{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=pd.read_excel(\"plclog20230613.xlsx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(576000, 112)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>sn</th>\n",
       "      <th>steps</th>\n",
       "      <th>status</th>\n",
       "      <th>x_v</th>\n",
       "      <th>y_v</th>\n",
       "      <th>z_v</th>\n",
       "      <th>r_v</th>\n",
       "      <th>pause</th>\n",
       "      <th>x_s</th>\n",
       "      <th>...</th>\n",
       "      <th>lift_code_dist</th>\n",
       "      <th>deflect2</th>\n",
       "      <th>pushrod2_out_time</th>\n",
       "      <th>pushrod3_out_time</th>\n",
       "      <th>pushrod2_in_time</th>\n",
       "      <th>pushrod3_in_time</th>\n",
       "      <th>pushrod1_out_time</th>\n",
       "      <th>pushrod4_out_time</th>\n",
       "      <th>pushrod1_in_time</th>\n",
       "      <th>pushrod4_in_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-06-13 00:00:00.086</td>\n",
       "      <td>plc</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.074901</td>\n",
       "      <td>0.150925</td>\n",
       "      <td>-0.008602</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>3.759514e-06</td>\n",
       "      <td>...</td>\n",
       "      <td>-752.316</td>\n",
       "      <td>1.898266e-310</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-06-13 00:00:00.186</td>\n",
       "      <td>plc</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.150925</td>\n",
       "      <td>0.008602</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>-9.218238e-07</td>\n",
       "      <td>...</td>\n",
       "      <td>-752.316</td>\n",
       "      <td>1.898266e-310</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-06-13 00:00:00.286</td>\n",
       "      <td>plc</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.224704</td>\n",
       "      <td>0.226387</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.019073</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.028450e-05</td>\n",
       "      <td>...</td>\n",
       "      <td>-752.316</td>\n",
       "      <td>1.898266e-310</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-06-13 00:00:00.386</td>\n",
       "      <td>plc</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.226387</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.019073</td>\n",
       "      <td>0</td>\n",
       "      <td>3.759514e-06</td>\n",
       "      <td>...</td>\n",
       "      <td>-752.316</td>\n",
       "      <td>1.898266e-310</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-06-13 00:00:00.486</td>\n",
       "      <td>plc</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.299606</td>\n",
       "      <td>0.075462</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.019073</td>\n",
       "      <td>0</td>\n",
       "      <td>1.312219e-05</td>\n",
       "      <td>...</td>\n",
       "      <td>-752.316</td>\n",
       "      <td>1.898266e-310</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 112 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      time   sn  steps  status       x_v       y_v       z_v  \\\n",
       "0  2023-06-13 00:00:00.086  plc      0       1 -0.074901  0.150925 -0.008602   \n",
       "1  2023-06-13 00:00:00.186  plc      0       1  0.000000 -0.150925  0.008602   \n",
       "2  2023-06-13 00:00:00.286  plc      0       1 -0.224704  0.226387  0.000000   \n",
       "3  2023-06-13 00:00:00.386  plc      0       1  0.000000  0.226387  0.000000   \n",
       "4  2023-06-13 00:00:00.486  plc      0       1  0.299606  0.075462  0.000000   \n",
       "\n",
       "        r_v  pause           x_s  ...  lift_code_dist       deflect2  \\\n",
       "0  0.000000      0  3.759514e-06  ...        -752.316  1.898266e-310   \n",
       "1  0.000000      0 -9.218238e-07  ...        -752.316  1.898266e-310   \n",
       "2 -0.019073      0 -1.028450e-05  ...        -752.316  1.898266e-310   \n",
       "3 -0.019073      0  3.759514e-06  ...        -752.316  1.898266e-310   \n",
       "4 -0.019073      0  1.312219e-05  ...        -752.316  1.898266e-310   \n",
       "\n",
       "   pushrod2_out_time  pushrod3_out_time  pushrod2_in_time  pushrod3_in_time  \\\n",
       "0                  0                  0                 0                 0   \n",
       "1                  0                  0                 0                 0   \n",
       "2                  0                  0                 0                 0   \n",
       "3                  0                  0                 0                 0   \n",
       "4                  0                  0                 0                 0   \n",
       "\n",
       "   pushrod1_out_time  pushrod4_out_time  pushrod1_in_time  pushrod4_in_time  \n",
       "0               5000               5000              5000              5000  \n",
       "1               5000               5000              5000              5000  \n",
       "2               5000               5000              5000              5000  \n",
       "3               5000               5000              5000              5000  \n",
       "4               5000               5000              5000              5000  \n",
       "\n",
       "[5 rows x 112 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "##利用steps 将数据切分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "##排除掉部分无用的数据（感觉有问题，需要核实）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11001"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data[data[\"x_v\"]==100])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "576000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=data[data[\"x_v\"]!=100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(564999, 112)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[\"change_status\"]=0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1248361/3571451586.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  data[\"change_status\"][data[\"steps\"]!=0]=1\n"
     ]
    }
   ],
   "source": [
    "data[\"change_status\"][data[\"steps\"]!=0]=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[\"change_flag\"]=(data[\"change_status\"] != data[\"change_status\"].shift(1)).astype(int).cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.drop('change_status', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(data[\"veh_coarse_position\"].iloc[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(564999, 113)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['time', 'sn', 'steps', 'status', 'x_v', 'y_v', 'z_v', 'r_v', 'pause',\n",
       "       'x_s',\n",
       "       ...\n",
       "       'deflect2', 'pushrod2_out_time', 'pushrod3_out_time',\n",
       "       'pushrod2_in_time', 'pushrod3_in_time', 'pushrod1_out_time',\n",
       "       'pushrod4_out_time', 'pushrod1_in_time', 'pushrod4_in_time',\n",
       "       'change_flag'],\n",
       "      dtype='object', length=113)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sqlalchemy import create_engine\n",
    "mysql_user = 'root'\n",
    "mysql_password = 'qx123456'\n",
    "mysql_host = 'algo-dev-internal.li-ai.com.cn'\n",
    "mysql_port = 3306\n",
    "mysql_db = 'aiomp'\n",
    "\n",
    "db_engine = create_engine(\"mysql+pymysql://{}:{}@{}:{}/{}?charset=utf8\".format(mysql_user, mysql_password, mysql_host, mysql_port, mysql_db),\n",
    "                            pool_recycle=7200,pool_size=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.to_sql(\"plclog\",con=db_engine, if_exists=\"append\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_in=data[data[\"steps\"]!=0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "groups=set(data_in[\"change_flag\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{2,\n",
       " 4,\n",
       " 6,\n",
       " 8,\n",
       " 10,\n",
       " 12,\n",
       " 14,\n",
       " 16,\n",
       " 18,\n",
       " 20,\n",
       " 22,\n",
       " 24,\n",
       " 26,\n",
       " 28,\n",
       " 30,\n",
       " 32,\n",
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       " 40,\n",
       " 42,\n",
       " 44,\n",
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       " 48,\n",
       " 50,\n",
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       " 56,\n",
       " 58,\n",
       " 60,\n",
       " 62,\n",
       " 64,\n",
       " 66,\n",
       " 68,\n",
       " 70,\n",
       " 72,\n",
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       " 78,\n",
       " 80,\n",
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       " 86,\n",
       " 88,\n",
       " 90,\n",
       " 92,\n",
       " 94,\n",
       " 96,\n",
       " 98,\n",
       " 100,\n",
       " 102,\n",
       " 104,\n",
       " 106,\n",
       " 108,\n",
       " 110,\n",
       " 112,\n",
       " 114,\n",
       " 116,\n",
       " 118,\n",
       " 120,\n",
       " 122,\n",
       " 124,\n",
       " 126,\n",
       " 128,\n",
       " 130,\n",
       " 132,\n",
       " 134,\n",
       " 136,\n",
       " 138,\n",
       " 140,\n",
       " 142,\n",
       " 144,\n",
       " 146,\n",
       " 148,\n",
       " 150,\n",
       " 152,\n",
       " 154,\n",
       " 156,\n",
       " 158,\n",
       " 160,\n",
       " 162,\n",
       " 164,\n",
       " 166,\n",
       " 168,\n",
       " 170,\n",
       " 172,\n",
       " 174,\n",
       " 176,\n",
       " 178,\n",
       " 180,\n",
       " 182,\n",
       " 184,\n",
       " 186,\n",
       " 188,\n",
       " 190,\n",
       " 192,\n",
       " 194,\n",
       " 196,\n",
       " 198,\n",
       " 200,\n",
       " 202,\n",
       " 204,\n",
       " 206,\n",
       " 208,\n",
       " 210,\n",
       " 212,\n",
       " 214,\n",
       " 216,\n",
       " 218,\n",
       " 220,\n",
       " 222,\n",
       " 224,\n",
       " 226,\n",
       " 228,\n",
       " 230,\n",
       " 232,\n",
       " 234,\n",
       " 236,\n",
       " 238,\n",
       " 240,\n",
       " 242,\n",
       " 244,\n",
       " 246,\n",
       " 248,\n",
       " 250,\n",
       " 252,\n",
       " 254,\n",
       " 256,\n",
       " 258,\n",
       " 260,\n",
       " 262,\n",
       " 264,\n",
       " 266,\n",
       " 268,\n",
       " 270,\n",
       " 272,\n",
       " 274,\n",
       " 276,\n",
       " 278}"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "139"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(groups)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [],
   "source": [
    "lift_list=[8]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "##分析第7步的时间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_in_lift=data_in[data_in[\"steps\"].isin(lift_list)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "lift_values = data_in_lift.groupby(['change_flag','steps']).agg({'time':['min','max'],\n",
    "                                                                 'z_s':['min','max']})\n",
    "zz_max=lift_values.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "zz_max.columns=[\"change_flag\",\"steps\",\"time_b\",\"time_e\",\"zs_min\",\"zs_max\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [],
   "source": [
    "zz_max[\"time_delta\"]=pd.to_timedelta(pd.to_datetime(zz_max[\"time_e\"])-pd.to_datetime(zz_max[\"time_b\"])).dt.total_seconds()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "zz_max[\"time_delta\"].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    138.000000\n",
       "mean       2.704348\n",
       "std        0.055196\n",
       "min        2.500000\n",
       "25%        2.700000\n",
       "50%        2.700000\n",
       "75%        2.700000\n",
       "max        2.800000\n",
       "Name: time_delta, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zz_max[\"time_delta\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(31082, 113)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_in_lift.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_in_lift_pushrod2=data_in_lift[[\"time\",\"change_flag\",\"steps\",\"pushrod2_retracted\",\"pushrod2_extended\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "ll=list(set(data_in_lift_pushrod2[\"change_flag\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "union_t2=pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "for  change_flag in ll:\n",
    "    ##第4步最后一条\n",
    "    step_6_last=data_in_lift_pushrod2[(data_in_lift_pushrod2[\"change_flag\"]==change_flag)&(data_in_lift_pushrod2[\"steps\"]==6)].tail(1)\n",
    "    step_7=data_in_lift_pushrod2[(data_in_lift_pushrod2[\"change_flag\"]==change_flag)&(data_in_lift_pushrod2[\"steps\"]==7)]\n",
    "    step_8_first=data_in_lift_pushrod2[(data_in_lift_pushrod2[\"change_flag\"]==change_flag)&(data_in_lift_pushrod2[\"steps\"]==8)]\n",
    "    step_6_7_8=pd.concat([step_6_last,step_7,step_8_first],axis=0,ignore_index=True)\n",
    "    act_first=step_6_7_8[step_6_7_8[\"pushrod2_retracted\"]==1].tail(1)\n",
    "    act_last=step_6_7_8[step_6_7_8[\"pushrod2_extended\"]==1].head(1)\n",
    "    union=pd.concat([step_6_last,act_first,act_last],axis=0,ignore_index=True)\n",
    "    union_t2=pd.concat([union_t2,union],axis=0,ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(414, 5)"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "union_t2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "union_t2[\"time2\"]=union_t2[\"time\"].shift(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "result2=union_t2.groupby('change_flag').tail(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1248361/1867648687.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  result2[\"time_delta\"]=pd.to_timedelta(pd.to_datetime(result2[\"time\"])-pd.to_datetime(result2[\"time2\"])).dt.total_seconds()\n"
     ]
    }
   ],
   "source": [
    "result2[\"time_delta\"]=pd.to_timedelta(pd.to_datetime(result2[\"time\"])-pd.to_datetime(result2[\"time2\"])).dt.total_seconds()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "###反应时间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "result_f2 =result2.groupby('change_flag').head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result_f2[\"time_delta\"].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    138.000000\n",
       "mean       0.136957\n",
       "std        0.054137\n",
       "min        0.000000\n",
       "25%        0.100000\n",
       "50%        0.100000\n",
       "75%        0.200000\n",
       "max        0.300000\n",
       "Name: time_delta, dtype: float64"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_f2[\"time_delta\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "##运动时间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "result_r2 =result2.groupby('change_flag').tail(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result_r2[\"time_delta\"].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    138.000000\n",
       "mean       2.781159\n",
       "std        0.127039\n",
       "min        2.600000\n",
       "25%        2.700000\n",
       "50%        2.800000\n",
       "75%        2.800000\n",
       "max        4.100000\n",
