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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <title>Human Resources: Background Checks Process Has Improved, but Some Inefficiencies and Gaps Persist</title>
      <link>https://trid.trb.org/View/1567061</link>
      <description><![CDATA[In July 2012, the Amtrak Office of Inspector General (OIG) reported that Amtrak’s background check process for hired employees lacked significant management control. This review provides an update on Amtrak’s actions taken to address the July 2012 report and assesses the effectiveness of current background checks for company employees and contractors. A sample of employees hired during FY2017 were evaluated. It was determined that the company has strengthened the effectiveness of the background check process. Only 7 of the 1,293 new employees hired in FY2017 started to work prior to completion of background checks. However, Amtrak does not oversee that contractors have conducted background checks. OIG recommends that Amtrak: (1) hold  background check vendors responsible and (2) ensure that contractors use approved vendors for background checks that meet company standards and that departments know who is responsible for ensuring contractors have completed the required checks.]]></description>
      <pubDate>Wed, 13 Mar 2019 15:55:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/1567061</guid>
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    <item>
      <title>Frontal Obstacle Detection Using Background Subtraction and Frame Registration</title>
      <link>https://trid.trb.org/View/1491262</link>
      <description><![CDATA[Systems such as Automatic Train Protection and moving block sections help prevent trains colliding, however collisions with unexpected obstacles in front of a train can only be avoided if seen by the driver. In an effort to reduce the possibility of this type of collision and to improve passenger safety, an obstacle detection method has been proposed using a monocular camera and image processing. The proposed method can detect obstacles by comparing live images from the camera with images obtained by other trains operating earlier along the same route. The difference between the two sets of images are defined as obstacles. The performance of the method was verified by conducting experiments using rolling stock and imitation obstacles.]]></description>
      <pubDate>Wed, 27 Dec 2017 10:29:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/1491262</guid>
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      <title>Comparison of Background Subtraction Methods on Near Infra-Red Spectrum Video Sequences</title>
      <link>https://trid.trb.org/View/1472216</link>
      <description><![CDATA[Background subtraction methods are used to detect foregrounds objects in video sequences. However, a lot of parameters of video sequence could complicate this process. Like noise, moving trees, rain, wind etc. Most popular methods are based on Gaussian mixture models (GMM). Four methods based on GMM were used: GMG, KNN, MOG, MOG2. Comparison is realized by using twenty video sequences captured in near infrared spectrum. Each video sequence has one or more moving wild mammals. On twenty randomly selected frames the moving objects are manually segmented for each video. Manual segmentation is done by group of people. Then, results from background subtraction methods are compared opposite to human segmentation by using brute force matcher and were improved by using Radon transformation. From results is obvious the KNN has the biggest similarity opposite to human segmentation. The method with the best correlation opposite to human segmentation will be used in near future for animal detection purpose.]]></description>
      <pubDate>Tue, 29 Aug 2017 10:13:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/1472216</guid>
    </item>
    <item>
      <title>Accurate Detection of Moving Regions via a Nested Model</title>
      <link>https://trid.trb.org/View/1349062</link>
      <description><![CDATA[A nested model with multiple features is represented to accurately detect moving objects and their shadows in outdoor and indoor scenes, even when the moving objects and their shadows have similar color to the background or when there is background motion. Bag of features (color, texture and movement patterns) is first extracted in each frame of an image sequence, and its temporal variation is calculated in the consecutive frames. States of the bag of features are then selected and updated according to the statistical computing during all the previous frames. Pixels with the most stability are considered as background, and moving objects and their shadows are therefore extracted. Experimental results on the authors captured image sequences and public image sequences demonstrate the efficiency of the method.]]></description>
      <pubDate>Thu, 28 May 2015 09:24:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/1349062</guid>
    </item>
    <item>
      <title>Adaptive Multicue Background Subtraction for Robust Vehicle Counting and Classification</title>
      <link>https://trid.trb.org/View/1217975</link>
