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Abstract Intestinal fibrosis is the primary cause of disability in patients with Crohn’s disease (CD), yet effective therapeutic strategies are currently lacking. Here, we report a multiomics analysis of gut microbiota and fecal/blood metabolites of 278 CD patients and 28 healthy controls, identifying characteristic alterations in gut microbiota (e.g., Lachnospiraceae, Ruminococcaceae, Muribaculaceae, Saccharimonadales) and metabolites (e.g., L-aspartic acid, glutamine, ethylmethylacetic acid) in moderate-severe intestinal fibrosis. By integrating multiomics data with magnetic resonance enterography features, putative links between microbial metabolites and intestinal fibrosis-associated morphological alterations were established. These potential associations were mediated by specific combinations of amino acids (e.g., L-aspartic acid), primary bile acids, and glutamine. Finally, we provided causal evidence that L-aspartic acid aggravated intestinal fibrosis both in vitro and in vivo. Overall, we offer a biologically plausible explanation for the hypothesis that gut microbiota and its metabolites promote intestinal fibrosis in CD while also identifying potential targets for therapeutic trials.

Abstract This study investigates the unintended socioeconomic consequences of housing market regulations, focusing on the home purchase restriction (HPR) policy implemented in cities across China. While the primary aim of the HPR policy is to curb property prices by limiting the number of properties a household can purchase, its broader impact on family formation, particularly marriage and divorce patterns, remains underexplored. Applying Becker’s economic theory of marriage, which views marital decisions as rational choices influenced by socioeconomic factors, this study examines how the HPR policy affects family formation and dissolution across different city tiers and age groups in China. Our analysis reveals several key findings. First, the HPR policy effectively contributed to a decrease in house prices, aligning with its primary objective. However, it also led to delayed marriages among younger age groups, especially in first-tier cities, where housing affordability is a significant concern. Second, the policy inadvertently encouraged strategic divorces, allowing couples to circumvent purchase restrictions and acquire additional properties. This loophole undermines the policy’s effectiveness in reducing housing demand and stabilizing prices. These results highlight the complex interplay between housing market regulations and family demographics, emphasizing the need for policymakers to consider the broader societal impacts of non-family-oriented policies. As China, like many other societies, faces challenges related to the second demographic transition—such as declining marriage and fertility rates—the findings of this study serve as a cautionary tale. Housing policies, while effective in addressing market concerns, can have significant and sometimes counterproductive effects on family stability and formation, potentially exacerbating the demographic trends a society aims to mitigate.

Abstract Agent-based modeling and simulation have evolved as a powerful tool for modeling complex systems, offering insights into emergent behaviors and interactions among diverse agents. Recently, integrating large language models into agent-based modeling and simulation presents a promising avenue for enhancing simulation capabilities. This paper surveys the landscape of utilizing large language models in agent-based modeling and simulation, discussing their challenges and promising future directions. In this survey, since this is an interdisciplinary field, we first introduce the background of agent-based modeling and simulation and large language model-empowered agents. We then discuss the motivation for applying large language models to agent-based simulation and systematically analyze the challenges in environment perception, human alignment, action generation, and evaluation. Most importantly, we provide a comprehensive overview of the recent works of large language model-empowered agent-based modeling and simulation in multiple scenarios, which can be divided into four domains: cyber, physical, social, and hybrid, covering simulation of both real-world and virtual environments, and how these works address the above challenges. Finally, since this area is new and quickly evolving, we discuss the open problems and promising future directions. We summarize the representative papers along with their code repositories in https://github.com/tsinghua-fib-lab/LLM-Agent-Based-Modeling-and-Simulation .

Abstract This study investigates the influence of digital finance tools on air quality in China from 1990 to 2020 using the cross-sectional augmented autoregressive distributed lag approach. The findings underscore the critical role of digital finance, especially internet banking, in reducing air pollution levels. The increased adoption of internet banking is linked to lower vehicular emissions and more efficient financial operations, aiding environmental preservation. Similarly, ATM banking is found to negatively correlate with air pollution, though to a lesser extent. In contrast, coal consumption, urban population growth, and inflation are positively associated with air pollution, highlighting the necessity for sustainable urban planning and energy transition policies. To combat air pollution, it is essential to utilize digital finance tools, broaden digitalization across various sectors, and employ AI and big data for precise interventions. Supporting green financial tools can help fund renewable energy projects, speeding up China’s shift to a low-carbon economy and mitigating the harmful effects of air pollution.

Abstract While whole genome sequencing (WGS) of cell-free DNA (cfDNA) holds enormous promise for detection of molecular residual disease (MRD), its performance is limited by WGS error rate. Here we introduce AccuScan, an efficient cfDNA WGS technology that enables genome-wide error correction at single read-level, achieving an error rate of 4.2 × 10−7, which is about two orders of magnitude lower than a read-centric de-noising method. The application of AccuScan to MRD demonstrated analytical sensitivity down to 10−6 circulating variant allele frequency at 99% sample-level specificity. AccuScan showed 90% landmark sensitivity (within 6 weeks after surgery) and 100% specificity for predicting relapse in colorectal cancer. It also showed 67% sensitivity and 100% specificity in esophageal cancer using samples collected within one week after surgery. When AccuScan was applied to monitor immunotherapy in melanoma patients, the circulating tumor DNA (ctDNA) levels and dynamic profiles were consistent with clinical outcomes. Overall, AccuScan provides a highly accurate WGS solution for MRD detection, empowering ctDNA detection at parts per million range without requiring high sample input or personalized reagents.

