01f_text_embeddings_spacy_only_wikitext103.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai.vision.all import *\n",
    "from fastai.learner import *\n",
    "from fastai.data.all import *\n",
    "from fastai.callback.tracker import SaveModelCallback\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from pathlib2 import Path\n",
    "import numpy as np\n",
    "import random\n",
    "from torch.nn import MSELoss"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can download the ebooks [here](https://www.openslr.org/resources/12/original-books.tar.gz).\n",
    "\n",
    "We will need the pretrained embeddings from https://github.com/iamyuanchung/speech2vec-pretrained-vectors. We will use them to compare our results and also to figure out what vocab the authors of the speech2vec paper used for training. Let us start with the latter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = pd.read_csv('data/wikitext-103/train.csv', header=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(29539, 1)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "texts = df_train[0].tolist()\n",
    "texts = texts[:2000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/sklearn/utils/deprecation.py:143: FutureWarning: The sklearn.datasets.base module is  deprecated in version 0.22 and will be removed in version 0.24. The corresponding classes / functions should instead be imported from sklearn.datasets. Anything that cannot be imported from sklearn.datasets is now part of the private API.\n",
      "  warnings.warn(message, FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "import logging\n",
    "from six import iteritems\n",
    "from web.datasets.similarity import fetch_MEN, fetch_WS353, fetch_SimLex999\n",
    "from web.embeddings import fetch_GloVe\n",
    "from web.evaluate import evaluate_similarity\n",
    "from web.embedding import Embedding, Vocabulary\n",
    "from gensim.models import Word2Vec\n",
    "from gensim.models import KeyedVectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "37622"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "speech2vec = KeyedVectors.load_word2vec_format('../speech2vec-pretrained-vectors/speech2vec/50.vec', binary=False) \n",
    "\n",
    "vocab = set(speech2vec.vocab.keys())\n",
    "len(vocab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from joblib import Parallel, delayed\n",
    "from functools import partial\n",
    "from spacy.util import minibatch\n",
    "import spacy\n",
    "from spacy.attrs import ORTH, LEMMA\n",
    "\n",
    "nlp = spacy.load(\"en_core_web_sm\")\n",
    "\n",
    "nlp.tokenizer.add_special_case('<unk>', [{ORTH: \"<sos>\"}])\n",
    "nlp.tokenizer.add_special_case('<eos>', [{ORTH: \"<eos>\"}])\n",
    "\n",
    "batch_size= 200\n",
    "partitions = minibatch(texts, size=batch_size)\n",
    "\n",
    "executor = Parallel(n_jobs=8, backend=\"multiprocessing\", prefer=\"threads\")\n",
    "\n",
    "def transform_texts(nlp, text):\n",
    "    docs = nlp.tokenizer.pipe(texts)\n",
    "    word_pairs = []\n",
    "    \n",
    "    for doc in docs:\n",
    "        words = [token.text.lower() for token in doc if token.is_alpha]\n",
    "        \n",
    "        for i, word in enumerate(words):\n",
    "            for offset in [-2, -1, 1, 2]:\n",
    "                if i + offset < 0 or i + offset >= len(words): continue\n",
    "                target_word = words[i+offset]\n",
    "                word_pairs.append([word, target_word])\n",
    "                 \n",
    "    return word_pairs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2min 14s, sys: 20 s, total: 2min 34s\n",
      "Wall time: 4min 5s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "do = delayed(partial(transform_texts, nlp))\n",
    "tasks = (do(batch) for batch in partitions)\n",
    "word_pairs_hierarchical = executor(tasks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "word_pairs = []\n",
    "\n",
    "for pairs in word_pairs_hierarchical: word_pairs += pairs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "219135400"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(word_pairs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "ws = []\n",
    "for w1, w2 in word_pairs:\n",
    "    ws.append(w1)\n",
    "    ws.append(w2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "438270800"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ws)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "c = Counter(ws)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "vocab = [v for v, count in c.most_common(37622)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "vocab_set = set(vocab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "word_pairs_old = word_pairs\n",
    "\n",
    "word_pairs = [[w1, w2] for w1, w2 in word_pairs_old if w1 in vocab_set and w2 in vocab_set]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['polyozellus', 'polyozellus'],\n",
       " ['polyozellus', 'is'],\n",
       " ['polyozellus', 'polyozellus'],\n",
       " ['polyozellus', 'is'],\n",
       " ['polyozellus', 'a'],\n",
       " ['is', 'polyozellus'],\n",
       " ['is', 'polyozellus'],\n",
       " ['is', 'a'],\n",
       " ['is', 'fungal'],\n",
       " ['a', 'polyozellus']]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "word_pairs[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "210868940"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(word_pairs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "vocab = list(vocab)\n",
    "word2index = {w: i for i, w in enumerate(vocab)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Dataset():\n",
    "    def __init__(self, pairs, length=10_000_000):\n",
    "        self.pairs = pairs\n",
    "        self.len = length\n",
    "    def __len__(self):\n",
    "        return self.len\n",
    "    def __getitem__(self, idx):\n",
    "        source_word, target_word = self.pairs[np.random.randint(len(self.pairs))]\n",
    "        return word2index[source_word], word2index[target_word]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 14 mln -> 180 mln"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "210868940"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(word_pairs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_ds = Dataset(word_pairs)\n",
    "valid_ds = Dataset(word_pairs, 200_000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10000000, 200000)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(train_ds), len(valid_ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "BS = 2048\n",
    "NUM_WORKERS = 4\n",
    "\n",
    "train_dl = DataLoader(train_ds, BS, NUM_WORKERS, shuffle=True)\n",
    "valid_dl = DataLoader(valid_ds, BS, NUM_WORKERS)\n",
    "\n",
    "dls = DataLoaders(train_dl, valid_dl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Model(Module):\n",
    "    def __init__(self, hidden_size=50):\n",
    "        self.embeddings =nn.Embedding(len(vocab), hidden_size)\n",
    "        self.linear = nn.Linear(hidden_size, len(vocab))\n",
    "            \n",
    "    def forward(self, x):\n",
    "        x = self.embeddings(x)\n",
    "        return self.linear(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn = Learner(\n",
    "    dls.cuda(),\n",
    "    Model().cuda(),\n",
    "    loss_func=CrossEntropyLossFlat(),\n",
    "    opt_func=Adam,\n",
    "    metrics=[accuracy]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>7.279257</td>\n",
       "      <td>7.275099</td>\n",
       "      <td>0.086880</td>\n",
       "      <td>06:04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>7.176283</td>\n",
       "      <td>7.175502</td>\n",
       "      <td>0.089820</td>\n",
       "      <td>02:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>7.124911</td>\n",
       "      <td>7.135908</td>\n",
       "      <td>0.090100</td>\n",
       "      <td>01:36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>7.081093</td>\n",
       "      <td>7.093219</td>\n",
       "      <td>0.091370</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>7.052563</td>\n",
       "      <td>7.053514</td>\n",
       "      <td>0.092935</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>7.040986</td>\n",
       "      <td>7.029871</td>\n",
       "      <td>0.094340</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>7.010113</td>\n",
       "      <td>7.014532</td>\n",
       "      <td>0.094785</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>6.999692</td>\n",
       "      <td>6.988066</td>\n",
       "      <td>0.094780</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>6.978326</td>\n",
       "      <td>6.971030</td>\n",
       "      <td>0.094760</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>6.976083</td>\n",
       "      <td>6.978474</td>\n",
       "      <td>0.094550</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>6.974166</td>\n",
       "      <td>6.957635</td>\n",
       "      <td>0.095310</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>6.940723</td>\n",
       "      <td>6.953903</td>\n",
       "      <td>0.094955</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>6.929806</td>\n",
       "      <td>6.931746</td>\n",
       "      <td>0.096440</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>6.942671</td>\n",
       "      <td>6.926918</td>\n",
       "      <td>0.095115</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>6.917469</td>\n",
       "      <td>6.913716</td>\n",
       "      <td>0.095910</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>6.915286</td>\n",
       "      <td>6.918577</td>\n",
       "      <td>0.095020</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>6.903223</td>\n",
       "      <td>6.910934</td>\n",
       "      <td>0.096990</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>6.904391</td>\n",
       "      <td>6.906753</td>\n",
       "      <td>0.096455</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>6.905397</td>\n",
       "      <td>6.895346</td>\n",
       "      <td>0.096755</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>6.885004</td>\n",
       "      <td>6.891578</td>\n",
       "      <td>0.096095</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>6.883260</td>\n",
       "      <td>6.892632</td>\n",
       "      <td>0.096935</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>6.888955</td>\n",
       "      <td>6.864686</td>\n",
       "      <td>0.098660</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>6.878586</td>\n",
       "      <td>6.885136</td>\n",
       "      <td>0.096420</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>6.877932</td>\n",
       "      <td>6.881006</td>\n",
       "      <td>0.096660</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>6.872884</td>\n",
       "      <td>6.878320</td>\n",
       "      <td>0.096800</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>6.857338</td>\n",
       "      <td>6.856967</td>\n",
       "      <td>0.096560</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26</td>\n",
       "      <td>6.863945</td>\n",
       "      <td>6.862631</td>\n",
       "      <td>0.097915</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27</td>\n",
       "      <td>6.863408</td>\n",
       "      <td>6.853336</td>\n",
       "      <td>0.097205</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>28</td>\n",
       "      <td>6.846605</td>\n",
       "      <td>6.859813</td>\n",
       "      <td>0.097480</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29</td>\n",
       "      <td>6.848239</td>\n",
       "      <td>6.849073</td>\n",
       "      <td>0.097840</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30</td>\n",
       "      <td>6.857983</td>\n",
       "      <td>6.854109</td>\n",
       "      <td>0.096825</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31</td>\n",
       "      <td>6.845841</td>\n",
       "      <td>6.854823</td>\n",
       "      <td>0.097530</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>32</td>\n",
       "      <td>6.842700</td>\n",
       "      <td>6.847174</td>\n",
       "      <td>0.098400</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>33</td>\n",
       "      <td>6.856168</td>\n",
       "      <td>6.843386</td>\n",
       "      <td>0.096625</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>34</td>\n",
       "      <td>6.851519</td>\n",
       "      <td>6.836527</td>\n",
       "      <td>0.097740</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>35</td>\n",
       "      <td>6.842906</td>\n",
       "      <td>6.843396</td>\n",
       "      <td>0.098080</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>36</td>\n",
       "      <td>6.838382</td>\n",
       "      <td>6.848223</td>\n",
       "      <td>0.096850</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>37</td>\n",
       "      <td>6.830406</td>\n",
       "      <td>6.842849</td>\n",
       "      <td>0.098205</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>38</td>\n",
       "      <td>6.824918</td>\n",
       "      <td>6.852972</td>\n",
       "      <td>0.096060</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39</td>\n",
       "      <td>6.826150</td>\n",
       "      <td>6.851136</td>\n",
       "      <td>0.097745</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>40</td>\n",
       "      <td>6.837220</td>\n",
       "      <td>6.831629</td>\n",
       "      <td>0.097060</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>41</td>\n",
       "      <td>6.822276</td>\n",
       "      <td>6.837327</td>\n",
       "      <td>0.097540</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>42</td>\n",
       "      <td>6.836083</td>\n",
       "      <td>6.825553</td>\n",
       "      <td>0.098575</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>43</td>\n",
       "      <td>6.824796</td>\n",
       "      <td>6.835401</td>\n",
       "      <td>0.097850</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>44</td>\n",
       "      <td>6.839267</td>\n",
       "      <td>6.828061</td>\n",
       "      <td>0.097875</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45</td>\n",
       "      <td>6.828279</td>\n",
       "      <td>6.834447</td>\n",
       "      <td>0.097895</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>46</td>\n",
       "      <td>6.836960</td>\n",
       "      <td>6.828586</td>\n",
       "      <td>0.097940</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>47</td>\n",
       "      <td>6.829963</td>\n",
       "      <td>6.831903</td>\n",
       "      <td>0.097060</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>48</td>\n",
       "      <td>6.833704</td>\n",
       "      <td>6.828218</td>\n",
       "      <td>0.097875</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>49</td>\n",
       "      <td>6.837545</td>\n",
       "      <td>6.819813</td>\n",
       "      <td>0.098095</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50</td>\n",
       "      <td>6.831043</td>\n",
       "      <td>6.821555</td>\n",
       "      <td>0.098370</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>51</td>\n",
       "      <td>6.831722</td>\n",
       "      <td>6.830467</td>\n",
       "      <td>0.098040</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>52</td>\n",
       "      <td>6.829860</td>\n",
       "      <td>6.822723</td>\n",
       "      <td>0.097405</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>53</td>\n",
       "      <td>6.824535</td>\n",
       "      <td>6.825526</td>\n",
       "      <td>0.097885</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>54</td>\n",
       "      <td>6.818530</td>\n",
       "      <td>6.827142</td>\n",
       "      <td>0.097260</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55</td>\n",
       "      <td>6.826184</td>\n",
       "      <td>6.820014</td>\n",
       "      <td>0.097480</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>56</td>\n",
       "      <td>6.815964</td>\n",
       "      <td>6.816849</td>\n",
       "      <td>0.098495</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>57</td>\n",
       "      <td>6.815796</td>\n",
       "      <td>6.822509</td>\n",
       "      <td>0.098035</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>58</td>\n",
       "      <td>6.823810</td>\n",
       "      <td>6.822627</td>\n",
       "      <td>0.098340</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>59</td>\n",
       "      <td>6.823499</td>\n",
       "      <td>6.825150</td>\n",
       "      <td>0.098340</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>60</td>\n",
       "      <td>6.823243</td>\n",
       "      <td>6.833741</td>\n",
       "      <td>0.097700</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>61</td>\n",
       "      <td>6.817612</td>\n",
       "      <td>6.817836</td>\n",
       "      <td>0.099765</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>62</td>\n",
       "      <td>6.819272</td>\n",
       "      <td>6.827132</td>\n",
       "      <td>0.098120</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>63</td>\n",
       "      <td>6.811393</td>\n",
       "      <td>6.806721</td>\n",
       "      <td>0.099325</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>64</td>\n",
       "      <td>6.815834</td>\n",
       "      <td>6.817740</td>\n",
       "      <td>0.098225</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>65</td>\n",
       "      <td>6.813401</td>\n",
       "      <td>6.811337</td>\n",
       "      <td>0.098905</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>66</td>\n",
       "      <td>6.818487</td>\n",
       "      <td>6.805078</td>\n",
       "      <td>0.098840</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>67</td>\n",
       "      <td>6.822258</td>\n",
       "      <td>6.820203</td>\n",
       "      <td>0.098045</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>68</td>\n",
       "      <td>6.822461</td>\n",
       "      <td>6.822577</td>\n",
       "      <td>0.097540</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>69</td>\n",
       "      <td>6.809373</td>\n",
       "      <td>6.817612</td>\n",
       "      <td>0.098010</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>70</td>\n",
       "      <td>6.813534</td>\n",
       "      <td>6.817507</td>\n",
       "      <td>0.098770</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>71</td>\n",
       "      <td>6.811471</td>\n",
       "      <td>6.819300</td>\n",
       "      <td>0.097925</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>72</td>\n",
       "      <td>6.822999</td>\n",
       "      <td>6.823081</td>\n",
       "      <td>0.097540</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>73</td>\n",
       "      <td>6.813905</td>\n",
       "      <td>6.820583</td>\n",
       "      <td>0.098825</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>74</td>\n",
       "      <td>6.812354</td>\n",
       "      <td>6.819722</td>\n",
       "      <td>0.098345</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75</td>\n",
       "      <td>6.815640</td>\n",
       "      <td>6.815002</td>\n",
       "      <td>0.097845</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>76</td>\n",
       "      <td>6.817399</td>\n",
       "      <td>6.812624</td>\n",
       "      <td>0.098025</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>77</td>\n",
       "      <td>6.816913</td>\n",
       "      <td>6.813545</td>\n",
       "      <td>0.097585</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>78</td>\n",
       "      <td>6.809205</td>\n",
       "      <td>6.822591</td>\n",
       "      <td>0.098110</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>79</td>\n",
       "      <td>6.820599</td>\n",
       "      <td>6.824402</td>\n",
       "      <td>0.098170</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>80</td>\n",
       "      <td>6.815453</td>\n",
       "      <td>6.813597</td>\n",
       "      <td>0.097005</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>81</td>\n",
       "      <td>6.807493</td>\n",
       "      <td>6.810299</td>\n",
       "      <td>0.098625</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>82</td>\n",
       "      <td>6.815387</td>\n",
       "      <td>6.821552</td>\n",
       "      <td>0.097650</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>83</td>\n",
       "      <td>6.811984</td>\n",
       "      <td>6.811971</td>\n",
       "      <td>0.098565</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>84</td>\n",
       "      <td>6.813164</td>\n",
       "      <td>6.806451</td>\n",
       "      <td>0.097275</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>85</td>\n",
       "      <td>6.806834</td>\n",
       "      <td>6.801295</td>\n",
       "      <td>0.098385</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>86</td>\n",
       "      <td>6.797489</td>\n",
       "      <td>6.815313</td>\n",
       "      <td>0.097385</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>87</td>\n",
       "      <td>6.816522</td>\n",
       "      <td>6.808282</td>\n",
       "      <td>0.099460</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>88</td>\n",
       "      <td>6.811388</td>\n",
       "      <td>6.808016</td>\n",
       "      <td>0.098500</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>89</td>\n",
       "      <td>6.814456</td>\n",
       "      <td>6.815868</td>\n",
       "      <td>0.098505</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>90</td>\n",
       "      <td>6.817852</td>\n",
       "      <td>6.809855</td>\n",
       "      <td>0.096880</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>91</td>\n",
       "      <td>6.820234</td>\n",
       "      <td>6.824955</td>\n",
       "      <td>0.096855</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>92</td>\n",
       "      <td>6.810772</td>\n",
       "      <td>6.821198</td>\n",
       "      <td>0.097125</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>93</td>\n",
       "      <td>6.801649</td>\n",
       "      <td>6.815637</td>\n",
       "      <td>0.098380</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>94</td>\n",
       "      <td>6.809424</td>\n",
       "      <td>6.804228</td>\n",
       "      <td>0.097875</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>95</td>\n",
       "      <td>6.820468</td>\n",
       "      <td>6.806956</td>\n",
       "      <td>0.098960</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>96</td>\n",
       "      <td>6.820102</td>\n",
       "      <td>6.810336</td>\n",
       "      <td>0.098795</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>97</td>\n",
       "      <td>6.828391</td>\n",
       "      <td>6.816014</td>\n",
       "      <td>0.096880</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>98</td>\n",
       "      <td>6.825587</td>\n",
       "      <td>6.819124</td>\n",
       "      <td>0.097995</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>99</td>\n",
       "      <td>6.807970</td>\n",
       "      <td>6.822797</td>\n",
       "      <td>0.097855</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>100</td>\n",
       "      <td>6.808415</td>\n",
       "      <td>6.809134</td>\n",
       "      <td>0.098410</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>101</td>\n",
       "      <td>6.797224</td>\n",
       "      <td>6.811866</td>\n",
       "      <td>0.097705</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>102</td>\n",
       "      <td>6.807795</td>\n",
       "      <td>6.805203</td>\n",
       "      <td>0.098510</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>103</td>\n",
       "      <td>6.808615</td>\n",
       "      <td>6.815318</td>\n",
       "      <td>0.097450</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>104</td>\n",
       "      <td>6.812893</td>\n",
       "      <td>6.814282</td>\n",
       "      <td>0.097880</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>105</td>\n",
       "      <td>6.815851</td>\n",
       "      <td>6.802891</td>\n",
       "      <td>0.098780</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>106</td>\n",
       "      <td>6.813992</td>\n",
       "      <td>6.800728</td>\n",
       "      <td>0.098415</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>107</td>\n",
       "      <td>6.820950</td>\n",
       "      <td>6.812036</td>\n",
       "      <td>0.098070</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>108</td>\n",
       "      <td>6.810546</td>\n",
       "      <td>6.812887</td>\n",
       "      <td>0.098135</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>109</td>\n",
       "      <td>6.809416</td>\n",
       "      <td>6.809206</td>\n",
       "      <td>0.098620</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>110</td>\n",
       "      <td>6.811981</td>\n",
       "      <td>6.804960</td>\n",
       "      <td>0.098845</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>111</td>\n",
       "      <td>6.819326</td>\n",
       "      <td>6.810277</td>\n",
       "      <td>0.098360</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>112</td>\n",
       "      <td>6.814247</td>\n",
       "      <td>6.810263</td>\n",
       "      <td>0.097805</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>113</td>\n",
       "      <td>6.800166</td>\n",
