MIME-Version: 1.0 Content-Type: multipart/related; boundary="----=_NextPart_01C5ECCB.555BE850" This document is a Single File Web Page, also known as a Web Archive file. If you are seeing this message, your browser or editor doesn't support Web Archive files. Please download a browser that supports Web Archive, such as Microsoft Internet Explorer. ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii" به نام خدا

 

 

پژوهش هاي جغرافيايي - ش&#= 1605;ارة 52، تابستان1384 =

صص 31-13

 

تحليل و پيش بيني آماري خشكسالي و دوره هاي خشك كوتاه م= دّت  در استان خراسا= 06;= *

 

دكتر زهرا حجازي زاده- دانشيا= 585; گروه جغرافيا، دانشگاه تربيت معلّم=

عليرضا شيرخاني-كار= 88;ناس ارشد جغرافي= 75;

پذير&#= 1588; مقاله :  9/4/82

 

چكيد= 07;

          = 78;حقيق حاضر درصدد شناسائي رخداد خشكسالي و دو= 585;ه هاي كوتاه مدّت وقوع آن در منطقة خراسان مي باشد. جهت دستيابي به اين منظور از &#= 1583;و روش بهره گرفته شده است. براي بررسي وضعي= ّت خشكسالي هاي منطقه از آما= 585; بارش ماهان= ة 34 ايستگاه طي= ّ سال هاي تحقيق (1997- 1968) و روش  گيبس- ماهر استفاده‌ شد. &#= 1711;ام بعدي به شناخ= 578; دوره هاي كوتاه مد¡= 7;ت وقوع خشكسال= 10; اختصاص يافت. اين كار نيز با استفاده ا= 586; روش زنجيرة ماركف مرتب= ة ا = 8;ّل دو حالته انجام شد. براي اين كا= 85; كه از داده هاي بارش روزانة پنج ايستگاه منتخب در بخش هاي مختلف استان استفاده شد، ويژگي هاي مه= 605;ّ مرتبط با دور= 607; هاي تر و خشك كوتاه مدّت همچون احتمالات ساده و اقليمي، فراواني روز= 07;ا، طول دوره هاي تر و خشك و نيز سيكل هوايي ت= 593;يين شد. سپس با محاسبة فراواني دور= 07;‌هاي خشك، احتمال وقوع اين دور= 607; ها و سرانجام دورة بازگشت آنها مشخّص گرديد. تحليل نتايج پرداز= 88; بارش ماهانه با روش نرمال، شرايط سال‌ه= 75;ي مختلف از نظر خشكسالي و ترسالي را معلوم ساخت= ؛ ب<= span lang=3DFA style=3D'font-size:11.0pt;font-family:"B Lotus";mso-bidi-language= :FA; layout-grid-mode:line'>ه گون&#= 1607;‌اي‌كه 57 درصد ايستگاه‌ها در سال 1970 دارا¡= 0; شرايط خشكسالي بسيار شديد ب= 608;ده‌اند. برعكس، در سال 1991 تمام ايستگا= 07;‌ها بارش دريافت= 10; بالاتر از ميزان نرمال داشته و 76 درصد از آنها نيز ترسالي با شدّت‌ه&#= 1575;ي مختلف را تجربه كرده‌= 75;ند. تعيين دقيق مقدار احتما= 04; دو روز خشك متوالي، اخت= 04;اف بين احتمالا= 78; ساده و اقليم= 610; وقوع روزهاي تر و خشك و نيزفراواني وقوع دوره ها= 610; خشك از نتايج مهّ= م اين مطالعه م= 610; باشد؛ چنان <= /span>كه احتمال دور= ة خشك متوالي از 71 تا= 98 درصد نوسان داشت. بين احتمالات ساده و اقليم= 610; خشكسالي ايستگاه‌ها نيز اختلاف چشمگيري مشاهده نشد. به لحا&#= 1592; فراواني روزهاي خشك نيز در تمامي فصول، متوسّط تعداد روزها= 10; خشك ب&#= 1610;ست روز و بالاتر از آن مي‌باشد.

        =               = واژگان كليدي: خراس&#= 1575;ن، خشكسالي، ده= 03; ها، زنجيرة ماركف، دوره هاي خشك كوتاه مدّت.

 

مق&= #1583;ّمه<= o:p>

ترديدي نيست كه اقلي= 605; در اشكال گوناگون از ج= 605;له خشكسالي نقش تعيين كنندهR= 04;اي در وضعيّ= ت اقتصادي و به تبع آن شرايط اجتماعي جوامع دارد. اين شرايط بالاخص در مورد برخي كشورها مثل ايران كه به= لح&= #1575;ظ موقعيّت جغرافيايي د= 85; مناطق گرم و خشك واقع اند= 548; ملموس تر است. حدود 78 درصد از وسعت 31= 3524 كيلومتر مربّعي استان خراسا= 06; از نظر آب وهوايي دارا= 10; اقليم بياباني ونيمه بياباني مي باشد و استعداد بال= 75;يي جهت ابتلا به بلاياي طبيع= 10; دارد.

وقوع پديدة خشكسالي و اث= 585;ات زيانبار آن ك= 607; بخش هاي مختلف زندگي انسان را تحت تأثي&= #1585; خود قرار داد= 607; است،‌ باعث شده كه مخصوص= 575;ً در دهه هاي اخير متخصّصان علوم جوّ= ي و نيز اقليم شناسان كشورهاي مختلف جهان ب= 607; جستجوي راه‌= 07;ايي جهت مقابله ب= 575; آن از طريق مطالعة شرايط وقوع دوره هاي اين رخداد در زما= 606; ها&= #1610; گذشته و نيز پي بردن به رفتارهاي خا= 89;ّ آن در خصوص نحوة تكرار اين دوره‌ها در آينده اقدام نمايند. از آنجا كه تا كنون تعريف واحدي از خشكسالي كه تمام متخصّ= صا&= #1606; علوم مربوطه بر آن اتفاق نظر داشته باشند، ار&= #1575;ئه نشده است؛ لذ= 575; بسته به اين كه اين گونه تحقيقات توسّط چ= ه سازمان يا متخصّص و ي= 5; چه هدفي (به لحاظ هيدرولوژيك¡= 0;، اقتصادي يا كشاورزي) صور= 578; گرفته باشد،R= 04; از روش هاي متفاوتي نيز جهت انجام مطالعات استفاده گرد= 10;ده است. تا كنون مطالعات زيادي از روش «تحليل داده هاي بارندگي با استفاده ا= 586; شاخص دهك ها» و نيز «الگوي زنجيرة ماركف»=   صورت گرفته است. از روش گيبس-ماهر كه بر مبناي كاربرد توزي= 93; هاي فراواني تجمّعي يك ايستگاه بنا شده است،‌ بيشترين استفاده را محقّقين استراليايي بعمل آورده اند. مثلاً= گيبس و ماهر= ;[1] (1967) اين شاخص را جهت مطالعة= خشكسالي ها&= #1610; استراليا استفاده كرد= 07; اند. خوش اخلاق (1377) با استفاده از اين شاخص و با بهره گيري از آمار بارندگ= 10; 37 ايستگاه بين سال هاي 63-1962 تا 92-1991 در سطح كشور، به بررسي وضعيّت آ= ب و هوايي كشور به لحاظ وضعيّت ترسالي و خشكسالي پرداخت و سطو= 581; درگير با ترس= 575;لي و خشكسالي را مشخّص كرد. مظّفر&= #1610; (1380) نيز در قسمت= 610; از كار خود جهت ارزيابي قابليّت هاي محيطي كشت گندم ديم در منطقة كرمانشاه در غرب كشور، از شاخص دهك ها براي شناخت خشكسالي هاي منطقة مذكور استفاده كرد. &#= 1575;ستفاده از روش زنجيرة ماركف به دلي= 604; توانمندي ها&= #1610; آن در محاسبة دوره هاي تر و خشك و همچن&= #1610;ن ساده كردن حلّ بسياري از مس= 575;ئل احتمالات مربوط به فرايندهاي وابسته، دار= 75;ي سابقة طولاني‌تر و كاربرد بيشتري نسبت به روش قبلي مي باشد. از اين مدل در علوم مختلفي نظير هواشناسي، ك= 88;اورزي، اقليم شناسي= 48; منابع طبيعي = 608; R= 30; استفادة= زيادي بعمل آمده است. روم&#= 1606;2 (1945) و كريشنان3 (1960) بررسي هاي تداوم دوره‌= 07;اي خشك را در مقياس منطقهR= 04;اي بدون در نظر گرفتن وابستگي وقو= 93; دورة خشك نسب= 578; به دوره يا دوره هاي قبل به انجام رسا= 606;يدند. آنها در مطالعات دور= 07; هاي خشك از توزيع هاي آماري گسسته استفاده كردند. امّ= ا بررسي احتمالات وقوع بارندگ= 10; بيشتر از آستانه اي مع= 610;ّن د= ر طول دوره اي از زمان،‌ با اين فرض كه بارندگي هر دوره پديد= ه اي وابسته به وقوع يا عدم وقوع بارندگ= 10; دورة قبل است= 548; اوّلين بار توسّط گابري= 04; و نيومن4 (1962) انجام گرفت.

ساستري = 08; كاپور5 (1970) روشي را براي ارزيابي فراواني روزهاي متوا= 04;ي با بارندگي كمتر يا بيشت= 585; از آستانة= مع= يّن ارائه دادند كه در آن از احتمالات شرطي استفاد= 07; شده است.

از آنجاكه سيست= 05; هاي سينوپتي= 03; مؤثّر بر بارندگي و دوره هاي خشك ممكن است به مدّت چند روز روي هر منطقه دوام داشته باشند، لذا تعيين احتمالات رويدادهاي متوالي مانن= 83; يك روز تر به دنبال يك روز تر ديگر و يا يك روز خشك به دنبال يك روز خشك ديگر لاز= 605; خواهد بود.

مدل‌ اح&= #1578;مالي زنجيرة ماركف براي تشريح فراواني‌طو = 4;اني‌مدّت رفتار دوره‌= 07;اي تر‌و‌خشك جوّي بسيار‌ مناس= 76; است.

كلارك و كاراس1 (1989) در يك حوضة= آبريز روابط تحليلي بين بارندگي و رواناب را براي يك مدل توزيع احتما= 04; مورد نظر قرا= 585; دادند و مدل توزيع احتما= 04; شرطي را براي نشان دادن چگونگي توال= 10; بارش و پتانسيل تبخير و تعرّق د= ر عرض هاي مختلف جغرافيايي بكار گرفتند.

خاوير مارتين ويد و ليدا گومز2 (1998) كار منطقه بندي شبه جزي= 585;ة اسپانيا را ب= 585; مبناي طول دوره هاي خشك از طريق روش زنجيرة ماركف انجام دادند و بر اساس آن نواح= 610; مختلف اين كشور را تقسي= 605; بندي كردند. به اين ترتيب كه روش ماركفي د= 585; نواحي شمالي = 575;سپانيا كاملاً پذيرفته شده = 608; قابل قبول اس= 578; و بر عكس، نواحي جنوبي اسپانيا تطبيقي با اي= 606; روش ندارند و در نهايت  در نواحي مركزي اسپانيا اين روش پذيرفته شده است و= لي&= #1603;ن اختلاف محسوسي بين مقادير تجرب= 10; و برآورد شده براي طولانيR= 04;ترين دوره ها وجود دارد.

مشابه تحقيق فوق در ايالات متّ= حد<= /span>ه &#= 1578;وسّط ويلكس3 (1998) صورت گرفت كه در آن ويژگي ها&= #1610; چند مدل استوكاستيك¡= 0; (عوامل تعيين كنندة وضعي= ;ّت آ= ب و هواي يك منطقه) در خصوص تناسب و كارايي اين مدل ها براي يك منطقه با استفاده از همين روش مور= 583; توجّه قرار گرفت.

در ايرا= 06;، هاشمي (1347) با استفاده از مدل زنجيرة= ماركف به بررسي آمار بارندگي روزانه در تهران پرداخ= 78;. وي آستانة= تر= ي و خشكي را براي بارندگ= 10; 2/0 ميليمتر در نظر گرفت و فراواني دور= 07; هاي خشك و تر چند روزه را ابتدا با استفاده از م= 583;ل ماركف و‌ سپس با استفاده ا= 586; مدل برنولي برآورد نمود = 608; با مقادير واقعي مشاهد= 07; شده مقايسه كرد &#= 1608; نتيجه گرفت ك= 607; در تمام ماه‌= 607;اي مورد مطالعه (نوامبر تا آوريل) نتايج حاصل از مدل ماركف به واقعيّات مشاهده اي بسيار نزديك تر است.

مشكاني (136= 2) نيز احتمال تواتر روزها= 10; خشك و تر بابل&#= 1587;ر را از ديدگاه بيزي تجربي طّي فصل بارش (مهر تا شهريور) براي دورة= د= ه &#= 1587;الة 1350 ت&#= 1575; 1359 با آستانة= خشكي و تري 1/0 ميليمتر در روز بررسي نمود و به اين نتيجه رسيد         =             &nb= sp;   كه &#= 1583;اده هاي بارندگي روزانه اين ايستگاه با مدل زنجيرة= ماركف مرتبة او= ّل مطابقت دارد.

تاكنون دربارة منطق= ;ة خراسان كه بخ= 588; وسيعي از شرق و شمالشرق كشور را در بر دارد، تحقيق جامعي با استفاده ا= 586; اين روش صورت نگرفته و= از اينرو تحقيق = 581;اضر در پي دستياب= 610; به اين اهداف است :

الف- شناخت وضعيّت ك= لّي خشكسالي‌ها¡= 0; منطقه؛ <= /p>

ب- شناسايي ويژگي‌هاي دوره هاي خشك.

&nbs= p;
رو&= #1588; بررسي

در اين تحقيق جهت بررسي شرايط خشكسالي منط= 02;ة مورد مطالعه از روش گيبس و ماهر (1967) استفاده شد. د&#= 1575;ده‌هاي مورد استفاد= 07; در اين روش،= دا= ده هاي بارش سالانه براي سي &#= 1587;ال از 1968 تا 1997 را شامل مي شود. در اين مرحله مقادير بارش مذكور با استفاده از نرم افزار Hayfa  پردازش شده = 608; مقادير بدست آمده بر اساس تقسيم بندي دهك‌ها و با توجّه به جدو= 604; شمارة (1) در سه گروه با شرايط خشكسالي، حالت نرمال و وضعيّت ترسالي دسته بندي گرديد.

 

ارزش كيفي

دهك

احتمال وقوع (درصد)

= خشكسالي خيلي شديد

= 1

= 10

= خشكسالي شديد

= 2

= 20

= خشكسالي متوسّط<= /p>

= 3

= 30

= نرمال

= 4

= 40

= نرمال

= 5

= 50

= نرمال

= 6

= 60

= ترسالي متوسّط<= /p>

= 7

= 70

= ترسالي شديد

= 8

= 80

= ترسالي خيلي شديد

= 9

= 90

= ترسالي بسيار بسيار شديد

= 10

= 100

 

 

از آنجا كه در تحقيقا= 578; اقليمي و= با&= #1604;اخص اقليم كشاورزي علاوه بر شناخت خشكسا= 04;ي‌ها پي بردن به رفتار دوره‌= 07;اي تر و خشك كوتاه مدّ= ت چند روزه تا چند هفته‌اي= 48; احتمالات وقوع اين دور= 607;‌ها و محاسبة= دو= رة بر گشت دوره ‌ها= 610; تر و خشك از اهمّيّت بالايي برخوردار است، لذا بخش مهمّي از تحقيق حاضر ب= 607; مطالعة اين ويژگي‌ها به روش الگوي ماركف اختصا= 89; يافت. داده‌ه= 575;ي استفاده شده در روش زنجيرة ماركف نيز داده هاي بار= 588; روزانة فصول پاييز تا بها= 585; از پنج ايستگاه منطقه مي باش= 583; (ماه‌هاي فصل تابستان به= دل&= #1610;ل فقدان بارش مؤث<= span lang=3DFA style=3D'font-size:13.0pt;font-family:"B Zar";mso-bidi-language:F= A'>ّر د= ر فعّاليّت ها= 10; كشاورزي مور= 83; مطالعه قرار نگرفت). اين ايستگاه‌ها عبارتند از مشهد، سبزوار، بيرجند، ترب= 78; حيدريّه و بربر قلعة= بجنورد. در انتخاب ايستگاه‌ها شرط وجود آما= 585; كامل و طولان= 610; مدّت (سي سا&= #1604;) و توزيع نسبي مناسب در سطح منطقه لحاظ گ= 585;ديده است (نقشة= شمارة 1).

معمول‌= 8;رين شكل، مدل زنجيرة ماركف مرتبة او= ّل م= ي‌باشد كه به شرح زير بيان مي شود:

را&= #1576;طة (1)    

        =             &nb= sp;            =          

وجود رابطة فوق  = 8; يا انطباق زنجيرة ماركف به سري داده‌ها با آزمون   x 2 بررسي شد.

 

 

 

 =

 =

 =

بر آورد ماتريس احتمال <= /span>– انتقال زنجيرة= ماركف

=  
 
نخستين گام در اين كار مشخّ= ص كردن مقدار احتمال از يك حالت به كلّ= ي<= span lang=3DFA style=3D'font-size:13.0pt;font-family:"B Zar";mso-bidi-language:F= A'>ّة حالت‌هاي ممكن است.  ماتريس احتمال زنجي= 85;ة ماركف (  P) را براي مرتبة او= ّل د= و حالته مي توا= 606; به اين صورت نوشت:

در اين ماتريس روز خشك با (0) و روž= 6; مرطوب با (1) نشان داده شد= 607; است. جملة= p11=  يعني احتمال روز مرطوب بعد از يك روز مرطوب و جملة p00<= sub>  بيان= گر احتمال روز خشك بعد از يك روز خشك است.

= به منظور استفاده از ماتريس فوق د= 585; محاسبات بعد= 10; نمادهاي p و q به شرح زير جايگزين شدهR= 04;اند:

 

 

 

نقشه 1-پراكندگي ايستگاه هاي = 605;ورد مطالعه

 

با مشخّص شدن عناصر ماتريس،= احتمال انتقال برخي خصوصيّات مهمّ سري مشاهدات همچون احتمالات اقليمي خشكي = 608; تري، طول دوره هاي تر و خشك، سيكل اقليمي، فراواني دور= 07;‌هاي خشك و تر مورد انتظار در هر ماه و احتمال= 575;ت سادة خشكي و تري بدست آمد كه نتايج آنها د= 585; جداول ش= مارة (5 تا 9) آورده شده است. نحوة= محاسبة= اي= ن خصوصيّ= ات به شرح زير است:

1-&n= bsp;      احتم= الات سادة<= span lang=3DAR-SA style=3D'font-size:13.0pt;font-family:"B Zar"'> وقوع روزهاي خشك و تر در هر ماه كه از تقسيم روزها= 10; تر يا خشك هر ماه بر تعداد روزهاي همان = 605;اه حاصل مي‌شود.

<= span style=3D'font-size:13.0pt;mso-bidi-font-family:"Times New Roman"'>2-&n= bsp;      اح&= #1578;مالات اقليمي كه نشان مي‌دهد چند درصد از دورة مورد مطالعه خشك و چند درصد تر است و از رابطه هاي زير محاسبه م= 610;‌شوند:        =    رابطة<= sub> (1)  =3D احتمال ساكن وقوع روز تر        =   

 


ة (2)  =3D احتمال ساكن وقوع روز خشك

3- طول دوره‌ه= اي تر و خشك، كه از اين روابط جهت محاسبه آنها استفاد= 07; شد:

        =         رابطة (3)  E0=3D طو&= #1604; دورة خشك در هر ماه يا طول دورة<= sub> خشك مورد انتظار

ة (4) E1&nbs= p; =3D طول دورة تر در هر ماه يا طول دورة<= sub> خشك مورد انتظار

ّص شدن طو= 604; دوره‌هاي تر = 608; خشك به راحتي م= 10; توان با جمع آنها مقدار سيكل هوايي ر= 575; نيز براي هر يك از اين دوره ها تعيي= 606; كرد. سيكل هوا&#= 1610;ي نشان دهند= ة<= sub> يك موس = 5; تر و يك موسم خشك متوالي است.

             &= nbsp;         =    رابطة<= sub> (5) Ec<= /b>=3D سيكل هوايي د= 585; هر ماه

ترين ويژگي‌هاي قابل محاسبه با اين روش،<= sub> تعيين  = 5;توسّ<= sub>ط روزهاي تر و خشك در هر ماه است. به عبارت ديگر اين كه در هž= 5; ماه به طور متو= 87;ّ<= sub>ط چند روز تر يا خشك داريم كه با استفاده از روابط 6 و 7 مشخّ<= sub>ص شد:<= /sub>

 &nbs= p;             =         =    رابطة (6) r0<= span style=3D'font-size:13.0pt;font-family:"B Zar";mso-ansi-font-weight:bold; mso-ansi-font-style:italic'> =3D فراواني وقوع، متوسّ<= sub>ط تعداد روزهاي خشك ه= 585; ماه

        =           رابطة (7) r1=3D فراواني وقوع، متوسّ<= sub>ط تعداد روزهاي تر همان  ماه

n        =           =3D تعداد روز در هر ماه

ة= دوره‌هاي خش= 03;n<= /sub> روزه در طول دورة= مطالعه (معيا= 585; تر بودن يك روز، دريافت بارش حداقل 1/0 ميليمتر يا بيشتر است)، به همراه دورة برگشت آنها پيش بيني شد.

ة<= sub> (8)، دوره= ;‌هاي خشك n روزه        =             &nb= sp;            =             &nb= sp;            =    =

Dn  =3D تعدا= 583; دوره‌هاي خش= 03; n<= /sub> روزه در يك دورة مع= يّن                 =         n<= /sub> =3D طول دورة خش= ك

N&nbs= p;   =3D تعداد كلّ روزهاي دورة آماري        =             &nb= sp;            =             &nb= sp;  p = 08;  q=3D عناصر ماتريس احتمال انتقالي

رابطة= (9)، دو= 585;ة برگشت را نشا= 606; مي‌دهد. نتايج مربوط به دورة برگشت ه= ر يك از اين دوره‌ها در نمودارهاي شمارة
(1 تا 8) نشان داد= 607; شده است.         =  را&= #1576;طة (9)، دو= 585;ة برگشت موسم‌= 07;اي خشك        =              =        

Tn= =3D دورة برگشت دور= ة خش= ك n<= /sub> روزه        =             n  =3D طول م&#= 1583;ّت دوره‌هاي خش= 03; مورد نظر<= /p>

 

نتاي= ج بحث و نتيجه گيري

در بررس= 10; نتايج تحقيق در دو بخش مجزّا ابتدا به تشريح شرايط كلّي خشكسال= 10;‌هاي حاكم بر منطقة م= ورد &#= 1605;طالعه كه از بررسي 34 ايستگاه حاص= 04; شد، پرداخته = 608; در ادامه ويژگي‌هاي دوره هاي خشك كوتاه مدّ= ت ر= ا با استفاده ا= 586; نتايج
پنج ايستگاه= 10; كه به روش ماركف مطالع= 07; شدند، مورد بررسي قرار م= 610; دهد.

 

1<= i>- تحليل خشكسالي‌‌ه= 5;ي منطقه

با تطبي= 02; يافته هاي حاصل از پردازش داده هاي بارش ماهانة ايستگاه‌ها¡= 0; منطقه با توجّه ب= ه گروه بندي تعيين شده در جدول شمارة (1) شرايط اقليم= 10; منطقه طيّ دو= 585;ة مورد مطالعه مشخّص شد كه ن&#= 1578;ايج آن در جدول شمارة (2) خلاصه شده است. نتايج اي&#= 1606; جدول بيانگر آن است كه در اين منطقه در دورة مورد مطالعه،= سا= ل‌‌هاي 1970 و 1991 به ترتيب خشك ترين و مرطوب تر&= #1610;ن سال‌‌ها
&#= 1576;وده اند. در سال 1970 حدود 81 درصد از ايستگاه‌ها ميزان درياف= 78; بارش پايين ت= 585; از حدّ نرمال داشته = 608; از اين ميان نزديك به 57 درصد ايستگا= 07;‌هاي منطقه شرايط خشكسالي بسيار شديد ر= 575; پشت سر گذاشت= 607; اند. بر عكس در سال 1991 تمامي ايستگاه‌ها بارش دريافت= 10;‌شان بالاتر از حدّ نرمال بوده، علاوه براين 2/76 درصد از آنها وضعيّت ترسالي را با
&#= 1588;دّت هاي مختلف شاهد بوده اند.

 

جدول 2- شرايط اقليم= 10; 34 ايستگاه مطالعه شده نسبت به نرما= 604; سي س&= #1575;له

درصد

تع&#= 1583;اد ايستگاه هاي درگير با خشكسالي=

 

درصد

تع&#= 1583;اد ايستگاه هاي درگير با ترسالي=

 

سال

ده&#= 1603;

ده&#= 1603;

 

30

20

10

 

90 +

80

70

 

5/9

0

4

0

8/72

14

7

10

1968

2/76

11

9

12

5/9

1

1

2

1969

81

4

6

24

0

0

0

0

1970

5/59

7

12

6

2/26

5

3

3

1976

6/78

4

8

21

5/9

1

1

2

1983

8/72

2

8

21

4/2

0

1

0

1984

2/71

5

6

19

6/28

5

4

3

1988

8/72

5

7

19

9/11

3

1

3

1989

0

0

0

0

2/76

12

14

10

1991

5/9

4

0

0

6/66

14

6

8

1992

5/59

5

8

12

19

2

5

1

1993

7/16

6

1

0

4/52

11

8

3

1997
 

 

2- ويژگي‌هاي دوره‌هاي خش= 03;

در تحلي= 04; ويژگي‌هاي دوره‌هاي خش= 03; شرايط پنج ايستگاه مشهد، سبزوا= 85;، بيرجند، ترب= 78; حيدريّه و بربر قلعة= بجنورد با استفاده از روش ماركف مورد بررسي ق= 585;ار گرفت كه در اين بخش به بررسي آنها مي پردازد .

احتمال̴= 4;هاي شرطي مرتبة= او= ّل دوره‌هاي خش= 03; و تر اين ايستگاه‌ها در جدول شمارة (3) آمده است. اعداد هر كدا= 605; از سلّول‌ه= اي اين جدول همانند مدل زنجيرة ماركف مرتبة او= ّل د= و حالته نوشته شده و بيانگر وقوع حالات مختلف در دورة مورد بررسي است . مثلاً در ايستگاه مشه= 83; در ماه ژانوي= 607; احتمال وقوع = 610;ك روز خشك بعد از روز خشك 82% است؛ در حالي كه همين حالت براي وقوع روز  مرطوب بعد ا= 586; يك روز مرطوب تنها 49% است. در اين ايستگاه چنانچه روز ا= 608;ّل مرطوب باشد ب= 575; احتمال 51% در روز بعد از آن وضعيّت خشكي رخ مي‌د= 607;د. كمترين ميزا= 06; احتمال نيز وقوع حالت مرطوب بعد از يك روز خشك است كه اين شرايط در ماه ژانويه براي ايستگاه مشه= 83; با احتمال تنها 18% بوقوع مي‌پيوندد. نت&= #1575;يج ماتريس ها نش= 575;ن مي‌دهد ك= ه &#= 1605;قادير  p00كه بيانگر دو رو= 586; خشك متوالي م= 610; باشد، بين 71 تا 98 درصد در نوسان است. حدّاق&= #1604; احتمال وقوع p00<= /sub> به ميزان 4/71 درصد در ماه مارس مربوط ب= 607; ايستگاه مشه= 83; است و حدّ= اك&= #1579;ر آن با 4/98 در صد نيز در ماه ژوئن ايستگا= 07; بيرجند اتّ= فا&= #1602; مي افتد. در خصوص احتمال p11 =   ني&= #1586; شاهد يك نوسا= 606; عمدة 46 درصدي بين ايستگاهR= 04;هاي منطقه هستيم كه اين اختلا= 601; زياد ناشي از احتمال 5/13 درصدي وقوع p11  ايست= گاه سبزوار واقع در غرب استان و احتمال 60 در صدي ماه مارس در ايستگاه مشهد است.

نتايج ارائه شده تا اين قسمت وضعيّت ماه= ;انة ايستگاه‌ها را از نظر دوره‌هاي خش= 03; و مرطوب نشان &#= 8204;داد. جهت شناسايي احتمال‌هاي شرطي مرتبة= او= ّل براي كلّ دوره، تشخيص احتمال وقوع يك روز خشك بعد از يك روز خشك ديگر در ك&#= 1604;ّ دورة آماري د= 585; هر يك از ايستگاه‌ها = 84;رجد&= #1608;ل شمارة (4) ار&= #1575;ئه شده كه در آن احتمالات شرطي مختلف براي هر پنج ايستگاه در ك= 604;ّ دورة آماري محاسبه گ= رديده &#= 1575;ست.

طبق اين جدول احتمال p00<= /sub>  براي تمام ايستگاه‌ها¡= 0; مطالعه شده ط= 610;ّ دورة مورد بح= 579; هيچگاه از 80 درصد كمتر نيست. چنان كه حدّاقل آن را به ميزان 7/83 درصد در ايستگاه مشه= 83; و ماكزيمم وقوع را نيز در ايستگاه جنوبي بيرجن= 83; به ميزان 7/88 درصد شاهديم.

با توجّه ب= ه اين كه ايستگاه‌ها¡= 0; مطالعه شده د= 585; نواحي متفاو= 78; آب و هوايي اي&#= 1606; استان واقع ا= 606;د، مي= ‌توان نتيجه گرفت كه &#= 1576;سياري از بخش هاي خراسان به= وي&= #1688;ه در مناطق مور= 583; مطالعه،= داراي اقليم بسيار خشك ا= ند و طبيعتاً با اين شرايط         =  نمي توان انتظار وقوع دوره ها= 610; مرطوب زيادي را در منطقه داشت. به طوري كه شاهد هستيم، هيچي= 03; از ايستگاه هاي منطقه احتمال بالاتر=   از50 در صد براي وقوع p11  ط= 10;ّ اين دوره ر= ا &#= 1578;جربه نكرده اند و حدّاكثر احتمال وقوع اين وضعيّ= ت ر= ا به ميزان 1/47 درصد در مناط= 602; شمالي در ايستگاه برب= 85; قلعه مي توان مشاهده كرد ك= 607; اين امر نشانگر تفاو= 78; اقليمي اين منطقه به لحا= 592; شرايط كوهستاني متفاوت و متأث<= span lang=3DFA style=3D'font-size:13.0pt;font-family:"B Zar";mso-bidi-language:F= A'>ّر بودن بيشتر آ= 606; از توده هاي مرطوب نسبت ب= 607; ساير بخش هاي
&#= 1575;ستان است.

البتّ= ه اين نكته را نيز بايد مدّ &#= 1606;ظر داشت كه با توجّه به گستردگي بسي= 75;ر زياد خراسان بزرگ، دستيابي به نتايج مطلوب تر قطعاً مستلزم مطال= 93;ة ايستگاه‌ها¡= 0; بيشتري است و نمي‌توان با قاطعيّت كامل نتايج بدست آمده براي اين ايستگاه ها ر= 575; به ساير مناط= 602; اين استان ني= 586; تعميم داد.

برخي خصوصيّات مهمّ ديگر مرتبط با ويژ= 711;ي‌هاي دوره‌هاي خش= 03; و مرطوب با استفاده از ماتريس‌هاي احتمال زنجي= 85;ة ماركف محاسب= 07; شد كه نتايج آن در جداول شمارة (5 تا 9) ا= رائه شده‌است. اي= ;ن ويژگي‌ها شامل احتمالات سا= 83;ة شرطي و احتمالات اقليمي دورهR= 04;هاي خشك و مرطوب، فراواني وقو= 93; اين روزها، ط= 608;ل هر يك از اين دوره‌ها و سيكل تركيبيR= 04;شان مي‌باشد. در اين بخش به تشريح اين ويژگي‌ها ميR= 04;پردازيم:

 

 

جدول 3- ماتريس احتمال هاي شرطي مرتبة اوّل دوره‌هاي خش= 03; و مرطوب

= 75;يستگاه

 ما= 607;  

تربت حيدريّه

بربر قلعه

سبزوا&#= 1585;

بيرجن&#= 1583;
ژانوي&#= 1607;

18/0

49/

82/0

51/0

209/0

496/0

791/0

504/0

193/0

447/0

807/0

553/0

2= 1/0

3= 88/0

7= 9/0

6= 1/0

1= 84/0

4= 35/0

8= 15/0

5= 36/0
فوريه

23/0

54/0

77/0

46/0

22/0

53/0

77/0

47/0

193/0

52/0

807/0

48/0

1= 77/0

4= 2/0

8= 22/0

5= 83/0

2= 06/0

4= 23/0

7= 94/0

5= 77/0
مار= 587;

285/0

6/0

714/0

399/0

259/0

549/0

742/0

45/0

22/0

572/0

78/0

428/0

2= 11/0

5= 05/0

7= 89/0

4= 94/0

1= 96/0

5= 13/0

8= 04/0

4= 86/0
آوريل

233/0

531/0

766/0

469/0

184/0

45/0

815/0

55/0

178/0

536/0

822/0

464/0

1= 62/0

4= 3/0

8= 38/0

5= 68/0

1= 26/0

5= 07/0

8= 73/0

4= 92/0
مه

166/0

435/0

833/0

565/0

131/0

325/0

87/0

675/0

154/0

474/0

845/0

526/0

1= 12/0

3= 38/0

8= 88/0

6= 62/0

0= 63/0

2= 6/0

937/0

74/0
ژوئن

042/0

386/0

985/0

614/0

0= 35/0

2= 62/0

9= 65/0

7= 83/0

0= 47/0

4= 08/0

9= 53/0

5= 9/0

0= 32/0

1= 35/0

9= 65/0

8= 65/0

0= 16/0

1= 87/0

9= 84/0

8= 12/0
اكتبر

071/0

404/0

928/0

595/0

0= 4/0

2= 72/0

9= 6/0

7= 27/0

0= 84/0

3= 8/0

9= 16/0

6= 2/0

0= 46/0

3= 8/0

9= 53/0

6= 2/0

0= 23/0

3= 45/0

9= 76/0

6= 55/0

نوامبر

097/0

364/0

903/0

635/0

0= 86/0

3= 69/0

9= 13/0

6= 31/0

1= 17/0

4= 5/0

8= 33/0

5= 5/0

8= 8/0

3= 74/0

9= 11/0

6= 26/0

0= 56/0

3= 3/0

9= 43/0

6= 71/0

 

جد= ;ول 4- ميانگين عناصر ماتري= 87; هاي احتمال انتقال زنجي= 85;ة ماركف

 

بيرجند

سبز = 8;ار

بربž= 5;قلعه بجنورد

ترب= 8; حيدريه

مشهž= 3;
163/0<= b>

462/0<= /span>

837/0

538/0<= /span>

148/0<= /span>

413/0<= /span>

852/0<= /span>

587/0<= /span>

151/0<= /span>

471/0<= /span>

849/0<= /span>

529/0<= /span>

134/0<= /span>

375/0<= /span>

866/0<= /span>

325/0<= /span>

113/0<= /span>

379/0<= /span>

887/0<= /span>

621/0<= /span>

 

 

 

 

 

 

 

 

2-1- احتمالات سا= 83;ة شرطي و احتمالات اقليمي

مقايسة مقادير احتمالات شرطي وقوع روزهاي خشك و تر در هر ماه و احتمالات اقليمي همان ماه كه بيانگ= 585; ايّا&#= 1605; تر و خشك به صورت درصدي است (ستون اوّ= ل و دوّم جداول 5 تا 9)، نشان مي دهد كه اختلافات بسيار جزئي بين اي= 606; احتمالات وجود دارد؛ به طوري كه به ندرت اين ميزان اختلاف از يك درصد تجاوز م= 610; كند. حداكثر اختلاف مشاهده شده د= 585; ايستگاه مشه= 83; در ماه ژوئن به ميزان 1/1 درصد است. اين مقدار در ايستگاه ترب= 78; حيدريّ= ه در ماه دسامب= 585; 1/1 درصد و در بربر قلعة بجنورد به يك درصد در ماه آوريل مي رسد. در ايستگاه سبزوار حدّا= 03;ثر اختلاف مشاهده شده مربوط به ماه ژانويه به ميزان 7/2 درصد است. اين شرايط به صورت بارزتر در ايستگاه بيرجند براي ماه‌ نوامبر = 602;ابل مشاهده است ك= 607; بيشترين ميزان اختلا= 01; را به مقدار 2/4درصد به خود اختصاص داده است.

با توجّه ب= ه اين كه اين اختلافا= 78; بسيار جزئ= ي بوده و در اكثر ماه‌ها مقدار آن از همان يك درصد مورد اشاره فراتر نيست، لذا مي توان نتيجه گرفت كه &#= 1585;وابط مورد استفاد= 07; از مدل زنجيرة ما= ركف براي تعيين احتمالات شرطي وقوع روزهاي تر و خشك از دقّ= ت كافي بر خوردار است و مي توان از آنها  با اطمينان در بررسي‌ها= 10; مورد نظر استفاده كرد.

 

2-2-فراواني وقوع روزهاي خشك

چنانچه فراواني روزهاي خشك بدست آمده در دورة زماني مورد نظر كه در ستون سوّم جداول (5 تا 9) آمده را         =    به صورت ماهانه مورد بررسي قرار دهيم،= مشاهده مي كنيم كه د&#= 1585; تمام ماه‌ها= 10; فصول مطالعه شده، تعداد روزها= 10; خشك به طور متوسّ= ط بيست ر&#= 1608;ز و بالاتر از آن مي باشد و تقريباً در هيچ مورد كمت= 585; از بيست روز نيست. كمترين فراواني‌ دوره‌هاي خش= 03; مشاهده شده مربوط به ايستگاه مشه= 83; طيّ م&= #1575;ه‌هاي ژانويه و مار= 587; است كه هيجده &#= 1585;وز مي باشد
(جدول ش= مارة 5) و بيشترين فراواني‌‌ه= 5; را نيز مي توان در ايستگاه‌ها¡= 0; جنوب منطقه ا= 586; جمله بيرجند = 588;اهد بود كه تقريب= 575;ً بيست و نه روز است (جدول شمارة 6). =

 

2-3- طول ميانگين دوره ‌‌هاي خشك

مطابق جداول شمار= 7; (5 ت= 5; 9) طول دوره‌ها= 10; خشك در اين ايستگاه‌ها تفاوت‌هاي چشمگيري با يكديگر دارن= 83;. نتايج  بدست آمده ب= 607; جز در دو مورد در تمام ماه‌= 607;اي ديگر منطقي است. بدين ترتيب در حال= 610; كه طول دورة= خش= ك در ماه اكتبر ايستگاه برب= 85; قلعه دوازده = 585;وز است و اين دور&#= 1607; تمام اين ماه را در ايستگا= 607; بيرجند شامل = 605;ي‌شود. اين شرايط براي ماه ژوئ= 606; اين ايستگاه نيز برقرار است؛ امّ= ا د= ر ساير ايستگا= 07;‌ها و ماه‌ها شرايط كاملاً منطقي برقرا= 85; است. با اين وجود چنانچه نتايج بدست آمده را براي كلّ دورة= آماري در نظر بگيريم،= نتايج حاصل كاملاً قابل توجيه است.

با اين وجود حداقل = 605;يانگين طول دورة= خش= ك براي تمام ايستگاه‌ها ماه مارس است كه در هيچكدا= 605; به جز بيرجند به پنج روز نمي‌رسد. حدّاك&= #1579;ر آن نيز مربوط به ماه ژوئن است كه با شدّت‌&= #1607;اي متفاوت در ايستگاه‌ها رخ مي‌دهد.

 

 

 

 

 

 

 

 

 

W/WW/D<= /span>

<= /span><= /span>

<= /span>

<= /span>

<= /span>

<= /span>

EC

103/0

897/0

89/0

106/0=

6/27<= /span>

4/3

08/14=

68/1<= /span>

76/15=

123/0=

877/0

867/0=

132/0=

01/26=

99/3<= /span>

31/10=

57/1<= /span>

88/11=

208/0

792/0=

788/0=

212/0=

43/24=

57/6<= /span>

17/6<= /span>

66/1<= /span>

88/7<= /span>

257/0

743/0=

738/0=

262/0=

88/22=

12/8<= /span>

55/5<= /span>

97/1<= /span>

5/7

33/0

67/0<= /span>

667/0=

333/0=

7/18<= /span>

32/9<= /span>

35/4<= /span>

17/2<= /span>

5/6

412/0

58/0<= /span>

583/0=

417/0=

1/18<= /span>

9/12<= /span>

51/3<= /span>

51/2<= /span>

6

324/0

676/0=

668/0=

332/0=

04/20=

96/9<= /span>

3/4

13/2<= /span>

43/6<= /span>

232/0

767/0=

773/0=

227/0=

99/23=

04/7<= /span>

6

78/1<= /span>

78/7<= /span>

075/0

925/0=

936/0=

064/0=

02/29=

98/1<= /span>

81/23=

63/1<= /span>

44/25=

 

خص&#= 1608;صيّات ماركفي

اح&#= 1578;مالات شرطي

اح&#= 1578;مالات اقليمي

فر&#= 1575;واني روزها

طو&#= 1604; ميانگين دوره ها

سي&#= 1603;ل هوايي

ما&#= 1607;

W/WW/D<= /span>

<= /span><= /span>

<= /span>

<= /span>

<= /span>

<= /span>

EC

اك&#= 1578;بر

031/0

969/0

966/0

034/0=

95/29=

05/1<= /span>

5/43<= /span>

53/1<= /span>

45

نو&#= 1575;مبر

119/0=

881/0

923/0=

077/0=

7/27<= /span>

3/2

76/17=

5/1

35/19=

دس&#= 1575;مبر

195/0

805/0=

81/0<= /span>

192/0=

05/25=

95/5<= /span>

14/7<= /span>

7/1

83/8<= /span>

ژا&#= 1606;ويه

25/0

75/0<= /span>

752/0=

246/0=

36/23=

64/7<= /span>

43/5<= /span>

78/1<= /span>

21/7<= /span>

فو&#= 1585;يه

254/0

746/0=

738/0=

262/0=

66/20=

34/7<= /span>

88/4<= /span>

7/1

58/6<= /span>

ما&#= 1585;س

283/0

717/0=

713/0=

287/0=

1/22<= /span>

9/8

1/5

06/2<= /span>

16/7<= /span>

آو&#= 1585;يل

219/0

781/0=

796/0=

204/0=

88/23=

12/6<= /span>

93/7<= /span>

03/2<= /span>

96/9<= /span>

مه

083/0

917/0=

921/0=

078/0=

57/28=

43/2<= /span>

87/15=

35/1<= /span>

22/17=

ژو&#= 1574;ن

017/0

983/0=

98/0<= /span>

02/0<= /span>

4/30<= /span>

6/0

5/62<= /span>

23/1<= /span>

73/63=

 

 

 

 

 

 

خص&#= 1608;صيّات ماركفي

اح&#= 1578;مالات شرطي

اح&#= 1578;مالات اقليمي

فر&#= 1575;واني روزها

طو&#= 1604; ميانگين دوره ها

سي&#= 1603;ل هوايي

ما&#= 1607;

W/WW/D<= /span>

<= /span><= /span>

<= /span>

<= /span>

<= /span>

<= /span>

EC

اك&#= 1578;بر

047/0

953/0

948/0

052/0=

4/29<= /span>

6/1

25

37/1<= /span>

37/26=

نو&#= 1575;مبر

114/0

886/0

88/0<= /span>

12/0<= /span>

4/26<= /span>

6/3

63/11=

58/1<= /span>

21/13=

دس&#= 1575;مبر

242/0

758/0=

747/0=

253/0=

16/23=

84/7<= /span>

6

35/1<= /span>

8

ژا&#= 1606;ويه

295/0

705/0=

707/0=

292/0=

9/21<= /span>

05/9<= /span>

88/4<= /span>

99/1<= /span>

8/6

فو&#= 1585;يه

32/0

68/0<= /span>

68/0<= /span>

32/0<= /span>

04/19=

96/11=

5/4

13/2<= /span>

6/6

ما&#= 1585;س

358/0

642/0=

634/0=

365/0=

65/19=

35/11=

86/3<= /span>

22/2<= /span>

08/6<= /span>

آو&#= 1585;يل

252/0

748/0=

75/0<= /span>

25/0<= /span>

48/22=

52/7<= /span>

4/5

82/1<= /span>

2/7

مه

172/0

828/0=

84/0<= /span>

162/0=

04/26=

02/5<= /span>

6/7

48/1<= /span>

8/9

ژو&#= 1574;ن

045/0

955/0=

957/0=

043/0=

67/29=

33/1<= /span>

57/28=

28/1<= /span>

85/29=

 <= /span>

خص&#= 1608;صيّات ماركفي

اح&#= 1578;مالات شرطي

اح&#= 1578;مالات اقليمي

فر&#= 1575;واني روزها

طو&#= 1604; ميانگين دوره ها

سي&#= 1603;ل هوايي

ما&#= 1607;

W/WW/D<= /span>

<= /span><= /span>

<= /span>

<= /span>

<= /span>

<= /span>

EC

اك&#= 1578;بر

06/0

938/0

93/0

07/0<= /span>

86/28=

14/1<= /span>

74/21=

6/1

35/23=

نو&#= 1575;مبر

12/0

88/0

88/0<= /span>

12/0<= /span>

4/26<= /span>

6/3

36/11=

6/1

13

دس&#= 1575;مبر

208/0

792/0=

79/0<= /span>

21/0<= /span>

45/24=

55/6<= /span>

21/6<= /span>

66/1<= /span>

87/7<= /span>

ژا&#= 1606;ويه

252/0

717/0=

744/0=

256/0=

4/23<= /span>

9/7

5

64/1<= /span>

64/6<= /span>

فو&#= 1585;يه

243/0

757/0=

767/0=

233/0=

5/21<= /span>

5/6

65/5<= /span>

71/1<= /span>

36/7<= /span>

ما&#= 1585;س

302/0

698/0=

7/0

3/0

7/21<= /span>

3/9

74/4<= /span>

2

74/6<= /span>

آو&#= 1585;يل

219/0

781/0=

778/0=

222/0=

34/23=

66/6<= /span>

17/6<= /span>

76/1<= /span>

9/7

مه

153/0

847/0=

855/0=

145/0=

5/26<= /span>

5/4

93/8<= /span>

5/1

43/10=

ژو&#= 1574;ن

04/0

96/0<= /span>

964/0=

036/0=

9/29<= /span>

1/1

25/31=

15/1<= /span>

6/32<= /span>

 

 

 

 

 

خص&#= 1608;صيّات ماركفي

اح&#= 1578;مالات شرطي

اح&#= 1578;مالات اقليمي

فر&#= 1575;واني روزها

طو&#= 1604; ميانگين دوره ها

سي&#= 1603;ل هوايي

ما&#= 1607;

W/WW/D<= /span>

<= /span><= /span>

<= /span>

<= /span>

<= /span>

<= /span>

EC

اك&#= 1578;بر

116/0

884/0=

88/0

12/0<= /span>

28/27=

72/3<= /span>

12

61/1<= /span>

61/13=

نو&#= 1575;مبر

176/0

83/0

825/0=

175/0=

74/24=

26/5<= /span>

55/8<= /span>

81/1<= /span>

36/10=

دس&#= 1575;مبر

24/0

76/0<= /span>

76/0<= /span>

24/0<= /span>

56/23=

44/7<= /span>

78/5<= /span>

84/1<= /span>

62/7<= /span>

ژا&#= 1606;ويه

255/0

745/0=

74/0<= /span>

26/0<= /span>

94/22=

06/8<= /span>

18/5<= /span>

8/1

98/6<= /span>

فو&#= 1585;يه

29/0

71/0<= /span>

713/0=

287/0=

20

8

18/5<= /span>

1/2

26/7<= /span>

ما&#= 1585;س

34/0

66/0<= /span>

66/0<= /span>

34/0<= /span>

46/20=

54/10=

54/4<= /span>

33/2<= /span>

88/6<= /span>

آو&#= 1585;يل

27/0

73/0<= /span>

72/0<= /span>

28/0<= /span>

6/21<= /span>

4/8

62/5<= /span>

15/2<= /span>

77/7<= /span>

مه

23/0

77/0<= /span>

77/0<= /span>

23/0<= /span>

87/23=

13/7<= /span>

5/6

9/1

4/8

ژو&#= 1574;ن

076/0

924/0=

926/0=

074/0=

7/28<= /span>

3/2

3/21<= /span>

69/1<= /span>

23

 

 =

2-4- سيك&#= 1604; هوايي

مجموع دوره‌هاي بارز و پي‌در= 662;ي خشك و تر كه با عنوان سيكل هوايي ناميد= 07; مي‌شود، در ستون آخر جداول شمار= 7;
(5 تا 9) نشان د= اده &#= 1588;ده است. بديهي است كه بر اساس نتايج بدست آمده طولاني‌تري = 6; سيكل‌ها مربوط به ماه= 204;هاي
 خشك و ت= ر است و كوتاه‌= 578;رين اين دوره‌ها نيز در ماه‌ه= 575;ي مرطوب  نظير فوريه = 608; مارس مشاهده = 605;ي‌گردد. به لحاظ ايستگاهي هم ايستگاه‌ها¡= 0; بربرقلعه و بيرجند به ترتيب داراي = 603;مترين و بيشترين سيكل‌هاي هوايي مي‌با= 88;ند.

 

2-5- دور&#= 1607; هاي خشك n روزه

دورة= خش= ك همان طورك= ه قبلاً ذكر شد<= /span>، به دوره هاي داراي بارش كمتر از 1/0 ميلي= ; مت&= #1585; و يا كلّاً فاقد بارش اطلاق
&#= 1605;ي شود. در بررس= ي نتايج دوره‌= 07;اي خشك مشخّ= ص ش= د كه فراواني دوره‌هاي يك تا ده روزه در &= #1607;مة ايستگاه‌ها = 08; ماه‌هاي مور= 83; مطالعه از بيشترين فراواني برخوردار است و به تدري= ج تا دوره‌هاي طولاني تر از تعداد فراواني‌ها¡= 0; مربوطه كاست= 07;
&#= 1605;ي شود.

در اين بخش فقط نتاي= 580; بدست آمده براي ايستگا= 07; مشهد به عنوان نمونه در جدو= 604; شمارة (10) آورده شده اس= 578; كه به تفسير نتايج آن مي‌= 662;ردازيم. نتايج ساير ايستگاه‌ها نيز روند مشابهي را نشان مي‌دهد كه جهت پيشگيري از طولاني شدن بحث از ذكر آن&= #1607;ا صرفنظر مي‌گ= 85;دد.

بررسي ماهانة نتاي= ج (جدول شمارة= 10) نشان مي‌دهد كه &#= 1575;يستگاه مشهد در پر باران‌ترين ماه خود يعني مارس كه به= طو&= #1585; متوسّط حدود 18/57 ميلي مت&= #1585; بارش دريافت مي كند، طبق بر آورد انجا= 605; شده طيّ س= ي &#= 1587;ال، 120 دورة‌ خشك يك روزه، 100 دور= ;ة‌ خشك دو روزه، 84 دورة‌ خشك سه روزه داشته است؛ در حالي كه دوره‌هاي دراز مدّ= ت 29š= 8; 30 و 31 روزة آن هž= 5; كدام فقط يك بار اتّفاق افتاده است. ام= ّا د= ر همين زمان در ماه اكتبر به &#= 1593;نوان يكي از ماه‌ه= 575;ي كم باران ايستگاه كه متوسّط بارش سي سا&= #1604;ة آن= 93/8 ميلي متر بوده است، 60 دورة‌ يك روزه، 56 دورة‌ د= و روزه، 52 دورة‌ س= ه روزه و…  را تجربه كرده و فراواني دور= 07;‌ هاي 31، 30، 29 روزة آن= به &#= 1578;رتيب 8 ، 7 ،7 دوره بود= 07; است. اين امر از آنجا ناشي مي شود كه در ماه‌ها و ايستگاه‌ها¡= 0; مرطوب تر تعداد دفعات= 10; كه بارش با آستانة بالاتر از حدّ مورد نظر و= صر&= #1601;نظر از اين كه چه مقدار افزو = 6; از آستانة 1/0ميليمتر رخ مي دهد، بيشتر است. در نتيجه تعداد دوره‌ هاي خش= 603; كوتاه مدّ= ت بيشتر از دور= 607;‌ هاي دراز مدّت است و حال آن كه در ماه‌ها و ايستگاه هاي خشك‌تر به دليل آن كه تعداد دفعات بارش صورت گرفته كمتر است، در نتيجه تكرار دوره هاي خشك كوتاه مدّ= ت كاهش يافته و به فراواني دوره‌ هاي ميان مدّ= ت و دراز مدّ= ت افزوده مي شود.

بررسي نتايج حاصل ا= 586; رابطة رگرسيوني برقرار شده= مي&= #1575;ن مقادير مشاهده و بر آورد شدة= دوره‌ هاي خش= 603; ايستگاه مشه= 83; جهت سنجش ميزان دقّ= ت رابطة (8) در محاسبة دوره= ;‌ هاي خشك نشان مي‌دهد كه ميزان دقّ= ت و اطمينان مور= 83; نظر براي تقريباً همة ما= ه‌ها به استثناء ژوئن بالاتر از 99% است.

 

2-6- ارزيابي دورة برگشت دوره هاي خشك=        

دورة برگشت دوره‌هاي خش= 03; با استفاده ا= 586; رابطة= (9) براي ماه هاي مورد مطالعه محاسبه شدكه نتايج آ= ن در نمودارها= 10; شمارة <= span lang=3DFA style=3D'font-size:13.0pt;font-family:"B Zar";mso-bidi-language:F= A; font-weight:normal'>(1 تا 8) آورده شد= 07; است. به عنوان مثال طبق نمودار شمارة (8) در ما = 7; دسامبر در تمام ايستگا= 07; ها بازگشت دو= 585;ه‌هاي خشك يك تا پان&#= 1586;ده روز كمتر از پنج سال مي‌باشد. هر چه به دوره&#= 8204;هاي خشك طولاني‌= 78;ر مي‌رسيم، دورة برگشت آنها نيز طولاني‌تر م= 10;‌شود. اين روند را در مورد تمام ماه‌ها و ايستگاه ها م= 610;‌توان شاهد بود.
 =

 

 

 

<= o:p> 

<= o:p> 

<= o:p> 

<= o:p> 

<= o:p> 

<= o:p> 

<= o:p> 

<= b>ج= ;دول 10- فراواني دوره‌هاي خش= 03; شمارش و برآورد شدة ايستگاه مشهد

دسا= 605;بر

نوا= 605;بر

اكت= 576;ر

ژوئ= 606;

م= 607;

آور= 610;ل

مار= 587;

فور= 610;ه

ژان= 608;يه

ماه=

ب= 585;آورد

شمار= ;ش

ب= 585;آورد

شمار= ;ش

ب= 585;آورد

شمار= ;ش

ب= 585;آورد

شمار= ;ش

ب= 585;آورد

شمار= ;ش

ب= 585;آورد

شمار= ;ش

ب= 585;آورد

شمار= ;ش

ب= 585;آورد

شمار= ;ش

ب= 585;آورد

شمار= ;ش

رو= ز

120

124

77

67

60

64

36

41

120

122

141

142

155

161

130

128

124

120

1

100

99

69

64

56

56

35

32

100

101

108

111

111

117

100

97

102

100

2

84

81

63

60

52

53

33

28

84

86

83

84

80

78

77

82

84

86

3

71

69

57

58

48

47

32

25

70

65

64

68

57

52

30

65

69

70

4

59

56

51

55

45

42

31

23

51

54

49

50

41

37

46

51

57

55

5

50

48

46

50

42

39

29

22

49

46

38

33

30

28

36

38

46

43

6

42

35

42

42

39

35

27

21

41

38

29

27

22

20

28

30

38

36

7

35

28

38

38

36

32

27

21

34

32

23

23

16

14

21

20

31

27

8

30

25

34

35

33

30

26

20

29

23

16

18

11

6

17

14

26

24

9

25

21

31

30

31

29

26

20

24

21

13

11

8

5

13

10

21

19

10

21

20

28

29

29

27

24

19

20

17

10

7

6

4

10

7

18

15

11

18

20

24

25

27

25

23

19

17

15

8

6

5

4

8

6

15

11

12

15

16

23

23

25

23

22

18

14

13

6

6

4

3

6

5

12

10

13

13

13

22

21

23

21

21

17

45

12

5

4

3

3

5

3

10

7

14

11

12

18

19

22

20

20

16

10

10

4

2

2

2

4

3

8

7

15

9

11

16

14

20

19

19

16

9

7

4

1

2

2

3

2

7

6

16

8

11

16

14

19

17

18

15

7

6

3

1

1

2

2

0

6

5

17

7

10

14

13

18

15

18

15

6

6

3

1

1

1

2

0

5

4

18

6

8

13

13

16

14

17

15

5

5

2

1

1

1

2

0

4

2

19

5

8

12

13

15

13

16

14

5

5

2

1

1

1

2

0

3

1

20

4

7

11

12

14

12

16

14

4

4

2

1

1

1

2

0

3

0

21

4

7

10

12

13

11

15

13

3

4

2

1

1

1

2

0

2

0

22

3

5

9

11

12

11

14

12

3

4

1

1

1

1

1

0

2

0

23

3

4

8

10

12

10

14

12

3

4

1

1

1

1

0

0

2

0

24

3

4

7

8

11

10

13

12

2

3

1

1

1

1

0

0

2

0

25

2

3

7

7

10

9

13

11

2

3

1

1

1

1

0

0

1

0

26

2

3

7

6

9

9

12

11

2

2

1

0

0

0

0

0

1

0

27

2

2

6

5

8

9

12

11

2

2

1

0

0

0

0

0

1

0

28

2

1

5

4

8

8

11

10

2

1

1

0

0

0

 =

 =

1

0

29

2

0

5

4

7

8

11

10

2

1

1

0

0

0

 =

 =

1

0

30

1

0

 =

 =

7

8

 =

 =

1

1

 =

 =

0

0

 =

 =

1

0

31

99/0

99/0

99/0

94/0

99/0

99/0

99/0

99/0

99/0

R= ­­­*<= /span>

R­­­*=3D ضريب همبستگ= 10; بين فراوانيR= 04;هاي مشاهده و برآورد شده<= span lang=3DAR-SA style=3D'font-size:12.0pt;font-family:Mitra'>

 

 

 

 
 

 

 

 

 

             =

 

 

 

 

 

نت&#= 1610;جه  <= /i>

جهت بررسي شرايط كلّي خشكسالي حاك= 05; بر منطقة خراسان ب= 607; روش گيبس-ماه= 585; و با استفاده از داده هاي ماهانةّص شدن ويژگي هاي سا= 604; هاي مورد مطالعه از 1968 تا 1997 خصوصي= ّات دوره هاي خشك كوتاه مدّت كه براي مسائل كشاورزي از جمله دوره ها= 610; آبياري محصولات زراعي مهمّ اند، مور= 583; تحقيق قرار گرفت. اين كار نيز با داده هاي بارش روزانةدر بررسي وضعيّت خشكسالي هاي منطقه، شراي= 91; ايستگاه‌ها¡= 0; مختلف از نظر ميزان بارش دريافتي مشخّص و در سه گروه با شرايط خشكسالي، ترسالي و شرا= 610;ط نرمال دسته بندي گرديد. ضمن آن <= span lang=3DAR-SA style=3D'font-size:13.0pt;line-height:120%;font-family:"B Zar"= '>كه سال   عنوان خشك ترين و مرطوب ترين سال هاي اين دورة آماري مشخّص شدند.

از بررسي ويژگي هاي دوره هاي خشك كوتاه مدّت به روش زنجيرة ماركف مرتبةّل نيز نتايج ذي= 604; بدست آمد:

-      ارزي&#= 1575;بي روزهاي متوالي خشك نشان داد كه احتمال وقوع اين پديده هيچگا= 07; از 80% كمتر نيست= ;. علاوه بر اين هيچيك از ايستگاه‌= 07;اي منطقه احتما= 04; بالاتر از 50% براي وقوع دو روز تر متوال= 610; را تجربه نكرده اند.

-      مقاي&#= 1587;ة مقادير احتم= 75;لات سادة وقوع روزهاي خشك و تر در هر ماه با احتمالات اق= 04;يمي همان ماه نشا= 606; داد كه -         بيشت&#= 1585;ين مقدار فراواني روزهاي خشك د= 585; دورةبيست= -      با بررسي طول دوره هاي خشك براي ايستگا= 07;‌هاي مختلف مشخّص شد كه حدّا= 02;ل و حدّا= 03;ثر طول اين دوره ها به ميزان   ة بجنورد و بيرجند مربو= 91; مي شود.

-         رابطة رگرسيوني برقرار شده ميان مقادير مشاهده (شمار= 588; شده) و برآورد شدة دوره هاي خشك ايستگاه مشه= 83; به ع= 06;وان نمونه نشان داد كه دقّت مورد نظ= 585; براي تقريباً همة ماه‌ها ب= 607; استثناي ژوئ= 06; بالاتر از 99% است كه نشان دهندةّت بالاي اين رو= 588; در تعيين احتمالات وقوع دوره ها= 610; خشك مي باشد.

-      ارزي&#= 1575;بي دورةك&#= 1607; بيشترين اختلافات ماهانه و تفاوت هاي بي= 606; ايستگاهي را مي توان در بررسي دوره هاي  برگشت دوره هاي خشك طولاني مدّت شناساي= 10; كرد؛ چرا كه وقوع دوره هاي كوتاه مدّت تقريباً در تمامي نقاط استان روندهاي مشابهي را نشان مي‌دهد.

 

 

 

 

 

منابع <= /span>و مآخذ : =

1-&n= bsp;   جعفري بهي، خدابخش(1378)، تحلي= ل آماري دوره هاي تر و خشك بارندگي در چند نمونه اقليمي ايرا= 06; با استفاده ا= 586; زنجيره مارك= 01;، پايان نامه كارشناسي ارشد هوا شناسي كشاور= 86;ي، دانشگاه تهران.

2-&n= bsp;   خوش اخلاق،= فرامرز(1377)، تحقيق در خشكسالي ها&= #1610; فراگير ايرا= 06; با استفاده ا= 586; تحليل هاي سي= 606;وپتيكي، پايان نامه دكتراي جغرا= 01;ياي طبيعي،دانش«= 1;اه تبريز.

3-&n= bsp;    رابرتس = 8;ن، جي. دبليو، نقش هوا شناس= 610; كشاورزي در توسعه كشاورزي و پروژه هاي سرمايه گذار= 10;. ترجمه كميته هواشناسي كشاورزي.=

4-     فرج زاده، منوچه= 85;(1374)، بررسي آماري خشكسالي در ايران،= پايان نامه دكتراي جغرافياي طبيعي دانشگاه ترب= 10;ت مدرس.

5-    مشكا= ني، محمدرضا(1363)، بررسي احتما= 04; تواتر روزها= 10; خشك بابلسر ا= 586; ديدگاه بيز تجربي،= مجله
علوم آب شماره3.

6-     مظفري، غلامعلي(1380)، ارزيابي قابليت هاي محيطي كشت گندم ديم در منطقه كرمانشاه،= پايان نامه دكتراي جغرافياي طبيعي دانشگاه ترب= 10;ت مدرس.

7-&n= bsp;    هاشمي فريدون(1347)، تجزي= ه و تحليل استاتيكي از بارندگي سالانه، ماهانه، و روزانه تهرا= 06;، تحقيقات علم= 10; هواشناسي كل كشور.

8-&n= bsp;    Eull Moon, S., Boom Ryoo, S.= ,Gi kwon, J. 1994. A Markov chain model for daily precipitation occurrence in <= st1:place w:st=3D"on">South korea, International Jornal of climatology.14,1009-1016.<= /p>

9-&n= bsp;    Hudson, G., Brine, V.R.,1999. A me= thod of land evaluation including year to year weather variability, Agricultural= and forest meteorology. 101(2000) 203-216

10- =   Katz, R.w., 19= 77. precipitation as a chain-dependent process, Journal of applied meteorology.= 16, 671-676.

11- =   Martin vide, J= ., Gomez, L.1998. Regionalization of peninsular Spain based on the length of = dry spells, International Jornal of climatology. 19,537-555.<= /span>

12- =   Stern, R.D., 1= 981. Computing a probability distribution for the start of the rains from a Mark= ov chain model for precipitation, Journal of applied meteorology. 21,420-423.<= o:p>

13- =   Subramaniam, A= .R., Sanjeeva rao, p., 1986. Dry spells sequencess in south coastal Andhra , Mau= sam. 40-1,57- 60

14- =   Victor, U.S., Sastry,P.S.N.1979. Dry spell probablity by Markov chain model and its application to crop development stages ,Mausam. 30-4,479-484.

15- =   Wilks, D.S.1995.statistical methods in the atmospheric sciences. Accademic press. = INC.

16-  Wilks, D.S.1998. Interna= tional variability and extreme-value characteristics of several stocastic daily precipitation models, Agricultural and forest meteorology. 98-99, 547-554. =


* در تاريخ تدوين مقاله استان خراسان بزرگ به سه استان قعلي تقسيم نگرديده بود. =

Gibbs & Maher - [1]=

 - Roman 2

 - Krishnan= 3

- Gabriel&Neuman 4

- Sastry & Kapoor 5

- Clarke & Karras 1<= /span>

- Martin–vide & Gomez 2

- D.S.Wilks 3

------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image008.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlh/gAwAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAMAAgD3 ACoAgAAAAAAAAAL/hI+pGd0Lo5y0Kues3rz7D35BSJbbaKbqypZoC4dvTNc2OSP5be/8DwzuMsFe 8Yis+QDLpMsJjcogTamnas1ql9jL4yH7diljrTnJvaLKEjCbeo6f0wcMxlvHvd4LvvwfQ3eig0M4 BYiIBsex92Tgd5EoWSRo0Vj4aAI5ydnhQ2QJGgbm2GlKZceYsrmownpqNvP2mufaQgtrJTuoh/tI upornGloOcx7fLqLnDzh2yx0x2AH/JxoDX1Diw3IDfslMgLcKpLtzJJ6zbQeThyBRV1t3nZb+3ep Q41q31c6H7limRyBnop5GafqX7+ABk+I8+YOYbxWa/ZYgxiHGz41ue4YMmG1cU3HQ3PQMRT1K12f ja7AhRsnkp0/XQgxBdPUsF65hTFnZtHoEZVKgOxI1bwCoknMZxht3sQJtWhETUedHV36FE/TdxyH rKrq0OjUe24uLgIbqOBHolsAslRIzt5WrnUmFvtU0i0/uHFl+gUyK+ffKCiljuTLNuLcvvR+LZRk FC1cr2uRBK6cGHG2IS4pSa4rjrHmZFUWm3w8ejPdTkpTz+Py+edV1+ZMS7FNW5u0zUNzIykAADs= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image018.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhFAAYAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIACAAO AAwAgAAAAAAAAAIdhIOJdgH+mGQQzkNvjpr7V1kLl0hj1WHfhaat6xQAOx== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image030.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhvQAvAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAMABAC2 ACgAgAAAAAAAAAL/hI+py+0Po5y0WhXC3bz7D4aAJpbmiXrZyJBp6Y7rkc1bHLo4t8s9+xL1cL9K 8UKqCTGs2uwYpPxswA90QoQhNMVrNDKsijtecKIsiXGH1K9lWkUbntn5qr3lzpnGe939BQckt6e3 dZa0kJR4dsO4BxioSANJ46SUV6lps6ND2Wh5yfapGZkSVvj2SCr2F8dndMhqioLa9DbbmqvjCRpb Skj7K2s5bEjaC0rViVs61uek1WzHOd2mhvmp5Jqd1u08/YyEZ2aqhuXL0xAMC47U8sB+Qwxh+w6v 0k6G7yA/7AOGnLxv7v4VNJhLmMKFu+KJskePoURhENWFEjUxIyBmhjn45XkIMqTIkSRLmjyJcqSz KyAnudQIMwoRfy/TxbwJA2MxfwTF4fz5oifQoUQP0SyKNNKxpEyBrmkKNarUU1OrZjxqNSsGP+v6 LdUKdt2qiLLIhT0rg1VIYljRDj1XU63buci6wjJL12qyuJDw5q0arZ+iO3/dtvVZWOrhw4klCpXi 11QBADs= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image032.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhZAAoAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAMABgBe AB4AgAAAAAAAAALWhI+py+0anpy01hBxhE3bD4KYsSUlMgJnyLbmcWoyCrv2Xa4kt99+mGPoNimg rPiTzISQke7SeyYXUqitOuW1sBRuFob8eFxe1fGLnpTTbOvjuILL5/S6/T5bt/edopMPKBIWSNih Ugj4x6SHeDVY86jmF0nVw/KUsRdjRdn1wgh0KKpGc0XTiSOasRozVnPB+kqYqUpEQhQnZmsZaLur CvaCciY8Cpp6+EubXOxpeUxWGlQ7yqskW63pdzuZ2aq3hN1oLQxNnj2OtSlSOT4s5Yr+FlZWAAA7 ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image036.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhGAAdAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIABQAS ABQAgAAAAAAAAAIrjI+gy9EMl5MxTnUrfpr6DmSZJoLb15WQgSGuN5IcqNJzesuoftq7HktNCgA7 ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image038.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhFQAcAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIABQAQ ABQAgAAAAAAAAAIojI+gq8HOImxRvnrXxHvXjmlZCIZAeSEqdJifa8GiTNGnfdueu5NGAQA7 ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image040.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhFwAYAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIABQAR AA8AgAAAAAAAAAIljA+pq9EMgXuRplmlzQdnDX6hV2HkZS7k1BlNGn6seNX0TEtOAQA7 ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image042.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhFAAXAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIABQAQ AA8AgAAAAAAAAAIjjA+pm6HOGGxxTXDjzBpVS33PKGKktYESdmwXJ8KfXNGSUQAAOw== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image044.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhFQAYAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIABQAP AA8AgAAAAAAAAAIijG+gu8HOXpyNUgjwRVZhPYEd+H2S5yEcmnWsGEHwOT9OAQA7 ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image046.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhEwAXAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIABQAP AA8AgAAAAAAAAAIgjG+gu8HOXpyNUgjwRVZhPYEd+H2ShHBnV7Gtm8GZUQAAOw== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/header.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="us-ascii"