      <description><![CDATA[In this paper, we present a robust vision-based system for vehicle tracking and classification devised for traffic flow surveillance. The system performs in real time, achieving good results, even in challenging situations, such as with moving casted shadows on sunny days, headlight reflections on the road, rainy days, and traffic jams, using only a single standard camera. We propose a robust adaptive multicue segmentation strategy that detects foreground pixels corresponding to moving and stopped vehicles, even with noisy images due to compression. First, the approach adaptively thresholds a combination of luminance and chromaticity disparity maps between the learned background and the current frame. It then adds extra features derived from gradient differences to improve the segmentation of dark vehicles with casted shadows and removes headlight reflections on the road. The segmentation is further used by a two-step tracking approach, which combines the simplicity of a linear 2-D Kalman filter and the complexity of a 3-D volume estimation using Markov chain Monte Carlo (MCMC) methods. Experimental results show that our method can count and classify vehicles in real time with a high level of performance under different environmental situations comparable with those of inductive loop detectors.]]></description>
      <pubDate>Tue, 20 Aug 2013 09:03:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/1217975</guid>
    </item>
    <item>
      <title>Accurate Motion Detection Using a Self-Adaptive Background Matching Framework</title>
      <link>https://trid.trb.org/View/1217946</link>
      <description><![CDATA[Automatic video surveillance is of critical importance to security in commercial, law enforcement, military, and many other environments due to terrorist activity and other social problems. Generally, motion detection plays an important role as the threshold function of background and moving objects in video surveillance systems. This paper proposes a novel motion detection method with a background model module and an object mask generation module. We propose a self-adaptive background matching method to select the background pixel at each frame with regard to background model generation. After generating the adaptive background model, the binary motion mask can be computed by the proposed object mask generation module that consists of the absolute difference estimation and the Cauchy distribution model. We analyze the detection quality of the proposed method based on qualitative visual inspection. On the other hand, quantitative accuracy measurement is also obtained by using four accuracy metrics, namely, Recall, Precision, Similarity, and F1. Experimental results demonstrate the effectiveness of the proposed method in providing a promising detection outcome and a low computational cost.]]></description>
      <pubDate>Thu, 08 Aug 2013 16:23:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/1217946</guid>
    </item>
    <item>
      <title>Pedestrian Tracking by On-Board Wideview Monocular Camera</title>
      <link>https://trid.trb.org/View/1214932</link>
      <description><![CDATA[This research presents a general algorithm for pedestrian tracking by on-board monocular camera which can be applied to cameras of various view ranges in unified manner. The Spatio-Temporal MRF(S-T MRF) model extracts and tracks foreground objects, under the assumption that background motion of camera can be approximated by a linear function. By this method, both pedestrians and non-pedestrians should be segmented from background motion. Then, Region of Interest (ROI) is classified by a cascaded classifier. However, segmentation result sometime contains error due to the motion of pedestrian. The authors improved the performance of the system by contaminating errors including in foreground objects. After considering the geometrical understanding, the motion difference, and HOG information, the authors combined those features to correct the result of segmentation. The authors confirmed this combination approach drastically improved the performance of pedestrian detection.]]></description>
      <pubDate>Fri, 28 Sep 2012 16:58:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/1214932</guid>
    </item>
    <item>
      <title>Compendium of Student Papers: 2011 Undergraduate Transportation Scholars Program</title>
      <link>https://trid.trb.org/View/1144011</link>
      <description><![CDATA[This report is a compilation of research papers written by students participating in the 2011 Undergraduate Transportation Scholars Program. The 10-week summer program, now in its 21st year, provides undergraduate students in Civil Engineering the opportunity to learn about transportation engineering through participating in sponsored transportation research projects. The program design allows students to interact directly with a Texas A&M University faculty member or Texas Transportation Institute researcher in developing a research proposal, conducting valid research, and documenting the research results through oral presentations and research papers. The papers in this compendium report on the following topics, respectively: 1) evaluating the impact of nighttime work zone lighting characteristics on motorists; 2) late night roadway visibility; 3) investigation of the use and pricing of the I-15 express lanes in San Diego; 4) intercity passenger rail access to airports: a case study at the Milwaukee airport; 5) development of overhead guide sign background complexity assessment tool; 6) identifying pavement preservation treatments suitable for performance-related specifications; and 7) arsenic content and retroreflectivity of glass beads used in pavement markings.]]></description>