Abstract Chemotherapy, the standard of care treatment for cancer patients with advanced disease, has been increasingly recognized to activate host immune responses to produce durable outcomes. Here, in colorectal adenocarcinoma (CRC) we identify oxaliplatin-induced Thioredoxin-Interacting Protein (TXNIP), a MondoA-dependent tumor suppressor gene, as a negative regulator of Growth/Differentiation Factor 15 (GDF15). GDF15 is a negative prognostic factor in CRC and promotes the differentiation of regulatory T cells (Tregs), which inhibit CD8 T-cell activation. Intriguingly, multiple models including patient-derived tumor organoids demonstrate that the loss of TXNIP and GDF15 responsiveness to oxaliplatin is associated with advanced disease or chemotherapeutic resistance, with transcriptomic or proteomic GDF15/TXNIP ratios showing potential as a prognostic biomarker. These findings illustrate a potentially common pathway where chemotherapy-induced epithelial oxidative stress drives local immune remodeling for patient benefit, with disruption of this pathway seen in refractory or advanced cases.

Abstract Policies to address climate change have been implemented worldwide in recent years. The core of these policies is to control greenhouse gas (GHG) emissions, which primarily stem from the consumption of fossil fuels. Consequently, the implementation of climate policies can affect other energy-related issues, such as energy poverty, a critical element of the UN Sustainable Development Goals (SDGs). This paper uses cross-country data from 2000 to 2020 to study the possible policy spillovers from climate actions to energy poverty. We show that a spillover effect does exist. In other words, a higher number of climate policies is associated with a lower level of energy poverty. The spillover is realized through improvements in energy efficiency, the promotion of renewable energy, and support for innovations. In addition, legislative policies are found to have stronger spillover effects. While the overall policy effects are positive for executive policies, regulations tend to have negative impacts on energy development. There is also evidence demonstrating heterogeneous effects between long-term and short-term policies, and between developed and developing countries. Discovering this spillover effect gives extra motivation for countries to adopt climate policies and actively seek synergies in achieving broader sustainable goals.

Abstract In response to the covid-19 pandemic, the digital strategy of education has become a key pedagogical approach for higher engineering disciplines. In this complex environment, the outcome-oriented higher engineering discipline faces the challenge of educational equity in terms of curriculum design and learning outcome assessment for its online engineering practical courses. In order to solve this problem, this study develops a digital teaching assistant system to facilitate the reform of educational equity in higher engineering disciplines. The teaching and learning functions of the system aim to support the interaction between teachers and students in the teaching process and the visual display of learning outcomes, and its intelligent evaluation and analysis function is based on the multi-criterion group decision-making model of Quality Function Deployment (QFD) combined with t-test to realize the evaluation of course learning outcomes. The results show that the academic performance of this system is significantly better than that of other similar systems. The statistical results of the teacher-student satisfaction survey of the two systems show that the teacher-student interaction and multi-dimensional learning evaluation analysis report function provided by the system are the most highly recognized, and the system also has better educational equity in resource recommendation, interaction and collaboration, learning achievement display and learning achievement evaluation, etc. In addition, the system is more in line with the teaching characteristics of higher engineering disciplines, which can provide effective assistance for teachers of higher engineering disciplines to improve teaching plan and cultivate students’ disciplinary practicality, consequently creating favorable conditions for the establishment of teaching equity.

Abstract Rapid urbanization and industrialization with their negative repercussions draw attention to the need for urban sustainability. This research built on the urban systems understanding linked with resource utilization, environmental effects, people-environment interactions, and adaptive management by integrating quantitative modelling of urban metabolism with a qualitative investigation into human responses. A hybrid methodology was applied in a typical industrial city of Jinchang, China, which exemplified a model of how complex urban dynamics link to and inform sustainability transitions. The study found that Jinchang City had taken on an unsustainable trajectory underpinned by continuous growth of material consumption, whereas a potential for sustainability transitions was also observed in decoupled negative material outputs, improved material efficiency, and environment regeneration collectively. The challenges in industrial cities have been framed in terms of development model lock-in, conceptual and institutional constraints, innovation and human capital deficiencies, and governance failure. The research proposed a government-led transformation system that integrates multi-level and multi-perspective transformations and management employing discipline insights to facilitate urban sustainability transitions. This involves governance, economic and technological innovations, social transformations, and implementations, in which urban governance and public engagement are essential elements for adapting to undesirable difficulties and exploring locally appropriate strategies. This research provided a theoretical and empirical basis along with scientific and policy implications, which contributed to the developing interdisciplinary knowledge on the understanding of complex urban systems and provided insights into real-world sustainability solutions.

Abstract This study examines the multifaceted impact of artificial intelligence (AI) on environmental sustainability, specifically targeting ecological footprints, carbon emissions, and energy transitions. Utilizing panel data from 67 countries, we employ System Generalized Method of Moments (SYS-GMM) and Dynamic Panel Threshold Models (DPTM) to analyze the complex interactions between AI development and key environmental metrics. The estimated coefficients of the benchmark model show that AI significantly reduces ecological footprints and carbon emissions while promoting energy transitions, with the most substantial impact observed in energy transitions, followed by ecological footprint reduction and carbon emissions reduction. Nonlinear analysis indicates several key insights: (i) a higher proportion of the industrial sector diminishes the inhibitory effect of AI on ecological footprints and carbon emissions but enhances its positive impact on energy transitions; (ii) increased trade openness significantly amplifies AI’s ability to reduce carbon emissions and promote energy transitions; (iii) the environmental benefits of AI are more pronounced at higher levels of AI development, enhancing its ability to reduce ecological footprints and carbon emissions and promote energy transitions; (iv) as the energy transition process deepens, AI’s effectiveness in reducing ecological footprints and carbon emissions increases, while its role in promoting further energy transitions decreases. This study enriches the existing literature by providing a nuanced understanding of AI’s environmental impact and offers a robust scientific foundation for global policymakers to develop sustainable AI management frameworks.

