diff --git a/code/NFplots.ipynb b/code/NFplots.ipynb
new file mode 100644
index 0000000..785ee06
--- /dev/null
+++ b/code/NFplots.ipynb
@@ -0,0 +1,501 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>acc_sum</th>\n",
+       "      <th>block</th>\n",
+       "      <th>block_c</th>\n",
+       "      <th>condition</th>\n",
+       "      <th>correct</th>\n",
+       "      <th>correct_response</th>\n",
+       "      <th>datetime</th>\n",
+       "      <th>endtime</th>\n",
+       "      <th>flanker</th>\n",
+       "      <th>jitter</th>\n",
+       "      <th>...</th>\n",
+       "      <th>time_test_buffer</th>\n",
+       "      <th>time_test_buffer_response</th>\n",
+       "      <th>time_test_constants</th>\n",
+       "      <th>time_test_flanker</th>\n",
+       "      <th>time_test_jitter</th>\n",
+       "      <th>time_test_logger</th>\n",
+       "      <th>time_test_target</th>\n",
+       "      <th>time_test_target_response</th>\n",
+       "      <th>time_test_variables</th>\n",
+       "      <th>trial</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>1</td>\n",
+       "      <td>test</td>\n",
+       "      <td>1</td>\n",
+       "      <td>con</td>\n",
+       "      <td>1</td>\n",
+       "      <td>m</td>\n",
+       "      <td>Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...</td>\n",
+       "      <td>280861.4</td>\n",
+       "      <td>gold</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>278922.0</td>\n",
+       "      <td>278922.0</td>\n",
+       "      <td>277194.0</td>\n",
+       "      <td>278204.0</td>\n",
+       "      <td>277194.0</td>\n",
+       "      <td>279138.0</td>\n",
+       "      <td>278721.0</td>\n",
+       "      <td>278721.0</td>\n",
+       "      <td>279138.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>2</td>\n",
+       "      <td>test</td>\n",
+       "      <td>1</td>\n",
+       "      <td>con</td>\n",
+       "      <td>1</td>\n",
+       "      <td>m</td>\n",
+       "      <td>Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...</td>\n",
+       "      <td>282714.5</td>\n",
+       "      <td>iron</td>\n",
+       "      <td>900</td>\n",
+       "      <td>...</td>\n",
+       "      <td>280775.0</td>\n",
+       "      <td>280775.0</td>\n",
+       "      <td>279146.0</td>\n",
+       "      <td>280057.0</td>\n",
+       "      <td>279147.0</td>\n",
+       "      <td>280992.0</td>\n",
+       "      <td>280575.0</td>\n",
+       "      <td>280575.0</td>\n",
+       "      <td>280991.0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>3</td>\n",
+       "      <td>test</td>\n",
+       "      <td>1</td>\n",
+       "      <td>inc</td>\n",
+       "      <td>1</td>\n",
+       "      <td>m</td>\n",
+       "      <td>Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...</td>\n",
+       "      <td>284735.8</td>\n",
+       "      <td>kiwi</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>282712.0</td>\n",
+       "      <td>282712.0</td>\n",
+       "      <td>280999.0</td>\n",
+       "      <td>282011.0</td>\n",
+       "      <td>280999.0</td>\n",
+       "      <td>283013.0</td>\n",
+       "      <td>282513.0</td>\n",
+       "      <td>282513.0</td>\n",
+       "      <td>283013.0</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>4</td>\n",
+       "      <td>test</td>\n",
+       "      <td>1</td>\n",
+       "      <td>con</td>\n",
+       "      <td>1</td>\n",
+       "      <td>z</td>\n",
+       "      <td>Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...</td>\n",
+       "      <td>286755.9</td>\n",
+       "      <td>pear</td>\n",
+       "      <td>900</td>\n",
+       "      <td>...</td>\n",
+       "      <td>284649.0</td>\n",
+       "      <td>284649.0</td>\n",
+       "      <td>283020.0</td>\n",
+       "      <td>283932.0</td>\n",
+       "      <td>283020.0</td>\n",
+       "      <td>285033.0</td>\n",
+       "      <td>284449.0</td>\n",
+       "      <td>284449.0</td>\n",
+       "      <td>285033.0</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>5</td>\n",
+       "      <td>test</td>\n",
+       "      <td>1</td>\n",
+       "      <td>inc</td>\n",
+       "      <td>1</td>\n",
+       "      <td>z</td>\n",
+       "      <td>Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...</td>\n",
+       "      <td>288676.8</td>\n",
+       "      <td>bronze</td>\n",
+       "      <td>800</td>\n",
+       "      <td>...</td>\n",
+       "      <td>286570.0</td>\n",
+       "      <td>286570.0</td>\n",
+       "      <td>285044.0</td>\n",
+       "      <td>285852.0</td>\n",
+       "      <td>285044.0</td>\n",
+       "      <td>286954.0</td>\n",
+       "      <td>286370.0</td>\n",
+       "      <td>286370.0</td>\n",
+       "      <td>286954.0</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>139</th>\n",
+       "      <td>119</td>\n",
+       "      <td>test</td>\n",
+       "      <td>1</td>\n",
+       "      <td>con</td>\n",
+       "      <td>1</td>\n",
+       "      <td>m</td>\n",
+       "      <td>Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...</td>\n",
+       "      <td>530180.2</td>\n",
+       "      <td>cobalt</td>\n",
+       "      <td>800</td>\n",
+       "      <td>...</td>\n",
+       "      <td>528224.0</td>\n",
+       "      <td>528224.0</td>\n",
+       "      <td>526693.0</td>\n",
+       "      <td>527505.0</td>\n",
