<?xml version="1.0" encoding="UTF-8"?><EOP xmlns="http://www.iers.org/2003/schema/iers">
<version>
<product>BulletinA</product>
<date>2016-05-05</date>
<volume>XXIX</volume>
<number>018</number>
</version>
<metaFileName/>
<headerLine>
<headerLineDate>
<sYear>Year</sYear>
<sMonth>Month</sMonth>
<sDay>Day</sDay>
<sTime>Time</sTime>
<sMJD>MJD</sMJD>
</headerLineDate>
<headerLineEOP>
<product source="BulletinA">
<sX>X</sX>
<ssigma_X>sigma_X</ssigma_X>
<sY>Y</sY>
<ssigma_Y>sigma_Y</ssigma_Y>
<sUT1-UTC>UT1-UTC</sUT1-UTC>
<ssigma_UT1-UTC>sigma_UT1-UTC</ssigma_UT1-UTC>
<sdPsi>dPsi</sdPsi>
<ssigma_dPsi>sigma_dPsi</ssigma_dPsi>
<sdEpsilon>dEpsilon</sdEpsilon>
<ssigma_dEpsilon>sigma_dEpsilon</ssigma_dEpsilon>
<sdX>dX</sdX>
<ssigma_dX>sigma_dX</ssigma_dX>
<sdY>dY</sdY>
<ssigma_dY>sigma_dY</ssigma_dY>
</product>
</headerLineEOP>
<headerLineUnits>
<product source="BulletinA">
<X>arcsec</X>
<sigma_X>arcsec</sigma_X>
<Y>arcsec</Y>
<sigma_Y>arcsec</sigma_Y>
<UT1-UTC>sec</UT1-UTC>
<sigma_UT1-UTC>sec</sigma_UT1-UTC>
<dPsi>marcsec</dPsi>
<sigma_dPsi>marcsec</sigma_dPsi>
<dEpsilon>marcsec</dEpsilon>
<sigma_dEpsilon>marcsec</sigma_dEpsilon>
<dX>marcsec</dX>
<sigma_dX>marcsec</sigma_dX>
<dY>marcsec</dY>
<sigma_dY>marcsec</sigma_dY>
</product>
</headerLineUnits>
</headerLine>
<data product="BulletinA" source="BulletinA">
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>29</dateDay>
<MJD>57507</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.03073</X>
<sigma_X>.00009</sigma_X>
<Y>0.46983</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.131725</UT1-UTC>
<sigma_UT1-UTC>0.000009</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>30</dateDay>
<MJD>57508</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.03233</X>
<sigma_X>.00009</sigma_X>
<Y>0.47097</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.133192</UT1-UTC>
<sigma_UT1-UTC>0.000011</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>01</dateDay>
<MJD>57509</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.03450</X>
<sigma_X>.00009</sigma_X>
<Y>0.47232</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.134844</UT1-UTC>
<sigma_UT1-UTC>0.000014</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>02</dateDay>
<MJD>57510</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.03667</X>
<sigma_X>.00009</sigma_X>
<Y>0.47395</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.136576</UT1-UTC>
<sigma_UT1-UTC>0.000016</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>03</dateDay>
<MJD>57511</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.03867</X>
<sigma_X>.00009</sigma_X>
<Y>0.47550</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.138546</UT1-UTC>
<sigma_UT1-UTC>0.000016</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>04</dateDay>
<MJD>57512</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.04061</X>
<sigma_X>.00009</sigma_X>
<Y>0.47682</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.140678</UT1-UTC>
<sigma_UT1-UTC>0.000017</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>05</dateDay>
<MJD>57513</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.04234</X>
<sigma_X>.00009</sigma_X>
<Y>0.47805</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.142905</UT1-UTC>
<sigma_UT1-UTC>0.000017</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>06</dateDay>
<MJD>57514</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0440</X>
<Y>0.4791</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.14505</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>07</dateDay>
<MJD>57515</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0456</X>
<Y>0.4800</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.14703</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>08</dateDay>
<MJD>57516</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0474</X>
<Y>0.4809</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.14880</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>09</dateDay>
<MJD>57517</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0493</X>
<Y>0.4817</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15036</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>10</dateDay>
<MJD>57518</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0512</X>
<Y>0.4825</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15174</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>11</dateDay>
<MJD>57519</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0533</X>
<Y>0.4834</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15299</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>12</dateDay>
<MJD>57520</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0555</X>
<Y>0.4842</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15419</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>13</dateDay>
<MJD>57521</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0576</X>
<Y>0.4850</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15538</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>14</dateDay>
<MJD>57522</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0597</X>
<Y>0.4858</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15661</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>15</dateDay>
<MJD>57523</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0619</X>
<Y>0.4866</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15788</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>16</dateDay>
<MJD>57524</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0640</X>
<Y>0.4873</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15922</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>17</dateDay>
<MJD>57525</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0661</X>
<Y>0.4879</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16060</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>18</dateDay>
<MJD>57526</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0683</X>
<Y>0.4885</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16198</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>19</dateDay>
<MJD>57527</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0705</X>
<Y>0.4890</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16328</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>20</dateDay>
<MJD>57528</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0727</X>
<Y>0.4895</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16450</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>21</dateDay>
<MJD>57529</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0749</X>
<Y>0.4900</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16562</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>22</dateDay>
<MJD>57530</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0772</X>
<Y>0.4905</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16662</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>23</dateDay>
<MJD>57531</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0794</X>
<Y>0.4910</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16753</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>24</dateDay>
<MJD>57532</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0817</X>
<Y>0.4914</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16838</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>25</dateDay>
<MJD>57533</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0839</X>
<Y>0.4918</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16920</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>26</dateDay>
<MJD>57534</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0861</X>
<Y>0.4921</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17004</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>27</dateDay>
<MJD>57535</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0884</X>
<Y>0.4924</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17094</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>28</dateDay>
<MJD>57536</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0906</X>
<Y>0.4927</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17194</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>29</dateDay>
<MJD>57537</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0929</X>
<Y>0.4929</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17308</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>30</dateDay>
<MJD>57538</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0951</X>
<Y>0.4931</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17437</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>31</dateDay>
<MJD>57539</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0974</X>
<Y>0.4933</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17577</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>01</dateDay>
<MJD>57540</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0997</X>
<Y>0.4934</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17723</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>02</dateDay>
<MJD>57541</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1019</X>
<Y>0.4935</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17868</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>03</dateDay>
<MJD>57542</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1042</X>
<Y>0.4936</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18003</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>04</dateDay>
<MJD>57543</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1065</X>
<Y>0.4936</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18126</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>05</dateDay>
<MJD>57544</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1087</X>
<Y>0.4936</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18233</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>06</dateDay>
<MJD>57545</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1110</X>
<Y>0.4935</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18328</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>07</dateDay>
