Journal of Rail Transport Planning & Management最新文献

英文中文

Integrating AI and edge computing for advanced safety at railroad grade crossings 集成人工智能和边缘计算，提高铁路平交道口的安全性

IF 2.6 Q3 TRANSPORTATION

Journal of Rail Transport Planning & Management

Pub Date : 2025-03-01 Epub Date: 2024-12-24 DOI: 10.1016/j.jrtpm.2024.100501

A.L. Amin , Deo Chimba , Kamrul Hasan

The integration of artificial intelligence (AI) and machine learning (ML) into the Railroad High-Grade Crossing (RHGC) systems represents a significant milestone in enhancing both safety and operational efficiency. The fusion of various technologies enables the seamless integration of real-time identification, accurate forecasting, and prompt reaction to pivotal traffic situations. This research introduces a state-of-the-art architecture based on edge cloud technology. It integrates advanced computer vision algorithms for object detection and segmentation with a custom dataset for RHGC safety. In the proposed novel framework, we utilize a Weighted box- Fusion (WBF) ensemble approach, integrating diverse object detection algorithms, such as YOLOv8M (medium), YOLOv8L (Large), and YOLOv8X (extra-large), to enhance the detection of safety measures at RHGCs objects. Moreover, we incorporate a UNet segmentation model to identify trains approaching the RHGCs. The amalgamation of these methodologies leads to a fully automated, AI-driven safety mechanism for RHGC. The edge-cloud architecture is employed, with surveillance cameras linked directly to an edge server strategically positioned at grade crossings. This arrangement facilitates real-time data processing, ensuring efficient bandwidth usage and minimal latency by relaying only the necessary processed information to the cloud. Our ensemble model demonstrated an impressive precision rate of 97%, with the segmentation model achieving a higher rate of 98%. This system establishes a novel standard within the discipline, amalgamating artificial intelligence, edge computing, and cloud technology to significantly augment safety and efficiency at grade crossings.

将人工智能（AI）和机器学习（ML）集成到铁路高等级道口（RHGC）系统中，是提高安全性和运营效率的重要里程碑。多种技术的融合，实现了对关键交通状况的实时识别、准确预测和快速反应的无缝集成。本研究介绍了一种基于边缘云技术的最先进架构。它将用于对象检测和分割的先进计算机视觉算法与用于RHGC安全的自定义数据集集成在一起。在提出的新框架中，我们利用加权盒融合（WBF）集成方法，集成了多种目标检测算法，如YOLOv8M（中型），YOLOv8L（大型）和YOLOv8X（超大型），以增强对rhgc目标安全措施的检测。此外，我们结合了UNet分割模型来识别接近rhgc的列车。这些方法的融合为RHGC带来了一个完全自动化的、人工智能驱动的安全机制。采用边缘云架构，监控摄像头直接连接到位于十字路口的边缘服务器。这种安排促进了实时数据处理，通过仅将必要的处理信息转发到云，确保了有效的带宽使用和最小的延迟。我们的集成模型显示了令人印象深刻的97%的准确率，分割模型达到了98%的更高准确率。该系统在该学科内建立了一个新的标准，将人工智能、边缘计算和云技术相结合，显著提高了平交道口的安全性和效率。

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引用次数: 0

A study on sorting strategies in marshaling yards with a limited number of tracks and track capacity 轨道数量和轨道容量有限的编组站分拣策略研究

IF 2.6 Q3 TRANSPORTATION

Journal of Rail Transport Planning & Management

Pub Date : 2025-03-01 Epub Date: 2024-12-17 DOI: 10.1016/j.jrtpm.2024.100498

Max Zien , Thomas Kirschstein , Christian Bierwirth

In marshaling yards, freight wagons are sorted from inbound trains to outbound trains for further transport. To organize an efficient shunting process, sorting strategies are proposed in the literature. The application of sorting strategies is generally restricted by the number of classification tracks and their lengths. This can lead to difficult-to-implement or even inoperative sorting plans. To handle limited track capacity, we decompose the shunting process into a series of consecutive periods of time resembling timetables of inbound trains. A heuristic is used in every period to decide on the postponement of inbound trains when track capacity is scarce. This way, sorting strategies become applicable on a rolling time basis. A strategy is said to solve a shunting task when it enables building all outbound trains within a given time horizon. We examine the performance of five well-known sorting strategies for a large set of shunting tasks within a computational study. The simulation results indicate that the sorting strategies perform differently when numbers and lengths of classification tracks vary. In conclusion, we are able to determine the most reliable strategy among the set of considered sorting strategies for a marshaling yard of a certain size.

