<?xml version="1.0" encoding="UTF-8"?><EOP xmlns="http://www.iers.org/2003/schema/iers">
<version>
<product>BulletinA</product>
<date>2016-03-31</date>
<volume>XXIX</volume>
<number>013</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>03</dateMonth>
<dateDay>09</dateDay>
<MJD>57456</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-92.98</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-11.69</dEpsilon>
<sigma_dEpsilon>0.02</sigma_dEpsilon>
<dX>0.037</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.076</dY>
<sigma_dY>0.020</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>10</dateDay>
<MJD>57457</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-92.65</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-11.45</dEpsilon>
<sigma_dEpsilon>0.02</sigma_dEpsilon>
<dX>0.025</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.058</dY>
<sigma_dY>0.020</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>11</dateDay>
<MJD>57458</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-92.71</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-11.39</dEpsilon>
<sigma_dEpsilon>0.02</sigma_dEpsilon>
<dX>0.012</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.041</dY>
<sigma_dY>0.020</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>12</dateDay>
<MJD>57459</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.09</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-11.53</dEpsilon>
<sigma_dEpsilon>0.15</sigma_dEpsilon>
<dX>0.009</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.033</dY>
<sigma_dY>0.150</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>13</dateDay>
<MJD>57460</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.48</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-11.72</dEpsilon>
<sigma_dEpsilon>0.15</sigma_dEpsilon>
<dX>0.018</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.028</dY>
<sigma_dY>0.150</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>14</dateDay>
<MJD>57461</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.64</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-11.88</dEpsilon>
<sigma_dEpsilon>0.15</sigma_dEpsilon>
<dX>0.022</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.013</dY>
<sigma_dY>0.150</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>15</dateDay>
<MJD>57462</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.53</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-12.03</dEpsilon>
<sigma_dEpsilon>0.15</sigma_dEpsilon>
<dX>0.015</dX>
<sigma_dX>0.119</sigma_dX>
<dY>0.016</dY>
<sigma_dY>0.150</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>25</dateDay>
<MJD>57472</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.01322</X>
<sigma_X>.00009</sigma_X>
<Y>0.40840</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.069337</UT1-UTC>
<sigma_UT1-UTC>0.000013</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>26</dateDay>
<MJD>57473</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.01259</X>
<sigma_X>.00009</sigma_X>
<Y>0.41044</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.071394</UT1-UTC>
<sigma_UT1-UTC>0.000010</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>27</dateDay>
<MJD>57474</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.01184</X>
<sigma_X>.00009</sigma_X>
<Y>0.41254</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.073409</UT1-UTC>
<sigma_UT1-UTC>0.000012</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>28</dateDay>
<MJD>57475</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.01105</X>
<sigma_X>.00009</sigma_X>
<Y>0.41449</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.075334</UT1-UTC>
<sigma_UT1-UTC>0.000013</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>29</dateDay>
<MJD>57476</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.01021</X>
<sigma_X>.00009</sigma_X>
<Y>0.41628</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.077144</UT1-UTC>
<sigma_UT1-UTC>0.000014</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>30</dateDay>
<MJD>57477</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.00937</X>
<sigma_X>.00009</sigma_X>
<Y>0.41800</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.078948</UT1-UTC>
<sigma_UT1-UTC>0.000014</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>03</dateMonth>
<dateDay>31</dateDay>
<MJD>57478</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>-.00865</X>
<sigma_X>.00009</sigma_X>
<Y>0.41971</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.080661</UT1-UTC>
<sigma_UT1-UTC>0.000015</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>01</dateDay>
<MJD>57479</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0079</X>
<Y>0.4213</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.08243</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>02</dateDay>
<MJD>57480</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0071</X>
<Y>0.4229</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.08424</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>03</dateDay>
<MJD>57481</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0063</X>
<Y>0.4245</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.08613</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>04</dateDay>
<MJD>57482</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0054</X>
<Y>0.4260</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.08814</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>05</dateDay>
<MJD>57483</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0043</X>
<Y>0.4275</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.09029</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>06</dateDay>
<MJD>57484</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0032</X>
<Y>0.4289</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.09254</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>07</dateDay>
<MJD>57485</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0020</X>
<Y>0.4304</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.09485</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>08</dateDay>
<MJD>57486</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0007</X>
<Y>0.4319</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.09714</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>09</dateDay>
<MJD>57487</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0006</X>
<Y>0.4335</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.09931</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>10</dateDay>
<MJD>57488</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0019</X>
<Y>0.4350</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.10134</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>11</dateDay>
<MJD>57489</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0032</X>
<Y>0.4365</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.10324</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>12</dateDay>
<MJD>57490</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0046</X>
<Y>0.4380</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.10507</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>13</dateDay>
<MJD>57491</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0060</X>
<Y>0.4395</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.10685</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>14</dateDay>
<MJD>57492</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0074</X>
<Y>0.4409</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.10863</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>15</dateDay>
<MJD>57493</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0088</X>
<Y>0.4423</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.11044</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>16</dateDay>
<MJD>57494</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0103</X>
<Y>0.4437</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.11228</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>17</dateDay>
<MJD>57495</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0117</X>
<Y>0.4451</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.11418</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>18</dateDay>
<MJD>57496</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0133</X>
