Exploring the Therapeutic Potential of Tranexamic Acid for Traumatic Brain Injury: A Rat Model Study

Exploring the Therapeutic Potential of Tranexamic Acid for Traumatic Brain Injury: A Rat Model Study | 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 Article Exploring the Therapeutic Potential of Tranexamic Acid for Traumatic Brain Injury: A Rat Model Study Kuan-Yu Chen, Jen-Chieh Liao, Ching-Lung Kuo, Chung-Che Lu, Tee-Tau Eric Nyam This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7165502/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Currently, there are no consistent findings regarding the effectiveness of Tranexamic Acid (TXA) treatment following traumatic brain injury (TBI) of varying severity. Anesthetized male Sprague-Dawley rats were divided into sham-operated, TBI (1.5 atm or 2.2 atm) + vehicle, and TBI + TXA groups. TXA was administered intraperitoneally at 0, 24, and 48 hours post-TBI at a dosage of 10 mg/kg/day for 3 consecutive days. Microglial and astrocyte activation, TNF-α expression, neuronal apoptosis, and cerebral injury volume on the ipsilateral side of the cortex were assessed using immunofluorescence or TTC staining. Brain edema and blood-brain barrier (BBB) permeability were evaluated using Evans blue injection, while motor function was assessed using the inclined plane test. The serum D-dimer was Pathological severity scores were evaluated using H.E. staining 72 hours after the initial injury. Compared with the TBI (1.5 atm and 2.2 atm) + vehicle group, the TBI + TXA 10 mg/kg group showed no significant improvement in motor dysfunction, reduction in body weight loss, decrease in BBB damage, or reduction in injury volume, neuronal apoptosis, or necrosis. Additionally, no significant decrease was observed in TBI-induced TNF-α expression in microglia and astrocytes, nor in pathological severity scores. Intraperitoneal administration of TXA at 10 mg/kg/day for three consecutive days did not show significant neuroprotective effects following TBI. Health sciences/Diseases Health sciences/Medical research Health sciences/Neurology Biological sciences/Neuroscience Tranexamic acid Traumatic brain injury Neuroprotection Microglial activation Blood-brain barrier Neuronal apoptosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Traumatic brain injury (TBI) remains one of the leading causes of death and severe disability worldwide [ 1 ]. Intracranial bleeding is a common finding in patients with TBI. Some intracranial hemorrhages enlarge after hospital admission, leading patients resulting in high mortality and disability rates [ 2 ]. Therefore, prevent bleeding and reduce hematoma size, which prevents secondary brain injury is an important issue to manage TBI patients. After TBI, the formation of micro-clots and vascular occlusion is a frequent event [ 3 ]. The mechanical destruction of brain parenchyma causes vascular rupture, the release and presentation of tissue factor, and the initiation of the clot formation process [ 4 ]. At the same time, t-plasminogen (t-PA) is released from the injured endothelium [ 5 ] to limit the overshooting of clot formation and to prevent vascular occlusion. D-dimer is the end product of clot, and high D-dimer level is associated with a poor outcome in patients with traumatic ICH [ 6 ]. Tranexamic acid (TXA, trans-4-aminomethyl cyclohexanecarboxylic acid), a plasminogen inhibitor with antifibrinolytic activity is usually used in patients with trauma [ 7 ]. TXA is a lysine analog that attaches to the lysine-binding sites on plasminogen and blocks its ability to bind fibrin. Blockage of the plasminogen-fibrin interaction prevents normal clot dissolution and allows for improved hemostasis [ 8 ]. Therefore, TXA can safely reduce the risk of death in bleeding trauma patients, as shown by the CRASH-2 study [ 9 , 10 ]. However, in clinical practice whether TXA results in improving neurologic outcomes are controversial, especially focusing on when the traumatic hemorrhage occurred. TXA administration in adult combat trauma patients was independently associated with decreased mortality and improved neurologic outcomes, with no increase in thromboembolic events [ 11 ]. TXA was identified as an independent factor associated with lower mortality in cerebral contusions or traumatic subarachnoid hemorrhage [ 12 ]. TXA is safe in patients with TBI and that treatment within 3 h of injury reduces head injury-related death. Patients should be treated as soon as possible after injury [ 13 ]. On the contrast, administration of a short dose of TXA does not lead to significant prevention of growth of posttraumatic hemorrhagic lesion or improvement of clinical outcomes [ 14 ]. In experimental studied, using a weight drop mode and hemorrhagic shock model, TXA (single dose of 10mg/Kg) did not modulate coagulation, inflammation, or biomarker generation in either the TBI or TBI/hemorrhagic shock murine models [ 15 ]. Using a controlled cortical impact model of TBI with TXA (single dose of 0.5 g/kg) was injected subcutaneously 30 minutes after TBI, it showed inhibition of fibrinolysis with TXA increased lesion volume by 25% compared with vehicle because of dysregulation of fibrinolysis may lead to sustained micro-thrombosis and accelerated lesion expansion [ 16 ]. However, using weight drop model of TBI with10mg/Kg attenuated cerebral inflammation and improved functional outcome [ 17 ]. Endogenous plasminogen-inhibitor-1 is released upon inflammatory stimuli via interleukin (IL)-1 [ 18 ] as well as tumor necrosis factor (TNF)-α [ 19 ]. Plasmin and plasminogen also demonstrate pro-inflammatory effects including cytokine production and the expression of several pro-inflammatory genes is altered in the cardiac setting following the administration of TXA and it demonstrates a reduction in the systemic-inflammatory-response-syndrome and subsequent vasopressor use [ 20 ]. Therefore, besides the inhibition of plasminogen, the effect of TXA on neuroinflammation after TBI is worth investigating because of exacerbated inflammatory response, or subsequent neuronal cell death via necrosis and apoptosis is a serious secondary injury after TBI [ 21 , 22 ]. The lateral fluid percussion (LFP) is a valid model for human TBI because it fulfills many of the expected criteria. Specifically, the magnitude of the force and mortality rate is similar to that which occurs in mild and moderate sports and car related injuries with the caveat that the pre-injury surgical interventions are unique to the animal model. There are both focal and diffuse changes detected after LFP and the lateralization of the impact allows one to compare the morphological damage on the side ipsilateral to the injury to that on the contralateral side [ 23 ]. The definition of injury severity from the fluid percussion traumatic brain injury animal model is the impact force range from 1.6 to 2.5 atm as moderate injury. The parameters to assess injury severity include mortality rate 10–25% and apnea around 20.3 seconds [ 24 ]. In current study, we hypothesized that treatment with TXA would attenuate post-traumatic neuronal inflammation and apoptosis and achieve neuroprotection. In this project, we will use lateral fluid percussion TBI model, a diffuse brain injury model, to give experimental rats 1.5atm (mild) and 2.2atm (moderate) impact force to create moderate brain injury, then To test this hypothesis, we investigated regional TNF-α expression in microglia and astrocyte and neuronal apoptosis in the cortex, and the functional outcome on the 3rd day after TBI. We also measured the peripheral D-dimer concentrations on day 3 after TBI. Our results will elucidate the neuroprotective effects of TXA on cerebral cortex via its anti-inflammatory effects after TBI. Methods Experimental design The overall experimental protocol including three parts is shown in Fig. 1 As shown in Fig. 1 , Tranexamic acid (10mg/kg) were given through intraperitoneal immediately after TBI and for 3 consecutive days. Microglia and astrocyte activation, TNF-α expression, neuronal apoptosis, cerebral injury volume in the ipsilateral injury side of cortex using immunofluorescence stain or TTC stain; brain edema BB permeability will evaluated by Evan’s blue injection; while the motor function will be tested by the inclined plane after 72 hours of the initial injury. The observational period set on the 3rd day after TBI was based on our previous study in TBI [ 25 ]. All of the tests were performed with investigators blinded to the study groups, which were revealed only at the end of the analysis. The animals were provided with food and water ad libitum throughout the study. At the end of the experiment, the rats were sacrificed with urethane. Animal Adult male Sprague-Dawley rats were used in the experiments. The animals were kept under a 12/12-h light/dark cycle and allowed free access to food and water. The Chi Mei Medical Center’s Animal Care and Use Committee approved (Protocol Number 113-06) all of the experimental procedures, which conformed to the NIH guidelines, including minimizing discomfort to the animals during surgery and during the recovery period. This study was also conducted and reported in accordance with the ARRIVE (Animal Research: Reporting of In Vivo Experiments) guidelines 2.0 [26]. Traumatic brain injury Animals were anesthetized with the intraperitoneal administration of a mixture of Zoletil 50, 0.2 ml/kg་10% Rompun 0.1 ml/kg, IM. On a stereotaxic frame, a 2mm craniectomy was performed 4mm from the bregma and 3mm from the sagittal sutures in the right parietal cortex. After craniectomy and implantation of the injury cannula, the fluid percussion device (VCU Biomedical Engineering, Richmond, VA, USA) was connected to the animal via Luer-lock fitting and the brain was injured with 1.5 and 2.2 atm at 25 ms percussion. This force produced mild and moderate to high brain trauma, as the definition of moderate injury severity from the fluid percussion traumatic brain injury animal model is the impact force range from 1.6 to 2.5 atm. A transient hypertensive response, apnea, and seizure were observed immediately following fluid percussion injury, and they were used as the criteria for successful TBI insulted rats. Treatment intervention The rats were numbered in random order and indicated to five groups according to the random number table. Each group consists sham operated (n = 6); Sham; TBI control (2.2atm) treated with vehicle; TBI (2.2atm) treated with TXA (n = 6 in each different dose). The dosage of TXA were given through an intra-peritoneal route for 3 doses (10mg/kg), the first one was given immediately after the injury, followed by a second injection 24 hours later and the last and third injection was 48 hours after the initial injury. All tests were performed with the investigators blinded to the study groups, which were revealed only at the conclusion of analysis. Motor function test An inclined plane is commonly used to measure limb strength [26]. The animals were placed facing right and then left, perpendicular to the slope of a 20 x20-cm buffer ribbed surface of an inclined plane initially positioned at a 30˚ angle. To determine the maximal angle at which an animal could remain on the inclined plane, the angle was increased or decreased in a 1˚ interval. Motor deficit measurements were conducted with left- and right-side maximal angles on the 3rd day after TBI. D-dimer test The concentration of serum D-dimer, draw from tail vein, was determined from day 0 to day 3 after TBI. D-dimer (CA-1500, Sysmex, Kobe, Japan) were performed using standard techniques by Chi-Mei medical center biochemistry laboratory for analysis. Histological examination 1. Cerebral injury volume assay The Triphenyltetrazolium chloride (TTC) staining procedures followed those described elsewhere [28]. All animals were euthanized on the 3rd day after fluid percussion injury. Under deep anesthesia with ketamine, animals were perfused intra-cardiac with saline. The brain tissue was then removed, immersed in cold saline for 5 min, and sliced into 1.0-mm sections. The brain slices were incubated in 2% TTC dissolved in phosphate-buffered saline for 30 min at 37 o C and then transferred to 5% formaldehyde solution for fixation. The volume of infarction, as revealed by negative TTC stains indicating dehydrogenase-deficient tissue, was measured in each slice and summed using computerized planimetry (PC-based Image Tools software). The volume of infarction was calculated as 1 mm (thickness of the slice) x (sum of the infarction area in all brain slices [mm 2 ]). The similar procedure will be performed for cardiomyocytes staining. 2. Neuronal apoptotic assay in neuronal cells in the cortex using immunofluorescence stain Neuronal apoptotic cells were identified at the 72nd-hour after TBI by staining with terminal deoxynucleotidyltransferase-mediated dUTP-biotin nick end labeling (TUNEL) [ 29 ]. The number of TUNEL-positive cells were calculated in 5 coronal sections from each rat in the samples and summed using computerized planimetry (PC-based Image Tools software). The following antibodies were used in this study: monoclonal mouse anti-NeuN antibody (NeuN, Millpore, MAB377) in 1:100 dilution and then detected with Alexa-Fluor ®, 568 anti-mouse (IgG) antibody (Invitrogen, A11031) in 1:400 dilution. a monoclonal rabbit anti-caspase-3 antibody (#9664, Cell Signaling Technology, Beverly, MA, USA) at a 1:400 dilution detected with an Alexa Fluor® 488 anti-rabbit (IgG) antibody (ab150073, Abcam in Boston, MA, USA) at a 1:1000 dilution. Table 1 showed the detailed information of antibodies used in current study. Table 1. The detailed information of antibodies used in current study 3. Blood–brain barrier permeability examination Blood–brain barrier (BBB) permeability was determined by Evans blue (EB) extravasation at 2th days after TBI. Briefly, 2% Evans blue was injected intravenously at a dose of 2 ml/kg. Animals were then re-anesthetized after 1h with urethane (1000 mg/kg) and perfused using saline to remove intravascular EB dye. Animals were then decapitated, the entire brains were removed and homogenized in phosphate buffered saline. Trichloroacetic acid was then added to precipitate protein, and the samples were cooled and centrifuged. The resulting supernatant was measured for absorbance of EB at 610 nm using a spectrophotometer [30]. 4. Microglia, astrocyte activation and TNF-α expression assay The activated microglia were evaluated on the 3rd day after TBI by detecting OX42 positive cells using an immunofluorescent assay [ 31 ]. The TNF-α expression in activated microglia were evaluated at the 72nd hour after TBI by detecting OX42 with TNF-α positive cells using an immune fluorescent assay. The number of OX42 and TNF-α positive cells in the samples were measured in each slice and summed using computerized planimetry (PC-Q4Q5 based Image Tools software). Monoclonal mouse anti-OX42 antibody (ab78457; Abcam, Boston, MA), anti-GFAP antibody (MA5-15086;Thermo USA), and polyclonal goat anti-TNF-α antibody (sc-1351; Santa Cruz Biotechnology Inc, Santa Cruz, CA) were used in this study and detected with Alexa-Fluor, 568 anti-mouse (IgG) antibody (A11031; Life Technologies Co, Grand Island, NY), and DyLight 488 anti-goat (IgG) antibody (ab96931; Abcam), respectively. 5. HE stain 5.1 Paraffin sections The wet tissues were trimmed, and processing with serial alcohol solution, xylene and wax by automated tissue processor (Shandon Excelsior, Thermo Scientific, UK). Next, the tissues were embedded by paraffin wax. The paraffin-embedded tissues were cut at a thickness of 5µm. 5.2 Pathologic severity grading The histopathological slides prepared from the submitted specimens were examined and recorded under a light microscope at magnifications of 20×, 40×, 100×, 200×, and 400×. Tissue lesions were evaluated based on severity, distribution, and the percentage of affected tissue. Lesions were graded according to the 5-point scoring system recommended by INHAND (International Harmonization of Nomenclature and Diagnostic Criteria) as follows: Grade 0: No significant pathological changes, lesions involve less than 1% of the total tissue. Grade 1 (Minimal): Lesions involve 1–5% of the tissue. Grade 2 (Mild): Lesions involve 6–25% of the tissue. Grade 3 (Moderate): Lesions involve 26–50% of the tissue. Grade 4 (Moderately Severe): Lesions involve 51–75% of the tissue. Grade 5 (Severe/High): Lesions involve more than 76% of the tissue [32]. 6. Statistical analysis The results are expressed as the means, standard errors of the means for n experiments. A two-way analysis of variance for repeated measurements (in the same animals) was used for factorial experiments, whereas Dunnett test was used for post hoc multiple comparisons among means. A p-value of < 0.05 was considered to indicate a significant difference. Results TXA treatment did not significantly reduce body weight loss or improve maximum angle performance at 72 hours after TBI. As shown in Table 1, there were no significant differences in body weight loss (n = 6 per group) or maximum angle performance (n = 6 per group) between the TBI + vehicle and TBI + TXA groups in both the 1.5 atm and 2.2 atm conditions. TXA treatment did not significantly reduce Evans blue extravasation or serum D-dimer levels at 72 hours after TBI. There were no significant differences in Evans blue extravasation in the peri-lesioned cortex (n = 6 per group, Table 1 between the TBI + vehicle and TBI + TXA groups under both 1.5 atm and 2.2 atm conditions. Similarly, the serum concentration of D-dimer showed no significant differences between the groups (n = 6 per group, Table 2). Table 2 . Transamine effects at 72 Hours Following Traumatic Brain Injury TBI, traumatic brain injury; TXA, transamine *P < 0.05, ***P < 0.001 compared with sham groups. ## P < 0.01, ### P < 0.001 compared with TBI 1.5atm + vehicle groups. zP < 0.001 compared with TBI þ vehicle groups. Although TXA treatment showed a trend toward decreasing injury volume at 72 hours after TBI, the difference was not statistically significant. At 72 hours after TBI, TTC-stained brain sections revealed a significant increase in injury volume in the vehicle-treated TBI groups (1.5 atm and 2.2 atm) compared to sham controls (***p < 0.001, Fig. 5 ). Although treatment with 10 mg/kg TXA showed a trend toward reduced injury volume in the TBI groups (1.5 atm and 2.2 atm), the difference was not statistically significant (n = 6 per group, Fig. 2). TXA treatment did not significantly reduce neuronal apoptosis at 72 hours after TBI. The TUNEL assay revealed no significant difference in the number of apoptotic neuronal cells (NeuN and TUNEL double-positive) in the peri-lesioned cortex between the TBI + vehicle and TBI + TXA groups (n = 6 per group, Fig. 3 ). Consistently, the number of NeuN and caspase-3 double-positive cells showed a similar pattern (Fig. 4 ). TXA treatment did not significantly reduce neuroinflammation at 72 hours after TBI. The neuroinflammation assay revealed no significant difference in the number of OX42 and TNF-α double-positive cells in the peri-lesioned cortex between the TBI + vehicle and TBI + TXA groups (n = 6 per group, Fig. 5 ). Similarly, the number of GFAP and TNF-α double-positive cells showed comparable results (Fig. 6). Figure 6 Effects of TXA injection on TBI-induced neuroinflammation, determined by the number of GFAP and TNF-α co-expressing cells in the peri-lesioned cortex at 72 hours post-TBI. ***p < 0.001; n = 6 per group. TXA treatment did not significantly decrease the pathological severity score for hemorrhages at 72 hours after TBI. There were no significant differences in the pathological severity scores for hemorrhage in the isocortex (n = 6 per group, Fig. 7 ) and corpus callosum (n = 6 per group, Fig. 8 ) between the TBI + vehicle and TBI + TXA groups. TXA treatment did not significantly reduce the pathological severity score for necrosis and atrophy at 72 hours after TBI. No significant differences were observed in the pathological severity scores for 弓necrosis in the isocortex (n = 6 per group, Fig. 9 ) and atrophy in hippocampus (n = 6 per group, Fig. 10 ) between the TBI + vehicle and TBI + TXA groups. Discussion This study employed a LFP model of TBI in rats to evaluate the neuroprotective potential of TXA. Mild (1.5 atm) and moderate (2.2 atm) injury intensities were applied, and TXA was administered intraperitoneally at a dose of 10 mg/kg at 0, 24, and 48 hours post-injury. Contrary to our initial hypothesis, TXA treatment did not result in significant improvements in motor function, reductions in neuronal apoptosis or neuroinflammation, preservation of blood-brain barrier (BBB) integrity, or decreased serum D-dimer levels at 72 hours post-TBI. Although a non-significant trend toward reduced lesion volume was observed, it did not reach statistical significance. Table 3 summarizes previous and current studies investigating the effects of TXA in TBI animal models. Our findings are consistent with earlier experimental studies reporting no significant impact of TXA on coagulation or inflammatory markers in TBI [15] and, in some cases, even an increase in lesion volume when administered subcutaneously at higher doses [16]. However, our results contrast with other reports demonstrating beneficial effects of TXA in experimental TBI [17,33,34]. Several factors may account for these discrepancies. Table 3. Studies of TXA effects on traumatic brain injury animal models First, the dosage and administration protocol used in our study were relatively conservative. We employed a cumulative dose of 30 mg/kg (10 mg/kg × 3), delivered intraperitoneally. In contrast, studies reporting positive effects used substantially higher single doses, such a s 30 mg/kg [34] or up to 100 mg/kg [33]. Griemert used higher doses, also reported negative outcomes [ 16 ]. Additionally, the intraperitoneal route, used in this study and others [15,35]—may result in reduced bioavailability and suboptimal pharmacokinetics compared to intravenous administration [33,34], potentially limiting therapeutic efficacy. Second, variations in injury models and animal species likely contributed to the differing results. We utilized an LFP model to induce mild and moderate injury, whereas many comparative studies used controlled cortical impact (CCI) or weight-drop models, which typically produce more severe and focal injuries. These model differences may influence the detectability of neuroprotective effects [17,33]. The LFP model, characterized by a combination of focal and diffuse injuries, may require distinct therapeutic strategies. Furthermore, our study used adult rats, while others employed mice, which may respond differently to both injury and pharmacologic interventions [34,35]. Third, the timing of our assessments may have limited our ability to detect therapeutic effects. Evaluations were performed only at 72 hours post-injury, without assessments during acute (1–24 hour) or chronic phases. This limited time window may have missed critical periods when TXA could have exerted measurable neuroprotective effects [17,33]. Lastly, although a comprehensive battery of outcome measures was used—including assessments of inflammation, apoptosis, BBB integrity, and motor function—none showed significant improvement with TXA treatment. This suggests that the dosing regimen and administration route employed in this study were insufficient to modify the key pathophysiological processes underlying TBI [35]. Based on our study and a review of the literature, we suggest that using mice as the experimental model, employing a controlled cortical impact (CCI) or weight-drop injury paradigm, administering a single high dose of the drug intravenously shortly after injury, and conducting early endpoint evaluations may be more appropriate for assessing the neuroprotective effects of TXA. This study has several limitations. The relatively short observation window (72 hours) may have precluded detection of delayed or long-term effects. Additionally, we did not evaluate dose-response relationships or alternative administration routes. Future investigations should explore varied dosing strategies, earlier intervention time points, and longer follow-up periods to more comprehensively evaluate the neuroprotective potential of TXA in TBI. Conclusion Under the conditions tested, TXA did not exhibit significant neuroprotective effects in a rat LFP model of TBI. These findings underscore the complexity of TBI pathophysiology and highlight the need for careful optimization of dosing, timing, and injury models when evaluating TXA or other antifibrinolytic agents in the context of TBI treatment. Declarations Conflicts of Interest: The authors have no relevant financial or non-financial interests to disclose Institutional Review Board Statement This study was approved by the Institutional Review Board of Chi Mei Medical Center, Tainan, Taiwan (IRB No. 11306). Informed Consent Statement : Not applicable. Data Availability Statement The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Funding: This research was supported by Chi Mei Medical Center (Grant No. CCFHR 11303). Author Contribution K-Y C, J-C L and C-L K conceived and designed the experiments. T-T E.N performed the experiments. K-Y C, J-C L, C-L K, H-YH, analyzed the data. 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Rapid and widespread microglial activation induced by traumatic brain injury in rat brain slices. J. Neurotrauma . 17 , 185–192 (2000). Shackelford, C. et al. Qualitative and quantitative analysis of nonneoplastic lesions in toxicology studies. Toxicol. Pathol. 30 (1), 93–106 (2002). Daglas, M. et al. Sex-dependent effects of tranexamic acid on blood-brain barrier permeability and the immune response following traumatic brain injury in mice. Thromb. Haemost . 18 , 2658–2671 (2020). Culkin, M. C. et al. Early posttraumatic brain injury tranexamic acid prevents blood-brain barrier hyperpermeability and improves surrogates of neuroclinical recovery. J. Trauma. Acute Care Surg. 95 (1), 47–54 (2023). Baucom, M. R. et al. Tranexamic acid administration does not alter inflammation after traumatic brain injury, regardless of timing. J. Surg. Res. 302 , 106–115 (2024). Statements & Declarations Additional Declarations No competing interests reported. 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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-7165502","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":499622394,"identity":"40e52d48-310b-4f30-9b09-17710ead1fbf","order_by":0,"name":"Kuan-Yu Chen","email":"","orcid":"","institution":"Chi-Mei Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Kuan-Yu","middleName":"","lastName":"Chen","suffix":""},{"id":499622396,"identity":"f85a0deb-5fc6-4070-9c0c-51543d9feaa1","order_by":1,"name":"Jen-Chieh Liao","email":"","orcid":"","institution":"Chi-Mei Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jen-Chieh","middleName":"","lastName":"Liao","suffix":""},{"id":499622399,"identity":"5bca9d29-f30d-4a3b-8262-d5fba82d33ff","order_by":2,"name":"Ching-Lung Kuo","email":"","orcid":"","institution":"Chi-Mei Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Ching-Lung","middleName":"","lastName":"Kuo","suffix":""},{"id":499622403,"identity":"3394faac-6556-4d9c-a78b-313817044695","order_by":3,"name":"Chung-Che Lu","email":"","orcid":"","institution":"Chi Mei Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chung-Che","middleName":"","lastName":"Lu","suffix":""},{"id":499622405,"identity":"9914f281-03f2-4395-bce7-53948d8422da","order_by":4,"name":"Tee-Tau Eric Nyam","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYLCCB2wgkvkAkJCQIU5LAlgLWwJICw8pWngMwCRB1ebtvQc/JJTZJPZL93x+daPGgoeB/fDRDfi0yJw5lyyRcC4tceacs9usc44BHcaTlnYDnxYJiRwDicS2w7kbbuRuM85hA2qR4DEjpMX4B0jL/hs5z4xz/hGnxQxii0QO8+PcNmK08JwxswD6pX7GjTQz5tw+CR42gn5h7zG+8aHMxph/RvLjzznf6uT42Q8fw6sFGbBJgElilYMA8wdSVI+CUTAKRsHIAQCUikX/dCwn1wAAAABJRU5ErkJggg==","orcid":"","institution":"Chi-Mei Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Tee-Tau","middleName":"Eric","lastName":"Nyam","suffix":""}],"badges":[],"createdAt":"2025-07-19 15:53:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7165502/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7165502/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89109259,"identity":"d2216ce6-e43c-401a-9865-eac8c0d59845","added_by":"auto","created_at":"2025-08-14 18:28:42","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":54641,"visible":true,"origin":"","legend":"\u003cp\u003eOverall experimental protocol of the current study\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165502/v1/4d5a0728503d6f0b841b5fef.jpg"},{"id":89109260,"identity":"6401f9a7-6440-4b91-9bc9-0b42fccff0cf","added_by":"auto","created_at":"2025-08-14 18:28:42","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":66634,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of TXA injection on TBI-induced injury volume in the peri-lesioned cortex at 72 hours post-TBI. ***p \u0026lt; 0.001, #p \u0026lt; 0.05; n = 6 per group.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165502/v1/e49381cc4822481b1f14ca40.jpg"},{"id":89108625,"identity":"c5c0b07c-bdbf-4c54-a42c-34108fc8b654","added_by":"auto","created_at":"2025-08-14 18:20:42","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":46101,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of TXA injection on TBI-induced neuronal apoptosis, as indicated by the number of NeuN and TUNEL double-positive cells in the peri-lesioned cortex at 72 hours post-TBI. ***p \u0026lt; 0.001; n = 6 per group.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165502/v1/a850e9d158e9cfb39c6aabfa.jpg"},{"id":89109488,"identity":"2ad5e813-69c5-47f5-8d53-340e21fed19d","added_by":"auto","created_at":"2025-08-14 18:36:42","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":47280,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of TXA injection on TBI-induced neuronal apoptosis, as indicated by the number of NeuN and TUNEL double-positive cells in the peri-lesioned cortex at 72 hours post-TBI. ***p \u0026lt; 0.001; n = 6 per group.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165502/v1/689497a1b53d3dfabe44063e.jpg"},{"id":89108629,"identity":"6c23450c-b402-4c18-92a1-e94096c079c7","added_by":"auto","created_at":"2025-08-14 18:20:42","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":45101,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of TXA injection on TBI-induced neuroinflammation, assessed by the number of OX42 and TNF-α double-positive cells in the peri-lesioned cortex at 72 hours post-TBI. ***p \u0026lt; 0.001; n = 6 per group.\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165502/v1/0565149e98cb9945c9f50d17.jpg"},{"id":89108626,"identity":"5adb3fe0-5c56-49a0-abcb-2e8b1d64cd36","added_by":"auto","created_at":"2025-08-14 18:20:42","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":52113,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of TXA injection on TBI-induced neuroinflammation, determined by the number of GFAP and TNF-α co-expressing cells in the peri-lesioned cortex at 72 hours post-TBI. ***p \u0026lt; 0.001; n = 6 per group.\u003c/p\u003e","description":"","filename":"Picture6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165502/v1/d055c3d245d37d0168e3f412.jpg"},{"id":89108635,"identity":"baa1f51f-b569-4d06-aefc-dd3add397ad1","added_by":"auto","created_at":"2025-08-14 18:20:42","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":34298,"visible":true,"origin":"","legend":"\u003cp\u003eHistopathological scoring of hemorrhagic lesions in the isocortex at 72 hours post-TBI following TXA injection. ***p \u0026lt; 0.001; **p \u0026lt; 0.01; n = 6 per group.\u003c/p\u003e","description":"","filename":"Picture7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165502/v1/6817b64279b6e0a954216921.jpg"},{"id":89109267,"identity":"64da1088-b10d-4377-b19d-ebaf51ccd0bd","added_by":"auto","created_at":"2025-08-14 18:28:42","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":38825,"visible":true,"origin":"","legend":"\u003cp\u003ePathological assessment of hemorrhagic severity in the corpus callosum at 72 hours post-TBI after TXA administration. ***p \u0026lt; 0.001; **p \u0026lt; 0.01; n = 6 per group.\u003c/p\u003e","description":"","filename":"Picture8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165502/v1/97d13247dcea79cfbbaedd39.jpg"},{"id":89109265,"identity":"3c295edf-fc89-478f-bd14-0cc33c908ff4","added_by":"auto","created_at":"2025-08-14 18:28:42","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":49854,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of TXA injection on TBI-induced necrosis severity scores in the isocortex at 72 hours post-injury. ***p \u0026lt; 0.001; **p \u0026lt; 0.01; n = 6 per group\u003c/p\u003e","description":"","filename":"Picture9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165502/v1/337ed3e2b4c8e3016c4d276d.jpg"},{"id":89108643,"identity":"d3d030bf-ce67-4b5c-ace6-7ab26f461bf9","added_by":"auto","created_at":"2025-08-14 18:20:42","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":42537,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of TXA injection on TBI-induced necrosis severity scores in the hippocampus at 72 hours post-injury. ***p \u0026lt; 0.001; **p \u0026lt; 0.01; n = 6 per group.\u003c/p\u003e","description":"","filename":"Picture10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165502/v1/940bf1ba453345f9270f31ae.jpg"},{"id":92600455,"identity":"1381080e-057d-4fac-8551-2714100bd638","added_by":"auto","created_at":"2025-10-01 14:22:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1683164,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7165502/v1/741077a7-1fc5-4dd2-ba1d-74e2231b1f25.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring the Therapeutic Potential of Tranexamic Acid for Traumatic Brain Injury: A Rat Model Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTraumatic brain injury (TBI) remains one of the leading causes of death and severe disability worldwide [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Intracranial bleeding is a common finding in patients with TBI. Some intracranial hemorrhages enlarge after hospital admission, leading patients resulting in high mortality and disability rates [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Therefore, prevent bleeding and reduce hematoma size, which prevents secondary brain injury is an important issue to manage TBI patients.