Abstract Using Chinese-listed enterprise data from 2010 to 2021, we study the relationships among enterprise digital transformation, managerial myopia and cost stickiness. The results show that enterprise digital transformation inhibits cost stickiness, including operating cost stickiness as well as selling, general and administrative (SG&A) cost stickiness. This result holds after various robustness and endogeneity tests. Additionally, mechanism research indicates that enterprise digital transformation inhibits cost stickiness by reducing adjustment costs (ACs) and alleviating financing constraints (SAs). However, managerial myopia negatively affects the inhibition of enterprise digital transformation on cost stickiness by increasing ACs and aggravating SAs. Furthermore, the relationship between enterprise digital transformation and cost stickiness is stronger for mature, state-owned and high-tech enterprises than for those with better digital economy policy environments.

Abstract This paper explores the mapping from specific digitalization practices to specific resilient performance against a great shock. Based on an adapted structure–conduct–performance framework, this paper hypothesizes by theoretically analyzing how the pre-shock establishment of digital retailing practices could trigger physical retailers’ bounce-back and bounce-forward performance against the COVID-19 crisis. Using a difference-in-differences strategy, the hypotheses are examined with a sample including 549 observations of 50 Chinese listed retailers from the first quarter of 2018 to the third quarter of 2020. The empirical results mainly indicate the following binary findings. First, regardless of the differences in triggering bounce-back performance, different digital retailing practices are found to be effective in triggering physical retailers’ bounce-forward performance against the COVID-19 crisis. This somewhat addresses the concern about the temporality of digitalization-enabled resilience by revealing the generality across digital retailing practices in the sense of triggering resilient performance. Second, it is shown that physical retailers’ bounce-back performance at a specific stage of the COVID-19 crisis could only be triggered by digital retailing practices that coincidentally apply to the shock-induced market structure changes at the stage. The results emphasize each digitalization practice’s individuality in triggering resilient performance. This justifies the non-negligibility of the direct mapping from specific digitalization practices to specific resilient performance in digitalization-enabled resilience evaluation.

Abstract Recent years have witnessed an increasing number of manipulated online reviews in e-commerce platforms. Previous research has provided substantial evidence that vendor manipulation of online reviews has a significant negative impact on the stakeholders involved in the e-commerce business. Many platforms take various governance measures to filter manipulated reviews. Nevertheless, the effectiveness of these measures still remains unknown to a large extent. To bridge this research gap, this paper investigates the effect of differentiated platform governance, including defined as interventions to counterattack manipulation intensity, manipulation duration, and perceived quality manipulated, on the probability of future review manipulation. We develop a game theoretical model that incorporates the strategic interactions between the platform and vendors, which yield several testable hypotheses. We then conduct an empirical analysis of platform governance and review manipulation by using the review manipulation data collected from Amazon.com. Results of the analytical model and empirical analysis show that platform governance that targets manipulation intensity and manipulation duration can both effectively mitigate review manipulation probability. On the contrary, platform governance to counterattack manipulating perceived product quality exhibits an inverted U-shape relationship with review manipulation probability. This study provides novel insights into how to better mitigate online review manipulation for e-commerce platforms.

Abstract The outbreak of COVID-19 had a significant impact on the psychological and behavioral health of college students. However, few studies have systematically explored the relationship between COVID-19 and psychological and behavioral health among college students worldwide. Therefore, the purpose of this study was to explore the impact of COVID-19 on college students’ psychological and behavioral health using a knowledge-mapping approach. In total, 796 publications were selected and analyzed to clarify the publication volume and time distribution, core authors, major journals, research institutions, country distributions, research hotspots, and core themes. Since the outbreak of the COVID-19 pandemic in 2019, studies focused on the impact of COVID-19 on college students’ psychological and behavioral health showed an increasing trend year by year. The three countries with the highest centrality were Britain (0.34), the United States (0.24), and Mexico (0.13). The five major topics of research were mental health, academic pressure, physical health risks, college students’ majors, and daily living habits, with most research concerned with college students’ mental health. The visualized burst detection results were combined to identify three cutting-edge research topics in this field: the sustained impact of COVID-19 on college students’ mental health, the sustained impact of COVID-19 on medical college students, and the mediating role of college students’ mental resilience during COVID-19. We conclude by discussing the implications of our findings.

Abstract Film color and editing are crucial elements in filmmaking, posing significant questions about their effective use in eliciting emotional responses from viewers. While prior research has explored the impacts of color and editing independently, their combined effect remains largely unexplored, leaving the open question of how these elements together affect emotional perception. This study investigates the combined impact of film color and editing on emotion perception, utilizing both subjective behavioral scales and objective functional magnetic resonance imaging (fMRI) techniques. It employs two experiments with a two-factor design to assess the interactions between film color (colored and black-and-white) and film editing (fearful, neutral, and happy levels) on emotional perceptions. Under the direction of a professional filmmaker, a series of film sequences was created for six experimental conditions. In Experiment 1, 117 participants watched the film sequences and subjectively rated the emotional valence of the neutral face in the sequence, uncovering a significant interaction effect between film color and editing on the valence rating of the neutral face. In Experiment 2, 67 participants watched similar film sequences in an MRI scanner to analyze their brain activation patterns. Distinct activations were identified in regions including the insula, anterior cingulate cortices (ACC), and middle frontal gyrus, where a region-of-interest (ROI) analysis of the left ACC revealed an interaction effect on neural responses. These results underscore the integral role of color and editing in influencing viewers’ emotion perception using two types of measurements. This research provides novel insights into the behavioral and neural responses to filmmaking elements that underpin film reception and offers practical implications for filmmakers, encouraging a more holistic approach to considering color and editing to further enrich the audience’s emotional experiences at the pre-production stage of filmmaking.

Abstract Human mobility modelling has attracted scholarly attention from physics-based methods and social science explanatory approaches. However, there is limited knowledge of the nonlinear relationship of flows and distance in intercity mobility and regional differences in the nonlinear relationship. Focusing on China’s long-distance and large-scale mobility during the Spring Festival, this paper develops a framework to explain the nonlinear relationship. Using the Gradient Boosting Decision Tree (GBDT) model and Tencent Big Data, we find that there are three types of nonlinear relationships, namely plateau (almost zero distance decay parameter), drop (decreasing distance decay parameter) and rebound (increasing distance decay parameter after decreasing). The provincial differences also reveal that the nonlinear relationships depend on the domestic relative location and the intra-provincial urban system. This result shows that the cities in the coastal province enjoy a more inclusive spatial structure, which supports the migration from the periphery of the province. In contrast, the inland cities are concerned with embracing the migrants and settling them down.