<MJD>57546</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1132</X>
<Y>0.4935</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18416</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>08</dateDay>
<MJD>57547</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1155</X>
<Y>0.4933</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18500</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>09</dateDay>
<MJD>57548</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1178</X>
<Y>0.4932</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18587</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>10</dateDay>
<MJD>57549</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1200</X>
<Y>0.4930</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18677</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>11</dateDay>
<MJD>57550</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1223</X>
<Y>0.4928</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18770</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>12</dateDay>
<MJD>57551</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1246</X>
<Y>0.4925</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18865</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>13</dateDay>
<MJD>57552</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1268</X>
<Y>0.4922</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18960</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>14</dateDay>
<MJD>57553</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1290</X>
<Y>0.4919</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19053</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>15</dateDay>
<MJD>57554</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1313</X>
<Y>0.4916</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19140</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>16</dateDay>
<MJD>57555</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1335</X>
<Y>0.4912</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19221</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>17</dateDay>
<MJD>57556</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1357</X>
<Y>0.4907</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19294</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>18</dateDay>
<MJD>57557</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1379</X>
<Y>0.4903</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19359</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>19</dateDay>
<MJD>57558</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1402</X>
<Y>0.4898</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19416</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>20</dateDay>
<MJD>57559</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1423</X>
<Y>0.4893</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19467</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>21</dateDay>
<MJD>57560</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1445</X>
<Y>0.4887</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19515</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>22</dateDay>
<MJD>57561</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1467</X>
<Y>0.4881</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19564</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>23</dateDay>
<MJD>57562</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1489</X>
<Y>0.4875</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19618</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>24</dateDay>
<MJD>57563</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1510</X>
<Y>0.4868</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19683</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>25</dateDay>
<MJD>57564</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1532</X>
<Y>0.4861</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19759</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>26</dateDay>
<MJD>57565</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1553</X>
<Y>0.4854</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19848</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>27</dateDay>
<MJD>57566</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1574</X>
<Y>0.4847</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19948</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>28</dateDay>
<MJD>57567</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1595</X>
<Y>0.4839</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20054</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>29</dateDay>
<MJD>57568</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1616</X>
<Y>0.4830</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20160</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>30</dateDay>
<MJD>57569</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1637</X>
<Y>0.4822</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20261</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>01</dateDay>
<MJD>57570</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1658</X>
<Y>0.4813</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20350</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>02</dateDay>
<MJD>57571</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1678</X>
<Y>0.4804</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20425</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>03</dateDay>
<MJD>57572</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1698</X>
<Y>0.4794</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20486</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>04</dateDay>
<MJD>57573</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1718</X>
<Y>0.4785</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20537</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>05</dateDay>
<MJD>57574</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1738</X>
<Y>0.4775</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20585</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>06</dateDay>
<MJD>57575</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1758</X>
<Y>0.4764</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20635</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>07</dateDay>
<MJD>57576</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1778</X>
<Y>0.4754</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20689</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>08</dateDay>
<MJD>57577</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1797</X>
<Y>0.4743</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20749</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>09</dateDay>
<MJD>57578</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1816</X>
<Y>0.4731</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20813</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>10</dateDay>
<MJD>57579</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1835</X>
<Y>0.4720</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20880</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>11</dateDay>
<MJD>57580</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1854</X>
<Y>0.4708</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20946</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>12</dateDay>
<MJD>57581</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1872</X>
<Y>0.4696</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21009</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>13</dateDay>
<MJD>57582</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1891</X>
<Y>0.4683</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21069</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>14</dateDay>
<MJD>57583</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1909</X>
<Y>0.4670</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21122</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>15</dateDay>
<MJD>57584</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1927</X>
<Y>0.4657</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21169</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>16</dateDay>
<MJD>57585</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1944</X>
<Y>0.4644</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21210</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>17</dateDay>
<MJD>57586</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1962</X>
<Y>0.4631</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21247</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>18</dateDay>
<MJD>57587</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1979</X>
<Y>0.4617</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21283</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>19</dateDay>
<MJD>57588</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1996</X>
<Y>0.4603</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21322</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>20</dateDay>
<MJD>57589</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2012</X>
<Y>0.4588</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21368</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>21</dateDay>
<MJD>57590</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2029</X>
<Y>0.4574</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21426</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>22</dateDay>
<MJD>57591</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2045</X>
<Y>0.4559</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21498</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>23</dateDay>
<MJD>57592</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2061</X>
<Y>0.4544</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21585</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>24</dateDay>
<MJD>57593</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2076</X>