\u003c/p\u003e\u003cp\u003eAfter TBI, the formation of micro-clots and vascular occlusion is a frequent event [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The mechanical destruction of brain parenchyma causes vascular rupture, the release and presentation of tissue factor, and the initiation of the clot formation process [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. At the same time, t-plasminogen (t-PA) is released from the injured endothelium [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e5\u003c/span\u003e] to limit the overshooting of clot formation and to prevent vascular occlusion. D-dimer is the end product of clot, and high D-dimer level is associated with a poor outcome in patients with traumatic ICH [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTranexamic acid (TXA, trans-4-aminomethyl cyclohexanecarboxylic acid), a plasminogen inhibitor with antifibrinolytic activity is usually used in patients with trauma [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. TXA is a lysine analog that attaches to the lysine-binding sites on plasminogen and blocks its ability to bind fibrin. Blockage of the plasminogen-fibrin interaction prevents normal clot dissolution and allows for improved hemostasis [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Therefore, TXA can safely reduce the risk of death in bleeding trauma patients, as shown by the CRASH-2 study [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, in clinical practice whether TXA results in improving neurologic outcomes are controversial, especially focusing on when the traumatic hemorrhage occurred. TXA administration in adult combat trauma patients was independently associated with decreased mortality and improved neurologic outcomes, with no increase in thromboembolic events [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. TXA was identified as an independent factor associated with lower mortality in cerebral contusions or traumatic subarachnoid hemorrhage [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. TXA is safe in patients with TBI and that treatment within 3 h of injury reduces head injury-related death. Patients should be treated as soon as possible after injury [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. On the contrast, administration of a short dose of TXA does not lead to significant prevention of growth of posttraumatic hemorrhagic lesion or improvement of clinical outcomes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn experimental studied, using a weight drop mode and hemorrhagic shock model, TXA (single dose of 10mg/Kg) did not modulate coagulation, inflammation, or biomarker generation in either the TBI or TBI/hemorrhagic shock murine models [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Using a controlled cortical impact model of TBI with TXA (single dose of 0.5 g/kg) was injected subcutaneously 30 minutes after TBI, it showed inhibition of fibrinolysis with TXA increased lesion volume by 25% compared with vehicle because of dysregulation of fibrinolysis may lead to sustained micro-thrombosis and accelerated lesion expansion [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, using weight drop model of TBI with10mg/Kg attenuated cerebral inflammation and improved functional outcome [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Endogenous plasminogen-inhibitor-1 is released upon inflammatory stimuli via interleukin (IL)-1 [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] as well as tumor necrosis factor (TNF)-α [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Plasmin and plasminogen also demonstrate pro-inflammatory effects including cytokine production and the expression of several pro-inflammatory genes is altered in the cardiac setting following the administration of TXA and it demonstrates a reduction in the systemic-inflammatory-response-syndrome and subsequent vasopressor use [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Therefore, besides the inhibition of plasminogen, the effect of TXA on neuroinflammation after TBI is worth investigating because of exacerbated inflammatory response, or subsequent neuronal cell death via necrosis and apoptosis is a serious secondary injury after TBI [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe lateral fluid percussion (LFP) is a valid model for human TBI because it fulfills many of the expected criteria. Specifically, the magnitude of the force and mortality rate is similar to that which occurs in mild and moderate sports and car related injuries with the caveat that the pre-injury surgical interventions are unique to the animal model. There are both focal and diffuse changes detected after LFP and the lateralization of the impact allows one to compare the morphological damage on the side ipsilateral to the injury to that on the contralateral side [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The definition of injury severity from the fluid percussion traumatic brain injury animal model is the impact force range from 1.6 to 2.5 atm as moderate injury. The parameters to assess injury severity include mortality rate 10\u0026ndash;25% and apnea around 20.3 seconds [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn current study, we hypothesized that treatment with TXA would attenuate post-traumatic neuronal inflammation and apoptosis and achieve neuroprotection. In this project, we will use lateral fluid percussion TBI model, a diffuse brain injury model, to give experimental rats 1.5atm (mild) and 2.2atm (moderate) impact force to create moderate brain injury, then To test this hypothesis, we investigated regional TNF-α expression in microglia and astrocyte and neuronal apoptosis in the cortex, and the functional outcome on the 3rd day after TBI. We also measured the peripheral D-dimer concentrations on day 3 after TBI. Our results will elucidate the neuroprotective effects of TXA on cerebral cortex via its anti-inflammatory effects after TBI.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eExperimental design\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe overall experimental protocol including three parts is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Tranexamic acid (10mg/kg) were given through intraperitoneal immediately after TBI and for 3 consecutive days. Microglia and astrocyte activation, TNF-α expression, neuronal apoptosis, cerebral injury volume in the ipsilateral injury side of cortex using immunofluorescence stain or TTC stain; brain edema BB permeability will evaluated by Evan\u0026rsquo;s blue injection; while the motor function will be tested by the inclined plane after 72 hours of the initial injury. The observational period set on the 3rd day after TBI was based on our previous study in TBI [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAll of the tests were performed with investigators blinded to the study groups, which were revealed only at the end of the analysis. The animals were provided with food and water ad libitum throughout the study. At the end of the experiment, the rats were sacrificed with urethane.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAnimal\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAdult male Sprague-Dawley rats were used in the experiments. The animals were kept under a 12/12-h light/dark cycle and allowed free access to food and water. The Chi Mei Medical Center\u0026rsquo;s Animal Care and Use Committee approved (Protocol Number 113-06) all of the experimental procedures, which conformed to the NIH guidelines, including minimizing discomfort to the animals during surgery and during the recovery period. This study was also conducted and reported in accordance with the ARRIVE (Animal Research: Reporting of In Vivo Experiments) guidelines 2.0 [26].\u003c/p\u003e\u003cp\u003e\u003cb\u003eTraumatic brain injury\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAnimals were anesthetized with the intraperitoneal administration of a mixture of Zoletil 50, 0.2 ml/kg་10% Rompun 0.1 ml/kg, IM. On a stereotaxic frame, a 2mm craniectomy was performed 4mm from the bregma and 3mm from the sagittal sutures in the right parietal cortex. After craniectomy and implantation of the injury cannula, the fluid percussion device (VCU Biomedical Engineering, Richmond, VA, USA) was connected to the animal via Luer-lock fitting and the brain was injured with 1.5 and 2.2 atm at 25 ms percussion. This force produced mild and moderate to high brain trauma, as the definition of moderate injury severity from the fluid percussion traumatic brain injury animal model is the impact force range from 1.6 to 2.5 atm. A transient hypertensive response, apnea, and seizure were observed immediately following fluid percussion injury, and they were used as the criteria for successful TBI insulted rats.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTreatment intervention\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe rats were numbered in random order and indicated to five groups according to the random number table. Each group consists sham operated (n\u0026thinsp;=\u0026thinsp;6); Sham; TBI control (2.2atm) treated with vehicle; TBI (2.2atm) treated with TXA (n\u0026thinsp;=\u0026thinsp;6 in each different dose). The dosage of TXA were given through an intra-peritoneal route for 3 doses (10mg/kg), the first one was given immediately after the injury, followed by a second injection 24 hours later and the last and third injection was 48 hours after the initial injury. All tests were performed with the investigators blinded to the study groups, which were revealed only at the conclusion of analysis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMotor function test\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAn inclined plane is commonly used to measure limb strength [26]. The animals were placed facing right and then left, perpendicular to the slope of a 20 x20-cm buffer ribbed surface of an inclined plane initially positioned at a 30˚ angle. To determine the maximal angle at which an animal could remain on the inclined plane, the angle was increased or decreased in a 1˚ interval. Motor deficit measurements were conducted with left- and right-side maximal angles on the 3rd day after TBI.\u003c/p\u003e\u003cp\u003e\u003cb\u003eD-dimer test\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe concentration of serum D-dimer, draw from tail vein, was determined from day 0 to day 3 after TBI. D-dimer (CA-1500, Sysmex, Kobe, Japan) were performed using standard techniques by Chi-Mei medical center biochemistry laboratory for analysis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHistological examination\u003c/b\u003e\u003c/p\u003e\n\u003ch3\u003e1. Cerebral injury volume assay\u003c/h3\u003e\n\u003cp\u003eThe Triphenyltetrazolium chloride (TTC) staining procedures followed those described elsewhere [28]. All animals were euthanized on the 3rd day after fluid percussion injury. Under deep anesthesia with ketamine, animals were perfused intra-cardiac with saline. The brain tissue was then removed, immersed in cold saline for 5 min, and sliced into 1.0-mm sections. The brain slices were incubated in 2% TTC dissolved in phosphate-buffered saline for 30 min at 37\u003csup\u003eo\u003c/sup\u003eC and then transferred to 5% formaldehyde solution for fixation. The volume of infarction, as revealed by negative TTC stains indicating dehydrogenase-deficient tissue, was measured in each slice and summed using computerized planimetry (PC-based Image Tools software). The volume of infarction was calculated as 1 mm (thickness of the slice) x (sum of the infarction area in all brain slices [mm\u003csup\u003e2\u003c/sup\u003e]). The similar procedure will be performed for cardiomyocytes staining.\u003c/p\u003e\n\u003ch3\u003e2. Neuronal apoptotic assay in neuronal cells in the cortex using immunofluorescence stain\u003c/h3\u003e\n\u003cp\u003eNeuronal apoptotic cells were identified at the 72nd-hour after TBI by staining with terminal deoxynucleotidyltransferase-mediated dUTP-biotin nick end labeling (TUNEL) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The number of TUNEL-positive cells were calculated in 5 coronal sections from each rat in the samples and summed using computerized planimetry (PC-based Image Tools software). The following antibodies were used in this study: monoclonal mouse anti-NeuN antibody (NeuN, Millpore, MAB377) in 1:100 dilution and then detected with Alexa-Fluor \u0026reg;, 568 anti-mouse (IgG) antibody (Invitrogen, A11031) in 1:400 dilution. a monoclonal rabbit anti-caspase-3 antibody (#9664, Cell Signaling Technology, Beverly, MA, USA) at a 1:400 dilution detected with an Alexa Fluor\u0026reg; 488 anti-rabbit (IgG) antibody (ab150073, Abcam in Boston, MA, USA) at a 1:1000 dilution. Table\u0026nbsp;1 showed the detailed information of antibodies used in current study.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTable 1.\u003c/b\u003e The detailed information of antibodies used in current study\u003c/p\u003e\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003ch3\u003e3. Blood–brain barrier permeability examination\u003c/h3\u003e\n\u003cp\u003eBlood\u0026ndash;brain barrier (BBB) permeability was determined by Evans blue (EB) extravasation at 2th days after TBI. Briefly, 2% Evans blue was injected intravenously at a dose of 2 ml/kg. Animals were then re-anesthetized after 1h with urethane (1000 mg/kg) and perfused using saline to remove intravascular EB dye. Animals were then decapitated, the entire brains were removed and homogenized in phosphate buffered saline. Trichloroacetic acid was then added to precipitate protein, and the samples were cooled and centrifuged. The resulting supernatant was measured for absorbance of EB at 610 nm using a spectrophotometer [30].\u003c/p\u003e\n\u003ch3\u003e4. Microglia, astrocyte activation and TNF-α expression assay\u003c/h3\u003e\n\u003cp\u003eThe activated microglia were evaluated on the 3rd day after TBI by detecting OX42 positive cells using an immunofluorescent assay [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The TNF-α expression in activated microglia were evaluated at the 72nd hour after TBI by detecting OX42 with TNF-α positive cells using an immune fluorescent assay. The number of OX42 and TNF-α positive cells in the samples were measured in each slice and summed using computerized planimetry (PC-Q4Q5 based Image Tools software). Monoclonal mouse anti-OX42 antibody (ab78457; Abcam, Boston, MA), anti-GFAP antibody (MA5-15086;Thermo USA), and polyclonal goat anti-TNF-α antibody (sc-1351; Santa Cruz Biotechnology Inc, Santa Cruz, CA) were used in this study and detected with Alexa-Fluor, 568 anti-mouse (IgG) antibody (A11031; Life Technologies Co, Grand Island, NY), and DyLight 488 anti-goat (IgG) antibody (ab96931; Abcam), respectively.\u003c/p\u003e\n\u003ch3\u003e5. HE stain\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e5.1 Paraffin sections\u003c/h2\u003e\u003cp\u003eThe wet tissues were trimmed, and processing with serial alcohol solution, xylene and wax by automated tissue processor (Shandon Excelsior, Thermo Scientific, UK). Next, the tissues were embedded by paraffin wax. The paraffin-embedded tissues were cut at a thickness of 5\u0026micro;m.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e5.2 Pathologic severity grading\u003c/h2\u003e\u003cp\u003eThe histopathological slides prepared from the submitted specimens were examined and recorded under a light microscope at magnifications of 20\u0026times;, 40\u0026times;, 100\u0026times;, 200\u0026times;, and 400\u0026times;. Tissue lesions were evaluated based on severity, distribution, and the percentage of affected tissue. Lesions were graded according to the 5-point scoring system recommended by INHAND (International Harmonization of Nomenclature and Diagnostic Criteria) as follows:\u003c/p\u003e\u003cp\u003eGrade 0: No significant pathological changes, lesions involve less than 1% of the total tissue. Grade 1 (Minimal): Lesions involve 1\u0026ndash;5% of the tissue. Grade 2 (Mild): Lesions involve 6\u0026ndash;25% of the tissue. Grade 3 (Moderate): Lesions involve 26\u0026ndash;50% of the tissue. Grade 4 (Moderately Severe): Lesions involve 51\u0026ndash;75% of the tissue. Grade 5 (Severe/High): Lesions involve more than 76% of the tissue [32].\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003e6. Statistical analysis\u003c/h3\u003e\n\u003cp\u003eThe results are expressed as the means, standard errors of the means for n experiments. A two-way analysis of variance for repeated measurements (in the same animals) was used for factorial experiments, whereas Dunnett test was used for post hoc multiple comparisons among means. A p-value of \u0026lt;\u0026thinsp;0.05 was considered to indicate a significant difference.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eTXA treatment did not significantly reduce body weight loss or improve maximum angle performance at 72 hours after TBI.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAs shown in Table\u0026nbsp;1, there were no significant differences in body weight loss (n\u0026thinsp;=\u0026thinsp;6 per group) or maximum angle performance (n\u0026thinsp;=\u0026thinsp;6 per group) between the TBI\u0026thinsp;+\u0026thinsp;vehicle and TBI\u0026thinsp;+\u0026thinsp;TXA groups in both the 1.5 atm and 2.2 atm conditions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTXA treatment did not significantly reduce Evans blue extravasation or serum D-dimer levels at 72 hours after TBI.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThere were no significant differences in Evans blue extravasation in the peri-lesioned cortex (n\u0026thinsp;=\u0026thinsp;6 per group, Table\u0026nbsp;1 between the TBI\u0026thinsp;+\u0026thinsp;vehicle and TBI\u0026thinsp;+\u0026thinsp;TXA groups under both 1.5 atm and 2.2 atm conditions. Similarly, the serum concentration of D-dimer showed no significant differences between the groups (n\u0026thinsp;=\u0026thinsp;6 per group, Table\u0026nbsp;2).\u003c/p\u003e\u003cp\u003e\u003cb\u003eTable 2\u003c/b\u003e. Transamine effects at 72 Hours Following Traumatic Brain Injury\u003c/p\u003e\u003cp\u003e\u003cimg 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GkEBQQFBAUEBQQFBgT9ZAQFoC7i7H4C2R4NiVC+pW8B7I6QvKCAoICggKCAoICggKPDjCghA++Oa5as7PgBtvkpKSEZQQFBAUEBQQFBAUEBQIA8VEIA2D8XOjVBJKWls9njJS/8Y9DWFvx6eGxrnhzZf+kcTHJVI/XIG+SEdIYc8UkA6v31D4yhppJFHEYUwuaXA3VdhVP9LR3qYWm6FENrNZwpI56/U978KqWOg9eW5y/ks3QKfjgC0Bd5COOcdwI2noRQ3VPsDeiN04WsK3HgWgk9QLH0bFxcE+j9SIC4xlYdvI6hTRv//qNd/ZleP3fKlQ00TRCIBaP9Mh7/slXT+HrvlR62SupQwUv9/6fZv66cAtL9N+pwLLABtzmmZX1sSgDa/OpO7eQlAm7v65mXrAtDmpdr5I5YAtHnrgwC0eat3rkQTgDZXZM1XjQpAm6/syLNkBKDNM6lzPZAAtLkucb4LIABt3loiAG3e6p0r0QSgzRVZ81WjAtDmKzvyLBkBaPNM6lwPJABtrkuc7wIIQJu3lghAm7d650o0AWhzRdZ81agAtPnKjjxLRgDaPJM61wMJQJvrEue7AALQ5q0l3wVaiTiJxLhkUrPmJSuLnJwSSvIyCPXteWvY16IVLKCVIE5NJiUlFUl6Z0TIKyhCWhwRgcEkpImRVVRDR79Q+vgSXhkK/DFAK5GQlpJMStonT5QvbJaRV0ReTkJqQjJpn78rkkFGQRF5GZnM/eJi0pKTSEkTZ14pQ8b9H94vuKOoQAKtWExKchJpkg9+fF1/WSV5SEz5v/H3jwFaqb8pSaSJc85fcXISyX/o/C2wm8JSU0hMSf72w1MkQl5JCT55/ma5RV4BeTl5Pv6BPUkyyYkpfBw5IgXklbK8/4uP6u8CbXKMNwdW7uby+6j0ULKF9FGTRCMWF8a4TCVad2pDuYK+eS85mfiEBJTU1ZGRKXgQVXCANpb3t85x7+kTklBFlTACwsUYlqpNpXIG3N80k+1XXqBRti0jbR2oaiqc2vBhfv8xQJuSwItLe7l0/yWgg4ZWONGRGb3U0NKByHCiUaJEk240qKbJywP7uO4blvHlR0sH6eFV0fFxKOsZom1Qhjp1GqOjEkvI3TN4XL1HQqoYBTVTqrTpToWi2v8+SH/xQfm7bi+QQBvtx+V/DvLcLwQZGR2UVMKJj81QUFtLh6TIcOJRp0rfjqhcPZ19f695kZCSluFv6+5UKFaw/P1jgDb6PZdPH+KFbxAiqb/K4cTHZfirpaVDSmQ4cVJ/+3RA2fMMN3xDkUgncOb8jYmPQ0nXAG2DstSu0whd1XhC7p3hzNV7xKf7W4zK6f7qIPe7Jl4OxS3QK7Q+F9l85CxpYkVUVCEpMZG0NFBQVEIFiElKRE6tBI0H9kT56bmP/iF9X1WdpKhwJJraaOsVpUyF+pQuaogk8Sm3Dh3jSXBU+jPdsFw/GrQuh7ZMzpz88V2gTUsO5KC9NRP+3oU/DZl/fg41I19xbNFqNj6LoHaHcTg5T6aKZg6NgDxvJplnHltZtmw/5Wy2MLG5YZ5n8KsBCwrQRt9dyeLFO0k1bktns/YYEY3XhfX881Q3HWDLBS7DbNoWAWi/MiD+GKBNiuDSxjHselqIXp26ohazF7dVx4nUqcmQcZYYxD3m6Kat6PRwYHivuoTedmHVtNX4UorWsyZRW0uNCB9PTrtv5UWkGjV7LMHKrDaioMtsGjOJq6EJ/FVvJMOmjsBUQ6nAn/hZIIE29C6ui214otqZAc0q4n93HUeO3iS+UDvGTepLopc7Rw7dpd48N+olHWLV9NX4SkrSeuYkammrEZnu7zZeRKpm+DukNqLgy2waO5lrIfGUqDeSobYWFNdULlD+/jFAG3oPVwdbHit3SPc30Gs9R47cIq5QW8Za9yHp/hGOHrpL3TkbqZfszuoZq3knLkmr6dbU1lUn0uc6Hu5beS71t/tiLM3qIhN8GbdxU7gaHEfxulYMsx1Bca2C5e/XPscLNNDed8Rsxg6qd51O4xKBHHF25WlUGmWaW9K5SVEe7FrAlcDqjHJxonSaJ5vHT+FKUCwmNQfQuV8LlOJjeHduMQeuBqNfbQjjp46imGoct3fbs3XzEcLE1Ri6zpkmJQ1QyBme5btACwl4bp6JmflyntOP85KdNJWI8Ts2lzpDFhEuU4i/997CtnkBPScxNZqTK0ZjPmU7zd182Glm+qt8mef3FwygDefyvC6suRxLrYFOWA1unP4tLyr4ILvWPqP54LGUjlxLv4lrBKD944F2Fvc0u2LRpyXJj1YwZ+IqAo07MtNpPuVVkzm/biaP9HszvFcz0kL349jflseS2ljudKapkQ4S8XvOL7Zh22lPFAuPZvo2a4qKnrGn/xDcA+Kp2GY2I6f2RHqEfUF/FVygXYVG7wX0ra6B975ZrF13mKhSY1jhMhH9kNu4Ll6D3qBFtDW6glN/Gx5J/d3hTBNjHZD662DL9n+uoWA8munbpf4+Z8+AIRz2j6NCGzusbHuiW8Dq3f4soF2Feq959Kumyf0Ddqx1PUxkydE4ukzAIPQOrktc0O2/kHbGV3EaYMsjcU1GbF9N08J66f5eWGLLtlNSf0cxbZs1xWResHfgENzfx1Gh9SysbHuhm0Ordr/zGVDQgdZq4RMsnJyprnCT1aMn4BmaSo0BjlgNaoTC3aWMW/oWy9WrqKL3kv2DzXH3jaFcq5lYTe2FnowM0X67WWE+i6fimlhsXkXTImq88ljB2kUbeC9ux7TTjlSSl8uxL6Y/B7RAkMcCavSdR5hInzn77jKuajyvbz/hzMVjPH3mx6PAAKJ167DUaQ5NimkjF+7J2CmLuHL3HbLF6zKme1PCzq5mu1cy1TtZMm1iC5L/6369CNavcmDTgVukKWrReqgNFd/vxuWoN2LVWoxaNIMmio9YNnMRl97HU7pWX2bNHUOFQoqIkJAU8xavcwdZu+E68UpppIrkaNx/Av3b10buzWFmDO2By1WoUaMfNWroULRiF8yGtKKwRjLvHx5l/7YzXHsWSkr8GzQbjma0eReqqD7F+j/7MxI7m/a8vH6c4667eC2rCeGB+KnqMtzBHatSOTvFCgbQvuSAWX/2v42iSPWBDLIeRwVjDWSyfih5Lc0A2pKN6d+zDzGPd3PlUSTapTrQdeggSusrQ1o8kW+f8dz7Bj5PnhIQG0RQrDK1u42gbePapPrsZs3aQ0RGxqNQfxLDyvpx6tghfII1KNtnGt2ry/L07AFOn71MbJoJHSY6UL+CZr7/afqPWaH9bOhHen8KtBV0P61fig38EmhJ9cXDwYYdHjcw6OjCLOvWqAtAm7MPlZxqLS0Wr8+A1jALqMQGHmDFZ0ArSvVL93enx3X0P/orAG1OWZKj7aTF4r3/U6AtJPtv2V5skNTfT4E23d8ltuw87YleB2dmWbdFQ+a5ALQ5akwONxZ5lVWjsgJtE1Q/+cLxjH1fA9o321lqMQdf0x7Y2s+gjJ58fgTaWG6utqGj7XpStZuz/eY+dA6Z09nmCg3nHWJpb0W2zhrL4m2eaNdfzrVLE5Gue4bfdaBcDVviDUrTumUr6ukFsH6lB0XNFmBV8wIjv3G/7sv9NGs8HO8oaDrEmlalNbizZx57r8dRrEobuvSrRTHFt+yx38DN+LJMWbOZOQPqoJgawynnMYyyO0sp+x1s76TPrtndmb4lDavjxxkvOcts++lsuRpJC/NVWLQphLZRRWrXLovM6+30aTuURyVGsGrlVMren0DjQccw7mzLZrcZFHmz4j/6Y8+oGo+wtF2PbH0nTu3sDGdXM272Lhq4vmVh05wdbAUDaON4ud+GJc4niUaVQlVb0rRdF2o2bEph6VKt9JUJtEpaxahZoxOmpbTwPj6fB766NBy5hKE9miITc4PtU815pGfFiNF9UQvcz3K7pQTItmTy+qVU05JwcZs1m7edR732AJrVKk6y332unj1CWGxF6g2pS1E1Jd7fOMqNu29RKT+WmUsnYqKYs57kdGsC0FZk8MoFVFcU8/bVBY4e9UCiVpzu45yobiL9veqpsEKb04MuJ9rLNtBWZLDTAqopifGV+nvMA7FqcbqNdaJGEam/z4QV2pzwI6fbyDbQlmeQ4wKqq4Lvyw/+mtJtrCPVi8gi4pkAtDntTU62l22gjaJUo1EMMG9NWvQbHp1az5nnMjTvNYGOLeqgLJ/Ey/yzQtsEq1U90X9yjxPHj+EtW4bxf7swa1AZkm6c5fg9WZoPbkkxlVRurTWjw+QdSHSGcODBZhpLa2zfuFGz+FDuGDfAyc2N0a21uXvwGknFKlAk9SXnvnV/ogc9a/TlQKQsA5YeZ7NVLZ6vakGFcecwbtCHtW5udCwlwaWzKqOPGtB/sRsuE9sjG3mHKR2a4uLXmuO3NtLeWJ6L62wwt1pDRIdVPNrZg+0jG2O78yX9Pik5iOLYmEZ0WudL50lbcLPvjE78cTqrduS0aRNWuLlhYXqBOl/tjx4PV8/GZvMZZGp0YtXGVfQsq8zru8+hVEMq6OXkSCtAf/o28T13Dtqz+8AJ/MIBNSNK1mhMx4HTqVNS/SPQqpg2ZdhUB+qV0cNrTVMc9r2jfK8lTBjWAxVJKM8vXoOS9ShdQp/UqJfsmN4ajydl6Oeyjc6llPDaOxOXdUeIrjeHzQsHkfLqNGsXTeHOyxga2t1iRDNN3h2xwcHFHbFaG8auc6Gyds56ktOtCUBblGo92lJUEsO9e+68CyxC88H2DO9TNfOkFQFoc3rM5Uh72QbaolTr3paixHDP6zDvAkxoNnghFn2qZforAG2O+JHTjWQbaItQtVsbiopi8fY+zFv/wjQbtBCLvlJ/M76wCCUHOW1ODraXbaANR+ev5tSsbUrYu+Pcvh6CcdXhWI4dTqli0i29ifkJaGvg6D6LYqmppOqWo2HlYuhqqaIg/YVBIkEsESFOes6jU9dwO7wE1z2PUdHtwe47+2kl3Wv1AWhLt8Rt82bM6hX+V/Hv3U8m0EbLY7byNG5mlXnj1pPiQw9QuqUZmze7IW1uc38R5rv+BdoU/630KjGE8yjQsFE9VJVEBL6/zsOHiaTVsOPFOSsOfhVoHzKrZEvmvwrGuIgpFcuXRsRtzv8TRrJBbRa7uTGx/A3qSYH2i/6IeX98HrUH2eMfmYKSqikt+41l/jJLqqgr5+Aoy2iqYKzQZuQqSYsj8v0Zjjiu4IzXW1JFipRpPpERk0Zg/Cyz5CDLKQeP3Tozb+vDj0CrrggSsQREEYQ9fM6rx+7sO7aX937F6O64h16VVP4F2uYO7JrVk4Q351m72IabT8Po4viKvlVFvDtlw8KV+0lTFYA2xwfkDzSY/ZKDmgzb7EgjQy3igu+wyXEO3o+DMR6wkUWDaiESCUD7A7Ln3aXZBtqaDHNzpGEhLeKl/q6Yg/ejYIz7b2DRYKm/QslB3pn2A5GyDbQ1GLpxOY2MtYkPvoub0xy8HgZh3G899kNqIyMSSg5+QPW8vzTbQBtNmRbTGG7dDR1SeXJmFstXeyBXbQj208ZSSEsmPwFt5qawz+UUJxLkdY6ZkwZz2NeUYeZWlIw4iK3zSSTZAdrs3P+TQBt/awHNG8zkScn+XNgzixL6qlmyN6KQZgiOXwPa8PMMqNKLnSESultvZNnIGlnqLFXR0dFBNSRzxflrgA74316F9VJXrp17S0BILKnlLLlzcy3Vc/g0qoICtKmpKcjJyWfq78M/4y3ZfP/lv5vAvrIp7HOgVUl9z80Dy9l36ipFy3SnRutKPHQdzaW3AtDm/VPu1yNmH2j/3RQGwVxdbsPGY5eQNxiG7fbplJATNoX9uhu50EK2gfbfTWEiQrjqaMOmoxeRMxiK7fYZlJATgDYX3Pn1JrMNtP9uCpP6e22FLRuPXkBO3xzbrTMooSBsCvt1M3KxhWwD7aebwmKDj+FsNhHvhCqYbVpDq+Ia+bGG9jPhQu8xxdycFce8GbI/jA091Li+2pzOtjtJ087GCm127v9JoE0LPMigyj04Ltcxqd8vAAAgAElEQVScbRf3MrC8bkbyoaH4aWlhlBiOy8Q2jN3gRVsnb06Oq5zZuZc41GmM7d1YWo9yxm3JIIwVgNRUYiMjQU8Ptf9acU6O5d3jd6Qal6SYdgp39i5k7HQXbr6LYNp5yf9nDW3Sey4fOoxhi1GU/nAgRmbNrG6lTljZOlAxZNUXpxx8DrQpd+YydcZmdDv8zdTRA1FKes522/aceS4AbS4+znKt6Z8D2ghurbXBdf9ZZHR7M8nNnjIqAtDmmkm/0vBPAW0Et11tWbvvDDK6vbDetIiyqgLQ/ooNuXbvTwFtBLfXTcV1nwcinV5Yb7SnrJoAtLnmUU40/JNAGx96DldLS26Fl6av80Y6ldcqAED73hNzMzM2n3lOvaX/sL0hLJ05gY3nnqBmlAVoby5Eu84MIj9f0czO/VF7qNZkBF5xyl+UHBSu3zu9hKFVKeXMkgNF2k5zY6ddP9STfXAc2RmbnT6UaWiGzfShlJZ5w5Ht25AbPIeFTYpyaPEwzO0OIiozjW1u7YjzC6Rq884oHx5OsWE70TauzeDxU+jTzJQ3F7bh4a/CuJkzqfrK8ev9iX7Bmimz2GU4lANzW6P+wgMzM3P2XivBnpBL9P5/rKGNuIzjiPGElbFj/NSu6OPHw61jWXDoJZW62mFl0Qudx98vOUg8P4Fxi4+g3sCcaVZDibnoiOv2g4QnZgJteUWubZmAy86LpH6l5KDxrFuMbK77seQgWbkcFiuOU69ITsz63Gvjj6+hVWzEuM0rqGeo9YmIn5xysGYeVQzUCHt7hkPOTni/DqNM351MGlEXFaHkIPcG36+0nBVoVfsw9/BCSv3XKQfO86himOGvu/NKvF6HUqbPDqwt66EqPcVCOLbrV5zInXuzAq1KL+YcXkjp/zrlYPVcqhbSIOzdWdydnfB6FUrpPtuZNKIeqsIpB7njT061+gFog5Ko1HEuVuO7fPbHELKcctBkCoNHt0FdJpwrO6Zz/PB9RBWGMOXvyZTQ+c0lBzFBOxnfcihbHiYhRoHi/WZw1MmOClmPnRWncmvjPDpYLyYsRZkqdUZi2yEB60UuBESp0KH/alznVGFDu3bMfu4LMnJUHLKEM05jMFSXg+/d32kGTcXnmHtMukMeyrfrh9vEPqwcbsGOt8GIZI0ZMsWNyS2uU7vDbOKTQU6xNZvP7GJAA23CfO4yb4Ela3d4gYwSsvrF6TzNkRWDm2KoIkvE/cOYDbXgyJ1otAyNsbQ/wNQh1dESJ+KxZTZWC5fwzk8RRXlZNFqOwsVxNh1UfFjYuP3X+xP9GLd55oxb+xBlOQVM0lJ4WKg6E513sqCVSY7/9ZMCUXIQcZldI8ZzNCwBJRXpcWpppCbFU77bBoYOb4Se/y1cpk/gckAIIlk5KveZRr9qkbjNWMOz5DRk5UvT02Y77aonsPPvgZx+HIiSYhVaD56IwpOp7L/4Hnnlnoy3rstphyncT0kDOWV62btT8t461u45SESaBA3DLoyYbIbnfhuu3Xwh3ZlGlebzGTGpM9o5X96cU4+TP+dP32ZVJPgwc82n8Sw+ETGyKFTuzrTpiyhr+OGU7Vu4TzBjv3cCadL3lZWQFYkQpyWjrVuZ+v2t6dy6NoryITzaOwvnTWeJSAJZvRp0sLGnR62/kP6oUpBfBfIc2iyCRz1wYaGNE76JyUiQx6D5aCaPHUsRLanHtzk8wYx93vFf9bdepr9K8qE83juT1W7niEiUIKub4W/32n+Rzw8n+WTo/THn0Gb19+FaFk1ZwdtMf/WbjUr3t6i2dGPNbQ5PNGe/dxypkk/nr5ZuJer3y5i/SgphPN6XMX/D0/2tnulvyQLl79eeMwX6HNoPHUrw4eTKWew7fZ0EsdSf0rQfsYAezaujmP6n3IJ5vH82azZ6ECb1T04ReQXp2bJiJGlQuekoOg7oQ0kTXZIij7J1ylQuvZI+0+XRb7mQSdO6USyH/kJrNs6h/bGPg4AAMDL6sXuyXv2r9387cgAZ7X89wYCAgP94L47w8HA0NIyQk/uxP8aX6utLtGpGzW1uvQoE0H7sfBpJicHERmuhrauMzMc/8vxj6sRGk/7n+H72/h+L9vuv/lNXaH+/svk7g4IOtPlb3bzN7k8E2rxVsOBF+yOAtgDJnuNAW4D6/sekWrCA9o+RPU87IgBtnsqdb4IJQJtvrPjlRASg/WUJC1wDAtDmrWUC0Oat3rkSTQDaXJE1XzUqAG2+siPPkhGANs+kzvVAAtDmusT5LoAAtHlriQC0eat3rkQTgDZXZM1XjQpAm6/syLNkBKDNM6lzPZAAtLkucb4LIABt3loiAG3e6p0r0QSgzRVZ81WjAtDmKzvyLBkBaPNM6lwPJABtrkuc7wIIQJu3lghAm7d650o0AWhzRdZ81agAtPnKjjxLRgDaPJM61wMJQJvrEue7AALQ5q0lAtDmrd65Ek0A2lyRNV81KgBtvrIjz5IRgDbPpM71QALQ5rrE+S6AALR5a4kAtHmrd65EE4A2V2TNV40KQJuv7MizZASgzTOpcz2QALS5LnG+CyAAbd5aIgBt3uqdK9EEoM0VWfNVowLQ5is78iwZAWjzTOpcDyQAba5LnO8CCECbt5YIQJu3eudKNAFoc0XWfNWoALT5yo48S0YA2jyTOtcDCUCb6xLnuwAC0OatJQLQ5q3euRJNANpckTVfNSoAbb6yI8+SEYA2z6TO9UAC0Oa6xPkugAC0eWuJALR5q3euRBOANldkzVeNCkCbr+zIs2QEoM0zqXM9kAC0uS5xvgsgAG3eWiIAbd7qnSvRBKDNFVnzVaM/A7Sp8bGkoICyisJ/9kUiEZMcH0da1ivSkomKSEDNuBDq8nL5SoecTCY1PpBA32CSJCCvYYRxIT3kZERfhhCnkBAVQVxSMooaBqh/Q0/pzeLUeCIDfImMSwJZebSNS6Gt+nM65gTQilNTSE5KRVFZCdHX+pelx8lxMaRmVUAiJiE6FlS10dFU4Svq5KQlP9eWWExyUgKpYvE375eTh9SUrJcooKKqQGpqYro+0pdIpPjlfBFL9UskVQwKCupI2/mZV7aAViIhNSmR5LRv5PO14KmpJCQlIkECyKCgqIScnOzPpFmg7kmK8iU4MIJkCSjqlqCwvtqXY/Tj/E1BUUM/2/M3Kj4JiYx0/pZEW/XnTM8RoE0f39LxJ31Ki5CTU0JB8TvPk7TM8SDJHA8KSsjJ5/PxkJJCfHLiN8efSCRCQUmRtMz5mHGxDArp/RMjAG2Bmr5fT1YA2j/AxO904YeANiUO38cXuHHBkySjzvTsXRvF/2g/OfYdl7Y58yomK9VE89RHnX72M6htoJl9ceNiiAdUVNWzf89vvDLO/xLu9lM49jCEQs1tsZs4DG21r3xQxL/j8rbVnPN+Sdn+K+nd0OSbYJcS9567uxewfp8HyQr6dJt5hG619X6qp78KtMlhz7l+9igvw4zoMLA7hupK38gjhlsbF3A3TPohmPkSpxL4Po5y3cfQrVlFsvWxnpJCUlICCipqiGRkfqrfP3RTlC8XT+7j6bsgZGT1UFYJJS5zPOto65EUGUqcRINqLcvgc/Y2kekf8lC4wkA6tC9HiO85Lpw4R0S0BJP6Y2nfwARRFnJPDLiT3v6bUAll2sygSRWNnwL77wFtmM8tHl+/Q1hyMrJqsgS/80ci0aFMraZUrVsddfkvv06kpSTic/sMr5++JFpVHSVJBO/fRaOl8xdVOvakrKFq9qWMjyVeIikw81fasZBHe9m5bBE3fCIpNnA7883rIfv5l7Z4X65sd+ac13NK91tB74ZFkMlq8GcKpcT5c2/PAjbs8yBRXpeuM9zpVtvwkzGRXVF/FWj9H57nmdcjImRkUVJMxu91EMoqRSjfrB2Vy5oi/9n0SktJ4s2dM7x6+iJjPIgj8H8Xjaa2dDz0oEyhrwD/NzojiY0mWU4eRSXl7Hb55697fY4NBz1IEyugqiYiMSGBtDRQVFJC+lU6OjEBOfWSNOvVmpBLB/F6FUiaBFR1ytCkbS+KmMQIQPvz6uefOwWgzT9e5FYm2QXa1PjXXNqymn+uXMQvMAKtBotYMKc3Wv+xtJYQfoON4/pz9X0WiEn/tO/ETKcFVNBVy2aX/Lg0bwGeyfK0H7WSSkbZvO03X/b+sCVTnDwwbPYtoH3J2Q1L8bj7mnK9NzG43afA87UupD7bifW0hUSmavwmoI3m3T9b2H7sJD4vnxKrK/VzPhV0v/Vl4z37LZtw8Lk4fZ3v40urMv1sl9Chbim+v8aTjP+t/RzZeQzj/ivoVNPgp0Dgh4ZF6D1cHWx4qt6DIS0r8v6WC4fcrxNn1BFr2/4keh3Cfd8N6sxwxPTuElbs90QiMaDD37sY0MSUmNcnWLt4Jv4mIxhnaUYJgywf3uIEnp1cylrnzQQmSDDpuJbZ1q1R+4ml6m8DbTSeK4ay2cOHGkPsaVXTCL/TC3HZewtlkyYMsplD44omfP71IDHyETunDcFLsTmDhw1EVyYUj40zueAVhUHzWcye3gft76zKZ2jtx+UF9ngmytJu5AoqGsv8FLT/kG85cLEkMZwL6y1Zf+guxQZs+w+gfcm5TcvwuP2KMr02MKR9EaQrfd96pT7bzeQZCwlPVv2NQBvG8eldOOFXiLZmE6lcXJX7u6aw+4wvmlUGMcluAiW0VT/xKX08TDfDW6EpA4cNSh8PZzbN4sK9SAyaz8RuWh90ZLP7JfMZxybPw7dEfTr2s6KIdnbv+0lj7ztiPnMnNXvMpulfARxycuZxZBplW42iW3NT7m//m4vvqzJq9VKMXmxl/lIXQqOSKVZ7CJY2UyiuK6zQ/qTy+es2AWjzlx+5kU22gPb+QRbMXIBW+br4+93g9ftwdBplA2jtFqLW2pomFY2Q/fCcF+ljZKJNtisOIq/iZDkOrxRVzJZcpMlfP/GJ/1XhUokIfY6vD+hVLo3x935q+0HxQ05NZLzDEQyb2fz3Ci0SpD/bp4klyMgqIPtRpG8Ee32A8VPmEJGilvdAG/qKo8tn4BVhSMlCrzh68TES42wC7djOPC1nR6+2ZVH++KGvjo5+IdSyQ3FpsXjtt2OtqzsVplxgTNuiOQi0/jy4/QYl3TKYFNflI3amA+0qtPosoHdVdbz3zWLtuiNElRzNirUTMQi9i6uDM7oD7OlcPIE9f7fklLcEmVYObJ3agddnV7D2RBITZ06msO6nK5pp8SGcdBrN2Yc+hIWGoaI7imnbJ1EsW5D46fj4NtCGcXHDNDxfF6ePtS3F9WSQ+O9l5uDp+IhNaTdlMb3b1fjil5aEaC/2OTqhXnMk7dtIf4mJ5d6+mbiuP0oUHZnp4Uh52WzAaeRVVlqNxytZmcGLL9CklGwOAW0qEWEv8PWRoFepFMaK2Vrjz/4sTorkstsYXPZ6/jfQ/tT8PcRE278JS1L5jUDrzxGHyQSpd6brwN7oq8sQ4bWCeZNWEyCpxYitq2hqoveJTwnR3ux3dEKthiXt2tRGSRSH1/5ZuK47QiQdmXF6ORXksult8CFmD7AhplJnRtguoaxhTgDtv+NBt2IpjJXk/83/viNWC58xYuVqqsnfYPXoCXiGplJjgCNWgxqj5L2cMYtfY7l6FVV04NGm1iza5YO4cANGTFlMk0r+wgpt9mdO/r1SANr8601OZZYtoCUEn+dQ3CQK98VTOHjJG/XsAO3sRRQd4PAfK3ASUhNCCH72hEcPrhP8LoD3ke8JExvRxmwCjSqVQDYplBfHbFi+8QIJqapUrN4ZHX0DKtU35cbxPbwPiEC+XDcG1NflzpmdPHgrQ+EGQ+jZvixxTy7ivvcAock61OlvR6cWpT/9WVsKSFJAcQ2k705nmhrpAAkEPjnBmYPnCU5MQ1G9BA279aWSThSX9u7gblASuuW60LNzQ5TlY/HzPsblM15EpKSSGuuLXu1hNGveGGMtVUI/AG29YYxoXpq7V3dxPzO/vv3bYiCfwtNrG9m37yyxcYlo17XDdng9RKJUov2e43VhH/fuByGSiyMwRIHirQZi3qsJcj5fA9pkQp+fwvPsDd4ExiFO8EGuTB9atmvDX8a6fK0q7udKDhIIfB+Frr4+cU9WMWfiKgKNO2ZvhXZsZ3xrZ3yAfPkjYzIxvg95cf8xPi8eERLlj8/7aIo27EeP7p0xVFMi7u0J9iwdy5mHEoqX7kSJ0lroFipLWtIT7t24S5qcOpXaDsck7CRnPZ8gVqpIi2EjKa/wkpNb1vEkOAHDMh3pPnQIxfSUPoWqwP3MHDAX5VazsLLtie7XVtk+jJcsQGv4CXwm8/aSK2sXr+ZNfAr1hs9B8c5+DLouokPjcnxebR4feJ69G45hUlyBQ7v3EytrSL/5p2lbUeWHp/b3Sg4+bzDltRvTLRYQrF+TATYOtKhe9Lsr5JKUaG7ttGHDFg+oNRN7+yFoJoUS/Owpjx9cJ8jXH/8If0LFhWgzZByNKpVENjmMl8dtWb7xHPEpqlSo1gldA0Mq1TPl5qm9+L2Xzt8u9K+vz72zO7n/RkTh+oPp0b4c8c8ucXjvfkKSdKjdbyadWpRFIet32bRYvNO/4ATQe9sqmhb+AGBRvLm+E48T3sRI5FDTr0xbswEYRN7D4+BhXsTIYlzDnF6tCvH+/nEun7lHZHIqKXG+6NaSzt9GGGurIZMVaLssZmi5GM5dOMLrIFVKd5tC37al8Lvulj5/Y2IT0K4zC5vh9ZBJHxPS+XiX6x6H8QmIRZwcQlCsEQ36mNPW5CWTp875DGiTCX3xD9fP3si4Xjp/S/eiRbt2/FVY96vlOL9acvD5mAjxXMC8mW7EluyD7cJplNb9dgmBdDzc3mXL+s2nkdSagf1CM/RkITnqHf5PXvLo0TVCA4J4F+xPrGp5eo+cQJUi+oji3+C1eQDLDwagpmFKuSp1UVM3pWIdTS4fPUhoaDSKdcczqHQA504fxSdQhZJdp9CtlhwvLh7hzPnLxKQY0Xq0PU2qGSD3YUxIx8OB2ax19afX5pU0k8b62kyKvMqqUVmBtgmqX3yJfMT2/gM4GRBN0WYDqCPjIQDtDz+V8uENAtDmQ1NyOKXsAW1m0PiXPwi0c9FqMZxKJrqIJDIoaxpTpHgRlOSlqympBN/bxNrFLqQ1WYRV38r4nl/B5vX7iFAbjP3e2RSODODpifms2uFBkowWrQbMp3RhNYzK10TydCHz7LYhKtWcZi0aopkWyzX35bwKLkLFbk2pWNSUeB8PLp++ToRaZ2a5OVI+60rgV4FW2s8Qzk3rwvrrIRSta47V1OkU1wTpiuv0vVEMsXGgflk9gm+swMl+KzLNJjO6fxuizo5k+brXlBk0h5ED2xF/dlL6Cq2acU2a1W2Dpm481w478irIhB4r9tKziiEpkY/Y5mCTDmC6/XbgZFGP5KArbJ4zjmt+RnSevJzGqrdYsWAxkZVmsWBOL7R8Dn6xQhv/ej8rps4ksHB/zMaNwNhnEXPmn0KjjgVWtmMprvXl5r2fA9p/B1+k94ofBNqOPC8zgQ4NiyNKARl5fYqWNUUjvYbuPSdtm3M0oh19xk2kqtZ9HCdM4Fl8GbrbONC1aUWib+7lwI5FnL8fSaUO82hZ2wBVnZIYqT3DccpUfGIllG9jQVVTLd6cW8HlB7HolmhE7dY1KKQUyLWt23iWYEr7cQ70aV0DhayLQjkCtJAS8ZRja2xxP/+AZJEy5TvbYmU+CP2vrEC/cB/JyTdN6d+nEJsmWHMvQkLtASuwGtwoywp29ib7jwFtOHeWjcDxnydU72TDIPPBX83v88hJkXfZYWOJZ5QxfadvoHkVbUK83HBdvIbURvZY9auC34WVbF6/l3DVgSzcPRuTmECenlyA8w4PEtCgZf95lDHRoFC5mvB8EfPttsJfTWnashFaabF4HnbkZZAJFbo2pWIxUxJ8znDZ4zoRqp2YuXE5FTSymPafQCvN/B17h7XA3UeRagMWYTWoA+qSqPQV130+VZg0fSyKz9ax0n4LoibWjOrfhpjzY1i+7iWlBszGamB71CUxH1dotUq2pXXtuqQkeXPF4xDBUWWx2HGEhipP2bnEljPXHqPddysrLBqk19km+BxkxdRp+Gq2ZfCYiZiG7mbekn381W85lg3CmPkZ0Ca+OciKaTMJMOrN4LGWmLxdwrwFJ1GrORRL23GU0P5yp0LOAm0A/9j0ZvczaDl0ET3a10fpK3XVWcdEUuQ9dk615FqEEX2mradFFWkJUBwvD09lmetNSpuvoX9TZTy3zsX95E2Uy9pi52SBduAT7rlPxfngI7SK1KFV18EY6ehQpEJZnh+1ZfM2D5Sr96V1g7KkvL/PFY+DBEeVodagxpTSVSPg+mGu3XqFUmkrpi6ZTDHVzF8JchRowf+qA05L1uEbJUZStLEAtNl7FOXvqwSgzd/+5ER2uQW0STFvcV8znqC04qgqqRBw4xLhylqUqNMHs8G9UVOVJzHoJU/v+2NQqx7GWvKE3N/D2kXTeRxQizEHdtNAR0TULWdmzF9FnKzBJyUHH4Gq3ACWLJhKIbkYjizpyr5LQZS3PIxN34pE39+D66LpPAqoyIidh2lmlITPnaPcvP2clNREAl+dwfteEkbt21NZVRmUi1CveScMozdhN34N4SWaYWXrQN1SOtxxaclpiRWWw3uioxDGqanN2fqoKD1sHOjSqBwJ77azxGw270r1Zdai6WjcmJkOtFq1R2E3fQx6spEcccjIr4HNBUa3K4oo/QuCDQcveaGVDrTVeHXYjiWuB0FzEDbb7PiLSN48ekyc6l+UKVUIuS9KDhS449ibZScCqd57KVYWLVFLusiydkPxNqjJQNsltKxW9IsaybwF2kTOO/fgekBRCunpEHL3Bn6pcphUakSPfiP5y1QF/4unCNaoRtnKxVCSTcRjZkXcrurTeNRihnRvjEJSCCcc+7LzjA/1bbKUHERcYYXVeG5Ei2hgtZGRXaoQ6D6EKSuvoF2hA8NsHahmAmdnVmTTVS3qWTgwrHdz5JJfceXQHvyjJJB0g/NHnyBbtBqVa1dBC1At0Z2ubcv9u8rz3RVa6WxMI+buJqbPXUForIgK7adjOaof+kqfrxU9Y4e5GaLBO+nTTImzNj3ZfDuYInWGYGU7g+L/VZj+HxP+R4A25O4qnOauIazGJOws+2BkkL2Nll5bO7LmGLQwt6N7yxrIy8t8nL/6NetSWFuB0Pt7cV08nYf+NRi9bzcN9GSIvrOGmfNWESujx5AsJQeR952YO3ElAWX64zB/KkaKsRxd0p19lwIoa3EIm76ViX3wob3yWOxwp5lRCm/vHePm7Wckp2TM3/teSRRq25ZKaqqIlE2o26wTJU118D0zicX27iTVGc2CqaPRkYng8OpxJFSzoVfL4lyY2YotD43pPmUxXRpXIPHdTpaZ2/Hmr97MsJ9OSbVUrmSWHBh0WIn9xPaI35zF1WEKt55F0Wnpc/qVe8ORJbYcvHAPjY9AG8tdp74sO/yWMs2nYmU7AANxEC8evEbeqCxFki4y+ZOSA2XurezPsuN+VO3pgNXwVqinXsaxwzDu6VRngM1iWtYw/WIFPSeB1vf0SBavuE6R7nOw7N0aLY1vbfDMGIReWzvjclxMsyGz6N6qJgrpJx2kEfPiNg9eiSjdpBZ6ymJeH5vGUpcDpKh2Zvz6pVTQlCXs1DgmLD2OfuWuWH4oOfgIpO5E1pnFxnmDkbw9xzoHG24+i6ThrOtYNNPB7/j09PaSVVoxxmUZWu9OcfP208zxcJb7XokUatOGSupqGeOhaUdKFtfN8k08Oyu0kBb/nn9WWrHj9GPE2i0EoM0J2PjdbQhA+7sdyP34uQW0SOvL0lLJ2PgtIiZgPyuHzOAppvRw3EWPKgYZnZO+L/LH3/Mhd+9t5diZa0RFfADQbABtZXOc5kxGVy6GE4592Hn2DQ1sLjK6XREiHh1g7eIpPPD90F4c93fY4rztH2Kk5/FIDyNKjy9C+h8m9bG0caBJhRT2WjbF/WVx2ts60LtNKpu7TUBv6mG61ZH+lHUD5xb9uSIB4yJ/oaWjS0ryHV4+TkWSvultPga37D6podWQicjI74w0v/8C2uJcWWKD28krKDe0Z8Fc6aa7z2DoC6ANY++Awbj7h6Cha0jhIqbAQ556xSH+xqarvAVaEKelIJZIR4IIifg6Lu3M8JTo0GCEA+Y9m6IiKzUinqg3z/B9cJo9J9bz8pk29TMBVDH5O0AbI0PjsVuwalee0JOjmbDkFIbVu2Fps4QyBiIuzS/J2nNa1BueAbSi6JtsmjiAa37SMSD+OE4/bOrRTwcUaQlIpv7ZAto4Hu6axsotx4lJkiAq0hBLm8XpNeSfvKQ1fXMeYzZ7BqZ6IiS3FzDZ6SxqpVun51u9eHY3TGa0ml2gTXh3mfVLbAjQG8uc6X0yIeT7z5jQ0xOxWX2VdiM20L19pU93+6fPnwD8r0vn7zaOn7lKZHgmgBrLfh9oK5nh+Pdk9BViObGiL7vO+FBv0nlGty9G5JODuC6ewv13H4A2kYe7puK87STR0jPxvpi/9dJrHptWMiYh7AYbJwzgmn9tLLeuorrcJTbPO01960XUKPGMNa0HcCVVTKEiJdDW1iMl5S6vnqQgNurI9BXzqagh/gi0HzaFJfteSges649DvgG0z9k32Bz3wASqS2s0BzdBNescfv15DW0k+4eY4+4biLqOIcZFTBGJHvHMO5Y0zcr0mbKYjvXK/PvTeqZdOQW00XfX8/fCFRi3cGa8RSPks3EkW+hpa6Y6X6HN8PV0a18JuaybwSTSA95EiFN88Lt+iwtXN3Hu4nPk1VszxsWZKnrZANomC9g2ozcpfpdZt8SG649C6LTkKX1rKPDeYzqLVu0hSUkKtA7Inp7Fmm3HifrqeKiLxWTpeCj8b719tkoOICH8NlsmDeDSm5T0/gjHdn3/OQgojh8AACAASURBVJHvrxCANt9b9MsJ5h7QfppaWpwUSDKAs/ignSwwr0W8vzf/bJ3HPw/iqNegH38VjsBj+2pehOUW0IogJorIxATSUhN4cnQl23cF0nf131SSHiOmpIyaumb6BpmXewcxb+1VCneYRT/982y63QxbJ3MKSfkm/Ahzek7kqWYl+o2aSf2qWY/b0kRbR5kwj083hWULaAcV4rjDFPZduItqrTnMWzzwy3rOz4G27CvWWIzmckQatXotYlDXyvy7VSezP19ZcMlroP18oD7e3IX5Wx9kbJob041gz53s2LMNJeN2NOjegYhtg9n74N8V1ZwGWhVRGknhIcRKEwu8yPIJC1BpNIVBo1qmA4isfqH0ldqPr+8BrSSNiEdH2LjhOJV6DiZo1WhOBcdRrJkt46yHYfTh2LbUGK6v7MBWb12qViqb8UWK+9w+8Zho1bJ0n+RA1yYV+c4vvp/ImR2gTYt8wbH1czif0gi7sWboqCuQmhBHcqocSmpKfHUvmjiRiNtbsVvtjmn3RVh3qZxe450QHAVaWohD7nM6ff7GUrd+H/4yieLsDmeeheYW0Moiis2cv2kJPD22iu07A+jtNJvKhbQ+mb/ihDDOuJiz7dgjylnto3WoPVdEwzG3ao1mxDHm9rbmqXoFelvNoGH1IlnqLTXQ0lFBNvXLTWHZAtq4m7hYjuVySDLV+yzFclgL1L8FtOXfsFZ6fWgKNXraM6hrFWQ/Xq+MqromSv8xf4/d8qNWSV1KGGVvlf2TQSNJI/71OVxdXQkuOYL5w1shKyMhOSqGVAU1VJS/cu5I+njYxmznQxTtao+19FkjSiMhJAo0dVCWSyLi+RX2uU7FK9yUpm36YBBzmt3u50hVkwJoTgOtM1UUY4mSPs/Tx8Nqtu/yp9dyOyobayNSytQva8ezA7Qp4Vx1Hs6VhGZUEj3F/ew/AtD+MmnkgwYEoM0HJuRyCjkFtMlxT7l1+DyhBpVp1agO8c/cuR2gTrW6zTDUVCAr0FYaeZTp3YpwY8dk1m45Qynpv3uXI/jeTtYutuNJ0L9Am/hwC1NmORAj0U7fNNMmc9PMx5KDH1qhzbLa+Z81tBmCx7zeh+OEqTxRK0sF5Kg4eytdy3w4O/cxbv9j76wDolreP/xQIiUhIAqo2N3d6LVbsbDAREExEOxWBAxU7ABb77X1mtfu7m4RAelu9vfbBRUpUdll9XvOX9fLnHlnPp+Z3WfnvGfGoiMnosU5mW70alUjJSczOopw8eNqdQ2C0+1ykCOgHVqWG6scWbv3NAq6fzFq7Rqq6IrbHEFglBb64hflM6zQRvOvXS+2PY2kUqeZ2Izojp44RVm8AXqEGDzSvLWfZixJD2iDeHLwMM9jRZjW6kiNEgWJfn2C07f9KNPQgjKFU156+gy0xdrNYGLreKbYL4BK7bFxcqOScTxHnaqz5fpXoM2fEMR/K63xOvyQyiMPM9GiQsqqy+eUgx9coVVP+6ZcLuTQJka/5djKOXgbWTCgZ2vCbrjh7roW73ATWs5Zj3Wj0hJoinuzF+cJKygzaTd9auqmgpQ3fw82Z//r/JS3mIn9kG4UUM35m9/fB9oI7nqNZsc1dToMHUEZowKIkmJ5eeEYIToNadmqJopxz7h58AwBBpX5q1FdNPIrEvHuLNtdF+FfbRDD2tWSrFbHhTzh7OarlB9pT/IZJ9Zs/o+Sw/czqWdFAu/tYI3LdB77fQXauEebcZrmSliyNr3nHKd1JU2Jb19SDn5ohVbp60pbtjm04lNIYnl+cjFrlm7gY+G61FJWpf6UZdQvqoUCT9jUsxPHI4vSZpQLPVvXIn+6+auUyS4HOQJaRW/+Hd2H7Q+