Subject: Re: [AUDITORY] Tool for automatic syllable segmentation From: Jan Schnupp <000000e042a1ec30-dmarc-request@xxxxxxxx> Date: Fri, 20 Sep 2024 17:29:18 +0800--00000000000094f652062289ae93 Content-Type: multipart/alternative; boundary="00000000000094f651062289ae92" --00000000000094f651062289ae92 Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable Dear Remy, it might be useful for us to know where your meaningless CV syllable stimuli come from. But in any event, if you are any good at coding you are likely better off working directly computing parameters of the recording waveforms and apply criteria to those. CV syllables have an "energy arc" such that the V is invariably louder than the C. In speech there are rarely silent gaps between syllables, so you may be looking at a CVCVCVCV... stream where the only "easy" handle on the syllable boundary is likely to be the end of end of the vowel, which should be recognizable by a marked decline in acoustic energy, which you can quantify by some running RMS value (perhaps after low-pass filtering given that consonants rarely have much low frequency energy). If that's not accurate or reliable enough then things are likely to get a lot trickier. You could look for voicing in a running autocorrelation as an additional cue given that all vowels are voiced but only some consonants are. How many of these do you have to process? If the number isn't huge, it may be quicker to find the boundaries "by ear" than trying to develop a piece of computer code. The best way forward really depends enormously on the nature of your original stimulus set. Best wishes, Jan --------------------------------------- Prof Jan Schnupp Gerald Choa Neuroscience Institute The Chinese University of Hong Kong Sha Tin Hong Kong https://auditoryneuroscience.com http://jan.schnupp.net On Thu, 19 Sept 2024 at 12:19, R=C3=A9my MASSON <remy.masson@xxxxxxxx> wr= ote: > Hello AUDITORY list, > > > > We are attempting to do automatic syllable segmentation on a collection o= f > sound files that we use in an experiment. Our stimuli are a rapid sequenc= e > of syllables (all beginning with a consonant and ending with a vowel) wit= h > no underlying semantic meaning and with no pauses. We would like to > automatically extract the syllable/speech rate and obtain the timestamps > for each syllable onset. > > > > We are a bit lost on which tool to use. We tried PRAAT with the Syllable > Nuclei v3 script, the software VoiceLab and the website WebMaus. > Unfortunately, for each of them their estimation of the total number of > syllables did not consistently match what we were able to count manually, > despite toggling with the parameters. > > > > Do you have any advice on how to go further? Do you have any experience i= n > syllable onset extraction? > > > > Thank you for your understanding, > > > > *R=C3=A9my MASSON* > > *Research Engineer* > > Laboratory "Neural coding and neuroengineering of human speech functions" > (NeuroSpeech) > > Institut de l=E2=80=99Audition =E2=80=93 Institut Pasteur (Paris) > > [image: Accueil | Institut de l'audition] > > > --00000000000094f651062289ae92 Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr">Dear Remy,<div><br></div><div>it might be useful for us to= know where your meaningless CV syllable stimuli come from.=C2=A0</div><div= >But in any event, if you are any good at coding you are likely better off = working directly computing parameters of the=C2=A0recording waveforms and a= pply criteria to those. CV syllables have an "energy arc" such th= at the V is invariably louder than the C. In speech there are rarely silent= gaps between syllables, so you may be looking at a CVCVCVCV... stream wher= e the only "easy" handle on the syllable boundary is likely to be= the end of end of the vowel,=C2=A0which=C2=A0should be recognizable by a m= arked decline in acoustic energy, which you can quantify by some running RM= S value (perhaps after low-pass filtering given that consonants rarely have= much low frequency energy). If that's not accurate or reliable enough = then things are likely to get a lot trickier. You could look for voicing in= a running autocorrelation as an additional cue given that all vowels are v= oiced but only some consonants are.=C2=A0</div><div>How many of these do yo= u have to process? If the number isn't huge, it may be quicker to find = the boundaries "by ear" than trying to develop a piece of compute= r code. The best way forward really depends enormously on the nature of you= r original stimulus set.=C2=A0</div><div><br></div><div>Best wishes,</div><= div><br></div><div>Jan<br clear=3D"all"><div><div dir=3D"ltr" class=3D"gmai= l_signature" data-smartmail=3D"gmail_signature"><div dir=3D"ltr"><div dir= =3D"ltr"><div dir=3D"ltr"><div dir=3D"ltr"><div dir=3D"ltr"><div dir=3D"ltr= "><div style=3D"font-size:12.8px"><br></div><div style=3D"font-size:12.8px"= >---------------------------------------</div><div style=3D"font-size:12.8p= x">Prof Jan Schnupp<br>Gerald Choa Neuroscience Institute</div><div style= =3D"font-size:12.8px">The Chinese University of Hong Kong</div><div style= =3D"font-size:12.8px"><span style=3D"font-size:12.8px">Sha Tin</span></div>= <div style=3D"font-size:12.8px"><span style=3D"font-size:12.8px">Hong Kong<= /span><br></div><div><div style=3D"font-size:12.8px"><br></div><a href=3D"h= ttps://auditoryneuroscience.com" target=3D"_blank">https://auditoryneurosci= ence.com</a></div><div><a href=3D"http://jan.schnupp.net" target=3D"_blank"= >http://jan.schnupp.net<br></a></div></div></div></div></div></div></div></= div></div><br></div></div><br><div class=3D"gmail_quote"><div dir=3D"ltr" c= lass=3D"gmail_attr">On Thu, 19 Sept 2024 at 12:19, R=C3=A9my MASSON <<a= href=3D"mailto:remy.masson@xxxxxxxx">remy.masson@xxxxxxxx</a>> wrot= e:<br></div><blockquote class=3D"gmail_quote" style=3D"margin:0px 0px 0px 0= .8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div class=3D= "msg473229531229307533"> <div lang=3D"FR" style=3D"overflow-wrap: break-word;"> <div class=3D"m_-8617555306533983283WordSection1"> <p class=3D"MsoNormal">Hello AUDITORY list,<u></u><u></u></p> <p class=3D"MsoNormal"><u></u>=C2=A0<u></u></p> <p class=3D"MsoNormal"><span lang=3D"EN-US">We are attempting to do automat= ic syllable segmentation on a collection of sound files that we use in an e= xperiment. Our stimuli are a rapid sequence of syllables (all beginning wit= h a consonant and ending with a vowel) with no underlying semantic meaning and with no pauses. We would like to a= utomatically extract the syllable/speech rate and obtain the timestamps for= each syllable onset.<u></u><u></u></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US"><u></u>=C2=A0<u></u></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US">We are a bit lost on which tool= to use. We tried PRAAT with the Syllable Nuclei v3 script, the software Vo= iceLab and the website WebMaus. Unfortunately, for each of them their estim= ation of the total number of syllables did not consistently match what we were able to count manually, despite to= ggling with the parameters. =C2=A0<u></u><u></u></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US"><u></u>=C2=A0<u></u></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US">Do you have any advice on how t= o go further? Do you have any experience in syllable onset extraction?<u></= u><u></u></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US"><u></u>=C2=A0<u></u></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US">Thank you for your understandin= g,<u></u><u></u></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US"><u></u>=C2=A0<u></u></span></p> <p class=3D"MsoNormal"><b><span lang=3D"EN-US" style=3D"color:rgb(68,114,19= 6)">R=C3=A9my MASSON<u></u><u></u></span></b></p> <p class=3D"MsoNormal"><i><span lang=3D"EN-US" style=3D"color:rgb(68,114,19= 6)">Research Engineer<u></u><u></u></span></i></p> <p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"color:rgb(47,84,150)">= Laboratory "Neural coding and neuroengineering of human speech functio= ns" (NeuroSpeech)<u></u><u></u></span></p> <p class=3D"MsoNormal"><span style=3D"color:rgb(47,84,150)">Institut de l= =E2=80=99Audition =E2=80=93 Institut Pasteur (Paris)<u></u><u></u></span></= p> <p class=3D"MsoNormal"><span><img width=3D"200" height=3D"50" style=3D"widt= h: 2.0833in; height: 0.5208in;" id=3D"m_-8617555306533983283Image_x0020_2" = src=3D"cid:ii_1920eb6c1224ce8e91" alt=3D"Accueil | Institut de l'auditi= on"><u></u><u></u></span></p> <p class=3D"MsoNormal"><u></u>=C2=A0<u></u></p> </div> </div> </div></blockquote></div> --00000000000094f651062289ae92-- --00000000000094f652062289ae93 Content-Type: image/jpeg; name="image001.jpg" Content-Disposition: inline; filename="image001.jpg" Content-Transfer-Encoding: base64 Content-ID: <ii_1920eb6c1224ce8e91> X-Attachment-Id: ii_1920eb6c1224ce8e91 /9j/4AAQSkZJRgABAgAAZABkAAD/7AARRHVja3kAAQAEAAAAYAAA/+0ALFBob3Rvc2hvcCAzLjAA OEJJTQQlAAAAAAAQAAAAAAAAAAAAAAAAAAAAAP/uAA5BZG9iZQBkwAAAAAH/2wCEAAEBAQEBAQEB AQEBAQEBAQEBAQEBAQEBAQEBAQECAQICAgIBAgICAgICAgIDAwMDAwMEBAQEBAUFBQUFBQUFBQUB AQEBAQEBAwICAwQDAwMEBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUF BQUFBQUFBf/AABEIAM0DIAMBEQACEQEDEQH/xADiAAEAAgMBAQEBAQEAAAAAAAAACQoHCAsGBQQC AwEBAQABBAMBAQAAAAAAAAAAAAABAgMECAYHCQUKEAAABgIBAwEDBwYICQgGBgsBAgMEBQYABwgR EgkTIRQKMSIVFhe3ObV2tnc4eEEyI9aXWBkaQiTVljeHGJhZUWHSM9TnqGmBYkNTNLRxUmMlJldE NXWVVmbGRyhIiBEAAgECBAUCAgUHCQYFBQEAAAECEQMSBAUGITETBwhBUSIyYSMUFTeBQlKydLQ4 cTNDc4OzhDYJoWJyw3UYkbGCUyRjxDVFFkb/2gAMAwEAAhEDEQA/AL/GAMA/K+fMoxm6kZJ41j49 i3VdvXz5wk0Zs2qBBUOqqquJSJpkKAiYxhAAD2jlyzZu5i6oW4uUpOiSVW2+SSXFss5jMZfKWJXb slCEE3KUmkklxbbfBJerZFhyJ8xnDrRgPIqs2h1ve5IeomSF1SLWSriDgCCYgubC6MSK9Axg7TGZ HdqFH5U+ntzYTZXjJ3N3Y43MxaWn2X+dfqptetLS+Ov0TVtP9I1T7ieZXZ/ZUZWsjderZhVSjl6O 0nSqcr7+rcXyxWus0+ceZA5yK803LndASMNr9/F8faa89ZFNlr86ry8KMlS+wrixyRAdJrkH2lWj kWRv4P8Al67d7J8XO2+1sN3ORlqN+PGt3hbr9FlfC1/u3HcNEu4vmV3e3t1LORuR0rLSqlGxXq4X T5sw/jUlxpKyrPB8V6kdFE5D721ldXuxqHt7YdZu8o6TeTdjYWuYGQsa6Z/UD6UFyqoSUTE38ZN2 VUhv4QHO7NX2ZtLXtKjkc5k7N2xBUjBwjSHp8HD4H7OFGvRmuuh743ltrWpajkM9mMvmZyTnchcm pTali+sdfrE3xlGeKMqtSTTZNNx18921KwLGD5L67itnRBARRXu9CKzp94TIA9VF3Ecp0hZBUfkK mj7gUPl6jmrm9vD/AG7qCld0LMyyk+LVu7W5a+hKX85BfTLqv6Dc/t1547z0iULG5crDP2uCd20l