<?xml version="1.0" encoding="UTF-8"?><EOP xmlns="http://www.iers.org/2003/schema/iers">
<version>
<product>BulletinA</product>
<date>2016-06-16</date>
<volume>XXIX</volume>
<number>024</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>05</dateMonth>
<dateDay>25</dateDay>
<MJD>57533</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.57</dPsi>
<sigma_dPsi>0.25</sigma_dPsi>
<dEpsilon>-13.68</dEpsilon>
<sigma_dEpsilon>0.14</sigma_dEpsilon>
<dX>0.222</dX>
<sigma_dX>0.099</sigma_dX>
<dY>0.006</dY>
<sigma_dY>0.140</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>26</dateDay>
<MJD>57534</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.81</dPsi>
<sigma_dPsi>0.25</sigma_dPsi>
<dEpsilon>-13.76</dEpsilon>
<sigma_dEpsilon>0.14</sigma_dEpsilon>
<dX>0.181</dX>
<sigma_dX>0.099</sigma_dX>
<dY>0.037</dY>
<sigma_dY>0.140</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>27</dateDay>
<MJD>57535</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.89</dPsi>
<sigma_dPsi>0.25</sigma_dPsi>
<dEpsilon>-13.77</dEpsilon>
<sigma_dEpsilon>0.14</sigma_dEpsilon>
<dX>0.143</dX>
<sigma_dX>0.099</sigma_dX>
<dY>0.058</dY>
<sigma_dY>0.140</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>28</dateDay>
<MJD>57536</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.72</dPsi>
<sigma_dPsi>0.67</sigma_dPsi>
<dEpsilon>-13.67</dEpsilon>
<sigma_dEpsilon>0.21</sigma_dEpsilon>
<dX>0.109</dX>
<sigma_dX>0.267</sigma_dX>
<dY>0.056</dY>
<sigma_dY>0.210</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>29</dateDay>
<MJD>57537</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.42</dPsi>
<sigma_dPsi>0.67</sigma_dPsi>
<dEpsilon>-13.48</dEpsilon>
<sigma_dEpsilon>0.21</sigma_dEpsilon>
<dX>0.084</dX>
<sigma_dX>0.267</sigma_dX>
<dY>0.036</dY>
<sigma_dY>0.210</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>30</dateDay>
<MJD>57538</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.25</dPsi>
<sigma_dPsi>0.13</sigma_dPsi>
<dEpsilon>-13.24</dEpsilon>
<sigma_dEpsilon>0.11</sigma_dEpsilon>
<dX>0.065</dX>
<sigma_dX>0.052</sigma_dX>
<dY>0.010</dY>
<sigma_dY>0.110</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>05</dateMonth>
<dateDay>31</dateDay>
<MJD>57539</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.35</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-12.97</dEpsilon>
<sigma_dEpsilon>0.10</sigma_dEpsilon>
<dX>0.059</dX>
<sigma_dX>0.119</sigma_dX>
<dY>-0.001</dY>
<sigma_dY>0.100</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>01</dateDay>
<MJD>57540</MJD>
</time>
<dataEOP>
<nutation type="rapid">
<dPsi>-93.75</dPsi>
<sigma_dPsi>0.30</sigma_dPsi>
<dEpsilon>-12.73</dEpsilon>
<sigma_dEpsilon>0.10</sigma_dEpsilon>
<dX>0.047</dX>
<sigma_dX>0.119</sigma_dX>
<dY>0.011</dY>
<sigma_dY>0.100</sigma_dY>
</nutation>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>10</dateDay>
<MJD>57549</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.10620</X>
<sigma_X>.00009</sigma_X>
<Y>0.49716</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.198043</UT1-UTC>
<sigma_UT1-UTC>0.000018</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>11</dateDay>
<MJD>57550</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.10773</X>
<sigma_X>.00009</sigma_X>
<Y>0.49634</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.199007</UT1-UTC>
<sigma_UT1-UTC>0.000012</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>12</dateDay>
<MJD>57551</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.10968</X>
<sigma_X>.00009</sigma_X>
<Y>0.49534</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.199966</UT1-UTC>
<sigma_UT1-UTC>0.000010</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>13</dateDay>
<MJD>57552</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.11227</X>
<sigma_X>.00009</sigma_X>
<Y>0.49438</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.200820</UT1-UTC>
<sigma_UT1-UTC>0.000007</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>14</dateDay>
<MJD>57553</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.11519</X>
<sigma_X>.00009</sigma_X>
<Y>0.49411</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.201688</UT1-UTC>
<sigma_UT1-UTC>0.000007</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>15</dateDay>
<MJD>57554</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.11803</X>
<sigma_X>.00009</sigma_X>
<Y>0.49447</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.202512</UT1-UTC>
<sigma_UT1-UTC>0.000007</sigma_UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>06</dateMonth>
<dateDay>16</dateDay>
<MJD>57555</MJD>
</time>
<dataEOP>
<pole type="rapid">
<X>0.12077</X>
<sigma_X>.00009</sigma_X>
<Y>0.49484</Y>
<sigma_Y>.00009</sigma_Y>
</pole>
<UT type="rapid">
<UT1-UTC>-0.203200</UT1-UTC>
<sigma_UT1-UTC>0.000055</sigma_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>0.1233</X>
<Y>0.4951</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20378</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>0.1257</X>
<Y>0.4951</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20424</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>0.1280</X>
<Y>0.4950</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20460</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>0.1303</X>
<Y>0.4947</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20489</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>0.1326</X>
<Y>0.4943</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20513</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>0.1348</X>
<Y>0.4940</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20538</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>0.1371</X>
<Y>0.4937</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20572</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>0.1394</X>
<Y>0.4934</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20617</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>0.1416</X>
<Y>0.4931</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20674</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>0.1438</X>
<Y>0.4927</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20743</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>0.1460</X>
<Y>0.4923</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20824</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>0.1481</X>
<Y>0.4919</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.20912</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>0.1502</X>
<Y>0.4914</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21004</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>0.1522</X>
<Y>0.4907</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21092</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>0.1544</X>
<Y>0.4900</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21172</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>0.1565</X>
<Y>0.4893</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21239</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>0.1586</X>
<Y>0.4886</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21298</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>0.1607</X>
<Y>0.4878</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21351</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>0.1628</X>
<Y>0.4870</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21405</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>0.1649</X>
<Y>0.4862</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21463</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>0.1670</X>
<Y>0.4853</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21529</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>0.1690</X>
<Y>0.4845</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21601</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>0.1710</X>
<Y>0.4835</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21680</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>0.1730</X>
<Y>0.4826</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21763</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>0.1750</X>
<Y>0.4816</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21848</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>0.1770</X>
<Y>0.4806</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.21931</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>0.1789</X>
<Y>0.4796</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22008</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>0.1809</X>
<Y>0.4785</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22079</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>0.1828</X>