CMGs8QpIDa6qhQFJyJFHxmhT4mH6FNo4j9pZsfxxGhQ7TsRlhQUFVBcn8jY0IQ5TN/P0VoE2MfsfxpY5cja/NgH5dKKCWD/GBMLcPn0WjxSDMK+kQ+vYmd6/eI6JoEzo0KEO09zm2uy7Gr4oVQ9vXluy5Kx4P57ZcpeyoqdTWfM7OhY4cufSIRtNuMLSZFq8PTmLRmv0kaHwF2uiL07CZuQPtCu0kT8Qqm+SHtCkHOV6hTQFkyad6ruXQxuB9fA4r9kZhMXkuFZVv4TnXQQBaKXOITKoXgFYmMudpkB8B2riP9/F0ceT8/edoFh/HhGV2lE5dHIjw2427pROPUwEzcG8vFuwR0dXWlY6tyhH/ehdrJ83mmkJVRrqsoLExnN9gy6p/rqLTdS5zutfh+tbp7Dl1leiEr0DLp9M4247nQShUaz0V8+qRhBh2pkagKw5zdhJXZVCGlINyQ/YyvW+1NCkHmvRccY+uFXIOtAkR79jn3Jt9V/yh2iTWLh6K1pfbY3m+eTAzPW+hbdKIVn0HU8lYgSdndxJYpCm9OnUi+pTD91MOgu/j6erIyWvP0Zfk0NYh6s5GJs5yJyRGicotxtG6dUmCbm/iVvIA7IY0QSMD0GoTcmIKtgv2oqZTkQZdh9KwZlECbu/mfpA67azsMdPOuK/ArwLtqz2TmbNiF3H5GtF/yVLaltdJhbNn7Oo7gAMhIhpLUgDKp6QALLlMnY4LGTS0BVoxF9gx2o5DoQa0H+VKD/3TWDusQsWsLv1tp1HC9yDLVq/FL/JryoE6EdzcMZHVnkdJLjwMG6emxAcEUNxQgRWzpvI2Ol+GlAPtCm0lgFzFVC015UCJyr1dsRvYGa2079n8KNCqWTDrkDNl0hzucG9zN7Ze1aGrvSv1y+qTGPGe/ZLx40f+Ih2xX+ZO1YKh3Nkwg5U732G5eR/NCn9dS7+3+i9c/n6NSqneTF0whdJ6OT+44HtAG3ZzMTNnrSJc0RB9o4KSfExRciJh/hGU7z2TwT1bkBy4B/e+TjyqPFCSAmCYP44LXnZs2XsHDZNiaKTus5cYFYSvnz7W6zaifMye1f9cQbvzbGZ1q8PNHbPY+98VohK+Aq1CwGkW2DnwIDiZqq2m0KxGNGEGnagetJAJc3cSmwnQlhn0D9MtaxD6dF9qyoEGPZbfoWvFHwBaRIS/OMYalyncfhVKwVbLcXFql/pGexzPtwxhltcNChRpSEvLwVQ2VuTp+V0EFG5Mz46d0BRFZti2KwPQmj1hs5sTJ64+Re9LDm0iISenMWrBPyhrlqRBFzua1NHg2dmdRJUcRbfSL5n0zUthuoT+N51RC/agql2eBl2G0LBmMQLv7uVeYH7aDrSnhE7GnS9+NeXg7ZHxLFzxL0laRdDRTtnRIDk+igA/JVrN9aJHDT1en1zCapf1+DSdzyaHllzdYs+WvbdRL1IUjXwp26QlRgfj61sQK689NFd9yPqFjpy5/hKzIWuxrarMUc/5nL37ElW9rykHCt7bmDBoJn6q5WjZz47yGo+JLjkQlSsTWLP9LPGZAG2jSZcY0bLwl5SDGJUyDFp0iIbFlVN+5Pwo0PrFUbnDbIaP6YxemscTAbfXsmbxUhTabsOhT1VUFRN5+/cwAWjzlFJyKbgAtLkkpBxXkzOg/cheuxbse5ZMkiQvVpwMqYSSshKFzR2YbG+Fcvj+b4BWzXs9Sxbs4Znfx5StbERKaBh1pofDSJpWMZHkhAU9PMVql4k8/BiKpnYLuvc25/GZhdx4GoyukR0TV46hqK4I/8O2jF18HFCicLWBDB3emNN2Q7iQmCRpR2OnbVgqXGWOy1I+JotQUKrKkPkbib49mh1/X5LkbqbUN5aikhXPlEv8pZ6UJEJRWSXjI9fElH03V6+9h/miHfSuYfSNi0kxoZzbM4Ndew4TGaGEQj4NzDpNZGhfC4q+PsB0BydeJCahoKhEI8dttFT4m9Uu+yTtU1SqxjCXbRR55c6aNevxSRahom1C96n76FxTF79bC1nmuIa3KKCoqEixJrOxm9yTwqFvJC+h7L5xmwSRAkVqt8PG0ZnSBdV4ctKdtZtX4u+rKNFbo85gbMaMo5q+Sqb7tf4c0IpzRCezcttxwmPF2omPhFVEUVkZ1QKF6DxpD51rBWUAWnz/xmPGVq6+eoqiZO/SZBSUG9By5Hi6tquEhkIyp+d2Zf2ZRygolaBBH2caJ89mwfZHKCjWZ/jC5TSppkv0m9Osdp0oGR+qWga0GjgP/Ydb2HXuPNHifOZabbHp0YmjCydzJSAYFPRp1MOFjjXvMnWKBwmJIkl9Nos8aFzt8+qoZCCQmJiIgqJyavsyTtiw+8uZO34ZH8RjDkX0Go/EccxYiukF89TTgvnb3pGQrE+jYS5YW5gT/3g5c8ctxUeikQK6RoPpb6XIsXXreR4kQreRLU5jxfcrEHh/KePGLydBfAaugiJKLRaweFJ3DHO4J232QPuc3QOs2Ovt9+2hFpIumkn2oe3VrhYJft8CrWbcMZb1c+SBpL/pr/ZM+W8phZ+cZY3rRB74hKCp3ZxuvZrz9Owirj8NQtdoJE4rxlFMT4T/kVGMX3SMZJEiRlUHMHRYE86OGcaF+ARECko0mrAZS6WbzHNbik9iMgpKVRg8dyOx98awXTx/k0XoFLJl4oqxFCv4deX66/xVzvyELvFLl65O7DsXR/8t+2hh/HUuJMWEcX5vyvyNCFeUzN/iHZ0Y0teCYgWUCT/pwVzXpRK/FZSU6Th3N8b3FrLz70uEJIvQ0m1Bm1oluHJqAx+Sk1HRNqbbFPH4N0SBJJ4ddWDNokP4SeawAlW7r2VQF2MuL53C7mu3JEfqFqnVhuETnCljoMGz/9dzzeaV+H1MKa9ee1DK/DXIl2k6yK8B7Q1Wt+nH+Thxfmj6qw5DNy/H3FSLVye+Au3qISqstHLiQUJSJve0Z/KJJVRSVuL98ZW4eKwgJEYR43L9sGgC23duIiBMhSpNpjPMoTsFNUQ88uzO/G33JZ/pxZvOxKqDGrsnTuRBQgIiRWW6zN1H2QderP17HyFJyWgVbMtgh8Fc3z+ZK9efIxJpULnJDIZN6I5+6i4i3x0PMa85vHgye07dIFYkQkG3JG2HOtPzr1qoqiQS8nQL690WcOdNApoGbbBdsZwqytdZOWqMALRyzDA5bpoAtDmW6rctmDOg/ZXuhREaHAN66XIS01QZGgw64m1gs7mSk5KIjo6U5LjK15XSPx29b4H319uYRFysOMNTG9Xvv3ScGi6GyIgw1NUNUFTK/uytnwPaX+1VSvvi1A0omEn74lKPW/9ef0ODA9DRM/jVxvwx939vhVbaHf0T5q+2rvgI2tw6tOWz4jGSo5Lzq6vxnen4Zf5GRYSRX10fJaXMdo/+6uSvAa20RwTkZEzExcZIGiKT429/scvCS2G/KKA83C4ArTy4IN02SB9opdt+ofafUyBvgPbn2irclb0CeQ20gj+yV0DegVb2ikg3ogC00tVXJrULQCsTmfM0iAC0eSp/ngUXgDbPpM/1wALQ5rqkcl+hALSytUgAWtnqLZVoAtBKRVa5qlQAWrmyQ2aNEYBWZlJLPZAAtFKXWO4CCEArW0sEoJWt3lKJJgCtVGSVq0oFoJUrO2TWGAFoZSa11AMJQCt1ieUugAC0srVEAFrZ6p3r0cQTxuPQEz4ERKOrmfEs+FwPKFSYJwp4B0YREhlPleK6eRJfCJo3CsQnJuMfGoOpZHNb4fqdFXj6IYyyJtppDgf4nXsjtD0nCojn7zOfMIz11NH7Zg+6nNwtlPlRBQSg/VHF5Kz8p9BYhi27LGetEpojKCAoICggKCAoICggKCA7BQSglZ3WUon0GWi7NihK9ZLf2VNJKi0QKpWFAvsuv+fOq2Bm9a8mrPDIQnA5iREaGc+Z+350rV9UvE2qcP3GCrjve8LoLuUy34v1N+6X0PSsFRDPX/f9T+hYz5Sa4u9nYQ5LdbgIQCtVeaVf+Weg7dawGDUEoJW+4HkUYe+ld9x+FcycAdWFz8Q88iAvwoq/EMU58uL5LVy/twKL9z1mTJfyAtD+3jb+UOvF81fse2cx0JYu+EP3CoV/XAEBaH9cM7m6QwBaubJDao0RgFZq0sp1xQLQyrU9P9Q4AWh/SK4/orAAtLK1UQBa2eqd69EEoM11SeWyQgFo5dIWqTdKAFqpSyyzAALQykxquQkkAK1srRCAVrZ653o0AWhzXVK5rFAAWrm0ReqNEoBW6hLLLIAAtDKTWm4CCUArWysEoJWt3rkeTQDaXJdULisUgFYubZF6owSglbrEMgsgAK3MpJabQALQytaK7wJtcmIg/m9DiUrfLg0NdAoVQl9R8Zda/PDcOs6e8yUYqNR5NN2q6vxSfbl2c9Qn7l65i2+yImWr1aeEYfb7QEZ9usfhrcd4FhmHhnF5OnfuRCl91VxrTlYVCUArdYnlIoAAtHJhg8wbIQCtzCWXWkABaKUmrdxWLACtbK35LtDGhtxk2ZjpbLvrI2lZvooVMQgNxScggPyampg07Ivb+CGU+Mn93r3vHWaqVUc234U+nm/YblVctgpkFc3/HMPbjeRkbH7GrjzCqKaFsm1XfKQf510saTn3DIZ1uuHp6Um7CgUyvyc6mpCQEAoYGaGkpPRL/RWA9pfk+21uFoD2t7EqVxsqAG2uypmnlQlAm6fy50lwAWhlK/t3gRZiuOw1BWvrJTynD6eTt9EM+HRyHjX7zMUnWoPuU3fiOaUlWj/R9oRwX5aMaILT9pdyBrQnmTzMjcsxalhNWItVy+yBVtL1s5NRMHf+DtDGcGXTVImeNT1fs23grwG8ALQ/Meh+w1sEoP0NTcuFJgtAmwsiykkVAtDKiREybIYAtDIUG8gR0F7xmoqV9WIJ0J4RbZcALdxnslkrnN/H0Gb4ajxX9sEIECVHEfTBF9+gCBIB5QKFKWFqhMaXU1lFJMUF8e6dL2FRiSRGBbDddRDuh3wkQLu1f0H8vH2JjE8RQkmlAKZFdYny8yMwKg6RghIF9E0x0k2pUJSUQJD3G4LTljczIl98FG+8fUFDHzMjHeJD/PAODCdJpIBGAX2MjDRICA3i7Rs/YgBVrYKYmpmgpaQISdG8e/eO4LBYUFBGz6gExYxSUg6iIj7h6+1DRJz4X2poaKSkXOTTM8L0wQKUm6cC7VoPamgG4hueRH5tI4oVM0JdCZJjP7Jj5gDsXE7RbO5pXHqYoKohbo8uqj+xWCsArWwnTF5FE4A2r5TP27gC0Oat/rkZXQDa3FTz96hLAFrZ+vTzQOt/nI41LTkRqcr49ReYYVESVUI5tWIy6y+EoVe0AsWjzrLurga9+lkxrG8XTAtAXORr9i6dworz8dRoUIuCQffZum0nL4NTUg429VHk39VurNpyhSAK03PSbGw7lMTvxCZGLtxBglkX5kyzpWHJFMBMjgvn1OopLExbvnt1uL+bnuOWkmxihZfXYDRfHWfOyPlcSjBj5BwnqiVdYcvm/VyKrEyror5ce+xN4SpDmDS/F8XjAji6ezkT5m4nPFmLHpM2sciqCqF3/mby6r188lWgfF1jXuy4zEtNMDarTINeVozQPIR2S2cMy9Ri0F/tifx0gQPXXqNTtAVOi2bQs64pvicWMXGSAztuQ82afahZU4+ilTpjNbAlxllkKGQ3JASgle2EyatoAtDmlfJ5G1cA2rzVPzejC0Cbm2r+HnUJQCtbn34QaBvhecmFgi/u8PeBrex+UYBxI0YyamBnxAuYfkedqNdrCWoN7Fm7dga1VK5i06wluwNqM83Tk7GdK/JwTS/ajT1B5eGLWTu9J1oBD3DoVT9NDm1RXp1ahbW1HRe8tZh9JZxp9cQLwl6YtRpN80XPWdXXiC8LviSnKV+TjW9uYl08msvLRtJ50hYStGux4eI1upf4wMrWdXE2ceXqxOIssLdm9fGiLHv+D/1VHjJr2DCWHg9mxJF7LG1rRPyHw3SoO4CTEfmwWnYCTytNPJq1ZdRlf9rbr2XtDHPeuvam4bwr1Ok0nsVLJ1DvVcoKrYphFcY4zaJH02LscaqByyl1OkzzZPOUnii8vsgCp964HPKhi7BCK9vR/htHE4D2NzbvF5ouAO0viCdntwpAK2eGyKA5AtDKQOQ0IX4QaGvSbHgtDEOece7sOfw/1WDSht3MG1Qchc8pCG+j+ctqGV6eVhgDXpYKWO+AZuM82T23GcsamzH7VhnGeXox16o+ypnl0EY8Zp6VNXP2XqfwpDO8md+M+17WtNpUlGtnZpHhEEifK1hbWeH133O6bXzDnu7RzLO2Zu7e64j0jJm24xZTqt6je60+lNviR9/oJVhbO3HddDpvbsykGD5ssrZm9Kb/KNB9I7d2W1PI/yQWNXuzJ1wlBWjb+WNRI82/rarw1tMCs0GHqdNtGp5eU6hwK2MO7bkZtWg2+1Zq/60okJC7OcPCCq1sJ0xeRROANq+Uz9u4AtDmrf65GV0A2txU8/eoSwBa2fr0g0D7NYc25PUeWjYazK0wFfrMO4DnyHw4lWnPUr9Euk1LeUlM/AT9M9CVsnTh/KoajNduyQ6dGszx8sSxcxUUMn0pLJory0fSaeIW0Ldizw1HbtiN5Wbz2eywqZWJQoHsGWvF4OX/ot7clX2zi7P80H3qvtjO6P1BtB+3lmk1bjNgtynndlnzfL0T1sM8eK1VnME9WwCh+Pj4EBoKBk1msMmlDbrpgVa8QmvellGXUldop7fmjVt3Gs2/SftRG/Ba0h39TF4KE4BWtgP6T40mAO2f6mz2/RKA9s/xXQDaP8fLnPZEANqcKpU75X4aaOE1ixo0wuFKGI37LMDToxau1Tux9mMC7UdvwGtRd/TTAG2NYR4cXVyeMZot2MF3VmjFL1/d96JFq9HcSdBkgN1owh/5MWrFXBoV0sy05/4nZlGzz3zCFcvSu287ipRuxCDDQxTruZEqjdpRWQ9Ue8xjg6UZp1eNw9puLe9rTufVCXvS7nyrqKiHjvh/ZADaKoTeXUeX9qPwLdiVnj3L8GLnP3xs1J3xI+zoXLVQprscCECbOwP1f70WAWj/N0eAALR/ju8C0P45Xua0JwLQ5lSp3Cn3C0D7lDmVzZn+MALzfovx9GrHv+3qYnsihPo9ZuPl5UAZddg5WIs+G5WxmOPFesdyzKtcDrfnanSY5iXJKVWLes/MPuVwORHz7bZdCa9Z1L4RDqcD0NIrQcfRc1kxwQIdVYXMex51maEVOrPRJwTN8m1Z6O7O4Fr3aa3TjUtqalB9IGd2uFK3qCoPDrhiZTWN24kt2fviBF3F2zOIr7t3uVutGtXE/50J0N5d15n+zuEM81hC4yIpt+iYlaO4dv6Uf+RghVZPFMh6p04M87hCo/lXuDBJnCD885eQcvDz2v1OdwpA+zu5lXttFYA297TM65oEoM1rB2QfXwBa2WqeA6CN5rLnVKwHpexDe/zZTIoTwbH1E5m6/BQJGiZM23GTyS0N4Z0XtUsM4n2tLmzc6Elb9dv0K9GC03VTDhpoW16LczNrYz7rJqJSTZk2y478/7rgteMmL0TQZ+NrtlmZoZDKrO88LSg+aA+UbYmXpycD64uzcrO+zk0pQbP5byjzl3hnA0/ExTf1VcRqu4hm47zYPXcgBdUAnysMsrbG679naOq2xdHNjiIfD+HotonhB58wr2kxRPe8KNF6NG+j1Rm47DiebT/Ro2ZvDgcm0KJFb4xTm6KuXhNr685UqZKyQqvYfAGGdbqy0dOL9uW1ODujFuZzbtN07EZ2z7VGP184RxePxMppG5/ow5J/OhD27A2trKZI2vujlwC0P6rY71leANrf07dfbbUAtL+qoPzcLwCt/Hghq5YIQCsrpVPifBdoo4OP4z7WjdMpB4V9c5Uu3ZzONoNpI37cnnqFP9nErAVbuPHGgESVEArq1cbOZRytU48SiwsPxnPWWLbf8EFFpTS9bEej/XQB6yQBSuOwaBVtqqZW5n+MLjUtCG+/CM8lwymm/h1x7m3gr/H7qdHKDkfH1pKUB7/j8+nn9hyLCY5Yt67A58NoQ17fYvH6uVy+5k9CgjL5zGrTf+IMBpYvANGBHHd1xePibcketTrlGjFhQicu9OqN083X6BoZkbImG42PTwiY1GPRRDtCTu/mSliE5C9VLYZiUyOMxZP/5oXk/xjTf8ISBrbWI/rdNVzd3Dh5x5cCekXoZudC39Yl+F73Muu9ALSynTB5FU0A2rxSPm/jCkCbt/rnZnQBaHNTzd+jLgFoZevTd4H2Z5sTFRVFnJoaeoopBw+kv6KiQJwJkPHPycQRDWiiGnob+06d0Jt6mxmtDH+2Kdnel5wcTEyMKhoaKfvaZnVFvjzCxBET2EUTlo/pkHoqWhCnNyxi8T4/LF08WTW2HQVUct7MsLAwtLW1c35DJiV/D6CNJzAwCh0dbZSVMx8PEIWPdzzGpj95hnK2KorjfyIqIg5FRRUKGhRFPUe/HsLw8QZj01/z6JcMTr0574A2mcjIMEADTc2vm+V97lNiYhA+3qGSfxYwLYausnJudDdNHeL4nwgKiJL8Pz2zklmfSBgexrugwEziq6JuYEhBzXxIRl+kD6euvaZcvToYa3z+iZtyW8TTE1wMK02LumZptgZMrdL7LF53denZsepP/fj8GWGkD7Q58PdDKIiggElRdFV+4AMuRx3+AX8JI+RtIOGirxUnxgUQEqZOubpV+PJ2hcTfN5StWxsTzXT+PjvBxdBStKhbIqO/H86x6Y4OPTpURT2LzLYcdSmLQnkHtPEEBX4iUvz5p6xMQdNimYzfaHw+fCIxIYl8mloUNDDMqM+vdP7LvZ/Hmzqa6bz5tvpoIj58Ilykm+3nb3JiIkEf3hMtUkfLxAA9lXSnEyXG8PTOVaILVqJqCQN+4uyiX+q1bIA2jb+Kyqnfb6kDODmZqMAAAqMiM+mHNrrF9SmQ62M9npjATwRG5MekuP6XJ+4ZGxDO+7eBiEQi1PQN0NcqkPL5nOaKeHaSS6ElMa9jhurnR/fivwc+ZNvFSNp3qouO4tcOSA1of3YUxIX5snqxPZRpi8+WFRw0aXJ25AAAIABJREFUHsa5ZcMolD1v/my4HN/3dMcIzG3Wkt/2lGQbsc/XVefG1HcLZ/paLyZ3r05WKb45DvSDBeUdaJPiw7m8cw6bzhdgnOs4KuhlNDIm+AmHVrqy52NDVqwcIllZz60r9NJW5u86hJpxa5rUyset3Wt4o9UGm9FjqWqSNdWGv/8PzzlLeVBkOItndZDs2JGXV14B7auzrnh4vqHpCEc61jP7+oXw/g4e21y4/8yUJl0awav9nLzpR61hXowyz8Ex0TkR89FJZm7xIDyxAU2al8Dv/AYufzLEwn4ZnaqmfZUztbI7a+k6aZMEvr65CpTHcvwUutYz4+mjBxQ1UWLzijM0HNKfisnX8FdrCWFvUTIqgvLtVWy8WQW7/jp4x5SlvJE6IcFBiJHeNPQANm6qLFjcmOgwKGRQlHxS/oaUNtC+OueKx8Y3NBnhSKe0/oq/M87OZ8qmEBp1bo1uyDX2nQ6kjdNielTKpW/AxyeZtdmDsKQGNDEX+7uRy58M6G6/lE5VdckY5SZL247hbPJXg5OTRJSoa4vTXEuMFBR49PgBpsaKbF5xlgaD+1NJlMbfQoVRvruajTcqY9dPlw+xZSlrpE5ocBDhiDAJPYjNQlWcFzYmJjz3/c0LoA27vB3nXQdRLdySxrXyc2f/Gl4XaMXwEWOpZqoB8dHcP7qS9YcfYFK3GzUKf+Dcgd1EVxzBlCHd0NPI3R+or865scLzNY2GO9Cpfkky1p7Exxdn2bByDdFxpSjZqgsWnWujkxZmvkzuB2ycNY84066YKrxn/xlf+rm50bSQkmTsPH38kIKlTXm0ZzMBhi3pUuUDr0QtKGeQS+M3B59h0gZaib9/HyKfUQuJv/f2reOV+l8MGzWW6kU1IS6cs5ums3zvDdJMm5SWm/VnqccwTJUVM5lrOehcJkViI5+xZYkbT97nw6R+F/pa/UWh9KuWwd78u28p+8+GU719F4rEXebMmWtot3FlRs9qKCkq8OH9OxQLFUL53jo8r1dkRD9dfGNLU1w3H+/9P2KS7wUTZr7EcWl/tEJfICpQDT01he+nHPxct37+rpigd0zvVQr3c0CNqby8NiPjvrM/X/0v3PmAqT3b4LIvDIMyzWnaBD7tOs01NBjtvo1JA/7KeuXoF6J+71b5BVoRyd4XmTWuO7eDknmb3I2Nfy+itqFWmi6JCLm9A2dne268TSbQyIHjhyaR+r7dd7oukgz6IqbFSfMDLcM9N93b4v6iJbNdx1FCA0I/7GR8k+noO3kwbXArNNN/oiZEc3e/Mxv+Wc2V+0nomC9n16q+FPyeEVL+u2yBVoQo4BEeU3tx2c+fRz7VsHf1YGDzcl++gIIvLqbPmJOM2H+ELibiL4hA9o80Z9Gd6rgc2kQD/ay/NCIjwhChgJZW9j8TPu6xps8SEc77PVPr+8CqTnW4YDyO2W4OlEq34cnH3Vb0PmLGdNsBlEmNHxl8Gc9NJ+hku5zGpe+zuld/Lpbuj7FhIRrnP4XzOjUcFztS6MEcJp7RxdKqGn4PvPG5cQ+9xrOZb1+JN+edmbHiLnUtm/P4dgJmEad5ptCfhbN6oKOVu1/46YeRdIBW7O/jVH/9MvVX9HQ77QZOpq37a0bVU5SsstxcVJOxe8qz4MBmGhpk9aQFfsRfyyUi5qf1t3MdLhQZm+pv+jF0iTl1bSjpcYBGhp/jK6OpaYKeZIJelvh7oXQ/TAoVorHqKRasU2PC4gkYPpjH5LM69B5YFf8HH/C5eQ+9RrOYZ1+Zt+cXMHPFXepYNuPx7USJv88V+uE6qye6uehvXgDtrWXtcX/WnBkLxlFKS4GogCvM621NUg93pgxug3qcP9tmDOJpGXsmD2qFlkoir8+uYbqjJ/XcDzKyfpFsP18TE+IJCQ1FX98wm5U4EaLAx6yc1ptLH3156FOV0Qs8GNiiPCrfWCzi01UXJky/Sdf5S2lfy5isnweIuL6wNlNf27PNox8GikEcHNUS97udWHFmBuWVn3FwdC+WRLamdfPikhNJd23zpqPDKkb1KIpipoCc+x/i0gba28s74v60KdOdx1GqgCJhPn/jYD4d3TFLmDK0DRpxAWxbNpanupZYtayAmkTwcC7tmsspDVtW2zRBWSmrz2oRH7zfU8QkJ3qJv+93MLjzfKpM3M6QHpXRykLjqFenmTVpEUXt1zCigQlKCpFcW2WP0/KX2P37H92KB3Fj7Rgmn9LCon81Ah758PHmPbQbTGNK3/e4jXEnvlFHQoK1aa35L1sv1WbavLHUKPtY/oA294fUn12j3AJt+F32rb9BhQH9iD07j6ken5ieHmgDT7Frsy8NhzTn1hw7nJ/WZm9OgTboDGM7DMFsyStGZ7NRRPzHe3xKKo5JatpAbMh7lo+sw6vqHrjYW6D97RNJIl/u59zNAjToXIgtrbtxsOL0/z2gjfnAlYOnyVezCyXz/8v4LhtokA5oCX/Hs/fKlK30+U3GBC7Mqc2Uo/VYdHQVtbWz+JBMjODCBgcOBDRlioMluqkbhGQ6SwMf8iygEGXLG6T+OZZdw0txWMWJOW6jKC5+wTPNFXR+GxcMLOlS/nPsWO6vGs6m8D5MdWyDrgJE+T/n4u6FrNlxAu0WVgyxGkMdEx2ID8H31j8sWeTMc8VydLObhUXdWmhrKpIUH03Ao+NsXDaTE89EtLafS9+/WmOqp5rNl3jufO5IBWi/8fcI47tuoIHL8jQ/WEI5t2gUU7bqsuLWUqp+/sV4dxFNrDfS3e04o/8yyXxVJzGCixsdOPCpKZPHW6KbzqNvVAl8xLMAw2/8/dumFIeUHZntNgoztcyA1o4qnrfoXCGLVDaJv4tYs/ME2uYDGWxtT10TXUgIwffmbtwXz+eZgtjfmXSvWwsdTaVUf0/guWwGx8X+jp5D35Ztct3fvADaeN/7fEosiolpyhON2OAXLBnWlai27kwc+BeaCvGEfHgNWkXR1RM/sRLhe2Mr0yaspu6i3QyuUThboA287sJMj/cMXrCc6kWy+JET+4GrB8+gUr0TJdWOMqHbBurOX5YBaMPfezKp22bKL9yAbdMS2c6thPeHGN17DDqOF5jXOQW6gw7b0n7WBUasuMiA2gWID/fj+Zl1uK/yJKJ4c/qNmEKrcmbkz+4zJ3em7ZdapA20Cb738U8sirGJjkSvuFBvPOzq8aLSIubb90KbSB7evIlmhWaULCieTyJiXp/G2e00Tac40Nwksychqc3/uJNh3V1pu+46nSsqZzsOoj+dxNViJp9sVrC8d1XJKmuWV2ywJE1Nv2hRVFXFCwJJPN5pz6j5rxhz7CDti6iQFC3+PN7D0sXOPKM0XUbOoHu9OuiIF6XeXOOglzNbjj2gUv+JDOrelwqFtBBnu8ldykEuj6c/vjq5Bdovysdwb3cWQPulzEcOTJAO0KYfAJGfLjK73zgMhnswqmsd8me50PSIZU3+R4E2jWihH3ZkDrTphI0OuMrsIf15X2YJy107IPnszOz6EaBNd3+490HG9nPAdMAWJgyuy3ezkLwPYmvjQctF++hSTlz6Hf+4uOOvpoq/vzL1yynw6q0uVS0s0Xy9nxOP31NUI55XAZqYaSYTW34wQ9oZ8/7BMQ4evUAhnUTOPNamVfkE/DXbYNmtPlpqWa9U5saHj1SA9ht/d2YCtL4cdLTD+Ukt/jkwEZPPX04RRxhRbwxaDluYY1U38/SqHwHa9P5+OMi4fg6Y9NuCw+C6aGYYQ+IV2uyA9j27XZfglz/F33rlFHj9Vkfir9abAxx/JPY3jlcBBTDTTCK2/CAGtzPhw4NjHJD4m8CZxzq0Kp+Iv2YrLLs1yFV/8wJo04/BtzdWMnXGEdpNWkrPxhkf+ScnRnF2+1RWHBAxadUcan3zRC3jiM4R0Ka5LcxnJw5dMwHa6DdsHN2JHUxg+9r+GGQHRMCH49Oxnrgfyy23GfgZtp6uonWvZdSasos5PYw4vdaDW5GJqCUko66ej8QQBXRbjqFHfd1s4Sw35u3nOqQNtBm/3y4xd+B49KyXYNe9HurpV18To7i6w5kDAeVxsOlNQfVscqZyCrTxgZxcbs+s8+XZvnsSpiopKR85veIj37DFeTT73rdipactpspR3Du6g+MP32KiHsebQC2Kiz+Py1nRu2E4e9ZtI1kdbjzXpEvtRF6FVqR5ty6ULfJJANqcii6v5f63gPYTNw7u5KEvkPCK7et2U66FEzXKit8WKoV5hxYUV0u35JrOuIdb+rPgRDHGu02hmpFaNhNPAFqxdN8D2qT4t9w9cpxt559Sun5H2pg3xEw/vQfReN//j/M33hKfEMfzu4d56VeCFi2qo6qminHtVjSuakbmi3lJxAQ/4uKeo2x/4EerjgMwr1sJoxy8fflk7V+Mfm3DnjkWqS9rhuP9wg+NfCGs3HqNTsP6YhoTRLyOMSpRAUSp6qN8cyEeb80Z382M0CQ9ShRSJyrMj+AYFQr7eGGxtTjr5zQjJgKMDPVRyfJxXe58YuQN0IZxfrEdkzdHMOP4XloWSoX2gD1YNXFCZ+Ra5to1TwOcKf5euPGWuC/+lqRFi2o/4O+xFH879MO8XuUs/L3EjOoDCetujV5MkGTulm4xkLbNq5Ly2mY43i9T/F215TodhlpSNC6IOG1j8n3299ZCPF6bM757Wn/9CY5R/uLvutnNiBX7Wyh3/c07oI0h/P1tjm37l6PBilh060+jaqXQVksLM2EEPr7C7q0neaFVlC4dLahXvkgm4zuJEJ8bXDx7g8BIEREBZzl2IpQmbTtTSE8BtdJNaWNeFZ0siCYroA2/vRYrmzmUHfA3lQM3cOyRjyQXvlqX+QzqWz1Dfc/3jsZm5n1sD/1Ht6LKKau5H3fQt9UMjGzXMdumNuFvvBEV0Obu4c2EmnWgXSllQlSLUVxf9YeA61dmsqyB9tE2a1yOF2G082RqGGtkeMkqPvwj6xeNQ7PZLCybliX9O9rxMa+4/O8R3gaJEMXfZdPa8zToZEcpU0UUClenfcdGGKb7sRH7/gLzJ47Cv6IrfTT+xevyC5KTRRRrYI+dfWsKZfkZ+Yl3l8+y7cBVks1q07FtO6oU1UZBIZ5gv49E5SuI8u0lrHjdhDFdSxCepItpwXj8faPRjb7KII9QFi/shXJQGPn1iqCtFi0A7a8MVnm4Vx6AVpScRFJycqocCigoKqV55JCbK7Qf2DBxOBdei0O95uF9fxQU61OxEmBUnXGznaiikzZHN61DIpIuzabx+INM2nSTjmW/9xtSANqcAO2TDRPwuveSm9cuYWAwGvsVk6hXLP0v9Eiu7l3Cpj1XiUmIIyjwLu/emVGpsiH5NNSp3t2WId2aZbrimhgZwkWveey9d5lrl19Qo95CRjv3p/yXHMrMZ6Eo4DTjOq+g6T+76Wys8O0XWFQkL54GolzRBLP83+bAxr1+y5METUqX1c/YHp8PXP0AZeqaoCejyZ83QAs824Wj9SSulu3FmP7mKD49yYmLD7hw/y2dZ+5mjkWlNJqK/XVn854rRKf1t5IB+TQ/+2uejb/z2XvvEtevvKBanYXYO/enXKHMX1R5cX4L7zUaUdpAgY87ZzDC8yJNbNYwd/RfaH2e0p/9rWCCmVom/sZrUrpc5v5e+wCl65ig972Ph5/wP6+ANurVLQ7v28mpu/u4d0eBdpYrGGr3F0W0vz5dCL78N1v/u861O1vx9alEr7Hu9O9eEfV86YVI5M3dPWxYuYUPYSLiY6/z6KEeRYuXpGBBBXTqWDJlnGWWK6xZAW0KoG6HerasnGdLOQNFbu0dz8h5t7BaeJLhzb5NfcgSaFtOx2D4KubYtUBLDF6JiXx6/oEgvYKUMtLKJif3JwzNwS2yA1oRSVfmY+6wn3HrrtC5fCrkp2tjwLUlLNmcjLXzWEoXyPh0KSr0NmtmzeDBx2REovvcuZmInkE1ihVTBLMWzJlvj4nSt5/vn+7sYrqTHVfUurBm+VTqmhbk1ZWljLBfSYUx51jUpyTKmay4++5zYf31t9y6uY/ExPYMdXalQ92CpOXfuDdveRKvQakyBt8+sQkO5NbTSIzqFaOI4tfPdyHlIAeDUp6L5D3QxvHw3+W4zfVCslWxekFaj1nPhI6lU2XLTaBN40QOc2gldyRF8eHmThYsOMhf89fRpXxOtoATgDYnQPvFkfB7LBs+mN3v6+J+3IMaGZ8XpxT9hZQDAs/gZDEC3yqjmOtmS9GsFuOTori2YRQLHjVmnbsV+jJ6AUQanxN5BrTizgQ+4uj+s7wKi6dKs5ZUD91CC8cjjFxxgYH1dH49hza9YIFnmNhjJL6V7JjtNpJi+b9PlWdnVcT1aSNmuXpQ2zS3txTLXUfzCmjT9iL08RYcBi3HePgCHAc0RyP9E+ekGO7tX8D0ORfpsnkbVlWMsl3NzK2Ug0wBldvMrt6Nt02nMdttECZp3iBLKX+ZwbuvYlk63Qqt3XrmDG+MuhzMe5kAbVI0Prf+xsXlAM1mraRrxcKZ5x/H+bFxdAs+NNmMQ58aqH8nrYMcphykAK0bFafvZ2RD8Ute4hH3ig2durA1qC3uJ52pop5NGkLsBw4tmojz5gimXdxDawPlDCvLOZ2JAtDmVCk5LZf3QJtMqN8bnj99Q7xYI8V8GJrVoozp5y2x8hpoE/G9s5u1Gy9RtpcDvRsVy6GTAtD+ENCKn/jtHkgX59vYr7lK31pZZLj+CtACN9zNmXK5JHPcVlC3WOZEG/n2DG7zV1F2mAeWtXLy4yWHQyIPiuUp0H7T3yiuu3ZhwuVyLF2/jGpZ7WLxCzm04nA33Zsz+XIJZruuoF7x7NOHxOU/7hmO5dYYZrl40LRMXm+ul/0AkQegTYz0Z+v0DhxRHcqKKYMx0MyYQxn18j+mO9oR0XYnq4dU+/WXwtLIkv0KbboUAiLYNqgSJzUnMdt1OEXT/MDxOTEDK6dVtPf4yOgGqS8sPVlBG8uVNJ93CIe2ZjLbySA716UPtIn43d3Huo0XKNl9LL2biPudeYt8jtkxZi1MWr2U6oY5yHP9JaCN5uz0Jsw63ZCFRxdTQyv7eMGX3Ok7xo06M+8yva0BSj/5aoIAtHnwJZWbIfMeaL/XGykBbWIYb5+8QrV4DQpnlWUAxEf4ssl5JLE1JzK0Sx3yKykQ8+EJF+6F0qB5HcRnBcQERIC2juSgj6+XALTZAW3YvZMc/VCcXu1Kf1kNEANtV5e7TNh4E4vKWayWiZII//SW4ARtTIroZ8jhSutA4Bkvzoja0qP5131txUA743pZCdDWNFYiye8TkWqGfDmfJCmamztnsPxKQebOG4epdsbDIL43YuXp7/ICtGH3tzBq1BTMxt1kaifDdNstpVHsh/zdxBlRm2/8FQPtjOtlJCuutUyUv/E38NEJzvhX/ab8/VXtmXTB9Et5efIufVvyAmjfHtmIt3FXGlXRlczTz0B7SssWd6cB6ChEcu/MWbQqt6C0eF9a4DPQJnbdz5J+5bIF2oRIHz74xmFYrAQaOZhqWQFt7J11dB2+kI4rH2FT8/Mb9Z/Y0L8h96ssY9b4NugEBxAoMkDfQIHED/9i32s0QX3/YZtNDQkABR4aSdf5/kzbsZ2WxWWXJ5uXQBsf4ccWV1uiqoxnaNd6qCkrEuvzlIv3gqnTtA4FPu8jHHYHl4F9ed12O8uGVkX1e6uz4k7FB/LqmQ+6Jaugl81JIwneF5np5IBij+3M7FwiFUbDODbBnMWfbPBc0RetSAU09NVRUuZL+2o3rYN2avs+A23TBU+Z0Fzrm7SDH5nTAtD+iFpyWFaegVaUlEhifDgXPScwcxcs2O5K7UIFUFRURjF1QiUnJpAU8Yz1E+1Z72PO3r2OGCsqoqSUWQ6QNyfWLOLK20yMKFSVHkN6U0Hz21eLPl2Zyzi7AxjWqU8ByZsjCYS/uYZiZQemOlhC4A7GNVlCeVcPRlnUIT8ikhITSQ48y4Quw3lQdQbblvdBX0kZ5Z/92ZgL40a2+9CCJC86KZmA664MsT9N5/nuDDAvh4qSsiQ/+vneUdjMfMCIA8fpaqKESPSIlS37crTKFLYt603Bbx73RfLswnb2n3xMbEI6MVTUKPVXPzo3qfj1pKfUIjcW1WTcnvLM27NRsg+tSHSJadVtSLJdzcyR4pzbi0ws0Zegbs7MXWiJGHsTI33ZNGUMIY0dsLOonXpEdS4YkEdVSAtoM/O3v3k58qX6m9JdEUkJMfi92sucqTvQ6zObed1qZvI4M5Lnqf7GZOpvXzo3qZTB35uLajNuTxnm7t5IAwNFRKLLTKthQ+KIlcwcaY6mwiUmlrIkqPN85iy0JHnvYHovimfO7g2S8oguM73GcBJGrEotn0cm5TBsXgDtwfFF2Rk1gunzx0v2oQ3x2cXkPttoMH8J/czLkRzqzQq7VvjVd2OidWsKqMRyf78rc9YGMmnLAmobaadLOUjE/+VJDuw+gW9Y+hNMQLNadwb2bJQhzefLeLvhxlD703Scs4j+LcqjqqSS+r5FEIfGtMYj1g5Pd0sMlMF373D6LX3I+PVX6VT+GSvMe7AnoSerzk2jnJIit5bWx+GfkszYtZ6GBs9Y3aY/J9qtYP+4RtlvG5VDv3KjmLRXaAOuOjN+9D70a9SlgHirRIUEIt5eh4pjmDy+HwUlICoi8MIS+o17w8zL7tTNZheCuMj7HNroxWPf5Azn01CsGYOGdsJEKX1+eyTX145n4kkT1m1ypGg+RYIvL8facRltFt2nif8iZjrepv+JDXQtYUjg3b+Z6eRGmUm7GNGgKEoKH/l32gQWP63G5t2OFFXOwepxFuYIQJsbozYP65BnoH32jxt7HgTw/p3kLS7JVaZiLeq3G0H9SinvJd9YP5mDz8IJ+OQn+beysgrlarejXScLShRJ/957AEfXL+GBeJeD9JdeaSwG9qZEOqC9vMqCzVczFi/Txpbh3c0h/Axrxu/DdIgtnRuXhcgQTm9y49QTPyIiwiU3ig8AKFO/P5bdmqDxzZvBsjNe1kD74eIe9l24xaOnz790smixElRo6UCXxoaEe59l298bePQomdJGlfgU8gKNKv0ZZmNOxqfRMTy+uIeTFx4Tl5hOM+X8lGrUmXaNq2aAz6Cn21m7Yx/Bnwww0zXimd8TyradQr8elVJPbnvExoELCG80iIFDzREfmhwVeJa1buepN8SW+qXz+jiMXx8f0gJan1R/H37jrxkV/ppAlyaf0zQCODRzJOdjStKipy3Nq5lmcTJaDE8u7uFElv52ol3japn4u4O1O/ZK/C2ua8Rz/yeUaT2F/mJ/JY9NH7PRegHh9a0YMNQc0bOzrN2xknep5X0l5YfQv0cLKRzf+evepa8hL4D2zbVleO69gCiuJKbqKjwI8qVZ36m0a1wc8Ta/SfERXD+5mH3HHqKtXgNdQniDJl0Gj6RuGf1MT/Lye3mBI4dOSnY5SH9plm1B3x7N0U6Xv+pzaS/7z9/igWS8pdxnWsyMCi0c6NKkUOqPpEAOr3Hn9It86Bj64x+nTp/uDjSsUAgF3nPQcS4Xk5owyq0vppIFEXH5hZy554u+CJQqD8Dapvl3t/zKfWezrlHaQHt1bW82XU5ElM6K0q1sGGbRAi3J0aXBXN24il2x9XAb3jybgxQgNvIFh7ds4k1gJkBrVAOrQd0wzHRhJ5yre9ew7Xg4BmWTCI0Kp0kLWzrVL8G7y3+zef1LWswfS8PCOsSFPOfYoZWcuvCBYvp1SYp5T6RhDQba9qGkdv5f2oHiu0D7/vYu/tl9jyCgSPOh2P1lJsvx8E2skNe3OHHkCvfCFGljYUGjsoZZJg9HvjiDx87TxBqXpFXjNtQsbcT3M7LyrGs/HViegfanOyXcmEEBWQNtji1ITiYhIhbU1FHJwSPHHNebtmB8PDExoKqVj/SnKP5Ufb/RTdICWrmS4Ef9/dHyctLZvADaL12PiSEyXhXNNDsbZJAlMoJIkRaa2aRwyULKhIR4YkSgmS9fjl4OEpcXM7JKPml9AP18r6UNtD/fMuncmZycTGRcLPnV1MmJG8nhEcSpaKVL9/v5tn0XaEPfXmXu8B4sOvGBmtPPcnNW05+P9gt3vvx3DjYzN/E+sAUz1vbFvHZtCutkvY9oQpgPDy4cYurcSTxRasNMt/n0bWCWyS/OX2iUHNwqAK0cmCCDJsgt0Mqg7//LIf4ngPZ/xOA8Bdr/EY3lrZv/a0Cb1/p/F2iJCcJrqgXWi8/mGdCKvC9hZW3N5lOvmXIukblNci6b3/lZNG02k6SezpxbOx7jHGzInvPa876kALR574EsWiAArSxUlr8YAtDKnyc/2yIBaH9Wud/3PgFoZevdLwBtPDHB/rx87kOUuM35tSlWojSFC3zdyDomJpiPL58TICkAaGhgUqoyJmoQHx+B/5tn+ISkJtXlz49BiYqUzACc8dzf74K19XRuJw/hatg66qbRKCLclw+v3xEWKwmAZur+l/kNTChuqEPMp+vY/1UXz4f1WPn4ICO+nAsvW6GlFU0AWmkpK1/1CkArX37IqjUC0MpKaenHEYBW+hrLWwQBaGXryE8CbRwvTnux2msf1xPrYVEujKMX75KvSDVGTl9CmxIQ+eI0c1d7ce96IlUtqsH1I+x9EszQDfcZbfwUL6+V7NvjQxnLRui/vc7RC3epM+sUS9sX+VaB5EhOrxyH1ah1eLd2J/SYfeoxhxBycyvjPfYSGqRGtcamPN10hsdqYFqqGo17W2HTvj6qUR+YP7Aasw8mM3LvPVZ0NZWtwlKOJgCtlAWWk+oFoJUTI2TcDAFoZSy4FMMJQCtFceW0agFoZWvMTwFt1JsLOIywZv1JFaZfucqEcqHsnj0U2+UnKdpoJftOWfDQwQbrpfvRst7D3WUt4dluHO1XYjjzPD0DF2BtPY+7DdzwPzCM/P7XWT3bmectNrLeMh3QxgazbWYbnlCSAAAgAElEQVRvrF1OktDHE9F2q1SFXuLeqC1jbwTSYcw61k1vzvvFvak78wJ1Ok3AfbkjdYw1SY7wZcmIJjhtf0nDeZe5OLm+bBWWcjQBaKUssJxULwCtnBgh42YIQCtjwaUYTgBaKYorp1ULQCtbY34CaOtwxWsqVtaLea7Yl7NJWxG/JvZg0yBajvIkWr04S49fRHn5YGw3HidexxDbTYeZ1LoaeioqKCrEcHXzdKytF/E0WUT71cdYOdAc43yf96NLJ0CaHF7SAu2n/+hRsxe7w1QYuPQ4ntZVeedpgdmgw9TtPh1Pz8mU14KE8K9Am5cvtUnLVgFopaWsfNUrAK18+SGr1ghAKyulpR9HAFrpayxvEQSgla0jPw60M2txfp0TVsNX8KbmdN7cnEVxwP/kPGr2nkMg+kzbeQtb/TMMdZzFyRtPCQvTpnKzrgyZPJ6hLSshen8Dl9kOrDl4Gf8ABYzLtGTQ1HHY9WyKoerXHFyJFFkBLW9Z3bItI8750s5uFWtmtuG1c3eaLrxDh9Eb8VrUFfEulALQynZACdGko4AAtNLRVd5rFYBW3h3KefsEoM25Vn9KSQFoZevkjwPtjFqcWT0ea9s1vCs0ktt+K6ieBmhDlArhcuAJdvXVCfM+z94Tpzm2aQtHLrwmslADdl6+RK8SEB3wkGPn/uP0P5vY9fddAnXLs2DfaZyaGn2rQJZAC2EPvLBoa8M7nc50616K13v3E2jehwnDhtO2koGkHgFoZTughGjSUUAAWunoKu+1CkAr7w7lvH0C0OZcqz+lpAC0snXyx4F2VgMeHHTF2moqt0Iasu3jRSwLw5PtNjQfsY44zVZsObMJ/TvXiKvanMZlVAm6s4+hIx3Yf/09k/6LZajyeV5SiiYNzUjwv8Nyx6FM3n6LPp5v2G4lXu9Nc2UDtLdWtqWfWwJjNiynSeGUe7RMSmCi9fUIBQFoZTughGjSUUAAWunoKu+1CkAr7w7lvH0C0OZcqz+lpAC0snXyu0ArivBj/ZSeDFt+geqTjnJ1TmvyRT/DdfhQ5vx9iRYej9jWRYVtNjY4HbtMu3VP2dY5kvmDrZmtOIg7G/tR8Olxho2w5cjDNpwKW0qk+wisDhdk09bpNFQJY+mYNszaXwLPZzvoV0zvWwUSwzm6ZCRWjtv41HsjyTusU45GS82hPRQQT7NmPTE2TrlNTa06/Qd2omZNU5QVFSQrtIttGjNxxxv6bnrF1gHpgFm2eud6NCGHNtcllcsKBaCVS1uk3igBaKUuscwCCEArM6nlJpAAtLK14rtAG3JqG07uO/FNbVeP+RsYUNkQQu+w2cOVXVdiiEnQQVU1H83HjGdCi7IQ482pXe6sOfic+NAodJSVCSpei97jJ9G3lBJPz6zE3escPr7RiPc0+Fi4NE2txjDSvBzqSukFiOXGjtlYWznzqOh4Hr9YSHlJkWcsadgZh+uv0C9SJPWc8Cjevw8C4zq4rfFiTLvyxAU+walTBVZcrcSCa//hVKeQbBWWcjQBaKUssJxULwCtnBgh42YIQCtjwaUYTgBaKYorp1ULQCtbY74LtN9rjvjs3vDYWNTVMz+7Nzk0lNh8+SR/z3CFhxMOFChQIJswyXy8uhUrK1tOPqvHnuCTdNOFyOcHGW/jyD7V1qwe14GU46eDObvBhfm7fLB08WTV2HYk+e1jQJVuHC7Yl/MXVtK4cHaxvtdb+fu7ALTy54k0WiQArTRUlf86BaCVf49y2kIBaHOq1J9TTgBa2Xr5y0Ari+YmxX5k1zRrRiy7SLkROznq3hF/Sc7uWvLbnubN/GZfmnFlfiMaLIxkxjovJncrxBHHBgxYmEynhatYad+GAsqKsmiyzGIIQCszqfM0kAC0eSp/ngUXgDbPpM/1wALQ5rqkcl+hALSytei3ANoUSQLYOmsUIxcdgVI1mb3ajqBlTiw9GIZBqWY0agwB/5zlBuqMcPPEqrAv7awnEJSgQr/pnkzo25wiKcu4f9QlAO0fZWeWnRGA9n/D5/S9FID2z/FdANo/x8uc9kQA2pwqlTvlfiOgzZ0O/2m1CED7pzmaeX8EoP3f8FkA2j/XZwFo/1xvs+qZALSy9VwAWtnqnevRBKDNdUnlskIBaOXSFqk3SlihlbrEMgsgAK3MpJabQALQytYKAWhlq3euR/sMtDoa+VBPf8parkcTKswrBUKj4omOS6SIXiYvV+ZVo4S4UlcgKTmZiJhExPNbuH5vBT6FxmCgkx+FlI0nhet/QAHx/PUPjZXMX+H7WfqGC0ArfY2lGiEgLBbbFVdJShahqCB8UEpV7DysXOxvskiEitKf9VJjHkr6W4QWAcnJIpQUhbn9WxiWTSMTk5JRFubv727jD7VfPH/Fvovnr/D9/EPS/VRhAWh/Sjb5uun0PV+uPQ3ErJCmfDVMaE2uKXDtWQBv/CPp3cQs1+oUKpJ/BaJiE3n4LoS6ZVOO8hau31eBwze8aV/LBAVh4eH3NfEHWy6ev4dvfKB2qYKUKPwHvpX+g3pIu7gAtNJWWAb1C0ArA5HzOIQAtHlsQB6FF4A2j4SXQlgBaKUgqpxXKQCtbA0SgFa2ekslmgC0UpFVrioVgFau7JBZYwSglZnUUg8kAK3UJZa7AALQytYSAWhlq7dUoglAKxVZ5apSAWjlyg6ZNUYAWplJLfVAAtBKXWK5CyAArWwtEYBWtnpLJZoAtFKRVa4qFYBWruyQWWMEoJWZ1FIPJACt1CWWuwAC0MrWEgFoZau3VKIJQCsVWeWqUgFo5coOmTVGAFqZSS31QALQSl1iuQsgAK1sLfku0MbFveHGDZ8vrcqfvwS1ahX58u/ExDhevLhBUFDK/1LOX4IytYqglxv9+HiTTRuOElK4FJ06daKEoUZu1PrH1SEA7R9naYYOCUD753ucWQ8FoP1zfBeA9s/xMqc9EYA2p0rlTrnvAm1M8A1m9RnIwhNPSAIMi43n2KuFVFdKaUCY9wmGNGvN7tfif+Wj59ZTePRtRK5sMvPWk7qlh+FdqysbNqynbYUCudPrP6wWAWj/MEMz6Y4AtH++xwLQ/tkeC0D7Z/ub1fwVtu2Sne/fBVqI4YrXVOxGreVudDSqesbM3vMAhybaklbeXNiMRrNuQWQkcfThjGg7zXKr/QGn8VjyH2GG5bGwsKCsiVpu1fxH1SMA7R9lZ6adEYD2z/dYANo/22MBaP9sfwWgzXt/cwy0c7feI/T6dS7HKtPFcSuec9uhw0um1q7Bce06BJw6xbv0QBsczL1bx7j96BNh4r4aVmSAZUvU/d5w/fp1fGPE/1OJwsUrUd4ULl99SGwC6BauRJ3ysPf/2DvruCi2No5/6ZZSKVHA7ha7E7tbQa/YfbG765pXwQTj2t2FCnZ3oCIqKIh0x8K+nwVUEFTQ3WX1nfnr3o9nnuc5v9+Z4Ttnz5w5eI6I6ATQMqdp06aU0vdi+ZarqaoVrEG/6gZcv3CCx4FaFKzRFLsq1iT53mH3QU/C0aduuy5UstKBuACu37jBa/9YVNQ0KVO9IRa841xKviS0zKyoVlKf45/yGdnQtEYZIp+c5qpPIkY21Wja1BbTmJds33KUQLQoU6Mp9apYo5Y2U52bVgpAm5vqyye3ALTy0VnRsghLDhTNkZ+vRwDan9fudz1TWHIgX+eyD7Rn8tBOaR2O/wVQpsVgXN3+pcrb+Vi3PU1Xx7IcmLGK55+BNpoXh6fiOOsEEUUHMq2nDpuWLefs3RCqOjizZ14tri0cxkjns8RqmTLi3+OMbQgbHexYfLskyzb/g11lY24dnkrjvuugcAPWrl1Lr8ra7PrXkX5Tj1OwbjMqGqnx4c0rrt31Qtu4JdPHa3P1/HsePvbE+60aeRvN5urh4Zgnx3PdbSG9ZzgTpW6M03p3hteIY/0MO6asD6Bw/e6sWr6A5Oup+YyKlaZK+dKI3ntz7vId1HUqYm9fnpggfx4/PMndJyrkqWDPoYPzqZYv99f1CkAr34smN7IJQJsbqud+TgFoc98DaVUgAK20lPx94ghAK1+vcgC0JmzoFY613TziCzdkw6Z1mB9qxLAPU1nW+AlODkvTAW0kF5YMpd+Sd8y56U4Py0jOzneg66x9qJqO47T3QsoHX8C+bk82P4ugXs9FuEw3Y1KLUVTa/JoptdJEeO1KFet+3C7WGFc3N+xrWODvMZ269WfxslgvPD1WU0UtlKldCvPPuSQ0+mzjxeauRJ1YjoODE9c/VGaTzy0crIAHblg3HYF/Yh6m7rzN5CYmvHbthHW/fRRrbI+bmys1EtPymdiy2NWVUS1KsqO3Gn22iVBr5MS53bMol3CTofXqsu15EaZd8GRmPTP5OpZFNgFoc90CmRcgAK3MJVbIBALQKqQtP1WUALQ/JdtvfZIAtPK1L2dA69yURWUqstzXnO6DmvNi33V6nb9JtZtTsM8AtJK3xcL5GKtL3nwxhPsHcWH7SPrPOgIGHdl5ey9NTIDH26naoie3ksyxzVeUemNXsrB3uS8KfA9o64/BZ+8cLNTCWDa4LuO3v6S7qw/b7a14d9UNe3sHzj7/SaBNB9Ae06tQf9Zt6o9xZe8ce7RjXjOlkzVLLwhAK9+h+v+dTQDa/0//BaD9c3wXgPbP8TK7PRGANrtKSaddDoF2NG+3tqH1sJMk6OsTVXwcb66P5q1bFkAb+Z4jO1bj/ugDBfKXIspnN0v/u45a3nRAC1xf3SI1nkVnDtxYTwPz1JfNUg4BaLPlsjBDmy2ZfutGAtD+1vb9dPEC0P60dAp3ogC0CmeJzAsSgFbmEmdIkGOg1Qo9Tb+6rTjwFuxWPeLYMJuUXRAyzNBGv2LdhL+ZtfkIpcefYKNDeXwPjabduP8Q6acH2vfsHWNLz33KJLwNxqLdPG4cGMHnXW4FoM3WaBCANlsy/daNBKD9re376eIFoP1p6RTuRAFoFc4SmRckAK3MJc4p0MZw2XUys06b4LZ2LPmUQlg1sgmTblXhzJkV1DZRzQy0767iYG+P29nnjDkVy8L6URyb0w+HRUdQSpuhbWQUw7HxZfk7eDYnJ+djSn97dlx+T+tVj9g7uDRqysCrDVQoPID76dfQnptCrUZz8cliyUGXjd7s6meTbslBedZ73+MvG+DRFoo2HoZvgh7jXS8xoUk+Lkwpjd2yt1/W0MZnzvdpyUHdUZvYN9cBndhPSw6smex+mTkNhTW08h2y/5/ZBKD9//RdANo/x3cBaP8cL7PbEwFos6uUdNr9cIY2IfApq6c5MvOSAc4bXOheNR/P73hwIcyA7vUqoZnszc7pY5mw6Cjvqc38K1sZXDyB1eOGMXuzO9p2A5lTowQPPP9js/stVHSrM3XFFAq93sKQhXdx+O8kM5qocnCiA0PXnCVZryaz3DbQv7Y5b9cPouz4nWBejnELnJnZpjBnJ3Wi9ZpLULoVR3a40ED1NWMdO7H2UgA2nVZwZtUgAi7OZ/CoGTx4D90WPsRlZBn04x4wq2sXpp96RZFyzWnfvCxJnv+x9NobzMs1Y8GC5ZS5N5NKk1LzzVjuzMQ6prgMb8LIva8wrT2Qvev+wUp0nkHdW3P0MdQecoT9i1uRT1s6ZvxsFGGG9meV+33OE4D29/FKmpUKQCtNNXM3lgC0uat/bmQXgFa+qv8QaOM+POPkWXfehUH+qu3pXO3LZ28lpSbEPMPjgDvPw1IL1y7ckDbNS8Kz2xy+eBO/ALApWZ6axcDz5n2i4sBAWw8IIywGdAs3pF0dQ564u3PfN4wkVDCxrEqjGlZ4HT/M7aiYlLgGxWrSvlJeLu88zPM0jYo1ak8t/DjgfpPU9Plp0Ko18X4nuXIv9XO92rqVadOlOsZaEPn0JG5nvYmO1qZE5RrUMnnF7os+klYUK1Yejbf3eRiXms+iQk2aF9DgyNHzBKZWQNVG7SnAZQ64f66Adn2aYCHpTi4eAtDmovhySi0ArZyEVrA0AtAqmCG/UI4AtL8g3m96qgC08jXuh0D7q+UkJoKa2q9Gkd75YjEkJYGqqvRi5nYkRQLa5ARf/J8FEPlZFBFhvt5gWYnK5UqReSgkER/qg78vWJSwRk1dul+qCHxwkxC00bO0xsxQG8lKlm8fH3j24G3KP+vpW2NWIC/K0i3np4eKogLtN/0uUInK5SV+f/I3lLjPvY/m3T1v8rfpRFmDdC+B/rQ6X07Mmd+fzoshytcH/9A8FC1nKYUqpBdCNkAbQ5SfD/4hMSmfM089Qnnh/oKSo4ZQREnpqw7E4O8XRt78JlK/PiWJ4kOD8PfzIU5siklZSwy/Tv9NOT8Q+PAdSQY2mFkafGkV+pTdR+9QqVU7ihhm3Cc89LozRwKr0aVVZTS/zuO1mblnTRk+pCl5Mmnw655KG2hDgx4QEmSCTfH8KKXVm5zgh7+XP5HiT/WKCPN7BRYVqVS+FOq/3o20CGG88orBupjZ59zfD/2d9qFP2XP0NhVS/NIlvS0Sv44GVqVTq8pofe2J12bmnzVh6OBm5FHOetDE+9/lTZIVRfHhdkhxKpfV4XOY4AfcCjKhcv54XvqJKVC8EFoSgeKCeeEXSoGCVih7neeNQWOKWiplqCu7MuY20Ab63yNJVAizAoZk7IDEDx8S4kVoGBpjVsAaTamP+UBeeYmxLvZlfH6tW6K/H6+C/JFwWcbDAMPi1uTXUE0t28+dRftC6De0I8aqyl+6khDJbfc9hJs1pG55K2QOtNk1Xmj38wooEtBGBuxlZe8pvNLS5ss9xoqmI2fQrmG5L0ArTiQm4jlHVs/mxnMRJer0oGn3lhTS1viuEMnJySgrfx9LJQGSEu6xffZwQq1HUNMiipN7TmDtsIiutaz4+llGHOjF/i0TOHFFm2YDBmISe5ITO/chbuDC7IENUtdz5/KhqEAbJfG7z1S8NbUy+N1kxAzaNSqHOnG8OPUP65fvJERdLd09tQr26xZRyyQdiGShcU783jFnBMFWw6hpEcOpPcextl9I19rWmfz+nCY5nuB319n17z/4R5pSpGEXWnZsRN5sA5XsB4VsgDYAz0Xj+M/jAcmq6Qd3C/4+MIfiny7c5ESiQn258t8E9t4wZ+SK2ZQ2/vHPUeK0v06fIOt7KoW+28oWl5MUq90XrXdH2Xs6hr7//EtlC81vPHyKEcUFcu/MZrbtOIRl0Q5UbNeGGhWLokUi9655YFLElKsHblKqZTPyRVwgIm8XlIMfEG9cEMOAo5y5W5Bm9UX4iapRzlqf0A9v+BAropDqHZw3iek9uDhhERoUKlQSDSlOfEgPaMWIPpxjxQgnXhUbz9yZXTBI8ywqYB+r+k7lpYZmuuuxEI2Hz6Bd4/J87+6anWtNLIon9N01jq6cxdnIlixyHoWpyrdvkBnb27HIeXS69ml+FTXl2oFblGzRhLxRHkQad0Y5+CFxxpYYfjiO+50CNKmfxDtRVcpZGRAa+IYAiV9qd1m7MZmeg4sTLvGrYAk01DJevKGXF3BRcwB1knZzWtSOzjXMPuuSfHcxqwN70K/YC668Tsa2RgPyaCoh/niHI7eDqV27PmFnRvOu/Apq26j8ZkCbTOLr7cwYshzjrksY2LseOpIxIhYT+fI0G//dhnbVHtjaKHPr2H+8z9eJgf1bkl/v+zM4Px4jYpISYgl6sY8tM5bwusQEZs/oitE3xkjgqTE4rTiLmqrq5weNZFE8CfmaMmHRTIrkgRfezzHLG8V/Lj50HNUEceALNE1rEfjsIlpFSxN8/RSROhWoYPpYAFrZ/0mSfQZFA9pdSzypOmwqhfJ86rsm2jp6qH++m8bx8fYuVrucpnK3GTRqVJRsLUOO8+XauRsUrtuRfLrf0TUpivs7nXB9UZNZM3qThzi8D81gkctr7HfspMZXDJUQcJtD/x3Gov1oatpI/jGMW2vH4bLHi04bPGgu+TBHLh+KDLQSvysPm4pVln6nAq2HtwUtOrZE5/MUvR55DDT57rNJnB/Xzl3Ppt/jcH1RnZnTe6OvFI/34Zksdn5Fn+07qZnllF8kvidX4rz/LXaDp1GtooUUZ6+kN1hkCbTPy46lo615uj/URhgYpf1BSwjC98Ylbjw4g/87L+68KcPY7ACtWESg9y0+JuSlePEiqH7v72OcH3undSC45jrs21ZAQymE05NbcUW9L47jHTHPNIUKopiXnFm7DB+VmrT/qzNm2unnHF9wbZMzj8T5CP4YQmFLFfzeWdO0Qwt0/Y9w8mEcunofePce9DUNsCzXneb1CxDqfZQz7o9RyhPN/UciSlrroG7YjNYtq6GlKb2faKQFtEkxvpzftgKP00cJKTWTuTMyAu2ufzyoPGQKVvqf4O7r+28W4zMxiNvnzpGvaicKGn0DUOP88PI4xyOfizy//YDHSl1Z8j2gzdS+C0syAK3ELxceifOm+GVTQIV3761p0qEFep/9CuDde6UUvwqU7UaLBhK/jnHW/TF88stKB3WjZrRqWQ3tz35F4vv4GfdOLSas5Ajyvz7MG4u6NKvTkkKG8Xx8+5KHB2fxwGIElXnAi6hkqjXpT/G8YTw5c5DrAUmUL1OJV8eWo9N2DvVLF02B3ZweuTVDmxh6jz3LFnPvyVNM2yxlYK9UoJWMnRPLxvDcwp4BPezQU1ciyvs06xYvQqeTMwMaFU33IPRVb+P8uHHhBla12pFfL+sxIgp7zv3zp/EJusWtozeILDf1u0D7fM8ITie3p02dMuTRBJLj8PLczI2IovTp2hGtpDtc2HWYD2qqPHseTaWS6oTFVqF563KEX3LjQqAhyuIAJI8b0eHGAtDmdIAqYnvFA9rr1B2/mGL5slYr2v8yuxasIbHtRAY2LJN9SQP2MHvIKuou8aSeZOeKbxyJH26yeaETobXW4tSxeEqrhCdbGTtpAWYOR5nU1jrjmaIYoiLi0NY3QDntSfLtyXHMW3mFNv9ewu47ubJf/K+1VGygvU6db/r9CWiL07V/J/S+PwGfUaSAvcweupK6izyoV/jbf0wSA2+xZaETITWd+btjiRRAk/j99+SFmPY9zMR2NplmV0KeuLJm8imKzVlOl9Kmv2aODM+WLdDOpX9zyy8/wabvR7w/L+/5YVS2LMEXl+KyLZB+y7MxQ5sUxb09U/EIqUW/fp3Qk/yR+sYRdWsek+edwG72aZqV1kpp5XugPzNPqjJw3CKqFs68HOXp/r/Yf704XcYNoahx5s+OBz07w6WjG7jxOAAjKyuKN5xO48o2EOPNozP/4n7pLlHoUaSOPc0btMHURI3EqI+8uOiK+9nTvAmGYjVbUqdhP4rb6H//gSuHvksFaJPjee25jTNeyeT33sQZzVHMyQS016nttIDi+XPw01LYZVYMGkl+p2t0q/RltixDF2Nf8fxhBGblTLm3ajyuL8oz73tAm6l9OeZlAFoIfnaWS8fWc/3RBwwLFaREw+k0qlwYpVhvHp9djfvFO0SgR9HafWnesC0m+dUQRX/k5SW3FL9eB4kpmuZXCWv9dEvEwnh58wInNx3FvFtTQj3vo1WxMlVs21M0XywBz69zdNlWtLq1Q+fFQ4LF+anSvAel8gVy8b89eCdrUaq4Ohd3eFPFsRdVSpTFUOs3AdqEj9za4cw1zcqYXJ6BX5XFOKYBbfTH0zgPX0WhgfNoW78s6pIuRTxl55IJeOo7snK0HarfWL7Bh/3MG76SmnPOUq9o1mMkMfQpfv7qmBUVcaS/Ax6FhjPrOzO0ka/vE2lYDvO0h6/EyOccX78WnXojaVCpIEpJ8fjd3sOFk3t48DKMguUrUamhE9VKm5MQdI+bx1Zy8fYrlPLko3C9sQLQ5vCepJDNfyugTYrh0eE5uJxTZcLsiRQwSP1Dlq0jm0Ab+vQgLguWYTViN90rSz5JBwRdYNHg0fg1dWblgOo/SBfE1eVOrH9QhFnrJlNAij87ZqufWTQSgPbbf0wkfq9duJxCw3bRvcoXvxcPGYNv49WsGFAjI7TFvuXkinHsjLDDZW6fzGspf9YkGZyXa0D7uS+SBxLZAO3zzc1YfMyCIas3UjFfqr+htxczfcUDOoxbRP0yX22JGHSK+YOnoNdzPYPaVchiKckDdsxZj3HdRoS8jaZGdQtenjhOUt2/0Pfez2PVstTL/5bbfoUopfqQi7RkUNuivL63G89HCdQvI2LfZVPaVQrlypt8tG7bHH1txZqhjQu7z+H1myjYchCxuwewL3m4/ID285gI4OLibABtpvZfA+0Dds7dgGGdhoS9jcLW1oJXJ08iqtMf/VcHeKxShnomEr8KUkr1EZfELXFsW5S39/fg8SieeqVFHLhqQtsKYSl+tWrbDAOdtJt1RBjefp5cm3sSq2FN8bn4COManahWuzhG8XEE+N7EY+Y28o/qQcL9y4TnqUntNnXIF+LLjVMHCE4yxMYqnNPuSTQc6EDJQkZ859nsm1e+/Gdokwi8v4uDF4Jo0aslN2Z1523lRZ+BNurDflYM3UaZMfNpWaM4qpLLLtkfjyUT2PKmEgtWDievSro1qul7lg2g/dLciz19fgy0XwsXcnE+a9zV6TlqJNYGqkSHnefgf1cpXrkQF2+q072ZLjcu+WDTuC5v9m0gvIwdBRL9UNErgNqzUwLQyuBvkNxDKhLQRgUeYevU9YSZW6EUEwnJYkq0GkaDmhXRV1MhKTqQo/904k5yF+xMXuJ65grJSXHoWbej76RxlMufcS1BQvQjLuzaik+QRNZXXDr7jFLl7TCSzP5a1KFDz1Z8PREc8ngfLgv+pejYXXSukD/Vj9CLLHMcycuSE5k3qzPffBVJLCbixQk2rNpOkYHLaVMmr9z9zCqhwgJt4BG2TVtPqFl6v4fSoGalFL8hHm/3fzly9ilxkpcORAmo6ppStaMj1UvaoPHVbECq39vwCZK8JZCF3z1akcY+n2VK8XvhaoqM2UmXz35fYvnAkbwoIVlj2BmDdC88xLw+h1HmztMAACAASURBVMtCJ6jwD1WjNrD9iheihBjyVnRi8OTeFNSQHsT86uCRDdAGcmXFVDzjjCAkAJIS0bSoRMPu9pQxNfpq7Wp2gDaKNzf2cuHSM+JEiXx4d4vgj6YUL2OFiqYWlrU608C2NF8/uj7dUI+lp0syzMWZ8kapQBt2fzkzZ3pQ32kRrWoUJb0TH44NZOLaB7RoPwa/2xvweh+MGFVq9FlNx9aV0FNJe+gJfoDbrqtU69qTUsYZ7yfBnovY5V8H+y410P76GenhasYdsWDSxLYZxsuvevjp/F+eoU2O567bIK7oOtKvczFuzGrHnqRhGYA2OvAo26avJ8S00Of7b/GWQ1KuRwP1r5/M33Ntxyoe+CUjFgdw3eMGBaxaY1FQCfKWpnGXzhTWy2rCQVpAm6ZM8EM2775Clc49KJVXL8OvKcGei9ntX4s+XWqg8/VLSw/XMP6oGRPGt8Pw61nF8FBeXNvEvosi6jQx5sqLj1Qv2YmSNYtgHBfL+7sH2XH4BZXbVePDy3OIjTpTr1FF8n7w5uzJXYQZlKK0ljsb3zViWPOGWFoZZxq/2RkX8gZaUaQfxzevQNV2IE2ranFoZPsMQBsXeoetTsOJqjmBvl2boqcGSRHPOLJyJkc/1mHRvyPIr/JlvXBC9GM8dm/D52MyYl5xxf0Zxcu2wDi/EpjXpl2PluRXzgqAfwJok+NxX9qM1+VdcGhcHOX0fr8+xuQtQQyf1BuTDC+FhXP1yGZCLO1oVrWIALTZGZSK3kaRgDY5MY73b7xAxwJdDXh3ZjWbjlygfM/FdGtWBaL82DWtMTfUOzNwuCNlLM2J+niJ7Qtn8Ux7IDNmdeHzUkzJT8exr7l27AAfJNsmxF3h7MEXFKrZl6IFAePSNGvTNEN7iVe/ArQJH+9w1HUFkSUd6dq8FpoKskOHogJtZr/XsOnIecr3XETXZlXRUIaEiADeBkZhYGCAcmIUd/fNZ+/1ELpMXUuDYkYZLq8Uv48f5EOEGOKu4n7wOQXT+926SaY30HMKtKntZxBadhgjB3SmgIE2Qa/2ssppISqNXBg7uBY6Of91USa3CdkALcQEevEqQo8CRuokfPTm7H+zOeljidPKNZTNsOY4O0Abx9v7p7l735sEURzvn53gRUBxqtcqhYaWOublG1G1fIlMa5RzCrRPN9Rn/kElGgyZQadGtuhpxPDw1Cw2bQ2m7biF1ClnngrA8XEEB0ahZGqIUcpD1ZdDFBTExyQNjE30Mq+ZDgvBNwyMrYyyt6Y/h47/GtAmEHh5Cat3q9BvzjgK6YXgMTMVaKeNqUliNOQ3tURFHMf715L7rzm6Gkq8c3fG9fB5ynabT7fmtmR8Vgvl1pEtvA5KRpzwjMtHPdAoMYAqJZUhT0FqtbDDXEcOQJsQT/CHyBS/DNUyvnwlCk71yyi/XuYX2sJD8Q0TY1TIiMyLT4A3W1hxuTxD6sdz6lEEtWo1wFAnbTwEurPypDpDOpXi4dVDqBbrTllLLRBFcv/qcZLzNaRUmAubYwfzV/28315X+oMxIF+gjcXr0Ezc31Sii2Nn8mr6s29kuxSg7dXYgGjVohQyhLfnXNh34Q36JUpgZWSKKPgmHuc9CSwzAZexrTIsOUiIfcONEwcJCE9GHHeNc4efU8C2F8UKKoNxKZq0boJBli9C5BxoI+4tZOmaGHoumUaRPF+9hBcdxfvAOHStjDPe/5OTiQ4MIVpbF+M8mgLQ5vCepJDNFQlovxYoOeYjJ1Z046JqHyYO641W4nt2TWtPuO0i+ndpgFbK/SU05SUs5z2xOO7fhm16ok0fMJtLDlKBdhYmA07Sv27az5ZpM7Svai3in1GNs34BKOIO+1YsI7JoD9q3a4y+otAsoKhAm5XfJ1d0x1O1NxOG9cZAK/M6vvi3HrgsHEdUnQ1M6lb2228PZ3MNbSqgzsKk/wn61Ut7ySk0dYbWu8YCloxqgkY6QM0SgPHjxKjOHPCvy5hNCyihIEQrK6D92reou85MnLmSMqMu41jPKN0SjewAbbpoOVhDKwHaJScN+Gv5QWoUSDdDu+AaLcYtoknFghnGhgRol54ukWFGNyboHC6O09DtuYDe7WuTxXBTmHv2LwFt0DVWTBrGfXEFapY0RUkpnve3TvJKXIZyhXUxKNeezu3s0P3qAVxy/z25sgeeKj0ZP7Q3ht9aQpGdNbSflZTyDK2sHAp+wMNoG0oaRhAQISa/qQWfd4WM8OFhiD6lLbQIDniFet5S6EvWyCZJ4PoNYj1rdMOu806rFjZ5f27LLkm35Aq0foeZ+vdkos3qUsrSECWlGF5dPklU3uoU1I7GvMsSutpaopwUS4jvK974B6CjX5C8Wn7sWDmNyFouOHUszTc3rZDlkoMYb/bP6MNb240Mal8czW+t4/3BWBG27ZLVxSTHuIoMtMSH4rFxKAdD6jF9dH+0kwKyANpkXh9zYv7qOIYdXk3Zb61ZzSbQxvi447zACY32hxnWvECqE68PMnbsNEz6HmZcm6y2LXjF8ZFDeGo7C8cOldGT4tvN0hgKvwvQSvz23DiUAyH1mDa6P4af1rSlF+HjHVwWjeNtyTnM7Vf9l4FW4rdkCYF620MMbWGZGu/1If4eO438fQ7i1MY6wxrarIE2iYcuDVnt0ZTx2yZh/enna2mY9wsx5AW0vNrHKKeZFOp3jFF26V8Ukx3QBhz5i8luz+m9yIP6aS/9BbmPY9qeCPqPW0Rlm4xPtlkBbUL4a3ZO7Ye42QK62VXL8ODyC7LL5NRfAtrESAIDgxAlJafVFsbN1UM5mdyLkcNaYmJogr5e+q0S05rFh+G5aRgHgmozdXR/jL4m3k89/ROBViYu5iyoXIE2PoT3gWEpW3OlHoGcnjcM/9JOdGlTg3wmFuTR/PqPaxIBd/5jnetlmjnNp1pBo2/fj2UItP4X57J4TwJD503DRvfntkiT9FgA2pyNT4VsrUhA+8rTFW/lJjSsVQAJE4ii/Di8uC/PC4xgWN+26BLO5c0jcY9txkjHbuhL9v1LCuX2Zic2Pq7CnH8GYZxOZbFYREJcLJ/v4+kdUFZHU0sj836VsT4c/ceJPQltWT+jN+rKyQRdXsG0ZXfo5byVmvmSSXj3Br8wfQqWNkJVLML7yDj+cTdn4ryBafmT+XhiBVf1BtCt2Vcvp+TCKFBUoH3l6cZL5cY0+uz3Ow4v7vPZby1xJLfOn0W7cH3KFDVECTFR3mdwWTyTPJ12M6CxRYYb6M/5/ZpjS53YHd+addP7oKGSTNCVlUxfepseazZjqx7Eh3eJGBUzQ0uyqXDwAzYtGUe47UpGtCuW8jO1ONGP0zM6c0pnIjMmtpbJxvo/M2xkAbSxH704d9kP2wZ1yKsv2fYqTa8lW2g06xbtSytnmKF9fmIJLtuD6P/NXQ7EJCXGkZAgItP+6Cihoq6JulraBukZHmyOMmvgTIzs1zO4dQVUlBK559yNg8HNcBwzAHNtEZGPnxFlUBQTyb60j9cwZOYOOsw4Q6NSminjJuq9OxsXuFCk90KaV7XJsOb2Z/SW5Tm/BLSZCgv+vOQg/S4Hrzw3463ckIa1LNPuv+84ssQeL/MhDO3b/qtdRpJIjIsh8cvXNb5kUVZFQ1MTlaw22xf747F4PJtfVvhql4NEIp94EalfGFMLrS/35c/tJbsipN+HVvpqx4Y/IjTSGhNznW/PNEo/7TcjyhVoM1Xx/vOSg0+7HGRskkRs8GtOuIzA23QAA3u2zbQ1meR+nBgXi+jTc1R2/v5K2iQ/ZZd9fy5+tcuBODGa4BcBKJtZYmionnINi6Oec3DJVJ4WGc34Hrao/OTsrAC0chzYskylSED7bNdg3K6rUrtNd4rpwTu/s9y7FEutgSOpUsQUZZIIeXmWvbsvkK98I4rYGBH9xoNrV+5SrP0y7Cqmx1mIj3rI6c3r8AnOQkGLenTv3ynTS2GSlkH3XVm/5gQmLfpS1SSep6fceVuqF393qQEE4LHQCbeTxjidX06RwJvsWDiO+/55MTb7tK9UGKGPnlNloRfdKuT+gkpFBdpnu4aw+YYKtVqn+v3e7yx3L8VQy3EkVYqaIY4N4cza0dyKL0ntek0xVwnF685xngfb0GV4Pyy/eukkxe8t69NeCvvKc4nf/Tpleiksxe8HrqxffQKT5n2oaprAs1PuvC7Zk7+7VOLl6X9wXvCINttXU99MsmY3jreX3Nh66gNVGzfGzEiJkGeH8bgRSJOhG6lhlft+f+q5TID23Q02r1xEXIl2VC9XBt2EVzw4fZz3+VvjOKjNZ5gP977Fm48hPD67gbN3xTTr05lSBa3IX7A8+Y3T778Whffl/3D3eEyc6CukVdHCql4PmtSukOVLNY939+fgvbzYNm2KifgR53c+o8jgKdhVsJAstGF1I0fCm0xh4PhOGCuFcmXDFG7GVMK2dgV0SN2+6Z16Mzr2cMAsj+L4ltX9XnpAKyLG/y77FgzlUlILRk4cQnELkxSYf7Z7KJuvK1GzdXeK6yrx/r079y7GUGPACKoWM/vq4f89nq4Lue8reeHnq8O4DHa9e1EkT8bVqUFPL+Mb+JaLu9dzM6QYPQe0opCJDRaFipJH9w6rGzsS1mgyg8Z3xlhZiU/tL+1ez41M7aX/goLnvDKciXPEcdwwLHVzsG2ZjP5A5x7QxhPxygPXWU6ElRqCw4DuFDDMk+a/iPA393nu8xhf7wd8VKpD645NMdfPvF46PuoRZ7duwPtjFk895nXo2q9ThpfCkhPj8fe6xft3dzjqsoH3Jnb06F4Pc7NS2FgXID7kECt6rcFy1Fy62lVFQymZkEcHWbvuGk0mTqKymWTS4+cPYYb257VTmDMVCWjD3z3ksdcjYmO00UGLWJVILMvUwsrSNN02O4mE+D7m0aOPiHQSESvHYWJagRLWVqh+tYBHlBDEq4d3iYjNQm5dc8pUKP2N7VQkL6fc4OmLd6grKaFlVIyiVcqjn7KIKgb/e9fx8tWgfOuaaIf68OTeNUKiMuewqtmdwhkZO1d8V1Sglfj9xOsRMRn8romVpVmK3+KkRAJ8bvHy1WsSEvTRQZlEHSUKl6+OmZF+ppvXj/wuXSHz2/KphnzLbwj3fcCTeyEUalQb889foktr7x2Hkl4cYmUlrK1rYGOhGLtayBJoRXERvH5xDd+3wYjFhmiQiLKRMaWqVEVf/QtkhD67xMvAKCLCQz+PecN8FpjZVMMsf/pNjFKv5ze+HzP/kqKsioFlic/j4euLR5QQjNftq3wIjkJXLEajSENKljRJW+MeyOOjniQUqETJCjYp13lq+zt8iE4GzTBU1EwpU9I25YUQRT+kB7SJRPk94d5DLxJRoUCZmlinXW/h79Oux2httNEiTiUyw79n1Cia1/evEhQlJhPRahpRpGxZDDQyfiz3w/2zvAqOJSY69WYp+WqjoVkxrIqWwUAvlMfHPEkwT/NLCb7fXgZAu6gSV7Sn4OjYHqOUTVZz98g9oI0j1Osmd1/4oaptRJEKtpgaGaQBbSIhL2/w+Plb9ApVo3ARG/TSv2SQTjLJ9ebz6C7hsVmMEV0zSpUvjXa6WfzkhDh8H13ibVAECfHxKZHU1DUwtChP8eLWKIne8OjcE3TKVqVwwfyokES430Oe+iZTrlI5tH/x03wKA7TBXgeY4jCbc8HRGJVryoIF86lX+Hufg/r+QA32uszGJRvYeO0xTYcsY/7gWqSP5nXZmSWj1+AZnoBVzfYsWLCAimlbWP7sJfBu33AazriAVbOOOA0eTP3CJt/+7ObPJsniPEUC2s/lJSWRJFZGJWWju28fIpEIZVXVb3zmUgoiicWkfK5PRXG2YvqZXikq0ObIb5GIJFRRkeW+vjn1WyxGlJyMSrqtan7GH1mdI4sZ2gy1ikQkK6mm25BeVj35ftzkpKTUT1pn83vykvbJysqoZrN97vQqY1bpAW02epPN+282Iv0+TYJPsWLsbqrNXIFtIV3Z/U3JgSK5B7Q5KPIPaqowQCvR1G9LNyz77iJ/tQ64urpiV+pbr7t/xwFxMq/Or8V+wBBuhQzE/eEUahRIezHoq9MuTitG3dkvKNbYHjc3V2pIfuX6xSP09i769HPgeGRzDpxZTxs5TO8pJND+oo7C6RkVUHigFQyTiQIyB1qZVC0EzUoBuQLt/6EFIU/uEJy3IkXyKWX3uUjmKglAK3OJMyRQKKDlwiSUGsz/JaBNDPfmH8fWTNwdwpjjt/mnxbcp9bVrJ6z77ZMq0JIUjefG8diPXA0t1nN1/1/84sTvD0eEALQ/lOi3byAA7W9v4U91QADan5JNIU8SgFYhbZFpUQLQylTeTMGzB7Rxcfg9ucJljzu8TkgCbWPq2LXEtrAZUa+O47LnYWrgsp0ZWTqIQyfP8zrMgLKde2Jn8+WH/uBgL64fOcjDD5LGBpiYaCP5JVjbojA1a9bE7FpWQJtEXOhLrhy/yB2/YFDXolKzDtQsVSDLtZOhvvvoVaYTxzXbceSOK60sDNJ1OphXN46w53xKAUR6bWSu69cztN/Pl5SUwMuH57h48T7BMaCiYo5JGrGa1G1P00La+FxYi4PDEDxeN2RPkDudZLwGUwBa+V40uZFNANrcUD33cwpAm/seSKsCAWilpeTvE0cAWvl69UOgjQu7wbIhPXDxqcekKT3J6+1Cr0kn0a/Yl0P751NBLZC5k/uxeNN1ynRzwOrSG15oeOPl/Q6dfA1Ze/UQHS0g+LIzrYYt4WN4SSYuc+CD6zL+Pf8INduujGhdgxZ97Sl1JzPQRn28ztQunfhPvQMuozvg59qSOZerMHLlMsZ2qJgJagMuz6FB7ak8qz2CFwfmUySvdpqiwewb3orRh99RrN10nBrCqmF/c8wvLMMM7Y/y3V/Rjk4Ln1K34xD6dRKxrsVsTpla0drWlsp/z2NUZWPCHh3BwcGBg7eimHYpjpm1ZGuqALSy1VcRogtAqwguyL8GAWjlr7msMgpAKytlFTeuALTy9eaHQBsVeJUJbQdCr+UsGNgQcdAlhtavw1avOmx4uZ/+BdU5vmwwDuO3E6jtwJXoTZR9djIF6PZeC8DpjIhFjd6z0d6BUVvcMei6hbs7e5N0Zi6Vu80mVqsVO2/vpYlkljPTkgMdTo2vSPMlifzt5sqs3tUJvzSb+nWmEd9pDp4bnLBM2Ufxy/HarQfWDjug/hh89s7ByliyFYUYv2MzsO29gHid9uy6u5NGeeHStGLUybCGNun7+dZWYqyxHXtMq7PY1ZVRzUtweXoV6s/ypcdCV5xH25FHDSKeHE/p//4bgXTc5MNeh6w28pee0QLQSk9LRY0kAK2iOiPbugSgla2+8owuAK081VaMXALQyteHHwItSUnEBkVDHnWSI0J553OdqSPbs/tGEaZd8GRmTZ0vQNvdFfF2e3h3FQd7e9zOPk8Fum6JLHNwYPKuy+QbegSvf1sRnga08Trd2f/IlTqS978yAa0vY2zKsCy4MAPGjqWdrQ1RH/Yzo+86nhbpwQVPZ+qZZXxxLGugDeHQBHvslx5Bs+w8PG9PpKjkY0KZ1tA+/n6+/Q2ZWe4vzlvVw9nNDcd6VlxMAdoP9F/hyvKhjdFVEYBWvkP4/yObALT/Hz5/3UsBaP8c3wWg/XO8zG5PBKDNrlLSaZcNoE3A+9pBXPcdJjG+CIUrqLF30RTOvMwB0Drk47bzeOyc1kLhwezf9zdhblPos2Q72m03c39XTyTbnWcCWpPTNMrbmXN61vTr50DNsuYkJX0gKAjQr0ifvo0p8NWn/LIG2ne4Odgzwu0sulXm43FzQtZAq7n3B/lKc6xHXQadUWHYnJWM62GNa8t6TH9flKVurgxvXjxlmy5hhlY6g1OI8kUBAWj/P0eDALR/ju8C0P45Xma3JwLQZlcp6bT7IdB+vL6Mdm1m8bGWI7vmjcBcJ4L5PUqx4lJOgNaKpNiXLO9Ul6nni9CgsSGisGD0O45mcW87ChmlfaHi6xnaYjforNaEvfmrsXDDBoY3L5FuX1cVVFXTf6IxVZAfAa221URO+8yjXFYztCZnf5gv6Pk+/mo2hFcGlShspUpUWCzNJi9jUJ2S6KV9J1kAWukMTiGKALT/72NAANo/ZwQIQPvneJndnghAm12lpNPuh0D7CRBrDHNh/9x+KL07ziC7dhx8/QVojy5xxH7SLoLTlhwk+17GwcGeLe4vU5cc9LXgxjoHWv39gGmeHvS0/lS8KtraWmh8+jpEpiUHESyqX5zxHlq0m7iS5WPbkV8bYl548VhdhyrFi2b4SoUk6pttfSjSeyuiDGtoo7iweACdpu0iTs+SBQcf0rdMEuenlKftKt90L4X5fT9fYXM2dTbGVTSW1audKJ622kFFRRMdHQ1U0r5ylR5ou27xZWfvrPfBlY6FIKyhlZaSihtHmKFVXG9kWZkAtLJUV76xBaCVr96KkE0AWvm68EOgDTi7lEa9ZvDEsAwTu/fBJOgBW45u446PNu0mbmBFb0vWj+nGnJPPoPoA7uxfiN7D7TgMnsSlVxHUGObM1km1ODx6cMoa2kIlGmBm9qmTJlSvU5eWfbpRyygOj1XDqT99H3lsqjBlmTMjWlYi/OK/tB+7nDtPYqjQvAPVrdTw9vOlVOv+TOnWHN2UT5l+OT7cWkzTquN4UG0wj44upnS+1G9RRzw6zMABY9h5+x02dTrRvrIVqtf+Y+FFH0xLN2beMjd6NbQg9OLKb+drHEkbi+7czmNKiRIl0UkJrYKxcUlqd+xC//Y10NVQIfj+fhzsHThyT435N4OYUEW2pgpAK1t9FSG6ALSK4IL8axCAVv6ayyqjALSyUlZx4wpAK19vfgi0SfGx3D53jCteEejq5qV8zRpofvTgpncEUJiGdcx5evEi/ml1l2/eHpPgB1y86U2s5Du+WjpUb14bv7XT6TxzM3lta2Ga0jaU69efEJekRdOhq3F1asgzjwu8jk39/q9Zmao0rFwaNZLwfnyFW4/v4ucXh3F+C/KVrk6d8kUxyOJT0GHvjuJQqTUH4+zY+2gbHS0NPysacPscR+++JipKi+IVq1At3xsOXXsLaFG4TB1qVi6AConfyfeIudVbsfBNPCWKF0eyIVhc3GuuX38Dpg3Zemo3vcoZ8PLsauwdRnLZryWHI4/S+ue/4Jut0SAAbbZk+q0bCUD7W9v308ULQPvT0inciQLQKpwlMi9IAFqZS5whwQ+B9lPrpCTIwae2MySJenmOUYMdcdMZhO8Ge1I5VETU2dlYd99ItQ5TcXWdzPe/dJuESJSMqmoWFJsuW0L4Wxb1r8vUfVrMunSeqbVS8fnTIRZDcrLkgwg/Ejpzvnd7Hak47BgNJmxmZa8KSEIkxwSwedZfjNsYnLrrQz0Drm+djr3DYp7ZrSH28OAsPwDxo+w5+XcBaHOi1u/ZVgDa39O3X61aANpfVVBxzheAVnG8kFclAtDKS+nUPNkG2l8pK+DOLgYNsOeI5Rx8VvVCU1sZ4uN5ud2Rxoue03OaK8uG1UE6E5kiXpxfz7BBEzir2Q/Po2MoZpgPY11NlH+lE8C1RVVovOANLSbvYEWv8mioJhMT8Ja1M3rh4teIg9snkS/8MstG9GXXs5asu72BzulmiH8x/TdPF4BWVsoqTlwBaBXHC3lWIgCtPNWWbS4BaGWrryJGF4BWvq7IBWglywsuHdnAtkOPEamWoFR1PXj2jCcBkZRt1R+HTnXIuJvsr4oQx6NLh3HedppoNKjcazADapeRwkzpM1xmLODaaz3ylyhBMdNI/C48I9jUhi5//UUx/yuM33gUPVMbmnf5iyblzflqie+vdizL8wWglYmsChVUAFqFskNuxQhAKzepZZ5IAFqZS6xwCQSgla8lcgJa+Xbq/y2bALR/vuMC0P75HmfVQwFo/xzfBaD9c7zMbk8EoM2uUtJpJwCtdHTM1SgC0Oaq/HJJLgCtXGRWuCQC0CqcJT9dkAC0Py3db3uiALTytU4AWvnqLfVsgWFxOK68IvW4QkBBAUEBQQFBAUEBQQFBgd9FAQFofxenvlHnJ6AtlF8X4zwav3lvhPK/pcCbD1EER8ZTqYixINL/kQIJiUn4h8Qiub5R+j/q+B/Y1cdvwihVUB8lJcHIP9DeLLskuX4lvhfMr4NxHs3/l27nWj8FoM016aWT+BPQdqhViEqFjaQTVIiicArsv/yGO94hzO5TUeAahXNHdgWFRSWkfAlQcn0Lx++twNIDTxjVriTKAtD+3kbmoHrJ9SvxvW11SyoXFSYjciDdTzUVgPanZFOckwSgVRwvZFmJALSyVFdxYwtAq7je5LQyAWhzqtjv314AWvl6KACtfPWWejYBaKUuqUIGFIBWIW2ReVEC0MpcYrklEIBWblIrTCIBaOVrhQC08tVb6tkEoJW6pAoZUABahbRF5kUJQCtzieWWQABauUmtMIkEoJWvFQLQyldvqWcTgFbqkipkQAFoFdIWmRclAK3MJZZbAgFo5Sa1wiQSgFa+VghAK1+9pZ5NAFqpS6qQAQWgVUhbZF6UALQyl1huCQSglZvUCpNIAFr5WvFDoE2MeczVQ3d4GZuYUpmSpiYaJJGYmEhSEuhWqUuXckXkW3U2sgV77WNc+yFsehpIscb2uLm5UsMi44nvri+hX4spnA6Np0iPhXg6j8Ysj1o2oitOEwFoFccLWVYiAK0s1VXc2ALQKq43Oa1MANqcKvb7txeAVr4e/hBoE6Kes27MEKasdyecwrSd/xfViSTw2SXW775K3lGn8ZlXX75VZzPba9dOWPfb902glYS5vaQRVZzOCUCbTU2FZrmjgAC0uaN7bmcVgDa3HZBefgFopafl7xJJAFr5OvVDoIVYrrpNwd5hKc/pznnxdlLwNewuYwYO5m7hBZz/jYH2tVsPrB12CEAr33EnZMuhAgLQ5lCwP6S5ALR/iJGQsh+poPvKewAAIABJREFUsA/tn+NndnoiAG12VJJem58HWpKJDg8lLMqH87v38uhDalF6hhUZOLQeT/bs5rTXe0SqelRuOpDOdfOCnx/HDy7jiPsrAiSNbRqx6p9hFIh6wcqVKzl/0w+0DGnQawwVPmzH5fhT0KvOoEXjkZwuOUSiOG66b2L79jP4RQCqqhSw68KIzp0pqptRmPQztEuWjOPBivncCo2lZNUujBjRGVNdyAS02vHcdl/PnvOpHarYdhgtrWPZs3sPXu8jUNUzpOnAT/X48fDQQda4uaf0x6aRPaOHtaWA9Pz5YSRhycEPJfojGghA+0fYmONOCECbY8kU9gQBaBXWGpkVJgCtzKTNMnAOgbYT+z6sptzTM4xYeZ3x/86hnpk6N7fPxMFhAY8TSrP2xSMcJUtqH7hh3XQEWi1dubixCW83ONB89DHydt3MltGGrJ74N1uOPsTUbi03jjqi8WQbtg2H4hslpmqNjpgSwyOvs3j5RlGl3URcXWdQxiCWw8Or0nYd/LVkCX+3ycPxQW3YrNQB5/XrMq2R/QS0xqYFMDGxpZj1M255vsQvRJcOszawaXxbQrf3zDRD++HmKewd7Dn5OICOm3zY65AXj22OdBy6kwStQqw87UPvIi9Y1qkuE67q0W/lDgaKVtNx9BZi9Adz6OlyamiryMVJAWjlInOuJxGANtctyJUCBKDNFdllklQAWpnIqtBBBaCVrz05BNrK1HOsSP7n9/HwK8puT2fqmeUh9NlxRjrYs/3aRzpue8+unmaEnJ9P+cFHmHfoCr2Lx/Fk3xqWHojGYcVUahnHcWm5Pe0n7UIp3xCOPFuNbcQZOlXuxr5AMW3/3oLrvFYk7+1P3s6bsKrXA1dXN+pbX6aHUgN2mJRk5JylTOrbGG3f0xy4KqamXUsKG2Y9Q6tfqS2urq60L2fIvbXtqTfoIJpNxuGxcyaah/tlXnLw7ioO9va4nX2eBrRWfDgzl8rdZhOhZsbK08+xfTiOhkP+RanYHDxujqdoxCX6l2nPlnBVhq05x6KeJZHH62UC0Mr3gsmtbALQ5pbyuZtXANrc1V+a2QWglaaav0csAWjl61MOgbYVK69PpsTTM8ze8Z7ZrgtTgJbEAHZOcGDgqpPo1lrJtfM9uTvegRkRPbjo3BUdSZ/i4ohOVEdTIwDfO884sHca09dcRs2oIztv76UJaUAboYb9ytO42peDC5NQajCf/NU6pACpXalYNnSowYADPuhZlaBmtXb0HdIHu3ol0c9Ct6xeCvP3mE7d+rN4WaQHFzydKXRq0E8A7XW0N9jjuOYE4kJ1GNKnEZo84+Dyg9yL1abD1J24Tm5CHjl4KQCtHERWgBQC0CqACblQggC0uSC6jFIKQCsjYRU4rAC08jUnh0Cb+lJYPVEcoZHx6ObJg7qKEiDm3bGZVOu9gCgNGxatXYHnwnXUXr+KwaVMU3sU9JQFTt1Yez6Spu0GUCzuDHPdzqOUNydAm4eYj89Zt9yeueuuEhSkhq5JITpP3MjKkXX5agktWQFtkPdGOhT5i4u/ArT7TxCw1J6Z+65j2Gwxh+dIXpMTkZCQDKiT16wsRa01kCgj60MAWlkrrBjxBaBVDB/kXYUAtPJWXHb5BKCVnbaKGlkAWvk681NAm7pJVzz3l4xlg94oVg0sAsGe9K3egS3+IsrVbUSFcvVZPGUw+XVVIewR0x0cWHDwFh22+rGjlxl3U9bUbkGknwOgLapGWFgiWkZ5iHp5gCndRuJyz/eb23J9AtoiDfvg6uZKbUtl3p+dRM0m83lfxoELZ1difsIxWzO0709Mp1rPBUSom7Py9BVU/7Vn6IbT6LZYxbXDw7BMWzIrjo0lQUsLDTn5KACtnITO5TQC0OayAbmUXgDaXBJeBmkFoJWBqAoeUgBa+RqUY6B1D3ehChDzdh9Dm4zijsOhtH1oIzk1pj7Nl90B/UrMcXNjXLuyqetI069J3fwEl7oJuE4fwsztV9AwSQPa2IPUq+WAZ6TG5yUHkUeGkqfNmi9LDrQ9GDHsOBVnzKVXFSPiUv59PZXa/o2b2zzKGmQU7xPQ6lVozRpXV3pUUOfanEbUmvqcRuNWsntmTyJ29s4MtIG3GengwOrjD6k2aCtrR5Th7tqxjFp7DpG+FStPP8X2waSUNbSRKuUZu2Ip3WpZkfzhEZeOX6XomIk0NNKSi5MC0MpF5lxPIgBtrluQKwUIQJsrssskqQC0MpFVoYMKQCtfe34ItLFh51hoP5Slh54RSSEatCqbsiY2zv8+l+77UuOfR5wbUTql6ugbcylrOxPlRoNxc51PbUvt1N7EBLFn8QQGLNhConVVutjaUUrnPgs2HyQq2YqBYxfRMO4Yf61yI1ikSk37cbhNasnuoX2ZcuIZmsaWOMxczqKmIXRvNZz7hg1oa2PA+1eXOC2qxtx5i/mrqTVp2T4rKAHaYgMPY21VClMrK2rmFXP+5mliSg5n2YJx1OcxY/v1ZcX1N+gVqsDUjdtwalQaEiO4umECbcZtIEJkRpN2fWhm7MWszQcJE+nQdbgrCweV59TOf5izwYWgCGtKFLdAnCcfth16MbZzM6wNNOXipAC0cpE515MIQJvrFuRKAQLQ5orsMkkqAK1MZFXooALQyteeHwKtODmW8OAwYkVZF6ZpkB9DrbTf25NiCQoMB01dDAx0UU23iFQUG0VweBRvfcHKWgc9LYiIiiYpGTQ0dFEngaj4eMSSrWU1NNHX0yI6NJw4SQPJylQdPQy1lYkICyc2NIrQoCDyFCiAmq4BBvp6aChnri8pNpSP4fGoqaggEgXg7xeFiaU1Gjr66OtqoZIYS1BwGKkf9QUtA2MMtNRT/js5PoqgsCjevM1cr5qGLgb6uiglxRIaEURoqB+QF13DfBgYGvBJDnlYKQCtPFTO/RwC0Oa+B7lRgQC0uaG6bHIKQCsbXRU5qgC08nXnh0Ar33KEbDlVQADanCr2e7YXgPb39O1XqxaA9lcVVJzzBaBVHC/kVYkAtPJSOjWPALTy1Vvq2QSglbqkChlQAFqFtEXmRQlAK3OJ5ZZAAFq5Sa0wiQSgla8VAtDKV2+pZxOAVuqSKmRAAWgV0haZFyUArcwlllsCAWjlJrXCJBKAVr5WCEArX72lnk0AWqlLqpABBaBVSFtkXpQAtDKXWG4JBKCVm9QKk0gAWvlaIQCtfPWWejYBaKUuqUIGFIBWIW2ReVEC0MpcYrklEIBWblIrTCIBaOVrhQC08tVb6tkEoJW6pAoZUABahbRF5kUJQCtzieWWQABauUmtMIkEoJWvFQLQyldvqWcTgFbqkipkQAFoFdIWmRclAK3MJZZbAgFo5Sa1wiQSgFa+VghAK1+9pZ5NAFqpS6qQAQWgVUhbZF6UALQyl1huCQSglZvUCpNIAFr5WiEArXz1lno2AWilLqlCBhSAViFtkXlRAtDKXGK5JRCAVm5SK0wiAWjla4UAtPLVW+rZBKCVuqQKGVAAWoW0ReZFCUArc4nllkAAWrlJrTCJBKCVrxUC0MpXb6lnE4BW6pIqZEABaBXSFpkXJQCtzCWWWwIBaOUmtcIkEoBWvlYIQCtfvaWeTQBaqUuqkAEFoFVIW2RelAC0MpdYbgkEoJWb1AqTSABa+VohP6AViUhMTkZNXV2+PZR1NrGY5MREUFVFWVk5NVvEWw6tWcPu297YDljMiKZWMqtCAFqZSatQgQWgVSg75FaMALRyk1rmiQSglbnECpdAAFr5WiInoI3i6YGDHLz3gvqOM6lhId9OyjJbXNhjDizbDXXa075+BTRVJUD7hBWjR7HsxCMaz73CBgcBaGXpwf9DbAFo/x9cztxHAWj/HN8FoP1zvMxuTwSgza5S0mknH6CNfcFSBwem7LrMqPNi5tWXTvGKEOXDzUU0qTYe4zGu7J1jj7EWIIrgzTMv3gRFY2xdjdKFtGVWqjBDKzNpFSqwALQKZYfcihGAVm5SyzyRALQyl1jhEghAK19Lsgm0kXx8coHVszZzIyIGfcvS9B4zhqbFzXj87xg2v/pUtA3D5/Xl6S4Xzt73B2zoOHoQNv7/0t/BiZNPRDRqMZqyJfQpX96UEyfOEBERA5bVGdOnGYFnlrHtRiylG3djzJjumPn6cmTvIg6e8UYSjcJNWLtqNJZE8uTCTrafeEpMouQf9GncvRtNTYNwWbaPlHLMGjNlUFO0fR+z67+VnLzrTzhgVLMXy6b0IF9aySJRHNdPr2XL1lP4ShqoqWHZqhtjunWnuB7EPbn/nfN92d6vOH1cYylcqhlNGpbCQL84+fK95dSpuykZ8tecjNuUWmnZfLm/fy8rN5z53J/J40ZTy/LTP2/HbuC21P+p2BvXnuZsd17IGW99KvYew4TOVdGTzACnOwSgle8Fk1vZBKDNLeVzN68AtLmrvzSzC0ArTTV/j1gC0MrXpx8CrTg5jhs7Z/DX8H8J77sFj78K4DahGfOOFGHBnYMMKvCOca2ase5GGMUG7uOGcyteHpjPsImn6bLQmcFNCnJhqSNj1x3ggZ8Iuy4zsS2tR6nabamsupXS9WagVagYlSwtMY3w4eiDj1Sxn8uImhf4a8wJzHptxXWEPs6TxrLp0ANMWzhz/dggLHjB/Ip1mXQvhMrtxuPmOosyBvDarQclpvvxj+tCrI91ps1aFbrM2MjURu/p3WkEt/2UaTd+G66z7DAgmv2DqtHRTRnHf/7h79Z5ODmsPW7Jbfh37Swil1bG7jvnxxxcyfwVE/j3QiwlK7WnfYsKGBiVo3EzM/4Z68D2U08pNPE8PvPqI4p6yuJODZl6TZt+K/cyxdydDv1n8DTakLm7HzC0oSFqwLXtDtTv6YZJlfqUExdExyYazzNH8Q8zYfzpqyxoYi4ArXyvEYXIJgCtQtgg9yIEoJW75DJLKACtzKRV2MAC0MrXmh8CbWzIU6Z3qcfi29XY92ArHczVcHcejcPwDdBnK482dcLv6Arshy/gpm9hxhybivnBHURWH4ZT79roqEmWlB7HwcGB/TcCmZh+ycFrV6pY9+O2QWXmurnh1FaT7SPXEVWtFVV0HrDlSAx9Fo/D1iiOyyscaDdpJ0p5B3P46Rqqa8PL7V2p1XM32HbC1c0VuxK6XJ5bG6eXLXFdNowwt2lseVOW4bP6UUIvkn1/labTxmDq9liEq+tQbNQv0EOpATvyF2fIzCVM7dccvffnOXpDTLWmNQj84fngMb0K9Wfdpn76JQcRT5jr4MDs/TcwSwHaKtz4dxytxq9HbNyXg483UOtzPYHYdpqKm+tkSuiCv8d06tafxUuLzpy5sZ4GeeJxHt2M4Rvu0WLFA46PKCsArXyvEYXIJgCtQtgg9yIEoJW75DJLKACtzKRV2MAC0MrXmh8CbejbPfQo3YWTWGJv3xEzPSV8Hh7h6NGXRFWehs+tmVjFhrB/iT395h8hoUAZhnWfypj/sXfWcVVkbRz/0iEpKGUXdnfHit3tGmB3YSsW2IqF65qwu/bauera3d2tgHT3rfdzL6iAIqj3Xi77zvwJzznPM7/nnLnfOfPMmfEdsU15Pp4p0Jb4BW8fH5xTvy2WmEicSB8DfT/eXn/E7l2zmLP2Mvq5O7H95i6a2gBx1xlcrjrrgioyy8ebKZ30mF72F2RuZ5nfrQS6cXHEYYBW/Fve3r3F72uHsGJnDNU7uuHtPY3SZiH4dKuBy85XmOQvRtWKbXAZ0592jctgLs9Dpu2zCrTF8XFxZpTPv5g2XsnlkyMpADxa1YQyo07hUKcr3t4+NC1u9BloG47j9S4PChnH4TO9My6eZ6gy4ww3ZjcQgFa9c0QjvAlAqxFpUHsQAtCqXXKVORSAVmXSamzHAtCqNzWZAm3A+dk0qD+LZ0U6c2S9K/ZWRshkYiQSQLcElSqYIt+sSuJ3mE7Ve7P/g5jm/X9j4/pefHw4/kNAG/wQ9zEdWX0yhlZdh1NGdBIP71NoWacCWqT8O7UyTec/oMkEb5Y4/kMbdzv2PV9MFT0teH+BgX3acuZ9IToMGkTeMzOZcDQyFdBCQvhbNq7oxazVFwgJ0cHQ0p7O0/7gN9dGmGahfZZWaKfYMN/FhTm7r2LVaRM3d7kg5/E33p0p3G83eat3xNvbm5alzQSgVe/4zzHeBKDNMalSaqAC0CpVzmztTADabJU/W5wLQKte2TMF2rC3W+nu+CsnbNpz6Kw3rQpZJEeYkECMvj4m2tqIYt9zcsM4Zt7SJvTYQV6KijJx5Xpmd6+BoY4WsU+PKUoO/r78gXHHElnqlLIX7ceSg/QrtBH3meHiwsJ9N+m82Y8tv9pya70zLcb9hdg8NdBC4JXFODWcyL1yLRjMI5h+id/b2YPfEVrW6MXphFzM/vsuExuZcdy1GM08Az4DrWEMIaFJmOTJTdzrA8zpNYYV115T4hdnfOZ2wb1jJu3N4NLcOtSZfok6I9ezb0F/rI21FNt2pS05cGTLYBeGrT+GYYFxHH2xlMq68Pz3lpQY+g+lmg3Ex3st1e1SlRwIK7TqnQka7k0AWg1PkIrCE4BWRcJmQ7cC0GaD6NnsUgBa9SYgU6BNCHvA7B4tWHA8gWYjPJgysBl2WiHcOnyIkBZ9GVYqL6c3zWTlbXPmL5wAJ6fQccByQov2Zsv21TgVM4XgW4xxdsbryH2q9N/L76PzEYs1VUV7KVFlHO/TA63fZVycnfH59xntve+ztl4SG2cOx2PHFQxt0gJtXMg9pnZowIoLEeA4medP5lNMruE9Hwo7jeKDyJRJm88y2O4FMwb2YuONVCUHYQcYPuQAFecsoG91axIODMW83SaqtJ+Iz7iitOmSSXszeL9nGOU7rUG3ylC2rBuNVfQLjGzs8Z7gwvJDd8mnqKGtydP9C+jqvJDXBpVZffIEvQvH8cevlej/TwxdJvmwfHI7bAzB98BoKrVbSUgK0BYwjGatayuGrb0hlByod25olDcBaDUqHWoLRgBatUmtckcC0KpcYo1zIACtelOSKdAiSeLphT1MWTCDQyeDKVCqFJYWJjjUaYnrwGYk/T2O0auuEVlyAAd3zETvigcuXedzPTYXjnWdWb3GiyYlo7m2aSqtXdcSKSpA9SbV6dqnN4abZzLo0HUwyUOrMcv5a0o3LI11ID6MvUun0m/eJhIdKtKhZluqWj1k7sbdREsK0H/yOtwnNFbs+SpLDGfHnF8ZMu8OzX2Osr1vhWQFo97hObQXrjuvYl+6Ae3qtaGMeCsj1l7D0r4xs5Z7MaTyJTq3GsrNXLVpWcCcD2+vcVavHgsXLMKlCqzJrH1HR0T+l5nQqxNrzolwrFyE2o1caFEsFs8Zs7gSHIN55Xas3/gHXUolcm3nQibNX0OgZTsczRN4dOYZFWdNxt25KyXyGkDQAzxatMDtli9YF8P9r90Ms71FtzYj+Nc3FgvHuqzatZteZfN+GiXCtl3qnTDZ5U0A2uxSPnv9CkCbvfor07sAtMpUM2f0JQCtevOUOdACMqmEhMQ4kpLe8O4d5C9QEH0jY4z0tRHFRRGXBGjrY2JiBOJ44uKSkCrOQwdjE1P0dUEmTiA6NpG3795RoGBhjIwMkMTHkSiVKSy19Y0wMTJAWytZAElSAjHxiQp/BQvpY6QP8QlJyM119YwwNtZPsZUhSownLl6MgYkJhropn5+Vf98gIZaIGBHh4VrYORhhpCMiOl6+ca02BkbGGOpJiY+NIykimtDgYMwLFEDPyIRcxoboamWhvYEuWjIpifExvPMLxNLSEqNc5uhri4mPT1RooKWljUEuUwzlHUqTiIuNIzQilmCggKkZJia5PscsFRMXFYNcTvmhb2yCobaYmJiEFD3B0MQszTkKQKveCZNd3gSgzS7ls9evALTZq78yvQtAq0w1c0ZfAtCqN09ZAlr1hiR4+x4Fshto5Tc7UUGPuX4/hqq1K2ORK6U+Ov1JJMTgF/iOsMhgAoISID4EHQNHHKuXx8EigzbfI4TCNhbfp8949zqQRAzBzo7KpR0xl2/w+9UjM/uXXPvzFC9StU2KfUdEfGl6jOuheLFPXYeqgFYcGcjboPf4B0YhFSUQHxWCdbkGlHTIj4nB55vDj+cpk4oJ83+M/5tgokRSxKI4pOaOlC6dn7ymxqTcj/6ELFLiYwJ5efspESIRiYnGWJctTkmHvHwlnE9+xAnhBLy9zc2XdrRqWYp03x/5ZJcY9Y7zF25RsHR9ihXKrYhXLBIhBgzuL6Ptegd8vDphIgF9PUP53TwJSUkY+B6i07wAvDYMxUYcD7omJMXHoqebxPG/fiO0aCd61rUhCUuMMxxv3y/LdwFtbDhvAt8RHBpOdHQCSREfMCldk5L5imNt8hVFvtc+w/BFRIb48vzmM+L0dBFrm1OwbAkKW5l9WqBI2zTr9lJJHAHvnxLw/B3BkiI0alYOfS1ITEhAS1+f0BOzWPG8EdOHVEVbaqxYOEhMyVfn+QGsXD8U25R8ydc6YmNjMYh7ygKvUzQbNoiqlhKStC0xSC9P4E22PDShR01bnl2+iE7pFhS3SxndUe84/SCYKhUrILm4kQf5B1GvZOYjXxVAK5+/74J98QuQz9944qNCsSpXj1KK+avzRcbk8zf8w2Mevg5BKpIgTojEslRdSjrYKGncJs/fV3eeEp6UPH+tyhajlL0NXwkHpFJiw/zwD/XnjW8M+sSSGCvFrmRtShbNg55Oal1FhPi94sPbFwSHWVGlcWXMjfVTzd8VtN9gy/oVnTCTaSnmr3zBKXn+Hqbr/A94rh2CnTQBrVTz98TmNQQX7kDPuraItJQ/f+V5b1czP1WKW33/BSBdC3FUIO+CfBXXa0lSSr7L1lNcr00NM86335sQopIkiuu1xLwEZUrnJ49pLsUL/d9/JM/fF7eeE6urg1jLjAJlHSlsbUaadH3qOL29OQXk14dU9pLYYN74PifyXRyxOiJiJKbYFyxAseL5yaWlRWJiAujpE/bvHFY+q8eUwdXRlaWa735H6LbAHwFovz+bGtUiW4E2xp8LJ7Zx+uhWDj2rgtfOpVTLa/pVfRJu72Dg9EVYVBtFzw6VwO8Av09bg6j5UpbO6I6d/JPBGRwikeJzcOjpfZsUAm64M33VU9oOHEthnrPBfRXmnT0ZO7AGll/pO3P7C0wv0wP/xu1w+BSfEcWq9KBjt8p8/UxVMzxUBbSv/hrO+L0BOHUfRaOKBjw6to4dR3xpMcGLng1LoJfuihf1YC8LvbZjW28YTtXskPpe4Y913gTWHsSyQV2wMMwIJSEmJhoTk2+rJkkM4/CfE7kTW5VOzRoQdHs72/d/oIPbHJqWteWLS7ZUTPDLa1w954PPyoOE11rMzjW/YqX1NcCI5tIqFyb/EUHfRV70bVwSXcT4PvqXf+8EU76kCO8tEjo3k+IbW4p2Leqik/SIA7tOYF3Kjn27InDuYc7jh2JqN/+Ft4d/54VdXcyjXiLRNkM7+BGG1SbSrpqZ0gbB9wBtzL/z6b5wP9XbT6Ztw/yE3/sbnzW7KNB7A659G5L+vlFu32Phfqpl1T6D/MUFXWf96hXISvWkVQV7ru1byyW/wgybO4oy5oZfaJGhvcdIylikuhDEPOHA1l3c8Y3HKm9hilSsSe26ZTEnlnsntnExxp5Ked5x7rohZeyCiLTuRvvq0RyU56ukLft3R9K3uzlPHomp1bwbRWxCOPDbbySVqsab2x+oWdOKN7eeUtRpHDVLpL0ZS7izkfmv6jG1iTnnj2zG3mkcpa2Sx5To/QW23IimtZMTb/7qT1jzTTQtpJ3pzZwqgPbV5pFM2OtP064jaVTRiEcn1rHzyHuajVtJz8Yl0U83f6Mf7lPM37x1htCsmj2Btw+y7dA9GgyeTcc6hb6wT5282JgYcpmYfHNsy+fvkb8mcTumMh2bNSTk9g62H/Cn3dRZNC1v/8WNpjQunCMrR7DlqRWde/WnrE0gJzYt5NjzYkxcsYi6RcyTdU3w5fyBXZy7F4xBbmuKl6lN9QaVsTPUwu/xSU7cCaKco4g/tkro2FSKX1xJ2javi67oCQd2n8Da0YYDeyLp3dWcp0/E1HT6hff/rOe5TU3Mol8hxQyd0EcYVJlA22rmfPXy8QOzWtkrtK+2jGbiHl+adBlBo0rGPDmxnh1H3tFs7Ap6Ni6FfroLZPTD/Szy2kae2oNxqu6AzO8qf23w5kP1/iwZ3BUro4x/UzPKd1zQDTb+tgKxYzdaVczHjf3ruOhbkCFzRlI295eLGl/ar+eib36GzBmVbB8XyMm/ZuNzuyB9XNpRxCSaV8e88TjygnYeGxhdw4pHJ3dwMdqGCnl8uXDdgNJ2wURad6ZttTiO7DlBbkcbDu6NFID2B8aoRjXJNqCNvs+htSeQlS1KzP2dbDiciwXfANqkN6fZdjQMJ5dO2Cl+46I55lqbWectmbn9HM2LZCCrJJ57/6znWlRZenRqTEYLwETfZ2nfzjxquoM1QyuiTxIP13RhoE8SHruP0jhfuv4/2W9nzdBKGdhfYE71YZTddJkWRT4CkhY6ukboK2tROYujSVVAG3xxPZcjq9DEqTK5dOXl60/xHNCGKCcv3AY4kX5h7+ycamwM7ov74hEUlOdRGsvlP6cwfbuU5X8toFyeDH7wou/z2/QlFBjmQ2vHjFezIh5uZrrHQVpN8aJ5+TyIIl+xdmxXnpd3w2NYO8zS6R778iBHj/iTtwIcnLCA25Xc2ZEB0IZdWsCwJc8xjH9L/Qle9FEArYTYkGc8ufuAS2c2ceCGlObO/ahdug5VSzmgJfHj2bUbXLt2kG1Hn1CnTz9qOdahehkb4l7d4t7z5xw5uJlY+1o0rNeK2uVrUOTz3U8Ws5ux2fcAbcL9rWy/ak3b3k7kNpD3Gc+OQUXZrzOOOYtdKWaSVveM7ccyZ/H4tPYf8zfUh9apVyMl8dze7cHKc0bM9JhAIQt9wu7vw23R+3s8AAAgAElEQVSiB/ld9zOpSb60cJBl+/ccch3J+qQmLJ3cl0IOZqlgKIGw1/d59PQFp4/+xt3owvzStit1ytWhVL44nl27zrXrh9h25Am1e7tQu6Q8X8UwN4ni9ZXL3Hp4lT1HTmHXoB11yjeiZrly2FkpBAOSePPgON5LV3HDrCz1LLS58/guFXsvYESzymjFX2H9rN84Hy2jcpGiPDqzF5tuMxnRoQNFcn97lVYVQBt8aQNXIirRyKkyJrpaxIc9Y/nAtkQ0Xc60/s0xS8Mroewb0ZI9Wr2Ys2gEhYy0kMYGs8OjBwd0erBqSl+s5ReBrx3RD1gzYwn5Bm2kdSmdDOE94tEW3DwO0mLSCppXsEEc+Zp147rxrNwU5gxtj4VBWo1kSdE8OLmXaNsGVK9QEF1tCe8uejNjwhwKTj7HzDaF0NYK5/qG+cw+b4DH1NGULmGtWKVPPiTEhTzn8b0HXD7jzf4bYpr1caF2meT5qyP5wLPrN7h67RDbjz6m1q/O1C5Vh2plbEl4dZt7L5Lnb4xtDRrWb02t8tUp4qCMJ03J0SkbaIMvb+RKeEUaNa2MiV5Kvge1I6KJJ9MGyPOdVt/zc2uxIaAHsxaOoLCxtuJ6fXXzdNy2iVjoPZeKtik3DOlzHv2AtTOWYj9wHa1K6X1+0iKJ587eeaw8o8+02eMpamVI2IP9zJzkgf2o3Ux0Kph2lfar9gcU9najdjHJqSAxTw4xc5IXZWdtol8l+2RfMVeZ2dqZy5XmsGNJa3j/gEdPX3L6iHy+F6RJm67Uls/3/PG8uH4jeb4ffSwA7U//4mRzB9kGtDIxSYlidAxkPNg9l+leQcz4BtDKH91KpKCj83nJ4PriiozdU5aFBzZTJ08GQoqjOb/Rlf3BjZg+vgcWXy74KBqGXVpG9+GLaLnajzG1k33ILs2mwuBtdJizj9kdSqZxkDV7OdCOoMKft2mXhUeKqhwKqgJapBKkaKOdUrweG3wZj26jsBjqxeguNeSFG6kOP9a0q8YFe1fcl7hSJFcyNN3dPY/pXgG4bV9KdZsMVidDzzCuzQAKLX3OyFpaGf4g3lzVlNlXizN78WoqyR/xJoSxb0lfZj2uxGGvqThYpo1IJklCJNZCT/8ZXg06sb/09K8Dbdh5pnRcTvEFo3i2xJ0Swz4CLcQGPufounH8czcKkQRs8tpTr9syWtS3BXEMl7ZMZfexy4SIzCmSKwSbFttwaV+KqEd/s3H5RJ7GFyWPzgfiHGcyY1gX7O0zf/yc1bHyPUCLTIJEqpVqjvnxe/va3Cw6lzlLevHxifkn399jH3oG17YDKLj4GSNraX+CVHFMEFtmtuGs+SiWTvgVS/mLugHXmDFxBIesx3FzaTe0Uy13fbYfmWKvldZ+STfFWHx5wJWh08OYfnUd9Yz0vhgvYc/Ps81zGNeC8mJEFAYFWtN/4ERKF5VwafPnfBVW5Gsr/dqXJlcueHLUkz//2MS7RFsK6r0kscYWpjjXwipl9VWBSOIwLnhtI659Wypq3+bYbj1aD2uKlfxlEBJ4cvwoT2VWNKgvZv3YN/Rc3hM7Q8MMHrd+zrQqgPbL+XuFuT1GYz5wOaO61sIozVC8zLRyfYjtv4Y5o5tgJs+L/Pq6yZUZZ/Lyp9dU8uc2/vrQDD3D+PaDyL/gEaNq62a4gnnLqzlzrhTGbZEXVex1FPN3/1IXZj0qz4GVU8kvf5M73SEvW0NLPqaSgw28vYMZExdRZuYBRtRxIPT+LmZP/JO6K9fSrYTdF2MhLugFR9a5cuxOBEkSyJvHjnrdltKivgPaUvn8ncbuY5cITjJHMR6ab8GlfWlinuxm4/JJPI0rjJX2B+Id3XAb1hV7+8/jO6vzNCM7ZQPtl/m+yryeozDtv4xR3WphnGZp2Z91nWpyNs9IZi12pbip/HcxgXt75zNjlT+TNi+mpr3F16/FoWeZ2H4Q9vPuM7Ku/qexLYkNYuus9pwxHcJC195Y55LP3+vMmjySgxajuLq0O3qpfuM/2p82HcKir9p3wffiemZO9KH60j0MrZ0vxddjVjfpwr6iE9i8pjd6ry6xY/lwrgRYp8z3Vrj0n0jZYlIub53OnmMXCUoyF4D2ZwdsdrfPNqD9dOLx3N2VBaBNJ5Q45jLzmg3isdMifp/ZIvnLbJ8OKYkxYUREJyAVx3J1hzv/Btdi1OB2mBppY2CaGwsTwzT1P892DWfQrIeMPnaGDg4pHfltoZvTbIpO/xv3HhXSPK5+tmsEg2Y9yMT+ArOrDqHQskM0cJBXWYKxpS25LU0yrNFU1XhQGdAqApYiTogmLDCUSyc92XM3N2NcJ1O5wJc/bg/+7MW844a4jJ9HjaJGEOPPmc2rOJdYi2lju2OZK/UzrySiQoKIlb/lGHGZWS6TKDz1LH2raYGuEZZWlhimuvjJI9k3xo6dia4pK4TyAlf5Dc14pp+w5I+1MyhklcEPLg9ZVf/rQCtNDOQfr+lcsB3C1KYJeAybmQpoE3l2YzdnX1vSvbwfE3cVZFZHCQfvyOjUzgndxLNs3/ac+g1sWfE3LBpXnH/3nKdg4zo83bIZWbN+2PpfRGJTFdvH2zluP5KxTWyV+sjy1N0PdKxTMItDS4ZUFEtkcBgPb2zE889H/Dp1LR0rJ9cLf3mks//rEb9O+WifRHRK/mQRl5ndbxKFppyhb1Vt0EvOH1G+eA1vSnD9lUwf0AzFxyFjnrJ+4gh+l/bk0hpnDFL9yCaEv8dr+C9fsR/JWmkPLv7mjF7UQ1ZPGMEei+HsGVmBgOgEkIGheT7y5c+NHiGc3fkXz2ycaGt6lp1PK9E67312RNZhWMNAdm5/Tr0GNqz8W4sFY4tzau958jfuReUCL9gw+2+KtW/Bw6vvadepBm93bSSw+jg6VErRRywm8NEl9izfhmHLX8gbfJrTQZXpPqgLFe1MEb94yP4dmwnRtqN0vnf4XLSk76iBVC+dl28/jAeVAG26+Xv5lCe77+Rm9LiJVCmYPqLrzKzcnbDuy5k9rjW55S8qy+K5/bc7bmtCcNu2mOppVuxERIcGEpsIssgrzOk/iQITT9K3mi5aekZYWFlilG7+7h+Xn53xI5m1cDzFzbQV8/eC9wTcjpmzYc0MiuZR3AVneMgUK4gzWbZPmylrZ1DBQsKp30ey+FphVk7tgUSapBgL+rmssctvi7GuiOc393D2tQVdyvozbXd+pneQcviujPZtm2KQdJ7t259Tt54Nq3fL8BhdnDP7L5KvYS1ebN+KtIkztgGXEOetgt3TvzluO5Qxv9iluQnL4sT7qpnSgTZdvq+cXs7u2xaMHDuRqoW+HIEPtzgz7x8d+oydS61iuSDWn7NbvTgXX51JY7pjbZJ6CV+e7yBiE2WKfLsPmEx+1xP0qaGHdkq+taL9WD3CiaDankwd0Bxz+VJ57DM2Th7FmqQunFvtgnGqF/MTI97jNcKJwNpLmTagxVfttQKusXKOK+/LeDD11yqY6YmIeXWaZTPXkWfYJsY6GXJpzxaeWDemjdkF/n5WgVZ5HvJ3ZE0GNwhh985n1JHndw8C0P7MYNWEtjkSaGMDOO7jxh/3SzJloStl09Ks/BeRu/JazkN3iBcl8cH/Bv6+BShfKR96xsaUad2fHs2qkfrSmCHQNp6B/cgNeIxolM4+A6BNY/+abaOn8qZkI3KLI4l5fJGH+mXp1HcwTpXyo8R3fzIdSqoEWlHEW+5dOMTuHVs4E1KAKRMX0aRuga++JCKOfcX22ZP5NzwfDWqVRPT+LBduF2fcYlcqFk9fH/ue3Yunc+GlfCeT91w89xAb2+YUKwHYVqLf2EGUM0/7A5ch0G6XsvhbK8AZAa00iddnNrPxYiIuo12wTbiJexqgTSX9w73MPJ2bUSMa8MXrG28v4b47nH7jWvHxfknRMimG68eOElKgNk0rOCj9Rue7VmjltyaiOF5d2sG+fQfYeSuaISNW0r51aXJnUKP+bfv37EnJn+xT/ppRrIQW2FZU5K+4NCxjoH3XiP0HppDv49Y18vWhbwHtu4bsOzAFkyeHcJswnMAS0xhYOZK778MI973BvcAi9J+7hHYlzT7BedilrewJKUf3NuVIU1Hx7hIeu8JxGdsKh/QkH/aS7QfvU6atE+Us090gSaXEvLrC+p2XqdDsF0xf/sZB2QCGtShPXjMDpIFvOXhwOzFW1amlt5vpbzuwpHMN8tqYkFkVkqqAVhTxjvsXD7FnxxZOB+dj4oRF/FK34FfKsyI5ObUNax470nPyaKramxL58hInDu5g55OCbPD2oGyadyB82bNEPn+lyGTvuXT+IXnyNqO4vGTItiIuYwZRzsIkzY1ShkC7VcL8bUuokdEj7pRpKK/RX7R6B0U6zlLUAOvE+rNhYiMORbViaPMCPPUNJjb8GQ/fQOORCxlYr8jnx+GP9jH7lAXDhjUgT6oxp+j63WXm7g6jz+iWivH4aUgkxXL9+FFC8tfklwr5lH5NVwXQyvP94OJhdu/cwukgByaMX8gv9Qpi8rkO49NFTX693uk+lROhdtSrWQqx33ku3C7CmPnjqFQyfbmBL3uXunHhhQSpzJdLFx6SJ09Tijtqg20FnEcPwlErImOgfVOX3XunUED3c0nKN4H2dV1275Pbiwm9vpXRw9fh0K0PFUxDuXLgJiYNJ+E+tga6qd40C7+8jT3BZejaphymqVej311h3u5QAWgzJQkNN8hxQCuJ5+Ghpfx5OYouQ2dQ9YtVBLng8jdxX/LePxyJOJY7h5dzJqAG/fv8gqmRDub2hSloZ51uxTWDFdqfAlqIDX1PnI4VJgaQ4PeEdW4tuW09Ao850yn2tTfNVDReVAm0ktgIAj74ERz5Ad/re9i+PZZWs6fRuUGJLy7wYReW4/73M+q1daaMQy5E8R84sPUPQh06MmNwW8yNUq/QxvPu0T1C42QQdZXlE5eSt/9OelaTbylgQdGSxTDTS1uzp2ygTYi4zxr3xeRtOY1ujR1JDL74CWhrRazhRZnltPlY05sQT3g85LI0+hJOkpKIiBFjmNs4bRmGTEZiTDxJ8q8myrfxU3L+vxdoZWIRoe+f8SEyjPAXR9iw+BalXaYyeHADLL8S3LftU+fvGismLSGPyw56VtcCA3OKliyOfoy/0oFW7478kfMczPr8xtQuNbA00iM27Cxz2wzmYZFprP7D+RMkS2PjiJbpYmKin/aFwYzypbi8iImNSULL1Ajjr72WHXKb9Sd9ade8GdHHx3CzhCddKhgm5zYxggsn9yAt3IEyr9zYYLyQiQ1zZWlFXlVA+3H+hkQF4Ht9t2L+tpg5hc4NS34xjpP8bnBsz2Euvg7B1q48ZSub8viQN/vim7B5wWjsLD7WEstPNoF3j+8SGiuD6GusnOSJlfMWelbTQcvQnCKOxTDXT3tb/1NAG3aOxSPdMOjmQR+nulgYapEgX+Eb3pCHRcbjNqYnRazMSIx9yF+TXdn6sBa/HZ9ByY8rggkJhMfLNG7+KnOXA3lW5PkOlF+v5fm+Ib9ex9DcLTnf6UqUCbu0irk7H1O7VR/K5DNFnPCBQ9v/ItimLdMGtyN3mprpBN4/vkuIIt/XWTV5Kbl7b6ZHDV20U/JtEBegfKCNec229fO4I/mF7m3LY6ItxvfBv/y+9TK/jF7NgPq2n25apHFxREt1yWWin3bxIGW+C7scKPkHSN3d5TSgDb2xlAkL7tHbfTkNS1lmDgBZrKFNXqHdQaeNIYyskZIFeclBszkUm7kbjy5l0/hKLjnYTqeNwYyskfJL/w37j3l9v8OF3tuleCxeTd1imT1kVN5oUCXQpo5SFOWL99T2XLcfz+Jx3dPVLPuxtmM9rheejfvi3tgpSpWTH1nO+D2MmdsWUTXvz9XQ7htjxaawnrgvWkUF21QlB6es2bxmOvkzWmrMYIXWf+9wWk38Gx09A3S1tZDJJCQlJqGtZ4C2pBiTT56mY/6Ma3qVl8Ef6+l7gTaNF5mIS0uasvB+eeYsWkEF20xw+1v2GdTQJoS/w2t4ZR6XWcmScT0VNbSfSg50+nJt5a/ofFFyILdfkc5+JGt1+nB1xa+EKIB2CeXcDzK81seaySD2DmmC573KLDzgQ21rZd86pFJOJkEkkaGro6vYP12qY8jnp6gyJGIxaOuiLU1EpGX4xZvlGWVaVUCb2p84yhef6R24ajOWRR/zkS4gqUSESCQGLR20ksLYNqsdZ8xHsnT8r+SWf7r9a0cWa2j3j7NhU3BnZi1aRSX5BeJjycHJ3Ph4TaegdQYlQ2HnmdZtKLF9drKoZ0n0U0oZkoHWieC6y5g2oFnKS0/RXF49ikmr3jLmxAk65NPJ0g3Fj83An2ulihXatPn2w8etI1fzjmLh2J7p8ufHhq6NuJpvKrMW9cFBMYjjubN7HjPXBDH1z4VU/84a2uQV16o8clzCItdeWMnHy8eSA3nJ0IreGHxRcvAt+x58uLyJmRMP0+qvjXQulldRSiiTPmBl024cdZzCn6t6kjddaUtGWRGA9ufGa7a31migTUpChL58+zjFERuwFbfOm6jltYsuFS0Uf4sP8SfRMC8WX9snU3E7Gsft/cs4F16Vfr2bYZrBc73IG2voNciD6oue4vZLMmiKzk2j9pgTjFp3jN5VLSFVPJ/tn+D2S/Kj8vT2otgwwpNMyGv52embrX3ot1tHAbS1i2RUz6n8YaEqoE2vvzgmkD+nt+KAbj82zB6MlZ4EibY+uoqF1OvMKNMJv2buuC/ui/ydDxDx/N9VuE27QO89G2jlkPvrJx95k2Vj3bEbu5du5TIGyHsb2jPt37yKl0qqF9BHFh/KnkXObItvw1q3/lgZayv2z5QHpJ1mS6KMa2hTBxQb9HmFNnmXA80+vgdoReEfCMcqzXi9sbwxk84XZPYiL+oWzYUsKelTPrNi/0mdyJssH+eO7eiU/H38AE5cMDvcO3NYuw8rp7pglUsbqf8V3CaOI7D+CtYNrIa2TCJfFEVHTwdpfMb2AfVXsH5gNSIe7sVtwlyKTjnA2Pr2KTeiYi7Nq8b0M91Z989EiqV/pPzTaRQjStJB7yuPbX+665QOVAG0CaH+JBjkwSKlFlI+fzfPaM0+rb6smzWEvCY6GcyX5KBCn+7Cw+0Pqo9ZSZfahTOeD/L8u87FZuTfdC+fMUDe39iRaSesmLrQi5oFDRTzd9/ifmyNbcFvbgPIk+vLeERxz9gxYwb3y4xnvnMVRf2qOCaM0ARDLPTCWe/amtcV3JkxuFVyDSZSHu8YxfClMhZfWkVl3cy3TFNWDr+3H2UDrSLf+nmwME1eGZfne8vMtuyjF7/PHIKNqW6qfN9gVoUuvG/kxuzFzuRT7MEo4sXJ35gx/Szdt62ldaE8X9+LNvIWK8fPJc/w7XSr8HmXA0lcMH/P7cohWU88p/ZLHl/+V5k12RW/2ktYO6gGusgQi2Up8z1EYX9Q1oNlX7WvyNPDS5gx4QKd9/9BN0eblHgC2DWgOWvedWPNkUkUz2KOBaD93hGqYfbZDrTSWK5tdcNtQwweaXY5COXW2j+4SS06D66FZfx7/hzdjL2i/ozoV5lkFIzg2a5dWPRZR7sqqWspkwj3e8KLN6GIkz859/nQ1sWiUGmKOVilfRwe+4J1Q9uw3XAkm1cMw94olDNTujPbrznea1wplCtdPF+zn9qd2b4f7cH/xFzm/luEabN6YK+oQfRji0tb/snTBw+30RRU40a0qgLai4s6cMFiNINdGmKhB/Gh11kyZAxJLecwuVdJri/bQnjZNji1LEUuIjg+pTVLXlfDfZE7NQqYIBVF8u+a4Wy86YjHigkUT7MNRTRv793EPzL5a4Bpjlx5KFG2ZMqb45//E/lsP5Ncl1J+iBcDWpRHEn6dpaNnY9p5DkPaVobohxxfe4HcLdpSo5zd5x/g+Bt4NO3JmbIzMty2S+7lvwy0zzb2YeXz5kyZ0QMHxUqbH1td2vOP9a/McRtNITN/zizeQkSZNjRtWQq/DO17McdtFIXMYjLPn66EhwcXM33TY0Z7etGwqCl+l//CzfMM3TyW0czRjOAH5zh+JIiqg9rhaKatsHfb9JhRX7XPDdEv8fYYySmTkfw2vQWm8s0u/M6yYER/PjTejueIquRS8gJt+PMD7DoaS0OX7hSXO1TBoQqgvbS4ExfMRzDQuSGW+lrEh97Ac9hYEpxmMKlPU/TiHynmi2Wz1tRMsw9sPAHPTvOn5xoiynZjeJ9fcTBLf97RvL2fMn/TT2HjPBQvVxJrxc4Pn4+o5weYPN6TsgOXM6BFRSQRN/AcMweTjjMY3LYqWrGPOLHuAhZOKfFIk3h6bAWLNt6hSd9eFLKQl3YkEnL5CA/shzCxawGubpvGupt2uM0ZS1ELA0QRz9m2YCRHdAbym3tHciv95kZ5yVc20F5e0oULZkMZ0LcRlgYp+R4+joSm05nYuyn6CY8/6VujvDFnp7VnycuKzFgwh1qFzJCJIjm1diQbbhRl1tKJlEyz60Q07+7fxE9+vf5avss6Yq0n5dHhpbhtfMiwRStpXMIc/ytbmOl5mo6zltCitAUhD89z4kgglfu3xdFCh8fftM9N+P19zJy0gIROy1njUkvxJC3B7yjTuo0kpvMWFo+qjlkWcywArfLGbrb0lJ1A+2yPJ3vvf+DOhSM89YPSVUpTrWJ1ajYfRI0yvqys15E99GLdeTdynfZg6NhVhGvZYPRpYTMWaZIpI/+6Q7s0u2rFcOOgF1v2XSc+eXOBz4euMeXbD6Vvm9ppXvJS4PHLPSyes54QkwKU0IvmTYQjLd1G0qKofNXwISvrd2SPrBfrzrkhf6/l2/bgf3o5QxesxaRYC6o72PDu3XmkepXp5jqaaoWsvtzkX4UjQFVAe8W7HQt2f6BE6daUt4DLL69jU7w3PQa0pJj1HaYU+ZXQjvPxWNJT8WW0uHdX8dqwhse+RpSsWQFZ4Hn8YwvRqqMLjasWS/chhvdsmT2W86++ArS2lRk2ZTTlLdKWbUhFMVzev4RN++9RtJgjOu8ekFjKhT4DW1LI3JAI32241l+G46JVjOpcA52YCE5v9uT0/UdcPXmeKLMSNKhdijI1etK1fT1M0tT0hnDRy42ZG/6hkNMgpriNpqip+lbZf2R4fM8K7aujwxm34hQ2RZpTI58tj96dR6LXnG7julO1sDW6XGRy0Z6EdpiP++KexP2T3v4CEr1mqezfszUlf19k0LZSSv5MSYx8yYGNS9l1M5TqJQoS9TYQ6+aD6dehBrn0RIpt3dwm3MbljA/tC1iRlJF9+xrkUuwMLyb8zSW8N2zlWbgdxctq4//qOsY2zXHpNzTT/V5/ROdnu0cyZNZ9Rhw+SYcCGe+z+iN9f2yjCqC96tOBBXv8Ke7YknKWWlx9eYM8xX+lx4BWFLM2IcpvO+PrL6P4/BWM6lITIy0JAfePstnbh1Cz4hSv2JmWTcpia5q6dvZjxL5snTOO8y8lX/ANNpUYMnk0FXKbpinlku+wceXAUjbtu0Phoo7ovn9IYqm+9B7QisIWhkTK42mwjOJzVzCya010YwL4c5oT3ifjMDI3TikdEJMUEUbNmZeY26UwiWFPObDtT87cheI17Yh8fYZ4/bJ07+NK5UKfXxD8mdyoqq2ygfbqH51YuNuXYmny3ZPu/VtRPI8p0X47GN9wGcU8lin05f11ftv0Ow/f6eNYowIEXcQ/tiAt2velSbUS6cplfNnm4cq55+Kv53vSKCpYmZEU9YqDmzzZdT2YqiUKEvM2kNzNBuLSoRam+qLkbcEm3KL38Y10KJIX0Sf7IKqWKETMu0ByO32014HESG7+u53l+w+QW68aBcro4P/6FUZ5a+LcbyBFrbK+Ai8ArapGspr6zU6glYoSFbVmUunnZVRtHR10dfXR0ZEhSkhEgi76hnogTiJJJEaW/pdRSwt9AyPSlsjIkIpFiOQb137l0NbRQ0/3y8/8yW8rRUmJREVFKy6yucws0df/+KKONE08KTvVfsNeXscjJikpCWlMLBHh2pjaGqFvqI+envJf/slsuKgKaKWSRJLkj/BDwwmMMydvPh105fWmikc8EpLiEpHp6qfSUV5DmIRIFERAYDx2dvlAS66Jzle2upEhTkpE8hWele87Kf/yW+o9Sj9qkKy7iA/+ftjZOSjqXZPjAZl8/+N4Edr6BujJa7VkMsSiRMQSGbKUwSXfz1JbVz5G0u+XKUOSlEiSWIqWjg76+vpK254ns/z96P+/B2hlUpFCN1nKeDVRjFcDRW6S197S5pNM7bOaP/l8FZMkEhHwwR87+/zo6uujk7KqIpXP/SQpukYG6Crqab9tn6yVDIkoifgEEQExkVjmzo2ZrkGaPS5/VNOvtVMA7c68+GydToGvf7/zp92pAmg/zd+wcIJizbF2kJdNpJsvCSLFHFLMF7mykuRxgvw6qpiDGZ1aVvOftv2n+fvBH1sbO3T0DdPO39TxyOTX7HjEki9j0NE3Ql++tdin8SLBL8gfIxtbrHWy5zr8vYNA2UArlST/jpLlfMuv1/Ka6SACguKwtcmHlrY877o/cb2WIZUkX6MDAz5gY+uArkHyOwryQxGjfL4bpprv37BXjEmpBJFI3u4d0TG5sLC0RldP/7vne5aBNj7kNWf2erPa6zxvrByY6O5OzzrfqLn53sx/spcSeH0nLi6TKDj7Ams65f/hnv4fGmYn0P4/6Ksp56gqoNWU8xPi+LoC3wO0goY/poA06gXbl23BsMNwOpS3zvxF1R9zo8J9aH8wIKGZyhVQNtCqPOAc7iBrQBvtzyZ3Z0avPEFN50P8uaQBdpl80/mHdRFHcXjZMFxWidl+ZS2N7b/YpPSHu/4vNhSA9r+Y1S/PSQDa/488pz9LAWhVn/ek6CiC4+RfmDJLVzKjXN+qWKFVboRCb8pWQABaZSv67f6yALQS3l3YhIvzWE9lPHkAACAASURBVE69rMrfoWfonMGLzMoIPSnCl3l9G3C2xCx2zemJVZoaOGV4+G/1IQDtfyufGZ2NALT/H3kWgPa/m2cBaP+7uc3ozASgVW/OswC08Vz+ww0Xl6U8rejGq1tzKCyPMegkPUcsJzA0DgrWZqJzS4KOLcbnShwFa/di4sRelEx5Czw62p+Tmxeycf8D4kR6WFgUx94++USrT1hF7wKfTzrgnDsNux7EeYM3rq3LEHptMb9O+SfZoPl89v3yFnfP37npb0/z+SuYUNmIq9t+Y5HPESIozizv36mXqr8Ht//mT4W9vIPilC6dvN2FnVMvRraokfypxhx8CECbg5P3HaELQPsdYv2HTIUV2v9OMgWg/e/kMqtnIgBtVpVSjl3mQCuKZP+iAbhM30V4D29kW50/ef5weQ7Fa89Ev0AJqhVpQL6CMi7/u43Hfvp09vBmw8R2GEQ/YU7Ppsw/a82SbT60dLjAlBbj2W9UmRk9mlNtrBut7T52mcjB0VUYdbcm3t4raFg4F+KEMNbM6o7rwhMU7eBCdSsdwt8/59zZs0QmODHa3ZKIt4k8u3qO6w/DyNPUk4sHx1JYL45rHh2oMfMCddtPw3NeLc717cf42yFUd3Jm6NhBdKlfjjQfylCOpmrtRQBatcqdbc4EoM026bPVsQC02Sq/Up0LQKtUOXNEZwLQqjdNmQNtfCg+0zvj4nkG0gEtb7ypWrgfN3NXZb63D65ty/DA04nKrieoMng1R5YOgReraFlxDDcrDeTWP56UNYxm2dD6TNoKM86cY3aDTzQL7/bzS0MXzHptxXtOcxTVs6IojiwbisukrQQ1XUrY8XGIb8lfGnPh8L04mq17ya6BDtxb6Uy7KduRWnZi+81dNDW9zJBS7VgbIqP7/P34jKrNB+/OFO53iOod3fD2nkbpDD5qpN4U/Jw3AWh/Tr+c0loA2pySKeXGKQCtcvXMzt4EoM1O9bPHtwC06tVdOUBb4he8fXxwruXAG5+eFHbZRrGeCzm3Ziy6fhtoW3oYV8q6cPXfFVQyikkBWmt+e3SAoaXyfDrje561qTnfF4+9DxlXN6VeITXQpgB11KMjCqDdcy2IKadlzGsI93xccBrlg8gsBWgtbzC6REtWBknp6r4bb9cGBCmA9h8a9lqKj/dgCubwcgO5cALQqnfCZJc3AWizS/ns9SsAbfbqr0zvAtAqU82c0ZcAtOrNk8qB1poglg5qwJSdOszy+ZO2hZ4yvrEzp+qM5uXueRSxVnyCCXjA9GK/4FPeneu7B2L3cW+8HwVaGxkv13ei2KCj1HAaw8KFbfmnfScWhErou+I43v0qqGx7FnWmUABadaqdfb4EoM0+7bPTswC02am+cn0LQKtcPXNCbwLQqjdLKgdaG2MR532mMcPrAQUqFMbIAEyLVcDZxZlyeT5+7lTC671u1On3Oy03PGRDp1RlCD8MtBD1/igTWvfjQd42lFG8yQaVhsxmaOVU/atXb6V7E4BW6ZJqZIcC0GpkWlQelAC0KpdYbQ4EoFWb1BrjSABa9aYic6BNDOfvuX1wdj9EXPoa2rue5Kvoil+qkoO7K5pTccyxTyUHRv7/0KdVT2JqjmNE91oYKzYZMMTWtghly+ZTfEGEJD/+GO/CyLOFOXVmLVUtU4mQGMGueX1xmXOAmK+UHAzeF8Hv7cw/lRwkmtRh48ULdMz7mqU96jD7oh1TlsylUgrD6unZUr58cfJ8gmn1Cq5sbwLQKltRzexPAFrNzIuqoxKAVtUKq69/AWjVp7WmeBKAVr2ZyBxoZXGcWz8Rl8GreVVvPgHnJiu+6U7Ea7x7dqbf0VuQy4qeM5axpoc1Qxt1Z+vLKIztSjBx406GFbqkqKG9Z5wbS8uP32rWw8zMGvtfPTgx1YmQ+3sZ7uxCaM9T/OtaOY0CUXcOM7RDH7a+CQO7smzaf4CS51fjPGcVzyKTKFZ3Kt6evTjg5cyKrdeQauem5+jtLJ1qiXvFlni9D8fKyhaDlE9V6+iY41CjGbNmTaFpKWv1qq0CbwLQqkBUDexSAFoNTIoaQhKAVg0iq8mFALRqElqD3AhAq95kZA60iHh0xBMX58lcC+nJGekWGshjVHxDXYQk5fvp2jq66OqAKEnMx0+3y7+nLo64ytSOvTmIA3WKF0cPEc+fX+TcuZegXZ0/Xp2h+Bn5PrfXmfhiD/2KWKVRQP6NX7FIjDTlrzp6+mhLxYglUoUfLS1tdHV1kEjESKXJnrW1ddHVC+H05IG0XH2aRt264aD4z3M2bjwHWjb0WuTN6jEtMMvhL4YJQKveCZNd3gSgzS7ls9evALTZq78yvQtAq0w1c0ZfAtCqN09ZAFqIe3OBCUOdWXdcl+mnzjG1QV6SP0+Q+XFsUkma78v/aRcEeQvJ2/OKXQr+ulaYnbc34T+vMz56vTnmOZS8JjqZd5oFC9/DbtTovQj9Icd4Ld8GIeV4urYjJUfeYKCnN55Dm6Akd1mISDUmAtCqRldN61UAWk3LiHriEYBWPTqrw4sAtOpQWbN8CECr3nxkCWghkRdn/mTqzMUcCy3PiJGtadO6NdUdrNHOJN6Lm9rQc8ETqjUeQKsWZchDMC/PnGXX9ccUbT8TtxbBDGgxl4qzvZnXtw5GmXWYRX0Cbq2hr8sErlv2YmaPxhQoAHGP3nDh33XcMe+I++zxNHbMm2n8WXSXbWYC0Gab9Gp1LACtWuXWGGcC0GpMKn46EAFof1rCHNeBALTqTVkWgVYeVBJ+zx/x8HUQ5DKnRJmyFLTIlenWV6JEf+5ef0BYnDFmdpaYEk34hyjIbUe5CqUwjHnL9bsh5CtbloLWmfeXdXlieH73Bq8DxejnsiK3JSQFhBKBDgVLlqewvRU5vNpAIYUAtFkfETnZUgDanJy9H49dANof107TWgpAq2kZUX08AtCqXuPUHr4DaNUbmOAtawoIQJs1nXK6lQC0OT2DPxa/ALQ/ppsmthKAVhOzotqYBKBVrb7pexeAVr16K92bALRKl1QjOxSAViPTovKgBKBVucRqcyAArdqk1hhHAtCqNxUC0KpXb6V7E4BW6ZJqZIcC0GpkWlQelAC0KpdYbQ4EoFWb1BrjSABa9aZCAFr16q10bwLQKl1SjexQAFqNTIvKgxKAVuUSq82BALRqk1pjHAlAq95UCECrXr2V7k0AWqVLqpEdCkCrkWlReVAC0KpcYrU5EIBWbVJrjCMBaNWbCgFo1au30r0JQKt0STWyQwFoNTItKg9KAFqVS6w2BwLQqk1qjXEkAK16UyEArXr1Vro3AWiVLqlGdigArUamReVBCUCrconV5kAAWrVJrTGOBKBVbyoEoFWv3kr3JgCt0iXVyA4FoNXItKg8KAFoVS6x2hwIQKs2qTXGkQC06k1FzgdacTyPD//FH0dvkcdpEK4dK2dJwaAT86ja04Ooyo3xGD+fvk3LYZqllpplJACtZuVDVdEIQKsqZTW7XwFoNTs/3xOdALTfo9Z/w1YAWvXmUYOANpY3B05wU6pN3aZtscmVRSFEURz3GsWwWXtxGHeQszPrZ7EhEHCH6aPa43nCmCHL1jG3dx2MdLSy3l4DLAWg1YAkqCEEAWjVILIGuhCAVgOT8oMhCUD7g8Ll4GYC0Ko3eZoDtLGXGVy6LdsSTVh5/DXO5bMohDSR93dPcfamHyYlmtG+fv4sNkw2C33gTacG/bifbyD7j3tS18bku9pnt7EAtNmdAfX4F4BWPTprmhcBaDUtIz8ejwC0P65dTm0pAK16M5cp0IY92sLMNVcUUeWvOZQhlQJYvmYvweSh5tAx/FraDOLesnnzZq7eDwBDc2q06UvJ0MPsOPcSXbMKDJw9gCKEE3DnIn9uPMZ7eWd5StKhuwuNSxgDcbw6OIkWfdbyXmRKt37TKFfIiqqtu1C/hAFxIfc5tvkw517K+zehfreBNKtaBHnL1PGRvwOrXGty9YQ3mw8/UcScu9kE+llcZPPhSwTE5KfVtIk0t/0sclzwEya1K4XX5TLMu3KSKTVs1JuBn/QmAO1PCphDmgtAm0MSpeQwBaBVsqDZ2J0AtNkofja5FoBWvcJnCrSiqA8sG1qfSVtfUKVHTwz3viEwXxAvXrxAS6sKG1/fwKUgBN7zoYrTKELioEqVKnD2DDdlYFFoCsdfTyFwrgs9PPZgNOIYp1r6MnnyZPZeD2bKKSmTbS7jM9eZabuekYQpTZr0IF8+e5wGjaWp/W2GNWjEVoexnFoygDdLS9NvuyNjvb3x6FsL3fgQlk3vwiTPM9DDG9lWZ6J8L+Hi4sKef59Ru4cLWief8pwXBAUFYZWvE9tu7qJp3mShU59fD+/XbHUupN4M/KQ3AWh/UsAc0lwA2hySKCWHKQCtkgXNxu4EoM1G8bPJtQC06hU+U6AlPhSf6Z1x8TyDqZMnz46NxezlKYa5uPDX+XfkH32UZ8ubox94gs5VurM7QEKrkRvxXlaJ/T3Gc4RmuI4xwd15BMeelGXrh/P0sI3j7BJnOs34G608/dn/aANFL82lSnd3ovTsUpUcJLBvRAU6rNNlso8PM3tWI/LKfJrUmkpEGzfO/TGNIiaJHFk2FJdJWwlKAVqiHjHXxQX3PdfIXX0xF66Ox/LsEsp3mkG4Tl6WHn7G4Kr6XwBtlRlnuDG7gXoz8JPeBKD9SQFzSHMBaHNIopQcpgC0ShY0G7sTgDYbxc8m1wLQqlf47wLaT8CX+JJVLi5M3nYe81qLuXBpPEU+Am2UHs4rj+P9qQg2nss+03F28eSZ3Qhu+6+iIvBqtyt1+68kUs+eBfsf0TV2+VeA9g4j7SvhFeVAt379aFKhILGhh1gxaR9vivXkzLk1NLDmm0BrN+U0r+c1hHs+FHYaxQeRGW7bbzKtaXJpQZoVaAFo1Tv6BG9ZVkAA2ixL9Z8yFID2v5NOAWj/O7nM6pkIQJtVpZRj92NAix8+Ls6M8vkXY0VJwTzKZwS0kmiOrxyFyzgf/KvM4PWN2cgf6geeSF6RDcFaAZgD2PAl0AZso55dTy5YlGTMmDE0qeKAVBpJdDRgVJLmzStipRcrAO3KS3SsU5DKRXMrZ1QIvWicAgLQalxK1BKQALRqkVktTgSgVYvMGuVEAFr1puOngdas0yZu7XIhb1ZWaOnBadlWGqYC2o8lBi0D51L5i5KDM/TUasS2vNVZ6O3N2Jal0UuvjyhKAFoBaNU7a7LBmwC02SC6BrgUgFYDkqCkEASgVZKQOagbAWjVm6zvAtoSw/dy16s9Wh+uMt3FmRXH/Kiz6hynR1QE30M0q9GH49H66UoOJLy96MMwl3H889yWhbfvMr6cFpeWu9BuxjbMqkxkx/6FVA3cRvlGQ3gSa8zwZUdx/cWYOGNDTg2oztADiTQZNIsFE3pQyByC7lzjsak9zapXwkQcxf5F/XF2203Exxra8HtMd3Fh0f5bOKSUHCTdWEuJVq4EiC0yLDmoN+8K56bUUG8GftKbUEP7kwLmkOYC0OaQRCk5TAFolSxoNnYnAG02ip9NrgWgVa/w3wW02DVg9KCGaL+/w/7zd8nfYAzLF4+molEUd9bOotnU1QSJ9Kg9YB4+swZTPI9B8tkkBnN+qyczF64gwHEYXUtbcGf/fnwdKzJx5mK6VrSA2FesH9qVQX/dx6FIHRo0LEuDYbPpLPuH/lPmc+KyH4WrNqKsvT4R2kY06daP4c1rIXt7ham9f2XFlTdQth3bfTZQO2gfLiMmc/JVKHmbj+TY2nF82DyDXz22EY0xHSYsY6nrr+Q3MyAx3Je5fSvgfhBG7LvLqnb51JuBn/QmAO1PCphDmgtAm0MSpeQwBaBVsqDZ2J0AtNkofja5FoBWvcJ/F9CW6LuC3/vmISrKGEv7whR0LEVBMz2QJBL49BkvQsKRAPqm1pRwdCS3sc7nsxGF8+bZE14HJREQlYilpSWFHB0paWP2ySYh4BGXHwcSFRWFfeFyOJYqhKmOjCC/57z2e8q7d3HY2hfA1KEYjgVskHcvigzk8d2nRKT0Yl28KvnEATx77UscoKNvQLHSjiT6vuZdSDRSwNjSmhIlHDEz0CE68AqjmtTC52Et1jw+wJCS1urNwE96E4D2JwXMIc0FoM0hiVJymALQKlnQbOxOANpsFD+bXAtAq17hvwtoc+K2VpnJGfLam85F+nGu4The7fKgkJVRZk006v8C0GpUOlQWjAC0KpNWozsWgFaj0/NdwQlA+11y/SeMBaBVbxozBVpR8FOWuHZj6l93Kd57PWdXDMDOUr1BqsJbUtgHrj04xyGP3mx+25wJyxYwpGVpUookVOFSJX0KQKsSWTWuUwFoNS4laglIAFq1yKwWJwLQqkVmjXIiAK1605Ep0Mb73WXXvgO8CZMHZkfbPgOoUFC9QarCW+yru2zYc4w4qTYVG3WkbvkimOY0mgUEoFXF6NC8PgWg1bycqCMiAWjVobJ6fAhAqx6dNcmLALTqzUamQKvecARv36uAALTfq1jOtBeANmfm7WejFoD2ZxXUnPYC0GpOLtQViQC06lI62Y8AtOrVW+neBKBVuqQa2aEAtBqZFpUHJQCtyiVWmwMBaNUmtcY4EoBWvakQgFa9eivd20egrVcmL8XsP+8YoXRHQofZqsCFh4E894/GuWkxtLI1EsG5OhWIiRdx51UYdcskf6pbOHKuArsuvKVTnQJoaQkzOOdm8fsij0kQs+vCG2qXyksJB+H3+fvU+35rAWi/XzONahGbIMbr4GPeB8dhaaKvUbEJwShPAd+QWMJjkihX6D/wRqbyZPnP9yQSSwmMiCefda7//Ln+10/wqW8kjvnM/+unKZxfKgXk8/epXyQOuY2xzIkv6eSwbApAm8MS9rVwT939wNUnIRS2MfkPnI1wCl9T4OrTYF4HxtC9fmFBoP8jBeQ3rA/ehlPDMc//0Vn/N0/10PX3tKqaT1ih/W+m96tnJZ+/h677Uq2YFUXsTP+Pzjx7TlUA2uzRXaleBaBVqpwa2ZkAtBqZFpUHJQCtyiVWmwMBaNUmtcY4EoBWvakQgFa9eqvEmwC0KpFVozoVgFaj0qG2YASgVZvUKnckAK3KJdY4BwLQqjclAtCqV2+VeBOAViWyalSnAtBqVDrUFowAtGqTWuWOBKBVucQa50AAWvWmRABa9eqtEm8C0KpEVo3qVABajUqH2oIRgFZtUqvckQC0KpdY4xwIQKvelCgNaGUyKTJZ2uAV25Noaf3QNkMyqQSxWIxUBlraOujq6qIt3+1EJkUikcr/iI6OtnrV0lBvAtBqaGKUGJYAtEoUMwd1JQBtDkpWJqEKQPvfyWVWz0QpQCuTIVPAlRZyCMp00ze5PTKQfcte3qccz77em8KfwkBu8zXOSolJEZaWxrzo+P1AKxETEx0JJlaY6H5MaxTvL57k7/NPiJfDpr4+xsZgbmT5v/bOOi6rpA3DF52CoGCAjd1rrd25KnauCgbiqmuDiC0iYDdY2N216hrY3YmKrSjS3Xy/N0BAkJcFFP3m/Cn3mfPM/cw57+Wc58ygVqQYJUyKUalkSfJqJp2Q4Xh4eWsb8wZas+JuMGVaWLB+vTt1TSDg2nrsZuyChn2Z83d3DLTVMmzrVxcIoP3VMwwCaH/9HKfVQwG0v07eBdD+OrlUtCdZBdq4mE+8vPuIkIh4YiLjiTEqTOWKFdBTSxtEpfp7jwgJl+ljjQpTKZU+PjoEn1c3uPVUh+btaqEhnSmUHbH+b/B6/4KA4HjUVaIJ/fwWzZL1KFeyLHpaMn6Ljwjg7asHvPWNRUc1jojICPKWqkcZk3yoqijqTM7oMg20UQFP2L5uN2Y9J1DfVEMeVTQ+9/cwsOUwjnyKxKxhT4YMqYHS4wcc27KOO/lqMeBPG2ZYtydPJgD07oIGVBt3MQXQ+lyYRfc/10KrCeyaZ4WxngBaAbQ5c3PkplYF0OambHy/WATQfj+vc/pKAmhz2uHc135WgfbpiVH886gILdp1RDv0FnuWbqZIj9m0b1MFnTRmVzPSR/s85KrHei4cP81DlT7MXTGagqoqSbO+b/eNZ4VHCA3MraheRoO313fwz+G7VOk3h/YNK6KeEMHzMyvYezmMeu16UcpYGa+LOzh7L4JWQ22oWVwvxQxyfHw80VGRaGppf5fkZBpo3+0fQ60hHlivdGdit2okIi3cY1KJVsx