Simultaneous Consumption of Vegetable Salad with Bread Attenuates Postprandial Serum Glucose Elevation in Healthy Adults: A Single-ingestion Open-label Trial

Simultaneous Consumption of Vegetable Salad with Bread Attenuates Postprandial Serum Glucose Elevation in Healthy Adults: A Single-ingestion Open-label Trial | 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 Short Report Simultaneous Consumption of Vegetable Salad with Bread Attenuates Postprandial Serum Glucose Elevation in Healthy Adults: A Single-ingestion Open-label Trial Mengwei Yuan, Naoki Kawada, Yumi Takeda, Ryosuke Matsuoka, Kazunori Utsunomiya This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8220213/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Objective This study aimed to evaluate the effect of simultaneous consumption of vegetables and bread on postprandial serum glucose concentration. In total, 15 healthy men were given meals (bread vs. bread with vegetable salad) after a night of fasting. At 0, 15, 30, 45, 60, 90, and 120 min following the consumption of the test meal, blood samples were collected to determine the serum levels of glucose, insulin, glucose-dependent insulinotropic polypeptide, and triglycerides. Results Results revealed that serum glucose and insulin levels were significantly lower after 45 and 60 min in participants who consumed bread with vegetable salad than in those who only consumed bread. This emphasizes the potential benefit of simultaneously consuming vegetables and bread as an effective dietary strategy for preventing postprandial blood glucose elevation. Trial registration: UMIN Clinical Trials Registry (UMIN-CTR), UMIN000053931, registered on March 22, 2024. Vegetable salad Bread Postprandial serum glucose Crossover study Figures Figure 1 Introduction In recent years, the prevalence of diabetes has been steadily increasing, emphasizing the importance of developing effective preventive strategies. Among the various contributing factors of diabetes, carbohydrate intake is considered a major cause of postprandial blood glucose elevation. In individuals with impaired glucose tolerance, postprandial hyperglycemia and insulin resistance may increase the risk of chronic diseases, including cardiovascular disorders [ 1 – 6 ]. The consumption of vegetable salads has been associated with a reduced risk of developing diabetes [ 7 , 8 ]. This beneficial effect has been attributed to the physiological actions of bioactive components, such as vitamins, minerals, dietary fiber, and polyphenols, which are all commonly found in vegetables [ 9 ]. The “salad-first” dietary approach, consuming salads before other dishes, reportedly suppresses rapid increases in postprandial blood glucose levels [ 10 ]. Numerous studies have investigated the regulatory effect of altering the order of food intake on glycemic responses [ 11 – 14 ]. However, many commonly consumed food items, such as sandwiches, pita wraps, and burritos, cannot be easily separated into different components. Therefore, the effect of consuming vegetable salads with carbohydrates in a single meal remains poorly evaluated. Thus, this study aimed to investigate the effects of the simultaneous consumption of a vegetable salad and bread on serum glucose concentrations. Materials and Methods Study design This study used a single-ingestion open design involving 15 healthy men who were at a low risk of developing anemia caused by blood sampling. These participants were randomized into two groups and underwent a 7-day washout period. Each of them visited the clinic twice and ingested either of the two types of meals: bread alone (B group) and bread with vegetable salad (BVS group). The test meals were consumed within 10 min, with each mouthful being chewed approximately 30 times. They fasted overnight, underwent fasting blood sampling, and then ingested each test meal. At 15, 30, 45, 60, 90, and 120 min after ingestion, blood samples were collected to measure the serum levels of glucose, insulin, glucose-dependent insulinotropic polypeptide (GIP), and triglyceride. For fasting blood sampling, general tests for peripheral blood and serum analyses were performed. This study only included participants who received a thorough explanation of the study protocol and provided written informed consent. Moreover, ethical approval was obtained from the Ethical Examining Committee of Ueno Asagao Clinic (Tokyo, Japan: Authorized No. 202401-39-KP001). This study was conducted at Hakunan Clinic (Chiba, Japan) and was registered at the University Hospital Medical Information Center (UMIN ID: UMIN000053931, Registered on 2024/03/22). Test food A vegetable salad (cabbage-based salad; Salad Club, Inc., Tokyo, Japan) and mayonnaise (Kewpie Corporation, Tokyo, Japan) were purchased commercially. Bread was prepared using a home bakery appliance in the Research and Development Division of Kewpie Corporation (Zojirushi BB-HA10, Zojirushi Corporation, Osaka, Japan). Table 1. enumerates the components of each test meal, and the nutrient composition of the vegetable salad and its extract. At breakfast, the B group received 70 g of bread, equivalent to one serving in Japan. Meanwhile, the BVS group consumed bread (70 g) and vegetable salad (65 g) mixed with mayonnaise (15 g). Considering that as little as 60 g of cabbage is reportedly effective in reducing blood glucose spikes, this study used 65 g of vegetable salad, consistent with the amount that is generally used in making sandwiches in daily diet. Regarding the mayonnaise, the recommended amount per serving was used [ 15 ]. Blood tests Flow cytometry was used for conducting general peripheral blood tests. Serum samples were analyzed for the following parameters: total cholesterol (enzyme method), low-density lipoprotein cholesterol (enzyme method), high-density lipoprotein cholesterol (direct method), triglyceride (enzyme method), glucose (Hexokinase UV method), hemoglobin A1c (HbA1c; latex aggregation method), insulin (chemiluminescent enzyme immunoassay method), aspartate aminotransferase (AST), alanine aminotransferase (ALT; Japan Society of Clinical Chemistry [JSCC] transferable method), γ-glutamyl transpeptidase (γ-GTP; JSCC transferable method), urea nitrogen (urease-LED-UV method), creatinine (enzymatic method), uric acid (enzymatic method), and sodium, chlorine, and potassium (electrode method). The blood samples were analyzed by LSI Medience Inc. (Tokyo, Japan). Serum GIP levels were measured using enzyme-linked immunosorbent assay kit (Human GIP Total Assay Kit #27203, IBL Co. Ltd., Gunma, Japan). Sample size Initially, the sample size was determined from previous studies of vegetable-first effects (Imai, Fukui and Kajiyama 2014). The Cancer Research and Biostatistics Statistical Tools software ( https://stattools.crab.org/ ) was used for determining the sample size. The required sample size was 15 per group when α was 0.05 and power (1-β) was 80%. Statistical analysis All results are expressed as mean ± SEM. The two groups were compared using Wilcoxson signed rank test and Bonferroni correction, as appropriate. The same methods were used for comparing the serum levels of glucose, insulin, GIP, and triglycerides with those before the ingestion of each of the meals. A hazard ratio below 5% indicated a significant difference; all statistical data were analyzed using SPSS version 29 (SPSS Japan Inc., Tokyo). This study was conducted and reported in accordance with the CONSORT guidelines for randomized clinical trials. Results Participant demographics and hematology before test meal consumption Table 2. presents the participants’ demographic characteristics. The body mass index was slightly high. All participants were healthy, with a mean age of 54 ± 2.1 years. The results of hematology, serum biochemistry, hepatic function, and renal function showed no significant differences before and after the consumption of either of the two meal types ( p > 0.05). Changes in serum glucose and insulin levels Figure 1A, B illustrates the changes, incremental area under the curve (IAUC), and ΔC max of serum glucose and insulin levels. At 45 and 60 min after test meal consumption, the serum glucose levels were significantly lower in the BVS group than in the B group, indicating that the increase in serum glucose level was slower in the BVS group. Similarly, IAUC and ΔC max of the serum glucose levels were significantly lower in the BVS group than in the B Group.The serum insulin levels as well as the IAUC and ΔC max , in the BVS group were significantly lower than those in the B group at 45 and 60 min following test meal consumption. Changes in serum triglyceride levels As shown in Fig. 1C, the serum triglyceride levels were significantly higher in the BVS group than in the B group at 120 min after test meal consumption. Changes in serum GIP levels As shown in Fig. 1D, the serum GIP levels as well as the IAUC were significantly higher in the BVS group than in the B group at 30–120 min following meal consumption. Discussion This study demonstrated that the simultaneous consumption of vegetable salad and carbohydrate-rich foods, such as bread, attenuates the postprandial elevation of serum glucose levels (Fig. 1A). Although the “salad-first” approach—consuming vegetables before carbohydrate-rich foods—has been effective in moderating postprandial glycemic responses, reports on the effects of concurrent intake, particularly in the context of composite meals (e.g., sandwiches or burritos) where sequential consumption is impractical, remain limited. Results of the current study suggest that the simultaneous intake of vegetables and carbohydrates can be beneficial in blunting glycemic excursions, offering a more feasible dietary strategy for daily life. Cabbage, the primary component of the salad used in this study, is rich in insoluble dietary fiber, specifically cellulose. This type of fiber increases the viscosity of gastrointestinal contents and physically impedes the diffusion of nutrients and digestive enzymes, potentially slowing carbohydrate digestion and absorption [ 16 – 18 ]. Furthermore, cabbage contains rutin, a polyphenol that inhibits α-glucosidase activity and improves glucose metabolism, contributing to the suppression of carbohydrate breakdown and absorption [ 19 ]. Moreover, the salad was mixed with mayonnaise, which contains dietary fats that prolong gastric emptying time, thereby delaying the transfer of nutrients to the small intestine. The acetic acid present in mayonnaise—derived from vinegar—can also suppress postprandial glycemic elevation by delaying gastric emptying and potentially enhancing insulin sensitivity [ 20 , 21 ]. These combined effects likely contributed to the observed reduction in postprandial serum glucose levels. Interestingly, despite the elevated serum GIP levels observed in the BVS group, the serum glucose and insulin levels were lower than those in the control. GIP is secreted from K-cells in the upper small intestine in response to dietary carbohydrate and fat intake, and acts on pancreatic β-cells to promote insulin secretion [ 22 , 23 ]. However, GIP exerts its insulinotropic effects in a glucose-dependent manner; when blood glucose levels are low or only mildly elevated, GIP cannot substantially stimulate insulin secretion. Indeed, Meier et al. and Nauck et al. reported that elevated GIP concentrations do not necessarily result in enhanced insulin secretion when glycemic levels remain low [ 23 , 24 ]. The present findings align with this physiological mechanism. Therefore, enhanced GIP secretion, combined with modest postprandial glycemia, may support glucose regulation without excessive insulin demand. Thus, these findings suggest that glycemic response reduction observed in this study is likely attributable to the combined effects of dietary fiber, polyphenols, fat, and acetic acid. These components may act synergistically to slow the digestion and absorption of nutrients while modulating the secretion of incretin hormones. Notably, effective glycemic control was achieved without the need to consume vegetables prior to carbohydrates, indicating such simultaneous intake as a metabolically favorable strategy [ 25 ]. This dietary approach is practical and sustainable for busy individuals who may find strict food sequencing difficult to maintain. Consistent with these results, Fukuda et al. reported that the combination of dietary fiber, vinegar (acetic acid), and fat produced a greater glycemic-lowering effect when consumed with rice, compared with any of these components alone. This finding supports the notion that multicomponent dietary strategies can act synergistically to enhance postprandial glycemic regulation, especially in typical mixed-meal settings. To further enhance postprandial glycemic regulation under realistic dietary conditions, future research should focus on identifying the optimal combinations of vegetables, dietary fibers, polyphenols, and accompanying condiments or fats. Conclusions The postprandial increase in serum glucose level was suppressed when bread was consumed simultaneously with vegetable salad and mayonnaise. This effect is likely attributable to multiple factors, including the dietary fiber and bioactive compounds contained in the vegetables as well as the fat and acetic acid present in the mayonnaise. Limitations In this study, the individual effects of vegetable salad and mayonnaise were not evaluated separately; therefore, it was not possible to clearly identify which component contributed to the observed effects. In addition, the actual rate of digestion in the gastrointestinal tract was not directly measured, which limited the understanding of the temporal dynamics of digestion and absorption. To clarify the underlying mechanism, evaluation of the biokinetics of the target component is required, particularly the assessment of its absorbability and receptor-binding capacity in the small intestine. Abreviations BVS: Bread with vegetable salad; BMI: Body mass index; HbA1c: Hemoglobin A1c; GIP : Glucose-dependent insulinotropic polypeptide; IAUC: Incremental area under the curve; JSCC: Japan Society of Clinical Chemistry Declarations Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki, and with the approval of the Ethics Committee of Ueno Asagao Clinic (authorization no. 2024-03; 13th Mach, 2024). Written informed consent was obtained from all participants prior to their participation in the study. Participants received a thorough explanation of the study protocol and those who provided consent were included. The study was conducted at the Hakunan Clinic. Consent for publication The authors declare that they have no competing interests. Competing interests KU declare no conflict of interest. MWY, NK, YT and RM are employees of Kewpie Corporation. There are no other patents, products in development, or marketed products to declare. Funding Author Contribution MWY, NK, YT, RM, and KU approved the study concept and design. RM, as the principal investigator, was responsible for the study logistics, data acquisition, TT and RM for manuscript preparation. NK and YT were responsible for conducting the trial, data collection, and performing laboratory analysis. MWY and RM carried out the statistical analysis. KU supervised the study design and commented on the manuscript. All authors contributed to the intellectual content of the manuscript. Acknowledgement This study was supported entirely by a grant received from Kewpie Corporation, Japan. We thank DR. Hiroshi Sakai (Hakunan Clinic, Chiba, Japan) and Tatsuo Uetake (CX wellness Co. Inc., Tokyo, Japan) for Coordinate about this trial. Data Availability The data presented in this study are available on request from the corresponding author. References Grundy SM, Pasternak R, Greenland P, Smith S, Fuster V. Metabolic Syndrome and Cardiovascular Risk: A Review. Front Cardiovasc Med. 2020;7:570553. 10.3389/fcvm.2020.570553 . Qiao Q, Hu G, Tuomilehto J, Nakagami T, Balkau B, Borch-Johnsen K, et al. Age- and sex-specific prevalence of diabetes and impaired glucose regulation in 11 Asian cohorts. Diabetes Care. 2003;26:1770–80. 10.2337/diacare.26.6.1770 . DECODE Study Group, the European Diabetes Epidemiology Group. Glucose tolerance and cardiovascular mortality: comparison of fasting and 2-hour diagnostic criteria. Arch Intern Med. 2001;161:397–405. 10.1001/archinte.161.3.397 . Nakagami T, Qiao Q, Tuomilehto J, Balkau B, Tajima N, Hu G, et al. Screen-detected diabetes, hypertension and hypercholesterolemia as predictors of cardiovascular mortality in five populations of Asian origin: the DECODA study. Eur J Cardiovasc Prev Rehabil. 2006;13:555–61. 10.1097/01.hjr.0000183916.28354.69 . Levitan EB, Song Y, Ford ES, Liu S. Is nondiabetic hyperglycemia a risk factor for cardiovascular disease? A meta-analysis of prospective studies. Arch Intern Med. 2004;164:2147–55. 10.1001/archinte.164.19.2147 . Salmerón J, Ascherio A, Rimm EB, Colditz GA, Spiegelman D, Jenkins DJ, et al. Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care. 1997;20:545–50. 10.2337/diacare.20.4.545 . Ford ES, Mokdad AH. Fruit and vegetable consumption and diabetes mellitus incidence among U.S. adults. Prev Med. 2001;32:33–9. 10.1006/pmed.2000.0772 . Wang PY, Fang JC, Gao ZH, Zhang C, Xie SY. Higher intake of fruits, vegetables or their fiber reduces the risk of type 2 diabetes: a meta-analysis. J Diabetes Investig. 2016;7:56–69. 10.1111/jdi.12376 . Tang GY, Meng X, Li Y, Zhao CN, Liu Q, Li HB. Effects of vegetables on cardiovascular diseases and related mechanisms. Nutrients. 2017;9:857. 10.3390/nu9080857 . Published 2017 Aug 10. Tanaka T, Sakamoto H, Matsuoka R, Utsunomiya K. Ingestion of vegetable salads before rice inhibits the increase in postprandial serum glucose levels in healthy subjects. Biosci Biotechnol Biochem. 