      <pubDate>Tue, 24 Jul 2012 08:20:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/1144011</guid>
    </item>
    <item>
      <title>Background Foreground Segmentation for SLAM</title>
      <link>https://trid.trb.org/View/1123359</link>
      <description><![CDATA[To perform simultaneous localization and mapping (SLAM) in dynamic environments, static background objects must first be determined. This condition can be achieved using a priori information in the form of a map of background objects. Such an approach exhibits a causality dilemma, because such a priori information is the ultimate goal of SLAM. In this paper, we propose a background foreground segmentation method that overcomes this issue. Localization is achieved using a robust iterative closest point implementation and vehicle odometry. Background objects are modeled as objects that are consistently located at a given spatial location. To improve robustness, classification is performed at the object level through the integration of a new segmentation method that is robust to partial object occlusion.]]></description>
      <pubDate>Wed, 25 Jan 2012 14:23:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/1123359</guid>
    </item>
    <item>
      <title>Transportation Security Infrastructure Modernization May Enhance DHS Screening Capabilities, but It Is Too Early to Assess Results</title>
      <link>https://trid.trb.org/View/1124351</link>
      <description><![CDATA[Securing transportation systems and facilities requires balancing security to address potential threats while facilitating the flow of people and goods that are critical to the U.S. economy and necessary for supporting international commerce. As the U.S. Government Accountability Office (GAO) has previously reported, transportation systems and facilities are vulnerable and difficult to secure given their size, easy accessibility, large number of potential targets, and proximity to urban areas. The federal government has taken steps to ensure that transportation workers, particularly those who transport hazardous materials or seek unescorted access to secure areas of federally regulated maritime or aviation facilities, are properly vetted to identify whether they pose a security risk. These efforts are intended to reduce the probability of a successful terrorist or other criminal attack on the nation's transportation systems. To help enhance the security of the U.S. transportation system, the Department of Homeland Security (DHS) Transportation Security Administration's (TSA) Transportation Threat Assessment and Credentialing (TTAC) office is responsible for conducting background checks--known as security threat assessments--for various screening and credentialing programs established for maritime, surface, and aviation transportation workers. TSA's programs are largely focused on identifying security threats posed by those individuals seeking to obtain an endorsement, credential, access, and/or privilege (hereafter called a credential) for unescorted access to secure or restricted areas of transportation facilities at maritime ports and airports, and for commercial drivers transporting hazardous materials. These screening and credentialing programs were created under various legal and regulatory authorities, and were established at different times. As a result, according to TSA, these programs and their supporting systems are made up of independent, stand-alone business processes and systems, making it difficult to adapt them to meet expected growth in demand, new requirements, and new capabilities. According to TSA, TTAC screens and/or provides credentials to an estimated 12.5 million individuals per year, and this number is estimated to increase to between 52.5 million to 62.5 million individuals by 2016. However, as indicated in the TTAC Infrastructure Modernization (TIM) program mission needs statement, TTAC does not currently have the capability to support these expanding populations in providing security threat assessment and credentialing services. To address this limitation, TTAC initiated TIM in 2008 to consolidate and standardize TSA's current screening and credentialing systems to better serve transportation worker populations, increase efficiencies, and reduce duplication. DHS has an acquisition management process intended to, among other things, help ensure acquisition programs meet DHS mission needs. As part of this process, the DHS Acquisition Review Board is to conduct systematic reviews of acquisition programs and