ZvrnilKKXRuPklGMbCXFuT5E8HHbyA8T+T5Y9nrLbEKlbn4JlDXVxMFQvpHZyeoKCLGXMQJE5A/j GYKOEw/+vmom9uzPcXYLlPP5STsx/prf1lqnKrlH5E/RXFB/Qb2dufIntJ3PVu3p+ehbzNyiWXvU tX8TWLBGMnhuySTr0ZXYqj+Lgzc3Orju4YAwBgDAPAbH2rrTT9eVtm077Ute1xIxkvpi3z0bAs13 AJiqCKJpBQgruDFAe1JMDHN/AAjn2dD27r25s6stp2XuZm7+jbi5NL3dE6L3bol6s47ubd+1tl6f 9r1bN2cnarRSuzjBN0rhjiacpUXCMayfoiFPkT55NHUor6E47Umc3LOkA6KFtsZHlF1+gc6AiVZN J8kM0/BNToB0Tt2gGDqJVvkzafZXiFuvVHG7rd+GSt+tuFLt18eTafTjVcpKVynrE0l7h+eeztKj KztrKTz9z0u3VKzZVY1UlBrrTpKilCUbD50nwVYHeRfkh5ecmvpCOvO0pGvUuQKuiprrXIK0ummZ OUwTO2cpx6gvZRA3Tr2yDlx0ER6dA9mbebJ7IdtthYZ5PKRuX40+tu/WXKrk02sMH/Vxh9Jon3F8 he7XdDHb1LPThlrlU8vZ+qs4ZJJwlGLxXY8K/XSutVdGlwPG8eudXKfi+Zs11JtuwR1YQVBQ9Cnj pWqhLEMuC6pSRc8C7dmZcQ6KLMwRWEP/AGgZ9Penabt/v5OWpZOE7rX87H4Lq4UXxxo5U9IzxR/3 T43b7vR3O7X0houfu2bKlV2XS5ZdZKUvqrilCLm+E5wUbjTdJp8SeLjr586BYDsIHk5rF9r9+oCK K9/1oLuzVAzhRUe9ZzDyBjS0e2TJ/wC4XkFDD/ggHyah728PdXycZXtAzSzEVVq1epC5T0SuL4Jy b/SjaS9ze7t158aTnbkcvujIvLN0XXyzc7dW3VyszfUtwiqcYXL8pOvwL1m/09v3S/ICvls+mdmV HYkQCSCjsa7LILycQLkBFNOQYLdj+NXMACIJOkUz9Pb25qjufZu6dmZ37PqmVuZadXTFH4ZU5uE1 WE19MJNfSbv7K7i7H7jaas1omdtZuFE2ouk4YuSuWpUuWpP9G5CMvoMvZxo5oMAYAwBgDAGAMAYA wBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAY AwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYBgXeHKHj9xviwlN2bXqNC BVsd2yiJJ+Ly0yzdM3YY7GHiSuJV8UpvYYUG5wAflEM5htPt/vPfN/p6VlLuYo6OSVIRftK5KkI/ +qSr6HX2+u63bvtrl1PW8/ZyrarGDeK7JVpWFqCldkk+DcYNL1aIL+RPn5jm4PoLi7qdWRXAyiCO wdumM1YB2KCkKjWArzj11iKF+eio4fJCX2d6A+0oba7K8Ors8N7cGbwrn0rHF/ySuzVFTk1GDr6T 9TRjuH59KkrG18h60V7NcubTw2LcvVUcJSupqvxWuaIJ998weSfJp8o43Rtu1WyOFYi7aqEdEhKP HnSOJkzIQsEVtGEVTAQD1hRFUwAHccw+3Nt9odtdjbDs4dLyduzKlHOmK4/etyVZtfRiwr0SNGN9 d1+4vcvMdTW8/ezKTTUG8NqLVUnGzBRtRlR0clBSfq2a1Zzk68GAMAYB/wBKYxTAYoiUxRAxTFEQ MUwD1AQEPkEMENKSoyRbjt5UOZPHQGcZF7IV2VTWvpkLSduFeXSNRbpkBIqbV8sulMsU0yB0TSQe FRAfaKZunTOlN6+P3bHe9bl3KrLXn/SWKW5e7copO3Jt83KDl/vI2A7e+TveTtwlbyueeasLlZzV b1tUSSUW5K7CMUuELd2EK1bi3xJ5OO3nP41bLFhCbtgp/QlmXAiSks49a666XcCIJF6P4ZuSQaCq YevRdiCSQfxlxABNmoe9fErfOhKV3SbkNQtL83hbu0/4ZNwlT/dnil6Q9De/t751du9wyhY16xc0 u6/z1W9YrVJfFCKuxcq1o7ThBJ4rvCrmRpd7pOyK8ztuvbdWbxV5Du9xsVSnIyxQroyfTuKRzEqq omMTr0MXu6lH2CAZrFquj6toWdeWztm5l7secLkXCS9uEknx9H6m5mg7i0DdOnRzmmZm1m7Em0rl qcbkG06NYotqqfBqtU+D4mmXIryYcPuNPv8AG27aDK3XRiK6R9e6xKhdrUR22VBJRB0ZkqSNjFyC PUU37tAwh17QHp0ztHZPYfuZvrDcy+VdmxKn1t6tuFHxTimnOafvCEl7tHSncXyf7OdtnK1mM6s1 mY1XRy1L004tKUZSTVq3JN8Y3bkJNJ0ToyB3kT53t+3sX8Jx+qEDpKvqGOihZpYrS97DXSIuIAoQ ZNAsOw9ZLoB0vdHB0x69i/UANm3eyvEbZuj4bus3p5656wVbVpcOXwvqSo+TxxT9Yehoj3D86e42 4XKzoNm3pdlvhN0v32lJ8cU49KCnGlYq1KUG3hut0kQtbB2ZsTbFiXtuzrxa9gWZwQElJy3z0lYJ IG5TmUKiRWTUUMkgQTD2JE6EL16AABm0ejaHou3skstkLFvL2l+bbioRr70ilVv1b4v1NNNb1/XN zai85qWYu5q/JJO5dnK5NpVaWKbboquirRVdEeHz6p8kYAwBgHoarbrXRZ6PtVJs1gp9niFveIqx VaZkYCdjV+nTvbu4pRJdE3T2dSHAcw9Q07T9WycsvmrUL1qapKE4qUZL2cZJp/lRmadqOoaRn7eb yl2di/aeKFy3JwnCVGqxnFqUXRtVTTo2iYbjt5xOUeqvdIbcEfA8g6qgVNH15sUqfsBsgigCBCpz EG2O3cAH8ZQz1iusoPyql6iOa0b18UO324q3dNlPTrr/AEfrLTbdXW3Jpr2ShOEV+izbnt75td2N oR6OqK3q9hcldfSvJKNFFX4QdU2sUpXbV64238S5E8fHbyzcNOQf0fFBsD7JLq9AE/qht4jWp+o5 ApSiVtL+qrBufUVN2oJ+9kcKf+5KI9M1D3r459z9m4rn2f7ZYj/SWKz4ceduiuKi4yeBwX6T5m+H b3y57M79lCzPNPTszJP6vNJW48KVw3quw6t0hGVyNyfpb5pSVkORUhFEzlUTUKU6ahDAchyHDuAQ EvsEBD2gIZ0U04uj4NGzkZRnFNOqZ/WQSMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAG AMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDA GAMAYAwBgDAGAMAYAwBgDAOa5NTc1ZJV/PWKXlJ+clHB3cnMzT93Kysi7U/jKruHx1FllDdPaY5h Ec9zsrlcrksvGzZhG3CCooxSjFL2SVEl9CPzaZrNZrPZmV6/OVy5NtylJuUpN8W23Vtt82+LPl5f LAwBgDAGAMAYAwBgHpoG63KrMpyNrFts1cjrOwGKsrCBnpWIZWGMMPUWz5KPVTI7QHr/ANWqBi/8 2YOb0zTc/dtzv2oXJWpYoOUVJwl7xbTcX9KozNympajkLN23YuztwvwwXFGTirkP0JpNKUf92VV9 B5nM4whgDAGAMAYAwBgDAGAW3fARNTElxj2rHyMtJv2EHuZwzhWT1+6dNIdo4pkW8USaprnMRumd Y5jmKmAAJhER9o55x+YmWy1nfmUnCEYyuZVOTSScmrk0nJ820uCr6cD1i8A8xmLnbXP2pSk4W868 MW3SOK3CUsK5LFJuTpzbbfEnazUY3wGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGA MAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAG AMAYAwBgDAGAMAYAwBgHNIz3VPzWjAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAWy/h+/2bt0/ rvN+gcRnnV5k/wCd8j+yf82Z6ueAH4eal+2r+5tk9mafm+wwBgDAGAMAYAwBgDAGAMAYAwBgDAGA MAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAG AMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMA5pGe6p+a0YAwBgDAGAMAYAwBgDAP6EhwIVQSGAhx MUhxKIEOYnTqAD8giHUOv/05FVUpUouTVeKP5ySoYAwBgDAGAMAYAwC2X8P3+zdun9d5v0DiM86v Mn/O+R/ZP+bM9XPAD8PNS/bV/c2yezNPzfYYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAG AMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDA GAMAYAwBgDAGAMAYAwBgDAGAc0jPdU/NaMAYBa04PUamv/CruJV7VoB0rYNd8nbBNrLxTNReUna2 ymEY54scxO47pgVkgDdUR7kvTL2iHQM89u6mrana8qMjGN2aVu/k4RSk6KM3bxxXtGWKWJcnV15n p52p0bSP+xfWbrsW3OeT1K624Rbdy1buu1N1XGVtwg4PnFxVKUKpeehJ5hn6EGjp0CgtmzhwCJe9 UUEVFQSJ7fab0wHtD2fKOUuUY83Qs3cxYsNY5KNeVWlX+Sp+fKi8f2mmosciSSZ1VVDARNNMpjnO Yw9AAAL1ERHIbSVWUznC3Fyk0kubZ/o4bOWinpOm67ZXtA3puElEVO0fYA9FAAeg9MRlGSqnUotX 7OYhityUl7ppr/YSbeJbi9qTlfydm6NumJkbDS6nqSz7AGusZqTgEJyVYWeEqqKLtzBqt3xGyZZg 6/RuukYVEyAJhJ3kN0L5Gb/3H272FDN6XONu/ezMLWNxUnGLhcm3FSTjV9NR+KMlRvhWjWz3ih2u 2p3Y7nTyOsxncy2Xyly/04ycFckp2rSjOUaTUV1XP4JQk5RjV4cUZa5c5dOVDQHLLduoaCWQSptO tLdKutpR4eQeMY6YgmdhK2FdUPUWI1F2KSZ1BE4kKAnMY3Uw837T7m1LePbrI6lnMPWvW/jcVRNx lKNaclXDVpcKt0SVEdc97dn6TsHurqWkZHF9ny96kFJ1ajKMZqNebw4sKb4tJVbdWSRcofItxd3B 476LxmpmrZqM2ZFwutI1s1eVuBaVjWMtR3jNaSkI58isZRVSURRct0zIokUOk6VFYSCIkP0jsHsn v7bXerMa9ms3CWVnO83Sc3O9G4pYITjSiUG4yacmlKEcNVxWwXcnyG7Z7t8esltbKadcjnbNuwlK ULat5ednD1LlueJzcryxxTUItwuXHclF/DP6Pj34DcduQ3BXkJufZcFOyWyoOX2RCUywMrNMxben Fpeuo+ztV27KOWSaO1lXb0/rg9TXIYhSlIUg9xjWe83d/emy+7emaXkbkI5W7GzK5FwjJ3Openbk nJpyilGKw4HF1bbbVEqvHvshsHuN2N1/WtRtzlnMrcv27M1clFW+llbN+MlCLSk5TutTVzEnGMVF QdZOBzNuDSgYAwCabw58KdE8upzfslvWCkrXFa1iNfMIGutJ+drbQ0jflps6j5VetOWjsyrMkKBU UxUFIfVMJym6F6aueTPdTdvbfKafb0i5G1PNSuuU3GM3S10/hSmpRpLqcXTF8Ko1Vm5nh92T2P3d 1HVLuuQnet5K3ZjC2pygnK+7vxuUHGdYKzSKxYXjbknRUif3DUo6gbb2lRIdV2vEUrY13qUWu/US VfLR1bszqGQOsZEiZDKmSRKJxKUoCPXoAfJmxO2tSvaxt3K5u4kp37Fu5JLknOCk6Vq6VfCrZqju rSLGgbnzmQtSlOGWzF21FypiatzlFOVElVpVdElXkkuBjnPtHwRgDALZfw/f7N26f13m/QOIzzq8 yf8AO+R/ZP8AmzPVzwA/DzUv21f3NsnszT832GAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYA wBgDAGAYd3FyG0Lx4gfrPvndOq9M18yah0ZbZ99q9HaPBSECiRuaxum/vKomEClTS7jmMIFKAmEA ESk2Q9bb+JT8SerXDhjG71tW3pJodRJwy1Jqq8y7cqiYiH8nIWtrDRLkpunsOg7OX/nwVq1NmnM/ 8XZ492fVOuaI5hzqqbpRE6kjUNNQLFVqTuAFkjku7xY3eIAIEURIPQeo9BDpkVKujI9PVPi1PGrO rs2s/rbl1STqpNBev5jW+sZWGaOFjkTVKU9Zuj16qmiJjG7/AHUpjEL1AvcIEyakOzMkF0j56vE9 vh0wi65y9pNKnXxk0/obcsTa9Og2XVEClTPJbCYsIQxxEQD+SenDr/Dgpdua9CWeu2Su3CEjbNUp +FtFbmWxXkPYK7KsZuElWhjCQFWzuMUVQXTEQEAMQ4h7MFB9rAGAMAYAwBgDAGAMAYAwBgDAGAMA YAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYBzSM91T81owBgFt7gn+C lsr9UfLf/wCXsOec3dj+KvKftWQ/87R6ndqf4D9X/wCn6t/d3zWD4eis1+QneVtmfQ8e7n4aI07A RUs4bJrPGELaHFodyLZIxwHtSeKRjUypf8L0i9fkznXmhn87Zyek5eE5RtzlmJyinwcoKyoSf0xU 509sTOE/6fOkaXmtR1zOXLUZXrVvLW4TarKMLrvu5FP0U3atuS9cC9jZCZ8tPFvihvyW4s0Dj2FY 1NRr5J029X6oLxNYZwVuaSx4uYcIV1rG98k3ZPSGIs4O8TVUAhzJkOAJ9/Cct459wO420Ibgzupd XOZizG5atXFKblBxUrad5zpByi6qKg4qqUmm5YedZvyz7Xdnt8Xdr6ZoqsablL8rV69ZpbwXIylG 7KGWjZbuqE4pYuopTSbjFpQU9Y/PDxf1xRz6w5GUaAiqtPXmzS9J2M1h2qLBnZ5U0YawMJQ6DUhE wfARu6TdLfxlgFITe0gibnniLv8A1vVo5rRM3cldt5e3G5Zcm24RrglCr44eMXBco/FTg0l11519 rdu7fv5LcOn2YZeeauTtX4wSirk6Y4XMKSWN0uK5LnN4G+Kk3u1xNptN4M+N+qcjdXaLd7w27btd U/Y1pTqLX1bzZ1r+6aOfdDPm7SQeNYqAaOygsk2bnIQEFFTJ9xlVM6q7i6nqndrvhd0PUM+shk7N 65ahjf1cOkpLFhcoRlO7KPBykm8UYqVFGJ3R2m0TRuxPjjZ3NpmmPVNRzNi1fudNfWzV6UfgxqNy ULViElijCDjWEpyinKc1qvPeZDjPuqnWXXnM3htZigmzkGsfBs/q/fElZP0zNlexS2pV1/X3hFCl KRdsKqqZg7u8pihnYmT8Yt+bU1O1ndsa1BVabk8dr4ea4Qd2N2LXOMlGLXCjTOodR8z+1ncHR7+m 7v29O6o1go2527zjNpxm63Ps9zLSjyxW5Tup8VRpH6fA7yXZyx7RxRJq+vRjqu1i6bfLtSNeJt52 bZntsDAhFyLX3MTulUzSfVN372UCpIppeiPT1Ms+XmxrmXVrcP2qco3Llux0Gqxi8F2WOEsXwp4O MMDrKUpYuND6XgX3Dt3p5jazyVqM7du5mvtMfhnNY7Fvp3I4W5us6xnjVIRjDA6YjEvmD53RFpmd x8NA0FVm8rV7jSlz7qkJ1rLz5/o2LY2YFGDEIdupHulEnHuRlff1f8XMoTt6KfN5F409o8zp2VyW 5/vC44XbVxfZ1FxhxlKFJS6jU4prGlgj8ai6/Dx4p5gd8clrOoZ7Z/3VZVzL37T+1ykp3PhhGVbc enF25NS6bl1J/VucafHw2Q5n0qok8IWhnqdahUXdf1bxXs8K4QjmyCsbYbTEQ6Um8SFEpRK4kAkH IuD/ACqCqYxuoj1zhHa7VdTl5WahB3ZtXMxnYSTbdYQlPBF/RDBHCvRJJcDsjvPoOi2/CbSZxsW4 ys5bT7kGopYbl2EOpNU/OudSbm/znJt1fE3m4GcvY/e/DKzbhY6cresmmowtNSGgVOVSLWZUdd6/ jrCJ2ZSRyARbV0Dn0U24kcCiQodVFPkzqfu/20vbS7o2dMnnbmaedwXOrcj8cerenCkvjeOUcOJy rDE3yidx+PvefLb47K5zVbem2clHSHcs9G1JK1PoZWzerBYF0Yy6mCMPrMCinilyUFte5dVnnX5G +GViHQVL1RFVa2w8EvDtHzO3PrG4Sk155JZ88CLiUlUWaxSmaoi26pHFQ3ebvAC7a5vtvn+0nZHW rH3hdzc7tqUlJpwUFhUWoxxzaclXE8XxKioqcdIMt3X0zvl5F7ezP3XYyFqzfswcItXJTauOdZzw W1JRdMEen8LxNyliSj+7z5Q0RG8uNeSEfGMGL6e0NXn027ZtUGy8u+bXqwRqa7kyJQFdcjZFNEFD 9TemQhevaUoBa8P8zmb/AG0zEJyco285NRTbaiulZlSNeSxNui4VbfNsnzuy+Wy3fO104Rh1NMy8 5tRScpu/m4YpNKspYLcI1dXhhFckjd3h5SqfJeDvdqkhVq+9UkdYcpLXIKOohiso9s9QaTDmKkFT KEEVHkapHtjNljdTpCiTtEO0OnU/czVtUseV+QUL04qN/JW1STVIXHbU4LjwjNTliXKWJ15s757P be0HN+EeqO7l7U3cy+fuybhF4rtmM3auPhxnbduDhJ8Y4I0aojKng65FNNq6KtGmUdawNPc8eGFI j3VuhHiXqbDLf5aySZF3bMjNIzd00Fgb1FBcreuZUTACfQQNx7yx2Vc2/u61qjzM7y1F3Grcl/Nd KNmLUZYnWMsXBYY4Ukqy5rlfgzv+1uXYmY0ZZS3YlpXTTuwdHfV+eYmnOOGqlDBRyxyxuTaUOTiN 8pHPSI5LS0po+P0FVdfONP7rupXWxyzjew221Hr7mQqBiEFCJjRj2kgYfenSBlHInVTR+f8AyfU+ yHYDtDmtiZaOqz1C5mVnMrbpZwuFuGJRnxrOeOUPlhKkKRcuHxcNR/J/vpke5mflpFvSbGUlp+cv J38SneuYXK20mrdvpwm1juQbuYpRtvEsHxQ9ZssakDAGAWy/h+/2bt0/rvN+gcRnnV5k/wCd8j+y f82Z6ueAH4eal+2r+5tk9mafm+wwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMA0y5q+QD ir4/NbG2Xyb2dHVBu8I6JUqVHFCc2TsKRap9wtYOFaGB07N3iQijg/ptUBOUXCyRB7sFUYuT4FGb nn8UtzC36/mqdxDi23E3U51XTRpZEixtr3vY44TimVVzKPUlY6BFYgFOCMagK6BhEoPVQ6DkVMiN mK58Ss9e9g33aNok7vs272/Yt0mlfXmbfe7LM260Sy/UR73UhYFnDtc/t+U6gjgupJHkMA/opTHM UhCmOc5gKQhQExjGMPQAAA9oiI4BbU8XvwvW0+Q0JAbq53ztr4+6vlkkJOvaYrrZi03lboxdEVUl 5RacRctam1UESGBBZq4eqE7imTaj2KCLM7yXItANvE54U+D+r3t92Lxr411qgUxsm5sGyOTThtsR oZdQQIUzp3uZ1ItjuHSvQqTVEgAc5gTRS6iBMks47kmafan8vXw6ui9jrE0TdKXoty7fe7PprTfH beupdZTblRok0/x+OoNcjo58gBkylBR2wOiU5fVAwB/KjBU4XWuJYa1NuHVW+KLC7O0tsWm7T17Y khVhrjQ7DGWaAeiToCiQOIpRUhHCBh7FkTiCiRwEpylMAgEltpoyPggYAwBgDAGAMAYAwBgDAGAM AYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwDmkZ7qn5rRgDALb3B P8FLZX6o+W//AMvYc85u7H8VeU/ash/52j1O7U/wH6v/ANP1b+7vmvvw7n/+4H//AD//AP1tnLvN T/8ATf4r/wC3ONf6eX/+g/wX/wB2Qdc0f2xeWP7y+9/vSlc2w7XfhlpH7Blv7mBpB3n/ABh13/qe