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As an important part of the management of railway passenger transport, the rationality and effectiveness of the clearing method of railway passenger transport are directly related to the operating efficiency and service quality of railway passenger transport enterprises. This paper aims to comprehensively and deeply discuss the evolution and development process of China’s railway passenger transport clearing method, analyze its characteristics and influences in each stage, identify the main factors affecting its evolution and development and then put forward thoughts on improving the future development of the clearing method.

Through a detailed review of the railway passenger transport clearing methods from the planned economy period to the reform and opening up period and into the new century, the basis, mode, subject and object of clearing in different development stages are systematically compared.

It comprehensively reveals the evolution of the clearing method, sorted out the characteristics and changes of the clearing method at each stage and the adaptability to the development of railway passenger transport at that time. The characteristics of the development of clearing measures for railway passenger transport in different stages and their far-reaching influence on railway passenger transport business are deeply analyzed.

This paper summarized the factors influencing the development of China’s railway passenger transportation clearing approach evolution, including the simplified rules of clearing, enhanced the market adaptability, establishing and perfecting the incentive mechanism, strengthening the construction of informatization, etc. This paper puts forward the ways to improve the railway passenger transportation clearing future development thinking.

The chapter explored the critical components, challenges, and technological advancements in construction supply chain management (CSCM), focusing on stealth construction (STC). It delved into STC encompassing nature, highlighting its unique challenges in its supply chain management and the necessity for adaptive technologies. It further discussed the benefits of tailoring supply chain management specifically for STC, emphasising the importance of developing the building’s cross-section, managing visibility, controlling energy transmission, and implementing countermeasures. Practical applications of CSCM in STC are also examined. This chapter sheds light on the complexities of managing supply chains in STC contexts and offers insights into strategies and technologies to address these challenges effectively.

Accurate prediction of port cargo throughput within Free Trade Zones (FTZs) can optimize resource allocation, reduce environmental pollution, enhance economic benefits and promote sustainable transportation development.

This paper introduces a novel self-adaptive grey multivariate prediction modeling framework (FARDCGM(1,N)) to forecast port cargo throughput in China, addressing the challenges posed by mutations and time lag characteristics of time series data. The model explores policy-driven mechanisms and autoregressive time lag terms, incorporating policy dummy variables to capture deviations in system development trends. The inclusion of autoregressive time lag terms enhances the model’s ability to describe the evolving system complexity. Additionally, the fractional-order accumulative generation operation effectively captures data features, while the Grey Wolf Optimization algorithm determines optimal nonlinear parameters, enhancing the model’s robustness.

Verification using port cargo throughput forecasts for FTZs in Shanghai, Guangdong and Zhejiang provinces demonstrates the FARDCGM(1,N) model’s remarkable accuracy and stability. This innovative model proves to be an excellent forecasting tool for systematically analyzing port cargo throughput under external interventions and time lag effects.

A novel self-adaptive grey multivariate modeling framework, FARDCGM(1,N), is introduced for accurately predicting port cargo throughput, considering policy-driven impacts and autoregressive time-lag effects. The model incorporates the GWO algorithm for optimal parameter selection, enhancing adaptability to sudden changes. It explores the dual role of policy variables in influencing system trends and the impact of time lag on dynamic response rates, improving the model’s complexity handling.

This study aims to examine the dynamic effect of FinTech on financial stability, with the moderating role of green finance (GF), its dimensions and mechanisms in the context of the spillover effects of the COVID-19 shock. This study used balanced panel data from 148 countries, including 76 developed and 72 emerging nations, from 2005 to 2022.

The research utilized the dynamic two-step system (GMM), and robustness was performed with the bootstrapped panel quantile regression.