Abstract Blockchain technology plays a significant role in new technology infrastructure and has a significant influence on artificial intelligence, big data, and 5 G, and its application has been extended to the Internet of Things, digital asset transactions, digital finance, and so on. In financial systems, it could improve the efficiency of data processing, reduce errors, and detect fraud. However, blockchain adoption could increase the stock price and induce manipulation opportunisms. Managers could also use this advantage to mask their performance and increase corporate default risk. Using the data of Chinese listed companies from 2001 to 2021, we investigate whether blockchain technology adoption could increase or decrease corporate default risk. Using the expected default risk model to estimate the risk, the results show that the default risk increases once the firm adopts blockchain technology, which indicates managerial opportunism behavior. The effect works in firms with CEO duality and higher power consolidation. And similar results are also shown in the dual-duty companies. The results are also robust in instrumental variable tests, difference-in-difference tests (DIDs), firm-fixed effect, placebo tests, and other robustness tests.

Abstract The paper develops a down-and-out call option to evaluate the equity of a life insurer. The COVID-19 pandemic challenges captured by the premature feature of the down-and-out call option are also identified as structural breaks incorporated into the contingent claim option. Hedging, shown by the guarantee cover ratio, reflects the insurer’s ability to meet policy commitments. Reinsurance, indicated by the risk retention ratio, distributes insurance risk between the insurer and reinsurer. The insurer engages in those practices aligned with Sustainable Development Goal 3 (SDG 3: good health and well-being). The main findings are as follows. The COVID-19 pandemic harms policyholder protection and deviates from SDG 3 due to financial instability. However, strategic hedging, reinsurance, and government capital injections enhance policy assurances, achieving SDG 3 by increasing payments to policyholders and improving financial stability. Moreover, the risk retention ratio increases during severe COVID-19 periods but decreases with more government capital injections, which can substitute for risk retention. Policy implications suggest that policymakers can mitigate crisis impacts on insurer capacity to fulfill commitments, thereby enhancing life insurance stability and well-being aligned with SDG 3.

Abstract In the digital age, the application of Artificial Intelligence (AI) has become an irreversible trend, with its potential in the field of education being particularly noteworthy. However, there are currently few AI education programs for children in Taiwan, and there is a lack of systematic teaching resources and methods, which poses a major challenge to the promotion of AI education. To address this challenge, this study designed a tailor-made AI curriculum for children in Taiwan, aimed at enhancing their foundational knowledge in the AI field and skills in using generative AI. This study was conducted in Taiwan, involving 30 elementary school students from grades 3 and 4, employing a single-group pre-test and post-test research design. Data were collected and analyzed through pre-and post-tests on AI knowledge quizzes and AI knowledge self-assessment, as well as the expert consensual assessment technique and the pupils’ attitude toward technology survey questionnaire. Research shows that students who participated in the AI course significantly improved their test scores on AI knowledge before and after the course. The students AI knowledge increased by 62.75%, demonstrating the course’s effectiveness and showing a positive attitude towards AI technology. Additionally, the student’s project outcomes demonstrated a high level of creativity. The students exhibited an enhanced interest and positive attitude towards learning AI, expressing a willingness to participate in more AI educational courses. This work provides valuable experience and guidance for the future integration of AI technology in children’s education, offering practical guidelines for teachers and researchers on how to effectively teach AI knowledge, as well as serving as a robust reference for educational policy makers in formulating strategies to promote AI education.

Abstract The role of venture capital in promoting entrepreneurship and funding innovation cannot be underestimated. However, it is important to acknowledge noteworthy concerns associated with collusive behavior in the venture capital process. “Guanxi” is a relatively intimate and closed social relationship, which can impact venture capital through trust and social obligations. Drawing on the theories of unethical pro-relational behavior and social networks, using data from GEM-listed companies supported by venture capital from 2009 to 2021, this research investigates the phenomenon of collusion behavior between venture capitalists and entrepreneurs, with a particular focus on the influence of “guanxi”. The research finds that the presence of “guanxi” between venture capitalists and entrepreneurs tends to facilitate collusive behavior. Specifically, “guanxi” tends to increase entrepreneurial self-interest behavior, and venture capitalists’ returns, infringe upon minority shareholders’ interests, and increase corporate operational risk. Moreover, the study further explores the moderator effect of equity incentives on such collusion behavior. This research not only enriches the theoretical framework of the relationship between “guanxi” and venture capital activities but also provides insight into the ethical implications associated with “guanxi”, contributing to the broader literature on social relationships and unethical behavior.

Abstract The present study aims to explore the influence of field cognitive style on the false memory of Chinese characters. Based on the related literature, this paper used Cognitive Style Figure Test (CSFT) to investigate the field cognitive style of college student and test the differences of field cognitive style in demographic variables. Using the DRM paradigm, with Chinese characters lists as experimental material. This study was to inspect whether Chinese semantic/tonetic association has any effect on false memory, and whether there is any interaction between field cognitive style and Chinese character component on it. The results showed that: (a) there were significant differences between male and female in the recognition rate of symbol types, with the recognition rate of tonetic symbol type characters being generally higher than that of semantic symbol type; (b) Chinese semantic/tonetic associations had an effect on false memory and gender has a significant difference in the recognition of critical-lures; (c) field cognitive style had no statistically significant difference in recognition rate on character component type and characters type (old characters, filler characters, and critical-lures); (d) individuals with different field cognitive styles differed significantly in the rate of misrecognition of critical-lures for semantic symbols.