<Y>0.4465</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.11612</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>19</dateDay>
<MJD>57497</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0148</X>
<Y>0.4479</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.11809</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>20</dateDay>
<MJD>57498</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0163</X>
<Y>0.4493</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.12005</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>21</dateDay>
<MJD>57499</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0179</X>
<Y>0.4506</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.12199</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>22</dateDay>
<MJD>57500</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0195</X>
<Y>0.4519</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.12388</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>23</dateDay>
<MJD>57501</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0211</X>
<Y>0.4532</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.12568</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>24</dateDay>
<MJD>57502</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0227</X>
<Y>0.4544</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.12740</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>25</dateDay>
<MJD>57503</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0244</X>
<Y>0.4556</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.12905</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>26</dateDay>
<MJD>57504</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0260</X>
<Y>0.4568</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.13064</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>27</dateDay>
<MJD>57505</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0277</X>
<Y>0.4579</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.13219</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>28</dateDay>
<MJD>57506</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0294</X>
<Y>0.4591</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.13373</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>29</dateDay>
<MJD>57507</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0312</X>
<Y>0.4602</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.13532</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>04</dateMonth>
<dateDay>30</dateDay>
<MJD>57508</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0329</X>
<Y>0.4613</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.13700</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>01</dateDay>
<MJD>57509</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0347</X>
<Y>0.4623</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.13881</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>02</dateDay>
<MJD>57510</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0365</X>
<Y>0.4633</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.14078</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>03</dateDay>
<MJD>57511</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0383</X>
<Y>0.4643</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.14289</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>04</dateDay>
<MJD>57512</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0402</X>
<Y>0.4653</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.14510</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>05</dateDay>
<MJD>57513</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0420</X>
<Y>0.4663</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.14733</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>06</dateDay>
<MJD>57514</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0439</X>
<Y>0.4672</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.14949</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>07</dateDay>
<MJD>57515</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0458</X>
<Y>0.4681</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15151</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>08</dateDay>
<MJD>57516</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0477</X>
<Y>0.4689</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15334</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>09</dateDay>
<MJD>57517</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0496</X>
<Y>0.4697</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15501</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>10</dateDay>
<MJD>57518</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0516</X>
<Y>0.4705</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15653</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>11</dateDay>
<MJD>57519</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0535</X>
<Y>0.4713</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15798</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>12</dateDay>
<MJD>57520</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0555</X>
<Y>0.4721</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.15939</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>13</dateDay>
<MJD>57521</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0575</X>
<Y>0.4728</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16080</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>14</dateDay>
<MJD>57522</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0595</X>
<Y>0.4735</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16224</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>15</dateDay>
<MJD>57523</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0615</X>
<Y>0.4741</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16370</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>16</dateDay>
<MJD>57524</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0635</X>
<Y>0.4747</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16519</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>17</dateDay>
<MJD>57525</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0655</X>
<Y>0.4753</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16668</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>18</dateDay>
<MJD>57526</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0676</X>
<Y>0.4759</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16816</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>19</dateDay>
<MJD>57527</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0696</X>
<Y>0.4764</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.16958</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>20</dateDay>
<MJD>57528</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0717</X>
<Y>0.4769</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17094</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>21</dateDay>
<MJD>57529</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0737</X>
<Y>0.4774</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17223</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>22</dateDay>
<MJD>57530</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0758</X>
<Y>0.4778</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17344</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>23</dateDay>
<MJD>57531</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0779</X>
<Y>0.4782</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17459</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>24</dateDay>
<MJD>57532</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0800</X>
<Y>0.4786</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17569</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>25</dateDay>
<MJD>57533</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0821</X>
<Y>0.4790</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17680</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>26</dateDay>
<MJD>57534</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0842</X>
<Y>0.4793</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17794</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>27</dateDay>
<MJD>57535</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0863</X>
<Y>0.4796</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.17916</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>28</dateDay>
