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The paper aims to investigate the determinants of China’s daily intervention in the foreign exchange market since the 2005 reform aimed at moving the Renminbi (RMB) exchange rate regime towards greater flexibility.

The paper uses bivariate probit models to test whether China’s intervention decision is driven by three sets of factors, comprising Model I (basic model), Model II and Model III.

Evidence from the models suggests that medium-term Chinese interventions tend to be leaning-against-the-wind, whereas long-term interventions are leaning-with-the-wind. Furthermore, by analyzing exchange rate volatility, this paper finds that intervention is used by the Chinese central bank to ensure that there are no big swings in the RMB exchange rate.

The paper will be of value to other researchers attempting to understand the policy of the central bank and, in particular, the factors that can lead to interventions during periods of financial crisis.

Numerical literature shows that agricultural insurance can affect pesticide investments, but few of them are devoted to explain how agricultural insurance affects farmers’ selection on green or traditional pesticides. This paper aims to develop a theoretical model about how agricultural insurance influences on green pesticides selections and tests our conclusions by using the data from China land economic survey (CLES) from 2020 to 2021.

We employ probit model to capture the effects of agricultural insurance on green pesticides adoption.

We indicate that green pesticides have a stronger effect on stabilizing yield and increasing income than traditional pesticides, but there are still risks disturbing farmers’ decisions on green pesticides usage. By providing premium subsidies after the farmers are affected by natural risk, agricultural insurance improves the farmers’ expected income and encourages farmers to use green pesticides. Further, we further confirm these conclusions by considering different scenarios such as climate risks, farmers’ entrepreneurship and credit constraints. We find that the effects are more salient if croplands are under higher natural risks and, farmers are equipped with entrepreneurship and formal credit. This paper implies that the agricultural insurance decoupled with green technologies also have salient positive effects on agricultural pollution control.

The potential contributions of this paper can be outlined in three aspects in detail. Firstly, this paper aims to revel the effects of agricultural insurance on pesticide selection by structuring a general theoretical model. By using the CLES data from 2020 to 2021, we confirm that agricultural insurance increases the probability for adopting green pesticides. Secondly, this paper discusses the effects of farmers’ characteristics on the results and finds that if farmers have entrepreneurship, the effects of agricultural insurance on green pesticide usage will be more salient. Thirdly, it uncovers some practices in China, which will supply experiences for other developing countries. For example, this paper further demonstrates that “insurance + credit” plan the present Chinese government carried out will be an important measure for strengthening effects of agricultural insurance on green pesticides usage. Moreover, it shows that decouple agricultural policies will also guide farmers to use green technologies eventually if the technologies are reliable and farmers can afford.

Current challenges in the educational sector along with age-related changes during early adolescence contribute to an increased sense of school alienation (SAL) among students. Some of the central concerns of SAL are failure to participate in classroom and socially deviant behaviors. This study examined the change in and cross-lagged relationships among alienation from learning, teachers, and classmates, and different self-reported learning and social behaviors across 508 secondary school students spanning a one-year interval from Grade 7 to Grade 8. The results revealed a slight increase in SAL and a decline in classroom participation. Earlier SAL predicted students’ later in-class participation and delinquent behavior, but not vice versa. The three alienation domains were shown to have different relationships with targeted learning and social behaviors: Alienation from learning and from teachers negatively predicted student classroom participation. Alienation from teachers and from classmates contributed to subsequent delinquent behavior. The study results emphasized the importance of SAL for students’ participation in classroom activities as well as in disruptive behaviors. Theoretical and practical implications of the findings for educational research and practice are discussed.

Using the remarkable olfaction ability, insects can sense trace amounts of host plant volatiles that are notorious for causing severe damage to fruits and vegetables and in consequence the industry. The purpose of the paper is to investigate the interactions between olfactory proteins, odorant-binding proteins (OBPs) and host plant volatiles through the developed olfactory biosensors. It might be helpful to develop novel pest control strategies.

