5DiHLjwYMHeHt7s2TJkkLbbd68mV9++QUXF5cyikwIIURZKpfFxrP0xjMmJgaVSsXdu3f1HQoA9+/fZ8SIEbi5uWFmZsarr77Kr7/+qtVGURSCg4NxdnbGzMyMtm3bcuHChTKP9VkrBv38/BgxYoS+w9DYs2cPr776KlZWVjg5OTF+/HiysrK02hw/fpwWLVpgamqKq6src+fOLXL/K1eupEWLFlSoUIEKFSrQtm1bDh8+XNKnIZ5THTt2ZObMmXTr1q3ANn/88QcfffQR69atw9jYuAyjE0IIUVbKZbFRFhRFyfPGrrRlZmY+dR8ffPAB0dHRfPXVV5w4cYL27dvTtm1b/vjjD02buXPnsmjRIpYvX058fDwWFhZ06NCBhw8fPvX4z6JHjx49d+MdO3aMgIAA/P39OXr0KN988w3btm1jwoQJmjapqam0b98eNzc3EhIS+OyzzwgJCWHFihVFGiMmJobevXuzd+9eDh06hKurK+3bt9f6XRGiIDk5Obz77ruMHTuWunXr6jscIYQQpeSFvhvV999/z7Rp00hKSsLc3BwfHx98fHz48ssvAVCpVADs3bsXPz8/Dh8+zIcffsiZM2fw9PRk0qRJRR4rJiaG1q1bs3PnTiZPnsyJEyfYtWsXLVu2ZM6cOaxYsYLr169Ts2ZNpkyZwptvvklycjKtW7cGoEKFCgAEBgYSGRmJu7s7I0aM0PqkvH79+nTt2pWQkBBN/EuXLuXHH39kz549jB07FoAtW7YwevRopkyZwp07d+jYsSMrV67Eysqq0HP4559/2LhxI1u3bqVly5YAhISE8MMPP7Bs2TJmzpyJoiiEhYUxefJkunTpAsCaNWuoWLEiW7Zs4e233y5yzorizp07DBs2jF27dpGWlkblypX55JNPeO+996hatSoAPj4+ALRq1YqYmBiys7MZO3Ysq1evxtDQkP79+xfrm639/Pzw9PTEyMiItWvXUq9ePfbu3cvJkycZO3Ys+/fvx8LCgvbt27Nw4UJeeuklgoKCiI2NJTY2lvDwcAAuX75MTEwMI0aM0Jq52rJlC926ddPEFBISwpYtWxg2bBizZs3iypUr5OTkoFKpWLlyJTt27OCnn36iUqVKzJ8/nzfeeOOJ5/DNN9/g5eVFcHAwANWrV2fu3Ln07NmTqVOnYmVlxbp163j06BGrV6/GxMSEunXrkpiYyIIFCxg4cOATx1i3bp3W81WrVrFx40b27NlDv379ippuAJqG7iHLyKJYx5RnakOFuU3AM+QnMrJVZT5+8uzXn7qPOXPmYGRkxPDhw0sgIiGEEM+qF7bYuHbtGr1792bu3Ll069aN+/fvs3//fvr160dKSgqpqalEREQAYGdnR1paGp06daJdu3asXbuWy5cv8/HHHxd73AkTJjBv3jxefvllKlSoQGhoKGvXrmX58uXUqFGDffv28c477+Dg4EDz5s3ZuHEjPXr04Ny5c1hbW2NmZlas8UJCQpg9ezZhYWEYGRmxevVqLl68yJYtW9i+fTt37tyhZ8+ezJ49m1mzZhXaV1ZWFtnZ2ZiammptNzMz48CBA8DjN9DXr1+nbdu2mv02NjY0bdqUQ4cOlXixMWXKFE6fPs2PP/7ISy+9RFJSEv/88w8Ahw8fpkmTJuzevZu6detiYmICwPz584mMjGT16tV4eHgwf/58Nm/ezGuvvVbkcb/88ksGDx5MXFwcAHfv3uW1117jgw8+YOHChfzzzz+MHz+enj178vPPPxMeHs758+fx9PRk+vTpADg4OBR5vKSkJDZu3MimTZswNDTUbJ82bRpz587ls88+Y/HixfTt25crV65gZ2dXaH8ZGRn5/hwfPnxIQkICfn5+HDp0iJYtW2ryBtChQwfmzJnDnTt3NAVwUaWnp5OZmVlobBkZGWRkZGiep6amAqA2UDA0LHpBWN6pDRStP8uaLrOoWVlZmuN+++03wsPDiY+P15oBzs7OLpEZ2oLk9l2aY7xoJGe6kbzpRvKmG33krThjvdDFRlZWFt27d8fNzQ2AevXqAY/fdGVkZODk5KRpHxkZSU5ODv/73/8wNTWlbt26/P777wwePLhY406fPp127doBj99Yffrpp+zevRtfX18AXn75ZQ4cOMAXX3xBq1atNG/MHB0dsbW1LfZ59unTh/fee09rW05ODpGRkZqZjHfffZc9e/Y8sdiwsrLC19eXGTNm4OHhQcWKFVm/fj2HDh3SfCfD9evXAahYsaLWsRUrVtTsK0kpKSn4+PjQqFEjANzd3TX7ct/M29vba/0sw8LCmDhxIt27dwdg+fLl/PTTT8Uat0aNGlrXL8ycORMfHx8+/fRTzbbVq1fj6urK+fPnqVmzJiYmJpibm2vFUlSPHj1izZo1eQqUoKAgevfuDcCnn37KokWLOHz4MP7+/oX216FDB8LCwli/fj09e/bk+vXrmiLo2rVrwOOfZe7sUK7cn+v169eLXWyMHz8eFxcXrUL0v0JDQ5k2bVqe7ZN9cjA3zy7WeAJmNMrRy7g7d+4s9jEJCQma6zK2bdvGzZs3efnllzX7c3JyGDduHHPmzGHlypUlFmt+oqOjS7X/F5HkTDeSN91I3nRTlnlLT08vctsXttjw9vamTZs21KtXjw4dOtC+fXvefPPNAt9AnTlzBi8vL61Pg3MLhOLIfVMMjz+tTk9P1xQfuR49eqRZ+vO0/j1eLnd3d60lU87Ozty8ebNI/X311Ve8//77VKpUCUNDQxo0aEDv3r1JSEgokXg7duzI/v37AXBzc+PUqVOFth88eDA9evTgt99+o3379nTt2pVXX321wPb37t3j2rVrNG3aVLPNyMiIRo0aFWspVcOGDbWeHzt2jL1792JpaZmn7cWLF6lZs2aR+86Pm5tbvjMhXl5emr9bWFhgbW1dpJ9l+/bt+eyzzxg0aBDvvvsuarWaKVOmsH//fgwMSv5SrdmzZ7NhwwZiYmLyzKj828SJExk1apTmeWpqKq6ursw8akCWsWGBxwltagOFGY1ymHLEgIycsl9GdTKkQ7GPadiwIQEBAQA0bdqUYcOGae3v1KkTffr0ITAwkFq1apVInP+VmZlJdHQ07dq1kwvSi0hyphvJm24kb7rRR95yVyYUxQtbbBgaGhIdHc3BgwfZtWsXixcvZtKkScTHx5fquBYW/7fuPC0tDYAdO3ZQqVIlrXZqtbrQfgwMDPK8Oc5vyurf4+X67y+aSqUiJ6don4BWq1aN2NhYHjx4QGpqKs7OzvTq1UvzCWTup/Y3btzA2dlZc9yNGzeoX7/+E/tftWqVZhlUUf5BdOzYkStXrrBz506io6Np06YNQ4cOZd68eUU6H139N69paWl07tyZOXPm5Gn77zz819P8HOHpfpajRo1i5MiRXLt2jQoVKpCcnMzEiRO1fpY3btzQOib3eXFmZ+bNm8fs2bPZvXu3VnGUH7Vane/v/r7xbbG3ty/ymOVdZmYmO3fuJCHY/5l9QU5LSyMpKUnz/OrVq5w6dQo7OzuqVKmS53fM2NiYSpUq4enpWeqxGRsbP7N5e1ZJznQjedON5E03ZZm34ozzQt+NSqVS0axZM6ZNm8bRo0cxMTFh8+bNmJiYkJ2tvWTDw8OD48ePa91R6Zdffnmq8evUqYNarSYlJYXq1atrPVxdXQE06+X/G4+Dg4NmuQs8riAvX778VPEUh4WFBc7Ozty5c4effvpJczF41apVcXJyYs+ePVqxxcfHF2kmqFKlSpoc5C5vexIHBwcCAwNZu3YtYWFhmrsl5Zc7GxsbnJ2dtYrKrKysp56ZadCgAadOncLd3T3PzzK3UMjv98rBwYH79+/z4MEDzbayvFWvSqXCxcUFMzMz1q9fj6urKw0aNAAez9zt27dPq/iJjo6mVq1aRV5CNXfuXGbMmEFUVFS+s2yi/Dpy5IjmphzwuPj18fHR3LRACCFE+fDCzmzEx8ezZ88e2rdvj6OjI/Hx8dy6dQsPDw8ePnzITz/9xLlz57C3t8fGxoY+ffowadIkBgwYwMSJE0lOTn7qT8+trKwYM2YMI0eOJCcnh+bNm3Pv3j3i4uKwtrYmMDAQNzc3VCoV27dvJyAgADMzMywtLXnttdeIjIykc+fO2NraEhwcrHXhcGn56aefUBSFWrVqkZSUxNixY6ldu7bmuhCVSsWIESOYOXMmNWrUoGrVqkyZMgUXF5dS+e6S4OBgGjZsSN26dcnIyGD79u14eHgAj69zMTMzIyoqisqVK2NqaoqNjQ0ff/wxs2fPpkaNGtSuXZsFCxY89feYDB06lJUrV9K7d2/GjRuHnZ0dSUlJbNiwgVWrVmFoaIi7uzvx8fEkJydjaWmJnZ0dTZs2xdzcnE8++YThw4cTHx9PZGTk0yemCD777DP8/f0xMDBg06ZNzJ49m2+//Vbze9SnTx+mTZtG//79GT9+PCdPniQ8PJyFCxcWqf85c+YQHBzM119/jbu7u+aaHUtLy3yXm4nyxc/Pr1hLF5OTk0svGCGEEHrzws5sWFtbs2/fPgICAqhZsyaTJ09m/vz5dOzYkQEDBlCrVi0aNWqEg4MDcXFxWFpa8sMPP3DixAl8fHyYNGlSvktmimvGjBlMmTKF0NBQPDw88Pf3Z8eOHZoLcytVqsS0adOYMGECFStW1KxjnjhxIq1ataJTp068/vrrdO3alWrVqj11PE9y7949hg4dSu3atenXrx/Nmzfnp59+0pouGzduHB999BEDBw6kcePGpKWlERUVVehafV2ZmJgwceJEvLy8aNmyJYaGhmzYsAF4fC3GokWL+OKLL3BxcdHMvowePZp3332XwMBAfH19sbKyKvSLxYrCxcWFuLg4srOzad++PfXq1WPEiBHY2tpqroEYM2YMhoaG1KlTBwcHB1JSUrCzs2Pt2rXs3LmTevXqsX79es2ti0vbjz/+SIsWLWjUqBE7duxg69atWgWhjY0Nu3bt4vLlyzRs2JDRo0cTHBxcpNveAixbtoxHjx7x5ptv4uzsrHmU9hI3IYQQQjw/VEpxPnoSQogSlJqaio2NDbdv35ZrNooh95qNgIAAWddcDJK34pOc6UbyphvJm270kbfc1+979+5hbW1daNsXdmZDCCGEEEIIoV9SbBTRoEGDNGvR//sYNGiQvsMrkpSUlALPwdLSkpSUlKce49NPPy2w/44dO+ZpX9Z5LYsclIWyyFthecq9fbEQQgghRGFe2AvES9r06dMZM2ZMvvueNH30rHBxcSn0TkguLi5PPcagQYPo2bNnvvvy+3b0ss5rWeSgLJRF3grL039v5SyEEEIIkR8pNorI0dERR0dHfYfxVIyMjDTfBF5a7OzsNN+KXhRlndeyyEFZKIu8vQh5EkIIIYR+yTIqIYQQQgghRKmQYkMIIYQQQghRKqTYEEIIIYQQQpQKKTaEEEIIIYQQpUKKDSGEEEIIIUSpkGJDCCGEEEIIUSrk1rdCCL1RFAWA+/fvY2xsrOdonh+ZmZmkp6eTmpoqeSsGyVvxSc50I3nTjeRNN/rIW2pqKvB/r+OFkWJDCKE3f/31FwBVq1bVcyRCCCGEKK779+9jY2NTaBspNoQQepP7BZApKSlP/M9K/J/U1FRcXV25evVqiX1jfHkgeSs+yZluJG+6kbzpRh