<Y>0.4774</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22140</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>0.1847</X>
<Y>0.4763</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22193</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>0.1866</X>
<Y>0.4751</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22238</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>0.1884</X>
<Y>0.4740</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22279</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>0.1902</X>
<Y>0.4728</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22321</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>0.1920</X>
<Y>0.4715</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22368</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>0.1938</X>
<Y>0.4703</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22424</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>0.1955</X>
<Y>0.4690</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22492</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>0.1973</X>
<Y>0.4677</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22575</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>0.1990</X>
<Y>0.4663</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22669</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>0.2007</X>
<Y>0.4649</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22769</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>0.2023</X>
<Y>0.4635</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22870</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>0.2039</X>
<Y>0.4621</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.22965</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>0.2055</X>
<Y>0.4607</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23049</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>0.2071</X>
<Y>0.4592</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23119</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>0.2087</X>
<Y>0.4577</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23177</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>0.2102</X>
<Y>0.4562</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23225</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>0.2117</X>
<Y>0.4546</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23270</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>0.2131</X>
<Y>0.4531</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23317</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>0.2146</X>
<Y>0.4515</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23368</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>0.2160</X>
<Y>0.4499</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23425</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>0.2173</X>
<Y>0.4482</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23489</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>0.2187</X>
<Y>0.4466</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23558</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>0.2200</X>
<Y>0.4449</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23629</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>0.2213</X>
<Y>0.4432</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23699</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>0.2225</X>
<Y>0.4415</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23766</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>0.2237</X>
<Y>0.4398</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23828</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>0.2249</X>
<Y>0.4380</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23884</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>0.2261</X>
<Y>0.4362</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23934</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>0.2272</X>
<Y>0.4344</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.23980</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>0.2283</X>
<Y>0.4326</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24024</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>0.2293</X>
<Y>0.4308</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24070</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>0.2304</X>
<Y>0.4290</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24123</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>0.2314</X>
<Y>0.4271</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24188</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>0.2323</X>
<Y>0.4252</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24269</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>0.2332</X>
<Y>0.4234</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24369</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>0.2341</X>
<Y>0.4215</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24486</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>0.2350</X>
<Y>0.4195</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24616</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>0.2358</X>
<Y>0.4176</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24751</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>0.2366</X>
<Y>0.4157</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.24882</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>0.2373</X>
<Y>0.4137</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25004</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>0.2380</X>
<Y>0.4118</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25113</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>0.2387</X>
<Y>0.4098</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25209</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>0.2393</X>
<Y>0.4078</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25296</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>0.2399</X>
<Y>0.4058</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25377</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>0.2405</X>
<Y>0.4038</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25460</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>0.2410</X>
<Y>0.4018</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25548</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>0.2415</X>
<Y>0.3997</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25644</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>0.2420</X>
<Y>0.3977</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25749</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>0.2424</X>
<Y>0.3957</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25861</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>0.2428</X>
<Y>0.3936</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.25976</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>0.2431</X>
<Y>0.3916</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26091</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>0.2434</X>
<Y>0.3895</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26204</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>0.2437</X>
<Y>0.3875</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26312</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>0.2440</X>
<Y>0.3854</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26415</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2016</dateYear>
<dateMonth>09</dateMonth>
<dateDay>08</dateDay>
<MJD>57639</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.2442</X>
<Y>0.3833</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26512</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>0.2443</X>
<Y>0.3812</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26604</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>0.2444</X>
<Y>0.3792</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26694</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>0.2445</X>
<Y>0.3771</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26786</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>0.2446</X>
<Y>0.3750</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26884</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>0.2446</X>
<Y>0.3729</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.26994</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>0.2446</X>
<Y>0.3708</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27119</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>0.2445</X>
<Y>0.3688</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27264</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>0.2444</X>