+       "      <td>526693.0</td>\n",
+       "      <td>528457.0</td>\n",
+       "      <td>528023.0</td>\n",
+       "      <td>528023.0</td>\n",
+       "      <td>528457.0</td>\n",
+       "      <td>124</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>140</th>\n",
+       "      <td>120</td>\n",
+       "      <td>test</td>\n",
+       "      <td>1</td>\n",
+       "      <td>con</td>\n",
+       "      <td>1</td>\n",
+       "      <td>m</td>\n",
+       "      <td>Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...</td>\n",
+       "      <td>532417.4</td>\n",
+       "      <td>zinc</td>\n",
+       "      <td>1100</td>\n",
+       "      <td>...</td>\n",
+       "      <td>530294.0</td>\n",
+       "      <td>530294.0</td>\n",
+       "      <td>528465.0</td>\n",
+       "      <td>529576.0</td>\n",
+       "      <td>528465.0</td>\n",
+       "      <td>530695.0</td>\n",
+       "      <td>530094.0</td>\n",
+       "      <td>530094.0</td>\n",
+       "      <td>530694.0</td>\n",
+       "      <td>125</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>141</th>\n",
+       "      <td>120</td>\n",
+       "      <td>test</td>\n",
+       "      <td>1</td>\n",
+       "      <td>con</td>\n",
+       "      <td>0</td>\n",
+       "      <td>z</td>\n",
+       "      <td>Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...</td>\n",
+       "      <td>535740.5</td>\n",
+       "      <td>raisin</td>\n",
+       "      <td>800</td>\n",
+       "      <td>...</td>\n",
+       "      <td>532215.0</td>\n",
+       "      <td>532215.0</td>\n",
+       "      <td>530702.0</td>\n",
+       "      <td>531513.0</td>\n",
+       "      <td>530702.0</td>\n",
+       "      <td>534018.0</td>\n",
+       "      <td>532014.0</td>\n",
+       "      <td>532014.0</td>\n",
+       "      <td>534018.0</td>\n",
+       "      <td>126</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>142</th>\n",
+       "      <td>121</td>\n",
+       "      <td>test</td>\n",
+       "      <td>1</td>\n",
+       "      <td>inc</td>\n",
+       "      <td>1</td>\n",
+       "      <td>m</td>\n",
+       "      <td>Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...</td>\n",
+       "      <td>537827.5</td>\n",
+       "      <td>kiwi</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>535755.0</td>\n",
+       "      <td>535755.0</td>\n",
+       "      <td>534028.0</td>\n",
+       "      <td>535037.0</td>\n",
+       "      <td>534028.0</td>\n",
+       "      <td>536105.0</td>\n",
+       "      <td>535554.0</td>\n",
+       "      <td>535554.0</td>\n",
+       "      <td>536104.0</td>\n",
+       "      <td>127</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>143</th>\n",
+       "      <td>122</td>\n",
+       "      <td>test</td>\n",
+       "      <td>1</td>\n",
+       "      <td>inc</td>\n",
+       "      <td>1</td>\n",
+       "      <td>z</td>\n",
+       "      <td>Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...</td>\n",
+       "      <td>540082.5</td>\n",
+       "      <td>zinc</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>...</td>\n",
+       "      <td>537843.0</td>\n",
+       "      <td>537843.0</td>\n",
+       "      <td>536114.0</td>\n",
+       "      <td>537124.0</td>\n",
+       "      <td>536114.0</td>\n",
+       "      <td>538360.0</td>\n",
+       "      <td>537641.0</td>\n",
+       "      <td>537641.0</td>\n",
+       "      <td>538359.0</td>\n",
+       "      <td>128</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>128 rows × 35 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     acc_sum block  block_c condition  correct correct_response  \\\n",
+       "16         1  test        1       con        1                m   \n",
+       "17         2  test        1       con        1                m   \n",
+       "18         3  test        1       inc        1                m   \n",
+       "19         4  test        1       con        1                z   \n",
+       "20         5  test        1       inc        1                z   \n",
+       "..       ...   ...      ...       ...      ...              ...   \n",
+       "139      119  test        1       con        1                m   \n",
+       "140      120  test        1       con        1                m   \n",
+       "141      120  test        1       con        0                z   \n",
+       "142      121  test        1       inc        1                m   \n",
+       "143      122  test        1       inc        1                z   \n",
+       "\n",
+       "                                              datetime   endtime flanker  \\\n",
+       "16   Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...  280861.4    gold   \n",
+       "17   Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...  282714.5    iron   \n",
+       "18   Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...  284735.8    kiwi   \n",
+       "19   Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...  286755.9    pear   \n",
+       "20   Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...  288676.8  bronze   \n",
+       "..                                                 ...       ...     ...   \n",
+       "139  Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...  530180.2  cobalt   \n",