<Y>0.4529</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21686</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>25</dateDay>
<MJD>57594</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2092</X>
<Y>0.4513</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21794</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>26</dateDay>
<MJD>57595</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2107</X>
<Y>0.4497</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21904</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>27</dateDay>
<MJD>57596</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2121</X>
<Y>0.4481</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22009</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>28</dateDay>
<MJD>57597</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2136</X>
<Y>0.4465</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22103</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>29</dateDay>
<MJD>57598</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2150</X>
<Y>0.4448</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22186</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>30</dateDay>
<MJD>57599</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2164</X>
<Y>0.4432</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22257</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>31</dateDay>
<MJD>57600</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2178</X>
<Y>0.4415</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22319</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>01</dateDay>
<MJD>57601</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2191</X>
<Y>0.4398</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22379</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>02</dateDay>
<MJD>57602</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2204</X>
<Y>0.4380</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22440</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>03</dateDay>
<MJD>57603</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2216</X>
<Y>0.4363</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22507</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>04</dateDay>
<MJD>57604</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2229</X>
<Y>0.4345</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22580</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>05</dateDay>
<MJD>57605</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2241</X>
<Y>0.4327</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22660</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>06</dateDay>
<MJD>57606</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2252</X>
<Y>0.4309</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22743</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>07</dateDay>
<MJD>57607</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2264</X>
<Y>0.4291</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22826</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>08</dateDay>
<MJD>57608</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2275</X>
<Y>0.4272</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22908</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>09</dateDay>
<MJD>57609</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2286</X>
<Y>0.4254</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22984</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>10</dateDay>
<MJD>57610</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2296</X>
<Y>0.4235</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23055</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>11</dateDay>
<MJD>57611</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2306</X>
<Y>0.4216</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23118</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>12</dateDay>
<MJD>57612</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2316</X>
<Y>0.4197</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23175</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>13</dateDay>
<MJD>57613</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2325</X>
<Y>0.4178</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23226</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>14</dateDay>
<MJD>57614</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2334</X>
<Y>0.4158</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23275</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>15</dateDay>
<MJD>57615</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2343</X>
<Y>0.4139</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23326</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>16</dateDay>
<MJD>57616</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2351</X>
<Y>0.4119</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23383</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>17</dateDay>
<MJD>57617</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2359</X>
<Y>0.4099</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23451</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>18</dateDay>
<MJD>57618</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2367</X>
<Y>0.4079</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23534</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>19</dateDay>
<MJD>57619</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2374</X>
<Y>0.4059</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23635</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>20</dateDay>
<MJD>57620</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2381</X>
<Y>0.4039</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23754</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>21</dateDay>
<MJD>57621</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2387</X>
<Y>0.4019</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23884</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>22</dateDay>
<MJD>57622</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2394</X>
<Y>0.3998</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24018</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>23</dateDay>
<MJD>57623</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2399</X>
<Y>0.3978</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24149</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>24</dateDay>
<MJD>57624</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2405</X>
<Y>0.3957</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24270</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>25</dateDay>
<MJD>57625</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2410</X>
<Y>0.3937</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24378</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>26</dateDay>
<MJD>57626</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2415</X>
<Y>0.3916</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24475</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>27</dateDay>
<MJD>57627</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2419</X>
<Y>0.3895</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24562</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>28</dateDay>
<MJD>57628</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2423</X>
<Y>0.3874</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24645</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>29</dateDay>
<MJD>57629</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2427</X>
<Y>0.3854</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24729</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>30</dateDay>
<MJD>57630</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2430</X>
<Y>0.3833</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24820</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>31</dateDay>
<MJD>57631</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2433</X>
<Y>0.3812</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24918</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>01</dateDay>
<MJD>57632</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2435</X>
<Y>0.3790</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25025</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>02</dateDay>
<MJD>57633</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2437</X>
<Y>0.3769</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25138</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>03</dateDay>
<MJD>57634</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2439</X>
<Y>0.3748</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25256</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>04</dateDay>
<MJD>57635</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2440</X>
<Y>0.3727</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25374</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>05</dateDay>
<MJD>57636</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2441</X>
<Y>0.3706</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25490</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>06</dateDay>
<MJD>57637</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2442</X>
<Y>0.3685</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25601</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>07</dateDay>
<MJD>57638</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2442</X>
<Y>0.3663</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25707</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>08</dateDay>
<MJD>57639</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2442</X>
<Y>0.3642</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25806</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>09</dateDay>
<MJD>57640</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2441</X>
<Y>0.3621</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25900</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>10</dateDay>
<MJD>57641</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2440</X>