在编组站，货车被从进站列车分拣到出站列车，以便进一步运输。为了组织一个有效的分流过程，在文献中提出了排序策略。排序策略的应用通常受到分类轨迹数量及其长度的限制。这可能导致难以实现甚至无效的分类计划。为了处理有限的轨道容量，我们将调车过程分解为一系列连续的时间段，类似于进站列车的时间表。在轨道容量不足的情况下，每个时段都采用启发式方法决定入站列车的延迟。这样，排序策略就可以在滚动时间的基础上应用。当一种策略能够在给定的时间范围内建造所有出站列车时，我们就说它解决了一个分流任务。在一项计算研究中，我们研究了五种著名的排序策略对大量分流任务的性能。仿真结果表明，当分类轨迹的数量和长度不同时，分类策略的表现不同。总之，对于一定规模的编组场，我们能够在考虑的一组排序策略中确定最可靠的策略。

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引用次数: 0

Efficient real-time rail traffic optimization: Decomposition of rerouting, reordering, and rescheduling problems 有效的实时轨道交通优化：重新路由、重新排序和重新调度问题的分解

IF 2.6 Q3 TRANSPORTATION

Journal of Rail Transport Planning & Management

Pub Date : 2025-03-01 Epub Date: 2024-12-11 DOI: 10.1016/j.jrtpm.2024.100496

István Ferenc Lövétei, László Lindenmaier, Szilárd Aradi

The real-time railway traffic management problem occurs when the pre-planned timetable cannot be kept due to various disturbances; therefore, the trains must be rerouted, reordered, and rescheduled. Optimizing the real-time railway traffic management aims to resolve conflicts, minimizing the delay propagation or energy consumption. In one of our previous works, the existing mixed-integer linear programming optimization models are extended considering a safety-relevant issue of railway traffic management, the overlaps. However, solving the extended model can be time-consuming in complex control areas and traffic situations involving numerous trains. Therefore, we propose different computationally efficient multi-stage models by decomposing the problem according to the rerouting, reordering, and rescheduling sub-problems. First, a lightweight heuristic MILP model that provides a fast but sub-optimal solution is given by reformulating the train delays into pair-wise interpretation. Second, we extend the heuristic model to grant an optimal solution to the original problem faster than the existing MILP formulations. The impact of the model decomposition is investigated mathematically and experimentally in various realistic simulated traffic scenarios concerning the optimization’s objective value and computational demand. The proposed multi-stage models significantly decrease the optimization runtime of both the original and the extended railway traffic management problems.

铁路交通的实时管理问题是由于各种干扰导致预定的时刻表无法保持；因此，火车必须改道，重新订购，重新安排时间。优化铁路交通实时管理的目的是解决冲突，使延误传播或能量消耗最小化。在我们之前的一项工作中，对现有的混合整数线性规划优化模型进行了扩展，考虑了铁路交通管理中与安全相关的问题，即重叠。然而，在复杂的控制区域和涉及大量列车的交通情况下，求解扩展模型可能会耗费大量时间。因此，我们根据重路由、重排序和重调度子问题对问题进行分解，提出不同的计算效率高的多阶段模型。首先，通过将列车延误重新表述为成对解释，给出了一个轻量级启发式MILP模型，该模型提供了一个快速但次优的解决方案。其次，我们扩展了启发式模型，使其比现有的MILP公式更快地给出原始问题的最优解。在各种现实的模拟交通场景中，通过数学和实验研究了模型分解对优化目标值和计算需求的影响。所提出的多阶段模型大大缩短了原轨道交通管理问题和扩展轨道交通管理问题的优化运行时间。