5FU4LiyWsd7fAJCoYz8tb+LvfX5wLLsTojdeZY26icMdeuXejxMA9KYA2NvQ9L18Hgq4xJUzzo6qS4QS8wtf7WYUCaH/WzCketwBaxb36lZQCaH+dbAqg/XVyqWhPsgS0/h4sGm1PgUFb6NGoGCpKMdxa3pmd72oxeMJUzAxTlQIk03dvVAzV5PrxUzFTOsfRTQ8o3KQcL/eu5KB3PRxTAW3Ig714hlWgcs2yaKgoERX0kh1TexNU24GBPZqjGvaAbfYTiW0+kb7mDdBSUSLW+yqr507Br5Yjdj1roJJsxjfk2U72HXlP4/6jKJY6XkVNzIQuc0Ab74VTi76cVLrBayMHPFaNwyRphjQNoJVMYQd/ZOFfjbHd8pSE6lN4cWsmaS8Nn0BczDMubp+N3apXqClDbMw1Ll6O/AK0sRtp3G8V0TFxUMScvStHofR8Cd3HHyQ2Nh7l9nM50OIVM+et4Pq7wrR1Xsak2lpc2rwMp3WHCUgozcxN7rQwS/wfSQKRQTc5tGwTG0/cJTg+mhr9ZjDWshkmaioovf5yPaXag9nerxAbl8ziyDMDzCdPYdQfddHKhNk5JRVAm1PO5p52BdDmnlx8z0gE0H5Pt3P2WgJoc9bf3Nh6VoD28z8jmLT2Pn3nnKJxaVXpzKfviQmM3vKRQeOcaFLFJMVs6Od/RjJp7T2Z3kxVUtqK778TGLP5I5bjnGiapP/E+Xm2rH9aGYdUQJvaw3DfK7iPm4Z+z9l0b1uTGJ99LB6+iUpjHfmjbjlUJUFFeHFw7kT20IU19j1RS/ZtU+C9JazZ/Jb245woVyDn6xEyAbTRvNswHsuQPkzV2IblGA+sz51g/G+Je4ynDbTEBHN04TAsbbfiQ2/OJGylSRojL9r3JtO7t2PeTT0sXdYzoREs7d+FJTd9UszQ3tgxhMa91hDeZCwvdztQRCcCtxl9GON0nKIdB9PSTI/gVw85dvw4fmFNGDqzOGqBCTw5f4yzNz+Rv6kT547aYqYOEe+OMbhpB47n68OihVOoeNOKJiOvUL7bdNzdx1JeV5XE6+Wt0oSGJroYRLxmp0cUFu7rcbAQQJsbHyK/YkwCaH/FrGbcJwG0GXv0sygE0P4smcq+OLMCtI/XNWfR8dIMW76cqvllk3ASQJzlcoU245xoXr0oyedo09M7uFyhdQp9RkAbR2xEAJ/ffuDure3c/1iYTr0GUrqgNmE+/7B85DKKDplNl2bVUJcEEPee0/Ps2OxVhdkrRpMvJohAXz+iYyHYawu7932kmcUYiuVXRkXXCKP8BqRTApxl4xUH2o/n6Gt/hokLplHc7xTjLS25XHYBZ1d1Q7a7fDpAGx/GGddxWA534zUt2eN/jD+UvfH+GEqU5DRlZfQLGfJx5xRaj1pFguFgDjx2pa42pFVD6312Go2azOS5HGiL68V8AebWiwg8NoqY27uxtLTk8N1QOrq/ZptFQe4us8DcdhtxBl3ZfnM3LQuEcsq2GS0WPKP9qLW4z+tC/qADtMnbifOlm7PU3R2L+kX4lHi9kn05e2EFtbRfs9/1CgX+aEejSiYo/plblnOVbgNihjbnvM0tLQugzS2Z+L5xCKD9vn7n5NUE0Oaku7mz7RwB2hkeNBw3h/Z1y8pmSOVHukA7w4MGKfTfBtqYwNd4XjuGx797uO1jRC+LGdSrVwodDSViQ19ywmUkl6mPed/OFFRPwMfzNKf27+Nunp6scBpAxIt/ObH3ID7BCURF3eXpQ1WKlapAHn0ldCt1omfPNhgo58wKVQoCbRjXVsxlX7G+zPmjNMT5sm+KJQNdbzPt5DtG//YNoI0N4cTSkViM3YA3nTkWuZUCRxdgZ7eRl5LTdPLReYoDlY85M2z1cXRbreDaP8OQVNqmVUP7TaDt7U7CVguCHx2VAu3eaz7YnUnAsQncW29Jq7/XE6OXCLSPmVmpGdMe+1KqYi0a1amICtfZt+Yufsa1cXZ3Z0y7CvimBuh8uaHIIOXNK4A2dz7MsjMqAbTZ6ebP05YA2p8nVxlFKoA2I4d+vb9nDLTRvL26jX2bDvJZskaphj7Vuk+hS90SPHFvkfYMbQ4DbXxUOCFB/oRGBOB7fxe7Nr6m9ghb2jSsgDpxhL+9xeWTZ7j39h2mxepRrkwcp3as4205e5yHNiE+KpAAXz8klaEhz9azc58vTS3GUtJYGRVtQ4yM4cGWFRy5dJtIybJfxpUx/3MENc2MsjwAFALa+LcXGbLpIVOH9qNYItA92ESZVsMJr7OAG3sHU1ApnRnaCD/c7bsycOFZlGvP4OXVSYRf/YfNm08QJAlfTY86f3QjdrMNf68/iXZxO068dKRKTgOt0km61+jJ7s/QZfRqXIZUTWZmHoyNjcmTB74CaAG0WR50ooHMOyCANvOe/QpnCKD9FbIo64MA2l8nl4r2JGOgjeXDk/Nc/PccYRKgVdWlVJ0BNKhhhOf6lsw7HElfpzM0kdfQBt5dzKyFN+kgqaGtXDhFGE/c5fo5cr0SJOolNawSvWxCN6OSgy/NxoV/5p9FfbilN5i/B/Ugr9bXH+FHvPJg1Tw7VP/YinXrEiTfHiDtGtowHp46yO2HT4mVrHWrY0a9FuaUKZ5HUVvT1WUMtHERXD6wgVtxlbDs0gDtpLreQA4Oa8Cf+4xZevIAAyq9/HqVA0m9sN99pnZrwzyPSLqsOsGeITXSCOYT24dbMNT1GOomA9j3cD0N8sDjZS2pMPJkihra7Juh9WR2tSZMfhRBu9Grq84ZlQAAIABJREFUcXfsjrGkfiAujsjwcCQ0q4kA2iyPMNFAtjgggDZbbPzpGhFA+9OlLN2ABdD+OrlUtCcZA236LQVfms6keSdpPfUI7avqSz/y+nBwBM6ntRgyfjqVjFSIRhN1+VJTaeoPjcDllBaDxk+nsqmO/GLpA23ExxdEaJliqK8u1SYC7XnlntiOsMDwy+YD0r8nxEXw5Pg8dpyP488JEyhlqJPiQ7Wwlwc5fuYztTtbYmqQM2UGyR3MEGijAjxxd91N6Z5/07xkSoIOur+AJjVnUGj0KtbPLM+icvJlu3rNZemybhj5P2fN/Bks33KD4u3Gsdj1b6obpPXKPpoHG8fTYsRKApQMsZy7jT/NgjgxcwizzvqlANq3+4ZTtcsKAhJraHUj2enQH0uHw4SnUXIweI8/q7sYJJUcROrWYc35K3QrFc79Bb2pMu4Ihcq0YsQkGzrUKoT3jSNcfAfdhw+nkr4GX11PzNAqei8LXTY6IIA2G838iZoSQPsTJSuDUAXQ/jq5VLQnWQFawp+y0aYX3pWmYWXZEQONdxweP5gn5UZh1b8mrza7cz+uDm0HNcZQslRWOvrHUn1b9NXls6sxbzgxdyLbXtX4atmuO269uKk5iC69WmCgoURkwHU2TZ6BUgtb+nZogFbyol2C8bqyk8NHblK85VDa1KuGhmo84YEveOnpRVhUqq1jJS/kjctTrmxRtNLZoUxRX9PTZQi07/aNof7wXegVKozWV6suhOB1/SlRVZswrFFeDrkfwjM0Hj0DE0xN9VGJNiF/vvy0HjMY8yY1KJNPV7Z9bRpHTLA3m8b1Y9A6D3TyV6BlByssDHfTae5ZNPVKY23vjkMPTWY0a8Xcl/6QpyA9nA6xqvY7Bnfoz+6PIWBYguWHTlD57BIsZrvyIiyGYjVGs26JJfuWWOK2+xbxygZ0G7qRJU7tMY5/h/uSGUxz20BgeAEKGGqjWrEl42xG06tGCXT97mBTP+X1dvxVM6ueZ/v5ooY22y3NdQ0KoM11KfkuAQmg/S42f5eLCKD9LjbnqotkCWgly3Q938cWty1EqOfHMPgNoUX6YT7EnJIGb9ndz4LTMZ2w3TKe4ioyOEvUR6rnxyCFXls6c3p/sz2nPL15fu86/tE6FC9lStnq7WncpjvFTXR4fHgI6w48Ip9xY0rnVebu6/sUr/0XbTs3omAeLfnsawRex5ez88gZ8lRoT+0G5lQuWwAtNUkMsXg/OcKRHbv5FPw10OpW7kr//uY/+qOw7zdGYmPB3x+Mjb/fNSEEH5/PGBoWRVU1N6xbkLm+ZwfQJiTEy/eLVkZJgf2iFdEnxMfL9pRWUkY5zf+RJSDZSURySPaLTrmvdAKy85MfCcTHJqCirpbxftYKWpgQH0cCsr2o09vXOkUECuiT2lRWTjdOmX+SRT4Uew2T3UCrSP5S9DvD8fEll5INwNPu17fynTJhmfUndbpztH9KSiinub+5JIpv75Gu4LBMkmUH0CoyHtMc4+mN34QE4hMk960SSt8Y4xIvJLe3cpqzGMnGyzf9zNix7O7fl7EjeS6pSF/1Jh0J8cRLbtyvjoy8yN4a2uwf38ift99+Xn95JitnmFcl5S87UGWcxbTuf4nP2fd7JLvCt+5PxZ9PivYnq0CbeJ3gQH+0dfUU5pPM6r/qT6A/fuF6GBaSrWf7sxwZztD+LB35f44za0AbT1igF173XhCnpk5kcAwaJcpQoVRxNNNcB1kRfRR+7x/z8pE3KrqahIWDcfkqlCqUj8SN3WIDX/Hk2VP8w9XRUQolLEET0wqNKGkkq92BDzzec5hHoRHJUuvLu3v6dJ4/nqJZTngoH57e4d3LEFS01KXXL1W9FiZ6iddPfQFF9AG8vHMLP38JJEOoRl6q1KxNvi/b6ckajQvjxd1/uffKmHZd6pHeFZNHkH1AK8nfC7zueX3Jd/EyVDD7Vr6/oY+PJdj7Ka+93xEQpoauWghBPoHkNWtMpfJFUZMkPDqMj+8e8/GzL8GRGmjGfyIsQY0CpZtRoYhs0b8Ux3/w58v5afQvw/Gcqn/J9Wn1L0jev5Ly/skvHh38gqf3bhOmWYOaNYuTHcuIZw1oA3l59ya+fnFS+AzV0KdKjVrk00zvF0qiv4WvX2y6+tgYb7xuPyQ0EmIj44jOV5iqVSqTegfy2PCPvHl8mSefzWjZunKKdSfjIvx443Wfd/4J6KrFER4ehn6p+pQrmh9Vxf5/J3c843hTDqwM9MHeeL5+TFBwrMQuoj4/J167CmVr1aZgXtldGv7oFP9cf/D1mNUoTY32zSmum/pm/yLNnhla2fh+ce8FsWpqsud18dKUNyuRxhtUybXl+vsviFVNTx+F//vHvJA/ryWfkOQvVxmzwvm/PK+DXuP57Cmx4WokqEYSFJKAtnFRylWrQB458UR/fsCD5++JjNNALdqXUA0Tylb6ncL6mSGixHi95PHGyvpXqgRaac41Ka6X3J/P7t8hVKM6NWuUSOqb5Pn06f0TvH0+ExKpgUa8D2EJqhibyZ5PWQG67ALaLP/c/Z80IID2F0h0VoA2LtKPMzvseafRnBYNahPkeYjD+x7wu/UUGlQy+epHWRF9+Mcr7Nq8Hv2a/alrZsTjU+5cfqxHF7tRlNXXgrD3eGybxVnf+nTv1oS8Sv7cOricK35VsbQdTilpqfYTtvfuz7Oa3TDT+5IkLd2mNOtdi2T/JP1jZEQY6hpaCs94BnpuZPm6i9TrNYqyeqFc3LaCp0qtGWzfm8StQpIPDUX0n65OYcW+CNr3t6Igrzi8eB5RNSZhYdWEvEmNxRPkdYKNztO4otSLRa5jMFLgeZ9dQCvJn8fOybxVbybL99NDHN4ryfdkGlQyTTPfKfWHObz3fpJeKSKAc2vH4eFrRrsuPSiS148bexZy5o4BPWc6U6eYHjHvb7JphSM+BTrRsW0jdGKfcGn7Yq4E1GfkbHvMUpTmy/zZ5Dydy0o9Weg6GuM0flHSy/eX/jWlRYM6BD1NGW9qyExLf2TvfWpbT6ZhJVOS969tlx4UzRvAvaNunLmjRpeJztQurgfRIby4dYQHd3dydO8ryvy5iGH9GmXLLoJZAdpPV6eycl84f/QfQkFec2TJfCKrT2SAVVMM0hhziuif/DOcY55mtG7fEa3Qm+xe5I5pDyc6tquKdLf2+Fh8n53l5uUtnNh9kcjfZjF7RnfyJuYwNoKnJ5ew71oMjTr0ooSREl4XtuNxO4xWw+2oVTTldxqyveAj0NRK/KDly13pc3UqK/aH0+7PIRRSSt6/JhikMWYk+pX7w2mbSt/fqgmGSkqEnXfGfvUFanezoX41Y8Je72ar424K9HShX5+WSJj21d4hzD+tTLXypdCWMm48Qd53eB5Zhb9txlI0r+RT4rSP7ADauEh/+f3bhOb1axP87ChH9t2jtpU9DSoX+WpddKl+12TeqjaheYO09eGfrrJ7y3ryVPuTuqWN8TyzgcuPdehkM4pyBtrS5/XZ7bM5+7kOXbo0xVgzDJ8r21l+6CY1/lrKoN9LoBTwgO3LbHltOJzO7SqhFfmWs5tm8yrfQAYO60phnZQDLjIiHHUNDZSVU96RX+JtTPMGdZL6V2uIPQ2rpN2/s7sm80b1G/oYyf15lIfS+/MlpfssZGi/RujIx0jMh5tsWeHER6P2tG/bmDxxnlzesYTL/nUZMXMSZnnTf9OWET4IoM3Ioez9uwDa7PXzh7SWFaANfryBZSsv0OJvF2qZGRAX+o79Tv3xKjGWEf3bo6OWsksZ6pXDeXTYkZ13jRg+dhhGumqEPD+Oq5MDhv13MaiRMT53tuHqdIDajq60KZlPeoHoRxsZN2kJlcYcZWhjSb2JDGixuUDXSl9iUEId1VQxEfmWU2sXEFh9Il3rpYWjqdIS+ZYTSybgoTOEmcObo0o8n88vYJrLLtrMv0LHMql+7b+ln3eFjmWVIOQO68YMxqf1ZiZ0L4cKsbzZNYQZ230Zsvggv5vK2oyP9OfMtrncu3KL+6ptcF72fYFWkr/lrhdoNsKF2qW/5PtF8TEM798BnVTTxVL9ygs0G5lKX2IMw/t1QFspjLe3zhBtVJuSJYxRVorH5/Y2XJ0dMB58kqEtTEgIfsX9G88oVKMhxvqSH/x4Xh6xwXn5U3quPUDTQl/8/uLPbR6otmbOsjSAVpLvdQsIrGpLl/oFU5R1pBXvAef+eBUfzV/9OqKrQP+S63W+6l8Cvvd34ursRpnx2+leWZe3V/by3DcfZlUC2WY9F/U/F2H9o4FWMh7HDsGn5SbGd5dsURnLm91WzNj+mcGLDlJXPh6T7gxF9H6nmD9qMiZWO+nRqAjKRHNrmTnb39XB2nYaJQ2UCH+xl/PnIiheT4+zU6Zzt6xtCqCNCrzLFruJJLSeQt+O9dCUbHHufQU3l8kE1HHBvudvKWbEQp5uZc8hb5pZjqWoYbL7MuQO7mOt+NRyA+O7l0/q38ztvgxauJ+6RVJN9Sqgj31xlAuextRuWRNt6WxgGMcnVudkfDeG2szGLL8SXntn8bjYMJpX1ENVwmLRwVzdsYSnhi3o3aGhdG/7nATa4CcbWbHyPE2HO1O7jKH0eX3A2YLnxUbyV39z8qQe33J9k+HO1EnUu1jgVXQkwyR6lQgeHZnDrjuGWI8eRgE9dUKen2CVy2z0e29hYJMihD47gpvLBirZLqNNaWPZ/RZ1B/eBQ7lZbiKO9q3xOeTAfLePDNyxmpp5ZKUGkZemMWzeRbpN20m7KoZf8hr5jtPuC/GvPI6u9QunyHdi/5oMd6JOmXzS/h10seC5JN5+HcmjkdJfqd71PE3+Sql/VnSk9H7PoxrJ26t7ePY5H6UqB7J9+HzUes9PAbTxwa94cPMZBao3oEBeyUfr8bw6OhGXFY/p5raPpoX/+2t3AbTfF4kE0H5fv3PkalkB2odr27PuSUWsbZ0pnV/yoArk3LrhuHpWYPHMcRjppZxxyEhvqBLMkQU9uZd/JKMHdkH6Bs73Nm7OE/DQs2bblPY8PTYf182fGbzYgQr5dGWeBF5gkdXfvGixnMVWdVFKBFrba/SqloFt4c/Z5zSBT/WWYt3GNEOPI16dYaWzDRqd9jG8tVz/ci+jx00jvu1qlgz5PUUbiugDry/DftYKGs96SI+q8ofu3fn0tdtBw783Yt2mnLR+y+/GErb/E0upAl7suVcax6XfF2gfru3AusflsZ7okjLfT8uzaPp4OXB+6b5U/6Q81raK6SVn+j3YhauLG+XGbaVr1TSK4ROCub3JBtcduow+PJfySbNpEn+WsuOfGEoW8GLvvdI4LE0DaMOfs9/Zho+/L2Zo2yIpgPbhOln/htq6UCZpPI/A1bMci2ak0b8kvTNl8kveM0vGf/p6iOHNpTWsXnCJVsuW0LBg8pKJqyxvPYzoXAC0kvE42WEFDWc8oEdVSX26ZDPHBfxpt536IzZg3bZ8Ct++rV+PddsKfD46jIlrHzPA5QyNS8nGuO+JsYza/JkhNi40qVQo2X3jyY6+AzhfaiwOyWZoQz/uYdFfW6g8wZn2dUvL3giEe3HAxYY9Sj1wn9oDlWSzq4F3F7F603vMbVwoY/wFZmTxrqTh9Hv0qCavc723kD8nbaP+cFm8ydEnQ32bCmm8Wo7DY2YVTsf/xVCbvzDR/hpWwz9fZNeqbVT904lqxeTPsnSeQNkxQ/twnTnrHpfFysaZspJXO1GBnHcfiatnWeZPG0dBKZAlu3/XmeP+uCxD0tEbqYdydGEv7hoM4++B3ZA+7n3vsHquDWd0B7PJvgufbm7AzXkLFey20OO3QjKfEp6wo58FF8zGM2tqfe7Pn4j7s6o4rhxNwcSFSH32MnWQC4Ws1zK0XcUvH4SHP+fAXFu8a83Hqm3xFB+KP3LvxLpHZRgywYmyxsrS/l1YP5KVj8syf/rX/UtfX4b508ZTMMWqSldZ0W4EUb3mYZVshvardCWEcGfzRFx3aDLygAsVVP57LbAA2gx/jrNVIIA2W+38MY1lBWjPzirHvzEjGDZxBCaSd4ZxodzZOZmV5/WZ6jgRk1QPyIz0Rsp+7JjamaA6Lgzq0VRW1yUHzn1xXVkzuzvvTi1h5ZrHdJu3kDom+jLTYu6xod8grpWxwXFmd/TlQBs6cAMNC4ZJJZoGRShkWkBecxpNiM8bAkJiIeoN/7ovILiiHV0bFgBVTfSMC6GvpZHmR1n+D/fg6rSc0uO2072aHLgCzrPQahQvGs1nwcimJJ8EVkTvfcwGxyVP6LXuAE0Kyn/4Pu5ikqULJsPWYt2xCnE+HmyYv4Zyg13Qv+rA0ivfH2jPOpTnZPRwrG1HYCJ5iyvJ967JuJ7XY/JsO0xT5zuT+gRJe7tnseeaAYOmjqKEpMQk6Ygk3PcjLzxvcfaCB7rVh9O/VdmkHEVL/FmwhnKDZP4su5IcaFPneyHBFWzp0qggSpJ8GxVCX1uDcw7l+VfeP+myi9L+TcH1XB4mz56IqeQVarLjrEMF/o35C2ubEXxbH0108GfeeXlx+coBgvVb0q9LS3RTFJrnHqB9c9yGOUue0GPNfpoUkr8y/bgb+0HOFLJawzDzqinKS76tX80w82p4rmnMwhMVGOG6gqry2VIJcM5wucYfE5xpXi35fy7SBtown6MsG7GUYkOd6dqsiqy2Nu49p1xs2PyqJk4rR2EY5YefT+Je8JvZs9+H5hZjKJpPCZU8BTA2NuDjcVsclzyix5oDKfo3eZALBa1WSeNN/jL77XFb5ix5RPc09IWsVmHdsdqXmkr5+Ij22cP8QSswHbGYHq0qkWpyUKp6uXsIW981Z6h1T/KnW5ssazA7gPbc7Er8GzUUK9sRFJG8xpfeb1NxO6fLpFm2FDFMWZrxLb3dLFsKqgaya3oX/Gs6Mqh7c7QlDz45cO6N6oirQ39UfO+yz206L/INpW/nWuirRRH8/BwHtvyLaX8nzGsqc3WZLWuuFWSi2yzMtOWz41EeLOg0HnrPx7pfXeI/v8E/VPK8fsvJ9YsIKjuOzo0Loyy9fwuir63JeUn/oq2wmjCCIrrK0v7d3TMV17O6SOItmrp/jpX4N9IKK5vUeh3sZk1Mpc8IaCXPp0+8fHqLs+fPoF1tGP1blUvng2bFfusF0CrmU3apBNBml5M/sJ0cAdojMCr5DKq8f+kCrVxvphaYPtB+asR8t1FoPT/GZqd5fPptCL3b10Y95BPvPT3Y576VqKYLmTe2JRr4c3OVEw/y16egUhCRr29z822YdHe6bq2rookf17Y7ce6+ZL+5AF49f0hsTA3MymuBrgn1ulpQp0yxND/M+RagPi9vJwfqLwlVRB+UHtD2n4NRv8VYdzPlrIsDb363YUBrEzw32+QuoD0MIxc7UDFxxjwx3+kBbTr6kAfbWLPtDBW7TKFZ9SIpPvIJfXKYC1dvcvbcafRK9qXHwAGUKiT/iCbiJcfnOvC6tg0D2sj8SQm0knw7c+5+YJr5rtvFgt/LFuNCekB7OIGRi2dRMV/KGs10gTaVPvLtNW5eu8jZk3sI0GxEz4FjqF7RKMWuOPATAK2FI/n6fl3jmy7QJtO/TA9oZ5yl6QQX/kiccZWOnbSBNjb0BcedR3CJhnT+sxMF1eL5+OQkJ/cf4H7eP1nl3I/QZ8c4tucQn0MhOuoOTx+qJe0Fr1OpM717tSHkxMS0gdZiDoZ9FkpLPpJPqKYLtOno8bvPtmW2vC0wBkuLFhilBash99g4ZSbGQ1xpXTF/hiuv5CjQHopn+MKZVDJK+XVBukAr15fRCEkfaN/Xx1k64xpHyOP9zJu8EoM2PSilGcD9sw/QrzuWYZa/oawci+/FFSxx2Y1+78mY1y2Fku9zXj29wJ5Nxyk/aCXWXUpwZ6cL5+4HkJAQwGuvR8REV6dUOW2UdAvzu+T+LVecS+kB7aE4hi+YRUUjvRQ+n0sPaNPUfxtow54c5cK1G9LnU57ivehuaYGZSfo10Yr85AugVcSl7NMIoM0+L39YS4oB7StOTJqCh68ECICynZgwtB/3FlZJe4Y2x4B2DEax4QQ+u8ipfy7yKiSIslWaUC7faxYuWEVRy0PYmpeQhhgbEUBEgg6aapKFAQK4sqYzm24Xwtp5D7VMYwn1/UBIRCxEvuTE6rl8rjiNvs0KgIo6eQyN0NF8yk6rSdxNzEzt0TgObo4igCqfN5aeqYj+20DrRHP9c6y+WYI5kwehqxbKPTnQznDqy7tz2yhYdxRF0/jgPzH07PooLN0Z2uwAWr+TuE5ypvDARbSqURHNVF8lxwZ/IjAihsiAB3isX8+tD9UZvsGGUkqRPDs0m6U3ijN78mDyyP2RAO00pz68P7edAnWHYxj/gdBwSb5f8e/qufhUmEKf5gVRUlFH18AIXa1vzNBmEWjjwgMJCg0nMuw9j46t58RZTXosnUbNFADxI4A2mjeXN7Nn/X4+S5aT0szLbz1nUjtkJXOWpjFD+4OBloQ4It7d4fLJU9x59ZoiJRpRoXw8J7as4n3FGcy1akhsVBCB/gHExiUQ7LmW7fv8aDFoAiWNlFDWMiB/fgM+pDdDmx1AG/kWj1UzuGvQkn5de2CYRqmBbHa2O0uvt2Giw0CMpVPN3z5+WqANecbedY68N7Kga6uyqCvF4fvsBGvXHaCqhRt9GhREOToIn/v/cuzfWwQraVC+Zl3KJFxi8vJ/aWezmx51jQnz/0CI/P49uXYen8ra0bu5CcqS+9dQdv+mO0P7HYA2NtiHwIho6fPp7MYN3HpXlWHuNpRSER+FZTS2c8vfBdDmlkxkIQ7FgNafCxvW4xUcKrtSvoZ07dSQWwvLsT+gM9a2cyljJKHIUG7vssftegFmTR/7VQ3tudlm39Tr48fO6Y15aebM6EFdySOZgAt7xl7nCRzQ6M8G+y5p9DSBgKtLmTxnDU1n3qNblXTMuDOP/lP30nnKITrXkn1MJj3SraH9wLGla/iUqCvcnQFdy+P/aC+uThPQ6+PBiDZFZH/1P8f8oaN428aNRYNqpwhAEf3b4xOZvWQnTWZ70aua/MfNewd2g+dTvO94VB9t5uLtV0ntxsdEEh2njIamLiXrWTFojBWFU74NTxFDdgHtOcfSHPDvxNC08j1tLEbSj7a+HIrpE4jzOcOS0VNQt9jFX60S9wxPf1AHXV+OvcNS6k97RK+i93FfNJULd15Kyoylxzf9+UYNbdrxTsbtmrFsPH/VvzIc8O8o90NJPv7T10tii3jtgavzBFTa72Zku2LJZox+BNDK94I/eYFwCdCq6mJWZwBFPs9lztJdNJr1jF7V5DW03juZNGQ+RUdsYGibcilmut5KZzy/rX+yrhlzj8TQ3+UcTeQ1tIG3FzJj0W062TjTuGLGNbRpjYjwV6dxc7FH03wX1q1MU9SypldD+/aEHY5LdtJo5lN6VZfX0H6zf3bMWbKThqn09lI/1mPVurz0ugmxgdzaMYN/3lVi+IgBGOikvS55vK8Hi0dOpMjEi3Stkmqt2nSGfXYA7fk55djv1x4rGxdZjWmspORgCm7X8jN96lj5R01fAshIb6Dsz+4ZTfEq6cCoQd3Rk8xES56nLjYcUO3N2kmd8L7ujpuzB82XLqGxSeJM9FN29R+AR5G/mTWrl2ynqhRHAp+ODMd+w1MGzDlBg1LJoPAbNbTn55Rnv187rGzmyvonLamYgtvV/EybOvarGuELTuXZ79uOIV/p8zFtyrj/VkMLBN9cyWSHpdSxv0OfGur/eekuMUOb/m9ATvxFAG1OuPqd21QMaNMO6sXegSw7o4ul7Vwqm2qQEOnPade/OJPQAZthvdDTUCYuKgbU1JFsRpKRXpdATq0cxBnJDiYj+6OvpUzcx2u4Ok8jtKELtl0qfxVIXPg7PFZP4GhwZ6ZO6YFkdjQmzI9PwRqYFvryoUX0lRkMmXOCHjOP8UfVZK+Oo7y5smc9geWsaPNbMtBNJw/R3ldwd56Az+/LmdJLRs8xT7Yw1m4Z1SccZmAdfWJiQFVD9nXrt/WHGFgvP+GPNjHd3onio87zVxNDaZuSeK2cL9Nn9k5aVUj+KvDLDO33/ijsxd5BLDujg6WtC5VNNWX5dhvOmfj2TBjWC/2v8p2BXlOF6JBHHF08H9/fxjKoXUUpKMUEevMpXAfTwnrEhQfhFxiNYYH8qMq/Ak8E2op/X8C6eerXtTJ/UpYcJEtmlDdX924goOxgWv+W8twX+wax7LQOFrYuVEndP+te6CnFEKuiiZq8SFqm18bCdm7aevV4gj59RDVvIXRln74nAW1Ig9VM6V0t2Y/djwDatAd5+OPNzLB3otjIswxrkk82jq/OZKjTZXo7bKdVRX2IikzaC14RfdCladjNPUm76f/QvqpsPL8/MAyXM3pY2UynYuHk9dJplxykjlayF/zjf5zYcVGVAbbjKZmqhjvs5SFOnPWjTucBKdYzlcQ7096JoiM8GNY0v7x/s7B2vkTPWbL+KaXqX4Z64N0NJ/bsj6PdyLGULqBFQlzMV/mXrCN9f5ctax/VZPqMAV+WJMvguZ8dQPti3xCWn9Gk/wQXqhbRkt6/Z1aN4HRsO8YP60VeTZWUz+tv6SX3g3Iwp90GcyaqA+OH98dAR4W4T9dY5TKd4LqO2HQtz0uPZbg5X6TZCjdalTSS/0fImxM23dnv3xP7VcMxSbVBTEzgPXbPHMLj0nOxsW6IbvJl1KK8ubZvI/6lLWn9m3EKWHy5fwjLTmnS3yZ1/9oy3ro3ebVS9k+qP61J//EuVC2a3A+5Xn7PylKTdslBXEQQfgHRGBrnQ1W+EHIi0Jb96wzDWhRId4fTjH7qBdBm5FD2/l0Abfb6+UNaywrQhr89w8rZTph0c6Frs6rEBV5h/fTFGHWdgnmjCsQF3+GU62kM/+hBrUqmRGWgVyWG1+dWsnLLTcztFlO3hC7e1zbhuukOnWxmUb1Iyhp3Yz9/AAAXnElEQVSvuOj3XD+0Do+HoTTtY08d+aKzQfd3sGzrB3pOGiNfp9SHSzMHseFTFSY4zsZMP4xPj6/w8lPU156r62FSriomhnlIc5322EBubLJh5UVD7BY6YZYnhEdbZ7Hokj5TXWzReHGCM0c+8pt1b8wkHzV9U2+PqWRmNeo9/zh042BEH6bOGkkhLR8uzRrE5ujOzJw8kPwp1lv/cUAryberoxOFu7jQtbk83zOWYNR5sizfIXc45XYaw7Y9qFVZlu9v6VWJwuv0UrbseUL19u0xkq77FUnArZN4m43FsqMZIU9PsnPrv1SxsJet20oIj7fOYuHRzwxdsI4ayb5elyUzLaBVLN+R8ngLdXGh21f90+HyvHUEV+pCU/m6qYl+SPQSP+Il41/uR8dGFSDsEyfcJhNfcwytG1VAXTlWNp5d/6HuuBW0qShZSkF+hBzHsZsdWrlglQOiPvDP7G4cDO/N5JmSDz4/c8lhMFsiOzF9siVGmp+547aKewn16DC0GQbRifpeTJ45MpnenOmTB8pqSMOfsdGmGx8qzsR6UEfyqr/h4JjBPK08nqH9WpEn+Wv3iJusHmjNndITUq5Dm+JuDeL5pW0cOnoPs7Z/0bpOJdQle8EHPOfF4+eERn99a6sVqECF8sXRivrAsdndORDeM514v/Sv/dCmGEZ7S/UHw3tiP2MkJjqJfpgz3X4gRlqSpffusm6sBf5lhvF7TVMk29bHhb/izeMQavQeQ5nCsjWxYnxusMllOWpd7PmznlmGtbOJvcgOoA1/64HbHCcKdppD1xbViQ+8yoaZi8lnPgnzxpWID7nDabczGLTpRs0qRYjOQK+mFMPr8264bblOe5uF1Culh/f1zbhtvk2HsTOoUUyPUK8TuLnMI7DhDGb0rS+Fu8i3h1k0bjJq3bYzvHtZNJOAVZK/B3hsW8+NkHz0sLCjbAHJ7Gw4n55c4dXHyFS7PwLqehQuWwXTfHpEvvPAzVHev+bViQ+6ysaZSzA0t5P1L1TWv7ytu1FL0r9EvbncD6l+MYZyP9SS/wCEHMeppz3qvVIu2xX87BS7t/1LpT8nUqtkXpQkz6ftjiw+8pFBc9dQs6BY5eCHgM1/uKgA2v9gWm47JStAmxAXiefFtezYeQKDAiVQ+fAcnUYT6NC5Hvk01Qj5uJtFvVdS3HYuPdv8hloGeok3cZHeXN63jL2n7lGmeAmiPkdQouto2tQvj3riki4EcmPlaPY/CKRU/f7Ua9SM0ib6SV+UBj09wfIVU/EOK0LxUjXh83XCNStgPmIsFQvlRQU/LmyYxtm7AV+nI48pjXoNpV75kunu1hQd/Igjq+ZyzjOIssb6hEab8rv1CBqU0pctK+b8EPNty2ksX5Ypff2XdW8j/S6ydcECXoRqYaoaSYBWM9qPGUDlfMm/PI4jyOsUmxbM5vKLSJoPcaCH5Gv5DAZVdpUcyPK9jh07jyfL93g6dKpPPi15vvu4UtzGmZ5tasjznVKv3Uimz6+lRkyoNwec/uDItRhUtRJfzcURGx5OjTGn+KttEcK9r7B7nT03nqtRpWxb6Zq976NNaW45lLoVTFMtBi/zZ7Pcn2ZDZtG9c0vyKElKZqZz9q5/mvlu2NOK+hVKoZxG/7QbjqdDZ0m8N1nWzIqgVlMZNrEbknn0tPz4olcjVrLxyOahHLnkS8kSf2Cs9JaHnyOo2XEELRpXQkdVhSCvG3gc3cGNezd46/UOFUNTypYtTcn6Y+nattx/fl0p6WhWNlaQjMdtCxfiFaqBqUoUAZpN+WPMAKrkl4w2yQxqfzziuzFx63iKKSnxbb3Mdj+v/WxauVG6t7xB4GvCSwym89AOlJAv7xcTGsClrXO48PAZLx89IFKzAKVLF6N0bQvMzZuhI132JILnRxex7fBZDKp24fdG5lQqbYSmdHYsFu/Hhzm0fTefQ9LYC75KdwYMMJfOiibFG6Ipu9++6t8AzsR3YeLWCRRPpTdRjSRQoh89gCpGsrtPUhM7a+Vt0NRPWus6IT4Sg9JtGSwp0ZH+xyuaV2dX4rYvAOupEyiW6qv7b93G2QG0kvH69JI7O3YcR79AMVQ/vEC74Vg6dG4gvR+ly6L1XUnRcU70bFcT9Qz0ic/rK/tXsPfUXcyKFifaN4LiXf6mTYOKaEie17ERvLp1hM0H1hEVUoXCFZX5/OEzpuU60Mm8Q7Ia48+cdBzMpaB8lKnXn4YNa2NimFhH5cfFjTPxuOubVFaU5JWuCQ0k929FM1QS4915HH1jef8ajKV9lwYYSfr3aQ+L+kj6N4eebWuhHi/3I7W+cwOMpEs2QPCLm0n35xuvt6gYmEjvzxL1xtCtXXkiPl1jt/tkrj9VoVKZ1iiH3edDVGGaWlhRt0LRFLvcZfa3X8zQZtaxrOkzBbTxsdFERkQRHQ9a2tpoqGXH5o5fd0Dymic8PBwljTxoq2dqL8SkxhLiogkPjSAmIQElFTW0tbVRiQsnOCIWZTV1tDQ0UEuCq6yZ+KPPzgrQJo/d18eb/MbJ6+C+3TNF9IpovnmVuFgifYIhryGaKZdYzBbb4+JiCQsJRi+vrEwgo0MRvWQXK8mR1u5GGbWf3t+zC2hzOt8Z9S/O25swrULofdk6LaNT/vPfMzv2MtT7eONLIfKnsbTufw4ygxOzArSJTWd2PCqil+wVr5NHDxWVtGtMc8qPtNpVJN7k52VWn119yQ6g/fr+LSjdpliRQza+v633/exN/vwFSe9/YXFx7wgL0UIvb8alXYrE9C2N32dvDPMXREnBvWczq0/r2nEfvQnTLIheXsU8zaiPmQXa+LhYElBCSVlZoeXCFNF/0ah8o3Qigbi4BFR+ciZSGGiD39xi/9b1bNr8lLjKZRk5fjwdaxTJlv3KUw6KON5f3IyF5SwqLvBgUfuMF8pPa1AFvT7NPEsrHM54YVy7C+7u7tT0XonlnH28UzegXfcxjO7djAKpP8XOaITmwr9nF9Dmwq6JkOQO5ATQCnNzvwPZAbS5v5f/HxFmN9D+f7j2c/dScaAN5b3nLd69CkNV8qYsTp2S1WtTJK9mOv9dUUQfwIs7N/DzT4CEBILV9KhS63dZeU2yIy46iI/PrnDjmR6tO/6O5lcf+P08OVAMaINesWSyBXarztJizDnWTq1Bfu1vfJKdlf7HBHFgnhWW69Q5eG45DQqlrLnMTNPBB4ehb+6aBLTtKugR+f4Wc+2scDkUyuA1e1nYtUJmmsyVWgG0uTIt2RqUANpstfOnaUwA7U+TqgwDFUCboUW/nEBRoA3w3ITr+kvU6TGCcvoRXNmxkkcxTRho/yeF09hOOX19XwrLZ1k/XZ2K64FI2v05iELK7zi6dC6hFccxwLoF+eTQGvXpHpdOruXiqfM8Ue3D3BVjKKj632uGf3QCFQDaWF6cccPSYhzn3jTjYMhROmRU8JeFXkUFvGFm3wbc/m0eW6Z0w0Djv5UcSEPwmIRS0zkpgJaEaO7sm4PlkOl4qo3g3Mel1MxCvLnhVAG0uSELORuDANqc9Te3ti6ANrdmJvNxCaDNvGc/+xkKAW3kW04ss+WcliVThrVAQzkB30uLmeGyjWazL2JeQS1lqYBUP5FzWhbJ9EuY4bL1iz70Du7jhvKphTvjupdHTSmed3utmbnNmwHz9lOvqCpK/qc4tOEhxdtU5+WuJex/X4fZvz7QRnDJfRIWAxfxrNZ03lybhnTlzs9nmDZ3N699wshbvCqDBw9C/9UBHDeeIiIairQfzATzBuipxuP76SlHN8xn++mXxMQpoa5igpGpKlqqKtS2c8Oy+Jdh+/7kJBr3O8Mwd3dGtSmH3/X59By/l4jIWFTbu7Cr6UscF67i+rsCtHJYgn1dDS5ucWXu+iMExJsxdb077cqry6bp0wJa4MOVjVhYWPCvZxVWe91hcMmf+7YRQPtz50+R6AXQKuLSr6cRQPvr5FQA7a+TS0V7ogjQRrzyYNXciaj8sZ1hbYvLtmB+uZ/xttOJar6MRUPqo5KsDCBt/QHG205L0ofeWsmU2SuoN+U2ParLgfj+Yizst1Lbeh3WbSskq9H9xPl5tqx/WgmHXx5oowPZ5zQIy2l7CertTsJWi6RcPlxsQaXRG5LNgEaxzKoMI1cH0mSsO7sdLNAOu4t9l7YsvG3K0p3utCl0nckdR7IjtiJTrXrRePhomkkW9Jce4ewe+huTvFrgvn4u9U21iIsMYPXMPoyecwyTDkPoUCk/IS/vc/jwYXxCGzJoRjn0I5V44nGYk1c/YNjYkbP/2FFGskxSOkAb/OgolpaW7L3mw8jDYSz5I4fKJxQd9VnUCaDNooE/wekCaH+CJOVAiAJoc8DUH9SkANofZPwPvKwiQOv/aB+rXJZRcuRmuv1WSDYbG3iRJcNG86yOI/P+lszafql7TdSXGLmJ7r8VTlP/6eQknJc+pIvrXpoVlq2nzqe9TB3sjPHAlQztVB21pI/t/p+ANsKP9ZO7YbnAA1IBbVrAeHZaTZrMvJkEtHGP59O6xnju1LTm3tF5lNMIZuGwRthuhake55jRONlX9c+3UqfZSIoO3Ym7fXPZUkYxwRxdOAxL2634tF1M0NG/ibmzRzrDevhuKJ03vGNzfyPuLbeko81W4gy6sv3mblpKVlNSAGi7rnvJ7uRTxD9w8P/XSwug/a/O/TznCaD9eXKVnZEKoM1ON39sWwJof6z/P+LqWQVaT7NxzJreA8Nkqw98C2gT9aGn7NMG2oGO5O0xj6H9GqOTBMkCaGVjIw1gTA20CW9X0ansUC6W78/F08uopR0qB9oCuHnux6rMl4XJb8ypTuOF/rgc8mR4HfkWnMmBVg7UyWdY7c4k4NgE7q23pNXf64nRE0D7I25ccc2cdUAAbc76m1tbF0CbWzOT+bgE0Gbes5/9DAG03zeDGX8UlsUZWv3YTywb1YIJGyIZv9yVdsWeM63LGG61GMu9DZMpaigD1/iYm0wo3Y49dedzfdufJFUhCKDNcESIGdoMLfrpBQJof/oU/qcOCKD9T7blypME0ObKtORoUIoAbcDj/axysUGr23GGtyshq6H1v8DC4aN502wJ8wfVRTlZyYEi+g+nJjNnyXbqT3tCrxryGlrvXUy2no+p9Tqs2pT/P62hzSTQHh1Xij8WvEgqOcirEsLxFWOZvzuAKnXLoq0OOsXK07VrV8rmS1wpP5anO+xoPHQDXTc/ZFn7JJxNWXIgZmjTvPkE0OboMylXNC6ANlek4bsHIYD2u1ueYxcUQJtj1ubahhUB2uiP19g414YP1Rdg37c6KkpKxHhuY4L9MqqM3otF/QIox0YTFauKhpYyMr0tH6rPT6bfzgT7pVQevRfL+gWI9NyKw+Q5FLY+yV/NC0jrbKOuOjDc5RLdZmyldcW8yfbO+H8qOYgOZI+jBRYzDhCauob2/kKKVhmLb4GqTJztSCODN2y0G4b7U5KAVun5dnq1HUh4zWEM6loLLeludFoUKVKB2rVLoibZbSzyDWtGWzLmdlWunVxA+TzJxmdUADsd+mHhcISINIB20G4/1nQ1TCo5iNStxZpz1+hmplgN7bADwazomPyCufbeSDcwAbQ/X84yG7EA2sw69mvoBdD+GnmU9EIA7a+TS0V7ogjQEhvEra0TcT2ry7h5TpQxCOfJttksvpSHSY4TKZInnBdHd3D2rj5tbLpSOCEkST92nhNlv9KroBTlzQmnHuwP7oLdjFEU0fXlsoMVW6I6MNXOEmPtZMuhRr/h+LyJbH/1G46//CoHCeFcWGeHxeAleNV14P0lewonZjMmgO1/N6C361P081enm/VkWvja0dv1ETr56+K46iB9Ku2jUxkrrqvroKOjIf9fgTKamnnI22cBD+d24tOtnQy1tCB2yHUOj6iYYqwEXtuD5R8D2O8bBvomLDp8mqoei7F0XMWriFiKVBnO2uWD2bvYkjV77xCvnJcug9ezzMoYJ6v+LLrxHFUtPTpNms/q8Rbk1VTF++pm6SoHxx+XwfXpQ4aWVnR45k6dANrcmZfsjEoAbXa6+fO0JYD258lVRpEKoM3IoV/v7woBreTb91BPjq2Zx6n7HzEzMiAithh1rUdQ36wASshnUI/qM/rEfCqpqhL7Tb3Mx6iAa2xfOBfPAGVMlKMJztOS9qP7Uym/btLuY3fXT+DEY29ePLxNUIwWJsUKUe43c5q1700JU52fLiEZ19ASi+fxxVhY2HDlYzdOxe2gWaq9DkJDZf3WTWPDhZB3J7HtO4KLumVoXK40asTg9ewCx47dIyqmGutenqP0KTsGDX/MtKfb6VPUMIdNjOHh4flYWtpxPWQAFyLXUz+Hr5jTzQugzWmHf3z7Amh/fA5+RAQCaH+E6zlzTQG0OeNrbm5VUaBN7ENcXBxhoUHo6SvGQYroIyPCSUhIQEv75wPUzOZWAaCFiHfXmDrSkiUHIxm57xSzOxZHssyrIoe0pvZwSdzXr8eiron0lNhXZ7GwtGTL3Yrsu74Yz8nd2WtoxWGXwRjpqCjS7H/WxEW/Z+8ca0ZPv4qJ42au2bX6z23llhMF0OaWTORcHAJoc87b3NyyANrcnJ3MxSaANnN+/QrqzALtr9DnH9kHhYAWonl78wAzps5iu6cRPfq3oXe/fjQrUZCM8PPm7v70nuRB0So9adm+Kia85/GJC5x6G0TDgQ789dsT+rVfRL057szsUwfNLOx0m5GR/pcPMmmtOw9v3SZfrYnMcragcl758mAZnZyL/y6ANhcnJ5tCE0CbTUb+ZM0IoP3JEvaNcAXQ/jq5VLQnAmgVdSp7dAoCrXRelUCfD7z/HAIaWhQobEI+bY2kWoz0womLDeTty/eERaujpa+NBlGEB0WAjj6mRQqjFunLy3ehGJiYkE834/ay0u2YQB+evv+MqoYW+QqYYKirkXKP5Kw0/gPPFUD7A83/TpcWQPudjM5llxFAm8sSkoVwBNBmwbyf9FQBtN83cZkA2u8bmLia4g4IoFXcq59VKYD2Z81c1uIWQJs1/3LT2QJoc1M2vk8sAmi/j8+JVxFA+339zpGrCaDNEVtzVaMCaHNVOr5bMAJov5vVOX4hAbQ5bnGuu4AA2u+bEgnQShZh7fd9Lyuulp0OuB72/P32C/9+ebSli/yK4xd0wCcwguDwGMwK6/2CvRNdSs+B2Lh4/EOiMM6buAmN8OpndeC1TyjFjHRItqL9z9oVEbeCDkjuX0nejfQ10ZPsKiWOHHVAssmaOH5yB7o7/asfG/NleeCfvDsifOGAcEA4IBwQDggHhAOZckAAbabsEmLhgHBAOCAcEA4IB4QDwoHc5oAA2tyWERGPcEA4IBwQDggHhAPCAeFAphwQQJspu4RYOCAcEA4IB4QDwgHhgHAgtzkggDa3ZUTEIxwQDggHhAPCAeGAcEA4kCkHBNBmyi4hFg4IB4QDwgHhgHBAOCAcyG0OCKDNbRkR8QgHhAPCAeGAcEA4IBwQDmTKAQG0mbJLiIUDwgHhgHBAOCAcEA4IB3KbAwJoc1tGRDzCAeGAcEA4IBwQDggHhAOZckAAbabsEmLhgHBAOCAcEA4IB4QDwoHc5oAA2tyWERGPcEA4IBwQDggHhAPCAeFAphwQQJspu4RYOCAcEA4IB4QDwgHhgHAgtzkggDa3ZUTEIxwQDggHhAPCAeGAcEA4kCkHBNBmyi4hFg4IB4QDwgHhgHBAOCAcyG0OCKDNbRkR8QgHhAPCAeGAcEA4IBwQDmTKAQG0mbJLiIUDwgHhgHBAOCAcEA4IB3KbAwJoc1tGRDzCAeGAcEA4IBwQDggHhAOZckAAbabsEmLhgHBAOCAcEA4IB4QDwoHc5oAA2tyWERGPcEA4IBwQDggHhAPCAeFAphwQQJspu4RYOCAcEA4IB4QDwgHhgHAgtzkggDa3ZUTEIxwQDggHhAPCAeGAcEA4kCkHBNBmyi4hFg4IB4QDwgHhgHBAOCAcyG0OCKDNbRkR8QgHhAPCAeGAcEA4IBwQDmTKAQG0mbJLiIUDwgHhgHBAOCAcEA4IB3KbAwJoc1tGRDzCAeGAcEA4IBwQDggHhAOZcuB/lXjrvKleai4AAAAASUVORK5CYII=\"\u003e\u003c/p\u003e\u003cp\u003eTBI, traumatic brain injury; TXA, transamine\u003c/p\u003e\u003cp\u003e*P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ***P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 compared with sham groups.\u003c/p\u003e\u003cp\u003e## P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ### P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 compared with TBI 1.5atm\u0026thinsp;+\u0026thinsp;vehicle groups.\u003c/p\u003e\u003cp\u003ezP\u0026thinsp;\u0026lt;\u0026thinsp;0.001 compared with TBI \u0026thorn; vehicle groups.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAlthough TXA treatment showed a trend toward decreasing injury volume at 72 hours after TBI, the difference was not statistically significant.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAt 72 hours after TBI, TTC-stained brain sections revealed a significant increase in injury volume in the vehicle-treated TBI groups (1.5 atm and 2.2 atm) compared to sham controls (***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Although treatment with 10 mg/kg TXA showed a trend toward reduced injury volume in the TBI groups (1.5 atm and 2.2 atm), the difference was not statistically significant (n\u0026thinsp;=\u0026thinsp;6 per group, Fig.\u0026nbsp;2).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eTXA treatment did not significantly reduce neuronal apoptosis at 72 hours after TBI.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe TUNEL assay revealed no significant difference in the number of apoptotic neuronal cells (NeuN and TUNEL double-positive) in the peri-lesioned cortex between the TBI\u0026thinsp;+\u0026thinsp;vehicle and TBI\u0026thinsp;+\u0026thinsp;TXA groups (n\u0026thinsp;=\u0026thinsp;6 per group, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Consistently, the number of NeuN and caspase-3 double-positive cells showed a similar pattern (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eTXA treatment did not significantly reduce neuroinflammation at 72 hours after TBI.\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe neuroinflammation assay revealed no significant difference in the number of OX42 and TNF-α double-positive cells in the peri-lesioned cortex between the TBI\u0026thinsp;+\u0026thinsp;vehicle and TBI\u0026thinsp;+\u0026thinsp;TXA groups (n\u0026thinsp;=\u0026thinsp;6 per group, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Similarly, the number of GFAP and TNF-α double-positive cells showed comparable results (Fig.\u0026nbsp;6).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure\u0026nbsp;6\u003c/b\u003e Effects of TXA injection on TBI-induced neuroinflammation, determined by the number of GFAP and TNF-α co-expressing cells in the peri-lesioned cortex at 72 hours post-TBI. ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; n\u0026thinsp;=\u0026thinsp;6 per group.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTXA treatment did not significantly decrease the pathological severity score for hemorrhages at 72 hours after TBI.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThere were no significant differences in the pathological severity scores for hemorrhage in the isocortex (n\u0026thinsp;=\u0026thinsp;6 per group, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e7\u003c/span\u003e) and corpus callosum (n\u0026thinsp;=\u0026thinsp;6 per group, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e8\u003c/span\u003e) between the TBI\u0026thinsp;+\u0026thinsp;vehicle and TBI\u0026thinsp;+\u0026thinsp;TXA groups.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eTXA treatment did not significantly reduce the pathological severity score for necrosis and atrophy at 72 hours after TBI.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNo significant differences were observed in the pathological severity scores for 弓necrosis in the isocortex (n\u0026thinsp;=\u0026thinsp;6 per group, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e9\u003c/span\u003e) and atrophy in hippocampus (n\u0026thinsp;=\u0026thinsp;6 per group, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e10\u003c/span\u003e) between the TBI\u0026thinsp;+\u0026thinsp;vehicle and TBI\u0026thinsp;+\u0026thinsp;TXA groups.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study employed a LFP model of TBI in rats to evaluate the neuroprotective potential of TXA. Mild (1.5 atm) and moderate (2.2 atm) injury intensities were applied, and TXA was administered intraperitoneally at a dose of 10 mg/kg at 0, 24, and 48 hours post-injury. Contrary to our initial hypothesis, TXA treatment did not result in significant improvements in motor function, reductions in neuronal apoptosis or neuroinflammation, preservation of blood-brain barrier (BBB) integrity, or decreased serum D-dimer levels at 72 hours post-TBI. Although a non-significant trend toward reduced lesion volume was observed, it did not reach statistical significance.\u003c/p\u003e\n\u003cp\u003eTable 3\u0026nbsp;summarizes previous and current studies investigating the effects of TXA in TBI animal models. Our findings are consistent with earlier experimental studies reporting no significant impact of TXA on coagulation or inflammatory markers in TBI [15]\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eand, in some cases, even an increase in lesion volume when administered subcutaneously at higher doses [16]. However, our results contrast with other reports demonstrating beneficial effects of TXA in experimental TBI [17,33,34]. Several factors may account for these discrepancies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Studies of TXA effects on traumatic brain injury animal models\u003c/p\u003e\n\u003cp\u003e\u003cimg 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fwgDiaWCicBOYEqSrEvVXjyL+wjaNqvE/40P2/M37bbEisAgzGafEWiCFk/yQ7Zq/ayiiqLBXoJWTIAjbnd/XComEcTsYVbQ6ovx4TP6AXdjSjivS9Cq/LMf/+ZtqrSIoMVDxgAeYhS7xaWu7XMVSWNBxEvOjN08QStZYPvioJ9dtyWlOBQXuia8V7GnRflv1fONMX8U4yWI+I7dKQjiwdnkxHJB5xPyYglcZwWtGCLhgAOcLCGQ1NJYdJKqa1tS4OdZvPYTtPienakeG6f+WK2KxcrfX5egbWto+4KJYORoyE7nZZizgtYgImeClKhF2kMFrWkPVTGkzAFdi+htgpYQ3OvvTfAJWgKpKkPLHvcSAqsIWu0gVkwnqZ7IsNoDH/sJWrgKbjAUbCUJnHodglbQRrivzGoLDFV8ZXEcicEjbwQvG1YNgBsy6R+mQlSIJScqPWMUtBIDlX32y+EFGAHe8bsHCFp2JtARqKpWBC3hKjjJus00EAdsH6aLCloVEstvBF3kRriqdqg89QWtyqQAIXlS/fAgxjaOdQla9mfKUnImuAtcKgKIm9iUdPCjeYK2VWkJ14MELaHiPEGZL5qqM91JLPqfGNmWoCV+PHfAz9t6X4lLW0KCk4x9E7SCPh8lAAgDvMW2FAX4MptTtT5I0AqY7EUSalqduMW/iwravn0pVKiIalv/wSTVRxzdHlptayEFQlyN+1c5ZgUtkQwjdmP62UMyAjoh6HMCHD6Wb6hE80efsTv4EUTOVV1t/i+hxHswImwlAWyo/1BTE7TsiMggTEylK160pUXzKrRmVPit+2oPsa/QoGgjOZEo8334EeDGV6KmDcSNa0vwCCOxAcf0H0pr2C6y5EAFVCyWBBKZTfBI3B0SFhw3pEJrlqEt/zAm+FDSqK2LCFr6AQ7sCUebqWT7EjkxTKHLjIP2tlkuPkLjKObsqsjVPlwuaeKP+FuVnt+z1zaW9BQhy75goK/7CVqJGNtho2xd/4ncdQnag9amr+LTS393k4LWtBZHQ8amBhyyzn6F1hSCyiACIAgYpkDcr/DNq9DKtp1PgFg/g2gYvMDWnsIU/Pb6O2FGpCEtU3EIRCWtTY/MA3RVQWuKTUUIUXFwRIToZdaqBIyuLTMQqAQGlUH9MzXAGLWvPwU0pEI7b8mBSjcnIiBMnRsDxIsgkLuszbQmLDkQUWcKHsEZMyKgOZqkQICE49iWHLSHwuDNBlvmS1CoohJHqloqAW1ZAPtUXULMKiSIQnBDqAiJsHCu8TSNiXwELQHC2rtFBK3xYMPWVrm+6U4+Ze23/wlX9ydsVTrMMiB944UUt/GA2zoErQqL9qpOGQtVNP1VbTMm8BfAiT4zQfqoz4IALpA4CP6CHIz9nTCVOBrLVqGVUPJDfEQ48g2iAIam5lXRVDMFE7zDH/meBEeVDT/ttSRpLxLeDx/JrLa2ZVRmACQrQwQtEYsP8Ct/ZG+qugT7foIWzoQ7DmKTbIXQ4O/LCFrjpQhAfOuLMVQJN6baJCGXzLVZHe02bt7ugONWfbVaX9Cqdqpo4iRCFr/jNvch9AhcPEawigHuTVjjYLgQtDjaWLMleIhZ+oVrJezshsB1rf6bZST1xkHCqf8KLqqNRCpb5fct4W+2YlmE5InIsLYbL1t6o5LGTiXVhAwbZI/azUa1QbzSVnGuzaK5nnvNe63WIoKWLjBuKp4t7mgbv9EW442bJJ4KUK39ZvcURPpraPkmn20PifHTRQSt7+FZeOM/fEiowUEs5bvENTuGhfa6J+Hf2ruqjS0tsAZ+UVJJz/BncYceEGcV6FrS5Hc8iBvEW9xhdnZehZZNswNJK7x8lwDGg+sUtOKQOGiGZycE7qqCVpVDKZvjWVeBFGRtDoIR4ByV0EEaHF2AIqY4GBHk++3daxzRoHEIDsuxfUdmKFthtKoaqjemYg0OgnRNBMqwiUAGj9yJ0PZ3RM9otJOhqwwIeIKJjBOJzVsv1GxyGUGLjARK9yYYOTxiba+/aHghK85I/CBQ42L6UOVEEBXYGfdsQO0LWsTd7591XA7XUlVQ4RJY/I4IJA0OhEsoIH1/Mx5Ip+GBuASHdiBsIkJl3TVUjeDZ7ieoqFq2CsWuZcbsgU2xrfb+VgTNvgh4R/s7u1VxbUtSkASMJBkCnkqJA+Ga9nauz0wjG2f4SLTYtMqL8SFO2a3AD3sB2VSo4MAWEZjxZpuEiWko+LIN1Q7EhMxVNFtSwT/YF6HgfMGQ/xBnqkSbPJYRtIIUH4YPXnDwy3578QeRTlwK2OyzrcXzM9I3Xv4OJ4kyXD1AaTxhKlAIsIQ+e4U9MULIGVNJJZHL59xfW9it6xsrM0ttiQ+hvMzymYPwwX3WDbKf9v5cnOH+hL2ZAwmRMWe7xGjDg0/7WeVP/4gh5ysmaDdeIcbbmwrcB6Zwg4GKn2ULqlx+JzwkAoSXoNmWxbg2X9EGlcj+we7Yd3v6HL7NTwgutjsrKNgmUYZvF00Q2r0lI+5DiPfjmHtK9iTqfKTxpzaIL7ir9dW1+JTERX9VJoktXIofVHY9+yCmSQ7xIBshDIgP3ObehCZhQUT5vpkafTSOxoOwhjH/bFunWyogTrmnA4+yVWPZrifGqRyblSAuJcsOfdEGDz3yE+OpH/hjdgat4bWIoG3fgYPYoM/z2s8ncJXCCD60zIMtmHWQJMGLuBJT9MMyDe2UROJICY/zcRT/kwSYFRRz+Bp9QUMoOLFbSS57NaZmDPk9/Ils9k6HaC+f0l48jld3/YAhv5JQ4W9+iM8USNqMMQ3B/2BGuxgTCZU+w7stVxGz2L9YBDMYsnkxvT08jvucw3fpJfdsBw5iy82vxDH8YUz4Mg5qh5ljfiMO7UScX1XQ7rqhrLN9ywjadd5/3rUIWuIFWez3iiZrYlQLTL2YDtzkIYAKpALtrr62a5P9n9q1DxJsU8Njtr+Fz25ZgCTKzFhba0mA4imiYCeC8obgWkbQbqgpddlCYDMIlKAdjusuCVrZl0qKCovqE7I66CEgGZ9KjyqO6vUmDlUH6xJN+7WKzSbuU9fcHQRKsO0/FoXP7tiqlpg98tyE6hIBa4rXTOFBL/nfrV4s3poStItjVt8YGQIlaIcP2C4JWlMqplZND5hGHToVavrBlMEqL67fDzHTiI5NXX/4aNWZ20KgBFsJ2m3Z2jruY6mC9aBtm+5F+HMd9z+sa5SgPSzk675bQ6AE7XCod0nQDm91nVkIbBaBErQlaDdrYXX1dSBQgnYdKNY1dhqBErTDh6cE7XCs6szpIFCCtgTtdKx9vD0tQTvesauWD0SgBO1AoPKNCd400J5SHf7NOrMQOLoIlKAtQXt0rfvo9KwE7dEZy+rJHgiUoB1uGlWhHY5VnTkdBErQlqCdjrWPt6claMc7dtXygQiUoB0IVFVohwNVZ04KgRK0JWgnZfAj7WwJ2pEOXDV7OAIlaIdjVRXa4VjVmdNBoARtCdrpWPt4e1qCdrxjVy0fiEAJ2oFAVYV2OFATO9N7d+3wY0tNO9bYCccrgezOZmc7O4XZscUuRXb0ajsQSZDs1NI/bHtqNzk764zlvZjLCNo+Pv2dZ+wK5IX3/b/bDceOSnYScuAsu6bZtcauSHYEa9uq+nt/POwAZRecvcbD+XbpuXhe245Qdq5q1z9efm5DEuO1zEYhy+CzDheytaxtcb2myo5S7d3Tdgyyg1PbYcmuQw67GtrJyk5LdnRysEc7BcHI57a+PsqbD6wD9129xrYErR3lbJtrO3r2Yqc026Lyc7tS2SXMzmJ2BLNT4l7ne2+6ncC8atLWquy3bO8YvOziZctpO8nZIa3hixPha5OQhq/d3sQnz/7YEdEOeo4jiW8J2uH0UxXa4VhN5Uxba9pO9B25x7btH21hbBtDW7PaohG5t80sEIuXuNudiFiw9SoB3A7i4ZpJWLZjHsOxjGDDO7a/tXWpLRxtxWzLVNso6j+h3/5um2gbgtja0SEwEmReju9/n7d9xI3H1boNR97ZGw9bGiN542ELR//bxtR+7w73I4ptC+1/bTN+xsU/7yy1Z7nA3N8icujYLIPP0GvvdR7s4PCJ3C4VVrau1G/bh9pe1UG43yu3CLa1KhEiUPq7wGl82LRkzH7wtsIdS6K1KoZH7fvbErS2YrUFri1n+R4+5Gv8TEJvp0q2aVtgW7vOOx9H8nvXILxwqK2hW6J11MZmkf7A66yJDWxhDF9xyHbLtl6Hl6RBAs73bS2skIIPfEfs8blt1M+W44EHJO6jPkrQDh++ErTDsZrKmfZWJ1ZtbEEI3CH3Jrcb0beTaJD4NTrieFVXAftKbruJeAgM+5mr7PJDousMKXZtZXyUBW2zD3utw+fuHVZnzErMbXvVRHu7/3YKS6JXJdY2zg/On/3fKg6uudd4XDfH42V5P+NBwLVq+nVSQNtGenbHPfc/fo7fMnZ9GILWpisqszYNELwekJVvVZqHZKVMtUvFRiCzqx8RbIc/SZYk4dy597uqmqq1feBVyd66DAj1nUNHYFuClg9+Lv1TAm+mio0RVOxLsqTCyD5VXonf/vm2TsejbM4GPadIe31uCdof29A5UnjiQr4J3/vkbIyZPSK14Ss2wdbs1iUTV2OiKND4weZMfNuOecRwKw4cusEu04AStMNRK0E7HKspnqmKd9MUBATpxzP4nyqnzh7T2w741B053zIiTIkTEyfuzr1QTiH57PcmJGhVawhNmBBfXo3XRCpBi6OQsOqgCoKqoqUcx44ImPYFbd/ujMdNcsp8djxMxfuuBMNyhL0Eran2u2Vld3Z5yFAbPwxB22+bbbLZk+oMfFWo/Q5XIgevvaurTlte0Re0trEW6FTOCX8JmOUfL66p36FDv1PnbUvQ9jt9xazsPysi+OATk9eukNVEXPeD3hfa+QSa5QgXSFt9f0RINmvJwf80KXhZLgWbW+fSLElrw1fC2mYAYYkP8VlbvuVq+MHYWB6CB0aNcQna4ZxTgnY4VlM70/SswE8gWTN7z1zDZD0ooWYtWBO0ptgv3E1hnyQzYgTi92/kdC47m5KgVT39TldtIPxMK/bJlqA1Ta5iA1cVCMsPHAh6L0HbxkOy4HvEmMqiwGg8hgpa1SFrmlt1eBm7PmxBqw8SAOtoTUW2ijiM9hO0lm/4zr07UfLerAJ9rJtJeMMyINR3Dh2BbQtaa1/5mfWclqxYn225izXb8wRt/3ziSqJ5kTzX7IFElz/XcQwC8BJXrJXdC98maFVkLfn4WieAPSfQF634wXhYHvcPYwe3BO3wESxBOxyrqZ1pCcGv5ZQsIr5jTtu+KSJmK7THTVH2tpwGRygv6MSFh3gQjWqtqR+ZNALa9WMVwWbJAeysASOcVGHbWln9JmgJUoHNutaXdBXC0+dUuqnJvQTt7HgQxJ/prtHGY6igtdbZ0hHr0ZatXKyCzzrGXuVGv60/hNn1O/xulf3ZT9CqTluXp6qmimY9nkq5Kcw6xofAtgWt9dhmT8wM4EZLDqxT5w/zBG3/fMsN2nGiTEitvVUgqOMYBOBlSYaZQPjeJWf8LGGbrdBKYsUXS4b+ZQZAM4WSfcWYZTluZ8akBO3woShBOxyrKZ3pqXEVMJmyoC8btobWWkwVRWtrTX8/MtcnERMeWjKFTfz2CQZ5eyPCVCq0prpUAk1tq85aQ+xJ3TZNZi2Yh5JMh3tAyVO93nhgvS3SVvFR3e0fbTyQtAeYVCItKVDF8KS+QNDGw9rnvZYcWNJg7amHKLxNYdnjsAQtOzTFSIB+KN9UcMrEkQ1aO2cdsZ9VZmbX0Lb+ErbWEfsue4ZZHeNDYFuCtr2FhC978MuaTEtdzJJ42IvANeuBK1UF21tF+uf7jL862Ck7Jtys85z60fCV2EtUG76eQyD64Wvpm0Qcvtb/48q393jM+tv21gkzYHDl5z4ftagtQTvcPUrQDsdqKmeethMDt0vxajH+b6SwNW3uiX0PdsmeVVyJItmwp3ZN+6jEEmjEbTumImgtu1A1MJWPg6yZI2JVYFVYYwDLAAAgAElEQVRoreVUFRQEiTEVXDgTmaYe4Wj6/ElJ4tbbOU6T5wmGxoMII2xnx8O0OewdxsN9VM4lHR6kcHj614MU7rEKyR+GoJUAsD9LWcwEEBTsj8BQsbVuTsKlba9J0W/NrP7D3j+HNxu4lqBo+UFN+Y6X2bYlaD2FT4Cq+LEX/EfIqhBK7q2D52vszjnOV/l3bjvfU/leI+cf4cWfcegybxkZ74jNb/k8vPr44i/+7jPYKY5IEBof4oMv5BIErzgkdCUNkn/8MOqEtQTtcHMvQTscq6mcqVJoOrwdRBkikel6eOlcvQoZ4aTS5elSB+JQ1e1X/6yLulhOrfVf57XLeC4j2Ajaho++WVaAcC0r8EoaDzbov6UDgpl1eJ7c97Nqoid7iayv59+aoFXlMR6N1/Ybj4apQEu4In9Tck3QGi9VC21Z5VgGn1Xu57uwIVAlSA64qcKoxghelh74THAzQ8Amva9SQuB3eDu8OoktSwpKTKw6Kof7/W0JWm9rwXvNBz0bwH74KN+U9Jt1aUtX5p3vdV7WyJttMQNT9vcT25mHFz/mz/CVxMNP4qCKS7TiWwc+VMXl787FD8bJdxUO8EO95eBw/XRrdy9BuzWo60YjQuAwBNuI4PlxFZRQXKXKO6b+Vlt3E4FtCdrd7H21ahIIVIV2+DCXoB2OVZ05HQRKsO0/1oXPdHxhl3tagnaXR6fathYEStAOh7EE7XCs6szpIFCCrQTtdKx9vD0tQTvesauWD0RgiKC1MPvhA693lE/zAmNPWtZasqM8ytW3RRHwHlkPbdWU+nzkCp9FLarO3wQC1uZbq+5VT3UUAmNDwBtWvLZt3zgzRNB6WMK7NKd+eALYe/RqP+mpW0L1v4+AtzR4qKqO+QjAx6vCSvCXhRwmAg+LiGfmbm+H2Y66dyGwDAIeLtxrV8j/e70hgnaZmx/F79SSg6M4qtWnVRGoJQf7I1j4rGph9f11IFBLDtaBYl1jpxEoQTt8eErQDseqzpwOAiXYStBOx9rH29MStOMdu2r5QARK0A4Eqnu/Wwna4VjVmdNBoARtCdrpWPt4e1qCdrxjVy0fiEAJ2oFAlaAdDlSdOSkEStCWoJ2UwY+0syVoRzpw1ezhCGxb0J4s9x+2f/hHD2im7fFe0G3T+Jh8um14r35ypv7ZKeNauVe8/aOXPTZdobV7xxNy20DbUtquEwb2trftn+3r5h36aL96O7HsdU7/e863HaF96p/e2wJ09trGSp/v2m2T95ncScmOI3YOquOY3VaMl/F5UbcLi7202+5exuPe3SL2u+SWoX+au7I8dexbC84Z+E0LWjvf2BL31N1T2lfOXYZaM/iH3da8ieWOuY/583MrWza7C8em8dmrj3YE88+e7n2fZbdw87YWnGFrW7sxDeGOXcBzG22wQ5wtQx/Y+fffdG+3uWLuUOfeOJAdPjEiPh0R1+9s8nIRcYpuNzv+jbd38diGoLXToTeeiLniy7NzFyp42LZaG2x/+9CI8NT6s3JraTv01UOTB1sNfF+cuwDOw/c5ie/j068/mfFn1Lt/HQzL/xR8i5y/6rlX64j0bhmgiKlNA428H5J7G9+vC3q7LGgbtt6kYBtQZGD/ev+ulPsvz8Pfvs1X7Yz8XQP3WkfWV0mh6tpe5TJ7/HSSNlF20xS0tm0VCG3tWsdPEHhSvgXk/hngELPtVL0V4wcRIXk7ysc2BNu589WBtmcUDNtWt2xSUvHoTCp2Eedt4DPbbz5+j+SO+2ZhoAmG2/TEGt/n37jYlsJ1/E8EYHjNbnvQP8jtgMUrouJeuUUzLPtbV+8yftsQtPpv2+Unp7DHic2uzhERfxgRb088Nx37d3ksVmnbLye+tqimafr48uN3TBnfbVZoT9DtvY4AvpD7ND8oqwQy3gt1xn7i/He6zOQEgpt3e76/OkmDGP5aRJw/hdXLc6/xk+b59mC/ce4Hb5BVatzL3tE3SNIeg6C9T/ZXdfTO3Z7M10kBat/6ef27dgavd3dk+6j8LkFqv/bLZ9LwiqxyE78CHMzs80zQfisD3Hu6SvZnu4rOnSLiY1lJJ8o4iSqPn31PBg7bJipWcc6j8F3jc8FOGHyp23v8aYmLfchv1o3XFxO382Yg/EBWws6WlR3VMQT0yo6k+Mcd8v82XmPAZxuCjQ97jyZ7xQkqY4TFrSMCtqo9KrXs+yZZxWDXKuXs2daz2imgqqRJMrx+z++bfq/0NvDZS9CepLPJE6ZdwQM+z80+29Odz5thUAH3d7MyCg4EMRs0s3CmxEtxAM5seCrVNPyp/2dI3iReJatmrcyiPSLf68oGVSC9J1Olm39fr6viEh9e2/aWnCU8