<Y>0.3600</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25992</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>11</dateDay>
<MJD>57642</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2439</X>
<Y>0.3579</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26085</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>12</dateDay>
<MJD>57643</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2437</X>
<Y>0.3557</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26182</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>13</dateDay>
<MJD>57644</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2435</X>
<Y>0.3536</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26291</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>14</dateDay>
<MJD>57645</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2433</X>
<Y>0.3515</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26414</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>15</dateDay>
<MJD>57646</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2430</X>
<Y>0.3494</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26556</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>16</dateDay>
<MJD>57647</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2427</X>
<Y>0.3473</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26719</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>17</dateDay>
<MJD>57648</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2423</X>
<Y>0.3452</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26899</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>18</dateDay>
<MJD>57649</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2419</X>
<Y>0.3431</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27088</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>19</dateDay>
<MJD>57650</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2415</X>
<Y>0.3410</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27279</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>20</dateDay>
<MJD>57651</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2410</X>
<Y>0.3389</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27462</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>21</dateDay>
<MJD>57652</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2405</X>
<Y>0.3368</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27631</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>22</dateDay>
<MJD>57653</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2400</X>
<Y>0.3348</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27785</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>23</dateDay>
<MJD>57654</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2394</X>
<Y>0.3327</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27927</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>24</dateDay>
<MJD>57655</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2388</X>
<Y>0.3307</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28063</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>25</dateDay>
<MJD>57656</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2381</X>
<Y>0.3286</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28197</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>26</dateDay>
<MJD>57657</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2375</X>
<Y>0.3266</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28334</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>27</dateDay>
<MJD>57658</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2367</X>
<Y>0.3246</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28479</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>28</dateDay>
<MJD>57659</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2360</X>
<Y>0.3225</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28631</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>29</dateDay>
<MJD>57660</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2352</X>
<Y>0.3205</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28790</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>30</dateDay>
<MJD>57661</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2343</X>
<Y>0.3186</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28955</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>01</dateDay>
<MJD>57662</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2335</X>
<Y>0.3166</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29120</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>02</dateDay>
<MJD>57663</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2326</X>
<Y>0.3146</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29285</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>03</dateDay>
<MJD>57664</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2316</X>
<Y>0.3127</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29444</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>04</dateDay>
<MJD>57665</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2307</X>
<Y>0.3107</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29598</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>05</dateDay>
<MJD>57666</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2297</X>
<Y>0.3088</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29745</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>06</dateDay>
<MJD>57667</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2286</X>
<Y>0.3069</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29884</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>07</dateDay>
<MJD>57668</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2276</X>
<Y>0.3050</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30019</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>08</dateDay>
<MJD>57669</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2265</X>
<Y>0.3032</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30153</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>09</dateDay>
<MJD>57670</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2253</X>
<Y>0.3013</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30289</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>10</dateDay>
<MJD>57671</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2241</X>
<Y>0.2995</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30432</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>11</dateDay>
<MJD>57672</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2229</X>
<Y>0.2976</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30587</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>12</dateDay>
<MJD>57673</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2217</X>
<Y>0.2958</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30759</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>13</dateDay>
<MJD>57674</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2204</X>
<Y>0.2941</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30950</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>14</dateDay>
<MJD>57675</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2191</X>
<Y>0.2923</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31161</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>15</dateDay>
<MJD>57676</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2178</X>
<Y>0.2905</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31386</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>16</dateDay>
<MJD>57677</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2164</X>
<Y>0.2888</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31618</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>17</dateDay>
<MJD>57678</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2150</X>
<Y>0.2871</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31847</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>18</dateDay>
<MJD>57679</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2136</X>
<Y>0.2854</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32064</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>19</dateDay>
<MJD>57680</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2122</X>
<Y>0.2838</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32265</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>20</dateDay>
<MJD>57681</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2107</X>
<Y>0.2821</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32450</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>21</dateDay>
<MJD>57682</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2092</X>
<Y>0.2805</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32624</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>22</dateDay>
<MJD>57683</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2076</X>
<Y>0.2789</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32793</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>23</dateDay>
<MJD>57684</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2061</X>
<Y>0.2774</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32962</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>24</dateDay>
<MJD>57685</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2045</X>
<Y>0.2758</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33134</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>25</dateDay>
<MJD>57686</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2029</X>
<Y>0.2743</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33313</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>26</dateDay>
<MJD>57687</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2012</X>
<Y>0.2728</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33498</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>27</dateDay>
<MJD>57688</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1996</X>
<Y>0.2713</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33686</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>28</dateDay>
