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High-speed turnouts are more complex in structure and thus may cause abnormal vibration of high-speed train car body, affecting driving safety and passenger riding experience. Therefore, it is necessary to analyze the data characteristics of continuous hunting of high-speed trains passing through turnouts and propose a diagnostic method for engineering applications.

First, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is performed to determine the first characteristic component of the car body’s lateral acceleration. Then, the Short-Time Fourier Transform (STFT) is performed to calculate the marginal spectra. Finally, the presence of a continuous hunting problem is determined based on the results of the comparison calculations and diagnostic thresholds. To improve computational efficiency, permutation entropy (PE) is used as a fast indicator to identify turnouts with potential problems.

Under continuous hunting conditions, the PE is less than 0.90; the ratio of the maximum peak value of the signal component to the original signal peak value exceeded 0.7, and there is an energy band in the STFT time-frequency map, which corresponds to a frequency distribution range of 1–2 Hz.

The research results have revealed the lateral vibration characteristics of the high-speed train’s car body during continuous hunting when passing through turnouts. On this basis, an effective diagnostic method has been proposed. With a focus on practical engineering applications, a rapid screening index for identifying potential issues has been proposed, significantly enhancing the efficiency of diagnostic processes.

With the yearly increase of mileage and passenger volume in China's high-speed railway, the problems of traditional paper railway tickets have become increasingly prominent, including complexity of business handling process, low efficiency of ticket inspection and high cost of usage and management. This paper aims to make extensive references to successful experiences of electronic ticket applications both domestically and internationally. The research on key technologies and system implementation of railway electronic ticket with Chinese characteristics has been carried out.

Research in key technologies is conducted including synchronization technique in distributed heterogeneous database system, the grid-oriented passenger service record (PSR) data storage model, efficient access to massive PSR data under high concurrency condition, the linkage between face recognition service platforms and various terminals in large scenarios, and two-factor authentication of the e-ticket identification code based on the key and the user identity information. Focusing on the key technologies and architecture the of existing ticketing system, multiple service resources are expanded and developed such as electronic ticket clusters, PSR clusters, face recognition clusters and electronic ticket identification code clusters.

The proportion of paper ticket printed has dropped to 20%, saving more than 2 billion tickets annually since the launch of the application of E-ticketing nationwide. The average time for passengers to pass through the automatic ticket gates has decreased from 3 seconds to 1.3 seconds, significantly improving the efficiency of passenger transport organization. Meanwhile, problems of paper ticket counterfeiting, reselling and loss have been generally eliminated.

E-ticketing has laid a technical foundation for the further development of railway passenger transport services in the direction of digitalization and intelligence.

To delve into the integration of global logistics and supply chain networks amidst the digital transformation era. This study aims to investigate the potential role of China’s Belt and Road Initiative (BRI) in facilitating the integration of global flows encompassing both tangible goods and intangibles. Additionally, the study seeks to incorporate third-party logistics activities into a comprehensive global logistics and supply chain integration framework.

Prior research is synthesised into a global logistics and supply chain integration framework. A case study was undertaken on Yuan Tong (YTO) express group to investigate the framework, employing qualitative data analysis techniques. The study specifically examined the context of the BRI to enhance comprehension of its impact on global supply chains. Information was collected in particular to two types of supply chain flows, the physical flow of goods, and intangible information and cash flows.

The proposed framework aligns well with the case study, leading to the identification of global logistics and supply chain integration enablers. The results demonstrate a range of ways BRI promotes global logistics and supply chain integration.

The case study, with multiple examples, focuses on how third-party logistics firms can embrace global logistics and supply chain integration in line with BRI. The case study approach limits generalisation, further applications in different contexts are required to validate the findings.

The framework holds promise for aiding practitioners and researchers in gaining deeper insights into the role of the BRI in global logistics and supply chain integration within the digital era. The identified enablers underscore the importance of emphasising key factors necessary for success in navigating digital transformation within global supply chains.

The shipper selects a suitable shipping route and plans for a voyage in order to import and export cargo on the basis of published sailing schedules. The reliability of the sailing schedule will influence the shipper’s logistics expense, which means that the logistics costs will depend on the reliability of schedules published by container shipping companies. Therefore, it is important to consider factors which can cause delays would for container ships sailing on sea routes. The reliability of published sailing schedules can be affected by a number of different factors. This study adopts the multi-criteria decision making (MCDM) method to estimate the importance of the delaying factors in a sailing schedule. In addition, the consistent fuzzy preference relations (CFPR) method is applied to identify the subjective importance (weights) of the delaying factors. The entropy weight method combined with the actual performance of the container shipping company are both used when estimating the objective importance (weights) of the delaying factors. According to the analysis results, the criteria can be divided into four quadrants with different management implications, which indicate that instructions for chase strategy, sailing schedule control, fleet allocation, transship operation arrangement and planning for ports in routes are often ignored by container shipping companies. Container shipping companies should consider adjusting their operational strategies, which would greatly improve their operational performance.

This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design.

This paper provides a comprehensive overview of the definition, connotations, characteristics and key technologies of digital twin technology. It also conducts a thorough analysis of the current state of digital twin applications, with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure. Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study, the paper details the construction process of the twin system from the perspectives of system architecture, theoretical definition, model construction and platform design.

Digital twin technology can play an important role in the whole life cycle management, fault prediction and condition monitoring in the field of high-speed rail operation and maintenance. Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management.

This paper systematically summarizes the main components of digital twin railway. The general framework of the digital twin bridge is given, and its application in the field of intelligent operation and maintenance is prospected.

