<?xml version="1.0" encoding="UTF-8"?><EOP xmlns="http://www.iers.org/2003/schema/iers">
<version>
<product>BulletinA</product>
<date>2016-09-08</date>
<volume>XXIX</volume>
<number>036</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>08</dateMonth>
<dateDay>10</dateDay>
<MJD>57610</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-104.43</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-13.42</dEpsilon>
<sigma_dEpsilon>0.05</sigma_dEpsilon>
<dX>0.168</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.064</dY>
<sigma_dY>0.050</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>11</dateDay>
<MJD>57611</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-104.41</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-13.39</dEpsilon>
<sigma_dEpsilon>0.05</sigma_dEpsilon>
<dX>0.169</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.078</dY>
<sigma_dY>0.050</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>12</dateDay>
<MJD>57612</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-104.54</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-13.23</dEpsilon>
<sigma_dEpsilon>0.05</sigma_dEpsilon>
<dX>0.172</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.096</dY>
<sigma_dY>0.050</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>13</dateDay>
<MJD>57613</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-104.86</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-13.02</dEpsilon>
<sigma_dEpsilon>0.12</sigma_dEpsilon>
<dX>0.169</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.131</dY>
<sigma_dY>0.120</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>14</dateDay>
<MJD>57614</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-105.20</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-12.89</dEpsilon>
<sigma_dEpsilon>0.12</sigma_dEpsilon>
<dX>0.161</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.164</dY>
<sigma_dY>0.120</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>15</dateDay>
<MJD>57615</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-105.34</dPsi>
<sigma_dPsi>0.15</sigma_dPsi>
<dEpsilon>-12.95</dEpsilon>
<sigma_dEpsilon>0.14</sigma_dEpsilon>
<dX>0.167</dX>
<sigma_dX>0.060</sigma_dX>
<dY>-0.184</dY>
<sigma_dY>0.140</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>16</dateDay>
<MJD>57616</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-105.28</dPsi>
<sigma_dPsi>0.17</sigma_dPsi>
<dEpsilon>-13.18</dEpsilon>
<sigma_dEpsilon>0.16</sigma_dEpsilon>
<dX>0.180</dX>
<sigma_dX>0.068</sigma_dX>
<dY>-0.193</dY>
<sigma_dY>0.160</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>17</dateDay>
<MJD>57617</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-105.17</dPsi>
<sigma_dPsi>0.17</sigma_dPsi>
<dEpsilon>-13.40</dEpsilon>
<sigma_dEpsilon>0.16</sigma_dEpsilon>
<dX>0.188</dX>
<sigma_dX>0.068</sigma_dX>
<dY>-0.188</dY>
<sigma_dY>0.160</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>18</dateDay>
<MJD>57618</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-105.12</dPsi>
<sigma_dPsi>0.17</sigma_dPsi>
<dEpsilon>-13.42</dEpsilon>
<sigma_dEpsilon>0.16</sigma_dEpsilon>
<dX>0.195</dX>
<sigma_dX>0.068</sigma_dX>
<dY>-0.176</dY>
<sigma_dY>0.160</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>19</dateDay>
<MJD>57619</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-105.18</dPsi>
<sigma_dPsi>0.17</sigma_dPsi>
<dEpsilon>-13.22</dEpsilon>
<sigma_dEpsilon>0.16</sigma_dEpsilon>
<dX>0.198</dX>
<sigma_dX>0.068</sigma_dX>
<dY>-0.172</dY>
<sigma_dY>0.160</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>20</dateDay>
<MJD>57620</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-105.34</dPsi>
<sigma_dPsi>0.17</sigma_dPsi>
<dEpsilon>-12.97</dEpsilon>
<sigma_dEpsilon>0.16</sigma_dEpsilon>
<dX>0.198</dX>
<sigma_dX>0.068</sigma_dX>
<dY>-0.182</dY>
<sigma_dY>0.160</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>21</dateDay>
<MJD>57621</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-105.54</dPsi>
<sigma_dPsi>0.25</sigma_dPsi>
<dEpsilon>-12.87</dEpsilon>
<sigma_dEpsilon>0.08</sigma_dEpsilon>
<dX>0.202</dX>
<sigma_dX>0.099</sigma_dX>
<dY>-0.203</dY>
<sigma_dY>0.080</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>22</dateDay>
<MJD>57622</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-105.70</dPsi>
<sigma_dPsi>0.25</sigma_dPsi>
<dEpsilon>-12.94</dEpsilon>
<sigma_dEpsilon>0.08</sigma_dEpsilon>
<dX>0.208</dX>
<sigma_dX>0.099</sigma_dX>
<dY>-0.201</dY>
<sigma_dY>0.080</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>23</dateDay>
<MJD>57623</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-105.76</dPsi>
<sigma_dPsi>0.25</sigma_dPsi>
<dEpsilon>-13.05</dEpsilon>
<sigma_dEpsilon>0.08</sigma_dEpsilon>
<dX>0.208</dX>
<sigma_dX>0.099</sigma_dX>
<dY>-0.167</dY>
<sigma_dY>0.080</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>02</dateDay>
<MJD>57633</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.23682</X>
<sigma_X>.00009</sigma_X>
<Y>0.38804</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.247388</UT1-UTC>
<sigma_UT1-UTC>0.000025</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>03</dateDay>
<MJD>57634</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.23664</X>
<sigma_X>.00009</sigma_X>
<Y>0.38701</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.248197</UT1-UTC>
<sigma_UT1-UTC>0.000022</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>04</dateDay>
<MJD>57635</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.23602</X>
<sigma_X>.00009</sigma_X>
<Y>0.38569</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.249111</UT1-UTC>
<sigma_UT1-UTC>0.000017</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>05</dateDay>
<MJD>57636</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.23523</X>
<sigma_X>.00009</sigma_X>
<Y>0.38400</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.250080</UT1-UTC>
<sigma_UT1-UTC>0.000015</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>06</dateDay>
<MJD>57637</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.23463</X>
<sigma_X>.00009</sigma_X>
<Y>0.38211</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.250986</UT1-UTC>
<sigma_UT1-UTC>0.000014</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>07</dateDay>
<MJD>57638</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.23445</X>
<sigma_X>.00009</sigma_X>
<Y>0.38010</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.251951</UT1-UTC>
<sigma_UT1-UTC>0.000013</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>08</dateDay>
<MJD>57639</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.23455</X>
<sigma_X>.00009</sigma_X>
<Y>0.37800</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.252785</UT1-UTC>
<sigma_UT1-UTC>0.000014</sigma_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>0.2347</X>
<Y>0.3760</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25355</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>0.2349</X>
<Y>0.3739</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25426</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>0.2350</X>
<Y>0.3719</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25495</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>0.2350</X>
<Y>0.3700</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25567</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>0.2350</X>
<Y>0.3681</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25643</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>0.2349</X>
<Y>0.3662</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25731</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>0.2349</X>
<Y>0.3644</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25835</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>0.2348</X>
<Y>0.3625</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25958</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>0.2346</X>
<Y>0.3607</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26098</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>0.2345</X>
<Y>0.3588</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26252</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>0.2343</X>
<Y>0.3569</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26411</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>0.2342</X>
