Anatomic ACL repair with suture tape augmentation and cortical button fixation for acute proximal anterior cruciate ligament tears: results in short-term outcomes similar to those of ACL reconstruction with hamstring autograft

Anatomic ACL repair with suture tape augmentation and cortical button fixation for acute proximal anterior cruciate ligament tears: results in short-term outcomes similar to those of ACL reconstruction with hamstring autograft | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Anatomic ACL repair with suture tape augmentation and cortical button fixation for acute proximal anterior cruciate ligament tears: results in short-term outcomes similar to those of ACL reconstruction with hamstring autograft Hannah Gablac, Marie Riedel, Dominik John, Tilo Patzer, Lucas Meyer, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8743118/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose The treatment of choice for anterior cruciate ligament (ACL) ruptures remains the use of tendon grafts. However, the concept of preserving the ACL instead of replacing it has gained popularity for the treatment of acute femoral avulsion tears. This study aimed to evaluate the effectiveness of ligament-preserving repair technique, for clarity hereafter referred to as the Ligabrace technique, involving suture tape augmentation and cortical button fixation. Methods The study included 50 patients with isolated acute proximal ACL rupture (Sherman I / II) who did not have any other injuries or medical conditions. The patients were divided into two groups: group 1 (n = 25) underwent surgical treatment with the Ligabrace technique, while group 2 (n = 25) received standard ACL reconstruction with hamstring tendons. Preoperative assessments of Tegner, Lysholm, and International Knee Documentation Committee (IKDC) scores were conducted at T0, and 12 months postoperatively at T2. Additionally, standardized Magnetic resonance imaging (MRI) and routine clinical examinations of the knee, including instrumented anterior-posterior (AP) stability measurements, were carried out at T1 and T2. Results No significant differences in any of the evaluation criteria were observed in either group at T2. The Lysholm (90,32 (71–100)) and IKDC (87,1 (62,1-100)) scores were comparable for the Ligabrace group and the scores for the hamstring group. The Tegner activity levels were 6.2 ± 1.7 in the Ligabrace group and 5.8 ± 1.7 in the hamstring group. The mean AP translation compared to the noninjured knee was 0.56 mm in the Ligabrace group and 0.72 mm in the hamstring group. Conclusion Overall, primary ACL repair with this technique showed similar outcomes to ACL reconstruction with hamstring tendons in terms of patient-reported outcome scores and clinical investigation in patients with proximal ACL tears in short-term. The initial results for the Ligabrace technique suggest that it may be a viable option for ligament preservation after acute femoral ACL tears. acute proximal ACL tears ACL repair ACL reconstruction Ligabrace technique suture tape augmentation Figures Figure 1 Figure 2 Figure 3 Introduction Anterior cruciate ligament (ACL) reconstruction using autograft tendons is considered the gold standard treatment for ACL tears [ 1 ]. However, despite advances in technical and biomechanical aspects, clinical outcomes remain suboptimal. Reported limitations include loss of proprioception and graft site morbidity, which may result in persistent altered movement patterns and gait kinematics, respectively [ 2 , 3 ]. In addition, revision surgery can be more challenging due to the loss of available graft tendons [ 4 ]. Furthermore, ACL reconstruction has been associated with an increased risk of osteoarthritis [ 5 , 6 ]. Therefore, primary repair of the ACL has received renewed attention in recent years. Although it was a common treatment until the early 1990s, mid- and long-term outcomes were unsatisfactory [ 7 – 9 ]. More recently, encouraging results have been reported with suture tape augmentation techniques. Heusdens et al. observed a failure rate of 11.4% at two-year follow-up [10], and Jonkergouw et al. confirmed these findings with a similar failure rate of 10.7% [11]. In both studies, internal bracing was performed for proximal avulsion tears, with femoral fixation achieved using a suture anchor. A systematic review concluded that internal bracing in carefully selected patients with proximal tears produced favorable clinical outcomes, and that bracing with a nonabsorbable suture, scaffold, or graft further increased the success rate of ACL reconstruction. In addition, marrow venting at the femoral insertion site has been shown to release pluripotent cells, potentially enhancing the healing response [12]. Clinical outcomes for patients with proximal ACL tears have improved due to advances in diagnostics, arthroscopic techniques, and patient selection. Magnetic resonance imaging (MRI) is now widely used to identify candidates for primary repair [ 14 ]. Moreover, minimally invasive surgery, early range-of-motion rehabilitation, and the use of suture anchors have contributed to improved outcomes of primary ACL repair [ 15 ]. Recent studies have reported excellent results in selected patients with proximal avulsion tears [ 16 , 17 ]. However, the use of intraosseous implants as a fixation method may complicate revision surgery if required. The present investigation aimed to compare the clinical and radiologic results of a ACL repair technique, hereafter referred to as Ligabrace technique, that avoids the use of intraosseous implants, with those of single-bundle ACL reconstruction in patients with acute proximal ACL tears. We hypothesized that there would be no significant differences in patient-reported outcomes, clinical stability, or re-ruptures on MRI analysis between the two surgical techniques at short-term follow-up (12 months). Methods Patients Between August 2017 and April 2019, a total of 269 patients underwent surgical treatment for ACL injuries. From this cohort, 50 patients with acute, isolated proximal ACL tears and no additional knee comorbidities were included in the present study. The Ligabrace group (LGB) comprised 25 patients who underwent arthroscopic primary ACL repair using suture tape augmentation and cortical button fixation. Eligible patients had an acute proximal ACL tear (Sherman type I or II) with excellent tissue quality confirmed by preoperative MRI and intraoperative assessment. Surgery was performed within four weeks of injury. Patients were required to have completed a clinical examination, including instrumental stability testing (Rolimeter®, Aircast, CA, San Diego, USA), and to provide complete patient-reported outcome scores (IKDC, Lysholm, Tegner) preoperatively and at 12-month follow-up. All patients were also available for MRI follow-up at 12 months. Patients with insufficient intraoperative tissue quality were not considered for ACL repair [ 15 ]. The control group included 25 patients with isolated proximal ACL tears (Sherman type I or II) who did not meet the tissue quality requirements for repair and therefore underwent anatomic ACL reconstruction using a quadruple semitendinosus/gracilis autograft within four weeks of injury. The diagnosis was confirmed by MRI, and all patients provided informed consent to participate in the study. Exclusion criteria for both groups were previous unilateral knee ligament surgery, multiligament injuries involving more than two ligaments, meniscal injuries requiring repair, contralateral knee ligament injury, or concomitant cartilage lesions greater than Outerbridge grade II. All procedures were performed by the senior author. Clinical Examination All patients underwent a standardized clinical examination at baseline (T1) and at follow-up. The mean follow-up period was 12.0 ± 1.6 months, with a minimum of 10 months (T2). The evaluation was based on the International Knee Documentation Committee (IKDC) knee examination form. Instrumental anterior tibial translation was measured quantitatively using a Rolimeter® (Aircast, San Diego, CA, USA), and results were compared with the contralateral uninjured knee. Patient-reported outcome measures included the IKDC subjective score, the Lysholm score, and the Tegner activity scale. These were collected retrospectively for the pre-injury status (T0) and prospectively at 12 months postoperatively (T2). Data were reported as mean, standard deviation, and range. MRI Evaluation Preoperative MRI was performed at initial presentation to confirm the indication for primary repair. Follow-up MRI was obtained at a mean of 12.0 ± 1.6 months, shown as an example in Fig. 1. All examinations were conducted by two board-certified radiologists using a standardized protocol on a 3.0-Tesla scanner (Magnetom Trio/Vario, Siemens Medical Solutions, Erlangen, Germany) with a dedicated knee coil. Patients were examined in the supine position with the knee in neutral alignment. ACL integrity was assessed on sagittal images and defined as a continuous band of hypo- or isointense signal extending from the tibia to the femur without interruption. Interrupted or wavy contours and diffuse high signal intensity within the ACL substance were considered indicative of graft failure. Concomitant meniscal injuries and cartilage defects were also evaluated. Ligament maturity was graded according to the system commonly used in the ACL reconstruction literature, shown in Table 1 [ 3 , 18 , 19 ]. Table 1 GRADES OF ACL-MATURATION IN MRI Grade Maturation of the ACL Hypointense the intensity of the repaired ligament was similar to that of the posterior cruciate ligament (PCL) and lower than that of the posterior muscles (i.e., gastrocnemius muscle and semimembranosus). Isointense more than 50% of the ligament had the same intensity as the PCL and the intensity was similar to that of the posterior muscles. Hyperintense less than 50% of the ligament had the same intensity as the PCL and greater intensity than the posterior muscles. TABLE 1: Grade of maturation of the ACL after bracing, similar to how graft maturation is graded in the ACL reconstruction literature (3,18,19). Surgical Technique: Refixation Procedure : The tibial insertion of the ACL was first exposed. Using an ACL tibial guide introduced through the medial portal, a guide pin (2.4 mm) was placed at the center of the tibial footprint via a 1-cm incision medial to the tibial tuberosity and proximal to the pes anserinus. A 4.5-mm cannulated drill was advanced to create the tibial tunnel, stopping once the tibial plateau was breached. A doubled 2 − 0 monofilament suture was then passed through the tibial tunnel and proximal ACL remnant with a suture shuttle (Accu-Pass, Smith & Nephew GmbH, Hamburg, Germany), and the loop was retrieved through the medial portal. The femoral footprint of the ACL was identified, and an ACL femoral guide was introduced through the medial portal. With the knee flexed to 120°, a 2.4-mm guide pin was positioned in the anatomic center of the footprint and advanced to exit the lateral femoral cortex. A 4.5-mm cannulated drill was then used to create the femoral tunnel. The ACL remnant was sutured with a nonabsorbable 2 − 0 suture (Ultrabraid, Smith & Nephew GmbH, Hamburg, Germany) using a suture passer (Firstpass Mini, Smith & Nephew GmbH, Hamburg, Germany). Three passes were made 10–12 mm distal to the tear, each approximately 2–4 mm apart, to create a whipstitch configuration. The free ends of the sutures were retrieved through the medial portal. The Ultrabraid sutures and monofilament passing suture were then retrieved together through the medial portal to prevent tissue interposition. The remnant sutures were shuttled through the femoral tunnel using the guide pin and monofilament suture. A continuous-loop EndoButton® (Smith & Nephew GmbH, Hamburg, Germany) loaded with two Ultratapes (Smith & Nephew GmbH, Hamburg, Germany) was advanced through the tibial tunnel into the femoral canal and secured on the lateral femoral cortex (Fig. 2 ). For femoral fixation, the remnant sutures were tied to the EndoButton using a knot pusher via a stab incision. For tibial fixation, the Ultratapes were secured to a 4 × 12-mm EndoButton with the knee in near-full extension. Finally, microfracture was performed at the femoral insertion site using a 1.5-mm awl to enhance the biological healing response (Fig. 3 ). ACL Reconstruction Technique : The patient's torn ACL was surgically reconstructed utilizing a quadruple semitendinosus/gracilis autograft, and an anatomical single-bundle technique was employed. Following the procedure, an EndoButton® (Smith & Nephew GmbH, Hamburg, Germany) was used for femoral fixation, and a bioabsorbable screw was employed for tibial fixation, based on the diameter of the graft. Rehabilitation Postoperative rehabilitation was similar for both groups. Patients were instructed to wear a knee brace for one week to maintain full leg extension and were permitted 90° of knee flexion for the following five weeks. Partial weight bearing was allowed, and crutches were used for two to three weeks. Closed-chain exercises commenced after one week, and strength, coordination, and endurance exercises were initiated after six weeks. Patients were cleared for return to cutting and competitive activity at least eight months after surgery if they successfully completed a series of functional tests, including strength tests, hop tests, and measurements of movement quality. Statistical Analysis All data were collected and analyzed using the SPSS software (Version 26.0) to determine the patients' demographic characteristics and outcomes. A post-hoc power analysis was conducted using G*Power (Version 3.1; Germany) to determine the study's power. Based on the results of the Mann-Whitney U test, an effect size of 0.95 was calculated. With this effect size and a standard deviation of 0.05, a power of 0.82 was calculated. Results Patient characteristics : Fifty patients with acute isolated proximal ACL tears were included, with 25 treated using the Ligabrace technique and 25 undergoing ACL reconstruction (ACLR) with hamstring autograft. Baseline demographics were similar between groups (Table 2). The mean age was 29.5 ± 12.2 years in the LGB group and 31.0 ± 12.3 years in the ACLR group (p = 0.662). The sex distribution was balanced (LGB: 9 men, 16 women; ACLR: 11 men, 14 women; p = 0.564). The mean follow-up was 12.0 ± 1.6 months in the LGB group and 12.3 ± 2.1 months in the ACLR group (p = 0.753). TABLE 2: CLINICAL RESULTS Table 2: Clinical results preinjury, preoperatively and at the 12-month follow-up (T2) for the two groups (Ligabrace (LGB) and ACL reconstruction (ACLR). The significance level p was determined as a standard deviation (p-value) of 0.05. (LGB, Ligabrace; ACLR, anterior cruciate ligament reconstruction; IKDC, International Knee Documentation Committee; Rolimeter, manual maximum displacement test; mm, millimeter; mv, mean value; SD, standard deviation) Patient-reported outcomes : Preinjury activity levels (T0) did not differ significantly between groups (Tegner: LGB 6.5 ± 1.6 vs ACLR 6.6 ± 1.6, p = 0.810). At 12-month follow-up (T2), both groups achieved high functional scores. The mean IKDC subjective score was 87.1 ± 11.3 (range, 62–100) in the LGB group and 84.2 ± 12.4 (range, 48–99) in the ACLR group (p = 0.420). Lysholm scores were 90.3 ± 7.9 (range, 71–100) and 87.8 ± 12.1 (range, 43–99), respectively (p = 0.446). Tegner activity levels were maintained, with a mean of 6.2 ± 1.7 in the LGB group and 5.8 ± 1.7 in the ACLR group (p = 0.532). Differences between preinjury and postoperative scores indicated successful restoration of knee function in both groups (Table 3). TABLE 3: PROMS 12 MONTHS POSTOPERATIVELY Table 3 IKDC and Lysholm scores at T2 (12 months postoperatively) for the two groups (LGB, Ligabrace group; ACLR, ACL reconstruction group). Objective outcomes : At baseline (T1), mean anterior translation measured with the Rolimeter was 5.2 ± 1.9 mm in the LGB group and 6.1 ± 1.6 mm in the ACLR group (p = 0.144). At follow-up (T2), translation decreased to 0.6 ± 0.7 mm and 0.7 ± 0.8 mm, respectively (p = 0.722). None of the patients demonstrated a side-to-side difference greater than 2 mm at T2, confirming restoration of stability. IKDC grades at T2 showed excellent outcomes: in the LGB group, 24 patients were graded A and one patient B; in the ACLR group, 21 patients were graded A and four B (p = 0.349). MRI findings MRI follow-up confirmed graft integrity in all patients. Signal intensity distribution was comparable between groups. In the LGB group, 44% of ligaments were hypointense, 44% isointense, and 12% hyperintense. In the ACLR group, 44% were hypointense, 40% isointense, and 16% hyperintense (p = 1.0). These findings suggest similar ligament maturation patterns between techniques. Complications No failures, re-ruptures, or postoperative complications occurred. The reoperation rate was 0% in both groups. Discussion The present study demonstrated that the Ligabrace technique, which combines ACL repair with suture tape augmentation and cortical button fixation, yielded comparable results to ACL reconstruction with hamstring autografts in terms of patient-reported outcomes, clinical stability, and radiological findings at 12 months. Importantly, no failures, reoperations, or complications occurred during the observation period, and subjective outcome measures were comparable between the two groups and consistent with previous reports. Although ACL reconstruction with autologous tendon grafts is widely considered the gold standard, limitations in clinical outcomes remain [ 1 ]. Despite technical and biomechanical advances, patients may experience deficits such as impaired proprioception and donor-site morbidity. These deficits can contribute to persistent alterations in movement patterns and gait mechanics [ 2 , 3 ]. In recent years, suture tape augmentation has shown promising results. Heusdens et al. reported an 11.4% failure rate at the two-year follow-up, while Jonkergouw et al. observed a similar rate of 10.7%. Both studies focused on proximal avulsion tears treated with internal bracing and femoral fixation using a suture anchor. Successful ACL repair has the potential to overcome two major disadvantages of reconstruction: loss of proprioception due to removal of the native ligament and harvest-site morbidity. In particular, the absence of afferent proprioceptive input after ACL replacement has been linked to altered neuromuscular control of the knee [ 18 , 22 ]. These insights have rekindled interest in ACL repair, particularly in selected patients with proximal tears. Several authors have emphasized the importance of tear location and tissue quality in determining suitable candidates for ACL repair [ 9 ], a concept originally introduced by Sherman et al. [ 23 ]. Historically poor results were likely related to the inclusion of all tear types regardless of morphology or tissue quality, as well as the relatively high surgical morbidity [ 7 ]. In contrast, more recent studies limited to proximal ACL tears have demonstrated low reoperation rates and high patient satisfaction at both short- and long-term follow-up [ 14 – 16 ]. In our study, only patients with acute proximal ACL tears (Sherman type I or II) and excellent tissue quality confirmed by preoperative MRI and intraoperative assessment were included. The average age was similar between groups and fell within the range with the highest incidence of ACL rupture, as previously reported [ 20 ]. The female-to-male ratio of 3:2 also reflected the higher incidence of ACL ruptures in women [ 21 ]. Discrepancies have been reported regarding the time course of graft remodeling on MRI after ACL repair. Ferretti et al. observed normalization of morphology and signal intensity at six months [ 25 ], whereas van der List et al. described a gradual sequence with hyperintensity in the first postoperative year, isointensity between one and two years, and hypointensity thereafter [ 19 ]. In our cohort, continuity and remodeling were observed at 12 months in both groups. Graft maturation was comparable, with 88% and 84% of repaired ligaments being hypo- or isointense, respectively. Three patients in the repair group and four in the reconstruction group showed hyperintense signals. No significant difference was found between techniques (p = 1.0). Furthermore, no evidence of strangulation or abnormal signal patterns was detected in the tibial or femoral portions of the braced ACL, which might have occurred with the whipstitch technique. Recent systematic reviews have confirmed that ACL repair and reconstruction yield similar results with respect to Lysholm score, IKDC score, side-to-side laxity, pivot-shift grade, and graft rupture rate [ 21 ]. Van der List et al. reported mean functional outcomes exceeding 85% of maximum scores and cumulative failure rates of 7–11% across recent ACL repair studies [ 19 ]. These findings are in line with the results of the present study, in which both repair and reconstruction groups achieved good to excellent functional outcomes with no failures at short-term follow-up. Several individual studies have further explored the role of internal bracing. Mackay et al. [ 24 ] evaluated ACL repair with internal brace augmentation and reported a reoperation rate of 6% in 68 patients at one-year follow-up. Achtnich et al. [ 16 ] compared primary repair with ACL reconstruction and observed a 15% failure rate and 20% reoperation rate in the repair group, compared with 0% in the reconstruction group, at a mean of 28 months. Douoguih et al. [ 17 ] reported a 14.8% failure rate at a mean follow-up of 2.8 years in patients undergoing ACL repair with suture augmentation. In contrast, the present study demonstrated no failures in either group. We hypothesize that strict patient selection—limiting inclusion to isolated proximal tears with excellent tissue quality—together with the use of a small femoral drill hole may have contributed to favorable healing at the femoral avulsion site. This may represent an advantage over anchor-based techniques, which have shown failure rates of approximately 11% after two years [10–12]. In our series, all patients in both groups achieved good to excellent knee function according to the IKDC score at the final follow-up, with restored physiological stability and no significant differences between groups. These results are consistent with systematic reviews showing no major differences between ACL repair and reconstruction in terms of functional outcomes or failure rates [ 19 , 21 ]. This study has several limitations. First, the relatively small sample size may have reduced the ability to detect differences in secondary outcomes or rare events such as graft failure. Second, selection bias may have been introduced, as ACL reconstruction was performed in proximal tears with poor tissue quality, while repair was reserved for tears with excellent tissue quality. Nevertheless, this reflects real-world clinical decision-making. All patients were examined by a single experienced clinician who was aware of group allocation. While this could introduce bias, it also ensured consistency of assessment. Although MRI was assessed by two board-certified radiologists, the possibility of inter- and intra-observer variability cannot be excluded. Finally, the follow-up of 12 months is relatively short and may not fully capture long-term complications or differences in graft durability. Conclusion Short-term outcomes of primary ACL repair using suture tape augmentation and cortical button fixation (Ligabrace technique) were comparable to those of standard hamstring tendon ACL reconstruction. At 12 months, patient-reported scores, objective stability, and MRI findings confirmed restored knee function without complications or failures. These encouraging results highlight the potential of ligament-preserving strategies in carefully selected patients with acute proximal ACL tears. In addition to maintaining native tissue and proprioceptive function, the technique avoids intraosseous implants, which may facilitate revision surgery if required. Although limited by its retrospective design, small cohort, and short follow-up, the consistency of the findings provides a strong rationale for further investigation. Prospective studies with larger cohorts, longer follow-up, and direct comparisons with other ligament-preserving techniques are needed to confirm whether the favorable short-term results of the Ligabrace technique can be maintained over time. Abbreviations ACL anterior cruciate ligament ACLR anterior cruciate ligament reconstruction AP anterior-posterior BMI Body Mass Index IKDC International Knee Documentation Committee MRI Magnetic resonance imaging LGB Ligabrace PROMs Patient Reported Outcome Measures SD Standard deviation Declarations Ethics approval and consent to participate This study was approved by the ethical review board of the Medical Association of North Rhine (Ärztekammer Nordrhein). Registration Number: 2018266. Registered 28. September 2018–Retrotively registered. Informed consent was obtained from all patients and volunteers involved in this study. Consent for publication: All the patients provided written informed consent to participate in the study. Data availability The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interest: The authors declare that they have no competing interests Funding: This study was funded by the Bundesinstitut für Sportwissenschaften (Studynumber 070602/24-27) Authors Contributions Statement: All authors fulfil the ICMJE criteria for authorship. All authors have read and agreed to the final version of this manuscript. Conceptualization HG, MR, DJ, JV Methodology HG, MR, DJ, JV Validation HG, MR, DJ, TP, PB, TP, JV Formal analysis HG, MR, DJ, JV Investigation HG, MR, DJ, TP, PB, JV Writing—original draft preparation HG, MR, DJ, JV Writing—review and editing all authors Visualisation HG, MR, DJ Supervision TP, PB, MH, JV Project administration TP, PB, MH, JV Acknowledgements: Not applicable References Gabler C, Jacobs C, Howard J, Mattacola C, Johnson D. Comparison of graft failure rate between autografts placed via an anatomic anterior cruciate ligament reconstruction technique: A systematic review, meta-analysis, and meta-regression. 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Development of a national cruciate ligament surgery registry: the Norwegian National Knee Ligament Registry. Am J Sports Med. 2008;36(2):308–15. Teske W, Anastisiadis A, Lichtinger T, von Schulze Pellengahr C, von Engelhardt L, Theodoridis T. Ruptur des vorderen Kreuzbands. Orthopäde. 2010;39:883–900. Johansson H, Sjölander P, Sojka P. Activity in receptor afferents from the anterior cruciate ligament evokes reflex effects on fusimotor neurones. Neurosci Res. 1990;8:54–9. Sherman MF, Lieber L, Bonamo JR, Podesta L, Reiter I. The long-term followup of primary anterior cruciate ligament repair. Defining a rationale for augmentation. Am J Sports Med. 1991;19(3):243–55. Mackay G, Anthony IC. Preliminary results of primary repair with internal brace ligament augmentation: a case series. Orthop Muscul Syst. 2015;4:1–5. Ferretti A, Monaco E, Annibaldi A, Carrozzo A, Bruschi M, Argento G, DiFelice GS. The healing potential of an acutely repaired ACL: a sequential MRI study. J Orthop Traumatol. 2020;21:14. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8743118","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":594818964,"identity":"5f6bb27e-b836-4289-b3c3-192e05202044","order_by":0,"name":"Hannah Gablac","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYBACAxDB2GDDwCDB3ABkMhOtJQ2ohZE0LYdJ0GLOfvbYg587ztv1z25s/PCDwVqOoBbLnrx0w94zt5Nn3DnYLNnDkG5M2GEHcswkeNtuJzPcSGyQZmA4nNhAUMv5N2aSf9vOJcvfSGz+DdRST1jLjRwzad62A3YGNxLbQLYkEHbYjTdm0rJtyQmGdw62WfYYpBsS4bAcM8m3bXb2crebD9/4UWEtT9AWGID62oBoDQwM9iSoHQWjYBSMgpEGAEuRQGetoTX9AAAAAElFTkSuQmCC","orcid":"","institution":"Asklepios Klinik St. Georg","correspondingAuthor":true,"prefix":"","firstName":"Hannah","middleName":"","lastName":"Gablac","suffix":""},{"id":594818965,"identity":"a94eea6e-18ff-4aab-9b9a-b19ce15840fb","order_by":1,"name":"Marie Riedel","email":"","orcid":"","institution":"Porz am Rhein Hospital","correspondingAuthor":false,"prefix":"","firstName":"Marie","middleName":"","lastName":"Riedel","suffix":""},{"id":594818966,"identity":"d2badf21-664d-4b8a-8b9b-9e23b683fd9c","order_by":2,"name":"Dominik John","email":"","orcid":"","institution":"Gelenk.Bonn","correspondingAuthor":false,"prefix":"","firstName":"Dominik","middleName":"","lastName":"John","suffix":""},{"id":594818967,"identity":"3c70c8ae-dd47-4c2e-be80-be9ec49c77e9","order_by":3,"name":"Tilo Patzer","email":"","orcid":"","institution":"Schön Klinik Düsseldorf","correspondingAuthor":false,"prefix":"","firstName":"Tilo","middleName":"","lastName":"Patzer","suffix":""},{"id":594818968,"identity":"165525cb-e687-43a2-9952-57b9ff449645","order_by":4,"name":"Lucas Meyer","email":"","orcid":"","institution":"Asklepios Klinik St. Georg","correspondingAuthor":false,"prefix":"","firstName":"Lucas","middleName":"","lastName":"Meyer","suffix":""},{"id":594818969,"identity":"72250ead-f1fe-4ad5-8735-665d5a9cd14d","order_by":5,"name":"Michael Hoffmann","email":"","orcid":"","institution":"Asklepios Klinik St. Georg","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Hoffmann","suffix":""},{"id":594818970,"identity":"b1e8481c-cf3a-4851-ac7e-e23f35352f35","order_by":6,"name":"Peter Behrendt","email":"","orcid":"","institution":"University Hospital Schleswig-Holstein","correspondingAuthor":false,"prefix":"","firstName":"Peter","middleName":"","lastName":"Behrendt","suffix":""},{"id":594818971,"identity":"1af8709a-cdad-400b-86c1-4ef97a1df8a4","order_by":7,"name":"Jan Vonhoegen","email":"","orcid":"","institution":"Klinik am Ring","correspondingAuthor":false,"prefix":"","firstName":"Jan","middleName":"","lastName":"Vonhoegen","suffix":""}],"badges":[],"createdAt":"2026-01-30 16:10:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8743118/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8743118/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103213327,"identity":"694c90f3-4c57-4f66-af1e-88036fb92c06","added_by":"auto","created_at":"2026-02-23 08:57:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":535466,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMRI T2-IMAGING 12 MONTHS POSTOPERATIVELY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFIGURE 1\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003e\u003cem\u003eMRI T2 imaging 12 months postoperatively. a) Ligabrace Technique: Sagittal view of the left knee showing an intact intact isointense ACL. Tibial Endobutton fixation was visible and Ultratape (Smith \u0026amp; Nephew GmbH, Hamburg, Germany) was slightly detectable. b) ACL Reconstruction with hamstring tendons and tibial screw fixation: Special ACL view with an intact isointense ACL and visible tibial screw.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8743118/v1/87b30e50dbfe291d4d9fbc68.png"},{"id":103213328,"identity":"8e29d506-2c94-4509-959c-b9f08b1cf1e6","added_by":"auto","created_at":"2026-02-23 08:57:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":246176,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePOSTOPERATIVE MRI\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFIGURE 2:\u003c/strong\u003e\u003cem\u003e Sagital MRI view with visible drill hole in an anatomic positioning at the femoral insertion site (*).\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8743118/v1/8c2003d2a333fab75cccd39d.png"},{"id":103213383,"identity":"a41a10f1-0b37-4c63-98b4-8df502a3c0d9","added_by":"auto","created_at":"2026-02-23 08:57:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":968214,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSCHEMATIC PRESENTATION OF THE LIGABRACE TECHNIQUE\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFIGURE 3:\u003c/strong\u003e \u003cem\u003eSchematic presentation of the Ligabrace technique with tibial and femoral Endobutton (Fa. Smith and Nephew) fixation and an intraligamentous Ultratape brace (A) and ist intraoperative imaging a) A No. 2 Ultrabraid suture (Smith \u0026amp; Nephew GmbH, Hamburg, Germany) is passed through the intact portion of the ACL(Ñ) remnant, 6-8 mm to the avulsed end with a Firstpass Mini device (Smith \u0026amp; Nephew GmbH, Hamburg, Germany). The suture is captured and retrieved through the medial portal. b) The passage is repeated with the same end of the Ultrabraid suture 2 mm more distally and again 2 mm more proximally to create a whipstitch-type suture. c) View from the medial portal. Femoral guidewire positioned in the femoral drill hole with the intact ACL remnant. (Ñ) attached femoral ACL remnant; (¬) guidewire inside the femoral drill hole with which the the ultrabraid suture is shuttled through the femoral drill hole. d) After femoral fixation with an Endobutton, the ACL remnant (Ñ) is reattached to the femoral avulsion side\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8743118/v1/54851d81f15d9ac8357eeea1.png"},{"id":108493324,"identity":"e2cbaf26-f770-40db-97b2-b0068807b4bb","added_by":"auto","created_at":"2026-05-05 09:59:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2127567,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8743118/v1/aeed26ae-8ef2-414e-ae4c-802dc91a5db7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Anatomic ACL repair with suture tape augmentation and cortical button fixation for acute proximal anterior cruciate ligament tears: results in short-term outcomes similar to those of ACL reconstruction with hamstring autograft","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAnterior cruciate ligament (ACL) reconstruction using autograft tendons is considered the gold standard treatment for ACL tears [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, despite advances in technical and biomechanical aspects, clinical outcomes remain suboptimal. Reported limitations include loss of proprioception and graft site morbidity, which may result in persistent altered movement patterns and gait kinematics, respectively [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In addition, revision surgery can be more challenging due to the loss of available graft tendons [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Furthermore, ACL reconstruction has been associated with an increased risk of osteoarthritis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTherefore, primary repair of the ACL has received renewed attention in recent years. Although it was a common treatment until the early 1990s, mid- and long-term outcomes were unsatisfactory [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. More recently, encouraging results have been reported with suture tape augmentation techniques. Heusdens et al. observed a failure rate of 11.4% at two-year follow-up [10], and Jonkergouw et al. confirmed these findings with a similar failure rate of 10.7% [11]. In both studies, internal bracing was performed for proximal avulsion tears, with femoral fixation achieved using a suture anchor. A systematic review concluded that internal bracing in carefully selected patients with proximal tears produced favorable clinical outcomes, and that bracing with a nonabsorbable suture, scaffold, or graft further increased the success rate of ACL reconstruction. In addition, marrow venting at the femoral insertion site has been shown to release pluripotent cells, potentially enhancing the healing response [12]. Clinical outcomes for patients with proximal ACL tears have improved due to advances in diagnostics, arthroscopic techniques, and patient selection. Magnetic resonance imaging (MRI) is now widely used to identify candidates for primary repair [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Moreover, minimally invasive surgery, early range-of-motion rehabilitation, and the use of suture anchors have contributed to improved outcomes of primary ACL repair [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Recent studies have reported excellent results in selected patients with proximal avulsion tears [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, the use of intraosseous implants as a fixation method may complicate revision surgery if required.\u003c/p\u003e \u003cp\u003eThe present investigation aimed to compare the clinical and radiologic results of a ACL repair technique, hereafter referred to as Ligabrace technique, that avoids the use of intraosseous implants, with those of single-bundle ACL reconstruction in patients with acute proximal ACL tears. We hypothesized that there would be no significant differences in patient-reported outcomes, clinical stability, or re-ruptures on MRI analysis between the two surgical techniques at short-term follow-up (12 months).