<MJD>57689</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1979</X>
<Y>0.2699</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33876</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>29</dateDay>
<MJD>57690</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1961</X>
<Y>0.2684</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34064</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>30</dateDay>
<MJD>57691</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1944</X>
<Y>0.2671</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34248</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>10</dateMonth>
<dateDay>31</dateDay>
<MJD>57692</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1926</X>
<Y>0.2657</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34426</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>01</dateDay>
<MJD>57693</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1908</X>
<Y>0.2643</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34597</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>02</dateDay>
<MJD>57694</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1890</X>
<Y>0.2630</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34761</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>03</dateDay>
<MJD>57695</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1872</X>
<Y>0.2617</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34919</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>04</dateDay>
<MJD>57696</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1853</X>
<Y>0.2605</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35074</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>05</dateDay>
<MJD>57697</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1834</X>
<Y>0.2593</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35230</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>06</dateDay>
<MJD>57698</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1815</X>
<Y>0.2581</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35391</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>07</dateDay>
<MJD>57699</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1796</X>
<Y>0.2569</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35564</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>08</dateDay>
<MJD>57700</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1776</X>
<Y>0.2557</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35751</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>09</dateDay>
<MJD>57701</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1756</X>
<Y>0.2546</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35955</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>10</dateDay>
<MJD>57702</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1737</X>
<Y>0.2536</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36179</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>11</dateDay>
<MJD>57703</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1717</X>
<Y>0.2525</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36417</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>12</dateDay>
<MJD>57704</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1696</X>
<Y>0.2515</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36664</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>13</dateDay>
<MJD>57705</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1676</X>
<Y>0.2505</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36909</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>14</dateDay>
<MJD>57706</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1655</X>
<Y>0.2495</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37141</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>15</dateDay>
<MJD>57707</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1635</X>
<Y>0.2486</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37352</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>16</dateDay>
<MJD>57708</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1614</X>
<Y>0.2477</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37539</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>17</dateDay>
<MJD>57709</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1593</X>
<Y>0.2468</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37707</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>18</dateDay>
<MJD>57710</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1571</X>
<Y>0.2460</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37861</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>19</dateDay>
<MJD>57711</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1550</X>
<Y>0.2452</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38009</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>20</dateDay>
<MJD>57712</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1529</X>
<Y>0.2444</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38155</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>21</dateDay>
<MJD>57713</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1507</X>
<Y>0.2437</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38304</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>22</dateDay>
<MJD>57714</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1485</X>
<Y>0.2430</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38458</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>23</dateDay>
<MJD>57715</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1463</X>
<Y>0.2423</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38614</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>24</dateDay>
<MJD>57716</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1441</X>
<Y>0.2417</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38772</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>25</dateDay>
<MJD>57717</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1419</X>
<Y>0.2411</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38928</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>26</dateDay>
<MJD>57718</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1397</X>
<Y>0.2405</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39081</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>27</dateDay>
<MJD>57719</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1375</X>
<Y>0.2400</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39228</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>28</dateDay>
<MJD>57720</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1353</X>
<Y>0.2395</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39368</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>29</dateDay>
<MJD>57721</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1330</X>
<Y>0.2390</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39501</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>11</dateMonth>
<dateDay>30</dateDay>
<MJD>57722</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1308</X>
<Y>0.2386</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39628</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>01</dateDay>
<MJD>57723</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1285</X>
<Y>0.2382</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39749</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>02</dateDay>
<MJD>57724</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1262</X>
<Y>0.2379</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39868</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>03</dateDay>
<MJD>57725</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1240</X>
<Y>0.2375</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39987</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>04</dateDay>
<MJD>57726</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1217</X>
<Y>0.2372</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40112</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>05</dateDay>
<MJD>57727</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1194</X>
<Y>0.2370</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40247</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>06</dateDay>
<MJD>57728</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1171</X>
<Y>0.2368</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40399</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>07</dateDay>
<MJD>57729</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1149</X>
<Y>0.2366</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40567</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>08</dateDay>
<MJD>57730</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1126</X>
<Y>0.2364</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40749</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>09</dateDay>
<MJD>57731</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1103</X>
<Y>0.2363</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40938</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>10</dateDay>
<MJD>57732</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1080</X>
<Y>0.2362</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41129</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>11</dateDay>
<MJD>57733</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1057</X>
<Y>0.2362</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41320</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>12</dateDay>
<MJD>57734</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1034</X>
<Y>0.2362</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41507</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>13</dateDay>
<MJD>57735</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1011</X>
<Y>0.2362</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41679</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>14</dateDay>
<MJD>57736</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0988</X>