<Y>0.3667</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27430</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>0.2443</X>
<Y>0.3646</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27615</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>0.2441</X>
<Y>0.3625</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.27811</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>0.2439</X>
<Y>0.3604</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28009</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>0.2436</X>
<Y>0.3584</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28199</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>0.2433</X>
<Y>0.3563</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28377</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>0.2430</X>
<Y>0.3542</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28540</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>0.2427</X>
<Y>0.3522</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28691</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>0.2423</X>
<Y>0.3501</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28834</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>0.2418</X>
<Y>0.3481</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.28977</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>0.2414</X>
<Y>0.3460</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29122</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>0.2408</X>
<Y>0.3440</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29275</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>0.2403</X>
<Y>0.3420</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29435</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>0.2397</X>
<Y>0.3399</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29601</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>0.2391</X>
<Y>0.3379</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29773</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>0.2385</X>
<Y>0.3359</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.29946</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>0.2378</X>
<Y>0.3339</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30118</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>0.2370</X>
<Y>0.3320</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30281</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>0.2363</X>
<Y>0.3300</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30439</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>0.2355</X>
<Y>0.3280</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30589</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>0.2347</X>
<Y>0.3261</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30733</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>0.2338</X>
<Y>0.3241</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.30873</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>0.2329</X>
<Y>0.3222</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31010</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>0.2320</X>
<Y>0.3203</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31151</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>0.2310</X>
<Y>0.3184</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31298</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>0.2300</X>
<Y>0.3165</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31458</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>0.2290</X>
<Y>0.3147</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31635</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>0.2279</X>
<Y>0.3128</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.31830</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>0.2269</X>
<Y>0.3110</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32045</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>0.2257</X>
<Y>0.3092</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32274</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>0.2246</X>
<Y>0.3073</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32510</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>0.2234</X>
<Y>0.3056</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32742</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>0.2222</X>
<Y>0.3038</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.32962</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>0.2209</X>
<Y>0.3021</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33165</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>0.2196</X>
<Y>0.3003</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33353</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>0.2183</X>
<Y>0.2986</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33529</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>0.2170</X>
<Y>0.2969</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33700</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>0.2156</X>
<Y>0.2953</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.33870</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>0.2142</X>
<Y>0.2936</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34044</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>0.2128</X>
<Y>0.2920</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34223</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>0.2113</X>
<Y>0.2904</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34408</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>0.2098</X>
<Y>0.2888</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34596</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>0.2083</X>
<Y>0.2872</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34785</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>0.2068</X>
<Y>0.2857</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.34971</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>0.2052</X>
<Y>0.2842</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35153</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>0.2036</X>
<Y>0.2827</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35327</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>0.2020</X>
<Y>0.2812</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35493</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>0.2004</X>
<Y>0.2798</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35651</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>0.1987</X>
<Y>0.2784</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35800</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>0.1970</X>
<Y>0.2770</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.35945</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>0.1953</X>
<Y>0.2756</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36089</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>0.1936</X>
<Y>0.2743</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36236</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>0.1918</X>
<Y>0.2730</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36390</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>0.1900</X>
<Y>0.2717</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36558</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>0.1882</X>
<Y>0.2704</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36741</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>0.1864</X>
<Y>0.2692</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.36942</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>0.1846</X>
<Y>0.2680</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37158</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>0.1827</X>
<Y>0.2668</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37385</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>0.1808</X>
<Y>0.2656</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37614</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>0.1789</X>
<Y>0.2645</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.37837</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>0.1770</X>
<Y>0.2634</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38045</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>0.1751</X>
<Y>0.2624</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38237</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>0.1731</X>
<Y>0.2614</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38414</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>0.1711</X>
<Y>0.2604</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38583</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>0.1691</X>