<MJD>57536</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0884</X>
<Y>0.4798</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18050</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>29</dateDay>
<MJD>57537</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0906</X>
<Y>0.4800</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18199</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>30</dateDay>
<MJD>57538</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0927</X>
<Y>0.4802</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18361</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>31</dateDay>
<MJD>57539</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0948</X>
<Y>0.4804</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18534</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>01</dateDay>
<MJD>57540</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0969</X>
<Y>0.4805</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18713</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>02</dateDay>
<MJD>57541</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0991</X>
<Y>0.4806</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.18891</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>03</dateDay>
<MJD>57542</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1012</X>
<Y>0.4806</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19058</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>04</dateDay>
<MJD>57543</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1033</X>
<Y>0.4807</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19210</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>05</dateDay>
<MJD>57544</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1055</X>
<Y>0.4806</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19344</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>06</dateDay>
<MJD>57545</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1076</X>
<Y>0.4806</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19464</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>07</dateDay>
<MJD>57546</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1098</X>
<Y>0.4805</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19575</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>08</dateDay>
<MJD>57547</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1119</X>
<Y>0.4804</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19682</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>09</dateDay>
<MJD>57548</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1140</X>
<Y>0.4803</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19789</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>10</dateDay>
<MJD>57549</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1162</X>
<Y>0.4801</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.19899</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>11</dateDay>
<MJD>57550</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1183</X>
<Y>0.4799</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20010</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>12</dateDay>
<MJD>57551</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1204</X>
<Y>0.4797</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20123</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>13</dateDay>
<MJD>57552</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1225</X>
<Y>0.4794</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20234</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>14</dateDay>
<MJD>57553</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1247</X>
<Y>0.4791</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20341</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>15</dateDay>
<MJD>57554</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1268</X>
<Y>0.4788</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20442</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>16</dateDay>
<MJD>57555</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1289</X>
<Y>0.4784</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20535</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>17</dateDay>
<MJD>57556</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1310</X>
<Y>0.4780</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20617</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>18</dateDay>
<MJD>57557</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1331</X>
<Y>0.4776</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20689</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>19</dateDay>
<MJD>57558</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1351</X>
<Y>0.4771</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20753</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>20</dateDay>
<MJD>57559</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1372</X>
<Y>0.4767</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20809</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>21</dateDay>
<MJD>57560</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1393</X>
<Y>0.4761</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20862</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>22</dateDay>
<MJD>57561</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1413</X>
<Y>0.4756</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20916</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>23</dateDay>
<MJD>57562</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1434</X>
<Y>0.4750</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20975</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>24</dateDay>
<MJD>57563</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1454</X>
<Y>0.4744</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21044</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>25</dateDay>
<MJD>57564</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1474</X>
<Y>0.4737</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21125</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>26</dateDay>
<MJD>57565</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1495</X>
<Y>0.4731</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21219</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>27</dateDay>
<MJD>57566</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1515</X>
<Y>0.4724</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21324</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>28</dateDay>
<MJD>57567</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1534</X>
<Y>0.4716</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21435</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>29</dateDay>
<MJD>57568</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1554</X>
<Y>0.4709</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21546</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>30</dateDay>
<MJD>57569</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1574</X>
<Y>0.4701</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21650</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>01</dateDay>
<MJD>57570</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1593</X>
<Y>0.4692</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21743</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>02</dateDay>
<MJD>57571</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1613</X>
<Y>0.4684</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21822</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>03</dateDay>
<MJD>57572</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1632</X>
<Y>0.4675</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21888</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>04</dateDay>
<MJD>57573</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1651</X>
<Y>0.4666</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21944</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>05</dateDay>
<MJD>57574</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1670</X>
<Y>0.4656</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21997</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>06</dateDay>