<Y>0.2362</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41834</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>15</dateDay>
<MJD>57737</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0966</X>
<Y>0.2363</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41976</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>16</dateDay>
<MJD>57738</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0943</X>
<Y>0.2365</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42115</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>17</dateDay>
<MJD>57739</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0920</X>
<Y>0.2366</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42249</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>18</dateDay>
<MJD>57740</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0897</X>
<Y>0.2368</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42390</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>19</dateDay>
<MJD>57741</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0874</X>
<Y>0.2371</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42535</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>20</dateDay>
<MJD>57742</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0852</X>
<Y>0.2373</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42681</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>21</dateDay>
<MJD>57743</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0829</X>
<Y>0.2376</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42820</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>22</dateDay>
<MJD>57744</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0807</X>
<Y>0.2380</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42955</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>23</dateDay>
<MJD>57745</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0784</X>
<Y>0.2383</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43085</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>24</dateDay>
<MJD>57746</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0762</X>
<Y>0.2387</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43214</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>25</dateDay>
<MJD>57747</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0739</X>
<Y>0.2392</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43341</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>26</dateDay>
<MJD>57748</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0717</X>
<Y>0.2396</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43462</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>27</dateDay>
<MJD>57749</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0695</X>
<Y>0.2402</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43577</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>28</dateDay>
<MJD>57750</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0673</X>
<Y>0.2407</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43690</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>29</dateDay>
<MJD>57751</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0651</X>
<Y>0.2413</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43800</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>30</dateDay>
<MJD>57752</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0629</X>
<Y>0.2419</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43907</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>12</dateMonth>
<dateDay>31</dateDay>
<MJD>57753</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0608</X>
<Y>0.2425</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44016</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>01</dateDay>
<MJD>57754</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0586</X>
<Y>0.2432</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44138</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>02</dateDay>
<MJD>57755</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0565</X>
<Y>0.2439</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44278</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>03</dateDay>
<MJD>57756</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0543</X>
<Y>0.2446</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44431</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>04</dateDay>
<MJD>57757</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0522</X>
<Y>0.2454</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44600</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>05</dateDay>
<MJD>57758</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0501</X>
<Y>0.2462</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44774</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>06</dateDay>
<MJD>57759</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0480</X>
<Y>0.2471</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44953</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>07</dateDay>
<MJD>57760</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0459</X>
<Y>0.2479</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45128</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>08</dateDay>
<MJD>57761</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0439</X>
<Y>0.2488</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45298</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>09</dateDay>
<MJD>57762</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0419</X>
<Y>0.2498</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45464</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>10</dateDay>
<MJD>57763</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0398</X>
<Y>0.2507</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45618</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>11</dateDay>
<MJD>57764</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0378</X>
<Y>0.2517</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45764</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>12</dateDay>
<MJD>57765</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0359</X>
<Y>0.2528</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45910</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>13</dateDay>
<MJD>57766</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0339</X>
<Y>0.2538</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46051</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>14</dateDay>
<MJD>57767</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0319</X>
<Y>0.2549</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46192</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>15</dateDay>
<MJD>57768</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0300</X>
<Y>0.2560</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46349</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>16</dateDay>
<MJD>57769</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0281</X>
<Y>0.2572</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46517</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>17</dateDay>
<MJD>57770</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0262</X>
<Y>0.2583</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46690</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>18</dateDay>
<MJD>57771</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0244</X>
<Y>0.2595</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46868</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>19</dateDay>
<MJD>57772</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0225</X>
<Y>0.2608</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47043</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>20</dateDay>
<MJD>57773</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0207</X>
<Y>0.2620</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47213</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>21</dateDay>
<MJD>57774</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0189</X>
<Y>0.2633</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47375</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>22</dateDay>
<MJD>57775</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0172</X>
<Y>0.2646</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47533</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>23</dateDay>
<MJD>57776</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0154</X>
<Y>0.2660</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47680</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>24</dateDay>
<MJD>57777</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0137</X>
<Y>0.2674</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47816</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>25</dateDay>
<MJD>57778</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0120</X>
<Y>0.2688</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47946</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>26</dateDay>
<MJD>57779</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0103</X>
<Y>0.2702</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48066</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>27</dateDay>
<MJD>57780</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0087</X>
<Y>0.2716</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48190</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>28</dateDay>
<MJD>57781</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0071</X>
<Y>0.2731</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48324</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>29</dateDay>
<MJD>57782</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0055</X>
<Y>0.2746</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48473</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>30</dateDay>
<MJD>57783</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0039</X>
<Y>0.2761</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48641</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>01</dateMonth>