<Y>0.2594</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38748</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>0.1671</X>
<Y>0.2584</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.38915</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>0.1651</X>
<Y>0.2575</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39086</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>0.1631</X>
<Y>0.2567</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39261</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>0.1610</X>
<Y>0.2558</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39437</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>0.1590</X>
<Y>0.2550</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39614</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>0.1569</X>
<Y>0.2542</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39788</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>0.1548</X>
<Y>0.2535</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.39957</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>0.1527</X>
<Y>0.2527</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40119</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>0.1506</X>
<Y>0.2521</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40272</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>0.1485</X>
<Y>0.2514</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40416</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>0.1463</X>
<Y>0.2508</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40552</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>0.1442</X>
<Y>0.2502</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40681</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>0.1420</X>
<Y>0.2496</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40807</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>0.1399</X>
<Y>0.2491</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.40934</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>0.1377</X>
<Y>0.2486</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41067</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>0.1355</X>
<Y>0.2482</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41209</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>0.1334</X>
<Y>0.2477</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41365</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>0.1312</X>
<Y>0.2473</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41537</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>0.1290</X>
<Y>0.2470</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41723</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>0.1268</X>
<Y>0.2467</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.41921</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>0.1246</X>
<Y>0.2464</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42125</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>0.1224</X>
<Y>0.2461</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42328</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>0.1202</X>
<Y>0.2459</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42523</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>0.1180</X>
<Y>0.2457</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42705</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>0.1158</X>
<Y>0.2455</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.42875</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>0.1135</X>
<Y>0.2454</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43036</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>0.1113</X>
<Y>0.2453</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43194</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>0.1091</X>
<Y>0.2453</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43355</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>0.1069</X>
<Y>0.2453</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43523</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>0.1047</X>
<Y>0.2453</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43698</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>0.1025</X>
<Y>0.2453</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.43879</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>0.1003</X>
<Y>0.2454</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44064</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>0.0981</X>
<Y>0.2455</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44251</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>0.0959</X>
<Y>0.2457</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44437</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>0.0937</X>
<Y>0.2459</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44620</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>0.0915</X>
<Y>0.2461</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44798</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>0.0893</X>
<Y>0.2463</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.44970</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>0.0872</X>
<Y>0.2466</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45136</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>0.0850</X>
<Y>0.2469</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45298</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>0.0828</X>
<Y>0.2473</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45455</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>0.0807</X>
<Y>0.2477</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45611</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>0.0785</X>
<Y>0.2481</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45768</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>0.0764</X>
<Y>0.2486</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.45929</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>0.0743</X>
<Y>0.2490</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46095</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>0.0722</X>
<Y>0.2496</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46268</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>0.0701</X>
<Y>0.2501</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46449</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>0.0680</X>
<Y>0.2507</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46636</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>0.0659</X>
<Y>0.2513</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.46826</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>0.0638</X>
<Y>0.2520</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47015</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>0.0618</X>
<Y>0.2526</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47199</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>0.0598</X>
<Y>0.2534</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47372</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>0.0577</X>
<Y>0.2541</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47535</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>0.0557</X>
<Y>0.2549</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47689</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>0.0537</X>
<Y>0.2557</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47837</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>0.0518</X>
<Y>0.2565</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.47985</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>0.0498</X>
<Y>0.2574</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48137</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>0.0479</X>
<Y>0.2583</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48294</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>0.0459</X>
<Y>0.2592</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48455</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>0.0440</X>
<Y>0.2602</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48615</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>0.0421</X>
<Y>0.2611</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48771</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>0.0403</X>
<Y>0.2622</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.48916</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>0.0384</X>
<Y>0.2632</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49048</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>0.0366</X>
<Y>0.2643</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49167</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>0.0348</X>