       "      <td>6.810455</td>\n",
       "      <td>0.098425</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>114</td>\n",
       "      <td>6.810133</td>\n",
       "      <td>6.811430</td>\n",
       "      <td>0.098140</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>115</td>\n",
       "      <td>6.807442</td>\n",
       "      <td>6.813333</td>\n",
       "      <td>0.097930</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>116</td>\n",
       "      <td>6.797825</td>\n",
       "      <td>6.812665</td>\n",
       "      <td>0.098565</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>117</td>\n",
       "      <td>6.815597</td>\n",
       "      <td>6.820081</td>\n",
       "      <td>0.098200</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>118</td>\n",
       "      <td>6.805617</td>\n",
       "      <td>6.802928</td>\n",
       "      <td>0.098515</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>119</td>\n",
       "      <td>6.798355</td>\n",
       "      <td>6.802276</td>\n",
       "      <td>0.098445</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>120</td>\n",
       "      <td>6.797455</td>\n",
       "      <td>6.810528</td>\n",
       "      <td>0.097835</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>121</td>\n",
       "      <td>6.812579</td>\n",
       "      <td>6.808427</td>\n",
       "      <td>0.098325</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>122</td>\n",
       "      <td>6.817417</td>\n",
       "      <td>6.805751</td>\n",
       "      <td>0.098175</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>123</td>\n",
       "      <td>6.810729</td>\n",
       "      <td>6.813835</td>\n",
       "      <td>0.097935</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>124</td>\n",
       "      <td>6.814631</td>\n",
       "      <td>6.806167</td>\n",
       "      <td>0.096565</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>125</td>\n",
       "      <td>6.807418</td>\n",
       "      <td>6.813980</td>\n",
       "      <td>0.097810</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>126</td>\n",
       "      <td>6.795087</td>\n",
       "      <td>6.793667</td>\n",
       "      <td>0.099670</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>127</td>\n",
       "      <td>6.811762</td>\n",
       "      <td>6.811913</td>\n",
       "      <td>0.097520</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>128</td>\n",
       "      <td>6.800287</td>\n",
       "      <td>6.817488</td>\n",
       "      <td>0.097395</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>129</td>\n",
       "      <td>6.827946</td>\n",
       "      <td>6.804562</td>\n",
       "      <td>0.099345</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>130</td>\n",
       "      <td>6.813342</td>\n",
       "      <td>6.808865</td>\n",
       "      <td>0.098445</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>131</td>\n",
       "      <td>6.817572</td>\n",
       "      <td>6.811945</td>\n",
       "      <td>0.099235</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>132</td>\n",
       "      <td>6.805671</td>\n",
       "      <td>6.819658</td>\n",
       "      <td>0.097890</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>133</td>\n",
       "      <td>6.809283</td>\n",
       "      <td>6.802891</td>\n",
       "      <td>0.099020</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>134</td>\n",
       "      <td>6.810859</td>\n",
       "      <td>6.802817</td>\n",
       "      <td>0.098195</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>135</td>\n",
       "      <td>6.805412</td>\n",
       "      <td>6.804797</td>\n",
       "      <td>0.098735</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>136</td>\n",
       "      <td>6.815120</td>\n",
       "      <td>6.812063</td>\n",
       "      <td>0.099670</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>137</td>\n",
       "      <td>6.815678</td>\n",
       "      <td>6.819301</td>\n",
       "      <td>0.097640</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>138</td>\n",
       "      <td>6.809628</td>\n",
       "      <td>6.796925</td>\n",
       "      <td>0.098725</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>139</td>\n",
       "      <td>6.816774</td>\n",
       "      <td>6.809916</td>\n",
       "      <td>0.098360</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>140</td>\n",
       "      <td>6.814684</td>\n",
       "      <td>6.810885</td>\n",
       "      <td>0.097590</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>141</td>\n",
       "      <td>6.800276</td>\n",
       "      <td>6.807665</td>\n",
       "      <td>0.098195</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>142</td>\n",
       "      <td>6.812976</td>\n",
       "      <td>6.800908</td>\n",
       "      <td>0.098030</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>143</td>\n",
       "      <td>6.798156</td>\n",
       "      <td>6.821835</td>\n",
       "      <td>0.097685</td>\n",
       "      <td>01:23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>144</td>\n",
       "      <td>6.823935</td>\n",
       "      <td>6.816646</td>\n",
       "      <td>0.098200</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>145</td>\n",
       "      <td>6.803761</td>\n",
       "      <td>6.802124</td>\n",
       "      <td>0.098585</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>146</td>\n",
       "      <td>6.805475</td>\n",
       "      <td>6.803923</td>\n",
       "      <td>0.098935</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>147</td>\n",
       "      <td>6.801533</td>\n",
       "      <td>6.803565</td>\n",
       "      <td>0.098615</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>148</td>\n",
       "      <td>6.809661</td>\n",
       "      <td>6.804802</td>\n",
       "      <td>0.098395</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>149</td>\n",
       "      <td>6.810359</td>\n",
       "      <td>6.814966</td>\n",
       "      <td>0.097395</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>150</td>\n",
       "      <td>6.823316</td>\n",
       "      <td>6.805869</td>\n",
       "      <td>0.098750</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>151</td>\n",
       "      <td>6.813276</td>\n",
       "      <td>6.807583</td>\n",
       "      <td>0.098205</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>152</td>\n",
       "      <td>6.808481</td>\n",
       "      <td>6.801314</td>\n",
       "      <td>0.098010</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>153</td>\n",
       "      <td>6.813464</td>\n",
       "      <td>6.814582</td>\n",
       "      <td>0.098445</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>154</td>\n",
       "      <td>6.802724</td>\n",
       "      <td>6.812099</td>\n",
       "      <td>0.098495</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>155</td>\n",
       "      <td>6.818197</td>\n",
       "      <td>6.820208</td>\n",
       "      <td>0.098020</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>156</td>\n",
       "      <td>6.803714</td>\n",
       "      <td>6.807841</td>\n",
       "      <td>0.098160</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>157</td>\n",
       "      <td>6.807450</td>\n",
       "      <td>6.801236</td>\n",
       "      <td>0.098445</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>158</td>\n",
       "      <td>6.802161</td>\n",
       "      <td>6.802813</td>\n",
       "      <td>0.098565</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>159</td>\n",
       "      <td>6.810601</td>\n",
       "      <td>6.800929</td>\n",
       "      <td>0.098585</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>160</td>\n",
       "      <td>6.809358</td>\n",
       "      <td>6.814111</td>\n",
       "      <td>0.098675</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>161</td>\n",
       "      <td>6.804171</td>\n",
       "      <td>6.804856</td>\n",
       "      <td>0.098625</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>162</td>\n",
       "      <td>6.805724</td>\n",
       "      <td>6.797754</td>\n",
       "      <td>0.099565</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>163</td>\n",
       "      <td>6.807486</td>\n",
       "      <td>6.801404</td>\n",
       "      <td>0.098200</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>164</td>\n",
       "      <td>6.813139</td>\n",
       "      <td>6.798878</td>\n",
       "      <td>0.099315</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>165</td>\n",
       "      <td>6.816349</td>\n",
       "      <td>6.802391</td>\n",
       "      <td>0.098130</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>166</td>\n",
       "      <td>6.812226</td>\n",
       "      <td>6.813262</td>\n",
       "      <td>0.097815</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>167</td>\n",
       "      <td>6.814002</td>\n",
       "      <td>6.804847</td>\n",
       "      <td>0.098530</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>168</td>\n",
       "      <td>6.804013</td>\n",
       "      <td>6.809921</td>\n",
       "      <td>0.097990</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>169</td>\n",
       "      <td>6.817058</td>\n",
       "      <td>6.809730</td>\n",
       "      <td>0.097900</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>170</td>\n",
       "      <td>6.792094</td>\n",
       "      <td>6.804601</td>\n",
       "      <td>0.099015</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>171</td>\n",
       "      <td>6.805377</td>\n",
       "      <td>6.803456</td>\n",
       "      <td>0.098395</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>172</td>\n",
       "      <td>6.824205</td>\n",
       "      <td>6.818175</td>\n",
       "      <td>0.097230</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>173</td>\n",
       "      <td>6.811737</td>\n",
       "      <td>6.790510</td>\n",
       "      <td>0.099595</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>174</td>\n",
       "      <td>6.815255</td>\n",
       "      <td>6.798967</td>\n",
       "      <td>0.098650</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>175</td>\n",
       "      <td>6.812642</td>\n",
       "      <td>6.816857</td>\n",
       "      <td>0.097845</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>176</td>\n",
       "      <td>6.811339</td>\n",
       "      <td>6.803589</td>\n",
       "      <td>0.098915</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>177</td>\n",
       "      <td>6.812035</td>\n",
       "      <td>6.792996</td>\n",
       "      <td>0.099035</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>178</td>\n",
       "      <td>6.806266</td>\n",
       "      <td>6.797392</td>\n",
       "      <td>0.098905</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>179</td>\n",
       "      <td>6.817129</td>\n",
       "      <td>6.809566</td>\n",
       "      <td>0.098745</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>180</td>\n",
       "      <td>6.814944</td>\n",
       "      <td>6.808319</td>\n",
       "      <td>0.098715</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>181</td>\n",
       "      <td>6.818076</td>\n",
       "      <td>6.821980</td>\n",
       "      <td>0.097780</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>182</td>\n",
       "      <td>6.796376</td>\n",
       "      <td>6.807445</td>\n",
       "      <td>0.098145</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>183</td>\n",
       "      <td>6.808597</td>\n",
       "      <td>6.801212</td>\n",
       "      <td>0.098510</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>184</td>\n",
       "      <td>6.804718</td>\n",
       "      <td>6.810217</td>\n",
       "      <td>0.098820</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>185</td>\n",
       "      <td>6.796797</td>\n",
       "      <td>6.800522</td>\n",
       "      <td>0.098060</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>186</td>\n",
       "      <td>6.807354</td>\n",
       "      <td>6.808746</td>\n",
       "      <td>0.098625</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>187</td>\n",
       "      <td>6.801476</td>\n",
       "      <td>6.811806</td>\n",
       "      <td>0.097765</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>188</td>\n",
       "      <td>6.808414</td>\n",
       "      <td>6.814942</td>\n",
       "      <td>0.097305</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>189</td>\n",
       "      <td>6.812326</td>\n",
       "      <td>6.793357</td>\n",
       "      <td>0.098250</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>190</td>\n",
       "      <td>6.820035</td>\n",
       "      <td>6.814283</td>\n",
       "      <td>0.097800</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>191</td>\n",
       "      <td>6.809803</td>\n",
       "      <td>6.804119</td>\n",
       "      <td>0.098060</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>192</td>\n",
       "      <td>6.806853</td>\n",
       "      <td>6.813294</td>\n",
       "      <td>0.097740</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>193</td>\n",
       "      <td>6.809855</td>\n",
       "      <td>6.815026</td>\n",
       "      <td>0.097930</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>194</td>\n",
       "      <td>6.807392</td>\n",
       "      <td>6.817468</td>\n",
       "      <td>0.098135</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>195</td>\n",
       "      <td>6.809894</td>\n",
       "      <td>6.807755</td>\n",
       "      <td>0.097260</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>196</td>\n",
       "      <td>6.807577</td>\n",
       "      <td>6.804664</td>\n",
       "      <td>0.098140</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>197</td>\n",
       "      <td>6.811104</td>\n",
       "      <td>6.806301</td>\n",
       "      <td>0.098630</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>198</td>\n",
       "      <td>6.813483</td>\n",
       "      <td>6.809010</td>\n",
       "      <td>0.099190</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>199</td>\n",
       "      <td>6.803223</td>\n",
       "      <td>6.815189</td>\n",
       "      <td>0.098160</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>200</td>\n",
       "      <td>6.800322</td>\n",
       "      <td>6.811309</td>\n",
       "      <td>0.098575</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>201</td>\n",
       "      <td>6.798549</td>\n",
       "      <td>6.799841</td>\n",
       "      <td>0.099385</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>202</td>\n",
       "      <td>6.798747</td>\n",
       "      <td>6.813717</td>\n",
       "      <td>0.098405</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>203</td>\n",
       "      <td>6.815198</td>\n",
       "      <td>6.805647</td>\n",
       "      <td>0.098015</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>204</td>\n",
       "      <td>6.795729</td>\n",
       "      <td>6.809772</td>\n",
       "      <td>0.098670</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>205</td>\n",
       "      <td>6.814570</td>\n",
       "      <td>6.797922</td>\n",
       "      <td>0.098760</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>206</td>\n",
       "      <td>6.800599</td>\n",
       "      <td>6.823513</td>\n",
       "      <td>0.096190</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>207</td>\n",
       "      <td>6.808721</td>\n",
       "      <td>6.807057</td>\n",
       "      <td>0.098290</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>208</td>\n",
       "      <td>6.804363</td>\n",
       "      <td>6.799524</td>\n",
       "      <td>0.099385</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>209</td>\n",
       "      <td>6.806625</td>\n",
       "      <td>6.819887</td>\n",
       "      <td>0.098340</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>210</td>\n",
       "      <td>6.818793</td>\n",
       "      <td>6.818613</td>\n",
       "      <td>0.098455</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>211</td>\n",
       "      <td>6.811084</td>\n",
       "      <td>6.818798</td>\n",
       "      <td>0.098045</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>212</td>\n",
       "      <td>6.813281</td>\n",
       "      <td>6.806891</td>\n",
       "      <td>0.099895</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>213</td>\n",
       "      <td>6.818297</td>\n",
       "      <td>6.789127</td>\n",
       "      <td>0.100110</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>214</td>\n",
       "      <td>6.802458</td>\n",
       "      <td>6.797925</td>\n",
       "      <td>0.099185</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>215</td>\n",
       "      <td>6.813762</td>\n",
       "      <td>6.800870</td>\n",
       "      <td>0.098855</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>216</td>\n",
       "      <td>6.798540</td>\n",
       "      <td>6.802134</td>\n",
       "      <td>0.098695</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>217</td>\n",
       "      <td>6.807602</td>\n",
       "      <td>6.810709</td>\n",
       "      <td>0.097560</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>218</td>\n",
       "      <td>6.811553</td>\n",
       "      <td>6.816187</td>\n",
       "      <td>0.097375</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>219</td>\n",
       "      <td>6.815701</td>\n",
       "      <td>6.815353</td>\n",
       "      <td>0.097955</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>220</td>\n",
       "      <td>6.812784</td>\n",
       "      <td>6.804245</td>\n",
       "      <td>0.098630</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>221</td>\n",
       "      <td>6.812148</td>\n",
       "      <td>6.804130</td>\n",
       "      <td>0.097485</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>222</td>\n",
       "      <td>6.811975</td>\n",
       "      <td>6.811557</td>\n",
       "      <td>0.097675</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>223</td>\n",
       "      <td>6.813548</td>\n",
       "      <td>6.803865</td>\n",
       "      <td>0.099095</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>224</td>\n",
       "      <td>6.809487</td>\n",
       "      <td>6.798366</td>\n",
       "      <td>0.099025</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>225</td>\n",
       "      <td>6.800327</td>\n",
       "      <td>6.802387</td>\n",
       "      <td>0.098890</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>226</td>\n",
       "      <td>6.802807</td>\n",
       "      <td>6.800502</td>\n",
       "      <td>0.099530</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>227</td>\n",
       "      <td>6.807868</td>\n",
       "      <td>6.807302</td>\n",
       "      <td>0.098480</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>228</td>\n",
       "      <td>6.797635</td>\n",
       "      <td>6.804923</td>\n",
       "      <td>0.098110</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>229</td>\n",
       "      <td>6.803724</td>\n",
       "      <td>6.797808</td>\n",
       "      <td>0.098375</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>230</td>\n",
       "      <td>6.802872</td>\n",
       "      <td>6.798808</td>\n",
       "      <td>0.098095</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>231</td>\n",
       "      <td>6.808567</td>\n",
       "      <td>6.809014</td>\n",
       "      <td>0.097835</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>232</td>\n",
       "      <td>6.809325</td>\n",
       "      <td>6.809989</td>\n",
       "      <td>0.097825</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>233</td>\n",
       "      <td>6.810887</td>\n",
       "      <td>6.807357</td>\n",
       "      <td>0.097625</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>234</td>\n",
       "      <td>6.814713</td>\n",
       "      <td>6.804721</td>\n",
       "      <td>0.097745</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>235</td>\n",
       "      <td>6.811304</td>\n",
       "      <td>6.804356</td>\n",
       "      <td>0.098490</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>236</td>\n",
       "      <td>6.804421</td>\n",
       "      <td>6.813632</td>\n",
       "      <td>0.098770</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>237</td>\n",
       "      <td>6.800614</td>\n",
       "      <td>6.807864</td>\n",
       "      <td>0.099130</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>238</td>\n",
       "      <td>6.808423</td>\n",
       "      <td>6.811508</td>\n",
       "      <td>0.099220</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>239</td>\n",
       "      <td>6.797454</td>\n",
       "      <td>6.803653</td>\n",
       "      <td>0.099330</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>240</td>\n",
       "      <td>6.795007</td>\n",
       "      <td>6.809735</td>\n",
       "      <td>0.099020</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>241</td>\n",
       "      <td>6.806768</td>\n",
       "      <td>6.808757</td>\n",
       "      <td>0.097945</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>242</td>\n",
       "      <td>6.798801</td>\n",
       "      <td>6.799870</td>\n",
       "      <td>0.098270</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>243</td>\n",
       "      <td>6.809785</td>\n",
       "      <td>6.810239</td>\n",
       "      <td>0.098470</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>244</td>\n",
       "      <td>6.810355</td>\n",
       "      <td>6.809809</td>\n",
       "      <td>0.099105</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>245</td>\n",
       "      <td>6.817408</td>\n",
       "      <td>6.801212</td>\n",
       "      <td>0.098990</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>246</td>\n",
       "      <td>6.806076</td>\n",
       "      <td>6.796695</td>\n",
       "      <td>0.098710</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>247</td>\n",
       "      <td>6.812294</td>\n",
       "      <td>6.803539</td>\n",
       "      <td>0.098535</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>248</td>\n",
       "      <td>6.812887</td>\n",
       "      <td>6.803268</td>\n",
       "      <td>0.098650</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>249</td>\n",
       "      <td>6.814218</td>\n",
       "      <td>6.810719</td>\n",
       "      <td>0.097110</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>250</td>\n",
       "      <td>6.812692</td>\n",
       "      <td>6.813153</td>\n",
       "      <td>0.098930</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>251</td>\n",
       "      <td>6.804531</td>\n",
       "      <td>6.809625</td>\n",
       "      <td>0.098150</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>252</td>\n",
       "      <td>6.814435</td>\n",
       "      <td>6.800996</td>\n",
       "      <td>0.098540</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>253</td>\n",
       "      <td>6.805838</td>\n",
       "      <td>6.824780</td>\n",
       "      <td>0.097865</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>254</td>\n",
       "      <td>6.821942</td>\n",
       "      <td>6.809824</td>\n",
       "      <td>0.098600</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>255</td>\n",
       "      <td>6.806304</td>\n",
       "      <td>6.812424</td>\n",
       "      <td>0.098275</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>256</td>\n",
       "      <td>6.803123</td>\n",
       "      <td>6.814848</td>\n",
       "      <td>0.098495</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>257</td>\n",
       "      <td>6.796880</td>\n",
       "      <td>6.805890</td>\n",
       "      <td>0.098185</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>258</td>\n",
       "      <td>6.814287</td>\n",
       "      <td>6.810144</td>\n",
       "      <td>0.098750</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>259</td>\n",
       "      <td>6.796136</td>\n",
       "      <td>6.803616</td>\n",
       "      <td>0.099040</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>260</td>\n",
       "      <td>6.804962</td>\n",
       "      <td>6.813360</td>\n",
       "      <td>0.098500</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>261</td>\n",
       "      <td>6.811384</td>\n",
       "      <td>6.804883</td>\n",
       "      <td>0.099090</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>262</td>\n",
       "      <td>6.808462</td>\n",
       "      <td>6.813786</td>\n",
       "      <td>0.099120</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>263</td>\n",
       "      <td>6.811501</td>\n",
       "      <td>6.812639</td>\n",
       "      <td>0.098050</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>264</td>\n",
       "      <td>6.808598</td>\n",
       "      <td>6.805040</td>\n",
       "      <td>0.098710</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>265</td>\n",
       "      <td>6.809418</td>\n",
       "      <td>6.815155</td>\n",
       "      <td>0.097755</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>266</td>\n",
       "      <td>6.811683</td>\n",
       "      <td>6.801325</td>\n",