Using the successfully expressed and purified OBPs of the oriental fruit fly Bactrocera dorsalis, a biosensor was developed by immobilizing the proteins on interdigitated electrodes through nitrocellulose membrane. Based on electrochemical impedance sensing, benzaldehyde emitted by the host plants, such as Beta vulgaris, was detected, which could be used to investigate and analyze the mechanisms of pests’ sense of chemical signals. The relative decreases of charge transfer resistances of the sensor were proportional to the odorant concentrations from 10⁻⁷ M to 10⁻³ M. Meanwhile, the interactions between OBPs and benzaldehyde were studied through the process of molecular docking.

The paper provides a pest OBPs-based biosensor that could sensitively detect the host odorants benzaldehyde. Meanwhile, the most related amino acids of OBPs that bind to host plant volatiles can be distinguished with molecular docking.

An olfactory biosensor was developed to explore interactions and mechanism between the pest OBPs and benzaldehyde, which showed promising potentials for small organic molecule sensing. Simultaneously, it might be helpful for novel pest control strategies.

This paper aims to analyze the effect of Y₂O₃ mass fraction on the tribological performance of CrNi coating, which solved the problem of wear resistance on AISI H13 steel.

Y₂O₃ reinforced CrNi coatings were fabricated on AISI H13 steel. The microstructure and phases of obtained coatings were analyzed using a super-depth of field microscope and X-ray diffraction, respectively, and the effects of Y₂O₃ mass fraction on the microstructure and wear resistance were methodically investigated using a wear tester.

The average coefficients of friction and wear rates of Y₂O₃ reinforced CrNi coatings decrease with the increase of Y₂O₃ mass fraction, in which the Y₂O₃ plays a role of friction reduction and wear resistance. The wear mechanism of Y₂O₃ reinforced CrNi coating is primary abrasive wear, accompanied by adhesive wear, which is contributed to the grain refinement and dense structure by the Y₂O₃ addition.

The Y₂O₃ was added to the CrNi coating by laser cladding, and the effect mechanism of Y₂O₃ mass fraction on the tribological performance of CrNi coating was established by the wear model.

Considering the emergence of e-commerce platforms and their integration into marketing channels, this paper aims to investigate how artificial intelligence (AI) resources – both technological and human – possessed by e-commerce platforms can enhance their channel power by acquiring market-based assets (relational and intellectual).

Based on resource-based theory and resource orchestration theory, the authors developed a framework tested using survey data gathered from the sellers, which incorporated six key variables: the e-commerce platform’s AI technology resources and human resources, rational and intellectual market-based assets, intraplatform competition and channel power. The analyses are performed using the regression analysis technique.

The empirical findings indicate that both technological and human AI resources are crucial in building channel power. In addition, market-based assets serve as a mediator in this relationship, while intraplatform competition moderates the effect of intellectual market-based assets on channel power negatively.

This study contributes to the existing literature by exploring how e-commerce platforms’ AI resources affect their channel power. The results offer valuable guidance to managers and researchers on optimizing AI resources to improve channel power.

Despite the many advantages this type of equipment offers, there are still some major drawbacks. Linear cutting machine (LCM) cannot accurately simulate the true rock-cutting process as 1. it does not account for the circular path along which tunnel boring machine (TBM) disk cutters cut the tunnel face, 2. it does not accurately model the position of a disk cutter on the cutterhead, 3. it cannot perfectly replicate the rotational speed of a TBM. To enhance the knowledge of these issues and in order to mimic the real rock-cutting process, a new lab testing equipment was developed by Hyundai Engineering and Construction.

A new testing machine called rotary cutting machine (RCM) is designed to simulate the excavation process of hard-rock TBMs and includes features such as TBM cutterhead, RPM simulation, constant normal force mode and constant penetration rate mode. Two sets of tests were conducted on Hwandeung granite using different disk cutter sizes to analyze the cutting forces in various excavation modes. The results are analyzed using statistical analysis and dimensional analysis. A new model is generated using dimensional analysis, and its results are compared against the results of actual cases.