<MJD>57575</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1688</X>
<Y>0.4647</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22051</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>07</dateDay>
<MJD>57576</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1707</X>
<Y>0.4637</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22109</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>08</dateDay>
<MJD>57577</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1725</X>
<Y>0.4626</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22171</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>09</dateDay>
<MJD>57578</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1743</X>
<Y>0.4616</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22236</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>10</dateDay>
<MJD>57579</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1761</X>
<Y>0.4605</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22302</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>11</dateDay>
<MJD>57580</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1779</X>
<Y>0.4594</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22366</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>12</dateDay>
<MJD>57581</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1796</X>
<Y>0.4582</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22427</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>13</dateDay>
<MJD>57582</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1813</X>
<Y>0.4571</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22482</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>14</dateDay>
<MJD>57583</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1831</X>
<Y>0.4559</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22529</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>15</dateDay>
<MJD>57584</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1847</X>
<Y>0.4547</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22569</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>16</dateDay>
<MJD>57585</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1864</X>
<Y>0.4534</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22601</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>17</dateDay>
<MJD>57586</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1881</X>
<Y>0.4522</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22628</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>18</dateDay>
<MJD>57587</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1897</X>
<Y>0.4509</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22656</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>19</dateDay>
<MJD>57588</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1913</X>
<Y>0.4496</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22685</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>20</dateDay>
<MJD>57589</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1928</X>
<Y>0.4482</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22720</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>21</dateDay>
<MJD>57590</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1944</X>
<Y>0.4469</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22768</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>22</dateDay>
<MJD>57591</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1959</X>
<Y>0.4455</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22829</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>23</dateDay>
<MJD>57592</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1974</X>
<Y>0.4441</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22907</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>24</dateDay>
<MJD>57593</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.1989</X>
<Y>0.4426</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22997</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>25</dateDay>
<MJD>57594</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2003</X>
<Y>0.4412</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23096</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>26</dateDay>
<MJD>57595</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2018</X>
<Y>0.4397</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23196</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>27</dateDay>
<MJD>57596</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2031</X>
<Y>0.4382</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23291</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>28</dateDay>
<MJD>57597</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2045</X>
<Y>0.4367</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23377</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>29</dateDay>
<MJD>57598</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2058</X>
<Y>0.4351</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23450</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>30</dateDay>
<MJD>57599</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2072</X>
<Y>0.4336</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23512</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>07</dateMonth>
<dateDay>31</dateDay>
<MJD>57600</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2084</X>
<Y>0.4320</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23565</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>01</dateDay>
<MJD>57601</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2097</X>
<Y>0.4304</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23615</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>02</dateDay>
<MJD>57602</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2109</X>
<Y>0.4288</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23667</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>03</dateDay>
<MJD>57603</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2121</X>
<Y>0.4271</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23725</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>04</dateDay>
<MJD>57604</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2133</X>
<Y>0.4255</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23790</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>05</dateDay>
<MJD>57605</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2144</X>
<Y>0.4238</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23862</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>06</dateDay>
<MJD>57606</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2155</X>
<Y>0.4221</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23938</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>07</dateDay>
<MJD>57607</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2166</X>
<Y>0.4204</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24015</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>08</dateDay>
<MJD>57608</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2176</X>
<Y>0.4187</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24091</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>09</dateDay>
<MJD>57609</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2186</X>
<Y>0.4169</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24164</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>10</dateDay>
<MJD>57610</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2196</X>
<Y>0.4152</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24231</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>11</dateDay>
<MJD>57611</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2206</X>
<Y>0.4134</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24291</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>12</dateDay>
<MJD>57612</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2215</X>
<Y>0.4116</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24345</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>13</dateDay>
<MJD>57613</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2224</X>
<Y>0.4098</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24395</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>14</dateDay>
<MJD>57614</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2232</X>
