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Fault diagnosis methods based on blind source separation (BSS) for rolling element bearings are necessary tools to prevent any unexpected accidents. In the field application, the actual signal acquisition is usually hindered by certain restrictions, such as the limited number of signal channels. The purpose of this study is to fulfill the weakness of the existed BSS method.

To deal with this problem, this paper proposes a blind source extraction (BSE) method for bearing fault diagnosis based on empirical mode decomposition (EMD) and temporal correlation. First, a single-channel undetermined BSS problem is transformed into a determined BSS problem using the EMD algorithm. Then, the desired fault signal is extracted from selected intrinsic mode functions with a multi-shift correlation method.

Experimental results prove the extracted fault signal can be easily identified through the envelope spectrum. The application of the proposed method is validated using simulated signals and rolling element bearing signals of the train axle.

This paper proposes an underdetermined BSE method based on the EMD and the temporal correlation method for rolling element bearings. A simulated signal and two bearing fault signal from the train rolling element bearings show that the proposed method can well extract the bearing fault signal. Note that the proposed method can extract the periodic fault signal for bearing fault diagnosis. Thus, it should be helpful in the diagnosis of other rotating machinery, such as gears or blades.

This paper aims to investigate the reliability, availability, maintenance and safety analysis method for railway network operation.

The reliability of the railway network is proposed based on the accident frequency and the topology of the railway network. Network efficiency and capacity are proposed to evaluate the availability of the railway network. The maintenance of the railway network is analyzed from the perspective of accident recovery time. The safety index of the railway network is proposed to measure the safety of railway stations and sections and the K-means method is proposed to find the safety critical stations and sections. Finally, the effectiveness of the proposed method is illustrated through a real-world case study.

The case study shows that the proposed model can produce a big-picture averaged view of the network-wide safety level and help us identify the safety critical stations and sections by considering both the expected reduction of network efficiency and capacity.

The potential application of the proposed model is to help the safety managers determine the investments in safety management of each section and station and then increase the safety and robustness of railway network operation.

The safety analysis of the railway network should consider the reliability, availability and maintenance of the railway network. In this paper, the reliability of the railway network is proposed based on the accident frequency and the topology of the railway network. Network efficiency and capacity are proposed to evaluate the availability of the railway network. The maintenance of the railway network is analyzed from the perspective of recovery time. Finally, the safety index of the railway network is proposed to analyze the safety critical stations and sections.

This paper aim at providing decision support for operational adjustment. In order to effectively reduce the external interference impact on train operation.

According to the reality that there are two kinds of high-speed trains running in China, considering the reality that there are two speed level train running in Chinese high-speed railway, this paper proposed the high-speed railway operation adjustment model based on priority, and the objective function is to minimize interference impact on train operation.

Adjustment strategy based on priority than based on sequence can effectively reduce the interference influence on train operation, which makes the train resume the planned operation back on schedule more quickly.

The solution of large-scale cases is too slow, and the practical application is limited.

The model was verified by a case, and the case results proved that adjustment strategy based on priority than based on sequence can effectively reduce the interference influence on train operation, which makes the train resume the planned operation back on schedule more quickly.

This paper aims to propose an enhanced densely dehazing network to suit railway scenes’ features and improve the visual quality degraded by haze and fog.

It is an end-to-end network based on DenseNet. The authors design enhanced dense blocks and fuse them in a pyramid pooling module for visual data’s local and global features. Multiple ablation studies have been conducted to show the effects of each module proposed in this paper.

The authors have compared dehazed results on real hazy images and railway hazy images of state-of-the-art dehazing networks with the dehazed results in data quality. Finally, an object-detection test is taken to judge the edge information preservation after haze removal. All results demonstrate that the proposed dehazing network performs better under railway scenes in detail.

This study provides a new method for image enhancing in the railway monitoring system.

Based on complex network theory, a method for critical elements identification of China Railway High-speed 2 (CRH2) train system is introduced in this paper.

First, two methods, reliability theory and complex theory, are introduced, and the advantages and disadvantages for their application in identifying critical elements of high-speed train system are summarized. Second, a multi-layer multi-granularity network model including virtual and actual nodes is proposed, and the corresponding fusion rules for the same nodes in different layers are given.

Finally, taking CRH2 train system as an example, the critical elements are identified by using complex network theory, which provides a reference for train operation and maintenance.

A method of identifying key elements of CRH2 train system based on integrated importance indices is introduced, which is a meaningful extension of the application of complex network theory to identify key components.

Research about the modern mutually beneficial nonprofit organizations (MBNPOs) has great value because of the increasingly important role that the MBNPO plays in society. The establishment and management of MBNPOs are critical for its development.