<Y>0.3551</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26567</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>0.2340</X>
<Y>0.3533</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26714</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>0.2336</X>
<Y>0.3516</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26847</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>0.2332</X>
<Y>0.3499</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26966</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>0.2328</X>
<Y>0.3481</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27076</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>0.2323</X>
<Y>0.3463</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27185</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>0.2318</X>
<Y>0.3445</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27298</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>0.2313</X>
<Y>0.3427</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27419</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>0.2308</X>
<Y>0.3409</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27549</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>0.2303</X>
<Y>0.3391</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27686</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>0.2297</X>
<Y>0.3374</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27828</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>0.2291</X>
<Y>0.3357</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27971</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>0.2285</X>
<Y>0.3339</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28113</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>0.2278</X>
<Y>0.3322</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28251</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>0.2271</X>
<Y>0.3305</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28383</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>0.2264</X>
<Y>0.3288</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28511</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>0.2256</X>
<Y>0.3271</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28633</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>0.2248</X>
<Y>0.3255</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28751</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>0.2240</X>
<Y>0.3238</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28869</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>0.2232</X>
<Y>0.3222</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28990</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>0.2223</X>
<Y>0.3206</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29118</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>0.2214</X>
<Y>0.3190</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29258</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>0.2205</X>
<Y>0.3174</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29413</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>0.2195</X>
<Y>0.3158</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29586</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>0.2185</X>
<Y>0.3142</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29776</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>0.2175</X>
<Y>0.3127</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29981</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>0.3111</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30191</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>0.2153</X>
<Y>0.3096</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30397</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>0.2142</X>
<Y>0.3081</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30591</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>0.2131</X>
<Y>0.3066</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30769</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>0.2119</X>
<Y>0.3052</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30931</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>0.2107</X>
<Y>0.3037</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31083</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>0.2095</X>
<Y>0.3023</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31230</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>0.2083</X>
<Y>0.3009</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31378</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>0.2070</X>
<Y>0.2995</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31531</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>0.2057</X>
<Y>0.2981</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31691</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>0.2044</X>
<Y>0.2968</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31857</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>0.2031</X>
<Y>0.2954</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32027</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>0.2017</X>
<Y>0.2941</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32198</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>0.2004</X>
<Y>0.2928</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32367</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>0.1989</X>
<Y>0.2916</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32531</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>0.1975</X>
<Y>0.2903</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32688</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>0.1961</X>
<Y>0.2891</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32836</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>0.1946</X>
<Y>0.2879</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32975</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>0.1931</X>
<Y>0.2867</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33108</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>0.1916</X>
<Y>0.2856</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33236</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>0.1901</X>
<Y>0.2844</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33363</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>0.1885</X>
<Y>0.2833</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33495</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>0.1869</X>
<Y>0.2822</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33637</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>0.1853</X>
<Y>0.2812</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33792</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>0.1837</X>
<Y>0.2802</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33965</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>0.1821</X>
<Y>0.2791</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34156</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>0.1804</X>
<Y>0.2782</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34365</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>0.1788</X>
<Y>0.2772</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34586</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>0.1771</X>
<Y>0.2763</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34810</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>0.1754</X>
<Y>0.2754</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35029</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>0.1737</X>
<Y>0.2745</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35236</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>0.1720</X>
<Y>0.2736</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35426</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>0.1702</X>
<Y>0.2728</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35604</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>0.1685</X>
<Y>0.2720</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35773</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>0.1667</X>
<Y>0.2712</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35938</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>0.1649</X>