c/eLhY0+IE/Zu0t+u8v6By+aS+G3+d89+yf82B6Jef8A+Hmm/tr/ALm4aQ8c+aHPzx9aGojfanGy VvPHCRaFl9fTVmTkq/JV+IsCicqi0+mYYkgkwaODOTKtm8my9bqoIJm9MgJl7Y3v2t7Pd5t3ZiWn 6nGxqcHhuxg4yUpQrFy6csLlJUSlK3PDw+JYnV9D9uO9Xfnx72RlI6lpMsxot1OdmV2M4OKuNSjG N+OKMIycpSjC9bc5OXwNQjhJcOH/AC+1j5UKFtulbK41hDVyq/QjOZiLTItdiU2YTsaDoEhaSR42 KUaSzQW5lA9NEqqICmqmqBv4ut/crttr3j3q+TzeQ1THdvYnGUE7VyOBquKGOalblVLi3GXGMo05 7c9ou7m2fK3Q9R07VtFVuzl8CcZz69uSuKVHG50rTt3ouLccKxRpGcLil8sXfh7o8RrLyZ8rdbV+ QUloHXuvN50eElFlUV1ZKIqe/wCsQLZwY7cATOZZFuU4mKHQRHqHszv3yY1bMa92J0nPXo4LmZv5 a5KPH4ZTyt6TXHjwbpx4ms3h1oWW2t5Ja3plm471vKZbN2YzdKzjazmXgpvClGslFN4Ulx4JIj+8 scNLxfPzkGvJRj9ghKzlXkItd40XboSLBWgxJCrIHVKBVkhMUQ7iCIdQEPlAc7l8dszl8x2d05Qk pOMJp0daNXZ8H7P6Ga++VVm9lvIDV43E4uVy3JJ8KxlahSS94ujo+VU16Mmz5o/gc6e/Uhw5/Jtb zVXtb/Fhnf2vP/rXTdrvT/BDp37Fpn6lk/J4dWLyW8avIGKjGyz6Skb9u2PYsmxBVcunzzUEEgkk QpfaZRQ5ygUP4REMyPJm9ay3fTTLlxqMY2cs23ySWYutt/Qkcf8ADXK5jOeN+47NqLnO5nM3GKXO Ten5RJL3bfBfSQPeO4h4bnhxlbzBTRK6O24JkshJFFisk9dAo0SRMV12GKqoqoUhCCHUTGAADqIZ tz3o/wDk9o9Udv408tN8OPBKrfD0STbftxNIfH/MWLHe3RJTkor7dajVtL4nPAo8fznJqKXNydOf Akp+IDoNuT3fpfZowb09GktUloqFhSROswTtcHcJWeWZrHTAQRWO0kkVEQP09UAP2dfTP29GeG+s abPaOd0/GvtEMy7rh64J27cFJe6xQadOXCtMSrsd597c1ix3NyWsStv7JeyFuxGfp1bV7M3Jwfs8 F6Eo1+ZYqVwypvxxo17bdbeEvZsJdoV/XZyU42cq7UELKNVmUmzibLBWSTYHWScAUyYumR0nBQEO vYoXr0HqAdO781nTtc8qsrdys1chDPZKGKLTTlCVpSo1zwyrF/SmbE9sNA1Xb3hPnbWctytXLmna jcUZJqShOF9wbT/SjSa/3ZI1W+HeXRKty8bGWSK4VS0Kuk3FQgLKotz3NNQ5SCPcYpDKkAwgHQBM HX5QzsHzUhNw0eVHRPMqvpV/Z6f+NH/4M6w/087ltXNfg2sTWTaXq0vtVXT2VVX2qvcgx5c12eq3 KPkPEWOIkIWSS3Xs9cWki2VbKnavLo9eILJ+oAAqg4RUIqkqQRIoQxTFESiAjtp25zuU1DYGnXbE 1ODytninXircU19DTTTT4ppp0aNFe6mTzWndz9Xy9+Lhchnb+KL5qtyUl+SUWpRfKUWpJtNM12zm hwMYAwC2X8P3+zdun9d5v0DiM86vMn/O+R/ZP+bM9XPAD8PNS/bV/c2yezNPzfYYAwBgDAGAMAYA wBgDAGAMAh55g/i++Gj8yPJp9ztHwVr5H+QmGwUDAGAMAYAwBgDAGAQH+Zrziav8Z9aU1XrltC7U 5hWuFI/r1CcOBcVbV8U/KHu81bTMFU1yAsQwqMo1MxVnIABzmRRMVQ4uQtuf8hzYuQPIndnKjall 3XyC2NY9o7Nti4Ky1msbkiiibZM5jIs2TZqVJpHRzUDiVuzaJJN0S/NTIUPZkGUkorgYWwSMAYBe g+Go8NEEzrVU8j3J6os5ednTJzPFChWBoDhrXYlusJU708bLiJDv3ahR+hCqkEEUig9J1Oo2USGP dueiLq2SWDmAfEJ+SG3c2eal51PXLI8Djdxgtc7rXXdaZO1iwdkvFccKQNgtLhMggm6dO36a7Zks PUpGKZPT7RWWFSDLtRwxICMFwl28OflF2L40uTlcnTzkm+43bJnoSvch9diqu5i3lYXcgxCwsmwA cCTtfIqZy3OmUDrplO2MYCKiJRRcgpo6QvPvcG7NL8Z3/LfjIWK2UtouOJt24amcLEUrm+NCosyS NiZspFik4WjZdpEFGViZFBNYAUbiiZFZJwcuSYsUm6MyJwn5saF596FrPIHj9ZizNamSgwsVdfi3 b2/Xdvbt01nkHOM0VFBaSDQVCj7DGTWTMRZE6iKhDmESi4ujNt8EDAGAMAqFbt+LO17pjc23NPOe E1yn3OqNnX7WridQ3jCR6E0vRbU7q53ZG6lZVMgRyZqKgJicwlA3TuHp1xUvKy2idbxbeRCG8nHG h/yPgtWyeoGTHZ1p1qNUlrW1uLpResREZKmdg7ZsY4gEWCSAoJ+l1L2CPcPX2C3KOF0JH8FJVY5n fFCUTh5yl3ZxjkuHltvb7TF0dU1zb2O5YeAaT6rZoi794TZr110duUfW6dgrH+T5cF2NpyVTePxN +cnSXlNtGytbRmuZXRO2aFFMrVF0SyXOMt6l5pCqxWDuRjnLNjHCJ4t2okm7QFERKVdI5TGATgmI nbcCcTBbNfOWG/GnFnjRvTke/rTm5MtI6xt2ynVUZyaUK6sKFUiVJUzRN2sg5I2OuCfaCgpHAvXr 2jglKroVP/74xrf+ofd/6fIH+auKl7oP3LoeCwfPlpaLgYuSnJySj4WEhY95LTExLPG8dFxMXHNz PHDly4eGIig3QRIY6ihzAUpQEREADAKyXMD4qbgxoOfl6Xx+p145d2aGUVbuLDVpJlrnTqz5AxkT oN7DPtn0g97FC9PeGkQs1OUQMksoA5FS7GzJ/QRaSnxiW5FZJqrDcINZMIci4GesZTcdql5Jw294 AwkSdtIRikif0upe8zdQO753b0+bipX0F7mymkvjCNTzMwyjeQ/Da80CHUVKk7tmpdnwuzVkSrLm AFBhrTFVkxE0SCXv7H6pjdDGKXr0JipDsP0ZaU4l8zONnOLVrXcHGTaMHsqoGXJHzKTP3iOstPnD IA5NHTcVKESfxb4hDAYE10igoTookY6ZinNJZlFxfEwB5SfIhDeMfjQw5HzurZPb7J9s6ra1CqRN ra050mvZ4iTlSuxdvGMiQSIhGiUU/S6m7wHuDp7RMY4nQrt/3xjW/wDUPu/9PkD/ADVxUu9B+4/v jGt/6h93/p8gf5q4qOg/cf3xjW/9Q+7/ANPkD/NXFR0H7j++Ma3/AKh93/p8gf5q4qOg/cmh8Qvm Mrfln/2hfq9oec0l9gP2Te+fTN+YXj6zfap9ZvT9P3GKjPdfcvq2bu7u/v8AVDp29o9wtzg4GMfL L51qp4rdza409P8AHGw7mc7E1iTZSM7D7KjaUhFoHtUjV/dDN3sNJGVP3R4qeoByh0N07fZ1ETC2 5o8X4tviCKh5OOS7/jhBcYrJqF6x1jadlDa5baUXcWqiFYloyKM090ZwcccDrDJAYFPV6F7BDtHr 7AnbcFU228tnlbr/AIptd6j2BYNLTG6Udr3ScpzeLh7sypKkKpCwZZsVzqvY2SBcqgG7AIBS9Pl6 j8mCIQxsgq/vjGt/6h93/p8gf5q4qXOg/cf3xjW/9Q+7/wBPkD/NXFR0H7j++Ma3/qH3f+nyB/mr io6D9x/fGNb/ANQ+7/0+QP8ANXFR0H7k+Hia8oUF5UtM7H3DAaeltMttd7OPrVaCmLmzuq8quSqx 1o97K4ZR0aVInbIAn6YkMPUvXu9vQBbnBwZGLzt+Jro3B7lnuXitK8RLXsSQ0/NQkM5ucfuGIrjO dNM1GPtYKEZOa88O3BMsgCYgKx+ol69Q69AFUbTkqkgviM8udd8sFd3hYK/o+a0oTSk1RYZ01mb0 xu5rAa7sZR6RRM7KLjAbg3CMEBAQP3d4e0OntFM4YCYjBQaxczuSrHh3xa3Zyckqk6vbHTFLc3Fz UGMujAO59Ns8Raegm8XbuiNzCK3XvFE/yfJglKroVWf74xrf+ofd/wCnyB/mripe6D9yzlyG5jRu gOC1v5uvKG+s0XU9L1/camvG0+3i5B62no9lIAwLIqtV0yHSB6BRVFuID2/xQ6+wWUqyoVjf74xr f+ofd/6fIH+auKl7oP3H98Y1v/UPu/8AT5A/zVxUdB+4/vjGt/6h93/p8gf5q4qOg/cf3xjW/wDU Pu/9PkD/ADVxUdB+5I/4tviCKh5OOS7/AI4QXGKyahesdY2nZQ2uW2lF3FqohWJaMijNPdGcHHHA 6wyQGBT1ehewQ7R6+wUTtuCqVbM91T81IwBgEpmlPKDa9McJ71w7Zaogpz60w+xq3DbGXtD1iaAg 9nN1kXwLxBGSoP3aAvHJm6oPESF7kwOkcCG9ToDdHYTTtz91cvueWbnb6MrM5WlBPFKy040niWGL wxxLBJukqSVVh2Y2n5KaptfsbndlfYbd2Obt37SvOco4LWZi43E7aTxzWKeCauQUaxrCWF4/EePb yETnAqc2c7a61YbPr+0ImtNpSFWtClOfsZmnunqke6SeljpQpkSpSbsiqAoAJxMQwKF7BA/1O8/Z nJ938plYyzMsrcyspuMlDqJxuKOOLjihxrCDUsXCjVHWq+Z4/eQOo9h9Rzk4ZSOds52EFKDm7UlO 25dOSngufClO4pQwfE5RalHDSWj2yL1MbR2JfdmWIjRKwbFulpvU6mwTUSYpzFunF7A6KiVY6hyp Au4MBAMYwgHTqI/Lna+iaTldA0XL5CxXp5a1C3GvPDbioxrSnGiVeCOkdwa5n9za9mdSzWHrZu9c vXMKajjuSc5YU22lik6JttL1fMkP51+Ti1c4taau15N6rhKCajS/1osc1HWd5P8A1qs4QRoQFWjZ dkzCKZ9F3BxbnUdH6mIHq/MET9L9pOw2ndp9dzeds5ueY+0RwQi4KOCGLFSTUpY5cIrElBcH8PHh sD3x8l9b737byGn5nJ28s8q8d2cZyl1buBQxQi0ulDjN4G7r+KK6nwvFsxxu86m29T0KC17t3U8F uhnWIZjX4S0sbSvQ7WrFxyPuqISYmj5ZnIqpoFKkChEW5zAUDKCooJjm4LvnxK21uTWbmd03NzyM rs3OUHBXYYnxeBY7coJuro5SSrSKjGiXYfbbzg3tsrbVvTdTyNvVY5e3G3bm7rsXcMeCV2fTvRuY Y0ipdOM2o1uSnNyk/Xba8916mqG/qOiNCQGnZp80eMkLdKW5O5jXk3xFCnWjoxnDxLQj1M5/UTVX MskB/wCMif8Ah+bt3w/0fK6xHM6tqE87CLTdtW+njpThObuXJOLSo1HC6cpI+xuXzz3XqG3ZZPRt JsaXdkmlc6zzGBST424dCxGM1J4k5K5GvODqRDcXuUGxOKm74PedIFpNTzAssynomwqvlo23Qs+i KT1q9O2UIuIqH7VyKdwiVdMhxA3aJR2R39sLRe4W1Lmk5usLcsLjKFMUJRdYyjVNcOTVOMW1wrU1 N7Zdydwdqt6Wdb0/DK7axKUZ4sFyE01KM8Li2nXEuPCajKjpQkS5r+X9XmHoOV0epxxhqKaYm61M q259sU13dRatdkSyXdHNTV+K90cuO0UTLCufogoon2j39wdKdq/GuPbPeEdWWpTzGCE49NWumpY1 T431Z4kvmw4V8SjKvChsR3t8uZ949iPRHpFvLYrkJu7K91nFwdfq49G3glL5XLFL6uU4U+Kqw9uj yb2zcHCTW/DVTVsLXG1Jhdb1eZ2A2szqSPZq7q2PSYxyacW4Yp/R7lUzRqo4W98WKYxDgUhCnACc m2v2H03bPdXM7nWandd+V2cbTglgnebc25qXxJYpKKwRomqttVfD95+S2s7x7KZLZ0snbsrKxswn eU2+pby8cNtK24/BL4YOcupJScXSMVKi+bwC8l+weCrW31ZvR4vaOtbjJo2N3UX085qclEWpFiSL M9YyLdpIETB22SSTcpqtFe8EUhIZPofvv94uxWi9252cxK/LK5qzFwVxRU1KDdcMoOUW8LbcWpRp ilVSqqWOwfknuLsYsxloZeGdyWYkpu1KbtyjcSw44XFGaWKKSmpQlXBDC40eL4HOLyBzfMHb2sNv 17W7HSM9qmJaNa/IRFm+tNqVmGFhGyNnaksWNijdjFwBTNEfQ/kTioYDCKggGZ2n7OZXtptrNaZe zLz1vNybkpQwQwuGBxVvHP5lwm8XxLCqLDx+X3w78ZzvDvPKazYycdNuZO3GMJQnju4o3JXIyd5Q tukG624qKwSxyUm58JKaD8QhZ4yoxbDZPG6Mt11ZthRk7HVtkK02Fm1k+oEWCOfQksdmc5enqAVw oUTdTFApRAhejdY8MtNzGoznkdTlZsSfwwnZVyUfdY1dt4l7fCnSibb4vYvQ/wDUG3PktMtWtQ0W zm78VSd2GZlYjLi6NWnl79Hhpi+spKVWowTUVhHZnnI2rtbR27dRWXSVJaye2YW4UyItcLZphowq FFuMP9X1my0Y9bOVJORTaKr9rwHrcnqHKb0O0nYblWheJ23dvbsyOpWM9ecMnK3clCUIt3LtuWNS U00oQclGsME3RNY6uq4juXze3nurY2p6RmdPy6uZ+Ny1C5CU1G1YuxUJQdt4ncuYXOl3qW4qUovp NRwyj84Tc0tg8ItpPdhUuIjLVEWKFGuXSlzLp0xYWCJK7I/SMm4aAczR62WJ1RX9NQCgY5RIYDiG dyd1O12jd1dvLJZqcrU7c8du5FJuEqNOqfzRafxRqq0TqmkdAdmO8W4eyu7HqeRhG9G5bdu7am5K M4OUZc18s4uPwTpLDWSo1KSeyvkE8n5uddCo1E+wWF1gSmW9a2hY17qF8sTgykMvDCybLjCQ4sWS wL+q5TD1PWUSQEe30g68F7NdhF2k1fMZv7wnmuvbUMCt9KC+JSxNdS5ikqUi+GFSmuOLh2Z5A+TT 766Nlcl9128kstddzqO51rjrHDgjLpWsEHWtyNJY5RtuqwcYos2HNVxgDAM16V5G7z46TprDpTaF s16/XVRWkG0LImNBTRmxDETCRi3wLRskRMDm7CukFAKI9QAB9ucX3Tsrae9cn0NVytvMxVaYl8Ua 0rgmqTg3RVcZJs5ds7fu8+32pfa9Fzl7J3HTFglSM8OLCrkHWF1RxSajcjKKbqlXiTlcdvPxZosr GC5Qaqb2dqmBEVr/AKoFCIsHpJoAT1HMHOLgwdrqqdTHO3eNCFAfmpezoOpu9fDvTsy5XdAzbsyf 9FfrKHPkrkVjikuSlC436yN3u3nnxruQjGxufIrNRX9NlqQu0UecrU2rU5ylzcZ2IJPhHhxne0Bz T4xcnUEg05tysWGbOidZamP11K7e2pESFMqY0PPlbv1EkhOBTLpJnR6/Icc1F3l2s39sKT+88nct 26/ziWO068vrI1im6cItqX0G9/b7vh2t7n0ho+oWrl5pvoyrbvcKYmrU8M5RjVJzgpQq6YmbSZ18 drjAGAMAYAwBgDAGAMAYBDzzB/F98NH5keTT7naPgrXyP8hMNgoGAMAYAwBgDAGAQ7eZ/wAqVU8Y XGhawQ30VYuSe105WsaAoj46SzZOVbtig8s0qh3AoaDr4LJnUTL85y4Oi3ASFUUWRFduGNnLI2Ts e9bgv1w2ls60y922Ff7DKWu42ydce9S09PzLozxw4WMAFKAnOYe0hAKQhehSgUoAAQZiSSPE4AwB gG53jw4uq80ebfGvjIPvQRO1NmxTC4KsDmTftdd15utcLMugYvQSrt6/HPVEx/gMUMESeGNTsIwE BCVSBhKvWomPga5W4iNgK/BxLVFjFw0JDsyRzRo2QbgVNFu3QTKmmQoABSgAAHQMkwTHe/tgrak0 TuvazYnqONZak2PsFun6RFvUWplOeWMhexToU/UzYA7R9g/JgLizi2vHjuRdupCQdOXz985XePXr xdVy7eO3KorqKqqLiY6iihzCYxjCIiI9R9uQZ5+bAGAdWfwS7m/2mfElxXkLcdtPyFboVg0NbmT8 UZBNww1TYX2t2SDsqnX1Bc15oyUUKoHUwKe3r16jJh3FSbKJukOWW5PBp5Q981zXTiTmtXa63pe9 T7T1O7kXRYTbOoa5cXjCNVMDo3RKXbxqhHsU+N/KIqm7T96CrhJWDIcVcgdN7j7vvVvKHS+ut/aW sra26z2jWmVnq8wh2prg3c9UlmjtEDGM1kWDkijZ42P89BdM6ZwAxRDJMVpp0Mx4IGAMA42HOj9t rmJ+9PyD+9qXyDOj8qL9XwoP4X1g/en2x+h9WyTGvfOWZcFo5K/m3/Ff5z/rwlfyOyyDMt/IjSvj ByQ2jxF33rDkbpqZ+hdharszSww6ioKHjpVqBTM30Y/TSMQy0dKsVVmjtMDAJkVTAAlHoICppSVD rl8IOYWrud/GXWPJnUrrpAX2HKM1XnC6a0vRbtG9GkvBPwTAOjqNeAZPu6AVZPsWJ1TUIYZMKUXF 0MNeXb8L7nt+6xuL9D3OCYfOjkP5Bmnb2yTAKdnxafNa9601bo3hfr+ZdQUbvlCybE3M7j3SzR9M UenSbSMhoUwoj8+PkZM7lw7IPTuFmiX2kMcowy/Zim6lRDxxePnbvkt5JsOOeoZauVh02qsvsK9X W1KLjDUnXtfkmMM7kDNmXVy/XM9k2jZu2RABOqsTvMmkCipBelJQVS4HXPg+uLzWtla23l1vubt/ uxymnK5U9eVati7FqUhThFSaUw6BMFupxJ9IiIlEC9wCHeKhY68vYrx+YLwZ7Y8Wreq7NiL8lvHj jd54lSZbBLXgqlmpl0cMVpRCKnI1N2+SAjxu2WM0eoLCmqKRyqEQOKZVBdhcUzXbw4c7r1wJ5z6f vkROyKGrdhW2uay3vUSPjowdo13apUsMd04QOIJHeV9V19IslB7TFUSFPvBJZUDCbkVKJ0cvK/46 f7T7i/H8bvth+w/3HalT2Z9c/s++0v1fqvDysT7l9HfTlf7fX+k+/wBb3oe3s6dhu7qEmLCWCVSt t/c2P/Mb/wDCF/3oZFC91/oICvMJ4nv7J/ZOnde/b59vf2s0eduf0v8AZZ9ln0B9CzwQnu3u/wBY 7H716vXv9T1E+35O0flwXITxmEPFtwD/ALSrlhEcYPtY+xb6VpF0uX14+on2jeh9UGSbv3b6M+mY Hu949Tp6nvYdnTr2mwTOWBVLMn9zY/8AMb/8IX/ehiha6/0E33hr8Nf9kj/tHf8A+R3+0B/tAfZB /wD2g+yn6pfZT9aP/wCaLJ7/AO//AFk/+x9L0f8AD7/mSW5zxlZr4vn9tvjP+6wh97dkyGXbHJmE PhQfxQZ/91jbH6YVbBN75C4X5hPE9/awa207r37fPsD+ya7zty+l/ss+1P6f+m4EsJ7t7v8AWOue 6+l29/qeop3fJ2h8uSWITwMgK/ubH/mN/wDhC/70Mihd6/0FdPy6+ND+yt5I0nj39tX27/XHSFb3 L9bvs4+zD6O+sN8stI+jfcPp6xet6P1d9b3j3kvd63Z6YdnccXITxqo8RXjQ/tUuSN249/bV9hH1 O0hZNy/W77OPtP8ApH6vXytUj6N9w+nq76PrfWL1vePeTdvo9npj39xAnPAqliz+5sf+Y3/4Qv8A vQxQt9f6Cwj4gvFv/ZTaS2Zpz7c/t5+0XaZ9mfWP7Mvsu+h++pRtW9y9z+sNi946fR/q+t65P4/b 2fN7hktTnjZz+fPz+L7zY/Pijfc7XMgybfyIsW/Bz/6N+eH576D/ACDaslFq/wA0XQ8Fgix83H4U HOf9SEp+WWWCqHzo5K+QZp139g8Z/wDbH8Xsfxg+uv2c/bTxY1jTfrx9W/rf9WveafEu/efoz3+L 987fR6en72l169e72ZJhJ0lUrN/3Nj/zG/8Awhf96GRQvdf6CLHy6+Af+yt43UnkJ/tY/bv9cd31 vTX1R+wn7MPo76w0Oy3f6S9/+uVi9b0fq76Pu/uxe71u/wBQOztOK4XMbpQhC4y6a/2jOSPHzj39 