<Y>0.4080</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24443</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>15</dateDay>
<MJD>57615</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2240</X>
<Y>0.4062</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24492</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>16</dateDay>
<MJD>57616</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2248</X>
<Y>0.4044</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24548</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>17</dateDay>
<MJD>57617</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2255</X>
<Y>0.4025</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24616</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>18</dateDay>
<MJD>57618</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2263</X>
<Y>0.4006</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24700</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>19</dateDay>
<MJD>57619</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2269</X>
<Y>0.3988</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24802</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>20</dateDay>
<MJD>57620</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2276</X>
<Y>0.3969</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24921</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>21</dateDay>
<MJD>57621</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2282</X>
<Y>0.3950</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25053</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>22</dateDay>
<MJD>57622</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2288</X>
<Y>0.3931</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25189</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>23</dateDay>
<MJD>57623</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2293</X>
<Y>0.3912</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25322</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>24</dateDay>
<MJD>57624</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2298</X>
<Y>0.3893</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25445</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>25</dateDay>
<MJD>57625</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2303</X>
<Y>0.3874</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25556</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>26</dateDay>
<MJD>57626</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2308</X>
<Y>0.3854</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25654</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>27</dateDay>
<MJD>57627</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2312</X>
<Y>0.3835</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25744</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>28</dateDay>
<MJD>57628</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2315</X>
<Y>0.3815</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25829</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>29</dateDay>
<MJD>57629</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2319</X>
<Y>0.3796</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25916</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>30</dateDay>
<MJD>57630</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2322</X>
<Y>0.3776</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26008</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>08</dateMonth>
<dateDay>31</dateDay>
<MJD>57631</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2324</X>
<Y>0.3757</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26109</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>01</dateDay>
<MJD>57632</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2326</X>
<Y>0.3737</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26218</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>02</dateDay>
<MJD>57633</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2328</X>
<Y>0.3717</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26334</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>03</dateDay>
<MJD>57634</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2330</X>
<Y>0.3698</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26454</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>04</dateDay>
<MJD>57635</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2331</X>
<Y>0.3678</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26575</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>05</dateDay>
<MJD>57636</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2332</X>
<Y>0.3658</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26694</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>06</dateDay>
<MJD>57637</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2332</X>
<Y>0.3639</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26808</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>07</dateDay>
<MJD>57638</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2333</X>
<Y>0.3619</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26917</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>08</dateDay>
<MJD>57639</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2332</X>
<Y>0.3599</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27019</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>0.2332</X>
<Y>0.3579</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27117</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>0.2331</X>
<Y>0.3560</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27211</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>0.2330</X>
<Y>0.3540</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27307</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>0.2328</X>
<Y>0.3520</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27409</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>0.2326</X>
<Y>0.3500</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27520</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>0.2323</X>
<Y>0.3481</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27647</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>0.2321</X>
<Y>0.3461</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27793</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>0.2318</X>
<Y>0.3442</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27959</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>0.2314</X>
<Y>0.3422</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28141</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>0.2310</X>
<Y>0.3403</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28334</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>0.2306</X>
<Y>0.3383</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28528</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>0.2302</X>
<Y>0.3364</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28713</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>0.2297</X>
<Y>0.3345</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28886</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>0.2292</X>
<Y>0.3325</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29043</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>0.2286</X>
<Y>0.3306</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29188</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>0.2280</X>
<Y>0.3287</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29327</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>0.2274</X>
<Y>0.3268</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29463</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>0.2267</X>
<Y>0.3249</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29603</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>0.2260</X>
<Y>0.3231</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29750</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>0.2253</X>
<Y>0.3212</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29904</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>0.2246</X>
<Y>0.3193</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30064</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>0.2238</X>