2023;87:1212–8. 10.1093/bbb/zbad085 . Aiba M, Kawahigashi M, Kawano T, Ebisuya Y, Fujimoto Y, Hashida S. Effects of meal sequence on postprandial blood glucose and urinary insulin excretion. Tokushima Bunri Univ Res Bull. 2018;96:45–52. (in Japanese). Maruyama C, Kikuchi N, Masuya Y, Hirota S, Araki R, Maruyama T. Effects of green-leafy vegetable intake on postprandial glycemic and lipidemic responses and α-tocopherol concentration in normal weight and obese men. J Nutr Sci Vitaminol (Tokyo). 2013;59:264–71. 10.3177/jnsv.59.264 . Imai S, Fukui M, Kajiyama S. Effect of eating vegetables before carbohydrates on glucose excursions in patients with type 2 diabetes. J Clin Biochem Nutr. 2014;54:7–11. 10.3164/jcbn.13-67 . Kanamoto I, Inoue Y, Moriuchi T, Yamada Y, Imura H, Sato S. Effect of differences in low glycemic index food intake sequence on plasma glucose profile. J Japan Diabetes Soc. 2010;53:96–101. (in Japanese). Kawakita K, Kimoto S, Takenoyama S, Murokuruma M, Ogawa T. Effect of food intake sequence on postprandial blood glucose and triglyceride levels: differences due to dressing. South Kyushu Univ Res Bull. 2017;47A:11–8. (in Japanese). Kato Y. Influence of water-insoluble dietary fiber on in vitro glucose diffusion speed. Nippon Eiyo Shokuryo Gakkaishi (Journal Japan Soc Nutr Food Sciences). 1993;46:351–5. (in Japanese). Kato Y, Tanaka J. Influence of commercial cellulose powder and pectin on in vitro glucose diffusion speed. Bull Fac Educ. 1999;81:93–9. (in Japanese). Papoutsis K, Zhang J, Bowyer MC, Brunton N, Gibney ER, Lyng J. Fruit, vegetables, and mushrooms for the preparation of extracts with α-amylase and α-glucosidase inhibition properties: a review. Food Chem. 2021;338:128119. 10.1016/j.foodchem.2020.128119 . Tabatabai A, Li S. Dietary fiber and type 2 diabetes. Clin Excell Nurse Pract. 2000;4:272–6. Liljeberg H, Björck I. Delayed gastric emptying rate may explain improved glycaemia in healthy subjects to a starchy meal with added vinegar. Eur J Clin Nutr. 1998;52:368–71. 10.1038/sj.ejcn.1600572 . Endo M, Matsuoka T. Effects of vinegar on suppression of postprandial blood glucose rise. J Japan Diabetes Soc. 2011;54:192–9. (in Japanese). Müller TD, Adriaenssens A, Ahrén B, Blüher M, Birkenfeld AL, Campbell JE. Glucose-dependent insulinotropic polypeptide (GIP). Mol Metab. 2025;95:102118. 10.1016/j.molmet.2025.102118 . Nauck MA, Heimesaat MM, Orskov C, Holst JJ, Ebert R, Creutzfeldt W. Preserved incretin activity of glucagon-like peptide 1 [7–36 amide] but not of synthetic human gastric inhibitory polypeptide in patients with type-2 diabetes mellitus. J Clin Invest. 1993;91:301–7. 10.1172/JCI116186 . Meier JJ, Gallwitz B, Siepmann N, Holst JJ, Deacon CF, Schmidt WE, et al. Gastric inhibitory polypeptide (GIP) dose-dependently stimulates glucagon secretion in healthy human subjects at euglycaemia. Diabetologia. 2003;46:798–801. 10.1007/s00125-003-1103-y . Fukuda N, Murata K, Mori M, Hiroi Y, Asato R, Henmi I, et al. Improvement of glycemic index (GI) by vegetable intake and its application to diabetic diet. Igaku Seibutsugaku (Medicine Biology. 2005;149:331–6. (in Japanese). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 06 Feb, 2026 Reviews received at journal 08 Jan, 2026 Reviews received at journal 17 Dec, 2025 Reviewers agreed at journal 15 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers invited by journal 10 Dec, 2025 Editor assigned by journal 10 Dec, 2025 Editor invited by journal 09 Dec, 2025 Submission checks completed at journal 09 Dec, 2025 First submitted to journal 09 Dec, 2025 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-8220213","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":558178000,"identity":"47077ee7-bbbd-4151-a7ed-c6524f1c0e68","order_by":0,"name":"Mengwei Yuan","email":"","orcid":"","institution":"Kewpie Corporation","correspondingAuthor":false,"prefix":"","firstName":"Mengwei","middleName":"","lastName":"Yuan","suffix":""},{"id":558178001,"identity":"02faf636-441d-431f-9ae8-0f25bc18e4e7","order_by":1,"name":"Naoki Kawada","email":"","orcid":"","institution":"Kewpie Corporation","correspondingAuthor":false,"prefix":"","firstName":"Naoki","middleName":"","lastName":"Kawada","suffix":""},{"id":558178002,"identity":"5e3f8c56-d173-4fd4-ae7b-5e0430277a38","order_by":2,"name":"Yumi Takeda","email":"","orcid":"","institution":"Kewpie Corporation","correspondingAuthor":false,"prefix":"","firstName":"Yumi","middleName":"","lastName":"Takeda","suffix":""},{"id":558178003,"identity":"0e2c8ac5-a4d9-46a7-87b0-2cb4089e5a0e","order_by":3,"name":"Ryosuke Matsuoka","email":"data:image/png;base64,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","orcid":"","institution":"Kewpie Corporation","correspondingAuthor":true,"prefix":"","firstName":"Ryosuke","middleName":"","lastName":"Matsuoka","suffix":""},{"id":558178004,"identity":"d200cc0b-aef9-4f97-9ce9-af51a553f6e2","order_by":4,"name":"Kazunori Utsunomiya","email":"","orcid":"","institution":"Jiseikai Nomura Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kazunori","middleName":"","lastName":"Utsunomiya","suffix":""}],"badges":[],"createdAt":"2025-11-27 09:23:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8220213/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8220213/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98434510,"identity":"7a422420-5ef0-499f-8a89-2acd9593b4d0","added_by":"auto","created_at":"2025-12-17 16:52:13","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":226738,"visible":true,"origin":"","legend":"","description":"","filename":"SimultaneousConsumptionofVegetableSaladwithBreadAttenuatesPostprandialSerumGlucoseElevationinHealthyAdultsASingleingestionOpenlabelTri.docx","url":"https://assets-eu.researchsquare.com/files/rs-8220213/v1/bf0f52c9372604ccf6de4776.docx"},{"id":98435259,"identity":"2a07c2cc-3f62-497b-baeb-04c917752183","added_by":"auto","created_at":"2025-12-17 16:53:23","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":6182,"visible":true,"origin":"","legend":"","description":"","filename":"4607aac62dcf42a79941962adffddf06.json","url":"https://assets-eu.researchsquare.com/files/rs-8220213/v1/39d8f013fa6925b97b71784e.json"},{"id":98434392,"identity":"a2269b94-7591-4073-9a2b-5d2bd654d2df","added_by":"auto","created_at":"2025-12-17 16:52:03","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":64619,"visible":true,"origin":"","legend":"","description":"","filename":"4607aac62dcf42a79941962adffddf061enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8220213/v1/9df800b1e58ddf9550983141.xml"},{"id":98434466,"identity":"3ccb602c-ed08-4f14-9b95-2e141c873792","added_by":"auto","created_at":"2025-12-17 16:52:09","extension":"emf","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11156,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.emf","url":"https://assets-eu.researchsquare.com/files/rs-8220213/v1/1e44fc8f8ffd6923962f8f8b.emf"},{"id":98268956,"identity":"1ddec176-229f-417b-ad27-fa17c9fabec2","added_by":"auto","created_at":"2025-12-16 01:06:22","extension":"emf","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":11712,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.emf","url":"https://assets-eu.researchsquare.com/files/rs-8220213/v1/a472f447fff01b522be1dfe3.emf"},{"id":98435738,"identity":"d8234c36-204f-4dc2-8805-c7ec776bb4cd","added_by":"auto","created_at":"2025-12-17 16:54:20","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":180158,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8220213/v1/8723ea87ccab67021208fee4.png"},{"id":98435322,"identity":"e26ff9d1-e7d3-4a21-b7b0-46bd3a1581f1","added_by":"auto","created_at":"2025-12-17 16:53:29","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10475,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8220213/v1/123ae5e2d472c829cac5c783.png"},{"id":98268966,"identity":"f8e2473f-c7bb-4641-a87e-e65c853db044","added_by":"auto","created_at":"2025-12-16 01:06:22","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10577,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8220213/v1/e27897caced7cfa5291fee81.png"},{"id":98435538,"identity":"74c44f9e-d1e1-40a0-95d1-51540cc773bc","added_by":"auto","created_at":"2025-12-17 16:54:02","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":56608,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8220213/v1/2373a4da4c91fd105384b954.png"},{"id":98268965,"identity":"876561a0-d339-4606-840c-28671c24b243","added_by":"auto","created_at":"2025-12-16 01:06:22","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":61139,"visible":true,"origin":"","legend":"","description":"","filename":"4607aac62dcf42a79941962adffddf061structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8220213/v1/fa88b27ffb5bb595e4b129ab.xml"},{"id":98268962,"identity":"5a65f10d-5a81-4d73-8c21-d1ffcf833d8c","added_by":"auto","created_at":"2025-12-16 01:06:22","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":70761,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8220213/v1/1c22b231de4ebb1160ec8b7a.html"},{"id":98268959,"identity":"b8b6e7f8-f7db-4371-8bf2-9620b0518b24","added_by":"auto","created_at":"2025-12-16 01:06:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":342497,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8220213/v1/abf78b0cd75f085548695468.png"},{"id":99306942,"identity":"b1c3af2e-e663-435b-aa46-670205e81223","added_by":"auto","created_at":"2025-12-31 16:04:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":879775,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8220213/v1/fd2aafb0-5011-43b1-8c73-a30505cec991.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Simultaneous Consumption of Vegetable Salad with Bread Attenuates Postprandial Serum Glucose Elevation in Healthy Adults: A Single-ingestion Open-label Trial","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn recent years, the prevalence of diabetes has been steadily increasing, emphasizing the importance of developing effective preventive strategies. Among the various contributing factors of diabetes, carbohydrate intake is considered a major cause of postprandial blood glucose elevation. In individuals with impaired glucose tolerance, postprandial hyperglycemia and insulin resistance may increase the risk of chronic diseases, including cardiovascular disorders [\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe consumption of vegetable salads has been associated with a reduced risk of developing diabetes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This beneficial effect has been attributed to the physiological actions of bioactive components, such as vitamins, minerals, dietary fiber, and polyphenols, which are all commonly found in vegetables [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe \u0026ldquo;salad-first\u0026rdquo; dietary approach, consuming salads before other dishes, reportedly suppresses rapid increases in postprandial blood glucose levels [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Numerous studies have investigated the regulatory effect of altering the order of food intake on glycemic responses [\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, many commonly consumed food items, such as sandwiches, pita wraps, and burritos, cannot be easily separated into different components. Therefore, the effect of consuming vegetable salads with carbohydrates in a single meal remains poorly evaluated. Thus, this study aimed to investigate the effects of the simultaneous consumption of a vegetable salad and bread on serum glucose concentrations.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy design\u003c/h2\u003e\n \u003cp\u003eThis study used a single-ingestion open design involving 15 healthy men who were at a low risk of developing anemia caused by blood sampling. These participants were randomized into two groups and underwent a 7-day washout period. Each of them visited the clinic twice and ingested either of the two types of meals: bread alone (B group) and bread with vegetable salad (BVS group). The test meals were consumed within 10 min, with each mouthful being chewed approximately 30 times. They fasted overnight, underwent fasting blood sampling, and then ingested each test meal. At 15, 30, 45, 60, 90, and 120 min after ingestion, blood samples were collected to measure the serum levels of glucose, insulin, glucose-dependent insulinotropic polypeptide (GIP), and triglyceride. For fasting blood sampling, general tests for peripheral blood and serum analyses were performed.\u003c/p\u003e\n \u003cp\u003eThis study only included participants who received a thorough explanation of the study protocol and provided written informed consent. Moreover, ethical approval was obtained from the Ethical Examining Committee of Ueno Asagao Clinic (Tokyo, Japan: Authorized No. 202401-39-KP001). This study was conducted at Hakunan Clinic (Chiba, Japan) and was registered at the University Hospital Medical Information Center (UMIN ID: UMIN000053931, Registered on 2024/03/22).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eTest food\u003c/h3\u003e\n\u003cp\u003eA vegetable salad (cabbage-based salad; Salad Club, Inc., Tokyo, Japan) and mayonnaise (Kewpie Corporation, Tokyo, Japan) were purchased commercially. Bread was prepared using a home bakery appliance in the Research and Development Division of Kewpie Corporation (Zojirushi BB-HA10, Zojirushi Corporation, Osaka, Japan).\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;1. enumerates the components of each test meal, and the nutrient composition of the vegetable salad and its extract.\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eAt breakfast, the B group received 70 g of bread, equivalent to one serving in Japan. Meanwhile, the BVS group consumed bread (70 g) and vegetable salad (65 g) mixed with mayonnaise (15 g). Considering that as little as 60 g of cabbage is reportedly effective in reducing blood glucose spikes, this study used 65 g of vegetable salad, consistent with the amount that is generally used in making sandwiches in daily diet. Regarding the mayonnaise, the recommended amount per serving was used [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eBlood tests\u003c/h3\u003e\n\u003cp\u003eFlow cytometry was used for conducting general peripheral blood tests. Serum samples were analyzed for the following parameters: total cholesterol (enzyme method), low-density lipoprotein cholesterol (enzyme method), high-density lipoprotein cholesterol (direct method), triglyceride (enzyme method), glucose (Hexokinase UV method), hemoglobin A1c (HbA1c; latex aggregation method), insulin (chemiluminescent enzyme immunoassay method), aspartate aminotransferase (AST), alanine aminotransferase (ALT; Japan Society of Clinical Chemistry [JSCC] transferable method), \u0026gamma;-glutamyl transpeptidase (\u0026gamma;-GTP; JSCC transferable method), urea nitrogen (urease-LED-UV method), creatinine (enzymatic method), uric acid (enzymatic method), and sodium, chlorine, and potassium (electrode method). The blood samples were analyzed by LSI Medience Inc. (Tokyo, Japan). Serum GIP levels were measured using enzyme-linked immunosorbent assay kit (Human GIP Total Assay Kit #27203, IBL Co. Ltd., Gunma, Japan).\u003c/p\u003e\n\u003ch3\u003eSample size\u003c/h3\u003e\n\u003cp\u003eInitially, the sample size was determined from previous studies of vegetable-first effects (Imai, Fukui and Kajiyama 2014). The Cancer Research and Biostatistics Statistical Tools software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://stattools.crab.org/\u003c/span\u003e\u003c/span\u003e) was used for determining the sample size. The required sample size was 15 per group when \u0026alpha; was 0.05 and power (1-\u0026beta;) was 80%.\u003c/p\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eAll results are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM. The two groups were compared using Wilcoxson signed rank test and Bonferroni correction, as appropriate. The same methods were used for comparing the serum levels of glucose, insulin, GIP, and triglycerides with those before the ingestion of each of the meals. A hazard ratio below 5% indicated a significant difference; all statistical data were analyzed using SPSS version 29 (SPSS Japan Inc., Tokyo).\u003c/p\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eThis study was conducted and reported in accordance with the CONSORT guidelines for randomized clinical trials.