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/oledata.mso Content-Transfer-Encoding: base64 Content-Type: application/x-mso 0M8R4KGxGuEAAAAAAAAAAAAAAAAAAAAAPgADAP7/CQAGAAAAAAAAAAAAAAABAAAAAQAAAAAAAAAA EAAAAgAAAAIAAAD+////AAAAAAAAAAD///////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// ///////////////////////////////////////////////////////////////////////////9 ////BgAAABgAAAAEAAAABQAAAAcAAAAKAAAACAAAAAkAAAALAAAADgAAAAwAAAANAAAADwAAABIA AAAQAAAAEQAAABMAAAAWAAAAFAAAABUAAAAXAAAAHAAAABkAAAD+////GgAAABsAAAAdAAAAIQAA AB4AAAAfAAAAIAAAACIAAAD+////IwAAAP7///////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// /////////////////////////////////////////////////////////////////////////1IA bwBvAHQAIABFAG4AdAByAHkAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAWAAUA//////////8IAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADDW/gGu7MUB AwAAAEAxAAAAAAAAXwAxADEAOQAzADgAOAAzADgAOAA0AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAABgAAgH///////////////8AAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAeQEAAAAAAABfADEAMQA5ADMAOAA4ADMAOAA4ADUAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAGAACAQEAAAADAAAA/////wAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAYAAAB3AQAAAAAAAF8AMQAxADkAMwA4ADgAMwA4 ADgANgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAYAAIB//////// ////////AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADAAAALYBAAAAAAAAAQAA AAIAAAADAAAABAAAAAUAAAD+////BwAAAAgAAAAJAAAACgAAAAsAAAD+////DQAAAA4AAAAPAAAA EAAAABEAAAASAAAA/v///xQAAAAVAAAAFgAAABcAAAAYAAAAGQAAAP7///8bAAAAHAAAAB0AAAAe AAAAHwAAACAAAAD+////IgAAACMAAAAkAAAAJQAAACYAAAAnAAAA/v///ykAAAAqAAAAKwAAACwA AAAtAAAALgAAAP7///8wAAAAMQAAADIAAAAzAAAANAAAAP7///82AAAANwAAADgAAAA5AAAAOgAA AP7///88AAAAPQAAAD4AAAA/AAAAQAAAAP7///9CAAAAQwAAAEQAAABFAAAARgAAAP7///9IAAAA SQAAAEoAAABLAAAATAAAAP7///9OAAAATwAAAFAAAABRAAAAUgAAAP7///9UAAAAVQAAAFYAAABX AAAAWAAAAP7///9aAAAAWwAAAFwAAABdAAAAXgAAAP7///9gAAAAYQAAAGIAAABjAAAAZAAAAP7/ //9mAAAAZwAAAGgAAABpAAAAagAAAP7///9sAAAAbQAAAG4AAABvAAAAcAAAAP7///9yAAAAcwAA AHQAAAB1AAAAdgAAAP7///94AAAAeQAAAHoAAAB7AAAAfAAAAP7///9+AAAAfwAAAIAAAAAADAAA eJy7cF7wwcKNUg8Z0IAdAzPDv/+cDGxIYoxQDAYCDAxMUP6/////w4T/j4IhBf4CMQs0DmF4FIwc EMSQD4QlDAoMrgx5QLqIoRK9KMALxBhY4XkeVB4wnWMCix+ASLshqzXgnvV/7ZujjMxAtgMjrEzx Z8hhSCXJTmTAxcDEiOwfYvWJMMDsdwb6P5ehAOiOJIYsku0XAtoP8grIT8TaD1KfBmUzQ+31BIZ+ GtAl5NgPspeFBPtBboWV6/+g8Taa/0cmAKZFJg609PHgiQLR6Y8RmHKYuSBpDz3viwMJ38zkovzi /LQSBdfC0sSSzPw8BWM9AwYeoJRLMFyMgRvIh3H0jBm+WG4qJNYFzAwsRLsWE8gwgNox2w5KQfkv iiUYzhhKQExmZGTm4mJkajnAzMzPyMDNyNRhyMAgSIFtgw+4MhQylDIkAkv+TGDpkwesB/ygvDKi SmUFYOghpydi7ATFlxllzkYBpNpPbTCU7QcA7vg3igAAAAAAAAAADAAAeJy7cF7wwcKNUg8Z0IAd AzPDv/+cDGxIYoxQDAYCDAxMUP6/////w4T/j4IhBf4CMQs0DmF4FIwcEMSQD4QlDAoMrgx5QLqI oRK9KMALxBhY4XkeVB4wnWMCix+ASLshq1UwX/h/7ZujjMxAtgMjrEzxZ8hhSCXJTmTAxcDEiOwf YvWJMMDsdwb6P5ehAOiOJIYsku0XAtoP8grIT8TaD1KfBmUzQ+31BIZ+GtAl5NgPspeFBPtBboWV 6/+g8Taa/0cmAKZFJg609OHBIsJALGAEphxmLkjaQ8/74kDCNzO5KL84P61EwbWwNLEkMz9PwVjP gIEHKOUSDBdj4AbyYRw9Y4YvlpsKiXUBMwML0a7FBDIMoHbMtoNSMAFNMQYWFjGIyYyMzFxcjEwt B5iZ+RkZuBmZOgwYGAQpsG3wAVeGQoZShkRgyZ8JLH3ygPWAH5RXRlSprAAMPeT0RIydoPgyo8zZ KIBU+6kNhrL9AKnXM/0AAAAAAAAAAAAADAAAeJztVTFLw0AU/u7SCqZibRAFcShOilCUTg662Aod rKK/oIqFiiZNbQUdWyj5DW6Cq6D+AhfX6g9w0N3R1cZ3yaXEDpK0OlT7hcvde+/uvnfv7t49PSZe Lm9nXtGFNSho26MY8emYLA4mAC7ltm3bntoeYqDwQSUi99ArQ/wf7MCgr4okstCpruCsOxV8iylE O3de5APe4o7+3jVv+PveWC37+u2BKcLOvJyyhSMchOL0QwVn/vUEHTcJj3+d1n+MMvmxh8PQ/Brx i6WINQXlF/2Lsq1I3hxFv0ie9MIveCMh+IWvEdluy33z7n6U2iNSHuLvg7nPeM9gdFIU1T173Xd/ mn6bpf2KcWIUq8msWStUS4aeTKeWMEamzG5HhxjJnpBK433lzgzqgdKP+5iFCEDx2ZKydZHD9nnO nZlRqlKZ1shAiTPEqKUDCai8uQpuLYM3F6GMUxB4fR5aI08KbU504vUFkstUp6g2IezuAGEvO3Yl DsQSzpxCLcwEQVd2Jhbjfh9ZmKihQJm/RNlHp3cgL6XTQFk5SdHzn6cgnCL3XPXn9heE5f9pDDL/ JzRMQhUAAAAAAAAAAAAAAAwAAHicu3Be8MHCjVIPGdCAHQMzw7//nAxsSGKMUAwGAgwMTFD+v/// /8OE/4+CIQX+AjELNA5heBSMHBDEkA+EJQwKDK4MeUC6iKESvSjAC8QYWOF5HlQeMJ1jAosfgEi7 IaudkH/r/9o3RxmZgewGRliZ4s+Qw5BKkp3IgIuBiRHZP8TqE2GA2e8M9H8uQwHQHUkMWSTbLwS0 H+QVkJ+ItR+kPg3KZoba6wkM/TSgS8ixH2QvCwn2g9wKK9f/QeMNlvdZoexRMDIAI6QaRwEaN2Uw xHABRmBqYeaCpD30vC8OJHwzk4vyi/PTShRcC0sTSzLz8xSM9QwYeIBSLsFwMQZuIB/G0TNm+GK5 qZBYFzAj2iRkABkGUADoXU2B8s9UeTJItHpCTGYEFlVcjELNIQzM/IwM3EBWHgODIANfADEAMQA5 ADMAOAA4ADMAOAA4ADcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA GAACAQIAAAAGAAAA/////wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABMAAAC3 AQAAAAAAAF8AMQAxADkAMwA4ADgAMwA4ADgAOQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAYAAIB////////////////AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAGgAAALMBAAAAAAAAXwAxADEAOQAzADgAOAAzADgAOQAwAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABgAAgEFAAAABwAAAP////8AAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAhAAAAtAEAAAAAAABfADEAMQA5ADMAOAA4ADMAOAA5ADEA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAGAACAf////////////// /wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACgAAACzAQAAAAAAABdTmy0DMx/Q 80LNBQxMbdoMQs2FYJ4fA0gExGNq0mBg6jAEygopgVU1aQINYWDgFoSYAgEFDGAeSBFIMRBwoZpJ c+DKUMhQypAILPkzgaVPHrAe8IPyyogqlRWAoYecnoixE1RWNVDkalRAqv3UBkPZfgADpUU7AAAA AACQb9r/AAwAAHic7VZNSwJRFD3vjUWNUjmFRRgMrYogElduIigDiQxq3cIiwagZxzRoqUL0N/oD Qf2CENpWP6H2LVy0zem+cUbGIWKmj4Xokadz7rvzzr3z7rvO81P05fp29hUerEJCyxzFsMvG7GFh AuA2b5mm6ZjNAXoKHzRC9h46Y4D+wS50+pShIg2Nfku48LaCbxHDUOfMi37AH7llv29Pb7p9m/tV 3Lw9MImu15jTU3ZwgqNAmm7I4Mydj9/7puDor1P+pyhSHAc4DqyvkL5IReTkV1/45+1rydbN0NPP UyQ/0Re6oQD6Ilanr7fsfRuc//4E1SIf8dTHTCPO/dYfo8qR5Hbtec/+NH1tFw5L+pmeL6tpo5Ir F3RNTS6vIEJTG3sdG8LEHbKcxHvqzvAbgYSQX9cvEId4j4k05mze3IohMhlrr8yYJMuMVzMQQxpn IJIAomJyjJJX6kXwyyUodcNiWQiLYLy2AH6VoFll3vKqLdICQDhKbpqjXoTFhJNwJsjda/470jBQ QY46f4G6j0b/A1mbnfvqyio9PXc9+dEU+5X6XdhdCKr/1+hl/U+X5UWr/////////////////wAM AAB4nLtwXvDBwo1SDxnQgB0DM8O//5wMbEhijFAMBgIMDExQ/r/////DhP+PgiEF/gIxCzQOYXgU jBwQxJAPhCUMCgyuDHlAuoihEr0owAvEGFjheR5UHjCdYwKLH4BIuyGr/XCumWHdm6OMzEC2AyOs TPFnyGFIJclOZMDFwMSI7B9i9YkwwOx3Bvo/l6EA6I4khiyS7RcC2g/yCshPxNoPUp8GZTND7fUE hn4a0CXk2A+yl4UE+0FuhZXr/6DxNpr/RyYApkUmDrT0IXFEhonY9McITDnMXJC0h573xYGEb2Zy UX5xflqJgmthaWJJZn6egrGeAQMPUMolGC7GwA3kwzh6xgxfLDcVEusCZgYWYpViATIMoHYMzyEp KP9DiBhDyQYxiMmMjMxcXIxMjUEMzPyMDNxAlgEDgyDUWj6g54WaCxiY2rQZhJoLwTw/BpAIiMfU pMHA1GEIlBVSAqtq0gQawsDALQhUlgezvYABzAMpAikGAi5UM2kOXBkKGUoZEoElfyaw9MkD1gN+ UF4ZUaWyAjD0kNMTMXaC4suMMmejAFLtpzYYyvYDAALBRm////////////////8ADAAAeJy7cF7w wcKNUg8Z0IAdAzPDv/+cDGxIYoxQDAYCDAxMUP6/////w4T/j4IhBf4CMQs0DmF4FIwcEMSQD4Ql DAoMrgx5QLqIoRK9KMALxBhY4XkeVB4wnWMCix+ASLshq30g0caw7s1RRmYg24ERVqb4M+QwpJJk JzLgYmBiRPYPsfpEGGD2OwP9n8tQAHRHEkMWyfYLAe0HeQXkJ2LtB6lPg7KZofZ6AkM/DegScuwH 2ctCgv0gt8LK9X/QeBvN/yMTANMiEwda+pA4IsNEbPpjBKYcZi5I2kPP++JAwjczuSi/OD+tRMG1 sDSxJDM/T8FYz4CBByjlEgwXY+AG8mEcPWOGL5abCol1ATMDC7FKsQAZBlA7hueQFJTPkSnG8CRL AmIyIyMzFxcjU2MQAzM/IwM3kGXIwCAItZYP6Hmh5gIGpjZtBqHmQjDPjwEkAuIxNWkwMHUYAmWF lMCqmjSBhjAwcAsCleXBbC9gAPNAikCKgYAL1UyaA1eGQoZShkRgyZ8JLH3ygPWAH5RXRlSprAAM PeT0RIydoPgyo8zZKIBU+6kNhrL9AFT7RQb/////////////////AAwAAHicu3Be8MHCjVIPGdCA HQMzw7//nAxsSGKMUAwGAgwMTFD+v////8OE/4+CIQX+AjELNA5heBSMHBDEkF8AMQAxADkAMwA4 ADgAMwA4ADkAMgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAYAAIB BAAAABAAAAD/////AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAALwAAAHgBAAAA AAAAXwAxADEAOQAzADgAOAAzADgAOQAzAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAABgAAgH///////////////8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAA1AAAAegEAAAAAAABfADEAMQA5ADMAOAA4ADMAOAA5ADQAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAGAACAQkAAAALAAAA/////wAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAADsAAAB6AQAAAAAAAF8AMQAxADkAMwA4ADgAMwA4ADkANQAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAYAAIB////////////////AAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQQAAAHgBAAAAAAAAD4QlDAoMrgx5QLqI oRK9KMALxBhY4XkeVB4wnWMCix+ASLshq33Q2cGw7s1RRmYg24ERVqb4M+QwpJJkJzLgYmBiRPYP sfpEGGD2OwP9n8tQAHRHEkMWyfYLAe0HeQXkJ2LtB6lPg7KZofZ6AkM/DegScuwH2ctCgv0gt8LK 9X/QeBvN/yMTANMiEwda+pA4JsNEvP5//5m5IGkPPe+LAwnfzOSi/OL8tBIF18LSxJLM/DwFYz0D Bh6glEswXIyBG8iHcfSMGb5YbipEdhFu+0GpmYWCVocMA6gdw3NICmqTQawYQwkQg/MJIyMzFxcj U6MrAzM/IwM3kGXAwCCI1z1DDbgyFDKUMiQCS/5MYOmTB6wH/KC8MqJKZQVg6CGbR0z5AyqrzIhR SCQg1X5qg6FsPwBlL3lZAAAAAAAAAAAADAAAeJy7cF7wwcKNUg8Z0IAdAzPDv/+cDGxIYoxQDAYC DAxMUP6/////w4T/j4IhBf4CMQs0DmF4FIwcEMSQD4QlDAoMrgx5QLqIoRK9KMALxBhY4XkeVB4w nWMCix+ASLshq33wq4th3ZujjMxAtgMjrEzxZ8hhSCXJTmTAxcDEiOwfYvWJMMDsdwb6P5ehAOiO JIYsku0XAtoP8grIT8TaD1KfBmUzQ+31BIZ+GtAl5NgPspeFBPtBboWV6/+g8Taa/0cmAKZFJg60 9OFwQoHoepwRmHKYuSBpDz3viwMJ38zkovzi/LQSBdfC0sSSzPw8BWM9AwYeoJRLMFyMgRvIh3H0 jBm+WG4qRHYRbvtBqZmFglaHDAOoHcNzSApq04ajYgw8wmKQfMLIyMzFxcjU6MrAzM/IwA1kGTIw COJ1z1ADrgyFDKUMicCSPxNY+uQB6wE/KK+MqFJZARh6yOYRU/6AyiozYhQSCUi1n9pgKNsPAB0o ei////////8ADAAAeJy7cF7wwcKNUg8Z0IAdAzPDv/+cDGxIYoxQDAYCDAxMUP6/////w4T/j4Ih Bf4CMQs0DmF4FIwcEMSQD4QlDAoMrgx5QLqIoRK9KMALxBhY4XkeVB4wnWMCix+ASLshqz1QMIVh 3ZujjMxAtgMjrEzxZ8hhSCXJTmTAxcDEiOwfYvWJMMDsdwb6P5ehAOiOJIYsku0XAtoP8grIT8Ta D1KfBmUzQ+31BIZ+GtAl5NgPspeFBPtBboWV6/+g8Taa/0cmAKZFJg609OFwQoHoepwRmHKYuSBp Dz3viwMJ38zkovzi/LQSBdfC0sSSzPw8BWM9AwYeoJRLMFyMgRvIh3H0jBm+WG4qRHYRbvtBqZmF glaHDAOoHcNzSBZq0wdvMQYeYTFIPmFkZObiYmRq9GQAYWZ+RgYgx5CBQRCvk4YUcGUoZChlSASW /JnA0icPWA/4QXllRJXKCsDQQzaPmPIHVFZZEqOQSECq/dQGQ9l+AJ7fdyP///////8ADAAAeJy7 cF7wwcKNUg8Z0IAdAzPDv/+cDGxIYoxQDAYCDAxMUP6/////w4T/j4IhBf4CMQs0DmF4FIwcEMSQ D4QlDAoMrgx5QLqIoRK9KMALxBhY4XkeVB4wnWMCix+ASLshqz3wcBrDujdHGZmBbAdGWJniz5DD kEqSnciAi4GJEdk/xOoTYYDZ7wz0fy5DAdAdSQxZJNsvBLQf5BWQn4i1H6Q+DcpmhtrrCQz9NKBL yLEfZC8LCfaD3Aor1/9B4200/49MAEyLTBzoCeSmDBPx+v/9Z+aCpD30vC8OJHwzk4vyi/PTShRc C0sTSzLz8xSM9QwYeIBSLsFwMQZuIB/G0TNm+GK5qRDZQbjtB6VmFgpaHTIMoHYMzyEpqE0fQsQY SjaIQfIJIyMzFxcjU2MQAzM/IwM3kGXAwCBIyElDCrgyFDKUMiQCS/5MYOmTB6wH/KC8MqJKZQVg 6CGbR0z5AyqrzIhRSCQg1X5qg6FsPwBBm3e0//////////8ADAAAeJy7cF7wwcKNUg8Z0IAdAzPD v/+cDGxIYoxQDAYCDAxMUP6/////w4T/j4IhBf4CMQs0DmF4FIwcEMSQXwAxADEAOQAzADgAOAAz ADgAOQA2AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABgAAgEKAAAA DgAAAP////8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABHAAAAeAEAAAAAAABf ADEAMQA5ADMAOAA4ADMAOAA5ADcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAGAACAf///////////////wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AE0AAAB4AQAAAAAAAF8AMQAxADkAMwA4ADgAMwA4ADkAOAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAYAAIBDQAAAA8AAAD/////AAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAUwAAAHkBAAAAAAAAXwAxADEAOQAzADgAOAAzADgAOQA5AAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABgAAgH///////////////8AAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABZAAAAcQEAAAAAAAAPhCUMCgyuDHlAuoihEr0o wAvEGFjheR5UHjCdYwKLH4BIuyGrPfBwGsO6N0cZmYFsB0ZYmeLPkMOQSpKdyICLgYkR2T/E6hNh gNnvDPR/LkMB0B1JDFkk2y8EtB/kFZCfiLUfpD4NymaG2usJDP00oEvIsR9kLwsJ9oPcCivX/0Hj bTT/j0wATItMHOgJ5KYME/H6//1n5oKkPfS8Lw4kfDOTi/KL89NKFFwLSxNLMvPzFIz1DBh4gFIu wXAxBm4gH8bRM2b4YrmpENlBuO0HpWYWClodMgygdgzPISmoTRyZYgxPsiQg+YSRkZmLi5GpMYiB mZ+RgRvIMmRgECTkpCEFXBkKGUoZEoElfyaw9MkD1gN+UF4ZUaWyAjD0kM0jpvwBlVVmxCgkEpBq P7XBULYfAFk7dw7//////////wAMAAB4nLtwXvDBwo1SDxnQgB0DM8O//5wMbEhijFAMBgIMDExQ /r/////DhP+PgiEF/gIxCzQOYXgUjBwQxJAPhCUMCgyuDHlAuoihEr0owAvEGFjheR5UHjCdYwKL H4BIuyGr3aA9k2Hdm6OMzEC2AyOsTPFnyGFIJclOZMDFwMSI7B9i9YkwwOx3Bvo/l6EA6I4khiyS 7RcC2g/yCshPxNoPUp8GZTND7fUEhn4a0CXk2A+yl4UE+0FuhZXr/6DxNpr/RyYApkUmDrT0IXFJ hol4/f/+M3NB0h563hcHEr6ZyUX5xflpJQquhaWJJZn5eQrGegYMPEApl2C4GAM3kA/j6BkzfLHc VIjsItz2g1IzCwWtDhkGUDuG55AU1CaDWDGGEiAG5xNGRmYuLkamRlcGZn5GBm4gy4CBQZCQk4YU cGUoZChlSASW/JnA0icPWA/4QXllRJXKCsDQQzaPmPIHVFaZEaOQSECq/dQGQ9l+AI3Sdev///// /////wAMAAB4nLtwXvDBwo1SDxnQgB0DM8O//5wMbEhijFAMBgIMDExQ/r/////DhP+PgiEF/gIx CzQOYXgUjBwQxJAPhCUMCgyuDHlAuoihEr0owAvEGFjheR5UHjCdYwKLH4BIuyGr3aA9k2Hdm6OM zEC2AyOsTPFnyGFIJclOZMDFwMSI7B9i9YkwwOx3Bvo/l6EA6I4khiyS7RcC2g/yCshPxNoPUp8G ZTND7fUEhn4a0CXk2A+yl4UE+0FuhZXr/6DxNpr/RyYApkUmDrT0IXFFhol4/f/+M3NB0h563hcH Er6ZyUX5xflpJQquhaWJJZn5eQrGegYMPEApl2C4GAM3kA/j6BkzfLHcVIjsItz2g1IzCwWtDhkG UDuG55AU1KYNR8UYeITFIPmEkZGZi4uRqdGVgZmfkYEbyDJkYBAk5KQhBVwZChlKGRKBJX8msPTJ A9YDflBeGVGlsgIw9JDNI6b8AZVVZsQoJBKQaj+1wVC2HwA50nYkAAAAAAAAAAAMAAB4nLtwXvDB wo1SDxnQgB0DM8O//5wMbEhijFAMBgIMDExQ/r/////DhP+PgiEF/gIxCzQOYXgUjBwQxJAPhCUM CgyuDHlAuoihEr0owAvEGFjheR5UHjCdYwKLH4BIuyGrbbBbw7DuzVFGZiDbgRFWpvgz5DCkkmQn MuBiYGJE9g+x+kQYYPY7A/2fy1AAdEcSQxbJ9gsB7Qd5BeQnYu0HqU+Dspmh9noCQz8N6BJy7AfZ y0KC/SC3wsr1f9B4G83/IxMA0yITB8mpDgEYgSmHmQuS9tDzvjiQ8M1MLsovzk8rUXAtLE0syczP UzDWM2DgAUq5BMPFGLiBfBhHz5jhi+WmQmJdwMzAQoH7ZRhA7RieQ7JQ/gdvMQYeYTGIyYyMzFxc jEyNngwgzMzPyADkGDIwCFJg4SADrgyFDKUMicCSPxNY+uQB6wE/KK+MqFJZARh6yOmJGDtB8WVJ mbNRAKn2UxsMZfsBOdIz1QAAAAAAAAAAAAAAAAAAAAAMAAB4nLtwXvDBwo1SDxnQgB0DM8O//5wM bEhijFAMBgIMDExQ/r/////DhP+PgiEF/gIxCzQOYXgUjBwQxJBfADEAMQA5ADMAOAA4ADMAOQAw ADAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAGAACAAwAAAAUAAAA /////wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAF8AAABxAQAAAAAAAF8AMQAx ADkAMwA4ADgAMwA5ADAAMQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAYAAIB////////////////AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAZQAA AHcBAAAAAAAAXwAxADEAOQAzADgAOAAzADkAMAAzAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAABgAAgERAAAAEwAAAP////8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAABrAAAAdwEAAAAAAABfADEAMQA5ADMAOAA4ADMAOQAwADQAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAGAACAf///////////////wAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHEAAAB4AQAAAAAAAA+EJQwKDK4MeUC6iKESvSjAC8QY WOF5HlQeMJ1jAosfgEi7IattWL+OYd2bo4zMQLYDI6xM8WfIYUglyU5kwMXAxIjsH2L1iTDA7HcG +j+XoQDojiSGLJLtFwLaD/IKyE/E2g9SnwZlM0Pt9QSGfhrQJeTYD7KXhQT7QW6Flev/oPE2mv9H JgCmRSYOklMdAjACUw4zFyTtoed9cSDhm5lclF+cn1ai4FpYmliSmZ+nYKxnwMADlHIJhosxcAP5 MI6eMcMXy02FxLqAmYGFAvfLMIDaMTyHpKD8DyFiDCUbxCAmMzIyc3ExMjUGMTDzMzJwA1kGDAyC FNg2+IArQyFDKUMisOTPBJY+ecB6wA/KKyOqVFYAhh5yeiLGTlB8mVHmbBRAqv3UBkPZfgCcyTSX ZmRk5uJiZGo5wMzMz8jAAAwAAHicu3Be8MHCjVIPGdCAHQMzw7//nAxsSGKMUAwGAgwMTFD+v/// /8OE/4+CIQX+AjELNA5heBSMHBDEkA+EJQwKDK4MeUC6iKESvSjAC8QYWOF5HlQeMJ1jAosfgEi7 IattWL+OYd2bo4zMQLYDI6xM8WfIYUglyU5kwMXAxIjsH2L1iTDA7HcG+j+XoQDojiSGLJLtFwLa D/IKyE/E2g9SnwZlM0Pt9QSGfhrQJeTYD7KXhQT7QW6Flev/oPE2mv9HJgCmRSYOtPThwCLCQCxg BKYcZi5I2kPP++JAwjczuSi/OD+tRMG1sDSxJDM/T8FYz4CBByjlEgwXY+AG8mEcPWOGL5abCol1 ATMDC9GuxQQyDKB2DM8hKSifI1OM4UmWBMRkRkZmLi5GpsYgBmZ+RgZuIMuQgUGQAtsGH3BlKGQo ZUgElvyZwNInD1gP+EF5ZUSVygrA0ENOT8TYCYovM8qcjQJItZ/aYCjbDwANezRJLQeYmfkZGbgZ AAwAAHicu3Be8MHCjVIPGdCAHQMzw7//nAxsSGKMUAwGAgwMTFD+v////8OE/4+CIQX+AjELNA5h eBSMHBDEkA+EJQwKDK4MeUC6iKESvSjAC8QYWOF5HlQeMJ1jAosfgEi7IattUNjIsO7NUUZmINuB EVam+DPkMKSSZCcy4GJgYkT2D7H6RBhg9jsD/Z/LUAB0RxJDFsn2CwHtB3kF5Cdi7QepT4OymaH2 egJDPw3oEnLsB9nLQoL9ILfCyvV/0Hgbzf8jEwDTIhMHWvrg+CDHRGz6YwSmHGYuSNpDz/viQMI3 M7kovzg/rUTBtbA0sSQzP0/BWM+AgQco5RIMF2PgBvJhHD1jhi+WmwqJdQEzAwuxSrEAGQZQO4bn kBSUbxArxlACxGCTGRmZubgYmRpdGZj5GRm4gSwDBgZBCmwbfMCVoZChlCERWPJnAkufPGA94Afl lRFVKisAQw85PRFjJyi+zChzNgog1X5qg6FsPwCQOjQMj/uYhQhA8dmSAAwAAHicu3Be8MHCjVIP GdCAHQMzw7//nAxsSGKMUAwGAgwMTFD+v////8OE/4+CIQX+AjELNA5heBSMHBDEkA+EJQwKDK4M eUC6iKESvSjAC8QYWOF5HlQeMJ1jAosfgEi7IattUNjIsO7NUUZmINuBEVam+DPkMKSSZCcy4GJg YkT2D7H6RBhg9jsD/Z/LUAB0RxJDFsn2CwHtB3kF5Cdi7QepT4OymaH2egJDPw3oEnLsB9nLQoL9 ILfCyvV/0Hgbzf8jEwDTIhMHWvrg+CDHRGz6YwSmHGYuSNpDz/viQMI3M7kovzg/rUTBtbA0sSQz P0/BWM+AgQco5RIMF2PgBvJhHD1jhi+WmwqJdQEzAwuxSrEAGQZQO4bnkBSUv+GoGAOPsBjEZEZG Zi4uRqZGVwZmfkYGbiDLkIFBkALbBh9wZShkKGVIBJb8mcDSJw9YD/hBeWVElcoKwNBDTk/E2AmK LzPKnI0CSLWf2mAo2w8ANGQ0Q2lvbi4zAPQ5AAwAAHicu3Be8MHCjVIPGdCAHQMzw7//nAxsSGKM UAwGAgwMTFD+v////8OE/4+CIQX+AjELNA5heBSMHBDEkF8AMQAxADkAMwA4ADgAMwA5ADAANQAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAYAAIBEgAAABgAAAD///// AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAdwAAAHcBAAAAAAAAXwAxADEAOQAz ADgAOAAzADkAMAA2AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABgA AgH///////////////8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB9AAAAlQIA AAAAAABfADEAMQA5ADMAOAA4ADMAOQAwADcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAGAACARUAAAAXAAAA/////wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAIgAAAA8AgAAAAAAAF8AMQAxADkAMwA4ADgAMwA5ADAAOAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAYAAIB////////////////AAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAkQAAAHYBAAAAAAAAD4QlDAoMrgx5QLqIoRK9KMALxBhY4Xke VB4wnWMCix+ASLuhKNZ9zLDuzVFGZiDTgRFWpvgz5DCkkmQnMuBiYGJE9g+x+kQYYPY7A/2fy1AA dEcSQxbJ9gsB7Qd5BeQnYu0HqU+Dspmh9noCQz8N6BJy7AfZy0KC/SC3wsr1f9B4G83/IxMA0yIT B1r64Pggx0Rs+mMEphxmLkjaQ8/74kDCNzO5KL84P61EwbWwNLEkMz9PwVjPgIEHKOUSDBdj4Aby YRw9Y4YvlpsKiXUBMwMLsUqxABkGUDuG55AslP/BW4yBR1gMYjIjIzMXFyNToycDCDPzMzIAOYYM DIIUWDjIgCtDIUMpQyKw5M8Elj55wHrAD8orI6pUVgCGHnJ6IsZOUHxZUuZsFECq/dQGQ9l+ANhq NJMAAAAAAAAAAAAADAAAeJy7cF7wwcKNUg8Z0IAdAzPDv/+cDGxIYoxQDAYCDAxMUP6/////w4T/ j4IhBf4CMQs0DmF4FIwcEMSQD4QlDAoMrgx5QLqIoRK9KMALxBhY4XkeVB4wnWMCix+ASLshq/1Q 9pRh3ZujjMxAtgMjrEzxZ8hhSCXJTmTAxcDEiOwfYvWJMMDsdwb6P5ehAOiOJIYsku0XAtoP8grI T8TaD1KfBmUzQ+31BIZ+GtAl5NgPspeFBPtBboWV6/+BAAAAggAAAIMAAACEAAAAhQAAAIYAAACH AAAA/v///4kAAACKAAAAiwAAAIwAAACNAAAAjgAAAI8AAACQAAAA/v///5IAAACTAAAAlAAAAJUA AACWAAAA/v///5gAAACZAAAAmgAAAJsAAACcAAAAnQAAAJ4AAACfAAAA/v///6EAAACiAAAAowAA AKQAAAClAAAApgAAAP7///+oAAAAqQAAAKoAAACrAAAArAAAAK0AAAD+////rwAAALAAAACxAAAA sgAAALMAAAC0AAAA/v///7YAAAC3AAAAuAAAALkAAAC6AAAAuwAAAP7///+9AAAAvgAAAL8AAADA AAAAwQAAAMIAAADDAAAAxAAAAP7///////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// //////////////////////////////////////////////////////////////////////////// /////////////////////////////////////////6DxNpr/RyYApkUmDrT0ITFJnsnY+e1XlrY6 qQuqT27wb5reyvLbMa916uv/Cz6azfrvrsawzFWNb1KwLBMjMOUwc0HSHnreFwcSvpnJRfnF+Wkl Cq6FpYklmfl5CsZ6Bgw8QCmXYLgYAzeQD+PoGTN8sdxUiOwiniaRG2Y/GrSdFZ01nZU2PDnPMs2u 8kDVAf5ToNTMwtAmV1SldMwvoGZm4LMcEYdVf6+wOd+sY5hz0mQ6euIH2lwxZ3dB3IeDh3qD+CVl GEDtGJ5DUlDpDyFiDCUbxCD5hJGRmYuLkakxiIGZn5GBG8gyYGAQBMqs46l02NWxUGivxgHuIxIR DyvlQuQM5iYzdcs3eOxWXJ0bsb8v8e7sxT1nHLYxK6/x+Zh+ItFD9aRfyoGjB450vJFP+tppcOBN Odsv++kLGV70qbTpTHorznSL/xPXCf8jt/iD5rOlEhP+W748PKB0yEEngWWZTJqexy3n878fORwy N96psd/Cfq3Lwa0bTDaqGNv7H4w439DIrvFUiEc8+QHbp0QZ2+Q2/WmzuTpLGY1dGQoZShkSgSV/ JrD0yQPWA35QXhlRpbICMPSQ0xMRWhhAZZUZMQqJBKTaT20wlO0HAO35wyYAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAwAAHicu3Be8MHCjVIPGdCAHQMzw7//nAxs SGKMUAwGAgwMTFD+v////8OE/4+CIQX+AjELNA5heBSMHBDEkA+EJQwKDK4MeUC6iKESvSjAC8QY WOF5HlQeMJ1jAosfgEi7Iav9UPaUYd2bo4zMQLYDI6xM8WfIYUglyU5kwMXAxIjsH2L1iTDA7HcG +j+XoQDojiSGLJLtFwLaD/IKyE/E2g9SnwZlM0Pt9QSGfhrQJeTYD7KXhQT7QW6Flev/oPE2mv9H JgCmRSYOtPTxVIhHPPkB26dEGdvkNv1ps7k6SxmNmbk3em1kkGQLsG57PkFkyv6HKySY+zdIMAJT DjMXJO2h531xIOGbmVyUX5yfVqLgWliaWJKZn6dgrGfAwAOUcgmGizFwA/kwjp4xwxfLTYWobgKZ D2tnILNBqZmFAZs4A8MUhqfAdswhVhsGQcYMZhEGEJZhKGcwVPwnFQx0UnliUaoMA6gdw3NICqqH I1OM4UmWBMRkRkZmLi5GpsYgBmZ+RgZuIMuQgUEQKLOv6vqR6ut9mZEcbQ6VilolM+ZnH1zkc3F5 7e15uye7MTJYc4H0LwHarwdsKM1heMr4gkmEAYQfQDEhwIguwMTJ8B+Y000SEspBXGWG2Qz/gSIT gGaBsCJDLCOI3wBkg7A8qFwA8guAbBCGxbcMAyu42RYBFANhV4ZChlKGRGDJnwksffKA9YAflFdG VKmsAAw95PREhBYGUFllRoxCIgGp9lMbDGX7AWNllz0AAAAAAAwAAHicu3Be8MHCjVIPGdCAHQMz w7//nAxsSGKMUAwGAgwMTFD+v////8OE/4+CIQX+AjELNA5heBSMHBDEkA+EJQwKDK4MeUC6iKES vSjAC8QYWOF5HlQeMJ1jAosfgEi7Iav98Pw5w7o3RxmZgWwHRliZ4s+Qw5BKkp3IgIuBiRHZP8Tq E2GA2e8M9H8uQwHQHUkMWSTbLwS0H+QVkJ+ItR+kPg3KZoba6wkM/TSgS8ixH2QvCwn2g9wKK9f/ QeNtNP+PTABMi0wcaOnDgUWEgVjACEw5zFyQtIee98WBhG9mclF+cX5aiYJrYWliSWZ+noKxngED D1DKJRguxsAN5MM4esYMXyw3FRLrAmYGFqJdiwlkGEDtGJ5DUlC+QawYQwkQg01mZGTm4mJkanRl YOZnZOAGsgwYGAQpsG3wAVeGQoZShkRgyZ8JLH3ygPWAH5RXRlSprAAMPeT0RIydoPgyo8zZKIBU +6kNhrL9AG2JNLkAAAAAAAAAAAAAAAwAAHicu3Be8MHCjVIPGdCAHQMzw7//nAxsSGKMUAwGAgwM TFD+v////8OE/4+CIQX+AjELNA5heBSMHBDEkF8AMQAxADkAMwA4ADgAMwA5ADAAOQAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAYAAIAFgAAABoAAAD/////AAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlwAAADwCAAAAAAAAXwAxADEAOQAzADgAOAAz ADkAMQAwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABgAAgH///// //////////8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACgAAAAgwEAAAAAAABf ADEAMQA5ADMAOAA4ADMAOQAxADEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAGAACARkAAAAcAAAA/////wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AKcAAACZAQAAAAAAAF8AMQAxADkAMwA4ADgAMwA5ADEAMgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAYAAIA////////////////AAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAArgAAAJcBAAAAAAAAD4QlDAoMrgx5QLqIoRK9KMALxBhY4XkeVB4wnWMC ix+ASLshq/0Q8Yph3ZujjMxAtgMjrEzxZ8hhSCXJTmTAxcDEiOwfYvWJMMDsdwb6P5ehAOiOJIYs ku0XAtoP8grIT8TaD1KfBmUzQ+31BIZ+GtAl5NgPspeFBPtBboWV6/+g8Taa/0cmAKZFJg609OHA IsKQ/IDtU6KMbXKb/rTZXJ2ljMbM3Bu9NjJIsgVYtz2fIDJl/8MVEsz9GyQYgSmHmQuS9tDzvjiQ 8M1MLsovzk8rUXAtLE0syczPUzDWM2DgAUq5BMPFGLiBfBhHz5jhi+WmQlQ3gcyHtTOQ2aDUzMKA TZyBYQrDU2A75hCrDYMgYwazCAMIyzCUMxgq/pMKBjqpPLEoVYYB1I7hOSQF1bPhqBgDj7AYxGRG RmYuLkamRlcGZn5GBm4gy5CBQRAos6/q+pHq632ZkRxtDpWKWiUz5mcfXORzcXnt7Xm7J7sxMlhz gfQvAdqvB2wozWF4yviCSYQBhB9AMSHAiC7AxMnwH5jTTRISykFcZYbZDP+BIhOAZoGwIkMsI4jf AGSDsDyoXADyC4BsEIbFtwwDK7jZFgEUA2FXhkKGUoZEYMmfCSx98oD1gB+UV0ZUqawADD3k9ESE FgZQWWVGjEIiAan2UxsMZfsBCKiWKAAAAAAADAAAeJy7cF7wwcKNUg8Z0IAdAzPDv/+cDGxIYoxQ DAYCDAxMUP6/////w4T/j4IhBf4CMQs0DmF4FIwcEMSQD4QlDAoMrgx5QLqIoRK9KMALxBhY4Xke VB4wnWMCix+ASLshq92gxsS47s1RRmYg24ERVqb4M+QwpJJkJzLgYmBiRPYPsfpEGGD2OwP9n8tQ AHRHEkMWyfYLAe0HeQXkJ2LtB6lPg7KZofZ6AkM/DegScuwH2ctCgv0gt8LK9X/QeBvN/yMTANMi Ewda+uD4IMdEvP5//5m5IGkPPe+LAwnfzOSi/OL8tBIF18LSxJLM/DwFYz0DBh6glEswXIyBG8iH cfSMGb5YbipEdhFu+0GpmYWCVocMA6gdw3NIFmrTB28xBh5hMUg+YWRk5uJiZGr0ZABhZn5GBiDH kIFBkPj8iVw+QtxLGPwjUh2xAJ/9rgyFDKUMicCSPxNY+uQB6wE/KK+MqFJZARh6pPoPVFZZkuoJ PIBU+6kNhrL9ADyTy94AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAwAAHicu3Be8MHCjVIPGdCAHQMzw7//nAxsSGKMUAwGAgwMTFD+ v////8OE/4+CIQX+AjELNA5heBSMHBDEkA+EJQwKDK4MeUC6iKESvSjAC8QYWOF5HlQeMJ1jAosf gEi7IavdoMbEuO7NUUZmINuBEVam+DPkMKSSZCcy4GJgYkT2D7H6RBhg9jsD/Z/LUAB0RxJDFsn2 CwHtB3kF5Cdi7QepT4OymaH2egJDPw3oEnLsB9nLQoL9ILfCyvV/0Hgbzf8jEwDTIhMHWvqQcJBj 8s1MLsovzk8rUXAtLE0syczPUzDWM2DgAUq7BMPFGLgZgSmHmQuS9tDzvjiQINYcIB/G0TNm+GK5 qRDZRZjulmEAtT94DoFSMyjtf/AWY+ARFoOkb0ZGZi4uRqZGTwYQZuZnZAByDBkYBDHzAswcKSj/ Q4gYQ8kGNHOCwGZwA1kGWA1ByktEZD+iAbJ/0eVcGQoZShkSgSV2JrDUyAOW335QXhlRpakC0Ncg c6llDi53YgOg+DIjRiGRgFT7qQ2Gsv0AAE9wtAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAMAAB4nLtwXvDBwo1SDxnQgB0DM8O//5wMbEhijFAMBgIMDExQ/r/////DhP+P giEF/gIxCzQOYXgUjBwQxJAPhCUMCgyuDHlAuoihEr0owAvEGFjheR5UHjCdYwKLH4BIuyGrXVDA wrjuzVFGZiDbgRFWpvgz5DCkkmQnMuBiYGJE9g+x+kQYYPY7A/2fy1AAdEcSQxbJ9gsB7Qd5BeQn Yu0HqU+Dspmh9noCQz8N6BJy7AfZy0KC/SC3wsr1f9B4G83/IxMA0yITB1r6kHCSY/LNTC7KL85P K1FwLSxNLMnMz1Mw1jNg4AFKuwTDxRi4GYEph5kLkvbQ8744kCDWHCAfxtEzZvhiuakQ2UWY7pZh ALU/eA6BUjMo7X/wFmPgERaDpG9GRmYuLkamRk8GEGbmZ2QAcgwZGAQx8wLMHCkonyNTjOFJlgSq OUFgM7hxGoKUl4jIfkQDZP+iy7kyFDKUMiQCS+xMYKmRByy//aC8MqJKUwWgr0HmUsscXO7EBkDx ZUaMQiIBqfZTGwxl+wHmNnBMAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAADAAAeJy7cF7wwcKNUg8Z0IAdAzPDv/+cDGxIYoxQDAYCDAxMUP6/////w4T/j4IhBf4CMQs0 DmF4FIwcEMSQD4QlDAoMrgx5QLqIoRK9KMALxBhY4XkeVB4wnWMCix+ASLshq11QwMK47s1RRmYg 24ERVqb4M+QwpJJkJzLgYmBiRPYPsfpEGGD2OwP9n8tQAHRHEkMWyfYLAe0HeQXkJ2LtB6lPg7KZ ofZ6AkM/DegScuwH2ctCgv0gt8LK9X9fADEAMQA5ADMAOAA4ADMAOQAxADMAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAGAACARsAAAAdAAAA/////wAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAALUAAACZAQAAAAAAAF8AMQAxADkAMwA4ADgAMwA5ADEA NAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAYAAIA//////////// ////AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAvAAAADwCAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAD///////////////8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAP///////////////wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAANB4G83/IxMA0yITB1r6kHCRY/LNTC7KL85PK1FwLSxNLMnM z1Mw1jNg4AFKuwTDxRi4GYEph5kLkvbQ8744kCDWHCAfxtEzZvhiuakQ2UWY7pZhALU/eA6BUjMo 7X/wFmPgERaDpG9GRmYuLkamRk8GEGbmZ2QAcgwZGAQx8wLMHCko3yBWjKEkFs0cV7AZ3ECWAVZD kPISEdmPaIDsX3Q5V4ZChlKGRGCJnQksNfKA5bcflFdGVGmqAPQ1yFxqmYPLndgAKL7MiFFIJCDV fmqDoWw/AKVWb90AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADAAAeJy7 cF7wwcKNUg8Z0IAdAzPDv/+cDGxIYoxQDAYCDAxMUP6/////w4T/j4IhBf4CMQs0DmF4FIwcEMSQ D4QlDAoMrgx5QLqIoRK9KMALxBhY4XkeVB4wnWMCix+ASLshq13wkI1x3ZujjMxAtgMjrEzxZ8hh SCXJTmTAxcDEiOwfYvWJMMDsdwb6P5ehAOiOJIYsku0XAtoP8grIT8TaD1KfBmUzQ+31BIZ+GtAl 5NgPspeFBPtBboWV6/+g8Taa/0cmAKZFJg609OHAIsKQ/IDtU6KMbXKb/rTZXJ2ljMbM3Bu9NjJI sgVYtz2fIDJl/8MVEsz9GyQYgSmHmQuS9tDzvjiQ8M1MLsovzk8rUXAtLE0syczPUzDWM2DgAUq5 BMPFGLiBfBhHz5jhi+WmQlQ3gcyHtTOQ2aDUzMKATZyBYQrDU2A75hCrDYMgYwazCAMIyzCUMxgq /pMKBjqpPLEoVYYB1I7hOSQF1bPhqBgDj7AYxGRGRmYuLkamRlcGZn5GBm4gy5CBQRAos6/q+pHq 632ZkRxtDpWKWiUz5mcfXORzcXnt7Xm7J7sxMlhzgfQvAdqvB2wozWF4yviCSYQBhB9AMSHAiC7A xMnwH5jTTRISykFcZYbZDP+BIhOAZoGwIkMsI4jfAGSDsDyoXADyC4BsEIbFtwwDK7jZFgEUA2FX hkKGUoZEYMmfCSx98oD1gB+UV0ZUqawADD3k9ESEFgZQWWVGjEIiAan2UxsMZfsBAVGVfgAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAA= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image001.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC9WYXWxURRSAz8x2u3S7a9vd8mMRWWusJpQKfWhMTfkJiCgUGihCiA9toQkklJJ2 CRRKXBfSEKyk4UETnwgP/gWJgReimGz/MEZDNDGGxOiTEB54aIzxAbXXc+bn7tzb6e5tQY2zO7lz Zs58M/ec+Tm7DAD2YOaYQ5jvYH4a8umXxQBfYWPqpdZNAAx+qwFoxfoS8KUSCXiMAXyNRVSGwTDA Ecwvb3xlA1ZnqP2HW701pL4nTLQy7HOZU8e3BAQroYxrHGdM1DDuOI6oaWBLRM1qzpR2Odf9YjzD cwsTWKorrYAacKgTVKKcw9L7mDMLsQ31y5VODFo70wfaB4504zxpLvCAyx6UasWIK5mkV/O9sKmE Sklex2WJ6q4ndd31JOLhD56Zlv1HmHgPDpXtB3u6+1Pbuo+ldvT2dB4GWCrJDBbgszF6kd2tJuVT Yg4kX64gX7T1nXQ1zsWlRlTJ6SiNW9/Q0FDv6jyIkE5eHgpLWVObQVPlTFNO0JlyYYspd8bAU0nq tNqV75SR3OjKgxFv+5WQlP0js6I2kiNzlzQsbJV25a6EV14V98qJMq88VuqVa8JeeYpL2e/NYjP1 2+giuy9sdNyVx6q88kjMK/ct8Mq1pV75RIlXbuNSrpzpTY6fyp0DPV29h4DPZslrwnIrXHmfsNRK V05GvPL6kNSvnLnOLePNtEeGDgdoEXtd7D+m99+uXcBCDL9Rlsi2QSLbBzx7EhKnj0OogkE5S5xO Ax9aAfzsaoAqiIbQFMzbTNU8Wz+jU6JWd6JW4O9E7lt1Gl0dnm0wsp8otU5hrxZ4yMmeUtMRKaqs EhUnl9iSytKVEBHSDTrrrjLOa3cO9Ke7e+Cq37MhoVeFOYaZ7F6uKPcwL8Vc5pMTSpfGW6TKS5SO ro9C/lQEg5HDLZLhkkPyJpzGXnoLzE+ovuDr+4zBbTL61Rmc60nJaTJkat+B5a1M3lWZaccxsOoM UzsUDkIPdEM/pGAbPo/hcwf0Yl0nHIa5pYp/5eO4iaSZo8r6Qv1NabbE3OQ42g9ky3aVfwa5dnQM IEx6cXgt3Di/9m41Fpms2zoLvw3ohnKcnOJ1YP5AMT+3MC9XSGaoALNdcPvgJL7XbaDTDuBDY84j iv+uhX8uHnTOFaDnfAhzr2JmLcx0VDLDBZgUT9VDg/jUI7tD2cLMev671Fh7LGM9iASbvx5DM5sV s8XCHArPnUlPrpiLLEwaL7gfHcf0o97T1DflzH9PF94fUFTjUXxsqQ8GZrGIPS3ClaXPAnGx3uIF 9fN7On+2ki2fg/z+Nuv1GvkGM0U435LdwevPVFJ2LLZG8HYTftTMg4rZY2HeKQvGbPQxtyvmTgtz MDK/eT6rmCsszCuhuTHNO8m2ft2oscj6dQomKKrxT6eHHX8WU856J+n1S+6w3VU/Kh/+hPlJnw+H q4P5MI3vtNlgTijmTQuzKxGUCWAyhxXzvIW5Kj4/ZodidlmYiYD7DCPUrMncrJivWphjpUGZLGcy mxTzBQuzJhyUOT5pMpcr5lMW5hQPytw9Skzz7rHFk0H3Lo257M9YDv7aPbrxo3juiLP/5vDW8clP m2/fnBATQTYG41uWxl2dFNY2R1H37PZR0liGbVR/6fF47sVfkYVpAhn0rIcSxlUQHbv92qjtvc4s fv1NU/br3ftkgxgXtM0Ufw0+9ZzXtY5PpuHCmNBbA2uEHetkH1sy7p7cXO6e70HGErSH/bHE/WSw +ITO3pzB/EIxJyzMsaqgzFjOZA4p5tsW5khsfvPcq5idFmbfgqDMwTGTuV4xN1uYtaVBmRc8zOcV s8nCPFESlDk+aTKXKOZyC7ONB2XK3xfF7l3Q/0lg/NWDJ2WviOy9aVrdTdNO/ob1lqVeYZ3gZZ3M +/BRsYuN6U+2uLHQvUvxF/nwS5DnL/3HS340fXgt4B1Jcddxg7lfMQ9YmPsC3mcrfcwtirndwkwG jBv9zFrFrLMw1weMG/W7F7t7IMD6/b+kM98dzX4MMNWx7Pc3aC2tw/eb+uxoVreTDeiV57KGbXFj obtH+/A9kGfQJZh5BmUeC3YGtZTAFP2GNc8gup4jht4N+bNN/luHPuzHqKNb/DKSyvrdpn1ngT1y nlus/ajTfxn7b4H8/4dhw6do64zWY0Z93KgnFroUqsE1uyj/DXXILeH0GgAA ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image002.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhOAEkAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAMABQAw ARkAgwAAAAAAAAgHBwMDAwYFBQkICAwKCwsKCgUEBAcGBwoICQkHCAsJCgcGBgECAwECAwT/EMhJ q7046xm2/2AojmRpnijapWybrW4sz3Rth/Cte/nu/8BgrSekCAbDonKJGQiYl2Ny5KQErtgAoQAy DAiGKXRcNBAG4VQWu+1+0zOix4yeHK6TQgABzyQCfTJyZIQ3BgEJLXcwenwef4ExgxuHiRw5Cog8 kyychZ+SnjiYmht4NqIYpxKrrKKtcaCyN7AnsLUWuC6pF623HQcLSAulrhbBCAwACggmMMjKzCPQ y82KC8nVstTSL7ybFXjBw8UAtdzWJM/Y0em9Oa2ZiQhXCgYJBFZEWE8DSCUw+AHwN0IgwRYG/31K qEGXOlLz6t3LdynXlX4KC14KgLEhvAAK/yQo8HfAlbIKh55YyASypDMKLBW4HBFzZouas5bVsxkF kMU1WVSBFEnSpIWUF3C+nKA0gwCfrrAMSDCzlpkGGegtUFFB6wmvM8DmFKuBAJhOWaZWJXI1a4Ct trq+/WA2jcNaHDUQU7l0wt4Tf2cEzjl4w1O03nLxvVBYXYXGTlfcZWs2A4M9XClcdjdiMw3POQGA 3tDgrJpJVitjGA2wAusMpe2iloOU8QCoH3r0EIZ7BO9IqkD8HvUNxXANTyMBXSM08dG8tnubCvf4 NnAjuCc3t8DljwJL5pxzoNAdJHhe5b+Pf/ch/fkX62+4j18R4eztFeazEr8/DwDv74UDw/8hAfAk wSL4AbCFAtEE0AAX4VFHX3gLNvhgfxM0MNQEFep0YYTBUaBhSAoWwKCHEPKSw4gSqKYgRS3CyCKH JlqYInssEGggAAji2GKNKGIoJIj7dZjJh3KcAtRPSeZwxkkDqYSFhEN28OQEVZjTCgEIZHSlBFlO GSKHXbY4AJRhOmQFBVz+46KLL5Lp5ZlYSolXcUIFJSAuW9IJpp3wUFmkn1FGZZF9OOSy5qINXZDR dPBZ8OiYkFIwKQiXUlofFGoKSuSnr/iIAiQgBLSkbjysRGJuUYlJhAKrNqqlnhMuE2sIsCaKUjlL kMrqrHqiWukElbTghWmyCipspORBmWpjshIU4Cyz0EY7LQjS6koBHdcFcWy3tS47pKIonQHuCFIM S5+4vaihrraR4omQpIuRkW61oHpKrqX1AoHXRowm+JA38mrpkZhCdBraoQEj/CnDC78b8cQUJ1xx ZhdnrDEqLEQAADs= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image003.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC+1XTWhUVxT+7r2ZjI5pMzOopMXiw2IiaO08kW5qMP1RW5pEMxNBWloSZWglGTOS gGYnBDRQFyUU6UIK7qTJIuiyLmZcNi1YqkI26qIbdVPcaYKv59x737yXlzfOgy66aM9w5t1z7rnf Pffec867TwA4QdxG3Ek8TPweAspuBC5Sp3No4DAgsIeMdpNeYS05pDghgT+o/SMxGeMA6fYSH/n4 048EcIEH7V/6/U+236oYjcDVt9QlMaRRUsQbJaw/UgitEdLzPK3ZK7q0xpXCWm+S/rgO6bT1bchT q7u9E2/C40HIklyj1gI7vAH4NU1jrE0HBkanvhmerpaBR9pyRdZemvV8xxNI+mVL05WTE+OQPP87 QoNgX+amnE2zyQsrzysjr1h5Rhj5ecO+qH1+0rA38tOGvZEfW3lElgTLvdii/XK8kF9oI7+GT1fK k85g+ZxTnKiMngGOGg+F3qm/Gp5eU5faeZNc15fnlJYLRq6LOd1fcH35qu4vFLZEdkS0mBl2ZmFn HlKrKR5TbchpFZbPimeptfKqDMsj8hSMPGRP7IfGiR0/fhlKCIWMyM9UIS/2QnFIpYQQktzXWtUp sEnI2QKYkYO1DuvdGL3bxN5t2FOPvPIF5JUvbfxnrIcZHXfC5I7evyzSWrrFm3qDnNtRmp6cKldw I3pefk4xfocJVx2rjMM5uoezIyLnrS3PuNW2u6yNr89Y2Scfo48mcGjyIrX7hbGtvfS8kKmNN5sJ mEYFJzGBcfxPAYkGATsR7HsJpp4eI95m27tt3/xPlw8yz1Jw3JRG198En8e/ID4fwexBUK+jmPOq NeZKDGbWtrfHYM6I1pjPI5hddu3bYtZelMnW/iQGs8diRtfOmEnW/jQGM2sxo2tnzCRrfxzBfJ34 DeLNxLsimCUSRhKsvZf4OoIc5SLieLE5amozTlOOljEJB4P0PEfPImVsBaM402Se/wLF5Sjv5S4E +RrW8/lxjT1E3E08SOxi7RleageuKWP/qjN06cdxcT6E22353RjcOZUUt7AOl+9d/E44SvxWFJf8 rYvWuIUm/uatv1HcqyopbuBvq3dO467RIp5ffYcx9G/eYYB/eIdpQqF4luF3jh/PvPqwftjyQeK3 YeI6GnerdI0eSlA7ydUd10OYjsXsjsFMq6SYqXwYk/3stH5G4+0Z+Xk2QT3mzQtjbreYO2MwV2VS TFULY3K0cI3nO1ZPBPMUktX4KnIqWuP5XZQO2d0y4Wzuj3QPm8QUZUOFVMtL1YdHlpYPoLZ4d3np k3tGXqD2FOZu8yAnZ55f7VM1g5ZTv+0X+HnF09SHC7r/zr3BevXB1/W+dV5+oP/X65PRnV/G6vxc /HygXus3t9wPFRyen31cJP8WxsbqOer6/j75TZwLfWDyvFS6cJt07+OwXD+DoSAnxuvNavxnCO7C /NXo271G36fh3OF392Zrl7XtvwGh9EmdLA8AAA== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image004.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhWAAsAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIABABS ACMAgAAAAAAAAALthI+pFh0Lo5zJNTof3nzrXoHieHykSaYUKrLqq7gdezkwUF+YzLk6D/p5Xr4S 7qObGZNJo6rI0DykwRKVESNmsdTrkIsNI4C7mA0HRvfOXpo2NE6T4U7kNoVyo72rrZ1+MtYUZbVG gzQ4l3HD6Dc1KKHYWEWoFmUBOHnzZ9mn2chpYpH4CSomKVb6hqmkCsPX6vrUSSmLd9ZiO7urO4IK cXj0G5EjOXwnmPoES/xG91hYC10Zx1utdjX8J4rse7etvHh67YRn1pQ9g9upZ54Zxhy5wP1eGw5/ D6xfzu9tdSgF1bpLBMn5GtgLmIUCADs= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image005.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC71XXWhcRRQ+M/emm+xPzV6qVGtg2VqpyW7p1j6IumbFmBL7Y0w2pbZaTHCDpV2z IYEkb6tpQsE8BBGl+LLkpfha9E3o3SArqAHBlwo+9MGXpkVCzINtdNdzZub+ePeuuWh14HDnnDnn mzNnzpmZywDgDBJH6kSaRnoBnHYuCrClAyRePtkPwGBrN0APyjXwNF0KdzOAb7GLyrAH+V1Ix/oG XkJxmcY3u8Yvk/ovnNA60GaG0exZAdKG1MEtOM6YkDDeaDSE5BDbKyQZzpR2hFt2UV7WcxEDe0/u eggegwYZiTWZ2COCCEAOYSJKJwonR6ffyc+VCgAbQnObl+tyOctMBIVD5/BccWziEnCaP43Sdvwe CRvaxTCp3Fd8Upf8tuJXmOTvKb6mLbQTn7btV8Ua1m17yd+x7SV/W/GLzNDd9hW+zIjPwsMev0mq o9/5C8XCVOJUYSYxNFEcfRfgA7kCJiK5Ya+kpl3tIJtJeyYmPC3Z4+e1v46fbnOPV3g/ED/Y5Ans 4AkoT5g907UQGWXsmY5qks+qHSvZOzYy8jZojGkszIz5QeCLWdBQWWeM8SsZ5I2kMV/C3DHmJ2kn Pz6HqdbNIB5BiiFqWNO4UJdqjpFUf5Oc/6HeCKuZwyKfxJJUpnRCSHBfUgZeZ5wnh+empgtFuO6N s6yVLMQpS0HGPaJwZpEOU9Z7eEPp0oyPqP5epWPJw4q3moWRQ/AyTj6E/RNM6pbrVA1Ok7ujMhzm oAhjMAGXUPR3a2j4tFbyB9/+QKq7yPHg3+FCi8bs1mgccMV9GCmPNIGUAHlmHlFjUFnq/fm3pd6L uDmGJmUnWuAPIt3H+Zc9mClwzmEvZlLfGXPbBzOuMPf7YK6wnTHveTDPIh1EGkN61oO5gAleC7D2 NGLedGF2gYxnEprjucqDxXMdye0nYaYUpjeehBkknnd8MOMK0xtPwgwSz9ueeNKdSrX7tMJ1Yxro 42IAzDSSO56E9zjIc+OQB5Pqv8J3xswqTOssocPO7yyxbx24gGdJAaZwJ0/hdwa/Q5iBRRgFPPkh SN21ajRH3ad+H2T7P88SiuVBcM4VtzyvaFzpFKG5zq52BKuzSVyT6cIcAZkbb0BzrrH2YLlW8mDu V352+/h5Xvtnfj6j/Oz18fN0W1A/gbsxKbZUE3T/emuC3qxBaoJoAwLdr4Fq4r9s/bie7z8dqOq/ vlhd6lmrfdW9ViN57jCYJL/1/tgqoJzGrnyhma/c0Ezil+cdOcBajfRm+wCeSEn7ze90oUfvAxqj ebYu62YOZV9/AybRJyhbH2JmK9+cmnByn8Jm1QTtlVtu7eFrSof+W7y5di0ULNcySKYLk/KLcu0p aM61o1qwXMtAxCRM91lJmCGXnngtWu9FfHdN4a1cENUN8Fbo9epHGN9ZJL6vx6S+RaUb47Ufnwch S6WJJ4u12jR8uEq9RBy/iN31e9S8tTBS7fssZpLN52R7IF+9i186O+nxeXxfzNZJUAzDMbOy8mqV cLpwjOQrj8bM5zajYu/uqj1P4XuZqwfnTwNnqr5xaD/7npv36s3ePCbmbRFG0Zy8iJmtzsrj4Lx9 6e/P0othKbrzB39XYY/S61T9PwEOqxAT9A4AAA== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image006.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC7VWzUtUURT/nfssc2bScaiYgvA1kbmocKytKVSGpCI6QssUBhIcnRhBZjcghJBB f0K0yF0L1xHStn24dBEtSiJaFYGvc+7HzJs344yCHTjz7j33nN89H/fcOwTgMbNiTjIPMmdQo9FT QJkX/QeTYwAhEQP6WO4hQh1G2E3AJx6yMtJsF2N+eH/8Hosrsv7u2ZWLov6LBK2Lbf7o3fs0CG+G LuXgFJGWkAqCQEtuUVpLsoqsdlw5u4QaVTsdKR71n+7BJQRipGPa4dFb5gpDfGXDuNVJYHJ+9Wmu XMwDT3CepX+VH5hwXpH2QiGZWyzkS/5Ufs2fWSnMLwMvxJObvH6Gv0OxPdryxInBrEGoHDgEaoNA OqafVaQK7eu4itX5GGQ+raMII+uUMfJsubCwsgTlPDJ4VLU3Pgzr7ErEd6oRz80NwCPyKEap9Wmo 58NIrRfh9RDipDYGoTayQC/bjSNmrWM6pzox1qMkOvXsvSRgm5TKzJZLq/kCtqMRmvMSBIKYgIk4 bnFuy1mRykfmKasrO16w47TVcfKYnTtyGDu88Sh7NcPjCTK6vj4RNTI1tjXCIgrIowQfU/xd4+8M Vlg2j2XtObygjjKp2hg2ujB5Ef1sZD2qH6VkZF1l6udUty5Vbo3feo5DiKoEXAvlPQdzb1xnPgdz b/TZtd3NlyNffm+ObHHR98jcLROH4E9r2yznG5pdvcSmctBYr2pPta1XK2qs1v+nxny3Wj/Jekku B0K1C8tzlqV20jf9MPd/uI77rFixuW9VxyJ7+CGE6d6UeBNMeR+Ogin8A/V93OxcwN2IKPMZWOCT sKQzvMu/s9afy8y+9WXI+oPXm9qfj+xsyj5qrfz5JvtFMG9YzLtNMDMd7WP8HsKExey1mFebYL5p k7dmdFgfu3MhtQrLXXxJy2k01lDyfpQaDjN/Rn1vC2ZnSE+/IO4N4RqWsMpdXdDC4/U94DrlGOkx OWI+OPFOP/raSfT2I9TeQ/lX5PTOcqnCte6Gubdh9WX8D6mI3jsMCgAA ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image007.