<Y>0.3175</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30227</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>0.2229</X>
<Y>0.3157</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30390</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>0.2221</X>
<Y>0.3138</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30550</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>0.2212</X>
<Y>0.3120</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30702</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>0.2203</X>
<Y>0.3103</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30845</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>0.2193</X>
<Y>0.3085</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30976</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>0.2183</X>
<Y>0.3067</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31096</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>0.2173</X>
<Y>0.3050</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31208</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>0.2162</X>
<Y>0.3032</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31314</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>0.2152</X>
<Y>0.3015</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31421</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>0.2140</X>
<Y>0.2998</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31535</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>0.2129</X>
<Y>0.2981</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31661</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>0.2117</X>
<Y>0.2965</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31807</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>0.2105</X>
<Y>0.2948</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31975</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>0.2093</X>
<Y>0.2932</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32164</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>0.2080</X>
<Y>0.2916</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32371</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>0.2067</X>
<Y>0.2900</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32586</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>0.2054</X>
<Y>0.2884</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32798</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>0.2040</X>
<Y>0.2869</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32999</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>0.2027</X>
<Y>0.2854</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33185</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>0.2013</X>
<Y>0.2839</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33356</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>0.1998</X>
<Y>0.2824</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33517</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>0.1984</X>
<Y>0.2809</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33675</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>0.1969</X>
<Y>0.2795</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33834</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>0.1954</X>
<Y>0.2780</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34000</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>0.1938</X>
<Y>0.2766</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34174</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>0.1923</X>
<Y>0.2753</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34354</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>0.1907</X>
<Y>0.2739</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34539</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>0.1891</X>
<Y>0.2726</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34724</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>0.1874</X>
<Y>0.2713</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34907</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>0.1858</X>
<Y>0.2700</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35085</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>0.1841</X>
<Y>0.2688</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35255</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>0.1824</X>
<Y>0.2675</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35419</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>0.1807</X>
<Y>0.2664</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35576</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>0.1789</X>
<Y>0.2652</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35726</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>0.1772</X>
<Y>0.2640</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35871</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>0.1754</X>
<Y>0.2629</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36014</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>0.1736</X>
<Y>0.2618</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36162</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>0.1718</X>
<Y>0.2608</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36325</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>0.1699</X>
<Y>0.2597</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36504</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>0.1681</X>
<Y>0.2587</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36704</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>0.1662</X>
<Y>0.2577</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36923</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>0.1643</X>
<Y>0.2568</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37159</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>0.1624</X>
<Y>0.2559</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37406</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>0.1604</X>
<Y>0.2550</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37661</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>0.1585</X>
<Y>0.2541</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37905</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>0.1565</X>
<Y>0.2533</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38131</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>0.1546</X>
<Y>0.2525</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38338</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>0.1526</X>
<Y>0.2517</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38522</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>0.1506</X>
<Y>0.2510</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38696</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>0.1486</X>
<Y>0.2502</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38868</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>0.1465</X>
<Y>0.2496</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39043</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>0.1445</X>
<Y>0.2489</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39226</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>0.1424</X>
<Y>0.2483</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39410</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>0.1404</X>
<Y>0.2477</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39592</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>0.1383</X>
<Y>0.2471</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39775</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>0.1362</X>
<Y>0.2466</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39957</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>0.1341</X>
<Y>0.2461</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40131</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>0.1320</X>
<Y>0.2457</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40294</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>0.1299</X>
<Y>0.2452</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40444</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>0.1278</X>
<Y>0.2448</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40590</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>0.1257</X>