<dateDay>31</dateDay>
<MJD>57784</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0024</X>
<Y>0.2777</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48822</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>01</dateDay>
<MJD>57785</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0009</X>
<Y>0.2792</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49011</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>02</dateDay>
<MJD>57786</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0006</X>
<Y>0.2808</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49207</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>03</dateDay>
<MJD>57787</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0020</X>
<Y>0.2824</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49406</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>04</dateDay>
<MJD>57788</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0034</X>
<Y>0.2841</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49597</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>05</dateDay>
<MJD>57789</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0048</X>
<Y>0.2857</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49774</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>06</dateDay>
<MJD>57790</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0062</X>
<Y>0.2874</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49937</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>07</dateDay>
<MJD>57791</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0075</X>
<Y>0.2891</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50096</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>08</dateDay>
<MJD>57792</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0088</X>
<Y>0.2908</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50254</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>09</dateDay>
<MJD>57793</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0101</X>
<Y>0.2926</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50416</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>10</dateDay>
<MJD>57794</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0113</X>
<Y>0.2943</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50586</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>11</dateDay>
<MJD>57795</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0125</X>
<Y>0.2961</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50769</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>12</dateDay>
<MJD>57796</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0137</X>
<Y>0.2979</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50955</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>13</dateDay>
<MJD>57797</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0148</X>
<Y>0.2997</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51150</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>14</dateDay>
<MJD>57798</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0159</X>
<Y>0.3016</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51345</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>15</dateDay>
<MJD>57799</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0170</X>
<Y>0.3034</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51538</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>16</dateDay>
<MJD>57800</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0180</X>
<Y>0.3053</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51730</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>17</dateDay>
<MJD>57801</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0190</X>
<Y>0.3072</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51913</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>18</dateDay>
<MJD>57802</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0200</X>
<Y>0.3090</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52084</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>19</dateDay>
<MJD>57803</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0209</X>
<Y>0.3110</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52253</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>20</dateDay>
<MJD>57804</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0218</X>
<Y>0.3129</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52407</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>21</dateDay>
<MJD>57805</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0227</X>
<Y>0.3148</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52555</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>22</dateDay>
<MJD>57806</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0235</X>
<Y>0.3168</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52702</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>23</dateDay>
<MJD>57807</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0243</X>
<Y>0.3187</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52849</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>24</dateDay>
<MJD>57808</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0251</X>
<Y>0.3207</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53004</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>25</dateDay>
<MJD>57809</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0258</X>
<Y>0.3227</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53169</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>26</dateDay>
<MJD>57810</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0265</X>
<Y>0.3247</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53347</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>27</dateDay>
<MJD>57811</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0271</X>
<Y>0.3267</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53538</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>28</dateDay>
<MJD>57812</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0277</X>
<Y>0.3287</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53749</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>01</dateDay>
<MJD>57813</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0283</X>
<Y>0.3308</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53969</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>02</dateDay>
<MJD>57814</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0289</X>
<Y>0.3328</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54186</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>03</dateDay>
<MJD>57815</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0294</X>
<Y>0.3349</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54403</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>04</dateDay>
<MJD>57816</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0298</X>
<Y>0.3369</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54600</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>05</dateDay>
<MJD>57817</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0303</X>
<Y>0.3390</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54790</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>06</dateDay>
<MJD>57818</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0307</X>
<Y>0.3410</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54970</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>07</dateDay>
<MJD>57819</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0310</X>
<Y>0.3431</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55144</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>08</dateDay>
<MJD>57820</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0313</X>
<Y>0.3452</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55312</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>09</dateDay>
<MJD>57821</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0316</X>
<Y>0.3473</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55490</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>10</dateDay>
<MJD>57822</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0319</X>
<Y>0.3494</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55679</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>11</dateDay>
<MJD>57823</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0321</X>
<Y>0.3515</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55883</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>12</dateDay>
<MJD>57824</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0323</X>
<Y>0.3536</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56092</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>13</dateDay>
<MJD>57825</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0324</X>
<Y>0.3557</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56310</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>14</dateDay>
<MJD>57826</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0325</X>
<Y>0.3578</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56533</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>15</dateDay>
<MJD>57827</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0326</X>
<Y>0.3599</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56761</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>16</dateDay>
<MJD>57828</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0326</X>
<Y>0.3620</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56990</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>17</dateDay>
<MJD>57829</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0326</X>
<Y>0.3641</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57214</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>18</dateDay>
<MJD>57830</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0325</X>
<Y>0.3662</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57427</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>19</dateDay>
<MJD>57831</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0324</X>