+       "140  Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...  532417.4    zinc   \n",
+       "141  Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...  535740.5  raisin   \n",
+       "142  Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...  537827.5    kiwi   \n",
+       "143  Fri Aug 02 2024 12:36:04 GMT-0500 (Central Day...  540082.5    zinc   \n",
+       "\n",
+       "     jitter  ... time_test_buffer time_test_buffer_response  \\\n",
+       "16     1000  ...         278922.0                  278922.0   \n",
+       "17      900  ...         280775.0                  280775.0   \n",
+       "18     1000  ...         282712.0                  282712.0   \n",
+       "19      900  ...         284649.0                  284649.0   \n",
+       "20      800  ...         286570.0                  286570.0   \n",
+       "..      ...  ...              ...                       ...   \n",
+       "139     800  ...         528224.0                  528224.0   \n",
+       "140    1100  ...         530294.0                  530294.0   \n",
+       "141     800  ...         532215.0                  532215.0   \n",
+       "142    1000  ...         535755.0                  535755.0   \n",
+       "143    1000  ...         537843.0                  537843.0   \n",
+       "\n",
+       "    time_test_constants time_test_flanker  time_test_jitter  time_test_logger  \\\n",
+       "16             277194.0          278204.0          277194.0          279138.0   \n",
+       "17             279146.0          280057.0          279147.0          280992.0   \n",
+       "18             280999.0          282011.0          280999.0          283013.0   \n",
+       "19             283020.0          283932.0          283020.0          285033.0   \n",
+       "20             285044.0          285852.0          285044.0          286954.0   \n",
+       "..                  ...               ...               ...               ...   \n",
+       "139            526693.0          527505.0          526693.0          528457.0   \n",
+       "140            528465.0          529576.0          528465.0          530695.0   \n",
+       "141            530702.0          531513.0          530702.0          534018.0   \n",
+       "142            534028.0          535037.0          534028.0          536105.0   \n",
+       "143            536114.0          537124.0          536114.0          538360.0   \n",
+       "\n",
+       "     time_test_target  time_test_target_response  time_test_variables  trial  \n",
+       "16           278721.0                   278721.0             279138.0      1  \n",
+       "17           280575.0                   280575.0             280991.0      2  \n",
+       "18           282513.0                   282513.0             283013.0      3  \n",
+       "19           284449.0                   284449.0             285033.0      4  \n",
+       "20           286370.0                   286370.0             286954.0      5  \n",
+       "..                ...                        ...                  ...    ...  \n",
+       "139          528023.0                   528023.0             528457.0    124  \n",
+       "140          530094.0                   530094.0             530694.0    125  \n",
+       "141          532014.0                   532014.0             534018.0    126  \n",
+       "142          535554.0                   535554.0             536104.0    127  \n",
+       "143          537641.0                   537641.0             538359.0    128  \n",
+       "\n",
+       "[128 rows x 35 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv('/Users/zakg04/Documents/HBC_lab/BOOST/Main/TaskLogic/data/test/test-7005/processed/NF/7005_NF_A.csv')\n",
+    "test = df[df['block'] == 'test']\n",
+    "test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#group by condition (inc, con)\n",
+    "inc = test[test['condition'] == 'inc']\n",
+    "con = test[test['condition'] == 'con']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+HwRu6KsWSdL0+rwiOBlYW1XrquoJ4BrgzDH9/inwGeC7PdYiSZpGn0GwCHhgaH19t+0pSRYBrwdWzHSgJBcmWZNkzdTU1KwXKkkt6zMIMmZbjaz/EXBxVW2Z6UBVtbKqllbV0oUL/RoESZpNfc4XtB44cmh9MbBhpM9S4JokAIcCr02yuao+22NdkqQhfQbBrcAxSY4GHgTOAd403KGqjt66nORK4HOGgCTNrd6CoKo2J7mIwbuBFgCXV9U9SZZ37TPeF5AkzY1ep5KuqtXA6pFtYwOgqt7aZy2SpPH8ZLEkNc4gkKTGGQSS1DiDQJIaZxBIUuMMAklqnEEgSY0zCCSpcQaBJDXOIJCkxhkEktQ4g0CSGmcQSFLjDAJJapxBIEmNMwgkqXEGgSQ1ziCQpMYZBJLUOINAkhpnEEhS4wwCSWqcQSBJjTMIJKlxBoEkNc4gkKTGGQSS1DiDQJIaZxBIUuMMAklqnEEgSY0zCCSpcb0GQZLTk9yXZG2SS8a0L0tyZ/e4OckJfdYjSdpWb0GQZAFwGXAGcBxwbpLjRrp9C/iFqnox8H5gZV/1SJLG6/OK4GRgbVWtq6ongGuAM4c7VNXNVfVIt/o1YHGP9UiSxugzCBYBDwytr++2Tec3gc+Pa0hyYZI1SdZMTU3NYomSpD6DIGO21diOyS8yCIKLx7VX1cqqWlpVSxcuXDiLJUqS9u7x2OuBI4fWFwMbRjsleTHwceCMqvpej/VIksbo84rgVuCYJEcn2Rc4B1g13CHJUcB1wFuq6q97rEWSNI3ergiqanOSi4AbgAXA5VV1T5LlXfsK4LeBZwMfTQKwuaqW9lWTJGlbfQ4NUVWrgdUj21YMLb8NeFufNUiSZuYniyWpcQaBJDXOIJCkxhkEktQ4g0CSGmcQSFLjDAJJapxBIEmNMwgkqXEGgSQ1ziCQpMYZBJLUOINAkhpnEEhS4wwCSWqcQSBJjTMIJKlxBoEkNc4gkKTGGQSS1DiDQJIaZxBIUuMMAklqnEEgSY0zCCSpcQaBJDXOIJCkxhkEktQ4g0CSGmcQSFLjDAJJapxBIEmNMwgkqXG9BkGS05Pcl2RtkkvGtCfJh7v2O5O8tM96JEnb6i0IkiwALgPOAI4Dzk1y3Ei3M4BjuseFwMf6qkeSNF6fVwQnA2ural1VPQFcA5w50udM4Koa+BpwUJLDe6xJkjRi7x6PvQh4YGh9PXDKBH0WAQ8Nd0pyIYMrBoDHktw3u6U27VBg03wXsSvIh86f7xL0dP5udmbpd/N50zX0GQQZs612oA9VtRJYORtF6emSrKmqpfNdhzTK38250+fQ0HrgyKH1xcCGHegjSepRn0FwK3BMkqOT7AucA6wa6bMKOK9799DfB75fVQ+NHkiS1J/ehoaqanOSi4AbgAXA5VV1T5LlXfsKYDXwWmAt8DhwQV/1aFoOuWlX5e/mHEnVNkPykqSG+MliSWqcQSBJjTMIJM2rJDfPdw2t8x6BJDXOK4I9XJLzugn97kjyySTPS/LFbtsXkxzV9buymwDw5iTrkpw937WrDUke6/49LcmNSa5N8s0kVydJ13ZS97t5R5Jbkhwwv1XvWfr8ZLHmWZLjgX8NvLyqNiU5BPgEg/mdPpHkN4APA7/W7XI48ArgWAaf8bh27qtW414CHM/gg6V/Abw8yS3AfwPeWFW3JjkQ+PE81rjH8Ypgz/Yq4Nqq2gRQVQ8DpwKf6to/yeCFf6vPVtWTVXUv8Nw5rVQauKWq1lfVk8DtwBLghcBDVXUrQFX9oKo2z1+Jex6DYM8WxszdNGK4/e9G9pXm2vDv4BYGoxaT/B5rJxgEe7YvAm9I8myAbmjoZgbTfQAsA74yT7VJk/omcESSkwCSHJDEYe1Z5A9zD9ZN6fEB4MtJtgBfB94FXJ7kPcAUTuuhXVxVPZHkjcB/SvJMBvcHfhl4bH4r23P49lFJapxDQ5LUOINAkhpnEEhS4wwCSWqcQSBJjTMIpFnQzdV0drf88STHdcu/NdLPmTa1y/Hto9IsSHIl8LmqunZk+2NVtf/8VCVNxisCNWlnZ2XNwEeS3JvkfwDPGTr2jUmWJvkD4JlJbk9yddf22ND+lya5O8ld3QemZpyBU+qLnyxWc2ZpVtbXM5gM7ecYTNB3L3D58Hmq6pIkF1XViWPK+HXgROAE4FDg1iQ3dW3bzMCJU4GoR14RqEWzMSvrzwN/UlVbqmoD8KWfsoZXDO3/HeDLwEld27gZOKXeGARq0WzNyrozN9hmGu4ZNwOn1BuDQC2ajVlZbwLOSbIgyeHAL07T7ydJ9plm/zd2+y9kcIVxy0/5PKRZ4V8aas4szcp6PYMhpruAv2YwtDPOSuDOJH9VVctG9j8VuIPBlcV7q2pjkmN39HlJO8q3j0pS4xwakqTGGQSS1DiDQJIaZxBIUuMMAklqnEEgSY0zCCSpcf8P342TeREu3zMAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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W/fffz49+9CMWLVrE/PnzefzxxwG4++67eeGFFzj99NNZsmQJa9euZfTo0Zx//vksWLCgVwYYmPfxqLeoz9qv3X1BtL0e+Jy7v2hmlwPfcvclZjYfeICQvE0CngNmuXvMzP4IfB54HfgN8F13/82x3ru0tNRXrlzZJ59LREREMsv69euZO3duusPollSxmtkqdy9tf2yf9lkzsweBS4AxZlYGfA34M+BuM8sBGoBlAO6+1sweBtYBLcAd7h6LLvU54B6gkDCwQIMLREREZFDo69Ggn+hk15JOjv8G8I0U5SuBBb0YmoiIiEi/oBUMRERERDKYkjURERGRDKZkTURERCSDKVkTERERyWBK1kRERER60dNPP83s2bM59dRT+eY3v3nC11OyJiIiItJLYrEYd9xxB0899RTr1q3jwQcfZN26dSd0zXSsDSoiIiKSdofrmvntuv3sq25g4ogCrpg3geFDck/omm+88Qannnoqp5xyCgA33XQTjz/+OPPmzTvua6pmTURERAal367bz55D9bS6s+dQPb9dt/+Er7lnzx6mTEmsnllSUsKePXtO6JpK1kRERGRQ2lfd0OX28Ui1jKeZndA1layJiIjIoDRxREGX28ejpKSE3bt3v7ddVlbGpEmTTuiaStZERERkULpi3gQmjywky4zJIwu5Yt6EE77mWWedxebNm9m+fTtNTU089NBDfPjDHz6ha2qAgYiIiAxKw4fkcmPplGMf2AM5OTl873vf44orriAWi3Hbbbcxf/78E7tmL8UmIiIiIsBVV13FVVdd1WvXUzOoiIiISAZTsiYiIiKSwZSsiYiIiGQwJWsiIiIiGUzJmoiIiEgGU7ImIiIiksGUrImIiIj0kttuu41x48axYMGCXrumkjURERGRXnLrrbfy9NNP9+o1NSmuiIiIDE71h2DDk3B4DwyfDHOuhsKRJ3TJiy66iB07dvROfBHVrImIiMjgtOFJqN4N3hq+bngy3RGlpGRNREREBqfDe7rezhBK1kRERGRwGj656+0MoWRNREREBqc5V8OIKWBZ4eucq9MdUUoaYCAiIiKDU+FIOONTvXrJT3ziE7z44otUVlZSUlLCP/7jP3L77bef0DWVrImIiIj0kgcffLDXr6lmUBEREZEMpmRNREREJIMpWRMRERHJYErWREREZMBw93SHcEw9jbFPkzUz+7GZlZvZmnblnzezjWa21sy+lVR+l5ltifZdkVS+xMxWR/u+Y2bWl3GLiIhI/1NQUEBVVVVGJ2zuTlVVFQUFBd0+p69Hg94DfA+4L15gZpcC1wIL3b3RzMZF5fOAm4D5wCTgd2Z2mrvHgB8Ay4AVwG+AK4Gn+jh2ERER6UdKSkooKyujoqIi3aF0qaCggJKSkm4f36fJmru/bGbT2xV/DvimuzdGx5RH5dcCD0Xl281sC7DUzHYAw9z9NQAzuw+4DiVrIiIikiQ3N5cZM2akO4xel44+a6cBF5rZ62b2kpmdFZVPBnYnHVcWlU2Ovm9fnpKZLTOzlWa2MtMzaxEREZFjSUeylgOMBM4BvgQ8HPVBS9UPzbsoT8ndl7t7qbuXjh07tjfiFREREUmbdCRrZcBjHrwBtAJjovIpSceVAHuj8pIU5SIiIiIDXjqStV8ClwGY2WlAHlAJPAHcZGb5ZjYDmAW84e77gFozOyeqgfsM8Hga4hYRERE56fp0gIGZPQhcAowxszLga8CPgR9H03k0Abd4GGO71sweBtYBLcAd0UhQCIMS7gEKCQMLNLhAREREBgXL5LlITlRpaamvXLky3WGIiIiIHJOZrXL30vblWsFAREREJIMpWRMRERHJYErWRERERDKYkjURERGRDKZkTURERCSDKVkTERERyWBK1kREREQymJI1ERERkQymZE1EREQkgylZExEREclgStZEREREMpiSNREREZEMpmRNREREJIMpWRMRERHJYErWRERERDKYkjURERGRDKZkTURERCSDKVkTERERyWBK1kREREQymJI1ERERkQymZE1EREQkgylZExEREclgStZEREREMpiSNREREZEMpmRNREREJIMpWRMRERHJYErWRERERDKYkjURERGRDKZkTURERCSDKVkTERERyWBK1kREREQyWJ8ma2b2YzMrN7M1Kfb9rZm5mY1JKrvLzLaY2UYzuyKpfImZrY72fcfMrC/jFhEREckUfV2zdg9wZftCM5sCvB/YlVQ2D7gJmB+d830zy452/wBYBsyKXh2uKSIiIjIQ9Wmy5u4vAwdT7Po34MuAJ5VdCzzk7o3uvh3YAiw1s4nAMHd/zd0duA+4ri/jFhEREckUJ73Pmpl9GNjj7u+02zUZ2J20XRaVTY6+b18uIiIiMuDlnMw3M7MhwFeBD6TanaLMuyjv7D2WEZpMmTp16nFEKSIiIpI5TnbN2kxgBvCOme0ASoA3zWwCocZsStKxJcDeqLwkRXlK7r7c3UvdvXTs2LG9HL6IiIjIyXVSkzV3X+3u49x9urtPJyRiZ7r7fuAJ4CYzyzezGYSBBG+4+z6g1szOiUaBfgZ4/GTGLSIiIpIufT11x4PAa8BsMyszs9s7O9bd1wIPA+uAp4E73D0W7f4c8N+EQQdbgaf6Mm4RERGRTGFhgOXAVFpa6itXrkx3GCIiIiLHZGar3L20fblWMBARERHJYErWRERERDKYkjURERGRDKZkTURERCSDKVkTERERyWBK1kREREQymJI1ERERkQymZE1EREQkgylZExEREclgStZEREREMpiSNREREZEMpmRNREREJIMpWRMRERHJYErWRERERDKYkjURERGRDKZkTURERCSDKVkTERERyWBK1kREREQymJI1ERERkQymZE1EREQkgylZExEREclgStZEREREMpiSNREREZEMpmRNREREJIMpWRMRERHJYErWRERERDKYkjURERGRDKZkTURERCSD9ShZM7NCM5vdV8GIiIiISFvdTtbM7EPA28DT0fZiM3uij+ISEREREXpWs/Z1YClQDeDubwPTezsgEREREUnoSbLW4u6H+ywSEREREemgJ8naGjO7Gcg2s1lm9l3g1a5OMLMfm1m5ma1JKvsXM9tgZu+a2S/MbETSvrvMbIuZbTSzK5LKl5jZ6mjfd8zMehC3iIiISL/Vk2Tt88B8oBF4EKgB/voY59wDXNmu7FlggbsvBDYBdwGY2Tzgpug9rgS+b2bZ0Tk/AJYBs6JX+2uKiIiIDEjdTtbcvc7dv+ruZ7l7afR9wzHOeRk42K7sGXdviTZXACXR99cCD7l7o7tvB7YAS81sIjDM3V9zdwfuA67rbtwiIiIi/VlOdw80s1Lg7wiDCt47L6ohO163AT+Pvp9MSN7iyqKy5uj79uWdxbmMUAvH1KlTTyA0ERERkfTrdrIG3A98CVgNtJ7oG5vZV4GW6LoAqfqheRflKbn7cmA5QGlpaafHiYiIiPQHPUnWKty9V+ZVM7NbgGuAy6OmTQg1ZlOSDisB9kblJSnKRURERAa8niRrXzOz/waeIwwyAMDdH+vJG5rZlcCdwMXuXpe06wngATP7NjCJMJDgDXePmVmtmZ0DvA58BvhuT95TREREpL/qSbL2J8AcIJdEM6gDnSZrZvYgcAkwxszKgK8RRn/mA89GM3CscPc/d/e1ZvYwsI7QPHqHu8eiS32OMLK0EHgqeomIiIgMeJZohTzGgWar3f30Po6nV5WWlvrKlSvTHYaIiIjIMZnZKncvbV/ek5q1FWY2z93X9WJcIiIiA8++d2HH7yHWBJOXwIyL0h2R9GM9SdYuAG4xs+2EPmsG+AlO3SEiIjKwHK2Ejb+BeMvVjldg6FgYNze9cUm/1ZNkTasGiIiIHMvhskSiFle9W8maHLdjJmtmNszda4DakxCPiIhI/zYsxbztwyad/DhkwOhOzdoDhDnRVtFxkloHTumDuERERPqnorFw2hVRn7VmmHwmjJ+f7qikHztmsubu10RfZ/R9OCIiIgPA5DPDS6QXdHshdzN7rjtlIiIiItJ7utNnrQAYQpjYdiSJZtBhhJUGRERERKSPdKfP2meBvyYkZqtIJGs1wH/0TVgiIiIiAt3rs3Y3cLeZfd7dO12T08ze7+7P9mp0IiIiIoNct/usdZWoRf7PCcYiIiIiIu10O1nrBjv2ISIiIiLSE72ZrHVvRXgRERER6bbeTNZEREREpJf1ZrK2oxevJSIiIiL0bFLcIWb292b2w2h7lpldE9/v7h/tiwBFREREBrOe1Kz9BGgEzo22y4D/3esRiYiIiMh7epKszXT3bwHNAO5ej0aAioiIiPSpniRrTWZWSDTq08xmEmraRERERKSPdGe5qbivAU8DU8zsfuB84Na+CEpEREREgm4na+7+rJm9CZxDaP78grtX9llkIiIiItKj0aDnAw3u/iQwAvg7M5vWV4GJiIiISM/6rP0AqDOzRcCXgJ3AfX0SlYiIiIgAPUvWWtzdgWuB77j73UBx34QlIiIiItCzAQa1ZnYX8CngIjPLBnL7JiwRERERgZ7VrH2cMFXH7e6+H5gM/EufRCUiIiIiQM9Gg+4Hvp20vQv1WRMRERHpUz0ZDfpRM9tsZofNrMbMas2spi+DExERERnsetJn7VvAh9x9fV8FIyIiIiJt9aTP2gElaiIiIiInV09q1laa2c+BX5K0Jqi7P9bbQYmIiIhI0JOatWFAHfAB4EPR65quTjCzH5tZuZmtSSobZWbPRv3fnjWzkUn77jKzLWa20cyuSCpfYmaro33fMTPrQdwiIiIi/VZPRoP+yXFc/x7ge7QdNfoV4Dl3/6aZfSXavtPM5gE3AfOBScDvzOw0d48RVk9YBqwAfgNcCTx1HPGIiIiI9Cs9GQ1aYma/iGrKDpjZ/5hZSVfnuPvLwMF2xdcC90bf3wtcl1T+kLs3uvt2YAuw1MwmAsPc/bVoBYX7ks4RERERGdB60gz6E+AJQq3XZOBXUVlPjXf3fQDR13FR+WRgd9JxZVHZ5Oj79uUiIiIiA15PkrWx7v4Td2+JXvcAY3sxllT90LyL8tQXMVtmZivNbGVFRUWvBSciIiKSDj1J1irN7FNmlh29PgVUHcd7HoiaNom+lkflZcCUpONKgL1ReUmK8pTcfbm7l7p76dixvZlLioiIiJx8PUnWbgNuBPZHr+ujsp56Argl+v4W4PGk8pvMLN/MZgCzgDeiptJaMzsnGgX6maRzRERERAa0nowG3QV8uCcXN7MHgUuAMWZWBnwN+CbwsJndDuwCboiuv9bMHgbWAS3AHdFIUIDPEUaWFhJGgWokqIiIiAwKFgZYduNAs1OAu4FzCH3GXgP+xt239V14J6a0tNRXrlyZ7jBEREREjsnMVrl7afvynjSDPgA8DEwkjAh9BHiwd8ITERERkVR6kqyZu/80aTToz+hiVKaIiIiInLierA36QrTiwEOEJO3jwJNmNgrA3dtPfisiIiIiJ6gnydrHo6+fbVd+GyF5O6VXIhIRERGR9/RkNOiMvgxERERERDrqydqgN5hZcfT9/2tmj5nZGX0XmoiIiIj0ZIDB37t7rZldAFxBWIT9P/smLBERERGBniVr8QlqrwZ+4O6PA3m9H5KIiIiIxPUkWdtjZv9FWHLqN2aW38PzRURERKSHepJs3Qj8FrjS3auBUcCX+iIoEREREQm6nay5ex1QDlwQFbUAm/siKBEREREJejIa9GvAncBdUVEu8LO+CEpEREREgp40g34E+DBwFMDd9wLFfRGUiIiIiAQ9Sdaa3N2J1gM1s6F9E5KIiIiIxHUrWTMzA34djQYdYWZ/BvwO+GFfBiciIiIy2HVruSl3dzO7jtBnrQaYDfyDuz/bh7GJiIiIDHo9Wcj9NaDa3TVdh4iIiMhJ0pNk7VLgs2a2k2iQAYC7L+z1qEREREQE6Fmy9sE+i0JEREREUup2subuO/syEBERERHpSGt7ioiIiGQwJWsiIiIiGUzJmoiIiEgGU7ImIiIiksF6MhpURBpqoOyP0NIA4xfAyGnpjkhERAY4JWsi3RVrgbd+GhI2gP2rYfHNMGJqeuMSEZEBTc2gIt11aEciUQNwDwmbiIhIH1KyJtJduYXdKxMREelFStZEumv4ZBg3N7FdMBwml6YvHhERGRTUZ02kJ+ZfB1OWQnM9jJgG2fovJCIifUt/aUR6atikdEcgIiKDiJI1kb5SsQn2vglZOTD13NCMKiIi0kNp67NmZn9jZmvNbI2ZPWhmBWY2ysyeNbPN0deRScffZWZbzGyjmV2RrrhFuqV6N6x9DA5uh8rN8M4D0Fib7qhERKQfSkuyZmaTgb8CSt19AZAN3AR8BXjO3WcBz0XbmNm8aP984Erg+2aWnY7YRbqlcmOY2iMu1gIHt6UvHhER6bfS2QyaAxSaWTMwBNgL3AVcEu2/F3gRuBO4FnjI3RuB7Wa2BVgKvHaSYx60li9fnu4Q+pWxTbuY2rChTdnG9caRnNfTFBEsW7Ysbe8tIiLHLy3JmrvvMbN/BXYB9cAz7v6MmY13933RMfvMbFx0ymRgRdIlyqKyDsxsGbAMYOpUzSzfWwb6H/rly5f37meMNcPqR8NEumYwcRFLZn+w964vIiKDRlqStagv2rXADKAaeMTMPtXVKSnKPEUZ7r4cWA5QWlqa8hiRPpedC4s/AUerwvQeBcPTHZGIiPRT6Rpg8D5gu7tXuHsz8BhwHnDAzCYCRF/Lo+PLgClJ55cQmk1FMtvQ0UrURETkhKQrWdsFnGNmQ8zMgMuB9cATwC3RMbcAj0ffPwHcZGb5ZjYDmAW8cZJjFhERETnp0tVn7XUzexR4E2gB3iI0XRYBD5vZ7YSE7obo+LVm9jCwLjr+DnePpSN2ERERkZMpbaNB3f1rwNfaFTcSatlSHf8N4Bt9HZeIiAxCFRuhfH3otjBlKeQNTXdEIu/RCgYiIjK4HVgH6x5PbB/cCqW3h5HcIhkgbSsYiIiIZIT9q9tuH6mA2v3piUUkBSVrIiIyuOUNabtt1rFMJI2UrImIyOA29by2fdSmLNWUO5JR1GdNREQGt6Gj4ZzPQfWukKQNHZPuiETaULImIiKSnQujZ6Y7CpGU1AwqIiIiksGUrImIiIhkMCVrIiIiIhlMyZqIiIhIBlOyJiIiIpLBlKzJwOMOB7fDwW3Q2pruaEREuqfxCDTXH/u46t1QuRliLX0fk2QETd0hA0usBd6+H2r2hu2icXDGpyEnL71xiYjEHSmHXSsg1gSTzoCR08PapJWbwLKgpBRmXpb63NWPhkQNwpxwZ34a8otPWuiSHqpZk4GlYkMiUYNwUzywJn3xiMjg1XQUYs3tyurgrZ/BgbUh6Vr9CGx+Bio2hlaB1hjseh0Ol3W8XrxGLa7hMOxZ1befQTKCatZkYGlp6F6ZiGSE5cuXpzuEXpflLZxS/w7DW6qIWTZ78mdRkTcVgFHNe5lR3/YBspVVZOFtynasracqr6RN2fCWck6te7tNWcXqA+wq2NT7H6IHli1bltb3HwyUrMnAMnY2bH8ZWhrDdnYujJub3phEpFMD8g/99pdhx2FgOqtWreIjC4rgnI+HZsvqXfDW/W2PHzsntArEZWWzZOkyKBzR9rhYM7yxHBpqwrZlwRmfhOFtkzoZeJSsSf9WvRsO74biiTBqRui7ceYtsPfN0KQw6QwoHJnuKEVkMDla0XbbHY5WhmRtxFSYcDrsXx32DZsIsz8Ylrraswqy82DauR0TNQgPn2d8OhzX0hCuo0RtUFCyJv3XnlWw6ZnE9vQLYMaFYVHmWe9PX1wiMriNmgkVSU2TOfltk6q518C080ILQPEEMAuDDI6Wh35u7h0u+Z6CYTDz0j4LXTKTkjXpv3ataLu9+/WQsJn1zftVboHydaH2bspSyBvaN+8jIv3bxEVhCo4Da6jJGQULbwwJW7IhoxLft8bCKPb66rBdvh5Ov0ELy8t7lKzJwOLeN8laxUZY81hiu2oLnPWnfZcYikj/ZRaaMqedy+a3nUuP1VRZvSuRqEG4jx1Yo2RN3qOpO6T/mnJOu+2zIauP/knve7ft9tFKqN3XN+8lIoNLqlr6XNXcS4Jq1qT/KlkCRWPDIIPiCV0/hdZXw8GtYbDByBk9rxHLG9J22wxyC8P3ra19lySKyMBXNC40ne57J2wXDIcpZ6U3JskoStakfxsxNby6cmgnvPswtEZLs0xcBHOu6t71K7eEWcWz80Kfk/iUIJOXhATwnZ9DQ3XoUDz3mkQCJyLSE3OuCisXNB2BEdMgKzvdEUkGUbImA9/u1xOJGsD+d8NAhIJhXZ+3713Y8GRie8RUmHpOGGBQOApe+15iHb+qLbDtJZh9Ze/HLyLp0VgL214MU3GMmhnuG32ZRBWNA8b13fWl31KyJgNfa7vFjt3BY8c+b/cKqN4ZRmoVjQ+dgOdcHeY/OlrZccHl2r0pLyMi/dSa/4GaqG9q7YFw3+hszc4TcaQ8PERm54e5IfOLev89pF9TRxsZ+CaXtu2jNmbWsSfKbWmE3W+EBK1mD+x7O0xCmR0tCF84suMN9VjNsSLSfzTWJhK1uOR1OXtL7QFYdS/s/iPs+AO8eV/H9URl0FOyJgPf2NPgjE+FJszZH4R513U4JK+1LjRjbv99WMqlcjMMGQsWNXl4K+QPg+a6UNOWlQ3zPxpmH8/JhwkLYPpFJ/dziUjfyR3SsQ9q4ajUx56I/e+2rf2v3gWbn4VmrWksCWoGlcFheEnny7I0HGbu0RWwM2rW3PsWnHJp6NNWUgoNh8OTbk0ZvPHDMMx+/kdgxBRYcutJ+wgichJlZcNpV8LGJ6GlKdSm90UTaLy2HsJ8jkfLw8Nh5abwkDl0TO+/p/Q7StZkcDhaBUcOhAQrv7jtvgNryfGkJ9umoxBrCsnd4TIYOjasXDD61MT+zc/AWbefvPhFpO/U7g8rosSaQp+xMbNC+bg5YUqghpqw4kBfTII96YywTmjt/pCoFYwI/WKb60NXjO6OXJcBTcmaDDzuoTYsvzg8HZetDM0KELYXfKztnGxZuR2vkZMHiz8Jh7aHGzgOJN2o6w/25ScQkZOlqS4s9dTSFLYPboNFn4CR08J2dm5Yb7ivFAyDpctg5ysQa4SCkbx3r2lRU6gEStZkYDlSHpaFqj8UmivnXAPbX0rsb43B9pfbJmsTFtCQlTTpbdFYGDsnTHQbP658XduFmUfP6tvPISInx8FtiUQNwsNexcZEsnYy5OTBKZeEWI6UhzIzmLS447GHdsCeVZCVAyVLQ79ZGfDSlqyZ2Qjgv4EFhGqL24CNwM+B6cAO4EZ3PxQdfxdwOxAD/srdf3vSg5bMEWsJ86fV7IFhk8LSU9k5oQat/lA4pukobPg1tLQbWdX+aTW3kHVDz+X8eReDZYXmzux2/zVmXw15xaHf2vApMEODCUQGhFTzLRYMP/lxmMHim2HTM7Dr1bDcVNXWthPk1u4PE3F7a9iu3Bxq5bJzw72r/WLxMmCks2btbuBpd7/ezPKAIcDfAc+5+zfN7CvAV4A7zWwecBMwH5gE/M7MTnPvzmRZMiBtfiaxNEvV1rCawNxroK6y7XFNR2HMbKjcmCibuLjD5dyyYfy8zt8