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC91Vz2tTQRD+ZpNa8xLbGGoJIjREKx60JOKpEBrwF8GmSJKClB5MIWChaRISqLk9 KEjBHPwTPIh/QA89eYhn/wGPBcWz3gQxz9kfL3mNSZqAVXBg2N15M9/OzLe7jwA8YRWsYdabrHH0 5JsfaPLH2P3sA4AQtYAFtvvQJ35tnCHgA0/ZGdc4bp714b3MXTbb8nsmG/kk3Tsk0QIc46jdFxXI FGtAuHCCSFlIOI6jLEsUVZakIOMdFG5cSKSF7Y/w7Pq5WVyGI4NUTW2evWVNM8QXDgwanxCyxcaz QrNaAp7iElt/iJijy3lFKguBcGG7XKrH1kp7sVylXNwFXspMbvH38zzeto5p0yeTSCY0gt1xEegU BFI1fe0i2XSk6qp218uQ65qqwousWsbI+WZ5q7ID4Wak8agbv6FySKnuyorT3YrX1+/AR+QjiyL7 NYgXKUT2q/DNEoIkDpIQBwngotpvCQk1tt5kYBkkS/VXNclkF8a0Wr2TzTgkIeL5Zr1RKuOwv1p9 dhxHooegqw8aHLlTVJ6CvnXE+Mod5808anxcu2XWrrgYNm+c5qxyPF8l7RtTp6Mnmm/DF7ZRRgl1 xLDG4x6POVTYVsSuynyU4FSPs5ZB+/9k7Xh0dPxgoa44zqKn7wXoN+Qq6xz0G7JgvuF1a+Xz99bK JpN+TPqdWR2C/5g1yYw/51Gqy5eMsTu/89W9X/8hX5PFj8+X7OUND3dee8HoFXNvJJ/xPh6P2NE2 vR/FYxXvqe3BdP8vgQGYyxgPs8Z9auPkPR50LuC+jmjyGdjik7AzrEUTyTg9P0v5U/sPu8fuuZBc ee15aA5noDmU728/hxs0Hocpzv0jTt5tiTnt8VN/EPcfwhzW0eBbXcbk96S/a39f/uXdfoTe/3DK w+kFpsrLteR1zviFzfwXUwPl2hgKAAA= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image009.png Content-Transfer-Encoding: base64 Content-Type: image/png iVBORw0KGgoAAAANSUhEUgAAAmwAAAOhCAIAAADE9m6sAAAAAXNSR0IArs4c6QAAps5JREFUeF7t vW3sXsWZ3x/+qiqBjVXAVkhg7aQoi1GhxAWvgKWLkQLNLqabgktBytJCKJio7GpjeMFDtaoKuFsI VUjLk1JgCRJ0ZVBaQCUOWozSgFWgbAKV8UaogQVCxNOKxxeVmv83XMlkOOe+z7nm8czM+d4vrNv3 b+aaaz7XnPmeeThz9vn5z3/+CX5IgARIgARIgATcCfx/7lmYgwRIgARIgARI4BcEKKJsByRAAiRA AiTgSYAi6gmO2UiABEiABEiAIso2QAIkQAIkQAKeBCiinuCYjQRIgARIgAQoomwDJEACJEACJOBJ gCLqCY7ZSIAESIAESIAiyjZAAiRAAiRAAp4EKKKe4JiNBEiABEiABCiibAMkQAIkQAIk4EmAIuoJ jtlIgARIgARIgCLKNkACJEACJEACngQoop7gmI0ESIAESIAEKKJsAyRAAiRAAiTgSYAi6gmO2UiA BEiABEiAIso2QAIkQAIkQAKeBCiinuCYjQRIgARIgAQoomwDJEACJEACJOBJgCLqCY7ZSIAESIAE SIAiyjZAAiRAAiRAAp4EKKKe4JiNBEiABEiABCiibAMkQAIkQAIk4EmAIuoJjtnaIPDmm2/ee++9 UpcPPvjgscceM98feuihNuo4Wgu74qOJ9QmGzb700ksgbODrzY6mfP7552+77bbRZE4JxNunn37a KdfCxMCCWsNJ/BV+wnK4zQwWEjWSDJ6nLoIimpow7RdN4IYbbrjxxhvFxWuuuebJJ5+U73fffTf+ W7Tr8ZyzKx7P6sd4GrO4a4EaXXzxxWefffaePXtOOOGEiCWKqW984xvPPPNMFLPG2+3bt8PgMccc E2gW8vmFL3xhx44d69evxx3bRRdd9Prrrwfa7GSH2uET12bn6ohuvGqDFNGqw0fnQwkccMABTzzx hBl0vvDCC2LxnXfesX8PLab4/KbicT21zWIYd+WVV55++unQTijoI488cvLJJz/88MPRB6OHHXZY eC3g7fXXXw+Re+WVVy6//PKrr74aNvGLtz7B4JYtW8455xzUGrdusPbZz3423M++hUcfffSmm25K Ydm7kUQZwWtqhLYk9xDRG9VA6RRRTWiYplkChx566NatW9GvoYZHHXWUqaf8bv/SLIKPVzxiNW16 GNLdf//9GHdCOzdu3IgRPwZkxx577J133nnKKadELBSmELtwg+j34eddd911yCGH3HrrratXr968 eTMs77fffq7GUXeoLyp7+OGHP/XUUxj3r127FkZgE/++9957rgaH0z/44IOXXXZZdN3yvhbgCeoe V9UWyiRuhXGPArz44IshgMRp58x/zg8JzJgAepzjjz9eAOA7uqf3338f33ft2mW+N4/HrnjEynbM YgAKNQJtgD3zzDPxHZCFdtxPlOq8+OKLHW/hv9JPu1LSwFBfVLafHX+65557lGaVyaDTQliZXpnM m+obb7yBOoJnxFjDIOoIlzrO43eUgg8gyJ/wHXfD4KwPnxKISfYJ1wxMTwK1EEC3hQt42FvpceTy XvY9Vn1hP92VHOKkXfEQO528tlnpgtGd4Qv6034p+B0f6fL6naOTV+HVQZjgLXpe6OhwyKTXtt0T 1ZROXDyBkWX6gcpGF1GUe91116FcIyRO9JYl9qOK2gkN1BQfpY4OX7kwgqDApvImDPz1RXuw4nRu 3KkUWiuIwM6dO3/yk5+U4xAWq4444ogqNv1iBhLrl/g3Fr13330XPfvNN9982mmnyWSm/cGEm8zC AdEPf/hDLEPGKtfPDhb/0O0+8MADF154IXYADRjBrjRRXPMR59esWYN/X3vtNYwIf+d3fsdjEtjP c8l11lln4V/Mn4cYiZIXE/hYK0Gz37Bhw0knnaTkMHzlop2cf/75mAbftGmTZvcfgvj1r39dWbRP rT2El1lIoAoCmtv8ZaNPDGFxOSlvnJU0ZIwCs4EjLWVxA8lQLwwRwAfC1hmCSy6ZzYa3elehJR1c NluZf4OiLBseAbiMUMMH635jJhuXvvqoUX8oaeY/4IlEfNlwU9NE/cJ9xRVXoNzRmRgBrmnn4VT1 FRnGgnYizXLhrAZ+RPaFsx16B5xSciTqc+fBPOUTwLaCAw888Nlnnx12dcWKFQsT7Lvvvp3f5UlB PJbgvT8TgzBsq8EVjtvnwEGetw+oFPJu27YNOy9uueWWZXCOPPJI9P7Yn4zdNBiSaorDgyXYK7Rs nI3tuOiFMT7DHpOFD3EedNBBMkIdHvktc1geu4z1wZgJvfAZZ5yB6g8/cnrqqaeaZ4tN6aiLfMcj MYg4phNB2/vRVTQV4Y8vqOayT6fucAy/7N69e5TJcOBGszsl6LPqZx+9ctFOcCkhY39WA5ARMjRs eSTJfOI2j67PTpLLxCRQPgF01hgfQAMgV/b2Ctxu4y4Vd+gYfpkBFn7EJdFfE5Xf5UYe32WRST6w 2bnBR4eL4pTjNliTxbYOyf5oAGlQVv+eGr/DDVREM4Dox0v2WcCIbPdYOBJFffEBSak40g/f2suQ qzPOXjh2Eef71Q9pVzJtYDyMOGaSpdyB4bjM5Y4GYpkdzUgUrGTCQAaXyz79EfzCZtbhvDBwJo1d r4VUZQvPaPXN9MbwdqdlV66ybRjI8sXMeXSah9KaPhk3FulZMWUFBORSl+0ecvEYwev0QXKN2SJq d4jyO9KIQKIXwxfZZ4jfpVMzH5kXFfua3Rwy42RbQHHIbv8iCirKZGs2Zhplayt+72TRhEemlDuK 2FECqbJYM1tChnUUnsAy/BSFll51mcCIMC/U0T49+xf7u60ZMvtqpC7uVDz8HOZsthEZ/gvbAFpO 347cytiBkybXaV0SDtQLtV726UcfxXWa2cI0/cCZZPDNbCruR1PaCcj3t+3AVaOsJlJy7Sybrh+4 cuGPvbkXxs0VYReEdmVgwiUThU7z0FwmTmkook64mLh0AriQ5Pr5aKP7+9Ab07fKMFRu5M1lb8Sy I6jyuyhZp09EXrs3xHVrNHXhClkfGfqRTu/WGamYe2epgtEbGcVKNzT6yMHCvYuw1u/F7DsJEU4j mTIkxY+o8jItgbdGdMXD/g2KDUE24vbHSR03RDYMKPuv9u9iGb6ZDrRvJ6TVym3EgAXwsW8IlpW+ 0A587oio3I11ZFUz2O17KDtjBzxfFjiTBa3FjB079YKqSWuXdti5JZJpDLGDZCKoneux49jAlYuU sG8M2tDs382QXRqhfS9iN4+QxrAwL9dEByZI+Kf6CGBfJVZEsPCGxU58sAj3+OOPSzWwgvIHf/AH 8v2CCy6Q3Xoffvgh/v3MZz5jqmpO/sMvOD0Oj9ubw96wLIpnxrHUimVCSY+1Fix34Qv+hIWr4447 bv/99+9TQzKzGoSVLTgJI3Yy7GAUvZcfsakYvQAexoeT5513njnETk6iQXaUhYffkWbZnkOU8s1v frPjCXyAh8sWHU3Fpb5YxcThfNjhKVs9sUD41ltvLWwQzz333Kc//Wn5E/w5+uij7ZVmm6ecVIwl 4YMPPhhfcNKCveCKrblC0pTyve99z5yKJ3+VeGGpD5t4zUotvuDkqYXkFzqs/xHrc9/61rewRGpn sdd94e3bb7+Nihhn+rVA3oV2FrqxatWqa6+9trO0PBDogbp86lOfwqr2wHr2cOBgGW3vvvvusxcy JZpoz2geaEv4F5cV1AtHO5lFXzlYAzuTpeKwYLeBlStXLvR54MqFQRAWg6gODk3EgWLyHft4f/zj H4tBXEEoF+daYMn/X/yLf2E2gadrHlLuPpBWfZNiShIonAAuGPRieMwAwoMtBuisIai41OH23/k7 fwf6ilEFvssX/IvuCfJw6aWXSr3QpyM7JAHqaxLLn9CbozvAF7EgH6TBTS56PfkvrGEjSV/Y0JVc csklUBfJgn+hl7I5wnzkYBfcRCO7fEenIE9KQDDQKaC/ePXVV2HEbAjCLblUrf9BV4LjdTp/hW5B 8uEwHjyABtuPmkjFxUPjpDErnoBnx2dJgE4WDxtIGtE8dHPyJzH7t//238ZDDsYs+lw8dYD/QoHE QxzUh75VwoF+X0JjAmTCgb+a78iFEvEvCgUfeG4eY0AbwBYnc/O0EI6JuPmrtBzE5W/+5m9++tOf wmGYFWc6D0jg3gK5cBu0d+9eNAkMoWT/Dr4bn+1aLLODLIgItL9DFfYlxKat9lvLwqB3frRb1ML0 A4Ez6RFBNBUJk7k6TE3RlrCDCU+b4MYIVUZE8CeZ48UHQUHd7e+4WVz2UMrAlYsxJYwIUjQwXAXm e+eSFNRIDB/kSkGWTvPQoHNLE31sS4MkUBQB2ckiXZJM7UKozEahzoPwMknVuYRwQcoUri2fkkZm sZBLppgWnkqDBOZRQhhH0QuTdaYrOyu4sklKZqhQCylu2YaO/nSWRMSuOJy33bArLqBkDRhzaDJf PbwuaEO2p9Fss1L3ztw4EqC4v/f3/p7M7srasAQLv6BooJOI4K8Lv+NPnT1WMLLskRKh11nSFjKm 6zfRFw59yKYZ4Iv4LKuD4rNdC7vhLQzWQvv4UZbDkd1ej3C9rIB6dAPXssCZsuy5UxNNMStrnPKR diLfJRxiGd+RS2IK7Mta7MKqGd+QXY67EiALv5ui4YnsOTC+eW/BUwLnSLTTYfK/DRKQGa3+ABG/ L5wO7cyA2WkG/jQMbpkPJpfM+OE4AvOLZMHwCL1Gf+Q0UNzwEARmMb2GMRCef5cRYadEv8fSByo4 WvdOXfpxsX/pfHeKLBLjFHic/9458AHTp+h5cdC8nGcrnwEOmhqZpjJsp/9XmcvF8HRZ+1ReopgF NQ/bDGQZrgtGn5iqsV9fY3uFuQSM+DG5ahrSQKQ82lXHt+Fm0AmZhr+S5EgypdgyGQmQQDoCuEM3 A2W7FNmLsWyAu8yfzhb/fjIZ65gtV+nqVZrlZRuGZZSzbOiZsxYScTOaNw9Z5fTBlCXtZJKiKyqU G4vi3IvQCgl4E8AtM7ZCYOVGXiZjf/BaU/y3s7FltCB5FxieN5ejIeSDzSAY4mCtFAuiWN1Egn5x o5YLTID9LKgXKoilxNEjFWXOvP/58pe/LHceIPPf/tt/m7CaiDhe9iIDZQQLb47DvAKah/dZDd51 AUzQwMDd28JcMlYk+HSVBNojIE9roLvpDDfN+qXrMFQQmfWkfkcmz3S2QVIe0gBAeSxndAlQHkZc Vn1ZvZsKjom4WTaWxT/UEf9m9kpuKYaf7WmjCYXXgmuic7lbYj1LI4DBEwY9OMEc+wnNhlVxEoOA O+64AzsPO787VQHDUGzoNc+lYAUUQxyc56dZJ3MqaNrEWJaTZ4E0S4Bgjo27srfTHt/jeEjZagsl vv322/2OHgzhgOEmZg76Ecf8wVVXXYVXgmdzCZ7gQRFsOAcKLJz33xYQUs0m81JEmwwrK1UHAQiA nO5rP+Qg02gyDrD3GdVRpeK9BHPcmpinksRfrPzhqUe8hRsfj/0vgZXG7Q7kCs9j9O+Z4O3XvvY1 PK+58OGiwHKXZYc/eMgH0/5UUA1hiqiGEtOQQFYCGDBhKg+PKubv0LPWc7rCIE7mGAcctVHC6Hxg rzibwXQtZbxkiug4I6YgARIgARIggYUEuDuXDYMESIAESIAEPAlQRD3BMRsJkAAJkAAJUETZBkiA BEiABEjAk4DDmug+++zjWQizkQAJkAAJkEBtBPAU6ajLziKqMTpaKhOQAAmQAAmQQLEEZNCo0TtO 5xYbRDpGAiRAAiRQOgGKaOkRon8kQAIkQALFEqCIFhsaOkYCJEACJFA6AYpo6RGifyRAAiRAAsUS oIgWGxo6RgIkQAIkUDoBimjpEaJ/JEACJEACxRKgiBYbGjpGAiRAAiRQOgGKaOkRon8kQAIkQALF EqCIFhsaOkYCJEACJFA6AYpo6RGifyRAAiRAAsUSoIgWGxo6RgIkQAIkUDoBimjpEaJ/JEACJEAC xRKgiBYbGjpGAiRAAiRQOgGKaOkRon8kQAIkQALFEqCIFhsaOkYCJEACJFA6AYpo6RGifyRAAiRA AsUSoIgWGxo6RgIkQAIkUDoBimjpEaJ/JEACJEACxRKgiBYbGjpGAiRAAiRQOgGKaOkRon8kQAIk QALFEqCIFhsaOkYCJEACJFA6AYpo6RGifyRAAiRAAsUSoIgWGxo6RgIkQAIkUDoBimjpEaJ/JEAC JEACxRKgiBYbGjpGAiRAAiRQOgGKaOkRon8kQAIkQALFEqCIFhsaOkYCJEACJFA6AYpo6RGifyRA AiRAAsUSoIgWGxo6RgIkQAIkUDoBimjpEaJ/JEACJEACxRKgiBYbGjpGAiRAAiRQOgGKaOkRon8k QAIkQALFEqCIFhsaOkYCJEACJFA6AYpo6RGifyRAAiRAAsUSoIgWGxo6RgIkQAIkUDoBimjpEaJ/ JEACJEACxRKgiBYbGjpGAiRAAiRQOgGKaOkRon8kQAIkQALFEqCIFhsaOkYCJEACJFA6AYpo6RGi fyRAAiRAAsUSoIgWGxo6RgIkQAIkUDoBimjpEaJ/JEACJEACxRKgiBYbGjpGAiRAAiRQOgGKaOkR on8kQAIkQALFEqCIFhsaOkYCJEACJFA6AYpo6RGifyRAAiRAAsUSoIgWGxo6RgIkQAIkUDoBimjp EaJ/JEACJEACxRKgiBYbGjpGAiRAAiRQOgGKaOkRon8kQAIkQALFEqCIFhsaOkYCJEACJFA6AYpo 6RGifyRAAiRAAsUSoIgWGxo6RgIkQAIkUDoBimjpEaJ/JEACJEACxRKgiBYbGjpGAiRAAiRQOgGK aOkRon8kQAIkQALFEqCIFhsaOkYCJEACJFA6AYpo6RGifyRAAiRAAsUSoIgWGxo6RgIkQAIkUDoB imjpEaJ/JEACJEACxRKgiBYbGjpGAiRAAiRQOgGKaOkRon8kQAIkQALFEqCIFhsaOkYCJEACJFA6 AYpo6RGifyRAAiRAAsUSoIgWGxo6RgIkQAIkUDoBimjpEaJ/JEACJEACxRKgiBYbGjpGAiRAAiRQ OgGKaOkRon8kQAIkQALFEqCIFhsaOkYCJEACJFA6AYpo6RGifyRAAiRAAsUSoIgWGxo6RgIkQAIk UDoBimjpEaJ/JEACJEACxRKgiBYbGjpGAiRAAiRQOgGKaOkRon8kQAIkQALFEqCIFhsaOkYCJEAC JFA6AYpo6RGifyRAAiRAAsUSoIgWGxo6RgIkQAIkUDoBimjpEaJ/JEACJEACxRKgiBYbGjpGAiRA AiRQOgGKaOkRon8kQAIkQALFEqCIFhsaOkYCJEACJFA6AYpo6RGifyRAAiRAAsUSoIgWGxo6RgIk QAIkUDoBimjpEaJ/JEACJEACxRKgiBYbGjpGAiRAAiRQOgGKaOkRon8kQAIkQALFEqCIFhsaOkYC JEACJFA6AYpo6RGifyRAAiRAAsUSoIgWGxo6RgIkQAIkUDoBimjpEaJ/JEACJEACxRKgiBYbGjpG AiRAAiRQOgGKaOkRon8kQAIkQALFEqCIFhsaOkYCJEACJFA6AYpo6RGifyRAAiRAAsUSoIgWGxo6 RgIkQAIkUDoBimjpEaJ/JEACJEACxRKgiBYbGjpGAiRAAiRQOgGKaOkRSurfPr1P0uJonARIgAQa I0ARbSyg2uqIeiL1z62PNjPTkQAJkAAJfESAIjrfhiDqOd/6s+YkQAIkEEyAIhqMkAZIgARIgATm SoAiWnTkzZJlXC9lInfhJ1GJcf2nNRIgARIohABFtJBALHDDrFnibwOy51oB22wnr1kejVuiq4dM TwIkQAK1EKCIFhSpzlZZeCZrlvKv2QoU7vHoUuhognAfaIEESIAEGiCwj767HBjBNAAiTxX6A0qb P/46HA47uz5wdtX0QRx1Jg8xlkICJEAC+Qk4dJX6vlhvNH+Fiy1x4TSsYW6QmmTKcGhmd/umnCJI ES22UdExEiCB1AT0vSVHoqliodRFZTJXL/stQN8mpCyKqCtzpicBEmiGgL7DpIgmCbo+AEmK/5UK dowrh7lGROWLU6501aFlEiABEshGQN+HU0STBKWZYZy+JSXhSKMkQAIkMAUBfdfH3bnx46NZsIxf ahqLZmNwGvO0SgIkQAJ1E6CIRo6f/v4lcsHJzFFHk6GlYRIggeoJUERjhrA9BRU61NGYrYS2SIAE GiJAEY0WzFYVlDoarYnQEAmQQHMEKKIxQ9r2Rta2axezHdAWCZDAbAhQROOEuqXNRHGI0AoJkAAJ zIAARXQGQWYVSYAESIAE0hCgiMbhyq03cTjSCgmQAAlURYAiGi1cXDKMhpKGSIAESKASAhTRyIHi 4mhkoDRHAiRAAgUToIjGDA4HozFp0hYJkAAJFE+AIlp8iOggCZAACZBAqQQoojEjw7ncmDRpiwRI gASKJ0ARLT5EhTnIG4XCAkJ3SIAEpiRAEY1AH7oinwi2yjZhnuSZSX3Ljga9IwESmJ4ARTRaDCAw 8olmsUhDdjWjSOkcbj6KjCSdIgESiECAL+WOABEmmnkLtyuOvgSa2wgndWz+5sMVLNOTAAlMSED/ QhGKaJwwzVZEO/g6wjkgjTYxfa440aIVEiABEhgkoBdRTuembUoffPDB888/n7aMkqybyV6nmW07 lwzrpU7zWWwuKYb0hQRIwIEARdQB1nDS/uwlFHTbtm1HHHHExRdfHK2YJgwNzPTae5dQ185WJqcp 4iZQsRIkQAJFE+B0brTw9Gd0MQaFgkoBe/bsWb9+fbTCKjc0Ovu9bC6FE7+VR57uk0AdBDidW0Sc 1q5de/zxx8OVrVu3UkFNSDSjyWWzwcsmfouIN50gARKYHwGORKPFfOGdC2Z0X3rpJajpfvvtF62k mg3p7+80tYxrTVMi05AACcyBgL5voYjGbA+js5QxC6vB1sJBZ9ynWZaNa/tP2sQttwb89JEESMCT AEXUE1xgNopoB2DnOZY8Mrbw0VX9JRHYBkazG/fy0Bj1hwlIgAT6BPQ9BkeiMduPnnvMUku1VRqN Qvzh3qhSGyz9IoFfE9B3F3zEJWa74djC0NQ3wZgBGLRlnpaJUqJ5hlWzT6pfotk5JXaiuEQjJEAC +QlQRPMzn0uJBd5SxNJRc4vgZ9CQ6UipLcxU1rlcJ6xn5QQ4nRs5gFwWBdACh6F2mMNj1LEwuszp MYXrkSVyU6Y5EpgxAX0nxpHojJuJS9XxoA5a1ZYtW5SZChyGKj0fTbZw49LokLTzhOtoKf0nYjnx OwqNCUggPwGORGMy19+8xCy1MFvlQwj0cGAgOzAHG+WuItDzwloK3SGBcgnorzWORCNHMUpfGdmn j5u77bbblPZx5O/TTz9tEj/22GPKw/QLhxDi3vBSZef8fdfR52hcOgcLj6ZnAhIggdQEKKKpCRdn /5lnnnnzzTeNW9dff/1DDz200Mubb775mGOOMX/66U9/+rOf/ay4+jg6FD4pGqLBjs4uSN7fixRu kxZIgAS8CVBEvdF1M9aynfKwww57/fXXjfeXXnrpaaedZv4LQZWhKr6I3mAAKn/df//933vvvWi8 pjPUfzNMddtizRgXFMNvC6YLBUsmgeoJUESDQmh3vjA07RhltCZXXnklxqCHHnro+++/byfGYFTG ppitxdtmdu7ciSN/77jjDiRDjU466SRJfPDBB7/yyiujpVSRoDPvKj4PPLtpAl1a7Wyfl/lW3S1C aZDpDwkMEKCI+jcPs/JsDwv8zaXPedRRR+3evbs/oISs4ncI51VXXfXCCy8cd9xx2Iv76quvvvHG G5BVDExlbLpmzZp33nln2M0qhuN9RTRS1JdSM86z06SPlVsJy9ZKO86PbiF2K5WpSYAEPvEJimhQ Kyh86Nmp2ymnnIJfVq5c2f998+bNK1asOPXUUw888MDLLrsMr0F94okn1q1b9+1vf/uQQw658MIL kQUJ3n777VFeYFLy0Ed5x9M5D6H8QC88t8G+JzCj7dEIMgEJkICeAB9x0bPqphx41MHfaMqc9957 L4ahENEjjzzyoIMOMkXJ7/bK6EIvMOWLAetwMjMSNapTLCU/x/xypYzqYtsDG/T1e/fzu80SSaAQ AvrLhCLqH7Iq+lPsD8Is7urVq2+66ab777//gQceEPlc9rs/jo9y9ltesZT8HNNfWoEkk2b3q3tS l2icBIoioL/SOZ1bVODiO4OB4+OPP46ZWCx2YsRpBqDLfg/0oOSFw8CqSfby53WjVJNGSIAElAQ4 ElWC6ibT36d4FtBEtpIpyWjMw8MGhnEetW6iPbISJKAloL9GOBLVMu2nK3xQguc77UMV/OsZlrNk SmYFt4pNxWFx+FhubtONCJOmZk6AItpmA8Cjn5s2bTr99NNL0NEyEUc/k6/Mai7zquSbm7pI0tuZ E+B0rmcDKHlOD8KJnURSsV27dpnTEjyrGpBNPyUSUEiErE7RrKVSw1zaqEWE2NMECSwioL9AOBL1 aUGTzP7pz3/H7qEHH3wQFdu6devGjRt9ahgpT5PDnQZOgdd3EJEaAs2QQLMEKKKeofWQB7wRxX4p ymjBJ5xwgv3WFKfz37H5FucN4QT5/fbbb7Sg1AnQZU9y25GuXgMHBKYrlJZJgAQKJEARzRQUHKS3 ffv21157TV8eHk1Zv369Se96/rt9nIK+0OgpG9Ybzbm10XlGMehxCxilXBohgfYIUERzxBTH0kJB zzvvPBzvvrA8jDgxVsPQ034rGXTXvFAFCXD++7vvvpvD3QRl1Ks3ozC403UUEROQQMMEKKI5gvvk k0/ecsst11xzDY7NW1geRpzoi/GWFbw7Bf9KmrVr17744ov4gpeX4agEHJgwev57lMpgXxLWXyHn W7Zsga5HsSlGEukNHMZu5MBHekImnCtdJQ2pcsRWQVMkUDUBiqhz+Dy6HuyPRT+L6Vmc8C4LhAs/ OAX+vvvuu/baa//ZP/tnkgAH9eFfHAcPL/ESFWdfvTLgDWh4PAbvctmxYwd89rKxNFMKvcGdx1e/ +lWsGd9www1xvdVbq27WmjO6+uAyJQkMEKCI+jQP7w4Ir0OxH09c9v2//Jf/In/C9K98kWPfDz/8 8AF3MWmMg/186vPxPBgBX3HFFVhSxUgUI7yFBi+++GLMNvuVhepcd911yGvuJPzsmFx47QyG6Z/6 1KdGx80L93ZF3Kpa3ay1xx1hYLCYnQQaI0ARLSWgUCx8OioIXUQ3h9/R+0PVBp74RMpt27Y9++yz Uerz1ltvQSNRLobCsNy3efnll996663eZV166aXmBsLbiMkIU2eeeeYnP/nJ4XeGD+zt8r4rWuh8 itF2OKW+hbi1TuEhbZJA+QQooqXECHOnmLDFFlzbITyggp4OfzrmmGOGHcVLWjAb/Oijj3rUR6Qa H7Mci1VY2DnnnHPwVlF7xImFUnlKB2r9f//v/zVlYd/TP/kn/wRrkzCFwSuSwdrwYUkYyyIBdFqG pMaUWNDUAp6gXPiM7JgnN0vIJi/cMM8ILdvb1RmKyU6u8E9Fs7scjIaHmxbmTIAi6hb9kB4HajT8 nCge6xx9qedCd6FGmNKEiH7605/2mGWFVMvhDGY6FKuwr7/+OpRAfjcf7BAWnYbKIpeRScg/liSx bQo/4sXdWElFxueee24A7oYNG/BX3B/IjmUjumJBExXAxPIttmvBT8yTIyMG0HZG2ZAlvyzc2yXR vOeeewRaLAU1PpQ/u1vLoFnTHpiGBKYhoFmiM30BXNSnbzKlNwHssz3++OORHbOg6cjgkL9OM/rt 3/5t/HLRRRcNNy9Mh8r07FlnndVJadZlxe3zzz/fJMB5DqYuOKfX/A5ZMt+xvOrRsjWIlj0vZBcH Le+Y6s9CS1zwwRdw0BTtmqYjq67ZM6QXDzMUxCJIoAoC+iuCZ+e69fAYu/itJGGUI0qGbhrDL7dS i0mNwR9GoljR7HiEISnG0P/6X/9rM5JGfTEFPToLbduJuMFHAyxzcXApf4kaDiZN4e451YWJSSCQ gP5y4HRuIGptdmgnPhjr4MgFbZ4y0kE48QgmfMES47HHHnvyySfjF6xoYpXxkksuwUTod7/7XfyI qdRDDz0Ua5N33303FjV37typUVBZjpXZVDO16HQ44kJI9oasAYp+90PeYbHnTkPWBbwdGM5o3Etk n2ZJoEkCDuMqvTI3SSp8JCHbXEs4zNY1QBBRbMdFLpy7ZO8Qhvh95StfeeSRR77whS/85//8n5Hg 937v9/73//7ff/fv/l0MWLHTx7UggZxH27IVtBCCEdE8ldUHYlosej+ZkgSSEtDrnUOHpTeatG4T Gmf/IvChnT/+8Y//1t/6W3hFjH1PEGXK2gkyppGxfanjhrKFOBWktOmUrEwd5WXuFEQmbpWA/kLg dK62DRQ4/6Z1PWo6KCg2H2HoiVON8GSqbTvzlDVG9lhm7rsRtbqpjJlLtLSRKCd1U4WcdhslwJGo NrCTD1y0jiZOZ4abUg426Nqviwmcstbf/aFoTDJDQRe6oWEwYUCdqqmpS/Q0E8KJXhcaJAEPAvqL lCNRFV4OQw0mGW6uW7cOv+Bxkc4L1zC7KxO8+jMTxDImZgXyU089ZcoyZzssDBJWZ+X4wL4bqqBO kQh11F+cUzj46zLtNi9um8+0jrF0EiiKAEeiqnDwxtzGJMPNDz/8cPiVpTiNSP8wj3TZcraDeU5G Xgw3fAAF1NfvzanhMYV7eFa1/8DPsiZVi3yK/50bRzPtHM5NdckxEQlMSkB/tXIkOmmg6ixchpsL pQtnHpkjk4aPy5eqIzGySHvFsQxy3KD5dP67kJafgurBw8Nlx/pD3fUKKiUOrICCA2477BfK6p1M kdI8Ed83zomZFMBps1ICFNFKA1eo2zjwD0+2QHUwQDzggANGvfza176G43mRDAf44UlTe68vHja1 /2sfhDtqNm6Cl19+eaFBLA9D9hYe0L9sInpAfoAOA3e/cx/j1rdjzT6wbPg+IKkbNE4CZRKgiJYZ l/q8sodQOEYfT56sWrVq+CBfZMH7U1FVLGpCL3FaL95oZg7zw/m9/+f//B/zX/sg3Jx0cE+w7Cxf vCMdo+1lpw++9tprfTXCL2ZZtPNX7JPCnzyOPs5JY+GolGul04aApU9LgCI6Lf82S5dpWAgM9h91 9qTY/8XZ8Xb9kR5zszjFXtLgPH283cz8V95MHv7BKNnIWEe0MPaVt8qYD14RMzCkhm94g7oRS9wT mPfPLJuINqO6vpTiiHwsCUd/C3o4sY4FGUzb//YrxV1I0bHTYLEEKKLFhqYmxzB+WrlypfEYc7P4 jt2zwydNi2AgDd7Bgi/yDhlMaZpc69evt/8bZarz7LPPxvn4sq0XBdnHKuGVLzi20H6D21FHHQWl NK+C6YQEvuEJH/OjLJFidhfTvP1zqWBWVn+h4h3VgXIjCwbuuG+I9UbYRK3H3m3R2XlhV0rYdo45 5EpqoqDQ7LQEKKLj/HnxjzP6xCegDbI6iGlJnA742c9+djRXB6ytkbBmb+eR03pHDWoSYLwIMVu2 IajzuptTTjkFNvHWNjO0kteXms/q1auRAAIpxwvL55lnnrHnpeVHDLJx04C5X6SUk4eNzGBOG+Xi g180C8maaqZI09+v2N8n1dmOZN9FwaVlU9kpvKVNEshEQP9WGnFIn76ZlPOstWv47FeM9V9AttBa ZrDSgDEMNV1/36utW7diGG1+R2JNXZDGziVvu8PTtDiRf9llbN65hrGseRebndiVf4b0UeI1224k Q4BYREQC+obK50RHblb6d9+Z7m5mUAzY9ocyieptj3pRqF00hoYYN2PseNVVV2HQecghh2AWF0PM m2666f7773/ggQdGn6LBoBmzxMZzrIw6PfqCyXDorr1CbLzNxkeDPVa8FtauzCprsDBNkwT0PT+n c8cbQLaOjNsxxoPhlcJcD2aVzpiBgGHt9uGHH5aJWQwQMauMeVdoKpZCoY6jCopceAZGpnOHz2nC widmks28NCaWkf7555/Hcz5Yi+0PQ/FLOfOfERc1li2X2muoXnFmJhKYgoB+/Ksf3uptFp4yZ5Xt soan9cxfC6c37F5Stv0ryTiD6VPZVYQPJm/x33CML774opmSHbaJ+WGZT8YHM8BIDDdk+nfZJyko fd3hhj5xYMo2WnggBGafloD+unOYT9MPb6e4GUhSZvj8lcbCwESW/af+hKRrnbMNqTWOacho7PTT DDfUkLenLfQnukHXGvlRcs2VLl7LPOEEr2uMmD4iAb3ecTo3IvaPmTITcWaSdmHn2Jlp7KSxJ77s oYDHsABZ7OniEuYJI84Q9rktjGv0t6dFN7jQ7f4sdKpWu8RuukgNVKTT+DNXmcWRgJIAR6JDoDzu vjvjRWN9WTc04ehQf6ulbEyuyRI5MBC1wLen9SsY3eAAw0S4RqM2Vbmda2fCK2UUERO0R0Df7DkS jRZ9M7YzU/m26eEVr2hOuBiavFfKP8CK/va06AaHR2YyneAS5Dhpp20q05YehyCttEuAI9EII9F6 F288htpxr4VlA3fvUjT3j95vT1vmVXSD5YxHNTy9g6XPWIgbeoeZsnYC+iZHEQ0S0Xrl04xpJrzN t5upvskOX5yT3xZk6Ds6g9GkESyHZ6wWkiFALKIBAvr2RhEdEVH5c6efij5+yt/m9E1E6dvoom+n xL4DCy04KUT0SinrPmGypE2xNJ6l+TNh3Fl0agL6xkYRHYnFqDakjmUi+4FjaKXgDS/gjQqkk5P6 Rp8I6bRmU1S/nGGoYZuimtMGjqWXSUDf0iii4yI62teX2Qg0057D45iFf+0Lm761iUt+6fvzAZ0K Ftjj52kY6e7zXCOVs75NXpV5ALIUDQF94+fu3KU8AXF4IKWJRMlpRHXsp/GkyuYjumX20Bog5kep Xee/o1U26XEM3sLE2KeDsuSdMB0fRo0jwTKzmrzVpTGXemf7t9ys2KH0qFqZQpV/U7cHOmaZDwGK 6OJY231Tk62h0z8OP4HT76CjMMErw+yXdxqbOK4WJXZeyanpOiVqy8xG8bkEI/0bnb5XdsiMoLo6 X+xNZJnq7oqX6dsgQBHtxtEeb7UR4xJqgddw4rz1jieHHXbY66+/3ncPh8IjCvYbOs2QVPRgYY1M x7rMbAkcAn3oTAYo5wCWTTYYZyqddClW4wOjzOx1EaCI/jpey6Yr64pomd7iPV94Owp0UaQRgoq3 l+B1mziE3XYYLxHD2PTZZ5996qmnnnzyyYUDLDOuWtiH4se+2TKZuHoVODuycL532IeSB3yamQlX wkxPAh4EKKIfg6a8tfcAPdss0EszZ7ty5cq9e/cCBQaLeNHY/vvv/95779lkoH+7d+/G6zy/9a1v vf3228tGnPbQ6umnn5YxrlkK7ZttAL5R0Fh1MQJp7kWqG9jZq/WxsNAOCbgSoIh+jFh1/YhrvPOn f/fdd80rOY844ojvfOc7gIwv8ASa2vHnlFNO2b59+7p162655ZZrr71W5gYwFWyvAnY2yxx77LEY 5uLHO++8E9bwarO+2fy1DilxWWXTjQs7873G+fIvh2Weh/BnXhJwIkAR/TWudJ2UU0jaTvylL31J Oj7M7qKmRx55pF3f733ve5dffnln4hEaObzv6YknnoAR+VcEu2O2OqQL65uiFrZM9pdOU5SYwiYn kFJQpU0lAYqoElSbyTIMNbAIio1CwId/t23btnr1ahS6ZcsWTMPi9HZoHiZj8Sc80IIF0RtvvPG4 445zYt1f6hOzTkbKSZwiIgPP/Bj5AXx5pqjDEy8MLwfOqCcp6I0WygQzJ0ARnW8DyDPy3rx5M6Zn 0bvhXyyFnnHGGSh3x44dxxxzjKDHkPTxxx9fsWIFVknvvffeevUvVkuKFRfcvoh8dp75gV72d0oj GWbCO1WArO7cuTNWvVLb4VajE044QW5Y+clJgCcWfYw2+vpYXVjOKHqXVXt9a/e/E7jw3UNQR9yR YBVZnrKFXuIm5sEHH8S/69ev7xeH1g6hXbVqFXZj4RZH0kA7MWdwwQUX4EYH/TIMejew/BnDGeb3 mSUWSEDfkDgSLTB8zbqEKVw82dJs9cIqpr9oB8p55ZVX3nrrrbvvvlvSnHXWWRjfL3uUCAlQ6Dvv vIOJAdsmsm/YsOHRRx/Fj0cffbQ5OiqsfplytzEe7WwuW8gOd0j4HbdN+Pzwhz/EEglyYS6nnxgJ cOktNILpCl6SgU2TIjoOUBr0eDqmGCSAKxk7abEvt3+KQgi5ZkITZQrkxRdf/KM/+iPooiBdu3Yt ZHXZo0Qyf3vZZZfdd999/+///T/ILf6LLvWiiy465JBD5L8HHnjghx9+GBKg/Hlr1NG+aprFaQMQ dzP2PDweBsOf9uzZg3//5m/+BndC+I6L6+KLL+7c9xx88MFySyQf2X8gAox/f/azn+WPUUslUkRH otlMHz15q73jjjvEB3lUNMrHflKQkQJS9JW4TTn55JPRk5qbv4WPEt11113Y5IV9Q1u3bkXGf/yP /zGmfJEF2e+55x4ESw6Twkp2lEhlNhLljiSDz/bzWv0tcsYBadvQSDxCbX6UoSfugRC4TZs2Sezw bBg+5557ru08puXx1LUpC/sP7r//fvwX+96RMUM12y7CYQkwynRT4TTtNTbTKaNxt1r3nPXCEOf8 889HA8CME0ZI0VtCX0Rj9aTpLNsQ0sUCoxM882Pv2EIIMDyVp4w6n44bGKwsTBY9fNENpuMZ7qrd ojStVPolxAJ7100cEcSzzz5b4wzmcnF3demll2oSM40Q0LcfiujH2owR0T5BPdO6WqF935Dac5ll 6pwsn6jQWPHK1hJiObyMJ7pgjGMw+rzpppswEHnggQeWbYR27eITRTDcbGqkSg8XzpFotNPYFwvY IIZ/5Z4G0cTAdEAXIZw4DgyPeyElhqo4R9Psh1e6PfNk+sbD6dwFd+IL8dW40DJ6GSy8vEdzeSeA fOZRUHgYMV6d/i6iZZukU6/qEQL9o0T2apzMAXoUV0KWRJHSVE24GXr90zM0RkwaqYhstBab2DL9 1a9+dcCISCY2V2POdteuXVRQJ+BOiTkSdcLlMMZ3sztdav0N13Q++pccOM4egGOkJaL4lRmLFDX1 j6h7zsA2oC+wc7cRsWGID9kqoq9ywyn1FyNHom7NIPqF4VY8U2cnsCziMraQri3WcM175JT02SFT 0+zsoxWYbjA9MOKM5v1HhniKQlyeEa1RRN1gprsa3fyImrrtOwPvkGkydmY+w8PioaOJnh3q16Uj GOGVzWPBA6ntmF3r/nektKdqE9UICip7iAZOcExUNM2OEqCIjiL6dQL9AN/BaAFJNWpRgJs+LnQG i/pRo2usA3tqu262z5o6p3h2qF+uudOq8ZbLIzp2U+mvaGYQTjsEDz/8sLxfoaJTGDVNt400FFFt HF17Va1dpstCoNPrDd83+MXao6deVvX+XPGAw1dfffXxH32++MUvJmVZ9bzucHSGh5hJqWqMn/nR BynPO+88TXqmyUmAG4tUtP16VZXpAhLNcMPCwoDaQuU93krUVIbN5nx2CA02c4PBc66f/OQn+2f/ elw6A/ci3hH3cMMjC0KMQxIKd9KjXsVm0V/IHIk6BLHhaU8HCk0k7Y9LTHADx1vpurkByzmfHZL4 j14Lb775JtI4nbuLc/M722fktSQ//elPYx1NZ09KdyZpC2/X2Z4NK5xDge5RRFVBsafXVBnqSTTa G9ZTFTdPTX8qU3nIHFH/2qaqAYWTHJDMqevHmb2d15fiaUgcbtU/+9ct0h9PHXHWPcQN17xttyhX GkWlp4g6hEPTdziYKyZpq/UaBiy9kpHPiBAq7aZd2+PALi1zci/SYDRpLGNYiV/sNxDg4Rzz4hHo 5QEHHGC7gaMisfcY56e/++67ru4NpHfduhWxaJpqjwBF1CGmvBl0gFV20ijLn6PddNkMgrwzc6Fy I9K5NL7+9a9fccUVGFbirBz7daTPPvssztyx30Dwmc98xn4RG45Qxzyw8QyyisPtsBZo3ksT5LSV ubq5pYg3ebEY0o4QoIiyJcyUgC0DNoKIt0p9dWmP9UI1wvG8WOC88MILcXarXWWMKXF2nf0LZn1P PfVUjEeFFf6K033NGBfyidePrFmzJhE3DkkTgZ2VWYqoQ7h5M+gAq/ikC8UyYogjmoqo64nCYqsR FBHvYlu4GooTXHES+qpVq4wbGHfi2Uf83tnmY/6Lo1+R+PDDD0/necRIJXKSZksmQBF1iE75fZlD ZeaddLjfjBLoWJuVYtlJHXAzJMWr11977bVOcbLwKYcrnXjiiXLyDhZHsZkI78Uc9g2j1c6INm5d ooQ7rku0VhEBiqhbsHjT6sarwtQRtwWFt5ZaFNTEWaqMWVnIpDzfgrEmvmB7EcRS3kNy6KGH4lwI bD7CG6Hxo/KlmImaUl2EqfeJmkGIWR624EAPLTi8W3QoL0vSJiulITdc8fC+1RWs6R/tNuZqRFPx DGng9tatW2+55RaUhR1GMiVb5qcuwnV5W2bElV7pewAHVdAbVXpZXbImW3CTldI0rVERDbxhcrpe TOJOrhqjg+dY1q1bF0hPE8EoaZzCFKXEECM1toeQ+k6YV98wOJ2rChOANjyR0nDVhqObtOL2Xpvh guzL1Z5MTuqeqt27JzLvG6nF+VrEHqGoBal7q6k7B0V0PH6mj6voehuv1a9SRFwC1BdaQsoM0Rx+ mNKGYDtjRySDk3FjYd43EtcsrQmB6trDHALH6dzxKOvH9eO2ikzRfAWXUR+YHEsxb7aMc0v8sY0I G25fffVVvLqr/B7fjO3Kd1VGolX4WWQn5+yU/qp0iIreqLO/xWdou/kumyZq/orNLKJmRq4PtsAG 5i0w8r6RKoZNdfVpBTaS4ntufwf1bYPTuf6U28hp95X2A+/S4y/7NFD30RUmu+6x6lvFfYlU3Kig +e8wBGgnHmvBgyt1KWisyNLObAlQRLWhH+1ztYaKSWf3lf3O3V7Pk/60v8JXu8QOSFqnvnGDVnJb MvIpcISDGUP3OeD8BMgnPtu2bcNRRPJYS/n3Cp1qxo1vOmslt5x0tS7cMqdztQFqaS7Fe6ZOA6tz nRfbn+oDqk+p4SOCZGPRTxwp7Tslw35anBEvJx4MeCJ/wlEJp512mm3/+uuvl2P8DjnkEDkXt9iI G7enBe4UnU7i6E0xxJm28+obCUeiCVtCgbeNw6PPKCxGx6xRSoliRBMgTRoPZ4xZ/bXqUYoyy8sv vzysoJikxeEJSNM5Ph6/4L0rOPkWm4nkT2+88Yay0KmSRQeOvVSYx7bf+DZV1VjuJAQooqmwy7Wa qAv2cDqDfPa9sgXVnhi054E96hIli37ApE+pdMwYjN6hKx3A6NN0+njd2GWXXTbgCV7q+frrr//R H/2RzQHKgRP78C9ezCIn5eLFZ0iAc26VPkySLDpwzGNfddVVGIvbb3ybpGosdCoCFNEk5O1rdVod NXKFehoZS1JnndGOrMp9hhF4nY18qZLGzh6MZoYA4ZROH5OxQnOgbaxfv/6SSy759re/LafGi9s3 3HADXmG2e/duHChvhqcYsEKe84VHXVLnKtDkAxk5+3f4g5e+ofp43WnSpmL7kK2gsarz778kQBF1 aArK5msraPRBjN7dztBzQk8GfO5vVtJXMErK0Zgm4tYfoycqqE8JW4HMj3hbp/0S7GVI8RIVnH+L 95FhuCk6eu2115opXMz0wnm8PRTv4t6+fbvGYJTYjRrp30E6QdZMTWM2uzOPDbzm1gQe4r94teqo q8oEZpPXaLtVGmSyCAQWXswDV7g+fXspBbem++usCy7LlQKR3SZS2E9q0ziftJROdAbKyhk4078n rfuLL76IN3qaIrBRqC8VUEdUHAfHL+tfjj/+eGTEvwsT7Nq1K2kVlMYHrtZlFq677jrUS/6KL3v2 7BktC5RkHjvzJ3PLzFy7EorTtx/uznW7EcENYP9mdnShZTSBmxPLU2crKJbDC+3krMVAWTndMBwW NrCItDEwOu6448zKJV7zecopp6xevVo65YgFlWDKDNecqoaXir/30eewww7DVPZwRTDle/fdd+O9 4pjfxiS5JMZI9Ktf/ap5LTmYY+UY26+wuvzCCy90tjf7gUrdTvy8aimX/vLndK5D3PtTKPaU6YAh uYaTzsAoPXGo7XRJM+Cyh7yjgZuOxNKSMWVqz8o6eXjfffdJeli48cYbIag5gTu5GphYBjSaSw+v Bzez0DgsYu/evStXroTgjToApTzzzDMx0Y15bLMejDlee20YCvroo4/CFFQWo9tRm0xQFwGKqEO8 OhekuVXR3OcqL2YHb6ykTp74FZE5l8GV9M4jc6VGi8MYaDSNJPjJT37yyiuvKBPbyU4++eRnnnlG brnuuOOO22+/Xf6qacMexWmyQL3gjGYXj8ZaP43m0sO404zOZfR55JFHYrHTrKraX7AGbP8Xs9/4 XH755XjWVn7vPAiEMajsf4Y8YxHarxb9XLO6NGJBS2GHIupGtdO5O3U9iYRBP+3gVtWpU9vDCDPO ju5UOT0Rxi4YzSgruGbNGqxuKhPbyTByuvnmm4Xtjh07OtOV6Whgc82yjbu4IcBgDgKTbkfSqI6+ ++67hpLIuQzQF35wKpP9OzBiiCkbns3vNljcG2G1Vf4U+H5yMBRKTj2PRzthFj0Biqie1cdSmi7e Kb9+fkljtqUp3GX1Nb0SEpjbfw0cfZoS+iN03FDQ8847r+82Jl2xlmZ+R4+MhUysYr711lv6OvZT ojvuDHyTcsBYTXb29j8YqEGHULoZC+JZGtQxpHb9vPYtbP9eAQ6IxuNfnF+I05cCSwdbTBHDCMKH p4AwAYAQBw64YRBvO0foTeDS3fQEVn9W2SmizuH2k0+7mNH7Yo1P7U3hDtc6g5r2HcjWST355JMY 3ywcpmB7i70495nPfAY9PgaUOABB004WppFXZ6Nzl0c/M3wwUDvggANQEG4IQLU/KoXGiHBCKvDY JeoY3atOE7Lt40FY6BMcw78AHr73B3cGsI8TLRBTbFfGfxEyOGB2G3nUDtuXJNf999+Pf5Pe9Hi4 N9ssFNFpQh9FR+d5FcVS09Ep4px48SAmipMDEDrrcNilYrdRDNdwygF+wWYW77ZrXp1t+mUp19ug JiMqgqlIHNqAuU3ZD4wPVBzyCWXFbQS0Ewm++c1vYuEQW4hzzu4Kf/lceumlmuqMpoFNBBQffBlN rElgDpk644wzTPrUUdM4NvM0fMRlygZgLgDX/rrVdVC/YCzrRxZStROPYkfi0TR+Pi/LNdok5K3X GKhhntB7wGRenY2lShgZLTSkjph7xJB31AKeOsWcJ85wwKwvtj5hXI4HWJMeIriw1hgiY4gv48gC PzKCN8/SmFufzK20QDLRXdL3sQ59hN5o9Pq0bdC1p2YgNO1h4A5d3+O4hkbjmCaN7Tw23WDnJ6QI RwJhqhMDNRxaKy9dCfmYV2eLET2TkEJRCxy0i8c8zjrrLFsJQmwG5rWvJpnlfuKJJyDkoB1oOVv2 qVpptgpOUpC+m+V07iQB8i90ILSdacCZz/OY2bn+F3/6uXLaU9Z4rBMjuS9+8Ys4mXbTpk1RFBT1 MK/ODl/j11PBCA/Tm3jeI2RBV1+cJqW9sLJwlltjhGnmTIAj0emj73QjuSxxX1ydzE5PoUgP9Hej Sd2P7kZ0g0mrn8G4XCydWW59uciIs/i9Z9f1BS1MySs9EOAyqsoZGo5EU/BPZXPh4FIGoMp4p/Ks Ubt5JjkBD70wpmqXHThgRktRZheytZbhSpXTZAxVLMHeddddjzzyiKscOp190XnXDc4I9D58yjCM 0jDKiUhdnlBEq4nXwr7P/Jitu6+GVwxH8/RN0E7sFcJULZ5QXOa1mXQ190x+9cumoJpK+VUhRS5z +eARFOVTKPbbWpzOvsAKt/3ILDYDG80GNEis/uAqQcFrP0WT0NukiOpZJU85uqhpj0g4AE0dj2x6 g6c75DxbbEkdfq4jipTm6XP1lUodx0T2oXzQP8gentLpn32BZ16NFmK/EtqSnL2Aj3lk1jiGwajE HWfZb9iwQQ7a5acWAhTRIiJlK6K9qcSWVTi6LFkRdWjLiWwKCmx4jhCPTuILBiiahzq8pTTPwFoa gmulKmo+Mk1tHMYDOf2zLz73uc8ZLXz22WfxYjUcam+yyCOz5r+HHnoollTxsCwmJHBYkubg+z6u nMGtKFgZXKWIZoA8UoS9fdROGr6/lNeVX3RzKqh4iDENHot0eqyiI6XKWOcZhnpXyi9e4bmU9KQg CN7GjRvlO+QTY0d86Zx9gX3Iq1atkjR4i4scSY+xqdwHd06ox9vo8AuU9Z577sFbAcrZuhwOdg4W KKLNRjlnd9kMxAknyTVj0D7n/rxFUbHQVMo+GXgS512vFJxWb6+b4qAluG2OE5IqQC/ld3wgqHgR OjQVX0y8bDLf+9735GXgeEoVx2j4HXnoWos+6ujnFU8SzfyFUkTzM89aYmdCOGvZtRVW9S4te2Ba DvjRDbpYU+y8fbMc55d58vLLL8t0LpzHcqYkwxJp/9B5kSU5gx7DTdsgfsRaqVjAW11xzKF3xc0w GqZC3igH8banqb39mVtGimjLEe9MFBtBbbnOvnXLP4Xr6+lQPvvogBT2nWyaDbpHHXWUEZuOBQzp sBJcwulFozO65oYAxy1hhy3S48AKrF+ad+/0D53H8BSHY2CqFgPNzqAcootzJ8QCtFYzZB+Aj2Ot sK0XCbAosDCZ5kEaCLmZpnYK9MwT87CF2TWANtQiethawrKsLvg9fNJPTx7DGjy3I+kHDsKFhEBs JtfR4QaAG4Jzzz0Xm6jxRm68kFUPIVZKjFxxXGL/cHzbbaTBK2g674jVO1BIIPQOJ02p7xA4Ek0a iBKN5+xGS6z/Ep8WPj5Ukf+2q4WMR80G3d/93d/FvtPOTKN5rmP//ffHmAwDKXRbywasGQIxDG3y J3bsJ2oMDcEFz+2J5T4rvGYAbPFvf7IXC9JmTRqBWLinKXCWOEPspi2CIjotf5ZeEIGFs98F+efi Sl8SRqcrXcyPp0XXjDVCjJz+6q/+6ktf+hKmCjGQsrPJcx3o1jHVid8xvHvxxRdxrO646WQpBu4v J3xip/9EjQEguJAAs+J4f9zKlSsXPh6Dd5piJgDvc8VguvMmV6Q3I1fsIsbrAfp0q1u0TtZAlt+A DzxK0X/6QpmYyUomIG2hZA8L8a12Srb/meuCpzXef/99xBH/4jVnKF02oJrPstW7aUM/fGnA5/zu gZuQlA+WkM33TqfeQXrFFVcs7PXtWuABZWNt4PRB3ADlr/i0Jeo7SY5Ec9+1lFDewB13Ce7Rh4gE ZACaeRiKEvGAhzwHgn8xW4tRZqdS5rmOTl8Zse4epoYndQO3/3j4gywLn6gRUxBX+VcYwj0bJgag C3XIrgUmA2RsiuHsD37wg86Njsnuvc7qV+W6clFE64pXHG/zd6lx/M5rpQFKtiRkvnOCiJrnJTC1 u337dswWRnyuI11byAxqtCL9J2oAFsoH2ZPDlpWH/S4s6JJLLlm3bh2aOk4uxHxv5+R9TMhjdzH+ GvLkzGgFq0+gHzLrh7d6m0w5CQGEcpJy6yq0GUrLOqmk4cDQExtZpWhM55ohDqZ58Qv+hARJHQgx XlToAUrmw4WbTMbKEfZCOKSmo3lxTARKGU3WXgK93jlseddv+a3+zqLpCjCOmvA2T6n5CmqivCxN 5meBlK5i9Inds/I0qnwYRCU6j2R6tpzO9cBbfZbSJqxKA6q/fkrzXO/P8OKf3k4/Jfp615d5hRQ3 k7ygikMBcfIRXhpDBS0q6BTRosKR3JkG1vmSM/r4bX624vIXlEJH+319/no1WeLDDz/8xBNPoGo7 d+40FeTdcAmxpoiWEIWsPvDCG8UtCzwyXSaf0SyVJoiuowv7+hrhmNAX0gZwsB8+WByVUwbNputC 3KsxxLF85ppoLJIV2JnDLGWKMDTPLWIFsWUUhxO9+uqrOB+ns9UzRWjS2ewwKWGVVLbI2ntxxavO TR7vkqO0Cv1FQRGNArwOIyV0BHWQ6nlp+qlWeyh9lzEawX5fP5ql/AR6Pk4pozQn+7rWl14+82k9 1JOkiE4bqXyl69tEPp9qK6ntuxC2kOH2OBz9FHP+SontOMY4RulX9BgpolGAl25E3yBKr8mk/rUt omalTRgre/BJA5K18IHop7i+9JMffceab6gZAq+PKTcWZQhHEUU02SdiBW7gwM8iuFflhHlkviOo VVUiobPoWM3HFKPvbZ086+xuW5Z32Qg4xcjYyf/5JKaINh5rueZbreRPfvKTV155ZVntNC8ibpVM YL2i79oN9KeE7PahPOYmI5GCmvr2N4rbQp669BKwl+8DRbT8GPl7aK6xJoeh4LJmzZr+yeaGF97D VfUGUf/Ax8hJHR2gaMPJcHENH6rX9zODSzGaWCM2KKKNBLJTDTMAbfVyuvfee3EsDk7Nfuutt0zd MfTEedk2CvPmZ/NlNN7mRJiFKRse1rMvHm0bdSGaVVv1iF2sLBTRWCSLs2MmgorzLIZDn/vc5x59 9FE8M4fTRI09vGH41FNPxUKp+UXe/Iz/bty48bnnnltWMiRZXgg1rKCt3pEMB4R98UI+hTeGwt2L 0QeUYoMiWkok6IcTARzDvWrVKmQ5/PDD7Yx40t/+7ymnnLJ582bIwKaPPp31JPPfG2+8UV4Ideed d9rHqnEwmrMv7q/2OTUJJu4T4A1QhlZBEc0AeZoi2r5+MJeLN1aC7AknnGD43nzzzXht07777mt+ Wfbm584iE94aLb/gy44dOwYCNreVwsytqLM9OHPpThdqyb5JRXLeADmhaywxnxNtLKC/rk57O/cg nO+9995JJ52Ex1owvsSbDuW1UHhH8Wc/+9kVK1ZcddVVGzZsOOSQQ4466igsl950003333//Aw88 ACmF4l544YWxgj2T5/DyNCFbjTr9fh4H/FpFFW2gCif9+KfOpW97HImmjsVk9tsbM4lkYuh5zTXX 7Nq1y7xYEbKKc8+hmvgrDunGjlwMKKGpWCLFYudBBx2Ed0hFVFCJaPkDkcCWp+9EnArqz6jLmGnh Ej7HUk5smXgSAhyJToI9X6G8FU3EOpHGJPLW1WyK2pnbDidpTOGJK42F6au4sqpwMko4ohvRNzyO RKPDp8G0BAp557OTEqQlEtu6vvtwLdljx3jJnJufjXCN7zzTU0Tbj7tMoLVRz9Le+dwM2E7zKFm6 CmnJ7S2XFAK2OjcootWFzM1hc+/fRndf1Dufm1SapO0kqXG3CyNGaupoDIrV26CIVh9CTQWa6e6x bwif448//rzzztNUPGmaxiQBrNJN5HoHonDI1FHvyDaTkRuLmgnlSEUK7B/90Jfzzuf2dm0krZGf 8SrabbFO+jH3uzAby6WPKUW0sdAPVcdve+SMALlUVX+NuVidOG26PjcEV0jebEDLdDJdQLOBnaog fUA5nTtVjCYo12Nv5ARe1lNkM5Pkgjz1xKk3Lu+My5pSiq120Z2s5zqYu6cU0bm3ANbfg0BqvfFw KTCL/r47sCDv7NGVL7pB76olytheK00EKtAsRTQQYGXZeV3FClh7I490NQpvdVE2mYtqmtuFOewJ ShfTWNdRA3Yoog0E0a0KvK7cePVSh0tCoAM1Zo/S6kJkz94QYJwJMVhjFOhzCgIU0RRUabNxAlEk oTRGVdwcGNnz8HbgeF4Pa6WFb6E/rdarKPgU0aLCkdYZXlFp+dZsvaLbAntq18zQDrft4b/awtzS NcJxdp4rkiKah3MppVTUV5aCjH6EEUgkSyKl5gMfhzcKDbd8205YdcvKTR3NEA8+J5oBcilF8KGx KJFoFWOKDbopbA4EcaFgQ0j0IRt2ePSGoMyb1MxRiHKVTW5ED40iOnmw8jmg70ry+VRhSQ1jjF61 6AZd24u9n0iZ1/a5r5rLZFLf5yrdiJuscPfiVjaKNT0xTudGAU4j8yIwOiKpF0fEqkU05c0zZJ7W dKOdeeO+M/oO17sigRnLHCIHVqqQ7BTRQgKR3I0SerTklcxSQMP9UfSqRTeYJcK/KESvi/qU2Zxn QTkJUERz0p64rHp7tInBzax43m/pdVGfsoRGxMimiAJFNAVV2iSBWgnEvdOqsdfWzwDXpaBxI1tr +07gN0U0AVSanAGBGuUhc1jafr6iLgXNHPpZFUcRnVW4Wdk4BCq9qUe/b38GWMS6RagU1DIyHXqN 1S7OtTE/KxTR+cWcNZ4xAc3pBPPUhs4dRv82or9Zt8Z2FOv2qMa6J/KZz4kmAlucWfvpt+Kcq9Ch Gmfz+m1goEuNJaVVNLx+NBeSicVkwvZeRTgm5GOK1l/gFNES4pXDB1480SlXh1TvsL4HGaWqL3TU VKIEESubyMOIZssPR8TKhpjStwpO54ZwZl4SaJNArD1BGSYPL7744qeffjowDA0MMTUEMoRD40Zj aSiijQWU1SGBOAQGdNQsHw6XpL+XN3Y++OCD66+/3qkCN9988zHHHGOyIDuM6C3MTVdmcrugbwDh KSmi4QxpYb4E2u6COzpqa6f50zAB1y57v/322717t749PfbYY3AAg9E333zT5HrjjTeUFjxkXmm5 wGRtt9UJgVNEJ4TPousmEGvOs2QKHbG0N/fKdzgv4mpqYWutR8d9+OGHd4BceeWVsLNly5aXXnqp 86edO3e++OKLGIwedNBB8qcjjjhCORKdlYIKHNd7mpJbZjm+UUTLiQU9qY/AHHolI5wLK9uRUqNM ktiJD0aTDz300AEHHGDaAeZmMdbEL7CzY8eOtWvX2k0EYrl37178C3GF0CLvaAN6/vnnJdkMFXQU DhP4EaCI+nFjLhKojIDHoFBfQyOWRlP1eWUVE/KGidx333131apVZsS5cePG9957D78jAcRPNNVY xtwvhqcYem7fvv2EE0447bTT8KeVK1e+8MILy0qHDO/Zs4cKqo8OU44SoIiOImICEqiVgJlZzSAb Hfk0mg11hMLhv7/3e79n+4PvJ554Iv69//77V6xYAS285ppr3nnnHUznrlu3TlJu2rRp8+bN9913 HxK88sor0NSTTjrJDsanPvWpBx98ENO5oqD4HHnkkchiCpKpYHygwfgXdt5++23XIXKt4affWQjw OdEsmAsoBD2I09xaAS7X4UIGfXIC0RlxThV0095uu+22Cy+80KkKysQYnt59990exksLmbK+gcnY AzgB1DcSjkSdwDIxCXQJTKVSHT/s7TzDq5gZQih7ZaUbuvPOO/Hl3nvvdS0XWSDAA7k+/PBDzP3q zUJ04Qn+LSRkes+ZsmQCDqMTvTKXXOHZ+sb70HShn5atGXqWow0Qqi984QtPPPGETJziMITXXnvN zLjGCoSU8od/+Idnn3222MRiamfz0bKypg1ZLAJ6O+y99awkpZ4YR6KubJmeBEohIKNPEapyFBT+ YMsPFiNNZ4RVz5NPPjk6NZRy++23y6Oi+OBpUSx5Ri+lAYN6PWigsvmrwJFofubTlDi3W+9slKfq oaYqVw8WA1Dsm8W2IJx+YJ7jHM0OUcTmIH36UYOdBNhhdPDBBx977LFy2wHpveCCC+wzj1wNFp6+ /HZSJkA9N4pomRGM75W+TcQvu2mLU92dTFWuUzBdWx0eYrnsssuOP/74Bx54IJGOynOi2MFb1Njd iapTYtcQOBlvOLGeG0W04WbQrVoV3W518ZiK6lTlOgXIyUlsR1q9erXY37VrV+dpFqdyFyY2i8fy V4goBBVqmqi4cIdjWXCKQqxCa7ejF1GuidYea/pPAo0QwNATD32iMlu3bsUjoSlqBcs4JhClyDD0 jjvueP/99/E9umCncN7PZufWwc8Icw0QoIiyeZBAKAHZ2NL/hNqdX37s4MUCKg5PwKahuLU3WoLD FnBokRh/9dVXURyOg8CzNMOP08R1JrO1mUxcZ6ZqiuN07lTkJyiXszrRoQ/M+fQnD+3SzV/tDs7O MtrxVRHNcpwUT7Br6ZOf/ORVV12FWGDHk0TkiiuuMKcGRm8hkxssJwSTo3ByQD+dSxF1Alt3Yl5O 0eOnRLpwSg19ev930U7NBawsOnqVnQwW4qThib24l19+ufJZUqeaFptY05aKdX5Cx/TcOJ07YZgm KJoLJBNA/9VznPZBQuYlJ/0f4aEtpZM4HLHQyZucOIClUCgovsxKQU1bihhQmuoQoIjOqEm01DWX ELak8mCClbSU1BhHJ6XTOWCWqGXCFofaH3jggV//+tfTlViy5apbUclgfzFvpG/l+uFt4XWeuXuM Y6wGkGeuclm88pQezipze3NaVw6vXS0Wamkt5fDUt1uORMuJWiZPOB7NBDpSMQtvcysaWNhD6tRu m45PCsU2IpyvGykOFZtJjb1iNDFcp4jGoFibDepobRH75VYjcVt/jxy3mjhOSI77cf2YdV9xXj5K I8rEJpm0bdFOvI5027ZtyoImSYaXiuPj8Yob21us9Q4Ymaq1TMJzkkI5nTsJ9iIKNR2Zfkq/CL/L cCJz32SKy1xuIth6Ee04YNpq34LdjDEGhYJKXqeTexPVN7PZDhxe4B789RcaR6IeeBvJIuMDM7Jp pFYZq5Gzb9I/+hICAGNNeRUoRpw4gkBM4Ts6FPldNriOfuwBK77jKUxYsMdbnT3Jyv9KW7UHnXZG 2ytzAtGtt96a6AzeYQg4fN+4ii+dETzYGrzGDt57Mzr5bMcFGWFEqOKLKcKe0zbX+GjImMCbAEXU G10jGamjHoH0Hkh5lNXJklS5Dz300N27d6PEww477IUXXpCiH3/8cZyT99xzz+H7hg0bRE0HPlAC HKeHf/F2TwjDu+++CwtPPfXUjh07Aqu/8HGgAZsYg1544YWBhfplx2thcPwvdgVDxXGyYOddqmBr 8Br7uNUAseHi7Lgg5Zo1a4QqntsxxzDhv0kbiR+QlnMp7wFNVPTpmbIiAtLEK3J4WlenYpW6XKjO WWedJY1BDpjF55577lnWA/7Jn/yJ/AlqMdpLnnnmmTmjNm2Txk0DRNSur0GE3/HQKk7xHSVmYmGn NHHpjDJh3/ySk3OrZenbD9dER1vyXBLo1wDmQmR5PcFqkpv91DHC3OD+++/fGTYBA86VxdCqupdu ThUmIYZBsLyXBiPR6EcBS9uE/YsuuqgzxE/dSGZy+esxcjp3Jk1ivJqc1x1nNHUKE6OI88lYS8Ms ImZfsSB64403HnfccVjPw9onfsT2HNQYv+/cubM6BZVYGVD2CmWGMD7zzDMoBcuxCFksBZW4IFJy Vj6iAwXFvtxOdSa5vcuAtNwi9INx/fBWb5MpSyNgWmppjhXlDyhN60+/3wzxRyZs5TVhth1MPOJ3 vCK783tIWZnz2qDs+c/UbmApFDzNjG5cgGY2GIFbWBH21eHx1TN0mJXSD2/LvWWgZzoCfPplmFNR 1wKDpWvUv06VJ3yYGz/nnHPkLuT2229fv369q58h6Secyg5xu5y8+kZCES0nasV5om9Gxbme3qHS OqkowcKE4YoVKzJ39+ljtaCEKLhGPceaJXY14wXjsWZ0R0s0CUprn3rPC0mpbyFcEy0kZCW6wVVS zXi0kMiFr4RhcfTYY4894ogjZCl0Dh/zyGmKymLxEmuWk5yaFHHJPAWZxmxSRBsLaOTqUEcjAy3Y HB7uFO/27t1bsJvRXDNLpPaeI/M9vJgnn3xS3vt9yy23jD5cG15cx0L4TVV0l1o1SBFtNbLR6lXa 1djp5hb2gAM/args60kz7/DUuBoxzdVXX43VO3y++MUvRjRboCl7oLZsY074YA6nJl133XWo/iSn JiUdZBcY0wld4prohPCrKVq/PJC6SsaTTj+4sNy+25o9OAuLMPbtW4rSlp3C/ZFj57wX8PDoBR6G wTE6N998s3dLgA9Yl8XJDJdffnmi52o0oGK1eYxBJzl3EPxjVcE7lFVn1NOjiFYd6HzO65tUUp80 3d+oAwNS6lTNKM6MeqtPUJo/es8zp1SC0txyZfbctbgGquBa5Vjp9V0Bp3NjMW/cTgmTuuEzbBKk zmKYiZz+smk82Iuqh8f8zWw2Tnm1k2Ds2H9FGh7w6J+x3jeMkxzsU9dhBzuEkaxz0vokwO12MokD 4YWWcNmG16JwCxTRwgNUlnvLFgvTedlZhozYKfT3lYi+OtUllq47FTpJ4q9//etynDoOEMCB8rYP ONuo8wv++vnPf75/xnrfc2wGtk9dP/jggx999FEk65y0PkmVzS3XhKVHKdq1VUcpdD5GKKLziXVo Tc0WDBjKIB5mZ4TpAlL0BZ1TbJwYddZH899h2N6mjshNN92EV7LgPFjzljH8V6qMA3SkSdgfqCO2 p3Z+7P938+bNdi2wCPr2228jGbI7xSJ14tR4k/pftfNJyUQxzjXRKBhnZyTDzKdy4Wpa9Hb3BE3N gGVZfZPikinWRNt87BqhIIxEL7300nRh9YuRX650tdBb5rKonlX/rlRz486RqB/huefStK0QRrXc OwsHGc5O2M+mxvXee++99tprIQFdmBfrpvhAOOV4Bznt4eSTT45eUMegR+v1yJK6FrRfCAGORAsJ RH1uxNWMvgxU1G1NfrOfdBiKpimv9MKC6Je//GU8AIP/7rvvvt5PwvTbOkQUD7Tg9+3bt5vp4kSX hDeruA0+Ue06ZidvmXmqmaIUfbg5Ek3BfxY2Ix5mZNqr/eR7LRBt52vx2dVPPOm4Z88evN4LT3Ci vjfccENEBYUzEE5sTcIntYK6VtxOH7HBL3TDLBiHONnPa6/6x7VMa0KAI1G2hCAC3vf1v2x/++wj Xyoad9q89LerQZTHMmdzY8IT1ccYqP4eDircQt9Re7wYd+wYeHmqmDaaSB9ojkQbbQLFVMvcXy/8 IvJZo4JKdeqVf48GMuGJ6h7eLssS2NgCx6OjV4H95FXEWtNUOgIciaZj277lARWx1zgDu60COZYm n3kGHFi5xDtJJBxvvPHGVKfZhbSHWKA0zdtOY/usvByiDElj1TeEeaV59dc4R6KVhrgUtxf2CJ01 zlJ8jeFHgQPQZZ11jOp+zMa0J6qHVyciqM4z08PjS3ulX6mg9gxNoNuB2cOxN2+BI9HmQ5ykggtv kzW350m8yWI0ysgghaeZRxsTnqgeSC8dqHSWUWX9kGghn6S+BUak5Ox67ByJlhzHanyzx2eVrnEO s7bH1oVEBQfYmsNpjcBjxhWn0eIsoXRO1jiLm46GWNaPLz08CVyF9SiRWZwIUESdcDHxrwmYa7tA gYkbJ/09adxyB6xhj88TTzxx1VVX4aSCBx98UFLi4IJvfvObhx566DXXXJPNExaUgQB1NANk7yI4 neuNbtYZ5zNHNK2CYqwJpdyxY8dAa0Mac9IsBPW0006bddNcUvlp4xglIh5V8MgSxdUGjOjRcSTa QLhZhVQE9BdSRA8gihhTwiCGm9/4xjcOP/zwgXeK4T3YOPdABqM4CP6VV17BO8vsl4tFdKx2U0kn XTPA4Xg0A2SPIiiiHtCYZS4EJul216xZI0NPvDjlhz/84VFHHdV5pxgkVl4fBgXFvzhFCMcJ4cva tWvxlhWcn4fpXOpok22UOlpgWDmdW2BQKnBpkiHaJFwmqakUunXrVjxVcs4555x11ll//ud/bqp/ /PHHY0EU/8WXT3/601DcLVu23HfffTYfyOr69esnIVZmoS0tQOjbZEu1ztyuHCDr77X1RjPXlsVN QmA+12fmmuIZkosuumh4HbQTcV6bo5dA5iCO+hOYQBnxxmodCM0pu5IwbHI61wksE8+UgDzDYz7R KWD2VeZm8YwKFBQjS9ci9HfDrpaZvkACnb3xCz00Dz4V6H9LLlFEW4pm7rrM5CrN8G4ZbA764he/ iD1BOFcPCnr22WfnjiXLq42AfcrusiuRt1YZoso10QyQmy1ibpNF+hmezCGfWyBc8RYbONeKLEvf F1HIJ1tFCF59m+FINIQz8/7yTLI5gNBfVH40MJGL1VC/vMw1QGAO8yX943ml1nOo++SNnyI6eQgq dmBuG+7TTY7hrD5M5J5++unU0bjXQ+pbn7jexrJmn48fyybtLJ0G0PcL82yObDqjBGYya5Su/UM4 V69eLZx37dqFx1pGmXcSzCQEHliQxb7V03d3rmWVmZ4Nwzsu+uudI1FvyMz4awJzmDVK1//iSHc5 cggPhm7cuNG1Yc0BvgeTTieo2c7qWkoV6dk8UoeJG4tSE56Fff1dW9U4klbT+xVjHG30x+VmANpv bwv34FTdLAecT9piW4Um9dKjo4i23RLy1W4mXXmB1SzQpXzNbklJeiZGU9PNNExLQ49iWj9LK10v opzOLS129Kd0AkXNjxXlTCGRc2KiedqykHp5uOGEwsM+s4AARZTNIAKB+Vyr5WxIBnP9zXKEGFdi wo9J21JaSehqdZMiWmvkSvO71dmwPudpayraaaRiWmdKa4R+CmpqYaS0tHp5+8Pm4Y1On5EiqmfF lCTwawIZBt9GL+0v8IBPAS5siIEKatvMENw811IzFcmDy68UiqgfN+aaNYGkN/j9sWb/PJpZ019U +YgKWs6MfZQoJ22rUTys3QhFtPYITu//bO92I1acY82QdhxRQcWNxnQ0hC3zjhKgiI4iYoJxAjO8 2/Wu8ugkrbfl8Ti1myI6tOgG22U/95pRROfeAlh/PwKuw1BO0vpxHs3lGohRg3aCpMadPPFIXLXz HvWdKgtFdCrytZZrtoZKBeZ8oSoHK53NtMpctbaPKfxOhLSBSd1EZKYIcrllUkTLjU2BnhnJ7Iyr CnS1EJf4LEohgfBzo14dnfPdrV+svXNRRL3RzS6jrQf2ftHZgVCPv6NveJkh6uEqZ5CKegdz9Xpe VzuniNYVr9ze9neN5vag1PJGeygqaJ7QjQYiihsZ1DqKnzSSnwBFND/zakrsDz2rcT2lo/r+NE// nrKuRdvWByKwGvVO6gZWnNk1BCiiGkpzTMOB1EDUR9UxW/8+x6b5UZ0zt0/q6Gxb2mjFKaKjiOab YFQqZoiG6lhC0DMrqFSZOlpC6Av0gSJaYFAmdqnzEMvE3pRXvObeQpOmvJrV4dEkCkodraNxTOEl RXQK6gWXOdUjGZ0dTGUSch2GuqYvs9bleGU/cTuVVxyPTkW+2HL30d8yT3gDWCy+9hxDlPVNIrz6 tsx4d095HPZo/x5ZwpHWaME0g2WhHE2QudblRzbzhZyZf4bi9CF26DH1RjPUkEWkIJAnxJ3xWaAE 5uksvMnkcS9FY8hpUygND9wD20n06ng3ieieLDTIhhfIWR9fimgg6qayJ73w+oPOKOz0bd2vuJAx UGrf/GpUYK6kDS9dfUt2u2Tf0kUkomX9xcs10YjY6zaVbgHPXsqSo44ikoprTRwThztu+/mcwj0/ T5grBYF0V42rt3ajLccr11rUmJ4j0RqjlsTnRLeu+hs671pF8bzT74SLX4aKexMrLWO9rEImKuJG IcpVENelqq3p2yRHolUHOprzKW5d7ZFcNEeXGAr031ww5kzgKA6HK3EUN8o34r2nbPKqmZmVwBYY WJFpSw90vvbsHInWHsEI/uvvufSFpbA5UHrIgCCFq8s6NcrqcBDr5ZOiFTldbvWi01czZ0p9QCmi OeNSYln6tqL3PoVNTem2dCn7lIiuLpwQtu1HnzHWMKkoTcRYTFLrCf3nXG70iOujSRGNDr90g/1B klJvNBULGRFq7CvTKC8AZbLhQj2UGwaTRkFJqcBktYvBVO2/dm5lNkV4pekbKaIFhi+VS6mv8Cia FKvyw85ERBGl/yoKXawQeNhpg0PmWmQuziOsNWbRU6WI1hhfN5/9hkpuZWR/q4bGvWVKqb88Rksp 05TSbTuZ5o571GyUBFFuSqJ4EmIkYsPQTISUE74QaEXl1UeQIlpU4GI6k0c7jcfF9n22lEYZgHZm YiP2X1HcG2hDy5pE6nKdmnWxDcmpFmbGPmLz6Dug7+hdnWd6PVuKaJutRd8CAuufWaq9vQ3XiWw1 DXd1WW+L3wf69GxtZnRolVR4vJuQR8ZESLM1RY8qN5NFHzuKaDNB/3VF9OH3rnyNl7EflqlqGnG8 q6+4PqV3yxnN2MxIVGoa8ZZoqqY4GrImE+ivBYpoaw1AH3vXmkfs1l2LjpXeCU7E7i/Q/w5529ro oM2pytLpj9oMrM5Adldv03kS13JgvcppinGxlGxNHzKHC0ZvtGQ0bfuWLkbpLGeOyGhFKrrfXyiu RgL9et7JRXRCCU/aFEcb3vC9RatYkjIPMa6PF0U0hHNxeRP1gPr2VByRRQ4NVKf2mobPFkxIYMKi 87Rb7wp6Z8xTryZL0TPn2bntNICBSb+QSuobU0gpOfMuvKlHNRuoqTn71/ttOdOOeKYtPXUj9D4i 2Dtj6hrRPghQRJtqBun6oEQKPSF9u0ZGPtMBnLCmVRTdXgNbiN1bDk3GmYCqotGKkxTRioI15Gq6 S8t7TFMyWbtLamAAGh11uuY04OpM7mA8qtmZJpkkOtHbWDMGKaLNhFJ1zGM7tQ2uienLmrxLCMHj 0cuHFGfyzkoblJW15VPi4j2WjRIjGukToIi20CqUF6R3VVPb93YsJCMHoCH0ouedSrmjV0RjUDM3 25dPY5k6qoGcLQ1352ZDnaqgDGKAIhrr4zJASxXvLHYn4dNeMxuN1fDt6fBFN0mMRmvUTAI9XofO UW+0GY5VVCR119NY3E231dhtQfS2mrpd9R1urKVFjwiJZUDaWVzQ9BKczs0Zl/hl5Zlo1bSk+HVL YJG7cJ2g5mldnKV0CoqdmPO63ugiZqSIRoQ5jalmFC41Pg50nAhP0q4mKdQJS2mJSWzyiFBEJw+B vwMZBgoZivCvv3tO9jjuzCbI0Virm4Agi8xIgCKaEXaCojKoQoYiEoDpmmS/7Ac5P7c22psfbeaq kQBFtMaoZfI5fweatGLsnV3x5idmnutwdXXm6Ru7VOuKJkW0rnj92tvUl01LK4ipWdXahgrzm9u+ /AKieerUzzJzaQhQRDWUikuTWuFS288JtKW65ORmysp5C5J/7DsJ0uiFmlO3cgYrei0qNUgRrTRw yQ/5a6k7a6kumdtrNnTs/cMjyydewhl6WKCIekCbOAu7G30AyErPaiBlaoycLYgSJhihjsYiqbdD EdWzKihl0vFB6h4zM8ekrDLXZZLi8gDMU8okANMVKvuwzG4sbstKh3rAMkV0Euz+hSZVOHMRttGj JWXlH8I6cxJmIXHrCGdnNVT+28b1WwjwUTd4du4oooISJJ31Smp8EoioEXuTWORtEY1OlZFaFqaF 9y7R+cdqJC3Z0feHDr2M3mhLKIuqS6K+xlyoLV2cbK6Jmm6nW4/SZhI17EQEcpolmZy07bL0HQin c6eKkXO5KebT7PnbKL2hc61SZmivRilpaW2bCUP78cQUjVPrENORwKQEKKKT4ncsPKIqtC2f7NMd W5ZncnsFzt7h4mSOwXLCxcSlEaCIlhaRHP6YmYqIqpzDb5cyGq6aC4ZMaftq6lQwg7UQF28vnFrR VIkpolORdys31uXU2P5bdj1uzSh9anuzqL2PdFkDjtWw09csdwn6NbncnrG8jxPgxqI6WkSU/QUz uSyjsKqjWdTjZV8sIbczaZAeUSIZD2hxs+hDwJFoXPKFWmtjAGpqUSjl5tx66KGHLr744jfffDO8 ZvZ2JPtUHU7k9tnqu+/wuNBCOAGORMMZJrcQclE18/iKPZSxe+Fl9Nk7B7bL22677cUXX7zyyiv3 22+/QFPLsnPOgAqaqGmFm9X3uhyJhtNObsHjCBJ7q6RH9uRVciygsxOqs7W4M8rRSKxj+ZUlxwjy 6aef1jv9wQcfXH/99XZ6WDjkkEPWrVt37rnnRhmJ6p1hSt7/1dUGKKJ1xKuzR2P0v6iVvWGyjkou 8rI/Ed15TnFh1Waroxg+PvbYY2Dy2muv6YOOsebu3bslPdQUCnrcccddc80177zzztVXX33QQQfp TTFlCAFuswqhN1VeiuhU5N3K7Q+2Rn9xK6Dg1H4j6Xnq6Je//OV777334IMPdo3n4YcfLlkuvfTS 0047DZp69NFHf/WrX12/fr2rKaYPIcBhaAi9SfJSRCfBzkJVBAJvzGeooxhTbt682WkY+vzzz2Po ecABB5iQYDMRdBR2tm3bJuNafkiABJYRoIiybRRNIPDG3D6aruh6xnPusMMOW7ly5Z49e5Qm165d i8SrVq166aWXJMuGDRuwDgodvfnmm/fu3eu0vKoslMn6BAJvGYl0KgIU0anIs9wRArH6FL/Z4OrC g81Bsn58xBFHwHnMx+JLZ+0cW23NL+b7ihUr3n77bUznYhuR/PWiiy5avXq1+Z5IRGPFt7pIDTgc eMvYEoqK6sJHXCoK1rxcjfv8g37D+rwoT1fbuPGdrh7RSiaQaChjGNL3GByJxuBNG8UTmOH6qCYm Mn7Fv5rETJOOAMfl6dimtsyRaGrCtO9JIMWNeQqbntWbfTbGwm4CpFHaBcGRaGkRoT9uBNLdmKez 7FZDpiaBXxFgm6y6LXA6t+rwtex8ik0W85nUxaMp5Z80RPHABawf8bR8tddcN4pozdGj7+4E5qCj OHVo06ZNp59+esk6muImyb05TJyDCjpxAGIUzzXRGBRpIzaB1EtEqe3H5uFgD8KJB1Qkw65du046 6SSHzHmTNhwFJUgSUILKn0x/f8ORaP7osMQRAnlm+eQ5yPaCgaNuH3zwQdRr69atGzduLLyCTYZA yXzOdVciqiIZR6JVhGleTma7PdffbFYXAIxHqzg4PlusS4tgw22vNNR+/ugDRBH1I8xcCQnk7Fj1 l0rCCs/YtBmNzW2JNGcjn3H78q+6vmfgdK4/ZeZsgMC0h+vKlPKcp/XMoYwzRDHnuDfQdZgqcCTa UjRbqMtUd+iZy7VHYHZnOrcBWafJzmpgqh/rtHBh11YHfXQ4Eq0ttvS3FQJmEGa/Pn3moxN7YNpK nJfWYw5PWzUfRFSQIjqHKFdTx2klZKD0PI7NfBhqmul81IURr6ZvWu4oRbSBIDZVham6lf7iqFml EwWNuGg3LMl5BLvwRjMfHZWmVXg46N4AAYoomwcJ/JJAZ5MLfjUTrZ0Z1/DdQMvuFaa6hyiwEcxE RxnxAtuek0vcWOSEi4nTEsi8uyekMvp9B51SRjOOJghxO3Pe8D1TLdFY2BI6k9iZA8TilhHQNzyO RNmKSMCHQMg4aXjwEWLZpybJ8phuyLtGRoPbmPC0FwhsOByMJmuDOQxzJJqDMstQEqhoJCo10t+u uqYPH8MpmadItvBJlYU1GlVHI8CVKk2ngstq4dqQUkSNNm0C+ohQRNlySiGgb7WleGzpKL4u7B/7 IuEqBnVhWSif4dOYdUEw9XVyu7o7yKIuw+jO6GNHEY0OnwY9CVTdiQyMqFxVs49Pfz17onfMNjx8 DK/vQndKgzDKzNXhqtv/KI3qEujDRxGtLrjNOsxOZCC05cDRdy7RW2oKCAtvCMLvAzwoeWSJTpgG PWYRKKJsNkUQYA8yHIYS+GimapM2pnAIGsmMVYqHEocXnZT/rIzrY0ERnVXDKLeyKQYZ5dbWy7PU iIaXb/V9ilfltJlc3Riu1LJSXUux7YTkhZ3UUdaCnn06fRwporNvLGUAYN8xGgf9VT1qqt/pyy/2 4MlPfpyK9ku8cDQ5YMpjRChi1gGi8dYvV0QN1jjJNBoC+lBSRDU8mSYtAX17TetH8daj32qQ/EDM PaavowQoipHi23LpDuovDR62UHosZ+Kf33BhJnCWDRz11UePIJ9+FpJfhrF/DOQwcNchska/9SFm yqkIUESnIs9yScCZQP+UfI0J+57aqOkyTdUYnFUaW0pHKx7ljiSKkVFXmSAWAYpoLJK0QwI5CDj1 6XDIVtD+efrsr5UxGz25MOIwVFyKblBZUyZzJUARdSXG9CQwPYHRPt12kUoZJWADzPXrZ0pPGDIl qBKSUURLiAJ9IAFnAvbU7rJRC0czzlgHMyzU0egKGtdnWktNgCKamjDtk0AqAmZ6Vmb/uG8oFWjL bkdHqaAZmBdeBEW08ADRPRIYJ+C6j3TcIlMsJ9DZ3sWp15k3ForozBvA9NXnlGOsGLjuOYpV7gzt iHAa4DMkwCobAhRRNobpCfBePmIM/B6DiejATEyx0c4k0KPVpIiOImICEqiMgBkhsaOvLHJ0t0IC FNEKg0aXSUBHgFPlOk5MRQL+BCii/uyYM5wAe/lwhrRAAiQwIQGK6ITwWfQvCHDKMV07INt0bGmZ BIQARZQtgQRIgARIgAQ8CVBEPcExGwmUT4Cz5eXHaMBDhq+K8FFEqwhTm06yj0gaV87lJsWb2rjT 8cipnaH9AQIUUTaPKQmwo5+SPssumwCvjrLj80vvKKJVhIlOkoAngRqH+9dff/2WLVvwr2ed28pW YwTbisBIbfbR3+zwqOVZtYwMlUWL0je/DP40WUSZkF966aXHH3/87LPPbpJ53EqVGcG4dSzQml7v OBItMHx0iQTaJ/Dyyy8vq+Sbb76JLuyhhx5qn4KuhhyM6jhNk4oiOg13lsp+YT5t4Morr+wo4tq1 a99+++1lBHbv3v3gR5/5IBqoKXcYFd4MHObT9MPbwutM9yYnwLaULQTloH7sscdQ65NOOgmCethh h0EjL7300oUckHLTpk34E2f7DR9O6ma7ZKQg/YXDkWjm0LA4h9ZJWOEEptUh6CXmZqUWK1eu3Lt3 