The findings reveal that FinTech significantly affects financial stability across the entire sample. The overall composite of GF boosts financial stability by improving financial soundness. The GF dimensions, such as environmental, resource and financial, positively influence FS, while the GF economic dimension hurts FS. The moderating role and all interaction terms of GF dimensions with FinTech contribute positively and significantly to FS. While the interaction term GF resources with FinTech negatively impacts FS, indicating that countries should utilize resources more efficiently. Additionally, the COVID-19 spillover effect negatively influences FS across all samples. In advanced countries, FinTech and green finance positively affect FS. In emerging countries, green finance (except for the resource dimension) and FinTech interactions enhance financial stability, (except for the environmental dimension), leading to environmental hazards from their highly intensive industrial carbon policies.

The findings suggest that policymakers should prioritize promoting the adoption of initiatives related to FinTech and green finance by integrating sustainable transition finance policy frameworks to maintain stability and foster low-carbon economies for a sustainable future.

Improved financial stability has more significant social effects, such as better investment instruments, confidence and economic growth. Policymakers can leverage these findings to establish resilient financial ecosystems, fostering sustainable economic development and decreasing the risk of financial crises.

This study offers novel insights into how FinTech and multi-dimensional green finance effect financial stability in advanced and emerging nations. It provides unique insights into context-specific dynamics and enhances the literature on financial stability.

Opportunistic and delayed maintenances are increasingly becoming important strategies for sustainable maintenance practices since they increase the lifetime of complex systems like aircrafts and heavy equipment. The objective of the current study is to quantify the optimal time window for adopting these strategies.

The current study considers the trade-offs between different costs involved in the opportunistic and delayed maintenances (of equipment) like the fixed cost of scheduled maintenances, the opportunistic rewards that may be earned and the cost of premature parts replacement. The probability of the opportunistic maintenance has been quantified under two different scenarios – Mission Reliability and Renewal Process. In the case of delayed maintenance, the cost of the delayed maintenance is also considered. The study uses optimization techniques to find the optimal maintenance time windows and also derive useful insights.

Apart from finding the optimal time window for the maintenance activities the study also shows that opportunistic maintenance is beneficial provided the opportunistic reward is significantly large; the cost of conducting scheduled maintenance in the pre-determined slot is significantly large. Similarly, the opportunistic maintenance may not be beneficial if the pre-mature equipment parts replacement cost is significantly high. The optimal opportunistic maintenance time is increasing function of Weibull failure rate parameter “beta” and decreasing function of Weibull failure rate parameter “theta.” In the case of optimal delayed maintenance time, these relationships reverse.

To the best of our knowledge, very few studies exist that have used mission reliability to study opportunistic maintenance or considered the different cost trade-offs comprehensively.

For the purpose of saving nickel, this study aims to develop new duplex stainless steel cored wires suitable for wire arc additive manufacturing (WAAM) with the addition of nitrogen.

The effect of nitrogen content on the microstructure and mechanical properties of the thin-walled deposits is investigated in detail.

The microstructure of thin-walled deposits mainly consists of austenite, ferrite and secondary austenite. With increasing nitrogen content, the austenite in the deposited metals increases. The austenite proportion in the bottom region is more than that in the top region of the deposited metals. The χ phase is randomly distributed at the grain boundaries and within ferrite. The σ phase is mainly precipitated at ferrite and austenite grain boundaries. With increasing nitrogen content, the tensile strength of the deposited metals increases, but the impact toughness of the deposited metals deteriorates.

This study proposes new duplex stainless steel cored wires for WAAM, which realizes the objective of saving nickel.

Given the popularity of online health communities (OHCs) and medical question-and-answer (Q&A) services, it is increasingly important to understand what constitutes useful answers and user-adopted standards in healthcare domain. However, few studies provide insights into how health information characteristics, provider characteristics and recipient characteristics jointly influence user information adoption decisions. To fill this research gap, this study examines the combined effects of physicians' certainty tone as information characteristics, seniority as provider characteristics and disease severity as recipient characteristics on patients' health information adoption.

Drawing on dual-process theory and information adoption model, an extended information adoption model is established in this study to examine the effect of attitude certainty on patients' health information adoption, and the moderating effects of online seniority and offline seniority, as well as patient motivation level—disease severity. Utilizing logit regression models, the authors empirically tested the hypotheses based on 4,224 Q&A records from a popular Chinese OHC.

