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This study aims to improve detection efficiency of fluorescence biosensor or a graphene field-effect transistor biosensor. Graphene field-effect transistor biosensing and fluorescent biosensing were integrated and combined with magnetic nanoparticles to construct a multi-sensor integrated microfluidic biochip for detecting single-stranded DNA. Multi-sensor integrated biochip demonstrated higher detection reliability for a single target and could simultaneously detect different targets.

In this study, the authors integrated graphene field-effect transistor biosensing and fluorescent biosensing, combined with magnetic nanoparticles, to fabricate a multi-sensor integrated microfluidic biochip for the detection of single-stranded deoxyribonucleic acid (DNA). Graphene films synthesized through chemical vapor deposition were transferred onto a glass substrate featuring two indium tin oxide electrodes, thus establishing conductive channels for the graphene field-effect transistor. Using π-π stacking, 1-pyrenebutanoic acid succinimidyl ester was immobilized onto the graphene film to serve as a medium for anchoring the probe aptamer. The fluorophore-labeled target DNA subsequently underwent hybridization with the probe aptamer, thereby forming a fluorescence detection channel.

This paper presents a novel approach using three channels of light, electricity and magnetism for the detection of single-stranded DNA, accompanied by the design of a microfluidic detection platform integrating biosensor chips. Remarkably, the detection limit achieved is 10 pm, with an impressively low relative standard deviation of 1.007%.

By detecting target DNA, the photo-electro-magnetic multi-sensor graphene field-effect transistor biosensor not only enhances the reliability and efficiency of detection but also exhibits additional advantages such as compact size, affordability, portability and straightforward automation. Real-time display of detection outcomes on the host facilitates a deeper comprehension of biochemical reaction dynamics. Moreover, besides detecting the same target, the sensor can also identify diverse targets, primarily leveraging the penetrative and noninvasive nature of light.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

The core objective of this study is to provide an in-depth quantitative assessment of the efficiency of public library knowledge services (PLKS) in China and to scrutinize the factors that have a significant impact on the efficiency of PLKS. Furthermore, this study also aims to examine the characteristics and evolving patterns of PLKS in China and to propose strategies for enhancing the quality of services provided by public libraries. The findings of this paper are expected to provide valuable references for current academic research and practice areas, guiding and promoting exploration and development in related fields.

To analyse and evaluate the operation mechanism and efficiency of PLKS, this study creatively constructs a multi-stage PLKS efficiency evaluation model and provides related indicators. Based on this process, the super-efficiency network slacks-based measure model was used to analyse the efficiency, and dynamic qualitative comparative analysis was adopted to analyse the recipes about the influencing factors of PLKS. Ultimately, through a comprehensive interpretation of the measured data and the integration of extant societal development conditions, the authors put forth relevant recommendations.

In the first stage, PLKS in China meets the basic requirements, but in the second stage, there is evident resource wastage. In addition, there are five recipes in PLKS of China. These five recipes reveal the configuration relationship between the factors that affect PLKS. The results show that PLKS in China are different in different regions, and the effects of the influencing factors are also different.

In this study, the authors provide an exhaustive deconstruction and interpretation of PLKS, thereby proposing a three-stage PLKS efficiency conversion process. Furthermore, the authors have identified a set of readily accessible and quantifiable indicators. It is worth emphasizing that the authors have taken a unique approach to analyse the elements affecting PLKS from the perspective of configuration, which has significantly broadened the boundaries and depth of PLKS research.

The rapid growth of professional esports has highlighted the lack of a universally recognised governing body to standardise operations and competition rules. This absence presents many challenges. A key concern is the well-being of professional esports players (e-pro-players), who often suffer from exhaustion. This study aims to examine the factors contributing to exhaustion among e-pro-players.

Using the conservation of resources theory, we developed a framework to explain the factors leading to e-pro-players’ exhaustion and the conditions under which it occurs. We tested this framework with 126 responses in a dyadic survey from e-pro-players and their coaches in China. Additionally, we gathered qualitative insights from 50 interviews with esports stakeholders to provide more context for our quantitative findings.