L75AQV/46LOsdhBauH3dddeFV78lC5y8KTOaFNEy49KsV/r7uxIQYI/o008/XYInlfrw7rvvHnTQ QeL8EUcc8Z3vfAcNAF/w3w0bNuC7fDDfa76bL5dddlmltU7hNid1U1CNYpPTuVEw0oiKQCIFFZ07 5phjVE6oE33wwQcrVqw488wzL7nkEoyN1PmKS5gIu6ae9957r9mCC5533333hRdeqMnINAsJTBjK uUVEj5oj0bm1jcnqq2+UTi7iYYnt27e/9tprTrk0iffbbz/c/u/YsaNqBUVNJ5zRxeomAgQf8O+2 bdtWr16NZsDxvab5LUwzYSi9fW4+I0W0+RAXVMHoXQAGN1DQ8847b8+ePVLP559/3mwERceNLlv2 s5i/YmzkSuS2225DFpTFx/9d0W3evHndunWIAv7FUugZZ5wh9yXRpw1cHas6PRdHiwofRbSocNAZ NwJPPvnkLbfccs011+ChCMmJZyeMoD777LPYAiqbWeSzZs0a9OCaMqDEMoQSBcUHA9OBpzI0NqdN M0nPe9ppp0E15bNsL+60WKor3XtxtLPqXF3Fi3WYIlpsaOjYOAHZxomzb0499VTpI7CKaaTu4IMP xkjItoJNLn//7//9/h6W/sYWM4S68847L7roIsly7bXXjvtUZArT8+aXUtyLcHNW3EYxrKP95i2/ wAdzQ4PvJllc32ZojRuLZhj0aaqcaE10uDLovn/84x+bvS143AKKqByMToMpcalGRKNPrS90HAoK +E888cStt97KLUVxY9u5oOzbI2VwJ7kk40JIZ00PhyPRdFGg5Y8RUF7YIdQuvvhibFrBqqcsfGJK 9thjjz3xxBNlShaLo1BQJPArAsYbGFHJWMQMRPxQ6HM9/PDDUFCk37lzpz4XU2oI2HHsDzSXWbDH qTI21ZTFNAMEOBJl88hHABdwnosWA6Cvfe1r9913H9ZEsSwnO3ixenrPPffw0HMT7wyjUhn6v/rq q5gwRyDyNTWW1COQIdwtUdePRB06Nb3RllCyLhEJpG5CGGseeeSR5un+iJ43bCp1ULCrGfSwLath hlVULdstbBU0Rp3UXxeczh2FyQTRCHhvLNR4gOdPcODq6aefbs6Z0+RimtRzA5BPKmghzSz/trJC Kp7UDY5Ek+Kl8QUE9Ld4enwQTjzIL+l37dpV+/EI+oqHp0wRjnCvaCEFAQ5G9VT11wVHonqqTBmH QIrxKKZw5c1ZW7du3bhxYxxHZ2BF31PMAAarSAI+BDgS9aHGPOEEUnTfGI9yQVQfmhQh0JfOlPkJ cCSqZ66/OiiieqpMGZkAtwtGBupiTt9HuFhl2qIJMOj68OhZcTpXT5UpIxMwzyxGtktzYwT0HcSY Jf69MgKp95FVhiOGuxTRGBRpI4wANw2G8VPllqfskZQKquLVXCJeZYlCShFNBJZmtQRS7DPSlj2/ dFTQ+cX8FzVm3NPFnSKaji0tawlwiklLKiydff54mCXmrokAFTRptCiiSfHSuAMBTjc5wGJSEnAh wPtUF1puaSmibryYOhEBXuSJwNpmeZuSAXJpRTDoqSNCEU1NmPYdCPCCd4DlmJS3KY7AWkjOidwM UaSIZoDMIlQE2MurMIUl4m1KGL+aclNB80SLIpqHM0vREmAvryXlnq6Z2xR5XIdNZbQJNBPx0ZpO mIAiOiF8Ft0lwMddMrSJ2rXHHmDVXpd04SaZdGw7limi2VCzIBUB6qgKk2+i2ocmtoLWXhffGI7n 40TuOKN4KSii8VjSUiQC1NFIIJeaqXSYQm3QNwzeYehZBaakiAYCZPYkBKijSbB+ZLTS7pUKqmwS ld4hKWtXYDKKaIFBoUu/7uvZIyRqDRVtzDGuVir/iSK40CxvNXLSlrIoovmZs0QtAXaaWlKO6cz7 c8q/RzGqwMagDDJBKUHFSkYRjUWSdlIRSN3Rz/Z5iVrmzIdVIXXzSNWsE9gligRQx01SRMcZMcWE BFLfVneel5hbN1SLji5rgbX7H/3KSn29RHe4AYMU0QaCyCoEEZB+p6IZzqDa9jKXrEOae5qS/Y8b qWFrGlY5/ZlPWRTR+cSaNe0S6Pc78+yRTa0L7Ig1Q6s8/pc87c/9RBP2bhTRCeGz6OkJ9Pvo2eqo LUUV7d2VNmRPJKS4FSh52p8KOm0/QhGdlj9LVxFI1y0uLH6eOmqkqJCZbY+gJ/K8c0xSgc1DM15X XWlM5E6AIurOjDnyEkjXZw10PZ1hWd4aF1FaOuz66vlpQ9zZ3YXjvBLg6DEyZVICFNGkeGk8DoHo fZZmlCPDmrg9chwcuaxEx57L8cizuwu1vJCGoWnJ2bDPs6B99Pd6nHmfZxMpp9ZogfrmOuy2qynX 9OVAC/dkqrrHKtfIjEfj0XR6GhnzKFoZuFiUlMXNJ5km9ELDoVfSG50PaNY0G4GIzc/VlGv6bEzy FDRJ9aMX6mHQI8vCiISo+Oi9IBKkU+g8DazMUvTR53RumRGkVwsIROwsXE25pm8pflPVPW65rovc +j50NNZmUWA0pUeCuJQ8HGAWiijbwIwIeDy5oZmsmxHBmqvaX+SW9tBpFea/1Keao53Pd4poPtYs KZBAFD3zGBawMw0MXGnZjZoulFWZIGXQS4tasf5QRIsNDR37GIHwTs1Dgz2ytBq2nChyliXx6shq 9CCmqFEKm9ErPgeDFNE5RLmdOnrMx0rlvZe4wsW7Afr5IeQvMXWYUtQohc3UHNqzTxFtL6bN1shM srneg3sraLMoWTESIIFIBCiikUDSTC4Crg+5eyuoq1TnAjBBOTlR5CxrApRRiySrqDg9jfE5UU9w zDY5AbsH6cxrdToXj1kvb+mdHEsKB0DDg6GTJwPRdLJTZuJEANlK04Vbz9bh2tAbTVcxWiaBPoGF 9+OBnX6iXq/S8PnRcB0nBYasZLYpOk+Dt2FuE8ZUHzKK6IRhYtGFEtBfP4VWIKpbfjT8ckV1vCxj fjciC+tgyyc5JwqzHizXRBOFgGbrJsC7e4mfviux4+2Xq+4Wo/DedWjeQYrs8sHvZpMdG6oCfNok FNG0fGm9UgIh/V2lVV42T+7XTfvlagZdvyJmQ5yyjkYyO8K58CAINlcl1RTJOJ2bgiptVk8g4uRb jSxC1ts4DB2IeB/OgP7pb0Rm3lxTXGL6ZkwRTcGfNqsnoL+Eqq9qrwIhdQ/J2x7JhTXqq6ZeLJch IvbojUePlNO50eHTYAsEXCffWqjzR3UInxgMl4RmYC6siOFjn9wbWOXZNtdAblGyU0SjYKSRBgnM sGOy77491NQjS4PtRlGlheuainxDSXjvEgjQOztF1BsdM7ZPYFY6aiuoR8X101/tt5vpasj7mPzs KaL5mbPEmgh4yElN1fto/tbe/2mcd6o4FdQO+ksvvQQgW7ZsydwSOBjNDFyK48aiSbCz0MoItLr7 cVT8lAkQTvbgJbTpVhtqfrajLd+4xJFo/uiwxCoJNDZRtnD02Q9Mfzxqj1xNRzNzBf3ggw+uv/56 m95jjz32/PPP+zX02267zS/jLwdGH53GwE82AhTRbKhZUMUEmhGJzuStpl62jvZ3HmksVBz4Mdff fPPNiy++GKl2795tp/3pT3/6s5/9DL9AX5EA/45Z+uXfkXLnzp3KxMtueryzM6MHAYqoBzRmIYH6 CNhDT9fdobaOyveIj2fUh9Ly+KCDDtq8efOjjz56+OGH2xXZf//933vvPfyy3377SQJlNZH+1Vdf VSZmshIIUERLiAJ9qINAjTO6HkPPhcGgai5ro6eddtqePXsOOOAASSBTuwcffPArr7wiv0gCTROX idyjjz5aP3JdaLbGhqrhU2YaimiZcaFXxRGocd7SXrOs0f/iGsESh1Z99MGmXBl6vv3222vWrHnn nXdMcvx1WV3uvfdeyWiWQg888MAPP/zQu+4MtDc6v4wUUT9uzEUCpRPQby8svSal+gf9k4E+VjEx nbtu3Tr577XXXrtixQpIqUnwp3/6p2ZKQL6ceOKJ8uXGG2+UjHfeeaeshuK/4TXmYDScodICH3FR gmIyEvjFI5VV3OabDrQKb5tsWNhwhK1GmMj1qN1DDz3kl9Euq5a26sEnTxb9PahDp6A3mqeSLIUE MhOoomPidZq5VXSKw17cCy644JhjjpnWjSra6rSIhkvXX0cU0ZLjSN/KIlB+x6S/8ssiS29iEyi/ rcaucWR7+kuJa6KR0dNc2wRKXmrSX/Ztx4i1EwIlt9WWYkQRbSmarEtaAiUvMVJB08Z+ufWnn37a +3CidD6X3FbT1XoSyxTRSbCzUBKISYAKGpOmiy1sAjr22GOPOOIInPPnko9p2yFAEW0nlqzJPAlQ QSeM+x133CGl7927d0I3lhXNGd0MQeHGogyQWUQ7BErbr0EFnbZtYSL3/PPPhw94JHTt2rXTOtMv vbTmWhqfAX/0VxZHohWFla6SwMcI6K/zMsE5Hc6OY31OOOGEwPPwonNYv379Ix99ClRQqSwHo9GD 3jHIkWhqwrTfFIGibu2LcsYvzFhTRMbwswX8Sp9DrgYaySRh0t+hciQ6SYBYaMUECrm1L8SNwEDq D2dHQVBc7N/BaQao+5VXXtkflSIB9sqKS/KGMvxS4NbZQGjMXhQBimhR4aAzpRMo6smBopzxjtzA 4ewdm8cddxz279x8881vvPEG3ppy7rnnytHt5oN3p5iXjm3YsAFn7x122GEvvPCCt29tZGzjfqvY WFBEiw0NHSOBpQQa6BbN4ez/9t/+W1Rn2Wfr1q0y7sS/q1evvuiii+TLZZdddt999+GsdiilwYTD 9jA8FVNIiWR4+GTmzaiNO62Sg8g10ZKjQ99KJFDCIlMJPhQYG8zlYiR66aWXFujbhC7pl/cmdLK0 ovXQOBItLXb0hwRIYIQA1jvN2ie+yEEHcu7BySefjC9btmzBVl78SVZGZ/7hYDRpA+BINCleGm+Q QAmjwBJ8KCe0ENHLL78c/mzfvv2kk04qx7FyPGGDcY2FfiRKEXVly/RzJ1BCf1SCD3NvB1XVXy8J VVUrobN6YpzOTRgGmm6VQAP7eooKDTYHYTRZ2kEKRSEKdIYzuoEAB7JTRNOxpeU2CbA/ihtXaCd2 0m7atGnbtm1xLdNahwBv/lI0CU7npqBKm40TmHw2dXIHIgYYY1AoqBjEA6AHHXRQROM0ZRNoqdmk jiync1MTpv25E+BNfawWgK1A1113HazdeuutVNBYVJfZYbuNTpgj0ehIaXAWBKa9qZ+29BQBxrIo FTQF2P6MLtcjNJz1I1GKqIYn05BAl4D+GkvBrj0RTUGJNvsEpm23FUVED4obiyoKK10tiIDczk84 OTZh0QWFga44EuAw1BHYeHKK6DgjpiCBhQQm7I8mLJqNoQECvAOLGESKaESYNEUCJEACpRPgHVjc CFFE4/KkNRIgARKogAAHo7GCRBGNRZJ2Zkpgws5owqJnGuxWqj35in4rIH9RD4poS9FkXXITmHBm bMKic1NmeQkIsP3EgkoRjUWSduZLgCPC+ca+8pqz6YYHkCIazpAWZk2AM2OzDn/NlWfTjRI9imgU jDQyawLsjGYd/porz0nd8OhRRMMZ0gIJfCJ/Z8SJODa7WATYlkJIUkRD6DEvCXyMQObOKL9yM97t EWArCowpRTQQILOTwC8J5JzUzazWjHHzBNiivENMEfVGx4wk0CWQ56ZefzQ2I0QCGgJ52q3GkxrT UERrjBp9LppAhpt69npFt4A6ncvQbusEM+I1RbTJsLJSkxFILW/s6SYLbdMF51yMaAwkRbSxgLI6 RRBIKnWpdboIgnQiOwG2Kz/kFFE/bsxFAksJ8KaejaNeAknv/+rFMuA5RbTJsLJSExMwOoouKWKv FNHUxIBYfJEEOBj1CAtF1AMas5DAOAH0R/JB0ihSyk2549CZggSyE6CIZkfOAmdGwJbSwKpzoBAI kNlJIDoBimh0pDRIAgsIRBySki8JJCXAVQMnvBRRJ1xMTAL+BCIOSf2dYE4SGCTA2Q7XBkIRdSXG 9CQQRIB7d4PwMTMJFEaAIlpYQOjODAh4TO1yhm0G7aKgKrK96YNBEdWzYkoSiEbAY+Mu59mi0ach zujGawMU0XgsaYkEHAl4SKljCUxOAiSQlgBFNC1fWieBUQLccDSKiAnyE+CMrpI5RVQJislIIC0B bjhKy5fWXQiwNeppUUT1rJiSBNIS4KpnWr607kKArVFJiyKqBMVkJJCJAKfRMoFmMSQQgwBFNAZF 2iCBSAQWTqNRViPRpRkSiE+AIhqfKS2SQAiBhTrKubUQpMzrTYA3cKPoKKKjiJiABHIT4LaO3MRZ 3iICvHXTtAuKqIYS05BAbgIepxrldpHlkQAJfOITFFG2AhIolIAZB3BAUGiE5uEWZ3SH40wRncd1 wFrWSYDyWWfc2vGaLXA0lhTRUURMQAIkQAIkQAKLCVBE2TJIoHQCnE8rPUKt+8cWOBBhimjrzZ/1 q5wA59NiBRBK0PnEsty2HbbA4fjuowckNyP69G03LNaOBLIRwKXH6y6EthlI2RgX/miXsnD4Nc9A zLAF6vWOI9GQa5N5SYAEiiYgQ0+5++/o3/DLc+xcktJ+6IjTm0VHPa9zFNG8vFkaCXgRYK/tgW2Z fNqmFj6Pu2wU0ldTD6+YpTECFNHGAsrqNEiABxi5BtUegI7mXTgkHZ627Y9rR0thglYJUERbjSzr 1RSBeS7FeYRwYP522JrfEVGmOA9XmaUNAg4bFvQLrW2gYS1IoCgCvACHwzG6UShRNDsz7U3e7nBj 0UDj4Ug00ZVFsyQQmUCTvXMURt6jzyilm4VSv7FsFB9oZEICFNEJ4bNoEiABHwL9xz0LWaQc3vHr U1XmKZ4ARbT4ENFBEiCBXxHoDDrt7bLlQAqcMzC3COXUiJ5wOpdtgAQaITDPZ11sXSlk0Dnanlwj 1akj7LtaGHWJCVIQ4MaiFFRpkwRSEZjhFg+Rk8DhXap4LLer3OhkK2WnjqO1HlZZ29rClEqk89zR pq+1Q9PUG83fXlkiCcyEwGjH2iSHejufvnpBupQbejuxdhLCheXabUOPlE1u+JqiiDbZ57BSzRKY Z49m5jaVg6diw68cnor/o0IYWE1lW1ImC3SmtOz6mwxuLCotdvSHBEhgAYHa5VOq5LQTyn54JtFK MJddwy82img4Q1ogARLIRICdfkTQmvsSAh8FThEdRcQEJEACRRDgGcIpwjAqkxqtTeFYLTYporVE in6SAAn88n3Go/0+SSkJLLsvsZ+3UZqabTKK6GxDz4qTQJUEOB6NGzabp62dPH1JyZkiqgTFZCRA AqUQ4Cm1cSNh62hn6xNvWUZRU0RHETEBCZRFgJOZiAfHSXEb5cC2Ya6JDqOmiMZtirRGAmkJsEez +XJImra10bqCAEVUAYlJSKAwArJ2VZhT07iT6AHKaSrDUiskQBGtMGh0ed4E7JlMSqlpC0Qx78ti stpTRCdDz4JJIIRAR0rNvkpqSQhV5iUBVwI8O9eVGNOTQNEElIebF10Hd+fmeb6rOyfPHDPEy7Nz PdsKs5FA7QTsA1drrwv9J4HyCXA6t/wY0UMS8CEwn3nd+dTUpx0wT2ICnM5NDJjmSWAKAvrJqCm8 8ylzWCn55I8PU3UeTucOoKKIqtsRE5JAJQTaU1CAn2E/Xk5zmyF8/UXE6dxyGio9IYFoBJocmXHa Nlr7oKF4BCii8VjSEgkUQKBVpWnytqCA9kIXQglQREMJMj8JlEagSb1p9eagtMZDf1wJUERdiTE9 CZRLoFWl0S9QlRsbetYoAYpoo4FlteZKoL1hKBW0hLbc6v1ZOFuKaDhDWiCBIgg03M21d2dQRItR O0H+A6gooup2xIQkUDyB9jq7hu8Mim9NdFBFgCKqwsREJEACUxFo785gKpIsNwUBimgKqrRJArkJ cMSWmzjLI4GPCFBE2RBIoBECrY7YeH/QSANttBoU0UYDy2qRQBME5M6AOtpEMNusBEW0zbiyVrMi 0LbGtDrCrq6Jtt3MvMNBEfVGx4wkUBABKk1BwWjRFTawZVGliLbY3lknEmiOAIdBzYW0kQpRRBsJ JKsxWwJzUBeujM62eZdfcYpo+TGihyQwQmAOU23UUV4GZRKgiJYZF3pFAioCcxiGGhDUUVWbYKK8 BCiieXmzNBKIR2CGJ7PPYcwdr4HQUg4CFNEclFkGCUQnMEMFNQxnNf6O3nJoMC4BimhcnrRGAjkI zFlBzaQupTRHU/t4GWTeZ04Rzd8OWSIJRCAw54lN1J3roxHakKOJOTe5AVQUUcd2xOQkMDUBjgam jsCsy2fz64SfIjrr64GVr5TAzMcE6MfnPKE9YaOdecNbSJ4iOmGDZNEk4Exg5uMAWz7ZoTu3HmZI QIAimgAqTZJASgKzFQ8z+pwtgZTNysH2zO/kOJ3r0FaYlARIoBACnL8tJBC8g6GIFtIU6QYJOBOY 7QiACurcVpghFwFO5+YizXJIIAaBGY4DqKAxGk5kG7O9n+tzpIhGbls0RwIkEJEAFTQizFimZngn N4COIhqrXdEOCaQlMNt7f3bZaRsWrYcRoIiG8WNuEshIgHKSETaLIgEVAYqoChMTkcC0BGY7DJ0W O0sfIMA2KXAoorxMSKAOAhyG1hGneXjJ1mjiTBGdR5NnLUmABEiABBIQoIgmgEqTJBCVAOfNouKk sWgE2DI5nRutMdEQCSQlwNmzpHhp3IMA2yTXRD2aDbOQQG4CvNnPTZzlkYALAU7nutBiWhKYgsBs b/l5AzFFc2OZbgQoom68mJoEchKYs4rwrKKcLc27rDk3UU7nejcbZiSBfATmOQylguZrYSwpjABH omH8mJsESCAqAfu121EN01gSAvO8ybNR7qNHwHvDJG2QRklgCYH2rjjl1J++U2LbmZYAAtpqsPRX nwMCvdFp48rSSaANAo31UOxA2miWHxuEUUR57F97zZo1IoECCVBBCwxKoEvKeYXAUsrPzjXR8mNE D+dIoKUeigraagtudS7XKV4UUSdcTEwC+Qi00UNRQfO1mIwltXSTF4iNIhoIkNlJgAQWE+A+21Zb Bm+M7MhSRFtt56xXxQQauM03/Wwb4+mKG1Ma1xlWw5W7c9M0MVolgTACHR0tsM/qK71xkiOVsOAX nXsmwdVXkyJadHulcyQAArZcTa6my5wpX/XZlsIJ6KUlvKxpLehrShGdNlIsnQQcCBihmkRKpy3d AROTJiPQ2LPLA5z0Iso10WTNjYZJIDYBaKfIp9mzE7uExfbsLUKT6HeearKUYQINLNWnCDFFNAVV 2iSBhAQySym3CCWMZT2m9SOzeuoUx1OKaByOtEICmQnkkVJ2nZnDWmZxbAYDcaGIltlo6RUJqAik k1I+5akKwAwSUUGHg0wRncFFwCq2TiC6lHIKt/Umo6ofb6Q0mCiiGkpMQwIVEOhIqfc2EI48Kgh2 ehd5I6VkTBFVgmIyEqiDgEhp4CZebsGtI9hpvOQA1IkrRdQJFxOTQDUEbCnVO+09ftUXwZRlEhDt 5ADUNToUUVdiTE8CNRHwGJJyGFpTgIN97WsnG4ATVIqoEy4mJoH6COhndzkMrS+6AR53xp3UTj+W FFE/bsxFApURGJ3d5X6iyiIa4C6nbQPgdbNSRCPCpCkSKJ3A8OwuxyKlxy/YP8pnMEKKaHSENEgC VRFYOCTlRG5VMXR2lpuGnJGpM3AkqkbFhCTQEAEzJDV14jC0ofD+sircNJQhphTRDJBZBAmUSMBj 426J1aBPSwjYD6vwDildM6GIpmNLyyRQOgEztQtHOaNberRc/OM2MRdaQWkpokH4mJkEGiAwunG3 gTrOqgpU0JzhpojmpM2ySKBcApzdLTc2Lp5RQV1oRUhLEY0AkSZIoA0CHJLWHkcqaP4IUkTzM2eJ JFA0gf7G3aLdpXO/IkAFnaQtUEQnwc5CSaBoAtTRosOzyDkq6FQho4hORZ7lkkDRBKijRYfn485R QScMFkV0QvgsmgSKJkAdLTo8nMUtIzwU0TLiQC9IoEgC1NEiw9J1imcpTBgmiuiE8Fk0CVRAgDpa cpB4RMbk0aGITh4COkACpRPgI6RlRohLoSXEhSJaQhToAwmUToCPkJYeIfo3EQGK6ETgWSwJVEiA U7tFBY1LoSWEgyJaQhToAwlUQ4BTu6WFisui00aEIjotf5ZOAvUR4NRuOTHj3MDksaCITh4COkAC VRLgkLSQsHFSd9pAUESn5c/SSaBiAhySVhw8uh6JAEU0EkiaIYG5EuCMYgmR58roVFGgiE5FnuWS QDsEqKPTxpL8J+RPEZ0QPosmgXYIcIl02lhSR6fiTxGdijzLJYHWCNhLpJxdzBxdnl6UGbgpjiI6 FXmWSwJtEuBuo/xxpYLmZ04RnZA5iyaB9glwdjdbjKmg2VAvLIgj0Wn5s3QSaJYAh6TZQstHRbOh 7hdEEZ0QPosmgfYJcEiaNMZce06KV2OcIqqhxDQkQAL+BDobjtjv+6NclJPD0Lg8Xa1RRF2JMT0J kIAPAZFSDkx92C3Jw9uRiDC9TVFEvdExIwmQgA8BSqkPtV4e7ieKgjHcCEU0nCEtkAAJOBOglDoj +1UGyCcV1Jte9Iz76OfTGbbo9GmQBEgABMy0pL47mhW3/rQtQaVuAHq9o4imjgXtkwAJqAjYUjFn kVi40jlnIKrWEzsRRTQ2UdojARLIRWCGA9OOcFIyc7W1peVQRCcPAR0gARIIIjCfgam+vw4Cyswu BPRB4cYiF65MSwIkkIvArB6J4dAzV7OKXw5FND5TWiQBEohIoO3jA/msZ8SmMokpiugk2FkoCZCA G4GGx2oNV80txnWmpojWGTd6TQKzJMBx2yzDXnSlKaJFh4fOkQAJGAIcsbExFEiAIlpgUOgSCZAA CZBAHQQoonXEiV6SAAmQAAkUSIAiWmBQ6BIJkAAJkMDHCMiJwfLZuXPnMJ2/+qu/MolTc6SIpiZM +yRAAiQwRIC7pVzbx1VXXfXWW2+55kqUniKaCCzNkgAJkMA4Ae6WGmfUS/Hkk0/+u3/37zwypshC EU1BlTZJgARSETAvAktVAO3WQOC6664bndTNUw+KaB7OLIUESCACgbZPL4oAaE4mCpnUpYjOqdGx riTQBAGZAuWQtIlgOlfiz/7szyRPIZO6FFHnEDIDCZDA5ATsISk35kwejpwOHHfccddcc42UWMKk LkU0Z/RZFgmQQEwCDczu8g7Ao0H88R//8caNGyXj5JO6FFGPCDILCZBAQQTqnd3Vv7SyINwFuLLv vvvedttthUzqUkQLaBF0gQRIIIxAjUNSKmhIzD//+c8XMqlLEQ2JI/OSAAkURMAMSQvyadAVPiQa EqlCJnUpoiFBZF4SIIGyCNSio1wKDW83hUzqUkTDQ0kLJEACBREoX0c5kRuruZQwqUsRjRVN2iEB EiiFQMk6SgWN20owqfv7v//7YnOSnboU0bgBpTUSIIEiCJSpo1TQ6I0Dk7r//t//ezE7yfELFNHo MaVBEiCBIgiUpqNU0ETN4jd/8zfNMUb5j1+giCYKK82SAAlMT6AQHTUnFHI7bqI28U//6T+1J3Vf f/31RAX1ze6jDypvo7JFhQWRAAlEJDBt3zVt6RExTmvK7Gfeu3cvhp59Z/Ai7sMPP1x+x3lGmNqV 73qNs23qo8aR6LQNg6WTAAkkJzDVeJQD0OShtQqwJ3WNgmZwgCKaATKLIAESmJiA33AkxGkzlMlf dIjbVee1J3WzVYQimg01CyIBEpiYQJ4jDjgAnSrM9k7dbD5QRLOhZkEkQAJTEsgzqcsB6JQx/sQn 7EndPJ5QRPNwZikkQALTE0iqoxyATh/gjzzIPKnL3bmFxJ1ukAAJZCKg33ipdyiFTX3pc0h5//33 SzU3bdp04IEHDlf55Zdf/p//839KmjPOOMODjz6gFFEPvMxCAiRQNwF9FzlaT7POyg1Eo6wqSqBv IZzOrSisdJUESCAOgVjv8eYKaJx41GyFIlpz9Og7CZCAL4Hw93jrByu+PjJfBQQoohUEiS6SAAkk IuC91YgKmigi1ZmliFYXMjpMAiQQk4CHjlJBYwagclsU0coDSPdJgASCCeh1lM+xBMOObODDDz98 6623Iht1MUcRdaHFtCRAAo0SGNVRWz65EbecVvC//tf/evDBByf0hyI6IXwWTQIkUBCBAR3lLtyC 4vRxVx577LHvf//7E7rH50QnhM+iSYAEiiPQWe/kY6DFRejjDv3Wb/0W3tny5ptvjp7A4FQR/bI3 R6JOYJmYBEigcQL2eJQD0MKDjXeIylvPnnrqqalcpYhORZ7lkgAJFErA1lEufxYapI/c2r17t7g3 oYhyOrfkFkLfSIAESIAElhL40pe+9F//63+VP8e93dFP51JE2UBJgARIgATqI4AnWw466CDj9zPP PPP5z38+VjX0Isrp3FjMaYcESIAESCAfgc4U7v/4H/8jX9lWSRTRSbCzUBIgARIggSACRkR///d/ H4YeeeSRIHO+mTmd60uO+UiABEiABCYigIOK9ttvPyn8m9/85iWXXIIvf/3Xf33ooYdG8YjTuVEw 0ggJkAAJkECJBPbu3WvcOvHEE+W7eRF3To85nZuTNssiARIgARKIQMBeAcWQ9IILLoDR//7f/3sE 044mKKKOwJicBEiABEhgagKdFdDf/d3fhUff+ta3MM2b2TWKaGbgLI4ESIAESCCIwMsvv2weDxVD OPxPvuA8+iDT7pkpou7MmIMESIAESGA6Av21T+wn2rhxIzzCefSZ/aKIZgbO4kiABEiABIIILFz7 PPfcc2H0O9/5TpBp98wUUXdmzEECJEACJDARAax6Yu2zX/iGDRvwI86j/8u//MucrlFEc9JmWSRA AiRAAkEElq16/oN/8A/E7o9+9KOgAhwzU0QdgTE5CZAACZDAdASWrXruu+++8qDL/fffn9M7imhO 2iyLBEiABEggiMDAqqc86IKNuzibPqgMl8wUURdaTEsCJEACJDAdAfMW7oUumAddcr5elCI6XXNg ySRAAiRAAi4EzFu4F2YyD7rkPIyeIuoSQKYlgdgEHnrooSuvvFKsvvTSSyeccMJtt9325ptv4vxr /IvlH/PXwJJRED6BRpidBKYlMLreidd0w8Prrrsu29FF+UQUnQI/JEACQqDfEz3//PNnn302JPPC Cy/Eq4Z//vOf2y8cDu+5Hn/88XAjtEACExLASmfnoKK+MyeddJL8mO3ookwiurDXmDAYLJoEpiXQ uSKgoEccccT27dtPO+00OGZGosZJDCJFfS+++GIMWPE75BYf+fHpp5++/vrr5a8ffPAB/tpJj/9e e+21mzdvxtAWZW3ZsgWJMeqVjY6wI7/ce++9GAeLzVgj4Gk5s/SWCGhWOnEdSZWfeeaZPHXPJKLe lcH9uPLjV4TSOJL52S8wl77KZaYsEGmgS3ipE678rVu3mpvojkHIHvRvz549iMiBBx4IrZUEyPj+ ++8/+OCDxx577Mknn/zGG2/ccsstSAaVveaaa1588UWkR0bR5iuuuAIpUcT555+Ply/iT7fffvum TZtEdPHBL6eccspFF12EjDD16KOPQpsDq8bsJBCRgEZEcYHIgy533XVXxKIHTJUuonkosBQSmJDA fffdh97h9ddfx0BwoRsvvPACJHb9+vX46x/8wR9AKUX5Tj31VLwE6rDDDsP3Y445BtO/Z5555nvv vffss88+8cQT69atw4ASIor0xiz0FX+CduJPcs8u41qYwr940g4WkBEuYSQKmxNiYdEkYBPAGqdy duQf/sN/iIw4ugjn1GdgSBHNAJlFkMAQAYwRIVc33HDDOeec4zT4O+SQQ5bZhejaEwmdZBi/mr+K NssHkrxjxw4MWPEd6oupXUaOBAohYL+Fe9il4447ThL8xV/8RQbnKaIZILMIEhgnsHbtWqgXJlqx INpJjbEmRpOY1MXv3/72tyGQULsBi5Je1jshhFgoNYlXr159/PHH33333fgFCTAeNdO5+AWjUvxy 1FFHYXPTrbfe+s4774z7zRQkkIWA/Rbu4QJ/8zd/U97o8v3vfz+Da6WLqH4zpx+s1Pb9vEqaS1/l MlMmhTOtcaxcHn300VdddZUtbHAJg0XoK2ZfERFsULz88suH/ZT0MmeL7RWSHtuIMLjESieWQnfu 3Ik/4fddu3bZeixCLvPAyHjWWWdNC4Slk4Ah4PTopzzognPqMxxdtI9+y4zsJ9Snt8PP3bm8GEig Q8DvUiJGEpghAaxu/sZv/MayimOmF6NP+68/+MEPTjzxRPzy3e9+V9b7XT96vcs0Ei1znye9IoEJ Cbhe1UxPArMl0H8L9zAK86CLZkNvINVMIhroJbOTAAmQAAnMlsDCt3AP0DAPuig39IaApYiG0GNe EiABEiCBtASWvYV7uFR50AWf1O/opoimDT+tkwAJkAAJhBDwO8DPPOii39br52QOETUHieFoMXmy O+IH+xhhVnbz4zt285vT0TpbHD0KlWcA5DQ1efDA/IIfl70b1qOgRFkwlWHOHIf/Bo54LsedSwUL fCIQ7slZdPh0TiHAEXfG4aStKzAueChFCJuz+vqVit5oA31mdhIojYBfT2sedHHa1utR9+Qiij4C B4nJiWVr1qyJfgr2TTfdhNNVpOYoBce+4MQyfH74wx/ivx5ETBZ4jocE5Ow0PHj3ve99D39Cb45n APDLPffcs+x8mZBCY+UVycRxqcbgHXfcgScc4Dn8l2ceEAucFYdfsPaOGIXfc8RyXuzgsDqIKNxD HO1TCHBbcNlll0ma1K0rsEY4YA/3MdJ+/vzP/3xhpeI22kCHmZ0ECiQw8BbuYW/lQRecWZ/06KLk Ioo+AgeJyakocv51xCChP8WJaLAvNn/84x9jNzMOP8PnjDPOwH9DysLzc3gs3VjYf//90WXjGXaZ JcAIw5y+FlJKory4sQBtHIVj7EN45Hw4PIwotzKIhWz+xnE5qGngPUf0itx88814qwnMovHIaXb4 LqfCmnolbV3hNQJnOVAen1WrVuHffqXiNtpwn2mBBIoiMPwW7mFXzWHUrpt7nQgkF1Hp++SzcuVK jBSd/BtILP3p1VdfbdLYB6ygzwo/bwXDCHnwHAqE3tB+Qd2KFStQbrZX1rlCw4kzpvtGXpmL/sY3 viGzo3IrY8fi05/+tB0p1+KSpofzr776Ko4gwU3M1772tW9+85sIipSYrnXFqpGcAYSXIP7O7/yO bdNUKnqjjeU57ZBACQSG38I97KF50MV1c69TxZOLqJM3+sSmP437zsVONweRllNGMQWaYau0vvp+ KWU6F6M3TOeWNnm7rEYyYYuZc0wMYOoeE7x1nYqOM4DAHMKP69kwtyvlF0rmIoGZEBh9C/cAB/Og C44uSjfgSS6iGH3alcSyaJTY4wYfM5Z4AxRu8/EFi5cYXcmMmfl0/uta7nPPPYfxmRyKholQrC/i HRcdI/1fXEvJk178lIlozI7iPR5oUp1YdCKVx7HhUiA227Ztw2QDpAgpMR+AxVFEHLKKD7YUJWpd 0esuwi+76jqVittoo3tOgyQwIQHNW7iH3TMPuvht8dXUPbmI4gYcIifdB95Ns+yNiRpf7TRQAnPW DBbMcAQoLH/uc5/DoaDopPDBF/zX1ayd/rOf/Sz+KxOhWHnFOhwEFWd/y/QC/h09Bzyk9Lh54Tn8 F8+xZRQroJBVEENEpHNHjMzUR9yiva3hrugLX/gCBs3mNSMm4jgbHR9MWSdqXd4+2xnRCKH3cmq8 MMetQL9ScRttFM9phAQKIRB+3pB50CXudpyP8dEfeybZ9OlNyuuuu07yoh+Rza5xPyKisImpV7PJ CApnv+/Jr0R5JxQ+sIYdvzKva/BJoSV/5D3M4iH8Ry0kCrJZGrEwdYEmlVYRe1cX/LRpi4iKw6lb VwgW+Cy1QLMU5v1KRW+0IQ4zLwkURQALaho5x9m5A27LG13wr1PV9HqX6QB6DQimIQESIAESIAEh gCWn4Vf+GVD9A+hthliJkx0teDHR5z//eSXe4g6gV/rNZCRAAiRAAiQAAvq3cA/jMmuIP/rRj1KA Tb4mmsJp2iQBEiABEmibQKzj+sxuj5CNvgOoKaJtt0PWjgRIgASqJKA/rm/4gT3zoAuOLkrxjm6K aJXNi06TAAmQQMMEcFAfNE9Zwf/0n/7T8GOg5kGX8O2+fZcoosowMRkJkAAJkEAmAk4H9eEshT/5 kz8Z8Mw86KIf3errSRHVs2JKEiABEiCBHARcD+rDo27/8T/+x2WemTe6IFn0o4soojkaBMsgARIg ARJQEnB6CzceAJUnQS+55BKcsbOsCHmjCz7Rjy6iiCrDymQkQAIkQAI5CDjp3H/4D/8B225FR//R P/pHP/jBDxa6aB50wdOicetAEY3Lk9ZIgARIgASCCOiP6MN5pb/927996KGHQkqlyD/+4z9e+PZQ 86DLXXfdFeRcLzNFNC5PWiMBEiABEggioHwLN16OhPdGS0mQ0u9+97v4gvPA8WN/4dM86IIEcd/R TRENCjYzkwAJkAAJRCSgfAv3BRdc8JWvfMUu99RTT4Wsio7+4R/+YV9HzYMuf/EXfxHRYYpoRJg0 RQIkQAIkEERA8xZurIDeeOON/TdR/qt/9a8grigeD72YCV7jjXnQ5fvf/36Qix/PzAPoI8KkKRIg ARIggSAC2EY7fMwCFBQ7ibAOurAYDEDx1mGx8Gd/9mfnnnuuney3fuu35P2PeMclJngHHOUB9EFR ZGYSIAESIIH8BDRv4cYQc5mCwmEMT/HAqGzW/ef//J93NuuaB10iHl3E6dz87YQlkgAJkAAJLCAw qm2yHXeYHST2tttukzQnnngiFllNevOgy2hB+vBQRPWsmJIESIAESCAhgWFts7fjDjuB94aal8B8 +ctfNttxzYMu8obRKB+KaBSMNEICJEACJBBEAMuZA9rW3447XBgGrGaz7r/5N/9GNuuaB13w/S// 8i+D3P1VZopoFIw0QgIkQAIkEERg4C3cy7bjDpeHzbqXXXYZ0mCzLh56kcTmQZdY7yuliAZFnZlJ gARIgASiEFimarIdt/9Ai6ZQjEHNQy9yQn30N7rwERdNIJiGBEiABEggLYFlD7dAXEc3Ew14hgVR nGEkT7bgVCOcyWAedPnrv/7rZRt9+YhL2mDTOgmQAAmQQEQCy97CrdmOO+wGZPLuu++WNHJCvXnQ xemtpctK4XRuxGZAUyRAAiRAAj4EFuqZfjvucJF4n6iZK8YJ9Wb06frW0oWlcDrXJ97MQwIkQAIk EJHAv/yX/xLbf2yDWMtceLafd6F4fwuOX+hk/+CDDxautuqncymi3hFhRhIgARIggQgE8PzJfvvt ZxvCZiK8EM1vM9GAQ9dee23nKZplC656EeV0boQWQBMkQAIkQALeBDpv4Q7ZjjvsA+ZyZbOu+ejf XbrMMkXUO+7MSAIkQAIkEIHAM888Y1sZPh03pDwMbf/0T/9UTtaVj/LdpQOFcjo3JCLMSwIkQAIk EErAPHMCQ9iOa161HWp3SX7sBP6N3/gN80dIOI4J7KTldG4i+DRLAiRAAiQQk4D9Fu5Y23GH/cPu XPtghx/96Ech9eF0bgg95iUBEiABEggiYN7C7Xo6bkipOL0BbxsVCzgOKcQURTSEHvOSAAmQAAkE Efj+97+P/H6n44YUjPd1ywn1eIM33mPqbYoi6o2OGUmABEiABIIIQL3weGi67bjDzn3lK1+Rzboh rxeliAa1AGYmARIgARLwJiDqlW477rBj2KyL8xwg4Y888oh3FSii3uiYkQRIgARIIIgARDT8dNwQ D6CjWBPdtWuXvHDU40MR9YDGLCRAAiRAAhEIrFq1KvUDLaNeYrMuhsKdAx9Gc5kEfE5Uz4opSYAE SIAEZkGAz4nOIsysJAmQAAmQwLQEOJ07LX+WTgIkQAIkUDEBimjFwaPrJEACJEAC0xKgiE7Ln6WT AAmQAAlUTIAiWnHw6DoJkAAJkMC0BCii0/Jn6SRAAiRAAhUToIhWHDy6TgIkQAIkMC0Biui0/Fk6 CZAACZBAxQQoohUHj66TAAmQAAlMS4AiOi1/lk4CJEACJFAxAYpoxcGj6yRAAiRAAtMSoIhOy5+l kwAJkAAJVEyAIlpx8Og6CZAACZDAtASc3+IyrbssnQRIgARIgATyEPj5z38+WhBHoqOImIAESIAE SIAEFhNwGIkSIQmQAAmQAAmQgE2AI1G2BxIgARIgARLwJEAR9QTHbCRAAiRAAiRAEWUbIAESIAES IAFPAhRRT3DMRgIkQAIkQAIUUbYBEiABEiABEvAkQBH1BMdsJEACJEACJEARZRsgARIgARIgAU8C /z/I6Th6YAZtfAAAAABJRU5ErkJggk== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image010.jpg Content-Transfer-Encoding: base64 Content-Type: image/jpeg /9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/wAALCAIpAhQBAREA/8QAHwAAAQUBAQEB AQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQAAAF9AQIDAAQRBRIhMUEGE1Fh ByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3ODk6Q0RFRkdISUpTVFVWV1hZ WmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKztLW2t7i5usLDxMXG x8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/9oACAEBAAA/AL/wu+F3g3xH8OdK1XVd G+0X0/neZL9qmTdtmdRwrgDgAdK7D/hSXw8/6F7/AMnbj/45R/wpL4ef9C9/5O3H/wAco/4Ul8PP +he/8nbj/wCOUf8ACkvh5/0L3/k7cf8Axyj/AIUl8PP+he/8nbj/AOOUf8KS+Hn/AEL3/k7cf/HK P+FJfDz/AKF7/wAnbj/45R/wpL4ef9C9/wCTtx/8co/4Ul8PP+he/wDJ24/+OUf8KS+Hn/Qvf+Tt x/8AHKP+FJfDz/oXv/J24/8AjlH/AApL4ef9C9/5O3H/AMco/wCFJfDz/oXv/J24/wDjlH/Ckvh5 /wBC9/5O3H/xyj/hSXw8/wChe/8AJ24/+OVXvvhB8M9NsZr280MRW8K75HN5cHaPwesu1+HXwzub u0tz4Q1KD7W5jgkuGuo1ZgrPjmTI+VGPIHStz/hSXw8/6F7/AMnbj/45R/wpL4ef9C9/5O3H/wAc o/4Ul8PP+he/8nbj/wCOUf8ACkvh5/0L3/k7cf8Axyj/AIUl8PP+he/8nbj/AOOUf8KS+Hn/AEL3 /k7cf/HKP+FJfDz/AKF7/wAnbj/45R/wpL4ef9C9/wCTtx/8co/4Ul8PP+he/wDJ24/+OUf8KS+H n/Qvf+Ttx/8AHKP+FJfDz/oXv/J24/8AjlH/AApL4ef9C9/5O3H/AMco/wCFJfDz/oXv/J24/wDj lH/Ckvh5/wBC9/5O3H/xyj/hSXw8/wChe/8AJ24/+OUf8KS+Hn/Qvf8Ak7cf/HKP+FJfDz/oXv8A yduP/jlH/Ckvh5/0L3/k7cf/AByj/hSXw8/6F7/yduP/AI5R/wAKS+Hn/Qvf+Ttx/wDHKP8AhSXw 8/6F7/yduP8A45R/wpL4ef8AQvf+Ttx/8co/4Ul8PP8AoXv/ACduP/jlH/Ckvh5/0L3/AJO3H/xy j/hSXw8/6F7/AMnbj/45R/wpL4ef9C9/5O3H/wAco/4Ul8PP+he/8nbj/wCOUf8ACkvh5/0L3/k7 cf8Axyj/AIUl8PP+he/8nbj/AOOUf8KS+Hn/AEL3/k7cf/HKP+FJfDz/AKF7/wAnbj/45R/wpL4e f9C9/wCTtx/8co/4Ul8PP+he/wDJ24/+OUf8KS+Hn/Qvf+Ttx/8AHKP+FJfDz/oXv/J24/8AjlH/ AApL4ef9C9/5O3H/AMco/wCFJfDz/oXv/J24/wDjlH/Ckvh5/wBC9/5O3H/xyj/hSXw8/wChe/8A J24/+OUf8KS+Hn/Qvf8Ak7cf/HKP+FJfDz/oXv8AyduP/jlH/Ckvh5/0L3/k7cf/AByj/hSXw8/6 F7/yduP/AI5R/wAKS+Hn/Qvf+Ttx/wDHKP8AhSXw8/6F7/yduP8A45R/wpL4ef8AQvf+Ttx/8co/ 4Ul8PP8AoXv/ACduP/jlH/Ckvh5/0L3/AJO3H/xyvnD4o6Jp3hz4jarpWlW/2exg8ny4t7Pt3Qox 5Yknkk9a+j/gl/ySHQv+3j/0fJXf0UUUUUUUVi634hXTLi10+0gF7qt2wENoJNuE/ikc4O1B6468 CoDaeLbhIN+q6VZkEGYQWbyEjHKqXcD8cfhUTaf4tmf7JJq9jHaeaGN5BARcsmVOzacopxuG7ntw DTpfBlpPcG7n1PVpL5WUxXX2ra8O3soACYOTkFTnPPapobHxNajYut2V2m0APdWRD5HXJR1Bz9BS TSeKrR4pBDpmoRbsSxQhoJAPVSzMp57HH1qpNpWqeJdSiOtW8dno1s4dbAS+Y91IBw0pX5QinkJz kjJ9K3tR0qw1eBIdQtY7iNG3qHH3WwRkHscEj8a53w5qraKLXw3raz295l0tJ55N8d0u4lVWTPLB cDa2G47111FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFfIHxt/5K9rv/AG7/APoi OvoD4Jf8kh0L/t4/9HyV39FFFFFFFFcb4fQaV4+17TZZY7u4vUXUVuSF85EJ2CJ8fwrgbfbd35PZ UUUUUUVz/jm3guPAutieJJFjspZV3jO1lUlWHoQQCD2xW5A6yW8UiOroyAhlOQQR1B71JRRRRRRR RRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRXyB8bf+Sva7/27/wDoiOvoD4Jf8kh0L/t4/wDR 8ld/RRRRRRRR1GK43wNplho8+r6XHp9vBe2NwwEyRnfLbyMZIsuRkgZZMZP3K3PD97rF9ZSya1pK abOszLHEtwJd0Y6NkdM+la1FFFFFIyq6lWAZSMEEZBFYJ8HaRFOJtPSbS5MBW/s+UwqwHQFB8p/K ql/p66VbJLqXi3VIrNZdqBmjVmZidq7lTc3XgdeB1rGMh1jVLSx8Oa1rNwgmD312Zj5UESk7kyV5 kYjaAORyTjHO5Jomu6VaA6Lrk120Tl1tdUxIsinOUMoXevXhjuxjoRUkcnjKKESTQaLcudrGCOSS Ipz8yhiGDYHQ4GfQUsfixLa6ltNbsLjTJlAaNiDNFMvqrqMZB4KnB/Cnr438LtBJMNdstscnlOvm Der+m372efStq2uYLy2jubaZJoJVDJJGwZWB6EEdaloooqvDfWlxcS28F1BLPDxLGkgZk/3gOR+N WKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKK+QPjb/wAle13/ALd//REdfQHwS/5JDoX/AG8f+j5K 7+iiiiiiiqmpapZaRafar+5S3h3KgZ/4mJwFA6kn0Fc/pEg1fxve6xbwNHZQWSWizPA0ZuHLbzjc ASFwBn1Y+ldXRRRRVSfUIoL23tTzJM2OP4RgkE/iMVDea5p2nLKb25S38tgpDsMnPQgDnmqZ8Qw3 un3k1jMF8h8LKU3rIobDMoyMjqM54rdHIrkbJINc8Z3+o3k8EsOkzfY7CAMCFk2K0kp9XywQf3dr dya66iiimeVH5nmeWm/+9tGfzrgbTVLPw58QdR0qwtLgWM0QeS2gG4Jc4Dlo4wchWR+cADMZ9TW6 vjjR1Ae7F9YQlinn3tlJDEGBC4LsAByepwKpa/4ttbuCPSfD2qW8upX8qWyXELeYtuHBJk3D5SwV WIGeuO1Wv+EUuNMCTaBq11bTqio8V5I1zDPtPVwx3Bjz8ykH1zU81v4quRHF9t02zQyKZJbeNnk2 A8hQ+VyRxkg4qvD8P9BRLh5oHnvbid7iS/JEdwZGBGQ8YUqACQAMCrjeG2V0e31zWIZEbOftIkB4 IwVcMCOfTtUDL4p0t1ZJLfXLbJDIyrbXC5bgg/cbAPTC9OtTWnizT5b7+z71ZtMv+StvfARmQbiu UbJV+n8JPUVNe+KNE0+5NtcajD9oCl2ijzIyqMcsFBKjkdfWtG0u7e+tIrq0mSa3lUPHJG2VYHuD U1FFFFFFFFFFFFFFFFFFFFFFFFFFFFfIHxt/5K9rv/bv/wCiI6+gPgl/ySHQv+3j/wBHyV39FFFF FFFczrLPf+MdC0xN2y136jOQmcYBjjGe2Sz+/FdNUTXEK3CW7SqJnUsseeSB1OKe0iIVDuqljhcn GT6Co3uoYxNuYjyV3P8AKemM8ev4VIjrJGrqcqwBB9jWXruo6jp0NqdO0eXUmmnWKVY5lj8lD1ck 9ce1TQ6TFHcSTy3FxcSv91pnB8oeigAAfXqe5NRxeH7APLLdx/b55Rtaa8VZG2/3RwAF9gKtQaZY WsDwW9jbQwvwyRxKqt9QBVrpXB+KfCGmWWkXl3p2kiS4ub2O4vJVjM06oZNzmLcSQeSdq8cnArrt L1jTtatzPpt5DcxqcN5bcocZww6qcdjg1eooorF8QaTfai1hcaZc21veWU7So9xCZFO6J4+gIPG/ PXtS+Hr2TX/C9vcajDA7zq8c8armN8MUPBzwcdDnrVfxVpkkvh6P+zLVmubCeG5tobdhGfkYblXo OU3qAeOat6X4j07VriS0ieWG9iXdJaXMZilVckZ2t1GR1GR05rWoooqG6s7W+h8m7tobiLOdkqB1 z9DVfS9H03RLU22l2NvZwFi5SCMKCx6k461z3g9pLXW/EOk28ZGl2l1uiLxlGSST53jUZ5QZBDYH 3iOcZrr6KKKKKKKKKKKKKKKKKKKKKKKKKKKK+QPjb/yV7Xf+3f8A9ER19AfBL/kkOhf9vH/o+Su/ ooooooorl/DhGp+JNe1rIaNJRp9uQ5YBYxl8dsF2PTuDXUVzGtQWb+JtPibRNQlnulZW1OzYxi3V RwHdWBAOTxS6p4LstSt0ia5vSFkDET3k0oI7gZfg+46VZbwraC+t7iO5vAsYw8clzJIJBjgfMxxj k/jW1FGsMCRIPlRQqgnsBgVg2t54mtjIl9pUN2zSFkktLhVREPRfnwSRzzjvVhtU1gHC+HZmGOv2 qL/Gqk1/4mluQE0KNLFomWRTdKJ9+OCpB24+vNU9EmvdAs76bW1W3EhT7OpPmuxCAEErksSRn15q STxNeafZX91qdqbWRgPsNu/7xpJNv3BsGeTjA68mq2i+NNQ1rU5be20mGVIFK3CQ3SM9vIMfK5zg c7hjrxmk1XTr/UL9NSg8PXtlqQ2o11a6jFEzoDna+CQ49AwP4ZNQaJ4m8SWcmnaTrujyPcXcxjg1 DeojkUEk7wPuyBAx24wduQa72uW8Sxa/d3UUdhaSG3hJk3w3CIZTtwFbccgA85H4Voafqmoz362l 1pElqFi3tI8ocE9AAV4z196w9Y1zxZpFstqmkW99qV/cGGyeG4CwxkqW+fcA2FVWJ4OcAd60PBum 3ejaWNPnsXgRP3jSyXAkaaViS7YHCgnkAetdLWdquhabrSxfb7VZXiOYpQSkkZ9VdSGX8DWQtp4l 0FVFncjXLJWwYLohLpV5+7L91yMrwwBOPvZNXLHxbpN5c29nLLJY6hOuUs76JoJWPOQoYAORg/dJ rcooorm9U0nUbPXTr2hRwTTyQGK8sppDGtyFGY2VsHa4OVyRgg84wK0tE1u212yaeBJYZInMU9vO u2SCQdUYevI5GQQcg1pUUUUUUUUUUUUUUUUUUUUUUUUUUUV8gfG3/kr2u/8Abv8A+iI6+gPgl/yS HQv+3j/0fJXf0UUUUUVh+Mb59N8HatdRTmCZbdlhkHUSN8qAe5YgD3IrR0zTbXR9LttOso/LtreM Ii9Tgdye5PUnuTVuiiiiiiiiuc0vwtpPhW71XV7VrsyXeZZ/OuGkUYyeATx1qC3vLa2u3k0S1t7m MyGa8XTFjzIWB27uQCw4JOefSrF/4qbTrC4vLjQtUjhgjaRmcRBQAM8nzK5zTG8S6jdWHibxDYz7 Io/OttLsyAtuWDrubcw3vtI6n5QxwOtdVpuq3sl1Ha3WnXSNLukEzlNgXAOMg5JGcdKmPh6xPiYe IMz/AG4W/wBnx5zeXtzn7mcZ961a4/W9at5fFvhi0t4pbj/TZG86HY0f+olUjO7qMgkY6V0ceqW8 mrXGmLv+0wRLMwK4BViQMHv0NZ0HivTS063dylu8bEqrgglOME/icfhTtE8QLqwvGSNmWK5McRUg +YnGGHTjnvzTn8RWL21yBqFnbTAMITNKBn5cqxU4OORxXD+HfEOjWwl1jxCLm6voVCTaq/8ApMMO NvChBmAFjnBRenJOM12PhjxXY+JI7g293byskrCMRkAvGOjgZJx710NFFFYOo+G3l1WTVtK1B9M1 CWDyZXSFJEmA5UupHJU9wQccZrmH1+48L69b282p6prcEMIh1NltPMEU7AGMrsHDMf4BnAYE4610 I8UX0Kq194X1aESIGj8hUuDkg/KwQ/KeB14561K3jDTLdQ2pR3ulguU3Xtq6ICMnmQApjAJB3VvK yuiujBlYZBByCKWiiiiiiiiiiiiiiiiiiiiiiivkD42/8le13/t3/wDREdfQHwS/5JDoX/bx/wCj 5K7+iiiiiiuS8VXOn2/ifw22sXSQWCPNIhmbbEbkbBFuJ4yA0hAJ6jPatG48YaBA4jXUormY42w2 eZ3OTgfKmT1qBNS8S6mN1jpEGmwEArLqcm6Qg4OfKj6dTwWByOlSRQ+K7bEbXek36hB+9eJ7d93O cgFge3THeom0PWNVlVta1fyrZXDCy0zdCrYJwHlzvYcjIG0cdxSt4b1G0GNI8SXtuuCPLvFF2gHP TdhgQSP4iOBwalTQdSjmaZfFGpl3+8HjgKe21dnFS/2Tqv8A0Ml3/wCA0H/xFVL0axoun3l7ceJL P7JCplMl5YZMagc5MbqCM5P3c896v+G9Ul1vw5YalPEkUtxEHZEOVGfT2PXn1rVyM4yM+lZt54h0 SwMq3mr2EDRDMiy3CKV4zyCc9KpQ+KvDMAVI9QtbdJGABZTEhJ9yAKxfF/iLQtY8LahaWXiKxMyy LGYopPMaZgwPkhUO47uF+XnmtOx8ZwNGketafeaPe+WrtBcRl1OR/C6ZDY6HoR3FbWnatp+rwGbT r2C6jU4YxODtPoR1B9jU13d29jaS3V3PHBbxKXklkYKqgdyTXKaTplx4o0mXUdU1DVoob+WR4rVZ fIC2xYiNSF5GUAJyc5Y/SodM8ELpvjiS/tLGxsNJjt9sC2cjo7O23fvj+5ghF5GCcDOea6V9A0x1 nVrYnz23SHzXyfbOcgew49qvxRRwRJFEipGgCqqjAAHQCuf1LTda1DxPCRNFb6KluQ0tvM8dyZCf u/3Sv61sLpliIkjNpCyooRd6Bjge55qqfD1gLD7FF50MJYlvLlILgnJVj1K9selF54a0S/ijjuNM tiIiDGyJsePBBG1lwy9B0Pasm3fWfC06Wlyt3rOjscQ3KKZLq29FkA5kX0cfN6561qWHifR9Ru/s cV35d5hj9muEaGXCnBO1wDxWvRWV4i1pdB0hrpYTcXUjCG0tlODPM3CIPTnknsAT2pvhvSJdG0to 7qZJ764me5u5kBCvK5ycAknaBtUeyitemuiSxtHIqujAqysMgg9QRWF/whXh7yzENOCwFw5t0mkW HIIP+rDbcZA4xiqlz4e1HRLV5/C9/PmJdyaZdyebBKAPuKzfNGTjAIbAPatbQ9fstftHltS6TQt5 dxbTLslt37q6nkH9D1BIrUooooooooooooooooooooor5A+Nv/JXtd/7d/8A0RHX0B8Ev+SQ6F/2 8f8Ao+Su/oooooqhrlxeWmhX1zp4hN3FA8kQmzs3AZ5xzWPoehw38Vlrup3dzqV3LEk0X2jCxwbk PCRL8oOHIJOT710kcMUWfLjRM9dqgZp9FFFFFZ2v2Q1Hw9qNmYfO863dRH/ebacfrisDw74e8P6n 4f07UUsFjmltY1lkiLQM7D724KRk7t3JrSHgrw6GDrpiLLliZVkcSNuxnLg7j0HBParcHhzRLazi tItIsVt4mV0j8hSAy4w3I+8MDnrVrUJhb2E0zQmZUXcUClsj6DrXLSytqd9CunaYs6hGEOqPbmKS A4+YKSgxnjkY79cVoazf6hdwyabpEBkvDGRM0m+JI8jg+ZtIz7AH8MVl6poeq6ksF4mk2tlrUYyu oWl6FkVsd/3eHU91bj+dY2q6h401S31rw1ceHbbUJlhjeO5tL1YfKLZMZYP1IZM8cYxXe6FBqVtp UcerTJNe9ZHjztJPJwD0Gc4FaVFFFFFc/J4iuLjW7rTdI09L02iKbmZrjy0R26Rg7Wy2OT6ZFMGn a/q128mpX502zUjyrTTpMu/qZJSoP/AVA6dTUkfhTw5ZxvLdWFtcSPIXe61ACaRmbA5d8n0AHTgA VVXw5o0N7HbaTe3umXUQO1LSdtu0FSVKPuTHI7dCcVjavqfia21O60jTNYicPbx3K6heQRg2o3OG GxQPM3GMAALkbic8Cn+JrnV9U03T7a80dra4h1G0naWG9haLYJVywzhypyRgKD059e/oooorB1nw +91qNvrGlzRWer2/y+a0e5J4z1jkAwSvcHOQeRTdK8RvNqj6LrFvHYasqh441kLR3SbQS8TEDdgk gr1GOeCDXQUUUUUUU1JY5CQjqxHXBzinEgdSBUcM0dxCs0Tbo25DetSUUUUUUUUUUV8gfG3/AJK9 rv8A27/+iI6+gPgl/wAkh0L/ALeP/R8ld/RRRRRUF7b/AGywubYNt86Jo92M4yCM/rXJnwhqF5oy 6frXiGaGyt4Eijj03/RgNi43u5JYnODjIX5RkHmr/g7Wb3VrO6F06XUVtL5UGpRRmNL1cffCnpg8 EjKk9OK6SiiiiiiuQ+H9xKLHVdJkKn+ytRmtUIbkpncuRjjhu+c9a6+iisux0G3sNb1DVo7i8knv gokjlnLxpt6bFP3a1KKx9Q8N2d/fNfpPeWV8yLG1xZzmNmVTkBhyrY56g9TWTqmoX3hK/tLy+1Oe 90S4byLgzW6mS2c52ODGoyrHCkFTjIORzW1Y+ItK1G+axt7r/SxH5vkSxvE5TONwVwCRnuOlO1nX tO0Gza4vrgLyFjiT5pJXP3URByzHsAKx7PT/ABPf6P8AbLnW5dP1Of8AeparBE8NuCcrGwK7mwOG IYc5xjipG8T3ukRI3iTSTaQhgkl/ayia2UkD5m6Oi5yMlcDjJ710iOksayRurowyrKcgj1Bp1cTp N2PBl3qNlrSPHa3V691BqKxfuW8xgNj7RiNgSBzweuc5rrbLUbLUomlsbyC6jU7WaGQOAfQ471kX 19pGtazN4WuUumuI4kunwjomARj5xwfpV2PRYrWZ7m2klNzg7GuJWkVfbBPA9hWRceBNN1eZb3XF NzqAbestvI8IiOQcJtbI5A6nnFVLjwTe2moTahpep/aJHC4t9ULyLhcEKJAdwGVU5IbHPrWnpfit bzUl0u+029sNRLyJskiYxMUycpLgBgVw3Hrg810VFFHSiszXdDtPEGmtZ3QKkEPDOmPMgkH3XQ9m FZmkeIZre9OieI3SDVFLeROV8uK+jH8aHJAbH3kzkdcY5rWude0ez2fadVsod+doe4Ubsdcc1R/4 TDSpZTFYfatRYMVY2Vs8qKQAeXA29x3pW8RynasGgaxLIzABTAsYHuWZgAKT7X4nutvk6VYWK72y bq6Mr7RnHyouMnj+LgUg0zxHNGouPEMULFgX+yWKggZyQpdmxxxkg0J4P05m33s1/qEuCN91ducZ JPCqQo69gOlc54xsrDwZZWeuaNHFp8kLJZNDDbEpPFIwXawTGCv3g3qMd66F/Dh1VhcavcP5wACi xmlgTAzjI3ZJ+Y9amtPD40Wxmg0SUxmVt2LuSSZFPqAW4+gwDTIvC1usKJLqGpuwHJS9kjXPfChs KOvA6Vs21vHaW0dvFu2RqFG9ix/Enk1LRRRRRRRRXyB8bf8Akr2u/wDbv/6Ijr6A+CX/ACSHQv8A t4/9HyV39FFFFFFQXlvbXVlPb3scclrJGyzJKAVZCOQc9sVzPw7jkTw5P84Nmb64+xKrZVIA5VVU ZOANpwM/l0HW0UUUUUVzfhFUeTXrkuXnk1adJGL5OEIVB7YUAYrpKKKKKKKK4nx3pk2q6x4Yt1v/ ALBG15JtuYlTz45RGXTYWBAUhHBA5OV6jIqvc6RZ+CvEttry2Ul3Z3MaWl3dPme5imL7Y5CSSzBt +whRxxgYzjvqRlV0ZHUMrDBUjII9K4rwtM2k+J9W8NxXVuNIsin2SGeb/SI2dFYIgzzEPmwTznKj IWu0kkSGNpJXVEQFmZjgAepNYKeNvD0thfXkGopLHZW5uZQFKsYwD8yhgNwOMAjIJ70eFLK7hg1H UL6ySzuNSuzdeRuDPGmxVVXYcFsLnAyBnGTXQUUUVm6voltrP2VpZJoJ7SXzYJ4GCvG2MHBIIwQc EEc1zmrah4g8K6ZPLqFwmo6aNifb4gsV1bA/KWaPGyTnB+XB5PynFWYzd2vhRoNGn1O9uHOyGaeB UaNjjqGVBt98H8a0Jn1e9la2hhECpCUlluVBjlc4+6FYN03c5HUVA2ka3cwxQ3l9YMkabQ8cDhzx jqXPcAniuiUEKAeoFLWfrWiad4h0uXTtVtI7m1k6o46HsQexHqK5bw9bvpXjW50W3W3ura2tlkku pbaOK4i3Y2IGXHmg4Yk7RjgEk13NFFFFcz4/hMng+6mDygWskV04jYLuSORWYHPUbQTjviujilWe FJUOUdQy/Q80+iiiiiiiiiiivkD42/8AJXtd/wC3f/0RHX0B8Ev+SQ6F/wBvH/o+Su/oooooorG8 V6NF4g8K6lpc3CzwkA8nDDlTgEZ5A479Kf4Z1KDVvDWn3sAgUSwIzxwfcjfA3Jjtg5GDzUereKdM 0tfLEwvL5n8qKxtWDzSSf3QuePcnAHc1a0bWLXXNOW8td6je0ckUq7ZIZFOGRx2YEY/+tWhRRWfq eu6VoyFtR1C3tzjIR3G9vTC9T0PQVmP4h1K+cxaJodxIP+frUAbWEfdOQCN7dT0XHB5qnp3gq5h1 bUNYu9cukvtQ2eelgqwwjYCBgMGJOD1JyauroniCKdRH4qla1CkbZbKJpSc8fOMDAHH3fxqeK18S xR7G1bTZsE4kksHDEZ4ztlAzjjgCmNP4qtWYtZ6XfpvGDDM9u+3Az8rBhkHP8XI9KP7e1KF3F14a 1AAKGVraSKYHrkfeByMDt3qWy8VaRe3a2f2lra9YAi1vImglOcdFcDd1HTNbNFFcv43cQ2ukXM+1 bCDVbeS7kwuY1DfKwJ6ASbNx67d1bGt6auq6W1s1w9vtkjnWVFDFWjdZAcEYIyoqh4Pv9Q1TRDfX ztJHNM7WcjxCN5LfjYzKOhbkj2IrfqjqOi6Zq8ezUbC3uRgAGWMEjByMHqOfSuI1OTUdF0bVfDVz pGpa5aTr5dhKiPIDDICCkzgEjy8HnklSvU1v6PZ6Jr+k2K3cNtqV3pipbySXFsQ8cqBd3yuAy5IB 5Hoa6aiisbWfEdrotn9pmikdfMSNApUeZuZVypJA4LjqRWFDd6jqsbX1/wCJ7bRxnMNlZywSeWMj Aldsh2OCCFwBnqetUdI+J1laRz2fim7s7a+t1VllhkBW4QnG7AyEYcblyQM5BIrLu9UT4rOmhiSx g0OR8vOx3TXRUZ/cKcFe/wAxHGDgGvVLeBLW2it48+XEgRcnJwBgVJRRUc88NtA888qRQxqWeR2C qoHUknoK5658Xw3EJTw9aT6vdswSPyo2WBSRnc8xG0KBycZPYAmpNB8PzaTdXeratqTXup3YUSyM SsUKjpHEpPypk9+Sea3Y5o5WkVGyY22OMdDjP9RVfVNTt9I0+S9uiREmB8oySScAD8afZ3i3VvDI yNDJJGJDFICGUe4NTxyJLGskbBkYZBHenVieL7CbUvCeo29uu+cR+bHGU3+YyEOEx33FQPxq1oms 2euaal1ZzI4ACyKAQY32glWB5BGRwa0aKKKKKKKKKKK+QPjb/wAle13/ALd//REdfQHwS/5JDoX/ AG8f+j5K7+iiiiiiiuUHgopqN40OtX1vpd3OLqWwgOwtL/ETL98K2BlQR064OK3dN0bTdHto7fTr GC2jjXaojQA4+vU56knrWbqPhjfqEuraLeNpeqSLiWREDRXOB8vmxnhiOzDDAcZxxU2iazd3lzNp 2qaebPU7aJJJQjh4pFZmUMjA5wSh4YAitquUm1TUvEl9c2Gg3Is9PgDR3GqmHeTKGwUhyQCRg5Yg gHjBINM0K58GWFysWnXlvPeTyiI3UkhmlnkUbcGVs7jwRgHHXFddRRRRRVPVNJsNasns9StIrm3c YKuOnuD1B6EEcjFZK6Hrenx7dL8RSSoqkJDqcInGcDA3qVfqOpJPNPTU/EFtLsvdAW4jyQJtPulb jAIysmwjnI6mpB4kCStHcaNrMDABgfsnmhs56GIsMjHQ46is7WtR1DXdJvdM0rQrwtcI0BuL+JYY UDJyxV/mYc4xt61o6ro5k8E3ei20xBOntaxyykk/6vaC2OvvirPh29h1Hw1pd5bxRQxTWsbrFEQU jyo+QY7Dp+FaVFFed/2h4g8K+IdavL7QZL+3viky3VlzHGqJjaygF845zjmtqHxOuu6XDHpEqS3s 6MJBEGIgwCDliBtIbAwefauojDCJA/3toz9aUgMCCMg8GvNryezufEWseHbvRb7WtPSBIx5U5uAr Ow+QqcLERgHLNkBQa6vwzpElv4ZsbfWLSBr1I9sm5UY4BO3cQMFtuMkcE5rXSxtIwRHawLkYO2MD IpY7K0ik8yO1hR/7yxgH86ytf1e+0keda6Vd3kUUbPIIRHtPBxyWDAggdAeCapf2xqupWtjNBo2r 2z/JMSjW4STI5RtzE7efQHp0rX0q81O7kujf6d9ijVh5AMiszqRznBOCP85rSpksUc8TxTRrJG42 sjjIYehB61zn/CN3ukTzzeGr+K0ikQk6ddRmS28zsyYYGPPOQMjvjPWjeeK7mNCl5appd/a273Fx bXoZ4pYxjc8Txg7wpxxjPzDIFXNJ0221jSrXU7PV9QWK6jEmbeRokbOTnawJHpz6Crz+G45VCTap qcsWMNG9wCrj34p0ejtaSG6sLueRwhSGG5nZoVBxwO/Yc80mkaLc2N011d6jLcSyK2YskRRszZOw EnA6Dn0PrWzVbUDerp1ydOWF70Rt5CzkhC+ONxHOM1yVnJrPh/VrW+1aOJ49bMUV9HbPlLa8wEVk 3HJRlCqRzgqD3NdtRRRRRRRRRRRXyB8bf+Sva7/27/8AoiOvoD4Jf8kh0L/t4/8AR8ld/RRRRRRR RRRWLqHh4X2qNfR6nfWbyQxwyrbMi70R2YDJUsOXYHBHFQT+F55ra5tU8R6zHb3KFHXzI3ZQRg7X ZCy/gagtvAmmRWcNncXN7dWcLKyWjyhIAF6L5aBVIB5wQcnk5q3r+izXGj2kOjpbQTWNxFcW8LLs iOw/c4+6MZ6DjimHxHdWVzBDrGjT2aXFwtvFcxSpNEWYDbuIwy5b5eVxnHPNdBRRRRRRRRRXC674 lu59VutIa7/4R6xikSKTUZ428yUN1MJxsQEkLvYnBzx0rrNHsLHTNItrTTAoskTMRD79wPzbtxzu ySTnvmr1FNkTzI2Qll3AjKnBH0NZ2gaJH4f0pNPivL27RGZhLeTGWQ5Ocbj2qvqHhXTL+4e7RJbG +bObuxkMMpOMZYjhv+BA9Kqzr4q0eLzoZ7fXIEyWheIQXJXPG1gdjMBnghc4HIqDWvFFvdeAdS1X SrzypEjaIFxtkhlJC7GVuVcE9D3xW9pGkWeh6bFYWMQjhjH/AAJ27sx7sTyT3q9RQenpXGeD77T7 TWtY8PwPrTzxTtcebqjblkDf88WPVB/nrW7f+IbDTrhEuJ4Viw/muZOYyoBxtxk8E/TFaUE0Vzbx zwSLJDKodHU5DKRkEH0xUlFFcl4hlXQfFFp4juomk0z7K1pdyiLf9kG7cshwchDkhiAcYBPFdPcX MNnZS3UhxBDGZGKqW+UDPAHX8K5201uXxHZwX2k2lxLZ3ODb3ZZY1Rc4bcrHdngj7p7Yq4sWpWUd lYWtu8kUBBkuTKqqyj+Hb1JPTsB1zVe10/W7qMy3dz5A+2tcJBMgkkVARtUMrYXofXhqS403WdWm nZLqTR7ZmB8tVSSSRh/ESp+UdOMknA6dK6F5REq7tzE4GFGSffFcb8QtStrjw7FpVs0c9/qhH2MA r8gQhmm+bjCDnP0Heun07UYbrTYZ2nTcUG4syg59TjgU7TtWsdWheWzuI5QjFXAYZUj1HUfjSnUF W/jgOwQyQmRZS+MkHGAPpzU8dzBLI0ccqO6AFgrZwD0/kalooooooor5A+Nv/JXtd/7d/wD0RHX0 B8Ev+SQ6F/28f+j5K7+iiiiiiiiiiiiiiuQ19l8Ua5F4XgZWtLcpdarIpzsUHMcII6OxGT0IVfcV 19FFFFFFFFFYXi6DW7rw7cW+geQLuX5HaR9rCMg7vLOCPM7LngE5PSmaHq9lDJB4fNjd6bcW8Qjt 7e5XIkjRQMpICVYAYzzn1roKKKKKK5vVfBOnaprUerC5vbS5WRJnFvIPLlkQYR3RgyllHQ49PQYi vbjXfDVwbySSfW9HIHnKIl+1Wvq6hABKnquNw7bulb+n6nY6raR3Wn3cNzBIoZXicMMH+VWqyvEN 7e2GkvLYaRLqszMsZtopVjJUnBOT6CmW2gRpOl1Jd3Uk6xeXE0nl7oVPYFVGfxzSxeGdJGXurOG/ uGOXubyJJJGP1I4HsMAVqxxpDEkUSKkaKFVFGAoHQAdhTqKKbLFHPE8UsayROpV0cZDA8EEdxXE6 Tqtz4S0Ka0vtA1GOx02aQG5Ro3jWBpWKMo37iioy544Cn0rtlZTGGUjYRkHtisT/AITTwz9t+yf2 7Yed5fmcTrt25x97pnPbOalPivw8qknXNOwBn/j5T/Gki8XeHJoklTXNP2uoYZuFBwfYnIqrrbXG q6LJqHhe+S4vUQrD5Fygjk55VmKsBjB6YOR1rkNctrqz8SaLeazodzd6VZwJDFbwrDcB7mXCMvzk NtGRjrkgnjHPX6YPDOuy3axaVai6hYJdQXNkqSoTyu5WGcHGQeQccdK2LXStOsTIbOwtbYyDDmGF ULD3wOaox+FtIVgZrb7YFG2NbxzOsQ9ED5Cjp09Ks6doljpNxdTWUKwi427o0UKi7c/dAHHWtCii iiiiivkD42/8le13/t3/APREdfQHwS/5JDoX/bx/6Pkrv6KKKKKKKKKKKKK5nxrdalZ6dDLazXFv YBm/tC5tIw88MW376A+h6kAkDkDitbRtMsNL08R6ep8qZjO0jMXeV3OS7MeSTnqa0KKKKKKjmmWC JpHVyq8nYpY4+g5P4Vgi+vds+qvHPHb+TJHDG1u5fO75GMYyeeffGOlRnU9Ya0sUSxd9WEQa5jYO kC5HPz4IznoME/Srsdx4l8pfM03Sy+Bki+kHP08qp7J9ae6H26CwigCn/UTPIxbPHVFwMZrO8U21 /FJYa5psJuptMMjSWg+9PEy4cJ/tjAIHfp3rZ03UrTV9Ogv7GZZraddyOO/Yg+hBBBB5BBFWqKKK KKK4TxfBY2N9bPoEATxYzb7aK0UAzJuBcTgYHlHnLN0PK88HulztG4AHHOKWqWp6vp+jWv2nUbqO 3iJ2qW6scE4UDljgHgc8VmXfiuNYmXTtL1TULry2ZIls5IlJHQM8igLkkevfjimyeI7zTb+2g1vS 1tbe5lWGK8guRLEJG6K+QrLkjAOCM4Gea6Kiiio54Irq3lt541khlQpIjDIZSMEH2xXB6p4ZsT4x 03SLNrm2sLq2ll1C0iuCkU8cZAUYznO5gCFxlScntXeQW8NtAkEEUcUMahUjRQFUDoAB0p+B6Clw PQVjXHhXR5743y2ptrs/ens5Xgd+v3ihG7qeuaF8Mab9qt7iY3ly9tJ5sIubyWVUcdGCsxGRng44 rP8AEFq2m+JtJ8SW2DI7ppd3GzECSGWQBCO25HIPuCwz0rqaKKKKKKKKKK+QPjb/AMle13/t3/8A REdfQHwS/wCSQ6F/28f+j5K7+iiiiiiiiiiiiimSxRzwvDKiyRSKVdGGQwPBBHpXJWMEnhzxhBou mSrJpt+sl29mwz9iVVALI27hWcp8mOCWIwOK7Ciiiiiq9/ZRajp9xZTmQRTxmNzG5RsEYOCOQaj0 rTYNH0u2061Mhgt0CIZXLtj3J5NXKKKo6zqsOiaPc6jOkkiQrkRxrlpGJwqKPVmIA9zVDwlpFxpO ju18V+331w97dpH/AKuOWQ5KJ7DgZ7kEnkmt2iiiiiqWsaiNI0W91JoXmW1geYxx/efaM4FZfhLS 2tbB9Tu5Y7jU9SxPcXEcvmKVOTGiNgfIqkAYAzye9dDRXLaxFJq/jXRtPjeWKLTAdTnljO0kndFH HnPRsylhg8KB3rqaw/Fmk3ms6DJbWFwIbmORLiNWAKTNGwdY37hSQMkcj9KisfF9hJcPZaqDpGox sQ1teMFDjs0b/ddSB2OR3ArdgnhuoVmt5Y5Ym6PGwZT+IrD1rxQunXraZp+n3WqasYDKttbrhE67 PNkPEYYggE+h4pLHxXbtdtp+sw/2RqKqHENxKpSVeMtHJ0cAnHYjuBXQ1l63oFnrsEa3AeK4hbfb 3ULbZYH/ALyN29x0PcGofC99eXukyDUJUmuba6mtXmRNgl8tygbbk4JAyQOK2qKKK5nxndJBDosM hRFn1a2HmyOERNj+ZyT67NoHdmArpqKKKKKKKKKK+QPjb/yV7Xf+3f8A9ER19AfBL/kkOhf9vH/o +Su/oooooooooooooorndIRrjxj4ivZPLzEbexjATnasfm5Jz3M5GOPuiuioooooooooorH8U6fP qfhi/trQsLvyxLb4xzKhDoOeMFlAOe1WtF1ODWtFstTtm3RXMKyL0yMjkHBOCDwR2NXqKKKKrahf 22l6fPfXkhjt4ELyMFLYH0HJrLXxZoUs72dzefY5tpzFfRtbsy8ZI3gZHI6Vl+C7+G3vL/w1DexX kFiFlspUk8z/AEds4Qkf3CCvXOMV2NFcl4IgMTaub+Fxrouyt/O7BhJkbo9hH/LMIwwvGOeM5rra Kjmt4blAk8Mcqg5AdQwz+NZJ8JaH9pkuIrI20kv+sNpM8Ac5JyQjAE5J5681No2gWehm5a2e4lku XVpJLiYyudqhVG484AAHNReJJdDGmm1117UQXYaFEn5LkqchR1zjPSuT0e8ibTw2s+O7dEsoVgEd pcCLGxRukkMnzs569gB69ac9tHqNtbWvhyz1iWWaMN/aOo3F3HFEnHzkMwMjHPCgc9yBXX+HtDh8 O6NFp8VxPcbWaSSe4fc8jsSzMT7kmtSiiiobyzttQs5bS8gjnt5lKyRSKGVh6EGud8KO+n3+q+HZ ZnkWwkWS0Mrsz/Z3GVGW5IUgrnJ6V1FFFFFFFFFFfIHxt/5K9rv/AG7/APoiOvoD4Jf8kh0L/t4/ 9HyV39FFFFFFFFFFFFFFYOhf8h7xP/1/x/8ApNDW9RRRRRRRRRRRXL6AJNI8R6noDyM9q4OoWRaI LgSSMZU3DghXZSM84fHOK6iiiise/wDFOjadctay3qyXajJtrdGmlHTqiAkdR19ayNeu7/xHod9p enaFqAM+IRcXYSCNc4JbDNvIA9F5IxXWSwxTACWNHA6BlBrG1fwxaal5Vxau2nalb5Nve2qgPH7E dHQ91bg+x5qN9B1W6YveeJ71WDbkWyhjhReBjIIYt0PUkc9KpzHxjp8cwlvNKns4IvNN81u/nsFG WXyVIUtwcEMByPlrJ8BazGNCjeGOfWNTvF+23lxA6HczHABLyAZVQFwvA244rqm1fUeNnhvUDnru mgGP/IlZ0+q+Ira2W0h0Wee9JYmZpISgUtnIG9ScA4wcZxWjqVzew+GbiZ/LhuxFgF2AXJ4znkDr 7ge9RpcanbW9nKLWS82oY5YraaMkcDDEsVBPBHHr0qPVvEV9pthJcR+Hr6aUbisXmRDftXd1DHsD 27fSofDWlvcyR+JtSuY7zUby3XyWjTbFbwt8wSMEZ5zyx5Pt0roXtbeR97wRM/8AeZATUtFFFFFF