Abstract Persistence of malaria parasites in asymptomatic hosts is crucial in areas of seasonally-interrupted transmission, where P. falciparum bridges wet seasons months apart. During the dry season, infected erythrocytes exhibit extended circulation with reduced cytoadherence, increasing the risk of splenic clearance of infected cells and hindering parasitaemia increase. However, what determines parasite persistence for long periods of time remains unknown. Here, we investigated whether seasonality affects plasma composition so that P. falciparum can detect and adjust to changing serological cues; or if alternatively, parasite infection length dictates clinical presentation and persistency. Data from Malian children exposed to alternating ~6-month wet and dry seasons show that plasma composition is unrelated to time of year in non-infected children, and that carrying P. falciparum only minimally affects plasma constitution in asymptomatic hosts. Parasites persisting in the blood of asymptomatic children from the dry into the ensuing wet season rarely if ever appeared to cause malaria in their hosts as seasons changed. In vitro culture in the presence of plasma collected in the dry or the wet seasons did not affect parasite development, replication or host-cell remodelling. The absence of a parasite-encoded sensing mechanism was further supported by the observation of similar features in P. falciparum persisting asymptomatically in the dry season and parasites in age- and sex-matched asymptomatic children in the wet season. Conversely, we show that P. falciparum clones transmitted early in the wet season had lower chance of surviving until the end of the following dry season, contrasting with a higher likelihood of survival of clones transmitted towards the end of the wet season, allowing for the re-initiation of transmission. We propose that the decreased virulence observed in persisting parasites during the dry season is not due to the parasites sensing ability, nor is it linked to a decreased capacity for parasite replication but rather a consequence decreased cytoadhesion associated with infection length.

Abstract Brain injury is the leading cause of mortality among patients who survive cardiac arrest (CA). Clinical studies have shown that the presence of post-CA hypoxic hepatitis or pre-CA liver disease is associated with increased mortality and inferior neurological recovery. In our in vivo global cerebral ischemia model, we observed a larger infarct area, elevated tissue injury scores, and increased intravascular CD45+ cell adhesion in reperfused brains with simultaneous hepatic ischemia than in those without it. In the ex vivo brain normothermic machine perfusion (NMP) model, we demonstrated that addition of a functioning liver to the brain NMP circuit significantly reduced post-CA brain injury, increased neuronal viability, and improved electrocortical activity. Furthermore, significant alterations were observed in both the transcriptome and metabolome in the presence or absence of hepatic ischemia. Our study highlights the crucial role of the liver in the pathogenesis of post-CA brain injury.

Abstract Promoting teachers’ long-term professional growth is a critical problem in teacher education. Professional learning communities have a long-term, positive impact on teacher development, while teacher resilience gives drive for long-term improvement. However, little research indicates how professional groups indirectly affect teacher resilience through their identity, which has consequences for long-term teacher development. After adjusting for demographic characteristics, a recent survey of 2815 primary and secondary school teachers in East China discovered that professional learning communities strongly predict the formation of teacher resilience. This study explores the relationship between professional learning community and teacher resilience by establishing a multi-mediating model, and confirms the mediating role of each dimension of teacher identity. Based on these results, facilitating sustainable professional development requires constructing strong professional learning communities, nurturing teacher identity, and enhancing positive emotions and resilience. Further research should explore how specific activities within communities and forms of teacher support develop resilience over time while accounting for contextual factors. Investigating mechanisms underlying the relationships between communities, identity, emotions, and sustained growth can inform policies and programs aiming to promote long-lasting teacher development.

Abstract Using generalizability (G-) theory and qualitative feedback analysis, this study evaluated the role of ChatGPT in enhancing English-as-a-foreign-language (EFL) writing assessments in classroom settings. The primary objectives were to assess the reliability of the holistic scores assigned to EFL essays by ChatGPT versions 3.5 and 4 compared to college English teachers and to evaluate the relevance of the qualitative feedback provided by these versions of ChatGPT. The study analyzed 30 College English Test Band 4 (CET-4) essays written by non-English majors at a university in Beijing, China. ChatGPT versions 3.5 and 4, along with four college English teachers, served as raters. They scored the essays holistically following the CET-4 scoring rubric and also provided qualitative feedback on the language, content, and organization of these essays. The G-theory analysis revealed that the scoring reliability of ChatGPT3.5 was consistently lower than that of the teacher raters; however, ChatGPT4 demonstrated consistently higher reliability coefficients than the teachers. The qualitative feedback analysis indicated that both ChatGPT3.5 and 4 consistently provided more relevant feedback on the EFL essays than the teacher raters. Furthermore, ChatGPT versions 3.5 and 4 were equally relevant across the language, content, and organization aspects of the essays, whereas the teacher raters generally focused more on language but provided less relevant feedback on content and organization. Consequently, ChatGPT versions 3.5 and 4 could be useful AI tools for enhancing EFL writing assessments in classroom settings. The implications of adopting ChatGPT for classroom writing assessments are discussed.

Abstract National innovation capability (NIC) is an important manifestation of economic development quality and international competitiveness. Previous studies focus mainly on the static impact of factors in the national innovation system on NIC in a given year. Research is still lacking on whether these factors have continuing, stable impacts on NIC in different economies. To fill this literature gap, this study uses fuzzy set qualitative comparative analysis (fsQCA) to conduct cross-economy and cross-year comparisons and discusses how the five elements of the NIS jointly affected the NIC of different economies from 2011 to 2022. The results indicate that the necessity consistency of infrastructure for NIC shows a temporal trend. There are four paths to generating high NIC in high-income economies, but only two such paths for upper middle-income economies. The path combining human capital and research, market sophistication, and business sophistication can drive both types of economies to generate high NIC. The research results have improved the transparency of innovation paths and provided a reference for different economies to achieve sustainable development.