\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eParticipant demographics and hematology before test meal consumption\u003c/h2\u003e\n \u003cp\u003eTable\u0026nbsp;2. presents the participants\u0026rsquo; demographic characteristics. The body mass index was\u003c/p\u003e\n \u003cp\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAcYAAAHwCAYAAAA8Qc+ZAAAQAElEQVR4AezdBXgssXU24O3fQNMwN5yGGdswcxpumJmZmZmZoWFmZmZmThpmZmja/3vdK3c8d5a8a3ttn/voXM2IdSQd1Kz/36j+FQYKA4WBwkBhoDCwjoFijOuoqIfCQGGgMFAYKAyMRsUY99IuqLkUBgoDhYHCwMIYKMa4MAqrgcJAYaAwUBjYSxgoxriXVrPmspcwUHMpDBQGdggDxRh3CPHVbWGgMFAYKAysJgaKMa7mutSoCgOFgb2EgZrLrsJAMcZdtVw12MJAYaAwUBjYagwUY9xqDFf7hYHCQGGgMLCrMDCFMe6qudRgCwOFgcJAYaAwsDAGijEujMJqoDBQGCgMFAb2EgaKMe7O1Txkhn3PwCcDZwrMFA4U+vvEVw18IHD+wH4LR8+Ebxp4X+DkgQobMXCcvN468OHASQND4dBJfErgjYHtxOFl0t+LAlcP7DfadYTM+VWBBwaOFFgk/EMqv+AAnCBxhR4GhjbXxVPmJ4HvB/4zIP6vxP8T+GvgO4FvBZT5WeJTBWYNDtGXU7i1d58894NDd7sk/iKgzx8mvkBg0fCPaeDcgY8HtPujxLcP2HCJZg7HT8nXBcz9vxP/JgAf4Jt5fnzgdIFDBJYZDpfGMLVEeyb8XWZiXuI8Tg1weqeU+nng4YFDBeYJ9sD9U+G+gVMH5q2fKns6HCOze1TgXgFMkQCWx5UIGII1v1RGc/jAbgjGOURjd2LsR0ynqzKWDGW1wxCi/pQhPzVw1sCJApcOYFKJRj/If/8SOHHgkoH3BOYJX0nh6wR+GRgX/pyM/whgPn9LvIxAQrpZGnp74MwB4Zj57xEBh20eCYxgcNnUo3Vg8M/P88kCCAlJ+4J5fnHgfIFZCX6KTgwI1A1TwpgTjQgoCDxtkdYobVaAU1L3OVPhXYGdDA7rDTIADCvR1ECgsYdenZIXDpwxME/4QwrfJvCcgLVLtFvDloybsHvdtPyKAKEv0WBwRm+SnH8LWI9EWx7unh5uHJhEO5K9MsGehqPDLmlEBPDLpS14+FXieQJlgxJy5AOV0HhaN/j2gbSKOhgYYoyfT/4TAt8LIESJDgqI60eTeocAZploqcHBQ/yX1ehp0hANgSaKwTAjIJJJHpFAz+ZhDjB/G6pLPIwXM8doaZW3THsOR6KFAwZwkYVbWb0Grp8hnTIwa4D316TwrQKfCCAWiSoUBlYOAwS+067IqJig56VxKzL0nRnGEGP8aYby48Asgal1XulllnaXWYb5jbnucWn0yYFnBvjn+NgwftJUk6SStXAgWJC8aaZHWbi10eif0sYdA5j7sjTQNLfjgfR774ziMIF5AnMy3+j7U+mrgQqFgVXDwCUyoAcEZhaMU3arwlnSMNP4vC6jVNu/YYgxbgYbmM9JUpEG+cHE/HcYJnPfJKaDKF4t5Tn6+Y2YNo+d93FB+Sskk/mQRssUyLSLWCZ5MDCZvTs5nwrQ8DBDdfkaaSA0R+/J3pKAmZ0wLTsozLDgi3lnUoY3jPk8eWfe/EZi/tS3JP5YAC4enZh5FoP8UJ6NmxkXrpi4z560bmBuxUg/m0TzelNiOGpr7fIJ3yp/qAOc7JEDTHNmAn5HEpgpn5aYVvz1xMxrcJ/HET/UbfPwhQDBSDt3zTOzaKIRsy8zLSFE/0zy5gr/1ph/jzR9vxTWJgYJHwQW4zA3Zd+W/MsHmHv+ObEAl9o7al5eFrB+iSYGBEF/9pi5wCe89isdLgnKYbj86vBnLfgh5RkLEyMg9DBpfTd1MOcrJrbPr5z4vQHzfnBi8zNma3KLvGtTHfuXOZ6JP8nrwUWIJ+bNPjAGlhtmevuHZs0KYV8w2fO1Wv+7pDycA+6Nt+bduhFuX55n9Y2BkAa3Lh3dLenK2ht8+M7H6ZOmXKL1YE2dN3Vo549Jjv1DSHtWns3Hcx7Xgz1NU3peUvjdzeVBedZWorEBruAY/toZgSPz6ldyZvRhj5qnPcuVYfxwZW/BAbC3rpcGtKOes8ZiZC9YXzhwpuBHfXutf1avnfrmlWgtaMd9BXX1wZysD2ZT2hm6Z23d1yAoPze1tM019dA8OztopD1sXdvZPEPyHhswZnsMjt3JOFfSuGbQBW4uY03SWkD7aIPW3XoQNo2XmVsb9qE5wY9z5cIUvL4ktd8Z4BZLtB7gST373PrBkz3mbCqkv3PkgVvqM4kpGfq7aJ7NMdHuD21BFpkJZNikDoLD7/BeKQ1a+HskRsARlzweFE6RFCYxC+VwIrgIFyKTrA0BcUIMbAyLSxL6S0rw8TE15nHmYN4W2tgtPpi58pSCNiHm8aWU4w9BEBAim80GZtJ1oBwQRIV/E5FyYOHJ4XpI6r408MeATcc8i1hggg7J75KOofTxhGE4GDa3co0hurjAvJtqI/1bn/YuzQUqzNdhQvgAIcf6vDAFrCNfM7wxf6qP2TlULmsg1M3Ue7SUR3AQBcQOwcWUzB3BwXyMX3/m5Kad/rWLsdhLGDOmjQBgjGlyLRBqCF58hNpYS5zwH3zyLcMt5m4+iAG8wFGrCucOv771a28hTgioefDl0lKNC47h7kmpbN8hcuZ1lbxjksppi39Jn8paE/vtX1PGxSxrSxBg2revkzw6Vv4jHMEZXBmDfjFCfdn71oAAao8htoiecdrHCDVGwdTskps9hYA1oeViad/YrAdizM9kva0D4ZBQZB1SbC3Anf2GMF8oKQSBaya+UUA9ghShI6/rAdHUB38Wom6shDRryLfbZS7rlfLgkgqc2dP6gCPMmGBg7cwvxdaCNsyBcMOk/u9JtV/hiACiHbgjnDlfb0g+xmxtnTVjP2/SMDf9OoeYRJJG8uGrnVX13zwajZRxbvI4sj6YIAGPgCkdDXpGMtGx1ye2TzBM51wb10qavXznxJ8O2DcYiXV8WN7tEWfLGl0o78618T4yz/YJvGrDmdZ/kteDcs4q0C7aaO/BWRPACA5fSw351sK+sq/tPeWStRasuT1m/dAg+8ge0zb/Ltxj3tYUrdYOhozuG/9aI3vhv8Um838YgFCEBtGwYfkdaQdKkJL6iykdkGBIW0yPCB4/nY1hg/THZlExXRogQqsPl39I2TYkwqPNWcAmRQQwHoyYdD5LvaEyNkubH8J38xTSLqL6+zzLR0AQMMICIvS5A+nGTuLFXBDYJI8ICjRhzBBjldYFBI2kabN30z1jOg6KfBK+/mgNCL85K0MjwuyMwzsgMZNymdF/nQRl1DcPBNghx6BJwYgHfBEmaOCkVGM6XuoJNBCaBUlZPi0XceU3dogwN1qMPaN8FxBp+CLwAOPkt+2WmeeZdumgWwv7zN4xBvumq20ioogpImD+5ofQ2lMYJWKGENrT8GJO1kZZuEJgra/9rF3707oSEOxlhA4zhwP13Fwm/SPsiLQ5iTEshNw6GANGpw/EkeBgr2rDXNyKtkdem8pwRQBzZkjx1sN4aPQYrvWHS4T2tylPC6CZWQtrQ9j0mQbi6xynyFqwF62jPvVjPytHCEZ01wp1/rPH7EFj4KqAb7iCD8wMM+oUX3/ESNTzCYi9xtqEscIVDRBjWC+cB1YKFgXzdG7MAYM6bvKcNUKpvW+Pt7OmHXQGDs0pRUf2PYEcHmnf9h48atP6ma/6cKI+JoIOGaszC8cENMKdMVm//lj1A9RRH+O0Xs4NhowJw42zwlpgXvYQwcA4jM1+xVThxppprwFN0BrbJ+pZM3tXe61MN4ZTbcJRN92zM2ycGDqBzLoTJK2necODs0sAcQ70B4fGPa4/7e46cJAWHbSFckgQEMzGwiKg7RDYqCSTSf1AKpMLxqisjWIRWh3PCAcCZDFseHkOkL4cCnnSZgEb2IaygRBe/c9Sb6gMCdktSdoCoganzMMkcLhx4EhUtAr9IP60GAym354DYzP20/vv2nFou+nwgBA7/A51yyPNMlE1YmBMGB48tjLdWF53DNpDeEiHJFzMg0kOk7BOtEnEsttGe9ZOWytp2tavscKTtC4g2LRRBw0hUvfZKcD8mGjuQLJXibQMZ56NCRFp74ih/YNAIeCYCcBI7EVaD2KpLtwhxgi+9wbmZG7tva2jeTKBwRUC2vKtHWaNYRIECVb2r7E4L62cdZSmf0RVunEbg7F4b4CYEcwQNAyClmNOLb/Fxmosrb727A3M2Blj7VDWHKR5BvpU15zU1Yb0LtDcCHvOcsMRBmW/0DStZ7e8Z2cb0dW+dZIGEFwME/NobUn3TCgw7vZurNqBV8IGU6pyzgNBFZ6V7YI69kI3zTopz8JirtbG2NtZtWcxBjjAMFtdDJLGjuGgYS29xcqjE/a2evYXRsoKgMmgRW191TH27n6Spt1+mnRrRBlBx66RBIyZRQLDt05JOiiYW3/99O8cW3+0rFXCjFlDaIjWCD3AQNE830PDCVrXBK1Wb1fHJrWMCVg0m9VGo1kAC6Rt8Sz92AzKA3UslGdAu0CUpVs4RMXmotLTXPSPuCg7DRxe4yPdM3GpO63OpHyCALOIA2NsDog0m0g9B9gzhkh65rNhnsHU5S8LaAWIeL89hwmBRQj6ed33cc/W1GGwHoiPuWCINAj4E9NuxtWfJ50m5bYzCwDC4bMdcxp3wCe1DR8IjrnTksaVxXgwEsyf2cs+A9LsN8R1s4zZvjV+uOv3b9/aA8rIpxWwgihv7NIwROeKz9I+6rfRfbdO2mICo2HSZAms3TLjnglvmIL65jyu3LR0GqPz1S1n7bRvHp67eZ712UyJ3hsg3phqn4C3/KFY+/YnJkRjxYicNVrSUPl+Ghyr384qgZJmb52UtVdoZ31aox5LCYHLGJTtgvXkdmB9YZ60vwBcwTd301C9bhvjnlnatOsOAiGSYMRKAn/j6oxLN54mBLQy5ob52h/GSJNlMcBExYRJ5unN9Nf6WLl4FoY1y6BphzRGZgLOZ9K2TTJL3X4ZC4GYi/t53i2QTy5srAYOAEIjfxLY2KQcG5um4xDAAYmrK6lPamPePMSNg5rExSdBAkX0521nWnmCBSJiw5JCu+VpPv20bv4szwQIxBfuSdRMg/w7TEKz1J+ljLXlZ4QrEjBJlTkRw8IoZmmjlUFw4Z60bt1bej922Gky8MYV0M9fxjstyhnpt9X6ttdJ6XxhGDHfIw2LaZNJEZFXtl+/+84c/MokWCd+JPibVifFNwTCE9iQOMeLus4TIbGPc0LjEH7NnaaHqRJkut0RxOzbIdx1y7VnZ5gv1DljeuRro722/GkxpjDprMIn2uQ8cVn02zNWef30djbtA0yyn7/IO5wTUNFdZ0X7BEq+2v4aTOvH+XZu+OL7Zc0NfvTnzgR/8NNTSBrGzEo2b3+pvprBJl50ZAgWkw3zhUsNmCICN2+7Do3xIFLMDQ54a8OCUelJJTa/ywn8P/IxOYRzaEPK7wJN0YUCZs1mY8cUXSRARJW1wWgu0oxH2iLAbEvyRKhIV4u0Nakupoi40jhord1NaqM7lJPq5gItcAAAEABJREFUj8vTDtxi5ggYgs3nRiseV2ez6S6MOHguMmDALlLQJpi0HNh52qUlsiqYN9PPuLr2GY3MHBETxLiVNXd7y+FvafPE5gJv8I8x9OsSzOBSuZZH20PM7XnaH/8fvLf8odhZYJYTk+J/NhoqNT7NGVKXSZV2N77k5BxaIe3MOvbnS6tgLu63YJ4uYRlDE1pbGWcSbemuScsbiuGZRcYFFNaZoTKT0riCCHusIENnFYOj1WOQ3CH9+TBFE8T6fTib3ATaZ+7u0hWaHhqBjvbrzfKuTWfEfAlUBG8+aJed+mswqT1zYhmy1wik/T1P8cF0nQfWFMJa689+ZcKmcU7qY9fkdRdos4O2ad2WIiVaXLFbZUwH09pExJVBgBAwMYczs5KFkgdsSNeDHSIbj++oMS6+L31hqMqOA/4KhMYC2/gIFsJpgY0XIbWwytj0iHJ/c4xre1K6w2PMiEZ3TpPqDOUhXG58DuVJIzTwzWEgbom6zSddHcLALATP+tGcbHx1AabiYgpfpXeCCdMShuJ9EdAfHCOK2mECwtQ9O6SYBGJNqwDSZwV7hkRrTWlhfa3DusjTrgsGCJ7bdywJ8vSD0GLK2vI+L9iTBCJrRzjq1rdvmQrta2NwgxRx4VsjXDKL8dvQULr1hp6tubnob5qlBh74VNVpbblRbB1oHF0m3fJnjZmtzQeh992wvaQuZsCEOGSSNneWJuvN8uOSEXyp58yiCYi192lAuFnkrKlvL447q87vRzIIQrWx0Zya/5IwQLjvnjOM3Vza2bRGLkDZj2lmZKzcMOppW9q8ANc+F3KWCFr2Mn8zE233jNrTxjOpfQwOg6Xg+GyElqg8WsLnb7/aO60/e9N6M1f3+1Nv18IkxmhD2tgYkAU1SYi1ARDbVteis6+3zct8oQ6fjcV2IJg21NWGNAh1iCAc4SFpkSgtjIOhbaYVi21jkYrctnLb0cYjCXH4IgKc5W5oOmDa74M2mD0wPOO2QTBhCw20xYZuTN2649qDFxKag2EzOPSuMGu3W789u1BAWqQBmYfLGMwQDqBLB0xg5s4sbM4ksm5b8NvMxPoiQTOxYeb6ECN2njncMUdt2bBw7WKAw4vwKwMH+tU/zZsUKL2BuREMzAneHH4avJuu2uDDsAcIQ9ohpFhbTMSBMn4mMZIw3PLXOPjezdUc+Si9Y3qYsLq0eeN0VRwTMQeEElOinXYPeRvrtFg9/mjSMxObNl1TN2+4YQKyf2iMbuViCubrxh0hzAUDpmLrrI6xu2VN+INz+wj+pVtD84UL+5pAgflhBszOxuBmq/Pgpqrr79bROTAPbcnj+za2BsZBQEAAnRN96Z+lw95Wl6CCGMKlT0SsgTNnDNbbniHcKAta/+bCn2tvMj06Y86Eevppc3L+MW7rY60QdrGzacyEY+2iAeZK2yKAwiucOqtubtrLyvXBPoB383HGtUNQpUHyOcOFPYQoGxcforV0TqTZs/L5/zA1Nyulw1c7a/azOZiTutqBJ2208QydVfhxVux1+9scfGLBKkaQQo8IJC6lYRDohvFbR2vkzDNtE3hc9rNG/JbmZKwYI/qA5lEUjMnY9CeGE/h13tBjc3V22pjFPp1ihrcv7D3z5LfUvv1D2YAfexVtNidn1HrChf2tHXNyMxjjh3uMELMlYFpDc1cOfp0X/cGxs+GWrvrydz1YjHGTcMARDQeW9ApsbgvE3GCzqAtZTBf8TmzbCCXJFxEggbqpxcyKiSlPMrSIGCKtzKahurt9ZpNgAggyJCNc/CY2hE3mFxyUtcGMhyrvEw6mCm0PgU1lE9io6vQB0bGhbSAM0pi0ry9moX6bNpM52sS0KIfaRkF8bOJ+eWYiRBlDYeZwaFwaIlE7HPCIyLgsgRDzsWmrrU3Dr42HsVgPm5W2ay6IG0LW+nVA4Z85Uj5Bg5Tq8CpjMzsIvpmDVwdXOjAexJHUSMCBX1qLb7vgApNCwBBhJmdE1zuhA+6MyzrbH5gppoQgI0YYH4Lq8xF7wDraIyRwwoLPKBBVzMIcaW6INH8jHBvfvGA8/C8IGGJiHgQgPz6AuJF87VFpGD9iDs/wJp8Gy3qB0BAG7H/z8oxAwRFC6BagMVs7hAn4ntBFBW3Cgz0DX/YXIs1sy/Td5qQ8M2jTFo0BwBeCrA2M17qZi/pdrc8tVGNHeOEcg8EcXc6wh+x/fdnn9gbGzp9mTexPhA+TsHYIorOHGRNSCCgIqvkz0xEKMSy3sDFGRFfbABHG9O0J44dHbdr/8seB/vipnD31rDsmbyzqwLlzAdf2snyCIjwQqO0dNMKnTi4dGYN1xfBpP3DQzhqcOGvmBbftrHHX2HeYWDurTNTtrDoDmD16Z29IN1b4gxNn0ljtO2fc3sE47AM0Ct3jirDn1FPGPMzRejhTBCkf1zMJ0+SdVfhFG5079JHA1WgNJob564vwZb3QXLTYeSaYmD9fNWuMcaAZlAk0hwBBUzZu4DzCqb1kjNxO1p6ALd/6ekcjjF3faL/1058yux7ahhiaCMaE6NmcXXDALSwC3+op6yDKYxZx+CAd4cBgSFWtrM1DKkHsEAFtk1h9X2RT0AwQCWnyAIKmnjZoAQi/dJKMvqWPAxsDc8W81OmDTylIuK2+vjFbB2xooTEAWk23HZudtjZUHuFkrtUP0BeCiEBiDDQ7h6+1R1vTlnptTJiNza6MuWDIbT4OPomzlaXt2NDGpDxTXnetHNKWZ736BAu+1LF26iOi2mztGztGY5zWghaJKCMO1tQaIi7qAuNE8JXx3gDTxYQRIIeP1cHe0b5DiaEj3N5b35uJ4Q6+zBkQguw7a+hw22+tXbiAT2PUN2KAoCJICK104FzQLuDBewO+abjTT0uztvAinaApHdNo+7n1jcAgbvK7QBvA3J2vbjoi65y1+p4RKOcGEbRmmL2zgoF15wknNArtybffzJPmaS2kA2tAiGCFsFek9cE4EPY2DjHcGLOy9oLv4IbOhrJdIBwZj3r2XfdsY3zSGzhLzIbilma89pW1km597R/r1c5aW1917GHnvJ01MbqlLnBWCQLtrHbPGcGA4KEdtKuPA0xW+/YZ4dg8MSWM3Z5XD26bxQATV1Z6A8IKYVTbaFJLt58bPu1R47Kv9aec/dry9dvqG6/5dtfYvrIflGtgv5qz/pSFw24eN5Q9ZR7Wy7p1+2tld208iTEuPKlqoDBQGJgJA7R2hJvQRTDpVkJwAM29m17PhYHCwBZhoBjjFiF2FzXLJOPiBfM1nwYTMZ9B3/e4i6a064bKtMyX2TRlpnVmZKZu5jTmMxrIZifmnPO/WWNmOSY1F9a4GTbbZtUrDOxZDDgwe3ZyNbGZMMCHwQ/Cv8PvwpzHJ8hR32mgHrcQAy5JuOzA7QDvzH1MkXxOfJqzmiLHDdHtRyZWPmqmPL4yJjeXasbVqfTCwL7FQDHGfbv06xPnw+BX7frF+Gj4Z9YL1cOWY4CP0Dr41IZvB7iIwme7aOcuq7gAp80G/J38w4u2XfULA3sOA8UY99yS1oQKA9MxUCUKA4WB8RjAGPkyCkajwkHhoPZA7YHaA7UHDoEx8mUUjEaFg8JB7YHaA7twDxTtGi133x4FY2w+h4pHo8JB4aD2QO2B2gP7ew/8BGMMs61QGCgMFAYKA4WBwgAM7CRj1H9BYaAwUBgoDBQGVgoDxRhXajlqMIWBwkBhoDCw0xgoxrjTK7BX+q95FAYKA4WBPYKBYox7ZCFrGoWBwkBhoDCwHAwUY1wOHquVwsBewkDNpTCwrzFQjHFfL39NvjBQGCgMFAb6GCjG2MdIvRcGCgOFgb2EgZrL3Bgoxjg3yqpCYaAwUBgoDOxlDBRj3MurW3MrDBQGFsGAv1d57DQw9Pupx0/6kQL+bFuiLQuHSsuPD/wo4O+kJpo5GNvNUtrf8vSn5Pzt1bxWmIaBFWaM04Ze+YWBwkBhYEsxcJS0ftPAiwLfDLwx4M933T/xCwLPDlw+cNjAMsNJ0tg/BoT/zn8fCbwk8NPAPOF/UvjLgZcHvhfwnmhHwiHS64kD4kSrHYoxrvb61OgKA4WBncPAj9O1HxV/QGIM6u2J/cHn6yS+ReBwgUcHLhVYljbmj0pfM+0dMSD4e6nPz4O/0/mNxPMEY35nKtw+8NnAToZjpnNCxKETr3woxrjyS7Q3BlizKAzsUgxgLj/rjf1vef9M4EkBmt3NEy9La7xA2rpoYFmMNk2tRLhrRkETTrT6oRjj6q9RjbAwUBhYTQx8P8P6eeBEAf7GRCM0lbbX/JLHSeJhAi3wWx4tL9Jph8fKMz8mf+CZ8oyBqHu8PANaqbY997UtzPMIKcffqc4x8tw1VcpXX1/dMWjHGGhxxqCe+sdNfYw+0XowLv3LB9pSpxUwnyPnRV3+0MPn2VhPkNjYvN8mzzcJaEe6/trYlDV/4wPd8afKzgSLuDM9V6+FgcLALsVADfsABjAYzOBPef9LAJM4b+KHBh4ZeEjglYG7BzAcDOQGeX5F4N2BiwQeHuAD/KfEFwvQPJW9XZ7vErhx4JkBptAzJm4BYzlzXu4QuFfgUYEXBi4dMC75p8mz9E8kPn9A2j8nxqiM4cV5vmSAafhBiV8buHMA00w0MrcL5uERB8C8XpXnOwUwMfO5Vp6Zej+Q2Hwukdh8X5cYDi6b+LSBPwTOELhb4KoBzPC2ie8TuFVAO8aFweZ1Z0Mxxp3Ff/VeGCgM7F4MnCJDp/18KvGvAhgFRia+Xt6BCzs3yjOm4PLL7/J89ADm98vE/JeYg2eMBONxyQbTwCg+njI0QpofxpbXtUBLxcS+ljf+Tgz313nmT6TZ5XHEDHzUPLhE1K3rhqux0+B+k/zHBfwNymck5t+8cmLljZOZGKM1l+snnc8SIztdngXjxsxohuaE4d8yGZjpxRPjMRglf+378g4/j02MGWO85niPvH8ngIEm2vlg0Ds/ihpBYaAwUBhYfQwg5DQ6I6VpIfg/yctTAzRGjAjz+3reMZw/J2ZuZR7EnDAuF3gwJlrmV5Lv1uhbE9OoEm0If83bhwMfC2g30XqgUTJVvisp2sKgaIC/zTtGprz2Mao/Jq2F/8zDGwLKYVafy7P6xkpj/GLeMUbz5EvN60g7yiv3gyTQjM2HMGA+0jD8TyfP3IwbQ1cfk1Y+WRvCKfPmliqcumBknISCJO98KMa482tQIygMFAZ2BwaYI5k9aWm+LXxPhs18+LbEgks6zIQ+52AqvHoSaXN8jnncEDBRsCFx4AWDw2C6WZjWqZLAv4nZ5nGk3MvywBzL7JrHtTR15Xnvg7zuGDBz3zxiWi7KYHKXSSWaLK2Qlkfjo70meUPQjvZaYnvmo6R9tvQWM++6zWvM50ki0yyz87fyvOOhGOOOL0ENoDBQGNglGHhLxsk8eNLEfHX8YjS+vK4FDEDeHfOGmWCICH9jXkleSnD5BaOiGdJGl9JoGqH10gIxubyOzAeT5AncWPQAABAASURBVOvkX6TdYV60Q/mLwH+k8tMCzMS0Xtou/6i5JXlnw+5ljDuLt+q9MFAYKAz0MeCGqR8A+NdkuGTicw7myrwuNWBgtEVMhWbabdzFmZMnAVNLtKnAZEp7dIOUD5Tvz3wwMv7PTTXaq4QBuzTEt+nij1/1gbuzpNwiY0/1xUMxxsVxWC0UBgoDhQEYOHX+O0eAD88v5eRxSwKNTfsnS+tujXZ9eMbgEsw482mqjA00QhdyvpASfinHhSFMnu9v2SZOJlnargs5D0x/bq/SsM+VZ5pwop0LxRh3DvfV8/9hoJ4KA6uKAdpLI9QYxyw0s5VjFuSP0wbmJV1b/G7aAd15Y2Z8c+r4XlAd/kQMRDn1xMo9LA8YpEs4/JouuWBiNC++zmSvfVOprv7F0hpIY/bFSI0DYISnT4GnBFygSbQWjFu++RiPusYmXSwPeF+rkP9aun6Nl3nWLVe3V8FZUwYz5FukoWLGn0saDdtlnDzuXDCZneu9ei4MFAYKA6uLAbc+EW+fQqCVvlH0yQKGMjRqxP2DyfCzcddOfL4AX2SiEc3uQnnw6QZND5NwOUdbGE2yRhiCTz8wPMzOL+AwNdJCMUU/BK6esi7YMHO6TfqsJNAgn5jYLVg3ZbXpgo7LQZjPFZLH9JpoLWBWNEs3UI3XB/jm+dLkviMg3y1TN2J9nuEzDpePWhuegXm6qOPHAswNw3MByOcdPhXxSz7G7dapW6i+c4QLjBJ+1HGpxyceLjW5yAQPGcLOBYu9c71Xz4WBwsDew8DemhEi7ds9hN4FFL6xcTP8YTL4zR6c2CcSPn3wjJm+KWk+lXAb06/bYDZufSZ5PWAWGIhvB/3kHCb3oeS6yKMNTCqva0FZP2KOcWIsAGNz2QezVMgYXGrBfHwSIq0LGLkP/X+fROCzE35Ez0kauaHqG0Pz1hZm7MatsWgPMwbSmEY/mUoYaqKRsv6yB+3zF0nwYwdMpnAEn75ldKkHjszFD6XzNfqeMcV3NhRj3Fn8V++FgcLA6mLABRS/4IIBNfArLzSboVFjCvL8NQ4MCSPE/Nzk5HfEBDCi1pZyyqvX2sOA3pyX5wRojxjjc/OsDl9f9/KLsjRUY1IGM2pMUZtfTT156j4vzxhdovWA6WPAyujPr9cwa7YC2vhSXvyiDk1Sfd8sYr4YvfZfnXztA318NO/G772B8nChHT94AK/NbEpDNHZ4pumm+s6HYow7vwY1gsJAYaAwsJ0YQPcB/x+Y1Pe+zIOcfTnxmnRhoDBQGNhnGOCn9Hur/II+6/BbqkzEzQ+6z9AxfrrFGMfjpnIKA4WBwsBexADzLh+nn7Rj4tyLc1xoTnuWMS6ElapcGCgMFAb2HgZ8CsJvyRfY/H/8i8Uce2tdjLGHkHotDBQGCgOFgf2NAYzRNd+C0ahwsLI4qLUZ1drU+aw9sF174PAYox9zLRiNCgeFg9oDtQdqD9QeODrG6EZSwWhUOCgc1B7Yhj0Q7bfwXHhe5T3wHYzRj8MWjEaFg8JB7YHaA7UHag/8F8Y4qn+FgcJAYaAwUBiYHwN7s0Yxxr25rjWrwkBhoDBQGNgkBooxbhJxVa0wUBgoDBQG9iYG9itj3JurWbMqDBQGCgOFgYUxUIxxYRRWA4WBwkBhoDCwlzBQjHEvreZ+nUvNuzBQGCgMLBEDxRiXiMxqqjBQGCgMFAZ2PwZ2K2M8ZFB/xMDfBaYFf2rlcCkkTlShMFAYWGEM1NAKAzuOgXkY43Ey2gsGDhHYyXD4dH7JwDUChw5MC8pfNYUuGpilfIpVKAwUBgoDB2HgQknxtwzbb3aeP++E9EQHBekXSepJA7MI8Cm2UDhUap83gC5eLfGZA/MoA/+Y8qcMXCogTrR/w6yMEdKvFTQ9PnDswE4FjO326fxEgdcF/hyYFn6bAh8KXDhwo0CFwkBhoDAwLwaOnwpPCvhzTe33VAnoSRoMBPEnJgezmpXOpvimAvp8p9Q0rja+Z+UdE/+HxNPCsVLgpoH7BLSBoS+HmafB3RhmXbCjZ3LnC5wscN3AToUrp+MTBizedxL/T2Ba8DfIvpBCjw3YKJdLXKEwUBgoDMyDgdulMBrS/Y3P+yXtr4F+OFIS5B018WbCLVLpAoFZmdPFUxYjpinS9jC40ybtroFzBqaFn6WAv9H4lsQ03Vn5QorvzTALApQ5fab//cDvAxcLbHbBU3VTwQax0HdP7acEfhGYJ2CgfgNRXW1g8PPUr7KFgcLA/sXA6TL18wTeE8BEvp0YPfl14n5gvqRJvi8Z6E6iuYP7E0ybs1RkRWOuvXwKfzjwtcCDA2jdPyU+Y4BGmWhswNx/mtxvBn4Z2Oy4U3VvBExv2kwOkwLHCJAoPp/4JAGMMtFgILFcPTns8OdOPOSTPGzSSTLMs2zi/5L3SYtnkzCDfizlPhlo4ch5ICXpC/Al2lRJHh0v/2lbH+fIs/bfkdhFnKsknmBiSG6FwkBhoDAwGqF/1wsizhB4W4DWyC1Ds8rrQeHkSUEv3594OwKlgaaHsXX7e2peMLlEFebFwCyM0SLbHJ9K488PHCFAdcfc8rghYFKPSQpzA63yoXlm9gTUeu2od/2kN9u7+Al5Z+I8ROKh4OIPyYcU9pdegVPknYR0/8SNKeZxLdAy75gnF3ASjb6b/5hgMWLjy2uFwkBhoDAwEQNvTO5dAoTyKyV+WoCgnmhDIHS79PLupP4xsB3hT+nkc4EhLe8PSf9h4L8CFebAwCyMERNkOmA2cOGFKeHs6QOzSrQeTp0nDOrriR8eIFm9OvFlAnx8mKPLMupiZs9JOkcxW7w2b5t3vsxEG4IxniYpxwxoO9F6IBE9Km8vCPAl0giNM69rTBCjvVte3h7AUG2QL+fZWE+cmLSVqMJexkDNrTCwAAYwuLemPjrjjgKGiG48JGmYYKL1gKbwL35jPWXnHtzF+F26x8z/O3GFOTCA6Uwqftxkni1AUyORfC/PpCEb4FR57tY/Qd5pbJ9NjAFiQiQtEo2brBiWNm6Y/F8FmDItHjPpV/PO74dh5XFDYLM3DjE/54bMvGgLw2Ynv0HelUs0ctPK7dUP5AXTTLQWMNej5Um+DZ7HCoWBwkBhYCIG0DMC/ItS6uYBrplLJ240EN1h1UL/0LpkTQ3auGVKEdb/M3GDO+T5mQE+v5bGd3impM0SMGftPj2FvxSoMCcG2qIOVbPQvmmhxXHs8uEBTI8Z0q0pzK3VxaBIV5ibui2dtCJdzAzLR8lGf68UuHeAiYKv8DV5drkn0YagraMkhfaXaDCQimiFJDpmXPPSx0dSeuiijg1pDsUYg6AKhYHdg4GVGCnlwH0HlizmU4M6a/5DU9CcPM4UWLF8AseChm41eERqczcR7FuaCzboXLImBr5Pt/cpESxpEwtX5jAGMJDhnNHIIlvsV/UK2BCfThoTK00wj2uBpPTSPLm9RbJxW4oZlbmTc5hGh5Fijt6ZJHz60QXfG6aJuYNvFV+bWnyJV0yM0dpQL8tzhcJAYaAwsEwMMFG+s9MgN48LOkyuLGSdrG19RM8pLO5WuH1vnNs6gL3SGUSOm4vvYt6VTOo4X2ADvkImUj7Gf01+CxbhgXn5UUBZ5lG/DOFW6AeTRmOkETJHYKiHSdosgRmU1kdjpL2Oq8NkyuR7zRSwOTief5DnoUBS+3kymHYTVSgMFAYKA3NhgMDvYgsLGneTm+5vSAvN9MkUyqTJF4n+YZ7J3tJAGUCTaaHcXlva2TIaX9U2xjFGWh0kMwv0mYeN8NFMCIPzWQbVPa8j5km2cTdRmVP5HP2EEg2TfV4ZzJOPz7eQ/5YEWmWikXGcKw8g0YaAMVpkTFUfGzI7L7/Js8s/mK6LPD4tGZLe+DWN3abuzy1NVCgMFAYKAxsw0He5oHloHCUBPeQGYlL16zjoJmAK5V7iKvK52I83tPi/L9rFPNFKdKkBi5evAdq7WJlGL/+39sb/1WEto8x85UAWN5S7FPIOJFU0CwYwpH45mpmfBGL2ZKfu52MmbpnSCP0aDo1QWZ9A+I6QpskX2YDfjwbnMw1t+Zkkps9H58UnHMrdOM8c2aStPG4INE1MzsbSx4bM3osPXN+bNPPyAa6x5nU9mBut0/jdHOvnrxesh8JAYWDfYwDj4ttjhTpLsIF+cNf4xIyf8RNJWyRgXFxPzJ7uWzTgxvINeLuHId2zb7OH+sOI/Vydb8j5K9FUcLMURlvR5zyOMPSm3bq3Ia0LFCJlMPlu+r57xkC6kyaRWKQHJJFp4JGJmUwTrQcmAZqhBXCjlPmUluiZc/jOKUmS6gJzLC3RRvA9pE8oMNZ7pKxvgq6QGEPD/PJ4UMCg1bNZJmmNpDc+UbZ+3yv2G3Jrlv3948lgSk20iVBVCgOFgf2CAcwCk0HPnpxJo4vcNC/J86KBJc3diKH7Ft27F55poKxt/T4xS+Za46KkPCMFjBW4xIPRtVuy3FeYvO/GaaApuhbQVL+1CtzYp+Cg/bTWtQL77b8+Y+R7w6gwMVoeBvmTHlL4+ywEs6dbUySQh6UMkynGSKsjwTTwSxA2FIkL48W8mB580O+zDxKZj2bflDZslEQHBRvRuJR1seegAp0EEp1fnWB67SSvPboMZI4vztuQmTXJFQoDhYHCwBoGWJRcNESfLpEUPyLy8sRcTC4T5nFs8E21zzcwUO6gsQUXzKBM+B3XRm+7sU/g0GZfBeiGK4vmaVysZtKAufiu3C+Fodfm6rtNtF7+voM+Y7QR+N6YIQGtC9K6iPFOg5PfwOL4htA3M8wLLV3s+5tXpgGmh8b4xPx8fjgA0N4mbR7j8usOGDXpilSTJjcEZg/2dMzWDdlupjySlW97aLe01W5+Pe9fDNTMCwOTMIAuoVVoGXro0o20SXXkYUbKcxt53yog6PfpsbECtJW2iH7qn1sKrfULYOpJA/JdmlSngXsd6LT8fQd9xrhZBGBU7O5MnbQ66ntryw/Zch5zCGOqLX0zsd9rxXxdrvE9JIbnFhZTB8bMrEuas8itfeZbtnc/LPCKJPoxgEQVCgOFgcJAYaAwcDAGlsUYSSFs0hgiu7bPNdi4+Rup82zjJBGSycGjmC/Fr8bTSjFh/fkkRNqt0wwTKu00j+vBrS+Xidyk9VN1XUlpvVA9FAYKA3sAAzWFwsASMLAsxkgTdHnGD3b7uSQXeO6b8bFbY0hMCtT4JC0cmCY4rNn69ct/yS5+wbSsv77v0JVpTJoPk38zxSoUBgoDhYHCQGFgGAPLYoxapw1iWmzTtEPApNlnVMouCmzf+mp9sqXzcw7Z/qWxs4sX7bfqFwYKA4WBwsD2YGDHelkmY9yxSVTHhYHCQGGgMFAYWBYGijEuC5PVTmGgMFAYKAzsCQwUY9yCZawmCwOFgcJAYWD3YqAY4+5duxp5YaAwUBgoDGwBBooxbgFSq8m9hIGaS2GgMLDfMFCMcb+teM23MFAYKAwUBiZioBjjRPRUZmEtx3q/AAAQAElEQVSgMLCXMFBzKQzMgoFijLNgqcoUBgoDhYHCwL7BQDHGfbPUNdHCQGGgMLCXMLB1cynGuHW4rZYLA4WBwkBhYBdioBjjLly0GnJhoDBQGCgMbB0GijFuHW7HtVzphYHCQGGgMLDCGNgJxnjE4OPSgTMG/K3ERDOFo6bUWQOXDBw2sMxgTKdPg/OMJ8XnCidI6eMGKhQGCgOFgcLACmNgiDHeIuP1Z5oaPCvvNwo0ZuQPEre8Ft8z+ccOzBL84WJ/kupyKXyIwCzhVCn0gID+7p34yIFlhWOmIX/o+AyJ/eHjRFsSjPkeadnfhpx13ileYaUxUIPbLxggPF8gk71X4N8CfVpx6KShTWhUH+6TvH8ItHCoPFwl8KTAUwM3DnTz8zoxnDi5rS/jOUXetzscIR36M4NnSzzER5K8IaB5aP4Tkwo/eMBJ87ySYWhCL8tI3xGwCUzkRXl+ZeCPAeGT+c/E/jnxtQJfCjwj8NPALOGbKXSJwKMCfwnMEtR5XArO+jcdMbkzpXx/8yZpQ/jHvBnHbxKbtz9nlcctCZ9Lqw8POAQXTVyhMFAY2B0YOGGG+cDA3Q4A+tKnLYg8pYKQ3Ydzpl6jdYfMs3aekhgtuGHiRwZeHCA8J5oYMEX09wcphZ4YxwvyfOrAdgZzvHU6PFHAGBJNDDdN7vUD6Cym+Ms8m/d2jzvdTg9DjNHfNXxPqn498PnABwI/CzSm5O8gfjzvGOLPE78+8MOAPxqcaGpQzqL6A8L+nuLUCingbzr6245tcyVpbCB52YjMlpMWjARz27RivjbWH/K8lcHfg/xGOnh8wKbaCSkvXVcoDBQGxmBgXPK3koHpPTQx+tenK94vlLw7BGiO3gGt6jFJQyMbraNhYaJcSTTH8yX/PwPcS7dMPESTk7wWMM475emDAcrIFxNjLujKE/J8pMCsQf2zzFq4V+54eb9JwPgTTQ0sfsb9tJR8dwA+n5mY64rmTEHJ6+qESYuwOqOcbyRMvTdIlcMExgXztpGvmgI2yCwMN0WXEggbv09L1w3MurFStEJhoDCwwxj4dfoHiTYEWuAnkvKcQJeWYIyI/qeSjjESxg+X5wcFMEPC8nvz/JAA4Z/21FxWSTooEKYxM4qJ9hT4Xf57a+AcAbQv0ZYG87lCenhdoI0hjxPD0ZKLqYvR3ryOKFosdXDifaWgDXKZg7JAVHzqPpW573tkCmCbZqbtI4X5s9mglWHXHxqbxbl4Mp4eICnpk6RGVSdBkVCo7vyj/54y/WDDXi2J7wp8NTAUSF+3SoZ5GNPF8tzwdfQ8a/exiUlPZ0+sX2UvlWfzYmrmUyQZ3TxpNkaikc3w6TyQEJXJY4XCQGFgF2MAM3zfwPjROsyDRicbM8DU2rs0gA5Nc0XRQNGdw6cCGpJoPXw0T1xdhH0Ws7xuWUCjmUG5hmbthIUQA79GKjQzNNp3jLzTIAkFeVxyWKC5RugXaGJDVczm7kl5foAt2btnkk6SRifPf28I3C/ghilVOo9rgb/y1Xn6SIC5kTn0s3kmWb098ekCAokLk2LG5R9klsCU9PGaFMCMmV1ffuD5nYn7wQ1R7X0oGUN+xeMnnQ+A2ffBef5+AAPWrzwmAU7zqyedI96YpFlsvlAMEbPEKF+VMhgj8yl8O0TmhDmXrzHIqVAY2KMYOG3mhSmgVXlc05IwwD4jYN1iPfpCCrEmJRobKABu6HcLaA9dkU577eYt85nG5/Y+Zqa/WdtG79D8c6UCCx0G6UISMzOhgMCQrNUJCPWk0VgETITzuQuYA8mFFNPqnzIP7PD8dp/J8xsDHNZU/8vn2cJ/JTEGyBzRrYuhcEQzKzw3ZVzweXJiWpuLP25yYpJJGmFCTBOkJH5O5YyHGeIXKYApYnY24LfzzpeZaD1gxjas8bvUs55x4EE6pzLfo0WkUWLmpDRz0+41U/YtARqtcb0tz+amnvpHyTtTA4b6/jx/OKAOZpjHkXS+Cnih/UorKAwUBvYOBliN+BOZWDGucTNDB9E/zJEvchKTQNfQZAoGOtba9IyWy6ehtnSxdJpZl357RkdZ8zw3OFYqGHeig4JxniapGDcam8eZA5Mx6x6FgRZNyaAwMAHPw2Bn7nDRgpA2qQ0Mxw0qV4O7QCv8l1Rs9cW0H/ZxzmTaEThOylgo2hkmktcRpkgV99wAw1AX02lpGJJLPyQUi9jSLQoJpL0rYzORlixeSx8XW3jjMmZ1++VsDtoec6cFlf/l/Ee6oQW3tCSNMN0mDY4O/JNvfm3BaZ3mJT5QZKQe04cbXZj/6P/+1VNhoDCwBzDAgoXmEZwnTYeLhdDskzcKwbiy6Kj7CSxqNC40Ci3TB01M7FJLnwlTSNyl6NJvz0yi7mLQ3LwDN2QJ9UNjQKO5qD6WzH4fSZoaaLKUjZemJPqInnJ9USSStFoBc5g0oq8lkybnokgXpFGBMYEUGUE+JmqhvDegGblpRfMiabT0fgxRP0mizaStPK4HWiBJaD1hwQdzthikrKGmmAswKxqizajMn/MfTZa5tDG8JC0cSIldpr9wg9VAYaAwsBIYcEGFFYkgP25A6CVXDNrnPsS4ci0dPeUqooWylPkOUj/uWKBV0vu0EhNzF6JLvz2zzjFvUmC8A+/G0vrrxhfOi5v7FJY8zh0wYf7F+6cm/kEpuXOeLxgYR4uTtTMBk1hGz9pB5C000+ez02gXmBohNcmDwYLbGMyu/JLMixZczH9IuxqsuAWJGDPGOasGugVDqCb3CgZqHvsSAwRrbhJWp66lqI8M1jB3LZgZJykOrR5FBPPzgysu+fnRE5/TuQAo9pldK7vMmPnTZUOmz0nzGdcnun6XZLpD8t3E2qGdMgtfKe+03USrEzC0ZYyGFvW9NGRDuAzTNWl6xjQnSQUWHPP0PSH1mhOaSdYtK6YD0lCaX0qwsFR6TNyv3vQbZRrFxPVv4br5pBv+yW7aZp7hAl5owySnzbRRdQoDhYHVxADNiInU5b5xI0QrL5NMF/SaFoYmTKPJaCF3FLOpiz20RYyLJiY9TS49cIXxl2K+3FiAn5DywCTqHgU/5riOWQIpOeiq8QN3RAgE/KvyxtXdkfRpizDroKjvbOkW1kewpCA2ZfV9aO/3TdmovQ8Bc6KLO648nzsFIMuv42CQeZ07mNe4a8uYsEs3rg8PLQh/IJ+iG6i0Vr5PA8BEjc2m8L4IOBSEBZdyjGORtqpuYaAwsC0YmKkTtOf8KekmPWUhjwcF9K3Ru65fkVKByWnjoEq9BLSWGZZ/0neQXFsYTq/YCB0m0DOZdkFf6HI3zTtrWb8NF2XchzDuBsZPibhNCvNxjjPBJntE+McjfG5i3NKMFe1Tj7IibWVgaAEM3AUUvja3lsT9AVN9XWCBRAsp38L4+TgSDF8cSQg8LJmQwGeXxxEGgxFiDq1/pgCXdyBbnS4wF7g1hYlhJiQxv7eqLQDZmJcx08RIJS7jYMjK26S0Q2WBsfjFCNKWn72T1gWLyJ/ItGHsbSxs+himxTQWjN48uvgxLmNpsXaNwViMz9zN2bMxucxD21auoDBQGFhtDNCKnO9xF1SMHl3DRFwyGTrbJ0khyoNffHFDv9EXrie/e4qmoF8YkM/WrpzyXcsVuoGpKcsc6XM4ljZ0LUVnDvqlIMxcYcaC6LOLRL5lhy/VaJq0Z37GkyUBjzlzYryC643lLK+rExDp/mgwgNcm0Q0kn2pQkx+ddwueaGRBqcGcsbQyvkESBWbgOq4P8yHHN35sy69IJZ870NRcM/bBO8bAl+hnhZI98lmFbxCV70ownm+fApDn91ttKkzSN4o+jXhz8jBhY8NUfbOIsbFly2deoHXqO0XXA6boQ1s3s8xhPSMPJBvXpn3czzRxxaQxI5ijMfosxJyYedX1axecyTYxhoppmvsLD9Rj9/djBgQJwgMJyzxopjZLilUoDBQGVhgDzrmzjdYh9hgSXx/m1R82RcE9Bdagfh4h2i3/yyYDHXG7FI0D104a2tEsUsqitW7/0/qSPcJU0Ca/q4pOoVHGRViXPwS0MbQT450G2vYZ2VA7s6aZA82Tj5XipB46yi+KEaOhYt+H4wUvSQFjTLS9YVJvQ4wRs8LkLAYNzG1T3+/5xEBbFoWGRxPC+WlsCL/fVoVUTFS+PIuPibXLM25pkXZIPZCmrDb1Q6Vmi1avCzQ+EgdkG5O6mKObVsyd+jcPGhyVHpPFTG3g26Vx7falKbdMfYhPI9a+/lJ0PcjHCNt4fKP5vOSaB0bLpGoDqGc+PvZ3+7ZphKQ+Y3M44EBZc9QfporRYqRMEWm2QmGgMLDCGHCzk3aHpjjHaI3fOm1MrDt0nzPQ8oa0IEL79VIY40Q7+uCCS6Oz2kHbKBqN8fFFoiu0Ld+I63+nmAqNGL2jAHQVDxcpudJozd1f+PF72n5LFk0lUKC7FDC4DUpWK2AoOz0izI4vjyN36Gozhutj+mUzke9k4hg+jdCHqzZpkrY0YOp8pzRWN7P6DHtLO6/GCwOFgcJAYWA6BlaBMZLAaJhuaPn9U5pkGznfHDs0La1JUi1vGTEHOXMs0wgz7lYyR+ZlEhOTKg2T9Dj/HKpGYaAwUBgoDGwpBlaBMTJbuvrLGcxsgAkyEfBL8gHyy7mavFXaFZMp2zutkUa3VQhnCqb1cry7/LNV89mq8Ve7hYHCQGFgX2BgFRgjBsEez7Hth8P5NNmgmRzZoPktldmqBWGjd2WaI9jzVvXDR+m7Hbdzt3I+WzX+anf5GKgWCwOFgRXEwCowxhVESw2pMFAYKAwUBvYrBoox7teVr3kXBgoDy8VAtbZnMFCMcc8sZU2kMFAYKAwUBpaBgWKMy8BitVEYKAwUBgoDewYD/2802jNzqYkUBgoDhYHCQGFgYQyUxrgwCquBwkBhoDBQGNhLGCjGuJdWczQa1XQKA4WBwkBhYDEMFGNcDH9VuzBQGCgMFAb2GAaKMe6xBa3p7CUM1FwKA4WBncBAMcadwHr1WRgoDBQGCgMri4FijCu7NDWwwkBhYC9hoOayezBQjHH3rFWNtDBQGCgMFAa2AQPFGLcBydVFYaAwUBgoDOweDExnjLtnLjXSwkBhoDBQGCgMLIyBVWGMx8lMbh34cOAkgVUOp87g3hy4eeDvA7OG06fgAwMvCRwjsMxwsjR2m4DwT/nvroF3BDbbz7+k7sUCFQoDhYHCwL7DQJ8xHiYYeHngx4H/Cvw+4I8E+8PB387zZwNPDZw2cMjAMsLR0sgDAvcKnDSwrHbT1MqEC2Ykjwn4Q8zHSjzpDyLL+8eU+bvAtKDMuVPoFoFPBA4buH8AkzxF4j7jTtJM4RspdfGAMW+WuaZ6hcLArsfAP2QGjw/8d+B/evCLvF8/0D9n6OiZk/6owOcDzws4q4kGw+GT+t7AUB9fSzpBNdGWB7Tnn9PLLQOUFHC+PE8K8HPVFPhoAJ/AI+6R5yMEdm3oM8Y/ZiZXDJgoysTWmAAAEABJREFUhvimPJ88AFmnTIx5nT3xKwIQ1q+f5LnDz1KD9vXKxDZGopUOX8joaFNPTPy3wCyB9nb5FPxmYFqg/V0mhQ4VmBbOmAI3Czh470tMkLlt4hcGCDaJNhV+mVqY+K8S3z1AeElUoTCw7zBw3MzY/n9R4md34HV5/nkAM2h0APM7YdIwhocn/nrgEoHrBjDVRIOBFYpC8ILktj6ek+cPBLT/k8SzBv1vxup26HSA9j868fEDNwxcIPDuwLiARl0tmdcJoOH4xKXyfNbAQwIYfqLdF4YYmwW0EIiiGf3Zf4E/BF4duG/g6AHIoKHkscISMXD1tGVjJpoYjpncRwQcUNpiHpca/pLWHhlAFK6U2MFJVGFlMFAD2WoMoI9HTSfPCKB3GFwDDOSrSScoJ1oLrEH3yxO3ya0SPynA0jZJSKWlqad8a7vFL079jwQw4EQzhbOk1DkDmHSimcONU/J2AfSEAvS5PKP5icaGIybnwgFlP55YMF+upivkBaNMtPuChZ931JCAcTKnHnneylV+IgaYZW6aEiSxRGMD6ZKE5lC9IaW2StP+XdomtSIKLAd5rVAY2DcYcK4+ndnSmv6auBtYgD6WhJ8GWsAMTpcX7gwm1DxODbTNt6SUtroMFG3W1qeSN41BpchC4V9T+z4BTPH5iVkOE00NTMjMxup3lSTCxI9Sm0su0e4LkD/vqCGDNII5/qZTWVvUeP7CLyb9+wF287Ml7hP6IyWNHZum85U8u5TSfFkXzft3AjaJBXp9nklUiUbXzH9Mr/omVRlLktYCjebpeTImm9hmpu38W9KYI6SBO+RduEj+Y9r8deKm9rOLk9zY1n+QdJvyXIkxokQj87D55TMxdvtXl1mTT8D4maFtbDg5diqrm2gETy4b8QMal7Lq3SWZJDXmB5IbvPBRJPmgQFs8T1KZtI0/j2ODMTJ36MeavCslmWBJey48tfE6FKdKXhuvObMeIAw2/Xb5OTKECoWBlcEAixnm1R2Q84dOdYXSE6TA7QPvDGCWztHx8uy+QKKxwRnD+PoF1Ef3nD9l+vnLeqfcoNm00tekUXPT91HyjM4nGhu4XDB0tMHdE/NlFj5varBmodN53H0BkZ511AgsE9+1UwHxflViPq1Ea4H54Cl5+lLAM1/kl/OsHOmqMYbDJQ3hxzSkiy2+Ovrgj7tBymiHmQJR/2HeBb60h+WBdMOP1t2wNrBLKKQ10gqHOec4BsVnqi0SDF9Bmhi9Nf9hRswkGHNeRzYIZso8wByh/LOS4YKLTWLTMHWeIWkYR6K1AB8PyhP/3mUTnyaA4WCsfKcYX2P82pfvdqoLMhgSBoWREyIwMAyRhgZPaWpDMA7auk04i1RqjT+TFph4rMn580wg0Idx8QlYAzjW3suSz6ziYORx5MBYZzihoUorKAzsZww4p4g++tbwwJeItv0pCVcJoCVozz3zjG4kmisQ6NECAvpcFecs7O4IWmMuGJwb7RgkM655oh/jmkRz+URd2ET31GHxwhTR6q1k6OPGtJT0SZPWAUT9Rx66cKO8Y4CQQAPL68iGYG5zmxHBl25R75xMWhGz34nzLNB0SBQQyh4NuZiDW01MFzRFmqbFOVEqsJknWgu0Mo5lzFa9tcTOf9JomPyjmABCbnEwWVosFR8TUIUWhMlhXL9NAg2SJoWhejduzAMju1DymQy+m/ihAYci0XowTnOiwWHAtFYbgzaH6Tsk3ztQGpP5YJ4xIuNlRjGWhp9kTQzmZDNjkC5ITSycTEzUxjdPa5KkERxaB2vlQMCXNWY6tQ6YPKFAWXMxVnuBpi+toDCwXzHgFqbLd+if8wIP6B8B3hmnMfLNs2g5U+jiNVLIeU00U9Aev/7bUhqjTTQYzpRUlwD10wBjoli09xZTPFJ8QyDco5O0Wtovmku5YM1DJ++d0tP8hKxQLhsR7F26oVCguam6e8M0xoiZuGwD3LJ66YGpkohsjkMeeKdJki4+mXeMLdFaoGqrw0RnYfTHHMpEiqg3BFp8TKT7TiNElC0SjUyD/57/aIGNaOf1oICIM9FiVMyFCogxIRuBJEZ79WmI2PVi6ZgiTZBpAFMENpW6GAnmpS3tAM8NtINhNa1QunEqhxlrXxrAGDFez8DcxQ6ceBroi4kFLuFxUnnaIJPP21PIeBKtBX3RzruSLM3QhZv+eK2neRAQ9LvWQP1XGNinGOAWQe8wkkavuHGcfW4egrHzQjlwWZHgyTKG+cyKMoKvC45cNpPqaJugjj43oL3pt7232EWhfltoCGHXPPRl/Kxw7hWwlKHZPjtRrl+3vaNHFB8CAQsXGsFPSfCeRxho7a1EPGnCBsj2jYEBl27YkZniENbHpgAtItHIprCQnvtAi0T8MQcMjv2aqVPb/bLdd0wZUyUVMTmSopg0n5lCNMtEg4EU5yaXa9YYHQZA+rGRaW8kJD4+jFEaJmVxbXamTzZyUhJQTn3SG7/BYIdJxEThh2YGDzaEuSZrZB4OiudlgLaNSTypPXMihLjQwzneLc/M6wA7gBiePON1QGjXQ+NVRr+T+qy8wsBexoAzgB4RzNHE/lwJ8l26phyag5liQP3yQ+9oMoGWBqb+UJmWpi9WIGNpgE5hcO29xZOEaMK6Oq1dzBFtRA8aDWx53Rg94FrziRneQHt190K9J6QgJplo9wWLMO+oSR4YloXmu+vWx4C67+2Z9ITYYo40MIwVUlv+uJjWKM/3NTQ6G4/5Vdo4oOHQ+jBfdm/j5C+jRTIn8s25UEOLJeVoB6O1yTBt5aXNAzYV8wmmyPzA3MwRzxRCgKCJzdPepLLGStCAP+bdcWXhiXmHP/EmKWSDJ1oLTMEPzhPhgQ/EeO8wGo2YoZ+cdOuVaEOA10mHa0PheikM7EEMOG/oEGaD+LcpOhsEcgoC+tbSW+zcDJ2plt+N0RCCLHdSt49umWU9a9/YuKgoBv12zUu+cv087xjf5fKAiWOuGCqazdLGveRbd8JEiuyusBnGODRDUgpTHPsyzaNfhh0agebLIuEwTfrpsn65/rvLIJgwxzabPcI9C5Oh9fDj8Q2S8CwOEysTA8aC0dKojEWfmDZGgoEyezCLSgdMILTIZkqVNgTySUk2ifb475iBMeih8ptNM38OeZt16BB222XK5iclBDB3dPOsk1+2eX8SjZf5wyUgTDNJ6wGeaOukV7CeUQ+FgX2GAUyLJYng7fy16WOKbntzQyjT0lvMEuUstvdJsYt5FIj3TCq0pDzMmuVIzNqFTnabJvBThDC8bnp7puCge+1djJFijhQN1ihpuw42wxgxNDcUMbl2w5O5lHbENIeJdRHBTs336PMDEshzk0k6YRbtMqAkjxD6LjKV92sQNgoJhNan3DSwKBgUjehuKcyPSMsyBg5mkgyGZRGTPcIsXQDi52QK4IDGEOUxx/KfKuN9CFzVdiPV5Rw2fheLMHHtDZWflEYTdIXanIfKwYn5YGZdH+FQWWnwwF9AsPBLFtLg0mcr1s0tVONlOqGRy++CNeJDwUA3M59uW/W8jRiorpaOAUyPZoSOdBvHOFhanF2uJsKkfBoVoZSlCvORNgnUx3gxUoL8pLKYmAuDTLVcOQ0I526FUkRamti41Om2ibnzJ3IDsRp1rWWsTXyYxqJct157dm8BDeGe6raNWaIb6P64uq2NlYz7jNHk2MNNlMkRc6BxMTECC+HmJeblswkTNzFMx7eALnlI93NCtELIxQDdcuTLU/aN+Y/mxuSIOLuNeemkYaA2GCLtJhdinOQRswUJjdnTphzN8M9i8DPSVC0en5pq2verDBbTJwxdZkc7xRRtTheN9IX52GjyMFEbHpM0f37PtpHEmJQDoO8u6IcgQRIkUdr48EsIYN7k3KapapdJw3zhBP58U0kqM/Yu2LDm1L/tZj1JftrUDwe4+bjFa860b2nyjBfz7o7VM1y7CWwv6BPTV9ZnNPKlFRQG9iMGMDkMq29VgQs//0YI950zuodeOr/Ov7OjDMAs0TJt8M1Ja8AyIw3t6tKmlt+NnUWfnBHcnecGzLkYeHtvMY1WnW4bnmmFXC3MxNwr6DDrEhqAljdNl/uJZdANe3xBXbSVcsSF5jM5NJHwjd4rh+kqt+sAIe0OGuGnWZwjiRgY0xlzICYG+BSpyX7L008iYRwpuhZoGy6pKIcwYzIW2icRTH9rhfIfTdO3MvIRfzeZbBLOW8zVjVdmvdY20yFtBUOjLaWJmYINzBnM98fU0SrROh+XF8ylv1EwZTdf5Xu2Ua6csjZqohEG4fMHjB2jxMykM936PIP5VL0umLtvCH0biBERHtwUZXaGWwdBPRKWizI2FW2WhOcHCwgd+uiCDWkMNHSCTMuzfhz3mKD1YzLGkAk5JEtaMWaKKVtHjLI7Vr/PqG1rgNljjszIJM4mBLW+Ki4M7DcMoCOYHIvU0NxZo5x1ny2gg5ii98Zc1EE3fKLlcw80U1oDNIBpE41qaQfiLY1ol5dMD8bph0fQFO9oRpLXAl5gzOhAlw6zFKKRxu7zPPc6fBfOhdOnr2sN7Yb/+owRMzIpzHEcUNOp10OmAfU5Xkkg6j8tSCCRJNoQ+CPdLvW9DemEBOXd1WIaSxfxtCwMlj9wHkQbn4svfI3dzpk7jREz7qa3Z05vF2eM3w8J0Mxanro+ipcHmB/lYR4YmPlI7wKpkfmYdtzSmS0wLj8w0NLEd0pjpEBMlODhECXpoAA/JDUmVRKqTamQMRizthpg6vwV8CxN3763sgY0c2kNvDMJ8ytoE+4xceOnyeqjoDCwXzHAIuQsjdPmCPHOtW8JnSk/HoKZdvFFMfCJBbpAAO7mOZOEU4JoN307ntEECotxU1owwm6/6CBBHg7Ms5vHooYpqmteaNg8tLrb1ko89xnjSgyqMwgqO7MEFX4cI+sU35FH5k8MkTY5JEk6RDb6kICwyIBJmzYhkwfmyGQ6S3v8lxivcQ8xXuN1CDBZN1YJJH7BAzOepf0qUxgoDBQGdjUGtpoxbgY5/G1MfAg0qYXpkl/T+2ba2+o6tGSmVGZm5hM2f/4FvgQmZd960ohpsMseC+bIVHPBNMxPm2hqwAyNFzPH+PgU2nhdE6f98pc0ky4tti/1Tu2kChQGCgOFgd2KgVVkjLQul0WYVvkfmffaxZ1VxDPG6EaacbpJ6pMHDJLJ0mUf/sO+6WGZ83BDzk8yMdHM0i5N0GcazB5uj/EpGC9GKY8Qwgfpdi0fq7RZ2q0yhYHCQGFgT2BgFRkjQsx/5maryydbyVSWtYgYIN+oW2kYDuAv7Tqvl9XXUDs0a7fOhvKG0phF/QRU18fpVplr28rzXfKleP4/qKfCQGGgMLAPMLCKjHEfoL2mWBgoDBQGCgOrioFijKu6MjWuwsDWYqBaLwwUBsZgoBjjGMRUcmGgMFAYKAzsTwwUY9yf616zLgwUBvYSBmouS8VAMcalorMaKwwUBgoDhYHdjoFijEYgJ+sAABAASURBVLt9BWv8hYHCQGGgMLBUDOwwY1zqXKqxwkBhoDBQGCgMLIyBYowLo7AaKAwUBgoDhYG9hIFijHtpNXd4LtV9YaAwUBjYCxgoxrh9qwjX/v6i3yX199Jm/dHv7Rth9VQYKAwUBgoDI8S60LD1GIBnP9DtT7P4kzP+9qS/5ejvHW5979VDYWBuDFSFwsD+xQCCvX9nv30z9xdDaIn+3tn10q3fIr1m4sJ/kFChMFAYKAysEgaKMG/PavjLF/7S9e/THfCHnv2tybxWKAwUBgoDW4uBan0+DBRjnA9fmy3tr1n481TqHyL/0SDfm3hV/8ZkhlahMFAYOIABLo8j5/n4gRMEWH/G0U4C7/FSxl0CoM5h8j4paP+fUkD5Phw36YcObGXQP5pkrOZ3tHQ2bn7JGhu0Y67+Fq12jjC25IpnbGbyKz6llR+ev3V4qIzyfYH/CVQoDBQGVhcDaOTZM7wXBPyB768mfl3g8oE+w/L3WLlIPpO8/zwAH0jsfkGiseGoyXlDoNXpxixNp0zeVgXzO08af3HgywF/3/XVif3h8/78kjw2aAee/GFzf8f1gSl51gBmmWh3BZNZ3RHPPjLSloXEcDCey6XqgwLHDCwj2CBXTkMkqUQLhXOm9hcD3wwI589/xp+oQmGgMLBiGDhxxnOzAAvPLRI/NnCiwJMClwp0A03pJEm4X+C6B+DmiTHKRGPDGZPzncCNA62e+Fl5/0Lgx4FZw1lSEI2ZlSGdPOVvGXh7wPyenPjUgScGLhqYpR109yYpe+/AbwKY4g0TY+q7UvjvM0Zq8Mszoa7E0n22OVwg6TIIz6/o1Plwnk8RmBZIViSUbvvd58+nATc3E00MVPbbpwTmBR6SZ4t6ncTLUuVt+DOlvT8EFgmY4OHTABwdO7FNbIwPyPMsOEuxCoWBwsA2YQB9pK29MP09MvAfAcT/aYmZHmmNh8tzC2fOAybm1vmz8wxem/jXgXGBlsn8ev0UeHpAHfCcPH8u4D7CLxPPGphiMedZyvtk7LQp+JTAowMY8d0OxJQKyoaxJWliwFjvmxLwRGD4Wp7/GNi1wcJ3B28yV0wCyYEv7BN5PlXgnwOnC7wy4JODtya2CUgTP8szbQozgkzlMYB+2ym2HjCFK+XtZAEbgNSij/vn3bd+H0tMWsFA8jg26E+/H0yJlwV+G7hd4BkBfr1ECwdztHkw8eYnnLdRDPsSqQRvz0/8lwAh43uJmWWk3yfP/BiJ9mSoSRUGdhsGMA6a3Ecz8L8GBDQSA/lpXmhKjc55vlXSaItMkWggoRf9SPLYoN3XJPcXga52hWGisWjwn5K3FcH8vpGGPx4wjkQj88Mo0XVzmjR+eYR7WjGh4blpYLM0MlVXJ7RF7Y7I4nw7CSSfRGuIEmM6j8kDxnjSxNcO0DATjTChd+SBpECrImlw5CbpoGAxIJM5Ql/vTgmMItEIQ3SDU/8/lzABSGqkNzZ8zGVC0YWy/iG1OcCZPjd7WQazP1fawRRJg+Dxef9RQJukSnOGX4cpyRUKA4WBHcYAZvHpjAGTSLQeMA/MCo1SRgarEv8jekSJeGcSaZkE/jzOHWiqrEssZ3NXnrECuovxorndKmi4OWLWaHs3r/tsfCxz2nlzMihV3gkFGHuSdmcYYozTZuLSCGkJoT9SrzDG9qakcTafOzEmmGhDOGzeMEWSyiSkp9jYoN1/Ty6JilN8s+2kiamBFodZYVwY+dQKAwUwVSZofoMGj0g5TDHRyCFjjr5YXq4RoK0nqlAYWFEM7O9hsVS5mYoZOLuwgT7wRTrfN0oCrfHqiW8QIMQnmiugby7CNAVlrsoLFmbRc1eDsjNJA1SOf5TShEaiy/jCE9I/7ZnGmcfdFzbDGEkHNgOJoo80DIppFCZIDUyInrtAk6SC0y676fM8Y8iXTAXO3e8mnhTMkQZLMuLDZJ5tvsuLp6KP7aUbNyaYpA3B1WtSYdugNoDNz/xpU9B+HQJtPCw1aZjmyEmPIb4+aSTIRBODCzngsinlllqiCoWBwsCKYYAmxLeIKb4xY+sKy3/LO/eIM49GEHYvlDQMJNHMAR1CBygZaM9QRTT0Ismg0aI9DTAlQjfa09LE6LE6qTIxYGZXSQlzQ1+780vyetAWtxlrGp8reuhm6z1S4icBisD5Eu/KgGnMOnCI4Ih144nZwC2m3w1U5iyGVIyLb65bRBuYkTKkjG7ePM9uijE1YGrjFq61J/9DeaFZksIwRTb1uyeNs5g/9V/ybEMwmXB0W2SLnuSROXwrDwSBRCPmEZdltHPeJNj0V0vM73CbxPybrj+7mXWavJMW+U6Vy+vYAJdMMfyu5ja2YGUUBgoDO4IB9AtdcGuTX42CMDQQNId58nnJJEhzPeVx5kDgVnjSbVZ9oFNnSEHm2gbo2R2SxirX0sTvSpo6iQ4KLcH8Tp8XFwHd1Rg3vxQZKcuyJWZSRh+1zz3ER8kyiBkPKUfqrzRMY4xufLIZA7emfJ/i9hKfGGdrX2M0WQwPY4QwP38GedKBG1Nuc2FM3jcD1HWMA5PGsKa1QeO7QArR6jDkPI7c2sIkX5QXl2AsrMU0dszSRRnaGx+qjUfbTNG1wFzyqDwxgzJ1aJdNXj2MldDwluSTmqS/NM8Oko2ax4mBkx9+bM4u3iZWqszCQGFgWzDAhOrSICG7WZAmdUxrA5PK9PNopJQKigfm2s/fynfaHz+hC43cZbP0RaP1a16YYitPi/XZBnztSjo2jTG2iYotGGbnmRRECsGkvHcBw8D4XDVmwiR9yFf/qnlwg5R0kcdNBYimfekb8ic1QhPEADE25oRWljTTl2SYZDFG88IQlaUtYm4/8NID0hTtspc8sknktXRXtYcEiJbfjUlbxmV+NNhuXj0XBgoDO4sB5k3CMMG3ywjGjcq5/2EyWYMSzRR800ww5t+bpY+ZGp2hEPqMXn8yZWfRLo3NvNBhrqPGG1J9LeADGDvz8lrCbvpvGmPkUHaDEvg25y6ZnO8PmVNpWMx+STookJLcFOULvGlyEXmfZHDoss0nadPBmPnx/t+UFjC3O6YMDY+j3ELmdS1gdBih8WtrLfHAfzayDe0VI2dnJxV53w5o87PhtqO/6qMwUBiYjgEWM0IrCxCGoAZmgsaNO6usWi4ZYqbKzwLMqOgN988s5ZdVhk/UHZFXpcGmuKDbaDaalOQNAT1F59FRFrgNmXlpc2i0NEm7JwxNeNzoSQC0J9IEUwK7+bXGFFbWDwXYFKQs5kiO2PenPIQl2nSwIKQQEsqk8TOzGh/tDXM8RqdHzM+nEcbFL8hv4BYVDZBv0GIqz/xJ++1U3fLHNj/xlndWHRQGCgMTMYAZ+hUXdwr49Gh0XELAjVM349E7ZkMMAjPUIMEcjUTzWIKkAUxUG1w8GKu0Bqxh0jFF2lZLH4rRv6HLN/6snW+iMS1Wsgb8fer026IY8Euihe9JJleQubnHYd7uSZgfPBgbQaC1o20XjfzSGHeRuWnPrVyXKykVu5KOTWIswdFggCQSE+ZEExsslESbgf8NIv1cEN8ZM2qyFgqkGhqfRib1L5+d/F55cHPU1WkbL69rgaTjVxr8cg/N0kb8t+TYUIlG6vBJYpbetwOYqN36xbgx5+3oc0X6qGEUBlYOA4g8uuGjfUzQvQPMoIFPqzAADI6AjXH6KUq3VjEimlef5hG43Ufg3uG26U6adoYhEcanMRT5+sPQtDMNKDTqdPvDxN0D8as1LHt+C7bNzbwuk8LeE418gsfM6mIPpi8NjWI59MMvFA2/gIOWovXwgaYqt+tgM4zRpM+RmdIeXcLJ42CgGbqh+f3kkmwgeBmIwpAtGn8gppvmJwa2euYPC4/ZKYyhWji3viw0MwIpy1Vr+RiUn4BTz/t2AUmST9IBJABsV7/VT2GgMDCMAVYvnx6gEX3waQIhljD78FR3k9PFE8qDG/NoT/8co4G0OhYqykOqrQfWLb/g9ZH1lK1/YOY17v7cvLtN7xKhUbgxj/H5BMV8pQGKg3IYo2e/EObGvzsm8nclDDFGarLbqEwDJoURigGfnJ/9wWB890cKkU4Tc9HFr6m72SQN8FHyTdLwaF+YmnS/mMBhS/VmYmXLlk4qwez0P+5bPlKPxaTZcRar1wUXa1z4aSYBDNRvEGLMbtKSyIzRWP1grvQu+JV7t8JIew5Ft23PTAoYGOmOqVUakOb7IxKhuUkDJDomCP3CrbQhIJ36/MNYHCrzHCpXaYWBlcfAHhkgRsW86I7FEKB/FADT9SsxLGTK8dM1IVteF9AVl3d889e/POjiHjOq2+3dOlv1TLnBvNFy4+6CND/m0hg7BmnM6HhLa+MybiZVdTB29L7l7cq4zxipyCbmI1GTZz+n8iPWwIKaNJuyPy+C6TBFviSz9+OzmJrNcs+8I/SIu8s2EPb1pAk+eIVwpgbmTD8th9FpXz0aJgapL3Z9dfpg42gDs9Fny2cawATVt2Et5BWSiTkZJwbsUxImU98YMQkne0MwZx/nM8Nqo5upff5VbZL2+CP9aLlvmmjH0ggUhAHXnn1+oazPQWikPvPottd9Jgiw5zuI2unm1XNhoDBQGCgMbBMG+oyRNIOQT7JXu9DiGxvSlGFiUmzqrQ6HM9W65fuzKb6Lae/qctS28uNiTMKv1OijD5i2D+oxZp9j0DyVIQFh2t02XQJi8sXwpLsdiykyWdIapXXBz7I9Lo35rUMmkTyuB+2zu3fLu6lrfr6tbOl+FomAQbNuaeLbrre08YGPwg1YP1is7z5D3li63goDhYHCwLZhYP911GeMuwkDNDqOXqZYPsxZ50IrxtxpaGzi/Tlrl5OZltfP24p342aGxkz9QPssHw5vxTiqzcJAYaAwUBgIBhDlRLs2cPTSsPzZK380dJb5MO8C3yW5jswv2BBA67tgXlyxZjfP45YHP7buZphfFGK23vIOq4PCQGGgMFAYGI+BWRjJ+NqrkeNqs9thNEEmyTaqcTGTrh/7dsPKN5a0Q/5NP0jgkozLRcys4+ovO93tV7+/yrfYN90uu69qrzBQGCgMFAamYGAvMEZTdAPMRRvf1XifBnx4LgVdNAX5/gCN03dBSdrWQFOk+W5rp9VZYaAwUBgoDAxjYK8wxuHZVerewUDNpDBQGCgMbBMGijFuE6Krm8JAYaAwUBjYHRgoxrg71qlGWRjYSxiouRQGVhoDxRhXenlqcIWBwkBhoDCw3RgoxrjdGK/+CgOFgcLAXsLAHpxLMcY9uKg1pcJAYaAwUBjYPAaKMW4ed1WzMFAYKAwUBvYgBvYxY9yDq1lTKgwUBgoDhYGFMVCMcWEUVgOFgcJAYaAwsJcwUIxxL63mPp5LTb0wUBgoDCwLA6vCGA+RCfm7in6rdJbfO03xqeHvUuLwgeMHThA4SkBaoqUGODxCWlzWuI15WW1lWBUKA4WBwkBhYB4MIOrd8hiUP+J7nSQOgb+76E8k+SOm0z2bAAAQAElEQVTEKbKUoC1/U/GZae1jgZMEFg3m5W8h3iIN3TvgbzI+P/EZA8sM8OUPLl83jf5TQDhZ/vNHiq+e2B9STjQYMMDzJKf9Lck8rgU/bA7P3b/6sZZR/xUG9gcGVm6Wzii6d7WM7BoB53aa8OqPGqhzlZS/cGBa0N45Ukj7+jl9ntGXRNsa0M6zp0d/ZWje/ikep0pdfwbQfPK4OwMk9EduchjIY5Jx88ChAoKFRrT/Iy/3Chw7sKzwuzSEEcy7EKk2GGiId0rOdwM3C9w9cNzAxQPTgg1hrtPKWfjbpZDyb0n8w8DpAo8IYI5nTvyMwEkD/WCecOnHy/t5/sqG+jdNhrVIVKEwUBjYIQw4q1dN3+heg2fnncB9uMRDAR14fDLQHrRIG3kdG9BY9Krb/rNSmpKSaFvDKdLbowK3CRhXopnDMVPyrgH8gcKTx90Z+ozxvzKNNwQskD/F9O08Pz1gIzw1sT/V9N7ENLHLJcYcEi0U/Bmod6eFbwT8ncRECwVzwpROm1aM31/ceGeeSW1PSDwpHD2ZtNdZ5nWhlMUU/T1Ifx3D5seAtfG85MEb6cnffOxvMGOziV6Scn8LdMN38gLXJEZ181qhMFAY2CEMOKtoAkbh77WypNEg75Dx+DuqidaD9Evk7QWBHwTuEvDXc/wlnzyODRdLzjEClwmgGQ9OTDm5QWL0JNHMQf8sTpsRqg+dXswVY8/jXEF/NE1/sWgD/ZyrlRUpjIkMDQWDbAS7MSt/K/BXKczk+YfE1H2+tTyuVLA5abPiHx0Ymfn8OM+T/s7iPyafljykxSVrQyAF3iopjw20Po6T53MHfhr4ZUB/4rPl+WiBFhwAG+iVSSAUJDooqPvCpD4ggMnbdHmsUBgoDGwjBtAQ9x4emj7fEfhmANN7eGJ5503cpYGEWWf2jUmnUf4k8V8CjYbmcTC8Nqm3DhCwv5YYY3xbYu4ZLpc8zhwOm5LjNNlkTQwnSi46yIKXx7mCcZ4hNb4f2PVhHGOcNLHfJPMXAeZGEkYe1wOtiaTDv0ayIj0MLZJ++RL54tjU/bHeJmW4LNPqa8PfSbTYOqHmS7tmXkhvfYbBHMumz79ooUg/2iKFaeOsqac+0K7y2sDoqP9XSj4Gh+kbu82fpA3BOC+dlD8G3heYN2CeTLw0w0l1+VvhmaQ6hMNJdSuvMFAYWBwDaMPn0wyGlWg9YGSE1/WEPKCHLGrSn5j3acwwRcYGAjPXDOsdzXNswSVmoN3o5rfS5m8D8wb0Er3CGBeZ+7z9bkl5DGrehkkxbnh+LhUxyURrgaRx+zxdOYB5YHD+Uj57Nf9ekteCPs+VJ7boEyZmi8akLIo8C0QSo40p0zdDymPzVy/VZwqYJInszilt7OZAoiP5NabzleTZ1IlGo9H4/0mIxvrVFMEcE60F2iFmhwEbm9hh+V5ymwTGKU17ZI6mxSZrbDCWzySXFDqLFpuiFQoDhYElYsAZpSWOszRhIo0GOKeYw6fTP8GaO4oZ1QUcdC3JMwdKA3r05NTAJBNteaDtoVcfT0+sg4lmDu5EmD9NuVkaZ668igXnWTDaIT8dpzAmwKT6+86k2LUvkHc+t+ckfkjgtgG+SI7lI+ZZwBhoQTQiDmrt8MmRUkhofJvMEe9PYePjf2z9kNx+nvT7BWzAvmRiXC9O3kcD2mOuZPqwuWinX0y68WG6tD3a6qmTxhf56sTqk3iYMV2oGVpkGqU6mGB3A6nrIGD2NjZmf6y0yT9rLLRSDN0N2XEHLcXXg74/mTf90aiHtNdkVygMFAa2GQPuB3CJ0OgwT92zYlEO0Cy0xCU8zOIpycR0Ek0NzjjXizqE967iMbXyAgUI8vyZaCJaOU9TFBdWObhoCsA89VeyrEWcNDC3ODEqQEPyyQPGRhP8VKeijYIBQizVH8NiW3fpha3c7arm0IVEm4rN3iIoSyr7bNrDDLxjOq/IO8bCNNrGSXPCYL+QPOUSzRSo+ObQ+iAZ0UwB7XamRg4UMlffXPItdsfg2WUamqhLPm6V0p7fmnq0x2slxjiNhTb93LyTOOGMwGEsSdoQmHEcNkx1KH9D4XoZi4HKKAwsCwPOo7P8pDT4roBzf9TEzvAnEjvjBHg0iq+QYOt2f6NhKTIYKAWUC0oF5sgsS8gfd/lGeRYoCgLa1gDtwZTR1JYm9lmZOv3OjcvnJ8pQHPr5k961d5oUcOfkw4nhItHuD5AyaRZvSiZmBPj0MEqMjjOaGRKTTJERB7XPEvjOvHfBjSy+PJoU6cJickpP05rY8W20a6cx0hNpiob3obzTwBLNHIyLv/EjqUFzdI3aN0PT5p/iBwWHgPZ8UMaBBMKDCzNus70qaeZs4zGNYHSYKhMxKY3vk0Z5z5SzwRIdFMwb/rRzUGYlFAYKA9uGAfQC3cAcWa36jIAy0DRIgyKIc5u42+DcSxsH2nppMtEOn4FhbBjk+ZKGASXaEJQndNNG0ecGvhhwY9ZFmpYmbkx8QyN5IaRzbbkJr80kzRzQpXOmNFo9b91UW91goWcdHamAaY95FIPBsFxCUZ+fjlZEE/TeBSZGn0xIo+1ZCCaCv0qYAD9LHq3KR/IYC03NYr8u6fMGzIU0xox68lRmnrVhaah53dLArEpwoCEzvXp2uGiK/BMODwFD2tAB2NLBVeOFgV2HgZ0bMPrj0wpaHbo2bSRcQCxo6CMr1bTy8pkjn5YHjBc9cMN+q6xFxuSTMwqILw7S7cwB7+A/RdtZ+GauuBsKmty84+Tj48NTF1K79d1I7b63Z4ttI0GizULrojG1/HExjYu5EVPz3SBzLoY5rvy4dFLN/ZPJxMHMgLFjSkmaO5g/6cglHht3WgOXTAH9MaHmccQ0QtIiaHgnJJA0tee9D5g33CnTz6v3wkBhYPswwK3DYvbBdIkGJFoLaIlLdixbQ5qhT7jQwLXCM/5HcEfr1CNQz1htrmIUGbTVJR+mVEALZd1D2zHM66fFIXeTND9S8sDkMxuriy+g07RYAj+XG+06RXZXwNzmHTEzIq2HFmby6vv2hqnQpwj8YdIaKP/1vGBKmIByPrtgeu0zFuPRboqvBczE1Weqvo9pmRq6G3Kt0Jj/tK0tC4hhY0a0TZt4TJW1ZGNQd+1l4D+3RZmCp5k2SXluwZovP0AbNyZHOpOveQfJrdmuCUY6oN1ioC4HDeUrU1AYKAxsLQZYw5gnuWRcymtn0dl1D4LAzx9IM2QRa/TDGUcnWIvQvnlGiXb5ZMNdDsLxUF1MR38YWQOCNwtUe28x7bDfBrri/getlLkVcHVRRoyZWdflyCHrnjlzSelPH+q6rf/2dILeuVPi0iX6laSxYSUzMIH+wCwqQg3p8rqanY3gQglfI2erzaCMiygQaDExA4ulbTGNye1Qi6AsRgepJBEMUjmfc1hM7fuWkD9TW8qzjauLGdko0iaBzUgjpYExw5K2+DPF/Hg2qoXE3M1VnxZXPdIZKUp9ZhNl+325tUpC4h809n6+d+mc3drkp5XWwBwIEqQq7TO1yuP4bszTu/lz3OuPCXvc4VC2oDBQGNgaDKANftGKJkTI9w10A7QOnXA2Ce0UBZ9qoC9Gwz+ItqF/7WxjUD7roH369IvgzpfoHYNCOzBbdJB2ii5oawjQT2Nw4a8B8yY657vslib2ScVQG7OmoYvGSMlA12attyvLWYTuwC383ZLgcwmLC8m+x2ngoohryS9LGd8skqDyOLIxOGA5fjEjjlx1bpRMv/35osRN6iABWSiMSTmMkkaIEWCAmHIX8cwQLvC4Ao2