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引用次数: 0

Capacity evaluation of ERTMS/ETCS HTD and moving block ERTMS/ETCS HTD和移动块的容量评估

IF 2.6 Q3 TRANSPORTATION

Journal of Rail Transport Planning & Management

Pub Date : 2025-03-01 Epub Date: 2025-02-03 DOI: 10.1016/j.jrtpm.2025.100506

Daniel Knutsen , Nils O.E. Olsson , Jiali Fu , Tomas Rosberg

This paper compares the capacity effect of different implementations of ERTMS/ETCS (European Rail Traffic Management System/The European Train Control System): Hybrid Train Detection (HTD) and moving block. This is done both on a conceptual level by looking at a scenario involving two trains, and for a simulated network. The effects are studied by modelling HTD and moving block in the simulation tool RailSys, looking at the performance indicators related to capacity: headway, capacity utilisation, and punctuality. The model uses existing infrastructure and a complete timetable. The results of the scenario with two trains show that similar results on headway can be achieved with HTD compared to moving block This is true even with relatively long virtual blocks of 500 m. The results from the simulated network show that various shares of trains with train integrity, as well as moving block, have a minor effect on the performance indicator punctuality. Moving block gives some improvements on capacity utilisation compared to HTD. However, by implementing shorter virtual blocks at sections of lower speed, it is possible to achieve results on capacity utilisation like that engendered by moving block.

本文比较了ERTMS/ETCS（欧洲轨道交通管理系统/欧洲列车控制系统）、混合列车检测（HTD）和移动阻塞的不同实施方式的容量效应。这是在概念层面上通过查看涉及两列火车的场景和模拟网络来完成的。通过在仿真工具RailSys中模拟HTD和移动块来研究其影响，并查看与容量相关的性能指标：车头时距、容量利用率和准点率。该模型使用现有的基础设施和完整的时间表。两列火车的场景结果表明，与移动街区相比，HTD可以获得相似的车头时距结果，即使是相对较长的500米虚拟街区也是如此。仿真结果表明，列车完整性的不同份额以及运行阻塞对性能指标正点率的影响较小。与HTD相比，移动块在容量利用率方面有一些改进。然而，通过在较低速度的部分实现较短的虚拟块，可以实现像移动块那样的容量利用结果。

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引用次数: 0

Rail freight transportation service network design with mixed blocking policies: Formulation and solution methods 混合阻塞策略下的铁路货运服务网络设计：制定与解决方法

IF 2.6 Q3 TRANSPORTATION

Journal of Rail Transport Planning & Management

Pub Date : 2025-03-01 Epub Date: 2024-12-13 DOI: 10.1016/j.jrtpm.2024.100495

Xiaoyu Xin , Xu Wu , Jiaxi Wang

In the current China railway system, the freight transportation service network is demand category oriented and is designed by using a hierarchical approach. This simplifies the design procedure, but reduces the flexibility and optimality of the plan. To make full use of the limited railway capacity and to improve the service flexibility and quality, this paper addresses the freight service network design problem with simultaneous consideration of mixed blocking policies and mixed service classes for heterogeneous demands. A mixed integer linear programming model is developed for the problem to maximize the operator's total transportation profit. Furthermore, a two-stage decomposition framework is proposed to solve the optimization model, where both exact and heuristic algorithms are employed. Extensive computational experiments on artificial and real-world instances indicate that the proposed solution approaches can generate high-quality solutions within reasonable time frame. Moreover, the mixed blocking policies could attract more freight demands and tend to result in higher profits, compared to the single blocking policy.

在目前的中国铁路系统中，货物运输服务网络是以需求类别为导向，采用分层方法设计的。这简化了设计过程，但降低了规划的灵活性和最优性。为了充分利用有限的铁路运力，提高服务的灵活性和质量，本文研究了针对异构需求同时考虑混合阻塞策略和混合服务等级的货运服务网络设计问题。建立了以运输商总利润最大化为目标的混合整数线性规划模型。在此基础上，提出了一种采用精确算法和启发式算法求解优化模型的两阶段分解框架。大量的人工和现实实例计算实验表明，所提出的求解方法可以在合理的时间框架内生成高质量的解。此外，与单一封锁政策相比，混合封锁政策可以吸引更多的货运需求，往往会产生更高的利润。