       "Name: time_delta, dtype: float64"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_r2[\"time_delta\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "result_r_n2=result_r2[result_r2[\"steps\"]==8]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(134, 7)"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_r_n2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(138, 7)"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_r2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "result_r_n2   ##134次"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "####对推杆3分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_in_lift_pushrod3=data_in_lift[[\"time\",\"change_flag\",\"steps\",\"pushrod3_retracted\",\"pushrod3_extended\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "union_t3=pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "for  change_flag in ll:\n",
    "    ##第4步最后一条\n",
    "    step_6_last=data_in_lift_pushrod3[(data_in_lift_pushrod3[\"change_flag\"]==change_flag)&(data_in_lift_pushrod3[\"steps\"]==6)].tail(1)\n",
    "    step_7=data_in_lift_pushrod3[(data_in_lift_pushrod3[\"change_flag\"]==change_flag)&(data_in_lift_pushrod3[\"steps\"]==7)]\n",
    "    step_8_first=data_in_lift_pushrod3[(data_in_lift_pushrod3[\"change_flag\"]==change_flag)&(data_in_lift_pushrod3[\"steps\"]==8)]\n",
    "    step_6_7_8=pd.concat([step_6_last,step_7,step_8_first],axis=0,ignore_index=True)\n",
    "    act_first=step_6_7_8[step_6_7_8[\"pushrod3_retracted\"]==1].tail(1)\n",
    "    act_last=step_6_7_8[step_6_7_8[\"pushrod3_extended\"]==1].head(1)\n",
    "    union=pd.concat([step_6_last,act_first,act_last],axis=0,ignore_index=True)\n",
    "    union_t3=pd.concat([union_t3,union],axis=0,ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "union_t3[\"time2\"]=union_t3[\"time\"].shift(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "result3=union_t3.groupby('change_flag').tail(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1248361/1586312081.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  result3[\"time_delta\"]=pd.to_timedelta(pd.to_datetime(result3[\"time\"])-pd.to_datetime(result3[\"time2\"])).dt.total_seconds()\n"
     ]
    }
   ],
   "source": [
    "result3[\"time_delta\"]=pd.to_timedelta(pd.to_datetime(result3[\"time\"])-pd.to_datetime(result3[\"time2\"])).dt.total_seconds()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "###反应时间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "result_f3=result3.groupby('change_flag').head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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1X3V2b3SFF/sq1fZHV6Tq3kqGRM3qwFcuYhFXfGzatEm7du3SaaedFjnW1tam1157TQ899JBeffVV7d+/X7t374569aOpqUn5+fkdXjMQCCgQCLQ77vf7E7aBEnnt7uZImlWwrWvhEAz7unyNeKXqv02q7Svrf9eo++7CvkqlGXsl1fZWMnk9q3iuFVd8XHDBBXr33Xejjk2bNk1DhgzRHXfcoaKiIvn9ftXX12vSpEmSpK1bt+qTTz5RSUlJPHcFAAC6qbjiIysrSyeffHLUsd69e6tfv36R41dffbUqKirUt29fZWdn68Ybb1RJSUmH32wKAACOPJ36aZeDeeCBB5SWlqZJkyYpGAyqrKxMDz/8sNd3AwAAUlSX42P16tVR72dmZmrJkiVasmRJVy8NAAC6IX63CwAAMEV8AAAAU8QHAAAwRXwAAABTxAcAADBFfAAAAFPEBwAAMEV8AAAAU8QHAAAwRXwAAABTxAcAADBFfAAAAFPEBwAAMEV8AAAAU8QHAAAwRXwAAABTxAcAADBFfAAAAFPEBwAAMEV8AAAAU8QHAAAwRXwAAABTxAcAADBFfAAAAFPEBwAAMEV8AAAAU8QHAAAwRXwAAABTxAcAADBFfAAAAFPEBwAAMEV8AAAAU8QHAAAwRXwAAABTxAcAADBFfAAAAFPEBwAAMEV8AAAAU8QHAAAwRXwAAABTxAcAADBFfAAAAFPEBwAAMEV8AAAAU8QHAAAwRXwAAABTxAcAADBFfAAAAFPEBwAAMEV8AAAAU8QHAAAwRXwAAABTxAcAADBFfAAAAFPEBwAAMEV8AAAAU8QHAAAwRXwAAABTxAcAADBFfAAAAFPEBwAAMEV8AAAAU8QHAAAwRXwAAABTxAcAADBFfAAAAFPEBwAAMBVXfMyfP1+nn366srKyNGDAAF166aXaunVr1Dn79u1TeXm5+vXrp6OOOkqTJk1SU1OTp4sGAACpK674WLNmjcrLy7Vu3TrV1dUpFApp/Pjx2rt3b+Scm2++WS+99JKeffZZrVmzRjt37tRll13m+cIBAEBq6hHPyStXrox6/4knntCAAQO0adMmnXPOOWpubtZjjz2m2tpanX/++ZKk5cuX68QTT9S6det0xhlneLdyAACQkuKKj/+vublZktS3b19J0qZNmxQKhVRaWho5Z8iQIRo4cKAaGho6jI9gMKhgMBh5v6WlRZIUCoUUCoW6srx2DlzP6+t2R0firALprnO3S3NRf1pKtX+fVN1Xnd0bXbpPD/ZVqs25K1J1byVDomYVz/V8zrlO7exwOKxLLrlEu3fv1uuvvy5Jqq2t1bRp06JiQpJGjx6t7373u1q4cGG761RVVWnOnDntjtfW1qpXr16dWRoAADDW2tqqKVOmqLm5WdnZ2Qc9t9OvfJSXl+u9996LhEdnVVZWqqKiIvJ+S0uLioqKNH78+EMuPl6hUEh1dXUaN26c/H6/p9fubo7EWZ1c9WqnbhdIc5o3KqyZb6YpGPZ5vKqDe6+qzPT+uipV91Vn90ZXeLGvUm1/dEWq7q1kSNSsDnzlIhadio8bbrhBv//97/Xaa6/p6KOPjhzPz8/X/v37tXv3buXm5kaONzU1KT8/v8NrBQIBBQKBdsf9fn/CNlAir93dHEmzCrZ1LRyCYV+XrxGvVP23SbV9Zf3vGnXfXdhXqTRjr6Ta3komr2cVz7Xi+mkX55xuuOEGPf/88/rTn/6k4uLiqI+PHDlSfr9f9fX1kWNbt27VJ598opKSknjuCgAAdFNxvfJRXl6u2tpavfjii8rKylJjY6MkKScnRz179lROTo6uvvpqVVRUqG/fvsrOztaNN96okpISftIFAABIijM+li5dKkk677zzoo4vX75cV111lSTpgQceUFpamiZNmqRgMKiysjI9/PDDniwWAACkvrjiI5YfjMnMzNSSJUu0ZMmSTi8KAAB0X/xuFwAAYIr4AAAApogPAABgivgAAACmiA8AAGCK+AAAAKaIDwAAYIr4AAAApogPAABgivgAAACmiA8AAGCK+AAAAKaIDwAAYIr4AAAApogPAABgivgAAACmiA8AAGCK+AAAAKaIDwAAYIr4AAAApogPAABgivgAAACmiA8AAGCK+AAAAKaIDwAAYIr4AAAApogPAABgivgAAACmiA8AAGCK+AAAAKaIDwAAYIr4AAAApogPAABgivgAAACmiA8AAGCK+AAAAKaIDwAAYIr4AAAApogPAABgivgAAACmiA8AAGCK+AAAAKaIDwAAYIr4AAAApogPAABgivgAAACmiA8AAGCK+AAAAKaIDwAAYIr4AAAApogPAABgivgAAACmiA8AAGCK+AAAAKaIDwAAYIr4AAAApogPAABgivgAAACmiA8AAGCK+AAAAKaIDwAAYIr4AAAApogPAABgqkeyF5AMJ1e9qmCbL9nLiNnfFkxI9hIAAPAMr3wAAABTxAcAADBFfAAAAFMJ+56PJUuW6L777lNjY6NOOeUULV68WKNHj07U3QEAkBSD73w52UuISyDdqTrJn44T8srH008/rYqKCs2ePVtvvfWWTjnlFJWVlWnXrl2JuDsAAJBCEhIfixYt0jXXXKNp06bppJNO0iOPPKJevXrp8ccfT8TdAQCAFOL5l13279+vTZs2qbKyMnIsLS1NpaWlamhoaHd+MBhUMBiMvN/c3CxJ+vLLLxUKhTxdWygUUmtrq3qE0tQWTp0ftf3iiy/M7/PArL744gv5/X7z+0+GHv/Z27nbhZ1aW8NJ2VfJ2Btdkar7qrN7o0v36cG+SrX90RXJ3FvJ2B9dcWBveT2rPXv2SJKcc4c+2Xnss88+c5Lc2rVro47fdtttbvTo0e3Onz17tpPEG2+88cYbb7x1g7cdO3YcshWS/h8Zq6ysVEVFReT9cDisL7/8Uv369ZPP5+3/i2xpaVFRUZF27Nih7OxsT6/d3TCr2DGr2DGr2DGr+DCv2CVqVs457dmzR4WFhYc81/P46N+/v9LT09XU1BR1vKmpSfn5+e3ODwQCCgQCUcdyc3O9XlaU7OxsNmeMmFXsmFXsmFXsmFV8mFfsEjGrnJycmM7z/BtOMzIyNHLkSNXX10eOhcNh1dfXq6SkxOu7AwAAKSYhX3apqKjQ1KlTNWrUKI0ePVo1NTXau3evpk2bloi7AwAAKSQh8XH55Zfr888/16xZs9TY2KgRI0Zo5cqVysvLS8TdxSwQCGj27NntvsyD9phV7JhV7JhV7JhVfJhX7A6HWfmci+VnYgAAALzB73YBAACmiA8AAGCK+AAAAKaIDwAAYCql42PJkiUaPHiwMjMzNWbMGG3YsOGg5z/77LMaMmSIMjMzNWzYML3yyitRH3fOadasWSooKFDPnj1VWlqqbdu2JfIhmPJ6XldddZV8Pl/U24UXXpjIh2Amnlm9//77mjRpkgYPHiyfz6eampouXzOVeD2rqqqqdvtqyJAhCXwEduKZ1bJly3T22WerT58+6tOnj0pLS9ud352fs7yeFc9XX3vuuec0atQo5ebmqnfv3hoxYoR+9atfRZ1jsq88+HUuSbFixQqXkZHhHn/8cff++++7a665xuXm5rqmpqYOz3/jjTdcenq6q66udlu2bHEzZsxwfr/fvfvuu5FzFixY4HJyctwLL7zg3nnnHXfJJZe44uJi9+9//9vqYSVMIuY1depUd+GFF7p//OMfkbcvv/zS6iElTLyz2rBhg7v11lvdU0895fLz890DDzzQ5WumikTMavbs2W7o0KFR++rzzz9P8CNJvHhnNWXKFLdkyRK3efNm98EHH7irrrrK5eTkuE8//TRyTnd9zkrErHi++tqf//xn99xzz7ktW7a4jz76yNXU1Lj09HS3cuXKyDkW+ypl42P06NGuvLw88n5bW5srLCx08+fP7/D8yZMnuwkTJkQdGzNmjLvuuuucc86Fw2GXn5/v7rvvvsjHd+/e7QKBgHvqqacS8AhseT0v577+H/PEiRMTst5kindW/2vQoEEdfkLtyjUPZ4mY1ezZs90pp5zi4SoPD13dA//5z39cVlaW++Uvf+mc697PWV7Pyjmerw7m1FNPdTNmzHDO2e2rlPyyy/79+7Vp0yaVlpZGjqWlpam0tFQNDQ0d3qahoSHqfEkqKyuLnL99+3Y1NjZGnZOTk6MxY8Z84zVTRSLmdcDq1as1YMAAfec739H111+f8r/CuzOzSsY1DweJfFzbtm1TYWGhjjnmGF155ZX65JNPurrcpPJiVq2trQqFQurbt6+k7vuclYhZHcDzVTTnnOrr67V161adc845kuz2VUrGxz//+U+1tbW1+y+m5uXlqbGxscPbNDY2HvT8A3/Gc81UkYh5SdKFF16oJ598UvX19Vq4cKHWrFmjiy66SG1tbd4/CCOdmVUyrnk4SNTjGjNmjJ544gmtXLlSS5cu1fbt23X22Wdrz549XV1y0ngxqzvuuEOFhYWRTwrd9TkrEbOSeL76X83NzTrqqKOUkZGhCRMmaPHixRo3bpwku32VkP+8Oo4MV1xxReTvw4YN0/Dhw3Xsscdq9erVuuCCC5K4MqSyiy66KPL34cOHa8yYMRo0aJCeeeYZXX311UlcWfIsWLBAK1as0OrVq5WZmZns5RzWvmlWPF/9V1ZWlt5++2199dVXqq+vV0VFhY455hidd955ZmtIyVc++vfvr/T0dDU1NUUdb2pqUn5+foe3yc/PP+j5B/6M55qpIhHz6sgxxxyj/v3766OPPur6opOkM7NKxjUPB1aPKzc3VyeccMIRu6/uv/9+LViwQKtWrdLw4cMjx7vrc1YiZtWRI/n5Ki0tTccdd5xGjBihW265Rd///vc1f/58SXb7KiXjIyMjQyNHjlR9fX3kWDgcVn19vUpKSjq8TUlJSdT5klRXVxc5v7i4WPn5+VHntLS0aP369d94zVSRiHl15NNPP9UXX3yhgoICbxaeBJ2ZVTKueTiwelxfffWVPv744yNyX1VXV2vevHlauXKlRo0aFfWx7vqclYhZdYTnq/8Kh8MKBoOSDPeVZ9+6amzFihUuEAi4J554wm3ZssVde+21Ljc31zU2NjrnnPvRj37k7rzzzsj5b7zxhuvRo4e7//773QcffOBmz57d4Y/a5ubmuhdffNH95S9/cRMnTuwWP7bmnPfz2rNnj7v11ltdQ0OD2759u/vjH//oTjvtNHf88ce7ffv2JeUxeiXeWQWDQbd582a3efNmV1BQ4G699Va3efNmt23btpivmaoSMatbbrnFrV692m3fvt298cYbrrS01PXv39/t2rXL/PF5Kd5ZLViwwGVkZLjf/OY3UT8eumfPnqhzuuNzltez4vnqv7O699573apVq9zHH3/stmzZ4u6//37Xo0cPt2zZssg5FvsqZePDOecWL17sBg4c6DIyMtzo0aPdunXrIh8799xz3dSpU6POf+aZZ9wJJ5zgMjIy3NChQ93LL78c9fFwOOxmzpzp8vLyXCAQcBdccIHbunWrxUMx4eW8Wltb3fjx4923vvUt5/f73aBBg9w111yT8p9MD4hnVtu3b3eS2r2de+65MV8zlXk9q8svv9wVFBS4jIwM9+1vf9tdfvnl7qOPPjJ8RIkTz6wGDRrU4axmz54dOac7P2d5OSuer6ZG3v/Zz37mjjvuOJeZmen69OnjSkpK3IoVK6KuZ7GvfM45593rKAAAAAeXkt/zAQAAUhfxAQAATBEfAADAFPEBAABMER8AAMAU8QEAAEwRHwAAwBTxAQAATBEfAADAFPEBAABMER8AAMAU8QEAAEz9H5mfMhEDQOGUAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result_f3[\"time_delta\"].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    138.000000\n",
       "mean       0.165217\n",
       "std        0.052182\n",
       "min        0.000000\n",
       "25%        0.100000\n",
       "50%        0.200000\n",
       "75%        0.200000\n",
       "max        0.300000\n",
       "Name: time_delta, dtype: float64"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_f3[\"time_delta\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "##运动时间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "result_r3 =result3.groupby('change_flag').tail(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result_r3[\"time_delta\"].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    138.000000\n",
       "mean       2.608696\n",
       "std        0.058545\n",
       "min        2.500000\n",
       "25%        2.600000\n",
       "50%        2.600000\n",
       "75%        2.600000\n",
       "max        2.800000\n",
       "Name: time_delta, dtype: float64"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_r3[\"time_delta\"].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "result_r_n3=result_r3[result_r3[\"steps\"]==8]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>change_flag</th>\n",
       "      <th>steps</th>\n",
       "      <th>pushrod3_retracted</th>\n",
       "      <th>pushrod3_extended</th>\n",
       "      <th>time2</th>\n",
       "      <th>time_delta</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2023-06-13 03:10:39.186</td>\n",
       "      <td>40</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-06-13 03:10:36.486</td>\n",
       "      <td>2.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>2023-06-13 03:55:48.186</td>\n",
       "      <td>54</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-06-13 03:55:45.486</td>\n",
       "      <td>2.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>305</th>\n",
       "      <td>2023-06-13 11:33:55.186</td>\n",
       "      <td>206</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-06-13 11:33:52.386</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>410</th>\n",
       "      <td>2023-06-13 15:50:11.486</td>\n",
       "      <td>276</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-06-13 15:50:08.886</td>\n",
       "      <td>2.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        time  change_flag  steps  pushrod3_retracted  \\\n",
       "59   2023-06-13 03:10:39.186           40      8                   0   \n",
       "80   2023-06-13 03:55:48.186           54      8                   0   \n",
       "305  2023-06-13 11:33:55.186          206      8                   0   \n",
       "410  2023-06-13 15:50:11.486          276      8                   0   \n",
       "\n",
       "     pushrod3_extended                    time2  time_delta  \n",
       "59                   1  2023-06-13 03:10:36.486         2.7  \n",
       "80                   1  2023-06-13 03:55:45.486         2.7  \n",
       "305                  1  2023-06-13 11:33:52.386         2.8  \n",
       "410                  1  2023-06-13 15:50:08.886         2.6  "
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_r_n3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4, 7)"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_r_n3.shape                  ###4次"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "###反应时间拼接"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "f2=result_f2[[\"change_flag\",\"time_delta\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/module/anaconda2022-10/envs/py3916/lib/python3.9/site-packages/pandas/core/frame.py:5034: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().rename(\n"
     ]
    }
   ],
   "source": [
    "f2.rename(columns={ 'time_delta': 'f2time'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "f3=result_f3[[\"change_flag\",\"time_delta\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/module/anaconda2022-10/envs/py3916/lib/python3.9/site-packages/pandas/core/frame.py:5034: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().rename(\n"
     ]
    }
   ],
   "source": [
    "f3.rename(columns={ 'time_delta': 'f3time'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "f_u=pd.merge(f2, f3, on=['change_flag'],how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "138"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(f_u)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "nl=[i+1 for i in range(138)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "f_u[\"change_flag\"]=nl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.figure(figsize=(16,4))\n",
    "plt.plot(f_u[\"change_flag\"], f_u[\"f2time\"], label='pushrod2',color='b')\n",
    "plt.plot(f_u[\"change_flag\"], f_u[\"f3time\"], label='pushrod3',color='r')\n",
    "\n",
    "# 添加图例\n",
    "plt.legend()\n",
    "\n",
    "# 添加标题和标签\n",
    "plt.title('pushrod_reaction_time')\n",
    "plt.xlabel('change_sn')\n",
    "plt.ylabel('reaction_time')\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/module/anaconda2022-10/envs/py3916/lib/python3.9/site-packages/pandas/core/frame.py:5034: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().rename(\n"
     ]
    }
   ],
   "source": [
    "r2=result_r2[[\"change_flag\",\"time_delta\"]]\n",
    "r2.rename(columns={ 'time_delta': 'r2time'}, inplace=True)\n",
    "r3=result_r3[[\"change_flag\",\"time_delta\"]]\n",
    "r3.rename(columns={ 'time_delta': 'r3time'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "r_u=pd.merge(r2, r3, on=['change_flag'],how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "r_u[\"change_flag\"]=nl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.figure(figsize=(16,4))\n",
    "plt.plot(r_u[\"change_flag\"], r_u[\"r2time\"], label='pushrod2',color='r')\n",
    "plt.plot(r_u[\"change_flag\"], r_u[\"r3time\"], label='pushrod3',color='b')\n",
    "\n",
    "# 添加图例\n",
    "plt.legend()\n",
    "\n",
    "# 添加标题和标签\n",
    "plt.title('pushrod_move_time')\n",
    "plt.xlabel('change_sn')\n",
    "plt.ylabel('move_time')\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [],
   "source": [
    "###收回的分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "back_list=[10,11,12]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_in_back=data_in[data_in[\"steps\"].isin(back_list)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_in_back_pushrod2=data_in_back[[\"time\",\"change_flag\",\"steps\",\"pushrod2_retracted\",\"pushrod2_extended\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [],
   "source": [
    "union_t22=pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [],
   "source": [
    "for  change_flag in ll:\n",
    "    ##第10步最后一条\n",
    "    step_10_last=data_in_back_pushrod2[(data_in_back_pushrod2[\"change_flag\"]==change_flag)&(data_in_back_pushrod2[\"steps\"]==10)].tail(1)\n",