<Y>0.2705</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36105</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>0.1631</X>
<Y>0.2697</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36276</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>0.1613</X>
<Y>0.2690</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36450</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>0.1595</X>
<Y>0.2684</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36626</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>0.1577</X>
<Y>0.2677</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36803</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>0.1558</X>
<Y>0.2671</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36976</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>0.1540</X>
<Y>0.2665</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37143</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>0.1521</X>
<Y>0.2660</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37303</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>0.1502</X>
<Y>0.2655</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37453</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>0.1484</X>
<Y>0.2650</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37594</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>0.1465</X>
<Y>0.2645</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37725</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>0.1446</X>
<Y>0.2641</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37850</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>0.1427</X>
<Y>0.2637</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37972</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>0.1408</X>
<Y>0.2633</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38093</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>0.1389</X>
<Y>0.2629</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38220</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>0.1370</X>
<Y>0.2626</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38357</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>0.1351</X>
<Y>0.2623</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38507</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>0.1331</X>
<Y>0.2621</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38671</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>0.1312</X>
<Y>0.2618</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38849</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>0.1293</X>
<Y>0.2616</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39039</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>0.1273</X>
<Y>0.2614</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39234</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>0.1254</X>
<Y>0.2613</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39429</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>0.1235</X>
<Y>0.2612</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39614</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>0.1215</X>
<Y>0.2611</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39786</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>0.1196</X>
<Y>0.2611</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39945</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>0.1177</X>
<Y>0.2610</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40093</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>0.1157</X>
<Y>0.2610</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40238</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>0.1138</X>
<Y>0.2611</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40383</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>0.1119</X>
<Y>0.2611</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40533</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>0.1099</X>
<Y>0.2612</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40687</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>0.1080</X>
<Y>0.2614</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40844</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>0.1061</X>
<Y>0.2615</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41001</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>0.1042</X>
<Y>0.2617</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41157</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>0.1023</X>
<Y>0.2619</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41307</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>0.1004</X>
<Y>0.2621</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41451</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>0.0985</X>
<Y>0.2624</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41586</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>0.0966</X>
<Y>0.2627</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41707</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>0.0947</X>
<Y>0.2630</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41820</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>0.0928</X>
<Y>0.2634</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41926</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>0.0909</X>
<Y>0.2638</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42029</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>0.0891</X>
<Y>0.2642</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42132</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>0.0872</X>
<Y>0.2647</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42240</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>0.0854</X>
<Y>0.2651</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.57643</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>0.0835</X>
<Y>0.2656</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.57514</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>0.0817</X>
<Y>0.2662</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.57371</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>0.0799</X>
<Y>0.2667</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.57214</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>0.0781</X>
<Y>0.2673</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.57046</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>0.0763</X>
<Y>0.2679</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.56871</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>0.0745</X>
<Y>0.2685</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.56697</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>0.0728</X>
<Y>0.2692</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.56528</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>0.0710</X>
<Y>0.2699</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.56369</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>0.0693</X>
<Y>0.2706</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.56222</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>0.0676</X>
<Y>0.2714</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.56084</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>0.0659</X>
<Y>0.2722</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.55950</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>0.0642</X>
<Y>0.2730</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.55815</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>0.0625</X>
<Y>0.2738</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.55675</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>0.0608</X>
<Y>0.2746</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.55528</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>0.0592</X>
<Y>0.2755</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.55375</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>0.0576</X>
<Y>0.2764</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.55219</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>0.0560</X>
<Y>0.2773</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.55064</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>0.0544</X>
<Y>0.2783</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.54913</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>0.0528</X>