make recommendations on the appropriate direction for moving forward. The Acquisition Review Board is also expected to provide a consistent method for evaluating an acquisition's progress and status at critical points in the acquisition's life cycle, and is to work with the acquisition decision authority, a member of the Acquisition Review Board, to approve an acquisition to proceed to the next phase in its life cycle. Given the current efforts to coordinate DHS screening and credentialing programs on a departmentwide basis, Congress asked that GAO evaluate TSA's TIM implementation effort. Specifically, this report addresses how the TIM program is being implemented to leverage and enhance existing DHS screening and credentialing capabilities in accordance with DHS policy and acquisition directive and guidance. While TSA initially focused on fixing gaps in TSA-managed screening and credentialing operations, it has since modified its TIM strategy to better leverage and enhance departmentwide capabilities, in accordance with DHS's credentialing framework and acquisition directive and guidance. For example, DHS required the TIM program to identify additional opportunities for leveraging DHS capabilities--or enterprise services--and identify cost efficiencies. TSA initially did not select a course of action that would leverage DHS capabilities beyond what TSA already had in place under its existing programs, such as using or establishing a consolidated enrollment service that could be used by TIM and other DHS components. During the course of GAO's review, however, TSA began to identify capabilities that might be leveraged across DHS. For example, in accordance with DHS direction, in August 2011, the TIM program identified several opportunities for leveraging existing DHS background checking and vetting services. For instance, TSA is now working with DHS's Office of the Chief Information Officer and Screening Coordination Office to establish a common vetting service, which could reduce duplication among other DHS services. Eliminating redundant activities across multiple screening and credentialing programs could help support the goals of DHS's credentialing framework initiative. However, as of the date of this report, the programs that are to use this vetting service have not yet been determined. It is therefore too early to tell the extent to which, once implemented, these initiatives would enhance screening and credentialing capabilities across DHS.]]></description>
      <pubDate>Fri, 16 Dec 2011 14:47:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/1124351</guid>
    </item>
    <item>
      <title>The Transportation Security Clearinghouse: Past, Present and Future</title>
      <link>https://trid.trb.org/View/1117063</link>
      <description><![CDATA[Prior to the events of September 11, 2001, a very small percentage of airport workers were required to submit fingerprints for Criminal History Records Checks (CHRCs) conducted by the Federal Bureau of Investigation (FBI). One of the first regulations put in place after that date was the federal mandate requiring airport operators to conduct a CHRC for each employee or individual applying for a job in any secure area of the airport. The Transportation Security Clearinghouse (TSC) was created in order to speed up the process of background vetting and has had to adapt, over time, to growing and more complex requirements, such as Security Threat Assessments (STA). More recently, the TSC has developed a secure web-based messaging system as an alternative to spreadsheets for submitting STA data, known as Automated Integration Services (AIS). The TSC is now the nation's largest civilian clearinghouse, and has held steadfast to its mission of easing the regulatory burden of the aviation industry.]]></description>
      <pubDate>Fri, 23 Sep 2011 07:27:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/1117063</guid>
    </item>
    <item>
      <title>Transportation Worker Identification Credential: Internal Control Weaknesses Need to Be Corrected to Help Achieve Security Objectives</title>
      <link>https://trid.trb.org/View/1102450</link>
      <description><![CDATA[Within the Department of Homeland Security (DHS), the Transportation Security Administration (TSA) and the U.S. Coast Guard manage the Transportation Worker Identification Credential (TWIC) program, which requires maritime workers to complete background checks and obtain a biometric identification card to gain unescorted access to secure areas of regulated maritime facilities. As requested, the U.S. Government Accountability Office (GAO) evaluated the extent to which (1) TWIC processes for enrollment, background checking, and use are designed to provide reasonable assurance that unescorted access to these facilities is limited to qualified individuals; and (2) the effectiveness of TWIC has been assessed. Internal control weaknesses governing the enrollment, background checking, and use of TWIC potentially limit the program’s ability to provide reasonable assurance that access to secure areas of Maritime Transportation Security Act (MTSA)-regulated facilities is restricted to