    "    step_11=data_in_back_pushrod2[(data_in_back_pushrod2[\"change_flag\"]==change_flag)&(data_in_back_pushrod2[\"steps\"]==11)]\n",
    "    step_12_first=data_in_back_pushrod2[(data_in_back_pushrod2[\"change_flag\"]==change_flag)&(data_in_back_pushrod2[\"steps\"]==12)]\n",
    "    step_10_11_12=pd.concat([step_10_last,step_11,step_12_first],axis=0,ignore_index=True)\n",
    "    act_first=step_10_11_12[step_10_11_12[\"pushrod2_extended\"]==1].tail(1)\n",
    "    act_last=step_10_11_12[step_10_11_12[\"pushrod2_retracted\"]==1].head(1)\n",
    "    union=pd.concat([step_10_last,act_first,act_last],axis=0,ignore_index=True)\n",
    "    union_t22=pd.concat([union_t22,union],axis=0,ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1248361/1543413903.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  result22[\"time_delta\"]=pd.to_timedelta(pd.to_datetime(result22[\"time\"])-pd.to_datetime(result22[\"time2\"])).dt.total_seconds()\n"
     ]
    }
   ],
   "source": [
    "union_t22[\"time2\"]=union_t22[\"time\"].shift(1)\n",
    "result22=union_t22.groupby('change_flag').tail(2)\n",
    "result22[\"time_delta\"]=pd.to_timedelta(pd.to_datetime(result22[\"time\"])-pd.to_datetime(result22[\"time2\"])).dt.total_seconds()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [],
   "source": [
    "##反应时间"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [],
   "source": [
    "result_f22 =result22.groupby('change_flag').head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result_f22[\"time_delta\"].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [],
   "source": [
    "result_r22 =result22.groupby('change_flag').tail(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result_r22[\"time_delta\"].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_in_back_pushrod3=data_in_back[[\"time\",\"change_flag\",\"steps\",\"pushrod3_retracted\",\"pushrod3_extended\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [],
   "source": [
    "union_t33=pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [],
   "source": [
    "for  change_flag in ll:\n",
    "    ##第10步最后一条\n",
    "    step_10_last=data_in_back_pushrod3[(data_in_back_pushrod3[\"change_flag\"]==change_flag)&(data_in_back_pushrod3[\"steps\"]==10)].tail(1)\n",
    "    step_11=data_in_back_pushrod3[(data_in_back_pushrod3[\"change_flag\"]==change_flag)&(data_in_back_pushrod3[\"steps\"]==11)]\n",
    "    step_12_first=data_in_back_pushrod3[(data_in_back_pushrod3[\"change_flag\"]==change_flag)&(data_in_back_pushrod3[\"steps\"]==12)]\n",
    "    step_10_11_12=pd.concat([step_10_last,step_11,step_12_first],axis=0,ignore_index=True)\n",
    "    act_first=step_10_11_12[step_10_11_12[\"pushrod3_extended\"]==1].tail(1)\n",
    "    act_last=step_10_11_12[step_10_11_12[\"pushrod3_retracted\"]==1].head(1)\n",
    "    union=pd.concat([step_10_last,act_first,act_last],axis=0,ignore_index=True)\n",
    "    union_t33=pd.concat([union_t33,union],axis=0,ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1248361/3881404604.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  result33[\"time_delta\"]=pd.to_timedelta(pd.to_datetime(result22[\"time\"])-pd.to_datetime(result22[\"time2\"])).dt.total_seconds()\n"
     ]
    }
   ],
   "source": [
    "union_t33[\"time2\"]=union_t33[\"time\"].shift(1)\n",
    "result33=union_t33.groupby('change_flag').tail(2)\n",
    "result33[\"time_delta\"]=pd.to_timedelta(pd.to_datetime(result22[\"time\"])-pd.to_datetime(result22[\"time2\"])).dt.total_seconds()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [],
   "source": [
    "result_f33 =result33.groupby('change_flag').head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result_f33[\"time_delta\"].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [],
   "source": [
    "result_r33 =result33.groupby('change_flag').tail(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result_r33[\"time_delta\"].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "##拼接"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/module/anaconda2022-10/envs/py3916/lib/python3.9/site-packages/pandas/core/frame.py:5034: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().rename(\n"
     ]
    }
   ],
   "source": [
    "f22=result_f22[[\"change_flag\",\"time_delta\"]]\n",
    "f22.rename(columns={ 'time_delta': 'f2time'}, inplace=True)\n",
    "f33=result_f33[[\"change_flag\",\"time_delta\"]]\n",
    "f33.rename(columns={ 'time_delta': 'f3time'}, inplace=True)\n",
    "f_u=pd.merge(f22, f33, on=['change_flag'],how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [],
   "source": [
    "f_u[\"change_flag\"]=nl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.figure(figsize=(16,4))\n",
    "plt.plot(f_u[\"change_flag\"], f_u[\"f2time\"], label='pushrod2',color='b')\n",
    "plt.plot(f_u[\"change_flag\"], f_u[\"f3time\"], label='pushrod3',color='r')\n",
    "\n",
    "# 添加图例\n",
    "plt.legend()\n",
    "\n",
    "# 添加标题和标签\n",
    "plt.title('pushrod_reaction_time')\n",
    "plt.xlabel('change_sn')\n",
    "plt.ylabel('reaction_time')\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/module/anaconda2022-10/envs/py3916/lib/python3.9/site-packages/pandas/core/frame.py:5034: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().rename(\n"
     ]
    }
   ],
   "source": [
    "r22=result_r22[[\"change_flag\",\"time_delta\"]]\n",
    "r22.rename(columns={ 'time_delta': 'r2time'}, inplace=True)\n",
    "r33=result_r33[[\"change_flag\",\"time_delta\"]]\n",
    "r33.rename(columns={ 'time_delta': 'r3time'}, inplace=True)\n",
    "r_u=pd.merge(r22, r33, on=['change_flag'],how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [],
   "source": [
    "r_u[\"change_flag\"]=nl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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DQyHX+dWvfoXp06cjJycHq1atwvbt2xP1axBCCCGEEEIIIYQQg+KJuCPpwarnMKWvhK1bt2LdunV455138Prrr8Pr9eKss85Cf39/xNs8+eSTuOmmm3Dbbbdh//79ePTRR7Fp0yb86Ec/0q6zadMm3Hjjjbjtttuwe/duLFmyBGeffTba2tqS8WsRQgghhBBCCCGEEEJ0SukC5SuvvIK1a9di4cKFWLJkCR5//HFIkoRdu3ZFvM3bb7+N1atX47LLLsP06dNx1lln4dJLLw2JkLzvvvtw7bXX4qqrrsKCBQvw61//Gnl5eXjssceS8WuRSWKwaxB//MY2tO/vSPVQCJkyFL+Cv373bXy8RUr1UAghhBBCCCGEJElaxdLKsgwAKC4ujnidT37yk9i1a5e2IPnxxx/jpZdewnnnnQeA1THYtWsXzjjjDO02drsdZ5xxBv7973+Hvc/h4WH09PSEfBHy++u348rfnIo7L/kw1UMhZMr4168/wMX3fxLXfYk2BgghhBBCCCFTj81mw9/+9rekPNaWLVtgs9ng8XiS8njRpM0Cpd/vx3e+8x2sXr0aixYtini9yy67DHfccQdOPfVUZGZmYtasWVizZo2W4t3R0QGfz4eKioqQ21VUVKClpSXsfW7YsAGCIGhfdXV11v1iZMLa/xH7t749O7UDIWQKkT7sBQDU901L8UgIIYQQQgghZGrZsmULvvCFL6Cqqgr5+fk46aST8Oc//zkpj502C5Tr1q3Dvn378Je//CXq9bZs2YK77roLDz30EHbv3o1nn30WL774Iu68807Tj33zzTdDlmXtq76+3vR9kclDamfdp+RBWqAkJFnkLh/715ef4pEQQgghhBBCSPpTFAWjo6OW3Nfbb7+NxYsX45lnnsH777+Pq666CldeeSVeeOEFS+4/mrRYoFy/fj1eeOEFbN68GbW1tVGve8stt+CrX/0qrrnmGpx44on44he/iLvuugsbNmyA3+9HaWkpHA4HWltbQ27X2tqKysrKsPeZnZ2NoqKikC9CJFkAAMjDOSkeCSFTh9ztZ//6C1M8EkIIIYQQQkhSKQrQ35/8L0UxNMw1a9Zg/fr1WL9+PQRBQGlpKW655RYo6v2ES9F2Op14/PHHAbDShOvXr0dVVRVycnLgcrmwYcOGkOt3dHTgi1/8IvLy8jBnzhw8//zz2s94WvbLL7+MZcuWITs7G9u2bcPw8DC+/e1vo7y8HDk5OTj11FOxY8eOkPt96aWXMHfuXOTm5uLTn/40jh8/HvLzH/3oR7jzzjvxyU9+ErNmzcINN9yAc845B88++6yhv5EZKV2gVBQF69evx3PPPYd//OMfmDFjRszbDAwMjGth7nA4tPvLysrCsmXL8Oabb2o/9/v9ePPNN3HKKadY+wuQSU0aKgcAyN68FI+EkKlDLUWMIeRipG8ktYMhhBBCCCGEJM/AAFBQkPyvgQHDQ33iiSeQkZGB7du344EHHsB9992H3/3ud7pu+4tf/ALPP/88/vrXv+LgwYP485//jOnTp4dc5/bbb8dFF12E999/H+eddx4uv/xydHV1hVznpptuwt133439+/dj8eLF+MEPfoBnnnkGTzzxBHbv3o3Zs2fj7LPP1m5XX1+PL33pSzj//POxd+9eXHPNNbjppptijleW5ai9YqySkfBHiGLdunV48skn8fe//x2FhYVajUhBEJCbmwsAuPLKK1FTU6OtJp9//vm47777cPLJJ2PVqlU4cuQIbrnlFpx//vnaQuWNN96Ir33ta1i+fDlWrlyJ+++/H/39/bjqqqtS84uSCaevpQ9dCnsDUqopIckj9wY2oOT6HpTNL03haAghhBBCCCFkvLq6Ovz85z+HzWbDvHnz8MEHH+DnP/85rr322pi3lSQJc+bMwamnngqbzQaXyzXuOmvXrsWll14KALjrrrvwi1/8Atu3b8c555yjXeeOO+7AmWeeCQDo7+/Hww8/jMcffxznnnsuAOCRRx7B66+/jkcffRTf//738fDDD2PWrFnYuHEjAGjjvueeeyKO9a9//St27NiB3/zmN/r/OCaldIHy4YcfBsDCY4P9/ve/x9q1awGwJy44YvLHP/4xbDYbfvzjH6OxsRFlZWU4//zz8bOf/Uy7zsUXX4z29nbceuutaGlpwUknnYRXXnllXOMcQiKp39kKoAAAICtFUPwKbHZbagdFyBQg9zkC/2/qpwVKQgghhBBCpoq8PKCvLzWPa9AnPvEJ2GyBNYJTTjkFGzduhM/ni3nbtWvX4swzz8S8efNwzjnn4HOf+xzOOuuskOssXrxY+39+fj6KiorQ1tYWcp3ly5dr/z969Ci8Xi9Wr16tXZaZmYmVK1di//79AID9+/dj1apVIfcRLdN48+bNuOqqq/DII49g4cKFMX+veKV0gVLRkee/ZcuWkO8zMjJw22234bbbbot6O14PgBAzpPe6tf97kYUhzyByi3NTOCJCpgZ5MDPw/2bjqRaEEEIIIYSQCcpmA/InfgajzWYbt97l9Xq1/y9duhTHjh3Dyy+/jDfeeAMXXXQRzjjjDDz99NPadTIzM0Nub7PZ4Pf7Qy7LT+DfauvWrTj//PPx85//HFdeeWXCHidYWjTJISTdSAdDF0bkht4UjYSQqUUeyg78v3UohSMhhBBCCCGEkPDefffdkO/feecdzJkzBw6HA2VlZWhubtZ+dvjwYQyMqXNZVFSEiy++GI888gg2bdqEZ555ZlyNSSNmzZqFrKws/Otf/9Iu83q92LFjBxYsWAAAmD9/PrZv3z5u3GNt2bIFn/3sZ3HPPffguuuuMz0mo1IaQUlIunJ/HLozITf2oXJxeYpGQ8jUIY8EIpXltuEUjoQQQgghhBBCwpMkCTfeeCP+8z//E7t378aDDz6o1Xb8zGc+g1/+8pc45ZRT4PP58MMf/jAkIvK+++5DVVUVTj75ZNjtdjz11FOorKyE0+k0PZ78/Hx885vfxPe//30UFxdDFEXce++9GBgYwNVXXw0A+MY3voGNGzfi+9//Pq655hrs2rVL6yzObd68GZ/73Odwww034MILL9R6xWRlZSW8UQ5FUBIShtQcunYvtwymaCSETC2yN1D/Re4cTeFICCGEEEIIISS8K6+8EoODg1i5ciXWrVuHG264QYs23LhxI+rq6nDaaafhsssuw/e+9z3kBdW5LCwsxL333ovly5djxYoVOH78OF566aWQ/itm3H333bjwwgvx1a9+FUuXLsWRI0fw6quvYtq0aQAAURTxzDPP4G9/+xuWLFmCX//617jrrrtC7uOJJ57AwMAANmzYgKqqKu3rS1/6Ulxj08Om6CkEOcX09PRAEATIsoyioqJUD4ekwBrnXmyVT9K+f23DLpx507LUDYiQKcJpkyFDAADc/8WtuOHZ01M8IkIIIYQQQojVhoaGcOzYMcyYMQM5OTmpHo4ha9aswUknnYT7778/1UNJC9GeSyPraxRBSUgYUj8LXc7ECABAbh9J5XAImRL8o370oFD7XvbQ/hkhhBBCCCGETAW0QEnIGL4RHxpGKwEA83OOAaBUU0KSoa+lD0rQYUnuSeFgCCGEEEIIIYQkDTXJIWSM1n3t8KISdvgwv6wT79cDcrcv1cMiZNKTG/sABML+5V5H6gZDCCGEEEIIIWFs2bIl1UOYlCiCkpAxpN0dAIAaRwtKBC8AQPakcECETBFyU3/o9/20h0YIIYQQQgghUwEtUBIyhvQhyysV8zohFLIaeHKPLZVDImRKkFsGQ78fzErRSAghhBBCCCGEJBMtUBIyhnSYNcQRi3shsGbC8FCqKSEJ52kdDvleHs5O0UgIIYQQQgghhCQTLVASMoZUz6IlXVVeCNPYW0QeoFRTQhJNbmebA5lg/3pG8lM5HEIIIYQQQgghSUILlISMIbXlAADE6XYIJWxhUh6kSC5CEk3uYs2o6jKa2fc+WqAkhBBCCCGEkKmAFigJGcMts7xucV4uhNJMAIA8nJPKIREyJcjdfgCAq6CLfe8vTOVwCCGEEEIIIYQkCS1QEjKGNFQOABBPFCCUs8hJ2ZuXyiERMiXIMvtXLGHdvIeQi5G+kRSOiBBCCCGEEEKSy2az4W9/+1tSHmvLli2w2WzweDxJebxoaIGSkCB9LX3oUooBAOKKCgiVuQAo1ZSQZJB72SGptnI0cFl9T6qGQwghhBBCCCFTysGDB/HpT38aFRUVyMnJwcyZM/HjH/8YXq834Y9NnT8ICVK/sxVAAYogQxAF9DSzSC5ZKYLiV2Cz21I7QEImMbnPAQAoLgEK0Is+FEJu6kfZ/NIUj4wQQgghhBBC0pOiKPD5fMjIiH+JLzMzE1deeSWWLl0Kp9OJ9957D9deey38fj/uuusuC0YbGUVQEhJEeq8bACBmtwEAhJoCAIAXWRjyDKVsXIRMBfIgq/kqTHNAsPexy5oHUjkkQgghhBBCSJIoCtDfn/wvRTE2zjVr1mD9+vVYv349BEFAaWkpbrnlFijqHYVL0XY6nXj88ccBACMjI1i/fj2qqqqQk5MDl8uFDRs2hFy/o6MDX/ziF5GXl4c5c+bg+eef137G07JffvllLFu2DNnZ2di2bRuGh4fx7W9/G+Xl5cjJycGpp56KHTt2hNzvSy+9hLlz5yI3Nxef/vSncfz48ZCfz5w5E1dddRWWLFkCl8uFz3/+87j88svx1ltvGfsjmUALlIQEkQ6yxRCxyAMAKKgsgA2scYfc0JuqYREyJchDrOarUJIBIVONXm6ljQFCCCGEEEKmgoEBoKAg+V8DJmIinnjiCWRkZGD79u144IEHcN999+F3v/udrtv+4he/wPPPP4+//vWvOHjwIP785z9j+vTpIde5/fbbcdFFF+H999/Heeedh8svvxxdXV0h17nppptw9913Y//+/Vi8eDF+8IMf4JlnnsETTzyB3bt3Y/bs2Tj77LO129XX1+NLX/oSzj//fOzduxfXXHMNbrrppqhjPXLkCF555RWcfvrp+v84JtECJSFBpGNsMVIsGwQA2DPsKAJbmJQb+1I2LkKmAnmE1XwVyrIgZLL3oNw2nMohEUIIIYQQQsg4dXV1+PnPf4558+bh8ssvx7e+9S38/Oc/13VbSZIwZ84cnHrqqXC5XDj11FNx6aWXhlxn7dq1uPTSSzF79mzcdddd6Ovrw/bt20Ouc8cdd+DMM8/ErFmzkJ2djYcffhj//d//jXPPPRcLFizAI488gtzcXDz66KMAgIcffhizZs3Cxo0btXGvXbs27Bg/+clPIicnB3PmzMFpp52GO+64w/gfySBaoCQkiNTEajaItX7tMsGhLlC2DKZkTIRMFbI3DwAgVORAyGGRk3LnaLSbEEIIIYQQQiaJvDygry/5X3l5xsf6iU98AjZboEfFKaecgsOHD8Pn88W87dq1a7F3717MmzcP3/72t/Haa6+Nu87ixYu1/+fn56OoqAhtbW0h11m+fLn2/6NHj8Lr9WL16tXaZZmZmVi5ciX2798PANi/fz9WrVoVch+nnHJK2DFu2rQJu3fvxpNPPokXX3wR//M//xPz94oXNckhJIjUxbp1u2ZnapcJmQOAj1JNCUk02VcIABAqcyHkyuyyrtgHeEIIIYQQQsjEZ7MB+fmpHkX8bDabVo+SC+6CvXTpUhw7dgwvv/wy3njjDVx00UU444wz8PTTT2vXyczMDLm9zWaD3+8PuSw/gX+suro6AMCCBQvg8/lw3XXX4f/9v/8Hh8ORsMekCEpCgkh9xQAAcWGhdpmQpaaato+kZEyETAX+UT96oC5Q1hRAyGeRk7LHYMVqQgghhBBCCEmwd999N+T7d955B3PmzIHD4UBZWRmam5u1nx0+fBgDYwpdFhUV4eKLL8YjjzyCTZs24ZlnnhlXY9KIWbNmISsrC//617+0y7xeL3bs2IEFCxYAAObPnz8uTfydd96Jed9+vx9er3fcAqnVKIKSEJV/1I/60SoAgHhyiXa5kDMM9FCqKSGJ1NfSBwVFAAChthBCodqcqieVoyKEEEIIIYSQ8SRJwo033oj//M//xO7du/Hggw9i48aNAIDPfOYz+OUvf4lTTjkFPp8PP/zhD0MiIu+77z5UVVXh5JNPht1ux1NPPYXKyko4nU7T48nPz8c3v/lNfP/730dxcTFEUcS9996LgYEBXH311QCAb3zjG9i4cSO+//3v45prrsGuXbu0zuLcn//8Z2RmZuLEE09EdnY2du7ciZtvvhkXX3zxuKhOq9ECJSGqlvfb4EUl7PCh+uQK7XJnHgvFlrsp1ZSQRGFNqIqQiRHkOHMgCOrlvYlLISCEEEIIIYQQM6688koMDg5i5cqVcDgcuOGGG3DdddcBADZu3IirrroKp512Gqqrq/HAAw9g165d2m0LCwtx77334vDhw3A4HFixYgVeeukl2O3xJTnffffd8Pv9+OpXv4re3l4sX74cr776KqZNmwYAEEURzzzzDL773e/iwQcfxMqVK3HXXXfh61//unYfGRkZuOeee3Do0CEoigKXy4X169fju9/9blxj08OmjE2MT6INGzbg2WefxYEDB5Cbm4tPfvKTuOeeezBv3ryIt1mzZg22bt067vLzzjsPL774IgBWcPSJJ54I+fnZZ5+NV155Rde4enp6IAgCZFlGUVGRgd+ITGTv/G4fTrl2EeocjZBGa7TL1524FQ/tOx23fmoLbt+6JmXjI2Qy2/fcYZz4pTkotXWg3V+KX35lK7719On4cs2/8VRD+MLNhBBCCCGEkIlpaGgIx44dw4wZM5CTk5Pq4RiyZs0anHTSSbj//vtTPZS0EO25NLK+ltIIyq1bt2LdunVYsWIFRkdH8aMf/QhnnXUWPvroo4jFPp999lmMjARqAXZ2dmLJkiX4yle+EnK9c845B7///e+177OzsxPzS5BJQ/qQ5ZKKeZ0AAguUQiFbw5d7bOFuRgixgNzCar0Kjn4ApRBKWOSkPJiVwlERQgghhBBCCEmGlC5Qjo1ofPzxx1FeXo5du3bhU5/6VNjbFBcXh3z/l7/8BXl5eeMWKLOzs1FZWWntgMmkJh1mC99icW/I5VqqaR/1lCIkUeS2YQCAkMmKRwslrL6JPEybS4QQQgghhBAy2aVVDUpZlgGMX4SM5tFHH8Ull1wyLuJyy5YtKC8vx7Rp0/CZz3wGP/3pT1FSUhL2PoaHhzE8PKx939NDXRmmIqmeRUiKld6Qy4VpbGFS7k9sQVhCpjK5g73vhOwh9m85W5iUvXkpGxMhhBBCCCGEjLVly5ZUD2FSSpuQML/fj+985ztYvXo1Fi1apOs227dvx759+3DNNdeEXH7OOefgD3/4A958803cc8892Lp1K84991z4fOGbnGzYsAGCIGhfdXV1cf8+ZOKR2litBHF6aCq3UMLW8eUhSjUlJFHkzlEAgJCrRlJW5rLLR8OX+yCEEEIIIYQQMnmkTQTlunXrsG/fPmzbtk33bR599FGceOKJWLlyZcjll1xyifb/E088EYsXL8asWbOwZcsW/Md//Me4+7n55ptx4403at/39PTQIuUUJMmsYKs4NzfkcqGUp5pOrMK9hEwkcrcfACDkqQuVVSxyUvYXpmxMhBBCCCGEkMRKYd9mYhGrnsO0iKBcv349XnjhBWzevBm1tbW6btPf34+//OUvuPrqq2Ned+bMmSgtLcWRI0fC/jw7OxtFRUUhX2TqkYbKAQDiYmfI5TzV1DNCkVyEJIrHw/4VCliku1BTAAAYRB5G+kYi3IoQQgghhBAyEWVmskCggYGBFI+ExIs/h/w5NSulEZSKouBb3/oWnnvuOWzZsgUzZszQfdunnnoKw8PDuOKKK2Jet6GhAZ2dnaiqqopnuGQS62/rR6fCapS6VlaE/ExLNfXRAiUhiSL3sv0yoYjtvhXVBCIn5foelM0vTcm4CCGEEEIIIdZzOBxwOp1oa2sDAOTl5cFms8W4FUkniqJgYGAAbW1tcDqdcDgccd1fShco161bhyeffBJ///vfUVhYiJaWFgCAIAjIzWWLQldeeSVqamqwYcOGkNs++uijuOCCC8Y1vunr68Ptt9+OCy+8EJWVlTh69Ch+8IMfYPbs2Tj77LOT84uRCad+ZyuAmSiCDEEUQn4mVLOFSVkpguJXYLPThyYhVpP72MFMUN9+GTkZyEcf+lEAuamfFigJIYQQQgiZZCorKwFAW6QkE5PT6dSey3ikdIHy4YcfBgCsWbMm5PLf//73WLt2LQBAkiTY7aGZ6AcPHsS2bdvw2muvjbtPh8OB999/H0888QQ8Hg+qq6tx1lln4c4770R2dnZCfg8y8UnvdQMAxOw2AGMWKNVUUy+yMOQZRG5x7tibE0LiJA+ydABnSWDXzWnvRb+/AHIzpX0QQgghhBAy2dhsNlRVVaG8vBxerzfVwyEmZGZmxh05yaU8xTuWcO3b582bF/G2ubm5ePXVV+MdGpli3Pv7AQBikWfczwoqC2CDHwrskBt6aYGSkASQh9gGklASOCwJmf1oHAbk1qFUDYsQQgghhBCSYA6Hw7JFLjJxpUWTHEJSTTrGOgiLZYPjfmbPsKMIvQAAubEvqeMiZKqQR9jCv1CWpV0mZLL3o9w2nJIxEUIIIYQQQghJDlqgJASA1MSitsRaf9ifCw51gbJl/AImISR+sjcPACBU5GiXCTksclLuHE3JmAghhBBCCCGEJActUBICQOpijXDEWZlhfy5kshp4lGpKSGLIPta1W6gMlFAQclkdGrnLl5IxEUIIIYQQQghJDlqgJASA1FcMABAXFIT9uZClppq2jyRtTIRMFf5RP3qgLlDWBN6DQj6LnJQ9sesVE0IIIYQQQgiZuGiBkkx5/lE/6kerAADiySVhryPksBp4lGpKiPX6WvqgqIcjobZQu1woZCUX5J6UDIsQQgghhBBCSJLQAiWZ8lr3tcOLLNjhQ/XJFWGvo6WadlOqKSFW482nMjGCHGdQDUpB/XkvdfQjhBBCCCGEkMmMFijJlCftagcA1DhakJkXoQZlAVuYlD3JGhUhU4fc1A8AEGw9sNlt2uWCk/1f7s9IybgIIYQQQgghhCQHLVCSKU/6kHXoFvM6I14nkGpqi3gdQog5cgur8So4+kMuF0pY5KQ8mJX0MRFCCCGEEEIISR5aoCRTnnSY1ZcUi3sjXkdLNe2jtwwhVpPb2HtQyBwIuVwoYRHN8nB20sdECCGEEEIIISR5aLWFTHlSPYuKFCu9Ea8jTGNvFbk/fAo4IcQ8uYO994TsoZDLhXK2MCl785I+JkIIIYQQQgghyUMLlGTKc7eyphzi9Mjp20