<Y>0.2445</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40732</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>0.1236</X>
<Y>0.2441</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40871</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>0.1215</X>
<Y>0.2438</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41009</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>0.1193</X>
<Y>0.2436</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41151</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>0.1172</X>
<Y>0.2433</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41294</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>0.1150</X>
<Y>0.2431</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41450</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>0.1129</X>
<Y>0.2429</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41616</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>0.1108</X>
<Y>0.2428</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41797</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>0.1086</X>
<Y>0.2427</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41997</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>0.1065</X>
<Y>0.2426</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42206</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>0.1043</X>
<Y>0.2426</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42418</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>0.1022</X>
<Y>0.2426</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42635</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>0.1000</X>
<Y>0.2426</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42835</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>0.0979</X>
<Y>0.2427</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43020</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>0.0957</X>
<Y>0.2428</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43191</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>0.0936</X>
<Y>0.2429</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43349</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>0.0914</X>
<Y>0.2430</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43502</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>0.0893</X>
<Y>0.2432</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43652</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>0.0872</X>
<Y>0.2434</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43804</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>0.0850</X>
<Y>0.2437</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43955</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>0.0829</X>
<Y>0.2440</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44115</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>0.0808</X>
<Y>0.2443</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44273</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>0.0787</X>
<Y>0.2447</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44425</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>0.0766</X>
<Y>0.2450</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44576</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>0.0745</X>
<Y>0.2455</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44711</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>0.0724</X>
<Y>0.2459</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44843</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>0.0703</X>
<Y>0.2464</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44967</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>0.0682</X>
<Y>0.2469</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45084</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>0.0662</X>
<Y>0.2474</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45190</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>0.0641</X>
<Y>0.2480</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45298</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>0.0621</X>
<Y>0.2486</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45411</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>0.0601</X>
<Y>0.2492</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45532</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>0.0581</X>
<Y>0.2499</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45661</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>0.0561</X>
<Y>0.2506</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45806</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>0.0541</X>
<Y>0.2513</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45969</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>0.0521</X>
<Y>0.2521</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46156</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>0.0502</X>
<Y>0.2529</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46361</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>0.0482</X>
<Y>0.2537</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46577</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>0.0463</X>
<Y>0.2545</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46791</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>0.0444</X>
<Y>0.2554</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46994</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>0.0425</X>
<Y>0.2563</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47191</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>0.0406</X>
<Y>0.2573</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47367</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>0.0387</X>
<Y>0.2582</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47538</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>0.0369</X>
<Y>0.2592</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47698</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>0.0351</X>
<Y>0.2602</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47853</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>0.0333</X>
<Y>0.2613</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48009</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>0.0315</X>
<Y>0.2624</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48172</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>0.0297</X>
<Y>0.2635</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48341</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>0.0280</X>
<Y>0.2646</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48514</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>0.0263</X>
<Y>0.2657</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48690</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>0.0246</X>
<Y>0.2669</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48864</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>0.0229</X>
<Y>0.2681</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49028</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>0.0213</X>
<Y>0.2694</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49177</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>0.0196</X>
<Y>0.2706</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49312</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>0.0180</X>
<Y>0.2719</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49434</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>0.0164</X>
<Y>0.2732</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49539</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>0.0149</X>
<Y>0.2745</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49640</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>0.0134</X>
<Y>0.2759</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49738</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>0.0118</X>
<Y>0.2773</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49830</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>0.0104</X>
<Y>0.2787</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49924</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>0.0089</X>
<Y>0.2801</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50021</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>0.0075</X>
<Y>0.2815</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50128</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>0.0061</X>