XxYe+Pu2MdyWoIWDgol4zdb0nT0pyvjsvVmsOVb6qtlHvugctog74fxHaafskXjz+1+NgRA33MaGryLW8zo99OYevj5T7RafL9vFmL+OiM/lrIJXB14h28b+3h8R+KHhazachhr1sU1Be4kUrMrgKn/IAIAIQhld0JIR+/1EHYl+NYmYIxC7hJVDgBLcDJCyO8LRD5kfkfzYbhCJPJsguK7rjUnQqijfIt+5RiBx+K8kqapOzfYP6VpSAR9C9N9TeMLyTd33Vbfg9+DM3JzjfW6mw02TGwPCwPc4Aqc4Swox92vVG9n2lxNTicW2CXlXHc30I+GEQGCuKnuejlhUDwU3IgCxs0/TlMbitjk2p81AyV4FQQkYoXaZLmkzbSSJ2fVjG4INN/xqCiu2x88tQZBgSfJe1XGChE7ShWeMifNwzEe6hM07DNmv8wi8N0TENXLZE2G3SVveBj57CVpCAR6ClRkcyRe7lGhJXj+cxQD2KNlnp7D520x4JVs4yNQw4Y8nJBVjqUqu6ju4le2IOZKfD2byeua0P1wsSSAWYWW2RuyyXIGQY6PsrvmypBdH4Hj4b/PYpqAlShWe+C17sSRIAYX9SUYVayT8sCByYeF3h6WICl8/ymThNRnD2pKFXV3Ssa2xhAN8JUf2B7h9VsUbvpZaWSZjMywxn+Cll5z/towtvq+wJfHw2bm6pZ2/GBGWLIwa320JWgH/ljmVLkjLClRUiDXBxBqlM+bGBRdOsSr4exE04ImueybRviwdQ3XLAFw0zzctxAlUujiR9YzIWNVhTIJWhVb1Ex5E+TNmlmbM9u/Xs5Jr2vXvZryKOJIQEP9wE7hgITv+/Qxgf7EHnqq9TdD28Zck1PETBNpyEPZHOMiQJRGqOio0xkXC4WdBxfqys6dtSiIcEggBEynxB4JCdZ7g2PVjG4JNYOTvpjOJBmKUX38+xYFZHHxCrBJlSB63mZKDoyTDIVEkQvCEA9n77KgKWgmoSiJbZF/82VImfMCn+4KWfVozKkFoa8GJX1iqSMKIMHMdVcdNYrYrNk/QEgjElnXIptJVuQh6iQJbIvQtS2CbbO83078VAvi3ZVqWkbkWXicYJGQS3W1iuE1Bq2LNx9ga/2JPKrBmT1RZfS4RaM+lKF4RsWILPnFI6sU+scqhEGMcpr40hqAlTtkRHOkqNghfvqsqy7YUDc2mmIVRMIHbW3tawgwufGkEB61h9ksCN9pjW4JWJYXIVJFy+F3ZG6CcfJ6g3UtQ7SVokYuBVh1zPdcX/MYoaBGmSrbgQfybppFBEe+z/ZsnaCUQzpMlq1YRugK+bTgZdwna9bksQYs4BDWZLnGlOigLVlVUNUQeKrOWazhPskJctId1CFqVCg+VeECHMCNE/LzrxzYFLbLmE4Qs/+AXEt8maJG9NbWqEwQa7FWF2g4zgithTJgJACpom55m2wY+szbS1tAStDAi6lVtJFrWfwpchMUQQUsIqZq1h8Zgq8o2hYMI/UTOAlpCoOpq+RWhakZGzGFbHnQyfSs2XT3Pb/5N0CokqIS5FiHns23vOLltQfupTJDYieq1woklVWahCDExCn6q/zCVfOK/9jAnQWspoipje5BZMQwvTvloghb/maG2ZNPsXx9fSxEsq1L59tyBB2bNytBEzY/FJMmX2QKHB8WJ2VE/9L0NQdvWyFqDhVwtBpflejKUESOEdQhago34M8Uje3bIkscmaIlwxmn637IAglQW5ollfZvt3zxBaypChkZA2bpYRcvPtj9UAfbQmbdHIAfnqdhYW0gsqIgjaBVcyw+QTFVo96ZQJI0oBCoVWlO2qrKy5bOmmOgLWtULyR0iIczgTsAKet6WYFqT/bIBgmTXj20INjhKglUbfjcDo2qiREKgRujWgfYFrXV3/kZkGBczG/yA4CBsiQoJtiUHmzy2gc9+gtaUrQor3CzBgBX7mxW0Ap0KIw6VAJtWVwViy/jHrMHUDqJANVqFUXIk2MNSYqA4gCOtPe4LWoUEvoxrrV9UHYc3XzejePH8DnF7FCu0EkaxXTz2PAzxKoHknzBRTfS/uNQELZ6jBWApLqkawlQiBkuJPcz5f5s9mJottv7iLYkWfPEXm2r4SqLg03yWoLWu25s4LGmTHPg7zeAfDqUxJBSKMfTZqPHdhqC1htWCbsLVE7WmIogmWYMSOEBVak3D+pnAMmimbgldDyZYOsDQVSkZuOndtqbucZntGURkrPoogyakZdWmzFTRDCbCbtO8izrEpl/bJWNV/RBsOThntv7PwxmIQRVK1uqBr37/TCWYqlHpFnist7WOC1mo0Kr2+h1mxhuOSIUAI25NTzB25zPyNybOMmVj4X/jZizgSwAYv6lnym28CFd2rPIFF5WY72bl0CunrNuUVPED1XGVMoHSFJvxEDAlKQhbMsM/BErXGcOrlDYt2ODGb62Vxw8Imh0icpVGNt/8RVWc4JCYEW8eBhNIVSydY80eH7LGEb4I/ZuLEsGC528an3nN6VdoJbISU3ZqDazghRNnBS3ekEipcBNapsklWBIAPIB3zDxYPnPU19DCz/Q2v1S1wn/WIRK0fF0skJiyIfYGKxxN5JpF4N+wFoOs7Rb/cIMlReKVYsW2+XMbFVpC1H3YER9kSzgNXmalLLXAeZJ5ekCS0JYSmFHh0yqF1nPDyfWINDMCOFFVcptJwIKuvvHT4SFBsBSIZoKvGSr2JHGCEZuzlIpApQloH3EE9r7XnpWBtcQDTyqe+Lu3nowa320I2o2P8pZusGlBu6Vu1G0KgbUicBiCba0d2PDFCp8NA1yXH4TANgTtoIbUSYXAphAoQTsc2RK0w7GqM6eDQAm2/ce68JmOL+xyT0vQ7vLoVNvWgkAJ2uEwlqAdjlWdOR0ESrCVoJ2OtY+3pyVoxzt21fKBCJSgHQhU7xUjU3w4YjhKdebUEChBW4J2ajY/xv6WoB3jqFWbF0KgBO1wuKpCOxyrOnM6CJSgLUE7HWsfb09L0I537KrlAxEYImi9WcArX6Z+eDLa65mm/mLnqdtB9f9/IuBl895YUsd8BAqfsoxdQMBbF1479hfn7wKQ1YZDQcC7sNumG3s2YIig9Xonu0tN/bhRvtLKK0XqKAQKgWMQ8AoeL/iuYz4CXhfo9WB1FAKHiYAY7t2lR/2Va4eJcd17cwh4B7H3Ou97DBG0B11jKn+vJQdTGenq5yII1JKD/dEqfBaxpjp3UwjUkoNNIVvX3RkEStAOH4oStMOxqjOng0AJthK007H28fa0BO14x65aPhCBErQDgaq3HAwHqs6cFAIlaEvQTsrgR9rZErQjHbhq9nAEdkXQ2tfZ9owXye3tbHdre1Z7iu/KsQsVWtut3iG3B/SA2oe69Xn/lQDZrvGG3cL/c+bWd++Ys3Wq9dDWAtsOtNYCr2ZZDW9b1tqO9TW97SxtE3qp3FrwU7m98OyWy7YxvEluJfzV1ZpyqN/etKC1xbUHMn8pt8C2hW07mj84h03bInN260bbOV8ofeIHh4DUpvFZd5dsnXme3HYUD9s+c5cPY28badxmi/RZ+7DN7wm7rVdtAfznc+zDVqvsw/rSde1j70Hqa+b2uLa+tW35qluK4gvbF7+h2+7575cYkG0IWv54u9zm25bf4lPbvhtfXj+3ZLV98Nvn2BYfF8Ne3sW5by3Rx6P+FfjeNvEVbz64JL6vOKprqXdB0GqDPYa9SeHFuf+6vbP/ICIQ6q4cuyBoBZtz5H7OBKv9l/8lAULMr+8SAwLqnkkIfRLlDPbOhvWVu/3Jv7QrwI60Hez2ZFm5F/Rv0e3h3oSpfckfHxEn7X3eHwvk7nzjZK9te2mP9di0YGO37JXterjqRT2gTh8Rb8n945+SSXAfRyLgeZlo3PmQguSm8ZlnN+wLhxJ6BB1h0ezvtyLiPp0AfFxEEFuzQksydp1un/jjRYT93v9txw2zbx/2smcfrU+nS/vA3ezjuzN9YR/+po93XVOQh99l0veJMsnYzVcszhhP17hHJ8qvtkfidtAwbUPQik9n73jxWRHhIR4xvCWRuJII82AP3vO2oNn49LAsBOjjFw/q0AT/3vB9ZkS8dw6+EqfPR8S9OuH7zX3wvfqQNwaMEd9dELQI4NpJAH/Yke2/diR0gSQfgR5hIVei4Z+7QdRmv/ueKq5sWPVLdt2qlZsYi10QtPqlv7JYwtTT5X+ZmAj6N8sM/tn5marFsTKLQ+Yq4U/s/kccBC2iJL4Qi7/PVhE3geNRu6anhy+eFR6EwgbPlQHS2Dw0In4+K0gI6Ydpqz4jKtj8Z9Kem12z5R+NBKhtCLbf6ET/NSLid5IrvpP27XVhl4iIZyT+uIE9s3O2jC9Onv4CZwJjlk82yRmGcBv4zJoKvyZ+Lpm2RayplLG/F3Q2d+IUeKp9zmV3Dng5ry9ofe7vsMW3u2iX7EOQZh/XjYhvZ3vNZrEPAkvis5d98GEiwRsAVrWP42YiwYdVhf3fj1/sDSfDXQxzP6LPzz5vvn/s5Hr4+wxHPyb7Ii4ay0X4YhuCVlu1u8Unb/jAbXC/YsanN2dBxrmz8QkWOPFRKWgrPv3vILAfvpJYMw3iP1uiFZr98Fvfhe+j5+DLt3c9eT0wJO6CoNUGUz4qMAj2fRHhnWMcX9Andi+bji8DRzoc+8I5/S7bM4UhA1/XlNE84HZJ0BJQBOwX0jiR6MWSNGDHoE2zPTUNG3HA7P1ZOSRoVRNbAGDoAh382xTRgcZTJ/wYAdWEU6VwkmComF8wK6+WdcCdDRMJxonA8U5Idt8Eraz6fDmlSGyYmXh6it9dh3kbgo1gOW0nUu+X1dgXpii7dERcNCJMbyJy4lVVkQ0TtargDgGWoMUP18qlIIKnGY5NV8e3gc9egpbwt/RFPy3HsBxJ9Uai9WcR8bZMFFQUT5T+T/xJHoglON8yuYXg+kiKjTYrtCu22ezjvllx1W79wW94UaJJ0Pbtg1i6VQrFJmgFdUsFLp/xRoURbosckgiCjA3iU0sgxC/2SOApJKiQm12w6+TZksclW2LaO3PphBkF43WCfF0kPnhEClpVTstCLFnCF6ae/X2/JTXbFLTik5knVVb8ZykBPzUL+4mMT7/S9c07mv3NP1yo6vjYxM9yQ7YrQSHMjCk8d30JzCK2ssy5YjV8JQjsB77wga/P4CuRuksWVo7fxZY3df78hLRp+BK0DV9xyffNjpvhHTW+uyBoDapswvpZa4TOn875/HRa5PCxnMogyAhY6+JUIAg102ZeGI2MNnnskqA9b1aiVF4YpODMcBGcjJigtbaMSIKZaUcVWNNxHICgdT7B63x4qmo4TxCsYzgCiNv0GQJhq4IN3AUj5ANvQQuuxgSxCJrEbhO0xsaYqMKovJieM7aWj+z6sQ3BRrAQWHCVQBAgp06bJdAIFoKWHZ8pbRqefJaAaILWmCDzj+eYWPuMT1Zd37jfGG0Dn70ELTHFltiehPXemVCdJEWtZUumiAlVNmo2wSwPIQhvvGuZB1FLxOIVuBLDu3SwD5V5vMg+jLckE6exD1PdBK1lWWdO+9BXMYYoaILWci4+TBTAYxn7wMWWB4hHeAFe/es9vEus7t5xseUQ9+8KMYQdIU7sOoyRyjL7JqaJF4KYuJbQSTiMp/c/i9/+6Zdr7jcu2xS0LT7hRGMhGSLM/Sx5Z0d+588fyGUZZq6IVoUtY8D+nhQRf5Wzt/psRmbqz36IKXCDD3w9EyNmiOfwlax6noAtS9YJXfbDdlRgm6BVXIHvXye+ZmfgO+q1y7siaBs5GpSzpKMLRkgK+XoAyiHwfyWdGOH43Dqxd22BXXdN0DJcWbmsSib89aw4NMJokNwpxZEHJhAJskCyAj+yFOgcCEUArArtYsZE0BIEHoZAuiosyEYFhoBVVXFYu4hAVGpk0sarCVp/V8WVSasiIh4PfhiTXT+2IdiaoIUZEWKJgRkcFR0JQxO0sFLtIQ5UYgmxz/YErQdPBf9ZPtkkxtvAZz9BKykyFcm2zAxIlK6XQkHFi936nF2KB6bo8QIbxiuSYLgT/bBTvWXjm0wCFh2PJmi/lmumiT6VJrN97KMJ2mYfxCH70G8JfRO0Zr30sT3E1eLNIu3pC1qVLxXU/vX49RWSf3GymQeFCJysqkzQKewQ48S5BOzDKcyJc31j+9pPpLepYjNuu1KhJWgJUbOmlhjwgW+k0CegxKFmP8Q7m7TkQ98IfjEKf7LDtiYaF4r9o64gLmJIe5zbBK34r8ItkYcvH5WMmrU1S8VG2A8szdrSATBsglZCxddVZp17JPDdBUErezMtJJAD3u8I18ABmnCViSBYn3MSQldlUlZh0T3nNqCbPHZJ0JrSNs0kuCADBM2wVR0QhoAvw0ekjF425iAGmqBl0Ihc0Le0A8m6BkzrGI6AtXsSKm87QBaIGUkQqIKZgMp+BV0PKDnH0759QcvO2bGxQfxmKyytWXS6c3ir13fmNgQbW+bz7YFHyQEBINCzdTM0BJsKLOwtTTJd2R6SaBVaU56CLZ/hE/jELMUmxdk28NlP0BKtZrNOk5VpSy+IWIKDYJVw4QGVQlioLjZBi0v8bunGJpdzrWqN7EMxhH3oK/sgjDwMp7+vS/tQtWIf+NLSgGYfTdBaasA+7tazD6JzkXXWfUGLV92zXc/0ufa4j4LCXoJWtVX1lmgRE3GMimwTtEQdMS4hJuL1V+XSWxz2OrZVoSXiPQPDNwkq3MdXiW9LX9gcn8WHnrb3s++oMopPTdCyVzyJF2kC8cmbEQj9KR99fCXo8IUZfPGeGQdLsMQdPm6WxTiwp76g5TPwxQWwZ5MS1VFXwHdF0BJmHqQxZcJ429PLnJWANW2uFM5JZGkIQuD3eg//TCsaTH/b1LELghY2DE8lgThSfVJ9gJFKQ6sGWqMlQAncL8tpB2Mt6FubpVIIawLqb1IEcwQBYOoZ8FD7QQKmfgQfa5ZUCwUN05SqCgIrmxaIJGwedjQFiUD8zRom1Rfj98YMUEQbG7eAn0jeZRHRcNq0YEPgKlYCnODHB9g5EjcGbPiTiaVASpwQuJZ1SPrYN3+x1AP+bN80p4QB1nxok8em8ZnX9vZQmBkX/EiQWi9KwPNzS4uaoPU2DlO9BAZuESSboCU44CuxYq8CoqC3S2to2YdpV/ahwscm2Id/OE/Fk9AV4C1nE8QJXPaB71S02IeHZT0Z7n9r2Fu8YR+LJDyWvVhCgEf5tmlc12NvZnLYI/zNRCpASF6vkj9bDuG1TNpsfbilMWZ5CNY/Sj/QdrNyxpOId03jYundfsvutiFo+eblEk8zf6a82ZAknw0RtsYHPtpOjBFf1g77rvikYkvo6zsfF9slVi0+TfnBZRhZPsBe+WzDl91LZtiTc4w1XyZm2Q98LR2SbJm9MrN7JPHdBUHbXn9k6uWMOSAGqr0DkZN7op9Rc1rrbVVakDVSNrjIw2tCGP0i5LNIINsFQStQ6a/XQQniCJmxWrfpgQcCyyGrR9SyWiLJVBScVV+tqYOl6TjGjkwlB6PPzhYZzDWcizhUeSRfEin4qcawS+NEFAi2Aphg5iEOgcfULvyNhUq7IKSKpppj+QLC97BO/32aa2juxi6xacGmksrfrbkj8t3Puk/VKwIW/uyb/5siJshgKPBZPiMpUCkX+PmM8/EJ/8Anm36yd9P4zBtY/ZdMsS22RqyeIZMuuLQ13fjSA2HEIBtWiYSJaXf2SMz5uT2U63oEyi4thWEfeI59aLsKoP6JDfjQeGuvhJPPzbMPU/04c9Y+2JREdJHjFD28tAemzd5cDw8TG7iXPbNlP7u/qplCBLHhfzER5viEHfuMjUuAiRNLl/CQyuVBr2HchqDVThwmPhFY4pMHvvkqoa/6rf+EFrskfo1bPz75Ls4Un/xNvMOf+HXU6zsXMaI9zoWvMRfDJQgS9oYvP2Xv8KWfxB5+3ewH/0ki2Ns8fNkinEd97IKgHQuAuyBox4JVtXM6CByGYBsTuoXPmEbr6LZ1G4L26KJXPRsFAiVohw9TCdrhWNWZ00GgBNv+Y134TMcXdrmnJWh3eXSqbWtBoATtcBhL0A7Hqs6cDgIl2ErQTsfax9vTErTjHbtq+UAEStAOBCrfaenpWOvO6igECoFjEChBW4K2fGH3EShBu/tjVC1cEYEStMMBrArtcKzqzOkgUIK2BO10rH28PS1BO96xq5YPRKAE7UCgqkI7HKg6c1IIlKAtQTspgx9pZ0vQjnTgqtnDEShBOxyrqtAOx6rOnA4CJWhL0E7H2sfb0xK04x27avlABErQDgSqKrTDgaozJ4VACdoStJMy+JF2tgTtSAeumj0cgRK0w7GqCu1wrOrM6SBQgrYE7XSsfbw9LUE73rGrlg9EoATtQKCqQjscqDpzUgiUoC1BOymDH2lnS9COdOCq2cMRKEE7HKuq0A7Hqs6cDgIlaEvQTsfax9vTErTjHbtq+UAEStAOBKoqtMOBqjMnhUAJ2hK0kzL4kXa2BO1IB66aPRyBdQjaX4qIB0TEZefc9n0Rca6IOE7vb2+JiAdGxL9FxN0j4ob5tz+OiId0n31/ePMPPPM0EXGXiLhPRHxvzjxk3DcAACAASURBVNkniIiH5n2/dsDVdqVCa8wulpj/akT08dSFX4+Ip0TEqWf684qIcP4lep9/PSKuGxH/dCCSR+uEn+k2yLhJRNyqs41/jYhnp/2epbPHv4mIO0XEZfLvn4uI28+xHzb91Ih4ekR8eA942JdzbMjxlwtCeNKIuH/6yrcW/O42T99P0P5CRPxhcsBbI+IvIuKuEfHv+fkrI+LJEXGGiHh0RLy+s+v/nGn8mSLixhHxxIhgr7PHT0fEFbsx/LWIELT/ZcHOX7DzoQtExDOX+O6QW5XgH4LS7p/DH/Hq6SLiI51Nvy4ivhwRn46I40bEvToeuFxEfCciHtnFnX+OiE9ExMMj4neye+zTNf77ELp7WIL2NyPiMRFBJ4jv+PbjHbd+NWOUuPrLEfHiiPh8RHwm9QLOPGXHF9/ttMJ9I+JPDgm3dQ3Vz3Xt//2IuEJEiCn4UAw6XkS8vevz47o4fMeMO6/pPn9CRPxw5ubHT758RF5jnh3hUtdlZzBe5KAZxD7tZMejO9YhaDnzNXKAGOajIuIGXXA5eQqvN3fg3DkDFuH00ojwmQBiQC7dkcLVU3SuU1gRdq9K4SzgzQ7Qz6fYOH9HPFeKiC+NRNC2Zt4yBSrjnj0Is3umkBJQOQJieW+OxX91nz0p+3/GdLJ1Yj8GRzD+z0q7YJ+XTJF1tQxSx0pBSUj94xIdcn2kgsD8+2TvGoj6HElkP5pzbeMlCFy8O+fCEfGNJe6/ra8cJNh+I8UoHN+TmJ45Iu7Q/SPUT5HJxAs6UTAPi4P64fqStffntftBQFLyHxHxrj2CIdvHRW9KQTIbQA6695C/H4TPkGus45yfjYhbZAKvn8QFMcHWBNPLp535326IsDtrJ9YeP3IhsQ7sTpWJq9j1R53NiBmPTeGqaNOEGhGGN57bidgPpP/j2tt0XCzWPiMF3TratOg1ti1o9ZfAx4E49c+7Bj8oP1NE+ZXUAjdPXrh+agD/fyr1A6zxhET4MJKARTE+6Pxjd8n7S1IrsQV9vUfX36tmIeUXk4eI2W8fdLE5f3d9XKhgc+uZXU3PnUk/rmOTswe9xL4dV1ky5i3R5PV+ZR2CVuA+bTc4f53ZaxO0qjACl6DVBO3fZVWW8H1wis1LddmXf8igBTRVF2SqqkoYuweHkH2ojH00ydfnKo7+l/V8IQ2fYDh7RCAiBH3tFC7E90XzvrJE9xNoH3aEBe1XOqF24s7AVaBVv1T9GLSKmMoUI/7dJJH1WtfuX43QhIeESkUFFghHtQBmbEj27EAWkgL/s8W/74TQ+ZJsVRHa39mYg907TyAhnH8qCYafIPSLdP7x8i7pe3eKroYW3yBiVRxvlG3zXcLjJOkTCF/lkn2b0fjTrHqeN9t1toj4h4j4s/x8kyNxkGBD0mZw4IXEzZrAnAhQtcYRxJY+OeDOLo3Hh1Ig8GfVG7M67e9I26Gi7u+SODg0fvA31XFjgOT/qkfkjV/gJ7FQPcI/MJX4EtmfzaAiqejzi+urZLi/MdLuL+4D8EH4bHJs2rX19zoRwT7MVhkTnEvo+52dsHv9F/gICYWGErTH2CZBym7ZcZvpk0iZ8WI74hthwrcdxJq/NyFGtPkejGdnILYx/u6xbUGrov3qTIjMxDRByr7En9umjymstL+xN5oEbuK+2S+FGzMzR0HQGgf9aX4o2YYNzcQX8Q5OUnjSX1xDr9BSqv1sCH447Qe9v6v+wk1F9ptZZX1jd10zZGYQxCKz4fxezPlYzw59z337esmsuXhjnLTHdfkBm3ZfPOt/vHie5Ez+gQdV2A9trNYhaPsOKag0QdsqosifYQLFgADmadlx350VtNp0zqwgOp+gMIgOxKuqQtAiB8Zh0IgJwd7yAdWH38vgJ1hxDILNVAdSR0AGkFG8IYXdURS0KitELDwkErI+Ar4JWr8jatV0GRnhO7WD7XBwSw5U+Ih8ywRgwpZlyQQTm2WnnJbg9Lvk6W6ZZRNLvsNukS88kflzUhw7l/AU6BCLaXe2+bIUWwjLgZj8DVGwZ2LK7IeA6d6WlyB7Aloixz9Ui1SJ2LexfUf6GoLiD/3K8CbG9yDBxp8lDpYkaR/fM6ugimVqTcKJIM0Q8E3TZQQY/OFjeQ3haMZBH03h6j88cIvPTdupPhpDyTXCFgBUh0wPvyinORG09sBeEmN8fzunjuEmyfY9AYWYNlXc+IWQFnxxi2UKAobxRPymCvea4TgIn02Myew1Ca97py3qXzvgQKRZejPb/qrQHoMSmxQfiFWzis1XG4aWtEnK+LUkbPbg01MUtL+VcV51lg/0RQ4fNSsgRuGueQIITxxFQUsUSp4V0sRnWgin4zV8T5f4HO9cK5ez0DCSf59dL2ONcyxzIXrx5YXymvjOtQlZtmsJFru1zBP30U24rtkxblDNxY0KIYoDeJo9E9zONT7iIvsmxs20mf3GG75r+U0rYOJHeuNQjm0JWgAB0tSpAETFE1TAnlehBd79Uhww6mtmdsABVMlUtwCKjG+agJuiBb4qjmDudxmfIKUi5jNBlKgz0Cq6BsM1jqKg1S+VFomFyouqo76rjAn+ptFVEyUF7zzEysGhGH7vpioFslBTMYjDFBe7gE3Liq2bU+1Dsg52S/zCkZiRrJlOY+OIhNA1A0AYEVO+axoX0dwsK7BIneDqT7MTStYwSTQIKGQnGBKDzicEnY80JCBEswzeGBLP1j45x3QnsjP2m54yHiLYCE92Z20hP5SgapuqEYIkDhEqAoeJKgOifVuKWqJX33wGQ2tqCVrinwC2XAQvCJIqBvjBeQSoe/SXHJgSRsQCAvwkuyri8IOVMVSpP33yAvzbjIbgKzEhhrXHz5ZKSOJV2ucdQ/DZtA+YTlRBhK3kqh3EvP6x49nlHiVoj0EJD4gliiiWaMxWWAmFE+6zZGWqgpb94CLJ7GyFVQLAZ8RmyeeUBK0qqTXBZpzwB99UlKBBcI4lUISkhAAn+dl3FE0scyE0W8HOzJ/nOxyKHvgOV7m+mEPf4Snn00liBh3QX3JguaVCDO6kE8Qx18KReNg9fFeMw5e4Emc0u9cmmk7C51zPQYh585Y1bJrnftzhdR57VWj7Sw6AI8vwPyU/T9CazgMSEaBKo7KqCmOABXDfUUFBxJYTqNw432F6tgUgSxRaxZhYEEwJEf1WZUM2gthRELT67R8HmF1D2x/j/pID50794MwwIQIJGQJJRZCwEcQkSPAkqjisLJV9qqKyJQmX7JkQVfGTVCEDAtl0NMGDuAk4U+7sHoGZaZgVtISpyivRS9B6oMrP/fPZLdIhrpCHjF/yosps+tg/ZEnAsHNBZZNTQEMEm8qCdvBnvqmSCi9CE8aSSwd/Vm2As6NVqlW/YUF0EagwJ24JMtchSuGJxAlbAtfY+F0S2xe0BAr8JBtmaFxj3vmqs5IbybAEBp78y7iyEQJde9iMxMNDHvOOIfhs2gfZswQHHgJjO1SEJG8C1Oz64RK0x6DEdhVXjLWg3x46ZKfsQfwh2tghAdBikL/jV/46xQqtYhLfsGzKzGrjIHhYjiDu4kYc1v7WlhHB7ahWaNmFtbPiDntRdKKPxAcJvEJIe7bIDAqccGbTK5Ir3EZgih8EsIRBJZy4JH7ZooKhn/GueISzLPuaFbTiBTt23VY06Z+PI8XHD3Ztfm2vgtse0sWvijoKBHgbt+PoSQhanb5dlscbAQgcKlCt4oEQhghaggOArRpmSk1wFOANjLL+yfIcWQ2DaNUvWTYyJ2IEprELWsLFukMCndApQTtcIlhCgDQ8FMipvZWjrfHkxMhFNZANES4EgWlwsw3EAHFFQKoMEmQSL2s2TacTZIsIWqRE1PqH+J6XlUb+oA0IDFGY5mTPCIytE8nEsjcGmLpSWRaETeUjpE0eQwWbSoA2+WdajH/CR5W1iQT990/VgfAk7gnPJmhVNMzWELCCgb4aBw99DhW0ZmdUMFQrEK+xRPYSXxzSKrpwNXbGXZDxN9Uk39M+fNUe9NGHvlDs4z0Un02OkWlJuGu76UcBjMj1P/u1NAUXwobYkKCVoP2JOGW7EhuCVozheypVCinWJ5p5UJUy9Sq24F9Lhtp0On9m48TL7JKFTY57/9rbXkNrGSBbs5SFqCK62CHfJXD5uYogP+IjEgd/Y3tmucyWie9mq3DzJpPybY1Bu4/CGt0hRtAx+E1SrSjXpustIcArxCI7w1OKeCqjBK3zJOPWu7Y39XjbDv2ziKBVvVX40x5FFHHEmCgMwN1MOL4znuKN2Uzxxs8SDwIZRxLLxlsM1Y5DGa91VmgZp0yDQFUtMj3jMADAERQ4NeFFQAq0DNj0oeChevD8PKetsUEOwCVarVcTVAwyoWrwiVIZsmsDlAAgKHynAYp4fN+6D0IA2Xjgw/0NDqI3ENq731POu/TaLn1Q9WOACFZgOlESB0OHk6qBPjsPmRBFKuMIAqkKYipXh/WQwrZJZK/7wQWZGHuvhjF9iCSsrW3rik1Ty6pVaS18hytbRtTWtRLEqjCmjNrULSGGpFUDZbHWu7JdROAaxLD7EamqwA42blwEQ9VevqQyqVphzGXThIdpemPswS+L87XBWlkZtHZZ9+t+AvBBr6NbdRyGCjbLiBAt4aiNlhewPeK/HfrPXiUZliUhe2LCmmQCWMUb4ep3m10gElSBrP9SqTYOSF1FUoLhWvBvy2okCngDSfMLPqTaK7ggasEWJ7iHSkXjFxUR/IJ73LM9xEac4w9BZd4xFJ9Vx+Gg77MfgYedww6+L8xiAnHR1tASZbAqQfsTRNmuOIVT4Wasjb8pWDYMP9wqBvF/yzr4Ipthj/hErMUT/YrkQWO2zr9vW9BqO5sTc/m1V5yZ3fJMDN7DaYpbCgjiMR5TQLD8SFzme4QeblNtdM5ROYhDs85m88QYDxcTuSra7bWlxL94gdcUTOACMzGAVmJ7dJSjxQ8xy7XEKssPJPkKAL7juwoE7JIIbd+htfAmDeGg1SQSljxI3LRBe/EpjtA+s1GWWOFWsZC9+5u+ENvrfPXqQmO+TkFrACwoFjCQZhMDAPNZOwQzAR2gggMB4VByJ8YQhFK5DI3Y4AiqBu1na06IVdd3rus7kAcRoE8EQbtu/34qECpdrX2ISjBzb2S0n7jbFUGrr6pXcGBws7j6HSEQYfrD2GAAF5h6iAV+grmgfSiZ1EJWuvmTYQUHgYpjs2VO2bcH4tRaUDjKXGGvyiWAEY0yaOuSXUNSpWLL8dmth5hUVhEAW2OnvktYEDz96Rk2aZwc7m+anj3zCTaPOPiT77seW+ZP2oyoBC7rmbY1vkMFG9zg0h4W1R+YzyaRrf+ND2DBb/m3sVGNbQ82tQfDkLTxwR+wci8/+55gqorbt3Vj57ow0waB1jhKCv2uT35nF7P8IvAgeTgbi+Zfe1npUHw2b+U/4Vt21fiSLUkAjAdOZjvsEjb6D7c6jrEvvMp2FATEi/YQWN+e+LLZA//YkpjITx0+23SCuddYHYag1Rb+LFbxSaIVVzVe5Z+NU8UoXIc/W/w3g+NcGgCHHpUDFvqIY/RPP9kQfPrxuOHjPHzGjuiaJiwVBNubNPCeQocigGuLRb7Ph9kdn6ajFDrEkRZzcKrv0kHaZRycL9HXrsaFtFqLN8bJ9bRFzJFwuKa4eKjjtE5Be1SMba9+7JKgPepYj61/poeQi0odwkAsiFolb5l3qy7TfwSkgqgirGq/rTVM2xRsqtfEqeldxK9KbQ2Zavg2DnxpLb6KsEryEHGyTXy2gUHdY5wIHJagHSdau99qVX8JlmVwuN7bcAhdM03b4n5VX9VcCb4q8rbuu+folKAdbrglaIdjNbUzrV02JWmaVsXLq1csJVhmQ4ZlsHNP0/Km8Qk+66G2VVnbpmBT4bVGq82+IHPTdts6VCwsZ1K1NT1o+vigByu3ic+2cKj7jA+BErTjG7P9WmwZgGcBLOtwSOyt+V90p8RlUVFR9oYgD+lbKkLYHmp1VkdK0A4fzhK0w7GqM6eDQAm2/ce68JmOL+xyT0vQ7vLoVNvWgkAJ2uEwlqAdjlWdOR0ESrCVoJ2OtY+3pyVoxzt21fKBCJSgHQhUvgXBk9YWRNdRCBQCxyBQgrYEbfnC7iNQgnb3x6hauCICJWiHA1gV2uFY1ZnTQaAEbQna6Vj7eHtagna8Y1ctH4hACdqBQFWFdjhQdeakEChBW4J2UgY/0s6WoB3pwFWzhyNQgnY4VlWhHY5VnTkdBErQlqCdjrWPt6claMc7dtXygQiUoB0IVFVohwNVZ04KgRK0JWgnZfAj7WwJ2pEOXDV7OAIlaIdjVRXa4VjVmdNBoARtCdrpWPt4e1qCdrxjVy0fiEAJ2oFAVYV2OFB15qQQKEFbgnZSBj/SzpagHenAVbOHI1CCdjhWVaEdjlWdOR0EStCWoJ2OtY+3pyVoxzt21fKBCAwRtD8VEccZeL2jfNrTI+KREfHlo9zJ6lshsCACn4qIc3Zbwv73gt+byumFz1RGerf7+dQujj+u26L7i7vdzGpdITAXgR91W/3+20HYDBG0J4qIZx90oQn8/VwR8ZcR8cMJ9LW6WAgMReBSEfGOoSdP8Dz4vLME/wRHfre6LOn864j4wW41q1pTCAxC4GkR8faDeHSIoB10twmcVEsOJjDI1cWFEaglB/tDVvgsbFL1hQ0gUEsONgBqXXK3EChBO3w8StAOx6rOnA4CJdhK0E7H2sfb0xK04x27avlABErQDgSq3nIwHKg6c1IIlKAtQTspgx9pZ0vQjnTgqtnDEShBOxyrqtAOx6rOnA4CJWhL0E7H2sfb0xK04x27avlABA5D0N4kIs6W7fMwyVtm2uqtCueLiOPnwxT/PrAvmz5tWUH7091i5gtn4z4QEf85p6EniYjrRMTJI+LPIuKlEfEfm+7QwOvPjscJI+L8EfG2mQfkjNc1IuIlEfH9gdfexdN+JSJuHhG/FBHPjIi/7zXy5yLi1hHhnFdExGcPWqQeEaePiNMlXrtiy+vEfaig/Zm08XNExAcj4g0R0fBgY5eIiEtHxKcj4mW9v+3V1mZvfOV76+zQmq81FJ8137Yut0EETpW2/KsR4enrF0XE8SLiShEhpr4+bXyDTVj40psStHz3vF3cunJEfD0iXhMRvxwRnxnAjQt34gh+gb2cKWOnN8U8OSL+uddPseamEQFnGuQfDsCA3rhAvhGAlpinN44gjMd06TAE7Rk6kXDLRPQp3WB9aQZdbTKIxAMH+a8dQX9ZQXuVfF0KcfTEOa+eYIAXzD4TT/8UEX87gAwIpRNHxPs3jE9/PL6Tb7zgJHfOtro9Mr9/RPxuRFwsIr654TZt8vI/n+Ty0G6s7psCvd3vtBHx1oh4fhIPPPY7Tt0J2hdHxEci4t5LviHjWJng/VVEfGOTHV/y2kMFGzv6jYh4VkT8a3LA1/KeAqBXCv1618ffS/vfz+/Z2/0i4ooRcfEVcfmttFf4buIYis8m7r3fNS8UEXfIf9+KCDzlTS4PGsA9227rrt1Psvs7actvjog7RYSE7bEpZF89QHhsu0+bErR89l5dQvrefIPC3VPgi5f1Kr9ho4zP+OJd0w/F9IadePqE1A4v7+LIvxxwyd/sioFPymKMOLVMEcWbreiLj2fCNqwXO3DWYQhaQvUWmYWoxPhdNdL/wBfsfjax8fmxM8vwDrJfyIGWFbdz2v8yGEHQa7V85nrOW1eGsqygJVhVXxntc+YIWn0iaL1S5at7CHhkSdgYLzjA6TZJIIwcTvrvn/s5x7kw4AD7GbXznceB4Oa7cCTsZsfD70TJDSLCe3mJb9/Xh1Ok491w5IKW6enjtSLit7tKwzWzAgjPO+Znf9iN2R+njbb++xXWrbIOP7gSXETTH+Tf2TOsnQtn4+p/1/GZ3/3MbtnvSZPs2N8Xcozbd/z9sIPGooKN7ajGvql7f+1rs+9eKXS3fC3ew7JP8GZXsGh2qK99e3t8917NG6e9wbvZLw5xNJx83r7rf393TZ+zY9hKOoxDf3zWwR2L4rOtsACvZ0TERyPilZ1dPbibOXtVvhpnW20Y+30u2hUiFGVwBJGrwIAXDtsn5+G6KUF79kxO+a0ClKRf0YrQ58PNn/icOMbn+J5//BNWeKz5u/+bf/b912eb8M9dsUFVbgl6K/iZdYIFv5Q0ELV/no2FIf910DtwafjhTBwrNpu9gm8/XjRd4H//xBzfoR3ELr8T0eeJiD+KiH/s6akWk3YFs//VjsMUtKalCTjiwDTFWXJ69z5ddnu7rgKo+mX62vvHvDvvUVkxI5xumxVCjqC6ox8yk89lef4KWWW7S4qAdQzApgSt5QYPSEFI4L9uZgoVCRBXN0pRrI+PjgjBHIGaukUaRBg8iQOGzyEY5hvz/HkVL+Lg+plgCGzICe5/GhGXSzx/P4WczwXAk/UErakRywxcQ1ZnCs44jLlC2wStZQLGhX2yQ1hfNsWpwC9wIZWrddPkV8++m2pkr869fUcoZ0yCf1farqqY5Qy+x56QxWNSVCALU5ePSHIxXs51bdn7e1IUE8fuyeZVxS17OMxjUcGmPyrXv5b4IlAJnelaJGzzEuSqWqhayz9UEPm/90D7/vUSY/YGj19MG7aU6StdQMQh7NTL5D+R57JP5H7cFG5mS1QlCZIPZ4WYKLlZjg8BQHSvKmoXxWebY8nfBUrVNcHMdOeYlwttE7t2Lz54yvRhAuK7h9GIAffclKCVcOM8Gw6pTIsdbInokrjiMILqhSnWzOyJI89LXzeFzl8JYUUa/s4ecSYuEMsILhwszvFP13tu+ueuLM0bMAT7nkLQ4jGJwQO72P3uXIJoKQe+1F/LsegdWkChRJwRnyx/I4RVx3GiJTH8WjzxffECpxLHrmUJA63w7dQHZrvcm86yJNTMpPdnm400cyZhcz9JiFgkcdnJ4zAFLfCQp8ETeAQVhGqNIsO2FEH1xPoSRqzCxXmIOdNi98hAp7Ij+FvGwNBN+yBqgctavXUZ/KYEbTMMwZiz/0mKnfY5QSu4C/aWYrSqlEqoaVKZMIM8TU5rM2hCjBA1vqaDOMC8QIV0bpUGy5H+Jqs1fiaciQjTaYy4jUdf0HIo4+IcRGSqg8A9CoIWcViLJGuGNSIg6i0daIKWncGZ7cECSROy1omyO4RCfDkP6cDTzlHWSrN/a8iNOdJA2LBlB5/sqhmWPLA5AZL9s3siG8nzFTZhTbb2HOaxqGAjXAl5NgOPz+caPP0RsPSPnQty8CPY+bgKDbx8LlGFN1GqQqsiAWNEq6pOZAiUSF1Ch0fgak1ZW6sLN/fDPQ9Jsct+BVDjIyFUkT9oWclB2C+Kz0HXW/ff8aggxg5tALErS7zW3c9NXa8tK1Lllhy12YFN3W/Z625K0CqKnDtFEhEEB/52gvRPa2lVGPkT3xW7FWE8O3PVFG4SfHGk2R5BRhyLW85r3Mff+9frL3tbFpdd+R5BK8ZfN7ULTlIcwmn8UywgaC11MTMAE0VAsQMfEq4E6MdS2Eow/i5FrKUDYpL/zfLB3fUtbRBTxDrFKRto0V+4UpJmHMU/HGsGGbdaMsbOd5InDlPQApBhEwGMuVUABW/AtSn6WUErCBpgQsxaU2sUHSo+ghNxp4pL7Akm6zo2LWi108NWnNhamtlt3hg34xWEZVzXzv4TQoxONZChWfvSTwDgJeC3wEz0q4BzHIcKoYfWOIh7WncjoXDIpGVzph88DAbrvqC1ZlbV0jkErfPbFPC6cD+M66h2c3JrVuHBrlT33pcJUxO0xkr/4c2XTNGopCIDYpN9s2VEb0pbhVYVxyHBQFYyb5kzoetQJZTkGV/joCpJ/BknVXO2bareIcNep40vg/Wigo2gNRvABhE4EeUBL8QqGSNoVRsIrYfnVp0qqezftp1sFd6tOgEbS3rgJCFTUUXk8BXE4avaY/xcx/WRvu+Z4XlBkjv7vWQ+kOZc33c9iYl7SVz4pzZL8NxvyLEoPkOuua5zcIEAxbcth2JXq1ak19W2sVyHLZhlIChwaH/94y71YVOCtvVRAYkQlYibFfHP7IlZx+ZPfEGRwAwqW+NXEk6xSzzCBYSvpAA3Skjxr889MIpHZ6+3zBrRXRqX1pYmaPG/+K/fYq2+37MnaCX3/FY8kAiI/4Qswcr+aCL8qGBCK0gmzPoaAxrA/xJ12LbnlyRlBK4qrJjuO3QXQSsGGQ/FQd9VrMKvu7is5lAeCrOuUEWLoDVFO1TQtrUkApJpDKK2L2gZBmHl2taVeghLwFrXsQ1ByyiJFn1sB6OVgZmSQUoMmWhcVtDO4sGYZbp7CVo4W8aAfIixvqAlEC6TDkSMwFyiYdp3Jw1+oDEgZiKLyDT9YkocUROl+kjQqhwgANVswQyBGB8YWepB0CJtgpbo/VD3/cv3ZhIkIQSyJKQJWlVGtks8+Z4qhcy4CVqk7hykJuFTOVZVPMxjUcHWqjLeZCLZgqcgpbLPxohYyam/wQbmsJKoWS+mOoGw2ZsECtnzBcQvmSCGiWPbJDZBaxxVdyS5xsG9VIv6gtaSBMKY/fI5xC5QHNUKrQSM7xISgqfkTNV6Z6cTD9PI59zb7BYeVvEyRe5nszHwtERm145NCVp+qaJn2aCqnZkWtmQWSTXRsiGzjPzJDAu7M8soMTSb6kFo4onfiW0Ek6SVb0oWmqAlZvnn7PVc5ygckmV2Y2bJsjP2BQ9FCzGITjJ7xMbgg7/gLWEXZ2ANT/GCPlKcUj0/cxYHCGWFLXHLLGITtPSG+C+O4FJaY1bQim0t8VVMw7tVoU2rIw4EJIcgJFsQbEytEg1t/ZsBUDUQaEwhCkQcB2EojZsWbGvrTGE6BHnCk8OYul/nsaygVflhMDJYBkcACNxEEwO1dkUFlNPLVAka0wXtgIO1MSpGbapW9co0D9El+2Lgvgs/WbF1hqrejBm+8LaEYN4hQ7RVjwAAIABJREFUW5YEELQyP0LCGDg4lnudNUWG9suwCQgOIdgTJMQbEas6TkhY5qCSeJwUJGOq+shqkQahz/6IG5jIYFXrYKD64H+ZK1uUsar6EWnGgIBF4ASpcbEGSXUd1qa9BUFP+KvssH0VYKRE8MLW8gTrktmw8YWraq/pNtexfldCaArJZ4d5DBW01nBJ2NgT0W+tHZ/SR2RNpPMDf2erpr7ak+REqr6qmCJT1QI+AhciVsVX0sX22BzS9j/bJErxjAdR3Ys/EsW+63qWNTjHNfEMnzQ+1pitY8nSUHy2PYZmIQRDeBP6OEafCZ91LdPadp+2dT/8zV7935a+XSTx5N/4kw3tUtDflKCVYEu4+ZCEU4zmm2ZFcBV+av4khit0EFaWFakAEq58FZ7WyvI5uLmGmMSncSyBR3TNXu8oVGjZEaEOCwKeLYkfBCZe45viAJ7EX+KRhIH4tdQQjhICmsJ54ohEQywiXiUSYrW4JS47F5ZmE/AifhW/iFmfO1fxREwypmbTcCiB7FoKiTt5HMaSA1OOwG4H421Te4Bl/IQaoUdQaKPARhgA3docawxVsEwL9wWg6q/qi2mMdS/OX1bQMjIVJm3j9H+RYokg9S5X/en/3TqZ/sGIBHpTrkSt65julLkRr4IQIeo6hE5bHkBkwlMlS9BvT0jOGqLxIN44iKlHleAmkqzRIS7gbEysj5KQOJ8gITKIZpUeB4FmCoTYUqXkmBxEW8dySIpkoQjXeLFHYwUTiYNqgnFAtMQKYWD8iACVW8sUEDRRizwQuPFCCJIz4tY5xgq+RLCpH78bWwkbm0fUEgGiGLkYY1UQiZzfXVMbDnvN3lDBxo5hAr/WX7giR8kcH5e8sTe4t6U17FqFtT24JGDqf3tClziGQcMbJmzdedbLwtHDXX7nD2xTcOQffNHYmXVA1M7FH218WqK8iu0OxWeVeyzzXXarmgYb1ZzZ35e55hS+w+7wH3sVo3AiDsZ1Ejb+TrhJsnYpkd+UoBUXiFpxQ5yQqOMssQBX4TtVVz7d3qEqzuAz1dkm+n2mEIMLPBcCWzNgMGy8utf1xmx3zZ5UoPGfvuIhsQLH4ycVU5VoYhV/4U16gAC2DFA8gp+4JfaIRc0G6SbxWeUWN7Jb+kviRdCaDWvxS1vEarNi4rcxdE/LIfxj07u6pObHNnAYgvYg4xP4BBX/t1dSHfSd9nfVQ07FedZ9LCto192OMVwPKZkOR3Ye9KuKzxhGbbk27qpgW6436/9W4bN+TOuKiyOwKUG7eEvqG4XAhhDYNUGreqNqqQJrMXJ/l6b9IJCteH2Fioup2k0cJWg3gWpdc+wIlGDbfwQLn7Fb+NFofwnaozGO1Yt9ENg1QbvLg1WCdpdHp9p2WAiUYCtBe1i2V/cdjkAJ2uFY1ZkjRaAE7fCBK0E7HKs6czoIlKAtQTsdax9vT0vQjnfsquUDEShBOxCofCLbmwN29gm/4V2pMwuBtSFQgrYE7dqMqS60MQRK0G4M2rrwriBQgnb4SFSFdjhWdeZ0EChBW4J2OtY+3p6WoB3v2FXLByJQgnYgUFWhHQ5UnTkpBErQlqCdlMGPtLMlaEc6cNXs4QiUoB2OVVVoh2NVZ04HgRK0JWinY+3j7WkJ2vGOXbV8IAJHQdB6Wbp3ntom0wvRN3XsJWi9INouH16I/+7cJWu2DXYCeWC+RN+LkO0ONYbDC8RtP/iAfHnzGNpcbdwuAiVoS9Bu1+LqbssgUIJ2GdTqO6NC4CgI2lnAr5wPbtldaJ3HXoLWbl0nzZ05bE/qfbi23GyH3Z9sY2d3JNvI2U7OFnN2QznosKuHnVJsI7jtw64sdgnRZu1fdk/7TY3HtvGo+81HoARtCdryjd1HoATt7o9RtXBFBLYhaAk627Hays4bAux7b6tJ26/ZEu/zua2aSqft2By20rPtm40VbN1qi8bv5VardqGyf7Hr2sLSeQSlrd3sc2yv99fn7z+fQoy4dT+7iNmy1VaPix57CVoVYkHddnU2dbhCJ15v2tuSVBu1T1+I07vmtn/2qW47aKng2gYVBl/M7T9tZffU3H/Zlqf6aztfW9Xp12cTB9vl2YiibStoTJ3jc5jbwtVe7X4mUm3h+pXEznZ2bbtCn+tD+74tbVVor9q159rZH+fbb9v2pPpjnGzF5362L9YPY0sEw1wbjIf2E/s+t3Wu+/j7mLbEXdRepnL+pgQtW7XRCpvh27ahZXsXSvuxiYotIfmW7Ta1w9ajfKr5u7/hHPb6UzP2iodsTczn/J1PbOLYFD6baGtd8+giUIL26I5t9SwR2IagJfjs52xf4FN24ufZuU8wsXPOTvQ8NiJuln+7cwaeO0bE81O03SiF0ek6AfeCbj/iC3cC7iq59zqhRtwKXPdM4fz4rH4SWrdIUfjcLuC5DsH1sAySixrBkDW0+knkPWiffbxvnVjoi32sCVVtg4WfbRdrCQVBqdr78QzQxDIB+Cd5LjwlA4K+fem1z/UkADCFi33aYU7o25/Zfu2u4fVj9ncmAIhs+3DDyLVPkLu02Xr4bPldotb+0UQ3Aew+BPD9U3C7trbcNj8/a0S8KHHWFpXel+b4EOoE8Mdya2Pito7xIrAJwXbs9HGiFkfx5ZflTIE9ztmPJI4dPrTzm4fnzMd9UpiyY4kTjmHblvvY05wtfiITZ3ZPzB4vBbIlS8vOQuw3epvAZ7zWUi0/LARK0B4W8nXfrSGwDUFr2vzGKaIEoKunYPqnFFhP7qoub+3E67VSbDYh9b4Mav7+1RSjb+8qrdagEsCEKRGlIkqcWef5310VkuMSbKoud8vPBLLLR8Sfr/Ae2YMEreBJVD+na9+X9xhBYlWbntSrqKocEdo/SjxUZVVEBXHi3/VUnPTv6ynQr5GC9THdVsG2/bXs4SEplAXpm3eCUgLwiKzK3ilF9nHz/3uk+LQ04gu5Btjf4HTprIi7NkFLnLv3gzNxYDPEwCNzHF6S4lXVmNBQ+bpdVnRfnqLceBwn+/L9iHAvyQghzw7qGC8CmxBskqrmw8/LJE+C9qxcy93sh52b8eAfr8zZBOvY2eulIuIHvWRX0vf0FMYf7uzxcWmvkFfVZbM+X/exCXzW3ca63tFHoATt0R/jyfdwG4JW1fH2WSUx/UzAfDoi3pLVFwLWtLwgRMT62XpT4vOWeY5Apq3ONU2okmvKnnhSdbxBBitVyxdmMBTkVAMFROKM4HxnCsdlBn4/QUuUXimrk6ZH5x3aLmgSgG15QDtPnwlJAhY+RDrx6p4ELVyIZdOnKlXXycqSv100gzcBQBTD6YpZkVJ1stRCAuDvKtmPyoqWSjGRKuA6/2J5juq4xAO+quvOJ4xN9Wofoa2/BCyS1AZrfN3XZ/fL8VE5M24twXBvAtlYOODhPpKQOsaLwKYEm+rsqzMhwwNEpxkCQpTNNPthU4TtG5M7VGedL0m2LIFdslc+xhbNRPCty83YsxFgj+s+NoXPuttZ1zvaCJSgPdrjW71Lst80EKaoBRT/E5emvFVCLA04VU5lm562jIDIekUuLTAVrRLpoSJC0NSgqst7FxC0+nabrAoTZoTXskFrL0ErsJ4/p/rflu0krK13bYeq6WVTrKoUWdfq786zLrCtq7X29wm5FneTglaV+L65rtX6VlVzyxIIUGLAuBC7Kq6quCpbBK/KsoouEU2U36snaIkN5xLC1t46LBtpglaFViJijAmSS3TVZXhZG13HeBHYhGAjPlVpv5WJngROAtxmd8wQsJ93JLeYLVCN5ePW3N49k2YPYLb1+x/sCVoJM597Wq7PZc/W0FqPv+5jE/isu411vaOPQAnaoz/Gk+/hNiq050tR6mEu4s+yAQGKmDPtrKLqgQ/TiF5npQJjfabDelBLC1R5LS8wha16eZMUxMTvrVIME2DWclqSoHJLXFl2oNKjQqkys9dSgCGGsJeg1R6i2QNuRJ5+CpQqx9bvWTt6vWyjPqg0eYiFuFeNtV6QwHSua6iW6rMpVHj4OxHvc5jpp2As4BOllhPoI7GoOuzhL+dYx3rvrByr/lo6YHmC5QwSBNi2aVaVXcJWVVxF15pD9yI8L5m/Gx+Bn6AlDggHY2UtrPNVYAkLD/aZHmZbljaoyBoPlWnJCVyMiwqa7xIndYwXgU0INsmvBNcMgWSYzRG01mhLtvr2Azm+YTmPxJg9sVnLWbzGT5VWpdeadH5pDa0ZB+f41+x5ldmb/UZvE/iM11qq5YeFQAnaw0K+7rs1BLYhaAksywQIIgLO0/AEmIqgJ+WJnXb4TFWm/6CQZQMqfj73BgA/E3MqmKoqxJPqraoLYUwYWl5gel412PdNS5q2b28VWAbgvQStJ61VMtuh4kioe3hFn/XXg1mqsg4ikXAlrlWLjQEx6Br6LYDDyd9d2/pa1VyVXAmBAAk/wtm1BXjX9Ll7+5woJYR9BlM/w1kbXMe1LR0gGFSP++1x/zY+2kvsqly5twdrtJcIsLzAuOoDoU5ItOt5i4Tz4OCtB208nOsaqmna7tp1jBuBTQg2tsZv2b+DvbJR/uQhyFn7Yd/snv3zBQkwnsALOMN3XY8fNnt13WbPbHETD4S5xybwGbfFVOsPA4EStIeBet1zqwhsQ9ButUO9mwlwpi49lEbcqj6uchz0UNgq167vFgJjRaAE2/4jV/iM1bKPVrtL0B6t8azezEHgKAtaa1YtRzBV6WGmVY8StKsiWN8/igiUYCtBexTt+qj1qQTtURvR6s//QuAoC9p1D3cJ2nUjWtc7CgiUoC1BexTs+Kj3oQTtUR/h6t+P1znWMQyBErTDcKqzpoVACdoStNOy+HH2tgTtOMetWr0AAiVoh4NVgnY4VnXmdBAoQVuCdjrWPt6elqAd79hVywciUIJ2IFC5yYHNCTxgVkchUAgcg0AJ2hK05Qu7j0AJ2t0fo2rhigiUoB0OYFVoh2NVZ04HgRK0JWinY+3j7WkJ2vGOXbV8IAIlaAcCVRXa4UDVmZNCoARtCdpJGfxIO1uCdqQDV80ejsA2BK17eNH57L1scrDKRgfDe7meM9dRoYWBd+PaQMEL4B0NHz/bkKB9vp5WH3MV9/SyeocNELxc3nt63cs9Vz1cyz/X7m+Ksep1N/X9PhbtHnv1odmufi27bfJsP5od2MTC0fxgnRjOs7VN4DlU0O7Vnk3h637whO26xg1+xoz9uO4QXx2KzybGZtlr6iP84DbLV8tec1vfmzc+PtOPWb5rvLipWMRO3HMRexmCU7PtxuVDvjNU0GorXIx9P05tguPdy3X1p42Ne/vdmKxrF0n3adccgtVB5yxyvUXsca/7zrvfXuOxCT3hmrvCp/uOzTYErV2wbJFq21XkzklsbfnxbgerR49oTeqqgvY4uRf970XEtXJnM4NzqdzS089Pz/3pD3KoRf5uhyRb614mdy97au5zf5f83/a4trld9rDl6O0j4uK5He6Nc6ezZa+36e/ZeveeudsZLAh62wAblwvl7nO28LXD1Dk6e71f7qZm+1Tb9/7rig3kc67rHcnGBHE/JHd0szXwm3Jb51USDbu//XZuoXzD3P51xWbv+fUhgm2v9pw98bV7na2XbVu9DnztAGZ3wAfkltDvGig+D8LIDoXG7XRpQ3YvPOgYgk8TyrartrMfG7FzmW2k2YEgb4c0f8OfuNPugXbgO3/+3U6Jtr5eVQQIlOzQToC23H5W8pPrr3rY+Q12n85dHVe93uz3jc8tc6fEe+U99MNW61dL23p4t63yJ3OHRefY7dBW3s/IrcvX1SY4Xj23Ir98ble+ytbrrV3EzbnStrX5jwfa9hBBK7nE39dMO7p7bkOPH2/dbVt/4dxx8lG50+MqWMHHFva2rT5PRHwofYpWcDw2Iv50YN/2a4fdAfXDsy/4flV+WeR6fXsUZ/8h/apvj7bhZo97JcftfvxP+8Vq44GHjIfdVukou3c68L4twgnpZ3a6620rYoiL7ACKq++bY/T2Fa/Zxgs+t8jr3yd3dFzFprb22q6zJNE8NLewtT2tYIN879AZ3PdX6sV2vryqoLUV7s0j4ne7LWGvl4LWtrZP6ozvwdkFBHu7NeNBPAmCjP+30oD8b/tQgXHVACgg2N5Y4H5ebmJBQOzqcc6u7/eIiI9mAqH/gp0tehHA5TLYvSCFpaChb3fM4E7ornIIGsbEVsQSDYRB0CIixOZeqx6Sp2tkm3dB0M5rj6T2yYmprWfxwHPW0H/4CvgCgcSFT61L0LqmRJC9C1DrFLSE13NzO2h4sI9XZQBTDJAEC4i2+iZ0X9ht/32bFLl8WeHgMWtIXmwXzC4FQgJZmwTIVQSt4HrRHJerdAmihNGGN+s+jM+dU+gLkLZCl9jcqNsG+Qnp134WmGFny+43d1sr3ywTWOJwXdV8W5mfOf9JOrRnHYKWEFQEYYdPXLOgVfwQmz+WItDW8i/NBEcyYoOiS+e20q0YsOwYwse9PpuCTHwlzsSm161xK2pcS9DymaetQdAucj32eKeuoIf/2Bz/lbSyQdwndkog7prxeB6W/fspeInlfMh44Eu2gBP0je+yc/4lrolz/ME298sekml8qhCEF+i2dQla+IirtjRXOLJF+UrHNiq0GtgXtEjGQfGreFHon8gqn4Hi9ID7enZWtvjhjoyen8Hu8UlSsnzBCpnLeFwH+D9KkfiRrAyrahCNr18JqYhVBa3bE7X6gUwFiItkv2WqDln0U7Ji0Jp7+jR6FZsrRMRrMzvmKK9IEcYgYHbJzMwQg+ThUynWGCCMkAUSRCRIo18FhJPs+FR544av+6oK3KBr801zXN6RJPewnihG2vphTFZxoBWH6cCv6wssOD9C8LuATUjCBDmo1gp0Ks8EoaweOXwmCRgJ9cdDdow42nhoxF54IqTzZUXCGBFgqrLfy8/6AdVYENQI0fGedHwC4foZiPnJOzsfulJ3LdUn1SYHwUiUC6R/cSAqy58wtAI52x7ETsjDUtVB0PlcjoGKFrI7eWIl0UDgV83KjXE6CF8BTADgbzA2PoSicYQVvvA5vhBcXFMlmX+ohgrk583PGh9BSYDhB9q+CUFLQPYFuDaxx2904ujlyaWqZcQuDvAzfxMQbO9NjOBMtkPM6Q+xe+0MdG/I6goOEPx+JYMk7sHHPlf9UYVji3hP0JEQnzo/VwXlQw4JnrH7Wv6OA1SbXpQ8h8/dU8Io3jyw436zHcTjJo42PnxLrJHYGU/9aUkDn2ID7INoVyUUsFWj2YND9VuCoJ2SCUUX1/AZvHEfe7pA/nzs/B67weE+/2pOqRsnNixpM3vAJnGo6hy+cfBRSdI/JScpehDaxp1/ayOhwr/ZBGGBD4aKiyEVWvGTEOJ7/EOBQmLF/lQ4xR424Hf94VMSHxiLwyqFMDJ70MfHWEgCHS9Lf2v4/DAxleDwcfb27Z5haBP82VzzV/jyV3bGrtzT/+wZn+AROqHFLt9XDcT3q1ZoxYtFrkfnGMdmj6r2Eh1Y6Y82KWgR9vOqtLP3w/30A78yHvzc7y1hUxDjv2b+jJHr0wfsWxIh9vgMJ+BT33Md2oRt8/9mj2IHbsaDtASeNIsmqcIJbELRgC5hL/yL/0h2XHN2fHARMS+RND7GGT74VOwi+Fc6DlPQCnBvzEoDsgA6oDk1cGUcF0xi5MwOREJgCCaMwLSEA6ECFnEwAM4OJGQEfMKE0cs4lz02IWg5KYITMBmDe8CgVTiRJGHFCB+U5PXWDDyIU58FEAFMtofwkLSpGtk00cB5BEL3QqgfyPshkna4D3wkAYgFrgjw/TNgOcd9OAqCMH4EGoNmxBKTNl21LM6b/t6soBUc4MhW/iQJG1ETB0gXbmzIOTJIwr4/Hr6HpI0HscRhCYG98GTTiOx9ibNlB0QMe+8nGPyDECAAfK4drt93euMt+PTHo11j1wWtfguEyNeY6BuSZrvIUL+aaGLLcBBc+TV/9go9VXb+gYhhyF4bvmyZDfMp/CLgsVc+gS8kXvzB2PK/FkwIPGMhOeGb2iKRaccmBS1BJVjyKWOL9P9/9u4D6JqvKhP9qplyHBVMIIrKKIpIECUIAqLkIIgoSYIoqIggWRAQBAcl5yyhLEBEVEQFBCUIgiAgoqBIUIu5OuaM49wZ1Lm3f/7XqmmaE/qc0yfvrnrr+97z9unee4VnPWvt1b3ZCtvj9+ZnuRF5JQvjIz9jF1BU2JwHQ+CFeSOP5ktWZAgvkJaHJc4gZXDTvchfoiSRkNxqJ0Jq2LaWIjIjR9cgc2N8cRKukp8A6z7IlkCrSIGU1cFWtZfsitBWJZ1MtLYYr/sL0gglf7JqhvTSO2LGJlTNxBEJG5tTEYUH7BYpQYQVWtiHeV45Iq6d55KbYgUcpy/yFczZs8KKJIDsJB/sF7lBcrV49A/jK6JdeIuQmcc2CK17059kSXwoIs83EWeYhdDyFxjHDobyseW8FS9JvjYCslYwUOUjH+QONpV82Dcbg8PO+/BABr7nfiqc/u589txP/LWKGSOZ0A1Z1orCqgR0WfxZ9XpDQsuXEbmyR2OlZwn4GEKLJ5i/hIg+6It9IaYKWuK9e0gE4KaYJgFxHt9GdOEM/sTfJQDiHTywQqi4wjYVQ9ijQpV7wg++a2UID0OOnctvjAcm8QPn0kV/5bf0AxeQaNeu15+eDKHl6AQi6Fh6lwEI4AIOEJINUJRqIweTwQJoYCNoAVckymd6vmSEnIRB+66Ah6hRoOoBgN6kUrUNQsvAKFu2wwCHhJZzARAGB/SQlarw+ptKg0AGRBzAGqECqKrSt0+DBjoIEeMlL6RBAKtWD9VKBinrZdTkzsGG/VlAhzPQl/YJQbUOSQhgkrED70M9hoSWAwJMzvumnrwFG20A5inxAxKcEEj39WHOAKP0AeRlteQpeJEjeZIr2dCPIKayKnFQ+VJJoNeX9x4QU4EEIAIr8HZPOusv/dKHc5zLDvoJ26ET2uumPRq3owitCoAEFlnj33ouqyJqnsAWoVWJ6MuXnAXdkq+ggeRKQuhcBYDMybvwwooFUq3KWYkAXfv8ORkkXKMfaLZFaPv+IvgIcvxI5WYVQishZYOSfvOGKYiAw5wQCnNlk4ITOVXFF06ofgmOqih8mq2yT7bn2ogtMkg3EgJVSNXYkhF/Yqv0oMJTFeGa364JrXmKAebOX2CkZEUMQcrFhiGhNVbzEJv4N7wU8OEDEkGGVlQQWj7M/1UXkV54IRmDkb7nc9U51yNvBNiKC3yQYCkCwH/xj3z7tma8MF41DX5Xy8I2Ca25Gx9y6BBX6RMxQtCLQNE/ggK3Sj6SGDhKPmIL+YhbfFUiBMv4u6JIyUchS0wRs1T3yLKPcdptJEX8Qazkr+y5/9xHrSDShZjar1qvSkCXxa1VrzcktHSN7NErm1iV0CL07Exhij4kPEVoycoPOavkIrR803cQT8UufAKe0iv/Jlf6lRizv1ott0IrXpGnJBlO0JNVKRzM9/g+nVQbUemHvmulgzzJzHXoR0Gy39d7MoRW7wfSxfixdg6t0kVByCpHkAn4u4oY8isrQcoI9IYJ2ogHBVsiYiBImcBuiQ0wuwaA4QC1LLbMaGf9fRuEVvZjruYEvBgg4OxXhJYRWsFLoPevyg4ZVAYkUzZunwNEgVpgf0QaFWP3N8aPFNODJS/ZOSAf9s2RMcC2lOm7wKufKUsmOBSCeKjHkNDWEk4lTiotEgHkUlWAAwqI/m/pT3VlGaFV9SFPjg4ISp6ATIUHiLkmB2fLgASpkHQBKofPAY/Ay4bdF7lSQaqjrw9EUEApfRw6ofWgAULB9tkg8oMw1PLqIkLrO+QytFfy1eOHtNAzeTnIzL1U1VRg+3iBFPf7OdkD+7bkS4Zsud/jvwtCi7AgCwKWJWb2puIsUCMGyD8Cb67wkfyQS0QVuagEYBGhtYKAvJsb0o+gqIaZt/sJSAIe3IUDqsPIqF5YvuD+xqL40O8rrweLEFr4zo/6x64JreSoqrFVfReM+bgArSKocsqXYGUtSY8htOaGTIgv/JmOxLDyWaQAAZQM0AX9SRjIHQ6w38IHmDDctMeY6Jc9qpLzD/69bUJLX3Ac9rF/JFQyqLDkGQSyq17NRYSWfNilmE4+qnzm0ZcPnfBN10aIJLD8Ex47/J2MEV86kSANib9ikESLPLU7qD7WCuSqBHRZ3Fr1ekNCWw/B8T9Vd/ZAxnQ/pkLLdpBPqx7kSx/sF1+qB56r/VISh7hacVlEaJ3vwTzyk7ySHQyFJzBGIlYE2fz9Xez60Ar6UZ13fYmgZLvi2NETWgxflUTwZpycHRnjQCovKrT6m5A7/UXYPGNl6AQMUGW8iCCFClLIA/CgDBUNQMxgLLcBEaV4xPfQCK0KMqMDrAiMcVJ2/9VXywit4EU2lgBk8PrGLPcIvAK8pXNHEVrnk6csDrkVAAEF8ovMIk8qrwCl72DAVSAjc1UH56syFPAIZLJ6QRjwHuoxJLRkzWkFPQFYSwE5sE02imCxLZUBy0TksIzQssNZ8qTfehqdfIACgCJXGSyiRj8qZe5jCUeQBCA+M64+mUUCBYLSh2SoquaHTmjZnKBY8pUMVUV1WYWWLbNhcvZT9qqizgdgQvVLSrz0odO7JWXVrj5e6LfrL4/pIYM/lkrrwSLL91XB3RahdV+Ekn/xefimQmsubEIFy8oTIsSO/B85NEbBECYiFwLGMkIrOKkUSUjZlO8jVu7Hf9kU369VFxitlUiQkzxL+hBdWC6o9Q+JiCVID5xK6JCfvt3umtDWgydwVtD2OxIhiCNZ7ANplDjwtX6leVmF1gqW60hCyV1Vm2wVKqzIsE26RMjYEz+HmfCEbIb2O8RbyYKKLpuFJ5IcxZptE9qqqMEd42ZvikpsTsJj3PCRLhcRWvJRABFjEM2yFfIRl9iclVqEVjKhqGUFRpKFiLkPksZfra6KTeJ731/J22oPu2S9P9L+AAAgAElEQVS7MEXMZ6uwfVUCuixurXq9IaFVna4HjJFR8+N3895qM7yf8xQDyZAdI7PkwmfFYIkpWYor9Eae1Yowr0KrKm5123X6eEqusBUGuTZOpn0RL8NXXE+lfZl+YDUbxgtgicIku6GfoyO0MlROIUOog8HKSlQSGadMhVLrATBLgiqWMjU/gjng4ACEwogxfMqVRSKEgNSB0OnplMkCXdmbagFivMmxaYWWIasGkQPHE5QZS8mHISFN9dBcjVXG78l7GRiyL9jLmBzIF6OyDMaQObUDwKqwIvQqLWSEnCFJrudvgjuwFdCRCf1SAJTcHf6OIAG16jMEyM5TMQCulickCvWmCmBneeKQD4RANZMsVEXJoj8/IG2J11E9zJy2AtcyfZCboMW+kY2Sp+AoYLqfgCSZqOZ9FSNB37/uaUmULiRl5O0AUJbakOr+eK1EsIvSB9svsui77MmSqmCxjWPMQ2H8W6AZjsdc+Si75Q+WNQU48wd01fft/6ou7NRc2SHCPku+gBIxQFIESj5WOkXc2Cr/6eMF+ag41nhU6dyvfIRe+I/Eke8il4IJmfd70WfJd4x8fE/bD5yU7KuGSe7JBo5JVgUTgYm/wkeJkUChWiUwILQw1LzgHfsSDNmLAEomMIJM2Vr1EbNF5Mv3BTZkuHpe9eTW91XUJVjkQsbuwyZdm3yLjKkeu77khNxgNRyRBNKb+zmMRQK8TH6r2GxhK3ur68M/Dxn6nf8h2GTKR4wbnkoe+GefUJID+5Gwiy/kJVbxQefqPVaIERdUFutdneyuKtrG7kE795e86m+E5WzJvVyz5IFww43q4RX3/G68vsfW6AmxdV+/wxb+Lilc9k7kMQ+FmTObR/TZgwSfL8CbGg97gI9sjHwsO5d8yJV82KqqvXG6r2JVyQfB5Yfl6yr/SB2yK/5pFTRHchC3JAnIGhk44Bn7lzCZs/gpCZScwXUrtMbPLpFuPuNzFV5jo69N3mRhZbh/PcSZjmA53fd7gNkj8gbTyLXsnT3AD7HTd5FF8pbQqmL2H6p2P0kXfLCUz6/4FH9iH37nczUn8oCf5AdvyULMcm3+K+Yh0vCB7cNW49JmIubUw43ilCSvOJpiC33DhmqFk1xJ1oyBfuh4ln6MB0fhCzCOH/keoowvkA/7N46N3ni1q4fCVgGlVc9VleF0tVSLFGsvYMxTHpsS2inH0r9WveMTIABZBsmQkc2qzi67N8ImkCL9DAr5LuJ8yG8sWDavff19CnkiECpKwNOhKiYzByrLgtcu5z2WsE05ppKvSozKGHtFSslKYrjo2BVe1Bj2IZ9lslZlRmyRB/6NyKoY6nmUJCyyLytIquCIjSAmMCM3/X76Zfc/lb+rklkdEaTJDPngt8jLIhmyXyQP2WG/loThrYDff8J/SjmNIbRT3s+1VHXNreQDv8gHeRlLKlUJq5WGTJFe8V7/8aHgoMRPG4WEgx+sOi48DKn30KEY3F/RmFons65X9igxUkmnM3iKCC8bi6RaQl3vDFZ0oK+96OcUCK3KmQxZVcNRvZD9J2unMIpDJbReh6LqpIrDGAGFJS3LPX4fc6jUyl5rdxgGKXP2cww7f42Z4y7PmSVPFQlZ6lh5AkgZdbV0qGRJ0sYmKbua7z4ImyqEakXfXsfKV4UIXugbFXhUmFR4psaLQya05KcaI3mtjRtU1DwAtuw9yypRiIm2JtijyoLcbrI5y65sder7aE2xQqIiy5bgrSXZZTIkf3jrO/CADsba77pz2AehRdLJRwJU8lGtI5+xpE/VE/nv+6uKbcX7deUx1fdwKEvwCCkdruMHKq7IrBUVhbmxsplqDuxRUmsubNGPcYhXyzb4UdWnH8+NFJ7uTT+nQGiBqkqB1gKHB6q2UVU8VEJLhzJERskhAKQ+o/7DQ8sMn0PpLatdishPoFpmzMuue65/nyVPBGCVdyBa5rOsa6nMof9b4Bxb2diV7PdBaDeR767w4pAJbV9+xqkXlh7HbEXel5/z9TZO2TawK7ud4j5ijvaraiuyQjYmMdrEftcd9z4I7bry6c+RvVm6tyzvENuWrcKsK6Nz/R57tMol/vu/+D82Xh2Ufk6B0O7KCA+V0O5q/u0+TQKzJLAPQntMmmjyOSZtne5Y90FoT1eabWYHKYFGaMerpRHa8bJqZ56PBBphW6zrJp/z8YVDnmkjtIesnTa2SSQwhtB6oveQ3ys6iSBGXEQ/kJ7SttwxQljtlLORgF5Wb9rYdd/XsQi4yedYNHXa4/SQj77IbT10dtrSa7PbtwS8vq7ebDF3LGMIrdebeEfnuR9eOeP1FIfSjH7u+mjzPwwJeMjDm0XaMVsCHhLyYEwj/M1C9ikBDwF6BVM9ZLrPsbR7NwmsKgE9vUv708cQ2lVvfKrnt5aDU9Vsm9cmEmhL6oul1+SziXW1704lgdZyMJUk23UOVgKN0I5XTSO042XVzjwfCTTC1gjt+Vj78c60Edrj1V0b+UgJNEI7UlC5w4gXkQ/32x5/hXZmk8DpSaAR2kZoT8+qT29GjdCenk7bjAYSaIR2vEm0Cu14WbUzz0cCjdA2Qns+1n68M22E9nh110Y+UgK7JrS2ZbWD1bXyBfEelPBSb/tb20t9naPmsO2HLg6Z0Nq21gNr9pq3l7I9sO2RXPL2d/LxY3tLO9ws29JuHV2071ywuYWtQG1U8bhun3h7yZ/ysS9CawehJ+Ue5++KCDuA2VTFBiP2c/+K3k5ifMP+86tsNjKVzsbIh83AMf5pn/NFh21r7c5jC1rYuc7hXn4ObZOOdeayi+/AT7uh2baVzPm3OPYp3fauvxQRX587hNltyYYodkr67Ij4lnxB/S7GuOwe+yK0tvP10Ch7e2xn3z+UL++/f2d/D8+dtcQr8nxM7gDo3ye2jX2WqfTf/36RiPBgLht0eKvK83OjqR/r7O/bUt583a6IuNc62/OOGsy+T9o1oS0FPDqfuLRV3FMj4uIdEbtnbp+2qkzunGT4vat+ccXzD5nQmgoC9eLOWG0FbJevOuw09cMR8eaIeH0SXyTrvitsjbuiqNrpZySBMYRtW+K4fEQ8M0G7//S2zx+YpM9WlIL5a/P1YmO3Hp5qzMvkY990eOhf7Uxw0Ja0844pCC353CRJ2jZ2VZxKdod0HTspvSi3o/5Qb2Bf2G0B/IQkEW9K4mYrUEmK+LYsQdnVHPdFaO3wdbdMniQFtVuiz5FWO1OJRXadu3BuCew1gP+0K8GcwH0kT4+MCK+2euPgjSoPSRk/rZPxw7pXt92w40u3SFJ7AlP/+Cnsg9AiWKolMjLVQn2pX9CRKxmb7JeBXykibppOwBH93f7hr8jh37LLNN6Q5z4n9xx+Xr5jD6GzFaNzbRU61XEMhFZG9h257/UsQvuqbqvKW2eFx57sMrV2TCsB9lvbYb57ENBsE0j+f9IlF6o+v5F2PO0Idnu1ZYRtm6NBzFR9VHj674fuE1pE1yv3rFaoCO16m9Zl8hFgbpZjYzcfzrmopHwgk3yvTUQE3pe2dZ+sRn9mVqPZmf+Tw0W76/1mRPxaklZEHqm6bib+CKzvXy8ifqfb7hJm2FbZGNzfCo+qGhm6Jxw2B3jqu4gawub7qpEv7O5ry9fPyMrlxQbnf25uTY7ceaf5jbKCabty15ZgIIrGcMgHQivWWAnov7rRtreqYn/VbVX9spyApEM1zM+hHPsktGQmSWNX/e2VYaC4r7JNfpdO+4WL215xPRS9TDEOhBZZ/clu9fU9cwitpItd0oHXCA7Pm2Ice7/GvgitbOHKuQSIiNqw4CNJYC2bW1IDyMroMmBLtw9IZajE3i/3dPadR3UV3udmNnzbfPnuVyYYI6GVEW4q7FMgtJIA8hbUyfOjmwqlff8TJCD5QhLe0gVwdv6xPONCXdB/SkcivjkiXpL2K/lAQtjxsR7LCNs25zWG0KrQsnnEDk4cWoX2aknKraLAQYHcUrYKs4rLB3PVha8KRrBNBeulSTBVW5CC2yXZVCSAoUitz22KwwaRecTx97LFC5F+dZ6HXKoQS7QkXKVTCRiShuwipMZzqcSO13QVNjaNeD80iR6yq/2jf75rW3pXjfvinOu9Mqh6t6SEQ6vIoqr0Nm1o7LXnEVoxFLk3RzIWb67aJRPvyOX0sdff9nmHSGg/KVcMFVosm9v84e0btNJsW4aHev0xhFYsktiz1Vud6vuI90VoVWhVH7zsGTlFtOq4QwLf47MPSY/SvbNM7jxEQRVWtYAjqBCo8mpbQBRUKhwcQyVXxWGK45gJrUCO7AuWv5/A8cdTCKVd4xMkIKgjFypWltiK0DpR9Yq9qkio8ujt1Aqi5+lYj0MltGR7lUySbW6gKrluz+kmulkmHxgskCOpSChCaTObeYRWb3D10God0maEqFrBekavZxMOPmsGofWswrDloHpq/Xv9JKSwAvb+6sCeBcMvTYKKkLBnP+7/9CTD5nPZvP+XzCC0MN/89Dq/7oCW5RfpeR6h9R1FFysF2udUrS2nV3Kyie1M+d1DJLTmd8dutfbqaf/8VaLWertX0/wiQosbIbJ82yoW/7bSc5IV8H0SWi0Hlsf0eKhSWWpzqBzqpVF5BQ4qBAjZ1yXxXURoVTv0klj2/ZwMYP0ljtXM5OPPPmZCWz20EoCTNORNFDvxd/mUZVVLrWx3GaFVOZSIHeuxjLBtc15jKrSWw/d5jJUPe/npJIpIJBycVaHtE1oBStKkdxMZWIfQ6lW8RlZzkWAtYUgvsqyCOyS0t8/lTdVcxMMYYKOKr5U0rQPXyZ8nZ2//sEJrZUKl1zKpiqYeykNanp9lL4sIrST2e7OtxWqL2HZoFedDJbSSAcnN7+aDzCf7wNIWQWhMhVbLQT8WbXE4+7v0PgitPiqkE3gDTlktYPT0oz6aG2cTOSO3XKhy4f8yOX0fAJZyLHfJPoCof5FfD1eofllSR241SE/1ZPMxEFpj1K/UX8LuPxTWCO32fW0ZofUEtAqVCi0ygrhYBj7WYyxh28b8EFr4ISHu9zX2e2gPndCqTnkYDDFU6Xx5h12W8y1fI6r6Cb3RAFbaulSfqyV+f9eGgKjAU6sCCLDKoOoo7EQoVWcEMtfw9DgMJR8rNpYhYaUVMNjr+loUvCnCd2YR2mtnBdc9600pnrR+RN5fa4I3UMBjKw+XSUxyvgfRkFn3/vt8EtucJXQSu0M+EFpVfw84zbIprRVilYcU+fihFQ72SWg9r6HVR3wakio9yBIaNsRGWxvc6l6A0CpasTsFv77t1UNhjdCuLtel32C8lqX0fekxQj5VYxm6BxcEd0+QAmEPMfx1klR9Yb6jVUGrgT19nQc8kALXQGwthXlKWJ8tMPfQw1TAcsiEVl8dUq8/RuB7ZfbEqdg8KAOQgO/hBbJsx/YkoMolsFlq9QYOAC0hAzbePvG2rH75HIEQaHbd1znl7PdFaC1rs222j3jBA8kym9eupLdTe80wwZty7mOutUw+HvgSdLRMIZsSexin4ilIsRN9