<Y>0.2793</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.54768</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>0.0513</X>
<Y>0.2803</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.54631</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>0.0498</X>
<Y>0.2813</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.54503</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>0.0482</X>
<Y>0.2823</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.54383</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>0.0468</X>
<Y>0.2834</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.54270</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>0.0453</X>
<Y>0.2845</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.54160</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>0.0439</X>
<Y>0.2856</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.54051</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>0.0424</X>
<Y>0.2868</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.53937</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>0.0410</X>
<Y>0.2879</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.53813</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>0.0397</X>
<Y>0.2891</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.53677</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>0.0383</X>
<Y>0.2903</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.53525</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>0.0370</X>
<Y>0.2915</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.53357</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>0.0357</X>
<Y>0.2928</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.53178</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>0.0344</X>
<Y>0.2940</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.52991</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>0.0331</X>
<Y>0.2953</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.52804</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>0.0319</X>
<Y>0.2966</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.52621</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>0.0307</X>
<Y>0.2979</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.52448</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>0.0295</X>
<Y>0.2993</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.52286</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>0.0283</X>
<Y>0.3006</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.52132</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>0.0272</X>
<Y>0.3020</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.51984</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>0.0261</X>
<Y>0.3034</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.51834</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>0.0250</X>
<Y>0.3048</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.51679</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>0.0240</X>
<Y>0.3062</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.51514</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>0.0229</X>
<Y>0.3077</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.51341</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>0.0219</X>
<Y>0.3091</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.51161</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>0.0210</X>
<Y>0.3106</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.50979</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>0.0200</X>
<Y>0.3121</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.50797</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>0.0191</X>
<Y>0.3136</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.50621</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>0.0182</X>
<Y>0.3151</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.50451</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>0.0174</X>
<Y>0.3166</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.50290</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>0.0165</X>
<Y>0.3182</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.50136</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>0.0157</X>
<Y>0.3197</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.49990</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>0.0150</X>
<Y>0.3213</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.49848</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>0.0142</X>
<Y>0.3229</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.49707</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>0.0135</X>
<Y>0.3245</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.49562</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>0.0128</X>
<Y>0.3261</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.49409</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>0.0122</X>
<Y>0.3277</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.49242</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>0.0116</X>
<Y>0.3293</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.49059</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>0.0110</X>
<Y>0.3310</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.48859</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>0.0104</X>
<Y>0.3326</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.48643</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>0.0099</X>
<Y>0.3342</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.48418</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>0.0094</X>
<Y>0.3359</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.48191</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>0.0089</X>
<Y>0.3376</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.47969</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>0.0085</X>
<Y>0.3392</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.47758</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>0.0081</X>
<Y>0.3409</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.47560</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>0.0077</X>
<Y>0.3426</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.47374</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>0.0074</X>
<Y>0.3443</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.47196</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>0.0071</X>
<Y>0.3460</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.47021</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>0.0068</X>
<Y>0.3477</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.46842</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>0.0065</X>
<Y>0.3494</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.46657</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>0.0063</X>
<Y>0.3511</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.46464</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>0.0062</X>
<Y>0.3528</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.46264</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>0.0060</X>
<Y>0.3545</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.46062</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>0.0059</X>
<Y>0.3562</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.45861</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>0.0058</X>
<Y>0.3580</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.45666</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>0.0057</X>
<Y>0.3597</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.45480</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>0.0057</X>
<Y>0.3614</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.45304</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>0.0057</X>
<Y>0.3631</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.45139</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>0.0058</X>
<Y>0.3648</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.44983</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>0.0058</X>
<Y>0.3666</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.44833</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>0.0059</X>
<Y>0.3683</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.44684</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>0.0061</X>