\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003ePatients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBetween August 2017 and April 2019, a total of 269 patients underwent surgical treatment for ACL injuries. From this cohort, 50 patients with acute, isolated proximal ACL tears and no additional knee comorbidities were included in the present study.\u003c/p\u003e\n\u003cp\u003eThe Ligabrace group (LGB) comprised 25 patients who underwent arthroscopic primary ACL repair using suture tape augmentation and cortical button fixation. Eligible patients had an acute proximal ACL tear (Sherman type I or II) with excellent tissue quality confirmed by preoperative MRI and intraoperative assessment. Surgery was performed within four weeks of injury. Patients were required to have completed a clinical examination, including instrumental stability testing (Rolimeter\u0026reg;, Aircast, CA, San Diego, USA), and to provide complete patient-reported outcome scores (IKDC, Lysholm, Tegner) preoperatively and at 12-month follow-up. All patients were also available for MRI follow-up at 12 months. Patients with insufficient intraoperative tissue quality were not considered for ACL repair [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eThe control group included 25 patients with isolated proximal ACL tears (Sherman type I or II) who did not meet the tissue quality requirements for repair and therefore underwent anatomic ACL reconstruction using a quadruple semitendinosus/gracilis autograft within four weeks of injury. The diagnosis was confirmed by MRI, and all patients provided informed consent to participate in the study.\u003c/p\u003e\n\u003cp\u003eExclusion criteria for both groups were previous unilateral knee ligament surgery, multiligament injuries involving more than two ligaments, meniscal injuries requiring repair, contralateral knee ligament injury, or concomitant cartilage lesions greater than Outerbridge grade II. All procedures were performed by the senior author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Examination\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll patients underwent a standardized clinical examination at baseline (T1) and at follow-up. The mean follow-up period was 12.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 months, with a minimum of 10 months (T2). The evaluation was based on the International Knee Documentation Committee (IKDC) knee examination form. Instrumental anterior tibial translation was measured quantitatively using a Rolimeter\u0026reg; (Aircast, San Diego, CA, USA), and results were compared with the contralateral uninjured knee. Patient-reported outcome measures included the IKDC subjective score, the Lysholm score, and the Tegner activity scale. These were collected retrospectively for the pre-injury status (T0) and prospectively at 12 months postoperatively (T2). Data were reported as mean, standard deviation, and range.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMRI Evaluation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePreoperative MRI was performed at initial presentation to confirm the indication for primary repair. Follow-up MRI was obtained at a mean of 12.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 months, shown as an example in Fig. 1. All examinations were conducted by two board-certified radiologists using a standardized protocol on a 3.0-Tesla scanner (Magnetom Trio/Vario, Siemens Medical Solutions, Erlangen, Germany) with a dedicated knee coil. Patients were examined in the supine position with the knee in neutral alignment.\u003c/p\u003e\n\u003cp\u003eACL integrity was assessed on sagittal images and defined as a continuous band of hypo- or isointense signal extending from the tibia to the femur without interruption. Interrupted or wavy contours and diffuse high signal intensity within the ACL substance were considered indicative of graft failure. Concomitant meniscal injuries and cartilage defects were also evaluated. Ligament maturity was graded according to the system commonly used in the ACL reconstruction literature, shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e [\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e]. \u0026nbsp;\u003c/p\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eGRADES OF ACL-MATURATION IN MRI\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGrade\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMaturation of the ACL\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypointense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ethe intensity of the repaired ligament was similar to that of the posterior cruciate ligament (PCL) and lower than that of the posterior muscles (i.e., gastrocnemius muscle and semimembranosus).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIsointense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emore than 50% of the ligament had the same intensity as the PCL and the intensity was similar to that of the posterior muscles.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHyperintense\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eless than 50% of the ligament had the same intensity as the PCL and greater intensity than the posterior muscles.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTABLE 1:\u003c/strong\u003e \u003cem\u003eGrade of maturation of the ACL after bracing, similar to how graft maturation is graded in the ACL reconstruction literature (3,18,19).\u003c/em\u003e\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eSurgical Technique:\u003c/h2\u003e\n \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eRefixation Procedure\u003c/span\u003e: The tibial insertion of the ACL was first exposed. Using an ACL tibial guide introduced through the medial portal, a guide pin (2.4 mm) was placed at the center of the tibial footprint via a 1-cm incision medial to the tibial tuberosity and proximal to the pes anserinus. A 4.5-mm cannulated drill was advanced to create the tibial tunnel, stopping once the tibial plateau was breached. A doubled 2\u0026thinsp;\u0026minus;\u0026thinsp;0 monofilament suture was then passed through the tibial tunnel and proximal ACL remnant with a suture shuttle (Accu-Pass, Smith \u0026amp; Nephew GmbH, Hamburg, Germany), and the loop was retrieved through the medial portal.\u003c/p\u003e\n \u003cp\u003eThe femoral footprint of the ACL was identified, and an ACL femoral guide was introduced through the medial portal. With the knee flexed to 120\u0026deg;, a 2.4-mm guide pin was positioned in the anatomic center of the footprint and advanced to exit the lateral femoral cortex. A 4.5-mm cannulated drill was then used to create the femoral tunnel.\u003c/p\u003e\n \u003cp\u003eThe ACL remnant was sutured with a nonabsorbable 2\u0026thinsp;\u0026minus;\u0026thinsp;0 suture (Ultrabraid, Smith \u0026amp; Nephew GmbH, Hamburg, Germany) using a suture passer (Firstpass Mini, Smith \u0026amp; Nephew GmbH, Hamburg, Germany). Three passes were made 10\u0026ndash;12 mm distal to the tear, each approximately 2\u0026ndash;4 mm apart, to create a whipstitch configuration. The free ends of the sutures were retrieved through the medial portal. The Ultrabraid sutures and monofilament passing suture were then retrieved together through the medial portal to prevent tissue interposition. The remnant sutures were shuttled through the femoral tunnel using the guide pin and monofilament suture. A continuous-loop EndoButton\u0026reg; (Smith \u0026amp; Nephew GmbH, Hamburg, Germany) loaded with two Ultratapes (Smith \u0026amp; Nephew GmbH, Hamburg, Germany) was advanced through the tibial tunnel into the femoral canal and secured on the lateral femoral cortex (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eFor femoral fixation, the remnant sutures were tied to the EndoButton using a knot pusher via a stab incision. For tibial fixation, the Ultratapes were secured to a 4 \u0026times; 12-mm EndoButton with the knee in near-full extension. Finally, microfracture was performed at the femoral insertion site using a 1.5-mm awl to enhance the biological healing response (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eACL Reconstruction Technique\u003c/span\u003e: The patient\u0026apos;s torn ACL was surgically reconstructed utilizing a quadruple semitendinosus/gracilis autograft, and an anatomical single-bundle technique was employed. Following the procedure, an EndoButton\u0026reg; (Smith \u0026amp; Nephew GmbH, Hamburg, Germany) was used for femoral fixation, and a bioabsorbable screw was employed for tibial fixation, based on the diameter of the graft.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRehabilitation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ePostoperative rehabilitation was similar for both groups. Patients were instructed to wear a knee brace for one week to maintain full leg extension and were permitted 90\u0026deg; of knee flexion for the following five weeks. Partial weight bearing was allowed, and crutches were used for two to three weeks. Closed-chain exercises commenced after one week, and strength, coordination, and endurance exercises were initiated after six weeks. Patients were cleared for return to cutting and competitive activity at least eight months after surgery if they successfully completed a series of functional tests, including strength tests, hop tests, and measurements of movement quality.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAll data were collected and analyzed using the SPSS software (Version 26.0) to determine the patients\u0026apos; demographic characteristics and outcomes. A post-hoc power analysis was conducted using G*Power (Version 3.1; Germany) to determine the study\u0026apos;s power. Based on the results of the Mann-Whitney U test, an effect size of 0.95 was calculated. With this effect size and a standard deviation of 0.05, a power of 0.82 was calculated.\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePatient characteristics\u003c/strong\u003e: Fifty patients with acute isolated proximal ACL tears were included, with 25 treated using the Ligabrace technique and 25 undergoing ACL reconstruction (ACLR) with hamstring autograft. Baseline demographics were similar between groups (Table\u0026nbsp;2). The mean age was 29.5\u0026thinsp;\u0026plusmn;\u0026thinsp;12.2 years in the LGB group and 31.0\u0026thinsp;\u0026plusmn;\u0026thinsp;12.3 years in the ACLR group (p\u0026thinsp;=\u0026thinsp;0.662). The sex distribution was balanced (LGB: 9 men, 16 women; ACLR: 11 men, 14 women; p\u0026thinsp;=\u0026thinsp;0.564). The mean follow-up was 12.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 months in the LGB group and 12.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1 months in the ACLR group (p\u0026thinsp;=\u0026thinsp;0.753).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTABLE 2: CLINICAL RESULTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cimg 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CgZqSl+uAeWFYgBhDAjj9LAtI8G1krqXAnYD//a3v8W//vWv/BYZcgsQtztjB9HDz14rKpnDffbZJzgdWo1qttlmi969e2fDT8iLGH2ODTJSeQ+yml+gf7311gu7A/fdd1+Qd5Xhp1yV8BRHB+MS39xz7z3hIWo7BbfeMuSNTPLJVbsADFS8ynggO92b8l5cwEtftdtdxwLou4uypd1CgUKBQoGRpACvFYUhtlhMuzcmVMmr1o477rgMfMSfCq3xtgevBFQWQPKFWA9r8bbzVP2gocR4vYQvaFecKk+SNrXnPfQ8pOKbvcJvscUWG8k7KNULBYZQ4KabbspAHchadrllY+ONNw58u+GGG+bjpptuGt9Z6jsBcF1xxRX5gUhvt/nd734XwNGTTz4VQD1eZXgCbL1m7xX4noEgNAdf601feF/ZKvmwmo+mVWtKOeeOEl73pVkPNVoXXnf45JNPulRSN1KAHPK8jxCVXXbZJW6//fb86lBf7gXEAWEx9VWykwMwtxoSr76HrAF119X3jBBD0e9FFlkkVfHHEgAAEABJREFUpplmmvzBvm233TaHJAoBwzt2CSTj8bva0dEv2QmsA/HCtBgVwoG0qZzx4Oflll8uv6mH4emL247CFtVlFCjfnWm8BPTdSdDSdqFAoUChQFdQgGfcGxmAGa+iBNYpKAqpSsAHZSJ+VPiBUAHbzt6lzWskn5fT6yh9KGqzX/4yKD3erwUXXDDErvJWaU/7+vne976Xv5QJAI0KJdQVtCptjPkUGDToqfzAtQcU11pzrRzTXB+1UIVNfrpJfi89HvVAJPCPn/E1gNerV6/8znpHIRg8+16vyotqHeBpybrB+/i6SvgbOLPzxKuvnLxqDEDX+uuvH4AYj7/wiuKlr6jTfUe7I4w5sozMW3zxxYMx9tOf/nS4O8UDvisgLEeoDt7ACykN2ZHxmwHIky+enrGw0047BZk3/fTTB4862akuHsB/HCAMvQ022CAbGgD/aqutlsNp8BCZyWDAv6f+5dTwvQ88p33XyV5GgAfAh/uGhrNCAfTDSbBSvFCgUGC8osBou1kghaddPKhQAckDYvUkpAZwMUjlPWDoQSzbvMCIozAHChJ4p8B4373Fg1dMm1XSj7fbeFCMAlNOuyUVCnQFBX7zmy0Dr+FLYJzBWW8XmAN8lBkwYED07t07Xwa0vXZQ6Az+FI7DiytUbI3vr5Gf91CQ8Xn55ZfnPrQh1deK39rXljh5vzfbbDNV2xLAb825JhQD+Gu7WE66nALAsfkV/nL99deHB6KFEf76178OnvgR6ZCcE57og2R2HCtvvbaAc3l4yC4OXgTo7Qgpz8sOkOMvctTzSSmlbGTa6SRP1RPutc022+SPngkDspOUUgrGg4dxef09mOuetM9Y0H93px7d3UFpv1CgUKBQoFBg1FEgpRSACeUyKrxCo+7OSk/jOwV4THlC8XVKQ7yuYxZNymg6SwFgXoy6oxAX3nXe+hEF8p3tl+HIg84Tr8/O1lOOQYD3nHeU3MOItN9Rm525VgB9Z6hUyhQKFAoUChQKFAoUChQKFAp0CQWAXgBeGKGQlS5pdDxvpAD6sYwBynALBQoFCgUKBQoFCgUKBcZmCqy55po5xObiiy/OX3JNqey4jOx8FkA/shQs9QsFCgUKBcZMCpRRFQoUChQKjJEU8MwPD72H8j3bM0YOciwbVAH0Y9mEleEWChQKFAoUChQKFAoUCnQtBUprYzsFCqAf22ewjL9QoFCgUKBQoFCgUKBQoFBgvKZApwC9p5Crr2iV48dRaDBiNCh0K3QrPFB4oPBA4YHCA4UHCg8Mmwe8/Wd4LJROAfqbb745lllmmfAy/pJmK3SYrdCgrIPCA4UHupUHipwtcrbwQOGB8ZoH+vXrNzx4PjoF6L3TeKmlloqVVlqppEKDwgOFBwoPFB4oPFB4oPBA4YExhAfGTWzaq1evrgf0888/fxxyyCHhC1glnVjocGKhQVkHhQcKDxQeKDxQeKDwQOGB7uKBn/70p10P6H2iebLJJguf0C1p8kKHycc/GhS+L3NeeKDwQOGBwgOFBwoPjCoeGN4PbnUq5Ga4TIRSuFCgUKBQoFCgUGD8pUC580KBQoFCgVFOgQLoRznJS4eFAoUChQKFAoUChQKFAoUChQJdR4EC6LuOlqWlQoFCgUKBQoFCgUKBQoFCgUKBUU6BLgH0b7/9dgwcODCOP/74OOqoo+Kqq66KV155Jby/fpTfUemwUKBQYCgKlB+FAoUChQKFAoUChQLjNgVGGtDff//9seWWW8bmm28e/fr1i4MOOih++9vfxs9//vO47rrr4pNPPhm3KVjurlCgUKBQoEaBzz77LN57773g6PDxlNqllqfKKCs5b1VIvuvS8H5spGrPuN5555346KOPqqyhjvpwXepIbrumzIcffjhUfT8++OCDeOutt6L5GufO+++/H+qN6Pi1X1K3U6DdDsyp+TOX7RV69913Aw90VMb8a+fNN99slxfxKl6X8GV7/Q0r3zoc1ni0b9zG1ao9+a5rq/m6usbYqg951oL10lyv/B51FMCLZJ75qCf8jM/qIzFXeFNyXr/WfK5NfIE/mq+Nrt89RqZjN3300UfHv/71r1httdXy6xxPOeWU8Kqdhx9+OHbZZZe47777huoCAV944YX473//Gy+++GJUxED01157LVxD6KqS8q+++mpIVdnqWjkWChQKFAqMSRSgMG6++aY44ogjYs8994zTTz89y0D5rcZJpj3wwAPxpz/9KQ488MC45ZZbvlKMbLzjjjuys0S5//3vf18p05mMRx55JL9+WFv18mTsU089Feecc07su+++2TFzwQUXxEsvvVQv1nY+aNCgvBN7yaWXfgW4n3vuubmNK6+8ciiw9sYbb8Rf//rXOOaYY+LZZ59ta6ucjB0UAFzOOOOMoO9bAVt38cwzT8dhhx0W119//VBz71o9Pffcc7kd6+Pqq6/+itMPv8MHBx98cObXZgxRb6ujc1hCxABebG/9AeTXXnttnHDCCfHMM8+0bE60AVzz5z//OayVqpBxDhw4MPbbb784//zzA42qa8pdeOGFccABB8STTz5ZZZfjaKAAXHnxxReH+auSaJJTTz11KFn09NNPx9/+9rcsv/o1nNNkWXuyinOCvCTP8NlouK2WXY4UoH/00UfjxhtvjIUWWii22Wab+MEPfhBrr712bLvttrHxxhvHkOs3tHVMQZx44omx0047Za/+zjvvHBaKfIvj7LPPjt122y2uuOKKNoGAoH/84x+DMEHEtsbaObGQTAzlxYK68847G+1dHrfeemv2mrVTrWQXChQKFAqMNAUuueSS2G67vkGWAd5/+ctfYocddoibb765zXlR74TcI6vIt2OPPTbLOSCjXobcA7Apof79+wdApF69zLDOH3/88QwuTj755PjPf/7TVlw7TzzxRFZiu+++e9x77705fHLXXXcNclffbYW/OOHIufyyy7IDZ/DgwV/kRjh3v8DR3//+97xDUV1kMABXwB4jpsovxzGfAoCq+QROHesOt2r0wPB+++0fxx13XOahjrybANB5550XeOW0006L559/oWomH4FvYbt4FT546KGHcv7w/NHHoYf+MY488shgwMICrerDKPic4f3888+3KpJBPKel9ckJWRWyTt0DkOg95PqsrjFgzzzzzAwQ2zOAqrLl2L0UYBxyhJA//RvyE5CXyOhqzpVhYP7hD38ImFF0CYc03nj55ZeHGiD5xZDbf//9Q3vN14cqPIp/jBSg79GjR0gWvO0zyiGlFNNOO20Ou7GYll566XxLgwe/ERTG73//+xCmM+WUU2aQjWgWg0X8jW98IywC9RBYewSEhc1K1ldurIM/Fu75fz8/tt9++2w5b7TRRrHRRj+OX/ziF1lpGWcH1culQoFCgTGIAmPTUDgSKA7ykHKgNHgZgWKeTY6L5vsh4zghyD9A+Z577gngt14OWJJv+x6YUqd+vaNzwAoY2W677YLH0Njq9cnLiy66KC5teNvJSACF4pt11lkzOLvpppu+8izUjDPOGLP16hV3NnYNgPiq/9tuuy3vvE400URhh5YMr64xbijPRRZZJGaeeeYquxzHcAoAK3ab9tprr+zBxqv1IQM35n3HHXeMs846K4dU1a+3Osd/+BjQVfehh/49VDE6esCAAcGzau009zlU4aYfyjJKGaQnnXRyDv9KKX2Fh1XTDw/rDTfckHeajEt+c/INntlmmy0bqHfddVfb5ddffz3vqKWU4t///nemT3XxscceC4byvPPOm/FQlV+Oo5YC5hR2JENFjphv8o08Fh5ufvChHRZy8P/+7/+yk1m5+eabL+PRa665ZqhBk/Pq23nBb/oYqsBo/DFSgN4XZDfYYP3AvL/73e9iq622ykoA03/zm9+MPn36xDLLLJu97VdccWVWKMsss0xe+Czv0884PXr27BmsftvOP/vZz+JHP/pR3qKWx0q3TbvYYovFJptsEgD/sGiFuKxoFhbrya4B5aofE2nrZVhtlOuFAoUChQLDS4Fbb7klnmh4wtdaa61Yc801Y4oppggOjQ022CAr/Ntvv71lk2TW17/+9aBAKAthN/IUpjCAYyB/uummiwkmmKAlOFG2VXrwwQeDJ4nyWX755XORqm0/yErepqWWWio7QaaffvpYfPHFc9gNBwzHi3L1NPXUUwdFCJTx9mtPAv4BsB//+McBLOk7Gv8YK3YI3Muiiy4aAH8ju/wfwykA6Jx00kk5vGqOOebIuto814cNLNlpt1OPv4BfIL9eptW5dmaaaabMy/fdd2+Ou1cOjzAE8TujUp6yjp1IwcDkZb2iscu/7LLLxlRTTfWVkB7tMGRhC0YusD7hhBPmsbjWnHzcxzo2DgaIo3Ha9dfO6quvnvvxm9defeuCAf+9730vpplmGlkltUMBjgo7m4w4xtghhxySQxDtanJyqEaGCL3iPYcv60meXU7ySNl64tDAS5NMMkmYp29/+9vxne98J1ZcccXAr+QbZ4PQLzIQ78wyyyyxxBJL5BDH3/zmNzHXXHO1NckhYjeVETrnnHNGSq2NxbYKo/hkpAA9gL3VVr8N1jkALxbNttwvf/nL+PWvf529PiaLkLfViri9e/fOW1gUzMQTfyMI+GefezZ7diacaMLYqeHBn3322XPsKS+7xbPZZpvFPPPMk4nXGfr0SD1issknC5NBmdny5qGiSEx+Z9ooZQoFCgUKBYaHAm8MHhyffPppAD8TTzxxrppSCsrknXffGSrUJV/84g9woMyqq64aX/va14KyqhQZ2ek3cFNXLF9UHeaBkqO8eJQA7eYKQhp5zikzStGugh1Ru6GcNBRgSmmoaowKYZYMFsYH4AdIUbiUIYOGA8VvgIcn0w6Da4s1nDNDNVZ+jLEUAMwBdIbdoYcemj3N9HHzgIEf4WBbbLFFNtbwc3OZ+u+qje9+97sNcLVk3HzzLfnZOWVgBKAZ337/+9/PWEH+8CS8ycMq9BdGcR/1+vqAR5Th8BMmjN/rZern1iScYk1bi8YGuIvN177w4gUWWCB4chmyeJ4B6z6tK8Z6vb1yPjQFPB9J5gjbhtU4XcWye9mKOYIh7RTZdfHCFY7jepLHCNDO0C1H3nkxF+QrBzHn7j777JOdywwu5cknhilns7Cp0047LXvpyTUYlAGgHD6y2yn8ceONf5KxqzmWXB8T0kgBejdASBP8JgTxEZf3BuMD+jztH3/8UX7ACoEojE379AmJB9/ijc9jSHxp47jgQgvlh2oRm5VLGVnYwLj+OpM+/ezToFAoyEknnTRY36wpbRhDZ9poWaZkFgoUChQKtEOBGWaYIe8iPvTQQ9lDrRjlf+9998brr72et//ltUqUAtBOZvFSDRo0KBejpCrvp/YplXyhk3+EuFBKq6yySjYsmqsBIBJgTnaLJRbmSJk6N67mOn4vuugiwZvPi8ZrxRgQj7zCCisEcMP4INvtOFCYHDjGwjGjfkljPgWAILDFLPkAABAASURBVG+rA9QZqSmlr3ixeZ8B/nXXXTeA/2GB+fpdwwn0ux1+fILXgLf77rsv5p577uDYq5fvzDkjUxiv0AkYoNV4rC08buwA5Le+9a0ODYeUUlh7eJrxy6NrzeBv+SuvvHJ2OBq368AhEInXrenOjHt8LkOmoaedGVEfdoWOOebomHPOOfKr0BlfcNwaa6wRdjvNbXMyB5zKzXQkfx955OH8YLKwQqFRQLldJfHxnnWACRl5ZCAjUNjhMccckx3CQsDJN+3Co1WYjvBExhyedW1MSSMF6O++++4A0Ae/8UbeggW8EUo4zd57751j4Dwp/Pbb7+QFw1Lt3fDQ/+iHPwxpwx/9KD9M64li1hErGYFYuI6IhJiI7bzTqWEYAPEWd1WHlZ3SVwVSdb0cCwUKBQoFRoYCPI5Aq+1jgMG2v+M1V1+THRYUV3vtk3EABmAE4EhkICXy4ksv5S1gCktee220ygfKbCuTf63AjZ0ARoNwAX1TZGQ3+UkuCxNq1efss88Rs88xe95ZFevMiOGEWWmllXKM/GINT7yxU9IAPcWJNnRAq3GWvDGPAnZihKxUfNeKD/AVvsUvrfiro7tSd7nllstF8Bm9j2fwklCVib/Y5coFOvnHmD3Dx3nXajxCN3h/Ae499tgj76ZV5YynvW4ASqARHz/yyCM5hG7wm28Gfmc42BXQtwdweXm1z1hh9LbXZsn/ggIpMj4E5vv27RsLL7xwLL30MrHttttlxwicif5bb711eKGK5zCbk5DsOt77ouUcojjLLLMGY4AXn4PZQ/v68jCzXRVGJFBv7uxIeoaTFx//eWuT8G3zDswLUbST0KtXrxwxklLKfcQY8m+kAD1LxwRc/I9/5K0NgNxCwuCAu0lAKAt1yqmmzJ5yoJ9Fb+ujSiaK9ZtSCluz/fv3jwUXXDBP7MAbBuZXQmmnohnBIlW/2zvWy9TP2ytf8gsFCgUKBUaUArx1YjDJLkBeqKCdy0UXXTSHKwDX7bVNPgEUyvIYCg1888234h8N2Trn7LPnN4lVwKO9NkYkX59ktvhSzpgll1wyfthwuGy00UZZpjNOWhki6i27zLJZEdtREOfPcPAcANDO+6oMw4TnknIUmjEiYyx1xk0KCCebd975coyynR7vc7ezz6uKVwDkrr5zz4ucfvrpOVwCKBNfDaQB+kC481b8jqdXXrl3Bpi8vAyQ9959NxgexsmAtW7dByOWkStUA9938h7G+2Jzzjln3plBiJRSoOe3vjVdDseygwNce61uq8SJDHSrW0+TTz55foaIHF5nnXVy5Abn8aabbprxKEcGPiSrvHrdK0g9eyE80S6lNslinnqyWBlynuHJUYFXzbddGTK83vfoOB8pQI9hWaAeLvGUsJtEeBb2EM/828ESmnGmGYMlTiGxilhCYjclD07Z6hCDaREceOCBWZGwgsS/Tz7Z5PkhWkpD/bfeejO/hoqiaLXwRgcRS5+FAoUChQIcFzx14o3JOUeKhOebYiErO6LSxx9/HB4UXHrppfPrgP/zn0fyx/kWaRgEHtzrDoXB+QKIe/MML6vx9ZhgggBQbClTaO31u9KKK+UwHrGpgBgZb/zaqMINeNd4uL71rW/lUBzXSioUQAH6G48xYr2KFS4YMGBABtvdFarijTbisb1pT4gZZ+Jll12WQaP1yhBnWBhfPaWUGobH3Dn0xgs8AHo7E9Z7SimH3BjzrbfeEnfdeWdMM+20AaDW2yjnHVOAnJGqUvCenUvGFIPLg6tANSdDlfyWyBjRHFXd6qje4MGD80PX9bbJPCBeHZ59hhfZ5VzdlFLGrow1wH1Agy9TSgHcA/rbbrttxqF4SeiOh6vJf3VHZ+oxMp3bYuahtwB43cXbiS2SvIqSJST+btJvThprrblWrLHmGvmVlfIkX5dlKR1++OH5lU+2exGOd58lxJvPU2SLyyuxTMzDDz+SH8Lt379/nqTm8Zs0guKjDz8K59V1zOHcBDuOd6nccKFAoUC3UoB3z3YtcGuLlxz0UBxnBO884NLRAMgtu5q85M8880yccMKJ+WM14tJ50evyTDtkGoXXnO9aZxNvk9dQPv74Y7mvXO/zz6PyOIllptRyftOfRRZdJO88DBw4MMTPk/c9e/bMpcRc277msbTrCtxUyjIXKH8KBRoUwNf4Bu8D03gFrhDq08zXfuN3fN+oOkL/GZ2chWKx9WN9eg6QYcH5aGepMmybO8C/wmgYHvffd19Ylwx15azbpRuG+IsvvhRXXX11zDfPPAHgu1ZSJyiQIuyWDBr0VFthz91w8pJRIjjgQ2+YscNSJb8lzl9OA5XxkuTc8xIeoPWGwyrKAw+RrwC4uefMILc4ick99SShiHgO0LdrCcR7gNo84xsGHUPAjqy5FqGi3uhMIwXoxdb96le/yq+1ql7ThkgmAFj3cIGts5RSINzJJ50UnlTmbarilkyUV1WaDJPnDQkesvWbZeahlY033jg/Pc+aQniLz0MUiN1MPFaXWM011lgjvzauuu5Va/KWXmbpKqscCwUKBQoFuowC5BVwS3lcffVVYceSI0JoIucEb15HnZFnwLPXRlIWtnnJQcADiHFd/ZRSjt/0VjFvrxECUCkw14cnkcUrrbhi3Hbb7flLipwnvJi2sD3kKBSnPUVFDtulffHFF4Ni8zBsVZYBA9BTnHYeGCnA2/CMrZQd9ymA3wGiqaeeKr8lBjAGluTX7x7vP/zwQ8Fg9npU66F+vbPn1qFnRPbZZ5/8XRpx9MJm7J55Ex6sAde0ak8+ZyOefvmVV+J7q6+ecUlVlhOSMWDdz90A9LBKda0cO6YA3Hb/A/eHsBrybMCAAXmup5iiZ5AxZA35aeewVbIjSL54JgjA9055eNHzFHr2ESlOYI4HcfOwqfn0EgKhV56FuPXWW0Ocvf6vv/76YEDw5APwHMtCxPdp8E2/fv3CkZzWvl0ePGTu9TU600gBegMnyC2SE044ITwEdvnll4ftEB+iYPlUAj6lFFM0JscT6K4ra6vWF+O88N+CQkC/LeiqHkOAcrGQnVNwJtZ586I3HpPqtZleo6WMPImnyURvt+12fpZUKFAoUCjQpRQgm3iDeIC2336H+MlPfpIdGAS/V+gCK80dppRyFsCSUspAnZNjvvnmCwpntdVXy++4VkgZQNm5RFaK+bzttttCn/I6Siml3KZ2qnLk98aNcYovZRyIHfXKYc4VSovyrMq2OlKEvKl2H4y7XoYi5qnn4QLaxgSFVx9fOR8+CtC3dd5pVXtY16s6+K7S8YzXZZZZNsc3MwLpd+1I1oA6zm9rGJ3AuNcadhbQq6d+SskhP8AII1QJTyojMYoBy1ywxZ+UUg4b47C0q8VxWC/GeYnX4Q7e/o7aqtcbB85H+hbQf6opp4qrrro6gOfNN/9VeGMQHAl0d7YDIYKwIvAuVAYg9yCt+dptt92CwQaA89YLseIssfMiuoT3Xb0h/W8eQsIZfGScuax4xtF4jFlKKWW+ijHg30gD+vo9WByEe7VQ69fq564jYl051a93dG7C1LP1VRG2o/LlWqFAoUChwKiiAGVw7LHHRt++fcM7rikNHh1eoFZjIAs9hGXL2Ba+MrbxhQUIRdysz2ZZWQBTdkOB7Ao4c4QAQwwF19XtKFFevhNS9aOs/nnWGQb6Y4To2z1oX5mOEmUnhtROKqVZLwuY+VIuRSqUIaUhoKpeppyPHRQArIFpAMt5q1F7OwkPJ+PQblWrMvIYeXbqhTH4jX+9pURdYMvOEH72qlX8KkwmpZTf9GSnB0hTb1iJ11b9DTfcML9OtlV5mMV43RunX6sy9TyhY7zIxjpT0xeP0WW//fcLffpokXuo1y3n7VPg008+zQ/+290k57ZtOF6FbQPaw0NH+BMI93yEc0Dczol2ySKhVmSV8C7g3nWjIgN95ZsMFAa+7bbbhv6FTeIRZeqJQcpxTG7a5axfG53nXQroR8WNsI4tegt7eCZ6VIyt9NFNFCjNFgqMJRTgZOBRsn1vN1LoIW9de7IKoAZ2AWnl3CYlA8RQGEBJSimU0y5lYzczGv8GDx4cwM3cc8+VQX8jq8P/c889d1CWVT9V4ZRSMDi07XVwAL2+3EtVpr3jdNNNF5Qu8NVcHjBbf/31wzujKdf22ij5Yz4FABi7NwzW9sA6z/TPfvazDLzxcHt3ZScLmBI7r4y1gSfxe5WH3xmE+NVuVUop70LhMbs9rqvbUbJOGKVCJtRrVVbfPOvuC7ZoVaae17Nnz+xBxtMMkfo15+uus272AotOSKkYsGjS2SSsRoif72aQQb17986hfJ2trxyjigEndNu5PLyLr+yeksnwI6dGM1DHvwD8jjvsEMK+yUBj0kZzwk9kHj4WdtN8fXT9HusAPQLzBLUnVEYXIUu/hQKFAoUCFQUAGoqk+t0dR88r8dgvvPAiOVSnK/qg5ICcrmhrdLVR+h33KCC0AYj3vJ0QX+fj3l2On3f0+Wefx2eff5ZfciLsydxKXU2NlFI2EIbV9tcmnDA7ULq6/1HR3lgH6EcFUUofhQKFAoUCYzoFeEx5oopzY0yfqTK+kaVASimqZ1Eqz+vItlnqjxkUEH69xvfXCC9W4QgZxaMap7orgH6cms5yM4UChQKFAoUChQKFAoUCYwcFhGB5NkO4n1CWsWPUY+YoC6AfM+eljGpcoUC5j0KBQoFCgUKBQoFCgUKBbqZAAfTdTODSfKFAoUChQKFAoUBnKFDKFAoUChQKjCgFCqAfUcqVeoUChQKFAoUChQKFAoUChQKFAqOeAl/psUsBvY89eErZE+lf6WkcznC/vobo/uu3iRbypeZrVTllmlOrsvrwVotW16q2yrFQoFBg5ClQrcf2WrIWlRmetahOq9Tch3YlZZuvtffbOMiY4anTXlvytdPRGPTnuqPynUlVm+o5b6+O61JzGR/Oco/t1Sv5naOAOWtF33pttB9WmXp551Ud7fvdXtKupHx7ZZrzlTf/zfkj+lvf2myvvmuScu2Vac5XVp2O7r+9MvLxtvrN7ZbfXUsBNJbQvL2WXZfau66u6x3NdXt1uzu/ywC9r3L53K6vFz733HPdPe4xpn2T61PPvmY7aNCgPC7C57///W+cf/754WMGPi5z4YUXxlNPPRXK50KNP2+++WacddZZ0b9//7Z05pln5i/tPvbYY2GRN4rl/2+//Xaceuqp4Uu8gH3OLH8KBbqTAuNZ274eeOutt4Y1ePbZZ8dtt90WH3744VBUeP/99+P222/P6/bKK6+Ml19+OYYl2K3d2xttXXfddVGlf/3rX3HHHXfkV7Xp4IMPPoh777039HvGGWfEDTfcEO+8845LHSZ9a0edV199tcOynblIPpFj5JWP+NXruPbCCy/EZZddFqeddloo8/TTTw/z/t999924++67469//WuWczfffHO89dZb9aYD7e+6665MV/eijHoKUZ4DBw6MP//5z522QnOKAAAQAElEQVSiiTolDU0Bc/fiiy/muevf0DfoSWcPXSryvFx77bV5fq+55pp46aWXmot85Td99O9//zvP3QUXXJD1HB1YL6jMww8/HH/729/y+sIPzWurXr46V+Yf//hHXHHFFaGNKn9Ej8Zlvbg3bdfbce2hhx7KY0Qja3Xw4MH1Il85R1frDs3+8pe/BPyjjfpYlbGWBgwYEMpYN/ABvtYgHGDdW1fKyiupaylAbt93331ZvqL1gw8+OBS+0ps5e+CBB+Kcc87J5e6///787QPXqmTNmGvyz1zje3xTXR/dxy4D9ISxDwL4QuJVV101FHAd3TfZnf1TOscff3xQ0D40YXIJC1++8wEDXx/zVbktt9wyfPCAoq4W7YsvvhC+WibtvPPO4RPFzn2MxmeIGQOVUveqrmeeeSZ23XXXIDC6855K24UC4xsFAHNrz4eQdtxxxyDLfOn1D3/4Q1RK/aMGuPdlQO/CVmaLLbYIHx8BNqz7VjQDuO+5557YdrvtwsejyAUfu/EBHm2/8sorQaGTE+uvv37ulxzwoRsfQnnttddaNduWZ2y+1EqxdMV77xkfvqpIHgHvbR01Tm666aYwRh8AIofItHXXXTc7GerOh0bRtv/kF/lX0cyHXbxu09djjV1BSpKs87Eec+BtF8r7OBfgn1LK79kH6AHC9mitrZK+SgH65q4778z850NN5gAv4i+ft69qoPWee+4ZeBRv+siOBIhXZZqPQDFwg1/N3bbbbhvrrLNOnNoAtwCS8nQkILveeutF3759s87bYIMN4rjjjhumMWjt4G8GX1d8HwGQxnvGA+QZn2SMxuMd9+4B/6MRXcxhp0yr9L///S/IATTTrg8i4V1GKdqoQ29b09a9MuiuPGDouje7WGv77rtvAJTySuo6CpCvZBqew6N4kKwB7MlnPZl/Zbw6k+xXBgY74YQTMo9aQ0888USQ2+aR/DPXdARnLoeMdkZ36hJAz/oEaBEFgZzXBUXzTSJOc17zb2Wk5vwR+d2qnVZ5I9I2q/uWW27JQsxXGyloAN/9U/pXX3119opQfjz0lFW1aFnolNnCCy8cFPrRRx8dhBeh632sBx54YGirEmbyfViLMBqWoh+Reyl1CgXGRwpYX0AJAe+LlUcccUReh7PPPnsQ1jz2AOuJJ52UvcS+3npS41zyDuWDDjooe9dbyRTg85FHHgkKG/hn5FPov/71r7OBrz4HyMknnxzTTDNNaMuaX2qppYK30+8KGLWaGzt8ZA3lw+ivl+GF4m3Sdz2/1bn7e/zxx6Nfv37ZiwiIk+VVWZ54IAe42WyzzcJ4fU1R32SXuq3unzeyf//+4cuZRx55ZFCQ5B3v1oknnpi9ZDyTyvhgoN3MY489NhZddNHsKfVbu7726eu52nj00UfHG4dRRf+ROZqjoxq6hYcSGDn99NMD6LTby5Cit/GYOTEPADm+was86eaXXms1hnvuuTsYbPSSdaOeL7wefcwxAbDiIYbg4YcfHr7cyijTJ15XnvOrVbvy6DjzjS+WXXbZob6GbF3ZIbv00ks75bnHz5xpQNiAhqccmMdX+qGHr7/++qBvOeWsAXxqvTLWnQOFytYTmgHhAwcODF84RVcGkQ8XHXbYYcEYAepFLuBxXytVBmAUxUDXDxo0KCaZZJLwPQmgEAYwH/V+xrdz8yJ1xX2bW/KVsUa2w0577713MKLIVo5ovGSO8LGvdpO/XqPpI3v4D7/gxX4N2Wiuv/e972X5xzgz18rY2e2qMY/MfXcJoMecN954Y6y44orxi003DURi1VvM9cFZVLaVLRLlbVXZ/nryySezFaQsxQLwEjYSIYTRI1wddtIn4PzAA/fH4MFvhH60Y0wWoMWC+Jdcckm+RpmbLOMg+OqT4tqdDc8GBWJczb3zaPAYEQIWKwZw35QeWgDxFNHyyy8fvE2EKOVKwWsrpSGeJwCB955HYNMG/TATATjXnHNmL4Ytfow5Z+M3D4JQAF5696qdkgoFCgVGnAJkgjXVs2fPDE6Anp///OcBeFDI5AUZce6554aPOO2zzz7BMw1EUwq8+xRCKzlFWQC70047bd6B4x2lCPbYY49goFMstnatZeAAWP7hD38YZACwD/CQm63uTggFY4OcAIApl3o5cg8IJyvq+c3nZAv5+Jvf/CZvNxtrSkNkk7LGpo3nn38+VllllbxLyDO1a2O3kKeLl5Lc047y9USuukceSp55XjI0mG666QLQI5PdP+/r/vvvH+hOFrp/QOef//xnmB/nW2y+eXCAMHRa0brebzn/kgL4R0JXnnfgkVe5V69eOeyLBxmwBGQAGl5MYJan2pyZp0pnfdlqhPk+//y/Z6MMSFV2pZVWCo4s88VLbd0ImWFs7r//foG3ef3x/7e//e22kLN6u861LeyKUYDnGITyq4RvDjjggADO8EeV3+pIjzNWeNthFcZESqmtqPoMF0603/72t2EdGCceRCPAHO+3VfjiBMgH8JZYYonYfffdMyhnqNP79DzcYJz4G0bQNtrjcZhAvtBazcEA6McBiN7yxpdkLVe0gMHQwLqHC8lPdHA0d3i1VRIapoyy9WTH0dzPMsssYXeV3MYH5CKak+/m9uKLL84G5yGHHJx51DzirwUWWCDzN4OWQejjZuQ/+Wc+tWM87cm/+lhGxflIA3pAlzKg1FZtCHtbFgh77bX/GmqxWtiUH2bfZputY+tG4q3mBUBwdRCXBY9QADAP0NaNBXZKw3tVbc8OiygWEOVKKO21197BG6ZP7bHSeAX8/u1vt8rXeIMAcGPTtzFUfRAoxkgxarfKr47u2yQD7bwI8ieeeOKs9DGJLRoGQkope99MPsudIFO2Siml7H2g1AgVwo/F/7MGqMCQxoHpo/EPQxJQBEmrMTWKlP+FAoUCw0EB4IMSJxsoZ+uQcc6j6BygJdDJoBlmmCEIees0pRSUgvXKicDr19ztJx9/HBQRuUBG9u9/WlAe8rQhWdMMeGDIb31OPfXUWSbou7nN6je5pN/eK68ck08+eZXddiSbyQrgqC2zxYlylCeDhkd8/fXXD3JLUjylFIAejyLgYieS8cC4AY6UaW+cQjEYRiussEL2irk3ddBD++gM5PMC88K6f6l+/ykNAV8LL7JIpjd5CDDpt6RhU2DWWWcNAJr+wdMppcCr5h3f4H/6CjBZcMEF81ynlAI/ANMMR6EqzXxkzgFSbdp1MZcppfB7pplmys9N0IHCwb773e/GEkssGRxkDGTlhTgwHFrdgbXGWca4pF/xW3M59yA15zf/pkOtE+sLnzF+8V5VDh9zlPG0MlDdh/4Y1Hi9Xraq4zhxQ9czQhnonG0ppaz78bf66uF3H06iv1986aUcOuZcVIO20bhqixMQTTkhGRnyx4dELpK9jEJ4C3bbbrttMz5jDKIBwI5/YbdWiYzhIFa2nhhd+K93795hjvAe3MagshtC3usfBmRsLbLIotnIVYaTVhll8aEdHAbkHHPMEebX/HNMmGep3u/oOu8xsh1jTlsSlNoqq64aiyy8cFis1113fViU2qdUTjvt1DimsQ3HUjr11NNiy99sGbbMWGaECYLYnuWlsqAsdtt/k042WRzW2K7jqQL6tddR0s6LL73Y8L7flGM7MQclZNIINW2Kg9pvv/2DkWHb3IIn3Gyv8wBV7XuoFTNQ2rYUq/zqyGv19ltvxZINC32yxjjlE4grrbRiFlwbb7xx8OJRhHYmZptttrzNrj1lq2TM1Xl1pNQwkn4JxQq8zzXXXIG5CKjO0KNqrxwLBQoFWlOA7KLQAUvrTilAgQPA+WKLLhpTfQGwKYgPP/xAdk5CUeTZrVMnZ9b+vPf++/nBWbuOvKJ9+26fPYC8dDxR+gNYeAR58VT98MMPg1OC0l9m6aWjynetnuzcpZRCeA5Q4hqv4LXXXpu932QEuUaGcQAIKyBrlasnHnSOGA4Nu4iUVP16SikoMR5eHirKzHVySSgBeWQ7G3iRX0+APJA01VRT5Wz6giGCbt9ebLEM8oXSoD1gqRB9wQv/1ptvhvs3P/Ip0NVWWy0obrsCwI/8kjqmAPoBLnQHXgCcfrX5r/IDxnaJgG+8BrCbezxZtciwwh8MWterfMeUUjYk8WsdgNKrjAO6lKGonjljNOMh8eP65dWs9Kb26sl6YrjRmYs0DDnX6ECADB/jZ2XsPADA8lzDX8rWE97jOORMA9Lo1Pp1a4fBYQ1WOwF4S5vwCd5mpNTrODd29wMsopE8Y4IbrNk5G8BPX9aU9bPbH/4QPLvwB8AIHzAu1JPmnnvu7CxAF7STNz4k/INPhMbgs8MOOzw4Y8kXmE1IMzrASSmlDKbJoHpKaYjRH03/4D7lyBvRD2huB5bT2G6A+TFn2kbzPn36hJ0S0RJ2kuyuWj+MNHkMUO3pxpoRjmXNWFut5J9yozKNNKCnQDC9uDleaoxM6PNAEfZuBqH+ec0/w+IE1FdueJRsLbPGUkrZaqUMEcfi51Un5BdbbLHsWbC4KClltDfM9HmExaYdD3BZdN/5znfyFqFJtZVoYj2ko01Kj3VMKNnqMQYTadGx6oyjmsSqb2OiVCb42tdiyoaySinlS6z6XXbZNXb8/Y6BEdDmkEMOCX2JvWKY6DMXHsYf1rt+CcMKvBO2mAujGu8wmiiXCwUKBTpBgZRSVhTR+CdUD5gXzkIO/XSTTeJb000X5ACFc9JJJwfPJMB8yiknh4fbyRCAo1F9qP/WaUopCHw7jjxOlAkFIyaTnEkptfVNNvz9738P4Jrhv8uuuwYHRzT9owTJH2CEzKkun37G6cGDBTAJKyQjeL8YEwAVIFSVrY5kDNDDk+icbKuuVceUUh5jSinLUaDD/fDeAmgAS0pDZGDU/qWUcr1o/DMWMdbi7+mIzbfYopEbWf7rNxr/lDnvvHNzHD+PvPCN6pojecyA0i8l3KhS/neCAikNmRs6jY578YUXs6HIQw8ES+hJf9ebo2+AHteb+QKAocsZiaeffnrwcgJm2hfCo7ydFKDbc3VAPt7HL/ABR1t74SXAkj7xZAWWzTtvuHAIvKc9nlsGijyhXHRlffzOrR+A3L367T4d6yml1Man+hWbD0zOPvvsAQD27NkzWv3DkykNoa2+1eHgdI/fXnzxvNOlnnWqXevGvTOCOT7RyHXJGrSbAmi6V3njRWqQz5y4dyFha665RgbVvOFkHIMNaBYS5k1ZrRJZqkwzvcgJtBTmzVGw3XbbBecBw1ZfQsnkkzucCPgVj66//vpBNuNRjhPtVnNtzsyRkEMRGgw2TpmUGjei4GhMIw3oAW2KDUFYpgQ2olBuPO683xbdq6+91thyWyJ4A9wvIeHhG4sNgdRRjmJEfJNpcXjoS9sIyJJSd1hJewA9z5WyFpN+LRjA3m/CSJ7ryq+22qph0dvme+edt4N3gFDauOFlt/iUqydjMaaJG9tu+qqupZQCY+68085BeVNe2223PuGPXwAAEABJREFUXfAAMH7sGNiZwMBVnfaOBAQgrw/MpBwBazyuYVZ5JRUKFAp0DQUA9mOOOTbvJgqNE4pnV9G6Axx4+KxpSn7jn2wcDz7475hyyqnCdbKseRRkgQflPADqgTweZkqFF8gOH1lX1SErz2gAI7GeZJWdPYZASl9VFOQlTyiZVQEe7ay+2urBYdG3b9+gZMgOCsxv/VbeTmVHJHF2eN6AMvN8EyBFRnJedNQeulLIFC962j6vvKFVvTcHD45TT/1LHHjgQcE5xBEya2NXs7ruSGaTvQylzshQdUr6kgJrrLFGiG0XH2xHBGARBkMfp5Tik08//bJw44xupIPwdkpD82FKKb8MYr31hrzpiAfTzhNgxLNf6Vk8U4Vs4UG8w+AUxsMrq/1GV23/ladb5c8808xt+XiMg04bQBcAJ2yFAYu/tVmB9rZKw3kCa8Ax1qz+HIWCpTT0vdebxYd0+84775Rf3WlHSpw2XGBNcw5Yr3vttVd+JfWpp56aw5qsBbsAVVvmwHp+883B+fWhVf74cERD0Q0cKO4X3rF7QQ4y3MgP4Pm6667LD1vDnfXEUOUMUbeetIuPOBCEE5LBcCX57dkIBiV+w+fzzzdfcH7gL/iT0xnwZ1BoQ7vKMQLMJT4B5u3+tGfwqTMq00gBeoASQwLhbvLoo47KBEEAhCTwTQLLFMAnQOo3xxtg4pRlxTvK056FIPFE8W6vtNJKOaa0Xr+9c+0QJhZ7VUY/lK5FU8+rzjGTbUke9dtvvyNs31nQYtkpxapcdWTVUSzaZRxU+Tzw4q6EG/Fa2crnZRKrzyJ8+umnQ5k333yzUaV9IdG4GKx5/VBiBKq8lFL22MlHH3klFQoUCow8BSiNA/bfP3vHOQPE1FIEVcvAsHUMkNhtI8yBb148QIK8qMpWR95zYSfaI/9SSgHsMPDJDcpKWR5J/VHyM8wwQ37bTe/evV1qmax9cpWcS+lLOaIv3njAR59k15prrpkfwAV45msorZYNdjKTAgQCARgPutplBaw6qg58U5QUKmCHZsbp/qt6aO/6AQccGL169WqA+gOjUu5VGUf3QyeQf+S8vJI6pgA6oRd+ARjxNOAN1PBC0nmTTz5Z1q/CnOqt0dvq4u/6fFVleNCBG6GydJ04ZOCa4wzv25XHo8JWeKTNH5CGNxmigLv2q/YcgSb6E9Ca8OsTysqJ7vZMBrAs6Vtbffr0yfzNsASic+ER+AMQnv6FQe1+GdRCZCac8MsxNDeLtt4mZefAA8IiAKwPMiGllN9uxcPLEcBrjw7CNoTd8NTz5puXql20+vDDj77y/Yvq+rh8JB/NcXWP8Bp+gQdhTfhJ1AVjrjkdeOCBORSvqlsd8Yj5s7tK9qCvvCWXXDI7YeAxfUiLLrZYLNZIzjlNe/funXdtGGN4Q5vk3l577pnDxclT/Zpr18aENFKAHlj3FgNMf9KJJ0b//v3bkkXN2uWlN1ES4VG/ab9ZPkCxhWkCLUjeA4pTogh4mAgI1+r1Ozxv6DjtVmUsvOq8OlZ5jhNN9PW8tUaY8MAB9ISTLd6qfP1o0i16wgiwr66J96KY7rzjjvzmHkKQovcw3frrrx8TTjRhtr4t4sZ6z9VSagw2n335hweeh989iKVHP1fRy04GJq3y5JdUKFAoMOIUsKaA05NOPjmAdQ/PASDWn1bJBd70m2+6Kb93GoDZYfsd8usYgVFKgrJQtp6uvPKK+MUvfp5fwQgcuQaoMOi12bNnzwBePBQLQCy40EJ5d0AogzWufKtEppBBzz737FDKXx35xkKuSe7Bb/nkUav2OpM3cODA4I0CwoA4SpXc7qguHUCG884D8cIqybOJJpqorZqdBvd+xJFH5l1cDhFl6YO2Ql+cUMAppXAvKX1Vbn5RrBy+oID554EHgOniL7LzqxI5nPDgBx+8Hz17TpkBvRAHxmJVThyzeaC/mnlH2/fdd1/ccced+Q0vHhAV9mLdDBo0KD/AzAjGewCRvqp2zX9KKcfgm8sq3xG/0q2OlcErP6WUHzpV3pgAPfrQuTz9pDRiPMGhiEd55O0cWY8MFG3qu73kPhm2AwYMiD123z0bogCesaujXffes2fPzLPy0BFgdCQ7GKjyHYFHa1iS15k0rpQhB8nF6n7wIbnMCIXDzIndDa+ebE486mha1a2O+NYcwmmt+I/RyfGrDFmFp6u68JXfeBF/wat2g25s6IDKi8/ZmtKI8VzVT1cee4xoY0As73xKKT/o4U0LSzSsHpYP7xMQLtYbwAVOLWwPhnrw1CJ1TmlalCmlQHjWEW+Oh8UshPfefy/E41EevP4WiX7vaIBlMawU44iOv17PpEme6LcdTHGznu0MmNR62eocI1DixsC7pr5r7h9zHPLHP4btRAqIArSDgSE/+fiT8LwB2qiTUspvHFCGcLANKdyHle+e0dKWH6GlffRirarfioGVKalQoFCg8xQga0477bQQuw5Ii8+1Nq1d4YRkEuBgPe/WUNrKeS6IsvGgnbVpJ8+6p4TIJ54cskE7N9xwY1BEFALwyiNqu5b8YDxot3///rHQwgtlQGCXkozUNzmk7+a7sf4pmvfefS9/mKq6blzGrT5vvF0E4L/Kc69V2c4e3QO5xEOmXc4a4TzkEJklT7vKuUchOWQ+BYpW7p0c48VMKYWxuDf1OTY4LoRWLvmdJQMopDyrMuKzq/vXHrmPPnY5UhpzFGlnaTmqy6WUAv14kTmq8J65oY/wIFrONluvoPeEg3Fk4UdlhIThS6EPPMsppfzGJvoJ76eUcpyx8ClhPMCpteKhZ4aBh0zpdd5pXmqhOMqY2yuvvDKTgs4H7vOPL/4AukCcdfXC8y+0vS3PesIP6mtn/YaDzPNxgCAebG+tfNFsuwf0Eb5BPwuRY5TYdXIP+FufjHHpjjvvyB9/AtKBRM5HNGMwbfB//5cfgFcHfwOnQsfQAA4S4mF90vUDGgaA+7FGzYHBobl61nWVJ398SBN8bYK4/Y7b49xz/xbm1hyfffbZ+aF5DwvDWwwsbwRrlTgJYDVz5BWkQmWcM6Q8H+kZDlgSjRmpMCb+gsUYcHat5Am51r85PPfcc/NzkDz7MB4nDuP45w0HDSe2tpSTzDX5N7rnaoQBvbc2iGdi5QtXab4RC8MbXiw0At4Tw0JaCGxbT1tuuWVYMIgKqFvEFAXgz1vD+/PbrX4btrcxOEVLYZoo5VholEFzv4hK8APO9WsWLQvYtSrfggKQqzw7AISQcgRNq/uq6hqv6ymlfB+YxzXbxOJKKW73IFbW9qbtQAIUIzB23LexSkJwxB/aThR/Z9vun9dcE+7Zu3sJN21LAMObgwcHurMs5XVvKq0XCoy7FLD+gFUPkFLSlC5Aby1WSRw9R4K1CUj367dPiMUUYwn82D6nUMgEgNNzMieddFI21JdZZtn8dcGHH3kke/ZdE+NOLto+7tWrV36NJdAADJNtVb/AChkC+DbPAFlFVpJh2nJURrwuWSLZKQS+7Dz4LcSC0lKuo4Qm5GJVhuwExnhjyVxOGfdsnMbYp0+fQAdjOOHEE8KzBgAcGSiEAcijL3j31ZHIWU4LY/cAont89JFHo057xgg6U5zGon0gkzyk5OkN+SV1TAGvWaV/gUU8i//wFZApnyOLgeShaUfeTvMgdIvH2Px6lgNfcHZpA0CiN+2ce3gbT6ijXbrZWqH/gSw60BjofjzPu2m3AB8AZ61GDwTzfuIhY1AGqDJGvCxdfPHF+aON8AT9arwMDWU7SsYtVWXwHvCIT/EjL70xGx/+FjJrbTIc8CNgB7vgcTqd3DAWtFRHUs+aQU9gn/xAH+vf0QP3nmdAJ3LDWABJDxWjFR6XN76klBrG+ecRRx11dN4FxCdeqgI7oVNn6YBfdt5l5/w9EXKDYQRPoScsifb4nzMaTiO3OVbIMzzO6UBO4WP94y04DIYlO8nFS/5xSVgD5lnCK8C/a50dZ3eVG2FAL9YJMMXstkOaBwiEu+ktG8AduBdLR8FYELw7BDpFwzqX1GclUUgWhomw7aQPAkbMHQFui5dnmnVMwKhXT+qIt9e3xeRalWcCeSLkWUTGQUCYyJQaDNW4YIKMy6QSKo2sdv/37t07v72ChY55FGQREix2HzBDtTiNiQJjrLD4lJ1qqqmjb9+++WMqtpgZA7wk6hEaXvO5+OJL5K1Q5aUBDcv+o48/Dl4PBo68kgoFCgVGnAJkGWABaAAGvMnWokTg806SUdYoj/xaa62d1yTPDq81hc2DZARTTTVVDtnhvCB3GN2/3XrrvB3PAcDwt4u33377hTh3Ms0OHCXz85/9PL+CUr+S/rTDY63tekop5bc1GPsNN9wQ5KHrDH2yEtAydjsHZIU8/fI8KtdeMh73T6ExXpRLKYUwAkqWXKTgtGmM+iBHKcyUUizRkFc8aeQsQ4A8I+PQVTl1JPKQ0wSNnKM9g8MYXZd41tx/JecAu3vuuTsWWGD+/E7plIbIbGMsqX0K4E281q9fv8AXDCMGkZ1v/AvQmHfz4y10do1SSoHv6aH1118/P7elB7qSUwo/pJSCXuelpjfNJUOT/gOc6N+UUphn/A404Vf623V9O9duc5JP9/N+MrJd17628LKEDxkjziUPsVe8onyrZC0Zv7arstY2foZNYA/rUcKD+Fuf8Ii6a66xZuBL9+m3ta8e4wX91JGsXWtAHwxT968tzkIyARZBtznnnDMPk4FhFwWo13e19vLF8eAPWbHgAgtGnz598tuX0A4At1uCFzpLAvy12qqr5edvnONr9BTrbs7hPm0LkyJz4FR55otsB87N6ywzzxz6lsh0c2YN4Vsvc8Ev5rlKMK6+OjvO7io3woDe4mFxIwDCNQ8wpRSLL754tpQQwFseeGt4b3i8GAK2VTAy4IwYCCv+DvDl4VLeBwMsXAtDHyaXAKJAlJdXTxa9UBkToZxrJojCZhhUC4iHnOCSp8+UhigHgsp9EWJVn9polbRFkFmIkntJKYXJ1x8BKmaUxwKzWMS8DtW4jc+bHBg6gL7kNw+BV+UZC7pUfdvW9hYhQpRQca/VtXIsFCgUGH4KpJQCuCHgrUPJOqyS3x5+IvitNwDZWhZG4tWSHAJAckpD5EevhsedlweAJT9SSkE5WPtidNWztc+h0bNnz/zBOSBZP1LVb3XUFmDU6s4oE+MRmsezx8GhX+20l9Rp1VaVRzYBSYAcGSufrORJJJu0W42tOipLaapLH3iLBJmqvnAMdapU1fGb0YBeAJHfVarKOJLj5CnZ6nV1r732emy88U+CkjW2koZNgZRSfhCbt5OTqH///uH5NE6vOnAEbHs3nFTmgc7C3+rgfb2klILxRX8DrymlbNgywug6vK0eLzTDMqUha0K7DDMGhOvWgbkHrKKdfzz7vPD0Pc8o7zjDhL42vlbJGNpbK1U3sApgZk3rQ74+2uNB/cAqABs60M3WK95m+FZrQjkJz1bJww074fAAABAASURBVK/aVw8mITfQHiaoaFTpdzt0aMMBuNZaa4Y1p+64ntrur+GdN3fogj740xzBSG1lOnFCppLljErnqpDDjClGFR7VNh6ot62M+WRk2W069rjjgsw2z+Q+uQkXmmOpmuPqCEuOCXM2woAeI7oBR0RrlVJKmTEJ+ldffSW/PcL2ByLwSPHGMwx4dLSljZSG1EFggkB+SkMEg+u23SxABFRGXnMypuZ6nc1LaUj/yje32/w7pRQAvcV+0cUX5YddqzLqG4N7IDgwBTpU1x1TGtKXcq5LziX1lakShSYe1ZZznz598sN41bVyLBQoFBhxCqT05Tq09qzDKvldX7cppeytBAys7fo1I0gptck8v6uknDbVc6zWd0opgyL9SK7Vk7yUvpR/UfunDQ4SQF7Ii3CYqp96G/VzdWpNtDxVprlf7cqT6u05l6eOxqpyKaX8fnnXqqRsleQpm9IQevktVderozz3J+TBtjbvKlBZ9afPkjpHATTDs3jQEf2ba6aUhuJvdepl/DYnjlV+SinzfL3dlFJ1OR9TGlJGv+a2Vd+5YO0Po8Duzm2335a/OosP9K1+q+RaSkP3W2uu7VTfUpWR0pCxqS/V2/ZbSmlIu87VTSnlN6D4XaV6Ped1GjmXB7OggTbii3+803bZvMefsTDbbL2+uDKeHBpg/vP4PD7+5OP8vAT6oFWdRsNDCfOhbkpD5kzdlIbMcUdtp9R+GfOn3SoZX5Xkua6f0Z1GGNAPz8BtT/Xtu31+tdRTTz2ZY0bFwtumYrUKQUnpS+J31LaHTGx72AYbE4hod0GIzPvvvR+did/r6N46uvb+++9lobbO2msHDxom6qh8uYYCJRUKjNsUEAIhXlc4iudrxsW7FSLiYU6ytm/fvnlLfly8z3JPQ1MAKFtrrbVyeKkHGceEGOWhR9g1vzxQCQ8JCeHJ75pWx55WGIKLLbpY2J0ouGbk5m2UAHoLc7755gvbZaed1j+/8cH2knAaMX3DA8x5u6ttkJG79a6pzUrjNRImROF0TatfbWXCCScK25T79OuXt+m/WqLkFAoUCoxvFBBOaPuYZ8/W/rh4//SDLW9b5ZR+t91jaXiMowCdusfue4QHI+GIMW6AXTAg8fnCn4SqcX52QZNjVRNCX4QWCs+bqPY627HqJsaQwY4SQO9eU0oZiHoi3quCeJbEnro2tieL0C5DdypUjO4hJQKOghvbaVbGXyhQKDDyFEhpSHy05wCA+5Fvccxrgbzz7JF7dD7mjbCMqLsoYL7F2ntubFwF9MJw8Lbog+6i45jcLqeo9c1Rm1LnIjXGhPsZE8cwygD9mHjzZUyFAoUChQKFAoUChQKFAoUChQJjOwUKoB/bZ7CMfxylQLmtQoFCgUKBQoFCgUKBQoHOUaAA+s7RqZQqFCgUKBQoFCgUGDMpUEZVKFAoMN5TYKQAvY8kPPXUU/Hwww/Ho48+OlSS58n0999/f5hE9joqH2by2iavXvORFK8p84rKYVYeywr4Kt2dd94Z7777bn5F0yOPPBKSL8m1uhWvtEJHX6BUp1WZrsgzB88991zoy7yOaJu+unn33Xfnr2SOaBujqh6ae4e3r8tVfaI33vMVxbvuuiueffbZ8MrQ6rpzc4jfzZsjvh00aNBQry2tyvvWQjXfVV45jn0UIJPMdUfyzLrBE/iqM3forTTWtTfU4KtWdfRrTUl4s1WZ5jwy1BrEx83XRvS3Mfo6ZnvjbG4XDawLY0CX+nVvrSHbyXxrT3IuT/vqWnuvv/56vVo570YK+EoqHmvVRcWDeNs8tSrTnEef4Bk4QB2/m8vgA31qV//mvrlMq9/eSe/Lnfik1fXhyfNmOv2T38YzPHXxKx7v6O072qQD3B8aSPTsvffeGz4yNzz9lbLDTwEyk3zxwS58WE/mBKYyJ3gPPymnvKSsOa7Pk3J4hi5wffhH1L01OgvoW47imWeeCU9m+wKc5PWN9eQdyW68ZeVaJiJddNFF4W0NFJx3rXs92dVXXVUrNfafYhJPcvs4FCZhDHmnvHfzn3PO2dGs+Nzx7bffHj5e4w03DzzwgKwuSYTQv/71rzj55JOD0DGeI444ItAdiB3RThgEPr6hbe2OaDvdXQ+Y8vU4H5KgsIwVCPL1OB9T8YGcjTfeOMyNj4cQyhY+sOTjFOYNz0vKK+djFkceeWSYVzztHgY1gP4+++wTV155ZRAu8koauyhA0PvYiTkm81qNHg8ps9VWW4WPzEUH/yiRf/zjH7HllluGL1OSe3ikLivx2WWXXZbXvjJ4zLc78Cheba95fMcY9datVuPAw+3VbZWvvQcffCDILd8NISdalavy3NsFF1yQ38hVjZs8ILu0pX8yYq899wxv9qgnb7pgLPuAno8P7bvffmOFY6C697Hx2DYfe+0VPpxTvwfyasCAAYHv8J/kYz90RntgRnvPNxxDRzZ0ibmt6pjPqg7dQ6/BB66Tocr6Si2wVB9D87l14QNjPu4zePAbQ13WtzRUZosfytBxvoejX/3jVffJUHDfLaq1ZanvQ1A+euYeGBhtF2snyg0cODCv83POOacNwPsIHF7/e2OddLSWa02V0xGkAL3tw2DmuZ7wsXTmmWdmGcOw9OVisrheDk+QueYSuD/66KOz3MIvysIGDFfXR3CIXVptpAA9JUZQA6o+EOXrpVXy8Q+vpPR1t86M2AJDOMpT0u6LL73UmapjRRmC6IwzzggCY43vfz9/TRao5Iniwb3ooosDwzTfjI+p+OiE9zC3Jzia63Tmt773aQBN4FR5yvY/j/0n7rvvvszg8kYk+SKg11D5Ih4LeETa6O46FMo111wTPtTlC5iesAfUfGr67LPPDq9YZdj4rLfXpFrEFJL5IYAJZKDEl4J79+4dSy+9dPgICm+kryF6Hav2LPJFFlkkvKEBPYCV7r63MaP9cWcUFPfpp58ewIZ12mx0WzfKWEeHH354BvPkYnsUABYGNpR8v3798nclVl999fBNjQsvvDCAcHJQGfwJRD/44IPhK4fegnHWWWcFpcNIxFut+uDVxmtTTjll5st6Gevx1ltvjQpY1a+1OnevPIkHH3xIAOnGhv9bla3yfODK64kpSO8Q91Yzawpt6An1yfYrGgau9eDNPN7g5f3Tkvvy9rPVVlstLrnkkmD4yKvaL8euowDjjAedE+Jvf/tbdkRUraM53uPg+Oc//xneTGdOAG7zi1/xR1W+OtJz1sufDjss72x6pbM31fzpT38K+XibnPTVTjyFr30k0s4Xg4LRyCis2ms+8qYb6/LLLxfTTfetoS4ziOnTVuOqFyTHGSUHHXRQ3lX1YUtv0qFrrUEOxXr5+rnx64dBAQw6l1cvU51bA9Y55xavPFmRUsrvW59r7rnj2GOOCR7+qnw5dj0FUkpBvniTkETe4G1y8Nprrw3fACB36HR8Zc68F18dyRt48C8nA4fNvvvumyMr8Kx6HIInnnhiwFNdP/rhb7HH8Ff5skZKKX8N0OsULXwLvZ6AImCmqgGQIhwwRKlg8OoaoqU0pL2UvjxW1x3VR3D1KQf1TQ5iUlaEiXISAUHRmgi/pU8+/jjkKe93cyIIKBl1tOu6PihJyTkwqG9KWx7hpE35yrdK2nLfJ510UgC8K6y4Yi6W0pAvk2EagJ2izhe++KMfyj+llL8miUbxxT/9K29Hg