Our study found that e-pro-players’ intrinsic motivation to engage in training reduces their exhaustion, while their struggle to cope with uncertainty in esports environments (intolerance of uncertainty) increases it. The effect of intrinsic motivation is weaker for those who believe their talent for playing esports is fixed (entity belief) but stronger for those with high relational identification with their coaches. Additionally, the link between uncertainty intolerance and exhaustion is stronger in players with strong entity beliefs.

Our study sheds light on the factors contributing to e-pro-players’ exhaustion within the partially regulated professional esports environment, a phenomenon that significantly influences their overall well-being. Through the identification and examination of these factors and the conditions under which they affect exhaustion, we deepen the understanding of the drivers of exhaustion for e-pro-players who operate in an industry lacking standardised regulations.

The present study delves into the incorporation of the Metaverse in the insurance industry, with an emphasis on augmenting consumer experiences via virtual interaction.

We explored secondary data sources on metaverse in the insurance industry and went through a thorough analysis of the literature and case studies, showcasing best practices and inspirational tales from top insurers.

The study found that insurers are ready to capitalize on the convergence of the digital and physical realms embracing the “phygital” environment. By making investments in the Metaverse, insurance companies can reduce new risks, enhance customer satisfaction, and streamline operations. But it also brings up issues with user privacy and security. The efficient application of metaverse solutions may be hampered by problematic areas including malware, cyberbullying, identity theft, cyber hacking, and cyberattacks. User privacy and data security are complicated issues that need the cooperation and accountability of several stakeholders.

Insurers may revolutionize traditional insurance interactions by utilizing cutting-edge technology like virtual reality (VR) and augmented reality (AR) to create personalized, interactive, and instructive experiences for their consumers. For insurers, the Metaverse has ushered in a new era of digital transformation by giving them a powerful arsenal of technological resources to engage with customers and develop creative business plans.

The study on the Metaverse in insurance—a virtual customer experience is an original contribution based on literature and case studies on virtual experiences. The ultimate goal of this study is to offer insights into the optimization of virtual client experiences in the digital age by examining the possible advantages, difficulties, and ramifications of applying Metaverse technologies in the insurance industry.

This paper explores the association between directors’ and officers’ liability insurance (D&O insurance) and management tone manipulation.

This study uses data from A-share listed non-financial companies from 2009 to 2021 as its sample for empirical tests. In addition, the study relies on text analysis and the construction of models to investigate the relationship between D&O insurance and management tone manipulation.

The authors find that the purchase of D&O insurance will lead to management tone manipulation in the “management discussion and analysis” part of companies’ annual reports, and operating risk and agent cost are the two paths for the effect. Further analysis shows that having a male CEO and employing high-quality auditors can weaken the positive impact of D&O insurance on tone manipulation.

This paper provides a new approach for studying the literature related to D&O insurance and management behavior, and the findings enrich our understanding of the influencing factors and the mechanism of management tone manipulation, thus revealing policy implications for further standardization of the terms and system of D&O insurance in China.

This paper has a dual purpose. The first is to provide a thorough analysis of developments in international marketing in relation to the coronavirus disease 2019 (COVID-19) pandemic; the second is to capitalize on these developments to set an agenda for future research in the field of international marketing.

This paper zooms in on and reviews the 18 papers published in International Marketing Review’s (IMR) Special Issue on “Covid 19: advancing international marketing theory and guiding practice” (2023, volume 40, issue 5). It also integrates recent research at the intersection of international marketing and the COVID-19 pandemic.

The paper highlights five areas that embody significant contemporaneous changes brought about by the COVID-19 pandemic and affect international marketing practice. These include (1) shifts in consumer behavior, (2) digitalization and artificial intelligence, (3) disruptions in supply chains, (4) communication and corporate social responsibility (CSR), and (5) international dynamic marketing capabilities. In order to advance international marketing theory in relation to pandemics and other external crises, the paper establishes research directions for each of these areas.

The paper provides a novel and comprehensive categorization of fundamental shifts caused by the COVID-19 pandemic and lays out a research roadmap to advance research in the field of International Marketing (IM). Important implications for practice are also discussed.

This study investigates whether Chinese local governments’ environmental attention can mitigate corporate “greenwashing,” focusing on the extent of environmental content in annual government work reports as indicative of government environmental attention. This study aims to determine whether enterprises respond to changes in local governmental attention by improving the quality of their environmental information disclosures.

Data from China’s A-share listed companies spanning 2013–2021 were sourced from the CSMAR database and company annual reports. Environmental attention data were manually gathered from local government work reports published on official local government websites by using text analysis methods. These datasets were analyzed empirically to assess the impact of local governments’ environmental attention on corporate greenwashing behavior.

Results show that increased governmental environmental attention significantly reduces corporate greenwashing behavior by alleviating corporate financing constraints, enhancing independent engagement in environmental initiatives and bolstering stakeholder oversight. Moreover, heterogeneity analysis indicates that the influence of government environmental concerns is pronounced in non-state-owned enterprises, firms with subpar audit quality and those exhibiting myopic management tendencies.

This study enriches the existing literature on the government–business nexus. It also introduces methodological innovations by employing a lexical analysis of environmental themes in local government work reports instead of using typical event study approaches. Furthermore, it uses a mediating effect model to identify the mechanisms through which government environmental attention influences corporate greenwashing, namely, government subsidies, corporate environmental initiatives and external stakeholder oversight.

In the field of steel defect detection, the existing detection algorithms struggle to achieve a satisfactory balance between detection accuracy, computational cost and inference speed due to the interference from complex background information, the variety of defect types and significant variations in defect morphology. To solve this problem, this paper aims to propose an efficient detector based on multi-scale information extraction (MSI-YOLO), which uses YOLOv8s as the baseline model.

First, the authors introduce an efficient multi-scale convolution with different-sized convolution kernels, which enables the feature extraction network to accommodate significant variations in defect morphology. Furthermore, the authors introduce the channel prior convolutional attention mechanism, which allows the network to focus on defect areas and ignore complex background interference. Considering the lightweight design and accuracy improvement, the authors introduce a more lightweight feature fusion network (Slim-neck) to improve the fusion effect of feature maps.

MSI-YOLO achieves 79.9% mean average precision on the public data set Northeastern University (NEU)-DET, with a model size of only 19.0 MB and an frames per second of 62.5. Compared with other state-of-the-art detectors, MSI-YOLO greatly improves the recognition accuracy and has significant advantages in computational cost and inference speed. Additionally, the strong generalization ability of MSI-YOLO is verified on the collected industrial site steel data set.

This paper proposes an efficient steel defect detector with high accuracy, low computational cost, excellent detection speed and strong generalization ability, which is more valuable for practical applications in resource-limited industrial production.

With the rapid low-carbon transformation in China, the industrial approach and labor structure of mining enterprises are undergoing constant changes, leading to an increasing psychological dilemma faced by coal miners. This study aims to reveal the relationship and mechanism of factors influencing the psychological dilemma of miners, and to provide optimal intervention strategies for the safety and sustainable development of employees and enterprises.

To effectively address the complex issue of the psychological dilemma faced by miners, this study identifies and constructs five-dimensional elements, comprising 20 indicators, that influence psychological dilemmas. The relational mechanism of action of factors influencing psychological dilemma was then elucidated using an integration of interpretive structural modeling and cross-impact matrix multiplication.

Industry dilemma perception is a “direct” factor with dependent attributes. The perceptions of management response and relationship dilemmas are “root” factors with driving attributes. Change adaptation dilemma perception is a “susceptibility” factor with linkage attributes. Work dilemma perception is a “blunt” factor with both dependent and autonomous attributes.

The aforementioned findings offer a critical theoretical and practical foundation for developing systematic and cascading intervention strategies to address the psychological dilemma mining enterprises face, which contributes to advancing a high-quality coal industry and efficient energy development.