<Y>0.3700</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.44531</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>0.0062</X>
<Y>0.3717</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.44368</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>0.0064</X>
<Y>0.3734</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.44191</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>0.0067</X>
<Y>0.3751</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.43995</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>0.0069</X>
<Y>0.3768</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.43779</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>0.0072</X>
<Y>0.3786</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.43545</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>0.0075</X>
<Y>0.3803</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.43296</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>0.0079</X>
<Y>0.3819</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.43041</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>0.0083</X>
<Y>0.3836</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.42789</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>0.0087</X>
<Y>0.3853</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.42548</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>0.0091</X>
<Y>0.3870</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.42323</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>0.0096</X>
<Y>0.3887</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.42112</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>0.0101</X>
<Y>0.3903</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.41913</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>0.0107</X>
<Y>0.3920</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.41720</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>0.0112</X>
<Y>0.3936</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.41529</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>0.0118</X>
<Y>0.3953</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.41334</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>0.0124</X>
<Y>0.3969</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.41134</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>0.0131</X>
<Y>0.3985</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.40929</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>0.0138</X>
<Y>0.4001</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.40721</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>0.0145</X>
<Y>0.4017</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.40515</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>0.0152</X>
<Y>0.4033</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.40315</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>0.0160</X>
<Y>0.4049</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.40125</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>0.0168</X>
<Y>0.4064</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.39950</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>0.0176</X>
<Y>0.4080</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.39789</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>0.0185</X>
<Y>0.4095</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.39641</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>0.0194</X>
<Y>0.4110</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.39501</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>0.0203</X>
<Y>0.4126</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.39367</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>0.0212</X>
<Y>0.4141</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.39233</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>0.0222</X>
<Y>0.4155</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.39093</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>0.0232</X>
<Y>0.4170</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.38948</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>0.0242</X>
<Y>0.4185</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.38782</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>0.0252</X>
<Y>0.4199</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.38604</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>0.0263</X>
<Y>0.4213</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.38400</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>0.0274</X>
<Y>0.4227</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.38177</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>0.0285</X>
<Y>0.4241</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.37947</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>0.0296</X>
<Y>0.4255</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.37721</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>0.0308</X>
<Y>0.4268</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.37490</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>0.0320</X>
<Y>0.4282</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.37294</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>0.0332</X>
<Y>0.4295</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.37115</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>0.0344</X>
<Y>0.4308</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.36953</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>0.0357</X>
<Y>0.4321</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.36803</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>0.0370</X>
<Y>0.4333</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.36651</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>0.0383</X>
<Y>0.4346</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.36503</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>0.0396</X>
<Y>0.4358</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.36351</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>0.0409</X>
<Y>0.4370</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.36180</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>06</dateDay>
<MJD>57879</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0423</X>
<Y>0.4382</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.36005</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>07</dateDay>
<MJD>57880</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0437</X>
<Y>0.4393</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.35823</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>08</dateDay>
<MJD>57881</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0451</X>
<Y>0.4405</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.35639</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>09</dateDay>
<MJD>57882</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0465</X>
<Y>0.4416</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.35455</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>10</dateDay>
<MJD>57883</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0480</X>
<Y>0.4427</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.35274</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>11</dateDay>
<MJD>57884</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0494</X>
<Y>0.4438</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.35102</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>12</dateDay>
<MJD>57885</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0509</X>
<Y>0.4448</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.34945</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>13</dateDay>
<MJD>57886</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0524</X>
<Y>0.4459</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.34796</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>14</dateDay>
<MJD>57887</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0539</X>
<Y>0.4469</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.34656</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>15</dateDay>
<MJD>57888</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0554</X>
<Y>0.4479</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.34518</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>16</dateDay>