4VY7999oC+B7V70zWvsXHVKVR20JIzQTh2vBTMW9+me3Bt6KK+e5F7QT3uuE1T1vgGJddddN554/PHslVanM8lYjcO8Gaf2geJqTuW5D0n/2mT46V8dv6tkPBTP4MGDq6yhjuhq8U433XTBC+9+eYwYlBYqq9vHy3hfnAP4gAV6ayilFNNPP332vPA+EtrKWdgA/hVXXBEXX3xx3nHxKtN11lknhCvIU7+kMZ8C+Nz64IUDRqz1+vqr7gCPknnKUA7yU0oOLRN+vvzyy7MiAWq0z1sHvAv/YjjiTyAYnwMOQAZv4k9+8pOwJWxceLZVB+QFILbmmmuGL2rXy/C2brPNNnHzzTfXs1ueW4+8inaigPSUUpZB0cE/QMz3RShC9+YT7I4+lkOeMAjIG/KbckU3YJKxdEwD3Njt5QygKH08b5aZZw5rilzooNtyaQQoQEYCNJwW5513XpZV5H/VFJnKoKJfeCPtZuJTfP7Nb34zyDjAuCpfHfHA9QMGBEwAMP/+978PPG5e7cLjgzvuuCMA7x/96EeBr3fbbbcgQ6eeeupsxOmzaq9+pKM4xVJKscoqqwYeql/X1g477DBMgxUf4mnGBN5jJKtrt8DYrA/rv962c2uOQ45eQDN6Ea+m9NX1Tvdok4NMmbrsmGqqqWKdtdcO3uPzzz+/zXOvj/ExoSO8Qt6RO3Q/2uDBih7mw7X2En6uytaPDDUgnFPOXJM3ffr0CXp57cYckKnmB14gm37961+HSAVl1cH3iy66aJDJHIAcd3iV849s9rpyBhs9UO93dJ2PFKCvBm1hIVDPnj2j5xcJsJNHSJiwe+69Jy/s731v9WDp25qmYCySqp32jgh9zz33ZO/UqquuGpIPqVx//fVhIi1ACtFvbVj4QhxMDqtbHobgYav6ldecfK2NQLi8sdWtXdcxFa+BCQYgAUqKyGTajgEACTzWOtCpTnMyHpNOAAJ3LEBljCmlFDy9Pi5BwKKVaxIvHQHIywtoKy9hdh4vbdkJ0b/7tCDQ031gYgYEIcwLuM46a+ctVUBeOqzhQQFSeBgoeQaFuQI4CKuf/vSn0bt37xBGYutfvjERhjwpa6yxRqywwgqhHM8hAea6Noy3Z8NDyANT1XOto0TJWyQ+HgPAfH+N7weBj/aEIuWAb/RL+QM2QgvwAbBd9YN+hC4wQek09+k6r6P7BnrwKJqZG3OObyeeeOI2q56HkVJCQ/lVewQ0770dKHUYB3akjNO3Aq6++upgdKHHggsuGN9qGA/oKq9qoxzHXAqQOfjnuuuuC55mvGLOm0dsXd90003hK48MWdetUcdWCZ9av7P1mi1WXmXl/NVT37Gw1qxxPA1UADXCF8k67ZCxBx14YFjnSy21VLQaC952HZ/iRe2pWyWyjDHgWOW1d7QeABL8a2sZD1sn7ZWXTw4zJtBh2WWXzSDRvZFFDBUAyhjdv7Xj93vvvZtD/hgfQB/lqi3gzvony9C4I5oqX9LwUYCRJHSFEUon+mBXncbOzYEwM7uY00wzTQZBnBvK0h30WnOv5pXepXfoAb/Nq/r0E94jM3/4wx9mZ4preES7gBO+q3RJc9t0D11jt8B3bFIaGki7J/p5WHxqTAsvvHC4t8UXXzz0b5eWPrPu0aRVG8ZOhuNfNKO3lUOr+li1odz555/X0I8/Cc4ffF+VSSmFe7VG7XTQRdW18fEITB988MFBd8JZ5IedHTgDLkAT/EbvK6Nsc2LoteIbMhD9za8Ee5mbiRs6nmEG8NPJ+oEFZp999iy3GA5TTz0GXgB3AAAQAElEQVRVqDtxoywdL3SHA8+OKbxGz/t2gPrWQjMfGPeoTj26okPExpSEue1UydYYAIzhM5DecqsADJdbbvkMyG1riV3D0AiR0tCLsxqX+qx5wI2CFdJDyRH0FA1Lm8cAiAPitWVB8i4AVZdffnl+ABXY/tu55+ZtbpNatV8/8kbbXrQNVi1AE2v8lKxJI3CMA0Px2FLk2qO0eKeAwnqbzvVtiwdTGLu8KhlvJaB4MN5++618STs8ed+c9Jvx3e9+NzBmSilbioQlBck6xPjGxaAB4AkT1iRaCP9gNKk/9dTTZMvTIkHTmRveL8oT7QgmR8rb4jrllFOyYYZx0V47DCr1bDFRBIT1+uuvn70LmByQQCuD54EgsCwSPCGvo4QG6GouefQGDBwQi3978UA3fXt+gHGz3HLL5VAloB8vzTrrrIHveBIBfH0ATAC++aIs5NWTeTUmniQgzTW0BUDQgWeUx8b2MICi3VVWWSVY6xSZ8h0lAkI7PA7WhbKM3MWXWCI/YGsXQF5JYzYFAGahVFUoDc9MqxEvueSSYS1a/9ZUqzL1POuz+v3Zp59Vp9mr6BrlgKc//PCDYCTyFuF/z9GcdtppQdYARCl9VV4CGuoCOwCUxskC65DXi3yzhh0Bezts1p1yzYk8YFjzSvXp0yd7Q63T5nL133ahgB5yhSEO2HlO4PyGF5JS1OaHH34YgBc5wzGywQb/F55XIUOsy6oPa9K6s54Z4GhT76ucjxwFABIeaY4oehRPVbTXsrni6BFmIJxWHt6hd+l3ukcd+fUELDPEzB35R4cd/+fjc2gJw8COPZ2JP5ZZZplclUyGF+gY66xXr145v/5H3/QwPrDLbR0YL57DxxJ94Tpex/PAPX6rt+Pc+qDjYIqUhqwj8tpYjZ9eoQuVrSd8beyMir59+2Zj3LjqZYyJzoQF1lpr7RxvjZby6+UARfqMZ9darF8b387pYvraLvdpp/UPupgD4eSTTwqgm1yDJTkI0b5VgnfMf0e0MwdkEay44YYbRsXX2sYrrsNQG220Ubjet+/2oSwshtc5L+024hX9MS44YGA6fJvSEF7qaAzdfW2kAT3Gt8htQwhT4LV2JKDF51lQwBfG3WeffQLBKEDeH0rTFgjQlNJXiZFSyvFKABqvsq079f/85z8HBWqBAXeEP8vKOCgwSsoi0T7QzdtFuPDgW8wm0kKUCBNHk5lSytvKqceXZEkp5bAibaU05Nw985Lpm6fbvQB7FK6+oukfpYQJKFkLuX5Zvyw9YzLm++9/IOQxKiiytdZYKwBTY3SftuV5BDEcOqClMeifkCIYefNSSsG7LI9wsVhYqNpMKeWH1hgY6ME4sYDQguLluUBndT04QgE/+O9/Z/BOqAIuDAhgg2Am5PRp3O6NsphnnnkbxsfrMWjQU7KGmVJKOebSwjni8CNC3zz26A7kmO/qPtCfQWjOeVUIbwmN8BLFYMsXTZs7do/ux326D9dTSo0t4vnC9hphIjSGhx8YodTcJ4WhrvIdJeNl6TMqKRtlKQkKkOAwTnkljakUGDIuPMaDJr7Wumtv7sW/r7zyytnLh/+G1G7/L28gwPDYfx4LRiq5ZBeOk4BC0gYefuONwXHGGWfklFLKgH/vhvxkzAPk1Vqr90R+4Lt55pknA3/XLrn0kiCPyWXgjSxirPotUUzKNSdr2A4B49S9t+qvuY519c47b+ddBGvIWnYvnAi8a/ifbHbUprXCU8sINiYAn5yv2p166qmDbAT+Kf0qvxxHngLmhkODh9rc4ruOWjVfdnHpcGtDuAJe7qgOXcU5ctyxx+UdJTpT3Xod/TJCGQ54E5jCD/UyzuEIMp9sBfhTSnl3/o+H/jE/tIuXXcf/xug3/QEMqt9RopvpFg414GyllVZqWZyOs9bRTAFjd6wn+IPuJDPoyG99a/o8zpRSvVg+d5/oir8dc+b4+OcL0nAEbr993yArjj/+uLALIoSQjIKB4By4oFUSrgdfdUQ+c8P5pxy5bj6VJ1vIrvfffy9jrzXWWCPgIc4MERswkzWirDkXnrvX3nuFKAkyjJ5gtLk+utOXyHUER+JGLTIEAKAkSs5vE2SBWWjAl60URJR42nnALDiKSDuthvD+++8HEGlLTn1ATH0LjweZt+Cdd98JXmigy29tsqqEaDAkgGNAirJgFVMqPPgMBUfb6hZ1SilSYxBS49D2P6WhcxgSHsoB0lJK4d54JPSr/7aKjRP3pT9KDKBuZH3lv/YIEUxBqBg7y89C3+D/NshbndohDDG4cjzzGBND2T4knMWTE7rylCdAJd4MQlAiNN9+++3AmAaiXHXuaC4xuy1wAnuttdbKwvi1V1+NlFK4Z/O166675PhH9wX4slzFzmqTMJt++m/FJ598PNSDVq61l4zDuOedd54wZoACuHZEX/OrfXxAGdkNUIdi+fjjj+Kmm27MBge6AdL4C52a+3P/ABGwgO7V9Ykm+npYyAwkQGr77bfP84r3hFcRGOa3Kt/e0ZiMrX5dPwQS+qJd/Vo5H78oQH6RY9YuDziDmdFoZwj/S7yMjFgA/7hjjw1xy/jSuuAcEZqnTDPl8Jb1aBuYjHR96qmmzg9s8yBZ09rn+fdbYtQr11HC0x1dr66R1R999HFM+s1vZocLR4EtdLt55BrPpXUnRJATRAK6GNLCB8lhMrlqb6KJJgrGD6OAMq7yy3HUUuDjjz/Oz13YKaLf7LzQd/RRRyOhlxhz+DulFJxK6tfrAPPK0GscSbyg5GW9jPOPPvoovx4bT+DflFLWR5wy+FjiOFEXz/htN6BaB9polYRpeE6DYwpQJ+e12apsPa9tTdQyrUnrmFfXvdBV9I2yZL+izh0lMsCY6RWgUt74mtCHnLCLY86mmKJnrL32OoE+nKTm37zCAnBMcyLzzH1H9BO6x8kMgHNkkoXKk0n4jsednOU0IZvwu3BfjhcGpbIppfyA+F577pUNSfgE/yhXn1tlR0fqMbKdmggLl2CmeCSWi1AJMZLAI1A/3bTTxsRf/3pbdxbm7LP3yvGTrCPESCm1Xa9OWK4WHWUEyFX5zgFkE/3+e+/n7RMKkDUF1GqfsnSdQTFwwIDstQI8KY2f/vQn4YEIyQO9BE01wVUf1dHYqnNHbU877XTZm+83Jc3zjhbAorwqqUshGRvGqfKro+v6XXrppUMbrNFnnnk6PzTE08Ywcr0qpy1AlVCTr52JJ544MHRKqeEVf62RNYSO00wzdeN8yH9lAXvtSENyh/4rf6KvT5S3+lMa0gY6p5Qa4PyTLECBW8bDI488mgU08C/O3u6I+9diSikbIQT+88+/IKtTSfmZZ54lqoXpvpxPOtmkbbROKeVxGKtGV1hh+YbSny3uufueAGa8EUi9FVZYIYcJKFNPeBENGS76cw2PMfYYfxQBQ9BukHAwigbQZ/g5129KSbWWSVv4VfvmRKGUvqQHo0teSeMnBfCcNQPozj777EFW4RchNZQMfifrGNOM9uWWXz4Yg2SBXTn8JzQFyGqmoBhjeRwp2nEOKAsXI5OFOFobALWdUfl4W7muSIwD7a+2+upBaQIs8847bw6xdI/GLfzMOHj/Z5555lAeHYwzpZTfslWNhWNAGxwi6rv36lo5jhoKkGc87XZ57P4yQulL8m1YIzD3jFe79QAT54jQ00pP4AdeWIDJqwJ58+mbVu3S48Ii6N6qb/yx0+93yuGQeFnoqmt2eqwvBiUQ2Ko9eYxmII5BYYfbLgFQ6dqIJMBTnymlHObLGyzEg85xr3AHJ13VtrFKdI+xVPnj65Hcq2MkMpAss/7RloMPpsRX9VTJxkr+taIf/rn00kszjiFX6/3og0zcfPMtgqEAJ5G5nJnkE76DLbQLRylDXuEbjj88LWTIWlFmdKaRBvQGn1LKgIuyqqeUUt6KxrSD3xwcH3/ySVT/3Pxzzz2ff5o4J60Etvam6DlFWBQ8QMpJFgBgllLKwM3WsO1Z4ShAHXAs1o5nF8EvveyyDHpZ4bz0u+22e+yxx+6x++67xTbbbJ29WCml+LzR+KeffZZBY+M0MwBlktKXIA5zmOBKMLHeGCUm2xjUq1JKKRsS7sPCrfLrR/cNpGMSW9b9+58eDJMNNtggx4yz/JVXDtOjA3r4LZ9y58EyHu1E4y4a3bbdgzLtpZTSUOUav4YqWvXhqB/3jpHFG7Ji119//eBlYcgZg8rGgWbm2IKQN6ykfWW+9rUJHHKq8vKPdv5885uTBm/8oKefzq9FE6NulwhYaFWF9W9MQh0quppL26PaEX+pX3MJFAEbm/1yswAs7PRo07WUGpRqJL+r5L4ZNsoxNhldrmlveOmhXknjHgXwCMOREvGMD88OI54RyRlA0fDs8fx89NGHeQsYFVJKeccIoMGX8poTRWTNkYvWqet4leypkrrVuWNKSbEuSWQf+aNvPK9RfVgLPG2S3TOxsPfcc3eWrcpIxu1ofTpK2iEzATf3nVLXjVX7JXVMAfKRVxPQdi4UAoCpz1FzC3SAHU5GgDopDcEAQBfeq7zRnCNi2IXEal9oQ4UDmtv0Gx9bEzzeZLc8ST4ek5zjFf34LaX0VZ7Bm88//3x+yQbPPIDHwIUhtDmiCfDkxDFG7dKTwm/kA3yMamu/al++ZF0Yc5U/vh45PdGuun+/33jj9fy2LrqUI1GInhDfeuLV7927d5A9Vd3mI8cJWcsQEI6b0pd8wchibHlmrl6PrE5pCL7Ec56nIqvxT0opY167pmSTeYWPYjT/69EV/btBqVVbwDyv53//+2R+wAD4NWk84ix2is1Cshhb1Sc8Fph/geBlB9bVJ+jVtbU122yzBfDOavImEoJC2x7KBH49eGMxESTCdCx4IH+33XaL3Rqgfvfd94gtt9wqK0sCw6SwyAAw4wSsCZ36+JTBHBSwc20zIngDMEv9PlJKGZRrmzJTvn7deUW7H/xgvcbPFB76sLOx3LLL5nAXjNW4kHczgFUA1PY0UK894/W7Z8+ewYKtlKM6w0rq62tYdQhHNOFtIdgB3C233DIIQrsIxmRe9IduGJxAtxC1TTGjo2vKdFXCH7zx+rD1pV/zbHyt+rDogSagh1GoDCCEBykjHhsGii1QhpNyt992e343P6WUUsrhSuYELyqHfspRYsIHtOPtRwS19pXDI+iBV+WVNH5QAJ8w9s0/frNGzjv33PwBN896TNzYXZMv5pwc4BVaaMEFY8YZZojrrrs+GIjqWOseGkc1XkRKxHk9zTDDDFleMEqrdWZ9a1+yJshDMtdvyfV6G8Nzjq/1BRxZf+QqGUg2C3E0bnKBQ4XnlewSFrlbQ/YedNDB+RWc+icbGDdkMy9cNQb3oLy69EiVX47dTwG8SMfZqSQH7bjb3XZO5jkqQ6Y9879n8uug8QDgw0vNY07f4QHhrPjYdViAJ9VOL77BC8JTyHHt4knlmu8Qb+AtZdTXtzJ4RB3JusDf8v2WrD+/FrRdCQAAEABJREFU64ke8/yZuPkfrP+DoNO0rbz28aT2rTn898Ybb9Srt3tO97svz9bRkY7ahkOEKAH49HPVgPvXH51AB1X54+MRvoLbBgy4Pr9l5s2GA9gLPd55592A7eA8RhJjsVXCn+ic+fGZZ4JMcV7REi4A3DlzycEq3zyTYerjRfONZ+nwf15zTR4LBws5tvvuu+c38cBbytD7lRHgeYgxwSjrUd3YiBwRA9FaLcCqPQuVZUWJEA7eYsJSZZUjiO073lTtaE+yCB21CxTZttOO+DaLwsMRFgrhsfXWv80gFmAWtvLmm29mwAXQU5bCgbRnwRiHcaWUsuLDRFJKQ6w11puxUC76kowTI2gjvviXUgqGAwbAZMZC+NlG1sYXxdoOPXv2zB5eY8No1YWqzereMY5tQ8DXcc655spF0YGQoUA9lKMcy9/4CCbjuOOO22PTTX8RdiUIuU8//SzTITfQ+FPRUzvOAXQLwFaW+gwm46nG0qiS/ysrzxjQ+J133smecB5tD4u6d8rbfVdKl7DH9LbgCVkCUfxk375989sOcsNNf/RjbPqpLlV5+q/nKeOavJRSCFVgVABNFj8atLe4ACFzjJYUjjbkCWdYqfdKIQZyyPbb5oE3bRXbivU2E885KK9/ddFf+IB32XuYi4HjgRltUX7aVd58oAdjAqiRV9LYRQFro+K59kZe8Wm9nLk/4cQTGruA2+TwGnw5a8MJQcHwdtrlwke8P0Jx8NIss84a6zd2vsidrbfeOoe2WaO28FdcYYWglKzf5nGQedY0BaVf13nDvcVEwsfAFaDht5BEMfnKDSu5N6leDk8LmbC2KbzZe/XKYYz6d09AnaNwNUY3MGOdAl2UtQcXOQTcm+1w97/GGmu0dUG+U6zAVl0JtxUoJ11CgYpfybWqQbQXtgJkmQMgSlgMeSftvffeObzTvNPrQDzeskvjuSbONrxrfukID2TjW44ODxvSn4C1eRdupk3hr30bOoI3tRpHdaS/6XcAmOw1ZqAKnsDLkj6Bfd5+v7VFl1ZtOFrHnHSe6QDgH3n4kQDm9C+R9xdffHF+HsuD6nQB/lW3OVkPdFaVD+PwFONhvCzZ9YVDGDKe+aMTq/KwAEPFNfdX5Y+y4xjUEXnGwNl7730CLznCNnQuOqaUskdcufZSNP7hW9iEYw7fNrLyf6GucAnsRA/nzMaflIbsfMJVMJDnQ/RPJp18yin5jTt4Fr7xNi68Kbae4QYbwrLwhnkn2xtNjtb/IwXoMSMmBlgRudWdyHezQjIAQpNkkSMuYlh4yrimLSAIeMf4wDzAzboFHpXx0IL6FvZhh/0p+vTZLIe06Bt45OGZrddswWJSlxIRZrPQwgvFfPPPp1i7ief2sMMPC4CP0Onfv3+wuilZY0tpCPB33zy6GMBrHIV5bL755vmpbIu3uQNAlxJjwPBeVdfdq3Zdl/eNb0ySX5ekf4vftZRS3kqi0PTrvg477LD8FUivimTgGAcmw8hopN2pp54qJp10Ms3mhMZoOvXUU+dXYGrbw0raJFRZplNNOVVU13Olxh9MOvU00+SHUwgdjOy1ZHZLML6tKgtO39WWKSHv4ROLgBCmKAhhD8W51mj2K/+NGRjxMEx1Ud/yek7Rsy0syJy6j0knnbQtD70I0emnnz4Yf+asaqP56H4XW2yxTFMKwHVtiqE87dTTAsihmAAdH5+i0CgoHheCN6UUPIZoYXF7QJGVDtyYG3zujTzOUxrCL+ZdO7wMgI0+Sxp7KJBSaqylScOawT/tjdw6xpvkV1UG8Hj5pZfzw+EABJ7mhQd2gHoy0HuRbd0eeOABeTePDNl8iy2yYrNuyDsAhNI56uijs3xKaQhvVf044mu7SEAN54E8BrttYskOkt+OfgMs1r1yHSVjJhfIeWulKstowPeUpTXeWJBZBgJUjHxA37jJB99yUN+OHYAnvPC6667LxoojGYsWymhfe3ZW6QDGtPUmv6SupwDdUPFu1TqZxUllPvAteS/8hrwzX/QYHW6ennn6meyhB27JZYYqp4YyeIBRCcxzftFjQhKtI+AaL1btDhgwIPRTB2LVeJQXlqY/9T/68MPssFIeL0vGS+949bTfYvMZDVUbjkA4kM8YcG/4V/lqDF6qwCA1NnU9aO6obj2llLKTjn5Cv+paSqmxDL5Mrlk7+Li+dugYOmGahj6ef775soOxamN8PH7y6SexwIILZJrStXQvnoF1YK3O0sT8kquMA+fq4RmyCo9z/tXnwXXx8oxSBh1jj7z1/Bx56406jAA6f5999snyDZ8Zl0gKDjrYlAM2paS50ZpGCtADbBaOmxYn2d6dVIvxuuuujdtvvy2Ep1hshDiGl6qHblg7wK+F2qdPn9wkhSKc5vrrrw/bt6x7gmWjjX6crbZcqPEHkDOeq668Kj+J3MgKHnqK64K/XxDe+CCvo7TqKquGBa4fW+Inn3xy8GwxRAgjQouSXnPNNYIQIIQIpTqgbW7fYgYKKftzzjk7v19dGR41CtZWDhrJ23TTTfM2O4AuD9D10CnQuNJKK2VhgXl4TAhMdECrnXbaOSaffIosGHgFrr32uuwV1KZk7OYJUGXkaBt9Paxzyy03h9g0xpK2gAJ1JHN86y235FffGYu6PDcEnznE3Ghj0aWUclzs7bffHi+99GLDOPlRGxAy1xYO8K3dekopBaXtHoWsADSuA+jyLJ7KWCBAhR7wEFXlUkrBs2Jb1+sm8ZP6rZJrQgPQEJB67bVXc7GUUn74kMHCQAMm0MKDYDyNaJLSEOOKEScsx44A4UFBoCPPDo8O4JcbbfwhTLQH9Pz4xxtlwNbILv/HIgrgmV133TWsVXzQ3tApBTKDIqrKWPu88NaL9St/8sknD4AeX5AhZI21OeOMM7mcEwDLI6o9fIgfefE7krPGSSkNHjw4yCWgxXrAp9KgQYMCgAFY/JZ4yXOH7fxJKQWFxnkAcFdrTnEOFEb66aefHkCLPN4vssu6JZvIKPKiV69eLmf5RamSGffee09D1v6roRNuz2/MsrZzocYf3kshEWQkD1mzEm4UKf+7iAJksp1JqWrSrgi+wysSXiHrJOe81niRXiGP8cCMM86YqzvykN57773hGscJPUpH4H36FB9K2tJmlayF3r1753aa/3CI0FnWgtcoM5w5o7QhaU/C537TTfin3g4dZicdX7ovZau+HRm41oT1x9no95ZbbllvIp/jc/LeOqvzbb5Y+8MJZI3z5hqvS4wFNIFnfrrJJrHgQgvJHq/T5599HrPMNEv4xo1oA0kUAvwxPISxQyTCAj86V5dcNKd0dnsOtZlmminofs5Rc0ru6t86SGkIUGcActa5Zk7xN7lIDqY0pIz+RmcaKUCPUIAW5h6WwE2Jl2uymGuuubOCYPHU61AU8rQJwFv41QJAIGVZ/xQqBYO48lyrkt/KSNqR7+i3lNKwiZ5SyqCLcWAyjUtyjykNqW9B9ugxQX7g1xYyxgGQ9ddeMm7b05Q4DwejYIIJJmjz9lb1tIMOBE+Vhw7ogS7yUkp5V4KSZLAQquq5JilnXtTzW0opZa+0/B5fvGdf/0D2LLPMmtsDPvRTXVfPuTw08FvSLg8048tCqF8DJgjZ+edfINZffwPF8xP/PB2MMjTNmU1/jEU/xlBdqvqWl9IQ2qeUMt0J3JSG5Cnv/tHN2PzuKPESAj6vvPpK/PXMM8NcVOXRHSA3/xaq8/r9pTSE9vrCg1Wqxu4+qrYc7UgwojxcywCVV9LYRwH8Zs6b57d+J/gEH1h/VX5KKe9uNefjV3LD7uFcc82V12ZKX/Kz+vrCf3gR6DIG+R0lO1W8RpwSYvfVqXi01dGYO2rPNeMgP+vrsMp3X3XZKN/9W2PWj3E395HSkDU066yzxbe/vViQIRNNNJGqOTFEjJ+XzS6i6/lC+dMtFCBnza95rDqQh9+lVnxT6ZGUUpbH6qpT1SeHzb23HQG1Fe+klLKTp1Wb8vRnbVTt1I/asBOeUgo6VNgk/lOvvYR36204Nzb9SK3qVfxalXNUr55SGnIf+k9p6HVbL4cmyliHKQ0p99prrwUdycDxca+qv3q98ercm0gaN/x5fJ5l5RxzzJnfXIdmjezh+p9SasmPaGy+W/FD1YF5JmvILfimVf/wgTLkNvzVqkzV3ug49hgdnY7NfVqgJnWCHsNHOgxlG3KhhRYOXgvAd2ymQ3tj5z3hJREPydBQzr3/4Ac/CFvxHS0oZUdFojB4gb7/ve/HhRdcGMIauqtfXiKeATsIjKfu6qe0WyiAAsCD3TA8bVdA3tiWhCPwstnytrNJ5o5t91DG2z0U4MzzhhO7P15K0T29dF+rnEf0gd1kO3B2vLuvt7GjZesbLpDQp1OjLoVaUmD4UGnLJsavzMUWWyxstW251Vb5dZnDc/fTTz99HHnkkfHjH/84x7EPT92xpSxPtNh6nkIL1LgBel5GXju/x4TEM9OvX78QKmV83TUmXioPbokZ5rnsrn5Ku4UCKGDNMVatQc+FyBvbEk/slltuGQfsv3/eORzbxl/G230U4BEFhD2TwePafT11X8uzzjprflsKp1dKQ7z23dfbmN8yb3j//v3DMxbdqYvHfEqM/AgLoB9OGlI2tsp4n1Ma/sWorlhaW5zD2fVYUZwHxf3Zkh3TB8xjDmi3iIHssqELp+BpHFuVT5cRojQ0yigg/AGoFw44yjrtwo569pwievdeKWac6ctnCrqw+dLUWE4BjiHPVXgmbWy7lZRSAPSecxtXMcDwzomIB45AdElp+DHV8PY3LpcvgH5cnt3RcG8pjX0LMqXuG3NK3df2aJje0uVYRIGUxlbeM25pbCF2GWehQOcpkFLh7c5Tq5QcHgoUQD881CplCwUKBQoFCgUKBQoFCgUKBQoFRoQC3VinAPpuJG5pulCgUKBQoFCgUKBQoFCgUKBQoLspUAB9d1O4tF8oMGopUHorFCgUKBQoFCgUKBQYzyhQAP14NuHldgsFCgUKBQoFCgWGUKD8LRQoFBhXKFAA/bgyk+U+CgUKBQoFCgUKBQoFCgUKBcZLCnQ7oB8vqVpuulCgUKBQoFCgUKBQoFCgUKBQYBRRoAD6UUTo0k2hQKHAMClQChQKFAoUChQKFAoUCowABQqgHwGilSqFAoUChQKFAoUChQKjkwKl70KBQoE6BQqgr1OjnBcKFAoUChQKFAoUChQKFAoUCoxlFCiAvoMJK5cKBQoFCgUKBQoFCgUKBQoFCgXGdAoUQD+mz1AZX6FAocDYQIEyxkKBQoFCgUKBQoHRRoEC6Ecb6UvHhQKFAoUChQKFAoUC4x8Fyh0XCnQ9BQqg73qalhYLBQoFCgUKBQoFCgUKBQoFCgVGGQUKoB9lpB61HZXeCgUKBQoFCgUKBQoFCgUKBcYPChRAP37Mc7nLQoFCgUKB9ihQ8gsFCgUKBQoFxnIKFEA/lk9gGX6hQKFAoUChQKFAoUChwABkF0UAABAASURBVKihQOllTKVAAfRj6syUcRUKFAoUChQKFAoUChQKFAoUCnSCAgXQd4JIpciopUDprVCgUKBQoFCgUKBQoFCgUKDzFCiAvvO0KiULBQoFCgUKBcYsCpTRFAoUChQKFAo0KFAAfYMI5X+hQKFAoUChQKFAoUChQKHAuEyBcfveCqAft+e33F2hQKFAoUChQKFAoUChQKHAOE6BAujH8QkutzdqKVB6KxQoFCgUKBQoFCgUKBQY1RQogH5UU7z0VyhQKFAoUChQKBBRaFAoUChQKNBlFBhhQP/ZZ5/FRx99FB9++GGH6ZNPPhlqsB9//HGu9/nnnw+V394P5d5999344IMPwnl75boy/9NPP8335P6Gp886TZx35Zjaa8tY0cc8tFem5BcKFAoUChQKFAoUChQKFAqMrRQY9rhHGNC/9NJLcfbZZ8dRRx0VxxxzzFfS0UcfHUceeWQMGDAgjwIgv+uuu+Ivf/lLnHTSSXHjjTfGe++9l6919Oe///1v/OEPf4hzzjknGAMdle2Ka4D4/fffH8cdd1ycfvrp8eabb3a62f/973/53tyfcQ+PMdDpTpoKPv3007HffvvFaaedlo2epsvlZ6FAoUChQKFAoUChQKFAocA4ToERBvSDBg2KAw44IHbZZZfYaaedcnK+884753PHXXfdNf72t79lb/dZZ50Va665Zmy11Vbxu9/9LtZdd904/PDDg4e5IxoD1sD822+/3VGxLrtmPDfccEPsueeeGSi/8sornW77kUceiT322CMOPvjguPfee4Nx0OnKI1hw8sknz32deOKJ8eijj45gK6VaoUBEoUGhQKFAoUChQKFAocDYSYERBvRTTDFFLLfccrHyyivHiiuuGLPNNlumwNe//vX49re/Hausskq+tvDCCwege/LJJ8cbb7wR8803X74unOWwww7Lnvr2PNl33nlnXHTRRTHHHHPESiutFBNOOGEOuwGUqzrOgfDqdx5E44/frjlKzWWqvKpMo0r+n1KKmWeeOZZeeulYaqml4hvf+Eb4p7yy9fPmNqeccspYZpllYskll4xpp502UkpfGW+9vva0W8+rn7suVWVcq5J86Zvf/Gam9TPPPBNnnnlmNp6qMuVYKFAoUChQKFAo0A0UKE0WChQKjGEUGGFAP88888QRRxwR5557bg5N2WijjWKiiSaK6aabLvbaa68477zz8rXNNtssbrrppuw9nnrqqXNoDq87oD948ODo379/SxD6/vvvxymnnBIvvvhiKAtkp5RyO5dddlncc8898fxzz8Ull1wSZ5xxRgwcODDeeeedTF7hPXfffXe+5nj77beHHYJbb701e82F0Qj5Of3003M+w0Ecuso9evSIeeedNzbYYIO8izDZZJPFW2+9le/h4osvjucaff773//OOw9//etf8zj0p+4MM8wQ//d//xdrrbVWNnBSSvHwww/HpZdeGvoQMgScv/rqq3H99dfH1VdfHS+88EIOPTLGK664Ipf/17/+ldu/4IILcl1jNQZ9qP/ss8/musq7F0YEujN+tKNcSYUChQKFAoUChQKFAoUChQLjBwVGGNB/7WtfCx5pnuipppoqJplkkuyRli8MBHh3jVed9xjwnH766bOnfYEFFog555wzlxevzlvfTO4nnngigFMe/2WXXTYmnXTSXOTiBqjefvvt4/e//31s17dvbLPNNvl8yy23jD/+8Y8ZfOuLMbDddtvl8J6+jeMOO+yQY/pff/21+NOf/hS/+c1vcmiQfOfHH398Ngh4vRkBjA7x/owOAPpPfzo0tCekRsiQMey4446x9dZbhzEB9YMGDQrtqPf444/ncCIge9ttt40TTjghA3eA/KGHHop+/fqFvhkmr732Wo7Z167029/+Nvo27k3ojvvUp+cP7Ah4+BXQ17f78CzDTDPNlHcx0Jmh4B4yscqfQoFCgUKBQoFCgUKBQoFCgXGeAiMM6OuUAVKr386l6jcQCmD73bNnzxw2A+Q7n2CCCYInvrquTJV4wT1kqqyQG8DeNd5tD4IOGDAgLrzwwuBBV+Y///lPjl23M6DPF196MQDx2267Le5qeOu9badXr15x5ZVXZUAPcM8yyywx66yzBqPioIMOCmWN3XiAY/3wqgPRPPMSrzwAPv/88wevPs+7XYbK0/7UU09lL361W6Cstlw3Lu17GPj5558PBoA29GEnQn/XXXddzueRX3nllfMbge644464tXEf7kHdq666KocxGTvDCA2EPNldePDBBwPIR6uSCgXGFwqU+ywUKBQoFCgUKBQYnynQJYC+IwICqxW4rUC58hM0PPyO9et+Vwl4BvaBfjsBVT7QKokd33fffcMDrB6aXWKJJQLgFa4CJE/4tQlzFbsExx57bNxzz92x8cYbx6mnnprflvO9730vh+rw5DvniReCo0+7DCml0E9KKe8kGEc0/omP90YZITwbbrhhDuEB2vWZUgrlUhpSJxr/tCFV+Y2s3F5Kaaiyrkfjn7AdRgmPvLf7LL744nm89993X95BYOQ8+eSTeccC4LdzMfHEE8c000yT22M8FEDfIGT5XyhQKFAoUChQKPBVCpScQoFxkgI9uvuuANUKyPNQ64+X+tMv3k9fv+6a5Po777ydQ1YAd+E88utprrnmCkAcYF9wwQXzg6g89Tzfr7/+eqQeKRcXD7/aaqvFHHPMmUEwz78LPObCYDysyzsuj3db6AwA7nc9Va/N93Au77wwF15xZdyX5Lwzyf1J9bLVb+Pt3bt3LLTQQiFs6Yc//GF4ABnA9ypMOxPucdFFF43vfve7uQmAXgy9cfPsMy7yhfKnUKBQoFCgUKBQoFCgUKBQYJynQLcDet7uKSafPBNSKIuTzz//LHubxXp7kLbugXddSqlHpJQCWAX65dWTOH2x+/JcB/pTStkI4KlPkVzKYFh4jx9AN7D7eQOde+OOUJsHHnggtLX88svH3HPPHUCx68q3StpyT64p66i85Dynpj+u6dvRJeeS8+bkOQOGSZXPgJh99tmD5118/DXXXJPDcHjuhdwoZzzexmM8aCHJL6lQoFCgUKBQoFCgUKBQoFBg3KdAj+6+ReCSh9nRO93FjQPTwkIA+hlnnDGD9vo4Ukr5bTmAKo+zsJz6dedCTx577LH8WkhlnCvHqw10f9YwGpTThuSc8cCT7TegLMRGuI6HU3/5y1/md+qLR28PbGsjpSGGgvNhpZRSfvMPIM+Q0K5zITreq5/Sl23J1x5g7lglRotXgBq7h2CB+m9961v5laGMHeW0K85fGwyCVgaSciUVChQKjHkUKCMqFCgUKBQoFCgUGFkK9BjZBqr6wGR1Xj8Cz99dZpmYY4458isavZ1lv/32D293AV5/9rOfZdBbr+PcayoZAkA6MCyvnnisfdjK22i8McarMXm2xdJP0XOKHNuufEope92j8Q+YX2+99fI15b1OUgiLt+P42urAgQOzhz+lL4F2o9oI/WesqOg+GDM++iRe3wO0PgLFqEnpq/3wsqf0Zb6dh5VX7p1j5D0QLCTIg7De9Y+2+vCgrBAiwJ6BJJ5efkmFAoUChQKFAoUChQLjDAXKjRQKtEuBLgP0wCRQ7xWUjlWPwOx3llwyfvSjH8Wkk02a36vuTTHKrb/++vld78pU5asjIMw7rZw3xwijqa45Aq1i3/fcc8/8znbXted9+ClSfPzRx4rl8JR80vjjAVKeeLH3dgj69esXXj8prt4Hr1ZfffUAkhkRALmje/m84e3/5JOP826A+2w0lf/r08nnn3+er6XU6LmRqjxHBgbwLa7/kEMOCa+g5J23i8Crrh/1teuoTUd1pZRSzDPPvCFmHp08j+CjV4wT1yXtia83XnRjCMkvqVCgUKBQoFCgUKBQoFCgUGDcp0CXAHqhH9///vdj//33j9133z3HotdJJwzGe9WPPPLI/M54744/9NBDA8BtLzyEFxrI5pHmzeeFrrfpXfYHHnhgfpe79ryz3W8PlQK0ffr0Ca+i3GyzzdpCelJK+SNV+ha+4t31v/rVr8IHsuR5uBagX2GFFfK97LbbbvnB1BlnnCm23Xa7/FpM4S/KGMsaa6yR89ybh2RTSvlNO67xtDsC876Iu/fee8fmm28eDBBv3ZFnhwFQZ7hsscUWuS0GifAadavkuva1yWPfu3fvHPdfXWcseA2nZwEWW2yxbJRU14b7WCoUChQKFAoUChQKFAoUChQKjFUU6BJAz2sMBAun2WqrrfJXUutUSCnlmPhf/PwXAXQLcfExJ++Br5ernwOnm2yySXjLzX333hu80PXrwmu8vQZABs6BemE9QC9PvC+27rzzznlnoA6QebkZA8A8I4BRAdTLc019r6YUV+8DTwwOMesMhF122SV8lVU5Y1lxxRVz3P1PfvKTeOSRh8PrLL2iUxuAtyPaKFeN04eoAHLt+WiUN+bw1nulpvZ9ZbYaL2MGUD///PPzl3B57xdZZJFg6GjbGHj2eedffvnlsBuw6qqryi6pUKBQoFCg2ylQOigUKBQoFCgUGDMo0CWAfnhvJaXUqSq8/sDwY48/Hvc0QD3wKhylClMRstKphrq5kA9YHXbY4fH3v/89jG/GGWfMBkxKnbvP9obnXfyMDcaAD2fx1P/6178O7Vd1GDpXXHFFoIWwJqFI1bVyLBQoFCgUKBQoFCgUKBQYAyhQhtDNFBgtgL6z9+ShWZ58r5N8/rnn8gOrPNRi5Zdbbrm2UJrOttdd5XjL7TbYpTC2bbfdNnvRR7Y/oUN2B7yTfu2114699torePDtTlRt2xFw7iNX6667rtOSCgUKBQoFCgUKBQoFCgUKBcYjCozRgN48CE85/vjjY4MNNghA1oeW/vznP4e4dYBXmdGdZpll5hAj7w02xircR6jQyI6LR168vXZ9AEucffM9ez7Bg7a8+MD/yPY5Vtcvgy8UKBQoFCgUKBQoFCgUGA8pMMYDejHovXr1agthAZR9HVbcOc/4mDBnX/vahHl8s8wySwDVHhLuinG5P+35gNT0008fdiya25U322yz5f6Vb75efhcKFAoUChQKfJUCJadQoFCgUGBcosAYD+jHJWKXeykUKBQoFCgUKBQoFCgUKBQYqygwVgy2APqxYprKIAsFCgUKBQoFCgUKBQoFCgUKBVpToAD61nQpuYUCo5YCpbdCgUKBQoFCgUKBQoFCgRGkwCgH9F456cuv9913X37Votc8vvD883HnnXdG9caW+r3Ic03yisbXXnst7rrrrrjtttvi9ttvz0lbzzzzTPhSqvbq9Z3L88rLhx56KC677LK48MIL48Ybb8z9uaZMR0mZV199NW655Za46KKL4tprr41Bgwa1fUSqo7rlWtdQwCs8L7jggnj5lZdzg+bk/fffj3vvvTcuv/zyuPLKK+OBBx7IXwZ2LRdq/HnrrbcCf1T84uhDZU888UQb/zWK5f9e/amdhx9+OL9+NGflR//bAAAQAElEQVSWP+M1BXyp+pFHHsk89O677wb51UwQfKgMufTmm2+2LNNcRzuvvPJKlntkm+9IkFH1cvj4jTfeyDyOZ/Ujr16m1blxXnfddXH//fe3ujzcefr0rYtHH300v2lsWA34fobX7LovH71zr811yGo0U4ZsrZdR51//+ldY8831yu8hFOiKv+aVTr377rvDfOF1efW2/R48eHDgP/OFR+XVy7Q6980U31C59dZbg272u7mcOX/66aezDq/6by7T6re1Qk5bG62uD2+edfXggw/Giy++OMyqH37wQb4f91RPxlKni/sd1MAIMMNjjz2W9ZLGlXnyySfj+uuvD+tUXkndTwHzge4w4wsvvDCUjKb3vXocLzYnc0ge4VWjNH9kPExB3sOj8lwbE9IoB/QWT//+/WPH3/8+KDSEvrQBsr3BhQCoiIJIiOxjVT7wdM0112RlAkz7ONMvf/nLUEfyrvZf/OIX8bvf/S4vFAqlaocAAvR23XXX2HTTTcMHpbSnvt/AvTFV5ZuPJlsZ/XgHvA9YaUNdH8h66aWXCvhrJloX/wbKvdnolL+cEh+8/0E23AjKah4dpc022yy2227bDIDwlWEA5z7YZb4333zzzDOO5g/f+HaA9pWVBg4cGPvtt19Y/HhQXknjHwU+//yzoOS9grZPnz7h9bk/+9nP4phjjgkAp6IIkLPbbn8I/OWjeo7edEW2VWWaj5T/X/7yl9AuuSLhx5NOOik7GZTnyDjzzDPj5z//eeZZvIq/BwwY0KEjgbwDFg466KAMPLRVpc8//zwrMscqb1hHiowS3HHHHcL4gL6O6jzxxOOx1157hrGSk+hx9NFHByWqX+0xDPbYY/e2Mu7/qKOOCsBe22Tu3/72t9hr772/8kFB10saeQrQeZdccknWiegv0W9XXnFFG/hkdPnGyRZbDJGbrptPDhRz1GoU5pjs7NevX55f6wYv4MfnG447dfAAp543w+F77VoLu+++e8hXpr303nvvxamnnppTMyDWt7bbq9sqX3vnnntuWOfWVqsyVZ72r7766rxu4Q1jl4wdpoE7lOEsqu7fGnD/PqhZGagwA3qcedZZWZdV7Zdj11PAfOCp/fffP8+b+aD/fVCUAec6eeQjpOaySubUOblrbsljsu8f//hHyNtiiy3y0fmll16anYNdP/rhb7EdQD/8DXW2BoVjYQPvCISglB/gZXFpR55F8Yc//CHOOeecWHDBBWO99daLySefPBsBBIY3v2y00UbhY0o+QDXllFPG+eefH8AbUFYBOgqX4Dj77LNjhhlmCIB8n332iVVXXTV4JrzykbVfldd/PZlsi5EHwbve//SnPzVA43bh7TtHHHFEeK1kXcHX65bzkacAAc2rTols+KMN8xw+3fDq/OnQQ7NXftlll4199903vLZz4YUXbvDA3+Pggw9uAzMWIl6abLLJMq/gGe/0n3322eOGG26I3XbbrVHn/Lwgzak5xl+UXXtKa+TvqrQwJlOA/CGj8Aa5ga8IbvLnsMMOi7MaihiYsO7x3nnnnR++FcGhQA4B9Oedd14ATc33CSQBBYc2+JeC9xpeCZildNQjiygJcgv4x7O9e/cOXmvyiuw0xua2/SZLTz/99Jhpppniu9/9btT/6U/fwHU9v71z92iNHHDAAXHVVVcHz6j12F75d955O6+9s88+J+aZZ54sJ2eccYY48cQTM80AHjRDn7POOjvmnXfeXMabvJQxbjrBW8ysUc4bwL69e21vHCW/YwrQwTfffHPgJbvWP/jBD7Js/O9/n8hylLzFg3Y/f99wvD3wwIOhzE9/+tPgZKMPGXmteIEOP+WUU0Kib7fccsuYeeaZ82+vXja/vJonnHBCSK4xEnwsEQ/QqWR2e3fwQGMXloNtlVVWyW92q5ejzxmzrdZdvZxzPAVYwxfAnXbrjh1lmhN9cP2AAYFmXik911xzhTTnnHMGnvWWOWvmuOOOC8a47+cwaKabbrpsDONv63+BBRaIb3/723HCn/+cnQbN/ZTfXUcB/Mh5IpEzZDT6//Wvf83OGbzmzYneFGi+yK355psvf7zz3//+d8aI1sLXvva1HBWyyy67ZmwBd6655pp5/hhn+AdPdd3IR6ylUQ7oU0qRUgrM3zgJ/5xLzhEFoNqnAbqFt2y00Yb5He9AvTKSCQDiTc6OO+4YgL9F1Ldv3wD2CJP//e9/QYFQvpQSoMa7xhInQAglyphyVIaQiRb/KBWKkJW9/fbbx49//OPsMdOnr7JSwPqsqhKWgwYNatuixFDVNUfXn3rqyXydYKCw5UvuXV8EjWTL3G91XKes5RG0lHIrgapce4kyRRdjcrzn3nsyvQgZfRPWtlYBYLSrt6NuxeDuV536defGp4xtdEeLRb62be3aoiRslXMf7t/2lTLtJQKSoUY5rLLKyvlbBJm+994b3vcPBPGc8pgwtlZfffUckmWbs6KP7xcAN3Z2dthhh2z0URx4gJCmaBiUxmAxL7/88vmrv2gvr6RhUGAcu2y9DRwwMICeddZZJ4NU6//www/Pipi8sEYGDhyYw+9WXnnlDI422WSTLKsWW2yxAETJsWbS4Df1rAO8ix8l4MqaE1aG78iVlFIceeSReecRuGdUpJQyqKp4u7n9f/7zn0Gm+QAd0FG/rt/tttsuhw7W81udGwuPPE/VLbfcEhNNNFFMMMEErYq25d10401xxRVXxtJLL91Gjz322DOWWWaZcD/kxsMPPRTGaI2Rv2jGM7vkkktm0EMuUJ4+0jfP3HMHRUwutXVSTkaaAoMHD45LL7k0GK10GtAOeB500MHx8iuvZCeaa+c2dkl4Me1+0rM8m2QsmYy/yfTmweBrwHqppZYK/K2OPjjgrmh4/+kdspkT7Xvf+16Qw0A/XjDndIPU3K7feBI/TDLJJNG7YeDiSflVsmO+0047te30VPmtjnQRgx3v6Y8zJ6XUqmhbHr2JP5dYYonsRGIIVMl3coyHA1BYL3yyTwPD8OTqwxrAx4wGjgFgUL92B9xXWyfj4QksgTZCW/CPnVHYAK0qcsAQrpkDx3qSR64qU5WvjnAdmbr44otnOQ4n7LrrrkGuw4lCr3v16pUxgbnkDIQLGLAppYAnfvKTn4Q+RAm8++7bGW/CkRX/6MtcOo7uNMoBfUc3DHiZVIubh4qwP/zwI2L2hjcVkK/XpVy8gx24531l4VvMJgKgHNQA1ZSuBcOKpphMHGFg4VF2PF+2WlZaaaVoxQz6I7wcMUw1BvV9qdY4gcrJJ59MkRg8+I046qgjY+ONNw5K3q4CgcWzpQCAe8IJf87XeRgsav3fd999eSuc96Lfvv2Cgu/bME4wE+bDlMCFPEJwtdVXC4KSULQYtD2sxMq86qqrgnAmaNG290q9A13QCGi2vU+oogsvCEEDOFhge+yxRxivcW/ys02y0K9og9kJMW0TZGgDUBBkTz31VL43oMAi4OGkPLSz9tprBaGnTHvjZ7iIB7Ygp59+hjxP6OR+zIljSimDDQYW0A74mN/6nNb5ZdJJJ80eFYYAZeb+GEnuFU8BJEDRHXfckfuL8m+8ogCeevyJJxr+hhQcAT7eRjY54lvGth07yhsvWpPkDx7jjQNOKSh81Uw4YJV3zvold8gvidcIqLCWgAbyi/JRlmKTbxfKOrUrpa/mto1FCBn+Vk9f9TLuy9gd6/mtzhnaDN055pgjADIOFYZOq7JVHnqQCeSWb3IYozX5ne98J8hA9AAUyUF0rGjGuwnwUIrkhPZ8Z4QcQmcGgLUpv6SRpwAg/uh/Hg2eZfIa/+E9zgxzxdvI+LqvoZd40O1mK2MNAOZ2o1yjq5tHQxeTqWS/9vGgungS36WUQuyxc2tgiimmyLxh3fBq05f6bG7Xb3oCf9sx69UAYfLqyRrB3/W89s45rjjr6GgGhXHU9UWrenibo4ocsBboCDRwz+7RvdHJdAjHHx2E34315JNOCrrODp5y7oGetBNcOZNa9Tk+5Jmz/Q/YP++W9+vXL4PtddddN2Ajetm8kA1CYeU1J1EZnLXmopleDDfyE37AV/jR/C2yyCJ5B9V8wnXkjfmSGLz9+/cPefAXWQaH2P3p3XvlMDZrSLvAPp7s3bt31hfN/Y/q32MMoMfkPFp77bVXAJhrrLFGtoJZs50lig86Lbroojl8wuS+9OKL2ZvFY2Yym9tRnjUGaE4//fTNl/PvtddeO2zHiNvjpRAPauubFw3Atd0yxxxzhi1zHo5+/fbNW4xA+fzzzx+21m3r8cQf3vDweXZg8smnyFvNGIPXQrsWNRoQlJQ2C5XipuwwtTKOdhe2/M2WoT07FLbQCZc82A7+UIi8LUJXMCt6/GyTn2VvHkPItrq+gG3WL28HAaqOBUNQ2Wai3KdojJ/H0DgJZgCEAKcIgBACnXKwpWrnBNBglAwYMCB4HC0EhsR8882ft+N5AvXZaviEv0UI8Diika16HncLSfylsV588cX5XgAPi5CHCKBo1WY9D/AhgC1849Q+A1C6seFxZNTUy5fzcZ8CeAB4oUgGDx7cZtT5/dDDDwWwK59hjxoAarUGGdjAOHlABrleT2QOnrV+AAHXABFywJHisabwnTEwpHn5GKkUmr7xq3rNSb///e9/c7gL4OD6c88/l7eNrVHy1Tita7KEJ9X6Vq45GZt1dcYZZwTvo7XXXKb594QTTZSVGuBD3rjuXowLPSjlib7+ddn5gcCqDMNcGfcPACmgP158ZRgC2pFf0shTAIDBW3jMXFUtvvb6a/HEf58I8tk1c0Um1ss4B/bNpzJV3erIMGDQkb/mUpgJryfnmpAdYQ+89AAwHScEFm97/oTet6aMrWqvOuJbjjoy3RrRj/X46COPZv7Gy3Si8dJDADuex1NVG/Ujuc/jSp8D19qqX28+d52RTo9x9NC9HGDirGEA/FuVMX5hS3BFdW+A+0QTTpgdT9oGKjmOAMWnnnxS1nib3nv/vXjo3w8FBwLjHV0ZWmQi3MOohw9gAXT1oHVzIiPIkWYikiPk+QcfftCQ45/ly3iEEYGnyCRt5wuNP9oQJw/owyh2YxrZYd4d8Z1dKjIZFuOlN4f41vXRncYIQE/AWAwUyNlnn53DKihJgmV4CTTZZJNlj7DF9+Zbb+XQHouHABnetpTnjTBpjsAz4GvbmlUPoFOOGAMDAO68GbwMFDZBttpqq2WjggIl3BZbdLGGF/+o2KexHQfsA9MEDy/0x598nBc8bwVhcNRRR+WHdRgQBCIPuHaNB6NjPoYG5jTWYSV0xuCMFG3/8dA/5hAiwpmF6X4IJ4KX8pfvYWQCjFJnbLGOq3Cj0047Ld+buSIUAQ4GEk8iTzmaGzclQBAbnwVCkNreQktzY8ECSK43J14/7YgJNn7XeYmMgQcP3RkJ6AEoGZ/4TotW2WElAIt3xqJUx+Jn2PAs/uc/j+SwrWG1Ua6PWxSwRnhwHK1Zaxd/UCL/vOafJgsVnQAAEABJREFUmSfwCl4GfO1OKQMcO950003Z+2N9DosyytiNFD8shpOi4P15443Xo3///jFgwIC8Q2lnUew5eQEQkZfNbQPzAD9jtAL9l116WXYekFnkExAGpPst2bVrbsdv/dmWtu7It1b9KVdPQJJ1w/infNEDuLrhxhvyljU5Md988wVQh2bknjLAF5qhqfFVbTJKePF599Wt8stx5ChA3uFdTilecWAUT11x+RVB3poHAMVurTIcJ3gLQKcP7n/g/uw0wxcdjcR6oWeEPJDd+Fvbb7zxRtCbnD3mn251pNusgzoPVO2r53k4642DjZxmPB962KGZv/v27RucYjADLy/epiM4aqo26kdecw45eknb9Wutzt2rMfPgop8deDoOj3qOzpqi5wBEtBKjTaehM9ru0/A8n//3vw/1ECynGoP1xZde6vBB91bjGZfyzKXEqUq+7bPPPgEbwECMOCAfJoJPhMm0ShwfZE8zXWAF4brXXXttDjXEZ2STNslevIaPqnrmD4+TURyY8s09nuVUUI9TVLvGZP3su+++IYysMzJSe92ZxghAX90g8Gcbrk+fPvl1bhbK8ApyE2QCWFKTTz55bpoFVp+0nNnJPwSb8BEgVBwosAq8ArwYDIAkELMB8eab+WFbWzSa50m2FcSaJxh57Hr37h089xiY0lyjsRNBaRGk1b1a6LagMY17YH1qj3LUJ4PBcwHuE9jWtuvDShjO/VC8QKttULsX35jkG8GjYhyuE5iYF81sgTsOenpQEMBCZgAQY7XY0MFYgX31hOrwehBw6K4dAlPfxiccgWAHltyfOhaW5Ho9qUNIGxNBimau84AQlIwPz1kwjBhSwIzYTh56i5awVL6jZHwEsfFU7aMLuj/S8P64h47ql2tjOQVaDJ+Stx0unA5At+skRA3YJlckvMJTSOgDpDxxylHyQAVAjadaNN+WZV1d0FDy1g6epsSAcevlgw8+zHHrYoYpDLIQiBAHT6mo29bQFyeAhHVZrWPZwh6sDQmYNia7WH5Lc8wxh2IdJuuwwwJfXEQPoQaMbHIcPez4vfLyK4Ee5BXZyPtmXXMc8HAyxjkP0B0dvmgu3z/5QMlWHrLqWjmOOAWAYrvDdj3touJh4YeA0gzTz5AbNg8cJosv/u3guDFX1gBZa4fWdSA9F27njx1m7XNAKU930nMTTNAj7wKstOKKeYcWgOMMIucZnfinuUn6gUdfGUDK+uvRo0cs9Z2lQviWREdYm9Yu3maQuNfmtkbkt77oHPqPfqP37Srw1lpPF110YX5Ykj4xVk4zuto9M1TwPwP96aefbuueM8v45NFBbRfGwxO6Gq6CtcgoTjzyjh6GC9HHHEwwwQTZ6Vk/Ku9aK7KhseefXnzxpfjlL38VeJixB4Djoaqdqi4jlOG4YoM34TD55B95a25hNnOKX+GwX/7yl8EZKxaffFN+dKYeo7Pzqm8EkwBfXm2eaIuEEgPQELIqO6wjxUB4sPZYWYArwAvsNdc1ASZQbBSw3XzdJAqBMfmECNDLarQ1CLj6zZrjXeIl117Pnj3bmsEsxiENAYafx3TTTpu3patCFjpBpP+PPvwoZ1eAEsNp0zVjMc7TTz89gGW7Be4PAGiPmXNjtT8WjTHxKlTZFsPEX584eKr1J786On/xxRezV+Huu+4OXgfJlhQaM1jUp3AJOguQguZl4XWv2jG3VXKv2pVc169z1x3rSR7vBiFtgSuPHmIXCXd5vDu26GzX8Wby0lMaQnA++OCDenMtz1nePCnmiLJQSH/GxTPYmTbUKWncooA1wiNOePP84EUAXziZa/hDAsJ333237HWmdHj9KHrywjpujyrkAaC0+RZb5Ddm2Z1cddVVs2zA1xQ9Dznjn0cQf+rf+sXf5EFz2zyo8ihB69K5HUIeS/fhbTp4G4ADMuRTXMp1RUIPnjIADXBnXOhfWAUvGXq4N2F7+qcw7Ua4bzLfPdflp3vwm+xmJJmDrhjn+N4GfQGckuWeEUFnPMOw8gyaecQnjEG6zjNh6gAz5lIZ5emAVrSkZyQ8IKyEzqQXADMOqEkm+WYOS11n3XXzW8u0BczhFfJeam4Xv/O2G+skk0ySLztnMDJ48bK1goeEu+JBHno7TLnwSP5x//PMM08wfIR74mP6gqef4fDss88FPUIn42sGBp43HmHA6G3d0qfVUKr1ADuQB1X++Hq01vFCdf/mmewjIzgrhHJxQDYn9BXL/uyzz1ZV2474mLNFRACshM4rrrRijnxAfwm/q8AQEw2BrxgW+pdP5pL5joxgz0wZK2zJOaE8py4eVX50pjEG0ANrvAaIBigC9zxNvLCAWjOot8DqhCNAAD1byEAjBUipmmzgTwIG63UAfaEzFAxh06wwTBCPG6Gh7fp1QHLdH6wb2gRoMYYx8SRV5YzJ2Bkl+k2pRzz/wvM5JMhvCQiwyDFuJSBTjxTo4Tp6YB6MJNZcXJlkG5Mgs9XooWFlh5WMS7s9Gu3Xy34en9d/DnWOhgSUUBpbTfq+6KKLAgAhMAlR20620Hl0eBTFC5508kn5wdNPP/l0qPZSGurnMH+gC2DAqDF+iw54B0oYUmhcNUIYAPcEqbmt80xKQ3esLUDBcwDq4bmK/vpzjTAgtKv2y3H8oADeYMzxugg18/AcrzjQQClTAMAKBW4naM0118qvUB04cGAAqpwKlAFl34pijEg7frvvvnt8d6mlcggeMGOtp5SCV4k8Uc5YtJFSyq/pw6PABFkjv56ABzxPnlgn9WvOU0rZeEhp6LXgWlck40WP3o1dSLt46MHgAcaNGyCinHlggXjOEN4tNFPXWiPnqrHYqQDurEMppe4Zd9Xf+HLEI/QdzzA5breXA8Sc2HW1cwrAAFGPPfZ45ml6jIxnAKirDH5rphne47nkcKI/XTd3dAjgw+is6uEL1yWOLXyvrCSvnqwNehAgs77q16rzlIbwd/W7K47V+rOeLrvs0jj66KOCs6pqm/6hw40f/6KLPDqkKkNe0GNkgjJVvvuAF9ADbar88fVInr777jttt08Hv/rqK1nu4R87pIw1hmc9yaP38Udb5S9OyBA8LYQST+LjQw4+JId1mydGK9mkuHkVkSCCAKZKaYi8SWmITDZ3HHx4UHnJnJLV5r+VTFZmVKYeo7KzYfWFwMogjKfvbWdgeqEehEi1uBwRFchznZDwFhgA18MxrGMTBdjzclHOYvkoG4qDIHnsscfyA6smkcWtfEpDJtAYJJPFshZWYjtSWfUlYTDXX3d99myz/CTlKSiC8N133w1GhK05AJSXz3gGDrwhf8HRwzrGDyQzCCiyySabLD779DNdtyXCgEXqHglgHgCAlTVqBwOoJaAJEGMS51cJ0rZGRuLEtql7QS8LhsfDbzsFQI4Fgy7G+f/s3Qnc51P1B/BzZ8pamv5FthjZ2wwtlrahUggjiShGtsrSiEpSZqjIUtNOUaNsFRlCiMzYyS4h21gipZClyPL/ve/jju/85vcssz3PM+bOa+7z/f7u927fc88953POvd97WcmjRo3KXpcrLr8ivB9jgdEzM03AB6bc9RdFgT8Ie1P74vSp9fLqIQyAeEqHIGBoGIClXgNROgJUWdbvmj5mnPAi6Wf1Sa9/pSOcm2V4VsO8QQFjzXrOcePGZj6m0CkGxqrZQ+PVuOX5BorwlLFgWRwvDwWCB/Hs3ffcndf3ArPGpjXmpu0B3HEHHBCcDviXLJNmxRVWyB/in3vu74NH03gjw/DqkJaMsmSuKKFmb3CAAAZTpkzJ6/w9K3IS7wNMPPLGsd+CcSHdzARlk3HkIxlkzJiKNstqLHpXzwF3tEATaQA+adCPbDAWyZIRI1YLH8KWtmgbRwowJJT4ep01CugrxpalBzzw+Bb/4S+y3EwrPeMDRA6tkgZv0leMWkYbPtLH8uAB93jCd110Np1Bz+EFfGws0JN0CrlKVjPYpLGdKd3pudD+hvidgSwt3QcDSEMP4GOBDNcu7fDbO3lX6WY0KN94NENv7CmHrv3Sl/aNCRMm5E0wtIXOZfCbYaCX1S+vODr7P088ETffdFPeSln76JTSFt/loJd8AGGJnxevQ4YOiWuvuzY4DIu8c//kk0/lvf7JNrMudDZ52wziOIDhK33f5EdljR8/Ph8WSZboRzIJ75FJsF+h9z333pO/CdSXZGWJd9VHlgvLy2kMb8EJjARlNh2C0g9U6HdAj9mFp595JuK5Ls8wgugIA74QgtXD+0y4IBrvNKDmuUFsbbrpDmvQgX/rNXUSTxePug4hBExT8+YCftYBuueVBz4tXQHmCC3MoOz2YCp4xOoj8jIXYJUXWl5rRSdPmpwP5MAUQKapSV49zLXvl74U248eHcA9o8J77LLLzvm3MnmlTEVaZ/fud70rNtxgg6CMn/rfU/Hcsy0Y/DxtDHTvyVNuOpsQtiZx7733CuBB+3lT3FsrZmqJ0mx/D78pT7Rv0tlvXvRnnm31h0St4LngmeklDG4tpPYaVN7P8h/vTNEyhgh7StpAsyuOZTfqo7T1m/JaRecZDVdB+ZSJ4F5ceyD8KXbCTxqeGlOclg+wpq2J0y+mQs3w4AsDFc2Bf3mU78Mu3lZLIrwTPuAl1XY0ZTioW3qCXFA3b6j4GuYdCqSUguJlhJ9yysR8ujSeHt0az3ja+CXgAQzAB2+Z5TM+yRaU4k0yZils4MZSMGPUWPAtDiADGCkXT5riNaXMiHj5IovkrW3/85//5u1pfRNCRlnmJ501wmSFeprBeDQzCVwZM56ZPcP3ArBt7TrZY8yQjWaopOspGBPGEBndTEdBkjlm77wXL5pw6qkT81aXvg3YZZdd8o42ruhBVi222KIxceLEvIUuecLbRvHus8+Xsjeu1FFkBzrrixJfr7NGAXKR3COzzaCgPxloPThnGD3GOcVwxb+WU5Y0eIe+w08LLDB/NnbxPt7SX/iPbgSELbPBA/Q4o4Cuxuv41D3QazkEo3jMnnvG/ffdF9t+4hP5I/D2N6QH8T0gZewUnrQEDi9rz6mnnpq/vVOvOJiA/m0vq/033cRgN7bLM5hEefSL2XD02GbrbcI3JwwWy+q02zhHR9gCfzNa6ReGvzF7wIEHxue/8IW8K93Ht9kmz1qXOgB+hg0DRvklfl680utwy9ix4/J2lXiKE9W3CGReSqlPZFEGfsOPdDhet5qCAbvbbrvm2SY4hoyUjlOlFHzvPffm5cVmX+HPEu+qb8l9chD+Irfl51Q0ZnxHOGTIEEkHNPR7C3Qca2vlFVfMHz2l1DWVTHi0gyfCX8cArTzvvPTy6gQdVaxwhNRp9le35MO9OJTVERQOwaKTeA1Y2gQDJWNXHYMwpc4M40OyH3z/B0FIMBAoYR9NaCvhRthR7tqqfp3MSz6xJVwefeyxzJzq8XzMmD3zUpUnn/xvPp2Uxw8wPeTQQ2PFlVYKQmrFFVbM3jkDXftTSkGQ8cbz1PNiTMEpoWoAABAASURBVJw4sUW7+QN4J8i0C10ffvjhbGE2BZMyhJS66Ix2w4a9UlQOADnr0odOOaL1R1u9NyFDQQPJBLH2Wj6EdgacaS40/eT22wcBao0j+rNiCbx99tknGyn6icGk7kUXXaxVQ9d/oIRiMb2lP7tip/1rr2600G8Gk6dmCSgifapc3lRePiAGUOf9HDFiRF62ZDrTFNqwYcMCfbQFfdRpYAM0ppq1RdmE+5SWh5Mw2GCDD4Z+Fl/DvEUBQN2YYxj66NUSEmOFt4cX2XgDMniHrCnGfxQ/XrUUjTFIBqWUYuiQoXkcGKe8Oiml7HXidACCKCEBMACM5WOgql8d6gbEgYbDDj98GlAQjX8MbzMHPKL43CPlAQ6COgAVVwaydJ5L111IKeUPWo0hRu/QoUOnJk0p5fcSkVLKs5Vk4BZbfDTISGOLTDNLaRzLi4Z77bV3doRYesO4SSnlPajRTFmCdloKQr4AkGYAxdcw6xRIKYX+ICfpUx5HM9ziLHEVl1LKh6hxeuh3TjVOHMCF3BUXkcI//Sq4x6+ALMOWntC/vNhFLtMnxhbjd+eduxxcDFXG4oFf+1rs1IozTpTVDOTzuuuu29J782Xe4vkmq3nP8TL+Vt+TTz4ZZstKXNEZzbKa9ymloO/oQOOx+cw7GYvqTinFm1dbLSa0vPPwCF1ovONPTiyOPu3G32PHjg3GBE8xfanM/b/61dhk001DmX5rI0yz5BJLxKqrrBIpddHSs3kx6P83v+nNwdgzg4k2DEMYBz9G9I0qKXXJpEJnGAb+IjvvuuvuvCU6h7BlOrCTvm2WDPcw2kr+8szvDVpOV4cKMlrNHsCRnIjjxo3LDqCSdiCv/Q7oASSWrU4DzAwCOyJYDjNixIjpaAGcEzimbXU2BcsLThkAjoLBRSiwoHyo0F4I0Ae8+QCW4CKYeOyL8GpP3/4b+DNoTRtSMup35an2PiW9wW1d7KWXXBLqUB9lBkxK4115JFiLkyZNCm0AEChLzyktDMMbzhARJ6SUglIzJcorff75f8hfVhMaGE0ajLheS+B511Kf+BLUDSRgQjMaJR6TagvvYEopCxY01jZ1Sqd9ZkjQztS49Dwj3tfzZYcPD+Bj8uRJ+eRMfeXjKUIbnQAgdaqbESCPoJ3K5cHsbtAS/jyJyiEg5RMITn2qTWgyefLkvDyBxay90gg+XAaIKBW8IgBoBiQ+NHilKwHoN62MF9dcc60SXa/zIAXwhqVl+BbP8ygaG2XMIQlgY7ziP88FigKw95xCsRTQmHBoD28cbyVvfZMn8aXgQ0VjmKJRDr4nbwRLVTxTbneB44G327If4GbMmDFBVpagznLvCnh1V1aJZ4gDMoxoMqrEk83oAvQBReKNY0Cx0OP888/Psw3NfOQpJ4F3007ynfIuNFMO5wDaG79mXVNKomuYTRQAVHk+0V8f4S8faTdlp6roBfKzpKGf9LtnAj0F2OIBji1xgDGjllzG9/rZTHR5Lo0Zl7Et4Et34yHjhm5Mqft+ZgwwAuS59rrr8vcgDAZ8XEKTv9XfbKt624NxZkzzqHOulef0JV0FWFr6W+KNYXUWmcDBRj9JX9IAfMYK3eQ5Gnxs662zMSINQ8Qz+GDb7baLVVZdVfS8HZ6LWHzxxQMf6beLLrowL4nmLZ8RwjT5UXny4jurBy684ILA73jNzEq7ExH/6ReYSL5OgVEJH+Dpyy+7LGyc0D5mOuXrr7h+B/RezCAivFPqGrwUZPO3NCWklPJAQHxCqKT1uwR5DaiUusoreZtXeSlXU+m8wsCksppperqXlveBMlKGslKavj71vPL//i9PzVG+fjfLTSnFy1++SAxvgWBtQIvmc+8hpDR92eIx5+tet3wAtM2yTUM+8+yz2fPVNDKaZXsHNGvmc9+XOO00WCh3AltZzbL1wdJLvzafPsgrrlxB2dI270u+lFL+OMV7pTT9+0qHzrw77g0kXnj3QimTYfi6170uGBja6VkJ0mibdjSDOj0r6cqVsgCsLKtC6xJfr/MmBfDO0ksvHca9cZXS9HyKrygeYB3vpzRtGjypnJRSNpjdy9MpeJZSysROKQX+VzZZopz8oIc/I0eODF7Uc887L3gt5elUT4nzvIfi8qOUXhinOeL5Pyl1yWZjKaWuNnukbGMSPXxwntILzzwXvKc0lCFZltILaRgiHD5mMywFYdTLU8PspUBKdNHLs67C4/qkvYaUXkiDD9vTpNSZB8h8PMvRpP868VlJwyjuNG7a27LAAgtkzzc5z7FkOZD24LdOwbOUXuCr9vLKb3pAWu0pca5+K9fV7xK0A73ocPcpTV+HPIyWIjfUUfLb1cYsO2OD51jd5dk8eW2B+efiubxZCLoB4q9+9aJTZ/9mhCYpdeZH/Ld4azYEfsGXzf4o5Uujvzs9K2lSekEmv3rRmWtjKWtOXIfMiUJrmf1PAUKRx5knvP9rn3M1ppTyR4OjRo0KXhSGy5yqjYKwHtrSheYynDlVXy23UmB2UwDY2WqrreJf//xnPkhldpffH+VZhsQDZjrb+tSUpgdM/dGOHuqojwaIApxxdtrhSQWMB6gZM12tJWiWj5qBsjKBkTTThb1IMgLxCy+0cHZevEheacBeowL6ASP97K2Yh4PHgIU5e0se+NJ4QUy1mrbttKRqdrWQhW69nW8uqnd+dlG1ltOfFOBd4qG3BM61P+ueXXXx2PvobOz+++fZ2dlVbi1n7qcA/WbpKBn96le/eq58oZVXXiksS7NUJ6VqrHJG+tbA93d0/VzZqT02uv8eVkDff7SuNc0CBSzzsRbfMqVZKKbHrJYOWCPJa5JSFbQ9Eqs+HLQUoBR9A2IZ2qBtZA8N45zwvZSliz0kq4/mUQrQAeQ0PpnbSJBSisUXXyLPOjNO5rb2z4n28tBbBqNfU6p6d1ZoXAH9rFCv5q0UGAQUqE2oFKgUqBSoFKgUqBSYtylQAf283f/17SsFKgUqBSoF5h0K1DetFKgUeJFSoAL6F2nH1teqFKgUqBSoFKgUqBSoFKgUmDcoMPsBfS90c4CAQx8cbmI/1l6Sz9RjBweVAydmtQ47Lmivg05mqjE1U6VApUClwBygwAMP/C3IuXYZZycNh1Q5cM3hUXZv6lR9SWN7y+7SdMpX4yoF5jQFHAhlRzM82l4X/e7gPwcA0s8wRac0MEZPadrz1N8vPgo4V6av+I3cdCAfuYmvOmG+ZhqytxPvDSQV+x3QOyHN6YrHHntsPPHEE3Pk3Z1+eOSRR8bhhx0eDlmZlUocfORAFx08K+XUvJUClQLTU6DGzBwFbr311th///3j5z//+TQyDrh3jsJhhx0WDtqzj7vDT26//fagjNQGEEnjsLxdd901HD5l1w3gx/MaKgUGkgJA0rnn/j722WefcPhSsy2Avj3oHeD46U9/OqexQwrgVtIxTqVxsKGD0+yY9Otf/zo6GQclT72++Cigv8ePH593FHKmRU9v6OwLB07hGXyFZ2BUp8qWfOSmA9hsD062OjTUgXsMx5JmoK/9DuiBbaenORnWwJ0TBHD40CWXdp3WqqNmpQ4CRcAcs1JOzVspUClQKTA7KHDvvfcGMH7ssccFYN6Uo4899ljY3tWJs3ZrcjCV05PFkb3q51niVOGscLKr7Vqd1uzkzqYCk7aGSoH+pADQRN9+/evfiNNPPz146Rv1xy233BLA/NVXXx0rr7xy8KYCYc4PAfal/dOf/hR4+bLLLotVV101p5HnV7/6lcc1zAMUAOA5Kci9q666KmDCnl77uuuui89//vMB1NsdbMqUKQHU20qz8NVtt90Wu+++e05jq02zn3hPmll1HPfUthl51u+APqWUT0tMKXXbTlMdQvEolYQGO+UlXpAGYBfcl3Tlak/mlFLIU9LIV56Xq7ye6zh1lPhy5fVy76os15LHb2UK7XHy9CWUvOpWtnYIfstf4rRRHeKaofm8tKf53L2ylKkMV3nEC+6VW9rhuSDe8xoqBSoFBgcFeIh22GGHOOGEE/IMJzDebNkpv/lNVjjbbrttHH744cFDtdlmm8UZZ5wRkydPzrLwjBZQOv/888OZC8C+GUhpTjnllDjzzDObxdX7SoF+owDPOiNzp512iiuuuCKK/o7n/zFW8TOj86tf/Wrmb+ctDB8+PI477riwtEIaAOvhhx6Kr33tazkN45Vxy2gFyp4vrl4GCQUK7oBRYA7YQ3DfbKLfPQVplcWgGzNmTBx00EF59lIez7oLVl8c9ZOfxAMPPJB5hjwUnGL9ox/9KG644YZgIHyrJU85U4B4fHjEEUeE037NEDE01d1dHf0V3++AvrcXswznZz/7WVgyY51cSS/e9LJOQlSd9vWvfz0cMjF6+9HxzW9+MxMeMJWHMPjf0/8LU2+f+9znYvTo0bmzWPYljesfr/xjHHDAuHyk9I477hgEBOsMcymnhJRSXHDBBXma++yzzwp1b7fddvGlL30pTwtec801ceCBB8YnPvGJUJ+T7JRf8vd0tW7rmGOOyUIJc5gm33mXnYNg4qGgjMUpmwL2/oVJWYm8caaA0IKgu+SSS4JwVKf3+POf/xzf+973sgLfcsst49Of+XTwVmBSTMg65fG7tJWPRbv99tvn6XppildPWTVUClQKDBwFKDnLbIz/TTbZJJZaaqkQV1pEJpzeAu6vfOUrY+ONN46FF1443DvAxp7X5557bjDoL7v88lhkkUWy7FxwwQXjNa95TXzkIx/JhzideuqpQWaUMuu1UqC/KGDW/uCDD47FF188Ntpoo3AuCP1U6ocHTj755HBGgUPT7F/u5NhRo0YFHQas01f09Fprrx3vete7slEAdG244YbhOW9tKa9eBwcFLFmB9+C+37QcEhwN8Ay8B99opRUSEydODPioUyDbYESBs4NB6DDKFVZYYepSQ+V0Cr4hurLlxV9rrbXiQx/6UOa7N7/5zbHVVltFfnbllWGp+O/OOiufH7DBBhtkWYn3YKU77rgjY88mr3aqpz/ihvRHJTNaBwId/q3D4/obrp+aFYBnFbmaMgbsf/nLX+YB+8TjT8RPf/rTDEJNQcs0/3zzh3WjY8eODeWxwlhb1uVZf0ppmV7ZcYcd4+STfxOUIWHAMtt3331DmvYOAv4B/gLieQMwDwCv3IsuuigrWAAc4Kd4taW3wOPAO2ZtFq8CEH/9dddn48G0DyHnqGgB8PauGNw7eYYWGI7SZsCYOuKBY1CgAYvSu1tnKM3ll12eDRHC0TveetutceSPj2wB/c8Eha7sy1tKXznWHgIBvb1DfV4pMK9RoL/fN6UUgAnjfMeW8+FlL3tZllulHaZ9eSlf8YpXhINaxKeUwqFsADzlRGZRoK9+9atzvDSCpTdkAwVKToiroVKgPykwbNiwrMN98/He9743z+Q366dP8ThDFo97ZoZq+PDhOa3lN7ABfSrNfPPNJ0kGX0svvXS+l4auzz/qn0FBAfIGWOds5xkrAAAQAElEQVSMNJsClOvHr371KzFu3Lg880JmwV7wDudte+AQVQ4jz6FjviGyzKrIwe5eFP6B+8jF5ZZbLjg4pE0pBQ89nAhbkaucpPiqWaY0KaXAm/CWvAMZBh2gR1CW0n//85+46MKLskcJUVlcwCnLHeC0Pu79739/GPzA6h577JEHNcIj6LPPPZstsw984AM5DWYYOXJk/PGPfwxeet5p4JkCA6SV8ZPWtMsnP/nJOOecc/L6PctXePqVJ+iwJ/7zRCy55FLZG8+D/p73vCeXx5uAGSlbbTQFU4wLeXsKmMoaL23xQYZpR8xIWJ199tnBA6H9pgwJMt5/QssgYK2us846ed2sNWOm2Q0I1i4mZQBdf/31eQZCfuXw8mF8axS167lnn8vT996BIYIOjBp056VHb+lqqBSoFBg4CpAHPFdkDjBPbjRbY5xSOsaxtOUZYCMOGOIEIB9475uyzXMnbzLeyY2St14rBfqLAta70+O8qk3+VT9eN5Mtng5MqWvJbkopg7AFFlggPMffKaXw7UiTv/E7nQf0NWe1lN1PoVbTDQX0bZE7Tayz8cabtJytJ2c8xgGx9957xwEHHJBBPqBfgjhefXzBKcGD/sEPfnAah0U3VWeMSN7BepwezXSFh8hVs0MMQWA+pS7ek1Z98kkDL4kbyDDoAH1KKd7whjfEG9/05uAdZh2x1iwjYWUD+xQUQk6aNCkvJfnLX/6Sp4+PPfbYeOc735npqYNMJY8ePTp8wLDKKqvERz/60exB/9sDD8Stt92WP7ABhk1JY5jFFlssPvWpXUI9ltBQfE2hkFKKBeZfIBgJpmSUb+pP3o1aU4Sm9kwXvulNb8rTNgRMbkwf/yyxxBIZeC+55JLxjne8o2U4LBkE1RZbbBGsx7e85S2xzDLLZCOHccGLzhBgJWI4S2vQRjk333xzEG6s1QkTJoTpJ+9y5513ZmsSc7JMNc2AIuy23nrrGNkyeryXK2uUkYGW0tVQKVApMHAUSKkLqBirWmHcupZgTIszzlN6QemklPJMpufkhjSAUUrTpiE7PJMu6r9KgX6mAJ7k0MODQnv14vA24zOlLt4tceIBKrxrfCirmd9zvz2Xx30Ng4QCra7ULzAVh+qiiy4avnmwpFlfwTX6z6wNoN4e4DG4EABPKQVsiAf6+nbqVg++auZRp+A53pJmvpe+tJkky1V1eTbNgwH6MWSA6u2xWqD1HS2vs6UygDXA7rrpppuG6TWA33ZrCMmbDKx+7GMfC+uvgHCF8zqz2ABsvwVTzwj/1JNPxt/uv19UrLjCCrlT8o/Wn5e+dL7MTMA4j5YObUVP/U9QALyuIgkg1j8rraTVrnIvTV+C9N47pRZ3tzJgSgy2wIILRKmrFZ1nIVJKeY08QA7QH3/88bHXXnvltft77rlnAO3aA+Tz5Jlm5Nlj0PhK23o1hpLyhOfiuUwDAN5vQd3eAzOjmbgaKgUqBQYvBayXp9SAduO2tNRvRjnnANlFXvGINdNQWGb9jHsyreSt10qBwUCBlFIAevj0idbsfWlTSik76XjdzTDhb3xNLzb1lt/i8T4eL/nrdfBQgCNT/5UWwS76HI6BBeG8rbbaKmC99mBFAcdvydvXa0op4MT55psvmnwlP54iO/EMZy889Njjj3s0NXgOJ5KZMNzUBwN0MygBPeK+q+VpR0TbUU2ePDmT593vfndeD4ew1pICptaPv+997wtTae4tgzFwo4WLhw4Zmj3lOXPrT45vXREes7Ru8960KSW3ORAYOmjo0KEhNIWCBCmlbAEqw+9mmX7PSliwBd5T6mpLqbcJ5pVd4tUvUOA+lrUnqjXve7WAvXX3lu7w6v/2t78Na+gxu9kIwN5ynpVWWmma9bepRTDvqw4hpeRSQ6VApcBcQgGygCEPrAMwpdmW4YijuMg9wAd4F1fSmHaWTn7pSny9VgoMFgq85jWL5ab888EH825NftC/ls/id847AJDO/Pejj07Vb9LAB64wRVPPKaOGwUEBTgcAubTG78cffyzIKw5O8fBPe9CvcJt4aWYkpNQ168nZga+UVfJz6qaUYtiwYVH4xqoHQL+kwXucyJzFg4GvhpSG9ec1pTQVmHdX79ve/vYYMWJE3m7NOnHr6/xGcOvngXcfSrDYvvGNb+Q9QzGAdes6NqWU10d1V75lOAyHq6+5Jv56771Tk/kYVrDshvJT39SHPdyos7vH2kVZYrru0nQb/9z0T9Sl7cWj/prXvCbvCmDpkOknH8+apsJ4xRj6whc+n4E9emE+Cr393ZQ7fW01plKgUmBuoEBKKctMxjs5SN6QPWY3KZ7VVlstOzgY+r41Kjt+UKJkKoBvWR/lNje8b23jvEWBV77y/8KyDLrNrLO3B6ZsRmHZK75m1FqCes3VVwfPrjRwgm/w6HNLb1Oqzip0mYEwx5OmISn06w3Pb4QCi1x77bUtR+0jeTcvfev7QCsyfGPYDOJ8UMuY60tD4R54jBGoHjOb8J4lzGYClAEfnXXWWdmYsJuNtfOuN910Uz77QxrBBijy++5jngX0iEiZ2CLRri1C+WrZllMUDKvMWimg1DaSFI1Bm1LKhwQ4nMo0i11m5LFtEeU1fPjw7FnXaZaSIHp7UP/w4cuGtenWmu/3la/kj2B9AMrDzcL3YQXhQClOzd8BXHumPNcS/C5Bm0477bTwQQeGKWk6XeVpxvvd6R3ESzdq1KjMcL7oNjNhhxuM7cNXH2nwti244IJ5FuKSSy4Nit3OQAwgAvHx1vQROkXrvUqZyi1BnFB+12ulQKXA4KCAcVlCs0W2pbWkwPa2liCSaT74p4wsWeTpWn/99fO2leSAGVDfHvmYn9K0e05KFfA0aVrvB4YC+LtZ87CWp9TJr4Ae7PC73/0ub3hhFnrzzTcPPA43cGzZxtI20tLgf+DMMg04ollmvR8cFIC5bCu6335fCZt9HHXUUXkfeX263nrr5WXH8B9PeacAVHcC1O085G3tImjzDzzEC88x6htIYH7s2LEBr5GfZCcMamWIOn14C4va/EQa+W2taYWIbxVTGni5OcQL9mfQcSwp678Rw+b8guUzwqRJk6ZOp1FAALqTu3zsSlFZZmLpiH3ZdSAAa7mJLSjtwz569OiQZtFXLxr/17Lo3Zf380EDz/yCCy3UmiGYP58M5hALQNsyla/st18A8MrUSfISIqby1LXgQgvmD2x5x0uZADOPd9OrJQ6DiQOYfQNAcfL8l3zNq7JZgDwQKXUxRanbe7gv6ZvtQRPbbGJ0W3oyGmw7yUvvGwNT54TY6quvHtbZW19/2GGH5w9s7RDkXXnqKHkMq72lnpRSnmpSdrP+8ny2XmthlQKVAjNEAbKQzGC0N8cnDySnBA+U3azGjRuXlwj6dma55ZbLspGnfrfddgveTVvw2gqOzCL3yNsZakhNXCkwmymQUso719C7+LIUj8+dr0DHc+jR+5xX8IA4YN64sJe437CEZahwBl3JGOClL+XV6+ChACwCm5lJJJN4430Yy9E7K0YYGYmPYKzytrCn3Q7tFsipCf84WK+JBW2D6RwDmEoZ+ArvkZvOS8B7dhV861vfmrdahZNK+QN5HdLflZva4BmylzqvcnsAyhG4tAsgtt5bMKDFI7CvoeVlDCjP/diWdWXqA5jWEQd/8+DswZZHeOOb3hSmajYbNcrP8BGGLSu1hcWmg5RjWYoPISQC9PdrAX07x2w2arN88NSaa64ZKSWPA/CXT+djGgYLi5KF9573vCdPcdsJxzHVSy65RM7T/seSGbMN2lIEGMFjW02AncFQ8kiD4eVBD4xIqKmPAmfZ8kygQ0optNUzHrh99/1SfO97382HcImz5SfQT9jxYvhSvNRDOFrW9K1vf2vqntblWb1WClQKDCwFLCsgdwB1sqK0huwkv4xtQJ1CJB94msgm6aS3o5WpavJFGuPfd0meD/ZQ2/fipgDwxClFt6+77rrTvCzgRB/T2fQdHsa/9GtKXTqZx5XepgsZtN/73veyt5dOnKaw+mPQUODZZ54NMo0cAua/+93vZKzF8TgrjYShgO8mhuIghvfgRo5M5cOChWfgHjxDNtqx0HMBroS98J402gpHcZh6PhhCvwN6QJlVM3LkyDBY2wNiW/NmGY2pDR8hUDRAfJNglJL1dJbGWHoCUAO50lBqnrHsCAdxAu+26RO7yfgtKNcWkWYDPvDBD4atJwuo9lyH6jBx8gG/hIpnAqAPNGOMlFIG+uLe/va35xMYWZ7W6APzypanPfCMay/PGaPAc8pXvcrxPuIEaXxLII/f0tn1h8I27WhrJ5448eX561//+rzGflTLIGFkYF4C0Hvz8Gk7o8PMiTwCujmR7+1ve3trNmM+UTVUClQKDBIKMLjJBt8WlbFemkbGkn08SuQaOUJ+leeulhOaJubNlE6a5syjNDVUCgwEBTiq6Cied7q02YaUuna7oe8trQH8LcsoerOkpdPoeg4vuhGuUG55Xq+DjwLk2EorrZQPz1t//Q8EjNLerzPa6jXWWCNgpiaGgh1hUPEFRykXroOPyEw8w8AQ3wwwJAwoDew5O9rYLH9W7/sd0PelwZdeckls8ZGPZAsN8axvanZIexmzY6CmlNqLnS2/U0qxagtQ77ffV2KxxV4zW8rsrpCe6JBSytPtUf9VClQKzBMUSCn1acz3JDei/qsUGKQU6AvfSpPSnNHtg5Qsc12zbDGun3wv2WnNe3+/UEopO2Z7qld7e3o+UM8GJaB//RveEJ/ba68wXeLDgyWW6LxUZaCINiP1sjp5unnnZ9XanJF6a9p+okCtplKgUqBSoFKgUqBSYKYosNhii4VttoU6SzhTJJyaaVACemvdfNjlgxZTZVNbW28qBSoFKgUqBSoF5lIK1GZXClQKTEsBy1hs3mEJFQfotE/rrxmhwKAE9F5Ax6aU3NZQKVApUClQKVApUClQKVApUCkwr1Bght9z0AL6GX6TmqFSoFKgUqBSoFKgUqBSoFKgUmAepEAF9PNgp9dXrhTIFKh/KgUqBSoFKgUqBSoFXhQU6FdA7wtmx+3azL+78Nhjj8WTTz4Z0r4oKDyXv4RzAB5++OHwBXp5FXEOpXEIhGf6tNlf7vWhvmz2s8NunAJcyilXcQ57aNZRntVrpcBgo0Dhb7ztJOje2ic9Hpe2GcR5VvKXcaVcz0p8b1fjxjickTw9lakdxqprT+k8k6b5TuVevOfNUGSCNCXe+3tfR627L/H1OnAUsNUy+S40+7G3FuFDMt+1U1r86Tk+6GtfS6cdjz766GzDBPgPfyu7Uzvb49BAGwT37c/99s7eTdl+lyA93aa+ElevA0MBfaOP2vFKe2vwhf6Svv2Z3/iYzNLnfg+m0K+AHjEnTJgQTiQUHAxhJxsHIbkvcSeddFIg+mAi1LzalssvvzwcwvCXv/wlC1SM7owAh3k43MuX6Q5XcHoaRkcnaX7/+9+HgxvGThms9AAAEABJREFUjR2X+9sBH4cddliccMIJccstt0xjIDz44IMxfvz4+PWvfy17DZUCg5YChPill16a+ZW8cqLgPffcExR3d43G36ecckqQfT/72c9CcOjNxIkTg2KQT5rTTjstjxkH5B177LGhXM96CsbcmWeeGQ5B+fvf/95T0j498x7XXnttGNMPPPBAr3mcuPiLX/wiv5P3EpzMec011wRgqACyXDplOhhPmjvvvDPTTPvPOeecfNid80ekr2HgKPCvf/0r8CGZL/zud78LYLqnFgE+1113XRx55JGx33775SsZj5fkA5Duv//+LPsdoOhAtKuvvjr0vec9BePDAT50g7HXU9q+PFPG6aefHsYXPdVbHmD8jDPOyAdTwSm//e1vQ1zJ5x1vvvnmcMCVd3f985//PPXd1OEwS2PEfclXr/1HAXLo1ltvDQdCffnLX86y7YorrpgGg5TW4NUpU6bEEUf8KKQp8eX6t7/9LfQl2e/wPrKyL3xc8s/pa78Cepb5+eefH7/61a8yeAPuAEOC/oQTTshxwDyFSUjM6Zev5fdMAV4z4AJQcGgXZjcott566xbDHxEEGcF8yCGHxCc+8YkgKDE3T8ZZZ50Vthz92YSf5X7V1wbALrvsEg6y+eUvf5lnYrTglcOGxdAhQ+LAr30tbrzxRlE1VAoMOgpQ3sDoRz/60QBKTj755Nh9993zlmu33XZbNnjbGy0PMLvPPvvEnnvuGQCN0wYpFmWY5frrX/8anhtXygdePvOZz8RWW22VjV/jrr3c8vvee+/NCkoaJxmWeFeKDIDRBr97C9Ldfffd2YBnfDMyessjHaNe+72XQNkx6Mlw9ZP3aEbOn3rqqTFmzJjYeeedg+K0+YFDhCZNmpQNHu/RW531+ZyhgP62s9y2224bxx9/fDA69Zs+5ozrVCseO/vss8MuJZxzdADe3n777QPIlweYB3b32GOPkJbx+fGPfzzoiJ76Gz+ed955GUAtvvji0x1wiL+E6OM/bb3ooouy0TFx4sSp+qe77IC78brNNtvkNjDIvSdHlWfyXX/99eG5d/buHJNohp/VZxtGh1fKSw7IU0P/UQB/cS5wPjoxVh/hZ7IVD+Cx0hppjYHDDjs0Dj74m6FvyzNXDofPfvazITB6Dz744Nhkk00yT+traQY69Cugf8UrXhE8NMDdiSeemK1ap3Y5+ZQVLo4gMfCdZIg4iGzQMgaARXHtoaShPNzrpEJgv+VzFSeN4Hd35XSqS5mlHFdt6lRGe5l+q1d+6eVTv9+edYoTX0LzuXpLfPOqLGVqt6vf5bn88rlqh+fa4HdJ0+kqLY/LTTfdFIAGocTr4khk4B4Y4VkjlAlydfDCS688v/XtPi0gA7zrV2DFoPKMUOT9l3b+BRaIj265ZSzYuhokDAnxNVQKdEuBAXhgFuqAAw6IlVZaqeXtOTo7JkaPHh0UBkVhbLU3y1gzuyWeImDU/uAHPwjjCPg1ruQVPvjBD2bgQA7uuOOOwftjbBnX8rcH45z3z/ONP/ShaJ56KO3kyZPzWR6MDb97CrywxvOYMWOyYe7glJR63mWM553n601velMceuihUd4NYPtQqz0vfelLs0HiXZdeeuk4+uijgxG00047ZcPd7EZKKVZdddV417ve1aLpT+OGG27oqZn12RyiAO8x+XziiSfEdtttl50wAL0zVBhkeLFT1cA6h46DH/Uzg+1zn/tc3HHHHdkoUC4Qb1ZXv/N245OXv/zl2ettpqZTueIYupxC2vD2t799msN+jDX6SZ3qkL67QNcpy/sYgxxRKfXM28YUnfXTnx4dADoaoM8666wTv/nNb+Kqq64KY9v4RAOGkHc302ws8dQDgMaA00cXWWSRbCA9/PDD3TVzno3XP/AGeeZe3wrum0Txu7vQTNe8xxv6jpzabbfdQh9xIjO0yOEpU6bk5PobHoFXjj/+hDx7mNILPMJJaeYR3lEOQI+PF1xwwexQ6YmPcwX99KdfAT3mdsCS018NjLXXXjsrIUrtbW97W4h7xzvekRUmz41O5a0H9imM4447Lu5peZB0fKGPKbkLL7wwnypLkegUioxy0kk8WDrxptY02Omt6bLDDz88dKTpFAOylKOuyy67LHueS1133XXXVK+bjj++5bWgvF2POOKI6IuixAjac/HFF4e2YYLvf//74bdnFBjBRHARfJRkaZP2ezft1SaK/r6WNw9TlzQ8fPJ9/3vfD1OCyiZs5JVGu1miN7eAOTqwTrVBmub7S9sM8pktoWwJVIdi8bj84x//iLe85S3x3ve+N1772tfGcsstlwUei/fJJ/8bBGcpB8Cg7PUzhQ2w7L333vHFL34xL6nSFway9Msuu2x84AMfCIIfcGr2sec1VAoMJAXwKUBgzAAs6623Xh4HQPmnPvWpcHYGENzeRsYrOUHG8XyOGjUqNt9882wkGw/GlTHjcBXKRLlrrrlmUBo87sYpgNBert8MBYrFGFthxRWnATyeX3LJJRlkG8t+dxe8EzljXDLa3/zmN09XVqe8lBjj2zHqjkLfbLPNYosttsjhDW94Q3g3skca7/O+970vtJXRwGnDMFIucOc0cLLMDCCaia+h/yhA19Fr9DBwSuZvuOGGebYGv+LF9tbQQzzRdKwZF7y9yiqrBGOU4wYP4F3LzRh0ZmeNE3wPJHP+8MC3l+s3fXzuuedmww8gdiy/+BLwCIPQmGzqzPK8ecV/ltiMGzcuOKPorObzTvdAOgCPX40LPL7++utnemi79mjDq171quyh3741I+F98bG0xhxdqexlllkmjGvvY0yim/gauijw6GOPZi833Q9fwTAwH1rBd1LpY/jDLEd7gBcsc3ryySclnSbgo9tvvz30E/kEf77//e8PMo781M8ywGGwCdwI8yy88MKipwZLbX7ackisvPLKscMOO2QnhJUG+F67hMGAWfoV0E+lzvM3PTG2jtCpvAWAH++Oaa0dW94d3gJ5DSjg1HQKMO+e0BDkxQyWcMi3W2tq/PNf+EL2jPEOU8KEkaZgFsJBR/E2qMsUoUGqo9R15VVXxle++pUwFT527NjsXcBw8vcUTM0pz9S88gDqgw46KCvs8ePHZ+HHKy3e1DUPFgWrTaao5fFuBBeFv1NrqvpPf/pTNjR4AAAK+ZRFGVr3SHma8kYftDJt+Jldd81AmkeDV8F7MJY6td37MjhYtQZBEeYAPE8DkOG59ZYGkecOAjvppJNjrbXWmqZIZTUjeO157yhzg7es02Uxq4vwNajQoJmv3lcKDCQFLDkgCyjnFVvg+Q9/OD973IBaQp0xymHR3kZjsCgNCmvvvffKssPYI+PwPc8lY3311VfP2VNK2fvHiGAUS5MftP3h1adogAWg2GPjjWJxbQ8lXrpmUA9PFsAN1AFy3aVt5qME5SMDzNgBcUcddXTcd999OZn6pVl00UWzAvzDH/6QZ2UpWMYNoChhSimWX375eP3rX58dHWgqvob+owAe9c3Gu9717mzMmVUFgsl2QAeQaW8NHuGkshxG33GSmTHS51u1Zly3bAX8wVgYPnx4MFqVgaeBJve85fjPfTMw7rSBzmHglmfqLAF/CX6Xa0nXvOJPxiVDnE5ldEjfTNN+Ty9NmTIl1l57nTD7YBkcjOCeweN93ZuxA/i9GwedmQnL1rQb7ZRr/DKQ3AP1ZIn7Groo8OA/HsyOVDhG4OAkT8gIjtMiQ+EacZ2CpU7FgOoqtesv2uM1WOWqq68O+EK/3nHnHdkJg3el1HfLtZyTEyZMCJgLj+IrzwT88LcHHsgOTLwsjrw3cwSr6fdOfCxdf4YBBfQ9vSjLndfalIYlOsAfhUGAAO7Wdf/2t6flj6lWbE2B81RRmAYO4uo4g/bJp54MSo81BlRbQ2cAEl4AsE4DUDEQD5uBy+JjBKgT+MUoOu2hfz0UyrEEBQjXmV3v0P1fbdAWgsvMhAHNWNB+wgCwPemkXwdDooB/QpDXnfBhWZ500kl5is90oXdkrADz0lDAa7U8emed9bsA3se0psx5BHnGlEOY3Xf/fUFJEsyMkJIG82pfe+vFKQOTmzExWyINT/uWW20ZBDRh7f3R1BQkIeVdnPombU8BqOexAWh4BKVNKQVB6321VbvF11ApMBgoYLzhSTKCYgHCrRVnhJIFAEindhrTlAFjgNI55ZSJeYrWWlzjTx7KH0CgIPymfDgByI1NNt442r1F0gjWeL70JS/JXu8yRs0GUohkG08WuWWa+Kijjgpgi1dU3mYATKwF9R48WJRZ83l394Ab2Ug+qY/sZLBwjHCkkD+WGKABg5/nlswjP8lVMqOUDfyQj2T1XXdNKdH12g8UIO/xHNCrTz/ykY+E/gKAOV/o1k5ghe40u6QfLWPA0/rXmvK9WjOxyqRD8CAeVn55Hb+NJfyBT0p8ufLs4296ohgTyjrhxBMyH+M3OlQdgDaepwvlK2WUK4PSjJD3WWqppUK95Vmna6GHdIxPHnnfvwDyPPCWcHA4ec7jz1tvrG29zdZhNsGYoB+B/FK+mQn60Tt1JytK2nntirfICA5EGMCH2GTJUkstGRyd5BfMYFUAfmwP+sQKgLJMu0k/cfgSD4357GfDDJTZRHy70847ZUeC9FaHWCal/zhH8IB4wb324Xf4pMnH2iXgY+8h/UCGQQnoKc5JkyZlIE64GJAGAS+YaS0fYt51110BnCLerp/5TKy22mph2YZBC2imlDzKgaI0FTx69Oh43eteFzqU1QY4ApWMBECdx8ggpEiBV8xlKpqBMHTI0Oy5MM1CoRNanucK+vDHgGYkYCzvoR2m4SnRtdZaOzDp4osvHqx7Ao5iJhi8P2WHoXjOCAUGB48KIPDpT38qzDwsseQSIZ/38g4EXWGw+eebPwgYbWaFAiHa4f0xa3vzlUOxErqYuzwnwPb90r55kGmvbyIMPjMk6EKwYuySvrtrSil7PVjegFJJB5ToQ2Vof4mv10qBgaYAmQCYADzGAeDCsUDWALSMWrKkvZ3ADq++8WIq2czZIYccEsaOmTdjuZnnwX/8IxjsQAOPuZk146KZxr1yecIXXGihoLTECedPOj/nVxePKVkKkFm2p1xAW7pmSCkFGSmI7yQTxLcH6TlQPv3pTwca/Pa3vw3eM/LZThAAF5qRn5ShJYHa8O53vzuvZWVklDIZFTxf5Ny99/61RNdrP1AAOAWE9RWdaqYIb49tzUTjPbO/+rSdL/z2ESEj0dVssT6lX+kFBiRZnlIK5TRfxe+UUt5phB5oPnNPL4inE1Pq0uUAvVkDbQO+6EflA/f4Cs8Zp/I3Q0opf1Br3Gpz81mne3pTOcYOejC2jSez3/QhR5vluaUsV/pqSBqSMYhxgee1rZRP19PLdG4zvjyfp6+t7n3m2WcCnhrTckjCRuTK5z//hbwLGN7jKPT9JbzUKey6666Bxu10xNuw3aOPPpa962YCYbHFFl0snnj8iSh9gfoYNwUAABAASURBVB+LI4Osapajf5Xj2pS10uApsqs8FzeQYchAVt5d3QYTQImwvNC8BUA0zzrAS/DweN9++x25E1nxKbW4olUgQAi0tm6n/tdZgHDpMEBVx+gEQoK1pi7KFkPxOvOi8+Ib3NqSUlf5Bnex0lLqiptaUYcbTKDsxVtg3XIVSQgFbVh0sUVDvDhWnnZqE6XGqyefaXVGijYxCAB5S4kIs7XWWivWX/8Dcdppp8bee38+eCEsJ2LsyKtc9RMwzfdXl/cnsKRpD5hc+Uu1vBmmrMpzZWo3pU2g8iJaDmX5DjDDY8maLum7u6IpgZ1SCsZaSTd06NBQZ6lf28uzeq0UGEgKGEP4Ef+bKeRlHjVqVAA9nnEKMITb20gWSWO2kRec0uLxsyTB9zBkTslz/3335eU4ppktMwAggIDyvHklBzg5llhiiQxWyrOPbvHRbHDzbHEcGOdmE/wWOCpK2lm98sQDbZb0aW+XEv58/gbKbCG5Sdlpo9lFnjKGDVnGSWEWlizTDopROvLPu4mroX8okNILgBuYp/vwqhkVQInnVH+S2+0twvuAlGWuHDsbbLBBXpZK3zDwyHmz7O159bPxhD+U0SwXkKfnXe2AVJ7Rn1/e98tB59Bz9D4POeMab2u3tpT0M3tNKWUDV34ORHqNkTK65RDkqQfKzeprnzQppeyZN24F48DSVjLBc4HOhRtgG/pNXF/DPJHuuQhLGc0QlvclO81+wGf4gQw1s0cutgezneRhyVuusBRjbOGFF8ozo4w+uMV3gHjo4osuKkm7vaaU8iwpGdWOmfC1OHycUu94sNtKZtODQQnoEclgWWCBBYKisOzDlAhvGAFDOfB6EQoRLU7ohRhpSMoe4ZS6CJ5Syt52AgVIVRePWamL0hMYEUA04SStagiVdgEkvqcgL8U6pNWOZjpM4Jm4ck0phfcXFl544dAO7+/q/YF2ChGzA/voccQRR+Z1qwaDbw60V5klpJTyx8cppRyVUsrvn390+IOugjaUdgHsPIq2p2ToUMhmRcxqEKSMLl7DSZMm5e3AUkodSu6KMsh47/Qva7wrtuuv/lCX0BVT/1YKDDwF8LvximfNgjF0GaC8PWbKKJNOgF4eRupSreljBrs3Ma5XXmWVGPqSlwTAI47CMtN21NFHx8iRI/N+9JwHnnUKnBrkFs9WGaPSycOzv+666+Y1omQVkGadvSnrpVpGunSzGtTJGDd+ycSUusY7OnFSGOPenWdNIK/QDA144gExwEa60hZlGv8UZImr1zlPAX0CbA5tOVTwsgC8AOKAD37lgacPmq2RRl8DXfhA/4rjVKOLzCAt3AJSC7f0mD7VtyU//vUbb6inxLvig/K8Wafy4QB8LNDZgDJe95uebC9LeTMa0IFh4MrI9D7u8TN64HHjlo6ix9DGOzK+tW+rrbbK38CYfaNH1e+dSjBuxdUwLQXwIXnVjE0p5Y/rzSCZmWHMAfbNIO7444/P6+Oj7Z8lUwxSS3Is6cPneNOKAmVecumleWVDW7ZpfqaUQp/jgX899NA0z/CAcvCi59M8HIAfQwagzl6rNEgR3mDYdNNNgkcMsOahp0ARjtAB6h988J8BYBIOCiZEKEf3vQUDjAAwEA0yXgl18TiVuggo7SllpdSluMpv9RI6yipxna5d2abN2ymPOB58DESofeQjm0/z/pQhwaK9PqDlBcPQvjPgqSDcDAzldGrH9HHTx6AJA2TKlClTmV2Zpq4cYmM5kLallPJgk5bg0y+mHV1T6npX9Ivn/2mTGRFbl1m6QAA3AYZ3MgC9X5Pmz2evl0qBAaMABQ/AkknkDV7WGALdWPDMOBBPHpALnv/qV7/MAH38+O9MHUuAPy+fdGQYDxSj2G4g9uf+9re+FZbENceOspqBAjFO77333lB/eZZSCvkE40gaY9dvIaWucRkz8c87abN3fPDBB/NOPQwFY1mcIr3bP/7+96wAeVDJVoa+9CUNmglkHLrJh65oQnbUsY8i/RdSSnkXEMYqgGr5iNr1F3mtb8hpfNTkAfyETx9//LG4//778lZ/8v3vqafyUglAeKmlls5l0yWMXs+Be7oEL9FnyhFfAh6g/8XLV+JdxZWAt4Xy21WamQneVXsE94wU9MC3ZqtLmcYa3sXbZsKtubaUDI9Lk1LK3v2UUnaaeRfx3h1ttVG54mqYlgL333//1F3y9IHf8I1ZGk4UzkIzRb5tbA+2lMSjStSH+NS9cvyGLdyLE1JKLtnwyje9/OG0YLRNufPOjDclV55vJxgh+KH0tWcDFQYc0CNK+8sjnOUklNa3vz0+rGO3LZGdIHxYZrcE1ropZQPatC+QaOcV4BaRm2V2qsNz8ZSebaYol8MPPyysjbOcp9Rl2lDaZ597Nu8s474ZWOHW9bECCxM1n3d3r+72Z+IE72S2ALA/9NDDwo4Y3t900dixY/PWjtIRtMqgRAkeH9z4uNeV0JHG8+dasxjl3u8SOsV5pl4eNGUYVOIIok033TRv++UDKNYyYG9aceLEiXl7PH3yzne9M6+XVLb8PgY0EPWZPrL+jaefAWDtrXKVLxCW1h7qCwI1pa5B51kNlQIDSQFywpICY7ysoTUmjzjiiLA8zmwVRU35250DzxufHA/4Wpzx4iNwuzjxKFFSZJj19wxl0/uWLPzpxhtDfofwWQdvfLe/u/EBDD/15FNTvfzSkEPkpUCOKp830W8bAlCQ0vUWjN9mGkrREpmf//znAWTxrBqngJnld2Su3bdMb99+xx15tyvA3AdryrKGn2y1ht/3ARwvnA+UoXq8o7LIvqKYxdfQPxTgYSff8Ql9qp/0l49NgRUzP2S1eMsb8HFKKTYbNSoWXHCh+MUvjg38Jf603/426EVec31pxkjfymfM4CPjwcyRLQTb31A9PP/GnLFVwDJ9olxt1Daz1gC15S/i8KCx1l5eX34zYoxJ35uYNTJufXemProObyvfUhrGhu0spTHGLDP1DYlvCehq74mvzah7F/UD8wx3etXYEVfDCxQY+pKheeOPH/7wB4HWsJzvIjgERowYkVdYDB8+PH/Eilebwbp4fMbgfPzxx/M5AfqEMWpm0FIeSxutaMCH+ojMJa99JOv6QkuiI87Tb1Y/cF4wHowDfOz7DXxo5qb0dbOs/r4fUEBP0FMUQvPFU0pBEVnygoCAn/V8vjJHfMs+EJjA8CHO/S3vgKUoFC6BwqJjLaWU4rlnn4t260xdpW4K2sCzDvymm24OZey40455i0cdZP068Kkc+aR3LQFIta4LsG1/j5JGXc89Nz2jtKdvttMHsLbWpNB33nnn2GHHHcK2lYwcXjzMTflTqkCytGhEUVpyA1hgbm145ulnQhvcl+B3+7uUZ2hMYFHIBhdg4hl6+zCFQLL1prX0AtpR8pbdaJOyU0p5Ckw67fVB7ujRo8OHs7w61iUyWpRbAjBPIK+6yir524gSX6+VAgNNgZRSPhXQenSKvcgk/GxmDxiixHmZjUeAhSdy9RGrh7FpWlYeY9ksIOPX1XgG8IFuY81YKuPFmLG8Dqhpf3/AlyPCWDNuyA5pGBjyC9rBUNh7773Db3JTXdL1FJTZLhuUb19uDhXesSIb7SkOzFhDbU29NKNGjcree3LENLdt4Bj20qABwAPIaVNpB9CmXOCRcVTi67V/KACk6htLExhfdAleBYDwJH2ALxil9BBQ5Lcd5uhes+Ly6+PDDz888CZ+A3jphJEjR+aPtZVLT1hLbumsGfdObwjQFz1mRkwaS7RgAnwDXHGkcbzhL3HaCThL21PQbqGZxkzXAQcekNfnM3p5ZL0/PgXatFvAo96TMcLxZR022tGL3l0emMW7AXqlDnpZHegLfJb4F/t1Rt7v5Yu8PCZOPDXv824pMd6Dvxj+fS2HMebMHk4GRpqZVX1BXlp1QRYrG65yNcOY0rSOQ7xB3rmWevExfsbHZCxewAeMTPcMh5J2IK8DCugBRsSh2IDEJiEMEp3JQ2CgUBympVltgCWFSEmuv/768b3vfT8oL1NfBhjAOP8C8+cpL5bTD3/ww/zRCpCvDnWpE9gU57fO8YU+gfGB9T8QDAWeCgOaoqaY/OZtUEYJ6jdtTsGlNC1jSANwM0S8C6YocZjrawd+LS9ZEccbYetK3j904X3bZ599wvsTEht8cINwMAZha5cI7+/jOoyr7eutt27sscfuwfstDq0IJWv6eBi0XxvVhcmVrbwSJ74EcRjXlClvmulCz7TRbkH6TDsMCKADHdFGO7wvQTd69OggCLVHn3g33jvvYxYBAKLwlSsYGECQZQsf3GCDbJGLr6FSYLBQAF8bt7x0DNkPf/jD+UMrsoK3LqWUd9EyrgAO42WhhRcOisD4IAMoEGWQYz4QJROMI14fY4NzwHgxpsg045QsbKdBSikf4MQg+P3vz4lHH/13TuKbFnJQ8OGY2TRl+q1d7UZ0ztT4Qx4am8a4dyqPeL/IYcqSTCUjVmkZ3j5GHD9+fD5czo5caEP2LL/88ln+ohkl6n3JBI4KbQKAgHflMx4obzOj73jHOnntv/ga+o8CKaWwtphc1z944FO77JL3Byfj8ak+p3vpKPokpRRkOP7GLwA1fYjX8C897A14U80s4xX9z/CjC+h0/CZNezAD5cPzKVOm5Flzz/ES41T5gvEhuBfodLpN2u6C92BQKMd9SYfXD/rGQWG5LQdeSil/pImf8byd4QA345jTT1vkBTbpVw4qswXS4HWGv7EpDcPeTi1moTgq6WXxNbxAAc7NN77+jXn77q222jJ23nmnbADilWY/vZCj8x0sR7bAcbAI7Ibn9KO+1Udkt98M0XbZisff8Y53hDX6sF+pJaWUd8nBt+SzmUd4h8zGx+RjSTuQ1wEF9BQeUErJsaDaCaEjAWiEN2AIDN50YFbak086KZ/SZrmJjxw2+tCH4p8PPpinbF633OvyWjYDFQjlCUipC3Cri2CiUAmUlFIA0QYn5aouVxY2hlAXoeRjF14Dv0vgUcYEQL2ySny5Aqjeb2TLQ1HaLc57YTR5pcUQPH1AArqk1NUmAqC8P4XK81HaVMohnPbd98ux3Xaj89pb7eYlIziAcu/Pgkyp6/3RFbNiRHV3CqapgBJTpKa/WKzSaRsPmn4jQA0eHhKGAxpKQ8jrJwLZ4BEIffRTJ2VfaCG9QKFb3uR9DahCF8+6D/VJpUD/UoCSxsPAuXFnnAEAhV8Z4pS/8VDGqXFIkfC283BT+jx8xlIpz/gQjJVmUFYBD+1vahmEnWOuuebalsy7Ma9hVm8zf/t9AVntZZXf3gOwM74pxxJPtnkHyxDIlJRSBuzknnHNqOG4IL94V5Ujb0oplEPeoRkDRRpeypSSJHkmz77TFPAee3x2ml17coL6p18ooM/oS3JbP+26227BeVTkukZYJuY5/ZBSV/95zvOMv/fdd9/Ak/Sl8uRxHT58eJ61YewZN/QhPex5p0A/0OkQcgb0AAAQAElEQVTGieUT999/f0jPaGzn6fKbntOWTuWVOOWqm052X+IZAsqmk41J8dptth/PM8K9n7zN8WiMjxgxogVAd84ON7vkKbuUoRzfhdFt9Du9m1IX3Tyr4XkKPBex0MILhdmcPff8XOy6626Bp2Cc51P06SI9voHv4ByZyFk7DzGyyF87FTE8yWXPm0Gfw0oM2nasl1IK8o6cxsfkGcMW3mmWMZD3AwroZ/XFl3vd67Iy0EGU5PajR8een/tctqwpGZ07q3X0lt+yFsDXUcIpvXgGakopAHXeOFPq/3jwHx1JkdKsvzMaUuiEI2FfBmLHCmtkpUClwFQKkHsA8xlnnhnWjE59MJfc8M5bj2odtHfh9Z9jTa8Fz1UUYChbLnHLX/6SvfR4ZTC/ADDY3j7LVR0GaQaaZ78/MEl7Gwb97xaYfy6ey0ujOUgHfXsHcQPnakBvmYklHe9///vy18q83KacDzhgXF7D12mAze6+YI2z7JsW+eyuY6DKAxRYobxp/37k39Otw59d7TIV+ZKXDI0xn/1s8ADNrnJrOZUCL3YKAD2A8MILLTTXAnprXXmCeX5f7P1V36/vFEgp5RmCj26xRfjGoswS972EgU8J0DO0LVviJR74Fg2+FsBOm2y8SZj5hOEGSwvnxnbM1YB+gQUWDFMnhxxyaF7rZ/2ftXprr71Ov63BNsW3wAILzI1936c2jxw5Mky/lmn2PmWawUQMh9122z0+se22U78pmMEiavJKgXmSApYNWMKy22675a0i5zYiWMpDxtiW2FKdua39tb1zlgKWYVnqYrmKGdw5W9vsLx02MNOdje6FF579FbwISvS9hD72rSB59iJ4pQF7hbka0KMai86aNh83GPyWa1ASntUw6xRAX+sLCaZZL61zCerQd3Oyjs41D2RsrbtSYPZQwLgxfuZGwJNSCvKbl64/ZlRnD8VrKf1FgZRe4I+UZn15Z3+1u9SDp41NS21SmvvaX95jTl7RCH2EOVnPvFD2XA/o54VOqu9YKVApUClQKTAPU6C+eqVApUClQC8UqIC+FwLVx5UClQKVApUClQKVApUClQKVAoOZAgXQD+Y21rZVClQKVApUClQKVApUClQKVApUCnRDgZkG9E5tc2qc/VWdltoeHLPrGGWnHzbr9rX62WefHaeeemr+cr35rNO9HRBs3i+PL8Y7palxkbd8sluM7bHQw1aQTvNDZ3vJzy7a3XbbbfmwK8d8z427DqBNDbNKgZq/UqBSoFKgUqBSoFJgMFFgpgG9wxJsrm93BYcwtQfxwoQJE6a+rz1GnR7qgCgHNTzwwANTn3W6se/s0UcfHU46vP766/PBKZ3Szctxjif+5z//GfZxR6d77rknkwNtnWjmoIsTTzxxtm1pp0+clnf44YeHwz5yZfVPpUClQKVApUClQCcK1LhKgUqBfqHATAN62ws5FdHJck5TA/SAyb/97W951wLxgi0JPfvrX/8axx57bBxyyCFxxx13BMDZm4f3lltuiZ/97GdhBxsncs2NuzjM6V5EQyfpHXjggfH73/8+nnnmmVylnX7sTrP00kvn/vAleX4wi3/se/22t70tLrnkklyfvp3FImv2SoFKgUqBSoFKgUqBSoFKgVmgwEwD+lVWWSV4ap0ieswxx4SjwoH8xRZbLByvy2PsGS89b/64cePC8eCAvfb2BjAB1aOOOirkddjQCiusEPLwCl977bWhHMtLrr766pg0aVJYClLArOUlU6ZMiauvvjqnu/uuu2Ly5Mm5LB5tZTMqzj///LjwwgtzGvHa1QyWrVgydP6k8+OPf/zjNEuE1HX33XfHVVddFYyYRx55JK644opQpnjPm2VZDqPd5557blx55ZXx73//e+pj7+E9zULwtt90001x8cUXh3IkevTRR3Oec845J+SXTnmeoYelNdI6wEJ7//GPfwQwv91228WnPvWpeN/73pfrU/+NN96Y7+UV1I12nt17772isjdfOeedd15+J+XlB60/tpZSHoPhmGOOmdrG1qP6v1KgUqBSoFKgUqBSoFKgUmAAKDDTgJ633IEADgN5zWtek73AKaWwpzgwKZ431x7D11xzTfbmSvehD30oUup9P9a7ngfhjATeeQc4oY/lI4DqFz7/+bwUx+mCTmrdYYcd8rITYN76/u9+97ux7bbbhiUne3z2s9ngcIIskK4MBz04kEVeS4Cs93/yySdVkZf2AOdf+MIXchkf3uzDsfXWHwvHUF9++eXZCw48W9v/iU98Ivbdd99wouqWW26Z6/n0pz8dvikAlhkKwLaZiY9//OOx2Wabxcc+9rFQNmCuQoDZc+0V74jorbbaKhg0DBdLabznpptumvNL96Mf/SgbGL5hYDwB+IwCRpN18wwDMyKHHXZY/OEPf8gGgYMb0EnbtEvd8mivOr2zbxa+853vBBqPGjUqPtZqhzaV9wbkX/e614W+ZQzx1JeylFdDpcDgpkBtXaVApUClQKVApcCLjwIzDeibpADohBLXvBdn2QcAfcQRR8Qee+whqtcA7AKzAP1KK60UDk+RiReZ9/ikk08OoJ3XntcYsNxrr73id7/7XQDSt99xe/B0n9xKN7nlnV9wwQVjwQUXCh50pxICqJYKWTZkqQrQyqNvCcl1110X0gDsvO/LLLNMPP74E+F7AKAe8OXlv6tldNx8881x/PHHB2CtjdpTlsDwhvsI+Cc/+Ul8+9vfzmvOzTQwOnxL8PmWUQJ45/befnt4Z15vHnM01LYTTjghf4SqHIbNiiuuGJYiHXrooeEdGFDSoo2QUsoGCYDvY1gBHZdaaqkQZ0aBp1+9ZhGAfZ54Mwze02m71t7feeed8frXvz6GDB2a38+SHnHqcFDG8OHD86mujDVGkvgaKgUqBSoFKgUqBV40FKgvUikwF1FgtgD6nt4XwH3zm98cu+++e7zjHe8Iv3tKX54By5alAKzW0KfU5dWXn5fYlafaGnsebKDf8pOJEycGT7sZBGUNGzYs1+3j2m222SZcAdy11lorfvjDH8b3v//9WHPNNePWW2+N4447LgBbRoFlLAyFAw44IIBvgN9yIgAWgPeBr7YB0045NBOg7LH77x+A8Q033JC99Jb+aBPQzoOvLMYCgM3QMDOgDGVpL7D8la98JRg/POTenbdenoMPPjgYLdrhGwSGzYYbbhjK1dbll18+gPGNN944g+1SJlppk2VRQLwlPzzz3pV3Hz3XX//9rZmTyPQB/M1cmAX41re+FWZbLGuyDEhb1aVdymXQMA60vYZKgUqBSoFKgUqBSoFKgUqB/qfAHAf0KaWwXGaRRRZpAcYu73Fvrwk0WjYDfM4///w5f3seyz4AVGB8/fXXj3XWWSeAeAAawBySul7NWn9LXN773vdmYMq7nlLKXnxLRgQGgDovu+yyePDBB/O6eICdR3yTTTaJt7zlLXkpzYgRI3I+QJqxkVLKzQKWAWtt+OiWW8Zb3/rWbFT85S9/CYYJzzbQDECbDTBzYCbgySefzB+Xus8Ftf4wTBgeG220UZjZAKwZLsA5T/9BBx2UPf3ay0jgxbf8xfOFF144e9X9bhUV0riio5mODTfcIBgMPl62Zl4wsyHuPe8ZGX/9633x97//PS+bQkPr9X07oBxeeDMOZibUo16AXnrP1FNDpUClQKVApUClQKVApUClQP9ToAv19n+9PdYIQAK5rgwBYLU9Ay81wCseWAVKAUxr23mYU+oC2+Kt9ZcOAAbYAVzLar73ve9lD71lPMstt1w2HCyHKWnEAa/yWv9fymEAAPwppWykDGvNAvhWQDptKXmkYZgAvNpkKY7tHi2j0dbhw4dn8CxfCXYGUkZKKQPyX/3qVwHgm+HgzVcXD7n0KXWlQSdBHLq5dgorrbRybL755vGf//4nTpl4Sp55ANDf+MY3xogRI8JafuWggWU42urDZ8bI8NzWodlQ0T5GWkopf08gT6f6alylQKXA7KRALatSoFKgUqBSoFKgMwUGJaAHdoFnQN7acQC8vfmW11g2Anz6kNOuNcCpD3KHtQB2AZnK4LmXf4EFFgjAHEB9z3vek3fpsS5+zz33jNGjR+cdYdTL+y8fb76lLergVVdHSimUD8CrQ+DNZgSo31WelFLeaYYnG/gF8tXxi1/8IhgSPk7dZZddYosttgjvqxxttNY/peQ2eNJ55C0R8kHsUUcfFZbBmBHICZ7/U/IC82jl+vyjaS7azPP/soVfFpdecmn+3sAMiJkFxgvapJTyTIePcK3nNyvgg9mddtopNthgg5BeHYwj9TKqlDtNRfVHpUClQKVApUClQKXAwFGg1jzPUWBQAnq9UIAizzavu7hmsLTGbiynnHJKBubWdwOab3jDGwLgLqA2pZQBc7T+Wfe93nrr5Y9G5bcERh4fyvJ+81AD3pbMAOHWwfuY1Ye1Pha15ATgZgy87OUvyx70VrF5/b0PaO0uY7cahoB19coZ3vJsa5P3YBRoF2OEt/7MM88MRoAygGNXxoar4INcBo17YHvJJZaM0047Ne69t+vwKIZGSil7+VNKIb2Pc30Iq56UugwD+UtYbbXV4u1vf3veupIhZKbDciRAnZeesaBc9EGbhx56KLRV+M9//pvBvv5guKhj2WWXDe9ayq/XSoFKgUqBSoFKgUqBSoFKgf6lwGwD9MVjC7gCgt29BuAqSA8QdpfOR6OWywCXPNTtaQHfCy64IGy5CGxby83TvOWWW+YPQi13UY/lMaUOwNNuO3ZvsVPMmDFjYvvttw+7vmjz2muvHZaz+KjU2nWefVtHOgWXt1qbrZX3bL6XzpcBfUpdy07suc/j7iNdIBzo5w0HkD+65Ufz2nVr0m1z6YRdO+owMIBr7VO29rr6Lay00kohAP3qt+WnZTBPPvmUx1FAN1DNELnvvvvCc9tVen+hlOkqkw9cfRsAwPttuU1pg11/zFZIo61mFNDIzjj6w3kA8jCE7r777rzchsFSPfSoUkOlQKVApUClQKVApUClwMBQYLYAesDXx6frrrtuPsSI17e717GkxcFE73//+/Oa9e7SWfYCqALkwC+vcDMtEGo3GF7lN73pTXmduaUsvOKW1rjyPEtn+Uy0/qWU8k47lpFYUgKgAsyWv9gCc/XVV89r4oFwu9uMHTs2Rr7nPWGrSeUA4gC+3WRaxWVAz7BgSDhASzuUoTzbSvo4lUd/l513ySfkemfvpawvfvGLYYZh2LBh2Yjwca/2ep/SXgYNgL7VVlvlj12B57322ju++tWvBqMDkGY8AOgMGeUC6NbheybejIQ4faTN8803X2iHD4otodFWRoxnlv4wcNCC4bLccsvFiBGr5T3z1WnWRDozGZY7yYeG8omvoVKgUqBSoDMFamylQKVApUClwJykwGwB9ICdnVgsIbFGHCjtrtFrrLFGPmTqN7/5TQCe3aWz9tz6cgDUbiyPNk5WlQdAdVCTQ5JOP/30vN0i+IQEMwAAEABJREFUMO0ZzzcwbkeZcePGZcAsXgA+bVnJky6vJSo8/O9617uyZ18aARi3ReRvW2Ur31aWDpDi5fe8BJ5vy3N45y25Ud73v/e9sF98ScN77qAmy3rUOXHixNh///3z9pbS8Ih/85vfzKfAOqCKQSJeeNvb3hbW+Sv37LPPzvvjMwaU5dAoS3HQUX71izejwOgYP358Xi5jFkMblef9Af+f//znob8crpXSC0tz0NuHsyeffFJ479NPPyMYN4B7Sl2zEfbJB+oZZvpTuTVUClQKVApUClQKVApUCswyBWoBM0WB2QLoZ6rmPmTabLPN8paR1oT/+aab8tp3S28sj3EVgF9efwC/D0VOTZJS18etPqKdGtnhhrecccHT3v5Y/QC9JTGuduTRliFDh7Ynzb958z0H8HNEH/8A2WY9esqnndK0Gxx9rGK6ZEOHviSUx1hrPrRdp/X03sWHutI0n9f7SoFKgUqBSoFKgUqBSoFKgf6lwKAG9MC2JSEAvA9NracHIC2JAbKB2P4l1wu1AbS847zr1p7PqEHxQklz153vGRwmZXmQJTtzV+untrbeVApUClQKVApUClQKVAq8aCgwqAE9Klv+YS92h0MBzT7adLCTJTO83dIMRLCExamsDo+ydh+oH4h29HedPo71HYElPgNJ//5+71pfpUClwLxKgfrelQKVApUCg58Cgx7QW25iq0UfhFr/7belJ5bapPTC2u/+JnVKKe/Jri12jElp4NrSn+/uQ139wYDRH/1Zd62rUqBSoFKgUqBSoFKgUmDQUmAAGzZkAOuuVVcKVApUClQKVApUClQKVApUClQKzCIFKqCfRQLW7JUC/UyBWl2lQKVApUClQKVApUClwDQUqIB+GnLUH5UClQKVApUClQIvFgrU96gUqBSYVyjQ74DeTjV33XVX3HjjjdMEW1Pa3/zBBx/M21P2tQNsF2krRXkfeuihnPeBBx4Ivx1K1ddyZjadHXhsXzmz+Wu+vlPg3nvvjcuvuDwef/zxqZn+9a9/Bd657LLL4qqrroopd94Z//3vf6c+xx8PP/xw3HLLLdPwm4+Z77nnnvjPf/4zNa0bv6+55pr4+9//HvKKq6FSoFAAL9npCS+WcN9998Wjjz7aJ35xENytt94arqXMcsW3U6ZMyfyMN8mW8qy7Kx4l766//vpoP3yvuzy9xXsXbdSe3tKq/5///GfY+eqmm24K9+3y0Hs4t8I4veOOO6YZn9LSBzfccEPQDb3VV5/PWQqU/iQv9Sn5OiM1kpv6+Kmnnpomm9/GjQ0tlE1Xq2uaRB1+4B26HD+675BkhqLwm/FinPVWnuf4VrvLWHf929/+Ng0PezfxMM3999+fT1AvjbKltfg7W3pJ3SW+XgeGAvoDf5JT3fGffsIjDs/Ut51aKq80eLMvcrJTGXMibpYB/Yw2ygD51re+FQ47+tSnPhUOZBLcOxDpS1/6Ukw6//zojpDt9SE+ILf/V78akydNykrh5JNPjrFjxwZF255+dv42sH/0ox8FRTY7y61lTU+BRx55JBykdcQRR2QwpN8vueSSfNAW3tl+++3DFqd7fPaz8eMf/zjwmVII5YsvvjgcxlV4TvrPfOYz8dlW2q997Wtx5ZVXhoEuPaD105/+NBy8NbsAknJrmPspQIgfc8wx4fC3MWPGxJjnwxe+8IU477zzpvJQd2+KZx2o95WvfCUbmM10QO0hhxwSu+++e5aJePPoo4+O3pwSePSHP/zhbONXcvekk04K7wTINNvY6X7y5Ml5DJaxRX7/4Q9/mNpuIP3cc8/NaYy73XbbLQ4++OAA4NFDYIx8/etfD4Z0pzpqXP9QQF/gY32vP4Uvf/nLYctovN9bK4B0/fjtb387moYAJ51d6Ywbup7sVe5FF13UW5FhXBx44IFBhmtfrxl6SaCN8Mf3v//9Xg1gOgSvlnFerrAFYwdNHmsZ8hMmTAi77+Fv70hHAXuagv8dCokm8IK4GgaOAuee+/vYd98vBblVdH57a/TT4YcfHnjZfftzv/G0Aze/2sKdeFTcYAj9DugpIIKbsnAKqv3M11133XB6q91iAKmvtIj0xz/+MXvbeyOSQWXwXHrppcFKlp7F9Nhjj/Ypv/QzG5z4autKltzMllHz9Y0CTuo94YQTYoMPfjCcBAwEAA/HHXdcLLvssrHTTjvFRz7ykTAADTRbieI1SgBf4I+n/vdU2KHnjW98Y9h+8+677w6ClgJTnpYMGzYs3vSmN4VynVAsrobZRoG5uiCyBl9QBjz1PNlmB10B4Z5ejmK3/e5+++0Xl19+echX0lMOtoE99NBDw+5db3/724Mnc9999w3gmlFa0rZfgSJjA8+2HyoHvPAgGQft+Tr99n5k2kEHHRTK7S2fsrURYFlxxRXDuGKwMJK139jjbBk3blycc845sc4664R3QwfKkpfMWSJveMMb8gwHoNWbAdOp3TVu9lDALCewfeGFF8bqq68eznoBxOk4HuaeauGZ16ecKRxcZTzoz1//+tcZHJGx73znO8PZLfh6n3326dGIo8fhAXWT27atLm3AW+S6mSz3Jb6nK6eQMXbkkUfmGaXuAF0pgy4BzvEwR49xbty6V6fxQiftv//+QZdsuOGG8fKXvzzQC8jXfpjmLW95S6DpaaedVoqu1wGgAEcDzDBp0uRuZ+Dx7SmnnBIcNzCovm5vKp7+5S9/mTGCMYMv2tMM1O9+B/ReNKUUq666anz+858P3ioDghXOI8XLCkjxvpYBZ+AgIiXK8kfkppKzfeKQoUPD1baWn/jEJ2L8+O/Ea1/72uw1s0RDWRQUJWdQ+q0t4h5++KEw2EuceEG98sqjbm0o8TretJ0lGvJ5Jr3nnilPW3W25+IF7Vam9NohnfSe9RSUra2EhPTyapPfngEMytJW6cSpS/3q8ruUTxhJI5S4nq7K0WbvoSz1qkudyi1x6navLHXoJ7+1Vx7Bb89dH37k4ZCnvIP4ToHxRwEQjOut994AAniNrr7qqhg9enQAAjwjwMUPfvCDWG655cLgRX/laaOTfjf/8ObBC0qof/e73w2D8pOf/GT20FNEaEpprLfeeuFQM/vtewdl1FApwHFgSv1d73pXAAW/+MUvQsA7G220UebLTlQCPHgk8Sjwjh9T6trm1tgC8HmxP/ShD+VyASOzUc66ABiMs+jwTzx+H9YyQjlF8G4z2fHHHx9bbbVVXorWjG+/1x5t3GuvvWKPPfbI4CSlFCml9qTT/D777LMDSPvwhz8cQLxxteOOO2awxKNKXhx73LG5PDNkPJvo4N6sGLCkQHLaqeAXXHBBMA7E1dC/FMCX5B2ZyegESvGWWXPGmSWKnVpEzuPfnXfeOeTX5/ippCU/ASTG5ne+852g53k/zaheffXV2dAraZtXZdx88815tnXke96TjcXmc/rDbBZHDh3XfNZ+r40cOltvvXWYzeqL3lM/kO6KpxkWxrowfvz43B468KDWbBMDhV7hGOLR32KLLeInP/lJAIQwyRprrBF0F5DPCG5v37z+W//oEziATIMT0FYfF9roB89giU6hne9KPlc8TTbR9bfc8peME/WLZ+2B8caIlUealKaVgdoKe8Cq2kzmpjRtmvYy+/P3kP6srFkXYrFegTPBPY/A+9///qwYeW8QT7B+jnDZdttt46Mf/Wie3jr99NMzCG+W6V7H8i6xsAgT6zYpkhNPPDEbDw6oIgjOPPPMrIx4cz/WGug77LBD8BwVJgJgeeJYdJTiJ7b9RAaOBJs0PE5nnXVWnrajmIBD8TwGOpug4TFWF4GGQbXPgGbAGPCEJcH2+9//vtfZBMAXCCVMLPNRPgE1/tvj47rrrguK3zugDw+berSFdwwtSv0GBo8HjyAB47d29RSsOSOIf/3rX4U2fPzjHw9CDk0pdNOXjCh0AnRMVQII3vPII49oCfqfZOAtjfdmsLmO3m50bPWxrYKg7255lPZ5PwNt0003zUAbT+ifZ597LnuRDCrtx1M8ldq29tprT7M+PqUUQP1CCy0UgBIFs/zyy+elOB9sef15T9BLOQDGW9/61gwuytSq+BrmbQpYCwuAr7DCCnkNLa8keeOANedRpDS9YKeEyCMBYN9yyy0zEfG1G8+BDfc8lmQh2bfmmmtmcE/+FP6WphkmTZqUPZw832atms/cA2nGrrHid3eBgiTryDTG7CabbNJd0mni0WJoy5Gibu9vbC299NKhvcr0brffdnueDXtPC5QtsMAC+Zmxudhii2WvpXTSewf5GSHk9jQV1R9znAJ33XVX0ENkof4HqvA2/WW2c8SIER3bANSceuqpeXZ87733jlVWWWWadCmleP3rXx90wzve8Y7gcFt88cUDf9P5eL2MhWZGPMuJI27t1swOHnHfDHjb7Dh90Ixvv1cHHUzHWPIFYHeqs5mPLrcsjMfdmSvKEIxP49170KOMfGBdMBac02LVAecQ3ageziEzE7ADRxO6Nuua1+/JKRgAtgCmOel22OGTge/gGPSBX+AY2Afeag9mBtFc2vYAA1qGjQ93aOG8RRZZJDt629M98Le/ZYxHbr35zW9uf5x/628OHH0NI6SUesVuOWM//RkwQE+Q60hA1UABpnjlgWqDxpIIRDPtxWN1ZGuaDBDj2QfwKT+dlNK0StRgMQ2iHJY7YMmqHjt2bBhQBifLmZfIGkH3i7560TzFLe76FjgmIHjMCDNtAvxe9X+vyla3NIQfYaQ9KaWgzIBFVp0lHDwQBrJpQkKEx+PXrWlH7/y3B/4Wx59wfJ6W83EQ5YUO0vfU5wQcgctzh+nVL++hhx0aY8aMycpfO8RbA25pACFI6EjvqnxKGLjgcfCeKU1LP2naA+By6mmntsDvPtmjQqDpA4DdWl9T/uL04yHf/GZO453kOeigg+PXvz4pCDrl6EtClbAW98zTz+RB9NvWdCT6tNctjmBEX2AdaBfc60vvxmjxPixnVj6DAxCyFKdZnvdt/nZPuQAY8nkncYS15WD40FSpAS6+hnmXAsYnBQ/AGD+MccrBLKNlKsZiJ+rg1ZVXXjmvIefFxrfNdOSVcQHgWqpgxtJ6XJ4+eQFdcrCZp9yTUfj23e9+dzZWxRuDU6ZMyQCL/NNucbyN4ju1Uz2AmPaRXSNGjAj5BGV2FwAXSzN+23KukM+ULEC+5FJLZsCWUsofCGq/saQcZZrVNKaARsa/+DIOGdDktLga+o8C+gGIfc1rXhMcNfgaQKdj8a/+6dQa/YoPOJrogmHDhk2TjOOE/jNeGGweAmccNM89+2wss8wyHWeC8MYZZ5wRdC/gJB/dZbaW/sXPeEmg48V5ZjxJ2wx0ojYCjNrhHZvPO90bJ4Cg8jjLOInMQsARDHDxeNjYmX/++QKPK0d75KVrtEealFL26KuX7PBu0tbQRQFAnCzjZDzqqKODXl944ZcFnsI7U1ryDM/oB05IOr8ZxJnZQ/euEqf9q5zYqtYAABAASURBVDyzo4yBkSNHZn7TT81UymdAwBBwIXmoD5tpyFpGhSXjvpewEqA9TTP9QNz3O6BPKWWCIorBxevOIjNgeJ153keNGhUbbLBB9tTzggOy1qcByxQdbzEri2eYhQ6ANYln4AviEBwoBO5MiwHEvNiYxDNMwzrcbrvtwkC7/IorgnEBIBISPPimawgDHmYWNuaxFtRsAiHFy857bJpZPt8DaCfwaoqP0OK1xzTxXMT/nvpfFmSWinjOc0cwaG93AQNqr3fBTGhBAZvV4KlAR3ECRmPU8Iitt956AcwX7yKmZMQA+x/4wAe6q26aeHUTTPPPP38wpDC+vqIECFPT9GhIATz51FNxw/XX54+an/7f07kP9a3nptsZcASdj6O0FRgn9K9qTb9q2zQVt354X+/HwCMQW1H5P28P+jIKDFTGlyk1QveYYya0AMmz2RuUE/fwB90ZIwwGYAKNU0rBC6tdjAmKroci6qN5gALPPPNMnkIHki27AcwZfRQRpUNGUfLtpKDoeXt4PoF2Y6mZBs+TO4xJU/aWIYjjkDCuyJv2PPLjU3kAKjNK+Fj8UUcdFWQBWcVopuTIPXFknI8epWsGsgCIJ4eMhZRS83G395wrgNJfbrklfBxm/DN6PrTRh2LE6iOykWHckqdkDhmCRpbbiPMbPVXAOaINZMo999wtqoZ+ooA+4YyiMxmn5Lt+4R0t+g/Pd2oOnWD2heHJm93Oq/gfTw0bNizrfX1OxwNnvNpmAzqVC+Rx5i2xxBIhvzTGyef2+lzmb8Y0vcBhRh/i7zEtxxb+kbYZtAuf0hmcXu1tbKYt9+rCp9qBFt5PW8ws77ffl/NH7a973euyM++qq66O22+/LWfleDv//D/kb0Lk874emLmil2+66c8ZZ4iroYsC+gOdyLTttts2L4uFDfQpZ6GZQ7KTvseb7QE2I3vMFHaVOO3f4cOHh2WBMKC6pn0a2elALh519NGx+eabT8WezXTyce6pG26yxBJvi2+mG+j7fgf0XhgRgCTgzhSGJRWmfFndrDTr9wCqlFKeBjRlZV2aTjUgWewAPgAGqFJqym2GlF5QShSWNaYGFJDmIyzgUKdQzIQN5cRIALoBed7zxZdYPH+tT6la3wkgq4sVx8vkPdRJmQqUmQGtDu3CiNpIWTEgCJ+UUrbmCUFTf94TI6b0Qnujm3/qUxaPnDyMCkKFoBGHTt4L45b2EUSUKsChbdphzaN1wN15XTpVnyKFOnizCUj0cgVqCEq048khfB/597/zlJaPUMWpy3N01140Vw66AyP6Rdsolva6DXRtllZ95TkAzjAzE8Fa365lkKXUxS/AxbgDDsx9V9J3d0VTdVBm7ks678FQJIDxaomv13mTAsY3JwPFgd8Y+QxyyoTMsOyA974TdQh+odMz4N1YVQaZduyxx+Z1wwxnhi9ZCBi05zUDxrNvzJNL5Tn5aKwwdMWn1DWD6Hd72pLHVfvINvfNceB3d+GUU36Tv0MxrjkwGO089pww5517XpYBlgVqE8/mHnvsntfoox0AmVLKsjBa/8hosgAN7733r62Y+r+/KED2oXuRg75FsqwAn3MIWc7AQdSJL1JK2WljfPTWXnL05JNPyuvo6YOx48Zlx1Z7PvUwILSH7kop5STqGPaKYXm2d9iwYZl3xNG3+NvV75y48SelF9qo7Majbm+VB1CahZ4w4WeBv81AGf+XX35FMOTVZ7aZjt95513CNygcXaeeelo8++yzea12Sl1t1146BW/DPd1WPC8+aJEImGfQWxIN45BVQDgdbMYONlhppZUC7ugUgHZpO5EPT3Qn2/CD/uNYJcc4VRip2lPKcg8PGhcMM85IMk18M025H8hrvwN6BPTCQDlr1/Qeb9Q222wTKaW8B7PnJR2LG5ADYFNq9XzrITBnoFNCFKEOa0V3/v9c5IHPky29RK46DdP4ra5mGbxawuOPPR7W7hvM1qVT2qZvMFyzM5UBkFKyGI9xQmnxjMnLUAFkH3n4kZaD/rk80AHvwmTy9xa0UZ2EgrZLj4GV8ZKXviQLVXHtwZTlWmutGdatE5JmRhgW73vf+8LsQnv67n4/12o5w6HUTQGrm6BylQ8Ny73f2kswEnx+p5RynQZDKcd7yed5p0CoM/rwAIAiDRBkOtRARFfrM3mSeCRNv62xxltCXzGopO8pqF+/6T+GUEopJ6dwvCOamSXIkfXPPEsBPMqA5I1noOJF488sHQVjjFvaMqMEIsvIE8b1ni0PIx50P6o1S+nKC8lT2V4uMA/ov3rRV08z9nnmLX8xa+VDU2PNUgi/BUZ5e1kz89sYPPbY4/L2sMD6zjvvnLeNJfPIZJ5eY4rjglFCWfJkGrO8spYjkgHkh/pTSnn3KuDSeBRXQ/9QgMwmo/E4B5Bvv+hLa47pZX3NW08Wz2yLGHBH/OhHse++X84ed7PLnDqdyqNDyV3XoqOl00b5AGuz8xxB9LFZdnF0NP0o7awG9fL4A+krrbRyxhDieHBdgUx6wfKMfffdN88G8+CiFeeSsVt0iLbgdb/R0LgVV8O0FOCwRdsSC5/4bbaEHBw9enSQaYB+e2BodZKTpazurpwpZovMjHIoWBJFdt1+++2hXqsxGLNmPn0cjufM3MCs2qQvOTA4pcmu7urpr/h+B/TlxSgaBATIfCCzzz77BG8vj6vlKQC1tAQ+y55yAL7EGUiUBsBIqYrrLgCi0cJowFlKrZtGwpSm/e2ROpQpvaUzlBUhYpmPgHHMFhAu0gsppfyxl0FL0VvDbXpIPkDTgLcd2MqrrBzPPduyMFrVKj+l1o0CZiCog+CVRVuF5AVFdAgGxdprrxNP/+9/cfLJJ4edKTAlLznDpkOWbqPQpeRRr5BS6jZ9ywbIdKEwSiJ5yn1frimlLEwNHIMvWv8ofN5Ry2x4MVNKgU/MBph1sQTquWefDTMmreQ9/jelasaFwSB/Sl3vI57wTWlIFHr3WFB9+KKmAP6zptfH0+7Ly6aUMqBOqYtvSnxfr+QFoxePzb/AAlOz4WdGfxlvUx88f2NMecaIwKfPRwe5xPCWl7GgXGUBGIK4knZWrsbgvffeG0CKJUVkg/JWWWWVvO75nnvuyRsGAGa8WhwcjG1OHAa49JS1IB9ZDvS512bXGvqHAvhIP+Ap/UI3lZrxEh4tv2fmilcYkwd/85t5KSM9yhBu1tMsN6WU9UZKKR9UVp7hC4YGPsbfJR4QFOeZdynxs3Ll9DrllFPy9q1NnTXfS1+a9ZF6ADiz+WbWYBYzGpZkwA2MEUtt0VQ7AP2CaeQVV8O0FEAjWK/EuqeHyS9yzWqGlVpeelvktgdYsjt+KuV1uupDWFL5gDrMxonLYYhvySyrGzhQGI9APaeF2cibbrop79IHs3LiNuVwp7r6I27AAD0BLnjJlFIe6Ka3CBQfsV5x+eX562GeHErBMhGDRHqDjSXFs6UjdYr42REMXoKBILNGFcgbOXJkjGwF9QPFloBIl1KXEk+pawcVxom26FjrA+WxLAYTsOJSSpFS6thMzIyx5O2YYGpkyyCYet91k42Wrtvp/hIoDKZFF1ssT+WbKuQZ0VaJvcd///ufePTRf2d6i5uRIP+MpJ/RtISf2Rk8UKYqDXB9jwdYzmZxSrnoZ3pMP+CNEp9SVx+V367yUTSMHJ7E5ZdfXnQOeIwRSXGgYY6sf+ZZClAujHsfW/PYFEIQ6uQEzzpQhO8oIbzTl7FBCVFOxj9vUCkXUBDwPllU4stVPGP9X//81zQnJ5fnrox2a4eXWmopP2c5WJZBRpGDFCDjwG/erFI4rxZPmfHpuc0AeDkpRDMZ6OSDSIa4WULjW15OGl5gvxk44mroPwqY8SYvzeT6bqjUbEZXf3MC4VXjQJ/rr5Kmp6t0Zk551N/7vvfm/b3NEnFMdZcPDwDprsaAMdWelpGBf6xn5oxpfz6jv9Vh3ALd7ul4s3G++3JfyrP0luEJF2ifAy19l6c9ZqHoJuu+XWGXlLr0PV1Dh9ElxkUpr167KMBY4+W+6qorcwRsSM7qE0CaccQQNBvTKXC0kolkrj4kf5WRC+vhj77wPYYlN5wOZhM5YC0dpPstqTIr43smQF8aM0F0gSVC6vQNh2+kjI8equqXRwMC6BFdaL5hSl1rtHldDeIf/+QnYakFYhI0LF8DxxIdxLT7zA6f/GTwDlGGPLLNMnVm+d28V6f4TnElnvDSQTxQptR4layV9aU0Aac9BBKFqm7PfejDUjeIWeuYz44PdgvALNJjHvU++8yzoS5tEQhMaa3Z83EGgSK+PeS8PPyNB7mcFsZvgnpxQkmGMXkNKFplmFbVds8xvvbtssungpIV1x5yWa06mvHiSijxfivftcT5Xe5d/RbclyB9CSWuXAlKU78AAUEqHlgwLSxev/gYFtBiEPoAF++sscYaQdhLn1LKJ1cee+yxeUcgPMaLz1NocPIqGpS8jdJri74HYBhD+k18DfMuBUzlG5/AjG80fLRl3NiRhiDfeOON83aopuLHjBkTlgCQDe0Uw1tCiZeXtxIPUib4kZFqNy2KiUIxm1nSlyvjwbpRBqyxUco0FUzmWAtqa17PtUWcWVBKspTR07WUV9Io51vf/lY+wE0Z2mQ5BtlFAVJ2HDHenRzxTmQM77yP8tHsJz/5cdhFh0I2PssWnuow1izHAeZ54sTV0H8UoPPITuCVLP1JS//iRwCGAwjA0Rpg1dKH888/v6MDiGxv8g5dznPN2/nQvx4Kfc/AG9MaI2Qugw8PKbuElFIwYvGYfEXuP/roo2F84GX8zeniubHit1nxkraU1enabF957r0/s+tnAi/jX4CdnmSwA4voYbb969/4RgBynHX0wrLDh4dxhr95cxkBHERkBYO6lA/QK5dRy1gp8YPz2v+tGvqSoRl/4D1LBg8++KDAexyjsBjAjx/o/k6BrJHGjCX+sNTZfac3ga8KDzCw9KfvowQYjuxiQDAUxTkwzxJx7fBbsBIADtQmzkDym4HXqb7+jOt3QM8Dz0uDGIjZ/rKAlnVSlADwzHs1btzYMMBMbQD1pkOs2dx1t92yEtWZr2t5V4e98pXZA276jbdVXTp/heVXyFPRKaX8XBwBxsuk/pRSLkddFCUQOXr0dvngKwKDMUHJ6mCg0YdCRRH72JYSB8QNVALLnrMEn7ZaVwdYUvzqVTbv+LBhw3Jb1I+5GC+mbQgWv8U3g/ooR4zm3rOUUvCsLL/C8jHfS+cTlZeHSOf9CoOpF6MCp9pLUOXErT+E6d133xO83QRmK2q6/wQX+gM15SGam/4ym2EgiWe06Ft0kIfHQl+U5/pb+wnr0jbvor2s8BKnrBLQizGibWhDYXgmjtcHsCcofbhlLRzv/EYbbpi3CVRXSl3LcfQtMDZp0qS8/zUvFMBFiVm+o7zSTjTBY54buN5FnTXM2xTAKxQOcGtrWLM7xsHYsWODEsC/loXdfffdean/xLdRAAAQAElEQVRA4dUm1Xh0CP/CUymlMI54AikvMg5fP/Svf4VyLe8rfNksR13rr79+Hu/kJM+p5+59OwJUWEpmnScZJM4sYdObLn2nYPxqk7FXnpNJ97TkBBBlHPkN0ANRFCTAYxzxQpJ1vjeYb775ghIE3ozf73//B8GoZogDSRwNpXxA7Kqrrsq0oGBLfL32DwXIbg4O/A18fv/73w/y1Awz3qRPtMQsKf42E+N3eyD/6V5y3TNp8RFQRE7jSzJYYBiSw3hJ2mbAg4CSPGS6Z+Sx/HhZsPEEOW1JhHg6lxEsbXfBuNFGuqE5rpR9/3335x3hjCXjFIDH42bgYADGB3rgeeNDWXjdDneXX3ZZMPK9F9637NZ7awc5YBze1yrfmKXrxNfwAgXIEHyz0EIL5+8WbXUNRAPm5MULKXu+I5st9+O8dN+eGhbiCOE4SCm1P86/U0r5Ow8YVd/lyLY/MALsg5fgmrbHA/az3wE9gAcUs6iLR7T59p4bMLxKOpRgeO9735cHC883D48rb7mBYVDaZYWnFnCmROysIB0ASkmy+IBwaVNKsdZaa+XDjKRXd0op1MXjRoGqc8kllwrbavIuiKe8WeDKXmihhWTLe8uqV7y04n0HgAkZANogP08HQJxSClY75QdgEwgKwhDvf9/7MhMtvfRSWUmLbwbvwutvFyDCzrOUUvBOfGW/r2SPhjhAQVvsZ80AEee9tYsXjYej5PdMmwkpApdQF9ceeBUYJ2ZLyjODjJDzxbcyxBsolDpjC2ixzozAK+VS4KxucQaUPAYFr4gprdJe8SWgkT5EtxN/+cupO9egGc8R2qIxmgJZAjp5X3mlMzVLQeknaV0F9+jEACttVC+vkqnVd7/7Xfm7DvQTX8O8TQFGuG9h8A1+shMI2cIBQVGgjnFuXPA+GovimsHWkBS/8VbiySweP2WSbfLbQs1UcAEFJW3zythkNFtGR4F5ZkYRb3cK2l1knrSdgvFitsG7UWglDZkI7JGD5K0x4Z15a8k6clBwb6cPMiallB0pDCHj03t7TgaU8al8yzIYHWYayF95xdfQvxQAYs0I4Z3Ci+Q5/aC/U0qBf/ERmSquvYVAsJkg+soznn16Rx7lupbgN/2B56RtBs42Xm7gmrMM4Db+lCVfpwAz0DHNctrveVTNEPDi4t/ynJMN/3pffJ9SysuAx40bF9prTBqbHHYcYsaDvAwdaX76s5/l81Tony9+8QvBSZVSF2BkBHmHJZdcPOh9413eGl6ggFULyw1fLvAdmSrAT7DaC6l6v8N38pFVsEV7DpgBLiEHO/Gd9HgPHsELHKbi2gPZLg2+YIi0Px+o3/0O6DGzKVUDoRNBgTDA0JRsEezyiONhtv4OuAMIU0rZy22gA506k5BZcskl8/ZG8jEaKD2e95S60uuwkr4QXpx0DIqUUo6Wl+K1q4UAxBbwKoH260zKiQdY29VvMItjRLj6La08hIh6tDWlrnpYp9ffcENu8xprvKUjoPcu6uAZcK+slFIQROILINUGViMalzqlxYDeRfqUuuoVr27LS0aMWC1e9ar/EzVdIATRqyksxXkP76ZOmdQByIvzXH3agiaea6P2iysC0VWbxJVypG2G5VuzL7weZhEc6tG0mnn7LXPSP4C5JVj6sJSVUmq916uy8cXzR8G44iFtafaDOtHDci5W/pgxe+Yt0sTXUCmAAmQC3iGHKAcAvgm68b2x0u4BlFegZMgRcsDvEvBrkXF4WRplleedrq961avyEjIGKJ7lNVIvHu8u4PdOZZW4lFIY58Zu871SSqF93p28TalLhhjz2qrNgudo1CxPemOUPKSglWPclzQ8wmbYOFXs0lPkxfPP66UfKYDn9L2+BOSBW7xZmoB/yVi8V+KaV7qIvC79S+8qj8wVmnzpN12RUhcvNctRp/FlG0Ped15yZdI5zTKa9+qhY5rltN8rF/agc9yX5/hY2drf5HtjgUPJeEcP46vJn+7hDc/wt7SLLrpYxiXKNvtg2Y4zarbf/pNZD4mvYXoKDBk6JB8qpd/RE+8NGTJjEBWPkMn61317LWQR+UwOpjQ930kPN8EjsEyTFzwrAe9Io6wmJizPB+o6Y9QaqFY26k2pcyc0kgya25T61taUUvYEsxwJh/58AcxrWnzXXXeLYcNe2Z9V97kug2fUqFHxjnXWCR5Cnrz2zCn1jdbt+dp/W3fnewgeKAAjpdlTbns99ffcTYGUBgdf8OyvscYacfY5Z+cdFwaKqin1To+Upk9TDGhLdcy6ths6A/U+td6BpwDjwhaQQLEZ005LKPqrlSlNz7vtdac0fRpL8OgThoCtFumy9nzz+u8UKR9Chw762nXmw7ydc64D9C/G7jLIebZYlf39fqxYHpfuppb6uz3d1ceitpYTsGeEdJduVuOVbU2kJROdlgDNavk1f6XA7KQAAAwIb/yhjQPvzs6y+6MsCpyX9otf/GJYytMfddY65h4KmEW1pIW3dO5p9Qst5WE2K4W/eZxfeFLvCgXMglgGJfQ2w1Ly1GtnClRA35kuNXYQUoBgHD16dJjGnVPNs5TL8h7LCFJK01VTIyoFBhMFAAbOAEaoZYODqW19aQsjxLJE3kvLHvqSp6aZdygA4JktteSF82lue3Pt992BJUx4fW5rf3+0l+PMKgFLljg3+6POF2sdFdC/WHv2Rfpevh8AYubU66WUph5qMqfqqOVWCsxOChgPwI7r7Cy3v8oCdF6kiry/SPiirgdf4++58SVTSnnmLKXqHJob+29ua3MF9HNbj9X2VgpUClQKVApUClQKVApUCryIKDDrr1IB/azTsJZQKVApUClQKVApUClQKVApUCkwYBTod0DvIyinkzqcpGw/aI9Ze7Xadq2dEtJ4ZvcRX7nbs9hvB5EI7pWlDGW352/+driJ3RRs0+jAKGU3n/d2L712OOzivvvui4cffrjjaXm9lTMjz9HK8cd2g5iRfDVtpUA7BebF32SDcUp2zMj72/+abLFLxYzka09LJhnDyiK72p+3/1YvudYM2i++Pe2M/tYWZXX3TuRvoZf7vpZPNnk/clFQB1nZ1/zNdNqofcroS5+pR9p2ejlgSFnNsuf2e/rLe84oL+hL/fPEE0/MMgmUoSx91Bt9tVNabS7B777k7UtD8aqx1d4O7wsPNIO24NPeylUWfUu/wwn0vfJ6y9fTc2XqO23tlA6fo4s0nZ434/C7dIWervj/xcjvzfee2Xu0xwd4zrUZxKE9mjbjm/clTaf60d3zTs8GKq7fAb2Bdcopp8Q3DzkkHxL0zNNPx+RJk+KrX/1qOFWunRBnnHFGPvXTgQ0PtwD0lVdeGb5690X0mDFjwiFFDiYaP358OGkVs7eXgej2gXXgkIOhHJC0++67xYknnhj2QG5P3+m3rRJPOumkGNOq0+EnTtXz5brT4xgHnfLMjji0cngB4YI5Z0eZtYxKgRc7BR5/4vEgOxxyQ1Ycc8wxUQ5f6u3dCfnf/va3We7I53dveTo9pyicfuqgvM9+9rNhHDvZsqdx/Mc//jEfFqfNZJvgED55r7322k7V9Dnu5ptvzqfP2rO+PRMA84tf/CLUJZBrQEZ7uvbfwI8TOtHZqc0+KHfv9E5ytz19T7/Ryzs60MXOPQ4RuuGGG6InQAXQOFwOvchm9HJokAOOJk6cGE7g7onePbVnsDxjCNJf9N7uu++et+51Ojl69dZGIBZP0a8OSOoOVHYoZ7qoG2+8MQ5p6W10djgY3p4uUSPC87Fjx4a+0S/yuXfwDx6c2XGlCueE6HfjtMkf8IVxXw6JwksCXsL/8nYXALnJF0zOY6TgBO2mgxkP3eXrLZ6Rqw32029Piz8dWKUehxyeeeaZAZy3pyu/GRgO0DJG5RHw+9e+9rU4/vjjY8qUKXPcyVjaMjdc0dcheXiuGWwRDjPaDvWOO+4I+PKwww6LkkZ/SUPuTpo0Kdpl2V/+ckuQMeeff34MJvnS74CecJo8eXIcd9xxQRk88+yzceVVVwUmpVQKk0gHQNs+kHJYYonFY9iwVwSB//Of/zwoEfeEhlPYdIZT2AguA6iUA+A7ndABFU4rpKR8ZHPxxZeEHVMoWoZEd51CaFIqn/70p+OTn/xkEKzyR+vfOeecE05FVKfDXboro5V0pv9jGHRgUMx0ITVjpcA8RAFK/YQTTgiHFBHGxi+lBww1ZUN3JKEEyAynFQIuBP6Mjm3pyYqPf/zjWdY5GOeb3/xmljlXXHFFt0rAITQUvNNfr7nmmrj66qvDO3BGAMxAQRPAdPcOzXjpb7vttgxUlH377bdPfayd2oY+wAF5Ssk5wXNsC4y1K7KpGVs3ZjuBEOAHsCIrgTRA2ntThuRvK2mv/7Xx/D/8IbbaaqsAxtAB/TfYYIOwj7fnnQp5+OGHMn3VTx+gGbrTEVtuuWWWz9dff/1cC3IAcjrAabunnnpqBmz4iD7Sb51o0ozjUT/mmJ8Hfj744IMD7zWf9+Uej/zpT38K/ewkz1tuuSXoUsYbHaiNncrRh/hN/+Fj/XPZZZeFE4OdAkuvdZe3U3ni8Jgx7F2+853xob+bZcAUnhkvMMUPf/jDELw/I0gZnQKgfNBBB8VGG24UDFvl+FAbtihjQZpOebuL01Z58LF3ZhA106pj//33zwa8Z2iJxs5a6W7cMCyMr1/+8pfBUPP+jCNg3snScM4fWuOou/HSrH9euIebjj322NAH+MEVfck222CTp5ylnLuelTR4RhryjYEIj6IXXiM/DzjgwIxZe3PQyNOfod8BfUopUkqRWqF1k98VQDZ4Ukr5Ny8CArNCX/GKRbIi+vCHN4+XvnS+VpYUDpzYdrttg/fM4HNlWTkIiKU1YcKEwPgGFIvXs8UXXzxbX9Irm9U2atSo+M1vfpM9HurMlbf94QHilbj00kszQFA+75XgXhkTW54gAwqQ0OHlSphSiNqhWM/8ZoGrj/IT3wzSSuO59OiCPil10UZaaXgTlCOt3+L7GghoDKp8ebVTfZ3a09cya7pKgcFAAbwNSPzi578I5yuQBZQfAERhGrP4vru2Gg9XX3N1ENpOLDT+OQ9mVEFSEt86/PBQF6PgV7/6VfCiMRaAnO5mBlPqOmRljz32CIqIvPIOX/rSl/LBUQccMC7PbHbX/vZ48uGss86KvffeO89YeE6euArkyMknnxxAPIOHIQSs2WZPmwF86doDwEEuepf3vOc98Z3vfCfPeJKt3tdpjUCMuvVJe/7230Da17/xjeydBHLU7b1tyclZA1B2V05KKTbaaMPggUYzYJ5y3myzzfKsLQOh6Sxqr3sw/y78YktPIIPeMSNdQLX+66n9+PDaa6/OJ3DSiQAMWd9TnvZnnGD0JRryXOobxpqxAvR0N/OVUtcOLwxRgBov09UHHHBAzDfffNlw41Fur6+738YSY837a8P//vd00I/N9N4RiLONKx5Qr6C9tj1upi33ePmYCROy2TFrBwAAEABJREFUoeG0WXzL4Uhu8Oy/853vzGPR75KntytdyngxW4V2wHtKL+hw72LcnXbaadnIN27wrbrwMeOnJ353Ii1+wO/oahwy+hgtxqXZiO7y99b2/n6unfAIGYun4BHBfbMt0onrFDxrpi33w4cPz7NK+gAfkG34x5kATgbmBHZiMQPQM2kE8tZpyM4GWn/99cN5H9rIuWxlBpCvznb+K/UO1LXfAX1PL4o4iIbRWcv2Jz3ooIPjwx/+cDSP15XutUu/NnSIzlhzzTVjm222CZa5ATmxBbB5pAhDAgQD8D7xClAQyy67bHzgAx/IS3de/4bX52U3BEGntlF0rHR74bLWRo4cGUsssUQ4DGHdddfN0/LqVJ+2s7QNTHlMtROAnj388MNBmBpsvGH77bdfEEo8TKVe+S+88MKQZ9y4cWGwEzZNBUxQsMopUIzFW8NCNwBKOb1deQ3QaNKkSYFBv9FSpGYZKHMAprf89XmlQH9ToK/1GR+XX3553HXXXcFDSzYst9xy+X6ZZZYJ3k7T9d2VByAx3p9++n/xhS9+MV75f/+X85Al3eXpFM8jedHFFwcP80YbbRQUCO8bmUHRa1+nfOLIN4qEQUK+rbPOOtnT7PC3O++ckmc2petLII/IE2DMPs/yUESuAi+7GVMAgdGDVhwjFNo+++wTzmWQrj1Y+shj7L2kI6Pl1W5032nnnWLYsGEBsKFpe/723/rETAojipxW7tvf/vbYddddQzzPMhDUnq/8XmyxxcLZEWim/QAd2fi+9743yGJAEGAo6eeWKy88nvU+jKwll1wyAGR79wOB3RmG5f3onIceejjMmMhDpyizPO/tilcYt3SM/tC3xhEgZO9wZeGF7mibUgp8S0euttpqoQ2bb/7hWGON1fMS257GQXvb6CaG6UUXXRT4FW/S7c102pNSCuAdLwHI723xgEBvN9OW+3vuvjvw8mtaPMSYNE5XXXXVPGY33njjMIvPQO3JqCxlleudd96ZgSSHorYAh+WZK6PDrJJ96i3hXX755QPf4n1GOBkED0jbKXh3NMXva6yxRrz//e+Psa0ZNSsG4AN6nSzslHewxcFeMB9awT/ANUxy9tlnBdykvfCNZ2YfOgU8iG7SNsMiiywSI0eOzHIY5nOeQVkirV8dZkdOcUrgZ2nwuf5BPzKR3CSTyTJLxvABPoZJjY9mfQN9P2SgG1DqTynlaVGMaFDxSACtDmVwX9J1d7WXsYFDgVJSQKsOAFoRn1KUpuRPKYVBeuYZZwbBD6CXZ80r4JtSygOG0mg+c7/CCivkmQLGBCvOQDSVw9vF4mNtU0ZmCT75yU9mLxJPIY8+ZeVdefQJRN4Xhglr0ro9z1mChFZKXda9vAatqc/z/nBeTJgwISxLMn3ZkwDQVgED8qiYWuIF3GGHHYIBwiPh9/77fzV7yaStoVJgbqMAIWwa1CwegFfab4aOAqTwewIRgO/kSZNjtdVGxFtaipKQv+66a/PSF+OwlNfTVTrlUDCcDtoiPfmgDTyeFIaxKL5ToMB4Us3CUWqUNMVH8VNAnfJ0iiNXKHsyZfPNN58uiXaSl5QYucCrSTa8ZOjQbEQANu2ZtJvRJD0gz+ig8Eo63tctPrJFWDa08847B9BSnnW6oheaAOxLLrVk9oZJl1IKTh19almkdxHfKWhTe/zw4cNjy622yrO6jALltKcZ7L/pMO3WD4WOTs32bngIXbp7B/rA7BJQY7YCmOGxt1SjJ1o2y9M36sCDAHLZD97Vb2mNt57KMw7wMX7mqZ4y5a644447gwHIuaaMvgRtYRTQq5bBwAXt/X7DDdcrKhuBwD9AZlYOj7enlVC7b7r55rirBerXXGut4I1tOtDwNboBnIBmSl16WN6egnI5D+l/WOAVr3hFNOvXHnRbaaWVsuFQylpxxRVD/zLE4YIS335VltCMl4+Xnrwh5/R/8/lgvYfVJhwzIfSVwOjk7Nx22+3yqgp0IGvgk+222y46hbEtY6Y349b7c6bAOvAg2YWPxZdABkkDi+l38muBBRbIjz2TT58y+uTFk/nhIPkzKAB9Sl2DxKDRoQQIy5rlaUB1olU7M0tjILLCCUBW97/++c885U1o/F/L0yZNM0hP0bOem2C/mcbA8JznSXrPDBQDUjtNFetoHatNBjLhR3kD8YwSCpgXjDJmsFjTCUSz8M466+zsqbjhhhti//33D8KX58VUN2tQ2SmlPLWI8b/+ja8HZW8d2HXXXheAP2FBYWtP9OGfthKud9xxR4wePTp76Q0gNDrllIkxZcqUPpRSk1QKDD4K4G3AF/gx7koLCWX8je+FEt+8Gr+muilaHj0G/BYf+Ug8/PAjeUkKYNJM3909+QO4KM/YbKajbD1/+OGHs2xqPiv36jGeP/OZzwTgYl05Q5+ne2xLcVHcJW1v1zVbs5dm8kaMGJFlSHv6f//7kbw8kfcL6COvLJnZ4qMfzeuk0bM9D5lEeXoPoAWwak9DtvHMev8iN9vTlN+ec6gwBG65+ZY8Y/rss88EOcsoUA9ASLaWPH29AkhoTk7PTP6+1jOn0pH5eBc9Sx3ohbddPcdn5VnzStcAhmu0vOFLL7108DTSZUA+ejTTdnevbONFXyy66KKhzpIWH3puvHXik5RSeA6gmSHHy75r4eXnwQaW6MRSXm9X45HeM8vViefkv7alExnsHHG8toKluz7IZcxI0wzaTZcbc3R8JxwAuOFPtGvm7emeAWaWnYGg/9rTqg/deNqbfcuA9Zt80Lb2fL39Nt60Vf+SQb2lHwzPved///PfPO6thOCB58hce+218jp132Dgdw5RoL5TICO9e0/vQ45wVpBfnBud0uN1S6tgLMZRs+9WWWWV3B4OYvqlp7oG6tmgAfQGPq8zpcuLRejwRiP+jBCHAaCsR/797/DBbUope4g6DdS+lGvgUTQGWUpdhsddrel8ipVAEjCadVkEhnooENOighkDXjrMYQ0txpTOe7l3NfB4TXipeNtNvQH2FLpZB+9DkJ599tnx5xv/HMssu0z+jsA6SvmVb+3cpEmT+vJKOY0y5TO1bqaCh44RZXCZkvI8J6x/KgXmIgo8F89loGwcGrel6X4X4WzMlPjm1TjkVABUKHcgknKknC3bsCykmb67e2NHHa7AQDOddvjtuWunIB9lD2hY6qNdAAy5YrrX0oNO+TrFpZSmgjDlRtu/J574TwCFHAjAFm8mQO+9zTpaatGej4xQTEopyyGyye9ZCZwulpTw/O/fmiXkYLB+mXJFw/Y29LUubRN4+Wa2jL7WNbvToTMjBM8IpXzvgSZ0HZDid3lWroy/s846KyzZXHvtdfIsBTnPsOM88p2J8kv6nq7PtIyraKk+PFjSpZTCeEop9bgLkfRAEj4W8K58HF4cUHShNH0JKaVslHpfITr8s1TLMhlLNoB6y0gtaQESeV07vbOy0JKO71DkTEWllKaOu+jwz/gXAEN9WZLoZ7+1U7tK/Ixc8Tua4/kZyTdgaVu8hRZwH4cu2cMQ32233QN/X3fddVnOwEYMw04BoIeZenoHGEtQj3Ggz9vTw1TqW3311QMmaj5PKfXKfzHA/4YMcP1Tq8e8wKsPmIBMHezjGd7sqYn6cMOyVRZrHmMQQqYmKef27NJRZoA0wdn+3O9FWlNlRbkaZOIABTMBvB7WE5q25uFS1pChQ0KdPA/SDRkyJKQDEKyZw5SW0liWQ6Cl1CUQp0yZkj1SGMmAVo9yMJ8ytJVX4/HHHg9eLGved9ttt/yxm7oJcAJTvt6CsqRZtmUYFCGmDh4IV4OopJGuhkqBuYUCQ9KQvGTDWG0qNDxNyQ0dOiR/kNfpfXzrwmgmQ8ghyoWhbnwDQNbukkud8jbjjF+AJaUUT/3vf9F8ph0ppSwjUkrNR1PvAR5OAh/yAbW8ku7JGssDGe7dyauphfTxBoAAKkwvlzWlpqJ564FBjpX2d/Z+5J+8ZJJ3aq+OR5c8Yozoi/bn7b95f3k0N9lkk9as48T44hf3iV+f9OuwxpWBRU4NHTq0PVuvv03Vk/36Y0hLFveaYRAl0N5hw16ZAXN7f3M06Rd0ka692fjV8k9jwIeTdI6tQM0+8d7y3iujPV/775RSLLTgQjHfS+fLW/c19YLxJD3+SWl6XpY2JR8sb5SXTnDY+ZATL1u6YIxZuy6dcmZHAPbGjx+fvxkYPnx4WKJjiQYesvQVTzfrwVPLLrtsNk7Qpfms3KMzDNFXXi75erousOACWU7R283xY9zos/nmmy9Smp6mPZXpmbYymnj+OQDEzS1hueWWC0C+tNf3IuQCxwY5Y6YFH8M9Jfgt+HAe/ip5269kEAMP1rOMEj5sT4MPOW44NH0jQma0pxnsvwcFoEfslFLoMF5iH5GZlrPcZf/994/uBlo7cQ0GgoxCBOZ1GiBtaYlOak9PoAHW2267bVx9zTWhQ9vTvGWNNfKuEsotQhVAtxzGx2Y+fF135MhoClVCgqBNKYV34/1Sj7VXBjBPlA/JfNhT6pQnpa70zTY0y5X2JS99SZ465U3Tbh87WStoeY+1ss28Pd2nlLIQa6bRhubvel8pMLdRAA9TAmQBYF7ab9xZJrLIIq/I67JLfLk+8cQTweCm8JddZpmwhvzfjzwS/3vqqfCbTAGMmmWWvO1XbVhkkUWyN+fR1kxh8zlwSVlTuNI1n5V7Y56Msb6WV9WHb2SiZTfyW75H6Zf0s3I17awtlscUmQWgmVbmUADKyZ1mHSmlIFe9o49/C7BrpjGTQEaZZezLzEZKKStzipkR4Rsju3dsv/324V0BMgZEs46+3F977bXZS42eM5O/L3XMyTSLL75Y4F38WerRH8Al8EbHlfjm1UyHWVuzSwssMH/gZUtQffOlz4F9xk4zT6f7lFJIj//xQkmjDUCu38UR5L5T0Eb14mVLtCyrMHtNn1qvDGR1yjejcXStsYWPGZ3yp5Ri2LBh2cNrbKOl+BKMQYayNEAjmpZn5eq96Vhtdl/iZ+X68pe9PMgpILTZt//+97/zklorFbRtRuuAU5TJ4J7bAH1KKZpjFI/hEbzH6DHjBJQzAkuwnMu9zUs6yaFCv9tvuz04PskRGJOMK8/KFc60xE+/8M4XHirP54broAD0hVBFMFhH5sNPhPeFPyDMS17SuWJ2HS4YyDrTFpSmaAkOg1TH8ASYQrHWnBCUXn4Kn8eNkpb3la1Bn9L0FjFvlcFOuVCkBAKFy3ozYJTz2OOPZeBeylZ+CRhRPp4RIN60nx1uvJt3KgKE8sZkBC0FJr+6DFDvl1IKXn/CirFiD2DLeHgfeBgI1zIY1KkM+ZRTQ6XAvEIBYwB4ABKsnzUGjEvrak23FtnQTg+KmuyQ9wc//GH88le/yrtQuR7z85+HNfWWnzDOlWmMGZ/Kbi/Lb9/mGKvqLEYAzxkvITlHYUvXXUipSxaV8tXFIPFbuSmlKG0oMqS7snqK107y5JZbbkZkOhoAABAASURBVJ66e47yKDdyzgwhWdtehg+OgWRrXSla7dM2AXASZ2cZYBDwp5ilUXZ7WX6TX9bG/uTHPw5rVXnml3ntMkFGq1+/6FtpO4WUulSZ+gXyz4fEdMLiiy8e6667brczM53KGyxxiy66WPbkMpwK8LNMBVgn93kx29tqRgl4EW9G58QTf5l52TImutT6Yc4yhpM0+ga98LXfzZBSiqWWWrJlBL8szAzRlZ5zhtHNKaW8u1BPfSO9oF8E9RkTeIHRCDi5xx+eSTszgYFinHJ02ZlHXd7J2CYP0Isuby/beFxqqaXy+/Huo7O80nlPS3+9u7IAQs/ofTRzL92MBuWQRVYg6AvlCJZDeQ+GDzzQXbkppewwkEcgC+SzOyB6AqQ95Y/B9q8l7shotNA0/MARq+/0DZlAnsBRnAXN4DsRS6sst0IL/aJ/3CtLuPW2W/O3gWYiO40ZadQHb1mOwyASN7eFLik4CFqN+DqxNIUHyMdchPExxxyTd0zAtJ7rLMoaSAeQPfcFum0lDVhea9NtALe1VTraVB/vDy+caRUfnbG6AXNpDHZltwcf5vpw1GCx3aQyKAnlEI577jkmzjjjzOyxUvezzzw7TREppaAYo/WPkrQ/LO+Jj88wLwFGkFk3b4Bbw2odrzSmJF1bWbPBQMkZ6CxSu9oQ8rZ6Gjt2bP6wleJDI9OpdqvgcZB3mvD8D/R+/nbqRVwJUyPrTaXAXEQByszMl6lb48j4AMTtbIC3radtF+jGjDSmdi15M+bJhZe9/OUZTJENtjWjICdMmBAPPPC3+N3vzszbywKinchDKfgIkZzgNOCJNCZ5knxXY3q5Uz5x2kN5GePCiSecEOSOD7oAAW3hieRNIkcot6bsVEZPAR3Kc+/GY3rjjX/OB/BoJzBOpvKseociv0oeV/TlTEgp5f31LQ0CfH5/7u/z8gptVTZZTA5fdtmlmV5AtvztQZsA1SOOPCLIZu3gRCEPTX8DKCm1tH57xud/k6vkMnqht9lTswMUtNkNnupO7/F89kF74cQBUnkieScZhOhyyy235F1BgNFm49ER2GdI6tdpeLnFz9Lbmm+R1v3vfve7fLYBYG5ZlyVnzbLcp5Ri+PDlwjp8sx36lU5CY/m0je6ie6RvD0Aw0EpX6xtGM70mAPNmq12vu+7avA98MUTay2n/7T1LKM8Ypgw/7bQTjjFk7bx3k9YHqsZwSV+u8pkJAuKMJ9+OnH7G6XHeeedmXsRLjGhL0sgXhrkZJHwKPJZyuruqu/2ZfsCXDKETTzwxe4/pbeUaW2WMt+crv40V/ICm8ljOZMc69LOkRH5ll/SD/aqt1113XXznO+ODLMabMBsZYrYQ3dGMk7ZTgL2MbzOYZDTZz7FQ3vu+++/Lu/f5bpBsL/HNK0OYoYmHOCGazzrd4+1OfdspbX/FDQpAX4iS0rQCm1fFIGJd61wWlAEJ0BMMBLYv5/fcc898WqCOsA7T+k/pUkp5b1dxPEqsb55/gZecUrQW3fIe952IbiDvtOOOYS0tRmABq9PHsOq99trr8h74jAmGw9P/e3qaYjCq9yD0gAp5fXEPjFsiwxvAm6DtlhdR2NpmrT2DwUwDZqawle/7AoDE9wXKsiWWKTZGBy8/2gAxBGYnAT1N4zr80BcpTdsPHZLVqEqBQUsBYNn44V2z1pKcoPyASzNuBH+z8WburJ0XT3a0ywLxgK1xN3ny5Ljqqqvj178+KcgChn6zrHIPJPA483ADCMaqZXGMcktRKKCStv3KwAcW5BE+veuuAZQMHz48yyEgiFzhHVcmkEw+tJfTl9+ms8k/HxKqk1zjuKAMv7LffqH9ncoB4AB6Mgsg41AhV3fZeZcA7ilO8hYQZ6BccMGF2SgBBjuVR1mTp0suuVRYxqgdZjR55qyRRc9O+SJSEFfAkL5Gr1132y3Gf+c7Ec89F5xC+l/5MRf+025gE4hBD991AKs8jR/72Memm3UAMBlDQCf9In/ztfUb42aVVVcNoB/oBcz1FaOombbcM8i0AXjH82g8duzYoLPoxfY6Sr6UUqsLnstL2YwF+YxLH11rh77Bd3j3j3+8Mht8+rHk7+maUlfZKaWpyZSpPb7FY5Dqd/qR8WOJLD08NXHjxnhHK7xsjFnjj4933HGnfFbNIq9YJOhk7y+b5bvKRzNjVVxfQkovtJVMUR6aMDrwuPb6rk4cvu+pzGuvvTa8k7Ty+QiYw9C9pctLLrlkT9kH3TO4A49feOFFYezvvfdeeamz/iQz+9pgspwc47F3Lx/g/Y+//yN/i4Jn9bf49sChg4fQDn5sf97pd0ov9Gmn5/0d1++AHkD2cc7xxx0XS7SmQikma0MpVEqgSQDEJUh4uQgQHiPeGp4YcbzzLFQea3EEnbJM85ZydIy97J3+xUtgCpIg4eXgZaCEmulLvnJNKcVrWu0kiAxiZRx22KFZmavTNKa2rb322lm4bjpq03xiIqFi0Aq8dYTEj398ZHgf6+kZKLwdygAW0MGVdfmdljJCo5/+9OjAmNIC68oiBLyLvD6cO/jgg4KFbgkOxUpBf2ijjYJlSxCX9yjXlFJeuqPMfff9cksZdjGk+ikLNOXhTKkrvuSr10qBuYUCZMyoUaPy6Y4OcqMseXoB1U5jnaE+ZsyYfJAb73mn96RgyQtjjRefF8yY7JRWXEop75JgrAK42uCeHJAvpc7ji3w777zz8kE3xqIw8ZRTgtwhG0aPHp3XA6sDSKJ8GPxkg7ieAg+lLeDIw5JOPjOD48aNy3ILqAaobas7arPNplnTWvKUKy/Wji1nB1nKWUGuCWQWWUxWkeFkEo+h2UX1lfzNq3eQ5ufH/DzQCL2UgXY+bOwun+n4E0/8ZWuW9IygC9Dr1IkTA81+/otf5E0DOEJS6kzvZhsG4z36MeCcBIou6E12A9Y8yu1tRke8T69Y853S9O/NScQQPLHlGaabgFkz4pa6tpfnN9rTzfSSfmY4fbelo4wp8SlNX4d8xgh+Y3iWvtEuvIxn6BuGrTbTn8UTK29PIaWusUX3An9NgIZXOLPoauCWbjZut99++/wtQHflencz9cYYZ6Ed6TjPjjvu2JjwswlBv5Ir8qM777olZ373FvC99+VQaKblvAPKjTXjjtFAvug/uKWZttzjd/0ALxWaoufEFs/Ly9FHVuGbkqcfrzNd1TNPP5OXbhnzZAgDRR/qE/KjrwWjqfFx4IEH5m8U5Esp5YMFOToZwuI6Bc4cuBLfptSZp+WDlcg2vIwvUuo+rfT9GYb0Z2XqwmgYztp2AJSwAD5HjhzZccABpQY7oebjLUtwdAqClkAREAYGGGKrpxnEEWLSU4isWp4B7SBMmmk73aeUMlhn3VGKo0dvn4E5QUggAgneQ15tYFFiLL8F9cu7+eYfCULGqX+UunfR9uEtz1tKKa+JE69tvHimOc0smDYlcKL1T1k8kBQ/gbj11tsEgFGEDWv0vvvvz/vZq7OVZbr/AIwZA8K4PNR+6bXd+t6UBg+TljbWa6VAXylAyfMuE7iUvuUH+LpTfsrTGPNdi7HRKY1xR8YYr8oxPWus8ip1Si/OmDK2jXdtoKjJB/GedwoAOsOerCqBbOQgALqa8opHVVkrr7xSj8C71MPLrf3qKHGuKaWs/NZdd90s16yxJhvQ0POeAtqRowAOuQpworX3JOvlTSnF31seMjTUJ+I6BelXXmXlDJ6UhW50g3fslF4cHUJmFVq5eg86w9IF7Utp7pZl6EI24x8yn34AKlOa/r2k1R90ZHe8qV+lwWd4wvKNl7/sZfmgRTTtFPQBvgF29PFHttgie+jFd0ovThu1Q5+UoE6639gpQC2llL2xZtQ4k+TtKaSUwqyAfrckqdkG93hPOznhzD7R0UU/9lQu/jTG6HjOMmN2gw02zO+JZiWvGSczc6uvPmK6jSVKmuaV0YIfyYJmvHvyhtxR3+jRo8P742nPOgXPpEHHJk3RAlaAl1Kani86lTXY4uafb/4gh808ffjDm2eA35R3fWmv8e7sDYade3lSSnlJNLmgL8R1CvqHfDQmOj0vcSm1nLyveU3oN7gypcFD7yGlkfX64qCAqSuClBeF0HtxvNXzb1EvlQKDgAKMZgCLh7w34T8nm2usWzIIfM/Jema1bPRiBO2yy6fyrMWsllfzzz4K4CE8vNvuu+cTSmdfyX0vSRsAW4CWk6zvOQcuJVDNuCqgceBa8iKo+bmud3DegSXDXb/q35mhQAX0M0O1QZyHRcsSZWm6H8RNrU2rFJgrKcDbZ2mO9eE8ogP1EjyJPOMLLrjQQDWhT/Wi0VprrRmjRm2aD/nrU6bZkKgW0TsF6Ai6gs5oeqF7zzn7UvCq25qVN50HevaVPGdKslLAbMlKK608dcnqnKlp3iiVse97HMtr8OO88dZz5i0roJ8zdB2wUlPq2l/e9OGANaJWXCnwIqZASl1jDFAdyNcEfuYGBZhSykB+oADjQPbRYK87pa6+GWh9gTfKEpzBTjMGiLGX0uBZajHYadZT+wB6szO+fxxAedZTE+eaZ0PmmpbWhlYKVApUClQKVApUClQKVAq8aCiQUgpAfqCNyhcDQSugfzH0Yn2HwU+B2sJKgUqBSoFKgUqBSoFKgTlEgQro5xBha7GVApUClQKVApUCM0OBmqdSoFKgUmBGKVAB/YxSrKavFKgUqBSoFKgUqBSoFKgUqBQYeApMbcFMA/p//OMf+fCTn/3sZ+EAgE7BwRNOrbMt1WOPPRZON3OYhYMULrjggnDimmdTW9PhxulnDnk4+eSTw5ZG0t9zzz350BiHoThk4cYbbwynzXXIPk2U/Xa1V1n2kX366afDIS7afsUVV4T9ZafJ8CL74eQ0h2Y44Oauu+6a5u2eeOKJuOmmm/LhLOhx7rnnxgMPPBC2nJsmYdsPZTpx8LjjjouJEycGGs9NdHzkkUcCb3ot7T7vvHMzPzvR0m/xszvgu0cffTTQri98W+qXdvLkyeFQsUsuuaRXnneK4Z133pEPJXKwyZVXXhmPP/54znfNNdfk0w9PO+20Xvu41F+vlQKVApUClQKVApUCg5MCMw3op0yZEoC246idvNopOGkNgP/73/8eTqZzeIKT0aR1aMNee30u/vKXv+TjoTuRB4A58sgjM4AB4qV5+OGHwylijjd2CuS3vvWtAE4Afc97CoC/9sp/2223ZQPBMcHinPrl2Oye8s/Nz4BWBtZee+2V6ffnP/956us8/PBD4YQ2X5o7oVb/OADL4S5AIAA6NXHj5qGHHsr9usMOO4RTOD/72c/GDp/8ZDAGGF+NpIPuFthlbOp7xgj+0f9zmh/Uc8cdd4QTi51mZxz1hTjyAfH6z4mCZ511Vo8GqHGiv7feeutwCqrx4rRE49AzfeoExcMOOyyMhR7bUB9WClQKVApUClQKVAoMagrMNKB3Itmb3vSmcHqi070WWWSR7HHndXTamj2aPVth+eWLub+FAAAQAElEQVTj978/JwDzP/3pT+HkPyea8f4C+4ceekgAV52odN111wWw5URVJ8X6EtrMwMUXXxz//Oc/wyEUu+66a4wYMSKfstqpjGacehgXygA4gSSgVJx2+91M/2K490685hMmTIjx48eHGQ+Azvt7Px74iy+6OL73ve8FT7vDqOwJzHPtGOSvfe3AfIqftO3h1FNPjR/84AfB27/qqqvmren+cP752QC7++6725MPqt94ADjGX2iicWiFH/AmfhA3u4M6zA6hrdmS+++/v9cqtOXss8/OHvWrr746875TFZXVKbOZhXPOOScYvFdeeVUstthiMXz48LjlllviRz/6USjLwUhO9GQMa0vhh07l1bhKgUqBSoG+UqCmqxSoFBgYCsw0oF955ZUzCDzhhBPi6KOPji222CLsJevUuS9/+ctx/PHHh2dbb7NNXHjhRQHEeHbMMcdkb7DDLJ5++pm44IILA6Buf32ghLeUZ95JiAAJYHrmmWdmQGMf2NVGrBabbrppLN8yGlJKeSkBo+HU006N008/PW699dZpik2pa9/YlNLUAyHsKZtSCtdo/LM0Adg5+TcnB2+ougEoswZTWrMTF1xwQairACEA8f/Zuw9AvYoyf/zPJJQAugYIvQUBAaUEREFACEUQUAkIGiwQqqDIRkVFioQmqKiIwsLuogGlCVJV9ictiIIrLYqr7F9QsCAo0lxQ+v985jLJycn73nvT7r0JJzD3nHf6PPPM83yfZ+acc9NNNwWvL8CsKscqeFV//OMfZ2NHXDMAj9IBNQaHdG0zZtRn/GjBqztlypRwffTRR0OaXYW777671yMT+m0n5ZhjjokCslOaPv7nnn0291m9DKavf/3r4UjUuHHjspH0s5/dlo/R6Fc96AMaA8CbbbZZOPrEu+/LeVOnTs20Qat6GffKMch+8YtfZA8zel1++eW5D8YpMCyuuOKKQDu/lSuBAQKA//Daa8PcKO+4UEk3H+bt1ltvDfOAvt///vfz8TBjlA9977jj9rjnnnuyMYnG+sND793ieME7kfHltVU7+gcM18fjXhlzAJhfc8018eCDD6q+16BuxrBMxlLu/e4U/vnPf4TjMgxXfIIHO+Wrx1lrjpWh06abbppBPCD/jne8IzbccMPwejAG+Lvf/e5AO4ZZ66WvU7C9bynQUqClQEuBlgLzFwVmG9ADPsDIq1/96nAF5g09pRTAtk85S1t8iSUy6D755JNDWGuttWKZZZaJkSNHyt413HfffeEcM2DFO6++Sy+9NE466aR8tvv/nvq/OPOMM+Pwww+vQO59+egOj+uECRNi7733jr332TvcA5rO6ndtqJEAZAGk6lX+gx/8YOy99wdzXby5QDfA6XjJxz72sQwKgaJLLrkkHCM6+OCDKwPm5nyMCKhUh7qAx0ZT+eeNlUfbUQiAG4AUCWCecMIJId4ZZ4aB4xEHHHBAHq929EvdjrswfIBXZZuB8XHzzTfH6173ulxfM33Y8OGx/dveFl/84hezBx84HzVqVPjYQ0op/Eup5+q+BPXyzJt3OzQrr7xyAI92Z/TXeJtgXFlg+8ADDwyBAWAcvhJnHPrgKIrf5tD40KGMjVe6HA3axxxXcyPPkUceGY5TmTsGBj4zD44BOeZV6kJPxpl+n3nmv4VdiOeffz6fMWeEMjbwtXrMnWNHyuqPdhgZ8iuH5uoWX4L6gW55jLUeGATm2Jh5zoFt9bjHt9ovBle93NNP/yMbb/jOp8ZXWmmlenLHe/z+v5Wxoh9bbrllWId4S9uO4bzrne+M4cOGZZ4YXXnu0Y5xYtwdK2wj5wUF2jpbCrQUaCnQUqClwFyjwGwD+noPeA2FEle/H7HoorHzzjuHc9kf+MAHshcdIAbsAAjHOwDIUrZceZ6BHoARSHQFTBwf4GEcPmx4Bp1+P/roYxUg/UL2RAJr66+3fqy26mrB6w0Q8nA+/fTTpequV95TbR533HEB+DxaecI3ffOmseyyy8VPKi+789a8vQwSAIuXnCddPh57HmDPBOg7ECqdYcJrveSSS3ZsVz55gPgCgHmKgTug2dEiwIynWZwdCmDTbofjMcbIaOkGJPUVMP3KV74SDIJmJ3jl7ZYAlQBjSimMiXdcu45mOPLULAe0A6TDK4PA2NTzmte8JhtqvORowovdqRxvMB7g2V5rrTVj9dVXz8dBPNvgWBBjYpVVVonf/e53+fiOsaG3Y0Of/exns+d+hRVWiI03fmM+DgRcMwbQCE/xUJsDu0SA7MYbbZS90uaIp1rf9Nl8R/WPsbj0UkuFsRTeveOOO7LH3dEx/fnZz35W8dgX806Tuh1RAoK32mqrAOwdJVPGA8far6qd4X+84XiSuWL8mVfPNaCBuRGP92YoVP3A9zzrp59+en72Ydlll61ie/+f4fNMtfMiF3417xMnTozjjz8+H7d59rnnotqiCl56x+asDWPBd9H+aynQUqClQEuBIUaBtjstBfqmwFwB9H03Mz0HAOpBPB7cFVdcMRwlWHzxxadnePkOwAV4gCzgK6UUu+22Wz5HDMwCWUCoBwQffPDBuO6667NXnNEAVJ3+1a8GMAa8AU2O36Q0s6f55eYqfJPy0RUe8xtuuCGfB+f5BRZPOeWUWH+DDcJ5Z6DMDgRDBPgDfgE44BOABcqN7b57782eekBXP/RZXqBPYNAA6CmlDCQLuIzqX0opx0X1z/hTStN+q8/ugLf1oOPqFRgGFp2L7gTIpPMgv+Utb5npWFF0+IdOHpy8/fbbA9A99NBDo5PB5diKoAp9Sill0MzYQgNgH7iWXg/GaUzmnJcePfGAOQYst9hiizB/5tYci0NbgWHG+4yeQLCjXgdWuxbadA58ypQp+YtzKaXMC2984xvD/KGT5y3kA5rt+hiXXSJ933333eO4CuxqT5/NK0MGyBbsiJhzQN4OAH5jPADba1U7TrvssssMOw4Mz/qY3TNQHA8bP358bLvttsH4Ued2220X733ve2OvvfaqDMeZwTo64XtlAXA8pr5uQf+tG0aVPHjDfGjrxoo+DNzrrrsuG9birEGGG6OylFGuDS0FWgq0FGgp0FKgpcD8Q4EBBfRALKDmgT2AhteehzOlGYE2QAUQAi9AB2CJpDzSgDEQBhTyPvsNaAF6q666agBn66yzTmy62Wb5XL+6GAdAtzq6hZR6zuAD9IDqmDFj8kO3ANvYsWODFxsgBNb1ywO/+sFbzhMP6AFf+uoNMndNnZqPAYkD/j3YyJOrf84uA3G8xfqX0ozj79ZH8UAncLreeuvFuHHjYpNNNslv63FWHnCTpx7sDjgSlVLKILeeVr93DzSbEx5kwPujH/1ovOtd78ogWXo9GLsgzhhcgUlBWe2m1H1cQC+QutpqowPY9ducelDT8SBziJbqNS40tWMBjO+www4BrMu31/velz38DDfPNKSUsnGWUsoPbI+p5vG1a6wR6tNfdenvsssuk42klFLe6eFhN7/SUkqx0UYbhXkbPXp0eOBXWcaF8o4XMXL89gpJR3IciVLWzoGx6Hc9qIPxwsCYNGlSqMNcHnvssdmAYTisXhln9TLu0VJ9+uZ3XyGllOdLOXkdg2L4qH/VateDQcPwwY/Wlv7iZ/QD7JVpQ0uBlgItBVoKtBRoKTB/UWBAAD3A4IiFM7weiHQO2Gv0eGiBuCbJAKMKl2RgBozW80gTlHEVACtghAeT11UaAAZ0udc+IOa+W0gp5SRHSYBSdQHjIoFI9QJJpS5gklHCmHC2HyACtHlfAWMPBANN8gGHvJ9AP8PDA7S8vI6D6L821Bs9XcjeU+MR3wz6gSbi0YWX2L38pS6/ZyUo54w3Y8uZfUATmDdHhQbN+oBMNFKWAaT/jnqYC31ifOlfs1z5jZYFsItLKWWArVxKPfcpvUyQiPzwqjlUp/4VgCs/YFplyXlcBfnQKaUUKaW8e5BSkpSDfuebDn9SStmDjockpzRjOUaCY1mMHe3bGfFwrt0iRhvDVbl60B+01Fdtl/6nlPIzKNLQpF5mdu5TSnlnxRwoz5BZozJoHFvDh3gb3+FzfcLDKaVMI/nb0FKgHxRos7QUaCnQUqClwBCjwDwH9MCLbX/HHoB5AGLfffcN3mVeeAAXGK3TBbAZNWqZDMIAj2Z6PS/QxYsOXDo24KwzUAm0ODMtrzRAOKXkZ8egnwAO0KNOH1ly1tvZbZ5hZ4z1Y+SSI8PxEK/e5CV3vOGOO+/IgIj3fcyYMflhS2MF9JxRdnzDboKHaD0YCfjxzL7nPe8JQE7bHvLVb204zgH8i292ljGgP8CzIzt2H9Br5MiRGRA38/fnt6NE3ufvvDXjxe6Bo0v6g46AtHu7ANoE4AHZUaNG5d0Buxb65fkB6UAro62A1k59SCllmjXTChBtjp33Wnvmg3GIb9yjs/4rt9LKK+XqlE3DUqBLdP2Xcoq8xmeu3OfI6o+yKfXkqX7O8L+20Ynx5qFWD+G+/e1vz295spMA0DNw6oUYdHaJ0BNdNt5447A7NXyh4SHenOtHvUx/7/GCucEL7hkyjJ6UUn6lKH5hcDq3n1LPQ+voBdybS3zv6A2+72+bbb6WAi0FWgq0FGgp0DcF2hwDRYF5DuiBFG8WccbbPRABdAO1zjF7UA+gaQ7YkQRAHNACOprp5TcQAoQ7tgH8O9IgeLjS6/ikOz/OQ6ntUq55BeaAOG/UWW655fIrHoE1r9n0AKRjNUDauF3H5SMijmg49qGe5559LgDYTTfdLBgXjBYAztVbRoA/AMuHmoB6OxXOwTteot8A1cMPPRznnXteeN2g/gNo6m4GwBn4ds7cGX/n8RkY+uKYSzN/X7+NyVtw0Eqf5QdKzcthhx0WPg7GIHOm3llywTEj433zm9+UdxOAaseHHO0AdoFDhgzgqr5ZCeahnt9vgZfZKxcZPI5sOb5ibtACoNfeVm/dKj8HUS/f6V59aC7N+I3tO9/5TuCfYcOGi+4a8ND1118f3krjQVU7LdpmcAwbNiwbKQB1SjMaA4we837oRw+Nk085Oe777X35mwAeBP7wRz4cdkMeeOCBru12SzAW/beWHP2ZOnVqoL9jYvjOXHkzlCM30qwHr4HFj4w0R3DMEz6U1q2dNr6lQEuBlgItBVoKtBQYuhQYNre6BngDFzzWQFKp11tcgGHeeHGOoQBkzml7vzcAy3sorR4AekCVEcDrW+oE6LTFO+s+pRS84sAn0A7cAKEF6AHz3vLhrLD82lCXe/1Vj9/ArN/OxnvNpPyMEADcOWlg753vfGd4HeLIyhsO/Dif7OiJOgHcUaOWzuetgX1xxrDNNtu4zUCPVxToFtwPHz48n//2kKcxAYhe3+itLupXULx+uReANK/zBAA97AuU8fR6E4p65ekWjFOasQvuzZfnBniO/ebhdcba/JgbD5sCzNK9+QZA9Fv/3/ve8dnLzPjQd+9id4zGNwl8pyClGUGt+rVrTOgOZE/dbgAAEABJREFUHJc48ebAfIuThubGLj8629XwECmjwfyaG8YhMMrQsGOiXnUwstSnLnW4dzVedFDf2q97XTZIPARt58QYn3vu2WwUPOdNMApXQd+E6jb/j9+WX3754PlWDl/4cJp6HbvyXANwnzO//Adwxk+XX3Z5fP9734+f/PgnwRByf+UVV2ZDTvsvZ+96MT6J6ONqTMo58mMeGXwMSbtFeNlOjw+4MX6sQTsJeMX8oS/jDa95/sRVnW1oKdBSoKVAS4GWAi0F5i8KzBVADxwApe9///vDe7sB2UIGYIwH0/vGBUc53ve+94W8grd78BaW/OUKnPN2AzC80ICrNOBt/PjxuTyvrTggVxzgzVO50047BZDFg+1tMLzuKaUMnvUB4ATAARjgRp+9XYWn0nER56ABVGf8ATTHgzzIyAPt+ExKPUDVO9uBygkTJsQee+yRj8/oszYE9QBK+tgtAP9euch7D2yhj4878ZDzuAJlgH8pj5ZApPHqu/btJOhXydPtCoTqF7rzKMsHqCqrXWlCfX6Mi8fXfKCT+fJcAMBqZ0Rf7TZ4Nam3sfAGF6NH/c0wevTo/D58fTDvKaVAA3OCjuinTOmrvgDQ5saDpeYYsAdYPRzr+NaZZ54ZyuIDBgW6+I126jLPdjDUhW52YByB8mYbv72lxhw7RrTzzrtkHrazopzyaKW/aKOccdu18Z57ZeXFb/rFE17GoGwJ+NYRK/UI+iK4F9DWmEv+bld16IexoUlKKcyNceBXtEwphT7iV3101l//rAdvB3KuXv0MAUfJvAqTAaY+8W1oKbAAU6AdWkuBlgItBRZICswVQA8EA3OOgTgr73x5oRYgA+j4+minIH/dACjlgD1nuZ0x97pH3kVp6lYGcALSxAmMCkdYHLXxekNvHfGFVGBHugDk6ANQox4ebd543kuACiCUDygE8ABF+aUDRs5wSy+BFx/QZzQAlsrrL5Ct3MSJE0vWrlfAmKcfQFQGYAXa1OG964AYQF88svKjtSMuxtlfMK8DDCBtGBdaiANi0UB8pyAvAO/MNyNH//RXP5TnFWeQKIvm5RWU0joF9QCa5g/9Ukr5bTLm1Lv/AdWUekCqODy188475/Pp6jMGb+JBc2360NSOO+44Ld2uDuAqHZ2UMS/oqC4GB55AU28uUofA48/4QnfzXecHfGbc8o2uDBJ14h9n582BeGN3DIehKL0Z0MmcydspoLN+Ncs1f3vtpPIAPIMjpR7wju8d1XIsqZRhqPlQl/z6qawxSrcDYXfDukLzTkaIfG1oKdBSoKVAS4GWAq9MCsxfo54rgH5eDZmn1ZEZxwKc/3Wkoa+2Uup5awgQ11fe/qQ7vjC36uqtPQBTW93y8KRLcwXu9YnhIW6wA3DvCAujaqD6YvyesZjT9oBi9aD/7NTFmGUUDeTYZ6WfKfWsB4ZmSj07S8o7+88IMXYGEy+9+Da0FGgp0FKgpUBLgZYC8x8FhjSgBxIdRfGQ4S/uvjuee/75+Y/Cc6HHwCbPME+5Yyd2FuZCtW0VQ4ACg9EF5+49gOutN8C8Izl4bDD60rbZUqClQEuBlgItBVoKzDkFhjSgNzznyj2cue+ECbHIwguLesUFho1jJs47O5bS6YjSK44o7YDniAKO5lx22WXh+Bkv/RxV1hZuKdBSYCAo0LbRUqClQEuBrhQY8oDeg3rOTTtv7WhH15Es4Akppfxe9ZSmH5uI9l9LgdmgQEo9H86y49N8LmQ2qmuLtBRoKdBSoKVAS4GWAoNMgRkB/SB3pm2+pUBLgZYCLQVaCrQUaCnQUqClQEuBWaNAC+hnjV5t7pYCLQVepkB7aSnQUqClQEuBlgItBYYGBQYN0Hswr06C5u9mWj3dfT3U8/Z1P7vl1DsnZZVvw5xRAP071SBe6JQmTlo9iOsWSr5u6W38gk8BPDCvRtlX3dKFWW1/dsr01kZ/6utPnmYbs1NGHcoJ7tswZxSYl3Tspe7c6b7Sc6bGH2WERvQc/eyrvr7SOzXenzLd8nSL79ROGzdvKdCfuehPnnnby861Dzig9+rJ3/72t+E1lD46hTBeoXfbbbeFr3g2u+nLl9K8i97Hpfy+/fbb49Zbbw1fxxT8/v/+v/8vfPmyWb78Vrc6/uu//iuuvvrquPnmm+Ohhx4K7Zc83a5eFfnHP/4xt6msL3L+7//+b/zjH//oVqSNn8sUQP9rrrkmHn300VyzeXvkkUfC3JvTH/7wh3HnnXfG4489ltPLnyeffDLzGj4R8A1++vWvf53rUk/J693sP/rRj8JrUr0atMS311cGBcimP/zhD+H9/PiqLh/IgN///vdh3ZM1JfzmN78J9/hTnm6Ueuqpp8JD7bfcckso44N59bza1h7e1L5+iKvn6XSPf32x2FeHe5N/ncp2ilOfNXbXXXeFPnfKI06e//7v/w7fMfC7t2BdGY/81uDvfve7IPtLGWvNG5fuvffeTBv0KYG8l37PPffElClTwhefS7n2OmsUoD/xLx68++67g2zsVgPeo6fxbF96Tt4///nPWRaTr+auyd/1tsle+hivdWu/xFtT9LbgvsTP7hUvWS//8z//E8369Ofhhx/O48CnxlHn025tGpsxoSv6dlo3aIi/5Zk6deoMukd5dEPrbm208XOHAuafHKfju/GouYAlfHgRT9RbJsvMozzqmBsyt17/nN4POKBHxPPPPz+OPvroAMgsKoDssMMOi/vuuy/q/ywuX0z1gSafzUdMQNxHnj784Q9HPRxyyCHxqU99Kn784x8HAVPqMYEW23HHHRcHH3xw+PDRoYd+JA6p8rv/3ve+N0P+Uq5ctfn9738/fHBImUMPPTTX4d7HoCi2kre9zhsKEP4+suXDUISfOQV8zLd5qM/JkUcdmQF56Qkg4MNm8hV+cY8XlLviiitCnfJbvIy1L33pSwGAiGvDK4MC5NJ3vvOdLCMKn5AP5A5+e/zxx8NHyfBNPeAlwUfXyLNO1KIYvvTlL2V5hefU7yNjRfEDqddee22QgdIEbV9yySWh7U51ljh1aNsbi9RT4mf3CsD4CBkZy9HSqZ6yHvUR6OuUp8SpD12bY/O2rrLujEGb6kPLQl/3F154YXa6MAI++9nPhvXZF01K2+11OgX+9Kc/hQ8Aom2h8zHHHJON0em5pt8BPeSrjzN24wO56Uf6u+jHUvfXv/71YKTJQ4/j0cLXrqecckr0Vq9yAlDtg3gAvd9zGvRF2z7kV/hPndYOhxGeE/TRK7PpAsaKPJ3CY5UDSR75y9jVT3/QJ8qQC2effXZe/yUP/FMAPAx0ww03xKRJkwLdlWnDvKEAvPa5z30uzBleKK14jTNeN+fmEg+QWddff33Jkp0J5JG0Mo+wBQNxWqZBvhlwQA9sY/ZfVhYyYY/pLZg77rhjBg87Yh9xxBEBxPnojS99en2jvKzrpUctHd6f7T3am2++eVDIvg5qMnirCl0pAl/wBL4pgn322Sc+85kj89dJCaKPf/zjUZR2KVO/MjImVQsNgPShK4xAKBIGBI16h5qVVu//gnDPWr7gggti5513Cm87Mqe+0sow9MVWi8oc+0rrf55zTjW/n4kCNHihfvnLX4b3rOMVczh27NjwUS5g3qJ1xYc+DiWdd5ahR1ktCPRrxzAzBeox5AKPy5FHHhnWuVflbrnllgFke11s4Z8ll1wyllpqqfBmIGG55ZYLcgrIJNPwT71e94DCVVdfFWefdXYsv/zy8YlPfCK8uQv/nlPxKr5jdAIB5NA222wTu+yyS2gToOLRk0ddnYI+3nTTTbHZZptF88N0+gYI9Vc+4XfA+vOf/3woR6Y22ySzrUWvO+XFJwebeeq/0YainFp5JXfaaafYc889w/plHF166aU5KwPBDhuvKLr6UBs6C75B4u1mxkf+k7l2MnLB9k+/KMBguuiii/IravHjBz7wgcC7dCt9VoB3qYzMlPaDH/wgOMN4l0ta82p36jOf+Ux2pG2xxRax1157ZT1unrSJX1xPO+20vCuz//77x6qrrhoA7he+8IVenWn6rR9A85ve9Ka8bkr71ixPKY84TFHie7syrOmKc889NwC4ejkyn+MQsNbWHnvskXcwrIXJkyd33I1X/t///d8zOEwpxQEHHJD1E+PF+Kwfa4qh8OUvfzkbOBMmTAjfkkET4wf28fVWW20VdrD+4z/+IxuwvY2jTZt9CpgXH1TEt3hTTUC+eFjOnOFhuMJpDLxtx1Q+OIT8Jq/M9ZprrhlnnXVWmFsOH3kGOww4oE+p57WLKVVXoaIAgQ1wuVJelCPPPK/T29++Y1hUFoF0wVcvd9l5l+BF4rVhcVEyrCZlLQpb4BYTBUVZmKSLL744gz1W2BlnnBEWFM+FsoRG1ZWZ/mehqWvffffNZSkk7RxXefwpH30kHEpBTGKbWD8YH01hqE8Ei3QeCsrWmJV31Q/MIWjXb8JLsL0tTllMSKAo199A+RLergSJelwJeV4CaTwEgIC4Uq9+YWL9la6McZR0V33RZ3nQA12VkSZYKOpHD/mMQ956HvmagVCn+IH1bbbZNgNzfQAmxo8fnxfT3nvvHQSlOX3HLu/IxyKABv1WH6DF6Dv88MODV4qyIaTNv/5YzIxEefHZ1ltvHeZVH8W1YcGmAB5w1Mq6tbbJFIofXzEMOQgYgLxqPMvki4B/gHzv9D/ooINmAtSoZq1ffNHFWYkT/O9///sDePfKUEod//PU8UR+8IMfDHKPEUFGWeN2B61NdTWDfvP0MxSAKYZCPQ+5Zo1wltTjm/fWCXB04IEHZhlHJpGzKVUyupbZerXDgDbkkqSUZswjrh6AQgCRwc1gsgaB+REjRsSVV16Zs0onE8ZWhja6MnQE9+973/sipZQNKZ4xDhbl6vIpV9L+6UoBfM2wAhzpLd50PP6GN7whrrvuuhm89HiNzvPtF3xBL3erWDojlB756Ec/GuQqB5n55XgBiOhAxrJXT9shsL6OqBx12tYOg6FT/ep2LOi8886L7bbdNtZ+3etmyEafqAuwwq8zJDZ+GBMMsNtuu4VxSU5pOt9ag1OmTAlrVZ36yZi2ywBr3HjjjUGfKVcP1h89sf766wcMgj8Z6mPGjMkGjjL6qe6UUtY96AQkchgwHqz9lFJsvPHGsfvuu4fdLE6FejsL+j3sQJ6QA7AJupE15gUfGL+rNHigU0BneeTtFOAnspRcwQ/kW8mnLY4RIB4WwMN4AC84VsPQwhunnHxy4AdryFzDpe9+97uz4wev9tZ+aWteXwcc0HcbUEopv2ed9wUxCW0L8NRTvxRrr712Furx8r+UUgBpwqKLLpqJvNpqq2WAzwtEgAB0lDEwqDyFK48yJpP3h7KgON/4xjd29RQQFkVRFhDrNwVKwe+4446x2GKL5Z6ZdAxjl8BEU9AUrjHJQEGfe+7kOOSQg4MHgHKnwHmvMJn6MQnQKbznPe/J2/wAtDGJo6DFU4yEFKGi7pp3YhoAABAASURBVL6C+glQ5XhLeKb1kYAhlK666qr413/91yxUCEn0V7fFRugAIfqr35Q6ujIwtGuB6QuFjabjxo0LeY0FUFAHK5eQRA8C3Rje//73ZaPKXKmnU7C4CT5zRElYNOikTvOoj+JSStk7csghh8R73/ve8LEki7jUufDCC2eewS/ma5lllol9KyPN+NGfgSC/NOCf54fXRlypo70umBRIKWXesK4XXmSRbDTiE95hcUadUsq7OrzggnhGIT6xznn1OoEfnm4G7qabbhp4LqUU5JD8999/f34OSFvkUuFR12bb+tAMlBBD9K1vfWsGvM10sotMouyaafXfwDHvOOX1/srgIBekW1eugnXguCPjQLodUzSQ1i0oD+ygz9ve9rYsp41znXXWCV54Cts6Zji75/EC2O1OkJloYD2W+reqxsmzDESSiSW+vfZOgZRS4CnztUilL/EpuuK7lKYDW7WgP68zWbvRRmN69Rab3xVXXDEfJbH7yejVBg88Bwx9x8HFMKYbgFYy27zSv8qT5dptBrzLAQdAvaXagR++0ELNLHl3jPNJPTMl1iL0g+GibWB6k002mWlco0ePzh52Djv9Q6/VV189Yw+82WkNGSvjiD5j1Be6kg/WC95OKQU6S8P7roxZ9NeflHroj3awhL7edNNN+XhHbQgL9C0ZBfMxBL/61a8GfnGSouzsGTy6MLDgkGaAM84999zgFJC3U7ALygHD+UEWp5Sm8QBDd7vttsvzbx7NPWctfsVb5h6fwTBA/1ve8paMVeUhC2EUhqk579T2QMYNG8jGurWVUg9Ts+YR3eQAzDxBLPtO5ToRz2S9+c1vzg/XPvLXv8aDf/pTAJQbbLBBvPa1r53BKFAn7xpADexTMOKaYbvttg1HfvTJjgCGY3FTgpQfkE0YUDC2bE466cQMCMaNGxcEA0YFjjEb6+/oo4/J/XO0g7JzJuuYY47J/dT2j27+UfACehYAABBHwfGoaJf3eIcddsj5gXOeRXn6ChgTcOYVJLAJI7Sypc97xsOApttUW/5oZiuW50W/jz/++Oyx3mijjcK4APjjqh0Kx1LUC1ScdNJJ+UFj4MJRKMKLx9wxKEKbFcxjo179kG/RRUcEmqEtYN5pDACR8uutt14GXSmlWL0StOZUfYwQXhH3gAEvn3myMAnPUqd+lvtyNT/oiRbAlXZSSsF7SiHxzFJIJX97XTApQOFuv/32gWfs6OFt6xqgwHe8aXVeQgXrk/GuDMcDhSy+GfAkhUBG4DPp2vPbOrLWGKuUBB4++uijgyJT98orrxy77rprlifKNQOvK57VPyBBunVmPdpStiMGVFA4FBrAzhMmXz0Ymz6QVWQuB0hzvaSU8jHFU089Ne8iyAOQ1Otp3qeUsmFPvqyyyio5WX95IP/84IOx1lpr5WcEHnjg/iBnbrrppiCLHcvgHWP8o1EuWP151atfHdtVitd47NI1+1hlaf/vQAH6a1ylj1JKebebvCSv8QnDjIGlGN4gjwEs9F9mmWWngR7pzWD+8SewDuiklLJjjJFLntJvDAPGHJ3FA3vRxRfF507+XGjb0TI80KzXb/zASURvA1biOKWsF3yMn/GSOLwuTpo4eeuBnOf9po8Yl4yJZro1jPf1WRre4sgyFmsVeBNfD9axeo0N4Pz2+d/OXnh9I08YO9alcQL5duiAUfTn9eV8pMdKnXaH4R0OJmu3xC/o1/976v/yC0c813DVVVfHW9+6VZbFF1xwfpAd5oAcgH84MRhn9SAO2O6GIexQnfVv/xacBHDUWmu9LvNpoSs5qx1H0UqcNeCoFMNrlUoOw3fPPvdcdhoyAEo+OAEfwK54scQP1nXIAHoLyIKy6Cx8gBkonFXCAOYppfhd5f0qiwLRR44c2bEqk2PBU2qdMmw4ZkzeSiQEbP/ZDt9nn32yonVWjlBTloCihDfe+I354SPeaCCZwKL8ebYAegLuy1/+St7aphxt7xRGfe7557IAtfgJVOezeAB4pJTnTZ40aVJ+oBhoJUSAc8zUqe/1OPT1G9MRNtpmPI2rBD3h64yqc7Hq52U3HgvANtUNN96Qn1eQZlwWBQCjbaCfgmXVOoMoDSjhCUEb9fBwuDenhJZxAS0EmwVDcBLg+tcMypsfi04d0gn54yqDAnh3/l2/7CoQrocd9tG8Pdpf3jH/5hZAAN5TStmA4wn81a/+J5/71GYbFlwKWL/rrLN2MFj/9557gtK1iwWMO6rneEBKPU4HVKBcPH9j3TmmwuMuvlOQl6GMz1LqqQOwt8blt8u1wgrL5y1368261D6+3/3duwejO6Uk67TgRp12INW1wgorTHNWnPlvZ+Zz6jxHnAXWnqMQfvM+AknK14M6gDrnePWzyIp6npRSyMPg5wipp/V2z8OqzrJ2ARm0HbnkkoF2DA5eYbRECwBz/PjxQSaRIY7dlP6YJ4CLfkCrEt9b+21a5B3kjTfeOJ+b/69rrgl61vNHZBwQYz7phauqXdp8TKva4WQk9od25Df5bG7k56zhtDHfZaeUbhA4nw776GH5uTjzziNNjyjXDOaY/l5++eWj6G4GxyEfPiTzN2cavqF76GO8bbcdEGvWpX+8sngH+GryTUop0wiflnE4QgHkWWd0ZHGu1etOKWUnk/UDYE7814l5bMaOftqVxtgZPXp0GD/9iKf1A+3hlVKn+bBLhfethRL/Srg+/8Lzwfj5cDW/Rx11ZOXUOCEOPfSjmWYAOz6Atzj/7Iw2A57uNEf4msy7/Iorwu49x0nESxXOmk5Vc27u8bJYvOfZjcsvvzxgjLdVDlRyFC8UuS2fAGfgYceBpIsbzDBsMBtvtk1BWagYHfMDjAjVzNfbb94wVroF8+p/+Zes6Fhu4jqVay7uZp5FFl4kWNLeOAE88opbnIQJLwcQW0At5c1a540qC5nHjweDwnryiSeyhwlAkL5Itb3/jnfsEquuuko+96289pXHeBQ1JiNcjAfopKQ91MEjIc2DGrxyyvUVjFWbY8aMyaCVsrX9SPA4ZsKTI44HnMC1GHip1fv444/n84eMGl59i0C/CB9Mz7oGCBxT4dm89LuX5geJ1AEoF2Z31ED9BLytWffSBe3Ug/7ydshL6aTUA2y0rd+24BzHAYDUy4o+//wL8tGhO++6q1q0L9Wr63jPyMBj5iOlnvotUAv817++J4+hY8E2coGhgPn/5jcnBwHu6IBdLDtLdgkp30u/+90ZXnHHE+gIHO88oECBdyMGXhWGpemiFl8LyliP1113fZATvOSAFlBll+vSSy4NDg5rSN56AFx4nngOyYaSttaaawXZYT2TI/gaoPBboBhL3vo1pZRlZT2ueZ/SjHnKGJr5Ov0ml3m8OCUcp/BwGeNe/3bYYcfKc3xKXFx5b4H4I444Iu/cWYfoArSVOhn2ZBFAX2RKSWuvnSlAPwFDwDa62zGmu8h4u688wnZNOKDw/F7ve1+WnehrjulOeTvX3hMrD9nPSONR9eIIoLYntecvg5nT66gjj8pAmF4kv3tSp//VLp2mTs64kmKtbPLGTTJ/W3f0FhDI6MXbdII8JX/9mlIP7xpPPb55b60xOul5eMTRVLvp1nAzb/239s+dfG7gXfKAw4qjik6HY9AYbezCMWgBQ4Y2z3Kpx3isT4bLk08+UaLn9DpflH/pxZdiTIVLyD36fsSIxYLjkQyAtchoc0vWdQrKpJRmGqs5JEM5LDlnzK8A1Ls2+ZoReeaZZ4TdQf3hOOTwK/NvbpuN4KmUZm67mW8gfk/XMgPRWpc2EETSfvvtF4QKkAz0mghntTuBPfk7BYqOkgCGBRYwgUYJNPObUIr5uuuuy6/QbKYTKACt89W2zyh7C5aSIZhMuPPn8lCumGPkyJHTqkkp5fOyvPQUmnGywqdlqG4WWWTRGDVqmbCIyzgxsVAl560haeom/M4999ys/HkILf511lmn65a88vVAUKINcFziLQQLZJFFFylRM1zzuJ5/IewQMCQEho1y2sbgvAkMDR4ZOwtZgN01tQcgvIypjV1YeumlptXvN6NEhHvXehBn7hapDB+GRkopAyuGhHkjAB2Z8cxCBl6XXhp2F+7+5S/jyiuuyG8+qtfX6d4CRl+8oh150ENwbu6ZZ/4pqg0LMAXMv/Vk/u1S2enhJXYE5U8PPph5CQhFAjKDEQ0cURB1wCG9GSgD9f79//6eQZJ0a1l91s6IEYvmB+j8Jvs8W1K2/63XyZMn57djKFcPjFdeI2u5KBvpnnHRb0YuR4R1A0jYjRMoNvkGMhjbxRdfnN/ww4A+6qij8rM66EIeAZEf+cihsdFGG+c3mYhnoDvWYxeyDugBIbKUzCEfBnIc82NbaATU3HTTTXmXFe3xxaGHHpp3SMTTK4553l/tatM7PPUMWuXwGWcW+Y9vO9GAw6wYaw888EAAw7zmeE9+5ehSO6t2YOxKe37JLpTnuvCEfCXIT/bif/Nd4j0XRf/ib7u7HELkNqMEbzMQll566ZJ9lq/66BibXXjjUB86lXF0qlBfyQQ6fpfKOWfszoCTEYwk4+Ahxs+MVbsSjpQJ0nmftavulFJ+sB54FcS9kgJZWZ/vESNGZHqQH3gTTwH8jnk1A55i5Dfp5QgZ5ydZ64FjfO03mcI5yaAyf8oxIp3HP+uss/POKF3gyGVKKYqcfeLJJ2WdFswdOQyLaGNawiDdDClATxlZoLbGWPgEOwJ7YMvC6YtGwJ/FA1QDu7ZgeKcIDufsCIh6HRS5BciaxjCEXz3dRBMWnzvppGnvzCXwCBLnAt+9x7vzkQzMAQCaUMxX6lAfAYGJTHwaNmwmw0E8UAnYLjR8oVx02PBh00D6sKoMgWIrjoCxnWlbHl0wMSbvC1TkSqs/+pNSykqz+pn/FxeVcZn8yTExDXj4SYgyQoBm7QqEJ6FnC2uNNdYIHk2GBiPMmXZg4thJx+ZF8MKLL6hmWqiDj2mRXW5S6tkKpTBsg7300kv5YSELk6ePB0RRCx/f2FZ2BndUJdR5UdFWercAGPBWoS+BzEiRlzC1SP0e/vKciG/DgkkBa5bBT2bgg5R61gg5xMtNUZAVRo8XGfCAAw9kX/xs7cgDIJAn6njmmWfya1XtAr3mNSPD7h1lpm3p8q9RrSsA6NG//W2a7JFWAtmIP//y17/kNVHiKRZ1UUDypJTyw6h+C+RUyTsQV2MlH3iEKWtgjOFv7Nq3BnktGS68meKEYVW/yXy0ME5xAocNOSAupSSqDb1QAK0YRWSaHRFzIDs+4ZBCY8DdPOA/O6KcVebMkTN871kpzzLJq2w9kLGOZR533HHZgUKXMiBHjRqVszEIeDu97agAd32wu4UXgSht58wv/0mpR+77CRC7Cin1AF58TMcbG53uXpx66Ut5ZzXgU+N0pNSYHRt1jFOd3erSd7oO/5a1rS/oSqf88Y9/CA4xxqdjeWSGuugrxqr1ifZkini0hAXw/LBhw0XPNM+sAAAQAElEQVS9ooL1X2hh4O4ff/yx/AA9LAdzeR6hU+AUQHPl6gFv2dWzawSH2QHl8SdHOGPtKuFr+M+xHYat53TgPjtKpa7XvOZfYvjw4fHwQw/N8ME9shvvON3AOVHyD9Z1SAD6MvhCEIzOS8VLBpg5WmHxlHwp9SiplKYLdJNkC8t2mS1nABgT8KqrwzYX4F3qoMC//OUv5/dO8747+pHS9PrkA7Kl/fgnPwlCDsOJFyzU2352WwbHGMaCpWSclydASx4eBd5jwNi4gAHMI13gIeHtW2vNNWd6M4t0ix9QJlz9JiwKo/3nf/5HKE+YEAaYlPAg5OTtHl52m3fPkFNSStlSBaaBHv3QNuHp9V+8Mtol7CkI27mOS/FGPPzQw/Hk33us2Xp/COFceT/+pJQC/Y2JYFcPJWBu0cz8EYj1qtCXUBw9enR+s0NJUy6l6fOLVrah7Tiwwm3XDquMJ/kJdHUAeOZUXBsWXAow0ikDPIWXy0iBm/t/97tYYonFowBQwptzAPjpZEhbi3gHz+J1IIp8IJcoKHXjZd458Y6pveY1r8nPfdiWly44XkduebtHAUfiSwAO9Pnxxx4PxmeJr1/xNE8W2VSPn5f35AQQV8CbN+NwPliPdja941+/Sx/ID4CI59hOaYm/a+rUfAzR+iebxVv/aE8mkqfi2tA7BVJK+Qw6+ccbSZYrgZZ2Ol0ZrZxFwIznvM4666zguAG68TjPMhBFP+Nhug9QUg8eBX7MqfKMtfrcyEf/2W1XThlxnGzWEhm7xBJLiJ4WAKcCkKwDa2pa4ss3eGDcuHHh2ZCyNl9Omq2LXXg8iB68unZ66+NQqTRrG3YAAvG4sTtuWvSzMXmJhTW58sqr5OcW9NVbUJRTj/HQW8pb23CGeHrn/mqXxG/0FPdKCcOGD4s77rwjbrnlJ3nIaDRlypRKtj0VeJAc8NwgejMem4EDGC4xR/AX+eteGXzp1AC+hgMdj4Ih1GU3lrHL6HTU0SkRTlOO4GEv4wEdGjVqmYBrrBmyW5w+Opmgb+R8Pb/0wQgDDugpOQN9sfK2Vq5gt9XFQwo9IUdUfzA1a5nCsy1lUoowslhMgK0toN8ZN959x3NsKTv2AcwTQB6Wsegxh3tbXZ/81Cfz2xfUwQvnnByvVtXsTP/zBK+3/npBKNnu4X3w8I3tdl4H25cMCMrTdqIdAkeGbAlqiwKSZ4cddgjMwlLUP0yD2RghGMwYgEdMEjW8jQ7aNR67Cd6+wSvwsY9NjNtvvyM/TIeRgQFP8POQUKgzDaSKwODVJdPbtQTn11586cXyM6ebJ4FBhFmBX4LdW34+9rGPBa8M2gEjdiwIOmNm+LB0eeJeeP6FsLAoeXVpoFzdCwSj4L5TQBtCkiWsLGHvmA0FY7vWEYUJEybkV6cxAk8+5ZSwWAEZSkyd6nc+2javeaMIpDviAOwYTwEN2jAWQdvAnjrasOBSYFTlTSTYzb01iy8Ea93877nne/JuEwoAI3YCV1555WyAi6sHRgD5YL0AP9at9W/d274Xbx0BN35TBrbh9QEfTpo0KYMpcsfaOeigg/KbFeptuOcJZFQAxHYQ9F28h7msB4HMBIgoLr/JHzuG8vUViqzolq+010w//Wun59e/MayLnAZe0Ew/GPzAEllMTpDRZAwDxa6fIJ8rIESWkm/a0Sd0BPbsXgwFBapfQzmk1PMwM+8mPYqngRq6By96bkMaGe8sugC4uKI7/cOJg09TSmFH09wxvsyHYwlADn6m0+hk80vO2kHGn56LA2jxH+MOcAbwveGF/ibT6zRMKWWeB6jJ4aLPAGJOI7xMlt9+++1hl1a94qwf/ajX1eke7wolTRk7zJyC1hzgZ+e7jMN6xcMA9wEHHpBfaIGf6Q5jBODtVhu/vAA+TOABcrxKLzEYgE760xrnjLJ+pdH7+mKcnAp258gNca+UgAce/dujmbYwzKc//ak4/fTTAw3p+pRSdtChVadAjqSU8gkIshONzas31uHlEuzimxO8Rb/b2Yed8DV5zeh1ygDPmn/86USA/E4pAP8ebIZ1zLkXlsCX6k1pusNwsOZtwAE9wmPkN22ySQBcKaWgHG1fI1qdEKx3xAPqeQJ46XkTCBx5gTzeLkq2LC5CigBKqYe4JszkAsMseQLg+uuuz1+zs2h5JEx2Sj356+27J3RO/tzJ+cl6vy1M5+OMg7Kh+PXJAtQOgcnKds6cAKK0gQTpBA5B+vTTT+UHTB0lIkwx8NrrrKP62HCDDfPr4XjzRVBahAMlR+gSyphvkUUWzW+74RGh+OT1qk7ClRD1ux5SStnbbWtq6aV7tkOl65f6l15q+tlDceYDWDc3jA4g+pZbbglnYY0LMxOqaIr5x43bNQgjXjheTkLf2Clqir3UucIKK2o2BzTk9TcuvJAjG3/Gjh2bn35nGJlnyQwIYIBwp3QoCx5QAneXnXcO9ORdQjtjsNgoJLwC/DAwlLOlynLnNdQXdVNShDcrf6ed3l55Z2f0HsnThgWLAtYP4W39AsrOEPMaM/KtbwZg4Q/GJe8NINSJZ/EP6qTUI0/koRTwmh1CRxkoGr8Z8RQZpaVtINWul61g9ZB9jIPStnpLUG6nnXbKO4S3335bPu4gjUwkfwQAgYOA3PS78LV83UJKKayv8tBht3zkArls/dfzcA7omzhrCCAkO8jy3//+9/n4kP7omytgxdkB5Bm/89yUJK+cnVnKXF0CsAXEATyOLFjf4tvQOwUc+6L/AF80B1DIS/PHE88x06kGeloaAFXSzZf5dRVHF5DR9CwvNR7XBj50zEw+IJ++sHY43eg9PAHU0q/qaQagC1+okzdfOseMD7DhZYFesWuuHb+l8XrL2y1YS3SOXVn38tEreAnA49jRf+260heu8shrPbkaV0opOAMBdf1AVzrSkQ06U1343xo2fg5J63/KlClBPzEAOAJLfQwKhgJ9bL2If6UEdAW+vVKSo/S2227PX8x2VM96n1U6pDT9PfP1sniXnMED4slZ80Ke4MmUUv6KsDkXikGJP/A5fYBvYDBYq8h2jh/1DXYYcEBPeQKCp33lK3k7CnF4oHl2CZAmQTA3i9cCoWgQlWddfh4oV0EelhUBYdJKPSZCvcA38OasprNUylKYjAN5Sv7mVf8Afls8vF/KK+tenRZtSj3K27bypz/96Xw8h0dfPoJUv9UL1LLyzjnnG3H22WflfLzt+qAdghMYBfqBCWUEW5K8eBScvp999tm5LOOBYSMPpl9n3XUDIAFixdWD+ilHdCK4Shr6qpcCTylFSim8I17/ARfl5GGRGjvPij4A0xQF2lkcxx9/QvBy2K4U0MZxI/fStaltfShtAwMUOZoR4CW+fmUs8eARgoS2NG0ar/k2D/qjb+htwekvICUvwU1p4RHproLxHX300XmsJa/8wL4HJD3wy/hJKYluwwJOAeuG9xg/4Q3BvZ0/fFqGD8jiYx59a6PElyvFwGtJiZN1KfUY0rxG+K6sHyCg1Gt9A/fqxaM8hPICYJ3WcmmLIQoQXFc5KAAQIEO96ugWOBBK+U5XslNfyFhj7ZQnpZQ/jEeeUsL1PNrnASZPyAfyzViEep/8JlPRiAzjADBu65h8I5PIirI2Kd6rrro6AB47ocsuu0y92fa+FwqQl3YteY/NATrjb7uodA+90yyON+khechg6SmlDLLMHSM0pZR3k/wW1F0P+AAP4QPOHevJ3LqS0/RqSp3lq/btOKeUghOLZ9QaxRf1Nur31k83PaL/grXGscaz7l4c8OzIkTEI9Tr91lf6RvtnnnFmwA3GVcqqTxlrG//Kz+C3llJK+cgI4G/caG/d0En0bJEhjF9gn2G0ww5vy85O9b9SAkcAPkMXNEer448/Pjs3Z4UGcJNn/JzusOvZLEve2PXkEOTkM0cwJUewdgVzWYK5sttkjTDO8KQ8+BjuIMNgwGY7g/V7wAE94YLQJg8zp9Rzxg8YRuwmIeSxeKQ7V8YS4o1nZZXgt8khBJrl/U4p5e1xhAcuWccEHO+x9L6CSZdXeQCR10J/OrVn0TMgGBauTYWs//q9/vob5A8YoYX69SGllL3oBIxxiythkUUWyWm82fqvjiKQ5OEd58Gy/aMNcfWQUgp9Qat6OffNOOWNDwOrQ18ISmCFtxvt1JVSjzDWf0Jb38aMGZM/4oU2aDF69Ojs5S7tKKdOQTkCrNN4pQvK2YXgAfnhtdfmt/6IFwABfWd4mBM0YTSpV7pgDHhNWgn6xAOofyn1jEFegTfItptFvNJKK4tqwyuEAngFb+Al65whXgBlIYHfeK4T78gjHb/hQ7JOXEo9a8+6sXvoindTms57pRz5RHboh/4o3y1YYxwGvKE+SMeDqd3C552u2u1Wn/iUeuSxMZI54joFO1zkoX7X08kz4yerpZHdnfohjswuNDJWbRo/2itH7pS6ecq+8Y1zsmfTjsnCCy9SkgbsOr83ZM7oJPxFVpPZKU3nwfr4yFDp5mGRSveUNPyDN+mIlHp2c8xlp4APlE0pZf2L7+mP0naZ+1J3/SoNKOb8A+gdZdMna7JTW+KkAV71epr36jUuOse9dGXoA3V0CtLwsvaNic5SRtmUUtarxsa45giyBuWVLqSU8vgZBXQ3faWOeh67/o7rOjUwZsxGir3iQkop0xJ/cBSQJSl15s9uxCEzzJf5dd/MZ87ND/qbw5R62iR7Os09GWfdpNTTD3wgzjzq5+z0sdmnufl7wAH93Ox8W9d0ChA0vOjO5E2PXTDuLB6GyiXf+U7eDptXo7Kt6sEYgI4ns5NAmFdtt/W2FJgdCgARtoo9fMrLNzt1DPUyDJXrrrsuHJmz68e5MtT73PZvzikAPHGsLLnUkuGZjL6O08x5i4NTg3XrmbQxY8YEQA90Dk5PBqdV3+gAmjl0U+oBzoPTk7na6qBU1gL6QSH73G+UBx0QXRBBKG+fh54c4+GVnPvU66kxpZQ/Imb7lfewJ7b921Jg6FLA2nD07H17vW+B3qbn+XTm2jGFlFqlP3Q5cu72jDf0hONPyG8YWVCBLk+x42WO6tg9mLsUHPq18ZY7eutIGCNu6Pd46PawBfRDd27antUoQLA7z2yLqxY9V29tDzuX7FjEkFcec3XkbWXzKwXwqWMUHsRzHGJ+HUdv/XY0wTERoAf46S1vm7ZgUcB8e3Ods/4LorPKbDm+tO2222ajxe9XWuCUMMd2G8mzV9r45+Z4W0A/N6nZ1jVPKUCxpzTvvHMppfzWkHk6iLbylgJzmQIppfzRk5Tm3dqIQf43r9f+IA9vnjc/PzeQUsr8HQvov5TSAj2+aP8NGAVaQD9gpG4bainQUqClQEuBlgItBVoKtBRoKTD3KTCXAP3c71hbY0uBlgItBVoKtBRoKdBSoKVAS4GWAn1TYMABvXcle73iX/7yl/wKQr99IMIHHDp9EMkbDqR5NZsPU/ial98PPvhgiBN8qEUd6uptLGSFBQAAEABJREFUyJ4m94EqXxv03mZ195a/mSa/dn3AQj3euiCumW9u/kYrH2HpRJu52U5bV0uBAaPAADXk3eXkDBnh+wJ9yQd5rbf+ds+7sckiHybpq+7+1PnSSy9mmUbG9ZZfu8ZUD2QRGdhbub7SjEOdaIB2feUv6T4Ko30ffxPciyvps3ot49OPvsqSv9ojl/Vd8NtH5mZlDH21MxTT0Qn/GS/d2K2PL730UqCH0C1PM76UUb+3fzXTZ+e3+ehLV2v38ccfzx8gM5clKDcnOlDb9Kj60G1W+m/8vn/g1Zk+ztYfvuxWv/HBIf2lK1lQ5239J6f6I8+69eGVGm/e0LI/ctJrsvFcU46ZP7S35vDFUKPlgAN6RLjwwgvjs8ceG94tTCBf+8MfhjeYWCx1AiHe+eefn7/G9u//fnZQOLfeemv44IWPKnnziY+v+Aqbjz34wqJFW6/DvQn43ve+Fz4m4SNWPtLk9VA+UuHrhfL0FvTDR418bEWbHpz0sSMfUfGhCF/H6638nKR5jaKPs+infsxJXW3ZlgKvFAoQ3NYm2WCtH3PMMfGjH/0omgIaPawr3x/wMRJfOvZbfF/B2vzIRz4SPoJCNvWVv690X4nVB1+z7paXvPzxj38cPmbjC9TkkXd1+1jKpEmT4vrrr4/ewF2netXpC6xo5MMp+uBrrf15TSB5++1vfzvIQnLR12vR/JJLLsnyulN7vcWZB+MwZ+T8VVddNe0ruJ3KPfLIX8MbMoo+QAv36HPOOf+Zv17d3/nsVP9QjMPDvljuI4T0n/F6AxAnU6f+cl754qavfHdK7xRHN6ufXsZTnfLMapyv03rtqPetd+Mt+MAHCvGTuRQEH2bzwTbOuFltF4C7/PLLw8et8JXXO1tjQH5fdf3qV78KH9d6//vfH15l7LXQ+M1rYs1DX+Xr6QwSr6fEm9Yt+k6dOjV6489bbvlJWE8HHHBAoIP5Rht9+MEPfpANtXob7f3MFGDA+Vjkpz/96SDfjj766JgyZUqYj5lzRzAoyXR8AriXPPiFDlHePEyq5C0+mFV5W+qbF9cBB/SIeMcddwRmtNAQ6Ve//nVceumlwSIqg5TmK12f+MQngkd8ww3HhI+5/LrKa1G4PvPsM8GSIrC++93vhnfWUgLyl0VCMBEEvtzoAxVekeS95ibKa5I+/OEPh0Vb8pf2y5WyY0QQmhaRPnpfrDp8zMnkUoCs9251lLpm53rbbbdlJc2qn53ybZmWAq80CjzwwANhbXv9qHvrkkLfe++94zvf+U7eGazThNcLIALQfVSsntbtnsHgS4EAJ6cDz7R2uuXvFq8MhQNAk3XADg9cb/nJNw4KRj5QwYvH43feeeeFr91edNGFoc5uddTjyd+f//zn2WmCRt6UgwYMFaBc/+r5y714ABI4AbYAcR+F8npJYEl5ChHgL2V6u5b6yGlz5PV1ZB8ABuABep3Kc9bQJcZAscpH5jN6/vVfJwbFe8stt8w0553qmh/izJd3sgN3vvZq7ukGoJOBRy+ipbHQXfiU40pePCq+r6CcDx3hpyuuuCJ8wbS/89ipbv25//77A4BVF1CObzvlFc+4tA5gAPNJx9PRJ5xwQgC28IM6O5VvxsEbV151ZXzyU5+M++67L7z2GD8B91MrMN3MX34zOIBA/PelL30p9MWXbWEQ/KkfaINWpUxvV/k4HOEIvOrtPeSH3/CFee1UXp/hHc5OtLCu4R11+boyOUd+dSrbxkUG7WjFKIL/vFHH1W8ytEl3/CIdZiSTefXRET+YbwbB1VdfnR9iZhT4Pg4HtbmRb7DDgAP6lFKklCK/nqi6RvXPvVdSpZSqXxEsJJ/eZQGNHj06LGSeH4tAXl8Ppbj+/ex/j3POOScHQovnnVKyUAg5i8gk+EwvRSMPwVaCybn22mtDOsWQG2/8oVwJS0KI4tIe601wb8HfeOONAQyYVAxBALna4sQQhJRqMYXfhKP+yS++HvSZt09Z+cuYU+qhjbzy6C/Fpb5Sv7T+BExMMOijsuitP5RDf8q3eVoKDFUK4GdeEx8i8ppDa1Swg4e/3QPCpf/WIBlBeCvrbSolrdsVmOCpoWy9bs7aIdyt125lusWTBXYSeC7/8Ic/hlenpjR9rXcqRwamlIL31HiKLGKULLbYYsHAAPA7lW3GkQMACkcF4KK+r371q+F92HYGOT6aZfwmMwB2jpRdd901zjjjjCBX9YUyBH78BrbJG2V6C+SYOhgrHCT6QS6vt956QZ73BkbRw+6AHVTtKysw4ICnr33ta/mDdOattz7MD2mAJUMLQD722GOz7itjZQBJw+dk+0033ZR3ciZPnpwdX+jUnzFqw24RXvTRMgCbwTa79KPL9NG6tL6E3vqhnz6UiJ+VK4GRyNj8zncujv6uNQbNN7/xzVjjtWtkHlWXnSgygMFizTf7Ypy//OUvQz5Hbezs4yv8LBx//PHZQOQwMA/N8p1+ww/WlXGddtppAd/YNYEv9IMu71QupZSNEN+a0PcS1LXpppvmtW5+zVmn8vNDHPkAM5lT2Aa/kC/NuZHWLaij01jhJICbIfeFL3wh76YyLOU1B+Sv+xIYxOQxvqljUkYUHIh3lTcPypP/p59+etgxwzelnsG6Djig722giEXBYnCL2bvHKZkddthhho+myOdDSsC+dzDzDFHePszgfbUsWt4jR2FsoVNyFoTjNj7vq+xb3vKW7MXbYostAjOY+E59Awx4eByxoUB9utpXzV7zmteET1PzUKkDY2BAng0KhGFhtwCQwCQUI8XJombdE06Ew0MP/XlaswQxq5HXX3/RwUIn4EomXihggrFz4EEHBiAAjDACSp6+roSIbXKWJgWgn4wVChEj91W+TW8pMFQpQOADqdYpQGcnzSfht99++yAnHqi893WPFrDCY0eO8N70Oa4qA1nx45/8OIMkMmG1yukArJABVfIs/c87R14svfTSQTnMilJYeeWVo8hAwNcOJZn5+ONPBFnSn44ALDy+yjtSQLaRoWQuOt1www1ZPjbr+ulPfxq8qGuvvXYcfvjh4T34yy+/fNgB5Xw54MADYs011wzGDpneLN/8ra0rr7wy1llnneD1IqO9l5onGpi/++67O/aj1LPkkiMzLbSpDkD0uOOOi3e9851Bfpsf8jnm83+AOifPuHHjwvEP+swcoDkeQif8j8/xFZDP0bV8NTf94S156ADl8AS9AGChH90zq+RDcw4vO1ljxmxYgdNXZTDcVz12aFZbbbVYY4014nWve11+Rzsnnvr+/OeH+g3oHfPh3cafZAEPOz43Nrs4cEKzL8AlPWzXfVxF58MOOyzIk6WWWir3xfEbaw1N0QrNmnXUf0tniDCKzNnmm28eyyyzTLznPe8JOAStAcZ6mfo9vLPiiitkWuBvH5DUL4YzGWDdMIS1Uy83v9zjLzgN8IZJGFAwyUUXXRywinEwWOA6DoROgZwyb/LWA1DuY3TwFKOfowIfjK5kNpqTTyX/3598Mjh9GXv0QYlHV3nxivkyh+bv9a9/fdhhEW/XiO4pZQbrOmQAfUopn2+1PcIjv9JKKwWAaTJ4CpoEQuR6HNBrkVLcFOvjjz8eJobCpKCAbwujXobA4EFiNHT7Migm0v7YsWNj5MiR9eL5HljAjBaXD0QACPqPgQgF9ZtsVp2zb7ZzCBigHNN+8pOfysqXdcriIyy0ybMk3XYhg8P4NIg+tlYB8d8/8PtgcNg+0of+CFx0s0iAGILKkSMCV394HLQ5K8aBPrWhpcBQoQAg4JiFI3xkQekXpcFrTRADPuKtA16XhRdeKJ9PtfNnrUnrLRDgP731p0EmUA5v3XLLykNzZ1DMvZXrlEamUGDWI9DQn/ZLPcYkMPqNDcAm88hO9ZZ8vV0BEmXXXXfdvDsg78ILL5yNn5RSTJ06dSYgTYaQc7z6wDcAXeST8pTobuN2iylTpgTHBYeK+N6CusgdAIXSlVedjDDtGRcwJ75TkKcZr57ddt89jIdTpbfyzbJD9TdQ+fnPfz4cRy06y9gZROgHqIwYMSLvgNOdHDdkfH/5AY3oTIYeAOSDXvQqXUanzipd8BfDAgjdb7/9KzD/YuhvX/Xoh/YALvqcgQLs4SU84dpXHdKBaHwEoBX9zxnHCFKnY7Py1QNgd+stt4TjZ+9973tn0vu8vRx11htwnlKqF5/h3g9jscYYY/V1xoGgX9aw0BtdetJeUl0OxoKmnJTWDsDZkycnz1d/Hn3s0bi42nUhK+AmRike/NCHDgq7IYA6/uY48KxQp8CZi0+aAzeHyk2YMCHLAXTiwIDB7CKSlcqYo3PPOy8f/eZwJdcLPV2tLYB91DKjos575kFZ9ZpfdQ1mGBKAPqWeBWFrlccbc2NWYDmlnrQmkRC5GZdSCp4dBL7//vvjsUcfzVkoCYs4/6j9SSkF4Qewp9S5HQseACAoTZ7ivF+8Rs6KYj4KviiclFIltF7I3ilCF0hnyTsDyGtEyfHie0BpueWXCx4EZW3ZABesPt594IChAWSklLKAtuNw6qmnBsMBAOAlA/4JJ7/1I/r5D40wKcGkT6x83h73xtzPatpsLQWGHAUASsDeeiUngAoGLwDPk8mLTUk44mH9HXroR8O6KwNJqbMskG7dMLaBgXHjxmWPNOA0fPhC2bjmHZWvv2GrrbYKXlBArb9gPqWe/nEiMO7tROyxxx4xfvz4vGvAa8RT3p8+kGWcCeQjeikDAFGE7sliNHRfAhoAWhQcMI/WJa1c1UW2AtMp9fS3pDWvxm3XwxUd6unKk3fStVdP6889uQ04AQT63Z8yQzlPSikbXkVnoRndYTfXHAJ46EWWMxQBTvPZnMNuY7QugClzB9AzivAofWeno1u5TvHqotPwyoQKUKmrzGFKvfMEXQcL2KFxNNaxLkeMgDAg2xrv1GYzzlEuvAiEo4N0PIW/8T7Pr7h6eObZZ+Mf//xnoCePeD2t3KsDjdRd4rpdrS/tmAO8WM9HvwOCdLG5rKc17196acYY4ykGAdmm/hlzzD+/Xnzhxew4MNe87T/84f+L3XffLR8puuKKKzKucwQK/ukUJk6cGE3ZUUaPV8wT5+eu43bNzhu0Iy+tFTzpeJqjUE56jBs3Lq+xQk95Gc+A/M+n/jwf3zOn+Juha/7IffWUNgfrOmywGq63m1LKVjulC5z6DLAHUkwkYtXz9ufeRFisUdWbUgqTaVJiNv7xeitPgJbilDmPO4tSoEA9MMurgXksWkxhq3PLynvHOGF5ykOp8HoB8YsusmhmYsqKx8uiVhcPhPYw9+Zv2TzTRv+9bcDW2rLLLZsf0rnllluCZehcnvO8vOylj31d0QiI4b1h8GgT3cUTwK591dGmtxQY6hQA5nkI7Wi94x3vyMIcbzOEORBs4ztOJ04wnnJ13wyEOM8cZU/I87xZ79YQDyIDv1mmP797a7NbeTICmKZoABR9IKsY+o74dStXj9euoBB/U6EAABAASURBVK6UpoMsgEW+bkqKnEspZa+XfHMaCpgxnnpd5J62Sno9rT/3pRw9Ypz9KTO/5DE2zqFJkyblBz7trjqmNCf9B9wZuYBsSil4Pe1kA8