cv4UEd9qeu6y03nzPevaRuGyqwxcKq44xksT6kmuoooooooooor5A+Nv/JXtd/7d/wD0RHX0B8Ev +SQ6F/28f+j5K7+iiiiiiiiiiiiiiuVS7ttF8e3sV1JJbw6vDA9u0mfJkuF3o6huiuUEXy8ZxxnB rqqKKKKKKKKKKK4qyGp6p4t1jWdLFl5EW3TY5LrzCWMZJkKYwAu9gp65MZ9K1/tnie1LedpFjepv ADWl2Y32nGTskXGQc/xcihtY1z7QoTwvcG343M15CHzz0XcQRwOrDr0OKhm8R6nYuk2o+HLmGwaT y2mhmWeSLphnjQH5T6qWx3GKl1vU7a88BapqWn3iyQPp08kNxE+B9xsEHsQfxBq9oem2OmaRbQ2F pDbRGNCViQLk7QMn1PHU81o0UUUdRg1xngmHS9Mv/ENhFHFa351OWWWDhSUbmJlX+6UxjHcHvmuz IyCMke47Vl6BpV1o+ntbXerXeqSGVpPPusbgCeF47CtN0WRGR1DKwwVYZBFZN1qPh/wvb7J7iw02 NgXWIbYy3TJCjk9R0HeuW1PU9Y8V60+maQb+w0uOJllme1MRuXIPRnU7UXAGcZYseMDNbvhzTNX0 5zFdeSlpGiQQRpP5mI0UKufkU7uOTnHsK6OiiiiiisjxVbXV54T1a2skMlzLayJGqsVJJU9CCCD+ IpPCj2D+FNLOltusxbIsZKBDwMHIHAbIOffNbFFFFFFFFFFfIHxt/wCSva7/ANu//oiOvoD4Jf8A JIdC/wC3j/0fJXf0UUUUUUUUUUUUUVW1DT7PVbGWyv7eO4tpRh45BkH/AAPv2rnfs+teFrkNafad Z0V2Aa3d991ae6Mx/eJ6qTuHYnpW1pOuafrcUjWUxZ4SFmhkQxyxMRnDowBU/UVo0UUUUUUUVR1q e6tdC1G4sY/Mu4raR4EClt0gUlRgdeccVU8JwWlv4V04WV295BJF532l2JaZnJdnOe5ZiSO2cVs0 UVwOr+FHs9eF3FY3OpaBK/2ifSYZgFS53Z83y2IDg5JK5AyM4JrpbDxLYXl+NOZLmzvSCUt7uAxN IoAJKH7rAZHQnHPpWzUN1Oba3aUQSzbRnZEAWP0BIzWDDf6y1tc3LIJYdjLFFbKkkyOTgBvm2kj0 H40abaeKoYo3ubzSzI6J5qm3fdkDk5D4yfYY44qzPD4nePbDe6TG5H3jbSNjn03+lUJPDN/quqR3 Gvy6VeWqAjyUscNxyuHYlgQ3OQfwq/F4VsIIxHBcapFGv3UTUpwF9gN/SmXHhHTrpUWe51WQI4kU HU7gYYdDw9C+FwCivrmtyQozMsRvCvXPBdQHIGeMsapax4H0+48OaxZafEI77ULdo2u5naSVjksA XYlsZPTOBmodO1270bQbeGXw1rfk2UCLcO7pM69mx85aXGM5A6dOeK6bTtTsdXso73TruG6tpBlZ InDA/wCH0q3RWP4lnnt9JZ4Z7m2AOZLi3QO0SgE52lWyM4B4OM5ptgdSudPgkt7+KSB7cFZpoSZG frk/dG3/AICDVeGw8R27kwXOkRqzF3UW0pDk9+XqeVPE4iJjuNJLBTx5EnJ9vnqvqK6zqDwWFvCk axjdc3F1HmJ+ONgVgc7sH0HvWdPYtf8AjO90jWbm9ktrmySWzjguniiMaYSVWVCDu3MDkk5DADG0 119tbQWdtHbWsMcMEShUjjUKqgdgBUtFFFFFFFFFfIHxt/5K9rv/AG7/APoiOvoD4Jf8kh0L/t4/ 9HyV39FFFFFFFFFFFFFFFFYGuaDNdaha6zpMsdtq9sQm9xhLiEkbo5MAnGASCOVP4gv0fxAb3Ubr SdQtVsdVtsOYPNDrLGc7ZI24LLxzwCDwe2dyisbUPFeh6Y9xFc6lD59uuZIUO+QHGcbRk5Pp1rJm m8WeILaG3jsI9Es7oK0tybstdRR8EqEC4V2GRncdvPfFaMXhWBHzJqmtTRgEJG+oSALk56qQx9Bu JwKV/Clm91FML/WEWMEGJdUn2Pnu3zZ47cioX0PWdPdpdF1uR0JJ+yapmePvwJM+YvJHUt06VXXS vEGvTtJrd22lWse5YbTSrptznkeY8uFPuEAA9c9Kv/8ACNK8qPc6zrE6rnEZuzGDnufLCk/ia5Gw 19fAEJ8KJoN1PLFcytYxWjqwlgkkZ0K7jnILFDnoVyTyK9IRi0asylCQCVPUe1OoormtQla98d6P aW8Tv/Z8cl3dSYwsaujRoue7Mdxx6Ka6WgjIwaztH0LS/D9tJbaVZpawyytM6IScuep5rPsNXvry 8u2juNNuIULiK0iytxlTjDktgcj0p1xea60sbpo0uFwwWO8jAOR918jnBz0qT+09cXAPh4sQOSt5 Hg/TNLHrV1C00mq2H9n20aAiRpRJubPT5adoc9/dNPcXUE0UMuGiErg8ey4BUYwcNzk1sUVgeNbi WDwjfrb+d9puFFrB5Jw3mSMETByMcsOe1PXwb4bRUVNFs1CIsYxGASFGBk9+O5rLvLG/8HRPf6PJ cXWkJIZbrS3/AHjRR4JdoGJyMddhJB5xjpXUWN9a6lYw3tlPHPbToHjljbKsD6Gkv7C11TT57C9h Wa1uEMcsbdGU9RRp+n2ulafBYWMKw2tugjijXOFUduakmuYLdo1mnjjaRtqB3Clj6DPU1LRXG+Pr ePTNJu/FNndS2esWcAWGVDkTgE7YWQ8OGZiAOuSMHiui0K/fVNBsb6SOaN54Fdlni8pwSOcrzt+l aFFFFFFFFFFfIHxt/wCSva7/ANu//oiOvoD4Jf8AJIdC/wC3j/0fJXf0UUUUUUUUUUUUUUUUV5+Z df1Tx1eXtta6fdW+ku1nbRG4MTRM6xlpJOG3AqTjHp071u/2DrGpMH1nXZETywptdLU26bs5YlyS 7dgMFeM8c1abwtpbqVYXxUjBB1C45H/fdXtO0yx0i0Frp1pDawA52RKACfU+p9zzVuiiignAzXI2 mo6x4vWeXTLldI0lZHhWYxh7qVlJVsKfliAPTcC3HQVt6PoGnaGshtInM823z7maQyTTEDALuxJP Tp064FadFUNS1rTtHUNf3UcG5GdAx5cLjIUdzyOBzVM+KtHk077Rb6lYGV4t8cU10kZLEZCtycc8 d64uHxNb2Pju/v7tbZ572yhFrcC6UQxW6EiQE9WIkJOQDkEYwAa9NjdZIkkVlZWUMCpyCD6U6isf /hHYf+EsHiEXl2Jfs32c2wceSRnO4jGc/jWxRRRRRXM6pH/avjfSdPdGa206JtSlBVSpkJMcPJ54 /etwOCqnNdNRXOy+EooJ7m50XULrSJ7h/Ndbcq0DSd2MTArk98YJx1zzUjaHq00axz+J73GQXMME MZbHUA7SQD+fvTh4XgeVXudT1e5CggI966Lzjn5NuTx396B4P8P+ZJJLpcNzJIArSXZadsDsDISQ OB09Kzn03VfCgSbRWuNS0qNcSaXNJvljXJOYHbk4HGxicgAAit/SNYsdcsFvdPnE0JJU8EMjDqrK eVYdweRWH8Q7n7H4Qlu1MonguLeS38qPeTMJV2AjuC2M+1dVRRRRRRRRRRXyB8bf+Sva7/27/wDo iOvoD4Jf8kh0L/t4/wDR8ld/RRRRRRRRRRRRRRRRRXJ66lx4c1eTxRao01k8Sx6rbqMsI0yRMvPJ UE5HcH1FdVG6yxrIhyrAMD6g06iiiiiiuB8QaVaWPjPSLh2m0/Try4LzTWs7x+bd8bFk52hWA9Pm IAPv31FIxIUlRlscAnGTXPeHbK8uEbUtd0xbTUt7IkP2r7QkSZ4KHoueM4/+tW2bK0ySbWD3Pliu b0eKx1Pxjr99HawSw26W9gkxVGHmIHeRVxnAHmJnpyD6V1YAAwBgCiiiiiiiisrXdeg0GC2aSCa4 mup1treGHbukkboMsQAPcniudtG8SaX4hn1vWdON1De2sUPk6aA7WW2RiFYEhpMiTJZehB4xityD xZo8l6tnPPJZXTfcivomgMnT7u8AN1HStuiiiiisO/8ACthd3smoW8lzp2oSY33VlJ5bSYBA3ryr 9f4ga57xhb3+jWtnrV9q8uoafp97bzSWktuisfn2lgyFM7d4YAg/Mg+ld7RRRRRRRRRRXyB8bf8A kr2u/wDbv/6Ijr6A+CX/ACSHQv8At4/9HyV39FFFFFFFFFFFFFFFFZOq+JtG0ZZRe6hAs0YBNsjb 5mJ+6FjHzEnIwAOawNVvLzxbYWelx6HqVnHc3EbXpvrdQIoUbcQfmIJYqowM8E12oAAAAwB0Aooo oooorP12HTbjQb+PWBGdNMDm5MnQIBknPbHXI5FUvBsmoS+D9Lk1Rma6aAEs4Icqfub8/wAe3bu/ 2s0al4lW21M6TptlNqeqKnmSQQsFSBT0MrnhM9hyx6gYoDeK5AzGPRrfJO1C0spA7ZOFyfwpn9ia 1dqBqPiSdU2ruj0+BYASDk/MdzYPTgjill8IabdDbey6heR4I8q4vZWQ5GDld2Dx61s2tnbWFstv Z28VvAudscSBVGeTwKmoooooooqjrOqwaJo13qVxzHbxl9oPLnso9ycAe5rI8PaBIJY9e1t/teuT R/eYfJaKefKiX+EdifvN3PYdLUN1Z219btb3dvFcQt96OVAyn8DXKWU83gq8g0m/lkm0GZkh0+7l YE2zdoZDwSvACsc+hPSuxooooorlvGUY1Y6b4bEDS/2hcLLOc4VLeJlaQk46nKqMYOXHIxXU0UUU UUUUUUV8gfG3/kr2u/8Abv8A+iI6+gPgl/ySHQv+3j/0fJXf0UUUUUUUUUUUUUUVzniLVrpr+08P 6NOseqXZ8yWYAN9kt1I3ylTkZPCqCMEnPRTWjouh2WhWjQWiszSSNLLPLgyTOxyWdsDJ7fTArSrP 1fXNN0K2E+o3SQhsiNOrykdkUcsfYCs+PWNcvvmsvDrQxFWIk1G5EJJBwPkUO3PJ5xwPehbXxaWW Z9U0pWyN1utm5TG3n59+7Oec46DpU3l+J/8An50f/wAB5f8A4uqba5qOk67ZWWuNYC1vldYbmHMY WVedjBmPUZxjuMV01FYJ8YaVI2yxF3qLeaYv9CtXkXcM5+fGzAxjr14qhcWeqeLriGK/sW07QoZF le3nYNNeMpyqsqkhI8gMQSSeBgc11tcTotzb6Z498RWVtdwtp8pS7ummkw0N24UeWrE/MCihiP4c gDrgdsDkZHINFFFFFFFFFYHi3W7rQtNtri1Fqvm3KwyTXe/yYQVbDOVGVBYKueg3VLJc+JjE4i0v ShJtOwvqEhUHtnEPSq0Hhqe91CLUPEN8uoSQNut7WOPy7aFsnDBSSXYDADMTjGQBmujooqG7tLa/ tJbS8gjnt5VKSRSKGVh6EGuUQ33gm4jieS5v/Db5CsyvNPp+BkAkAl4uMAnleMkjp1VneW2oWcV3 Zzxz20y7o5Y23Kw9Qanooqvf31tplhPfXcoit4EMkjnsBXP2d3LrPirTtQi06+gtIrC4Uy3MQQEu 0JUAZzyFbt2rqKKKKKKKKKKK+QPjb/yV7Xf+3f8A9ER19AfBL/kkOhf9vH/o+Su/oooooooooooo ornLjXr6/wBYl0vQLeKQ2r7L2+uQfJhbAPlqAQXfBBIBAXPJzxTo/Dt/cyJLq/iC+uCoH7m0P2SL ODk/Id569C3YVo6Zoun6P55srfZJcP5k0ru0kkrerOxLH2yeKj1fX7HRmginMkt1cNtgtbdN8sp7 kKOw6ljgDuaoTap4ivo5o9M0MWhKssdzqU6qFbbw3lpuJGT0JHSrGjeGbXS5lvZ5Zr/Vmj2SX90+ +QgkkhR0Rcn7qgDp6Vt0UVBd2drf2z215bxXEDjDRyoGU/UGsBvC9xplw9z4av8A7BvA8yymQy2r kYwQuQYzgYJU4PGQSKx7M6h4r1S60jxNcyac8KEtpFplFuIt4/eef1kQ8KQu3GSG6iuiuNf0TQiu lwZaeGEslhYQNK6ovGNiA7R0AzgVF/aPiW+z9j0WCxQ9JdRuMtjdj/Vx57c4LDqKavheTULua58Q XrX4Yp5VrCZIbeIKD/BvO8kkkls9AMcVZHhDw2DEf7B00mLfsLWyEjf97kjv3pi+D9FhZmtIJ7Is gQ/Y7qWAEDOOEYDjJ7VXgh8T6KEgVodcs1O1Xlk8m6RecbjgpJjgZ+UnrzViPxDd7cTeG9WjkBIZ VWJxwcZBD8g9aP8AhL9KSCKW6W+s1fAP2qxmjCE9mYrtH54qs/ia71WcW3hmxF0uG8zULoPFbRkE jAOMyHI6Lxjqw4zO2n+JyplGv2gm37hF9g/dbc/dPz7unfNS+Hdal1aC6hvYI7fUbGY291FG+5d2 AQyk4O1gcjI9R2raooqpqn2L+ybz+0vL+weQ/wBp837nl7Tuz7YzWX4J+0Hwbpv2jz8+WfK+0Y8z ydx8rd/teXsz39ea36KKKKK5m98MS2Uz6h4YnFheGRpZbViTa3ROMh06IxwPnXBzknOSKtaV4ljv NQbSr+1k03VlXeLWZgRKvdonHDqO+OR3ArcrH17xDDoX2ONraa4uL2XybeOMqoZ8ZwWYhV49Tz2z Wde6dr3iWNLXUUttL0tnLTwwy+dPMFbKqW2hUBxk43HsCOtdTRRRRRRRRRRRXyB8bf8Akr2u/wDb v/6Ijr6A+CX/ACSHQv8At4/9HyV39FFFFFFFFFFFFYPibVbyyjtNP0pVOq6jJ5VuzoWSJRy8rDuF XtnkkCruh6Pb6DpEGn27O4jyzyyHLzSMcu7HuzMST9a0aK4+6ih1z4jWvkJCP7Ei8y4uUTMhkcEL BvxwuCXIzySvpXYUUUUUUyWWOCF5ZXVI0Us7McBQOSTXDy2N38QW0/UWRtK0qCRpba4ikZb2ZCAP lZceUj85GSSAOnbrdM0fT9GtzBp1pHbozFmK8s5JySzHljz1JNXqKKKKKKKK5TVS2geMLPVwQLLU 9lhdgkjZLyYpPTnlPxWuroorI8U6MfEHhm+0xZBHJNHmJ2PyrIpDIW65XcBkdxkUnhnXk8RaR9rE axTRytBcRK+9UkU8hWHDKeCCOoIrYoooooorL13QrXXrJIJ2eKaGRZre5ix5lvIpyHQkHB7HsQSD wahis/EkUYRtZ0+Ygn55NPYMRnjO2UDP0AqpJ4SOqHPiLUp9UTduFoq+TbDBJHyKctjj7zHpVIpd eCLu2SK5Fx4eurhLdYbiT95Yu5wuxz96PPG1uV7HHFdlRRRRRRRRRRRXyB8bf+Sva7/27/8AoiOv oD4Jf8kh0L/t4/8AR8ld/RRRRRRRRRRRVbUb+DS9NutQumK29tE0shAyQqjJ479KwvDel3U93L4j 1qAR6ldqBBbk7vsUGBiMHA+Y9WI6njoK6aquoajZaVZvd391FbW6feklbA+n19qwJtb1bW4zB4e0 2SKKRWU6jqKNDGvy8FI+Hc5Poo4PNa+haLa6BpEGn2qjEajzJcYaZ/4nb1Ynkk1pUUUUUVyOsA+K fEI8PJk6XY7ZtVYHiRiMx2/vn7zD+7tH8VdaqqiKiKFVRgKBgAelLRRRRRRRRRVHWNKt9b0i5025 LrFOuN8bbWRgcqynsQQCPcVkWep+I9Os0i1fQ5L6WKI77rTpo2EzL38tyhUsOcDODxViHxhorzrb 3Fy9jcM2wRX0TQEnGcAuADwexrbV0f7rq30Oa5rxji+/srQPtUsK6rctFcpDw726xuzgHHygnYpP o2Mgmuit7aC0gSC2hjhhQBUjjUKqgdAAOlS0UUUUUUUVgS+ILuXXL3TNM06K7aySMzyNdiMKz7iF xtPIC559RUFxaeKNTtDFdx6BHE8fz20sUlyrtkfKSdox15we3FP8J+Hr/wAPw3MVzqST20rB4bOK MiO0PO5UZmLFTxweB2xnFdHRRRRRRRRRRXyB8bf+Sva7/wBu/wD6Ijr6A+CX/JIdC/7eP/R8ld/R RRRRRRRRRRWT4i0htb0n7GrJxNFNslGY5NjhtrjBO0kDOKix4p/vaP8A98y/40yS38VXGEF/pdmp BzJFbPK/TjAZgBzzzmlsvCljBfrqN7JNqmoqMLc3pDmP5t37tQAqc/3QDwOTit2iiiikZlRGdiAq jJJ7CuNg/tzxlAL+21SbRdL3s1l9mjBmuAD8kkm8EbDydgHIIya2I9I1cl2uPEt0WZshbe2hRFGB wAysfU8nvWPFDqXgie5lEcmq6LczPczyRxKLq3kbl2YKAJUJ9BuXpggDHV2V7bajYw3tnMk1vOge ORDkMDViiiiiiis/V9SGmWgkA3Su22NdjtuPp8oOPx4qnb+KNPZI453nS4IAdPskuA3cfdpl34ps xan7EZpbqQEQRm1lG5vfKis298UfatRtorS4njthMvmMtlNucHGAMqOM5zzxx15rsaiuLaC8gaC5 gjnhcYaOVAyn6g1lS+EfD8siSDSbaGRAVD26+ScHGQSmMjgdfSsfwnptlB4n8QS2/mzLbSR2sM88 jytGoQM8Su5JwGPIB612VFFFFFFFFc74qvbsnT9F024e3vdTlKGeNctBAozI4yMA4woJ6Fge1amk aPYaFYLZafAIoQSzHJZnY9WZjyzHuTyavUUUUUUUUUUUUV8gfG3/AJK9rv8A27/+iI6+gPgl/wAk h0L/ALeP/R8ld/RRRRRRRRRRRRRRRRRRRRWF4wnuU8N3FtYsRfXxWztyHKlXkO3cCAT8oLOcDopr XtLWGxsoLO2TZBBGsUa5JwqjAGT7CpqK5OXTdR8LXtxfaJbve6VOWluNLVwrxyFgS8GRg5G4lCQC cYxk1v6Vq1nrNn9qsndowxRg8bIyOOqsrAEEelXaKKytW8SaPobpHqN9HDI67hHgs+3BO7aoJC/K eenFXLLUbLUoTNY3cF1EGKl4ZA4B9DjvVmmS+Z5L+SVEu07C4yAe2faqGgprMekRLr89pNqILeY9 mrLGRnjAPPStBkRypZFYodykjO04xkenBP506iiiuShuJfC+v6lHdW93JpV/MLqC4hhaYQyMD5iO FXcBlcg8j5sZrodN1XT9YtBdadeQ3UJ/iibODjOCOoPI4PNXKKKKKKKq6ne/2bpd3ffZ5rj7PE0v kwrl5MDO1R3Jrn/CNoNQQeKLy8hvdQvY9qNA4eK2izkRR8Dp/ETySD6AV1VFFFFFFFFFFFFFfIHx t/5K9rv/AG7/APoiOvoD4Jf8kh0L/t4/9HyV39FFFFFFFFFFFFFFFFFFFFcxcvFqXxFsYEjWQaTZ yTSuWBEckxVUwP721ZPoG966eiiisK68KWc13cXVrd6hp0tzuNwbK5KCUkAbipyA2B94AH3pG8J2 ayme2v8AVracsC0qahK5bAIAIcspHPpVa0vPEWjMbTU7GXWIFOIdQs9iyMvYSxEjDDpleD6L0q0d e1CSVUtvDeosNpLPM8USjpgcsSScn8qb4e0u+iu77WNX2jUb5gohSTelvAudkYPQnkknHJY0y60W /s/ED6zob2oN0gS+tLgsqTFQdsisoO1x0PBBH0q3oGujWobiOa1ez1Czk8m7tHcMYnxkEEfeUg5D d/Ygiteiiq0Go2N1IY7e8t5nAyVjlVjj6A1mXPirTotSbTrVZ9RvUJEsNknmGHGM7zkKp5HBOfam Ta/qThY7Dw3fyTMcZuXjhjUerNuY/kCaijg8YwNFcveaVds2/wA6zMbRIo/h2S8kkdDuXnPap4tQ 8SzsANBtLYBAWNxqGct3A2I3A9Tj6ViapoPiWTVV1rSY9K07UUQ+aUmklW9AHyxyLtQdf4+Svb0r o9A1231+wM8SNDcRO0N1ayEeZbyqcMjAE+nB6EYI4NatZl14i0WywLnVrKMltgVp1yW5OMZzng/l VdPFujSu62889z5eNzW1pNMozz95FI/WtDTdTstYsI77TrmO4tpB8siH8we4I7g8irdY+ueIrbRj DbLHJealc5+y2EHMspHU+iqO7HAH6VEp8VzsGK6PZLsHykyXDbu/PyAAcetYdhDdeDfEca398k9h rT/vJRB5UcN5wBgDIUSe5+8O5NdzRRRRRRRRRRRRRXyB8bf+Sva7/wBu/wD6Ijr6A+CX/JIdC/7e P/R8ld/RRRRRRRRRRRRRRRRRRRRXM+DTHcLrV+jmU3OqTYmLEh0QhFxnsAMDHHFdNRRRRRRRRRWB q/h+4n1H+2NHvvsOqiHySXjDxTqDkLIvXg5wQQRk/SoT4putMjDeIdFuLKMIDJd25+0wKcHdkqNy gY6lccjmqour3xXrV7Fpmsmy0mwCRieyMcj3M7IHzuIYBFVl4xkknJwObsvhX+0Ly3l1rUptTgtw xS1kjRIizADcyqBuIGQM8DcauSeGNBljiR9GsCsQ2xgW6jYOmBgcDgVesrC0022FtY20NtACSI4U CrknJOB3JqxRRRWbeeHtG1C6a6u9LtJrhlCtK8QLMB0BPfFQf8Il4e/6A1l/36FXbPSNN08ILPT7 W38sYTyoVXaPbAq5WBf+FLeW6nv9Lu7jSdSmO557VvkkfsZIj8j++Rn3qhH4p1e0WTTtQ8P3M2to B5S2ak21yCceYJTxGucbg3K9t3BOj4d0KXTmu9R1F4Z9Zv333M0a/KqjhYkJ52KOB6nJ6mt2qeq6 Za61pVzpt7HvtrhCjgcEehB7EHBB7EA1R8J3V3d+G7dr6YT3MLy20kwXb5pikaPeR2J2ZPuTW1RR RRRRRRRRRRXyB8bf+Sva7/27/wDoiOvoD4Jf8kh0L/t4/wDR8ld/RRRRRRRRRRRRRRRRRRRWX4k1 FtI8NajfoCXggZkAIB3YwOT74p3h/TDo3h+x09jueCELI24tufqxyfViTWlRRRRRRRRRRR1GD0rl PCNsulav4k0po2ST7eb5T82x4puVKg8DBV1IHdSe9dXRRRR3xTI5Y5QxjcNtYqcHoR1FRx3kMt3N bKW82EAuCOmelT0UUUUUUUVy3hu7fS9Uu/DV+iRziSa8s5VY7bmKSVnOMjhkLYI57Hvx1NFFFFFF FFFFFFfIHxt/5K9rv/bv/wCiI6+gPgl/ySHQv+3j/wBHyV39FFFFFFFFFFFFFFFFFFFcbZWR8Wa1 fXGszeZa6ZfPBBpYUrGrIQVllz/rGIKso+6AQcE812VFZOranfafcwGHTZbixwWuJoyGZPQBM5P+ FQDxPAzaZtgYLfSOvzuA0YAJ3MPQ4H0zTn8TW63U8MdlfXKxPt821gMqE4BxuXuM4Iom8Rqm5V0r WGbsVsmNR6JrVzcSQ2F1aagbgIxe5ntRCrAY+bGTjOelb9FFFFFczrsNxpviHT/ENpaz3KCNrO/i t03u0J+ZHC5GSjjsCcO1aml+INK1oMLC9jlkT78J+WWP/eQ4ZfxFaVFFcfcX91qeuX+iWF7YR6ha 4lMyzkzRoTlVKbMY5weT1zita30K6tomWLW72Mv8zhViYbzjLAshPOPpTtO8Px2GrXGpve3F1d3E SxO8qxr8oORwirWxRRRRRRRRWVruhQa5axI0sltdW8gmtbuIDfBIOhGeCOxB4I4rK07xdHaK2n+K Xi0zVbePdI0jBYblR/y0hY8EHuv3lzgjoTcj8W2NxuNpaandRjA82Gxk2HIB4JAzwR0qhf8AxB0/ Sju1CwvrWIZJaXyw+0A/P5W/zNvGM7a6i2nS6tYbiMOElRZFEiFWAIyMg8g+xqWiiiiiiiivkD42 /wDJXtd/7d//AERHX0B8Ev8AkkOhf9vH/o+Su/ooooooooooooooooooorndU0C7TVG1rQLpbbUn Ci4gmJNveKBgBwOVYDgOvI6EEcVb0HXU1qCdZLd7S/tZPKurSQ5aJuo5wNykYII4INa9VNUs5NR0 u5s4byazkmjKLcQY3xk9xnvUWn6TFZ2ltHO32y6igELXk6KZZR33HHf0q5BBDbQrDbxRxRL91I1C qPoBUlFFFFFFFUNY1i10Ow+2XYmMfmJEFhiaR2Z2CqAq5J5PauabT7nxhrlnqUtl/Z2m6fOssEss W28umUnHUZii68H5mB7A89pRRUa28CTvOsMazOAHkCgMwHTJ6mpKKKKKKKKKKKKQqG6gH6ihmCqW YgKBkk9AK4/wetvda34g1SxtgdNvLhHt7plwZmC4kK5GSm4cHOM5x612NFFFFFFFFFfIHxt/5K9r v/bv/wCiI6+gPgl/ySHQv+3j/wBHyV39FFFFFFFFFFFFFFFFFFFFc5rekX8eqR6/oQhOoxxeTcWs xKpexZyFLfwupztbB6kHg8aOia3ba7ZNPAksMsTmKe3nXbJBIOqsPX3GQRyDWlRR0qOGeG5jEkEq SxngMjBh+YqSiiiiiis/W9Ig13SJ9PuCyrIMpIhw0bg5V1PYggEfSsvw54ha4KaPrJFvr0KsJInU oLgKcebHnhlPXjOM810lFFFFU9S1Wy0e1FzfziKJnWNflLFnY4CqoBJJ9AK5PUNf8SLp02viCHTN MgeMR2d5Fme4RnCl5DkeVwcheT/ex0ruOvSiiiiiiiiiuPu5JPGmqS6ZbPJH4fs3KX86MyG8kGQY EIx8gON7A8/dHeuthhjt4I4YUWOKNQiIowFUDAAHpT6KKKKKKKKK+QPjb/yV7Xf+3f8A9ER19AfB L/kkOhf9vH/o+Su/ooooooooooooooooooooork5Wn0Px6hjijuLfXgFZUBEkDQocuezIQQCeCCR 17dZRXJeI7g+IdSj8J2M37uRfN1aaM8w24OPLyOjyEFfUKHPpU174Rjtplv/AAy8OkajGMbEjxbX C/3JYxgEejDDD1PQ2PD2v3er32p2lxYxRiwlELXME3mRSPgEquVByueeODW/RRRRRRWdrOh2GvWi wX0RJjYSQzRsUlhcdHRxyrD1H8qx7638SaFafbbHUH1mK33NLZXMSLLLH1wjoB847AjDdOOtdFY3 kGo2Fve2zF7e4iWWNiCMqwyDg9ODU9FFcvd51fx/aWpLG10iD7VIAGwZ3yqAnOOF3EdetdJPBDdQ SQXESSwyKVeORQysD1BB6iubXw9qmhKn/COaiWtUPGm6gxeILz8qSYLp1GM7gMAYqRPGFvZy+R4g s5tGm2F/MnIeBwDg7ZV444OG2nB6Vs22q6deSmK1v7WeQDdtimVjj1wDXP3+u3Ot3/8AY3hi6TI/ 4/dTRRJHarjIVT91pTngchepHQVKYvEmhThoZH1/TyDujlKR3URyTlWwEkGDjB2ngcmrv9u3H/Qv av8A98w//HKn0jW7bWVnEMdxDNbsEnguYTHJGxGQCD1yCDkEitKiuc8T3l5LcWGhaZLNDd37lpZ4 hzBbLjzHBIIB5Cj3YVsaZptppGnQWFjEIraBdqLnP4knkk9Sat0UUUUUUUUUV8gfG3/kr2u/9u// AKIjr6A+CX/JIdC/7eP/AEfJXf0UUUUUUUUUUUUUUUUUUUUVl61oVtrcUHmSzW9zbOZLe6t2CyQs VK5BIPY8ggg8ZFUom8WWO2OaPTdVjHy+cjtbSHgclcMuc56EdRxTZ/8AhLNRikiiXT9JR2CibzGu JUXAywG0Lu64zkd+elaej6LZ6HY/ZbNWOWLySyNuklcnLO7Hkkkk1S8WaxcaRpMX2NEN5e3MdnA8 ufKieQ4DuR0Uc/U4HermhaRDoOiWmmwsXECYeQjmVzyznk8sxJPPetGiiiiiiisrW/EGnaFADdyl p5PlgtIhvmnY9FRBySfyHcgVD4Q0250nwnp1ldjbcJHueMHIhLEt5Y5PypnaOTwoq9q2rWmiaZNq F9IUgiHOBlmJ4CqO5J4ArOh1XX54Ul/4RsRbxkJLfKHX2ICkA/iaWS/8SMoWHQ7RHJA3S3/yqM8k 4TJ4zxT/AA/o9xpzX95fzRTahfz+bM0QYIigYRF3EnAH05J4raopGUMpVgCpGCCMgis+50DRrzb9 p0qxl2Z2l7dTjPXHFXLa2t7O3S3tYI4IUGEjiQKqj0AHAqWiuR8P3UOm+KNa0u/zDqN5dtdW7yMc XUOBt2E8EoBtKjpjPTmt6bXtHt5mhm1awjlQ4ZHuUBU+4JqifGWhMQtvdveMXMaraQPNuYEg42gg 4weenFc7PrF1ZeMo/ENzpN1DoksK6e9zd/I8DGRsOse7IRjs3FgDwh6A16BRRRRRRRRRRRXyB8bf +Sva7/27/wDoiOvoD4Jf8kh0L/t4/wDR8ld/RRRRRRRRRRRRRRRRRRRRRRRRRVa/0+01Swmsb63j uLWZdskUgyGH+e/aue0Wa60PxA3hu8u5bq1kg8/Tp5yWk2qcPEzfxFcggnnB5z1rqqKKKKKxtQ8U 6Vp93JZGWW5vowpa1tIWmkG77uQo+XPXkjjnpVX7X4m1SeNbWwi0e0xl5r4rNM3y8BY0bA5PJLdu nNZ7eC7vTZRrGj6nJL4g24uJ747o70ddjgf6sD+Epjb6NVyLxJrlwo8nwffB40/frNcRR4fkbUJO HHH3sgYI78UtnoWo6lqltq3iSaBpLbD2mn2wzDbuVwXZiMyPyQDwAOgzzXTUUUUUUUVDdXKWls88 mSqDJAIB/Wsoa7FcRaZLDcRxG5YFomAdtnT1G3krzz16Ut9b6F4n042up29tcwCTmG42kq6nqOeD 7g9DSSPoOj2MxtrawUIHcQW6IC7BdxAA74FbMe3yl2AKpGQAOlR3Vrb3trLa3UKTW8qlJI5FyrA9 QRXPeEZnsn1Dw3cyu82lygQNI25ntn5ibOBnAyhPPKGunoooooooooor5A+Nv/JXtd/7d/8A0RHX 0B8Ev+SQ6F/28f8Ao+Su/oooooooooooooooooooooooooorm/Eu621zw1fpKqkXrWrKw4ZZY2z9 CNgx9a6SiiikJCgkkADkk1yAvdQ8bZXTZJtO8PE4a+GVnvR6Q90jP988n+EY+auj0zSbDRrU2+nW sdvEzF2Cjl2PVmJ5Y+55q7RRRRUfnx/aPs+8ebt37fUZxmpKiiuYZjhJAW5+U8Hg4PB561IWA6kD HvS5z0oorJ8SNJHoc8sOiprM0eGjsmKjec+rcDHWnWuj6fIq3kmk20FzPGpmTy1JB6kEgcnPf2pR 4c0MEEaNp2R0P2VP8Kki0PSLd98Ol2UT4K7o7dFOD2yBV8AAYHAorlvE7f2PrOleJSmbe332d8yx glYJSuHz1wsipnrgMxrqaKKKKKKKKKK+QPjb/wAle13/ALd//REdfQHwS/5JDoX/AG8f+j5K7+ii iiiiiiiiiiiiiiiiiiiiiiiiue8bwtJ4Su5Ug897VorvYMbiIpFkbbn+LarYrctbmG9tIbq3kWSC aNZI3U5DKRkEH6GpaKK57xyC3hC8i3MqzPDC+1ipKPKisMj1UkfjW9DDHbwpDCixxRqFRFGAoHAA FPooooormPFTaTpSR6pqJ1hi8qwKLGac7S3H3UYADgZrSj8P2sZ3C61M/wC9qM5/m9Uj4L0r+0Y7 7demeM71Zr2Ytu9c7unt0NLqHhy51eWR73UmVcBI1tQ0XyZyd5DZYnj2HYVsWFmlhZR2yO7hM/M7 FmYk5ySSSas0UUUUUUVBfWVvqNjPZXcYkt54zHIh6MpGDWB4Pvpkt59A1B2bUtKIiZnbJmhOfKkB wM5Xgn1U101FFFFFFFFFfIHxt/5K9rv/AG7/APoiOvoD4Jf8kh0L/t4/9HyV39FFFFFFFFFFFFFF FFFFFFFFFFFFFcho8kPhXXbnQZ4Wt9PvZ/O0pwWMQLKN8AzwhDKzBehDnHTFdfRRWZ4i01dX8Oah YtIsRlhbZKzFRG45R8jkbWAP4UeHdRbV/Demai6hWubaOUgNuwSoPXvWnRRRRRRRRRRRRRRRRRRR XOeJdKvDPb6/oyK+rWCMPJY4F3CeWhJ7HIBU9mHoTWrpGrWmuabFf2TMYnyCrqVdGBwysp5DAggj 2q9RRRRRRRRXyB8bf+Sva7/27/8AoiOvoD4Jf8kh0L/t4/8AR8ld/RRRRRRRRRRRRRRRRRRRRRRR RRRRVHWNItNc0yawvULRSDhlOGjYdHU9mB5BrCtNe1LQtOSHxNp90xt8o+p2qCaGRAuRKyr86Z7g rgHvjmuks7211C1S5srmG4gf7skThlP4ip65PxBv8Ra1D4ZiM4sVXztWdMqDEQdkO7I++c5A7Dtm uqjjSKNY41CIgCqqjAAHQCnUUUUUUUUUUUUUUUUUUUUVyV3G3hfxTBe27oNN1q5EN1A5wI7gqdsq /wC9t2sO52mutoooooooor5A+Nv/ACV7Xf8At3/9ER19AfBL/kkOhf8Abx/6Pkrv6KKKKKKKKKKK KKKKKKKKKKKKKKKKKK5+68KQi8nv9HvbjSL2Y7pGtgDFK2CAXiYFWPPUYJwOaZpev3EOrvoeveRD qBO60mjDJFep1ym7o6/xLknuOKb4V2XWpeItSDvIZdQNukjZ2mOJFUBfYOZBkd810tFFFFFFFFFF FFFFFFFFFFFZniHSRrmg3eniQxSSpmGUZ/dyqQyPx6MFP4VH4a1eTWdGWe4SKO7ilktrmOKTeqSx uUbBwDg4yMgHBFa9FFFFFFFfIHxt/wCSva7/ANu//oiOvoD4Jf8AJIdC/wC3j/0fJXf0UUUUUUUU UUUUUUUUUUUUUUUUUUUUUVR1fR7HXNOksb+BZYW5HJDIw6MrDlWHUEYIrF8AzRJ4Yi0vMYvNMd7W 6jXcG3qx+dg3OXHz5PXd1NdRRRRRRRRRRVW/1Kx0q2NxqF5Bawj+OZwoPsM9T7Vj23iLUNUZZNK0 GZ7QruFzfS/ZlfoRtXazkHJ5KjpRD4sit7pLPXbOXSLmRwkTTMHglJzgJKPlzx0baeRxToPFB1Ca 4Gk6Te39tBIYjdI0ccbuCQwQuwLAEEEgYz3NPsvFVlc3sNjdW95p17MuY4L2EpvOCSFYZViMHIBr dooooooormbKN9O8f39tG2bbUrQXrISfklQrGxHb5lKf98e9dNRRRRRRRXyB8bf+Sva7/wBu/wD6 Ijr6A+CX/JIdC/7eP/R8ld/RRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRXMXcRsfiJp11EExqNpLbzD BBJjw6t6HqRz6109FFFFFFFQXrXKWFy9lGkt2sTGCORtqs+DtBPYE45rlfD82peJ4JL2fXprV43a GXT7SCONraRcBlkLbyWBBwcgEEEcYNa+n+FNJ0+5W7ML3l+P+Xy9kM03bozfd+6OFwOK2qjnghuo WhuIo5om+8kihlP1BogghtoVhgiSKJeFSNQqj6AVDqGmWOq2xt9QtILqHOdkyBgD6jPQ+9YVx4bu dKuob7wzJ5Lq5NxYT3D/AGe4Qrg4HzbHGFIYDsQetTtr2sReUsvhW+LyAD9zcQuqtkDk7hgck5x2 oafxXfBhBZ6dpafMA9zK1xJ0GDsTavXP8R6VXtdY12wF1aajpF3qNxFOVguLSJI454yAVY7nwpGS D/u571cGo+IJpgkWgQwptJZ7q+VeeMABFfPfrjpSvf8AiGCVRJoVvPGwOWtb8EqeMZDonB56HtVe 61jxFZaZLqEvh+3dIlMj28N8Xn2A87R5e1mxzjdz0zW5ZXlvqNjBe2cyzW08YkikXoykZBrBtpDf fEW8eMp5enaetvIQ2SZJXD4xjAwqAnnPziulooooooor5A+Nv/JXtd/7d/8A0RHX0B8Ev+SQ6F/2 8f8Ao+Su/ooooooooooooooooooooooooooooooorC8Q6ZqFxc6dqelNA15YO7CCdiqTI64ZdwBK ngYOKaPEd3FAXvPDerRspIcQrHMBzjI2tlh34GfatDTNZsdYFz9ildmtpfJmR4mjaN8BsEMAc4YH 8av0UUUUUVh6r4Yhvr06nY3U2mat5ez7Xb4+cDoJEPEgHoeR2IpvhTWLvWtOupLyKIPbXk1qs8PE dwI3K+YoySAcYwT1B7YreoooooooooornD4J0gSz+U17BaTlmksre7eKAswwzbVIxnuAcd8Zqvpu nW+h+OXstNDQWd3YNcy2ytmPzVdEDgH7pKnBx1wPSurooooooor5A+Nv/JXtd/7d/wD0RHX0B8Ev +SQ6F/28f+j5K7+iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiud8WahdJDa6Npkgj1PVHMMUmQDCgG ZJPwXOPcitXSdJstE06KxsIVihjHbqx7sx7sTySetXaKKKKKyvEOsNoumrLDbG6u55Vt7W3B2+bK 3QFsHaAAST2ANZPh/wAC6ZpuhWtpqVlY3t5Gp8ycwA5JJIGTkkAEKCeSBk810tra29lbR21pBFBB GNqRRIFVR6ADgVNRRRRRRRRRRRXN3zPa/EDSZSm6K7sp7UENyrgrJyPTCkfWukooooooor5A+Nv/ ACV7Xf8At3/9ER19AfBL/kkOhf8Abx/6Pkrv6KKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKgvLy206z mvLyeOC2hUvJLI2FUDuTXO+Hln1rXbvxNcW80Fs0ItdNjnBVzDnc8pQ/d3ttwDzhAeM4rqaKKKKK Kzde0W21/RrjTrkAeYp8uUDLQyfwyL6Mp5BrM0XxDMl6dC8QfZ7XV4lUxur4ivUPAeLPOeOU5IPc gg10tFFFFFFFFFFFFcz4u2W9zoF+ZTFJDqccYk3YG2QFWB7YIwK6aiiiiiiivkD42/8AJXtd/wC3 f/0RHX0B8Ev+SQ6F/wBvH/o+Su/ooooooooooooooooooooooooooooooork9YC+IPF1loed9lYK L6+UHhnz+5RuPUF8Z/hFdZRRRRRRRWZrusjRbKOVbWW7uZ5RBbW8WAZZGBIGTwo4JJPQCsmHwtc6 uIbnxXeG8lSUTpYwHZawMCCuBgNIVx95jzk8DpXU0UUUUUUUUUUUVR1jS4Na0e7025/1VzGUJxyp 7MPcHBHuKpeEtQuNR8OwNeAC9t2e1ugCCPNjYoxGCeCVz+NbdFFFFFFfIHxt/wCSva7/ANu//oiO voD4Jf8AJIdC/wC3j/0fJXf0UUUUUUUUUUUUUUUUUUUUUUUUUUUUUVQ1rVYND0W81S55itojIVBA Lnsoz3JwB7kVR8K6Tc6bpss+oFG1S/lN1elANquwACKe6qoCg98Z71u0UUUUVWvtQs9MtvtF9dQ2 0O4L5kzhRk8AZPc+lZ//AAlnh7/oNWP/AH+WsmfUD4q1fS00m3lksLG7F1PfyKY4m2q6hI8jLnJ6 j5RjrzXX0UUUUUUUUUUUUUVy+lg2PxB1yyhglFtdWtvfu4CiNJiXjb3yyxqe4+Vjxmuooooooor5 A+Nv/JXtd/7d/wD0RHX0B8Ev+SQ6F/28f+j5K7+iiiiiiiiiiiiiiiiiiiiiiiiiiiiiisLxNpV/ qsenLZvbmO3vEuZoJndBMEBKjcucYfa2CDnaKhfxJf6cM61oN1BCN265sm+1RqATyQoDgYGfu1r6 dqun6vAZ9PvILqMHBMThtpyRg+hyDwfSrlFQ3d3b2FpLd3c8cFvCpeSWVgqoB3JPSsFPE17qS7tD 0K6uYWAKXV2fssTA4II3DeRg5zt7VJPf+KYhLGmh2M0hQeVIl+dgY5++GQNgcHgHOabp/hhv7Ri1 bXbw6nqcS4hJQJBakj5vKj7E/wB45bHGQOK6KiiiiiiiiiiiiiiisjxBr8GhWqHyzc31w3l2llGf 3k7+g9AOpboBUXhvQ5tLhuLzUZxc6xfssl7OowuQMKicDCKOAPck8k1uUUUUUUV8gfG3/kr2u/8A bv8A+iI6+gPgl/ySHQv+3j/0fJXf0UUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUVj6j4X0nUrj7W9sY L0dLy1cwzDr/ABrgnqeDkc1Sa08S6PKXsbtNZsyOba9YRzod2fklVcMME8MOw+aprPxfpdxBcm6a TT7mzg8+6tbxDHJEgGS2OjLwfmXI96z9I0g+JLo+INfsyUcqdOsLn5hbxcEOyZI8xjgnPK4A9a6+ iiiiiiiiiiiiiiiori5t7OBp7meKCJcZklcKozwOTWFJ4ysJiY9GgudZn5wtlHmPPP3pWwgGVI6/ hShPFl+Dvm03SYz2jVrqUfN6naoO32bk1Z0fw1Y6PKboNNd6i6bJb67cyTOMk4z0UZP3VAHTjiti iiiiiiivkD42/wDJXtd/7d//AERHX0B8Ev8AkkOhf9vH/o+Su/oooooooooooooooooooooooooo oooooooorN1nw9pHiG3EGrafBdoOF8xfmXkHhuo6Doe1Ykh1rwiFkMl1reiIuJAw33lsP7wIGZlx 1H3+M/NXSWGoWeq2MV7YXMVzbTLujlibcrCrNFFFFFFFFFFFFFZmua5b6FZLPKkk00sght7aLBkn kPRVB/n0A5NZVj4cutTvotX8UNFPcxnda6eh3W9mfXn/AFkn+2en8IHfp1UIoVQAo4AAwBS0UUUU UUUUV8gfG3/kr2u/9u//AKIjr6A+CX/JIdC/7eP/AEfJXf0UUUUUUUUUUUUUUUUUUUUUUUUUUUUU UUUUUUVz194Ui+1yajolydI1N1IaSCNTFOc5/exnhuSeRhuTzUMXiqTS7l7PxRAmnvn9zfR7jaTq TgfOf9W3qr/UEiulR0ljWSN1dGAZWU5BB6EGnUUUUUUUUUUUVzPi/SpJYrfXtPCjVtJ3y25bbtdC MSRtuwACvfIwQOa19G1e017SbfU7EyG3nXcnmIVb8Qf/ANXpV+iiiiiiiiiivkD42/8AJXtd/wC3 f/0RHX0B8Ev+SQ6F/wBvH/o+Su/ooooooooooooooooooooooooooooooooooooopGVXRkdQysMF SMgiucXwkNOmaXw/qM2kq5Be1VBLbHAIyI2+4eR90rnaKQ6xr+kL/wATfSPt0Cjm70rLHGDy0LfM On8JbrWhY+JNG1G4e3t9Qi+0o21oJcxSg/7jgN39K1aKKKKKKKzdS8Q6Po7FdQ1K2t5Ahk8t5BvK juF6n8BVV/FVmWRLaz1S6ds8RWEq4HqS4UD86zbq01Hxfd28N9pz2GgwyebLDcsplvGUnapQZCx5 AY5OTwMDmutVQqhVACgYAAwAKWiiiiiiiiiivkD42/8AJXtd/wC3f/0RHX0B8Ev+SQ6F/wBvH/o+ Su/ooooooooooooooooooooooooooooooooooooooooqnqGk6dqsfl6hY290o6CaMNjnPGenIBrF 8IMtqNV0X7YZ102+aK3WR90iQlEdVJJJIUuVBPYCumoooooorl/C6xf294meRW+3/bgHZwd3k7F8 oDP8P3sY966iiiiiiiiiiuV8XfELQfBE9lFrUk6G7DGMxRbwApAOfzFdLa3UF7aRXVrKk0Eyh45E OQynoRWPD4t0u48ZXHhVGm/tO3txcODH8mz5ejevzCt2vkD42/8AJXtd/wC3f/0RHX0B8Ev+SQ6F /wBvH/o+Su/ooooooooooooooooooooooooooooooooooooooooorJ1Tw3pmrTpdTRPDexgiO7tp DFMuccblwSOBwcj2rJk1DWvCmw6s51bRgMPfxxYuLbk4MqLw64xllAIwSVxyOot7iG7t47i2mSaC VQySRsGVgehBHWpKKKKy9c1+y0C0SW6LvNK3l21tEu+W4k7Iijkn9B1OBVXw1puoW/2vVNXeMajq Ox5YIh8luFXCxg/xEA8t3PTAreooooooooorx34r2NrqfxM8A2N7Ck1tcSzRyxuOGUlMijRb27+E fidfDeryvL4U1CQnTb1zn7M5P+rY+n/6/XFjSyD+01rJByDoy4P/AH6r1qvkD42/8le13/t3/wDR EdfQHwS/5JDoX/bx/wCj5K7+iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiuRutMu/Cl 82p6BaS3GmSlmvtKhYZUkg+bAp4DddyAgNnI5HPQaVrOna3aC6027juIv4tp+ZD6MvVT7EA1eqrq Go2WlWbXd/cx29upAMkjYGTwB7k+lYB1XXvEAA0S0Om2LD/kIX8f7xvmx+7h69ASC+Oo4PNaGleG bDS7pr4tNeak6lXvbt98pBOSo7IvsoA4FbNFFFFFFFFFFedeOPDerat8RvBWqWVoZbPTpna6kDAe WCVxwTk9D0rsPEfh7T/FOh3Gk6nEJLeYde6N2ZT2Iry34ceBPFXhv4nXl5rW66sY7BrS3vjID5ih k2DGcj5V7+lez18gfG3/AJK9rv8A27/+iI6+gPgl/wAkh0L/ALeP/R8ld/RRRRRRRRRRRRRRRRRR RRRRRRRRRRRRRRRRRRRRRRRRRRWBrPhr7XdDVdKuP7O1pFwtyi5SZf7kyfxr+o6giqa634ouoRZQ +HVtdSAKzXNzNm0Q8YZCvzSA5yFwp4wSKuWnhhTqUWp6xfS6pfQ58gyIEhtySeY4xwGwQNxJbA69 a36KKKKKKKKKKKKK5JvHNovxOTwd8vmNZGfzM8+b1Cf98Zautor5A+Nv/JXtd/7d/wD0RHX0B8Ev +SQ6F/28f+j5K7+iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiio bq5isrOa6nbbDDG0jt6KBk18u6Hf3WvX/inx3Dk6hpV9b6hGM/8ALHc4dPps7e1fUNleQ6hYW97b tuhuI1lQ+qkZFT18gfG3/kr2u/8Abv8A+iI6+gPgl/ySHQv+3j/0fJT/AIp+PrrwBoVpe2dlDdTX Nx5IEzEKo2kk4HJ6eteTf8NJeIP+gJpn5yf/ABVa/hn45eJvE+v22kQafoVpJOGxNdPIsa7VLckH vjH1r0D+2fGv/QQ8D/8AgTNXDeLfjR4o8IayNMuLPw/euYll82zklZMEkYyT14rB/wCGkvEH/QE0 z85P/iq7bwd8SPFvjPSpr+2/4RWxSKYwmO8mlVyQoOQAenzfoa331vxqiM32/wAEHaCcfaZq8q/4 aS8Qf9ATTPzk/wDiqP8AhpLxB/0BNM/OT/4qj/hpLxB/0BNM/OT/AOKo/wCGkvEH/QE0z85P/iqP +GkvEH/QE0z85P8A4qj/AIaS8Qf9ATTPzk/+Ko/4aS8Qf9ATTPzk/wDiq6Pwd8YvFPjPU57G2tfD ti0MJmMl7JKqsNwGBg9ef0rtP7Z8a/8AQQ8D/wDgTNR/bPjX/oIeB/8AwJmo/tnxr/0EPA//AIEz Uf2z41/6CHgf/wACZqP7Z8a/9BDwP/4EzUf2z41/6CHgf/wJmqtqPibxnpumXd8934LlS2heZo47 iYswVScD3OK8x/4aS8Qf9ATTPzk/+Ko/4aS8Qf8AQE0z85P/AIqj/hpLxB/0BNM/OT/4qj/hpLxB /wBATTPzk/8AiqP+GkvEH/QE0z85P/iqP+GkvEH/AEBNM/OT/wCKo/4aS8Qf9ATTPzk/+KruPA/x b1TxdoWv3Mum28FzpqxPH5BJEgckYwx6/L1z39q6k+Kb5BCbjy4LuW++zSWOBm3HlSOMsfv52A5G B6dDRbeOnZY/NtInyfKISb97vEXmFzHj5Y+2c+nFSQ+M7s3YhuNKiTDWxkMd1uKpPu2EDaMsCpyP yJqpD48vdQtJJLXTIrfDoUkuLhSoQyBDvxkq3OemPenRfEOWc3Bj0VwqqxiMlwqkkSKmGXkrktno eK0rDxXLceJn0a5sooWUsnmR3HmZYKGPAXgc98HjpXT0UUUUUUUUUUUUUUUUUUUUUUV5h8dfEn9h +AJLKJ9tzqb/AGdcf3Orn8uPxrhv2craK9TxTazqGimhhjcHuD5gNekfCm7lttI1Dwtdtm70G7a2 GephJzGfpjj8K9Ar5A+Nv/JXtd/7d/8A0RHX0B8Ev+SQ6F/28f8Ao+StPxdLa3Ey2d3odhqkNtbt eyC8AIRQdvyAqctgn06e9WIvA/g+WFJF8L6PtdQwzZR9D+FPPgLweRg+F9GP/blH/hVTUPCHgTSr GW9vfDehxQRDLM1lEOpwB06kkCuctrLwxqGnxzad4J8OtMTOzxukRVViOPvKhG48cdOetdRaeC/B 13ZwXK+FtHVZUDgGyj4yM+lSnwD4PPXwtox/7cY/8KwPEegeFNFe2S38E6LctIskj4sVJVUxnhUY 856nAHc8iq1vZeErnUYgng7Qjp8t9/Z6zLboXMvl+ZnGzBTHGc11P/CB+EP+hX0f/wAAo/8ACj/h A/CH/Qr6P/4BR/4Uf8IH4Q/6FfR//AKP/Cj/AIQPwh/0K+j/APgFH/hR/wAIH4Q/6FfR/wDwCj/w rO1vwr4V0nS5LyLwZpFyUxlBaxIAM4JJIrHurHwbFrstj/wh2i+RbSrDPLJYgfO0YcBTsK5wwGCw JPSrWieHPDGo3n2e78FaBD5lql3C0Vsj5RiRhsoMMMD1HNb3/CAeDv8AoVdF/wDAGP8Awo/4QDwd /wBCrov/AIAx/wCFH/CAeDv+hV0X/wAAY/8ACj/hAPB3/Qq6L/4Ax/4Uh8AeDsceFNFJ/wCvGP8A wrm5NI8JadcXS6t4N8PQQxIrJJFDGwMhOBESyKA569cY9KqrbeGLiyhurXwT4fdRaNeXI2RnYqtt KqVQhm6nsOK66PwN4PkjSRfC+j4YBhmyj7/hTv8AhA/CH/Qr6P8A+AUf+FH/AAgfhD/oV9H/APAK P/Cj/hA/CH/Qr6P/AOAUf+FH/CB+EP8AoV9H/wDAKP8AwrF13w74X0VoZm8G6G1gWVZpmtVBTJxn hCAB1JYgdqmiFt4XuryOx8L6XbRyRbibLCnIYBBNhABksSMZxg10GlXUl+blb20giu7aXy38tt6n jIIJAPQ+laAtoBKZRDH5hXYW2DO30z6U7yo858tM8c7R26flTfstuBIPs8WJTmT5B859/WgW8Ad3 EMYaTG8hBlsdM+tKIIhMZhEglIwX2jcR6ZqSiiiiiiiiiiiiiiiiiiiiiiivlH47+JP7b8fyWMUm 620tPs4A6eYeXP54H/Aa6v8AZo/4+PEf+5B/N67nW2/4RT4yaRq2Slj4hhOn3J7CdeYyfrwPzr0q vkD42/8AJXtd/wC3f/0RHX0B8Ev+SQ6F/wBvH/o+Suvv9E07VJopry2EkkQKq25lO0kEqcEZGQOD xxWgAAMAYAoprxpIhSRFdT1DDINZc3hnRp4FgawjWNXeQLGSnL/e+6Rwe46VqoixoqIoVVGAB0Ap apX+k2WpmM3cHmGMnaQ7KRnqMgjIPcHg1FHoGlxaiL+OzRLheVKkhQcbchc7QccZxnFaVFFFFRXF tDd27wXEYkicYZT0NVpdG0+e9S8ktUadcEEk4JHQlehI7EjIpunaJp2kvI9lbCN5AFZi7McAkgDc TgDJ4HHNaFFFFBGQQe9Zdh4c0rTFdLW12o/VHkeRc5znaxIB96bJ4Z0aUQBrCNRACsYQlAATuIOC MjIzg5FawGBgdKKKKKoXejaffXS3NzbLJKoC5JOGAOQGAOGAJPBzVaPwvo8Ruilq2Lrd5ymaQq5b knBbGfer1hp1rpkBhtIvLQsXbLFixPckkk/jVqiiiiiiiiiiiiiiiiiiiiiiiiiiisrxLrcPhzw1 qOrzkbbWBnAP8Tfwj8TgV8OXd1Le3k11O5eaaRpHY9SxOSa9e+AXiOx8PanqEep+Zb2+otHBDdsu IRKu47GboCQ3Fez/ABT0KTXfAd6LUH7dZFb21ZR8wkj549yMj8a2fCOvR+JvCem6xGRm5gVnA7OO GH5g18tfG3/kr2u/9u//AKIjr6A+CX/JIdC/7eP/AEfJXf0UUUUUUUUUUUUUUUUUUUUUUUUUUUUU UUUUUUUUUUUUUUUUUUUUUUUUUUUUUV4j+0X4k+y6JYeHoXxJdv58wH9xeg/E/wAq8r+G/wAM9Q8e aiJG322kQsPPuiPvf7Kerfyr6lXwb4fXwr/wjQ02E6Vs2mEjqf72eu7POeua5Cy1XUPhzexaJ4km e88NTny7HVpOTBnpFP7dg3+RH8MpB4f8UeJPBbN+5gm+3WHTBhk549hkV4h8bf8Akr2u/wDbv/6I jr6A+CX/ACSHQv8At4/9HyV39FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF FFFFFFFFfPDeD734wfEzUdZuHeDw1azfZkm6GZU42x/U5JPbPrXvmmaZZaPp0Gn6fbR29rAu2OOM YAH+PvVuq2oafaarYTWN/bx3FrOpSSKQZDCvCdZ8O6v8L/H+i+II7ie88MwsLbzHO57WFzgxuepU ZyCfTHFef/Gshvi5rhByD9nII/69469o+EHizw3pnwt0azv/ABBpVpdR+fvhnvI43XM8hGVJyMgg /jXb/wDCd+EP+hr0P/wYw/8AxVH/AAnfhD/oa9D/APBjD/8AFUf8J34Q/wChr0P/AMGMP/xVH/Cd +EP+hr0P/wAGMP8A8VR/wnfhD/oa9D/8GMP/AMVR/wAJ34Q/6GvQ/wDwYw//ABVH/Cd+EP8Aoa9D /wDBjD/8VR/wnfhD/oa9D/8ABjD/APFUf8J34Q/6GvQ//BjD/wDFUf8ACd+EP+hr0P8A8GMP/wAV R/wnfhD/AKGvQ/8AwYw//FUf8J34Q/6GvQ//AAYw/wDxVH/Cd+EP+hr0P/wYw/8AxVH/AAnfhD/o a9D/APBjD/8AFUf8J34Q/wChr0P/AMGMP/xVH/Cd+EP+hr0P/wAGMP8A8VR/wnfhD/oa9D/8GMP/ AMVR/wAJ34Q/6GvQ/wDwYw//ABVH/Cd+EP8Aoa9D/wDBjD/8VR/wnfhD/oa9D/8ABjD/APFUf8J3 4Q/6GvQ//BjD/wDFUf8ACd+EP+hr0P8A8GMP/wAVR/wnfhD/AKGvQ/8AwYw//FUf8J34Q/6GvQ// AAYw/wDxVH/Cd+EP+hr0P/wYw/8AxVH/AAnfhD/oa9D/APBjD/8AFUf8J34Q/wChr0P/AMGMP/xV H/Cd+EP+hr0P/wAGMP8A8VR/wnfhD/oa9D/8GMP/AMVR/wAJ34Q/6GvQ/wDwYw//ABVH/Cd+EP8A oa9D/wDBjD/8VR/wnfhD/oa9D/8ABjD/APFUf8J34Q/6GvQ//BjD/wDFUf8ACd+EP+hr0P8A8GMP /wAVR/wnfhD/AKGvQ/8AwYw//FUf8J34Q/6GvQ//AAYw/wDxVH/Cd+EP+hr0P/wYw/8AxVH/AAnf hD/oa9D/APBjD/8AFUf8J34Q/wChr0P/AMGMP/xVH/Cd+EP+hr0P/wAGMP8A8VR/wnfhD/oa9D/8 GMP/AMVR/wAJ34Q/6GvQ/wDwYw//ABVH/Cd+EP8Aoa9D/wDBjD/8VR/wnfhD/oa9D/8ABjD/APFU f8J34Q/6GvQ//BjD/wDFUf8ACd+EP+hr0P8A8GMP/wAVR/wnfhD/AKGvQ/8AwYw//FUf8J34Q/6G vQ//AAYw/wDxVH/Cd+EP+hr0P/wYw/8AxVH/AAnfhD/oa9D/APBjD/8AFUf8J34Q/wChr0P/AMGM P/xVH/Cd+EP+hr0P/wAGMP8A8VR/wnfhD/oa9D/8GMP/AMVR/wAJ34Q/6GvQ/wDwYw//ABVH/Cd+ EP8Aoa9D/wDBjD/8VR/wnfhD/oa9D/8ABjD/APFUf8J34Q/6GvQ//BjD/wDFUf8ACd+EP+hr0P8A 8GMP/wAVR/wnfhD/AKGvQ/8AwYw//FUyfxr4OuLeSF/FeiBZFKErqUQOCMcHdUdn4v8AA+n2cNnZ +JPD8FtCoSOKO/hCqB2A3VP/AMJ34Q/6GvQ//BjD/wDFUf8ACd+EP+hr0P8A8GMP/wAVR/wnfhD/ AKGvQ/8AwYw//FVFc+MvBN5ay21z4l0CaCVSkkb38JVgeoI3V8sfFWbT5/iPqj6XdxXdiEt0hmim EqsFgjXhgTnGMfhXG0UUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUU UUUUUUUV/9k= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image011.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC+VXzUtUURT/3fvGMcfUSS2sFF5FFprVFFQUItGHSWWmE7RwocJAgpPjB4iuBEOk D/BPCNq0q8Rl0GxatWkRYbsWraNlFDSdc+95M9fXjI4EtfDK8dxz3jm/d9+5v3MvowDcJVEkdSSX SM6iMG5VAg8jgH/l5lWOytQAx8gfQWiwwwNqCegdTSkYqxp4TtJ9uecSuef5+dueiU8cvqwZrYpy rilOPGJAKkiqdACnlTIepXO5nPEcV03Gk9BKoqt1kLdT+5Gn0XqatUbrsA85TkKc7CzNVkmGosAH WkO1xOzEzeHpe8nZTAr4zGvBD20zeBw0b+xQFr1RQ0c9njXQLBndTbOfev6XjV1WvJ6IRjw5mk5N +b2pGb9/PD18H3hkURR2kD4VW/LmKjh2Im/3eWxnxJ5UqYi146E3cEHoLz4wmx4ZH4O2uNqs8puD P2jy28Ue0mtmbZ2wK/ZzDt4mK7bIWpCyWhukxB8rU2WtbEg3w37ZEan/5Xz979w5B08pT8WUfpD1 vDqFaqWXEsAuxPRiJ7xaokH9Qkb+68V21C9MmPfHBC1mdtx8lqwwjkpjvWaOrCitDw7MTk2n0lgJ f6Fn4nYxi0h4vdWC0g3L96qQXS+x/L49Mm+SmMAfQ4FNcDCeEg99evV+saOe2Vu0kmqWXIRyDzu4 Z+RZMmrz+kndMJtATfYrl3PSzD7nuYlRpJHCFHz0kp4h3Y9x8g3jPrbvUPlRqDPXMilyHtZ/EfZs 5Hq+73nS9eX74645OhKWPOu7UQK/D9zvwBsH85BgthXB7PPKw8yEME/AnuHMjwMhzBTxbVKVjxlw iqlZjFMIeh6zxJ8RYtFYCdTtOYpximt5FAV+uf4B2D08Ln7ewzAvBiPl8aKd5KOD2UCyF/a8aQ9h rpExpDfH7BRM96zxc0V5UeZZs/Edzkz+n3c48Hd3eIlSOrwYH3PPmoAXzIViZxDfJS0ktRLr7iEX MlvGHiYoagab97Yq0dtbu8PN1/7zO5wZkIW9nwP7jdhK7FemFgX7Zch+4eRvvIdb623G5z7kfgz3 Id/75fQhn89fsb4PuVKVTpypVVAt2sMpTFMHpvP1OBf63kTIPunUi0db6HlrqJ6Qb2ffM7GXHT1N Qj8biElWB/7bYl8QfVp0h2hfYlvEbhadhf19MU9cYZ1V623I841GqTvf7cPrKJwkfGoEcVTr+SBO Of4ax89Y3KuNkh+X+W/vJE1JcA0AAA== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image012.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhRwAsAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIACABB ACAAgAAAAAAAAAKHhI+pyxwPYJu02iTD3fzK2IUihmjj2Zkgylqq2sbOA8t2eedKLdI+H6OdICag rlWc/IRH5cHYHCVRy6r1+jO8njxrdPEJf3sw8fgGPffUtjR7w4y63x56Q/jZKTXz4FTvoNXHYiZY haOlVhYImHi2xUgi+PjkBJgnFxdZQqQoM0j1+YhJBlMAADs= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image013.wmz Content-Transfer-Encoding: base64 Content-Type: application/x-ms-wmz H4sIAAAAAAACC7t+9tgsBjA4wKjAxMwJYn2KZWQAMphPAtlMDDJgWVYg5mSCsZgYGaEsRqb///+D WXqMElAxbrg6HiYFpgOMQkCWGhs/gxTDf5BiBgGQbUDWMiBuABp0DIi5oWp4GHwTSzJCKgtSGRgC wHb/ZlL4D3HhBJClDCxMDAIhmbmpxQp+qeUKQfm5iXkM/axc//r4T5RPB2KFC6fKWYDqdIGqOYC0 EdcDRlGwew0rIeY1/IOZBxRlApkXXJmblJ/DUD75wvFyB6DMV1auu5jmMTKA6A9wcxsYlRhA5hZU ckFdzwX2IdiZULcLMLCDeXtAYbKJkYlJKbiyuCQ1l6EkiiuthAGoQ5GhC6IBCEo+CzHA3A6xi5GB GSwDAH3Oy4aoAQAA ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image014.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhEwAXAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIACAAO AAwAgAAAAAAAAAIdhIOJdgH+mGQQzkNvjpr7V1lLNjaS1WHptn5dUgAAOw== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image015.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC51XfUyVVRh/znnhAvfywhVQbiFxL5jpwAK3wkoE9CJDEJUPA9Pt8nGnNq6AIAhz DayUpW3ozMqP5A/7Q//pouZic/lCm235T2vVnLHWqj9arUVlLfuAnue857335eXeedfZnvOc85zn +Z2P5zlfDACakBhSKtIAUjGE0/PJAK/GAbgrNm8krcJFAE+iPA4siQQKQAoC3cYiKoMP63VIld6q DSgeovZPL1wuIfVnFEJLQpvzjAz1PuORkrgBxxkTEsbn5uaE5HHmEpIizqS2gxt2ydwdV+ZIw9Jy Wyo8DHNkBE6sa1i6RjUHwGfYr0PqJMPmlt49DQNdfoCvaSzwF9ctKOWKHlcxHT2DAy9QqJSOpUHb Yiz9zd1zuu4oE2Pm4GzYG/D3uGv9/e66zkDLPoBjOgqDROSr7Ro/ZyflolA9k1G9EHTEodlYEbkY 30wI2cfvJujITgsSSnHM4KwfCLR2dgA3RqTb85D99SSy7wrVl4Jet+JBRLyF47mRSKqrQvVpG9VL ZH1EORxH9fxQ+yzT260rwR64tvNnMqKMxZNNd6jep5hntp/1xOntxTIS2kOR0NjYBApjCrMz/rKm KKkMHIyPFAIsAjs/UgJKCgZk2kvdIu8CfiQfRA2okY8UIU/LNZsWkalIdtmbXcSmcLBcWyckiNoN iuYrjPPc+oGeXn8ArljXVpHRSZC4NcWMHBLnIFIB7SBLPU3qUo9LZNkldQy5HcKRDyaMMgR3Y+dZ sl6gCO/DcmRLpS1YbB814T4l2wZtul0dshoRkIgrdmg4jUow4WvYCwHwQw+4oRZ5P/I66ERZC+wD OXFT/6DDi3qiSbZJ8jTZVkgy9cgm9bFN6gd8BZSDyk6J3FPmKFevlatbytWV5Wq5k2eCB1S+WOQ2 ytmPIq8VeUFZhke971F/86i/eNTzHrXbo5Z4yG4p5ICK3WDOHZSz05DT2/XFcEoWzCQjH9371TDF eHGOWq6yt8UU1jMcAzwiyllYjpZYKIXXmebdIIkiMRvpANIKY33Gjpd+9+fx0nPoZI3rspoo+FuB ThB25qAJ0yExUyNgZrLYMAtRgzAN/1MYDc3+f//nIN4Z1FeRX2LkcwZXka9B/pPAYfAzo/Vh8C/y FOQqjnMX8g7kCcgPSP6i5Ee5jnNC8rOSv8NpPzAIIl+J/Evk6chnxG3BgCs6z1B0vRxF7z9foX3F oBi5DXmpouNVKXS/Mdgi7kAm7kgXjUvcTQwGFIiamCkADP8r0i9GLJjlhg/rkR5C2gF04s734V08 fHwxxUUwTYP5eziSD0P3Db4mAtCKXuvAlqwJHPyhV15rbmbVQa0NqlvdwT/q895n9m07gvF5612w pK/UVZq2btHTG72YEZpe0jOfzPPDyZVvTq7s4Onq+qbg5ezm4GoqzGU3Vwcr6907myZ4N++s8E7w LmLNTRNskHdX1JGcDXqbQ2qQy7tQDdYSa8aZXIVcUoNcdlWo1Qg1VoVi73huro41xapIiVWxKaG0 W8da9mAfunea97DhQwXm7+166cPd0ocDEXx4PSk2H9K8ZkyYTGKmR8Ck8z0mTFz8GYhpb0eIi+n2 tgp/XoUvr8KP5Ase69vjCg61ut3j7dPU4A4qy32tbXuIt/iD0wTTnud1j7e0RWhuy/N7gy153nFo q6CLoIwuAwsNxetkTR99DBrRGzjnH+qY1p4cuLXV8dzkJ2erJsts737o9jEt+MJ7twDv74v38jXD zr2xcZIWiXSZXEMm8Qjr+9XbJ4+6VM17SdXufePQFvasp3BcqFose9vw4S7pQ38EH95IjM2Hq3Cu d0yYVRJzWwTMaVtsmCV2VTNjFsrxrwH9j2HGPIxvjBHlwZg0FjPmYjnO7AjjnGUxjvNO5SRhxnCu xXQ3OVMCt8jmJAKtTV+hvfltK2xN3DHcgXz0po43dvGfm9qG7ZPT6wB+rwQNceFZmF5njcEaxOLQ OHnxLVXrhZNTFIPeU4emyrC9SbVMxgi886DdR3Jamm+fSA7Jmj6vFzFJuP2ZSdrrSIU1tZNGX8TN MdzYwIQu9R9lKaO+TaKda8bdtFbKN8DCuBiLjy0uukHVNBPmMomZHwGzT4kNs8uC+QTobyB603os mD0Yv/tZLOPE9xLMPyvJJwkmPfELMP4BeFb2QC9GWUAIa9FgG9J2pH75Thgq1deTcC4grbf0ezA+ /H/XXHr7gidGhP87fXx/jZv/fz9w/14rNd2NM/7vAU69D4M0sPzfKcX6f4d4X6r1/x4thWOtYSDa WVkN4X8J9WDo4VoPGXrMJFdNcsLCnx5kSHunLP8HZR2X0DARAAA= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image016.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlheAAsAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIACABy ACAAgAAAAAAAAALLhI+py30RQHS02ouznlD7D4bWJInmiV5kmbZuSnbvTG+GXOc6A0Ur/dsJWUDc UBicJU+95tLV2z0dzqjEdztqp4sOh5elVrm5cZAMJiJi2uPK3H3E1SGz/Q63eb4K9uM81rYWmIBW KHd1E8NnKJjRqPiXZSTD5whjREFpmQZ5uaUZ9jk618BJikrX5QnC6miV6ppa5PM05TU7VJk2l5mr 5KdIKCr7i/HGu6ZsXIZYupzIDOT8jOgrjXkNPYiFrQTj/VJ8GN4CW6d9WQAAOw== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image017.wmz Content-Transfer-Encoding: base64 Content-Type: application/x-ms-wmz H4sIAAAAAAACC7t+9tgsBjB4wOjAxMAJYm2MZQQxmE8C2UwMMmBZViDmZIKxmBgZoSxGpv///4NZ eowSUDFuuDoeJgemB4xCQJYaGz+DFMN/kGIGASD/AJC1DIgXAA16BsTcUDU8DL6JJRkhlQWpDAwJ YLt/Myn8h7hwAshSBhYmBoGQzNzUYgW/1HKFoPzcxDyGORxc3H38J8qnA7HChVPlLEB1ukDVHEDa iOsBoxbYvQaVEPMa/sHMA4oygcwLrsxNys9hKJ984Xi5A1Cmn5XrB6Z5jAwg+gPc3AZGJQaQuQWV XFDXc4F9CHYm1O0CDOxg3h5QmGxiZGJSCq4sLknNZRDn4UwTZwDqUGTogmgAgpLPQgwwt0PsYmRg BssAALn3JaqoAQAA ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image019.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC+1W30tUQRT+Zu4tc9d03TTsh3Ezkqg0LSiCxGBbI1IRf0CPKiwmuCquIksvC0Is ptBjf0RP0mPGvvfSQ0SPPQS9VW9GgbdzZubuvXvdxSv4ZM1wds6cPee7c883Z+4IAE9IJEkTyQ2S O/Db/WPAug046aEBQOB1A3CV7DZCjQ0W0CiA96SSM14R6DrJwwePUmQu8P/fPrSn2H1JMlo9xdwV HHhJgdDDUC89OCmEsgjpuq6ydIs2ZemVwnjHpRfXIB27ZCdJ6zzehLNwOQgJmpdIe0NSIIiPtIa4 8WnA0NTy0/H8Ygb4wmvBb6kjuHWoJ3YJjd4iIVMWa6dIm7FbSfsjC7va96Xg9dgSifHZbCbnDGdW ndGF7NQ88EKjCJyg8WasaG1a7Lto5pNyADxPI4yIfRClWt/PMvKSWFHIvQbJcaMiCYMkDVJJdqv3 6VG5CK2J3h6JsXx2emEOsvpKJmWr4qdPscqZvlfO9MREDywhLBETybU0rCaBuJDFHqAZMfm8D1Yj E17spd/k2qJ6bsygxBSn6nXMyhKoU7O3vAu2hJQdY/ncciaLrfCbWcpvZ7uZdwoJrzRucG6RXOed F5onjS8/8bTR24yPZ4/B3zEIYJS4ZkjOmXnKUrlDJw3nTSxCsZcDuLfNfzO2jhulYVDoOi3sum4g TPFS3n+YRRYZ5OBgmMZVGkexQLYpzKsMcP/xzHXDGnedI5T9WK8cgz2KXyV+Le+9OLV6NbxgDGo0 UW47216eOZfjRjpN/rugzz/O5+eNzf6vvzb6N4m7oqVtgzXwR8A1vbP9LoDJ+Geg99m1ECafj5Ny f8w0yXf4/Fs1+EdE/v/V5vPv1xnn8gr8vRC0exyyjb+LfB5cRCWHK+S4JPbnkM4y8L4I1rDj/ufw oK0ah5xLj0PmrVpt87wd+jxl3yCH3TQpRahD+kARD5HqUH8hkSe+pom1ucNLwBFoB63DMWgO+fvL Z+kF7D1LW2W0s7SP5BMq65D3RF3AT90kvLsEcZjDMlVg9vAScARalDp8DP9uw7dmz49yXfD8RMB+ MmBnLLoFosXEJ4z+F7A6YbGsDAAA ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image020.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhMwAsAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAMABAAs ACQAgAAAAAAAAAJohI+pyxANYwxU2ose3pN7pn2iEY5faXJoiq2s5ZLUHHtzU9Zvxu9QqPORDkEh LXi82YjCzpCVTD6ZFUW0aE08NFhb1DFtgsLiLLg8PqMX1bX7ba204Q4uvc6k5+5Afl6v5Hf3Nxio UAAAOw== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image021.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC61WTWwbVRD+3qybNLZf4pqEFBKIN1JLSltIkCASreVakEJDG1CSSq24OJUsEalu YiVS6gtyBYooFKkH1BO/EieOFSAOqPKdGxI5cKg4cEMipb3wI3WZefvWXjsb1hSeNPvem535dubN zJtVAM4xEdMA02GmabTGVgJ4lyk3c+YkoPBNGniS+Ql0DGE4QL8CvuMlC+NzBr3B9NKLp15gdl3e 9xy/K6/xJglaH+sUlCgeMiB7mPoogCOlDEeR53mG85TabzhTpKx0igK9NOUSpUSWVwd7BvAoPFFC hvcNXn3FlGOIH9iGlJVJ48zS+huLtdUy8JPYgj/J15Axbr54VPnogwRyHVk9xKuhxBCv/qL6fV/2 uhJ7EoTM4nKlvJabK2/k5lcqS5eA93wUhb08P5O86hxzRLZq9yU6CdnPoBMRMYhk7LvTRK4qH3nK IuW8bpGURSKL1KBh5SNldtrE3iOzUKtcWLkIirakRNtGP2+iKif9cvOkz549DkcpRyVV9q0ZOAMK KUXvTAH7kKTNPJx+CbgwWKBqvrttx+Xe80haxKSJr3HNWplBr9l9KxlxUxGNL9TW1ssV3Oz00jFy nrdPsoZJrE5ZnKeZjkgWduyzVla++LBd77cyAT+JVvYghFGS+mEasXvXMeeIgzyNWl106B4I4T5n 3w0lfL15nk4rv2br9z0vpGZi1MxFLKOCMtaQwxzPGzzPY4V5S7gk2M3hecH3xLQJuw7bIfwFpkWm QaZHrO2HrY0HPnu/8PPv1wrbvCmRzzuN6PEaU56jt4V2X8TH3p3ifixRYz/W2YsKYGIfP3b5fKTf ZH0TGrd+S/ZOd/h3jA/iqhPvX5VtvBXCJHtmqYgzk7uymzObYfo1dGYSk6j4y+gm/nzW9SDWCq1Y a8uHtZsr0sRcRsauu4uAb1u94ONLf6mhvb+8nm7vL5NclM+iu/5S4v28095fvv/ki7yIP+/scpAI x18hKu8J7XkfzgvxQfLCxc68qKr4GMqdKnkRzvuc9+Ax7OwvDfow6d/dey2af5dP/uf+UqIfe6O7 gorsCsrGkJr6X/eJ/mpzPwp//09dJj6GRxGu4SCGTiiG4dqW+nvMxnGiI4bDvGl0UYdT+HTPBrqq Q98PzvoKLnDULkL+tmz/o7cbTtD/Jtv7n+l8/FwFbQqM9EF5KX2RNrPjYVXTOs148N7YinVQNuHe GOBcRntvDPZxvTE+huiqDv/X/sN1Fdd/zGlF9p/WmLVz1toxKTy9OaufmNW3aAJFaPWBkXBPpIr6 y6J+tagPFXUxQ8N8iWgaMs8eeapfzHPOPI+cGHT1H66+5+rfXP2Rq6uuzruiN4oxuaLlSSl5qhsY W1/dutI/gjtpnq8v374i1T49potafWxvE7YEj5v1iCr+q5jQrtJh+WuF3erwFbT+beQPOpCL6z8B VlT/+RvZKLrDuAwAAA== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image022.