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The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail. The operating environment of the high-speed rail is complex, and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters, perimeter intrusion and external environmental hazards. The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.

In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments, the research status is elaborated, and the latest research progress and achievements of the team are introduced. This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological, perimeter and external environmental situation perception methods for high-speed rail operation.

Based on the technical route of “situational awareness evaluation warning active control,” a technical system for monitoring the safety of high-speed train operation environments has been formed. Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters, perimeter intrusion and the external environment on high-speed rail safety. These works strongly support the improvement of China’s railway environmental safety guarantee technology.

With the operation of CR450 high-speed trains with a speed of 400 km per hour and the application of high-speed train autonomous driving technology in the future, new and higher requirements have been put forward for the safety of high-speed rail operation environments. The following five aspects of work are urgently needed: (1) Research the single factor disaster mechanism of wind, rain, snow, lightning, etc. for high-speed railways with a speed of 400 kms per hour, and based on this, study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment, revealing the coupling disaster mechanism of multiple influencing factors; (2) Research covers multi-source data fusion methods and associated features such as disaster monitoring data, meteorological information, route characteristics and terrain and landforms, studying the spatio-temporal evolution laws of meteorological disasters, perimeter intrusions and external environmental hazards; (3) In terms of meteorological disaster situation awareness, research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines; (4) In terms of perimeter intrusion, research a multi-modal fusion perception method for typical scenarios of high-speed rail operation in all time, all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and (5) In terms of external environment, based on the existing general network framework for change detection, we will carry out research on change detection and algorithms in the surrounding environment of high-speed rail.

This study aims to review the recent advancements in high entropy alloys (HEAs) called high entropy materials, including high entropy superalloys which are current potential alternatives to nickel superalloys for gas turbine applications. Understandings of the laser surface modification techniques of the HEA are discussed whilst future recommendations and remedies to manufacturing challenges via laser are outlined.

Materials used for high-pressure gas turbine engine applications must be able to withstand severe environmentally induced degradation, mechanical, thermal loads and general extreme conditions caused by hot corrosive gases, high-temperature oxidation and stress. Over the years, Nickel-based superalloys with elevated temperature rupture and creep resistance, excellent lifetime expectancy and solution strengthening L12 and γ´ precipitate used for turbine engine applications. However, the superalloy’s density, low creep strength, poor thermal conductivity, difficulty in machining and low fatigue resistance demands the innovation of new advanced materials.

HEAs is one of the most frequently investigated advanced materials, attributed to their configurational complexity and properties reported to exceed conventional materials. Thus, owing to their characteristic feature of the high entropy effect, several other materials have emerged to become potential solutions for several functional and structural applications in the aerospace industry. In a previous study, research contributions show that defects are associated with conventional manufacturing processes of HEAs; therefore, this study investigates new advances in the laser-based manufacturing and surface modification techniques of HEA.

The AlxCoCrCuFeNi HEA system, particularly the Al0.5CoCrCuFeNi HEA has been extensively studied, attributed to its mechanical and physical properties exceeding that of pure metals for aerospace turbine engine applications and the advances in the fabrication and surface modification processes of the alloy was outlined to show the latest developments focusing only on laser-based manufacturing processing due to its many advantages.

It is evident that high entropy materials are a potential innovative alternative to conventional superalloys for turbine engine applications via laser additive manufacturing.

As the demand for human–robot collaboration in manufacturing applications grows, the necessity for collision detection functions in robots becomes increasingly paramount for safety. Hence, this paper aims to improve the existing method to achieve efficient, accurate and sensitive robot collision detection.

The external torque is estimated by momentum observers based on the robot dynamics model. Because the state of the joints is more accessible to distinguish under the action of the suppression operator proposed in this paper, the mutated external torque caused by joint reversal can be accurately attenuated. Finally, time series analysis (TSA) methods can continuously generate dynamic thresholds based on external torques.

Compared with the collision detection method based only on TSA, the invalid time of the proposed method is less during joint reversal. Although the soft-collision detection accuracy of this method is lower than that of the symmetric threshold method, it is superior in terms of detection delay and has a higher hard-collision detection accuracy.

Owing to the mutated external torque caused by joint reversal, which seriously affects the stability of time series models, the collision detection method based only on TSA cannot detect continuously. The consequences are disastrous if the robot collides with people or the environment during joint reversal. After multiple experimental verifications, the proposed method still exhibits detection capabilities during joint reversal and can implement real-time collision detection. Therefore, it is suitable for various engineering applications.

This paper aims to study the effect of the establishment of bankruptcy courts on bond issuance market. This paper helps to predict that the introduction of bankruptcy courts in China can mitigate price distortions caused by the implicit government guarantees and promote the development of the high-risk bond market.

This paper exploits the staggered introduction of bankruptcy courts across cities to implement a differences-in-differences strategy on bond issuance data. Using bonds issued in China between 2018 and 2020, the impact of bankruptcy courts on the bond issuance market can be analyzed.

This paper reveals that bond issuance credit spreads increase and is more sensitive to firm size, profitability and downside risk of issuance entity after the introduction of bankruptcy courts. It also reveals a substantive increase in bond issuance quantity and a decrease in issuer credit ratings following the establishment of bankruptcy courts. In addition, the increase of credit spreads is more prominent for publicly traded bonds, those whose issuers located in provinces with lower judicial confidence, bonds issued by SOEs and bonds with stronger government guarantees. Finally, the role of bankruptcy courts is more pronounced in regions with higher marketization.

This paper relates to previous studies that investigate the impact of laws and institutions on external financing. It helps provide new evidence to this literature on how improvements of efficiency and quality in bankruptcy enforcements relate to the marketization of bond issuance. The results provide further evidence on legal institutions and bond financing.

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.