The effectiveness of the new RCM test was demonstrated in its ability to apply various modes of excavation. Initial analysis of chip size revealed that the thickness of the chips is largely dependent on the cutter spacing. Tests with varying RPM showed that an increase in RPM results in an increase in the normal force and rolling force. The cutting coefficient (CC) demonstrated a linear correlation with penetration. The optimal specific energy is achieved at an S/p ratio of around 15. However, a slightly lower S/p ratio can also be used in the design if the cutter specifications permit. A dimensional analysis was utilized to develop a new RCM model based on the results from approximately 1200 tests. The model's applicability was demonstrated through a comparison of TBM penetration data from 26 tunnel projects globally. Results indicated that the predicted penetration rates by the RCM test model were in good agreement with actual rates for the majority of cases. However, further investigation is necessary for softer rock types, which will be conducted in the future using concrete blocks.

The originality of the research lies in the development of Hyundai Engineering and Construction’s advanced full-scale laboratory rotary cutting machine (RCM), which accurately replicates the excavation process of hard-rock tunnel boring machines (TBMs). The study provides valuable insights into cutting forces, chip size, specific energy, RPM and excavation modes, enhancing understanding and decision-making in hard-rock excavation processes. The research also presents a new RCM model validated against TBM penetration data, demonstrating its practical applicability and predictive accuracy.

In recent years, a great number of top conferences and workshops on artificial intelligence (AI) were held in China, showing Chinese AI plays an important role in the world. Meanwhile, Chinese government announced an ambitious scheme, “New Generation Artificial Intelligence Development Plan,” for the country to become a world leader in AI technologies by 2030. The AI research in China has covered various aspects, ranging from chips to algorithms. This chapter attempts to give an overview of the recent advances of AI research and development in China, as well as some perspectives on the future development of AI in China.

The purpose of this study is to investigate the effect of Y₂O₃ mass fraction on the electrochemical corrosion performance of CrNi coating, which provided a foundation for the performance optimization of CrNi coatings.

CrNi coatings with the different Y₂O₃ mass fractions were fabricated on AISI H13 steel by laser cladding, and the effect of Y₂O₃ mass fraction on the electrochemical performance of CrNi coating in 3.5% NaCl solution was investigated using an electrochemical workstation.

The electrochemical corrosion performance of CrNi coating enhances with the increase of Y₂O₃ mass fraction, and the CrNi–15%Y₂O₃ coating has the largest polarization resistance and the lowest corrosion current density, which displays the best electrochemical performance among the CrNi–5%Y₂O₃, –10%Y₂O₃ and –15%Y₂O₃ coatings. The protective films are formed with the increase of Y₂O₃ mass fraction, which inhibits the occurrence of electrochemical corrosion.

The Y₂O₃ was first added to the CrNi coating to improve its electrochemical corrosion performance, and the influence of Y₂O₃ on the corrosion resistance of the CrNi coating was discussed by the corrosion model.

Chinese marketing scholars have been studying marketing channel strategies for the past 20 years. However, the emergence of the internet and the digital economy has led to new marketing channels and practices that question the usefulness of this existing body of research, challenging Chinese marketing scholars specialized in channel strategy who are limited by path-dependent foundations and methods. This article reviews the research on marketing channel strategies by Chinese scholars, identifies the challenges posed by new channels and practices, and proposes some strategies for addressing these challenges.

This study systematically summarizes the research on marketing channel strategies published by Chinese scholars in English or Chinese in the past 20 years. Including articles published in either English-language or Chinese-language marketing journals allows this review to summarize the overall current state of marketing channel strategy research.

The theory and research methods used in studies of marketing channel strategies are relatively mature, and the field is saturated. However, the development of e-commerce and online channels have changed the structure of offline marketing channels, making Chinese scholars of marketing channel strategies to necessarily change Chinese scholars' thinking, methods, and research topics. Scholars from the fields of e-commerce, information system management, and big data are now conducting research on marketing channels. Chinese scholars who study marketing channel strategies need to establish and develop novel approaches to researching these new phenomena and practices.

This article analyzes the challenges faced by Chinese scholars who study marketing channel strategies and provides suggestions for future research in the area. The findings will assist in the development of research on new online and offline channel phenomena in the era of the internet and the digital economy.