95UxSF+/fv4+Li8sS2UmwIIfTGwODxZWM2NjbywqIDa2tryZsOJG/FJznTjeRNN5I33ZR13or6IaFcIC6EEEIIIYQoFVJsCCGEEEIIIUqFFBtCCL1Rq9VMnToVtVqt71CeK5I33Ujeik9yphvJm24kb7p51vOmUopyzyohhBBCCCGEKCaZ2RBCCCGEEEKUCik2hBBCCCGEEKVCig0hhBBCCCFEqZBiQwghhBBCCFEqpNgQQujNkiVLcHd3x9TUlKZNm3L48GF9h/RM2bdvH507d8bFxQWVSsWWLVu09iuKQnBwMM7OzpiZmdG2bVsuXLign2CfEaGhoTRu3BgrKyscHR3p2rUr586d02rz8OFDhg4dir29PZaWlvTo0YMbN27oKeJnw7Jly/Dy8tJ8KZivry8//vijZr/k7Mlmz56NSqVixIgRmm2St7xCQkJQqVRaj9q1a2v2S84K9scff/DOO+9gb2+PmZkZ9erV48iRI5r9z+prghQbQgi9+Oabbxg1ahRTp07lt99+w9vbmw4dOnDz5k19h/bMePDgAd7e3ixZsiTf/XPnzmXRokUsX76c+Ph4LCws6NChAw8fPizjSJ8dsbGxDB06lF9++YXo6GgyMzNp3749Dx480LQZOXIkP/zwA9999x2xsbH8+eefdO/eXY9R61/lypWZPXs2CQkJHDlyhNdee40uXbpw6tQpQHL2JL/++itffPEFXl5eWtslb/mrW7cu165d0zwOHDig2Sc5y9+dO3do1qwZxsbG/Pjjj5w+fZr58+dToUIFTZtn9jVBEUIIPWjSpIkydOhQzfPs7GzFxcVFCQ0N1WNUzy5A2bx5s+Z5Tk6O4uTkpHz22WeabXfv3lXUarWyfv16PUT4bLp586YCKLGxsYqiPM6RsbGx8t1332nanDlzRgGUQ4cO6SvMZ1KFChWUVatWSc6e4P79+0qNGjWU6OhopVWrVsrHH3+sKIr8rhVk6tSpire3d777JGcFGz9+vNK8efMC9z/LrwkysyGEKHOPHj0iISGBtm3barYZGBjQtm1bDh06pMfInh+XL1/m+vXrWjm0sbGhadOmksN/uXfvHgB2dnYAJCQkkJmZqZW32rVrU6VKFcnb/5ednc2GDRt48OABvr6+krMnGDp0KK+//rpWfkB+1wpz4cIFXFxcePnll+nbty8pKSmA5Kww27Zto1GjRrz11ls4Ojri4+PDypUrNfuf5dcEKTaEEGXu9u3bZGdnU7FiRa3tFStW5Pr163qK6vmSmyfJYcFycnIYMWIEzZo1w9PTE3icNxMTE2xtbbXaSt7gxIkTWFpaolarGTRoEJs3b6ZOnTqSs0Js2LCB3377jdDQ0Dz7JG/5a9q0KZGRkURFRbFs2TIuX75MixYtuH//vuSsEJcuXWLZsmXUqFGDn376icGDBzN8+HC+/PJL4Nl+TTDS6+hCCCFEKRk6dCgnT57UWg8uClarVi0SExO5d+8e33//PYGBgcTGxuo7rGfW1atX+fjjj4mOjsbU1FTf4Tw3OnbsqPm7l5cXTZs2xc3NjW+//RYzMzM9RvZsy8nJoVGjRnz66acA+Pj4cPLkSZYvX05gYKCeoyuczGwIIcrcSy+9hKGhYZ47jNy4cQMnJyc9RfV8yc2T5DB/w4YNY/v27ezdu5fKlStrtjs5OfHo0SPu3r2r1V7yBiYmJlSvXp2GDRsSGhqKt7c34eHhkrMCJCQkcPPmTRo0aICRkRFGRkbExsayaNEijIyMqFixouStCGxtbalZsyZJSUnyu1YIZ2dn6tSpo7XNw8NDswTtWX5NkGJDCFHmTExMaNiwIXv27NFsy8nJYc+ePfj6+uoxsudH1apVcXJy0sphamoq8fHx5TqHiqIwbNgwNm/ezM8//0zVqlW19jds2BBjY2OtvJ07d46UlJRynbf85OTkkJGRITkrQJs2bThx4gSJiYmaR6NGjejbt6/m75K3J0tLS+PixYs4OzvL71ohmjVrluc23ufPn8fNzQ14xl8T9Hp5uhCi3NqwYYOiVquVyMhI5fTp08rAgQMVW1tb5fr16/oO7Zlx//595ejRo8rRo0cVQFmwYIFy9OhR5cqVK4qiKMrs2bMVW1tbZevWrcrx48eVLl26KFWrVlX++ecfPUeuP4MHD1ZsbGyUmJgY5dq1a5pHenq6ps2gQYOUKlWqKD///LNy5MgRxdfXV/H19dVj1Po3YcIEJTY2Vrl8+bJy/PhxZcKECYpKpVJ27dqlKIrkrKj+fTcqRZG85Wf06NFKTEyMcvnyZSUuLk5p27at8tJLLyk3b95UFEVyVpDDhw8rRkZGyqxZs5QLFy4o69atU8zNzZW1a9dq2jyrrwlSbAgh9Gbx4sVKlSpVFBMTE6VJkybKL7/8ou+Qnil79+5VgDyPwMBARVEe3+pwypQpSsWKFRW1Wq20adNGOXfunH6D1rP88gUoERERmjb//POPMmTIEKVChQqKubm50q1bN+XatWv6C/oZ8P777ytubm6KiYmJ4uDgoLRp00ZTaCiK5Kyo/ltsSN7y6tWrl+Ls7KyYmJgolSpVUnr16qUkJSVp9kvOCvbDDz8onp6eilqtVmrXrq2sWLFCa/+z+pqgUhRF0c+cihBCCCGEEOJFJtdsCCGEEEIIIUqFFBtCCCGEEEKIUiHFhhBCCCGEEKJUSLEhhBBCCCGEKBVSbAghhBBCCCFKhRQbQgghhBBCiFIhxYYQQgghhBCiVEixIYQQQohi8fPzY8SIEfoOQwjxHJBiQwghhChBQUFBqFSqPI+kpKQS6T8yMhJbW9sS6UtXmzZtYsaMGXqNoTAxMTGoVCru3r2r71CEKPeM9B2AEEII8aLx9/cnIiJCa5uDg4OeoilYZmYmxsbGxT7Ozs6uFKIpGZmZmfoOQQjxLzKzIYQQQpQwtVqNk5OT1sPQ0BCArVu30qBBA0xNTXn55ZeZNm0aWVlZmmMXLFhAvXr1sLCwwNXVlSFDhpCWlgY8/sT+vffe4969e5oZk5CQEABUKhVbtmzRisPW1pbIyEgAkpOTUalUfPPNN7Rq1QpTU1PWrVsHwKpVq/Dw8MDU1JTatWuzdOnSQs/vv8uo3N3dmTlzJv369cPS0hI3Nze2bdvGrVu36NKlC5aWlnh5eXHkyBHNMbkzNFu2bKFGjRqYmprSoUMHrl69qjXWsmXLqFatGiYmJtSqVYuvvvpKa79KpWLZsmW88cYbWFhYMGDAAFq3bg1AhQoVUKlUBAUFARAVFUXz5s2xtbXF3t6eTp06cfHiRU1fuTnatGkTrVu3xtzcHG9vbw4dOqQ1ZlxcHH5+fpibm1OhQgU6dOjAnTt3AMjJySE0NJSqVatiZmaGt7c333//faH5FOKFpgghhBCixAQGBipdunTJd9++ffsUa2trJTIyUrl48aKya9cuxd3dXQkJCdG0WbhwofLzzz8rly9fVvbs2aPUqlVLGTx4sKIoipKRkaGEhYUp1tbWyrVr15Rr164p9+/fVxRFUQBl8+bNWuPZ2NgoERERiqIoyuXLlxVAcXd3VzZu3KhcunRJ+fPPP5W1a9cqzs7Omm0bN25U7OzslMjIyALPsVWrVsrHH3+see7m5qbY2dkpy5cvV86fP68MHjxYsba2Vvz9/ZVvv/1WOXfunNK1a1fFw8NDycnJURRFUSIiIhRjY2OlUaNGysGDB5UjR44oTZo0UV599VVNv5s2bVKMjY2VJUuWKOfOnVPmz5+vGBoaKj///LOmDaA4Ojoqq