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhLwAsAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAMABAAo ACQAgAAAAAAAAAJihI+pu8EPYZix2uOufnl71H1fKG5keZ1opa5SM8WtSSnh7Bp3zmH8q/txZENZ TdPB8ZIuozEIAhx1TmWCxBRWs0Jgt/cFh23TsfksdVibVDR3vDsn16hMORyToq97Xz8dUgAAOw== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image023.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC7VXz08TQRT+ZlqptLVFIoQYCQ34K6FqMR4lYKSFKj8ESvRIqWvEUKq2ir01MTFG OfgnYGK8ajgZYyI3D/4DHjkYzxw4mBiob2Zn2qXdskvR17x25u2bb2be9+bNlgG4Q8pJ20gnSHtR ldtHgSI9jMQnEgDD/DHgHNk9qBGvaQwx4Ds1yRkfadw70tGR5HUyl8Tz057Oz8J9lQu0VhqTYGL2 SxLkCGkr13CcMWlhvFwuS8tF1iUtA5wp7wDX44J8mK/52ql1tiWMkyiLQXJPG9R6TzrvA37RwIDy CWIiXbifKj40gHl0kPUPj5TN7bxhchUcbanFrJGPTBorkZlcNr0MvBYruUDPKTS47N9k2y3CeaDS j3pFP6YQS7sakTkgMrnHrQpyifVJ5Hiln/DU9GH2a9fuNBPUTKy6ZjkmI+NlXbNMDUKaLWYXckvg jVa6I/fcX+mHJEODklcR61Ql1nNzY/Aw5mF+1v48Dk+YIUCtDHAcfv5iEFUrfxlT1v491gFhFeJX 6H7JtqRM7aANPtn7IvJjnXHeO1vMF4ws1msjYGaywAvC3E9AoUyTdomMrOm3K18xX6dqdykfbfer vhaNsUbLGqY1zVB7nJm+EZmpVTFzTzGIRWRhII8IJul3hX5nkCNbGsSn3PdegcUKW4//LdY5m5kf LoRVBDhjiXtKaZL0BMx61qOePQ2uDv38vTq03QJsqtiPN8C/BXGigWcWzKjCjNlgRr3uMGMKU/Mv 0rO0W89/5QS74j8M8alGzxrJwzCpsfW3W/7s243xretvnn8Ry/OWXLDaNYfXYJ7DGzDvOSuHfZQX JRccxkm3LJi9CrPfBjPhaQ5T38cBO0wcDNOp1hws1/Yy7Zxr1bnc5s9BpH7nhx1fL41qjc41wZVd DRJ9US/CpN01HEaZu3pB1yK9mzjXC+h7GkXia4FYW1KxkM+GR/H1k3103HDoGMGpMWx8a5bj/euF M36zHO5XL2YVh1dgnsOrqD+HO15351DUhR8WzA6F2W2DGeLuMAeZiWk92wLTZ/GT7z767YfyIo8C neqsS5Z0tD8gJi4tGX97r9KQqDWP8ITqRIFqSE5Wi38nb3vCa+JGP/Uqibsj6UJ6auGBkSkklwvG 43vpjOE0Pi3H24ubs30T1Xc58U9D+9FfoZI1f0IwzzuUv2j/BaEmJjVgDQAA ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image024.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhUQAYAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAMABQBK AA4AgAAAAAAAAAJqhINpy+2d1JszoroC3U8fDn4i9Hnh5mnm2ZUtsLIYfMZOSkUyp4c2JLmNUJYf roYakmi7nLJTfP2G00xUmLHOtswL89n8fo/LFxV2PVRzaTJjWlytxWFp3Yy/Y+eytUpvB5jFJghV qBZQAAA7 ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image025.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC9VWTWhUVxT+7p38OT+Z6dCUoRAcRKNFq6O4CNEkU6MNogbJj7gQmqQdMZCXhCQ0 jqsBrShGGlyVrrTQuBcXXUTyXhdDqApdFM0yggjd2IKbgujznPvum3kzeSMvVhceOLx7zz3ne+c7 57w7IwCcJpWkCdJDpFtQlmcNQJ4O00dOfA0IPI0CbWQPoUrqHGOzAO7TkpxxheIukPYePtpD5gKf 17W3/sPuo5LRNlHMXsFv365A6kk3SRdOCqEsQtq2rSy7RUpZ9kqhvSPSjYvKrMw2JGnV1hDH57A5 SHEyabXIO+LyjAIj2ieKEyOz5wbzUzlgGC1kfSnTtkNnQagsJBKDY0ZuJt2Xm0v3TxojE8A1zuRL Om+i577wmrhaz86Z0v42nH1CIRZeu4iKKCEO5I3RyXFIB0coZv+W8ApioY7jp9bFwzceOl6U4hdD 7Hq3jMdvRqdmWJHPWxmuz2xJ1X2itO9QTKdV97iih0sVHRpqR0iIkAiL5MVphOICESGvZIBPEJaX O5G8OAF5+THkJTNUcQqENVpY9VA1QtcigUa1W+Ku3xFSbhnIz8zmDNyproUzn7bNeDSyKuOIxukh TfGkVe2T2pff+Jlep7SPaw/rvSsuRpZmK0tZ9dP6uHB802oCy+LMlK45xmAghxmk0UfPOXr2Y5Js I1TfShElAbbpXFh26DUXw7XzKwa18v5T0jhpqz77Pjrf/fS/+e5dtFnTeR6Hv5wk/Rb8bZR58bsK r315ObOJPHEYJSbjqv7aM9uL5d+gLXZVXfy52rYfpwOaUzfpZn2GweuK09X6YJwylMWcB7NBY4Z9 MG8jKCYwF6BOwrdODr7Ll2MHdG774czXQTj3stNDjpjvfkXDXgiQ207SVQ9mi8ZsrcB05qJZBsOE xvTOO2M2evzUV+p+p8R3BrM06QZ4CmpA+846w7izXqtOGVT+fnl7uBCwTlOkz6s4BZ/12jKyOX5z I3wFKr/tYyjfOfUe/jFKz1uXZjhzDO3P69Wu1S7Fuy1mDq/2WufHeqw/kjGzS3n1WlPLZ4s/xYzi Ss8h61YHzJZ2mHxS9+Ir669wn/WEbIUDMM80G8UH5Mf+K/ScxY3f/w8nr93t4Xad9x6s7+FiKFgP 7/4SMx95MBNaUz6Y3MsgmJ0aM8C3Hehuz9+ImsNnTllO5JDFOXM9UzSnO/iyRkSfl8+ycaP488OI ubJ0tui1f0f2L/5uMs/fo76oM8rlXqVPhuzf/Bo1L9Fzq/ZhafpzvLj2w5BVq4/vWzb6bbv3M99T 3MOtWN/DpYD3Fdd92YPp/t9t9MHsQDDMabp1fsS73oEb/4/HMR/1f7wa8qHvwDdRSZV65AwAAA== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image026.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhQwAYAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIACAA9 AAsAgAAAAAAAAAJVRGIIy+1/klrTwINfsrprBDpKRVkkE3kUloncmULlp9biSHeh3sQ965txbjxS pIKzuUpGIWr13ERPtkkQ2UNZnS+l9ysbzqjgMk/cNatVyd/67YkUAAA7 ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image027.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC5VXTWzUVhAee+Nd+9neOEsCK0phhQKiotDQAkWEiFBwUwRJl2w2oeUfkSisCCCS FV21VEZLEJaJhDhwKUU5tFUPPVSIA0KAUlrR0vaAWvFzqFQOabtLOESoQuFHcefZz44JG7F90VvP zJv55r2Z8fiFA4DNOHmcGs59OOfCxDghA+RwMaE3vwvAwVgUYCHKQzBpVLjCKAfwC5KoDGNodx9n 07r1a1Fs0PU5x5oc9d94iiahzV6Oen/bkQo4Jd6D4znOkXC8bduOZDEXdyRLeI5py7xnp/CNvEFi SM0PV8JMsKmRc6YhpL7C2UgA/kZDmeko0Lyrr7std7ATYCfUoPQpn7Dd45zinF3woLXt7ensTbR0 Hk60HujZtR/AojtZhOsiPt8k97hbElWu8/kWgfJLfP40uLzrwRj3PHAv8cA5Zx71PRlct+PpkM+3 Rii/3+fP8M/zK8HV1yZ5dhKOnlO5nt0H9gHvncj1x/n2bSJVXeTz88OUb/B5I0T5Cz6f4dz1yf64 kv5ePF+mgtofdKqBZmiPn6F0ejOEOC7EES6WPwShSg5kjj+xBKAKCH+8AWL5/cAfvwP8saHQVKux uUHbOrpKB2HeiFMzTuLZCTSIONxlWmXnOZ6fm8r19nX2wPnJEXPfBxKmiAq4J5IZzkGccVrZk/gY 06UepzM6znQ8OWG8NzwMAxcacVetSG/kXN2EU/ETw61hVmOwF3qgE3ohAS34PIzPVjiAsl1YLwCq GpGJRARCpAghgiQRSSREJJKqoszxLJNIJBKLqbIzJIVUEUWRFRX/iExkVVbkSk2NynKVTKgpUSVE I5RBUIlyapQokqTSZUkShHBlJXE8adPw6QzqqWpmFYTDETEqxxRBFOVoWAxjNL0hitFoVKpSFEWV iaqKoiJFVZWoioL7qcIfETVk3BHuOCzLQpgIVTJMMTh/CMK8QNzb2OzGWQ1uX5zD1mDw5OrhsZOr b+Fu77HYb5wCPwm0M6jqRwHMFQxzVQnMFqE8zCUgK0HMMMMkJTBPw//D9GqKFr0x/mJN+X3rJTX1 z+ATO7+vtiJRvM+oiuI6/DC4FEVzqUKTR13yqdnvedSoL9uwMORQtcWecy5ebTE/6FHHGbWg+P45 j+pksteL9ec8apMvA3CpuuKr5zzqrUGPWs6opUX7c4+q8WVxpKYIZaCmVhW9mqKxXAAT9RWUeznc A+67vRfcb3Awh91Ya0YZOTwE2dipAGYLw0yXwGyNlIe5H0aEoQDmKwxzbgnMM3y5mPVqENO7f0RK YK6Ecs9+qY6ePdgTS9UveF8jyGGt7saKpW93Zb+Bv11WTXLLw1xHl9WwGZ9dZvqsqX+R/9k29W+6 TP1bU79o6kOm/qtJYe6ZesHU/zX1ZwP6WTP9tZm+3GUe+QGNt6Kxmb5ppocRcScy7cmMYDYPms0X zOafUOmu2fwHoj8wm0fN5jG75kT1cG7HiHCRawRj+41rCljraqvzCbgYggrjWjV7ilQsMjH9yqTS 7R1XohAxCjf/4iHDWw0ntOHcllQqw9nLVqBfe9lS+nunf8jqq602w5XHaDtw1qcIZaB+h3PBnujV L81VUJ5iOdzMcrizRA7bxPJyuAjarbsBzDUMc30JzPnh8jAb7KwWxJzHMBeVwDRC5WFegPRz+6xk mDNKYGa4MveptdsUs4z+W6J+Zw00zUol7U2NRj30iRlue/E6tf/y7iNE6Cg8/OyJbY32P/pk+kA/ FXU7XjO8fXhj4Ty2P+OKo9i3YqD/GfpMMq3EiuFcsvAO3iyocXamna12FTCmqSQFMQqHx+lqfpzL RnGZLhT+HGcGuqvdTS92yZRdc3fGcK5/qO81KkaJXbN12nCuXtd6NeYXdbpRNKJcFfBNGBGu8ljc 1vUd27fcuKZh0B+krG3V7VZW7LCmCGWgfrMflNN/vRy+wXK4plQOK8rLId7tBkbh+R7k9TVvOLdJ 7z6JOeyFPvx69qCocPR3HuysmLKzcTeUHQUJY40NxtKfOTGI0xgcfaAhsKVTmHYzbunxDjurmPGB /lEaQzeEli5ajavy97RVWnaxv1KHCbDGMgtdARZMzeXpmIHv+0LXYbGla6YujoStI5q5TSz8uPax bS07hQ0lP8ZnZ9vZWQP6s+SAriRTrnkHHnlpCExdG1le+G71Y9uXF+r1p7Y1Vv/0049THfYy40Ps Qbc9ytQV+zaeydymwRRjIof9Q1P1oA0wcTcWAjlVMVXBXOO/rM7dCJg+pf8DwlMczvgOAAA= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image028.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhcAAYAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIACABq AAsAgAAAAAAAAAJ+RGIIy+19klqTuoPx2ztqznmVB5YWUhlMqrTmi6rvFVMpnUWQfNfPdFvldCse ZMjqzUy6oKxjWYZc0uhF+ENerbsg0JYdbp9SoI+7/LKKRyw5XXSG2ET0zDy21ptVvXwepdQ3eEdo +GP3dziouAiT6BhpJwn39kFJeIlZhlAAADs= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image029.wmz Content-Transfer-Encoding: base64 Content-Type: application/x-ms-wmz H4sIAAAAAAACC5WTPUjDUBDH7y6p/VQTa0GcagdRpH7tgoi4iA7aweJShYqCrUqLUnBwcxXcnDq6 FZ0dnFzE2UkQnAVnBeO7e+kzbQU15aX3e/nfZ/IeH+4uQK5bt2BDlK2rRWTDekF1g5Q8DakVJbZs tQhRdpA8z5OdcRyQnSlCXx2npl+CCvat26es4a5eGASPncDhnMq6VOvEBYioMHFfk4Cljep2rrZf BHiWot5Je/CVkYxZ1NH7aZYKIbaSytpyud4POvnU2jPkemwCJ7dTKlbSy8Wj9MpeaaMMcKqjIETU /3Ts3ppMsPbAcDjGvO9zAw97WnkoHtQ3MNmmP48wlw07XczLPtdpAZjnQVec9v5aMUn/b6ZyC596 g5nAWkfNTtss+NWpn7NaK23u7QI1J6Djkek8KZ2Nmconupmzho/DQa7TjB3U12lNvoIZP/93Zz/n 7+wn7+j4qU7/X95laycW3kmkKUh1TuJfM27gnMx41PBSQkdu8qvMbMTwg3wN44bz0Vb/aiior9O6 pePF/DMQk3MihfpzdCAsdMMn6xqJMqu1SrVYguv27i3RfQFfGBAT3AMAAA== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image031.wmz Content-Transfer-Encoding: base64 Content-Type: application/x-ms-wmz H4sIAAAAAAACC41SPUvDUBS996a1TS0Y/IAiiKGDn1Sog5uLu0VswLUVggqmrbQgnRycBWf/gVsp joKZukk3Xd1dXFUw3ntfjFARfeEl57zcj3Pee4/3gyvQUbNDC21BPQ+BgbWH/IIZ/ZvmaZOgFE9C 1BWkKIp0ZQ0LulImjKPH6SsvT6FVsycZLYxNwCxEkgQO85DRHU+X251ZnBPH5GG73jn0ui0f4Em0 wBuZDBlF7VhCU32aejgkQVOM5m3R+05uZGIvUfSkCBzvKPDbbsU/dXebQb0BcG6qIGT5u567oEZW Yhsx36EHMNxUDD/+W5FU30tSec7aykhOS50IfyU2C5XWSRyxgddjEvHNhymTYTjQomrxfmiBP90Z LZRoeVYtywk/SAsvJ7ygfEl3e6QT8eNUu8F+8xjoN68r6qSUOLnRequJk4Hu3ybk4rPO6X1QI3FP BzLKbuUG9ZGoWO22O34A/VFPlsZ9AvmXUujEAgAA ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image033.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhRgAmAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAEAAQBE ACQAgAAAAAAAAAJhhI+py+0fwpu01mizznj7r3Tg+EnkqYno6qjsm7jwLM9vba94fu48afrBfEIP sZgKInvK5ejopECjkCbVeAVas5YpN7T9TrziA7kMOJfVa3TS3Q3DwXOpvG6+49N6PLtcAAA7 ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image034.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhZwAzAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAEAAQBm ADIAgAAAAAAAAAKRhI+py+0PYwtB2otzprr7f3HgSJJiiabWqbZuwr6yGs/2WN+6lu++1PsJJ5Wh ERI8HilFpRORfAqjUh+1qrtibdqtrOt1gcO0JnlqPlvT6iy7zX3Dv/K5uG4v52/Mfdz/B0gnOEh4 Z3iIqKeYMsb44PhIJFkSSalgeQmFpxmR2dnX2fEJyinqQKqZernKegpSAAA7 ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image035.wmz Content-Transfer-Encoding: base64 Content-Type: application/x-ms-wmz H4sIAAAAAAACC7t+9tgsBjBwYDrAxMAJYk2MYwQxmJcC2UwMMmBZViDmZIKxmBgZoSxGpv///4NZ eowSUDFuuDoeoJkOTEJAlhobP4MUw3+QYgYBIP8AkLUMxAOqTQNibqgaHgbfxJKMkMqCVAaGBWC7 fzM1/IO4cALIUgYWJgaBkMzc1GIFv9RyhaD83MQ8hnVsXMv6+E+UTwdihQunylmA6nSBqjmAtBFX NJMT2L0GlRB+A6MVyFoGT08uqK1cYJeBjYfaKcDADubtASncxMjEpBRcWVySmsvAkM6V1scA1KHI 0AXWANJZ8ViIAWInI5j+AJRhBusHAIZuM6BgAQAA ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image037.wmz Content-Transfer-Encoding: base64 Content-Type: application/x-ms-wmz H4sIAAAAAAACC7t+9tgsBghgWsDExAlibI5jZAAymJeCBBlkwJKsQMzJBGMxMTJCWYxM////B7P0 GCWgYtxwdTxAMxmYhIAsNTZ+BimG/yDFDAJA/gEgaxkQHwAa5AZUzw1Vw8Pgm1iSEVJZkMrAMAFs 92+mhn8QB04AWcrAwsQgEJKZm1qs4JdarhCUn5uYx8DMyaXcx3+ifDoQK1w4Vc4CVKcLVM0BpI24 opnkwO41rITwGxitGEBO9PTkgtrKBXYZ2HionQIM7GDeHpDCTYxMTErBlcUlqbkMDDPZ03YyAHUo MnSBNYB0lnwWYoDYyQimPwBlmMH6ASAcvrdgAQAA ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image039.wmz Content-Transfer-Encoding: base64 Content-Type: application/x-ms-wmz H4sIAAAAAAACC7t+9tgsBjBQYHJgYuQEsQriGBmADOaTQDYTgwxYlhWIOZlgLCZGRiiLken///9g lh6jBFSMG66OB2imApMQkKXGxs8gxfAfpJhBAMg/AGQtA+IHQIOeATE3VA0Pg29iSUZIZUEqA0MC 2O7fTAr/IS6cALKUgYWJQSAkMze1WMEvtVwhKD83MY/hFiuXWR//ifLpQKxw4VQ5C1CdLlA1B5A2 4nrAmAh2r0ElxLyGf4TMe8nGdR/TPEYGEP0Bbm4DoxUDyIigSi6o67nAPgQbC3W7AAM7mLcHFCab GJmYlIIri0tScxn6NnGm9TEAdSgydEE0AEHJZyEGmNshdjEyMINlAKOeRiKoAQAA ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image041.wmz Content-Transfer-Encoding: base64 Content-Type: application/x-ms-wmz H4sIAAAAAAACC7t+9tgsBjB4wKjAxMQJYl2OZWQAMphPAtlMDDJgWVYg5mSCsZgYGaEsRqb///+D WXqMElAxbrg6HiYFpgeMQkCWGhs/gxTDf5BiBgEg/wCQtQyIFwANOgbE3FA1PAy+iSUZIZUFqQwM AWC7fzMp/Ie4cALIUgYWJgaBkMzc1GIFv9RyhaD83MQ8hgAOrvt9/CfKpwOxwoVT5SxAdbpA1RxA 2ojrAaMP2L2GlRDzGv4RMk+fnWshpnmMDCD6A9zcBkYrBpARQZVcUNdzgX0INhbqdgEGdjBvDyhM NjEyMSkFVxaXpOYysKhwpgGN42JQZOiCaACCks9CDDC3Q+xiZGAGywAAdEuEGqgBAAA= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image043.wmz Content-Transfer-Encoding: base64 Content-Type: application/x-ms-wmz H4sIAAAAAAACC7t+9tgsBghgcmBi5AQxAuIYGYAM5pMgQQYZsCQrEHMywVhMjIxQFiPT////wSw9 RgmoGDdcHQ/QTAYmISBLjY2fQYrhP0gxgwCQfwDIWgbEB4AGPQNibqgaHgbfxJKMkMqCVAaGBLDd v5kU/kMcOAFkKQMLE4NASGZuarGCX2q5QlB+bmIegxA3F3sf/4ny6UCscOFUOQtQnS5QNQeQNuJ6 wOgIdq9BJcS8hn+EzFPh5GLENI+RAUR/gJvbwGjFADLCtZIL6nousA/BxkLdLsDADubtAYXJJkYm JqXgyuKS1FyGOwEcaXcYgDoUGboYoTHAUPJZiAHmdohdjAzMYBkAwdWajagBAAA= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image045.wmz Content-Transfer-Encoding: base64 Content-Type: application/x-ms-wmz H4sIAAAAAAACC7t+9tgsBjA4wKjAxMwJYn2KZWQAMphPAtlMDDJgWVYg5mSCsZgYGaEsRqb///+D WXqMElAxbrg6HiYFpgOMQkCWGhs/gxTDf5BiBgGQbUDWMiBuABp0DIi5oWp4GHwTSzJCKgtSGRgC wHb/ZlL4D3HhBJClDCxMDAIhmbmpxQp+qeUKQfm5iXkMR7m4WPr4T5RPB2KFC6fKWYDqdIGqOYC0 EdcDRk2wew0rIeY1/CNkXgcXlySmeYwMIPoD3NwGRisGkBGulVxQ13OBfQg2Fup2AQZ2MG8PKEw2 MTIxKQVXFpek5jLcd+ZMu88A1KHI0AXRAARXHgsxwNwOsYuRgRksAwBUthlfqAEAAA== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image047.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC91dDXRVxbWec+/JTe5FMJa0RKgkgEAaUH6iiKu0BGgSpFpBqQUTEBCU+opAiESw 1UsRsEXRor5Sm1pExaogP/KXNJDw04rYLl0+XmWtR199j7d49S19jX+AKPL2nLPnZrJz7p0JOfdk 8g5rODNnn9nnfHvvmTmzZ9+JxRj7EaQMTLdbjH3Bmo+c/ozN78lYfskNpYxZ7In9jH3ahbEujBw2 pDBj3aD+G4S0tbfNzuSGGTBggyHlQwJ2g6xii30d8tmQQtmN/wZV2QxM/N4KSBPx3r7FNrsI+fUu jibylwMPkR9aHHJ42U4pPrpPcWaCZhezRD6XNecvxfz58+dZDua7QvoK5kOQ+kDKgtS3+d7zXtdi iEUc4h75GfKz5ecNxfzF8OID4MzlYuF9lsSzP97Hrw1ELCGkcf7yPSEpnwl8+zc/O67z3l58rBR4 THvWhfLujXIVxx1w85dwvgnSAssxc3ZaCBuPx1wlbefwJrMfsnlsDlsElv49OFfD+SY2H67NZHcz /eNEVuxRhu1SvJt7/l546ekj3GRYcebK0MNfrXXw8vsr8L4dcI2/0nE8/2Xba9UM296Zy+8duiNa y34cqWWzgf7WP7qzD2aeHfpZlmUPT/IuvA4/c/1tgvsfhMT5Xg/niU3dnevyUQDXzgDPi7BOyO0e El1Fj2aZJdp87/N5/PV6zF7sqC2hq7Akezu17PPHsEqQ/kynT2vPAbJc4y375oPL/nc5CdmvEbJ/ K8eV+Zkcb9lXhWpZbq9aFs9Jv+yjKD9Z9rnJZT+Qyt5Oogcul4+T64HdAFqoAl3MbKceotHYSua2 80S/ke2hh4fDrh74/Yk2EMY2EPbWQ33XWjbehjYA9HffadZDqYYe6uH+J95x9VAB5xnHWuth5DFX D9nYx8t6iEDq1wY9ZEiyjyhkPxakPhtkz9ov+1Xesn+Vyf1PTSgh+1VC9odCrszfDyXvf2oyahlv C6bLPpJED5mp9eDbOAByfUi898V47WIPPeRmJvTwUEWibbjyn5uZvA1w+2+KtNTDKJ/1cLHUh4Rw /M3A8V93HMgkeujf/P0U17ku9MaZngpAbz+KxjYdfeuwxxjSrLetF/2VHY+6euP3C73ZMVdfg2PJ x5CKi2oZb0f5c129vZ1lzdYZQ764szs7eqertxo4r5/bWm/3zm09foekMaRnG/SWJcmej0efBjBu gCw3cNnzNtMNr3VLLfsN7ZX9KJ9lz9+3C+m7uC1d1oa+K5qkPaTjOv0Wl+9P9V0e9fEbXcyJqEwF T369wONZ8D7xAo/n0nmaPC8Uc9lMTGLu3AuTn/O4Aun9cyWZiHcQ8/cZwPAz6R2C0A0j76SrG4pT VzfJ9HELzqOvxP6pHG4+hHK5Eq6UWzwdgvwhp0z1w5Lox08ZxtooQ47la4jlMLb9XJTT+5Buk/Sd jfdv0PRrjMA6nPcGwiNO6HFCn07o0wl9FKGPIvSehN4zIDnL/UgqW00mZ2EzIdKm4/G4Z3u1PHDr 6IPK55BU5nxoOZ3yC12A/HTbltze2yonIQd5rip4DGLeMpPpGwh9A6HHCT1O6NMJfTqhjyL0UYTe 00OHvZLoWNiAPBeX730tBdaxhD6W0G8h9FsI/S5Cv4vQ7yf0+wl9LaGvJfSNhL6R0OsIvY7Q3yT0 Nwn9BKGfIPTThH6a0LtYLeldrJb0PELPI/QiQi8i9DJCLyP0ckKntnCh7T3cjv5SfG/MxH6xI99l MJ6nw82vG/Quf2w5X43L33Cif4yl+DaMJRlHiiAd1Ogfv4X3JeyKlCeRcjkpzyHl+ZAOSOUlpLyc lB+BtF8q/xJSo1R+hpRfhtQglXdC2iuVOa1eKh/BvkCUj0LaI5X/HXmI8t9xkinKH0F6RSrzb/cX pXIEhP6sVM6Gco1U7gnlJ6Ty5VD+mdwPQ/nHUnmk5a61JfphKE+Vytdbbt+c6Ict1xZkvR/yWb8H 2qjf/US/jUS/DUS/+4h+64l+64h+dxP97iD63Ur0+zLR73NEvzVEv78g+l1O9FtJ9FtB9DuG6DeP 6Jf7A2X91ktlrt/FUpnr9zIop1O/B9upX1X7bSD63Uf0W0/0W0f0u4fodyfR7zai381Evy8Q/a4n +l1H9PsI0W+c6HcB0W8F0e9Y0n77kfZ7juj3z4br1+/2u4fodyfR7zai301Ev88T/f6G6Hct0e8K ot97iH5vI/otIfrtR/R7hrTfA6T9/oTod4Bh+j3gc/tt6/i7m+h3B9HvNqLfTUS/LxD9rif6XUf0 u4bo96dEv4uIfmeS9juBtN8hZPzt6vHdJfxYVop5rVeMCcN5H6cNQ91cxfz/lrfIN6SXj0n2odJv 1l7EfpN9Zwos30Qs3zYYS5kmlhLEMt5gLJM0sdyIWG4yGEu5JpapiKXCYCxzNLHcjljuMBiLGGtU WObhmLIAsZuIZYkmlmrEstRgLMs1sSxDLA8ajEV8n6iwrMZvjzWI3UQs4ttKheVJ/MZah9hNxPKM JpbfIpYNBmMRPiUVlhfxW3cTYjcRi/geV2F5FdLvIe1C/ZiIRcwlVFj24hyjEfMmYhHzIBWWwzg/ fgP1YyIW4UNVYXkb7etfIdUaikX4f1VYjmOb+RtiMhGL8F2rsJxEH+l7iMlELMLvrsLShP3xx5C2 GIpFrBmosJxF38Y5SC8ZikWsd6iw2Jb7jZBpuf52E7GItRoVFv57pafgfInl+hpNxCLWmVRYci3X P9rLcr8zTcQi1shUWPrCfTz4vD+cf24oFrG+p8Iy2HLnlEO4/9hQLGJtUoVlhOXGf1xruXN/E7GI dVUVlmK47wdwHgfnWw3FItaEVVgmwH3FPH4azuMMxSLWs1VYJuO6zA8sN07CRCxirSdVLOpg9PNz n8XVkP6AMWpFcOVq4DYMEs93Rt+/wCd8/6MlfN+CK6Oh9E1IPN8Z1wMEPrEecJ2ErwyuXAelEkhl huKbpIlPrBHcLOGbBFduhtKNkCYZiq9cE59YN5gm4SuHK9OgNBVSuaH45ij8vALf7egbuRP7I9up 2wjlQ0A75OQ74/qCwCfWFxZK+ObDlYVQmgdpvqH4lmjiE2sO90n4lsCV+6BUDWmJofiWK3z3At8y 9PWtwPZqO3UboHwQaAedvKlrE40a+Fajj/VR1Lft1N0H5QNAO+DkTV2vaNDA9yT6XX+F+radunuh vB9o+528qWsY+zTw/Rb90M+ivm2nbj2UG4HW6ORNXdeo18D3IvqmN6M8bKduHZT3AW2fkzd1raNO A9+r6K/ejfKwnbp7oFwPtHonb+r6x24NfHtRFvvRz247dXdCuRZotU7e1DWRHRr4DqNf+0/oe7ed utuhvAtou5y8qeskWzXwvY2+7r8gTtup+wqUtwNtu5M3de3kZQ18x7GPeRf7GNup+yKUNwNts5M3 dT3lOQ18J3F9+3/wd0m2U3cDlDcCbaOTN3WNpUYDH19j4f7vTyA9jfg+giufQKkJEs+buu7yCw18 Z/HbjP8m8XHE9wVc+RJKZyHxvKlrMcs18PG1GP6NnYWx0LZTdxmUVwBthZM3dX2mUgNfN4zJ/wqc qxBftrUAylVAq3Lypq7ZVGjgy0Xf89fxN9TO3hrWrVCeDrTpTt7UdZwxGvj4Og73DQ5Av7Tt1B0N 5XFAG+fkTV3bydPAx9d2+G/Fh1ruXja2U/cyKPcBWh8nb7L/2uv3iXL8eqr9AwqlWPYDGMv+B5/9 9RlSvWR4U/3+UtefXRhALLtfWMo0saQzlt0vLJM0saQzlt0vLOWaWNIZy+4XljmaWNIZy+4XFpWv uTCAWHa/sCzRxJLOWHa/sKh8yIVSLHsDxrIfMBTLI5pY0hnL7hcWVSx7YQCx7H5heUbh5y6UYtn3 4ly/0VAsLyt82oVSLHs9xk42GIplp8J/XSjFstehb3CvoVgaFL7qQimWfQ/a1+8NxXJEEf9dKMWy 78JY9lpDsRxVxH8XSrHsr2Is+y5DsYi9EFRYjmOs9N/Q32wiFrGPgwrLSezz3kMfuolYxB4UKizc z/o8xrL/zlAsYv8MFZaz6Cs+h+OriVjE3h8qLNx/+s8Yy/4rQ7GIfUtUWLivdDXGsq8xFIvYc0WF hftF78dY9mWGYhH7xaiwcB/o3RjLvtBQLFcq/NWFUiz7rRjLPs1QLCMVMdOFUix7McayjzMUi9hj SIWlGP3PPJb9ckOxqGKmB/0/8icHsTdKUP7kIPZGCcqfHMTeKEH5k4PYGyUof3IQe6ME5U8OYm+U oPzJQeyNEpQ/eVAn8yc3Mr29UfahP9lUH6wq1ljeG2Uv+pNN9cGq4orlvVHq0Z9sqg9WFUMs741S h/5kU32wqnhheW+UPejnM9UH28D09uDYizgaDfbBHmF6e3AcRt28YbAP9qjCByvvjbIF/cmm+mDF 3qs6e6O8hP7kzQb7k59nenujPIv+5I0G+5N/w/T2Rvk1+pOfNtifvJbp7Y3yGPqTHzfYn7yC6e2N shz9ySsN9iffw/T2RlmE/uTFBvuTb2N6e6NMQ3/yDIP9ySVMb2+UcehPLjXYn9yP6e2N0gf9yab7 Ldu673NHxs0GtQ9EEHGzQe35EETcbFD7OwQRNxvUXg5BxM0GtQd0EHGzQe3REETcbFD7MQQRNxvU HtBy3Gwj69x7QAcRNxvUHtBBxM36uX9CR8fN+rlXQkfHzQa1B7QcN9vZ94CW42Y7+x7QctxsZ9gD erdm3OxO9HPuYebuAb1DM252O/o5dzJz94DWiQE+if7n99Lgf/Zzf4JNmnGzL6GfczMzdw9onRjg s+inPpeGGGA/9x3QiQHmfs6n0c/5DDN3D2idGOBuGAN8SRpigP3cT2CNZtzsw+jnfJSZuwf0TzXj ZuPo51zOzN0DepFm3OxC9HNWMXP3gJ6pGTd7G8bNzmLm7gE9QTNudjzGzX6XmbsH9BANLHwP6CuY uwf0UMOwmPIur3fwu4jjDsvdk0haq0jkI0muZya53lV6d53rF4o7ox24bxb1LffvnrcVq/x3173a geWTLDPI+09Gv+b3URb8dxw9xBpQ09tjvn/Pv4wRNP6s65k7ZonjPB5TuL8nMjBSGhkfmRApi0TQ jsJYL6zxHlPQJ8uftdjjPQQtlOI9JjLeR+Q7+9TYRB70eZPRHxpF/yl9nqBZiuflt16Xa/WsY+hz 5e9/xuNZgtYjxbP432IYAvIdBvLNZwVw3hK5KlII+RK4WhQpgVwZ6GACnK8EyrgI7peFSchE6CQD 5RLF6xl4PVO6V+guC8uZmLKIDXrJ9jO87wsPvIKmI1tbIdvJOOfg/DhD+qxzms+6QvNZluXyy/R4 lqCJZ7Ekzxrm0Ua92mUW8uvr8SxBU7XL0gi3jyFgGcMiYUnPsi0ke4+O7Gt5X9iWMcakd7F9eC/b x/dKNqYIm+4j+VFfJ3YmaCqbHoqyFH05HwdrkOcLhKeghRQ8hwPXDA++S5HvCg++SzX4XpWE7xTk e7sH3ykafEck4TsC+Y7x4DtCg+9IwncG9qk5yDeP8BW0cAq+k51+aGhCbxk+tW07De0pHNB3rV/t iffvf2bu30U5RnQjaDpjRIbEswTrXefBs0STZxHhORXrTfPgOVWT59WE5zyst9CD5zxNntcQnsuw 3goPnss0eV5L2uVarPdrD56CFlLqaFir9r4R627x4LtRm29RK751WPegB986bb5Xt+L7JtY95sH3 TW2+17TiewLrvu/B94Q232tb8T2NdTlDyve0Jt/hHnrrYrl1czz4Cpqab2u95WHdAg++edp8W+ut COuO8uBbpM23td7KsO5ED75l2nyv9W08CadhPIkm+bbVuX6hOKLtwPEArlt+hOteKh9BlOS95qO8 33wH0j8g/ZdHn/qOxnz0GphZfAfmm83zUnfm6c5P89kVMC8tgPMwoA+PNM87xbzSlr47ZH+BmIeG Jd+BTMuSrlM7i2rMYTpan8nssjPYYhZ+g/B9gZ9qpy3yuM0FltuffMofyOO5wm56zA1E3s6dxDew H7IqVun47y/s6LPqUrbVurHxcHUPyY7XX8Im8nPjg93Z/0KK59Syif/5Jd+6m2Wv6J6oXT92tbNG g8MOa4J7bZBENz4eD3qK5b91pLprrM+qGZkDw029alnseHcnMZRJy8NKtKd3Y1NCvB6vfywai6yD Z27d9lo1PzfAmdMmOu/xWvUpKP8dEpfVbLbaeXYXqY0wbAdcLyg7Z57A0+zFrnukv+RXn+zwcXms RL2so+MeXrNT9AOcT1FkILTy77Ty+8l6L5Ce3fH2UDOLy3bA8e4OtmT20NS72R4eQnsYaZ+q3vMf X4OGcKp6fOZXWS6c66Ox3o1wjacef/28UrYHXv88YslN2FTNrGb7MscepiCPB1AvKz3sYWUbfLBh o22AscEgy5PjP688B6nfdZ87eu6L7TaEiR+aNpAnbEDoUNgA7wOyoO6oU4er7a1Hqrc0Ha7mfRJ/ VghlxwyxgSeQx3elbw9qAw9gnWQ2MLuFr7qlt9przJfHeZuM8W21n8403nP+A9BHFPKwT1k3BdLz xG91Ys1yb3F/TLqf7nd/qcZveMTvlwpw/sbXFj/zQYZZ5B1lfKrfL30D0gf4LmcMexehQ0v6RvD6 /ZRsv2L9exDGf6nWAEPoK+R1xmEdweMaLAu7CGnakWyrMmahf+7b+dDxP7p/Q0d+R+r34vOBUpTL P+E8Xe43StGWslLMHSucNZ950KcvYnPh30zo1eT1J7nvsH2aX2YR+cj6UrXrdNpke99F2GQshU3S fkL+bczHKfoHYYeriB3eR+ww1W8JC5K0N/G3R5ag7fG/Kf8p6vs+uPITKC2BxPOp7JGvn/0MZbLe wx5/jvYYSWGP/HuoCqRRyWaBLVa1mItmSGtofuq9rWNLOm2wve9CxzZLo08StvScpg3WExvcimWd v/0i252IM3oF7W4b9nlefaSXvT2I62QfoO+T2lsD2ls0hb3x7zJuaZX4fz67E3rBlrYm58M+rtuQ NdG413jYETbY3ndpz9j835o2eJ7Y4MceNpjM7sRY+yGmT9pod3zcDVkuZh4nQO2O03TG3UVgcbPY UjaHLXZsTx5vaT6cRh1bBtmbFUCfJ4+7/O+I6djbt62W9jbc0h93vfo8/ve9PsQ1BdV33r0YV8ox V3jY2xi0t0yFvc2C+Xsluwts7W7HD0Xng3aa+jYrybd+R4+vIRZ87Iuf79LW783QBYzRydrFYIwV E/YyA+ervTBJsQlxWWYFHvO/ZDJTzQmpPGQeUWynOfCQ+T3deJtUPOW6Mayb8GQr6iaTnZcMKNZS 5u7XweVSckPpoMJid98SF198NLp74nK+FPWejXVCxc3P7IY6YwI/pP8DzEidl5TBAAD= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image048.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhJgHhAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAQABAAd AdkAhAAAAAAAAE1NTWhoaHx8fIyMjJqamoCAgKenp7Kysr29vcfHx9DQ0NnZ2enp6eHh4fDw8P// /wECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwX/ICCOJBCcaKqubOu+ cCzPdG3feK7vbun/JlRkSCwaj8ikcslsOp/QqHRKrVqvyhTQF8B6v+CweEwuhwNb0cnMbrvf8Ph5 25Xb7/i8/ov+1feAgYKDcn0kf4SBDolfD2APC4xVhiaSWI4IVQsDmUUQRgxOBXmfRAkKkV4QCwpI nU2OgicjiJZTAg8Bjq1PDQIFoUaoRA6vS3WlYo6pwqkNBgECj7xGuk64g7OVtksJTAIODgsNTwrG xAYGi04PnwRDBdRgBQ8GRw7piwgL60YP/UUW2EvyQB4RcAK5HZlVS2HAdxFexco0igEDb0vWPRgA UUkujK4CkBsVoUCAc0kc/1CL9SBYBINLCGArkgmaywiOGPwiCLNkBJ0kY+EkglJPCodI6JEksGuA N6YkkxFhoKDqriIEOoYKBWGrTgJShxSLNQrBRQPMfvIKFe4BSQVOSw6IpNIIxq0Rug5hMDAW0wQP 3n2Ci3HA1KoKHhT0BI+IYcIlBaRimk0I0iIOAhQggEAB2AgGGgzwDGFgZyMOFLfbiJjwgIsBEnAy AKwqNHBDyEVI0I82tAENqP0ecCJB1gQYQw8oEDqTAwGdzQkQoCBB7Nm1T8slbeBBps6hCYwjGSG1 YggNQEZsZW88aNHMIwSg+lmW5ctECjYoPgQaf2fkJeFfAASQk0ABkiVowP+Bmt202xAIBDDAJ/tR t0ABpUCAQAIMIKgAdAVM2B8KJsWSgADRhLZANAsoyOBA5RUHAXGtNFCASSjA6E87RNgYwQK5BGDP gARwYpJ6gByFnxM6itUkGcUQAUFHKRkwo2FLPGkFPkhwCZoUXiIxEECEKLmkERuOMqWDD8zERmYL mhRgEqM0oBsSa4Lhyz9YDtHmPwQ4yMSfeAaqkJlOPHZCVYsC0iaV5e30hmfMCYpET0U8+ggnfhLz i6ZQPDennwJAKgmiTEQYwYQOFAlBq2fGKqsXazzRUDVZ3OdEF3XUeuuswAabRK27HnOMrk3wOoSv RaBwwLPQRivttNRWa+3/tdhmq+223Hbr7bfgghtAt+NaW660RKDKRBcTXgnBjAsJK6+wxBabxREH pIvsursVZ11s8c4rcKz18musEfkuuy8Yvw7s8KkNBzwsEgnLtzAfD2fMzcVIRHxrxeoyrPHIjHAs cccU61vwGSS3HEjIKB+MsMoRX1GzyzibAXM1K6ebBMgm25zz0IUErbDMlgHdM8ZEN93G0hPfq3Ad St88idNYlwH1yScnTbPOWYd9htXLylz2EFWDLfbaNpMtn9lvo/211mzXPcXWuJqNSNp02+33rm57 nLfcU7stheF/r413s3DvPTcZiCce9uI+S302EXxDLvnmPEPRcMG1ZD5G/+ScE0355QvVG/rjo5de +ulxR4064RbDfrjrm8NeMyINiS4G6bi3rHvj+LL+e/CJD2957EX4zjLyfp++O+PFF6429GwrL/vs tO+MBfDYO6x9zNx3b/QR/zIaAEzghy/w+IOXH4HzTUgTgQCsmtq++/JKT3zK1pMCA04wQO7tj3/A gl/8Gka/bwyBOKjjgQQnSMEKWvCCGMxgChq4BCzh7119qhwCnea/5TFvZgGMgk4EABuAxW+EOVMg 9eRnPttF4YAwXJIMZxcxDn4vh0M739b+YDIfCg2IOBOi4Ka2BCNaAYdI3JgSl1dE4z0viiPzngjJ V7smWlFkWMxiCbd3M/8nXi2MGjvfCWdIQ8x9kWlofNgYuWg1M1IBinEsE9k+xzsn2PFueRRf4Ial Oj++kVaBHNgcO7dFL6YwCawgk70S2b896u0JPiSAAXQCSErSa5BkhAIHHYCh/XTSkwm0JBVFecj8 /ON2qJyVsibJNbcZsQDWUUABJGnCWOJnh8wznBGrEwAImMNzvpTVIhcYBSfeyAAIEEqyknmmWU4z lM1sJZq0tD1qOmSZbEScEVOTH2R68zLg5KEUfMiAAoXQVudECjD7uM5WIgAt9rthPL+pyqipsXna LA8vDbZPW6QzbloEYO3w+MKC6tGcMUto9RY6BQcQ5xSNaqhDX0Y5qPH/zobzC+gRdvnAV+lvoyVb HK9+Rc8p+NCiwPiSfExSwDUyFKVt6+jn2JjNRxJEGrEIwCJQFEENGvWoSE2qUpc6LpFK8zMfhJdG cYoHaxK0a1Zwok6S0SYW/gtJa6RqVTtKSJ7W06dHmNE9i9JLsd4hnYXMqkj7A9a2ujUOB21pFf7o gLDA7a5Fgyc25YrWvDRAmqcEbGBpyUws0K8goyBnYhULh7ya1aVvhEsDCICcyVL2aWHlWji/0EAI GEcxkbvpZ3MlWDqS9pCfqMeorrlaN5B1sI5940UWsQBT0ba2OutnvCRqyMLuRTHp8Cxwfydc6hG3 CU7srXKXy4fmOvef/0wwYmC4+VfqVre1jQWDE30xXe+2LVk7bSMVnEjK8pr3bioNrV5fa9xMpfa9 DLstrohIBifmwr34tdUydaVa/943wDm9GUv5219tbna2V0UwIBW8ygbXtxQxhaWE7xhf15aBgwjg rW8jvGEBM3aGqnVjfRmwiP9quMSesxpLLyveQ67DlC+GMXpPHME2+BC5EO6ujlFG4Yk9d73aVMwd hww4HiMUu5it7xIg0AUFZJTGTPZZkSMK5bNSdAoFzJ9os9ys6c24kR8OKGIjMsuGpBiweLPqaN/g 3yNAsFdlZqqe98znPuu5zjyTEAjHnGUhpm6+bGAvyr5KaCYbbcFoTv/0XAFc4kdb7s0/m3SOyazF M4dW0lLGB28oveGgefrTZtAueTft6C3vt8te0C4BMCVkGHeYyCCl75eXsGp9kvloJD4brGOdZM6Q Gr+3Htywcyvl3OQToq1e16kxDd2AGvPY5h2iTRFthwYi4EYhqmuwS+1qJqqXzm/0K6sRbGnyURuT mvZ1pdstsXfDu9lP1HGncbuHBm4G3AVIi5Pf670ZH9nHb1QyUWjNRQkXnMv2ZiW+c/POcWe73Jdb toV3rYTUIKDitfau4Gph1Yj3lONKgACPoB1gj56QwJb447qpO0TQ+crkXj44yy8u7dSdu9/x3vly Td0xnXc76OAdOtH/h5vro098yRfXdsA0DgeZy5vmFyvkzfFj9Z9MhypXjvRnl4as++Cc2E8vAjgy I+apKtajNsfzmbouFpMYEOvHOnTTgZ52NCE0z34OvOAHT/gZdL1DJZUqllH68KnvHRBdR1Fx+ON2 xnPsVnIPFt0Hbvm4f3QNjx/E5n8r1qy7GfQDG73FCwp3khvdFqoPuTdX2ssVPCz2dp09zLZ+89Az Avfd3CeqUB9A38Me6Zz3pQoYp7rltwz4Ddf9gj9vfIdAv9GBtH3GbY7ykV2/8nl0/tvMzgKnfX/x cRQ/sGl2dkKcX+xRBH35dz3/rL3/5wjU/pMLd5Tqz+r+qAZD6kd7//zXfgoBgAYoSCtVf/2nf3+D gEA0fwsof+q3ORAIPeSHKGbigK5zgchTAwtVf8HjgX+TgcQygK/nNySINSujfS74ggmYeshHeiQD OhZTgAXYAom0gpXkes2nJDHgTTz4S57HfjewUapnZeuDfaAVaE6YZ0aIA+aGhDO4KibleD4YaNQH eE+oMk54hChHdZSkeplXOWVXhKyjVFwIY2RYVIX3hnAYh35Whe1Scb1CYJYxgWt4hy4ndMGXe0wI foIIf4GIfoZIiMqmcYw2iIh4iPj3iKCUfIwIiX74h5YYfZcmhpeIiZs4iQHoiJ/YiKAYipRYiYVY it33a8GTgqqYNf+s2IokpImwGEOyOIsu84q2SIv+V1ZOYB2WggQEsEdGM0DzkXc3yFr98ovHGAHB 2HOpeIzE+IsrEglbM43JuATWyIwNY40wY43RiF672IkBAXJHkAsDdQTkACvrYhHTo15/sAkHY47X lI4jhlDsmAQM4GIRk491AI9KwI84IVT/+F/0iI//NR81dSzhyIlJcSdMoCFRYBbJEgrtGIB/UAAO KTEQeVUS6U8UuQT2czP2g5H1MwQbqQT51JFJIA3FqGC1CIig8GxMwHB25gQDhAD1mHEExUnLQ5PM Q45nc5P12ACpUDNEuRcyiY7MwHBH+UC8FglCCY725jYJ2QTihgT/DMBW90BSSLOTSzQEVylCWSkz pHSOVaFeZ/kTNZOWD6IEaTmWbskLZSmVtkU5KKKMNKEOUEAA59gsXJkrCwiY91OMhNQF99SXXcSM 5ygEmnGOwfgOHPOYg4mXknmYSiCZinmZBDJTiNl3ueiKL/mZGYOLolmDoVmainSaOdQAnXkF/bBy iqOaCMQAHJEM1/YSGUkFPgIhPplEsikvufkmlFEE1bEI6qYEwVke5AEkdUOaGRMlBMEE0JkEd/IJ zyFwrzSdRMBZdEKO5KEaAheLC+kwxrEjRRAMjrALm0Em62A/KicWAoAR6YkTusSXRWAA9mkKELEP SVGeD4Ac4iE2/86ZMe+wIX6BE4ESHJuxCuJhALoEF9ZwEAzwDH4SGi2RFajQoLoECcTBEqhwoAba AFSBGfCwIQywAGbxlyz4m8LSHR3aH46AI4FyCvHJGSjAmmhCQCZJHBJCkbHBGQRgEqHRD8/RJy6q C9FApGRBHDiilwLKosFiJS+xDlJqBVU6BlKqAJLkHQ3An1oaPVA6K9/2ElgypkSgok1AGzjBXVQw pnCBJ9PRCv5oNwM6MJvlAM/gCHdqBfVwnFdwp3nKBIEKpuOJmj0Yg4YqRYWaqKm0qIyqTGH6qES4 i3JYqZZ6qUf1jGckqQRTp4jKqZOAAtsAR6A6qWiARxF3gpCmNf9vRnaBg2mOyos9xlpagKqAiUPc dm4VqVEyZnGGI2NQlmK7ejtaMKo/VJi7s4F8+HcE+Gh8xIfLR4H84jG9F616GIIW6Y55SIEyIG3U OoGMyZhMVKxQBK40wHyxs63jpyx5GIVB+Hc3iGfEl4PvKnfiuq7pWjbElwPbt3/y92Q+CILMCq8N WIC0QKr51mZdJK9HwywKmV536K+kaDDs2mbsWmbCRisXa6/9h69Mc7Hjd4zVSgnGuqlCo7ARG7Lx WoZnFLEuO7EHU7ESy2AZ+10oO7AEiEghy7C8t4Bc0D4HJIG214AiyGHgKrIVyGFfM7I5uIyhOq7m mq6yyK0WS7UqovqzsPappaqQzZIGmPq1YBu2e5YGQSC2Znu2aJsDZFsCadu2bvu2QBACADs= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image049.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC91dDXAWxRne+3K5/KAYRUskChGjpB9Sg/yIDmhQDFGLBupPpJk2ICBaEAUkyo8T EbQU/4ZC1aKi0GCdiBB+hARCEgImRTswSh1njOKUGcWfdhhFQFTSd+/eTTZv7vt2Q75cNk1m527v vX3vnn3f3bt97t39LMbYNEjxmCZajP3Mmv9OZjC2pBdj6TeMyWHMYjs2MpbXjbEERv5sSHGMdYfy 7xLRht42O5Eax0ABuwxSOiRQ19/KttgFsJ8CKZRS/TEUZYWY+LkFkPLw3L7ZNjsD9fXOTmrazwAd Yj8rO+Tqst1c8bUXZSc0yexs1rSfypr3z8f9xsZGdi7unwnpHNwPQboIUiKkvs3nNvodS0Ys4k+c I19DvrZ8vSzcPwtu/FLY8nqx8DxL0nkJnseP9UMsIZRx/fI5IWkf7FV8SfO1i3Xu20+PFQWPadc6 Xd29sV7F32Q4mdfsOEgPWK6bs+OisvHvOc9IGzm829i9bDqbzGaBp98C2yLYjmMz4NgEdj/T/5uW lLz+wP56t12Ke/O2m9jc43uz3LZ1xicsq1u5i5efX4Dn5cMxfkvFuP2wrK6IYds7kfFw1oYzy9l8 p5wlgjx9ag/2nwkns95PtCZdEeFeeBm+5fb76Z4e7AAkrvcl2L4K5ZPJ+Q/DsROg8wwsE/K6h6au omdznTW1+d6Nffjt9Zw0xzVbk63ipLrnZb+PXPdsDNT9bDYTarp9f1CXq3ndO7DfHY9196n7hqSm ul8t6t5O9ur8smT/up8dKmcFZ5SzzUkt6354jOue3283rD9R99yXLoxc9/1o3dvS/plSW4t2XNiK X+tYMO3kTZ12ItnqzfbaqiPbSUhqJ73a0E7i22m30z1O+2D5/Gj9sR3Dvlk8Cx1Sv0InP57pcy24 n+JMn+vS57P8PiDeYRIwiXemNEyxfH5nSvefKtWJuAfx3vZ7UHhSuocgbMPIPenahuLUtU0ke9yB 708DEHsBnFyH9TIAjhRYPNXBfp2bp/ZhEewTyzp02liHA/AZWYDv0xficY7vK44Zjv+A+RQ8v0Tz fXYoluG6S4iOhUS+kMgLibyQyEcQ+QgiTyPytIDqWe5HovlqpHoWPhMibbq4uNi3vVo+uHXsQeun TspzPTTfkfUXOo36021bcntvaz2JepDfD4WOMPOvM1leQuQlRL6QyBcSeSGRFxL5CCIfQeRpPjZM i2Bj4QOyfG8UfCOJfCSR307ktxP5fUR+H5E/SuSPEvkyIl9G5GuJfC2RVxB5BZHvI/J9RH6IyA8R +XEiP07k3ayW8m6k/vsQeR8iH0zkg4k8l8hzibyAyIX929vG49rRR4p3jEJ8x+jMe+mP5/D3nfcM upd/tHwPL5bf20Sf6ER5H3QiPDv4OOMdjT5xOJ4n8jkkn0fy40l+MqQ9Un4GyT8CabeUfxxSrZR/ GtIuKf88pGop/xqknVK+FNJ2Kb8F0lYpX+WO3przvE2sk/IHSD/+KaSVUv4wpGek/LeQ5kv5nyBN kfIOVPqNUj4F8hlSvhfkvwPji3wG5DdJ+cshP0HKXwX5Y6ea89dD/g9Sfgzkt/7cnL8T8v/8qbGR 2t1k+9YQ+1YR+1YS+1YQ+75N7FtG7FtK7LuG2PdFYt8lxL7ziH2nEPveTOybKeW5fX8k9q0h9i1q bGnf1MaW9l11qqV97VOda989xL67iX1riX13EfvWEPtWE/vuJPbdQexbTuz7NrHvRmLfdcS+a4l9 VxH7riD2XULsO5fYd6qU5/YdK+W5fYdIeW7fc6Q8t+8XjS3tW9bYsfZ9p5323U3sW0vsu4vYt4bY t5rYdyex7w5i3wpi363EvpuJfTcQ+5YS+5YQ+75M7Luc2HcJse98Yt9pxL53EvteK+W5ffv6PJc7 s39ub/utIvatJPatIPbdSuy7idh3HbHv68S+rxD7Lif2fYLY9yFi30Ji3xxi3wxi35Okf95D+ueF pP1+5tM/C+7KijKW9fueyPD9MBW5KW6rQSz27/IWeYf045Vk3pS+s6YR/430nimwXI1YRhiMJUcT yyjEMtpgLHmaWG5BLGMNxjJeE0s+YvmtwVhEf63Ccjf2y1MQu4lYZmhimY5YHjAYi3hOqrAU4fNx LmI3EYsYg6mwPIbP9kWI3UQsYvyowrIU3zOfQewmYhHchgrLCnxHfgHtYyIWwcuosKzC9/vV+G5o IhbBKamwvIFj0TcRk4lYBB+mwrIJz+Vj6W2GYhFcngpLJXJA1Tg2NBGL4CFVWOrRH/m327cMxSI4 VBWW95F7+xdyMCZiEfyvCksD8oYHeUyOoVgEd63C8jmkpyB9CelZQ7EI3l2F5Qi+i30HaYGhWMQ3 AxUW/o1sEvNigu4xFIv43qHCYlve+DgBtjcZikV8q1Fh6Y4c3tmWd10Tsai+992B8WeCUxqMzxrb Lbsb8vUgq3f3uyLPJPAJnukaCd9wOHIN5K6GNNxQfDma+AT3lCvhy4EjuZAbBSnHUHx5mvgEHzVO wpcHR8ZB7hZIeYbiG6+JT3BUBRK+8XCkAHL5kMYbik/FWwl8gre6Bzk42y1bC/k6kNW5+12RyxL4 BJf1oIRvBhx5EHLTIc0wFJ+K3xL4BL81D/3Zdsvugvw7IHvH3e+KnJfAJzivxWhv2y1bA/k9INvj 7ndFHkzgEzzYs2hv2y1bDfndINvt7pvKjdVo4FuBvMCLaG/bLVsF+VqQ1br7pvJlVRr4ViGfsQbr w3bLVkK+BmQ17r6pHFqlBr43kGtbh/Vhu2W3Q74KZFXuvqm8WoUGvk3Ip21FjtB2y26D/A6Q7XD3 TeXa3tbAV4kcWw3itN2ymyG/DWTb3H1T+bcyDXz8nWw982JENyG+vXDkPcjVQ+L7pnJypRr43sc2 +CG2Qdst+wbk14FsnbtvKk+3RgNfA/a1nyFHabtlX4N8CchK3H1TubsXNfB9js/Kr5C3tN2yz0N+ JchWuvum8nlLNPBxPu9JSEfxXcZ2yz4J+aUgW+rum8rxzdPAdxLfxU8hX2m7ZR+B/AKQLXD3TeX9 pmjg47wf5zATMU7SdstOgvxUkE11903lAm/WwNcd+c9zLD5n3MOXYt0I+TEgG+Pum4hPxCmr8KVa OO/A8uYcuXOJrUshHwZZ2N03mf/0m0thkbmSkeogHEDcXbxUztGYz3m6fGg4gLi7WGHJ0cTSkXF3 scKSp4mlI+PuYoVlvCaWjoy7ixUWFX8ZDiDuLlZYZmhi6ci4u1hheUQTSxFimWswlscVHGtYirvb hXF3ewzF8rSCTw1LcXc1GHew21Aszyu407AUd1eNcXe1hmJ5TcGThqW4uyqMu9tlKJZSRTxkWIq7 24lxdzWGYtmiiIcMS3F3O5BrqzIUi5iDp8JSiZxoNe6biEXMH1RhqUfO9l3EZCKWAwqONizF3W3G uLuthmIR8zZVWBpwft9BbDsmYjmsiO0MS3F3pRh395ahWMR8WRUWztP9DePuXjcUi5jrq8LCObmX Me7uVUOxiHnKKiycf/szxt39xVAsYo61Cgvn2p7EuLs/GYpFzA9XYeG82sO8nOXxxCZiEXPbVVj6 Ihd8CWzvNRSLmJevwjIAzruVc36WF3NmIhaxpoAKy5WWx1lebXnzmU3EoopTDWLuc1AcbBBzn4Pi YIOY+xwUBxvE3OegONgg5j7HkoPVwXI3YpliMBYT5j4HxcH2/z/iYPt3MQ5WB8tSxPKMwVie15yT vgI5vhcM5pNf05yTvgq5sdUG88mlCj5ZnvtchRysqXzyFs359ZuQq33bYD65SnN+fSVytdUG88l7 FXyyPPe5AjlYU/nkA4o4YHnu8zbkYLcbzMHqrBXQgG3rYAesFRBLDnaz5tznjcjBbjGYg92gOff5 LeRgywzmYEs15z6/gRzsmwZzsDrrHnAOdg1ysGuZuRzsy5pzn1ciB/uKwRzscg0snINdhhzsCoM5 2CUaWPoiN36Jwdy4WDtThWUAcuicg13AzOVgp2lg4RzsfcjBTjcUi1izVIVlpOWt8z/K8vglE7GI 9VZVWG7G3xS5BbbZhmIRa8WqsNxueb/hkw/biw3n+du6DmpnxmYHtVZFELHZQa1LEURsdlBrUAQR mx3UehNBxGYHtbZEELHZQa0jEURsdlBrRsix2V1hTdTOjs2O5VoQnR2bHct1Hzo7NjuWazx0dmx2 LNdzqNKMza5EzqaambsmaqVmbPZ2/C6wk5m7JmqFZmz2NrTJdmbumqhbNWOzt+B3AVPXqhW/a6ET m12G3wVMXav2U8145gbsJw4yc9eqFb8nohObXYLfBf7OzF0T9RXN2OyX8LvAKmbumqjLNWOzl+F3 gRXM3DVRn9CMzV6E3wWeZOauifqQZmz2LPwuMMdQLOK3f3Ris3+H3wUmGIpF/G6RTmz2KPwuMNpQ LJcr1t2VY7P74ncB09bdNeVe3uvkexF/4nec/X4b+kzpXnSOx+L3qNuKo9Djvt11XXox9e+hWxGu axP9tzHvu9FEvFfet54n+PAj74+8/aEPRgoZv/6vOWCpXhvxj/N4I51cZ6BzkzPa8Wwmfl83TuMe ePk5eJ35PvcgZKEo98D50wEs3dUfp7gefzdcgDq/9rmekKVGuR6/z8tdzKOddJYJ2/XOYCcM+zfA 0UHODbA32ukHNZLOfgWS6x3v3uR6ESke79PB64o6i8djtnRenOeD7tbBlKCBmdfxN6j/Wx/M38S4 jm/Ddzyu84TP9YTMwuuxCNe7grX8DWO/a3Ge8gfUd5bV+lpC5ih8OMfhtrscrDbQkW1gY73ER7mP zuw35N9y1un/TLqXuICeEbr3Fak/FT6djrxFBo75ZT8TMpVPZ6EviXaZhmOnDOSsZJ1CFlK2k6ym vkXWOw/1PuGjd56G3sER9N6Feif56L1LQ+/QCHqHot6RPnqHaugdRvTyZ+cv0K5cbx+iV8jioujl egaC3iyp/443zG+7Uhvi9bifeb/z8DGxh5Cp2tBAyca34TdeXi7XR+coTZ2DiM58LFfgozNfU+cQ onM6lnvQR+d0TZ1XEp2PYbnFPjof09R5FWmLy7DcSh+dQhZS2mhgqza+Fsuu99G7VlvvoFZ6K7Bs rY/eCm29Q1rp3YdlP/LRu09b75Wt9B7Cst/46D2krfeqVnqPY1mukOo9rqn3Ch+7dbO8suf66BUy td7WduuDZTN99PbR1tvaboOx7AgfvYO19ba2Wy6WHeujN1db71VGP0NMHR9HwsFjUj9A3vZwlOeP 7pj4I/w+/SGOKw4ROwtZT8X48EoYTYyCcV/zOFGMBPl4MZ0NgHFiJmwHgvwKx8Mqxnzy+EMeL9Ix nzwudMgY0u9dpSuPW7qCL/I8X7OB63y1nb7I13x4wPL6k+/5BXnsR5yXnvOCFjdy0nIMu5fNZjNd fvj0/i7aeD7bYN1aXV/UU/LjV89meXxbvagH+y+k2aFylvfvUzO5PGVxj6bSO65b6saw4GOHHYFz bajR7vx53P+vLH3/3qLrEi/aWJjQLy4roZwlN/RwE8M6aflnNbWnlKT8EC/Hy3+UlOy8ANfcUFZX xLdVsOWyPPc+6oqOQf4wJMcdkyx1r91NaiMM28GFrKnu3LEBT5PmuOZvskMI+wE+tjmLeb9HeAGO w+R+4Cw8ZkfpB7ieQU4/aOWjHIe0Y9numdK1O98fXprI6/bShh7uPUTyB/u8Zn/4I/rDMPtYUdZg aF2Jx4pyE85jqbBdnZi8bxgc46nnJz/OlP2Bl29ELKlNPvXSxGb/Mscf8tEfFqM/POXjD0+1g0Mz ywcYuwzq8vPcH2f+DOniG3907dwX220IE//T9IH9wgeEDYUP8D4gEcoOP1ZfZG/YW7T+SH0R75P4 tUJYd8wQH1iOPjAWfWCxjw8sxjKRfGAScsf8yU/ZY1t6nuvwxG31n670vOd4L8V6Dvn4p2ybTOl6 Iq7faa73Fuc70vl0/fXzNeL9xVwHzkl9hXMefohBHcaTe5TxqeY6XIDfMvi9nDDsXoQNLekdwW+u hey/4ntsb/xeofrmFUJ+MAW330o6wpgXfhHS9CPZV2XMwv6ZGM/SH791yPdIea/5yLHweuHf84+R fkPIEqOMHQtc/nk69Omz2FT4nwC9WhyWscl4wY7R+DKe1I9sL1W77kifbO+9CJ90ovgk7SeEP92N /qTyw3nED2cQP4w27ygzQnuTf+vxCPKIR5n4rccjkD8KsqPufjR/fAC/gX6NzzTqj4+izInij/x9 aDZcaSabCL44u8UzK176bhlLu7f12dKRPtjee6HPNkujTxK+9KKmD5YRHyzBvM5vkch+J+Je1qDf rcU+z6+P9PO3RRiD+jXyK9TfNqMsKYq/FbqxChPQ32ZCX3iPuyZkPPlGbpN3plj3g/I8xFAn+2B7 76U9z+ZPNH3we+KDX/r4YCS/E8/aL9Dvvmqj383H+IOvMZaO+t0JzefuLPC4iWwum8zmuL5nk/gA uwP7PNnGlkH+ZgXQ58nP3QstPX8bYrX0t19a+s9dvz6vn+X5XthSv+fxdXT5PHuO+Tc+/jYMZQkK f5sI4/eZ7D7wtftdHoqOBe0O6tusCO/6nf18DbHgv4nH8l7a+r4ZOo1ndKR2cRnGrQh/4bGZJ7F9 pLUcwxfLdZbpM/6LVGeqMSGtD1lHErbTkxmMLenlcefRdMplk7FsE5OtKBup7vzqgGLNwZgFXi83 jMnpH872Yko8fMXXIt1TLO/noN1TsEwou/ma3dFmDOV8/3/gH/F0vLIAAL== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image050.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhJgHiAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAQABAAd AdoAhAAAAAAAAD8/P01NTWhoaHx8fJqamoyMjICAgJ2dnb29vbKysqenp6+vr9nZ2dDQ0MfHx9TU 1OHh4fDw8Onp6f///wECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwX/ICCOJBCcaKqubOu+ cCzPdG3feK7vbun/JlRlSCwaj8ikcslsOp/QqHRKrVqvyhTQF8B6v+CweEwuhwNb0cnMbrvf8Ph5 25Xb7/i8/ov+1feAgYKDcn0kf4RuCk8OElQTchIKkF4LDgaURBSJfIeccA9NDgQEmROLFQoOShQH bqcVpwsQX6ELjpquSxQLn0snI4i+U7hLBqtKEwXFQwoLm5lJB71fkgfRzhQGB5NRyNJGEwffSaHD ScAm51UMjuRFDg8MSZAUA7RFEpsU80gUBBIOECjg5F00Zvk2DUBlBFkBakUEJoEYUaKSd+uGABOW 0QkDSxUGHFlQ4MGaChQk/6iMhctev02OrBXYZKTAogMQChgoYq5CzIAVSA4ZOGQlEVowfSorRlNk BQMziQhlgC+lSn1IXFENSrBCAV1OOxJJIRaKBAIKjunyOuSjAggvr/o8JuHBAW45IRiAcEACBAIB WqI0B5gBwwMBCEDI+YDAg14f4T7Y6bOkAwUCFRTQy1dCu7EPHLiSBMERQQYGFDxAZTWCYVVDuo5b XSEyVQOW1pYlW/YJBAcnehpwBDgxvnDFHVc4waBAc8THaFagJSFA34VbfSpgYDIAhHsDNhUvQIBy BcQBSiJu/jwARQbBUQ4gMGR48QEIJSno9tSRggD4VVAcA+UB2NNuQvQWRf80mDQjHRh1DTEBfUf4 pdmDRSiAIRUMRFNEgxo+0eARISp4BG8mOrEAA6swoMtfZFBgHWIUESFJBQcWASMW28xlhIupUNgE kEfsmGIRKB5ZUFSXIATGaiUeQcGGRDSJhQQjRuPATFaKElVDwymJZIJMnGRSKGeKqeaahCT5i0bw LRcnm3TWaYebWWi03J4c2ennnehA0acRgwpKZpl6dqHon4ziMWihJzYBqRN4BiqnonOOGQACnHbq 6aeghirqqKSWauqpqKaq6qqsorppqK+6WmqsrSKw3KFZrJFmmkhM2uivUjwaxaS+LmFrpXwAq6wX wgqKqBXH4nrGstRW0Sz/pZJeEe1JZBRb7bdjWYrtm8MmuK23U6ALLrXXjpvnsHpWcK4Z6q77a6Xo civuE3XUMW8Z9drLKL786ttrun/8263ADI8l7Z78PhtsEQqPEXDDfvZpMLnvTkxExWJcjDGd7WbL Mbwf37oxGCKPvKbGKx98srMUq9yyxC6DC7O3xFIhDMjT5rzuzsX2nK4RQLMstM774ty0uykjy+zS 35Y8c6RHI20zvVRXa3XHT0M9RNLJdr3s1zJfbbLWUmNxs9kdoZ022BEfQfbUcN8b9t7hZs32w2Xn PTDfWNMtdtSA4y34nxrTnKvff8es+OJ1yl34wQEPerfblGdMOKFOH464/+Scd175532rHfro9Xb3 AK+Xm65m43WrbvvmvULwwAABZAq67C+jnrrwvyeB+xEPPDTBonMDf6TlSK7tOBLHGxEaN8zH7ryJ 0A9PfPRKVI/k68xxxMP56Kev/vrst+/+CuIT4TrsxW/P/fdGR0x6/B7bf3/zhtPem/a3NYD5L0Xd i1cAf5E4eRVwYQdUEO1EBz6UGeuBFotgbxIIMdstsGZtu8LbNBgHDuZveuHDYMhIKJbuNbCDKDSe CoPGwnVMkIEnrN0FQ2iFEdYQYDHj2eqGaLcZKu2HnyAYBb23xMj5EIBIDASehEjE7/HPglEcxMOo +MEuOpFrWUzEzpoIQ/8dMuGKMQzjHsZYRQWa8YxGDJwapQjFOjJRek1A4xvn6CjiQYp0dpQhD63F RzoG8o7hqle9xAcBBTjJi4V0ww09+EIB7rCSXjHA7tIYSTgk0FeKnMLxWjEB4HCyk5I8JCJXCcki DrIoWCEjKg1oyVq6sUyAFCQmz7OAAGCGSvWb5Rs+2UbQXUx8zqDPdvAozDZM0ovqyl4U9PjIYDaT Dc/8XDRzSb04JkECHmrlNUtnS1aWUZa65OYQDmCAdoaznOOcnDnNGcoqoDEBAsBRAHI0z3iKUJW3 tCYzoSC+lECCAQ241Pf82T+BlrOe9vSmjgrgAJEohk8LZWgauQhQhz7/oXou+s6tMNpRjWJxng3M nLYkaoQpjbR3wnifTGdK05ra9KYqQKPu9MnPgJr0n/D0aT89+lGWDuEfBwiFeTz404b2M4cDlUL8 JCCSahK1qZwsGlNLmsJXFuWUWKXUyrS61asW1au7eydXw0qojXGzUOqs4EpfOSEG2BWdbO2VWwEJ 13MW86y7/FCN1ppXJoYQrnEVqiiNKiW1yrWwG22iSr+wuVJatayQfaxiNcvZXD3RgW2zBkouG9TM 3pGsC5UmFnCnAAJsaQGDFadps2lLRSYWjiGcAElUki/T7hG1hP0saCsJCSzp5q+zBegfIUdZlspj EzkBq299CtzSDnWa/0ZtBJb6gdfM0tajkxVD/KK7x+meVrJOBUNBdSJd335XI5ILr3gZO4SKtte7 h5QaRMfAP9J21rzvha9srytV+qLkuJjNa4A3u1/+Grg69y3sgv060pM62KsQLu90zUdB1UZVvQ/u rXkdZj5QPq5gwu3mK0eB4AH/VFov7KuzUuxK4q6zpxk1Ka7atlxD0fiLTGAAdAlCIfr9F79mpbCS c0yF4z0AJgEwpUIJq1EOf3jJ1l2tUWkCHMQkiskMtTIRG8yG6qlkG0Lw8GYVHFQZR7i5rzRKv3xn M5za+c54zvOd0VgHIxO4ym0e8I8vGVf/HpmtMZVUEC38hqkyWsJmRf9WNPHg6DcD+tACVm5g5+tV YIK5mYhQJxsRNeg8Gji9kHZYh3l22zDosbv+DHWMZbtpTtfa0vGUNV9TC4jqteIZuBbmjpco4j2I TwL21bCO9VVdTP+5DMfeTLBneahmr9nZjTZwsmEN6iRzEMtyiHZsP13IREe12IKIn0mm3Ulz5wl6 XoUD7lx0l6+wu9xXhXEu+8UJ3DkWucKGp8EUBcpbt+HVV851pNHBUUIgHOCodPcC0Z0I3B3gK3fh hrKvGVOoXvvZccBdLNvCkATzUd9DbHi/T12BUXBbjTtO3CdLDefApoRALw9jtSVNuHjrgX8TAGfO s1jtd2uzwhl5uMn/YV5LfRe81ZRm+b1rKOanqTnLgbgiBLzDU3KTsOpQfKuJrvgACMPU6xEMNZYn DO5P6FEkV6e54Dq+OpWLBY0OoEXchR3zHo8Jh1BPt9T3M2VN6fnwiE+84mtwxQKkp+tUPiCKgijN q7c18IL3+dS3J/ETDbxocs+25jeOxM57Psltv7vUSU/1RDKw6WvAvNtXP3TnyfpqpCP4n5TuYtmp QFNtRTpJccgo3qMdbkly07CfHvo7GD/ylONNfEvs+X41/+e0T7j/Yq/YvQbK4GPPPsQ7dxL99i33 slfQ87HetRUA35h/0D3gv7V+1Oct+cr/fPVVJrD6Y/v+CVJ++qdq/5hzfb7gfyDHMNwSe/KnV2km gLpmgAcofkvXMO4HX9RXfsKHUeBXfBTYewq4c5+3gE4ngao3erWnM2TBAiTGgARHgh0ILAj4cUMj gBgYgRCodh+4LDOYeipIJvgXfxdYZ8DTgyYYNzn4gBB4fgF4hGJihBjThEP4e1P4exoEhewygi5w g9JHhFGEhWeThEAIA3WWfoIDhpWjhTbAhU7IMGgoQSL4AmUYAztYhNnnZzS4RnE4hzdAYk2FcGcH fSI0gpeXPu8HWYBIYS8YgYZ3eY5YiO/ziCM2Ntm3d4tnhTc4ia5WiXTGh5f4iaAYijSFcHjIJ3HI PEGIiin1aCU1af9v5ordBYuxWIfWRXEQZ4uCxopZhou89oq0aH9tCIxgxHp5iGrHhz+/qIlCg4LK OHcx2Ixmw4zQGI3POI1LI43WeI3V+HpP0Es4dgSOh2K+4jrcyFd14I0n5hV/ZH2UNwTkmARbp3eQ Eo9BsU9KQI/quAT0KDX0+I4MZ4YQZyRLUB2e1hAo0RW/QD4SY2JDIJBYQ5DPsgoUgJBYs0/rVg4Z BillVwcOyRMQBpFKsJEtd5AhaXYK6Vlypy7j8AQTwF0e8Y2gsXYoRQQr2TEtiTPc8S72OClO4StO UZNK4BQ3yQRhkZNLAHehsI4AaXKb9AQl1wRCsgQm0RwLuTZNuS//T3k5UYk1U0mRR5B3awaWOBIW SCCWqcAEZrmVX0kLXTl/zhQFF6kiUCAPT9AKBdlBDKlPJzNuqUOXHWOXS0B4WCaYcYkEghkUTECY LmmYrHEABYmNuOQtvAOTRIAad1kEX1ImjhmZ/OdZIWGP/1gbBvCYJ5GZ+2cdBel4BJE4qvmZ39ia lrkErekVqfl4qBmZwQg8jcAGDyJ0XrONfDQKpUAEsJAKGCEFW1IEhlE1wFktx8kGS2EE2RAL3uAP ulEazLmU1MIPA8kE3HkRxCkfx1EU+7CYXjFuFmEEunEV43kvzQkuQpEPzIAUPqEdF/cg0iGULTEA L1GfMvEgUCEd//FZG+15HlzhE7AlbcoCmeDSFR9hGkVhGZiBFpuxF33xF4ERk6JRFHRhF3hRoZ2B obhAGhD6oBQQDwxBE1oxC5KxmQv6nssSJoDhCGFyHiegHr3jHF8RANGhnPgxAOYwISegHMyho9Dh ANJhDxRiH4FRHQEyWuskICkwmlmondQyIiEyIuzwb1YAIhviGQ6wnKlwmRkDo8BCJK1VG8flok7Q Iz4CBkCSpkcwAQOwEA2plmFopcCyJZvQJHxqBVhiCmDAp12yBIWanbmZjSRjpopag3raqI6aqJAq Jgw6qQLjc6KYqZq6qTTlgGRmqQvqqcYIqo1CNKNKqowjqroYMv/Wx3DOVGrtKFavqgfM9l/cV33q AFbAGX8gWEdgB0lupn1+uKo9JKyY44C5qmyVhIlLuCjyh0not4hUyEOWh4GeWIYtCG789nouSIRk SHzER4bs6FcokKzjggPGhJc2mGadiYM08GUVxm99t4YQ84LxYq9MWHl9CENN+FIkNa/veq9It4jx ek5aYK5VBK3/yn+t+lLb6pbfl2mtqp0Tu60MGHwP65kn9qyZ6KwbCKyJIoTxKq/V1we8eDSoWK8N e7HauoorK2AUC7MW24B4WYykVrDZ47Exa4qqZoPDx4XBQIy4KYUr6IJDOIgXmIQsw44rO4ZFyyxC qIQBmK1LW0BBBMuChlcC1hZmCcgmebkCXOBxqDo4ZegHksapaJu2aos+abC2bvu2cJsDaaAGcVu3 dnu3hjC3dIu3fNu3nwgEIQAAOw== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image051.