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引用次数: 0

Introducing the concept of grades of automation for shunting operations 介绍了调车作业自动化等级的概念

IF 2.6 Q3 TRANSPORTATION

Journal of Rail Transport Planning & Management

Pub Date : 2025-03-01 Epub Date: 2024-12-20 DOI: 10.1016/j.jrtpm.2024.100500

Matthias Reichmann , Gabriel Stephan Himmelbauer , Adrian Wagner , Jürgen Zajicek , Burkhard Stadlmann , Herbert Wancura , Nikolaus Furian , Siegfried Vössner

In Europe political decisions have been made to shift freight traffic from roads to railways, triggering substantial efforts to digitize and automate processes in the rail freight domain. As currently, only automation taxonomies for driving in rail networks exist, this paper provides a taxonomy for operations in so-called marshaling yards. Marshaling yards are critical nodes in the rail freight network, where the wagons of arriving trains are separated and are distributed to outgoing trains. Using the Design Science Research Cycles of Hevner to ensure a transparent procedure, this work develops Grades of Automation for Shunting Operations. The key outcome is a systematic classification together with a pictorial representation of these Grades of Automation, providing an overview of basic Shunting Operations and their functional realizations. This taxonomy facilitates a comparison of automation levels across different marshaling yards, aiding rail freight undertakings in planning efficient transport routes within the rail freight network.

在欧洲，已经做出了将货运从公路转向铁路的政治决定，引发了铁路货运领域数字化和自动化流程的大量努力。由于目前只有铁路网络中驾驶的自动化分类存在，本文提供了所谓编组站操作的分类。编组站是铁路货运网络的关键节点，在这里进站列车的车厢被分开并分配给出站列车。使用Hevner的设计科学研究周期来确保透明的程序，这项工作开发了调车操作的自动化等级。关键的成果是系统的分类以及这些自动化等级的图形表示，提供了基本调车操作及其功能实现的概述。这一分类有助于比较不同编组站的自动化水平，帮助铁路货运企业在铁路货运网络内规划有效的运输路线。

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引用次数: 0

Demand-based capacity assessment using mixed integer programming 使用混合整数规划的基于需求的容量评估

IF 2.6 Q3 TRANSPORTATION

Journal of Rail Transport Planning & Management

Pub Date : 2025-03-01 Epub Date: 2025-01-15 DOI: 10.1016/j.jrtpm.2024.100502

Christopher Szymula, Nikola Bešinović, Karl Nachtigall

Understanding railway network capacity and potential reserves proves crucial for optimal planning decisions, which are required due to the high utilization of European railway networks and the intended future modal shift to rail. Capacity reserves emerge where the network structure does not match the demand. We propose a mixed integer program (MIP) for investigating the demand-based capacity reserves in the network. Extending the MIP-based railway network utilization model by adding demand structures, our model allows to optimize the train ordering and the locations of trains in the network, whilst regarding for the traffic demand to be served. The infrastructure is mesoscopically modelled by the individual blocks of the railway system. The demand is represented by a corresponding line plan and its given frequencies. The model determines the interrelations of demand and network capacity and thus allows to investigate between transport demand and network infrastructure. We test the proposed model on different artificial networks and a case study. In particular, the results show clear capacity effects of mismatched infrastructural demand and supply. It is thereby shown, that the efficient use of network capacity depends on the fit between demand and network structure. Furthermore, we can see that the emergent utilization behaviour is network specific and often non-linear, which strengthens the necessity of network approaches for global capacity assessment. Also providing support to other fields such as urban planning, the models incorporation to integrated and interdisciplinary planning approaches is left for future research.