<Y>0.2654</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49274</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>0.0330</X>
<Y>0.2665</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49370</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>0.0312</X>
<Y>0.2677</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49455</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>0.0295</X>
<Y>0.2688</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49530</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>0.0278</X>
<Y>0.2701</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49608</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>0.0261</X>
<Y>0.2713</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49689</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>0.0244</X>
<Y>0.2726</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49783</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>0.0228</X>
<Y>0.2738</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.49898</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>0.0211</X>
<Y>0.2752</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50035</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>0.0195</X>
<Y>0.2765</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50193</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>0.0180</X>
<Y>0.2779</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50363</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>0.0164</X>
<Y>0.2793</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50545</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>0.0149</X>
<Y>0.2807</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50721</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>0.0134</X>
<Y>0.2821</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.50892</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>0.0119</X>
<Y>0.2836</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51051</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>0.0105</X>
<Y>0.2850</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51198</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>0.0091</X>
<Y>0.2866</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51334</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>0.0077</X>
<Y>0.2881</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51467</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>0.0063</X>
<Y>0.2896</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51601</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>0.0050</X>
<Y>0.2912</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51740</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>0.0037</X>
<Y>0.2928</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.51881</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>0.0025</X>
<Y>0.2944</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52029</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>0.0012</X>
<Y>0.2960</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52185</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>0.0000</X>
<Y>0.2977</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52349</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>-0.0012</X>
<Y>0.2993</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52517</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>-0.0023</X>
<Y>0.3010</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52680</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>-0.0034</X>
<Y>0.3027</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52839</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>-0.0045</X>
<Y>0.3045</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.52990</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>-0.0056</X>
<Y>0.3062</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53140</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>-0.0066</X>
<Y>0.3080</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53281</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>-0.0076</X>
<Y>0.3097</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53416</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>-0.0085</X>
<Y>0.3115</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53549</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>-0.0094</X>
<Y>0.3133</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53683</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>-0.0103</X>
<Y>0.3151</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53825</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>-0.0112</X>
<Y>0.3170</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.53978</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>-0.0120</X>
<Y>0.3188</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54146</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>-0.0128</X>
<Y>0.3207</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54336</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>-0.0135</X>
<Y>0.3225</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54550</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>-0.0143</X>
<Y>0.3244</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.54778</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>-0.0150</X>
<Y>0.3263</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55001</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>-0.0156</X>
<Y>0.3282</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55209</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>-0.0162</X>
<Y>0.3301</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55400</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>-0.0168</X>
<Y>0.3320</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55588</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>-0.0173</X>
<Y>0.3340</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55772</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>-0.0179</X>
<Y>0.3359</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.55943</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>-0.0183</X>
<Y>0.3379</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56110</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>-0.0188</X>
<Y>0.3398</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56276</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>-0.0192</X>
<Y>0.3418</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56453</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>-0.0196</X>
<Y>0.3437</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56633</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>-0.0199</X>
<Y>0.3457</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.56824</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>-0.0202</X>
<Y>0.3477</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57021</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>-0.0205</X>
<Y>0.3497</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57215</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>-0.0207</X>
<Y>0.3517</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57398</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>-0.0209</X>
<Y>0.3537</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57572</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>-0.0210</X>
<Y>0.3557</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57738</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>-0.0212</X>
<Y>0.3577</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.57900</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>-0.0212</X>
<Y>0.3597</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58060</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>-0.0213</X>
<Y>0.3617</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58216</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>-0.0213</X>
<Y>0.3637</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58372</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>-0.0213</X>
<Y>0.3657</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58533</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>-0.0212</X>
<Y>0.3677</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58701</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>-0.0211</X>
<Y>0.3697</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.58875</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>-0.0210</X>
<Y>0.3717</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.59063</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>-0.0208</X>