Y/qd9u+79Uaa+t30P9Yfqr9p98YUj6S9w96Y+/e4+/et7v7yj6vb2eoTr3AK26KpcL/ubH/mN/8A hC/70MULPX+gky8UHw9v9mDyhkOSP+119uHv2rLZrP6mfYH9mnpfWiYipb336R+utg7vQ+jOz0fd Q7u/r3l7egiid3GqUKyOe6x+agYAwBgDAGAMAYAwBgGbkON29XOk3XI1DWNnU0izlRhnGxAaohCE eBJEhRMBTKA4M1B8oVqLkqYogv1S7/UAShxWW99pQ3StEeat/bpRxK1X4qUcv5MWFYsNcWH4qYeJ y+OwN6S2ZLcX2O792xuK27+GlvE2ori+Ljjat40sHU+rxY/hMI5yo4gMAYAwBgDAGAMAYAwBgDAP 9mzlwzcIO2jhZq6bKprtnLZU6DhuukYDlOQ6QgYhymABAQHqA5TOELkHGSTT4NPk0Sm06rmiUDjt 5e+ZOhRYRUrc0t2UtqYiZ63tz3uflUmorgdT3WdSUTmU1QTASJe8LuEUw6dERAOmdCb18be2O8MV y3Y+w33+fYpBVpwxWqO21Xi8MYyl+l6my3bzy07zbAcbUs3945aL/m81W66OSbw3qq8nSsYJzlbh VfVtJIni46+bPihuD3CF2eMzx8uDoUEDJ3AwTlBcO11RTAqE/EJFBEhQADHVkGrRMvX+MPtHNQ97 eKvcPbWK7p+DUbKq/q/hupL3tSfH6Fbncb9kb3duvN3tbu1xsavG5pOYlRfH9ZYbbaSV6CTjRUcp XbdqEa/O6Nkutdsldt8LH2Spz0LaK7LtyPIqersoxmoWTaKh1Kq3dRqiqCyZg+QxDCA5rdnshntM zUrGZtztXYOkozi4yi/ZxaTT+ho290vVtL1zT4ZvJXreYsXVWFy3KM4ST5OMotxkn7ptH2sxD6Aw BgDAGAMAYAwCHnmD+L74aPzI8mn3O0fBWvkf5CYbBQMAYAwBgDAGAeVvV3qes6Vb9jXydY1ej0Ks ztyuFkkznJHQFYrMYrMv3i4pFMb0mzVE6hu0oj0D2AI+zA5nI38nfPC5+RbmFszkVYzyDCpu3n1U 09Tnq3qFoupK84VSiWIFKIkK6cAdR6+EvsM7cLGL0KJQCDNhHDGhH3gqGAMAYBZc+FIo7W2eUaTn nCKSqusuMO2rwxOoYpTt3T+yVvWwnTASG7jihYVCdAEvzTCPX2dokWr3yHSayTFNIvJkYxPG95BD kMYhycIuVxiHKIlMUxdDzwgICHtAQHBVD50cebIM0YAwDpZfCtpy5PFYxNJLpLM1uQ24VK+mmCYH axAJRKR01OwhRE4vyuT/ADhMPaYPb06FCTFu/OUzPPi1bNPL1zaSaN0GqR7/AFB0dNuimimZy91P X3qyggmAAKiyyhlDm+UxjCI9RERyC/b+REsPwsvkle6f3pJ8A9o2BUdXb/ePLBpRSScdzSmbuj48 XLiOROucpW7S1R7cxQJ84BfoIFTKB3KpjEUXo1VToLZJjDAGAcbDnR+21zE/en5B/e1L5BnR+VF+ r4UH8L6wfvT7Y/Q+rZJjXvnLMuC0clfzb/iv85/14Sv5HZZBmW/kRpXP8b9owHHPXvKpeG960zsX ZN40+wsrQVFSQ+yKJFMLCvGPwAva3O8jZFNwyETfy5UnAFD+QOOCrEq0Jovh5fKgPAjk0GnNtWL3 HizySmImDuDmSdnTidX7KP2xcPag9URSbtT9SsZY/wA0PdhTXOYQaEKIouwxIvheXQxT+Lznochi nIfituAxDlEDFMU1OciAgIewQEMkxofOjkQ5Bmnb2yTAKZfxcXDy9Xajce+Z1Jg3k5XdRNrJqfcZ 2DX3letV61yzaZr0qt6BBUJHEkReNHCpzdhFXLcAABUMIwy/Zkk6FN7h9zE31wV3lXeQnHO2J1W/ QLV7EOk37FKXrlqq8sZMz2Hl2LgQI8jnYopmOTuKcihCKpHTWTTUKL8oqSoy3/xz+MDqLlmwjOWv EiwxEimVEslc+PFqjp6PfHOfoc6Vb2OrHqsyJl9oFGbcCb/lL09qpYdh+jJUUfLT4OvKDrgdEbs2 1SU67YpevTD7VHJplZ9LpfTUJIFk48xpp2q0gVFiOU+gJtpc4m/iHKJTgBpKMFyLNvqt4b/E6iaL tNZ4TceJNBZBJ/ESZYH6yRLpu5S9RJdEHzly0WKJRAyagAPT2GKPXoOCnHP3JR8FIwCgr8YR+0lw 7/Ufev08JkMyLHJmkHwtv4r9Q/Uhuf8AIzfBVe+Q6ZOSYowDnu/F8/tt8Z/3WEPvbsmQzJscmYQ+ FB/FBn/3WNsfphVsE3vkOkjkmKMA503xdX4kek/3INb/AH87KyGZVn5B8Ir+JHuz9yDZH3861whe +Q6LOSYowDlH+fn8X3mx+fFG+52uZBmW/kRYt+Dn/wBG/PD899B/kG1ZKLV/mi6HgsEWPm4/Cg5z /qQlPyyywVQ+dHJXyDNO0Nxk/Zt4+fqP1P8AoGwyTBfMzhggqx/F1fhuaT/ff1v9w2yshl6z85SE 8ZX4kfj5/ff4offzAYL8/kZ2F8kwhgHNIz3VPzWjAGAMAYAwBgDAGASlav8ADpzg2jRGd+a0yrUx jKsCSkHBX+1owFqmGC7X3pE5WTdF0LIVuoFKR8ZucBEBMUpR7s6A1/yY7Ubf1d5OV+5elB4ZStQc oRadGsTaxU5twxr2bfA2b2t4h98N16CtQt5SGXhOOKEb1yMLlyLjVNQ4uFeSV3puvFpRpIllvmrb 9pTwOWzVu0K28qV8pyUvH2GAfKNV1Way/MI8gicirBRVuug4bLJrIrJHMmomcpyGEpgEdd9E1/R9 0+X1rUNPuq9l71HCaqk0tPo+DSaaaaaaTi000mmbOb121r2zvAK7pmqWJZbNZe7bjO3KlYv76g1x TcZJpqUZRbjOLUotxabrq8dOK+9eVlreVDR9GeWx9Et2z2wyartjD1yssHa4oJqv5CWURbIioJTi mkBjLKgQ/pkOJTAG6m9e4G0u3unRzOrZhWYzbUFRynNpVajGKcnThV0wxqsTVUaC9vu2O+e6WrSy eh5WWZnBJzdYxhbi3ROc5uMY140VcUsMsEZNNG4G3vD1zd1BT5K8OqXWb7DQjJaSnG+trQnYJyLj 26YqKK/R79Bk8dgmAdTFaJrHAPndvaBhDrXbXkt2p3LqccpG/PLzm6R60MEZN8liTlGNfTG4r0rV pHbu8PEXvds7SJ565lbeZtW4uU+hcU5QiubcGozlT16cZ0VW+CbUXWd+msowBgDAGAMAYAwBgDAG AMAYBKx4ar1dobnhpqkxFvs8XTbh9pX1sqcfOyjStWYYjTlhlmgv2KCpWrszZ0gmqkKpDCQ5QMXo IZr15O6Tpea7Q53NXLNud6z0cE3GLnDFmLUZYJNVjiTadGqptM2k8ONW1bJ9+tOytm/dt2Mx1+rb jOUYXMGVvyh1IJqM8MkpRxJ4ZJSVGky6/nlee1wwBgDAGAMAYAwCHnmD+L74aPzI8mn3O0fBWvkf 5CYbBQMAYAwBgDAGAVe/ipeZb7QvCCp8bahLrxt05dW15CTp2axUnKemtcFaTs8n3pj6qf0jIu4t mYOgFWbqOCCIh3FEy7ZjWVfY5xuQZQwBgDAGAWnfhFfxI92fuQbI+/nWuEWr3yHRZyTFNIPJr+G5 5Bv3IOV/3DT+CqHzo49GQZowBgHWF8Euj3mgvFFw6qcszUZzlr1693DLlWMYXCg7qs77aDH1CGHo kdKKlGiIk6AJezoYO/uEZMO46zZzfvK1t1nvTyR81tmRjsr+Gl+Q2xIWvyBFTrJSNao0yehxrhMy giPprsIxJQgfwFMAAAAHTIMqCpBGkFMt9k17cKpfqZLvK/cKPZYK31SejlTISEJZK1KJTTF4gcnt Is2dIEUIYPkMUBwVPidijg/yahOZPEbj7ycgSs0Utwa0gLJMx0eqZdnA3RBI0NYIshz+04RU61eM xEfaIpe3JMGSwyobU4IGAcbDnR+21zE/en5B/e1L5BnR+VF+r4UH8L6wfvT7Y/Q+rZJjXvnLMuC0 clfzb/iv85/14Sv5HZZBmW/kRaj8BnErVXOHwX7s407ijU3VU2HyM261ZTCbVFxMUq1tKdVnMVPR oqiX05CKeARZP5wFUKBklOqShymn0LNxuNypSa5Z8X9pcM+Q20ONm44v6OvOsLG4h3TlFNcsVY4d YhX0bMR53JSHVjpZgqk6bHEAN6agAYCnAxQgyIyUlUtb8E/Kl/tR+Ernvwq3RY/et+8ceGW2Ps8l pRfrIbO0NHVJSKa9VDiPrydUMdJi46gUyjQzZT+UOVyoAsyhhuJlLzBfO3tkmAfFslbr1xr05Urb BxFnq1niJGAsdcn45pLwc9By7Q7B0zeNX5FEHLVygoZNVJQolOURAQEBwCpbzX+Ez4+7RmZq88L9 vyvHSXkl1346nvcc92JqYrpQgACEY/TcJT8G2Mfqob1jSQFERKmRMnaUsUL0bzXMrub3+Gx8sGkz v3MTpSs72gGKi4GsGjdhV6wC4SSATlOlEW00JYVvUAB6FTjzCA+wQARDqoXVdgyGXa2ltw6Js6lK 3ZqrY2obekQVT1jZlKsdGnhQA/Z6pWtlbNljpCPyHKUSj/AI4LiaZKX4lvMfv/xr7YrEY5s1jv3F CdnGjTamkJOQcSUZGQ0g8KV1N1dJ6cSxU8zIYywFRFNF709JwHtTVSFE7amvpOqFWLLA3Ot164Va UazlYtcHE2WuTTE4qMZiBnWCcozdImEAEyThuqRQg9PaAhkmGfcwCgr8YR+0lw7/AFH3r9PCZDMi xyZpB8Lb+K/UP1Ibn/IzfBVe+Q6ZOSYowDnu/F8/tt8Z/wB1hD727JkMybHJmEPhQfxQZ/8AdY2x +mFWwTe+Q6SOSYowDnTfF1fiR6T/AHINb/fzsrIZlWfkHwiv4ke7P3INkffzrXCF75Dos5JijAOU f5+fxfebH58Ub7na5kGZb+RFi34Of/Rvzw/PfQf5BtWSi1f5ouh4LBFj5uPwoOc/6kJT8sssFUPn RyV8gzTtDcZP2bePn6j9T/oGwyTBfMzhggqx/F1fhuaT/ff1v9w2yshl6z85SE8ZX4kfj5/ff4of fzAYL8/kZ2F8kwhgHNIz3VPzWjAGAMAYAwBgDANreDFLiNhcxONlSn0G7uEktwUtxKsHjYrxnJsI eWJNqtFkzmKBknZGwon69Q7TCPQfkHr7uxqmZ0XtpqeZstq5DK3MLTo4uUXFST94t4l9K9Dsrs1o mW3F3Z0fJX1GVq5nbGOMo4oygrkZTg1VVU4pwftirR0o5s/NrzB5Daf3fq7UGpNm2nWNa+yuO2VK u6PLu67Nzs7O3CarRU3TyOMRwZo1QiCimiBwIYyphOUwgTt1W8VO22y9ybUzWp6jlbeau/aHZSux U4xjG3bnWMZJrE3cdZUrRJJrjXdXzg7qdwdt73yWjaZnr+Sy/wBlhmG8vcuWbk7krt638dy3KMnB RtqkKqNXJyUnhw5v3Fuu48h/BXO7c2A4Re3Ox1CAjbFJIt0WgS8hS+R7OjGenSbAVIiz0saC6oJl KQDnN2lKXoUOLbW2tpey/LiGm5JONi3cm4JuuFXMnK5hTfGkceFVq6JVbfE5N3F3nrvcHwInq2py U8zdeWjOSVMTtarasqbSolKcbalOiUcTeFJUR7fxg6uubHxYou+P0tXKfuvci+1ZyOuNnRcKxUTb Gt4fa2bPFvQbvjmBlGw6Z0CegcgKh1MmICfu+P373BpV7yCw61Cd7I5JWIu3CmKUHbjecVVxXxTu NSeJPDykqKnLfGfaWv5XxXlc21ctWNU1N5icbl1ywRuq7LLxbajcaUbdlOKVuUVNuTg6yxZT4KcY /IJoHZFgf8juTsHvDVlirz1FavSV32PfLDFWsjtBZm8j171GIGZIlSKsksik4KkcFAEUzGKQxPgd 3d+9l946FbhoelzyObt3E8atWbUJQo8UZK1N4nXC03Gqpwkk2n93x+7X+Sfb/dVye59Xs6hp9yy4 uDzWZzVxXE4u3OLzGXg40WNSpcpJS+KEpKMoVdvIjS65r7m3yRq9TSbNoFvsh/KtGbIqSbNgvZ2S FoctkiIiJE02zp4okUgdAIBe3oHToG/fZbVc9rXavTMxmW3cdhRbfN4G4KTrzclFNv1rU8z+/wDo enbc7z6xlMpRWo5qcklRKPUpccElwShKTil6JU4UNL87POoBgDAGAMAYAwBgDAGAMAYBJd4fPxF+ O/8Arb+4yz50V5LfgnqX9h+82TZTxB/iJ0n/ABP7pmC8Tnk+e3wwBgDAGAMAYAwCHnmD+L74aPzI 8mn3O0fBWvkf5CYbBQMAYAwBgDAGAcz/AOKN345235RLHrdB2ZWB426q1xrFm3TOUzMZ2yRH2syS 5e35VhNYEWqo/wAAtgL/AIOQzKsqkDJPj5+H+4xeSTUqeytA+UcpbBEJNEdk6jsnEdmy2Zq+YclH tSkmKO1D+qyXMU3ukg3E7ZwBTFKcFU1UkwlccHxRv5/c2P8AzG//AAhf96GKFPX+gio8lPw4fLXg fVh2vq6wG5eaSi4xV7d7XRqE+qN814domK67iUqxJOdWNDESDu+kGjxcqYFOLkjcgEMooVRuxl9B XbwXRgFp34RX8SPdn7kGyPv51rhFq98h0WckxTSDya/hueQb9yDlf9w0/gqh86OPRkGaMAkF8XvC Cy+QXmnp3jxFsXylOfziFs3JONCrkSq2nas6SfTjo6zcSigq6RErFobuDq7col6h3dcFM5YY1Omp 5QuXNa8enADdO54s8dX52uUcNcaNg2gIMUlNnWlgasVxszQIQSGSizj78oiQoADVqr06AXqEmJCO KVDkVKqqrqqLLKKLLLKHVVVVOZRVVVQ3eYxjH6iYxhHqIj8uQZp/ngHQ3+Eg3+4vnCjeHH+TkDvH /H3diU5Ct1HAnCJom6YMZdq3ImYRFMhp2HmV+oAAGMqb2dQERlGNeVJVLX+CyMA42HOj9trmJ+9P yD+9qXyDOj8qL9XwoP4X1g/en2x+h9WyTGvfOWZcFo5K/m3/ABX+c/68JX8jssgzLfyIuh/Cg/hf WD96fbH6H1bJLF75z9fxHXik/wBtXj6PJ/TNeUecnONlZkXasTEs/XlNuaaZqnmZGFAiX8ovJwwm XkIspAMdQRXbFIdRdLsC1PC6HN8g7DO1l25f16YkYR68h5+vO3cW8XZOHMFaoRxWpJmczcxRM2fx 7tZuumPzTpKGKYBARDIMo+NgHb2yTAKF/nN8tvlc4V8/9t8ftXch1dbaVcQVHu+pmrDUGmnsk/pV vqjQ65yylprj6RUBnPtpJoVZNwAiKJgEREOgQZFuEJRqbG/Di+ZjbfITem3uM/N/fkrf9gbOawVt 48Tt2UhYtFxOV8jxOerTMsW3atiuXzRZu9ZtyJlAQauADqYSFwRdtpKqLoeSWCKrzVwfGGT8avKu S5SxdVd1mC1Lc3OvJKcbRxrHEbndQirepmri7wPVQnF533VNEEjAChRMRbq3FUBFcK4uByXsgzDr /wDivbWFn41OBTa0kdpTKXEfQIKJPjFM7SYG1nHHZEU7RESmKyFIOw3zi/xTABgEMkwp/OzffBSU FfjCP2kuHf6j71+nhMhmRY5M0g+Ft/FfqH6kNz/kZvgqvfIdMnJMUYBz3fi+f22+M/7rCH3t2TIZ k2OTMIfCg/igz/7rG2P0wq2Cb3yHSRyTFGAc6b4ur8SPSf7kGt/v52VkMyrPyD4RX8SPdn7kGyPv 51rhC98h0WckxRgHLd+JG1+7o3l+5MPlGpm0ZsOI0zsCCEx1VBdNH2m4OvO1eqvX2Gl4x4AAHsAA 6B8nTIMu06wJOvhF+Umvdebo5N8XrrYI+Ds++oXW101MlJOWzFGwT2rvp1rLxTcyoALiRcsJlF0i iB+opNFhKUfbhFF6NVUv0ZJjkFvxF/Iah6R8WPICqWGyRUfed9Ma/qnWVXXctvpm1v5C4Rj6YM2b nN6p0I2ETcLrrAUSpj6ZREDqJgYXLSrM5cTVq5euW7Jk3XdvHa6TVo0apKOHLpy4UBJNNNNIBMc5 zCAFKACIiPQMgyztaatqZqFrLXNGOZQ5qXRKhUzHVWScKmNXK+3hxEyiJEyHMPo+0xSlAflAA+TJ MA93gFWP4ur8NzSf77+t/uG2VkMvWfnKQnjK/Ej8fP77/FD7+YDBfn8jOwvkmEMA5pGe6p+a0YAw BgDAGAMAYBmHj5tNTSG89RbeI3cvE9cbEqVvesGaoIuZOKhZpF48aEMIlABdNSqI+0enzvb7M43v HQI7q2nnNNbUftNi5bTfFRcotRl/6XR/kOUbI3HLZ+88hqyUpfYszZvOMXRyVu5GcoV9ppOL9Gm0 y1jyu4X8efKnH645G6w5HRdU+gKanASdojoRjdY5xUffXFibspJg5lYdeFkY9y8dCoC5wOXvMRRM BKAh56du+6G9PHu9mdD1DTJXupdxxg5O28dFByhNW7iuQnGMaYVTgmpcT1Q7q9me3vlTbyu5tJ1m GXdrLq3Oagr0emnK5CNy27tp2bkJXJueKkmnhklhTXjOWrnjRrHxF7L0hpDb1KutfoSNV1vHumlx gJSXnr0z3DGWWXJ6bNYfUfOFzOnxkkSiUEhE5A9IoGz6/be3vzXvJLLatq2Tu2LmY6l1p25RjG08 vO3b4tcIpYLdZcXKifxOhw/vPd7W7c8O81oG3tRsZu3lr2Wsxw3oTncvLP2cxeolJtya6l/DGqVu so/VpM1t8W3ITj9uviLd/HvyDtjCnu5D63RlNNKyrKATsNUuz81h6RL6W72oT0TOLrOkkFC/PAyR iJrARYC827/7L3ltXuRl96aLZd5RwO5hTlhnbWH44xpLpXLSUHJPhSSco1hXhPjH3C7f717TZvt3 uXMRy3U6isSk4wUrd2SmlbuTxQ+0Wsw3chGcUpYoYYXMF2nrIrwp8UtCvHWyeUHKgJnVTFBw7Zw8 izhtOsXftD0yOpZWakV34dqhQKkyI3VUUEvaPt7DfNzHlN3D3haWR2/pODNyaTknLMNe9IK3BR5P jNyilWq4VX28v4Xdre3937y3Vr8Z5GKbUXGOVUnVUTuO9dc006KFtRnKTWGXHC66W5kNYNts7Fb6 VdzT/UqFwnktdvbCRROYdVMkgcrNRYFiJq/OS6CX1SFU7eneUp+4A3X2xLXp7dy0tUUI5x2o9VQ+ VXKLElzXP2bVeTaozzx3XDbtvc+bjpEpzyKvXFYc1SbtYn03JNJ1cac0n7pOqWM8+6fAGAMAYAwB gDAGAMAYAwBgEl3h8/EX47/62/uMs+dFeS34J6l/YfvNk2U8Qf4idJ/xP7pmC8Tnk+e3wwBgDAGA MAYAwCHnmD+L74aPzI8mn3O0fBWvkf5CYbBQMAYAwBgDAGAcgLyo3pfZHko522xVyV4kvys3hCRj oveBV4Co7AfVCNMAKFIYAFgxR9ggAh8g5BmwVII1y498jd38U9qV3dfHrZFj1bsyrqH+jLLXHCRT Ls1jkOsyetXhFWclHOewoLs3aSqCoAAHIYAwS0pLidCTxN/Ec6I5nlrGkeVJq1x35PuitYmMlXL8 I3TG4ZYwEQTCJey6ojBy7tUwlJFvVTFUP2lbuFVFAQIMadpx5FmbJLRWu8n/AMNvxk5oLWHbfG1a F4t8jpEy8i/NFRRg0lsiVU6qGNNQsSTviHrg4B3yMWQOomOos2cqG7gF2F1x5lDDmV48eX/Ai4KV Tk1pmy0pkvIOGNc2AzQNPauuoIiYxTxFgiwPHuTqJFBUWxzkdJFEPWRTN1KEGRGUZcicf4RX8SPd n7kGyPv51rhFF75Dos5JimkHk1/Dc8g37kHK/wC4afwVQ+dHHoyDNMqaU0jtfkZs+oaZ0jRZ/Y+z L1KoxFaqlbZmdPnjhUep1VTGEqLVm2TAyrl0uciKCRTKKnIQpjADaSOoF4V/EzU/F/x9XQsSkZae Tu3m0NM7yvLMCuGMSdm3FVpVYRUxSm+hodRVQTrCAHeOTHWP0TBBFCTDuTxsqB/EpeTdjzJ5PM+N morGSX498WZWWilZSLcouITYm7lQNGTMsgq2MJHTGHSAYxir7SiYHSqZjJLlMMF+1DCqlaXBdGAW 