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC91dC3BWxRXe++fm5sFDbLREQzE8lDRBDYRHFCsRAdFCSBEwIqUQIgSKEAIaVCI/ UxzF8BAxPAXzIIQEU+KjncloR7RDwdeMIjqKMKW2Y+tUO2gHsKWanr3/2WRzcv9/N+TPn4U/s7m7 99w9d79zzu7dPbt7r8UYWwQhGsM8i7FTrOU391rGSnszljxu0njGLLaogrF+8YzFMPKzIUQx1hPy v0NIDX1t9l1iFAMGbDCEZAjALs3KslgfiPeC4Ot18DPIymZj4NfOhJCD1/bPsll35Nc3K645PhB4 iHh6ls/lZbsp/+h+WTHNNDuLNccTWUv8Kow3NTWxKzDeA8KPMO6D0A9CLIT+Ldc2eZ2LRyziJ66R 7yHfW75fOsYvg4JfB0cuFwuvsySe1+J1/NwgxOJDGucvX+OT4qAv/7Ut9/brlNuLjxUCj2n3ulDe fVGu4rcALv4cjlMgFFqumbNzQtj4ezqgpJc4vKlsAXuA3c+WgaVnw7EYjlPYEjg3hy1m+r9FcfEH jr1/xK2XomyB48vskXNvp7t1q/tJlt6t0cXLr5+J1+XCOV4kPx4/fvFwMcO6993AFekNPRrZSqeR xQI9uSCBfT3nv+lHY638oUHKwvPwI9ff/+YnsGMQON/n4FgO+ePJ9Svg3HfAszvm8QWah+amoneL zJrrfN+ma3jxeuc/5KqtWVdRkux53jPBZc8mgeyXsyKQdMd+IMtKLnsH4j3xXE8P2Z+Ia5Z9pZC9 HR+Q+eB4b9kv9zWymd0b2StxrWV/S5hlz8vbDeUnZM9t6SfBZT+Iyt6W4j2kuhbqvNAVv9fZyNST F3TqiaSrFzqqq86sJz6pnlzdjnoS3UG9Xeh52gbL14dqj+0wts3iWegQ+Qqe/HyKx72gPP4Uj/vS 57PcHxB9mBgMos+UhCGcz+8UqfyJkkxEGUS/bS4wPCmVIRK6YaRMurqhOHV1E0wf07H/lI7YZ8HF +1Eu6XBmlsXDfojvd9NUPyyIfsIpQ6edMkzHZyTHcgDb7ESUwbsQ7obznyHeXnj9Bs3+7AjMw3lv IDyWEvpSQp9G6NMIPZPQMwk9idCTIiRnuR0JZavB5CxsxkfqtN/v96yvlgduHX1Q+eyX0pwPTXem /HwXID/duiXX9/bKSchB7h8KHtczb5nJ9A2EvoHQlxL6UkKfRujTCD2T0DMJPclDh0lBdCxsQKb/ NgS+CYQ+gdBnE/psQl9B6CsIfROhbyL0WkKvJfQ3CP0NQv+U0D8l9G8I/RtCj7Na0+OI/PoTen9C v5nQbyb0KYQ+xWptixdaB6M60IaJPkA+9gG6siw34DVz4OIGg8pS37qf7Jf7VaLNckL015wgbfsI tD9VmzUGQp2UzibpGSQ9D+uOSBeR9CoI+6R0KYQaKb0VQrWUrsIg0rxPUS6lX4WwU0ofhlAmpT+E sE5K/xnLINL/hLBYSp8j7WQUCC1DSl+GfhSR7gPp10F5Ip0C6TlSehi37R9a0lmQHiilJ0I6+fuW dC6kf3e+qYnqqSP6qFPoo5boYx/RRw3RRzXRRxXRRznRxy6ij21EH5uIPp4i+niM6GMx0ce9RB8/ k9JcHz+W0lwfnze11seuptb6GN3UWh8Hf+hcfdQp9FFL9LGP6KOG6GMv0Uc10UcV0UcF0cduoo8d RB9lRB8biT6eIPooIfooJPr4lZTm+rhLSnN93CiluT66e7RjJuljH9FHDdHHXqKPPUQflUQf5UQf u4g+thN9lBF9bCT6eILoo4ToYynRRx7RRzbRx3DD9FHbTn3UEH1UE33sIfqoJPooJ/rYRfSxg+hj C9HHJqKPUqKP3xB9PEz08QDRxy899CF8GVaIsY3X/BL/pSFtGMp2JIQXwtxHskifxcvPIPvRaB8p idhbsH6NwJKFdnE7C38/OFxYsjWxTEQskw3GMkMTSy5iuc9gLKKPq8KSj23LfMRuIpYiTSyFiGWZ wVjE2EKFpQSfwX7EbiIWMS5SYVmLz6t1iN1ELGJMp8JShs/rbagfE7GI8agKSwWGPRhMxCLG0ios 9TgmaEBMJmIRfgAVlkbsL7/G5zYNxSJ8GCoshyBshnCEBfqUJmIR/hcVlg9w3H8MwnpDsQjfkQrL SXzGnMJnjIlYhN9LheVLXGf3FYQlhmIRPjsVljN8XoyvdcC5VxOxCH+jCosF1w3hc2BWYFxmIhaV j3k6rkkQ48pMHFfabt5aSNcDrd6NX4xjTYFPjDXHSvjGwJmxkMqCwOMX4/hT4BPjzxwJXzacyYHU RAjZhuKboYlPjElnSvhmwJmZkMqFMMNQfPM08eUjvgIJ3zw4UwCpfAjzDMWnGrsKfGLsuhzbI9vN WwPp/UDb78ZNHc/q4CtBfKslfKvgzGpIlUBYZSi+UsV4XeBbi+PB9WjPtpt3L6TrgFbnxk0d99Zo 4CvD8fF21Lft5q2GdC3Qat24qWPhag18FdK1NYivCv6qIVUBgcdNHR9XaeCrR4wvIkbbzVsB6Wqg VbtxU8fM5Rr4GnH8/wec+7DdvLshXQm0Sjdu6jh6lwa+Q+g7eAvC84jvMJx5C1KHIPC4qWPrbRr4 PkD/wEc4l2u7ebdAegfQdrhxU8fbmzTw8fE2n+P8C/pDbDfvRkhvBtpmN27qGPwpDXx8DP4khK/R l2K7eZ+E9DqgrXPjpo7LH9PAx8flKyH8B/0ltpt3JaT9QPO7cVPH6os18PGxurtXEdc+uFsOrUWQ LgRaoRs3EZ9YW6PC1wOuuweOl1uBeTvbzXsPpO8D2n1u3ER8Yq2QCt/VcN0ozo+vDUJ8faxRkB4N tNFu3GT/i9f6QYus3w8mg9QIzP1HS/kcjT0GF+qPSY3A3H+4sGRrYunMuf9wYZmhiaUz5/7DhWWe JhbhU5lvMJYiTSyFiGWZwVhUvpJUae6/BvsZdYZiKdXEshaxrDMYy1aFjydVmvvfi+OZWkOxVCn8 OanS3H81zvvvMxSLWCeswlKPOBoQu4lYXlX4oVKluf8qnPvfayiWwwqfU6o091+Bc/97DMUi1par sHyAfpdj6F8yEYtYF6/CchLXlZxCTCZiEWv6VVi+xPb4K/SPmYjlnGKtTKo0978Z5/63GIpF7KVQ YeH+hPU49/+0oVjEPhAVFu47eJznsQI+LhOxiD0sKizcT/Ao34ttBfxeJmIR+29UWK5D39ZPcT+I iVjE3iEVlqG4J2K4Fdg3bCIWse9JheVWK7A3+jY4/txQLGLPlgrLXVZgX/kkK7Af3EQsqjVMkdgb Eyn/WCT2xkTKPxaJvTGR8o9FYm9MpPxjaZeQfyztEvKPpV1C/rG0S8g/lnaR+cd0sFQglj0GYzmg uf+qHn1PDQb7+l5V+PrkvTF70D9mqq9P7JfX2RtTif6xaoP9Y5Wae2PK0T9WZbB/TGcv2Un0o53q hL1k4fSP7dLcG7MT/WO7DfaPbdfcG7MV/WM7DPaP6eyL4/6xzegfM9XXd5nC15cm+cfWo3/MVF9f H4WvL03yjz2O/jFTfX0pCl9fmuQfexT9Y6b6+sS7XFRYuH9sCfrHigz2j+VpYLkVfXzcPzbXYP9Y tgYW7h+biP6xyYZiEe//UWGZjvsa77UCPjWTfX3tfVdOV66di9RexkisnYvUvsVIrJ2L1B7FSKyd i9R+xEisnQvn3sOuXjsXqX2GkVg7F849hV29di6c+wd1sJQhlm0GY1H5BlMj4BsM575AnXWAnekb DOceQB0sjYjlNYOxHNZcB3gI7fEIM/c9Ux8q/Jzy2rlK9A1WM3Pfm1OpuXauHH2DVczc9+aUa66d 242+QVPfmXVO4eeU187tRN/gbmbue3N01jRy3+A29A3uNBSLeEesztq5Z9E3uNVQLOL9tjpr5zai b/AZQ7GId/PqrJ1bi77BdYZiEe8V1lk7txp9g2sMxSLeiayzdq4YfYOPGIpFvM9ZZ+3cr9E3uNhQ LOJd1Cos03HfMPcNzjIMiyllaejisoif+F6SKd/fay+OBwP+Yrctv5qpvztmBbmvTfhPRb9VMZaV PyeuFD7k00dvm/bgh7cJmo2+R78k1yb8cT7jnEHOECfDwU8Tu+WNU9w7F30ZnP8zHvcWNF+Ie/P3 t13PksUnkUPe7wTup4jFPhW9n6Alhrgff+fDjc4EwHqHk8xS4HjAGeakQnwcnM1wxkHsDpDFXXC8 ASi3O4Gyie8GRUkhGsvp4H2jMB2N52RZRgVszz06GGI0MHMZ+6wA/1gPzIIWLhnzEIc8e3rcT9As vB8Lcr8M1vobRF73KsR+p1vPPO4laE4IbFw+4x2uuxtdC5Z1YKNcokOUoyvbC93vdZpYlqgIPRt0 yxWsHRU2PQB9G4PQlybbmaCpbDodbUnUS16WJ5DnM4SnoPkUPIcC12gPvguR74MefBdq8B0WhG82 8r3Xg2+2Bt8RQfgOQb63ePAdosE3k/CdjTZwBfK9hvAVtKgQfKe6905v1ls0aQtMsNuLqQ7xOeVX WOCdua8TfQiaqg4NkXQ8Fa/l+XI8eE7U5JlBeOZjvgIPnvmaPIcTniWYb7UHzxJNniMJzzLMt92D Z5kmz5tIXazDfC978BQ0n1JHQ9rU8Tcx7zsefN/U5pvRhu9xzPtXD77HtfkOb8P3W8x73oPvt9p8 R7bhG28F8iZYbfkKmprvTW34DsC8gz34DtDkO9RDb6Mw71gPvqO0+bbV292Yd6YH37u1+Q43uk02 dZwZDAf3rf0ewlmspx0dW37CAmsn+TzcvyH8iehZ0HorxlsjoXc+FsZRLeMuMbLi469kdj2Mu1Lg OAToQ50AVjGGkvvz8viLjqHkcZZDxmRez/6LeRxwMdhiNwh3QEhmwd8XqmuLU/hY0Qq0J2f4DeG3 JioQng4smHuJO/8msQVsOStic9iF/vpNvoo1WJMPHinuLdlx+eUshx8Prklg/4KwKKaR5Xz+A1+O w3o9ntCc+7UxpW4dZIjtNFxrg0R7QvyPaTtY8vtvF4+J7Td5dsygqNNJjSz+RIIbGMqk9c9qrk/l Uc/7eD6e/5O4eGcb3LPhxcPF/Pg6HDktxy3H4eKzkP4HhFi3H1Tq3rubVEcY1gP+7XaUndvX5iH/ IVf9rb5pLvpTnM8a9LNuIe1ATzyn8jFlwAg9mY11HFKPZb3L3zrvent4Lo/L9roTCW4ZgtnD6b4t 9vAk2kOmfbY4ZxjUrtizxRNirmSJcMx34gty4RwPvU+eL5LtgedvQiyJzTb1XF6LfZljD7loDyVo D2s87GFNB3xSZtkA9MlAll9MOF/0PYQBd5539dwf660PA/9p2sACYQNCh8IGeBsQC3lvOXuk2G54 u/jA6SPFvE3i9/Kh7JghNvAs2sCdaAMlHjZQgnmC2UA++mL5k596Y23pea7jd22v/VxMz3uOV3x3 3edhn7Ju5G+1izXlTovcW11Pv9Mur1u/SmOtuVhnz+nv8joJTD4Lgwyjmfd37H0a6+y5D/k9LMtx w8oidGhJfQSvdf6y/Yp5zURcb6WaO/Kxlu/ypmMewWMgpoVd+DTtSPWNXi6/o5j/I1JG6kdaif6a 9/A58glpNwQtNsTYcabbr3wA2vRlrAD+5kCrFiXNc8njBTtM48toIh9ZX6p63Zk22dGyCJt0Qtgk bSeEPc1Ce1LZ4UPEDhcSOwy15yUlSH0T78kuQNvj7zr/GPW9EM4sglQBBB4PZY98DmoFymSjhz0+ jDQnhD1yO17OlkAvIw9scXmrZ1a0NA8YTr2399nSmTbY0bLQZ5ul0SYJWyrTtMF6YoMVmNZ5T7ls d2L9yPNod5XY5nm1kV72tgbnn97D+1N7a0BaXAh74/0ybmlF+D+ZzXfrQTSZc7ZJnync7aC8B87X xTbY0bJ05Nl8XNMGvyU2+IWHDQazO/Gs/Rva3d/baXcrcU0tx3yl1dbuzmg+d5eBxeWxR9j90Kpz 27PJfLvdiW2erGPLIHuzItDmyc/dJEvP3jKs1vY2yNJ/7nq1eXyNxlFcx6Tq563A9Zsc8y887G0E 0mIU9pYH4/cieIrPYYtdPxQdC9qd1LZZQfr6Xf189bHIzzGHsyzt7W/6LuAZHaxeDEZ/tLCXuVZg /0cSBmkM75dlluIx/gsmM9WYkMpD5hGH9XQu3KS0N2MqnnLeeMzb7MlW5A0mOy8ZUKzjcS0Al8u4 SePTUrMCY8sAPv9odPf45fh41HsvzOPLarlnT9QZQzqP/x96b5UFbKEAAK== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image052.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhJgHXAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAQABQAd Ac4AhAAAAAAAAE1NTWhoaHx8fJqamoyMjICAgL29vbKysqenp9nZ2cfHx9DQ0NTU1MbGxvDw8Onp 6eHh4f///wECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwX/ICCOYmCeaKqubOu+ cCzPdG3feK7PZO+bk6BwSCwaj8ikcslsOp/QqHRKrToDvmzAyu16v+CweAw2ZUdbsnrNbrvf5XMa Tq/b7/gutjfP+/+AgXBmJH2CgBBPCxFSiW8SDIxcCBIFRJKHR4QAhpl5EQZNDQMEQxAIQQgLSKBs pxOnCQxdDROhQq1JEQmAm52eeLdKEgQSRAgJiZhHobxcEgjCqckFBgiOTqtFu8sQodpHtb17v8Bu Etih2EXKAuJCEowRCqwDofZL4EHrxkbxEwJQFdFGwBkRA6WMFOgXJBRCJPrymClnjoykCAhmNZxA KkgECSBh9YsgQKMxYxgR/y4TYs2ALAL0grxDWWlCgoQdJ4QUsurkhAgQiuEKIiBIAQKYbgZRMOuj BAdBFryztZSB0gkEbhUdB6QiG0kJwhZIsKqUvQa3nJ4ssADS0YwEGIxdyGBAAIbyatkr6MyAgAEN GBAY1YCXggQNFKANQqzBAgQECECWm2ChAkkQ3C2wBI2BsVKHJUhF5fRBrXelEkQYfTixXFWWuFL0 6sWkAAJHG4IKMCA2EQh2eTeAYEIB7qwB2C47HcCAgQAMmOpEkNFEAgEKBCSyi7A3SxMGFjw3fvS5 wQkFAghYRXKAbgF31a/0PMRABM/yuSsYoEB9RDwo0KYGNEIIJIRvYkggTv9QRUBi3EoFQhgFgkTE hoCEChlxISzAnCAgGRIIkEB2+ihAIRgRNEdAAAbCg8p/qUgzRQH01DSEiRNE0wSOx8iYiYcfjhHN QkMsgNQaDFC3Di5LFklkFTYOhNRmDCVh5EpUegUkE101EABzUwUp5phkBrEll2b2N0EAapbp5pta dtVEGlvUuSacePoxG5pr7LmmnHzaaWeehNbhpxKHVuHnmUvQqSabnZhwwKSUVmrppZhmqummnHbq 6aeghirqqJUGQGqpp4JqKqZDMJqEh16CqUmhtIaRKBK3SlHOAa0CKkautQaLq6Js7NorsFAgK+yy Zlqh7BPGCuFqGcxWC63/s30iwau0vtpq7beNEpvtEdua2S214KZrxLPNjmtEuX+yy6e69N4prhoU wTvtF/LWS2a//SKahL7n8usvvfIGLLC2x7p78LcJFztww/g+nG7EFU/MrcLDWmwtwA6/SzEZHHvc 4b0kK0FwyeuaXC3GGTO8ccgu0wrzGH6uTHPNhN786xI6x8xzoT7/rPLIOA9da9H8Hhp0ykoTjbKt BQ/xdNJR90wFyy0DjbTRWbsZ4BRcE5Ho1WCH/e++82Lt9cxRePllrLOqXebYuu4crxBoz8lAA/C1 WUTZdrfB9sJQtzxH30w0UBBx9g5e+N1Tezvr4l+LIh4Cg0o++ZhMezHb/5aMN9qA3IKb/TnolRv8 qtWZN27C6V8OvsPtuOeu++689+67qbG7vrqAoeuBeBCliz78h8VzsachyRu/PG3sVo3t60RE7/z0 WipKeOR1ww534tx7Ur31rUsr8vhul//j1oeTfTzfwSvv/vtbC+15Edpff78gzfNf1/hXP+n9LxDV 09/+slfA7R2wF+kz4AAJyL60PRBAERTgBBlYQctdUCL5I98CKWiu77XrgxiUnwhVJ7MS6g2Fhgth +zbIQRcyIUlNmh8M35DAX1lvT/0jCVO2coUd2qGHVBvd0TpYBLlMYAHAMqERaVjEFbbqbTZkAkgw FL4pxlCFM2RiDffGhP+CsEgobfPiC3UoPNWhbwL9W0oB3COYOanxi3mz4p3eGMeB2PGOa2SjBM0W Pzg2EAnAmQDdqAjINl5LjydcYhaZgAnpQKqLjfRgsiAZSY1NUglZMVEEBjCLzrEwk5p8ZBiv2IQ+ DiEBwdkjJlHprDfO0n4dY0IfPyIEua0pdaykpR5syUgH3rKFZFSCceoihL8psnaE/J00p0nNalqz mv0LSgIQQMQ/CtN5xDxlKsWpy0PCg4vH/OYm82hBcpZTjLhUpwyh9T0lQiGOgGOLLdAZTHmCkZ5l s+c9zZmKolRJkP5M45wKGQWBHs+VwAxXQtm5znH281Vy2mVyClCAHBb/c6K5rKhF1celjBKUQxNQ gI/SCVKWYq8MDm0U5uBpJW+2VKE4xVZMH1rA+2Twphet4kgZSlL60ZQBBpjFP0QK1JAKdajg02H0 khQWA4yFqU0d4VMdedJOaA8CauIcVrMa1JxqMJo2NeonjZAICThnrGTtZFrjqVWnqjWZR0CAAhJh HLiSVVmE2+lLxxg/sCrSADHZalzlatZ5ftSddyWqTRKi2LgCdpVFlSi5COq48zQWqJcdKWPtKr61 IsEufgUtRbmaWc1ulqbHiOJiy+paukLWpYaE7RDEqsq/StZc7aSt7XJ2Ut5yRCbQrOtNfwtc0d6q kK5czBMdVQ4p/o+5/8yt7W3X5bTipuE5zarubLEbTplG6rdn864LTSnclkYRb7VUXG8liVclGJe6 0bymfvfL3/7615X3RW6YWqvahjqXmMDqIxRla1kDO7ey9JXsAFr0WXkiK6Ckxe36THuQGKXWnxd+ 8FxbeUiBGHfEEw0xuh673Qi/URwnrrAwVcxaAst3CnFsS1Y+/E0a29bGw61CH3cy3xQ7uMZRHawU XLlaIxf5rEB4LheYfGSQ+th7kRoti9/J4QYdVMZ3JG/TsoxgLwz5y9qdsZhF9wv4ZnjJBCUyhFHp ZkRlt5hS/sIu+bllNdYZo+VNZ571fNIm95jHc16UlqlAZUT72dFmXf/UnbFYX9E2ksGDbK9ucWxO 8SQD0jvEtDGVazs1DJmboEbhlR183jKvYcgTTvUHRZ23c7H3zYTedEFl/UBak626bww0p3XtyyeH mZ6Z3tjz4BA98TgHIVthAHSeOeBFqxq9CqPI82796gYyBAL9aIAE6hRRa8860JNubqkBbV0SVtoJ ReF2kqco2RQ4VtPcskOjo1LKefs71K4WIJAOJWwzF3q3qLhkfv3L8IY7/OE02PeKSrFIUs9aogFz VZ3E+ydA7HvOFyR4wdE63DanOwzNzsqzk2rskJc045rYdrudoD1x38izSlb1yxPGcUBngsrjBvn0 PCTyP3dMTgH64cj/2eBKkGRH6Mszeq/y5ys6ZVnd5mDyRzza588VEmDdqrO9BfRxFHPP6HTyXlRV EOQglR3MhZP0+Wyo9DK9Pc1Rl3uyNn5FRnXl5Hm4O0LDxnY7S11yYU884P8g+JzH/etWz9WZCq/s QjUe11n7c5SflXS8zmHxPz84rw+GPmyrm+8Lr9blNeyvgffBEJTfubJhD3qvrL7rCBM73adF+6Qj PfL1ur3FLcb7em8+8lU/vOpF33KIASr2sQey79m+ApMJv8UfO/6xXO/3v7dg+zMX0/XxDSc3j73y yo1BvP6utvEDmWgs2Ju9Na7+9Ss/au43N/GS3336H78G2Bc2d1dx/wGIQLZWfd83fTigf8tzdwo3 fD7Uaia3cQhoTZnkgP6md/nVdiQHfvrFgf6EgRxXfBJYchDXarOVW102JxF1gi74gjDIcMw3BATI SmI3cB00Np/3dYY2eJiHe+/3g0D4b44HgsHlg0NIhEJYgBDYhE5Ifk8YhEJYe6wHhVZ4hVKYhKsG d1k4hKFleCnYY0sXhuVDhWQ4OWZ4hnaThmpIeGPYhqvDhnCoNHK4bk6QAMnlBCuyd+EkN9W2bgiW Bnj4h1MXBHtoZyUkaciVh0cgbaV0KI5oE4zYiNOGFSjoBsjCTE8wbnxGBOxBWabjJd40aJq4MJzI J58YKLSzBOKWdv+sGHQTUIpJ0Io6EQAQUodR2BAwogSGFQWKcQW1kCifJ1ThMS+9eDy/iHHB2ARb cStbUYzMuA+JpWujJgrd5AQU1gTu4QRe0lfzMmiA0zbZOEHbKFHdCIoQoRGJsgAaEY5MwI4FYoQK xIrKgnOsOI2UZB+jKFSi6Fr2uD+J4U2g0InUwYAF+UxNcJA2IY84U17wQYhHIEpRcCRXoI8v925B 9pDmlVIFwGdAQpFg2BydOHEYOQQkqZFLQJIS2YFktQgWMQTo4DK4eD+jAIqvkCO7KArSIB0mM5N5 kpNjQAwHhQzKoAgNIg300ZNvaC3zkARoNgRNCRFC0A5h8g9RaZL///gQHQYPIKERD+OThXIVXFkk OlGWKQGSHkEU+zASJcEYZhkNaHkUSUFZPMkSk6UTYREXxLeU1pIQoYEVjDEYjxEZkzEXkGAX36YZ sVEJbSEXkiEYlEEXiMkYGfEZKZUA8TAabkkVrREdaMF1zhd+bqKP8GEMFvkczSEebHIcz6EcFeIf +xAcgEEcq1keyeGSHvEX73EX4yYA8tAP99AcJtBRHgOWcOIbG3IiEzIGFrISEqAAC8CTG1Izxukm PKIjPCIEAwCaRUAjOqGcU4AjOvIbAhAQHsYz1UkmV/JEC7GeVBAlX3AlWWIlT0KdfDmHapOe+Fkv +rmf6tKf/gku/5AXgwRaoAZaTQu1bAGKnhdZhAvaeg26hA/6MRFaheCEdYVIMiZUMIHYJ6JJSP00 OrYUPx86jBZahFeXbAyohNVIB3NneAqKK8Gmg1YnS4ICfOBEgdR3fx3ncwl4fp23kTAqf0T3AjIV kjsaZYloXpzgoOuHJoOyJdpHgfpXevbCfns0oouWdjiYpa+3XuESo65no1EaiPYkKO3iexjKXVhw pjfgRmTqit7Xo69nA+pTo1eKerM3A2mKejWafFfqgfXXcX4aXkSXpSYoA2kqS2TaXDPapk5akn1n o+HlqIU6pMOCp38qjAq6eX3aoyfkij53pOxXqDe6UAuDpo1Kp4dyVwISCqNFOqX/d34xp3SF5321 h6uaKqXzl23Ip6OEin7DZH95OqsyRw6vSksm+pV4l4h70KRJmEkAOg6NhQJ8EK0TajMyegJ8kKLZ yqxsugmFIIEHWq7meq52mqjP2q3o2q7u+q63cwYlAK/0Wq/2qgLyOq73uq/8aq75Kgf9GrACy3Dy GgIAOw== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image053.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC91dfXSVxZmf9+bNDURgaanLhwUCoqRJiglgbQ4CEQXsbmmAjXwUXflcoMjHASQs etgrqwUBAQHTQEI+kZU97jHVnmPxYOs5dYWVlaPWelixdWttT/9wKz0eU+pHs8+89zc3kyfvvTMh N5dJb87kzvM+7zzv/OZ5Zt6ZZz6uJ4S4j0I2wlJPiF+L9s+nY4R4crAQedNnzRDCEy2nhfD7CZEj 2MenkCXEAEp/jrFaRvji8pAsQQJEEYU8CiSu0CvzxFcpPpBCZOBLFympWIwg772bwmzcO7rMF/0g b0RZ30R8DMlQ8eKySCDLD6jY1FFlOQmeXyYS8SGiPT4U8ba2NvEVxPtT+DLiEQqjKPShMLr93raw a7nAoj7qHv0Z+rP15xUj/jeU8RvpW5aLJzp/bsB9kjcWWCLgSfn6PREtTvqK3dD+7JhNvsPkeCnw uPasK5U9AuWqPivo5t/Q91wKG7zAzMWfVGHjcyCurGclvAqxWqwVK8QmsvTv0Hclfc8V6+naErFO 2H/u65v7zFuvnw3qpcpb/Ps5se1PrxYHdavfL0XxNacCvPL+u3HfAromsxTD99s/PFMpUPcuj9la 3NL/lHgwekr0IX7eqkHi/5Z8WvxmH2/5+CR5kWnkt9Tf5ysHibcoSLm19N1A6XPZ/Vvp2mWS2Q9p IvHmIdFUDG4vs0SdH9E2UmZv8PItgdoSusrSyl6m/SR52YtZVPabxUYq6e59qCybZNlHKT4A1waE lP27fRNl36TK3s+Nl3lRbnjZb46cEnf3OyV+1Ldj2d+a5rKX+b0G5afKXtrS8ORlP5aXva/F+2t1 LdV1pSv5rNbM1JOnbeqJpqunu6urnqwnEa2eDOtCPcnupt6u9Dpvg/X7U7XHfhrbZvUujCZ5X8rr +SHPovzE8kOey9/Pen9A9WFyEFSf6TqEdL6/87X8D9HKROVB9dvuJYG/0vKQCd0Ilidb3XCctrpJ po956D8VwT7m0c3HUS5FdGWeJ8Nxih8PaFv9pLMMo10swyLUfYnlKbTZQ9BGvEbhNrr+DnQ9EPc/ atmf/QbSSNmPMhnrGH8d41cwfgXjlzJ+KeOPYPwRGSpnvR1JZavJylnZjKqrynZisVhoffVCcNvo g5fPcY2Wcjjdk+UXuYLys61ben3vajmpctD7h0rG10R4men8Rxn/UcZfx/jrGL+C8SsYv5TxSxl/ RIgOr0uiY2UDOv/fUuArY/wyxq9g/ArGX8X4qxj/AcZ/gPH3M/5+xm9m/GbGf57xn2f8c4x/jvHf Y/z3GP9jxv+Y8XO8jvwcVv7DGH8Y449j/HGMP43xpzH+PMZX+u9uHc/qRhup+hiL0ce4mnkpQPuy kG4+6VBeTnTsh8f0fptqE6Ps3ZGsD6S/O0pgn6Y2cRJrN6ajbim6nNELGb2M0WspNGl0JaNjFBo1 ejeFBo0+TKFeo+soHNNo2aep0Wg5IKzW6NOQoehX5DhIo19n7bh8Rz+k0R8gz4r+A4XVGn2ZwnyN jlChT9Xofl68f63oa4m+TMpX9Eiif6bRXyN6u0ZPIPoGjZ5MdMtf2umZRA/W6DlEl3/R1sb13pP6 bTbot4npt4npt5Hpt4Hpt57pt47p9xjTbw3T71Gm3x8w/R5m+n2c6Xcv0+9Opt8Y0+9WjR7pdewH SP0u1Wip33/QaKnfMo2W+i3QaKnfASH1Wtdvcy/TbwPTb71Bv7UG/R5h+q1i+j3I9Luf6Xc30+/D TL/bmX7vZ/pdw/R7L9PvbKbfKUy/+VdZv81d1G8T02+jQb8NTL/1TL91TL/HmH5rmH6PMv1WM/1W Mf0eYvrdz/S7h+l3J9PvQ0y/25h+NzL9rmL6vYfpt7mX6beJ6beR6beR6beR6beB6beB6bee6beO 6fcY028t028N0+9Rpt9qpt9qpt8nmH4PMf0eYPp9jOl3d0j9Vb4rL8VYNmw+UX4KwbsJZS99xk+m uc/qsT5kmF9J95vyPut1rH+RrJ+psJQCy60OY1F1z4Tldtj4DJH+MVa6sJRbYpkFLLMdxrLQEst8 YPmuw1iWWWJZAizLHcaixnomLGvQ5q8DdhexVFpiuR9YtjqMRY2xTVi24937ELC7iEX5B0xYdqHf sAfYXcSifBsmLAfR53kC2F3EovwyJiy16L/XI42LWJRPyYTlBMaaJ4HLRSzKH2bC0oJx0nPA5CIW 5cszYXkBdeZF1BkXsSg/pAnLyxT2UTgDv5SLWJQP1YTlvIiPpd9AO+4iFuX/NWG5QOFfKFyksMNR LMp3bcLyPvoxv0U/xkUsyu9uwvIhhZUUPqLwPUexqDkDE5ZWCndR+LNch+koFjXfYcIiHzhZ5gH+ bRexqLkaE5ZcrK/o78XXHbuIxTTfNw9z/sqnNAF+GD9I20T0CeKdCOK90c80T1szIfFN1vBNoiuT SVophUmO4jP5nhQ+5XuaqeGbTldmEnU7BRnvjf4ohU/5o+Zo+MrpyhyiZlEodxTfQkt8yke1SMO3 kK4sImo+hYWO4ltmiU/5rVZo+JbRlRVELaGwzFF8ay3xrQG+9Rq+tXRlPVFrKKx1FJ/Jv6XwKf/W P6O99YO0DUQfJ97xIO6qz8sG33bg26Hhi9GVHURtpxBzFN9uS3y7gG+vhm83XdlL1C4Kux3Fd9jg s1T4DsKXVIX66gdp64luJl5zEHfVX9Zgga9Wu7cJ+Oror4GoWgoy7qoPrd4C3wn4Df8d+vaDtMeI biReYxB31a9WZ4GvBTr8EXToB2lriW4gXkMQd9XXdswC3wvwlf4E+vaDtDVE1xOvPoi76n+rscD3 MvyhZ1EefpD2CNHHiHcsiLvqkztqge88/MNvwk79IG010bXEqw3irvrpfmCB7wJ8wO9Cj36Q9gmi jxDvSBB31Xd32ALf+3gH/g7vQD9Ie5DoKuJVBXFX/XmPW+D7EOvzLon4Ohw/SLuf6EPEOxTEXfXx 7bXA14q+3Kfw8/tB2t1E7yPeviDuqt9vpwU++cBHJC7sEfODtI8QTRQFGXfVFxizwJeL9aDyvIod wNfP2070DuLtCOIu4lPrlE34BtF9W+QmYaxz9IO0W4jeRrxtQdxFfGrdtQnfcC9+bsko+t4AfCO9 +4jeQLwNQdxFfGoduQnfWC++17vQi68d8oO0i4leTrzlQdxFfGpdvAlfiRf3Dd7sxedK/CDtHKLv It5dQdxFfGqdvwnfJKwPn0rf04BvsjeF6GnEmxbEXcSn9i2Y8E3HevdveXHaD9LmE11EvKIg7vL8 StheLY/txU5WBgUZWNebraWLWuwXTzXfksofWqCt623Eut7jjmKZbomlJ9f1pgtLuSWWnlzXmy4s Cy2x9OS63nRhWWaJpSfX9aYLy1pLLGouZJ3DWEzzHgUZWNebLiwxSyxqjuMhh7HstsSi5jP2OIzF NHdRoK3rrYd/qslRLKZ5igJtXW8d8DQ6iuUpSywngOWkw1ieNcyvFGjreo9hXW+Do1hMcw0F2rre GqzrrXMUi9qfbMLyMvzzZ4DdRSymOYQCbV1vNdb11jiKRe0LN2G5gHmFi8DuIha1p92E5X28i34L TC5iUfvxTVg+xHr5jzAP4CIWdZaACYv0+T+Gdb0HHMWizkEwYZHOjl1Y17vHUSzqDAcTllz48Ptj zsJFLOr8CRMW6bd/kL7/1ovvU3ARizo7w4RF+ug30Xce5iJcxKLO/TBhkf54uY+hAPMOLmJRZ5aY sJTgLIuJmGNwEYs6b8WERfrZv0PfUzCf4CIWdVaMCYv0qUv/653Ym+EiFnXOjQlLuRc/92yuFz/z 0EUspr0WmTi/I1N+/sK/Ij9/Js7vyJSfPxPnd2TKz5+J8zsy5efPxPkdmfLzF/YyP78NlvuBZavD WEx+/sK/Ij9/YS/z89tgOQgsTziMpU7YnRFTC79zvcNzFiY/f2Ev8/PbYGkBluccxnJa2J138wJ8 4i86PGfximH/h35+Ry38/PUO+/ltzu45D//+Gw7Pv7wj7M7uuYD5gIsi/Wf3pNPPf1TYnd9RDT+/ q/Mv6lxWm/M7quDnPyLc9fNXCbvzOw7Dz+/q/Is6D9fm/I7H4ec/7LCff7+wO7/jMfj5XZ1/UecQ m7AMwr4K6eff67Cff6cFluGYd8nDnJKrfn6b86HGYt6lwEv/+VDp9PNvs8BSgr0i0s//gMN+/o0W WCZhn8cUzCm56udfZYFF+vn/CX7+1Q77+e+xwCL9/Ivg5/9Hh/38cvze1bO8bdb/N2JewNWzfV1Y /5+ps5Uysf4/U+coZWL9f6bOTMrE+v9MnY+UifX/mToLKRPr/9N57pENlp6cF8jUGUeZWP+fqfOM MrH+P51nF9lg6cl5gXSeU2SDpRZY6h3G8pTlvowTwHFSuHsO/rOWWFqA5TmHsZy2xPICsLzoMJZX LPeYvIy6dUa4+/sEr1tiOQ8sbziM5R3L/TIXMBdyUbj7WwsfGOae9PX/tZgXqBfunutts/fnQ8xt fCTc/d2Iy5Z7f1oxr/PnHtj7k87zfWos1/8fwbyAq7+BoX4Dzmb9fzXmBWocxaJ+v85m/X8V5gVc /T2PkZZYhgNLnsNY1O8G2qz/P4R5gSpHsUwwzAnq6/8fx7zAYUexqN9rtFn/vw/zAq7+zor6rUmb 9f97MC+wz1Escyz3l5VjLnBuD+wv6y4WV/Jy8irnRX1WUMLfaGl9Ld5fy4vN9SvF4XcDx+r4XJH4 KiUcpt2f7AwnL8lzfSa/QsT3eq1BXuW88LVq/ujSm7fddf/Pb1M8+fxvw7enPm34yN+AGR29M1oS /bvoHdF4PclGyALGVHlYALnyOd8PyYPiRVLkQc4ffF3kBfKzDM+TZ67uhMxPQp6neENSPE/uYbwp wDwzmify6fuZ6MRoAcWn09UJ0ekUmxkdSyWSJ8YR5/ZoPG96uaiQjXxG8dws0Nm45mv3ZcVtMFGu UY02lXEr5H8egrk1zWUswxdKptf5eYrn4XkiyfMmWtjPBvTzpbyhIc9SvKjBhmdEpe5uIq2VRHUd +KLdppPl42q2G7Id6Er751JesjL0jrDNV7L2VNn0SIyNr4ffVrczxTPZdDFsSdVL2abvgMzHmEzF ixhkjiep2SFyV0LuxhC5Ky3kTkwidxbkLgiRO8tC7jeSyB0PuZND5I63kPtNJncx2rrBkDuayVW8 rBRyK4I1FsUJvWWztsAFu+1NdUiuK/kPEf9trx8zfSieqQ6VaDquwJoImW5miMzbLWVOYDLnI92i EJnzLWXezGSuQbr1ITLXWMq8hcncjnQ7QmRut5RZyurifqSrDpGpeBGjjko61fFmpH06RG6ztdwJ neQ+j7Qvhch93lruzZ3knkPat0LknrOWe0snue8h7e9D5L5nLbe0k9yPkfbzELkfW8odH6K3HC+e dqDXWa7imeV21tswpL0+RO4wa7md9TYOaW8JkTvOWm5nvU1D2r8PkTvNWm6p0+8QV8fHyXDEUP+l ff93iveP7Zj4AtpSOa97CXOhup4Vb7BhfHgLjSbuoHFf+zhRjQTleDFPfJ3Gifn0XUL88dE4VjXm 08cf+niRj/my2DhbH0OG9VV687ilN9hiNvqusr+6r5u2OFeObb14e/KJfCB9Hs6KhwPxRb7PSqfl LLFabKYe/hJxpZ9RfxwqWrzyl85WDtbsuOFLYrb8funhQeIPFDZHTonZ7/9FDiXEwEcGJVKfnrZH /CviMluX6F6fSnQAxX9WeFTkvf5q5YDcUX9cnDM2qzjnlMh9d1AQBMqk48dL1Kf/zV0Qkelk+gt9 c6PV9MyWH56plN8/pW/Jmx3k40xlK9G/p+AFaxb3BM++RqsjAroZLhJlF4wNZFi+JVB/Qg8RtAPL YRfbMIbYy9qBPrjmp2gHpJwJ0bFUy++IRlk91vWerz376ttD7VJZtje+OyjIQzJ78K9tt4ddsIdv +q2VByZS7erTWnlnzrViCH2P6JtbXU3XZBj8y8826vYg07cBy5CETdUubbcvd+xhAexhE+xhW4g9 bOuGD80tGxCiiMryd3d+tvELCtd/67NAz6NRbyMI8mNpA0eUDSgdKhuQbUAfSntr69lKv+XVymcu na2UbZJ8VgRlJxyxgcOwgamwgU0hNrAJaZLZwPLAd5wnwrzHPnt3m/zEXbWf3vS+l3hvxHxSJMQ+ dd3ka89T+2Ci7eXe4f6odj//TYyhFvtjEvs1KbxGocyLr+Pqbhlmszzq+Ex7g67BejeZl/9xLC9K h57WRwjbm6Tbr5qP7Y+xt2nOKxL4FONpbkAaJWMoaGUXEUs70m1Vx6z0L/tKb6Kv9wuWR+73ehCy z8M/eoG1G/mwpT4pxo53y7UmYi216ZvEKvpbQq1aFtL4bLzgp2l8mc3KR9eXqV73pE12Ny/KJqMp bJK3E4k1ArAnkx2uZnZ4D7PDVPv08pPUN/X7RItge/I8zLeh73voyr1ELaIg46nscQN8kecx1uX2 eB/sMZrCHmV/aLNYT72MpWSLmzuMRbO1ect06r2r75aetMHu5oW/2zyLNknZ0vctbbCO2eBB0Da/ D6XbnVr3cgB2dwhtXlgbGWZvD2PdssT/nyH21gh765vC3mS/TFraRvzPEyuD/cjZbI7cZ32mdLeD +r7dyFW2we7mpTvv5v+ytMFfMxv8RYgNJrM79a79Oezu7S7a3YNYly4xy9/65Hb3geV7dxNZ3FIa 3a0QWwLb89n6AL8H2zxdx55D9uZloM3T37t9PDt7y/M62ttXPPv3blib92UvbntyjbOpnyf3ZY72 4pinhNibnOd4Df7bVPa2lHoPG8X3yNbWBX4oPhb0e6ht85L09a/2+zUiMj8nns688P6mMPQ3I1fw jk5WL4qCcUO7vdxLQn6F+nFdxzF8TC+z/JDxX7IyM40JeXnoMvqinn46RognaVBlkqmnzUXahCfb kDZZ2YWVAcc6A+vRZLlMnzWjsKBMiDEJfLGpcPfE9PgM6H0g0kTK2p85ADoTqp2i8P++XRWcsLwA AL== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image054.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhMwHVAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAQABQAq AcwAhAAAAAAAAE1NTXx8fGhoaIyMjJqamoCAgL29vaenp7KystDQ0MfHx9nZ2eHh4fDw8Onp6f// /wECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwX/ICCOYmCeaKqubOu+ cCzPdG3feK7vKOn/pYhwSCwaj8ikcslsOp/QqHRKrVqvRBPwZ8J6v+CweEwukwPbUcDMbrvf8Dgb vV3L71LHA8/v+5l0XH93EEsQC04PDFSFchAIDmIJRXuDV1okdpZvEAVMAkwOBQKIQ5MRCAhKnXCn qapgC55DEKBMCptJgQCauW6zSrbBpUMLDIiVSp6nWKIIxELGCwYFkHnJRHrAQmt6Sou+Rpi84W+e DcqfBkUQD+3rSdWeAwNN6ETY6Ni07gK4RvciGGBGxICAfQ8ibYtAQODBJAHLccPUSyIZT8KGILAF DIKDjxEeBKQnZE8hBwgM/0YykkDBg2oICtQrRitCIVAbhQywBZJmSJsR9BhYCTSCsAIGoOVUMMnj xwapCECbxTSnzpkZLVK0SKZRAAczdUZIwGARM6eRHCR1sCCBTARS47IdEABWUCGnChQgkIBZgQAC nkkV0GAd2aoK0g5ggDJBgAUL4kZ2kIBoYLBCICRWNZMsgwZNPxIFVq8AhAagD49FwKByWK4ouI55 UMoEtASR60YAd4QuYFx/EwgQjiBA0kZCFtUi8LJuAliPDDQwwSCAgscMTdAL+zfAgGeAhRMPQLA6 9pACBBTCnR1wxGIIKuGG5J6ACbUC9J6XHVt2GLUOKOBSEdZ8RkaAQxRAVP82rC2GxDFeWIOEhAY2 ISEREJbkXxYnbAjGAwKQF4GAsMC1W1ZgQBCAfq8xGAE0GKI4hQL1iGKEiSc6gWOMHh7RX49lNDCA A4W9F8YCqSxoBHIASdeMAY3sI2QkRdozZBFVAslhF1p26eWXbfwI5phklhmFmGamqeaaaCLB5QLY wQnjmnTWKUebbnLjWATkVWTnn4Ce0WETdqxhKJ+BJqooGHj6yA2ihy4qaRl+DlKpm4MCoqehe07q aRiX+hGqOJkq0aGcL+43xAkHtOrqq7DGKuustNZq66245qrrrrz22iurvgZ7awC0+lgqqJ8m68Sx liJxgLFcjjGqstQy+8f/pc+SGq0Y01KbrLV9hJptEY1i0a23n54bh7jQqiuFu+gqCu8b7Go77xP3 xvtnvmaMOu6W/Gqqr74BnyHOEP+uCq65AxMcTkWRJjzRtsg27G3B0h5sh8R8LnyJxRf7QvGjQnBc 7scgK4sxqBT3YrLHVqyccpcyf4Gmy+1SOnO6Ih+Ls7067zxpzV5UWtHLI9sstKREF+0oEUg3ncXS i0qN8tRFRB001YFaXYXRRmhtMNddi3xw2DmPTbadXlMBNtpAQwHnY6g+vXadbU/xdtZp43tMiJ2e fTedeZ9pN99xP7HAAC5FKvjgaRZu+ONQ9+3EAg1U4zi5kLNpNufOWk4o/2QmBA5652ZKju/hiJML sxFzkz4nD7TXbvvtuOeu++4oiJ0x6mWqvizrrQO8NfBgCk8o8ZUnzi3yySfNB8TT+v489DS/Ti/n 0pcsOhEQ9GXk8threTIcI3fvvfPgB9aAjAKX3+P5bjDbrfVEZB7BdHrLb/4mPmsC/pakpOH5b34A LNW5Bqi0A3pIeUvwk7oY6DQH+geCpmLeEShYEgYgYHwRtOAFAUg5JXDQKNVhAGGggEERspCEJUzC CZlCAAcwYCEhdKFEWpin0wnwe0UYwHMIAMIe6vBhltjbD9mXhB2R74i54CHx5nVCLL0QilFMogZl CMRiMIBJq8OiFseINf8ocBApDoBfDsV4LRiW8QkcFKIC1JhBNraxWRyaQhXbQYmG1C2GdkSfGzuW ryoegSx8Mt0bA3knMk5Mj11UAgEWsblFMlKQ15IgFTi4AAEQQBUFqEQXKrmqS95Binn0YRSqeB+i jFKRpTTluiy1rYKdUEVRaQSE/qgw3vnyl8AMpjCHaQJDCkEB8DCgLOegPnplCmPGFEIB67jMfjWz foCE4/cakJirVVNQqCSZJaUwwNaooifv+uYc8BjLKwwQKgZgSl/6p061hSubZgQiBAywhuLQs57X u6cqWcilKibknwBtoKgG+sKNRVKaOHxiQiso0EcVLGJdREQaeXPFiTL/bKGlxNigGEiWPagQoR79 2h0t6k0KIgACEOALSlOaznBpMmbF6+W0TlpTmrpNVBDz5vpcpz4HEOAfk/NpT/GgQKEO1XhK8OdS lRrG6T0Tpxt8KCryFU4LhvNHF+UiEwnEVaomlakMBcQoxUrUaUn1rGbVxTX7lVaB+UurB51qXMe6 vXEOT31VfKsQGpKqOYlzr1o93mHP5LETVgca/EvkpbpaPvqpTXu6WGJbkVAKA9glAn9h6RYRi6jp bUmlmoXqjYSAgNd0iJSLJW0770Q91KZWp0gwwB4iG8s+GVG2s11XUG1724ldaiXVAR0vjUvM5jr3 udB1LgcbAJaIxg+4/6U95VWJW1xCjgqdcCUtKvtzrxSQM7E/xW52G+nXHBbyoeDtqGylONx3YTan xlVCfKsqXtM+0m0BO+F+lRlXywYUtgSGJF8zA0b+mvW+TquvXs+7YKcqFcLmknB4FbxZez54rjar JWMRTOEO/26vLdxuQ4nGyfwY9rpUTXFsuApiJwS2rAU+ZV0jWOPunqwWSJWvT1M8kfUK+QtVTO6E J0pk0TK2DLec5EyZLNxe9Di4Yqiifab8TQOHuL3tktwARaGXMnO5ml7OMJfmVSg3MHAfZ15mmmOm AvtemcOqDWhCMXioO3csDtEcQgoL+9t68vm/G2ZDoKPhAE5NlsrYjP8WiF/Lw0UPARQIpuzA/Kw3 TfTYUKgc4NwGUOZk7o+SRsZyIOdM5zaP2A8MBCNTNKIK344Wixhuda5ZfTVjNlon3iF0W6NL7GIb +9g12OM06HhrKObagJI+V6G6milDJgTOa2Qkp/EVbW5vu9P/1YSlHcxG1Q3q07wG8MLGnWAdrjlM deYxqK3aTHZL1N3pDiNm5+1MRDPB3jB2Yb5DOMp9P1vd9wJ4tvH9bbme7JmSox6nFU5N+Z274Q7X 3rSFV/CVUTyzBzQvt2YsclMdfOHeBcPHC429k5t82i/XKca1lXKprbzZayu5bVmgqYEvy+U+BjrI IUdylkG8lgoEuhL/X/uGm+NTaDov2sVJufGOt3rYlUZvnKGudJmDFeld9/oKYK31JW966hCW4Au4 R153pS/q5XD6jofWMrh7m+dTcwG5YdAjuYOZ7p62u7EAJvK2G/jtLSiT31XdtbrTD/GJJ/y0ID/2 Py0+tpFzfNURj/V4ix3ulPe8pAC+XMYDyWeaj7bE185cvCus80wfGMBt/XSmot7KSWd963FASMmz fuaAmn2qxWk0zRPVxP5O+Wl3b/XP/xLzwyeb8B+t/F4iv/d5xr53i61q6mNx9rAkGbJnYP3s30y2 pFcV88fP/va7f5hln9zNzl39/ELq9m1++JErHnD+o9z/AMhyASiA/0OXfYySaASYgLX3d3PXgAz4 gKaHc9CngAvYfUJHdPtXgP23Mz6nXqjTgR5IdBcYgncDgiSYcyN4glxjgipINSyIKU9wHS/WG+pC P7HDY0Vmcsekfq4zBHShg/XXg6nCg4IWAJS0U0Y4IkSYHEkIbEkwaEFYhOBwg3eHTU/AAIQVCgHQ YEiADhDQIj5COvHTLZqAhTnUaFyINV4IhlhDN6GyAL8WfcUQh2bIWXGIhkkAh3awhnZYKGJYhWEC BQVQREbwAATBBOwRQYhAhhEoToO4RoaYbYnYQ9gxLbZwLhxBiEYxBJEYDEQwiUdwiYtIUMA3gEfQ SVDwWUyQhUoAJ/8JwIanw4jRwGy9oIqPw4pP44qwKAQNAA7d0ouzqATAqBHCyFG4iCVTSB67GH/p dTnwEmRL0BZO0AlpWEaymCrZBo2CI43URI1RBQvdkgrRMCriOATaSATl+CKHSCB24Y2AaE3qEiIz WAQJACVPMADVmAWmoVagNiodIo8xV4/5OCj4GHMrko90UQ8ek5BGsYQRwJBjYY9IAJEPWY0QeZAj pmktmCgvuJEz05EeCTIgGZINM5IkSTApeJIWY5IqeTEpeUSKwAZM4g0l+ZIiJAqk8ImsZYtSACKf eI7VYpN/Mo9mkJNEIA0/AQU06UNIspJCaSemBhBL8ABRKZVGIAD/UdkO73AEA5FbDxFEDPIAPPkt T/knVpENC4IMQIESKrEkQiAMIuGDM2ESQZESAqAkSKEUtjBrReAJOSEK9ViVZFmKiVIPniEWQbEY jfEYklFDi6MbRHAZYaEWcNgWb9GYcwGZNrEZD4kXZYEaZyEEy8AACsAASeEk8cKSdIIb9gELidgd 31Ec4hEYxrEADWYe0OAb/gBa5DEctHkc+JAe64EIrekeJVEKnmAfJzAUZ0eYgVIg93AhVSCdYUAh 7wEgyJQcRDmYGukfJsJTTiQQ21kENBIU1jWdhMVTwTkcycFsKlOWajIlVTIlV6AWURIG9JklEIGa IgmfLcmd/+lA/6oZoJ4yoATKNP55oFVzdO/XoA76oMEkdZKmoDyjZp5GoQUqoRcqXK83eNbETHLF bSBqU280eSRGihvqcAdoejXjfRB4jRI4gceHgH31UzJzAuQgh8mHKRD3SPn3Z9oHhDzKfMzVc/K2 ftsXeLGXQWQ4b5TWcU8KM9cUpVGaXUvaajm6eTTAPVa6Zn32pa6WpORXWjDnarlnA+IXbhYlYvfX pWi6XhcHKX+mpL4nA2kaKVUnp3p6CVoQpkO6PHjaez86p376pyBXpiw1aXbVpmTKbx1aqDQHhPyW f7HnqP8HOn2WqIN6oj/XpzKaToEKc3pacJ8ahW1YZD9aiqlqppKWamWlujqTyqihSjSpqqmixamE gqPkQKvxNnYkV3l82o+kWqRSh1tA+nXmhXGqB6VzaoBfI6x4SmnbZ6FB0J0c2Ijy0m4ZmQnWiqHr 9Ky6qgYQOq7kWq47AK7hqgbe6oIpAAQJuq7Z0wN1YK70Wq/2ijtpIK73uq/82q8tkK/c6q8CO7D1 CrDzSrAIm7DGlq8hAAA7 ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image055.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC91dDXAURRbu2Ux2SUDMiUowghFR4gZNICBnFUo4/iKKBoxCYUTDj0gUBUQDqBgE PA/kLxCTkJBsEsydwgmKPwd1Flx5KmJZRQXK8zi4E49C6+rk0CqQEpV7Pfs66bzMbnfIZmjcVGf6 zZt+M1+/1z0z73X3WIyxRyHFY5pmMfYFa/5lXMvYiu6MpY4cO4oxi/31A6C7MNaJkZ8NKY6xrlD+ E8La1stmp5PjGAhg/SClQgJx6Va2xa6EfBIkX9Luf0BR9iAmfmw+pFw8tne2zbqgvF7ZCU35PiBD 5DOzfY4s26GKh16dHWji2dmsKZ/MmvM9MH/27Fl2KeYvgnQJ5n2QrmZhvL2bjz3rti8RsYifOEY+ h3xu+XyZmL8YLvw62PJ6sfA4S5J5LR7H9/VFLD7kcfnyMT4pHwC51zafu1jnut3kWFHwmHauc5Xd C+tV/GbAwV/Cdjyk2ZZj5ux7Udn4WxNW0pvcvIexuWwmK3DaVXt+jyYkvn5g3x6nXYprC2+3s4Xf 78102laXw+xQwg4HLz8+X9h74g4HYz/cfvbGR0UM297pPvMz5/l2sPwuO9hbUDb14W7sm4IfMhs7 WdMGRLgWXoZvuf5+nNGNHYDE5VbBNgTlE8nx82HfaZDJrzch3DU4SXQVyc111tTme529il9e32lP hbsXoas4qe7t6HWflAc1P4tNZ08A0jthWwTb8exx2FfAHmtb3W/VqfvMzk11v1XU/cTO4Tov7uxe 99su2sGe8e9gnTp3fN0not3Ldd89ct13p3VvR9ADr5eTkfXAxoIe5kE7KGh/G6jjevBDvivu6xq9 DdS1tw0MibEe+PV2Jm2A11/PNrSBeCl/kdTnRdsvdMXr7pQ3bWZLG/urLSb2V6LN+KQ2c0Ub2oy/ nXo71/30XigfH+2+GB/De6R4JgmQ+pWukaW5nAuupzjN5bz0OUl+LhPPkgFM4tk1BVMsn6PSpOtP lupEXIN4fi4AgYela/BCN4xck65uKE5d3UTSx734HJuB2CfCwQ2IIQP2TLR4aoB8g0NT/bAI+oll HQbaWIcZeL/kWF7DPjsZ015+n4P9BxFvEh5fovlecROW4bJLiIxFhL+I8AsJv5DwJxD+BMIfTvjD CT+D8DMIP4XwUzzSk9wPRbP1SHoSNucjfUJxcbFre7dccOvok9ZPg0RzOZTuyPrznUP96bZNub9o az2JepCfNYWMfsy9zmR+CeGXEP4iwl9E+IWEX0j4Ewh/AuEPJ/zhhJ9B+BmEn+JiAykRbETYkPws Lh/7apS6Gk74wwl/AuFPIPxCwi8k/EWEv4jwSwi/hPAbCL+B8HcS/k7C/5TwPyX8I4R/hPBPEv5J wk+wWvITrJb8noTfk/AzCT+T8EcQ/gjCn0j41BbOtb+Ia0d/K553puDzzvm8lhvwmPvg4M0GXcsf WvbNxfIzpOhfA1GeTQMR7kMDIb2i0b/eiscJOofQ4wmdT+jpkDZJ9OOEXkDoJZDqJXolocsg1Ul0 LSZBc92FJPptSDUSvQtStUTv4e9zEt0IaYNEH4JULtHHIJVK9AlyD/kB0iqJtqHSfyfR3Le9VKKT gX5WonsDPU+i062W95hBQE+W6KFW2L8t6NuAHirRdwMddNF7LPX7Shv1u4nodxPRbz3Rbz3Rbx3R bx3Rby3Rb4joN0T0W0P0W030W0X0W0n0W0H0W0b0W0r0W0L0u5ro9yWi3xeJfpcS/T5nuH7rFfqt I/qtJfoNEf3WEP1WE/1WEf1uIPotJ/p9meh3HdHvaqLfFUS/LxD9Lib6XUj0O5fo92Gi3/uJfu/6 hbXfekX7rSP6rSX6rSX6DRH91hD91hD9VhP9biT6rST63UD0W0H0W0b0W0r0u47odw3R76oY63dT O++/Kv1uIvrdpNBvPdFvPdFvPdFvPdFvHdFvHdFvHdFvHdFvLdFvLdFvLdFviOg3RPRbQ/RbQ/Rb TfRb7aJf4UezorwXu8WY+S8deQOwrgax2D/LE5+Zq49L9uHSZ9YUYr+RnjMFliGIZajBWHI0sYxC LLcZjGW8JpZcxHK3wVjyNbFMQiz3G4xF9NcqLFOxn3sIsZuI5XFNLLMQy2yDsSzQxFKEWBYajEW8 Y6uwLMb7+1LEbiKWlZpYViCWVQZjEb4NFZZSfOYtR+wmYhF+GRWWGkx1mEzEInxKKiyv4rvFFsRu IhbhD1Nh2c7C70XvIHYTsQhfngrLe+gT2I3YTcQi/JAqLB+iP+Nj1I+JWIQPVYVlH/Zh+9GnZiIW 4f9VYTmIfiQex6gwFIvwXauwHEUf2FeIyUQswu+uwnKchf0t3yImE7GImIEKy2kW9g2fYWGfpIlY RLxDhcUHx/2Wx7Rgu9xQLCJWo8LSBY57no+7h+0yQ7GIOJMKy+Vw3NNcBo4XMhGLiJGpsKSir/0a 2D5pKBYR31NhuR7jBP1g+4ihWERsUoUlywr7bG6C7QOGYhFxVRWWW+C4O2GbDdtxhmIRMWEVltFw 3C2wHQPbbEOxiHi2Css4KzzuIc8K7zMRi2oMxr04xmuAFBP5PY5xGwh7bgJqACSevxB9/wKf8P1n S/huhT3ZQA2BdKuh+HI08Yl4wBgJXw7sGQPUKEg5huIbr4lPxAjyJHzjYU8eULmQxhuKL18Tn4gb TJbw5cOeyUBNgpRvKL7pmvimIr4ZEr7psGcGUFMhTTcUnyq+IPCJ+MIcjPvYTtk6oBuA1+DkL8SY g8AnYg5PS/gWwJ6ngSqCtMBQfEs08S1GfMskfEtgzzKgFkNaYii+lZr4ViC+1RK+lbBnNVArIK00 FF+ZIvYi8JWiP7wC+yPbKVsL9CvAe8XJmxrD0MFXIx0r8NXCXz1QNZBqDcW3WRFvEvhexRjAH9Ge badsCOhNwNvk5E2Ndejg24743pXwvQ173gVqO6S3DcW3SxFjE/jeQxv9C9qo7ZStAboeePVO3tSY SEgD34cYB9qL+radstVA1wGvzsmbGifRwbcP8R2Q8DXCngNA7YPUaCi+Q4pYo8B3EGNZ/0R7tp2y G4GuBV6tkzc1nlKtge8oxva+Rn3bTtkqoEPACzl5U2MsVRr4jmO87zusD9spuwHoauBVO3lT4y6V GvhO47PLj2intlO2AuiNwNvo5E2NxVRo4PPhGGY/jn22nbJlQFcCr9LJmxqfKdPA1wXHZCdhfdhO 2VKgK4BX4eRNjdmUauC7HMeYX4H14ayNY60Dugx4ZU7e1DhOiQa+VBwz3we26xFfb2sN0OuBt97J mxrbWa2Bj8d2+LviDbBdi/jSrZVArwXeWidvarznJQ18WRjjHYxzHWyn7HKgVwFvlZM3NQb0oga+ W3AO0DDEaTtlXwB6OfCWO3lT40JLNfCNxvj27YjTdso+D/QLwHvByZsaK3pOA984jI3fg3O3bKfs s0AvBt5iJ29y/MhtfrA8fyTa+iFBD+aSxEvlIuGNNv9ZN54U9GAuSayw5Ghi6ci5JLHCMl4TS0fO JYkVlnxNLB05lyRWWKZrYhHxn4cMxqKK9QQ9mEsSKywLNLF05FySWGFZoolFxHCWGoxFNZck6MFc klhhKdPEImIz5QZjqVX48YPSXJIQHltvKJbNCp99UJpLUoNzSeoMxfK2wn8dlOaSVONcklpDsexS +KqD0lySjTiXJGQolj0Kv3RQmktShXNJagzF0qjwQQeluSQbcC7JRkOxHFLMiwlKc0nKcS5JpaFY jinmxQSluSQv41ySCkOxiDVgVFh4nGM9ziUpMxSLWL9GhYXHNNbiXJL1hmKxFf7ToDSXZCXOJVlj KBaxbpAKSxecP3Mx+lZNxCLWPFJhuRz9iz1wro+JWMR6TSosqehLvAZ9oSZiEWtNqbDweMN8nEvy tKFYxDpZKiw8tjAb55I8YSgWscaXCguPIzyEc0lmGopFrE+mwsJjBvfhXJLJhmIRa6upsPD4wFic S5JrKBbVXBIv1ozyys/vxZpRXvn5vVgzyis/vxdrRnnl5/dizSiv/PzpvyA/vxdrRnnl5/dizSiv /PzpF5ifXweLmJexymAsKj9/+gXm59fBUiPFBEzFslkTy6uIZYvBWFTzKOQ1o0Lo5zc1/rJLE8t7 iGW3wVj2ML011j7ENvOxwbGkRk0s+xDLfoOxHGJ668UdxDjNYYPjYseY3npxRzHu8pXBcbETmliO I5ZvDcbyA9Nb++40xs/OGBzjE2uw66wZVYl+/mqD/fyVTG/NqAr081cZ7OfXWceP+/nL0c9varyy t2IujLxmVBn6+TcY7OcvY3prRpWin7/cYD+/zpqEWeI7Clbs1ySMpZ9/HdNbM2ot+vlNjb2K71To rBm1Cv38aw328+usrzgOY655VuzXV4y1n7+t3484n+P/vVpPyovx/16tHeXF+H+v1onyYvx/LNeE 0hnPPAnfP+9n5q7zP10Tyy/hWxJejP/3al0nL8b/e7WGkxfj/71arynoQVwglmsz6WApRSzlBmOp 1cQif0fCVCyquEDQg7hALNdX0sGyHbG8YzCWXZpY3kMsuw3GskcTy4eI5WODsTRqYtmHWPYbjOWQ 5jymg+h3PszM/b7PMU0sRxHLVwZjOaGJ5Thi+dZgLD9oYjmNWM4YjEV8u1Nn/H8NxgVM/YZUV00s XRDLxQZjSdbEcjli6WEwFvG9V53x/9UYFzD1217pmliuRyz9DMYivrOrM/5/I8YFQszcb0noYLkF sWQbjEV831hn/H8VxgVM/eba3ZpYxiGWPAOxmHItm8/ztYjfDCj4Zcu4C5PP35b954ojvh04JmN5 vhbjFdLxkdZwsiKcN57I599mmAjpQbxWPr/oMhE/OtE47J4n9w8TPG77d3DAUr2exR/34Y/0j/Hz NbL8GucrRJmzXc5XqHm+G1iqsyZXnOJ8/P1qDsr8l8v5BC85yvmegXyGP8ff3z/an8rSYLvVP9Af hPxI2JvlHwm50f6+UAOp7EbgDPeHry0eU5yUOC3qqRPuE8f6MR8nlQvg1o8poIGZ1/EXKP+YC+Yv YlzHefgux2X+1+V8gmfh+ViE8w3SsB9uM9+IurNan0vw/FGw8foZ5ee6ywCt9ffLOrCxXqK1m/PZ R/A235a+zqRrsWNwXXYMrytS3ylsujf6j6+D9BqxM8FT2XQm1qVolz0xVsBlvkxkCp5PIbM/SI13 kVuEcp93kVukIXdABLlTUe5jLnKnasjNiiA3F+Xe5yI3V0PuwAhyh6Dc0S5yh2jIHRRBbhrKzXKR m6Yh96YIci9FuVe5yL1UQ+5gSa5J7cvtGa4jnwNj1e75uJetLPxttZ1EJ4JnKdtos57zcMwGLzfG ReYoTZlZROYkLDfZReYkTZmDiMxZWG6Oi8xZmjIHE5mLsdwyF5mLNWXeTNpNCZardJEpeOp+tH+r 9tiAZbe6yG3QlpvVSu5OLPu+i9yd2nIHtZL7KZb9zEXup9pyB7eSewTL/sdF7hFtuTe3knsSy/7s IvekptwBLnpLsMJlL7FayxU8tdzWeuuJZa9zkdtTW25rvWVi2Ztd5GZqy22ttxFYdqyL3BHacm+O 2f0krgPuJ6a+v0fCsRzj4j+x8Pdo2vvO/jkLj0n9E8Z2PiB6FrzuinfawfAGNALeVZvfbcXbK3/H TWU3wLttGmz7A3+AP/xOJd5T5Xcm+R2XvqfK77J+8t4bL6VfwrvWhWCLvCz/nu8V+J7QHlvkYzxn W+H+5CQ/IR/LFRdOa8KDkN/kTtWxbCabx+ayAnauv6sH9mDbrLt27ynqLtlx6Fcsl293L+3GjkN6 K2EHy/3yZ75EEEta1q2p9J9/s8IZk8YQ2wk41oYa5XjeT9/AUvftLSpMuHrgg4G+cbtTdrDEQ92c xH9dW12L1dSekhIm+ng5Xv7zhER/OZxz2xsfFfHtLthyXq5zHR8VnQL6a0j8nNPgLY/L7Sy1EYb1 y5/5se4cvxxP055y1N+kBx/2A8I3Nwd9LsWkH+iE++Ki9ANcTpa/L/QDze2a+mDSpPOef1uomuLU OegnLootDAw028KLaAu/tk8VzR4ILavTqaKcwGUsGbbDEhLvmQ/7eOp++Mxc2RZ4+bOIJbnJnqqm NNuWObaQh7YwC21hjostzJGesyP7/Fq+A5qnf8b6QT0eyzkz9ydI19x2xtFxL2yvljT/QVP/9wr9 C/0J/fP+sBOUHXJqT5G9bW/R1hN7inhfxM9lYb0xQ/T/Iup/KOp/lov++b7EKPp/MIKfW9eX3Vab uZDu7X700VyJmFiEOTY+CXtAmpMTaK7rFscHpOPp9zl6aMzVEfOUkvHZ8g4rPFasvXXoJ9co41PN U+L8T/Ba/m7YtQgdWtLzgNs8Kdl+RWw4BccequJvPvQdJaHPplGS0RdpYRc+TTuSbVXGLPR/LY53 TMPxjvI1Uh/XM3h9n6Dv9TPSVwhepyjviXxOTCr0KAXsCfYw/BVATxaHZWzybmDHqF37Sf3I+lK1 6460yfZei7DJQBSbpP2EsKcH0J5UdlhE7PARYofR5gymRWhv4ltJM9H2+P3lAOr7EdgzC6iZkHg+ mj3OxvkvvE7WuNjjQuT5o9gj933MY4/Dk8UUsMV5Ld4746W4aiz13tZ7S0faYHuvhd7bLI0+SdjS ek0b3EJsMIS0zreqZLsTY3CqyRhvtz7Szd74fKPXEf9+F3vbiryEKPbGn5W4pc3F/6lshrOeazyJ 4dvkeSnW/aA8h9h3nm2wvdfSnnvz3zRt8H/EBv/tYoOR7E7ca4+g3R1to93x++53iJn7qandfad5 330CLG4KW8ims6cc27PJ+AW7A/s8WceWQfZmedDnyfddPo5Zx95utFraW29L/77r1ufxMcf7cMyx 6jlvPsYZOObbXeytP/ICCnubAnfxuawQbO0xeMpr/R5od1DfZkV41j/f91cf8348Tiyvpa3Pm75z uEdHahfOt3sleymwwnOaUjBJ4xDktTGK01ze/yLVmeqdkNaHLCMB22kGnGRFd8ZUMuWyiVi2yWut KBup7tzqgGIdxcLrfvB6GTl2VHowm7E+TfiKh6KLp1jOj0K9J2EZX3bzObuizhjyef7/12hEo8TF AAD= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image056.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhJwHdAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAQABQAe AdQAhAAAAAAAAE1NTWhoaHx8fIyMjJqamoCAgL29vaenp7KysqysrMfHx9nZ2dDQ0MbGxvDw8Onp 6eHh4f///wECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwX/ICCOY2CeaKqubOu+ cCzPdG3feK7LZO8Dp4lwSCwaj8ikcslsOp/QqHRKrVqdpp8vcO16v+CweEwWB7SlsnrNbrvf5vOP C6/b7/g8WE6i6/+AgYJ2WX2DeRCHSRCJXQwICBGKhIaTcAgDDUSSExKcSAltkhGQEl4IEg2mQwpN n5ZRhUCwbgMFmkMRoRMIuEcRBWERDkW6Ew0EAcRdnkUSwUvPtFOFftNk0kUGCq9HEhAFAt1UDQi7 Q9sRBg2NR75ECctFqAXtE8Hx12HV+lQO40IkQSBAAIkDcUcQBAA2AOESBEIa/RsiD8mAgkZaTbhY BIKCAPaIPCIS7GOjRhEa/2ns1wQFSykDBQhxAAlihFUTCEAjxpOmAAZGCpgqoM4APIkT/gUzIDOm EAk4eSWdSiwBzlUyJyiwOkES0wkjk0JaIKnBMknQRn7NOUBI1pdLXMJtUq4Ag103oXYqUHOAgQIJ BiQgYGAAJAEBVpmSABSCiQQQhTQUkCCwAgGQJlRGYHeXBMPmBNgSTNgw0SEBIBuVUGqjZr5h8z4I Fdk1twYjN9tVwNfoXCVyfx8Bei9AAZ1IkgUYQMyEAgLPCwQwEBWohOWfzRFnnKCBiYMMBCQaYPw4 tOLGG0h/Hj3ASq0mNEEQLYQ6+QDijTggXp/x9fzkAUYZfu8IV0RwBuZiU/8mY0ggD0bOODBYVERE 0oUCIQ2RQCIWNrFhQgIlGFcQIg4hAQGqJPDeFxIIoABTvjkDEX9FNNDWFZztVQQDwThwIxM8uvNj iUkgKCIE5AlgQIZeDFZARUToZZAyVxzEySsOJJYllFNSmBSVRAJHYixBWBPmmWiuYSSZE5iZ5ptw XrHmE1zUGeedeFIzphR2upnnn4ASMScWbRYqqAkHJKrooow26uijkEYq6aSUVmrppZhmqummnEpq xKBM0GHnp4GWGuYBn+4JhR9+Gmrqq8KheqCq+8Bq61yyHmqCGq3e6qsiuaJG6x6/FktLsEKA2kWv xjaLB7JtDvsFs85W+wb/tMrKae22eWArrRfUciuuGN7uWka446bbRbnoUtGuuvBKwS6v8dYbxrzn 2qsvnyTiS8a7++4rl79jABywvQOnai41ySJh8MH1WkPwqg37+TDE8Eqs8MXRFmoxxiAfofGsC7M5 qrA7pKzyyiy37PLLL09MZ58ih2xzw0TIjAXNpN4Msps6tySqwz7/bETQ4BaNMdAb06t0wH4ivezT UB8htbZUI4zE1VZwnDWsrXJdhddfmxp20/mWrW6vYrur9tpJtM3w2+IyKzefdNetxN2x5F2tsnxT 7HezgKN9BASQAGRuq2QPfmbhJLcawU8H1eyx5Y4XW7LVhhex1TEfX95z/+a/hns1VIqLfiDppTeB 9HwJBIBJgTyjDPPtuOeu++68nyB1ZSD5uPrJgrJ+a7tSR+BXAnwJixrRxoPtRNsIvEVo9GY/IbWU x/SNfanvIk1AAgwMKfj3fwIctPKQWX8++niq37k3TLYEf54GB07n/fFHof/1/HtTu/yAtPCs4x4A AU4A0ZStignhagrpBN4WGKYGiu5qsatfXChYwW8dagjJcw9vElgkDhLJgiPTVbsG4z0TimiARZDb O1gFPRca6F1mkhljQuXA0dnwNzCM4fx4MYDFeAlnxHveD4G4PyFGzgjm4EwCtpGqHq5uiXDBIeee 2JEGFIYXbiqTq5LVu/8ymvGMaExj0Ezho/MUT3VvxGI/tLhFFR5BARph4egYJ8c5NrGOtjucURwA Hbf18Rp0BCQZN5cRCLXwkJZAlwel5qMV/RGSg2hgnew2RM+575KYDIQHdbW3ThLBAW58XygBMUol lpKLSYjg3FYpSkZi7pV2VIIsJ0hLVgJwCRDkWON6ObVf4jKQuhQmMf8QRNeZcgi7fOQy69BMZ8IS CdFU5TTdUE1r5hIJ5UslKLfJhkROz5SNYBDJcOZDcpZzRLYEZifVIQTeEC2J7HTnv1q5SXmZMjLZ ROIYXanPgsWziv68JhFwEdCOJTGNEI2oRCd6A6Q54DPidGDoCmpQSVb/YXtH1OgtOUos+330mZ04 4sL4SNJamfSkCnVGSF/a0qTx8AogHVtNp0VTmH7zFyS86U67Bs8v/K+nQ5UmqYYJwmdypkO8TOrM DmrFdaGUFJ80plRDRVXnGRWl4DHkVndGra4m9Kd3zCpSx1okqjL1aGBljljZqsANkuFql5krXUfK VzCcrjZK3StBY3qvIXKmAIgt5CwFG8eavTVu8xQqSxk7WIWxQWYI0AliEUujy+FzoGxNwYjaILMI sAMe53jeZx8bymyx9piLRNd1lgra2m5VWa8d3ekkELsrPpSiwA2ucCPKtZvYg2YbpWuvLCgnc+mP RJMNrQJzG7ldHVWo/0NdXFGd5kS0ujS7uKVuxc5GWJ4mFbdqoup17QrezYmWV5NEKdZ2ykezdu29 W5MvUfUJ3eXaF2//faB+dcpf9J4rwE0tr03daaTFiTdaCBawgovJ4D1tUrwrOCsy/1Xhe76WufKc 8Hxbq12HtZJf96XDeuu6Svx27MVxALFvJexdoVU2n5hU1YX3IRdNWnhU/xtaciHZ4Ajb2JAtoPGG vbdaOfbXxEa+IoRPLLL4iriEcLwxB13s4D3016w9djFcrwy93w73zGhOc8uCXFUtY+/LOo5yHFXA VWuI2ZtLniqO3Rw9/H7Ztqsak2unvGMNx5a7/NMxhAkc23D9WM6KnP8yokkH55LJeGMOdjShF/1V Mus1c37eNKBvKeY4s4rKPs3zd9UWHD9furqisrSiXYJqKqwYy2/LMKFpuDMV2tnCjX61VT292Ju1 +thUZiSdERRrXaPsDreu4cEeTWs68yvJyLS2VwUR7b5yy9S2a/aJBV1kS0s6k2F07oA/rTn3upvW 596zqeFcPBeYwbKk9LWuu91Os6XbTDZAqL5z0NF8h1sG+Oa3lOMH8HnPYOA6MHhlaaXsdz98VlNQ eGNfQvGGyzrgEMeBxDn97JDfYORjWHF03wDukc/b5LlDq+4Evu1ArLfJJF/kOlH+6J2X/OBqjgG+ f15zIt28ts32uc7/fxp0GMi84TRX19FDN1ymU9vXNcbe1GHd9K57/etb7xmzoRvvc194pWIcJ66x y162s9jtb2+73ONOd2EvfONzXzvd9y7tvPed794OvODvDvh+673s91b73xd/+MYzfvB4dzzkI/94 w1ee8HanbJoyr/nH1brzcOI86Esk+tEnqPSmFw7qUz+X1cO9ymStc68la1cwL92xXY31aPf8QRjD PucY92CXp/rg3td+rZJ/Y1l131ZDMavEJubzroZWZt/7lvpiHzX1l0tG3kO5+JS/PPALr0RNe5+g ZR3/nDeIfSybf9SIt5yj2w9P8PMZ48d/ffbZm/7uT/f89OdY58dO//1nfcMzgAFIW/CXdQWjTcl3 fyi3R21XgICWgNdXgBT4fOHnfDeFaq7ndzOWfyAYgiyWfhaoWgA4gD2kgdInUNVXgfe3fcTHcrPH VVrVfLRXV7ZngMrXgc9Hdt/Hg4d2UPDWVtMHMB/IenP0eUpIekzYhKf3hKyjQTaThFkzO5vwFEHl BA2QWgrAJXdihU9jC+9gDLxQIFNwIhUChnEihncCDHCQDUSQDkiAhhoChuCwUDMlQFLoK6uQIWxI EQ5xR7kwAQPhSKc0iJKBiIYIH0wSDI0AFbxBhR0EabfiFW8hCdwjFVQhFj/hDG4REDiBHJ3oAD5B I1uxCpgoBGFRBP8FsBYSsA4GAFht2Ie30haVsQptkR2hQQASoACkIR3VkxiCohpPwReQ4BeAQRqF cRjE2Amt4Rq5iBuAhQuAARkQwDyZBShueCf28YzUgR63oADVwx4n4CUfEQC+oBxy5RzQoRPTERXz 8SPf+B/tcBNCUAAB8h8fkj62aCsf0iH9SAUYQgYBOQ68xVsQAVXg84+vEiTCAxZudBpPkCNy6AUQ aT4BYQJGYSO20o1vkiUOQiUiGSVQYCUBAQYiuSVIwAhfEogMZ4lQmEUOOZNLKJM2eZM49HU82ZM+ GWgBZn85iXxBeINDSQhAaU5HiQdI6IFwMHzGt0/w9XtHJpWEwGv/AIhgICaUrjRkjEZ4C2iUSKgm TKknSal48YdpZ0dKy+ZRYjIqSSZ8YIZw5HZnDOh8mSZGR7iXb1l/a5lhtbaVRuhRyGVnntVPkmSC HIiYKvhZw4NcDpVPkOl+OriY8MaY8DdKPAOZiNmUZwBDIldvHtNqh5l2wSZ0IlWa2HdyqqWXZhd8 eAlyfOlZi7aWrsKatFmaoymEUDYLRMmbBziZtHmEC4hecLmbJwiByHmYHNiVmalpxxlq06eChBKd w9lPU+Wb+peULHCa3dmXlblpRbgsZ1dtrqZtOlVttdmadmkybYltZKWdI0hpYSlA86lCIuCW94OT rfd+dSYH+rmUS2UpNCeQBvcpoJM2mD2wfD7ZoA6KZv8pCwaKoECUAnPAnxTKTSqABg/aoR76oRJ6 oSA6oiSqZmiwoCWaoioaUSfKoSv6ojDaMicaAgA7 ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image057.