       "      <td>0.098585</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>267</td>\n",
       "      <td>6.810200</td>\n",
       "      <td>6.807550</td>\n",
       "      <td>0.099065</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>268</td>\n",
       "      <td>6.813264</td>\n",
       "      <td>6.807850</td>\n",
       "      <td>0.098190</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>269</td>\n",
       "      <td>6.809503</td>\n",
       "      <td>6.801270</td>\n",
       "      <td>0.098200</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>270</td>\n",
       "      <td>6.812043</td>\n",
       "      <td>6.817836</td>\n",
       "      <td>0.098360</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>271</td>\n",
       "      <td>6.801016</td>\n",
       "      <td>6.817752</td>\n",
       "      <td>0.098325</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>272</td>\n",
       "      <td>6.811846</td>\n",
       "      <td>6.812830</td>\n",
       "      <td>0.098740</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>273</td>\n",
       "      <td>6.807490</td>\n",
       "      <td>6.819817</td>\n",
       "      <td>0.097965</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>274</td>\n",
       "      <td>6.808527</td>\n",
       "      <td>6.831662</td>\n",
       "      <td>0.097055</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>275</td>\n",
       "      <td>6.800013</td>\n",
       "      <td>6.805114</td>\n",
       "      <td>0.099025</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>276</td>\n",
       "      <td>6.807954</td>\n",
       "      <td>6.806219</td>\n",
       "      <td>0.098410</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>277</td>\n",
       "      <td>6.827345</td>\n",
       "      <td>6.810677</td>\n",
       "      <td>0.099060</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>278</td>\n",
       "      <td>6.814585</td>\n",
       "      <td>6.815671</td>\n",
       "      <td>0.098585</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>279</td>\n",
       "      <td>6.814789</td>\n",
       "      <td>6.806940</td>\n",
       "      <td>0.099245</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>280</td>\n",
       "      <td>6.807589</td>\n",
       "      <td>6.811557</td>\n",
       "      <td>0.097820</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>281</td>\n",
       "      <td>6.802865</td>\n",
       "      <td>6.815736</td>\n",
       "      <td>0.097820</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>282</td>\n",
       "      <td>6.808122</td>\n",
       "      <td>6.820879</td>\n",
       "      <td>0.097955</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>283</td>\n",
       "      <td>6.810336</td>\n",
       "      <td>6.796389</td>\n",
       "      <td>0.097550</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>284</td>\n",
       "      <td>6.805551</td>\n",
       "      <td>6.810339</td>\n",
       "      <td>0.098115</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>285</td>\n",
       "      <td>6.808583</td>\n",
       "      <td>6.803507</td>\n",
       "      <td>0.098740</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>286</td>\n",
       "      <td>6.809577</td>\n",
       "      <td>6.795016</td>\n",
       "      <td>0.099070</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>287</td>\n",
       "      <td>6.806799</td>\n",
       "      <td>6.821817</td>\n",
       "      <td>0.097165</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>288</td>\n",
       "      <td>6.801805</td>\n",
       "      <td>6.812918</td>\n",
       "      <td>0.098600</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>289</td>\n",
       "      <td>6.804828</td>\n",
       "      <td>6.810999</td>\n",
       "      <td>0.099040</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>290</td>\n",
       "      <td>6.815981</td>\n",
       "      <td>6.801451</td>\n",
       "      <td>0.099410</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>291</td>\n",
       "      <td>6.817956</td>\n",
       "      <td>6.794485</td>\n",
       "      <td>0.099095</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>292</td>\n",
       "      <td>6.814143</td>\n",
       "      <td>6.805396</td>\n",
       "      <td>0.098630</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>293</td>\n",
       "      <td>6.799996</td>\n",
       "      <td>6.796183</td>\n",
       "      <td>0.100015</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>294</td>\n",
       "      <td>6.814234</td>\n",
       "      <td>6.803937</td>\n",
       "      <td>0.097260</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>295</td>\n",
       "      <td>6.816646</td>\n",
       "      <td>6.806213</td>\n",
       "      <td>0.098330</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>296</td>\n",
       "      <td>6.807881</td>\n",
       "      <td>6.805310</td>\n",
       "      <td>0.098830</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>297</td>\n",
       "      <td>6.813548</td>\n",
       "      <td>6.810851</td>\n",
       "      <td>0.098185</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>298</td>\n",
       "      <td>6.815199</td>\n",
       "      <td>6.809024</td>\n",
       "      <td>0.099595</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>299</td>\n",
       "      <td>6.824696</td>\n",
       "      <td>6.804759</td>\n",
       "      <td>0.099340</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>300</td>\n",
       "      <td>6.816120</td>\n",
       "      <td>6.803893</td>\n",
       "      <td>0.097675</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>301</td>\n",
       "      <td>6.812484</td>\n",
       "      <td>6.800614</td>\n",
       "      <td>0.098280</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>302</td>\n",
       "      <td>6.805597</td>\n",
       "      <td>6.808625</td>\n",
       "      <td>0.098240</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>303</td>\n",
       "      <td>6.808436</td>\n",
       "      <td>6.806581</td>\n",
       "      <td>0.097950</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>304</td>\n",
       "      <td>6.812503</td>\n",
       "      <td>6.804681</td>\n",
       "      <td>0.097220</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>305</td>\n",
       "      <td>6.810037</td>\n",
       "      <td>6.801777</td>\n",
       "      <td>0.098580</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>306</td>\n",
       "      <td>6.807591</td>\n",
       "      <td>6.806132</td>\n",
       "      <td>0.098025</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>307</td>\n",
       "      <td>6.798753</td>\n",
       "      <td>6.807386</td>\n",
       "      <td>0.098460</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>308</td>\n",
       "      <td>6.787781</td>\n",
       "      <td>6.805527</td>\n",
       "      <td>0.097630</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>309</td>\n",
       "      <td>6.800560</td>\n",
       "      <td>6.790765</td>\n",
       "      <td>0.097650</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>310</td>\n",
       "      <td>6.813952</td>\n",
       "      <td>6.810011</td>\n",
       "      <td>0.098460</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>311</td>\n",
       "      <td>6.817323</td>\n",
       "      <td>6.813236</td>\n",
       "      <td>0.098210</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>312</td>\n",
       "      <td>6.811387</td>\n",
       "      <td>6.806170</td>\n",
       "      <td>0.098860</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>313</td>\n",
       "      <td>6.805859</td>\n",
       "      <td>6.804413</td>\n",
       "      <td>0.098330</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>314</td>\n",
       "      <td>6.820842</td>\n",
       "      <td>6.809205</td>\n",
       "      <td>0.097460</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>315</td>\n",
       "      <td>6.806611</td>\n",
       "      <td>6.805274</td>\n",
       "      <td>0.097600</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>316</td>\n",
       "      <td>6.817349</td>\n",
       "      <td>6.799741</td>\n",
       "      <td>0.099205</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>317</td>\n",
       "      <td>6.807092</td>\n",
       "      <td>6.805922</td>\n",
       "      <td>0.099105</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>318</td>\n",
       "      <td>6.807742</td>\n",
       "      <td>6.809929</td>\n",
       "      <td>0.098820</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>319</td>\n",
       "      <td>6.821012</td>\n",
       "      <td>6.810460</td>\n",
       "      <td>0.098285</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>320</td>\n",
       "      <td>6.811116</td>\n",
       "      <td>6.810955</td>\n",
       "      <td>0.098080</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>321</td>\n",
       "      <td>6.807281</td>\n",
       "      <td>6.809070</td>\n",
       "      <td>0.098380</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>322</td>\n",
       "      <td>6.821820</td>\n",
       "      <td>6.817947</td>\n",
       "      <td>0.097530</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>323</td>\n",
       "      <td>6.812004</td>\n",
       "      <td>6.810022</td>\n",
       "      <td>0.097400</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>324</td>\n",
       "      <td>6.794926</td>\n",
       "      <td>6.803256</td>\n",
       "      <td>0.098900</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>325</td>\n",
       "      <td>6.811295</td>\n",
       "      <td>6.814054</td>\n",
       "      <td>0.097335</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>326</td>\n",
       "      <td>6.811425</td>\n",
       "      <td>6.812488</td>\n",
       "      <td>0.099170</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>327</td>\n",
       "      <td>6.804629</td>\n",
       "      <td>6.806945</td>\n",
       "      <td>0.097925</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>328</td>\n",
       "      <td>6.799429</td>\n",
       "      <td>6.795981</td>\n",
       "      <td>0.099950</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>329</td>\n",
       "      <td>6.802517</td>\n",
       "      <td>6.799275</td>\n",
       "      <td>0.098425</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>330</td>\n",
       "      <td>6.795856</td>\n",
       "      <td>6.813066</td>\n",
       "      <td>0.098220</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>331</td>\n",
       "      <td>6.809942</td>\n",
       "      <td>6.800334</td>\n",
       "      <td>0.098995</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>332</td>\n",
       "      <td>6.796100</td>\n",
       "      <td>6.801463</td>\n",
       "      <td>0.098410</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>333</td>\n",
       "      <td>6.817955</td>\n",
       "      <td>6.800142</td>\n",
       "      <td>0.099465</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>334</td>\n",
       "      <td>6.791809</td>\n",
       "      <td>6.804327</td>\n",
       "      <td>0.098030</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>335</td>\n",
       "      <td>6.803190</td>\n",
       "      <td>6.807184</td>\n",
       "      <td>0.099035</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>336</td>\n",
       "      <td>6.809016</td>\n",
       "      <td>6.804996</td>\n",
       "      <td>0.099165</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>337</td>\n",
       "      <td>6.807644</td>\n",
       "      <td>6.813812</td>\n",
       "      <td>0.097260</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>338</td>\n",
       "      <td>6.809717</td>\n",
       "      <td>6.813416</td>\n",
       "      <td>0.098205</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>339</td>\n",
       "      <td>6.808849</td>\n",
       "      <td>6.798246</td>\n",
       "      <td>0.098880</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>340</td>\n",
       "      <td>6.822229</td>\n",
       "      <td>6.819505</td>\n",
       "      <td>0.097795</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>341</td>\n",
       "      <td>6.804890</td>\n",
       "      <td>6.796114</td>\n",
       "      <td>0.097405</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>342</td>\n",
       "      <td>6.811591</td>\n",
       "      <td>6.807514</td>\n",
       "      <td>0.098625</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>343</td>\n",
       "      <td>6.805733</td>\n",
       "      <td>6.798879</td>\n",
       "      <td>0.097570</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>344</td>\n",
       "      <td>6.801782</td>\n",
       "      <td>6.816132</td>\n",
       "      <td>0.097640</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>345</td>\n",
       "      <td>6.809768</td>\n",
       "      <td>6.795129</td>\n",
       "      <td>0.099225</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>346</td>\n",
       "      <td>6.796983</td>\n",
       "      <td>6.807473</td>\n",
       "      <td>0.098525</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>347</td>\n",
       "      <td>6.804701</td>\n",
       "      <td>6.813427</td>\n",
       "      <td>0.098465</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>348</td>\n",
       "      <td>6.806517</td>\n",
       "      <td>6.809032</td>\n",
       "      <td>0.099140</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>349</td>\n",
       "      <td>6.805654</td>\n",
       "      <td>6.823634</td>\n",
       "      <td>0.096575</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>350</td>\n",
       "      <td>6.820928</td>\n",
       "      <td>6.815892</td>\n",
       "      <td>0.097200</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>351</td>\n",
       "      <td>6.819595</td>\n",
       "      <td>6.805939</td>\n",
       "      <td>0.098315</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>352</td>\n",
       "      <td>6.817988</td>\n",
       "      <td>6.821734</td>\n",
       "      <td>0.097960</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>353</td>\n",
       "      <td>6.800428</td>\n",
       "      <td>6.810613</td>\n",
       "      <td>0.097585</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>354</td>\n",
       "      <td>6.804418</td>\n",
       "      <td>6.800238</td>\n",
       "      <td>0.099405</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>355</td>\n",
       "      <td>6.811014</td>\n",
       "      <td>6.808129</td>\n",
       "      <td>0.098675</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>356</td>\n",
       "      <td>6.813385</td>\n",
       "      <td>6.799293</td>\n",
       "      <td>0.097680</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>357</td>\n",
       "      <td>6.808994</td>\n",
       "      <td>6.799494</td>\n",
       "      <td>0.098000</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>358</td>\n",
       "      <td>6.797316</td>\n",
       "      <td>6.812810</td>\n",
       "      <td>0.097035</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>359</td>\n",
       "      <td>6.807761</td>\n",
       "      <td>6.813525</td>\n",
       "      <td>0.097800</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>360</td>\n",
       "      <td>6.811835</td>\n",
       "      <td>6.800923</td>\n",
       "      <td>0.098060</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>361</td>\n",
       "      <td>6.800825</td>\n",
       "      <td>6.812940</td>\n",
       "      <td>0.097520</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>362</td>\n",
       "      <td>6.805995</td>\n",
       "      <td>6.807636</td>\n",
       "      <td>0.098520</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>363</td>\n",
       "      <td>6.804957</td>\n",
       "      <td>6.793812</td>\n",
       "      <td>0.099340</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>364</td>\n",
       "      <td>6.803078</td>\n",
       "      <td>6.806343</td>\n",
       "      <td>0.097530</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>365</td>\n",
       "      <td>6.820141</td>\n",
       "      <td>6.800073</td>\n",
       "      <td>0.099720</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>366</td>\n",
       "      <td>6.810059</td>\n",
       "      <td>6.812685</td>\n",
       "      <td>0.097540</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>367</td>\n",
       "      <td>6.814459</td>\n",
       "      <td>6.818759</td>\n",
       "      <td>0.097505</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>368</td>\n",
       "      <td>6.791834</td>\n",
       "      <td>6.815909</td>\n",
       "      <td>0.097790</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>369</td>\n",
       "      <td>6.806014</td>\n",
       "      <td>6.809831</td>\n",
       "      <td>0.098055</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>370</td>\n",
       "      <td>6.817047</td>\n",
       "      <td>6.818066</td>\n",
       "      <td>0.097335</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>371</td>\n",
       "      <td>6.802967</td>\n",
       "      <td>6.802047</td>\n",
       "      <td>0.098325</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>372</td>\n",
       "      <td>6.805735</td>\n",
       "      <td>6.800234</td>\n",
       "      <td>0.098405</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>373</td>\n",
       "      <td>6.809734</td>\n",
       "      <td>6.823861</td>\n",
       "      <td>0.096890</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>374</td>\n",
       "      <td>6.807591</td>\n",
       "      <td>6.815989</td>\n",
       "      <td>0.098290</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>375</td>\n",
       "      <td>6.808948</td>\n",
       "      <td>6.817441</td>\n",
       "      <td>0.098025</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>376</td>\n",
       "      <td>6.814030</td>\n",
       "      <td>6.804903</td>\n",
       "      <td>0.099310</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>377</td>\n",
       "      <td>6.810276</td>\n",
       "      <td>6.806912</td>\n",
       "      <td>0.098470</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>378</td>\n",
       "      <td>6.806278</td>\n",
       "      <td>6.797497</td>\n",
       "      <td>0.098715</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>379</td>\n",
       "      <td>6.816390</td>\n",
       "      <td>6.821157</td>\n",
       "      <td>0.098870</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>380</td>\n",
       "      <td>6.808629</td>\n",
       "      <td>6.804667</td>\n",
       "      <td>0.098910</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>381</td>\n",
       "      <td>6.804234</td>\n",
       "      <td>6.822458</td>\n",
       "      <td>0.097185</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>382</td>\n",
       "      <td>6.808772</td>\n",
       "      <td>6.805777</td>\n",
       "      <td>0.099120</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>383</td>\n",
       "      <td>6.803004</td>\n",
       "      <td>6.799666</td>\n",
       "      <td>0.098440</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>384</td>\n",
       "      <td>6.815505</td>\n",
       "      <td>6.800270</td>\n",
       "      <td>0.098760</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>385</td>\n",
       "      <td>6.816897</td>\n",
       "      <td>6.806723</td>\n",
       "      <td>0.098030</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>386</td>\n",
       "      <td>6.817544</td>\n",
       "      <td>6.799043</td>\n",
       "      <td>0.100150</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>387</td>\n",
       "      <td>6.806293</td>\n",
       "      <td>6.805354</td>\n",
       "      <td>0.098120</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>388</td>\n",
       "      <td>6.810429</td>\n",
       "      <td>6.815157</td>\n",
       "      <td>0.098700</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>389</td>\n",
       "      <td>6.814873</td>\n",
       "      <td>6.808306</td>\n",
       "      <td>0.098440</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>390</td>\n",
       "      <td>6.819078</td>\n",
       "      <td>6.813256</td>\n",
       "      <td>0.098545</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>391</td>\n",
       "      <td>6.806953</td>\n",
       "      <td>6.809515</td>\n",
       "      <td>0.098520</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>392</td>\n",
       "      <td>6.810292</td>\n",
       "      <td>6.803160</td>\n",
       "      <td>0.098995</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>393</td>\n",
       "      <td>6.807657</td>\n",
       "      <td>6.819632</td>\n",
       "      <td>0.098035</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>394</td>\n",
       "      <td>6.816018</td>\n",
       "      <td>6.816675</td>\n",
       "      <td>0.097590</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>395</td>\n",
       "      <td>6.809841</td>\n",
       "      <td>6.808754</td>\n",
       "      <td>0.098705</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>396</td>\n",
       "      <td>6.812478</td>\n",
       "      <td>6.805886</td>\n",
       "      <td>0.098620</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>397</td>\n",
       "      <td>6.804818</td>\n",
       "      <td>6.810273</td>\n",
       "      <td>0.097970</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>398</td>\n",
       "      <td>6.807870</td>\n",
       "      <td>6.821774</td>\n",
       "      <td>0.096745</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>399</td>\n",
       "      <td>6.810142</td>\n",
       "      <td>6.813745</td>\n",
       "      <td>0.098970</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>400</td>\n",
       "      <td>6.816045</td>\n",
       "      <td>6.822809</td>\n",
       "      <td>0.097725</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>401</td>\n",
       "      <td>6.814112</td>\n",
       "      <td>6.811016</td>\n",
       "      <td>0.098215</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>402</td>\n",
       "      <td>6.812618</td>\n",
       "      <td>6.807880</td>\n",
       "      <td>0.098580</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>403</td>\n",
       "      <td>6.799925</td>\n",
       "      <td>6.798388</td>\n",
       "      <td>0.098605</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>404</td>\n",
       "      <td>6.801542</td>\n",
       "      <td>6.812049</td>\n",
       "      <td>0.098615</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>405</td>\n",
       "      <td>6.808510</td>\n",
       "      <td>6.804724</td>\n",
       "      <td>0.097585</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>406</td>\n",
       "      <td>6.810063</td>\n",
       "      <td>6.796816</td>\n",
       "      <td>0.098640</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>407</td>\n",
       "      <td>6.794625</td>\n",
       "      <td>6.803798</td>\n",
       "      <td>0.097790</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>408</td>\n",
       "      <td>6.798760</td>\n",
       "      <td>6.823495</td>\n",
       "      <td>0.098250</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>409</td>\n",
       "      <td>6.811514</td>\n",
       "      <td>6.808362</td>\n",
       "      <td>0.097255</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>410</td>\n",
       "      <td>6.806380</td>\n",
       "      <td>6.796126</td>\n",
       "      <td>0.098555</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>411</td>\n",
       "      <td>6.807628</td>\n",
       "      <td>6.814826</td>\n",
       "      <td>0.098875</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>412</td>\n",
       "      <td>6.797375</td>\n",
       "      <td>6.811554</td>\n",
       "      <td>0.099040</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>413</td>\n",
       "      <td>6.820319</td>\n",
       "      <td>6.801106</td>\n",
       "      <td>0.099485</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>414</td>\n",
       "      <td>6.801922</td>\n",
       "      <td>6.819184</td>\n",
       "      <td>0.097100</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>415</td>\n",
       "      <td>6.811760</td>\n",
       "      <td>6.818705</td>\n",
       "      <td>0.097865</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>416</td>\n",
       "      <td>6.817171</td>\n",
       "      <td>6.799268</td>\n",
       "      <td>0.099065</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>417</td>\n",
       "      <td>6.795419</td>\n",
       "      <td>6.825975</td>\n",
       "      <td>0.097410</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>418</td>\n",
       "      <td>6.802904</td>\n",
       "      <td>6.807814</td>\n",
       "      <td>0.098925</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>419</td>\n",
       "      <td>6.799816</td>\n",
       "      <td>6.795524</td>\n",