<Y>0.3737</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.59271</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>-0.0206</X>
<Y>0.3757</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.59502</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>-0.0204</X>
<Y>0.3777</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.59746</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>-0.0201</X>
<Y>0.3797</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.59999</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>-0.0198</X>
<Y>0.3817</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.60241</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>-0.0195</X>
<Y>0.3837</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.60473</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>01</dateDay>
<MJD>57844</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0191</X>
<Y>0.3856</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.60685</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>02</dateDay>
<MJD>57845</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0187</X>
<Y>0.3876</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.60883</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>03</dateDay>
<MJD>57846</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0183</X>
<Y>0.3896</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.61075</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>04</dateDay>
<MJD>57847</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0178</X>
<Y>0.3915</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.61261</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>05</dateDay>
<MJD>57848</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0173</X>
<Y>0.3935</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.61450</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>06</dateDay>
<MJD>57849</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0167</X>
<Y>0.3954</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.61647</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>07</dateDay>
<MJD>57850</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0161</X>
<Y>0.3974</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.61845</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>08</dateDay>
<MJD>57851</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0155</X>
<Y>0.3993</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.62045</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>09</dateDay>
<MJD>57852</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0149</X>
<Y>0.4012</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.62258</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>10</dateDay>
<MJD>57853</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0142</X>
<Y>0.4031</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.62478</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>11</dateDay>
<MJD>57854</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0135</X>
<Y>0.4050</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.62697</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>12</dateDay>
<MJD>57855</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0127</X>
<Y>0.4069</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.62914</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>13</dateDay>
<MJD>57856</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0120</X>
<Y>0.4088</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.63124</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>14</dateDay>
<MJD>57857</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0111</X>
<Y>0.4107</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.63325</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>15</dateDay>
<MJD>57858</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0103</X>
<Y>0.4125</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.63514</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>16</dateDay>
<MJD>57859</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0094</X>
<Y>0.4144</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.63699</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>17</dateDay>
<MJD>57860</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0085</X>
<Y>0.4162</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.63874</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>18</dateDay>
<MJD>57861</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0076</X>
<Y>0.4180</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.64044</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>19</dateDay>
<MJD>57862</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0066</X>
<Y>0.4198</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.64212</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>20</dateDay>
<MJD>57863</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0056</X>
<Y>0.4216</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.64379</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>21</dateDay>
<MJD>57864</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0046</X>
<Y>0.4233</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.64555</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>22</dateDay>
<MJD>57865</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0035</X>
<Y>0.4251</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.64748</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>23</dateDay>
<MJD>57866</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0024</X>
<Y>0.4268</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.64960</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>24</dateDay>
<MJD>57867</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0013</X>
<Y>0.4286</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.65190</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>25</dateDay>
<MJD>57868</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>-0.0001</X>
<Y>0.4303</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.65429</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>26</dateDay>
<MJD>57869</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0011</X>
<Y>0.4319</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.65665</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>27</dateDay>
<MJD>57870</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0023</X>
<Y>0.4336</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.65894</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>28</dateDay>
<MJD>57871</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0035</X>
<Y>0.4353</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.66111</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>29</dateDay>
<MJD>57872</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0048</X>
<Y>0.4369</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.66309</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>04</dateMonth>
<dateDay>30</dateDay>
<MJD>57873</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0061</X>
<Y>0.4385</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.66486</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>01</dateDay>
<MJD>57874</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0074</X>
<Y>0.4401</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.66650</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>02</dateDay>
<MJD>57875</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0087</X>
<Y>0.4417</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.66817</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>03</dateDay>
<MJD>57876</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0101</X>
<Y>0.4432</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.66989</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>04</dateDay>
<MJD>57877</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0115</X>
<Y>0.4447</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.67168</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>05</dateDay>
<MJD>57878</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0129</X>
<Y>0.4462</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.67354</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>06</dateDay>
<MJD>57879</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0144</X>
<Y>0.4477</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.67548</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>07</dateDay>
<MJD>57880</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0158</X>
<Y>0.4492</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.67736</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>08</dateDay>