Abstract In recent years, the increase in child problem behaviours has become a significant public health concern. It is crucial to understand the complex dynamics between parental co-parenting, parenting competence, and child problem behaviours to develop effective interventions. This study explored the intricate relationship between parental co-parenting, parenting sense of competence, and child problem behaviours in a sample of 407 parent-child pairs from Shanghai, China. Findings indicated that neither maternal nor paternal perceived co-parenting significantly predicts child problem behaviours directly. However, maternal parenting sense of competence emerges as a significant mediator between maternal perceived co-parenting (both supportive and non-supportive) and child problem behaviours. This highlights the pivotal role of mothers as primary caregivers in shaping parenting dynamics and child outcomes. Conversely, paternal parenting sense of competence does not mediate the relationship between paternal perceived co-parenting and child behaviours, suggesting a nuanced dynamic within paternal care-giving roles. The study underscores theoretical contributions, validating the theory of inconsistent compensation effect and emphasizing the primary caregiver effect within the Chinese family context.

Abstract Economies-of-scale have always been a significant concern, but previous theoretical studies have primarily focused on the traditional manufacturing industry. Consequently, their findings are not directly applicable to the tertiary sector, particularly the hospitality service industry. The hospitality service operates in a high-risk environment and is susceptible to market exits. Therefore, it becomes even more crucial to effectively leverage economies of scale for improving survival rates and long-term operations. This study aims to explore the effectiveness of economies of scale theory in the hospitality industry by examining how sharing accommodation’s economies-of-scale impact personalized and professionalized homestay businesses’ survival. To achieve this objective, we analyze a panel dataset comprising 551,605 properties located in New York City, Los Angeles, Chicago, and Austin using panel survival analysis techniques such as the Cox model and the exponential model. The findings indicate that economies-of-scale can confer short-term survival advantages to professional homestay businesses in comparison with personalized ones. However, in the long run, the social benefits of personalized homestay businesses surpass the impacts of economies-of-scale, thereby enabling them to achieve better sustainability than professional homestay businesses. The likelihood of survival for professional homestay businesses increases with a greater number of listings in operation, referred to as the advantage of economies-of-scale on professionalization; conversely, this is not true for personalized homestay businesses. Moreover, effective host–guest communication both facilitates the attainment of benefits for personalized businesses and amplifies its impact on professionalized enterprises; high-quality products offered by personalized hosts can derive more advantages from scales compared to low-quality products, while superhost-certified professionalized hosts experience less business benefit than uncertificated hosts. This study is one of the pioneering efforts to investigate how economies-of-scale can contribute to the professionalization and personalization of homestay properties, thereby enhancing their business survival. It significantly contributes to the existing literature on hospitality business survival and expands upon the economies-of-scale theory by elucidating its advantages and potential pitfalls in relation to homestay businesses.

Abstract This study explores tourism implicit conflict and its spatial dynamics in rural China. It proposes that residents in different spatial structures within tourism communities perceive implicit conflicts differently. Data were collected through public participatory geographic information system (PPGIS) mapping and semi-structured interviews. The findings reveal that conflict perceptions vary by residential structures. Residents in core and peripheral areas experienced heightened economic and cultural conflicts. In contrast, those in expanded areas were more concerned with issues of tourism governance. The study also highlights two key spatial aspects of perceived conflict: internality, the overlap within their residential areas, and significant externality, which spreads across the entire ancient town. From a combined spatial and psychological perspective, this study proposes the concept of spatial relative deprivation to explain resident’s perceived tourism implicit conflict. This study affirms that qualitative-spatial analysis sheds light on socio-cultural phenomena, contributing to a more nuanced understanding of the underlying conflict mechanisms in a spatially explicit manner. The findings suggest that tourism planning should consider the intrinsic and micro-values of communities.

Abstract This study examines the impact of geopolitical risk on energy transition, focusing on the moderating roles of environmental regulations and green innovation within OECD countries. By employing a multivariate linear and nonlinear regression model, we identify a substantial positive effect of geopolitical risk on energy transition. Our analysis indicates that stronger environmental regulations and advancements in green innovation significantly amplify this effect. Through threshold effect bootstrap sampling tests, we detect a nonlinear relationship between geopolitical risk and energy transition at varying levels of environmental regulation and green innovation. We also explore lag effects, revealing that the influence of geopolitical risk on energy transition grows stronger over time. The inclusion of interaction terms in our analysis further clarifies the moderating influences of environmental regulation and green innovation. Utilizing a range of geopolitical risk indicators and regression methods, our findings are robust, consistently highlighting the proactive role of geopolitical risk in fostering energy transition. These insights highlight the importance of integrated strategies that harness environmental regulations and technological innovation to facilitate a resilient and efficient energy transition in the face of challenges posed by geopolitical uncertainties.

Abstract The relationship between work and family is essential to sustainability, affecting the fertility intention and fertility behavior of childbearing age. This study aims to explore the following research questions to fill the research gaps: (1) Can WFB improve individuals’ fertility intentions (FI)? (2) How does DW affect individuals’ FI? Drawing on the job demands-resources theory (JD-R) and life history theory, we have developed a theoretical framework of work–family balance (WFB), decent work (DW), fertility intention (FI), organizational support (OS), and family support (FS). Data was collected through a questionnaire in China, and hypotheses were tested. We find that WFB significantly and positively affects DW; DW significantly positively affects FI; WFB significantly influences FI, and DW is a mediator between WFB and FI. However, OS and FS have no significant moderating effects on WFB and DW. The theoretical implications of this study are that it preliminarily explores the spillover effects of DW on family life, enriching the research on DW. The findings can be applied to formulating government policies on fertility support, human resource management practices, and personal work–family development.