       "      <td>0.099590</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>420</td>\n",
       "      <td>6.808762</td>\n",
       "      <td>6.816344</td>\n",
       "      <td>0.097570</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>421</td>\n",
       "      <td>6.811372</td>\n",
       "      <td>6.809514</td>\n",
       "      <td>0.097845</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>422</td>\n",
       "      <td>6.809907</td>\n",
       "      <td>6.806989</td>\n",
       "      <td>0.098555</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>423</td>\n",
       "      <td>6.804411</td>\n",
       "      <td>6.820337</td>\n",
       "      <td>0.097005</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>424</td>\n",
       "      <td>6.809735</td>\n",
       "      <td>6.825444</td>\n",
       "      <td>0.097650</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>425</td>\n",
       "      <td>6.808535</td>\n",
       "      <td>6.808833</td>\n",
       "      <td>0.097640</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>426</td>\n",
       "      <td>6.812619</td>\n",
       "      <td>6.807972</td>\n",
       "      <td>0.097920</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>427</td>\n",
       "      <td>6.807296</td>\n",
       "      <td>6.806403</td>\n",
       "      <td>0.098230</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>428</td>\n",
       "      <td>6.807368</td>\n",
       "      <td>6.797089</td>\n",
       "      <td>0.099755</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>429</td>\n",
       "      <td>6.815872</td>\n",
       "      <td>6.807333</td>\n",
       "      <td>0.099710</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>430</td>\n",
       "      <td>6.807151</td>\n",
       "      <td>6.806413</td>\n",
       "      <td>0.097710</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>431</td>\n",
       "      <td>6.808748</td>\n",
       "      <td>6.815477</td>\n",
       "      <td>0.097525</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>432</td>\n",
       "      <td>6.810680</td>\n",
       "      <td>6.805145</td>\n",
       "      <td>0.099345</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>433</td>\n",
       "      <td>6.816915</td>\n",
       "      <td>6.813923</td>\n",
       "      <td>0.097775</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>434</td>\n",
       "      <td>6.805082</td>\n",
       "      <td>6.813204</td>\n",
       "      <td>0.097640</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>435</td>\n",
       "      <td>6.825769</td>\n",
       "      <td>6.795148</td>\n",
       "      <td>0.098465</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>436</td>\n",
       "      <td>6.820107</td>\n",
       "      <td>6.826044</td>\n",
       "      <td>0.097585</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>437</td>\n",
       "      <td>6.802264</td>\n",
       "      <td>6.806050</td>\n",
       "      <td>0.098025</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>438</td>\n",
       "      <td>6.804709</td>\n",
       "      <td>6.804771</td>\n",
       "      <td>0.098725</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>439</td>\n",
       "      <td>6.804148</td>\n",
       "      <td>6.799254</td>\n",
       "      <td>0.099400</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>440</td>\n",
       "      <td>6.799027</td>\n",
       "      <td>6.795260</td>\n",
       "      <td>0.099060</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>441</td>\n",
       "      <td>6.810817</td>\n",
       "      <td>6.795077</td>\n",
       "      <td>0.099220</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>442</td>\n",
       "      <td>6.812297</td>\n",
       "      <td>6.822618</td>\n",
       "      <td>0.096895</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>443</td>\n",
       "      <td>6.809431</td>\n",
       "      <td>6.809963</td>\n",
       "      <td>0.098730</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>444</td>\n",
       "      <td>6.806733</td>\n",
       "      <td>6.813656</td>\n",
       "      <td>0.097875</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>445</td>\n",
       "      <td>6.802291</td>\n",
       "      <td>6.806047</td>\n",
       "      <td>0.097635</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>446</td>\n",
       "      <td>6.815578</td>\n",
       "      <td>6.795990</td>\n",
       "      <td>0.098545</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>447</td>\n",
       "      <td>6.811253</td>\n",
       "      <td>6.807267</td>\n",
       "      <td>0.098625</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>448</td>\n",
       "      <td>6.800757</td>\n",
       "      <td>6.810567</td>\n",
       "      <td>0.098580</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>449</td>\n",
       "      <td>6.809044</td>\n",
       "      <td>6.813083</td>\n",
       "      <td>0.098885</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>450</td>\n",
       "      <td>6.811944</td>\n",
       "      <td>6.812553</td>\n",
       "      <td>0.098015</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>451</td>\n",
       "      <td>6.813627</td>\n",
       "      <td>6.815056</td>\n",
       "      <td>0.097415</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>452</td>\n",
       "      <td>6.814413</td>\n",
       "      <td>6.808554</td>\n",
       "      <td>0.098775</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>453</td>\n",
       "      <td>6.804325</td>\n",
       "      <td>6.810931</td>\n",
       "      <td>0.099060</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>454</td>\n",
       "      <td>6.807952</td>\n",
       "      <td>6.808098</td>\n",
       "      <td>0.098675</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>455</td>\n",
       "      <td>6.815145</td>\n",
       "      <td>6.819755</td>\n",
       "      <td>0.097690</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>456</td>\n",
       "      <td>6.810347</td>\n",
       "      <td>6.801141</td>\n",
       "      <td>0.097840</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>457</td>\n",
       "      <td>6.811150</td>\n",
       "      <td>6.806323</td>\n",
       "      <td>0.098265</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>458</td>\n",
       "      <td>6.803398</td>\n",
       "      <td>6.806114</td>\n",
       "      <td>0.098565</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>459</td>\n",
       "      <td>6.812668</td>\n",
       "      <td>6.813349</td>\n",
       "      <td>0.098945</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>460</td>\n",
       "      <td>6.808108</td>\n",
       "      <td>6.802604</td>\n",
       "      <td>0.099045</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>461</td>\n",
       "      <td>6.811118</td>\n",
       "      <td>6.809832</td>\n",
       "      <td>0.098580</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>462</td>\n",
       "      <td>6.805113</td>\n",
       "      <td>6.820524</td>\n",
       "      <td>0.097300</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>463</td>\n",
       "      <td>6.813332</td>\n",
       "      <td>6.815374</td>\n",
       "      <td>0.097825</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>464</td>\n",
       "      <td>6.807256</td>\n",
       "      <td>6.820538</td>\n",
       "      <td>0.097385</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>465</td>\n",
       "      <td>6.794599</td>\n",
       "      <td>6.821747</td>\n",
       "      <td>0.097365</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>466</td>\n",
       "      <td>6.808328</td>\n",
       "      <td>6.805315</td>\n",
       "      <td>0.097690</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>467</td>\n",
       "      <td>6.813903</td>\n",
       "      <td>6.807013</td>\n",
       "      <td>0.098650</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>468</td>\n",
       "      <td>6.806219</td>\n",
       "      <td>6.809781</td>\n",
       "      <td>0.099240</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>469</td>\n",
       "      <td>6.813953</td>\n",
       "      <td>6.798548</td>\n",
       "      <td>0.098860</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>470</td>\n",
       "      <td>6.793692</td>\n",
       "      <td>6.803854</td>\n",
       "      <td>0.099320</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>471</td>\n",
       "      <td>6.802911</td>\n",
       "      <td>6.811961</td>\n",
       "      <td>0.097800</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>472</td>\n",
       "      <td>6.818853</td>\n",
       "      <td>6.809989</td>\n",
       "      <td>0.098105</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>473</td>\n",
       "      <td>6.817290</td>\n",
       "      <td>6.817884</td>\n",
       "      <td>0.098335</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>474</td>\n",
       "      <td>6.802339</td>\n",
       "      <td>6.806864</td>\n",
       "      <td>0.098815</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>475</td>\n",
       "      <td>6.811930</td>\n",
       "      <td>6.805620</td>\n",
       "      <td>0.097260</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>476</td>\n",
       "      <td>6.808892</td>\n",
       "      <td>6.790969</td>\n",
       "      <td>0.098760</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>477</td>\n",
       "      <td>6.807367</td>\n",
       "      <td>6.819515</td>\n",
       "      <td>0.097235</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>478</td>\n",
       "      <td>6.804520</td>\n",
       "      <td>6.788754</td>\n",
       "      <td>0.099365</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>479</td>\n",
       "      <td>6.807824</td>\n",
       "      <td>6.805285</td>\n",
       "      <td>0.099030</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>480</td>\n",
       "      <td>6.807707</td>\n",
       "      <td>6.808624</td>\n",
       "      <td>0.097290</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>481</td>\n",
       "      <td>6.812397</td>\n",
       "      <td>6.809022</td>\n",
       "      <td>0.097955</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>482</td>\n",
       "      <td>6.818726</td>\n",
       "      <td>6.810791</td>\n",
       "      <td>0.098330</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>483</td>\n",
       "      <td>6.813272</td>\n",
       "      <td>6.810634</td>\n",
       "      <td>0.097355</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>484</td>\n",
       "      <td>6.807385</td>\n",
       "      <td>6.814864</td>\n",
       "      <td>0.098230</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>485</td>\n",
       "      <td>6.810207</td>\n",
       "      <td>6.811568</td>\n",
       "      <td>0.097795</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>486</td>\n",
       "      <td>6.807490</td>\n",
       "      <td>6.809682</td>\n",
       "      <td>0.097630</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>487</td>\n",
       "      <td>6.816746</td>\n",
       "      <td>6.813406</td>\n",
       "      <td>0.097435</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>488</td>\n",
       "      <td>6.809765</td>\n",
       "      <td>6.804999</td>\n",
       "      <td>0.098515</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>489</td>\n",
       "      <td>6.808847</td>\n",
       "      <td>6.822091</td>\n",
       "      <td>0.097770</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>490</td>\n",
       "      <td>6.809693</td>\n",
       "      <td>6.800409</td>\n",
       "      <td>0.097990</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>491</td>\n",
       "      <td>6.803259</td>\n",
       "      <td>6.802071</td>\n",
       "      <td>0.098120</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>492</td>\n",
       "      <td>6.810607</td>\n",
       "      <td>6.808106</td>\n",
       "      <td>0.097195</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>493</td>\n",
       "      <td>6.809562</td>\n",
       "      <td>6.820624</td>\n",
       "      <td>0.097820</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>494</td>\n",
       "      <td>6.807368</td>\n",
       "      <td>6.810383</td>\n",
       "      <td>0.097755</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>495</td>\n",
       "      <td>6.808889</td>\n",
       "      <td>6.795386</td>\n",
       "      <td>0.099375</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>496</td>\n",
       "      <td>6.824916</td>\n",
       "      <td>6.809061</td>\n",
       "      <td>0.097990</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>497</td>\n",
       "      <td>6.797005</td>\n",
       "      <td>6.802836</td>\n",
       "      <td>0.098310</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>498</td>\n",
       "      <td>6.806380</td>\n",
       "      <td>6.803247</td>\n",
       "      <td>0.098295</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>499</td>\n",
       "      <td>6.811753</td>\n",
       "      <td>6.805707</td>\n",
       "      <td>0.098390</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>500</td>\n",
       "      <td>6.815330</td>\n",
       "      <td>6.801330</td>\n",
       "      <td>0.098470</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>501</td>\n",
       "      <td>6.799644</td>\n",
       "      <td>6.808502</td>\n",
       "      <td>0.097105</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>502</td>\n",
       "      <td>6.813369</td>\n",
       "      <td>6.811327</td>\n",
       "      <td>0.098190</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>503</td>\n",
       "      <td>6.809512</td>\n",
       "      <td>6.811215</td>\n",
       "      <td>0.099040</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>504</td>\n",
       "      <td>6.804521</td>\n",
       "      <td>6.815688</td>\n",
       "      <td>0.098070</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>505</td>\n",
       "      <td>6.819638</td>\n",
       "      <td>6.796091</td>\n",
       "      <td>0.098930</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>506</td>\n",
       "      <td>6.811010</td>\n",
       "      <td>6.809465</td>\n",
       "      <td>0.097990</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>507</td>\n",
       "      <td>6.801710</td>\n",
       "      <td>6.810802</td>\n",
       "      <td>0.098065</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>508</td>\n",
       "      <td>6.819807</td>\n",
       "      <td>6.814836</td>\n",
       "      <td>0.097705</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>509</td>\n",
       "      <td>6.808402</td>\n",
       "      <td>6.806421</td>\n",
       "      <td>0.098395</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>510</td>\n",
       "      <td>6.807313</td>\n",
       "      <td>6.808554</td>\n",
       "      <td>0.098900</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>511</td>\n",
       "      <td>6.819277</td>\n",
       "      <td>6.812069</td>\n",
       "      <td>0.097295</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>512</td>\n",
       "      <td>6.817697</td>\n",
       "      <td>6.810831</td>\n",
       "      <td>0.097765</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>513</td>\n",
       "      <td>6.817294</td>\n",
       "      <td>6.802333</td>\n",
       "      <td>0.098200</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>514</td>\n",
       "      <td>6.815667</td>\n",
       "      <td>6.817045</td>\n",
       "      <td>0.098565</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>515</td>\n",
       "      <td>6.815946</td>\n",
       "      <td>6.804016</td>\n",
       "      <td>0.098525</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>516</td>\n",
       "      <td>6.819618</td>\n",
       "      <td>6.819160</td>\n",
       "      <td>0.098030</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>517</td>\n",
       "      <td>6.805892</td>\n",
       "      <td>6.790697</td>\n",
       "      <td>0.099310</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>518</td>\n",
       "      <td>6.814883</td>\n",
       "      <td>6.810747</td>\n",
       "      <td>0.097560</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>519</td>\n",
       "      <td>6.818979</td>\n",
       "      <td>6.818264</td>\n",
       "      <td>0.097790</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>520</td>\n",
       "      <td>6.796279</td>\n",
       "      <td>6.810830</td>\n",
       "      <td>0.097715</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>521</td>\n",
       "      <td>6.804465</td>\n",
       "      <td>6.793419</td>\n",
       "      <td>0.099330</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>522</td>\n",
       "      <td>6.793638</td>\n",
       "      <td>6.794652</td>\n",
       "      <td>0.099305</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>523</td>\n",
       "      <td>6.808948</td>\n",
       "      <td>6.806609</td>\n",
       "      <td>0.097595</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>524</td>\n",
       "      <td>6.813661</td>\n",
       "      <td>6.811327</td>\n",
       "      <td>0.098615</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>525</td>\n",
       "      <td>6.800080</td>\n",
       "      <td>6.818528</td>\n",
       "      <td>0.097820</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>526</td>\n",
       "      <td>6.810505</td>\n",
       "      <td>6.815781</td>\n",
       "      <td>0.098750</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>527</td>\n",
       "      <td>6.800414</td>\n",
       "      <td>6.805626</td>\n",
       "      <td>0.097970</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>528</td>\n",
       "      <td>6.798522</td>\n",
       "      <td>6.820520</td>\n",
       "      <td>0.098535</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>529</td>\n",
       "      <td>6.799551</td>\n",
       "      <td>6.807801</td>\n",
       "      <td>0.099215</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>530</td>\n",
       "      <td>6.815915</td>\n",
       "      <td>6.805402</td>\n",
       "      <td>0.098310</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>531</td>\n",
       "      <td>6.812191</td>\n",
       "      <td>6.809356</td>\n",
       "      <td>0.098010</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>532</td>\n",
       "      <td>6.812269</td>\n",
       "      <td>6.804363</td>\n",
       "      <td>0.097855</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>533</td>\n",
       "      <td>6.804077</td>\n",
       "      <td>6.809925</td>\n",
       "      <td>0.098555</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>534</td>\n",
       "      <td>6.803352</td>\n",
       "      <td>6.804760</td>\n",
       "      <td>0.098035</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>535</td>\n",
       "      <td>6.817367</td>\n",
       "      <td>6.815213</td>\n",
       "      <td>0.096590</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>536</td>\n",
       "      <td>6.799495</td>\n",
       "      <td>6.805979</td>\n",
       "      <td>0.098105</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>537</td>\n",
       "      <td>6.808605</td>\n",
       "      <td>6.808203</td>\n",
       "      <td>0.098210</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>538</td>\n",
       "      <td>6.805134</td>\n",
       "      <td>6.805132</td>\n",
       "      <td>0.097465</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>539</td>\n",
       "      <td>6.804650</td>\n",
       "      <td>6.815662</td>\n",
       "      <td>0.097960</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>540</td>\n",
       "      <td>6.805501</td>\n",
       "      <td>6.795059</td>\n",
       "      <td>0.097900</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>541</td>\n",
       "      <td>6.808284</td>\n",
       "      <td>6.805957</td>\n",
       "      <td>0.099250</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>542</td>\n",
       "      <td>6.810846</td>\n",
       "      <td>6.805721</td>\n",
       "      <td>0.098060</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>543</td>\n",
       "      <td>6.809015</td>\n",
       "      <td>6.808356</td>\n",
       "      <td>0.098940</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>544</td>\n",
       "      <td>6.804437</td>\n",
       "      <td>6.812273</td>\n",
       "      <td>0.097945</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>545</td>\n",
       "      <td>6.801792</td>\n",
       "      <td>6.795998</td>\n",
       "      <td>0.099355</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>546</td>\n",
       "      <td>6.806637</td>\n",
       "      <td>6.813626</td>\n",
       "      <td>0.097565</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>547</td>\n",
       "      <td>6.808916</td>\n",
       "      <td>6.812303</td>\n",
       "      <td>0.098775</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>548</td>\n",
       "      <td>6.808704</td>\n",
       "      <td>6.800213</td>\n",
       "      <td>0.098660</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>549</td>\n",
       "      <td>6.795227</td>\n",
       "      <td>6.799641</td>\n",
       "      <td>0.098690</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>550</td>\n",
       "      <td>6.814005</td>\n",
       "      <td>6.824627</td>\n",
       "      <td>0.097990</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>551</td>\n",
       "      <td>6.813973</td>\n",
       "      <td>6.813637</td>\n",
       "      <td>0.098855</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>552</td>\n",
       "      <td>6.803794</td>\n",
       "      <td>6.815194</td>\n",
       "      <td>0.097945</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>553</td>\n",
       "      <td>6.810681</td>\n",
       "      <td>6.803253</td>\n",
       "      <td>0.098375</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>554</td>\n",
       "      <td>6.800698</td>\n",
       "      <td>6.806385</td>\n",
       "      <td>0.098860</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>555</td>\n",
       "      <td>6.800874</td>\n",
       "      <td>6.818264</td>\n",
       "      <td>0.098225</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>556</td>\n",
       "      <td>6.815200</td>\n",
       "      <td>6.805577</td>\n",
       "      <td>0.098305</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>557</td>\n",
       "      <td>6.818302</td>\n",
       "      <td>6.813969</td>\n",
       "      <td>0.098910</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>558</td>\n",
       "      <td>6.810709</td>\n",
       "      <td>6.817672</td>\n",
       "      <td>0.097715</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>559</td>\n",
       "      <td>6.810051</td>\n",
       "      <td>6.808486</td>\n",
       "      <td>0.097240</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>560</td>\n",
       "      <td>6.813808</td>\n",
       "      <td>6.798949</td>\n",
       "      <td>0.098715</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>561</td>\n",
       "      <td>6.815383</td>\n",
       "      <td>6.798641</td>\n",
       "      <td>0.099405</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>562</td>\n",
       "      <td>6.808283</td>\n",
       "      <td>6.817555</td>\n",
       "      <td>0.096920</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>563</td>\n",
       "      <td>6.810425</td>\n",
       "      <td>6.809639</td>\n",
       "      <td>0.099455</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>564</td>\n",
       "      <td>6.808998</td>\n",
       "      <td>6.811986</td>\n",
       "      <td>0.098600</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>565</td>\n",
       "      <td>6.809171</td>\n",
       "      <td>6.817630</td>\n",
       "      <td>0.098325</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>566</td>\n",
       "      <td>6.815083</td>\n",
       "      <td>6.816865</td>\n",
       "      <td>0.099130</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>567</td>\n",
       "      <td>6.802867</td>\n",
       "      <td>6.815354</td>\n",
       "      <td>0.097610</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>568</td>\n",
       "      <td>6.802233</td>\n",
       "      <td>6.814486</td>\n",
       "      <td>0.098110</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>569</td>\n",
       "      <td>6.810732</td>\n",
       "      <td>6.801575</td>\n",
       "      <td>0.098565</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>570</td>\n",
       "      <td>6.797646</td>\n",
       "      <td>6.809129</td>\n",
       "      <td>0.098260</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>571</td>\n",
       "      <td>6.811992</td>\n",
       "      <td>6.812066</td>\n",
       "      <td>0.099700</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>572</td>\n",
       "      <td>6.804762</td>\n",
       "      <td>6.794423</td>\n",
       "      <td>0.098835</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>573</td>\n",