Kxmmo6RKmmhFhN7hwFAAi5wyGXC5W57Oej+UkfEyGEEEIIIYSQ5KEFSjLlSXIRAECcmxvxOkIZW5iUh3MiXocQYo7czWq8CnmjIZcLVSxyUvYXJn1MhBBCCCGEEEKShxYoyZQnDZUDAMTFzojXoVRTQhJHltm/QoEv5HKhpgAAMIg8eAcil2AghBBCCCGEEDKx0QIlmdL62/rRqZQAAMQVFRGv56yiVFNCEkXuZeUVhCIl5PKimkDkpFzfk9QxEUIIIYQQQghJHlqgJFNa/c5WAEAheiDUFUW8nlDNFiZlJfJ1CCHmyH0ZAABBCL08IycD+ehj12nsS/awCCGEEEIIIYQkCS1QkilNeq8bACBmt8Jmj9IkR001HUE2hjxDEa9HCDFOHsgEEGhGFUyw97LrNA8kdUyEEEIIIYQQQpKHFijJlCYdYIseriJP1OsVVBbABtbIwyNRqikhVvIMsRqvQknGuJ8JGew9KrfSxgAhhBBCCCGETFa0QEmmNOkYa8ohlg1GvZ49w44iqJFclGpKiKXkEVbjVSjLGvczIYstUHpah5M6JkIIIYQQQgghyUMLlGRKk5pYxJZY6495XcGhLlC2RF/MJIQYI3vzAABCefa4nwnZbGFS7hxN6pgIIYQQQgghhCQPLVCSKU3qZM1vxFmZMa8rZFKqKSGJIPtYt26hKm/cz4S8EXadLl9Sx0QIIYQQQgghJHlogZJMaVJfMQBAXFAQ87pCFouclNtHEjomQqYS/6gfPVAXKKvzx/1cyGeRk7JHSeq4CCGEEEIIIYQkDy1QkinLP+pH/WglAEA8uSTm9YUcSjUlxGp9LX1Q1EORUywa93NnISu/IFNvKkIIIYQQQgiZtGiBkkxZrfvaMYJs2OFD9ckVMa8v5HoBAHI3pZoSYhXedCoTI8hx5oz7uSCo1+t1JHNYhBBCCCGEEEKSiBYoyZQl7WoHAFQ7WpGZp6MGZQFbmJQ9iRwVIVOL3NQPABBsPbDZbeN+LjjZZXJ/RlLHRQghhBBCCCEkeVK6QLlhwwasWLEChYWFKC8vxwUXXICDBw9Gvc2aNWtgs9nGfX32s5/VrqMoCm699VZUVVUhNzcXZ5xxBg4fPpzoX4dMMNKHrCu3mNeh6/qClmo6fhGFEGKO3MJquwqO/rA/F0pY5KQ8mJW0MRFCCCGEEEIISa6ULlBu3boV69atwzvvvIPXX38dXq8XZ511Fvr7w5+oAsCzzz6L5uZm7Wvfvn1wOBz4yle+ol3n3nvvxS9+8Qv8+te/xrvvvov8/HycffbZGBqi7sskQDrMakqK0/p0XV9LNe2jwGNCrCK3sfehkDkQ9udCCYtuloezkzYmQgghhBBCCCHJldKVlldeeQVr167FwoULsWTJEjz++OOQJAm7du2KeJvi4mJUVlZqX6+//jry8vK0BUpFUXD//ffjxz/+Mb7whS9g8eLF+MMf/oCmpib87W9/S9JvRuI1OjSKP1//LzTsaE7YY0j1LBJSrNTXlVuYxt4ucn/sdHBCiD5yB6vtKmSH30ASytnCpOzN032fB1/+GM98/9+mxzQ6NIo/ffNfaNyZuM+fWAY6BvCH67ah42BnysYQi3/Uj//91ts4vq3B9H18+Pcj+NvN75q+/UjfCP74jW1oeb/N9H1MBaNDo3j8mm2497wtUb92/Wl/qodKLLDnfw/g5Tt2pHoYJAn6Wvrwh+u2ofuYJ9VDiSgZc3rC7H/hKJ774TupHkZUDTua8eS6f2F0iJqOTnaKX8GmG97G0X+4E/YYnYe78MdvbMNAR/hABzLxpFVRL1mWAbBFSL0effRRXHLJJcjPzwcAHDt2DC0tLTjjjDO06wiCgFWrVuHf//43LrnkknH3MTw8jOHhYe37nh5qF5tqf79lB654eDUufP7feLqhKiGPIbWxhQ/XDH0p20Kxmmo6RKmmhFhF7mQTVCF3OOzPhcpcdr3RfN33ecWXh7Bz4BRsX/QRVnxtgeExPXvzdnz116tx6cv/wpPHE/P5E8tj39yBbz19Ota/sxUPvn96SsYQy2t378Zlv/wkzvnLDrzcXmvqPi65WMG+4VX4YOVhLPriHMO3/8uN2/G1R07Fla9vwxNHy02NYSr4v9t24qpHT415vfJX2tFymRK2HiyZOM6/QkCTfy6On9kI8ZSaVA+HJNCvrtqJm15Zgx++vwV3v7Mm1cMJKxlzesJc+pVRvDf0CexddhBLLpqX6uGE9Z0vHsczjauRV/QuLtiwKtXDIQm09Rfv4ZJffBKnP7EXWzyuhDzGnRd9gAf2ng65cyvWP5We82ViTNosUPr9fnznO9/B6tWrsWjRIl232b59O/bt24dHH31Uu6ylpQUAUFER2pW5oqJC+9lYGzZswO23325y5CQR9u9hixUHOkoT9hiSh+Vsi3NzdV1fKGMLk/Lw+E7DhBBz5G5W21XIC7+TLlSxyEnZX6jr/hS/gv0DIgDgwL+7sOJrxse0fy+Lqq7vLjB+Y4vsP8D+PdCYujHEsn8nK49xwFNp6va+ER8ODrMJ64FtHaYWKPd/wF43B1qdpsYwVezfwyKU52Yewyli47ifKwrwh49PRZtShu5j3SieNS3ZQyQW6WnoQaOfLQIdequVFignuf2H2ancAbe+uWwqJGNOT1hWw4Eh9Zj6r04suSjFA4pgf0cZAKD+MJVem+z2v8uCvg70VifuMepZAEO9pCTsMUhypc0C5bp167Bv3z5s27ZN920effRRnHjiiVi5cmVcj33zzTfjxhtv1L7v6elBXV1dXPdJ4iM1snRq93AlFH9iojmkIXaAFBc7dV3fTKopISQ6NXAeQoEv7M+FGrZAN4g8eAe8yMyLXmKh+5gH/WCLK9JRc+lDUqMaLT2SuhM+qY09ttSrP6Mg2SSJfS43jFbCN+KDI8th6Pat+9rhBVvclI6Ej6CNOYZm9nqQBstM3X6qkBrYMfWSU9y4feuasNd5xd6ONqUM0s42WqCcwOp3tQEoAgBI+yPXdCeTg9TJTs4luSjFI4ksGXN6ArQf6MQw2LFQOqKvfFWyKX4F0jALIpI9tKA02UnHWRBCq78cQ54h5DitD/KRetl8Re6lHhGTRVo8k+vXr8cLL7yAzZs3o7ZWX5pYf38//vKXv+Dqq68Oubyykp3stLa2hlze2tqq/Wys7OxsFBUVhXyR1JLa2SJgHwoh11ufcj/QMYAOhe3kiisqYlybESrYh6qRVFNCSHRyLztREYrCT1SLagKRk3o+C6SdgVqEfFHGKKlTjdpM4WaE1MMivCUvO6FLR1Ir27QZRaapGpDS7o7A/yVzJ6ySGuXa4q/AcI+5Rc6pQOpgC97ijMiLyGJuO7vu+55kDIkkiPRed+D/x8Jv/JDJQ+pjm1jSUPqWuEj0nJ4w0q72wP/r03MR2OOW0Qc2r+Mb1GTy4pvIANCwqzXKNc1R/AqkEba+I/enTdwdiVNKFygVRcH69evx3HPP4R//+AdmzJih+7ZPPfUUhoeHccUVV4RcPmPGDFRWVuLNN9/ULuvp6cG7776LU045xbKxk8TiuyEAIO2w/gOtfgdL9y9ED4Q6fQvSQjVbmJQVWsAmxCpyH5tQCEL4n2fkZCAfLJVYbuyLeX/Biyt8UcYoHrUo+/SllScCjzAYQm7aNsqRPIHPwuDFRt23/zBwosoXOw3fR3+J9v+GneHLuBBA6nECAMQTIi+6i072fEiHKO1uIpMODgb+32QsqplMLP5RP+pH2cl5p1KC/rb0jJhN9JyeMNK+wIqf1J6e5aiCn3+5Ly3ipEgCSUGlkqS9XZbff9fRbgxAPT8fpCa2k0VKPxnWrVuHP/3pT3jyySdRWFiIlpYWtLS0YHAwMLm68sorcfPNN4+77aOPPooLLrgAJSUlIZfbbDZ85zvfwU9/+lM8//zz+OCDD3DllVeiuroaF1xwQaJ/JWIBthsSiGpMRDSHey+LMBCzW3WnmvBU0xFkY8hDJ3CEWEEeYBMK3oQqHMHey67bHLtDX/DiSvBJkV6KX4HkZSd8PSiEf9Rv+D7i1dPQA4/i1L4PjopIJ8Fp1dKHvcZvfziQgmYmPXF0aBSNvkBmRCImv5OB4lfgHmZ/J3FJ5PeEWMEiUCV3ekbsEn14Sh0ASB2U8TGZtX3UgREENnfqd6bf4l8y5vSEkQ4HsggkOcKub4pJHwQWUSnibfIL3kRORMmR4KwpecjcRjdJPyldoHz44YchyzLWrFmDqqoq7WvTpk3adSRJQnNzc8jtDh48iG3bto1L7+Z+8IMf4Fvf+hauu+46rFixAn19fXjllVeQk5Oeu0kkFKshF7TjcmgwyrXNkQ6whQ6xyKP7NoXVhbCBTfzlBuMn44SQ8fiEQiiJPFEVMtj7VW6NvTEQvLgiDVcYTo/uONiJIbDISwV29LXEjtq0GqshFxA8oU8Xg12DaFOCFihN1LsKTkEzU0Oy+b02+IJKaVO9vfDk+h4tpa5uReSGRqLI3itSS1ZSxkUSQ2oOek/0US3RyWzs5lVwen+6SMacnjDBpVLSNeU/OMJbHqBjzWQ2bhP5Y3N14aMJWfBOYd14Yq2Ubl0oSuwTxy1btoy7bN68eVFva7PZcMcdd+COO+6IZ3gkRdhuSFA6yHHrozl4XSaxVP9EyZ5hRyFk9ECA3NiHikXUlIGQeMkjbONIKIs8URWyBoARQG6PvQgWvLjSh0J43B5Mm+HUPR52whfoNCo39qGoNrllHcaeZAZHRaQLVktouva9mXpXUltg07BdKcNg1yByi/VPMFlaeaAzZCImv5MBS6kTUGrrQF5p5C664hy2WSB1p660AYmf1BW0GOStoqYkk5i0L7SeI998TyfJmNMTJrhUSpdSjL6WPhRUFkS5RfIFbyLLwxTxNpmxTeSgOVqj9SVHgrOmqEfE5EHFH0jaGZv+IbVYX1NCamJr82KtsfRNwaHWwmuhHWBCrCB72YRCKI88URWy2QKd3OGNeX9jF1eM1rtyvx8arSg3JT8qLzjCAAAkKf1O6MamU7vbjGcouMekoEnvNke4ZoTb7wuNZOedYkkofkwVc6KXChAXqY2ZBiIvYpL0F5xSN4wctO83Xh+WTAzuQ6GbV+nYFCkZc3rCBNeFBtIz5T94E1keSV0jQpJ4Y2uTSx3WP98hC96+9FqMJ+bRbJ6kHfdBthuSBTbxcndZH80hdbJFEXGWsYmSkVRTQkhssp9NKISqyBMXIY9FTspdsU++3OriCv/8MJoePTZaMRWbEe5jbONE+wxsSb8oA/dHbOFW+zvLTsP3wVPQtPswmJ4oHfWG3N7dTrvn4fCUStEZ/b0gLmNZAU3+CngHYm8GkPTjG/GhQW2aor2v0rSGLYkfj1zXPgMb06+mXzLm9IRxq6VStL/13vRL+Q9+/uVRWqCczPgmsvZ6VBtQWvoYQfPjXhTBN5J+mzTEOFqgJGmH74asKDzIvk9ANIfUxz4kXQuN7bYIWexEz9OafimXhEw0/lE/ZIXt+AvVkReXhHyWuit7okcSjvSNoNnPivHzzw/3AWMLjGOjFeW25L/XpWa2caJ9BnqSm2KuB4/U0cY4bKzeVV9LH7oU9jm8nN+HwfREqcEeOgaqtxeW+xh7TYvl0V/LZSeUIBtDUGCnjugTVPN7bRhFJjLgxZL8IwAAdxrWsCXWkNrYybn2GdiVfps0yZjTE1YXul2tC73C5DE1GYKff9lPi9WTGd9E1l6P3krDdeFjPsaYrKne5uTXjSfWowVKknakVhb+f9pClkLY5LM2msM/6ke9GmEgnlwS49qhnLlsJ1jupFpnhMSrr6UPinoYEmojT1SFAhZR6Ilxnt24uxUK7MjGEJbPYpEDRjsSB9dwAvSllVuN15Djn4FmGsgkmtTEagmduoCNsVuZht4m/c3DeOqZ0+bBibUedp8G0xOldpZWrv2dRqyf/E4GPKXO5Yr+t7Fn2CFmsjR7aU9nwsdFrMdT6mozWjCzmH1gpmMNW2INycPKMmifgX3WRyjFK9FzesLU72CbSoXowWLRAwCQjhsrY5Vo3gEvmvyBju79KMDoEJ1PTVZ8E/mTJ3TBBj+GkIuOg9bOLaTB0A0PamI7OdACJUk7fDdk+anZyMIw/HCgaY91dVTaPurACLJhhw/VJ1fEvkEQIZdNquRuCiEnJF5yI9vpzIA3anMUQS1VKPdGL7DNF1XEzGZtMcZoR2IerZgJNa08BZsRvIbcqWezaJhWfzmGPOlVVkLqYGNbeFIGptnYYrCRelc8nVvMbtVqAfNFT9330eMEAHzyDJYmNog8dB7uinKLqUnqZgve4uzYpQLEAnVhfz9FIUxE0ofs5EzM74RYyT7Dgjv7kslFGmKbV/xYUT9aBf9oei1K8Tn9sk9mIxtDls/pCRN8THXVqcfU5vRK+eebyHx+BQA9jbSgNFnxTeQ5J9hRaW9jl1lYcmS4ZxjNfhZwpM3Zm9MvapgYRwuUJO3w8P/pS5yoy2A7glZGc/APx2pHKzLzDNagLGALk7LHsuEQMmXxBjSCrSdql1nByX4m90efbPNFFbGg23RHYh6tOD/nGHvM7uSe7PlGfGjwsQnXSZ+rRR7Y34h1zU4fPJ1anF8AMVudeI5phhD19gfZJFIskrVawLw2sO77GGIbTHNOKUWlnf19WMdYEowfU8VFsUsFiKXs9SYdpaiWiUg6wk7SxOI+iC72uTk2KpxMDgMdA+hQ2Hv7E5fPgh0+eJGF1n3pVXM0MKcXUJdp/ZyeMNJ+9tktFnkgzmYbs1JnejUN4c+7K7MJuVBr+jfSZthkxTeRxXl5EHNZdL/RuvDRNO5m874cDMKV2QSAmthOFrRASdJKcA05cVkZxAI1beUj6w5g0r4edv95xjtbCoVssULuoYgEQuLFJxKCI/r7WyhmkXXyYPRoSL6oIpb2m+pIPOQZQquf1VI8sZJ9PshJLt/W/F4bfMhAJkZQdVIFxCz1hG5v+kQGKn4FkrcKACuTIQoeAMbqXUlqIyCxfBDiAnYSZSQ9UZZkyGDPcd3yCoi57KScf74TxjvgRZMvcEyNRaxmm3A8NYtMLFIDm5uIVaMQ57LolXSsYUvix1N6iyCjZE4xahzqsSKNmiIlY05PGF4iRSwNOqb2p1fKP3/exYIuCHYWOUkRb5MX30QWl0yDOI0931aWHOHzYjGzBc5MdcE7BXXjifVoBkrSCg//z8EgSueVQCzh0RzW1auRjrAPL3Ga8QmSlmraR28dQuLFJxJCZvQJqlDKIuzk4eiRQHxRRaz2mepIzKMU89CPmXVqOYfe5G5GBNeQs2fYIRbylNv+pI4jmvb9HRhGDmzwo2ZpBcRyln5upN6V1MSiYcVaRasFXO+t1J2eWL+LRUqW2DqRX54P0alOfg+lVyp8qjXtaYUfDmRhGOULYi/WizPYZoDUEbnkAklfUhtblBSn2yEudrLL0rCGLYlfIKWXfRaKeSw6jaf5p4PgutBl80sTMqcnDC+RItb6IS5ln/UNo5Vp1dWYP+9iST+EDPZaoIi3yWncJnIFm++PbUQZD23Bu7ALQrbaIyIFdeOJ9WiVhaSVQA25FtjsNojVLCLKymgOt1uNMKgciXHN8YRpbBxyv7HUcELIeHwiwScWkQjlbGFS9uZFvR5fVBFnOEI6EvM0kFi03dislqDNiOTWcArUkFPHUsoWb6WP0yfllkfoVNlbkVWQBbFWrfdpoN4V7zYrzs5CzdIK2ODHMHLQfkBf6h9PJxdz1JPzSnXya7Ap0mTHj6l16oJ3LOJ89rxIvdQRfSKSZCcAQJyXC3E5iwZvU8ow2EWLAJMNj1gXizzs32LrI5TiFVwXms3pKUI7UXhdaHFWJqqWlMOB0bRL+Q/eRBYo4m1S45vIxbYuFFQWBEqOtFhXcoTPi8WSAQi5ag3KrvSZKxPz6AhB0opWQ65QPTnn0Rzt1kVzSG3sw5F/WBqhpZoOGWu8QQgZjzegceZGn6A6q9j7Xx6NXqOQL6qI8/Nhz7Abrnel1XAq7A681weSuxmh1ZArUT8La9Ri943GGsgk0tgyGWbqXfF0bnFBATLzMlHNa0jqTE+UDrIFF1FQxyJSvb1wglPq9BCXsPeQNFxBHdEnIGmYLUqKS6Zh2gwn8sGe/3SrYUvip6X0lqmfhZVsw0+qT58SRMF1oYHEzOkJo9WFXlCAjJyMQMr/buPlrBIleBNZyGbzPrmTIt4mo3GbyFrJEWN14aM+RqO64F3jg5DPm9jSvGUyoAVKkla0GnIl6s7wCSxiihfateQxPCw0SpxnfIIklLETcXk4x7LxEDJV8QY0Ql70HU+hin0OyP7IExvFr0AaDtS7AWC43hXfjXWVDUAoYdGAnqHkLngF15ADAHEmG4fUET16NJl4hA6vKSQuZM+L3npX/lE/6kfVGpZqKhpf7JT26Sv6ydPJeXq52aZIk11wSp0edStYg6Y+FMLjTnIBVhKX3qZedCvss69uWTmLWMtSF/7TqIYtsYa7kZfJUD8Lp6ubNG3ps0kTXBcaSMycnoyvCw0AYj5P+U+fusz8eXctyA9EvHWmTwo6sU5gE5nNI3iTPitLjkjt7PPENSsDQoHaI4KmLZMCLVCStKKF/9eoO8PqQoPbwmgOaYh9OIonCoZvqzfVlBASG59ICAXRJ6hCDYvMG0RexHqSHreMPrDFKb7IYrTelbtBreFU4w9sRowkN9LD3apGGExXPwt5ym1f+qTc8hpCYoUa7akuMtaPVumqd9Xyfhu8yIIDo6haokZ8qYud7kP60r3cTSyyVaxTx6J+nrup3l6IQEqdvrSn3OJclNnUhkM7KOpuIuHPl9PmQVEtOxlMxxq2xBpSZyClFwDEuezY4fYYn9smijsopRcIjtAuT9mYJqO2j0LrQgOBOvvuQ8bLWSWC4lfgHlbnZkumQchnxyTZQxFvk5GbN0IsUzeR1ZIjLf4KDHmsqRXuDsqaEorY60jupaWtyYCeRZJW3OpuCE8DqVvODrS9KIJcH/8u4EDHADoUdjLtWlVp+PZCBYucjJVqSgiJjTeg4ROLSIpqAlFxkT4H3NvZyXmZrR25xeoin8F6V1Kn+vkzMyNlmxFSjxrhrUaaiCexqERppDJtUm7dLWojDrVMBq93NYpMtLzfFvP2POWsxtGCjBw1CkitCSxJ+tITpW62aC3OYQvJvClSi78Cwz1U04rjqZT8mKqH1hH9AwpFmEgCTVMCC8timVrD9hhFKU02wWUyAASaIg2lz+KfNHZOr24e9kCgCG0L8dIo1fZWZOapC9ZV6ZXyP3YTWShkn0keTwoHRRJGag7dRC6ZU4xcsOORFSVHFL8CaURd8D6pGIKTXS73p085JGIeLVCStBJcQw4A8svzUWpTU/8siOao38FqshSiB0JdkeHbC9VsXLJi/LaEkFC8AY0QI+AjIydDq6UmN4ZP1+b1bly5gRqGRjsSS72BEz4trdyX3JRhLU1dPdmsXc4mYIPIQ8dBfbU0E03yqNFZak0hR5YDtQbqXfGUM56CBgCu6cZqSEr9ahrbQjaW0nklgcnvzhZd9zEV8JQ6vuCtB6/ryVO0yMTAny+X4NEuS8catiR+rEyGenKupvS6VrJjR6dSgv629IiY5XN61wI2d84rzbN0Tk8YXhqFl0oBANcMdoovtadHSSr+fPNNZEE9jZL7aCliMuKbyK65bBPZZrfBldXMfmZByZGuo90YAPtcqV1WAWEaO8Z5BqhHxGRAnwokbbDdEDbBci0t0S4Xc9RoDnUBIh7BEQY2u4kmOWqq6QiyLQtRJ2Sq4g1oeEOaaAQ7SwGWmwfC/lw6pKaROAMRlnxRxt0TOz2a1XAK2o1VNyN6UAj/qD/m7a3Q09ADj+IEEIgezy7KRpVdXfzT2UAm0XgNIdcSp3ZZoN5Vb+zbH1ZTw6cFFpt5TWBJjr35Mzo0ikaf+lyp6eWs3p76d6J6ewB4Sl1oXVY9xAoWgeo+nh4Ru0SfsXVZgUANW3cHZX1MJm0fdWAE2bDDh5pl7LNQEAUUgS1U1e9M/eJf8JyeZwIAgCuXRdlbMacnzNi60EDwMTU9Uv55RD6P0Bec7BxM7s9I2ZhI4ozdRAasLTki7WSfIxX2NuQ4cyCUsteRnOS68SQxaIGSpI3uYx70gy0A1i6r0C4XneygJh2KP5pDOqA23ynymLp9YXUhbFAL8TbEPhEnhETGJxK8IU00QgZ778qt4TcGJDevixhI7zXSkbjjYCeGkKvVcBJqWeSkAjv6WvQ12YlX/S424Zpm60ZhdSByU8xVI07SIOV2sGsQbYpax3d5IJVQLGZ/I96FPBqecsZT0IBADUk9BdSb32uDDxnIxAgqFweNoYDq7QWT63vQCzXadaX+kiYuF3uvSC0UiTCRSM28aUrgs46n/6ZTDVsSP75ZFVwmAwDEbHXxT92MT6WIc3oeoW3BnJ4wvDQKL5UCpF/Kf6BpCnv++ca0TBFvk064TWQAEEvVkiMf66uJHc24Be8ytSxTkuvGk8SgBUqSNsbuhnBiOVtwkCyI5uB1mMRScxMje4YdhVAjuSKkmhJC9JFH2PucN6SJRshSFyjbwy+A8cUUUQw6OV/Fulrq6UjMT/gq7W3ILspGbnEuMsAW0JL1Xucnla6c0OgXHhXBoyRSidcOykcfps1wape7qvXXu5La2PPOU9AAQFzBTmDblTIMdkX/fOZp5HUZzbBnBN2HhZPfyYCn1JXaOpBXaiDFmzqiT0hSl1qLcHbg85Rno0jeqrSpYUviJ+1Ty2TkhZb94JvvfDM+lficvjyoLjQQ2ES0Yk5PGF4ahZdKAQLH1C6lOGmbrNGM3UTmG9PyMEW8TTYRN5EtLDkyNmuKekRMLrRASdIGT/cQc0PTGHmBXaklM/7HaFK79NaaT9kUHGotvBba/SUkHrKXTSR4Q5pohGw2qZU7wnfk5ospfHEFMNaROLAbyxa/bHYbBBub+MhNyYnIC0QYhC6maid0UupP6Hj6tJgVWiaDdx3XU++Kp3HzFDQAcLoEFKibP7xWcMTbf8Q+g8WC0FRusUZtitRIUxsg6JiaY6w0gLhIjWYdKI1xTZJOAil1gYXlmqUVsMGPYeSgfX/s+rBkYpCOqCm9xaGZPGIZO4akQ1OkiHN60bo5PWG0utBBx9Si2iIIaZTyP3YTWWtEOJLcRoQk8fgmcm1GS+gmslpyROqI/zkft+BdyV77sq8g7vsmqUezeJI2wtWQA4KiObrij+aQOtmCiDjL/MQoVqopIUQf2c8mErwhTTRCHouclLvCn3jxxRS+uMLp7UgcroZTsjcjtBpyZaGfLbxbttSS+kgDnj7NawlxRupd8ZQznoIGqDUk1e7DsdITeRq5WBy6cGzl5Hcy4CmUvEyKXrwjepO/At6B8BsCJL34RnxoGB2fUpdVkIUqu/q+SpMatiR+gZTe0Pcn33yXmlJf1y/inH62dXN6wvDSKLxUCifm6DumJgNvmsKf/0DEGx2vJxttEzl/zCay2gDXipIjUitf8GafhbxHRC+K4BtJ/QYNiQ8tUJK0Ea6GHBCIBpAGSsbdxih3rxphsMD8DouQxU765PbUp1sSMlEpfgU9Cntv84Y00Qj5LG1X9oyPIvQOeNHkV4vxLwutYai3IzGPTgz+/BEy1c2ItuS817UacnWhvyPvli15Un9Cp5XJKAtNIdTqfcaod9Xf1o9ORf0cXlER8jO9BdSlBvXkvDo0lVub/PZSvT0gkELJy6ToVXZCCbIxBAV2NO5OfeQNia3l/TaMIhMOjKJqSeh7kHf25WnBZOLjKb3i9NCSGnzznW/Gp1LEOf0iFu1nxZyejKkLPfaYylP+D6ZByr+2icyef74xLftTP68h1tI2kUtCSwvwZlnSSGXcJUfGZk3xuvEA0Nuc+pIGJD60QEnSRiD8f8yES11waPRVYnTIfG0x/6gf9TzC4GTzEyMhh6eaUp0zQszqa+mDH6zkQvDEIhKhQG1OFSYYrHF3KxTYkY0hlJ0Q+t7W0qPd0SdDPDqRRysCgDObRYBESiu3WrgackDQCZ2OBjKJxmsH8VpCXN0ytigSq94VTzUTIKOoNrRjN68NHCs9UWpj0ZrijNApjJWT38mAp1COXfCOxZ5hR12m2hF9T2eMa5N0oKXUOVrgyAqt75VONWyJNdweFiknzg1tCBFoilQ87jbJFq4uNGDdnJ4wvC50AXrhdI2JoFSzMaRj5staWcE74EWTL3QT2VnLXqv9KKDXwSSjbSJXhT6vtcvZOfgg8tB5uGvc7Qw9xpgF7xxnDrKhztmpie2ERwuUJG2EqyEHABWLypCJEfjhQOOu6LXJomn7qAMjyNa69JqlpZp2Uwg5IWbxxjMZ8IYU0I9EUOfdct/4wxZfRKnLDK13AwTXu4reiMet1nByzQvUUBRy1c2IzuRMnt196oRrYeiCLe+W3eKvwHBPahcZpE4W9cDTqbmi2iI4bR52ne2RP6fde9QaljnjI/N4eqI7RgF1d4+TXX9eaGoY7xQ7gPy4J7+TAU+hHHtM1YPX9+SpWiS9ufexEzIxf/yCsljB5izpUMOWWEMaUiPmgspkAIHN9/rRSvhHU7so5Y4wpy9fUIosDMMPB5r2UIR2vLRjanZoXWgg6Jia4pT/pj2t8MOBLAyjfAGb5wh1gQ3KnkZaUJpM3HwTeXrofDy7KBuVaskR94420/c/0jeCZjVryrUikDEg2NQmts2pjxgm8aEFSpI2xu6GcPYMO+oymtl14ojm4PWXqu2tyMyLowZlPluY9KS+pAshE5angS18CLaecZPqcAQnu47cP/69G6lpChBU76o7elmHcDWchDw1rbw78Sd6vhEfGnzja8gBQMmcYuSCTbgadprfpLGC1Msic8KVydBqSKrNEcLeXk0146lnIbefpdaQjJGeKA2pkRhLQlO5c5w5qLCzSS/vIDuV8RTKsQveeoglLM1eOko1KCeCQF3W8QvKWg3b1tTXsCXxG+gYQIeizpfHpPRWn1wBO3wYQTZa96W25mikutBsTk8R2laJVBcaCE75T23jEP48i5nN2iZyZl6mNq/hG9ZkcpD4JvIJ4+uL6q0LH03DzhYosCMHgyidF8iaEjKoie1kQQuUJC2M9I1ErCEHWBPNwesvufLjm7QJhWqqaU/sRRVCSHh8AsEb0cQiFLOoOnlw/AKl+whbROGLKsEC9a4idyQe8gyh1a82blketBtbwDYjwqWVW635vTb4kIEMeFG5OLSGnM1ug5jFTuh4tEQqKH4FklddRD1pfAqhWMT+UNKByLvXPNVsbCMgABDnx05PlCUZMtgJb93y8ZHw2uR3itfbGx0aRSNf8A5zTI1FrFY7ojfQNHEiCKTUjV9QDtSwLRr3MzLx1O9gx4JC9IREoQFs0afakfqmSMERTtHm9Dzyl5in1YUuHb8oo9Xw709tyr/7w/CbyIKdIt4mI20TeUyENwCIzvhLjkh71ajhzJaQAAchU+0RkaS68SRxUjrz3LBhA1asWIHCwkKUl5fjggsuwMGDB2PezuPxYN26daiqqkJ2djbmzp2Ll156Sfv5T37yE9hstpCvE044IZG/CokTryGXg0GUzR+/kOCyIJpDOsK79Ma3Uxct1ZQQog+fQPBGNLEIpWxh0jOUM+5nfBHFVTO+7ILWkdgXuSMxr+GUh34UzwpE5QlFLCVS7k38ZoRWQy5jfA05ABAL9DWQSaT2/R0YQi5s8Gu1hIKJ5WoNyeORI055d1meehbMtYx99td7I6cn1u9ikZHFti4UVI6PCnGpHWN5B9mpiqfUZWIEFYtMLFDOYK9BqSN2+QWSelIb+1x0zRg/L+FR4elQw5bEj3dkDpfSCwAu3hTpw9Qt/gXXheYpvcEoQts6UpNaFzrKMbVhtDKlnY358zx2E1nIYN9TxNvkEbyJLK4cP090Vap14eMoOaJlTRWOWfBOct14kjgpXWHZunUr1q1bh3feeQevv/46vF4vzjrrLPT3Rz4BGxkZwZlnnonjx4/j6aefxsGDB/HII4+gpqYm5HoLFy5Ec3Oz9rVt27ZE/zokDoHw/5awEy7erTWeaA5JUiMMKkdM3wcACNMip5oSQvThEwg+oYhFKGfpibJ3fMoIX0ThiyrB9NS70nZjs8bsxmqbEYmv38RPJsPVkAMAV5l6Qvdx6orJ84icKnsrsgrG1/QUa9V6n82R/15SF0vf5qlnwWqWVsAGP4aRg/YD4f8OPH1czAmfwi1W6muKNNlpdVkzmsfVZdWDp2bxVC2S3iTZCQAQ541fUOZR4a3+cgx5pvbC/WTAI9RdYcpkAIBYnPqmSMEpvWEXUWvin9MTRurgx9Txx92qJeVwYBReZKU05Z8/zzwyn+Mb1BTxNnnE2kTWSo60mC85wufBYklogIOQq/aI6KKmSxNdSqvmvvLKKyHfP/744ygvL8euXbvwqU99KuxtHnvsMXR1deHtt99GZiY7wZk+ffq462VkZKCycvzKPUlP0v7g3ZAZ434uznAAbwFSu/loDl5/KbhLrxlCMXvbyEPRm24QQiLjjWeEHH0bBkIFixCSR8fXJ5R6WdSjOH/8z3i9q6OjLrh3d8K1unb87SPUcNLSygcSvxkRrYYcoHbNPhjoop0KPG1azOsAUDXu57z7eLR6Vzx9O1xdxMy8TFTbm9Hor4K0qz1s5J90kEVaiEL4vHtRtAG7qN6etuBd0AXAZfj2vL6ne5h1RNdTJ5akjjSslqgYU5cVAIpnTUMe+jGAfNTvaMGcM6cneXTESlpKb1n4qDOx0gu4Aak+de9ZbU5f0I2Ic/p/xjenJ4zUx+c/44+7GTkZqHE0QPLVQtrdgeqlqTkvjrSJLGQPA/2A3EkRb5NF6CZymFJAWskR47WxtcdoVBe8x2RNCfnsdSR3T+0N6skgrbauZLXQV3Fx5FoZzz//PE455RSsW7cOFRUVWLRoEe666y74fKEv0sOHD6O6uhozZ87E5ZdfDkmSIt7n8PAwenp6Qr5IcklHw++GcFZEc0gyq9UTLsLACJ5qKg+PTzUlhOjDG88IefompkIV+wyQ/aGTGsWvQBoO3zSFi1XDVtuNLR2zG1vCNyMSv9gVqCEXfueXd82WOsZHkCYLj8gRp4VPHeSNcyLVu/KP+lE/yhY2ebfZcffB0xP3hV+A5Onj4WpYAoGOsVK3+cnvZKDVZS02VxKgbgU7ke1DITzuJBRhJab1NvWiW2GffXXLysf9PLiGLY8WJxNXtJReABCnqxFKbanbpNHm9KXhP38oQtsarC50jGOqmpUhfZi6c9tITVO0iLfO1KWfE2vF3ETmdeHjKDkitbPX0bgF7wK1RwRNWSY80wuUo6OjeOONN/Cb3/wGvb3sZKWpqQl9febq+/n9fnznO9/B6tWrsWjRoojX+/jjj/H000/D5/PhpZdewi233IKNGzfipz/9qXadVatW4fHHH8crr7yChx9+GMeOHcNpp52mjXOsDRs2QBAE7auurs7U70DM08L/w9SQAwILDzxKwNRjhOnSa4azUo3kCpNqSgjRh08geCOaWIQatvg1iLyQWpIet4w+sMUovqgylquUHZci1bviUYliTegJn1DGIgLlkcRvRkSrIQcEokN5tEQq8JpBYkX4qFfXcvYZG6neVeu+dniRBQdGUX3y+AY3QGDxM1J6otTMNohcYvgd8kC9vchNkaaCQF1Wc6lOeaV5KLOpDYd2hC+NQNJD/U72/DhtHhTVhm+E4ypMfQ1bYg2pM3KZDAAQ57JNeMkT31w3HpFSejkr5vSE1YUeRk7EutBAoO6+dDi+8lZmKX4F7mG1YduYTWQhnx2fZA9FvE0WMTeR1ZIjLf4KDPeYS+2PlDUVqBufVvF3xARTz6Db7caJJ56IL3zhC1i3bh3a29kk9p577sH3vvc9UwNZt24d9u3bh7/85S9Rr+f3+1FeXo7f/va3WLZsGS6++GL813/9F379619r1zn33HPxla98BYsXL8bZZ5+Nl156CR6PB3/961/D3ufNN98MWZa1r/r6elO/AzEvWg05INCttQcCZMn41shg1yDaFXWBckX4E2O9oqWaEkL04Y1n+IQilqKaQEScXB+IBOCLJ2W2duQWh4+OjtWRmEcl8ihFLlD3MvHvda2G3AnhNz5412xphKXcpkKsMhmx6l3xGpY1jhZk5ISvMMNrBPOawePuo4stVItzwpfY4E2Rmv2Vpie/kwFPnYx0TNVD64j+AYUjpDMtpS478kKyWMaiw3l6MJm4tDIZC8KX0uCdc6Wh1DVFijmnVzcTzc7pCcOPqdX2VmTmRViwrmIbs6lK+ZfreyJuIguF7POIIt4mD76JLNaFn6eWzClGLtjxqGFni+H7V/wKpBE1a+qk0Gwdwcn+lftTVwqJWMPUAuUNN9yA5cuXo7u7G7m5gRPCL37xi3jzzTcN39/69evxwgsvYPPmzaitHV8fLFhVVRXmzp0LhyPw4ps/fz5aWlowMhJ+d8jpdGLu3Lk4cuRI2J9nZ2ejqKgo5IskV7QacgCQX56PEpuapmAimkN6txkAUIBeOF3x7SoL1WyMskKvE0LM4o1nBJ1vx8y8TORB7fjYGIjU54snfDElnFgdiQM1nMbsxmpp5ZFrKlpFqyGnnlyOxaMjBpGHzsOpSdOUPGqZjLnhI0odWQ7UOtRUUrUrecjtYzQCAoIKqEeoISn1szQ2cWH4z9/SeSXIAUsxatw9dSP/IqXUGSEKakf0g9RhNZ3xpiliUeSzfB4dnsoatiR+/lE/6r1qNFqklF51E75DKcVAR/iySYkWa06fV5qHUptazoMitE0LrQsdnjidnerzLI1k489vqa0DeaVjUrzVwzhFvE0e2iby7PCbyPGWHOk+5kE/2GPULgsNOBKm8brx1CNiojP1ifDWW2/hxz/+MbKyQl8A06dPR2Njo+77URQF69evx3PPPYd//OMfmDFjfCHlsVavXo0jR47A7w+k4h06dAhVVVXjxsP19fXh6NGjqKoaX9SfpF5IDbmTItcf5V1bzURzSO+x9CYxuzXuYv881XQE2dQRkxCTeOMZoVj/YUiwswUuuTlw0hWodxO5vlK0eldsN1Y94Ru7Gxu0GeEfDV/vywohNeSWh4/wzi7KRqWdTfSlneE7WCeanjIZfPHR/cH458N9iNewjFwKhi9+uj3jFyBHh0bR4FOfq6XhU7htdhvETKq3F61pil5iBXVEnwi0lLryyAvJWg3bTipNM5G1fcRSeu3wRSyTIdQVoRDs87d+h/EIpXjpqQsNAGIORWjHK1ZdaCBQd5/X4U+2QNOU8ZvIgpOdj8n9Ke3ZSywU2ESOXAecNc8yV3KEz3/Lw2RNCaXJqxtPEsvUAqXf7x/XlAYAGhoaUFiovzD9unXr8Kc//QlPPvkkCgsL0dLSgpaWFgwOBiZZV155JW6++Wbt+29+85vo6urCDTfcgEOHDuHFF1/EXXfdhXXr1mnX+d73voetW7fi+PHjePvtt/HFL34RDocDl156qZlflyRYcA25sbshwfgChPuA8R1hLcJgTJdeMwqrC2GDWoi3IfKkgBASGZ9AOEv1d8h2ZqgRlK2BjQG+eMIXU8IZ25E4WMfBTgwiL2wNJ6GWfS4psKOvxVx9ZT14hME0WzcKq6NM6njK7b7kF7sf8gyh1a8uei2PXDeMdyHnXcmD8RQznnIW9vY8PTFMAfXm99rgQwYyMYLKxVHGUMgWJt0fJu45S2eyJKMHbBE50oK3HqJa51NqoWiEdOZuYidlYm3khWStgVVv5E1gkv60lF5H5JRem92mpfu798Y/5zWq+5gnZl1oABCdbGGSIrTNc7vZv7w0Sjh8Q9E9FF95K7OkQ+omsnP8QrRQrEa8DeqfB5L0pWcTGQg0pHQfNV4j2/2eBwDgyhu/US+UqWWZRuJrhktSz9QC5VlnnYX7779f+95ms6Gvrw+33XYbzjvvPN338/DDD0OWZaxZswZVVVXa16ZNm7TrSJKE5uZm7fu6ujq8+uqr2LFjBxYvXoxvf/vbuOGGG3DTTTdp12loaMCll16KefPm4aKLLkJJSQneeecdlJWlrh4LiYyfnIfbDQkmlrNFCem48WgOXnfJVRb/RMieYUch1Eiuxql5AkxIvHjjGd6IRg8hi01q5PbAZNzdzG4vRmiaAoR2JA6uXwkETvgq7W3ILgrddc0tzkUG2GJaIt/rgQjv6JGRolNtIHMo+ZHbDbvY53Qe+lE8K0pUTJR6VzzFjKechb29uvjZrpRhsCv085qnjddmtMCeEeU+StR6ex+baxAz0fFjaomtE/nl5uunirN5R/TElzgg5sVKqQOCath6U1fDlsRPT0ovAIhFHnZ9Exv68eIRTtHqQgOAWK5GaB9PXHbCZBerLjQQSPnvUooTutEaCT9nc4XZRBZKeMRbatLPibX4JnIGvNE3kdWGuGZKjvD5r+gcv1Ef6BFBmQITnamY6o0bN+Lss8/GggULMDQ0hMsuuwyHDx9GaWkp/vd//1f3/ShK7EnSli1bxl12yimn4J133ol4m1iNdkh64bshLDoo8iKyS1SA9wGpxfhOm9SkdumttWYiJDj60OMTILfQzi8hZvDGM7wRjR5C9jDQB8gdgQg8qZtFarjmRr4fXu+qQymFtKM1pA5toIZlB4DQaA+b3QbB1oNOpQRyUz/qdI/UmECauifq9cTKYaARcKcg5da9uxOAC2JWC2z2WRGvJ063A/8GpPbxJxw8xYynnIUzbYYTBehFHwpRv6MFc88OlH6RPmInV2J+FwAx4n24an3AYUBqnJp1rbTXdE4bgPB16vQQF7HnSxqY2h3R0x1PqXMtihx9XbO0Ajb4MYRcdBzsQNl8ek4nIulI7DIZgLoZ356apkg8pdcVY04v1inAe4C7maLnzIpVFxoABFGAABkyBNTvbMX8zyV3wynaJnKgESFFvE0GbBO5GnUZzXBkRZmjzcoANgcaVBp6jChZU0Ilex3JPtpUnehMzd5ra2vx3nvv4Uc/+hG++93v4uSTT8bdd9+NPXv2oLw88oo5IeFE2w0JJs5Rozm69JcR0B6jky2GiLOsmQgJGWokVyvVoCTEDN54hjei0UPIY5GTclfgpIsvnoiLonfb0epdqSdP2u1j1HASHOxEMJGbEYEactE/T0RRbSDTkvz6OrxWUKwyGYF6V+OfD2lITRGPUsMyOD2RR5Zqt1fTxsWS6CfnWr09E5PfyUBPXVY9eEf0Jl8FvAOR0/JJ6vhGfGgYjZ1Sx2rYqnW8d0VuKEbSmySpZTKipPQCgc14qSn5tf2SMacnjFYXOkJzPU7MCX9MTQYegc8j8oNpEW9e85H+JH2EbiJHxptn8QaVhh6jlS94j48a5j0ielGY0LrxJPFMH7kyMjJwxRVXWDkWMkXx3RBXZYyTc7XgrjRgPCJE6mPpTbwOU7yErEFgGJDbI9e9I4SEp/gV9Cjs/cwb0egh5LOUXdnDPjO8A140+dVi/Muil/AQnTJ2DwbqIXGSFL2GpZA5AIwCclvi3utSc+wacgDgmscm85In+Sd0gTIZ0VMGtRqSQ6Gblf1t/ehU1OLpK6LXwhILu/HR8PgC6lIDr2EZPXVbm/z2mm8QM5HpXfCOpXxBKbIwjBFko2lPM1yra60YHrFQy/ttGEUVHBhF1ZLoAQJibgea+yshfSBjWZLGR6zFU3pdM6I3e+Sb8XxzPpn01IUGANeJPELbfJT3VDbYNYg2RV2gjFIXGmAp/x8MAdLBFKT8a5vI45v08A1qvmFNJjbdm8i85MgIKzlipHktz5riGxzBguvG9zbJEMTogQskfZleoGxqasK2bdvQ1tYW0lEbAL797W/HPTAydfAC/OF2Q4LxBYhGXyVGh0aRkaPv5esf9aPeq0YYnGzNREjIGQZ6AbljatY4IyQefS198KtF9PmEQg+hQG1OpdZab9zdCgW1yMYQyk6I/t4Wy4eB5vE1bHk0YqQaTkL2EDAYmlZuNT015ICglNswDWQSjdcKEmui70qPrXdVUMl+t/qdrQBmogixJ41i6SDQMT49UWpj0ZnRalgC8U1+JwNJTZkU6+IrBWDPsKMuowVHR12Q9nTSAmUaYil1Vah1tMCRFf35Eaf14t3+QNQ4mXi0Mhlzo6fEak2R+pLfFCkwp4/++WN2Tk8YVhd6OvLRh2kznFGvK5YNAW2AdCy5UWXeAS+afJE3kfkGdR8K6TUwCejdROYNKQeRh87DnSidp//cPNqCd44zR9tUlRv7aIFyAjP1SfD444/jP//zP5GVlYWSkhLYbIHJv81mowVKYki03ZBgFYvKkIkReJGFpj2NEE+p0XX/7Qc6MYwy2OBHzVJruthpqabdya/vQ8hExxrOFCID3qhF9McS1LmG3McWqKQ9nQBqUZfZAnvG9Ki35fWuxtaw5dGIkWo4CTnqe70zcZsRvIYcjxKPhEdJtPgrMNwzPK6pTyJJnSzSgadPR1JUWxS23lVoI6AYC5S1fuBAoHawNoYedjvxhOip27XL2Of8APLRdbQLJXOmVudiLaVuTvzdt8WCLhz1uLTULZJepA9ZaQoxn30WRiNWDAMNgahxMvHoTulVN+PrRyvhH/VHbSpmNb1z+tAIbf1zesJIe7sATIeY1Rq1LjSgHlM/TH7Kf9OeVvhRiywMo3zB+BIUQl1gkamnsTdqAz6S/vRuIrOSI61o8VdA2tmme4FypG8EzTGypgRbD9qVMnga+6NUKifpztQR65ZbbsGtt94KWZZx/PhxHDt2TPv6+OOPrR4jmeSi7YYEY9EcrKM7W5jQef9qvaVqeysy8yyqQZnPFiZljyV3R8iUIjex1F3B1mMouk1wsuvK/Wr6Gq93UxC93g0QOFlyj6l3pZ3wRfj8EfLULt7diYk80FtDDgBK5hQjFyxFq2FnS0LGE4nUq79MRrh6V7ybLO8uG/X2s3gNydD0RGlYnZjGODnPceaggtfb2xm9M/pk5O5Xj6kLox9T9RBL2HvVfYRqUKYjLaWuOPYCMo8Sd6eghi2J32DXINp5Sm+MMhnVJ1fADh9GkI22j6J3/Laa3rrQPEIbMDanJ4zeutBAUMp/V3JT/vnzWpfREnaRPKsgCzlgZXfYxjWZyPRuIgO8MS4g7dNfK5tlTdlZ1lSERm9CBntfUBPbic3UAuXAwAAuueQS2O1Ts0MmsY6RGnJAYCGCRw3oIe1TO5rmWTdJEwrVVNOeqZU6SIgV+MSBN6DRSyhmEXXyoDrZPsoWTfgiSjSBeleBSc1wzzBa+OdPhBpOQoG6GSEbGqpurIZcJjLgjVlDzma3QcxST+j2xl6UtYriVyDxMhknxY5GdKmLkMH1rrQaluWxJ43ifJ6eGIim6GnogUdxsp+vrAx3s9D74JPfDxL0xKWp0aFRNPrY38e1PP5SAK4aFjksNdB8Lx1J9TylLvYCcqCGbfwL1yT56newz/5C9IREnoWTmZeJaoe6UZTEpkjJmNMTRm9daCCohn+SU/71bCILdvbcy83Jr49JrKV3ExkARCd73nlTLV33ry54i5nNEYMbhEy1iW0C68aTxDM147z66qvx1FNPWT0WMgXp2Q0JJhazhQi+MKGH+1D0Lr1mjE01JYToJ7eyCQmfSOgllLKFSXlIPdFWF03E6tilFsJ1JOYnfLkYiJgG7BRYOqTcm5jNCFZDDqjNaIEjyxHj2oBYwKIlxjaQSaSOg50YQq7uMhmiugjp/jgQdepu5I2AYkei8vREyVuldWKUdrCT7WJbl1bXMup9qB1kjUx+JwOWUudAJkZQsSj+BUpxBntNSh36SzGQ5JHa2WdhrJQ6ABBPZBOXVNSwJfFz72GLPGJ2q67MA74pbyRCKV4hc/oYdaGBwOaikTk9YbS60AaOqfWjVUntbqxnE9mZwRYxKeJtYgveRK5brmOeWMnOzXlTLT2k/XzBO3LUsDObzfkSWTeeJJ6pYhQbNmzA5z73Obzyyis48cQTkZkZmjZ73333WTI4MvnxGnJsN2RGzOuL1aPAx4C7Xv/CoCSpEQaVI2aHOY4wLTTVlBCiH584CNnGFo+EcpaaKHvZYglfNOGLKNGE60jMohBdELNaYLPPDP+Y2mZEYmo3ufcF15Cri3l9sXQA6AKkj5PXoItF4JSi0t6G7CId0Yu1CrAv0J0cCKSW8VSzaGqWVsAGP4aRg/YD7ahYVAbpfQ+7fU4bgNhRIGLFMNAIuI9PrXp77Jhag7qMZtgzXHHfH0/Vknqccd8XsZ7b4wQAiPNiLyDzKPFWfzmGPEPIcYavu0vSk5EyGQAgTuvD272BTfpkcO/qgN660IA6pz9KEdpmuDv4MTX23ISn/HuRhZb3W1C9NPZx3AqBTeTI8xUhcwAYoYi3iY5tIhdhmq0bhdWxa4mKog3YZazkiPsIex2JpZEXvIXcEaAbkLuoie1EZuqIsGHDBrz66qtobW3FBx98gD179mhfe/futXiIZDILhP/HrqECAOIMtTlGu/5oDqmVffi5plsXASUUswmBZzD+JgSETDWeDjZx4A1o9BIq2Am1PMom5nzRRE+9m3D1rngUoqswSvoRTysfSMxmhJEacgAg1rBoUakxiU0P1DRpMVdfmQzejVzqDEQ68tSyWI2AAFaXqsoemp4oHWTRFaKgL2VbFNnnPf/8nyq0pik66rLqIS5hJxruYdYRnaQXaZgtOupJqSueNQ15YJ95rAMwmUh4Sq9Yqi/SjG/K8zIAyRCIcNL3+aNFaLfTYrlRvAQKL4kSTUZOBmoc6vxnd/JqkvJztWibyEI2W5iUOynibSLTNpGz9dX95nXheaNKXY+hzntdNZGzpoR8Xjee5isTmamQkI0bN+Kxxx7D2rVrLR4OmWq08P8ouyHBXPNDFyZ0PYbMavXoiTDQS0s1HaZJFSFG8YYzvAGNXkIVW4iU/YVQ/Arcw2qtvZP11VUa25GYRyGKpZFTzYUSdpiUhxKz0CU18Bpy+nZ7xZkZwGZA6oi9KGsV6bCxMhm8kY7Uz54X/6gf9aNV7Gcn6+vW6MrrQFNfFaR9MlYAkI6z14xYpi/q1jVXnfx265/8TgbaMbXYmhIAdSvYe6wPhZDrZThd0RtfkOTpbepFt6IuUsRomgIEatgeGJkFaW8XZv9H/BG2JHmkJv0pvQDgmmEDtgNSW/I2aaSj7Djm0jmnpwhtc1hdaIPH1PwO1PfUQPqwB59I5OCC8OfVNT/yfEXIZQvpcmfsUj0kffFNZJfTo+v6rsXGS45I7ex1FHXBu0DtETG1yo9POqZCMLKzs7F69Wqrx0KmIJ6qraeGHBCI5uBRA3poXXpPtO7EKpBqmrxFAkImCz5x4A1o9BJq2MLXAPLRvr8DfWCLT3wRJZax9a60Gk41kU/4hDIWDSiPJGYzQmrTX0MOAER1k8bdm7xi9261RpBYoS8Fi3cjbxithG/Eh9Z97fAiC3b4UH1y7IUUILAYyhdHpWa2KSTW6dsVD9Tbi13beDLRk1JnRF5pHkptai27HRR1l07qd7Lnw2nzoKhWX+Mb3vE3mTVsiTWkTv1lMgBAnKuWQvEkb1PBSF1oIChCe0jfcYEw7fs7MIwc3XWhAZbyDwDSYevKXUXDNpHVpilLIqf8CvnsWCV7KOJtIjO6icxLjrT4KzDco29uKfXyqOHI3eiFIl43nspGTGSmnr0bbrgBDz74oNVjIVOQkRpyQKDwbg8EyFLs7ZHBrkG0K+oCpY4IA72ESjZunmpKCNGPN5zhEwm9imoC0XAfvFQPACiztSO3WF90NF+04SdRPApRnBk5mSCwGZGY97okO9kYdEZ48y7a0kjyUm55mrTo0pcqWLWkHA6MwosstO5r19K0axwtyMjRl7ihpSeqNYSlLrY4zdPHY95ebYrU7K/UPfmdDLSmKTOsm5yLOWqavZrCRdJDIKVO/8IxjxZPZg1bYg2tTMaC2Cm9QCDtXxpKXlOkRM/pCcOPqVX2VmQV6DwmVqkbs0lK+Zfre9ALtnESbRNZKGSL2RTxNrEZ3UQumVOMXLDjUcPOlpjXV/wKpBF1wfukyBv0gpP9K/fr+wwi6cnUDHb79u144oknMHPmTJx//vn40pe+FPJFiF58N8S1QN/Jf355Pkpsav04HdEcvEtvAXotTU3TUk0VfVELhJAA3nBGMPiWzMzL1GqoffC2Wmsvt1337QP1rtTIkj4du7FaWrm+k0KjtBpyUSIMgvGJ/iDy0HnYmjqDsUge9jnnmqcvinRsvSutLmJep+7H5IuhfHFU6mdpbHpqWAJA6bwS5IClHDXunjqRf1pd1nnWRfeLTnbmKB2iLqvpJNA0Rf+ZPY8W59HjZGLwj/pR71VLmizVl9LLN+U7lFIMdEQuY2IlPRFOwfLL8ylC2wTemZ13ateDZ2nwrI1E489nqa0DeaVRUrzV0yiKeJvYjG4i85IjANSGldF1H/OgH+wxapdFDjgSpvG68dQjYiIz9WngdDrxpS99CaeffjpKS0shCELIFyF6KH4F0nDs3ZCxWBfXQOOGaKT3WDqTmN0Km93CJjm17CR5BNkY8hjrREzIVMcbzgjFxg9Bgp0tdn3woZpKJvTovm1wvSu2G8tO+KLuxlazE60epdDyiMXgGnJ1y/SVrcguykYlbyCzU18x8niZKZPBupID0oc9gRqWxfpqWAKAOJedREmeIvhGfGjwqc/VUn0p2za7DWKm/snvZCENxU6pM0osV9Psp1hH9HSnpdSV61845tHiyaxhS+LXfqATw8gxVCZDqCtCIdjxkW/WJ1LInN7A548Woa1jTk8Yo3WhgUCWBq/Ln2hahHdO9E1kwcnOzeR+U20xSJowuokMBBrk6ik5wue75TGypoTSxNaNJ8lh6tPg97//vdXjIFOQxy2jD04A0XdDxhKFHuwZDBTkjYZ/6PG6S1YprApEU8kNvchxUrMcQvTiEwfegMYIIaMfzSPAB01qupvOuohAaA3bzsNdGASbUNUuj5J+pG5G+OFAX0svCquta7rCasgVqjXknLpvJ+a2o6W/AtK+Hiy1bDThDXmG0OpXozyX66/9K07rA3pYvat63gioUn9TJC09cbAMze+1wYcqZMCLysUGxlDYhUNdM7SmSJOdLMmQwRaReeqkFcQ6BXgPkFoS08memCM1s89PsVb/wjGPbOPR42RiYCm9Zah2tCIzr1rXbWx2G8TsVnw4XATpvW7MOzexYwye0+utCw2wCO3dOuf0hJEkXhdafz1JrS7zkP5jaDx4xD2PwI9EKFYj3gbp+DJRmdlEBtSSI136So5oC9657LMwEqFMLcs0Yl1jXJJ8FE9NUoaH/8faDRlLLGcRizx6IOpjHGO1TcRSayc+jiyHtjMtN06Nk19CrMIbzgilxlMwhEz2Xv6wfzoAQBT1n5wH17v64EUJAFBpb0V2UeSd1tziXGSALaxZ/V43U0MOAESn2kDmUOKjtxt2sbHloR/FswxExQTVu+JdZMXp+qPY+WJom1KGg1uaAQC1GS1wZOlPTRVLpla9vfpdLMKg2NaFgkrrShKIc9Q0+66p1RE93UmdxlLqgNTUsCXxk/axRR4jKb0AIBZ52O0PJD7Fm8/pjdSFBoIjtPV1JyfG60IDgZT/TqUE/W2Jb5LFI+758xsJ36iWhyjQY6Jim8gZxjeRa9g5utQYezmKz3dFZ/SsKaGCvY7kUcoSmMh0L1AuXboU3d0sCu3kk0/G0qVLI34RogdP5zBSQw4IFODlBXmjPkaT2qW31vqJj+BgixVyC+36EmIEbzjDJxJGCDlskjIAtaPpbP1pHME1bN96Qd/nj81ug2BTNyOarJ3Um6khBwBipXpC5078AgNPjxazWgyVyeD1rtxtOXCrXWR5V1k9ps1wIh/sM/ZfL6v1tvL117AEjE1+JwP3ex4AgTIoVuEpW+6BqdURPd1J/caapgCBaPFB5KHjoLH3E0kd9yGe0mtsk4xvzvPN+kRKxpyeMLwuNC+FoocgCigCe45Y9kZi8Yj7WE1TAo0IKeJtopJ2s40Tw5vIBkqO8PlurKwprYmtLzF140ly6M6v+8IXvoDs7Gzt/zZbcrqAkcmLp3PE2g0ZS5zDogXcOqI53B3qIsYs62ubCBn9aPABcivVoCTECN5whk8kjBByQ9OExUXG6im5ctrQOViCt95jnx88GjHqYzr60DlaAk+TtVEo7mNs48RVYWyTQxRtwK5AFEUimS2T4TqB17sSUK92kXUtceq+PSug3or9IwXac+UqMXhyPsMBbAHc7VNjJ50fU12CtbXcXCtYRESTrwLeAS8y82ghIdV8Iz7Uj1YBMJZSl12UjSp7C5r9lZB2taNsPi06TwSSxMtk6E/pBdTN+f2AuzHx9f3cB9Q5vYG60EBQhHY3LSjo5R5gn8lGjqkAIGa3Yd+wAPeeLpxw3swEjCyAR9zz5zcSLeLNq6+xEkk/7n1qI8T8TgB1um/HS464e2P3oXC3sHP/WFlTQg37HOlFIfyjftgzpsYG9WSj+4h12223af//yU9+koixkClG727IWOJCtiAhDcTuZCj1qREG862f+AhZg8AwILcbGz8hU5niV9CjsIkrb0BjhJA/ZoFyWeRaNOHwelf/7poHAHBVxn7/CpkDwCggt1n7XjdTQw4IPqFLfMotT48WS40tzvIakocHa7XOizzFTPd9FHZjf2fguRKrjKVqa/X2eqdGvb1A0xRrN83KF5QiC8MYQTaa9jTDtbrW0vsnxrW834ZRVMGBUVQtMVZTTsztQHN/JaQPZCxL0PiItcyk9AKAOCsTeB2QOhO/+GN+Ts+OY7zJBolusGsQbYrauM5AXWiApfzvawekg0lI+R/Q1zRFqGIbiHzjmkw80hG2cSIWG9xEHlNyJFqWDp/vumJEDfO68Qrs6G2SIYjUvHkiMrWsPHPmTHR2jk8N8Xg8mDkzsTsyZPKQdO6GjOVazg7Mjb5KjA5FPmH1j/pR72XpTK5l1kcJOHPYJEzumBr1zQixQl9LH/xgKSB8ImGEUBAo15CNIZQvMPbe5vWQtEUzHSd8QjZb8JE79Dd50UPqMl5DDggqdj+Y+OgnqVEtk1FjrEwGX4zkf+ciGJ8ousoGQu6Dp43rvv1SdoI0Vert8RTJWCl1Rtkz7KjLUDui76G04HSgpdQ5WpCRYyw6jnf+5Z2ASfrjnZd5J2a9XAvZZyffrE8kPqd3uQxuuC3TN6cnDK8LnY8+TJvhNHRbVzlP+U9svc/RoVE08qYpMTaR+UZ1HwrhG0l8KQJiPUlthOiqNvb+5c20BpGHzsNd0R9DLTETK2sqx5mDLKjn59QjYsIytUB5/Phx+HzjP0SGh4fR0NAQ96DI1MDTOWKF/49VsagMmRiBHw407YlcR6X9QCeGkQMb/KhZal1HU07IYztGcjcdUAnRi08YMuBFXqnx1FunM/D/uswWw+kbYxdv9NRwEnLU93qntSdPPGIkVoTBWHzC3+yvxHBPYhcZeG0gXitIr6LaIggIpBqL2cbrIo6tHSyeYOz1UruMfe4PIB9dR42lqE9EgWOq8eZTsYgF7ORhqnRET3fSh8EpdcbwCDfeCZikP2lQjZg70dgmj3gyO8bUj1bCP5rYRSke4WR2Tu9DBprfs7Z+7mQUqAvdaqguNBA4pkpNiU35b9rTCj8cyMIwKhbFWKCsCyw49TTGLrlD0o/UxjZOjG4iZxdlo9LOzuOlnZHf+yN9I2j2s/mcnqypRNWNJ8lj6JX0/PPP4/nnnwcAvPrqq9r3zz//PJ577jnceeedmDFjRkIGSiYfd7864VpkbMLFojlYV9do0RzSLlaou9rempCaWUI+W5iUPZbfNSGTFp8wCLYew5NrABCcgdvwRRMjxp486alhKeSpXby7rTvB84340DCqRhgYqCEHAKXzSpADFgnRsLPFsjGFw2sD8XRpI8ScwAYS7yZr6PZjagfztHG9cpw5qLCzSW+0ye9kEVjwNlaXVQ+xhL1vpaPWRhETc8ym1AGBqHGpJfE1bEn8BrsG0c5Teg2Wyag+uQJ2+DCCbLR9ZKwDuFGBCCfzc3r3rsSOcTIwWxcaUFP+AUhdiU35589jXUbsTeSsgixtPkMRbxOT1KM2QjS4iQwEmmpJ+yLXrm3c3QoFdmRjSFfdZCGDvUeoR8TEZWgL5YILLgAA2Gw2fO1rXwv5WWZmJqZPn46NGzdaNjgyeXkHvGgysBsylljQhY89Li2KIBxpn9pRMK8DQJWpcUYjFLLFCrmHGkYRohfvei84+gAYrzklFAc6BPJFEyPGRivqqeEkFKibERb2HomnhpzNboOY2YJD3hmQ9nZh1mdc1g0siOJXIKllMnitICPEIg8+UOeHYpmxRkDA+NrBdcuNR8KLue1o7S+H9IGMky81fPMJIySlzuCCtx5i9ShwFJAaqOB8OpDq1aYpVcYXjHnUuORJfA1bEr/6HS0AZqAAvXC6jC3+ZeZlotrRhAZfNaRd7ahcbOxYo1cy5vSE4R3ZxTLjdSS1ep8JTvnnkfZsEzn2/ESw92LIn0sRbxOUNKy+9w1uIgOsUeX2fkA6FHkxkQUj1UHMbIbNHjsQTsgcALzW140nyWNopun3++H3+yGKItra2rTv/X4/hoeHcfDgQXzuc59L1FjJJBK8G2K0hhwAiMWxozl4fSVeb8lqgjpPlPvohI0QvfiOppBprki7UBqIhharjZdXCD55ysUASubEnqgLRSwVUu61bjMiuIacI8sR49rjuQrVlNv9iZvQdxzsxBByYYMftcsrDd9eLAtMOMema+u6/cmBBexptm4UVhtfUBGdbFc+2uR3Mmh+rw0+ZCATIwlZhBBnsNeo1G6sBh5JDKmdLTIaTakDAlHjPG2YpDfpPRYp58puMZV1wDbpo0coxSskwukE4xuPLorQ1s1sXWggOOW/KqEp//x51LuJLDgo4m2i6mnogUdxAjC5iaw2quRNtsKR9vMFb31Rw1rd+PYRw+Mh6cHUysqxY8dQWhp7UenEE09EfX19xJ9v2LABK1asQGFhIcrLy3HBBRfg4MGDMe/X4/Fg3bp1qKqqQnZ2NubOnYuXXnop5Dq/+tWvMH36dOTk5GDVqlXYvn177F+MJA1PzWa7ISYmXGoh3mjRHJKkRhhUJuYDSpjG7l/utz59nJDJijea4RMIo4TyQFoiXzQxgte7AgAxS98JX2Azwrq6TfHUkAMCXbV5l+1E4GUyKu1tyC4yng4avCjJU8uMqFlaARvUztQmalgCQfX2okx+JwNtwVtHSp0ZPHVL6nFaft/EOElWU+oMNk0BAlHjLf6KhNewJfHTUnpNlMkAAHEaO7mXjiTuueZzejN1oQF9c3rCSJ3m6kIDgZR/L7LQuq/d6qFp+PMo6myaImSx+QxFvE089bvY3Mz0JrKolhxpjTzHlI6y15FYqnPBm9eN76IeERNVQo8Ex48fh9cbeTds69atWLduHd555x28/vrr8Hq9OOuss9DfH/kFODIygjPPPBPHjx/H008/jYMHD+KRRx5BTU2Ndp1NmzbhxhtvxG233Ybdu3djyZIlOPvss9HWNvlrUE0UgfB/c40LxBnspcujCMI+hvphp6dLrxlCMZscyIPWNyQgZLLijWb4BMIooSLwnjdT7ya43pXu3dhi9nkjD1i3GRFPDTkAEGvYxEtqTNxhXPpALZORa64uWPCipLigIMo1w8sqyEKVWkBdFDzmxqBNfif357R2TM03XpdVD3HJNPY4w4lJESXGSEPseTCTUlcypxi5YAsCia5hS+KnpfSWGi+TAQQ26fmmfSKEpvQaF4jQjt20bqqTeF1oE8fUjJwM1DjYe55vQCYCj7TXu4msRbx1UATtRMMjvE1vIqt14XmTrbCPoS1461twFPKtrxtPkiuxbbxieOWVV0K+f/zxx1FeXo5du3bhU5/6VNjbPPbYY+jq6sLbb7+NzEx28jN9+vSQ69x333249tprcdVVVwEAfv3rX+PFF1/EY489hptuusn6X2SC2fbQ+3j7hfhPYj75uWKcev1iU7fVwv917oaMJc5jCxN7O+pw73lbwl5nV+tsdl0dXXrN4Kmmh3oqIo5hqsjKtuHi205A1UnmuqXv/vN+vPHnyB3Z9cjNs+HyexajeNa0uO7HrO5jHvzfhn340h0noaDS+MRRjw+eOYRXHmuCEiUYrLjMga8+uNJUxBsAPPfDd3D4g8Sl2fxzF3vv8sYzRglVgUVJvmhiFK93xaMQYz5miboZMaT/b7p300G89kRzxJ+/8C82djM15AA1emJzoMt2IsRbJiO43mdwurah+8jrQFNfFcRyc69JPvnd0Vw7qT+n31LfV2JJYpoM8NStHgj42ZlbkGlyrT47x4ZL71yA8oWJSS8+vq0Bz9xzBL4UB07MnJ+NL288xdRtvQNe/HHdO+hoDf9L+HxAl7IGgPGmKYBawzarBQdHZmLjt92YLh4zNU4r1M7IxKUPftJUJo1/1I8/Xf82WhriiyKfuyQXF2xYZeq2wz3D+OO3tqOrPfILzmYDzvl6NU68cK6px3DzlF4TZTIAdZN+O7D5QGXCPgP/qX3+mJzTWxCh3by3FZtuP4CRYfPR8jYb8Llv1mH+52aZuv3xbQ349yYJlzxwiunX9JPf+jea3JHnBW7vJwCYqwsNAGJeJ+p7a/DQXR5sfWZL2OvEO6fnz6PeTWQhly2iezqsywjZ9tD78PsUfOpbS0zdvvuYB3/+wXsY6E9t9kW8c/pYtv/+Q2x5yvxi9c4P1GAgs5vIJ7JsgIMDkedo247VsuvqXfAuUHtEGKgb/9LtO7Dv3dTXQJ1Wase1fwi/BjalKAlUUFCgHD16VPf1Dx8+rABQPvjgg4jXOffcc5XLL79cufbaa5Xy8nJl4cKFys9+9jNldHRUURRFGR4eVhwOh/Lcc8+F3O7KK69UPv/5z4e9z6GhIUWWZe2rvr5eAaDIsqx77BPJLadtVgAl7q889CmD3YOmxvCf87cqgKLcdvpmU7c/9Nox3eP84NlDph4jlncf22fJ33GyfF0+fZupv6Pf51cq7S2WjOG7Szdb+yQb8MNV7H119zmJG8PczI91/R0eu+qfpu7/w78fTtrr5f8t22xqjB63R7HBp2RgROlv7zd1H1fP/acCKMrPztQ3hlfv2qkAirI454DuxxAd9br+Do9cae65evN/diuAopyQdcTU7fW4cdnmuJ6rxl3NCqAoWRhSRvpHTN3H5dO3KYCibPy8uTHs3XQg5Z+Nyfwye0zVw6rP6etO2JqwMZ5dsiPlzwH/2vWnj0z9Dk+u/5eu+y+xdZj+O51Xtj3lfx/+tfnne0z9Di/cZt3v8OHfD5saw2NX/VPX/c/N/NjU/SuKonxm2i4FUJQ/fsPcHOvlO5P3nrjjM5tNjXH/i0cVQFEEeEzdXlECx4p4v5bmmnvfKkrg8+f1e3aZuv1rG3bqGmMmhpUhecjUY1w58y1dj2F2Tq8oilIEjwKw51UPPif76RmbTT9msMHuQSUPfUoOBpTe5l5T98Hn9OnwZXZOH4vP61Om2bosGeMNJ20xNYaOQ52KDT5dj6H3WHHb6ey5++ZCfXMN99sNuseQ6K94jhXpTpZlRe/6WkojKIP5/X585zvfwerVq7Fo0aKI1/v444/xj3/8A5dffjleeuklHDlyBNdffz28Xi9uu+02dHR0wOfzoaIidNenoqICBw4cCHufGzZswO23327p75POTvpEDr7WtC2u+/jL0eUYQD7qdxzHnDOnG7691GEs/H+sOWdOx88v2Iq9H0S//cJ5o1j4hdNNPUYsy786H3f+eQuOHE+bt1FKNHXn4vWuZTjQZi6aTa7vQYva/fHKmdtgM5GF9HF7Id7qWYID9fmmxmCF/W72mj5wxNxrOhbvgBeHvS4AwKWufyErQxl3nV0NFdg3PAcHPjQXPrT/rXYAs1Fpb8XZMw7HM9yoCvJ8+NYDs03dVhAFPPK1t5Cda0de6WpT93HTQyLKfrwF1z4Q+VgT8phq3UvZq+/11d/WD8nHdnyvmLENjghZ2GXTRnHxhmW67nMsHj0hjVRC8SumojVikVriK5NRvbQSD13yTxSXZyAz75Om7uPHv6pC3Z1bsPa+JaZuv/jLc3H3OVuw//Dk/5wuyvfhG79YkLD7/90tEp76k/nPBakzH5s9J+NAc5GFowq138OaOZ1f8S6KC1KTLvj6sVlo8lfhwNtdWHq58dvvf49FE83POoqVdZGjsL90cSYAc5HJP3uwCNW3/RPe0dTV/NvqduH4aB0ObO/BGhO337+TRbvMzjyO1WKDqTG8cmwuWv3lOLCtAws+b/yYtH8fO9Yuyj6MZbXjs0BGRm34X/dqHPGK8A54kZlnPPSYd1w2k9ILAGd87yT8+NUtqG9O7GegUODDdQ8sNHVbHqEtQ4AsyRBEwfB97G9lf6czi3eheprxdHhPfyb+3rIK9UPGG3dy9X1ONpbtvTjDxO3372AR8DMz3DjNFbmHw9nn2pFdZO6Y+qNfViP3//0TQyPh3/txz+klGT1gz5/epilCIXsfGYl4i0Z6txkDYN2e3e8ewcIvmHhvq3P61YXvY3Z54hpMRRPvnD6Wto860K2Uww4fvjrr36bvJz/Xh+/+0lzUccmcYvz2yrew7V/R55nTa0fxqfX6IgsFJ/tX7tN3PnZwawsU1KDY1oXzZ36k6zaJUlk6CiB2p/JJL5ErpUYiKL/xjW8oLpdLqa+vj3q9OXPmKHV1dVrEpKIoysaNG5XKykpFURSlsbFRAaC8/fbbIbf7/ve/r6xcuTLsfU61CEorzM86ogCK8sa95nYJF2YfimuXkaQPHqFUZmszdfv3njqoAIpSams3PQa+67wwOzHRsnqclLtfAVi0QyIce4tF5GVjUPF5fWGvs/HzbNfwEvFfph7jvi+w219cZ+72kxWP7nDaug1dvyiOaJBYBrsHtR3XjkOdCXmMlfkfKICiPHfTOwm5fzK1/OvX7yuAokzPkBJy/95Br+KAVwFY9G6q8AilDWdvNnX7r81it7/rLHO3nyjWn7hFARTl5lM2m7r9txaz29/0CXO3VxRFuaiORav+/AJz0T8Xq7e/7wvhx+Dz+pQsDCmAohzfFv38JtLts8E+64+9Zfz2E0mJrUMBzGc9ldraFYDNKc04vo3NsbJgLjJRURSlxt6kAIryveWbTd3+/6lZCzeazFqwQrxz+vefZnN6IxHet3+a/d5WRde/fs8ubX700u3bTd0Hn9O/+BNzt7dCvHP6WHgmYK2jMSH3nyqPrmURueeV6Xvufvc1dv1zdV6fmGMkgjIt2qWtX78eL7zwAjZv3oza2tqo162qqsLcuXPhcARWxefPn4+WlhaMjIygtLQUDocDra2hO5mtra2orKwMe5/Z2dkoKioK+SLRiYXdAALdBY1Q/Arcw+y5MFtDjqQPXgOrXSnDYJfxXWvpfQ+7nxzzNVD468g9zKLJUoE3LeDRDpbfv44umeJsXmzaXKQFL6LPi+oTRqhmkZM9SqGu11e8RcP1yHHmoMLO7l/amZjHkQZZnUBxER0TSfzEpSwyqWG0Er4R6yNCmt9rgw8ZyMQIKhenrplPvB2JpU72eRPcZGoyEuvYZ6nUbO73lNpYfXFxuvlTGbGCN5AxN2/gjR14rduxWFM2tSmJegw3ov1AJ4aRAxv8qFlqrh7gRCHmqMczdU5oxEDHADoU9vlipi4rAAi17LkcQTaGPOZqHst+Nvcy25RNa+4pJq6hUSxxz+l5c70c/fMSwcl+X7nfmijf4HNT6aC55lLxNCKzSrxz+likfSwyVMwz1wgxXQmlxurGx9uIjFgv7gXKoaHIH+K/+c1vxqVaB1MUBevXr8dzzz2Hf/zjH5gxI3ZI6+rVq3HkyBH4/YFi0YcOHUJVVRWysrKQlZWFZcuW4c0339R+7vf78eabb+KUU8wVLCfjiWWsuQR/UxvhccvoA5sI1K0Iv2hMJg6nS0ABWBON+h3GO4JKh9gBQXSaz+3gr6M+FEKuT34qRl9LH7oUtjBZ762Ef9T6znF6umTyhSRpwFyKkjY5NpnSO1nxExc/HOhrid2ERDrAPh/FIk8ihwUxly3q8xMCKw33DGulF8Tl1LmZxK9qSTkcGMUoMtHyvvWL6tJudpJVmxF5EycZxBnssc12JI43pXeiEGezRRypy+SGmsyOd+K8XPNjUI91/NhneAzqsVZcFDklmR+z+THc0P2rnZar7a2m0sMnElFgczf3AeOLBHzuWYgeCHXmNtQKqwKvQ7nBeGM434hPO7eJ1pE4mlgL3skQ75zezec/gv65uFDMgo7kQWte48HnptJx4/Px4Dm92QVvK8Q7p49FOsIbISamuV6qCGVqWaYRfccGqSm+RmTEeqZmcH6/H3feeSdqampQUFCAjz/+GABwyy234NFHH9Wud9lllyE/P3LNrnXr1uFPf/oTnnzySRQWFqKlpQUtLS0YHAwcnK688krcfPPN2vff/OY30dXVhRtuuAGHDh3Ciy++iLvuugvr1q3TrnPjjTfikUcewRNPPIH9+/fjm9/8Jvr7+7Wu3iR+Yg17E0uNxuvtSTtYdGuZrR25xeYnliQ92Ow2iNnsOeWRY0ZIx1nkglg+bHoMeaV5KLWxk1P++kqm+p2BxxxGDtoPGI+UiEXrfB+lS6a4jEW8Nfkq4B0wXn9N8qgnfAnqfD9R5RbnIgPs7yk36lig5LuxZYndjRWd6gndQeu7rvMTk1wMoGROYqKCydTiyHKg1qFGk+22PmJD28TJj7yJkwziPPMdif2jftSPqhkmJjvfTxTiQnUxp9/c76lFOJ1ovF6hNgb1WMePfUZ4B7xo4ps4yyJ3pefHbH4MN0Lap0ajTbIIp3DEcnYcM7OgFMhaaDVdj9mR5UAh2DFVz3F+rJ7GwKKm6U3iQXXBO47XdLysmtO7KvTPS4QSHvFmzdyTLzgBgGSi9iqf0wuQUVSbugySeOf0sUzWrCmhgr2O5FF9XeSnStbCRGJqgfKnP/0pHn/8cdx7773IygqEsS9atAi/+93vdN/Pww8/DFmWsWbNGlRVVWlfmzZt0q4jSRKamwNFwuvq6vDqq69ix44dWLx4Mb797W/jhhtuwE033aRd5+KLL8b//M//4NZbb8VJJ52EvXv34pVXXokazUmMEWeyD3ypU9+bP5gW/p9rPqWXpJd4Uv6lFnZA4OlepsegpoibSQ+K19hJHI96sPQx1HRBsTpy1HL5glJkYRh+ONC0x/hCrZbSm8KUlnRks9sg2NQTl6bYr3GpiX0+Jno3Vqxgi/qS2/qyBtJetsgjZrUkpAEPmZrEfLZ5I31oPEIpFukIO8kSS1IbDcJLjkhDxuecbR91YATZsMOH6pMn95xVS/n3GU/572/rR6fCFjbjiXDiC0H82GdE4+5WKLAjG0MoOyHyIms8Kf/SYR7hZP37Jd3Ek/JvVdaC4GCfHXKL8c3F4EXNZn8FRvqMLfoM9wyj2a9uTkRZ8E6GZM/pA40IrQlakToCwVFmIrS1Be+c5Ac8BIt3Th/LZM2aEirZ60j26Xvup0rWwkRiaoHyD3/4A37729/i8ssvD6kFuWTJkoidssNRFCXs19q1a7XrbNmyBY8//njI7U455RS88847GBoawtGjR/GjH/0oZBwAq2vpdrsxPDyMd999F6tWrTLzq5II+JtY6jUeWcPrgbicqemKRqzH63aYSfmXuqxJaeEp4jxlPJmkgwOh3++zPuVWT+f7eOpdDXYNok1RFygppXccIycuydqNdcWZnhgNPzFxFaY2Go1MLmIxex/xxUQrSQ1qNEjVqOX3bcTYjsRGaCm9jsmf0lu5uBwZ8MKHDDS/Zyzln0c4FcFcx2eOH+ta/eWG6w7qqQsNBI7ZUrvxxRce4eSqmlwRTuG45pqvt2dVDTkhgx335FbjWQnBm5cK7GjcbWxBiV8/B4MonZfa6Olkz+m1iDdv5KxLQ2PoC/Q3MBOhzef0iS7TE0u8NWxjsaJMRjoSathnSC8KY5bc8o/6Ue+dGlkLE4mpBcrGxkbMnj173OV+vx9er/UhyCT9iCexhUnJa7wpCY/24dE/ZOLjkWLBaRV6uXkNp4XmavZoY1BTxHl6STJJx0IPgDzqwdLHUNMFxROiRy3zelfuD41FETXsYpPjfPRh2gyn4fFNdkImm7DqOXFJ1m4sPwEwW+8qGuljtsgjlg7EuCYh+olVbI4o1VsfsSG1qZs4cTRNsUJBZQGKbWrdQYMlRyZr04JwHFkO1GaYS/l371EjvONsRFY8axrywBaW+DFQ9xjUKOBodaGBwDHbTMr/ZI1wCieelH93ozVZC0IWW5iT243P4cbODdy7jS0o8euLmanPWuB/R7eZMl4DamSzgTm9UMXeI7zJUDwUvwLJW6V9b6Ypm/tj9vuLZdaXzzEqnhq2sWhZUyksKZAIvG68Ajt6m6JHn0+lRmQTialZ3IIFC/DWW2+Nu/zpp5/GySefHPegSPqrXV4JG/wYQi7a9xubWEotrCyAKKam2zKxnjhLTfnvMLb76R3woskXu4aTrjHw9KCW5EeduNWU3iywSa3bbe3kUvHr73xvtt5VIKXXfA2nyUzIZhNVuSP63zWZNeQC6YnWF1Dn9YV5vWFCrMAXD91t1te5lXrY+yHWJk4yaB2JDTawmqxNCyIxm/JvVYSTzW6DmKUuku41Fi0uHVU3caLUhQaCUv6HjWcmuD2TM8IpHD4HbPRVYnTIWBS0VVkLzhz2/pM7jEdhy22hi5pGF5R41oKYBlkL2py+09icfnRoFI0+42nqQjV7nD4UGl5MHKvtow5twclsUzZetzIdmqbwzxf3EWsDwAY6BtDOs6ZS2AgoEXKcOdr5WKx6su4d7LUxFRqRTSSmFihvvfVWrF+/Hvfccw/8fj+effZZXHvttfjZz36GW2+91eoxkjSUVZCFKrtaRNlgvT2evpHKLnXEWi51p9TdZyzlv2lPK/xwIAvDqFgU5wKl+npyd1kfTRaL1Mle0ysKD7LvLU65De58L66qinpdV425elfuj/jk2HhR9KlAyGEpdnJn9BOX1n3tWg25mmWVCR0TPwFo9ldiuMfaqF2pgy3y8HrDhFjBdQJbaJFkp+X37R5ST4zToIauS1BLjhw0lnLKN7emQkovALjUeqHuw8Z+X5614CqPv6QLP+YZzTrgx1hXTfQFFXEle132QIDHbXDBepJGOIVTsagMmRgxlfLPsxZcC+OLwBPy1ON8t/FFsrGblzwLQS9+fVcaZC3wOb1kck6fiRFDc/rgzuvBzYbM4OekVfZWrSmbe5fBQBp1Tu+akxXjmolndk4fC2+EWIgeOF2T7/NFb934qZS1MJGYerV/4QtfwP/93//hjTfeQH5+Pm699Vbs378f//d//4czzzzT6jGSNMXfzPzNrRfvbicumnwfiFMVjxSr91bGrPcRTKvhlBG9hpMerhPZBMds98R4SP1sEnfaQjUVQ7a26x9PE9TT+V6rd9VhLOKC1xpylaV+cpyOhDx28uHpiv765pPjGkcLMnISu7hXOq8EOWAn6EbrXcXCaziJ862pCUUIEF80WTSyJEOGGkG5MrEbA3qY7UgstakpvdOnRhQ7rxfK64fqZWUjMn7MM1pvT09daADIK81DqU2dLxtI+R/sGpy0EU7hsHp7rCmqkZR/K7MWhHz2GpA9xm87dvNSajQ2p+XXF2MseCdD/HP6ZkNz+qyCLG0uY6aDesgY1BrwrrwOuArU953RCO3+9GmaYnZOH4vWCCh7cmZN6a0ny7MWXMWTvxHZRGJ6ReC0007D66+/jra2NgwMDGDbtm0466yzrBwbSXO8q6CRentWpvSS9FGztAI2+DGMHLQf0F93h6fAxKrhpAd/PTX5KuAdSF4tXN+IDw3q5PjUs9lijpmOoNHwNEE9ne/N1rvi9UPTIaUlHQkF6olLjAAYPhEW86wvaD6WzW6DmGkuPTEaxa9AGlFP+E4y3giNkEjqlrGFyW5lWszaUEbU72IRV8W2LhRUpsFJpcmOxJJHXWSdO/lTeoFAyj+vH6qX1GVdIzJexkIyWG9P6tW/iSPmsGO39L5H9/3zCKcC9E7KCKdwzNTba/vIus73QiF7Lcg9xhdsZA97z2eCRWFK7cZKTaRT1oLpOb3OuqzhCHZ221gRbzHHcJiXyeg11ZQteE4vLk1+wMNY8dSwjcaqzvfpSqsb3xZ9jYI3IhMrp0bWwkRhaoHymmuuwZYtWyweCploxAr1ICzpryXJw/+zMYSyE6hb1mSRmZeJahMp/7xOYqwaTnqULyhFFobhhwNNe6yNJoumdV87vMiCA6NYdelMAEC7UobBLuu6ifM0QVGIHa3MI5Tcw8YaWPH6obz2EAklFLG/pdwb/cRFmxwnaTeW16uysoB65+EuDIJNimuXpz4ajUweRbVFcNo8AAKdmK3AF3547cdUE9XUQKMdiaUhNWIuDdLUkyFw8m1sAU5rRBZncz0gsCAkdepfUFL8CqRhdbM9Rl1oABCdasr/If3zgske4RSOWKzW0DawoMTnnFZ0vhfUl6HcZ/z0mG9ezs85xsbVG/t1EczIgneixT2nLzY+pxcc5juoh4whaMHJTIR28Jy+aom1kf5mmJ3Tx8IjxnnH9slGqxvfHv2zZCo1IptITC1Qtre345xzzkFdXR2+//3vY+/evRYPi0wE/M1spN6eFv6fGX9KL0kvgZR//TWWeE0Vsdp4QfKxWHqQGk22J/HRaxxPRapxtKBkTjEKwRYRefSDJY9hoPN93Qq2oNSHQsj1+ssvBFJ6Ux99lI4CJy7RF3B5d2KxMjlRvGKJmp5osN5VNNJOtshTaW9FdhHVCibWErPVE18D0WSxBDZxjNX4SxRxoVpyxEBH4oGOAXQoagmcKZDSCwQWYvlinx4spZfVYraiERlP45R69UeLB9eF5sfcqI9Rzo7d0nEDm4b7p15daD4XNLKgZGUNOWEae1y53/hCp9zL5rMnVqpz4ZEK3QtK6Zi1kOw5vZClL+It5hiCFpwCEdr6m7IFz+kTXaZHD7Nz+lgme9aUVje+K3rJBF6Sayo0IptITK0Q/f3vf0dzczNuueUW7NixA8uWLcPChQtx11134fjx4xYPkaQrcS77wJc8+uvt8SLkVqT0kvRiJuVfatdXw0n3GEykB8VL+lCdHOd3spRbfvL9nnUnFUY635upd6X4FUhe6074JiOhmB0u5YHoJy7JriHH61UZrXcVjXbCp6OkACFGiUVqNNkB6+rd8lqPYll80TdW4amBRjoSBzctCG4aMZnVLWcLkx7FiZ4GfSffPMLJipReILAgJHn1RygZqQsNBKX8t+hf+JrsEU7hiDPYccxtIOWf15CzovO9UMwWpORB481R5H5220Xz2OZkPwrQfcyj67ZdR7sxABY5WbssPTYnzMzp+fPGn0cjtIi3jvg2d/k5qTg3R1t0MtKULXhOnw7M1rCNhXdot6JMRjoS8tnrSO6OUTd+CjUim0hMn9FMmzYN1113HbZs2QK32421a9fij3/8I2bPnm3l+Ega429mI/X2rEzpJemF1+/g6RV68JoqPM0r7jGoryv+OksGSe0+yifHvJ4Lj36w5DHUNEFxtr5oNqP1rtr3d2AYObDBj5ql6TE5TjdCiXriMhT9OUh2DTm+uO82WO8qGvdBdqIgOqloOLGeqHZeNtpAJhpe65EvBKVa5eJywx2Jp2JKb2F1IabZ2O/N64jGYnUjMl5vbwi56Diob1HCSF1oABDnsOOG1KU/JX2yRziFI84zXm/PyhpyQin7HJGH9UfccfIgu21FtQPlNnUOtlPna1q9XoW9DTlO44+dCPHM6V0m0tSFXDXirTO+bBBtwWmx01RTtrFz+nRgpoZtLFqZjDRoBJQIQoFaTzZKAPBUa0Q2kcQdcuH1erFz5068++67OH78OCoq6AmeKsTl7AO/1V+OIY++qIVA+H/qu9QRa5lK+VcnDXpqOOkag5YelLzyAVpKb5W6+K5GOxjtCBr1MdTO5OIifVE1Rutd8RO+KnsrsgqMRw5MBUIp+7vII9FPHpJdQ47XqzJa7yoaXldYrIwv1YqQcMRa3kDGuvQ5qYtv4qTH55c9w45aXnJEZ0fiyd60IBIxmy3O6M06sLoRWXZRNirt6hh01tszUhcaCNTKlAb0ZyhMxbrQ2oLSkP5zSStryAnl7L5kr/ENRr55KZRmagvXeheUjC54J0Oy5/RCHpu/82ZDZgx2DaKNLzgtLzfVlG3snD4dmKlhG41/1I96r1pSYJJmTQXqxkc+H5yKjcgmCtNn8Zs3b8a1116LiooKrF27FkVFRXjhhRfQ0NBg5fhIGiueNQ15YFFiDbv0hZ1LHeyg75ppTUovSR9GU/5lSUYP2AGBp3nFPQY1moynjicDr23Da93waAce/RAv74DxzvdG611ZWcNpshIq2PMseyNHBqSihpxrKZtcSiPWFVCXWtgJiYuKhpME4IuIUqd1kRu81qMVTVOsIuYbKzkyFVN6AUAUPAACi36xJKIRmZirplB+oK/enpG60EDg2G0k5Z/XhXal0Ws60cSVbNFEhgBZ0vlcWFhDTqhk9yGPGv9skkfYbYWyLLim8QUlncEbh3jWgnU1BuOV7Dm9UMg+/6JFvMXCz0Xz0YdpM5ymmrKNndOnAzM1bKNpP9A56bOmBCf7V+6LfC42FbMWJgpT776amhqcd9556OjowG9/+1u0trbisccew3/8x3/AZqMneKqw2W0Qs9jug3u3zrQYntKbBl3qiLW0Yvc6U/7d29lkocTWifxya14PgY6gTkvuTw+3rKb0qpNjXs/F3WHN79S4uxV+OJCFYZQvKNV1G57m6G7WF02knfBNo5TeSLQTF3/kE5dU1JDj9aoGkI+uo9bUPZU87ISYn6AQYiWeUuY20EAmGt+IDw0+NRpkqb7PyGQQS9jCpPuwvtTTqZjSCwBiOVuc0Zvy79ZSeq2LcDJab48fW/XUhQaAikVlyMIw/HCgaU/shRL/qH9K1oXOL89HiY2dT+hN+XcPqlF7FtSQE6rYHNKjGD9+e7zsc02oyNEWrt06F5T49fQueCcDn9O7dc7peX1Es3N6Qf2TR4t4i8W9h20KiVmBBSejTdnGzunTgdE5fSzuHey9VW2Pv/N9uhKmseMpL70QzlRsRDZRmPoU+MlPfoLm5mY899xz+PKXv4zsbOryOVW51De1nnp7il+Be1g9ibAopZekD9dKtlDSppRhsCt2JASfLLhy9E1C9TBTbyZe0lDo5FjrCNpnTSdG3pFczGyGPUPfR7ZrrlrvqltfFICW0lsRfw2nyUqoZhPuHqUwYqSiey/7PHQlcTc2x5mDCp6eqLPeVSxaDSedJQUIMcK1nL2+GkYr4RuJvxRG83tt8CEDGfCicnHyPvtjcRksOcKbFrhmT84TxkhcdcZS/nmEk8tEI45I+MIQPxbGHEM328Thx9pY7Bl21PGU/z2xN/SnQoRTJKI6J9SzoBScteBaFbubeixCLXteR5Ctu3QVxzcvhao8iCJPj9a5SdyaflkLfE7frndOz9PUTc7pBSfvoG6+pEG4BSejTdn4nN61xGl6HFYzOqePhWdNufLTp6SA1fTUjXd/PDWzFiYCU0f3a6+9Fk6nEwDQ0NBAad1TmFjGPvD11NuT63vQB3bwr1sR/0SCpBenS0ABWBSCnpR/XkuF11axAk8r6TGQHhSPvpY+dClsIZJPjnm0Q723Ev7R+CNheHog71CuB19Y4rUrYz6GhTWcJiunyP6mfjjQ1xI+ZTNVNeS0elc60xOjGe4ZRotfLSmwPH0We8jkUbWkHA6MYhSZaHk//kV1XuOxNqMFjqz0KR/DO9lK7foikSd704JItJT/Lp0baham9Gpj4PX2WvQtOAbqQuuP2uPHcF5DM+r9q7UwJ3OEUyS8rqeelH+rsxYKqwKvQblBf0aJb8Snnd8I1fmBpkjd+tLz+fX47dJB8Jye/52jMVqXddzjlcSOeIs5BvVc1FUWWIw00pQteE6fTk1TjM7pY7Gy8326clao9WRHIh8npmrWwkRgaoHS7/fjjjvugCAIcLlccLlccDqduPPOO+H305M8lYg1ar29xtgnBTz8v8zWjtzi9AmdJ9aw2W1aKgVPs4iG11LhtVWsEJwexFPIE4nXtBEgo6iWTSB4R9Bh5KD9QPxF/HlHct6hXA9e76rJVwHvQOw0OHc37zxNKb2R5BbnIgPsbyk3Rlig5DXkypK7G8vrVumtdxVNw052IpKLAZTMsSYKmJBgjiwHah3GGshE496nNk3Jt6ZpilWMdCSeqim9QKBuqLtP54bakHUpvdoY1GOfW0e9Pe+AF018E0dnXWggcAx3H4l9TJb2qdFoU7AutJGUf6tryDmyHCgEO55GOs6H09MYWMwU6oqMbxIPqgveFr6m4xU8p9fTwIo/X/z5M0pPxFvMMYRZcOJN2dxNsSMzw83p04HROX0sklYmY/JmTQXqxudFvA7PWphKjcgmClMLlP/1X/+FX/7yl7j77ruxZ88e7NmzB3fddRcefPBB3HLLLVaPkaQxcSZ7U0udkT8AOJ6ukU5d6oi1RAMp/1IL2yXltVWs4jKQHhQvbXKcE1gMzczLRLVdndTp7Aga9THU9EAjne/LF5QaqnfFU3rTKaUl3djsNgg29cSlKfzrW1InwMnejdXSE93xv5ekvbyGUwsVDScJwxcT9USTxSIdYSdZrpL0igYx0pG47aMOjCAbdvhQfXL6RO4kA68b2uCLnfLf39aPTkVtiGRhhJNrMVsY0lNDu3H3/2/vzuPbqO/88b8k3+f4lG8pztHcCeSA0nB9S0rotwtk6ZaFB+VoadmlDpBSCsuXo+UogdAuR+kDtmxL4NtCu/v9baCbfZA2TXEgkISQECAQTAKJlMNHEsfjI741vz9mPiPJ1jGSR9LIej0fDz/iSGN5bI+kz7znfbRDgR05GEDlLOPBZGcUJf/p3BfaqZf8R86ki0fVgpShvo7IbcYvNIpgZg4GkFOcoweUWr1VGOoNHwQa7B5Eq1erwIki4J0IUa3pWye2phcT1LuGIp9PhtyHE+MDTtFkaAdb01tBtGv6SNKhakrvGz8aOotZVC2k0yCyVBFTgPLFF1/Ev//7v+Pmm2/GggULsGDBAvzgBz/A888/j3Xr1pm8i2Rler+9nsiZNnpJb4zp/2R9oo+HkZJ/T2d8SlpEybg43uLJ0xJ8cSz6uogsiAl9D23yvZhQbkQ0/a76O/vRoWg9B1nSG1akExff1djEluRF2+8qHL2HUyGbhlP8OMvU55IILk6E54iWDVJjbDpyooiWI0YmEuslvRnpV9JbvcCBTAxjFJlo/SB8yb/IcCqGDMlpYgal9t7X7nVE7D0o3lMbstoM94UGfO/hnuORK4jSIcMpFOeMKAJKB83vISdlqu+BcrvxTEBx0VKyqQHlytkVyMEAFNhxdHf4gJK4Pxf9qJhprezpqNb0Wn9E8feLli/jLfYBk2LyvXO279hxzVPPNTwGhrKFWtMnW7Q9bCOJR5sMq5Hq1GOgG0VB2215R7w4PBzYmousI6YAZWdnJ2bNmjXu9lmzZqGz03ifNEp9zjPUwKRnuDrk4AjBY8EpdWQukTkmyizC8ZzWsiBMvnIlSsY9BqcnToTnoFbSUhm4kBV9XYxOBA37PbTyQDGh3Ci939Un4bOKRL/QAvSitLEk6v1LJ1KWungNdeKSrB5y0fa7CsfzhRrkcVYYayhPFAtnjVqm5jk88QwOT4d2EWeKeUNTzFBYXYgym/o6HGkisRhakI4lvRnZGajPNFby7yvpNW+4HgCUTStFPtQgU6Qe2rH0hQZ87+FGSv7TIcMpFOdcrTzaSEApDj3kpGw1KCcfN75+E2sCKVM9Nmx2G5xZreo+Rggo6VULWdarWohqTd8n1vSxlUaLCepi2FC0FK8StE2GnqFtYChbqDW9FRhd0xuhD0K0UEsBs4mBVwrsQfvGp/MgslQQ02pu4cKFeOaZZ8bd/swzz2DhwoUT3ilKHaLf3gDycKIl/Juwu1W9quZ0xj9wRMkhyipEmUUoIwMjODoan5IWvTyoLf5ZKKFKekXWg8iCiJXijX3yveh3JXpYhuIr6U3c5OlUJeWoi1b5xPjfqXfEi8Mjybkaa2YDdc9RraVA3cSnKxOFIoKJRgfIhOPp1nroRnkRJxGMTiROh6EF4Rgt+Y/XIDKb3QZnthYk3RM+8BhLX2jAr+R/MHKlgkfrhZmOfaH9S/5HBsJnRcejakHKVZ+L8gnjGdlyh/o1UpYvk1NUIXj2hX9O6wHvIusl+MS0pl8U2zpEqlW/Ry+KIgYSgzm+70TQgFM0Q9mS1abHCKNr+kj6O/txXFRNWWgQkNlyS3KRDe25HKSfbDoPIksFMQUo165di9/+9reYM2cObrzxRtx4442YM2cOXnjhBTz++ONm7yNZWE5xDqrt2gI8Qr89Pf1/unWm1JG5RFmFKLMI5dj77fAiA1kYQtU8kwOUIpusM/49RTydwRfH+kTQ9okd6xOZfG+035Ve0lvEkt5IpFw18CyfHH/ikswectH0u4rEfVw7pqeyaTjFjygt88gTz+DwDGoDSxaUTPixzOaUtJYjESYSp3NJL2C85D+eg8iM9tuLpS804Cv57zZS8i8ynCx4TMdb9QIHsjBkqOQ/HlULUp42DO+U8b+vuGgpLmICgLNCBJQiBFlF1UK59aoWolnTjyITWRhC9YLYWgX5T2H3HzpklDgHrbG3I7vQV2YezVC2UGt6K4imh204YiJ7IXpQ4pq8GZQA9L7xXUeCBCjTeBBZKojpKL/gggvQ0tKCK664Al1dXejq6sIVV1yBzz77DOedd57Z+0gW58xTn9yejyIsuLTsHpHtQ5OPyBzzDNeELfnXezhltkbVw8nQPmgl46KEPJ70xfGYMnX95NvARNCwj79TLTWrsJ1AfkWUJd4G+135Tvistzi2GilfnLiMv7qezB5ylbMrkIt+KLDrU7hj5evhFHsfKKJIROBFTGSOVfeRbnQp6mOJAJCViFLBSBOJ07mkF/D1DxX9REOJZ4aTaGshAkYh9yGGvtAAUOAoQLlNyxTdGbqMPN37Qtsz7YZK/uPVQ04qUP/+cpfxrxEXLUvyfWXhIoAd8SKxhasWErmmzy7MRi608vooJqjr+xCmTYbhDO0Qa3oriKaHbTi+NhmTv2oqXD/ZdB5ElgpijgyUl5fjsssuw3e+8x1cf/31OOuss/Dee+/hT3/6k5n7RylAPLndn4Xu1zJ8ehjHRtWTB9fS9FtwpQtR8j+IXBzfF3ph6d6rHjPR9nAyQmSTHTVQHjQRaknv+H43gK+vi9vARNBw3B90qY+XG/00cFHu6I7Q78pzVOvhVGe9kharkQrVEwg5yLWYZPaQU/tdGStPDEfxKvAMqSd8rjMjDz4jipUoLetUyoL2hzJK9HYstZ1CUa0FTyq1liPuY+EvWqTD0IJw9JL/jvAlze44DiIT74HiPTHkPnRrF3FiaCmgl/yHuaDvn+GUrn2hXYVaQClMv72OT4KX9E6UVKQeB3K38eCN3KU+z6V835rTNVU9jtzHwx8n4v5oA96J4L+m7/gk9NpGBP4muqaX7OrjiKFD0XB/pgahggWcjGRoh1vTW4HRNX0k7k/Sp2pK7xvfMT4+ke5VC1YXU4By48aNcDqdOOecc3