Comparative Study of Working Length Determination in Teeth with External Root Resorption Using Clinical and Radiographic Techniques: In Vitro Study

Comparative Study of Working Length Determination in Teeth with External Root Resorption Using Clinical and Radiographic Techniques: In Vitro 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 Research Article Comparative Study of Working Length Determination in Teeth with External Root Resorption Using Clinical and Radiographic Techniques: In Vitro Study Toka Akil, Ali A.Razooki, Nader Rezallah, Farah Albanna, Ahmed Tarek This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7168945/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 Objectives The aim of this study is to compare the accuracy of CBCT, IOPA, and various electronic apex locators against the control group (Actual Working Length determination through visualization method using K-file size #15 under Microscope) in teeth with external root resorption. Materials and methods In this in vitro study, the sample consisted of 13 extracted permanent human teeth. External Root Resorption was induced at the 3 mm apical root. The control group will represent the actual working length (WL) that’s measured with a K-file #15 until the file tip can be seen visually at the apical foramen by using the CJ-Optic Flexion microscope. Then the teeth were placed in alginate, and the WL for each tooth was measured using two brands of electronic apex locators (APEX-S and RAYPEX 6) with a K-file #15. Measurements of WL from the file tip to the base of the rubber stopper at the reference point were done using a digital calliper (Mitutoyo 550-331-20 digital calliper, Japan). The teeth were then fixed with wax into a gypsum model, and radiographic techniques, including periapical technique & CBCT, were used to record the WL. The WL of each method was statistically compared with the actual WL (control group) using one-way ANOVA with p < 0.01. Result One-way ANOVA test showed statistically significant differences (P < 0.05) between all groups compared to the control group (actual WL). Whereas the Independent T-Test showed no statistically significant differences between APEX-S EAL and RAYPEX 6. Conclusion This study showed that there was a significant difference between the actual WL and the digital periapical radiography, CBCT, and two types of EAL. Thus, the combination of EAL and CBCT could be a reliable method for determining WL in the presence of ERR. external root resorption digital radiograph electronic apex locator cone-beam computed tomography Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Introduction and literature review 1.1 Introduction Accurately determining the proper working length is a critical factor in the success and long-term prognosis of root canal treatment. It plays a key role in ensuring effective and predictable endodontic outcomes. The root canal treatment should be extended to the end of the canal; the most appropriate landmark is the apical constriction or cementodentinal junction, or 0.5-1mm short of the radiographic apex of the root. (1) However, this task becomes significantly more complex when external root resorption (ERR) is present—a pathological process marked by the progressive loss of root structure due to inflammatory or other etiological factors. External root resorption (ERR) is particularly challenging to diagnose and manage, as it often mimics other conditions and may arise from causes such as internal bleaching, traumatic injuries, ectopic eruption, orthodontic forces, pulpal inflammation, or jaw pathologies. One of the main difficulties lies in identifying the apical constriction, which is crucial for determining the precise working length. Conventional radiographic techniques may lack the sensitivity to detect these irregularities, increasing the risk of procedural errors such as over-instrumentation or incomplete canal preparation. These limitations highlight the necessity of employing more advanced diagnostic tools to enhance the accuracy of working length assessment in teeth affected by external root resorption (ERR). (2) Accurate determination of working length (WL) is essential for the success of endodontic therapy. Several methods are employed to establish WL, including radiographic assessment, tactile sensation, detection of moisture on paper points, anatomical averages, and electronic apex locators (EALs). Among these, intraoral periapical radiography remains the most commonly used technique. However, this method is subject to limitations such as distortion, magnification, and superimposition of anatomical structures due to variations in horizontal and vertical angulations, which may compromise the accuracy of linear measurements. EALs have gained widespread acceptance as effective tools for WL determination, with reported accuracy ranging from 55% to 93%. Nonetheless, anatomical complexities in the apical region can reduce their reliability. Consequently, many clinicians recommend a combined approach using both EALs and radiographic methods to enhance measurement accuracy. Furthermore, advanced imaging modalities such as cone-beam computed tomography (CBCT) have become indispensable for the diagnosis of root resorption, offering superior three-dimensional visualization and diagnostic precision. (2-3) Cone-beam computed tomography (CBCT) is an advantageous diagnostic technique that can show anatomical features, including extra canals, canal angulations, and the exact position of the apical foramen that are frequently invisible on traditional intraoral radiographs. Clinicians can more accurately examine the extent, size, and severity of the lesion due to its capacity to produce multiplanar, high-resolution images, which makes it especially useful in the evaluation of root resorption. Notwithstanding these benefits, the routine use of CBCT is restricted due to its significantly higher radiation dose compared to conventional intraoral radiography, especially when determining working length (WL). The regular use of CBCT for WL assessment is therefore a subject of ongoing discussion, as the choice of an effective imaging modality must strike a balance between patient safety and diagnostic benefits. (3-4) A few studies have been performed on the impact of ERR on the accuracy of WL determination of EALs and CBCT. With the increase in the use of CBCT in endodontic treatments, we decided to compare the accuracy of the three different modalities (CBCT, digital radiograph, and EAL) in root canal WL determination in teeth with the ERR method in an in vitro study. (3-4) 1.2 Aim of this study The aim of this study is to compare the accuracy of working length determination in teeth with external resorption by using two brands of electronic apex locators, IOPA and CBCT against the control group (Actual Working Length determination through visualization method using K-file size #15 under Microscope), Because of the altered root morphology and potential communication with periodontal structures caused by resorption, establishing an accurate working length becomes particularly challenging. 1.3 Literature review The goal of endodontic treatment, also known as root canal therapy, is to save teeth that might otherwise need to be extracted by managing pulpal and periapical pathoses. The treatment consists of multiple crucial procedures to eradicate interradicular infection, debride the canal system, and obturate the area to prevent reinfection. It is indicated in situations of irreversible pulpitis, pulp necrosis, and apical periodontitis. (4) Clinical diagnosis begins with a comprehensive history, pulp vitality testing (thermal and electric), and radiographic assessment, which is frequently augmented by cone-beam computed tomography (CBCT) in situations of complicated morphology or non-specific symptoms. Following proper aesthetic and rubber dam isolation to guarantee asepsis, an endodontic access cavity is made utilizing straight-line access principles to preserve peri-cervical dentin. Canals are first negotiated using stainless steel K-files and then shaped with NiTi rotary or reciprocating instruments, which offer greater flexibility and resilience to cycle fatigue, especially in curved canals. Irrigation procedures include profuse use of sodium hypochlorite (NaOCl) for organic tissue disintegration, 17% EDTA for smear layer removal, and supplementary use of passive ultrasonic irrigation (PUI), apical negative pressure systems (e.g., EndoVac), or sonic activation to improve debridement efficacy. (5-6) Gutta-percha and a sealer—typically resin-based or, more recently, bio ceramic sealers due to their superior biocompatibility and sealing qualities—are used for obturation after the canals have been completely cleaned and dried. Based on the anatomy of the canal and the preferences of the physician, obturation procedures like cold lateral compaction, warm vertical compaction, or the single-cone technique (particularly with bio ceramic sealers) are chosen. To avoid coronal microleakage and structural failure, it is advised to immediately put a permanent restoration or core build-up, frequently followed by full-coverage crowns in posterior teeth, as a properly executed coronal seal is crucial. (7) Because of the action of clastic cells, a pathologic process known as root resorption causes the loss of dental hard tissue, such as cementum and dentin. It is generally divided into two categories: pathogenic and physiological (as in primary teeth). It is usually pathogenic in permanent teeth and, if not identified and treated quickly, can cause tooth mobility, discomfort, or loss. (8) Root resorption is divided into two types: exterior and internal, with different etiologies and pathological processes. External root resorption originates on the root's external surface and has numerous kinds. Surface resorption is a modest, self-limiting response to small injury that normally heals on its own. Trauma, necrotic pulp, or infection can all cause inflammatory resorption, which is characterized by fast loss of root structure and periapical disease. Invasive cervical resorption (ICR), another name for cervical resorption, begins beneath the epithelial attachment and advances rapidly into the dentin. In its early stages, it frequently shows no symptoms and might be misdiagnosed in the absence of radiographic imaging. When the root surface is resorbed and replaced by bone, usually following traumatic dental traumas like avulsion, replacement resorption, also known as ankylosis, takes place. This causes the tooth to fuse to the surrounding alveolar bone and ultimately results in tooth loss in developing patients. Internal root resorption, on the other hand, typically occurs after persistent inflammation of a critical pulp and starts inside the pulp chamber or root canal. On radiographs, it appears as a symmetrical radiolucent expansion of the canal space and is usually asymptomatic. Dental trauma, which can harm the periodontal ligament and expose the root surface to resorptive cells, is one of the main reasons. This includes luxation, avulsion, and root fractures. Inflammatory mediators released by pulpal and periapical infections, especially those involving necrotic pulp, promote external inflammatory resorption. Orthodontic treatment can cause pressure-induced resorption because it compresses the periodontal ligament and causes sterile inflammation, particularly when severe or prolonged forces are applied. Internal bleaching with high hydrogen peroxide concentrations and periodontal or periapical procedures can harm the root surface and cause external or cervical resorption. Prolonged physical compression from tumors, cysts, or impacted teeth can also cause root resorption. Individuals may also be predisposed to resorptive activity by systemic disorders such as hyperparathyroidism, Paget's disease, hypophosphatasia, and specific hereditary abnormalities. Idiopathic root resorption, which can be localized or generalized and often familial, is the term used to describe the ailment in certain cases where the etiology is still unknown. Accurate diagnosis and successful treatment to preserve the damaged tooth depend on knowing the underlying cause. (8-9-10) External root resorption and root canal treatment are inextricably linked, especially when pulpal necrosis or periapical inflammation is the underlying cause of the resorption process. When the dental pulp becomes necrotic due to trauma, deep caries, or other insults, inflammatory mediators are released into the surrounding periodontal ligament via the apical foramen or lateral canals, activating clastic cells and initiating external inflammatory root resorption. In such circumstances, root canal therapy plays an important role in slowing the course of resorption by removing the cause of infection and inflammation within the pulp area. The canal system can be properly debrided, disinfected (typically with calcium hydroxide as an intracanal medication), and obturated to help get rid of bacterial by-products and provide an environment that prevents more resorption. To stop the resorption process, protect the tooth structure, and avoid consequences like perforation or tooth loss, early diagnosis and prompt endodontic intervention are crucial. As a result, root canal therapy is an important tactic for managing and reducing external inflammatory root resorption in addition to treating pulpal pathology. (11-12) When a tooth with external root resorption undergoes root canal therapy, a number of issues may occur that complicate the process and raise concerns about the outcome. Particularly in cervical or lateral regions where the dentin is thinner, the resorptive lesions can alter the normal canal morphology, making canal localization and negotiation difficult. They can also raise the chance of an unintentional perforation. The uneven resorption flaws can retain germs and debris, potentially resulting in a prolonged infection, making thorough debridement and disinfection challenging. Overuse of irrigants or medications through the weakened root surface into the periodontal tissues increases the risk of inflammation or tissue damage. In irregular or resorbed areas, obturation becomes more difficult because a full and hermetic seal cannot be achieved, increasing the likelihood of failure and microleakage. Furthermore, the likelihood of vertical root fracture during or after therapy is increased by the structural weakening of the root. Particularly if there is substantial loss of cervical or root structure or accompanying periodontal involvement, these teeth frequently have an uncertain prognosis and provide additional restorative challenges, occasionally requiring surgical intervention or even extraction. (13-14-15) Determining the optimum working length (WL) is an important step in root canal therapy. In cases of external root resorption, however, finding an exact working length becomes substantially more difficult due to structural changes in the root anatomy. External root resorption, particularly in the apical or lateral regions, causes loss of root surface continuity, uneven canal outlines, and, in certain cases, the formation of resorption chambers that interface with the periodontal ligament space. These changes may interfere with both radiographic and computerized methods of determining WL. (16) Even though they are often employed, traditional periapical radiographs do not fully depict the degree of apical resorption. The canal length may be overestimated or underestimated due to radiographic resorption flaws that are overlaid or poorly delineated. It can be challenging to spot the apical constriction or apical foramen, which are crucial features for a precise WL assessment, when the apex appears blunted or uneven. (17) Since they can identify the location where the canal ends at the periodontal ligament, electronic apex locators are usually more accurate than radiographs in situations of apical resorption. EAL readings, however, could be erratic or unstable in situations involving open apices or holes connected to resorption. The EAL may provide erroneous readings if the resorption has produced several departure points or lateral communications, confusing these exit points with the apex. (18) When resorption is substantial or unclear, CBCT imaging can be very helpful. In order to help clinicians, determine the precise extent, position, and shape of the resorption and to facilitate more precise WL determination and treatment planning, it offers a three-dimensional picture of the resorptive flaws. Additionally, CBCT can show if the canal is still contained within the tooth structure or whether it has communicated with the outside of the root surface, which would change the instrumentation strategy. (18) Tactile sensation during file placement and paper point tests can help determine WL in addition to imaging and technological approaches. A quick decrease of resistance upon placing a file to the tentative WL could indicate a perforation or penetration into a resorptive cavity. The degree of communication with the periodontal space can also be determined by inserting a dry paper tip and looking for blood or dampness, which indicates that the WL has to be adjusted. (18) In conclusion, external root resorption poses substantial complications in endodontic diagnosis and treatment, particularly in accurately establishing working length due to changed root morphology and probable communication with periodontal tissues. While traditional radiography and electronic apex locators are widely used, both have inherent limitations when used in teeth with resorptive abnormalities. The variation in accuracy across these methodologies emphasizes the need for additional research, particularly under controlled conditions that allow direct comparison. As a result, the purpose of this study is to assess the effectiveness and accuracy of clinical and radiographic approaches for determining working length in teeth with external root resorption using an in vitro approach, thereby offering clearer advice for clinical decision-making in complex endodontic cases. (19-20) Materials and methods 2.1 Materials used in research: 13 single-rooted teeth, high-speed hand piece, straight fissure high-speed bur, round high-speed bur, endo Z bur, K-files #15 (Dentsply), standard ruler, CJ-Optic Flexion microscope, digital Calibre (Mitutoyo 550-331-20 digital Calibre, Japan), apex-s (rogin dental brand) electronic apex locator, electronic apex locator (Raypex 6), gypsum, wax, film holder, film sensor, digital radiograph (IOPA) (planmeca romexis), 3D imaging (CBCT) (NewTom). 2.2 Exclusion and Inclusion Criteria: Inclusion criteria : All maxillary and mandibular intact teeth that have a straight and single root. Exclusion criteria : multirooted teeth, curved roots, destroyed teeth, calcified canals 2.3 Sample preparation: In this in vitro study, 13 permanent mature single-rooted teeth were used (that had been extracted due to periodontal disease or as part of orthodontic treatment). Teeth was cleaned and disinfected with 5.25% sodium hypochlorite, then the teeth were numbered by order from 1 to 13. (3mm) from the apical third was measured by a standard ruler and was cut in 30 degrees using a high-speed straight fissure bur; this simulates external root resorption. The crown of each tooth was flattened using a flat diamond bur (D and Z, Switzerland) with a high-speed handpiece to produce a flat stable reference point for measuring the WL. An ideal access cavity was prepared for each tooth by using a high-speed round bur and endo z for deroofing the walls to give us a straight-line access. The crown of each tooth was flattened using a flat diamond bur (D and Z, Switzerland) with a high‑speed handpiece to produce a flat stable reference point for measuring the WL. An ideal access cavity was prepared for each tooth by using a high-speed round bur and endo z for deroofing the walls to give us a straight-line access. 2.4 Actual Working Length Determination: The actual working length of each tooth was measured after the rubber stopper was adjusted by placing K-file #15 (Dentsply) in the canal until the file tip could be seen visually at the apical foramen (resorption level) by using CJ-Optic Flexion microscope. After removing the file from the canal, the distance from the base of the rubber stop (reference point) to the tip of the file was measured using a digital calliper with an accuracy of 0.1 mm (Mitutoyo, Tokyo, Japan) for the actual working length as the control group. Teeth then was placed in an alginate mold (mixed with a normal saline) until the cementoenamel junction. The working length was measured using the first brand of electronic apex locator (APEX-S- s, rogin dental brand). The working length was measured by k-file #15 and the file was measured from the base of the rubber (reference point) to the tip of the file by the digital calibre. Then different electronic apex locator was used which is (RAYPEX 6) brand, and working length was determined by K-file #15 and the file was measured from the base of the rubber (reference point) to the tip of the file by the digital calibre, then the readings was marked as electronic apex locator (1) and electronic apex locator (2). The teeth were then fixed with wax into a gypsum model to stimulate the bone. IOPA (Planmeca) was taken for each tooth using an XCP film holder in a parallel technique. The length was measured from the reference point of the tooth to the coronal border of the ERR using Planmeca Romexis software. The teeth were then scanned by a 3D imaging unit (NewTom) CBCT, and the working length was measured under Standard CBCT Settings: - FOV: 10 x 10 cm - Mode: Regular - Kv: 90 - S: 9:60 from the reference point of the tooth to the coronal border of the ERR. The analysis of data was performed using NewTom Software. Results 3.1 Results: Table 1: the table showing the WL for each method 3.2 Comprehensive Statistical Comparison: This section presents a full statistical evaluation of working length determination using four different methods: Apex-s EAL, RAYPEX 6 EAL, Intraoral Periapical Radiography (IOPA) (planmeca romexis), and Cone Beam Computed Tomography (CBCT) (NewTom). The analysis was done on IBM SPSS which includes standard deviation, t-tests, and one-way ANOVA to provide insight into the accuracy and consistency of each technique. 