<MJD>57881</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0173</X>
<Y>0.4506</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.67924</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>09</dateDay>
<MJD>57882</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0189</X>
<Y>0.4521</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.68102</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>10</dateDay>
<MJD>57883</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0204</X>
<Y>0.4534</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.68271</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>11</dateDay>
<MJD>57884</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0220</X>
<Y>0.4548</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.68432</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>12</dateDay>
<MJD>57885</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0236</X>
<Y>0.4562</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.68580</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>13</dateDay>
<MJD>57886</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0252</X>
<Y>0.4575</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.68714</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>14</dateDay>
<MJD>57887</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0268</X>
<Y>0.4588</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.68845</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>15</dateDay>
<MJD>57888</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0284</X>
<Y>0.4601</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.68964</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>16</dateDay>
<MJD>57889</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0301</X>
<Y>0.4613</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.69081</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>17</dateDay>
<MJD>57890</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0318</X>
<Y>0.4625</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.69201</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>18</dateDay>
<MJD>57891</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0335</X>
<Y>0.4637</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.69327</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>19</dateDay>
<MJD>57892</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0353</X>
<Y>0.4649</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.69464</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>20</dateDay>
<MJD>57893</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0370</X>
<Y>0.4660</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.69612</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>21</dateDay>
<MJD>57894</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0388</X>
<Y>0.4672</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.69772</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>22</dateDay>
<MJD>57895</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0406</X>
<Y>0.4682</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.69939</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>23</dateDay>
<MJD>57896</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0424</X>
<Y>0.4693</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.70117</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>24</dateDay>
<MJD>57897</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0442</X>
<Y>0.4703</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.70292</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>25</dateDay>
<MJD>57898</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0460</X>
<Y>0.4713</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.70453</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>26</dateDay>
<MJD>57899</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0479</X>
<Y>0.4723</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.70603</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>27</dateDay>
<MJD>57900</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0497</X>
<Y>0.4733</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.70728</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>28</dateDay>
<MJD>57901</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0516</X>
<Y>0.4742</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.70847</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>29</dateDay>
<MJD>57902</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0535</X>
<Y>0.4751</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.70960</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>30</dateDay>
<MJD>57903</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0554</X>
<Y>0.4759</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.71074</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>05</dateMonth>
<dateDay>31</dateDay>
<MJD>57904</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0573</X>
<Y>0.4768</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.71188</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>01</dateDay>
<MJD>57905</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0593</X>
<Y>0.4776</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.71312</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>02</dateDay>
<MJD>57906</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0612</X>
<Y>0.4784</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.71442</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>03</dateDay>
<MJD>57907</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0632</X>
<Y>0.4791</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.71576</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>04</dateDay>
<MJD>57908</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0651</X>
<Y>0.4798</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.71704</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>05</dateDay>
<MJD>57909</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0671</X>
<Y>0.4805</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.71831</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>06</dateDay>
<MJD>57910</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0691</X>
<Y>0.4811</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.71951</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>07</dateDay>
<MJD>57911</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0711</X>
<Y>0.4818</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.72069</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>08</dateDay>
<MJD>57912</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0731</X>
<Y>0.4824</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.72183</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>09</dateDay>
<MJD>57913</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0751</X>
<Y>0.4829</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.72290</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>10</dateDay>
<MJD>57914</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0771</X>
<Y>0.4835</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.72386</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>11</dateDay>
<MJD>57915</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0791</X>
<Y>0.4840</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.72469</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>12</dateDay>
<MJD>57916</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0811</X>
<Y>0.4844</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.72555</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>13</dateDay>
<MJD>57917</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0832</X>
<Y>0.4849</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.72633</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>14</dateDay>
<MJD>57918</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0852</X>
<Y>0.4853</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.72723</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>15</dateDay>
<MJD>57919</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0872</X>
<Y>0.4856</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.72816</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
<timeSeries>
<time>
<dateYear>2017</dateYear>
<dateMonth>06</dateMonth>
<dateDay>16</dateDay>
<MJD>57920</MJD>
</time>
<dataEOP>
<pole type="prediction">
<X>0.0893</X>
<Y>0.4860</Y>
</pole>
<UT type="prediction">
<UT1-UTC>-0.72916</UT1-UTC>
</UT>
</dataEOP>
</timeSeries>
</data>
</EOP>