Abstract After the implementation of Poverty Alleviation Relocation (PAR), the social integration of migrants has gradually received attention. While studies recognize the factors affecting migrants’ social integration such as human capital, social capital, and policies are multiple and co-influential, the role of community support in simultaneously influencing migrants’ social integration has been largely overlooked. This paper addresses this gap by introducing community support into the social integration framework, taking China’s PAR that cause complex spatial, economic, and social changes as the object of study. We evaluated the social integration of Poverty Alleviation Migrants (PAMs) in five Ex-situ Poverty Alleviation Relocation (ESPAR) communities in the southwestern province of China across four dimensions: psychological identity, economic integration, communicative integration, and cultural acceptance. Utilizing a multiple linear regression model, we analyzed influencing factors on social integration. Results indicate that overall social integration of PAMs is at a medium-high level, with psychological identity scoring the highest. Notably, community support significantly influences the social integration of PAMs, particularly in terms of psychological identity. In conclusion, we highlight the imperative of enhancing the spatial environment of ESPAR communities to facilitate the better integration of PAMs into society.

Abstract The centrality of job satisfaction in fostering the stability and progression of the teaching cadre and in underpinning the effective operation of educational institutions is paramount. Drawing from motivation theory and the Job Demands-Resources model, this research delves into the influence of psychological empowerment on the job satisfaction of 533 preschool educators in China, employing the Psychological Empowerment Questionnaire, the Occupational Identity Questionnaire, and the Job Satisfaction Scale. The inquiry probes the intermediary function of occupational identity in the nexus between psychological empowerment and job satisfaction within the cohort of preschool teachers. The findings underscore that psychological empowerment substantially foretells heightened job satisfaction in preschool educators, and concurrently, occupational identity serves as a partial mediator in the association between psychological empowerment and job satisfaction. Augmenting levels of psychological empowerment and occupational identity among preschool teachers is a strategic avenue for fortifying their holistic contentment in their professional roles, thereby contributing indispensably to the fortification of a robust teaching workforce in kindergarten establishments.

Abstract Venture capital (VC) significantly contributes to the development of regional economies and fosters innovation. Analyzing the factors that influence VC investments holds key importance. This study employs two methods to ascertain the relative significance of different factors at the city level: the Lindeman, Merenda, and Gold (LMG) approach in multiple linear regression (MLR) and variable importance in random forest (RF) machine learning. The findings reveal that several factors, including economy, finance, innovation, location, and policy, significantly influence VC investments. Both the MLR and RF models highlight the preeminence of economic and financial variables, followed closely by the city’s potential for innovation. Moreover, spatial heterogeneity exists in the importance of these variables. In the economically developed and densely populated eastern regions of China, the financial environment of cities emerges as the most crucial, whereas in the central and western regions, the economy and innovation, respectively, take precedence. This research contributes to a deeper understanding of the distribution of VC investments and offers valuable insights for the development of regional policies.

Abstract With a national research-oriented atmosphere in tertiary institutions, many Chinese EFL teachers rise to the challenge by working collaboratively in professional communities, leading to increasing attention to collective agency. However, how their collective agency manifests remains underrepresented. Using a qualitative inductive method, this study investigated the manifestations of the collective agency among six university EFL teachers in a research institute of a Chinese university from a social cognitive perspective. It was found that the teachers’ collective agency manifested as their ability to form a collective mode of practice that aligned their professional goals and paths, to foster a dual-natured social network that supported professional development and to maintain a shared belief in group efficacy that enhanced collaboration and collective identity. The findings point to the importance of understanding collective agency as an emergent and contextualized phenomenon filled with complexities and nuances. Theoretically, the study enriches the understanding of the dynamism and complexities of teachers’ collective agency in a Chinese context and broadens the research perspectives of teacher collaboration. It also has practical implications for teachers and administrators who are seeking ways to cope with pressure in an era of research excellence.

Abstract The impact of attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) traits on suicidal thoughts and behaviors (STBs) remains inadequately explored. Hence, the present study aims to delve deeper into these intricate issues, contributing to a better understanding of these complex challenges among Chinese youth. The data of 90,882 participants was collected from 63 Chinese universities and colleges in Jilin, China. We aim to explore the risks of STBs on ASD, ADHD, and co-occurrence of ASD + ADHD by using the Autism Spectrum Quotient-10 items (AQ-10) and Adult ADHD Self Report Scale (ASRS). Propensity score matching (PSM) was implemented to balance demographical variables across the four groups. Binary logistic regression was then conducted to further analyze and compare suicide risk across the four groups, also accounting for sex differences. Suicide risks were significantly higher in the ADHD (OR = 1.24, p

Abstract China has experienced both ultra-low fertility and moderate aging in recent years, both of which pose serious challenges to the country’s development. Previous studies have shown that social capital is one of the most important factors that influences fertility intentions, but so far empirical research on the relationship between social capital and fertility intentions is very limited. Therefore, this study aims to explore the impact of social capital on fertility intentions and its underlying mechanisms by combining offline and online social capital. Based on data from the Chinese General Social Survey, the fertility intentions of 7,518 respondents aged 18–60 years were analyzed and broken down by sex, region, and age. The marginal effects and mechanisms of offline and online capital on fertility intentions were explored using an ordered probit (oprobit) model, which revealed that individuals’ fertility intentions are positively influenced by offline social capital but negatively influenced by online social capital. The role of social capital in shaping individuals’ fertility intentions also varies by gender, region, and age. Women, eastern region groups, and those aged 30–60 years are more influenced by offline social capital, and their intentions become stronger as offline social capital accumulates. However, online social capital negatively affects the fertility intentions of women, Midwesterners, and 18–29 year olds. Furthermore, online and offline social capital mainly influence individuals’ fertility intentions by affecting their perceptions of pensions, filial piety, and “social justice”. Our findings suggest that increasing the value that individuals place on social capital is crucial for improving fertility intentions in China.

