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The practice of renovation and construction of university libraries is flourishing, but how to attract readers to use the library is an issue that urgently needs to be explored. Spatial cognition is a subjective judgment of a person's tendency to take action in the future and implies behavioral intention. Based on the sensory–image–cognition relationship, a theoretical model of university library readers' spatial cognition is conducted, and the influencing factors and mechanisms of spatial cognition are explored based on empirical data to provide theoretical references for spatial practices in university libraries.

A visual and art-based mental map approach is introduced based on a questionnaire survey. The questionnaire is mainly used for the specific evaluation of spatial use and the breakdown of the detailed elements, while the mental map method is mainly used for the evaluation of readers' spatial cognition. Relevant empirical data are collected from the library of the Zhejiang University of Technology.

The results indicate that readers' spatial sensory experience and mental imagery have positive effects on readers' behavior via the mediator spatial cognition, readers' spatial sensory experience and mental imagery have a positive effect on readers' spatial cognition and spatial cognition has a significant effect on readers' behavior.

The main contribution of this study is to construct a theoretical model of readers' spatial cognition and to explore the factors that have an impact on spatial cognition and the influence of cognition on behavior. This provides a more rational and in-depth thinking paradigm for the study of university library space and provides theoretical references for library practice.

This paper aims to explore blockchain integration strategies within a three-level livestock meat supply chain in which consumers have a preference for quality trust in livestock meat products. The paper investigates three questions: First, how does consumers’ preference for quality trust affect blockchain integration and transaction decisions among supply chain participants? Second, under what circumstances will retailers choose to participate in the blockchain? Finally, how can other factors such as blockchain costs and supplier–retailer partnership value affect integration decisions?

This paper formulates a supply chain network equilibrium model and employs the logarithmic-quadratic proximal prediction-correction method to obtain equilibrium decisions. Extensive numerical studies are conducted using a pork supply chain network to analyze the implications of blockchain integration for different supply chain participants.

The results reveal several key insights: First, suppliers’ increased blockchain integration, driven by higher quality trust preference, can negatively affect their profits, particularly, with excessive trust preferences and high blockchain costs. Second, an increase in consumers’ preference for quality trust expands the range of unit operating costs for retailers engaging in blockchain. Finally, the supplier–retailer partnership drives retailer blockchain participation, facilitating enhanced information sharing to benefit the entire supply chain.

This study provides original insights into blockchain integration strategies in an agricultural supply chain through the application of the supply chain network equilibrium model. The investigation of several key factors on equilibrium decisions provides important managerial implications for different supply chain participants to address consumers’ preference for quality trust and enhance overall supply chain performance.

This study holistically and systematically consolidates the available research on digital reading to reveal the research trends of the past 20 years. Moreover, it explores the thematic evolution, hotspots and developmental characteristics of digital reading. This study, therefore, has the potential to serve as a research guide to researchers and educators in relevant fields.

The authors applied a bibliometric approach using Derwent Data Analyzer and VOSviewer to retrieve 2,456 publications for 2003–2022 from the Web of Science (WoS) database.

The results revealed that most studies' participants were university students and the experimental methods and questionnaires were preferred in digital reading researches. Among the influential countries or regions, institutions, journals and authors, the United States of America, University of London, Electronic Library and Chen, respectively, accounted for the greatest number of publications. Moreover, the authors identified the developmental characteristics and research trends in the field of digital reading by analyzing the evolution of keywords from 2003–2017 to 2018–2022 and the most frequently cited papers by year. “E-books,” “reading comprehension” and “literacy” were the primary research topics. In addition, “attention,” “motivation,” “cognitive load,” “dyslexia,” “engagement,” “eye-tracking,” “eye movement,” “systematic analysis,” “meta-analysis,” “smartphone” and “mobile reading/learning” were potential new research hotspots.

This study provides valuable insights into the current status, research direction, thematic evolution and developmental characteristics in the field of digital reading. Therefore, it has implications for publishers, researchers, librarians, educators and teachers in the digital reading field.

Attracting commuters from driving to light rail systems has a good potential for reducing carbon emissions. However, the light rail system is interrupted by disruptions frequently, which reduces its attraction to passengers. Therefore, how to provide a quick replacement service during disruptions is of vital importance to avoid passengers change to other higher emission vehicles. The purpose of this paper is to focus on the decision analysis of the replacement tool for disruption recovery service in urban public light rail systems from the perspective of environmental effect.

The traditional approach – bus replacement service – and the new approach – taxi replacement service – which has been recently adopted by several cities, are examined individually and compared. The benefit of the light rail company is formulated by balancing between carbon emission and financial cost. The involving parties’ decision functions taking the passengers’ behaviors as well as numerous other important factors into account are formulated.

Both theoretical and numerical sensitivity analyses are conducted to shed light for light rail systems to better coping with disruptions, increasing service level, and attracting more passengers to the environmental transit system to reduce carbon emission.

It is worth mentioning that this research is a successful application for disruption recovery in a public transit system considering the environmental effect. To the authors’ knowledge, this research is one of the first of such applications in this area and can be used not only in the public light rail systems, but also in other urban public transport network components such as the subway and rail systems.

We examine the effectiveness of signaling by disclosing innovation in annual reports in terms of securing R&D subsidies, using a novel text-based measure of firm-level innovation intensity.

The empirical analysis includes regressions with firm and year-fixed effects and an instrumental variable approach. Both mediation and moderation analysis are conducted to identify the plausible channels.

We find that firms are likely to receive research and development (R&D) subsidies if their annual reports contain intensive disclosure of information about innovation. We also identify the site visits by government officials as a plausible channel through which innovation disclosure in annual reports can help firms receive R&D subsidies. Additional analysis shows the main effect of innovation disclosure is especially pronounced in firms with severe information asymmetry and those facing a low-trust environment.