DZZZdh5cqV+sff//3fm72PZHFi6I3HE/rqmijpzcEAKmdZ74WfzJFdmI0au5oZEK7kX+/hVBb9IiSSqnmVyMIQvMjAsffDN7ufiLYPOzCM7KAlveLk+7hSif7O2EvRRFmgmEweDdHvyj0YfoCV56S2OGZJb0RSsfp7lHvGn7gku4ec6F81kQbqJ/d3oh/q8VC/JLqWAkTRKK4vhgSt/Pnd2LN+4zU0xSzO6dpE4lPhS1DTYWhBOL6S/5Kw28VzEJl4D/ScCB1QUryKr6VAlH2hAcApqReywpX8p1OGUyhibRguoBSvHnIlJeq/cq/xU2Rx0VIq8mVBiioET0/440Tcb8WqhUSv6aWM6Ceo6/sgAk5V448ZI0PZxJo+AyMJb9NjhNE1fSR61VSF+W0yrEbvG398/DGR7lULVhdTgPKWW27Bt771LRw7dgxerzfgY3TUeinqFF+uKZH77enp/1ltppf0krW4tAwykVEWjCh5cdWZn+Foz7SjIdPY9MSJEKVHdRltyMwNDO6VuCQUQr2KK7IhYvoebnUR4qqKfhq48yw1wNSLIsiHw/wtepIzeToVSVrsQO4dn+ngdquvg66a5FyNFf2rIpUnhuN5Tw3yVNvbkVPMXsEUX65cLes3wgCZcPSLOFLsjxFPrvmRJxL7Dy1wnZ2eFwZcZ0QeIOOf4eRaPPGBYGPpAaUw/fa63LLeF9p5dk3U38NVFbnkn32h/fvthQ4eiDWmqyD6CpNwpFL1e8p9xoOeco+6ppX8uvo4z1DXVp6hqpABpYCqhUXWTN7wrelDXyj39WWd2Jpeyg6d8RZJuICTkaFs4db0VmB0TR+JmMjuapj8VVN63/jO8bEpdxoPIksFMUWK2tvbcfvtt6OqamJXGNasWYOlS5eiqKgIDocDK1euREtLS9ivWbduHWw2W8BHbm7gwXXDDTeM2+aSSy6Z0L5SaOLJHa7fnj6lLg4lvWQtorxC9PcIRvRQiVdJizjOIvWbmQjPx2JxPL7sxWa3wZmjXXX+IPaTDE+bmn0Ty+T7/Ip8VNi0hWWIfleKV4FH9HA6gyW9kUhl6ltmV1/2uPs8HdrieEpyrsaK/lWin1Us9DL1PHNP+IiCcRZrGZSfxt7/VgR6nI7oM24SQUy0DddyRFzEKkJ3wKCIdCL6h55SStFzLPj7dvve4yGrFszgCyiFzlAS76WVtuPIK4u+HF+U/HtaQwe/0inDKRRnoyj5D/07jlfVglSmBqfk/vHv86HIferXSCW+9//6xeox2odCnDrYFfTrOj8/hdMoCNjeaoyt6dXzQPF3i5We8XYi+knV4hzUNXN8wMnIUDaxphf9Kq3GyJreiHhMvrcqqSBM3/g0HkSWCmJ6JfmHf/gHNDc3T/ibb9myBU1NTdi+fTs2bdqE4eFhXHzxxejrC58iXlxcjNbWVv3D7XaP2+aSSy4J2OaVV16Z8P5ScKIkyROm356e/l9ufkkvWYvo5xGu5N+j9VCJpYeToX0Q5UGfR7/IMcqzX/05Qy2OjU4EDfs9tLLAWCffi96VoTKUTrScxADyTO/hNFlJ5dqJy8D4v4enS30ddH4pOT3kfA3UY39OeUQPpxI2Daf4czrUAEykATLheFrF0JTYS97iychEYpb0AkW1RSi1qb+Hw+8FP/kWJabxynASbS36kY+T+4NfTBe9I2O9iOOcob53hCv5FxlO8RgElCqcM9X3MU93mIBSnHrISRVq4EYeNJ5ZJferXyOV+k6r88ry4LBpa7D3Qjz3tdur7B3ILbFmJpdvTR8mm1Ws6WdObE0v5WkZbyejz8QMF3AyMpQt0preCiKt6Y2IZ5sMq5EKtX6yY5J//asW0nEQWSqI6R3+mWeewbe+9S289dZbmD9/PrKyAqPwt956q6HH2bhxY8D/161bB4fDgV27duH8888P+XU2mw3V1eHLYHJyciJuQ+YQT+52rwMDXQNB32R96f9sATDZOV02YCfgbgtTSqGVccXSw8nQPtSOAF8A7sPxaycgetmI3jbj9qGiHzjhy4aI6XucVrNvYp187yyRsbsf8HwWPBPDvbMDQAWq7R3IKebrZSRShZpRIQ8FeY0bSO7VWKP9rsIRLQWc1dGXVxFFy1mvAHt9QcZYeDrFRRzj2U6JJCYSHxxxwrP7BBrOrh23jT60oLgrwXtnLc6cDpwaKIV7zynMuWz8/fogjvyTAOpM//45xTmotrejzVsF984OVMwcX3LraykQW4mlmA7s7gtdou45ITKcrFdmmihibSj6fQYTrx5ykkN9XHnY+MVGcdFSBDcFZ95xdJyuhOfDLpzxj+O/LjDgbc1AiVjTh23jNRB7X1Z/YsiQGDpkVH9n+Mn3Y4eyFVaPD85FWtNbQaQ1fSTeEW9cJt9bla9vfOC5oFq10IgC9KbtIDKri+nd75VXXsFf/vIX5Obmorm5GTab783BZrMZDlCOJWsh7rKy8KWGvb29cLlc8Hq9WLRoER555BHMnTs3YJvm5mY4HA6Ulpbiq1/9Kh5++GGUlwd/Mg4ODmJw0HdC1t0de2+HdFQ2rRT56MNpFODIrnZMv8g1bpt4l/SSdUQq+Zc9MrqhXhUXZV2m70OjHdjqO+7iQUwbFb1txu1DvRf41JcNES3/yfdiMnm0nI5BoBXwHApRrqaX9J4AwABlJFKV+jeXhwOb2Z8+cRonFC2YvDQ5mahj+13Fkomln/A50zOLixJLHyBzMvZMDnev9ryba70J3oKzoBMHZSc8n/RiWZD7WdKrckpd+GAg9AAZUWLqLItfhrcz7zja+qrg+UjG4mD7IC7ixNAXGvC9l4uS/2CZoKIHpnP25M9wCkWsDbuUEnQf6UZx/fj1ZLwm30vV6uPJI8Z///KQ+jVSZeCFEmdJN9477atOGMtXtWDd804ja3rZpDW9GDI0NuMtkiO72gFMCRlwEkPZZEjwvNuGOZdNH7dNpDW9FURa00dy/NOTGERl2lRNSSXqv2P7xqtVC41wZrfDZp+W8P2iyGJ6Ft5zzz144IEHIMsyDh06hIMHD+ofX3zxRUw74vV6sXr1aixbtgzz5s0Lud3MmTPx29/+Fq+99hp+97vfwev14itf+QqOHDmib3PJJZfgpZdewubNm/HYY49hy5Yt+PrXvx5ygM+aNWsgSZL+0dDQENPPkK5sdhuc2Vqz+z0hymLiXNJL1qGXUoQo+Re9U8ptJ1HgiM/UQpfIJtOOu3iItDh2TVevpItsiGgde1+dfJ+NQTjmxDYQQO931Ra814w44XOVWXdxbCX6iYs38MTFCj3kjPS7isRzShv+MIMDcij+RImZpy+2/rejQ6M4MqoNmIjD0BSzOMvVksFQE4lZ0qsSfURDlfzrGU7V8ctwckXotzeRvtAAUDWvElkYghcZOPb++FJ2tS+0OnwnHTKcQimsLkSZTT2fOLwrRHm0KOmdH7oMPBZSjXqeIivGL3rII+o6T1zEFEQgWwS2x5powDsRIq3pxd+nzNYZNDMxGmLI0NiMt0jEuacacAp+gTXSULZ4BbzNFGlNH4lok2H25HurkkrV91bRgkEQrbdcxZyLYVUxBSiHhobwj//4j7DbzbvK0NTUhL179+IPf/hD2O3OOeccXHfddTjjjDNwwQUX4L/+679QWVmJf/u3f9O3ueqqq3DZZZdh/vz5WLlyJTZs2ICdO3eG7Jt59913Q5Zl/ePw4cOm/VzpIly/PcWrwD1oTvo/WZ8or+hQKtHfOT4TQi9pyQ2+6DRlH/TyoPiVzIheNqEWx/rJd5iJoGEfX5tA3pAZ++R7vd9VZ/CFtugT6qxKzuTpVCPVqich3UpRwBAFK/SQM9LvKhJPv5aNZvIJH1EwYoDMkZFqjA5F3wqj9YMOjCITmRhG9QJrlkcCgLMm/ETidBpaEI7oIxqq5D8Rg8j0gFKIHtoT7Qttz7SjIbNVfaz3xw/jOL7vBAaRmzYZTuGINaJ7z/hBgwE95EyuWpDq1fXSIHIx2G0scCiPqseFCG4KIpAtAttjedpFwNu6VQuR1vTuD7rU7UxY04shQ2LokFHi3FOciwYTaShbpDW9FURa00ciJrE788cP95yMQvWNZ9WC9cV01nv99dfjj3/8o2k7sWrVKmzYsAFvvPEG6uvro/rarKwsnHnmmThw4EDIbaZOnYqKioqQ2+Tk5KC4uDjgg6LjrFBf8D1fjG9sLB/uRg/U32nDUpaRTnaljSUogJoxopZdBJpoDycjRJlJNyTInihrRQzo6+jDSUXNbgi1OBbZD57hmpATQcPxfKL+DsVE8liIskfP6eCZGPHq4TRZiRMXLzLQ2+ZrpC4WvMnuIScGN4gThmgMdg+i1av1JoqxpQBRNGoWOpCBEQwjG+17ox864tmtnmTVZ7YhI9u67WNEyWCoicTpNLQgHL3kvzP47yERg8jEe6GnLXgAcqJ9oQHfe7roqRnw+FqGU429HdmF1uyrmihOSQsoBSn5F1ULhehBicvcgFJRje/4kw9HXqeODo3q5zjiIqbgG4oU4iJxClQtGF3Tu6SJr7XFkKGxGW+R6AGnyuDBRwBhh7IZWdNbQaQ1fSR6m4zS9BiEKFouiBYMAqsWrC+mAOXo6CjWrl2LCy64ALfccgtuv/32gA+jFEXBqlWrsH79evztb39DY2NjTPvy0UcfoaamJuQ2R44cwcmTJ8NuQxPjrFOf5O4j408SRElvpe048itY4j3ZqSX/6t88WMm/+6B6rIhyrngocBSg3KZmJ4jjz0xiymgxZEjO4IvjukVVsMGLQeTi+L7or1aKCeQTmXzv3+9q+PT4sjjRU0j0GKLw8ivykQGtiftRvwClRa7Gukq1E7oQ/a7COfKeesKXh9NBh0MQmS0zNxN1GVrZ3e4YXiPF0JSC8ZloViJa27iDtBxJt6EF4egn333Bfw9ukeEUx0Fkvn574wNKZvSFBgBnmfqeLt7j/bm1ChNXmmQ4heMKU/Lvfl8r6Y1D1UJGdgaKoAYm5WOR1189rb61wNgWL8556vrQfTp4Cwr3aS0LdAIB73jzX9OL37s/8fcxY02vT1AfiC5g6zmqBZzqQgecwmVoe95V34fCremtYGwP22iJSexiMvtk5+sbHxh74CAy64spQPnRRx/hzDPPhN1ux969e/H+++/rH3v27DH8OE1NTfjd736Hl19+GUVFRWhra0NbWxv6+30neddddx3uvvtu/f8PPvgg/vKXv+CLL77A7t278e1vfxtutxvf+973AKgDdH784x9j+/btOHToEDZv3ozLL78c06dPx4oVK2L5cckA51T1Se45OT4AKfp9iOwemvzClfyL3imil0rc9kErNxEl5WbyLY5Dl7Rk5Weh1q4t6t6L/tgXE8idtdEvQoSqeZXIxmDIflfx6uE0WdnsNki28ScuVrkaG6nfVTi+Hk5tSStTp/Qjgovuj6LPqBc9HZ1lvRG2TC69h9vA+MwcdWhBLuwYZUlvmJL/RGU4iUBRsH57R3dPvC804HtP9xwZfwqWbhlO4ej99lrHZ9PpVQthSnonQspQX1Pk1tAZeYJ8RP1b5WAAOcWBgTXXEvU4avVWYag3MCiUSlULYdf0reat6UNlvEXiFgGnqaEDTuGGsvna9MSv9ZQZ/Nf0R3e1Rf317rb0qprS+8aPBl5w4iAy64spdPzGG2+Y8s2fffZZAMCFF14YcPsLL7yAG264AQDg8XgCel2eOnUK3//+99HW1obS0lIsXrwY77zzDubMmQMAyMjIwIcffogXX3wRXV1dqK2txcUXX4yHHnoIOTnWTaFPda65Wr+9nvHN7j2fxb+kl6zFVXkaOOnLLPMneqe4vhTf56NT6sb7/cHLgybK02KspNeZfwJHe2vg2StjabTf44T6xuqaGnvpotrvqg2fj7jgef8kXMt8LTQGugbQ7tUyUpZYt3+b1UgZvegcKYPc5juu3CfU1z8xGClZnE4bsNvX1yoaeg+nwvic8BEF4yrrxdbu0ANkwhE9HUWPR6tynqUGIWSt5Yh/ho5a0luJ2ox2ZOXXJmkPraFmoQOZGMYIstD2YSvqlviqntSqhakohmx6Sa8/8V7Y5q3CYPdgQMBJ7RlZD2dWK+yZU2L+Hq6pGcBWwHN8fOVCumU4heOcEbrkX6wtXZXxqVqQMvtwZBSQ2yNnBYogpmTrARD4N62cXYEcDGAQuTi6ux2N5/uGsB7d3Q7AiVz0o3K2dYd8ARHW9KIv64yJtyTQM95GohsuqQecwrTJCDeUTazpXZK11z/h1vRGiEFArlnWHQRkJqlO/Zt3owjeES/smXZ4R7wcRJYCkprbqiiRr7aMHWzzxBNP4Iknngi5fV5eHv785z9PdNcoSs4z1Bd8z3A1FK8SkIHjOWT9KXVkLme9F/jUV3bhT/ROEeVccdsHxwDQFrw8aKI8Wpm6yxF+cews7cG2XoScCBr2e2jlgKI8MFbOwk583uXSe1oKai8hF/LRh7JpHF5lVElWHzASeOJilR5ykfpdhSP6B4t+wkSJ4KwZBg5Bn9AcDU+HejIrejxalZhI3KmU4fCujsAAZcDQgvQOUGZkZ6A+8xgOjTTAs/tEQIAyMMMpfgHK8hllyMNp9CMfR95rw7Svunz7ENAXekrM30O8p3uClPyzL7SPc66WzRqk5D/eVQtSdj8wCHR1RF67dbWq60ApsxdAYCakzW6DM6sV+4cb4Xn/ZECAUq1acMKZ1QabPfoWZ4mkr+mPBVnT94k1/cTL1Evq1MCkGDpkhOJV9ICTa1HogNPYDG3/vsViTe+sjF/rKbOEWtMbkW5VUyVO9ZhUYEdvWzeK64u1qoVKDiKzOGuv6ihliH57A8jDiZbAflB6Sa8zviW9ZB2ir8fYkv+RgREcHU1MSUu48qCJ8hxTf75Ii2ORBSGyIoxSvArcg9rvaeHEgoeih+XYflcs6Y2NlKMuYOUT6u/TO+LF4RFr9JDTyxND9LsKx3NUaylQF/00ZaJY6QNkgmSTReKRS9THmGn9bBC95YjW8kbwlfRau0w9UUTJ/9gBMokaRKb229P6oo7poW1GX2jA954erOSffaF99IDS6PiS/3hPvpdy1eelfCJydrasBTGlrOAXrEVVgmdf4HNcD3gXxT4IMVH0Nf2JwMzGgDX9oolngYohQz0oHvc3D+X4PmOT78MNZTO6preCUGv6SPo74zf53qpyS3KRDe25rPWN5yCy1MAAJZkipzgH1XZtAb5rzAu/VtLrnM4S+3Qh+nqMLfk/9r7awykLQ6iaF+cApSgPOmV+Vpun09jiWJ8I2h7dsS8f7kYv1OfNRCffh+p3pZf0xqmH02Ql5apBZ/mk+nvt+OQEhpADO0ZRe2ZyF30i6B+s31UknhPqxYRwPZyIzCaCix45+owOz6DWomKCF3ESIdREYpb0BhL9RMeW/Pum9MZ/EJkvoBQYiBTvoc7aiV3EaViivk+Ikv+A7yEynOI4CChVVC9wIAtDGEUmWj8I7A0Y76oFKU8N/sinIv+txcVKcfFyLGeFCCgFBjv1qoVy61ct6Gv63sDX2tYPOjCKTGRhCNULJt4qyH/IkP/woXCMBpzCDWUzuqa3gnA9bMOJ5+R7KxvbNz6waoGsigFKMo0zT32yjx1Kopf0WnhKHZlLZJKJkn9B7eEENGS2wp4Z35efcOVBE6UvjiOUqfsmgkZ37IvJ4xW2E8ivmGCJd6NaxuI5HphlxJLe2Ej54sRFvdIuFsdqD7nkLm5FvysFdq2/lXGeHtE0PLreT0QT4RsgE93Jbc+xHpxS1GO2YbH1e+iK0sGxLUdY0htI9BMdW/KfyAwn8Z4o3iP1fdD6Qov31FgVOApQblPXQod3+QJv/Z396BAZTuwLDXumHfWZ4wNK3hFv3CffSwXq317uirytuFgp5QW/yCAC2uMuEqdQ1YJvTV8TuKbX/i71mW2mrOmzC7ORC/UihBg+FIlnrxqAMhJw8mVoB85EMLqmt4JQa/pIfG0yzJ98b2VSphqYFH3jOYgsNTBASaYRT3b/fnuJLOkl6whV8i/KttQeTvElyk2OjlZjZMC8IQpqSa+xBsv6yXeQiaDhiDJAZ27007/H7UOIfleiP6izzvolLVYiFaonE7J2HSaaxXG8iX5XgO9igBGKV4FnSHudPmN8A3mieBGlZp1KGXrbjJc5q0NTgBJbF4rrrX/xM1TLEb2kNwXK1BMhVMl/vEt6A/ZBCxiJAJK+Dyb1hQaCl/yrfaGBAvSitLFkwt9jMnAWqGtF/5J/tYdc5JLeiZCK1HWR3B05kCN3qc9tqSB4ya0eUDox5iLx8fyA+61MrOkHkYvj+3xrHb1MvcC8Nb1kV//WRiaoA9EFnEQrDc9+XzA5mjW9FYTrYRtOulZNSVnqcSRaMehVC1WsWrAyBijJNGIIjsfju7omSnqzMQjHHGtPqSPzZBdmo8auLrbdO30ZAnoPp7KJ9XAywr886Nj70WWThdO+9ziGkW2opFdkQXQolejvNF6apk++L5EjbBmZ3u9qMDAjw82S3phIxerrm9yjle8fsFYPuVD9rsLp/PwUTkMNANQvTo/eRGQNxfXFkKC+zomgoxHuPb5skFTgnB58IrE7zYYWRCICte6ukoDbEzmITLwnuo/7ssnN7AsNAE5JvbDl/tS3LvD1hU6vDKdwnOXjS/71qgV7/KoWJO3pKPdGPk0WFyulwuAXe0VVgqhSEFKpasF/Te/fxkv8XcTfyQxSRmDGWyTinNNIwMlZo56DuP36wkezpreCUGv6SPQ2GRXxb5NhJWP7xrNqITUwQEmm0fvttfn67bl3qVfaGkxK/6fUITLKRIYZ4N/DybyMxlDsmXY0ZEafTRaJWJzVZbQhMzd8cK+0sQSFUK/qiuwIQ9/jkLbgckQ//Xss0e+qe0y/K9Ef1DU3uZOnU43vxEXLirBYD7lQ/a7C8bynXkSosncgt4TDGSixnLnaie8HxjM7RC9Hl9QVj10ynSgd9G85ko5DCyIJdvKd6EFkrjlaQMmv356ZfaEBwOkYX/KfrhlO4YiSf7dfyX8ieshJJer3k/siB0DlHnVdKy5ejuU7pqv08mi1akF9zqdK1UKwNb37sLamrzFvTS9lqxlvXe3G1r/RBJxcjeMztKNZ01tBqDV9JGICeyoMAjLT2L7xomrBNZNrXStjxIhMI/rtuf367enp/wko6SVrCVby7+4QPZwS89IjjruxE0EnQi9Tz48c9LTZbXqGz9iJoGG/h5h83xB8wRsN/35X7nfVfVG8CjzDLOmNhVSmHrvyafVvZLWrsaLflTuKBuruD7UTvryJtxQgipaYzOxpMd4PVwR2RKDH6vwnEouWI+k6tCAc0U/0lFKKnmPqe2373uMJHUQm3hM9Q74e2u4d6t/KjL7QQPCSf/cXYhAQ+0ILesl/h6882v1Z/HvISeVqoErujzzlV+5Tty0pDb4GEAHtXhTh1MEuAGrVQh/Ui8OpUrUgft/uz3yvuSLQJ/5OZhib8RaJ3ibjS5EDTsGGsrn1Nj3mJTLEk/+aXvSrN0JMYBcT2dOFaL2g943nILKUwAAlmUYMwfHvtydKel0V1ih/pMQR5Rb+Jf96D6eZE1/gG9qHMpFNZmyhY4S+OC4ztjgW2RDuT4yXtbvF5PsZ0U3/DrkPY/pdnWg5iQHkxbWH02Sln7gMqH8bj2ytHnKuqaKBuvHnmEc74XCVdEfYksh8YoCM+wvjmR2eVjE0ZeIXcRKheoEDmRgOmEicrkMLwimuL0aJrQuAr+Q/0YPI6peoAaV+5OPkfu0ipzb80Yy+0ADgnKGV/J/yVTCIDCdXmmU4heOaLfrt+QJKiahaKKlUjzN5MHLQS+5Xt5VKg59S55XlodKmHjeiWkH867AdR16ZNdYOkfjW9H7ZrNqaXvydzCCGDYmMt0jcp9WLGkbaZAQbyib6URpd01uBWNO7P+gy/DVu0SZjdnpVTYnWC7LMQWSphAFKMo3rLDXQ0e51YKBLK1/RS3qtP6WOzOWaopX8t/uCbKJsy3VmYrL2RCn52OmJEyGmizqrjQU9Rb8X0f/F0Pc4rWbbuOabM/zBpfWyFL0txQlftb0DOcXmBEHThVShnljKg9qVeO2CjGthSbJ2KUCoflfheNxaS4HqibcUIIqWq0HLbGg1ntkhejmK3o5Wl5Gd4Ws5ok2+FSW9rmKW9PpziaoD7YKaqFpwJWgQWU5xDqpFvz0RUBItBUzoCw0ALnFB36/kP10znMLxL48WxJpSrDHjQXKo30Mejhw8FBcrpYrQwXOXVp2gH9NawNuV3xHqSywn6Jp+QCtTN6EvqyDliwnqkS8+RRtwCjaUTazpXTXmJTLE29g1fSTeEa8++d61OL3mQfj3jecgstTBACWZpmxaKfKhLrjFi4DnuCjptf6UOjKXKLcQ5ReyR0Y31CucoodK3PchSL+ZifJ0qI/lMlimLvq9iOyISIZPD+PYqLboM2nyvehlKXpb6tkgecmfPJ1qpCr17y+P5OP0idOW6yHnK0/09buKRC9TdzKLixJPHyBz0nhmhwjsiN6OqUCfSKy1vknXoQWROLW+op5P1VJnfUpvAjOcRLsL0W9Pv4hTZc5FHPHeftSv5F/0vEy3DKdwxFqxSylB9xHtb5GAqgWpWn1seSTy30IeUreVKkNfLHFq1QmiWkH860yhqoVga3o5Dmt6qUh9XZQNXAvwDziVTYscJA02lE2s6c0sU4+3sWv6SBIx+d6qpBL1366eTLjf5yCyVJE6z0ayPJvdBme22qdH9NvTS3pnJaakl6xDL6XQMsxEr5Ry20kUOBIztVCUkovj0AzRLo5FNoTIjojk2PvmT77X+11pvS31E7449nCarMSJS9dokd5DrgjdkBrMyXadKNHPqg+Fer+rSDynzG0pQBQNMZnZ02css350aBRHxNCURamTDTJ2InG6Di2IZOwAmWirFkzZhxKth7YIKLWpwSen05yWAlXzKpGFIb3kX+0LXaN+jwQMAkoVhdWFKLOp5xOHd2nZrKKHnIGS3lhJNeraUVYiXwCRR9S1nbh4GYwIbItAt9kB70QYu6YXf48yWycKq80LqkvaUkoMHwpHnGtGE3AaO5TNam16jBi7po9Eb5NhT0ybDCuRStX3Wbk/i4PIUggDlGQq8aQXLwKipNfM9H9KDaLcQpT8+3o4Ja6kRS8PGjDviqHoXWN0cSyyIfwngoZ9fG3iuJmT70XgyaP1thR9QVNpcWwVUq16MtKtFMG9x3o95PLK8uAY0+8qEk+/GuSJ5wkfUSj6AJmRaowORW6F0fZhB0aQhQyMoGZh6vSREpNuPUe0Ukm9pDe9ThgjEX1FRcm/p0PL8I5jSe+4fageE1A6JVoKmHMRx55pDyj5P77vRNpmOEWi99D+4BT6OxMz+V6qV9dKg8jFYHf4dZI8qh4bIqgZjAhsi0C3p10EvK2xbjBCrOk7lEr0d/br5epmr+l9E9QjtzqIJeA0dihbtGt6Kxi7po8kEZPvrcq/b7xetcBBZJbHACWZylmhveB/MRJY0qtNsaP0UdpYggKoGSNHdrXrPZycUuJKWkTZiQwJsmfivaP6OvpwUtFKCw0ujkU2hGe4xlDJrSj/ExPIzSDKID2ntX1ps9bk6VQiTly8yMAn72p/K23BaxXOMf2uwhnsHkSrV8tGM6mlAFE0ahY6kIERDCMb7XsjDyERPRzrM9qQkZ067WPGTiTWS3rnsKTX39iSf0+Xuo50filxGU4icCTaX4i+0GIYpCnfo9BX8i8ynGrs7cguTI2+qonilLR+ey39etVCvCffF9X4npPy4dBr1tGhUfRAPSbExctg9ICSVq2QilULodf05vRlFcSwITF8KJxYAk5iKJvnoDemNb0VjF3TR5LOVVOi9YI8lOerWqhj1YLVMUBJphJPes/RDL2kt8J2AvkVLPFON2rJv1ZKsadTL9cS5VuJEKw8aCJEz5piyJCcxhbHdYuqYIMXg8jF8X2Rr16KiePOcuNTvyMZ2+/K06Utjr9kXm/OdJFfkY8MqJlQH32sDQGzWA+5sf2uwjm6Wz2mc9GPipksLaTEy8zNRF2G1h5mt4HXSG1oirPgZFz3y2yi1Y2nW2JJbxj6ybdW8u8Z0DLmtBLThOyDX0ApHn2hAcBZplUaHRjSe12mY4ZTJHpA6ZBXL8uNd9VCRnYGiqD+TeRjoddiPa29+ufh2rw456nrRRHojkfAO95CrukrzV3Ti2FDYvhQOJ6j0QecfH3hM2Na01tBsB624YjJ6/GcfG9Vet/44Xxf1cJUDiKzOgYoyVTiSe85ke9X0hs5I4ImJ/+Sf0+ruugQvVMStg+iPMhANlkkvsWx8WBndmE2asRE0F0GsoO0ieNiArkZRL8rLzJw7P12Xw+nFFocW4XNboNkU09cPjqmnkBbrYfc2H5X4eg9nLLaLFOmTulHBBs9H0fOsBc9HJ1lvRG2tBa9h9tgFUt6w/Av+e9t68UJRQvmJDDDSZR7evor4tIXGvC9x3uO2NI6wykSvd9ea2ZCe8hJGerri9waOjtPPqL+vXIwgJzi0AE1EVA65q1CX0cfWr3mB7wTIRFrev+Mt0g8J9WLPtEEnERLDU9nQUxreisYu6aPRB+EmIZVU/rAq9EiVi2kEAYoyVTO2erVCU9vqS/9v8Tc9H9KHaLswvPFiK+H04zEli/5lwdNlJgqGm1Jr8iKEFkSYb9HHCbf+/e72r+1HW1icbwkdfq3WYk4cfm4bwoA6/WQG9vvKhy9pUCReS0FiKLlLNUGyOyPnOGhD02pSdzQFDP4TyTeu/EIgPQcWhCJf8n/zpf3A0j8IDIROGr1VmP/22rwwsy+0ADgbPSV/Pv6QqdfhlMkesl/Z6GvpDcBVQtSphoMldtDZwiK4KVkCx9YrpxVjhwMQIEd7/7uMyiwIwcDqJydOkO+AL81/cFReDpFX1Zz1/R6xttI5MGSnh7tInEUASc9Q7u3LOY1fbIF9LB9P3IlgZi8no5VU1Kdemx0o8hXtXCGsYF8lDwMUJKpxJPeM1SNQ1+Ikl4O4khXouzCfSQD7j4tC2JuYrP2RPmJ++DEs9x8/W6iWxyLrAiRJRH2e2gTx0U5oFlEv6u3X1eDpHk4jfIZfJOOhZSlLmpPQysXsdjV2LH9rsLxfKFm8TjL2TSckkcEG0XwMRx3h3qSJXo6poqi2iKU2tSMna3/k75DCyLJyM5AvVby/9YG7feU4EFkFTPLkQf1NfGdjVr5tYl9oQHAOVN9j3d3l8Ddph3TaZjhFIkIKLl7K+AWJb0JqFqQstV1nnw8dNBYblO3kTLDZ3PbM+1oyBpzTGe1plzVgr6mP5oBd5/Wu3GusUEtRukT1EfDr6vUNhla/+woAk6ipcbhkRocPBDbmt4K9B62H0fOutarphLYJsMqRN94BXa9aqF+CediWF1qre7I8sSTvh/52H1A63OX4JJesg5RdvHF8UIcHdUWEosSe8XYJbLJWieepeI+qv480S6OXVrfF7c7/HaKV4F7UMtuXGhs6rdRot/VWx+oz0tXduotjq1Cyg7MqLBaDznR78p9OvJzzS1aCtRFnp5MFC8i2CiCj+F45BIAgGtW4oammEWUEorXYZb0BidK/vXfU4IznNR+e22B+2BiX2jA9x7vGahK6wynSPSS/9FqHDyu/S2mxb+HnJSrXlCWT4TO1JY71G2krMgBLhFQ0o+nwviXqZtNX9N3FMVtTS+GDfWgGKNDodclx/edwADyom6TUXtmlZ6h/e6n2t/CYm16jBBreveB8JUE/Z396FC0AGUaVk3lluQiC76LDBxElhoYoCRT5RTnoFrrt7etcyYAwPWl1JlSR+YSmWU7u2bAiwxkYQjVCxL7BilKykWJ+UR4OrWMuShLekVWhOgDE4p8uFufCCnKAc0i+l2J52UiejhNVlKeLxPWjlHL9ZBzLRHliVUY6g1fMug5oWYruBJwwkcUinOmNtlajjyowDOovoeYfREnEZxSFwC/1+E0HFpghOgvqv+ekjCITASQ9H0wsS80ADjPUgM8MiTsO+0EALgWlpj6PSaDmjOqkIUhjCIT78nTAQDO2fGvWpDy1MCPfCp08EoEL6WcyINiXBVqQMl3TJsb8E4EsaZ/T56OUWQiC0OoOcPc9Y9/Kwf/IURjiZ7u1faOsP0/x/Ifyqb/LSzWpscIXw/b8KEcMfm+AL0obSyJ925Zjn/feIBVC6mCAUoynStPfdPog9afhIM40pZrkZpZJo6FhsxWU3s4GSFKyj19E89y8/SqZSSuedGVtIisCJElEfLx/SbfFzgi99+JhmuqWhqlPy8rWNIbKynfd8W6NsN6PeQqZ1fo/a7ElO5QPD1a0/DZ5h5vRNEQgRnPQPgLWD3HenBKUY/ZhsWplw3icqiBDPE67JrCLPZgXLXqa6z+e2pIfIaTeI/U92GqeX2hAaDAUYBy28mA75GOGU6R2DPtqM9Ugyz632Jx/CtxpAI1ACR3ha4CkzvVbaS8yBcanLVqNqD+M6Rg1cLYNX29yX1ZATXRJQfq66QYQhSM6Onuyo9+EKvI0Nb/FlGu6a1AvB6JvvWhiEFArpz0HYQoZfguBrBqITUwQEmmG/vkT7UpdWSeukVVsMF3YmF2DycjRPnJ0dFqjAzEngHhHfHi8IjWYDnKkl59emt/+OeCmDQej8n3Y3tail5CFL2SQt+JhRWvxtrsNjizIjdQV7wKPEPR93AiMpuY0NyplKG3LXTWzOH31IB7ia0LxfWpd/FzbMsbkTlKgcb2F01GhtPYthdm94UGAGeub3pwumY4GeEs8K0doy3pjZVUpK6R5DCzDeVT6vNZKog8sGvs4EMzByEmyrg1fUF81vQldvWXHm6CuujpHkvASQxl0/9vsTY9RojXI9G3PhTPPjU4l85VUyXZfgFKDiJLCQxQkumcVb7yx2wMwjEntabUkXmyC7NRY/dlcImeKYlUvcChlwe1ftAR+QtCaN97HMPIhh2jqD0zusWxyIroUCrR3xm6VM3zmXpfPCbfjy2HFL2EKHpSsS/IMHahaxWiPNGzL/T+dX5+Sh/0U7/YWmXqlF6K64shQX3dE0HIYPSLODnhM4OtauzEW+f8yCXt6Whs4DYZg8jGvkfGo6WAU/IrPcxO7CCgVOIs972PJWryvaQ9NeWe0IFEWVuqSYWRL/iOrVJIxaqFcWv68visf0TGmxhCFMxEJt+LoWwAYlrTW4Hew3YwfNa1PtwzCW0