qualified individuals. To meet the stated program purpose, TSA designed TWIC program processes to facilitate the issuance of TWICs to maritime workers. However, TSA did not assess the internal controls designed and in place to determine whether they provided reasonable assurance that the program could meet defined mission needs for limiting access to only qualified individuals. GAO found that internal controls in the enrollment and background checking processes are not designed to provide reasonable assurance that (1) only qualified individuals can acquire TWICs; (2) adjudicators follow a process with clear criteria for applying discretionary authority when applicants are found to have extensive criminal convictions; or (3) once issued a TWIC, TWIC-holders have maintained their eligibility. Further, internal control weaknesses in TWIC enrollment, background checking, and use could have contributed to the breach of MTSA-regulated facilities during covert tests conducted by GAO’s investigators. During covert tests of TWIC use at several selected ports, GAO’s investigators were successful in accessing ports using counterfeit TWICs, authentic TWICs acquired through fraudulent means, and false business cases (i.e., reasons for requesting access). Conducting a control assessment of the TWIC program’s processes to address existing weaknesses could better position DHS to achieve its objectives in controlling unescorted access to the secure areas of MTSA-regulated facilities and vessels. DHS has not assessed the TWIC program’s effectiveness at enhancing security or reducing risk for MTSA-regulated facilities and vessels. Further, DHS has not demonstrated that TWIC, as currently implemented and planned, is more effective than prior approaches used to limit access to ports and facilities, such as using facility specific identity credentials with business cases. Conducting an effectiveness assessment that further identifies and assesses TWIC program security risks and benefits could better position DHS and policymakers to determine the impact of TWIC on enhancing maritime security. Further, DHS did not conduct a risk-informed cost-benefit analysis that considered existing security risks, and it has not yet completed a regulatory analysis for the upcoming rule on using TWIC with card readers. Conducting a regulatory analysis using the information from the internal control and effectiveness assessments as the basis for evaluating the costs, benefits, security risks, and corrective actions needed to implement the TWIC program, could help DHS ensure that the TWIC program is more effective and cost-efficient than existing measures or alternatives at enhancing maritime security. Among other things, GAO recommends that DHS assess TWIC program internal controls to identify needed corrective actions, assess TWIC’s effectiveness, and use the information to identify effective and cost-efficient methods for meeting program objectives.]]></description>
      <pubDate>Wed, 18 May 2011 13:23:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/1102450</guid>
    </item>
    <item>
      <title>Background Subtraction Methods for Motion Detection in Video Surveillance Systems</title>
      <link>https://trid.trb.org/View/1082910</link>
      <description><![CDATA[A main activity of many computer vision systems is foreground object detection. Motion is used in a video sequence to identify target objects. Many background subtraction methods have been proposed to identify motion that belongs to a moving object. Each has advantages and disadvantages when applied under different conditions. This paper proposes an overview of 5 background subtraction methods. One of the features that was found was that the more complex methods, such as Kernel Density Estimate and mixture of Gaussians, achieve more high precision and recall when applied to practice. Lower precision and recall resulted from the more basic methods. However, the more basic methods are less expensive in computational costs.]]></description>
      <pubDate>Wed, 15 Dec 2010 08:57:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/1082910</guid>
    </item>
    <item>
      <title>Modeling of Evacuation and Background Traffic for Optimal Zone-Based Vehicle Evacuation Strategy</title>
      <link>https://trid.trb.org/View/910883</link>
      <description><![CDATA[This paper discusses details of developing an optimal zone-based vehicle evacuation strategy based on an optimization–simulation approach. The optimal egress strategy is obtained by solving a universal quickest flow problem, and the solution is implemented and evaluated in a mesoscopic simulation model. Evacuees would follow optimal routes to safe locations outside the hot zone and then select behaviorally realistic routes to their final destinations. Background traffic is included in the model to simulate more realistic traffic conditions. The route choice of background traffic in response to the evacuation strategy and driver information strategies is carefully addressed. Operational issues such as temporal loading intensity and queuing at parking lots are also modeled and discussed. The modeling framework has been applied to a bomb threat scenario at a football stadium. The case study shows that the proposed methods generate reasonable and meaningful results for the intended no-notice scenario.]]></description>