STJ0/u9Y1D9XbRuxyhAJzoFnH1PL3dp5QyqMIP+BtY4xgD0BkcAFRv5UsaGuGhws/iy2/8IF1cPaSUKuiQshOtXi7m4F9px/qsV1N+l/R6Wn/ujQFdAcz+5B+qecgZOGm//fbLOyMrrrhS7L//AXke7LKYB0dd3lvtmHQKdmMZR72NDx+9bfu3BVyG3hyncBg85xmJUaNG5TcoLrnkktkpW6+LY4AzCHbzthynR+wKqKMpO+vlBvp+2EA32K09jOncJuXrnDnr13YL4dKtTKd4HiXxvAEEgEmmdIFm8fWgTQpf6LYgllxqqVAnjwEmUJ5w22ijjYL3w/l5ZXlJbBGmYSlvyRCCFFFKKTAKwcQjyJvGCMAM2k0pZebBWOoBsssix8Q8YH7rK8YjyO759T3hfKi3YmAuZwFTSrmf+tdXUJc8q6yychaa7lNKYVuWsGN0lDzS2tBSYH6kgJ0mXj2Ogu222y6/3nCVVVaJ+6vdOztnKaXwxiprl0FNMVqTALG13GnMygIUgI41yCDwHIvdMQY9L5A12qns3Iora5Px71kjD8ideeaZwUsLONmtc4zOOp6hzQ4/Fl9i8WCQcIAU+ab+MoYlqvRmMXLNVjX5ZNzo1syjPrTiOeyrH2QOg8T1qaefnqEqil5dlLH0GRL78cN8kv2l/n4UmS+yoOmUKVPyqxgZkXZ58CI6ze4AzDveBurtPn/oQx/Kr/nz0B8njzTrpD/122HGm/Q4Q9Ouln7ScXgGMDKv3eqiu60vXlPte0D6jK9/Pe9AAVPq0N9u5Us8cObecxwlP9rhb/w7YsSikmcIaEhn86rTuTMkVj/UQz6QL3jL7yq66/8AH8yQUornnn9+hnzFYajNlNIMaX39sF71z/rF333lH+rpTmTATaWfjkeaBzIErR2FAeYZiM3guUNHj0rZTldYzYkEJx/sqpKXt956S1x++WVhLcF05pP8t6Nn/uFPx3PM36TKcGZwSLc7euuttwaPv36aAzitU7sDGTckAD3GTCkFgOrsEuXLO83L5Fw3gvaHKBYtQWRxAPSO3/A0WPydJtui5jl3DpQA6rQwN9t007B4PfVOEOjHiiuumLfJPaXO6z527Nig5KQJFA9BllLKHnhblZQ+zx7h5s04wD2DoLSpzxiCwFNHCRRaySOdcNBfDGwLytW2piez3/nOd5ZifV5TStPAfMms3+W+vbYUmF8pYL3YyXLk4KKLLopx1RaqHTUP15E1drUEMsG2vvXEiWCHzC6XZ1IAEPU0aXD55Zfn96tvuMEGseYaa8Ryyy4bo1dbLT+0x2vv7D4l2yw3L35Tdo7WANc8SJ4TougAbA/hNWVJpz685l9ek4/wMVDIGnnQyG/3K6ywYjTlQkopHOkAIgA8SlDeekC/3XffPe+IcFbU0zrdjxw5spKhw+PRv/0t70iWPGQ0xQqYkX8lvr9XHmzlAYW6jO5v+aGYzzwxHB23sjNLB+FZNJqT/jJ+HCEwr57nWHmllWKF5ZePddZeO5yltz4Yx/irr3YYBUARI9c6tAad/ccr1iRgZQ12qwfYBurpWjrT0ZKddt45eFfVbdyd1mezPnXgZwZJyW9d4G/rdckll2oWycdwtWe8jP1mBvQ3hm222SYYHOpr5qn/NpZ/+ZdXZ2/z//397/WksONAp6N5c53NkLHDD7uFzoMbB7yT0qwZBB2qnCFqoH+Yp/oaR2eYbokllsi0I9M9C9MpcB50mgflYUIyyPoHvJ0CMXf4YerUn8ctt9waMJ4dpXGVrnDMy0PgeNeul50pcsguEVAP0HOY0AV77rFnNjKBevUPNM2a7Q1rRgzmb6BW+8DwhAkT8uIlkJ1FtwCllZBSj2fbpBMw0hHeE9C2bghwRHZu3ZaNh4MocPkxjgmy7U6AUSaUYkozLwjbPJQma845c4tc+ZR6wDrP/R//+IcKuL8wgyIq/dQ3lhzhRfCqx8OxBJWy+oOxMBkvvvNj+qYNix0zuk8phTzOfKWUwlEeAJ6Ak84gwbzqcqXEigFS+tJeWwq8EihAuNvdI3g5CQhhit1as1Yoa0AeyLfDxdhmZBP2dsgcQ1t99dWzEqnTi9D3ULryX/7KV+Kcb3wjJp97bnzjm9/Mr1a0JcuT5CF4a48H8skn/54f9q/XMzfvjakEa96zOmQA5QMg8AACUeRQp3bRhexjAAA96CP/LbfcUgHshfJbOOpKttThiJ43kHjonxHz5JNP5p1GfSFnyUpvCUFPhsezzz6TDaFOSledIytAv2K1ze71fpwn+qHvXp8ojQHRqR/KCimRxy/kPqC9MVC6+sbzR4GTr/LOzwFdgA08ix6OCtj1pTPRXvrsjA/PTJ06NdTNEKNzvzl5cpRgF4iDjH4CqLWF34BKZZttehGFNSjoK4OZ4UzH013eEoMvmuXqv7VRAv6lQ4E667ToQe0L8tXLlnt86p7hWfSqeqxRu9/WsvR6UL9XQgLi6AA041u0xVv42hE+mMMRp4UWGp6/+4Dn5KnXVe5XWWXVfJTEsVk7/vKRUzzAK1YOQs/plbydr/j7xczf+sJrDe9YpzzLMI/13rns0I9NKeXvDRW8Y4xwGxrbVYV9nEQQRz40g9eGk2N4ET+Ya/f4xfv6vbKS/BZHrqjXHJCTEyqs6cQE5yh94GUh+AZ/ciw7OYLXGc0nnnDCtBMYDDFvb8IveOkVDegRtkLAmdPcI259UZocgoBiBcadTzURCgCshDWvtCM6JstE8Jiz5llYmACheawoFczPo+39od5j6x3KhAzLlkDkjVB3M1goHzrooPwmGhMOlNvys2XP42Cr84Ybboz1198gH6154fkZgX1KKW9pW2ys/Ztuuil/VEufLWiCCvMRIBbmt771rfyuVK+iNB6CR5/QhiAkKDGRV17ecMMNIT+hyfBhyVoInj3gtcfMynYKaC7U08yB0Iyv55l7921NLQXmPgXICLLCMzg8V5Qyz4sdMbLCO9pTSgHAE9wTJ06MiVUAMIANgty2KvlR7501wQFgzfJWArMAIqEuEP7OcVrnQC7vjgffvfHKDmG9rm732ujP+pNPAJqNSwC4HC8iFwAEssLY7QqSdeQDGdJsm9Nj2223Cf1Vh7dwkZWAnQfEyKVmGb8BbEcyeBbJQcYRpcpzqR+eT0AnChGdyOtjj/1sfgmA8s1ADnt7Bc+reUJDYEp9XjPIY5zSzA6XnnpeittvvyPOOuvs/No5W+pkvd1XTpM99nh3ULgpdSvfU8v88JfRRYcBNMbEgMzHUc44I48dj9InzbHgF6EZX36rFz9ZA17NZz7wdQna4hzjdTc31gEd4zV/ndqjcwEgc2B9WWsebGV4OO7glY3ddhT0E+DCQ3hbG+YUHsBHjpUBePhZmjx2F5Qr4ynXDTZYP++e0ZXWPv5WL9BnzS9f7UCUvOUKmDmeAQjSoXCCIxaXXHpJ0Pv6AXiSIR4YfvLJv+fjbtY6sF7qqV+tI/Sjm/E1GsIADHBOw6a8KWWNiWOAzjdOa8N68+YWa45BAr+QP6XM/HgdXhlFaPGFL3w+OFkvvPCCzM/4zkkGxivehOk6BXxF9nKCkmNk2JOVkwGOdOrDjpZ4uEoaXhg9enSYP3IOjsOngqOM2mVk0QXatw7olvMqfIYXr7nmB+Eo2IUXXhjjxo3LPJbS4MuXQfHQUzSEfEo9BLCAyoTUmRF4BdQxtYVEMQKtKaWgsG3bAdkEi61ygsI9T5kJUBelwvqymBBffYcf/smwMHhuLCqCZqGFF5Z9poCJPrj33qEOx3ecT3UMSD2etiZ4MAEvIObRV2PDgCozNop+7NZbZ0bFOIwCFrbzYCx+R4r05cQTTwiMRHjwIBqj/huzeglZigrwd2aWkNSuNngV9U99LFk7Ad22/lNK+bhNoZF+CmVeLAy/29BSYH6jAOUHjPKo2GYlD6xXa06wZq03a6YeCu+TQ+JT6pFNZfwMZYBHul0xHsKSVq4ermUQ8DI7LwxEnHvu5AB+Sp7ertolO/paf/LpB6VkTAKj3ncuOCAAEACCDLr99tsz2LBNzVhotk8GjBu3W3hLDscJueMYAVly+OGHZ2dEs4zfKaX8vnj0pRiBStvTPgrFK+6d+hSeVx5yWtxxx51xzjnfCEdxlG8G49EHoJ7SdUwDYFE3w2GFFVZoFsm/U0qx6KIjwm4MWUgfnHDiifHdyy4LO6uMmQMPPCi/sSQXmM//0Dc8xniAc4gOrPP3tyrAwVNcHyZ+wld4vB5fv2fQ0aGAuDfJ1NPcA1GMM/dozaAoBhwHm/h6SCmFPjaDfuA5vFnPX7/XT8DMh83wtjmlp+0gAK94g+OOrgOQecsdz63XUe5f/ep/CYaF/HgBf1vHdL4d7pRmXOelHICMrnha3Xjx8MM/kZ/DATzpW+l0M1lzzTXX5FeJApGljvrV7oa1wTC1LoxBv2EAxo166vnL/fDhC2WvPOyCFkcdfXR86ctfDjtqcA6sAF/0Rs9S11C+kk0rr7Jy5aW/Nx+9Pv74EzJGOe644zJY7m/fn3r6qWrtfzfjQ+uAU8curdeFMv5gNXyFnxlG5sP6qPMp/sOngnvpPPnkITx21ln/lj/YBthvscXmgRfwS3/7OC/zDZuXlXeqG+MSQv9VLQCLDME87MATDajWyyAkhgdQAXrCnTXrN283ZaWcq62ss846K1hbJqvUY6JYYRSOoy+8ZsAwZUsBUiL1/KVc/cqTwNNPWKrDQiTMbHexJk00xaUtVj8vgDb1X6DkzzjzzOA5ZMXbJuVlsbCBD2NSdpNN3pQ97hQia5ywcoSI4iZoU0pBUSuvLh7888//djjL5Q0eBCUDhGfBeWHMXB+H+5R6ju7o/8knnzLtWIF5MA6WLA+NfsvfhpYC8xMFPLzkYTzAEQCwpe04msBLTZlzFDTHZI1OmTIlKO5mmt/WB1Bh/Vtr1qv4eli+8vbxKJMP1j/ZxUDvlLdezj1Ae+ihhwa5NHbsWFEdA8UNAABVxmNcAgVPljDkHZkgZ1XguxbO1pMLndZ0SikcT5w0aVKQoZTd+eefH98455z8ER11dAvkJlljzGjH8yjwopLF6KxN+RhBgCI6dquPUiTTeJkBFfIZkCHzUuoMvFZddbUgb801PSDcdeedcfOPfpRfeeecuV2IlDqX79aXoRpvx5rBw0NsrObd/At0Id7nWaz3n26iI8j3enz9nr6gy9Cc97ue5t48eraN3jU3nGcewqXDpfcnOPbEaOABxY+dyuBbPFDGZ1xlnOYZiMLP+gNwAXz4plt91gt9du655wbdf9LnPheXV8beUUceGU06Nftjp4txbJeLc+2rp50e1rY1Kp4DTxnr3ppEZ787hZRSwDfWp2N7xqFO641GJxTNAAAQAElEQVTh2amMOPgELdAdLe684464/bbbMs/DCMA8Osg7PwevrVx37XXDeoeNOBfIFXiuN5nRHPNyyy4Xl333snCKggPU/JM7MBN6w1/q1g6ZBDM16wDeGX/WjPUmXT34jmy87LLL49RTv5RPWnz962dkOZnS0JAvAw7oLUSEtmVrolJK+f2hto4oNcSrB3kQVbrFTmHb7iZ0SuBNWnXVVfMZtZRmJmxKKZzDBIp32GGH8K5elhlBrz/19rrdy0cAUPwYwTt63VvU9QWlHWPT11JXSikfx7F1Q9lSdIQQL59xqVfelFL+ghzGITzVg1a24wptUkrBwBgzZkyMq7Z6xo7dJghVdFIHrwUPoTrRSVwz6C961QVJSj1tK1Pve7Ns+7ulwFCmAMFrvQAoAkBdAnlhTQGYzTFYX3ifcm6m+W39j662aOWRV1ynQB5owxoCMtVHfnXKW49Tf1mzytbT6vcppSzLyDzjKWMzVv1Th7pKGd5Ev8kZtCnxzSu5Sp6RjcDassstN9PDsM0yfquT9xFYUZYCVo+jOClNl8WOhlCe5K5y3QLaAkbqsatK/qU0vZ5mOXIPvdGiBGNFCzLW2Jtl5uffZLfxmW/jLfPv6jdd0DQg0RQ96LtuY7cm8BT+7UYz9Wqb7nDMxnnmLbfcousuTrMtfK0NgCmlznOqbWumPj7jUs66pjNT6inryA0j9rWvXb3ajVl+mnOq2a468QJgv1ulMzfaeON41atf3czW8Tf+YvBuscUWQXePHTs20BJNSwG7gp4rsAbo5hLfvKaUshHBQLU7QM9bd8189d+ccv2hRb3M/Ho/bPiwjGU4Q8yVtT9s2KxBVDxqvvCxuUOLlHroDndxQDiOCPuQXdKbQTweVA+ZVdJT6vnOkfJk3SabbJKxWEo9/FjyDeZ11qg1mD1t2+43BQh3W0sEZ78LtRlngQJt1pYCvVPAFjIFbx0CAL3nnnepgIxzzLac510rvdeMFqtWnnS0QJPec7ep8wMFAB07y/vsMyG/FWYw+uwY6pgxY+IjHzk0Ro5ccjC6kNsEOgFQO2wAeI5s//SbAilSzms+OSTzj/bPbFGgBfSzRbahW4hVSriwHlmrQ7enbc9aCiy4FAB4PMzJG8fjM1gj1T6Pe7cjCQPRL3Jo4403Cufq3Q9Em0OqjQWwMwxFb63hyUypB5AN9DDxEk83YxWoHuj2S3t2Huyo86SnNDi0KH2ZH692jjzb4FkHcnN+HMNQ6XML6IfKTMylfqSU8tcbB1PAzaWhtNW0FJhvKZBSzzocTDCPeAz8we6DfgBfgvs2zP8UoF8GG3yllPKDkykNLohOqWetpzS4/ZhfucquhuNM3Z5Nml/HNbv9npNyw+akcFu2pUBLgZYCLQVaCrQUaCnQUqClwOxSIKUUKaXZLd6We5kCLaB/mRDtpaXAK4MC7ShbCrQUaCnQUqClQEuBBY0CLaBf0Ga0HU9LgZYCLQVaCrQUmBsUaOtoKdBSYL6hQAvo55upajvaUqClQEuBlgItBVoKtBRoKdBSYGYKDDig/9vf/hZe7O/Las8888zMPZoLMU899VT4KMD53z4/On3Fblaa8HEnH2F67LHHZqXYKyavV9L54IWP7njXtIGjv4+cfP3rXw+vzPNBEx+L8N7iZ555RpZ49tlnwwdoTj311PjiF7+Yg3sfAPOBk/vuuy/nyZmrP+jvIxw+DlLqqKLb/1sKzDMK4DPfdPBRO7zsg3YPPfRQeL1aaRT//+Y3vwkfjPHlwcsuuyz+9Kc/5a87ljzNqzJ//etf84dJ8L6PnvgQVl1WWR/3339//tCcPD7YJI+11ayv+dtXP/XFB3Gaaf357b3aPgDkIzo+cleCj9wJU6ZMiW5fxHzuuefinnvuicmTJ4eP5/gIz5///Oeov47O/QMPPDCNZtoxVnTRvwcffDB8IMlH7vxuw5xTwLz8/ve/zx9XwhvmB2/jcbXja7xb5rpczTdd6suw3vsubzP4UqqPLH7ta1/LctyHwfB3WSfm1RduyXUf7NH2r3/969CnZl3N3+q2/nzwyppops/qb236QBU9gs/r5X2d1ofjrHVrztitZfxaz9ft/tFHHw36Cy26ldH+TTfdlD+ghCbqUs7HLsmQuTFGdbahMwXQ3wf0yByYolMufIFHzEczDx6hB/DIaaedlj/G9/jjj3eqZlDiBhzQ/+UvfwlfESQkEG5ejPrJvz8Z3z7/23H2v58d/VGAvfUBmPeVOYZIb/leqWkUAeb2YQ0fyaAgCF+voDLPwL5PlQPr++23X1x11VVh3uUrAv4//uM/soBDa19486nmgw46KAhUCxBtvRrMPVCvzm7KRd42LKgUGLhx4TX898EPfjDwLoDDOBUAoQJW8D2DFQD4wQ9+EJ/97GfDb+AbkGn2WDmG76Rjj83GLsUCBBx44IHhK4TaFf7f//t/sc8++8Rxxx0X8px++umx9957B2AP5DTrLb+tK7IVmPdxpxLvCmSQh32tHUrrW9/6Vhx//PEzhM985jMxceLE+OpXvxrkuLGotx60a+2jB2B31FFHxeGf+ET84he/CPRQBuD/9Kc/HdYymp144olhzaOZunzk6OGHH44TTzop0EpcG2afAub7Zz/7WXzoQx+Ko48+OgB38zNhwoTgWMNvjFJxZc59URPvffKTn4yPf/zjOR/+afaCEcpZc/AhBwfDFK+ay0mTJmXDVn5z+bnPfS4+9alPZSMW8P/whz8cfRls+j1lypT45je/md/c1nxbk7YFPKWdvgL+8yGqY6u1Zz1bK6UMfuaUQhNrjA7Do/TQf//3f2feLXk7XY3x5JM/FydVPIvWaNopnw+9oSudp4w8XilrrAxgYFFcG+YNBe66664soxmJnTAdHoEvrAP4BV+UnjC8yKyPfOQj2dGiDrIOP0sr+QbzOuCAHuP+/e9/D1+a6+9CnFUCmRSKi+JLac6enC71qHNW+/FKyE8h33333fnru76S90DleZs8eXIQlkceeWS4JyAx/m9/+9ugvHl70AZt8cD73//+7NnhOZpUKYI99tgj7r333gAgeDvwjFek7bvvvvk1Zeedd140LWf1taGlwNyggLVuN4lyZrACKAD1IRVo+elPfxpnnHFGUAa8aeJ5Gw8++ODsqNh///1DHuCc4drsjzIA9yWXXhq+XMgTDfSmlAL/MxZ4BSl8APewww7L3mprCXihPOx+6WOzbr8BYIaIun1xVVwJvlyrjbL+SnzzyhB4z3veE8BcCUCdL8LyKnrfti/SpjSjbP3DH/8QX/jC58MOAXqg0yGHHBK/qryxjBZrFk14R++8884A6ihNhj7A/5WvfCXvbHiNHRmgHs6CbuCo2e/2d2cKABs+dc/77PWADLIDDjgg7r///szLZLav7fowUplv4Bsv09VeN+pd767NFnj9eZc5cwBl/Ow7KAAxT6i588n9q6++OrbffvuQl8HLaASgtd2ss/zm5Vff6NGjw5da64DeOmJIcABZF6XMDNfaD+CZYeB95wBbHX/oo50kAG255ZbLRqx28SCjg0MPDWvVTbulm/AyvXXOOd8I+cRNy1C7ITN4dTm4YJOSD6B/+9vfHpxW1oxx14q1t3OJAniA0crggj06yVB58JU89TnCb5yRsAy5qh5YZqWVVgr5GX2wzFzq6mxXM2y2S85mwZRSeIetEB3+IRwr2qIDCutZKDiCwaKhGGxdWdA8A4CfhSl/iuQSi41YLB5//PG44oorsvdgypQpGWjmxJf/aG/KlBsrz9fZeQuYBfdyUr6k1FOXHwAp4WRh2pI2ubxQtp/1Vf0U1GWXX5YXtjL9CYQLBirKnEL+1re/FTxZylvgPArqxjh1RnSvX8W7bavo/yqDSbkS0IUyBzIIc1eCGAMKAIS+E4z6QfCpT3ypo9PVPFDOhKAv9hG4FLPjMoT3rrvuGpT/+uuvH5TDXnvtlZUIAFTqGzFiRLzxjW/MH50pZYAXQh8AmFQBfHMo/8orrxw+1oMGAJexi29DS4G5SQGeSJ4y/M8rzpDcYIMNYr/99s+GK6CC/6zPK6+8MnzE7b3vfW8APfIC0+QRQNrsF54lKzZ505sCbwMqb6+U+bve9a4sM8g965ks2HrrrQPIksfaYfhac/KQW826/SY7rJeddtopAwRxJQAeDBBytMR1uvKQW4t2Jz7wgQ+EYPzAvLHyUDHem2VvmnJT5Ym/O7xPGt3QAyjym3zhnaQw7T6oT73yGJcPYJHnnAMppXj9618fW2y+ed7RU67ZVvu7/xQgRxlxq6yySsXD+8Vmm20W73vf+wLN8QJgD5iIMyeCe3xAN02oPPn4gXxvtkqPOCK1y04753kvvLrooosGOQ8U4UkfoGIY0wU+SKV+/EhfNev02xrEM7fffntYB4xJ8SXQaYw9AFkfS3ynK/0MdAHzyq244oozZNNHOkU91i+9teWWW+adCV82ptOMcYZCL/9g8H/0ox8NOpNRhGZ06svJ0y7iGAb05VJLLZUx0LTE6maNNdaI8ePHB8MC/qmiXjH/P/3U08HIwS+O59kdvPDCC2bYncMPaG0eOgWyqRhInQhH7nIqwI/LLDNqJvqXMubHyYGRI0fmPCn14D9yC9ZcccUV4qijjgwf6/NRM7u3MAknSKljMK8DDuj7GixlV7btTHDJT8kdc8wx2cL/4x//GBYyL5CtPIpxv/32C0AQ+FWGQLnvd/flbUaCRBpQeVS1BWzyLTAK95DK62a7+4QTTszlLWieIopTPSWklPK24yGVx8k23GGHHRY8ErxM6tY3C9tWzaEfOTRb+QRpKd/bVZ8BbXVR3LwkAC2Fiom0yWOiHW0TkOhEqV9wwQV5a17aySefHPIqDxAYoz7whBDKRxxxRD4+gB7GaRHJAyDwwCl78MEfqhj2qCzMCF3AxGLo1H9GDWFH4PpyoDwEr8VAEKvX4uONMR+2MPV3q622Cu3KL5SFmFKKlFIGIpT8G97whqwULHL5BMKW4aFtwllcG1oKzE0K4HdbrQDMm9/85izY1c8JARQBAIAMT7l1yJilyOVhoG644Yb5SEonIGodWHtfPe204HnkAb2/8pQ6usNDt9pqqwW+56kj21LqWRPWiH7pE2+ovmivHqwzAAl4Wn311fNaUk4fyQplrTtl/RYvvV5HuU+pp92UUlCkPJbk5nGTJsWqq65ass1wffihh/LRBKCN11Eir+4yyywTxsnQFzhE0Ait5EE7v+WxuyFOeUaSto2pWz/lbUPvFLDjwbFi/n52221BnjKc8Bw+wS9qSKlnzvEI44o+Afr3/uAHo8yVfPXAEFhu+eXj7l/+MuhoOpVOwKvqxmMM4zXXXDMAWWXttq6zzjqBHxnFneaW3rrwwgvzGmGAKKdfhW/Vb70I7sUL8shbD4C6ftDznH/4s56O/xigwByQllIPHegZa8XY9bleptzLs8IKKwTjgvEtX3M8fl/7wx/m3RA7HbE+xQAAEABJREFUX9ttt21em/W+aocjwHjoXGuhtLGgXx/+y8Nx6pdOzU4/GG3SpOMyBoGF7JqgMRzhyBiZ0CnAP2R2J1oxBgB5u5777jshGGtoL5T85ui6a68NO6C77LJLNnbxVUlXt92kLbbYssInrwpOCc4cspi3Ho+mlEr2QbsOOUBPkFNoPGC8xQiN8O55zRCOxc3LvPbaa4cJt5g23mijuPyyy4KSRc3hw4bHY48+lj3ytkaAWoLNA7nqsuVCYV540UWx445vzx58HnDCDbi21YYRUpo+SU88+URQ5AQh4cDiY+3rA68dsG1LkVXvKEonha5vzWCMFJeHRLWPQQ7Y/4Cg/AhVSvGkk07MBgRhTPAQeOhhDOjj6iiKc7c/rBiTx4AgA6rd8wCgE08FQ4FnhsdAX/7xz3/kcTn/Om7cbvnBHmDeboVdiG7CxRwB1bxt5k1dG2ywfuy2225ZuPPkoRP6O7fJcGHNAjLy9hYYBWuttVZ+cMpCQiP5lbXdz6jTtrg2tBSYmxSgXJceNSqDU8AHUFA/frPmyB/yg5AnIxix1qg8w4cPDwAWgLBGxfWEnr/qJjPwNk/6F0/9YjbCrT2eSwDKjhePKDmYUsrHUMgsu3TSGBkLL7xwT4W1v+QF+cDrXTxGt99xe/Yekg1AmrG4Tp48OcdPnTq1VsPMt9Yd45k8pGC3qDyXM+fqiVlm2WUDHRyXI3vEosMv7v5FPqJEjhizPqAZWsijjN8UKJqKk2Zrm1xRnzLi2zDrFCAvx1feX9cTjj8+HLfhIALwDzzowAC267XiW15SfM7Js0oXA04ZBijni+M8ZL1Az9CBZD0j0246oGpOlRFe9apXZUMZPwBs4upBObzJgLZWpKnHGqDPBPqE401f/XbMh7Etbz0wJOhmz7fY+bFG6+mMbP21U1YcU8ZOz9Lh1ps1Wy9T7hk0vLR0ql0rPFzSXOlm6/KMM88MeTnqlllm2bympdfD6pURjuc544yrnrYg35Ohj/z1keAExBcwFAy08MIL5WOIHI/miFGKPp0CfLNwB5mI/oxGdZKnEyd+LJZccqks2wtN5eE8PuHEE/MccRTjGfHyuHJCuMIdnJ+TJk3KZ/EZIIB9Jx5WdqDDkAP0hDtLFXMjFMa2uHhuWL877LBDXgwURkqpEgopLMbjTzghTj7llGnC6bnnnwuLk7eaVUwZTai2Di14ngTA3HGZDdbfIJ/V3nHHHfOWIfBJ8EyZMiW/Icd9vPzPPcayPU6Iue68887Ze8GqA6ZtdW+33XaZYXgrXi7a5yWlFECsh5Gcc+Qx4AmjECdOnBh77vmeICzXWut1WTliIEaDNvTBVieGN1bMzTggmNU5oRo3YWaMwDfQgDbO2+pYSil7S/bcc8+wLclLcdBBBwVhDfgTpNH4ZxFi7oUqAEOQpdRj+LzmNSPz2Vg7FhYeQ4URZQz6QfjqV6O6jj8pAYDCYiqCEn/ou3qBqo4F28iWAnNAATy22aabBgcAYx3/AsGUAnCLJ/FjAZlAJ9mgyZRSlgfSGQDiugWy6PcP/D5c5XXlzaznVw/D2s4fsG59Auwp9ay3el5yDUCybskpabx9vE6O2gDl+uzYoN8CQ0G+bkGfOCsoMzK01NspP2dLkdt24hg/rjfecGM2zNHNOI2pTjO081ud5J2rwHMK0AGeAJ64Nsw6Bcw5Q+mpp57OnmH0VgvPc4qU9ZzfgrkBKIErAGiXXXYW3TWQwX95+OGs76wbYNmVrqaj6GnzLi6lNK2e8tt844lpCS/f0BH0Du934Tl1TT53cvai2rl2DAI+4HTCy0A9rPByFdMu+gJMW8/4WJiW2OFGHfSUOulLzi2e2A5Z81ofPXp06CPaNfOgAecjXeuZMHnRQz40cC0BiMTv1vkTTzxRohf868tswbCE13bccYfgWPzYxz6ed5MYi3AML/xJJ52UHzxuXhme6NckVuaZyZMDr6A/w6xJfzzEwQHPaAN+wiMppYyL5CdX8Sl5at14OYIdA9jE7iXHqTIxyP+GHKBHj9dVnlnKASilpGxJs9JY/CxsBHeGyRP673znu/K5wIsqTztAiynUYRIAPwuSkLHgbLWJ5yn6zb33ZkH25je9KXjFlRGcg1tnnbUD4KfMivCTJrAC7QywJP0mcDCSdikl+QkO+TCAPP0JylGG+pJSCh4rbajT2XGLn4JbfPHFcnWEtG0oAoPXwpEjRoZjO0A4wMszwDgCpBlELEv3rrxeaKEyjIhGzscWwcWboz31dxJUGNkCeNWrXx36qR4hpRRowvi44IILQrA7wkgAVngonFFLKcneNaTUs9WPLhazq8zogEYWqDGKa0NLgblJAbxmLTieZ50xbnesDP5JlVdm8803z/yOD5d41RKRUspg1RrSB1dlhg1Llbd6uKiugXK3Y+ZogW1kiv/UymNfL8BL6YgchcGrap2PGDGinmXavTUNIFFa5J2Ed73jXWHHUQBMlOUs8FvglZSvW+AwsHuw7bbbhmMS3fKJ50l1rI688DAv54vfyy+/fOUVWzI/0D5isRH5jSVkI1op56rfrsCXOME94wQYBerFtWHWKUCHOkZKdzhy4qFsgJUeMz8Mr1KreWG0ApW8zosvvkRJmulqvhiJdC8nFD3kOChQZKecp14ePIcn6hVwCEkzx9ZSPY1eovP1BcAtaXadPnvMZ8NxWx5cetGOlTeP4GXrky4u+WfnSt9Zkxx7pW7HwVLqXV91a2vKlCn5jSh23MgORopg/HQoWYEOyqMFwwN4fPLJVxCgrwaPBhwVnqerfmYgjT/hIFgM1sG3eM3OSQl+C47lwWvK1gOMKO8uu+wSY8aMyW89RH+8hf7mgYMD33KGknOMAHwgjWEpL51Q+ujUhB0vRgQ8YxfHMxjy19sejPshCeiBRMy/+GKLBS+6h2cIdIsCWKYgnF+31cWrTOCzkigsD8C+FNV/L72UFUcdbJqQlFJWwsOqK4IDsuLdl5DS8PzeZIIlpVSi89XEqlM5EQRVSqlS3gtFSjPmlT4rYeTIngcxlCl9WnTEon5OCyWeIMB0hCFDgEHB0GGQEK52CwgHFiVGRS+gAFDfeeedg6Asdak8pRSMB/eCcabUfTzaFuSrqK1IDhYdYQvso5FFSTEQuATv0/94OljcPDu5QJc/tlMtZMqA4NZOPSsAoP16XHvfUmBuUcDaIE/OO+/cIMDtnAHcjpMBFsJyyy6XZQwPD1mhbfKAElhkkUUrD//IaP6TTpYxSKVZv9Yu5aDOn//8F8FQxd/AknjKzA4bkGxNKdcplDWl74I8a6y5Rn67yDbbbBOcG9rj2LCLyEFCdsjXKVBQHtLjHSd79a9TvhJnbEC8XQ1v02EQAUcesgS07OQtOXLJWHzxxfMDwPIrqx00M7ZRo5YWNS0YB1knuJ+W0N70iwJoTI7iKXKYIwwP8L47802GOvOO31SIN4ET+sFciusW8DzANLryUHMmmWM6xEPQgJFzxk899X/BSfTPZ57JXvxSF1Clb3SeMiXeVb1Alfl+8aUXReWwyCKL5PPP+FbfRo4cmevGy/jT2Jp15YL9+KMt6ximYPwAlgwSOCSl1I8aOmfh0KLLGEl0siMawCcjy/qwq2AOlNYHV+vhueeed/uKCtZ/SjPS2k+6n3yAIRhaZHEJfgt2T81fk2Bkth0Xu4zoz9FoLhybthsA7Dtfb44YX+PHjw9HhTmQYRhz5CgX2WfdwJ7WRkop9IuRgO/1z7zFIP8bFECfUgqThyDR5Z8HF9ZZd91ATJY/ocFrRgjYEvQkuEUMPPI6TJw4MXvVHdN58YUXY1iqhvZSzPDwpaYsmpRSPiul/Xv+93+z1SZNYLXdf//v8nEdikd74ushpVT/me/Vm286/JFGSLl2SJ4W1aHaagDTkqfdqIfgsgMB8BKm3mHLqAGaPaRKUWNCAJvw4N0jPCwKjM0w0qdplVY3ncZaRXf8X90EqsXy5BNPTsvDM6MNXr2iJCTqJw8fmmuntJ1SyryQ0nSa2kGx0PR74403zsZHSj3pFg1Pv+M4+hDtv5YCc5kC1pfdLQr9mWeenfb6RiCFYmDQM5x5pK1DgOipp57KvcDz3ihCyFuDIgu/q1c+R2AcSaNEpAuURUopgx4eIUrfmlWWwtp3331nMLiVaQaA2briVdePZjp5ZvdMn5tpnX4DVTfeeGO89rWvDUYAmd3Mpz19FM/wAOApVkqRMrSzgR7Wqx1UHjcAz/M3pY/asauIruutt76qcpBuHvRb+ZR6ZEBObP/0mwJkpnkCHMtcKYwfBeBaujiecfrVuXHOH3H1IL+8ruLxs/oZXH4LKaUg58nxRSrDFgh64P77g+c5qn/mFaBShzXS5CtrQdvqcFRFvqrYTP97VgU/yTdT4ixGcAoWLGHXihFvd7tZjbHXadhMb/72Ck9ORwYU/sb7ds+M2TqkF1Pq4WvrwNpdpDJc5GnWtUD/rkhAr5MhZZwA9V//+kiQWZwejC0PtnYKjiTiBWXrc8TI82wSx2KhP/qiP7ni3nFlO6Tkkzj5nLDAV+ZInN0ac0dmM461I+B/V7yIb90PZqhQ78A3b4EiimMgLCHBtp8rb4IFw7sMmBIwwLtz8rZflfURDJPrKAdPl8UPXKaUguA3WX2NiiBhhTsr+K3zzsvvPffwBCVu0pwzf9USS+Tz+n3V1Vs65rJtzjABUHvL2980NMBsjB60An4pTcbItdddG2iDlvJRruiBRhS+RXPuuecGgVoXwv1tu+QDpgnq5ytPAutUW9IsIHPBwKDceePtsNhpISQXGr5QsGotmpRS/hos5a6/LGfHcZR1ftFC4kUCjtQtADvm3AIzJnFtaCkwtylAuXroHSjlsSRznLME6Lfdbttpr2PFy3bBAF8PbwPidsIockoIv0q3pUtZWYsAFMcDT7aHsfC/NckTziNISfA4SePtpNA8nEtGqovSt+6bYybTrBkyUxvS5SVnBUCK8jI2vwXyQL5OQf7/+dX/hHUupFRp3VpG8sYbydAEWCQDyDnAiMwm7+yYos0224zNzzeR64VmaIVmdgH0hTyrgyj9BOisc7Kr1nR7208K0BM8iniIc4dHHX/Qe456ASyOsY54+RiXN47QGZwvwE69GfOLJ3mdHe/Cy9tUOz/4Wl10EP19zX9dE+Yfr2mbHncswbMoDDR8zEnniAUjud6Ge33GbwDSww89nD9EKN5aokvxiv7jI4aHZ0zEueJZeWclKON5NA4vukafGCPq1FfGpuMc1tTlV1wejmhYq/1pg7ON3oNV6DUvr/CWN1jGrpvd9ALerSdzow/AY3/qH5J5ZqNTeAmdzz77rCBryVDPRpBn5hnesDPj6EyngNfkJTN43MkkctQRxTr9nb13nJtsZgR4/tARRPNijjhFxeMrRxd9iE0e8+XYMDnMoNBH/fUiFZiTwwO/zsbQ52qRAQf0AK4FZDvOxFjswtixY8OVd5dyMMGsJk9XPc4AABAASURBVAoAg5swQke8M222jwkW5Tyc6pWMhIctccoOWLUICaFCMZ4Eaf/45z/zmU4T5zjHJz/1qfxmFpY5JvLuZG0vvMgi+QNYyuj3P//xz+zxV3ep073F7VrijK/EEUIA98EHHxwAa8lTv6rfmOv91W/eb3HSS35M6rf+sPyd7+UN1+fd3717fOD9H8h9dlyA1Yg++uPcvDivfbSVjwkJV0Lk2coLSYDpa2lHG9oX777El6t5MAe2RCnlUtYc2i3x2xEBvylq7RKO+stiTinlNxDZ4nXmUj6CdNy4cWGXgZADDHj4tFXa5eVBW8eLXmlCr9Cgvc5bCqSUAqDZc889AtgGqglzD0IR3Id99LAYWW33A0NeVcubYyt3zz33zO+SBj5trdsFs67JFM+2ACHKOPpg58kxODKHzKLsHR1wphnQBYKVtbVsXVgf1jKldvbZZ+fnf5pUoKgood/97nfT0jkorD/BztzkyZND+34LlFOznvKboX7vb+7NThIyuMSXK6eAuhxRsC49xG9to5ljNsDKfvvtl3fYDj74kEAPhrxtbQraFc3IBHTx0BqlXOrnoSNX137d62LppZYq0e11FikAONsxIevRW8DTPpTjjTeOrwDRqv3TH/+UnSz0Lr4WVwKdBCzZLQJq6QWAlYxmkFojjnceeMCB+XkJD3DjRzxOZ+N38h2AYhBYT4yJUn/9ygDBT/QDg0Gae7oe3wLFAJh1Y12IgyfwjLzdgjHgKfrJvXzKWBccRQwGvKv+suaMEU9bD+g1adKkfBpA2XpQr3Vg3Za68TznUwmMU2ny0MF0WEo9hrLxAYr0KrrV617Q71NKeaf+9NO/FuaRTGTo4xG/o5//0PATh38iH5PkmCWnC+1d0V9V5oosMgf1OeLlVwZ/wFrSBXHWEH4lk60f/eKYIePg05R65lH9gxUGHNAj6sEVuHV+CchsBsKlCBJbIBje9jYPfbGAeKKc0aSsKAXeMPURKpQiZQG8fuTQj2RlVIi75hpr5O3zsVtvnaN46J2xAih55IFOT88TPCZWJsJHcLyFNwJYXW+99aadl2fJaVv/CEVBnAfZxOkzr5O29UudzUBZUrYHHnhQflpeOsXm/Cz6YDhxAuYhcJShBAkXRpAFsOEGG+a31LAyKXd9oVSlM1DQUVl04gG0WHgdWMBHHHFEPmOrDQETY+Bm+9JKAC4AH4bKX/7ycI5mdGkDUPCJawLQXKCRo1EsZIYGwE64AzAeLNEOmvFaeAc3jw/lkNL0RUIQXnHFFZlGFlDTg5Q70P5pKTAXKGBtHX30MXH66acHYxm/8dZbNxwHpQlgwvryxgPC3pri7XGfUsq8Sq7g/xJn+52xevTRRwd5BTiQZ7w95COFTs5YG9ZFPYgnh4qMLP1wBYL0xwONjHWAS956eWus/hsQUrZTIAP0AaBBj2YedCB/AETKUbodNQ8tolmRKwx0HjHpjHNtyqMvaHLA/vvH5085JRtR8giUKW//8ssvH9tut10MGz5cdBtmgwJksjcUMSzpXkYpw4uuw4MF5Kga75HHAHhK02WvtJRSPsNOXxb9wng99YunBp4H3BkPDDMA2ZpRznEHu8baohvJfWvGVXqnoE/0yB/+8IfgKcfLeIxhXPgX/wjlN97Tn071lTh8TB8J7sXTy3QNXrdOS32u6mesM3DkO/qoo/P70q1TZesBLjBGa7DT+pSXzmL4GAfeFidwNtoJ5EBDt77GocyCFOz0bzRmo2CgwRV7Vs4UGMKcwlD9HSvgzeHC0dCJhnAHrGROYbpO9eIzeIlBWnCgfPAoJzJAT2bDVpwrcBJZKc9gh2ED3QELgeeWAmNhNwNrn/eZUrJd62wbwA4E1vvKsw4sUgzOpFIsztjLY+HxIvCeAcbihNdWgN55VAvOb4FCcZ6VccDTNGHChNBHaQKgDVibfJOoHQpZmkBAEQKUFwBNYekHQcALl1KKV7/qVbHCiivGuuuuE53+Aec8egKGk2exxRbL76dWTx3QY0TgQRn5MBKDA4g3BvQkWMu4MSeFbGyAsvETGHtW3kTj5gUhvAlpAkmdgvIYlVBjVIlrhtEvPwzFU3fHHXdOO55EgYytdlwAIPMDFBH4lLw09RgnbwtlX3jBFaBHB0oHLeUtgSfFVi36MsCa6SVfe20pMDcogO95j4EPMsZ6YcDW66Zs8DpDtaw/coLils8VeAIWnLkXR05Ya3hdvQLlwSuHp5W3TWxtWM/1oB1GQDfAQBZYYz+45pp8VIEsqJdv3nsOSZ86BSBGPxgk+tXMQwZb42QtOSOd3ALEyCPyxi4ox0a9vL4D9cYnz+dOPjm22377/ICxOhjuPKKO6QE/1npKM4JL+foX2lwoQN46OgAw4VM8TdeVeZNHwHt0QeFVcSWklILuMKecVCn1zMmKK60YdK06zScdKb0+59aN9YPX8QYArU+l7uYVD+O7ddddNxwTggOsR46nJg+X3/pd9GKzvvIbf1ojxu5ePGxB1+FHOqjU5+o3Ix2voxVjh/6tAz11CHCBPqAhHhfXDOSBcQGqDPCSblfNtyLQ921v2z7IiJL2Srmir7mBF0499UvZkQLfzMr4YT/zRSbVcVOpA8/BIQxb817i61f9AOg5T5rz7OgNHsTH+B226mQ41OsbyPsBB/T9Gdztt90WFpyHwljqFGK3ibVwgM+UeoRLf+rvlIcAmReLiGfhhRdfzFvxq6/+2k5Nz5U4dMCIKXWmA0ZGp7nSWK0SViomdz7TUZhaUr4lwLSbUud+5Uz9+MODwetDsLO+uy3GflTVZmkpMEsU6A8PAy/W36zKEHKN7JmlDvWSGQCyHfzjm2/Ox4V6yTpPk8gbY+urEXnIrno+XkreeWmUs2s9vb2ffQqklPJbhhiis19L55LmnKzvnNoTK12+nl+9/+Vsssvuw2S+l0CX9l5i/kx1JNYRZEeLeO5XXHGl+XMgs9lrBrzwzLPP5ONeZKkwm9XNWbF+lsbDKc0ZpulnU7OUbUgC+peqITgKwoLlWebhmVVFWVUxJP6nrHjJWHLFIzAkOjaXOmHbkDVM2HrQeS5VO1M1zvN7+wJDj8duqC/4mQbQRrQUGAAKMA44QMhODzAOQJNzvQlnlR977NGwk9vJUzzXG2wrHJIUIOO323a7ePuOb88PSjr3PCQ7Ooedeuyxx4JucwzIhynnsLr5rvjiiy0ediwd95oXhuZ8R5A56PCQBPS2nTx84yFKW8IpDT1LaFZonlKaduZ+VsrND3kJXVu5p556ani2YV712XarNj5zxBH5wz7zqp15XG9bfUuBeU4BZz2dx+/tjPI878QcNMBJcMopn8+7tHNQTVt0AaCAHXpH0zhy7JQtAEOaaQhljM7fp5RmSl/QIxxnchbdcTCe7wV9vPNyfEMS0PPGO//Euz0vB9/WPXcoQNA6azYvdyDwAkW/6MuvV5s7PW9raSmw4FGA/AQSyND5cXSUuiN1rbdufpy9ud9nzhz8jK/nfu2DXyPdht/bo2WDPxfzew+GJKCf34na9r+lQEuBlgItBVoKtBRoKdBSoKXAgFCgaqQF9BUR2v9bCrQUaCnQUqClQEuBlgItBVoKzK8UGHBA7+HJvoInnudXgrb9bimwgFKgHVaNAmQUOeZai+71Vt7+lpFX6LXClxPl86pf15ej5viin7NSibaVce1UTny3dPH636lcGzewFDBPnUJ/emEeBeV7yy9dvt7y1NPknZv8Mavt64s+CO47hVKnazNd33sr28zf/p77FDAvnUKzJXnMlWszrfyWJo9Q4obKdUABvdczef3UD37wgyjB65p8da78dp06dWp4TeFQIVLbj5YCLQVaCqAAIe71cjfffHOWYXfddVf4CJK0bkEZr1tV5nvf+1542N9XKSmGZhlxvnAoj+8uNNObv9X9q1/9Kr+ru9NrY5v5+/qtfd8Auemmm8KbpfrKr31vt/rJT36S6eFruL5uXS/nq5je4kHOo4GvOSonD7AztZL33jXuzWbi2jA4FDBPvimCp++8884owTcBvEq0W6/o6vvvvz98gZz+9nn8f/zjHx2zm3cfPfOxqP7w13PPPRd45tZbbw33HSudhUj85u1PcEh/3pqjzXvvvTeuv/76+OEPf5jftmO89SbRBs2s7SlTpgT5oB15YB500V6znPQ2zHsK4GtzWPi5XH/xi1+EudMDcu/xxx7LHzHDw/I8/vjjkmYIZOwdd9yRZd2NN94Yvh8wlOZ1QAE94vnSoo8VleADCz5KUX77kNK3vvWt/FGUGSjZ/mgp0FKgpcAgU8DXHL1Okdwiq3zo7bTTTou//e1vHXsGwAC5PhzlHdM+QufqoyWUfLMQkHHRRReF968D9c305m+gSPs33HBDUErN9Fn9zTjxhUbfAAFM+ioPjBubD/Oghw9x+SAPA0ZZypQ89yEX6cZl/PpbFKG8PnZEQSrThsGhwAMPPBDm0gcbzWMJPh4G6HfqlTkEdM2/ufXhJeV8lRYvNcsARPjDhwZ///vfN5Nn+s2Y8HGz+++/f668Kc6XZ30Yy1tV+jIggfmLL7440MN6FXz08Lvf/W5+X7rOeuWk8RiztU0uyEdOAPXWJODo9dvAnzJtGFgK/Pa3vw0fNSOrzVMJeJ0zxBwB/D7+R04VHvaRMPxSeuteHvWQZXArfvANHoZbyTeY1wEF9D4q4VVqBDpieBUVL5SnvH0syGKQtsMOO4Q3p/RGmDatpUBLgZYCA0kBnmVfieRd9KVLTggAnJPi+9//fkcPYgEwXsP75je/OSZNmhRvectbgrfaa+qaXiDK31cIeRGB9b7Gp14eo7Fjx4avJNbzA0yMgmYb9Tz1+6effjqMxevjgA+App7evOegAeR483fbbbeg7LyJBFii5NCGZ/OUU04Juw6f+cxngpIEzo477rjQP6+99Z0Rb+SRrz9jbvaj/T13KPCnP/0pe6HpY196feMb3xgbb7xxrL/++uFNM51aYYzh6TvvujN8XROoBfKBZkZbs8w3vvGNOP/88wM4Yuw10+u/7fTgR3GbbbZZ1N96xFD++c9/nncRtCdPbwFow3eA2CWXXBL6rY7eytgZOPjgg8MaZsQbn90HBoZ1qiw+Z1D7qNyxxx4b3iNvbfuKqDZ8F8LatEN14YUXhn4o14aBo4AdRzuI5ojsLXw9ZsyYIHc4Y/DZeZUj2au3GbB4/pvf/GaceOKJQS4y3Hw1+JxzzolRo0ZlWffOd74z7MzIQwYPhbkdFEBfgDtLhxJ67WtfG/vuu28A8xQEQO/VZaYcse+5556wgFhaTSHwwgsvVsrikaAAf/nLX8ajjz6aFyvhxELmJaA4KB/GgwUpr3z1CXAvzsIrbdUteMJF+5Sjqz6pUx97C/pgS5pCU79yrEK/CRQKTJv6hfH0o16ffPqrT5Rs0xIkzJRTJ+Zy1Y661aPfZfyEqHbUh0GbbcnfhpYCCyAF5nhI1hMBz4tJfvFdhrstAAAQAElEQVTC8fScccYZ4b3vlLc8zYaADmv+Xe96VwCs48ePD0B+m222yTIN4C5lrE9ggWfcK2BT6v2d1GTHf/7nf8Zqq60WjAXguNTlytP/gQ98ICgbv7sF/SYXfPyOtxFwAsxT6r19nneeW3KccUOGU4wbbrhhJZP/mo9NXnrppblZAM+Hc3bfffcAABlHQI9ECnLPPfcMdamzlUuoMrABDzgK49WJjFZzw7AU8Ouaa67ZsUN0oXkb/97xASxz0vFw4sWpU6dOA7DqB3R57lNK0Rd/yX/bbbfFZZddFr5FAyNE7R8cAGQD3H3pYYblFVdcEdagozsciyn1ztvWM8N05MiRccIJJ2QvPWPU+oBN6Fi699prrw2vnMT/AP8RRxwRPiRp7GSFLq+99tqx3XbbhfUoXlwbplOA4wBeg3XgKxgGRoH98IGcrgwruKVTwAPyyFsP8Bd5aq7I7S9/+cuBp08//fSwS+TDdeaSjGZ4mV9ykGFq3uy08N7jhyuvvDLINg4PfM6A4/n/zW9+E+Rnp/brfRmI+wEF9AZkIVMYFrxrSikv7vJbnDyEusXHq4N4FBMFSmEAyPHyv5tv/lFlLX0q9tln7+Dl9xEKi+qLX/xiPttKoRI0trxssVAq6uIhMlGqMem2xQmuffbZJ6Rr6+tf+1o46yqPvjA2MAHDQ5+cl5PWW8B8tpNNPoGgj+rXT+VPOumkqu/7xF577ZW3Oy14jKFPN998czW2T4e2lCFoCUTMpU1CjcD72MSJsfcH94737PmewIz6iEHVQygSNqd95St5G3+vvcZnOmmXx0I9bWgp0FKgdwowpHnhl1tuuQBKAVIG9KqrrhqUA7nCs9msBVjdb7/9QlhyySXzsQFOjNGjR2eww/ujDHBO0aiT58d7t8lAad2Cc+fA1NZbbx2ARzMf+UDRUWbNtPpvgIecpEzJSOBaem/tU8LaN5Y99tgjlNV34IbSJLPIMIp62eWWzV+CJNvJeUp0qaWWygaN8YvbaMyY8C0LwAtto/03oBTg+HG8xXyad7su9A9nEQBLJ3fq0GKLLx4jFlss/vmPf+QdKjoH38mrnLrc41M6GX8ATnhBfLdgPQDAPKibVd75Tu3jbfm61VHi6WDAbJVVVske10022SSvvZI+8zXCuBnbDO8tttgiG5t06o477hiM6E033TTXYU2/+NJLQT4YK54XGORFHqCpMdDbztPL26nNV2ocugDS8BFvt2Ms+++/X8Y+eBBdyATODnl40JsBLgTM5a0Hsg3gxnfu8bV5heucAiF7fN/GcTHgnHMGrwnS8al73n2OC0bkG97whoxZGYbrrLNO5gNzav7rbQ/G/YAD+vogCwHKtZ5GuADYtpRtY7H6KUdeLl4ci/muapsPeP/pf/93vPvde8RBBx2UlcQFF1wQFBSl88jfHonrb7g+fDmRgDEpa6yxRqhj8uTJeTJ4GYBgykRblNqKK64YXzz11ACgCbuHHn4ogHpbLhaqLRnejHqfO91jIt718847L+7+5d1B8a+77rrhHB7m+NGPfpS36QgICpJSJxCVYczwAPAsMEpsewLitu7sPOiP8f/m3ntjfAXUP/XpTwWhNbkalzzqwbjqMA6C5UMfOjiAEN5GNOhE+07jaONaCrySKUBZ8BABnd/+9reDZ5C8cXTQziBATfA3aWStcwRstdVWQW5YbzzxvObqGlMBWTKCnHMUYe+9945ddtklKJpmXc3fFBPw8JYK8JBt0u3iOZt/11135YfzgHmOC+0x7ilP+epBv7bccss47bTTgkzi8dfPep7mPQCPJgwPRxgOOeSQLH95wTxQhh7qXXihhePFahdVP9WhXmXJLzKcV078qGWWibe+9a1x//335wcPxbVh4CjwxBOP513uJ554InjnzafAeYU38Win3qxR7a7vvttulY69IfMOYISP6BjA3ZoAxuhfHuujjjoqXv/610fhh051itOPKVOmxOjK8LVGxNHn9Do+xs+MQbvoeF2cNMBK3nqg9zjE6Fa61O96eqd73mF9xMN0Ltwg6D++pYuBvb0qR9wyo0aF4xieOyEP9MUpg/quAjmAJo7r4f9Obb5S48zjz3/x8yBX0Y4M3HXXcXFDhdtgQPOK/xiFTjMwrOpBnFMIZF2ThsoB9JzAjAZym2MUb3uIWX5z+ba3vS0YXer56ulfzcaEe84NeHGFFVYI82uHtchmxiSsyTmxesWnJV6dgxUGFdB3G7SFZHvjlltuyUrC2UyTzApzxolX2vGZ73//B2F75vCPfzxv95kkC87CmVb3SxGp+o9CPbUC6BYcK89iA6YxAasN6N13332D59yV4SAPIAzwp5TixZdeDNY9xiD01Bn9+EeJMUYIlIkTJwaP+corrxwEnHpYhhiXgjdmQJxxgbmBAYxk58D4WZOMAdtIgMFiI0bEMUcfHeokcOw8APW2rAhA3UvDUmyz7bah3xQuQ0Ee1q++ydOGlgItBbpTgJcPWJg6dWo4B7zSSisFEGwNTZo0qVI+N3QEKYQ8sE35q50SsOY5LOzW8VYD3P/2b/8WlL6tXt6gvtYluUUuqXeZZZeNlJLq42tf/1rsuuuu8Y53vCOfVeaMsDvI6y/esYecsfZHHwEn28nO/PbVtqKFHuQMjyUPmJ0CO52TKnpoR99eu8Zrw/g4K5555p/Zk0lRA+7kE2WuPs4R4wekyHZxbRg4Cjz22OOBJwEgfOCYieci6EX6iYOpU294Kddbb718zpxBio8BrG222SbvytDlztLTWXapis7si8cAeoG+sx60jecOPOjAfHTGMyz43w4QJxmgvv/++wcHlrz1wFuuj/Q5Xu+rbX3WFv6ENfCuZwqUB+CsJ2NMKeXjdpx/jAqnABi3eJlj0O5C6QdASOcqp+4S314rClSiC83tdsAxcBw5+OlPH5GPC3oOB/08rO8h5U6B0UUGVbXN8D9+Jn8YYRtssEHAdXYUGYTa4vxIKWUHCuOTEQlDMWLx9uabbx74RxrZyGsf1T9yS13mmzGwebWLk1I1kCptMP8fkoAe8YFdSotl5ZwqC5gFxyK30C0MARNssOGG0x6Y4ek2cYWoL8VL2TMmniWVUspn3tybFPXxagHRvFe2iwFfC5cXSSA0UkrhP/UwKkw2hVXa6XYlPASLedVVVo2UUti259kS56EjzCIOw+iP8bEOMTnlZktfn3jdn3nmmfycAME1bty4uOjii2Olyji4+uqrgkARAH20066ACfUbrVJKeWu7jL9bv9v4lgItBaZTwHoSrFVOA8cHKBFGOpBO6Vu700vMeGctUywM+quuuioAEgCHcue95MXkaLBeySVHF6z1p59+OtzPWFsEuQj8AjzWd0nfcostY8KECfmIj4dNpfEWclIItohL3jm5ogXAgx52TzlLgECyWrzjScZhjACic6e77PKObGyce+55eUzkJ2NHP9xzcpDD5K24NgwcBegiOhYoZ3DyPDPMgBa6mOEKHDV75GFD+T3DYc795gHlkALueVLxN17kJbdG8DU+d69O9/V68TsewEd4oqTRuTym+Fhd9BnQDNCLs6Z4W0v+2b1qX9vWrPVlfGWtA4G87MXxxjlmh87aFQ/gKcMxeNedd07rgl0BOt+OVOuhn0aWaTcvvfhSwG2eNRBJrsAsdvrwHznpGBRHZjPgFXQ1X8rWA34grx3fMo/4h/PUTpL6vKHJXJcy2r/i8ivC8R67M05rOCZV0vEqfHX88cflUx8MVMaHuS15BvM6JAG9hc6zRMhTgoSJ7WWEtcA9qWwSbPla5JRWISILfIkllig/8xVzWFCuIlwFk0O4UMisMG3x2mvPlZDbtvJsS6vsAkUzGC5KKEf04w8BQfDom+wpVaZBFZZ41Yz9lCYYP2VoXIwWfdEnng7GBOGpTxjL+Xy7F8cdd3x4pz9jQDn1lDB82PD8NLcxi3MVjN/vNrQUaCnQOwWsX+vq1a96Vey8007BICZnPLBHJlEO1m2nWsgqu22f+MQn8vvi7bZRAnbtePZ4L5Xj1QaqPEgKrANIQBFlJb0eKDgygvdy+PDh05Ic16HAjjjiiOAlJSeAM4AD+OBAmJZ5Dm7QgwNC+7yRxkIW89KPrrafGRycIZQ05QiA2YEcvfroOPSjh+Y3pygPlJVuqItSfuKJx6uoamu1+tv+PzAUMA8e6rSLg7dTSmE+nR8313QNI67eG3PFOE0pBRDvfDnd7JiOs8jeAMPIw+N4gYeVwwzwxR9+43E6uFkvA5fetMZKmvuPfPgjUfjbLhmeYlCKs/sMAJb8s3uFO9DDunI8aOzYsZkWPMDWF6CHHhyB3lluTRkzvWxXw1E8Dxjfcuut03bt1Gktopl1O7t967vc/JsDn5EBZQRZ3r76VfktM+jNUcGJ2SngAU7OUrZcyRi7lUIB3dpgYMJx5pADGQ8KeApIdzLCPDoBwovP8FSnncXPnXRSfOvb385HpTlb8Yi0oRCGJKA3CRZvSik+/vGPhTN5AgvLwtl5553zdp5F98QTT1TbfRRADzkJDsqw59fLf1Nkz3g0/gG0PUzz6vyazE5tYR5nqEpRCzOlqsIS0c8r4ZDSjOVSSvkMvyr0xVWw8AnTlFIcccSn85nGMn5nwAgVCtQ5+O985zvBA+dhEsLS9iiFWq9PnSnN2La4NrQUaCnQPwpQBmTSiy+9FM8+99y0QpS79Uo5WOPTEl6+ocApBNv0zpY7PgjMW6MppWBY28oHRBjujHYeP8YB76bnZCicaPzTJtkFGBVlI4t+UFj6qj8ppSzb/BZPfsk3pwHo4/0iZxgspT71k1365t75V310Nt9uxudP+Xxs/pbNQ59to1PiygJvjCL0MIaIVl7FAP0zh97SARTbmfa7NP3iCy/kY1LmNKUZ58ScAa74yrETc5dSzw4wxxOwRB877uLq+I5vDdh95kQD7AGmpqGgHvyqD7yxrkJKPUaGNPyvn/qgb+JcU5qxj8rNakgphfVu/ehbnb/xK3wiMDqMC9CHRVJK+eiGI7/6w7OsfFT/OCh55lNK004TVNHt/zUK4Al0KlHuH3nkb/lEBf5iNE6cODG/PITnvISJVRynhbkpZcsVDzpC4+gUmVPizSn+wbv4EX664oorSnJ+TaudRfKb41hZ+ThKrrr66hg/fq+we+WYYEpzznPTGp7Dm2FzWH6eFDcxQDSC3377HWEy/SboeawAWYveeXaeqmuu+a8K1D+R+8Litx2Wf/TxR/0WntcTWXg/+9ltQRBpy2J2fh5IxljyCs0qLVLWo4XdKX16/pk9Tp3yi7ObQOFjpjvuuDM/6KpPKaXgkbctymvHe09p8qwwcliKzoYRzgSduqa3P3fu2lpaCrwSKUDw88Zb55QDbw46AOnO8vLsABkEv2Ny1qc1SHbw4tj9A2gpIV7FlHqUAA+oB+YBKcG97WDb9j5oQ/4ACNqqB4CD7KIEOwF+edXtrVcMBr/nJJAljzzy4PR+KgAAEABJREFUSH5/OGPDWO1eurfDULyOZI+H1+xaAFiUpGMK5BKjBRDyMBpvGm8mOa5f6vHwGrm71FJLi2rDAFEgpZRf9eyFD46SeS5C03QiXnf1Egj6F68BNuab7vEMiN+33357fk2pcvSh+cbDdoa8fAFvC54/4ZCi3+zc8ILiE+VKwAPWiPqtJe2XtHJVBm/b7WJYlvjZvVq3jm4wPrUHc/C8Gwcju9TriIZjYcYt6KvnC9BAHkCRQc6pOHr0avm4r3jygHHC0CVLxLVhOgWGDR8W3kTkvLxYNHaMkZwlSxxJ9owg2cg5UA/ixo8fn7/DATNxDKA3+Wsu8TVnsPlVN4DOsCRzzLErPndcUFl5yG0GqPnleDCvdk+vrsD8QR86KI6bNCnjMnmHUhhUQE9JILhrnSjDhg0LnnEPnQHwzmF+8lOfrKyi8WHr2paIBefhBg97AbjORimD6IifUo/CdDZLGya33oY2Tb6r+ni5nfVzHo8XjaBgGHjYBkOV8uVa6mJc2E620NVX4utXbZRQ4v1u1qWf4uXxajxnyJyJN35bSnu9b6/8Fh9bgIQJ69BYne87/vjjA8MD/JjQzoU0delXsy3tiJfehpYCLQV6pwCZBHwANuSELVmedgCdsf3ud787AB4ex/333z8/z0JRALuOClIiAL3jKY4mkDe2gR2T40QAuktgHGiPIgHmgYBm7zg9GPBkBkVV1jfFpV5yEWAiLyk/vx2noCSbdTV/d5INZMnxJxyfz/7bSSA7nFt2zODcc8/N3xA54ogj8qtx9dt55sUWWyy/uQb4cqbYw/0eeAPq9BEtSttohXbLLrtcfgtKiW+vA0OBMWPG5NcZAzT0CH1Dr51/wQWBdzwcmFIKx2joWY4zfEJP4lvPSDjyMmnSsXHYYR8NQJxHlQ4bPXp0yCN4gxJvtp0tOox3G683R4mH7EIDxow/6Zx3eE5/BMd9HFPTH7/1peSVv1t4qdplE+rpDG7j9dIMnnUAElDUT0fVGKXoYg0zSIxLHjLAMQxjxeMTK28xWkjffvu35R047eiXderhWoaOuDZMpwDMQgZ89rPHZA88OQGIk1kw2PScvd/99ZG/5jeQ2W0C6uFE+InThQEI25HdHA0wo28GwFHkFYeCq6ORZD3nigde8RbDjiwnBy+/7PIsB5UlywXPd0rrvXfzPnXYvG+iewsUFaFOWPDc1HM6g0c5WWS84HfdeVc+B47YFi6rnGCwiBxDWWqppUIdFpYvgS2y6CKRUgqL5+07vj1/fCWlHpA/YsSI/IaKbbbdJjdJadqWmTBhQvB4mTzeL8raAteW8/QYi/LNhV7+w5tO0ADQTSEhi7aMb7PN3pK3vkscY2XrrbaetuB5I5x55WknRChrnj0MxjM29a6pscyoZYIAYXRQ6JiOkKFcbc3rhz5TnLaLKHn9ViejJKWe8fOueUXcVltvlWmkT21oKdBSoHcKACMUOgDB28YTR3E7TsPTA5gA9fJR9n6rcezYscGbzUMN3PLQkSnWYUo9a1K+EoAcD2cB9iWueVU3UKw9a58ylIcMEke2khEUmjb9JmPIBPm6hZRSrLPOOvnVmWRbyZdSimWXWTZ8YEh9KaUAuuwgUIxeKOANQGM23DDQA130kZwjoylN6egmP7BEfqtfnwFJZ63XX3+9fL5efBsGjgL0J70ByLt3VMpuFH1q/gov4ik8gH/1jp5y9AB/O95w660/DUbZ8ccdl0EPHpCvBMANf3Gi4f8S37wuu+yyQW/x9vOA19PxsmCdCO4FfCTU8zbv6Vbn/Olk9yXdmmFw4Gnx+kkfc5B5DoSx+eCf/pS/8wLgo0dKKQBPv/GyI0SAI0wDT6CT+ulnu+kAJvBHNohvw3QKPP/c87HuuuvG1luPDbT6298eCThv0qRJAbtMz9n73ULDF8qec3IP75FV8CFDC6/YSeJ953TxfIe5wNP4HLYko8kheE77dqwYpMD69ttvHwwMDhy8CyMWWY5feu/ZwKQOKqBHEKCdZY+o9SGbDMLCmXBfbPNqNFfWlcUury0RVhRvF0Vr8W299dbx6N8ezWfgKDAPP1A6AGwhurYA9UnHTsrn2cRTOP8/e/cBZ1dR/QH8TAJJQIFQDdUAUhRQ/hoQCwoICBaKKMWghCLNhmJBigQRFZUOgg1Qqh0Q7EiQKggioNLUAIIViAXpyf9+52WWl8fbzSbZbDZh8snsfXfu1DNnzvzOmXPnlrq8rMPdxqJja1tdhABrucXZfQnrrffiwCjapJwSX64murq0G3OJF6dsb1uXPAQSPy7WdkwiHignGPT7K1/9SrhiTpYL5WAsZWirnQxbRrRQFjkTQToWASdQaD+aykdgH9BYEg7+2MEV0CNIDZUC/aQAeQKwmnOCuQWcAASKsIizjLMkUuaBV8fNdgvmK+AuXwnmKFdCZXTKmpKmXIEowGTSpMvClj8wwxrVra4SJ0/J3+1KZrI8kZlAS0kjnhwTzyqvnZ7xjy4yCD2OOfbYrLzou+cWPoYQct5zcpwbButsSi1lxvY6SyulZI89ds+GG3lrGDwKpNRS0IyxdcYa6MqAxIhlvFNKwWKJb62z4vAFpc26ZWztXjFEvX38+ACOOntgneMial0DlDqfl3troLXMmmn3m6uPdRvAKrzcecWb1uJSRrcrzGEthjn8Lmko4Xb3tQsYFI+HgXPvr+HdL335y/mFXApJSi3etZaWOafv0imDURFtlMONx8uz5golxdouvoanKUB2LT9m+UA7fHfqqaflc9/JiadTzfyX8eCtAN/4nVIKcsyYG5/C1wyfxlyJKaUYM2ZMVs7UXdKQUwzLFDz8Dv918ly5J+PKeCtzXoV5CugJBKDTxPe7GxFMYgNi8ptoJnpKrcl077335K1tW718m2yJfPDAA8PHpLbeauv8ZrqFVh2jGqt8KV9d6iwDLj6llH2w1EWAlbo8E+QnLCxQ7ku44YZfxbrrrpePXFJuiS9XcerSj5Ra7S5x6i/pUkr55Axt9bzEy0tD1X/Wg3YhlFLKi58dBs9pm/qLRhQRDOZemdpfylS+cikWJa5eKwUqBWZOgZRSmDsrrbRStgSZw+ZZyUn4m3us2yml/HKVedktMAJ0yhPlmLPK6PbM8xI8J/seaAwYP7/s59mHWb3d6ipx8pT8vV3JGLKuvV8ptWSNeO0reVNqxZNR5JB2o0F57iq9+hkg7BiShWSQZwLrPBcOYHGbbbarRgZEmUfB2Fv7rCeu1pL2pgDYeKCdj/CJeWD8rZ3G2pi35yu/U0qhTOnlK/Gd15RSMGgxYP3s0p/l783gGWuZ8rsFz2YGllNq8as5nFJrPVa3tshvTfRbnKA88foGG5hf2uFZCWgBELLw429ly+c5oOq9EoEVuIBIz2qYkQLTYlr2YkBDtC67QDOm6vvO2OCt9jFIKQW+hp+MUeHrlJ4ef6VK4xk5RZ4Za/EppYwl8T2Z3cl74uRNacby5B3sME8B/Zx2lqbPJ4p1ypdeadj//c9/wiLHz619Ys5pXb3lV88hhxyctcDe0tT4SoFKgUqBuUGBtddeO7smcEnkpz836pibZXoHwMtwLLesZkNgTZyb3a1lzwIFgGIvTq/xgjXiuuuuyycjzUL2IZHUy8NewHzFK16RdzeGRKOGWCPgNACeMQAgH2LNm6+aM18D+uWWe17wezr77LPCNqAtPy9o2e6maQ/GSNDcl1tuuWpVGgxi1zoqBSoFZqAAiyn3AT6hrEQzPJwPbizg3j/gz8rFcj5ocm3iIFKAtZYLBZcHvDKIVQ9IVRRVL8wzPLL0D0ihC1ghXG28p8F1r7ednQWsy3OtO/M1oEcVwH2DDTYML5vwD11vvfXyNrdnz6ZQ+1opUCnw7KNASim7/ngJdX4F9GuuuWbwywd+nn0jWHvcFwVYb9dZZ51Yd9118/tufaUdis+4n3mPzdHYdhyGYhvndZu4AxtjNJoflbZ5Tb/2+ud7QN/emfq7UqBSoFLg2UgBC2FK/fbhHFIkSinVHc4hNSJDqzEppZ7T4GI+/JdSmg9bXZs8P1KgAvr5cdRqmysFKgUqBSoFKgUqBSoF5joFagXzCwUqoJ9fRqq2s1KgUqBSoFKgUqBSoFKgUqBSoAsFBh3QO9XAMWU+wNAefG3NR0e8Fd6lnX1G+QDGvffemz8K5Zgopz34Up2PAfSZsT4cEhQY7EbgEfzi4yntdTvr+A9/+EP4sMRtt90WDzzwQPvj/NtHznxApfCu33jNhyiUmxNN/+ODYD5k4dn0qHpZACjgvHRfk/TlRx+NmVmXpMEDeKcEH4HzEbvODz35QBOewnud/NRbPcr67W9/G+Rgb2n6G++LlurXzr7q98x8IWvV3xk80+/OeqdMeSjIeeuAZ/qPlj4mU+LE1zBvKGBcjSX5Zmz72wr5yDvy09V9b3l92AcPPP74470l6YnHH2S1L7l246eehP34gb+ciCf49kFfWaRFh94CGdDeR+UpF45pn4fKyR+luv/+aE/fV9312cBRAM+QZXi5cyzJWHizfVykw/u9yXZpSxrr/mOPPTZwjR2AkgYd0FuwHC/5zne+M39JzodXBEdQTpgwISZOnBjObEW4/vTPgF1//fXhqMqf//zn+Wirc889L3+UAMH7U8bsprFoffe73w0MMLtl1HyDTwFf7PMhlJNOPilXjoeAeB+SeOtb3xrli3BOD/HBG0I5J2z+XHzxxfnT0r7W6yu++BYvO3LPR86U3STL/y1E4r/1rW9FVS4zSeb7P8CnE1mMu69Yk2XGua+OAci+pumjPT5wIuy///7h41EWFXktNj5o4svP+EpaH6OZmRwEJHxUzgd3lKGs2QkWpm9+65tR6vfhux//+Me9ghCyz4d89EN/BL/lw/M+8tc+F7RJ+5xm4cNDpd/m3qRJk/IXsPspRxVVw1ygAF674oorAu+Rg86AP/fccwPo6as6gOnss8/OctGJLvjgoosuymtxZz5A2Gl0EydOjMmTJ3c+fsY9HiKXL7jggvydhWck6GfEffffF5/97GeD3N5ll10yzqBE9pb9zjvvzDyJr9uDDxb52JZ1n0KCZr///e/DRyGVLZAPDEKemZ/6q2506q2+Gj93KEDJOuSQQ6J9DP02jh/84AfDt4vwJHl2/vnnhzUfHt1tt93ymFJQS8us4d/+9rfz/CCjpXFcOl4paeb1ddABPeFwww03ZBDsq4o+HuFkGr8xvy+tHdgQ+tc33hi085kRyKTxJbYrr7wy7r3nnrwAPfroI/Gf//w7LBYzyz8nzy+88MIgvG6++eY5KabmHUQKEMIXX3xJXH/9r2LX8btmfrmx4TUT/Jvf/GbgQ18odGrItddeG3vutWd8/etfD4BHM1mKrr7m6rxY+fiK83OdznHVVVflBc0xqtLgS2/u+4rimWeeOUtKqnpqGHoUYFFnOHA0rg+UOIbOVyQt4L0ZDyiDdmnOO++8uOaaawK4t/Q0q24AABAASURBVEgIFAHPWXw+//ljwtF2rJd40LnbwDUZ05ccc4Y7sONL0D540k415eJFMrc9vvO3OeHDTu/e/91h95RMZlQB6Cx43eSwNkkLhJegP5MmTQrg7uqrr+6R3xZC/fWFXV9r1KYyn5xiou3SAD0W18721fu5TwFjjOf222+/sJ75IjIrJYBDfvU2LuJ9XdORg8C3fLfeemsASz72qNyY/g/P/OxnPwtfDTYXzKfpj7pe8Ii68YtjK9uPNCRfzTkKdnsd3QqiSJ504klhrpqz5i5FRd+A8W55zBllF96mfODh733ve5m/KQPa4DmAaI3w0SgfNaKYf+xjHwv5HSvr9D34hJKDBt3qq3FzhwKPPfZYAPXGSSB/jR2ZSSbfcccdWWHFZ+Qd47DTdsjlz3/+85mPAXb88NWvfjV8HAxecDKXFp900knZeKwc/CBuXoZBB/Q660SGF7/4xcFKyspjopnkBAPLwPW/+lVc/otfzADICQ4LyL333hsWqvaJoTzHQzkWCrjafvvt4pBDDg1f/bJYTZkyJVtICRBCiuCxgGjLf/7zn7wFTCloL9MzwVa5POqmcIgzcNpD8BE6gm028Z6r006EtrJEYQ7xgnoJGGVpR3u5nvcWCC1tUY/6lG/bEqPJo1zb5YScfpa2eCZorz5qk/q79RWYKGm0Sz/kFdRpK1U7pFO3IN7z/gbt7Gs8StnaUeimTuPkmTg0Vbd79YrTNn1TdmffpSnBWH73u9+J9ddfP172spdlqw8wftNNNwXrIushYHHcccdli84j/3skvvGNbwR6KwOvLb3U0rHHnnvkBYIl8gtf+EK4+tKlReyss84K7cCLtH20JsyNuTJqmP8ogKfOOeecAEic+U5uEeZ2Z3w45heNvMKHnT0TZ0GwsJN3FnuB1W7ixIkBAABS3/ved2OLLTYPgJcsPOKII/LxuyyByugs1725xzq/xOKLx+s22+wZx/rhuQMOOCAALOl7C2QGJcX3NLRN31j89ZlsLrzfnt9XFCkg+lGCb4E4S37s2LFhBwN40vbLL788L3oW0JEjRwVZnVLr5I+UUviWx5ve9KawI/CTn/ykvZr6e5AoYIzJPOsJxQsPGE/KHQUNmO3WFGD7zDPPDEczkp3y4WvHSRt361XJxy3MjhYZTJFLqcUD5Xn7Fe8BXvgRmGccaX+O97WT9b69jvY0fls7gDRzYbvttstyGk/bhRDf2+7p2muvnRUP9eNvV8q8o2E32mij2GabbfJ8A+S180Mf+lAo19zda6+98pdt0cZ6gTbmxRlnnJHBpXbV8DQFrI/WSxgFPoA9rP/GuKTCD571FsgZaUr6ciWLyDJjKBhHyibjx2te85rYeeedAw5jeYcXjZ9gTYdFJ02aFJOaoE3ifOWaVV4aspfxz3OGlW71l3YM1nWeAHqdA3ZM+tGjR8foJhD+L3zhC8OkQxgDaqD9BtRoRxZSW1om1k9/+tPAAMpqD/LcfPMteXEAoGx9ESIsXT5QYZvc5LMI06oMzjvf+Y68JWPSy688jGOQJjaL7jve8Y4M4Ag4Wrdn6v/hD3+YtTtMgiEwILBJALLc29pjsZWuCB0aovYQBBiLReTSSy/tsWapu1vA8BQeC/7pp58e++63b/iA1mmnnhb6yJK299575y1FgoVFAe0ECzb6leeEYDsAMRlY5GikhJHtJJooQQ38a88NN94QaPHjH/0ojjnmmEATaYFXYFqa/gTgRv8vvPCCrNAZD3RATwLQs3fu9s5Alwxmnngi+wajr74DVYD3hAkTcjuUJ+8BDXAxOVlL+SyWcexsEyGur8AT4UzgP/DggxnY08x9wtu5uL5at+222waaUT6NOVoqj+K41JJLhbQs9Cw+r3vd6wIvWXi46eDZaP6xtjpDGVCZFTo1Wev/IUQBc9scs0Bvv/32YUEw/rZdU0rBCt+uAJem45vJkycHWUeBfO5znxtF1uENPMVaaQ4yQqy66qpBNgK4lETzEPgp5bVfKaLybvSKV8SY5Zd/xtGP5r3nZEd7vvbf5gmgRYZsueWWsf766wewbocKT5NXLFLmSXs+c0BbzQ38DbBIx3UNfbbeeuvcD3KPHAEIyUOWLTRpL2vUqFHx2mZxRVuyU5725/X33KcAeWVN8JEvfAC4APNkqnUSaMWr7S1xT9allPJahAc833TTTYOyS7YXqzrZZ93Ak+ZBbzwtv2BtJ/8pGHY5KcTi2wMjDJ7r5M32NOatOWBuvvnNb46VVlopyPYtttgif78BGNP39jx+Wxv0h/cA/jbXL7744ryju9++++Z5gk+tf+YK3l5kkUVy2ZQFa7C1IJp/yy67bACP1h319dXeJvmz7j/MxDMDvrG+W3P3a/CN+zI2jJl2VYByWKYzwG7FwNdOQLKFclbG0YfK7JYwKsAdMCdZJh62xPvGS/wb3/jGvBOvfeSkdZ6B7g1veENIQ5bBq3iVQixNe93z4vc8A/Q6D3BbyAh4gwEsX3jhhZmIJh0BD1DazrOFhWgEBHAE3BvETqIpjx+ghYGl+u577o5TvnBKBmasp4hvYmIaA4hJ/vWvf4eJxtr222a7UJnuAVsM5v5fU/7VWP0PCcCRtqZswsLkJKwMuglOG7SVZwGzMGIeWzn6pW2sE1/80hfzVg4gb8uPwFSOenoLLNTaD4zzCbvn7ntCvkMOPSQAa0rO/fffF9pCcGJ4fbWbAeQW+hFUttfRD53UpxzAgWWatgpQACjabQIRhtrJivfO3XbLLigErZdK0UO8e2XNLNxz7z1x2hdPi3e9a+8gsLXRorBfs9Vr8aDo/HvKv0PbgHZ1SOP9CAoFRYZgBJL0Sz4+u9KhERBkDPSjsy34jBsNcGUy4i8LyzovelG2hh522GFBOeMSRqE00fk5K89kTin1FGkx67lpfiiL4Cfc8YJxkIZAAZLwMZo2Sev/+ZACxhNPmT+UuJRavGChH90YJOwY4a/Orpnzds7MQ370FgPKsAVMeZ7jNdYhMhC/UVjxMcv1q171qsCHneW6Z9EmczbZZJPQLnFkqnkgnnzCg+aPssV3tpEctiVtjgNwyhDIAO4T8ppryhHfWzAnWa3QYkIjI8hvaS2cW221VZARLPrkdzdZN2aFFeKVr3xltmwCj/IugGHIdgmP4h3AZrHFFsvtTCllF0S8AVjh1fxg+h+8Y10AbvCa8WfIYsnEj4A7PpLf7ow10Pq18cYbz9SAZb5IT+766Jgq8SC+xscAHj4SrMXiPJNG2hLwO6OPnTDzqcRTyNdYY42wTsMVJb7bVb+9z8KotMXmmweF1bph3ppXaMbFzBpsLbJWafPyjZKtPGsDxVcbGBKtBeJraFHAWMI2ADacQub87W9/z+8woCl6kZVHNLuW3l9gkO0MeM+62yqx97+whroYHMhNYwMLwItwpnGVGz/DAe6NmzQXXHBB3rUnw6TBa/AEHsdPvclpaQcrDDqgT6m1ELIKAVAmAFAIBNPogTxaD4IjJuu2bW5bGyaVRQzosj1sEC2kFo12ghkkxE0pxbA0LBYavlDQ0ggVk41vqslosnsRQvnqJxyuuvrq7IJje4xQUQcFQt2E1aRJk4JCYDvGwkz4WYQxo0kNkG7ZWLr4Y2McV4LEAo4xtU2/Vl999Qwe1Q/Iam/08S+llLf49BWTazOwDVwQWICtvn3zm98IlmbMiCkpDQA85QQtKUHyAZpe5AHEWcalndjsRhA4aGzrFI3124RDR81j4bDVhA40aJYceQAez2cWlKOvhCllSpu1nVDVFhaPS39+aeALtLryqquy6xWaaeP73vveMB7oTOtGc5q0ifqDH1wS/HGBC+V1tsV4Ul6Mh0nqubZsttlm+WUYC48dFeVRJvCnsbZgmLzSzyygmX4AQRYC7dZX9ah7Zvnr86FJAYuM8WRdT6klw7QUjwIvxhwgEtce8KF5DzDx4Rw3blzeccJbXHAsVPiLJZxSDcQwbHBfYHBghe/Ge2SV8iwmq6y8co91/qyzz8q7W+QZ+QPkUA74+ZJfFOX29vmtb+owl90L+HX06NF550oZnovvFswbMoYcYihZrZFtJR3LKrlOWehGn5Ju8QZEsg6TI6y4Jb5e5z4FAHNjjKfaeUDN1hu7SuW5uBLwhHUUHwJb1jLjZ10gPxmzlMlCbj31wqxdT3NG3pSenkelzHI1J5Q9ZsyYIFPFizNv8DHMYJ4wrgF34hi61C9tCeo3N613eLHEA2UMbp71xZfSm7vcLpXx3ve9L0aMHCk6v2+ifOsRMEi5gWuATvSQLyds/gD91vw77rg9+toxa5I++/43bIAnYCk4ityCU/be+13hNyCND8hE6z6M0B7EoTfFsi/iUfrwIYOe3Rrj2S09JQ02YRR9+YYbBuDfmY7MxBOUV0YXblUpNR3pTDhH97OeedABfWki4gI4/DuBOsLAdq3tKoNju8sgmywWFoDUYmqh4cPG0iWvbTdCp5Rbrim1iEtwAFVOLrGNYiJbXAgJfnAAIEYCDk1wiy8BZWKyMhFkFiv+gBZuws/WpElpMqvP1WJv+w9olI/FGFMCdhhIXykfKaUYPmx42M7GKKxgNPmUWu2NPv7pC4H7+te/PtCENZiQAFCB0MUWWzxWWeX5waoB/GqXNqG19IA3gE7Q2B5Eb0BCG4B7wpZ1jLLAbUV+zO1ammUisLCgI99GygNBSzkqafq66gMFC4i2JWlSlfHgZmByWEBYu40Hepb6pd1xx52yu4O8tGZC2jhSbFZaaeXAN9piPDrbYWwpL/jIWJbneAHfcelh9WdRtDBYmMSbtNpR0vd1Va8+4hNXPKw+PKruvvLWZ0OfAsYxpTRDQ42xCOPt2h7wrDnDMomPuO3xVcbnLH5kC0AM2JNrjBX4EGAhM+yamYPtZfqNHwEesmXkqFGicnji8SeyGyC5ZR6IJAsKcMGf4tqDdqeUsm97e/zw4cOzi4Hn7fGdv1n4gTdzkFwjWzrTzOweXYEe7baLObP09fncoYC1sr3klFLg7248II7sp7RaPymOeNdODKCNl7lycbkiy+08ke34Ut4i16Pjn2fWKOnwVHksHvgGplzlF9yXIE1Jn6/NVE0pBV5u75s+iZNeiF7+kePWcnOR24y1UlJ59B2/mluUcYYu89u6bm5TZKQVrL8AJ2XVOiSuhqcpgM54iBGD/LBm7rzzLgFn4CEp7XqQm3by2oM4OyBkrXS9BRiOsc8Ywi14oDPtf//7n2D45X5MHh18yCEBZ7SnM+7nnXtueIcD1ntfo+Rxn0ypYbb2hPPg96ADehNBPxGVn53JbjuWb5JnhAPrqckmHeFOGNiSLgNAKIwdOzYvNha2Ei99t2Aiy+/qOSbBNIC0e8GCohxtAIBZpS2kLPSOWhPsHgDU0mNAaf12ldYCa8EEnAFkA85vnzAw8EBiNGM+bPiwIKjUKX9/A+GlHP2XRx9Y6HIYOUJUDmiXUlNRc0eJsKDTdLVFm7hfBdiUAAAQAElEQVSQoJttIkACKGZd43Jk18G2F+0THVJKmc7TYlpTWmS/wzJx1I+W+i/kBP34o33Go/Rf+5VFC0+p1W7PpNNnRSof8MYL7rVBvmHDhoX2ixPKGEvvvj2YiLaOjaH6PLNoWHyMJzDCkok+JjWLAOCPP+14lLbI11vAv2iCttovnTK0lzB3P1RCbUf/KYDv8CQeas2EVl58BkwYX/zYin3670orrZTfz2FBtIiYuyzR2227bZAZt956S4iz2LNOkYt2E/nkmg8MC/jz6RJbv8gabTEn2uu1kwlU4F0KsrmhbrJWHH/kVgmtvyml7DNv3mhPKzayS4T5v9BCw2ORRUZFSq15WZ6XqznBMnnzzTfHdtttF4wm5dmsXFNK2RJLfppDMV3ezEoZNe3sUYCcIhNdAdT2UowH/l5kkUWewQMptXjHWuYlaFZKBia76wAWYxKF1DtO1lprjF1i6yGDmHgGOTK4s07rPplsXpRn5iBjH162g+xUGeuIOsQxxlgfS3rX4cOGh76pgxIgTqBE6+uoUSMzaBTXLVg7Kavm2oQJE3qU3pRSAOnm//rrrx8777RTBn7cjOxEqI/B0fxQLvkg/aOPPpa/lyOuhhkpYCzxSYllrDCecBPXKLKNsa0z4DcGEDKx5O28Gg8GVrxMLlIYOtN49qUvfTnw2NJLLxV4jBLXno7y5h3GIz7xiYw7pIEbhg8f3p5snv0edEBfemqhsdiZlDQvRGR1tX0iIK60iy2+WN72NSDuBRMdYU0WC5G43oIJF81aZNFLqfnRljClp+9Tevq3wREwDqsaqwPtm8XBNgy3DEpHKSqllCe6OvTrgAPen91p2vOxyo172biY+tTUnE3alJ6uM0f28Sf3o3k+sgHuQGzz8+n/TTFJJ5+O6fmlHsDAlmBpD8sztxsWFRZt4P3wwz+e3114y1vekv3EKFo0UwKtp7DmB7o0l57/KaWe3/35MW36Qq1dnemf0a+OBCObrc6UWvUVeuQkraj8s68/yhcI8tIv1kWKDOsRoQ20WUS4yRAgH/nIR/IHplgJ8F308Y9AAWwANMKp0EpdFhB195G9PhrCFBg9eokG2C6ST9h69JFHelpqbAFfi3U3nn7ooQfj9ttvC9fCs2TW4ksskctYdNHnZGCA7wCPHNn8seA8//nPz8p0u+xrHuX/eAs/PdiU3/5cGRZFc37RRRfN1lVtcy9eXC5g+p+UUn6RT5uAqOnRQbZSQBdeeEQss8yykVL3SUZOT5o0KT+3C2qOljJm5Yo2jCjypKQuwV0Ng0EBfIOn+CEb+1In3ia7lllmmezyWeJd8R85t0ij8OGrlFpjRn7aJcaXFNJHH3007EQBxHvssUdw6SR3rfnWImu58kpIKWWLOp546KGHovxTn7LxMYOJ+5RS3rEVR7nVh5Le1b08+tFeFuWVsWvZZZfLCq203YI0/KQp43bE29OoUxsWaZSdUU3wzL149NSvsmaghfuSxrWGGSmARu0x7lnMKXJonFLKPDhixIhoD2SXkFKL/9rLKL/xoUNOWN0ZVKQvz1yNDYxmvce7J554Un6RuT0dWY9fD//44bHKKqsEtx8yT1uUMRTCPAP0Jmu74EBE/nHAENB8/XXX5UXlJeu9JGy/2b5CdBOEMHDPVcYAiRsoYmoXAcDqQCu0ELI8UDosXlyDgDttTynlBZfAo4Hbdpk2bWo8/PD/gpWNAACKubYQaI8/8XjXZk6bNq3J83A+Ponw65poFiMLTdSPEd2zJOgHRcoizO8cuAVChw0bHph14sSJwR3G4k4z1jahP9WjCcuLRYFlpz95BjONRWfMmDHB4lnAAysAHkIP1iOg3ngK+nHzLbfkFw7lGzbs6emCJtKgLRpy02LZx5fcuJSpb+huUbCgWHDE1TD/UQCwNa7mJ5c7427B4RKIlyiAQDm+xzf4CI+wQr5l+7fEkUd+MswN/MACzZfdYqHMsc1uo3K5w+Ep5XKFEwAX87WTYgwKdn7+/re/Z9lRnqtf2wRgi5GEnHQvqL+kdR3eWJbIXmn0RRuVgWfJB/XbCk8pZcsimaAceQXtvf2O20P/lSNudoIyWW61x5ycnTJqntmnANkEpLCqc0vAA/jaOx34j+Wd/LMG2tXFr+65PkhnB5MclO/P997bKLG3590a73vZ5T7xxBPzyTcsmtYX66v3pOwIA2vtLccD+M78mDx5cn6HynPzCb/hFb+5ZeJNz8R5Jt59CcDWeuutmxVq76OUdNxoWNCt0fqn3eYt0N8+R8xViq13XzrbaU3QBjsPXFTNW3RxjxaekQnaohxrqvZYh8TV8DQF0rAUdvqAbmMB6zmR7qGHpgTDBvlifaZceW+uPVhzGSjJOxiE9wGe9LvU4H2L+/9yf3AThu9KvKux+tKXvhQOLQDQnVDE0Imf8At+wPdwKXy08Ws2jpNPOinLPM8FaZQ1r8PTCGUQW6LzwgxVNjcs4k5fMYEQD/Di103YsJADnI6Oc4qLgR0//u1h0phETz35ZFYAmmIyyFa+yS1gkPbB9bu3OPkssI61Mkn5vnoDmnXeSzdeMrXgmJiUD3Vzz7AY2npZb70XN5rb1/N2jTNuHWXIMo4hgP7SHldtFdRJcLL8Y1T34juDNreeTet5pC+M3tP8mR6rbOlcHSEGXBKotuK9pMsdyC4Iwcl6JxBGntmW0ldpCSHMjrGVpfhcnx/TQ6nHrUlk69PRk4SXuGeEpulPPvX0WHmubH1rL7s9zm/PpJG+BHXn302Z+dr8kbaE5naG/8sss0zmF3ylrR7S/vk4G0uuRsZA+wXbeOeee24Q+rZSLWDKBnoodiY3JdRLUF5CtKsh7e67795YNZdRfObJe5sFDn1tQ+fI+me+o4CxZ2G0GNi1s4AIwArrnfdayAQgHF+w3hD048ZtkHkOOOaXaY6xBJlngM2mm24am2yySTgCkuuAXTMna3lh1qI2YcKE7JLTSTCAHgAzJ8xTfCkNw4G8gvPt8TU55N7L+4wL0pWQUorVV18ttwHIYTXF2xY3i6DdK0YBc41M9gKiMtwrQx/vvefe/M2PpZdeWlSfQT6htLckJh8ZSsii1dteqi3P63XuUgDAtvYCowwTeBC/AFHko3XWmHEnBcStU+4dAPHCF74orCfWGL7jANE9d98dXBvk5Re92267hcCVDFgyzlxTKATmTXvvUkoBLONdCiSQ7bm1yNwrvGzt1QbzSpw1i2yWtgRKAYPcuuuulz8IBUeYm7CE+aNt2gJzWOv13U5rya9+QB8m6Gwnhdo7VuafdR7NzBHrPUXamlHKkcaaaC6RISW+XlsUgEW8Y4aOeMk4n3LKycGaDoSTv9L0FjxXkvFXximnnNIocQ+JygHtfVOGSyC+ypHNH/zDoGns8FdKKfAwGX744YeH9R3Pcw1TJjkFD513/vlR0rgy8pDFTZHz9P+wwa7dgNiOAqTKIJQ20GadkmCS+7CUBWndRrs+8shPhEln8eTLjsA77bRjfOCAD2T/OJN2idGjo2x70YClV5dJ6MzwUW0vjtkW9rw9TjpAXZz873rXXgHcaQPfc0xC8zvooIOyBVtbLcbjxo3LH5uhaND0KRtrrLFm8LPCDMA+IOcISAJAW5ccvWSop/QbWCVIlWFXAJOVZ+WqL+i2xBKjY9iw4SU6L/asa8Onx6WUskW50NcLp9oPABC4mJSQBib4iyvTMVwshZgaqAXoTSS+aSoi4BZdZNE8BqwUKbW2tlJK+bhH9Q8bPix/TZWGzSqJVvJ2BnQu45FSqxy07G081Dd8+PDcJ+PjtzJTatWt/WgqTpBee9rjxAsAB+HAwkRQi5MOGLMosAJ873vfyx8UwWusqNu8+c15UhPoKaXsN4d/+FUCdGh1wQUX5A9PAfIWMwtIaadJzvKoXZtssokqaxgACsyLIizSlGEC3cJPJgwbNix/kMxCkVIKCwreYP0z9oD6Rz760fyyNplAfgHYlH/gmZKpXPFAFfmhDtYqiuL48eOz+0Fnf80Z8iellD8cpU3SkI0WQ8AFXzoq1bwucbaepWsPXqYnn7bbbrugwBYZsfPOO8e73vWuvL1NRgH8DBp2TEt+Sgd5ZX7g8RLf7WpOkEvmp9/taSjY2srKbyex/Vn9PfcpYD0Ctr3gB6zjTQYKByA4Fpl8Ns6UPIcmAMBaxb0EoDFuQDI+vvaXv4w99twz3rrDDpl3UkrZJSul1tX62im3ldUeWOi9JM74Yk30DK8B43hZXV5yJKNZV/E7IGgnVNr2sOqqqwVF1PqR59dRRwWA550V65608tmltX5xxxEn2GnTVvPYWiGuBHPfgQxwAjB65JFHZkOetdY62q6Yopu+WHfN81JGvbYoQMnHQ0A1+XfqqV+IlVdeJX+rBn5qpZr5X0oe/rXT5LccylYuIM+Lol32kNF2140zucRQTCHDX/jK+3N4gnFXGrx7/XXXh2fSCOS6+shI9c3LMGywK7d9wgIEDAFYnfXTmi14tvBY7C1cW221dVxyycXBymVCW7SOOupTsdLKK2efKie8mNy27wgmmjZQaeJYOA2Sl25NSIMJwDlZx3Fq6jcxWeSlI9CAzjFjls/nzrNGAdoXNKANo3ibHTCXD+h1rKGtIYs7hiGEgHjlG2jtImgAa/V4jkFYvvRNOerbfcKEvIWDJtoovj3YTmLdY8lncfdMOhYB8RZUcdoAVKIxAaZs/WURRJPSplNPPbWZMCs3ysGw4IZDK7XLYFx+9KMfBgsd33rjoJ+sKTRZx3WqR1A/of+Nb34jb4vZSUFTVojSN+nagwUCnQEV44EmtrkABRYi9ymlbDFEb8KScAe4tQ9/KE9e27dov95664nKweKCT9rj8oPmj/Z6yUU7pTHJm+gM0vGQMTZxuT4YP5PUjgPAJa+0LPFAESFAiLvKYzFAMy81tved68Ivf3ltjBv3ssYSuroiaphPKYAHzAN8SPET8C3eKWNuruAF/EpO4FNKJJnGimO+eG7+UQKQwhwlf8gSz8xF5bKEKkOaboFMI08vvvj7+T0PaVgqb7/99mDtFigGruLw6U477STZDMGcs5hS+IHqs885J8hYfRjdGEok1j8WKu4YFH20EG8+6pfdS7JXXG+B3HKwgAUTECzpLKpkApD45je/KVv7y7N6HTwKGGtAnkJqDcMD+JU81wp8wgceT1H23OMDp4xYK/As5VE+vshLddmxofRZny+55JLoJqPVIwDFDCSMSWQxUEb5VQdextPaIfgtqNeaL397GDFiRADS6uS/b220Flqr8LW0dg0Y76wBQJ84wRyzDlhDU0qiZgjAPiu9dV65P/zBDwJeUJ+5LzFl1RxZdNFFYquttspKjvganqbAtKnTYo0XrBGwDDlYxsl6jceeTtn3rzFjxgSDJb4tMkZ+6zZeYQRpL8H4k+m/bJRQaznl0bpeAr6i+NnJgX9ymj/+Icpz6aVx8AA53l72vPg96ICeEKAJMP8oTQAAEABJREFUAZ4pPXOCpJSyNRawNfkRJaXUgK7nBL901k8Ar0wWzxHSxGI5TSnll9fcq8uAEVSeSSu0p3cvlHTqTKnVLoxAsABpts8IFGVKX4J6aOJAomcpaeuiGbwBr6y+tLqUWmWWetoXP8LqmmuvzS/3qCelVtpSh6uy0Y2Fy29xAjqK01b3KaVMP2lTapWTUiuOYNYm1ob2+lNqWbsJWMJ5+eVXyC/5osXoZkHXZjSjILTTUX25/sUWj+HDhge3EgoQeoxpJpbnnUFZaNZeTm9x6tYG/QVs5BveWOuVmVKrT9K08wJat9ND2vYARLGqXDZpUvDPbH8mr3Gk4LAKGHv9bk+jPejgmeC3NqBDezvkMa4UqSlT/hUTJuyed1PE1zD/UiCllL/6SibYnTP+KbXmmV7hT3yKX1NqxafU4lXzz/wCgjv5Sl55yAsWarImpVZ+z7oFfMct7C9/+WsAYYCxMsjO3kL7vO8sU5uA7ldstFGWX+5LmpRafVBnezyeF2delLS9XdGGXDJXzOmSjsWfEkO2U+pLfL0OPgWMEeMR10GysnNcyW08384DWikd3jWGZCi+EN8ZUkrNWr5ofhFVXZ3Py31KKTZq+JDhx44AEI9n8FpvvO1ZX2WaG4C7s8WtT8or9cln3uJPv0u8/irXGlXiOq/Sa5O+r7nWWnn9Tak1d+1q2K0D6Pfee5/GsDOuM3u9n+4yy20Y/Y3RCxpwbz2eVeIYU+PYKWPwJ77txpdkojG2nncGeeQV/O587l6857Pa1rmRftAB/dzoxDwvcwAawA+XhZfbzgAUN8+KYL1jxSHg5lkj+qjY5PVexrLLLBOsSX0kneNHtlkBejsQLLeEzRwXWguoFGijgPlmB4kVkyWw7dF88ZPSa1fAThZL59JLLzNftLs2cu5TADBjpX/iySfCbi2D0dyvdWBr4PZBIaFA2N2ua8Az6ZtSCkqRQB5E/TfbFKiAfrZJN3AZMTKLMMuc3wNX8uCWxJphB4CFPqWWhWJwWzDz2lJK+Uu6/JO5Qc08x+ynSCmFrTpuWhan2S+p5lyQKDCQfWFZ4pZGaZxfwYKtce5F3BQGkja1rPmfAtbFQw4+JO8YzY+9SSmF3TzrjXVxfuzD3G6z+e/9A65YMMTcrm9BLr8C+iEyuhbjlIYmCJ4VElFIUhra/SA0AKAdd9xxVro2y2nHjh2bXyq0+5LS0KbJLHeuZhgSFCA3AAZ+oMD9kGjULDSCvOCqwFeZS8QsZK1JnwUUsKPKf32TTTbJbqDzW5e1/81vfnPMQfvnty7PcnvNe77yXlAmD2a5gJqhhwIV0PeQov54tlEgpbkLslOau+U/28ar9rd3CqSU8kkivacYuk9SSkO3cbVlQ4ICKc2/PJLS/Nv2ITH4tRH9pkAF9P0m1QKasHarUqBSoFKgUqBSoFKgUqBSYL6mQAX08/Xw1cZXClQKVAoMHgVqTZUClQKVApUCQ5MC8wTQO4Df28yu3cjiqCfPpPFbGlf33YK00rSHkr7bs/Z05fespFemI+IE7ZG3lOPqvlu8Z30F5c5Ovr7KnBvP9Ftbhb7a67kwkG2YXdoOZBtqWZUCs0uBwr/mTbe54bn4ziC+tzpL2t6e1/hKgcGiAF7E20I3nhUnTWcQ362N4nsrq1v6GjekKFAbM8gUGHRA/49//CN8VMUX5XxkxGTt7LOvuPmIibeefdjIpHZs1WGHHZY/9uQrbJ4JPoThQyU+MPTYY4/loggLZ79OnDgxfAQmR/bxRxt8lEJZZ5xxRvgiXbfkjzzySDhn/YQTTghfz3OCiXOgfWDGV+DUC+w6c/a4444LHyLoVk63OPmUc/TRR8cdd9wR+twtXWecfPfcc0+U+jufz+69r+X5iIw+t5ehnkMPPTQck+fjTAcddFD4qEb5UmVJ+8ADD+SvqX35y1/u+ehNeTYnVx928OEs524bt/6UhS/uvvvucDRef9L3J42xVp72OJqsP3lqmmcvBcxnH8nxYbhPfOITWY6RNeZ6+9xx3raPu5k3Jbj34SVzvZOCZJWPy/mwT3/5sMwHc7mzvDm5JzPIXdc5Kafmnf8ogIfxMl60PuBxvI7n8b4ekdeOcPR1zcLbvrh59tlnBzla0klbwuTJk8MHzqz/8pf43q7K8EVP5fn6a2/pZjVeufriI0J+z2r+mr5SYDAoMOiAHtDzeXFfJfT5dJOvvaOA0q9uuCEAYqAeKBYH2Jv8vgJ20003ha+3CYC4Ce9LYL7wqSwT7vbbbouvfuUrcfkvfiGqz/Dggw+GT/wCisoimJTRnmnKlCn53PIJEybkzzub2A8++FD4cp0j13yumPAhdHx1jMCSpr2Mvn7Lp/2EHWHUWX9vee+8886giKDLQJ3Tq27lOQP43nvvnaHqq666KgN4p2voO+WMEuIrlPKVxA899FCml6/n+V3i5/RKqFJ8fK31qaeemmlxeIdiQoGkhMw0Qz8T/POf/wzfDcAz8+P53/3sZk02QBSgdOPB973vfWGeAyhkxr777pvP2ManQBHePvzwwwNfmVtf+MIXgsHCvOs2v4FzRgtGBPln1lz1kJ+MIxTxmaWflecAnP6Qn7OSr6advymAp/Dn3nvvHUcddVT+yJn1A6/j5bKG/P3vf898je+t7Xgbj5955plhHVNOJyV8dMyXV33ls9vzzvTmiG9/OAaREafz+ezeUw4oKYccckhYq2e3nJqvUmBuUmDQAT3Qx5LEigOUAeriSic9u7oBjaxHDz/8cBSr1JNPPpEt5+94xzuyhZ8wIBQoBgQJaykwbAdAWSbd/xqLugnuvregbsLCx018GY8AIYzaF0dlsUYTEia2TwETRF/5ypczuH/lK1+ZP/dMKVCPNuuHq/v+BnWyuKlPu/qT709/+lOw3smX0sC8TZ9SCjsev/nNb6Lzy2pAsWOmfG1WH40Razngrg2lzdoPbAj9EcQl38yuvkYIjDizurNt3fJqBxr5rDf6dkszO3EWJ4AIn/anHbNTR82zYFDAHCA/fA3Vl6AZK0466aSgMANCDBwMHeYSOeRcZjLmU5/6VAjkzhvf+Maun4w3FxkzJkzYLX8he2YUMxd9rtz8Jmdmln5WnjOuAGazkmcw09a65g4F8K61Dy/vt99+gbfx+HrrrRd4nlXeHGCosta+/OUvD8ot3qYAHNTs8jpvnpGos4UveMELGoPVxHjta1+bPz7U+bzz3noPU1AqB1IuW+vgAgalerRiJ9Xr/VChwKADeh03cVdZZZWs6ZrwJqF4AWCeNGlSLLroonkBA8jEp9QCq76k6gMNgN2aa66ZP9qw8847x7rrrhO33fb7YI2VPqanT6mVL8d1+aNuYO+vf/trcOV53pgx2Z0EYCvJgbZvfetb2a2Fm8/73//+XK9zxrfaaqvw0YgVVlghWOa1nyDRx5T6rruUX64ppabZTwft+uY3vxl//vOf41vf/lYWbKx1LB7oQkD+5Kc/iQcfeDBbzdGN4KRI2Pq2owH8AgSseO3uM/ITTvpFqFKO7DDIy60IHS3+6rf4A8MAO+uec9WXXHLJUAbhNmLEiGyNB/bFdfan3AMQ8h9zzDHB2nHeeedldxx5BP3CD6z9rP9HHfXJRmE6Ju/GyKuclJ6mj3ttu+Tii+Oeu+9u2nB2TJw4MWz7UvCUyUoDeNthsbAI+qE8baEEWlzQ6Mc//nGPAqls+QuNPOdqheYWMLRmpXd/wQUXBH6RXr7egjqvueaavKvDteL000/P7QXo1NNbvho/f1OATDAfge8999wzXv3qV4ePmr3rXe/KV4YNhgRGDvOunCu/5ZZbBvkCzDM2mGvdKJFSaqKFyIq4HQDz4ayzzgoWUq49ZBj+pNyy5ts1o2SYs+QC3rTjyVBBZrCi/vSnP33GfFAO5d18YEwhM8gGigiwpqxLLrkkGAOU2TSs/l/AKUD24YNx48bl7274QOKrXvWqwOvWQjIab1MkH2x2w9/0pjfF9ttvH86Xf8Mb3hD43PqZUouH28mVUmrWxGEZzFvb7AJZZ+3cn3TSiXkdwe/Kl49S4Rl5Sq7iSXzIE8AayCvAGn788cfHHXfcHtY4+QTpzD9zwK63tc9aIa+5YA0xT8VzC5anhgWWAvNlxwYd0FtUgF2Wquc///lhAlokCvVo17Thl770pflDEtKXZ64AONDpaoJbLAHBhx6aEiNHjgqLpnT9DcAZ8LjuOuuGOt/YCBhWJkLDBFfO5MmTs6Lg4wcWV+0XX8Laa68dX/ryl4ILBnBb8pXns3pNKeUs3/7Ot4OlzsJ/5CeOjPPOOz8v0BQKQgsQ+NEPfxQPTXkob3PaakQ7QHH33XcPwNl7CgDu/vvvH1xj0E5gVd91112zpeScc84Jgm6XXXaJ666/LismBBva829kebNoE8wE2kYbbRTPfe5zcxsXW2yxLMQBfFYZQDU/mP4npdQI5BQABHem8ePHZxcCPr+Aw2677Zbbri5A/iMf+Uh+P4Eb09lnn9P04djYd9994vvf/34GFwS0bU9gRD8uuPCCeP8BB+Q2sPgAGwD6AU3cPffcE3fddVdov/qBcPQw5ic1FtJ3vvOdjcJwbLYiUX5Ylz7xiSMCKDGGeACNgCLKBxpxuQJYCHhlKp+bBKVrepd7vaAhheW9731v6LfxsOhQJA9qrFQWxl4z1wfzLQUWX3zxYEXHe2RI6QhwY76OHj06GzAefOCBIMvwJ5e9D33owLATaa6TdSVf+xWQMc+lVxZexPtkxqc//ekwH/g0kyPKNj+LggvMA0jaQVnFk65cHCi63Gc+9amjQt3mGlntvaGijJf5wH1IWeaCucNIIE6e9rbW3wsmBazjZL91B6/rJaCMr/DAsssum9dyyiS5igcpjGQeXgGOxcvXGaS1JpDhgPXRnz06rGXm08knn5JdZf2mXMIC1vKbb7k5AHq8zzhl/WZ04wKkjeYh3h0/ftf8jp21R17GMmugtcGaKI95ow1kvh00WEUZypSvs731vlJgXlJg0AF96axFzBfUuMhwGSkT2mIyZvnlg7afUirJm2vrtwnrJTHBIkaQAHAssttss03Y5msSR2M+zpeZ/QEiKRGbbLJJEDxvectbgrJwxRVXhAksP0Hyn3//O1vll156aVEzBLsJ4142LlgmAPqBmugP//fhLJgIG8LPtqb2WSxZmilFhJRdCwD+3e9+dwbOgP3CCy+c30NgpbOwA+Cs/AA58Hn88cfnF5GAya9//evx0Y9+NN9/4ZQvxOte97rYYostslXks5/9bOzc7IAsssgicfmky+OJJ5+IdddZp8cVhwUG7VhcWPhY+gnydgKhB4FMUKIx4atO7ZXntFNPyy+sEv7aBtgC2xQR4H3y5LuD9RxYkEb5LCfKRSNA5Yknn2x2MD6RrfOULqCF5YaSxlK04oorNorBvgHsAOKADMVMe7WFgLcInX/+NzKosshQOCh3hLo0rP9Ay6U/vzQoJhYyymB9XnQAABAASURBVA3AZMcopRaPtve9/bfytdvCtkKzowOIUSSUoa2AW3v6+nvBoACZYFdrgw02iAJ4yD2Wc0oni/1yyy0Xv/v97zN4pkhSYK+//ldx/PHHZ6UemC4ysp0q5oB3OMgI/AXg25WaOm1a9mc2h1hAAW4Wyg033DAmTJgQ5gMgJGiL+TBy5MjszkhmME6Qg+aDuaCd+FzZAJb5YG4CO+eff37YSdAP/RO/7bbbZhDX3tb6e8GkgLXFrpJdJOsBnmQQwkejG2WVEiuOhZ4Mt6NpPRDwErk6efLkZsme9gwC4UEKrnz4m+y2K7pOswYB4NaU5z3vecFqjkcppVu9fquwe8+AtEmzrjNE2ZXadNNNswJgHbVeWvu50ShbW6S3U0Cp5ddvB4Hhye7aAY2BaKmllsrlWhPXXXfdbKh6RoNrRKXAPKTAPAH0JrdFbrvttstuN8AzKxDt18IFMK688spdJwxNmWWTEAC4jj322Ay8P/ShD8WBBx6YLV39pSeLKYsWgeSzw6NGjQoLL2BOcShChiAhaqTT7v6WP6fpUkq5P8DtDjvsEHwPna7DKg74EpboZCHmd8sVCZBnRUMXoNzCTUgttvhi8b+H/5cBP/9CC7EygXXK04QJE7K1Xh3LLLNMCNpPMHKPYv27/lfXx4te+KJYvgGjngnGEt3UiW4EKyEpPqWUx1BeFnVxxgnAoIx49wEPXHPtNaE9ALb2849nYfRuAgXGDghFRDncDgRp1Z+GpdxWgpxCZxx33HHHDJwAZzTSfzRCC8B7iSWWyLsAwDQhTyESCOxHH3s0bK1akOyAUFRYbdDI+xt4buNXbxzorUxlobsx0Z7+hOWWe16u33YzEAQMoSGw1J/8Nc38TQGuWieffHIA9Js0gGOnnXYKvISn8SNepvR6vs8++wQ+PP2M04Mi263nKbXmWUqt63KNcgCwUGzNIfPBziV5hsfLfMDzfJSBcHORqwHw5blniy+xeFYw1MuFxu7Y2972tqzgmw9kBpA/boNxQUbYpQPolKkM/enW3ho36xSYX3KQ8YCy9ZmxBv9SIq215O/mm28edl/tAOE38poB6qKLLgxpOvuZUsqGpWGpBVUaDg9gXrnmjrVi6623zi6PDG+MLHickY1cNhfGjh0b5LbA4EcBWGnllbJRCm+T94xklAe7pwxa5g1jF4XX+2LWWbxtHgHz5H7Uf5UCQ4wCrVkyyI0y6Ql74IoFlQBgBWJBYmEyoQA76Z5uGkgdGQixzBMGwCirlcXH4jVmzJink/fjFwXC9htBQNu3qLHGAoIWL5NcG0xeYJ4lWPs6i5aG5ZhA8FvoTDM799NiWn6PwAJZFAk7BH7rtzLbr+q1kBJ0thr1Bxi18F73y+skzwrUPffek5UgQktZHizSWOBZzAk0/aXEiC/lO7Hn9jtuj8033yK0wbP2QBGyRUnosYCwlhjjlFIW1MAq6zwBDpDLSzh62YlQBXLEATbAgfaU+9GNlQd9S1vEtweAZLXVVssWQXVqv37JI52+oI38KaUMPjbeeOPwjgLgg0Ys7kD88GHDs2sPy7wdGoC7vS3ccopSpVxBuerpT5B+iSUWC4uKtqaUsvKhDkptf8qoaeZfCgAPdoMAehZ7u2d417whw1i+uXiRi5Rpbi+bbbpZXHnFleE9n5n1nMzA/0AMGYrHzJ8yH8wDPOiKb1NKAbDgc/KOrDAfKK+3/f62rJBLZz7gT77R5qh2UELJjL323CvUUcp19byGZxcF8JS1nGGNQczuMXlJPlszxBcl1XoB6NsZBronNbu/LOUzoxj+Jjut9SmlDMoBeDwqaAP+c3VvXpln1lBzDl9TcA895NCwq6U+ct56b+1klDJnxJsX3hWxnpYylSt4XkOlwFCjwHRAP/jNMtksMiYXy9H1118X3//+RdntxfZdby3ybPNGy2e55TMNXLHw2y5jxe0tX2c88M3aD0gut+yy4XrrLbfEnXfcEYs997lhUTz33HNDmYQRi6ytN755nWXJa9fA4ms7UL8608zufUopg/qUUi4ipdY137T9SakVb+FlAUEbINzCzuWEUCvJn3ziyQzsCakS52rrndLSTbByB/n3v/4dG264QQbO0ncG1hKWdcCYwsWiLk1KKVtZCELjHm3/jIN4QTRh2km/lFp987xbkAd4aX+W0ox5UkoZnKhH+7yHcNRRR4XdCpYcY0eYe64crkXoI7gvAY0on/qWUirR/b4qf/jw4Zke7ZlSmvWy2vPX30ObAviIkssdhX8ud0PugtwUtNxzrjP4Co+IE/A1a6L4p558StRMg/lgDqXU4qmUWtduGdV70003BfBFhnGLYGgxH1gzS1vMB7+lby+nzAdgv8Sn1Ht9JU29LlgUYF33XhaDEJmKz7nTlJ1L/MFwxsgilN4XcI6/O3mrpOm8LjR8oRnkZ0q985v1hZ++dYn7DIOcXShrojXeeoSvpVO/36U+7bQe4nHpUmrVk1LrWtLVa6XAUKHAsHnVEBMHsGEltmh54fNXv7ohvAEPQPfWLhOvPLPFS4BstNFGwdLOl9MkLM/7uvLFA9i5lnyyAXZ8TVmWz/za1+ILp56a37y3ZcifVRrbbNxCLMYsyqVsE/36668PljWgl9VZ3zwvliy/5ySU8rqVkVLKvocW8ZRSfsF00qRJYWvcTgZ/P1v4hJdytJd1Q9v0r5QJxAO4lAHW9JRaQssYecbyAviyWpQ8nVdWZnWxvPDxp1ywkAAXtizRrb1OQp5VUNtY+LSvVWZrN6b1u39/n87bPb3naIQ/KIDq5cpkzAEZ7dZX9JF2pRVXym4Qv/rVr/IOQymVddUJCMCZ8sTro6sFwcKmDPe9hWm5e/lPTxJ19twM9R+1fbNMAcAA33hXghV84sSJ2b2vFMRaCOAD0vx5SzzrIYBkztolLPEzu/aHn/C7+XD55ZeH05eAHL7D5gNLJv7G08paeaWVszXU+0ZFBotnOPCSLCVX+pRSVpxn1r76fMGhAB4B5gF46+oRRxwRXGLI9dLLO++8IyuNXC4Z8Eo8BdJOOes4HFDi+7pOa3au+3penlnjvLPErZbCQHbbiffOHVCP//Gw9YnhC3BnqS/5tc0ut5dgyXXxKaXA51H/VQoMQQrMU0CPHizf/La9tEUYbLfddtki7Vl/AvcMC5HFjl8eAD6zfAQQYMmCzR+Pr7ktwDXXWiu/9GK72zYboAbwmfR8qW3tOXWCYOAT7mXe884/P58VbStdO1gcADqLnrZ8//vfb3YeWsGLZ/rJoj+zNvb3OSGoLgstYcTKR/gAy9pNWHqBmNKh3wSbPgPYXlrSJoqIU1woOIAHBUbfU0r5FAAAmBWPm4rt0b7aplx0kI41RFqC1a4K4WonxQtKdjtsv7KabLjBBrF2Q3vtlX6gAxqhCRDPH9lYuaeooIk+246ltLgHcigl/DG1D434EKMXfvDSLhoR7HZkgCGATJ+8pKUe9B/oftTy5k8KAOVON2J0AMy50uAVO4R4CxjCj89fZZV8IhM5BmTbSaKUmy9kFNkypxRIqeWmgD+9r4TnzQcyxPwkuwAuPvwMGOaDODIa6Dr77LOzPDMfGDEEQIj7jflAvpAX3BblndP21vxDnwLWGEDZGuPdCmsxHihrn/VlscUWzzu7FFpylEuo9fP444/P35fxXhWD0Jz2NqUWf5PR1tr7778/u5eS6eYhXuZqaQfZWune+gDgk+HitUsafTIPtUnbUkrZV98JZ4xT4muoFBhKFBh0QE/IWzgsYH6b/CzsKaXYYMMNgq9bSi2/awuEhSalFI899njeZnvyiSdmoB/gyQ/bFjbL8lGf/GR2k3lq6tSc3gIzQ4bmxsQG1ABOL4ayqjfRPf9TSsF9xAIKrFl8AVKWK4DV6SRewNxq661i9wkTQr38A1l8U0rZB5twYHHjGlTCW9/61uCfCnz3VNb2o7SVkEkphXtWBPclGdCLJqwUAv9bIMHOAR929+jphU8v27HUW4S9Z0CRYHFmZbezgfY777xz6It7Pu6OE3O1I2G7lMWen7kFfNy4l2WrdWlLt/YZj0022STvECgfrY0zQMLaQeijx3aN4uZ9BfV85KMfibGrrpot4YAG3ih1lP7mPjembbQwbiWNeGnFuwrlt2d4aOzYsdnvH/g44IADwhi+eL318vGZ2sLty7astuBNoF8e28b6wNqERrZt0YZfqA+hvOhFL8rHmeqHRYDw9+IVkEZZ0Jb2kFLKJyg1l3jqqak9j7QTnVx7IuuPBYYCdnOAeXxr/lF4GQjwHpngxTtK5fhdd82nJ7HQm7dOijEfySKuheZjJ1HMD/xujvn9xOMt+ei+pC2uOtxmzAcygnHCriSZsfpqq+UXDSmj5CG54UVF84GbBNDPDccLsKyZ2m8+mBfmkmMEKfCUYMCJpRZQIx9KG+p1waUAcA7Ap5TizDPPDPIUbwv42HsiXlL90IEHBpnpBCX84zAAoNtukPXB2tFJJfxk3jz2+GN5J/q///lvPPrIo/m3tHjeWmC9lRZ/MliRp9zIKA+UBenIbe3Bv1xnvaRrPgL91nfyHVj3LosDCxjv9EF/zD3rGkXVUcbmqDK1oYZKgaFCgUEH9Kw8FgaTmNZrEpvYQPLhHz+853xzGrPtXJMopZRdYAgGYHVG4kUU1xvW3x132ilv+VpcvNCy0447dibPlgKLpToBS4tcZyLuJeqzPafNnlt8WZVZr7wBv+8++4Y0tuS8HEZo0fa9dS+euwsloAT34gk15bUHdLBoazPfVc92Hb9r2Jpn0XMvcEdCvx3eskOMHDEytNNLdGhlIfbSmt+f+cyns/sSVxIWP5Zl9PEOgrr024Juu9wJNcpgySdYU0pBqJ100om5fgs30Dpu3Aaa0BMINturdjd6IpsfXoLiOqC/AAOFg0vN4Yd/PAh8/usUG8eDOTZyww1f3uSK/JEdux9bbfWGvL0vkrKlLMLYFq669A/P6MeOb9sxvFhVFEF5KCxABeFtbAl4/eRShO/08bOf+1wcddQnM4323HPPoAAZ26OOOir40iuHMEcjIN1Ls8ZCOsKfhd72sbG1cNgpArwoCpQAC4sy2oM45XzoQx/OL+Z6pn3jxo1r2nJUOOFEXA0LFgUogUCv+SDgmRLc41/8A2Sbo4AEnscrZI00+L4bVfAa/qN0k6cUdLxPIS3pV1t9tfzRPEoEfqOMmg+UBXN/iy23zN+hcM/lce+99+6ZD+KkVxb5QtZRdLXN3GfFdIiBuWi+felLXwzxW231+p45LG8NCy4FnEJmncSnQuHtct1jjz3yi/+vevWr87HC1l1y+EMf+lDgJ2sLedqNQvjemkC2kv/k87777RsAtvQMXp4dd/xxscaaa+S1nXGP0oDHX7vJJoHHjz3mmDjwwA9mHOEIaLJeOLBRMhju1E/Ol/XJenPSSSfl3XfrifpKH80v7VJ/DZUCQ4kCgw7oLVrAHFAE4CAGixHQyKXXBui8AAAQAElEQVTDBBUH1ALJriml/NEnlqy11l7b42cEwNYknDBhQj5SEMCziDq9oTOx7WGAVvnAZudz99oB0CnDi2sWQvHaY7EFqgE8QglABDw9lw9Ak491m7AqwT3hxqolbXuQjyUBHSzGKaUM8NRVFArpCRY7AZs0gsoiSoFAS8AZMCWYgPYPfOCDceSRn8gLuefarU1orJyUUjhxRvstwK7uPRMoSW9/+/ic3wJ+QGPZBjo8K4Eg1T7W/xJXrtIaD0rQ6NGjc/SoUYvkLwQqD+1YRFgB88PmDz5Qnp2AQm/uOqw5AoWJVcUYO/YSzSh+6NE+jgS0OM+aYvPRnxQAghiNipvXhz/8kYZGR4Z4YJqQRiPvdShbXgqk8UMjwKv92Ute8pJ8RrjdDXlZioCqtdZaM0aNGiX7DMF4GQtgCMjzMKWUd6UoXgU4ia9hLlFgHhRrThpz81/ATyW4Jw8LP7gCO8DD4YcfHvgVoOit2fjMHGNEIE/tVlK0zYGSB7/jr1e/6tU5iqxigcTPFAFzx9w3D4AgskQ55B4Zyd2mzEcGA7LC/JXe/Egp5XIBLh/rYezYeus3zJLrZC6g/pkvKWCtJevxslB425XxxvpILuoceW8dxz/WAUomvvGsWyDvzQGyFt+S63i3lIcvPdtn731ixRVWzEXgffyOD1/fKKvm33bbbx+HHnpY4G9ttR6S+fjbWiUj5ZhSql3mHsW2PEsphV0q/cP/+pFSi+/lraFSYChQYNAB/VDo9EC0AZC2mA5EWXOjDIJu5MhngsrOulJK2aohfeezcg/c6mtfaUra/lyVo8z+pJ3bafQrpb4Fc0otGqXUdzpbw9wmtthiy/ri1NweuAW8fMqfMNjdNB9mVmdKKYP1lPqeDzMrpz5/dlIgpXnDP9ZsSu/MqG5tKnNvZmnr80qBoUSBYUOpMbUtlQLzMwXsfnCbYhGan/tR214pUClQKVApUClQKTB/UaAC+nk6XrXySoFKgUqBSoFKgUqBSoFKgUqBOaNABfRzRr+au1KgUqBSYHAoUGupFKgUqBSoFKgU6IUCFdD3QpgaXSlQKVApUClQKVApUCkwP1KgtvnZR4EK6J99Y157XClQKVApUClQKVApUClQKbAAUWDQAb2PMfgAhND+8ZN2mkrjYyk+tFPSuLrvDL2VU9K7tpfd/ls9veVvTzdUfmuroN2D2Sb1qbd89Ml9RO8t8Nz4ydN7qjl/og5tErrVZezFa8+c19b/EtSnXu3rf66acihToIypa2/t7A+/yY8vhN7KGcx47cCr2jWY9da6hhYFCu/21Sp8Il1fafBRf9L1VcZAPSttweMDVWYtZ/6iQOEB1/60HH/DmK69pVfWzNL0lnduxw86oPdFN19j++Y3vxm+mIo4nZ186KGHQprzzz8/fJlNmjvuuCN83VXceeedFyX4wqevzf35z3+OMgjSu/fMZ6c7yy/3f/nLX+Lb3/52+ApqyVue9XX1NVGfjVZPX+kG8pk69RNdfAVP2YAsWmEu93Mj6OPf/va38KVLH73xRVp9b69LGuNa4rXVl/QmTZqUv5rbnnYgfhPQ99xzT1xyySXhIzw+vmMcf//73/fUJ40vGF5wwQX5y8EDUW9/y3B85c9+9rO48sor+5ulphvCFMDff/zjH4M86e2T70899WT84he/iJ/97NL8KfveumPumhu//OUv81eDe0s3GPFPPfVU+FLmj3/845gyZUq/qyRvzHXfXeh3pppwyFLAOnLttdfGT37yk17baJ258MIL49Zbbw3zobeE999/f/zwhz+Mu+66q2c97i3t3I4nh3/0ox+FuaaP/alP3x555JH497//Pc/b35/21jR9U4B8+1mzFpO7faeMINOuuOKKOPfcczP+vO+++56RBc6RBv40X+DMWcGOzyhwgCMGHdD/9a9/jWOPPTZ8qMhHHh599NFndOnmW26Jgz72sfzRnmuuuSYLkMsvv7znI0fyHXHEEfmLhIceemj4QJEPWPz2t7/NZSHwjTfeGL78duFFF+W4zj8m7u9+97v48Ec+EtKwKnSm6Xavvb4w5ytygGu3NHMjzoILvB533HEBVBA6vmLqy3x///vf50aVuUz1+NKsj8joMxBNUOaH0/9oj3Z8+ctfzjHufQH25JNPDvlz5AD9MbYmqQ+CGHP0AOh9JGf8+LdnxQPgIMAtQB//+GFx5513DFDt/SvGeGiT8ekvX/Wv5JpqXlCAQou/fVSG/OpsA54knw444P1xxhmnh7namabcP/DAA2FefP3rXwuypMTPiytATkk59thjotvi1a1N5haQ5Guf3WjRLU+NG7oUwLsMWtZRcr5bS4GhM844I3+Rm1FJnm7pxFmDfV34iit+ERRGcfMq/OMf/wjzlhGqc83qrU0Am6+Bn3XWWWEN6S1djZ+7FBiI0hn44EzjCaz3VeY///nP+PSnP50/5PeJT3wifPxs//33Dxix5DMPPve5z+U08Od73/ve/Pumm27KGLWkm5fXQQf0JrlFzWS7otGGWN7bCWAS/bKxFtx1552ByEAz8P3ww/8N+XxV8Stf+UoYpNNOOy0+9alPxf/93/+FRebII48Mi5TyLJbS07TddwvqslibxN2eq1dof0Yw2CVgsesUbNKW0J6n8/fM0nR77st4r3zlK+M1r3lNLLroonHvvffG17/+9WCFll4d5er3rAZ5hc58Dz/8cLbc+PoezfXUU08Nv9vTTZ48OVjCWWfEG+OHpjyUFQ/3yhX87i14LvT2vMQbq+MbpYb1e7vttstWU3UD+Pfdd3+eiHYGfBhknXXWide//vWxzDLLluw91/7UJY3Qk6njh2cltD8C4oE6Vq32+Fn53a3cWclf0845BcxvO0EEPVBAUcPb7SWTIfjt0EMPi1tuuTUrsPK1p2n/LT+F1wIzbdrUvBBMmzatPcks/5Zf6Cuj50J7Gh/QefGLX9zIlNdGt691Si+056Ggm29XX311Vwum9EJ7ns7fngud8eXeM6Hc1+vcoYC18vrrr4+DDjoo7BqRre01GQO8euaZZ2Yj3N133z1TJdR8aK3bj/TwtnLay53V3/ILveXzrIT2NL78uskmr42XvvSlMXLkyPxIuvyj+eO30Pzs+c8jgPX1D3/4w1zhb/WV0FNp/TEDBeaUPniQfPKlX1eyti+ZbL3+wQ9+EAySL3vZy+L0008PXyS248oobA6Q27wjeCngJ2kZkq+66qr4zGc+M+heADMQrO1m0AG9ui0kSy65ZNaAWVERVLwAMLN2dX5NNKXkcfjM8yabbBKve93rwield9xxx5g4cWJYmG5pLPuChCm10ivHfW/B8zSsRQYCTX7WqjsbhYKQ0xaTXBsJQAqIAaaQSFuYxb1tS9s71113XbgvTAQU33bbbcHFB0CgyChXWcotbdN3AF0ZkyZNytoh5vTcZ6/f+MY3xrbbbpuFky3NKf+aElOmTAlWEQKIcAY6pC+BQmObVN2lPeWZq/r1D/Oq96abbsrbjSaVsllvWOJ8Pt64+dKeL+7JK1jg1a3t0qmLMoWuQDU6oAvLjnaihXwluOcW5Tm6UJS0qTzvvEqvHDxwULMQ+Sy9SUhbplFrn/7I57P048fvGiussILbvMBQ8m644YZmAft5ppvFR/1lHGnk2oAHrrnm6rj00ktzOv3MhTR/0JEiaKfAJBf0u6RJqX+81xTV87/wHqVI/cYDjxjnJ598oidd/TE4FMD/5uI73vGO4B642GKLBf7vrJ1hYZ999skW7sUXXzzzWGeazntzQ/l//evfspuOuX777bdnFxy8RUE278rcl19627vizSk8gjfEXdPsYpa5Q0ZJX4L5gr/xMX6Sr6QxP1/96lfH9ttvH0sttVSWx9KSUcCbMs1LckpbtIFcJEvMF7ug5pO6lKk9+vLzy36eZVeZD+QBaxkjxD//8c+wyGqPeVzSKEMd5p86BX0lVzyrYWApYEwYaN7+9rcHnsC7nTUYW7ugLJZ4f9SoUZ1JnnGfUgr8bSzxw88u/Vkeb/IUb4snK/ERkBTT/4nHI9ZJ66v5II90+NaaSubiwelZ8lwzF7jUWLusM9Y/9UijTzvs8NZ47Wtfm9dMafGsq7rwIB4nc7XFXPnt736bXS/UjT/RSZ3kM3lQ8pgj8qjHXIAFGHD0WXvJb/xe0ijD87JmeI7udryU8WwOxt64k3tkC9oAyuhX6AMT/PWvfw1j1S1Yx9GaHLLruMcee4RxZqhIqbUe90Zjsu7cc86JVVddNWNJ/AJL7LTTTqEdgnYd8/nP5zS8FTbbbLNsPNxvv/0C7iKrjHFvdQxWfAvJDlZtTT06bcKPGzcull566Wz9xejNo/zfhLBIrb322gGclcmZH/byR7qRI0dk64FJ2UuyXqMNd0opCJEPfehDcfDBB4etGgu1wJ3Dogkcc3sBGN1//OMfD4xo4k9slApWYls1737Pu7M7EMGlvybuUUcdFdIrd9999429935XAKFcWPRxSgPMuWlgEEFZmApgUC8anXDCCUFDvOOO2+O888/LVnqCyRY+0KE8QhpTl87+4vLLQ58IMm0p8a7Sfe973wtCW13a7qoOAkv7bZ8Sbvr7wQ9+MO8IyFsCRmfRcLUIH3HEEXnSjRo5Ku5uLDr6rD+0ZVdbt2WRNuG4zOirtnuOPhdffHEey1JH53XhESOycqR9dnBMZIsNrdqODd7SN37/H/vYx/K4KoPiYWz1cf/935377f7AAw9srKu35DqP/OSRQVE49NBDQ3to4fs3W2/oS7irywSmuXuu7aVvtmnbAYo6+xOMC97DZ4cffnjmvRaP7J1/W6yKYOtPeTXNnFPAAoK/WPmMiZ2elEiKGcsGNCwAhxxySKy22mo9O4Qzpnr6LqWUAQ9rPt7EQ/jHHLzooovyOyCsRe6B65j+z/ibKx/+8IcDwGZFMq/NyQMOOCDzyfve975gPS88aOHj3ohH8bCgXLwMoJgj5i4Lkzn+93/8PQ762EGhLwc380bb8L9y+dnjf/NXn/ErmWcumM8W0QOadpB973n3e7JsY8UitwCxo48+OsvVTxz5iTyv9Fn5Z599dn7ngNz2jpS2it93v31zOrKIbJlOhnlzWQBrtd7g71e96lV5rVq7WW/JofauAkkAtfHYp1FaGZWsVe1pOn+nlJo58FhceOEFwUVNvr332Tuvfeozzlw38YPyS35gDm/ja/xtt508xHvKwbfuAWft1A68B1xpX+EbaQB789f6Yj2wk/1ws8N/2aTLwhz4RLNGkfn77rtPsw7vnUGcOrXhtFNPC2sfY15pIzxi7qnjPe99TwZy8vOh1hbr/0c++pEwj8zJUq62myvaqgzuGtoqkO/K+853vpN39Qodno1XSph5jqZkj/GGB9DP+xhobCxhCTKmWyDnKILkJLzFmAdPrb766iF/X3SluP75vvti/fXXj7XWWisnhU2BdtiLrKNM3NEYeddYY41Yd911T+B7KwAAEABJREFUcxqeEozK8uMf2CA/mId/Bh3Q62tKKVh8LYQmD6swpvcMmBs9enRssMEGeeET1x5MOoLBYkfbtfiZKL/5zc2x3nrrZQt+Tj8b29gWORMQExlQIHy77bbLVlqLICvFrrvuGmPHjs3beBhrueWWi+OPPz60w24BcL3DW3bILwZpl0XTQqjNFiyDTnDtssvbg+Dhi0qwsVpxZ1GvfACjeIxKaSCgXJUzatQisc2bt4mVV1o51lxzzaCNArHaT0BMnjw5k+Dhhx+OH/zwh1lAscBpf37Q/MHkBKJJREEBDEyAF73oRUHgWmif//znx3sbkLB8Y+FmCTehXvjCFza5n/6v/9tss02MGTMmLA6UgmWXXTaiwT4AvclgchJi2oU+xhvoILz1b+WVV86+jvpM8HFxYA3Rxuj4hzfe/OY3B3BusUBz6WnR2jJ+/PgwMVNKWaFQzr///a8AKiwSxtHuDgHNVQsI154pjUKFBylI3//+90M73ve+92e/UcCIexc6oSlf0x9ccklsvdVW4V2B9zU0Uj6hdOutt3S0eOa3+gkUeUlc+0Y1lrCDmt0HfQPmuZgRVjMvqaYYKAqYK1tuuWX2d58wYULgrW5lU/zIiY033jhYvI1lt3TtcSmlAJSMOVC82267ZcMAWWBBWmaZZbLV1FwmL+Rl6KD8s2bZ3TSXuBlavPAfxRSPUD5YLKUDqPH5SiutFMCJxRKf8ismO5WrHFZxfE1OAUwXXnhh/O+RRzIABzzE4X/gHE+aNy94wQvyO05krvrMQZbKIyYekX1R9UGcuaTcu/5wV3aPUxYZIaAB2UmWa4f06mBE+PSnPp3dgMwvhgJzU3trGBgK4CHgFi8UN87OksllsscaYZ1JqRHqnYm63D/22OPNrubvwlpxzOePiZdv+PKgaAojR44MSjIrtvVHdjzvNzdK65R5BCQ76MC9NrKWwgbWCOCK9RbPK9P6Y+1629veFpRicpj8Ngfw1h//+Idm9+vJABzx/QUNfwNun/vc58O6RuZyo1WXHTn9tnOF9ykxjGTKB+ROOfmUrKjgXeu4Nc66e+stt+YDGpRx2GEfj8033zy/WIl/AT48bD6aO9Z5YB4I/Eyj6Lqiw7M1ZPlw111BVjAsHHLIoUGmWYuLPDP/pTOm3QIeksbaSV7jGes8fuuLruQ10A6PkPGMzSU9GaZMMolRgSyWpr1MeA2wp3DAaPLOyzBsXlSOSIhicbComdyIwdp6UQOmVm20qrUbTamduAEhRgSwy1pmsXUF4Ez8TTbZJAA2WyxNstn+b4ApEzR7AoLGbSJbOA064GzSArvqtED9+Ec/DhohaxYlhVAgECy4tugIKA2i3XlRcvfdd89aPl8sDCzce889QTBYIDfddNPYYYcd4thjjsmWLsJXu1JKkVLKPvRA6+jRozPQUDdA8YY3vCFbmn9z881ZK2XJ1wbPaaraUIIFnF8wZgbmgQr0ZGEn5NDUxNEPNJWfNtrpP084c3fikmCR13+/5QXyCeA999wzgG9CGTj+wx//mF0U7HaYEKwvxvMtb3lLBhFoim4maWlvuZo8FATC3HOWFGNFqHvH4MLGMmTiSZ8SekVDs2H51AVK19Zbbx2HNdZ3VxbSt771rZlW0faPpRWgNk7oot2TJ0/OSoFxsCO017veFR9tQDctHg9u1YB7yqmFpK2oWfqp3XgEyFGvPuLF++67P79Pou5ZKrAmnm0KkD2MDrZhzd/eaA8YlDnRW5pujaA4438ykLWaKyFwMLnhsw033DDMJTtM5CO+mDRpUuY/vEYeKFN9ZB4jAz4mqyw+5jwl1RzGy/icW428QL0yWdTNn5SSopo5ki95LpB35i13DKCPqx/FXD6AZJVVVglKuzlLNlA88D2lnQGEHDLfyfivfe1rmXeHDxseK664YiiXnASW7KiRffpNGWHAYCwxpyjtxx17bN5FMwYptdrZamX9O6cUMDZ4g4xOKeVx7ywTmMUL3t+yZuO3zjS93Vu/Jk6cmN258IJ6KI7Sk73KI+OVaezxrDR4TRrx3oEiC607eAb/2ilm/CL3GUC8U0fhIH/JbGsNBfPyyy/PLnLmcUot3kkpBXdR9bPkmxPykLkUCGuLNcT8Mv8YqCgBFzYKAKWYPLbOwgXmnLnK+m+tSyllN2BKqXayMmu/tlhjAT5rrjXfmqo/Jxx/fJj/1nF9ftaGZniefOrJbOQlw3bY4S0xYcKEvFNI2eEWhTcYFewodgvkIJk0fPjwIJ8Ab7/xUV909RzuhD+Nf3ta67zguTHEs7BNexr8ZJ5QNpTV/mxe/J4ngF7HLZIWB0KF/5GJw3fqoQcfjE35vDVWSuk6iWJCGewdGsC7emMlMhA0MVYywLIz/azcq88ArbnmGtmnNKWU3X4wB0u7iSuNgVWv36zmU/49Je79871Z2WCxI4RYc1l9aZnaII9tTVqfe8zDEuA3ZtigWcQJT0z7pje9KS98FlDCx4KmLmlLUL8yLfZ+00w3aZQa7fdSsYX92muuzS8SEyCYveR1xaSs2hZZgst4iJcOKNcfQqiR9PnlIIu/592CdmifdpTnU5+amieoMRZnIlCGpNUvGq82CCwkFnraOMGuLBYYdJG3M1ACAA2CnbAllF/xilfkvr7nPe+Nc849N7c5pdQAlVYwHtpHuVlk0UVzkRQzSowbdbpqH+FNoFsM0NM4oTMa6IedCjxnJ8cOg7bbflX+U02/lTOrQf0E0Ite9MKspMlv0SWctAnviYuof+d3CuAlPIX/9IUsIBvwG+sjBQGfArh2aKY89FBcffVV2bKJX6VTxgtfuHazK7muInIwj/GuRZAFkfJMJlA6coLmj3mirsmN4oBfm6gZ/uM1yrv2pdQCQGQE3lcnPnUV8CS5qC68yy3HHDYfzGnl21kgi1JK2SWJ4pJSyygxduzYPE+V4TdFBlCjKABpN9x4Y1AOgKCU0gztrDdDlwILj1g48BC+1krymnIMuANG1jPylfz+03TjjnVyw2ZX/oXNDjC+kQ+4th75zXCE9xnVrLl2qvENBZKvvDR40L3flETzxO/2QJ7jwTL3AEVrMv7G23jaHNAG93a0GGoefezRYKXH28Cj3XVzwA7AE9PfcTK3YAX1mcP6DcQri6EO1qFQU1a553gVfueddgpzTZ5ndWiIgUZkGDqklPJ7kcbJWMIi3IYpSLwo2oM4yiJ+kHdWQkopKKzwj3Fvz2v8jTGeAdpTSvHU1KntSfJJTnhH/hkezKObYfOo3izIgSNaMvcJrgoXXnhBJq6JnFKnAG9GvGksIG9S2EL+6le+Eqw5Bhe4MhmbJHP0n1B47nMXy0CwFNTXYLGqT5s6LYalYdlNg6UKWLWwaitAhimUVQSP35iF9ucqUEZMclZhgtAW4D777hvAKrcRaeTrK1gQAQH0YHH4XmNZIFjFpzQjPTHv/x75X7ZYYNZSLiH43Oc+Nx753yPNNuUTJXq2rvrR3mf9zQVNmxZAPbqYTIQmuhGcBDaeoNykNGOb5TV5Wf2ktUgYf1uf3HcmNhYhdVzU9Ns2Z0qt/GjHHUD+RRYZ5dIT9LXnZvoPypFypt9mS48yUkrZz97YvOc97wnKGysTxcOi0BeflLL6uqL9EkuM7kmiTmWm1OpHz4P6Y76lgDEVnvvc52S+Kh0p/GZeUuSAFwsJK7sdt9/+9ncBrAAg8su3+OJLZDcfvwXzTV78aHGTbvHFF89GCc8FzxdZZJHMx+oS1xk8L+3xDF8qy+/OoAxKuTxkoXlpLvvNlYPllHyRzlUbSxlkrd/KpjRwlbBbB+BQkO3EuffSOVkhbQ2zSIFBTm4sR44YGc95zqI9NeMfcswzfFDkNmWPxZ27DX55Y2PIwhPSydNpuSargWP8Zq2Xzg5RT0XND/cp8eN/vLl75v+UUlaMtac8VZeyyn371VwS9Mm6jrcF88h8ZLCy9k+LaVHqll+ZKbV2PpTNSMa7YOedd87Yx7txe+21V1izKODyPNsD2SAUOhijRZr1mixDezuZdss7A5rChIzCJW9/rymlgEPJO5ikPR8sgl/J0OWXH5NlLSNtexpgXj5l4N32Z/Pi97B5Uak6CWgDxhpjMvOforHT0Ah3aboFi5xBN7mBPhYhWjFfNRaibnnmRlxKLZBFCyd4nD7Db4vPqoWJjxw/OkAdU2jD9Cx+9oSUWpOecGORO+Tgg4OVnmsONxKA0aJOkKXUqrMnc/MjpdSjfLBmALisfBc2oPbGG24IOxr8H5ukM/xHRz74hCNAXR5iUNvg6IvJS/zsXFN6um0lP+HmN5oZf9udn/vcZwPdBNYPIIBVjtCUtj1QVFjI+VOiCcG5SANQWERY87hCmdiEQMk3bFjKLgLq/tOfJpfoLFjRvSeijx8ppVAXyyZh7OQc1nkvKvP5ReeUWmMZc/AvpTQHuWvW+YEChjil7uOcUsp8xlolcCswl/E0ANE+Jyxyjz76WJR/gIYFZ/nll4+iYIpjFS1pKLrkzHOe85xcT4mf1WtKKcsdixggA4RTrM1h88KOKTcg8oiMJANTSl2rSSmFvrDEcfMhy4vvNsBni52Vv2vmGjnkKJBSyrzRrWEptXZnGJ5GjRoZP7300nwwBvltJ7nkwS92mMo9vMDt1dpv3bLWWcPIY2lLOmmsC9YE8r7Ez+o1pZSzmCf4mxsqg1vhb25slG5tto6pK6VWnpyx7Y9n2mWusPBb3/E3kM/n3xrfvl61ZX1W/TTHya/SaUY4lnm8YV3nzuT9PjslncGOHmt+yTsrVzwlkD/wkLz4jaHZmJFfSy65VDbA3PfnP/ccxy0d/CAtQ4u04uZlmFNAP8dtt9UKmJ911jlxxx13Bp84xO2tYJOjPEsp5TeO99hjj7C1ZbBZiMrzuXFNKeWF0MAL3EhGjx7dbIlfnYWY3zS7k08+Kb8kg0EBwZjJPwrN/vvtl91FLMgEBV96oNpkb++3olJKmcFoh/qOqVJKzY7FpqENQCehRugoIzr+EVR8Ey34TroxeVg9+MoCy3x8MWlHtq63KaXcd+3Q96nTpnZNVyIJYDsXFDdbZU78oAXTcrncAMiAe0qpZOm5As4s6PqHZvpvHNDZws//3paq8tBMUJ/+WATk8fKVttrJUE5KKbe/p5I+flhkbB2vu+46YYxsHwMjhDL6GYfO7JQkE1+ftLXzeb2vFOikABDBT9f8PPPMM4M/LncE6VJq8StZx5KNp8y7884/PwNjyjB+J1e9N8JQgjel8RKhOWeOAETKm5WQUuqRf8oDZshAix/3A4YAbb/llpvzDhaXIQArpRTd/qWUcnl8/rnRfe5zn8vujnYV7XBaJOU3j6P+m08o0NirWxvqvbYXP3Nb/M63vx18pMl1vusypNTiFXLa7vSjjz4a99x7b3zlq1/NVvAXv+TF4ahi65sDCrhn4m9rgBdP4Qflzw7PlLWaEoy/rVNrr712aIs1Em+r1/strOuAem3e9goAABAASURBVDTNTc2f3urDv94zgVP0VZlc4SgJnslX6tX/Z2MYvtDw/EVfCo7xZnRgyGw28/NRkcA6o2mndb7cM56SPf2hnXHl4sVV0NoM53hXbdKkSeHlZfXfcccd+Ts/3KTIN0Zj73eQU2SaNAyhPAO4NJKnZFV/6p+baeYJoMfEQBZGBrxM5scffyzWWnut7DeVUsrWU8+lQ4DOqziBxYrPue1dC5dTVIC8Ik+mPvWUZF1DKb+ULVFpm98leF6AmgWMdZavJ2vSk08+FbZ8vD1PGfGCKbeZK664Mp+Tb1F98skno9RVynRVpmcppfxS7Uorr5z98JXr5Z4jjjgiv+DBjx4ol1ZQFsFCa+VXRjslKJS32mqrh21ATGt3gBVAXZ0BKPbyDtp7sYew8Wa59xMWXniheO973hMrrrBCzqb/fqjXtTOYSMAyxcALwSYKOmlPe9pSDj80k8g2mXbYVvdC3fhdx+ctSALUTo0y2vP7zRLohSPPuL1Qekx0E9rOiD6jnzY92YyNNqvXLoX6TGBHhpqcXswzMVNKGVRI+1STp1u7n2zGsJTD//O73/1ePuUD7b1gxbpgQtsdien/SjmsDCwztgwpTNMfz3BRt/JLnvKwxHle4ubf6/zbcuMwszEwdsLM003tkW+FIvLhsZIXL1G4ue5R6PE5S1FJn1LLv53VEF95ifr0BvDga2Hs2LH5SD6KuxfNzBVpWM/Jyl122TnzvHrVKShbG/TV7xI8K/HmHfnHj5mco1CYfxa9iRMnhjrM5QMP/FA+196uwqhm21w9QkqpFNtDA2Wbn2NXXTWfdAHIe5GSLFEXOhSw15O5/hgwChhfhRkf125BGs87eaMzrXRPNjLUtTzzW17Bb/F4ecstX599kBly8Deg7FkJ9//l/vDyKN7dfcKEuOfuu/PpJ9Y365Z1lzzFJ9YQrpoUgHe+8x15Z5qsf7KR2+W9Jq6xyi5t8FtwXwJjmN0ta5l6eQ9YJ1NKYV3hBuZlboYgQM7avNDwhXI/lNUe9Ne9OQMHAKV2sayx5g4DpHjKiTTSPltDSg3mawyBRx/9mTzme+21Z1CC0N47B7NLlzIG7fkZHw444IDgzmy9Nt52ExlSredkD2zAYu/3+uuvnxVJvCgtOec5fmAcwX8UyPY65tXvQQf0JozTTCwqCy+8cPbvJLBZZ4DhIrhZo4BahKK9rrfei4PPGcHfSSwgDxi1sBEOJiHQZdK8YqONOpPn+5RSAMTv2muv2OjlL8+Lm8XDZGUdsqBKCEgDi5QGZQOK6tlxx7fFiiuukH3Q3fOnVqetcYuwvmgTawHtzpvxG2/8GkXmoO/A9i677JK/vGoLEiAFrEeNWiSfR40u3HgIL/VibIsdJUiZ6CP/2GbxViihpL3cWABs7bage9YtoBuXEe3XTlYJgtV2+VZbbx0LjxiR32nY8W1vy9Zobe5WDovDu9/97uAihOGf+5zn5t/utafkYc3WZkIMffWHUNNOVkaCkVXSaQKEZUpPL/6ljFGjRoVJji4m1NqN9cS4APJ4SHnGT1u9i7HbbhPCeKDN5ptvkb94uM0222aLJ8FqvAlT7ZHHOHH5QQ914j11vHO3d8YKzXib9MC5NCw2lEe8wbJoAcBDo5sdG4uLNPJr8/NXWSV/6EKZnSGlFPIRDKz+KbX6La/xUBa6duar94NDAeNgfpongEi3WsuYA9Pmarc04szdbbbZJvBimRv4joUIX6+44oqS5QAAWEzML89Lerws4Bn8ir8Ei08xAuBpQNv8xkP4lPGjpFlrrbVDGjJIGfhricWXCDxINpe6zAsWf/OSbFYGGWTukDMppXw8oV01ccpU16abbpLn2uabbx5LNdvV2223Xdgt9Dx3rvlDxpN3ZPpqq60WJ55wQlaSyS7yQL1kkZNA2vM1Wev/AaQA+YknhW7F4n/vYpGVxiSllnzqltaaCmgXGS8NnucOaW6U9SillI9cZtgh65WfUqtcvC3fq171qthyyy0DL+A1H7iyfgD+yrROcL+07rLOS0M2v/vd74mll1oqgzC8w+3L/IAlCr+l1KoLPwPlZLXf2qMOMtdcBwjRheK8ySab5I9OKYviSuZLbx01b/CzdgvmtHLRzLzRD8fSAo76l1LKJwBRsNFUnmdzYEhb50XrNMbRXRrj59QYPXrJLAu4NpEHs0sbcgfOaJfJeMc6CyfgJfztHqYwxvjNmMJ0ZLKxTCnlo8q5A2666aaZJ4299sFgeGd22ziQ+YYNZGH9KQsRgF1bJSZGSilblE3WnXbcKQN85Xhj3CIBlKWUAqEJ927Mb9Ep6Vlvga71118/H2P55mbxVF63YAKaqCasMggE7TC5y4KmjRYzGpkF1sLSasun4oQTTowNNhiXAfluDeAzYR1Fx92GlcqCm1JLcdBnC2Fph/IJPkwzduzYrBiwStMa5cc4Rx99dD4KC9ONbkAi64BytEN7tUOd6IJO2sYqQQNVN4FS6ut2TSnlDymgmYUfGObDvmVjOSmAlrCntZoYGLtbOdKaNBQS9Nxggw2CUATy2xkd6NbW12y8cS7GM9uujp3UX7RDf/n1JSfq8kebKDvS8qXjk8i3kSXSQqKd6KvNAA7AMPlPf4pDDv5YcFOwCGgngGbrzW6HCa89LCjabtKr2mTPvHXkJ2OtNdfK46Ru/nzaTCDrJ1CPdngJOBKnHPmNH540hpQa5baHlFLgPZo/ZdfYei4vpYU1gVKSUmsR8qyGwaOAcTCueMY4dquZn6d5RE5YwLulEWfu4g0LBdkiDq8CPMYfr4oT7Po4zQNP86dP6enxBwrwlbLMO/MX/wPG2iu/54VXzW1zRRruOOaXegEe7V5xxZWy371z5MWVtkm3ZQOqvKtEdivbPNZW5Wm3eshbYMoOqXnsjG8AzpxifKDsAlPK0zaBzDJnWPfxPMDF0qovrTI+FwCQ+Sl9DXOHAngS3zKIdKvBmBtfspSC5r5bOnF4y5oGIBlTcYAxRdKa2D6W3FUYRQCkdkUWb9sJWOMFLwi7qngXj5OFZL8yBXw1YcKErDjiO2l22223/L5UNHMFELSeWr/Jd23Cb9aXlFpzCe8yFOJNv/E9Wa4s6xJjjrzW0iLz1XXwwQeHOakd0uB9/OxeMLesL+K1kyJDsbBm4W1laAtDgTkiz7M5GHPrJqxx4okn5Xfq8Ix1b07oYu00DtbeUo4y4Sh4Cu+LN+6wCCXNdwJOPPHEjGHa85FdDCCFD/BlsdorYyiEQQf0hAHmRsCUWpMKoUyadsYGykxeV4QyQdrvxbWHUoZyCJJy315me/qIyBYqZZY08slf7qVPqXWsEdCq7eKUDfBZuLVL3IgRI7NFgBBZsrFIEQ4ptfqn3NLnmP4vpRRooD7PRbuqhwDE3NomzrOUUj5/XjmlHWhDQApTpkyJL5z6hbyL4QM0GI+WKW9fIaVWuRhbndqjfyVPSinUqa0ptfpTnrVfRzTWfO0wAfzWDyGlp/MoV588L3n1T5y6BfWLK897uypLu4wBganudpqnhL4j84kGw5st0anTpsW1v7w2uMcQxqeedlrs1iwGTkeyoBDKKbX62l6O+tG5vV3qNv5AHLpJL04adDI++i5efjsfDz70UFjQ0EdcZ9Bn+dt5TxrlKctz9zXMGwoYF3xqbLu1QDx+NFYppW5Jcpx00uCNlFrpUkqhfONvnLkRHPnJIwMQ8X4G0Eyu5AKm/7EAAj2ueMo8UOb0xz0X5Wm3uVXSaENJgL+0W5ygDeJSarVNOvNVvOfuS5nKK2k90y/zQVvND3NC+vKss33mlba5SpdSyjuCyi1lqNuzGuYeBcr4GL/eajGWeGBm4yEdfmpP114+Fxg+yBQ3hhVrFPmL/zvrxt/Ksh6S7+1llrTy4X/8jefcl2fqlb/wKD5r5zfpUmrxHN5MqcXz6lGfII90+iWvegTlptRK7xnalLTSC8oUrx3uzRv55Nen9meeP9vD1Gmtd+/IEDLAuM0pTfC0kFJrrJRnPIyDeL/FCcYHDxkfbWjnJc+FkoZ8kmYg2qjcgQrDBqqgWs68pQBBecvNt4QXL22ZczfCsPO2VUOndlu6p5zyhWBF8eLL17/2tWC133///YJVnoCdW60lnFjAWJjmVh213LlNgcErn8vKr67/Vf6uAr6xa9O+8AAO3rexqwN8DF7Lak2VAnNIgWkRf/vr38I7ZwAza74dn/ZSgS2753aN2uPr7wWTAo4EtTM59vljs+vzgtnLwelVBfSDQ+e5XgsrNWB65plnBteAYnGe6xXPJxUAPixB3HPOOOOM8Hb6WWedlb9M280NZiC7pW6uGt00/oGsp5Y1/1MgpZR90m3r+t4CFxkKYXvPAKEPHHBAcLdjTWp/Vn9XCgxlCiy08EKx1dZbBbcT8pd7C/lY2pxSyr711rA999ijRM9/19riflOAK5/dGjvn7bzQ7wJqwh4KVEDfQ4r5+4dtP/6z3pjnI+Z+/u7RwLfedpmXttDICzGUnqWWWnrgK6olVgrMAQXsrPFF5rfcbefI3OZzTBFlrZ+DqmrWSoFBpUBKKfC0Y/7I324uC1xV8PbzxowZ1LbVyuYNBYB47xFyv2rfiZw3rZm/a62Afv4cv9rqSoFKgUqBSoFKgUqBSoFKgUqBTIEK6DMZ6p9KgUqBSoEFlQK1X5UClQKVApUCCzoFKqBf0Ee49q9SoFKgUqBSoFKgUqBSoD8UqGnmWwpUQD/fDl1teKVApcBQoIBTae64445w7a09njmByhGmvaVxBKUP0ynLx016Szcr8Y8++mjcdddd4fhLxwDOSt6atlIgYlo88MA/409/+lPXr6H67oljVgW81hfFnMTm7PnJkyeHfH2l7e8zxzWr23n25k9/80k3q+nlqaFSYChToAL6oTw6C2bbaq8qBRYYCgDeX//618MXAwHxbh37z3/+E1/5ylfCR06A+m5pxPkq5Xe+851wss3tt98mao7Dn//85/xxHqdfPfbYY/0q7+GHHw5nhf/0pz+NqgT0i2QLbKJ//OOf4aNiPrRDKW3vKJCPV30pU/BhqhtuuKFXngG+fVjps589Ov75z3+2FzXbv6+44orwYbRrrrkm+gvQ//a3v8X3vve9fMTzbFdcM1YKDEEKVEA/BAelNqlSoFJgaFMA0GVNP/vss8Mnw33RFRBubzWA8de//jUcz+dLxsB8JyhqT59Syl/Kdg63j6G1P5vd306NeM5zFo1Ro0ZGSk9/XKW38rT59ttvD190vuyyy3pLNojxtap5QQHKn52dI444Is4448xnWOgfeOCBmDhxYpx77rnh1LBXv/rV4fsewPUtt9zSFVyn5MN9i+YPJOLLgeiXU558oMm1P+XZGfjJT34SjoW1U9CfPDVNpcD8QoFh80tDazsrBSoFKgWGCgV+97vfxUc+8pE48sgjw3Y/QJHSjIAZIDrssMPi85//fE7jeLaUZkzT3h8gZ4sttsgfOnOMm2f/lKsBAAAQAElEQVQUh3/84x8BZNsBYF0U51kJXB2Ak9///vdxzz33BDBWnjnj+X3ve39su+12oY2UDmUANq7KZWlVhjyPP/54KIsi0p7WM+H+++/PbeE68cgjj4jKwe6CdrLCir/77ntyOuVQEnKi5o/fDz74YOjLbbfdll2BuGI0j+r/IUIB/OML2j5qdv7552clE++U5hnrH1xySVx88cXxjne8Iz71qU/leeAr3MaU9RvvlPTl6kur++67X+yxx54xevToHK2se++9N/DuH/7whzxP8oPpf/CL+WUu4VU8K27643jpS1+av/7tGMyUUlA08Jc+3HvvPaE9eLbwGJe3O++8M6ZMmRLSuZb5ZA6YC7c1u2P33XffDC5GnuFlvF3a84c/3NW0d0ppSr7qj7zq1WZ15Af1z+BQ4FleSwX0z3IGqN2vFKgUmHUK/OhHPwrb/VtvvXX4OI6z4duBhhIBHuk222yz2GqrrbpaLaUrAbD45S9/GT4oBYQo79e//nUcdNBB4Wux22+/fXYv+PGPfxyAhXxAxhe/+MXYbbfdGtC+bey+++5x5plnRgE+AM55550XkyZNCqDmqquuio83SoadBdbUbbdt5fGxNSAMoPnil74Y9zYg67vf/W52JdIWzwC197znPbkt48ePj8997nNx9913a0Y89NBDwS2D8nL88cf3tIdLxuWXX96jZNx8883ZBaj05/3vf39ceOGFfb5/kCuofwaNAgDrOeeck8d0zz33jP/7v/+bgXcpfVddfXVwJdt1111j2WWXDR8723nnnfNvPKyMzgZzT/vWt74VF1xwQc5b7vfee+/YZpttYqeddsrKgd0uc0F+1v6JzU7A2972tsD/H/zgBwP/y+s54Ix3KYjmy5e//OVcBhe3PfbYoyn3zdnVze4BJdZ8/Na3vxVc0VjpzTXg372PXVFQ1LPvvvsGZcaOmnLVw/VIua32vDX09+ijPxuUW2mAebzM9ci80h9pfRXX3NPeGioF5iYFKqCfm9StZS9oFKj9qRTIFHjFK14Rp556agaxa6655gyAJydo/mywwQb5OXcbaQpIaR51/Q8UALw/+MEl8c9//qOx/v0r3v3udwcQss4668R6660Xv/jFL+LAAw+Ma6+9NoP6I444IgNkBb7yla8MYIs/P3AC9LBA/uAHP4jrr78uA/o/NFbQM752Zt4F8FuZlAJfafz+978fPr42eonR2SoLpPkIkHZ94xvfiAkTJmTLun4ttdRSGdBrixdu1QW4A/nHN4B+xIiFY/XVV89g/dBDDw2KAmulL0J6T+AFL3hBvPzlL48bb7wx73RceeWVvfpe61sNg0cBHzYDbI25XSguLXigtADItRuz+OKLh48YxvR/Sy65ZDzvec/LfAvsT4/uuVBCvZdx2WU/DwoikE2hwz8bbbRR/uDUSSedlJVICqVdsL322iu79fggIL677rrrAmC+9NJLswX9j3/8Q1x00YXNztTdeQ5eedWVec4B6ykNi3XWWTcos3bKWMx9tGqx5y6W+Vtb9dUc+cxnPhN40/OXb/jy0L999tknv/sCqFOQv/3tb4d5ArSvssrzIzXlH3PMMXHsscdmhVTb3vve9+adKW5IY8eOjS996UuZv4vi20OM+qNSYC5QoAL6uUDUWmSlQKXAgk2BV73qVbHllltmEMHy1623/IpZ+wD53tJ05uN2A1QDCyzjrHsbb7xxdtthTTy5ATzAjzIBFSDDDgGrfAmvec1rQjxLJ4DCXWL48IVyVWlYymBGGpZN1ntuQ6NHjw6AHtAGsoCRt771rQGwUBLUDfzYDQBS3HsREijjkwzwqceXPwF4YJCFc4cddggKA9B21513ZgBPGeKmcdppp8UJJ5wQm266aaSUFkBAn0k+3/0B4FnM8QJFzdi2dwI/4GdKHX5tf0YJ9JyLSmc+6fCIkFKK3/zmNxnY2wU45ZSTAy8efMghsepqq2ULPv5keT/ggAPCi+d4DuCX328K4sILj8iuZKUdw4cND+1XpvLsNPjNim4umSt2l1ZeeeU4pKnLjhblmNK7+eabh50r/H3yyScHJZxFnmIxfPjwzKMUmNNPPz3wt/m24oorhude8rX7RZGhDNmt8n4BRWL99dfPynQ3eqBJDZUCA0WBYQNVUC2nUqBSoFKgUmDgKMDiudZaa4UTPA477NAAJJZfYYVsoWfdZu1kPeS+AqComSUTiGZ1vOmmm2LkyJGinw7TIhZdZNHgKrTGGmsEVyFWer723CSADoCMwsBNwD0wdPc9d8dSSy8VdhCAnosuuiiXyeqqffJIC+S97nWvC23nM13cNbRnucZ6u/baawc3IqedcI9YorHycqOgpABNudD6Z0hTIKWUwW238UopzbTt0xoelGi1BrhTAIFz7iyXXXZZbL3VVvH+970vxHOtWXXVVbOrjd0AeSjSgPeNv74x+8sXIO+ZMC2mhbnwhje8IfCicjbccMMM+otyUvgaz1JM8CPXtIUWXijvhnmJHcinwPKHx/Mptfo1bty4oGAr1w6UnTNlKNtcpRh/85vfzCcDcVnbolES7LKZlym1ytDOGioFnkGBAYiogH4AiFiLqBSoFKgUGFgKTMvuC6ecckoACpddNilbFHfcccdsNWfxdsoOUMVKCJir35UVccSIEQFEPwPwNGiKhXOZZZYJeUse+YB49yUA6AKg/9///DcefODB0B4uRMLVV18dgIpdAOnkX2qpJWORRUaVIrJCoQ0stis0ygggz2IpLxeHt48fn0/UufvulstET8b6Y8hSANAVpvzrX89oI17BXwBvSr0BWIh+WtgFwAMA9vnnfyP222+/ePvb355ftuWSA2QDyMstt1yUfxTU5ZdfPh745wP5vYyUnlnHc57znOzTn1LKioc8eBB/Kgevlqs47jXA/a9v/HWeW8cff3zYPVI//i5plaEtKSVReXdOXcoTKBqHHXZY3gHzvsn7GsVk13e8I7sMoYs0OWP9UykwlyhQAf1cImwttlJgiFGgNmc+osDUqdOyj7xtf64Dtu/557I+spCz1rNaTp06NZzcUcCCe0Ce1RCQKfHtXU8pZaBT4lJK5ecM15Ra8cCZ4CU/7dAegRsEYD9hwoQM3NUF9ES08kXzL6XW75RS9u8H6rkqeDnSS7kA0yWXXJIVBSCuyVL/D3EKUNjsvkx56KH84mxprt0aIJjLi1DiO68p4