1evVi5evKgkJycrGzduVADl3LlzyrVr15S7d+8qiqIo33//vbJx40blwoULytGjR5XOnTsr9erVU7Kzs7VyVLt2bWX79u3KuXPnlDfffFNxc3NTMjMzFUVRlKNHjypqtVoZPHiwkpiYqJw8eVJZvHixcuvWLUVRFGXmzJlK7dq1laioKOXixYtKRESEolarlZiYmALzKcSLTIoNIYQQogQFBgYqhoaGioWFhebx5ptvKoqiKG3atFE+/fRTrfZfffWV4uzsXGB/3333nWJvb695HhERodjY2ORpV9RiIywsTKtNtWrVlK+//lpr24wZMxRfX98CY8qv2HjnnXc0z69du6YAypQpUzTbDh06pADKtWvXNOcBKL/88oumzZkzZxRAiY+PVxRFUV599VVlwIABWmO/9dZbSkBAgNZ5jxgxQqvN3r17FUC5c+dOgeegKIpy69YtBVBOnDihKMr/5WjVqlWaNqdOnVIA5cyZM4qiKErv3r2VZs2a5dvfw4cPFXNzc+XgwYNa2/v376/07t270FiEeFHJNRtCCCFECWvdujXLli3TPLewsADg2LFjxMXFMWvWLM2+7OxsHj58SHp6Oubm5uzevZvQ0FDOnj1LamoqWVlZWvufVqNGjTR/f/DgARcvXqR///4MGDBAsz0rKwsbG5ti9evl5aX5e8WKFQGoV69enm03b97EyckJACMjIxo3bqxpU7t2bWxtbTlz5gxNmjThzJkzDBw4UGucZs2aER4eXuA5FebChQsEBwcTHx/P7du3ycnJASAlJQVPT898z8XZ2VkTd+3atUlMTOStt97Kt/+kpCTS09Np166d1vZHjx7h4+NTpBiFeNFIsSGEEEKUMAsLC6pXr55ne1paGtOmTaN79+559pmampKcnEynTp0YPHgws2bNws7OjgMHDtC/f38ePXpUaLGhUqlQFEVrW34XS+cWPrnxAKxcuZKmTZtqtcu9xqSo/n2huUqlKnBb7hv8kvTvcypM586dcXNzY+XKlbi4uJCTk4OnpyePHj3SaldY3GZmZgX2n5vPHTt2UKlSJa19arW6SDEK8aKRYkMIIYQoIw0aNODcuXP5FiIACQkJ5OTkMH/+fAwMHt/D5dtvv9VqY2JiQnZ2dp5jHRwcuHbtmub5hQsXSE9PLzSeihUr4uLiwqVLl+jbt29xT+epZWVlceTIEZo0aQLAuXPnuHv3Lh4eHgB4eHgQFxdHYGCg5pi4uDjq1KlTaL8mJiYAWnn666+/OHfuHCtXrqRFixYAHDhwoNgxe3l5sWfPHqZNm5ZnX506dVCr1aSkpNCqVati9y3Ei0iKDSGEEKKMBAcH06lTJ6pUqcKbb76JgYEBx44d4+TJk8ycOZPq1auTmZnJ4sWL6dy5M3FxcSxfvlyrD3d3d9LS0tizZw/e3t6Ym5tjbm7Oa6+9xueff46vry/Z2dmMHz++SLe1nTZtGsOHD8fGxgZ/f38yMjI4cuQId+7cYdSoUaWVCuDxDMJHH33EokWLMDIyYtiwYbzyyiua4mPs2LH07NkTHx8f2rZtyw8//MCmTZvYvXt3of26ubmhUqnYvn07AQEBmJmZUaFCBezt7VmxYgXOzs6kpKQwYcKEYsc8ceJE6tWrx5AhQxg0aBAmJibs3buXt956i5deeokxY8YwcuRIcnJyaN68Offu3SMuLg5ra2utokmI8kJufSuEEEKUkQ4dOrB9+3Z27dpF48aNeeWVV1i4cCFubm4AeHt7s2DBAubMmYOnpyfr1q0jNDRUq49XX32VQYMG0atXLxwcHJg7dy4A8+fPx9XVlRYtWtCnTx/GjBlTpGs8PvjgA1atWkVERAT16tWjVatWREZGUrVq1ZJPwH+Ym5szfvx4+vTpQ7NmzbC0tOSbb77R7O/atSvh4eHMmzePunXr8sUXXxAREYGfn1+h/VaqVIlp06YxYcIEKlasyLBhwzAwMGDDhg0kJCTg6enJyJEj+eyzz4odc82aNdm1axfHjh2jSZMm+Pr6snXrVoyMHn9+O2PGDKZMmUJoaCgeHh74+/uzY8eOMsmnEM8ilfLfBZ5CCCGEEKUsMjKSESNGyLd8C/GCk5kNIYQQQgghRKmQYkMIIYQQQghRKmQZlRBCCCGEEKJUyMyGEEIIIYQQolRIsSGEEEIIIYQoFVJsCCGEEEIIIUqFFBtCCCGEEEKIUiHFhhBCCCGEEKJUSLEhhBBCCCGEKBVSbAghhBBCCCFKhRQbQgghhBBCiFIhxYYQQgghhBCiVPw/tzFpbnn+DZIAAAAASUVORK5CYII=" }, "metadata": {}, "output_type": "display_data" @@ -1486,11 +1565,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "train data size: 2540320\n" + "train data size: 1107768\n" ] } ], - "execution_count": 16 + "execution_count": 70 }, { "cell_type": "code", @@ -1500,8 +1579,8 @@ "source_hidden": true }, "ExecuteTime": { - "end_time": "2025-03-31T14:59:05.601202Z", - "start_time": "2025-03-31T14:59:05.593686Z" + "end_time": "2025-04-02T16:43:22.895694Z", + "start_time": "2025-04-02T16:43:22.891020Z" } }, "source": [ @@ -1543,15 +1622,15 @@ "# # model, scaler = train_catboost(train_data, test_data.dropna(subset=['label']), feature_columns_new, catboost_params, plot=True)" ], "outputs": [], - "execution_count": 17 + "execution_count": 71 }, { "cell_type": "code", "id": "5d1522a7538db91b", "metadata": { "ExecuteTime": { - "end_time": "2025-03-31T15:06:24.620370Z", - "start_time": "2025-03-31T15:05:42.433755Z" + "end_time": "2025-04-02T16:43:27.845040Z", + "start_time": "2025-04-02T16:43:22.900703Z" } }, "source": [ @@ -1591,30 +1670,30 @@ "name": "stdout", "output_type": "stream", "text": [ - "33.37918215613383\n", + "25.79150579150579\n", " trade_date ts_code future_return future_score label\n", - "244753 2023-01-03 002148.SZ 0.015781 0.035495 45.0\n", - "876303 2023-01-04 601155.SH 0.011962 0.027340 43.0\n", - "57142 2023-01-05 000596.SZ 0.006810 0.025770 42.0\n", - "423377 2023-01-06 002683.SZ 0.030527 0.042989 47.0\n", - "615161 2023-01-09 