<MJD>57889</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0570</X>
<Y>0.4488</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.34380</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>17</dateDay>
<MJD>57890</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0586</X>
<Y>0.4497</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.34247</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>18</dateDay>
<MJD>57891</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0601</X>
<Y>0.4507</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.34098</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>19</dateDay>
<MJD>57892</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0617</X>
<Y>0.4516</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.33939</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>20</dateDay>
<MJD>57893</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0633</X>
<Y>0.4524</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.33753</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>21</dateDay>
<MJD>57894</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0650</X>
<Y>0.4533</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.33556</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>22</dateDay>
<MJD>57895</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0666</X>
<Y>0.4541</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.33340</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>23</dateDay>
<MJD>57896</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0682</X>
<Y>0.4549</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.33112</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>24</dateDay>
<MJD>57897</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0699</X>
<Y>0.4556</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.32889</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>25</dateDay>
<MJD>57898</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0716</X>
<Y>0.4564</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.32670</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>26</dateDay>
<MJD>57899</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0733</X>
<Y>0.4571</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.32466</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>27</dateDay>
<MJD>57900</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0749</X>
<Y>0.4578</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.32270</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>28</dateDay>
<MJD>57901</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0767</X>
<Y>0.4584</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.32087</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>29</dateDay>
<MJD>57902</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0784</X>
<Y>0.4591</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.31911</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>30</dateDay>
<MJD>57903</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0801</X>
<Y>0.4597</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.31738</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>31</dateDay>
<MJD>57904</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0818</X>
<Y>0.4603</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.31565</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>01</dateDay>
<MJD>57905</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0836</X>
<Y>0.4608</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.31394</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>02</dateDay>
<MJD>57906</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0853</X>
<Y>0.4614</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.31221</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>03</dateDay>
<MJD>57907</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0871</X>
<Y>0.4619</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.31054</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>04</dateDay>
<MJD>57908</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0888</X>
<Y>0.4623</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.30898</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>05</dateDay>
<MJD>57909</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0906</X>
<Y>0.4628</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.30754</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>06</dateDay>
<MJD>57910</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0924</X>
<Y>0.4632</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.30625</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>07</dateDay>
<MJD>57911</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0942</X>
<Y>0.4636</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.30516</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>08</dateDay>
<MJD>57912</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0960</X>
<Y>0.4640</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.30429</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>09</dateDay>
<MJD>57913</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0978</X>
<Y>0.4643</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.30345</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>10</dateDay>
<MJD>57914</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0996</X>
<Y>0.4646</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.30282</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>11</dateDay>
<MJD>57915</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1014</X>
<Y>0.4649</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.30221</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>12</dateDay>
<MJD>57916</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1032</X>
<Y>0.4652</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.30155</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>13</dateDay>
<MJD>57917</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1050</X>
<Y>0.4654</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.30089</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>14</dateDay>
<MJD>57918</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1068</X>
<Y>0.4656</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.30017</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>15</dateDay>
<MJD>57919</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1086</X>
<Y>0.4658</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.29938</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>16</dateDay>
<MJD>57920</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1104</X>
<Y>0.4660</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.29855</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>17</dateDay>
<MJD>57921</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1122</X>
<Y>0.4661</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.29759</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>18</dateDay>
<MJD>57922</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1140</X>
<Y>0.4662</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.29650</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>19</dateDay>
<MJD>57923</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1158</X>
<Y>0.4663</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.29530</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>20</dateDay>
<MJD>57924</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1176</X>
<Y>0.4663</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.29408</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>21</dateDay>
<MJD>57925</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1194</X>
<Y>0.4663</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.29289</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>22</dateDay>
<MJD>57926</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1212</X>
<Y>0.4663</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.29173</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>23</dateDay>
<MJD>57927</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1230</X>
<Y>0.4663</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.29071</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>24</dateDay>