Current studies have shown the effectiveness of signaling in capital markets in terms of securing bank loans and venture capital (Cassar et al., 2015; Hoenig and Henkel, 2015; Connelly et al., 2016; Plummer et al., 2016). It is unclear if such a signaling can attract the attention of government officials. Our results suggest that government officials view annual reports as an important means of mitigating information asymmetry, which in turn helps firms to receive external R&D funding.

To improve the high-temperature wear properties of the SiCp/A359 composite, foamed iron-reinforced SiCp/A359 composite (A359–SiCp/Fe) is prepared. The purpose of this study is to investigate the tribological behavior and mechanism of the A359–SiCp/Fe composites at different temperatures (100–500 °C) and loads (7 N, 10 N and 12 N).

The A359–SiCp/Fe composite was fabricated by vacuum-assisted infiltration. The dry sliding tribological behaviors of A359–SiCp/Fe composite were investigated using the ball-on-disc-type tribometer. The worn surface and wear morphology of the longitudinal section were examined using field emission scanning electron microscopy and metallographic microscope.

The critical transition temperature for severe wear in A359–SiCp/Fe composite was 50–100 °C higher than in SiCp/A359 composite. Foamed iron prevents exfoliation cracks from penetrating deeper into the matrix. The friction coefficient stability of the A359–SiCp/Fe composite was higher than the unreinforced composite at elevated temperatures. With the increase in temperature, the friction-affected layer was severely worn, and the wear mechanism transferred from abrasion and delamination to oxidation and plastic flow, respectively.

The preparation procedure for aluminum matrix composites reinforced with foamed metal has been less reported, and the research on the tribological behavior and mechanism of A359–SiCp/Fe composite at various temperatures is insufficient. The foamed iron structure considerably enhances the wear properties of SiCp/A359 composite in elevated temperature conditions.

With the rapid increase in the number of installed wind turbines (WTs) worldwide, requirements and expenses of maintenance have also increased significantly. The condition monitoring (CM) of WT provides a strong “soft guarantee” for preventive maintenance. The supervisory control and data acquisition (SCADA) system records a huge amount of condition data, which has become an effective means of CM. The main objective of the present study is to summarize the application of SCADA data to fault detection in wind turbines, analyze its advantages and disadvantages and predict the potential of future investigations on the use of SCADA data for fault detection.

The authors first review the means of WT CM and summarize the characteristics of CM based on SCADA data. To ensure the quality of SCADA data, data preprocessing methods are analyzed and compared. Then, the failure modes of the key components are discussed and the SCADA data used for fault detection of each component are compared. Moreover, the fault detection methods for WT are classified and a general framework for fault detection is proposed. Finally, the issues in the WT fault detection method based on SCADA data are reviewed.

Based on the performed analyses, it is found that although the fault detection accuracy based on SCADA data is relatively poor, it has low capital expenses and low computational cost. More specifically, when there is scarce fault data, the normal SCADA data can be used to detect the fault time. However, the specific fault type cannot be identified in this way. When a large amount of fault data are accumulated in the SCADA system, it can not only detect the occurrence time of the fault but also identify the specific fault type.

The main contribution of the present study is to summarize the pre-processing methods for SCADA data, the data required for fault detection of key components and the characteristics of the fault detection model. Then we propose a general fault detection framework for wind turbines based on SCADA data, where the maintenance workers can choose the appropriate fault detection method according to different fault detection requirements and data resources. This article is expected to provide guidance for fault detection based on time-series sensor signals and be of interest to researchers, maintenance workers and managers.

Financial technologies, also known as “FinTech,” have brought disruptive changes to virtually every aspect of financial services and are becoming increasingly important in the world economic system. The purpose of this paper is to proffer a bird view of some recent studies in the key research areas of FinTech, such as artificial intelligence, blockchain, crowdfunding and then to summarize the key contributions made by all the six papers in this special issue.

A literature review approach is adopted, and the summary shows that most types of FinTech innovations generate positive value to innovators, financial customers and the society. The current implications and future directions are explored based on theoretical and empirical analyses.

The benefits from and determinants of FinTech applications vary across different financial sectors. Together the summary of this special issue suggests that there is substantial value creation in further exploring the dynamics, mechanisms and social consequences of FinTech.

This study helps to extend knowledge by summarizing the current practices, proffering new insights and watching out emerging trends of financial technologies, and to shed light on a variety of subjects of interest to practitioners, academics and policy makers by suggesting for the future research topics.

The purpose of this paper is to investigate the impact of mechanical vibration on the heat transfer and pressure drop characteristics of semicircular channel printed circuit heat exchangers (PCHEs), while also establishing correlations between vibration parameters and thermal performance.

By combining experimental and numerical simulation methods, the heat transfer coefficient and pressure drop characteristics of supercritical carbon dioxide (S-CO₂) in a semicircular channel with a diameter of 2 mm under vibration conditions were studied. Reinforce the research by conducting computational fluid dynamics studies using ANSYS Fluent 22.0, the experimental results were compared with the numerical simulation results to verify the accuracy of the numerical method.

The use of vibration has the potential to attenuate the degradation of wall heat transfer caused by buoyancy-induced PCHEs on the upward-facing surface. The heat transfer enhancement (HTE) was maximized by an increase of 18.2%, while the pressure drop enhancement (PDE) was elevated by over 25-fold. The capacity to enhance the heat exchange between S-CO₂ and channel walls through increasing vibration intensity is limited, indicating maximum effectiveness in improving thermal performance.

Conducting heat transfer experiments on PCHEs with mechanical vibration enhancement and verifying the accuracy of the vibration numerical model. The relation based on the dimensionless factor is derived. To provide theoretical support for using vibration to enhance the heat transfer capability of PCHEs.