tPBS6wQyCgcdyKIHlfTWXjG/6+E3Noboe+hK8iRhgoP6WGHi5+USuV5bf1cd9q8WAuciuaqOs1oOXF9vLnx2TecbP2KO1MJxdg6PrbpVsFVgoCfj/NGsaBbx1kJ2yC1Qkgi6sFxLfirL+oFVxSUX5IXASzIQdDqvQ4LrITqtGmLSvh7E3RehRVJV9cmB/YlN7EfyxU7ZkBUCK6qSmpOvIo4BjRXO0dqm3cWrOCWJVRgkc60vWoGsUlvxhhMnLd99VGhX0NVBnXrIhPagBNUGM1cC/R7aKd/AsU+RLyNs+xzbIdy7yecQtNDGsC9C2yTfJLAzCTRCO17UjdCOl1U78xMloK9bJaKWgS0NHXNltmbYCNtia2/yaWhwCBJohPYQtNDGsFUJNEI7XryN0I6XVTvzEyVgSfLmuWRsKdzy2insItYIWyO0zd8PXwKN0B6+jtoIN5RAI7TjBdgI7XhZtTPPRwKN0DZCez7WfrwzbYT2eHXXRj5SAo3QjhRUPrjmwStPJLejSaBJ4AIJNELbCG3zhcOXQCO0h6+jNsINJdAI7XgBtgrteFm1M89HAo3QNkJ7PtZ+vDNthPZ4dddGPlICjdCOFFSr0I4XVDvzrCTQCG0jtGdl8Ec62UZoj1RxbdjjJTCG0HpnoU0Qzv348m7LSa9a8sLydjQJNAlcIAHvF31XE8ZcCZCPLW2neh92E3WTwDoSuHT3Tma7u53Cg6jrzL9957glYGMI78VeiKNjCO1xi2G60beWg+lk2a50OhJoFdpWoT0daz7dmbQK7enqts0sJdAI7XhTaIR2vKzamecjgUZoG6E9H2s/3pk2Qnu8umsjHymBRmhHCqr10I4XVDvzrCTQCG0jtGdl8Ec62UZoj1RxbdjjJdAI7XhZtQrteFm1M89HAo3QNkJ7PtZ+vDNthPZ4dddGPlICUxHaRdfRxOvv+3ooYqp7T0loS15jZLLs3FXmNzy3r7dZY1nl2iNNbqenLZPdrMHses6zdDLGLpYJsn/dbc5pHUI7azz71tU691+mA39fRz513UX+uc54p7CDm+RDwvDwoRHxz2OEsMVz5sWeRT40tW9MIddVYnF/bsPvzZv3JoR2Wxg1xs6dM7W+tmiOcy+9zEaW/X3smNfBheG1t22LY+ey8nmrDHzexT89Ih4bEV8VEbb3/NKIsLXnf86n0l4aEd8aEc+NiL9eeYSbfeEzI+IxEfHEiPijOZf6DxHxWRHxPyLify+43VSE9roRcd+8z1Mj4k1z7kl+N42Ie0eEMT4zIl4REf/aO/+rI+Lx3dsX7pJvYFgkrS+LiOd3Ovi+1M/lUjb0Z7OIR2bwLQDxd7q7X0T86mZq2Oq3/0unuwfkHMjoYxFxkYi4Ryfba0fERzq7/NER8jHIMfYybzIX6uT5yRHxt0tm+9kRcYWI+J2I+Mbu/Hulf3gC+eoR8WOdHr49/77oUnztWyLiVYM3b3ia+U4RceWc9yU6fd829egeUx+rEDZ+9l0dIbpsRPxAyuo/RcTt8ud/doP74Yj4vRGDJO9HR8QLI+I9I86fdwqd3z197R8i4p45LngwxbGKfOp+/P2bIuJ7E0c/kHL5y8QqPvn1EfEZEfG8lMGyp9c/t/ONH+xsHObwiXWO/5gY8pIeJtw/8eSX17nght+BkU/KLaXpju+JaWQOz4ab4Bg/n7leV2B5RETAxB9Jm1x3wxzX4F+w9a/WnA+sNY6LRgQ8hhHG4/+/ndtlw7Q/zeu/IyI89f03aRe3zxjhM+OYRWrXIbT89TsjwvgeFBF/HxG3iojbRMT3d3/74zXn2//axdL/bhQRH+3meNeI+O+9E2wXLomyqRFu8ZwcE7lMkfhPMIWFl+DLuNEPRcQLcsvz/rg/rZs3H/rUiHhU8pB1xiQe3DDjiWuJI+L2qjbJ5uDqlZLPfUmHzR/M2MYGL5yxVCL7bzn296UuvicxC9bgS4/r7OSf1pnMut+ZgtCaIEH+WidEr/gyiW9LcgB0X7zu4Hb0PUFBQPVKiL4jDW8/BaH9nI5sPSOJhus/MInXrCoHQ7pMRPxKBrdbdMTlwZ3B/EUOjKy/owM8nwM0rxSbdzDSWyaRvmOnnz/M4Caw/Uwa5Yc6ovVzEfF/EhyRQcECWTxkQnuVBNvfiIhnpZN9c0QgcpIoSQHSi+z+yxZtyn0Q2p9fco+vzKTk7yLibhEByO+QwerWGSiAOsK76PiCDMhv7p10yQzkyEUlPxIiiQ8CuW9Ca3zsCYllywjIV6QdI1psHnbcZ4evx7tG2sizI+IbUqZeU7hM/mNNaR1C+0kZBP8gb/KwiHh9/tygew3YzTLAwxOEVlKEBEnIbxwRf9aRAKSHbcH4n0wygsy9Mf9v3pI/58OBX+ySnn8cTMr1Jcv09esdWWJzSPEbIuJFEYGMSM4RKyTXtb8oCQ9feGUSMnpFRgRJcn3dhGQEtiGnb8nkznyNwVyGySW5SujZoaB9nbQ9ye+6hHasHSw6Dyn+4pzDtTpZ0zGCS26SX/FBLIBvyIq/iQt0hsjAC9gmRs3DuHUILTkhrhIH/kqmbO2qiblTEFp2KBkjf8WZIulsk0wkmGI0QigmIX8S0GMhtGyOH/KTp8wgtJKGh6eOFQbXTaT5Ivsgn89PTHt/h68vz5g+1k4VCvC5t6Z/KwhKanwOH9km30Fi2cLXZEJYHMbfFWoUJiSZOz2mILSyXqRWdqXyUoSWYlQ/GCNBILayFX9/W5I0ldyfSENmoAgUQxbYASlQpuz+ARgRlk9JQGIkyCiBE75sUtXz6Xm/h3SZ7pPTYPxdsJdhCjTup5rFWREixvDnczQwBaH9unRQc3PI2J7WyeedM+4JuICTH46NkKg0G7dgIRAZq0qESs48QkvmAIgeOBUSreID2JEr8iGDt+f7RCt7dA9zfk0acclLAEGK6bZkLuB+YZI5QWyXhsz+JCTmR55+F6CMF+CzF/JBWMy/9C9zJE8gqvIATIx7kb0ICr4DKJAewZ2dIxWqwJfqAs/LsorgnqrxkgT3rgOpQAjcHwipMAJo+qNzxMDfVZFe25HxH++CF9DnW8ADKeVDKrCISwUVpAPQCEKua3yqNUiIoOR7xiOhenWSFDb14QRcmbxrSuqMybtTF61Y1HxWJWyqFexfUEY4+HrhBpszX7IUvMgEQCJrwFrihqyoZNAB+ZsjOUgO6nxBhIz6lUjyMd/r5/n+zlbYuKACQ+CSz12bX7ku/6Qrn5MVW1cpNWbjdM6iY1X5DK/Fr8zTON+dZB9GqsDAbzbPxuiWbNiPqhZMpkcJn5UxgY1sXctqlbHzZZ/DZ4SQv6i6OPg2ovS7GSCvmTKSkLguP1JdUi0mdwkUP2Lr/qbaLsmDqVYeXMuKz28tWC1bJ/gNCa3E3f0r/pAT+zHmn825SJoku4iUGMD3ESqYpgKoEoWwwzK2BkP8rkBD75JI9kKWrvHetEP6EGPEEjpA3OkHpvJJf0NSHWwMSSMzhBExRQr4fRFa2A/Xyv/5ADt2nV9IUsvWrXqw0Z/q6W8oy3UIrWuUv7IXZNP46RROSAjoW4xQpWaX5g2/8AEVOzGK7ODJrHe40x9dKaSwQ7phK2TJ3xVfxHv3J2vXEt/ZO1LPpr3r+fIZ51SxjUdSTFb8gb52WikcCB9XgRt8bJjMmacE9YrJaST47JGfwG34wR7wJ/jElvgTv5Nw8n12zRbFZbbIj8nHap2CFR2RKdtiN2wf7rKv0pe45ffic+Tl3ftFaCUziLL4Z3z4GjwV8yQdFSvgq/FuUm1eBwf+/TtTENr+zRlVEVrkQIAGLowfEBKG9gPB1vIIY+PQgj/jV6UR1GSpnBNRAAhVIQQKHEMAQk5cF6G1DHLndCQveQdSBC4oMhDLd+4LQBiIe1ECMuNaHMb/t12hZVQybYZahLE/v3mKJFfLLoI3oGD8gE6A5dCLCC2QBhSc2vctHQFTnyM2AJojDJcMa3wAjbzIjz4ECESY/IGL6p9zZWyCASBZdZljbQNOB+wTWsGBo5mPqhIAZnsORIr+gSZiL1AAZXNDfgRDc1tkL4BXxmoJ7OJp7+ZMt2TAtmXkwJutkhFyBGjokT3WRiWzCC0SC5TZBRtVfeILzmUDltcFaLatalcZPTJD/u5nyZ49s3d+CPD8GIPkBflzbX/nJ1oczNv1EGKkm68iJcuOVQnbkNBWpZZtwgvVRGMyRoEAOKoYSMD4Kf8Bog52L7EzZnN3vt+BNJKFxBRBc1/Jse+oLNTfAT8QRrCrwu3/CI7kRiB1Dp9TYVR9EBDY2DbkU/I2XgEbaYQXfM/Rl5fffc7WJa1w0k/fH5AwMpTg890itHSPGAzPR0qGB3sjOzaEzJBPVbD7LQcCJnL13UlQkCj2SC/0ZpVkjMyW2Vz/7wiReZmzeCYxpyOBHwnQ58tnxSW+hJTNIrT8ZHi+KhP7gR9sgU8juVUhJEtxB/mAJ4I/EkZO/FeCaQUNGXB/5yFbfFOCguAMjyIEZExW5mQ+7Ftyyt+Nh97NEWnbNaFFkhCpwg4kSdGInCXdyA27Y1tWx+BJFZUW6dY8FGDIzpzFN3hOxggSQqvFSkLpHHogJ0UxK5aIIQzGHyTwuAV+YJXKiti+jjGEFt6yIYmkij3ditXmA89qtcG1YCGij3SyafKFExIeuEn+/FLhSqzhl8gqbsTuJKniVZFjSces9o1qSxTv3B8+s1+6ZZf0rjjYb4M8aULLgARxBsnZAQISiwwIKP5PaQRKMcgZ5fgpAwQO/QoXoC9C4XoUJlsWkBmF61rCBaACDyBHOCzVUyZHAMZ1P0aBnO2C0AJSDm88Musaz6IlfYBVy4jIDCKLgJAZIwW0gpOWj2FFTbZVBm7+skQVOqCsgoOoMnY9MkhX9WjRW59wL5KXbJEjygotU6zbn7cu2AwrtMYN8BF4ARuhpV92YI70r4JC/yoJgooALOggdALFInsxziGhRZRdg+1JEtghAqTiAoQBDaIqcRBwq597FqEFzsYpwFa/mAoEe6Y71wM0+pQQ9lpi5BfmhLAKwogYMHSO+Ugg2Y7s2jmuw9+QDpU/BE1lCqG0cjI2AGxKaOkGiSpCav7GiISpPqscICsSMKQXmAJNyS+CBEvYLxt0PrygC4nfrIqVYIHQIqy+X9cTGB3u7/8CJEJSy/CSQL/TQZ/QLbPbVeUzvJ5ARa/aD+CFRGRWhfZrJya0iATdIBYOtmPlw2eLCC37QUSQGwe7kvhtk9D2Ww6qQitRh42wUsDlD2QoSeCHwwqtalf/fHNEGuo5Aj4CB/mRRBXewU6ra+4hflQFEflCANg0kuZz5BcZQwLZH1KBHAyJxDxCaz5VoYVR/FpcRCx2TWjhiaIR8sVX+RtMRCLJy+f8kUz9Dk+WPVsgIZew8nEkWBEGIVMV9H/3qQIOP4RPReAkmjDR72IgvPdHT1QAACAASURBVJAEwwIxc9kqyjIf3vTvYwit8dMnfgD7xBBkHB6JU0M7UYgjF3iAV7DxkocVGYRWPBePcC+rbxIknImMVW8V8OinfHU4z1mEVpGgX6FFaOmtioEnT2gtlxM4ZY0htMibYCMLBOZ6iLQe1DEktBSib5EBM3ROIKNRORSwABmAOQRCy1gBvN5XxIthqXwseghGJQ75RViRF4aMsAMLGRPyj6yphAji/cP3kBcA4X7AHhADWtcgV4AsqdBDizxUtjWW0CKUKp1AxNKcoLdLUjsktDJ8VTjOrIoA7MwVAAOJRYRWwHHOInsZQ2hVBFTNBEEkka6AjJWEfp/bOoSWDZA3oiUoFtBZHhJs2ZYkTdARABCxZYRWQoWwCPQInu+R17Cnchawr0rYhhVaFSxgy3c9FAOUBUNLYosILQKBdKjOjSG0NT8VPeSPP/GbRYSW7yEiloPJVxKJTGyb0Bojmaio8Ef2LFBLQKwo9HtozUHwgrGzKq7rVmjNF+mrai8c1X5hqbM//0ok4LXiBRuUKFe/dlUYEbJtVWj7hLaCMx1LDAVcuGic/EKAn0VoVT9nnc++YCzs5hdsEo4iShJgyWP/enB4SGitWCEfkgMVYjpFVPjO8FhGaN0P8a5EBx4cGqGFSfxNtZoPSQzgybxWNPjoPEvq4rSkk6wUXSTuMBwu69EWMxcRWkUEBNJqFh7g/1Y49klqpyS04h1bFAMkAf61wriI0IrJSDE8sdoiSYAhYuQmhBbHwhm0m/AHem+EdlChlTkwRktrQJ2BykbrYNyWkTg1pwGgqpBAHXD5m4yZcBEafz8UQguEEHuBgmEi70B01jKf+Zq/pURVD46NAKku1uF3ALqo5aDOVeGqirhKoqwNiUXw6sEO2deqhFagUkVWdawHRnb5ENmQ0Bq/JX+yE+wFG8RMVdpcNyW0slwVFlkqoixQWk6TXJCnXkK2KNC4P1sG6JILR/9ho3UILYKgYqt9wJJaHcDf3FSAgYwxsA1J5DJCi3hb4bAkKrADKAF3zENkmxJaCS958gs6006g+sompyS01b8OV5Boh3vOI7QIJHlKTpAQ1QoBYReEli0hjiqAEjQyRuARKgFJVRoOIm9khViZ15SEVpVNhYh/W+JF6i2bIwd9Qivx4PfINnvjb4gM4oXIWR7Vf7trQqvCrj/YD1wTL2CAID6L0PKT4fkSXLGHTSLzklTXsgLEn8UVSVi/hWEWoeWn2pjcQ4xSsGHbs5Z5lxHa6vOl8+qjFv9ci23OiyVT9tCOqdBKXFWj6QHhEntmPUSmcAKvJfwq30iSaq54Yk5wyQpYtRyQ/7IKre+4nvYMtom0wd19vRVhSkLLL/mgJN4Pu1Qdn0doxSMYBiusLqn+wnXcYxNCqwhnZVghEQZUhdb1VWwlmcuq8rMKJBt9NmUPrcCNeAFchskI6ym7espPtVXwImTGLXMQmGX3QFrDNDLKeDkNw7VM3j8AuWUjQCLjE6jcR7ai9QAhRhhVHZFFyvS75SbXJXj3EzAsyQI34wYUQGdW1uz+UzwU5jqWwAElkKN4/6qqqWogSHX/kqeKrIODyvL7ryjqE1qkTfUBWWXgw/aDPqHty8tSIHnQS98ALSMJaEN5qXIYm0AKLKoqI8OmV8a9y8NYLC1JFoxZYBVsEE22oxoNAGo+nBmRMXakUy8R8sY+EE86WGQvKj4ILJAmH5UsVXDz9rmgqffOPQQnwQYIs1OEqN/zSl96alUe+AtbZZfsA3F2LySFT3m4x1h9xz1n9d+xB/dgMwit+yK3qh30hSDxQdU2S3aSPQkjAisA+RwmkJdKyJhjFULLVozbfIxH8inIV4+gFQNyVF2jRz7ONyRfqjiwgW6At2qOyhkfllyQvfPhhmoOEsqfq72j8EH1R6UVUXR/4+iPRx+lqof+PEvFSAyiz6e0TpGrhI2+tkH4+zLv4/O8d4/W54veY1l/W/V9nrPecTrrPsN3X84b9xh7WuWcekZDzyS/Uk3W2lMyYW8q8fCATfMH5EblTrxRqaJn+MH3FA20KknQkVaYz9Z833f4lkof0mWO4hz/Qg5cX9IDR/ko/2XLMBEGiHUIAHLjkOwO3+PLxvgd29RKp1ChGgefJawOxMR43YeNO899jIcfwLxZS8jrEFrzIT9+ZbyVuJCF360WII9kJmHhY2RRbRgSH4mQeYt79XxCfyVRjHZdc3Yo2PDbikV9Qmt1Ez6K83DLvI0P3sFH8qJjcRJmiG0IH11WL/0q9jXFuWyJbZmnNh5j6z8YRra1kgi76I+NwBzyrYcrqwLqes4TYySa4h48khhUr209ZKYqDr+QS3KoZxHE/2o7GI6n5oyziYtiioIHfxEf6KMOnMPzBTgcn2N/ZK3IxGbpo190mUKeC68xJaHd+mDzBv2Wg7F9flOMbSpCO2sslqUFUVnkogfTFs0DICA6QLye8p1i3u0aTQKLJLAKoT1HSTb5nKPWP37OSIEqtcRVQcCbK5A2Pd67CvjrENqpNIdnmLMYZ+l7l3F7qjm06xyBBI6N0MqUZQAyEBmK6tWuMq9tEVo6UFX2hLX5jHlV0izTkgmr+Opfld21o0lgFxJohG2xlJt8dmGFh32PenUgbLcqJGapYqpsbvPd2H2p7JPQKrYg9Cp3Vmj2tfR/2FbSRrexBI6N0HIIFVrLL4ibaua8J/Q2Fs7gAtsitFOPs12vSWCXEmiErRHaXdrbMd4LoUNqtTj4v6qs/sdZ72Xd1vz2SWi3Nad23SaBj5PAsRHafaqvEdp9Sr/d+1Al0AhtI7SHapttXP9XAo3QNms4eQk0QjtexY3QjpdVO/N8JNAIbSO052PtxzvTRmiPV3dt5CMl0AjtSEFN+JaD8XdsZzYJHL4EGqFthPbwrbSNsBHaZgMnL4FGaMeruFVox8uqnXk+EmiEthHa87H2451pI7THq7s28pESaIR2pKBahXa8oNqZZyWBRmgboT0rgz/SyTZCe6SKa8MeL4FtElov+vXSeC8T9nJzW9qtc9gQwIuTbRiwqzcazBrnLiq0XktGZl7yXy/g74/Fi8SvmK96sWvQmK1Jh3OxM5OtcIeH9yN6aTO91eEF2LZX9ZoZO754UtebJpxrVywvfT63o96p6CXi3qdon/JVD3r0zuB6Wfqi79ttia7L9r3s3Mu4HTYnsevQPo9dElo26BV3w8PT4myUXAvT2KbdbPzNjoK+54XlXpTvCfNdvQtzl/LZpx20ex+2BBqhPWz9tNFNIIFtEVrEzA4UdlTxQmVk1NaNdt5Z5bA7kB0qfM8OGqt+f5V7LTt3F4QWmbVLlO0iXzMYkMTATkWIFGJpS0a7Jq363lpbQCK1Av1Nuy00fzF3c0Fk7TxiByzvCrQLDfJsxys7s9iJxU5NdmeyJ7sdWZCtczsunrtG2VXIril2jurv3jZGHja/sIuKxOAS+Q5iMucrdtThP3bMYe92u7HrjV2KHHYyowe+a3csu+bt89glYbPbm61q2amd1+xQY0chRNcOTl5W7zN4Y7tS24MK5BI4vmPPe7vy2D1O0riLY5fymTUfdmJ3NL4ugSrMt/OgXabsZsfGfG7nM7sm2j4Vxgy32t6FvNo9tiOBRmi3I9d21QOSwLYIraoqAlr7wQNGVdpVXyJtWzfbfdpf/uFnQGgFXO/ZVXmzrWp/0wgysHe3oH7VJFO2s7MF4CoHwmq7QATW9WwtitzabtSGDD6TRKjM1r7stkZVMUbEbKdn73KE9xwPhMr2jrZXpSPbUCL8qxzIAhKGpNoyGKmwTaTPbpUkVwJoi1Zbatqa1faFkhdVdD6hAsm/VBz3eeySsEmmEFZbXsMDSZVtHK+Wn9XWnLaCtCWjc3zHez8lgva652Pr7sa3jpx3KZ9541PRR1pVqdmOLSolBWQpYbXa4v+whex8ZutLCbakqb0Ifx3NH9Z3GqE9LH200WxBAtsgtJb1HtUFmPsmEAJEgeVxXRXle3L51N7tAJWTqW4hSAK2PbCBp2vU+cYoENnH2f9VEFRgEDGE7wYJvvbKFrwEOPd2PaQNEUMKHMgYYo2wqd6sUvHddoVWFUmwtUe9Paof3FsWVbmzt725WnouvTlXVYpczVdV9zZZcX1gkl2VQMTnCUl+ai92Ab4IrUqrzy3ZOpd8BDikzYvAVSEdCC290BdScaqHXdfIz17rCCP7YavXS7shK3ogGzZkj2t7V9u3nVyd/5Ku4vqCiPjtlJed7dh3tQ6UHui0CC2Siuza+5u+EC92p1rLBxwILeKhHcTWmbvaKW+erndJ2EpmCH4RWttF+5yv0xE/scUoX5J8qMzCFHpRmb1LYs+ubHeX8lk2J/6LzKrw15ar7Ird2i4b2UV87cbYCO0yaR7X3xuhPS59tdGuIYFtEFrDqIqS4KLH8E4Z/F+US62Wat+XJPWtSciqZ1SPJlKmqoAQIKqCkQCGWN0tl7yfnwHsQVnJQujcT2C7e1fNsrQuqKl6IWjIrmV6VS6BDhlYZbl+m4SWHhBTlVLyMhfBt7+FbRFQZOaGuRz4jKxOWU4UxJEwAUpl76lJaG2HO2u/8CGhpTeEVrVRzyF9WIJUKZQkIHbnQmitKNw+q69sxfI2OyMTBNQPOSMHkgKkVRLFpmsL4j9MMjW076GbDgmtlgNJheuwT4mFSjxihAyfM6Et2Q0Jrc/5Pf+/QiZbVhCele0zVoYaob3Af4eEFq7xbzYsEXtxR2pflqsQrUK7RlA90K80QnugimnDmk4CuyC0KqKqq+/O/tDLdj1algb1BaqAIa2Wueq40OB81StBHyk1XpUv/1el9f8hoUUE9Bk+utsr+zoJzIDaUruqg2Xen89K7SqS3Cah1VpBJv5Fmiz/649V9auKXhFQFaevyUoKQmtuHhRCoBxvj4g3pAw9MPTSOZOcR2hLvoiUxOBe2Q9N3udCaEtkV8pqKbuTTHmQqAitSjXCxH6tNkgm/IuEOk+1XGIikPTtewyhvU+vQsuOL9m1eNwz+0Ubob0gYe5XaPuEtiq0kjy93rfI9plGaGcTWsmTlQYJk75wqwJPT4xphHaVCHHY5zZCe9j6aaObQAK7ILSIFuL6gSRXAoslLaApKA0J7ad387I8++YkwKsSWsB8vySzHhh5ZAY0D1V5yEmAA9yIsAcjxh7bJLQe0qqHXRBYc7akrF2j9vueR2gtT3sgRmDSu2xZ/JUTEVqETo+ovk4E91wILRtEIB0q095IgLAuIrRWIbQJqIarEvqeJGVTQsteVeWtVKiYN0I7jtBq3ZBUkJuEQktPazlY3HLggUcJAVvX5sTfWw/t2Ahx2Oc1QnvY+mmjm0ACuyC0Xp2jqqgvVNBHKlW5+hWufgVLwEZI9XKpVF0zSYGHzDyh7EEQFVoPMgBfhNhTuQin6qz+MN+1dGapEUFU0UEYVS61NHjI6bUrPhyyLUJrPCrHiKuHtYzXEjcSo/paD1/NI7Sq0HpoVVJVdi0fei2RqvgmFVrXIF9k+2a5jCvAqRyrgHtw7VQP89RPqBccqe/3NM+q0CL7ErTXpY1qCXlnEtxNCC0Cre9WGwp96rHlH0iaw8M7bH+fxz56RJdVaPmRpFm/bCWK/Mfqg1UHmLSrYx/ymTe3ZT20Vnq00MBQSVyr0O7KSrZ/n0Zoty/jdoc9S2AbhNYrhxBG/av+r7fQK3KQVNVDhEtw9hQyEobIWc6tJXMi0cOouuVVUQgewuuJckCrdUBvqaVYS++u5fr6RpFO56sqXCRl66EZD+2oXiJ+Dkv1Xo+1yrEtQvv5Se69wknfL3noE9ZH7E0DZFMkn/y8e1Yvsr8jPL7jATm/I/F6i/Uok583I5B/vxfXnC1h+zvi774SBOTXQ2AIbB3aH5Cnj3TXuHnqywN7yC75+/wUDxXasld2pbpPruZtGVtbjMo1+7a0TR9aWSRpPiNPNlz2LTGZ9ZooMmW/Dj3QL8+e5f77aelFxaze48yWvRnBoSpfD4vtSw+7JmzacpBViYVDVRyBZef8w/K5w8N6VoDekf7AT1Qd2btVG5/v4ti1fBbNid97SJQNkYPD2zUkxQ7+7pWBxgxbne/VXu0tB7uwlO3eoxHa7cq3Xf0AJLANQrvvaXkC39KsIOcA4Miy6uwmx7YI7SZjat9tEti3BA6JsO1bFrPu3+RziFo5vzE1Qnt+Oj+7GZ8iofW2ANW1ej+nZXPLtlWRWFfJjdCuK7n2vVOWQCNsi7Xb5HPK1n88c2uE9nh01Ua6pgROkdCak77UOrQcTLFk1gjtmkbWvnbSEmiErRHakzbwE5lcI7Qnosg2jfkSOEVCuy19N0K7Lcm26x6zBBqhbYT2mO33XMbeCO25aPqM59kI7XjlN0I7XlbtzPORQCO0jdCej7Uf70wboT1e3bWRj5RAI7QjBZVvUKi3AYz/VjuzSeC0JdAIbSO0p23hpzG7RmhPQ49tFgsk0AjtePNoFdrxsmpnno8EGqFthPZ8rP14Z9oI7fHqro18pAQaoR0pqFahHS+oduZZSaAR2kZoz8rgj3SyjdAeqeLasMdL4JAIrZfX25DhLfmS//Gz2M2ZrUK7Gzm3uxyXBBqhbYT2uCz2PEfbCO156v2sZn1IhNa2tbYZ/aPcAevQFNEI7aFppI3nECTQCG0jtIdgh20MiyXQCG2zkJOXwCER2kMXdiO0h66hNr59SKAR2kZo92F37Z6rSaAR2tXk1c4+Qgnsg9C656Uiwt7ql8n/fzAinhkRd4+Ie0XEZ0fEsyLiXyLidrl3/R26yu29I+JyuZ2tfcftCPZnEXH/iLh0RPzPiLhqRDwx9yD/PxPqpBHaCYXZLnUyEmiEthHakzHmE55II7QnrNw2tQsksA9C+0kRcZeI+NSIeHYS2492xBWpfVTXcnCniPhwRNyjI6YXiohHJ/H1f995ZEdw3xQR14iId3Tk9+n52Zd029t+f557rY4MPzQi/t8JFd0I7YTCbJc6GQk0QtsI7ckY8wlPpBHaE1Zum9r+CK1taW8VERfvfp6b1daPRcSLIuIZEfGkiHh/91aBL4qIJyfhvURE/GFE3CgrtK9NBf5lRLwvIm6eRNb3vzYibtCRde+MbYS2WXqTwHYl0AhtI7TbtbB29Skk0AjtFFJs1zhoCeyjQksgF42Ip3Vk9JYR8YqIuGtE/FsSWFVbhNaB0F4sz3lV9/aDO0fEl0fEAyLiM7LS6zqN0B60mbXBnbAEGqFthPaEzftkptYI7cmosk1kngT2QWhVaG8cEaquvxcR/1/XC/uPEfG/IuKxEfETEfGaiPjXrmp7yYh4YUTcLVsS/P6CiHhxVl+1Kfj5rq5n9rIR8YSIuFn20T6s+96fT6j61nIwoTDbpU5GAo3QNkJ7MsZ8whNphPaEldumdoEE9kFo/0NEfH3X/3qTiPDQFoLrM60DX9q1IPxFklgE16Ef9t1JeP3+1VnZdf4v5Pe/LVsYXhkRN8zr+RuyizBPcTRCO4UU2zVOTQKN0DZCe2o2fYrzaYT2FLXa5vRxEtgHodUq8D0RoYUA4fzMiPjuiPj5fAftoaqoEdpD1Uwb1z4l0AhtI7T7tL9273ESaIR2nJzaWUcsgX0QWhso6IV9XNci8GkR8dcRcYvu57cnrKZuQyWN0G5Dqu2axy6BRmgboT12Gz6H8TdCew5aPvM57oPQHqvIG6E9Vs21cW9TAo3QNkK7Tftq155GAo3QTiPHdpUDlkAjtOOV0wjteFm1M89HAo3QNkJ7PtZ+vDNthPZ4dddGPlICYwjt5+Y7Ykde8mRP+4rs8Z3y3bYnK6w2sbORgAc833I2s119ouTz1gNvp1p9Vu0bxyYB8UvyaTfNdjQJHJsEvJ71l5fh6BhC65xPPrbZb2G8z8udzP6fLVy7XbJJ4Fgl8IHc7GSqt4kcqxzmjbvJ59Q0epzz+bFup83HJ6k9zhm0UZ+zBP4l9ypYKIMxhPachdife2s5aJbQJPCJEmgtB4utosmnec0hSKC1HByCFtoYtiqBRmjHi7cR2vGyameejwQaYWuE9nys/Xhn2gjt8equjXykBBqhHSmoiGiEdrys2pnnI4FGaBuhPR9rP96ZNkJ7vLprIx8pgU0IrQ0SbIZwpW5zhKdGxB90W87+Um5jO/L2Wzntit0Y7hcRD+02bPjvE95hDKH91G4ns1dHxDV69/2GiPjDiNCDe92I0Nz84MG4PiUiHp07ov3khGN2qf8UEffq+k9+KCJeGxG3X+P6l8vxX2XGd83XvLxT2GGHt8dExJNz++KLRMTP9mRyj0wO1hjGzK+Yn406HGT8sSUXXud88rt/RNwlIl431cAj4jq5zfNHcg5v612bf/146u33e5/bWc/OeF+cPXH7fkhxFUJ7iPO9UUTwOdtw3yYi/mZC/brUKvJZ59ZX6O7x7elzf7fOBTb4zudExPMj4j6dbxzqswVko3/0nRFx24ggozum/zxxooekvqDbqfK53cN/14+IZ3Tbsj+o9/AKf711biBkG/f/3ZM3+f1cN6Z7R8TvbKCHMV/dhNCKTw/Jhz/f2G1R/5+7HTp/JDFLbLtlZwN/HxEvz+3rf3XZwztjBjw45xIpqy/J+Gk+x9K3/1ndrqz/NfmR+LFs3M5nmzeOiJtGxO+O+M5Ykd4pIp6TXONbI+Ive1+8aNrx93d7Bfy33uf0/8gcx0tyh9ex99vpeesSWqSA0/5TRDwrAcJWtt/Xkae/3ekMLriZLXMR2dd049pWgB9DaC+f9xfELpSkGoFFBJEWZO+lHfl7QkS8Io2UDr4uie7TJyZ7ZHPliPimfFMFUELyfzEi3ruCni4bEZdJQmwr4hukg5K5z+ncv8CcU5gfwHlDzvGzk7D/dES8aYX7jjnV3B6b5I/8lhHaVc7/9HRkTwa7x0fHDGjkOQgpsEIIvjMJPyAhS/6FtEp8BAtkqw7Bk2xt/fzDEwXkkUOeedpYwtafr8Tgazv8MF8Ecl/z/fyIeEonwx/IRI+d/kq3NfeUAXmMfGz9LQkW9C6cOyg+IoMKfPA3vvXstPN+QPyqTLQQjCmx14PA7Ax+sHtBlZwQlzoulngF9/sBcBN7mvK7xodkKrzwFYkh3fI58yHvf97whmwXHiL0cEJyJJmH77Z2Z/digGTVv0VofU+R4XYRgVi8Z8NxLPv6uoSWbV47In40MdyT5jfvYu3VEhNtkqRo8Wc5H75duL9sTGP/rljywNzqXlx9QIfzP5j6HHuNfZ3Hj+4eEQo5iiKKfosI7Rd1haCHdWT2NyICeVwWz1aZlzdd0BvbhC/Ggcd54Eoxjn/TrcQebjngj5gPJyWGiizs+iCPdQktJTEomRpQIBBVPGSJMP60C9bv6rKAb0wSJ3P71wzgMoKvSQEieC9LpwecBM147Rz2V/k7UiGzdvxM/l3V06twgBJguFuXPV4vDf71Sa7ensowHtVjlWTjYiiuB4AEL+P66lTaH+U1ZilrDKHtf898BCKZO4e3IxpDuGcHeObkiVP3dtg9jTEZn89k9cj5P6aBCSgXz+2CVbkumc5MxhVgfAdBogef+b7POMelktDaaphhyrJVC1z/DknCnU83DLp/v3/ogFjGKEv7i5RzEVrX/y95/SK0n5TZ+5uTOJszosCBOMMqRHqM0xiDoKCi+YIRADD2fOepnNwwqzu/3lWif62ns+HY+IRKDJJEzkCdLmfJ03cRfwHQD/3Qv93zAAngoWMgCLz7hJbPuqbkybleq6dK7v9ASUWKDwmg70/9CjZs5WYZUAX4r8zxSUqcxxfZFtvxXQlY2eciPYwhbLPmK0DVU9fmovKyaL5kohr0eTnfP+70AgfYrO/TjyoOv0Ou+Pmfp88JyoAciWaPSI2/qbzfKn3UToVWdcznxanDb0m7cj4ZDe9nPMuqLWPkw2ckvexGAEP0vR2h8NA46eYnMsgNCS07/a1MomEk2cA79gDbjN8BI2G1FZN+ZWaWfovQwr0+wYdVXkXmuuYmGaM3MmfT8MR82NBvJtmDv871d+QIBhiLbc+Nd1tkmB+YL7y1vTr/VanlB/Uaq/IfMlOUEXdgqPF/YeplaE99eZEHfJeY/VsWdWCRCpu/wQTEWqEFPvUrtPTD1iT6qrX8nB3zBTgCA/ilOGsOSK9K7jokfF1Ca+xsj94UQsQOfuB3/ithgO9sU8LlHPMnD/HV2CveiyHijDhFZsP5sBvxmtxhFpwiL5VKxIuPilniqmuLJ+6FL7if812jfz8V8L7Mx8SUqc8xb3HY6w0XVWiNXeJF//AGrvOVeRjDflRckXx8h7/5/7z5kyv7hjFVUJCAsCdFNfeHJfAG/tfBjmFSfVdslNiIFXzpfyQ/8a/iIn95R+pwp+R3XULre1fPDB4xRI6QVhO1nCN4yOg4ggAL5CztWYoGvEgsRVCaz1QZACRnAACA3TK2JfJ3J2kmXKSIwlyToToP8N63y4y/LIGBQ1CM6tZdMysC4JQN1FS2BLsaozFTCjJpOV4lbtbyzyqE1jXNWVAy/v6B0DIMYypDLULLcYGeYISYC86qH+bqB6EEugLpNbMaQIYOpMjYXRcJQ6iAjzm7nkq6wE4v5uJvqpUCjQosowaqlu/rfkjQ8L2FyGwRWiBdBIu8VewFEI6rClJk+xgJLeKkhYEcAYAADJQ+PAPt2CCbpHe6lcgBI4FRdo6YkOksebrclyeQy4AFMPqTrEk+VNVnEVptNT+VCQW7EFCA/ofSJ5AO9nDVGf6oRejhOa8nJQGSkNC1CqEgJhEb887KMYRtKDLz5efky4ZWna/kUDVSVVKQM1b+K8gC4kunXauGIBnsGoHmK3TiM1U0icH3Jr5I4iTnAs6rkiQ7D974jgBL5nU//9L1smNV+SAARRB/IQmD4APTVBit8PQDHN+mQ6RI4kmPxgn76J5dwAsYh8SbB0xattpQhBausi+VR4QByWKTVlrgk+oNXSIUyK35VKgAKwAAIABJREFUSr5hOvtDNmAE2/Z/ZAj2OAd+I5hTVpaH+uDHVoxgkODNdvinapk4JAkydj+WVWE/u1Sc4UOC89CeFumc7swHDltdYY90gnghlUNCS8diKN1KLtmg8arsqsqzQcSF7uhQDKSPVY91Ca14jlSJZ4oU4pIkgKyQF7gm9rMnmE/O/If+4VcVBV6U34cpYj3fqflIrtg0W4ax4j7SC6PEUHZWNkcWCC27FseNS8LE98UdWCI+1f1g7pjEfFV5rnL+WELLt7QDkCkM5r/fNcc/JGtiriIcbEBIYZrzyYB8+Oi8+ZMXOcFQRSkkmj/iCXQ2i9DSCe6gzcm1JYX4yStT9nyJvnARfiN5wQd2dqxLaA3Qd1VHGTYAFSQ5G+cHbBwTaKk6WT5lVJxKViVoEA5CJaCosCANwFFwIgQkj7OrpqomAaNH5T0ZNCE6D0kTmATJZ2bwQZaNCxgwbEqjeCV8VZg/SWcxFqDDWYzPfBiFatnwWIXQcmpVQ4DZ72sTWAGp8fTJQr9CKzAxSpVRWZAxmotEgJyq50rVRPZTGRA5uA69AFUAIWMGyv2KqooA3QAl8hCwETGBhd4Ex7rfLEOcR2gZt6AFcOhQ5cX16eAYCS1AZs/fkTJWjZB1AorhIfNlM1oeOLJlOM5NHgCKvulv1kH2AIgtAwkJi+AFUNxrHqFlCwIeX0C2JYPGUOPld3QqgeM7xiC4IxmSHImLqhR7QIT4Lx9xHlsaGwRWJWzrzpd9kW/Nl5+av2RatQYok4FzzIn9s73CKr5hThJrVVnBAD6RB7yQSBQ+kX8llr4PL4A8vdb9llVmS9erykdQk6CbH/LFH+kGTtHXkNCyU3jBZ8kWTqmwwE0knw3Rrx59idUqPeDw0DUlvCpHfuC7gMUfVFzJCd4gZWTMjlXfLKeTlYNNImlkDRcQIQf/2Hb1DB6yexVTxId9iz3sSbxQzVJlJO+yHbjLf8UfAV4M6dvTvAAN38VCcQpBQEpdS5FFNXoWoWWrfJWu3YtfGhMSbDySGTFDhUwyTb5jba8/znUILdKDLCGO4mYRWveHIWwTvkhUFETYAvtUPLKCC/99zh6dC9P4n/lYeRrOp2KYpJoMyZ9vs19E1/VUaF2PvuAeGzIedooTIMHsse43T1e7/HwsoVUAlIjiRHxJAkkOs1o4kEpzdT7upDAoyYb55k8+fVLan6/xwDwcAkYoHkr2cRJ8Yx6hlYTgNHBQNVbiIdazX0kJbuJ3fo+XFP7uTNbrElqGx8iQLoOWWQErIAagZhFalRhgy+gJEpHyO4d2yCQQXBUKgYqBylIEF9UCDk347occyAQqWCG0teSNqCHQyJwgxQkQOIDr/6pYrllL4MgEx+IMnBcYz8qAVyG0Mm0EW4A1BocMXTbJIPp9aP5WhBYZku0CC44r02Ucxl9L9QI6cDYHoFDLdWTknpZJzV+2LBD2CS19lzwEc5myim3pE1gO7zc0xnmEtuTvfOM1JyBI78dIaAU8suH45sD+ED76GR7mDsCdL2iyR4FIhUKQQjbmtVogB+4FHOhHnx2SQn4Cv+8JclUZrop4ydt9BGRLpKr/iAxgUpFE4BCYIaHln2yMTwhADkEfCKpGCqRj+7dWJWw1X4Hescp8ERArE+aLUPkdAKv4OZAIdk9GiIslZsBKlsiFYKqiAPg9yFQEv3TsWn74PyySjPBDAdY14JK/r9Jju4p8kHJBit/DDvrk77BMpcy4kKv+A1j9HtoitOaGRPUJsBU19ql6KGAtazno27gACNslXEgbWSKoYgBcJFN45LoSeQSjlkMFVZiL+BgT8g0LXU+/INvcxQNlyI9eVcEeoUXS2Q/5wjTzYffwjz2Zg+RCtZZcyY49zQvS5mTuKrOqlbDeXMUzMcU1EDkkrQhptRwgLfTC3hAU7SfGBzuQFeOW5LBbfi3urnqsSmglMzBNgi0+6N03L/riD/yYrKqPnx/zD/ZZ7TswRKxjj7CFPYqx5uMz1fD+fNgZLiF+qeSzf1W+PqHtX4/eVCrJic+zTTKt++3CrsboYSyhVdDjS2wAdvN7/IjdDZMYJJTs4AJyybacI2klN7Fn1vzZodVp50o88CVYSp90A0MRU/7Jp4ufFP8S/xBaiQqMwudwPzqHCwgtrJRAw4udktp1CS0FEbyMzfIVwsL4kTUTlWGYEKETjGqIyQGHIrQEJXP3Ayxci/MI3n4AhKUGFUuHKi0AAjYygiKKwwC/KqEFHqoOQAUh5LgUNTzGElrKFDiRCksgAioAMDeECLADctmOJfoyGNW1ZYRWRYTTWjYUJCxFFyEhK4aFPCGqjmGFtk9oARbiaUkcYQPsMnEZb59AD+WwjNACFA6CgCHUEhz2gWBYttTrM+Uxtie27jn2fLJGjhAY/dpAEtGY9fCGc9kkX/AdgM1+tQSw93mElh1YdpOJc3x2wkYcKjqLKrRDQutcQUumzkfqqWTVxb4/qnQgTdWTyn74s4oU+7PMJTDToe8uO1YhbOaLTPAvgL3qfBcRWj2GCKGWCyAPBwRYfuhzOKQFwe+WyMlnHqGlA3hG94KuShVZSNC2RWjhm6CB8LAHB9uwlFhBCKEQMLSz1DGW0DqfzyMcgqQEygETJE5kJCmqiqliAptQPJD8khcb48tao/izZAq2IyCubWzatujV39kQjELsEBS+A1sEUziJiPAZPrJO1XGZbdbfETJ2J1i75xhCaw7mD8eQU7bC/mb1rzqXTJB3+E6WKq70RXfwYFGFdhGhZde1ugBP4UsR7rHzd96qhLZ/7UpoxGg/YjbMMx42IIEX7xValhFatlTzQbr6Dw+LLYgZeUgy4YTEdx6hlXzjCriIAhkyzF4lVgj0sRFa3EP8heGwGC+qYtxQ18ijhEElWhsI/iB+wz/zn0do4b7VPYUOdsv/JRr8D7dYVKFVUJxHaGGmlUoFHfGDnvkasr2zYxNCK1OTwTIqwlAWB0wyUkIGBlg7gydgACmL08+FRNWbACgNGZANMEoAKYAgPs5H3hyyB8YOdDXO948izoIPYqDqKvhUIKuqhs8AubHKLFVlgZRgp1fM8sY8JYwltOZgSdM4zRXBk0n5zBwFctVoYKD642Bkgi9HNy4ESMYuACAjsn6GjSRZbjFWgAlEqnLHSAUU2bsx0K3rCMyIBLARyAQl92HwgqjgD4RVByx1qVzX/YavMELKjUPFgeGbA/27FoADIPSEqLuvKnoFN5VjFSZkqqpzUxg68k527qNi7dr1qhzB3nj7y5rD8zk2IDU3Abiq84Kg6nYtB5Z9I0qWFcmRHmu5C/EARPQmiEveJDbkKeM1DjqrQyLl2vwCWXId+izCP4/QsgHzteQkqWEPgq25AxFyB4aqiCoodE33/FG1V4XT2GTZZMaPBWKVXQSK3SBMwHLMG0PGElrzlXCR36rzVTljq/358lXkqfDEWFU22DAQFSgFfnhALmQrYCC0goFrqvTSPb8gI2SfzZAPm1Hp4ANsnRzhGuBW5avEY5kNj5FPLbEiPjAMRgjmcMs43BuGzGs5qAr8vAot3bNZibtz4G8tR9K3nlIYykYLk8gM/sISVUK4KSFFbmCUhErlyPfcX2sVHIC5fADu8XU2R8Zwnv74DLnCeDiCkMCfbRxIJv9QVJCU8ll2UvYk1iBD5tq3J/plJ1YxVLbLnpAlZEtxhk/Tk3nyPfiu6m2VyxzJDhYvIrTslSwlvjDTw80STHZqlc91FT6MA1nQ18tG+zgyVm5TEVo4qPBDdnyZbYgD5ED/dClxFKsRLPakXYbMkTWxzrxnzQc2KcKII+wIgZIMsTFy4ov8mH78H95KptiSdjC46No+q/tV4WusnKY+j++avzggGeJ74oOkQCLJ56r9kK2wIzbJHmCw5FZskYTBHzJxuK6YitPABTYJL1TyzZ8syLuP4eIRP3TUQ4ySaCR0EaHFLdhzva7NPekVP2GbknCYKbHhL+aJL9WD0VPLdO711iW0Lkj4fgiWMDgyB6/eWn+r3xm932XxzgXS1fvp+4JO/wEp5/nM9+pzS+oUqAdr+OQc8uHvzvXj9+qvrev7DrLlX+Oq/xuL+1X/17wm5rGE1vzNtebUl0cpwv37r+Oo8fu7+xtbzaWuVedXX5t5GHvJx33IwLXqs7qWv9U965y6nt9dy+9kUPLqy77G7W/u7yj9uJ/P+rbkXtXr1R+X77nu2P7MMY5QduU+/WuTobENe/RmnW9eiJDkqd935JqcuPRi3K4poQDgwLvfp1myLVmXXQ1tufynL7ehX5TdkGPf3kue/i39llxdwxj6453lj9Uv7m/li+RCZkM5LtPBGMK2jfmSiTGX3KrqV77Txxhz8nlhlfHU20Tos/Tj786rfcNLluyqruG7/WtPIZ/++OZhRM1r6DvVd1i4xabKl8mkbNbnzh3ihs+RBkEImarrD/HENcvW+3jpmoUVxli4WjHB/QRExBUZQdD6ukA4tlWd7eMV+fiZ5z9j7Mk4VaglV3oVEZExujOOsrm+vZS8KlYU9rpmybXiVsWBdXuONyG0xlx6Ndb+nMueCj/IyDnla5XwFyaal2vNmk8/Dpac2Ef5ZeFcyZMsCs/Lhys+DmPsMj/d5t9Lz4UdxmqciijsiE+UD/RlUDhjvtoEFFvEp1nnFv+CWcW9hq/86vuDsbhO3/8qVgxjfz/Gz+MnPu/bQB8vtinbj7v2JoR2V4OkBARCdUFWYMljH8dYQruPsbV7ri8BPiAD1rJhOW/ZK3FUT2Slqj31rr7173783xxLaI9/puvN4NDlowdRBVWFa5W+2rHSEAxVqKzmWf0a8+aMsdfe9XmSWxUufYqqj9si4tuY16aEdhtjOtdr4jT1eju8YtGrrcQnq9xWFq0ULXs7ybnK9N/nfQyEFuAqzzuU1JcRjm0ptBHabUm2XfeYJXDohG3fsj13+aja6M8Xa5DAKVdn9q3bY7p/I7THpK021rUkcAyEdq2JbeFLjdBuQajtkkcvgXMnbMsU2OSzTELt77uQQCO0u5Byu8deJdAI7XjxN0I7XlbtzPORQCNsi3Xd5HM+vnDIM22E9pC108Y2iQQaoR0vxkZox8uqnXk+EmiErRHa87H2451pI7THq7s28pESaIR2pKDyNRResbGtfcfHj6Sd2SRwOBJohLYR2sOxxjaSeRJohLbZxslLoBHa8SpuFdrxsmpnno8EGqFthPZ8rP14Z9oI7fHqro18pAQaoR0pqFahHS+oduZZSaAR2kZoz8rgj3SyjdAeqeLasMdL4FgIrXcZ2u3Gji12odnH0Sq0+5D66vdkK3ahsYuNfb/tJLXomHe+z+0oZdtFGy54qfW89056r+Dn5+4rU79n0y5gdnupHZxWl8jHf8NrlGxx6HpjdgJbdr9dElrjppPhUS8g957QwjRzswOOv9ntyntQ/d1ro4x5Knkeknzs4mUHLzboBezDF6svG2v7+wW7MdrBif3Ajnkb7cyTFf+yM6Nd0IZH7eJYGwP4ux3W6Mq7SMU4uMWGfa69rTaz2FQ3uya05Gir4f5czcE8vXrT6zhhrIOM7Q4Gr51/qdzF0N/IYJ2d0TaV166+TwbebU7v7MMOhIvebzzvfJ+zOxt/2JHUz6zrsC04yq7Y2DG9S3mpTo6F0Nppw7actsy0/eC8w3Z5DlvBTX00Qju1RLdzPcTlNgmmtmi8z5KtNW09a6tARMnmHXY0Yj82WvD+Y2BrG0L6n2VXApiNGeylbUtA2z1PddiRyO54L8s9umddV/A1PrvNjDmQOi+6R3ZeNWMntTHX6J+zS0JrQwubAAhw3m1qC0lBEHmQcMAIn9kiFBaYn21t2YTv0qctZW0L+cFVJ7rm+buUj61z7aNu++efThkY9qpbywqOV00Zw946bLtpW1PbcArC4oftrd1PosBe17nfmqKd/Gt2/7PVOHvhV7ZPtSXuKkH/0zufekgmwnaDsn32ayLC5/wUobtWZ6u/maQZCbGDmrhGrt+eW8vahGLs9tNjBLFrQmvbYXOxWYftbuEon1NsEMevlPP3mW3TbeFO3mQNg30XubPdq00/VtHBGHkcyjnizq2TxIs/tqK1/fW8+YpXNmVgo863Ta6EyFbJZMa+bL7gnf2znveRLNg+2bbV7GvVhO1Q5DZzHMdCaMcK0V7hgMI+9lMfjdBOLdHtXA/RUVFF8H4oM337is9zXIFZAEeI7H1tv3o2xJY4vR9A4XqvnrPtskAuiD12QkILsOztjpD9/gJR2ePcft/vXUGcsvg7JvmzB/gmxy4JGyJunkjsw7sk5IVd8vL+3D9cteEHczcd/o/4+l1CoPKBONgJzjavAuqujl3JB/Fkv/ZVZ6cCIhIP41+wIiHwHYTODo1X6ezrqzKp4iNIBgL27iQrkgT3fW3Kdp377UoXy+4j2D8+Se1dcjUQEVyFTFkNQGLfnqs2MIGMJJI+J7d7J1GTIDwgLqgKPzK3IWW339ANlF8jwFMduya018yVAgnPd+bq6k91W9dfLquIV08/9JlVBSSLXfFnq2KPSJs7ZTJLt7ZcR/r9wKvP7CrYD0xbmKV7K4GKKHxR0vOzuX0uImzjEjup3j4xUkI/rPBfPG3udzPWNUI7gYdZGntwGq83ByALMmPGT1mC7eMy679RZhrOp6y35N+BLQCyLZwg5ZBxAHaO8dSJd6VphHYCxe/gErVHuFsJDsBUcJq3B7oALGDdsCOOt0075PQqrk/L7PcbMxsGIP1leks3CK9qoKzYeYgVkAHSr8wAiXC6D3LlO8/u7PxHenvcv6FbFn9iBrvaBx0Jt2xki92+vwh0KpT8BRg+NyuSQPDmme0jUfzFNQAkYiOIOv966W+WAwVT39tk971dETb6pFsVCAGvCK1qRu1/jrjZHvKNqffrJpnwHYT2OWkL29jidZ5pb0s+lqdf3rMzJP2eOQjE3XI5G0Ow2Bd7uXBWHMmPLNiS6phgiLha9r3TIGnjQ34QLq0Mzq/EAfnwf/hN9nD40Amt8SGM4gM/f2bOQRVR9Z5cYYWlb7hgdcQcyVIljdz8rvoKD1S/VcXFHJVYtlYYhLwVoZVU+RxWWDVSebTiQ1eqs8/L714/5e1+U7Yv7ZrQVjsBObIL7YLIK3wju/v1CC1yqyoLsxA1CTeCK55b8VolodhBiJn0FuRUW9/CZvFKIWMeJle8YifiFVznk7BcYqnNSqX/shln6jpWCKza4EtW59gwTqOgQy+Xz9WXJ+R59GalU/xg5+y4VjDxMPFK4eegdv7bR4WWAr8pHdrSIDAoQkpISueAw57ZSIag/JQEXVmbzIIilOopHwBxCMsVj0mltgrtpD53lBcTPO6e1Vp7r887+ICWAbb1v5IA6We6a9qgnm1EEUG1VF2ElqMDELapYsjh2awlIVn0e5JsWgYGVEDH94G531W6bpJLQ1dIIsBuAb5zAboghDTwF76hoiP7ZvcO1TgJIbJhXMbMBxAbZNjyMKJBDo4+oQNwqr9IDVK47rEtwrZoPAJen9A695OTzNrzXHKhSg+c35nV+VMitObKJn89A5/VAcTqFqlvdjSs0EqkipxZ5tUewy+Qe+SObSK+Q/Iwi9A+KlfB2CM7VXxQ6V+3Iryu7a3zPbJDBJBJczUXiebfZPWQHyMJ5qLAIjkV2CUDVkqs+vBzFWykUyVW/GJzw6NPaGGEQyIpSZVoIBYqkEVuEZtTIbQlC3jXJ7QIELIkiVK5RtqRfYmohAIBOydCW3ISrxBZ/sgv55F48UrLCvxTXRULyIu98kPJpdYrtqdwIpFQECFvsUSyD/P9H/5L+pFaiYPzrUa6vhgo2aMr52hrwMdemmQZj+PzZ09oKZCAEQgASsDA+TopaNVZFQRLP0BEdUvAtoQBPAixTzBkHECXMmUSAngjtOtA/Wl9B0mUHMlKxzwcw+ZUZDn6z3XLjfdKm0IMZxFadqe6yV4FSfYs0UIOEVLE8x6ZnHkA6b4J2s4FQM6TVesp06enD1FQdfisKsSIL38BYOyaz5S/IGxAh39Uy8G1MyBbfkJgVH5mEdoigEjzJv5yaIS2KrSq5ZJcsqLTUyK0bERCL3AhRvoR4aLAo+I3i9Bqi5GAWYYUhOAt30CKETgJ06xWjFmEVmJUD+jqX3Y/1WK+cOgV2kK5Koio1iKs+g2LgCJgCALSq32Db8MHya3qLRnyX7LWqyiGzSIg8whtv0IrAWWb8Mb1z4nQKmhVdZCvskFVbrI+lwpt2aMKKT/mRworyw4FlSdn7zECDOMVV/jwkNDWapzElZ0jwRIH8QEp5sMKi+KV/lx2CBNUyBFXfxdfVNWtMLwu49XBPay3jwrtPEKrT4uCPKCjnYBBE6aeRoZuSUwVwhJvI7TLzP28/87p9NK+PlsAxkqjiKIqDftDBj2sYBmWr8hoq+dIdVVDPiDoE1qZtsoDoqfVAUCoiDkPiVDV0iaAKEvYfHartG0JmYA5htDyFwTFD0LregIvAmxpyLh/5owJrQqavk5Aj3CxiVNpOWA3CJD2Fku0Kv4ehvPvIkIr4KnCVMCEpyowCNYqhLZaDtxTRRwBVLVEDg+d0JqvSrZ4ohom8eSbiwgt+QjiqqlWX9jSVITWWJBnWIJAnyOhRZgk5mSsKICsnROhZU9WmeFUFTXGxCzEVRKrsOGZD8mVVQSJJTu3EiCeSKwUT8S1IaFV+BGvfC7OiVn8WpIHT8QVcVDckjxXvHKOeDWGfI+ZyyTn7JPQqsAqjwNSypBZeMhDliKTUKGyTENZMgqg0wjtJGo/6YuoZgoSHJu9IJ6cUavKogMpZZMAVTaqp8uyPPJpKR857j8t7qEtPbKWC/2rwuDNCJb5kVkVV4BiGUmFUFXWkpqsF0AgrZZ2VChUkgGLyrAlOABvabPGYk5WIGTE/IVvmBPC6hyE1hIRH6nlUnMFcCqw2hLKrzyUgkA7jM/S8zLZLJLbIVZoJb2qCYgWwAfKqmDmi+DSx66ObciH7bAHBQCBCG4i7x46GhJab/pgL0gC+5P06IGriqLqzSaEtnr52NE3HwGh5dOCOxkgtJIcy6zzCK2KGfn4nj5Zc0RstbRsWqFFXvg8GxEDVb0t6/JPhG4VcrPMnnfdQ1vjWdRyoEKrSuiNCDAMqX9XVmi1grDXVd8ysUwOh/Z32K6lTNFDfKF/SSpMXtQ7LF6p7osnkqtqPRBbkFLk2PVcQzyRzCp2wA0taeKbZA4+ijnildWteiuQKjnb1HIjBuo3F6/8rt/cio/K8CbPX0yui30SWtkC5XFiZAGZsDTroS5VLURABQLYyGD0fcg6BGzgqQrlGgKUz4GNagEw4LyqaVP2d7SHwiY3v61c0LJJ9Zi6AXKqf8gT8l5FhOj0s8o6Xw+qoKKtxQGIBX8kAXHQ+jI8XE/Fix/5vocaAAi79LsVBlUX7QbsXD8twBbAgIyM2IoEYEc665Vf7Jn9OwRc4DXPX/gNcGGfes/1lCO+7m3e9aCBAC4oGyO/Akp3TuK8yftot0HYFhmG91eqEAqCjurn1P7hAdJ6GKX08bZMGOiSbPQ6Igul560YYe+i25IPYuX5AvYmeElUBBx2ysYcyCrSpVrPvryWyu+eqlcsgKXkIbAJjALp8LhaPkzoe/wGMa5nHZxrfuwbwStCO8tXti3nsdcXX8zXQ3III0KhjUdyiCB40NjDLnBDHNKSYRUENnioUpwxP0kz+auAqZYPXwNnhUjVmqz14pK/HtmSf41XbyISQX7+hQfwREx0r6nedLAvQkvO9bCgxAvhknjDN7jm0BJGLlZj2agilgTcQSeLekrH6v1QzyMf8apwC5GVcGmZYm+SUbGjjjqf3eFBb00MEK/8jqBqnRvKzKq3ooteequM5M3nrVSQseuxO7GIXcMFXEpM8oBpvRlHzFIg0D8Ocw7q2CehrR5aYHIMRyO0x6Clwx2jDFcfuKx3zGFpEyFVoRBUVWwRF4Fu08NDAMi16xb5Wfea2yJs647n0L7X5HNoGjnP8eyL0J6ntI9/1uKVpMyDx/UWhoOf1T4IrXvqF5FFqMjK3raxEcLUwm+EdmqJnsf1VEVlzio12hO8VmXsYWVC1dE7LGXGsmb9dl6vtO6hAqJCIhP3INGm7yFshG2xJpp81rXU9r0pJdAI7ZTSPN1r1SqeiqzWzw8d02vT9kFomYIlVUHaoX/jGDKARmhP14m3OTM+ZlnTYRl81Xcq8pX6mcJfjMeyq3acKfyuEbZGaLfpP+3a00igEdpp5HjqV9k0Xu1VPvsitHud9Jo3b4R2TcG1r520BBqhbYT2pA38RCbXCO2JKLJNY74EGqEdbx2N0I6XVTvzfCTQCG0jtOdj7cc700Zoj1d3beQjJdAI7UhB5VPknlT1epd2NAk0CVwggUZoG6FtvnD4EmiE9vB11Ea4oQTGEFoPpmzynsoNh3gwX9cH6dUWU/QdHsyk2kCaBDaUgJdt918rs+HlTu7rTT4np9KjnFCLX0eptjbolIBXDHoV68JnUMYQ2ibRCyTQWg6aJTQJfKIEWoW2VWibXxy+BFqF9vB11Ea4oQQaoR0vwEZox8uqnXk+EmiEthHa87H2451pI7THq7s28pESaIR2pKBahXa8oNqZZyWBRmgboT0rgz/SyTZCe6SKa8MeL4FGaMfLqlVox8uqnXk+EmiEthHa87H2451pI7THq7s28pES2AWhtV+zPcVrIwVDsz+13Y423aXItTS7XyT3Ifey+G0dqxJaeyt/abcft3/tkf5X2dBsrB60sy86MuBBs1UOOrOLh+v+5YoPqXlBvzHZmc1L/h12Brlk7iXt879dZTBHcq55f2HuQ/8PaXuayy+ce7ezwz/JnetWmdIseY75vn27bW1rU5G/yy/07YVu+Miq+h1z76nP2TWhZf8Xi4jPSxu2z7gHNeEA2/6PA3+ber6rXm9K+diy2Nwdf582+2+rDmjL5/MpPzA7eefaAAAgAElEQVTvWB6gFZtg8qctkQ1/hOPw0sN+sOQjve/AA7EOlhS+Di/JTj83Iv4sIj62ZV30L79tQsvvzJ1c+sc/Z5wbE5vJjx7sYrhL2WyiBrht3rV5jrgihv7phvZf8uRHYkEd8A+H4FswYOxGPfOut8ncD+67uyC0hP+Ibt/4G0TEr6UEvqwzgMfl3vSbALIdj74vIi7XEcQHJzlgXAzgryeW9qqE9rM60Pqebo5fn8TE+IDhNbvxfX9ugfqENQgkMnTVJLVvWDEpADZ37eT1M+lwtkH93oigj6/tdqT60fzbpqIT0D4nifMYINv0fsu+b563ioibJ7H99ohAhMz7kREBdG3z9/4VAMI9h/JcNo76O7s1FoHvN3MnsBtGxPUS0I33xyPi1Svqd9b9K0jwhz4wjh3rsvOmJGzL7uXvgPnauRUwP/iOTpa/FRHI3kNSv8+aAFvGjGXMOVPK55tyvuz2mR2B/4kFxGnM2KY+B9bTgbjyQ5mwTX2PbVxP/PAUtcTWHvZI1TszabpoJv0SqPtGxGtzK+uviYiXdXb3/B5mXDYifjGv9StzsISdXrfD8F9KQrKN+cy65rYJLUJnG3vxhc17vSWypfhy/17iPm++/PqbO5ncJ228nyjsSkbr3IfNPzAivjGxXLz7zK6A99iI+O0NSK0kizzF+A/3bEnS/rAuVrylK8a8ZER8kHwpnFy6K6I8L234dSvGuXXkMu87xuOtOFPzs3+/3y4IrftcMQ0dsSXcH8l/H5WVynUFxglu0YEMcEGQVbvc4xci4r3rXnTO91YltHUZ40MaAdxzOqBH4K8cEX+Tjj/xMFe63KU6UvbE1A2gVTVAujc9rhIRXxURP3VgAVcycb9MIoACHVwmAegdm056g+8DwB/sCPZPRsSfZ1D9wERVCokV0vfyrHxsMMyZX52SsK0yNuRB8KO/u2SlTBWe7b1yj4A9nMPU8pH43KS7yQ9vKUFZRQfDcyWyd89ktrB+k+vt6rtIghUTGKAAofgiRiG3sFrwRVrEK8nTdTLWvCfxvMZ554xFf5QJ8iEk8zW2bRPaus9zM/7+cvpgrQguW41VqBHH4fODBpXvXdnBuveRED0gIh6TMeVJWTDyO74z5cFO3et9GS+WyVVi+ZrkWYo2imiv3yM+irvGg+yPrS6Plt+uCO3lkzSpAKpqySxelFUoBE/QJehbJul7aAbhRyfpowgg8g15jkqWTPAOuUz8bd1S3LOz6iULsXQu4/66rJK+sVsGY2TAaN2K8LqE1hhkcbItyvy9iLhCLlfJYhG/n8slC8RDRtY/fPeluZwKLFRlgK5WAe9lc9wjKyPaO1QbgTEgQYq+NdsTnIPAIdVAA4lSTbhEL6PmgG/OiiGyAMTJC9lSjVD5unWCjeupcv5sGuh3poM9rZvvM7pq520i4q1dYvEtW3Dq0QY+OPFq2fpCzlYLEEjVGNXkd+W/b8p/yYJNDZe+yF+FxbzpBfiSp2orcgXIydbxqrRrFXnLUOzV+SrkP5BZtiD68LwGcCJjgbL06zME5ilZMTKmX+/+/uT83fnsyvk/nUkE3ag2qyjRI/15lzRbmLryMTVhG6vbL085SxjZPRkgVKq2ALPkQec/n7Zc7R1j7zHFeVPLB9nyw89U8fklEvn7qe+Ppv/CP/5raRK5JA/L4PyUnbyiZ//wVvKp6su/4ZKVr7cnTsNbGMWv2bn7sSmVHr5E/jadcW0rAnyEnU8dzKfQx6xrIFNiIay7fo/QkpeiCRlabbtpykDVkf/3WyokUzAejrBJMp3VvvUV3ercHbOQwDfJEuYqLLx7g/i0TDb7ILRitOKShMDS/NM7O71ttnyxL6RGvLY8/9Vpvz53HrtiT85REGJPV4+IG+eK5+RkaJkAF/y9T2i1UsJdcRvngNPmJ9G+W7a1sB08iL18MOOIOPTdHY5JgsxfnL5WxnJYDtv4qJVUMYH/vTC5AG7iOndK2dRQ8SKcQZHECrEKuLinAPChjDl8lHytrPxqyr2fiOEqVWG/fWIGMo3Lua8VTrqFMcYvvtAxDJF0i0XuSQ4wW7wyHjHTKsWkbUm7JLTAUhVQnxJgqAqq5VcC8DnFEQKwRjKU1YENAoF8cUqGTSAECND/sSNWRWgZkUotcNXfhFQhfUijg8J2TWgZpconR7xdRx4tdyPwxkeZCAqwREDNm9Eh5HUwYGBp7AyLUT++I+tIuvPN7Z5psK5jiUywkgTQLxIlUdD/xaDI0j04nkTDtSybcRDESpACyO7pc2TKD/LnewxZsESOLR8AHcmJCiBQFhBvlPoTAOf1km2AH2t/FbnhwHrYBHskSNBhaxyQfZGxg1wkWYJ6HeRlbhIyzo1YSAjIxXI+4gQYAAKQYIeSMkvkHF/lhn1zbueRNwIsQPo/gCJXcqdv+tVCA/iAI9Dzr0Shlo1UjaqdQiIDbARTOmID2hf4gbnoTZv6mJqwjR0fWxYUrCiQk8ApGbxSyocMAKbkgFws271gxBLd2PuPPW9q+bA5WAIj2JBEpfRNDgiA1gR2ab7sFVayed+xNAoDEQeyQdjYjyCLuErk/E3vnmV3n/F9mCAwwRd4YMXJfQU1OGNJnt36rnsb27EQ2r4u+4S2P36kHT58RmK4/sU6zP9miedimKoYQkK+feJlGZlO4D7fhMVkizS4BkxfNz4ts8ddEVrxCTmFh+aptYotWQ0Un8RnJJ784BlyRVbsTqyHb87xjAnyg9zhATBUsjaU6bJ57+LvCK1YIlGE/WILPUtexEek0vzwEzxIvP6ijAOSG5gljpu3g8/hA2KIePoHGZckrTBOXFEYe1veS9yo8/CJIolk7r5+fFfyAAfYp/hlXGIPPFG1xa3EcvzBNdirc4xHHBN34KyEVdEASTZGfI5/GIffrZ4Zh9Uk9iBu0i3OgT8Yz0lUaCmZYCi+lK9yIOAgeciFiphgrdqFzDFmfUuIKyKxiNByAudQeAE+BSINrrnJA0/rVmgRWlUNzkiZKhjG6DOGjGxwasReUGF0iFGfRFliQIoFaBU9BIpzMD6OoPJWxIlxITMyICQN0ZQ5kZ8gxNA4XBFaTlS9T8ibH0tn5Efuw0xYxdn1jUNCASgrgfix/K6lI/o7REKrgi2L5HgILqInqNOLqqkEQFAxJzoCqnUI2nSIpHNo4GqO5Cn40Z0g70E/MnJt2atKjP8Lhn15/0YGsT6hRUj7+gUKAAJZ6S8vAUR2I5ACM0Gj9PE7PYLM7ur+p0hozRVJkyyyPyRXtYJOyJyu+Qc/Qf630Ue8KGhug9AitRIuwR4ukYEgBQ+syvBftst/BSa2TR582qpCPXNAFmwVLgo8Eq7yb2TWSoLrwlXXQrhcR7UJfsAGVUU9vQKUFQkkrZbsT4nQkhlyZm5iFyJaybqkEXbwdf5GBoI7+Q0JKlxUfeSrcBmmwGXxSTK7rWNXhLbfciD2sc2+z/kMNnp2wJicL3Y5Tx+uZB9G8ltyVHVUBBArEbhtymhd2bMNWKMSbRXIXJBC/sEOisBJNMV7xB7B43N8lq/dK4tvPmdPEiOxR5FIzLLKJwkS05Fkn9WzIciqeyG58KAIrb+7v37eIrTIqLglTrFhZFYCAhtcA99SPKxrKFqJH1YI+TO7pT92bXzGhRwrUGr1Yt+ILuJudVaLRNk3fzG+6i+evMq+ywqt5QdkAImgPMBIAQgt8oV0UiwByPBVHiwxCFYUw2AE9bGEloCV6QEQwVKiTHDVtwqUkW9KaAUAlUBGpKpEFgIB41BBReTdg5ELDHUwcNmadgvZHGcAgoi65UYgQH6CDOCQ4Zo7gB0SWtflIAJ7n9AKgIgcMkUHviu4GUsBsrELbr6nOoY0GO8xElpggVxySHIEOACCbFSiBCUyAFCqTv3D+XRhVcHcAQJ5IhC+a1lJ0zsCIHGxKjEktIgoAsbGLTf2CS3dIbF0TL9FxlQAEAvkBDDq7UNEXMdYzpXQaiPiA4BV5VCAFPhUxAVGGIOI6OMXLHe9Te+uCW2ReYQAeeW/swgtLIEVKmUSJitkPhPY+LclScmaQgO5sjFB6itzCRWOwW4JlYCoenuqhFY8QsTM0coVWyMLrT+CsuRSZRduIAKSAhiPBPDZ/uHcWgoWi3xPfEKCFBvWjU/LyNg+CG2fsIgfSBScZF9WTJCjRYRW1Q/Z9a8KIo6wLfksk9+iv/dbDlRT68BbENYitFVsgunsQgEE8fXwr6o12+B3CCVbkrQqAvJhNocIDgmtPm9Yp5rKlvrL+GMIraTB6q1YhS+x3UqEzWMZobWiKUGjT3jDV4p8u67qLvvGLcgCBzt6QqvSitCqNFIkBQNDpXdEDiEDqIzX5CmVogR7igKmDJriGAGj5qAcxhI+wAUG/QqtTMl9ZdOCmWUdFdB1l8DXJbSW4JTqKdRxjayekYUxmheybomZc6uWaqmoQ7Dg0Cqi+lFUYFQUi9AyOMsxHMP8ETN/X5fQytAQMzKnHySZ7GRekgPJiMqCg4EeE6GV2Qr0+mQdnA8AkJXeNwGZzQn0yHtls6ULMgBell2QJACgnxmh1UIiSUOS6YCdqahqGdiE0H5xErNqf3A/OlCNBBgAQoA8N0KL9ANs4O8QMFUI+CmyhczSjwRQAkEnErRdP6gzNaHVQqBFwAqCgDes0EqI+K9KkGRZYFTdkviopgo6VneQLZUT8hN0yNK12Sp5KXbwE8k0e1dYQIxhrwQYZluJUfUXFJ0H0xQh2KY2B3rY1hL6JgRk0XeHLQdkBR/YDtmqwgriAr9ADsN9h13BDoSWj5KR4svwae4itHAHsROTrB7AWH3K7HQbx74ILRLHZhRmVPLYDbmJUeLHIkJLDnri2RIyLIZOXtWbQNhjCW2tFltZ0TogKRLT9diK41ZTzZNfWrGF+Qit1VnJuGdW+Ly4jE/hUfp12Rr/5bNWWEtGYwitMfk+EopriI/svK6xjNDiN3gBzIG1ZKHIQ7dl0/6VCEtIzPmoCa2MtnoBCUomghggp6pkwFPVxO+qt9oPKFQViuIoSeUMYVPJRDQQXkbAGQgRuABRWQYlAwiBHhmwZAF09ShaFlv3WIfQAj73V+53f1VPhqq6hrSqhiDdDBcZZdwqLP2DgbiOCqwlP5VdwQgwOl9CgESp6DmAh2UGlZNa4masKjGqq8CW46j+IW4IVx1IkSqNpQWOYikbUKtSWhKz5KHvCUgDKNm2uahcuC+SgaALgNWfSt/rJhHr6mrW99iOgItk6u+r3ljOJkip9AnK9Axs6QTB7QdkqwfIpARKRYVdqdaSJ1ukG29ScLgm53VN9sk2BXu/IxbkzraBiWuQk+9YrkE+6BdYyHyRZ2QZQLEBVQDknB58Rjd0a2xIrt+RXOeZq0RRAomsTN12MDVhG6NzBA2hk5CQeS3vka2+MfPnDyqMMIB+2O6wWjbmXpueM6V84AC99lfWVGz6+oYJSBVdI7X8l20LTIoE7MwqjNUhuMHm9M8bp0BLXuXffECwYu+w2/1hA7s0DiTJNbwb17Iw+3Zv45FQSPKO6dDqA6fJ1xzEHfNgbwgte+KX/BrRJRPJrJgjhvXlA0cRMLLqk1SEBObDGfjsPLGM/OhpW8e2Ca3kkY+RVd8+2ZXEil3gAexQ24BzYJH4AQ+RVrhHHsgeuYtZcEvBRlHoEO3JCpx5wx3FH8UeuIsQiqEKbjU/MV98MDdxiFz6r4o0f3O38vb/t3enMdNtVZ3A66udmGjaxKDpdkYEZQiIirYIiDKIcEHwKjI4MQioqIAogy0qIHa32NqoJEQRURmUScDZtrmCgtKKQ9sJsQktYNLpYDDRRD9YP+5asD3UsKvq1Kk6Veskb573eeoMe6/hv/5r7V1nIYjiFc7Al/kY+/PTtQp7vh/EN8kuuYEEtj3SfvEKHILs8SvJBd3gBsbIn/EGtt1+UQv59IV8z4IN/q+CKy6KS7bVIN25QmY+xiuGuqd7I+T4HTnwFTo3LgnzLL8UdiwnnfK++xDaKcaXy80qqw4OhSgD5Dqmk4BKgi8BsBMHEstxgfglH2MStkuUU8nnErU6vzkdm9AeSyIKDlZvJWHnWJ091rzrvntIYKo9tHsM7ewuOVdCa/kRic3qk2qVpVdfAqtjOgmopMtCZaYO+2NlvAjNJR9F2DZrt+RzydY/n7nNjdBaGbAKZQ+87YTnWJ2dj/avZKRFaPsVfa6EFoGy3JO6tOwx9T7Bfile7pnk7xv29hk6bMGw1eLSqwpF2IrQXq5XX87M5kZofW/Elz0TRy9HEzWTo0mgCG2/aM+V0PbPoM4sCYwvgSK0RWjHt6q649gSmBuhHXv+db8rkEAR2n4lF6Htl1WdeT0SKEJbhPZ6rH2+My1CO1/d1cg7JVCEtlNQ8WUf36z2reI6SgIlgZslUIS2CG35wvlLoAjt+euoRnigBIrQ9guwKrT9sqozr0cCRWiL0F6Ptc93pkVo56u7GnmnBIrQdgqqKrT9gqozr0oCRWiL0F6Vwc90skVoZ6q4Gna/BIrQ9svqVBVaL/L24n0vRNZdxouV29/PoWlBvxTP70xvibhNfJvWi751RPKS6uwZfq7y9y1gL7b2fkYNLk517EJotfj1Unld8XSl0R5U5zuHN3VopuJF6vq8e3G9l/97eb2Xqp/qgJFawxqXF997qfkuxzb5uP8toxugl5L3dNbyJg1ybOW3y5j2OZe96SSmIYkXv9exWgKH2ou7HkO/RWjP02LZC5zTEbXX/3eZiUZI+ILmHp6lCZJ4MXz7jgYrYp/mB+s+1zhJvMnYuMs4Jjm3CG2/mE9BaHWS0cVHyzvtFYGS9/Pl79rhadm66WCo2s5paVeB6CMlpXuKjkBa9el6op3nH8d7fMeQf7+F7XamjnO6ziCEiM2pjm2ELcelNa3uMDoF6UCng6BOQJqAsFGdawRyf2fjkjfvVtaWVTvoYQvRqeYLIwUFL3fXobCHcLZj2yYfHc0030DiderS+W/bIQnTxCPlt+38Qz/3PDrTRUsfeu8GveRDMqUrknl6bVTP4fyPC+zQwW5fe/Gs1K93r+oAOMYxBqHV5MDhHdv7HprNsFvfRRn7lYZ8gr/S29j33ne+267TMZLfI5o6gY3ZzVASrvOk2C8ZRVa9G103yeEhnuj0pzPl8HP26H33urTq/nWuLYj/VYu6bYK/9s9PQWhVhrRK1D5OoNPaU6vF/N3ftlWMgLN2mMY/dtvTS7AJgecx4cTaW7aEZQz5X4KMNs1hG2HLa7VK1k0tQbF9UbrKrb9LKrSNTH1IMFQutBUdtUXihErZJh8kXmXkY5aV2pd2EtoJh/+hR0nuYJGge+mE9guW7btvH/ao1W/PoYW1c19+pmRqDEIr9mhXagVrX8Kobbs2qlqH73uPdfrQBvt3Dxxfj67HPEcy/7B4564WsmMSWvFLq1mNl6zk9vCFdXPj/9rgviASmrF1N4pMq0LbL8ZjElrBXqcpBvMJQT4Bxwvj75b5BHs9kp3ndwRAsBdkNFIANoBGhfFpQX4FU8ukj4qlAr2lnxpL7LI1lSEEwiELu91yaVXVFwn+lfj/Fy0ru09Y9tnWC1qWRw7/aY9KVb+kj38mu5cZm6skgbN6g8Xbo4qoIki2stmU9zr5qzoiwT8UVQddbQR81Zrvjf7ZT1r27f7/y6Wax8fytZ+qfSlP41CpozdLyZIU1TDtiy3D5/USE9l2jv+nol+4Cq0qs8+Ml/5k5qp+xwaebYTNy9F1/Pn6JRh+fFRk/Z8tvmpZgdWy2f/1Ale5AegILgL7ypAD+/3amB+y+8DoGc9X2KW+5u7xxbE94XlLe35WnA/U6SLlIYCoNriPPuyeT3f6quf15J1beYz/0aFj/qh63PoDG+EP65qZbJMPXVrKo/9fjGq15+V8yY5f8nc++rqoXsOCVy/t5TdCruRnbEgVWZCl+5Gh/uvszzVZzScHmEEOL1o+/yejj7tVHHb4zYP7sWlyJWt968lXr3mNXJDcnwj/4SfG5ZnG4L78IHvSq3gO5zfsP38IApAnWfJn1SbLrfDVnCyV8k9Lu+mft4rxSSiQLbgHhyUZtsZ8R1SlHhr2RB+SEDbJjlTBbIn5zKjkm7vCAfv5uZj/3ZYT+r4gWz+/xITXxj8+bkWCDZFTVudtK3tmyNG92Zv782X4jri9YkcMPpTQ3jXGyT+N9xaxjH2HwBljtmJkvE9e2paKH5vwOVlYaSTzHw/sMx62R95iDLyFg2zUPMUppBf+uR9b4qOW5/2En/wGOeZ/nm1cxkeP4tS2Ys8hdjbWtXzaqgfcF4vYA/uTGNmW5f/kgZjydTGDPbBt82dj5MYn4ZjryYTtsnWrs28JH2e7ZKnCCvvIWIt22MVv2Tyfdm92b1UG/rFN2Of+9KZCf+y4spd8i9D2i+2YhBYAA32AC3yBgABMPwiTMr+Klr2e+btrODLiaw8eAsCwBT73QrIQoL8IEER8ETdALABxAIb9nhCBZTJgg2w5nP+ScCp7NYGo8QkUgHzOrQjJAWnh9PYEkRfiYZ+gbBnAWOpr5b1N/vQmUALpHw3Ht7wm8P/aUk8CAoAGHuSJTFhGJ08VdxUeicqbAljo3ueCXl5ve4n7AUGBmk6MN+0EmAMi439fgN2uS+T9HnHzmdsIm0Bjvgi3JS3jM27yl1CZGwJrngISe1VRQHJUzF1rPraB