Integrated marketing communications (IMC) theory is applied to the research on establishment and management innovation. The establishment of MBNPOs needs four sequential steps: identifying the target group, providing services to meet the demand of stakeholders, designing appropriate communication tactics and deploying proper organizational structure to accomplish efficient communication.

Three types of approach enable traditional enterprises to transform into MBNPOs: product innovation, operational innovation and synergetic development. The application of IMC theory accomplishes management innovation of MBNPOs in three aspects: leading market-orientation specific to stakeholder-orientation, making management innovation systematic in MBNPOs and clarifying targets of management innovation in MBNPOs.

This is one of the first examinations of establishment path and management innovation of MBNPO based on IMC theory.

This paper aims to comprehensively clarify the research status of thermal transport of supercritical aviation kerosene, with particular interests in the effect of cracking on heat transfer.

A brief review of current research on supercritical aviation kerosene is presented in views of the surrogate model of hydrocarbon fuels, chemical cracking mechanism of hydrocarbon fuels, thermo-physical properties of hydrocarbon fuels, turbulence models, flow characteristics and thermal performances, which indicates that more efforts need to be directed into these topics. Therefore, supercritical thermal transport of n-decane is then computationally investigated in the condition of thermal pyrolysis, while the ASPEN HYSYS gives the properties of n-decane and pyrolysis products. In addition, the one-step chemical cracking mechanism and SST k-ω turbulence model are applied with relatively high precision.

The existing surrogate models of aviation kerosene are limited to a specific scope of application and their thermo-physical properties deviate from the experimental data. The turbulence models used to implement numerical simulation should be studied to further improve the prediction accuracy. The thermal-induced acceleration is driven by the drastic density change, which is caused by the production of small molecules. The wall temperature of the combustion chamber can be effectively reduced by this behavior, i.e. the phenomenon of heat transfer deterioration can be attenuated or suppressed by thermal pyrolysis.

The issues in numerical studies of supercritical aviation kerosene are clearly revealed, and the conjugation mechanism between thermal pyrolysis and convective heat transfer is initially presented.

The Internet of Things (IoT) is used in the fresh agricultural product (FAP) supply chain, which can be coordinated through a revenue-sharing contract. The purpose of this paper is to make the three-level supply chain coordinate in IoT by considering the influence of FAP on market demand and costs of controlling freshness on the road.

A three-level FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT is regarded as the research object. This study improves the revenue-sharing contract, determines the optimal solution when the supply chain achieves maximum profit in three types of decision-making situations, and develops the profit distribution model based on the improved revenue-sharing contract to coordinate the supply chain.

The improved revenue-sharing contract can coordinate the FAP supply chain that comprises a manufacturer, distributor, and retailer in IoT, as well as benefit all enterprises in the supply chain.

Resource utilization rate can be improved after coordinating the entire supply chain. Moreover, loss in the circulation process is reduced, and the circulation efficiency of FAPs is improved because of the application of IoT. The validity of the model is verified through a case analysis.

This study is different from other research in terms of the combination of supply chain coordination, FAPs, and radio frequency identification application in IoT.

This paper focuses on governance in higher education in China. It sees that governance as distinctive on the world scale and the potential source of distinctiveness in other domains of higher education. By taking an historical approach, reviewing relevant literature and drawing on empirical research on governance at one leading research university, the paper discusses system organisation, government–university relations and the role of the Communist Party (CCP), centralisation and devolution, institutional leadership, interior governance, academic freedom and responsibility, and the relevance of collegial norms. It concludes that the party-state and Chinese higher education will need to find a Way in governance that leads into a fuller space for plural knowledges, ideas and approaches. This would advance both indigenous and global knowledge, so helping global society to also find its Way.

This study investigates how social interaction-oriented content in broadcasters' live speech affects broadcast viewers' purchasing and gift-giving behaviors and how broadcaster popularity moderates social interaction-oriented content's effect on the two different behaviors in live-streaming commerce.

A research model was proposed and empirically tested using a panel data set collected from 537 live streams via Douyin (the Chinese version of TikTok), one of the most popular live broadcast platforms in China. A fixed-effects negative binomial regression model was used to examine the proposed research model.

This study's results show that social interaction-oriented content in broadcasters' live speech has an inverted U-shaped relationship with broadcast viewers' purchasing behavior and shares a positive linear relationship with viewers' gift-giving behavior. Furthermore, broadcaster popularity significantly moderates the effect of social interaction-oriented content on viewers' purchasing and gift-giving behaviors.

This research enriches the literature on live-streaming commerce by investigating how social interaction-oriented content in broadcasters' live speech affects broadcast viewers' product-purchasing and gift-giving behaviors from the perspective of broadcast viewers' attention. Moreover, this study provides some practical guidelines for developing live speech content in the live-streaming commerce context.