The results show that (1) attitude certainty has a significant positive impact on patients' health information adoption, (2) the relationship between attitude certainty and information adoption is negatively moderated by physicians' online seniority, but is positively moderated by offline seniority; (3) there is a negative three-way interaction effect of attitude certainty, online seniority and disease severity on patients' health information adoption.

This study extends the information adoption model to examine the two-way interaction between argument quality and source reliability, as well as the three-way interaction with user motivation level, especially for health information adoption in the healthcare field. These findings also provide direct practical applications for knowledge contributors and OHCs.

The purpose of this study is to identify the existing research themes and future directions of the FinTech field by analyzing the dynamics of co-word burst.

A dataset of 1792 SCI or SSCI articles retrieved from the Web of Science database. First, the paper conducted a scientific production analysis. Then, using bibliometric analysis, the paper conducts co-word-burst analyses for keywords, title, abstract and Keywords Plus to detect the emerging trends. Based on these trends, future research directions were forecasted.

The study detected six research themes: the knowledge of FinTech, FinTech applications, FinTech technologies, COVID-19, FinTech ecosystem and FinTech implications for research. These six FinTech research themes were further conceptualized as a six-dimensional analytical framework for FinTech investigations. Then, the study forecasts that these six themes and related conversations will be an ongoing focus of Fintech research, particularly COVID-19 effects on FinTech.

This study is the first attempt to review FinTech literature based on quantitative and qualitative analyses of co-word burst. It overcomes the limitation of individual/group determinant(s) studies and presents a holistic view of current research themes and future research directions in FinTech field.

Cyberbullying has become one of the reasons behind the increase in psychological and medical problems. A need to prevent recurrences of cyberbullying incidents and discourage bullies from further bullying the victims has risen. This problem has attracted the attention of all stakeholders across the globe. Various researchers have developed theories and interventions to detect and stop bullying behavior. Previously, researchers focused on helping victims, but as the times have changed, so has the focus of researchers. This study aims to analyze scientific research articles and review papers to understand the development of the knowledge base on the topic.

This study analyzes the performance of literature on cyberbullying perpetration (CBP) using the widely accepted bibliometric analysis techniques: performance analysis and science mapping. The study is based on a dataset extracted from the Web of Science database. Initially, 2,792 articles between 2007 and 2022 were retrieved, which were filtered down to 441. The filter was based on various criteria, but primarily on CBP. VOSViewer and MS Excel were used to analyze the data. In addition, VOSViewer was used to create “bibliometric citations, co-citations, and co-word maps.”

The findings include publication and citation quantum and trends, the top 20 active countries, the most significant research articles and leading journals in this domain. Major themes or clusters identified were “Cyberbullying and victim behavior,” bullying behavior, adolescents and intervention, “cyberbullying associations,” and “cyberbullying personality associations.”

The study is unique because it analyses research articles based on cyberbullies, whereas past studies explored only the victims' side. Further, the present study used the Web of Science database, whereas most studies use the Scopus database.

COVID-19 has aggregated the need for a non-contact medical logistic system. A non-contact robot with self-navigation ability has greatly enhanced the efficiency of the medical logistic system. This paper aims to design a new medical logistics robot system for the complex environment of hospitals with dynamic obstacles.

Targeting a medical logistics robot system for a large-scale hospital environment, this study proposed a dynamic obstacle avoidance system to reduce the robot’s delay time as well as frequent route switching. In the algorithm, this study proposed a new loop closure detection with an artificial correction factor. Moreover, this study presented enhanced 3D object detection, improving detection accuracy in hospital environments.

Experimental results confirm that the robot can move along its global path and reach its destination without colliding with stationary or moving obstacles.

The medical logistics robot system has safe and stable performance in real hospital scenarios. The implementation verifies that the robot has effectiveness and reliability in both hardware and software design.