YmUAbmXXbm7UBTtLOFfbl4UvsUWXyzPAT77pQw7Uvh7kUUWyQppLqo8bLu2+LAVkZL6Wr/b/0qTUsq7AYA6V7Hzzz8/A3D8/dWvfjW/YPva1742u4M1SZs6Z4RMKbXK1m79f/3rXx/4mUJgvqjP+yxekKe4uK+hUmBuUWBG7pxbtdRyKwUqBSoFKgVmiQI33XRTlJcCX/ziF+cX8vjmciXgP/zCF74wgBKuCfzUWRlZG30USjx3BcB+liptEqeUsvWRG4ETQOwAcMnhmsBHmquOsrWPT72Xa5tskVIL3PjdGewY8DV28sjZZ50Va7zgBeH0nqOPPjpYXO04VMDTSbV5ed973QsttHA+LpLCCABTKIFZVmnvfXDhomz2VkJKLf6imLLK4wsuMpRDJ97YzVGel1Pt3HjZmrKHFx05CeyvucYaoQ5Aurd6eos3N/Aa/pb/RS96UQPUhwc+pjBTou00UToBe9b13soSn1KL7/VH+80TbmdOfPJiLSXE/FSX9DVUCswtClRAP7coW8utFKgUeFZQwIINOLNQ99ZhaQDumS3qngvKWWbppQOAAeK5qrBiAgkppQBCvHDL99ypMV5sZbWfOHFi9gP28h8/e6AFeFG/MrVR+a7uBb8F6VJKwY1goYUWyq4PTvBgDWV55Etsl8ALg+r75CePzMdbsrIrR/+UETHNbQ7qRRtXVl3W1hNPOikOb9rplCAvxQJw/JztAuRM9c+QoUDhi9a4tprFVcsxrM5+Z8X2ETJWdcoZdy9uM3iolXrGv3hBUO7IESPyqU14SX4BL1MevXvhKFauPYA+vmfpdtY9V7N3vvOdwar+2GOPh/LwtJq0U9mCe8EzQRwwP3r06Gz594KtE2ucnkNhtuPkFBvW9Y9+9KB8wg2epHDK/9RTU/PJOsosQX2Ce4q2OWIOaq92l/4o35ySroZKgblFgXkG6OdWh2q5lQKVApUCg0WBlFJ++Q6Qsfh3qxeIcPwj4Ascd0tT4rxMusIKK2Y3gBc0VkjgmcUT8ADoHfPI6mc7n+UcaAC2WeUBIsc/eknW+e+O5QO+VlhhheAzn1IKoFq+dsDF51naMcuPyVZ2Lysqk0VUvXYDPvjBD+SjLp3HDVixXK600srZ/x2wU4Z6VlxxpVioseCW/qiP1ZM110uEQJ8j/ZyMQ1HRH6flAG+90a+UVa+DTwHjCmAL+Li0YJVVVgm+5l4K9RKo02CkpXiuv/762eJd0pbrQo2SiEeUJe3OO+8cjl0FyCkGAtDND91JSF4+xWuAMrDtN2v5QQd9NHZq8uIXrj0rr7xKPtkmpRRjnjcmSvmlXkoBnseL2vDyl7887zBQls0bc0471Odlb3zpxBruQI6A9VwZ+HjppZcpxea5QqlQH/7mMqTtfmsvmphDH/7wh2OTTTbpSpOewuqPSoEBoEAF9ANAxFpEpUClwFylwJAtfNSoUfnDNfxmWfq6NRSQALCBBKd0dEsjDthwZKTTa5ymAYwD1gCT4yH54d5www35vGwgIqUUjhZ0zJ6yHTvpCjQD5Sml/EKtfKyGQIkj+7gseIGvADTgzDF8p3/1dM3ICgpgdv311wf/ZufbAzLADTcb5+I7MvOnP/1JsNRqNysm9wtuFyuttFIuxx/1absdA243gA3XBOeIA0/cEz75yU8GsJRSy3VBvhqGBgWMq9OIKJOjR4/uaRTeYUW/4IILspWdgsY1xjjjh56EbT8olXjk9NPPCMB+idGjw44PUP3DH/4w8AmFFJA2r4B+/G9uOQGHa5k69txzr6yYKpryihff8IY3Zvczc4GrDJcwz1NKwQcez+PFlFJQQrwLYi4B7/ifUup0GwqmeeTkJv02j/TVEbTOmbdD4F7ZgLsdJvVx06GscyHSF3Pk0kt/lk+o8vEtMkCeGioF5iYFKqCfm9StZVcKVAos8BQAvIGPlHoHpCVNAQO9EaWkS+npsgAkgJfPPMt6Zxnufa1z7bXXzn7F7kv5KaXGYr5Qj3XQM2117UyjnhLnN+sjEKZN4lNKQSkoPvQjR44SnUNKrXqUndLTbVePONecsPnjHugHrFhY2581j+v/IUYBvCB0a5axxJsALd7slqbEpZTy8ZHKSulpHsFTTnIaO3Zsfl7SlyvgDHQD1+pL6em8eEecq/TKXmihhbL13L3gWXsaccA3ZQXQTqlVnnR20rizUZgL30vvmTLa48R3q0/Z5sjYsavmE29SapUvfQ2VAnOTAhXQz03q1rIrBSoFKgUqBSoFKgUqBSoFs7CaOgAAEABJREFUKgXmMgUqoJ8NAtcslQKVApUClQKVApUClQKVApUCQ4UCFdAPlZGo7agUqBRYEClQ+1QpUClQKVApUCkw1ylQAf1cJ3GtoFKgUqBSoFKgUqBSoFJgZhSozysFZp8CFdDPPu1qzkqBSoFKgUqBSoFKgUqBSoFKgXlOgQro5/kQDG4Dam2VApUClQKVApUClQKVApUCCxYFKqBfsMaz9qZSoFKgUmCgKFDLqRSoFKgUqBSYTyhQAf18MlC1mZUClQKVApUClQKVApUCQ5MCtVXzmgIV0M/rEaj1VwpUClQKVApUClQKVApUClQKzAEFKqCfA+LVrINLgVpbpUClQKVApUClQKVApUClwDMpUAH9M2lSYyoFKgUqBSoF5m8K1NZXClQKVAo8qyhQAf2zarhrZysFKgVmhwL//e9/4957742//OUv8dhjj/VZxBNPPBF//etf44EHHugz3bx6OG3atHj44Yfjz3/+c+jXvGpHrXfoUeB///tf3H///X3yeEnjOvR6EDF16tR48MEH81w1F4diG2ubhhoFFoz2VEC/YIxj7UWlQKXAXKAAcHDzzTfHscceG+973/viwx/+cJx66qnxhz/8IQDjblUC88cff3ycf/758dRTT3VLMk/j9Om6666Lgw8+OK655pp+tUVf9fl73/tePPLII/3KUxPNXxQwrueee2585jOficmTJ3dtPD645ZZb4pOf/GTceOONXdPM60iKxre+9a046qij4m9/+2u/mkNJv+yyy+KKK67oV/qaqFJgKFKgAvqhOCq1TQscBWqH5k8K3Hffn+Oggw6KL3zhC/Hkk09my9+nPvWpDBZYMrv1asqUKfHzy36ewTLw3C3NvIzTJkoHMG/HoT9tYekEkA455JBq1e8PwebDNMDs4YcfHj/60Y/i73//e9ceAPT33HNPUOz++Mc/dk0zryPN07vuujNuuOFXAdz3pz133XVXfPCDH4zzzjuvP8lrmkqBIUmBCuiH5LDURlUKVArMawoAvpdccklMmjQp3vGOd8RXvvKV+NKXvhRvfdtb4zvf+U785je/6d7E1Gz7PzU1hg0bFimlDCq4uDz++OM5PVDkN6ugOnLk9D8s+o8++mgA0J4DJ9LKL74zvWziWFe5z7i6Fy/4Lb9y5FeO+M03f12ce+45sdVWW2UXBWnULR0QJJ02SKu9nl177bXxn//8J/fJvWeCdNILyhFXgvL0QztK/Z1tlFY69ZY+tJfv+bMsDGp3je/tt90WwDwg7z6lhol7aUVKKYYNHxbDhw8P423cjV0ZM2NtzPGFsqLtn/Tlmd/yFL5w35le1sIb6pG3PY388qlLG/DWoosuGvvtt3/eSVt55VXyLpk02uWqHGnlVb54/eZSV/okzjN1qbPk0RbxJTz+2ON5ripL3dJJL19J43ept9vzkq5eKwXmlALD5rSAmr9SoFKgUmBBpICFeIUVVowDDzwwdtttt3je854XK6ywQrzyFa/MoPZf//pX126nSOE/0AD4f/SjH40DDjggKwR33313dln5wQ9+ECeeeGKwDMb0f0AE0HzSSSfF5ZdfHqeddlq2hFIiPvCBD8TEiRPjxz/+cfz73/+eniMywP7Zz36Wwdj+++8fhx12WFx66aU9af72t7/F17/+9ez+w8L+oQ99KLgW3H33PXHllVdlX39pvva1r4U2feMb3whpDjzwg/HVr341+1MD8eecc07885//DH0+5phjghuS9nLDkY51873vfW9o++23355Bjkb+4he/yP2gFB199Gfi3e9+d24ra3ABPvydL7jgglzvfvvtFx//+Mezlbi9n8qqYe5Q4B//+Eec0uxAGYeNN9448H2fNWX2TnHfffdl0Iy37dwYQ2MGHJ955plx9tlnZ/4sZQHuLOD45ac//Wnmi4svvjiOPvroeP/735/nAyUZOC951IH3DmzmIN457vjjgssPgCyN9BRtafAtV6Df/va3gQd/+cvrGmX64bj11lvi9NNPD/PEThs+1V5zCW8D8t/97nfzeyVXXXVVVtrtXKnjV7/6VW7fe97znvjIRz4S5of5gkaef+3rX4vzzj039OPggz8W0pnXtzUKkvkhmCPmsHo9//znP9/sHtzQM0f0o4ZKgdmnwNM5K6B/mhb1V6VApUClQA8FWOte97rX5a34NdZYI+688868cF944YUxduzYWH311XvSdv4YPmx4BuVANHDx61//OvsdAy8PPfRQ3H/f/XHCCSfEd7/33Z6swBAwAByo6+STTw7KwJkNOJKHiwzgzDefsiDjWWedlYHwlVdemcEThQDwoEgAHMAVMMNfnn/01VdfHb/73e+y/zNg8etf35jdK4B+7wdwJ9JeQObII4+Mz372sxnEAziAFgsl/2pAyEu1gNHxxx8f3DC8BPzlL385++bfeuut2fJ/xZVXhDKV/dOf/iwrENr2sY99LNShTEDwiCOOaIDXrVkRAbwAOOAJcNLPGuYOBdD/hz/8YVYCKYSbbrrpTCsaloZlqzdwjKcmT56clUGA2ljiEXx45CePjDvuuKOnvJtuuinwHN/766+/Pv/GFxRMiiJQDth7vwMQpmjYNfj0pz+dFd8pU6YEhcCc+HUzn/AGxZLPPyXw5z//eVAU8KI5ZC5RQn/3u9/Hcccdl9+BoWQA8JTXAxolW3qKhrrUaQ5Obvpjp0i79tlnn/j2t7+dXe1+18ybQw89NM9bvK6fZ59zdhzWKKAUid/85ub405/+lJ/rJ+DPIm9+eO+Gm5t6zFn9Roce4tQflQIDQIEK6AeAiLWISoEFmQLP5r495znPiSWXXDKfWANk7r777tnSt+2228Y666zTK2mADQv++PHjs6XSor7iiitmhYBVftwG4yKlFJMum5TLVhCfZP7LL37xi2PVVVcNAAZwBn5Z+ARtObMB+IDS73//+2At10blA+7C6NGjs0Xy7mY3YKGFFmqslP+LESNGZMv4KaecEttss02IV7Y2aisAw0LrfQGA44QTTgzlAj5ACaD1/Oc/P5Zeeun8gvCGG26YrbPA4A477JB3H84444zQVmDNS4mAkvKBpJVXXjkoKNr+rne9K79UzELKSk8Z0QY7Eso4qdm5oECxtIpHmxrmDgUob8DmuHHjAq/2txbjMnLkyPwuCVAPZFMyv/nNb8bCCy8c//d//xd//9vfg8WbYik9wM3ivskmm8Tiiy+eQTK+oNjibWWwbOM/wJefPqVus802y/yMNyYePjErfurEv8oF2l/0ohcFvqGAqhvfPfroI1mp5A5DIV5ppZXyfJHXjheADdAvv/zysffee+c2vf71r8+7XOYHRYJCDMSrW1u23HLLvONFYUkpxaOPPJqVUPnsckn3qle9KssISrk2qgN9v/jFL+Z+fOTDH87tAv77S++arlKgPxSogL4/VKppKgUqBZ7VFBg+fHhYqN/85jcHADBp0qQAXAGKTsJMi2l5wX7JS16Sfe+XW265ePnLX5791f/9n//EAw8+mK37mzbWUO4DwAFgC8wDQ69+9avjuc99bvZRfs1rNo43velNWalYa621gkLB8gf4AMQs54C2/BQFwOUFL3hBdjlgxQS6tPFlL3tZUEKUDUR1ttn9uHEb5PZyK1p//fVj/SYARlOmTMkKQUpJsvwbyEeDYcOGxZprrpmPCORasGqjiABrLKfaNHzY8KwEvH2Xt8e6664bY8aMic033zzQBBCTf9SoURncUUaUuVID/k884YS8M+J5rrT+GXAKsDKzJFO8uLMstdRSuY6UUna7wTc5ouPP1GlTIxpW2GmnnfJYLrvssvH6Buga+zvvuisfefnKV74y8BmAj0cBeRbvVVZZJV760peGcRXGj397mCcUVXwOvOMdvMzKPmz4sFjl+avE3//x92ylp2Qqw05T4R/KqrybNsCfsmDutNreNDKi6UtESil23HHHeO1rXxvau8EGG8ToRvFVhv4D8PIMGzYsllhiiXxErV0mSgBexdv6QFkA8rn6UFSiqcK8fPvb3577q8929fjTU5KVp83m+bnnnpN3x974xjfFV5qdLPMg6r9KgQGkwLABLKsWVSlQKVApsEBSgP88CyJLOEs96xqLG1eB3joMvAINngPqrNtAwxOPP54B+lu23z6fGHPDDTfkM+FZtYFjfsy2/+VZe+0XZmCvDIHlGlgAKgAMLhO27rm+aJetfAoCkCxdSg3iaDIuvfRSjVV+ePPrmf+1SVhhhTE9D90vtthiDRhqKSc9D6b/oFQAQkA7y7q6uQOxZqoXQPJs+PDhscgii8Qyyy7T0w/PBMqCdu6yyy4xrrEQ678ydt999/jCqadmn/3p1dXLAFMA7bmSXHTRRbH22mtnWgPcgDRljTLIxaRrtdMiA/KxY8dm/pAGCPYyqrxPTZ2ad68owHYAKJ/cqwD1N77xjWGnCm8AuiuvvIrsOQDilFEKJAt94W+W8Q8c8IH8LgvXLIpISimfOiWjupdcaslIKbl9RpjWKCCjRo1sgPriUf7hP/Whg7lW4l3F4W/Xu5tdrokTJ2bl8oADDggWeApv4f0UKVv2lSVvSinwtDLtDFBUKEuUjuOOOz68I7L3PnvHJT/4QVZ85KmhUmCgKDD/AfqB6nktp1KgUqBSoA8KWJD583qB09a5pKNHjw5WQO42ngEe4rsFgFwoz6ZNm9Ys/xEppQyIXtpYzbnXcEvg2uIYTGWPaazY0fwDClgBWfma2/wfYAJGgGRgGVCw3c/XtwS+zFxnuMUATvKPGDGyyZ+a0Nv/adlVov1pSt3Tp5Qa5WChDOYAlne+852x77775gCw8OEfP358UAjQUP3a3F52+Z1SCoCSn70XaoF7afk6c4sA3kraeh04CnCP4RJibIB3ihi+seuD5tyjjEFvNaZIYfcnpZSTTMt/o4mN/A9/vvENb8hp8LaXo43rps2u1IgRI/IOFv4GmnOG5o/f+NtzZTdRsewyy8b4t4/PQBh/A8eUVleWdvxljo1YeITkvYbhwxeK4U0oCVJKkVIqtz3XlFpx5lZKKbsOqQt/c8vxLQpzy5xTrzktLTqWQlJqleFevLT8+fn6U9bN88997nPZTY1CLl0NlQIDQYFhA1FILaNSoFKgUmAoUmBO2gRMe5mO/7gtdou38oAhlnlgtgAP8bMabOfzZ2e95G7CwsmNIaUWIFC/evmgl7J/dumlIR03G0AYqACcuRzIu/322weAwTIKMJV8KbXKLPeze00p5fK5HXHRAMIoJdwZ1M/dAFD04mFKKbhnoJsQHf8APLT0Iu33v//9rCgBlu65Zei7FxQ7stXbAaAAvuWCxeJNcfJeA8BspwQ/4cuZuYR0G9PctEZxdX3d5ptndywnyHCf4e7F9cszPAq8ew+klAPoUm5ZwM0NfvHmgJfPC3+9oVESvPTqhWz5Ukpdgbk6ZgxF5ZgxtvMupZayahfB3GpuA0/jbUFbzFdtx7/T4oJNM1kAAAu5SURBVJnlapdygXkWfuBde/WBixNgzy3NzhpLv7Q1VAoMBAUqoB8IKtYyKgUqBRY4CgA9gA1Q6eVTp9s4EpLbDXcECzT/2md0fPoaXxb28tx9CeIs+HyNKQbA63rrrZf9iT1LqQVUnGyjbu4QXmj1wiA/XmBniy22iBe+8IXBVeXMM8/MH7Lywh+QBtCzkrJgttepbEFcubb/FlcChcAzIaWUX5K1U8Fyy4rLms695qijPhVcN7SR64+XAwEV/Zv61NRS3DOuyhfQkuLk+MFf/vKXwZoL3FEa+Es/I2ONmGMK4G3W4mJ9trPCCl34cbvttstAtltFQCyeENqfd94DrXjUex3cZ1jn8bo8eMOVC4tgXjkphjIoz2qrrZZ93il85psXZPGFF1WBYoB6RJulv71uv1uhxXt+T53atHq6oqHeVtzUmDq1lQY4X2ihhcJuhW9PsP4D8ldeeVU+neryX1we3/7Ot7Pbjx27kl5+ZSmzPYgTKCQ/+clP8tGXTncC4s1p/vXeOeB21J6v/q4UmBMKVEA/J9SreSsFKgUWWAoAHSyCLPSABh96bgmsiMDPrrvumv1lOwlgsQcIAJqUUs9jAJvlb8RI7i+taC/UveIVr8g+9TvvvHMrsvkLDLAQPu95y2WwrN5jjz02XrPxxvk8bFZMZQHvLPXAPkvrJz7xiWDd1GZgWDnchACHlJ5uCz/fFVdcIbe/1d7lsotMU3X+n1LK96zw2iHNW9/61tzOY475fD7LnsXSqTZ//vO9wbLO/92Rk4C+D3GpQ72UHmXkgps/ykIfOw2e77nHHvmFYy43+uCoTz7JfJela7LU/4NEASAZzY1Rb1WOHDEylllmmfxuREmTUsq+5M8bMybv4JR4L5HbTbKLw6e+xAPCCy28ULauG3fvYADKFAv8gy8oAEcd9cl8PrzjK/GGI1vf9ra3xR4Nz+AR7cXfFJRStnkrP+XBTgA+9Ls9jf7JZ45K72VWL+R6+ZX7FyUE/9nxsnuEt7na2C3jS7/RRhtll7PRS4wOc0Q9pX71FJ6nmGg3/lee35RvipM5ou6Sr14HlgJeeLYz0hm8f2RncWBrGxqlVUA/mONQ66oUqBSYryjghTt+s9xAgGegniWZHy8LcrfOAAfSsn62L/ReCHR29ysbAF/yWfwt6hZ+LgklHhD3mxXVsYIs3472Y51cf/31sw++56yIgD6f5wMO+EAA9vx1gSGghRXQ2fc+jKUuecR7fuqpp8Vmm70uH5HJOrrnnnt5nAMQRGkBtigd+qEMrkHq4OvPNQNt0MOZ9c66P/2rp2eFY8UVV8zl2MVwlKAdhZRaCgWAJz03D+W+ulFSjjnmmHykH7r6rQ7HYeZC6p9BowCa4zFKYrdK8Sowa3za+ZWy6iz44487LpZdbrmerHhOHi5UY8eO7YkH6Ic1/LD//vvl8+gBdnwE8I5plAIJAfa99npXePkcyDb38J+5ha+lwf94lFKsHnHycR866aSTY8UVV4rXvOY1+chU7fZcwIPmDX4D7CnI5oDyP/nJI2P11VcLfG9HwLw7+GMHxzGfPybIgaJw6Jt2KQOoV642qE+buReZRxR/c9hOA8VceeaEnTZ5apg7FMAnu+++ez4ZrP161FFHhSNL506t87bU2Qb0tB/bo46PKsHZyPO2O7X2SoFKgUqBgaUA6x7AwDIoADJLL710ti52qwmg8EKqF2dTaoFY6VjMAeHnPe95+Wx4R9lxJXAqjfOtWUalK8GVpVFZxQUC8E/p6TIBYiffyL/LLjvnIy657gAS8gPdjsx0eo604lJKAcBoi2tJ0w7ipOXOw6pKqZEPHeTZeus3ZCUgpZTdcEr7gPdNN9s07xAANvKsvvrqwRoJNLkXSn3Kd896qV+bbrpp7LLLLkHxYdGleHhew+BRAFDuHK/O2lmfKZoFeHuOXwBYc2ORUaPCy+I33XRTOAGJWxa+AfqlLYHSqozNNtss8DdeY/kvz13xsXK5vtkRAuCBcfV5jn+1V5tSas0L/IS3xJs/FG9lSyOPYI6a0/iMlV95eNALrJtuulljdV9asnxELb4077WRUlB4WR68D5gD9zKklHIeoL70xU6UOek9l52bXTj91YcyR+SrYeApYHy4ZnUGLyKn1OKVga913pY424DeB0UIXsxeAgvNvO1Orb1SoFKgUmDuUMACIQxE6bffdlu8Yeutg5UaUGYZbQc8wI56nnpqat7a78/ir20pzZuFSvvUr81zEpSR0rzpw5y0u+adkQLOnwfiWaqd/U4BaFfQWOgjUkybOi1SSjlEH/9SSjO48sQg/8PfwpxUm1Kam32I+m9GCtgRKcbm9qtd0rKDOGOO+f9utgE9rdRWExBfgo8rzP8kqT2oFKgUqBSYuxQYs/zy8a69984v2XGJYcErNaaUgrXQFyW33267CgIKYep1vqEAqzqXLa5i3rNgiS+NZ0EH9r13sc6665boeq0UqBSYQwrMNqD31T8+bXzfSnjLW94yh82p2YcsBWrDKgUqBQaMAtwAvGRHdrJgAjnthXPPef8BB8SWr399j798+/P6u1JgKFOAmxfexuM+FtXeVpZ67i5ehOUK1v6s/q4UqBSYfQrMNqCf/SprzkqBSoFKgUoBvrvF93ZBo0btz7ObAimlfArOnLqpPLupWHtfKTBrFOgXoJ8yZUp4Afbyyy+PGioNKg9UHqg8UHmg8kDlgcoDlQcGgAcqruwFWztGdVYgfb8AvY8tOHppq622is6w9dZbh7OaZxak68zb7V66Upbf3dKI86w/6aSdWZgbZXlhuLSvs/5Sn6tnrtK6up9ZkG5W0s+sPM/nRpnKHYjQW9vED0T5c6MMbTNG/S27pHftb56abqtnyKO5SRPjKQxUHcZaea4DVeZAlqNtwpyW2Z/+tafxW72uc1r3zPL3Vo+6PRP8nlk5Q+V5e1v9np32l3xlDetP30oeactvV/cLUtCnQlPXmQXpS//9Lun97oxvjyvPul2l61ZOt7SzE6f8ks9vdbmWuHodvHXHC7wDDugdZ+Y8VkdQdQYVnnDCCeGN4r6Cc2s783a7d56ycpSp7G5pxPU3nbQzC6Us9fo9s/R9PddP5ThL2Tm3zoTuTC+N/rl6pk73ffVXuhJOOeULmd4lf4mfk6uytMF1TsqZG3nRRdvQqZTvXF/x5b7P62mn5ePTBjONs5G1WTv7Uy+6S+/an/Q1zeCMafv4mcvGaKBob6zJCteBKnMgy9FXfZ7TMvszT9vT+K3u9vk+p23oLb/+dauntMH4eN7OB72VNRTitbu0w+/ZoSN+PO6448IaJn8pr69ru7xTb2907auM+eFZoQ2eQBv80VeQvvRLHmnRBo0649vjyrNuV+UYH/jC725p5iSuvR3ar83tcXNSdntec0poj6u/Z1zXHNU64IDeC1yOVfNls87gRVhnxT744IPxr3/96xmBu47PHDsVZ/z48dGZv/PeaQ/Se0nM2bOdz93rpBdtnIXvqDdfoxM/O8HJPM6L/t///hePPfZY+D075ZQ8zqVV1o033hC33npr/nqer82V567OxE0phbR2Pl7ykpfkurfddtuZ0kf+171u03j00UdCPvcDEYyPz1Q7u3cgyhvIMlgH+Bs7u7eUi++Ecj+Urr6o6Xzkvni4vb14AP2djzsU6d/e1mfTb+OC9/SZnODvnlIK562Lm9Ng/pOP48aN69e8n9P6ZiW/PjpaEA/3R273Vra85DiZPbM00krjGGQvTs6pLFZWX8H4OjLUWfnt6fx23rk2WNOsNb2tf9IOpcCa6qxzbXLe+VNPPRVePC1x4vsKaOKF1vvuuy98ERkPzEzO+nYA2ey8eWsdy765QgYqr6/65rdnzq331Wh9c7SsL8rikc5gXj/wwAPh5V99xD9edJfe2fhbbLFFoA2e9x2Jv/zlL9nTQdq+AjnkBCzfsLj55t+Eb1r0lX5Wn2mT8/bLfN1ggw3yl3q9uD+rZc0svXrwy8zSPZufo/+sAPr/BwAA///pnaRJAAAABklEQVQDAC2/tz832rDiAAAAAElFTkSuQmCC\"\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003e\u003cem\u003eClinical results preinjury, preoperatively and at the 12-month follow-up (T2) for the two groups (Ligabrace (LGB) and ACL reconstruction (ACLR). The significance level p was determined as a standard deviation (p-value) of 0.05. (LGB, Ligabrace; ACLR, anterior cruciate ligament reconstruction; IKDC, International Knee Documentation Committee; Rolimeter, manual maximum displacement test; mm, millimeter; mv, mean value; SD, standard deviation)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient-reported outcomes\u003c/strong\u003e: Preinjury activity levels (T0) did not differ significantly between groups (Tegner: LGB 6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 vs ACLR 6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6, p\u0026thinsp;=\u0026thinsp;0.810). At 12-month follow-up (T2), both groups achieved high functional scores. The mean IKDC subjective score was 87.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.3 (range, 62\u0026ndash;100) in the LGB group and 84.2\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4 (range, 48\u0026ndash;99) in the ACLR group (p\u0026thinsp;=\u0026thinsp;0.420). Lysholm scores were 90.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9 (range, 71\u0026ndash;100) and 87.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1 (range, 43\u0026ndash;99), respectively (p\u0026thinsp;=\u0026thinsp;0.446). Tegner activity levels were maintained, with a mean of 6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7 in the LGB group and 5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7 in the ACLR group (p\u0026thinsp;=\u0026thinsp;0.532). Differences between preinjury and postoperative scores indicated successful restoration of knee function in both groups (Table\u0026nbsp;3).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTABLE 3: PROMS 12 MONTHS POSTOPERATIVELY\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cimg 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\"\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003e\u003cem\u003eIKDC and Lysholm scores at T2 (12 months postoperatively) for the two groups (LGB, Ligabrace group; ACLR, ACL reconstruction group).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective outcomes\u003c/strong\u003e: At baseline (T1), mean anterior translation measured with the Rolimeter was 5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9 mm in the LGB group and 6.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 mm in the ACLR group (p\u0026thinsp;=\u0026thinsp;0.144). At follow-up (T2), translation decreased to 0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 mm and 0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 mm, respectively (p\u0026thinsp;=\u0026thinsp;0.722). None of the patients demonstrated a side-to-side difference greater than 2 mm at T2, confirming restoration of stability. IKDC grades at T2 showed excellent outcomes: in the LGB group, 24 patients were graded A and one patient B; in the ACLR group, 21 patients were graded A and four B (p\u0026thinsp;=\u0026thinsp;0.349).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMRI findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMRI follow-up confirmed graft integrity in all patients. Signal intensity distribution was comparable between groups. In the LGB group, 44% of ligaments were hypointense, 44% isointense, and 12% hyperintense. In the ACLR group, 44% were hypointense, 40% isointense, and 16% hyperintense (p\u0026thinsp;=\u0026thinsp;1.0). These findings suggest similar ligament maturation patterns between techniques.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComplications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo failures, re-ruptures, or postoperative complications occurred. The reoperation rate was 0% in both groups.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study demonstrated that the Ligabrace technique, which combines ACL repair with suture tape augmentation and cortical button fixation, yielded comparable results to ACL reconstruction with hamstring autografts in terms of patient-reported outcomes, clinical stability, and radiological findings at 12 months. Importantly, no failures, reoperations, or complications occurred during the observation period, and subjective outcome measures were comparable between the two groups and consistent with previous reports.\u003c/p\u003e \u003cp\u003eAlthough ACL reconstruction with autologous tendon grafts is widely considered the gold standard, limitations in clinical outcomes remain [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Despite technical and biomechanical advances, patients may experience deficits such as impaired proprioception and donor-site morbidity. These deficits can contribute to persistent alterations in movement patterns and gait mechanics [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In recent years, suture tape augmentation has shown promising results. Heusdens et al. reported an 11.4% failure rate at the two-year follow-up, while Jonkergouw et al. observed a similar rate of 10.7%. Both studies focused on proximal avulsion tears treated with internal bracing and femoral fixation using a suture anchor. Successful ACL repair has the potential to overcome two major disadvantages of reconstruction: loss of proprioception due to removal of the native ligament and harvest-site morbidity. In particular, the absence of afferent proprioceptive input after ACL replacement has been linked to altered neuromuscular control of the knee [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. These insights have rekindled interest in ACL repair, particularly in selected patients with proximal tears.\u003c/p\u003e \u003cp\u003eSeveral authors have emphasized the importance of tear location and tissue quality in determining suitable candidates for ACL repair [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], a concept originally introduced by Sherman et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Historically poor results were likely related to the inclusion of all tear types regardless of morphology or tissue quality, as well as the relatively high surgical morbidity [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In contrast, more recent studies limited to proximal ACL tears have demonstrated low reoperation rates and high patient satisfaction at both short- and long-term follow-up [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR11\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In our study, only patients with acute proximal ACL tears (Sherman type I or II) and excellent tissue quality confirmed by preoperative MRI and intraoperative assessment were included. The average age was similar between groups and fell within the range with the highest incidence of ACL rupture, as previously reported [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The female-to-male ratio of 3:2 also reflected the higher incidence of ACL ruptures in women [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDiscrepancies have been reported regarding the time course of graft remodeling on MRI after ACL repair. Ferretti et al. observed normalization of morphology and signal intensity at six months [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e25\u003c/span\u003e], whereas van der List et al. described a gradual sequence with hyperintensity in the first postoperative year, isointensity between one and two years, and hypointensity thereafter [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In our cohort, continuity and remodeling were observed at 12 months in both groups. Graft maturation was comparable, with 88% and 84% of repaired ligaments being hypo- or isointense, respectively. Three patients in the repair group and four in the reconstruction group showed hyperintense signals. No significant difference was found between techniques (p\u0026thinsp;=\u0026thinsp;1.0). Furthermore, no evidence of strangulation or abnormal signal patterns was detected in the tibial or femoral portions of the braced ACL, which might have occurred with the whipstitch technique.\u003c/p\u003e \u003cp\u003eRecent systematic reviews have confirmed that ACL repair and reconstruction yield similar results with respect to Lysholm score, IKDC score, side-to-side laxity, pivot-shift grade, and graft rupture rate [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Van der List et al. reported mean functional outcomes exceeding 85% of maximum scores and cumulative failure rates of 7\u0026ndash;11% across recent ACL repair studies [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These findings are in line with the results of the present study, in which both repair and reconstruction groups achieved good to excellent functional outcomes with no failures at short-term follow-up.\u003c/p\u003e \u003cp\u003eSeveral individual studies have further explored the role of internal bracing. Mackay et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e24\u003c/span\u003e] evaluated ACL repair with internal brace augmentation and reported a reoperation rate of 6% in 68 patients at one-year follow-up. Achtnich et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e16\u003c/span\u003e] compared primary repair with ACL reconstruction and observed a 15% failure rate and 20% reoperation rate in the repair group, compared with 0% in the reconstruction group, at a mean of 28 months. Douoguih et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e17\u003c/span\u003e] reported a 14.8% failure rate at a mean follow-up of 2.8 years in patients undergoing ACL repair with suture augmentation. In contrast, the present study demonstrated no failures in either group. We hypothesize that strict patient selection\u0026mdash;limiting inclusion to isolated proximal tears with excellent tissue quality\u0026mdash;together with the use of a small femoral drill hole may have contributed to favorable healing at the femoral avulsion site. This may represent an advantage over anchor-based techniques, which have shown failure rates of approximately 11% after two years [10\u0026ndash;12].\u003c/p\u003e \u003cp\u003eIn our series, all patients in both groups achieved good to excellent knee function according to the IKDC score at the final follow-up, with restored physiological stability and no significant differences between groups. These results are consistent with systematic reviews showing no major differences between ACL repair and reconstruction in terms of functional outcomes or failure rates [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, the relatively small sample size may have reduced the ability to detect differences in secondary outcomes or rare events such as graft failure. Second, selection bias may have been introduced, as ACL reconstruction was performed in proximal tears with poor tissue quality, while repair was reserved for tears with excellent tissue quality. Nevertheless, this reflects real-world clinical decision-making. All patients were examined by a single experienced clinician who was aware of group allocation. While this could introduce bias, it also ensured consistency of assessment. Although MRI was assessed by two board-certified radiologists, the possibility of inter- and intra-observer variability cannot be excluded. Finally, the follow-up of 12 months is relatively short and may not fully capture long-term complications or differences in graft durability.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eShort-term outcomes of primary ACL repair using suture tape augmentation and cortical button fixation (Ligabrace technique) were comparable to those of standard hamstring tendon ACL reconstruction. At 12 months, patient-reported scores, objective stability, and MRI findings confirmed restored knee function without complications or failures. These encouraging results highlight the potential of ligament-preserving strategies in carefully selected patients with acute proximal ACL tears. In addition to maintaining native tissue and proprioceptive function, the technique avoids intraosseous implants, which may facilitate revision surgery if required.\u003c/p\u003e \u003cp\u003eAlthough limited by its retrospective design, small cohort, and short follow-up, the consistency of the findings provides a strong rationale for further investigation. Prospective studies with larger cohorts, longer follow-up, and direct comparisons with other ligament-preserving techniques are needed to confirm whether the favorable short-term results of the Ligabrace technique can be maintained over time.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACL \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;anterior cruciate ligament\u003c/p\u003e\n\u003cp\u003eACLR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;anterior cruciate ligament reconstruction\u003c/p\u003e\n\u003cp\u003eAP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;anterior-posterior\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBMI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Body Mass Index\u003c/p\u003e\n\u003cp\u003eIKDC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;International Knee Documentation Committee\u003c/p\u003e\n\u003cp\u003eMRI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Magnetic resonance imaging\u003c/p\u003e\n\u003cp\u003eLGB \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Ligabrace\u003c/p\u003e\n\u003cp\u003ePROMs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Patient Reported Outcome Measures\u003c/p\u003e\n\u003cp\u003eSD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Standard deviation\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the ethical review board of the Medical Association of North Rhine (Ärztekammer Nordrhein). Registration Number: 2018266. Registered 28. September 2018–Retrotively registered.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all patients and volunteers involved in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e All the patients provided written informed consent to participate in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This study was funded by the Bundesinstitut für Sportwissenschaften (Studynumber 070602/24-27)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions Statement:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors fulfil the ICMJE criteria for authorship.\u003c/p\u003e\n\u003cp\u003eAll authors have read and agreed to the final version of this manuscript.\u003c/p\u003e\n\u003cp\u003eConceptualization HG, MR, DJ, JV\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethodology HG, MR, DJ, JV\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eValidation HG, MR, DJ, TP, PB, TP, JV\u003c/p\u003e\n\u003cp\u003eFormal analysis HG, MR, DJ, JV\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInvestigation HG, MR, DJ, TP, PB, JV\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWriting—original draft preparation HG, MR, DJ, JV\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWriting—review and editing all authors\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVisualisation HG, MR, DJ\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSupervision TP, PB, MH, JV\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eProject administration TP, PB, MH, JV\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGabler C, Jacobs C, Howard J, Mattacola C, Johnson D. Comparison of graft failure rate between autografts placed via an anatomic anterior cruciate ligament reconstruction technique: A systematic review, meta-analysis, and meta-regression. Am J Sports Med. 2016;44:1069\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarret D. Proprioception and function after anterior cruciate reconstruction. J Bone Joint Surg Br. 1999;73:833\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKraeutler MJ, Bravman JT, McCarty EC. Bone\u0026ndash;patellar tendon\u0026ndash;bone autograft versus allograft in outcomes of anterior cruciate ligament reconstruction: a meta-analysis of 5182 patients. Am J Sports Med. 2013;41:2439\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGriffith TB, Allen BJ, Levy BA, Stuart MJ, Dahm DL. Outcomes of repeat revision anterior cruciate ligament reconstruction. Am J Sports Med. 2013;41(6):1296\u0026ndash;301.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurray MM, Fleming BC. Use of a bioactive scaffold to stimulate anterior cruciate ligament healing also minimizes posttraumatic osteoarthritis after surgery. Am J Sports Med. 2013;41(8):1762\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCinque ME, Dornan GJ, Chahla J, Moatshe G, LaPrade RF. High Rates of Osteoarthritis Develop After Anterior Cruciate Ligament Surgery: An Analysis of 4108 Patients. Am J Sports Med. 2018;46(8):2011\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaylor SA, Khair MM, Roberts TR, DiFelice GS. Primary repair of the anterior cruciate ligament: A systematic review. Arthroscopy. 2015;31:2233\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan der List JP, DiFelice GS. Primary repair of the anterior cruciate ligament: A paradigm shift. Surgeon. 2017;15(3):161\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan der List JP, DiFelice GS, Jonkergouw A, van der List JP, DiFelice GS. Role of tear location on outcomes of open primary repair of the anterior cruciate ligament: A systematic review of historical studies. \u003cem\u003eKnee.\u003c/em\u003e 2017;24(5):898\u0026ndash;908. Heusdens CHW, Blockhuys K, Roelant E, Dossche L, Van Glabbeek F, Van Dyck P. Suture tape augmentation ACL repair, stable knee, and favorable PROMs, but a re- rupture rate of 11% within 2 years. \u003cem\u003eKnee Surg Sports Traumatol Arthrosc\u003c/em\u003e. 2021;29(11):3706\u0026ndash;3714 Jonkergouw A, van der List JP, DiFelice GS Arthroscopic primary repair of proximal anterior cruciate ligament tears: outcomes of the first 56 consecutive patients and the role of additional internal bracing. \u003cem\u003eKnee Surg Sports Traumatol Arthrosc\u003c/em\u003e. 2019;27(1):21\u0026ndash;28. van Eck CF, Limpisvasti O, ElAttrache NS. Is There a Role for Internal Bracing and Repair of the Anterior Cruciate Ligament? A Systematic Literature Review. \u003cem\u003eAm J Sports Med.\u003c/em\u003e 2018;46(9):2291\u0026ndash;2298.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNguyen D, Ramwadhdoebe T, van der Hart C, Blankevoort L, Tak P, van Dijk C. Intrinsic healing response of the human anterior cruciate ligament: an histological study of reattached ACL remnants. J Orthop Res 2014;32:296\u0026ndash;301.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan der List JP, DiFelice GS. Preoperative magnetic resonance imaging predicts eligibility for arthroscopic primary anterior cruciate ligament repair. Knee Surg Sports Traumatol Arthrosc. 2018;26(2):660\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDiFelice GS, Villegas C, Taylor S. Anterior Cruciate Ligament Preservation: Early Results of a Novel Arthroscopic Technique for Suture Anchor Primary Anterior Cruciate Ligament Repair. Arthroscopy. 2015;31(11):2162\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAchtnich A, Herbst E, Forkel P, Metzlaff S, Sprenker F, Imhoff AB, Petersen W. Acute Proximal Anterior Cruciate Ligament Tears: Outcomes After Arthroscopic Suture Anchor Repair Versus Anatomic Single-Bundle Reconstruction. Arthroscopy. 2016;32(12):2562\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDouoguih WA, Zade RT, Bodendorfer BM, Siddiqui Y, Linciln AE. Anterior Cruciate Ligament Repair with Suture Augmentation for Proximal Avulsion Injuries. Arthrosc Sports Med Rehabil. 2020;2(5):e475\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSolomonow M, Baratta R, Zhou BH, Shoji H, Bose W, Beck C, D\u0026rsquo;Ambrosia R. The synergistic action of the anterior cruciate ligament and thigh muscles in maintaining joint stability. Am J Sports Med. 1987;15:207\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan der List JP, Vermeijden HD, Sierevelt IN, DiFelice GS, van Noort A, Kerkhoffs GM. Arthroscopic primary repair of proximal anterior cruciate ligament tears seems safe but higher level of evidence is needed: a systematic review and meta-analysis of recent literature. Knee Surg Sports Traumatol Arthrosc. 2020;28:1946\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGranan LP, Bahr R, Steindal K, Furnes O, Engebretsen L. Development of a national cruciate ligament surgery registry: the Norwegian National Knee Ligament Registry. Am J Sports Med. 2008;36(2):308\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeske W, Anastisiadis A, Lichtinger T, von Schulze Pellengahr C, von Engelhardt L, Theodoridis T. Ruptur des vorderen Kreuzbands. Orthop\u0026auml;de. 2010;39:883\u0026ndash;900.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohansson H, Sj\u0026ouml;lander P, Sojka P. Activity in receptor afferents from the anterior cruciate ligament evokes reflex effects on fusimotor neurones. Neurosci Res. 1990;8:54\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSherman MF, Lieber L, Bonamo JR, Podesta L, Reiter I. The long-term followup of primary anterior cruciate ligament repair. Defining a rationale for augmentation. Am J Sports Med. 1991;19(3):243\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMackay G, Anthony IC. Preliminary results of primary repair with internal brace ligament augmentation: a case series. Orthop Muscul Syst. 2015;4:1\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerretti A, Monaco E, Annibaldi A, Carrozzo A, Bruschi M, Argento G, DiFelice GS. The healing potential of an acutely repaired ACL: a sequential MRI study. J Orthop Traumatol. 2020;21:14.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"acute proximal ACL tears, ACL repair, ACL reconstruction, Ligabrace technique, suture tape augmentation","lastPublishedDoi":"10.21203/rs.3.rs-8743118/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8743118/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThe treatment of choice for anterior cruciate ligament (ACL) ruptures remains the use of tendon grafts. However, the concept of preserving the ACL instead of replacing it has gained popularity for the treatment of acute femoral avulsion tears. This study aimed to evaluate the effectiveness of ligament-preserving repair technique, for clarity hereafter referred to as the Ligabrace technique, involving suture tape augmentation and cortical button fixation.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe study included 50 patients with isolated acute proximal ACL rupture (Sherman I / II) who did not have any other injuries or medical conditions. The patients were divided into two groups: group 1 (n\u0026thinsp;=\u0026thinsp;25) underwent surgical treatment with the Ligabrace technique, while group 2 (n\u0026thinsp;=\u0026thinsp;25) received standard ACL reconstruction with hamstring tendons. Preoperative assessments of Tegner, Lysholm, and International Knee Documentation Committee (IKDC) scores were conducted at T0, and 12 months postoperatively at T2. Additionally, standardized Magnetic resonance imaging (MRI) and routine clinical examinations of the knee, including instrumented anterior-posterior (AP) stability measurements, were carried out at T1 and T2.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eNo significant differences in any of the evaluation criteria were observed in either group at T2. The Lysholm (90,32 (71\u0026ndash;100)) and IKDC (87,1 (62,1-100)) scores were comparable for the Ligabrace group and the scores for the hamstring group. The Tegner activity levels were 6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7 in the Ligabrace group and 5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7 in the hamstring group. The mean AP translation compared to the noninjured knee was 0.56 mm in the Ligabrace group and 0.72 mm in the hamstring group.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOverall, primary ACL repair with this technique showed similar outcomes to ACL reconstruction with hamstring tendons in terms of patient-reported outcome scores and clinical investigation in patients with proximal ACL tears in short-term. The initial results for the Ligabrace technique suggest that it may be a viable option for ligament preservation after acute femoral ACL tears.\u003c/p\u003e","manuscriptTitle":"Anatomic ACL repair with suture tape augmentation and cortical button fixation for acute proximal anterior cruciate ligament tears: results in short-term outcomes similar to those of ACL reconstruction with hamstring autograft","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-23 08:56:09","doi":"10.21203/rs.3.rs-8743118/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b273f508-9358-465f-aa82-6b7f9533db71","owner":[],"postedDate":"February 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-02T16:09:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-23 08:56:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8743118","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8743118","identity":"rs-8743118","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}