+Ano2S57feySHL03fkpQ6OzGZdLwS7FVYZU8LEuyX8/2XOTKQfeu9wzkx7gctkoIJsaFzBm/INvqD/ALuKuObfIZEtr7DOaLbLI9570x5CHgGKOlSjbMdsxVhRcRRiYltzAEwUAsjNtPcsxDZztzEsycTy6C35cP7ifoIVhIieCGnMIZ2CMhECiRFiRZQHRPRCUDK+xEQiRgiFnq8yHxN0FyrADJD9kcnUnWBXAygZewDhmge9WwXPHiswiaccNHNiLgk5ckwXglu8brOsmBPd/IqUoueTuff7IbgV+iBU/9na37P72xFfvCPVPyYLzuAYMkDfQsgWFfrlF44C9sng6NGQGk/97qMX0fSmiRUfZGl5akES0+ioDaLmRctg+REdtAetiRVuz8lA2Tjfjln/uJMTdFosRu+CAb48N09Tdhd78ZxMs9JUQwgX6NQ6JAPzCRXvnLIRXkXfHv0PONm33aUpjFJvGAbT0u4gHZ8g8+KNG8f8gfxvubBBaOwSD2w57YB+zPCq3VMXakmGDLIj9Q8IAPMIeu+LnEDQ7a6iUWsTU+IE7RTRHaQzV+Jtcfk9AiToK4aqrAYInV/1W01hFa5EAAEuQcwJExC25AOfd+CfQMHngAIE7CeexRFGASFIHyEwOckC4OAYRU0fJ6RLAdz5moZudhSAAEOoFHNYXs/26xWLw+QNvctxHaVfIXqAS874+gBXyQWoDsANAqZIKAalcu4xgLUmA5BwHKY9X1CIfj30TAk9SoVgiaxqxy0xLCUxNatmOs5kvuAqEKODsVrBGyTYTWvGwLkQw4gLEv6qmsCfiqZc5h/77MwHaRT8RBgCUPz0uCjIyq8qjiqOCosA2vl+ipdjsQjvsGsZXgqYCYk/m41nwkFesSvF0JLdLSzhd5FPQ8E4lCspBINkR+ghLiikyp/JkbcsQuzAtukV1u6UDM2kMgUx1SybW/mT6esuZ+7HEdoVWpfU0QCoHTHkmE1liQEz7ld89r54d0kveYh6qS+Vp+5nv0p0oqqULKjI9MECfkiL/ATvpFwNgK+yJrCT7in/bHxlRJ2Qe8UEhggwiZz1TFEQSJEFLiYOu+lMNPETl2ySbpAv4m3ueXbSQG9Cv5kDQYv5UG44E7CIbEdkpCi2zCNsmP/Z5WBMzXioH/I/npf63/IGtsl32p8ok5cNfefwkEm5DIsxP39Q8Wkgk9ImdsEqFjR0is5Ejxhl74X273yPvNjdBKAmAg+X5syIL/SP6s0pk7fIP9Ei+2Ab/4EcLKrm8IG2Vn/uEPmYxnwonwK2YplLgHcportDA6P88KLFLLj8RIZBueFKEdE6lOeK9jE1oAx9FlWUALwWLImwjtAyLT5/gqds5HSoG06x0toWWYloI4CkAAJkDcoSosWFl2MAYkC0DJoC+N0EogzE/W2RJahAA4qI70ENqh/N8cJKsltAiGZyE/Ku0SkCGhlfkiJZ7dEg4EwvUIBjLjestIDgEGaUGCz5nQClTssiW0ABaZUJESsDcRWkRBoAekyACiKrC1hNY5gF9FQTWDflXZkuC3hFaAtZRH3pJHehlej3i/IeQ8rKAem9Dy33a+tlcIdAKORFQgIwOVE4HHCoO5CIDIBrLPX5F9Ve9thNZSMTsiU7Yl2K27HyJxKKG1ZGp+Kmm2xpgfojNWhZbaVhFaNsGG+EsSWsRQwObHyKHP4SFCmYRWAQCZyPHyQaSDbZG3hLEltFYV3FdF2EqBwoKtLHxZMoY02CrDBxQZ3BtBlhDkl63cTwXXig+Cd+6EVhImcVDt43/8h2+TJSKLeFlBIK9dCa37IVPIK9+17K66eKmEFmHlv5JyMVlCJWbfK2zB1phVhFbVFsbyrTtHQpAVWraG5LK3XGHANSR3iC/fE09c73NxXwx0L8kJnxXTitCekICO/ehjElqVOgZj+RQwWKaStWbg5cDA0LK1YON3FSEADDRVCxivjF4GJuuyl4tz2JuE4CKvKg+MXabHWSxZIAIOhIkxM3w/OUiCuK0LjB1IAxcO4pljBqGx9bXpfilvlS9zFKRko8iXbF/WD5D9LeW9Tv4qMsgE+ScpQExVCXw73jK6IOZzMkNMLME5hzzdX/BSQfI8wdY5QEywEwDa67NSlFtOBAlVOqRY9cLvgrCEBvk49mvdtlUgLWOxmSQtSBOZqY6Ssf8jYciXCp9Ko4oZgsEOVabYu+sRAQTOkjLCmgDOHu0dFkCd7x7+hpyRB/tNeSBRqhrsniw9GzlEgvJ6QZMvOgDOimkAACAASURBVOjBkiafRIY81/3ozwoK/RkvOazyh23yyfsjyipMiJcgZu7may62V7g3fxVcEAckh0364hz/ZrcClnPZBiIhYKlQkxn7cC6i3n7BzvORLSQNSbCPU7Vn1f3YpqqjyqclTsRLEmfZFzHmP0gv2fAJ9mdM8AhxRPbotdWnhFkVekwsoUuFAOOD21ayBG7JIh2aJ/9EktifMZApHJA8Wp5FQu1PZC/8KfVhvnRF5+YHU1XCkFj+Su4q3rDX5+wO3iAQKut0IIkiM6s18J6eEdes8vtcYgMv6E/yx76N23PYv6XmVd9WX4d7h245QPJhkaTRWK0CqsqyWfLlF2xDImBOSC0ZScDEElgrNvlnawyyzn/JSwWWfVpxELfYP1nwQ3jhH7xgU3QLL92X3PkfW0TCnCduKkyQ7Zg2daz4ZAWIfOhXscNbdxz+T9627vAP8cPcfC5+2NYmwWev/tkqAO/IjD051+og+Ug4kFMklez5r1UltgQLkVm4oVIsHlpBIGOrFfDRqorVAX/jL/Tb+/aPY8lt5X1rD22/uI9JaI1CwAScDFwQBlYMSHCy98ryFmDL3wVfQYTzM0BgIggDWwEXWANE93pEAAFwBIYM3WdIgqWdPDI7NAbGLBDacyPIqqSp7HIWziYgHHs5u187u5+Z8iYny9TkK/tFbgQ4wUdlbxf5q6wjpvRFH1ltV1mQbAADwEOeQAXopzwBkACgoi5ISlQQPtUb1wvGCEF+C9Y3sQUS2xiAmEqXSggdIyT0Ktgc+52BPYQN4bKlxZFJlGVZQQ4wA2m/IyCCG0IAZM1XkMvrzZMdppx8jmDQGzJCnmTMd8h5lTwEYUkd2XkGokP3SGteTxd5uAfCx9eQIYRyqD97A4H8Kn/YJp+8P3uU/LCddr7G5nm2ShiD+auamB/55Rc0VW35taAvENqHySYQKrZD/plwDYORZyMKxorsGtO6++UXvZB5uCKGSAyQa0FR0m3rjfP4kmeyffq1kiCxzi0A9GnJemziYS7It1dpWYExf3uvfYlG0tj6pwRI8oMwIaCwlA+SLx+Cka7j1zledoqEmB950b9CgL+Rv4RUgpD3Y0teeYVkJQklc8REQgGjVeTyyOf7jM1lQoX8qdR5PmK8y5dzDiW0xmZ+iD5d07+VFSTSnGCU+AC3+A+fRDThJxtkJ5ICJMrWFnqx+sROkGR/ZweJkXDL+Yiee7Mxn9mvizzDT9fDT8kp/7O6aHz5+1ziExmZI3tlq2KHxNL8cAIYj4j6KR6zJUmFfdXmzy7ZD5ySePAxXEDS4XMJJd/mm/AXPrBb57uHeCMh8Dz+KpFjZ3AZXronPbmX311/7Liye0QPI9vrwiu86NiE9gpFWlO+AAlsI2wXMMWDplDyOUh8e13cbjkQ7McmzHsN6sQXjUFoTzyFenxJYLMEqkLbbyFFaPtlVWdejwSKsG3WdclnWl8Q0yyRqhyqZPq/Nw5cO6ktQjutHdbTTiCBIrT9Qi9C2y+rOvN6JFCErQjt9Vj7fGdahHa+uquRd0qgCG2noOLLBb4Vb49UHSWBksDNEihCW4S2fOH8JVCE9vx1VCM8UAJFaPsFWBXaflnVmdcjgSK0RWivx9rnO9MitPPVXY28UwJFaDsFVRXafkHVmVclgSK0RWivyuBnOtkitDNVXA27XwJFaPtlVRXaflnVmdcjgSK0RWivx9rnO9MitPPVXY28UwJFaDsFVRXafkHVmVclgSK0RWivyuBnOtkitDNVXA27XwJFaPtltW+FVpMCLzXX1UTXDy9MXnd4MbmOYc7xEm4vAx+7z3n/jG8+00uwvdRdIwedcK79mIs8vNxd1yYv6fbS7N6DvWps4HrNMzSd2HScE6HVkcmLyL0MX9ecbYfzddLxovBjfdnzmPIxfk1UvIC+Z76tPHQA0tnLO1u92N+L6R307oXrbEADgmxQ4DlewO73bO4Br3TV0oTlFIcmMvBSc5Q8vNTfK7t029KhzhjzyPl4nZdmCuaYMdBL63UX8+L5SzwOJbTsQkcqzR1OHZPmpB94qtmD5gmvanxn1RzYsw5ybFeDHHxBw486OiVQhLZTUAdWaLWf1dVH28d170NkxNr56Zyka4guYbqi6Mo19aEjiG4s2kFyKGCma07bMnPqMY31PJ2edEPRhWufQzA8d3kgKVpjam/oPZy7zBXRQYK1j2SPmxIw8jsmYdtFP7p+afWqg5pOW+9aczHZ6PCks45uOkjhBzqI+y5jac89lnzghU5pCJuEcxdCrouVTmC6jukupvuQ9ph/GZ2D/M1nfJ/+dRySYOuEp82y5Fb3INchOLuS6X1lObwOpuqIBiuRWN2MdNbSUYoNIxG6dWkZq1uSVqu6XCENZJDn6jaXXZXc6xJwbiirQwktrsBXxLBtmDCWfi/lPr3xn30ivbr/6YwmOWfTUx7Gql05fJTkzeooQtuvrn0rtGQs+ABfxinwqtaqfGkPqCKALN4p+p6rGKkkILMyYS3+PjraziFTqqSCi9aDWlgCGX93H72d3V9bwX9Y9mX+99ETWz9ybQAROYTFsxmr6wUm57lOBcbftRDUclXgQgyMX9ByDwbvHjJPlT8tH83DffzTNtPz25a6/VLuOxOh1DqSbI3LWLQFNT4tfclEW0bAm+RTqz5zFMS0ERSwfa7i6jrz9jtZIDiuB97ub77mSX7maL4pj6H8htXQobzIhT4RKz/pwLPbRGeob8/SlpgetB7UapJOXSMway3pn7Frl8kWfKaFof7dPjMnBI4dshM//XOuykCrf20okQHEYFvw6iFs9GS87N7hmWzNeMnB/43NmMmazsieLOnGtfTrPsgGmZlnAi5b4BPGirz8ULQw9Xe24O/OdU/tOb8tbEBLVmOiV+SNH2k76qf78bVV/rpLkOmRT5/Vf+RZZKJd7tPD39k4WZKhQxtXOpagsqH3h4zJk93Sg+rm06Jd6a8GOWZjWgKzGbb4XdFqU8tNuPOMCHrkoM3tKZsW0Bd9/kjYC0L6aTFG9qINqKoygoD4axX+4KiUIXlwXbtlePfD0RK5JeiJ3+RFFn4mvsEdNpZJv+v8nnjC3sifnbuOXOmATbI7WOBedMAPstLsGjboM7JN/cF07VETy2HS8P50smpV5VBC6zmtn7E9ftXGH3YF79LXnM8e2YyxrsIfPk6u8MYhMePb8I58xR8xBR471zjgFQzwu7nCCzJyPh145rm0vV0V/+Gv8YkjsJyfaTP7nEi2yIsc4S/9S1r9bl5swj175O862E92cJP8/S3tJ+Md+Sbe8icre1oY/2E8K+O9ZycmpL2mrbr/OrzZF992vq4Ibb/I9iW0jNbSHie3FKoPvb7zQFTvZAQMkH5j9L7Wu50hqzwgtDdFxValjeEBQYZveYzzCsZ6veuTzrn1JrdU4b6ep681YxPIPZPjc5j/uqzeqUyoujw5QBk46WGOVN9luZwowFle1OPe8h1AfWRUb93jz6MC4jM9oRGE28Z1AHTbcnW/9D98JgeSQT4g7s8RPVdQ19v826P3+o3Rb5rTAj/91slP9msp/acj8LsXHamEk5MsWdVJcBEYXxPyBbIC/wNj/uYMYDxHMgKQgYW+6xzfwenJi358nvJ6QugJ2VE9lTjk0lLqgL4AicDGPixbAXLzt8RsnnQDEFXSyYGNAEtVKPd8UfQGF2jc13uUVTCzNzoA0jscIfB85zwodD8WoYUxQBKJEODYiexfL/K7RTAC1uxRMP7xIJLmodc9m/vOIO5A3zgtcZsrP2D/SLu/+Ud/CC2dW+0QSAVHiczrwsfcl1+o2qli80fk7oawLQHWWJAkf3NO66/fE/fvsd9jE9pXLxaLNzUJnvkjcORunrmtAhZIjofVRz7hvLcFHthawIfJ1TV+Pjz+JvmTMCAZ9Ph7W5ZQe+Rz6Dlsy5zZMZ0h3WyfTBAdS7dIN5+EqXCAnSCYMErSooBgbuwBLrQEHXGw2sEe+UviKB/kk2QNoyUTbOhWYauwU7UNJpAvP3a4TsIIU93T9TDk1rHaIZFi53Aa+TYWS/2SU7qyTUISK07A+fb+zhUXYMLwOITQIopwgz9IGPgkO0DQxTVjJzu+af5Wd9jNs5fj1XoYvhrzs5bjvnPgj9hGnrbVwUxE3T9+iUiZB3wlA9ta7hvPd/0dIsm1gkTvZCIesG3x0UqNsZ3DYe5iBdvgT+IBf+KL4gtfYr+PCGwiL+e+M3iAuT4pSChfhqNiL/mz91XyF7Ncb3XCc8RAdgtzXQvbrWi4lqwkWWxRXILJ7NU4fmKxWNwrfMp1VnDcE0aIabANvrINJFlFmY3iD2KPotGkiUUR2n6T35fQZoWDgzFoVQIBlLMzNIDGoRkrY2HYzmU0nB5ZETxkRgIzA7Q8+OgAY/dBQgB5AgYyCkwBEOMG8Eg1kBHYPQPoAXskgxEyPNUey4iAH7g4172RXkFc8GCsyDeSpNLpd4CCnKvcuPauTdWoX8J9ZwpEQEHWae+jwIAUCgq5p+72QRgfEgRJ60sHeZMxYuc+5gdUBS3yUM0BPoBSQCQ3ekeAkX5BwXJsykPFFJEmA2COHP9BVPc8D9EVjOxJNN6UF/2QJZ0Mgw/AFvAQPIT47rEHW6BgF8gG0uena80FQCG9Arjgw+YEYc9mc8AJGRfUXYPQ2nuoCicgpv7Nlf7pfixCKxFgQ4KtRMHzBOx7hPwlYioCiDr5sHEgj5TShyBleZxtCWrkwf7JHMkE0pJEwY+tJ6FVmZDc8SFAi/CzF3KkDwGB7bBr/mCcruVXnkmeSAMisspfBYGe49iE9mUhGzZOf3wYSSNf8zEvdvmGICLDMdP1vaMikyRAcONjkjp2whbYveCFQDjfXlWETmKBIJL9MRLYbTLmRxIadmDexoZg8l02RT4+U/ljO4gnssRf+bPADz/gFtLFJ1vd8lt+RBZ8jbyQLM+EG+4FZ2Ern+Vjqq+qYWwJFkmKnh+YiZyxN+eRqf3LElPkJvHAlhjbZtzbgdQgkRK09v7IpXG390fec49zK7tDCC2eYAyeb+6IFHwhJ0nl/WMcZMK3jZ9v+h3GIrhkSEbImtVHn0miEKasjotzzuef5ISEwS0/4TV8JxMJCHnRK1xWhGGzsM7fVeO3rSxts6uxPofF8AoeGR8Mgyd8k075l4QZBiOQyCTcgoOqpGyM7YnPdEg2/BAewjzyZyvsLOUvvvBH3EChRjJETgpg5Ov5fAXZhccq3cahkCY+wFMxUIynt0yM3cd2HbrJVRD6hANilmvEH/qXOMLcSY8itP3i3pfQUjDQZ5j2vHFK1TUBE4nloAxsHaFldA5gzCEYiWwUCQbSjB6Zc31WDRiX+3IQf1OJBUC++KGqwmA5GAPmKADDucBRhiZICPwAWjDjcEiU57o30sN2gLGMmqPk+citc4A/hx378FzVC/ITtC2HCl4ATVbI0X0um0xQUBFEmjiuc43NZ8gjgusQ4PxDonyOVDmXQwtO5Of+QCTlgVQCGAR/VRDxxROy8NOBbCCXrbyGMqJL1SJB0niQZoCCQCB/iKFnCSzGiATKlgUVtiDxoVN2Z7wIuoBtjyCAco6KLEDNSjL90y9QZGdkMxahRcoRSkFIhRRZVNFRdZDMWUkAyEARqPpcFV2QVslQbTZX+rb/mcwFOf82EdrcQ2v+KrzmC3DT//wuMAvSEkHk1nOQfcGQ3o2llRddCCD0fy6EFi5JfiVm5Mbu+TWizjdtmWBvVjFWbQ2gG4ntMLGCAWQgGAugedABubFByRx5IBSwKRPHsX1+0/2GWw6QSLYD44wTRuWWA+QJHt4n7NH/c8sBcokEwGKYm7JCimGtShtCoQAAY8hasuL+SW7hCTmwG74LYyWZ8J4Pq4pZOeB3qlfpywoASAwMJmsEhv5gBSKnait+9NwfiVm1B/gQQkv+VlHMGV7SM5+Cp/xD4UAyQJ7ITCbk5ktWbJIdSa7EQJVACSWbZWOSxky+fO46ybYENGVrdeueEefsjyY7soTH8J4d+jyr2eeyDxoOG1fiqbGyB/NHYulLPKXzVYTWHGGTQpZkgWzFM/JUYSV/Cb/Eq5W/+AHvkFAJHntSHGPbnsfO4AS9kr2VR3GMnMVK1/oyO38XO8QU95dEwArxnp5UxI0dzsJjupQ0rsObo2JDEdp+8e5LaMmYUSjZM6BdCS0yynhdz9mBigx/LEKLTKjGIK+InKy/JbSeC+QZL9DlKJ4tw0OYECFgNiWhFSQEDEEIUCMhKhPIILKGiCKmwAQgALkEZEuK5gkABD3OKmhJOlRlgcomQitIpTwQQURLQAfOyINnJklF7lt5Gav7t/IaElrgBAABhIqZao/gAUhkvSrxsmo/k9AaBzIGJAVLFTmEwz38QwoRSMSWnFpCK0lJ/cu+kaMxCS25PzESMdUBekPYBSo+JckyBpUvXzgC3MaBdKj8AWM2SeZJzAUzhDYB2v2R0NwvqbqLCAh8KmO5d5cNt4SWfHPPreCSFWpVOxUNgRgwC0BA/5wJLfKGbPBHmMEG2LGKKnkK/O1BL4i5bTrIA9uVLCcR4M9Wk8w7yZ0KGsKCxEl82D27gk+q2XQ19dESWgFe9Y890ZmkIwmtSr2xswE4wSdaQutLsJJD9g8HWkLrfDjIfj0PaVYwyPuzZQUFhMD1iflsG/74nc8iHypaEg16Qm4QFISVvJPQkiGMhWsqbHDWsq77S0AcYsqq+9OHvw+Tl0MJLfuAZfCzl9AipJIJsudPiBhbQ5iS0FpCNxc4pcJPJ+wVsfI31UB+aYXBuRJf9qbySc/OZ8twRULud3jG7k+5tzv9gO7pOIsruxJaSZh4z/ZgnmQgE4RDCa0iA5tjv3Sgkk63SWglb+KbwgIbpU8JG9njAklozRXe0Bs88bM34R8VL4rQ9otzX0KrQsUBARpFqyrKkICDZXoghbAIugyW0aiiMlyZDoNT4RNwVVrSuIEzoxFwkBkkSYULSXNfmRlAAJ4qD6opAIXDy5oBq8qUoIR4AR3PyWV4y8RABJCp/skkOQBCLdNmuAybUas+qBK6X+4HQyLtqxobVBAVMkTikBjzFrQQOeNBzM2BswNAAQUBNnYZpHORFHMTmBA/lU/LVM4jT/dAFs2VvJyvQmv5EgElG/IgAzLm+ADUQd6CpcN4Ul7IWMoLQbOExx4QzPZgB5YejQtJBvLmjLw7FzGxVCdw+YwukRk6oHfnqJwgNT5DwCUf7sGGARcbMS7BEvizJfpnl+RjnOaEGKpCbTq2LanDGIEGwSAvpAmRBOzAmm0iAypWqux0QoYIreCHBBgvHSFbrqc7ZItMADB7UEGwzYY/8RlVdTKSBDhPokFXkhcgjQxbAuWbqhG2lbBZevF85FVFXQAlF/JC6PgIAs2uVe0QuU2v1tkmn34E+sgz6Qkx4me5QsB22TzcMWayEqjaQzKHzPJ7FRvYwt7JxJI9gsDHyS6rrgIYO6EPNsg+kBV+RVZknhX/Q+a0y7V83wqJMSNxqk7wh8/aX8qG6JcM4B08MEfYq9qJ8L8l/JWerW7QLZ/Jg70I6P5ZYZAQIVuSJ0u7iBmySMa59Yit8kPbj9iTe8MNVTo44Eu3zuG3ZAyDnWc8cMhBR7CVrcIfv5M3W9t0f0UPhGd4HEpoJdDsib+Sp3jC5uAl7OG78B+ewGbYIZlkE/yev1sNsV2LP/u/+/g7QsVf84u2ErPc+y7BVV2EqeRHd2zVfeE5/5JceSbZ8EkFDdh5Dgc/hH2+D0E+qvHwxPwl8fAELtGvn/zLPMUiVWfn8zsyFPvZNszBFcS/3CaV+7FT/mRg9ZJ/0xnbhBOu9xzcQsxSKIB9CjpsL79kakXQdZ4DD9itSix+AmNhqvm4BhaaJ1vlh64bO+536bIIbZeYPnjSvoQWIRQ4BB9ENffHCASyfsGcszLg/PYm4mmZAQlhkAwcYQSKAo2f7gtsbaC3DOt3AGrfpsDPYN0PAXB/z2VkyJA9S8BbRUVQAMy5/80SgiCGhAAsf7dUzXBtcTBm5yMQ5uP+5gdIAK9KB7tCRvKb6/1S3n4mYiLbNWcyTXB3JRlYOvFFmfwiHKAzJ3IiE2M3H+MzB4CBYPlc5ZDcgaV5ITCSBgSR/HNZlgxSHuYtO+X07k8m7V5CulNdMZ5WXgBIRdKSe3uQHaAjf7oGzMDEcpPn0h9CISADmFwCMg6Bk3wEaQFcNcl19Jj6MBZ2wf6AJAKdm/qNQ1AwViQHKabDTUcPYWOn9GXfFRtk32SafuEeCIBnCk5kQIbGkQErv3lONgiF+bBj59KXz9kyUu/e7IKM2Ah/cR57T3slW3bBllY9P/VLNs5p/dW92RrbEQA2fQGlRz7brX79GfyNb/NnlcV8u4j58QVJS0vQ3AkBJRtBNHVO/uZhTuZmvuwubZlv+H/7Fg9blPJLfplwHDKXXa81D1ukjDcPvoG0sjN+CV/zQAAkTuwBgfT2gYyB5rbK3tmuSilb5b9k5P4Il/nDC9UrvswfyQ9R9Tu5s0nn8TNJNpyBJa6Ds+QMk3zOt9sEMm05kxXbDjbdX4KGiKwiE4cSWvqHSeZk3OZE7ubJBuGfuSE6nm9eyCjSKW7wWX9jd/BHTII/fNw83UMihly1q1bk5PrcE8v/VW35PAygN/6JcLMHzzj1mzdaOyYj+oVD/FM8QuKRSzqH21aEEEJyae0RjpOPJCBXTjI+D+WfumDXDrFI0kmW7u+5DjLDEdgv/4ZvYkbiLYx0D/fzf5js+XSadu8aYxfv2avP4I2KuW0yJ6nOmlwR2n4I3ZfQ9j+hzjxUAgidJCBfEn/o/er67RI4NmHLSo5KlkNFzNKw4H+qwz4xS7+SUFWJTd/kPbZ81skAaZLQqCqepFpyKuWM/NzhHlqka47HoYR21zlLJKz2WCVCXMsGd5XgvM5PvPF2j5PtXy5C2280RWj7ZTX1maoClrhUDizv1DGdBI5N2FQf7dvLaqLlLpWLuRzHls9QDiqCKmOw3V64c3l90Vz0NRynqpntFKpqlnBVaedIzqYktBI+S9+2IqhK21c89XaUudrb3MatwqzooEIr9p6qycoH5VaEtt98itD2y6rOvB4JTE3Y5ibZks/cNHaZ452S0F6mBGtWZy+BIrT9KipC2y+rOvN6JFCEbbOuSz7X4wvnPNMitOesnRrbKBIoQtsvxiK0/bKqM69HAkXYitBej7XPd6ZFaOeruxp5pwSK0HYK6oC3HPQ/oc4sCcxPAkVoi9DOz2qvb8RFaK9P51c34yK0/SqvCm2/rOrM65FAEdoitNdj7fOdaRHa+equRt4pgSK0nYKqCm2/oOrMq5JAEdoitFdl8DOdbBHamSquht0vgSK0/bKqCm2/rOrM65FAEdoitNdj7fOdaRHa+equRt4pgSK0nYI6gwqtzh3Z3ah31N7dqVWdNoXZwnLbtbrraI/nfZY63ugg8svxAnmdqrR/1a3F+y29UF5HJW16dcvRNWjT59uevevnXnqufarWl17gPeY7N3VP0XJQW1TNGtzb/7VX9Z5FnXF0W8l3UuoEo2Wj1qNjvyd11fNaWek6piWkrnI6V+WR+iebVe0wd5X3qvOL0F42oRUjdInSjlmb3Wzx3GM77I9PaBvN/jSicD9dkbTs1OXOy/eP/V5XuMUHdBDUyWjb89LfdJXb5yXx5qjVKez17lodmTY9E5Zof66DHnzZNr4e2Q/PKUK7j9Smu0Zs1wXOu1y1uNWufHiISTopakWvzf2qd76yPd29NADJVuta1LKtMe3KWHTP0w7ZM7Vl1oVPp76THUVo+0V/6grtPcNQAd4xDzZxv8VicasgZzq+PHvZWvCVy5aDuoAIbpxOhyQkVucmL81GqJBf3Yk2fT7m2DmscSCcTxqZ0Goz+YIg62ThyLa2XvavDSRdtG0ax5xbe69Nz6MvbRDJ4eeDIBxrHEVod5fs3Ak/cnefIFxPjHaXu0vh5isEai/a15bzuct2nL8wAaHNxPQ/xjN1nNsW2NPfEGCkdtdDov3ly3at3xPNBbYR2l3vv8/5RWj3kdp010j+JI3iykPWEFpx7inLJFE79e9bQ2jFxAdFy2Ft0491aH0rwRV3tTTHTyS7eMI+SeAo4yxC2y/GXkKLCD05+ijrbf386OWsiqYHtWqBKp5+03pP63CFNL582ef69XHdl0UFUA9lQKQ/tYqG3uO/uPz5ojD6L10sFu9dnvucCBJmI+jcNvowq4AwbhVXQeTroprp2ciYftpD4xsSWpVhY3xt9IVvCS0ii0jJFBFbFduW0K76vF/ifWciczoicV79qs1V/3Dy/u74+eKomgIDMhGgnf/CIKR6sH999LWmgzdEANftJqtIKtYCE5kJVKrCb1wsFrJf2bDqk3aogjSir/+74K3KixQgx8NuOWT71Bi3zwRC9qF1r8BLl4Kvv8vePY8u9ENHDshboGYDgOVd0cvdPT8QFSL6Z0OqyexSP25jN3+y0iOdPL4qAEnXl20Bv9XMGISN3nQVIierAfq+Pzj8hi60upVkkTOiQB6qWjo4GetjYmUAoJqjfuV8Q7/0Xwk7cE/zHRIUqw3kRRfmzjd0nrPaILi8J6qM/9Rnjh9x1jb5wAu605HqrYEXVkkeHr5Jv3/b2JOqiO48PxcycZ3AAiPYn9UBfp7zZdvt/a0yIHlfEboXiPRk/7dLu/+8sP2XhFzh0w8GJv27pZ09Os4lf9c/MOzIM9kZLIFFer3zSx3ebgi80mmL/K10sMdbhmxVMuldJffde8p422Uqwlap+O5dQp4w4caoYrGj+8aYJO9skU/wQf79j/EA8lCJggWvCLzmg1puf2IQDcmv+1kRk+TDGOfTJ9tDRMiHHcNM9oGokKUqGr3Rv/vBAuTa/ayEHXIck9Aa/9cEDpGvaqPqNLtlk3TOHmAkXPpvgUH8njz44GfEObCTHOiGPZE/XDvnw/yN7MlQfQAAIABJREFU931hX/yTD7EhMTv1h2yaD3uAcwpE7Cf9/RZRtMIZ4Bd/8fmj4nwrcPydf5MvWYppbATWsSd+yd9/P/DsKyNpJFf26/nIcxao+OUDlisJfx/jUBQRfzIG4AN3WPqmDo2uE4OM+9uWvv8Ny3G+KTADjtCjFVpz/+qo4P564LeYo+Clwmxsr4nfR9VrEdp+cfYSWoEYoaRowQipYpiCANL0OREoLRkgJ4iOAIO8MGT/GLZlOkBgKYpBA0RG+0thFAxRsAYY9Oh8wQEJZvjaDSJBQAQZ4BiIMoNkfAwYqR32oU9CaymBAwJhwJzkB2HlDADXtQg2gpeVym2f90u870zOJmgYo/FwZmTS3N8WRAUACEqIj0ADRB8WlWcB5G5xns8EZE7PoekCWQa2dIksWVb5pghegjDCQ7f08B0BKHRDrwI1nZO75wCLlHcSKPoQyI0fkEt6XIOgIK3vXAbPz47g5nnAENGmD4AJ+MyFjQB+AAJogI5KOZKCVAA688r5k4kqGb19SYCYYG3cSG/vsY2wbbuPYADQ2aPlKrakMmZcxmqMABDJAIgCP3JO1ub45rB1S3RsnyyAqq0XAB7ZR1JUPdj0XzcDkvQIrnROx3TIDwUgVRB6QJL/bkeS30v4+abnGysbgjEIpLHQryDAdnwOKxAFOEBfEhBbfZACpBhx5fPkQY90796Ca+IRuxe8kAskmDzJRYXF/8mbrGATrEHwLdGTLb34J1lwwCj4Q3awznWSASRWQiDwGj97FlRhHH0Idr8VvsiOjRlJR6olk8eo7iC0xklW7EZwlmzyFX5nDM4xPn7EV+gfaXAeLEAG2IX5wUjyJSfbsmCyRJ/9IKH+T4/8zT3Ij/4kZ7AT6TUWvg9f6VhhQGIFA2Dq8H62TOxTLU5bPBahJQvjJxu+TLb3CKLODh66LHJIHsyPvZPx4yMh5Y/iliRLPIFb/J6PGy/SL1bBKnI+x8P8jdH8YTrMUMTgn2xEYsx2+La5mxd7Qgj5qRjPjyXtYpa5uwebZJ83RSKJkCqWiC1JaNkRm+PLZMqWYZpnw48s0sB/BS2FNMWwfL7x4Cfwly4kfHxScpLb9/iFRNbv7A8OI+/8wzXi7fvj+f8nfAG+KDjAE3avsMev+Da8gcHtdr3R9FqEtl+UvYTWHRk2Z9ZTnYMjsaqwjAzQc2KgztA4PAMTEN4RJIxjI1BIGLAEioISg0FCOYpqoaqpv8vSgKGABzw4DfAUpDyTw6gwCYzILucR6FW8hsewQsugzR34Io4yztxSoKrIQTxHoEBKhhXa4ef9Eu87k/OkvIChuQmwyB5ZcyLVSPLk9OSh2kEHxsa5EFdgQh6cVvDjhAgkUikTthyEzKr+tlsyksgDLfJVCfqrpmKqkoMAI2sAKQmtgPW0IMycOw+6Yg/IL+CwxxBpzS0gAAH4q9izKZku2SPlSAMCyxYQaOBmju6peuD/bMP8BUjjBaBALMfgb4JPb5X2UELLZulPZQfgAm7EC2lLfQBO2T/CTi5s0vjpQgU95UsWbBWR4CuqmGQh6cj5tpUuARNB5KOCMSJNrhIR8hYoDiERdLpJPnxXgECiswpoPOy21a+kljzYMTxQ/Ug8UR1kH7CGvSKdAolAYx6CprnBIwSVrOxn9bn7vS4IRStvSYREis0bj+vJjy22e2hhF72RsYB1pyUB/OYgsapz/rE3wZv98T36sXXH3lLP5x/0z8da/+jz/r6zskIL+1Sf7LtHusiLTJACOCGZIx/zyMpo+sUdQ7a5MoKwIp/mA2vyfEkVfdAfwgu7YTXSwM8kyOKBlREknp8ZHxlKJMUF1eLh/dj0IbZ4LEJLA+yMPiXmqU+xgD/lc/kdPCIveAQHJVzIkqLErYMUwiOrAciZgop7wLc/Db/wLHIQv/ZdNemzmv6zjImPSn74J0KpmsnekVv2IFnLqibd80txwv/hufkiv3gAe1R8YQ9sFjFlhxKdltAiqTBfciSWwEa+z8YkCa4Rs8lPIQQ2wDq4ms+HofThfHtvPZ8/Dvfw+owNew5MEPORePqzQusZ5g9PzEU8MjfxEXGGafiC+HyMpPWD2ipC22+0vYSWM6pMcFKZK9I6JLTAyzKdSmJWnFT/gIAA3RJaIC9YISqCtKAtuKg+Ao9cMkVCVFVuE8ZlCRGoAmDgiwxwBhkZMoW4AAuG2R5DQgtwkTQk3U+VmZbQIl2eIZAx2CGhHX7eL/G+M1tCizTSk4qeqhW5yR5lkxyfPFYRWkQXYRdgEAXOb95JaGWnMmagSj+rCC35cFwg3UNojdt4EFRjzCPlhwghD4J/+zwAIjAIcKp6AAIRtA0BuTFuoGMuKiKASpa8jtCqLiD1bElgBaoSq97jUELrOcCSnfiyAwBEQFXyVAPpw34tchqb0LqnaoeKBD9A+AGyQDAFobX8xpfgAN93CHrm2+oXsVbp3JXQCvyqqAic7RMIvArtkNBmNSjlzf4FSYHV2NYRWngiYKo6CmpkqaIrsAnGbFEyIkE8F0JrfOSuKowAwIgeQiuYw102g3xLCMiXbnoIrYqVRIG/ICK2M+SXehAiBEYSCl+umdAiXLAb4YJvklI6Uj1EvOABfFW4WfXFqV7cGvO8HkJLr0gfrBGn/B+xtLKC4O1DaCUFMJOv8m32KclKQsvO3Bc3QCjFb/5sxSmfD+/Ev3WEVtzEX/iL5FWiZRV6E6FlyxJHHCXx25YkuFCEdkzLO+BevYSWMhmPZU/kRrBQHZGBytgBIwBElpArGaxzVUMsoQJLpFM2xdiRJARXNQShtddWVccytKzYfRkL0up8hNrSn4oJw7Vfy2eCNGNE9gCm7QmeP/xS06ovhQFtVU8ZmfsnoQXIHAGZk6EiZi2hXfX5ASpYeWlLaI2N3GSZnFpGK7AKYECQ/IeE1tK+sQMZOpFNI1SWuI5JaJEWupegGBOSKgmhYwAjIaJfVa6W0KoAGa+qPJ2qLiNBgBLhA47OQYjodhuhZRNsEtipGAIwVaLe41BCm9VQwcnYgS+Ci8inPlRtJYdJaBEsPoIAAE52SX7kpRLfW6G1tM/3JJiSB9U097W/cwpCa7UDiRZ0JFRwQ2CSBK/S7zZCK/iTBdmxdVhhLvzCPPkx8tYSWoRXhTj3XKtcCjx0YXldtVxgohfVdKQCruRhnDDGT/IkS/ezwpFLzOdEaMlGAs53rGLxPQmgJJ8vIedsgczIMiu0yDsZqlKrwpknUup+qwjosEKL3PNpNgbTJZBZTLgWQqviqpCCeIk/5M3+JN8pb9VxfgzHYbIKOixXLOldNerFrrHO6yG0/Nw/ibq4xF8kV4ot8N18+QvbkiSKDwoozkHobWURF1Q9c8sBkqkQkPu+rdi2FdqW0CLPniuJa58PU5MAr6rQ+hvyS/78gj7wkXWElj7dT7LH1q38wHa4UhXasSxuhPv0ElrGKRAjRJYdVLsAJ4OVUQlKlhAYHuIh6CAeAJCzI6iypnxFF+NVzVUBRToQIOcyYhU5Ri+rRcJUa4GFoOjvnmV50lKaManuAXOGpcIgm2OASb4ZqaUC2a/MKsEcaAtSAInTAHefCXqcxjMEScFz0+fHACQyVqHkMJa1OBsSSLbkSebGjvAgd5ZSBS2kUEXK8pAlH6ChikXGtnVIAuzHRNgEIKTR4Tl0hBwgnwCF89KT8wR/To+k2IYAnFVmUk6ucUgc7F2ka+cZl7FnlV1iYA8VIKJncwQ+dC2hoUtEj+zJAPlwH4RFRVYwUNWwAkD//o9YeI4vJOQ31i2xInHuw0ZURnZZyjuU0LJzCZ4xCHIAl97YOALAnhFXc0AA7ceUpNjnSGfGap8ZuQuKCBefIiuJF9+hT8QMAbHsm3aIvNM/u0DSyNWzBB0kTTKqonCI3W6SDxuQTAh0ghn7pQ//Ur/sS8VUcOCT/o60C3gwgc3lkq+kWDWF7gVFn0nmyE6yyU48g33ml0xVeFRPyUDiTd6wzpxhmbEJoqplApWA2y4ZIoKWVWGIxJbM+IaKs2097MzYjZltqXDCE75mznAIllkFYYPtHucRYPtDvsZeyIO9kQ0yBcP4Cp+y9Mp+yD5Xd+An+Tsvt/OYJ59UeSYnc2Cz5mOu7BhOKhzAYf4s2XQv96AzCSN/zMPqChmRMfnQhUQdkXA/hQp2zX73Xa495pYD44c/9mtbaYSd4h9fMh+kDBmTKPmMvG3fksCZn4SCvzknEyx2DjPJX9Fh33mPZUOb7pP646cwhA+xIXPIt/AodOV3TsTZtB/JueTTPOEB8scPYB0/Ne/EN74oDvBZduvvsI5/si1JqZiVRSY2Jjlm7/wPNiCzMJMvsF/3s2rDZ8VMK8H81N/dl0+LfXxfXEXAFd6MG3bCWVVfK0jmjetIBOlZcgJ3cSB/w0+MR7X6EExdq4vactBv7r2EdnhHIMVYc88bI9l0tBXHMd+ruuqZnABxAiwCf+7j65dKnTm2BNiLSilwaoPe2M8Z636HEtqxxnGu95lKPsiERFTibM9mHecnASswKlYSyqME9A1TPiahPT9J14iuUgJFaPvVvi+hFWhkoCoqspVNFQiVFlmdDExG5RvLx8xMZVkqBjaey6brOK0EZMgqPRIZVY1z/WZvK6WpCNtpNbP/06eQj8SU7aiq2HaAvEiI6jgPCahqIbJigC0yx2pysmm2RWjPwxZqFEeUQBHafuHuS2gtF+Xrs+xD9e3MdQdCa8k/tyrYlnBMQts/+zpzCglYYrcP0Z6yOVRnyWQKwjaF7I/1jCnkg9Da82tfveVxCWr75oxjza3u2ycBRFbCYduHGDB1ddYoi9D26arOmrEEitD2K29fQtv/hDqzJDA/CUxB2OYnlQ+PuOQzZ+1dztiL0F6OLmsmayRQhLbfNIrQ9suqzrweCRRh26zrks/1+MI5z7QI7Tlrp8Y2igSK0PaLsQhtv6zqzOuRQBG2IrTXY+3znWkR2vnqrkbeKYEitJ2Cildc+KJWvnap/8o6syRwuRIoQluE9nKt+3JmVoT2cnRZM6ktBwfbQFVoDxZh3eACJVCEtgjtBZr1xU2pCO3FqbQmNJRAVWj7baKX0HoRsRcseyn0sK1s/9O2n+mbzRoceMXTIT2+tz/pfM7wjlYdUzQUOFS25Od1OvS07d3AJOANFBow+OmatluSz9v7eXG1d07Sy766GUu/xuGtGcPDO4fNxb88su2sN2to0uDb2cbhXC/VXiWncyS0Xmxv3BoM7PKN8rQvHe52aS6xyUPOQT5wXmMRDQHIJA/zhSH8yWerDnjGFuCMF8Nf0zG2PfTI+1jy7SW0bMWrJuGGN2VseivPLmMdC892eWZr5zCQ7a+z833ue4pryFHTBhg3POhLi2V2lofX9/FvmA4D6JaONT7x94vy6SK0/SbZS2h1+NAhRmvDde8R1U4OYOjutS8x+6jo3vHq6Drmfu6rI82Uh/lypGP31eakuv3ovKUrlw4l+x753k7dUnSt2fYOXqTPeyS9H1gTirdGp5cEx+wi5H7e64sA6rais4tuX/sc9Ks7kM5wXt+276F7lA5Qxqqjky4tZImwATttO70mzCuFEHZdm5yjg5V3IuuMpnOXTjI6/QyPcyBs7ZiQcHO2NUjr6Z5kxfVkQhbsS7edQ+yrHc+p5ZMd6XQP8kJ/ukySLyiyMe+uffcK3bJ7nbO8Tk7DhmP7+L42fozrWnt4+EhbzchbNyydxabG6V5Cy3/oXFcp5MfcJfD7HrqvZWJv7rpMeQ/vLonmvs92XWKzDmYwGdZN9exDxr3uWsml99rDau+R16FL5z2xXyKuE57OZZqriEPO14lM51BdI3Up1aFSV0htny/q9X5FaPtNrpfQ9txRgPACfW3oVMXGOBgrfWrrOuXBubS7/ZMjP1SA8T5fAVhL00MIB5DTjYuj68m+jdDq8oYkaYkKNJB4LURbQpv3yx7kAFQbR20uT3louwnwkBMtUAFaklvEHOkjBwCI3GtD+9AAuttEi0QETza/6jg1YRuOSRVCn3Ttnc13F0KrxTD70sL0EPs6N0KLVNj/r90o8tob0NnMgyMh0jb52ght2oMWtHP/7kQvof3CxWJx72gNLEbBCMnuvgc81A4VXvba3b7PWnUdrL9jYIJkfe6E1nvtFVe0VrbCaE5apltJYa/0BcMksAoQsFDVVitaBFeBAsbD/OEq45hyP8m9itD2i72X0N46ejEzKAFBANGDW6arDzoC4bMHBdHwdxXH7wzyo8LnkIG59pbxu171j1tWkp4VwVoDBgAhm6ZHvcBl1bJfWTbjRUz8X99oPaX1fR4uMXgZOwewpKjvNtLmHgKgCuNzwyEQV+NEYBAczqKHsx7eup8Z/9uX/Ztf1zzTZ7eI+1vyQQxduy+J1zddf2vOiXCQDdIIcPUE1wP7K6OqKQP9sVhmImPVEfJUYdWxDfFXUaUPhNZcspMbeSGBZAgMgDKSo9KgJzVZtvJwf0Q37/dX0dNeVuwl9+6BEJs7+QGg+0WPbLKWEAiadENnemurBqugsgdzdb2+8BIXWbjzPYcdmKsM3UHmbCSDh2cjdUhNElrkVHbvPj8b4CYhUcGgI727LVEhtIiMca8LamMSWlXpl0bVgb0j2BIF8yMnv5unSo8VCWNl/3TH/n47eqmzA3atymz7j/MFAHpF3MlQV617hZzJlzx9Rof6pJ87oRXAfiTsnc+REd9gMxI+8mBDSWRUntmoKjTdmy+Car7sWwJA/qqHKjzkT7bkze/d3/nsjR1ZNfD5IdW7fvTd/0yJsJ7zGpboJc8mnrf8ku8nhV3zY7hsNYLc2D3sY4fkQT58AKGFN3DD0jX5/UEzLJUwMUIVnJ06B5lQEYet9EFWbNAzVcTdH95+3hIP/ijkyefImm+TL52NcfQQWmTW+I2LHfF5CbG/P3K5ovio8JFWnhpGwAu+B2va+eiKBlNUo2ESIiWesB3EjGzuFFVbMhHH4JEiABwka+e3zYUUE8QljUTeGDgLL+mGftvxiDmwla6thBo3uz4FsR5Dh+5BRvwXpn9WQ2itBvu7LUTfGhwDhvFVuMamxBeE9ksjhtp2cFFHEdp+dfYQ2gQoxEeFDqCpiHFy1VhAisjakqCSJKgiofcMIsj5ERLgAER1lQEK/v+yCEaABXlFSgRqy/DIpecxXKTVMwV792fkjFh1ZkhKcryWooH4/1gGs9cH0FjqFujcS2AUQMkA6H9KPI/zGJtrjcHngNuB9D0/xgiwBdRVhLpfA4tFS2hVGRFQDvsFQZyBNkBEbv8wCK5AYf/ntwSpkWQAS2SA/BBa+8QEeuTTM+jDcgxC6wCMzwwgRX5dP5THM0IO7tcSWjpcdT5de4bx0zES5Tq6tYxEXsDZuOyZokvBWcXshgiItjOQKdKrmsKuHrGmuxxQT0JLHg5zpW/6JE/ViyeFLqcmtIgT0PXvnWFXZP3pMW6kGglgq+RinHxC9SX9R9Bkg5ZKkVyEwLkI7F+EvrWTRtDYLv3Tq5+2/yA2fHQOhJb+kHoykOwgVxLSdwSm8HsJFf80H3JDTsiRvMgSUVHVQQgQJ7Jnf+TvGrah4sN+fYa08S12RIYSLHh1zgRBIieRZeOwkw9JSmHH+4KkkR97eXHI6S4xT/NCQMkQFvDxFwbhV3CAcUhBbs1Q9WJnCgRwEOmiEz4rYUh581/4TY7kl/KWtFkOPoZ8ewgtm0rCA2+M4+mBB2REjkh5ylNs8J0GPqbIAFPNR5dD9iMJuF3ID3GFaeYuCRZbtPdGMGFhJsaKA5IJ8VL1EQmlp7QxeIjUsnd6lFg4j34VCmCl8fib8bBntm08/okH52yvu8RDxbOs0ObqCTn8QsgBiVdMo5vcR1uEdhcJX/C5PYTW9GVNSAWwA4LILMKHTAoKQBXBA3ZAQ2BGyHIPGyeXeQIQPwUU1UE/kSNg4n5AECESxBEhhBaAAAMOL2sGLogX0EGSV20A/9QgqcYr60MIHxN6NF5E0HyQHdkuJ7JMD9wBTc4POULgBQbPAe4yRHNAgt0fqB9ytISWnMmOHBx+AjjBGVlBToCoLF/VAzDThzkCOE7/2CC05Kb6YK8p+ZNVO9aW0AJrzx3KA1iqoA8JLb05X/Wa/Iw75aeKCLD9jnSpfrmHJMcYc98X/boHedqbjaipAN0UVTmETOVZZs6+Vn3xYR2hZU90pULLZtxbJYU9TlmhVUFTpWFvua/LWAQ48xeEyBBAsyfE0xjpFQGhL+dI3CwzIrXIhwDnHL4g+Knu0G8GNcEPAaFPnyUBPPcKbfoRsolcpb1LjmCClRFVG7ZgFQPmqJSxn6wgkiWfYVsIMPmzv7Zyw26yQouMDPUBI86ZICjaSPr5nX3g7AwRQ6LYBn3DN7L6zMAB/k4mVpKS0PrM36xGmS+84esqmQ44C4/hp9UAsmSLVnoQLeeRtzHASasjMJ7t5T3ohXz/dzzDMj35jtH+fCxCa0wpT7bDf1T82B+/bOcDr8kDNsJNcyFv/o3cWqkkRysqVmKsMJCP81W13V+y3hJasrbqAufFRfKStNBvOx5+AEvoWsJBH2IVDDlne90lPq4jtHCcbGGYuAsLyEoyUoR2Fwlf8Lm9hNayhwAA7HoILRIiMCOiKiDILVJlaYxDImAqIYKzPS9JIC3btEvcLaFVhTAGhA4YWNpZ9YUe6uohtLnUJGsW4AA7QtESWtVezgNokC3j4UCA5ViEVqVJJUQwVqlDylS+VV9U9wQQVWvEDNEWnCQWghPSzfFzy4EKIUJpGVoAcQ+g6hgSWuDovq08bG/Iim9boUVonW88SHQrP1k1u3JOVsJUKt4SFQjArkqyjtCqztKNvcVWBZAVlfVVRw+hJUMVP6sIAteUhFYlR0Xfs7PagNAiawg3+zJPsmgJLTtj25bK+Y9KpICXhFYyJ3iq1CAQSWhVN/2djUosVDbnSGglr6rMKoMq9kgrTPF/VSz77Oj+7isILVvJijR5IRSqie02giGhHepDwnrOBKGH0CLxSJpVLf/YDLsaElp44+8IkuSXzWTy1UNoyRtGInWeM5Q3Qku+yLble9VzGDaGfI9NaM1NJRA5zW0SLaFVfWZrEksyg6/wmAwl0LAH4d1GaCX7krjcDiEZWUVordBJ7q1IXDOhFY/ZldiE4BahvWCSusvUjkVogSSyJYPKKorgZHkQQbM8jCDK4gFED6E1L9UH+6EQ5U1Z/jZCyxmAPaKHYMikfWkAyQC0OR4VMqCGjCMmqmKejRQeg9ACKYRORcCWAUvTvp0vgCEq9swaI/C0jxj59w1bVVIVBRU5y6cILUKk0mDLhessE5JdVmmHWw5UXIbyEKg8b9WWg+H5rhW0VMJUiW3pUBWnM1UeQIwAA/xNhJasJT2qIPmmiXVvzdhGaCVI9IZY2t+L1CC05iMorPtW9lh7aO2pE3Rz/7YqO7sjF8kZsqqqRSctoTVWAU711d5PurSfLgmtz1VvrIaYSxJaBE91J6s8fIYc51ahRXwkdeSjMuvtFebk7/Yf2lMOR1RXhxXaltBKItgeO7ACRP7IFfzJCi3yTEe5J50++MwYhGsXLN7l3B5Ca9n2xrB/S/5WTSQ/LaFVJFCFJFvbUxJvclvSroSWfylSSNDghiqa5XR4QL78YUz57kpoLddL0l0HWxBRiT7styVqWBFVEYQfqsvsx3zICD4jui2hVeUmc0kqomW+VhJeFTa4qUKb3zWA5ewVFqwitGKPQo4x2ToDS+EZGVt+P2eb7bXvbRVaiYVEnw9LxPAIsU/RQHw+9/3vvXL40Hm1h7ZfZL2EVoapSsSJVQKRAUucgA+RUdFAxAQfBiVgIyVIDPKCeAEyQIBMqj4CU9U31VoZsCUthAxRyi9nABog7FmWtAQ259ozpMKLqAEAVV6VyfxilvHmF4uMVwZnidIhCNpXZlyqQDJplTvENpfJXK9awUFUmlUhjdf8kUKAYm8ncAEqGQD6Jf/hMy3NkxOAAppA1fhk+eZsng5/N19zz20W/kaHiDBQVLkiL8GJPFTGBSs+YewqlQ66sGzlHLoAvsC5lYdlMbrN+0kgVMmQKokJALVFA5iSn/PzfaBIrLde+CKEZyHTZCizdj/6zeqi+7EbRNwSKSKDtNi+4jA+tgTs28MyK6ImGaF/11kCFFB9locxGa+gZByeL4kiX8/09+ExFqF1X1VTNoNMGZ8v6iCpgp85sTH/Z0/Ip6DrMB92Qe78RyDN+frClLFLGuzbY3/8hhzM354z+rFNQQVDsE77OuTb3SmnMeWzzmfYNkJrPyJ7Z9vmb8+m1YHck6xyLZHiK+ZmbHzfSoOEjK5t0UFkXUP+VmN8q1pCIBkgx9xfSx9pkxJb2DPG8vi6ee7zd3OWyAj+7ID/ZoLDjmCezyVBEqj8cpzqKd+A3zAb3vAzOKbg4F7IaB4q2/zFqhUyZeWELMiILiQT7EuChRjzW/KG67YLkbdYoFLJxr0ZwLUquXweMYER+8q3h9DyG9hDp3A1v4xqnrCdnOClpX3yNC6EFO6ouFrOh5sIZs4H1pqTBF3Bxr3IxtyRZM9MeYh5sNZ3Gaw4wVQrDXA/45WVS0SbH/NZfszmYYbxqLZLLoxHwYDNikfuh/y69yWQWRxDPFVssVpIRooZ7KR97zg9iDf0h9TiFOTGvnJfMdyAhWO9e3sfPx3lmiK0/WLsJbT9d1x/JkDguCoonFLVgHPb79i+GH3TsyybMfp8jRentoSFQKlS7vvC/zHmV/cYRwKybQFbguSQgNhyAZymOqYgbFPN5RjPKfkcQ6p1z10l0ENod71nnV8SOCsJFKHtV8eUhFbGnlVE2aelA6TFvqBtnT1UJlUaER2VvXwpP0KrCqmCoPpVx/wloHJme0U28FAhUR2i46mOImybJV3ymcoS6zmbJFCEtuzj4iVQhLZfxVMSWnqx1OSLSv5vf1Fv60nLCZZuHfbF7btE1S+ZOvMH6VmxAAAKvUlEQVRUEqBrlfhsdYjYTt35pQhbEdpT2X89t18CRWj7ZVVnzlQCRWj7FTcloe0fVZ1ZEjitBIrQFqE9rQXW03skUIS2R0p1zqwlUIS2X31FaPtlVWdejwSK0BahvR5rn+9Mi9DOV3c18k4JFKHtFFR8Q943Xefe07t/xnVmSWC7BIrQFqHdbiV1xqklUIT21Bqo5x9dAkVo+0VcFdp+WdWZ1yOBIrRFaK/H2uc70yK089VdjbxTAkVoOwVVFdp+QdWZVyWBIrRFaK/K4Gc62SK0M1VcDbtfAkVo+2VVFdp+WdWZ1yOBIrRFaK/H2uc70yK089VdjbxTAkVoOwW1Q4VWJyodaB4YXaF02Bnr0A3I+2l1P1nXinSsZw3v41Vgurjo7pLNHXRk0Umo7TalC4se8ppAaApRx2VL4FwIrc5DfEOXO12J8vBqMw1GtD/WNcwr8KY8zkU+U865nnV+EpiC0Oowpxuftr15iAU6VOpyuenzfH+6pkJ5eF+6boDZJez8pFojOisJFKHtV0dvhVZbRb3A9Tj3JTJt51a1DO19sp7sWlhqt6hFp8DsnbQAYqpDK0Rt8nSmQg6Mw8F+dDHTFlZLwbcuybZ+79rhvjpaOB7S6naq+dVz9pfAVIRNq0394bX/HB6SyMdGW1eJ5PAc73N2jkRs6raXU8lnfw3WldcggSkIrdbdd4qYp1uhOKU9q9bKWrLyQZ9rnY7ktp9rf4vMKgBprauN+fdHYyAtbet96tdgpQfOsQhtvwB7CO1HBZm9SziyapAAqtOXRgnI6d9EH2vO759rEEStaOlD0HYeIvi3y97hnxyEUcXzT6MD2P+Lvs1eqC/r9dNL9fW11lcbAdVRTNbr3A8MpqmahRi7zjWARQUWSZZdG4cx+10VVm94YKM/9tc2hNZtVY31iNbv/E3xHD27nxd/f0u/iOvMGUrgUMImyLEvdqspxPvjd6LQ8YyNatf8NfG54Mim9Stn3/qP53lWLvipqlDas8/Yu0otP1jnHzkOPzUkGfrMvqo5VD77PreuKwm0EpiC0Hrep0a8QmStIiro3GoZj54eMe5T4vP/vOJzcednonjyP5edMe+zxINvX664PDhwoTRaEtgogSK0/QbSQ2hVZznqJywWi9cHGVRdtVR/r8Vi8fBwTtWkT4+q6+0Wi8UvLxaLn11WObUyvV+QTcRWC1vtar9lWRn9zcVi8SfL14Y9crFYPGyxWLx3sVh8xTJ43ztI5Xtieeb+i8XiEYvF4r8vFgtVLcuvwCQrukj0jYvFwnkqV8jBs5fE+rlBoBFcoPT8xWJx07JN7tct73W36Ejl7+aTFdp1hBZ5/9HlXP4oqrX9Uq4z5yaBQwgb8vigxWJx1/CZj1suLz4lEidyeFQkZ5Ij7aCRU4T298OP+JlOaT+5vMfvxHYYAVFSpgr05vgbP5Ic2i7DN/yzgsJfrXxI1O4QY5Ho/VlUicbYMnOIfOZmCzXe85XAlIT2OdGmXaHkzuGz4pHiDkIr1mjjPvxccUelVtxAhl1r5c/fpl5ZOV9N1sjWSqAIbb9x9BBad7Ms75/tBipIiOpj4jEC7+ODkCK0iObnLBaLLw7i94y4TnUUcfzrqC4JzjLez46Aj9AipvYXCfqOH14sFq+JYK6ahaSq8v7AMmg/pMlwVbxkzJZfkQHE9btiyRbAuA6JNYZ3LO/x3cuK1ROiavZjca9thBYwGY9KF7JQx+VK4BDC9knLQPXM5b7Wp0bCxW+QVURTcse+2fmXLZO+28YKxSui6sO2Xrbc5nLfZaJ3w3JJku8IpPbJsmsBVAKI3CLJbNYyKAJtlcG59uZZzrTC4BzV22wdjQT/8QhqO0Q+Izy+blES+KAEpiS0YoiVOT4qWf29ILVWLBFan1tFGX4uwZWwIrvvWiwWVjqtaP6X+j5GWXGPBIrQ9kjp5nPGIrQqrJbkkUr7hRBXgdyXWXzBShXX9oM8VEUtuyCIlmMRUHuLbhlEU7XVsivi6acgn+erlMqGEVTXtgegeUFsTXjAYrH46mgagTAg0Cq1iOndo8JsWRghV93aRmg/NuYmu0acjd2BOBhfHZcjgUMIG9L6jUFQ273WEsHvXfrJG2KVgw2xQ0HutZEI2t7i//xDYmhFQGLGl14e/qDCiqD6kiaS+9Ko9PIPVV/bZRBb/9yfD9pq8M+xcjHGF8gOkc/lWEnN5NQSmJLQ+k5FbjmwGmnV8dFLX393EFqf55aD9nMFlXbLgdVHMcf1tttVlfbUVnTmzy9C26+gfQitJf0XL6udj4vAjEByZkEYIW0JLSKpAoow2hAvW/XPsmoSVA4vcP9gVJ6M6aER6FWY/jKqSpsIrT2xvg3uvi8J4PHMVYRWdQyYIB3IsY38KleWaXOT/nAPrTHbCmGeKruWb+u4XAkcQtgkc6o1VhRUYlRIYRIiieyq3qqyqqJaibAMaXuOxE+CJtjZY25LDt9x3quW2wnuEef9Roj9nrHCoPpj68KQ0PInVVtB2Dj+Q6xQjGG7h8jncq2mZja1BE5BaP9vfKfEHlhxw+/tHtrh574HkoSW33/+8jslPxUxzmphEdqprWZmzytC26+wHkLry1iC7e0jUFuy9I1/7XJVilRnVY/sZxWIBVLbAW4TVSb7bAVTy6a2Brje0r8Kkm9u2zerymkp1jKOypRK769GwDZGe26/Ic5BnBEBhNoyDhKKZKtkIZ72zyKriLVtDwDFN0x9ntmyMdr64NmIA+JtG4EqsnvYi2teAAcR92Uc8wBMqrFTvo2hX5t15lgSOISwSa5sFfAFL/bJnmwV8FYQX+SSvLFt/vCt8UaNVwbxVdnhE/lFS8mc1Qsk1n5ZFVd77+w9d64vNdp+Y2WCf6gQCa78QzJov54kL31OBZgv+aKa//uS5T7HIfLZ53l1TUlglQSmILTinxVGRZBfi9UOxRJfaPaFTSt+Plfw+PXB52KFRFT85O/ijUT3bbENb4z97GUZFy6BIrT9Cu4ltMicQK2K+fbYI2v/n+VSf7d3SKC0LO//voxCD/YcIZj2BCKdKlC/HYRQcFa9svSqwiTgc3RLs56HLHtllvf2CdjO8XxfLPMc2a4vhyG0zvVlMaQbKVWF9RMxQKIRi8+N/beeb6uBvUwOlTNvM8jtCwiI6pdvoefhGTm+fUlAv1bqzFNL4FDChsyyIfZnKwtCasmfXXoFl8DI3rzrmF2q6rD9OwYhlfAhtvbj+pwt/6/wO0HQl7+8as4KA3Jrz/oq//ClSgGVf7jGff3uuXx/37ceHCqfU+u3nn8ZEpiK0Nrew5fz4Lv8ky8ivOs+V33lb+JVHuIN/1doqaMksFUCRWi3iuhDJ/QQ2v671ZklgcuQwLEIm1ULKwz2yZ7ikHza+23vHt/f9z2Yx5LPKWRSz5yvBKYgtPOVTo38IiRQhLZfjUVo+2VVZ16PBMYmbCo09s3BJl8ksfVlzsfY8pmzLGrsp5NAEdrTyb6ePJEEitD2C7oIbb+s6szrkUARts26Lvlcjy+c80yL0J6zdmpso0igh9B62blX3Fz7YR+e7iW1Of3aLaHm30pAm2df1KpvIK+2C++99WaGkk/5zSkl4I0its/suxf8lGOvZ5cEfMncF+E34mgPofXFH1+iqKMkUBIoCZQESgIlgZJASaAkMKUEutqR/wvbdYASg59SagAAAABJRU5ErkJggg==\"\u003e\u003c/p\u003e\n\u003cp\u003eFirst, the dosage and administration protocol used in our study were relatively conservative. We employed a cumulative dose of 30 mg/kg (10 mg/kg \u0026times; 3), delivered intraperitoneally. In contrast, studies reporting positive effects used substantially higher single doses, such a\u003cstrong\u003es\u003c/strong\u003e 30 mg/kg [34] or up to 100 mg/kg [33]. Griemert used higher doses, also reported negative outcomes [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e]. Additionally, the intraperitoneal route, used in this study and others [15,35]\u0026mdash;may result in reduced bioavailability and suboptimal pharmacokinetics compared to intravenous administration [33,34], potentially limiting therapeutic efficacy.\u003c/p\u003e\n\u003cp\u003eSecond, variations in injury models and animal species likely contributed to the differing results. We utilized an LFP model to induce mild and moderate injury, whereas many comparative studies used controlled cortical impact (CCI) or weight-drop models, which typically produce more severe and focal injuries. These model differences may influence the detectability of neuroprotective effects [17,33]. The LFP model, characterized by a combination of focal and diffuse injuries, may require distinct therapeutic strategies. Furthermore, our study used adult rats, while others employed mice, which may respond differently to both injury and pharmacologic interventions [34,35].\u003c/p\u003e\n\u003cp\u003eThird, the timing of our assessments may have limited our ability to detect therapeutic effects. Evaluations were performed only at 72 hours post-injury, without assessments during acute (1\u0026ndash;24 hour) or chronic phases. This limited time window may have missed critical periods when TXA could have exerted measurable neuroprotective effects [17,33].\u003c/p\u003e\n\u003cp\u003eLastly, although a comprehensive battery of outcome measures was used\u0026mdash;including assessments of inflammation, apoptosis, BBB integrity, and motor function\u0026mdash;none showed significant improvement with TXA treatment. This suggests that the dosing regimen and administration route employed in this study were insufficient to modify the key pathophysiological processes underlying TBI [35].\u003c/p\u003e\n\u003cp\u003eBased on our study and a review of the literature, we suggest that using mice as the experimental model, employing a controlled cortical impact (CCI) or weight-drop injury paradigm, administering a single high dose of the drug intravenously shortly after injury, and conducting early endpoint evaluations may be more appropriate for assessing the neuroprotective effects of TXA.\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. The relatively short observation window (72 hours) may have precluded detection of delayed or long-term effects. Additionally, we did not evaluate dose-response relationships or alternative administration routes. Future investigations should explore varied dosing strategies, earlier intervention time points, and longer follow-up periods to more comprehensively evaluate the neuroprotective potential of TXA in TBI.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eUnder the conditions tested, TXA did not exhibit significant neuroprotective effects in a rat LFP model of TBI. These findings underscore the complexity of TBI pathophysiology and highlight the need for careful optimization of dosing, timing, and injury models when evaluating TXA or other antifibrinolytic agents in the context of TBI treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflicts of Interest:\u003c/h2\u003e\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eInstitutional Review Board Statement\u003c/h2\u003e\u003cp\u003e This study was approved by the Institutional Review Board of Chi Mei Medical Center, Tainan, Taiwan (IRB No. 11306).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eInformed Consent\u003c/strong\u003e\u003cp\u003e\u003cb\u003eStatement\u003c/b\u003e: Not applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eThis research was supported by Chi Mei Medical Center (Grant No. CCFHR 11303).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eK-Y C, J-C L and C-L K conceived and designed the experiments. T-T E.N performed the experiments. K-Y C, J-C L, C-L K, H-YH, analyzed the data. C-C L and J-C L contributed reagents/materials/analysis tools. TT EN, C-L K wrote the paper.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eSpecial thanks to Chiao-Ya Hu, for her valuable contribution to this study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data is provided within the manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAndriessen, T. M. et al. Epidemiology, severity classification, and outcome of moderate and severe traumatic brain injury: a prospective multicenter study. \u003cem\u003eJ. Neurotrauma\u003c/em\u003e. \u003cb\u003e28\u003c/b\u003e (10), 2019\u0026ndash;2031 (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMahmood, A., Roberts, I., Shakur, H., Harris, T. \u0026amp; Belli, A. 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Res.\u003c/em\u003e \u003cb\u003e302\u003c/b\u003e, 106\u0026ndash;115 (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStatements \u0026amp; Declarations\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Tranexamic acid, Traumatic brain injury, Neuroprotection, Microglial activation, Blood-brain barrier, Neuronal apoptosis","lastPublishedDoi":"10.21203/rs.3.rs-7165502/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7165502/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCurrently, there are no consistent findings regarding the effectiveness of Tranexamic Acid (TXA) treatment following traumatic brain injury (TBI) of varying severity. Anesthetized male Sprague-Dawley rats were divided into sham-operated, TBI (1.5 atm or 2.2 atm)\u0026thinsp;+\u0026thinsp;vehicle, and TBI\u0026thinsp;+\u0026thinsp;TXA groups. TXA was administered intraperitoneally at 0, 24, and 48 hours post-TBI at a dosage of 10 mg/kg/day for 3 consecutive days. Microglial and astrocyte activation, TNF-α expression, neuronal apoptosis, and cerebral injury volume on the ipsilateral side of the cortex were assessed using immunofluorescence or TTC staining. Brain edema and blood-brain barrier (BBB) permeability were evaluated using Evans blue injection, while motor function was assessed using the inclined plane test. The serum D-dimer was Pathological severity scores were evaluated using H.E. staining 72 hours after the initial injury. Compared with the TBI (1.5 atm and 2.2 atm)\u0026thinsp;+\u0026thinsp;vehicle group, the TBI\u0026thinsp;+\u0026thinsp;TXA 10 mg/kg group showed no significant improvement in motor dysfunction, reduction in body weight loss, decrease in BBB damage, or reduction in injury volume, neuronal apoptosis, or necrosis. Additionally, no significant decrease was observed in TBI-induced TNF-α expression in microglia and astrocytes, nor in pathological severity scores. Intraperitoneal administration of TXA at 10 mg/kg/day for three consecutive days did not show significant neuroprotective effects following TBI.\u003c/p\u003e","manuscriptTitle":"Exploring the Therapeutic Potential of Tranexamic Acid for Traumatic Brain Injury: A Rat Model Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-14 18:20:37","doi":"10.21203/rs.3.rs-7165502/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a17f27b9-acba-40bf-85f3-2747147800a4","owner":[],"postedDate":"August 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":53071173,"name":"Health sciences/Diseases"},{"id":53071174,"name":"Health sciences/Medical research"},{"id":53071175,"name":"Health sciences/Neurology"},{"id":53071176,"name":"Biological sciences/Neuroscience"}],"tags":[],"updatedAt":"2025-12-02T18:53:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-14 18:20:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7165502","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7165502","identity":"rs-7165502","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}