8/g/b2tH8seWOsiuCFb27jvA3tVqJieqstrrZTGvpqAAkEwlSLaTgIgcADvDqBvYJSLN9cEdAPJM YYBxsOdH7bXMT96fkH97UvkGdH5UX6vhQfwvrB+9Ptj9D6tkmNe+csy4LRyV/Nv+K/zn/XhK/kdl kGZb+RF0P4UH8L6wfvT7Y/Q+rZJYvfOWZcFo5sHxHPimPwr5DKcndNVojLi/yRsb16aOiWwIRept 0PyLTEnBgkl8xvGS5U1ZCLKUCkIHrtiEIRun3wZVqeJUK1GC6dvbJMAr7+e/w/vvJTp+s7F0ojEN OV+j2ci2pSUq9bxEbs+hyLgJB5WXbxwHpt3STgBcxayxgRTWOqmoJCODKpi5bngZzXtk6w23x72P K6/2nS7pqXaNIlSlka7aIuTq9ng5Ji470l0yuSpqgXvICiDhIRIcOh0zCUQHIMtNNElOtvPN5ctU VppU6pzX2A9iGLNFg2PsCq6r23NkbIFEhAGU2vATUoc4APTvM4E3ye32BgoduD9DS/k1zb5acype LmeT2/tj7kVgjLKQEZapw4VaurOkypLKx0LFlbREesuUhQWUbtiHUApQOI9odBUoxjyJQvDZ4S91 +Q7adQ2NsypWPXvDGtTDOZu+w5pk8hVNqMox2mueu1T3gE1Xqsj7UXEikAt2afqG7zLlTQUFE7ii vpOoBGRkdCxsfDRDFrGRMSxaRkXGsEE2rGPjmDcrVBBFJEAImkkkQpCFKAAAAABkmIfuwCgr8YR+ 0lw7/Ufev08JkMyLHJmkHwtv4r9Q/Uhuf8jN8FV75Dpk5JijAOe78Xz+23xn/dYQ+9uyZDMmxyZh D4UH8UGf/dY2x+mFWwTe+Q6SOSYowDnTfF1fiR6T/cg1v9/OyshmVZ+QfCK/iR7s/cg2R9/OtcIX vkOizkmKMArQfEP+HW3+QKh1HkVxwimcpyf0lXnVZd01Rw1j3O4dUi/WnCRbVy+OmgSXhnzlw5Yp qnIRYrhdMTeoKIYLtqeF0ZznbBXth6evj6vWeFuOsNm6/nyJSENNsJmm3imWiGclckBVB6Vu+j3z VUpTl6gQ5DAAh0HoOQZXBokrqHnM8s9HgGNag+cG23UZHEBNsra0KZfJoSAUCACsneYqRkl+gAHT 1VzYKOnD2NEN+8mOQPKa6faHyL3FsDclxI29xZzN9skhOmiI4T+r7rHoOT+7RzTv6n9Bqmmn3CJu 3qIiIqUVHkWJPAD4T9xchd6av5i8iaFK0Pi/qifh9iUlhdIpxGyu+7jBOAlIgkcxkCkUUrTN6mk6 dvlSeg5AgNkQVA6x0Bau3ElRHRhyTGGAVY/i6vw3NJ/vv63+4bZWQy9Z+cpCeMr8SPx8/vv8UPv5 gMF+fyM7C+SYQwDmkZ7qn5rRgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgEl3h8/E X47/AOtv7jLPnRXkt+Cepf2H7zZNlPEH+InSf8T+6ZgvE55Pnt8MAYAwBgDAGAMAh55g/i++Gj8y PJp9ztHwVr5H+QmGwUDAGAMAYAwBgHGy51FMTm5zGIcpiHJyp5ClOQwCUxTF23LgICA+0BAcgzo/ KjVbBIwCxp4w/iN+VHCBOA1RvYJXlHxsYe5RzOGss0sbbmtoduUjQpK7OyZlPemLZAvROLke9IAI RNBZoTu7lS1O0pcuBfe4T+RziB5BaYFs4z7aiLPJMmaLq063mgLXNq0cyvQhiSsG/P7ymmVQfTB2 h6zRQwD6Syge3JMeUZR5m3F4odH2dVJqibIp1Xv9JsjM8fYahdIGLs9ZnGCggIou2M0ks1cJiIAP aoQQ6h1wU8iPXi34ieEfCzk5b+U/GKhT+qLdedX2LVNho0Ra5CT1YeGs1wg7u4dtY2xFeO494R3A IESI1eJtCJHUKDf2kEgrc5SVGSbYKDAXK7T0lyH4t8k9AQ0wxrsxvLQW4tPRVgk0HDqNgpLZmu5G lIPHCTXoqog1VelUUKT5wlKIB7cEp0dSobpb4PGPSlGb7kTzTeP4RNUgv6vpbVyMRKO0Acm7gRnr zIPUW5xRAvQTRCoAYw+wQL86KF53/ZFobhF43OHvj0qbyt8Y9TR1WlZto3aW/Y824Vs20LuRscFi lkpqT6uBbAoHqFZtwRaEP1MREoiIjJalKUuZX++IF87lf0dVrpwg4b3dKU37YEpGqbw2vVn3qNNI QiyajB9Bxb1mYAG4OQEUl1UjD9Gk7gAQeCHu4uW7dXVnPzyDJGAMAtQfCKJKj5Ht3rAmoKKfCTYi SioEMKRFVt763OQomD2AYwEMIB/D0H/kHCLV75DorZJijANNZ3xz+Pe0TczZrNwS4a2KyWKVkJ2w WCd4waSl5udm5d2eQdvHjuQg1F3Tp0uodRVVQ5jnOYTGERERwVYpe5n3U+ldN6Fq6lH0ZqXWWmKW rKu51WoanodW11V1Zt+ik3XeGj6e0ZtDOlk0EiqKin3mKQoCIgUOghtsybgg1Ku/ATgnsy2Tt92R wq4lbBvNofHk7NdLvxx07a7ZYpJQhUzOH0jPQzh47XMUoAKiqhjCAB7fZgqUpL1M0an0rpvQtXUo +jNS6y0xS1ZV3Oq1DU9Dq2uqurNv0Um67w0fT2jNoZ0smgkVRUU+8xSFARECh0ENtmTcEHgNm6o1 buunv9e7k1rQNtUGVXYOpSj7Np1dvlPknMU8JItVHEZamztksds4TIqkY6YiQ5QMXoIAOCU2jV/+ zK8bn/D54Qf7qGhv8gYJxz9zd/BSMAwrujjdx75HQ7eA3/o/U26YdkVcI5jtHX9WvCcUZyJROdmN jauDs1DCQo96IkN1AB69QDBKbXIjxkvAt4iZV6s/dcI9dJLr+n3pxtm2hDMi+kkVEOxtETyDdPqB Q69hA6j1EeoiIiKupP3Mw6n8RnjM0lIspjXnCTj8ymYw5Fo2astHZ7DmY1wmoKpVm7vYgyrhBcom HoqQ4HAPYA9AAMEOc36kiiSSSCSaKKaaKKKZEkkkiFTSSSTL2FKUpOgFKUA6AAfJgpP7wBgGAtw8 UeLfIeSh5nf/ABs0FvKYrrFeMr8ruHTuu9mSUFGunHvSrdmvdY56q1QUVDvMmmYpRN7RDrglNrkf D1bwr4b6NtiN90pxL4zaevLdi9jG901bofVmvrYhGyRATcNySNSimjwqDgoACiYKdpwD2gOA5SZs zggYBr3t/iRxS5CTcZZt+cY+Pe8LJCxQQUNYNv6X1vsubiYQHakgDNs7uca9XQagusop6RDgTvOY 3TqIjglNrkfh1Pw04gaFtCl40ZxT426YuisU7glbfqfRmsNdWhWEfrJOF2ZpCoRbN2ZqsogmZRIV OwwkKIgIlDoDlJmyWCBgGum3eH3EnkDZGNy31xb46buuEZBtqxG2vbuktabJskfW2T9zKox6D65R j10kxSdPXCxECnBMqiqhgL3HMIiVKS5DUXD7iTx+sj65aF4t8dNI3CTg3NYkrXqLSWtNbWSQrb1+ 2lVo9d9TYxk6VYqumTdY6BjimZRJMwl7iFEAcpPmbF4IGAMA103xxC4scoWqDbkTx301ugzNqdlG yOxtd1e0T0K1UU9UxY+Skmx5CP7jdeotlkxHqPt9o4JUmuRoc+8CXiHkHa71fhJr1NZwcVFCMbXt SMaFMIdP5NvGz6SCRf8A1SEAP+bBV1J+5nrTfio8cOgZZjYNVcMNBQFji/RGKsspRY652WKVQKBS qtZG8fST1sv0D2qpqlOPt6iPUcEOcn6kgWCkYAwDFe3dF6S5A1tjTd9ad1Xu6nxk42s8bVNu69qW ya3H2RkwcxSMggxuTN61SfJNXrhEi5SAoVNVQoG7TmARKbXIwhWPHjwApNkr1ypvBrh5UrhUpyJs 9UtdY4zaWgbJWbJAv05VjIR76KhEnTJ8ydJEWQXROVRNQpTFMBgAcE4pe5uHgpGAc0jPdU/NaMAY AwBgDAPU0qkW/ZFqhKPQq3M2+32N4DCCrlfYLyUtJuvSMuYqSLYDGECJkMc5v4pCFExhAoCIYGqa rpuiafPN5y7GzZtKspzajGK5cW/p4L3bSXFn0dI0fVtf1K3k8jZnmL910hbtxcpyfOijFNuiq37J Nvgmft2Jre+6kt0rQtmVKdo9yhBbfSlcsbBaOk2hXjUj1E4prAHcmsioVRM5REpyiAlEQHLWja3p G4tNhnMjehfs3K4ZwalF0dHxXqmmmuaaafEr1vQ9Z23qtzI6hYuZbMWXSdu5FwnFtKSrGSTpKLUo vlKLUotxab9JbdDbnoev6Zta56yudZ1xsP0vqVc5iDeMoGw+8tDSKHoLqlAv+NNiGXb93T1kiion 3EATBg6du7bGr6xe0/K5q1dzOW/nLcZJyhR0dUv0XSMv0ZNRlRuh9PVNlbv0TQ8vqecyV+zlM1/N XZ25Rtz4VWGTSXxKsofpxTlCsU2fl1PpXbO9bGvUtPa9tOxbE0jlpd7GVeKcSSkfFN1ComcuTph6 TZD1FCJgdUxQE5ilARMYAG5uHdG3dp5FZnUsxby1pyUVKclFOT9FXi3RN0VXRN8kyxtnae5t56p9 i0nK3c3fwuThahKbUY0TlKieGKbjHFKixSjGuKUU/JW6oWmg2aapl2r8vVbXXH60ZO16eYOIyWin 6HTuTWQdFKchuggIdQ6CAgIdQEBz6Onalp+r5GGaytyN2zcVYzi1KMk/VNcGfN1PS9S0XULmUzlq di9ak4zhOLjOLXNSjJJp/Q0eczNMEYAwBgHoalUrPfLLCU2lwEtabVY5BCKga/BsV5GWlZBybtIk ii2KY5zD8o9A6AACI9AARzC1HUchpGRnmc1cjatWouUpyaUYpc22+CM3TdM1HWc/byuUtTvXrslG EIRcpSk+SjFJtt+yR6LZmpdl6aty9C2nSLFRLi3bMnh6/Yo5ZjIHZyJO9BZMpuoKpK9BApyCYoiA h16gIBh6FuLQ9z6cs3p9+GYsttYoNNVXNP2a9nxM7cm2twbO1OWT1XL3Mpfgk3C7FwaTVVLjSqa5 NcOfHge33Dxe5B8f4uqzW59S3HXUVdUBWrj2xRwN0XihUQcmbq+kY4tHpEzdxmrgE1yh1ESB0HPl ba37s3eOYvWtLzlrMzsOk1CVacaVX6UW+Uo1i/Rn291dt9+7GymXv6xkL+Thmo4rbuwca8K4Wnxh NL5rc1GcfzoowLnLjhJ7vWmsdgbjusJrrV9TmLtdrEsqjEV6Dbgu9c+7oGdKqGE4lTRQQSIZRVZU xU0yFExzAUBHPk65ruj7a0u5nc/ejYsWlWU5OiVXRfS220klVttJJtn19A0DWt1a1Z07TrM8xmb8 sMLcFWUnRt8PRRinKUnSMIKU5NRi2my9Y7A05dZvXW0KnMUm7V1ZJGXr043BB6294QK6SUKJBMms gukcqiSyRjJqEMBiGEogOND13R9y6XbzuQvRv2LqrGcXVOjo/pTTTTTo0000mhr+ga1tXWr2najZ nl8zYlhnbmqSi6Jrh6qUWpRkqxnBxnFuMk34TPrHyBgDAGAMAku8Pn4i/Hf/AFt/cZZ86K8lvwT1 L+w/ebJsp4g/xE6T/if3TMF4nPJ89vhgDAGAMAYAwBgEPPMH8X3w0fmR5NPudo+CtfI/yEw2CgYA wBgDAGAMA5HvmZ1u61X5Ued1YeJqpKynIq87IIVYBA4tdxuSbeQMHcI/MOhOEMX/ANUQ+T5Mgzbb rBEZeCoYAwD1lHvl31ja4W963uNooF2rbwkjXrfTJ6UrFmg36YCBVmj6FVRdN1AARDuTOA9B6YDS ZZ+4TfFY8vNJt4mm8taPAcraSzTbsy3Jq5a633SwapgCPes9jWq0NNeimACBV2KLhU3UVHYiPUFS zKzF8i3l48/Mvwp8ls5KUTQU7fYXbVepLvYdj1Tsijv4CxxNRjZxhWnL0H8OeRrzlNF9KNEuxGRM qPqlN6fQDdslmUJQ5krWCg/hVVJBJRZZRNFFFM6qqqpyppJJJl7zGMY/QClKAdREfkwCJzlR5wvG XxIZyyV55NU7YFyi/WRDWminLfb92dSSBROZmp9VFVImLc9A+STfNCAPsEwCIAIrVucinh5H/idu T/KmLsOqOKkI+4o6alveI9/amM0Z9v63w6hDoGTVl4wU2tbQcEMAqIxoGcFEO330xBMU0VL8LSXM rAGMY5jHOYxznMJjnMImMYxh6iIiPtERHBdP5wBgDALl/wAHjrZy/wByc1NwGQXIzqmstWa2QcmT UK2Xc7AtUlaFUyHE4FOdItZTE4AQwlA5eol7gA5Fi++RfHyTHGAaazvkY8e9Xm5ms2bnbw1rtkrs rIQVgr87yf0lETcFNxDs8e7ZvGkhOJrtXTVdM6aqShCnIcolMACAhgqwy9j5X9pr43P+INwg/wB6 /Q3+X8DBP2H9pr43P+INwg/3r9Df5fwME/Y2G1vvvRe5BdBqDdGptqixL3PQ1vsan3kWZe0h+qv1 YeOvTDoco/O6ewQ/5QwQ00ZZwQMA8le7/RNW1Gc2Bs261LXVDrDUr6yXa92SHqNRrzE7gjQFn0lY Fm7NokKqhCAdVQodxgDr1EMDmam/2mvjc/4g3CD/AHr9Df5fwVYJ+xtrSL1SNmVOCvut7jVdg0a0 MSSdZulIsMRa6nYo05zJlcMZGBWcM3aAmKIAokoYvUB9vswU8j1WAMA/hVVJBJRZZRNFFFM6qqqp yppJJJl7zGMY/QClKAdREfkwCN/a3mC8YelpN3C37m5oRCYj1TN5CKqdvJsmQj3JFSoGRcI62Tll EFiGN89M4AYvtEQAAHoKlCb9DGkF53fEfYpFKLj+b2r27lbp2KzsRsKrRwdyhUvnvLNDNGiftMH8 ZQPZ1H5AEQE9OfsSPan3dpnfNbC4aQ2zrbcFU700TWPWN3rV6hUl1U/VBJRzWXLpJNXt9okMYDB/ CGClpoyhgg0g/tNfG5/xBuEH+9fob/L+CrBP2H9pr43P+INwg/3r9Df5fwME/Yf2mvjc/wCINwg/ 3r9Df5fwME/Yf2mvjc/4g3CD/ev0N/l/AwT9j0dQ8gvAnYNogKPQubvEO73S1yrOCq9QqHJTTNlt Fkm5FYG7dmwj4aaWdvHS6hgKmkimY5jD0ABHAwyXobF3/Ymv9T0+b2FtO807WtBrSCDqx3i/2aFp tPr7Z08TjklHsnYl2zJoRRwsmkUyqhQE5ylD2iAYKeZqj/aa+Nz/AIg3CD/ev0N/l/BVgn7D+018 bn/EG4Qf71+hv8v4GCfsP7TXxuf8QbhB/vX6G/y/gYJ+w/tNfG5/xBuEH+9fob/L+Bgn7G0Gstr6 t3XT2GwtN7KoG2qDKrv2sXeNZXGu3ynyTmKeHjnSbeTqrl2yWO2cJnSVKRQRIcolN0EBDBDTRjrb /Lfilx7m4ys785Oce9H2SaignYav7f3RrfWk3LQgu1I8HjZpc5Jkuu1FdFRP1SEEneQxevUBDASb 5H4dT8y+IG+rQpR9GcrONu57olFO51Woan3nrDYtoShGCyTdd4aPqEo8dlaoqLplUVFPsKJygIgJ g6g4yRslggYBpB/aa+Nz/iDcIP8Aev0N/l/BVgn7G0Gstr6t3XT2GwtN7KoG2qDKrv2sXeNZXGu3 ynyTmKeHjnSbeTqrl2yWO2cJnSVKRQRIcolN0EBDBDTR5bcfJHjvx2bQL3kDvvS+i2dqXkGtYd7j 2lRtYtrG5iU0lXSbBS7PmJXh2xV0hVKkJhIByibp3B1BJvkYI/tNfG5/xBuEH+9fob/L+CcE/Yf2 mvjc/wCINwg/3r9Df5fwME/Y/Wx8k3jqk3aDCN59cK5B86OCTZkx5T6Mdu3Cgh17U00J0xzm6B8g BgYZextLS9g0HZESE/ru71C+wRjEKWapdlhrTEmMomCpQBzBrLoiJiCBg+d7QHrgpPX4BTm5E+EH lPqYr6a1M7g+QdUagdUE64UtW2Ag1SQFY51ISacKJLiAh2ETZPXKxx6dEw+QPTbZXlb293G42tRU 9OvP9P47TdaJK5FJr3bnCEV+keN/cPwo7s7OjK9puDV8vH1tfV3klGrbsTk68eEY2rl6bqvh50iA tFUtFInZCr3Stz1RssSqCEpXrNESEDNxqwkBQCLtJRNJdEwlEBADFD2D1zZPIahkNVykcxlbkL1q arGcJKUWvdSi2n+RmpOoafqGk56eVzdqdi9adJwnFwnF0TpKMkpRdGnRpOjR8DMwwxgDAGASXeHz 8Rfjv/rb+4yz50V5LfgnqX9h+82TZTxB/iJ0n/E/umYM/ecJvGuOeNbbyzw8XFOtQ62SlpNBoL1d iwVsswis4KiQSisdFHqYCdQE3QA65w/xQneh2iuO2sUlmb2FVpV4LdFX0q/X05nNvOKFuXfKKk8C eTsVdK0+K4q0qq0XpVV5VRk7zG8t9G7I1lx147ccrrVrpQqiJLpMqVVT3uNgCV6u/UitsCrFKUqa yTJ0/wDWbj0OmHpdxQ7gz4PjN243ZoevalreuWLlnM3vq44+Dljn1L0qeqclbwy5P4qNnJPL3uxs bcO2dG23tjMWr+RysepJW08MMEFZy0E+Ci4wd3FClUnCtOT3o8L2sa3x64a3LkjsR2yrJNtzrmwu 5yUN7qnH64ojhasxoK+r84vrSJ36xB9nqEVSEAEOgj1L5Ra7n969zrGhZGLuvJwUVGPFu9dSnOnv SCtp+zUvpO8PDPb2kduOzmc3Vqk45eGdm5O5KVIxy+XcrcG0+EW7rvOv50XB8VQ0k8+egvq1tvWP IqGYJJReza8pRbgu1bGL/wDjSkFBZk5dK9Ohln8OuRBIOoj2MB+QADr2r4fbx+37azWiXZNzys+p bTf9Hc+ZRXtG4nJ/TdR0v557A+6d7ZTcNiCVvP2undai/wCes0SlOXJudmUIQXOliXpSkGWt9Y7B 3Bbo2hawqE7ebjLEdqx9errFV/IuEWDUz1dTtT9hE0UiGMc5hAoAHtHNstb13Rtt6bLOZ+9CxZhS s5uiVXRKvu26Jc2aQ6Dt/XN06rDI6bYuZnMXa4bduLlJ0Tbolxokm2+SSbfBHzrrSLfre1TdHvtb mahb648FhO1ywMF42WjHXpFXKVVFyBTAB0zlOQ38U5DAYoiUQEb+l6rput6fDN5O7G9ZuqsZwalG S5cGvp4P2aafFFjV9H1bQNSuZPPWZ5e/adJ27kXGcXzo4ySaqqNe6aa4NHupzj1vCs6ugd12DVd2 iNT2dZujBX59BPEK5ImeGUKgYq5i9CpuBSN6JzABVOnzBHqGfJym8tqZ7X7ml2c3anm7SblaUk5q lK8PdVVVzXrQ+znNjby07blrWL+Rv28jedIXpW5K3JutKSapxo8PpKjw1ofN1HpPbO+bUSk6d1/Z dh2YW4vFo2uR6josewKqVuLl4uftbMWoKHKQVnChEwMYA7uogA3tx7p27tHTnm9TzFvLWq0xTdKv nSK5ylRN4YpuibpwMfau0dz731eOQ0jK3c3mJLFgtxcmoppOUnyhBOUU5yainJJtVRKlwT4YcpeP POfjHZdx6TudLrTq3WBsFkWbMpiutnS1ElkU0XL6urPGrRZYw9Ek11CGU9vaA9B6a+92+5+wN6dp dUsaZnrV+6rUXgTcZtdSFWozUZSS9XFNL1obSdjuz/c7t73z0W/rGm38talekuo44rafSuUUpwco Rk/zYyacuNE6M9t53ph/Xeb+nrBFKFRk4Lj5r6YjljpEWIk/jNuW96iYSKgJTgVQgCJRDoP8OfJ8 RMtZznanOWbirGeduxa+h2LCf+w+755X7+V7z5G7alhnDTrLi+Do1mc006NNOj48U17po855JuV/ L/kZrjQmotxcT5rR6FjskbcoAhmNlkZbZ99awqtaRTiWz9sksxKROdMBow4uHIHWSAx+oABs/sd2 57a7J1vUNS0vVoZ524O3L4oKNm05Kb6jTak27f8AOfBBqMqLnT4vkX3h7udxtv6Vout6JPTXdlG9 FdO7izN6MXbrZjNVil1qOzW7ci7lvFLjHFIhWODrhXw/uNcSvHGMJyScVWyT6UU4p8O32gN1DaLm Sj1xedpXpXn0SVBMAMsA+7/yBg9PqnnTGod2YR8l1nbWpy+61OEKq5J2On0Iqaw/Lh6mJ8qY/jXG