       "      <td>6.801354</td>\n",
       "      <td>6.817327</td>\n",
       "      <td>0.096625</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>574</td>\n",
       "      <td>6.813544</td>\n",
       "      <td>6.814940</td>\n",
       "      <td>0.097970</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>575</td>\n",
       "      <td>6.811256</td>\n",
       "      <td>6.814161</td>\n",
       "      <td>0.098460</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>576</td>\n",
       "      <td>6.810021</td>\n",
       "      <td>6.810412</td>\n",
       "      <td>0.098540</td>\n",
       "      <td>01:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>577</td>\n",
       "      <td>6.816337</td>\n",
       "      <td>6.801471</td>\n",
       "      <td>0.099020</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>578</td>\n",
       "      <td>6.811559</td>\n",
       "      <td>6.809603</td>\n",
       "      <td>0.098710</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>579</td>\n",
       "      <td>6.809797</td>\n",
       "      <td>6.804951</td>\n",
       "      <td>0.099955</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>580</td>\n",
       "      <td>6.814247</td>\n",
       "      <td>6.811171</td>\n",
       "      <td>0.098760</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>581</td>\n",
       "      <td>6.804180</td>\n",
       "      <td>6.819279</td>\n",
       "      <td>0.099480</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>582</td>\n",
       "      <td>6.810348</td>\n",
       "      <td>6.809199</td>\n",
       "      <td>0.097885</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>583</td>\n",
       "      <td>6.816344</td>\n",
       "      <td>6.807403</td>\n",
       "      <td>0.097650</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>584</td>\n",
       "      <td>6.810174</td>\n",
       "      <td>6.804088</td>\n",
       "      <td>0.097945</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>585</td>\n",
       "      <td>6.800735</td>\n",
       "      <td>6.816742</td>\n",
       "      <td>0.097685</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>586</td>\n",
       "      <td>6.807600</td>\n",
       "      <td>6.815356</td>\n",
       "      <td>0.098530</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>587</td>\n",
       "      <td>6.799652</td>\n",
       "      <td>6.805259</td>\n",
       "      <td>0.099015</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>588</td>\n",
       "      <td>6.812794</td>\n",
       "      <td>6.815500</td>\n",
       "      <td>0.098415</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>589</td>\n",
       "      <td>6.819873</td>\n",
       "      <td>6.802549</td>\n",
       "      <td>0.099180</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>590</td>\n",
       "      <td>6.819160</td>\n",
       "      <td>6.811099</td>\n",
       "      <td>0.098400</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>591</td>\n",
       "      <td>6.810794</td>\n",
       "      <td>6.818981</td>\n",
       "      <td>0.097815</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>592</td>\n",
       "      <td>6.810729</td>\n",
       "      <td>6.807594</td>\n",
       "      <td>0.098145</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>593</td>\n",
       "      <td>6.813726</td>\n",
       "      <td>6.803513</td>\n",
       "      <td>0.098075</td>\n",
       "      <td>01:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>594</td>\n",
       "      <td>6.810294</td>\n",
       "      <td>6.809366</td>\n",
       "      <td>0.098045</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>595</td>\n",
       "      <td>6.810260</td>\n",
       "      <td>6.813951</td>\n",
       "      <td>0.098450</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>596</td>\n",
       "      <td>6.798739</td>\n",
       "      <td>6.816114</td>\n",
       "      <td>0.098925</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>597</td>\n",
       "      <td>6.792528</td>\n",
       "      <td>6.818881</td>\n",
       "      <td>0.097885</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>598</td>\n",
       "      <td>6.794209</td>\n",
       "      <td>6.812174</td>\n",
       "      <td>0.099310</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>599</td>\n",
       "      <td>6.809770</td>\n",
       "      <td>6.812715</td>\n",
       "      <td>0.099040</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "NUM_EPOCHS = 600\n",
    "learn.fit(NUM_EPOCHS, lr=1e-3, cbs=SaveModelCallback(fname='text_embeddings', every_epoch=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>6.817412</td>\n",
       "      <td>6.807299</td>\n",
       "      <td>0.098670</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>6.805937</td>\n",
       "      <td>6.798475</td>\n",
       "      <td>0.098790</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>6.797688</td>\n",
       "      <td>6.796981</td>\n",
       "      <td>0.098265</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>6.808464</td>\n",
       "      <td>6.799053</td>\n",
       "      <td>0.097835</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>6.804440</td>\n",
       "      <td>6.792874</td>\n",
       "      <td>0.098925</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>6.799543</td>\n",
       "      <td>6.795477</td>\n",
       "      <td>0.098060</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>6.806483</td>\n",
       "      <td>6.790527</td>\n",
       "      <td>0.098715</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>6.802697</td>\n",
       "      <td>6.800794</td>\n",
       "      <td>0.098160</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>6.798816</td>\n",
       "      <td>6.782240</td>\n",
       "      <td>0.099700</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>6.788992</td>\n",
       "      <td>6.794506</td>\n",
       "      <td>0.099260</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>6.794882</td>\n",
       "      <td>6.792207</td>\n",
       "      <td>0.098755</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>6.797490</td>\n",
       "      <td>6.801632</td>\n",
       "      <td>0.098725</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>6.803877</td>\n",
       "      <td>6.795835</td>\n",
       "      <td>0.097860</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>6.795769</td>\n",
       "      <td>6.801101</td>\n",
       "      <td>0.098130</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>6.789007</td>\n",
       "      <td>6.797603</td>\n",
       "      <td>0.098765</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>6.803473</td>\n",
       "      <td>6.794757</td>\n",
       "      <td>0.099445</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>6.793154</td>\n",
       "      <td>6.801056</td>\n",
       "      <td>0.098560</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>6.802106</td>\n",
       "      <td>6.806484</td>\n",
       "      <td>0.097610</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>6.788180</td>\n",
       "      <td>6.787962</td>\n",
       "      <td>0.098950</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>6.792339</td>\n",
       "      <td>6.813460</td>\n",
       "      <td>0.097595</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>6.786837</td>\n",
       "      <td>6.795909</td>\n",
       "      <td>0.098405</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>6.786129</td>\n",
       "      <td>6.801437</td>\n",
       "      <td>0.097830</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>6.794202</td>\n",
       "      <td>6.816885</td>\n",
       "      <td>0.098390</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>6.800876</td>\n",
       "      <td>6.796738</td>\n",
       "      <td>0.099375</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>6.796177</td>\n",
       "      <td>6.795005</td>\n",
       "      <td>0.098915</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>6.802271</td>\n",
       "      <td>6.787264</td>\n",
       "      <td>0.099595</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26</td>\n",
       "      <td>6.785506</td>\n",
       "      <td>6.817342</td>\n",
       "      <td>0.097245</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27</td>\n",
       "      <td>6.801961</td>\n",
       "      <td>6.793834</td>\n",
       "      <td>0.099385</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>28</td>\n",
       "      <td>6.796973</td>\n",
       "      <td>6.799377</td>\n",
       "      <td>0.099060</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29</td>\n",
       "      <td>6.788856</td>\n",
       "      <td>6.805281</td>\n",
       "      <td>0.098275</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30</td>\n",
       "      <td>6.793480</td>\n",
       "      <td>6.780124</td>\n",
       "      <td>0.099895</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31</td>\n",
       "      <td>6.813818</td>\n",
       "      <td>6.792781</td>\n",
       "      <td>0.098625</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>32</td>\n",
       "      <td>6.818279</td>\n",
       "      <td>6.808770</td>\n",
       "      <td>0.099035</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>33</td>\n",
       "      <td>6.788306</td>\n",
       "      <td>6.802174</td>\n",
       "      <td>0.098515</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>34</td>\n",
       "      <td>6.803430</td>\n",
       "      <td>6.796421</td>\n",
       "      <td>0.099870</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>35</td>\n",
       "      <td>6.812659</td>\n",
       "      <td>6.791215</td>\n",
       "      <td>0.099590</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>36</td>\n",
       "      <td>6.801785</td>\n",
       "      <td>6.791967</td>\n",
       "      <td>0.099070</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>37</td>\n",
       "      <td>6.795094</td>\n",
       "      <td>6.803923</td>\n",
       "      <td>0.097510</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>38</td>\n",
       "      <td>6.793787</td>\n",
       "      <td>6.797164</td>\n",
       "      <td>0.099065</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39</td>\n",
       "      <td>6.795381</td>\n",
       "      <td>6.788576</td>\n",
       "      <td>0.099460</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>40</td>\n",
       "      <td>6.789899</td>\n",
       "      <td>6.793686</td>\n",
       "      <td>0.098815</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>41</td>\n",
       "      <td>6.795133</td>\n",
       "      <td>6.811826</td>\n",
       "      <td>0.097995</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>42</td>\n",
       "      <td>6.804105</td>\n",
       "      <td>6.805239</td>\n",
       "      <td>0.097500</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>43</td>\n",
       "      <td>6.798796</td>\n",
       "      <td>6.790854</td>\n",
       "      <td>0.098695</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>44</td>\n",
       "      <td>6.801117</td>\n",
       "      <td>6.797301</td>\n",
       "      <td>0.097805</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45</td>\n",
       "      <td>6.790199</td>\n",
       "      <td>6.796376</td>\n",
       "      <td>0.098090</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>46</td>\n",
       "      <td>6.804387</td>\n",
       "      <td>6.793540</td>\n",
       "      <td>0.100400</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>47</td>\n",
       "      <td>6.794992</td>\n",
       "      <td>6.806789</td>\n",
       "      <td>0.098505</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>48</td>\n",
       "      <td>6.791464</td>\n",
       "      <td>6.802407</td>\n",
       "      <td>0.097945</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>49</td>\n",
       "      <td>6.801528</td>\n",
       "      <td>6.800645</td>\n",
       "      <td>0.097845</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50</td>\n",
       "      <td>6.780560</td>\n",
       "      <td>6.796226</td>\n",
       "      <td>0.098030</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>51</td>\n",
       "      <td>6.800981</td>\n",
       "      <td>6.793346</td>\n",
       "      <td>0.098085</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>52</td>\n",
       "      <td>6.797218</td>\n",
       "      <td>6.801913</td>\n",
       "      <td>0.098915</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>53</td>\n",
       "      <td>6.789435</td>\n",
       "      <td>6.798126</td>\n",
       "      <td>0.098880</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>54</td>\n",
       "      <td>6.807672</td>\n",
       "      <td>6.796501</td>\n",
       "      <td>0.098710</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>55</td>\n",
       "      <td>6.792479</td>\n",
       "      <td>6.798482</td>\n",
       "      <td>0.098310</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>56</td>\n",
       "      <td>6.794161</td>\n",
       "      <td>6.795400</td>\n",
       "      <td>0.099555</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>57</td>\n",
       "      <td>6.799437</td>\n",
       "      <td>6.794256</td>\n",
       "      <td>0.099020</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>58</td>\n",
       "      <td>6.799314</td>\n",
       "      <td>6.808710</td>\n",
       "      <td>0.097540</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>59</td>\n",
       "      <td>6.804718</td>\n",
       "      <td>6.796445</td>\n",
       "      <td>0.099115</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>60</td>\n",
       "      <td>6.785124</td>\n",
       "      <td>6.810504</td>\n",
       "      <td>0.098155</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>61</td>\n",
       "      <td>6.793448</td>\n",
       "      <td>6.807094</td>\n",
       "      <td>0.098385</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>62</td>\n",
       "      <td>6.803284</td>\n",
       "      <td>6.800095</td>\n",
       "      <td>0.098640</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>63</td>\n",
       "      <td>6.789430</td>\n",
       "      <td>6.799635</td>\n",
       "      <td>0.099355</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>64</td>\n",
       "      <td>6.807635</td>\n",
       "      <td>6.799261</td>\n",
       "      <td>0.097955</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>65</td>\n",
       "      <td>6.810052</td>\n",
       "      <td>6.806047</td>\n",
       "      <td>0.099055</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>66</td>\n",
       "      <td>6.796291</td>\n",
       "      <td>6.800194</td>\n",
       "      <td>0.098575</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>67</td>\n",
       "      <td>6.792666</td>\n",
       "      <td>6.795680</td>\n",
       "      <td>0.099260</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>68</td>\n",
       "      <td>6.797915</td>\n",
       "      <td>6.794539</td>\n",
       "      <td>0.098515</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>69</td>\n",
       "      <td>6.799057</td>\n",
       "      <td>6.783728</td>\n",
       "      <td>0.099070</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>70</td>\n",
       "      <td>6.796355</td>\n",
       "      <td>6.806823</td>\n",
       "      <td>0.098460</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>71</td>\n",
       "      <td>6.786822</td>\n",
       "      <td>6.793172</td>\n",
       "      <td>0.098780</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>72</td>\n",
       "      <td>6.792992</td>\n",
       "      <td>6.788941</td>\n",
       "      <td>0.098460</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>73</td>\n",
       "      <td>6.805757</td>\n",
       "      <td>6.792372</td>\n",
       "      <td>0.097805</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>74</td>\n",
       "      <td>6.793343</td>\n",
       "      <td>6.789083</td>\n",
       "      <td>0.098935</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75</td>\n",
       "      <td>6.786746</td>\n",
       "      <td>6.807124</td>\n",
       "      <td>0.098210</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>76</td>\n",
       "      <td>6.798827</td>\n",
       "      <td>6.803010</td>\n",
       "      <td>0.098625</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>77</td>\n",
       "      <td>6.808709</td>\n",
       "      <td>6.805426</td>\n",
       "      <td>0.099310</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>78</td>\n",
       "      <td>6.797786</td>\n",
       "      <td>6.803269</td>\n",
       "      <td>0.098665</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>79</td>\n",
       "      <td>6.810936</td>\n",
       "      <td>6.801503</td>\n",
       "      <td>0.098795</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>80</td>\n",
       "      <td>6.811866</td>\n",
       "      <td>6.800615</td>\n",
       "      <td>0.099415</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>81</td>\n",
       "      <td>6.799452</td>\n",
       "      <td>6.807697</td>\n",
       "      <td>0.097670</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>82</td>\n",
       "      <td>6.801761</td>\n",
       "      <td>6.797446</td>\n",
       "      <td>0.099420</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>83</td>\n",
       "      <td>6.798753</td>\n",
       "      <td>6.798386</td>\n",
       "      <td>0.100780</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>84</td>\n",
       "      <td>6.800081</td>\n",
       "      <td>6.799119</td>\n",
       "      <td>0.098460</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>85</td>\n",
       "      <td>6.784244</td>\n",
       "      <td>6.790460</td>\n",
       "      <td>0.098825</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>86</td>\n",
       "      <td>6.804882</td>\n",
       "      <td>6.802968</td>\n",
       "      <td>0.098745</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>87</td>\n",
       "      <td>6.792927</td>\n",
       "      <td>6.785237</td>\n",
       "      <td>0.100145</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>88</td>\n",
       "      <td>6.801754</td>\n",
       "      <td>6.805685</td>\n",
       "      <td>0.098475</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>89</td>\n",
       "      <td>6.801069</td>\n",
       "      <td>6.790333</td>\n",
       "      <td>0.099480</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>90</td>\n",
       "      <td>6.792653</td>\n",
       "      <td>6.797169</td>\n",
       "      <td>0.098545</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>91</td>\n",
       "      <td>6.794592</td>\n",
       "      <td>6.788107</td>\n",
       "      <td>0.098320</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>92</td>\n",
       "      <td>6.803163</td>\n",
       "      <td>6.794190</td>\n",
       "      <td>0.099005</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>93</td>\n",
       "      <td>6.802270</td>\n",
       "      <td>6.808473</td>\n",
       "      <td>0.098610</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>94</td>\n",
       "      <td>6.793469</td>\n",
       "      <td>6.799941</td>\n",
       "      <td>0.098130</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>95</td>\n",
       "      <td>6.795025</td>\n",
       "      <td>6.801143</td>\n",
       "      <td>0.099500</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>96</td>\n",
       "      <td>6.783832</td>\n",
       "      <td>6.795430</td>\n",
       "      <td>0.098945</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>97</td>\n",
       "      <td>6.802711</td>\n",
       "      <td>6.800804</td>\n",
       "      <td>0.098055</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>98</td>\n",
       "      <td>6.806490</td>\n",
       "      <td>6.801483</td>\n",
       "      <td>0.098505</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>99</td>\n",
       "      <td>6.794538</td>\n",
       "      <td>6.786826</td>\n",
       "      <td>0.100095</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>100</td>\n",
       "      <td>6.802165</td>\n",
       "      <td>6.796352</td>\n",
       "      <td>0.099350</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>101</td>\n",
       "      <td>6.798120</td>\n",
       "      <td>6.798011</td>\n",
       "      <td>0.098585</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>102</td>\n",
       "      <td>6.796244</td>\n",
       "      <td>6.795000</td>\n",
       "      <td>0.098875</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>103</td>\n",
       "      <td>6.790847</td>\n",
       "      <td>6.788898</td>\n",
       "      <td>0.099005</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>104</td>\n",
       "      <td>6.792396</td>\n",
       "      <td>6.792241</td>\n",
       "      <td>0.099445</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>105</td>\n",
       "      <td>6.807541</td>\n",
       "      <td>6.807056</td>\n",
       "      <td>0.098855</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>106</td>\n",
       "      <td>6.799216</td>\n",
       "      <td>6.794063</td>\n",
       "      <td>0.098130</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>107</td>\n",
       "      <td>6.789007</td>\n",
       "      <td>6.802447</td>\n",
       "      <td>0.097765</td>\n",
       "      <td>01:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>108</td>\n",
       "      <td>6.794141</td>\n",
       "      <td>6.803143</td>\n",
       "      <td>0.098955</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>109</td>\n",
       "      <td>6.804801</td>\n",
       "      <td>6.811659</td>\n",
       "      <td>0.097360</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>110</td>\n",
       "      <td>6.785336</td>\n",
       "      <td>6.789041</td>\n",
       "      <td>0.099030</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>111</td>\n",
       "      <td>6.791317</td>\n",
       "      <td>6.788959</td>\n",
       "      <td>0.098880</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>112</td>\n",
       "      <td>6.814237</td>\n",
       "      <td>6.790664</td>\n",
       "      <td>0.098800</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>113</td>\n",
       "      <td>6.792987</td>\n",
       "      <td>6.793185</td>\n",
       "      <td>0.098130</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>114</td>\n",
       "      <td>6.800905</td>\n",
       "      <td>6.804642</td>\n",
       "      <td>0.098670</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>115</td>\n",
       "      <td>6.796189</td>\n",
       "      <td>6.798711</td>\n",
       "      <td>0.098575</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>116</td>\n",
       "      <td>6.794269</td>\n",
       "      <td>6.805776</td>\n",
       "      <td>0.097070</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>117</td>\n",
       "      <td>6.802590</td>\n",
       "      <td>6.807241</td>\n",
       "      <td>0.097435</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>118</td>\n",
       "      <td>6.779250</td>\n",
       "      <td>6.798500</td>\n",
       "      <td>0.098515</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>119</td>\n",
       "      <td>6.801053</td>\n",
       "      <td>6.808766</td>\n",
       "      <td>0.098280</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>120</td>\n",
       "      <td>6.807215</td>\n",
       "      <td>6.806367</td>\n",
       "      <td>0.097445</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>121</td>\n",
       "      <td>6.797635</td>\n",
       "      <td>6.794807</td>\n",
       "      <td>0.097760</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>122</td>\n",
       "      <td>6.792934</td>\n",
       "      <td>6.800779</td>\n",
       "      <td>0.098665</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>123</td>\n",
       "      <td>6.789599</td>\n",
       "      <td>6.804542</td>\n",
       "      <td>0.098985</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>124</td>\n",
       "      <td>6.807192</td>\n",
       "      <td>6.783184</td>\n",
       "      <td>0.100110</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>125</td>\n",
       "      <td>6.795372</td>\n",
       "      <td>6.791327</td>\n",
       "      <td>0.098865</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>126</td>\n",
       "      <td>6.809121</td>\n",
       "      <td>6.800460</td>\n",
       "      <td>0.097815</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>127</td>\n",
       "      <td>6.796276</td>\n",
       "      <td>6.798317</td>\n",
       "      <td>0.097770</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>128</td>\n",
       "      <td>6.809391</td>\n",
       "      <td>6.798683</td>\n",
       "      <td>0.099225</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>129</td>\n",
       "      <td>6.787748</td>\n",
       "      <td>6.799819</td>\n",
       "      <td>0.099045</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>130</td>\n",