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC91dDXBVRZbu+3Lz8iMyjOiSAcHAqMHHP6I4pYWJaERGx4wgMKOWoGDkH0JMMCA8 hEAg/IQQIEFQnJlyx1lFdNetYXZ213Jn1p+dctEd/3Zgl9Kpqa21xmXdBZl1d7On+32ddE7ue90h D+jaUM3tfuf2uffrr2+/7nPu6RcIIRZRykV6OBDihOj8u/QqIRoHCFF8213lQgTi2E+EqC8UokCw v5BSjhB9qf7fMdHhIaE4U5QjSIEYSamYEqkbEZQG4nLK96MU6/fab6iqmI0kz72fUgXOHVYaij7Q N6S0oCN/JenQ+bGlMaUrVKXkzUNL8zpkYanoyBeJzvw3kG9vbxeXIn8xpUuQj1EaSimf0rDOc9uj PisEFv2nzzGvYV7bvN5Y5L9GN341HWW7BDgvMHRehfPkZyXAEoNM6jfPiRn5PNJ7Vee1ky73HaUn yIDHt2udre4haFf99wid/Akd76G0LFDdXHypGxt/TSmSXpHwpov5YrGYJ1ZQT/8OHWvpeI9YSp/N EUuE+9+igsKXfn30TfVc6ntLHf9U1H359lj1bPU5LsZedEThleffj/Nm0WfylpI4fvDyG7UCz96Z K1eOPXzxEbE6fkTkk7z40f7i93P+a+x7+cHc8WnuRdaRR8nff1f2F7+mJPXup+NBql/Izl9Jn50h nX1QJ5YaHjqGigGdbdbxzA9pv0Le3oC5NYq2Dq5yjLYPM7e9qKa2z8YfteXh6LY3xjVq+2MFHW1/ WLd9WJhq85GF0W1fHTsi7u9zRPxZwblv+wK0n9n2RenbvoS3fZiGB9kupzLwcBfxUC2qqMf3mocf SB7ilO+Lz/pGPAMGDz/oLQ83ZZkHeb8XMR5k+w3uAQ+5Rv5iY8zL9LnmSrbd6fMzXr3gMl4ZXL3g 4zOjx6uY8cwM7MF4Fc8Sb3nn7xl7MfoZ6zrWGd8zL/b2e8bHZywvDScun/N5iHl+pjlJXhbnJ3o+ mM/aSOuUnw+PuBZ9nhwecV0+RzXnxHoen4ek1w2DkLI5hx1u3H+R0Sb6HvTaZTYpPG7cw/ngRrB7 cuWG43TlJh0fM7CG0NeZSSc/j3YpoU9mBjI9T/nnVZnzI9Lwk802zO9hG5YAr8TyIp5l+fkYSkfl OGnw3Q/ntziu6a5HHam7helIMnmSyRcy+UImn8HkM5i8jMnLmHwUk49i8iImLzpPPJnjUKa+no4n 3edibExIJpORz3sQgduFT94+zxtlqYeXz2X7xc6i/VyfTXO86Gk76XYw5/lax5Uius1MeQuTtzB5 ksmTTL6QyRcy+Qwmn8HkZUxexuSjmHwUkxdF9IFBafqI7kPmOsg894UMbXUjk9/I5BVMXsHkc5l8 LpOvZPKVTL6Vybcy+bNM/iyTv8rkrzL5W0z+FpMfZ/LjTP4Fk3/B5PGgqzwedJUPZPKBTD6ayUcz +WQmn8zkM5mc94WzHS9yejHe6vnOHIyrF/Je5Ll/ROn7dPIhj+7lT7quwZLmHFKPr/kZ5qb5ab6H 5JzzaYfxVR4PGOVSuYYxylMpPWWU76W0zyg/SKnNKEur1l6jvILSHqP8BKXdRnkTpV1GeSeSLst7 aTLKz1HabpQPU2o0yj+jtNko/4LSRqP8DqUNRvkjSuuM8ie4R13+PaU6o/wlpRqjHAQpjLp8EZWX GOXLqLzAKF9B5XlG+Zog1Ya6PIHK3zfKk6g83ShPCeR6urMs5yzljPe9jN89jN/djN8Wxu8uxm8z 47eZ8buT8dvE+N3O+N3G+N3K+G1k/G5h/DYwfjcxfjcyfjcwftczftcxfpOM3zWM39WM3zrG70rG bw3jt5rxW8X4Xcr4Xcz4fYbx+zTj9wDjdz/j9ynG7z7Gbyvjd28vn98djN9tFn43MX43MH7XMX6f YPw+zvh9jPG7jPG7kPE7j/H7ION3FuP3u4zfKYzfUsbv9YzfEYzfNsZvK+N3L+N3D+N3N+O3hfG7 i/HbzPjdyfhtYvzuYPxuY/xu7eH4vNny/NYzfustz+9axu8TjN9VjN/HGb81jN9qxu9yxu9Sxu8i xu/8iO9lPZcPMqybovy/8m8EZAm0/yiMCdmc0wRsjhFlAzFtfHxOM4jNL9LNQzSWCRiXJqJ9fMSi 50Y2LJMwppYBu49Y9LzOhmUKxqNvA7uPWPSc1IZlGsbSGcDuIxY9n7ZheQDfA7OB3Ucsei1gw1KJ 76wF4MdHLHodY8OyHN+31cDuIxY9h7NhWYW5whpg9xGLnn/asNRj7tIAfnzEoufONiw7kJqRfMSi 1+02LPuwPjwA7D5i0TYHG5YfYe77x+DHRyx6Pm7Dcgjz8peByUcsei1hw/JTjBN/gbWmj1i0ncqG 5XWsh38JTD5i0TY2G5ZfUXqS0t9jfPYRi7YP2rB8gHXnx8DkIxZt27RhOYHv/k/x3e8jFm2XtWH5 DL6mz4HJRyzapmzDcgrzyjOUaj3Fou3hNiztmCvHYF/xEYu25duwFMDm0we2IB+xaD+EDUt/Ou9R qQN2UR+xaB+KDctgOu9h+e4VHR/xFIv2/9iwlASpNX8iSK35fcSifVc2LONhQ7+Ojvd5ikX73WxY bgpS78HeHKTsUD5i0T5DG5byIGXnu4OO3/EUi/Z32rBU0Hm3SpsfHW/3FMtIi31sBs5JwF4zGrbB UH2+m8ptJGtTeV9t/3sc8E2ATeYG2P9CVbeFyq0ka1V5X/0Bux3wTYKN6hbwHaq6u6i8l2R7Vd5X H0GLA74psEPdCb5DVbeZyntItkflffUb7HLANw22qZngO1R1d1J5N8l2q7yvvoRmB3wPwFY3B3yH qm4TlVtI1qLyvvoXXPBVAt9CA998+mQhlSopzfcU3wqLPVjjWw5742Poz6Gqu4PKu0i2S+V99UM0 OeBbBfvrWvAdqrrbqdxMsmaV99U3sd0BXz1srJvRHqGqu5XKTSRrUnlf/RXbHPDtgM15F/KhqttI 5R3qn8z76sPY6oBvH+zKT4PvUNXdQuXtJNuu8r76NRod8P0IffPH4DtUdTdTeRvJtqm8r76OLQ74 DsEv+Ar4DlXdBipvJdlWlffV/9HggO+n8C38HO0RqrobqbyFZFtU3lefyCYHfK9jDP1b9NNQ1a2n 8maSbVZ5X/0kGx3w/Qr+lKPgO1R1N1C5gWQNKu+r72SDA74P4DP5R7RHqOo+SeWNJNuo8r76U9Y7 4DsBH9Jv0U9DVXcdletJVq/yvvpY1jng+wxzs39De4Sq7loqryfZepX31e+SdMB3Cn6wP6Cfqr09 6JM/UOkUJZn31RezxgGf9MXId9pzEEMaqrqrqZwkWVLlffXPrHbAV4B39C9Ge4Sqbh2V15Bsjcr7 6rOpc8DXHzEHA9Aeoaq7ksqrSbZa5X3146x0wDcY72QPRXuEqm4NletIVqfyvvp2ahzwlcAHOgLt Eaq61VReSbKVKu+rv6faAd94HeOC9ghV3Soq15CsRuV99QFVOeCTPiAZU1KK9ghV3WVUriZZtcr7 6hda6oCvHDFIUxH7EKq6i6m8nGTLVd5XX9FiB3wV8HVPR3uEqu5CKi8l2VKV99V/9Eya+FEzfiTT /hIJI5bkAGJJDmbZX5Zr1EuHN1N87CAW62bDMgG2m4nnIC4mW1hKLXExCSOW5CnEkjztKZaplriY hBFLsg+xJAc8xXKvJS4mYcSStGEM2e8plgctcTEJI5akFbEkT3mKRcel2rBUwge5APz4iGWFxe+f MGJJduOdv1ZPsdhiSRLnIZYkW1hssSSJ8xBLki0stliSxHmIJckWFh1DbsOyD/6JA/Cj+YjlOYvP LGHEkjQilmS7p1hs/pWEEUvSgFiSRk+x/Mzia0gYsST1iCVp8BTLLyx294QRS/IkYknqPcXyjsUG nTBiSdYiluRJT7F8ZIm/SBixJKsQS7LGUyx6nw0blhOIVfgU8Ro+YtF7hNiwfIa52+eI1/ARi97f xIZF+jSWIJZkuadY9N4sNiztWB/EEIfhI5aLLDELCSOW5GHEkjziKZbLLDELCSOW5AHEksz2FIve z8eGZTD2R5WxJN/zFIvei8iGRfob7kYsyT2eYtH7KNmwjEc8gIwlucNTLHoPKBsW6UeYhFiSMk+x 6P2rbFikz2ACYkkmeopF771lwyL9A9cglmSkp1j0vmG2uJgEbE+jRPb3jcmmnb9VuO0ZtQd2fl9t faXCbQ+cSbCjlXls65sq3PbAmQK72LdF9vfAyaad32UPnGmwCc7w2G75oCVOx9wzqhl2/t0e2/ld 9vOphH1zgcc22BWW+BRzz6gm2Pl3eWznd9mbaBVstWs8tidvEm57E9XD9togsr83UTbt/DuE255R 28CJr7bx/RbbuLlnVCPs/L7axp+zxI6Ye0ZtgZ1/m8d2/gu9Z1Q27fwXes+obNr5XbC8Diy/9BiL LRbC3DNqA+z8m4S/dv564bZn1HrY+Td6bOd3wXICWD71GIstnsHcM2ot7Py++pL0Ptcue0Y9ATt/ 0mM7v8u+ZO2YX8YCf/1ien9xlz2jHoedf7XHdv7HhdueUbWw8/vq47sicNtjbTDe4S4Osr/HWjbt /NXCbc+oKtj5H/PYzr9cuO0ZtRR2/iqP7fxLhdueUYth51/msZ1/kXDbM2oB7PyLPbbzzxdue0ZV ws6/wDMsvtzLoQt8L/pP/wZhb36/uLc4cnuB4z7UlzGJA0X0b32ki9sI0t9DFz1y/7pFsPvKe5LP 52WoL06+V3bvY/9QpmWy7p2YI+q/dvxJ/3hJfHI8ER8eHxdPPTOh6PwNY9s9zMK7JvmwcfJ70LJY hnuoUD6r4o7rZrreMbzPk4/1CL+elhVluJ6ck42JTyG8t8eLhcT9UnwCtUCxuI0+vTZ+G+Vuj5fE p9JxNEkmx1P3pn/zLoe1j5TFcd0clHPxWWicl5Pqj+oYR8pzwDwL8eVS/79GYP5tltt4OtZJUufJ iOtpWYDriTTXu150/x1yfi0ZE/nv0FcYdL+WluVlwCZ/B7w8LrkbQ6yNI7a68hCibXIt2C/kWOL6 +9o+3kuYhfsKs3hf6cZV3bflmPxD1D/E+puW2fr2WLSlqXM7dLZF6NzuoHNchM466KyP0FnnoHN8 hM550LksQuc8B53XRuisgM77InRWOOicEKHzRugsj9B5o4PO6yJ0lkDn+AidJY5jGtd5CXQOjtB5 iYPOiVkaZ8Jz8GznnKc5YbaebfkOjNzrSe6n+peMDy3r6XM4CfVuidA5yVEnf2amod7MCJ3THHXy /l2JegsjdFY66pzIdK5CvbUROlc56vyWoXMW/Eev4D0FrlPLYlaOxnXMx7TeZ1H3JxF6n3XWe203 va+i7l9F6H3VWe913fS+hbrvReh9y1nvxG56j6Pu7yL0HnfW+61uer9A3a8i9H7hqHd8BG/y97Rl 3a8F3fVqmV1vd94Gou43I/QOdNbbnbcxqHtDhN4xznq78zYZde+M0DvZWW8nbz6N276v5dPhkP6u IyK1P9Q7Gb5/XNfsH+GdE7lf32mMASbPWjbAsn6dSKudW2ml07mO1SvV4WoFNIrWscPpOI7k4+Op dZhek5prI3M9y9ek5ro1zta4uUb6f7Keirxfl8/PFkdeL3DkYl4yUKTfpy5Ic608xpOME1gWpM4/ JS8o/fA5qdSU+hHbV6Sx9S4xX1SLKrWX9Nn9Df3wG+JwcPdrb9YOMPr0wa+LCnl8bUN/8TmlH/c5 Iio++V/pChD96vt31P75LY0KqwC2k3RuSK0l2+JvRuwTxUffrv1hztAPG94fJi7POSIKj/VXSf5J mRDDhJTL/FjSO/r0m+p8mb8J+Wl0lPJlDQdFOOyA+N7JNvEANZgsy7eSZN+XZdnGZ6he03+0KZ1S LjHIY9V/tqnzV9FR6pD52ZTm1ihqu+wVMx3vbEpBFWwt69iYkI/PcjKMCVLPtfESGhM6n/E443x4 mn5xYfrC/ocUF8RPTqa+kNPZFxrQF24IT9c2TaAnK/907ZS8y0QRHa8uLJzcSp/JNOD4V1VmX5D1 24GlqKM/7X+os28FHW16MOeZmO4j7xYUhq10zuGX36iVx7+mo5RVqHpv1J6m8r9Qku08VzSKvtJH bIydAs+pXBei7RTXMqXrC9PRF5agL1RF9IUqY86d3tbXzS7jGf9CjKR2/N2Ur6r+h9I37/hKcTwE z2sgOn8/25H/WzX/mj/Nv3xW8/GMh4ffrn3p5Ju1ciyS1wrQbsIT/hvAfyn4XxLBv/ysMAP/s9PY t11t2D3tMz5+P6b7npcYr6Z0uej+++ycj+HG9fRvuud3tnWX8/OZL8j0Edl8k2NEav/f7waptVtv 2y3O7svEZPNdSbvmu7iXY57di+YtZswBOG8x1me1n1jaNT508L/FYOOTde5GHa1jMsq6LwSOfSfK /ycM/mVc0Psi9ZtGH7F75Dau1RijZbvId1h+w8aHe9CX8jOsE6W/pFgsprF7hXiU/s2h0SsHdUK2 NgizNGePi+g98mIOz/K57JO9vRfdJ/Mz9Ml8oz/EjP5Uj/5k64cHWD/cyfphLE0/5M+C2ffM3294 H7EpHwv9+w3vU/ljkn2s8pn6o/QhPIM2+fOI/ngQ/TGeoT/OUr7jpTSbeIj6YnWXdWeu4UPNJu8x Eb1P44Xog729F/59FjiMSeZ75i598Bjrg0dRjtqfMpbhu1DH3b6Dfvcuxrx070jw/ibfD/8n1JN7 WvP+9s+4t4IM/U3Oj2RPq8L/xaJS/S5mLvPX8/cgsj0OmnOa4AL3wd7eS2++m78euPXBa4KufXBw 0L0Pput3+rt2UJDqd0OCnvU7+b07MkhhvjOi30mZy/fuCupxD4k6MU/UqL4XsvcUwnM45pkcxzzq bzFx/t+DyOa99HT8jTn22XTPw0g1f+sck2Zj3TAIyfAHm+uxZNRaLl079fRdPVNHAZ7PS+kijQNo pW3RadYtRN0Oi6Glbrq2i2oDjrUc7x3IdrntrvIRCVp0X9mBL3kzltdJM18OrvuhTqy085p9wZnQ +Cn9H2oKaCjcqgAA ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image058.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhMgHeAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAQABQAp AdUAhAAAAAAAAE1NTXx8fGhoaIyMjJqamoCAgLKysr29vaenp6CgoNDQ0MfHx9nZ2fDw8Onp6eHh 4f///wECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwX/ICCOY2CeaKqubOu+ cCzPdG3feK7vAen/pYBkSCwaj8ikcslsOp/QqHRKrVqvWMkJCBRmv+CweEwum8c9rsh0brvf8Ljc nO7O7/i8fk/nevmAgYKDfHUlhGUPUxCISw+KYREIkI1wJj5/lVgRBQlDCE4MA6BEjBIRpkoKcRAP CA0OYQ1DEUikTbWaT5drulgMBASeEhCZSQUEDEUPBkMNykoPBRKUWRAR1dQGDgMBt1iuQ9nExkkQ Ar5OvADl6VAJAblD6EwERwoJs0wQENMC8lcgKGiQagg+AQ7GFQFYBAG0IgwSMNB3BJ1Dd1l4tcPo RAG9IdPMDTEgoCARBwIe/xqJEKDBNAIBYjFZRWyIA3kqkQwYkITmgI9DGCGIaSQBzwY0jUwbKtNU KyJJOSLRKDXUEGUR5YWUEDGBp2tQ6cWK9axBSyQFYg3YpsAeEQOmsEqwh0DAI5i0ZI60KYEsAoDQ 6CF4FbSuIgc0uy6YJs0Io5CIJRiW8JMI0KpFUGBuEqBAARRaS0UYfWqA1wQFDAQTgIBAa6/dhvU1 CNKEgVsEBARQUEBAAt+rDKDu9PcU6wStAyBnTUCBCYCdUZ9C4ECfgE4NnpG6NnqaA73zpEHQLkG4 53wFHkjfbEQzeyVmlZvYKoHikc8BfEv4XLcuvG1FESNASfAwgA8tCRjAUv9L8qk13wBulWfCALDk 1998RsSnzAMDQuKcfAgd8QADDEmgQAQNsBRiN7tdV0AEKb2X2QlS0KhJAiWeEYFsJyKxYwMUJsGA TAq9k+MQOA45BY5IKEmNjFPZWOON9jDwjY6stXUZETtKINtKEV6RgD2cHAFMBGE+AYyPaULZnpRR bMQHAyHWBAcCAxRgnxEPgLeSfr/UyRADygEKBaE5Gfelm2+yMSWjkEbqi3txRhnAAZhmqummnHbq 6aeghirqqKSWauqpqKaq6qqsamqpnErICauktNZ6xQFHUAqFrLb26isWuDY666O/FmtsE8HO6CgY wx7rbK/JEqFrRs9WW23/tENMi0Wz1nYLJbZawEmtt+TaCq62V3Bb7roYnSvutuzG66a7y36hrrz4 EkLvvZzl669U+4rB778E3xFwGAMXrPAbBzO78MODNGwvxBTzIfG4FWc8x8XqbJSwxiB3/AfHTHjR zschp5yEECPn+m7J9Wam8swZLUvyEiZPRfPOVdR7c6zZCsvD0EQXbfTRSCetNAo/rxx0rjxHvesR Ta/ssdRY44xE1cRm7fXTVLscM7xffy0n15WW7fXZYqOss9pYw4r21HDTjG4Rc+9St93hMpG3Onvb Pezf/QaeMreEl2z44U8krvXiGqvrONCQV3zv5E5XDjG/ib/stubGDtw5/+Wg+8syFYS/rEXppq+O ettKRKAAdTK73h7r+aqOLOxIOBAAA3S+ne3SxBdv/PHIJ8/CzQmsQmjtJ+Mu7+dVgzVj5tKX+7kE TT/QQAJ+kp59twlL+TOHQzVAwJ7Cj1/tx+bz3pNqfbUJtfvHsoFy/MLiUkv498Pfr3JmBf4pC1YQ aM6YAHg7ARZLd4XDm/yY0IAtBdCBvRrbLtqRNwbWDoO22p8SmpadIrUPhJDSIM7uNoSfDUABKKEb ClNIBRa2cILLGMVvZDhDKMEPgtzD4RGwwcMesmd/KpRg/xBmxM3YUHGNE2K6moiZ0/UsCpg7IRXT AURl9Q2LUvzEdZRRgP9UXG2LHOHXE5NQNXic4oMNROOkBtZFNoYRKvG4nhblSIgffqxpdPIKAXIx NuUZ8pCITKQiUzC3MQ0venwcxBqjlIUOSgt7kQREHYcHNmAJETEmtF0cM1kIdaUgDBxTXy1IU0RS 4kGNm4ziEovQPNQoYHatdKUc6BhLJ5AsAvRzo950eYckWs0MVXvAkfZITDLojzOOMmYl73gV+kCx mWdgWbNO6Qbm1UcA7BMfNp0pyhVuT5YHRIIBoFGXXI6TWdKUVjzBcDNQOMA17nwn2YYph6q1k5/6 tJcpzymFpt3zSo8LaM8IGCsaEXQK/rQgJhU6pXhyMw/JXOYFKRqneU7/8gxtNCVHp7DJjyKTmvDw kwofqsuB6sGA8lShTEwDPWaO1GXm7CU5WzbLIkCAFEbZI0vR+EyYzdMNMH1kOxrjpXJocKhU1KbI oNrQaF70ZrkQ5ijDtciuevWrYLXBz4ZEgGZcspydvGlMYXfUMmjLZtRkpR43etMkXvQNNnJoJq4a V43SVZ8ONSpVgQYnFSj1hj0dol+3GlCp5pSqlLorV43hnqbJFXAjfdeyBiszbubVsEtoGj/SptCV SnZbMTutSYnws98ACKDvhNVq9WayzR7wj9Rsaj7lqNe1xrStlrqduEA7W8SmUwmB3C1Rv7hWnVKu tpEFLT1zq9UItrSQ/85VnK4uWtzQxnV9ysXgXk0LXLHdVqnZhWhu/4nZLZ5us/B12GTR+1s4VI0B 1kxoVId72g1SVq/97acQEeCZAi9Kv0Z8a3pXZ1XpzlcPJDNJeEsX38IGuFFCY0ElONaWYHjGAFFZ KQq1+QcA17BvLahvI0iWDQI/DZIOdKyKoflfF1QFbSxhLFqzNy2TAtjB3cVobiHgAJLA8cigs+qD jdnjFzCKa8qshlPDSuUqW/mro5uo5vhbyFd9trwAy60UOWu68UrJwZxM8XHNJWbS7o3E0P1ynE0c ZBll8a9m43KGf0vmMCd2n3ErcQwmO2h83VnHfHOPolfAZy/m69BI3v+ZnGEwM0if9XCCZjShM91n X1k6rQqr8Q289ukda8+8lG5yp61V6lUjYso4kF6rBzjlTdOAq9mbta+czGdOgzlwunaTmVPLaEqj MNgYIbZneW3rBs/QcWd8KYx7PYPbaliOnYs2Uts2NAyjF9Z8hLaW03UyZjdbstitsxHFneEru/vd 8DYau/GMZGNTW7XgtrZaw/bn9sZR2Wq+94XX/G0079u4M3Yz9MxdaBq3+9oH926/C/jIh/tY2QIf eMSVSPBx2ducODT3xtU78SviWmSJlcHIUdnm3XJZ1DVYuRh0/XJrp9rVI6d5vWzAXJnjQecq/7XP 2wD0RQ+9XS0fptD/jx4IZDP9PU5/+maiLvUbJ93fVcdMtseddaSXPHPT7rqfO164sIvd62SHotnP no7UpTXecI+73Ef99betXZzWzfs1sb53vSO4737H+98HT3gtz1Z191KjwgFfeJs6nt6Ph7zkEc11 weNd3ZOPNAgTv/jGu3XBbM8g6ENfK8yTXlKmP30KR6/61S+99ZFKPexlJPvZH5H1lPTvrrj1UYvW Fma+zT0nj3lY4ffc7sOC7jUtWnzslbf2lK985qN/1uRfWpyy1fz1QX1phkLN+zorsdbAH37tv5f7 VR0s5yes/QZaH/1wnNVe+579F6sds9uE/7/7Rf6c0qGjnWd59/N+/6YWf/W3fVt1gP1XU2VHgPmn f0GzgFbzep43fRBIfY6WUASof5SFYAd4cs5nXfLXfp00ghW3exQogNJngYoXQRtYgOX0gSaIgJ0F gVYEgzc4ghIYgTTof850VG0FXC7lcBD0WSB3fN6Gg0oGckWoP/LnhA4Hg7gGZtBne1VRhVaYRrhX ORL2ZltoOKLwDaaACl/AVJ+QKO/zhXuDDCrBDM6AhlPwAGGCHOuChcVihnLQJvgQTrSgBBeBBGHS Jdqjhs4iDxIGh0WAEoiYFKZAEl2oiEdQGY4hGUQRiUFxCl5RRt5ih8ViCpMxhuBhVmNRHxNxFkTw EPRgPSYiFrNRFv+mSASDMQueaBd9ERVEsBR2EQEDEBFmZS2c+Cu0KByzQIswggDIARPL0RqvYRTK IS0GoB4hoYunkRqroYzCwIyyIQnVIQHBmA/kwSUgUR62ZBoD0IWhQ4jH0iPIaCK5YAATUiGsEY// 4SdmASMPgR/6wR/yGACvRQQcQovqCCJ60Sd7wSK2YY7nmILdwiRcEQsMaQUPOQYM6SQLoSDNcxUe 9Cy/2CtrcgpVkiYwFAWOdAr5dQUdiSZI8ADzoQgoGS8bWSuIoigx6VNRQCd6sViH8juKkgQPMIaG UofomIXu8JJC2QhEWZR9FJRIqQlHuZSB0JROWUoK+VhzV5VW+VX/NMYObYBzQpl8l0BmXJmFXtkD YCltw4dTrxSWSHiW0JQHFDiWWplNuzcxtsMrWzlufWaXsEVSzEeCgfdbvfB/U0VjkxaBTmhiFMeE GmZwuqeYxUZcmiF0N0h8hhWZxvaEVCGYNtdwPJgzFQaF0USYt8aDX/R7kzmBPOc6z2RFq7lwp+ll 1VaXpXl+rTmZsoUCh+BW/pV/rFlUv0doF1hV2jV8cSaFR/hcgVWcohacwaV2eWWYq1lUHLgFuUlO O6Wa2PmbUGicqDmcpZlm3DlFKMZg4Dl/9rdtjvVenkme5ullmABV8FmZi3mYjIkwmkafSplmp4Sf viZjn7dp80VAQdLlMbj5A1PZg8Qkfu9RbgVqoAeqlrY3bA3aBVdZoRZ6oTOgBkGAoRzaoReqoSTg oSI6ovEGompAoiiaoocEoiEAADs= ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image059.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC+1dDXBVxRXe+97Ny49AU9GC/JlQlPhACGBArZRo+QsVBUUmVik/8qMtiAloEGyb VmmZavlNyP8PoJWpWrA/QzPDjLadjkyqtloGGX8YwLE6atVhlGq1pmfvOyfZnNz3dpPcvGyYvszm 7d5z99z9zjl3795zdvc5QojVkFIw3eEIcUq0fS64RIjHBgmRNWPuTCEc8dBzQmzuJ0SaYB8XUliI AVD/r4x0cIQrPh0cFsBAjIWUBQnYjXHyHTEM8pmQQpnPvgZVxRJM8tzbIc3Dc0fmu6If8huRn96a HwU8KJ+bH/J4uV6pdFp2fmorzc0XrfnBoi1/EeZbWlrEBZjvD+l8zIcgZYsY3pFt57b4HctALPSh c9RrqNdWr5eL+a9Awy+FbykXB89zFJ6X4Hny2GjEEkKa5K+eE1LyqcD3krZrl5q024+PkwCPbdfq Ku8RKFf6rIST34TvmyDd43hmLv5NwsbP9piSfiPhLRB3iTVihVgHln4DfJfA901iLRxbKu4W5p/V 6RkHjv79iHdfUtti378VG//dnOvdW/3eELnnNXl45fm343mFcEw2qRS/jz39XInAe+/TURtyD/Zv Eg9EmkQa0LPuHCj+tfQ/uS+nOcsnxmmLrCO/pf6+WDVQHIUk+dbCdyPUz2Dnb4BjnwLPflgnFOse WruKQW0ya73nR7RcLJs3aPl9se6FdBVWZC/rfhJf9mIuyH69KAZJd+8DstwrZR+B/AA8NsBH9q+n t8p+L8nezYjJfGyGv+zXh5rE7f2axO/S28v+moBlL9t7HsqPZC9taXh82Y/msncV2adoZF8AvfUC Ma7bOgBZPu4ve+WZ0t7uH++u3dso+xSmB93x/kpfmOg46VPK92xy+rEnTfox5V56srv3Uk/2YyGl HxvSiX4s0k29dfU4f0aq5yd6XroBPjtprJLK5Ku0UeT4XAvaU5rjc10+flLHazTGTMVEY9qhmIIc X+Uo7R+syITaQOPqJcDwhNKGZOhGsDaZ6objNNVNPH0sxPFtLmJfBCfvQ7nkwpFFjkz7IL/PK3P9 iDj6CVKGqZ2UYS6OYSSWx7FfH4y4X4B0g6LvTDy/3PB9YzLWkbzLGY8tjL6F0Tcy+kZGX8Poaxh9 MaMvZvT5jD6f0acz+nRGn8zokxn9Mka/jNGHMvrQJNmB2s8lupfi2QHZdIj1OaWlpb79ieOD28Re uHz2KWXJh5d7Un6hLsjP9N5X+6POyonkoL5fEI/Lhb/MVHo5o5cz+hZG38LoGxl9I6OvYfQ1jL6Y 0Rcz+nxGn8/o0xl9OqNPZvTJjH4Zo1/G6EN9bGxoHBskG1Xpv0wg/+mMPp3RCxm9kNFXM/pqRi9l 9FJGL2P0Mkbfz+j7Gf0wox9m9JcY/SVGf4vR32L0zxj9M0bv77Sn92fyz2b0bEbPY/Q8Ri9g9AJG X8TopP/u9kHhbvThNEZbin11b7ZlHJ4jx4v7LWrLY+3fP0vVcS/12akJxtOpcZ5teZD2GvTZ0/C8 Vrti5Zsh7VHtipVXsXIRK29i5c2QGpXyNlauYmVpww1K+SlWPsTKf4RUr5Sfh1SnlI+x8kn5jqqU 32XljyHVKOUvIVUr5TQn1mYqnw/lSqU8DMoVSvlShz3nnFhfR+WrobxT7YehvF0py3HPVrUfhvIj PnpPpN8955h+6zX6rdPot57pt4bpt5rpt4rpt5Lpt4LpdzfTbznTbxnT706m3x09rN9Gpt9Gpt8G pt96pt86pt9apt8apt8qpt8Kpt8ypt+dTL9bmX5/zvS7men3R0y/JUy/a5l+lzP9FjL9zmb6ncz0 m830G2H6fRseBqp+/wjl/9+/Xb9/a5J8/5Yx/e5i+t3B7t/t7P7dw/S7J2D98vu3Mcn6bWD6bWD6 rWf6rWf6rWf6rWP6rWX6rWP6rWX6rWX6rWH6rWH6rWb6rWb6rWL6rfLpn8n35yR41/aLl8vPGKRN UnQR9Fie+fl8/XKq35mPWYey/ineOJOwTEUs+RZjKTDEMguxzLEYC/UbOizz8f5cgNhtxLLIEMtt iOW7FmNZZYhlBWK502IsRYZY1iKWYouxbDLEcj9iecBiLPSM12F5EJ+1P0XsNmLZZojlF4hlu8VY qgyxVCCWaoux0LhQh2UPjt8eRew2YnnKEMsTiOXXFmM5ZIjl94jlDxZjoXdFHZZn8J3gT4jdRizk h9Rhacb31xcQu41YjhliOYpYXrEYC/l/dVhOYH98CrHbiOVdQyzvIJb3LMZCfh0dljP4XP0EsduI hWIGOixfiJgvqgWx24iF4h06LBH0o6Wj/8RGLBSr0WHJRB/gQMRuIxaKM+mwDMH4w3DEbiMWipHp sIxC3+to1I+NWCi+p8MyDuM+ExC7jVgoNqnDciX6vL+B+rERC8VVdViuw3jrDPTr24iFYsI6LNdj rPhGJ/ZebSMWimfrsCx0YnG/W53Yu7+NWHRzMBbinGry80/B92TXq9sI5UeB9qiX74u+f8JHvv9r FXzT4Mi1UJoKaZql+Ao0PkHCNwvfO7+NfhHXq9sA5X1A2+fl+2KMgPBRjOAWBd/NcOQWKM2HdLOl +BYZ4qO4wWIF3yI4shhKt0FaZCm+VYb4KJZwl4JvFRy5C0orIK2yFF+RIT6KL6xT8BXBkXVQWgup yFJ8mwzxUczhBwq+TXDkB1C6H9ImS/Hp4hCEj+IQP8PnievVrYfyXqDt9fJ9MTZB+Cg2sUPBtw2O 7IDSLyBtsxRflSE+ilfUKPiq4EgNlCogVVmKTxfDIHwUw3gM865Xtw7Ke7w/me+LcQ3CR3GNAwq+ p+DIASg9AekpS/EdMsRHsY4mBd8hONIEpd9DOmQpPl38g/BR/OPPeL+6Xt1aKDcCrdHL2xoTMcHX jPheVPA9D0dehFIzpOctxaeLkxA+ipMcR3t2vbo1UG4AWoOXtzV2YoLvBOI7reA7CUdOQ+kEpJOW 4tPFUwgfxVPeR3t2vbrVUK4HWr2XtzXGYnL/nUE5nFXuv4/hyFkonYH0saX335eaGBLh+wLHOgLn krpeXTji1AGtzsvbGoupNsAXQV9/Bs6Fdb26lVCuBVqtl7c1PlNlgC+TYh84l9f16lZAuQZoNV7e 1phNpQG+IRjfGIH6dr26u6FcDbRqL29rHKfCAN8ojHnkoL5dr245lKuAVuXlbY3t7DbANw5jQBNR 365XtwzKlUCr9PK2xnvKDfBdiXGea1Dfrld3F5QrgFbh5W2NAZUZ4LsO414zUd+uV3cnlHcDbbeX tzUutNMA3/UYC5uH8nC9utuhXAa0Mi9va6xohwG+hRjv+g7aqevV3QblXUDb5eVtjh/5rQ9W148k 2vMkmoS1JClKvXh4E61/No0nRZOwliQoLLrYUVRZS9KAa0n2WorlZkMsPbmWJCgsiwyx9ORakqCw rNL4Z6PKWpJ6XEuyx1IsRYZY1iKWYouxbNL4JaPKWpI6XEvSaCmWzRofQVRZS1KLa0kaLMWyTeOv iiprSWpwLUm9pViqNL6pqLKWpBpTnaVY9mn8NFFlLUkVziGptRQL7W+gw/IE6ubXIvj5sUFhob0Z dFhkfKUc15JUWoqF9pXQYZGxlJ24lqTcUiy0J4YOSzP2YXItyS5LsdB+HjosMkbyCK4l2WYpFhkP +bkBFhkP2YJrSR62FAvto6LD8g4++9/DZ7+NWGgPGB2WMzjHRq4lKbUUC+1fo8MiYxr34lqSDZZi ob13dFgiuJ+qXEtyj6VYaN8gHRYZq1iGa0lWWIqF9jzSYZFxiYW4luRWS7HQfk06LDIGMRPXkhRY ioX2mtJhkfGGK3AtyRRLsdA+WTosMrZwMa4lGWkpFt08/2Ts55MsH2wy9vNJlg92zDnkg03Gfj7J 8sEmYz+fIH2wvb2fT5A+2N7ezydIH2xv7+cTpA+2UfTufj5B+mBNsPTkfj5B+mBNsPTkfj5B+mB7 ez+fIH2wvb2fT5A+2N7ezydIH2xv7+cTpA/WBAvNXX/BYiw27OcTpA/WBAvNST9lMRYb9vMJ0gfb 2/v5BOmDNcFC88pbLMaim0Ou7udTiT7YGmGvD9ZkbyKaLz7QsTf2OsxwbyKaGz68B/YmCtIHa7I3 Ec0DH+3YG0fWzflW9/MpQx9shcU+WJO9ia7EecTfcOyNidM+/Cb7+cg5wzMQu41YbtDMa1b385Hv 0zeifmzEUmi4z9JC3MPo1h7YZylIP798/+3s3v4mc7PpNxJs3VN6muG82amIJd9iLDbMzU7WHj7J mJudrP16kjE3O1l780RF39rnv7fnZge5544JlvsRywMWY9lsiOVc2Oc/Ks6dff6j4tzZ5z8qzp19 /qPi3NnnPyr61j7/JlieQSx/shjL84ZYmhHLCxZjOWa49uco+jdfEfb+/sJJQywnEMspi7G8a4jl HcTynsVYPjZck3UGfe6fCHt/S+JLwzVZX+Azv0XY+/sL9LuKJnOzazAuYKte6DchTeZmV2NcwFa9 DDPEMgSxDLcYC/0Wp8nc7CqMC9j6Gx+5hljGIZYJFmO5WhMTVOdmV2JcwNbfK5luiOU6xDLDYiw3 OGZrS6/HmNONFv/2SqEhloWI5VYLsdjSlv293Bb6rISKbyp13fYxmE4d76+03eR4V3G73cA9D9sv xwtDuoD1IpF4/x4nIFm6rP0yBiDX0d2EspC+6gspnvXRy9fecu8/riWa/O3663E9JH1a8CPXiM2M zI6MjsyI5EQmRMLYhhBeM+zTJt6OBej7ltf6vk87iOYkaIfUw+UGmF+HtBr5vepzLaINTnAt6Q8e D5gnRGZFsoREfSByRSQK+RlwdBJIIkvMAonMge9xQPkWfLsohxSUSViRjYsyTsNjdG6EyTCMNhlG WkQpJ8IsdfQa8j/lg5loIa18s1rbo9PnaeT5ts/1TjN9ijjXm4IYE11rA77jevycjtciWmoCbLdD PgusWGpvPOhtQqRNP66ioxCz5ZQ42ENO7JquT3uIprPlLEM5pyC/VJ9rpXTxWilxbCgN+fX3uRbR QtprZbXKVodtAPLM9LnegIDk2JvPFNnnd+ZZalNbwkkab5i2K96zk2zp6+iXkfM2Hme2RDRdf5SL 94bKcyvyrPLhudWAZ57CsxDx/Rh5PsJ4Ei2k4TkBWpriw3cd8v2hD991RnzzfPmuRL5FPnxXGvCd GKe9hcj3Dh++hUZ8/ds7B/ne4sN3jgHfSXHaOxX5zvbhO9WIr397xyPfq334jjfge0Wc9o5Evpf7 8B1pxNe/vRcg34t9+F5gwDdPaa9NfUxf6u/kfLIncQx1iOmBaI72fm/f383Cet/24TnLkOckxvM2 rLfYh+dthjzzGM+1WG+dD8+1hjynMJ4PYr2f+fB80JDnVexeKcN6dT48iabvkyd0uAf3Y92nffju N+Y7qQPfw1j3Lz58Dxvz7dhnvIR1X/Xh+5Ix3ykd+L6FdT/w4fuWMd+rOvD9jOo6Hfl+Zsh3oo/e 5Lha1v2aD1+i6fl21Fs21o368M025ttRb3lY95s+fPOM+XbUWwHWvcmHb4Ex36usfobY6ueKh2Mr ziOR79jNCZ4/pr6n4zh/6w8YM/0L0zPRBmn8MFPgnX16JEvxx5DHRfplssTlkUmRHPieAPSJkZg/ gXwr6vu96pfhvhXV/xJhvpoUJZ0L75h9wRZTcDwt/a0/6aYtSh/nPU6sP/lEXhA+D4VjaXtscv9v ZLBirrhLrBfFYqno6if7wEXioHPjs0dKBil23PhVMU9+P/vQQPEBpP39msS801/K6bMic/PA1tqH r3vYG4MIxPYRnOuCRKUs/jymWmT9vbnkSDj7wJLU0eFh4SaR8fpAL8nPgA5tcVrvp8z0wpCsJ+sf T8+IVMI1Dz79XIn8fga+JW2e147nSs5C+R1I8vrLxcMe3/OUe0SgboaLVtmJJZiW3+epv1UPIewH lqBdFKGfsJT7lfBYOEE/4I13I6OhH2i7r7nfMEe5bu/bQu0yT+agn3AiWwi32cIWtIUr3bMl91wB d1ba2ZLZqReKwfD9y/SMDzbAMZkGvfF5sWoLsn4LYhncak+1y9psyx5bWIC2sAZtocjHFoq6GAew S/9CjAU5/nP258X/hfT1gs89HY/A+9VR1hUZ6v9D0j/pj/Qv+8M0qHvN2SMl7sHmkgMfHSmRfZG8 loNyE5bofwvqfxrqf42P/uWxjAT6XxInNmMaf+mszfSlZ7vEeKmcP4SYRJy1ayEFe6qy1i21Tdbt zk9Vzue/SXKRwRo4Wv93Ps6FnevE5mB2V4YR1kYVn279n7TyF7Etb1jWFtKho4wH/NYfqvZLcy4u xDm9urhzCNciZmJ/ekzhkY1lsouQoR2ptqpiJv1fjPOIR+I8YrWN3Mf1APrj/4Z+3FdZX0G0tATv ibG43xrox9eJO+FvKfRkYazjsncDN6B3yQiTj6ov3X3dkzbZ3baQTaYmsEneT5A9fQftSWeHxcwO VzI7TLQWNyfO/Ua/D7Ucbe9OfDd1Pf5HoXwcaMe9fCJ7lHMp1qPNPexjj/ciLZLAHgs9HmsB5zKw xfXt3jtTlLkAQeq9s8+WnrTB7raFP9scgz6JbGm7oQ3uZzZYi2WT3+dS7Y7mtlWj3dVhn+fXR/rZ 20OQfoU29Tcfe3sCj6cnsDc5VpKWVoz/s8Qqz/5T2LwTl42Xgu4H1bX5oV62we62pTvP5qOGNvg+ s8GTPjYYz+7Uva+O4nygztidfO5+iLb1Faej3X1o+NxdBxa3TGwUK8R9nu25bK6N24N9nqpjxyJ7 c5LQ56nPXflbuSb2NtZpb29Zjvlz16/Pk79hexTjErpx3gacLy9tao6PvY1HWqrG3pbBO3ux+B7Y 2t3es56/B7o91Lc5ccb6vf18DYnkx7+DbEtnx5uhLjyj490XY3FeGdnLEnxfHYpJeYdX95wpzfF5 /4snM907IZeHyiOd7m+4yGODYu9riXiqdTOwbqvXWlM3nuz8ZMCxzhSx3yiQcpkxd+aYaL4Qo1rx lU5DF0+pmp+Jes/EOqH8tmsOQJ0Jwg/pf+aMGtqExwAA ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image060.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhIAG4AHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAQABAAX AbAAhAAAAAAAAE1NTXx8fGhoaIyMjJqamoCAgJGRkaenp7Kysr29vbe3t9DQ0NnZ2cfHx/Dw8OHh 4enp6f///wECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwX/ICCOY2CeaKqubOu+ cCzPdG3feK6vZO8Dp4lwSCwaj8ikcslsOp/QqHRKrVqPpp8vcO16v+CweEy2ZrWmsnrNbrvf1wAa Tq/blZCIHnLvG+U9XH5WDVERCQ5GEksPbhAPDYlXEQoLCpJChYN2gCKCm1MRBUUSo0gFBZpCEgoT D5hGEKN8XhKwE6wNBQGqXb2iS6WgYWdAw1SmTREDtEMLDxIRSg+jAr1TEBINjUTPBbdFD9JGBq1G D81Co+XHbmef7XgT7KMN5hMDRuMPBL18CwQSnELlQIGAe4uE8MljYII9IexwwRo3gU8DAQmJ5MMn IJ29ZdfmGRkF8uEEBdw2/8aLIwfeyiIEHDQw4E1kggSFRDVYwHNChAV6RA149c3AxQYEYg5Z2GgA KktCEgj45sCAgwGHJtzcSU1IBAN6HCQYoKuqrgQUYwLT1mBcw5vRFjjkuUCCwCENDfD5uZWnAXHJ XlJBIfhIAhO7ArqaQMBEBGtFIDQOQGABBBMGCBg40ZZIowgBDOxS8BfXggQPTEiVumjyAMXqTAzd lXlzmiGHeeES0FGdBAEmBFBUOLyABHEBhE/OfBhy4cFBnhNJkK5I3TARuAkrkn3BgIzWwU+hXvGI 3pPikZwPL/1LdOmiWj2QSwRCgsC1AgzgzY3IT1xH2IefIQW0Akx9BVAnGv8Tsty11H3tuXebFAk0 5BA4YvSnCDpjRDNcfUocV50UGpIil4hMSEAfEShG2MV7UEBAXysrumjjjS7C+AQEM00wClA4Bink SzpCIVdD1w2p5JJQuGTGhFA4EMEiEWzD5JVYIuHkk1u+aMIBYIYp5phklmnmmWimqeaabLbp5ptw xilnmAHMOaYQRYLRZZZ8SrcnFAfgCaUYf/ZpaDuFPhHoBHm6d+ijhQ1axaKNepEopJjCUWkUlEqq Z6aggnKpE52OegR9FWIR6qp9mMpEqVQAI6OWrNaqaRiwSiHNLD3+YeuvbLj6qqDCClEJAbTUOESx wDbLBLNK5DrFKFKmx6j/s9g6iiuxZOzg7bfghivuuOSSK+0Y0Gar7rVinEvouvA2SYa7xMRr77Pz cltGuvfWym+0+nbb78BF/JsEvU/QF4mqBBNs8MEBE3jSBMri2bDDaiDMxK4+Uvwhuxfb+zDEjHrK xLEQIJneyCFfuWkXGjdBkpVElGvzzTjnrPPOKMT8YsvxsoyEz3EAva7QQ0f8rtHZIn0E0WYwja3T Tytdr9TNUm0E1FVojfVzXheBcHbWKnRJVBYW/PWvYRNBL1KPLSHQrAyvvWrbblttFchHWMlj2jXb fTcdGucxIhH3VMy34JDinXfJWz6w2U19VzlBtQXzrPnmnHfOOcINHDZP/4lPOM54q3VoPJYBgEdh +ul0mLwG0QWQ7sTrsLuzuBsaj1N2E7jn3kbwQtArGVJFC58l8cVbrctFSUBw9oV1K88k8xNoLMHv UU2sOPbWf9oH13038uPH4IdvqR/kH9GKyr6qP2T67RPRVk40qy1/kOlnb7WPRrHPFDxHwAIa8IA1 6J0AfNK1/eGof/6DHBJAkzwHRgiCEWxUAVinuNtZMEfDINoAMAS8D/oJgxmUnVcaaELBcAGF5+JR E3KBtuq1MB4oTCE8+FER7vGhIXSL3w1xGI9zPQAnBFCAg5DQiL/ZcIibyGHzJEiEqyBHCbD4HhSP IcUpNmoBAxqCPVqBOf8hbnEQXdRhESpBMZVIAYFwjKMcCeguSgiogme8Qxq9aLIGuHGAeeTE7tqB MFn8a4/he6F0ECYBAiwwaoHUlApBoboOli6SkmxPHeVyFTxicg2IfFyRcrInGlLPjJ/cl4vcBYFE UBAJP/TeE1N5tQgZTyxh9EzHgKQ/WqLrRoxkwBIkAb9e+lJ8NtKYJR2iAAPlj1hzjKY0p/ktZf7s mD8LJcnypAAEHE5e2PSSkMbmgEeyMJznDJLGWOdJdIJzSBorZzvd+SxtDouKkTHAEs+Bm9ZZjJ6X vFI8zXkqhXTQnhd7WTL/V5Fl0seJqASorxBKqog5ABUFSKISaqRFiSb/YZI4OldV6LKAkOBmEWVc FjVXytKWvuBc2qDIN9Lp0WU9ymcL8GdAa2rTmzKUITr1YE1fSNEpxCwakJSoIjNVP9cNtaiTYuj6 lMqqpg6hPwuL6DFByierCmFGFJslJon6K6+GdZfow+ZSyyrVJdCnmIHbKlS3hc8oJIBKz+xpKrmK KbMuwaWADWxL/YqvPBLGWdEh7F8Ny1dMJbat81TfJxrLJxgdVrFKmKuQiKrZNw5qBVTE7EdNSNnr 3UYFahMEZlOlVcZNtrQ30lEKVCoI1KrRCkE0Juw4G6oX1My3t60CRHXLNCjNVkmyndBxaduC36ZB tB3FGmdhGynj2lYG/9DcJnWrOKXMCfa74EWgaGkVsuU+8LMugBxo1etcYY1XrFl7rUI5gV6X4KC9 +C3sb4fw3tYCy7bDSK59beBd+/7BSfVtbnB/+d/pztdS9fUuc2PAXuY6V8LQpPAgP9Ff4iIXweo1 L4QHTGIJE7jC2aVtiDW8YaNCNqmx3VJ695u5Axe4wODKcLk83DbMZtXDiCKxglV6YwsbWceb029I X7wEGtVNxgcu8YWnrOIVsyC/KT4glv+55UMp9nzxEzCGqzxhBJIZxWg+7JFH3FlFMVkJcO1pS8es NDFT+c2MU2yVShTePvu5c3h+Y4qza6pC71TJixWqohE92kUnuoSOzv9soJ0a6UZD+tKMtnSmNf3o Tnta0pUmL6Qf3NtDf3qs2+XpwEit6vKmutUiezWs4cXqKtguQNNjAmuHiYpvDiEaJNSlEG59VbMF ezE1nIYQLloAX2snAsE2JbFpKL1oK0ATu1bEtS/XayTQENj1dNwyjbBPWI57KciGM8V8/VVnuHU6 GzUoEx6a7oKKxDKwFMlZA6RvrURPJLmNBcDrHRmRIInddVXDucVI7Pr0qgkNj4r0uLfvca8or9ZR yMORUKOGo2riyt43EzMR8SZu/Aj9KblWQJ5ZWTth4UO4x7ydsD1lBLUb7o53zHXebp7XPAkr+goW c44EWMjcCFkc+ir/uIcJof/V5U24axPu14SUMqIJraS4VhIi9SRInepeR2l3ldD1iEs960kYY1TK pnaw962Zlxv7283RcLWj/eltnjUXoa53xPK97w3OO+DR+PfB+6vwhr8b4hMPqlrn8RDg0HqKNCQO xy4+fKjoBStccWxluLGklhe8HbbD7yV8TAnLqM4zkHqO00ekCIGRUujtZpJfTwTdMoLNEVSyj36A CCDl3k8zHgKSkTDTJ5ITQOc3e/lMvUXqFvpKWMZSFqMYxQFJgYVaTPGToBRgKBc1izWy/+sGdOb5 0viPQtShFZw8ACsFOL1pRW8H4wBnVwnZhX6oERrNOCU0nTEdJqAJ/5JhApVxGf1nG7wwHL/RG/YX AKAhHMTBfpOBGfI3f19zHgqwCOuxfna1EGGggeLxFaHDDUkye0zTICnTbAkCexeoDwXiE7kkBSq4 IOSQChUBIY3XfI+iIriADj54BRE3BT7YIklghCjIeEbjeErod/TXhO7Ag1BYWVI4hVhSKX+WhVoI aLcjO09ohfAVZZwGhstTOl74BqclY2HTfCbDVzxYhVryCckwg6dlhnvyOpMlapEFYlMVhkCmLYJE aaNyAsYQhvNlAgpQIObHCw5QW9sWANfWALoxEw8zAAGQCrqBGZe4iH50iZtWM6kgiYWgiaHIC5gh RiiwbS1XKI3oEP+ZiInJIYq7sAABQIujGBqWAouEIYqIaH6bwWV4V4j+lXAfdRmpkRrJwQ0BkBqM coxpsIyXMkkvJDrXAo3IOEip9VfOWFvNCI1rNQG8sUDQuFiFIgCNcI3e+A0YQQDgyBjXiI00llnM qEhcgI7IyIzw6F3CqD83MFElsxkZZTH0GBovhI9IBgM2FQDUOI2ayDf9iCe58YvVGJHfaIvVWGYs FpAEySiHcVGEQROHIZHyRQM1Izr0yCi/SFT4OIjvYIhctQIGkYksYBDXZht49yf5IIolg4nmR5N/ pIdIIIr2cBCIIZQx6YlC0BiSqGZYII2FMJTXxgvAAY3ywQtQiRhfp2YEvHgCu8BMU3kCNhmNhLiP emUjTHklU/krkohpcTiWZJmPUKSTtaKUbNmUxeAJ8PCFZBhXbXmXJZCHe9knd5gCaLCFhnmYcaQF eImYjNmYO6OYgeCYkjmZ4OIDIQAAOw== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image061.emz Content-Transfer-Encoding: base64 Content-Type: application/octet-stream H4sIAAAAAAACC+1dC3BVxRnec3NyCZGXoiUKQsAgMUQNBnk4qAHlYXjIMBFB0xgYkceIkICER8Rb 3oooNCAQAgkPWxy1oNWpzDCDr1ZFq4wg2ham1kFpbe1oVWREpf/u/TdZ/px7d0POPXexvZnN2T3/ 2f/st/9/9uz+/+4ehzF2L4RUDBMdxj5mDb/vshjb14GxzMEjhzDmsEOvMbayFWMtGPm5EFIYawP5 3yKk3Z1ddjIjhQEDlgshEwKw6+kUOKwTxNtBCLV76S+QlZVi4NcWQxiN13YrcFkr5Ne5oGV9PAt4 yHheQUjwckUqcmPXghb1NLeA1cczWEP8YoyfPn2aXYjx1hAuwHgIQlcIaRC6NVx72utcOmKRP3mN eg/13ur98jDeFgp+ORx5vTh4naPw7I7X8XM9EEsIaZy/ek1IiYO8It0b7h0xKbcXHycOHtvudba8 O2O9yt8kuPgYHMdAmOkINWffysrG3+qokJ7j8IrYVDadTWKzQNNHwbECjmPYDDg3gd3HzH/3tkzf dejAG+K5lGWLHn/L5n+7P088W62Osrzz9gi8/PpivG4cnONFiuDx8LOvVzB89k5mzc3b3XoPqwzv YWlAz5zSnn0+4bu899Kcu6+JURaehx+5/L6f3J4dgsD51sCxDvKnk+vnwrmTwLMV5glFm4f6pqJD Q53VP/OdT3fhxetw9xwhtnpZpSh1z/N+E7vu2Uio+9msHGq6eT+oy2287sMQb4Pn2njU/ZGW9XW/ Tda9mx6t89x077qfHdrDilvtYc+3PLPuB/hc97y852H9ybrnunRp7LrvQeveVeKtlWct3nkpK36v E8E8J0+bPCeKrJ5urqwS+ZyElOfkkiY8J6nNlNvZnqdtsHp9vPbY9bFtlu/CMKlfyZOfz/a4F5Qn ku1xX/p+VvsDsg/TAoPsM3XE4Of7O1spf4ZSJ7IMst92FzD8q1KGIGTDSJlMZUNxmsomljzGYv+p F2K/Ey7egfXSC87c6fCwA+I7RJrKh8WQj591GG5iHfbCdyTHshPb7Axsz9+BAN1edhTxtsPrqwz7 s30wD+ddRXgsIvRFhF5G6GWEXkropYQ+itBHEfr1hH49oecSei6hdyT0jgHJUW2n4j0LseQodTJE 2oxIJOLZHjgeuE3kTetnh5LmfGg6kfUXOov6M3121fakqfUk60Htf0oeVzHvOlPpVYReReiLCH0R oZcRehmhlxJ6KaGPIvRRhH49oV9P6LmEnkvoHT10pGMMHZI6ptJ/Haf+BhP6YEIfT+jjCX06oU8n 9AihRwh9LaGvJfSdhL6T0PcS+l5CP0DoBwj9GKEfI/SThH6S0Fs5Z9JbkfrvQuhdCD2f0PMJfSih DyX0Owldyr+5bUhKM9pg2UcqxT5SMstyNV5TAhc/aVFZfnXmOCKi9jtlmxuO058Nx3g3cT3YbtDm FuB1Ml1I0kUkXULSU0i6nKQrIWxT0ktJ+jEIW5X0RpLmvOqU9DMk/TsItUr6ZQhblDS3iW5W0u9D 2KSkuV5WK+l/QNigpL+CsE5J/wDhl0q6hRPFINPnQ3qlkr4E0suUdJYTbftk+ipIz1PS/Zwz30OD ID1ZSY+A9J1KeqzDbS+N5Z5I+W5LsHxriXy3EPluJvKtIfKtJvLdQOT7OJFvFZHvY0S+K4l8lxH5 Roh85xH5lhH5TibyvYPIdziR73X/4/LdROS7kch3PZHvWiLfNUS+q4h8HyLyXUzkW0nkO4vIdyqR 78+JfEcR+Q4g8r08YPn+v33+abfPTZXvNo18t2rkW0fkW0vku4XIdzORbw2R7yYi341EvuuJfNcR +VYR+a4m8n2EyHcFke8SIt+FRL5ziXxneshX2t6cOGNlL38o//VEWm+s+77M/768Q/qQXnYx1e5L +6wdif7G6mdKLDcgloEWYyk0xDIMsQy3GEuRIZYxiOU2i7GUGGIpRix3WYxliiGWexDLVIuxlBti mYlYZlmMRb4ndVjm4/vuAcRuI5alhlgWI5ZlFmOR/U8dllXY71iN2G3EstEQy3rEUm0xFtnv12HZ iv2/HRi3EcszhlieQiy/sRiLHG/psLyA/fAXEbuNWORYUYdlH44hXkHsNmKR41wdljdx/PM2YrcR ixyj67AcxDbvMMrHRizSvqDDchTtDh8hdhuxSNuIDstxtIF+hvKxEYu06+iwfIn2268Rk41YpE1K h+UU9l9+REw2YpH2NB2WVCfaJ0tD+4uNWKQtUIelLdqIL0DbkY1YpB1ThyUD7Vsd4bjcUizSBqvD 0g1tc93h+AtLsUj7sQ5LLlzHJ8Be7UTHmDZikbZvHZY+cN0MOPZ3ojYCG7FIu70OC58nNgmONzlR 242NWKTPQYel0InO2xnpRG1lNmKR/hIdliL0k96O/jUbsejmYIzFOV7Szt8PwhM4b68PnOkHqd4Q ePxctP1LfNL2P0jBVwBnBkHqBggFluIrNMQn/QEjFHyFcGYEpIZBKLQUX5EhPukjGKvgK4IzYyE1 BkKRpfhKDPFJv0Gpgq8EzpRCqhhCiaX4phjik76EaQq+KXBmGqTugTDFUnzlGju2xDcTbViz0c7o irx1kN4BtB0ifi76HCQ+6XNYqOCrhDMLITUfQqWl+JYa4pN+iOUKvqVwZjmkFkNYaik+nW9C4pO+ iTX4vLoiby2ktwNtu4ifi/4KiU/6KzYp+DbCmU2QWg9ho6X4dD4MiU/6MJ5AfXZF3i2Q3ga0bSJu q1+j1gDfU2ib3oVYXZF3M6S3Am2riNvq69higO8FtD/vQXm7Im8NpOuAVifitvo/Nhvg24fP3qso b1fk3QTpWqDViritPpEaA3xvoo3+jyhvV+SthvQWoG0RcVv9JNUG+A6i3f4DrA9X5N0A6Rqg1Yi4 rb6TDQb4jqJt/m9YH67I+zikq4FWLeK2+lMeN8B3HOcc/xPrwxV510J6A9A2iLitPpYqA3xfYt/l G/TJuCLvGkivA9o6EbfV7/KYAb5T2Ec7jThdkXcVpNcAbY2I2+qLWWmALxX9Fy3RJ+OKvA9BehXQ Vom4rf6ZZQb42qJPoz3O5XVF3iWQXgG0FSJuq88mYoAvA/0cnXBduNifwlkI6UVAWyTitvpx5hng 64a+j8vhuADxZTkVkF4AtAUibqtvp8wAXy76Q/Jw7Ygr8s6A9CygzRJxW/09kw3w9UEfyXW4FsYV eSdBeirQpoq4rT6gOwzwcR/QODjejH4TV+QdB+lioBWLuK1+oeEG+Lhf6Ba+Xh19L67IewukRwJt pIjb6iu6zgAf9xVx38o4XHvlirz9ID0AaANE3Gb/kdf6YHX9SLw9R3ICWEuSquSLhTfe+mdTf1JO AGtJ/MJSaIglkWtJ/MJSZIglkWtJ/MJSYoglkWtJ/MIyxRBLIteS+IVF5+vJUdaS1OFaku2WYqk0 xJLItSR+YVlqiCWRa0n8wqLz1+QEsJbELywbDbEkci2JX1h0fpicANaS+IVF53PJUdaSbMa1JHWW YtH5V3KUtSQ1uJak1lIsOl9KjrKWZBOuJdliKZa3NOsvcpS1JBtxLUmNpVjkfh46LAexLTuMbZmN WOReJDosR9GO/hH6C2zEIvdR0WE5jmsbPkNMNmKRe8DosHyJfYSvEZONWOT+NTos3KexEteSPGop Frn3jg5LKq5V4GtJHrYUi9w3SIelLa5VuAB9FjZikXse6bBk4FoFvpbkAUuxyP2adFi6oS2fryWZ bSkWudeUDksu2u35WpJplmKR+2TpsPTBtQ18LUmJpVjkHl86LNyPMALXktxqKRa5P5kOSyHa3kfi XtE2YpF7q+mwcP9AFq4l6WEpFt1akiD2jArKzh/EnlFB2fmD2DMqKDt/EHtGBWXnD2LPqKDs/EHs GeWnnT/Ze0YFZecPYs+ooOz8QewZFZSdP4g9o4Ky8wexZ1RQdv4g9ozy085vgiWRe0b5aedP9p5R ftr5k71nlJ92/mTvGeWnnT/Ze0b5aedP9p5Rftr5k71nlJ92/mTvGeWnnT/Ze0b5aedP9p5Rftr5 k71nlJ92/mTvGeWnnT/CkrtnlJ92/mTvGeWnnT/Ze0b5aedP9p5Rftr5k71nlJ92/mTvGeW3nb+p 349I5vz/oPaTCmL+f1B7RwUx/z+ofaKCmP8f1J5QQcz/D2r/pyDm/wf1LYkc9tP5lkQQ8/+D2sMp iPn/fu7XZIJlFWJZbTEWG+b/+7kPkwmWrYhlh8VYdH6BHHZufUvCBMsLiOVFi7G8bLguYx/a3F9h 9n4X4y3DdRlvog39bWbvdzHeN1yXcRBt6IeZvd/FkN8yNJn/X41+gc3M3m9JmKwxOY7vos+Yvd/4 +MpwjcmX+L78OgFrTPzc08hkjckp9IX8mIA1Jn7uX7TOcP5/FfoFbP3Gh/zuqMn8/zXoF1jL7P2W xGrD+f+Pol9gDbP3WxKPGM7/fxj9AquYvd+SWGE4/38Z+gUeYvZ+S2KJ4fz/RegXWMrs/ZbEQsP5 /5XoF3iQ2fstibmG8//noF9gHrP3WxIzDef/34d+gTLLsNhSlieTXBb5mwQZjyl5XSXeWimLyfmz xeE2A8dtUV8RawUZL1Guj7WHkxPjvi7hX4S20duxrNyXepH0H33x3sDb7j84UNJ4Ofk6pIhSr6fx x/c5uzqcH+4RHhzODvcKu3h9Ct4zBcsfrxzjsCz8XnM8yiFpoTjlGA3xK1lm/T3j3e8Ii/rBOc9P PO4naRlx7lcpcA8DxEPDmYwj3xXuHc6B+GA4mw+1kcmGQq0UwvEqoNwUjpYtFUOKElKxnGG8r6y7 VDyn1mNKVA/FMYyhhQFmXsefIv9/eWD+1Oc65uFz5Pkfj/tJmoP3YzHu1w8x6vT4K+TH9yyl9/rK UI+HhLnsrgap9QqrMnCxXuLpcTLbDt4WNKUNtKksKQG9J0zLFatNlTqdhTYYvq/eTqJnkqbT6TzU JflcdmHRMUc2jtVVnpIW0vDsBVxTPfguQL7LPPguMOB7TQy+05Dv/R58pxnwzY/BdzzyvduD73gD vr1j8B2KfMd48B1qwPfaGHz7IN+BHnz7GPDtE4Nvd+Sb58G3uwHfvjH4Xoh8u3jwvdCAbz+Fr03P 7bnUhvRGv08/9IGocpA0R/u8N8i2COeFPIN5KM9hhjzzCc9izFfqwbPYkOe1hOdMzDfbg+dMQ559 Cc/FmG+5B8/Fhjz7k2dlLebb7MFT0vRtcq9Gz+BOzPusB9+dxnzzG/Hdi3l/78F3rzHfaxvxPYB5 /+TB94Ax376N+B7DvJ978D1mzLd/I74npbydxnxPGvK9xkNufPzF817kwVfS9Hwby60L5s324NvF mG9jueVj3gEefPON+TaW21DMO9qD71Bjvv2tfofYaiOIhYP3D59n0e9RvBnn/WNqF/iQRe303J// PYTXiJwlrYNmfNwXRlM3w7i3YZwsR8J8vJzJroRxcjYcewH9mnAUayqxH9DxMh3zquPiMBlDpyrh pzBuOxd0kdc139+F26oWNVMXeV99phNtT77hN4TfkpRoWB2d6PwcN9yOZFOhP1HOJrCz/XUdfjHb 7dz60hsVHRQ9rjufjebHl5a0Z/+GMDu0h43++Ec+9ZC1W9q+PvfeQStFH4Qhti/gWhdqlNfFqz2r WeaB/RUd0rsOL23RI6VTyh6WfqS9CPzXplFZnPrn6aP0cSGej+f/sGV6eAPcc/ezr1fw4z44ctpo UY7XK05A+u8Q0sTYaaXge57yjDCUzaWsvu5Ev46Hu+cI8dfLIYTtQCnqRRnabyKkHUjDcylx2gHO h1sHbw43PNfUnpOt3Df5ulAzUdQ5yCclji4c6NygCytQF/q5Jyra9YYnK+1ExbAWF7EMOF6Rnv5g BpzjocPRU+WqLvD8pxFLRr0+1Uxs0C17dKEIdWE66kKZhy6UKf3s2PbDxs+8XfJnLBfq8dNhp8p/ gHDZLaeEjDvj8+ooaywM5R+plz/KT8qft4dpkHfAiTcq3N37K3Z98UYFb4v4vRysN2aJ/Feg/G9E +U/3kD8/lx5H/qUxbOamdvGm6sy59G7nWPneY50QE4uxjiekYA8r637CDXV9xvVh5Xr6DZCLDdYD ybVQXH/e4fJ3ovPRmluHqaSMKj7dWiiefhfLcsSyskgZOkp/wGstlqq/0v/cBucr6nx8IbQttsP7 HVbn4mBa6kXIUI9UXVUx16/phXAI7/MBKSO1cfG+/xVYL3zd3J9JWyFpaXHGidy+lAktygQ2i02B vwnQkqVgHpeMDVyfxpKppH5Ueeme60TqZHPLInUyHEcnaTsh9WkM6pNOD6cRPSwhehhvXWJ2jOdN fo+pGHWvFMemruB/CNIfAu1DEY+nj9yueC/WyWIPfZyOtHAcfRwnbJYzoGcxEXRx9hnjzlTFR+un 3Jv6bkmkDja3LPTd5hi0SVKXlhvqYC3RwSpMm3wPS9U7Oc9nDerdWmzzvNpIL31bgusaOP4/eOjb NqS1jKNvXNe5ppXj/0w2WazfSyXzAVzSX/K7HVTXKYeSrIPNLUtz3s37DXXwY6KDhz10MJbe9VTe s4dQ55qid5U4n+VdnANN9e4Tw/fuLNC4iWw+m8TmCN1zyVwIN4FtnipjxyJ9cwJo89T3Lp/HYqJv XZ0z9e0ix/y969Xm8W/ict37maPv5/F5n5c5Ucw3eOhbFtJaaPRtIozZy6EHMYHdJ/z+dBzoJqht c2L09ZP9fg2x4P3ffpalqf3N0Fm8o2M9F7li3NCgL3c50XVWHTEoY/iIWmfZHuO/WHWmGxPS+lB5 tMTn9LssxvZ1gOdXw1PNm455663Wmryx6s6rDijWIThPgdfL4JFDeuYUROc+RfFFbkQTT0SND0G5 t8M8oYKGe7ZBmTGk8/h/AbaXk+LUxAAA ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/image062.gif Content-Transfer-Encoding: base64 Content-Type: image/gif R0lGODlhIQG6AHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAQABAAY AbIAhAAAAAAAAE1NTXx8fGhoaIyMjJqamoCAgKenp729vbKysre3t8fHx9nZ2dDQ0OHh4enp6fDw 8P///wECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwX/ICCOY2CeaKqubOu+ cCzPdG3feK6zZO8DJ4lwSCwaj8ikcslsOp/QqHRKrVqRpp8vcO16v+CweEy+ZrWmsnrNbrvf3QAa Tq/brQ/I3S7vcfdhDFUPCA1HekqCbREMDoZdCRIKiEIOgGx9In+XXhEFVAUFlkMQCkIMj0eeEV8Q qUKlEg4FAaNWEQMSkUMPn0oQvpxSZ0DCX8FDBqZKDwOsRAkMeg9J0gUCtlQREA6KQ9HAr0YM1EbK Rg4Du0Of58ZhZ5vvUBHuBawRDwYSzdlE5QwIZMOXgACCI6EkBFAgYBmsIfj0OVjmztU/iBIiOBBA aUguCQMEPKukoN8/Sw4O/7LjN8DBRCEKFH2c9ySLPJpLCDRwECCBrwEFGgwgxOrBLgcJkvJL8KBp gQGoghpwMLUBAZ1C8CkKUCCBQwQCgjYwIJQQAgRIGfjS17QBgpZSqT4oOURnLwncHFDbJ+EsBKOy kgbFu2ufgaIJziJNYIAcMpxLUEBugsAEgQAHHwgIIADsX87likS4HIBAgggmDBAwADTA1NCCHrjW 7FoRhMQMTID1THqAQXYmoNJSzZqWSiGVa+EVIFJCAT2bQRfRS+k5OdCkVVfGNrmJ5O5KEIyk88D2 YyHlEwzo+I39FPEZzT2b1OSwkQTuwTMJot9IL1MMrPMGBAGEJIA3/0TiXv8ECJwXxX/8IOPJQfU4 KFoBx2XVYH9R8CfFX484AgeCdvwVmhHjFQEBAylOQSIpu6zYohG30cgih1B4GMVpkZgiII5ABsmh jlEI5JwuJwqp5JLvEPmEIAftgx+TVFYJiJNONNBAbN1Y6eWXbmDpxQkHlGnmmWimqeaabLbp5ptw xinnnHTWaeedeK45hJhf3ATmn4AuccCeaajhZ6CIJirBoELwOaaikCrKqEKFlnFopJhSOamjcWTq qZebVkrGpZ+W2l+opD5q6qr6bYLqGqmyKuseXPzx6hQNhMKKiEbEOuuvdLhKqK9IsCKIj0cQC+yy sA5xKxWCfMJUr8xWywf/Ec9+qIeU7ilr7bedOjtsFYo80CURO6Sr7rrstuvuu+5mO4a34NY7TBHy ikGvvfzuZ0S+8PQrcLjYjmvowAhT4SfAYOybMMKHMtznwxR7d4TEqlasMbUXG2zpxiCjiwTGS/xV iTiNhhwyqSQnwQ1MuiSrMsg3CduoqFCgdZC0SSo0s8Z+FtoyElLqo0u3P1OMM39DH7ETly/6nDTE SwfR9DDwZq311lx37bUJDBuVX45TQ8yxuDcfqp5mZpQ9cND4ekwEWVJX4bDbn8Idd9pJNDVjTXjz q3fBfB/BGGZ8TXF34JEOTjill6YkgASNKcw4uDWPLDeNeP3t7+XVOv44/59vuaM46MyKPjrOCEWN AF+8FrE46n+qjjbkTEDQYgS7IHs27azWnCrD+Sih0T48/w68qcLLLvTmWQlEwBKRcKv88plWLbyt 0MsiyuRINJAHP+fKjn2ptTovKtPdwzK2d1/HL//89Mt/9enne2p73Yu2H4oDDLJb/vRnPpmtjlRs 6xngBti46/FPCBJrwOxSxkBF7W9h7XOOAUx3rwomKnMG3BvuljAAlDlhgh6cjO0u1TIFnjCFgQKh A/tXOFL4wwoohOE85ME6CnashqeYXPHapkMvNQ9dPbwdkajiAIPE6igmzGERr8Q/IjkqX0JRS6ru 4rsCTlFJ6UPi+pIIQf/oKSASuenbkZLnxS8GaWlYYEK+GMQgC0miIPU42gzdCJ4VNkFi6VjCJ8xF ovoZ8pCITCQNiLdBIvIRRzIUmRMiCD4BPnJIbZTkHzPIO0desjt+fALDIGAAO77wk6D83XdEmUG0 eBKVO3Se+qSQL8AI5ZWw5IT2ZhmFfL1MNrjMJa0euMoRQgFg00ChFIWZMR9qkpbdi4Bb7BgBBYQo iswURiT3ZIVRLoAJB+niM7N5rXE6cwoS+xE6ooWkPZITE5k8JzozqE4jmMJ68XxnGyJZzBzZzJjo UIJeLEHIEOozTEjkpeKeB0QiKEABntuPIidK0YrSL2wNqKTlDtqs7fH/kIyRESGfDJAh/HH0YIQy aAcPmISMBvOkE+Nmr2bXQ+LR4qUwxSEPVQo4lm1uFqEggEZNmtOMhTFti7si9CjhwgUWlWCUUijW BLW5sTSoAFPB4VO1+tHtbZSqDXVFdUx4yq3eq6uVoqmySMaYQyhgFLEzp1nhl1JZdiiqrGwoEfLR SBRRThIxc+dck7WJwqbhbpz6IUBR1FQJsHNa+RxsHAHaz5rc7X5FeAQ+5SpZjlkRpEkArRIwO4SJ mKKggp3rYZFqWNGmFqyLbZhFZ0vb2q6LtGTrLGHxGgTXSrWbGWymbqM6Rt+KcZk0jG3Ahsvb4p7S uMcMLlTNulrIpTWx/9ZVA26dqtrD/qG39MIucPW6XOqmYFiiNewbtltWjhbqvcX11XnhwF6LnbRW 3v3OfCOD3OiS1wneiKtM3etd1saqtYBgb+8CG9lHIlhHlZ2peNegYCGwkbOfhC9/VCDR/o5XuU4o jB4b7Ebw4jfCCQVxgqUbnmmUz8C2jbGMZ5yC+n6uxBrmcGhPXN3u2DikHryujvsZXw+34cdKMHLC eMxh8KoPxUBCcmiXl+P57re5UFaSlCdbtqDd4LhKNsaWefozGzx5wlYa82vtJeQXgFnHq1IziUPn URfAOMtxZnETBCzP7O3yzjlA2I/FOWArfbbI6prajy8s00P/1tFifP+0c9/8LuD9eLON/vPmIL3p rR2Xjz9GbQFpjN5Pl1qYcgY0jVfN6ommOtPxlVoxJfNdCPeWu0C2r65vzOtc93rK7fV1rtG80l8D e9fCTjKulR1sZiPb2ck+trG5TGzmMg+61r52mLNtaGxzW3/e/jamqg0tJ1STrEZ4XRNydY+SPQDd Q/BG1IigiHMnYgjqroYQ2O0527zbZW89xS8Cbm+3jiLfBpcAv5FQCkuACH7bLkI9k1DSYk3cr/Oe my4iyuCLC0FAFYdGVjweWGMpQcSnKdZfGayKlfdF5fvoZBJYEXPHzvyvUuK4isVAciK8eOZUeRI4 q/m+j3+DeqXNeMn/g54EASl9F+Khj75ZjgRF/LwIgjjeEuS99b4QvcNv6LlDnyB2vBSdF4lr+tFP Pna1rx0J64BA0ddhtJa+PXxtd5rI7e4+JaSi7vyNOBEQcPZKmGvd42uC0iHSgMITHjlFf/xAW6zw xCPh8TanvDTfZ1rIJ6Hzkz9C58XH+YcK/POm3zzExY25cLPegq5/PaLILfvZx772tbs99ghhwsKX DEHkGLfugfc/IsTCsfBmQjOgccMYDr9UwLj5EhrrH2dIXBr8GIcLOWhhIohP+IJP1EuM/4rQEOQ3 SJgJQIyEEd6h3yPNKe1pW1KET7ykPAYQQPKpRPtZ7cMvK8cW7/YW/7MwFkxkFVhRF+KzFkzhFFCR KwZYFVfxCHmxF8iBANQAGPFxJIrBAENRANTHf89XKs+xGdTwHBYWHFpEHK3xGkWQHKMwGpZxGqmx Gi2oF6TAHKyAgiYoHUP0CaSRGiEoguEHKPZBH/aBEVEAHzoHBUkodegxFQigCFPiZ0X4JRNSIRNS f0OIHgVwWqZEDxiSEaVkDqKQERsCblfoJTUiIzVyBYs3BW8oI79wI2qIe8vSf3j4JXq4h922hn5I E30YiEwyiIQIRiN4iEBia63WiI5IW2OyPoqYSnEgiZMIGVIEYW8AXzMFK2GWRL6ViHYVLJuADHY0 iLMGB4VFZkQlV/+ZKG3RFlN1gFg5dALF0GdIJVEK8IUoUQsS1CgBtxAuUQtUQSwgNQBcwROWkBrJ qIwgwRVJJl+ioIypoRDTWAvVWAkoEHA7Fiu/6IzJaALYoBy0kAA9gY2uEY37IQr5xQXUKIzFWIs2 wU04IDuokUa5wRlbkUYBkBv52I9oNQP0WBkpA5D5SEH12Cj+WF0G2WMSwByTA5Cq1gJDcCCOdVj5 GBQcMT0PKQEEcJCtRQN7wo8FeZG1ko8HaQbziIvZ5S/p4xpcwZEvSSkGYAJpFHipUisE6TOYwYws mSPJUZOyFpRHpQvKUZQSJkjTA5MKURm58h0GkBhMKV/7QZDfxZOeQolfKalTfXCVlZgCE7EZy8gC DLEaoJVluQCO4egSDGEKM2EFyhiWJmB/xMgQc1kX6NiHyhGWb1UL0ZEby5AbbBkdYbhneTmX7miX KFCTymSLtwiI/RIdpsITsXhCKFACD5RCzvgpl9F8GNZhxKAJkHmJz2aZjukHj5iaqolIWJMCaLCa sBmbNKYFoimbtnmbiUSbqImbvNmbXOMDIQAAOw== ------=_NextPart_01C5ECCB.555BE850 Content-Location: file:///C:/304D0512/file3938_files/filelist.xml Content-Transfer-Encoding: quoted-printable Content-Type: text/xml; charset="utf-8" ------=_NextPart_01C5ECCB.555BE850--