<MJD>57928</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1248</X>
<Y>0.4662</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28980</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>25</dateDay>
<MJD>57929</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1266</X>
<Y>0.4661</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28891</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>26</dateDay>
<MJD>57930</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1284</X>
<Y>0.4660</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28802</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>27</dateDay>
<MJD>57931</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1302</X>
<Y>0.4658</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28717</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>28</dateDay>
<MJD>57932</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1320</X>
<Y>0.4656</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28628</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>29</dateDay>
<MJD>57933</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1338</X>
<Y>0.4654</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28540</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>30</dateDay>
<MJD>57934</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1355</X>
<Y>0.4652</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28448</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>01</dateDay>
<MJD>57935</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1373</X>
<Y>0.4650</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28358</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>02</dateDay>
<MJD>57936</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1390</X>
<Y>0.4647</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28272</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>03</dateDay>
<MJD>57937</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1408</X>
<Y>0.4644</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28201</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>04</dateDay>
<MJD>57938</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1425</X>
<Y>0.4640</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28142</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>05</dateDay>
<MJD>57939</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1442</X>
<Y>0.4637</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28099</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>06</dateDay>
<MJD>57940</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1460</X>
<Y>0.4633</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28077</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>07</dateDay>
<MJD>57941</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1477</X>
<Y>0.4629</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28072</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>08</dateDay>
<MJD>57942</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1494</X>
<Y>0.4624</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28076</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>09</dateDay>
<MJD>57943</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1510</X>
<Y>0.4620</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28081</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>10</dateDay>
<MJD>57944</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1527</X>
<Y>0.4615</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28092</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>11</dateDay>
<MJD>57945</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1544</X>
<Y>0.4609</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28097</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>12</dateDay>
<MJD>57946</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1560</X>
<Y>0.4604</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28100</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>13</dateDay>
<MJD>57947</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1577</X>
<Y>0.4598</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28087</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>14</dateDay>
<MJD>57948</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1593</X>
<Y>0.4592</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28061</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>15</dateDay>
<MJD>57949</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1609</X>
<Y>0.4586</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.28019</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>16</dateDay>
<MJD>57950</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1625</X>
<Y>0.4580</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27960</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>17</dateDay>
<MJD>57951</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1641</X>
<Y>0.4573</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27890</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>18</dateDay>
<MJD>57952</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1657</X>
<Y>0.4566</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27817</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>19</dateDay>
<MJD>57953</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1672</X>
<Y>0.4559</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27750</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>20</dateDay>
<MJD>57954</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1687</X>
<Y>0.4552</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27689</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>21</dateDay>
<MJD>57955</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1703</X>
<Y>0.4544</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27645</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>22</dateDay>
<MJD>57956</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1718</X>
<Y>0.4536</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27608</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>23</dateDay>
<MJD>57957</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1732</X>
<Y>0.4528</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27573</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>24</dateDay>
<MJD>57958</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1747</X>
<Y>0.4520</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27533</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>25</dateDay>
<MJD>57959</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1762</X>
<Y>0.4512</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27487</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>26</dateDay>
<MJD>57960</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1776</X>
<Y>0.4503</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27430</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>27</dateDay>
<MJD>57961</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1790</X>
<Y>0.4494</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27367</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>28</dateDay>
<MJD>57962</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1804</X>
<Y>0.4485</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27304</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>29</dateDay>
<MJD>57963</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1818</X>
<Y>0.4476</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27251</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>30</dateDay>
<MJD>57964</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1831</X>
<Y>0.4466</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27208</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>07</dateMonth>
<dateDay>31</dateDay>
<MJD>57965</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1845</X>
<Y>0.4456</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27173</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>01</dateDay>
<MJD>57966</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1858</X>
<Y>0.4446</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27142</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>02</dateDay>