      <pubDate>Tue, 16 Mar 2010 06:11:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/910883</guid>
    </item>
    <item>
      <title>Aviation Security: A National Strategy and Other Actions Would Strengthen TSA’s Efforts to Secure Commercial Airport Perimeters and Access Controls</title>
      <link>https://trid.trb.org/View/901824</link>
      <description><![CDATA[Incidents of airport workers using access privileges to smuggle weapons through secured airport areas and onto planes have heightened concerns regarding commercial airport security. The Transportation Security Administration (TSA), along with airports, is responsible for security at TSA-regulated airports. To guide risk assessment and protection of critical infrastructure, including airports, the Department of Homeland Security (DHS) developed the National Infrastructure Protection Plan (NIPP). The U.S. Government Accountability Office (GAO) was asked to examine the extent to which, for airport perimeters and access controls, TSA (1) assessed risk consistent with the NIPP; (2) implemented protective programs, and evaluated its worker screening pilots; and (3) established a strategy to guide decision making. Although TSA has implemented activities to assess risks to airport perimeters and access controls, such as a commercial aviation threat assessment, it has not conducted vulnerability assessments for 87 percent of the nation’s approximately 450 commercial airports or any consequence assessments. As a result, TSA has not completed a comprehensive risk assessment combining threat, vulnerability, and consequence assessments as required by the NIPP. While TSA officials said they intend to conduct a consequence assessment and additional vulnerability assessments, TSA could not provide further details, such as milestones for their completion. Conducting a comprehensive risk assessment and establishing milestones for its completion would provide additional assurance that intended actions will be implemented, provide critical information to enhance TSA’s understanding of risks to airports, and help ensure resources are allocated to the highest security priorities. Since 2004, TSA has taken steps to strengthen airport security and implement new programs; however, while TSA conducted a pilot program to test worker screening methods, clear conclusions could not be drawn because of significant design limitations and TSA did not document key aspects of the pilot. TSA has taken steps to enhance airport security by, among other things, expanding its requirements for conducting worker background checks and implementing a worker screening program. In fiscal year 2008 TSA pilot tested various methods to screen airport workers to compare the benefits, costs, and impacts of 100 percent worker screening and random worker screening. TSA designed and implemented the pilot in coordination with the Homeland Security Institute (HSI), a federally funded research and development center. However, because of significant limitations in the design and evaluation of the pilot, such as the limited number of participating airports—7 out of about 450—it is unclear which method is more cost-effective. TSA and HSI also did not document key aspects of the pilot’s design, methodology, and evaluation, such as a data analysis plan, limiting the usefulness of these efforts. A well-developed and well-documented evaluation plan can help ensure that pilots generate needed performance information to make effective decisions. While TSA has completed these pilots, developing an evaluation plan for future pilots could help ensure that they are designed and implemented to provide management and Congress with necessary information for decision making. TSA’s efforts to enhance the security of the nation’s airports have not been guided by a unifying national strategy that identifies key elements, such as goals, priorities, performance measures, and required resources. For example, while TSA’s various airport security efforts are implemented by federal and local airport officials, TSA officials said that they have not identified or estimated costs to airport operators for implementing security requirements. GAO has found that national strategies that identify these key elements strengthen decision making and accountability; in addition, developing a strategy with these elements could help ensure that TSA prioritizes its activities and uses resources efficiently to achieve intended outcomes. GAO recommends, among other things, that TSA develop a comprehensive risk assessment of airport security, and milestones for its completion; an evaluation plan for any future airport security pilot programs; and a national strategy for airport security that includes key characteristics, such as goals and priorities.]]></description>
      <pubDate>Tue, 20 Oct 2009 07:41:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/901824</guid>
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