3.2.1 Standard Deviation Analysis: Standard deviation measures the variability in deviation from the actual working length (AWL). Lower standard deviation indicates better consistency. CBCT showed the most consistent performance (±0.67 mm), followed by Apex-s EAL (±3.71 mm). Apex Locator 2 had higher variability (±5.07 mm), and IOPA was the least consistent with a wide spread (±8.02 mm). 3.2.2 Independent Samples T-Test: APEX-S EAL vs. RAYPEX 6 EAL: The independent samples t-test was used to determine if there was a significant difference between Apex-s EAL and Apex Locator 2. The resulting T-value was 0.580, with a p-value of 0.563. As the p-value is above 0.05, the difference is not statistically significant. However, the higher consistency of Apex-s EAL (lower standard deviation and fewer outliers) suggests it may be more reliable in clinical use. 3.2.3 One-Way ANOVA: All Four Techniques: A one-way ANOVA test was conducted to compare the four groups. The F-value was 3.03, and the p-value was 0.030. Since the p-value is less than 0.05, we conclude that there is a statistically significant difference among at least one of the groups. This supports the notion that method selection has a measurable impact on working length accuracy. 3.2.4 Final Interpretation: Despite the lack of statistically significant difference between Apex-s EAL and 2, the overall analysis favors Apex-s EAL due to its higher consistency. CBCT, as expected, remains the most accurate and reliable technique. IOPA, while commonly used, presents the highest variability and greatest risk of large deviation. These findings can guide clinicians in choosing the most appropriate technique based on availability, clinical context, and diagnostic needs. Discussion, conclusion, summary and limitation 4.1 Discussion: The accurate determination of working length (WL) is fundamental to successful endodontic treatment, particularly in teeth affected by external root resorption (ERR). In the present study, four measurement modalities, Apex Locator 1 (APEX-S), Apex Locator 2 (RAYPEX 6), intraoral periapical radiography (IOPA), and cone-beam computed tomography (CBCT), were compared through statistical analysis involving standard deviation, independent t-tests, and ANOVA. A detailed comparison between the two apex locators demonstrated that AL1 offered superior consistency, reflected by its lower standard deviation (±3.71 mm) compared to AL2 (±5.07 mm). Although the mean deviation of AL2 was slightly lower, this advantage was offset by its higher variance and increased incidence of outliers. These results are consistent with previous systematic reviews and meta-analyses, which affirmed that fifth-generation apex locators, while accurate, may exhibit variable performance depending on canal conditions [21,22]. The t-test revealed no statistically significant difference between AL1 and AL2 (p = 0.563), but clinical relevance should not be overlooked. Devices with higher variance can lead to over- or under-instrumentation, potentially compromising treatment outcomes. Studies have shown that devices such as Root ZX (analogous to AL1) exhibit consistent accuracy, particularly under moist conditions or complex canal anatomies [22,23]. In the current study, AL1 displayed fewer errors and more predictable measurements across cases. When apex locators were compared to IOPA, both AL1 and AL2 demonstrated markedly better performance. IOPA presented the highest standard deviation (±8.02 mm) and the widest range of measurement errors. These findings align with Ramezani et al., who observed that digital radiography consistently overestimated WL, especially in the presence of lateral apical foramina [4]. The two-dimensional limitations of IOPA, including distortion and superimposition, are well-documented contributors to such inaccuracies [25]. CBCT emerged as the most reliable modality, with the lowest standard deviation (±0.67 mm) and the smallest mean deviation from actual WL. Its three-dimensional imaging capability allows clinicians to precisely visualize apical constrictions and anatomical variations, even in complex cases like ERR. This reinforces findings from studies that ranked CBCT highest in correlation with actual WL measurements confirmed through magnification techniques [26,27]. The one-way ANOVA (p = 0.030) confirmed significant differences among the four groups, underscoring the impact of the chosen modality on WL determination. Post-hoc comparisons highlighted that CBCT and AL1 were statistically and clinically superior to IOPA and AL2 in both precision and accuracy. It is important to note that while CBCT demonstrated excellent performance, its routine application is limited by radiation exposure, cost, and accessibility. Therefore, AL1 stands out as the most practical and clinically consistent option for WL determination in cases where CBCT is not feasible. Combining AL1 with IOPA may enhance diagnostic accuracy while mitigating radiation exposure, aligning with best practices suggested by recent literature [28]. In conclusion, the results of this study corroborate earlier findings that emphasize the importance of standard deviation and consistency in clinical settings, not just mean deviation. AL1 offers a balance of precision, reliability, and practicality, making it a preferred tool in routine endodontic procedures. CBCT remains a valuable adjunct in diagnostically challenging cases, while IOPA should be used with caution, particularly in anatomically complex scenarios. 4.2 Summary: This study aimed to assess and compare the accuracy of various techniques used for determining the working length in teeth with external root resorption (ERR), a condition that poses a significant diagnostic and therapeutic challenge in endodontics. The four methods evaluated were two electronic apex locators (Apex Locator 1 and Apex Locator 2), intraoral periapical radiography (IOPA), and cone-beam computed tomography (CBCT). Through a combination of statistical analyses, including mean and standard deviation evaluations, independent t-tests, and one-way ANOVA, the study provided a robust comparison of the precision and reliability of each technique. While all modalities demonstrated some level of accuracy, important differences were observed in their consistency and clinical applicability. Apex Locator 1 emerged as a particularly reliable option with low variability, and CBCT outperformed all techniques in precision, though with considerations regarding accessibility and radiation exposure. The results were contextualized through comparisons with recent literature, highlighting alignment with findings that confirm the superior performance of CBCT and newer-generation apex locators in accurate working length determination. Meanwhile, the limitations of IOPA, especially in cases of resorptive defects or apical anatomical variations, were reinforced. 4.3 Conclusion: According to the results of this study, it was concluded that: Apex Locator 1 demonstrated the most favorable balance between accuracy and consistency, with a lower standard deviation and fewer extreme outliers, making it a highly dependable tool in routine clinical settings. Apex Locator 2 showed slightly better average accuracy but higher variability, indicating that although it can be effective, its reliability is less predictable across different clinical scenarios. CBCT proved to be the most precise technique, showing the least deviation from actual working length and minimal variation. However, its use is best reserved for complex or diagnostically challenging cases due to its higher cost and radiation dose. Intraoral periapical radiography (IOPA) consistently overestimated the working length and showed the greatest inconsistency, reaffirming its limitations, particularly in cases involving ERR or anatomical deviations. Statistical testing confirmed significant differences among the four modalities, reinforcing the clinical value of using apex locators—particularly Apex Locator 1—as a practical and effective method for accurate working length determination when CBCT is not feasible. 4.4 Limitations: One drawback of this study was the limited sample size, which may have influenced the statistical power and generalizability of the results. This was primarily owing to the difficulty in obtaining extracted teeth with verified external root resorption that matched the tight inclusion criteria. Another limitation of the study was the use of a single type and generation of electronic apex locator, which may not reflect the performance variability among different devices; various apex locators operate on different technologies (e.g., single vs. multiple frequencies), and newer-generation devices may yield different levels of accuracy, particularly in the presence of external root resorption. Abbreviations CBCT: Cone-Beam Computed Tomography EAL: Electronic Apex Locator ERR: External Root Resorption IOPA: Intraoral Periapical Radiography WL: Working Length Declarations 2-Ethics approval and consent to participate: This in vitro study involved only the use of extracted human teeth, with no involvement of live human or animal subjects. Ethical approval for exemption was granted by the Research Ethics Committee, College of Dentistry, City University Ajman, United Arab Emirates (protocol waived based on national guidelines for research using anonymized extracted tissue). The requirement for informed consent was also waived by the same ethics committee, as no identifiable human data were used, in compliance with applicable national regulations. This study adhered to the principles outlined in the Declaration of Helsinki. 3-Consent for publication: Not applicable. 4-Availability of data and materials: All data generated or analyzed during this study are included in this published article. Further details can be obtained upon reasonable request from the corresponding author at [email protected] or co-author at [email protected] . 5-Competing Interests: The authors declare that they have no competing interests. 6-Funding: No specific funding was received for this study from any public, commercial, or not-for-profit entities. 7-Authors' contributions: Toka Akil carried out the experimental procedures, data collection, and drafted the manuscript. Ali A. Razooki and Nader Nabil Fouad Rezallah supervised the study, contributed substantially to the study's conception and design, provided intellectual input, and critically revised the manuscript. Farah Albanna and Ahmed Tarek assisted in methodological guidance, experimental execution, data interpretation, and manuscript revision. All authors read, revised, and approved the final manuscript and agreed to be accountable for all aspects of the work. 8-Acknowledgements: I would like to take this opportunity to sincerely express my appreciation for all the help, as well as the endless and selfless support, given to me by all my loved ones who stood by me throughout my final year. First, I would like to express my deepest gratitude to my supervisors, Dr. Ali Razooki and Dr. Nader Nabil , for their invaluable guidance, insightful feedback, and continuous encouragement throughout the course of my research. Their expertise and dedication played a crucial role in shaping this work. I am also sincerely thankful to my co-supervisors, Dr. Farah ALbanna and Dr. Ahmed Tarek , for their constant support, constructive suggestions, and the time they dedicated to helping me navigate challenges during this journey. Their contributions greatly enriched the quality and depth of my research. A special thanks goes to Dr. Yasser ELramady for his unwavering support and encouragement. His belief in my potential and his assistance in various stages of the project were truly motivating. I would also like to extend my heartfelt thanks to my partner and best friend, Raghad Ammar , for always being by my side. Her help and emotional support meant the world to me and kept me going through difficult times. Finally, I am profoundly grateful to my Family for their unconditional love, sacrifices, and encouragement. Their belief in me has been the foundation of my academic journey, and I owe much of my success to their endless support. Thank you all. 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Saudi Dent J. 2022;34:11–20. Bhagat PS, et al. Comparative evaluation of accuracy of different generations of electronic apex locators: A systematic review and meta-analysis. Endodontology. 2023;35:202–9. Golvankar K, et al. Comparison of accuracy in determining the root canal working length by using two generations of apex locators: An in vitro study. OAMJMS. 2019;7(19):3276–80. Ramezani M, et al. Accuracy of three types of apex locators versus digital periapical radiography for working length determination in maxillary premolars: An in vitro study. Clin Pract. 2022;12(6):1043–53. Goel T, et al. Comparative evaluation of working length using conventional radiographic method, radiovisiography, and apex locator in single-rooted permanent teeth. JOHCD. 2021;15(2):49–54. Kamaraj PS, et al. Comparison of five different methods of working length determination: An ex vivo study. Endodontology. 2020;32:187–92. Hasheminia SM, et al. Comparison of the accuracy of apex locator, digital radiography, and CBCT in root canal working length determination in teeth with ERR: An in vitro study. Dent Res J. 2024;21:8. Nanda Kishor KM. Comparison of working length determination using apex locator, conventional radiography and radiovisiography: An in vitro study. J Contemp Dent Pract. 2012;13(4):550–3. Graph Graph 1 and 2 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Picture1.jpg Graph 1: Standard deviation comparison across all four techniques. Picture2.jpg Graph 2: Boxplot showing deviation distribution for all four measurementtechniques. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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12:58:23","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":59064,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraph 1: \u003c/strong\u003eStandard deviation comparison across all four techniques.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7168945/v1/de792c7ceb87ca722f107610.jpg"},{"id":91862263,"identity":"5146689c-8c44-4565-8659-8db729f0f072","added_by":"auto","created_at":"2025-09-22 12:50:23","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":53877,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraph 2: \u003c/strong\u003eBoxplot showing deviation distribution for all four measurement\u003cstrong\u003etechniques.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7168945/v1/d7e36aafbe910ad436c45940.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Study of Working Length Determination in Teeth with External Root Resorption Using Clinical and Radiographic Techniques: In Vitro Study","fulltext":[{"header":"Introduction and literature review","content":"\u003ch2\u003e\u003cstrong\u003e\u003cu\u003e1.1 Introduction\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAccurately determining the proper working length is a critical factor in the success and long-term prognosis of root canal treatment. It plays a key role in ensuring effective and predictable endodontic outcomes. The root canal treatment should be extended to the end of the canal; the most appropriate landmark is the apical constriction or cementodentinal junction, or 0.5-1mm short of the radiographic apex of the root. (1)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, this task becomes significantly more complex when external root resorption (ERR) is present—a pathological process marked by the progressive loss of root structure due to inflammatory or other etiological factors. External root resorption (ERR) is particularly challenging to diagnose and manage, as it often mimics other conditions and may arise from causes such as internal bleaching, traumatic injuries, ectopic eruption, orthodontic forces, pulpal inflammation, or jaw pathologies. One of the main difficulties lies in identifying the apical constriction, which is crucial for determining the precise working length. Conventional radiographic techniques may lack the sensitivity to detect these irregularities, increasing the risk of procedural errors such as over-instrumentation or incomplete canal preparation. These limitations highlight the necessity of employing more advanced diagnostic tools to enhance the accuracy of working length assessment in teeth affected by external root resorption (ERR). (2)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAccurate determination of working length (WL) is essential for the success of endodontic therapy. Several methods are employed to establish WL, including radiographic assessment, tactile sensation, detection of moisture on paper points, anatomical averages, and electronic apex locators (EALs). Among these, intraoral periapical radiography remains the most commonly used technique. However, this method is subject to limitations such as distortion, magnification, and superimposition of anatomical structures due to variations in horizontal and vertical angulations, which may compromise the accuracy of linear measurements. EALs have gained widespread acceptance as effective tools for WL determination, with reported accuracy ranging from 55% to 93%. Nonetheless, anatomical complexities in the apical region can reduce their reliability. Consequently, many clinicians recommend a combined approach using both EALs and radiographic methods to enhance measurement accuracy. Furthermore, advanced imaging modalities such as cone-beam computed tomography (CBCT) have become indispensable for the diagnosis of root resorption, offering superior three-dimensional visualization and diagnostic precision. (2-3)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCone-beam computed tomography (CBCT) is an advantageous diagnostic technique that can show anatomical features, including extra canals, canal angulations, and the exact position of the apical foramen that are frequently invisible on traditional intraoral radiographs. Clinicians can more accurately examine the extent, size, and severity of the lesion due to its capacity to produce multiplanar, high-resolution images, which makes it especially useful in the evaluation of root resorption. Notwithstanding these benefits, the routine use of CBCT is restricted due to its significantly higher radiation dose compared to conventional intraoral radiography, especially when determining working length (WL). The regular use of CBCT for WL assessment is therefore a subject of ongoing discussion, as the choice of an effective imaging modality must strike a balance between patient safety and diagnostic benefits. (3-4)\u003c/p\u003e\n\u003cp\u003eA few studies have been performed on the impact of ERR on the accuracy of WL determination of EALs and CBCT. With the increase in the use of CBCT in endodontic treatments, we decided to compare the accuracy of the three different modalities (CBCT, digital radiograph, and EAL) in root canal WL determination in teeth with the ERR method in an in vitro study. (3-4)\u0026nbsp;\u003c/p\u003e\n\u003ch2 id=\"_Toc200489428\"\u003e\u003cstrong\u003e\u003cu\u003e1.2 Aim of this study\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe aim of this study is to compare the accuracy of working length determination in teeth with external resorption by using two brands of electronic apex locators, IOPA and CBCT against the control group (Actual Working Length determination through visualization method using K-file size #15 under Microscope), Because of the altered root morphology and potential communication with periodontal structures caused by resorption, establishing an accurate working length becomes particularly challenging.