hpqmxwSb0CYibr/yZLrkwnbLz8+n5iSaqP02MVIRZ8hnYiEy8xmNzcn7b8BhnvzOSH5OBjdaEh34ZjJ1GzFfQN4HSOJkYHDifvlwhlfk+mU7yuB5In5irbxmZKdYz6qEwUBjYFgygRW6Xu1WKmaEP6FoD9JE1zGBYgVyiQwudZ2VoY+ibM6wMIIhjZsowvUpjtkQL1EG/MMUvJYOJ0839PA4GArOx+SMG06A7hsHGpiSid8bG9Eqgn1J8d2f3GSMiboFoczQiEg/mct9ME/j+0K3Oe+Qdc7AJ8rgW1OUTJDHdOCmYn59Y840ippOktYC5vSZPFh+TdaUZo2Uq5QvUttubrW2LQOPDUFtaqg8GWiWnNemOau8Wqx8YwBRtcD8OYEzMBPrFvMzLJqTy+36ROeBBaV0dY83jhoDBvzYpxoKh5/Gg4HdfXRzC1PuZmLFvOG+SDJKoje0AOFhJWg8uHNEYjZcmu55RD4WBwsC2YABNcDZ9j4ie9IEA3j3j6MgdMzJnGl2hZDAtdukIGoVGMlMSeNETTBK9RTd9/412UDQI4WluWwNrFoEcD+i6ndAs31NTNLrp3cHBhd939ulel+Z3y+yK5z5jpO4z9dGmxgGNx4ZRtj9JaS6nuKWkPudxs8d3y0qTR0NU1ucX3vUNodpRnsZGczVOJkVpkwBz1p6+G9BqLSTfnv60490cvNuoNqd2W30aZnczy+uCen4kwAHAvIyzm0/Km8TMMEfzNUZ96bdbnzbpWynmEA7who9umXouDBQGthYDhF/E3jkdArTDWW6jcE4J8Y0GOePdfOW0yfWELjW6g/619qWjVf166m4HGBMaaW7m0/pED42NAN9Nb/lic1MPHd+p8RvHwoDhLNzIkhtgziWxsOMzxZKiMIedkJ4mTa2Zd5lPSFJd8++ketPymJgxRdInyXFa+cpfGAPVQGGgMFAY+D8MrCJjdNnHT6f5s00YxOsz3A8EVjHwCfiJN+ZXl4eWMUZ/eobE5Rc0aLbLaLPaKAwUBgoDhYEZMbCKjJFZwSUZtzUxCYyRej/jlLa1GJOwn73jR2U2WUbnfjkHs2VOWUZ71UZhYF9hoCZbGFgUA6vIGNmmfb/Ij4fZjLNnLzr3ZdU3Xv5ETHIZbbLh932Oy2i32igMFAYKA4WBGTCwioxxhmFXkcJAYaAwUBjY+xjYmRkWY9wZvFevhYHCQGGgMLCiGCjGuKILU8MqDBQGCgOFgZ3BQDHGrcF7tVoYKAwUBgoDuxQDxRh36cLVsAsDhYHCQGFgazBQjHFr8Fqt7iUM1FwKA4WBfYWBYoz7arlrsoWBwkBhoDAwDQPFGKdhqPILA4WBvYSBmkthYCoGijFORVEVKAwUBgoDhYH9hIFijPtptWuuhYHCQGFgL2Fgi+ZSjHGLEFvNFgYKA4WBwsDuxEAxxt25bjXqwkBhoDBQGNgiDOwFxniM4OaigTME2nzE/kbilZN2zMCi4fBp4IwB7R0h8big3PmS6S/7+/NZeRwKW5Z23LR8gcC/Bg4ZqLAYBv4+1U8ROHpgLwX75Hh7aUI1l8LAMjGAgYxr74jJuEnA3xz0txFvn+cTBE4cOFlgFYID/sQMxBgvnxghSzQS/3seHhc4eWCRAA83SwPPCDwhcKzAUMCgH5OMZwduHsAkE21bwBAfn96M09+zPHSeK2weJGc4kgAAEABJREFUA4dK1asFLhX4x8B2h6ukQ/u6Cw9I2lEDwqnyXzfPs/U/TdKnBXv6Dil0yUAJUEHCDAHOnLF7pey/Bf4u0A9ow22T6Axai/Pk+RCBSUH+1VPAethzeZwaDpcSZw2o42/WHjbP2xHsFX8O8Nrp7JGBEwXGhX9JxkMC9uUtEqOPiaaGE6bE3QLqPTmxc3CYxNsaxjFGC+wP5V4po3lmwAT9fcC35vm1AQwy0VKDzXb8OVv8Scq/OEA7687Fn4CycBbno8lfJPiTUvrwZ7CGDkNr25/KwqSNxWZv6dsVfywdPTAw6+FK0QpjMACH9jzN+2kp893A2LBFGc4aAnvatH/FwLsDTwr8OiB8M/89IiBg4Pbpw/LyjcC08OUUIMRdP/FlAxUmYwCxdrYQbMA61acFhKdnpRnCy/USE6afmvhCgUlBW3dNgYsEZqEbLGCY751S/n4BzHo7hGDKBsvcPdPngwM3DBwtMBTOksSXBD4SoEw4R6/O8zT6jtE+NOXg1tyek2cKzq0SS0u0PaHLTFqPFudyeWEONKD359lhs+gWnCa07EEeOX1cMDCvZODvFn4l9X4a6AZ/wxEjR9D+1M3YxPPfUsffhfxDYu0mGgyY8VeTo89E2x5+mx5/EDDeRBU2iQFngpBGOLxL2sCI/M3NPG5rIGh9Kj06f99K/L6A9bXP8jiyr+39D+bl54HXBey9PyaeFuyR/0whRJy2wk2w7DOd5vdMgH9aD6LtnA3hipWGAI2WYZL3zuyZqy+eGM1MdFBA7+T/80E54xN+nKz7B24TQJeGxpKsqYHQhYFNLXiggD3z+jzDwycSOyeJDgosihQEzBMzVBYjp+XeMqXNOdFBAd8hpNnfT0mu/fnhxK8J3DRAgNjsXFN9vjA0ORqPQTh4v+k194G80yATLS2Qdmyqi6VFUkmiCoWBHcOAg41ZvCgjIAwl2rPha5nZ9wNN4M3jfg8T509IAkOF0EUaDmEd7aTNYwoI/hCd1Qb/NfqHwXmfB1gIKASThPV52pu1rPkR0Ib6Rb8x+qOkMYJcK0PIe1PSKD/j3HBwxJf/TynXZZ4EEe3AozjZWx8Mpt8L6djik2Ko6311+b2pADnSSQVswQCXP3XyBJLSffMgnUrM9HrNvJNSbpf49AeAbdy7fqjRzBXMRedMvmDTXCEPTBLaUq75WJI8NpDYLBBz0ZCPUb6LNDYz/+l10tKkSzXJXg/GfI28tTExL1i0JE0N5sNm3ury29pE3YrWxOYhcZoz6evCKcC8l2hD0N6Nk6I9azGLHZ/kRghR3rrYrMzm+uI74Ecwn5OmXePjLz17nuHSWsnP61qgaTA5qmvtrPtaxoH/MBn5zNr8LdbdvjqQPRqXf7YUYILR7q3zTOI2fxqcNPM9R9LPHGDastb8ZfYX04sDmqyReZjrY/Oinv1j3+Z1MKjHUmINPj5QQn9wwO/oAMO9dpnCtAs3l0g9vm3rxg9Eg1AeDpiSXAqDe/W4KtSBN/4iVhkxc1maWShYG2PQj3kbR79BjP+TSbQH7Lk8VlgSBv6cdpisaTyYWF43BNoPje1zSR3KT/KuC/ayex8G3leq3pVEjA8NcM7yuiHgO99LCt85QY2Chk6jBawmX0jetgUEoN8ZUwz/BvMMOzJ1+PwphMgkGjHdUHF/lReLfrrECJM06m9eR9R9k7Hw2kIYMD6miPekAAc2AkY9J2UhaPyFDjJC+pmU4exGKPgJSV8vT5rxUOcnHWIIZd9HEKj9fSKDyCKwFgiBemfaRexulHhowZK8Idwgb0wrCB3Jhg+Kj2da3SOlHlPLKRM/PACvzCGvyDMGkWgtYEKEig/lTUwqdKHH+BymJK8F7b0sTwggYQK+xZOYo/XGcAgE2iMQYPQuCnwnbSHod06MybwqMaGGfwtRBRg0xpqs0WXyn/V6aeLnB/hI+J/hNa8j621drbdymIp8DGQo3zrbT/IRC/tJH4i2Nf1rKr0gwNRCozPmN+YdIyHk/CjPJHD+DAJDXkdMMC5lWSMSK3xj8O3wKtMF9Qhl9iJJtZsHL7RIe9e4wJtTgKCIQcIdgen3SfNs3zFv8v024cs5OXby7U34VO4+eSc02AfSCZCEEXNO1qaC/Wh/6VsfzuGn05Lzab9jznkdwaW9rC9r291f8gs2jwE0E+3DENC5fkvynUd7fds0of4gtugdQ3OOu/sJX0Ej0XXz7ndtLzrPGKCz9twUQO+VvXueCXGJ5gubLa3Tfl2LZDFJwcwsCDWmRCMg7VtkpgITQbwwGRokoiLWHiJGUyPN809qw+WBryeT3wShZz7QFyKECWuPio5AQyKkYGKYA5PPG1IXgyV1I04Qn6SDgrFhEBhod2FaQYQSM0GsjOdtyfhigCbX196SfFCgfWBC/IkkG5cgMBm3tQ4qfCDBhmBfJ1xgxvrFBGibmLyNgFDSitjjHah3pC6i5UIFfNEgz5s0gWRGm4ML+CdIwA8iK38ckMoQcdo9YuhQYlbmYFzWHbO0NgQX6wBoT7RJhJ3v1j6wPoDGYayEHhYD9bWNwJMA4Vf7bpjZL21s2uMTa/nWjLNePuaC6RC+vAN7xX58e15YNB6UmDXBfkTwP5932p596xBhtBgof4zDhoFbOwwAHq1JqmwI9hSmYVxtL7cC5gcn9hcJnzDgQhYGhDm6ZGH8bZ9jSAiESwiYHgHEnrEvxQ67MbjYgWmbAzzDh34w0Na3fXGcvCjbBRo/C0r3HMu3H+1RQqfzRsMm0BircVqzNLcWCLHW1NkyxrXE+m9TGLAOBCKCDaHVHiTA9ukQ5nDd9GDd0b08blkwJsKyfdEF+8Ee66bxq6NRmx2MM+rcmDMhtTtve127zqtynvvgDFBmCHHoNJ/jC1MIHUm0fQHShnqzWKRjg3teCiAGzDGkf4QPEU/yWnCYETyaBVVZooUglZsgRDi8bsAxf+mT1omYyFO+D+piGqRbhLnlM00g5OdOAk21i/gkrQeMmQaBEawn5sGiM19ZAJpYkkaIAsKB+XT7kjcNEGCSDSEAQR03HpuPSQ/zgsvWLob8lrzQirQhxig/m7SGG30glogxJkgAwdhpSTSxLvPAHAgaqT410IgwrFbQuLRnbR1oxFie9o3BMzBHDIgpUWw/AIIB8xGN0XozpTArykPU5WFmmK52Wj4G6YD285WZBexVPgxxK+8Q0poIEPaRMQBzw6zc9ITHVr7F9q+x2xMN/y2vxQ6+OXT7k4eZE/A8A2XM0TPw3Pacd2B/wi/ce9enMnDhvYFxMSkTjrpAQMTQ2lopT5gE+vcOCJbe3R3ouwzsA2PHZOFH+YLNYcA6uCXqXFhbwqs93xW4254kTBJ8N9fT7LWMyR2O7r7xjF6xfhGmvQOCbness/fyvyXtW4Ir5eaOSWIdQ+8JC/CCIf4w6XCT6KCgrHOJTtIe0XiKgfigwluZYCCT2idtkn6YpHBuDI/kTBKHcHUdeBolcyBzGcIJIRCASMuHLDf9mPAQXwfUjbo+cdEe4HNxUBEJ710gCTNhQra+unnTnklq2sZkWt+IEU2JiVH6tDb6+TaBDYEY9fPaOw0Ls8esW1qLCRUkdcSPNvP3o9GoPw5aN22J3w9hwzzh4EutkSXFNCBEGqNygIealY7R0Qq7+eZGK35UEq05aZg2Yr8wEcqzJwglKTKy8e0PG18+SbGbr8xmAW7gvF+fYGUctHXCUz/f/mj7up+3k+/WnmBKy+gCYZNAZ83a+DBaeCdo9edCgBiat7pwNmkPK1MwGQPWgUJhXawTGkeIR8taTQIkYMFoaVsZGxNLifF0gWLCVUJgbOnenclFxsMFxDVFyeDC4HIiKPAVapswPo4xOrPcYBQqYzJurhHWSlroIuOaq+4QY3SYSP3MShojTTL/YI6kC1Il7YdkLR9joTVSdzFRxIWJD9HGMCwMM5nN4lCSUmih/DE0OG30gdRgHN0N1cpAeGNqLW3WGFF3+M1B+7PWW7QcJmKu/G79tmhjcCjduJQVe28Ab/DoXTsYk1hdacuCWXBLGEFE4Y9pDmHugr1CC0EUmO2Y8/i4mGpJgvaG8WJSBAEat0sqfMvqtnxlNgv2NVMRvDJpdcfn2eGF0822v8r1MFFzpBEQYAldTLPwwVe/7D2zyrjYqbHBsb3MZQH/FApj8exMoJfKSNtr4FwRelkb7T+MkeuIMEBB4kYYmjN6wsojz/lk4eCOIEDwxzKroj3ytxwQkKFO2IdpJy0Ph6cF4OA0Nuo2BtjyaU2kcL4b30DaCE0y0IcJMYEyYZk8xsaXRntrbXRj+QBBZRbr5nkm+dJQqObeZwVz4MeksWIu3XrMk0y93bRZni0o4QFBGjcemwWR5muFj367NgFpSjs0QqZXOOuXY3rlX1NWv9016pfdzDtcGyvNjclwqA3rAoeYI8tAf5zSMW2E2BqRHlkSaOXWn0kQ85evH/uA6ZZvjsnEt7MEo6G+Z00jRNBMWRXsse4YzVH/3bTWrvGoSyg0h5a+SLzddZ1VBMhFJVI38zpizD+M4PT3qP0IF86UfbXd493L/dmDFIZmYkczaUBcN/IAdxELEK2K75cCQoDfzXixx9A0pmIxrdR8KESEb899cN4wT3QSjZHP+sGSxwKChkjbFnAohjrihHXLEJHr5iOatAGLbcItz0RemRcmPyYfk2OWS9KIZgkxYu8k+OYr46eSBiCm9UfbZMbFSBBL+Q2049IIjcQCtPRZYlKaX8JxSQSDxuDVaxuWZON9VjBm2rMNTQocV4/P0JgJDvruljMG9R0SJkW4dEgwyFYOE7FW8s2B1IWIuWTRLae8cgg/BuB9HGCs1rmb73akzci8a627ee3Z2tL2WAMISupoS765kBTFiDIiIN2+cLmJiYS5hJ+PBaHlw3vLJxSQrOGBoGAuXULhfdrcMHVzwOD44VwBhxcMAP75O4aYrz1NoLMPlTX23QZwh7higsx48M2NYQ8OzYUFRR3f3DnbQ2UqbXMYcDbRMQxCCwRKP+FmTRrYi84zhYOW75LauLOnjXnB2XF3AQ3uAqHa7fNumnf7Yd4+xpU3f6ZR+9B5H7cH1SfQESDQ4kZPpBNU0TwX4rxvCyAWQx0hDCbCdNo0KwNmKiWFI9AuKHTrYoRu3yGKCGBbXMzDBQg+JG1YKBqlm5QIJubmQCJUTKcYH3+c6/gII/sybc5YSQ0Wz2ccpAj9awvjYH5URhrCKx1xQxylNVAXYTcXz+bCFo44kJpbuW6MGdjc2sWMMBTzQPwRcqZiRFWfbOHGYz6tDWP1iQZiz45PczJWGjFmyfSlPpwwHxBKtI0J2KguDCF0bmpqEyOlEfi04B5JsEbmz9xgjPBNMzOWZA8Ga+xTB9YBa2Qc2mLatH7mCCegOxeN+QxA/+YBd8bf8KgsPBoPfyMzCEamPTjj26C5y2dm8aPr8glJ3Xx+VmX5rjE27RojxubZjWA3UI0PjrRhbA3sRV0u8QoAABAASURBVJ9LuJzisxFjBC5EaBvzbGVbbFwuhtGEtdvSW2x9pdujcCYdHs0F3o1VGiD9Igxic1OPH1ke8Gyf2J/OhTTzZ0pWHpgXAqo/506ZLihv/6lP65BHQyasOW/WpAvOkvaUA86Hdu0zFh/CjvSCYQwcYzQaWUc0rlvCOjpLfi7Nejjb3AMEP59oIfjd8rM8Wyc00CU7+71fx7pZd3vkkP3MGd7tC0LgDEU3FNGfvWuO4+gLxsYKZL+hcW5gu2zUbQjdMT80S3nn0UVE58Vtc3PWvvnjLe644BXdNrbs2eSGGvcLNyR4BNDgaTMkcAtNAnBLErPo1vWOEAH1Wh4GyebM3IqwM+1gdD7DcLlGPWY0EitpCUO2YMbAB8V0SBuV5taU6/fMcupBLrMEIuLzAJ8iOOTKuSWLWGJENM82Hlf3mev0h2j6Ho1UB/EYVyvXjREMl0T8qDpzq/mpY4MgQMaKmSPGNjRijzHpXzukIUQeYYcPZmXzMWY/y0VaVEb/GKMNJY9WDDcYjY/wSU7aY47wbjxuftKCvYuVRdxdfiFwKD8E8ozXhSgam0syvvPzziclhktmOL5ETLC1YxzwQUhwKN16o+Uiri4fmAdhAKO9dCrBuXRrhZHKZ2alzTkYLZ9PBhOTD6wdadra8NnYL8zJzNZwyTyIKLkB57MIzCndrQX7xkUbzNdhg0/Mw2cW9jJ8rxXs/OdwwqHD3yV+Dq52zMFhtUe1Yx/zm8IRBmcMiKM19DkQImr+NDZj429FQK05wUKaPWh+pHrCj1u6hAh7nhWCkIMh+64U4SAEGTKhiGXFHLWjTQIT4dI6IExdbcAzszbBAEHVhv1pv9oL+pZWcDAGnAMCI0HaWqAv6AfcKe08EEjulhe0AGCMzqTnob2WohOD/YQGW0dnrBW2F9FOjAYTdgaYYwmMrUw3Rm+UJRROA2fMXujWb8+EKHRUGYIXgRA+7CfPrRx6ij46L2gkmoJftPwWY+zmx61lH8IRuo4mUASce3tSOUoMK2Wru+XxEGNEHBBxxNVtU0TSBiBFuzCDcCBa/cFBHKZhciTylk8TQvAgEWKp8A4/tbpJACaNwEMCgsuch/HRKBFd/dsEGAFi0fqn+WkPYhEzBInq7ZIBKd6Y/LUBCG7j0S7CiOmqhwC6+IGQtzL92DhpE2zk5oAJatdVbCq+RSXVIJQ0CRsFsdZXa0sZ1+YtepsPombzdMvRkhFQ2jEiJ4Y/eGxtiZWz0R0IxBLhgxv4wARszm676nTBeKwxAgu3bo0RYLSLaGMm8IfoMoUwBXfrK4eJuVCknH7hB5FQzpgdWD5EAowDjim2fEKQA+vgtHzMpOVrw5o4+IiR9SJUmTPcY4j6tYetNQbbras+RkpaJcAoa+0cUntcfh+ss71PIHH41VFGeQTA/rRnaIJ86dbOmltv6YgjwY3gpaz68oBn2qC9SWCwZtLgl1YNF9wG5mVOhD3tIcra9o5JEgqMCcG1bsaiHQybKU66ecOR9C4QJtTVlpgmKo32YB9LKzgYA2gKE6h9aC3g3LpTGJR2lgjC1tm62mdoEbo26QyqiwFYK1ai7v51fu1bdKRLT+1Fn1boB62xf9AAwqX2tgqcDXQUndCnPYoOYoAE9dYvoczlTfsKzScAw0/Lb7FP/8yPVbLVNzfCHyER7cNz4LXhudVdVjy2HZMbmzlHhnYQUloFxjhH1SpaGFgpDNA0mcYJJIgVQrhSA5wwGISSIIvx8Wf1i7IMIDwYp7KEDsSYBaMJm/069V4Y2HcYwNAWmTSTIWkTkBxoCEMHcpE+qu5yMYDQ00oAiWy5re+N1kjfNF7meJe0aAK7YWbWlpbJPMt8y4rSxk26Z+42N9I/F4D1JwSQ6lu5igsD+x4DizJGZh4SKnMcGzw/yL5H6lYjYIH2aRJMGEzSzCGuQjN/Mmks0OyerMrczuTpjDB974ZJMkUxUTNx8ydigsxQTORM2aw53t2EZL7iCnDRasjUtRvmW2MsDGwJBhz6RRp2mYYjnxmVP9IllUXaq7pbiwGagQtU1sza8zHxRzKtbW3Pu691WhV88fe68LMbZmDMLl/xw9IO+TQxddqjC1QuVijj0pWLUMzG3nfD3GqMhYFtwwDiuG2dVUeFgcJAHwP1XhgoDKwaBooxrtqK1HgKA4WBwkBhYEcxUIxxR9FfnRcGCgN7CQM1l72BgWKMe2MdaxaFgcJAYaAwsCQMFGNcEiKrmcJAYaAwUBjYGxj4X8a4N+ZSsygMFAYKA4WBwsDCGCjGuDAKq4HCQGGgMFAY2EsYKMa4l1bzf+dS/xcGCgOFgcLAAhgoxrgA8qpqYaAwUBgoDOw9DBRj3HtrWjPaSxiouRQGCgPbjoFijNuO8uqwMFAYKAwUBlYZA8UYV3l1amyFgcLAXsJAzWWXYKAY4y5ZqBpmYaAwUBgoDGwPBpbJGA+ZId8s8MCAvwmXaCWCP8h61ozk/gF/WSLRWjDeW+fpPoFjBxYN/orBtdPI3QJHCowL+j1HMv3JnzMm3s7wd+nMnwgzRmPIa4UlYMDaX34J7axSE/7W6slXaUA1lsLAdmFgiDH6e27+Zts6ZDDt2d9ue37eLxM4XKAb/j4v5w3IO3LiVQkXyUBeGrhTAAFLtBaM94J5ulRgEiNL9tRw+pR4UuDxgYsH/K3DRIPhkkl9ceAOAX8WKNG2hbunJ+t3x8QnDlRYDAMEjTOnidsEfhnY7vCUdNjOpvgbeX9UoO3nq+VZehdemTR/Ji7RxPCT5D4k4HwQLvO4rwPa9rZgAC6flfhEgX5AU/ytyw8kQ7nrJD5UYJZgL10rBf0dUHUJzv5+apK2JejLeF+X3gj4xpPH9eBP1L0hb8bWB3/S7LDJmxTURyO/nEKfCdw+8A+BlQxDjJHWd92M1h89/VXiiwYwFHClPEv7j8RvDfjjpzZDHkd/yn9XDpwm8NnAsoOx+sOx8/5RXeN8eAZjPonWg/FeOm8I26J/b89CXz1tfT8wLbw+BR4X+Gtgu8MD0uEtA38IVFgcA6dIE3cJvCjwzsB2h5umw+sF7G3CmL+76A8UO6NJHr0w/50/8PnAcQPOD83263meFpwJAhTmep4U7hPKJO2LgL5dLDP192bvm5iV5weJPxRAO7p4uWzSWGPunRgd9I6eTmMArEiY0g1TD3NkzcF4X5B3dDfRzAGD6ist0yrri9Dsb7PaQ0cZqHCGpJ0q0J0vmozh2X/+8HWyB8PRkgp/lAK4OE7eCV0UiaG+kr2zwcT6I/CHS0me30vG7wPiRGvhq/mfdGwBTfZNeXdoEm15sCFJY/N25K+T/zyVJi1csrctGM/P0hvGnGi7Q/W3JAzQylgh3pj2PhbYidDOKoHM2eye1TYemp90Gu2nkqhOopkCzeAVKem8b7d1I92uRDhlRnHPAIHj/YkJHYj61/Js/RthF6ON70s6jRHtfE6eCcxdF06SDgrM1g9OKreOdfxhnm8ewOCukvgwgVnDJVKQ8NNlYEmaGL6Z3FsFHh1Am/p7hMWAEEhhYm3ArAGa/JLUoTH26yR5LRAsKEzvztvpAup7/06eMUo0fYgPJXvnwmYG9F8ZLq2HNHr4PN8vsNU+RYeSZH6C9FWhMLDTGCDhN2ZBOPzbTg9oi/o3L0z/CGn/toFDB/ZTwBDOlQkfI8DEmWgt/C7/o3/uLnCj5HXULGsYWxN6MRym1AunwDhGRYO6YvIJ7l9K3AJB5qN5uVBgXitZqmwqmJdxDFV+cxIxN/Q/j2sBXuCIxWwcY8TUtctqR6hQ/x2p/dCAuky4m+FDqb51YbMD+nOGxE/23cSnDdAaLR5TDdMl6SLJ6wEDvX7eLDwp9IN5Ji2QJvK4Fph6mA7YoDFbkgSg5j8jJZg9MchP5PntAdJHopGLM4/Ngw2pbQgnvSVpYjhmcplG2NRPmud+kP+0JGqTbxUh7I43WWMDqYgfwsH4SErxc85aF/Pn5yWR6hsuaCdpZkNwoOD0c0lVjtR2wjz3g7VwiLX3qmTaiIkmBji/c0ogiqRC6/qFvLMk3CAxxqB/h5b/lnR7k6TLJ8DIz+vInJn6HHBjVNYaygP2H+lWvn3D7GfNm6Cl/hVS0Djekribz0ehTeuOaBuPg+oAS3dYz5I6TFTW2KUjpuSPJ41Ure88jtRxMcu+gyPP03zk6iBm2v2xRg4AxsH0+Nq8818zpzGzGg/zOSIB//xHX0kZhAZxzePo7PnvMQF72X5kklMPEZGHsDLN0UisxY1SdrQg0EicAWPRF5yaQ7fZH+UFLq2TvZnXfRPsEWdP3GcY9qw9RxskONDs0EXaeWMSmBuN3Tlh6h5CnLPC+sa1wiTZymjD2UZL7IeWvhMxZuZsd/u2H5lWf5FEpuVEg4HbxrkXdwvgAb/pJqzSswXf7Hi+lYqfDJCI2J8ddocZsqQlay0gBnwVGAsVGiPF3J6Z3C5zc5sVs1UfcXtE8hERzOVyeXZphPrNrm+j8WO6NSed6YLJg43cAUaMJl0uYRdnDkH81bM508VasOCkQGYQxBpjYQtHVNn/5a8VHPMfRk1QwCAQRhvqqSk7SWpM9lowFkIALUS/TBfXSM6zA41Z5HFECHHxQvsOJoYhne/I5R8Mxfup89/TA4grvJsHk5DDnuTBcLKkMqlYS+YSkjBzGrw/L3nwgDlihs/NO58En8h78szvom/4BExDxmfuGAmftPWyxik+so7WCxB8MBOEWl356ll7gCnI578haT4yBfhFMDHzsS6IEEaMoGDAmIxyZ0tZzNCewwDtT3tfXYKHfQU/LkRhpPbiEVNnKOjHfieEYBgIWCunL+fAesCJNgkv0rULf/BJ8NEGYkuSNg9Mkc/Qmqpv3ZjYMC+XFjD/36YjeeahPJwZT5LnDs7ly1LLXieM8KMxp+kDoXtC8rSN2H87z4i3ctLyuq8CwZ7g3p00bdq7vWSNnF3mU3tQOmjvBAp7VNo4sBfhuJuvD/vUfu+mr8KzMdmr6Js9M25MXEf2eT+f4qEe/zfG28/f0XdI3+wALBopAIIQMocbYey3Z+MgsKRchFsdkjKCgnArjwlgVpAEkbQsxKCZJJTpg81IO9Snm3bGwweAECHuNBh99+t553P0qQbG7r0LNigCIY8WhjC8NwWMHwEnJeZ1bEBUaIsOiLliDnwG2jTmcRUdPoRcX/xW5gNPGBCtjWCBKMH1v6cR47hrYjgipNw4z/BH48F4ME8MmQmIJq7cu1IGc+xKpknaEGhgmLG+9YGp0vTVR8StDa0IbjAsc6RpGYN6mIo0TAzjw3h+nR5oapgqAoK4m4fyJOyfJr+1TxjJ61rgn2GV4PdwuAhLbgauZeY/bUrP43ogwWJ+5ujiA0ZrT8ErrUifNGeHkTYKz/wkJHZaKSGAcEHoWm+082DcGLzxGlsna2RPYdz61hcBDS5okPBD+jd+9Yyb8IVoWjdMzt6RThOFE/vGWI+VTgiT1sLeTsaDAAAQAElEQVS4CY5wQthoGh5CY24YcBekmUv/rJsjjZo1gY+S1kirNTa3El3SckbT9ci5NSeMEUOVth/AvmH+Q0cIKWhdmzc8wKn1sieUaXnzxPadtTzKaDRyzgmWrb4+7E80qKV1Y8LfVZPQXW+3Z5l/rWE3vc/YU22hQHC0r/it7cl5GoNHgiPlBl2dp+62lLWwy+qoLXC/PVLTE5PILGmBEW0ElfkhyWuBDZpGhPCR7DEABIG5Yq3AwH82kQ1AW+wuDEQjIq6ZYw4DVdeSHHQbcu2l8x8Cg2Frx8GQhcjRoDBi85Q2KyD8mIzxIoLj6tGsmPswsu58aCU0IEyZ1IlxYyyYEeLc2mPSo20yu5w7iTQsmw8RbeUQOoQPsU6RqcG6MAe1goiA25e0ccKMdDhSrjtmG5/52GF8WAq5xQzMgQCAOWK6zHSIOxMevJMglcMUUm0kn5WBliuf6YX23PKVmQWstbrdsgiZfQjnhAX9EiTgDCNq8+vW8Wzc5mW+/TblA/scQfXcBXgHLU0ZZdu79dGm8bY0sXfpnoEzBeeeNwtDZwMDND+4dgZb28ZpnZ3R7rlt+Xs1tsaEEa4Ugi0Lhr3N1YDxmDehQjnPmwFns+1pFgNWNHSZJk94cSaG6NRm+lpmHePUHjokngcwVJYTgti8Z3mefjZd1gJstjKbOSJsU9COxENtSUfsMRRaxr1SiGTscOdxLZCYaQqYInMTU6KNQWJeKzDwHzWeBtYnEAgP6df4wEDViUkIBu3VhkWoFG5z4N/xLG1WUB5hQWhIgOPqMa0hSl28KIsgIljmaj6YI7ybp/wu0OYQWj4w+MPUMOZumUWe4aO1R2Ic15Z5Ih4ODS2R1gZovxgOLdo8mYPNg7WBMEPbsk8QA23Lx4z5OOXbO5hEf82VnRcQeJYMJmBatvHp3ydJxkgwG2qTRI+pWs+h/J1KIxgxUyOyXZDmPGBs3bHBpz2OySP2LQ9uad3WuqW12LxpR+19P8RMhVw0BEK0iSDOGuKMIepoFzzal318OAcEWeXgtZ/f3tFHGqm9jvahhYQQZ1371raV7cZcAKwS3fW2n1nOWCO66e3cdusv8szaQmCwV+Zph2Ds/DPV0zbnqbttZRdhjKRqkqXFpFEhaEMDd5D4yvijLCInNQLORNDKI478kMxJzHZMPK9JJq1vHAFqhxmTSNH14EBrG/SJwXqhKQ8YFILRxw+zFeIwpfpgdhvXYGYSzcdcMZS8bgjmAszHmBDnSeXk+1ZoQyNLemnjEE9rko+Y2ZoZsQskYHPhP2aeYzYnQGCQiA8TkbYRpW4+BmkftXxlFgG4JHAQwLrj89yYc79962js6sJzP3+3vDNDwzuNnH+RJYcpmBkf8TfP/lzMG/TT9/K7+bKyMEnzAbosxZLFKoNGEToIeegWRkiobviwR9A/TImA29L7sT6Y/2lRzgwXhDbRV2b4eZlPv/1lv6P9GHnXqjZLH/DDJcT9xX0xCw2Zpd2ll7Fwm2nUR6Ts1wgUJkfCGdcO86Hve5gk+AKHytlwJDD+F9IYzcJmJMXT4Ibq0FJtKCZIm69fxobdzIYi3dnELpWQbrrtuknr0kU3bdozhkfyQ+RJeOPKkwoRI5dchubjg2uaJ+lUTCOkQfbbM3ZSJm2NtMps2S+zyDuhQf8uZIxrh7CE6TnY1qe7z9R3QckcmWO05dILMxV/lwsrLAfyPVtD+Uyz8s3b2sgf1/8s6fBkjPzRNEdCSasHbwhUe+/G5oaREpK6RLBbZrc8Y47OJXwTTOGX1swn3J0DgmYNWXr6ed1y++EZPeJ/tXeY32mKzqSLg3DkrLe9ZB+ha+4rzIMb+xHtI6DQVFeNgbhcaM40xlnnRYgk5BI4XSxD69R1joHnlQELOe9gEHoMwsUIxJGpjFYwrh3Ew+cTyo5bYMTbhRLaGITbZIC5S1pr2wEl4XtnMuC8JbmpLw0gvPrkW7MI0uYBDMrnAXxNCLKxq88uzk9oHt5nBZon5kBbnoQnQgEJzKbrasGYn8NGckSUjc/nKg4PSb87DnigvbsKrT1SJ7z2zZ5wqs1u3f993vg/XBN+Wqr9QlKEH+bdlt6PaX+EJf0wm2BqNj+CwWTslqiD4qLUmQ5UxsjdvERwrLu+uvkuBfE1tnxtwQdrg/lpT1P6Ibip730cIGgkfiZ5zMD6Kmv/wGt33tIbsIzw+3rXr3g3Aj86Am9f8m2x6vBRExj687FX4JOkD+f9/P3yjtHZg86evWnPtrm7uEVwcNbtIemsOvaZs9gYgfRJ4Ozzy1sH+9J5H1fe2XF/A4NuYC3dGm/vLSZQjmtnnnT03+dD6CvlZNa6/KXw5mflGl12ftAG+2vWdralnM3e7wjBcbkCQUdgxK0M6do1cdfNbQoXJxwW+SQpxARhogFKA5zTJGxmUQzLAmGqkEKbpBXYDLdIYT4kzI+moRx1W13EyAbBpNjebT592JyIqEsxDrqx8xGR5jFWBBpx1o92LUy6WQv60JayxrWWmP/45dwq1a9LIYggZuNHDdzq5MNLsYMChg4XmCfp21gxNc8YifE4HPozHofHwWkN6Q9ejMuVfziR59YZ4t+0bYSJxEVTF5svnGPkpEy/0gHnLvxYK5dwpBuP/pjOjEsa5/ekTakc4cBtyv/P3l2AtxJcVwBWvjZJ0zAzMzMzMzMzM2OTNMxMDScNMzXMzMzUBhpmaLBwfuWNu963smVbkmX5vm/um93hOTt7aWZl42X5w54LjpAnVDxHDMMYjLcRS8Q+ghOcTsVaL4SaA1bmCkfP0BgoN9YiN5X69nIxFGtKvkNWLZ+XQL41YQy0cYeRrFNzsffhmlDXL+ZijPrSdpesL+OEkWfrOfM0UPy4U7tl27X+PU+eBeVauphwZg3rzzOWhsxD/56Bd0sago3y8LU2rWXP39jlw9RctIcJSkPWhjateZhxm3s3lZXfJRYLoa9va9M7Ip9ywkrH4My7EZee087WqXIYIcveGlR2knKr7KqStU8h9D2e50qhcCCuO1+eDesdptzSnqcDOtag9dLKeh4sc3u8yrR0vNbnYLYKKJ32NSetwVbHs8L7vMuNKDjqUkhbmphi2eoNxdYFbxgvmfU0VEaadWe9UirxV2ld4mmxP+8UOHkgj3Juz9O7SGlvaw2GlFDvunJLQ5hNfzCYHi2DQMFoaEJtIhaGF8VESXpCA7PHGH0T6KF7gQi5xgBoUQSel92LBVQPiosAMyewuHR8buBB24hu+xzqeREBRxjz7WOUBBqfPgsL03R60cPAeD1YP9UkzdyY7xacfS2fcDiJSBBqG8PxcI23PUTz8VDtKYjlGxchbMzaHCLz9g0dItQtfK4QAtUixcTVgxvhRNty0o3CIF2/Fgomb6MeBnCXTtgZv3KIkkAA+MFoeRa98dmb8BJi3gSHOZobJmg8NEkC2ua8PN9acmVqc4iMkYbn5Ya35+XZe+4+w7DnB2efb7A8CNLWjv7l21PgRjYPz9knFBQI914SGi7MzAEerEbpLZ9b3dzkmwuNvdWHuXFwuzu0YO2ypuVbt9YWzRv2PoVxmKcxfOOkBBmPb1q5CD1ra5wyY+7KDJE9I4oHC916U0ZfDrr48F5dCoXxUHYcgqAI6Ns6tg3BojYvAta84EeTprxQeAgxc+DmxHRhqT3KCSvBGvHemb93FRbWjDXhvTUmz4XAx4BhxLvjcxTvoHVgruasbCPzMB7vjTQMm9D1TCgN0vYTead4p7wvBJ9nZ1tjCAO/BwpjzwfODht6ZpTmofItzRr37hMS9nk9a8+85U+KPXPbMwToZkShntQOwW/tElzeF7wF76IE9OtIs/5t1/Tzhu4pz95Z7Vqz3utWznrHE3i2WtpSxEOCEaPyIg0RNxjhgil0XygMxstEGKqHeWKGJolJE4gsDfV9VIyxeuERYccl6kE4eEGoIC84gagN5MXmZtQG64nAlM61SUvy8uqbRdJdVJhF0+DkE6AYJaaECUkjqCww7TUyLpvh8rkBCMnuQ23l+jFmg6moh7nRrLrz8LJ0x+ObtW4bLCtCmVWgDYrAkPDysvlmkMWtnPl4ObptGS8NlGBUxicnBJ15ecm9WN3yQ9eYM6tEfZ9bwNt8CGRpjfxVlX57nhHr22Eq5XgYPOvWDwbixfD8MGuMAe7dfIK+5XsO7lu+mNLCctM+QWCdEHSsQGldsnYJKPUaEWLm4iQqzAlFylzLH4rN329bEnQUGe8RxsN67/ZH6FIq2jOSBwuCkoLkfojkObFH6evma48XgAXYTW/X3j9MqK0XlknLa7F385uj0YgF6j0m3FueGA5O6WKA5uXZszYJBnMcwmOV0yhaMPBO99/l/rytd7zO+wZfz9la6Zaz3qxTZwkovvK8B3iRdOtfO9IXRXiJvj3/RpRg73p/DAwX79EkYUZRZnzg1XgqAdpfx60PHg+WZFeW9PvblXsLf1c6rk4LgT2OAOHJ80EoY3JcUXtlSoQexZOHpa/MYOQYInc1DxCPBuWNArJX5lfjLAR2hEAJxh3Bt7KVuc/sd3HVsW5XdqI7nBjrlfeC+9d+4Q6bW1h1GrotER4HrkKWr87F7nlcCEyHQFiu3K5c48oULR8CNaIZI1CCccaArkBzGCP3qY14VpHf+bQX2d0/XIFpzmQKXF5cZyxHLsmZNLqARhzO8os/tjW4hFmD3HoEIXe8g11c49zgyF7QAoZVXRQCy4FACcbleA7LNAp7KvZ42z6AfTd7diyIZRrnMo3FoRR7ucs0ps3G4nn6sXh7/+1ZO/hhLuray7QH6bqoENhXCOyqYNxXSNdkC4FCoBAoBPYEAiUY98RjqkEWAoVAIVAILAqBEoyLQnrl+6kJFgKFQCGwGgiUYFyN51izKAQKgUKgEJgRAiUYZwRkNVMIrBICNZdCYD8jUIJxPz/9mnshUAgUAoXAQQiUYDwIkkooBAqBQmCVEKi5bBWBEoxbRazKFwKFQCFQCKw0AiUYV/rx1uQKgUKgECgEtorAMgvGrc6lyhcChUAhUAgUAjtGoATjjiGsBgqBQqAQKARWCYESjKv0NJd5LjW2QqAQKAT2CAIlGPfIg6phFgKFQCFQCCwGgRKMi8G5eikEVgmBmkshsNIIDAnGZ2TGPwr9JeTvzX03sT9Pc6TEwrXy3/dC/mzN/yb+aei1oZOFFhUOnY5QormGI6b1IYySXKEQKAT2AQL/kDk+OfQ/IfyuS79I2k1Dfxfqh2Mn4f2hm4WG8pM804AfnictPib0ndBlQocI9cNRk/CgkLH/OfH7QucLbWWM/jbrOVMHLl9O/JzQSvHJocncOpO8QsiEAQy0O+f+VyHhZfnvHKF/C/0hdJPQlUPfDC0iGPMF0pFF4DqXcwkW2gPT8lFCFQqBQmB/InC8TPtooZeGnt+hN+b65yF/4JkBkcu1gHf449WnW0vZ2sUZUly/iaYOx0nJs4XUPW7iIaFI0b9d8vy9lyTPbQAAEABJREFU1TckfkvoVKPRCE+/ZK6H6iR5LchnAJnbg5P6+ZB6t0hMcUi0GmFIsNCIfpjp/Sz0g5A40brw69xJ/13ib4UWGY6czq4aovkkmlu4RFo+f6hCIVAI7E8E8Ed85tmZ/o1CN+4QL9rXc/+lUD+cPQnHCm03XD4VzxQiiBJNFQjop6fkW0O8eYkOCidMym9Ctw+ZD1KHwLxb0g4b2iio/5AUOEXojqFnhXgP+4pBkvd28OD32gxumwFfJXTI0LwCret+abysxYBQoRDYpwiwgj6bub83ZGsp0VqgnH8id7aSEq2Fo+fqUqHXhRgZiRYWjJcXb0hQEbLy35nREGaJRr/Mfy8MfSVk3CzdXA6Gv0+qbbSTJv6nkDqJVjPMWjAePjDdJvTh0H+GPhe6YOhQoRZoJzfPzSdD/xHykB6V+Bgh4dT57xGhL4S4TPmxv51r7l3luHqPPBqNnpg01ipNJ5drQV/nzZ0H/o3E+uf2+HSuaXEWCM2HO0D/3MUesr0AdWlDj0zZ04SOH1Lv7YmN6wiJaUofS8ya/kxifc1TSKeLCoVAIbBLCPwp/fYFzTGTxoVoO4mwye044Ke2mQjSvsAcF9jF/wjpL6Z/fNV1LseBO5j3zzy7cxlndv7DF/FeFimr80TJ4+49TOKVCx7krCZ1uDR0/xChQ2M6d64Jnhckvkio9XX1XDPl75P4JCGC7fqJrxGilahr0Vl8p0/aY0PMfQL0nrm+WsiBIAKK9mKzOUlrwTgum7sLhTw0Vh9BZ4/Agye875E84yM0T5tr2t1DE3NfcI/oQ5p+zpJ0btXvJ1aGK/eiuSYQf5LYxrN9WAI3txUKgUJgxRE4V+bn3f9q4m6gSJ84CRTtrvBJ0tIG/Ayvxe/aOZKhwV46iSxKSsINcv3wkD1KPJm7OberE5qwmjSjkyfjX0LP65G0Cyete5LJ/VmTRpDRKAiVJ+WehUjYOcmU25HTrbQU1hxBxar0QGgf2iMEPaS/jkajj4QI10cnZp1Ns9ictuL/b+W5Oz6Y+tqwmPXB8rOoWX388bQoWBDqKToYCGuC8ynJtbfKp/+4XLN0L5aYEE5UYTsIVJ1CYI8g4JQqfubACj7QHTZF/sdJwGcSbRoYAjxhz0zJLo/lpr1TL40C7uBLkmcW8DyKP4vRwaJJ/JUxwVjgXXtPeufRc+jyFbm+ZeiaoZUyDACTOU0MhNvDksvt2CWWE1cowZbskQdsXw7IH08CoYG4MwkhDxS4yRoRqnzVLMBTJoHmwfLL5bpAMPKXr0vc4o19gT/26jg4ZNE9IOn6YFmyYGlOSRoMXKXmdubkmre5oefmnuA3v802rlO0QiFQCOxxBJz+PEHmwI3aFSQUZIYBwYHvpMimgfXlkw78tMtf352aLwl103xigWcmeWaBN40376lpkUcs0WBgKdqDJPBZwz7zwJtfndIMF/x8pfjfZoKR35mWYPJdIjB/G1DawrA3x+JjeTmizJ2AHBtmoV0uZZ10TTQiqLhQX5wbblDWob3C3C4kEObGQCB+ID1eN8QlYCM6l4PB/LwMn0ou16u5oTY/GtOy7SlkqBUKgd1AYGX7ZBVRkFmF+GGbKMXZGQVeKtZXS98sxj95y/o8Fi8ihPTRSBn8eLM2p81nzHCP8rDZE92sXhsrgdjKOkfikw0u5Gb4tLw9HW8mGKedHGEDMMJjI8tLe/YSHahxOsrpUgdZpC+KPMB7pzN7m/Y5HQTa7BtM8/t96hCGXMG5rFAIFAL7DAHbJbxGhBVB0aZPWOJr+J9PIJBzCCwt31s7V9G2klqd3Y59iuZAIReura+NxsOzZsvJ4UUewH5Zecr00/fs/awEI9OaFcmtyKymQTVQLA5WJIEE1LskQ9k3JZ7W5ZCiMwtOV1nETlc5PTtNwzQ1GptNZsKcttXqWfCsyJVyJbTJVVwIFAJrCHAnUo6dW+gKRhakcw39Pce1ikt24eChMxO2tWwJGR5rGI/m4XO/RrkwL941P3TA/ZqkdQEeLN91iXv5ZlaCkUX1tgDBjeCU0l1z3QQFoUg74U+ncQGWhsKdmWLbClyb2vEwt9qAU6uEmQNA3cU91I6FwgI2P598GPd9U9C3lOaSyxEN0s8jmZ/7okKgEFhNBAhGnqOv9abHgnT63gGWRu9KGQo15fuVuWZVJVoX8DHnGxwEJKAa8WY5bOMztZbmsCLLdF0D27jxOQkXqkOElP3WhL1Gp/nxupbWYtagj/nxTqfxm2HgsKLzFQ4i7YaR08Y383hIMDq66zMGEybUAEFTaGUJCz89ZKPZQrF/6HcBuSN9rkHY+LkgWoaFYcHYe7QwaFb82QSlk10O7Nwhs9I+TcwvRvjVB8KG4PPTRfK6ApDwtZ/HDeBbGp96WGBpZhxcG7cDPYSak2Is1XFm/jNOC9GvWMjzraQTV4Sl/owBBsqwgKVxi3jwXK8Whb1R8zE/31P6Pmgngj7DqlAIFAJLjoBvm52VsP83i6HytNlWOlUaw/8a4Vt4ULsX+0LAN9UpOhjwZzwP76S0E4AOBHUtQPz2CantA30HefDqRn7v2qdq7h2KNEdePeNIlREeh6/7VAO/5HnzzfqHkokSrU4AZn82/OEEgZNRwLp2CnAfAjuXI1oLoeKnkGhHBJSNZ0LSSaorphDw5TnW6+ixzyWSPA6Ei2O+hC/B5hdmnL6idSngodh8pmUx97XXfbi0KCe0HJum5bw8lSywRONgMVxyNBox7x3scTCGRdfm6hMNfX40pY1bXd81GjPNiEtAHzQkp7WMk5Zo0fDHm4/FbH5O1HIdO4mb5ioUAoXACiNA2WcJUoo3mybB49tplh5hs1n5nebjz9dJI7ax9Gu/08FCVl6SR/gf3sraxbv65NM6PE5ZnjFWoHMgzo5I4xHDa/3IioOLPIOsYd+IO4ipzMoQsPqTYWITfI18r+I7G8JBWb/G3vJaTJMgcOQD6+65kOeTCA8it2uBxuXwy62S4odsnYrSJ6AJUL/Fp24jLgUCK8XHgeVG4BFqhBfBNs448J9jx/fKdauvn3fkvrkILFJCkQvDD+oaLyuSi9SPhlvIKT6iMdkPVU75Vt/8pWtfeXWVLyoECoHVRuA1mZ73v/GC3E4Mvs/GX6YtP7GhKTPwZ/wIX2rkO2ufp2nCmBkbLa8fMxYIfmXxaJ48xgIhKQ3xkOG9eOpNk+BzPP3mcrXCkGBcrRnWbFYBgZpDIVAIFAILQ6AE48Kgro4KgUKgECgE9gICJRj3wlOqMRYCq4RAzaUQWHIESjAu+QOq4RUChUAhUAgsFoESjIvFu3orBAqBQmCVEFjJuZRgXMnHWpMqBAqBQqAQ2C4CJRi3i1zVKwQKgUKgEFhJBPatYFzJp1mTKgQKgUKgENgxAiUYdwxhNVAIFAKFQCGwSgiUYFylp7lv51ITLwQKgUJgdgiUYJwdltVSIVAIFAKFwAogUIJxBR5iTaEQWCUEai6FwG4jUIJxt59A9V8IFAKFQCGwVAiUYFyqx1GDKQQKgUJglRDYm3Mpwbg3n1uNuhAoBAqBQmBOCJRgnBOw1WwhUAgUAoXA3kSgBOPwc6vUQqAQKAQKgX2KwCIE4yGD7XFCRwodIjRt+LsUPEpIXW3kcqmCuRwzIzp2aJrxHTrljho6VsjcEs0kaOsIaenvQ4sK1o256HuoT3gcORnHC211XMofNvX0kahCIVAIFAKLRWCI+Rw3Q7hu6EYb0PWTd7rQUP0krwsnyd2/he4WOlRomvAPKXSF0EtD7wqdMrRswRifm0G9PnSy0EaB8Lx1Crwq9IoQgZpox4EQuUha8ayOnnhRQV//nM4OF+qHIybheqF/DX00dMLQiUPXChlnl06dtH44RhJuELpQyPwS7TBU9UJg5wgcJk3gQ5dNjPdRjHN5UDhBUq4Rauv82rmmICZaFyiP1vgNk3rBkPtEU4fzp6S6rZ8r557ynWhu4R/T8vlC+L++8R7ve5LWAmX5PLmT38bWYjwAL5iEXaqN4ACvC+fmYqEhHpPk+YYhwXb6dGkitPZcjs6Q/x4fAogJEW4e/FWTZhKJNgw/Su4DQq8O/TU0bfhLCp4i5GEkWrrw54wILg9K/IPQZuEnKXCq0KyC53CPNHaB0NtC2k+0kGBNfCs9/To0FH6VRJZ+orVgvLfM3b+Erhhyn+igYB6fTKqXyMuVywqFwK4iQJG1dv8po3he6PIhvDDRukBZJgifk1TlEP5AMU7SWsDs7587AoYnjSGyFcOB1+nJqf/8kD7QTXI9NKYkzyRQUr2PiGwgAK+Wlm8V4rFKNA48RXDqjs340GNS4rShSQGvv0wy7xxS/j6JjxZaeBgSjCbMGnh6RmNy70z8h9AHQy8MPSt0r9AXQ9M8CMzzDSn7mdB/h6YJf0whluLnEy9rMBfYvCkDNMdEE8MPk/PW0GblUmTqcImUpLE9JfHXQsaTaO6BQKM5f3ZCT+YIl66y8O8py4J8RuLfhljZmMdXct0PlCeC8dHJuF3IPBNVKATGCOzGf79Ipy8OedcZA0N8M9mj4+c/WwzWLMsIsQb778qNU44gw2O9v5TF2yTtZqFpwnVS6LUh3jh9IG3im0meKjwypc4UmjacOQWvGYLDMxMTXDx6lFxzbLKA8o8fEYDG1Yii+9XU+3rof0NDwfjfm4xnh2AM61wuPui83yuN/dtJ/J/QUDApTA+zm1RmqN5W0/SzKGa/1bHtdnkvxJ0yCIv7x4kXGez70nj/Y4udep6/Tx0x4SfO7WCQ943kEKZ3Scw9lahCIbArCPBe/TQ944s/Tzwp8N5g7t9Lgf8MeUfwSvVzOw6E59VzRelnXOBxX8o9ks6NmNuJgaDhRrU9RWB/NyX187PEWwkEOCV32jonSkHbHOaH73tH8R5zs/2W7BGj6k+5eGDoyyHjasSa9k5/P+mTgnYp1t9JAVjrI5eLD0OC8RMZhoeZaGL4ZXI+HeJONGE+d3uC9p7Om3Su1vaApdGgaByAS/ZawPBoP1y3yvDjr2UOXDDTW3l1uC2aj9uCs7dlf4qP20M/fNpgmitrTPa7krQunDx3FqQyXCStvSSPuA/sH9pXIIzOmkT904q4E86V+8uFunVyOw7merZcKd/6blpVktcC66v1r62uW2KtUOfCvOwncFd+oJPuEuasyLPnxpjgYF7ahV2SR8ZuPMZl7tIamaN0dbRj/i2vxTD8r9xgFInGwTo6Ta48D/Vpi+afpB0Flqc1Av9d0x53NIOqvF8QoDCy+u6ZCfOIUOjsoXs3kjQO3n9bVYQb64kQkUHYuPf+4aXKSe+Td8C7YP/t3cnkdblKYu96orkGQtgc8Ui8xBiNlzfxI+mZECPkyQ+8KUlrgYwwzvclRflEB8KSRt2Htt0h3j4VmdVPTIzBY2R3zzUh4vqpuZbPDO8yWoyXSW6/igWiHYdZlH146lg8iQ4KBIn8ByeHfz7RWrCo9E0g0nAemxxpfNdMeYS5q4gAABAASURBVAvJvmWSx8HmLt++/pV/XFLth7b9MQLCeJ6WdNcWhn098xTLM5ZWPsXGwSY4X7yxqEPT4iaxVzEucOA/ysAdc61/i+xJub5fyB5CosFgzgQfN6QXqhXywth34IZoLkgL8qQpwC1578SXDHlZPQdKBLzlJ3lkwcNHvj6U50o3RxqgOVgvxsk1TDiqpy19c68rA3uCl6CUvxOibdLQz5FGYJSoQiGwtAh4//A7Cv4jMko8ER/M5Th4V9r7ZbtgnHjgP/cEDsVVuQPJB0UEDx7FYiQguWIJYYLqoMIzTPhU2npP6BYhvJcBhH/hD1ynSZ4Y8FyGSxOgEwsuSwZGt9Ox8DPzC2OIXAgO2bBQ3pGGHbx5UWIMutsX05vQYIa3/Uy+a8yZRuFhD1mtLFXCS1naiX1Ipne6GOnbgrpvblizYkzVYrW39fKke5hOh7K6CG0L7AVJt3f6sMSuCTRWJouHH1891iFXhXkSLsb3kpRXRlu5XBccVCIIuTr1jeyzaqcVZHlZYPpED02GcRDAFpy2k3RQMG4vD3dDN9MesDYoATTLjyXTQnZAiGVpox9Wb0m6ZyYdHvqjbDgMwArUBsxemXIsQEKQAkNj9AxZg1xA3B4pMmJ13jYXtGRMgWCGGXdpkncUaNRc9hSB/gGGHTVclQuBGSPg/fAe4zv4xxPSPsFFkBB4uR0RXoSmd9u7KK3Rb3IhHa9ULrcHBfzSe43/OPRCAeVKxUv1NaneQQ1tI8F4Har5UOraH2UsEM6vyX1XQc/tQYE8wJM3cqMeVGk3EzC6nfaPmTKdWRCYNfcq37N717QJ+5bdfpw0YhXxsxOEhJwHTpBi0r9LYUwx0UHBA3pjUrV908QWU6IRxsnKJCBoaUg57WPiDr9g3nz/FhCrTz0LmjbD6qMVyWOhEPQEq/kZi4eK2f94NBoR0BYkn7k2usR3b1yfSyJSB9H0nORM8jgQOha6+RB2xv/x5BDu+u8K0SSvBbhxtxJYa4m50A5lwljhaF7cG/poz8LzsYiluzY/gtTcPRNaq3zPgxJgnjD10poDq5oioG66HMGe61qfXhhl1LW/wKJVZiekLX3Bpm9t76TdqlsIzAMB7xV+w9PhZCWL0btsi0N/3h1C0jvufrvkvfC+Mwx42vAmwmqIn/O0UFYpmF3iwXtdBtBNwx8p7Ek+KJgbnuOTs28mlxXIk8QjN9RviowDj5nPUhgz+PA4cdn/22hC8xw7Ru10In97f5E4oOHBb9Q/7cP+E+sO4zYPblHCx4IhPKQRaq0d6dypjgxLIwzVpeGxHBENzOL4Qgps9yFyJ3KXbLR5TCu0APv9E9b6txE/qX+Cl6s2Q5xZ8Czgfpa0SNglGgcvg2fVxnKppMJGWi5HxmEfk7LR0qTPmvRj3rNut9orBOaJAC+R9im+Yso8ZZMC6b5LlF18j2LqvevmbXRN+eYRYgjYAumXZWTwXuE1XeLVuVIKd9OcMKWIJvmggE/zOimvHovYdgmXMV52UIUDCTxM5uurhK3M60D13YkIj93ombXFBLe/SKBhfNyPYicRaV0bjQsjZw3ShggTWpgHRpsxJ4uMxTdpU9pDVofFRONy1LlLXImspI3GMCmP5aV/gnjSQmj9c8/aD+z27doxbgt6Uh+zTmf5wo5rtT2Hi6cTAtFz8rLC2r6wlzBZ4+BFZMnByks9Ttxr/9V4C4E5IWB7h0XWmvc+4Qu8OJT3li52T7nk9SFIpE1D3k2epkm8Zpo2piljO8O3629PYXPyfSY+JZ1A5WlL1rpgS4fi7BMN816Xucw3hMhujI/rzcGOD6dz+3CA4zO/ee6Z99MwWa47TJorD8MmTC0qi4/A47ZgwqfJdYFrg2uOuxdTd2p2XYEd3lioFql2hxaL5mmO3J1eBoJU2rRkbtqfpQUFO8oA7dP+hefBevYBrx8PgCntkACk1LSxeo7IHLwELX27sTZYpeJuG/ow725aXRcCy44AAYfPsBKN1b3tI9scfaXduQEKP++L91v5acl7yZ2K90xbZ6vlfCLC2KDMGx8hzkVLKPtMZYjXMT64WpXZan+7Wn63BCOLiVvTQZ0zBgGmOGvFPiBtKkmbBouBGU/I8edzP1oYhKrFJd+JT77w5h60n0YwEkr85BYnPzn3Z3uwBJrNcw9100EMFOC+9TI4pGOjvV8E5ubISuN/dwpVn61/wvLSqWRsiQ4Kxm5xEvwHZW4zgSCilNAAubc9Dx/tUjy8zPAzJoeDCMnWDYztp9AaPYeW3mJzRe1+s9gLRsjCR1n9OqhlbwOm0ooKgQ0Q2NWs9g63QfCo2GtHLc21PXgHDXlhpBM4DrHJwxekTaJ+H94RJ8udjies+vW8f/ib8wFd0rezBd007zDe3G/DPT6g726+syUEMsVVmT5pGw/0AweEaT9/ae+BttnggMrFSVB4CP3y0rgOMWp7Z/18D119Qgmw8rk9bf5y1zkV2SVmOWsIoB6eMQ61qx2/xfn+XBgD874xbYdo7NURMj5B8H2RPpwCdRCIm9KJU6c2WUVOXTo9pgzL1XyUSdMj8zb+/hiMz9z0LV9ZhInbaPZZg4/wLT75DhWJpfvmk9DxXQ8FgUAimPRvHLCy56e9PrHYfPPEd9/PM27PwcGdtoCNz710FnKrQyibk/n5BQzjuGgyjaGRPVwC0f4F4clKT5G14GXxS0jG67SvF0G/nq+xEHLcL+asPoErX3nPtTVkHBSjuyaBRp1oHIzZ+Owdw3WcWP8VAruEgPfdO+x96g7BO+YkuQN1zi7gcw7csAJ9b9gsRnXwH59J+T6aRwsf8d7hsyww+cp5d7yTvoX2zkhThidHPe+T94ai7zyDw3JDwsc7ZFzOUHSJlwiv7abhQfiCvvr05iQwOnyaBQfvLyXamF6WvH7f8im1DJChdxdvNj+8B35pYi3AF5mj8a9lLOrC4Cf1RTj5hIE1xnqxgcvdhtG3OhaJD1oxP4ASPMA1IWUsDp8B0EQwWMd2pdM0uO3sp/kOpksWDYHi2xyHQYwDgwakul2iqRBw3H38+S2PS8KJMJ8POAjj+0DfK3pAyirHssOIfU7CTeCTCtajh2+RKWMcGD7Nz16guXpQmL69SQvDuLhzLWR1jMkPhfusxMfu5uaTFEJDPsvHQ2f13SEJNsG5gv0sFKzUJzQJnWQfFGBHUHBtejEU8OLoyycY8PKS+q7Q2FjVFBDp8mFuvJ4txYNla46w8ayNtxF3N+LuZhkam/4aeRlg5RMPVqN6vh212K0tG/n6sM/ARUtBce93Jz1n5RvpB6400Na+NUXIcsU0RaXlVVwILAoB7zz+4f3k3fGxOp7i/WpjcMDGe249s96cn3BQzadNrUyL/bQcXkIweO8JKN9FEz6tjHWP3zIg2ntOiLI0fSrh/aHEG5vPJryLrW435kXDC733m5F9wyaYu224Zsk6uEgQU4b1T4H2WZdP8/r9kwGUd4Jx6N1lKJifgzzmoA8C0lYKbCkVp0jiQ0LkAGUjl4sJmNeknmyWEiweGu2GpoABEiitjr0yAsUBGi5LDI+gakwdyAQK4UQrcpJUXcydYMSwLYAuYdK0LouEtkQA6HfSHhNG6xONPvgEpR+hxaS1r38LxLyMAXFdcLdy5yqDgWPs3JXm4FvFNn+CB/Pm5mPNmbdf8+FDf1QaM6dE40DowQ4uMPGg7Z062EIQWRD2Q7lUCFgvkf5ZTU57wW3c0MB/MIexRUSgK0KYc0PDznPwTZM+YQY7GqZ0L4aTcl4k161P7lxHvy16aY1Yek7tslJpvvrqE9xZyHDSph8T4CKnLHGN6t/cLXDPgMtIHiaDkSA/JmAtYDhd7dpLAyfjhXu/77ovBBaBgLXnUCAFHcPGvL3z3i/9e/9sM3jPmgHBG8Wz07xYyjWiYPqWmCLq20BC0RrHc1oZnhMCgQKL30jH0/BT/avnvePF6fI05eZB5sgLp39CnRHhvWUtDrlw8Sk80Dzh1x+Tz/PMD78jvOXDyrkT7TM6eKooJHDsC17l50YbCUYPyV4dS6ERBtmdpMGyNFq+mFCQbtDAUUc6IjxIfsKBQAOO9C6x6JyQ5B5o6QRVt19ta4clitFaRNL65IGxQLTDUuu3oTzG3spgwhatdHMgoNRtZBzSLRLtddPhpV4j7TRstMt1AU9tymvlWLetf+W7ea1MP4YN64/F2yx4G/ptPGJ9mq+XyX0jLzNizUmTT4CpzxKV1oh7mnbLAlanP452rx/zUs9cvMjwMR/zhrF+5G9E2oCvZ0so+x6UMmMNtb4qLgQWjYA1aT131641ad23seB13m9lxNZ9yxuKCQHr3XvI2HDfLYcPeGcoivqXpwweqm/9qNfnO8rNi/A9/N2Y9W/8XQy6/RqzseMF3fR2TRian/koK13s3EKbnz5c4+PyF0YbCcZ5DYI7gGXkcAdrq7kJ9Gc/SRqG6qFL6xMrkglPM2ON2GcksPrldu9+MT3TMGlwLDpWMQtyOz3bL2B5Eo6sc+7x1g73K0vTAiXAW/o8Y25hljjr1y+JTLJU5zmGarsQKAT2MQK7IRhpClyUfM/cAXzyiEuN0GOZOMVEOxp6NNyE3JhcoFyovrMbKrcf0vj6CUcuUPtx25kza047tDv7kZ4F8my4M2i/XM6Tnsd2+tyojg17z5hrmLU4SSPdqI3KKwQKgUJg2wjshmDEYG1I2+h1GIOfmlC0Cc1fzp/MZJ80KULRxq39KhYFQTup7Kqnc6PYt7XXQLBtZ77a4EK1z8hKsy/reTghx9XtZ+w8s+20vZ06XMAEtT0aY9tOG7OsU20VAoXAPkNgNwQjiPmS+Y0xQW465Fqa/I2IS4+Pm89/IwG6URurlEdosfp2IkQ8D3sBrEPPAnFnb7ZPMg8cWYj2GcxrHu1Xm4VAIVAIbIjAbgnGDQdVmYVAIVAIzAWBarQQmAKBEoxTgFRFCoFCoBAoBPYPAiUY98+zrpkWAoVAIbBKCMxtLiUY5wZtNVwIFAKFQCGwFxEowbgXn1qNuRAoBAqBQmBuCJRgnBu0kxuunEKgECgECoHlRaAE4/I+mxpZIVAIFAKFwC4gUIJxF0CvLlcJgZpLIVAIrBoCJRhX7YnWfAqBQqAQKAR2hEAJxh3BV5ULgUJglRCouRQCECjBCIWiQqAQKAQKgULgAAIlGA8AUVEhUAgUAoXAKiGw/bnMUjD6s0fnzFCuEDpsaK+HY2YC/gxWoh2Ho6WFE4UOEapQCBQChUAhsMQIDAnG22W8/h5fo+fm/hahJuwumOuW1439OShl/TkpQjLFthT8sd27pMahQhuFYyTzcqGHhQjiRDMNhNfp0uLNQ/42YKJxOHH+90eBn5PYn2c6UuKh4A/9XiQZJw21ALub5Obaoc3mlyIVCoFCYAkRwJ+6PA+vPMwG48Rf8cunpEy3XrvGD/xh7mTPJej/rGn5CSF/Rs7fOd1KfydIvYeG2nj9acBL5H67fxT6xsv3AAAQAElEQVQ9VfdGAFx/pK9MwrtCmPuVE7805I8Btz9B9OncA4qguEGu/RFbf7+PQPxz7rcTLK4bp6KFd8LEk8KpkvGQ0P1DdwudJDTroI97ptH3h94cEiyQp+eC0KMAXDrXNw0NLRAC8QzJ+1Wohe/lwqLyItwq1xuFyisECoHlQ+A0GRK+cKPEjY6e6z+FJgV87TLJpGS3Oi2+YdLxr3n96TwKPkH4wPTz8RDhfMfEVwwN8f0krwvKXCwptw+1MTNI8MCV/5NwJp95rwv+zuH7kvLN0BdDHwr9LNTA8PcQP5l7AvHnid8U8vf7vp94o0WS7InheMk5Y+g4IYJjaFzJGn01/90m9PzQdvtK1YmBNceyM3/z9rcBCT8L5BSpZa5fSvyF0HVDXoxEa8GLcKncqQubXI4D7PytQ21fKSmXDE2aY7IqFAKFwBIhcMiM5d4hnjMCp9EDkubdTjQYjppUfICi3OqIT530H4XeFvK3UBNtGnjjzrVpqf8vwEt1r9x+NvS60OdDbwgxPk6ZeLNw+BTgxTtfYmNGPGhvzP20Y07RvRmWgTkz7U8b+D4S+mXoAqFjhSYFC9Fim+aPGk9qYyidALxOMizityZumhwN6WS5l//TxITlLxIT4vYNczkOyhF8X8/dJ0JDQX3WOA3y+EMFKm3FEKjprAICeBKhdMRM5uQhPCvRpoGX7eUp9bVQNxCM305CPz1JMwuUeXyLcfPHtIpvMmbMQV6SNgxXSS7vGc+g8xa53T9hXoLRPuBtA6P9uKcmtqgIllweFGgmBOGrkkOr4Uo9c653GuwBcgNw+xoDl8akMejLmO+ci7eHfhDaarCXoP13bFLxo8m34M6emBaWqEIhUAgsKQIEiS0jWyRPzhjxE7yNdyi3GwaK8Hd6Jf4h97ZibFH9LtfzCDxfV03Dfw39MEQoJhoxKH6TCx6rjcZ/7JS5U+iiIVtH5ny1XGs30eqHeQhGB2+A+OHA95gQP/qzEtO6hgQBy8veJBelhUegXTbljxDabmCNEYYWxMPTiD2+JyW2IBMNhrMklYZlD1W93I4Dly23MguS65RbxRwJTy5khbiBWb0WkPLSJpGxmO8kPCbVq/RCoBBYPAKE1z3Srf06wsxeo4N/+MoQP0vRDQN3pDMLzi/MyyV5uIyA4k0I2hrL7Tj8Ov9z4TpcSODndjDYOvN1wTWTix86b+KMBQVhO3NOM3srbCYYuQdZcFyGXfJgWXpDIHEzPi0wfCbEdHdyi+ZCy+oLOxaWB/CNlGXuO/Dy3VwTUvYdc7nlYFGwFLllncTi2vy3tOKeFvSPue4HmhCLz/6pvdJuPoH4ziRox1id8qJJvThpNEIL7Ly5Nnb1aWLG3jBK1rqgjP1G/am7LrNuCoFCYKkQ8P4TLs4d4GF4AL7mIAthOcQDJ01AWZ+AUY6bUt0viyfzXnX5rWt8jSXnuhGjgqLeb4OrF08jeI2/5bun9OO7+mnp/dh2EUuXF88BzHbQ0PkPZy365VfufiNwTBZzv08ubDJ3yWcLHvBm9VN1xLJyaMUmLv+8tEbu9eEwjzSaClcmtwWtZpr21esSfzhBZdPZA5ZHqD0xF68IEdKJ1gXCjALw+6QSoInWBcLaJxoSndB6QS64iS26c+eaVvnlxNq5e2InUFmoiMWcpLVAAaA8WOQs0LWMuigECoGlRsD7/sGMkILN+uLZIoSSNFWglDvDwJs2qQKBxlLr8lvXtpcIKKdM3SOHgXiv+m3hQ4yafvp27nm3GAEMHIeJHMjZDl/eTt/zrbNB65tNkCV3y9T3KUWXpL0n6RZKog0D4cRCoq10LSSaDtOcEGNhckMiC+DIadHRYP74XG4p+JhefZZZq8i9+aLcPDPkQSdaFywip7hodOsyOjf/nuv7hSxObgWfY1jk9gudLrPR7vCNTzK4kO+QsuYiHpqHPrt4pHiFQqAQ2AMIOFzn5DnLjRCadsgsQYq7U+344VA9irMtpS6/df2BFPapGsXcPSIkWbPJWhco+PjRusTc4Dn4HKGunyRNHfA4BgKFnsU5dcW9WHAzwTjPOTlwwxVAO/IdZCOWGdclNwWX5FbHQOPi5qXdbCTottpuv7y9UGN9bTIsTsLPpxosTgoFN6uNb/55e54pVqEQKARWAAGKtq2TrU6FG5LV+JOtVtxieUKRMUJo41OtOuuWcOTKJRxb+jRx84pNEujTtLFnyixCMBJOrEMCo+3fSfM9nx8O4K/nb2/k3qJj+TmgslUwnbzyENUlrLr1CSlWXjfNtfIEWROo0jYii+saKWD8fPG5HFmENEhWND8+jYzANPeuhmXu7m2MczOruwWqooVAIbAkCPiu2ns+zXC897afWF141DR1tluGxUhhx9/xKn1ri5C0feP0Px4lbStEmOLheNxW6u25soCb96C5NblLfRjahAh3gnQHdPr9c3X6ptED8OsQW3U32qe0YP10kdOxXAf60Kd9Ti5R912iAfreh0bVF6bdcq6VYc3Syt4t4QARrvYy1ScM9Wuv1IvDnXyg2Ei+fQEKAGWhpVdcCBQCy4kARbY7MocIKcF+aAS/6uZNusYTTp9M5ynwjlwOBuXwFy7TLjkxb0+zm3b5tGAsiQ4KDhzqx2FBbRKOPFd4kU/KNrP88Lluozxwto+4dLcjVLttLf31kGAEID8yi42rU9yfCGHl2DELC/OXD3CCgfvTPhvthLbCF044vDCFCCCWlV+NAfSQ5uSB0aqY+zQsP8Okn1QfBw+Mr17bhN04sfOfNh2Oscf4iKRbvPYu7QtycUpP8rpAA3LqzMEc31yuy+zdmB+XiPLqtWzzdyDH6TGnai1kR7t9t8il2srBhWD0ob+F29Ir3ocI1JSXGgH88fwZoU+//PiHbRq8x/mHlyQdP0k0Dg7v2RvE+yi/48TOfw4Z4l2fS9p2BItfvvlW6k4b/ICAHxdwgl7f+LUTtT4T8RNxrR0GisOUj0uCuRkjg8QndhdKmnuHJM3ZL+fM2w2cLnc/ePD9URAgAMDUPWynsB6fQhh6otG18h9gL57YAvDAmO2EqCPMfjPV4mCuK0cQEW4sJELRgrJp7KAKy5AASVNrwT1BRkBp30f3xsMFyj/vZKn9SJqSk1mvT037lYnGgbDy8B16oeGwGp0cVc5PI40LDfzHyvTNjm8SvQADRcZJV8//MGHR5nJdsEFtg/zBSfWbs49N7Kekur/SQ+nQ/seSRwlIVKEQKASWEAECzHtOiXdAkIfLuQJ8y+Gb7pApu3jjOZJImCRaF3xUb+tEe+syejcUbAcbKfSbES+cLZleE+NbfNCYWY62fHwZgAfjSd06eKofP8HX8FT1lKPc42G2tfBP19LHja/6f0OC0bcqBA3zmwuBtkE4ETLweFn+Y5ITcqxLPmvfutCeuAZ9ouA0pnqEjIdjr80iIyCUZQEi+T6eT5Nrwb39QQ9M+/rhWiBo1bc3aREaO23Hj+L6aHWtgVxwbxCEfnpJG06OsiI3stC4Qh3D5u7wqUiaGQyPTioBaj65XBcsKkeb1adl+RC44aYgPP3Ukk9SuFSkFRUChcDyImDrhdBgGPgRD0q5tP77/5nRaIQX4pV4SX9GrE7K+kY8qF9np/eMEifxGRU+syAU8ehuuw7p2OrC0/FeyjqDBm82n/OkMG+fevJyu/qBcFn9WU4/QxqRheTnlFjA09fcvCShSGukMNAEh16ezVupEoVAIVAIFAJzRaAE48HwsjRZoDQ/+4kHl9h6ioM410s1LotHJbYXm6hCIVAIFAKFwLIhQDAu25h2ezz8735KjrvTKbBZjIdrmevY3qr9yb4bZhZ9VBuFQCFQCBQCM0CgBOMwiPYBHGn2027DJbaWShj6Q6E+Jdk3fvqtQVSlC4FCoBBYDgRKMC7Hc5jdKKqlQqAQKAQKgR0hUIJxR/BV5UKgECgECoFVQ6AE46o90ZrPKiFQcykECoFdQKAE4y6AXl0WAoVAIVAILC8CJRiX99nUyAqBQmCVEKi57BkESjDumUdVAy0ECoFCoBBYBAIlGBeBcvVRCBQChUAhsGcQmEIw7pm51EALgUKgECgECoEdI1CCcccQVgOFQCFQCBQCq4RACcZVeppTzKWKFAKFQCFQCGyMQAnGjfGp3EKgECgECoF9hkAJxn32wGu6q4RAzaUQKATmgUAJxnmgWm0WAoVAIVAI7FkEZikYjxgUrh16aMhfg0600uGUmd01Q4sOp06HFw39fWgo+Gvc90mGONHU4RwpefpQhUKgENgFBKrL5UFgGsF4jAz3AaFPhf499I3QM0P+xuCpEp8hdOTQI0JPC10/5D7RSgaYXTAzu0MIHokWGs6W3uD734n74X5JeFHo7qGThQ4RemHIOLv0/KQdK9QNv8jNY0Ke3yETVygECoH/R+Doubxe6HWhW4a8W4nWhb/L3UVCHwp5326U+FChoXC4JD41pNyTEx82NE3Q3k1S8NOhr4f+NeRdTzTXYL4U55enl2+GPhZiCE3iFUdN/rNC5ve4xP8Y2ixQ9i+eQu8OfTv0mhB+h+fmcnFhow4Pk2F4AATiCXJ9jdBJQoShh2Gyn8+9gf8y8b1CXwpt1Gay93w4d2Zwq5C/r/jxxIsMXrwzpcPPhIb+ruNDkn670H+FBGVunIu7hg4d+mPIi+uF/VGuu8Fiv3oS/HHmqybWV6IKhcC+R+BEQYDSSTBeLtdHCxEUidaFK+WOt4Yhcbpcu79N4n8IdYP23pcEfxT9nIl/HXpT6JihjYJ3+NYpgNdSjgnTq+X+LaHThrYSzEF709Y5cQoSdOdKTIDxmD0j13cM9edHThjT95PHE4UPvTLXjKxEg4HcuHRyHhnSlz4umWt/ExdeuVxcMJih3gB+22Q8PMSKIAi+lWsTZKl8INeY6BtHoxEXam5Hf8p//xla5XCUTI6y4CF/LdeLDtyof02nW8HZ86KwsAi/l7p9gZikteBFJfCvkhQCOFGFQmDfI/AfQYAAwLR/muuhgDfcKRl4I4vx97l+Qei6obOHWmBwUFRZUN61nyTj6aFjhwhV+bkcDCdMKsvVFg7hQajyCB0v6Tx2fQGV5IlB+TNOzF2fQUjdMEnPCZ0mdIoQq9kcb5rrk4ZaMK/75oZs4VmE1+Nzb7zwmTQ/faTYCF4EK+uURU0oEsZDiojycyGD7zcs7QJJJBjflZjE/kvifvhZEgjOQyfeD4HLwIM9fCZL2/ufxIsOtMOPplOWX6K5hK+mVQue5blfnm2mXKEQ2BQB7wUaKsi6wfy5N9v7yR3I9ck92Bj7yVMZf/1C4h+HBMqq+/PnpitkcrsueB/fnJTPhQQWGaFKSedOZdBInzVx+xojIWz+f04Hrw3ZtmEYsT5zOw6Ud/MwH0JRorrGaN68j9L6pM03JvErIQYYK/oNuf5uyLW0XC4mEIL9noBLIzHZlyWzPeRcHhS49OwrHpTRSSBY+Zm/mLTzhPTJZP5ErqVzIdCWzLqYYQAAEABJREFUcjsC2ityIZ0Pm1svt+vCcXL3xJAFqBwtjraWpLXAv/2w3HEPPjsx9yFqWkmSRjQSlp82uES5D41N3hDplyvlrclkfSVaC8ZNC/xkUiwMLpQP51rbFAwvB+2Mz9weLczaHp+xPzplpSvP9UIIJ2ldOFLuuCU+krgbuDRenAT17X9s5o5J0YlBxq/yn/0L+6hettxWKAQKgQ0QYKldK/m8ZoRVY+K2mFiEF0seS8r2hLMZx829d4w3J5cjMV7K8uOpUU56nyit+GZXKcczeIL6ZWd5/9s0xvo1v1yOA8+VMf9hfPe3/4wbj+Iytc1mXnKUJShZglzMG/FZ5RsRluRBn+e1/LnFQwPEsJmuJLXJbNS5iXO/bVSGwKBdYNjMaA+V/5kAoIkQOAQHwUVIEhqEyNvSKEFCODZtixCgpXBVEEAOihBoL03Zpmlpk7VDG7Mfat+NpYfRp9hIW+fLhdOz9gIcHnpn7vVr701+btcFafYWCfCm0bQChCJXgT0IY7hQMvTtZfBAH5R7go/7gcXHBW0sDu+wPglnmGvfXLkhfpc6XjD7uLkcBy8Mlw7ta5yQ/7g1CP735JqgpzDAmxBN0raCRaxvL/IV0oK5J6pQCBQCExBgTOBHrCmCsBVr91yg3kmCw4l97xZDoZUTu9cO4aictD7x3KFuOh5ivxEP6yvs3XI7ucbn27mF1g6+QAASzCxj6RR6c8Xn8Ulpjdzjzfj9pPm1strmMsbTyIR5zav1d1A8JBgBzYo5qPCBhCMkZhERIo0czPFATSjZ6wKLk3WH4XYzWHMYvTQC5d654FN+b2LCFiA/yDVhQXAClXXIlUhgelgfTL49P0LHprRyxk7YMd2V+U7KPCkkTjSyQO2hsbJoYLQhLgIPmLBiKY96/7gwfP7gAf2wl0eB4H/n4qA5sj4JRAvpUSlLEbCY5bvWj3FfInn86YQ3y5xr+stJ45dXhsC/S+4FC+7CuaAUJBoHC0dZlrV0OBOQTrjRtMaFtvkfwUg4w97Lus1mqtquIlCdLwoBfAdt1h+BgJcM8d3N6g7l47fNq2P/r1mq3bJ4h8+7Gq9uMZeug0TtXuwe/+/Wn3RN+OG7eM7PDxRq8zOuA0lbjvAb/NnBHoYLS5xRteWGdlJhuw8IAKwJjJlFRBhtdxxAJBxMniuytfPZXNjg9cAJVS4Ilh5r0X2yx8HBEvUunzsaDKHgoTm5xfVpYRCmb08+waQfQs5pzecm7XmhB4a4N4zDZm9u1wUaHsFP+BAY6zI7NzREgraTNNKnOm3MYj5zQpul2C3rmvZlcRJ87pExUwza3oI0Qss8uHaNSxriViGUXW+XzAGOrGHa6HbbqXqFQCEwPwTwCQr2S9IFfploYQE/xht463bKb/qDxnt4KykbjIPbpwA5kWgxYUgwYoosI8IO8P2RsOZYbKws/mWWmG9bWBlDGku/fv+ekGVeEz7aa/nAIcx8LkKIOI5MmyBkWhmxh8I6VF8+7eXVyVDeqS8WHCFuToQUi5DWxmdOIP5zyhKiNowJRg8kSeuCvUkPadYPh8A2N/OHQ+sUxvb62j0LmNVtrtIIe756exgEobR5kDnDah5tV5uFwKoggFeh/nwo6ISHQyj4lnfdPh0+1C/r4I48niPl+vn9e7zImQ08Dz/u57d73iqHKH273CVnEnjlumnu8f9Wd1JMNtiKso3TvH7KGrc5DMkBLlYKPP48NH/1EePCIRxnRJx4dQLf9hT+Ln8hNCQYCRDMlpXCQhsaiIlbCGLANIY9VHbaNA8YeP3y3JMEE7IYuAD6ZTwQlhjALQRW5mVSyAEYlp4HyE1KoCR5xPpSlhvU+Lvk4SnTJfNUXv9DmHXLbuWay5VLl2XLVWrP8GZpwIazje1cjggmVizhbxwtzbxcz4rgb37d9swZtt20ui4ECoH1CGDm9tAIQgf/Wi5egecwGii73iW8Fb90XqKVE3v/pDtDoJy0jQivdGaBx0udjcrOMs9W1IPTIB7LjYpH5HYc8F6GEgPH9tg48cB/BBvlwPmLaeZHvthysrVGFuHZB5qaf+TB9Xvh5mNNmQB3owMn/TKzvAeSvUQAXycNE4SJ1sKlcsXlSOtS1jdBFluS1wUWFW3E4rRonPpy+tUJW65Wc5FOI6MVOezS74s7tbuwWwceqDF6ODTAlj6LmPBGDuX4xRpC3GEdL5v2jUe/Fpx7RHjbhzQWwlTaTsii5ctnIWqHMKaImDNFSVpRIVAIDCPgfXROAD8lOJqC6f20vYMXqYl/UXhZQV0vEW8R16SDO5R0ZTci1qXT7vbhui5U/MwYNqq7kzweRPt/hBWPYVdRxy/Mj4fOPLrzk+cgDX5CSZh2DKxPnjOYkUvT1ttxuSEQWV5OjXrQJuNUJ+a8rc5SCXgEUS5HFs3owD8CDEOW7xAM0/6KybtFyANINDpL/qN5ENK+HXQEmMuzKwwwce5Re220MmY+Jk/LSPURrYZL1bz0qS1AE8L3T4E2N2O7ee4JoUTrggfEpWvhtbGtK7DNG6dvHdzhzrCfSnj7VSGCuDXJQrY4ulqhuXCPKOeQjm+JWnkxAWc+rqchv16kjnkqb46UD9jpQ1pRIVAITEbAKXqMn+KOTyjp8wSWzztyg88lGuFz788Fj1bjURR/vNaPA/ghlWRPDA68UKJ9mkXhbwXxEt8JtvsWG4sfJ2BZdklZ/A/vaenuCfJWtxsTbs5xmA/50OZDADqM2ZQBlrN5+K6znZMwPxayefPSddvd6JoVjRc5uU/52KjsTPOGBKMOWAlAultu7M/xYdvkBQ4AuPZYckBPkXEAgsMaGCpBNU7Mf7QIgo8WwWdMGBJswEz2yL6eTxQcLKE58S07UMMiIpwxZyY6gaY+oJxOtYdoLCxCwlFZAkMbDqbwgROS+iNgaTIWHSFjIdifu3MGQOPSF6HrYQ9pNKxZD5WQcMIr1dYFgomAJYxYnS2TZidNrIx047e4CXyC0EkwQs4YGllcFrP5WfDcqNwT6jeiKPhMhDLhAJT+9QMPc3aiywlV6bCChaPixtPa0L75+KEGc5MOP4vY2rBX6/lJLyoE9jsCPE7e4yEvGp5JAfcxP/7mXaT02irx7WHDznv82Nzgk4wAgsi77rQ73ic/2SPnCijjfg3H+ywNb1FGmgM3jV+I/y0FCA+8KpdrgSBzQMZZii7h5z5ra+cs5PnJN/NYq9y58Otn5ueX0JzD0CfCVwlHvFdx7mC8F5+7QRIIRZ4wZZ+Q+zY/v9pjfj6lI0coEa9PPjctTPB0n+NRJJw1SdbiAuY31BsBwcoDBKZqYA6oYNBOTZLgACdwDN6Du2caMiHAABzjT9I4AACjJlC5FQgD3zYSVE6GetC+v7tySrPmMGOnTzF95ZM8MiafMziJaRGpbywewD1SQFqikf65IuX7RELfBLrPQeRph0bDP++XFTxQbloLhHWsb+30yYMlwAg1mkzLdwjG4idM7B/4lpD1BzsvAC2SdkYY+z4UloQdfH27yWXa7xOe5uQlMz+CsvXXYsoC5cX3oBYZ7ZHF6yXgm4e3OROexsEatAC5bc0FwY/rFgYUE21bkJ4d5YSyIO0AVVQI7EsEvDdchz6/okBSvPEVwq8LyKtyg4f47IxSyarzfTSBlay1wF3qu2TnBLgleWvwRMr/WqHeBV7tR7vPmnRKfV8AMj4IrGSvC8oxSvS5GeGheMG6BnKDfzEiuDObYEvyOGgbT8FXxwn5D1/Bp/FGPJOsYOUqm+zBwCMm33kLn6Dh3/g9fqrfwUrzSgT2Zm0bLA0AE8cwLQbuAtakgavvQTVhKJ8fmtCT18gioUmxEC0wD4E1qh4gPBBCg6tUGwAaEghMcZYWAaUcDaar5dhDdKqJ0COICCxjBXwbi9gi8rC04dcaCOi+gFKuEcFC0LC8CCLWljwf5jo1pR1E0/NrP+ZFC5KGvExOocp3j3yDSVs0RveN4ESY0VBh7xnoa4i4Xs1TXQoGNwc3BmvRS0xrk7cR+cGBJgSNxTPSP0ViqM9KKwT2EwIEW/89sidIuezigH/Y0vE+Mhq4KQmFbpl27d3kAfOus5ooyC1P7H0kBFmI3kMCDq+b9B77QRF8WN1ZE29Z4/39/s0T/+73iQ8zmhhWLEZz6JZRx/xYkfCVT7Fv7XM1kwcMgG69hVxPIxgXMpA90gmL0G8TEvyEx06GbaHRLGlXFka3LULYS0eb7KbP+5qlSllgfRLi8+6v2t9FBKrrQqAQGEagBOMwLhulElaI65XVulHZjfJYyFwofOqsZNfKE072bwnGvtUtf15k34RblaZH+Pc12Hn1W+0WAoVAIbBUCJRg3Prj4Bqxl8DFOek7z2la9fkFH7wTa/zo9m8JQwLX/p5DQdwn07Q1izI24+2V+n3WeblkZjHOaqMQKAQOQqASZolACcbto2kPwL7k9lsYjQ8K+bto/PTNt+7QDQG5k3a3U9e3q062badu1SkECoFCYGUQKMG4Mo+yJlIIFAKFQCEwCwR2WzDOYg7VRiFQCBQChUAhMDMESjDODMpqqBAoBAqBQmAVECjBuApPcVnmUOMoBAqBQmAFECjBuAIPsaZQCBQChUAhMDsESjDODstqqRBYJQRqLoXAvkWgBOO+ffQ18UKgECgECoEhBEowDqFSaYVAIVAIrBICNZctIVCCcUtwVeFCoBAoBAqBVUegBOOqP+GaXyFQCBQChcCWEFhywbiluVThQqAQKAQKgUJgxwiUYNwxhNVAIVAIFAKFwCohUIJxlZ7mks+lhlcIFAKFwF5AYBkF4yED3GVDbwldIdTCoXPxjNCbQzv5O4ipPhjOkdR7hxYdzPc66XQnf8Iq1acKh0gpfZ0ocYVCoBAoBAqBAQSGBOM1U+4/Q38K/XfoB6HHh44UWkS4cDohAC+Z+PCheYd/SAdXDV0/9OrQVoI/KvyGVPhFyN9O/EPiT4cI9kTjcPr8/77Qr0Py/Z3Fy+S6hSPm4rghfyA40ZbDSVODEuFvKP5vrv2B4e8m9geQE60L8n+elAeFzhOqUAhsE4F9W+1wmfnTQ+8Mef8TbRiOktx/CuERf0n8oRAe93eJh8KhkniakDp4CUPAn6RL0twC5Ryfuk96+ELo9iFKdKItBbxUG+9KrS7vPkLuzRuPxIO69JXknTq0VGFIML48I7xAyER+mvgqoTuHfhVaRADqA9PRb0LdQFDfKgmEytcTzypcPA1dLPTY0Fbb/a/UIVTvm5jgI1jPlevu3zW00C6atIeFXhG6SMhiTzQOhKKF8sPx3db/+1aqXD50t5Dwuvx3xpAXK9FB4R1J+dfQnUJewEQVCoFCYAoE8Eu8wvs2jeAgHPCss6ft14feFDpJ6MWhS4f64ahJUB4vyuXoWvnvyqGt/H1W3qCTpc5WwtFSmMfq5Il54/4+8VYDPPCda6ci5SHRWjhDrvA4835+rtELE3889M0QpSHR8gQPemg0hOCPk/usbBAAABAASURBVMHC+XbiRQYA/jYdEoSJ5hqOn9ZvGnpV6Duh7QRaIAuNpUYI/nmgkb8mjQDzx437i8AihrU5p9i2gva/fKDmTxIbS6LBQGt7b3I+E3pS6BihCoVAIbA5AkdOkTOHbOsk2jQcLyXwsTsmvvEBenJilqZtG4Izt+OAF1NuGSLeSx4firr64wJT/mdL6LwpS1Almir8MKV46V6WmOcKD87llgJheu7UMLdEa0E65f8OSblRqOFws1wzJD6cmFGRaHmCh7E8o1nsSCzuh6ZLSsBHE29nMaTajgNtknuVwNpxY1M2QJi/MWVpeLdJzJWSqEIhUAhsgMDZkkfg8KTlcqrw7pT6j5CA17wkFxRoCikelNtx4ElibT0rd7w6iRYeCGG8YTsdc8UyNBgA3fq24/AabmHXLc/cWah4n35b+lLEWxGMh82IrxHiqntpYovkAYm/F/Kgr5iY39xeJM2HdWTv6+pJ98CPk5iL1B4XFyT3LG3CHpk9uD8mnzU15G/W7umS/9yQdl3nchxOmP+5DVlM9iUvlPvXhmg+r0x87NBQ4Le3GN+WzL6FRVA8IukssfMnboH7g3Zz2yQYU6IdBWOnYbHK7TXa54TZU9IqzfThie3xsu64Y/nqb540gtw+8L1ybYEl2nLgwrBYuc2PueXaVaEQ2F8IHCbT5RJ8e+Ihr1CSDwr2z7y7XaUbj8Ob8LumDB8rNQlEPMw7ycLiEsUTCOJkL3Wwt3i1jNA2HC9jd76u8ftkrwv4vvl9KanKJFqesBXBSCO4YIZOmBA2p8z1E0JnDXn4hKT06+aezxrDvVKuaRGEZi5HBKON3a7bkIZBcNKsJgFEeBB6TqkSDqPxv7/9Z48Q6YcwMSe++Rsm237A/RMTdInWgjJ86toiINYyFnzhkM7n0ifBzP0BX7EXxXz+OXkEPU3TAajL5f6DIWN/VGKC0x6n+eR2S8GL+dXUsEBPm3gvvIAZZoVCYOEIUIK5/vAq2x47GQDDgSL6mjTiwFyikYNwJ8jFj0KXCOFZrEZuV3x2md9N2HD/woaRlOFPFSj6LOmd4jlVZ1sttBWGykrBqGk8rD6nslhPHu4n07GHTcthYXmQTHIm8ouS50BNonFgHfU1LoyfBdQ0qHHBzn8EKR84baqTPL60kcsy1NcXk0LAujYmC411aW8gWWuBlUWg65dFtpaxwAsWOMH9ngN9OpDD8jUm+DYr2vjM28a8zWpaKEsWpnCxp8DyPtDMliIYOTV3qtTabhupWqEQWGkEKI88Wd65nUwUv7V94WDhs9MQQ4C1dalc/y7Ee/W8xLcM8boRkvbm+vwr2eNwlvz/1JA6jW6de0K83bdYv8maeeAJdIiPl858punA3iqjAO/ry4Jp6s+9jAe11U5MnmlM8KnrnvWhLe6G7yfRg2FN8qPzxxOOO9UM+KctnjQ/GIzHgmuZAEeOP6OWLiaUPFAChhCVtmgijMyH1tTtu+HZVxKMlZuilTVu1O63E8MLNix98XbamFWdaqcQWEYE8ApeGdsbDIGdjJHrkMftOWmkWVe8WTxseCgF2DvpXbelQlD6tIPBkSoHBR6fRyaVwdLIQULbXe2+xQ7ypOhMAwODt844GUzTNs5YgcWnUgG/S7RcgTCb9YhoMPYcfUhOGD4tHXATLBMA5o0ytIWFrkXGoqYNOr7cF4ALG9CBjoyFO+TAbUWFQCFwAAHvhrMUFFhC6EDytiL8xjtPmeVt6zfC+9MVvBT996eQTx+OnngoMFCciKdcN2KI2MNs9y3uKtVDbW0nzYl621G8WNPWhwPX6wdSwVgTLV8wyFmPyjc3DuncIw3TehzR5SsHYpKWItDILFDaGq1np4Oi7VnIk1we2rdnaPG7piEirkz3iyIuj74QJJiNX7yocVQ/q47AaszPfqBvFn12cYNMCS/D1G0/OAfgbAQXZf+dStGDgrMDtm+4UG0/tQI8Yc4Y4Ae2o1p6i3m98Kp2vywx3ukwIp7iDAls/DgMPkeQM4zMuWsQGLs5njMXvpNPtJxhHoKRVkQAsBx9I+iTCP55e4/TLKBFIGUhcvkSijSynfbp43zaHhfBkEtSPxZE0zrhYU+1+4LsdAyb1de/hdst5+UmFO1jEuzdvLouBPY7AgTSWwPCViyiFD8oOAdAePjFnO5hP3ttlHRnB/AhnrV+ZYda8Ip++m7fU6Q/kkEQcIR7LqcKDkiq6/vFZfIirhv8PASjBeDbPB0RGA7HfCM3DTw+dC4AWkUTlPYmaWdcFyk690AL81AtRodaNurQ0Wn5hBut0XWfWMncHvYDaJDdfBg7gUUjZCE6YUswehkskG7ZeV7Tbn3q0p6DvrhBuF24vr2g0ooKgULgbwjgU9yeeFgjp0ntpznY57M1p8q779Tfav7//w7I+LWuJyYJn0g0DniFU/sUUgdX7Dn65MGepgL4hsN5TqFT4qV1Ca9khPgOULuN7IU+JgUdcmxpYv2pk6wth6EK5kwoviCZDRufa5gHF6nvNeV3+Qp+z3OI98IvVZczAL8/MsKCye8IP9egTwQwdZulmD43AsuI5PcQbQy7lw589w9JoxaDbwVtXGO+fMrAZJ0AjItCGz4D8bNHmLQTWjZynUAlKPn3jQegxuPoMiHqZ4uY8ulm5BANsAk4Qtm9cZuDcTPtXRur8oim4pStsTgdNbRgCC0nRJ0QO1Mq+WzCgSJWHsHGdQCTZI347x2x1ia3McvMSTZYXC8FtMGC9qIZpzl1f2lH//DzGYaxmyfszFE7DurIh6U5ubbp7ZoSguSlq5GxcW/oG6nrVzScbvuaAgeIgPZspaEDyRUVAoXANhDAywgEn1V5vzXhPXTvUzZ7gfhOo2aJuif4fIqGF94lFb2z90vs/ffzjfhLbtcF9XxTiTfhFY0ceGR0tPsWOwGqzrpGDtzgPw7gcXHiP8bBfdx1g+JN5oe34x0Hqm4pwi/xarJg0li21OC8Cg8JRhoO68KJIZoMQPjVxTQaGhMtxYf7Pnh1PJhLgIYAXO5CH+/L8/mBRXLPTIBLINGIsPG7oX43kMAgTJ2i8nNEvnP0bZ7fFdQe4ejBexC+9fnYaDTyWYOFQzjkdtSEqoMs0rRJaBifhUPQ+gaSYLUA1EGEojraIqykdcmGuw/ouVEIXPPSv/HRgqSzflsd86IM+J1DWFnYXggC/3Yp9ImQYAwsNIvMPSL4aX/q+5kkljbMjYsA9jNvTpt5+bxAynlONDWnzZwCVta9un6CSt8I9hY5zY7lrj9E4BKcsCbspRUVAoXAxgh45/3hAHwFH2ilWZF4GE9QS6fgsty8l32iZOMprT6ecIvc4GHeWUaEH/Ng7SV5roEApsDjhfg7ueC3lI2ldewgpfk5Odvm1/JaTID7pMVvRbOEW3qL9UN2sLL3nGDkEmy/Zye+SWb1zJDJEjrSkB+7ZRLfNXnuG7knVP1yjLr2GPsPl5/dbwWq43cBWZS+t+ECYFlJb8SVYM+SJaY96QSrB5WuR1wU0hoRBn6s+5bJbGl+9syC7T4MD87itDfIGrQYUmUcaEosT5qcuo48NwvvX1LCohnykduT8E2lHzFofXNtcC+k2jjQHAlse3vjhPxnoVl0rY6YksDdQMlw38iv//j8hTBsadPE5mB86W7EMlfHIuYO0r/0okKgENgYAXyHd8gPbNiSaaXxB++996m92wwL79kQEX6U71ZfTOi0951ltiiF1TzMpztOfJxCblyIUm1+BKfy0vqEl+LnPFQNg24Z2OFfy7hn2h3nqCsM1mXskxsL73GZK6uTG4E1l9sRK9dGOKvN/SoR65QFTZv1J2IoHas0v5pLIVAIFAI7QmC/C0bg+X1Ce5r24OzVSSMY+em5IFlX0laBCH4b/ty2rF4W6R6ZVw2zECgECoHFIFCCcTRyyMZmMNeuzWHI+0k27lhu3SGXgDJ7lbhNuaK5RvbqHGrchUAhUAjMDYESjP8PrV+I8MO9UmywO01mX9X9qpA9Vodtlt7HvyqA1zyGEajUQmCZESjBuMxPp8ZWCBQChUAhsHAESjAuHPLqsBAoBAqBVUJg9eZCMPpOrmg0KgwKg1oDtQZqDdQaODzBOKp/hUAhUAgUAoVAIfA3BAjG/i8y7Jf7mudoVBgUBrUGag3UGli/Bn5LMI7qXyFQCBQChUAhUAj8DYESjH/Dof7f6wjU+AuBQqAQmBECJRhnBGQ1UwgUAoVAIbAaCJRgXI3nWLMoBFYJgZpLIbCrCJRg3FX4q/NCoBAoBAqBZUOgBOOyPZEaTyFQCBQCq4TAHpxLCcY9+NBqyIVAIVAIFALzQ6AE4/ywrZYLgUKgECgE9iACQ4LxGJnHiTo0zd8jVMbfLlTPH/j19wzTxF4O47H/ff4/dqjN62i5PmToMCF5h0jc8pWZRDD5x5QVjpn/uuUOnfvNgrrHTyH1xO5zu6Ng7CdNC48N+RNUP0l891C/beWM8ajJ07frXA4GZY+VHONsBDPpSV66cNyM6JOhx4W2umbh9L7Ue2PI801UoRAoBFYBgSHBeM1M7DmhL4f+PXSN0Ebh75J5hRAG857E9wudObTXA4Z+q0ziuaGHh8wL3TXXtwthqodKfIuQMl9K/JHQg0MP6NAjc+3PV108MQFxvcT/GvpqCL6XS7xRIIDV+VwKvTN0z9CpQzsNp0gDLw/5W5TnTvyi0ANDlwl1w0lyc4OQ/M8nPlNoUiAU35pM80LfyvU/heCUaNcDLCkDYoP5r/z3ptAnQv5OZaKpg/Lm+q7U+H1oN8MJ0/kRQhUKgUJgBggMCcanpF3M/yuJhevkP9ZCosHghbxacgiSZye+TQizTbQ04XQZyYVChHiiTQOriMC7W0o+IXTj0K1DBOAZE186BLs/JX5QiLDy9xxhpp7yjW6SfLj8LrHAOrlXLr4bEmB3JBcTiLC5UvL8EeUnJr5j6FOhnQSCgcLDAvxiGvpZ6BGhm4YoOInWAgHg7zceOSmHDW0U/ADzu1OgzV38zNzDKdHuhQM9w/KquW6C+pe5pgy8NPEfQ1sJf05hCpP18fNc71YwF+uDorZbY6h+C4GVQgBz70/of5PgRSfcPpjrc4YuGZoUzpCMo4d+G/peCCNNtFThOBnNKUMstkSbBu7Ry6YUIfGOxJjmfydmMT00MWGSaBzg9Ytc/SE0FFgTcGy4KP/jFHxv6EOh84fOF5oUWGjcfKwbwtc4JpWdNp3rm4D3zH59oBJX6styrY9Ea+E7uWIVfTbxRoFleYkUeEyo/fbiC3PNkk60FOE+GQWLMdHKhLNkJlcMEZCJKhQChcBOERgSjK3N3+TilSF7KVylhF9u1wUW2HmSws1HeORyXcCACSX7TfYg3XcLsFy0Kx/R6KV1y7BSpLNM7e+18vbq9N8tO6trFhxhRCk4WRrt9kP4fyxpWwksPPtRhGKr96tcvDjE0iaEWYS5XRf0y9olXP6yLmfyDYzsE3OvwfQoKdp9zua+qcTDAAAOrUlEQVRlT+zwSdc+S8OzYSUnaTAY90YCWTs3T80Lhgh8Vq12p1FEjIci4jlba+oZtzn062P+nrt8pIy+0+1IWfXbWoEnDFi65nqXFLplqKWr29rrY5Ri4yB/0vq1Tj077bhWwRj0ZT7GYk6wNVbrVr5yjbRvvPKRMm0+yqhvvsbsucpXTh33J08h7n3KqXF6rvA0HvXMn7fHnjhK8VUINYdCYL4IdBnmUE8OFnw4GawW+1r9F9teIgZgjybF1gUM4c5JcaDj0YlfH+JC9FLncuQF5rp7cm648Z6a2J4NF5+XPrcj7bPQ3p4bbs2LJL5u6Bmh14b6+2FJmkn4dlr5eAizeUHiy4cIy0QjliHLsVla0jYiDAoDHSpjj+/TyThX6MShfiCYCaWuhdov0733LLi+4Wyf81nJtJ/J4m+CD6awPFXyCIR7JL5DyFwTbSsQBqzP16U2AW5f9VW55r5ONDHIZ2Ham+aCtt9KqD4vNV4T4rJugoJwuH3SnhSyJrho7d1eKvcEAaz0y5Vr/p4ZS936o7xRMFjvLCyWo/1j69PaghXs0tRasE71d/+kWJ+vTnzfEMwILPuu1jSruGF3seRzlb8/8Q1DFMo7JVbGfOS3+VhP8rjHzYe7HX4XTXnzIezsVxvfvZMm/VqJnxay9rngzZHgJ2DNRzlriaJl3ISmd4yrf17vSoZToRBYLQQ2E4ysRoKLpuol71p8hBfGhTlw83WRaUIPU3f4wt4T6wgjuFkKevEJWy8+ISMfY9QOpkWoptg4cFPShAkXLl57oBi5fSttY8rjgjP8z7wJai5EDBcGmCOmam/pC+nLuBJtGAgjDMxBl6GChKuDTjR7QqGreGB29o7elopD1niSDwqwpTxgnhiiPT57mcZOOKjARU74EMhcug4SEY4Oy8jfDrF+H5aK+tPv43PNdQ03LtbcDgbrg6JBsLC8WNaYOOvTnqz6MFfZ+DF7z0Q/rD/rzPitDc9FHdYa6whuxkJAq6Pdn6YhQktdAol7mwVmPSZrLRB+/5w7yoo+rc835J4g5bYk3Kw/c+y+E9qjGFCGzOejqQNb82Fxw4XAS/KIdU1ovzk32jcm1p2YsEvyyHjb2rfenp5Ewtr6ZAE3l7Vyxmkf3LV1o6x3yntnfVmLqV6hEFguBJZxNJsJRmN20tLpQhorASkNYQqY0NDek/0rlskrUhCzoqmzPgk2Wi6mgbEQroQMxi/vhynPZUojz+XoM/nPSUxtfDPX+sJ8fpBre19eeGPI7Vo4e64wfYy+EY2dVq6NliamWaf4YOAepqGzQjAsh2jekpIslsa4crsuON3pAI620deT6zASRprLwcAi/35yjAWjz+U4sHDgzY06TtjkPwyeJQgvz4vQ0e6/pJ7+b5t43oGgJwwcSMKorREW3aR+CSn7rNaHddDGLSa4CAWWjnVivRBgTvMSgoQ6YkkShJ45j4Ny9kkJa9aWdGumPwZjtT5h1M9zghgRPPZerU+ncvVtfRLmFEKfuXTrmg83u/lQ+KyB/0kB64AlSdCyGs1DG8kaaYMwtfYJNfMhbNUn3K19Hoy29n+USu5hQ6HI7brAErV2CHdrwLvCGmXRrytYN4VAITCMwDSCkcByKIPVQ1tm1XhxMQ4Cx4vfbV2bXtizJtG+GuaAMCl5yrPyuF8JGGW8yE4HEr6pdlDwgneZm3sauPZQt4J2WRmYUCNuL24w+4UtTcwV163bvdYHLV09zF27GDCtnIvSic5uedeUCC5nbSPXLAJtyR8iAh6TZUHT9OHLrUeB8I0hvIbq9dPOmwSWNuHf7c+eKKZKaPeViFSZS8D0WSqYPkuvKTqTOjPH/vM1D6dGrSPMnouU4kBgeL4EDWu+36a5Wxvifl7/Xr+om04Ie3aEL+xanud0ttwQ2ASZet0xJ2st6FuZluCecCTkzIfw8z5QEClSlDmeEHGr02J1u/2417d10l/76lAWCHJryhaGuVAwKabyiwqBQmATBIZerH4VDIIVYp+L24qm2txjQ9aMNmmrBKo9JC9mlzDor6UTVsyFE3PBsWZo2oRkknY9EPyYFuaDCbEEWHTGidlfejQaOYFprhsNlmuYEPW5w6RyyhCelAd7RA6fnDaFafhD+CZrMHguMvpCyPPzOUaXuSo3byLUuDC324/6BEmrz8piPfpEwv6dfTZrpuXPKrYuWeqUE+tgVu1SsliSrT3zsT3BzX3tJFIknILO5Y6C9Ukg2iO372iflQVPadpRw1W5ENgvCGzG2BsOtHcvGHedPbPTJMPeFcsgl+sCjRZTp907wLAus3NjL8wBCtqtQwLclItm3p3hrLvkLnNgBfNqGVxzDrI4qGF+9oqmwY+lQOi1doZibkQuSAdiMEsWNEUElkPlJ6UR5NyXQ/nGD+uhvHmlcVMScCy47fRh/oQJ4X7lNGDfjOVmb9leaZJmHihC3KzWAOuu24H1AF8WXzd92mvzIezNxw9psHq5Z60p3gb507Y1qRys7Yfa17RfyVvAnW+PtfYZJ6FW6YVAB4FpGLviBKBTeQQCq4m15KDEkCDzYtoH0bbTgdyP2mjESuRi5JblSrV3w7ps+csScwEOuR65pezbOACxFUbGep7kKsb84YApO+BB6HIZbgULglV54+5bjdLtZRKOrhdFPAXWjX2/rfZpbVg79gjhfP00QPCzFGGf25mFbkNcoAS6vnhICMiWz4Lk8rbGW9q0MS8KNy1B5d1wgMj745d3vFfTtrNZOUrVOVLIHPxwgQNZTsReJWn25BNVKAQKgY0Q8IIO5XuBMQGxfIyJIMSUuBjti3jx5CHltMX9hKEQHr5nc2qV9krzZm36mJ1LsisInb7kvrLv2DRaaa61JU/b7vWF3Ld0fUtrZJ8GM2WlNXIAhZDmZmppYmNp9fqxPUQHbbjV9CWfxWAeFAWChiCTbrzKGBeS1sg9S5Ab0D6ldOX7+GoPvhgooegghrIw0K+YwBNL7xOLw+cfjus78dhwMQ9zkOc5qqc9+YSP5yltIzI3dZRxLe6SZ2cPWnvGp22HrxyCsQ5av9063Wvzsmdt/UgXs3Lslxl3w1nbsDMGVptrafqzPtzDW750bTXSBoKF8aKh8sbKe0GA2bfl6jx9GvHcCTNCkdUHD6QffabIWjAf+9LmIV/sRLY9S59k6KMVNnbjhV0bjzTrQ7q2pWtHHbF0JN2cKBBc8MbjeXPNNtepw0PeXYd7vHfag4Fy+tFmUSFQCHQQ8JJ0bseXXJwOmNAwacyEmxeQ1s+V5cSgvUDarkMRfsfTz2zRrJ3cdPTcKU6HFGjDhKK9E8ze5xkOBXhZxdxsD0mvDp04redlx1T8EgxGy/q5evK1x8L0DaOPmvVJc8dMaMT6UDdFR4SPwxmslc1oo8M33JsYoM9H7GmZF2vZvo3Tihi+Prk+4UUbR5inso0weLhxY2qPta28eqxDeGNQ8h228Ru19s4wYEKSpeRTDrg4qm/ubT/RfBupb2xcjE6nOs5vDJ6Ngx4Ep7Lw42KDmfaVgT3mLb9PPj2Au71h8+UCVBcTVtYaIogxfFavg07meNJk+jwh0abBWvK8ufusIZibI3cglz3cuLE1xI0KD4IURgQ7hUu/5mJOvBKUnjZG9Vhl9nIdwJJnfcOBADEfa0Y5RIhw71u32rR2fWtJwfHcPQvfi8LSM7devSPqIvPhFfE5hvVgzHD0PlEoWby+1STQzJXSZD6EHC8FrH3P61S0tW++ngFMPX/jtfa1TcATeFzNvBJcvbYwrDHr1pqgpNibtc8JH58iUV6N33hXi2o2hcAOEcDU+k3QZh36ILDsLXbzMW3M2f5XS8cEaNheRN/PEaDyfO4gzcvbCJPBuOU7Zeg7K8wU03LUnqDwjZ2DA/rWNuvPy+3Iub0ZdQlUv1GJiWJe0mZJGBembtyYiP60T6DDxWlcVqM0zMwYCSLfvmHi0hu5962ieSqLaPBO4WLArZwYZpgpy9Y9gid3JKwc5GkYyOsTVykMfWKibc+SAuJUsXZaeczZQR/f+dnjaumTYu3aD1Pe2LvlzMez9Kz9UhJXpL55Crp9duv0r5WjbHiW2oMDC8t9K8uapgQ5Xel5wISgIcBYdzDz832EKSFtHK2uGG6Eg8NeXP3GrB/rzTPmzlaukXXq+VuzYsTr4CCTMtzpFBDPEZ7SGpmPZ0X4mI95UKrctzIsYYLZJxnm414Za4hSZm9aDFc/aNHWm/1P47X2KVCeB6ycASD4XpIO/NYxPI1DmncFJtaDd817CjtzSPEKhUAh0EVgSDDSjL1UjQg9TEU9VokTmu0ew/QitrJi94Sa8hgkxiwdI+Nak45o+/oiZFg0mAMmTYDYL8MIvPjqNrJnggFi9C2NJYE5aE+7syDzJAQxV3PBlPWnf0wYw9EPwc0qlrcRmRNGp44Tvt2yGLR+5Jmzubd7TA2e3fIYKCtK+SGCI2YLV7/aw9pp41UefsbTbdOYnI6V3yfuTB/Jt/Lahbe5t7Lq8iIoY7wUhbZGWpnNYoKJ0NMGAcvt2K2jP8qT520NKk+weSbGw5JTtxFvgDrdNghEpz9ZjtpXt5UnvLplXXtmvnVURvuEinR9E/zSkbz+fClErYy13xdCxubdMh9CzbOHm7XtmVkH2m5krLw18luaZ0GAO/3rWatv3erLyW912vNo74e1YLza8f6aT1EhsKwI7Mq4hgTjrgykOt23CHDPWof2CFcBhFWbzyo8k5pDIbAlBDCkLVWowoXAjBBwuMSnP/bX7KPZO7OfbM9sRl0stJk2H/ur9vG4Xu37+WxpoQOpzgqBQmBnCJRg3Bl+E2tXxlQI2PPiTrd/yu03VaUlLsRdyd1rPtzPSzzUGlohUAhMQqAE4yRkKn3eCNjHJTzafpnY3mLbx5t3/7Nuf2g+9qbtNc66r2qvECgE5ohACcY5gltNrwoCNY9CoBDYTwiUYNxPT7vmWggUAoVAIbApAiUYN4WoChQChcAqIVBzKQQ2Q6AE42YIVX4hUAgUAoXAvkLg/wAAAP//oZzWtQAAAAZJREFUAwDuHZQ4qROaxgAAAABJRU5ErkJggg==\"\u003e\u003c/p\u003e\n \u003cp\u003eslightly high. All participants were healthy, with a mean age of 54\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1 years. The results of hematology, serum biochemistry, hepatic function, and renal function showed no significant differences before and after the consumption of either of the two meal types (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eChanges in serum glucose and insulin levels\u003c/h3\u003e\n\u003cp\u003eFigure 1A, B illustrates the changes, incremental area under the curve (IAUC), and \u003cem\u003e\u0026Delta;C\u003c/em\u003e\u003csub\u003emax\u003c/sub\u003e of serum glucose and insulin levels. At 45 and 60 min after test meal consumption, the serum glucose levels were significantly lower in the BVS group than in the B group, indicating that the increase in serum glucose level was slower in the BVS group. Similarly, IAUC and \u003cem\u003e\u0026Delta;C\u003c/em\u003e\u003csub\u003emax\u003c/sub\u003e of the serum glucose levels were significantly lower in the BVS group than in the B Group.The serum insulin levels as well as the IAUC and \u003cem\u003e\u0026Delta;C\u003c/em\u003e\u003csub\u003emax\u003c/sub\u003e, in the BVS group were significantly lower than those in the B group at 45 and 60 min following test meal consumption.\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eChanges in serum triglyceride levels\u003c/h2\u003e\n \u003cp\u003eAs shown in Fig.\u0026nbsp;1C, the serum triglyceride levels were significantly higher in the BVS group than in the B group at 120 min after test meal consumption.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eChanges in serum GIP levels\u003c/h2\u003e\n \u003cp\u003eAs shown in Fig.\u0026nbsp;1D, the serum GIP levels as well as the IAUC were significantly higher in the BVS group than in the B group at 30\u0026ndash;120 min following meal consumption.\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study demonstrated that the simultaneous consumption of vegetable salad and carbohydrate-rich foods, such as bread, attenuates the postprandial elevation of serum glucose levels (Fig.\u0026nbsp;1A). Although the \u0026ldquo;salad-first\u0026rdquo; approach\u0026mdash;consuming vegetables before carbohydrate-rich foods\u0026mdash;has been effective in moderating postprandial glycemic responses, reports on the effects of concurrent intake, particularly in the context of composite meals (e.g., sandwiches or burritos) where sequential consumption is impractical, remain limited. Results of the current study suggest that the simultaneous intake of vegetables and carbohydrates can be beneficial in blunting glycemic excursions, offering a more feasible dietary strategy for daily life.