jO99D7E37/hy8nmtFj9+Pq3UnZgs1j+2TdqWKiuKf2bBGjkpdL6qSo3EhO4a2bk3ws5kw8ZA6As9 r3GvFS9OlNJzcRMRNlnoCbaJzSpmx0UVVGxSpMyOyPQTVQBEgnHuTERzabudp2xO6XbKc72oW7WS Uo3I5iMoyhGUXhVeKT4ycHCqlidFSXA067P673G7M94LUcvpl29qFJWZZSdu5G7OM0pNJKLlH4Yq 4rijKCguo626s8T5Dd37c3zydtdo3XrBbTNzgImDpxNavE330jWYSNQPJtSuV5BNA7xVyD0zgHBU iJqEUKJC9naI/U7MbT25s/YVnL6XmlnbFyUrnWVKTlJ0k0k2opYcOGraaabrU+V3831uvuB3MzGb 1nJvT8zaUbX2eSkpWoxVYqWNRlJyUsanRKcZKUVgcTxOn+EPLLfVfJbdT6JvVqqq3q+52YWbSBr8 p6DgzRT3J7ZVmbZ96SpDEP7uc/aYBAeggOfV3L3V7d7Pzn2fUc/Zs3VzhVynGqqsUYKUo1TTWJKq fA+Js3s53R7gZL7Vo+mZjMWONLijhtypJxkoXJuMJuMouMlGTcWqSSMdbk49bu4+TLWB3TrC365f v/XGLPYopVCLmitATFYWD5D1GL8qPqkBQW6xwIJgA3QRz7W2d5bV3llXe0vNWszGNMWCSbjWtMUf mjWjpiSrTgce3dsbeOwtQWV1nJ3snclXD1IOKnhw4nbl8lyMcUVKVuUkm6Np8D+NU8fd37zSs6+n tV3fZCNMZIP7QpUIF9Mlh0HZVjoFV91KPVdwDdUUUC9VVew3YU3aPSrcG8dq7UlaWp5uzlnfbUOp NRxNUrSvoqrFLlGqq1VFG2dlbw3nK8tIyWYzn2eGO50bc7mBOuHFhTo5YZYI/NPDLAnhlTNNB8e3 NLZ9PY32lcd79KVSVaFkImUdoRcAaXjlEAcpuWjexOWjp03XTMBkVUkzEVAQEgm65xbWe83a7QNT lk83qVmF6DpKKblhdaNScFJRafBptNeqRzXbnYbvDuzRYajp+lZi7lrkVKE6KKnFpSUram4ucZJp xlBOMvzWzVO0VazUiwStTuVdnKnaIJ0ZjNVyyRT6EnIl4UoHFJy0kk0l0FO0wD2nKA9BAf4c7CyG oZDVMnDMZW5C9auKsZwkpRkvdSi2mvpTOr9Q07UdIzs8tm7VyxetukoXIyhOL9pQklKL+hpMkQ8P n4i/Hf8A1t/cZZ86V8lvwT1L+w/ebJsR4g/xE6T/AIn90zBeJzyfPb4YAwBgDAGAMAYBDzzB/F98 NH5keTT7naPgrXyP8hMNgoGAMAYAwBgDAOdr8Whxvc655yat5GR8eZGuckNPs42TkASKBXWx9NOS Vh8UxiD8pYB5CgXuABHoPQRAPZDMmy6xoVU8F4YAwBgDALTvwiv4ke7P3INkffzrXCLV75Dos5Ji mD+Tf7NvIP8AUftj9A3+CVzOLzkGcMAYAwBgDAOlR8LNxyc6c8ahNqzDEzWd5ObZuOx2p10ypOwp FUFPWUUmcolA4JncRL52iJhHuI5AxfmmDrJi3nWZZOwWhgHGw50fttcxP3p+Qf3tS+QZ0flR9DSP ArmnyTpquw9A8Xd3bhoqE0+ri1s17r+wWeBTno1BF04ZmcxiKiYOEU3KRjk69QA5R/hwQ5xT4mQL L4sPJRUIpacn+B/LJrFNe4zt420RsaVIzSIidwZVcIiPXOigQhBEypwAhfYAiAiHUFOD9TTKt2e7 ayt0bZ6fYbVr6+1CVF1EWGty0vU7dV5ticyIqNncWo3esnSJupe4hynKPUPZgq4NHQ8+HU8y9650 QNn4o8n5pKf5G6mqZLdT9jrJtGT/AG/rFi+QhXP0kRsVNJSwQi7puVVZMoGeN1AVOUVUnCqsmNdh h4otIYLJT3+LT5tBRdH6k4LU+Y9KybulW+2tuNmqpPWb6rosoKMIycEN7fSmbIkLkhi+0BihAfmn 6DDL9mNXUoI4Mgv3fCXc3/r5pDa/BK5TKi9k0fIuts6fau1O46up7zLlTnGDYCh0BKHszgHR+4e4 xpXoXqUg9pGPejR1LhGSWBgHMT83Pml3Fzx3XsHTOpr3OVDhdQ7HJ1SqVKsyLiJbbo+gngsVbJYl GRk1JNrIuERXjmK/8g3b+kYUgcCooaDKt21FVfMjd4o+NDnbzeYO5ni/xrvuzqyyeOI1xdO+v0ug BKMyFVWaFsGwnsTCqO0SnKKiBHQqFAxepQ7g6itzjHmbE7l8Eflj0PTpK/X3hzdHVVhmP0jLPdd2 3WG3pGNaJNSOnCisZqqcmZUqTQDD6yvu3plAhjdwkL34IVyD9TQHjtyW3txO2fBbj48bOtWq9hQC 6KjearMio3Rk2aTkjo7GTaKd7OVjHBkyguydpKoKgHQ5BDBU0pLidTfxAeR2I8mnD6u7pdxsfW9s 1GXX1tvOpxfqEiYzYkNHt5Az2NI5UUWLEzLJyi8bFOYwpGOo3E6hkDKGkxJxwSoc2z+yJ8oP9Qjl P/Q7cP8As2RQyepD3PFbF8Z/kF1HSLJsrZ/DfkRQqBTo48varjadX2eHr1fi01CpGcO3TxAqSKQG OUBMYQDqIYJU4N8zR3BUSCw/ig8ltgiIufg+DHJ2VhZyOYy8PKMNR21yxkouSbFet3CKibcSqJLJ HKchgHoICA4oU9SHub+eMPxh+Q/WPkP4X7D2Hwv5G0ui0vkbqyx2y2WPVlpioGuwMVaW7py8eOXT cqaDdBMomOcwgAAHUcFE5xcXxLt/n6/CC5sfmRRvvirmSWLfzo5R+QZhIcz8Svk3kGjV+x4Iconb J82QeM3SGoLeog5auUgWTUIYrboYhyGAQEPlAcUKepD3P0/2RPlB/qEcp/6Hbh/2bFCOpD3H9kT5 Qf6hHKf+h24f9mxQdSHudDj4fjS22uP3i90vq/d+urfqrYsLb9yPJalXqDfV2yRzWZ2lKSrRRZrI kIqQjhsqRVMRD5xTAIewckxrjTnwKwnxfP7bfGf91hD727JkMvWOTMIfCg/igz/7rG2P0wq2Cb3y HSRyTFGAcQnIM86gPwzH4QWhPz43v98UxhGJd+cix+MY/wBG/A/899+fkGq5LK7HNlInWGrdjbqv ld1fqSk2XY2xba5cs6xSqhFOpyyTzpmwVlVU2rViU6qx02yCihgKA9ClEfkDIMhtJG7X9kT5Qf6h HKf+h24f9mxQo6kPc8ZfvGV5D9W1aTu+wOE3J6r1CESM5m7HIaXvYxEIzImZQzh6s2ZKEaNSAX5y yolTKIgAmARABEqcH6mANFch948Y7/FbS4/7Tumpb5Drt1m1gpk06i1XSbZwVyDd6gURayLFQxQ9 Vo7TVQVDqU5DFEQwVNJridRnwt+TBHyccR2uybMxioHeWs5wuut416GIdvEq2VGNSkmc3HoKnUOh HTjQ/qkTMYfSXTXSATFTAxpMOcMEiXjBQYc3Hx80lyCghrm59Y1DYkaRBw3ZnsEUirLxBXQdqho+ RbenIRqpgD/rGqyZ/wDnzk+2N6br2Xm+vpeau5aVU3hl8MqcscHWE19EotfQcJ3r232J3GyP2fW8 jZzcVFpOcfjgpc+ndjS5bb97c4v6SDzkV4C6RN+/zvGHZ72kyBxXXRoGzvebBVTKKKgJEWszGJjJ sUEidQD3hu+OYenU4fLm2GyfMPVMrhs6/lVfjwXVs0jP+WVuTwSbf6MraXszR7uL4D6bmnLMbXzz sydX0MzWUOLVFG9BY4RiqpKdu9KTpWa4twQchODnKTjAs7V27qWxRdcbK+mnfIRIlnoLhNRyLZE4 y0EK7ZqZwPQU0XQor9BDqmA+zNutmd19gb+ilpuchO41/NS+C6uFX9XKknT1lHFH2kzRPuB2Z7m9 sLknrWQu2bSdFeSU7DrLDH62DlBOb+WEnG5RqsE3Q1NzsQ6wGASXeHz8Rfjv/rb+4yz50V5Lfgnq X9h+82TZTxB/iJ0n/E/umYM3+dr9tuN/UhQ/y9N5xTxH/CqX7Xd/VtnNPOf8bV+xWf1rhE1rLX1h 2xsWjaxqiBXFl2BbICnwhFAU9AsjYZRKLTUVFIDCRBIyveqfp0KQBMPsDNi9d1jJbe0W/n8y6Wsv blcl74YRcnT3bpRL1fA1N0HQ9S3NrmX03JpSv5q7C1bTdE53JKMaujoqtVdHRcaMs/eZq8wXHPhV pjiTQjCxY3RSuVVJoYAWV+zDScexcmBQ/XvK4WlPos3qG6+oBVevUeuaEeL+k5ze/dLPbkznxSs4 515fXZlyXBeyh1VT0rH6D008y9YyHbrsxpezshVQv9OFGsVcvk4waxPmpu67MlJ1csE/WrPe7ASU 8iXh2Y2owKzWz6lQkbf6hkweSy+1NGC4iZUxUWg9fep5i2eAiQPb2vSD0/gz5OjSXZXyall1SGVv 3un7RVnM0lBVf5tqbhif/wBN8fU+vuGM/IPwzhnJ4rueyVhXW2sdx38lihdlht87mYsq44RS/po/ D+aRU+CX9tuS/UhfPy9CZsF5cfhVH9rtfq3DWbwY/G1/sV79a2YQ8wf4i/Ij/VJ9xlYzlfjT+Cem /wBv+83jhfl9/ETq3+G/dMuTO80fwOdPfqQ4c/k2t5q/2t/iwzv7Xn/1rpuR3p/gh079i0z9Syeg 8eA1Phz4qJ7kylViO7fPVrYe2LIRygo1eWeSgp6Qqtaj1HAJiunGnRbtxIIAYifvKyxAH1DCbF71 LUu5vkLb0B3aWbc7VmFHVQU4QuXppVo51cq8m8EYvkqV+Od3Ru0HipmN2Ry//wAq9G/eniVJXJWr tyxloOSWJWXhjKPNRV2dyK+N1wR46vLfvzkByjr2lN3x9EeVzZ6NoSrj+sQTiuO6jYIeCdWpukUx 3Ln3piuizUagRbuW9Q6ZvV6FOB+Wd7PHHZ2zu39zVdJlejdyuDGpyxq5GUowb5LDJOSlVUjRSWHi muGeO/lp3E353VsaLrasTy+e6ii4Q6crU4wlcgk03ig1B28Mk51lGXU+GSnrH53wAeb2nwEAEB49 6/AQEOoCA7cuAfw5z/xA/C3N/t1z+4y51J/qFtrufY/6TD+/zZvX54bXYKHT+J94qckpD2qm7nlL XWpdFNBZaKsFdi2kuyckI6IokcyDlEhwA5RKIh7QEPZnUXiHp+T1fUNXymZjjtXstGE4utJRm5Rk uFHxTa4OpsD546pqGh5HQM7lJu3fy+auXLc1SsZwVuUZKqarGSTVU1w4o2Bq3LHd8r4jXXKx5ZWB 93pa3uMwS0krsEmzCXhtlvqkg5+jit/o7vK1QIIk9H0xP7e3p7M4fqPbnaeW8k1t2Fp/YHetrBjn XDKxG444646Ym+OKtPX1OXbf7vdwNR8NZ7ru5lfeqtZhdZW7a+K3nLmXjPp4OliwRTa6eBy44KcC Izxd722lyV8mcDtPc9kLcLs51Zdo36VGIhYZFswia2DFBJBtAt2zVApEzn6iRMBMJjCYREwiOx/f 7aW39jdh7un6Xa6FhZi28OKUquU6tuU3KT405t0okuCRqn4vby3R3D8mctqet5h5vNSy95O5KNuP CNmUY0jbhCEaR4fDGNaturk2/f8AOXTUHvrzO621NYEiDXLojqUbYgRRVqpKV2Erys7It/VaiVQi rpgxOgRQB7iiYBAfYGfH7TbozWz/ABfzGo2X9ZY6+D1pOU8MHR8GozkpNcnx9z7/AHz2Xk9++ZVj SLyStZqWVV3i4uVuNqMriUotSUpW4OMZJ1i6P0N0vKh5Ftj8KbLq3RHHuApsBJPqCzuMjKytfTfx sFUwl3VUio2KYIHQZtyFNFOAU7iGAqYJlTKX2jnVnj52T0PunkM3rGtXLt2MbztqKm05TwxnOc5c ZOuONKNVeJyqd3eUvkPubstq2S29tyzZy/8A8aN1zduLjC3jlatWrUKqEVHpSxJwaUXBQw0Z7zX1 6ZeVPxm7HfbQqUE32FFtb7BgrEMlG8bF7YocIWyQ0tFg/VXXbFVSdtQcEBb5xTro93pnEM+TrOkX fHrvxlYafem8tcdqVJOrlYuycLkJ0SUqOMnF04NQlTEj6mg7hy3lh4zahPU8vbeeyrvQTjFxjHNW bUb1m5aq5SjihdtxuUl8SldhwhJowF8Pf/ok5E/rGqP6MrZy/wAzf8w6b/U3P10cN/0+f8u6z/XW P1Lhgiqeb7ds7y5iIJet0dPjzP7RZ0ZCvDBSBLZH02UsxYNGWM/TcqKHlkUDlXUS9MUDj3JlTKIg cvMNR8UNq5PtzO4rl16lbsO454lgdyMMThhol02/hTriXCTk+KfXmhecu9tW7n2ZdOx9z38xGCt9 Nq5GxOaUbjnicnejBqUl8jdYqEapr9PxB+uqzF2/jjtOOj0mtrt8NsOn2d8l8wZWMpbiHkosTlIA AKrcZd2QVB6mMQSF+QhQC14Za1n8xpWp6fOVbNidq5Bfou6rinx9n04unJOr5tl7/UF0LSMjurRt Qtwpmc5ZzELkq8JRy0rDt1jyxL7RNOXNxUYt0hFKPrw+fiL8d/8AW39xlnzuTyW/BPUv7D95snRv iD/ETpP+J/dMwXic8nz2+GAMAYAwBgDAGAQ88wfxffDR+ZHk0+52j4K18j/ITDYKBgDAGAMAYAwC Dz4gzg295teO3YKdNiTSu3uPLz7fNatWqPqSU0nUotw3sEOj6YGVUPIQC7o6DcgCKzxBsXp16CAu W5YZnLMyDLGAMAYAwC078Ir+JHuz9yDZH3861wi1e+Q6LOSYpg/k3+zbyD/Uftj9A3+CVzOLzkGc MAYAwBgGf+K3HS+ct+RenONutGpnNx3BeYeoR6wpHWbwzByoLqRlXIJdTAyh41Jw+dCUBEqKJxAB EOmCJNRVTsYad1VT9F6m1npbX7E0bRtTUKpa5qLI5gUWQrtMgkK+0BU4AHqLCg3KKig+05xEw+0R yTCbqzI+CBgHGw50fttcxP3p+Qf3tS+QZ0flRfq+FB/C+sH70+2P0Pq2SY175yzLgtHPG+LW05pX XvMfRWwKBGQNf2luXUc5YNzRUK2QYrTatetAQULYXybcABR7JJA7ZnXEO5QrEvcIiXrkMybLeE0R +G3kpNj5kuJ7Vg5XQazMdyBjZpJL/q3kYlxrt8wRNX2D8wHjRBQPk+cQuCq78jOo6/fsYti8k5N4 1jo2OauH8hIP3CLRixYtERcKrLKuBKmkkkmUTHOYQAoAIiPTJMQ5CflE5kyHPPnNvvkaLp4pULDb Fa3qlg7MuUIjUlLIFbgEyorD0bKO2SAPXSRfZ704WN7RMIjBmwjhjQ2kn/E3bojwv1PyZg3kxscl viQTmYMTrFZs+Nko5S1nFzB0FC9Sufro2OUBKAAdo7TU69ChgjH9ZQ1P8ZXMeU4G83tDckm7p8nV 6rbW8LtGPYlOupN6ltofV6xN/QKBgcKpx653LYggPRyikYOhigICZxxRodfGHl4uwxEVPwb9rKws 5HMZeHlGCxHDGSi5JsV63cIqJiJVElkjlOQwewQEByTCPO7GhJeza9vlbr780VPWCmWiEhJMoJmN HS8rCLsGy4Ar8wRRWUKf53s9ntwDipz8DNVWem6vY4x5C2Gty8lAz0NIonbSETNQ7w8e6bLpqfOT WQXTMQ5R9oGAQyDPL8vhQ8+PAelcRNE8SuQ1jJxl2LpipJUJvNzkDKL6nvjdg9UWRk05aARdFjJB +VUy78JEiCQuPUMRY/eUoDGuW5YqotQ6o31o7fEOWw6R3Hq3b8GZIq4y2sr9Vb0wTTMIB1OrWXTk qYgJgAQMICA+wfbklppoqocxfhTY7kjyz3PvXWfKOs6I1rty8OL0jrhDSb65u6hK2Fii/mgbnQs0 O1VQdTZnblBAhESIpKlSL7CAIxQvRvUjQlS8N/h5kfEq25BxxuTR+QUTvVfWL1GPPqFTVidMkddp z6Cqyf8A+K7IR4aTSmkyqfMREnuxPafr0LJROeMm2wWyLHzcfhQc5/1ISn5ZZYKofOjkr5BmnaG4 yfs28fP1H6n/AEDYZJgvmZwwQQ8+fr8ILmx+ZFG++KuYK7fzo5R+QZh2vtZf6NtffmPU/wAgt8kw XzPcYIGAMA57vxfP7bfGf91hD727JkMybHJmEPhQfxQZ/wDdY2x+mFWwTe+Q6SOSYowDiE5BnnUB +GY/CC0J+fG9/vimMIxLvzkWPxjH+jfgf+e+/PyDVclldjmyul4BvxfeE/58Xn7nbHkF258jOrhk mGMA5Fnl/Yaai/JlzLj9AJVdDVjXcconDNqUDItUaTn0Y0NPosCxoA2Tbo2EXxCkRAEydO0gdoBk GbbrgRZV+DijLUVXn7MgY6VIWJxvjBIqQfSe2pqa7OgFAwpiAGatFh9cAOX/AK5LqBvYJCLV/wBC 79kmOMAYB/mqkkukogummsismdJZFUhVElUlCiQxTFOAgYpgHoID8uVRlKEk06NFM4QuQcZJNNUa fJr2ZGfyI8SfDTkB75Ko0M2n7k5AT/WrUJmlWRWWDvOAuYcyKsIuB1D9yqhWqa5/k9UM732V5H9z 9nUtyzH22wvzL9ZtcuVyquLgqJOTiv0TWDuF4hdmd9t3bWWem5h/n5WluLpWilZadmjbrJxhC5Ki TnwKn3OPiRIcLN5uNOPbsz2AgrV4W3xNkawq1eWXi5tdy0Km4ZquHZUHCarRQBAi6hRL2m6gIiUv ol2o7j2O6W0lqcLDy76krcoOSnSUaPhJKNU1Jc4xdaqnq/KfvT2nz3ZjfEtGv5iGb+rhcjcjFwxR nVfFBuWCSlGSopzVKPFVtLNHiBVSR8ivHY6yiaRBU2skBlDlIUVV9IWVAhQEwgHcc5gKUP4READ2 5xXyUjKXZTUklX+Y/wBmZst/7DnPiHOFvyI0lyaSrmFx93lL6S/K+C+k3Y86vH3cTjd7PkUzo8pI aYZa0o9RlbywUZPI+DsKdjkkAQfIoKi6ZkUO8bkTXVSKic6pCFOKg9udW+JO8tsx2nLRJX4xzrv3 LitOqcoYIOsW1hlTDJuKbklFtqiqdyedGw93/wD95HcEcrOenfZ7Vp3orFGE1K5wuJNytp1ilOaU JSlGCk5tRMb+CrQpNjcn7FuSVaJrwWhKmZ1HmUEDB9fNgJOa7HdUzlEpyJRqUkr169SKlSMHt6CH 2/Lbd70PYFvTLbpc1C5R/wBVapOfH0bm7a+mLkjjfg3sSO5e6tzVrqTtaTZxLj/TX8Vu1WNOKwK9 JPhScItfRKHvrzfac0luTY2om+o7teT64s7+oSFnip+DjI9/OQggzkE0kXqZ1AK0fFWb9wj88U+4 PYIZ0HtDxR3LurbGW1KWctWPtNtXFBwlJqMuMG2ml8UaSp6Vo+KNnd9+cO1dm7xzmk29OvZpZO9K 07iuRgpTtvDcpGUG6RmpRTq1JLEuDRnbhD5RtY83Nh2jV8Jr6y6+sUHUFbgzTsctESjafi2ko3iH aaQsSkEqyBniJuwQHuIJh9gEHOId1+wGvdqdEtahdzMMzbnd6bwRlFxk4uUW6t8Hharwo6L1Oedj /KXbve3ct7SbeTuZS7bsu7HHOM4zjGUYyXBRpJY4tLjWOJ8MLIueFmtIPiP5mNnaXfmTiYewwOxo 3VSZSmBmvB21qy2jDtAVUAhRMhEN1GxjAHQXCQkD2iAZsB3S13N9yPGHK6rD4525WZXvfFBys3JU 487jUkv0HV8DVjsnt7I9ovMjN6Fd+CFxX7eX5tYLkY5mzFyaXFWVhb5O6sCq2fL8o/jl5Wbd5mWj a2ntbO9i1DbrGii2koqWrkejWpqt0thR3DSR+mnrYzYnbFkcg5UAqAlWAoHE5TAF/sB3t7d7c7X2 tO1PNLLXsm7tVKM3jjO5K4pQwxeL53HCqyrFulGmWvKPx67s7q7z5jVdIyMs7l8/Gy4ShK2lCULM LUoXMc44H9Xjxyw22pxSk5KSW9/km1/I6n8RMPqyYeNJCW1pTuNOv5R/H+r7g+kaa/hK6ush65SH 9FVVsYxO4oD2iHUAHOouxus2NxeSNzULScYZq7nLsU+aVxXJpOnCqT4/Sd8+SGgZzaniLY0vMSjK 7k7OQszca4XK10oScapPC3FtVSdOaR87hVBk5d+Hh3o6s2FmW7I0vZmqFzPVCpNYa3xtneWSEbPD IJnMm1VZOI8VFCpmMCSgiAGMHtyO6ecfbfyZjq1+2+g7lm8qcXK24RhdlGrVZKSuUVUqpLgmfL7I 