vtwBO+8AJhy0iGWbE1LZLPQ0vSV2jVX8Idr0OzUdh/OlhlHlvqdoKNXuheBJU7wj91iB04cgpgBkXhu3yDdEUQrmAhRrBVfeEUeqWFQZE9cUgCEm7tCRrZjYMuAi4FcDdm4AmM7sWuCQ67F7gReBO4FrgIXdvBLab2RZgKfDaSQ1cMkf52nbb60OyNvrUtouuj5gK868NIzyPHICR02H8/JMaKs31cGBdeBoePy/1os0ikj5zroJp54ZR30UpVhCItcDbD4SBBhC6RJx+A4w5teOxlZvDgIG8Iph69rHfe/vLsOOV8H1jLTTWwLDJif3VO4ELQ/Polt+FBM6A8QtCt476Q2Hwg8dCMjnqlHCfkwElXTVrpwAVwE/MbBGwCvgCMN7d9wG4+z4zi/+vmQysSDq/LCqTwSp/GNQldfKPT1B76vvDgIHqnWHVgZmXhSaEktLeff/meqjdF96jq+SruQFW/iQMeADY9RqU3qYZykUyTVcTZR/elUjU4g6s6ZisVW6G1Y8mtqu2YN7FdKbuYcRnXG5hmLIjOVkrmhC+bno63HfqqqClPjx8Trsg9LFNdrRSydoAlK5kLQc4E/i8u79uZncTmjw7k2q8tKc80GwZsAxg6lTNKD9gnfo+WPuL8CScnRO2IXTU7evmyqqtsPax8LSdlQ1zPwTj5qY+tmJDIlGD0Cx7YG33nrhFIg888ABHjhxJdxiDVkHsCIuOvIbRSrPlA8b+vEr2vFLe5rgZ9e8wqvlAm7KiIaUsX74cgOzWJsY37yS/tZ5DOeOpzhnH4iMryU6aOijbm6kvX0OuN3I4eyw7Ng0j9sI2Ftc+x/imneS2tpDlBsTYt2kXrbaX+J9IN2PthgIas9/syx/HoFJUVMTNN9+c7jDSlqyVAWXu/nq0/SghWTtgZhOjWrWJQHnS8VOSzi8BUi7E6O7LgeUApaWlKRM6GQBGz4Rz/zI8XRaN6zjTeFfqq0NTQksDTFzY82Witj4fEjUIzRBbftd5sibSC44cOcKyZcvSHcbgUHcw/B+vqwr3mRmXwKanYO26sP5vXlYYYLTk1o5zNm5+NtSeNx0NzaBZOSxZ+meJqT9W/gRqk1ZBmHMuNJ0eVk+JO+0DMOnMsKpBdjStUNVWWLkTduyDnOHhIbFwJBMmLIRZH4C9b4bRodPOo3SMRqr3pniinW5pSdbcfb+Z7Taz2e6+EbgcWBe9bgG+GX19PDrlCeABM/s2YYDBLOCNjldOLz39Zr4sb2H+0VfIa20EwpPoxiFnQfYIli9fTm5rPSNaKmiyAg7njAmddttZVPsCOZ4YYepmvLk6N+Wx2d7M3KPryG8NqyM0ZeWzfmMxLVnv9NEnHJwy5elX+jn3sHj70WigUt3B8P3B7SFxGzYpzLs4cVHHRA1gyOjQX63paFiq7vTrE4nakYowmjPZgTVhBOiwyWGAwYipMDxqAk1O1N59OCzynlccJs4dOzcRT/EETdA9CKRzNOjngfujkaDbgD8hrFX6sJndDuwCbgBw97Vm9jAhmWsB7sjEkaB6+s1gsZYwN9Het6BiXJtOxKWTFsLsK8OizW//DGJRH7QxY8LNNllTHbzpYXTpkNEhQZuwgNK5H+r8vZtvD/O0ucO4uZybN6TzY+W4ZMrTr/RzDdWJRC2ucnOotYJQg59bGO4Dqex8NYw2b6wJy0jFkuZvyy0I94v4tBsQ1h+FMKdbZ/O67Y8GTGXnwrTzQ1/Z8fPDe+xbDRufCn1gS29X94oBLG3Jmru/DaTq9X15J8d/A/hGX8YkA9j6J8JElw2HQ6IVX04KIJ48lb2RaN6EcJM+UpHowFtfDW/eC43RclRHDsDCG8Mcb13JLYDJZ/b6RxKRXpZXHP6/xhdRbzoaatBaGhM1XWYdp/mp2Qvrfx0GAeQXh+mCcvJDQhWXXwxTzwkJHQ6trTBh4bFjyk0awGQWatNKSmHDb6BifRgF2lANb/00zA83bs6J/AQkQ3UxTEVkgGiuDyOsINzMhoyGI1FzRH5ReAKu3BwGK7SXXIG7963wRG0Wmi2KJ4ZX+wl0RaR/ys4Jq57kDQlTZVRtCnOYtTaH5Gvs7PCAltzP1R3WPRH6uA0dEx4ID24L+8a1mybolItDs2fc6ofD1B1dmbI0JHruYZqOguHhXtVwuO39qaURqrac2OeXjKW/MjLwZeWEVzwZGxfNdTbjotAh+PX/DAu25xWFJ+LCEeG4EVPDDbruYGIeo/ZaM641XkROxJhZMOov4bX/aDvnmrfCvGsTqwlAmJR212tQ9sfwEDh6FuQUhuTulIthSopmycrNgIXruIeatgmndz51SOEIOPvPYeWPwoS8DYdh24tt48BCojh0zIl/fslIStZk4MvODYnZ1ufDzTE7J0y3cXBr6OC7791wc4WQkJ35GRg1M6zBt+I/Q/mYWTD9Qtj7diLpGzI6TEAJULYKdv4hjOCaXBpu1CLSP2VlJ/qpxbmHV7I1/xPuEw01oS/Z2NnhIW/UjFC+/eUwAGDONYlEqqG643Ubarqe563hcHhozEuan3H8/HDN8nUwdFyocTuwNgximHFReMCUAUPJmmSuxtqwBEysCSYsSoyqOh5TlobVDY6Uw4gpoWatYmPoa9Ka1PzZeBSy8sJNsSJpiarKzeFGXHpbuCHm5Ien4eyccHPc/Ezi2J2vhhv02NnHH6+IpFfJWWFanrhJi9t2eag7GBIyCP3EqrbA0aqQKDUdherd4eFt6wthjeJRM2HiGeH+U7k5cZ384kT/2c60tnQsyxsKF385NH/ueiM8LB4pD6+avaE2Lks9nQYKJWuSmVoaYdW9IWED2PMmLPmTRMLW0hhGQVVuDk+Qp11x7BvekFFtnzYnLW67+kB2bni6zS3o+PQLYYDBhNMT6/TFHd7T8djDZSFZa6gJfdxSDfMXkcw15axwvzi0I/RNbT+XYnZe+L/tHkZ1TlgYauDnfwR+/+1wTPWuMBCpdl94ECzfANPPD/eQeNeLaee1bdKMtYSF3A/tDA990y+A4vEhyaveHY6xrMSgpZx8qClrG1vD4dAvd9ikPvnRyMmnZE0yU+XmRKIGoenxwGo45ZKwve2lsB4ohCfJtb+Ac/6iXT+OYyieAO//R3jm78NTcuFImHh6eKKG0C8k3ifNsmBMJws3p0oSiyeFmMo3hBv6hIUw+4Phe5HjoOlJTo6C2BEKW2s5kj2S5qyCqHQr8AfyY0eZ1riOobEaarJH0WK5jGkO87PHLJvNQ7I5+tpyZtZtZkRLBaObyxgSqyHPG6mLBjVVlLey+90K9ubPAmrg94+2ef8pDesZ17T7ve3DOY+yZcgSsryF0c1HyWtt4FDueOo2JWr9pjasY2xTImFrNWP1xiJasvL75GckJ5+SNclM2Xkdy7JyE98f3t12X+ORUPPV06bSiYvgU4+FiSyzskNtWE50g1v48bBun7eGofLF41Nfo3h8mKdtxyuhuaKkNPR9K98Q9ruH5tyxs8NEliLHQXM4ngS734AtzwF5kNUAC65u+3925Y+h9pTE9phZoWas/hCMnM7SeE19Q02o+d/6QqhBizUyIjsXsnKZNGUpi2ZeGs6r2Ru6UNRVhYfBWVfAG/8FjW0Xk7/swlvDUnqdaayFd38ephrKyoGZl3JWb6+HPEhlykOSkjXJTKNnhpm8402MBcNDYhU3vCTUqMXlDU2M4oQwT9LOV8Ixo2ZAydLO+29k58DkMzqWdzVRZXuTzgivuOTlY+LqDipZE8lUsRbY8fvEdmssDBCI/5+NNUNt23U/OVwWmhqTmxtjzYDDoo/D/OvCfGirHw7lo2dGNfiLwjxrax5LtCDsXxNGkhaMCA+fEPrr5g9LzPGWrL469I9trA1NtGf9aZjQN29oz5bfk35ByZpkpqxsWPypMGIz1hwGB+TkhSfH+kNhcsmmI1C5JdFnLbkJdN3jibmODu0Ic63NvPTkxT9mVhjSHx89lpWtRE0kk3lr20mxIfSNjcvODRNkH6lIlLXvE7bvXdjwK3DCw+aC62HBR2Deh8P9KPledrSqbVcPgOqdobvEuw+HFVcaDsPYObD9pUQXEAiJ3jsPhoQNwrXNQp9aGZCUrEnmysoKSQ+EZOv1/wo3w6FjoXA4LLoZFnys43nNDYlELa58/clN1oZNgvkfDfMvWVZYBkZD6UUyV05eqKE6sDZRNmlx22PmfjiM7Kw9EKboOO2KxL6affDCPyeWmqqvhqIJoca96QiMnB6+rv1F6Pw/fEpIAJMn447X0k07LySFYwpCs+bO18IcbvF1Q2v2JBK1uPINStYGMCVrkvlaGkOitvlZwEPTw6TFYah6qmQtOzc0AzTXJ8oKhp2saEO8m34bRoIVjghJYvGEk/f+InJ85lwdVic5ciAkV+2XlSoaF6bvce84WGjjbxLLS8WaoGozeAus/1V4YBs1IyRx8dq0io3hwdNjobVg1MxE7Vl9dVhdJa65PswTOeH0ML9afnFiJGrcybzHyUmnZE0yX+Wm0AGX6MbU2hz6oiUnY8mysmHW+0NfkdaWkLidklSr5h7mRIr3Z+vN4e0Vm2DFf4TRrPnF4Um9/lDPR6qKyMmXlQ1DRkJLfdtpfdpLNao7Fi1JFW86baiBspWJaXsO74b8dmt3NtfB+X8VmjWT+9SOnhmaQSH0XzuwJiR8h8vCwu6n3wgjZ4QWg5z8UGs/9RhrFEu/pmStl2XKyJGBZGTzPk6pX8/o5kPktYYFlmvLG1mzdxxVf1xOdmsTM+vfojhWzcGc8ZQVzKE5q4Ds1kIKvI66rHx83ZPvXW9KwwbGNe0CwA12FCxgf/ZkttblU9uSTXFOjJlDGsnL8pTxdMY8xsIjLzG+aQd5rY3APup37aU6Zzzr3mmiPltzrYlktB2vtF2r89T3hfnWumPMqaF5Mt5HNq8oMVAAQm1brKHtOfEa9/aDn0bPhDlXhfkl6ze0HaVeviE0t+YWhqRx4uKoz64mwB3IlKz1Mg2v7wOxZlh1T1gpoCbMacTZn2X2pMXhifTpO+HAvlCeXwWzR8CSz6S+VksjvHI3tI59r6i0aByP515Jc8XR98qmjB3KtYsn9yzOuoPwejVUDQ2TYEK4YU89myXnfr7rofdyQvSQJCes7hBsehpyCkItFsDuFaGGbfeKUCM/5WyYsCD1+TMuCV+rpoRloPKGwhs/DLVnEBoGZl0RWgbqDsKwiaEFoDMTF4XXxqfCMndx1TtDf7fcwtCsWr4GTr08rLwiA5aSNcl82blw5i1QsT4Mpx87B/KGhH0HtyXmM4PQH6Tsj3Dmp3s0Ae3Oqro22zsq6zo5Etj9R9j3dripz7gw9G2BMCS/cCSMmBaerBuqww157oeVqMkJKSoqUkLahyY0bmNS42YmNu2gFaMqdxIxy6MgVkPByw/TYnkczR5Oqz3FxiFLOZo9ovOLeStDW7eAO7PqsxnRUk9h7AhGKwcO/prq7HHsKpxLc1YTrHrkmLEVxmqZXfc22R4m6C6KVXEkqyFxf/NW3l2bS3P2kF74SUh7RUVFxz7oJFCyJv1DTl7bedbimmrDE2ZTUnNDvHkg5XXyYdKZIaGDcNzUcxi9I4+1ew5zuL6Zofk5LJw8PPX55evbrhe4+pHQHy1vaLjW6deHjsBF48IcbTMvV6ImJ+zmm29OdwgDV9NRePV74KVQPR6qdzBl6EjIK4ajWdAU/ZksHALj51M647ywBFQqjUfg7QegLlr5ZMKnefx3r3DtKY1QMJKS+OLwUxaE2rDuajgcBiTkDYX6w2EqD28N/XlbYywpcThlacfRqzJgKFmT/qv+UKjlaqwJzQr5w8LoyzM+2fV5p14easOOlodOusMmMqZiH3uqG2hojnGkMUb21E76f1RtbbsdawmjPuPrBg4dAwtvDE0mtftCR2UlayKZq6kuJD4Q1t/ML4a8QsiNJpctj6byqD8Y+p0NHdf5tcreiAZDRfavpjkrD4a0G6mZPKF3dxQMhylLE9v5Q0PzaG5hGL3a3BBGoI+aEY6VAUfJmvRfm6JlWiaXhr5sOXlw6d+F+Y+6YhY6A4859b2iPdUNLCoZTkurk5NlHKhpoLElRn5OuxGcQ8fSQfuyxlp4+8EQW1Rz12ZCSxHJHEVjQ014PIEqHBGWjytfH/rLDpscHrzMwlJy8bkfU2k/yS0QI6fjVELdXRmlMxMXwcHtbafu8NbwGZSsDUhK1qT/eq8T/9DEDbR44nFdqjAvm8P1Rm52aD7Ny8kiJyur43xKk8+EmrIwNUdWNky7INSmJdv1euLp2h12rQgLuWtSXJHMtPDjYRBBfXUYeTnhdBgyJjwEjjolJFenXNJ582fcuPlwYF1iO7+ImpwcOP1DoXtEQ02ohZ9y9onHPHJaSCjjsnNCYikDkpI16b9GTA39OOKGTUq9hl43nDdzNE+8vZeWVscMzjtlNNnbXwhD57NyYPqFULIkXH/Bx0LTSVZO6ibOxsNtt93DE7eSNZHMlF8UpulINmIKnHtHmNtsyOiu//+2xsJaxFVbwzxtuUPDQ9yUs/E1j4a1jM/sZIT68Zq4OCR/+1eHAVczLk4MvJIBR8ma9F/xpV6qd4YateSlX3po2uih3H7hDPZW1zOmKJ8RtVtg6+thZ6wZNj8TbrjF40NZVzfFsXPD5LhxBcPCuSLSv+QWdt3sGbf95VCDHlecH9b47K5DO8P5HoPJS0Lt3rGYwSkXh5cMeErWpP/KGwoLPtrz81pjsPNVOLQ99DebcRHkDWVIXg6njosmrt2zt+N5NXsSyVpXxs8L/UcOrA1P7FPP1eoFIv1JS2PowF+5KUzHM+sDXfczq9zcdrt2f6j16s4SUPXVYeH21mgR+epdcMan9IAnbShZk8Fn+0uhXxnA4T2hf9kZn2p7zPCSxPQeEJ5ih0/p/ntMWND55Jkiktm2/z7RH+xoZVh8/dy/DP3CUhkyqu0o0NwCyO1mk+TBrYlEDUK3icrN4R7UXB+SxqqtoVn1tCvD3I0y6Gh9CulfmutDorXtRThScXzXSG6iBKjeHeZaSjZuDpScFfqrVG0O/eGGjE7sP7gN3n0EVj8azheRgaOmrO12c32YuqMzp1waauAg9GM97crOE7v24uelKtv6QuiX29oSauvW/qLtCFAZNFSzJv1Hawze+ll40oUwx9qZn06sr9ddhSPCHG1xuYVhNYL2jhxINEUc3gM7Xg4jwmr3h0QtPjfTwe2w9E9T33RFpP8ZVgI1+xLbuYVQ2MUAg6Gj4ezPRvM9FvdsbsWRM8JktvveCYnYmFkwPqqVP9wuaWw4HF6FI7p/fRkQVLMm/cehHYlEDcLTZvKaed0187JEX5KG6vB142/aXrupLvQdSRZf1qpyUyJRi8fRfrJcEem/ZlwYptjIyg7Nj/M/cuyaMrOQtPV0EmyzMBjhnL+AxTeHRC2+nujwdlNxFAwLk3/LoKOaNek/slL8c+1uU0OyonFw9udgz6qwcHNzPexfExKucz4XlqTKyQ/9TpobEufFJ5tMNemkJqIUGThy8mH+dSf3PQ/tCA+N7iFJnHdtaF5troeqLVGftQ9ClupYBiP91qX/GDG17Yis3MIwzL2nmuuhtTk0cyYngM31YQg9hJvlrA8kksH8olAjB2Hiy9EzE+eNmwujE6shiIj0iDtseyHRH601BtteClMEnX49XPIVOOtPO9a0yaChmrVeVFRUxPLly9MdxsDmrQyPxcjxZqpzhhFb90i3TzVvZXL9Osa27AXLosVyyGttanPMug251GcnmhmyfQj5rXXUZ+Xiax5vc2x+rADMaNxcDq/88MQ+l5yQoqKidIcgktKI5gOw5n/CwvBTz05dC+8epgtJ1lLf8TgZtJSs9aKbb7453SEIhCVi9qwCorX8iidQ19TCH37/PMU7tmDZM5g+eihjCrNC37PKjezesYUp517Pkov+pvM50ZrqwkAENUOISHeUr2dm/TtQEf2pPbgNli7reA/JygpLXCX3wZ2w8KSFKZlPyZoMLHUH4a37E/MWVayHs/6MFTsbOVK1j2KgOeZsqzzKiCnDyWk5CiNnUFVWxxRvhV2vdVz/r7E2DJk/vCdMxDv7qjaLwIuIpHRgbdvt+kNhcu0RKeZsnPUBGDoOaveGOR0nLur8uq2xMA9kzR4YPjV0B9FD5ICm364MLBUb2k4wGWuByk1U1jZRXZC4QcZanYb6OsgugJZGRrYcgL1vhskw29v2YkjUIMzHtuFX4boiIl3JL267bRYe+FLJyg7rD8/9UJjKw6zz6276bTQH2ybY8jvY+lyvhSyZKa3Jmpllm9lbZvbraHuUmT1rZpujryOTjr3LzLaY2UYzO/5FIGVgS3UjzBvKtNFDOFxYwrZRF1GXO5qWoRMoLP1keBqt2EBua2NIxKq2dpyy40h52+3mBmis6bvPICJpFWt1yg7VUdPQfGIXmnI2jVmFie2Ss7peEL473OHAmrZl+1ef2DUl46W7GfQLwHog3qP7K8Bz7v5NM/tKtH2nmc0DbgLmA5OA35nZae4eS0fQkqEaj0D+8LDaQE20tufIaTB2DqVjs2iOOZvLT+fwtDO5YNYYsosLoGId7H0rHFswIow4Pbg9fI0bNaNtwlY4ou0EuLGW8FTc1ZOwiPQLh4428T9vllHb0IIZnDdzDEtnHGeCVTiCtUPP57zFHwy1bCeaqEG4z+QOCd0z4jqrrZMBI23JmpmVAFcD3wC+GBVfC1wSfX8v8CJwZ1T+kLs3AtvNbAuwFHjtJIYsmaxsVWgO8NZEv7KisSFxA7KBC2aN4YJZY9qeV1IKlZvZf8CYNOH0UDZ0bNtjpl8U+ohUbg5LTp16OS2tzoot+4ite5KJTTuYMn4MhXM/AOPn9/1nFZE+8/r2KmobQjcHd3htaxXzJw1jaH4nfy5bY50PSgLcsrpeBP54nHo5rP9V9N45iWmFZMBKZ83avwNfBpIb9ce7+z4Ad99nZuOi8snAiqTjyqKyDsxsGbAMYOrUqakOkYGmpRG2PZ9YVaDpaFjPc1IXHXTjRs2AaecQe+stsCyYuDDMm5YsOwdmvT+8Iq9uqmD/6peYcngjVUBD034W2pMwcrqeckX6sXiiFtfqTl1TrGOydrQK1j8Rlp8rngBzPxxWMDgZxs0NgxCOHAjvrXvOgJeWPmtmdg1Q7u6runtKirKUq9m6+3J3L3X30rFjx6Y6RAaa5rqOHf570qds5mW8U3QpnP+FsOxLN5ozt1cepagpsTzV0aYYjU1NHfu3iUi/MmdC2+WcxhTlMaYoxRJSG58MiRqErxufPAnRJckvCpNzK1EbFNJVs3Y+8GEzuwooAIaZ2c+AA2Y2MapVmwjE//KVAcljnUuAvSc1YslchSPb9lMDGDcv9bGH98DRitAskdTvrNVywvJS3TRqaB41+RMZWR9WPMjNNnLy8qF44nF9BJHBKhMnEj/SmEtlcw4FWa3kFDTxw9Ud6wbOrH0W80S525u8ubKhw3GQmZ+xNy1btizdIQx4aUnW3P0u4C4AM7sE+Ft3/5SZ/QtwC/DN6Gt8yvgngAfM7NuEAQazgDdOctiSyU6/Hna+BnVVYQ60SWd2PGb7y7DjlfB9VjYs+FjbZaN64KJZY3ni6JnsjdUxsWErU6dMIPv0K3uU8IlIP/5D/3ZxWM8zbuR0Shd/Im3hyMCW7tGg7X0TeNjMbgd2ATcAuPtaM3sYWAe0AHdoJKi0kTcUZr2v8/0tTbDr9cR2awx2/OG4k7XhQ3L59HmncLh+CkPzssnJ7qJHwdGqsMZfbmHnx4hI/zLnqjDf2eEyGF4Cp2lGKek7aU/W3P1FwqhP3L0KuLyT475BGDkq0nMeC69krSc4hxIwvDC3851NR+Hdh0N/lqxsmHFxWBtQRPq/guGw8MZ0RyGDRNqTNZET0lgbRnF2p5PtiGltmy1SNZXGla0MS08BTDkbpizteWw7X0t0QG6NhZUQxs2FgmFdniYiIpJMyZr0T62tYdh8+fowenPi4tAMkWok585XQ5NnrDmanmMRjJ3deRNo9W7Y/Gxie8tzUDS+7VxJB9aFPnCxxpD0zbiw43XqD7Xd9lZoqFayJiIiPaK1QaV/Kl8XEjUIM1fufQsObut4XN3BkFS1xkKiBmEm8a76qh3e3XVZ3cGQKNYfgqa6kAgeWNfxnDGz2m7nF0HxpK4/l4iISDuqWZP+qa4qRdnBjklY3cGQzB3r3GTDUiRUyVNyHC7reM3qXTC+3XQhkxaHJLF8bUgQp18YJtgVERHpAf3lkP5p9KmhT1k8acrKTl1b5g61eyE7P1qXzzrWeLU3cjqccjHsWgF46LOWfO1UydywTuZXK1kSXiIiIsdJyZr0T8Mnw7zroOyPIVGbcnbHRZL3rIJNz0Becaj5ysqBhTd0b/3OaeeFl3vHfnBDx8BpH4Dtvw/94CYthgkLe+uTiYiItKFkTfqvcXPCqzO7/xi+5heHBC0rJwxE6InOlp6avCQMLHCHLHX9FBGRvqNkTbqlPy6XMv/IqxS01r233WrZvL3hh7ilTq7642fsiX47U7yIyCCnZE26pV/+od93DmxIWlx5+vmcNeOi9MUjIiJyHJSsycA1cSEMHRv6qxWPDwMHRERE+hklazKwDZvY+UhNERGRfkA9o0VEREQymJI1ERERkQymZE1EREQkgylZExEREclgStZEREREMpiSNREREZEMpmRNREREJIMpWRMRERHJYErWRERERDKYkjURERGRDKZkTURERCSDmbunO4Y+Y2YVwM50xyH9whigMt1BiMiAo3uL9MQ0dx/bvnBAJ2si3WVmK929NN1xiMjAonuL9AY1g4qIiIhkMCVrIiIiIhlMyZpIsDzdAYjIgKR7i5ww9VkTERERyWCqWRMRERHJYErWRERETpCZvZruGGTgUjOoiIiISAZTzZoMGmb2GTN718zeMbOfmtk0M3suKnvOzKZGx91jZt8xs1fNbJuZXZ/u2EUks5nZkejrJWb2opk9amYbzOx+M7No31nRfeUdM3vDzIrTG7X0FznpDkDkZDCz+cBXgfPdvdLMRgH3Ave5+71mdhvwHeC66JSJwAXAHOAJ4NGTH7WI9FNnAPOBvcArwPlm9gbwc+Dj7v5HMxsG1KcxRulHVLMmg8VlwKPuXgng7geBc4EHov0/JSRncb9091Z3XweMP6mRikh/94a7l7l7K/A2MB2YDexz9z8CuHuNu7ekL0TpT5SsyWBhwLE6aCbvb2x3rohIdyXfP2KEVqzu3INEUlKyJoPFc8CNZjYaIGoGfRW4Kdr/SeAPaYpNRAa+DcAkMzsLwMyKzUxdkaRb9A9FBgV3X2tm3wBeMrMY8BbwV8CPzexLQAXwJ+mMUUQGLndvMrOPA981s0JCf7X3AUfSG5n0B5q6Q0RERCSDqRlUREREJIMpWRMRERHJYErWRERERDKYkjURERGRDKZkTURERCSDKVkTEemmaN3Y66Pv/9vM5kXf/127415NR3wiMjBp6g4RkW4ys3uAX7v7o+3Kj7h7UXqiEpGBTjVrIjJgmdlnzOxdM3vHzH5qZtPM7Lmo7Dkzmxodd4+ZfcfMXjWzbUm1Z2Zm3zOzdWb2JDAu6dovmlmpmX0TKDSzt83s/mjfkaTz/8XM1pjZ6mhSVMzskuj8R81sg5ndb2Za1kxEUtIKBiIyIJnZfOCrwPnuXhktMXYvcJ+732tmtwHfAa6LTpkIXADMAZ4AHgU+QliA+3RgPLAO+HHy+7j7V8zsL919cYowPgosBhYBY4A/mtnL0b4zgPnAXuAV4Hy05JmIpKCaNREZqC4DHnX3SgB3PwicCzwQ7f8pITmL+6W7t7r7OkJiBnAR8KC7x9x9L/B8D2O4IOn8A8BLwFnRvjfcvczdW4G3gek9vLaIDBJK1kRkoDLgWJ1yk/c3tjs31THHE0Nnkt8vhlo6RKQTStZEZKB6DrjRzEYDRM2grwI3Rfs/ybGbHV8GbjKzbDObCFzayXHNZpbbyfkfj84fS6ipe6OHn0NEBjk9yYnIgOTua83sG8BLZhYD3gL+CvixmX0JqAD+5BiX+QWhOXU1sInQjJnKcuBdM3vT3T/Z7vxzgXcINXRfdvf9ZjbneD+XiAw+mrpDREREJIOpGVREREQkgylZExEREclgStZEREREMpiSNREREZEMpmRNREREJIMpWRMRERHJYErWRERERDKYkjURERGRDPb/AxDiT16Y8pcYAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 720x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# plot accuracy as bar chart by condition and plot rt as a scatter plot by condition\n",
+    "\n",
+    "# accuracy\n",
+    "plt.figure()\n",
+    "sns.barplot(x='condition', y='correct', data=test)\n",
+    "plt.title('Accuracy by Condition')\n",
+    "plt.show()\n",
+    "\n",
+    "# rt\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "sns.boxplot(x='condition', y='response_time', data=test, showfliers=False, color='white')\n",
+    "sns.stripplot(x='condition', y='response_time', data=test, alpha=0.5, jitter=True, hue='correct')\n",
+    "plt.title('Response time by condition', fontsize=15, pad=20, color=\"black\")\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "tensorflow",
+   "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": "3.8.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/code/NFqC.py b/code/NFqC.py
new file mode 100644
index 0000000..7d2629b
--- /dev/null
+++ b/code/NFqC.py
@@ -0,0 +1,98 @@
+# run Quality Check against new sub data
+
+import os
+import sys
+import pandas as pd
+
+def parse_cmd_args():
+    import argparse
+    parser = argparse.ArgumentParser(description='QC for ATS')
+    parser.add_argument('-s', type=str, help='Path to submission')
+    parser.add_argument('-o', type=str, help='Path to output for QC plots and Logs')
+    parser.add_argument('-sub', type=str, help='Subject ID')
+
+    return parser.parse_args()
+
+def df(submission):
+    submission = pd.read_csv(submission)
+    return submission
+
+def qc(submission):
+    # convert submission to DataFrame
+    submission = df(submission)
+     # check if submission is a DataFrame
+    if not isinstance(submission, pd.DataFrame):
+        raise ValueError('Submission is not a DataFrame. Could not run QC')
+    # check if submission is empty
+    if submission.empty:
+        raise ValueError('Submission is empty')
+    # check if submission has correct number of rows (within 5% of expected = 145)
+    if len(submission) < 137 or len(submission) > 153:
+        raise ValueError('Submission has incorrect number of rows')
+    
+def plots(submission, output, sub):
+    import pandas as pd
+    import numpy as np
+    import matplotlib.pyplot as plt
+    import seaborn as sns
+    import os
+
+    #load csv
+    df = pd.read_csv(submission)
+
+    #drop practice data
+    test = df[df['block'] == 'test']
+    #group by condition (inc, con)
+    # plot accuracy as bar chart by condition and plot rt as a scatter plot by condition
+
+    # accuracy
+    plt.figure()
+    sns.barplot(x='condition', y='correct', data=test)
+    plt.title('Accuracy by Condition')
+    plt.savefig(os.path.join(output, f'{sub}_NF_acc.png'))
+    plt.close()
+
+    # rt
+    plt.figure(figsize=(10, 6))
+    sns.boxplot(x='condition', y='response_time', data=test, showfliers=False, color='white')
+    sns.stripplot(x='condition', y='response_time', data=test, alpha=0.5, jitter=True, hue='correct')
+    plt.title('Response time by condition', fontsize=15, pad=20, color="black")
+
+    plt.savefig(os.path.join(output, f'{sub}_NF_rt.png'))
+    plt.close()
+
+
+
+    
+
+def main():
+
+    #parse command line arguments
+    args = parse_cmd_args()
+    submission = args.s
+    output = args.o
+    sub = args.sub
+
+    # check if submission is a csv
+    if not submission.endswith('.csv'):
+        raise ValueError('Submission is not a csv')
+    # check if submission exists
+    if not os.path.exists(submission):
+        raise ValueError('Submission does not exist')
+    # run QC
+    qc(submission)
+    
+    print(f'QC passed for {submission}, generating plots...')
+    # generate plots
+    plots(submission, output, sub)
+    return submission
+    
+    
+if __name__ == '__main__':
+    main()
+
+
+    
+    
+
+
diff --git a/data/placeholder.txt b/data/placeholder.txt
new file mode 100644
index 0000000..e69de29