\u003c/p\u003e\n\u003ch2 id=\"_Toc200489429\"\u003e\u003cstrong\u003e\u003cu\u003e1.3 Literature\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cu\u003ereview\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe goal of endodontic treatment, also known as root canal therapy, is to save teeth that might otherwise need to be extracted by managing pulpal and periapical pathoses. The treatment consists of multiple crucial procedures to eradicate interradicular infection, debride the canal system, and obturate the area to prevent reinfection. It is indicated in situations of irreversible pulpitis, pulp necrosis, and apical periodontitis. (4)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eClinical diagnosis begins with a comprehensive history, pulp vitality testing (thermal and electric), and radiographic assessment, which is frequently augmented by cone-beam computed tomography (CBCT) in situations of complicated morphology or non-specific symptoms. Following proper aesthetic and rubber dam isolation to guarantee asepsis, an endodontic access cavity is made utilizing straight-line access principles to preserve peri-cervical dentin. Canals are first negotiated using stainless steel K-files and then shaped with NiTi rotary or reciprocating instruments, which offer greater flexibility and resilience to cycle fatigue, especially in curved canals. Irrigation procedures include profuse use of sodium hypochlorite (NaOCl) for organic tissue disintegration, 17% EDTA for smear layer removal, and supplementary use of passive ultrasonic irrigation (PUI), apical negative pressure systems (e.g., EndoVac), or sonic activation to improve debridement efficacy. (5-6)\u003c/p\u003e\n\u003cp\u003eGutta-percha and a sealer—typically resin-based or, more recently, bio ceramic sealers due to their superior biocompatibility and sealing qualities—are used for obturation after the canals have been completely cleaned and dried. Based on the anatomy of the canal and the preferences of the physician, obturation procedures like cold lateral compaction, warm vertical compaction, or the single-cone technique (particularly with bio ceramic sealers) are chosen. To avoid coronal microleakage and structural failure, it is advised to immediately put a permanent restoration or core build-up, frequently followed by full-coverage crowns in posterior teeth, as a properly executed coronal seal is crucial. (7)\u003c/p\u003e\n\u003cp\u003eBecause of the action of clastic cells, a pathologic process known as root resorption causes the loss of dental hard tissue, such as cementum and dentin. It is generally divided into two categories: pathogenic and physiological (as in primary teeth). It is usually pathogenic in permanent teeth and, if not identified and treated quickly, can cause tooth mobility, discomfort, or loss. (8)\u003c/p\u003e\n\u003cp\u003eRoot resorption is divided into two types: exterior and internal, with different etiologies and pathological processes. External root resorption originates on the root's external surface and has numerous kinds. Surface resorption is a modest, self-limiting response to small injury that normally heals on its own. Trauma, necrotic pulp, or infection can all cause inflammatory resorption, which is characterized by fast loss of root structure and periapical disease. Invasive cervical resorption (ICR), another name for cervical resorption, begins beneath the epithelial attachment and advances rapidly into the dentin. In its early stages, it frequently shows no symptoms and might be misdiagnosed in the absence of radiographic imaging. When the root surface is resorbed and replaced by bone, usually following traumatic dental traumas like avulsion, replacement resorption, also known as ankylosis, takes place. This causes the tooth to fuse to the surrounding alveolar bone and ultimately results in tooth loss in developing patients. Internal root resorption, on the other hand, typically occurs after persistent inflammation of a critical pulp and starts inside the pulp chamber or root canal. On radiographs, it appears as a symmetrical radiolucent expansion of the canal space and is usually asymptomatic. Dental trauma, which can harm the periodontal ligament and expose the root surface to resorptive cells, is one of the main reasons. This includes luxation, avulsion, and root fractures. Inflammatory mediators released by pulpal and periapical infections, especially those involving necrotic pulp, promote external inflammatory resorption. Orthodontic treatment can cause pressure-induced resorption because it compresses the periodontal ligament and causes sterile inflammation, particularly when severe or prolonged forces are applied. Internal bleaching with high hydrogen peroxide concentrations and periodontal or periapical procedures can harm the root surface and cause external or cervical resorption. Prolonged physical compression from tumors, cysts, or impacted teeth can also cause root resorption. Individuals may also be predisposed to resorptive activity by systemic disorders such as hyperparathyroidism, Paget's disease, hypophosphatasia, and specific hereditary abnormalities. Idiopathic root resorption, which can be localized or generalized and often familial, is the term used to describe the ailment in certain cases where the etiology is still unknown. Accurate diagnosis and successful treatment to preserve the damaged tooth depend on knowing the underlying cause. (8-9-10)\u003c/p\u003e\n\u003cp\u003eExternal root resorption and root canal treatment are inextricably linked, especially when pulpal necrosis or periapical inflammation is the underlying cause of the resorption process. When the dental pulp becomes necrotic due to trauma, deep caries, or other insults, inflammatory mediators are released into the surrounding periodontal ligament via the apical foramen or lateral canals, activating clastic cells and initiating external inflammatory root resorption. In such circumstances, root canal therapy plays an important role in slowing the course of resorption by removing the cause of infection and inflammation within the pulp area. The canal system can be properly debrided, disinfected (typically with calcium hydroxide as an intracanal medication), and obturated to help get rid of bacterial by-products and provide an environment that prevents more resorption. To stop the resorption process, protect the tooth structure, and avoid consequences like perforation or tooth loss, early diagnosis and prompt endodontic intervention are crucial. As a result, root canal therapy is an important tactic for managing and reducing external inflammatory root resorption in addition to treating pulpal pathology. (11-12)\u003c/p\u003e\n\u003cp\u003eWhen a tooth with external root resorption undergoes root canal therapy, a number of issues may occur that complicate the process and raise concerns about the outcome. Particularly in cervical or lateral regions where the dentin is thinner, the resorptive lesions can alter the normal canal morphology, making canal localization and negotiation difficult. They can also raise the chance of an unintentional perforation. The uneven resorption flaws can retain germs and debris, potentially resulting in a prolonged infection, making thorough debridement and disinfection challenging. Overuse of irrigants or medications through the weakened root surface into the periodontal tissues increases the risk of inflammation or tissue damage. In irregular or resorbed areas, obturation becomes more difficult because a full and hermetic seal cannot be achieved, increasing the likelihood of failure and microleakage. Furthermore, the likelihood of vertical root fracture during or after therapy is increased by the structural weakening of the root. Particularly if there is substantial loss of cervical or root structure or accompanying periodontal involvement, these teeth frequently have an uncertain prognosis and provide additional restorative challenges, occasionally requiring surgical intervention or even extraction. (13-14-15)\u003c/p\u003e\n\u003cp\u003eDetermining the optimum working length (WL) is an important step in root canal therapy. In cases of external root resorption, however, finding an exact working length becomes substantially more difficult due to structural changes in the root anatomy.\u003cbr\u003e\u0026nbsp;External root resorption, particularly in the apical or lateral regions, causes loss of root surface continuity, uneven canal outlines, and, in certain cases, the formation of resorption chambers that interface with the periodontal ligament space. These changes may interfere with both radiographic and computerized methods of determining WL. (16)\u003c/p\u003e\n\u003cp\u003eEven though they are often employed, traditional periapical radiographs do not fully depict the degree of apical resorption. The canal length may be overestimated or underestimated due to radiographic resorption flaws that are overlaid or poorly delineated. It can be challenging to spot the apical constriction or apical foramen, which are crucial features for a precise WL assessment, when the apex appears blunted or uneven. (17)\u003c/p\u003e\n\u003cp\u003eSince they can identify the location where the canal ends at the periodontal ligament, electronic apex locators are usually more accurate than radiographs in situations of apical resorption. EAL readings, however, could be erratic or unstable in situations involving open apices or holes connected to resorption. The EAL may provide erroneous readings if the resorption has produced several departure points or lateral communications, confusing these exit points with the apex. (18)\u003c/p\u003e\n\u003cp\u003eWhen resorption is substantial or unclear, CBCT imaging can be very helpful. In order to help clinicians, determine the precise extent, position, and shape of the resorption and to facilitate more precise WL determination and treatment planning, it offers a three-dimensional picture of the resorptive flaws. Additionally, CBCT can show if the canal is still contained within the tooth structure or whether it has communicated with the outside of the root surface, which would change the instrumentation strategy. (18)\u003c/p\u003e\n\u003cp\u003eTactile sensation during file placement and paper point tests can help determine WL in addition to imaging and technological approaches. A quick decrease of resistance upon placing a file to the tentative WL could indicate a perforation or penetration into a resorptive cavity. The degree of communication with the periodontal space can also be determined by inserting a dry paper tip and looking for blood or dampness, which indicates that the WL has to be adjusted. (18)\u003c/p\u003e\n\u003cp\u003eIn conclusion, external root resorption poses substantial complications in endodontic diagnosis and treatment, particularly in accurately establishing working length due to changed root morphology and probable communication with periodontal tissues. While traditional radiography and electronic apex locators are widely used, both have inherent limitations when used in teeth with resorptive abnormalities. The variation in accuracy across these methodologies emphasizes the need for additional research, particularly under controlled conditions that allow direct comparison. As a result, the purpose of this study is to assess the effectiveness and accuracy of clinical and radiographic approaches for determining working length in teeth with external root resorption using an in vitro approach, thereby offering clearer advice for clinical decision-making in complex endodontic cases. (19-20)\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003ch2\u003e\u003cstrong\u003e\u003cu\u003e2.1 Materials used in research:\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e13 single-rooted teeth, high-speed hand piece, straight fissure high-speed bur, round high-speed bur, endo Z bur, K-files #15 (Dentsply), standard ruler, CJ-Optic Flexion microscope, digital Calibre (Mitutoyo 550-331-20 digital Calibre, Japan), apex-s (rogin dental brand) electronic apex locator, electronic apex locator (Raypex 6), gypsum, wax, film holder, film sensor, digital radiograph (IOPA) (planmeca romexis), 3D imaging (CBCT) (NewTom).\u003c/p\u003e\n\u003ch2 id=\"_Toc200489433\"\u003e\u003cstrong\u003e\u003cu\u003e2.2 Exclusion and\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cu\u003eInclusion\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cu\u003eCriteria:\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cu\u003e\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u003cu\u003eInclusion criteria\u003c/u\u003e: All maxillary and mandibular intact teeth that have a straight and single root.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eExclusion criteria\u003cstrong\u003e:\u003c/strong\u003e\u003c/u\u003e multirooted teeth, curved roots, destroyed teeth, calcified canals \u0026nbsp;\u003c/p\u003e\n\u003ch2 id=\"_Toc200489434\"\u003e\u003cstrong\u003e\u003cu\u003e2.3 Sample preparation:\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cu\u003e\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eIn this in vitro study, 13 permanent mature single-rooted teeth were used (that had been extracted due to periodontal disease or as part of orthodontic treatment). Teeth was cleaned and disinfected with 5.25% sodium hypochlorite, then the teeth were numbered by order from 1 to 13. (3mm) from the apical third was measured by a standard ruler and was cut in 30 degrees using a high-speed straight fissure bur; this simulates external root resorption.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe crown of each tooth was flattened using a flat diamond bur (D and Z, Switzerland) with a high-speed handpiece to produce a flat stable reference point for measuring the WL. An ideal access cavity was prepared for each tooth by using a high-speed round bur and endo z for deroofing the walls to give us a straight-line access.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe crown of each tooth was flattened using a flat diamond bur (D and Z, Switzerland) with a high‑speed handpiece to produce a flat stable reference point for measuring the WL. An ideal access cavity was prepared for each tooth by using a high-speed round bur and endo z for deroofing the walls to give us a straight-line access.\u0026nbsp;\u003c/p\u003e\n\u003ch2 id=\"_Toc200489435\"\u003e\u003cstrong\u003e\u003cu\u003e2.4 Actual Working Length Determination:\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe actual working length of each tooth was measured after the rubber stopper was adjusted by placing K-file #15 (Dentsply) in the canal until the file tip could be seen visually at the apical foramen (resorption level) by using CJ-Optic Flexion microscope.\u003c/p\u003e\n\u003cp\u003eAfter removing the file from the canal, the distance from the base of the rubber stop (reference point) to the tip of the file was measured using a digital calliper with an accuracy of 0.1 mm (Mitutoyo, Tokyo, Japan) for the actual working length as the control group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTeeth then was placed in an alginate mold (mixed with a normal saline) until the cementoenamel junction.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The working length was measured using the first brand of electronic apex locator (APEX-S- s, rogin dental brand). The working length was measured by k-file #15 and the file was measured from the base of the rubber (reference point) to the tip of the file by the digital calibre.\u003c/p\u003e\n\u003cp\u003eThen different electronic apex locator was used which is (RAYPEX 6) brand, and working length was determined by K-file #15 and the file was measured from the base of the rubber (reference point) to the tip of the file by the digital calibre, then the readings was marked as electronic apex locator (1) and electronic apex locator (2).\u003c/p\u003e\n\u003cp\u003eThe teeth were then fixed with wax into a gypsum model to stimulate the bone. IOPA (Planmeca) was taken for each tooth using an XCP film holder in a parallel technique. The length was measured from the reference point of the tooth to the coronal border of the ERR using Planmeca Romexis software.\u003c/p\u003e\n\u003cp\u003eThe teeth were then scanned by a 3D imaging unit (NewTom) CBCT, and the working length was measured under Standard CBCT Settings:\u003cbr\u003e\u0026nbsp;- FOV: 10 x 10 cm\u003cbr\u003e\u0026nbsp;- Mode: Regular\u003cbr\u003e\u0026nbsp;- Kv: 90\u003cbr\u003e\u0026nbsp;- S: 9:60\u003c/p\u003e\n\u003cp\u003efrom the reference point of the tooth to the coronal border of the ERR. The analysis of data was performed using NewTom Software.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003e\u003cstrong\u003e\u003cu\u003e3.1 Results:\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cu\u003e\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u003cimg width=\"600\" height=\"358\" 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aRfYL2dI1e4aZ8E9c57U3RY9PfQLhroxmUs/nbz82c10FtaRWiMkChFYlj65NVZdC0+eZpXtxub7wHQn1pcorHPZdPDWlPLuAS87/AN3PFaWpTxS+JtMSOVHYc/Kc1sTWkE9qbeSJWixgKRwKgt9GsbWVZIoFDqchu9HKw5WZNglk/ijWDdeX5u/gOccYqfwqFEN/5Z/0cXB8v6e1EWgx3Gq3899ACssoaJ88kYrYt7eK0iWK3RVjXooojFoFFlDWdXFiFtoChvZxhFJ4A9al0azisLLyklWWV23ysGzzS3Wj2V5N51xCHk6BvQVLaafb2IYWybA3J96dtR21LNFFFWUFFFFABRRRQAVf0nref9cDVCr+k9bz/rgaliZnjpS0g6UtMfQKOn0oopgUNcge50W5jiyXK5FULKWDU9At0ivmtHhXD7WCkH0re9xWdPoGnXEzStbqrN97bxk1Mlclq5gPNJd+DbkXEzTYuvLDseSM+tXNbtorTw7AsCCOJnQSkdSO+a2jptoLL7KsCiAEHYBxn1qaSCOSEwyKHjIxhulLlFynP6/HZR2libHy/PEyCLyzzt71NbusPjG7MzKhaJSCxxnir9totjaTCaKBQ68DPb6VJe6XaX8ivcRBmToT/KjlY+VnP2sqT2fiFo23Ke4pjR6cPBO5PK80r8mD82+t250uKLTL2GxhVHnTG0cbvaq+m+HrOG2ga4tl85QNy/7VSosnlZpWO8afb+Z98RqTn6Vg6/Y281pLfLqLSGM71haQFCfTFdJj5dpwR/IelZ3/AAj2m+bv+zjrnaehNU4lNFnTZ3utOgmkTY7qMqO1WaQAKAFAAHQClqkUgooooAQ9DWjqP/Htaf7lZx6GtHUf+Pa0/wBykxGfRRRVDCiiikBzumypZ61qdncyeU87B43JxkY9aLZpLTxMtquoSXMTwM7BmDYNbF5ptpqCKt1Cr46E9RTLPSbLT3MlvAokI2ljycVHKRymV4ds4GOoTtEGm8xtrHtxUegpZSaTdteeX525vNMh5zzXQW9pFaK4hQKHO5veqs2hafcTmaS3Xcx+YD+L602htHNFmTwxaM5by0uPkLdlz/KtfVZ4pfEGjJG6u24n5Wz2rYks4JrU28kSmDGNmKrW+iWFtLG8cADxncrHqKXKxcrMqwWyfxZf/a/LLhRt3nH1qbwwNsuoLD/x7CY7MHgUqaAtzq13LfQAxuMo4PNbFtaw2kCxW8apGB0pxXcEmYl8b3+3xM2nyXNvAv7sKwHJ6mo/CFzLKl0jWzqpmdi5PGc9K6ToBg/jUNvaxWqusChNzFj7k0ctmPlsyXtxS0d/8aKsoKKKKAO68Nf8gSH8aKPDX/IEh/GiuR7nM9zdb7pqlV1vumqVSjJiUUUVQBRRRQAU5PvrTacn31oBbnn2p/8AITuP941Vq1qf/ITuP941V6mumOx2rYMZBHtUFrfQ3nm+Sx/dNtb0NJqE5ttOuJR1RCRWPYXaaP4TjuGTdI2Wx/eJNDYXOgPp29aKy7KTVt4e9WIwMu87eCnf8aqR6lquoQy3djHGlvHnCtyXA96OYOY36KwLnxFJ/ZNpeW0OXmfa0Z7GpIdS1C31aC1v0TbcjMbL/CfQ0cyFzI2gQc5IOO3pS4wcVy+mtqb+KL6MSqQApZSONue1WotT1O+1Oe1s0QRwP80jenpRzIOZG9UNzdRWkPmzsVjBxmsldR1HUridNMWNY4DtLPzvbuKq3+pHU/DUplTy5o5gjr7g0nIOa50iOHRWXJDDIPtTqjtf+PSH2jHH4VJT6FdC/rP/AB8x/wC4P5VQq/rP/HzH/uD+VUKEJBR278UUdjjrVDGyyJDG0kjqir1c0JIksSyIytG3Rl6GsbxGRdva6YGAF0+H5+6PWmeHZfs0F7p5YM1ox2D/AGexqObUls3v0orm4NW1i8spbu3ijWKAnIP/AC0x6VYuPESrptpNEFWa66bzgIe+afMg5kblFYVlrMz6l9glmgmkkQtHJEeAfcVEPEU/zWZh/wCJj5m3bjjb/eo5kPmR0JICkscYGcmkjlSZA8bKynuvSorrd/Z0u/BcRnI9fes/wsMaDF/vt/Oi4XNeisVtRv7+/uINMVFjt+GkfncfSmw+ISuk3M9zDi4tm2PGD95u1HMg5jcorLsZNXZ0e7SIxSLu2r1T0571U1DU9Q09ZLiSW2EaH/UZG8jNHMg5kbxIHBIHoPWlrltXnv5db0x7WQKkvKAjvjvWlealdpdQ6fbqpvGXdIxHCj1xRzIXMjXo+vSse01O6jvp7HUVXz44/MR16MPpUWj6jqeqSCRo0jtlYq3HLUcwc1zcJCAsxCqO5pkM8Vwm6Bw6gnDKeCaivrKO/h2Ss6p3CnBNZfhJFj0y4VBhEuHCj0ovZ2G3qbv1oooqhhV3Sf8Aj5k/65mqVXdJ/wCPmT/rmaTEym33z9aSlb75+tJQhoKKKO+P1phcjmuIrdA00qxqxwC3rUnU5H/6q5rXIF1vVfsW/EdrEZic/wAXpVmy1aT/AIRY3OAZrcbH5zkio5iVI3KK5x9X1aCxi1KaGP7K5GUHXB75qzqGtlbyK0tZIondA7SSnhR/Wm5Kw+ZWNqisOy1i5vYr23jMT3lsAyshysgptn4gl1Oe3gtI8S/8vORwhHUUKQcxuSSJChkkZVUdSaUEMAQcgjIYelZXijH9gXHX61es2CabAx4VYVJ/KnfUL6liiufTU9VvrZ72yjjW2UnardWxUsviBn0y0mtYc3F0/lohP3T3NLmFc26T1I6d6oWzaogkW7WN2xlGXjJ9Kz31i9sry3W6lgljlfYUQ/MlHMPmsb+RuxkZx09qWuZjOpv4vuEilTHkg4I425/nV2TUb6+v5bbS1RRBw7v3b0pc6Fzo2aKw4tdmOm3bTRBLu1O1l7N71Y0a51G8jFzeIiQOoKKOtNSuPmuXp722tMNcTLETwNzU+GaKeIPDIsiHupyKgubGxmkM97FG4Qcl+QBWV4Vi2R3ksQK2skp8pT/Si+oX1N+iiiqGFX9J63n/AFwNUKv6T1vP+uBqWJmeOlLSDpS0x9AooopgFFFFIBrOI1LsdqjqfShXUx71YFCM5zxj1zVTWRnRrvnH7pv5VhXsrnw5pFnGxQT7Q5B5x35pOViXKx0CapYvN5SXcO/p94c1NNNHboHnkWNfVjWZqOgaf/ZMscdtHG8aEpIo+bI6HNYt9dfavDOmy3ZDqLhVct3A9alyE5M6uC7t7niCeKQjsrZNOe5ijlSJ5FWV/uqx5P0rmwtrN4ltW0WLYiofPZBhcVW1NTqF1d6pG/Fgw8nnqO9HMHMdh3IFLUNpcrd2UM6nIdQfx71NVp3KTCiiimMKKKKQCHoa0dR/49rT/crOPQ1o6j/x7Wn+5SYjPoooqhhRRRQAUe46j9aKqapcNaaXcTp96NMj2NJgOm1Gzt5fKluo1YnhWYZH1qSS9toFV5Z41U9GJ+99Kx9F0azk0mOW6gWeaYF5JJBknNU9fjtrK/0pJIme2Rs+WF3H6YqbktnSw3ENwu6CZJAO6tnH1plxfWtoQLqeOMnszc1zmkTwP4hu5bOI2sIgJELDbvYd8VPoFjBqMFxqF9CtxLNIQPM5Cr7CkpApG2+o2kaqWuoQG6NvHNC6lZSSBI7qFyenzAmq8mjWEVlKgtY3VVZgSM7eKz/C1haHTBMbaLzRIcNjkU76hfU6DpnPA7Yo570evoe1FUUwooopgFFFFHQDuvDX/IEh/Gijw1/yBIfxorke5zPc3W+6apVdb7pqlUoyYlFFFUAUUUUAFOT7602nJ99aAW559qf/ACE7j/eNVatan/yE7j/eNVe9dMdjtWxX1GD7VptxCP44zWFa276t4OjiiIFxESAD0yD0NdJk4Bx7EVDbWUNo0nkKV8w7mHbNJq4mijZXmoXOyGexWGMJtZ92e2OKo2o1PSbWXT4rJZl5EMm7AwfWujzn3HWinyhynOy6LPBpVjbph5El3y+gq7qNpNNrmmTxr+7hJ3n04rVoo5UHKjESG70/xJPcRQedBcqq7s4KnvU2kWk1rqV9JKuEkbKn1rVoOccHmjlDlOftk1DQ7m6WC0FzDM5dW3Y5NRnRrmPQZUKg3E83mOvXbz0rpM9xkZ4oo5UPlGQKVt4lb7yoAafRRT6D6F/Wf+PmP/cH8qoVf1n/AI+Y/wDcH8qoUkJBQMd/xoopsZgvpD6nrk9zfhkijXy4djYJ96jOjPpes+fYhzbzRFJixyRxXRUhAZSrfcIwcUuUlxOR0i61NdJnt7e0WVJWZUk3YxmrdzoEsWmWASNJ5rM5eJuj561u2dnDYQmK3BCk55qelyBymRYHE5kTR4YCikh14OfQVmvpF/539sj/AI//ADP9X28v0rqc0UcqDlIZt09k/wAuHePp6H0rE0aXUtOtUtX08MAx+cPxg10NGafKPlOfijvtGv7poLQXEFwd6kNgg+lRpoV1LpF2ZdqXlzJ5gQcgEdBXSUUuUXKZVjeahKY4JbEQqi4Z92e2KwpdLv2sbm2lsVmumbP2hm6DPauyzRQ43BxOf1Cyu4zpd1BD5rWpG9M+1SXkV9HqkOrW0Admj8uWItyB9a3KKfKg5UYdra3V5qM+o3UPkfujHFHuyfqataDay2mmmKdcMXJ61pUUco+Ur3081vCXt4POfpjOKyPDi31p5lvdWgRJJGl8zdnGe1b9FDV3cLBRRRVDCruk/wDHzJ/1zNUqu6T/AMfMn/XM0mJlNvvn60lK33z9aShDQdeKQkhd38SjIFLRQBz1h4fW5kubrUTKs00hICPj5aqzabNpNvqkCA/ZJE3oxOea6uorm3jurdoJgTG/BApcpPKcyn9qalotrYG0VEYKfO3cbR7Va1DSXg1SK9is47yJYxG8b8Yx0IrehiW3gjgj4SMbQDT+h4pcgcpj27zRWVxJbaXFbSkYj2cFj71SsdHutHvILmEeYbg5u1z0J9K6WijlDlM/XrSW90iaCAZkboM9ar2VzfTwR2lzYCKPywhffnoK2KKdh2Obtv7U0yxfTorJZcMfLk3YBBpZtDubXTrA2wElxaSeYVzgNnqK6Oilyi5THkm1PU7C6jFsLVmTCNv5zWQNMup0slGniJoZAZZi2WauvozRyhymHPFd2PiU3tvbedDLEIz833TTPLvtH1W5nt7UXMF0d/3sFGrfoo5UHKjnU0m7OmahLMgF1dnIQHO0elbWnxtDp1skgO5UC49KsUU0rDSsYHiGPUbmeO3t4N9n1kw2C3tWhpk00kZjlshapGAEAbOav0UW1uFtQoooqhhV/Set5/1wNUKv6T1vP+uBqWJmeOlLSDpS0x9AooopgFFFFAFXU4nn0y5ijGWeMgfWsy40ie58PWUSYS8tlVl+o7Vu0VLjcVjAuLzWb+1azFgkMko2yS7uAO5FGo6Mw0uwtIEEqRTKXB7jvW/mijlFyla6j+zWM/2KFFkCnYiDGTWRY+FbYWCi6MvmyZaTD8ZPaugoo5Q5TJ8O21xY2clpcDCROREfVa1qKKdigooopgFFFFIBD0NaOo/8e1p/uVnHoa0dR/49rT/cpMRn0UUVQwooooAKiurdLu1lgfo64J9KlopMDnbKbV9Kt1smsVuFTIjk34yPen6jBqDXOnXotw80LbnQNwK380VPKTymDHaXup63HfXduttHEpGA2S+ajtk1LQZJoYbUXVq7lom3YK+1dFRRyhylO2e7nsJftkSxSuCFRTkYqDw/ay2WmGKdQr7yfwrTop2HYKKKKoYUUUUAFFFFHQDuvDX/ACBIfxoo8Nf8gSH8aK5Hucz3N1vumqVXW+6apVKMmJRRRVAFFFFABTk++tNpyffWgFuefan/AMhO4/3jVWrWp/8AITuP941Vrpjsdq2CoZru2t2UXE6Rk9Axxmph1rkbqVG1zUkntJLv+FNvOzj9KGwbOoW7t3XekyMmcAg8ZpY7mCVGaOaNlT7xB+7XL3unPZ+GbK1mIR2ly20+p9as61Zw2dvYW0AMMM8oExB6jHelzE8xvQXdvdEi3njkYdQpp6yxu5VHVivUDtWDqtpDp2p6XLYqI5Wk2kKfvLipNHIGt6qGIxncATjAo5g5jZE8RVm8xdqnDHPANNW8tmm8lZ42l/ug1y0cgfwpqhDkL9qbDD0p+o2Fpa+G7S6tsrcbk2uGyWJPNHMHMbNzfTWmvQQyMPs9ypCjHQitOue8Qsxl0oniXzB/9euib7xpopO4lFFFPoN7F/Wf+PmP/cH8qoVf1n/j5j/3B/KqFJCQUUUVQwooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKu6T/AMfMn/XM1Sq7pP8Ax8yf9czSYmU2++frSUrffP1pKENBRRRQAUUUUwEpaKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKv6T1vP8ArgaoVf0nref9cDUsTM8dKWkHSlpj6BRRRTAKKKKACiiigAooooAKKKKACiiigAooooAKKKKQCHoa0dR/49rT/crOPQ1o6j/x7Wn+5SYjPoooqhhRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUdAO68Nf8gSH8aKPDX/IEh/GiuR7nM9zdb7pqlV1vumqVSjJiUUUVQBRRRQAU5PvrTacn31oBbnn2p/8AITuP941Vq1qf/ITuP941V9a6Y7Hatg5z79q5S4sgmq3sl9YXVz5rZjaAkYGO9dXSgkDG40NXBq5haXpDy6YItRDELJvjVjyo9DWpe2UGoW3kXKlkPT2qx1HPX+dHXqeKfKCjYzrLQ7WzuBMm95VGFLnO2ku9CtLy7FywdZCMNtbGRWl15zR7dBRyoLGLf6RHbaDcWlhEWEjb9nuetJYeG7OKO3klDkoAdhYkK30rb/mOlH159qXKg5UZN5aTXviG2aSPFvbKTn+8TWtQOg5oppWGlYKKKKOgPYv6x/x8x/7g/lVCr+sj/SY/9wfyqhQhIKKKKYwooooAKKKKACiiigAooooAKKKKBhRRRSFcKKKKACiiigAooooAKKKKACruk/8AHzJ/1zNUqu6Sf9Jk/wCuZoYmU2++frSUrfeP1NJQhoKKKKYBRRRQAUUUUAFFFFABRRRQAUUUUAFFFHagAooooAKKKKQBRRRQAUUUUAFX9K/5fP8ArgaoVe0o4N5/1wNJiZQHSlpB0paY+gUUUUwCiiigAooooAKKOtFABRRRQFwooopAFFFFABRRRQAh6GtHUv8Aj2tP9ys49K0dS/49rX/cpMTM+ijsKKooKKKKBBRRRQAUUUUgCiiigAooooAKKKKACiiigAoopKOgHd+Gv+QJD+NFHhk/8SSH8aK5Xucz3N1vumqVXW+6apVKMmJRRRVAFFFFABTk++tNpyffWgFuefan/wAhO4/3jVWrWp/8hO4/3jVWumOx2rYKKKKoYUUUUgCiiimAUUUUAFFFFABQaKDS6A9jrX8PQ6jHFM8zqWQcCmf8Ifbf8/ElbNl/x4Qf7gqeudydzlc2mc//AMIhb/8APxJR/wAIhb/8/Elb9FHOxe0kYH/CIW//AD8SUf8ACIW//PxJW/RRzsPaSMD/AIRC3/5+JKP+EQt/+fiSt+ijnYe0kYH/AAiFv/z8SUf8Ihb/APPxJW/RRzyD2kjA/wCEQt/+fiSj/hELf/n4krfoo52HtJGB/wAIhb/8/ElH/CIW/wDz8SVv0Uc7D2kjnZvCtrbwSTPcS7Y1yax9mknOJbn8AK7LU/8AkE3f/XOvPe1XTbZtTk2rmh5ek/8APS5/Sjy9J/56XP5CqFFaWZpYv+XpP/PS5/IUeXpP/PS5/IVQooswsX/L0n/npc/kKPL0n/npc/kKoUUWYWL/AJek/wDPS5/IUeXpP/PS5/IVQooswsX/AC9J/wCelz+Qq9pFvp0t4Y4JZ97KRyKwq1PDf/IYT6UpXsTK6Rrnwhbls/aJdxNJ/wAIhb/8/EldAe4pKx52c/tHcwP+EQt/+fiSj/hELf8A5+JK36KOeQe0kYH/AAiFv/z8SUf8Ihb/APPxJW/RRzsPaSMD/hELf/n4ko/4RC3/AOfiSt+ijnkHtJGB/wAIhb/8/ElH/CIW/wDz8SVv0Uc8g9pIwP8AhELf/n4ko/4RC3/5+JK36KOdh7SRgf8ACIW//PxJR/wiFv8A8/Elb9FHOw9pIwP+EQt/+fiSq994dstPt/OlnlK5xgV09ZHij/kD/wDA6ak2xxm27HOCPSjk+Zc/kKPL0n/npc1n0tbHTboX/L0n/npc/kKPL0n/AJ6XP5CqFFFgsX/L0n/npc/kKPL0n/npc/kKoUUWYWL/AJek/wDPS5/IUeXpP/PS5/IVQooswsX/AC9K7SXP4AVoaNbWE88sVvLOS8ZU7gKwOnNbPhT/AJC7f9czUyvYmd7Gj/wiFv8A8/ElH/CIW/8Az8SVv0Vlzs5/aSMD/hELf/n4ko/4RC3/AOfiSt+ijnYe0kYH/CIW/wDz8SUf8Ihb/wDPxJW/RRzsPaSMD/hELf8A5+JKP+EQt/8An4krfoo55B7SRgDwhb9rmT8Ky7yx0yyunhkluCw7gCu0HJrhvEH/ACGZvwqoNtmlOTk7DfL0n/npc/pR5ek/89Ln9KoUVtY2sX/L0n/npc/kKPL0n/npc/pVCilZhYv+XpP/AD0ufyFHl6T/AM9Ln9KoUUWYWL/l6T/z0ufyFHl6T/z0ufyFUKKLAXzHpOP9Zc/kK3V0K21Kzt5EmkCgYGa5I9K73Rf+QPAPaondGdVtIzf+EQtv+fiSj/hELf8A5+JK36Kz52Y+0kYH/CIW/wDz8SUf8Ihb/wDPxJW/RRzsPaSMD/hELf8A5+JKP+EQt/8An4krfoo55B7SRgf8Ihb/APPxJS/8Ihb55uJevWt6lHUDtmjnYe0Zxl9p+m2Fy0Es05Yegqv5ek/89Lj8hU3iX/kMyVlVtG7R0x1Rf8vSf+elz+Qo8vSf+elz+QqhRTsOxf8AL0n/AJ6XP5Cjy9J/56XP5CqFFFmFi/5ek/8APS5/IUeXpP8Az0ufyFUKKLMLF/y9J/56XH5Cjy9J/wCelx+QqhSdqLBY9A0BYRpMQgZynOC3Wio/DX/IEh/GiuZ7nO9zcb7pqlV1vumqVSjJiUUUVQBRRRQAU5PvrTacn31oBbnn2p/8hO4/3jVWrWp/8hO4/wB41Vrpjsdq2CiiiqGFFFFABRRRQAUUUUAFFFFABRRRS6A9j0Oy/wCPCD/cFT1BZf8AHhB/uCp65XucUt2JRRRQIKKKKACiiigAooooAKKKKACiiijqBX1P/kE3f/XOvPu1eg6n/wAgm7/651592rWjszoo/CFFFFbGwUUUUAFFFFABRRRQAVqeG/8AkMp9Ky61PDf/ACGU+lTLYmex2x60lKetJXN1OPqFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFZHij/kED/frXrI8Uf8ggf79OO5UPiRxlLSUtdJ29QooopiCiiigAooooAO1bPhT/AJC7f9czWN2rZ8Kf8hdv+uZqJ7ET2OxpKWkrmOTqFFFFMAooooAKKKKAFH3q4bX/APkMzfhXcj71cNr/APyGZvwq6e5rR+IzqKKK6GdKCiiigAooooAKKKKAEPSu90X/AJBEH0rgj0rvdF/5BEH0rKoZVti7RRRWJzBRRRQAUUUUAFKv3h9aSlX7w+tAjivEn/IZkrKrV8Sf8hmSsqumGx2x+FBRRRTKCiiimAUUUUAFFFFHQDuvDX/IEh/Gijw1/wAgSH8aK5Hucz3N1vumqVXW+6apVKMmJRRRVAFFFFABTk++tNpyffWgFuefan/yE7j/AHjVWrWp/wDITuP941Vrpjsdq2CiiiqGFFFFABRRRQAUUUUAFFFFABRRRS6A9j0Oy/48IP8AcFT1BZf8eEH+4Knrle5xS3YlFFFAgooooAWmefCZTEJozIBnYGG78qJZlt4JJpPuRoXb6DmvLbdbix1O08ZybxHc3TRNn7vlNwlID1SilOOoOQeQaSmAUUUUAFFFFHUCvqf/ACCbv/rnXnvavQtT/wCQTd/9c6897VrR2Z0UfhFJAAJIA7k01HWRdyMrKehU5rL8RTMunraxHEt2wjXHX3qt4djOl3d3pTlsRnzULddtac2ppfU36a0saMFeRVJ6KTgmmpcQyPsSaNm9A2TXKatBLql7d38O4ixKqgHTIPzUOSG5WOtLoHCFwHPRSeTQzqhCuyqzfdy3Wue1icSRaXrEROFYBuezcVU8TvJcaujwH5bDZIcdwetLnJ5zrGdUGXdVHTJOMn0oDKWZAwLDqM8j61halINV1bTIF+6R57Y9ulSWGT4t1Qtn7qc59qOYfMbdanhv/kMJ9Ky61PDf/IYT6U5bBLY7Y9aSlPWkrm6nH1CiiigAooo+lAC9OD1/nVZ9RsYpTFJfWqS9NjSgEVaj++MDjNePxXHhyGfxINYs3nu/tD+W6RMxHpgjpSA9eDBlBUgg9x0ornfARmPhG2M83mnJK/NkqvYE+1dFQAUUUUwCiiigArI8Uf8AIIH+9WvWR4o/5BA/36cdyofEjjMgDJIAA6mo0ureRgqTwsx7BxmoNW/5BFz/ANczXGmfTToVlHaQtHqGVDS7SoBzzk963crHU5WZ33ems6xqWkcIo6selM+0QxrGslxFu2jOWAzWT4hRtQFrpULf8fLEsy+gpuWgc2hsmRAm8uoT+9nigsoXcWULjOc8VzmnxG50G/0qYNvtyyrzzjtUM14934Qt7dDid3FuQPQcGlzaBzHUh1KhlYFT3B4pPNjwD5qYbhTu6muYtL1rbwjc2znM8bGAf0pb62FnaaJEOCJFJ9z3oUg5jqTWz4U/5C7f9czWO3BNbHhT/kLt/wBczRLYUtjsaSlpK5jk6hS+lJWH401SXRvCl3d25xPwiH0LHGaANR9SsY5vKe9tllzjy2lAb8qsenv075rldL8C6OdIgN5bC4u5FDyXLnMhY88Gunt4RbQRwISUjG1S3WgB/Tg9aKAAOlFMBR96uG1/nWZvwruR96uG1/8A5DUv4VpS+I1o/EZrOiqWZwi/3m4ApkVxDOcRSxuf9lwaw9RX+1PEcOnSuwtokLugPDHtWjFpFlZXH2m3iEGBg7TgY961vqb3L3akMkYfYZF3nkLnnH0pEuYZCTHNG20ZIVs4rjpfN+1HxEu4oLnbgdBH0/nScrA5WOz3oX2B1LjnbnnH0pN6BghdRIeQuecVh3zC28T2F6nEd0vlMw6etZl9PIfE66kDuhtpfIfHcUc4nI68uoZVLAM3RSeTSq6vnaytjg4OcVikfb/GKAH5LSIPx0BPak8N48/VOo/0puCaOYalc2z0Nd7ov/IIg+lcEehrvdF/5BEH0qamxFbYu0UUVicwd6rHUrBZPLbULRXzjaZVz9MVbXIbjqQa858E+GdI1jT9QlvrJJJjdSDzj94c0gPRAQ4DKQVPIPrRXH+DJbiw1rV9AnuHuIrNwYHc5IUjOK7D/OaYBSj7w+tFA6j60COK8Sf8hmSsZ7iGIgSzRxk/32ArZ8Sf8hmTB5rib61t7vxhGlzCJI/IHyvzzXQnZI7E7RRvxyJKuY5EceqnIp34ZrnLm3TQNas2tWKW9yxWSI8qPcVvrPDJJsSaMyH+ENk07j5hzSIjBWkRWPQE43fShnRWCswDt0Unk1yesQyave3d3Du2acA0eOhYfeq1rE/2i00rV0PzIyhseh60uYOY6JpEQgM6qT0BOM/ShnWMAyMF+pxmuU8TyPd6lDJATssF81se/Iq9qcv9qX2k26nhwLhgPalzBzG6HUuUDqWAyQDzS/w5rEsh/wAVhqBzwFGB+FbnUZqk7jTud14a/wCQJD+NFHhr/kCQ/jRXO9zne5ut901Sq6xG01Uwh/j/AEqEZMZRT8J/fP5UbU/v/pTAZRT9qf3/ANKNqf3/ANKAGU5PvrS7U/vn8qVAm5fmP5UB1PPNT/5Cdx/vGqta+oW2ntqE5e/ZW3HI8vpVf7Lpv/QRf/v1XTFqx2JqxQoq/wDZdN/6CL/9+6T7Npv/AEEX/wC/VPmQ7oo0VfNrpo/5iL59PKo+y6b/ANBBx/2zo5kF0UKKv/ZdN/6CD/8Afqj7Lpv/AEEX/wC/VHMguihRV/7Lpv8A0EXz/wBc6T7LpuM/2i+P+uVHMguijRV77NpuAf7Rf/v1S/ZdN/6CL/8AfqjmQXRQoq/9l03/AKCL/wDfqg2um4/5CLe37ujmVgurHaWX/HhB/uCp6ZaLGLKELISNowcdalwn98/lXM3qcctxlFP2p/f/AEo2p/fP5UhDKKfhD0c/lRtTg7+D7UAc/wCMxeS+HZbbTo2ee4YR8fwqThj+VYd78M7QeHXtYdR1F3ii3RxNP+73jkcfWu8ATP3z+VG1M/f5HtQBkeGZLuTw7aDUIilzGgSTPcitT+tP2qeN5JHoKMJnG88+1ADKKfhP75/KjCf3z+VADKKftT+/+lG1P7/6UAVNT/5BN3/1zrz6vRNQSM6bcB5CqlMFsdK4n7LpvI/tF+P+mVa0nZG9F+6cpf6bJq+uoJmkhtoE+V0ODv8AaoZtGfTdXtLu0e4nViY5hK247a7L7LpvP/Ewbn/plR9l03H/ACEZP+/dXpc0srnPy6db2MU1xaW4+0BTtx6ms3TvC8b6eDc3V3FNOC0qrJhcmuy+y6b/ANBF+P8AplQbXTcf8hFz6fus0OzB2ZxtlptwdAvNNnQ4iYmEnuB0o0LTriXR7tr9NtxcoYjn0HSuy+y6aT/yEH/GOj7Lpuc/2jISeD+6osgsjjfDFldRXM818hBjURRA+g70STXOm+Ir64WzeaOVV2lfauy+y6ceP7Rfj/plR9m03nGoyY/650KwKxlWk7XNskrR+UW6qa2vDf8AyGU+lRfZdN/6CL+37utHQrexTVFaG9aR8fd2YpyasEnodUetJTyqZ+/z9KNqf3/0rmOTqMop+1P7/wClG1P7/wClADKKftQ/x/pRtQjO8/lQAiEbwTxzk+9ed6Xc6h4f1PWI5NDe8W5uGeMjgEHsa9Ewg/j6+1O+Ufxn8BQBy3gbRbvRtKuftqiJ7qdphApyIgTwM10tPwg/i69Rijan9/8AIUAMop+1P7/6UYTI+fr04oAZRT9qf3/0o2p/f/SgBlZHij/kED/fra2p/f8A0rM8QxQSaaFmnMa7vvBc1UXqVD4jzzUo3m024jjGXZCAK5xDeXHh+PS10wmTbtMjnAHPWu8FrppGRqL4/wCuVBtdNPXUX/791s7M6nZs56DRLVre3S6QSyxIF39+KoDR31PW7i4umngiiUJD5TbTXX/ZdNzg6i/PpFS/ZdN/6CL4HX93T0FocjaaXJo/iNHgaWW2uE/eNIdxBHrVWz0m7j8S7GX/AEKNmlDdiTXcC200f8xF/f8AdUfZdNJ51F/X/V0rILI4e80q6k8SMkSYspXWZj6FaveJYZmNnPbwmVYZQxUdcV1X2bTcc6i/P/TKgWmm9f7Rbjr+6o0CyMKw1KS+dxJaPbgcjca6fwp/yF2/65mqpttOI/5CLn/tlWp4dgso9SLQXjSsUPylMUSegpbHT0lP2p/f/SjCf3/0rnOUZWZ4l0ca/wCHrrTy4QyAFXxnDDkfrWttT+/9eKNqf3zQBxOn+I9esLOHTrvQZJb2ICMOr/K/+1ntXX25la3jNygjlK5dQc4P1qwQoB+c89eKQhFw2/ge1ADPrRT9q92P1xRhM/f/AEoAaPvVw2v/APIZm/Cu7Cpnh/0rkNat7F9UlMt80bnHyhM1pTa5jWjucPqlpdW2rRapYxiUqpSWMnqPWp7W/uNSkaOSwaO2K4dmOT9MV0f2XTv+gi3t+6o+zad1/tFge2I610ub6HM6hp6WOm3B02AC4lXaMdqqjwjbnTfJN1dglMlN/wAu7r0+tdh9l0wH/kIv/wB+6Ps2m9P7Rf8A790nZg7M4qa0u7rwoiMhF7aHKD1qSHSppvC0scq4up8SEejCuxNrpxP/ACEH4/6ZUfZdNzn+0X5/6ZUaCsjlvC9tcRW01xfLtuJpM8/3fSqdndXWk3d+rWMkiyzl1YehrtTa6aTj+0Wz1/1VH2bTe2oyY9PLoVgVjNjcyQq7LtLDO30rv9F/5A8H0rkTa6bz/wATF/8Av1XZaSkSaZCscpdMcNjrU1HoRWd0WaKeAn94/lRtT+/+lZHOIvX8Oted+HL3V/Dsd7ZjRJbiR7h3Rg20HJ4r0XCZ++fTgUvyH/locUgOZ8J6Jd2M19qWrbRfX8gd1XnywOgrou3PWn4XP3ufpQFTH3z9SKAGUo6j607CED5zz7UBUz9/nPpRcDh/Ep/4nMlcXqZubXxLFeRWrTxeVt4PQ16BrsFk+qO0t60b912ZrOFrpoGBqL/9+q6E00jrVuVHJpa3usanBd3tv5Fvb52R5yWJ71dfT7WzEt1bQAXCqShHUmt/7LppI/4mLhj/ANM6Ps2mdf7Qf/v1T0HojjdO8MpLZGS7nuopZyWlRHwOfaksNNnXQ7/TJkO2MsYGzyc9K7P7NpuRnUZM9v3XWj7LpuedRfOf+eVKyFZHHeH9OuZNOuzqCESToIufQcU3wzp93Hczy3qFfJPlxH/Zrsza6aST/aT/APfug2umk/8AIRk/CKjQNDjZpLnT/El3cpaPNHKowVrcs7hru0WZ4jET1Qnmtb7Lpw/5iL5/650htdNPXUW/79U00NWOs8Nf8gSH8aKl0BYE0mIQymROcNtxmiud7mD3Nh+nFctqHjHSdO1SHT5ZmkuZn2ARjIU+jHsa6hjwa8+8c2dvb3miyQwIjzXpZ2C8sfc1KMjtRx09OM0mPwoz90c5AGaPpTAKKKKYBnFOQ/MtNpyffWgOp59qf/ITn/3jVWrOp/8AITuP981WrpitDtS0CkZgilmBIAzgUtA9c8Dj8abAw38SNAyvcWcsdszbRKw5H4Vf1HVIdNgDujSMy7gq8k1n6zK2sXCaTa/MAQ1w46IB2+tal9Gn9nzHaCViIB7jiovcm4afdi/sIboZRZRkD09qW9uvsVsZfKeU5wFQc1U8Nc+HbPudvH51pMwjBd2wAPmNNbDRlWWuefqC2d3bNbyOMxn1ptxrN3byyKNOZ40J+fPUVFbF9Z1xL5RttrXKwk/xnv8AhU/iS+e107yISfPuW8tAPfrSWwlsT6Pqf9rWJuRGY/mKY+lX6r2FothYxW6/wqM+5qxVrYpbBzSHsD69aWg9KNLB0PQ7P/jxg5/hFTd6hsv+PCD/AHRU9cr3OOW4lL3H60lHbnj0NIRhaz4iuNNu/s1npc944TeSBhcemfWptF8S2etaTJfoGhWFis6MOUYdqm1/XYtC05ppPmmcbYYV5aRj0wKoeDtDl0zSJTqCqbm+mNzMmMhSe1ABoXjG28Qa1d2Fvbyx/Z4w++RcFgT2FdD2PIA7muQ0kBfilqyoMAWUeAB05rqL0H+zrkpwwibB98UAc1c+Ogk90bLTZ7qytCVnuF7EdcetaF14nRdLtLzTrWW9N2Mxqg4H1PasvwOVPgO6LFcF5fM57980/wAC3sOneCHubuXyreKZyGPp6CgC9oPipNYvriwuLaS0vrcAtEw6g9we9b341ynhe2uNV1y98S3cZiS4AjtUbg7B3P1rq6ACj8aKKYitqX/IKu/+udefex4+leg6n/yCbv8A6515/wBq1po6aC90KB1GeB6jtR2/rVC61OW2uliS0eUEj5lrVmpHfaz9muxaW1u1xcbdzBTwo96m0zU4tTgZolKMjbXRuCprP0I7vEOpn7rkjB74pNE517VCvCE/mai4rmlqF8bKNPLgkndzgKv9TUGnawt9cS20sTQXMYBMZ7j1FaE08drA80zhI0GSSax9Hjlv9TuNYnQosihIlPXaO9NsTeo2PxFNcO4g09njRym7PpW2rF4kZhtYj7tc+1hqeh2lxPZ3ayQqzTNCy44781tWF2L+xhuQu3zFBI9KExplitTw3/yGE9cVl1qeG/8AkMJ9KJbBPY7Y/eIH5mk/GlPWkrm6nH1CiiigDM1zWH0iKEw2ct3NM21EjGQPc+lVNB8Vx6ve3Nnc272V7bLvkiccbfUGtm7vodNtZLu6kWOKJcsxOOPT61x+lWtzqTa54muI2jFzaPDaofvBADgmgCxN49CNPNa6bNPYQOVluQOnqQO4rp7K7hv7KG6tX3QzKGRvUGuV8JlB8LW5GPs0nme5wc5q78PlYeDLLcMLjI57dsUAP1LxDqNjftBb6PJcIP4weKZoXjKDVrK/urm3NnFYk+aSc5PernivWjonh25uFY+e48qED++3ArlNc0yXQ/hdHCP+PmeVXuCe7N1zQBu2Hiy61OeFoNImFhK2FuG4OPXHpXTHgnHeuEuL/wAQeF9O0u9uL2K6sZXjgMAjClAemD3rulIZQwGMjPNAB+NFFFMArI8T/wDII/4HWvWR4o/5BA/36cdyofEcb2A9KOaB9e1Q3c5trdpEjaRhztUda6TsG3t7Fp9o9xOcIvp1J7Vn2/iDfcxR3lq9v5/+rY/xf4VQ129e8s7ZpYHgUTqCGHXmrXiwEw2RX7wmXBHUVDepm2bbnYjMw+UDPWsS28Rz3hzBp7PFv2bs+lbkyh42X+8ME1zclpqfhzT5Jba7EtsjF2iZMcHrzTbKbNjUNTi0y2EsquzsMhFGSf8A61P02+XUrBLpU2BuMUyaRLvRjclBl4Mqe65FV/DHOgw55+Y5oTQJo1enX8q2fCmf7Wbp/qzWNnPNbPhT/kLt/wBczRPYJ7HYUEgKSeQBnAopR1rnOM5C68ePZ5nudIuY9OD7GuWU7hzjJHpW3q3iG00nTFvZg8qSLmNIl3M/GeBWL4wvH1xh4X03Ek1wQbpxysKA55PrXQy2UNvozxLGD5FsypkZK/L2NICHw9rSeINIhv4o2jD9FJ5FTavq1toemyXt4SIkxwOSxPQAVifDnP8Awh8B/wBtv5mrnjDQpvEGhtbWzqLiN1ljDdCVOcGgCnaeNCdRtrfU9Plshd/6h26N7H0NdORx9O3pXmvi678Q3v8AY0Wp6dBblblMPHJuZiDzgelemPjefft6UAIMZBrhvEHOsy13I+9XDeIP+QzN+FaU9zakZ1Q3d1FY2slzOdqRjJ9T7VNWJ4sONKiyQFMy7vpW8jd6Cw+Isywi5tXt4pziKRh39/Stng89B2/xrD8T86Laj+Ium2tkZFnkjOIvz4qEyUzMl1xnnkisbV7nyjiR84GasXOpPBBE0drJJJL/AMswOn1rn9DTVRoklzZ3SIFZm8srnfg9zW5aXt5qOiwXVoFjnkGTk8ZoTBMXS9YXUpZrdomiuIeWRumPrWl3OK53Q/Ottcu4dRA+3Srv3qflK10X06U4lRsxD0rvdF/5A8AHpXBHpXe6L/yCIPpU1DOrsXfYGue1fxPc2F7La2ekz3fkKGeTGFx7HvXQ1k+JNeXRNOIjBkvbj5LeBeSzHv8ASsDlF03xJY6noP8AayMyQrkMpHKkdRiq3h3xZB4jv723gtpIBakf60YLZ74p/hPQTovh+O0u1WSaVmmmBGQGbkjFZnhwf8XB8TAYABiwPTigZ1xOAc5xjPFcjcePHtB9ouNHuY9OD7GnYEFecZ2+ldf2+v6VyPjC7fXZF8Mad+8mnIN245ESZ7+9AHVxyLNEkqHKOoZT6g08dQO+eoqOCBbW2igT7saBF544GKkX7w+tCEcT4k51mSsutXxJ/wAhmSsquqHwnbFaIMcY65/Ssy/1n7Ldi0t7dri4xkqOiipLzUpLS6WJbSSVSASyjgVQ0Qs/iTUmcYcouATyBSbCTNHTNUj1OKQorJLGcSRtxtpdS1KLTbdXkUuzkLGg6k1n6OP+Kk1UqMrtXvxmm63j+39JDHC5bOemaV9BX0LNnrZnvDa3Nube5K7kU9GH1qGfXrq3WRn01xHHkls449abrnPiLSiPv/N07in+Jp3m8jTImO66cbsf3O9FwuaGnXo1Gwjulj8sP/Cas02KJYIUiQDaihRj2p9WloWlod14ZJ/sSH8aKXwz/wAgSH8aK5Xucz3Nthwc9PSuE8ReGdb1u+ikTUUjgtpfMgXaMj613jfdNVN3HSpRkVLBLqOzRb6QSTgYZhVj8c0/zD6CjzD7VQDKKf5h9qPMPtQAynJ99aXefalRzvXpSDqed6n/AMhO4/3zVXNa+oalImozjy4zhiOlVv7Uk/55R/lXTHY7Fsijn602RS8TqCVLDGcdK0P7Vk/55R/lR/akn/PKP8qoZyNr4YuLPf8AZ9VlXe25v3fJP1rRvdPuLu1WFL1oRjDsE+/W7/akh6xx/lS/2pIefLjwPaptoLoc7pmkTadbNbm+eaLYUQFMbPekn0Zp9G/s9ryXnrLjk10X9qSf88o/yo/tST/nlH+VFtAtoc1ZaJdWRjC6k7xIMeX5eARVqfS0n1SG8kdj5K4SMjgH1rbGqSc4ijz9KBqkh/5Zx5PqKOgdCl3pM+tX/wC1HHHlR5+lJ/akn/PKP8qfQfQpfnQenerv9qyf884/ypP7Uk/55x5PtRrYNbHb2X/HhB/uip6ZaSlrKEkLkqOlS7/pXM9zjluMpR1B7jtTvMPtRvPoMUhHJ654Jl1jXYtUTV5baSFcRx7NyqfWtLTtI1CxtJop9YkupZPuStGB5f4Vtb/YY96N5HagDjbbwRqFrrL6mviOY3MgCyHyR8yA9K310p116TUTeSGJ4wn2Yj5RjvWmXI7CjefagDkJfAjrJcpp+sTWdjduXntQmQ2euD2zU2ueCItW0qx0+2vZLK3tOiquQ5HTPrXU7j6DnpRvJ7CgDn9G0DUdMvFludckvIFXaIGiCgehrd47Cn7z17+lHmegFADKKf5h9qPMPtQBT1P/AJBN3/1zrz7tXouoylNNuWwDhOlcQNVfH+qjH4VtTN6PwlH1zn6UoY/gParv9qyf88o/yo/tSQ/8so/yrVs2uc9eaK0179rtLt7Wdl2syrncKdDoyW2nzW0MzrJMdzzY5J9a3/7UkPWOP8qP7Uk7xR/lU2FY5zU9COp2VtbNdugg/ixnzD70+z0q7tpQ02ovPGF2iMpgV0H9qSH/AJZRflR/akneKP8AKj5AcxNoNzcqYp9Ula2JyYgmMj0zWvFElvCkUS4jQYUDtWj/AGrJ/wA8ovpik/tWTtHH+VFgsUc/WtXw3/yGEOD0qD+1ZP8AnnH+VaWgag8uqqpjQcdhRLYUtjqyMmkp5c5II/KjzD7Vz9Tk6jKKf5h9qPMPtSA53xZ4WPimC3iOoSWiwPvwq5Dn0NLpPh2/0+fdd61JeW+3aYDEFGPSuhD5zgD3NG8+2PagDjj4CdFnt7XWJrfTJ3LyWYTIOeoz2FbE+gKx01LO6ktILEYESDIkHoa2d57qM0b/AKUAY2teHotcv7Ga5mYQ2jb/ACccO3Yn6Vc1XTodY02azu1zHKCMjt71d3HpgE+9G89cf4UAcla+B5PNtRqery39pZsGgt2TAUjpk966o9iePan7iOwzR5nsM+9ADKKf5h9BR5h9qYDKyfE//IIH+9Wz5h9qy/EVw0OlhgoPzelOO5UPiOG7UuT759aujVZCB+7j/Kj+1ZP+ecf5V0nWm7mTqNjHqdo9vOSVbkHHIPrVG30JhdQy316915IxGpXAH+NdJ/aknUxx4+lH9qSdPKj/ACqWIxorF4rq6mNw7+eu0KRwnuKoPoFzcqsV3qck1sDkx7MZ/Gup/tST/nlGPwo/tSTP+qj/ACpsbMO+0+a6tUt7e6a2iVdhATOR6VFpGky6Uvlm8aaIdEKYxXQf2pJxmOPPpij+1JP+eUf5UkJFLP1P4dK2fCn/ACFmz/zzNVBqsn/POP8AKtXw3fNPqZQogwh5ApS2FN6HTUjAsjKDgsCAfSpN59BR5nsK5zk6nD2Xw9vNOe4e08RzxvcOXdvKBY/jW9qGjX95pMNnDrElvKilZZhGCZQeDkdq2tx7AZ9KN/Xj60Ac14c8KXPh6B7ZdYkuLVkIWMxgbSe+atQ6HdW2hS2MOrSC4d9wuSuWX2xW3vIxwMetG889PrigDm9P8KPFqsepavqcmp3UIIhLrtVM+1dFj8qcXOeQtG/25oAaOtcN4g/5DM34V3Yc5HAFcfreovFq0qiOM9OcVpT3NaRhZ+tQXtnFf2j284yjjHTke9av9qyf884/yoGqSdPKj/Kt2dBzMOgOssLXl891HAcxxlcBfT61fjs2j1CW5M7urrtERHC1r/2pJ2jj468Uf2rJ/wA84/yqUgRyzeG2BmS2v5ILaZtzwhc/katS6S4hhjsLl7TyRgELuBH0roP7Uk/55R/lSf2pJ/zyjH4UrE2MHT9JFndyXU07XNy42mRhjj6Vofn9avf2rJ/zyix9KP7Vk/55x/lVLQpaFEng9a73Rf8AkDwfSuQOqyY/1Uf5V2ekzGXSoWIAJrOoZVdiyD7Zrk9U8Dz6h4jbWYdamtpiu1F8vcI/pXX7z3Ao356gYrE5zGstH1C10ya2k1iSa4k+7ctGMp+HesnTfBd/p2sy6kPEMss0zAzgwgCQDt7V1/mHI4o3nH3R17UAZUOkSw6te3v22R1ulwsJHyxcYyK52x+Ht7psk72XiOdGncu7GIFj+Ndvv9hmk3H0X86AILOF7e0jhlmMzIMGQjG73qYdR9advI4IGKA5yAB370COI8Sf8hiQ1k5+v5V0Gvag8OqyKEQ/UVm/2rJ/zzj/ACrpg9DsjsikCR0JFZd7o7XF+L21umtbkjazKuQR9K6H+1ZP+eUf5Uf2pJ/zyj/Khjauc/BoqW1hPBHO/mzkmSbHJPrS3mjJe2MEEkriaDGybHII71vnVZB1ij/Kj+1JO0cefpRYLHP2WkG3vftl3cvdXAG1WZcBR9KlTTETWH1FpGd2XaikcIPatv8AtSQH/Vxn8KP7UkH/ACziye2KfyD5FHP1/KjP1q9/akg6xR5+lH9qyf8APKP8qBnW+Gj/AMSSH8aKl8PztPpETlVXOeBRXM9zne5rvna2PSuC13/hKbO3utTjvoI4YDuW3H3WX3PrXeuPlODj3rzzXNYi8Uak+hWVysNjEwN7OxxnH8I96lGZ1OiagdW0Kz1Bk2G4jDFfQ1ePFQWaW8VpEtns+zou1dp7VMBjp0qhC0UlFAC0qffWm05PvrQHU8+1P/kJ3H++aq1Z1P8A5CVx/vmq1dMdjtWwUh4BOQPrS0Z4J7dD60x2OdFzqUXiWCK6lRY5Rnyl+6B9an1Ga5uddi0yC5NtGI/MkcDk+wqlf6rZN4nsnE6mONcFsHANaGrR6XcTRS3F0YZwMpIM5K1FyBukXFzFq11pt1MZxGvmRyHqRU/iC7nsdJea3OGBALgZ2g9TWZoEEa6nfX8RdrUJsEjdWI71Y1zVN+irLZufIlYI7hc7R34ovoHQgiuJ7bVrBLbUWvY5gTKuOg9at6jp98yT3I1OSERqWRAoxispIrTTdSsv7Dm8ySX5ZEAyGX1PpVnV9Xhv786atwIIE/18hB5/2RST0Enoa+h3ct9pMM0wG9hgn196v1XsXtpLJBZMHgT5V4wBirFaLY0WwUe/egUGjoHQ9Dsv+PCD/dFT1BZf8eEH+6Knrle5xS3Ckz60Uo9f0pCMLWdE1LVbovBrUthbqnCRKD83qc1z+m+LdQs/BWqXN6/2m5s7n7NHLj/WZ4DVb8ZeK0tLqPQrSdYLq5X97cODtiTv+NVNXsdOn+HU9j4ekW6+zMsjkA5cg5JNACaguu+GdMtdan1iW6BdBdW7qAuGPb6V3RnRbY3B+4E3/hiuC8SeIbLxF4Ss9N0yUzXd48WIgpym0jOa603tozy6CkoN6tvgrjsRxQBy1p/bfiTTr3WotXms1idxbW8aAqQvQn61o6el54y8P2dyNSmsJoiUlMCg+Yw61k+G/ENjonhfUbDUJfJvbaSRRCwOX9MfWtPw/O/hj4eveXalH+a4RMc5bkCgCloMWox+Pp7KPWbi+sbOLNwZFAG49BXeflXNeBNMey0L7XdZ+16g5uJCeuDyAfpXSUALRSUtAitqf/IJu/8ArnXn3avQNT/5BN3/ANc68/7VtTOmh8IVW1C6FjYTXBHKLx9as1R1uB7rRrmKIZcrkD1xWrNmYso1SDR11U37s5w5h2jGCeldJbTLcW0U46SKDg1zU+r20/hWO1jctdOAnk4OQc1t2c8Vmlrpzvi48sAKO9TElMp6jp98UuboanJF5al0jUDGBVO91S7k8K2tz5hhld1VnUc4Pek1XV4NQvTpn2jyLaI/v5CDlv8AZrUluNJbTY45XQ2n3V4OMip0fUQ3S7MxSmUapJdIByrAcVq+46HpXLwi1/4Se1bRt2zYftG3O32rqOpP86tFRYVqeG/+Qwn0rLrU8N/8hhD7US2FPY7Y9aSlPWkrm6nH1FopKKQGZrenX2pwww2OovYgNmV0GSR6Vz+h6hf6T4l1XSb29bUbe0tftKysMFf9k1q+LvFMXhfTlkK77qdtkC4JAPqayvDiaadLv4Y9QjvdY1CJzMyg8sR90e1AFO1Gva5oFz4hh1iW3b5pYLYKNmxecZ966zw3qx1vw9aX7LiSRBvHo3euP0LxHY6X4AudMu5Sl9bo9v5BU7mY5AxW34Ynh8O+HNJsdRbyrq7XKpg9fSgDK1ue4vfH9xpr65JptrHArrtAwSa6RNGuG8PCwXWZ2kZtwvQAWx6VT1ibwlcX0w1hoftKLiTcCDj8Kp/DcyQ6Peu7SjTBO5tvMzkJn37UAZuq2Gq6T4g0uxs/EF1c3FxJukjdBgRjqa9ExjABzjjNcb4QWTW9e1HxHOpCM5gtQR0A4J/Guy7nP6UAFFJRTAWsjxP/AMggf79a1ZPifnSP+B047oqHxI4ylAyQv600Uq8H2zXUzsMBGvNb1K7SC7e1gtj5ahBnc1WfD99NdQTxXTbp7eQxl+xx3qlpl9DpOqajDfP5O+UzISPvCl0SZLW1vtRuMpBPOdpI5IPSs0QjU1DTpr5lMV7LbY7KM5rI037Uuq3qLfSXNvbx4yw6t/8AWrX1TUVstKku1OSV2pj1PSodEtRp+ihp8bpAZZSfU9ab3G9zJ0ZJtSi8+XWHSUSEGIAYwD0rqQMAA8kDrXJ6z/Yz6cW08g3bMPK8vIO6uotd4s4BL/rPLG/PrjmiO4ovUlrZ8K/8hdv+uZrGrZ8KjGrN/wBczRPYc9jsaQ52nHXHH1paQkKrMTgKCSfauc4+pwniWx1zQtKn1r/hIZXmhcN9nZAEIJxtFXNX1fUNS1DStIsZjZS3cYmuJlGSq47VkT+I9M8Wa5i+vFttGspPljZTm4cdz7Ve1q8gsPG2k607gabPD5KzAHav/wBakBa0q61DRvGL6HfXj31vPEJIJXABDdxXR6rZS6jYvbQXklox6TIMkVy0N3BrnxEN/ZMZLLTrf558HGe4FdRYaxZ6lZPe20m+3iJDNj060AcPqdhquleItK0+y8QXVzPcSbpI3QcIOv516KcZ46dPpXGeDVfWdd1PxHcBtrObe2BHIVe4+tdlzwP1oAUdcGuG1/8A5DM34V3I61w3iD/kMzfhWlPc1omdVDW759P05pYhmRjtT2Jq/WP4oheXSN8SlmhcSED0FbyOllO5/tDR4rS8kvnnEjASxsMDBrow26PeAeV3AfhXNatqNvq1jZWlo/mzSuuUA+4O9ba3sQke0ifdcwx5246YFQiEc39vuZ7O6vJNTaCeJ9qwY6c9Ku6hqF59l0xJZDafaDiaYD7tZapp97p899fXBTUdxPA5UjoMVZu7uW+tdMg1T91bzj96xHX0HtUk3L+k3FwNbntEujeWqID5hHCt6VvcY4rmdJ8my8QNa6XIZbFk3OuOFb61039OKuJcRD0rvdF/5BEH0rgj0Nd7ov8AyCIPpU1CKuxe61x3ju6120s3uLC4S0tIWX5xy7k9seldhXH/ABH1axg8PTWUlwBcl1IiwScVicpa8Sa5c6T4OtLq3YC5uvLi3n+EsPvVl3b6t4Tv9JuJdXkv7e9kWGaOQABS3cYrW+16FrXg+KO9uI5LNYkR2II2NiuTutKsNR17SbDRr2e/NvMszuc7YkHakM9Plj8yN1RyoIIDjqDXA+KNJv8AQdImvl8S3rzs22GPYMMxPArtItWsrnVJ9PhlLXNv/rFx0rl9S3eJPiBbaeATZ6WPOmyODL2H5UAdLocV1Dolot/L5115YMjnqSeavj7w+tIcHp2pR1H1oEcV4k/5DElZVaniT/kMSVl11Q2O2OyAc9uT09Kw5pbrVdbmsbe6a2gt1DO6DJYmr15Y3VxciSDUJLdABlFAwayrSaPR/El2t7KUSeNSkhHU96UmDZa0K8uHuLyxu5DK9s2RJjlgelaN6t20Oyy2CVuNzdh6/WsbSLpPtupaq/y2rYRWx1x3raN/axWqXMkoSJ8EOaL6BczfDF1PcWUxu5fMkSVk3EdcGq+qWmoWlpPff2o4kiy4iKjaR6U3wpf2zR3UXm/vHndguOoz1qC71a11jUTbz3Hk2Nu/zAg/vD6fSl8yb+Z0dlO1zYwTOMM6BiKnqOCSOWBGgIMWMKR6U+rWxotju/DX/IEh/Gijw1/yBIfxorle5zPc3HGVI45Heubk8FaHLI8jachkc5dgxG4+tdI/Q1ky6rYw3Iglu4UlPAQuKhGZLZ6fFp8KwWkflxqOADmpvLbHSm57g5Ht3paoQ7y2o8tqbRTAd5bUqRsHWmUqffWlqBxeoaReS6hOyxrgsSPmFVv7FvO0a/8AfQqPU2b+07jDMPmPc1W3N/fb/vo10xTsdi2Lv9i3v/PMf99Cj+xbz+4B/wACFUtzf32/76NG5scs/t81OzHZkx8LuT/x5xeueKWTw1NMAJLVGK8AkjgVQOowC6W2+05mYZChs0t3fw2UYkuZyik4HzHJ/ClbQmxproV0qBEgQR4xgEYpF8P3KRCNYI/L/u5GKzba/hvofMtZy6ZxwTkVLLOIY2eSUrGoySW4FHQfQtQ+Gpbdi0VqinqTkZH0pH8MyOxZrSNieT05rNtNWtL+QpbXRkdRyMkGo5PEFhDM0cl4yupww54NHQXQ2o9AuoU2Rwqi9cAinf2Le/8APMf99Csu0v4r6HzbWZpUzjcCan3N/eb/AL6NNXsUti7/AGLed4x/30KDot7jlAMH+8Kpbm/vt/30aN7/APPR/wA6NbCd7Ho1pC62cKsOQozUvlt6VWsv+PCD/dFT1zM5JbjvLajy2HOM02k/OkIhm0q2uJN81tFJJ03MoJxT4NPgtVZYIEiDfe2gYNRX+pWelQma/uUgQfxMev4VIlzFJai5SQGAru35wCKAGQ6TaW0xmitIkkP8aqOPpU32NBcGfyk88jG/HJH1rMs/FGj6heC0tb5XnPRCCM/Q961R145JoArzaTaXFwJ5rSFpB0YqP1qaa0S4i8qaJXjHRT0NY83jHQba5kgl1BBJESrgKTg+lWL7xBpumwQS3l15aXA3RNtJ3CgDTWIquFUKoGNo7fSl8tqx7HxTo2p3YtrK9WScjITBBNa1ADvLajy2ptFAEOoRO+m3KDqU4riRo16f+WX5sK7PUiRpN1g/8s68+3N/fb/vo1tTN6Pwl7+xb3/nmP8AvoUf2Lej/lmP++hVLc395v8Avo0bm7O3/fRrSzNtSwvhuVJfNW0iWQd+Oaf/AGBcmQSeQu5RhWyMiqmXzw7H2yapz61Z2s4hmuysh/hyTilawrGmfDMjne1nEWbvxzSnw3KYfKNtGY88DI4NVlcsoZZGKnkEMaR5hFE0jyFUUZYljxQloHQtw+Hp7cfuoET1wRmpP7Evcf6sEf7wrMtb2K+gE9rOZIicBgTU25v77f8AfRppMEmXf7Fvf+eY/wC+hWjoOl3VvqqySIAAPWsHc395v++jWp4cZjrCAsxGOmaUk7CknY7cxtk980nltSHrRXMcnUd5bUeW1NooAiuLCG7C/aIEl2n5d4BwabDpdtbSeZBbRxP6qAKkmmit42lnkWONRksxwBUFhqVrqtt59jOJ4g20uOmfSgB7aVavcCd7SIz9S5UZqWS0SaSN5IkLR8oSAdv0rLm8VaNBfCzlv0WYnbjBwD6E9K1Q2RnOQehFAEFxo9pdSiWe0ilk/vFRz9asfZlEflBFEeMbVGB9KiuruCxtpLm7lWKGPlnY8CorbUrO8sPtsFwj2pBbzc4XFAFmK1FvGI4o1jQdFXgU/wAtqx7HxTo+o3P2a1vlebPAIIz9M1q8+h/woAf5bUeW1NopgO8tqy/ENrLcaWEjGTu6ZrSrI8TkjSQQSPm7GmtyofEjmhot6AP3QH/AhR/Yt6OkY/76FUgzf3m/76NJuYDO9v8Avo10WZ2Wdy1L4cmnZTLaxuV7kinNoFy8exoEKDouRgVSeXy0Z3kIUDOSx4qra6xaXsvl210XkHUZIpE2Nd9AuZECvArKDnaSMZpx0W8Jw0Y+mRiqW5uPnfjtuNV7nUILNo1uLko0hwmWOTTAvp4Ykjl8xLSIP+GKm/sW9/55D/voVl3WoQ2UQkuJzGhPGWPP4UWl/BfR+ZazmRPUE8Urgan9i3v/ADzH/fQrW8Oabc2upl5Y1AKetc5ubH3m9xuNbPhVmOrNlmI8s8E0pbCnsdj5bUeUxBGOtJSHoece9c5ydSqdDsM5+wwD/gIqeSwhlthbyW8bxDohAwKy/wDhLdD+3CzN+gnzt2nOM/XpWncXUNpbtPczpFGoyXZsCgB0FjFbQmK3hSKM/eRQBmljskhiMccKLGcgqowDUNjf2+o2q3FlMJYH6MKn/OgAhtVt4hFAgSMdFXgU/wAtqz/7a08aqNL+1p9tK7hBnkCr35+9ADhG2R0rkNa0u6n1WV0jBHHO4V1oJJ61w+vsw1mUBmA46GtKadzWimR/2Le/88x/30KP7EvGBUxAg9iwwapbm/vN/wB9Gje2PvNjGfvVu0zosWIvDc0MheK0jRz1ORxTxoNysnmCBQx/iBGTWbDqEFzM8MNz5kkf3lDHipg7DkM//fRpISRYbwvI8vmNZxl+ucjFSSaBcTx7JYEdT2JH6VmXmoQWIX7XcFMnAyx60t1qENlGJbm4KJ2OSd30pCRow+Hbi3UiK3RAfQjNSHRb3OPLGf8AeFZNpqMF9GXtp2kUHnk1YLP/AH2x/vGhDRdOi3uP9WP++hXZaTA8Wlwow+YDmvPyzYPzt/30a7zRSf7IgySeKiomZ1djQEb+lVp9KtrmQvPbRyO3BLgGputVb/VbHS4lkv7pIVY4G48k+wrE5iQaXbCBoVtY/KPVAowfrTrXTbewUra28cWeu0DJ/GhrmJLY3LyBYNm4uTgY9aoaf4m0nVLk29jeq8wHKkEce2etAzSWzRJ3mWBBK/3nA5ahLNInkkSNRJL99h1NDsI0Z2JVQMlvasQ+N/Dysc6goI4OVPFAG/5benAH50CNgc9Oegqva3cN9ax3FrL5sMgyjjvUwzkZPegRymvaXdXGqyPGgIPuKzv7Fvf+eY/76FT+JGI1iQBmA9jWXub++3/fRrpinY7Ip2Rd/sS9xnyhj/eFRzeHp7gDzoEf0yRVbc2fvsB/vGq95qdvYAfarhos8AZJNNpjaZp/8I/ciMxfZ02dCgIxSN4euHjETQIUHAXIwKo293HdRLLBOWjP8QY0lzeRWcRkuJmjQdyxpILF2Pw1NC++O1jRh3BFN/4Rdzn/AEOLrntzWfaanb36M1rcmQL15IIqu3iLTlbDXjAg4Oc9aAN5NCu40CpCFUdgw4pf7Fvcf6sf99Cs6C6W6hWaCYyRt0YE0/c395v++jTs7DSdjv8Aw/bS2+kRRyDDDPGaKj8Nc6JDkknnqaK5ne5zu9zbk6H6V5V43/4Ruztru0Swd9VncESBW+Vs/e3dK9Ukztbb1xwK4XVdc1S5tbrTn8LyySygxoxddpB43VKMzf0GKWDQbGOaYTSLCAZAcgmr9ZXhbS5tF8NWljdSb5YUwx9D6VrfhTEJRRRTAKcn31pKVPvrQB59qf8AyE7j/fNVatan/wAhO4/3jVWumOx2rYKMcnGN2OvtSUvTmmxtnNS2MFj4qshAuGdSzMepNSas8dp4nhu72NmtBFtVgNwVvpUdzHq82swXi6fxCNuNw5Fat5d6hGIzb2IlBHzjI+U1HQgytDuYJfE96LPIgeIN0wM564q14qill05CqMyJIGlVe65qXTdPuYJLq+uQpvJgQEHAQdhU6z6iumCR7dXuz1jWhD6GDqGpWM2q6ZLpoKujbSQhX8/WtjXTa2WmzzNBGZH+VRjkselRQ2d7qepQXOoQJBDb5KRDGSfc1JqNhNqOsWvmgfYoPnJH8R7Ua2F0JtDsP7O0iGEjDH53HuetaH06Uck89etJVrYtbC0GgfnSHsT0zR0DoeiWX/HhB/uCp6gsh/oEH+6KnxXK9ziluJR14H4+lFLx1PTvSEcp4/0azu9Bur+4jLywoBECeFOev1qDWLe6u/hUkVirNL5SEqp5ZQecfhVzxmmr32nTadpmn/aI7hBmTcBsOfSn6JLrdr4e+zzaaI7u2QLErMCJKAOM8Ra5os2haUNJjliv7WaNV/dFTHk4IJ716vGfnjZhjAGa42XTtZ8U31qNVso9PsLd97x8FpWHTkV0Bl1Q63LH5cY01YgY5T94v3B9qAOGsVuPC8+rTav4ZlubaS7eYXSsCFQnriu7tv7O1zTre5WKOe3ZN0e4cKKwNTufFV/bXOnJpcaLODH9qLDaFPGcVcbRrvSPA/8AZWlfvbryfKDe56tQBk+FbSDVfGGoa3DCkdtan7PbbBgE9Grt6zfDmkroeg2tkMblXMh9XPU1pfrQAUUUUwK+p/8AIJu/+udee9q9C1PjSbr/AHK8+HT6ela0zej8IUcd6Sl/DNam5TfVLYb41mzOqnA+grJ0OzgutDu5p4leSYuzM3JrbNlbFmfyV3HOSOvNYkVpqumxXNjbQrLDMSUlJ+4D2qWSy14Xdn0RQxJ8tigPsKj1iX+0b1NMSQBFHmXBzjjsKngtLvSrC1t7MLIwP75j39adc6BaTzyT/OJZRgkHFJt2E3oV/CQRdGdI8ALcOAoPQZrbrG8N6O2lWkgm3CVpGIGe3atn0qo7FR2CtTw3/wAhhPpWVWr4b51hPpRLYU9jtj1pKU9T39qSuY4+oUUUUgKGtaTbavYtHegvFGrMI84DHHeuc8BwkeDdQitgFfzJVjA7HBxXR61PfQWR/s2z+1yuCpTdjAx1rnvBVtrekwTWd9pvlRu7SiUuCAT0GKAOatb/AEe18D3ulapbSJqqh2cGJiWcdG3V3fgy4kuvB+lyzZLmAAk96ytS/wCEm12CTTf7OisoZTtlujg5Tvgdea2PIv8ASYtKstIijks4l2TF+oA6EUAYPiuVfEeoTaKkyrZ2kRmuzuxuP8IqnplpHffCiaBbmOAK7kknjjoDW7qHgbTrkXk8XmpcXAJOGxlvesS18BXMXgeTT43ZL1pxNtc5U7TwPxoAyLTVIfEeo6FZSWf9ltaMGE7rtFxt7KfQ+9esNyx6nP6Vwt9puueJI9PsrzTY9PitJUkafIJO3suOldwBtAXk4H40AFFH50UwCsjxR/yCB/v1r1k+J/8AkEDH96nHcqHxI4umSzpbx+bKcIKkxwKa8aTJskQMnvXSdl9Tn/EN/FeafDFby7o5pQr444z0o8R28VkNPmt4wjxyqqleOD2NXdW0ZLrT/KtFWKVGDpjoSKrNa6hq9xbC/gFvDCdzDOd59qh7kG7K6wxtJIdqKMk+1cZqf+nwjVJmXm5RIVz91c9fxrp9lxdy3MN4ii0YYjI6n1zWRqnheN7OKOy3l1lXKk8baHewPYdqjJb+ILS7vUL2gjIBA3BT7gVHpF1BN4rufsQK28qAn5SBkegrUuGu7COKKxtTcIB82SMj86ZpVhcJdT319tFxPjCJ0jApWsCRq9a2fCn/ACFm/wCuZrG789e+K2fCmTqx6Z8s1Uthz2OxpCAQQehGDRQ2QjFRlgDtHqe1c5x9TifHdhplt4fGm2lnGL68kUWyKPnDZyWrc1HQLe+0CKDUgZ/stux2k8MdveuV0+z8V22tXGq32kLd3cjFYiXGIk7AeldXqd3rH9ip9m07zrudGSWIMB5WRikBQ+HAA8G24HQMQMd+a2Nd1iLQtJlvZWGVG2MHu56D86wvBNtrWk6V/Z9/p/kiNSySFgdzVoHSJvEWkCHxJAqyrISoj9O1AHHaVp39n/EPRbi7lRry8SSaZi2dpI+7Xp3U5PX19a4a48AL/wAJjpt5CZms4QxlcvyD2FdyOFAHUUAKOtcN4g/5DM34V3IHPb8K4bxBxrEuR6c1pT3NaJnUyeFbiF4nJAYdutOpszPHCzxJ5jgfKueprdnSzB0W3itPEmoQwIEjUD5ffHWugJCLuY4VRkmudsY9Vh1ue7kscLPjI3D5RWvtupruWG4QCyZcKQec1KZKOV1xhqlpNqLkeUjiOBc9Rn71dRetDHawzyW5umRRtC9uKydW8LRvpxjsQ2/cMAnjGa0ZVvdOt4U0+EXEaqAysefzqdbiRneGnjn1a/uFUwM3HkMMED1rpPSsbTrK8l1d9TvkWEmMRpEO31rZ49auI4iHoa73Rf8AkDwfSuCPQ13ui/8AIHgx6VFQirsXfrXGfEXRrObR5tSlXfchlCFjwg9q7Pr7e9cp42t9a1O0k07TtN82JiG83eBnFYHMReL7a4ufANj9mR5Fj8p50Tq0eOa5/Xdc0e7ufD0miq0dzFcxxsfKKYXuvvXZWN1rcPh9Q2mBbqBVRYmYHeBWeml6v4i1e0utZtI7Czs28xIBgsz9jkUAdc3z5JAORyDXFeO7ezisbfSrK0iF5qUojUheVXua6a3m1N9bu0uYol09ceQyj5m9c1lW+iXdz45m1W/T/R7ePyrQE5znktQBuafZR6bp1vZwjbHCgXH86sjqPrSZ4657/WlHUduelCEcV4k/5DMlZVaniT/kMyelZVdUNjtjsiCe/tbaYRTyqjt0XHWsfTlS/wDFF9LMm8Qoqxg1tS2lvO4eSJHcdGYVlTWV7p2sSXunQrPFMgV4uhBFKVwlcZoaC31zU7aM4iXbIq+hPWtme1hudpniEm3kA9KyrCxvbOG8uyEa/uOQh6AdhS6wmrXGlRRWqATSD98VONvqBRd2FfQr6bHHceKLm5slC2sa7HI6M3/1qk8RpbwWAihgjFxcsI145571Jo32238u2ewFvbqvL56n1+tPawnuvEQu7gYtrddsQ9Se9IC9p9othp8NsoK7FwR796sUZ9aSrWxa2O88M/8AIEh/Gik8ND/iSQ4z3orle5zPc3H6Gq2U5GCT1NWn+6c1yXivxdb+FLeFpIGuZpWA8tTggev0qUZnRfJkcEn3o/d+hqvaXIu7OK4AwJFDbfSpaYh/yeh/Oj5PQ/nTKKYD/k9DSps3rwajpyffWkBxmoPpg1CffFOW3HOGqsH0n/njcf8AfdRan/yErj/eNVa6YrQ7EtC/v0n/AJ43H/fVG/Sf+eM+e3zVQpHbajEAkgZA9aqw7Ghv0rHEVwB/v96XfpWc+TPnv89cjca1qVkoubywCWxbBw3IHqavX1zegxrYWomLgNuJwBU6C0N/fpROPJuDjr8/NG/Su0U//fdc7pOqvqDTwXEPlXEDbXUHr71bvJpobcvawedJ0CZxQrBobBbSjx5Nxn/fpN+k4x5Nxj/frmLXVrtdWi0/ULcRtMMxurccUXV3rUUkrR2kZhTJDlhyKHsHQ6ffpX/PGf0Hz0btJ/54z/8Afdc/omoS6np/2maIRsWK49vWtHpTS0GloX9+lf8APG4/77o36V2hn/77qhSdunei2graHpFr5X2KHYG27RjJqX5M9DVay/48IP8AdFTVzM5Jbj/k9D+dH7vPIOPrTKOv4UhD8pnPzfXNGU9Djsc9awNY1DXYrvydH0xZo1TeZWcAZ9MVDoviibWNBubqKxP261kML2wbq496AOl+Q9jzRmPHRsVxo8U6xpuqWcOvaWsEF6xRJEkB8tvf1rsVXLAZODxQApKdTu9+aBs64I9SDXE2fifxHq91erpWmRPBa3DQb2cDOO9auveIptFtrGJLUS6jeEKsRbgHvzQB0P7vng8/rRlO4auZ0rxFfN4iOiavZrDdMhkidGyrDvXR0APynofzo+T0P50yigERagYv7Nud4Yps5GetcVu0rGfJnGf9uuy1L/kE3f8A1zrz3sOK2po3o/CaG/Sf+eM//fdG/Sevk3H/AH3VCo550toHmkOFQZNaM2sae/SSc+RP7/PR5mlAf6m4x/v1yB16+S2W+lsh9gYj5t3IBPBreR1ljDqRsIyGpLUS1NHdpQ6QTjP+3Ru0rtDOQP8Abrl73UNVhaWSCxBhiGSWblgKsx6vHLpCagkTsHwBGo53elAXN/fpXH7q4/77o3aV3hn/AO+65zQ9Wk1VJzLD5TRtgr6Vqd80xl/fpX/PGf8A77rR0FtPbVFEEUqvjqzVz9anhv8A5DKfSlJaClsdwdhPQ5+tHyeh/OmHrRXMcfUf8nofzo+T0P50yigB+UB6N/hRlMfdOaytbvdStIoU0mxF3PK2DltojHqfWs7QvEl3eatd6Tq1kLbULePzQFbIde2KAOmzGR/FwKMp6Ed8A1xmpeKPEGlxtf3OjKunI4Vx5gLBf71dZa3KXlpDcxf6uVQ6n1BoAn+TJ4OT6nrRlMg4JPSsTxR4gTw3pLXJj864Y4ii/vGqNp4vP/CFf27d2+xwSpiDdW9KAOpDJ3BOPejKdCpB68HpXGjxZqthcac+q6akdpqLKkbI4JjLdM+tdgRhyPTj2oAdmP0P50fJ6H86ZRTAf8nofzrM8QNbjTP36uybugODWhWR4o/5A4/36cdyofEc5u0of8sZ/wDvugtpXTybg/8AA6zx7+lKOcc89K6LHXYv79Jx/qZ/ruo36VkZhuB/wOuXn1e7lvprbSrYTfZxmRy2AT6Vb0nUhqdo0gQxyoxSRCfukUluSjd3aVj/AFM//ffal36Vn/U3B/4F2rC1PUDp8AKQPNIwJCj+ppNI1B9R01bqRNrZIKg+lNjZu79KxkRXB/4HRv0nH+onH0frXLprskusxWgtmSCQNtduNxHtWzQtQWpfDaT/AM8Z/wDvutXw6bA6mfs8cqvsPLNmubrZ8KD/AImx/wCuZqZLQU1odnlD2P50fJ6GmUEkKT1wM49a57HIPzHjocE+tL8hPQ5NcVqXinxBpUEmo3WiqunIwDDzAWC5xmtq/wBS1F7e1bQ7IXPnqGMjNgIP60AbWUznDUfIRwG61zfhnxJcavfX2nahafZr20PzhWyCPWr/AIh1uLw/pL3syGQghEQHl2PAFAGrlDxg47jNGY8cA4/nXHr4p1XTtRs49f00W8F6cJIjg+W3YH1rriOeTyaAHAxg4CkVyOtNpw1WXzopmfjkNXWDrXDa/wD8hqb8K0prU1pDd+k/88bj/vujfpXaGfn1aqFR3Ey29s8zhmVBkheT+ArZnRY1A+lcYhuMf79IH0rtDcf99VzWlazLqN/cQSW5hEWCATya1exIzxzihLQSNDfpWBiGf/vujdpX/PK4/wC+65G11fVtQaZrSyRoo325LYzWleT3qJGLO2E0j/eycBKS2BG7u0rr5E/HQb6TfpXeG4z/AL9c3pGqzXt1cWd3D5NxByxByMVq9eaECRfL6Tj/AFNx/wB912Ok+SdMhMSsqdgTzXnx6Gu90X/kDwfSoqIzqrQ0P3fYGjKYIG7P1plc/q+peIIryWLStKSWCJd3ms4HmewFYnMdHlMZAbijch5AJrn9H8Uw6p4cOqtBIjRFkkhUZO4cEVD4Z8UXGvanqNrcWRtWtSuFY5JBHBoGdMDHjocd+aTKFcYam8dyAAM5x2rlYvEur6zcz/2BpyyWcD7PPkbAcjqAKAOtyndTQNgboetQW7SSW8bzx7JSPnTOdpqUdR9aBHLa82njVJBPFKz+qtWbv0n/AJ43H/fVTeJP+QzJWVXTFaHZFaIv7tKwP3M/P+3Rv0o/8sbjP+/VD1754xWVe6pc/wBofYdOg8+ZF3OzNgIKb0Keh0m/SscwT+3z9KN2k9PJn3Hp8/Wuf0jVDqJmjmi8q4hOHXOfxqXUJL6NU+wwrKT94E4xS8xeZt+ZpWM+TPgdt1G/Su0VwR/v1ydvq+of2zHYXVqquyFjhs4ou9Q1m1imla0j8pMndvA4ouFzrN+k9obj/vujfpP/ADxn/wC+6xdKu5L7TYriaMxu4ztParfanbQa2O/0DyDpEXkK6pzgE5oqLwyP+JJD+NFcz3Od7m3M/lQvIRnYpbH0rxXVdfstS0rWtRvDL9rmIjt42Q4SMNXtbjKsDyDXPaz4dsdY0yayaCOLzcfOq8jmoRmJ4Yvob/w5ay2zEgIFbI71q+/aoLGxj0+yhtYlVUjUAEDGasYOelUISilwfQ0YPoaYCU5PvrSYPoacgO9eKLh1PPdT/wCQncf7xqrVvU0c6ncYVvvHtVXy3/uN+VdMXodq2Eo7+2Mk07y3/uN+VNkgMsToyPtIwQODTbGzBvmbxBeLY2oJtYmzcS9jj+EVp6hqEWl2obBaTG2JB1Y9qoR+D7aHPkS3cak7iFkNWL3w1b38kLy/aN8K4Uq5BHvUdCBuiadNaRTXV2ALm6be/wDsj0rQm/ew4hlVWIwrdcVVs9DWx83ZJcyeYuw+Y5OB7UHQozpy2Y88Rqchgx3fnTWw0Yxt7jR/EVpLfzfazc5RCBjZ+FXvEly6WaWUB/fXT7Bj+73qzaeHorS4FxmeaVfumRt2PpU76WkupR3zo5ljG1R2FJLQSWg+0tks7SK3iHyxqFz61NTvLcknY2PTFJ5b/wBxvyq1sWthKSn+W/8Acb8qPLfpsb8qLqwtLHoNl/x4Qf7gqeobIH7BBwfuipsH0Ncr3OOW4lGcUuD6GjkduPSkIxvEeujSLYRQJ5+pXA2W8Cckk9z7U3wxoreHNFf7Y4+0zMZ7lzwNx61X1jwLp2t6supXE11HdKu0PDKV2j2qSPwdZppN1pz3N9LDcjDNJMWYD2NAGbFHL408SW92qMuj6axMbEY89+5HtXYCVVlwGXzByRntXKWnw506x8oW17qSRxEFYhcHaMdsVuDRbf8AtqTU90vnSxCJk3fLge3rQBzOpeErjQ7PU9V0nVJLZsvdFX5QnriqGr6m3ifQdBtZIdmq6gN8UwO3yyOrD/Ct6XwDp9xK3nXl+0DNvMLTkgn/AA9qv6r4X07VrS2gmjeH7KMQPC21k+lAHNaDbXfhrxoLDWpft93exFobzuAvUY7V3mCOtYuk+FLPSr03wknnu8bRJO+7A74rbx7GgBKKXB9DRg+hpgVtT/5BN3/1zrz7tXoOpg/2VdDBz5def+W+PuN+Va0zoofCJWd4gDNoV0EyWwOPWtPy3/uN+VNeFnRkZCVYYII61qatmDeyIfBKsCDGYwB9a09M+XTLRHOJAgzmqieFrVJBxcNGp3CMudgP0rQfTVbUY7zEnmoNoAPy4+lQtCUjO1i9kmJ02wG+5nG1z2Re5NaOnWS6faw2qc7F6/1rOl8JWz3ctwGukklOWZXIzVpdFC6abJZLkIW3b9x3fnRuBneGATPqPvO3863vfBxWZZeGLewn82BrjJOWBckE1q+W/Uow9qpMpDa1PDf/ACGE+lZvlv8A3G/KtTw4jDV0JUgY9KUnoKex2h60lKRzRg+hrnOPqJRS4PoaMH0NICnqmq22jWL3d24VAPlXu7dgKxfCulXkl9d+IdTiMdxeALHE3WOIdM+9XPEfhSw8URwJqBmAgbcnlvtwai0zwfbaVdNNHe6hMSpXE05ZcH2oAoeIZ5fFV6PD2l/NArh724HKqB/CD611MMUNpDDaqQiIoRFJ5wK5SP4Z6VA8jW93qMHmsXcR3BAJPetuXw5bTDTvMkuSbD/Vt5hy3+960AcVrPiBH8T38uqaffGO1haKzVYSyZPVjUOi+IbD/hWtxDc2k0oMvlEOu0MznjBr0+ZDNBJC/wBx1Kn3BrJXwxpw0I6O0TPZli2CeQT3BoA4b+x9R8Ky6RqGt3B1CyLrFHCzf6gt9364r1DdvAbrnkZrm7XwJp9vcQySz3dysB3RRzSllU/SukwTnjjpQAlFLg+howfQ0wErI8Uf8ggf79bGD6GsjxOpOkAAE/NTjuVD4jjBSr94be5o8t/7jflS+W+eEYD6V0u1js0MHw0yi/1RSPnFwWI9qb4bIE+pygjyzcN8x4FXbzw7BeXJuMTxSsMOY2I3CpW0SE6d9hSORIMhjt+8SO5NQQtCe5GbOcDoYyeazfCwI0NcjjzG4q5e6QL+3SKQzqkYx8jEE/WotN8PxaWT5Bn2njazEgfhTe43uVdSB/4SvTB38t62uhNY8vhOCafznlujKMlWDnIz6VsRwOkaqFchRjJ60RBBmtnwp/yFm/65msjy3/uN+VbPhVGGrElSB5ZolsKex19JS4PpSMu5GUg4YEH8a5zk6nIeIZ5fFl5/wjumAtbKwN/cj7qgHO0e9b+oabdS2EdlpV4tnLGAASu44x6VgRfDPSrYyG2u9ShEjb3WO4Iya077wlbXttbR/ar2N7ZdsciSkM3+8e9IDD8HxyaJ4s1PRr1/tV68YuGux/GCehHauh8S6GnibRmtEnCOrrJHIOQrA5o0jwxY6MlybfznluQVlllfc5Hse1Knhq1i0STTI5rlIZG3lxId4P1oA4vxXBr8txotnqlzbu32hSkca/NJtPX2r0xz8248E1haT4QsdKvftm+4uboDCyTuX2D2z0rcwec9fU0AA+9XDa//AMhmb8K7kda4jX0c6xMQpI47VpTeptRMygZ3DHWneW/9xvypk1s08DxMHUONpK8EfQ1u2dDMTTVP/CWamAOeM5+lbeVYFQR05GeayYPClvb3P2hHuzJnklz831q/HpiJey3SiQvIu0gnj8KSJRi3mjzaTaT3lleNGQfM2N92tGGS51XR4JIJhbzyrkkjOKiPhWB2Ikku3iJz5bSHFWr3Ro75VH76LyxhPKO2pSEjJ0WN9O125srk+fcSJ5hmHcentXRVT0/RItPLvGsryv1kc5JHpV7y3/uNz7VSGhh6Gu90X/kDwfSuEMb4PyN+Vd3owI0iDIPSs6jM6peFYPiXXXsYRYacnn6pdfJFEv8AAD/EfYVvYIxXM6n4B03VNZk1SWa8iunXbuhmK4FYnOaXhrQj4f0aGyZt8pYySN6ueTWL4eVj8Q/E5wTgx5P4VrWXhqCx0uaxju7x1l6yPKS4+h7Vn2Pw+06w1H7dDc3/AJ+4M5M5+cj+960AdBevusbhInBlEbYUHkcV5t4b0u9/4QFtRttXa3a3aRhGBwhDdG9a9Ct9GgtdWutRRpDPcgBwx+XHsO1Y83w+0qa5lcSXccMrb5LdJSEZvpQBp+GdRm1jw3Z31woE0q/PjoSOM1qDqPrUcMEdvbpDBGEjjGAq1Iv3h9aBHFeJP+QzJWVWt4kRjrEhCkj6Vl+W/wDcb8q6YvQ7Y7IoXdxqMVyq2dms0QwS7Pt578VnaKT/AMJNqKyjbKyKdtdAY3x9xvrjpWfqGhQ384nYTRzAY3xnBI96HqDKGkMp8RarICNgVRn3FbUkqQwvK7Dy1G4kHtVaPQ4YdPezjSUI/LNn5ifrUkmlrNp32Jlk8nbsJ74+tCAy/DqNdSXWqSj5p22x+oUUniGRr25tdKiPMzb5cHoo61tW9p9mt44oYmVI1Crx1qGPSY49RkvhG/nuNpY9hTAsKojRUT7qgKPoKWneW/dG/Kk8t/7jflTvoPodz4a/5AkP40UvhsFdFhBUg89qK5W9Tne5uMcKTVQM3OMEVbYcE+1eUacza3rWrre+IWs5ILwxRQ5x8tQjM9M3t0zz9KTzDUNtEYLWOJpPMZRjeT9/3qWqEL5jUeY1JRTAXe1ORzvWo6cn31pB1OI1HUp01GcArwxH3arf2pc+qf8AfNJqf/ITuP8AfNVa6YrQ7VsW/wC07n1T/vmj+1LnuU9vlqpSONyMASCRjPpVDLv9pXXYp9NopBqlyT1T/vmuL1rTf7KtUu4Luf7X5gxlyQ/PTFbV5paap5RnmlRAgyiHHOOualk3Nr+07nPJT8Fpf7UucZyn/fNcr4caRLq+tRI8ltFJiNmOTn0zVjxHeS21jHHA2yWaQJu9B3o6Bc6H+07oc5QfRaUapc46qR67a4+8s/8AhH7yxntZ5mWRwkoZiwbPeoZ7211HVbldRvGit4G2LEjlcnuSaVxXO1/tO5HXZ/3zR/alz/sf981l6dHbx2ai0lMsJ+6xbd+tWapaopLQt/2pc99n/fNB1S44yUwf9mqgpO1FlYLKx6PaSs9lCxIyVHSpd7ZqvZf8eEH+6Knrme5xy3F8xqPMakpO9IQ8FiOMc+tG9gfp0B71z2t+FYNcuGuL28uUijQ7UikKY/2uKyvBQvNT8NahaS3kjRx3LRW9weW8sUAdsS4HGPwpN5PcY6g4rzvUtJ/4RXxDox0i9upJ7qUrLFJIX3j1welegTyi3gkmIGI1L4P0oAl3O3Tb6mgMxPyn9K8707R5PFGkX2t3l7cpdh5PswikKrGB0yB1q7YzQ+IfBtrca7qDWsMDmKZlcpvI9SOlAHb7mB5xx1NJ5jVwngk7PE2pwaVdS3OhqqlHkcv83cAmu6oAXzGo8xqSimBBqMrLply46hK4canc44MY+orttTP/ABKbv/rnXn1a0zoofCW/7TufVP8Avmj+1Ln1j/Fap889/elxk4yOa1NWWxql1jgp/wB8ij+1Ln/Yx/u9K5Tyv7d124huJJUtrcbQiNtJb1qXw/NKlxe2Erlxbt8jE87ewqbiudMNUuSeCn4rS/2ncjug/wCA5rmdckluL2y0yKQxrOSZCvXAqGKBtG8QW9vbyu1tdoQUkbcVI70riudZ/ad1jrGB/uik/tS5/wCmePda4jWYLS2jZra/lfUt42qrn8sV1FsZGtITNjzNg3eoNNDTuX/7TufVP++a0vD9/PLqqq+3GOwrCrU8N/8AIYT6US2FLY7gu3PIx9KTzGpD1NFc5ydRfMajzGpKKQDg7de39aGJHBrK1vQxrsMNvJdTQxK+51jbaX9s1zfhWKTS/Gmp6TZ3M1zp0UIceaxYxv3GaAO53Pz0wOvHWk3kd81wGq22pWfj3Qp7rUpJVuZJFEC/KqKBwPeu/wAc4PGe9AChmPHBPXnik3t3rgvs8fivxnqtnq93PBBZoohhjkMec/xZ71Y8GXt7d6dqemRXnmy2cpjhuG5IB6fXFAHbZYelJvPXpXD+Dobu08Z69ZXV9LdtGI23v0yRzgdq7f8ArTAXzGo8xqSigBfMaszxFcPFpYZcZ3dxWlWR4oP/ABKB/vU47lQ+I5f+1Lkgcx/lR/alz6p/3zVOlx+ddFkdiWpb/tS6PAKf980v9p3I/ufgtc74ju5bWwVIG2SzOEDDtzzVC+sz4fntLi0nlbc4SbexIbPpSbIudh/alz1JQAdttH9p3Q6eXn0281UYYB9q5qWG6t/FNi1xdPJ5wfKjgAdqbdhtnYDU7k8Apx0yuKDqdz3KDHXjNcf4qZDqmnLcSyRW7Bt+1iK09FgsYo5W06czqxG/dIWxSTEjd/tS6z/AM/7Na3hq+nm1Qo+3AjPQYrns/jWz4V/5Czf9czRLYJ7HZb2o3saSkOSpAOCQRn0rnOTqP3Njd09KAzE445rzzxZ4cTQtFm1iHU7s6lG6lD5h2sS3TbXSXehnxJYWP2+4nhUIGkSJihYkeopAb5Zh7jpjFAdjwMVxHgrzrPxJq+lxXM1xp9sB5bSNuKv3XPeup1a3F3pk0TXBtkIy0o42jvQBfJf2/OmiQ8Hgg+tecWMdpZ+NtOi8K6jLdwOrG9VpjIoHY89K9G9e3t6UAODtkf4VxuuahPFq0qKUxx2rsB1rhtf/AOQzN+FaU9zWiQ/2nc+qf980f2pc+qf98VUrM8QXstjpTNAcSSMI1J7E1u9DoZvnU7nqSn/fNJ/alz6xj/gNcbf2TaHbWl9bzytKzqJg7Ehgev0rplbegb+8ucj3qUCLv9pXP/TPn2pP7TuumUBHYJXH6zpKWGny3wu5vtSkFTvOCc9MVpXeoy2ujwyOpNzOoRFHUsaE7CvY3jqdyByUHPYUf2pck87BjjG2uP8ACqzwXt/BcTPK6N8xY5xXS46/XrTjqC1LR1S5x1T/AL5rtdImeTSoWbGT1rz89DXe6L/yB4PpWdREVdi/vNKGZhkdutMHFc5rnhO21a4nvb6/uo0WPKrFIUEeO/HWsTlOm3tnA798UFn4PAJrjPCC3uu+CDBdXcqHznjSf+J4weKoPpn/AAjPjPSrbSby5kF0h8+KaQuMDqeelAz0HzD9TShmxkYzSHAckDpkV59qFtqVn470iS71KSYTucRJ8qqPT3oA9B3tngg460CRieoxn0oYfMw7A/nSL1H1oEclr9/NFqsiptx7is3+07n1T/vmrXiT/kMyVlV0xWh2x2Rb/tS59Ux6BaP7Tuu5Qe22sXXLx7DSJp4zh+FU+5rFvLB9J0uHUobmZrpWUy7mJVgevFANnaf2pc9Mpn/dpf7TuT3T/vkVQSYNbLPjgpuxXNWVi+t2V1fXFxKJt7LCFcgJjpxQFzszqdz0JTPptpf7TuQM5TH0rlrLWZF8Mi5m+edXMKerMOBUHhxLiDWr+G5lZ2wrEE5Ck84ouFzr/wC07n1T/vmj+07n1T/vmqlFVbQrod/4eneXR4mcDJzRUXhn/kCQ/jRXK9zme5tyHCMScYHWvO9fu/Blzp98ZHhN2wYBY8iUv2/WvRXHynGOlZZ0nT/O802dmZAcljGM5qEZmV4KjvIvCOnrqG7z/L/i+8B2zW504p+wDncuD+lHl/7a1QhlFP8AL/21o8v/AG1oAZTk++tLs/21pUT5l+daA6nnep/8hO4/3zVati/00Pfzsb21GWPBbkVW/skf8/8Aaf8AfVdMXodiehQpskgjjaQ52qOg6mtH+yR/z/Wn/fVB0odDf2mP96m2Ns4SDUo77Uzd6ikoSJsQQ7eB/tH3q9r+sSQxRW1ojhrgcy44Rf8AGur/ALGi6/a7H86X+x0PW9sm+vapJ6HN6PPZQ2bQWqyYiXfISOWNVdadtT0iC+tYZD5Mgfy2HzEZ5rrho8aklbyyHY4PWgaSq/dvrMDsN3FPoM469uxr11ZQWiSbVcPI7LgLjtUNs1tpOp38d/a7/OYyRsUyGz2rtl0eNM7b2yTdydpobR43xvvLJvQk5pMTRzXhe3kg02RpUMaSSs0aHqoPStir/wDZa9tQtOO26j+yh/z/AFp/31VJ2RSehQFB6VfOkj/n/tP++qP7KHUX9pgdt1HMrBfQ7Sy/48IP90VPUdpHiyhHmIcKOR0qbZz99a5nucctxlH0OPen+X/trR5f+2MUhHC+NfEExvYtEgSeGCQZublF/h9F961LHXNM0zwzLJplrM0FknEW35nP9ea6NraNzl0iY+rChbaJRhUiA/iULwaAPPPDms20+qHWdZSdtSnOyGPZ8sC9gPeuxl1OG51S40TypvPaDcZCv7vBHHPrWiLOAMMRwZzn7o4NP8pS2fkB6FscmgDzrRdc/wCEc0C/0e/tbkXiSSCFVXIkz90ir+mPbeGvC1nZ69ZySi7ZpXATcsZPZq7VreN3DusTOO7LkileBXBWTY4PJDDNAHBeGoopPHM1xodvNb6R5X74EYR37Fa7ulWFI12x+Wi/3VGBTvL/ANtaAGUU/wAv/bWjy/8AbWgCnqf/ACCbv/rnXn/avRNQjDabcJ5iDcnU9BXFDSlGcX9p/wB9VtTZvRfulDt7iqF3pK3dyJTPImOwOBW9/ZI/5/rT/vqj+yR/z/2n/fVaNmzZx0M40PX7o3EchgmUMkgGcH0pdLkNv9v1WaGQRytiNMfMR61176RG+BJe2TAdATS/2SpGDfWePTdxU6EnI6tIyXWmatHC7xJnzFH3lBpDN/a3iC3ngjf7PaIzFiPvE9hXXf2Qu0qb6zKntu4oXSEjAVL2zUDsDQ7X3CxxOrXemX1pMqWkv2w8R4TDBuxzW9pqzpptut0cyhBu9fxrX/saINu+12O71zzTv7KB639pn/epoFoUK1PDf/IYT6VF/ZI/5/rT/vqtHQtPEOqK4u7d+OitzSk9AlsdUe9JTymT95TR5f8AtrXPc5Ooyin+X/trR5f+2tAHM+NPEU+g6ai2du8tzctsVlGRH/tGq/g250y2iNpbGd7yY+ZPNIuC7d6614EkA8zy2x03DNItvEjbkWFG6ZVQKAPPfFOvW83i7RJUinZLGWTziE4HFdbceIbaCSxzDcOL8/u2VchP970rUNrCScxwEnlsqOad5CAAfu8L9wY6UAcd4mk8Ntqj/wBp2lw95EoI8nKlx6ZHWk8EaedC0e91K7geAXLlxCR8yoPu/jXYNawu+6SOEt/eZQT+dPMYflmVgRjB6UAed6Fr1v8A8J9q900NwIrzy1iYpgHA5r0Hp06Un2SEEYSAYORhRxUhTqdyjJ60AMop/l/7a0eX/trQAysjxP8A8ggf79bXl/7a1meIbcT6aEM0UY3fec4FVHcqHxHDA4xUN3bC7t2iLsueNw61qjShjH2+0/76o/sof8/1p/31XRc67nHaxo72+mB7Z5JmhkD7TySM802/u18QTWVtaRSABw8hYYC4rs/7KAH/AB/2g9fmpF0eNclL2yUdyDipdiTIg1CO4u5oUjkBgxuLDhs+lYGpanE3iCxmVJSkG5XOOBXbf2SgJP26zGepB60n9jRHI+12OD+tDt3GzBvNTsojH9qhLo4yrMmcVn6HF52uXt5bwtBaMAFBGAx9cV17aNG4w95ZMB0yelA0lVGFvrNV9A1NAij29uwrZ8Kf8hZv+uZqr/ZS97+0z/vVq+HdPEGpbhdQSZQ8I2TSk9BTeh0tDEKjMeign8qfsH98D60eX/trXPc5DzNfEEGv+IPtusw3MdlZufs9ts+8w/iNbni7xZNZaXbppkMpkvhgS7eIV9frXWfZIf8AnnAfTKinG2jKgEREL0BUYFAHLeErrSrOxe0sVnaVVMs0rr80jd/xq8fEtpNoUmovZ3T26tsaEx/MffHpW2tvEpJRYlJ6lVApfIXaVBQKeoxwaAPNrr7FqHiLS5PC1pLBOr5nmRNqBPRq9IbqaEt4Y8mJIkPfYMZp2z/bXJoAaPvVw2v/APIZm/Cu7EeCMMtcjrWnCbVJX+2W6dOGPNaU3qa0jBrK8SWkl1pJ8lSzxMJAo74rpP7KH/P9af8AfVH9kj/n/tP++q2k0zoZxV9fDW7ezs7WKUOXXzty8IB1rbhvomu3tAkgeFPvkfKcelbI0eNCSt7ZKT1IPWl/slc5F9Z7u5zUpruLTucG2px6nqnm36Sx2tu37uIL98+prUu7C41K9tr+znEaIvyIw6H1rpjo0P8Az92Jz70o0lQABfWgA6ANQrCOK0C3v49ev2nkyhb5jj73vXT1eGkKM4vrME9Tu60v9lA/8v8Aaf8AfVNaDWhnnoa73Rf+QPB9K5I6SMf8f9p/31XZaVAI9NhTzUYAdR0NRUZnVehYxmuD8X6+97rC6EUnhscBrmdF5cf3RXfhDnh1prWsTElkhY/3iorE5jm/+EksdM8LyXWmWkzRWyhIoQvJPbNYvhTU7RtQOoaoJpdXvWC5K/LCD0UV3otogpULEE7qBwTSfZIFOfKh3eyjNAylb6xDc6zc6csUyy22CzsvyNx2NcX4j1+3l8X6VPHBO0dq+JCE6V6KIRuJBQE9SOtR/ZYGJPlQ8+qigBkFxHdwLPFnY4yAeoqUdR9aURBQoDqAvYDilCYbllFAjiPEn/IZkrKroNd08T6pI5u7dPZm5rO/skf8/wBaf99V0xeh2ReiOe8QWsl7os0MQywIcAd8Vk3uonVdJg0+3gkFw7KGBH3cdc12/wDZQ7X9oD/vUg0eNW3Le2SsepB5oe43uYi3EYuP7M2Sb1iAEmPlrE07UP7H0+6sbmGQzxuxjAX7+eldsNIUHP26z3f3t1B0eNmBa8smYdCTzSdhM4m10G9azs3Wby5EZpNhHAJ5/MU/S7fUF8U3rzygrhfMbH3uO1dp/ZQPP9oWhP8AvUn9kKGJ+3WfI+YhutFl3CxQFLV/+ygR/wAf9of+BUf2SP8An+tP++qq+hVzq/DX/IEh/GipdAg8nSYkE0bgZ5U8UVzPc53ua79DXP6p4l0nRnCajexwSNyFIJJH4VvStsjdscqpOK8n8O6pMLnWNR/sKbUXNwxaUgMFUfwjNQjM9ItLuG9to7q1kEkMi7kcDgipcVn6Fq1rrWkxXlknlxv1QjGw/wB0itD6VYgxRiiigApyffWm05PvrSA891RR/adxwPvmqu0Z6Va1P/kJ3H++arV1RWh2paCbR6CgKueQKWj9aYyOWSOGNpJWVEXnLVX0/UbbVUd7U5RG2tkVYmgiuYwkyhx3B6VjeG1G/VY1GxftBAx24qW9SWyzc6/Y207xndJ5Zw7IMhfrWhDJFPEskJV0cZBHQiubtJJtJt761uNNmmMjMwdQCCCOtXvCRY6CgbPyscZ7CkmJPUu32qW1gyxy5aVvuxKPmNPsb631CEvbnO04YEcqfSsu8Sax8S/bzZvcwPEEBUZKEVF4fmMviDU2ELwKyqfLb19aL6hfU6IqM8gUbR6Cl+tFWXoJtHoKCoOCRyKWg0raC6Hodl/x4Qf7oqeoLL/jwg/3RU9cz3OOW4mKMUUUCDqMHmlwTgd+3vSUdO/NIDn9U8a6VpV09vJ5spj/ANa0akrH9TWkda08aR/aZuE+xFdwkzwap+J9QstH0W4MkCNNcqY44ggJkY8Vx2o6VLpPhfw/pl2DtmuA80fZTnIH0oA6/S/F+mareLaxs8UrgmNZBjzB6itwcCuP8fRpBd6JcRIqTR3KquwY4PUV2T/fP8jQA3pRgdqKKYBijFFFAFbU/wDkE3f/AFzrz4AAdBXoOp/8gm7/AOudef8AataSOigvdE2j0FG0egpaPzrU2K93d29hA01wyqo6DufpVex1e0v5TEmVlAztcYJHtVLWx52uaTC/MZkY4PfijWFWLxJpUsaoHYsp2jqMVF9SL6m4wUDOBgdapW2r2d1ftaW7h5EHzYHFXHRZEZHGVcYb3Fc/b28Vt4zaKFQsawDAFNsbZ0O0DsBRtHcA0v4YoqhiYHpWr4bAGspgdqy61PDf/IYT6UpbClsdsepPekpT1pK5epx9QxRiiimBXvr62020e5vJVhiQZLNUGja1Z69Ym9smJgDFdx45qTUrC2v7VhdwrKIlZ4wexxXNeBIjN4Q1GGPCtJLKiY4AJBApAXpvHWkQ3LRmR3jR/LedR8it6ZroEdZIxJGQyOMqw6EV5rFcT6R4HvdFv9AuZJ4kfMyqNrf7ea7HwS8sngvSzKSW8hcH2oANW8Wafo101rMsssqrvdI1zsX1NW4Ne0240b+1Uuk+wgcyeh9KpeJLvUrSF/7K0hbySRCC+0ZFchY6W2pfDV7TTA0t5FeGee36EHOWSgDr9P8AGWmahfJZqZIpJBmIyLgSD2rd/wAgV5l4n1hr2DQkXRbmylhu4gJZFACn+7xXppJPJ+93+tABijFFFMAxWR4o/wCQQP8AerXrJ8Uf8ggf71OO5UPiOLwMAYFGB6UCo7q6js7driUnYvYCuk7BZ5orWFppmVEUck1Rtdcsru4EIDI7/c3jG76Vma9qUOoWUCwM3lNOocEY71N4qQRRWLxoEkSZQpUdBUORFzeOFUsccDNZC+JbCSUpGrs27bkLxmteZd6SKB95cZrmLdr/AMOWL+faxTW6yFmZR8wB702x3N+7vbaxtvPndY1xnnq30pbO6hv7VbiHmNuhNQXsdvfaX9pZA/7ndHnsDUHhgf8AEhiGMDcaEwNXA7gGtrwoANXbj/lmaxuo9q2fCn/IWb/rmaJ7BNaHYUHABJOABkn2paTGeD0Nc9jj6nNP4/0WO6ETPIIi+z7RtPl5+ta2q63ZaNaxz3UoxLxEq8mT6VgeO5IZtMTw/ZW8cl/esoVEQfu1zksfSq09qsfxC0ewn/eRWtoGQNyN3SkB0ejeIrDXWkjtHKTxf6yJxhgPWtXGegyema468QW/xWtDCAhmt9sgUYyBW14n1tdA0aW56TMfLhHqx4BoAF8UabJ4iGipNuvSucDpWt34rzDTLa00nx7oRe4iknmSSS5k3Z/eMOma9P8Ac4P09KAFH3q4XxAAdam49K7ofe4rhtf/AOQzN+FaU9zWiZu0egowPQUtHf14roudOxXvLy3sLfzZyEUnAGOSagsNWtdQkMURKzKMlGGCRVDWB5viPTYZBuQDfg9M0aooj8V6fJGNpK7WIGMiovqRfU2riWO2t5JZMKqDJOKzrbxBZ3ksccSSZfoSvFXNTtmu9Ont04dxgelYkF9d6HFbQ6haReSf3fmoORQ3YbZ0e0egxRgegpew9+aKpDsNKjB4Fd9on/IHg+lcEeld7ov/ACCIPpWdVGVVaF7r0FZOteJNL8Popv5wjSHCoOSa1T71yXxB0+0Hh+5vPIT7SXUGTqcelYHOdJcala2mm/b7qQR220Nub0PSsvTvGOmajfLaKzwyyDMXmDHmD2qh4m0y61XwPYx2UZkki8qYxj/looHK1z/iTWW1CXw+E0a5sZIryNd7qBj/AGeKAPTMDJ4IwMmuXHxB0iSRo41nl2vsJVcjOcV1LZZTuzyCD9cV55ZprfgbTLiS5020u7BJmkdkXMiqT1oA9CU70VgCAwBApR94euar2N5FqNhDdwEmOZAwz6elWB1H1oEcT4lAOsycVlbR6VreJP8AkMyVlV1Q+E7YrRCYGORRjI6CgnCknoKy5tatp47mCFnEyxMRwewoY2EviHT4pihJZVO13A+VT71poVdVZSCrDIPqKwtLgibwc2VUl4mZsjqfWrfhtnfQbfdnKjAz6Uk7slO7Lt5dQWNq89wQsacE96Syu4b+2S4g+4/HSsLVLiLVb+aBpFFtaISwJ/1j9vyq74VkV9CjCMpw7ZA7c0c2tgvqa+B6CjAx0FLR2qrF20O68M/8gSH8aKXwz/yBIfxorle5zPc25ACrA9CMGvPLfS/EPh6XUrPSoYbi0vZWeN3/AOWW7jBr0NxlTVXeoGMHHb3qEZmN4Y0Q6Bokdk0nmTZ3ysvQsfStbPuKeWU8EHkc4o3Kf4aoQzP0oz9KfuX+7RuX+7TAbSp95aXcv92lRl3LxQB53qZH9p3H+8aq5HXNbOoXlquoThrUE7jzVf7dZ/8APoK6I3sdibsZ2R60ZAHJ+mK0fttn/wA+go+22f8Az6DNO7HdmTdfafJP2LyvN7eZ0/GsnSdP1SwuJWlks3iuZPMk253D6V1n22z/AOfNT65pPttmc/6GCT3pati1ZzN3b6zdeZbie1jt243DO/b6VM1jNbWNva6bKsflYDM/8QroPt9lg/6GP8KU3tngD7GOBQr3BXuYF9/avnA6e1t5e3kS9c+tN0nTTp6SPNJ5txMd0j9voK6H7bZ8f6GOnFH22z/59BRrcOpnZHrRketaP22z/wCfQUfbrT/nzFVdjuzOyPWgsOCMda0fttn/AM+gpDe2fP8AogpXdgu7HaWX/HhB0+6Kn79qZaujWcJCAAqOKl3L/drme5xy3GZ+lGfpT9y/3aNyZ+7SEM/KlGAeQcDtTtyY+7RuU4+X3AoA4XUfDHiebxTJq0F5p0ypxbR3AJ8ofT1rS1Dw/qWv+Hhb6xcWyalHKJIZbfO1cciuo3LjIXIzmjcM/dGD1oA5GDw9rWp6raXfiW4tHjsv9VFbZxIfVs11eeT6+9Pyn93ijcvQrQAzP0oz9KfuTONvNG5P7tADM/SjP0p+5f7tG5f7tMCpqX/IJuv+udeej6g4r0XUHRdNuWZMgJyPWuL+3WeD/oY5rSmb0fhM7I9aMj1rR+3Wf/PoKPt1mOfsg471rdm12c7rGmPqEcMlvKsVxA26Nj0+hqK2027m1KO91OSJpIlxFHD90e5rpvttl0+xjnk0fbbM8/YxzxS1EYlrHeRpP9olR3ZiYiOgHYGstdN1oav/AGi0tj5hUIVGcYHpXXm9shjNmMA8Cl+22Wf+PNeaGDM4H5RuI3d8etGR6itH7baY/wCPMDtR9ts/+fQU7sd2Z2R61q+G+dYTkdKj+22f/PoK0dBuraTVFWO2CsR1pSbsTJux1J6k0mfpTy4z93H0o3L/AHa5jk6jM/SjP0p+5f7tG5f7tAGbrKapLZ+XozWqzPkObkHbg+mKw/Ceh+IdBiktrybT3tXdnzEDu3Guu3rtxjijco/hxnqKAOQvtI8Ua0jWV/d2EOnlvneAHzWX0rYn0+9g/s2HSZooLK2G2aN+rL2xWuWXIytAZeMLz3oA57UYfFMd9I+j3Ng1tIPlW4Byn5VDpHh7UNC0acWVxDLq1xKZZJH/ANXk9vpXThl6BR70blxkL7E0AcnD4f1jVNVt7zxJc2pjtTuit7YHaW9TmuqJyc8ZPNPyvQL70hdf7v19qAGZ+lGfpT9yf3aNy/3aYDM/SsnxQf8AiUDn+Ktncv8AdrM8QSxR6YGki3Dd0px3Kg/eOFyMDmg4IwcEehFaP26z/wCfQUfbrTtaCujU7LswdV02PU7IwcRsCGRlGMEVTXTL+9ubeTVZoWigOVWL+I+9dV9ts/8An0Ge1J9ts8j/AEJfrS3IMSOK8+0XLSTI0bACBV/hPvWdcWGsahCbW8ntUt2PztHncwrrPt1kc4sxnpil+22Qx/oQBpsb10OevLa8+wR2unNAEEexjL2HtUWh2V/p1uLe6kt3gXJHl53Zrpvt1n1+xj60fbbI/wDLmKlXEkZ5OOuM+1bPhTH9rt/uVW+22eD/AKGM1qeHLm2l1IiO32NszmiTdgm3Y6WkbJRghAbB2k9Ae1Sbl/u0bl7LWFzk6nn+neF/GGmahdXyXmlXFzcNkyyhiyj+6PatfV/Dup30un6pbXFvHrVoPnLZ8qT2+ldTvUc45bvRuTso4pAczpHh/UF1S41nWZ4JNSki8qIRf6uMdqt2+iyXulm38SCK+kDll29AO1bZZc/dz7Gjcn93HtQBxtx8PrA+KbHUoIIEs7cHzYcnLN2P4V14G0BRjgcD2p4ZR/B+FG5f7uKAGjqOtcN4gIGsy/hXdhlz92uR1q7tU1WVXtgzcc1pTeprS3MDI9aXIxyeO9aH22z/AOfQUfbrPqbMHAre7udF2c5q+mPfNDNbyLHdQNuRm6Eehplrpt3JqJvtTkiaVE2xrF90e9dML2zA5sxn+QpPttljmzHNSIwY4dQWzuFeeN5ycxN2H1qjLpep6nNCuqS2/wBnjO4rF/Ga6z7bZk8Wg46UfbbPoLIfT0odwdzPyPXpxRketaP220xn7IKPt1n/AM+gp3Y7sziRjrXe6J/yB4OnSuSN9Z4/49BXZaVJG+mQsibVx0rOpcyq7FjPf09K5jxfo3iDXYHstPl0+Kychi0wO/Irqty/3BSBkB+7g1ic5gWdv4kt9D8l5NON7EAsJUHZgetVLXw/q2pavBqHiS4tWW25igtgdu7+8c966vIz93ml3Lu5WgDJS31T+1r2WW5iNnKv+jxjqh9TWFf6R4t1e0k02+vNOjsZTiSWIHzGXPSuzDDn5c+1IGX0/GgCrZWcWn2UVpCMRRIFUGpx1H1p+9RjKc9BQGXd93vQBw/iQ/8AE4k5FZWR610WvXVtHqkivbBj61nfbbP/AJ9BXTFux1xvZGdkeoprxxyIyFVw4KkgDODWn9ts8/8AHoKT7dZ/8+gptsptnHroupQWkun29zCLJ2OWP+sVT2rRFnPbraQ2UqpbwjbIG6sK6A3tl1+xDp/nNAvbPgCzFJXWorHPXeh6fcLK32dPNkB+bJzmk0TSU0ew8kFPMZiWYd/SuiF9Z9fsYBo+2WeMfYwRR5gZ5IBxn8aTIx1rR+3WZ5+yCk+22f8Az6Cndjuzq/DPOiQ9O9FTaBJFJpETRx7V54orme5zvc1pM7GK8nHANcNqGreKrGO5n+yWotoQW3N6V3L/AHTXC+OrqS9ksPDts5E1/KDJt6rGOc1KMjY8Mapc634ft7+6hELSjcFHpWr70yC3jtbeOCIBUjAVQOnFSVQCUUUUAFOT7602nJ99aAW559qf/ITuP941Vq1qf/ITuP8AeNVa6Y7Hatgpr5CNtGTjOKdRkDJOBgck9AKbGc9fX2tabEt7ctbvBuAaNVwwGfWrWoajcvfQWGn7BPLGJHeQZCrVOa5j8R36wiaNLC2fLlmA8xvT6VI8kdv4xR5GCxy24SNieM+lQ2yG2WdM1G7/ALQl07UtnnxrvV0Hysv0rRuZZIIGeGIyyDooPWsdJEufGUs8Tho4rcBmHQH0zW3HNE0fmLIvl5+9nj86aY0zI0LUru+uLuK9VEeJuAo6fWl8QavNp0ASzRWumBbB5Cgdc1X0GWM6xqeJEJ35+91rOup72FdSmudPkeSZSok3cKnak27Cb0Oo06drrTbeeQYaVAxx0BqzWV4bne40S2DwtEVjAGT94etatVHYqOwUUUU+g3seh2X/AB4Qf7gqeoLL/jwg/wBwVPXK9ziluxKPyopc478CkIwtZj8ST3mzRZbO3gCbt86liW9BWZp3jWU+FdQ1DU4VF3YTG3kWPhXfsRVzxV4mTSwmmWckbapdjbGrMAEB6sTWFr2iwaZ8NZ4LS4S6lEqTXMkbbtzbskmgCxNrvifRLS11bV/scljO6rLDEhDxBjxzXcZVk3DlCARiuK8a6na3/gW3itZo5Zbt4REqMCTgjPFdZbTQwiO0aaP7RDGC8e7kDHXFAHL+IL/xZpFncasJbAWkLcW5Q72T6+tatxeaxqejWE+iCCKS5jEkjzrkRgjpisTxfotlf2N1qaa87NAvmi3eYGEkdttaEHi+DT/BVlqmoqsMssYEUA43t2AHpQAmga3qo8RXeha35Ek8SiRJoBgMD6j1rqK5fwlZAXFzqt/cwTanf4Yojg+Uo6LiuooAKKKKfUCvqf8AyCbv/rnXn1eg6n/yCbv/AK5159WtLZnRR+EKhu7lLS1knkzhBnipqztfjaXQ7lUGTjOPpWrZszNbU9XhsF1OTyDasQTCF+YLn1roIpFuIY5l5Vxke3vWBd3tu/gxCsqFnQKqA859MVracy29ja20rqJxGPkJ5qE2TEzdZ1jULKeIQQKsHmKhlfndk9qu69qT6XZq8KqXkcIGboM9zVHxbKgtLZS6BvPQkZ6c96l8TXa/Y4oFET/aHC72OVX3ouxNiRX2oWesW9peyQTpcKWBiHK4rb6H61ysFqNB1u1WOcXi3K7TlsumPQ+ldV0JxTi2OLYVqeG/+Qwn0rLrU8N/8hhPpTlsEtjtj1pKU9aSubqcfUKKKKAM3Wv7XaOFNENtHI7YklnXKqPpWT4e1vVR4hu9C1zyJLmCITJNAMKymtTxB4htPDmnfart1DsdsUZOC7dhWZ4SsQk9zqt/cwS6pfctGjg+UnZaQFa68TazD4u06yeyS2sLp3QF+XfA+8D6V2PXvz7da4vxZdQDxn4YzcQ4SWTd84+XjvXXve20UsIknjBlP7vLD5/p60Aczeaxq+reIrjSfDz28K2ihp551yCT0Ap+i+INU1Wxv7UwwrrFo/ltgfIfQ49KqeGJo9O8ca/bXcqQyPskTzDjcDUXhd4J9Z8S3z3Hk2d06xJOG2jcODg+tAEo1rxBoviWx0/WpbO6ivgSBboVaMj+ldmeG4yK84vbGPwz4p0y8tNRfVJrqQQMlw4kdFPdT2r0duHI/CgApKKKYBWR4o/5BA/3616yfFH/ACCB/v047oqn8Rxg/pQByKQU5eHFdPU7DCa/1HUNQuINLaGOO34ZpFzub0q3oupPqNs/nLtuInMcijoSO9UtAuI7bUdTindYn88yDccZWm+HmRTqV07AQPcHDk4BqEyEy3rGo3Fvd2tnaMiy3BPzyfdAFQW2rXVteXlrqBjmNtH5vmxDjHoai8QMl/qNnpzFIlcb/PY8rj+6ah0yFbLVLnSnkW4gnjLNNnLAejGk27ibdx51PWf7OGqAW5tgd3khfmCeua6CCZbm2jnTgSKGx6ZrltUsnsNFkgi1FXgf5Yogcsc9q6TToWg023jb7wjXI9OKcb3HG9yya2fCn/IXb/rmaxj0rZ8Kf8hdv+uZpz2Cex2NIc7Tjrjj60tJ0BJOAOpNcxydTi9Y1LxdotlLrE72P2OJhvtgh3hScdfWtm/n1jUbS0fQTbwCZQzyTrnbxWDqmpweMtU/si3u4Y9JtWBu5TIAZGB+4K39f8SWPhrSo3DI0kgEdtEGHznt+FAFPwvrmpXesX+j6ysDXlkA/nQjCyKeldBeTva2kksULTSL91FPLH0rB8JacllFc315dwS6jeHzJyjhvLX+79K6CC8t54/NimjkiBxvDDaPrQBzXhTxBquq67qtnq0EUBtlVo406rnsT3rqa4zwzdW58e+ID9oiIZECnePmOe1dpj5iOR9aAAferhtf/wCQzN+FdyPvVw2v/wDIZm/CtKe5tR+IzqjnkaGB5EjMjKMhFPLVJSEhfmPAHUk8Vuzo6GPpGp3t3qd1bXkSRmLBCjqM+tbDuI1dm/hBJxWDp0sR8VajtkQg4wdw54rb8yKRnh3KTt+Zc8ikiUYA1PWbnT21ODyBbISUjZcsVBq1c64x0+0eyjD3F4cIp6D1JrOv7D+zNKuI4NUT7Kc4jBy2T2FVpLAxHQobuR4E27d4OMH61DbJuzpbCPUUlZr2e3kQjjyh0NXsY44rnbVfsPidbSzuXmgePdIGbcFP9K6LjrjBPariWhD0rvdF/wCQRB9K4I9K73Rf+QRB9KioZ1ti7XK+MvEOr6PCTplmhhQjfcScrz2A9a6ofTNcv8RJ4k8JzxvPGsm9TsJ5P4Vgcxb1zxDJo/hi21BYxJcXARI1PTe3T8Ky21rxBoWo6aNce0mtNQYR7okIMTnoK0bzTbDxB4QtLWe6RFWJHWVXHyOBxXJ67p95Lquh2EurJfypcI+yI5CoP4m96APTHYIrPz8gJ474rz4eKfEN5oV1r9vPp8VnbuQLWRcuQDjB967i51GCFLoI6yTW6FnhU5bGPSvLho0eraHceJVv7e2dpTN9h3fuvlOMMvrQwPUdNvDf6bb3RjMbTICUP8NWh94fWs7w/qL6t4fs7x4fJaVOY/pWiPvD60xM4rxJ/wAhmSsqtXxJ/wAhmSsqumGx2x2QDt9ax7q+vrrVX0/TDHH5KhpZHGV57VavF1Q3Cmymt0g4yHXJrN0uQWvia/iu5FR5EVlJ4DUmwky5oupT3clzbXaqtzbN8xQcMKtX32xowun+Wrk8tIMgCsrR5UbW9VugV8ghVEmflyOtat55FzaiM3ZhEmCro+0n6GhPQL6GfpuoXo1qXTb8xSOi7lljHH0NReIdcuLCVYbFUeRRulLDhR6VWsg2leIJba1kF550Rcsxy4I6Ams29mvLfSLkXWnyCaaTLzFuD6Cpbdibs7eFzJbxOeroG/On1U0uV5tMt3kiMTbANhOat1oti1sd14a/5AkP40UeGv8AkCQ/jRXK9zne5uOMg/yrETQrZdcbVyJGu2j8oFzkKvt6VtuflOKqNIQRk4Y9ialGQm08cHijafQ0pZs5J9wKN7f3jTATafQ0bT6Gl3t/eNG9v7xpgJtPoacinevBpN7f3jSo7b1+akHU4HUrW4bUpyIJCNx/hNVvstx/z7y/98mrmo390uozgXMgAY4Garf2hef8/Mv/AH1XTG9jsV7DPstx/wA+8v8A3yabJYzyxtG9vLtYYI2mpf7RvP8An5l/Oj+0bz/n5lI7803cZkDwfabjiwlx6BTVm50JbuBI5rOVlj+6dpyv0q1/bErSmIaj+8/uh+ak/tC86m6k46/NSEU7bRRaQPDDZyBJBhhsOT9aE0TZZfY0tZRAOwU81aTVbiUHy713GcZVulKdSulXLXUioOpLU7OwamZD4Wht5hLFZTBwc5Cn9avS6fNPE8UltKUcYYbeKdFq80/+pvmkPoj9KWXVriFcy3rRjsWfANLWwdBsVhNDCsUdtKqIoCjaelO+yXH/AD7y/wDfJpU1S5kUPHeSMp7hsg07+0bz/n5l/Omr2Gr2GfZLj/n3l/75NH2S4/595f8Avk0/+0bzvdS/gaQ6heHH+lS49C1Gtg1sd7ZqwsYAVIO0cEVPtPoahs5HNjCSxyVHWpt7f3jXM9zjluJtPoaNp44NLvb+8aTe2R8x54+tIRjal4R0rVb37VeWm+fGN3tVjT/DthpcEsFtb/uphh1bkGrk97BaL/pNzHDnoZHxk1KkokRXjkDIRkFTkUAY1l4P0jT7oXNvaASIcoG5CH2FXv7JtRqkmoG3Bu3QIz46rVg3SLOsTToJiPljLckfSpNzdmJ9eaAMF/BGiyXRlazzubcU/gJ9cVa1Tw3pusRwxXtqHS34iAGNv0rRluY4E3TzLGpOMscCh51ij8ySRUjH8THgD60AZemeFdN0i8+1WUBSXG3PtWttP901HBeQ3as1rcxzDoWjbIFS72/vGgBNp9DRtPoaXe3940b2/vGgCtqSsdKugFJJj4GK4L7Jc4/495f++TXfalI66XcsHIITg1wY1C8I4upcfWtaRvR+Eb9kuP8An3l/75NBtLgqQbaRgeCCh5p39o3n/P1L/wB9Uv8AaF5/z9Sj/gVa6m2plx+F4I5vNWwfIbcBsOAfpVp9IZ71LprSQzIMK2w8Cpv7YmM3l/bz5n9wSc0/+0LwDm6m9uaLMLMzrrwzFezGSezlZjyflPNSf2Ahsvsr2TvDnIBQ8VcfU7mPHmXjrn+81K+pXSqWku5AF7lsClZisyhaeHUs5fMis5TJ2dlJK/Srv2S4/wCfeX67TRHq1xPzDfM/rtfNP/tC8/5+pfzpq41cZ9kuP+feX/vk1p+HbeZNXQvDIox1K1n/ANo3n/P1L+dafh69uZdVVZJ5GXHQmk72Jlex2BVs9DSbT6GlLsD1O360b2/vGubqcnUTafQ0bT6Gl3t/eNG9v7xoAzdX8PWGuiIajbCbyjuTI6GodO8K6bpNz9os7dlkxjPpWrLcJboXmmWJBzuc4FJBdR3KeZBOkq+qNkUAYtz4I0a6uDPNalpCSc+hNXZNAsZfsfm2+/7H/qPVKuy3KW4UzzrFk4XecZqTeTkhjx1waAMvVPDen6zMk15bgzJwJB1I+tPPh/Tjpf8AZxskFoDnywOM+v1q9Ncx28XmXEyQp3Z2wBUY1K2MH2gXkJgHBk3jaPxoAztP8J6Xpk4uIbbdOBhXfkqPatcg56NxVZNYsHcJFqNszH7qiQZNWtxKjJIHtQAm0+ho2n0NLvb+8aN7f3jTATafQ1leJY3fSQqIzHd0ArW3t/eNZXiSaSLSgySFTu6inHdFQ+I477Jcf8+8v/fJo+yXH/PCX/vk08aheYB+0y/99Un9oXn/AD8y5/3q6dbnWr3KF34ejvpRLNYy+ZjBIU5IqR9F32YtPsbiAEEJsOOKsyavPB/rr9o89MvjNOGo3ZA23MhDcj5utTZisyndaELyFUmsnIj+4dhyv0pLbQFtFcRWcm5xh2KnJq3JqtxCu+W9dAOm58ClTVLiRN0d47r6q1O2o7amdD4ZhgnEq2UrOORvUkD6VofZbjr9nlz/ALppTqlyjhGvHVzyF3cmnf2jef8APzL+dCuJDPstz/z7y/8AfJrX8LwTR6qS8UigxnquKy/7RvP+fqX/AL6rX8M3dxNqhEk7uAh4JpTvYU9jq9p9DQyFlKlchhggil3t60b2/vGuY5Opzg+H+gqSFsiu47jtOMmrV74T0rUYraO6tS4thtjJ7CtI6jbCc25vIfOHRN43flTri8htADdXKQhjgF2xk+1AGbp3hbTdKlkks7co8i7Gz3FWINDs7bTZLCCEpbyEsyjvmrMF/b3X/HtdRylfvGN91Tb2wOTzQBg23gjRrW5WeG1ZZVOdw6nFbuGbGQcdcVB/aVqJ/IF5D53Ty943Z+lWNzA9Sf6UAIAc9K4rXbed9YlKwyMOOQtdsHYkfNXF67e3MWrSqlxIo44B4rSne5rR3uZv2W4/595f++TTJbCaeF4nt5drjB+U1N/aN5/z8y/nR/aF4f8Al5kz2+at3dnQZUXhSCKUSR2UquOclTVtdIKXT3S2komkG1jtPSrA1S5Ziv2xyw6ru5FO/tG9zn7VITjgZ60kmJGYvheBLjzfsMjNnIBUkA1Zu9IN9B5VzaSSIPugocqam/tiUS+WNQO/+6X5FSf2heDObmUZ96VmCRSstCWw3G3s5VY/efackVa+y3H/AD7y/wDfBpV1W4kBEd67bTg4anf2hedRdS/nQrhqRm0uMf8AHvL/AN8mu50ZGXSYAykHHQiuJOo3mP8Aj5l/76rt9HlkfSYGZiSRyc9aioZ1di5tPoaydT8LabrM5lvrdpG6Hmtfef7xqG4v7e1Krc3UMJb7odwM1ic5nxeGNPh097FICIHOSPSnaX4b07R5Wms7bExGPMblsfWtNZC65V9wIyO+fpTftSG4EXnoJsZ8vdyPwoArQ6RawajcXyQ4ubgYkcdWFZreCdGadpfsWFY7miH3CfpW6HY9WI9ag/tG2M3k/a4RP2j8wZP4UASxwrDEI402xqMKqjGKeFORwetBZvX6mgMxPXjPTNAjjfEVvM+ryFIZGHqFrL+y3H/PvL/3ya1fEF7cxatIsU7qvoDWb/aN5/z8y/nXTG9jsjshn2S4/wCfeUe+w1UvNBW/KvcWcpcfxBTmrx1G8GD9ql/OmSatcQ8zXrIP9p8U3cp3Ky6Eq2TWq2LrCeqhCM02fQEubaOGWylKxDEfynK/Srq6ldOu5buQp1yGzQ2pXags13KB7tRqFmU7LQRYsWt7OUO3Vtp3VNcaY91CYZrWVoyckFakj1aeY7or5nC9Sj5waSTV5oSBNfGMn+8+OKVnsLUFs7hY1UW8uFGB8p6Uv2W4/wCfeX/vk04alduNy3UhU9MHij+0bz/n5l/Oqux6na+HEdNFhDKynngiil8OzSSaNE0jlm55NFcr3Od7my+SGAHOOPrXjt1dWf2vWl8S3t7baosh+yxpIVDL/DtHfmvYZt3kybPvbTj615LbnTmh1ZfE9jdy6m0jBH8stx/DsPaoRmdz4VF8vhmy/tX/AI+/L+bPJ9q1u1YPgpL+Pwva/wBpbzKRlBJ94L2z71u/jmqELRSUUwCnJ99abTk++tK4dTz3VP8AkJ3H++arVa1P/kJ3H+8aq11R2O1PQKR1DoVYkKwxkUtNkcxxM4XcVGQvrTYzmNf0q0sLSI2gcXjSARkN8xOa1dXupFggs4CftVyAuRztGOSax7O9mbUnvdQsbhpQcRIEysYrUn0dr28XUIrl4XZNu0jpWbuZu5B4Rh+zQ30O4sIrgjLfStW/hgns3FwZPKB3ELWN4esLuyfUZZXdtsrEIwx5nHWtI6lMdMW6aycsfvRdwPpVRbsNN2MbTfslx4qi/sotHEqfvUPG76VE2oWd1rN5JqS3EqwtsjijUsq47mrahtU1uzntbSS1SAkySMu0t7UQSTaBqV6r2kkyXDF0eNc8nsam7JuzZ0yS1lslaw5hJ4Hoat1k+HbKWysHM6hHmkaTyx/CDWtWivY0V7BSdqWg9KOgdD0Oy/48IP8AdFT1BZf8eEH+6Knrle5xy3Ck6D+VFHU9ePSkIx9X8NaVqM8t7qYdvLiIYM/yqPXHrWH4Cuv7P8L6ldXErmwjuHa1Mh6xjoM1H40v9QutTg0tbO6Ol/fuZYUJMn+zV42sHizw82lxwXGmW8WNoaPb09qAObto7ufx3oGsXZcPfSSeXGxwFiA4GK9Px8wX17+ledan4U1RPFOhFL+aaGNmzME4iGK69r24m1KfSGtpBD5HF4OASf8ACgDifG88viFLi4id10/S5QiFTgSyE8j8K0vGKzR+HNGu5S7afEEN0itgsP61T17wNe2Phia3sNRlmXzA/khOSSeTU2raVqNlZ6DLMsuo2dsCbqEDk+nHfFIBfCEtnqvjCa+8PExaVHFtlhY7dzHodtd9+NcPpkJ1Txvb6npWnTadYxQsk4kTy/NJ6fLXcZpgLSUUUwK2p/8AIJuv+udef9q9A1P/AJBN3/1zrz7tWtM6KHwi1S1i5a00m4mTghcA+mau1V1K1+26dNbjq68fWtWas5+40mKDwwl4hb7YoDmXdyea6Oxna4sLeduWkQE1zrXF7daOmk/Y5Bc8IzkfIAO+a24ZJLS4ttPWFmiCYM3YVCfcmL7mL4osSjW9y08jMZ0AXOABmuhvrKK/QRTl9mQcKcVg+JriW4EVvBaTuYpVcsF4IBq9qGrXR0k3FlayiVzt2lfmX3xSuhXRTs7aO18XeTYZ8lY8zqDkA9q6M+vrWBoM8dtiAWlwJpuXndfvH3rf6GqiUgrV8N/8hhPpWVWp4b/5DCfSnLYJ7HbHqaSlPekrm6nH1FopKKAKGq6Jaa2IUvRIyxNuCq2A319a5fwtbRWnjvV4dLdxpcUKh1JyiyZ5xWl441PU7HTY7fSbeWSS5Ox5Y1yYl71V8OyW7aa+i29jeWglQh7iSMguSOSTSA5zxrNP4gil1RJJEsLC6jht8H777sMfpXqEIzbxDvtFeceJfA9/Y+FltbC/luUSWPEKp/tdfwrrhdXeix6bZmGS9M/yyTD/AJZ49aAOV1rV7K98c3UGrrdy2VhGvl29uhfezdSwFdHo0Ph/XNFlh06Mm0L/ADwMMFT7jtWbcNceFPHF5qYsZbqxv4lXdCm5kZfarPg6yubJtV1e7tjAL1t6W4HIA749TQBjav4d02bxnpek6XB5TxH7RcOv8IHQZ969FOBwO3Fcr4L065D6hrGpxsl5eykBW6qg+7XVfjQAUUlFMBayPE//ACCB/v1rVk+J/wDkED/fpx3RUPiOL64BpRy36Un1pQcEMfyrqOw53T7OPWdUv5b0F1ikMKLnhR6/WpvDErKl5Zs7MLeYhC3J21DFJcaDql7utpJ4p281DGM/MexqTTo7rS9NuLyW3Lz3E2/yl5IBrJWvqZq19S7q8ViUjm1AOUjPAHIP4VmeFtklzqElo5FmxAiVjyp78dq0r7UWtViaSzklicchV3FT9KpaRBJLrNzqCW5trZ1AWMjBY+uKbtfQbtcgex+xeK7FjK8ksyOWJOR7Yrpq5e/1CaTXrW5SxuDHbqyt8nXPpXTRv5iK+CoYZweopxuOO47NbPhT/kLt/wBczWNWz4U/5C7f9czRLYJ7HY0hGVI9QRRSM21GYDJUEgetc5x9TgfGnhzStH8OvcWxmXUnlX7PJvy7OW6UeM4XEnhqTU7e5uLeNs3QgQsfu+lVLXVbu68QSarrmkXrtCxW0t1jJRB/e+tdfe+J2sI7aY6bdSxSru+RCWQ+hFICDwnceH5xcf2EjROv+tjkXa4/Cn+OdWk0bwndXUDFZSVjDdwGOCay9Atbq98V6j4jayazt2txHFERteQjnJFWNcgvPF3gu5QWZtrpZAyxOfvbTn9aAMrQLrwtbzWcEkd2t8QMXVzGVDt7Meteg4PQ5z6+teeahPe+MLXS9Mj0qa1kt5EeaWZNqptPO31zXoRx/CTx0zQAvU1w2v8A/IZl/Cu5H3ua4bX/APkMzfhWlPc1oszqjuImmgeON9juMBvSpKjmlMELyhS2wZ2gcmt20dLZgaHbCz8Q38KyO4QAZc5JNdH1zjHTrXL6feSp4gublrK4EVxgLlOlbsd5I1/JbtbkRxruEuOG9qlNEpmLr2k2NlpMkyeYLlmHlMWyxbPSr97eT2ulW0X3r2dRGq989/0rIS8nuNWa71KxuXELYgiC/KPeta40s6tcwahHO9vIEwFYcild9Cbso+FrdrPUNQt2kZyj4BPOTXS1zeg6Xd2ut3sk0r7C3Uj79dJ16dBxTiVEQ9K73Rf+QPB9K4I9K73Rf+QPB9KmqRVehd6dOtYGteGtGuTd6nqoc/u/nJfhAPT0rfrgvFt9fX2vpp89hdHRocNIYUJ89vT6Vgcxc8HX76R4Ce91F3aKKSRoN5yzJn5RWNpNpeR/EPTL6+d/tGoW0krJngLn5ePpXRXFjF4x0WK3SOfTYraRWRHTHTpx6Vi3HhbVI/Helv8A2hNLEsD5n2fKnP3aAPQ3Gc9gRj3ry7xbDoVrB9h037RHq7TgxzOSMNnu3pXewapcyareWRsmC26gpO33ZeO1cp4g1X+3tLuNOj8PXAv5TsSRo8Khz97dQB3VsHFnAspDOI13n1OKlHJH1qlpFrLY6Ra21xJvljiCs3qfSro6j60COK8Sf8hmSsqtXxJ/yGZKyq6obHbHZDTIikBnVST0JrAihi1jxJdLdZaC2UbEzwSetat1pdteXCzzh94GBtbFZTLLoeuTXK20k9rcIBmMZKke1TK4SuSaAGtdT1CxDM0URDords0viFmnvdPsN5WO4Ys5BxwKbpq3Vut9qs1uxln+7D32jpRq8VzOmn6nBCTJBy8XcA9aNbC1sR3EEWi+IbNrUFIZkYSIDwT2OKz7W+sLiS4u9USeZ2kKjahZUUH9K00Euua1b3DW7wWlshH7wYZiaq20txpNpd6bJYySs7MYnRcq2fWldk6nR2jwvaxtbNuhI+X2FTHpVDQ7KTT9Iht5cbhliB2z2q/Wi2NFsd14a/5AkP40Uvhn/kCQ/jRXK3qc73Nxz8p61TaGJ2DOquw6EjkVbJHIrkb7xxpVjcyRFLiZYm2yyxJlIz7moRmdIQuTlzn6UbUx9+oILiK6tkubeRXhlG5HXkEVJiqEP2p/eo2p/eplFMB+1f71KiruX5qZSp99aQHGahaWTahOWu2B3HI21W+x2P8Az+v/AN81Dqf/ACE7j/eNVcCumOx2JaGh9jsf+f1v++aPsdj/AM/rf981QxRj8BTsOxofZbL/AJ/n/wC+aPsdj/z+t/3zXNR6/azamtlEGZj/AMtMfKfpU2oarHYTpbiKSa4cZWNBk49TS6C6G/8AZLL/AJ/W/wC+aPsllnP25/8AvmsDTdVi1LzEEbxTRnDxuMEf/Wq/xnqAPU9Ke6HujQNpZHrfP/3zQLSyHS+f/vmubttetrvV3sIlYupI34+WmXmvfZZZFWxuJEi++4XgUr6C6HT/AGOx/wCf1v8Avmk+x2P/AD+t/wB81lWl1Fe2yTwHKOMjNTU1sPoaH2OxP/L63/fNIbKx/wCfxuO2Kz8D0oIH5UdBW0PSLVU+xw7XyNowcVLtXP3qrWX/AB4Qf7oqeuZ7nJLcdtT+9RtT+9TKKQiQYHRyKCFPV81g+I/Fdj4aiH2kSSzkAiKJckD1PtVttatYdCGrXDeXbGPec9R7fWgDTwuMb+tGFxjfxXJ2vjqCS6to7uxubWC7OIJ5Ewp+tdTj6Y9aAHhVB4agBQch+a5K+8crYSyvLpN8LKF9kk5j4HuPati81+wstKj1CWQmGVQ0YUZZ89MUAap2t1fNJtT+9WR4c1+HxJpP2+3ieNPMaPY4wwIrUoAftT+9RtT+9TKKAI9QRDptwrPhSnJriRZ2Izi9bI7ba7LUv+QTd/8AXOvPccVtTN6K900Psdj/AM/rf980fY7H/n9b/vms/j0pcc+v0rRm1jQ+yWWMfbn/AO+aPslljH21v++a52+1mO0ufs0UMlxPt3FYxnaPeptO1KHUoGkiDKyHa6MOVNK4jc+y2Q/5fn/75o+y2Wc/bn/75rHvb2CwgMs5OP7qjJNRaTqUer2RuYUKLvKAN14o20DbQ3fstkf+X5/++aT7HY/8/rf981zUniK0XU47JAzux2lgOAfStYjBpgX/ALHY/wDP63/fNaOhWtrHqitHdF2A6Fa5/Fanhv8A5DCfSlLYUtjuCq5zuJ9sUbU/vUw9TmiuY5Oo/an96jan96mUUASAKvR8UHBHL5rO1bWLTRbM3F4+B/CijLOfQVB4f8QW/iDSnv4o3ijRiGDjBGPWgDYAUdHoAUdH61x8vxAtkDzxWF1LYRSeXJcqnyg+o9q6m3njureOeFg8cq7kYdCKAJxtXo+KMKTnfzXN6n4ouNPv2to9FvrkAf6yKPKmoNO8bpqmnXlzbabdu9q4R4QnzE+1AHVlVJyWpNqf3q41/iAILi3ivNGvrYXEgjQyR45NdeOQPcUAP2p/eo2p/eplFMB+1P71ZniGKGTTAsspRd3UCtCsnxP/AMggf71NblQ+I5wWdjjAvWx/uUfY7H/n9b/vms7sOKXGcV0HWlqaAtLIdL5/++aPsllnP21/++a5u81yO3u2toLeW4lQbn8tchRVqwv4dStfPgzgHDKeoPpSuSbQtLIdL5/++aDaWR63zf8AfNYeoah9i2KlvLO79Agzj61Fp+sQ3yz5jeKSD/WI4wRRsNnRfZbP/n+f/vmk+x2P/P63/fNcnB4k+1HMFhcPHv2+YF4rbByoOMZFOII0Psdjj/j9f/vmtXw5bWsWplorhnOzuMVzVbXhTH9rtx/yzNTLYU9js9q/3qNqf3qZQSFUsegGTXOchLkf89DSDAPD1x9x4/itJPMuNKvo7HfsNw0fAOcZ+lauseJbTSLe3ba9zNdHEEUIyz0AbZCk5L5oIUnJesHRPE8GsXc1k9vNa3sK72hlXBK+oq9qt++mWD3MdtLcsvSOIZY0AaBwRguTSbU/vVxknxCFtcW0V5o19b/aJBGhePGSa7EjBx6daAHBVBG01yOtWto+qytJdMjccba6wda4bxB/yGZfwrSma0hv2Ox/5/W/75pfsdj/AM/rf981n0yWRIImllIWNRksegrZnQzU+y2X/P8AP/3zSfZLLH/H63/fNc7putwanczRQo6+V3YYzWl06jjGaECND7LZf8/z/wDfNJ9ksT/y+t/3zXKz+JFt2LyWNytsG2mUpwPerl/q0FlFEyq0zzf6pEGS1K4rm/8AZLH/AJ/W/wC+aPsdj/z+t/3zXPWGrre3L2skEkFyg3bHGMj2rQ/CnuG5oGzscf8AH63/AHzXZaTHGmmQqshK44OOteenpXe6L/yB4PpWdQzq7GhhTxu/SlGAOHNR1g+IvGFh4cIjnEk0+QDHEuSgPc1ic50RCnq+aMLjG/isy+1q003Rl1O6YrCyhgAOTnsPesmx8aw3GowWl5Y3Nkbrm3eZcK/t9aAOpwuMb+KXIxjzDiom+XJPQD8a5K4+IEVpIZLjSb+OxD7DcNHwDnGfpQB2G1P71AVd3U9fSo0dZI1kRgyMAwI9DSqPmGPWgRy2u21rJqkjSXRRvQCs/wCx2P8Az+t/3zUviX/kMycVlV0w2OyOyL/2Ox/5/W/75pRaWQ6Xz/8AfNZ2Pas+/wBYjs7lbZIZJ52GdkYzgeppjOh+yWWc/bX/AO+aPsllnP21/wDvmsPTdSh1OJnjBRkOHRxgil1C+FhCriGSVm4CoMmgDbNpZHrev/3zR9lsgP8Aj+f/AL5rndO1mO+uHt3hkt7hBkxyDBI9qrT+JFt3Znsrj7Ohw0u3ikB1X2Ox/wCf1v8Avmj7HY4/4/W/75rNjdZokkTlHG4H2p2KfQfQ9A0COKLSIljl3rzzRUXhr/kCQ9O9Fcz3Od7m1OnmQSIDgspGfwrzHTp7vw1pWqaVe6FdXTSGRhPFGGRgQeSa9Qf7rAdcVxeo6b4o1HzbNr22gsJDgyIT5m3uKhGY34bs58FWu/PGdmfTNdT71X03T4dK06CxtgRDAm1TVj/PNUIKKWigBKcn31pKVPvLTDqee6n/AMhO4/3zVarWp/8AISuOP4jVX8K6Y7Hatgo6/lR+FB6YA6/p702xswb2NI/FdgIkCrs6Ad6l1C1vYNcj1GziWUeX5bKTyOetRzaDfTX6Xbai4lj4XCjgVdu7PUJFjNtfPGQuGG3qfWo6EdDM0eWefxZeyTRLExgHyqffv71e8RakNO08LvCPOfLVj0X1NTWOkrYwzDzWkuJsl5z1JNS2dmYbRYbhvtLL/HKoOKEgSOasbnTrXxFbLBdRtGIwpk5+Zv8AGt3W7/7LaNbQKJLm5BREHXnqacdHg/tlL4RoNq7fLCDB96oSeH7v+05b6LUXjkc4Hy52j0FJKwbGnpFj/Zumw2zHJUfN9farlV7GGe3tgl1Obh8k+YRip/1rRbFJ6C0dqPwNIe3JPPpRdWHdWPRLL/jwg/3RU9QWX/HhB/uip+9cr3OKW4lL/n60UhOBk/hSEYHjeGM+E7+Yxr5oQDft5Az0zVS60aXXvhtDYW5CzPEjKzdCQc4q54m0C+1+FreDUntbZ0CyRhQd1Gm6Fqen6K9idXlZ1ULDJtH7ugDkPF99rU/h+wtL3TooDHcRLvB9CPuivTgDtUNjoM4+lczbeFLqfU4LvXdTkv8A7OcxQkYUH1Nav9m3B1uW+N7L5EkQjFuB8qn+8KAOc8cQ+JLnTbmOKO2XSFG6bY2ZWQdQBW9ojWN/4bspLaJXgSACMSLnaMfzrKu/CusXQmtW8R3H2OYkFNg3bT1WtObRJrfRYNP0a7ezWFQoYDOQKAMr4a/8izOQMYvZsf8AfVdb9K5jwt4XvvDblDqj3FqzM5hKj7zd66agAopaKAKup/8AIJu/+udef9q9B1P/AJBN1/uV56OeK2pnRR+EXse49PSqN1qptLpYfsN1MDj5o1+Wr34UoJHStGaswdCYt4g1JjkSZAGeuKTRONd1QLym7PH96rN5o0j35vrG6e1lZdrYGdwp0GjfZbCWCCdxPK2958ck1PUnqaE0ayRsXVXIBwSM4rG8JcaVOcY/0l6vz2ly9hHDBdMkijDSY5aqujaPPpLlTeNLAWL+WR1Joe4Pcra3Gqa1pIRVQFmJwMZroDyT9awr3Qb29vEnbUJMxMTENv3fatmFZEhUSuZGHDNjvTT1GtyStTw3/wAhlPpWX+Fanhv/AJDCfSnLYJ7HbHrSUp+8e1Fc3U4+olFLRSAhu4YpraTzY0k2IxXK52nFcr4ChNz4T1CA8GaaRPpkYzXQaxZ3l9Z+VYXptHPDMozkelY/hrwtf+HvMibVZJoHJbYVH3j3oAwWj1zw94LvdGm06CWGONwJy2AVx1PvXU+CRIvgzSxLnJgXGfSqVz4U1TUiINV12aaxL7jEFA3j0Na97pMk01h9jumtYLTgxRjh17A0AM8Ua0dD8PXFyjESkeXCM9XPSovB+kto/h2CNyftE2Zpn7l25Ip2ueHl12+sJLiVkt7R/MMI6Oe2fpWvKJHSQISjleD6e9AHH7j4n+IRJJex0hcezSHp+VdkTktk1keG9Bi8P6e8EchmklkaSSZurkmtegBKKWimAlZHij/kED/frYrI8UD/AIlAyD96nHcqHxHGClX74755pvOBil5H3RyK6W1Y7NDD8NHN/qbf8tBcEY9RTfDYP2nU1H+r+0MQB0BqefQ5ft0lzp949s0wxIgHX3qWPRvs+lm0tp5I5Gfe82OWPeos7kJFq8N4If8AQFjaXv5hwBWHoYkTUtQt77jUJlG4jkFe2K1L2xu5hGbW9khdOvHDe9R2WjNbyT3E1y813Mu0zMOV+lN6sGm2Zvl6p4a05nidJraNyzITg4NdFBKJ7aKYDAkQNj0zWRJoV5dDyr3UpJLcHJXb972NbKIscaogwqjAHoKIjQ6tnwp/yF2/65msb8K2fCn/ACFj/uUS2FN6HY0UdO1IwLIyqdpIIDDtXOcfU5PxldnV0Xwvpw8y4uSDMVGVgQHOTVea3W1+JWkWhx5cFmBHnse5plh4F1jTJriez8QzI1y5d3KAn861tU8LyanFYzjUJItUs+UuwOX+opDKV+D/AMLWsimNxtvnPfHbNdgM7xg4PfFc/o/hl7G7udQvb6W81G4j8rzmH+rXsBV7TdOubHS5baa9kuJn3bZnGCuen5UAc9G58UfENnJ8yy0dcKp6NIeD+VdlnPXnHf1rI8N6BH4d094EkM0sshlklbqzGtegAHWuG1//AJDM34V3I5IrhvEH/IZlrSma0TOpCquCHUMpHIPI/Kl/Co51d4HWJ9jsMK2OQa3OlmNpi7fFWohVAwBwBx0rd9cHGe/pWFa6De29+12dRkZ5CPM+X71acVrKl9LObhijJtWIjhT60kyUzP1+4a6T+yLRQ88+PM9EX1qvrkAg/s63smb+0YiPIx+uaLfw7fWs00sGqSK8x3MxUE1cutGkufs8y3ciX0AwJQPv1D1JepS0hpV1+YavzqDphGH3QnoK6P8AP8ay7PR5E1D7beXD3FwF2pkYCCtTOcntmqiVEQ9DXe6L/wAgeD6VwR6Hiu90XjR4PpU1CKuxdrl/iBDGPC08wiXzWdQZNvzH8a6j/OK5zxN4av8AxCGt49UeC1bB8oKOCKwOYZr+i3Gu+C7GCzK+fEIp1DdHKjpXOeKL/V76XQIb7To7bZeRgMD8xI9PautttG1S30U2g1iXz1wI5doyoHaodP8ACtwNVj1HXNQkv54RiFWGEQ+o96AOjbOcnr3965HxndtrCr4X00GWe5I+0FR8sMeck/WtuHTbmPVb27N9IY7gYSBhxFx1Fc1YeBdX0ua4lsfEMsbTvvdmQEn2zQB2dtbra2kMCdIkCA/QYqUdR9ahtI5YbSOOeVppAPmkIxk1MMlhj1oEcV4k/wCQzJWVWr4k/wCQzJ61lfhXTHY7Y7Io3mqGzuViFlczbgPnjXKis/RHMnibUXKkOUXhuoFb4Ygd8VlXujyyX/2yzujbXBXaxAyHHahg0V9ICjxJqwThSFI9M1tSSJBG0krBUUZYntWdb6MLWxmjinkNxOcvORzmmanos2o2EFr9rdPLxuYD75HrSF0IdKSTUdZm1dlKxEeXDuHJHrT9eujND/ZVou+4ueHAHCL3NS2Gn39rKvnag0kKrjywoA9qpReHb62uZ7iDU5FaU5Y7QT7CgVzctYBa2sUAPEahfyqWordJI4FWaQyuBy5HWpD06Va2NFsd54a/5AkP40Unhr/kCQ/jRXK9zme5uvyp+lVPM/i2j0q03IIziuA1/wASa1Y63Zxw2aQafJceVvk+9J7j2qEZHa7sEjaAKN+APlFc94p1y50v7FY6bGj39++yPf8AdXAySapWGravpXiW30jW3hmW8UmCaPruHUGqA67f/sijf/sim8dulJQA/eP7opUf5l+UVHTk++tAHF6hqSpqE6/ZIiQxGar/ANqL/wA+cNRan/yE7j/fNVa6YrQ7EtC//ai/8+UNH9qLn/jzhyaoUh6Hr06epp2GaH9qLj/jyh/wpf7VUk4soSfauOF5qaeJII7t1jilGREnp71Y1G4urrWo9Mtpzbgx+Y7r97HoKVxHUHVFGR9ih49aP7VU8fY4ea5bSLq5j1O60y7l84wrvWQ9SvvWnfJPLatHbTCJz/Gf4RQgRrnVAODZQgUDVRx/oUOMVx1rLeWXiOGxa8a8gmXLscEp+VRB7y/1m8hGqNaxw42rkDNK9xXO2/tRf+fOH1zSf2qv/PlDWXbRvDbojymV/wC+epqWrsUkX/7VXtZw0f2qMEfY4cVQoNJpWBpWPR7WUNZQkIoyo4qXeM/dFVrL/jwg/wB0VPXM9zjluO3/AOyKPMAzwB70ylpCHB+eF5z0o39iorlPG95rdpps0ukyRQwQoGkmb7x56Cn6h4guNL+Hyar/AKy4MajL/wB5jjNAHUFiFBKbcfpQXweVAz0rgL6fW/C9vp2r3GrPeQzuqzwPjau7ptrvQeAy87hke1ADtx6hOKN3GNgz6VwniaPW9JsrnVV8QESxvmO0Uja4/u465remvNWu/DtpNp0USXlxCrSGXOEyOfxoA3fM7BBx1o3jsorl/AGo32peHGm1K48+5juJI2c+x7V0v0oAfv8A9kUb/wDZFMooAi1CXZpty+xThOnrXFf2qpGDZw12Wp/8gm7/AOudefdq1po3o/CX/wC1V/58oaP7VX/nzhqhQBn1rWxvY0BqY6ixh/wpP7VXn/Q4c1ykst5q2szWltcm2igHzOnUn0qbQr2eZ7i0umDy27kb/wC8vrS6k9Tpf7UXtZQ89KP7UAxusoTn9K5rWrydJbWxsn8ua5Yjf/cAqC2mu9M1uOwurhriK4UlXfqCKG9Qb1Ot/tQZx9jhpP7VXvZwj29a4rxDq92k2ywkMcduy+c4756CujhYtBG5zllBzQtwRpf2ov8Az5Q1o6DqCzaoqC1iTI6iufrU8N/8hhPpRLYUtjuC/bAxRvH90U09aSuY5Oo/f/sijf8A7IplFAD9/PCijeF42gAfzrL12TUksGGkLCJyDmSX7qDFZHg3Vr248KXV3qMxuJ7ZnO71CjOKAOsDHH3MetJvB42jHpXnUM/iDU/DU3iWHVniKEypaLjyyg7H3rtND1Iazodnf4AM8Ycr2B9KANIMTz5dGT02cjt61zWq6Jqc93Ldw+ILmzgVcmNQNqgVj+E11rW9Avmm1e4AacpbXBA3YB5/A0Ad6SR1T9KTeP7orzrVINf0jXdLsYPEF1cz3MgZ42AwIx96vQyMHGc0AO3/AOyKN/8AsimUUwH7/wDZFZniC5EOmbjEr/N0NaFZHij/AJBA/wB+nHcqHxHODVVPWyhpRqq5B+xQjis6l6kehrosjrsi+NUDDH2KE+lKdVHObKHjqa5DzL7WtSuo7a7a1gt22KV6lverWg38t5BNFdY8+3kMbMOjY70la5KsdL/aq4H+hw/SkOqLnBs4cVi6nfLp9m0p5kb5YgO7HpWX4bu7+4N6l7JvlToD0QntRpcelzr/AO1AOTZRCk/tVf8Anyhri9SXVNKgW9a/L/vADD/Bg+ldHE5khRyMFlBIpoFuaP8Aai4/48oa1fDt+s+plRbRp8nUVzfatnwp/wAhZv8ArmamWwp7HZ7x/dFHmY5Cim0hztOOuDj61znJ1JN2OSnB6elIHz0QcVwXiG38RaFpc2tNrbO0LhjaD/VMpOMfWrmsa1qGoXelaVpsv2Oe9jEs8w+9GuO1AHYl8Zyo96AwPAUHPpXIaRe6lpHi1tB1K7a+iliEkMzfeJ7g10Oq2dxf2LwWt3JZyn7sqdRQBf3EdU4A60m/PG0ZrznU4Ne0vXtK0+38Q3V1NdSbnjYDAQdc16IxAPB+nvQA7fkjKjiuR1rURFqsqG1ifpya6wferhtf/wCQzN+FaU0a0Rv9qr/z5Q0f2qvayhzVCo52kWB2hXdKB8oPT8a2Z0M1Dqi8D7HCfek/tVO9nDx61yei3V++s3lteyg7ACFXoK3exHGcd6EJGgdU6/6FD7j0o/tRf+fKHmuL1YX+n2r3o1IM6sMW4PynnoB1qXW7y526WkU5tGuW/eP6cVNxXOuOqL3sYfb3oOqr/wA+cNYOmWk9uWMuoG7B+7kg4q/9BxVIdi+dUXH/AB5Q12Wkz79MhcRqAR0HavPT0Nd7ov8AyB4PpWdQzqrQ0PM5+6KUseRtGDUdcj45v9dsbQzabJHbWsTDMp+8xPYe1YnOdl5nP3R7UbscbMA84rm9e1i703wYt/arvuGiXcwGdpI5aufiv9U03UdGa31qTVBqBXz4GwRGp6kY6Y96APQw4P8ACCfWl3HB+QVXvpxZ2k87AssSlgB7VwMVxr994Yk8UpqxRlJdbRf9VtBxg+9AHovmd9o5oD5OMDGaz9G1FdW0e1vlGPOQE/XvV4dR9aBM5XXtQEOqSIbWJ/c9azv7UX/nyhqbxJ/yGJKyq6YrQ7I7Iv8A9qqP+XOH60o1VR0soQPas8Angd+1Yc815qmtS2Npcm1it1Bdl6kmiRTOsOqAZzZQ/T1pP7VXB/0KEY71zGhXlxJNdWV2/mS2x4fuQelaN5dx2NpJcS5IRTgf3j6U1sI1v7UUDmyhHcUDVF/58Yc5681x/h6+v5tWuor6QsAokRf7gPaq2n/btVmuWOrmALIQqAgcZqbiudydVXP/AB5Q0f2ov/PlDWdGCsagsWIGCT3pxq+hXQ9A0CfztIifylTOeBRUXhr/AJAkP40VytanM9zbflSK4D4gXMP2rQlNxEGW7+YbxkfX0r0BuATXMXngjRNQupLm60+KWWQ5Z2J5NQiDG8VzRWvi/wAM6jLIhtFkZDKDlQSvrS65NFqHxB0CG2lWQ22+SRozuCgjjkV0b+HdOk0oabJZxvZjhYzyBRpfhzTtFLnT7RYXbhnByTVCL54Y569z2pKeI3HYY9M0eW3oPzoAZTk++tL5ben60qI29eKA6nnep/8AITuP981WrV1HSruTUZ2VFILE/fFV/wCx7z/nmn/fYrpi9DtT0KVH6Vd/se8/55p/32KT+x70jAROeuXHSquM4/UL62bxTZOJV2IuCfQ1e1S1sLu5jnkuntbhVysqHB21rnwghbcbCAt6lxmnzeFjchVmtIX2fd3OMAelS9iGtDlfD8SDV72+SWWW2VNnmydWI6mtibULCfT/ADZJv9GkONwBrYXQrhI/LjgjWMjAXcMYpn/COS/ZxALaIQjom4Yo6D6HHJFbWHiG0GjymTz8+cmcgDsau6jDoM4uJJwgnUEMwJDZro7fwy9k2be0hQnqQ4pj+ExJN5slnC0nXdvFJLQVtDG8MGf+xENxuJ3nYW67e1a1XP7HvAABGmO3zjFL/Y97/wA80/77FUnoUtilRV3+x7z/AJ5p/wB9ig6Pe8/u0/77FF9A6HbWX/HhB/uCp6jtIXSyhUgZCjPNTeW2elcz3OOW4yjj168c0/y29B+dHlt6D8aQjmPHl/bW/ha8t5ZVWV0GxD1bmk02TStV8DxW15KklsIQsv8Asmty80Sy1GUSXlpHPIBhS3YUkWhWEEEkEVnGsUnDqO9AHm2u6PaXE2naVpusXmpSNMrLCzZSJFOetekDVbFNRbTxOPtUUYkZADwvrTrLRbHTCWsLOGAnjKjmphp8IuzciFBOw2tJ3I9KAOD8U23hjULG71JL5lvYQWjZCdxkHQbfrXR6Lqsi+ErS61l1hmeEbs8Z4/nV5vDeltdfam0+Dzs5345zVm70yC/hEV3AkqA/dagDkPhlqFq+hzWyzL55u5nEZ67c9a7SqlroOn2M4mtbKKGQDG5auiNvQfnQA2in+W3oPzo8tvQfnRcCpqf/ACCbv/rnXn3avRNRid9MuUUDcyYHNcR/Y97j/Vp/32K2ps6KHwlLrnHaqF3ZXc1yskF28UYxlR3rc/se9/uIP+BikOj3h6xp/wB9itGzW5yOnzx6X4ivorxvLEgDq7dDRo88aXWp6lK221Z9u/HX3FdTceG5Lsj7RaxSbemXFOPh+fyPJNvEYcfd3DFKwrHL6vcRwatpWpZJtvmBfHTPSmX039peILUWJDPbxMd/YEjiurfQJ5IBE9vGY8YC7xikt/DstopW2toow3Jw4pWFY4C/h1Sx0Ro5rdPmmDu/ctmut05pX06A3KhZNvQVqy6HdTptlijdOpBcc04aNeKABGmMcfOKaGkUq1PDf/IYT6VB/Y95/wA80/77FaOgaZdQaqjyIoUDqGBok9AnsdYetJTzG3p+tHlt6D865jj6jKKf5beg/Ojy29B+dAFLUr23srKV7qVY1ZGUZ9cVyvw7v7OTQ7u2aVSzTuSh6la6+70y31CMR3kCzIDkKx71DbeH9Ps5PNtbKGGXoSnpQBwGv6bo+n6Rdpp2s3ZW5yI7CJspvb264rq9DltvDeg6PpuoTCO5liCquPvMOtacHh7Tba7N1Dp8KTnnf3B9aszWEVzJFJPCjyRHKMf4T7UAc1491GWDSItMtNxu9RkEK47IfvGt7TLCHR9Lt7SPCx28YVj2OByanksopZ0nkhR5ovuO3UZ9KleEurKwBDDByetAHGeElbXPEWpeIZlPlKxgtAewHDV2PPX86SCzS1iEdvEsSA8KvSpPLb0wT70AMop/lt6D86PLb0H50AMrI8Uf8ggf71bXlt6D86y/EVrLPpeyNQW3dziqjuVD4jhhSrwVB4waujR73/nmn/fYo/se97xof+BiunQ7DkdIvItN1XUobxvLJlMq5/iFJoM8Vrb32ozuUt5bg7GI6g9DXUXHhl7tla4tYnYdy4zT38PzywiJ7aFol6JuHFTbzIsczqtvf3Op21xaokttGMojd2Pc1S8OT3n9rai9zGqRZzK390iu3XRrxAAsaAf744qNdAuELlYIh5nDjeOaTTvuDWpxp1O11vUg9xMIrG3b5FP/AC0Yd/pXUKwdQy42kZGPSnf8IehyPsMH0DjFW10W7RQqxoFAwBvFNaDRTrZ8Kf8AIWb/AK5mqf8AY97z+7T/AL7FavhvTrm21MvKqhTGejA0Tegp7HUUhIVSx6KMn6U/y29B+dIYmIIIGCMHmua5ydTzm78Qaf4u1wQ3F2sGi2UnzA8G5cf0q7q93b6f480nVHbFhPB5KSAfKCK6b/hFdH5/4llvknnirculWs1mtpLbRyWy8CM9B9KAOSW4h1f4kfa7Rt9rYW26SYD5Qe4rqrHVLLUbRru0mEtuhO5sY6daktNLttPt2gs7eOGI9VXvSw2ENvbtBBCkcT9VHQ560Acj4RR9c8Ran4inB8vd9nts9lXuPrXZ8c4pkFlHaQiK2iWOJeiDpUvlt6D86AGjrXDa/wD8hmb8K7vy2z0rjtb0y6m1aV40Urx1cCtKb1NaLMSkd1iQvIdqjkk1e/se9/55p/32Ka+iXUkTxvEjKwwwLit2zpOR029tz4p1BxKpEmNp9a3FvbdrqS3EoM0a7mUDoKtL4SVJAy2EAI5B3jOanXQLhZTKsEYcjG7eM1KJRxmtRaTPbS38M5F0DlCp5LfStEGzvdPtU1pEMxXcFfjFbQ8JhZvN+ww+YT97eOvrUtz4blvFC3NtDKF6AuOKSQrHKaMsUXiSePTCzWQj+cDoG9q6TGOM5qzB4fnt49lvbxRp1wHHNSf2Pe/880x/vimitiiehrvdF/5BEH0rjzo97j/Vp/32K7TSYJItLhRwAwHPNRUZlVehZrkviLqFtH4bmtnmUTl1Ij712Hlt6D86pXeg2F9L517ZRTSdNzVicxzOu675HgK3k05hLuWOCZgM+WpHJ/CueOn6f4XvdJu/Dd49zd3MqxzQk7g6t1b2r0q30e0tbd4ILWJIpPvIOhqK08P6dYSmW1sYYpPUdfwoGCanYXd3c6f5oeaFf9Iix90EV5/r+m6Rp+iXEWmaxdt55Ih0+I5VnJ6Yr0hdPhW4kuFhQTSDEjjq/wBar2/h7TbO5NzBYxRzZzvHXNAEPh2xbTfDtjaSctFGM47E9q0x1H1pfLbjI+vNKI2z+PrQI4jxJ/yGZKyq39f026n1WR40Ur6lgKzf7Hvf+eaf99iumL0OyL0Rh3lndzXSyW94YkAGU9azLCaPTPE15HduVE0alHbofWuuOj3mM7EyP9sVFc+G5LvAubWKUDkbnHFDGzl9KuY/7Q1PU5G2WrAIHI4461LrMN3qBspbBVlth+8w38Xoa6X/AIR+fyDD9ni8kjlN4wacmiXcaKiQxhVGAA44FFhWOL024v8A/hK7x7iFUyq+bj+EY7U/VoNCawuZogi3HJUxk7i30rsBoNyspkEEXmMMM28c1XHhQCbzhZQiTP3i460uXzCxQ0YznSLY3RJm2jOeuO1Xau/2Pef880H/AAMUf2Pe/wDPNP8AvsVS2KWx1vhr/kCQ/jRUvh+3kg0iJJAAwz0OaK5m9Tnb1Nd+h6YqhJNFGyrLKiFj8iu2Cf8AGr7cAnGfavMfGmjC11zSdQlup5pZrzARm+VB7CoRmehZ6k9hk9qZFNFOu6GVJVBxuRsjNUtb0w6tY/Z2uJbdSMuYmwxGOma534YwJbaFqMKZ2R38i8nJqhHZUUgopgLSp99eTTacn31pB1PPtTz/AGncYJ+8e9VenGT+dWtT/wCQncf75qrXTHY7VsJz6n86M47t9c9KWjscc8YNUMhN5CLgW/nKZjyEDc/jSXN7BaDNxKF9AW5P4VgSafDYeKrNYixZ1LMzHJNaurNa2ypcXFmbiQHaAFyRU9CehcguYruLzYZvMj9j0p0syQIZJZNkY/iZuKwPCgV3vp4/3SySki3PGyt24tYbyMxTxiRPQ9qE9AWxHbajbXhZbecOR2DUXGpWlrJ5c1wEb03fzrGFvbnxfb/YIlRbdMzlOhz0FVbV7K3uNSTVoWM0jttYoTlD0xSvZEtnVq4cB1fIbkYPBFLz6n86w/CMnm6IeSUSZlUt1CjpW51qlqi46oBn1P50c8AE5z60Uh/lT6B0PRLL/jwg/wB0VP8Aiagsv+PCD/dFT1yvc45bhR29PSkoxyOOtIRBeXttp8DTXkyQxjuzYz9KeLiE2oufMUQbdwctgY9a5fx/otpeaFdX9x5jyQxgIhPyA5649a1dGtIb7wnYwXMYeJ4QGU9DQBPZ+INL1G5MFrexPKP4AeT9PWtAfjiuD8QaZYHxboljoltFDewOZJnhGPLT3rup97QyiEnzNhCn/axQBQuPEOl2l0LWe9iWXOMbuh9D6VJqGsWGlLG17cKiy/cPXNecWM2iW/hjV7XXLWQak0ku6RoizE9iDXV+DILfWfB1g2owJceUNimUc7RQBr2XiPStQufs1teK8zDIXua0+1cL4WsbXU/GeoazbWyQ2lp/o9uEHU9GNdzQAtFJRTAr6n/yCbrBx8lefdjktz716DqX/IJu/wDrnXn3ataZ0UPhE59T+dLz6k+2etJ26ZqKS8toZhHLPGjn+FmANamrG3V/b2QH2icIx4AzyalimjnjEkUm+M9w2QawtPii1HxFeyXKLKIvkjDdAKd4fH2bVdStIh+6Vt6r2GfSpvqTc2Z7mK1j33EuxewLdabbXsF2haCbeAcMA3T8Kh1NbZYBNdQeeIjlVxkisbQGiutcvLmKL7MHUKIDweO9DdnYHo7G02q2Sz+SbpBJnAG7jPpVzPXBOPrXPeI7Kxg0wxR26C5mfEWB8271rbtI2isYI5PmdYwrH3oW41uS8+p/OtXw3n+2EGWPHrWXWp4b/wCQwn0py2Cex2x6nufSig9aSuY4+otFJRSASSRIkaSVlRFGWdjgKKhs7621GDzrOYSxZxuU55qrrukW2sae8d20nlRqWKIcB+Oh9qxPhtGsXhy4iRfLVbhgAOwoA6OTU7OK+jtJLiNbqT7sW4ZI+lWunBGB6VwGt6NaaZ468PTwB3muJpGkkdss3HT6V35PPfB7UAVr3UbTTIllvblIVPC7jyfoO9RwatY3Vm11FcqbderscAGuFv75bz4h3wn099RjsolEEA+6hPU10Wj3+ka3pF2kdgIxASbi0K9xQBq2Ou6bqU7RWl4kkqjJUHBP0rQ9+BnoT3rzOO4sdU8eaX9is20tLZTmR12+d/sivTD94gjA60AFFJRTAWsjxQSNJGD/ABdq1qyfE/8AyCP+BU47lQ+I4zsDk8+9Jz/eP50emecUkskcMZkldUQfxE8V0WR2C5wM7jx15qKG8huXdbecSMvUKeKY32fU4Hijn3ITyY2/rWN4dgjttW1KKEbUXAA70noSdFz6nPrmqs+p2ltJ5ctyqueq5zj61LcyGG0mmTqiEgfSuS0u9gh09rq5055w7lpZjzgf4U20DZ10k8cUAleULH1DlsA0y2v4L0n7PLvI9653WbuK61TToEjae1MZk8pejelaelX9pNdSWy2n2S5UZ8vHUe1SmJM1uc8kj8a2fCvOrEnOPLPWsb+EHH0rZ8Kf8hZv+uZpz2Cex2NGKKTseccda5zk6laTU7KK+jtHuYxcS/dj3fMfwovdStNMj8y9nSFe2TyfwritU0a10z4gaDLD5jzTTEtJIcseOn0rp/ERsLVEvL/TzeNE2EVV3EfSkBfsdRtNThE1lOkqjg4OSKkuLmG0gae4kEcScs57VxHw88m41rWb2BPskcrYFm3DJ/tYrf8AGllPqHhS7t7VDLMxBCDjNAFmy8S6TqFysFrdh5WzhfWtPoM9u31rhtA1fTNOuLGx1HRRp14ybI5SMh2+td1yD/MelAAOvJNcN4gz/bEuMgcd67kdfWuG8Qf8hmb8K0p7mtEzufU/nQW2ruZiq9zuorH8USsmkCNTt86QISPSt2dDL8GpWtxKYYrlTIOgLdfpVkknkFs4weelc3r1jb2WmWc9rEscsLrhl4JrolPmQqW/iUE+/FShIrHVrJJ/JN0vmdMbqsu6xRlnfYgGdzNWB4isrC30loo7aMXUzAR7fvE561oXGmrdaVFFds7CKMk4PDHHehMXUuwXEd1GJIJS6f3gakOfU/XNYvhMBdEUdBuIxW13/pTRS1EOcdT+dd7ov/IHgzzxXBHoa73Rf+QPB9KzqGdXYu8jtmq97qFppsYkvJ0hUnC72xk+1WK4r4i6JaTaTLqU+95lZQgY/Kn0FYnMdjJcwxW3nySokJXcXY4GPaqlhrum6nO0dndpJKo+7nBI9ajEFvceGbb7XCJ4UgVyhGc4FcRb3Nlq3j/TmsbI6UlshBZ12ecf7o9aAPSh16/pVaTU7KK8S0kuU+0yfdj3fNVpjliTwDXn+raLaaT460WWIu8s0hLySHLGgDv+nv7+lKOoPQ56UMPnI9/zoHUfWgDivEmRrMgyR+NZPPqfzrW8Sf8AIYkrKrphsdkdkAJ7E/nUFxe29koNxPt3dMnk0sl5awSqk88cbHoGbBrFsUi1LxNevcoJVhQLGD0HvQ2DN2GeOeIPDKHQ9Cp4pzOEG5n2DuSeB9awtBQWus6naR/LCm11XsCa17qyjvkEUzOEzlgp+97UAOt7qG6jZ7aXemcEg96hl1SzhuBFJdKJM4I3cCsrwshXTbxIBsKzOE9uazLaTTo9Cu7e+hYXpZtxKEknPBzS5hXOyznoxx25oOcdT+dZvhyVp9BtncljgjJ64FaVUtilsd34ax/YkORk89TRR4a/5AkP40VzPc53ubjdD2rzXxpeXt9qFjFbaXNItjcmRpB/EK9Lb7pqplcdTUIyZiz63ImireCwmZ3GDCOtc/4AuLyz+1WN5p8sX2m5eYOegB6V3eUznJoJU9zVAR/jmin/ACepo+T1NMBlOT760vyeppU2blpXA881P/kJ3H+8aq1r6gumnUJy7yZ3HNV9umH+OSumL0OxbFCjtkcnt/hV/bpf9+Sjbpn9+SndjuzjLpNYn1qC8XS1CQjG3zRyPWtS6vdSgkjkgsBLGV+ZS4yrfWt/bpn9+Sjbpn9+SkJXOW0qwu47281G6iEcsykJADkexJqW4k1eTRcRQIt8wwVzxiuk26X/AH5KNul/35KLBY5PRo7+wRITpO3ccyzGYEk9zUt7PqcskkMOlqxOQk7OOB64rp9ul/35KNul/wB+SlrYOhh6TYf2bp6w7tz5LOfVj1q7V/bpf9+Sjbpf9+SqTdhp6FCg9Kv7dM/vyUbNM/vye1F9AvodpZf8eEH+6KnplqIvscOwnbtGM1L8nvXM9zjluMpfY5wad8nqaMJ6mkI5jxmutXumy6dpWlLdJOgBmMwUIc9Md6bp0viK38KPbjSEgv7ePZbqZgwkPrntXUnZ6mj5O5NAHBeG4fEejbmufDQmu7h83N2bkZOT2HoPSuq8/U/7ckiNup05YwUm3cs3cYrT+T1NHyepoA47VZvEOqi4sofD8Vt5mY/tjShtqHvitC50y70rwYdN0dRNdiLylZjjk9Wrofko/d+tAGR4a0gaDoFtZf8ALULulPq561qU/wCQd6Pk9TQAyin/ACepo+T1NAFTU/8AkE3f/XOvPu1eiah5Z065352bOa4oLpmOHf8AKtqZ0UPhKHr6n9KrTafZzyebPaxyOP4mGTWxt0v+/JRs0v8AvyVo2zVs5R7S/wBK1ea6sLcXMM6jMe7btNOsLG+sra7uvLVr+diwizwo9M11O3TP78lG3TP78lSTuYNxc6jDbW0kFos8mP3ybsYPtVK0s7241ttUu7cWxRNqRBs7j7mur26Z/fko26Z/fkptXdxtXdzi4IdYTUpby60xbmQHEX70AIPYV0MDySQh5o/Lkbqmcha1Numf35KTbpf9+ShXQK5QrU8N/wDIYT6VFs0v+/JWjoQsF1RTCzlsd6JPQUnodUeppKeQmec0fJ6muY5Ooyin/J6mj5PU0AZus3F/BZMNM0/7dLICpQyBAoI65rnvA9trukwPY6npCwwvI0hnEwbGe2K7P5PU0fJ6mgDgtfh8T3/iLTby30BDDpsjFT9oAMoIx+FdLcXms79Pa309VEn/AB9o0gPlfQ962Pk680fJ6mgDjryx1fQvF9zq+jWIv7e+jVZYS4UqV6HJo0fS9a0m01HVDbo+qXsoY2wbhVHbNdj8nqaPk96AOHvrPXPFeqaa99pSaZBZTCZpDIHZiOwx2rt2ILnA+lL8nvR8nqaAGUU/5PU0fJ6mmAysjxR/yCB/vVtfJ6mszxD9n/swecWC7u1OL1Kg7SOGBI6VHNBFPGY5Y1kQ9VI4rU2aZgYkfH0pNul/35K6LnZcxzAlhA5sLRCRz5SHburH0uLVrXVbiebTgsdwRyJQSgrsNumf35KNumf35KT1IMRRdXE13BcxhLd0wj5zuz1rGht9XttOl0pLNXR8qs+/gKfau026Z/fko26Z/fk/Khq4NHIT6Tdac+n3GnoJZLVPLeMnG8Hqc1YsLS7uNZfUryEW527I4w2ePeun26Z/z0k/Kjbpf9+SkkCRQx1/Wtnwp/yF2/65mqu3TMffkrV8OrYjUj5DuX2elEtgnsdNSdj9Kf8AJ70fJ6msDk6nBa1F4nvfEunahD4fUxWDkgfaRmQdPwrfvtT162jtp7TRVn3LmaDzQDG3171vfJ6mj5OxNIDkNE0rVJfEt94g1G1Szmlg8qK2Vt2cdCTWnHe68uivO2nxtqKvhbcOAGX61ufIfaj92O/NAHEXdhrXizVNPOo6aunWVlJ5hJkDs7eg9K7VjuJJ7075PWj5PU0ANH3q4bxB/wAhmb8K7wBMjGa5DWl086rL5zuH46VpTeprRZg1Q1rT21PTWgjIEmdyH0YVvbNL/vyUbdL/AL8lbS1Oh6nHy2+p6slrbXdoLeGBgXffnfj2rXia7F/LG8I+yqn7t93JPpWzt0v+/JRt0z+/JSEjireDV11J7260sXEmcQ/vQAi/T1rYup777ApisA9xIpV4vMxs98963dumf35KNul/35KNQ1OV8OQ6hY24tbyyEaAk+aHz+lbfar+3S/78lG3S/wC/JRFsE2Z56Gu90X/kEQfSuSKaXj78ldlpIiGlw+UTsxxUVGZ1dixXJ+N4dd1Oyk03TNHW4ichvtDTBfwxXX/ux3o+T1rE5jnLS61+Pw/GDo6RXduqoIfOB8wDvntWXdWOt+Kta0yfUNLXTbewkEpcyBy5HYY7V2/yepo+T1NAzNt59Tk1u8juLdEsF5glB5b8K5PWovE994jsdQg8Op5Vk5wDcj96P6V33ye9HyepxQBXtpZp7ZJLmHyJmGWi3Z2+2e9TDqPrTvk65oAQnjPWi9hHEeJP+QzJWVXQ68tgdUkMzOG9qzdml/35K6YP3TtjsjJmsLS6k8y4topZRwHYdBWVJZ3mmazJeafbC4gmQK8W7btx6V1ezS/78lG3TP78lDVwaOWsLK+tIry+aNTfXB+WLPCgdBmr7XF5FZRyR2gmucDfFv2gHvzW1t0z+/JRt0w/xyUbAcjoEOp2RmhurEJHLI0m8SZ2k9sU69bVL8S28emRwGT5GuGcHC+oFdbt0zu8lJt0v+/JS1FYybK1Sys4reMkhBgk9z61P2q/s0v+/JRt0v8AvyVV9ClsdX4Z/wCQJD+NFTeHxANIi8gkpzjNFczepzvc13+6a47U/G9jp+swaaIpJZZJNjOq/Ip+vrXYP0NcD47hjin0IxIqFr3LFRjcfeoRkdBrmsf2LBGwtZrmWY4jjiXOfr6VS0LxXHrF/Np89s9pfwqGML91PcVt3FzFY2r3FxIscMS7mZuwx2rlfDkE2t+JbvxNPGYoHQQWoIwWUfxH61QHW59KKXvn0pKACnJ99abTk++tMOp57qf/ACE7j/eNVqs6n/yE7j/fNVq6Y7Hatgo6DP40UHoaoZixeIfP1hLNLVxE/SV+M/hWpeXMVjayTynCoPz9KydQA/4SywHT5M4HaotbvA+rwW9zDMbSL52KLkMfSs7uxF3YvaFq7azbSyyW/kNG+wrnNTavqB0vTZLtYvNKkAITjOayPCt/HLPqEapIN85YEjgCtnVNPXVdPe0MnlhyCGHPSmm7Bd8pBYXupXM6Lc6ckMLDPmCTOKrNrd7LqFxa2OnpP5H3maTbUJl1DRNTsoZboXNvcEoF24K471Nc6FcQ3FzeWV+YHdclduRxSu7Bd2Na3eSSFWmjEchHKg5walxWboGoS6lpSzzgCRWMbEfxEd60qtbFrYKDg/hRR2o6B0PQ7L/jwg/3RU/eoLL/AI8IP90VPXK9ziluJS5pKPakI5/xV4r/AOEciPlWMt3MFDEAYVV9z2rQi1SSbw+moxW++WRAywg9/TNU/Go/4o7USOpQDd681a8Pbv8AhGLIIQr+RhT2z60AYq+LdVsdWsrXXtHjtIr0lYpI5d+D7iut6Hk151rlrqmi67pmqa9dpqtskvlxKBs8pjxnA616KRk4GPUDuKAOQ1PxXrmnCe8Ogq2mwNhpDLh9o6ttrU1LxTa2GhW2pRo032sL5EQHLk9BWd4q1CXWZf8AhG9JIknm/wCPqUHiJO4Puay/GOnSWmpeFtPsbn7OkQMYlIyBjp+NAHTaRfa7c3KjVdIhs4GUkOs28+wxWzXIQXOq6B40s9LvL/7fb30TuMrhoyK7A8e9ACUUUUwK+p/8gm6/3K89r0HU/wDkE3f/AFzrz/tWtI6KHwhxR07UdOfXqKoXd3fQ3Ijt7NZEP8ZfpWxsQa1rg0kYS2kmfgnjCgH3rSt5fPto5cY3rnFZvibnw5OSNrHbn8+lXtP4022zj7gqVdslPUj1C6uLZIxaWwnlc4ClsAfjVaw1mSa9ntL+3FtPCu8gNuBH1q/dXUVjbvNOwWNRnnqT6CsrS7KS9nutRvV2G5XYid1XsaTuDuRt4hu2t5LyDTw9kjEFy+GIHUgVtW86XVrHPGcpIoIrnZ7XU9J0W7tw8RtArESMeQD2xWt4ejaLQrVWByUzzRFu+oRbNGtTw3/yGE+lZdanhv8A5DKfSnLYJ7Hakck0Up60lc3U4+oUUUUgM/W9YTRLHz2glnds7I4lySff0qr4X19/EOjSX0lr9nZHKmPOela84zbTEckI3XtxXMfDkE6Bc/8AX29AEOo+Ltb01GvbjQVXTEkCGXzfnx67a622nS7tobiE5jmUOpPoa5TxLeSeJbseHdLbeCwa8m/hiUfw/Wurt7eO0to7aJcRxKEAJ6YoAw9S1bxFbXrx6foMF1bj7srXG0n8KqaH4wv9Y02/nbR/LmtX8tI0fcJG781e8Y6wdH8OTPE3+kznyIQOpZuAal8N6ZH4e8NQwysIyq+bO7HHzHliaAMq28Xalbaza2GvaSlkLz/USRy7wT6H0rrT8rEHqK461V/GPiaHU9hTSdOysBPWZ/7w9hXYknn1PU0AJRRRTAKyfE5/4lA/3q1qyPFH/IIH+/TjuVT+I4ylPHagVDdSyw27SQR+bIOiE10nYLc3C2tu8zhii9lGTWfo+tNqs1xG1sYfJ6ZPJFXLCa5ucm7tlhIPAByDWXomTr+pk9iM81LbuQbjsI0ZmzhRkn2rAbxFeG0e+isFaxRiDIX+Ygd8VuTyJFbSyS/6tVLOAc5FcZ9hvZdLlvbcgaaXMv2Yt1XvzRJ22HJ9jp7i/umht3020Wfzk3/M20AU3SNVbUmnimg8i4tziRM5H4U5Wmv9Jgk0yYWm5QQCucD0rO8P7rPU72xuhuush2mBzv8A8KSbEmzoOOvbtW14UP8AxN2/65msY98/hWz4U/5Czf8AXM057DnsdhRnj6UtJ161znH1OVbxtu8U2mkw6fL5NxIY/tEg24I9B3Fa+tX2pWjRxaRp63sznne+xQPrWJ4kGPHXhoDp5hwPTiuj1e21C5t/L0u+WzmDf6woGH5UgMvw14mm1q7vLC+sxaX9mf3kYbcMeoNbN5dR2NrJcSqzKg5VBkn6CuO8HrNpPivU9L1NVm1KRBcPeK331PQY7V3AAJAwDzmgDm/DHiyTxFqmoWr2L2otVVlL/eYH1HaujrkfDX/I/wDiLnP7tMnNddQAo61w3iD/AJDMv4V3I+9XDa//AMhmb8K0p7mtEzqO1FULq7vorry4LJJYv75fBrdnSytrevDSQVjtpJnGN3GFA+ta0bbokfH3lDfnWR4pz/wjsh6Zxn1zmtaAf6LD/wBc1/lU3dyb6iTzJbwPNKQqIMkmsvRte/tdrkG2MIhzjJ5aoPEVyTdW1m8UrWzEPKUXO4elVNBvoJfEGoJHHKom+VQV+6Md6TbWwm30Llrrmo3257bS0eEPt3GXB+tbq5K5YAHvg1zl1pl7oVhPc2WoAIjbzGy8H2zW7Y3P2yxguCu0yIGK+lOLHEmPQ13ui/8AIIg+lcEehrvdF/5A8H0qahFXYu1zXinxj/wjp2Q2Et1IMbyRtRQfeulrmviCP+KRuCMANIufWsDlOhtJftNpBNjb5sYkI9MiuZs/HS33jH+xYbPNuVZkut33ivUYo8R6nc6Z4ItBaRTPLcRJFmMZZFI5auXt9W06y8aaDFa212scNq6MGiwXYnk0DPU2O0EnsO3euO1HxhrOkxG/vdBRNMV9jSibLgZxnbXYAhgGGACMjnpXDeONK1p7KW9uL9LrSrdhK9ntCbgD/eoA7eKRZoI5U5WVQ4+hGaeB8w+tVNKuo7/SrW5hTZHJGCF/ujHSrY+8PrQhM4rxJ/yGZKyq1fEn/IZkrKrqhsdsdkGPSsu81WZdQ+w6fai5uFXc4ZtoUfWpry7vYLlY7azWaI4JYtjFZ+isx8S6kJBiQopwe4pNsJF7SdVGpJKrx+VPC22SPOcVNf3NxbxoLS38+VzgLnA/E1m6P83iTVmXG3ao9ie9a9zdQ2ds8877I1Gfr7UK9gWxn6dq81zqMlhe2wt7hRkYbcGH1qtBruo3skos9LSRI3KbmlxnFS6PBLdX8ur3KbDINsMfovr+NVrnR7zSba7urHUNmMy7CuR9KWors6BCWRSwwxHI9DS1V0u8N/psFywwzryPerdX0L6Hd+Gif7Eh6d6KTw1/yBIfxorle5zPc3WOAT2rhtd8H6lrl8szeIZIYYZfMghEAPln6967h/unnFVfNbrxj6dKhGZy2veEb3X9HtLG51uVZYG3PMsQxL6ZFT6PoGr6bdxPc+IGvLdFwLfyAoI+oro/MbJHb+dJ5j49PwqhDO3T/wCvR+FP81s9vyo81vb8qAGfhTk+8vFL5re35UqSMWUHH5UAeean/wAhK4wCfmPaqn0B/KtjUNYvI9QnVWj2hiB+7FV/7bvf70X/AH7FdMb2OxbFD8D+VJ7c/l0rQ/tu9/vRf9+xSf21en+KIf8AbMU1cauctJ4aSW5W4a7l8xTx14rYiQJEq437RgkjrWl/bV8R96If9sxQdbvTxmL3PlipVyUjDs9Mis47pYd3+kMWJx0zUf8AY8f9nLaLNN8hyHycmt/+273Aw0WP+uYpf7avc4zFx0/djmnZjsc7ZaHDaXa3Msjzzr91nzhfwqOfw+s8shN1OsUrEtHk859K6b+270fxw59PLFH9t3pOQ0S47eWKVtBWMq2tYrO3SCBdsScYx+tTfgfyq/8A23eH+KLnr+7FH9t3v96L/v2KpXsV0M/8DRnOOpOemK0P7bvf70X/AH7FH9t3v96I/wDbMUruwrux2ll/x4Qcfwipu/SmWkztZQsSCSoPSpvMbPb8q53ucktxn4Uv4U7zW9vyo8xvb8qQjB8Q+GU8Q/LNeSxQ7dpjXvUdp4ThttGm06S8uJbdwAvJVkx0wa6LzG65H1Io81vUE+uKAOXtfA9rFfQ3F9dz3vkHdEjnhT/WtYaRGNek1MzS+bJEI/L3HaMd8VpeY3ONuc9ARR5jcgkD6igDjE+HVtDdTzwajcwvcOXkKk5J9K1b7wtaajo0VheSu7RMGjnzhlYdDW/5jEc7fpxSGRj3X8cc0AYGj+FrbSr5r6WWS6vCuzzZDnA9q3OR70/zGz95T7DFHmt7flQAz8KPwp/mt7flR5re35UAVNTP/EpuuP4K89B9jn6V6LqEzpp1zIuMqmRxXFf23e/3osf9cxWtM3o/CUOfQ/lRnHY/lV/+270D70X/AH7FH9t3meWix/1zFa63NjntU0ZdVciSd0QjG0dKINHWLT3tDPI6N0PORXQjWr3u0QPvGKDrd8Ocxf8AfsUrMmzuc3qGgw6ja21vJJIFt+nX5vrTrLRhaT+YLmaRcYwc4FdF/bd6T96L2/dij+27zON8X4IKVgscy3h+KWXNxczSx7t4jOcfjWsAFAAXAAwMDoK0P7aveoaE9v8AVik/tu8HG6L6eWKdmNIo/gfyrU8N/wDIYTPHHeov7bvf70X/AH7FaOg6pdXGqJHIY9pHZAKJXsKWx1R6nsaT8KeZGzgEAfSjzW9vyrmOTqM/Cj8Kf5re35Uea3t+VAGdrGlnV7UQfaZLcDqyd/asvQvBsWhNIIL2Z43Byjep710plbHOB6cUCRh1IPue9AHFwfDi3tWlNtqN1EZXLuQT8xPvW3NoEc/9nGS5nzYZ24YjzPr61s+Y3t60eY2Bhlb6YoAydU0K31e/srm5JItCWjXtn3qXXdJi1/S5LCeV40l+8yHtWj5jA9gPpR5pPG5MH3FAHJaf4Ej014DBqVyI4SMRgnBArqyMEdh607zW44Ao8xvb8qAGfhR+FP8ANb2/KjzW9vyoAZ+FZPif/kEjj+KtnzW9vyrM8Q3cttpm+Iru3d1zVR3Kh8RwvYYBP4UuSOx/Kr/9t3v96L/v2KP7avcfei/79iujU6zLuoWuLdo1ZkLfxAVl2nh1LO88+O5l3ty2R1rqP7bvR3i+nlij+2r3+9D7fuxSJMWLT40uLqTc8guBhkbOB9Kz/wDhGoQpiW4mW3JyYhnH0rqv7bvTjLRY9fLFB1u97tEM/wDTMZo1Gc9daLFOIvJkkgMa7V2k4A9xUmnaVBppkZC8kkvV25Nbv9t3ueTEPX92OaP7bvORvh/79ihXAzx6kH34ra8KnOrnPA8s1V/tq95O6L/v2K1PDmpXN1qRSVkwEJ4QClO9hT2On/CkPIIx1p/mN7flR5je35VznIclfeBIr7UEvZNRuPOjbchH8NXtQ8LrfxW4F9cRXEK7RKrH5h7it/zGx1FHmtjqoA70AYej+F7TRzdSo8s13cLtknc5JHtU1noKWOkyWEFzNh2LeazEsM1reaRxlcj8aPMbAGRyfSgDkrHwJHYak19FqFx5rkGQn+LFdUTk55+tP8x8ZG0/SjzW7Yx9OlADV6jvXDeIP+QzLgGu78wk9vwFchrWrXUGqyxo0e0Y6oDV09zWluYX4H8qMn0I/Cr/APbd7/ei/wC/Yo/tu95+aL/v2K3dzoOd1TRU1U7ZZ3VD1UdKcmkAae9oZ5WD4w2TkYroP7avSfvQ9P8AnmKP7bvcctEP+2YqRGbHGsUaLgtsGORmqsGlwW91czJnfc8tx0rc/tu8GPnhz/uCj+27wk4aLnv5Yp7hY5b/AIRqJyFmuZpIAf8AVEnFbCKEjVEUhFGAMdK0f7bvectFkdvLFH9t3uPvRf8AfsUagZ56dD+Vd7ov/IIgz6VyJ1u9A+9F/wB+xXZ6TcSS6ZC7EbiOcCoqXM6uxYrA8QeEo/EMh+0XkscTY/dKeMiui8xz0I/KjzGz2A96xOcytG0caPaeQZ5LhBwDJzgCifQra41211VuLi3jaNBjjBrVErc9D+FBkb+8BnoaAMqLRII9VvL7zZWN0uHjLHavbj0rHfwDazMYp7+6ksi25oGc8jrgmutMpz2xjnije2Oq/pQBFFEkESRRIERAFQDoBTxww7nNKJGAGSDzwcUokfI5HX0oA4fxJ/yGJP6Vl/gfyroNe1S5t9UkjiMe0eqA1nf23e/3ov8Av2K6I3sdcdkUMnsCPwrNv9GhvbkXCSSQzgY3rnkV0H9t3ueWi/79il/tu9I+/EO/+rFN3GzAi0e2g097WLzFWXO5+dxP1pmoaFFqFlBbTSyBIMYPXdj1rov7avvWLJ5/1YoGuXvUNET/ANcxRZgc7Z6L9jn837TNIMY2nOMVC/huKRmWW7maBjkxkn8q6j+273+9EffyxQdbveu6H/v2KVhWM6ONYY1jjTaqjAAFL+B/KtD+27zs0RHr5Yo/tu9/vRf9+xVa2KOr8M/8gSHj1oqXQLiS40mKSQruOegxRXM9zne5rtyCM4rzvxNqXiGz1zT5BPHbWE1z5QROTIvqa9EbkEV5v4/1ew+3aPEblfNgu8ygA/IPepRkdXrNne30EUVhfmwBP7yUYJxjtmud8M32oQeL77RJNROqWkEKyfaCBmMntxWxq+oaDd6bFDqlwv2S7wsZyRvI9x0rmfDqWuneOjY+HJTLprxbrlRk+W3+8etMD0HPU9T0pKXPH0NFMBKcn31ptOT760B1PPdT/wCQncf75qtVrU/+Qlcf7xqrXTHY7Vsgo6g+nv2NFB6ZPUdvaqGc2ftsHii2F1dF/MGfLHRR7Vq6zetZ2wjh5up22RKPWsS+1myfxNaTCQ+VGu1m2ng1dvNPv7zVI9Qsp4SmzEYft71lfQzvoHhQzi2vIp5TKY5yu41a17UH07S3liP7xiEBPbPesvwx9sifUZbkr5SysXAHJIHapteYaz4ejuraN2VHDmMjnGeaabsNN2H6VbWLXcZTU2nvOrjPBqpNfQ6nqtwt9fG2tYDsRF43HvmkuZ7TU73Tl0iM+ajAuyrjYO4NJavY6Vqmox6pFjzXLoWXO7PYUr6CudFp8aRWaLFN5sfVWznIqzWN4Xhlh02TejIjys0aHqFPStmri9C0woPSik64J4GafQfQ9Esv+PCD/cFT1BZf8eEH+6Knrle5xS3Eo+ppaPpj8aQjk/H0WqnSZ7i0vja2sKAtsHzSNnp9K1NOWa/8IW6/aXhleEEzgZKjuazPH+s2Vp4furGabFzMgaOPaSWGadoPiPTv+EPjlDPKttCEmRVO4UAYRRdN8U6VH4e1WS+kmci7jLZG31NehzyeVDK6jeUQsB3JHavNNSk0a91PTpPBqE6mJR5jxgjamed2a7/+2rdtbk0oK/nxRiRn2/KQe2aAOHsbW48Q+H9R1y41aWG+heQxKrYEYXoCK29NtT428MaddXVzNFKilS0JxvPc1ha+vhGb7aljbyTarOSn2aIsMyHue1dFZq/g7wAvmKftEUOQijOJD2oAx/Dmnunj+5isr2eew0+PbKXbId2/wrv+tc94I0p9M8PJJcD/AEu8YzysepLc4P0roaAEopaKYFbU/wDkE3f/AFzrz7tXoOp/8gm6/wByvPu3Na0zoofCJnB9aUfewSM+lHXHqO1ULrS/tU4l+1Sx4IO1a1ZszOaOTXNcntnmkjtrUYCp1LetTeH7iXz7uwmlMhgfKOepWq0NxHoWvXRvSywTqGWXGQT6U7Spfs51DVZ43WGRsKAOSOxqLkXLHiPUJLWK2gil8lrlseZ/dA603TksYPOmsb03TohLKSeTUHiHbONMv2iZ7eNizgD7oPc0yN7e+8S29xpseIIUPnOq4VvQUm3cTbuQRQy3+iz6o18wulLMoDYC47YroNIu2vtLt52zuZBk+p71zupR6HMkyWUTy3kpKiJCRhvU10el2hsdMt4G++qjI9D3pq9xp6lutTw3/wAhhPpWXWp4b/5DCfSqlsOex2x60lKepxiiubqcfUSilooATnPr/SuI+IiatBprX0V+be0iljCxR9ZCW5z6V25578e1cP8AEzWrJdBl04yH7W0sbiMKSSA2TQB0+oWzX2hCP7ZJabkUtPGMkDuK5HSP9D8eWtpomoSXllJGTdqzZCntXQf8JLpUvh0XhZprMARy7VPyn6Vy8X9l3Xi7TJfBqtuJP2yRAQm30bNID0SaMTQSxZKh1KkjqK898X+HY9D0jfb6ldtd3EixQJuP3j3rt7LWbfUdTvLGFJBLaY3kjCnPpXN7G8SfEP51P2DSE4yOGkbv+FAHUaVby2mk2sM7l5kiUSMeu7HNWqXOTk9aKYCUUtFACVkeKP8AkED/AH62KyPFH/IIH+/TjuVD4kcX+lL79RQMfpUN1bm5gMXmNGT/ABLXSdnUoeIb2Wz09RAdsszhEYds9az7y3l8Oy2k0NzJIkjhZlfvnoRTtZ0uS20xZIZZLloZA5DdcZ5xTdRvYvEEtlbWO58OHdsY2Y9ah7kPc6C8lMFpPKgy0cZYD3xXLpBLL4fOri9b7UMyY3cY/u4rok1GG4uLq3CN/o65kyOCK5nUYtFuYHi02J5bqY42KSAhPc0SYSZcv9Xa4i063W4W2W4j8yaU9gO1aOjxWSh2sbszr/FznFZV9aR6Vf6VNdx+ZbRxeW7YyFb1NWNL8u58Sy3diu20VNpYDCufpSTYk2dCfrn0IrZ8Kf8AIWb/AK5msb07E9q2fCv/ACFiP+mZqp7DnsdjSHocdccUvFIcAEk4A71znJ1OEvxq1p4+0Zry/ZoriUqLdfuhcVL8Q7hY9V0S3uL2SzspZmE8qZ4GOOlUvEfiXTD400aUTkx2kp85ghwnHWum1TxFoMK28mpMjW8w3xSyR7l/lSAPC9lp9vDJJpupNfI3GWbJFaepWkt9Yvbw3TWsj8CVBkqO4rjvC6xTeMdU1XSIZItINuBnGBK45JAreuPF9pD4ZuNajhlaKElRGVO4tQBz81lceFvF+j29hfz3C3u4TwSHPAHX2rvm46DHbFedeFNf0y41M6pqly0mq3ZCRxlDiFewFeikY5PXpQAD71cNr/8AyGZvwrue/PFcN4g/5DU34VpT3NqPxGdWbr17JZaWzQnErsEQ+hPetKsnxNbS3Ok5iUs0LiTA6nFbyN+hnXlrPokFpfxXMsrs6iYN0YHrXTBtyZXjKbhntxXNahqEWuWtnZ2W55Sy+aMEbB3zW3HfRG6eyCsZLePJOODUIlHMaZ9kvZZjfalJHN5pAQkj8q6TUrz+ztPGz55Wwkaj+ImsfVdQ0i80+WGGMPdMdqoqYYH60/8AsbU5P7OljmjD2ycrKejetK7Emw8Lm6W7voLyYySRt3ro+3H5Vy3h6LUF1++a4ZNpf94f730rqeoz61cdVqVEQ9DXe6L/AMgiD6VwR6Gu90X/AJA8H0qKhFXYu/WuM+IKasmnvdwX7W1nEygRoOXPvXZ1xnxG1qyg0SbTmlJu2ZSECk8Vicp00N5HaaBDeXT4SO3EjMevSuG0i/1S4+INjd3UzJBfwSPHb9lUHg/jWpdxN4y8I2lrod4itB5fn7wQDgcqaxp7DxHD4/0ZJpLUulswRkztVAen1pDPTCCMgcHB615/4p0KfQdHl1mPWrmTUI5NyFuj5P3cV10Gt282p3enbZBNZqGkcj5TxniuCbxZpviDxB9o1iSSDT7KTFvbFDl2H8RoA9Is5ZJbC3knAErxqWA7Eipx1H1qK2uYry2SeDmFx8pxUvcdOtCA4rxJ/wAhmSsqtXxL/wAhmSsquqGx2R2QD0A+mawJUfW9entjO8drbKCQvBYmtG80w3dys32mWLb/AAr0NZUc8eheIbl73cLe4RSs2MjPoaTYSZZ0GadLu9sLiQyi3IZGPXaa0NSvU06yedvvDhF7s3YVkaZOY5tR1iWNxBJgIMcsB3qbU7K61gWd1ZSRrGg37ZPU9KL6BfQreHjdR61exXkpYlFlKn+HIziq8N3b6rLLPqOomBA5SGIHAGD1p+nQakfFV757xk7FErL0Ix2qvZTWOn6feWV/Di6DsV3LkuCeMVF2RdnW26BLdFV9644b1qSs3w9BNb6HBHcAh+Tg9QD0rSrRbGi2O68Nf8gSH8aKPDI/4kkP40VzPc53ubrAkGsibw7YXEzyz2UTyOcsxHWtmioTMzKk0S0ltRbSWsbQL91COn0p1ppMFhH5dpbxxKeu0dfqa06KLisVPIcnPftR5D1boo5gsVPIelWFwwNWqKLhY4e98MX819NIqrtZiQar/wDCJ6j/AHVr0CitFVaNfas4D/hFNR/urR/wieon+FK7+ij20h+1Z58fB15j/UQn6qKcPCeojgKoA6Y7V39FL2rF7Rnn/wDwieoAfcXJ6kDqfej/AIRLUBwI4wB6dDXoFFP2rD2rPPl8I36ZKQxrnrgAZobwhfN9+KJ8dCwya9Boo9qw9ozgP+ET1Hphfp2o/wCEU1H+6td/RR7Vj9qzgP8AhFNR/urSf8InqOeVXAr0Cij2rF7VlC2tZIrSJGxuVQDipPIerdFRzGb1KnkPR5D/AP66t0UrisUmslkOZIopGHdkBoWzVQQsUYB6gIADV2ii4WKK2KR8xwQx56lEAP6U77MQxYIucYzgZ/OrlFFwsUBYorbhBEGP8QQZ/Onm2ZhhlUjOcEZzVyii4WKn2dsDAwPajyHq3RRcLFTyHo8h6t0UXHYzb20lmsJ4kALOuBmuSHhPUf7q139FVGbiXCbirI8//wCET1HHKr+FL/wieoHsK7+iq9qx+1Z5+3hG/f78UbDtkZo/4RLUNuPLTHpivQKKPasPas8//wCESvyMNGhHp2NA8IX6g7Io0HooxXoFFHtWHtGefDwhfA5EUYPqFGad/wAIpqPZFFd/RR7Vh7RnAf8ACKaj/dWr2jeHb2z1FZZQAoFdjRSdVsHUbKhgctnAo8h6t0VFzMqeQ9HkPVuii4rFTyHGSBzTGslZtzQRMemWQEir1FFwsURZKF2rDEFJyQEGD+FKlksefKhijB6lECk/lV2ii4WKf2U5yEUE9SBgmhbYrnaqjPXAxmrlFFwsVPIccUeQ9W6KLhYqeQ9HkPVuijmCxU8h6z9c024vtO8qEDduzW3RTUmhrR3OA/4RTUR2Bo/4RPUP7orv6Kv2rNfas4D/AIRTUuflQ/Wmr4Qvk+5FED6gYr0Gij2rF7Rnn/8AwiV//cQZ9B1+tIPCF8pysUSt/eVQDXoNFHtWHtWefnwlqDLhkQ56gjNA8Jago+VIx9BivQKKPasPas4D/hE9R7KtaWg6BeWN+ZZhhdhFdbRSdVsHUbKnkPR5D1boqLmdigbCMkk20J+sYpWsVddrQQso6BkBAq9RRcVimtrsUIkaKo7AYFJ9kGzZ5SEZzjaMflV2ii4WKAsIwci2gB9RGM1J5Dg5x7cVboouFioIHXoBXL6v4cvrvUpJowCpxiuzopxk0VGXK7o4D/hFNR/urR/wieo/3Vx3rv6Kv2rL9qzz5fCN8pysMSn2ABpf+ES1DrsTPqBzXoFFHtWHtWefDwfehtwhiDdyFGad/wAIpqOMFVJ7Gu/ooVVh7RnAf8IlqAJIRAfUUf8ACJ6j/dBrv6KPasFVaPPz4T1HH3Vrq9NsZbbToonGHXrWrRUyqOQpTctyp5D9qY1kjnLwxsfV0BIq9RU3M7FJLTyxiONEB6hVApfs5LBmRS3Y45FXKKLhYpi1IOdi5/vADJ+tMOnxE82sBPqYxV+ii4WKYt2UAKAq+iilEDhug61boouFjj9a8PXt5qTzRAFTVD/hFNR/urXf0VaqtKxqqjSscB/wieo46DPakbwlfv8Afiif/eGcV6BRT9qwdRs8/wD+ER1DG3y49vcdqUeE9RHRFAHau/oo9qw9qzz8eE9QBOETnv3pD4PvWbc0MTEdCVBNeg0Ue1Ye0ZwH/CKaj/dWk/4RTUf7q16BRR7Vj9qzJ0WwmstMjhl4ZetFa1FZ3M7n/9k=\" alt=\"image\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e the table showing the WL for each method\u003c/p\u003e\n\u003ch2 id=\"_Toc200489439\"\u003e\u003cstrong\u003e\u003cu\u003e3.2 Comprehensive Statistical Comparison:\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis section presents a full statistical evaluation of working length determination using four different methods: Apex-s EAL, RAYPEX 6 EAL, Intraoral Periapical Radiography (IOPA) (planmeca romexis), and Cone Beam Computed Tomography (CBCT) (NewTom). The analysis was done on IBM SPSS which includes standard deviation, t-tests, and one-way ANOVA to provide insight into the accuracy and consistency of each technique.\u003c/p\u003e\n\u003ch3 id=\"_Toc200489440\"\u003e\u003cstrong\u003e\u003cu\u003e3.2.1 Standard Deviation Analysis:\u003c/u\u003e\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eStandard deviation measures the variability in deviation from the actual working length (AWL). Lower standard deviation indicates better consistency. CBCT showed the most consistent performance (\u0026plusmn;0.67 mm), followed by Apex-s EAL (\u0026plusmn;3.71 mm). Apex Locator 2 had higher variability (\u0026plusmn;5.07 mm), and IOPA was the least consistent with a wide spread (\u0026plusmn;8.02 mm).\u003c/p\u003e\n\u003ch3 id=\"_Toc200489441\"\u003e\u003cstrong\u003e\u003cu\u003e3.2.2 Independent Samples T-Test: APEX-S EAL vs. RAYPEX 6 EAL:\u003c/u\u003e\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe independent samples t-test was used to determine if there was a significant difference between Apex-s EAL and Apex Locator 2. The resulting T-value was 0.580, with a p-value of 0.563. As the p-value is above 0.05, the difference is not statistically significant. However, the higher consistency of Apex-s EAL (lower standard deviation and fewer outliers) suggests it may be more reliable in clinical use.\u003c/p\u003e\n\u003ch3 id=\"_Toc200489442\"\u003e\u003cstrong\u003e\u003cu\u003e3.2.3 One-Way ANOVA: All Four Techniques:\u003c/u\u003e\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eA one-way ANOVA test was conducted to compare the four groups. The F-value was 3.03, and the p-value was 0.030. Since the p-value is less than 0.05, we conclude that there is a statistically significant difference among at least one of the groups. This supports the notion that method selection has a measurable impact on working length accuracy.\u003c/p\u003e\n\u003ch3 id=\"_Toc200489443\"\u003e\u003cstrong\u003e\u003cu\u003e3.2.4 Final Interpretation:\u003c/u\u003e\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eDespite the lack of statistically significant difference between Apex-s EAL and 2, the overall analysis favors Apex-s EAL due to its higher consistency. CBCT, as expected, remains the most accurate and reliable technique. IOPA, while commonly used, presents the highest variability and greatest risk of large deviation. These findings can guide clinicians in choosing the most appropriate technique based on availability, clinical context, and diagnostic needs.