6ZLu14b3NAy9+Ms3GGZscfhUbqvTv2ISaTpDpysxlJJvC26OSNEfGF42uU2t+YVO2pujWL3XVJ1E FtfOns1MQDgbDYX9Wd1lk1jiwb1wo5IVZ+DkzkgC3EiJiCfuMUo9t9+++Pb7W+2d/T9LzSzN/OYE lGMvhgpxnKU8UUo8I4cLpOsk6UTa6T8ZPHPupt/vHltT1nISymVyHVlKU5Q+KbtyhCFvBNufxTU8 cU7eGEk54nFS8d53v239P/u+a/8Avct+fV8Qfwtzf7dc/uMucY/1DPxPsf8ASYf3+bNyfiEP9EnH b9Y1u/RlHOr/AAy/zDqX9Tb/AF2d5f6g3+XdG/rr/wCpbMmcbNdWvdvg/jdZa2ZN5662nW+0IWBi DSDGOB9MtdzzLz3UV5FRJuiqoCQlKKpyE6iHUwAPXPib71zTdq+WEs/npO3YtXrEpSo3SLy1tVok 20q8aJvnRN8D6najaut7y8FFpWnwVzNX4ZxQhijHE/vC/cUayainKK4YmlxVWlxIyfEzqbY+kfJP G652vUJakXWF1vfVJCBmU0iuE0H1eSdoqpqNjqILoqpmAxFEjmIP8A+wc738itxaJursZPO6dejf sTvWqSjy4To1xo00+aaTRrr4p7X3Bs3yVs6dqlieWzNqzfxQmuKrZbT4VTTTTTTaa5Mz3y/2ZX9P +bvUGwLW7bR9biS6ojpyUerJtmMPG2muOakq9cKKmKVNuyK+FdUwj7CEEfb8mcQ7a6DnNzeKebyW XTldn13GKVXKUJqail6uTjhS92c47wbp0/ZfmzlNSzcowsWpZVXJSaUYQuWlblck3RKNuM3OT9os zN5muCO/eQmytabw0dUHGx28Zrtvre0V2GeRaM5ElirRIWNk9TRkXCIvEHQzKqZwQAxk/SAxg7Td S8W8YO7mztmaDmtJ1a8stKV93oTkpYZYoQhKLaTwuPTTWKiliouKo+c+ZfYzuFv7deU13RLDztuO VjYnbhhxwcLtycZpOSc4z61KRTwYG3wlw2H4taysfjm8ZG2ZPeC8VBXAsbsnZ8nX1JNm9bRNks9b aVWEghcsROgs9eOGjREQSOcnrriQpzAHdnDO4Gv5Hvd36yVvSlK5YUrNlTUWnKEJyuXLuF0ajFSm +KTwxq0nwOcdrto6n42eMerZjWHC3mrqv5l25STUbtyzbsWLGKNU5Tlbtp0xJTuNJtIwD8Pf/ok5 E/rGqP6MrZy/zN/zDpv9Tc/XRwz/AE+f8u6z/XWP1LhW31z/AKdaJ+tmsfpghm82u/5YzH9RP9Rn mRsj/wDIaf8A8dn/AM4lhb4h3/8AUvE7/wDam6f/AJSrZpd4Wfz2sfyZb/nnof8A6iP/AOS25/wa h+tkCL7w+fiL8d/9bf3GWfO+vJb8E9S/sP3mya8eIP8AETpP+J/dMwXic8nz2+GAMAYAwBgDAGAQ 88wfxffDR+ZHk0+52j4K18j/ACEw2CgYAwBgDAGAMAYBy9viAPGC98f3LWSvOu66q14u8jZOaumq 3DFt0iKJaVFgfTlQOZMxvRCPXW94jinAoHZKkIQVDt1xCDLtTxL6SBLBcGAMAYBad+EV/Ej3Z+5B sj7+da4RavfIdFnJMUwfyb/Zt5B/qP2x+gb/AASuZxecgzhgDAGAMAv1/C1+L55qmgSPkQ3RXlGd 529AK1vjlCyrMyLyu6mfHA8hZRI7KBiL2cxCJMDlAogwIZQpjpvQ7SMe9OroXC8ksDAGAcbDnR+2 1zE/en5B/e1L5BnR+VEiHj489PL/AMbOh3nHnRmuONtrpb2/2HYysptin7PnbQWbssbHxa6RV6fc YJoDUicckKZRbCcDCbqcQEABUolbjJ1NyLJ8Wl5M5yJcxsXrzh9TXi5TAlP1vV20nUszEUzE6pkt 95lWAiAiBg9RscOoB/B1AVSOjAr08guRG6eVO2LRvDkDsGc2btC4roqzlonTNU1DItEQbN2rVtHJ oM2DFqkUCINWySaKRQ6EIAYLiSiuBcX+Fj8X+xKraJjyNbrrMhU4V/TZWjcaK/PMFGcvZGtq9Mkv cCpOikVbxwsUxYRqn/6URw4UAASKidUixemnwJdfiRebIcS/HXb6HWZcrDavLF460ZU0UFjJyDOj yEeLu4yRQIZM3opQpvo4TlN3EWkETdBAB6SUWo4pfyHN84z6FuPKLkFpvjvQUTKWzcexKvQotf0V F0Ios9JptXMg4Kl1MDSNaiq7cG/wUkjG/gyDKboqnXisXETT1g4dSXB8YUrPSTzQhuPDOMTIRV1F 01GlhSmq6Rh7R9/aJkI4TX6gcFyAoAgb25JhVeKpyAd6acunHnc209FbFZFYXnUd9tOvbQ3T7xbG l6rMKxCqqBjgAqNXApeqgoAdDpmKYPYIZBnJpqp0ePhnubo8p/HzC6htU0aR2pxAkGOn5gjtcqkg 91au1UfUt6JS/wAVuhGpLQ6QfKP0aJje03UZMW7Gkv5SxRgtFRrzU/DkyfLHZFr5a8JZGs17dFyX NMbY0vZ3jeuVXZVjP2lWmoaSEnu8ZOPR6nepOxK3dKdVhVRVFT1oL0LuFUZSQ5D8JuXPE2TdRnI7 jntzUINXh2BJu20yXb06TcEVBAfo+eapqwsmmJxAoKNHSpBEfYYcGQpRlyNeK9ZLFUZhjYqpPzVY sEYqC8bOV6UfQsxHrgHTvQcxqiS6R/8AnKYBwTzJpuH3xCnkv4my0U3kd0yPJDXLU7ZKR13yIcvr 8dywQL6PYzsTpQLLHqkSEQS7Xp0CmAonRUAvbgtytQkdCnxr+STRnk20EjujUBH1an4F83re19UW B4yd2rWVxOzB37uqoz7Svox4UDKR0gVNMrlMpuqaSyayCUmNOLg6EhmCkix83H4UHOf9SEp+WWWC qHzo5K+QZp2huMn7NvHz9R+p/wBA2GSYL5mcMEEPPn6/CC5sfmRRvvirmCu386OUfkGYe2LsvYxC lIS/3YhCFApCFtU6UpSlDoAAAL9AAAwRRH9fabsj/wDMG7/52T3/AGjAoh9puyP/AMwbv/nZPf8A aMCiOylxpVVX45aAWWUUWWW0nqpVVVU5lFVVVKIwOYxjH6iYxhHqIj8uSYT5lEn4vn9tvjP+6wh9 7dkyGZFjkzCHwoP4oM/+6xtj9MKtgm98h0kckxRgHEJyDPOoD8Mx+EFoT8+N7/fFMYRiXfnIsfjG P9G/A/8APffn5BquSyuxzZSi0ju7afHDadQ3ZpO3vKFtKhPHkhUbdHs4qQeQryQinEGsciM43dNT idq6VTEFEjB0N1D29BCDIaTRJh/b8+X3+uxeP8xtO/zcwUdOHsYt2X5lvKRtyElq5dubu8VIScZm jpePq08y12k/j1ETN1EFB142ijiiumcxFiAPaqUehwMGArcF6HwOI3ih5882LLDQ+leOt9TrUq5Q TdbYv8FL0HUMGyVMPe6cT1gbpt3BESAJzIMQcuTB7E0TmECiJlOMTpmeLvx4UDxncU61x8qUqW3W p5JvLxtzYp2JY5a+bImmqDV04SR6mM3jmbdsizYomMIlQSKY4mVOoc0mJOTm6kiuCkYAwBgDAKcv na/bbjf1IUP8vTeemviP+FUv2u7+rbPHXzn/ABtX7FZ/WuEQNUtVio1mgLlUJh9XrTVpiPn69ORi woP4mYinRXrdwkcOvQ6SpAMHUBAf4QEM2U1DIZLVcjcy2Zgrlq7FxnF8VKMlRp/Q06Goen6hndJ1 C1m8tN271icbkJrg4zhJSjJP0cZJNP0aN4N5+Tfl9yL1NIaX2neoKVpc4tDLWMsbSaxBSdiGBlUZ 1sVytFN0ykIR63RWErciQCZMoD83qUeqdp9h+2uydxR1TT8vKF+2pYK3JyUMUXF0UpP81uPxOXBv 14ndW9fJPvD3C2rLRtWzsbuWuOLuJWbMJXMElOOJwhGiUoxlSKjVxVeFU8T8ZuZ3IPiIe7m0Zb2d bLsGPj2diQka9B2Nqo5hgcgxeJJziC5E3TP3xbsHoJDd4goQ4AAByLffbDZnciNhavZd37PJuFJy g6Spii3FqsZYY19VTg0cT7cd3t/9pbuZnoOZWXlm4Rjcrbt3K4MXTl9ZCSrBzm4+nxPEmjWWSkpC ZkX8vLPXUlKSr11JSUi9WUcvH8g+XM6WWWUVETqKqqGExjGERERERzndmzZy1mNu3FRjFJJJUSS4 JJLkkuCR1xdu3r91zuSlOUm25SblJt8W23Vtt8W222+LMlaR3bsjjvsuu7b1PPfVy7Vg70I98oyZ SbRZrJsVIx03cNpEiiC6DhuqchimL1DqBiiU5SmD4e6tq6HvTQrum6jb6ti7Sqq4uqalFppppppN Uf0OqbT5Hs7eG4tg7ks6tpV3o5rLtuMqRkvii4STjJOLUoycWmvWqo0mvubY5I7m3RuZxv8Au91k DbUNIQslG2WB7K0tW1q0RJONCMLCgiDEGIIkFIyfQ/eAqGMZQxjji7d2Ttja+2Fo+UsRWUUZRcJf GpqdcePFXFiq614U+FJRSSyd1793bvXds9d1DMzlnZThNXI/VuDt4en0+nh6fTwxwOFJKSxtubcn vsXzYc8yVEtZC5UQ0oVqDb69m13BGtwiBOz1RKP/ANzir/z+4dOvt6Z0+/FjtA9S6/Qu4K16XVn0 /wCT/wByn/rO/P8AvP79rR/sv2uzj/8Ae6Fvq/q9L6K9Kv5eJrBtPn7yt3VpeO0Ls3aLy2UFlIoS b0ZKMilbNYnDJ8Mk1CTlTI+/PCtVx7ydynUwgUTicSk7efbf7P8Abza+6JaxkMpGzmJRaWFyUIJq ksFuuCOJcHRcONKVderNy98u6u79n29C1LULmYyduWJqajKc2nWLuXXHq3MLq1im6t1licYYfE8a eW++eJNnk7RpG6KV08+1bsrNAv2TSbq1mbM1DKoA8YyJTpGWbmOf0V0+xZMDnKQ4FUOBvq767c7R 7jafHL6tY6qttuEk3GcG+DwyVHR8KxdYuibTcU18jtz3S3z2o1eed0PMuxO7FRuRaU7dyKdYqcJJ xbi28MqKcFKahKKnKu2Wx/MXzr2E6rjhvsaE16hW5qPn0o/XdWYRLOXkYxQVEiyIzJpBd6zHuEFG aigtlfZ6iZhKUQ660Pxn7R6JbuJ5WWZd2Li3dm5OKfPBhwqMvaaWOP5slVnam6fLjvtue5alHPrJ qzNTSy9uME5x+VzxKbuR48bU3KzPhjtyoqaZciOSm3uUuxx2nuOxpz1rSh46vRp2Mezho6FgopdZ 4g0Zt48pCpJFcOVlh+UwqKGMIiI52fsrY22+3+ifd+l2unZxObq3JylKicpN8W6JL2SSS5HT/cLu Hu3ulrz1LW732i84K2vhjGMYJtqEYxSiopyk+XFybbbbZ7jkjza5Gcsomiwm77q3ssbr1F39BN2V fhIEHElIIJNXD94MOgiLp4smgQvcb5hA69hCCc4m+VsftZsnt1fzF3SbDtSzLWJuUpcFVqMcTeGK bfLi+FW6Rp9juJ3i7i91beVhrubeYjk4yVtKEIKssOKcsEY45yUYqsq4UngUcc8X2eM/PnlDxKip Ot6bv6UdUZiSVmZCnz8DDWWvnmVmpGRnSJJRE67RY6aZAOLdVMFOwveBu0OmLvrtBsHuNmIX9Uy+ O9COFXIylCeGtcLcWlJVbpiTpV0pUzO2/fHud2msXLGh5zo2Ls8c7UoW7kJTwqOKk4ycZUUauDi5 YYqVVFI/O7538mnvJdhy1cXtE+5YxuEawkfoKHCvtq99EqwYxZYz0fdPcDNV1CiXt7xOYVe/1v5T LlvtJsO1sWW3I5emSlxccUsTliUseOuLFiSda0olGmD4SzPvT3Ku9yI7snnHLUoP4ZuEMMYYHb6a t4emrfTbjRRq6u427rdx4W3hu3YvIrZ9m2/tWZSnbva1GAybxrHsolkk2io1GGaN0G0eRNJFFu1b pplAA7jdO44mOYxh5RtXa2i7L0G1punw6diynhTbk6yk5Sbbbbbk236caJJJJcR3ju/X9+7mzGsa pcV3NZlpzkoxinhjGEUoxSilGEYxXCrUU5Nyq3uhoryz80tCVNhRoS+Q95qkM0TYwEZs6AJaXEEy R6gRFB+gs0kzopl6ETSWcqESIUCplKUOmdXbu8de1u8dRlm72XlYvTdZSsywYn7uNJQq+bainJtu TbO5Ng+U/ebt5pUMhls3HMZa3HDCF+CudNVfCM/hu4UnSMHNwhFKMIxSoYS5Oc6OS/LoY9nue/Gk axDyCkrC0avxjCt06MkToi2Bf3WNIU7xwmmc5Ulnii6qZTnKQxSnMA8q2H2m2L23UpaXl8F2ccMr km53JKtaYpP4U3RuMFGLaTabSOF9y+9Xcju3OC1vNu7atTc7dqMY27UJNUqoQSxSSbUZ3HOcVKUV JKTT/Fxs5s8jOJcfeYrR92QrUfsBu0LONX8DCWFBCSjklUG79oWbQWK2eoprHL3FASHAQ9Qp+wnb d3x2s2T3Gu2J6tY6ssu3halKDo6VjLC1WLaTo+K/Naq62e3XePuL2pt5mGhZt5eObilNOEJqsa4Z xVyMsM4qUlVcGn8Slhjh1eZyUhHyTWYZPHLaVYvkJJpIJKnK7byDZcHSaxVOvcChFCgYDdevX25z +5ZtXrLtzScZKjT5NPg1T2odYW62KdNuGGlHFuLVOWFqjTXo1Rr0NmeTXM7kFy8VpCm87cysZdfR 8kyriEbXYOuNkXE37t787VThEESqOnnuaHePQCF7ABMhAEQHgexO2Gze28b60iy7X2iSc6zlNtRr hinJuijilT1deLZ2X3H7vdwO7NzLT17MrMvKQlG3S3bt0x4epKluEU5TwQcvT4VhUVwNh/D5+Ivx 3/1t/cZZ84V5LfgnqX9h+82TsnxB/iJ0n/E/umYLxOeT57fDAGAMAYAwBgDAIeeYP4vvho/Mjyaf c7R8Fa+R/kJhsFAwBgDAGAMAYAwDVPmrw605zw46X3jbu6IK+q1xZg4h5xsiiewUK5x6RxjJ+JVV D+QkY5Y4iX2gVVIyiCgGRVUIYTGTi6nKP5+8C95eOzkNZ9BbsiFRM0VcSevr+zYrt6ptWhqOjIs5 qKUUMoXsVKXtcthUMo1XA6Knzi9RgzIyUlU0lwVDAGAWnfhFfxI92fuQbI+/nWuEWr3yHRZyTFMH 8m/2beQf6j9sfoG/wSuZxecgzhgDAGAWNvAv4V57yCbIZcgt8wkhDcNtYWFAzxF43eMV+QVsjFjH NX4tUOz/AO5mayZQmXpDdeg+6oj6p1FGwtXLmFUXM6WkdHR8RHsYmJYs4uKi2bWOjIyOaoMo+Oj2 SBWyKCCLYpU0UUUygQhCABSlAAAAAMkxT9mAMAYBxsOdH7bXMT96fkH97UvkGdH5UWWPBl4MuFnk V4WSu/t/Su7md6Z7uvWvUUde3qv1yBGBrlfhJNuYzeThJBQXAqSCvef1egh2/NDp7ZLNy5KMqImS /uoPi+//AIg5T/0sU/8Amtgo60zcnjz8P74q+N9pjLzW+NbPYNwhXIO4iY3VabLtJjHOSKCqRQkN YnBq8dZEwlMkqowMomYpTEMUwdRFLuTZM0UpSFKQhSkIQoFIQoAUpSlDoAAAewAAMFBzCfiQ+av+ 1n5F7nR6zLmkNWcUmbjRdTTRUSOwdXWMfC6uEgT0hOAqKTYDH94GEDosUjAACI5Bl2o0j/KQ1cfe Q24+LG1K/u7Qd0X15tSqITDeuXFnD16afwydgh14B4KCVnaPWxDrsnKqIn9LuApzAAh1HBW0pLiS O/2/Pl9/rsXj/MbTv83MFPTh7EbO+d97a5O7VtG796W9W+7Tupoo9qt7mIr8I8m1YSFb15sosjWW jJoKibJoikJwSAxgIAmER6jgrSSXAll+Hx5vf7F/kX1ohZZf6N1JyN9Dj/sv3lf0oyPWuEoh9XZZ X1RBFL6NsJGpVXB+gItFnI9QATYLd2OKJ0gecHLeo8FeL2z+VN8pt2vtP1UlVl52t69bw7q0uW1q usbR01kSTrtk39FqvJprODGVDsRKc3QemSYsVidCshYPjDdEN3qSVT4W7ZmGBniyaruy7TqFXcJM AcEIkqCETGTIGUMkJjHT9ToUQAoGMA9wRUvdB+5b6gJ6rbEp8JZ6++jLVSb1Wo2ehJJAE30NZKtZ oskg2XICpRKs1eNFynDuDoYhvaHtySwR87/8PHjN5Lt5D7TuHOmkJiRTcevbdc10NQ3IztcBEHKk nq48Q6drpnHuAXJlSiIdDFMXqURUpyXqc9jzieMCo+L3lDV6Bq+8TV01JtqhfaLRErerHLXipA2n XNfexUitFpNkHyaSqBVWzsqCInIp6ZiCdEyikGTbnjRuz8J7tez07yO2/WTF2uapbi493dtY4gVj lZGmaJMxtqi5ESF6AdyzTB42TEfYBHavs6iAgRF5fCdHnJMUix83H4UHOf8AUhKflllgqh86OSvk GadobjJ+zbx8/Ufqf9A2GSYL5mcMEEPPn6/CC5sfmRRvvirmCu386OUfkGYdr7WX+jbX35j1P8gt 8kwXzPcYIGAMAoA/GB1p015V8SrgcVfcp3j5ZK03AWxioA6qmx3UosJVu4QUOJJpLuJ2h2B0HqPd 7IZkWOTNO/haLlGVfytVyGkF2qDjYeidxU2IK5ceio4k2rRjexTRDoIKKi2hFh7OofNAw9eodBFV 75DphZJinzJuYj69DS8/LuCtImDjH8xJujAIlbR8Y1O9WUEC+0QImQw/+jAOI5kGedTX4cavlgfD jxHMdkdk9nT70sD/ANRRU5nZn3Iu2pNl+hzGKQqkek37QL0Dp0EQ7hERkxLvzsh9+MY/0b8D/wA9 9+fkGq4ZXY5srQ+EXXev9seU7iFr3adGp2yqDZbjcmtjo9/rMLcqfYGzXVU/IpJvYyxIOWTsibhF NUpVUzAByFMHtAByC7cbUGdDfkL4NvF3yHpNiqb/AIjal1PKTTFdGLvehKjB6dttTlBZg1QesvqS g1j1TtxKU/oO2q7ZQ3UVEj9xusmMrk0+ZzYPIvwE2744eTVs487VJ9Ks25CWPWewmbJdnBbP1zJu FEmMs0KsJvSVAyR27xv3GFu6SUTAxygVQ8GVGSmqk8Xgo8/mxdFX+kcSOa+w5C7cdLa8j6jrzbd5 lV39k0LMOTe5x7d/JvvUWd1FZUxG5/elB+jSiVQihGqZ0wFu5bTVUdCUpinKU5DFOQ5QMQ5RAxTF MHUBAQ9ggIZJjH9YAwBgDAGAU5fO1+23G/qQof5em89NfEf8Kpftd39W2eOvnP8Ajav2Kz+tcIYs 2gNNxgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgEl3h8/EX47/62/uMs+dFeS34J6l/YfvNk2U8Q f4idJ/xP7pmC8Tnk+e3wwBgDAGAMAYAwCHnmD+L74aPzI8mn3O0fBWvkf5CYbBQMAYAwBgDAGAMA YBpnzm4G8dvIXpGU0hyHqZZaNMZaQptziQbMr5rO0GS9NOVgn6qahmzgOgFWSMUyDhMPTWTOQemC qMnF1RzVvJ34XeV/jRs0lM2iDc7S45PJc7Sm8hKbGOVa6dByr0bNLE1SFVWtyxymAvpODCgsfqDd dbtN2wZULkZkP2CsYBad+EV/Ej3Z+5Bsj7+da4RavfIdFnJMUwfyb/Zt5B/qP2x+gb/BK5nF5yDO GAf6JJKrqpoopqLLLKESSSSIZRVVVQ3YUpSk6iYxhHoAB8uAW0PEP8NNs3fz6s7/AOfsJP6i0UQ7 KZruinIvYDbe2W3aV0n9LlTFJ1VYNbqAGKYSyKxQMBSNiim4MLM7qXBF/wBptNqevKnXKJRK5C0+ l0+Fjq5VarXI5rEQNegYhqVk1Zs2rIpEUG6CJCkIQhQAADJMY9LgDAGAMA42HOj9trmJ+9PyD+9q XyDOj8qL9XwoP4X1g/en2x+h9WyTGvfOWZcFoYBH15SuZTHgZwW33yLK6ao3KDqqlX1OzciiYZPb V2N9XIEpUVinBwRm7X9+cJdPa2bqj7AARAVQjilQ5Dbx5IS8g6kJB08lJWUeLvHr14uu9kJGQeri uoqqouJlFlllDCYxjCJjGHqPURyDNOmn4+vAnwXonDPj5C8n+K+uNl8g3mv420bbs1wZSa86jcbk