yrMK/BQMHkaUGBijJdP5P/oY4pP9TavHPMDO7h5MR/uVBnt2xZ7uJfjd1GW3IzI0uuFfaWIICqAu5I7vCnHwf0hZccZh8P7anZSoujq1C8ospWLWHnOhv5fk89HPO854asK+ydyC3hMMZKLmcueproyhJC8bzqZpR4yw2/yJOIoydeCsyRynQuAtqSchwGvse2bDU/MmvToffiXMaZzhF4qzxvY8lqmpBKlHPZbr6QgdDu7rV8xv/i5ahjDumU7RqIWBNXxOfNb2Urb7OiyFEwYie7rEEnPwztGNZ01uBWNN3Q4LsCf1+6DmmBthTcRCQWaRc3zqdg8hSAyNHZDr/J38ySnrJWvzLL5yNyXnJEWUonk9iv9rr+Vj9OZz5oUtmQ1Engmon33tCPyc8bepCeGwZoBn8+10Bqbs4tgKpzHccW/VqrOh3Fa6BuucjdVHrzDO/pQBRtMSkZk9LmLK+Q+pJltORmtkg/hNvC9GDEhczKIPx7y+arAwn//fICtsJ5FfEocTb773eWcm+0KH4B5QS1UNOKleDVnJ/6Im/cp+6jVQS+fHGBrhTtWohYE0/JT5repHxFm6CuujpHkvAyT9DO5Y1vRX4r+lF//pgPCfEcM/UC8Kaxb8FA6sWUkNSA5Rr1qzB0qVLUVRUBIfDgZUrV6KlpSXs16xbtw42my3gIzc38MVJURTcf//9qKmpQV5eHpYvX479+/fH80chP/5DcZzlqTeljszlX37hnGn+At/QPmhlKJ4DsWe76f1uymJbHIvsCNEPJuj36FSza5wzjE8kjGof/Ppd1S8xPxskXYgTF8C6PeREfyvPidD75/lMPQlwloRpskWUIM5K9Xj0HAyd6eFpVZ97znrzL+IkQvUCBzKhniw5c1jSG0pxfTFKbF0AkjeIzD+AFI++0ADgnOELfrEvdGj+/T8TVbUgVajHnDwYOgAm96vbSKWR+0nmleWh0qYeRw7bceSVWXPtEEnAmj4OfVkB39AhMYQoGNHTPZaAk//XxLqmtwKxphcXm4Px9IpBiIlvk2EV/i0YOIgsNSQ1QLllyxY0NTVh+/bt2LRpE4aHh3HxxRejry98UKu4uBitra36h9vtDrh/7dq1ePrpp/Hcc89hx44dKCgowIoVKzAwMBDiEclM/k/+ZJT0krX4Z5jFo4eToX3QylA8R2I/GfQcVr/WWR25GXrQfdCyI0Q/mKDf47Raxja2DNAsot9Vtb0dOcXxCYKmA6nC76TSoldjRXmimNIdjMctejiZ31KAKFqiBM1zLHSmh+ekNu14euisJivLyM7QW46wpDc80Wc0WYPIcktyUWVXAwDx6AsNAM65fhf02Rc6JDFoEEhc1YLkUNdI8nDoQKI8oG4jVRj724lqhVSuWghY0/v9Xcwk5WsT1E8FvxA10DWAdq96rhlLwMm/tUasa3orEGt6T0vwigLFq8AzHNtwz8lEtGDIRx/KpiXnPJSik9R3w40bNwb8f926dXA4HNi1axfOP//8kF9ns9lQXR08+0dRFDz55JO49957cfnllwMAXnrpJVRVVeHVV1/FVVddZd4PQEGVzyhDHk6jH/kpOaWOzOVffjG2D2LC9mGKHXgbeHN/Ldb+7+aYHqO5RXuTnxLb4thZ5wU+BV7fWYG8IPugKMDR0fPUbeM0+d7pGADaxOI4NcuLrECq8mtjYdEecuJiwMHB0Mf85o/VfXc6mcVFyScmNW87XBfymP2ke666bRKGppjFWXASh+SGtB5aYISzWMaHA0jqIDJn3nG09zni0hcaCCz5T+VjOt78146J6iEn3uflkdB/F3lIDV5KlcYu+Dqlbuw6ndpVC4lY00tF6oX8Te9KyAjyXtDVBQAXxhxwkpwSiiGjG1LMa3orEGv6/+/PhegJ8nvq7wcGcSFsSMzke6sSLRic2W2w2acldV/IGEtdrpO1cWhlZeF7o/X29sLlcsHr9WLRokV45JFHMHeuumg9ePAg2trasHz5cn17SZJw9tlnY9u2bUEDlIODgxgc9C0+urtT943DCmx2G6blHMXewRmYuoALrnQ3ban6fHbYjqOwOj6Bt4j7sLAQ+D2wd3AG7np9xoQea+q82IbLTJudDWwGdvTNw47XQ2+Xjz5UzYvP72naNAAfAlPL+Ro3EY7patZLia3Lsj3kGpZWIxPD6Ec+7nr9wrDbTp3DpuGUfNMWqc+l/cONuOv1xrDbNp6dumVa0xw9eFMGpk5hSW8402r7gQ5gan3yBpFNK5exsw+YOjU+j1+9wKFf0J96dnLWR6mgqLYIDttxdCiVmLokMf2zpVp1rScroSta5BF1m5JqY++h0+oGgFZgam3qVvSJNX2l7TiKauNzzDq0h32j60y8EWa9PDXnGGz22Nb00/KO4f1+KeY1vRWINf3mU4uwOczvqSHjGLIL6xO2X1bjqFUvfk6VOgEwQJkKLBOg9Hq9WL16NZYtW4Z58+aF3G7mzJn47W9/iwULFkCWZfz85z/HV77yFXz88ceor69HW5taOlNVFXiloKqqSr9vrDVr1uCBBx4w74ch/PLRPrz5p2ZccMt5yd4VSrK5l0/H2v/djNmL8wEkZwF+4W0Lcf+GZriPTuwlr6FmBMvvODemr135wJm4891mtJ8Mvw9/d3kG7JnnxPQ9IrnuFwvR1tqM6+5piMvjp4upFzrxr5c3Y9rcPNjsZyd7d4LKK8vDupvfxqa/hO/VV1c1gq/fsyxBe0UU2lnfmYuHXmnGgUPhXyPPXupF7aLQVTZWd/evGlB1fzNufHJ+snfF0n74zDTk/qgZTb+clbR9uP9XVZjys2Zc94sz4vL49kw7Xrr9A7R5huA854K4fI/J4jf3HsSnuz/G3MsT83sqaVADk4PIxWD3YNC2OPKomoQh1RjrxXjrM19C5upmND0907wdTbC5l0/H499oxqxF8VvTf+fnc9HatgVyb+gqPLtdwXU/iL0d0lNrh7D5/zXHvKa3gut+sRBudzM65dDvmTabgqtuyAOQvgHKlT9ZiHv3NuObq2qSvStkkE1RFEt0Gr/55pvx+uuvY+vWraivN/4kGh4exuzZs3H11VfjoYcewjvvvINly5bh2LFjqKnxHYhXXnklbDYb/vjHP457jGAZlA0NDZBlGcXFxeO2JyIiIiIioslndGgUmTlqgKx973E45lZGdT8REfl0d3dDkiRD8bWkDskRVq1ahQ0bNuCNN96IKjgJAFlZWTjzzDNx4MABANB7U7a3twds197eHrJvZU5ODoqLiwM+iIiIiIiIKL1kZGegCGo7HPnY+OGtPa2+3qhSA88biYjMktQApaIoWLVqFdavX4+//e1vaGwM33MomNHRUXz00Ud6tmRjYyOqq6uxefNmfZvu7m7s2LED55wTn7JJIiIiIiIimhykDDUIKbeeHneffKQHAJCDgaDl30REFJuk9qBsamrCyy+/jNdeew1FRUV6j0hJkpCXp05Gu+6661BXV4c1a9YAAB588EF8+ctfxvTp09HV1YXHH38cbrcb3/ve9wCoE75Xr16Nhx9+GDNmzEBjYyPuu+8+1NbWYuXKlUn5OYmIiIiIiCg1SJl9ODIKyO3jh9qIoKVk6wHAQXNERGZJaoDy2WefBQBceOGFAbe/8MILuOGGGwAAHo8Hdrsv0fPUqVP4/ve/j7a2NpSWlmLx4sV45513MGfOHH2bO++8E319fbjpppvQ1dWFc889Fxs3bkRuLt9AiIiIiIiIKDQpux8YBOTj4yfJy2396jaZvUjWAEgioskoqQFKI/N5mpubA/7/xBNP4Iknngj7NTabDQ8++CAefPDBieweERERERERpRkpdxDoAeQTw+PukzvU4apSVn+id4uIaFKzxJAcIiIiIiIiIiuQ8tTApHzKO+4+EbSUcsaXfxMRUewYoCQiIiIiIiLSSAUjAAC5a3zFn9yp3ifljS//JiKi2DFASURERERERKSRitTMSbl7/H3yKTVoKRWML/8mIqLYMUBJREREREREpJEk9V+5J2PcfbKsbVM4vvybiIhixwAlERERERERkUYqsQEA5NPjZ8rKPeoptFQceeArEREZxwAlERERERERkUYqVwOTcn/2uPvkPjWrUipJ5B4REU1+DFASERERERERaaSKLACAPJg77j75tBq0lErHl38TEVHsGKAkIiIiIiIi0kiOHACAPJQ/7j55QL1Pqhhf/k1ERLFjgJKIiIiIiIhII1WpmZPyaMG4++ShPHWbypyE7hMR0WTHACURERERERGRRqpVA5Nd3uJx93WNqPeJICYREZmDAUoiIiIiIiIijVRXCAAYRC4GuwcD7pNH1fuk6ryE7xcR0WTGACURERERERGRpriuSP9cPtytfz46NIoeqFmVIohJRETmYICSiIiIiIiISJORnYFC9AAA5GN9+u09rb3651J90bivIyKi2DFASURERERERORHsqvBSLn1tH6bfEQNWuZgALkl7EFJRGQmBiiJiIiIiIiI/JRkaQHK9gH9NhGslGw9SdknIqLJjAFKIiIiIiIiIj9Sdj8AQD4+pN8mt6m3SZm9Qb+GiIhixwAlERERERERkR8pV53eLZ8Y1m+TO9TbpKz+pOwTEdFkxgAlERERERERkR8pTw1Myqe8+m0iWCnlDAT9GiIiih0DlERERERERER+pIIRAIDcpei3yZ3qbVLeUNCvISKi2DFASURERERERORHKlIzJ+Vu323yKTVYKRUMB/sSIiKaAAYoiYiIiIiIiPxIkvqv3JOh3ybL2n2F3iBfQUREE8EAJREREREREZEfqcQGAJBPZ+q3yT3q6bNUrAT9GiIiih0DlERERERERER+pHI1MCn3Z+u3yX1qNqVUkow9IiKa3BigJCIiIiIiIvIjVWQBAOTBXP02+bQarJRKM4J+DRERxS6pAco1a9Zg6dKlKCoqgsPhwMqVK9HS0mL46//whz/AZrNh5cqVAbffcMMNsNlsAR+XXHKJyXtPREREREREk5HkyAEAyEP5+m3ygHqbVJEZ9GuIiCh2SQ1QbtmyBU1NTdi+fTs2bdqE4eFhXHzxxejr64v4tYcOHcIdd9yB8847L+j9l1xyCVpbW/WPV155xezdJyIiIiIioklIqlIzJ+XRAv02eShPva8yJyn7REQ0mSX10s/GjRsD/r9u3To4HA7s2rUL559/fsivGx0dxTXXXIMHHngAb731Frq6usZtk5OTg+rqarN3mYiIiIiIiCY5qVYNTMreIv02eUTNphTBSyIiMo+lelDKsgwAKCsrC7vdgw8+CIfDgRtvvDHkNs3NzXA4HJg5cyZuvvlmnDx5MuS2g4OD6O7uDvggIiIiIiKi9CTVFQIABpCHod4hAIA8qt4mVeclbb+IiCYrywQovV4vVq9ejWXLlmHevHkht9u6dSt+85vf4Pnnnw+5zSWXXIKXXnoJmzdvxmOPPYYtW7bg61//OkZHR4Nuv2bNGkiSpH80NDRM+OchIiIiIiKi1FRc55c5ebgb3hEveqDeJoKXRERkHst0921qasLevXuxdevWkNv09PTg2muvxfPPP4+KioqQ21111VX65/Pnz8eCBQswbdo0NDc346KLLhq3/d13343bb79d/393dzeDlERERERERGkqIzsDhehBL4ogH+tDdkEWFEgAAKm+KMJXExFRtCwRoFy1ahU2bNiAN998E/X19SG3+/zzz3Ho0CFceuml+m1erxcAkJmZiZaWFkybNm3c102dOhUVFRU4cOBA0ABlTk4OcnLY6JiIiIiIiIhUkr0Xvd4iyK2nkZ2fCUBCNgaRW8IelEREZktqgFJRFNxyyy1Yv349mpub0djYGHb7WbNm4aOPPgq47d5770VPTw+eeuqpkFmPR44cwcmTJ1FTU2PavhMREREREdHkJWX14eggILcPIDsvQ73N1g2gMrk7RkQ0CSU1QNnU1ISXX34Zr732GoqKitDW1gYAkCQJeXlq4+HrrrsOdXV1WLNmDXJzc8f1pywpKQEA/fbe3l488MAD+OY3v4nq6mp8/vnnuPPOOzF9+nSsWLEicT8cERERERERpSwpqx8YBLraB5GVo45vkDL7wAAlEZH5khqgfPbZZwEAF154YcDtL7zwAm644QYAgMfjgd1ufJZPRkYGPvzwQ7z44ovo6upCbW0tLr74Yjz00EMs4yYiIiIiIiJDpNwBoBeQTwwjO1cLUGadTvJeERFNTkkv8Y6kubk57P3r1q0L+H9eXh7+/Oc/T2CviIiIiIiIKN1JecMAAPmUF9m56uclOQPJ3CUioknLEkNyiIiIiIiIiKykpHAEACB3KcjOUT+X8oaSuUtERJMWA5REREREREREY0hFXgCA3A1kZ6vVf1LBcDJ3iYho0mKAkoiIiIiIiGgMSVL/lXsykJ01qt5W6E3iHhERTV4MUBIRERERERGNIZXYAADy6UxkZ2kZlMWR5ygQEVH0GKAkIiIiIiIiGkMqV0+X5f5sZGeqmZNSSRJ3iIhoEmOAkoiIiIiIiGgMqSILACAP5iI7QwtQlmYkc5eIiCYtBiiJiIiIiIiIxpAcOQAAeSgf2XatB2UFT6GJiOKBr65EREREREREY0hVuQAAebQA2UMj6m2VOcncJSKiSYsBSiIiIiIiIqIxpNoCAIDsLUL2yLB6mxa0JCIic9mTvQNEREREREREViPVFQIABpCHE6Ol6m3VecncJSKiSYsBSiIiIiIiIqIxiuuK9M/7kQ/AF7QkIiJzMUBJRERERERENEZGdgYK0RNwm1RfFGJrIiKaCAYoiYiIiIiIiIKQ7L3659kYRG4Je1ASEcUDA5REREREREREQUhZfb7Pbd1J3BMiosmNAUoiIiIiIiKiIKSsft/nmX1htiQioolggJKIiIiIiIgoCCl3wPd51ukk7gkR0eTGACURERERERFREFLesO/znIEwWxIR0UQwQElEREREREQUhFQw4vs8dyiJe0JENLkxQElEREREREQUhFTk9X1eMBxmSyIimggGKImIiIiIiIiCkCS/zwu9oTckIqIJYYCSiIiIiIiIKIiSUpvvc0lJ4p4QEU1uDFASERERERERBSGVZ/o+L0nefhARTXYMUBIREREREREFIVVk+T4vzUjinhARTW4MUBIREREREREFITlyfJ9XZIbZkoiIJiKpAco1a9Zg6dKlKCoqgsPhwMqVK9HS0mL46//whz/AZrNh5cqVAbcrioL7778fNTU1yMvLw/Lly7F//36T956IiIiIiIgmM6kq1/d5ZU6YLYmIaCKSGqDcsmULmpqasH37dmzatAnDw8O4+OKL0dfXF/FrDx06hDvuuAPnnXfeuPvWrl2Lp59+Gs899xx27NiBgoICrFixAgMDA/H4MYiIiIiIiGgSkmoLfJ/7BSuJiMhcNkVRLDOK7Pjx43A4HNiyZQvOP//8kNuNjo7i/PPPx3e/+1289dZb6OrqwquvvgpAzZ6sra3Fj370I9xxxx0AAFmWUVVVhXXr1uGqq66KuB/d3d2QJAmyLKO4uNiUn42IiIiIiIhSy6mDXSibWgIAaNl4EF9a0ZjcHSIiSiHRxNcs1YNSlmUAQFlZWdjtHnzwQTgcDtx4443j7jt48CDa2tqwfPly/TZJknD22Wdj27ZtQR9vcHAQ3d3dAR9ERERERESU3orripCNQdjgRflUKdm7Q0Q0aVmmy6/X68Xq1auxbNkyzJs3L+R2W7duxW9+8xvs2bMn6P1tbW0AgKqqqoDbq6qq9PvGWrNmDR544IHYdpyIiIiIiIgmpYzsDKxbtQM9p0ZQPiN0lR8REU2MZQKUTU1N2Lt3L7Zu3Rpym56eHlx77bV4/vnnUVFRYdr3vvvuu3H77bfr/+/u7kZDQ4Npj09ERERERESp6epffiXZu0BENOlZIkC5atUqbNiwAW+++Sbq6+tDbvf555/j0KFDuPTSS/XbvF4vACAzMxMtLS2orq4GALS3t6Ompkbfrr29HWeccUbQx83JyUFODieyERERERERERERJVpSA5SKouCWW27B+vXr0dzcjMbG8A2HZ82ahY8++ijgtnvvvRc9PT146qmn0NDQgKysLFRXV2Pz5s16QLK7uxs7duzAzTffHK8fhYiIiIiIiIiIiGKQ1ABlU1MTXn75Zbz22msoKirSe0RKkoS8vDwAwHXXXYe6ujqsWbMGubm54/pTlpSUAEDA7atXr8bDDz+MGTNmoLGxEffddx9qa2uxcuXKhPxcREREREREREREZExSA5TPPvssAODCCy8MuP2FF17ADTfcAADweDyw26MbNn7nnXeir68PN910E7q6unDuuedi48aNyM3NNWO3iYiIiIiIiIiIyCQ2RVGUZO+E1XR3d0OSJMiyjOLi4mTvDhERERERERERUUqJJr4WXWoiERERERERERERkYkYoCQiIiIiIiIiIqKkYYCSiIiIiIiIiIiIkoYBSiIiIiIiIiIiIkoaBiiJiIiIiIiIiIgoaRigJCIiIiIiIiIioqTJTPYOWJGiKADUcehEREREREREREQUHRFXE3G2cBigDKKnpwcA0NDQkOQ9ISIiIiIiIiIiSl09PT2QJCnsNjbFSBgzzXi9Xhw7dgxFRUWw2WzJ3p2odXd3o6GhAYcPH0ZxcXGyd4eIxyRZCo9Hshoek2Q1PCbJSng8ktXwmCQrsfrxqCgKenp6UFtbC7s9fJdJZlAGYbfbUV9fn+zdmLDi4mJLHqCUvnhMkpXweCSr4TFJVsNjkqyExyNZDY9JshIrH4+RMicFDskhIiIiIiIiIiKipGGAkoiIiIiIiIiIiJKGAcpJKCcnBz/5yU+Qk5OT7F0hAsBjkqyFxyNZDY9Jshoek2QlPB7JanhMkpVMpuORQ3KIiIiIiIiIiIgoaZhBSUREREREREREREnDACURERERERERERElDQOURERERERERERElDQMUBIREREREREREVHSMEA5Cf3qV7/ClClTkJubi7PPPhvvvvtusneJ0sCaNWuwdOlSFBUVweFwYOXKlWhpaQnYZmBgAE1NTSgvL0dhYSG++c1vor29PUl7TOnk0Ucfhc1mw+rVq/XbeDxSoh09ehTf/va3UV5ejry8PMyfPx/vvfeefr+iKLj//vtRU1ODvLw8LF++HPv370/iHtNkNjo6ivvuuw+NjY3Iy8vDtGnT8NBDD8F/fiaPSYqnN998E5deeilqa2ths9nw6quvBtxv5Pjr7OzENddcg+LiYpSUlODGG29Eb29vAn8KmizCHY/Dw8O46667MH/+fBQUFKC2thbXXXcdjh07FvAYPB7JTJFeI/398z//M2w2G5588smA21PtmGSAcpL54x//iNtvvx0/+clPsHv3bixcuBArVqxAR0dHsneNJrktW7agqakJ27dvx6ZNmzA8PIyLL74YfX19+jY//OEP8d///d/4z//8T2zZsgXHjh3DFVdckcS9pnSwc+dO/Nu//RsWLFgQcDuPR0qkU6dOYdmyZcjKysLrr7+OTz75BL/4xS9QWlqqb7N27Vo8/fTTeO6557Bjxw4UFBRgxYoVGBgYSOKe02T12GOP4dlnn8UzzzyDffv24bHHHsPatWvxy1/+Ut+GxyTFU19fHxYuXIhf/epXQe83cvxdc801+Pjjj7Fp0yZs2LABb775Jm666aZE/Qg0iYQ7Hk+fPo3du3fjvvvuw+7du/Ff//VfaGlpwWWXXRawHY9HMlOk10hh/fr12L59O2pra8fdl3LHpEKTyllnnaU0NTXp/x8dHVVqa2uVNWvWJHGvKB11dHQoAJQtW7YoiqIoXV1dSlZWlvKf//mf+jb79u1TACjbtm1L1m7SJNfT06PMmDFD2bRpk3LBBRcot912m6IoPB4p8e666y7l3HPPDXm/1+tVqqurlccff1y/raurS8nJyVFeeeWVROwipZlvfOMbyne/+92A26644grlmmuuURSFxyQlFgBl/fr1+v+NHH+ffPKJAkDZuXOnvs3rr7+u2Gw25ejRownbd5p8xh6Pwbz77rsKAMXtdiuKwuOR4ivUMXnkyBGlrq5O2bt3r+JyuZQnnnhCvy8Vj0lmUE4iQ0ND2LVrF5YvX67fZrfbsXz5cmzbti2Je0bpSJZlAEBZWRkAYNeuXRgeHg44PmfNmgWn08njk+KmqakJ3/jGNwKOO4DHIyXen/70JyxZsgTf+ta34HA4cOaZZ+L555/X7z948CDa2toCjklJknD22WfzmKS4+MpXvoLNmzfjs88+AwB88MEH2Lp1K77+9a8D4DFJyWXk+Nu2bRtKSkqwZMkSfZvly5fDbrdjx44dCd9nSi+yLMNms6GkpAQAj0dKPK/Xi2uvvRY//vGPMXfu3HH3p+IxmZnsHSDznDhxAqOjo6iqqgq4vaqqCp9++mmS9orSkdfrxerVq7Fs2TLMmzcPANDW1obs7Gz9TVyoqqpCW1tbEvaSJrs//OEP2L17N3bu3DnuPh6PlGhffPEFnn32Wdx+++34P//n/2Dnzp249dZbkZ2djeuvv14/7oK9h/OYpHj4l3/5F3R3d2PWrFnIyMjA6Ogofvazn+Gaa64BAB6TlFRGjr+2tjY4HI6A+zMzM1FWVsZjlOJqYGAAd911F66++moUFxcD4PFIiffYY48hMzMTt956a9D7U/GYZICSiEzX1NSEvXv3YuvWrcneFUpThw8fxm233YZNmzYhNzc32btDBK/XiyVLluCRRx4BAJx55pnYu3cvnnvuOVx//fVJ3jtKR//xH/+B3//+93j55Zcxd+5c7NmzB6tXr0ZtbS2PSSKiEIaHh3HllVdCURQ8++yzyd4dSlO7du3CU089hd27d8NmsyV7d0zDEu9JpKKiAhkZGeOm0La3t6O6ujpJe0XpZtWqVdiwYQPeeOMN1NfX67dXV1djaGgIXV1dAdvz+KR42LVrFzo6OrBo0SJkZmYiMzMTW7ZswdNPP43MzExUVVXxeKSEqqmpwZw5cwJumz17NjweDwDoxx3fwylRfvzjH+Nf/uVfcNVVV2H+/Pm49tpr8cMf/hBr1qwBwGOSksvI8VddXT1uEOjIyAg6Ozt5jFJciOCk2+3Gpk2b9OxJgMcjJdZbb72Fjo4OOJ1O/VzH7XbjRz/6EaZMmQIgNY9JBignkezsbCxevBibN2/Wb/N6vdi8eTPOOeecJO4ZpQNFUbBq1SqsX78ef/vb39DY2Bhw/+LFi5GVlRVwfLa0tMDj8fD4JNNddNFF+Oijj7Bnzx79Y8mSJbjmmmv0z3k8UiItW7YMLS0tAbd99tlncLlcAIDGxkZUV1cHHJPd3d3YsWMHj0mKi9OnT8NuDzwVyMjIgNfrBcBjkpLLyPF3zjnnoKurC7t27dK3+dvf/gav14uzzz474ftMk5sITu7fvx9//etfUV5eHnA/j0dKpGuvvRYffvhhwLlObW0tfvzjH+PPf/4zgNQ8JlniPcncfvvtuP7667FkyRKcddZZePLJJ9HX14fvfOc7yd41muSamprw8ssv47XXXkNRUZHe10KSJOTl5UGSJNx44424/fbbUVZWhuLiYtxyyy0455xz8OUvfznJe0+TTVFRkd7/VCgoKEB5ebl+O49HSqQf/vCH+MpXvoJHHnkEV155Jd599138+te/xq9//WsAgM1mw+rVq/Hwww9jxowZaGxsxH333Yfa2lqsXLkyuTtPk9Kll16Kn/3sZ3A6nZg7dy7ef/99/Ou//iu++93vAuAxSfHX29uLAwcO6P8/ePAg9uzZg7KyMjidzojH3+zZs3HJJZfg+9//Pp577jkMDw9j1apVuOqqq1BbW5ukn4pSVbjjsaamBv/wD/+A3bt3Y8OGDRgdHdXPdcrKypCdnc3jkUwX6TVybJA8KysL1dXVmDlzJoAUfY1M9hhxMt8vf/lLxel0KtnZ2cpZZ52lbN++Pdm7RGkAQNCPF154Qd+mv79f+cEPfqCUlpYq+fn5yt///d8rra2tydtpSisXXHCBctttt+n/5/FIifbf//3fyrx585ScnBxl1qxZyq9//euA+71er3LfffcpVVVVSk5OjnLRRRcpLS0tSdpbmuy6u7uV2267TXE6nUpubq4ydepU5Z577lEGBwf1bXhMUjy98cYbQdeO119/vaIoxo6/kydPKldffbVSWFioFBcXK9/5zneUnp6eJPw0lOrCHY8HDx4Mea7zxhtv6I/B45HMFOk1ciyXy6U88cQTAbel2jFpUxRFSVAslIiIiIiIiIiIiCgAe1ASERERERERERFR0jBASUREREREREREREnDACURERERERERERElDQOURERERERERERElDQMUBIREREREREREVHSMEBJREREREREREREScMAJRERERERERERESUNA5RERERERERERESUNAxQEhEREdGEHTp0CDabDXv2rs4degAABpFJREFU7En2rhARERFRimGAkoiIiIiIiIiIiJKGAUoiIiIiIiIiIiJKGgYoiYiIiMgwr9eLtWvXYvr06cjJyYHT6cTPfvYz/f4vvvgC/+t//S/k5+dj4cKF2LZtm37fyZMncfXVV6Ourg75+fmYP38+XnnllYDHv/DCC3HrrbfizjvvRFlZGaqrq/HTn/40YJtPP/0U5557LnJzczFnzhz89a9/hc1mw6uvvqpvc/jwYVx55ZUoKSlBWVkZLr/8chw6dMjQz9jc3IyzzjoLBQUFKCkpwbJly+B2uwEAP/3pT3HGGWfg//7f/4spU6ZAkiRcddVV6Onpie4XSUREREQ6BiiJiIiIyLC7774bjz76KO677z588sknePnll1FVVaXff8899+COO+7Anj178KUvfQlXX301RkZGAAADAwNYvHgx/ud//gd79+7FTTfdhGuvvRbvvvtuwPd48cUXUVBQgB07dmDt2rV48MEHsWnTJgDA6OgoVq5cifz8fOzYsQO//vWvcc899wR8/fDwMFasWIGioiK89dZbePvtt1FYWIhLLrkEQ0NDYX++kZERrFy5EhdccAE+/PBDbNu2DTfddBNsNpu+zeeff45XX30VGzZswIYNG7BlyxY8+uijE/q9EhEREaUzm6IoSrJ3goiIiIisr6enB5WVlXjmmWfwve99L+C+Q4cOobGxEf/+7/+OG2+8EQDwySefYO7cudi3bx9mzZoV9DH/7u/+DrNmzcLPf/5zAGoG5ejoKN566y19m7POOgtf/epX8eijj2Ljxo249NJLcfjwYVRXVwMA/vrXv+JrX/sa1q9fj5UrV+J3v/sdHn74Yezbt08PLA4NDaGkpASvvvoqLr744pA/Y2dnJ8rLy9Hc3IwLLrhg3P0//elP8fjjj6OtrQ1FRUUAgDvvvBNvvvkmtm/fbvRXSURERER+MpO9A0RERESUGvbt24fBwUFcdNFFIbdZsGCB/nlNTQ0AoKOjA7NmzcLo6CgeeeQR/Md//AeOHj2KoaEhDA4OIj8/P+RjiMfp6OgAALS0tKChoUEPTgJqANPfBx98gAMHDugBRGFgYACff/552J+xrKwMN9xwA1asWIGvfe1rWL58Oa688kr9ZwGAKVOmBDy2//4RERERUfQYoCQiIiIiQ/Ly8iJuk5WVpX8ushe9Xi8A4PHHH8dTTz2FJ598EvPnz0dBQQFWr149ruza/zHE44jHMKK3txeLFy/G73//+3H3VVZWRvz6F154Abfeeis2btyIP/7xj7j33nuxadMmfPnLXzZl/4iIiIgoEHtQEhEREZEhM2bMQF5eHjZv3hzT17/99tu4/PLL8e1vfxsLFy7E1KlT8dlnn0X1GDNnzsThw4fR3t6u37Zz586AbRYtWoT9+/fD4XBg+vTpAR+SJBn6PmeeeSbuvvtuvPPOO5g3bx5efvnlqPaTiIiIiIxjgJKIiIiIDMnNzcVdd92FO++8Ey+99BI+//xzbN++Hb/5zW8Mff2MGTOwadMmvPPOO9i3bx/+6Z/+KSDQaMTXvvY1TJs2Dddffz0+/PBDvP3227j33nsB+DI2r7nmGlRUVODyyy/HW2+9hYMHD6K5uRm33norjhw5EvbxDx48iLvvvhvbtm2D2+3GX/7yF+zfvx+zZ8+Oaj+JiIiIyDiWeBMRERGRYffddx8yMzNx//3349ixY6ipqcE///M/G/rae++9F1988QVWrFiB/Px83HTTTVi5ciVkWTb8/TMyMvDqq6/ie9/7HpYuXYqpU6fi8ccfx6WXXorc3FwAQH5+Pt58803cdddduOKKK9DT04O6ujpcdNFFKC4uDvv4+fn5+PTTT/Hiiy/i5MmTqKmpQVNTE/7pn/7J8D4SERERUXQ4xZuIiIiIUtrbb7+Nc889FwcOHMC0adOSvTtEREREFCUGKImIiIgopaxfvx6FhYWYMWMGDhw4gNtuuw2lpaXYunVrsneNiIiIiGLAEm8iIiIiSik9PT2466674PF4UFFRgeXLl+MXv/iF4a8vLCwMed/rr7+O8847z4zdJCIiIiKDmEFJRERERGnlwIEDIe+rq6tDXl5eAveGiIiIiBigJCIiIiIiIiIioqSxJ3sHiIiIiIiIiIiIKH0xQElERERERERERERJwwAlERERERERERERJQ0DlERERERERERERJQ0DFASERERERERERFR0jBASUREREREREREREnDACURERERERERERElzf8P6GRvWHt4mVQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.figure(figsize=(16,4))\n",
    "plt.plot(r_u[\"change_flag\"], r_u[\"r2time\"], label='pushrod2',color='r')\n",
    "plt.plot(r_u[\"change_flag\"], r_u[\"r3time\"], label='pushrod3',color='b')\n",
    "\n",
    "# 添加图例\n",
    "plt.legend()\n",
    "\n",
    "# 添加标题和标签\n",
    "plt.title('pushrod_move_time')\n",
    "plt.xlabel('change_sn')\n",
    "plt.ylabel('move_time')\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "py3916",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}