       "      <td>6.804949</td>\n",
       "      <td>6.790595</td>\n",
       "      <td>0.099340</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>131</td>\n",
       "      <td>6.789387</td>\n",
       "      <td>6.797927</td>\n",
       "      <td>0.098830</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>132</td>\n",
       "      <td>6.801360</td>\n",
       "      <td>6.801777</td>\n",
       "      <td>0.098210</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>133</td>\n",
       "      <td>6.800078</td>\n",
       "      <td>6.804251</td>\n",
       "      <td>0.098100</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>134</td>\n",
       "      <td>6.806883</td>\n",
       "      <td>6.797526</td>\n",
       "      <td>0.099145</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>135</td>\n",
       "      <td>6.778225</td>\n",
       "      <td>6.810607</td>\n",
       "      <td>0.098540</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>136</td>\n",
       "      <td>6.803912</td>\n",
       "      <td>6.800595</td>\n",
       "      <td>0.098495</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>137</td>\n",
       "      <td>6.793621</td>\n",
       "      <td>6.788701</td>\n",
       "      <td>0.100285</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>138</td>\n",
       "      <td>6.777997</td>\n",
       "      <td>6.794562</td>\n",
       "      <td>0.098325</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>139</td>\n",
       "      <td>6.795267</td>\n",
       "      <td>6.796135</td>\n",
       "      <td>0.098935</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>140</td>\n",
       "      <td>6.799720</td>\n",
       "      <td>6.805729</td>\n",
       "      <td>0.098395</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>141</td>\n",
       "      <td>6.804048</td>\n",
       "      <td>6.791603</td>\n",
       "      <td>0.099280</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>142</td>\n",
       "      <td>6.807046</td>\n",
       "      <td>6.805420</td>\n",
       "      <td>0.097880</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>143</td>\n",
       "      <td>6.798851</td>\n",
       "      <td>6.803709</td>\n",
       "      <td>0.098595</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>144</td>\n",
       "      <td>6.804968</td>\n",
       "      <td>6.798189</td>\n",
       "      <td>0.099155</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>145</td>\n",
       "      <td>6.796307</td>\n",
       "      <td>6.791877</td>\n",
       "      <td>0.099540</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>146</td>\n",
       "      <td>6.812322</td>\n",
       "      <td>6.786984</td>\n",
       "      <td>0.099460</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>147</td>\n",
       "      <td>6.804013</td>\n",
       "      <td>6.800281</td>\n",
       "      <td>0.098830</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>148</td>\n",
       "      <td>6.802984</td>\n",
       "      <td>6.801310</td>\n",
       "      <td>0.098120</td>\n",
       "      <td>01:30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>149</td>\n",
       "      <td>6.787704</td>\n",
       "      <td>6.792910</td>\n",
       "      <td>0.097790</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>150</td>\n",
       "      <td>6.800815</td>\n",
       "      <td>6.796520</td>\n",
       "      <td>0.099665</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>151</td>\n",
       "      <td>6.799809</td>\n",
       "      <td>6.784398</td>\n",
       "      <td>0.098990</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>152</td>\n",
       "      <td>6.809891</td>\n",
       "      <td>6.794212</td>\n",
       "      <td>0.098110</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>153</td>\n",
       "      <td>6.795274</td>\n",
       "      <td>6.800735</td>\n",
       "      <td>0.098335</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>154</td>\n",
       "      <td>6.796179</td>\n",
       "      <td>6.794436</td>\n",
       "      <td>0.098430</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>155</td>\n",
       "      <td>6.798256</td>\n",
       "      <td>6.815730</td>\n",
       "      <td>0.098455</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>156</td>\n",
       "      <td>6.786973</td>\n",
       "      <td>6.787639</td>\n",
       "      <td>0.099545</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>157</td>\n",
       "      <td>6.795186</td>\n",
       "      <td>6.806208</td>\n",
       "      <td>0.099160</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>158</td>\n",
       "      <td>6.791251</td>\n",
       "      <td>6.790786</td>\n",
       "      <td>0.099470</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>159</td>\n",
       "      <td>6.793869</td>\n",
       "      <td>6.796741</td>\n",
       "      <td>0.099155</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>160</td>\n",
       "      <td>6.806776</td>\n",
       "      <td>6.801435</td>\n",
       "      <td>0.099355</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>161</td>\n",
       "      <td>6.799575</td>\n",
       "      <td>6.809261</td>\n",
       "      <td>0.098925</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>162</td>\n",
       "      <td>6.787155</td>\n",
       "      <td>6.802175</td>\n",
       "      <td>0.099240</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>163</td>\n",
       "      <td>6.802415</td>\n",
       "      <td>6.810647</td>\n",
       "      <td>0.097615</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>164</td>\n",
       "      <td>6.811195</td>\n",
       "      <td>6.809263</td>\n",
       "      <td>0.097335</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>165</td>\n",
       "      <td>6.801252</td>\n",
       "      <td>6.788671</td>\n",
       "      <td>0.099395</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>166</td>\n",
       "      <td>6.798369</td>\n",
       "      <td>6.801425</td>\n",
       "      <td>0.097645</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>167</td>\n",
       "      <td>6.799872</td>\n",
       "      <td>6.806138</td>\n",
       "      <td>0.098320</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>168</td>\n",
       "      <td>6.805387</td>\n",
       "      <td>6.790277</td>\n",
       "      <td>0.099215</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>169</td>\n",
       "      <td>6.810438</td>\n",
       "      <td>6.801787</td>\n",
       "      <td>0.098035</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>170</td>\n",
       "      <td>6.806175</td>\n",
       "      <td>6.802965</td>\n",
       "      <td>0.098810</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>171</td>\n",
       "      <td>6.803035</td>\n",
       "      <td>6.807139</td>\n",
       "      <td>0.098730</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>172</td>\n",
       "      <td>6.797230</td>\n",
       "      <td>6.806274</td>\n",
       "      <td>0.097995</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>173</td>\n",
       "      <td>6.794432</td>\n",
       "      <td>6.803686</td>\n",
       "      <td>0.098500</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>174</td>\n",
       "      <td>6.795139</td>\n",
       "      <td>6.796752</td>\n",
       "      <td>0.099620</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>175</td>\n",
       "      <td>6.795223</td>\n",
       "      <td>6.802223</td>\n",
       "      <td>0.098360</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>176</td>\n",
       "      <td>6.793651</td>\n",
       "      <td>6.805779</td>\n",
       "      <td>0.098115</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>177</td>\n",
       "      <td>6.789386</td>\n",
       "      <td>6.795182</td>\n",
       "      <td>0.098905</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>178</td>\n",
       "      <td>6.802290</td>\n",
       "      <td>6.799786</td>\n",
       "      <td>0.099655</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>179</td>\n",
       "      <td>6.792135</td>\n",
       "      <td>6.800791</td>\n",
       "      <td>0.098345</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>180</td>\n",
       "      <td>6.800810</td>\n",
       "      <td>6.804661</td>\n",
       "      <td>0.098460</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>181</td>\n",
       "      <td>6.801787</td>\n",
       "      <td>6.795028</td>\n",
       "      <td>0.099195</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>182</td>\n",
       "      <td>6.791824</td>\n",
       "      <td>6.796244</td>\n",
       "      <td>0.098340</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>183</td>\n",
       "      <td>6.804876</td>\n",
       "      <td>6.785641</td>\n",
       "      <td>0.100530</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>184</td>\n",
       "      <td>6.794941</td>\n",
       "      <td>6.799807</td>\n",
       "      <td>0.099285</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>185</td>\n",
       "      <td>6.793266</td>\n",
       "      <td>6.803009</td>\n",
       "      <td>0.099940</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>186</td>\n",
       "      <td>6.793723</td>\n",
       "      <td>6.795399</td>\n",
       "      <td>0.099535</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>187</td>\n",
       "      <td>6.791589</td>\n",
       "      <td>6.814262</td>\n",
       "      <td>0.097470</td>\n",
       "      <td>01:28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>188</td>\n",
       "      <td>6.806554</td>\n",
       "      <td>6.795115</td>\n",
       "      <td>0.099135</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>189</td>\n",
       "      <td>6.806992</td>\n",
       "      <td>6.814249</td>\n",
       "      <td>0.098950</td>\n",
       "      <td>01:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>190</td>\n",
       "      <td>6.810267</td>\n",
       "      <td>6.796350</td>\n",
       "      <td>0.099300</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>191</td>\n",
       "      <td>6.812583</td>\n",
       "      <td>6.788085</td>\n",
       "      <td>0.098510</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>192</td>\n",
       "      <td>6.799792</td>\n",
       "      <td>6.796726</td>\n",
       "      <td>0.099290</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>193</td>\n",
       "      <td>6.803334</td>\n",
       "      <td>6.795894</td>\n",
       "      <td>0.099450</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>194</td>\n",
       "      <td>6.804103</td>\n",
       "      <td>6.797521</td>\n",
       "      <td>0.098105</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>195</td>\n",
       "      <td>6.799886</td>\n",
       "      <td>6.793175</td>\n",
       "      <td>0.099405</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>196</td>\n",
       "      <td>6.821154</td>\n",
       "      <td>6.791363</td>\n",
       "      <td>0.098945</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>197</td>\n",
       "      <td>6.796500</td>\n",
       "      <td>6.810588</td>\n",
       "      <td>0.097365</td>\n",
       "      <td>01:26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>198</td>\n",
       "      <td>6.805688</td>\n",
       "      <td>6.799293</td>\n",
       "      <td>0.098645</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>199</td>\n",
       "      <td>6.789433</td>\n",
       "      <td>6.796141</td>\n",
       "      <td>0.098395</td>\n",
       "      <td>01:27</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "NUM_EPOCHS = 200\n",
    "learn.fit(NUM_EPOCHS, lr=1e-4, cbs=SaveModelCallback(fname='text_embeddings_2', every_epoch=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evalute embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "from utils import Embeddings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "embeddings = learn.model.embeddings.weight.cpu().detach().numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "e = Embeddings(\n",
    "    embeddings,\n",
    "    vocab\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fast: ['fast', 'slow', 'paced', 'bouncy', 'luxurious']\n",
      "lost: ['lost', 'losing', 'regained', 'froze', 'missed']\n",
      "small: ['small', 'large', 'smaller', 'larger', 'huge']\n",
      "true: ['true', 'surprising', 'ultimate', 'essence', 'genuine']\n",
      "crazy: ['crazy', 'loud', 'stupid', 'hopeful', 'lovely']\n",
      "slow: ['slow', 'pace', 'fast', 'tame', 'paced']\n"
     ]
    }
   ],
   "source": [
    "for w in ['fast', 'lost', 'small', 'true', 'crazy', 'slow']:\n",
    "    print(f'{w}: {e.nn_words_to(e[w])}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluating embeddings using [word-embeddings-benchmarks](https://github.com/kudkudak/word-embeddings-benchmarks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "from six import iteritems\n",
    "from web.datasets.similarity import fetch_MEN, fetch_WS353, fetch_SimLex999\n",
    "from web.embeddings import fetch_GloVe\n",
    "from web.evaluate import evaluate_similarity\n",
    "from web.embedding import Embedding, Vocabulary\n",
    "from gensim.models import Word2Vec\n",
    "from gensim.models import KeyedVectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "tasks = {\n",
    "    \"MEN\": fetch_MEN(),\n",
    "    \"WS353\": fetch_WS353(),\n",
    "    \"SIMLEX999\": fetch_SimLex999()\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn.load('text_embeddings_599')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "our_embeddings = Embedding(\n",
    "    Vocabulary(vocab),\n",
    "    embeddings\n",
    ")\n",
    "\n",
    "speech2vec = KeyedVectors.load_word2vec_format('../speech2vec-pretrained-vectors/word2vec/50.vec', binary=False) \n",
    "speech2vec_embeddings = Embedding(Vocabulary(list(speech2vec.vocab.keys())), speech2vec.vectors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Missing 341 words. Will replace them with mean vector\n",
      "Missing 42 words. Will replace them with mean vector\n",
      "Missing 22 words. Will replace them with mean vector\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Spearman correlation of scores on MEN 0.41127243421399146\n",
      "Spearman correlation of scores on WS353 0.4865372320809481\n",
      "Spearman correlation of scores on SIMLEX999 0.19336495650448224\n"
     ]
    }
   ],
   "source": [
    "for name, data in iteritems(tasks):\n",
    "    print(\"Spearman correlation of scores on {} {}\".format(name, evaluate_similarity(our_embeddings, data.X, data.y)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<fastai.learner.Learner at 0x7f6ebd842290>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "learn.load('text_embeddings_2_199')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "our_embeddings = Embedding(\n",
    "    Vocabulary(vocab),\n",
    "    embeddings\n",
    ")\n",
    "\n",
    "speech2vec = KeyedVectors.load_word2vec_format('../speech2vec-pretrained-vectors/word2vec/50.vec', binary=False) \n",
    "speech2vec_embeddings = Embedding(Vocabulary(list(speech2vec.vocab.keys())), speech2vec.vectors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Missing 341 words. Will replace them with mean vector\n",
      "/opt/conda/lib/python3.7/site-packages/web-0.0.1-py3.7.egg/web/evaluate.py:336: FutureWarning: arrays to stack must be passed as a \"sequence\" type such as list or tuple. Support for non-sequence iterables such as generators is deprecated as of NumPy 1.16 and will raise an error in the future.\n",
      "  A = np.vstack(w.get(word, mean_vector) for word in X[:, 0])\n",
      "/opt/conda/lib/python3.7/site-packages/web-0.0.1-py3.7.egg/web/evaluate.py:337: FutureWarning: arrays to stack must be passed as a \"sequence\" type such as list or tuple. Support for non-sequence iterables such as generators is deprecated as of NumPy 1.16 and will raise an error in the future.\n",
      "  B = np.vstack(w.get(word, mean_vector) for word in X[:, 1])\n",
      "Missing 42 words. Will replace them with mean vector\n",
      "Missing 22 words. Will replace them with mean vector\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Spearman correlation of scores on MEN 0.4121189448279002\n",
      "Spearman correlation of scores on WS353 0.4836479209052387\n",
      "Spearman correlation of scores on SIMLEX999 0.20166613840308148\n"
     ]
    }
   ],
   "source": [
    "for name, data in iteritems(tasks):\n",
    "    print(\"Spearman correlation of scores on {} {}\".format(name, evaluate_similarity(our_embeddings, data.X, data.y)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Missing 392 words. Will replace them with mean vector\n",
      "Missing 61 words. Will replace them with mean vector\n",
      "Missing 24 words. Will replace them with mean vector\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Spearman correlation of scores on MEN 0.6056592803599269\n",
      "Spearman correlation of scores on WS353 0.43349390636024643\n",
      "Spearman correlation of scores on SIMLEX999 0.25938770901422736\n"
     ]
    }
   ],
   "source": [
    "for name, data in iteritems(tasks):\n",
    "    print(\"Spearman correlation of scores on {} {}\".format(name, evaluate_similarity(speech2vec_embeddings, data.X, data.y)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loss decrease and improvements on semantic tasks as training progresses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "\n",
    "val_losses, accuracies, task_perf = [], [], []\n",
    "for i in range(600):\n",
    "    learn.load(f'text_embeddings_{i}')\n",
    "    loss, accuracy = learn.validate()\n",
    "    val_losses.append(loss)\n",
    "    accuracies.append(accuracy)\n",
    "    \n",
    "    embeddings = learn.model.embeddings.weight.cpu().detach().numpy()\n",
    "    our_embeddings = Embedding(\n",
    "        Vocabulary([w.lower() for w in vocab]),\n",
    "        embeddings\n",
    "    )\n",
    "\n",
    "    task_perf.append([evaluate_similarity(our_embeddings, data.X, data.y) for name, data in iteritems(tasks)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "men, ws353, simlex999 = list(zip(*task_perf))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots()\n",
    "\n",
    "ax1.plot(val_losses, label='val loss')\n",
    "\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(men, label='MEN', c='g')\n",
    "ax2.plot(ws353, label='WS353', c='m')\n",
    "ax2.plot(simlex999, label='SIMLEX999', c='y')\n",
    "\n",
    "ax1.legend(loc=[0.07, 0.9])\n",
    "ax2.legend(loc=[0.7, 0.15])\n",
    "\n",
    "ax1.set_xlabel('epochs');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "\n",
    "val_losses, accuracies, task_perf = [], [], []\n",
    "for i in range(200):\n",
    "    learn.load(f'text_embeddings_2_{i}')\n",
    "    loss, accuracy = learn.validate()\n",
    "    val_losses.append(loss)\n",
    "    accuracies.append(accuracy)\n",
    "    \n",
    "    embeddings = learn.model.embeddings.weight.cpu().detach().numpy()\n",
    "    our_embeddings = Embedding(\n",
    "        Vocabulary([w.lower() for w in vocab]),\n",
    "        embeddings\n",
    "    )\n",
    "\n",
    "    task_perf.append([evaluate_similarity(our_embeddings, data.X, data.y) for name, data in iteritems(tasks)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "men, ws353, simlex999 = list(zip(*task_perf))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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tU6x931rSF7hKRbtgU3i2gFNwyO3NUTxcxCk6qKJi+M5hck/nSF+cJnl2kszWDIWDBVa9cxWr//tqcKBwoEDvlb1NWYddsDl+23EO/f0hnJzDC7/5QpSlyO3OEVvtsj4n59B9RTd21qY4UCSxwWVdylGYPaYfN+t5ZY9v6N/4vx9g9SH4E2clQzcNEVsdI3VeiswjGexJ1ypGOiL0vqoXa9wikogQ3xhn+ZuW0/ca1907H8hsyzBx/wSl4RLHbztO4dlKnlry7CQ9V/Sw6h2r6H5p5XmdkuO2b00co6PeiOT25Dh6y1EKhwqc+PYJItEIqRemmHxoku5f6Wb9n62nPFLGGrPouKCD3l/tnbfn0wgNz0ngZGI8pWMlDn/2MEbSoOPCDjrO70AiQiTpdqDaGM98QjmKqSemKDxXQFmK2OoY6YvSmJ0mF1xwARu7NvIvv/cv9F3VR7Yry+te9zrK5TIXX3wxDz74IN///vfZtGlTyxhPM3HBLbfcwj//8z8TjUZJp9N84xvfYHJykmuvvRbHcd1p//iP/8jVV19dd+/az8kpOxQPF0meEW5XsdBwig5HvniEkbtGyO/Pk74wzep3rWbZby6b8b2UrVCWIhKfG4Z41ecewFGK+z74Ck589wTH/99xcrtzpC9N0/2yboxug95X91Yt1k41lKPI78tTHCySeTTDxAMTjD8wjp2xWfHmFYzcPYI9UaGOYgqdL+nkrBvOIn1RmtF7Rzly/RFG7xlFTCG+Pk764jRbrt9CYn2CY/92jF1/sKuKfQLE18VZ+baVmL0m5WNlVl+32vXMPJUl9YIURtqgfKKM0WVgJGbHlkLDcxI4leKCEI0Rfk4hZoPXfOZ+bKX48Z+9cqGbMiNYkxbPvOcZjt96nGVvXMbyNy5H4uIyzl0us7Ezrmty4v4JYqtirPnjNa7xWFXvCszvz1MeLRPtj2J2mYz9eIyjXz/K6L2jrjfGcGPREhecrAPiukZVSXHhDy6k79f6ZvUci83whH6OECFCzDtspXCcpbPI1TC7TM77v+dx1g1nEe2pZ2Nr/ngNT175JNntWbb8ny2suW4NkVhzlpg8I1nlHVjxOytY8TsrKA2XQEBZisOfPIxTcN2Z+WdcFV58fZzUWal5ecaFQGh4QoQIMe+wHYW9BA2PRiOjA5BYl+Cyxy/DKTsnFa+MLa/E3LZ8Zsus77NUEBqeECFCzDuWuuGZDpF4ZM5iYacLwk8rgKUU71oIhJ9PiNnCcRTW89TwhJg5QsPjIZFIMDIyEk6uTaD340kkTr5aQYjTD7Z6/jKeEDNH6GrzsG7dOgYGBhgeHl7opixa6B1IQ4SYKWxHYdlO6xNDnBZoy/CISA9wE3A+bvrlO5RSDwde7wb+L7DBu+enlFJf9177GvCbwHGl1PmBaz4O/BGgZ3q9JfaCIBqNhjtrhggxT7AdRUh4Qmi062q7HrhHKXUOcBGwq+b19wJPe7vTvRL4tLc3A8DNwFVN7vtZpdTF3s+CGZ0QIULML2xHYTkh4wnhoqXhEZEu4ArgqwBKqZJSarzmNAV0ehsFpYFRwPLOf8D7P0SIEKcpHEUY4wnhox3GcwauO+zrIvKEiNwkIrUZsDcA5+JueboD+IBSqp3lzftE5EkR+ZqI9M6o5SFChFgysBwnVLWF8NGO4TGBS4EblVKXAFngIzXnXAlsA9YAFwM3eExpOtwInOmdPwR8utFJInKdiDwqIo9altVGc0OECLHY4DigFEuyekGIuUc7hmcAGFBKbfX+vx3XEAVxLXCncrEPOACcM91NlVLHlFK2x4y+Alze5LwvK6UuU0pdZpqhCC9EiKUI20tTCFlPCGjD8CiljgKHReRs79CrgadrTnvOO46IrATOBvZPd18RWR349w3AU222OUSIEEsIKpDD44R5ciFoP4/n/cCtnlJtP3CtiLwb/H25/w64WUR24G719WGl1AkAEfk3XKXbMhEZAP5GKfVV4JMicjGuMOEg8K45e6oQIUIsGgRJTsh4QkCbhkcptQ24rObwlwKvDwKvbXLtW5sc/4M22xgiRIgljKCazbZDwxMiLJkTIkSIeUbQvRbm8oSA0PCECBFinlHFeEJXWwhCwxMiRIh5RjCuE8Z4QkBoeEKECDHPcELGs+ghIleJyB4R2ScitXmawfNeLCK2iLwpcOygiOwQkW0i8mg77xcmxoQIsQjxT/fsRoAPXTVtOtySgK1Cw7OYISIG8AXgNbh5m4+IyF1KqacbnPdPwL0NbvMqrWRuB6HhCRFiEWLr/hEiIgvdjDmBE7raFjsuB/YppfYDiMhtwDXU52u+H7gDePHJvmHoagsRYhHCchRF6/mhALMWsautZDmcmCoudDMWGmuBw4H/B7xjPkRkLW6i/5eohwLuE5HHROS6dt4wNDwhQixClG1F0bIXuhlzAttZvHLqbzx8kCs/+8BCN+NUwNQ1L72foIFoRK1rVwifwy0M0KhT/pJS6lLgauC9InJFy8a03ewQIUKcMli2Q+l5smOns4hjPCPZEiPZErajMCLPD9dmE1hKqdoiABoDwPrA/+twdxoI4jLgNnfnG5YBvy4illLqW14BAZRSx0XkP3Fdd9Na85DxPE8xnCny1Z8dQIW1sZYkLEdRLC89wzNVtOqY2mLO49HtKT9PjPws8Qhwlohs9sqivQW4K3iCUmqzUmqTUmoTbqHo9yilviUiHSLSCeBtl/Na2qi7GRqeWSJXsvjzb25naCK/0E1piHt3HuXvvvs0xzOnvf96SaJkOUvS1fb7N23lU/fuqTq2mA2P5ZXweb7E02YDpZQFvA9XrbYL+A+l1E4RebeuyTkNVgI/E5HtwC+A7yml7mn1nqGrbZb4+f4Rbn9sgMs29vKWyzcsdHPqYHkruNN8JbdkYTnOkpwMhzNFjk5WL3ZstXhVbbYXcyotwc96LqGUuhu4u+ZYIyEBSqm3B/7eD1w00/cLGc8sse05d/fvwYnCArekMfQAt8KijEsSlr00VW22o/xFT/BYo78XA/Q4eb7E05YKQsMzS2wbmABgcHxxutr0AF9sKqIQ7aFsOw0n8cUOW6k6lh3sgouP8XiGZwka+aWM0PDMAkopth92Gc9ijfFYftB0cQ30EO2hvERjD46j6vpccPFjL7KFkBWKCxYEoeGZBQ6O5JjIlzEiwuD44nS16ZXcYnNthGgPerJeaoanIeOpklOf6hZNj5DxLAxCwzMLaLbz8jP7GRzPL0rJciguWLpQSgUYz9JStjmOqosrBrvgYmU8S83AL3W0ZXhEpEdEbheR3SKyS0ReVvN6t4h8R0S2i8hOEbk28NrXROS4iDxVc02fiPxARPZ6v3vn5pHmH9sOj5OMGrziBcspWg6j2dJCN6kOvrggZDxLDkGWutRyeRxVH6ivrlywuPpjqGpbGLTLeK4H7lFKnYMrndtV8/p7gaeVUhcBrwQ+7SUiAdwMXNXgnh8BfqSUOgv4kff/ksChkSxnLO9gXW8KgKEmyjalFK/97P3c8djAqWweECbGLWUEJ+elthK3HVUnaFnUqjY7HCcLgZaGR0S6gCuArwIopUpKqfGa0xTQKW49hTQwClje+Q94/9fiGuAW7+9bgNfP5gEWAkXLIRE1WNOTAOBIE2Vb2VY8c2yKAyeyp7J5QGXyWmwDPURrBBnDUnO12UpRtlTdMY125P2HR3OnTM0XxngWBu0wnjOAYeDrIvKEiNzklUYI4gbgXNz6PjuADyilWn2TK5VSQwDe7xUza/rCoWQ5xIwIa3qSAAw1MTx60rAXIAZkh3k8SxbB72ypMR6lFGWnVk7dPuMpWjav/ewDfOPhQ/PSvlqEeTwLg3YMjwlcCtyolLoEyFLvFrsS2AasAS4GbvCY0klDRK7TFVUty5qLW540yrZDzIzQ3xEjZkaaJpHqScNZANah3R2hC2HpIbjaX2oxHtupV7VVudpaLMIKJYd82eax58bmpX21CBnPwqAdwzMADCiltnr/345riIK4FrhTudgHHABabZ14TERWA3i/jzc6SSn1ZaXUZUqpy0xzcVT4KVqu4RER1nQnmiaR+oZnIRlP6GpbcihXxXiWjqtNKYWj6lm2NQNxgWZLTw9Ozn0DG8AKxQULgpaGRyl1FDgsImd7h15N/c50z3nHEZGVwNnA/ha3vgv4Q+/vPwS+3WabFxwl23W1AazuTjY1PIWy52qbwz790LMn/PtOBz34Q8Oz9FDFeJbQhKi72rR5PC0Gg+63B05kmSrOv4fDDl1tC4J2VW3vB24VkSdxXWn/u6Zy6d8BLxeRHbgKtQ/r/bdF5N+Ah4GzRWRARN7pXfMJ4DUishd3r+9PzM0jzT9KHuMBWNEV58RUYzm1dpPMFeMZzhT53a9s5e4dQy3PrcR4wgG11FBeouIC3c9rKxfMRE4dfPZdQ/PPeqzQ1bYgaMt3pZTahrsRUBBfCrw+iLsPQ6Nr39rk+AgeS1pq0OICgLgZadpp9aQxV4ZHM51cqQ3GE4oLliyCE/dSivE0W+zMZCO4oGHaeWSCF2/qm8MW1iNkPAuDsHIBbiWC4Sb71hTKNrc8dLBqwGhxAUDMjDTttAVv0pgrSbO+TzuGzM/jWWSZ4iFaY6mq2poxnuDzzITxPHUK4jy6bSHjObUIDQ/wzlse4aafNg5J/WzvCf7mrp3sODLhHwu62qLGqWM8WhHUDovRQdOQ8Sw9BBcLS8nVFlzsBMtIBZVsrRSe2vBEBHaeAsMTJlovDELDg7tdbzP3VaZYBiAfeL1kO0SN1oxHr1bnivE4M2A8obhg6cJaoq423dWUqu7zzgxiPPrZNy/r4NnjU3PfyNr3C1VtC4LT1vD8bO8JTky57jXLVk3zC6aKrsHx2YtX9l0znrjHeBoVCtUxmbma+3Ub2zFkViguWLIoL1VVWxMDY88oxuM+b19HjJK3J1HV67bDvuOZuWhuVXtO5efsKIfJ4qmRiy9WLI7EmFMM21G8/eu/4P2/ehZ/8uotWI5q6gIYzU5RlqMcGH+W9aMZipaNJcdwWAOAGREU2hgJAJliBhGpGJ4ZWJ7J4iTZkltiZ//YfsYL4ySjSZJmkkMjefKR7dx14D62T5W5fO3lbOzeSH+qn+54N3tH93Jo/BCbezeTK7tS1EYrzInCBGOFMSYKE2TLWZJmktWdq1nZsRK36lE13Gz0MvlynryVJ1fOkS97v608EYlw/orz6Un0tP2c84VjkwVWdiUWuhknhZNRtdmOze4Tuzk0cYiVHStxlMNYYYyx/BhjhTHy5Tzru9eTNJOMFcbYN7qPwcwgU6UpNnZvZFPPJpZ3LGd5ajnZcpYnhp7g6NRRRvIjjBXGiEiEnkQP5/Sfw3BumEMTh4hGoixLLaMvsZqMMYip1jKcewmrO3swxPD7v80Eeyce4bHBKRzlMJgZZDAzyHhhHEc5DOeG2Xn0EEdjz/LAWISJmM2rv/Ep1nevY0vvFnqTvewdsrn90VG+8vtXcOHqs1nftZ6R/Aj7RvdxeOIwMSNG0S4ykhshGU1SsksMZYaIGlE6oh10xDroiHYgIkwUJjhWPkYhkmTn2AG+s2c/MSNG3IwTM9xSk8ezxzk2dYzBzCB3PPkIjkyxrjeBrWxsx/Z/d8Y72dK7hS19W1jXtY64Gefg+EFO5E6QiqYYy48xNDXEwOQATxx9gvHCOMtSy+hJ9JAwE2zu2cyZvWdyVv9ZXLTyIi5adRHpWBqAkl1iODtMX7KPZDQ5R71sYSGLsaR/M3R0dKhsduZ1z2585Ea+88x3yJVz3mRZZM/RKdZ1L+Oy9Zu458kc6/thw3KLdCxNtpT1B8VwbrjpfVenVzOam6Bol9jUs55ULMlEYYIjmSMACAIqSUe0k7OXr+OKjVfwwuUvJBlN8uzos+wZ2cPhycNEJMJYfoxDE4cYL9SWwauHIKRjaTKl6Vd+hrOcjjh0JeOkY2k6oh0MTQ0xmBlseH53vJu4GUcphYjQm+hFRDg4fpCC1XrfobgRR0QQhDN6z+AVG19B3spjORapaIrJ4iSj+VHGCmOM5kcRhI09G+mMdfoDPm64gz5uxP0JIG7EyZQyHM8e53j2OAkzwZrONazpXIMhBtlyls5YJ6Vykk/dc4h3XNFNXxWyIn8AACAASURBVFroS/bRn+qnN9FLKpqi7JTJlrLkrTxxI05nvJPOWCfpWNr/OziwlVKM5EcYyY0wmh9lJD/CUGaIqdIURbvInpE9ZEtZVqdXs7pztT+Zg2sARvOjGBGD3kQvG7o30JvspTPWyerO1azpXENnrJOByQEOTRxiODtMV7yLbDnLT/bu4f9tPUwpcoBY6mkScQszYtKb6KUn0UNvspeueBeTxUmGs8OM5kfpS/ZhRkweH3q8Zb+o7UsrOlaQiqY4PHkYy6nPnemKd9Gf7Kcv2YdCcTx7nIHJAZJmkjN6z8BWNsemjvnP3ug9lDJAps/L6Yh20BtfwfBEkmXpDk5M5bl4fSdHpg4zMNm40G7ciFO0GwuD5hKCEJeVdJi9nLWyG0MMjIjh/x4vjLNvdF/T8RszYn4/uXDFhWzu3cz+sf1MlabIlXPsH9vPs2PPkivn/Pdb17WOqdKU/7ne9/v38ZozXzO79ovklFK1pc4WDKeF4fnEzz7BnbvuJBlNkoqmcByDn+49zvJum1g0w7Ojg3RE05y9fB25co6OWAer0+7k8MxgjCcPGfzu5Zt58aZeMoUSf33XDl51Xox0epgjI8LW/RO89sIYijIdsQ7OXXYuhhjcv+8QD+w7zLo+WNWX4aHDD1UNkg3dG9jUswlHOXTHu9nYvZGpXC+paJoL1naxqWcT/cl+ClaBvJXnmWMT/MP39vEnv/Ia/vKqy3hm5BmGMkOM5kcZzY+yqWcTZ/SewYHxA/zpf36Tg+PPcP6a5bxwTSeZUoap0hT9qX4uXHEhy1LL6Ip30RHrIF/OMzA5wDMjz1B2yu5EgWKsMIblWGzu2Uxvotf//JJmsurvkl1i+7HtjOXHUCgc5bDt6Da2HtlKd7ybqBElV87RGeukL9lHb7KXvmQftmNzePIw2VKWol2kZJcoWkWKdpGi5f5fdtwYmxkxWdGxgmWpZRStIoOZwRlNsO2iO97N+u71dEQ7ODh+kGPZY03PXZVeRXe8m6GpoTrXiWYGtmOTKWVwWpYurIeoJGd2vZRXbjmTklNivDDOeGGcsfwYk8VJOuOdLE8tpy/Zx0h+hHw5z4tWv4iXrHsJW/q2MJwd9g1fb7KX3kQvcTPOcxPPUbSKdCe62dSziYTpMsSyXeZY9hjD2WFO5E5gRkwuXX0p3YnuurZlihlS0RRGxPCPHRgZ44p//h6lyEGue7UQjypsx+aRQ8P8dO8xDLr49XMu57+9eDWCsLZrLavTq+lN9roTuxnnJ3uOc+3XH+G3L13HHY8P8IuPvpoVnQnKdpmJ4gQfuuNhvv/0fj795jMZKx1i/9h+1nevZ0vfFjZ0b6Bsl4kZMfpT/RStImbEZHXnamzHJlvOki1lyZazOMqhK97Faz//bUZyJ3jlWWfwoSvP8/thyS7hKIflqeWsSq9iRccKXvvZB1neGec/3vWyus8D3IXKaH6UwcwgBavAhu4NrOhYQd7KkzSTDb0JtdcPTA6w7eg2th3dxjOjz9AT72FFxwpWdKzg6rOuZkP3hhn3I1h8hue0cLV95Jc/wkd+uVJebs/RDFfufIC3bdnIn73mbC76X/dxzTlruP4tl9Rd++ff3M7+/QO8dNUF/O5FGxiayPPJ//wxb9hyAb/7kg3cuvUQzzzzFDdc9eo6F0+qtI+ndu3hVStW84Xfu5SiVeTo1FGy5SybejaRiqbq3u8NX3yQghHhPa+v79zLo6MknTQJo5uIRDhn2Tmcs6y+MtGZfWdyVjLJ1PA4r990Jh+5ulX1opPH1WddPS/3dZRDyS75bCqIqZLrsklFU2SKGe7b/Swf/I+tfP6/vYpfP38TI7kRRvIjjBfGyZVzxIyYbyyLdpFMMUOmlPF/TxYnGcwMciRzhFw5x5VbruTilRezMr2SvmQffck+VqdX0xnvxIyYvitEt6VoFelJ9PjtjIgbByzbZY5kjjBZnGSiMOGzzsniJGs717KhewMr0yuZKk2RNJPseC7CR/9zBxHS/MY5G/ncb9X3y5NBX7JxbkzUiLKuax3ruta1vEdnvLPuWMxIYNBL0unlXZe+yt825MsPPMtTu3YTNYQzOzfwW2ef3/S+WlyQjrsGTQf9o4brzsvllxFXEV6y9hWcuTzd9D61MCMmcTNe9+wJ9QKSzib6oqt40ZoXTXuPsu1QnKZqiIjQn+qnP9VfdbzROG92/fru9azvXs/rzn5dW9csVZwWhqcWU55SrWxXKuk2C3pOFVz3gPa164EQlFMHjwdR9EvmuPeOm3E29myctm2FsoMZabwy0q7/dsQFz5fKBRGJ+CvyWgQn/t5kL8uT64mpY3SYrmst1Z1ifff6U9LOdCxd1Z4gokaUTT2b2r7XgaEBDHqJGZElKy4I5vLoLhg3jTZUbe7Jqbg7NdWOq6NeQd65ShPQ79eOqq1sO35uXoiTw2mpast4xqRsO34gt5lEOVvShqe62rOvavN+N5JU+3LqGbgzi2W7qWHRx9tStZ2GcuqS9fx4Zv3ddcSNJWV4qkrjBMaD3uUzZkZa9l1dILUj5jGewH2UUv6mi7WbzZ1sm9upXFC2FYUllFe1mHFaGh5dfNCyHX+QNxsQ2kjpfAo9EeiSObFpGI9Wtc0kjlaYxvA4M5BTV6pTL52J62ThJ80ukmd+7NDYrApdahaeTphLKoE0uHhrxHhiRqR9xhOrZzyj2ZI//uaM8cygVpvLeJbO9zETiMhVIrJHRPaJSNPdoEXkxSJii8ibZnptEKen4fEZT2XvkGYLHj1xlOxaV5vrDpvW1TaLBNKC5TRlSD7jaSeB9DSsXKC/y8XwzMcnC/zOlx6a1bbnPuOJmUssgbS6rJSG7q9RU1rn8QTYHlSPq+AW83PFamfGeJ6frjYRMYAvAFcD5wFvFZHzmpz3T8C9M722Fqen4SkGXW2aRTTuUNliNePxDY/hDgztcmtUcqPiamu/bYWy3XTinImrrVIKZOEn4VOF8iJytT3+3BiOqrhqZwLdl9Jxc4m52ip/B1mn4yiMiGBGWjOeUgPGs2Nggo/c8SQDY5XtR+YidqmUmiHjUXPKeL7+4AEeO3RqNrxrgcuBfUqp/UqpEnAbcE2D894P3EH13mntXluF0PDY0xuHirjAMzw1MR79e65cbUWrPltbY0YxnkXuapsPt4X+bhaD4dETymx2ny37q/75c7Uppdh9dG6z54P9UsfbwP0+DBGMiLT8PLRB0YynaDs8sHeY2x45zPefqmwHMhdlqIK3aGV4HEdhO4pikyols8Fn7nuGbz1xZE7udZJYCxwO/D/gHfMhImuBNxDYlaDdaxvh9DQ8hUpWv56kGg0IpRRTpWpVW624QP8uTsd42hwkZa9ESFNXm3r+1Gr7p+/v5q1f+fmc3tNfRCwCJd/jz7mJhLNpip583RjP/DzLY4fGuOpzP51T4xPsl1WMRykiEbfKR6uFkO6vQcajFyjf33HUP688B/062JZWrrbqwq0z/04eevYEf3nnjqpjxWnc6vMAU0QeDfxcF3itkYy2tmGfw91nrXYl1M619Y1pdcLzEX7cxgowngYdOVey0f1Cr4hKTcQF5YYxnmo5dSsUytOfr41je9WpF7ec+sCJ7JwXgVwsxrZo2ewYcKuZz2ZiCSq75ivGM5ZzUwpOZEqwam7u2TTGE2A8LVVtgfgWVBueUtU9T/5zqdrqpIUxCbqsC2WbRNSY5ux63P/MMP/2i+f4u2teiGlEcBxFyXZmxYhnCUspVbunmsYAEMw7WAfUlje5DLjNy1FbBvy6iFhtXluH09LwZBq62uo7QDagSNKrnGKNuCA2jZy6MMMdSFvt3+MXCW1rP57FE2hvhMlCmcmChWU7mMbcEO/F4mrbOTjpt2U2E4tlu7lciagxb642vSDJzSIG1QzVe1ZVFwZ1YzwygzyeirggyDA6YgbZkj0nsctgW1oynkAbZiMwKHjV7QuWQ9qoVLSfq8r1J4lHgLNEZDNwBHgL8LvBE5RSm/XfInIz8F2l1LdExGx1bSO0NeJFpEdEbheR3SKyS0ReVvN6t4h8R0S2i8hOEbk28FpDqZ2IfFxEjojINu/n19tpy1ygytU2jZw608Dw1IkLplW1zaw6dSvGM5sYz1y4JOYDWqY+kS/P2T0rqraFZXmPBwLGs2I8toNpCHFz/hJIdb/Iz2GcbVrGExEi7TAe39VWyeMplG2ihrvQW9+X8u95srC9sS/S2n0WdLXNJjaZ93cPrhYrnUJXW1MopSzgfbhqtV3AfyildorIu0Xk3bO5ttV7tst4rgfuUUq9SURiQG0NiPcCTyulXiciy4E9InIrYONK7V6DS8keEZG7lFJPe9d9Vin1qTbbMGdo19UWZDylJuKC6HSqthnuQNrKNTebPJ65cEnMByY9gzOWK9Gfjs/JPcuLhPEcHMnSk4qSL9mzFhdEIxHi5vwlkOoVfLbYehLdMTDBzsEJ3nL59HXCqlRtQcajAoynBVPRbC+4oCtaDmt7kly4rofNyzrYfTQzJxu36X6SjBotxQVVrrZZsFDNkgol7TmZmRt+vqGUuhu4u+ZYrZBAH397q2tboSXjEZEu4Argq96blJRStSVYFdAprgMwDYwCFrOU2s03goxHd6hG7jB9nhmRirigpmTOtAmkM9yBtJWrzZqmrXXnLnI59aT32epYw1yg3CIZ+FShbCliRqStmEYjWI5D1IwQ9zL954PB6cB6O6622x55jn/43q6W5wX7ZdB15TiKiI7xtOi7lqMwDalSixbKNnHT4PNvvYTfvtStIzcnjCfArloZspN1tfmMp1ytkl3ovrpQaMfVdgYwDHxdRJ4QkZtEpLbK6Q3AubhBpR3AB5RSDq2ldu8TkSdF5Gsi0jvrp5ghgnJqa5pabfq83o5YSzl1o5XprBlPk8GpB3Y7cZvFXKvNsh3/sx3NlubsvnryWGhjW3bcHWoNaT3RNoJlK8yIEI8271snC/0Z5ZvsvBtEsSbO0gxVG8HVxHhML4/HdhTDmSKD4/lGt6Ds7e4bjJ0WLYeE91kYnsttLmKXeuwnYwaOmn6sWCfpatPX6M+7OMNF6fMN7RgeE7gUuFEpdQmQBWrLIlwJbAPWABcDN3hMaTqp3Y3Amd75Q8CnG725iFynJYCWNTeB0EzBXWVbVZUL3GY9dmiU50bcPTH05NjfEatLINU+57jvaqvvQHqwth/j0XLgZjEevPtNf0OlVKBkzvx17D//5nb+8s4djM3QeATLyIzn5t7wLLR70bIVUUMwjNZ5K41QthVRw3W1wfwYHl9c0MYkWrSchruB1sKeJsYTibiMx3IUf/udnfzJvz3RpF3us2tPQjHAeAC/gO5c9Guf8UQ9Bd00hieYl3RShsf7rcf6YhX/zDfaMTwDwIBSaqv3/+24hiiIa4E7lYt9wAHgHKaR2imljimlbI8ZfQXXLVcHpdSXlVKXKaUuM82TF+EppQJlcJw698z/+I/tXP+jvUAlxqO34YV6OfV0JXNmugOpLy5okcfTcgJosvKca9zz1FH+7RfP8Ruf/+mMBuNkvmJ4RrMzc7X95Z07uHXroYav6coFC814LMdV6hnSWsXVCEFxAcx8F9J2oNvVDuPR322rdlSr2gKGx4vxuK5HhxNTRcaaLDgsx43xiLhxHtfV5vjsr2J45jDGE6svz1OL4POcjKutwnhmpnh9vqGl4VFKHQUOi8jZ3qFXA0/XnPacdxwRWQmcDewnINPzRAlvAe7yzlsduP4NwFMn8RxtI1+2fQZiNZBTF8q2vwrPBAyP3uKgaDvEjIi/54oeULqWm4ZSasbVqf1VUKs8nlaS1KDhmcfVv+U4dCZMBicKnJhqfxfIyULF2MyU8fzg6WP8ZPfxhq9NJxQ5lSh7rrJIRGY1sejJ13e1zUMujzbO7cR4dD9uNeEGHzXYB4N5PJatyJfspixOsz1w3dhaXKDzZsyI+9pcLKh0P0lGZ2Z4pjPA2aLFSIOxoA1OvsaIL3RfXSi0m0DxfuBWEXkS1zX2v2ukdn8HvFxEdgA/ws1wPdFCavdJEdnh3fNVwAfn6JmmhRYMxM0IZbsip/b3hXeUPzFmixZGROhORivbIljK9z9r6JVZEFXB1bYNz/QMSXfSWtnqRE2A/lQxHttRdCWiwMzcQZMBCXWzle8r//knvPGLD/L4c9W1rPIli2OTjY1cMI9HKcU3Hz28INWELTsQ41nkrrZsOzGe2TAeq7r/a1Wb7SiyJbvpJG95bA88w2PbFMu2z/70azNdUD11ZIL7dh6tOhYUF8D0rrbaBNJm+Od79/B7N22tO66Ndq6G8Zymnrb25NRKqW24matBfCnw+iDw2ibXNpTaKaX+oP1mzh2CLGY0W6pjPJaj/ByTqYJFR8wgbhoBObVdZ3iihtS5d4KTRduuNm9gN2M0FcFA5fVvPHyIf7n/WX7x0V/zjwWvL88T41HKVQT6NbVmsCrXijYjIg1dbZbtcHAkx8GRHH9w01Ye+6vXkIgaKKXIlW2OZwp117jXVQQVzw5P8Re3P0kyZvCbF66Z6eOdFMq2q8xyXUszv14brvl0tZVrXG3bD49z4bruhtszt8t4qmI8NYsf39WmFIUWjEe70/SCLsh4jFnGeL76swM8emiU176wUqbBngdX23CmyIETWZRSVZ9lwY/teIbHFx4tPvHPqcBpV6tNM56eVKyqOrX+/m07YHiKNp2JKPFoJZGvZDm+sEAj1iDfIrgqmqmrzW1P/TWNarUdnyxwPFOsURQF/Ou2YjxX4nM/fGZOab2+VYe3U+RMJkfNKNf1Jhu62vRnuaEvRbZk++cXyg5KuYO70bMEXW36swzGk04VyrZDNBIhEpmdD18brlMiLihZPHVkgmu+8CCPNqmUXDE803/H1TuQVjOeiLTHeLSqDSqutkKA8ejXZsrkS5ZTd401I8bTnqqtUHaNau0+TPUxntDVdlphymc8URxVWeUEVWDaFTRVLNMRN4ibEb+uUsly6hhP3Kx3tRWrjEh7bQtO3o1WdI0qF1QqFDh157nHFT/efZzP/XAv++awNpp2daQ9wzOTgKv+fDf0pRhtYHj0wO5Px4DKYkFvMeAoGMnWu9v0xFH26mBBdRLwqYLlKKKmnISrzTVcup/Nh7swKC44NukyyFqXrYbuly0NTzDG06RygWUrciWr6UJF5/GAdrVVMx69K/xMGY+bOlF9jWYb7cV4gq625udpIz2cqfRPpSrbKdS62k5TwnP6GZ5MgPFAJaHLCkzqUyULx1FkizbpuFmVU1DyxAVBxMxIXQKa7ljJqDHjBFJovFJ2GhieRvvu6GeJmREs26kr1zEXCG5WBo0ZT7OJarJgIeKWPxlvMNnpz66/w61ooL+zoALreIM4T1BOrds3mx1ATxZu9n3ELREzK3GBa7j0hDgfm4+VfcZj+2WLmsVN9CJqRq62qsoF+DGeQtmts9Ysb6bsfXZAQNVm+3k8IkLUkBnnp1kNEnF1H0l6fXi6JNIqxjMNu9d9/sRUZUFVsh3fKFcUgjMTHj3fcNoZHp/xeIZHT2Z+cqbjunOmShaZokVH3KxyeZQsRcysrkwbNaRutaQ7WCpmtJ9AWm7BeBoUCdWTRTCYq98vbkZ8FVHwWecCvpsi3tgdtHNwgvP/5l4Oj+bqrp3Ml0nHTfo7YoznSnVuRX2v5Z0e4/G+s1zQ8DSI8+iJJLiz7EIwnrLO45HZ5fFow5WMucNzLhcMlffQqraK4Sk1cV/pRUUrd2ozV5vtOF6MJ+IvItz71U/0OgcK3IVTvmxjOcofg8CsKkI0ZjzVrrbpXJrtutr0PYIqT10mBwKMpzx9PPf5jtPO8OiJqDflqrF0R7A9JZTuB5P5Mpl8ma5EtCrIW7LrXW3aJRCEz3hiM2E8gbhQgw5ZYTzUnRccGMEaVJZTT/PnAv6eMX6Mp/r5B8byWI5qmKE+WXA/195UDEdVy6vde3muthrGE9zNc3rGE3C1zcOk3QquHHr2JXO04dIr8flxtVViPJp1NmMRbTOepobHlVObEakaJ41cW/qzA3dc6e9eMx6AaCQy41wty1Z130VdjGcOxAW67wZdbUGGpL0PJ1O9/PmA087w6NVzTy3jcao7ZqZgcWKqyLJ0rFIWp+xQsmxiteICo5GrrcJ4Zlq5ABobnkoCaeU8PQCLVvUKEyARNbCcgKttDicw3T5fXFBz79oSQ0FM5i26klF6O1zjX1uvTU90y9LVjCfI2BpJqvWKPVh1fKqNIphzDatK1Ta7GI8ZiZDyXG0ns2B47NAor/s/P6szXuUGjKdZwL6yJUirGE9jGb/jQCRSUaTV3re2XWagKoiOB1YxHkNmrAaznOaMJzGDGE/cjNT19SD0GA4ynmC/zdep2kLDc1pgqmgRNcRfqWs3hh3Yfx1gZKrEZMGiPx0PMB6nobggatSXr9cdKxkz298Izpqe8QTjULXnNWI8iai7Msz5rrbmq3/bUXzmB880DTA3a0uHt1os1OYx6cmqwerQZTwmvZ7xr63X5sd4vKrVU4G8Ko1GrrbgtggL6mrTtdpOIsZjGuLLfE9m64LthyfYcWSi7jPW7KZoOb6ysNEiwQmwx9bigsrkXLVpm1KYkYgvk9ZoxniigU0WJxswHjMSoewx+ft2Hm2LNbg5ezUxnmlUbTsHJ3jHzY/U7TzcmYhOG+NpyXhq83hCw3N6oFh2iJuGv6rKB3ytwU5wYCQLwLJ03F9tlazm4oI6VZtmPFFjxiVzoJWrrYGqza5fbep2ZxvESGqx52iGz/9oL//1TOOqALXQ76G3KK5dBdZuIxFEpuAxHs/w1EqqfVebx3h8cYH3HnEz0pDxBLdFWFDDY3mVC05C1Rbz8nhETi42pxdWtWwmmGdz1FO1NXK1BRdUrWTd+vJE1Kh6P8up1Gqrvnf9c+kCqeCOq0aMx4wItq34ye7jXPevj/GtbUembZfbBjfA71Qt2twGa8MTXLw9tG+EH+8+zrGJYtVrXQlzWldbS8ZTK6cOxQWnB4qWmxOgV1VBV1uQ8Rw84Rqe/nQsUCXYbli5ID6Nqi0VM9ruXFXusgbX6LcIvqYHT61PHSqrRD1xT2d49Kqs3UmuVk5dx/imCUhP5isxHmjAeLzB2xl342va1ab3jtnU38HwNOICK5CftVAxnqjpMp5Zlczx3E0iQipqnJSrTVcmqFWsBY3M0IT7WTYudFt571aMxw4wnqo8HkdhSLuutuo8HqumL4NbvaDsOP6zferePS3bpuv4VQtzqlVtwcWjrqhRqWTvnptOmC3EBfWMRy+YYmbEd3dX5NSh4TktULQcz/C4g8AXF6hqxqMNz7J0jHigUm4pMDA0og1K5viqtrg5O3FBg0lA3yc4h+jJttTQ1eau5BrFSJq9d7tundqs79pJxGc8DSaXyUKZrqTpX1vrptP3ikcjdCZMv9qEXr1vWpbieKZ5Ho9dxXhOfYzH3cht9nk8usgouJ/vybjacsXqdIFgGzV8w+M4KKW4+cEDPlMMfq+ta7V5hicaqWJUwa2vg2ioanMCqrbAOItHaxiPl1MHMDhR4BsPH5y2bTrPrZGbupG4QMcd9cKl4mprbnjcfB3NeEo8/OwIN/7Xs/5Cqi8V87fAXkw7kC4ETjvDo2M02nhow6Nq8goOnAi42qKVCtSNYjzTqdpcV1t7basSFzRkPBXJd+2x4KCpyKndATXZBuPRA6Hd1bWeuHRpl2auttrJxXHc6uBdiWjVZl9VbbEqLrV03PQTSHXbXMZTrFstNnK1LVgej+FVLphZDBzwqmN4k3QyZpyUq81nPLWutgbqsrKl2Ht8io9/52m+t2MIqI7RtWQ8gX4XHEu6VpsRqR43TV1tAcajETeDjCdStaXJsnScXxwYnbZtVkB4UntM50sF+6p2/2aLFcNjRNzcqmYGWM8BIjA8VeTzP9rL5374jN9veztidUVCw20RThO4rjbD79zB1WSw4z3n5Z/0B2I8ekOseK3hacB4KuKC9l1t1TGe+s5dUbVVjumVZbW4oMIYoLL/UL5cPQmfmCpyzRceZHA8X1dLqhX0JGNG3PL99a62xuKCTNFCKehKVmTq9YbHa79pkE6YVXk8MTPCmp4klqPqqh7oXCZ3UvJcbQsiLgio2hp89yemitN+zu6q32M8UeOk8nj8GE+dq62ReMXxv68Br/9Xu9rak1PXutoszXiM1uIC16NQifFoJGoYj+U4/vXdSbN1xfaA8KS2vUk/xlO5x5hveCoGImoI8ajRVFyg++2qrgQly+HnB0YoWo7fT/s6ovWVC0LGc3qgZLl7e1RcbZVBXeuuipsROmJGYJdR25NTt65cMKsEUsvx3RGNUir0Ct9pEePRk0rCM5iNMv8BnjmWYfvhcXYNTfqDqW3G472v4Q3G2tWrv39RzYPoYHFnwmy6l1GxXM14tOHMlSxSMcMXHdTGhsp2hREGM/NrmdFD+07U5Q61i1seOsjNDx6oOz4wluOpIxPu++tabQ1cbUopfuPzP+WLP9nX9D2Cq/5kzCR/EpUL/ImzLoelvuagrszhPo+bf1UtLmhP1ZaIGlWTuN76OiJtuNrs6jwejWrG45be0W1NxcyWzKHsNGA807jadG6TXrhoF3vCNJoWxNVjfl1vEqhsEzHk5bL1pmL1lQvCGM/pgaLlKoa08Qiu4monwGXpOCKBDbnKbtC6HTn1wZEcZqSyd7xqY2VTKNt+Xkyj8iV6oFgNjExwh8RacUGtqyr4fuCyPj2YZhrjiUYiJKKRusFYkVNX30/7zDvjZtO9jHTMx43xRKvEER0x03eNBA2pUso3hpajqio5BAUG2aLF7391K7c/OtDWc9biO9sHue2Rw3XHP/fDvfzJbU9gO24Ssmm4MY3aFe3AWJ5jk0VfSdYI5YBRSEWNaWXwrZBv6mpTdCejVceC7itteILMLDhWRrOluvGiu2Ut43Hl1PUxnoZyPW/6DwAAIABJREFU6mAej9GY8RgRV3Sgr096+WrTQY+Z6hiPeyxmuAvRYN+vFxd4hicaacpW9RhY15uqOn7EMzx9HTFyJcvdq0tvgRIyntMDRY/xmEb9o9cbHndl7cup7cbigtoiobc/NsAdjw/wuy/Z4K/y2lnZFMq2nxfTaBxVGE/l2PR5PNV5ILVGJe+V8siX7Lo94QHufHyA9976eMO26onMiLhVlGvdD76qrY4JOlVtm85NGTMidMbNKnFEMmYEaphVy8/1GLZsVRXcDgoM9EaAs439lB3FkbH6agzjuRLZouV/DzqPp3bCf3po0mtH44lSP4de9SdjJ6tqa+Jqcxx/LyX/mF1xXw2MaVdbIMYT+I5f+9n76wL6wTye4HMHt74OoqGqzalWtWkEDU9Uu9o8t5xptBZxNIzx+O7iCN3JqJ9Iq5SqiAu04bFcV1siajQ3PFY149nY7xqgwQDjcRR+4dPa9pxOOO0MT8ljPLVuBqh3C+kERs14ciUb22mwEVxghZcv2Xz0P3fw8jP7+avfPM8fbO3EeYqWQ2oaxlPZM6jeyFSLC3SMpLqdtRNYPhDX0SwjaHgeOTjK93YMMZatryCt26C3aK5lPM1iPEE3GujPTtVca7srZCNSFePJeq62RIPEynLNRBc0xEEjoyeN6bLUp4NlO2SKlj9JBd+jaFWy46OG61qqXdE+PegZniYsRrdbr/obqdrGsiV+7TP38/P9Iy3bm2vCeCxb0VnDeEoBxjM0WfD2wgnEQPXW7I7ixFSJwfFq1qYXRnHTaFwyx3smzXyaMp5IfYwn2Je1Qddj2Yi03mLcV7XV9BNw3cWu4XH7eb5c2bZBizO0QUxEI3UqTA29qNqyIs35a7t49yvOBGBwvIAREbq8z7tQckJX20I34FRDiwtqWQtUBoLu+Jrx6AGgXVaNXG2Op4o7NlmgaDm86UXriBoRn/G0sju6dLrPeKZRtVXJqRvFeHTQNLBKhOaGJ1+uMJ5gWR1tNJ70YhdBVFaLjcUFzRJIK240j/E0ESboiUar2pRyKzCkmjCe6vicU+1qCxie6Ur5tAP9HdSynpy3x4x26TSr1bbLYzzNWIz+HrUr2HW1VZ971/ZB9h2f8u81HfSz17ajbDsNXG2V2JhSMDSR9/tAKlbZc6pZcq7tx3giddt0GAHGo8tV1caMlFc9xFe1NXG1RY2Kqy1mRnx59XTwC8g2WLSZEaE3FfPjOsESTtlAHk/Mi/HULmw09OfTk4rx3ff/Clef7246d3SyQDJq+LGkXLmyLUSrPJ5//fmhhjHFpY62DI+I9IjI7SKyW0R2icjLal7vFpHviMh2EdkpItcGXrtKRPaIyD4R+UjgeJ+I/EBE9nq/e+fusZqjIi6of3TdGXq8AqK1jGeq6HbIRuICcCezYS9jeXmne60+tdXA0KXi/RjPNHk8VUlwfkXmerVOosbw1K6ydU5BvuT4q7VCYJLTA2nHwHhdW/TK0YxESDQSF7TLeBq52izbN0zphKtYKlqOJy4IxHiC1bwDUlarJhm4yvB47dHv+d9veYQfPn2s7vmCKNtOnUvzSE3x06miRcmqJK5GDWm4LcKuo9rV1tjw6O9zOsZz5xNupn47Ljh9Tu1EaTmKzkRlA2IR95xgheqBsbzfB7qT0Qpb1FL1mv6kJ9GYGfETNqF662uoFOit/d59tugznkr/rWM83uQfMyNuzGcacYE2aNA4j8eICD2paMXwBBh+xdXmbsmdaLDo0ajt212JqL/4SEQjVbFJ3Q9bMbVvP3GEmx86OO05c4Fm83Tg9WtE5EkR2SYij4rILwdeOygiO/Rr7bxfu4zneuAepdQ5wEXArprX3ws8rZS6CHgl8GkRiYmIAXwBuBo4D3iriJznXfMR4EdKqbOAH3n/zzu0uKA20AmVAL3OqO/vcH+bHp3XQe5Gcmpw/cA6Y1kbHj/G04LyaP+5LkEzXR6PrqQdPBacMHxVW7Q9V1s14wmyA/fYkwONGE+1q61WatuMWWjGowdwbV0vcI1DwvuMO704xGShXGE82tUWKDevJ/yUV66l1MTVVqmo4LKTH+46zmPPNd55U+OPvvEoH79rp/fcmvFUb/eQK7rl+0u+qyxSty3CZKHM4dG81/YmjMepXA/1MZ5nh6fYfthdCLSSWSul/BhPXWVmW5EwDb/v9qZi7gZ6AWMwMJbzPy/X8FQb7VwN43GUu1GbaUTqcs2MSEXV1tuhGU+N4fGNbnWMx4hI1UJR78fj7gbsus2nExc0yt0J/m2I0J2M+bk7wT2ipoqVGJl2tUFjaXmxpm9HIuIb2UTU8I/nAlt/txIXlGyHQ6O5ealQrtFintb4EXCRUupi4B3ATTWvv0opdbFS6rJ23rOl4RGRLuAK4KsASqmSUqp2CayATnE3GU8Do4AFXA7sU0rtV0qVgNuAa7xrrgFu8f6+BXh9Ow0+WWhxQa27DCqTpDY82niAO0Fqw1PLlny5tW1XDE+62vC0otS6Y6W9/W0aVqd2gqvI6mONGE+wvlWjml/BGI8eCLlGjKelq206xlMjOqhZFbpVH2qFCY7PeDo9BjhVsMgVXcNTK5oIPr+uyN1M1RastKy/71abih08kfUZjp6sahlP1hdAuL/NSH0ez+6hDOAy6uautupVfypqUrIqjOvb2waJiDv56nvcuvUQQxP1gge9VThU12Zz38chZoq/n1JfR4yy5VT1o4GxvD/BdgUYT7OqELbHbKKR6v2pLE9OrVmcZgK1jEcb3do8ntqFnmYRRZ/xTB/jqRU6VP52iIhrIHpSUca9uJ3Ou+lKmP5nXLLd3Kr4NIynUNO3oTKXBF1t7nirxMumQ8lyv8O53D24AaabpwFQSk2pijS3A3fOnzXaYTxnAMPA10XkCRG5SUQ6as65ATgXGAR2AB9QSjnAWiCoPR3wjgGsVEoNAXi/V8z+MdpHyfKKhAYYj04v0APBd7V1VAxPzIz4pVvqxAWBfJThTBHD8xlDpT5Vqxii70v3JtpWhie4VXew7cFj8Wj1AMiV7SpZd3CDOG0QqlxtXpuGJgp11aCrVG3RBjGeQPXjIGoZT7MCq8EYD7grz1pXW6MYTyLq+uAtR/nnBbdGCIoL9PO12tslW7IDVRHqXW1BZqHfS8f3ggvx3Z6b7ZL1PdO42iqqOMDfDE6ff+BElg19KVeaW7SZyJX56H8+xV3bBhu0u2Jwbcdh3/EMv33jQ0wVLTeW4m29kI6bJKKRqooPyajB4dFqxuPHeDzPQK0yUOfr6BhM8HiwckFH3GVatYsVn/FoV5v3GdS6jM2IK+YpBbwX003gQfZbG+PR6sFebzFQtGyf+azrTVXk1Jbjq9qgcU5TLeOBCrtLRI2qauMVxjN9qoUeG3uPZ5qe0yZMz0Wmf64LvDbdPO1DRN4gIruB7+GyHg0F3Ccij9XctynaMTwmcClwo1LqEiBLvVvsSmAbsAa4GLjBY0r1/qwZWkoRuU5/WJZ18lnoRcvNfo82UMzoL3mZx3TqGY8X42mgatPXD2fcPXwi3uDR9q3VykZPiFpc0Hg/nsDfNT7r2h0foXoA9HXEqjZIC75nwbIrCaRVlRxsPw7wVA3rqai3GifV6YHZNDk0WnGnNCo35BueRIDxeK62qFcVIMjg9POnYm7yYsly/AVEQ3GBVVEWTbflMbiGWU+KjcQFhXJla2P9Xm7lgurvUW85saEv1dzVVhfjqd6+o+SJYzpiJrmyTcaLOzaSJld/Poqnjkzy2KExnhvJuXv+eFsvdCejRI3KZA6weVmHG+MpN4/x1Lr6/JpsxvR5PKmY2XCxYgXclFAZl4ma8fb/2fv2ODuqKt1vV9Wpc/qcfr/yIIGEkJB3wsMAUV4iCo6gIIqAwmUQ5Q4Iziijo3fmqqBeh9HRmXFkGB84XkXBZ2QU8MqAjqBAJCASwiOAaZIQknTS6cd5VNW+f+y99t61T51Hd5/uTpr+fr/+dfc5VXV21anaa6+1vvUtok/Xm+NJUiugv0nFp00uFPePlNA/JK7pYR1NMckcca9XDrUleTydhsdDC6GhgiCisDrmBrpGT788bo8n4Jwfb/zcYrxX1zzNOf+RTLe8DcANxluv5ZwfCxGqu5oxdkqtwdRjePoA9HHOfyf//z6EITJxOYAfcoFnATwPYKncd76x3TwIrwgAXmaMzQEA+TtRj59zfgtdLM/zkjapG1EkpFTSnpPImKHJ8s0r5+Dz71iDJbOa1TZpz9WstgqhtlLI8cpgAd3N2mA5yuOpbnjoBstV8Xhiku48bnCqiYQCwvAA8Ta8KsdTDNWDNGKF2lbObQMAPLdrKDYWMm7a46kQaksIowFaVcF344loQLeuALTHs3e4iCDiyKU9MCY0s+LkAsnk8/V32ZpJgbHKrDYaI+176dcfwncf+lNsLOTNaPZgeajNLlAFqI7HiYXa8kEI12FozniqkNBGoMJNWjIH0N8LMbmafBfDhUCFu5KoyXGPx+irE4RSAsZB1veE4SEvItSGZ/s+QS5wHdG/yqai2032Ii7yJb7LUAp1HlI0gtOstqzvKlLJfz21C1/7b8HaKqnFjBVqszwe12FqcVGPx1Mxx2N4PO2S4bdvuIT+4SJa0uK6KMMTietFqhl2qBUwpZ6MSAN5PEZuktQ7qNFftfwvfR/PvDxuj6caqs3TZeCc/wrAIsZYt/x/u/y9C8CPIEJ3VVHT8HDOdwLYxhg7Wr50BoAnrc3+JF8HY2wWgKMBbAXwMIDFjLGFjDEfwLsAbJD7bABwmfz7MgA/qTWW8YK+RKJgEmyPJ5d28fbj5oEZEh++56geG0l0atr/lQOFmKfkstqGh3OubvCcX2eozVqBlxKUC8wHgIgSJnlAhdoMckHByCcUDK/BNiAlIyySRC6oRKculEIwFp9c7CJTwWrTzCBAdxyliThjGR4z1Ebn5HsOcr4XJxeYoTZq8iUn+40v7MUft8cpygUZY1dyPPJzdg8W1TUzDRvlBFLS4zEXC3lJmsj6nioktGGHm7JWzRK1Xs/5HoaKgWJaJh3LzMEEYaSOXShFssU0w+GdWSzsziHlidoYuo9mt2WwZ0icY9pzkDbqVyrRqSPOwZj2WExRW5cx9SzkfFd5PHds3Iav/Xpr7NraBaR2jiflOEqd2vccuDXIBUn5T/qbjKHuDVXCvuEi2nMpQeW3Qm0rD2tD2nMSa6jofoov+CS5wNOsNlJFIG+2mugC3a8N8Hiqodo8DQBgjB0lc/hgjB0LwAewhzGWY4y1yNdzAN4I4IlaH1ivC/EBAN+Wg9oK4HLG2FUAwDm/GcLtupUx9gcIt+0jnPPdcjDXALgbgAvg65zzP8pj/h8AtzPGroAwXO+ocyxjBoUN0p4L12FgTNQr2K1vPafcHqc9B/3DJfS2pHHM/DjzW9OpBblg6ewW9V49ygV/fuvD+M1z4kZWHk8Sq83UaFPFpOWhNpokkzweM6ltkgvM4ZF0T8GQ8ClaoQwlEuo6ilzAOVfGulIBaT6IkPFctV1yjidCZy4eatslJWZyMhne5DuxfBSRCUwPwXMZcmk30eMhwVfzepVCXjaBDRmsJvGbo7cljV0HCti+bwRH9jTHDNuQIhcIVpu52i4EoYj1G2M0CSCANiA6xxNvf02rfN9zsG+4qLwO8xrmSyFe3DMcC4UFEUfEtcdTknpwX7hwDTgH3v+tjRgMhfKCw0SYuRBE6B8uIe2JcGoxiGTUQHrHpTA2edPfNPZSyOE6okzAcRhckgFKe8rjGRgJykKedh1PmccjDU0pjNCc8aSSQX3kgnjxtdZGpAXWvuEi+odL6Mj6yKUFo5BzrkJtac/FaxZ04sHnyg1PXs0vRqhN5ombfE0uIBJDLu1i92Btj4cxYFv/sFLuaDQ450HSPG3N8W8HcCljrARgBMCFnHMuHY0fyefZA/AdzvldtT6zLsPDOd8EwKbJ3Wy8vx3C0iXt+zMAP0t4fQ+klzRZKIQ6BssYQ8oR+YWMIYkDlDes0vsAX3zXWrRl44V39IAUShF2D8Y9HhVqq7Kq2bp7CK2ZFLpyPhbL8F7NUJuV40lSLjDp1OTxmKE0U6vNvPeHi9LwBBEyKRGWtPMgJeNaZVKygDbSvVSqeTwm6cFPYLWJVbb4TsjQvCwND60S7VAbGQ9d4xOhJeMhl/ZiK/98gscThKIPTTHUdTjmtRDbaEN/eKfoB7Rjfx5H9jTHjPmw/CxP1vHYHk9ahsno2O1xWS/1OXaoLW8YnmzWQy7t4qV9YWLfnNsf2YYb79yMz5y/KnZcxnhsjCnJSBSfJ8JXlDehhcr2fSNIe5pJaAqJinMIFOVdsdrkPVCKIvhcnIeZ48n5rlqsDORLBlsuzuijBZ2d4yFDUwgiHdKsluMxjU2Y7PFQMe2+EenxZH0hPio/x1QMP2lRF266ewv2DBZUrZ/4DrTiBoE8niaDTk10bfpuq429GERY1NOMZ3cN4tldg1g1r63ituNB0jwtDQ79/TkAn0vYbytEic2o8KpSLlAaYIrKK8UIqd+OJVdi4rL1C/C5t6/G+kXdZe/R8XYdKCCIeDzURgWkVVY1Q4UAZy6fhbv/8hT0yn2TDE+QYHiqKRdkvPo8HlOrDUAs7Jb23ESvRImEunryMie/SgWkNPkSapEL6POp8RuRL8oNjyYX0Dn4rhMLl5hjjLPadHjRplabBZhcNgtU0ify85M8npSs44nleErC47HDZyYC6x7MWh5PQYaXsr6HkWKoPtv8fvYOFVEMoxgTKoh0qwgiyZgTJJELaDKnhcqO/SNIp8z6lTD2Web9xLlmtQHCCzWLNHWOx1OKFQMjJa1bVqGOx2a1EZmAwo6eW93jKVl5HfW3Ic9T7vGkVH5xSBYHm4YHAH5n9QCy721Ah/AyKRdpGeKnkD19t5XmhiAUpJXVh7Vh6eyWcTUEPNgwvmz9IQY7+Sdu8LAsx5Pk8bx1bRm7UIE8Hko4xjyeOnI8Q4VQ1e/QZyc9SFFSqC2hA2kYiVi7ydzrlCszM/xC3g+FCGgy15MctQlniZXvNN60MSnZrbDLjUoYm0iSlQuimFd0ZHcOj/5JlI6Rt5AxpGQO5Eu6jse3Qm2+V5FcYIbaSoZHA4h2yktmt2C+FHw01RBopapaLxgeFV07VccTC7WJ+iQz1PbTx7ZjbnsGxx3RKY5pJdi1zEo8x5P1XZHjyWvZfgJ9nyYhxDSog4oAoe9zz9V0at/VHs+O/Xks6MqpxUW+FPcKBwsBZsm/Q6teJ4h0V1+HMRXCzqVdJbM0kBfU7iCMjOLZOJ26LMfj6n48aTdZmshE5ToersJ/zWkPnsOwZ7CIXQfy6GlOqzDzUCGUoTax7arD2pDzXTzw3G68edUcdTxTcYPQadCpGWM4vCuLpyVRoBqRCNDf6ZLZLfjChWsrnt+hiFeVx1NUhofCC/EVFU1ESaoG1UArM2V4mhMMT4WbK4w4RkqhUixQdT91kAtMKRDb4/FkIR+BaJ3xUJuO1ReCUFVZU+xeMACTPR6dBHd02wi5DYWtgPIC0iSPp0wktBTPfVxw3Dy12iPyRZMvVIIf79uHtZ/6hXqYTTmdlOsgV+bxmKE2ytvo8BGd1w9+34e7n9gZC7XZzDnKe5mGbdBgtTlWWwRK1Juhthv/80m8/1u/V6KjL8s21MSMzCSE2tKSjTZc1KE2M1xJ5/jcKzohXYrKu7Ka9zktLiiX0WmoC9gej3mvmeceRlJlQBqYbXuHVTGm60Axwua0NckeTpFieAklCQq1WXTqBFYbtXBISVZbVXKBldfRf2tWG2OiiHTji/3IlyKsOKxVLQYFq1GH2lKug+MWdGLji/E6eiKPmDALSAFgUU8zXtwzHHutouGR96fNop0OmH5nVAVmS2UA8CnUVofHUw1keLYneDy11KnJA8lV8HjypRCfu+sp7B0qxg0P5zFCgK3O7DmOFWuuFWqLFPVzuBhoIy117WzPJYxE0lPkeKThtuo8GCuvLynzeCqQC0zj9PZj52nRTCvU9vzuIYQRV6wf0/CIUJtrsdo0zVux2gI9KZu0aZLpEf9H6j0aAxEaKtKprUZwhZLImenwWYD+oRJ2Dxbw+Xu2AABe2DMEz2E4rL1JfpZdx6M9nmIQqUR1nFwg/n5xj/B4HCa+L/KmyEuKhdoknZr6TdH9Aojnw1ycxQ2Pvp8iLupiUp64hy+4+UH8rx/9AYAIjy3qacZDHzsDa+a3w3cd7JcUeTHmsCzMWInVRt6ZYrU5DBGvvLir6vEYz3pbUwqPSjmi1fPa1bUfKgSS1abHsXJuK555+UBcvTuIyjye7uY0cr6LWa1iTljUo0s0aoXalOFJUFk51DH9zigBn/zpH7H+s7+sEGrTrJlqrLZqoMnuD1LTLCnUVmlVQxMbud2utf1dT+zEV+57Dr95drfVeTTOwIopF8jYtZmrUobH8EBsOjWtzkxJj7TnJHs8kY6P2x4Pbduc9mLhFnHshByPcWzOedkD3JHzcfYqofTbZBkeWjHvVOQD/V16Uu5+wGhhYGq1qVCb0bHU7GI6MFIyWkcbHo+RaAfiq/4hm1zAdWW6ZrXJ2iSZi2lrSuFbv30Rff3DeGHPEOZ3ZrVWW6pyqA2AkmgyFwZK+ZiL/VOuI6nScY/HDLURnbooacPNknkGQJILtMdjLibMc4+4aH+wqKcZHdkUOrIpPL9bGD/6qN7WjDhmysHuQS3GWQiiinU85coF4n2izJNBqJTnSWqcKLaPYl5fe1YUWbekPSzsyqlncrAQxFpyA8CKuW0IIo5nDJpzoRSWGckm38W9Hz4Nbz9uHgDRMkG/R3Tq5HEXZgzPoQ3PYdg7XCxbQdCNpFht8v1R2h3Mbsvgf6xfgD1DRWRSjspzAFq5oFKKZ9Cq3yGjR5P1Tx8TdVxmApzeN/+P53giuC6LGQbyqEhLjHMuw1Haw6IEqylimJZCkkk5HlcdPy5hQ/uSzpppWBJzPDJxb56H/QB/4PWL8Z4Tj8CcNuEJZHwXI8VIMYSIbm22gki5DtqyPgbyga5NMoQuTRqvrUwQhBwDUi2BtqGQDRk3Vc9istqIXODoWjH6mmxW2w4ZVjt3zVxwDjy2bT9e2D2MBV2a6pZJCTYlhdoKJZGDodU4SRnFrrFB6MilXRmK0mHZAwVN+SZ4kuFJjQ4ZY2qxQnRqcQ5WqM0qUnUYw+p57Xj0796I047uVfVXdhQh7TplfZLMlhJA5RwPLajyJWK1VV/cJRVX0/bmuCjUvPKwNjiyaBYwczx6HMvntgIA/rhdK3rkEzweAJjVmlH7LurRamPVVErMcdvnPx0w/c4oAc1poaxLk4Kd4yljtY3W8gD4xLkr8IV3rsGH33h0rPC01kNBiWlaXdFHhxHHvuEifvXMKwC04SGjGUZx6f+kHI/ZxZImKlJ0pknXDKl0GHmgglGTUCnHY8fibY+HaLZ2GMj2eIBybTf7YTuqtxk3vG2lup5NshPk/goeDyANj2SgEZMrRi4o6fxNMdRGiH4fMEJtQagNfZPlIcc8nqL2eOzvnowueSsUmn3Nwk6kXIYntu/HC3uGcESXnpxIpUGLVcoC0rTl8VjGnZD1PRGaMmjQpqyPvlY6b0LfiZkYVwSSwO51ZIfa9DG7m30VznVsw2Mpp4sQHrHamPztoCObQm9rOrat6aWYxeCV8jzxUFv5c0JoaxLnu1pSlukaH8iXEPG4OPARnVk0p71YwXGSx2NjUW95qK2Sp1as8CxMB7wqWG2kN0auPd30ilyg6MDiIRltjodw/rHzyl5zauR4aMVIqx/l8XCOu57YqR7GYsgRco60ZIFFnMceqLKOj0Y9RVNKFMz6nqOUCyjM1pH11aqUcjwjZqhN5nhsAkAgvSqxTZycoQ0PMdxCAFoBIW15PLRP2tB8S1o5msikHIwYhsdk5hFSLotJobRnfXVenOtJk5Lq4rw0u21gJFDS/0GkvSKV45H/DxZEZ9ThYqi291xWFmYVyWe3zOPpbUljcW8L7tvyCoaLIRZ2xzV4KaxIXi7RqQEomnnBMu6ErC8KaIk5BugcT7zVgKOuA30nXc3a40nHPB59L8TJBVyFisX+2mDYhB07YS5qZaKycd39wVPK6ubMhWHaq+3xJHXsVeONhdrE56ye1w5ARyEoj0a5K0A818vmtMQMTz4ob65nozWTUgXIKtQ2k+OZnqAJcI80PHTTe2ripLoDYmqNzfAkgR7ESgq09OBmEzye+7a8oh6GIIwQRZoiHVg5HlMyh9g6jIlVN03GWd+N5XUA7eWIvyuH2urK8dihtkycWg1U8XiUokC50GISmqQK9R6rLbfdqZImgv0j5WKa5AWVDKkYKiYlbTNiZVFxJaBj8yadmq6jksxxnLIarryUAqLvgzyejqyPFXNbVUfRBbbhkd+bORGR8TuQSKfWXkgu7Yk6F4OVl8Rqo4R9oaRDSirUloqTC4oVQm2kUEDoTmB3EuyFhQi1lT9/va2ZMnUH01Mze2tV8hxs4g1B5ELLCTja45GGR4ZzU1YkZMXcNmzeMWCEcWt7PIAmGGRrhNpUjsdtvFrBVOPVZXiGxOqwosdTRblgrNCr3uT3KTRD1E0zxzNYCDBbJmNVqM3Qwaqc49ErOZN1ljVCNmR4zFAbGbmRYpxckEoo8gyNhzZjhGGA8lBbIRYGispYbeL8eGzbWg8wHWPn/ni7BjvUpgoDlWekJ2WatM0wlFnTA2jFBCAec6eOnYCYfOk6DlbxeASrzVXNy8jwtGdTWHmYrkg3czwAlDdllgNk/fhkVLSuMc3zWd+F5zixJnUm5ZtADM/hYqgWNzrH4yYWkGZSTpxcEHGYjw55TEBCjscr93joeiZ1BzZhGouUq5UCKilUxxZoFZQLAOC8Yw7DZ85bhXmydsuXYsLUJsEkFwAizzNcDBV7sGjd25VABIOmWjmeGY/n0AZNgFQxTCso3e8jvupKhTweAAAgAElEQVRupMdjejBJoNAMhU7oo2miMMM6IbdyPMZDZE48pVCzdVIO00ww31UrfxVqy+nQQFPKUyGsWI4nweMpRVEZuUDTqcXveKgNapuYx+NaHo+hp1cNdE6mYXBYfEJLSVYbUMHjUQKbOgxlswVNw0bXLOUyRYoAhNfa2uTFlLDNpHcUiZqrfBCqOo+mlIsBafjasymskMlqk0qtzlWG2kjyyQy1EUqWx6Pp2K6s7I/KPR6rgBTQNHRAyyzF6NQlXUwpVCH0d0uSOQSzns02PHaozQzhJSmHmIjneFyjBCF5dVeqmOOJYp81t70JF59weCxHm0u7StQzZRmANTIk93tZ3Jyv0+M5dUkPls1pVfdmZXKB/r6nG6bfGSWA2CmU46EvUoXaVLhnfDmeJNRSp7ZZbRQei2SdQs5ghkWR1kIzPZ605yTmeMQ56tDOuoWd+OXml/HAc7vVyt8MtYkaE096PDrX4nvlygWhMRbyIG1h0CRyQSWPhx6yvJFbqgY6JzPU5rlx1XHBapOGR04eJuNLeTyRTmyXonhlfszwlEiVwIm1cxgqhMj5gn5s9ikya7gEc0+HmMhwZqVu2bI5rWAMMSq1Olcr1CYKSKt7PJQnyvmeYrWVrBxP3HMQfw8XA/gyl0ECl2kp9wKQcoHIA+XSXkwJg1hthKoeTwK5QLVTr0HuiYXaDHJBxRxPBckc2+NJQksmpeYNO9S2uLcZXTkfDzy3W51DPYbnDctn4efXnawXkbVyPDMFpIcmdI6HPJ54qM1MjjsMsRXPeFGrHw+FvqgFMQClalyUN7LniIk/5Lp6OuJ6ZS6an8UTqPRAmV0TP/5ny7GgO4drb9ukCQVZs1DQVQyqWKgtoYA0iU6tDE9YnuPZ+GK/ypsk5Xhso1VPjseG78aLZs0cD8XpC0GovMoBFWozCkiNvwGdvDfH5roMKcPYDxUDUfcix0yFtaZqhR1CJI+FyA+5tIclvS1YbLCeCFnfw3ApSMzxEGx16rltTZJG74lQW6jrZGjy9T3TSMtQWyEsz/EYHg+F2lKeUyZHxHncwJgdfF1Wv8dTa6J1nfi4q8lMidfjizL9Oq8Z3TjCkLgxyQWAeLZPXNSFB57dIzzaUlhXqI3gGR5xEmbqeA5x0Mp7z1ARDtNfuKrjMUJtY6FSV0OtAtKhYhArggMgK7G1CCIxjkLZxA6Ia4dlfa9cucDVOR5aXTenPXzy3BXYPVhQ/UTMHE8m5SgpGrONr1jd23Rqfa00nTou0U+G55EX9uLtX3kAv3r6FXVMQlmoTRm8Gqw2Y+Kd0ybyYCmjdon+J2NqhtpI5PPAiO5loyVzooorZPJ4Uk5cv26oECCX9vSCRl4X0+NR3SnJ45G/2w3D/9XLjseNb1tZdq5NUpfO7CeVM2rFfGthQKrin3/nGlx60hG6Y6f1Hdp1PIC4H+leNFltlJcaKYUoyiZyOUsVIrRyPL7noDVDpJlkckFHVucBbeWCSjCfFbEwi9e+2TCfjWo5niQs6mlWnnFS7um1i7qxcyCPrbuH6vZ4CGSMg4jjpX0jqkMtYTrTqaffGSWAJsB9wyX4nqM8GuXxGG0RGhlmAwzttSqstpy1ejW1qHyXJjke93iMHE8mFc/BCG9EbHfM/A6sNhLXlNikVVxHzPCQxxPEPI9EcoFh3MwwDFDOant2l6jupir26qy20Xs8FFYyw1v0PyByKCa5gMZFhZSBRaeu1AqbcjzUc0bleIohsmm3jC1p0nzpeqocj0+GR+fY5ndmVWV/7FxtVpsr9PHoVDtyKZRCrlbOtPJ+y+q5WDyrRXrM5b2G7DoeQDDT7DoeMhLUfC8eaovneGz2GrWRr+Tx9LaI8y2UQmXkaxke8zsmyRygcgvzeOtru46nRt2NUfCZtO1rjxJK1b96+hUEER+Vx+MYHs8Vtz6Mz939VOx9c6Ex3TD9zigBpLAs/tY3hs3KEh5Pgw2PCrckvz9cCGOrV8DweKQ+lC/DOnYBqSpo9N1Y9X8YRUog9Ob3HIcrTzlSHXtWSwYplylj0Jm1DI/vxut4KpELDEl5xphUG7Y8nrSYVEk8lYo8k3M8ccOTqTPHA8QNT1xxWfzd1pSKeTw0LqJTR1yH0UxP0gbln4hcQBTrYhCh2dehNrou5ndvd6ekUJkZ6qx2riOlOJ2aMabCdXQMugfslbfnyo6dFuvLruMhkFE4ojOLd594OE4+qluNg5QLyOsatFht9sKtW4bbXNf2eMRnkLxUjNVWwxjEpH6M77xyHY/OhQYRx96hIp7aOVC3x0PwvfJtD+/M4rD2Jtz71C71GfXC9Ij7h4tKfYMwk+M5xMGYlr/wY6ttGWozJHPsB2T8ny1+Vysgzfnlhodk381QW2Sw2pJk+lXxY1j5gXIka4qS8iarLSNrTMrJBckej/kZac+JydEA2uPp6xeGhwomk1htNOkQM65eVhtgGh6mPD3xv/i7rSmlwhgi1CbGZRZakhaakM+Jn6tveXSeK7+TIFLKE9m0V6aIYbKt7O6U9J3ZxZFJsOnUNB4yXuSZmK0ezDoZV+YI7fOyiRj6b01MufFtq1Rdkel5pVyGnO/GWkLYrDYA6G4RY7M9HrpWXc2+kASSdTwOKw/L2TC/Y9/wcmspAGRk7ddX7nsW77rlt2VabUkwlQaSQm2MMZy5fBb++9nd8rzGYHgiLkVp463ETaHe6Ya6zogx1s4Y+z5j7CnG2GbG2EnW+9czxjbJnycYYyFjrFO+d5187Y+MsQ8a+3yCMfaSsd+bG3tqcVCeJ063JXKBnswb7vHUSCAOFcIYsYD2CSNYhodLJpkmF9AKj1bRNHmbYbAkzOvQdSIxVpusDxkphbGQF63uTQgqqhFrlzL3gGYH0jUnT2fn/hF5zASPxw61jcLjObJHezwxqq1peEZKCKTXSOMyQRp2gVXHA4hqc0DXAHkOQ0oy/Qblfs1p19AAFL9NYgntS99Vkx/PcVQ9V19cW/K4KhoeQ38uXkgrczyW4TEnUpspljgOI9RGLSfiIqHlxBwiGJTRqT393VBvnpJ1T1VCygq11crxBJEgDaUk63D/SAn7hkt45UChpsfT25JWi9ZK9UXvP/XIshYr9cAUBC4FkcolEWY8HuBLAO7inC+FaHO62XyTc34T53wt53wtgL8BcD/nfC9jbCWAKwGsk/u9hTG22Nj1H2k/2Xp1wkA3TywEoZLj8dVhI1GrLQIxomL7MIZQ9oihDotCJgdxjyfUrDZAqxeYOZ4kzO/UdSJNBlU2k3JF+CQfoFAKFREjJUM15VXf+lq1ZDz0Sy/KzvHQqZPHY4bRylhtRpFkNZgP+PyOrMq7eAmhNpHjKapjtyYYHpLPset4AKBNeUhah41yPFSH1WSG2ijHYxQP2wZhtKE2QNci