<Y>0.3683</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57625</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>20</dateDay>
<MJD>57832</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0323</X>
<Y>0.3704</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57821</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>21</dateDay>
<MJD>57833</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0321</X>
<Y>0.3725</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58004</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>22</dateDay>
<MJD>57834</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0319</X>
<Y>0.3746</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58193</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>23</dateDay>
<MJD>57835</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0317</X>
<Y>0.3767</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58380</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>24</dateDay>
<MJD>57836</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0314</X>
<Y>0.3788</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58572</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>25</dateDay>
<MJD>57837</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0311</X>
<Y>0.3808</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58774</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>26</dateDay>
<MJD>57838</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0308</X>
<Y>0.3829</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58994</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>27</dateDay>
<MJD>57839</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0304</X>
<Y>0.3850</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.59231</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>28</dateDay>
<MJD>57840</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0300</X>
<Y>0.3871</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.59484</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>29</dateDay>
<MJD>57841</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0295</X>
<Y>0.3891</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.59746</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>30</dateDay>
<MJD>57842</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0290</X>
<Y>0.3912</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.60006</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>03</dateMonth>
<dateDay>31</dateDay>
<MJD>57843</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0285</X>
<Y>0.3932</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.60253</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>01</dateDay>
<MJD>57844</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0279</X>
<Y>0.3953</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.60477</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>02</dateDay>
<MJD>57845</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0273</X>
<Y>0.3973</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.60682</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>03</dateDay>
<MJD>57846</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0267</X>
<Y>0.3993</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.60871</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>04</dateDay>
<MJD>57847</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0260</X>
<Y>0.4013</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.61043</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>05</dateDay>
<MJD>57848</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0253</X>
<Y>0.4033</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.61216</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>06</dateDay>
<MJD>57849</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0246</X>
<Y>0.4053</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.61390</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>07</dateDay>
<MJD>57850</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0238</X>
<Y>0.4073</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.61561</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>08</dateDay>
<MJD>57851</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0230</X>
<Y>0.4093</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.61731</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>09</dateDay>
<MJD>57852</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0221</X>
<Y>0.4112</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.61896</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>10</dateDay>
<MJD>57853</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0212</X>
<Y>0.4132</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.62057</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>11</dateDay>
<MJD>57854</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0203</X>
<Y>0.4151</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.62224</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>12</dateDay>
<MJD>57855</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0194</X>
<Y>0.4170</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.62373</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>13</dateDay>
<MJD>57856</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0184</X>
<Y>0.4189</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.62517</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>14</dateDay>
<MJD>57857</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0174</X>
<Y>0.4208</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.62655</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>15</dateDay>
<MJD>57858</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0163</X>
<Y>0.4227</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.62784</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>16</dateDay>
<MJD>57859</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0153</X>
<Y>0.4245</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.62905</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>17</dateDay>
<MJD>57860</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0142</X>
<Y>0.4264</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.63022</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>18</dateDay>
<MJD>57861</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0130</X>
<Y>0.4282</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.63149</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>19</dateDay>
<MJD>57862</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0118</X>
<Y>0.4300</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.63282</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>20</dateDay>
<MJD>57863</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0106</X>
<Y>0.4318</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.63417</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>21</dateDay>
<MJD>57864</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0094</X>
<Y>0.4335</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.63563</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>22</dateDay>
<MJD>57865</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0081</X>
<Y>0.4353</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.63721</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>23</dateDay>
<MJD>57866</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0068</X>
<Y>0.4370</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.63897</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>24</dateDay>
<MJD>57867</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0055</X>
<Y>0.4387</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.64083</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>25</dateDay>
<MJD>57868</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0042</X>
<Y>0.4404</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.64279</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>26</dateDay>
<MJD>57869</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0028</X>
<Y>0.4421</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.64477</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>27</dateDay>
<MJD>57870</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0014</X>
<Y>0.4437</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.64670</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>28</dateDay>
<MJD>57871</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0001</X>
<Y>0.4453</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.64849</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>29</dateDay>
<MJD>57872</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0015</X>
<Y>0.4469</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.65016</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>30</dateDay>
<MJD>57873</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0030</X>
<Y>0.4485</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.65164</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>01</dateDay>
<MJD>57874</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0046</X>
<Y>0.4500</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.65309</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>02</dateDay>
<MJD>57875</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0061</X>
<Y>0.4516</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.65448</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>03</dateDay>
<MJD>57876</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0077</X>
<Y>0.4531</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.65594</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>04</dateDay>
<MJD>57877</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0093</X>
<Y>0.4546</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.65748</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>05</dateDay>
<MJD>57878</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0109</X>
<Y>0.4560</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.65917</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
</data>
</EOP>