\u003c/p\u003e\u003cp\u003eCabbage, the primary component of the salad used in this study, is rich in insoluble dietary fiber, specifically cellulose. This type of fiber increases the viscosity of gastrointestinal contents and physically impedes the diffusion of nutrients and digestive enzymes, potentially slowing carbohydrate digestion and absorption [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Furthermore, cabbage contains rutin, a polyphenol that inhibits α-glucosidase activity and improves glucose metabolism, contributing to the suppression of carbohydrate breakdown and absorption [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMoreover, the salad was mixed with mayonnaise, which contains dietary fats that prolong gastric emptying time, thereby delaying the transfer of nutrients to the small intestine. The acetic acid present in mayonnaise\u0026mdash;derived from vinegar\u0026mdash;can also suppress postprandial glycemic elevation by delaying gastric emptying and potentially enhancing insulin sensitivity [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. These combined effects likely contributed to the observed reduction in postprandial serum glucose levels.\u003c/p\u003e\u003cp\u003eInterestingly, despite the elevated serum GIP levels observed in the BVS group, the serum glucose and insulin levels were lower than those in the control. GIP is secreted from K-cells in the upper small intestine in response to dietary carbohydrate and fat intake, and acts on pancreatic β-cells to promote insulin secretion [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, GIP exerts its insulinotropic effects in a glucose-dependent manner; when blood glucose levels are low or only mildly elevated, GIP cannot substantially stimulate insulin secretion. Indeed, Meier et al. and Nauck et al. reported that elevated GIP concentrations do not necessarily result in enhanced insulin secretion when glycemic levels remain low [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The present findings align with this physiological mechanism. Therefore, enhanced GIP secretion, combined with modest postprandial glycemia, may support glucose regulation without excessive insulin demand.\u003c/p\u003e\u003cp\u003eThus, these findings suggest that glycemic response reduction observed in this study is likely attributable to the combined effects of dietary fiber, polyphenols, fat, and acetic acid. These components may act synergistically to slow the digestion and absorption of nutrients while modulating the secretion of incretin hormones. Notably, effective glycemic control was achieved without the need to consume vegetables prior to carbohydrates, indicating such simultaneous intake as a metabolically favorable strategy [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This dietary approach is practical and sustainable for busy individuals who may find strict food sequencing difficult to maintain.\u003c/p\u003e\u003cp\u003eConsistent with these results, Fukuda et al. reported that the combination of dietary fiber, vinegar (acetic acid), and fat produced a greater glycemic-lowering effect when consumed with rice, compared with any of these components alone. This finding supports the notion that multicomponent dietary strategies can act synergistically to enhance postprandial glycemic regulation, especially in typical mixed-meal settings. To further enhance postprandial glycemic regulation under realistic dietary conditions, future research should focus on identifying the optimal combinations of vegetables, dietary fibers, polyphenols, and accompanying condiments or fats.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe postprandial increase in serum glucose level was suppressed when bread was consumed simultaneously with vegetable salad and mayonnaise. This effect is likely attributable to multiple factors, including the dietary fiber and bioactive compounds contained in the vegetables as well as the fat and acetic acid present in the mayonnaise.\u003c/p\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eIn this study, the individual effects of vegetable salad and mayonnaise were not evaluated separately; therefore, it was not possible to clearly identify which component contributed to the observed effects. In addition, the actual rate of digestion in the gastrointestinal tract was not directly measured, which limited the understanding of the temporal dynamics of digestion and absorption.\u003c/p\u003e\u003cp\u003eTo clarify the underlying mechanism, evaluation of the biokinetics of the target component is required, particularly the assessment of its absorbability and receptor-binding capacity in the small intestine.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eAbreviations\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eBVS: Bread with vegetable salad; BMI: Body mass index; HbA1c: Hemoglobin A1c; GIP : Glucose-dependent insulinotropic polypeptide; IAUC: Incremental area under the curve; JSCC: Japan Society of Clinical Chemistry\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\u003cp\u003e This study was conducted in accordance with the Declaration of Helsinki, and with the approval of the Ethics Committee of Ueno Asagao Clinic (authorization no. 2024-03; 13th Mach, 2024). Written informed consent was obtained from all participants prior to their participation in the study. Participants received a thorough explanation of the study protocol and those who provided consent were included. The study was conducted at the Hakunan Clinic.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cp\u003eKU declare no conflict of interest. MWY, NK, YT and RM are employees of Kewpie Corporation. There are no other patents, products in development, or marketed products to declare.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMWY, NK, YT, RM, and KU approved the study concept and design. RM, as the principal investigator, was responsible for the study logistics, data acquisition, TT and RM for manuscript preparation. NK and YT were responsible for conducting the trial, data collection, and performing laboratory analysis. MWY and RM carried out the statistical analysis. KU supervised the study design and commented on the manuscript. All authors contributed to the intellectual content of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis study was supported entirely by a grant received from Kewpie Corporation, Japan. We thank DR. Hiroshi Sakai (Hakunan Clinic, Chiba, Japan) and Tatsuo Uetake (CX wellness Co. Inc., Tokyo, Japan) for Coordinate about this trial.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data presented in this study are available on request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGrundy SM, Pasternak R, Greenland P, Smith S, Fuster V. Metabolic Syndrome and Cardiovascular Risk: A Review. Front Cardiovasc Med. 2020;7:570553. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fcvm.2020.570553\u003c/span\u003e\u003cspan address=\"10.3389/fcvm.2020.570553\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQiao Q, Hu G, Tuomilehto J, Nakagami T, Balkau B, Borch-Johnsen K, et al. Age- and sex-specific prevalence of diabetes and impaired glucose regulation in 11 Asian cohorts. Diabetes Care. 2003;26:1770\u0026ndash;80. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2337/diacare.26.6.1770\u003c/span\u003e\u003cspan address=\"10.2337/diacare.26.6.1770\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDECODE Study Group, the European Diabetes Epidemiology Group. Glucose tolerance and cardiovascular mortality: comparison of fasting and 2-hour diagnostic criteria. Arch Intern Med. 2001;161:397\u0026ndash;405. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/archinte.161.3.397\u003c/span\u003e\u003cspan address=\"10.1001/archinte.161.3.397\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNakagami T, Qiao Q, Tuomilehto J, Balkau B, Tajima N, Hu G, et al. Screen-detected diabetes, hypertension and hypercholesterolemia as predictors of cardiovascular mortality in five populations of Asian origin: the DECODA study. Eur J Cardiovasc Prev Rehabil. 2006;13:555\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/01.hjr.0000183916.28354.69\u003c/span\u003e\u003cspan address=\"10.1097/01.hjr.0000183916.28354.69\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLevitan EB, Song Y, Ford ES, Liu S. Is nondiabetic hyperglycemia a risk factor for cardiovascular disease? A meta-analysis of prospective studies. Arch Intern Med. 2004;164:2147\u0026ndash;55. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/archinte.164.19.2147\u003c/span\u003e\u003cspan address=\"10.1001/archinte.164.19.2147\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalmer\u0026oacute;n J, Ascherio A, Rimm EB, Colditz GA, Spiegelman D, Jenkins DJ, et al. Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care. 1997;20:545\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2337/diacare.20.4.545\u003c/span\u003e\u003cspan address=\"10.2337/diacare.20.4.545\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFord ES, Mokdad AH. Fruit and vegetable consumption and diabetes mellitus incidence among U.S. adults. Prev Med. 2001;32:33\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1006/pmed.2000.0772\u003c/span\u003e\u003cspan address=\"10.1006/pmed.2000.0772\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang PY, Fang JC, Gao ZH, Zhang C, Xie SY. Higher intake of fruits, vegetables or their fiber reduces the risk of type 2 diabetes: a meta-analysis. J Diabetes Investig. 2016;7:56\u0026ndash;69. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/jdi.12376\u003c/span\u003e\u003cspan address=\"10.1111/jdi.12376\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTang GY, Meng X, Li Y, Zhao CN, Liu Q, Li HB. Effects of vegetables on cardiovascular diseases and related mechanisms. Nutrients. 2017;9:857. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu9080857\u003c/span\u003e\u003cspan address=\"10.3390/nu9080857\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2017 Aug 10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTanaka T, Sakamoto H, Matsuoka R, Utsunomiya K. Ingestion of vegetable salads before rice inhibits the increase in postprandial serum glucose levels in healthy subjects. Biosci Biotechnol Biochem. 2023;87:1212\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/bbb/zbad085\u003c/span\u003e\u003cspan address=\"10.1093/bbb/zbad085\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAiba M, Kawahigashi M, Kawano T, Ebisuya Y, Fujimoto Y, Hashida S. Effects of meal sequence on postprandial blood glucose and urinary insulin excretion. Tokushima Bunri Univ Res Bull. 2018;96:45\u0026ndash;52. (in Japanese).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMaruyama C, Kikuchi N, Masuya Y, Hirota S, Araki R, Maruyama T. Effects of green-leafy vegetable intake on postprandial glycemic and lipidemic responses and α-tocopherol concentration in normal weight and obese men. J Nutr Sci Vitaminol (Tokyo). 2013;59:264\u0026ndash;71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3177/jnsv.59.264\u003c/span\u003e\u003cspan address=\"10.3177/jnsv.59.264\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eImai S, Fukui M, Kajiyama S. Effect of eating vegetables before carbohydrates on glucose excursions in patients with type 2 diabetes. J Clin Biochem Nutr. 2014;54:7\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3164/jcbn.13-67\u003c/span\u003e\u003cspan address=\"10.3164/jcbn.13-67\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKanamoto I, Inoue Y, Moriuchi T, Yamada Y, Imura H, Sato S. Effect of differences in low glycemic index food intake sequence on plasma glucose profile. J Japan Diabetes Soc. 2010;53:96\u0026ndash;101. (in Japanese).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKawakita K, Kimoto S, Takenoyama S, Murokuruma M, Ogawa T. Effect of food intake sequence on postprandial blood glucose and triglyceride levels: differences due to dressing. South Kyushu Univ Res Bull. 2017;47A:11\u0026ndash;8. (in Japanese).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKato Y. Influence of water-insoluble dietary fiber on in vitro glucose diffusion speed. Nippon Eiyo Shokuryo Gakkaishi (Journal Japan Soc Nutr Food Sciences). 1993;46:351\u0026ndash;5. (in Japanese).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKato Y, Tanaka J. Influence of commercial cellulose powder and pectin on in vitro glucose diffusion speed. Bull Fac Educ. 1999;81:93\u0026ndash;9. (in Japanese).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePapoutsis K, Zhang J, Bowyer MC, Brunton N, Gibney ER, Lyng J. Fruit, vegetables, and mushrooms for the preparation of extracts with α-amylase and α-glucosidase inhibition properties: a review. Food Chem. 2021;338:128119. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.foodchem.2020.128119\u003c/span\u003e\u003cspan address=\"10.1016/j.foodchem.2020.128119\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTabatabai A, Li S. Dietary fiber and type 2 diabetes. Clin Excell Nurse Pract. 2000;4:272\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiljeberg H, Bj\u0026ouml;rck I. Delayed gastric emptying rate may explain improved glycaemia in healthy subjects to a starchy meal with added vinegar. Eur J Clin Nutr. 1998;52:368\u0026ndash;71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/sj.ejcn.1600572\u003c/span\u003e\u003cspan address=\"10.1038/sj.ejcn.1600572\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEndo M, Matsuoka T. Effects of vinegar on suppression of postprandial blood glucose rise. J Japan Diabetes Soc. 2011;54:192\u0026ndash;9. (in Japanese).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eM\u0026uuml;ller TD, Adriaenssens A, Ahr\u0026eacute;n B, Bl\u0026uuml;her M, Birkenfeld AL, Campbell JE. Glucose-dependent insulinotropic polypeptide (GIP). Mol Metab. 2025;95:102118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.molmet.2025.102118\u003c/span\u003e\u003cspan address=\"10.1016/j.molmet.2025.102118\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNauck MA, Heimesaat MM, Orskov C, Holst JJ, Ebert R, Creutzfeldt W. Preserved incretin activity of glucagon-like peptide 1 [7\u0026ndash;36 amide] but not of synthetic human gastric inhibitory polypeptide in patients with type-2 diabetes mellitus. J Clin Invest. 1993;91:301\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1172/JCI116186\u003c/span\u003e\u003cspan address=\"10.1172/JCI116186\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeier JJ, Gallwitz B, Siepmann N, Holst JJ, Deacon CF, Schmidt WE, et al. Gastric inhibitory polypeptide (GIP) dose-dependently stimulates glucagon secretion in healthy human subjects at euglycaemia. Diabetologia. 2003;46:798\u0026ndash;801. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00125-003-1103-y\u003c/span\u003e\u003cspan address=\"10.1007/s00125-003-1103-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFukuda N, Murata K, Mori M, Hiroi Y, Asato R, Henmi I, et al. Improvement of glycemic index (GI) by vegetable intake and its application to diabetic diet. Igaku Seibutsugaku (Medicine Biology. 2005;149:331\u0026ndash;6. (in Japanese).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Vegetable salad, Bread, Postprandial serum glucose, Crossover study","lastPublishedDoi":"10.21203/rs.3.rs-8220213/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8220213/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to evaluate the effect of simultaneous consumption of vegetables and bread on postprandial serum glucose concentration. In total, 15 healthy men were given meals (bread vs. bread with vegetable salad) after a night of fasting. At 0, 15, 30, 45, 60, 90, and 120 min following the consumption of the test meal, blood samples were collected to determine the serum levels of glucose, insulin, glucose-dependent insulinotropic polypeptide, and triglycerides.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults revealed that serum glucose and insulin levels were significantly lower after 45 and 60 min in participants who consumed bread with vegetable salad than in those who only consumed bread. This emphasizes the potential benefit of simultaneously consuming vegetables and bread as an effective dietary strategy for preventing postprandial blood glucose elevation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTrial registration: UMIN Clinical Trials Registry (UMIN-CTR), UMIN000053931, registered on March 22, 2024.\u003c/p\u003e","manuscriptTitle":"Simultaneous Consumption of Vegetable Salad with Bread Attenuates Postprandial Serum Glucose Elevation in Healthy Adults: A Single-ingestion Open-label Trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-16 01:06:17","doi":"10.21203/rs.3.rs-8220213/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-06T16:38:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-08T22:16:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-17T06:34:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"231446457288566840358510035844032311372","date":"2025-12-15T22:56:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"237246805450430857709765221375132881389","date":"2025-12-10T10:42:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-10T05:58:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-10T05:48:51+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-09T11:32:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-09T09:32:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Research Notes","date":"2025-12-09T09:20:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"71d211fe-0493-488f-9d22-474cfae08b0b","owner":[],"postedDate":"December 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-21T16:53:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-16 01:06:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8220213","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8220213","identity":"rs-8220213","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}