了解铁路网络容量和潜在储量对于优化规划决策至关重要，这是由于欧洲铁路网络的高利用率和预期的未来模式向铁路转变所必需的。当网络结构与需求不匹配时，就会出现容量储备。我们提出了一种混合整数规划（MIP）来研究基于需求的电网容量储备。通过增加需求结构，扩展基于mip的铁路网利用模型，我们的模型可以在考虑所要服务的交通需求的同时，优化列车排序和网络中列车的位置。基础设施是由铁路系统的各个模块在细观上建模的。需求由相应的线路平面图及其给定的频率表示。该模型确定了需求和网络容量之间的相互关系，从而可以调查运输需求和网络基础设施之间的关系。我们在不同的人工网络和案例研究中测试了所提出的模型。特别是，研究结果显示了基础设施供需不匹配的产能效应。由此可见，网络容量的有效利用取决于需求与网络结构的契合度。此外，我们可以看到，紧急利用行为是网络特有的，往往是非线性的，这加强了网络方法进行全球容量评估的必要性。同时也为城市规划等其他领域提供了支持，这些模型与综合和跨学科规划方法的结合有待于未来的研究。

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引用次数: 0

Integrated optimization of energy-efficient train timetable and rolling stock circulation plan with regenerative energy utilization 考虑可再生能源利用的节能列车时刻表与车辆流通方案的综合优化

IF 2.6 Q3 TRANSPORTATION

Journal of Rail Transport Planning & Management

Pub Date : 2025-03-01 Epub Date: 2024-12-24 DOI: 10.1016/j.jrtpm.2024.100499

Songwei Zhu , Yihui Wang , Guodong Wei , Yi Zheng , Datian Zhou , Nikola Bes̆inović

With the running and dwell levels considered, we investigate the integrated energy-efficient train timetabling and rolling stock circulation planning problem for a metro line, where the passenger demand is considered via the service pattern. A mixed integer non-linear programming model is proposed to minimize the headway variations, headway deviations, the number of required rolling stocks, and the net energy consumption. Specifically, the regenerative energy utilization is considered by the brake-traction overlapping times. After linearization, the energy-efficient timetabling problem can be solved by existing solvers. A two-step method is presented to enhance the computational efficiency. In the first step, the arrival times of train services at the first station are determined. In the second step, the timetable and rolling stock circulation plan are optimized according to the given arrival times at the first station. Two case studies with different service patterns are conducted based on the data of Beijing Yizhuang metro line. The computational results demonstrate that the two-step method can reduce the optimality gap sharply. Compared with the energy-efficient model without the consideration of regenerative energy utilization, the regenerative energy utilization of the model with regenerative energy utilization considered increases 25.64% and 35.95% in the two test cases, respectively.

在考虑运行水平和停留水平的情况下，研究了通过服务模式考虑乘客需求的地铁线路综合节能列车调度和车辆循环规划问题。提出了一种混合整数非线性规划模型，以最小化车头距变化、车头距偏差、所需车辆数量和净能耗。具体地说，再生能量利用是通过制动-牵引重叠次数来考虑的。线性化后的节能调度问题可以用已有的求解器求解。为了提高计算效率，提出了一种两步法。第一步，确定列车服务到达第一站的时间。第二步，根据给定的到站时间，优化列车时刻表和车辆循环方案。以北京亦庄地铁线路为例，进行了两种不同服务模式的案例分析。计算结果表明，两步法能显著减小最优性间隙。与不考虑可再生能源利用的节能模型相比，考虑可再生能源利用的节能模型在两个测试案例中的可再生能源利用率分别提高了25.64%和35.95%。

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引用次数: 0

Using Time Signal at Red (TSAR) as a tool for analysing rail network performance 使用红灯时信号（TSAR）作为分析铁路网性能的工具

IF 2.6 Q3 TRANSPORTATION

Journal of Rail Transport Planning & Management

Pub Date : 2025-03-01 Epub Date: 2025-01-31 DOI: 10.1016/j.jrtpm.2025.100505

Anirban Bhattacharyya , Matthew Forshaw , David Golightly , Seb Merricks , Roberto Palacin , Ken Pierce , Pedro Pinto da Silva

Reactionary delays can adversely impact train service performance. This is particularly true for parts of the rail network at or near capacity. To detect the causes of such delays, a metric with a granularity smaller than those of typical rail delay metrics is required. We present an approach based on the Time Signal at Red (TSAR) metric. The purpose of TSAR is to measure the duration a berth is continuously occupied by a train or reserved, which is closely related to information regarding the red aspect of the berth signal at an entrance to the berth. Thus, TSAR provides a low-level metric to measure individual service and berth performance, and to observe system effects that reflect reactionary delay. The paper defines TSAR and describes a data processing methodology to extract TSAR and signal aspect on berth entry from disparate data sources. The use of TSAR is demonstrated for a case study area – comparing different service patterns, identifying patterns of reactionary delay, and showing the impact of adhesion at different times of year. The implications of TSAR are discussed, including its utility for applications such as analysis of simulated network performance.