<MJD>57967</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1871</X>
<Y>0.4436</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27115</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>03</dateDay>
<MJD>57968</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1884</X>
<Y>0.4426</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27098</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>04</dateDay>
<MJD>57969</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1896</X>
<Y>0.4415</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27083</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>05</dateDay>
<MJD>57970</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1908</X>
<Y>0.4405</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27069</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>06</dateDay>
<MJD>57971</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1920</X>
<Y>0.4394</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27044</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>07</dateDay>
<MJD>57972</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1932</X>
<Y>0.4383</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.27014</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>08</dateDay>
<MJD>57973</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1944</X>
<Y>0.4371</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.26974</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>09</dateDay>
<MJD>57974</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1955</X>
<Y>0.4360</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.26922</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>10</dateDay>
<MJD>57975</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1966</X>
<Y>0.4348</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.26855</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>11</dateDay>
<MJD>57976</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1977</X>
<Y>0.4337</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.26775</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>12</dateDay>
<MJD>57977</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1988</X>
<Y>0.4325</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.26688</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>13</dateDay>
<MJD>57978</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1998</X>
<Y>0.4313</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.26596</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>14</dateDay>
<MJD>57979</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2008</X>
<Y>0.4300</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.26500</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>15</dateDay>
<MJD>57980</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2018</X>
<Y>0.4288</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.26401</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>16</dateDay>
<MJD>57981</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2028</X>
<Y>0.4276</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.26306</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>17</dateDay>
<MJD>57982</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2037</X>
<Y>0.4263</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.26227</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>18</dateDay>
<MJD>57983</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2047</X>
<Y>0.4250</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.26165</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>19</dateDay>
<MJD>57984</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2055</X>
<Y>0.4237</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.26109</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>20</dateDay>
<MJD>57985</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2064</X>
<Y>0.4224</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.26038</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>21</dateDay>
<MJD>57986</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2072</X>
<Y>0.4211</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.25950</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>22</dateDay>
<MJD>57987</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2081</X>
<Y>0.4198</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.25855</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>23</dateDay>
<MJD>57988</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2088</X>
<Y>0.4184</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.25752</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>24</dateDay>
<MJD>57989</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2096</X>
<Y>0.4171</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.25648</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>25</dateDay>
<MJD>57990</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2103</X>
<Y>0.4157</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.25541</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>26</dateDay>
<MJD>57991</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2110</X>
<Y>0.4143</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.25446</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>27</dateDay>
<MJD>57992</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2117</X>
<Y>0.4129</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.25356</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>28</dateDay>
<MJD>57993</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2123</X>
<Y>0.4115</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.25276</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>29</dateDay>
<MJD>57994</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2130</X>
<Y>0.4101</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.25208</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>30</dateDay>
<MJD>57995</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2136</X>
<Y>0.4087</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.25156</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>08</dateMonth>
<dateDay>31</dateDay>
<MJD>57996</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2141</X>
<Y>0.4073</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.25112</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>09</dateMonth>
<dateDay>01</dateDay>
<MJD>57997</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2147</X>
<Y>0.4059</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.25070</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>09</dateMonth>
<dateDay>02</dateDay>
<MJD>57998</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2152</X>
<Y>0.4044</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.25020</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>09</dateMonth>
<dateDay>03</dateDay>
<MJD>57999</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2156</X>
<Y>0.4030</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.24957</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>09</dateMonth>
<dateDay>04</dateDay>
<MJD>58000</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2161</X>
<Y>0.4015</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.24880</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>09</dateMonth>
<dateDay>05</dateDay>
<MJD>58001</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2165</X>
<Y>0.4001</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.24785</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>09</dateMonth>
<dateDay>06</dateDay>
<MJD>58002</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2169</X>
<Y>0.3986</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.24668</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>09</dateMonth>
<dateDay>07</dateDay>
<MJD>58003</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2173</X>
<Y>0.3972</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.24534</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>09</dateMonth>
<dateDay>08</dateDay>
<MJD>58004</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2176</X>
<Y>0.3957</Y>
</pole>
<UT type="prediction">
<UT1-UTC>0.24391</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
</data>
</EOP>