The aim of this study is to depict the spatial pattern of the development level of China's state-owned forest farms, thereby providing theoretical reference and empirical evidence for the improvement of the corresponding development policies.

A development evaluation index system was established in this paper to comprehensively measure the development level of China's state-owned forest farms based on the Pressure-State-Response (PSR) model analysis framework and the actual situation of state-owned forest farms by using the entropy weight - technique for order preference by similarity to an ideal solution (entropy weight TOPSIS) evaluation method and exploratory spatial analysis method.

Studies show that the state-owned forest farms in China are generally not well developed. The pressure system that represents the input level displays an apparent restrictive effect on provinces whose comprehensive score <0.15. The response system, which represents development dynamism, has an apparent restrictive function on the provinces whose comprehensive score is 0.35. In terms of the specific spatial characteristics, the V-shape displayed by southwest–northwest and southeast–northwest has an inward trend of gradual reduction, with high-low agglomeration and low-low agglomeration correlation effects as well as apparent basin characteristics.

In this paper, the development level and spatial pattern of state-owned forest farms in China were accurately depicted, and the development path support and decision-making basis were provided for improving the overall development level of state-owned forest farms in China.

In the face of climate change, environmental impact assessment (EIA) and strategic environmental assessment (SEA) are expected to translate global or national mitigation and adaptation targets to project and plan levels of decision-making. This paper aims to examine how to transform China’s EIA procedures to accommodate consideration of climate change and what constraints might be for doing so.

The main methodology used in this paper is doctrinal research, which is the primary legal methodology to find the law and interpret and analyse the document. Theoretical research is applied to analyse the ideas and assumptions of the mainstreaming approach. Comparative research is done to consider relevant international experiences.

Despite well-founded rationale for the mainstreaming approach, entrenched institutional, legal and technical obstacles cannot be neglected in the context of China. Urgent needs to fix existing EIA/SEA loopholes and improve the general enabling environment are also highlighted as a fundamental aspect of mainstreaming.

The potential of mainstreaming climate change into China’s EIA procedures remains largely unexplored. As a ground-breaking work from China’s perspective, the findings of this paper can serve as an important foundation for future research from legal and other perspectives.

The purpose of this paper is to measure Farmer’s adoption tendency towards drought shock, risk-taking networks and modern irrigation technology.

Based on this assumption, this paper evaluated the data gathered from 498 household surveys of Zhangye, Gansu province, PRC, by using the binary probit model. First, the empirical data was analyzed for evaluating the impact of drought shock and risk-taking tendencies on the adoption of modern irrigation technology by farmers. Second, the authors introduced informal risk-bearing networks with formal risks. Final, based on the empirical results, the sustainability test, along with the marginal effect analysis and the degree of impact was carried out.

The results show that the drought shock has a significantly deferent effect on the modern irrigation technology of the farmers. The probability of using technology for each level of drought loss is reduced by 15.02%. The risk-taking network has a significant role in promoting the modern irrigation technology of farmers. The probability of adoption for each additional unit of rural household labor security supply, the likelihood of adoption by farmers increased 23.11%, the probability of approval for each level of relative support, and neighborhood assistance by farmers increased by 13.11% and 17.88% respectively. This study further revealed that insurance purchases enabled farmers to adopt new irrigation technology with the probability increased by 24.99%; easily available bank loans increased the probability of farmers using irrigation technology by 31.89%. From the perspective of interactions between farmers, the risk-taking network can alleviate the inhibitory effect of drought impact towards the adoption of irrigation technology. Among the control variables, the number of years of education, the age of farming, the degree of arable land, the distance from home to the market, and the price of water all has significant effects on the adoption of modern irrigation technology by farmers.

The novelty of the study is that it illustrated the interactive influence of drought shock and risk-taking networks on the farmer’s adoption tendencies of modern irrigation technologies, the inner relationship among drought impact, the risk-taking network and the farmer’s adoption behavior and provide an interactive relationship between the formal risk-taking network and the non-risk-taking network in farmer’s technology adoption.

This study investigates the circumstances under which a business to customer (B2C) marketplace chooses to implement green marketing to promote green product investment (GPI). It further identifies the optimal sales model approach for implementing green marketing under uncertainty about the effects of GPI.

We examine an e-commerce (EC) supply chain involving a manufacturer who determines the product’s greenness level and a B2C marketplace who can operate in either an agency or a reselling mode and engages in green marketing to promote sales of green products. Using the backward induction method, we develop an analytical model to drive the optimal decisions and profits under each sales model.

Our research demonstrates that high GPI uncertainty drives B2C marketplaces to adopt green marketing strategies. These initiatives not only prompt manufacturers to invest in eco-friendly products but also boost profits for all parties involved. Nevertheless, these benefits depend on the choice of a sales model between agency and reselling. Our findings offer a novel practical application into the relationship between GPI uncertainty and green marketing. When the GPI uncertainty is high, green marketing is profitable for the B2C marketplace regardless of which sales mode is adopted. However, when uncertainty is low, green marketing only benefits the B2C marketplace in the agency mode. Moreover, the interaction between GPI uncertainty and the referral fee exerts a moderating influence on the preferred sales mode for both the manufacturer and the B2C marketplace.

Our findings offer a novel practical application into the relationship between GPI uncertainty and green marketing. When the GPI uncertainty is high, green marketing is profitable for the B2C marketplace regardless of which sales mode is adopted. However, when uncertainty is low, green marketing only benefits the B2C marketplace in the agency mode. Moreover, the interaction between GPI uncertainty and the referral fee exerts a moderating influence on the preferred sales mode for both the manufacturer and the B2C marketplace.

Overall, our research contributes to a deeper understanding of the complex but beneficial interplay between GPI uncertainty, green marketing and sales mode selection in an EC supply chain.