\u003c/p\u003e"},{"header":"Discussion, conclusion, summary and limitation","content":"\u003ch2\u003e\u003cstrong\u003e\u003cu\u003e4.1 Discussion:\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe accurate determination of working length (WL) is fundamental to successful endodontic treatment, particularly in teeth affected by external root resorption (ERR). In the present study, four measurement modalities, Apex Locator 1 (APEX-S), Apex Locator 2 (RAYPEX 6), intraoral periapical radiography (IOPA), and cone-beam computed tomography (CBCT), were compared through statistical analysis involving standard deviation, independent t-tests, and ANOVA.\u003cbr\u003e\u0026nbsp;\u003cbr\u003eA detailed comparison between the two apex locators demonstrated that AL1 offered superior consistency, reflected by its lower standard deviation (\u0026plusmn;3.71 mm) compared to AL2 (\u0026plusmn;5.07 mm). Although the mean deviation of AL2 was slightly lower, this advantage was offset by its higher variance and increased incidence of outliers. These results are consistent with previous systematic reviews and meta-analyses, which affirmed that fifth-generation apex locators, while accurate, may exhibit variable performance depending on canal conditions \u003cstrong\u003e[21,22].\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003cbr\u003eThe t-test revealed no statistically significant difference between AL1 and AL2 (p = 0.563), but clinical relevance should not be overlooked. Devices with higher variance can lead to over- or under-instrumentation, potentially compromising treatment outcomes. Studies have shown that devices such as Root ZX (analogous to AL1) exhibit consistent accuracy, particularly under moist conditions or complex canal anatomies \u003cstrong\u003e[22,23].\u003c/strong\u003e In the current study, AL1 displayed fewer errors and more predictable measurements across cases.\u003c/p\u003e\n\u003cp\u003eWhen apex locators were compared to IOPA, both AL1 and AL2 demonstrated markedly better performance. IOPA presented the highest standard deviation (\u0026plusmn;8.02 mm) and the widest range of measurement errors. These findings align with Ramezani et al., who observed that digital radiography consistently overestimated WL, especially in the presence of lateral apical foramina \u003cstrong\u003e[4].\u0026nbsp;\u003c/strong\u003eThe two-dimensional limitations of IOPA, including distortion and superimposition, are well-documented contributors to such inaccuracies\u003cstrong\u003e\u0026nbsp;[25].\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;\u003cbr\u003eCBCT emerged as the most reliable modality, with the lowest standard deviation (\u0026plusmn;0.67 mm) and the smallest mean deviation from actual WL. Its three-dimensional imaging capability allows clinicians to precisely visualize apical constrictions and anatomical variations, even in complex cases like ERR. This reinforces findings from studies that ranked CBCT highest in correlation with actual WL measurements confirmed through magnification techniques \u003cstrong\u003e[26,27].\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;The one-way ANOVA (p = 0.030) confirmed significant differences among the four groups, underscoring the impact of the chosen modality on WL determination. Post-hoc comparisons highlighted that CBCT and AL1 were statistically and clinically superior to IOPA and AL2 in both precision and accuracy.\u003cbr\u003e\u0026nbsp;\u003cbr\u003eIt is important to note that while CBCT demonstrated excellent performance, its routine application is limited by radiation exposure, cost, and accessibility. Therefore, AL1 stands out as the most practical and clinically consistent option for WL determination in cases where CBCT is not feasible. Combining AL1 with IOPA may enhance diagnostic accuracy while mitigating radiation exposure, aligning with best practices suggested by recent literature\u003cstrong\u003e\u0026nbsp;[28].\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn conclusion, the results of this study corroborate earlier findings that emphasize the importance of standard deviation and consistency in clinical settings, not just mean deviation. AL1 offers a balance of precision, reliability, and practicality, making it a preferred tool in routine endodontic procedures. CBCT remains a valuable adjunct in diagnostically challenging cases, while IOPA should be used with caution, particularly in anatomically complex scenarios.\u0026nbsp;\u003c/p\u003e\n\u003ch2 id=\"_Toc200489447\"\u003e\u003cstrong\u003e\u003cu\u003e4.2 Summary:\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study aimed to assess and compare the accuracy of various techniques used for determining the working length in teeth with external root resorption (ERR), a condition that poses a significant diagnostic and therapeutic challenge in endodontics. The four methods evaluated were two electronic apex locators (Apex Locator 1 and Apex Locator 2), intraoral periapical radiography (IOPA), and cone-beam computed tomography (CBCT).\u003c/p\u003e\n\u003cp\u003eThrough a combination of statistical analyses, including mean and standard deviation evaluations, independent t-tests, and one-way ANOVA, the study provided a robust comparison of the precision and reliability of each technique. While all modalities demonstrated some level of accuracy, important differences were observed in their consistency and clinical applicability. Apex Locator 1 emerged as a particularly reliable option with low variability, and CBCT outperformed all techniques in precision, though with considerations regarding accessibility and radiation exposure.\u003c/p\u003e\n\u003cp\u003eThe results were contextualized through comparisons with recent literature, highlighting alignment with findings that confirm the superior performance of CBCT and newer-generation apex locators in accurate working length determination. Meanwhile, the limitations of IOPA, especially in cases of resorptive defects or apical anatomical variations, were reinforced.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003e\u003cu\u003e4.3 Conclusion:\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u003cu\u003eAccording to the results of this study, it was concluded that:\u003c/u\u003e\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eApex Locator 1 demonstrated the most favorable balance between accuracy and consistency, with a lower standard deviation and fewer extreme outliers, making it a highly dependable tool in routine clinical settings.\u003c/li\u003e\n \u003cli\u003eApex Locator 2 showed slightly better average accuracy but higher variability, indicating that although it can be effective, its reliability is less predictable across different clinical scenarios.\u003c/li\u003e\n \u003cli\u003eCBCT proved to be the most precise technique, showing the least deviation from actual working length and minimal variation. However, its use is best reserved for complex or diagnostically challenging cases due to its higher cost and radiation dose.\u003c/li\u003e\n \u003cli\u003eIntraoral periapical radiography (IOPA) consistently overestimated the working length and showed the greatest inconsistency, reaffirming its limitations, particularly in cases involving ERR or anatomical deviations.\u003c/li\u003e\n \u003cli\u003eStatistical testing confirmed significant differences among the four modalities, reinforcing the clinical value of using apex locators\u0026mdash;particularly Apex Locator 1\u0026mdash;as a practical and effective method for accurate working length determination when CBCT is not feasible.\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch2\u003e\u003cstrong\u003e\u003cu\u003e4.4 Limitations:\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/h2\u003e\n\u003col\u003e\n \u003cli\u003eOne drawback of this study was the limited sample size, which may have influenced the statistical power and generalizability of the results. This was primarily owing to the difficulty in obtaining extracted teeth with verified external root resorption that matched the tight inclusion criteria.\u003c/li\u003e\n \u003cli\u003eAnother limitation of the study was the use of a single type and generation of electronic apex locator, which may not reflect the performance variability among different devices; various apex locators operate on different technologies (e.g., single vs. multiple frequencies), and newer-generation devices may yield different levels of accuracy, particularly in the presence of external root resorption.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCBCT: Cone-Beam Computed Tomography\u003c/p\u003e\n\u003cp\u003eEAL: Electronic Apex Locator\u003c/p\u003e\n\u003cp\u003eERR: External Root Resorption\u003c/p\u003e\n\u003cp\u003eIOPA: Intraoral Periapical Radiography\u003c/p\u003e\n\u003cp\u003eWL: Working Length\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e2-Ethics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis in vitro study involved only the use of extracted human teeth, with no involvement of live human or animal subjects. Ethical approval for exemption was granted by the Research Ethics Committee, College of Dentistry, City University Ajman, United Arab Emirates (protocol waived based on national guidelines for research using anonymized extracted tissue). The requirement for informed consent was also waived by the same ethics committee, as no identifiable human data were used, in compliance with applicable national regulations. This study adhered to the principles outlined in the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3-Consent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4-Availability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article. Further details can be obtained upon reasonable request from the corresponding author at [email protected] or co-author at [email protected].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5-Competing Interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6-Funding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo specific funding was received for this study from any public, commercial, or not-for-profit entities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7-Authors' contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eToka Akil carried out the experimental procedures, data collection, and drafted the manuscript.\u003cbr\u003e\u0026nbsp;Ali A. Razooki and Nader Nabil Fouad Rezallah supervised the study, contributed substantially to the study's conception and design, provided intellectual input, and critically revised the manuscript.\u003cbr\u003e\u0026nbsp;Farah Albanna and Ahmed Tarek assisted in methodological guidance, experimental execution, data interpretation, and manuscript revision.\u003cbr\u003e\u0026nbsp;All authors read, revised, and approved the final manuscript and agreed to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e8-Acknowledgements:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI would like to take this opportunity to sincerely express my appreciation for all the help, as well as the endless and selfless support, given to me by all my loved ones who stood by me throughout my final year.\u003c/p\u003e\n\u003cp\u003eFirst, I would like to express my deepest gratitude to my supervisors, \u003cstrong\u003eDr. Ali Razooki\u003c/strong\u003e and \u003cstrong\u003eDr. Nader Nabil\u003c/strong\u003e, for their invaluable guidance, insightful feedback, and continuous encouragement throughout the course of my research. Their expertise and dedication played a crucial role in shaping this work.\u003c/p\u003e\n\u003cp\u003eI am also sincerely thankful to my co-supervisors, \u003cstrong\u003eDr. Farah ALbanna\u003c/strong\u003e and \u003cstrong\u003eDr. Ahmed Tarek\u003c/strong\u003e, for their constant support, constructive suggestions, and the time they dedicated to helping me navigate challenges during this journey. Their contributions greatly enriched the quality and depth of my research.\u003c/p\u003e\n\u003cp\u003eA special thanks goes to \u003cstrong\u003eDr. Yasser ELramady\u003c/strong\u003e for his unwavering support and encouragement. His belief in my potential and his assistance in various stages of the project were truly motivating.\u003c/p\u003e\n\u003cp\u003eI would also like to extend my heartfelt thanks to my partner and best friend, \u003cstrong\u003eRaghad Ammar\u003c/strong\u003e, for always being by my side. Her help and emotional support meant the world to me and kept me going through difficult times.\u003c/p\u003e\n\u003cp\u003eFinally, I am profoundly grateful to my \u003cstrong\u003eFamily\u003c/strong\u003e for their unconditional love, sacrifices, and encouragement. Their belief in me has been the foundation of my academic journey, and I owe much of my success to their endless support.\u003c/p\u003e\n\u003cp\u003eThank you all.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKeratiotis G, Kournetas N, Agrafioti A, Kontakiotis EG. A comparative evaluation of two working length determination methods. Australian Endodontic J [Internet]. 2018;45(3):331\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKeratiotis G, Kournetas N, Agrafioti A, Kontakiotis EG. A comparative evaluation of two working length determination methods. Australian Endodontic J [Internet]. 2018;45(3):331\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSj\u0026ouml;gren U, H\u0026auml;gglund B, Sundqvist G. The effect of four root canal irrigants on the removal of the smear layer of human dentin in vitro. Int Endod J. 1990;23(2):77\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKumar A, Singh K, Kumar S. Comparison of electronic apex locators with radiographic methods for working length determination: An in vivo study. J Clin Diagn Res. 2018;12(5):ZC01\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShah N, Sinha A, Arora V. Accuracy of electronic apex locators in teeth with different root morphologies. J Endod. 2013;39(5):666\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMente J, Glickman G, Schmalz G. Comparison of working length determination with electronic apex locators and radiography. J Endod. 2014;40(12):2024\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePitt Ford TR, Torabinejad M, White DJ. The use of cone-beam computed tomography in endodontics. Br Dent J. 2000;189(1):39\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePatel S, Durack C, Abella F, et al. The potential of cone-beam computed tomography in the management of endodontic problems. Int Endod J. 2015;48(10):926\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMatherne G, Angelopoulos C, Kulild JC, et al. Use of cone-beam computed tomography to identify root canal systems in vivo. J Endod. 2008;34(3):262\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShah N, Sinha A, Arora V. Accuracy of electronic apex locators in teeth with open apices. J Endod. 2015;41(4):523\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilcox LJ, et al. Impact of external root resorption on root canal treatment. J Dent Res. 2017;96(4):443\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePatel S, Dawood A, Ford TP, et al. External root resorption: A review of diagnostic features and management. J Conserv Dent. 2019;22(2):103\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHeithersay GS. Invasive cervical resorption: an analysis of 22 cases. J Endod. 1999;25(8):517\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePatel S, Ricucci D, Mu\u0026ntilde;oz CC, et al. Imaging of root resorption: a review. Dent Clin North Am. 2015;56(2):319\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eH\u0026uuml;lsmann M, Sattapan B, Br\u0026uuml;ning B, et al. External root resorption\u0026mdash;A review. Int Endod J. 2005;38(2):89\u0026ndash;107.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMullier A, Boulanger Y, Berryman S. Assessment of root resorption using CBCT: A systematic review. J Oral Maxillofac Res. 2020;11(3):e2.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu H, Yang Y, Wang Y, et al. Evaluation of root length measurement techniques in endodontics. J Endod. 2017;43(9):1477\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDe Moor R, Deroose C, Van de Velde T, et al. Comparison of working length determination techniques. Int Endod J. 2014;47(4):340\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKobayashi C, Buzalaf MA, de Oliveira NS, et al. The role of CBCT in the assessment of root resorption. J Endod. 2019;45(12):1426\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eH\u0026uuml;lsmann M, Schinkel I, Sch\u0026auml;fers F, et al. Accuracy of electronic apex locators: A systematic review. Int Endod J. 2010;43(7):585\u0026ndash;601.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNasiri K, Wrbas KT. Accuracy of different generations of apex locators in determining working length: a systematic review and meta-analysis. Saudi Dent J. 2022;34:11\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBhagat PS, et al. Comparative evaluation of accuracy of different generations of electronic apex locators: A systematic review and meta-analysis. Endodontology. 2023;35:202\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGolvankar K, et al. Comparison of accuracy in determining the root canal working length by using two generations of apex locators: An in vitro study. OAMJMS. 2019;7(19):3276\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRamezani M, et al. Accuracy of three types of apex locators versus digital periapical radiography for working length determination in maxillary premolars: An in vitro study. Clin Pract. 2022;12(6):1043\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoel T, et al. Comparative evaluation of working length using conventional radiographic method, radiovisiography, and apex locator in single-rooted permanent teeth. JOHCD. 2021;15(2):49\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKamaraj PS, et al. Comparison of five different methods of working length determination: An ex vivo study. Endodontology. 2020;32:187\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHasheminia SM, et al. Comparison of the accuracy of apex locator, digital radiography, and CBCT in root canal working length determination in teeth with ERR: An in vitro study. Dent Res J. 2024;21:8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNanda Kishor KM. Comparison of working length determination using apex locator, conventional radiography and radiovisiography: An in vitro study. J Contemp Dent Pract. 2012;13(4):550\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Graph","content":"\u003cp\u003eGraph 1 and 2 are available in the Supplementary Files section.\u003c/p\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":"external root resorption, digital radiograph, electronic apex locator, cone-beam computed tomography","lastPublishedDoi":"10.21203/rs.3.rs-7168945/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7168945/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjectives\u003c/h2\u003e\u003cp\u003eThe aim of this study is to compare the accuracy of CBCT, IOPA, and various electronic apex locators against the control group (Actual Working Length determination through visualization method using K-file size #15 under Microscope) in teeth with external root resorption.\u003c/p\u003e\u003ch2\u003eMaterials and methods\u003c/h2\u003e\u003cp\u003eIn this in vitro study, the sample consisted of 13 extracted permanent human teeth. External Root Resorption was induced at the 3 mm apical root. The control group will represent the actual working length (WL) that\u0026rsquo;s measured with a K-file #15 until the file tip can be seen visually at the apical foramen by using the CJ-Optic Flexion microscope. Then the teeth were placed in alginate, and the WL for each tooth was measured using two brands of electronic apex locators (APEX-S and RAYPEX 6) with a K-file #15. Measurements of WL from the file tip to the base of the rubber stopper at the reference point were done using a digital calliper (Mitutoyo 550-331-20 digital calliper, Japan). The teeth were then fixed with wax into a gypsum model, and radiographic techniques, including periapical technique \u0026amp; CBCT, were used to record the WL. The WL of each method was statistically compared with the actual WL (control group) using one-way ANOVA with p\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e\u003cp\u003eOne-way ANOVA test showed statistically significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between all groups compared to the control group (actual WL). Whereas the Independent T-Test showed no statistically significant differences between APEX-S EAL and RAYPEX 6.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThis study showed that there was a significant difference between the actual WL and the digital periapical radiography, CBCT, and two types of EAL. Thus, the combination of EAL and CBCT could be a reliable method for determining WL in the presence of ERR.\u003c/p\u003e","manuscriptTitle":"Comparative Study of Working Length Determination in Teeth with External Root Resorption Using Clinical and Radiographic Techniques: In Vitro Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-22 12:50:18","doi":"10.21203/rs.3.rs-7168945/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":"cf12f070-fab3-407d-80ec-31651d84c615","owner":[],"postedDate":"September 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-08T05:54:05+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-22 12:50:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7168945","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7168945","identity":"rs-7168945","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}