The existing Nonlinear Dynamic Vibration Absorbers (NLDVAs) have the disadvantages of complex structure, high cost, high installation space requirements and difficulty in miniaturization. And most of the NLDVAs have not been applied to reality. To address the above issues, a novel Triple-magnet Magnetic Dynamic Vibration Absorber (TMDVA) with tunable stiffness, only composed of triple cylindrical permanent magnets and an acrylic tube, is designed, modeled and tested in this paper.

(1) A novel TMDVA is designed. (2) Theoretical and experimental methods. (3) Equivalent dynamics model.

It is found that adjusting the magnet distance can effectively optimize the vibration reduction effect of the TMDVA under different resonance conditions. When the resonance frequency of the cantilever changes, the magnet distance of the TMDVA with a high vibration reduction effect shows an approximately linear relationship with the resonance frequency of the cantilever which is convenient for the design optimization of the TMDVA.

Both the simulation and experimental results prove that the TMDVA can effectively reduce the vibration of the cantilever even if the resonance frequency of the cantilever changes, which shows the strong robustness of the TMDVA. Given all that, the TMDVA has potential application value in the passive vibration reduction of engineering structures.

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.

The purpose of this report is to demonstrate open and distance education (ODE) can support poverty alleviation. Taking the practices of the Open University of China (the OUC) as an example, this paper aims to reveal how open universities make contributions to local residents in rural and remote areas.

Focusing on 25 poverty-stricken counties, the OUC had invested 58 million RMB to its learning centers in these counties from 2017 to 2020. The first one is to improve ICT and educational facilities in these learning centers. The second approach is to cultivate local residents with degree programs through ODE so as to promote local economic development. The third one is to design and develop training programs according to local context to meet the specific needs of local villagers.

After 3 years working, cloud-based classrooms and computer rooms have been set up. Bookstores have been founded and printed books have been donated. Hundreds of thousands of digital micro lectures have been supplied to these learning centers which have been improved and fully played their functions. Nearly 50,000 local residents have been directly benefited. Village leaders have helped lift local residents out of poverty. Poverty-stricken villagers have been financed to study on either undergraduate or diploma programs. Local residents have improved their skills by learning with the training programs offered by the OUC.

ODE is proved to be an effective way to eradicate poverty. Open universities are proved to be able to make contributions to social justice. By fulfilling its commitments to eliminate poverty within the national strategy framework, the OUC has built its brand nationwide.

Based on the survey data of 1,152 households in three provinces of Shaanxi, Gansu and Ningxia on the Loess Plateau, this paper aims to empirically analyze the impact of aging and off-farm employment on farmers’ adoption behavior of soil and water conservation technology. This paper analyzes the moderating effect of social network and the mediating effect of technological cognition in this impact relationship.

Based on the above analysis, the second part of this paper is based on relevant theories and constructs a theoretical model of the relationship of aging, off-farm employment, social network, technology cognition and farmers’ adoption behavior of soil and water conservation technology. The third part introduces research methods, variable selection and descriptive statistics analysis of variables. The fourth part, based on the data of Shaanxi, Gansu and Ningxia provinces in the Loess Plateau in 2016, empirically analyzes the impact of aging, off-farm employment and social network on the farmers’ adoption behavior of soil and water conservation technology. This paper further examines the moderating effect of social network and the mediating effect of technology cognition in this influence relationship. Finally, based on the findings of the empirical study, this paper puts forward countermeasures and suggestions.

First, aging and off-farm employment have a significant negative impact on farmers’ adoption behavior of soil and water conservation technology, while social network has a significant positive effect. Second, social network has alleviated the effect of aging and off-farm employment on restraining farmers’ adoption behavior of soil and water conservation technology. Third, aging and off-farm employment have restrained farmers’ cognition of soil and water conservation technology. Social network has promoted farmers’ cognition of soil and water conservation technology. Social network plays a moderating role in the impact of aging and off-farm employment on farmers’ cognition of soil and water conservation technology. Technology cognition plays a mediating role in the impact of social network on farmers’ adoption behavior of soil and water conservation technology.

This paper integrates the aging, off-farm employment and social network into the same analytical framework and reveals their impact on farmers’ adoption behavior of soil and water conservation technology and its action mechanism, which enriches the impact of human capital and social network on farmers’ adoption behavior of soil and water conservation technology. Then taking the social network as a moderator variable, the paper verifies its moderating effect on the relationship of aging, off-farm employment and farmers’ adoption behavior of soil and water conservation technology. Farmers’ technology cognition should be included in the analysis framework to examine the impact of aging, off-farm employment and social network on farmers’ cognition of soil and water conservation technology. Taking the technology cognition as a mediator variable, the paper verifies its mediating effect on the relationship of aging, off-farm employment and farmers’ adoption behavior of soil and water conservation technology.

Although proactive fault handling plans are widely spread, many unexpected data center outages still occurred. To rescue the jobs from faulty data centers, the authors propose a novel independent job rescheduling strategy for cloud resilience to reschedule the task from the faulty data center to other working-proper cloud data centers, by jointly considering job nature, timeline scenario and overall cloud performance.

A job parsing system and a priority assignment system are developed to identify the eligible time slots for the jobs and prioritize the jobs, respectively. A dynamic job rescheduling algorithm is proposed.

The simulation results show that our proposed approach has better cloud resiliency and load balancing performance than the HEFT series approaches.

This paper contributes to the cloud resilience by developing a novel job prioritizing, task rescheduling and timeline allocation method when facing faults.