被动延误会对列车服务性能产生不利影响。对于部分已满负荷或接近满负荷的铁路网来说，情况尤其如此。为了检测这种延迟的原因，需要一个粒度小于典型铁路延迟度量的度量。我们提出了一种基于时间信号在红色（TSAR）度量的方法。TSAR的目的是测量一个泊位连续被列车占用或预留的时间，这与泊位入口的泊位信号的红色方面的信息密切相关。因此，TSAR提供了一个低级的度量来衡量单个服务和泊位的性能，并观察反映反动延迟的系统效应。本文定义了TSAR，并描述了一种从不同数据源中提取TSAR和信号方面的数据处理方法。在案例研究领域中演示了TSAR的使用-比较不同的服务模式，识别反应延迟的模式，并显示一年中不同时间粘附的影响。讨论了TSAR的含义，包括其在模拟网络性能分析等应用中的效用。

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引用次数: 0

Industry 4.0 for passenger railway companies: A maturity model proposal for technology management 铁路客运公司的工业 4.0：技术管理成熟度模型建议

IF 2.6 Q3 TRANSPORTATION

Journal of Rail Transport Planning & Management

Pub Date : 2024-12-01 Epub Date: 2024-09-11 DOI: 10.1016/j.jrtpm.2024.100480

Michael Luciano Chaves Franz , Néstor Fabián Ayala , Ana Margarita Larranaga

The railway sector is a relevant segment for the transportation of people and goods, and its efficiency and sustainability are crucial for fostering economic development and minimizing environmental impact. This research proposes an Industry 4.0 maturity model for passenger railway companies to manage emerging technologies, aiming to enhance them holistically to leverage the internal and external business dimensions. An exploratory and qualitative approach was employed, involving semi-structured interviews with experts in Brazilian railway transport. Based on the opportunities and Key Performance Indicators identified within the sector, we developed an Industry 4.0 maturity model for companies and subsequently tested it in collaboration with a transport operator. The findings suggest that the proposed Industry 4.0 maturity model can effectively guide practitioners in applying advanced technologies for robust and efficient train operations, prescriptive maintenance, strong supply chain management, and improved passenger experience and worker performance. This research provides a noteworthy and substantial contribution by introducing unprecedented frameworks that offer a holistic view of Industry 4.0 in the context of passenger railways. The study's practical impact is aiding passenger railway companies to navigate their Industry 4.0 journey. Academically, the research contributes to advancing the holistic understanding of Industry 4.0 as an ongoing phenomenon, enriching the academic discourse by discussing published works and presenting empirical data from railway companies.

铁路部门是人员和货物运输的相关部门，其效率和可持续性对于促进经济发展和最大限度地减少对环境的影响至关重要。本研究为铁路客运公司管理新兴技术提出了一个工业 4.0 成熟度模型，旨在全面提升这些技术，充分利用内部和外部业务维度。研究采用了一种探索性的定性方法，对巴西铁路运输领域的专家进行了半结构化访谈。根据在该行业内发现的机遇和关键绩效指标，我们为企业开发了一个工业 4.0 成熟度模型，随后与一家运输运营商合作对其进行了测试。研究结果表明，所提出的工业 4.0 成熟度模型可以有效地指导从业人员应用先进技术，以实现稳健高效的列车运行、规范性维护、强大的供应链管理，并改善乘客体验和员工绩效。这项研究引入了前所未有的框架，在客运铁路的背景下提供了工业 4.0 的整体视角，从而做出了值得注意的实质性贡献。这项研究的实际影响是帮助铁路客运公司踏上工业 4.0 的征程。在学术方面，该研究有助于推动对工业 4.0 这一持续存在的现象的全面理解，通过讨论已发表的作品和展示铁路公司的经验数据，丰富学术话语。

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