600197.SH -0.047347 -0.005790 26.0\n", - "771090 2023-01-10 600729.SH -0.040330 -0.005321 23.0\n", - "734311 2023-01-11 600603.SH -0.037655 -0.000025 15.0\n", - "717317 2023-01-12 600556.SH 0.005312 0.028766 42.0\n", - "163236 2023-01-13 001236.SZ 0.240337 0.174003 49.0\n", - "182872 2023-01-16 001339.SZ -0.045814 -0.015564 3.0\n" + "108174 2024-03-01 600515.SH -0.021294 -0.014906 21.0\n", + "137114 2024-03-04 601377.SH -0.005138 -0.003597 22.0\n", + "137115 2024-03-05 601377.SH -0.007065 -0.004945 16.0\n", + "20064 2024-03-06 000950.SZ 0.056106 0.039274 46.0\n", + "43829 2024-03-07 002252.SZ 0.015518 0.010862 18.0\n", + "9725 2024-03-08 000650.SZ 0.040857 0.028600 34.0\n", + "58797 2024-03-11 002539.SZ 0.003740 0.002618 21.0\n", + "30855 2024-03-12 002030.SZ -0.005742 -0.004020 26.0\n", + "164833 2024-03-13 603366.SH 0.005460 0.003822 22.0\n", + "62880 2024-03-14 002616.SZ 0.036372 0.025461 32.0\n" ] } ], - "execution_count": 23 + "execution_count": 72 }, { "cell_type": "code", "id": "d86af99d15cb3bdd", "metadata": { "ExecuteTime": { - "end_time": "2025-03-31T14:59:50.861647Z", - "start_time": "2025-03-31T14:59:50.140899Z" + "end_time": "2025-04-02T16:43:28.288257Z", + "start_time": "2025-04-02T16:43:28.041487Z" } }, "source": [ @@ -1643,15 +1722,15 @@ ] } ], - "execution_count": 19 + "execution_count": 73 }, { "cell_type": "code", "id": "ef9d068e-67f7-412c-bbd8-cdee7492dbc9", "metadata": { "ExecuteTime": { - "end_time": "2025-03-31T14:59:51.110863Z", - "start_time": "2025-03-31T14:59:50.995929Z" + "end_time": "2025-04-02T16:43:28.315175Z", + "start_time": "2025-04-02T16:43:28.292264Z" } }, "source": [ @@ -1663,12 +1742,12 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.7433127289155628\n", - "0.6971824619501555\n" + "0.7619606950196554\n", + "0.7280155931953278\n" ] } ], - "execution_count": 20 + "execution_count": 74 } ], "metadata": {