c9qcRSgtnaaXZAg8LGkEhQAxW4G+UwjkmJK5Jy4M3I/sR/FB/UY0h/8AuuZ/7bgpxz9zTfyCeAzg zsThxvyA4vcWtd6w5CtKM+tGorRS2UsjOr3Onqks7eIICzlZM6c+VoeMU7kzdpXHeUAOUogKo3JK XE5kf8qgr/7RFZFT/wBZNVJVM3/oEpiiH/oyDLOqF49t2VDzG+INrBbSlPpKybD1LceMPIdyHY9l 4zZcPXPqu5mRKYxQB8+brsp9v0MHYZwQOoCX2SYclgmc0/l3xP3Fwn3/AH/jpvCuuoG50aVXRbvT NXKUNca0sucsfOxKy5QB3FSaJPUQVL16D3Jn7VCHIWDLjJSVSbrxdfEi784Faxg+PW4NbocmdG1N MrHXouLg5p2ztawYmKBYxpJOWcm0k4VmUDe6MnCCaiIG9MjkqBE0SC3O0pOpLXePjENVoV58bW3C bYErbDpKJxqV42zXK/Xm65yCUqy6kDFSblYiRhAwolImKgB2+on17gVKFYfuVBOcnOHfHkH3/YOR PIKYjnlqlGLSAr9erzReNp9BpkW4Wcs4WHaulnCyLFso5VUEVVlFVVVDqqHOc5jCL8YqKoi178Jp wDukLLbP8hOxIJ5CVmeqEhpfQZJJA6B7Ui+nm0lZZ9uRXtN7o1UjEI5suACRU53ZQ6Cl1Eixel6F 3nJLBFj5uPwoOc/6kJT8sssFUPnRyV8gzTtDcZP2bePn6j9T/oGwyTBfMzhggh58/X4QXNj8yKN9 8VcwV2/nRyj8gzC5TW/i/wDY9drsBXycF6S6JBQsVDEdG3xOpGcljGKbIFBIFXMBROBOvTqPTr8u KljoL3Pt/wB8Y2T/AFD6P/T5PfzVxUdBe4/vjGyf6h9H/p8nv5q4qOgvcsY+GvyhT3lS0XtHcM/p 6I0y513tlTWqMFD3J5dUJRAlPjLR72Zw9jo0yR+6QFP0wIYOhevd7egSWpwwM0P+KD4D33lfxGoO +dSQLy137iNNW+xzlViWa7ybmtP3tgxSsDhmk1AyjlxDrw7F6ZLt/wDhSuTlHuKBDiq1JRl/Kc73 U21thaM2ZRdw6otEjStka2s0Tb6ZaIoyXvkPPQrortFTscFOiukYS9iqCpDpLJmMmoUxDGKMGU0m i5VoL4wR4wqEXEcmuIB7DdGDFJGSvGmthN4SHsbxMhUxV+gLaxXNHGP0Ex+yTWKJh+aQgdAxUsOx 7M018jvxQe5+XGm7nx947aYT420fYkU9q97vkneT3bZ1gp8mmZs8jmP0fHxjGCSkWxjN3RgF2qZI xipqJibripMbKTqytJqDUexd97QommdSVWTu2ydk2WNqdOrEQl6jyUmJRYEiAJjiCaDdEvcq4XVM VJFIh1FDFTIYwC82kjsK8MuOcdxG4pcfuNMY/Qli6Z1ZUqTJTbVI7dtP2SOjSHlpFNNX5ySchKHc OSkN7Sgp0H5MkwZOrqVVfjGP9G/A/wDPffn5BquGXrHNldLwDfi+8J/z4vP3O2PILtz5GdXDJMMi Z8xPjFpvk44sytCTRioffmtyStv47358BUAhreo1IDmGfOCFMoWDsSaCbd4AdQTUKg57TmblKIrh NwZynb9Q7lq2727W2xK3K0++UOxzFRuNVnGxmcvXrJAPzxjxm4TN/FVQXTMQ3QRD2dQEQ9uQZi4n QZ+Gd8rYcmdNk4Pbxs5XG+tBVtI+qpmYdGGR2jo6JKmwSb+ov7HEtVAMm3UDu9RViKKgFOKLlQBj XYYXUtX5JZGAMAYAwCnL52v22439SFD/AC9N56a+I/4VS/a7v6ts8dfOf8bV+xWf1rhDFm0BpuMA YAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAku8Pn4i/Hf/AFt/cZZ86K8lvwT1L+w/ebJsp4g/xE6T /if3TMF4nPJ89vhgDAGAMAYAwBgEPPMH8X3w0fmR5NPudo+CtfI/yEw2CgYAwBgDAGAMAYAwBgHy pyChLPDSldssNFWGvzbFzGTMFOR7SWhpeNeJCgs3dNX5FEHCCpBEp01CiUwD0EOmAVf+evws3Ebk GtL3viRYl+JGyXfvT1SoNo5zbtEzr85DKgQsUq4Tf131lehRPHrnbIk/iMhH2YLsb0lz4lTvlD4A /KRxcdya0jxymt2U9gZYUb5xxVV25FP26CokMqETEIp2lqmUnQ5jOopIAKPXr803bBfV2DJG/hOK xZKf5Ot8V+216cq08w4SbKSfwljiX8JLslS761sUSrNpNNJZMwCAh0MUMIovcYHQ+yTGMH8m/wBm 3kH+o/bH6Bv8ErmcdLVGhd474mC17SOnNpbfnDKlQGJ1lQbVen6ahgAeh0qy1cmTAAMAiJgAAD2j 7Mgzm0uZPdxH+F58inIB1Gy+7WtQ4ja/dGIq5kdiv2lx2OqxMYSCdnVqY6OYFimD2oyb6PN09ode odVC1K9FcuJcW8e/gp4JePhWEulWpbncu+ooqLgN57fIynJ+IkydFBVr8WiQsTXgIp3eiq3RM9KQ ew7pQPbkliVyUiZnBQMAYAwBgDAKnm5fhP8Aj5uXb+1tvyfLLcsNJbW2TedkyEOxpVJcMYl9ebQ6 s6rZFRwf1DpIKOhIQxvaIAAj7ciheV6SRNv4zPHpTfGbxzfcc6NsOzbNhX2ybNsk9jtkXFREoR9Z oqNilGwJQ4ikKSRY0pim+URMPX5AyS3KTk6khmCkYBFH5VPFnCeVCk6p1reN9XvUNE1japq8K1+l V2BmkrdbX0QECyePTzigdhopmq8TbgmUP/i1e4R+b0FcJuDIo9G/CecW9Qbl1ZteZ5H7a2RHa0v9 Uvi9BnqjS2EDcD1OaRnU49+q0E6oMXSqBSOCkDuOmJigJRHqEUK3ek0WuMksjAGAVVeQfwpPFzeO 8ts7lieRO19YtNqX+z7ANQa7UqdI1+qvrbKqTjpoxUfGKqDMjpdQUUxDomQQIHsKGRQuq9JKhJN4 qPEXXfFSXb8Tr/kNsTbFN3AaryMlULtXK9FR8DZqsDpsnJMTw5zGIs6auxQcl6dFCppCI/yRckpn NzNoubvjm4i+QulM6dyd1YxtTuDI4CnX+FdLVrZlGVcgInGLmY3ouRA5h71Gi4LNFTgUyiJxKUQE RlKPIrHbY+DtpbyVWd6M5vWiuQhnJ/d6/tjT0TdJVBoYREonmKfNQCKqhOnQQCMIBuvX5vToMULq vv1Rg6v/AAdm4HLkSWrnFraGZ+9NyFXr+mLRZnIsTKCCqgpSM9ElBUhegkT9ToYfYJy/LihPXXsS j8SvhVuCWibBCXPfFz2FyxsUGu1eI1y0tY3X2oXb9oqVwRVzAV5R3IPSAoUOrZ1LKtlC9SKpKFEQ xQolek/oLNULCQ1bh4uvV2IjICAg49pEwsHCsGsVDw8XHoFaoNmrZiRNFu3QSKBE00ygUpQAAAAD JLR9PANbeYPG2E5gcZdy8ZrJZZWnwW5ac5p8nZ4Ro0fS0M2cu0XYrIIvxBFQ4CiAdD+z24JTo6lY X+57cbv64m7/APMSh/8ATyKF3ryLbeu6c213r+ja/ZPF5FnRqdWac0kHSaaTl82rMKhCprKFS+aV RUqAGMAewBH2ZJZPY4Bqpzd4q1/m5xY29xZtNrmKPAbeh4aHkrVX2TKRmIdOGtbC1lOgjIiCKhjq MCpiBv8ABMI/LgmLwupWe/ue3G7+uJu//MSh/wDTyKF3ryH9z243f1xN3/5iUP8A6eKDryH9z243 f1xN3/5iUP8A6eKDryH9z243f1xN3/5iUP8A6eKDryJz/Fl4xKJ4s9QbD1BQdoW3akbsLZJ9kvJi 3w8PDPo58ersKx7sknCiKZ0vTYFP3G9vUwh8mSUTm5sk9wUFeTnL8NXwE5f2eZ2VQ0rNxT2lPLuX 81J6ebQ6+uLFMOzgdR4/qkumDRJcwh3G+i3DAqhxMdUFFDCbBcjdlEh3lPg5Lom/cEhefNXeRYGJ 7o4lOOstGvzlMmUxgURaXJ2mUSnESgJVR7gAB+b17Qihc6/0HqKH8HP2S5Vtnc8PXgUToCeNoeg/ dJeQSExvVAH1gtS6LMxQAO0fdF+vUeoB2/OUDv8A0FkPx/8AiK4T+N5k4faD1+8ldmysYWJsO7tk yCFs2lMMB6GUbpOiINmUQ0WMACq3jWrZNXtKKoKCQohJalOUuZJxgoIkfK34k9d+Vmv6Wr+wNuXT VCOlpi7TEW4p0HBzSk0pdmUayVIuE2YoJlQCNKJBJ8vcPX5AwVwm4GhnCL4aDR3CPlPqHlNVuTO1 7xP6hmJmYjarP1GoR0PMKzNUf1QxF1o44rJlIm/MoAl/wigHyZFCqV1yVCzDkloYBAH5Kfh7OMPk Z3qz5ESGw7porYj6uNYDYDjX8DW5SO2K4iBBCPknyMuBBTk27T/FVFymH1UU0SiACn1MLkbkoqhq jx++Fu11xh3VrXkBpznHvKs7L1Tao+21SVChUVZt74yEU1WrtEqxAcx79sdRq8bmHtWbqnTN80w5 FCXdbVKFqrJLQwBgDAGAU5fO1+23G/qQof5em89NfEf8Kpftd39W2eOvnP8Ajav2Kz+tcIYs2gNN xgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgEl3h8/EX47/62/uMs+dFeS34J6l/YfvNk2U8Qf4id J/xP7pmC8Tnk+e3wwBgDAGAMAYAwDD1w0FqW/bf0zvq21P6W2xx9Y7NjdQ2v6dsrH6ostxw7GAsh PcY14jGv/pFpGtk+r1usKPZ1RFMxjCImroZhwQMAYAwBgDAGAMAYAwBgDAGAfmFm0M7TkDNWxn6L ZZmk9FBIXaTRyqmuokVQQ7ypqHSIYxQHoIlAR9oBgH6cA/wdNWz1s4ZPW6Dtm7QVau2jpJNw2dNn CYpKJqJqgJTkOURAxRAQEB6DgH+EbGRsMxbRcPHsYqMZk9JpHRrRuxYtUhMJ+1NFqUiZC9REehQD 2jgH7sAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAw BgDAGAMAYAwBgDAGAMAYAwBgFOXztfttxv6kKH+XpvPTXxH/AAql+13f1bZ46+c/42r9is/rXCGL NoDTcYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYBJd4fPxF+O/8Arb+4yz50V5LfgnqX9h+82TZT xB/iJ0n/ABP7pmC8Tnk+e3wwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMA YAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAM AYAwBgDAGAMAgB8q/jH33yl2u13xpOSp9hXj9fQlRe66mZMazZHbmDlHrsike8kg+ilvWK9+cVy4 agTt9hjdfZuP489+dnbA249I1WN22pXpTV2MccEpRiqSivjVMPDDGda+lDz88q/GfuF3N3ete0N2 b6jl425WJT6d1yhJ0wOS6Uk1Jt47lvDhosVeFZLaWmdsaSsA1bbmurhrqdH1xbsbbAyEP9Iot1hQ MszVdEBF627w6Asgc6Zv4DDm+Ogbn27urJ/aNNzNrM2+FXbkpUbVaSSdYv8A3ZJNeqPM/ce1Nz7P 1B5XVcpeyd7jSN23K22k3FyjiSxQquE41jJcYtppmM8+6fAGAMAYAwBgDAP9mzZw8cINGjdZ06cq poNmzZI67hwuqYCFIQiQCY5zGEAAADqI5TOcLcHKTSS4tvkkSk26LmyUDjt4hOZO+hYSsrTEtJ0t 0Yih7Jtz3uAlVWoLgRT3WCSTUmVFRTETpe8IN0VA6dFgAeudCb18ku2Oz8Vu3f8At19fmWKTVacM V2qtpV4PDKUo/o+hst288S+82/3G7LKfd2Wk/wCczVbTopJPDZo7zdKyg3CNudF9Yk0z1nIjwwcv tK++S9GiI3f9PblVWCQ1uCxLgg3T6AHvFekhB6oscfkTjzvPZ8oh8mfO2V5QdtN1YbebnLT7z4Uv fzbf0XV8KS97nT/kPrdxPDnvFsdyu5SytVy0U3jy9XcSVKKVh0uOTq6Rsq8qLjJPgROy0RKwEm+h Z2MkIWYjHKrOSiZZk5jpOPdom7DpLoPCkVSUIPsMUxQEM2Iy+Yy+bsRu2pKcJKqlFppp8mmuDT90 ar37F7K35WrkXCcJOMotNOMouji0+KaaaafFNUZ8/LxaGAMAYAwBgDAPbUDW2wdrWNtUNZ0m1X+0 PCiohA1CCkrBKCgU4EMqZKMTUMmgmJg71TgBCB7TCAe3Pl6xrejbeyLzOfv28vajzlckoRr7Vk1x foub9D62iaDrm5tRjk9Oy93NX5JtW7UJXJtLm8MU3RV4ulF6livxieKnkjpPfuuOS26VarQGNKQu B2uuvpROyXaUUtNFk6YQXB4IVIxgkQskC/8A8Uqr8wSGSII9Q0n79+Qmxt07OzOhaX1MxK+7dbuH BbjguQuOmKk5P4MPyxjxqpNc/RHxi8Wu5ezN/wCT3LrStZS3lldpZclO9LqWZ2lXBitwjS5i43HN UwuEW6qytmix6VjAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAY AwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMA YAwBgHkrvQaNsuvOqlsWm1e+Vd6dNR3XbhAxdkhXCqPXsOZtLpLIiomIiJDdvUo+0BDPpaTrOr6D nVmcjfuZe7HlO3KUJJPmqxadH6rk/U+Lr+29vbr015PVMrZzdhtN27sI3IVi6xlhmmsUXxi6VT4p pkNHInwV8b9j/SE3o2xWHQ9lXAVUYUBXvGuVlwKZQwe5zK5JRmK6ggAmSfGSSL/EbiAAXNn9leW2 99Ew2tXtQz9pfncLd6nD86KwSovRwUpPnP1NMu4Xgn291+U7+g5i7pl1pUtut6xVVbopNXoubaq+ rKEUvhtejgc5E+LbmTxx97kpvWi+xaa1Koqe86jF7d4VFuggLlRV00QQRmI9FEgfyizpkmiA9QKo bp1zbzZXf/tjvikLOaWWvP8Aor9Lcm26JRbbtzb9IwnKXukaH9wvGbvJ22j1M5kXmbC53sriv21S OKTlSMbtuEUmnO7atxb4JttEeAgICICAgID0EB9ggIZ3QdBppo/5gkYBm3S3G7e3Ima+gtK6st+w XZF02715DRhyV+HUVIKhPpCVfijGRxTgUe0zldMBH2AIj7M4tuje+0tlZXrarm7WWjSqUpfFL/gg qzn/ACRizl+ztgb17g6h9m0XJXs5NNJ4ItxhVNrqXHS3bTo6O5KKb4Vq0TkcdvAPZpQrGd5QbVb1 hqoBFlqBqgEJewekogB/Tczk4gLBoukp1Kcjdm7IYA+ar7eoanb18xNOyzla0DKO9Jf0t+sYc+at xeOSa5OU7bXrE3d7eeA+u5+Mb+588srF/wBDlqTu0ceUrs07UJxlzUYX4NLhLjwne0Bws4xcYkEh 05qOsV6bIidFa5v0FLFe3RFiFKqU0xPmcP00lRIBjIJKER6/IQM1F3l3T39v2T+885cuW6/zaeC0 qcvq40i2q8JNOX0m9/b7sf2t7YUno+n2rd5JrrSrcvcaYkrs8U4xlRNwg4wqq4UbSZ18drjANft5 8VePPJSLGM3Xqep3g5EPd2c47ZGjrdFogbv7WczDGbyrQnd7RIk4KU3+EA5zPaXcPeuxb+PSs3cs JurinW3J+8rcqwk/pcW16NHXO/e0nbjubl8Gt5C1mZJJK5RwuxSdaRvQcbsY15xU8MuUk1wILeRP gFbKi/neLu2BaiIHXR17t0plke7qKpiNZ+vN+8pf8BFJwwMPyd6/ymzbbZXmLJKNncGTr6O7Y/2V tTf5ZONz/hh6Gi/cLwEuxlO/tfUE1zVjNcHzbeG/bjR8KKEZWVy+O661UFG+OI/I7jO+913VqW10 xmdwDZpZFGicvTJJc3UxSNpqDO5i1lRL870ir+oUBDuKGbb7R7jbI33ZxaVnLd9pVcE8NxL3lbkl NL6XGj9GzRffHa/uF22zCt65kL2UxNKMpJStybTeGF6DlanJJNuMZtpc0jXLOanAxgDAN5OOvjk5 d8nAjpGg6rkoSmSXoqJ7G2GKtLpIsly9SuW60imLyUQ6+wTRzZyID8oewenVG9u9nbfYWKGdzcZ3 4/0Nr6y5VfmtJ4YP+slD+U7p7dePndnuh07mm5Gcctco/tF76qzhdfijKXG5HhR9GNxrhVU4k8fH bwMaTpoM5vkZeZzcM2X01VahVzPKLQUDCQO9FZdmqM3Idpw6kVTXZgID0MkPy5qHvXy+3Tqbla0P LwycP/cnS7dfs0munH6U43Pokb2du/AzaGlxje3Lm55+5wbtWcVmyuFHFzT61zjxU4uw/eJNdrXU 2sdOV1Kp6poFR15XUuwwxNRgY6DbOVkyen6zj3FMhnLgwfxllRMoYeomMIiI5qvru49f3PnXmNRz FzM3H+dck5NL2VX8K9kqJeiN2dsbP2rsrT/suk5SzlLXCsbUIwxNKlZNKspU5yk3J+rMhZ8U5IMA YAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAM AYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgEK3k U/smPRsf+0h9Tvth6vfW+xD3f7e/pz0ydffvqp/i3vXZ/wBV9Yv5D5ent6ZtR2T/AO43Fa+5Or9i 4U+01+y4av5cfxYa8/s/xGjfkb/2jdPNffvS+8/ixfYcP23q4Y/zmD6rq4cOH7d8FKUKru0I/jkn b2Y6Xt27HtBevRGQLtDXVFjLfW44VwL2omqlpdsptYqfU3cYI8om+b0APnZ6CaBe3rLTJfelnKxz EVw6N25K3N09cdmMrar6LqtLjV8jy93TY2Lb1mP3JfzdzKSfxfaLNqF23HEqJdO/cheajV1bsJyS jhSbkpUeC7bw4s59g33HN7WsN4ItH+4y3I2rxVO1E5khXMIehH64l51ogiAdAW+nXqjcQ6CHT2hm vvdq55NXclJ6Xby1uxR1jlJyuX1GnrO9btNv9HoQU/8AYbQ9j7Xh/Y1OMdcu529mKwwyzlqNnKOW J0pby92+0kqdT7Vcdlqj4fEi2Nrz7O/qXXvsn+pf2efRyH1U+zz6D+pf0T2/yf0f9W/8R936fxfR +b/yZ51a39+fetz7y6v2nE8fVxdTF648fxV968T1m2t//LfcFj7k+z/YcC6X2fB0cHp0+n8GH2w8 PY9pnyj74wBgDAGAMA+NYvq99BS/1s+hvqz7g5+nvrF7j9BfRfpD63vf0l/i/u/Z17/U+b0+XMrI /bftkPs2Pq4lhwVxYvTDTjWvKnEwNU+6/u279t6f2fC+p1MPTw0448Xw4ac68KcyrRz4R8MDiVkk aTI2+J2Wo4XK8kuI0NC2GhMngpfMO6Y2h/F1Ry0AflJCu0Tib+MYM9BOz8vKGGXi85G1PKpKkc9K ULrVeKUoRnfjL6b8JKnJHlT34t+Gd3NXI6Vcv2s426y02EbmWjLCsLdu7ctZedvl8OTuQrKtZJ4i Feqxegz3t22u952+21k2XTOxmarqqmPr3NNiqAJ01YyXuTePi1Dl6gChX7wCj7ew3ToO0eoZjd60 hSyljLPNNcYzv3Fai/dTjl3KaXt07dfdczTnS8tsyeuyhnczmoZJP4Z28vblekqrg7UszCFttVVV euKLo6S5Fl7x2/2O/qQ32UDFDuX/ABT3ceUwRxdnDI+qPo/RoS4jVwf93Xp9Bj63b/G9nTNFe9X/ AHM4Z/eGL7Fxr9ir0aU448P1+H+u+GvI9JPHj/s46kPu+n3jVU+8sPWri+Dp4v8A4uOvy/Z/raUx ehP1mnB6DjAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgD AGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYAwBgDAGAMAYB//Z --00000000000094f652062289ae93--