<Y>0.2830</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50260</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>0.0047</X>
<Y>0.2845</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50393</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>0.0034</X>
<Y>0.2860</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50537</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>02</dateMonth>
<dateDay>03</dateDay>
<MJD>57787</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0020</X>
<Y>0.2875</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50686</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>0.0007</X>
<Y>0.2891</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50831</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>-0.0005</X>
<Y>0.2906</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50968</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>-0.0017</X>
<Y>0.2922</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51098</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>-0.0030</X>
<Y>0.2938</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51230</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>-0.0041</X>
<Y>0.2954</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51360</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>-0.0053</X>
<Y>0.2971</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51487</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>-0.0064</X>
<Y>0.2987</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51619</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>-0.0075</X>
<Y>0.3004</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51757</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>-0.0085</X>
<Y>0.3021</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51905</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>-0.0095</X>
<Y>0.3038</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52054</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>-0.0105</X>
<Y>0.3055</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52205</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>-0.0115</X>
<Y>0.3073</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52353</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>-0.0124</X>
<Y>0.3090</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52500</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>-0.0133</X>
<Y>0.3108</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52639</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>-0.0142</X>
<Y>0.3126</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52775</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>-0.0150</X>
<Y>0.3144</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52898</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>-0.0158</X>
<Y>0.3162</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53020</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>-0.0165</X>
<Y>0.3180</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53136</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>-0.0173</X>
<Y>0.3198</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53255</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>-0.0180</X>
<Y>0.3217</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53382</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>-0.0186</X>
<Y>0.3235</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53528</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>-0.0192</X>
<Y>0.3254</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53687</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>-0.0198</X>
<Y>0.3272</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53869</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>-0.0204</X>
<Y>0.3291</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54067</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>-0.0209</X>
<Y>0.3310</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54278</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>-0.0214</X>
<Y>0.3329</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54495</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>-0.0218</X>
<Y>0.3348</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54715</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>-0.0223</X>
<Y>0.3367</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54925</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>-0.0227</X>
<Y>0.3386</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55122</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>-0.0230</X>
<Y>0.3405</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55306</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>-0.0233</X>
<Y>0.3425</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55478</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>-0.0236</X>
<Y>0.3444</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55639</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>-0.0238</X>
<Y>0.3463</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55789</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>-0.0240</X>
<Y>0.3483</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55940</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>-0.0242</X>
<Y>0.3502</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56093</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>-0.0243</X>
<Y>0.3521</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56253</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>-0.0244</X>
<Y>0.3541</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56412</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>-0.0245</X>
<Y>0.3560</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56571</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>-0.0245</X>
<Y>0.3580</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56730</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>-0.0245</X>
<Y>0.3599</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56888</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>-0.0245</X>
<Y>0.3619</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57039</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>-0.0244</X>
<Y>0.3638</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57187</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>-0.0243</X>
<Y>0.3658</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57329</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>-0.0242</X>
<Y>0.3677</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57459</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>-0.0240</X>
<Y>0.3696</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57585</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>-0.0238</X>
<Y>0.3716</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57706</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>-0.0235</X>
<Y>0.3735</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57826</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>-0.0232</X>
<Y>0.3754</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57948</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>-0.0229</X>
<Y>0.3774</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58070</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>-0.0226</X>
<Y>0.3793</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58200</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>-0.0222</X>
<Y>0.3812</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58345</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>-0.0217</X>
<Y>0.3831</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58501</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>-0.0213</X>
<Y>0.3850</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58674</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>-0.0208</X>
<Y>0.3869</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58854</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>-0.0202</X>
<Y>0.3888</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.59041</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>-0.0197</X>
<Y>0.3907</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.59215</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
</data>
</EOP>