6RYRYlwxw1PSIVKC6zgoWXVf5jjNYwKVJ1iR44k0ucD3MFQMVIg3ijjs9Q6pF5QpF8jxtWZSUioplPp/tZ+/SjmeigWkIVdU+0CGRgHhwdbKJzHGVJ7HLiAlzGlrwrtPOEKc1yi8k5jHE0Uq9EsohsJg1mOMDzXUPCPGWCuAUwB8DQA450XO+b4qu1wE4Db59zIAv+WcD3POAwD3AzhvfEMeG2gS9I0JjeiR5kTYeFab+F1hMYbhQlhGjXVl3UVRJnF9V+dPaIKILFYbAFVgGNbw3MjjyaREszJafac90Ydl73BRtb1mjBnqAlZi1ngglvS2KMKCHWojULFnzOOpyGqr4fEY16w966Mj6yPlVSIX+Ng/UlKGwx4XoI2KXccDQLHgiFxAxrgY6BBaU0qTC3SoTewfRgarTYXaxBhqaXsB2kgRJTxdxeOh8cQ8HofJfjxVWG1u+XWz0ZRykS+GKAU6xxNxHYJMypkQM86e4Omeam0SRctUH1TPJFsmmVMjx1MKuQrJBQa1HahvoUl5nmqKClefvginH92jikrrgdmduBTyMo+H2pxPR9RzVkcCeAXANxhjjzLGvsoYyyVtyBjLAjgLwA/kS08AOIUx1iXfezOA+cYu1zDGHmeMfZ0x1jH206iNxFBbgsfTYLtTswPpYKE8x0MeDueQrDZHPdxJkjk61GZ6PNUMj/B4aCWdkXpsjsPQkfWRL4l2A1paSBzLfGBt43b07Ba8sGdI0X4ZQ0J1vWbhEcrIBXXW8ZidHtuaUujK+fBdFktMm6G2fClSHkNrguEhdhbn5Q0ByThQqEsVkIY6/JVJOWXkAnNisQ1Cky+2rcvj8TUrEzBCbWnL4wmjRMOtWJJB/B6METESrlv5OCTJwWBb0ufSeZax2pqTQ21lHk8QYjBf7v0nITZWk9VWSZ1aKhRQyNG8j+tZaFKep5rh6WpO4xuXr8ORPeV1WJXgqevHlUSWqelYDKJpGWYD6jM8HoBjAXyFc34MgCEAH62w7TkAfsM53wsAnPPNAD4H4BcA7gLwGAAy618BsAjAWgA7AHw+6YCMsfcxxh5hjD0SBEHSJnWBVrlJOR5zddhoj6dmW4RiUM5qY0ytrn3JyKMVM3lpZlsEMiBUpxGE1ZOm5PE0GfkGMjKdkmywYyCvrlU6weMpWdTzZXNaEHHgmV0HFKsq5TIk1eJW83ieeGk/ZrdmahbxetITbJLkh1Xz2rCopzlGDjFZbYAuBm01vAw6N1Ps0lZ1oNActZSgSawUmp6Ma4Ta4uQCMdlpAwUYBaT15HjsUJv8nJwVrqvo8cjcRjmdupxoYx4/aRw6x1PuCScZnlOX9ODDb1yCVQalHwBmt2bQnPaweFaL8ngG8qW6PEA71EaLjbBCqK0kdQW1x6MJEfV4PCcs7ERrxkNvS7rmtqMBXSu6h8KIx+jpwuOZfgKhQH1tEfoA9HHOfyf//z4qG553QYfZAACc869BhukYY5+RxwPn/GXahjH27wDuTDog5/wWALcAQC6XqxCwqg0datMPFTXJMsM2jc7xqALSijmeZHIBFSsSuYAmRlKqDTlXNQm0ejbJBdXOg3I8VISZSblqoqJJbMe+kTKWVtHyeMwV89LZQmvsqR0H1EqNaNb5UoSWtKfqZpI8nlIYYdeBPO57+hVcefKRFcdugiR+AOAf3rEGAGISLiarDdCGxwy1Nac9FIKiMvSAKaCawu7BQrLHIynuqj7H8HjoupgtMfKWBl1SAWklUEjNzvE0+eL+NRUiaMVc7vFolmSSJmGSfI6NdMrBSDFUoUbV+dNoomffd02+i2tev7jsWF3NaTzxyTfJsUqPR2re1YJNA6+pXCANpec4CEMek02qh0x0/IJOPP6JN9XcbrSgcVNeDhAyTqZM1nQsHgXq8Hg45zsBbGOMHS1fOgPAk/Z2jLE2AKcC+In1eq/8fTiA8yENE2NsjrHZeRBhuQmDJhfoSf7C18zHd993Yowh1WhWG00+SW0RzBoQE6bhoToeFWoz6ngodEWTr6q+r5Hj6WlOi06YqoreUcaAwjY792uPp1KOxyQwHN6ZRVPKxeadA7GVGk2Si2fpEEQlVtuPH30JYcRxwXHlfY2S0OS7ZSvkpAmUvAqqkzBZbc1y0jZXmnlleKTHQ+QCo8kbkQvyRn1OmgpISSfPYDRqVpvYZumcFhzRlcXc9vKCURu0KCCVZLpmXTkfXc1+7BomeTxCJFR4yC2Gd12pjqdSEt2u46Hz0x5PbSp08vlJj2ckGJPHUynH8/2Nffi3+5+T+UimyxTC0eV4Jgqu8nj0eEyCAZGLJgOMsbMYY1sYY88yxsocC8bYW2VaZJOMQL2u3n2TUG8juA8A+DZjzAewFcDljLGrAIBzfrPc5jwA93DOh6x9f8AY6wJQAnA157xfvv73jLG1ADiAFwC8v86xjAlJOZ6WTArHL+iMGYWGs9qqtEUwa0Bi+zh2qM1RE5dvPGSVOmKGNVhtjDHM62iKhdqolomUDA4UAhxhtY+IqyPEw3mOw3D07BY8teMA5rRndJgu5QL5AEfPblEqvnEyhwjHFYMIGx7bjmMOb4/1pa+GplSS4TGT5PFQ28vK8OjrnVOdWcs9HqIC0/6mZI7K8Rg5KbvdhkmXtVlt6xd14/7rT6/rPMs8Hnltrz79KFz4mvnq9aJRqxNnb2oljN6WNPYMFZWenH2tzOPboFBbNhQ5QXtBEiaw2upB2hNqGQP5UiLj0EbKIhdUUqf+yaaX8NK+ESyf06pkjqjnEKHRC83RgMLCI4bHY9byFINwUnI8jDEXwJcBnAkRkXqYMbaBc246GL8EsIFzzhljqwHcDmBpnfuWoS7DwznfBOB46+WbrW1uBXBrwr4nVzjme+r57EYhKcdDIEXoWmywsUC1RUjweOzuowTXYaoinERCaYKjSS2W47E6YtZTGHfBcfPVNvM7suoG77REQ4FyAgBA/Xjin7FsTgvuemInupp97S3J4y6Z1VJ2XEBce991sGN/Hk+/PIiPv3lZ1XGb6GpOY3Zb3GNwHAaHIdaquF22NN4phVGzMkQVRFy1N6bOrIA2Qsrjsep4XOnxlAIzd1POalOhNsPjGctEolhtVqitPeujPevjD337AQjjXQySPB5HKXCTh2erAyQpF9hQ5AKpqEHeJd13duvrepFJOdg7JMgfo/Z4jNqtIOSqrohUFQ7kA0mn1s94IQjBGImaTl0oixYmZs4p5vFMHqttHYBnOedbAYAx9l0Ab4UR2eKcDxrb5yAchrr2TcKrovU1YBieCjx7lzGEqC2hMVpQjicp1GY+JLGxmB6PK7TSCkbOByCPR1N5AWvlWWPp+T9PW6T+/tRbVyotubamlJq4beMR6/mTUKS6dHYrbntoG17cM6zGSdf7aNPwWN+B7zr4095hAPEao1r4l4uPSZwkPUeEwWgyndWWhuswPCPp3mlP1C4FxVCFYM0KfDISJOeiW4Lr3AgVkKrQVoxcIOt4zBxPEML3nDFOzNLjsbQGCUQ4KVVgtZkLFzpf+7urh06dSbmqZXjK063VVagtKicX1IO052KoGGC4GMaIH5WQMkKajsNiJI4P3f4YODj+7T3HY6gQ4EC+JBdijlTpFt7n/I4s/rR3uGYdz0SCbJ4ZajMliCYx1HYYgG3G/30ATrA3YoydB+CzAHoB/Nlo9rXxqjM8lVZzjgMgnABWWxV1auo+mrPJBczK8biOoRMmDQ/XHg9NTGaOp55CPIJ5cxOles9QMSHHYylgW9dq/SIhmPiHl/ar9sG+KxSKZxmeie11+p6DbdLwJIlkVsKctmQj5ToMCHVIJu25WNCVxTNSny7tiTDRUFHr5MVzPOI6vnnVHCzozimjGVMuoByPUp026dTS4zFDbaUoRgEfDcxQW6V2EECVHI/jqPupWerU2d5qLMdTJdQGiMnRd121nVrwcA6XMZRKJfT19SGfzycex8bFR7vIH9mGiLehPZvH5s2bq24fRhz/fu4cOAzYvHmz+r8jtQ+zjnYBzrF582b8zUmtCKIWZDwHETwwkGck8mIjpTa0NQ3X/LyJQiTH3Zwu4cRzRcq7I9qDzZuFB/v+1RkwoOr4MpkM5s2bh1SqpsH2GGOPGP/fIolbAJA0WZRNWJzzHwH4EWPsFAA3AHhDvfuWDabWBtMF9MDZvd4JZCAaXsdThU5tdx9VY3E0fZro1KpXSQWRUEDQqTnnGC6EsbYBo0VHjgxPZVZbkKDkvXhWC5bPacWTOwZiOZ7e1oxiy6UTVuy+52CHzL/MHoXhqQTPZUApPpku7m3Bc6+QOrb2TloUucAItalJ2sO5a+air18YRRVqc5jK8cSlheh6xT2eiIvwTqV7rxbo/ggMkVgTJrnApm3T9aB7hWqYbK+m3lCb2t7TNVMlxWoT93tfXx9aWlqwYMGCunpb9fUPY69UvZjfma1Z2xSEEaIdA3AdhmVz24SO4Y4BpUEYcY6ls1sRbd+PUCpGO0yHYAulUHmxHTk/0ZhPBoIwQrhjAB1ZX3U5ndOWQY9U7E7tOgDXcZQWoQ3OOfbs2YO+vj4sXLiw5sdxzu10CaEP8frKeQC2VzoQ5/xXjLFFjLHu0e5LmJ5cvQRUy/EA2kBMnHJBueEht7pMMseJG5rYpJDIatMeT/9wCcUwwqyWsU/glOehkFhF5YIEr+q8Yw6L7TOnNYOjeprR1pQCY8nX3/cccC4EVXsaUCuh+y0Zhsdk1RneiSIXGAneYYO9Zh5npBTK2iSm9POolbep8KDqeEzJnFJUU3G7EpLaSJhQskMxskMyU5NyPNVCbUkqzEBcH88sICVCA+ccrgPk83l0dXXV3VDRDM/ZYqJJoOOq3/J1DpG3oVbjVLQdRhyMie05OCKI53Jue9OUGR1ACwibc4NJQop4sjuh92fo6uqq27OsgocBLGaMLZQEsncB2GB91lFMXnDG2LEAfAB76tk3Ca8ij6d6qE1J2U+QVltSicFISSemk/YBEgxPTLmgPMdDzC076T4akGK17tRKSdDKkjmEc9bMxWd+vlmN8wsXrlHn1N6USswf0Lbdzemq1eH1gsZlsp9MphwJnwI6v2aGEfOleFiT7o18KTQ6uzqq4M8OSVKYUxFLIpHjyYyxGNBxmGKUJRmetKtZjbY0DxAvFFU5HmuBVa9Wm7kNhdqKRqjNsYxCPTA3ref5oy1olLQ/58L4hZH8W74fRBxpuR9t08guw2MH5X/1K6YR4hyodTkacR6c84Axdg2AuwG4AL7OOf+jxVx+O4BLGWMlACMALuQicZ24b63PfNV4PO1ZkTRvTpBLAfQN33BWW5UcT6UOgzZrx87BiJBBAqst4EoJelbr2D0H3fJYa7gBlsdTQR1hdlsGl554BF63uAeACBOZfWOSyB10fuMZs4lEj6dXkxsyKVedW5JEizY88p6Qx8mXIhVeooT+YCFQE7KtTm2G2vKlaFzy9vQdJy2c4qG2SMkfEZI8HrtWp1KLhKQx0GeWh9rGRi6IeTz1GB5Gv8njkRM4uPB6wOG6Dj52najQ4JwjDEMct/QIvO/d7wAAfO8730JPTw/Wrl2rfp588km88MILYIzhn//5n9XnXXPNNbj11ltHfV71nkfc4zENz+QZSM75zzjnSzjnizjnn5av3UzlMpzzz3HOV0hB55M45/9dbd9aeNUYnpZMCv/3ihMqFifSzT9hHo+8oXYPFnDn4yIESobDftC9Mo8nHorwHCGBQhIhTQa5gIoke8cRajPzMeb4yFBGEUfEK1+rT751Ja54XXnMuSPnJ676aeJsRH4HQMwrIRzZk1OrR9OY24xCQHui5BXErr/8mwzAgXxJGR5VQEoGy5LMGavHA+jvuFaOJ18KywycGUajejb7nnMdLW9UrY6HIDyeeKgtqRFcPRitx1O2nxFro0k8l8vh2S2bkR8RrTh+c9+9mDVnrnKDGIALL7wQmzZtUj/Lly8HAPT29uJLX/oSisXiqM9lNKBhm2tS0/BEiF+b6YRXjeEBgPVHdSf2YgEMj6fB9EotFCnUAN5584O45juPYvdgQXdctD7TXAH6Rr2EGKcI4Zjq1PFQm6hV6W2Ex2MVRJrspaRx18KSWc2Y35kte13RnhtkeFIJobZMysXhnVnlDdDkanrANOcRlV15PKaKsxO/JgP5wCBSxN+zRULH4/FQHi/JKLiSUlwMQ6UqbiLWvkLRqePHYUyTBSqFo2NSR1KCBjBFQse2cHMQX1jVAmMMTPk55TkewutOewN+fe89AICf/ugOvPX8d6jwW7VP6enpwRlnnIFvfvOb9Z7CuEClFg5jsXq/gyck2Hi8qgxPNWiPZ2LIBSHnuPI/HsHW3YJZlTdaGduTQKymwrNCbYzBZUyJPrrGJFoMIuwcyKMz59fsZ1MNdqjNLiAlba7RXqsb3roS//ae48peT0+AxyMUEeIP7VG9LWXCp80GlZ0MOOVyaP94q2Xp8Xjk8RihNisnZNaX5Evj9HiqhNroderHY5MYTMPZ5LtgLHnRYJMpysZgeTw0FqXVxvmYVuhm6Kze/YksoPaDzt8Awgid9dbzcdeGH6KQz+OpJ5/AMce9RgbjxAG+973vxUJtI9I7AoCPfvSj+PznP48wDDFRYMaiFBD3TRQLtU3fCfpVQy6oBd28q7HHZUTjjDie3TWI7ua09HY0K82eTGyPJyZfb1RgU/sD0yPZNZAft4puR656qI2kSUbr8VTqteI32OPxjGti4m3HzFWeoCIXGFT2Jt/DUDEUDcKMlbupbGGH8Q7kS8pg2qw2+h6pB8xoulPaqBZqo9cpx2PnDO3+NRnPTczPiXMKK36v5vh9z4kVrgLUCI7BLOP44F0fxKadm6qemyjqDMEYK+tNlYS1s9fiylWfjBspxsA5jxWQLFm2Etu3/Qk//8kPcPob3hTzchyIUNu//Mu/JH7GwoULsW7dOnznO9+pOZ7xgMlxA1pTj0BMz+mI6WpQRw13gjweQLvQhSBUdRQlQ1erWqLXZrU5chKMuMjxpBym2g8MF0O8PFAYF6MNMOjUlneg2EsReTyNeSoUuWCc4yZ4LksMmb5l9Vx85rxVAHRYzAy10aQnaNPJeTc7jBfzeCwWoJnfy5fCilT+ekBjq3QM39MFrbaBsxu+ZVJO4iLA9uZsxOp4YpI5RgHpWO6JsdxGLL5AY0guWTj1jWfjCzf+Ld769nfEP6eOGf1jH/sYPve5zyGq0OenERDjFn+7jqM8HmFEp2+obcbjkdB1PI3/oh1Ht66mia4YiI6LtlijORYAsq+NmeMhlV0Oh3EVEjp6Vgv+8NJ+7BzIY/mc1nGNl2ppKPGuPCrZSIw8tUZdq8aTC5yKISn1mS6F2gyPJ6UNj224Uq6DQqA9IdpfsNriuRGakGOSOaVozAWkgBFqq2R45PiSPCubsZZJuYlejTaqowu1lUJRNyPov/HjfvGsL9Y6NQyMlPDCniFkfa9ugdgntw/E7QiAWDse+fd5F16ClpZWLF+xEg/85tfq7Xpu3aVLl2L58uW48847sW7durrGNRaQwWT/vdEAACAASURBVPQcJqngXOWqpqndmfF4CMrjmQDtJpcxVZTYYng81LveXtXYE4U5ibrk8UjlAlq5rlvYiY0v9mP3YGHctOS57U342mXH489WCxkPM3kNaI+nUb3g6fwaZXhSFUJtsc+UE7ipGkFqD/liWFbnYuuvmWKtdi6MQlBm99lCUJ57GQ2oVXYlg5r2HM1qqxJqS7lMCs+WH4e2q0wuMENt2qsshZFatY+FTk27jJbRZn4UY/Euv/TXvHnzcckVV6k8kAk7x/PAAw+Ufc7HP/5x9PX11T2u0YLESgHx3HMIo0PGyBmTO3jwY8bjkZhIj8eUwGk2ChZLYZSoqUYPIE34KaOS3HEEuUBUY+vQxrqFnfiPB18E0JiQ1RnLZsX+N2V7KLTSyFBb2nPqagJWD1wnOdRmfyYgQlgkpZIlckEQltV72Ww2U8/MVnhI2R6P1GobD+GjGquNXqccjy206VoLmeaMl1ixn5JKz5WETInIIhr9uboRnCHfNJa1iCL2jLLoNG7kWCzU9rstfeCg+1a89tqTT8GStUK/8j2XXoarrrwi8dhPPKFbg61Zs2ZCQ20AFOGBFr0ms226ejwzhkdiopQLAMj8C8njiEmhFIpQW5Igo2uFc+J0agZXaW/p0M+6BZ1qm/HI5VQCsaYAw+Np0LW6+ITDcdwRHQ2LZ9teYhJIVy3tiXxHMYjU5F4Ky5W37byNTdWmYwHl3lEQcRTDsUvmALVDbaZoqe3xmN6f5zj47HmrY/katZ3j1PQUm1KubIug1alFGFmu0MdRxzMaozWvvSnmcTMWr4fhEIZMKynE95+Ax3xMkHw8APo5F4W48v1panlmDI/ERHs8JKnfEsvx8MQHnVZ+diU8Hcslvn+kJ7fe1gwWdGXxwp7hhrHDTFDyGtCFr40Kta2Y24YVc9saciwAMaZfJbRkPJVkJ6MaS55boSjb4JiGTbePEPsrrTa5D4VZG8Jqc5OPYXo81SWYGI7qTc4BeoYxqTaO/SMlpKQ+neeI9hDK4xmHcsFoFn3NVj1eErnAbJlgB9oOmgndGIbOmemWHgeLgWw0ZgyPhKtWXY1Pe7mMYaQYFwQtSo8naWXuWmEdU7TRZSIUEkQcnMWN0rqFncLwtDVGesaE6fEQnXoquzdWQ1ezH5P3ScJl6xfg5MXdALSHEmuBnkAuAMpDboA2KN0tPg7vzGKxTJDTJEyGZzystnrIBaWKHo8+l2oiuNRmva5xGESEIOLa45mkHE/5QRIMj6x5Mz9Dvzf2j2okmPHbrJej7+kgGWbDUZfhYYy1A/gqgJUQfuGfc84fNN6/HsAlxjGXAejhnO9ljF0H4EqIa/jvnPMvyn06AXwPwAKI1tfvNNpiTzp0XqXxx2YGuUCLUspQW8IKk8Zg19HQOFWhmcWIu/iEI+A6DrpzjTc8Kc9Rk3nQYFZbo/HJc1ckauOZ6Mz56MyJ8CRdX5subILONanIkgpDs76HX/316ep1muOp4d94PJ566NTDw0EindpcTFXqtQMIA1UrRGlTxz1XMjalnR9LqM11REhsPE3PGFjZd+4a+SqrvOig8XiU4WGyLAJMtDdJcfX6dES93/SXANzFOV8KYA2AWGcizvlNUjxuLYC/AXC/NDorIYzOOrnfWxhji+VuHwXwS875Yoh+3h8d/+mMHROlXCCOafR4ycQNT1K4isaQFGpzZNw6lMoF5uS/dn47Pnv+qjE9/LWQmOOZwu6N1dCSSaG9Rk8XE0TwMA1PuZoEeTwUBtXnXq2rLaBbnI+P1VabXFCoUEBqEliqNQg0FacrIWPJAvmuaKtNCfGx3BKe42Dp7BbVYnwsYIbHQ4sxx1iYMbCY+3DQ3LlM/2JMEImK4QydGoyxVgCnAPgaAHDOi5zzfVV2uQjAbfLvZQB+yzkf5pwHAO4HcJ58760Avin//iaAt41++I2DLezYSLiMIU90avJ4Ao5ikJzjsWtFyjweSS4Iwsa36q6ElGt4PBGx2qYHG5+MSjalAwD2BK3JBQmhtgqTNX03IyrUNv46nmoez8sDeRSCSClP2OMAquflPLc+cgGgr0fKdVAK+LiLir2EsoLRwMzxmHVUZqjNzPOMJSQ4EaAx0bnTAo/UDF7NHs+RAF4B8A3G2KOMsa8yxhJb4jHGsgDOAvAD+dITAE5hjHXJ994M3a1uFud8BwDI373jOI9xY6LUqQERfhi26NTFMEIQRfATlojksRCNOlbH40CRCyo1Y5sI0Ioa0KG20bTXPphBk2iTb7C/KqhJJFX3VwqhkfbYULG8K+hoUYtOnXYd9A+XAACvO6o7Pnbj/qlGHmjNeEpZoxKabF06V5ALpnyiND7Wcxhu+sTH8PV/+7J6lt75trfgL6+5Sm3z4Q9/CF/4whdw7bXXYuXKlVi1ahVe85rX4PnnnwcAnHXWWVizZg1WrFiBq666Smm23XrrrbF2Cl/96lcBAC+++CKOO+44rF27FitWrMDNN988uuHL8VOurniQh7PHi3pyPB6AYwF8gHP+O8bYlyDCYn+bsO05AH7DOd8LAJzzzYyxzwH4BYBBAI8BCBL2qwjG2PsAvA8AfL/+8MloMVH9eABh1CjHY4fa6vF4zEnQkeSCMBLu+GR5PH7M42msZM5Ug76DtOeqgr6yHI/6Lso9nmqq0y5jqsX5+NoiVC8gJYPU3ZwuU66op9cOAPyvP1uuWmdXQsYygL7roBRxHWqbonvC9GY8l2HN8etw/90/lcXWEfbu2YMDAwfEtozhwQcfxFlnnYXt27fj8ccfh+M46OvrQy4n1tS33347WltbwTnHBRdcgDvuuAPvete7ACRrvM2ZMwcPPPAA0uk0BgcHsXLlSpx77rmYO3du9XEboTZA5lKHIwwVArgOGxch5WBGPWfVB6CPc/47+f/3IQxREt4FHWYDAHDOv8Y5P5ZzfgqAvQCekW+9zBibAwDy966kA3LOb+GcH885P97zJo6E506gx+NKyRzALCCNUKoQalN1PAk5Hs9xpLSGzPFMBBsiAUTXBUw69fQyPClXNzezFyApKxSbRC5IguPoRUdDGsFVCbUBwKlLespyfHHlgspjmN2WwRFdicEMPQ4VatPXrBSMj07dCJif6jkMa48/ARsf+i1cBjy3ZTOWLl+B5pZmDOzbh6BQwObNm9HU1IQ5c+bAkd/5vHnz0NHRAQBobRXGOwgCFIvFmp6c7/tIpwWpp1AojLro1Ay1AUJGKOt7r95QG+d8J4BtjLGj5UtnAHjS3o4x1gbgVAA/sV7vlb8PB3A+tGHaAOAy+fdl9n6TjQnVajMOqSVzRFFh0uStDU+5FL7jQJELwkkMtZnKBaGiU0+P1ZhmqmnFgzJygWWQ/Do9Hs9hqnh4PDmenpY0HKZ19GzQeE47uqfsPTISSbqAo4VteISi8vhYbQ2BGWpzHfTOngPP8/BS3zZs2vgQ1p1wAo47fh0e+/1D+OMfNmH16tW4+OKL8dOf/hRr167Fhz70ITz66KOxQ77pTW9Cb28vWlpacMEFF6jXf/CDH2D16tW44IILsG3bNvX6tm3bsHr1asyfPx8f+chHano75rDtJnwh53UpdR+qqNeF+ACAbzPGfABbAVxu9eMGBGngHs75kLXvDxhjXQBKAK42KNP/B8DtjLErAPwJwDvGcR7jhlIumAAPwkxkkjYYiYQm1vGo1U881wMYummBYBJlUpOX4yGPpxROs1CbwSJMUiYw/9ehNv1+NY/H1OkbD536sPYm3H/96ZjX0ZT4fnPGg+swVZsUG0OClzZWkOdlkguKoVnHE9/+mQ8+g8FNg+P+XBPNa5ux+IuLY6/ZHg8ArDvxJGx86Hd48tFH8NG//hCef3Eb/t99v0ZrWxvWr1+PefPmYcuWLbj33ntx77334owzzsAdd9yBM844AwBw9913I5/P45JLLsG9996LM888E+eccw4uuugipNNp3Hzzzbjssstw7733AgDmz5+Pxx9/HNu3b8fb3vY2XHDBBZg1Ky49ZUO37xYwv6Pcq93wcM43ATjeevlma5tbAdyasO/JFY65B8J7OihAK7WJCBWYE3Qm5UjvIUJQSbmgSqiNREJDLlhtk+fx6BwPhVUaMZEdDCDDnjJYXWUioZbHQ62iOUdV1elYqG2c8fqk7q2ES08SBbFJNHIyrI0gg5x0ZBde2jcSa5JXCqKpz/EYzy19RyeccBJ++9sH8fwzm3Hs2jXonjUXn//CF9Da0opr/+J9AIB0Oo2zzz4bZ599NmbNmoUf//jHyvAAQCaTwbnnnouf/OQnOPPMM9HV1aXeu/LKK/GRj3ykbCxz587FihUr8Otf/zrmKdUzfqrlATia/Olb3z99z2yUIIMzUeQCQtpz1SRer1ZbrI7H0erUohHc5OV4CsrjaaxI6FTDNCp2oajaxo2/Lgr+hBdYzaC4DsNAXrDNxuPx1IJZEFs2BuU5j/9eOX1pL05fqgmodC+TMrRNU7Y9k4mCDllpmZwT16/HV/7lSzjyyCPhui46OjtxYGA/tj79FE466Rv4/e9/j9mzZ2Pu3LmIogiPP/44Vq9ejcHBQRw4cABz5sxBEAT42c9+hpNPFuvnHTt2YM4codq+YcMGLFu2DADQ19eHrq4uNDU1ob+/H7/5zW/wV3/1V/WP2xh/ymNwmTNtnq8kzBgeCVMReqKOTS2HacIqVlQuiHs8dlsET0rmhFHy/hMBP8HjmS5Uz5QxMaukuWXQtSekz5lqLqoZFIcxVQw4HnLBeECezkTk5FKug6FieBB4PPI3hIHP+h4WH7MWu3fvxsUXXyy3YVh89HLkh4fQ3d2NRx55BFdeeSUKhQIAYN26dbjmmmuwf/9+nHvuuSgUCgjDEK9//etx1VWCiv1P//RP2LBhAzzPQ2dnJ2699VYAwObNm/GhD31IdRT98Ic/jFWrVtUx8Pj4AdEe5GCpM5oozBgeCfqiJ4KpRc9iWgorUlxctEWo7PHY3S4BsXrVygWTV0CaLBI6PR4OswrfreTxqNfLa2Kq1eeY0cjx0KnHA+1BN/77SrkMQWiQC6Z4wnQYg+c6qqHcwMCAeo8BuOEf/1W1Oz/rrLNw1llnlR0jk8ng4YcfTjz+Zz/7WXz2s58te/3MM8/E448/Purxmp4OYTSqG4cqpkeQvgGgCWKiCkgBzWryZY6nFPIYcUCPJe7xmGNSjeD4ZLPaBG0WMLXapsftY9bmJGmxxbZJqImpxlajEK7DqhdvTiTsGqRGQoXaKpALJgtaAaDKNgnexcGCg3BIE4rpMXM0AG6F+o2GHJuR4dHsqWoFpHZbBMa0eKPZ+lpI5kxujodzrujU0yUGnTLo1CoRX7Efj+nxiL+reTzmomOqajJs1YWGHtt1UArHL5kzXozGqEy1V2ZCsdqmeEiMsbMYY1sYY88yxsp0MxljlzDGHpc/DzDG1hjvvcAY+wNjbBNj7JF6Pm8m1CahPZ6Jo1ObLDUyPEl0alp1p62wTjGUUu+KXBBNmsfTmfURRBwD+UCF2qZqBd9opJxyj6diHY9xzvR9Vsvx0EQ8Hrmc8aKSF9cIEEMzNBvBTWzDzkTQt1LNqNTjFU02kkJtkz4GxlwAXwZwJoRgwMOMsQ2cc7Ne83kAp3LO+xljZwO4BcAJxvunc8531/uZMx6PhFYuaPyxyZaZbQ6KAa/YCI4eHvO9lFfu8YQRV4yliQa10941kFehtuni8ZgTs/IOaigXACIn5LDqXrI2PFNXk5HUQ6hRINIJ51OrXGCqPFfcRL55MHk8hCke0ToAz3LOt3LOiwC+CyHirMA5f8CowfwtgHnj+cAZwyOh6ngmpC1CPMeT8hwUglDkaBIMh2fleAA9aThMPNxEp54soc5ZsmL+5YEC8lLwdDz9Uw4mmCSOSvmQJE8o5TFkUtVDaHaYdSpANUcTQQbxXIYg5AinmFxgqzwnbyN/H0R25yDJOx0GYJvxf598rRKuAPBz438O4B7G2EaprVkTM6E2icmo4yE6re/qosJEjyfB8NDqmuoUQs4RTmKOh9ppvzyQx/b9I+hu9sclAXMwIZXg8ZSz2spzPynXqenJHAweDyDu64kJtQm2I+V4popvor2ZahvRtgeR5ZGYhDF5Vv7lFs75LfTxCdsndlJkjJ0OYXheZ7z8Ws75dimP9gvG2FOc819VG8z0WLI2AK5KHk+g4TFCbWR4EnM8iR4Pi/UZCSOOUpSs9TYR6G2VHs+BPPr6R3BYR+Uq+kMNusV4tTqe8vsj5To1PRm96Jhqw+NMSE7OZrVNtUioOYF/+tOfxooVK7B69WqsXbsWDz/0EK54x1vwh00bAQALFixQhaGEtWvXYuXKlQCA++67D295y1vKPuu0007D0UcfrVojkDrBtddeixtuuCH2+VdffTUA4LHHHsNJJ52EVatW4ZxzzlE071KphL/9q6vxhvWvwZo1a3Dfffep/b/3ve9h9erVWLFiBf76r/96fBcICEhsWf7cYrzXB92uBhBhtO32ARhjqyE6Ub9VKs8AADjn2+XvXQB+BBG6q4oZj0diIj2eslCb6yjhyKTJQPXjMVWpXUetJjuyPvYNlxDxyavjyfoeWjIedg0U0Nc/guVzW2vvdIjA7C5qKxTY25gGyR+FxzPV8vYT5/GIUJvd/XPSYXk8Dz74IO688078/ve/Rzqdxu7duzEwNBLfGMCBAwewbds2zJ8/H5s3b0a9+Pa3v43jj4+riN14441Yu3YtLrnkEjDG8NWvflUJj773ve/FP/zDP+DUU0/F17/+ddx000244YYb8N3/+AYA4N4HH4ZbOICzzz4bDz/8MPr7+3H99ddj48aN6OnpwWWXXYZf/vKXMTmfBuJhAIsZYwsBvATRZeBicwMp8vxDAO/hnD9tvJ4D4HDOD8i/3wjgU7U+cMbjkZhI5YIkj2eoIENtCROSlzBZpVxHGcdTlvQgiDgiPrnqAbNbM9i+bwQv9Y9UFKs8FEF5spTnJBaKAkgMwaXc2v1SnIMl1GZ4zI1EynUEtT+a2kZwKscjf+/YsQPd3d2qVUF3dzcOk2rR5gjf+c534nvf+x4A4LbbbsNFF1005jG0trbi05/+NK655hpcffXV+NSnPoX29nYAwJYtW3DKKacAEMWmP/iB6JX5zJancMLrTgFjDL29vWhvb8cjjzyCrVu3YsmSJejpEWrjb3jDG9Q+jYbsDn0NgLsBbAZwO+f8j4yxq0gMGsDfAegC8K8WbXoWgP9mjD0G4CEA/8k5v6vWZ84YHgmlXDAhdGrxW0ngeFoqP1G5wOrNIf5mahI79vB2tGdFf/rJXGHOas3gj9sHUAwjzJtGobbDu7LobvbRlHJ1LqeM1VZezHvF647EdWdU1yIjO1WpPfZkwXUc+AnFyuMFXZdCaWpru+wk/Rvf+EZs27YNS5YswV/8xV/g/vvvL/OKAOCCCy7AD3/4QwDAT3/6U5xzzjl1fd4ll1yiQm3XX3+9ev2iiy5Cf38/BgYG8J73vEe9vnLlSmzYsAEAcMcdd6h2CstXrsJ99/wcURDg+eefx8aNG7Ft2zYcddRReOqpp/DCCy8gCAL8+Mc/jrVgaDQ45z/jnC/hnC/inH9avnYzdR/gnL+Xc97BOV8rf46Xr2/lnK+RPyto31qYCbVJTIZWWzzURh5P+efZygW0j2usxk9b0oMfb9o+qQrRva1p/Pezgqo/nTyec9fMxZ+tmgOvSh1PUmuB1yW0ILChvvsp9nhSE+bxiPOjzqV2jueZZz6IwcFNDf3M5ua1WLz4i4nv0cc3Nzdj48aN+PWvf43/+q//woUXXogbP/0ZuY0eY2dnJzo6OvDd734Xy5YtQzZb34IqKdQGCLHQnTt3gjGGwcFBNDcL6Z6vf/3ruPbaa/GpT30K5557ruqmfOG7L8UTf3wSbzzttVi0cAHWr18Pz/PQ0dGBr3zlK7jwwgvhOA7Wr1+PrVu31nuJDnrMGB6JCQ21qcmnvJ4iyXB0t6TBmGaS0XbmQ/36ZbPw403bJ93jIcyfRoaHMVZWZFlZuWB015s86an2eHpbM5jdlqm94ShhezxTz2rT34/rujjttNNw2mmnYdWqVbj11m/GVEAIF154Ia6++mol+DkeXHfddfjEJz6BzZs345Of/CRuuukmAMDSpUtxzz33AACefvpp/Od//icAIOWlcP0nPoO5bU3obklj/fr1WLxYeNHnnHOO8sBuueUWuO70YJECM4ZHYbJzPIQkw7OopxmPfPwN6GrW3SZTXlwm/dQlPWjPpjC3ffIMwCyj++Vh7dMn1GZCeZUV+vGMlhlGBm2qczzfee8JE1THIw2P9HjK2iJU8EwaDVuVYMuWLXAcR03imzZtwoIFR2Bw8ACy6fi0d95552HHjh1405vehO3by8hcdePnP/85du3ahUsvvRTDw8NYs2YNLr/8cixfvhy7du1Cb28voijCjTfeqNSu8yPDGB7Og7U34Re/+AU8z8Py5csBQO3T39+Pf/3Xf8Xtt98+5rEdbJgxPBITymqThzRFQglJdGoAMaND+5iGp60phYc+9oZJLeKkFXN3s686UU43mLptJlQIbpRLenvRMVXIpSfmUfdVqE3neMIJ+aTqsOnUg4OD+MAHPoB9+/bB8zwcddRRuOWWWxIbs7W0tCQ2dAOAX/7yl5g3Txfp33HHHQBEjqepSSz6uru7ceedd+KDH/wgvv/974Mxhlwuh7//+7/HNddcg3vvvRe33XYbvvzlLwMAzj//fFx++eUAgN27X8G7zjsHvufi8Pnz8K1vfUt91nXXXYfHHnsMAPB3f/d3WLJkyTiu0MGFuu5Gxlg7BH97JURh0Z9zzh803r8ewCXGMZcB6OGc72WM/SWA98r9/gDgcs55njH2CQBXAnhF7vcxzvnPxn9KY4MzGaG2BI+n3lVoynXKVpOTrRzQK0Nt06mGx0YleZmkfjz14GApIJ0o0PUiNQuHTY3hUcQB+e9xxx2HBx54oGwzs07mhRdeKHt/wYIFeOKJJwCIep2RkZGybcxjmNiyZUvs//PPPx/nn38+AGFErrvuurJ9Dj/iCGy4/2HM78iiIxdvh3Dbbbclfs50QL0z15cA3MU5XwpgDQTlToFzfhOxHQD8DYD7pdE5DMC1AI7nnK8E4EJwxAn/aLAkpszoANormYhwhK02nUqQwqkFUdw4tRXXlOOZTsQCGxXreCrQrGuBvvupFAmdSNC9nJ9qVhv9PghVCerBITrsMaOmx8MYawVwCoD/AQBSRK5YZZeLAJim2gPQxBgrAcgioSL2YEA27YGxiWnWNdocTxKuPPlI7Nyfb/jYRoOe5jRSLsOCruns8SSH1Joz4lHJjjLEaPdimm7wLVbblNWPJlClDwVogzmlw5h01BNqOxIiHPYN2YNhI4DrOOdD9oaMsSyAsyCKkcA5f4kx9g8A/gRgBMA9nPN7jF2uYYxdCuARAB8y1E8nHeesnovDO8vd3UbAsSi19eR4bKw8rA0rD2tr+NhGA99zcNuVJ6rujtMRXgVW24kLu/CtK9ZhxSgVG6a7x0MGmnI8U6f8HCcXHDKgfjxTrU89yajnafAAHAvgK5zzYwAMAShrFCRxDoDfcM73AgBjrANCXnshgLkAcoyxd8ttvwJgEYC1AHYA+HzSARlj72OMPcIYeyQIgvrOagxo8l2ceGTXhBybbEuixzMBRX0TieMXdE7r1rypCiE1x2E4eXHPqEM5dg3XdAOF2uwCUmqTMFkgT+dQC7WN1+OZ7OvcKNRjePoA9HHOfyf//z6EIUrCuxAPs70BwPOc81c45yUIrZ/1AMA5f5lzHnLOIwD/jgrCcpzzW0jYzvMOTRKeHWozSQHTpX30dIE3RhJBJdg1XNMNZKhHJLnAcxgymQz27NkzJZPioXaVleEZg8fDOceePXuQyTS+PmuiUXMm55zvZIxtY4wdzTnfAuAMAE/a2zHG2gCcCuDdxst/AnCiDMGNyH0fkdvP4ZzvkNudB+CJcZ3JQQxteLRyAaHeUNsMJgdJCgXjOh5J5kxTVht5PJR/bM/66Giah76+PrzyyivVdm0oRooh9gwVEe71D6lrfSBfwv6RALw/PSaWaiaTidG9DxXU60J8AMC3GWM+gK0ALifxONLygTAe95i5H8757xhj3wfwewABgEchWqYCwN8zxtZC0KxfAPD+cZ7LQQvXWvX6h3CobbojVYHVNlZQv6SpruOZKJCB7usfRlfOl5Ong4ULF07qOH7x5Mu4csMj+L9XnIBj6pAyOlhwy6+ew2d+9hQ2XPNaLJvXPtXDmTTUZXg455sA2MJEN1vb3Arg1oR9/zeA/53w+nvs16YrlOGhxLVhbCZTa20GtaFFQhvk8cjDHEqr8NGAQpI7B/JYOnvqWmUk9bA6FDCR4sQHM15dZztFoMRhvVptM5g6NN7jmd4FpDTRRxyY1ZqusfXE4djDO/CO4+aNmnU41dCCwK+uyMehma0/xOBWyfFMdVHoDOJYNqcVy+e0orNBtPqDRTJnomCSMCZChLRetGVTuOkda6bs88cKr8E5xUMFM4ZnEmB3ofRnPJ6DFscv6MTPrju59oZ1Yrp7POb929ty6LGrphpuBYmm6Y4ZwzMJYFU8nsnsIDqDyYczzQtIzZyK2TZjBvXhzOWzMJAvYc4UeotTgRnDMwlQoTaV45FxXdc55AreZjA6TPcC0niobepyPIcqelrSuOrURVM9jEnH9FyGHWQoUy7w4gZoBtMXOtQ2PR81U/B2JtQ2g3oxPZ+GgwxpzxUCpEqrTVbHv8riuq9G2MXD0w1mvnIqyQUzOLQwE2qbBLz9uHlY1JtThke3V54xPNMdR3RlcURXdsraBUw0NCuLoXMaa/jNoLGYMTyTgM6cj9cvnaX+1zme6TkZzUDjonWH46J1h0/1MCYMrsPAmAizOdPUuM6g8ZhZck8BlMczTWs7ZvDqAWMMKcdB7xQWavp/xAAAE11JREFUj87g0MPMzDcF8BPaI8xgBocqUi7D7Bkq9QxGgZmZbwqQarD0/gxmMJWY1ZbBklktUz2MGYwDjLGzGGNbGGPPMsbK+q0xxi5hjD0ufx6QTUHr2jcJMzmeKYDK8cyE2mYwDbDhmtdNW0kgG5xHKJX2oFjcgQMHHsGBAxvh+7Ph+7MgWotF4DwEwOE4TWAshSgaRirVg0zmcHheBzyvHYx5yOdfBGMppNNz4Hmd4LyEIOhHKtUDxibvejLGXABfBnAmRP+1hxljGzjnZvub5wGcyjnvZ4ydDdFl4IQ69y3DjOGZAsyE2hqHMBzB8PBTyOWWw3HGlmcoFLZjeHgLPK8VnAcIgv3qhzGG7u63I5UanWQ95xHy+T9h796fY2joD3CcLFw3B9dthus2I5dbidbWE+E4qbrOsVDYhigaQTa7DI4zOvYY5xyl0itwnCw8r1m9Vij0wfdn1zWGamhOH5rTCOcRisWdyOefRz7/AvL5bYiiIeRyK8E5RxD0w/dnwXHSGBl5Hjt33oqhocfAue6E7LrNCMPBcY+FsZQ8LgdjaTQ1LUJT05HwvHaUSnswNPQEli//Ltra1o/7sxKwDsCznPOtYizsuxCdo5Xx4Jw/YGz/WwDz6t03CYfmHXOII+Uc2gWknIcolfbC93saetwoCpDPb8Xw8GYMDz+DbHYx2tpehzAcQRjuRxDsQxDsRz7/PIaGnsTw8JMYGPgtoigPx8mivf00tLefDiBCqbQXYTiIlpZjkMkswMjIsxgefhqFQh/CcABBMIAwPIAg6Eeh0Fd1XM8++1doazsZrptFW9tr0dx8DFy3BVFUwODgJvT3/wLF4k5wXgRjKRSLO1Eo9EE03QU8rwNRVEQUDVlHdsCYC89rh+/PRhQV4XltaGo6EpyHiKIRlEp7ceDAI+C8KI/VjkxmAYaHn4brtsDzWhGGw8hkjkA2uxSMeSgWX0YQ7IHrNqNYfAUjI88gDAcAAOn0EcjllmN4eAvy+a1gLIVsdilyudXo7j4Hra0nAmBIp+dN6qp7POCcI59/Hvv23Y/9+3+FUqkfqVQnGPPgeR3IZpehVHoFYTgAz+tEKtWFoaEnsWPHLQiCfutoDoAo8XNyuTWYP//D8P25SKfnIptdimx2OaJoGMH/b+/Mg+yorjv8ne5+68ybTQuMJbSAhCLsgJAFmLDacjAQY2ywARs7BHBRrnIoQyop7CILlYor2Aku5w8qMiEUiq3EbKagUuzYhlBlEEJIIMQiCQQajTQSmtHs89aTP/rO6M1oFo3QvH7SnK+q63Xfd7v716fvu+du797CfsBHJHynEBYYVPN4Xop8vo1stsWl4f2USjmSyfmoFsjldpHN7sL3UwTBDLLZD+nr28LAwAcUi5vw/Trq68/H89JTZcI5wI6y4xbgrHHi3wg8eZjnAuZ4IsHzhMCTYTWeUilHb+8mPC+Jat5lmmdOWBoNM+Lt+H49sVgjvl930DQ8YYn3Y4Kgnv7+rXR0PE939zpyuTYAkskFZDLLqas7i87Ol8hmd5JOLyGdXopqnvb2p+np2Uih0EEyuYD9+39HNttCKrWImTOvZMaMPxvSHovNor39KXK5XXhekkTiBJLJBSQSzeTz+8hmWxkY+IDOzhfp7/8AEY9EYi6el6S/f+tQZj0Rvl9PTc1SmptvIpM5g+7uV2hvf4r29icAEInjeQlaW+8us3uKRGIeQVCH79cRjx+H72eorT2V2tplFIs9iMTw/TqCoJ4gqCeXa6Ol5Wf09b1HodDB3r0PHaQlmVxIMrkQz6unVMpRV3c2yeQ8Eol5NDRcQDq9FBFBtUSx2Eex2EVX18t0d7/GoJPM5drwvAT5/D66utY6HSl8P8OcOTdTW7sMEY+OjmfJZltpbr6AUqmXQqEb30/R17eF9vYnUS0Rj88mFptJPv8xsdhM6uvPJpVaRLHYQ2/vW/T2biaVWsScOTeTy+2mt3cTHR3PsWfPmqFnCoJGMpkzSadPJpVahO/Xkc1+5DJYIZlcQG/vm/T2biIWm0EsNtvd9zhisZnEYmEGP5jRh81LnkuLeyiV8iQSzUOZ9KFQLA7Q1fUH2tufdnbYiWqWUmmAUilcATUWm0k83kx39zpn24/L0lS5U/GYNesKGhq+QDK5gGRyPsnkfERi9PZuRiQgFmskl2tDtUAQNJBKLR51iquwJltzUHis7KebSBxPbW2ks2cHIrKu7PgeVR1clHO0EvCo65aLyOcJHc+5kz132HWiWBf9cKmpqdHe3pGlxupBVSmV+l0zzX6KxS6KxV7i8U8RBA10d6+jWOymVOpj1XOPM7uuli8v+2N6etbT0fGs+1EfIJGYS339uWSzrWSzOygWe11TTQbPi1Ms9tHX9zbDS2geQdCAah7VArW1y8hmd5LNfjTs2rHYcSST84ES/f3bRpT8fKA47Did/iOCoIGBgW3U1JxKQ8MFdHa+RHv704wsIXpemmRyIaVS37CS/4F7z6Su7mzXpFEaeraw5L2UdHopqdRJ9PRspKdngyvZh47A9+tJJucRjzePmgnkch/j+6mh0mFv71vk83tIpRaTSMz5xKX4/v7t9PdvpVjswfMSJJMLSaeXHPVz7qkW6ex8ib6+LUCRrq619PS87mpLB5qSfD+DaoFSqR/fryOTWU6h0Eku10Y+v2dYM9RwBM9LoVpENRuGSJympktoavpTwGdgYDv5/B7CmuCBmkOYDt4YqjGKBNTVnUM6vQTPSwy9hwNOfniBbmBg+1Aho1DoolDYh+fVkEgcPwWWrE5EpE9VD/aO4XdnA3eo6pfc8Y8AVPWfR8Q7FXgUuERV35vMuQfd81Acj4g0APcCnyH0Zjeo6h/Kvv8b4Fp3GABLgVmq2i4itwLfdee9CVyvqgMi0gQ8ACwgXPr6KlUdWe8dRtSOR1Xp79+G5yXJ5/fS2fki+/e/QF/fuxQK7eTz7UNNIhORLSbxRQm8rCsZf56mpotdBuYDJXbtupf+/m0kEnNJJObi+xmKxR6KxR5Us4gkqK09jZqazww1G+XzHRQKHXheHNUSPT2vu1LvuRSLPcTjx9PYeJEr3cnQc/X1vUt39ytkMmeQSi12TV7voFqgoWHlmH0cAwMtdHevpbb2dFRzZLM7qav7HL6fdtcuuaaEVmKxGcTjn8L3bejt0cJgDaVQ6CaZPAHPSwz1jcRis4bVyAf7RfL5feTz+9xv4sBnsdjnargn4Hlxens3s3fvg+Ryu4GwnyPspFegONRZn0otJpM5g1hsFrW1p9HQcCFBYKPoJsMEjicA3gNWAjuBV4FvqepbZXHmAb8F/ry8v+dQzh31nofoeFYD/6eq94pIHEir6v4x4l4G3KqqXxCROcBLwCmq2i8iDwJPqOr9IvJToF1V73RD8BpV9bbxdByu4+no+D3Z7Ic0Nl5EItE81PErIgRBI76fQUQoFDrZvft+eno2uCp23tUWWslkVpDLtboaxgGSyYXU1i4balYIggY3cqWeIKjD89JkszvI5/eRyawY+rGef9dWzjpxBj+/ajFBUD/pZzKMYwHVIrncHkCJxWbjedb6PxWM53jc95cCPycs9d6nqj8Wke8BqOoqEbkXuBL40J1SUNUVY507kZ4J37KI1AHnA3/hROSA8Yr13wT+Z8Q9UiKSB9JAqwu/HLjQ7a8Gfg+M63gOl7a2X7J7931A2M4PUCr1l8XwicUaKRb7KJX6iMfnuNE+cVKpk6mvP4/u7rUEQROLF9+NSIDvZ6ivP49kcu4od5yYwN9O3A/M6RjTGhGfRKI5ahnTHlV9AnhiRNiqsv3vErZcHdK5EzFhjUdElhGO2d4MnAa8BvxAVQ+qeohImnBUwyJVbXdhPwB+DPQDz6jqtS58v6o2lJ3boaqN42k53BpP2OT0Bvv3/5ZsthVQNwLIG2qaCvs4PJqbbyCTWT7pe0yWB1/dwYKZNZy5sGnK72UYxvRmohpPpTkUx7OCcNz2Oar6ioj8G9Clqn83StyrgW+r6mXuuBF4BLga2A88BDysqr86VMcjIjcBNwHE4/HPZrPZw3xUwzCM6Um1OZ5DGeLTArSo6ivu+GFgrCrBNQxvZvsi8IGq7tVwaNNvgMF/QLWJSDOA+9wz2gVV9R5VXaGqK4LA2n8NwzCOdiZ0PKq6G9ghIktc0EpG+VeqiNQDFwCPlQV/BHxORNISDqFaCQz2zj8OXOf2rxtxnmEYhnGMcqhViJuBNW5E2/vA9eUjHlycrxH24Qx1wrimuYeB9UABeJ2wvwjgTuBBEbmR0EF945M+jGEYhlH92B9IDcMwjnGOxj4ewzAMwzhimOMxDMMwKoo5HsMwDKOimOMxDMMwKspRNbhAREqEMyAcDgHhyLpqo1p1QfVqM12To1p1QfVqO9Z0pVS1aioaR5Xj+SSIyLrBSe2qiWrVBdWrzXRNjmrVBdWrzXRNLVXjAQ3DMIzpgTkewzAMo6JMJ8dzz8RRIqFadUH1ajNdk6NadUH1ajNdU8i06eMxDMMwqoPpVOMxDMMwqoBp4XhE5GIReVdEtrpltqPScYKI/E5E3haRt9wieYjIHSKyU0Q2uO3SCLRtF5E33f3XubAmEXlWRLa4z3EX6psCTUvKbLJBRLpE5Jao7CUi94nIHhHZVBY2po1E5Ecuzb0rIl+qsK5/EZF3ROQNEXlURBpc+AIR6S+z3aqxrzwlusZ8dxHb64EyTdtFZIMLr6S9xsofIk9jRxxVPaY3wnXAtwEnAnFgI3BKRFqageVuPwO8B5wC3AH8dcR22g7MHBH2U+CHbv+HwE8ifo+7gflR2YtwCfjlwKaJbOTe60YgASx0adCvoK6LgMDt/6RM14LyeBHYa9R3F7W9Rnx/F/D3EdhrrPwh8jR2pLfpUOM5E9iqqu+rag74NXB5FEJUdZeqrnf73YRrE82JQsshcjmw2u2vBr4aoZaVwDZV/TAqAar6ItA+IngsG10O/FpVs6r6AbCVMC1WRJeqPqOqg380fBmYOxX3nqyucYjUXoO4dcOuYviClhVhnPwh8jR2pJkOjmcOsKPsuIUqyOxFZAFwOjC4sutfumaR+yrdpOVQ4BkReU3C5cYBjlPVXRD+KIDZEegaZOTqtlHba5CxbFRN6e4G4Mmy44Ui8rqIvCAi50WgZ7R3Vy32Og9oU9UtZWEVt9eI/OFoSGOTYjo4HhklLNKhfCJSCzwC3KKqXcC/AycBy4BdhFX9SnOOqi4HLgG+LyLnR6BhVCRcgPArwEMuqBrsNRFVke5E5HbCKVbWuKBdwDxVPR34K+C/RaSugpLGendVYS/gmwwv4FTcXqPkD2NGHSXsqBimPB0cTwtwQtnxXKA1Ii2ISIwwUa1R1d8AqGqbqhZVtQT8BxFUl1W11X3uAR51GtpEpNnpbgb2VFqX4xJgvaq2OY2R26uMsWwUeboTkeuALwPXqusUcM0y+9z+a4T9AidXStM4764a7BUAVwAPDIZV2l6j5Q9UcRo7XKaD43kVWCwiC13J+Rrg8SiEuPbj/wTeVtWflYU3l0X7GrBp5LlTrKtGRDKD+4Qd05sI7XSdi3Yd8FgldZUxrBQatb1GMJaNHgeuEZGEiCwEFgNrKyVKRC4GbgO+oqp9ZeGzRMR3+yc6Xe9XUNdY7y5Sezm+CLyjqi2DAZW011j5A1Waxj4RUY9uqMQGXEo4QmQbcHuEOs4lrAq/AWxw26XAL4E3XfjjQHOFdZ1IODpmI/DWoI2AGcDzwBb32RSBzdLAPqC+LCwSexE6v11AnrC0eeN4NgJud2nuXeCSCuvaStj+P5jOVrm4V7p3vBFYD1xWYV1jvrso7eXC7we+NyJuJe01Vv4QeRo70pvNXGAYhmFUlOnQ1GYYhmFUEeZ4DMMwjIpijscwDMOoKOZ4DMMwjIpijscwDMOoKOZ4DGMKEZELReR/o9ZhGNWEOR7DMAyjopjjMQxARL4tImvdmiu/EBFfRHpE5C4RWS8iz4vILBd3mYi8LAfWuml04YtE5DkR2ejOOcldvlZEHpZwfZw17h/qiMidIrLZXedfI3p0w6g45niMaY+ILAWuJpwodRlQBK4FagjniFsOvAD8gzvlv4DbVPVUwn/hD4avAe5W1dOAPyH8dzyEswzfQrh+yonAOSLSRDhlzKfddf5pap/SMKoHczyGEa7181ngVbfy5EpCB1HiwISRvwLOFZF6oEFVX3Dhq4Hz3Vx3c1T1UQBVHdADc6StVdUWDSfG3EC4uFgXMADcKyJXAEPzqRnGsY45HsMIp5dfrarL3LZEVe8YJd5480uNNkX9INmy/SLhyqAFwpmZHyFc2OupSWo2jKMWczyGEU68+HURmQ1Da9zPJ/x9fN3F+Rbwkqp2Ah1lC4J9B3hBw3VTWkTkq+4aCRFJj3VDt+ZKvao+QdgMt2wqHswwqpEgagGGETWqullE/pZwBVaPcNbi7wO9wKdF5DWgk7AfCMKp6Vc5x/I+cL0L/w7wCxH5R3eNb4xz2wzwmIgkCWtLtx7hxzKMqsVmpzaMMRCRHlWtjVqHYRxrWFObYRiGUVGsxmMYhmFUFKvxGIZhGBXFHI9hGIZRUczxGIZhGBXFHI9hGIZRUczxGIZhGBXFHI9hGIZRUf4f49buj59gYWIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots()\n",
    "\n",
    "ax1.plot(val_losses, label='val loss')\n",
    "\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(men, label='MEN', c='g')\n",
    "ax2.plot(ws353, label='WS353', c='m')\n",
    "ax2.plot(simlex999, label='SIMLEX999', c='y')\n",
    "\n",
    "ax1.legend(loc=[0.07, 0.9])\n",
    "ax2.legend(loc=[0.7, 0.15])\n",
    "\n",
    "ax1.set_xlabel('epochs');"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}