Abstract The present study tested the mediating role of problematic TikTok use in the relationship between academic stress and academic procrastination, as well as any gender differences. A total of 590 Chinese university students, aged between 17 and 24 years, completed questionnaires measuring their levels of academic stress and academic procrastination at Time 1 (T1), reported on problematic TikTok use at Time 2 (T2) six months later, and academic procrastination at Time 3 (T3) another six months later, while also providing demographic information. The results revealed significant positive associations between T1 academic stress, T1 academic procrastination, T2 problematic TikTok use, and T3 academic procrastination. Moreover, after controlling for age, urban-rural background, family income, TikTok use time, and T1 academic procrastination, T2 problematic TikTok use was found to mediate the longitudinal relationship between T1 academic stress and T3 academic procrastination. Furthermore, gender played a significant moderating role, with the mediating effect being observed only among male university students. The present study is one of the first to explore how problematic TikTok use and gender contribute to the longitudinal effects of academic stress on academic procrastination. The results offer valuable insights into strategies for preventing and managing problematic TikTok use and academic procrastination among university students.

Abstract Chemotherapy induced ovarian failure and infertility is an important concern in female cancer patients of reproductive age or younger, and non-invasive, pharmacological approaches to maintain ovarian function are urgently needed. Given the role of reduced nicotinamide adenine dinucleotide phosphate (NADPH) as an essential cofactor for drug detoxification, we sought to test whether boosting the NAD(P)+ metabolome could protect ovarian function. We show that pharmacological or transgenic strategies to replenish the NAD+ metabolome ameliorates chemotherapy induced female infertility in mice, as measured by oocyte yield, follicle health, and functional breeding trials. Importantly, treatment of a triple-negative breast cancer mouse model with the NAD+ precursor nicotinamide mononucleotide (NMN) reduced tumour growth and did not impair the efficacy of chemotherapy drugs in vivo or in diverse cancer cell lines. Overall, these findings raise the possibility that NAD+ precursors could be a non-invasive strategy for maintaining ovarian function in cancer patients, with potential benefits in cancer therapy.

Abstract Genome-scale metabolic models (GEMs) can facilitate metabolism-focused multi-omics integrative analysis. Since Yeast8, the yeast-GEM of Saccharomyces cerevisiae, published in 2019, has been continuously updated by the community. This has increased the quality and scope of the model, culminating now in Yeast9. To evaluate its predictive performance, we generated 163 condition-specific GEMs constrained by single-cell transcriptomics from osmotic pressure or reference conditions. Comparative flux analysis showed that yeast adapting to high osmotic pressure benefits from upregulating fluxes through central carbon metabolism. Furthermore, combining Yeast9 with proteomics revealed metabolic rewiring underlying its preference for nitrogen sources. Lastly, we created strain-specific GEMs (ssGEMs) constrained by transcriptomics for 1229 mutant strains. Well able to predict the strains’ growth rates, fluxomics from those large-scale ssGEMs outperformed transcriptomics in predicting functional categories for all studied genes in machine learning models. Based on those findings we anticipate that Yeast9 will continue to empower systems biology studies of yeast metabolism.

Abstract We have developed and validated a highly specific, versatile antibody to the extracellular domain of human LGR5 (α-LGR5). α-LGR5 detects LGR5 overexpression in >90% of colorectal cancer (CRC), hepatocellular carcinoma (HCC) and pre-B-ALL tumour cells and was used to generate an Antibody-Drug Conjugate (α-LGR5-ADC), Bispecific T-cell Engager (α-LGR5-BiTE) and Chimeric Antigen Receptor (α-LGR5-CAR). α-LGR5-ADC was the most effective modality for targeting LGR5+ cancer cells in vitro and demonstrated potent anti-tumour efficacy in a murine model of human NALM6 pre-B-ALL driving tumour attrition to less than 1% of control treatment. α-LGR5-BiTE treatment was less effective in the pre-B-ALL cancer model yet promoted a twofold reduction in tumour burden. α-LGR5-CAR-T cells also showed specific and potent LGR5+ cancer cell killing in vitro and effective tumour targeting with a fourfold decrease in pre-B-ALL tumour burden relative to controls. Taken together, we show that α-LGR5 can not only be used as a research tool and a biomarker but also provides a versatile building block for a highly effective immune therapeutic portfolio targeting a range of LGR5-expressing cancer cells.

Abstract Collecting duct carcinoma (CDC) is an aggressive rare subtype of kidney cancer with unmet clinical needs. Little is known about its underlying molecular alterations and etiology, primarily due to its rarity, and lack of preclinical models. This study aims to comprehensively characterize molecular alterations in CDC and identify its therapeutic vulnerabilities. Through whole-exome and transcriptome sequencing, we identified KRAS hotspot mutations (G12A/D/V) in 3/13 (23%) of the patients, in addition to known TP53, NF2 mutations. 3/13 (23%) patients carried a mutational signature (SBS22) caused by aristolochic acid (AA) exposures, known to be more prevalent in Asia, highlighting a geologically specific disease etiology. We further discovered that cell cycle-related pathways were the most predominantly dysregulated pathways. Our drug screening with our newly established CDC preclinical models identified a CDK9 inhibitor LDC000067 that specifically inhibited CDC tumor growth and prolonged survival. Our study not only improved our understanding of oncogenic molecular alterations of Asian CDC, but also identified cell-cycle machinery as a therapeutic vulnerability, laying the foundation for clinical trials to treat patients with such aggressive cancer.

Abstract The explosive growth and attractive features of mobile short videos (MSVs) have made it become an effective tool for disseminating health-related information. This study aims to examine the potential informational and technical factors of MSVs, which contribute to the persuasive effects on people’s decision-making process toward HPV vaccination. An experiment with a 2 (information quality: high vs. low) × 2 (source credibility: high vs. low) × 2 (media richness: high vs. low) between-subject factorial design was conducted among 248 Chinese female students. Findings revealed significant persuasive impacts of three factors, i.e., information quality, source credibility, and media richness, on participants’ HPV vaccination intent, via the mediation effect of attitude toward HPV vaccine information. Significant two-way interaction effects indicated that the persuasive effects of media richness varied across different levels of information quality and source credibility. This research not only applied the theoretical lens of the elaboration likelihood model and media richness theory to understand the influencing mechanism within short-form videos but also offered valuable guidelines regarding how professionals best adopt emerging media to maximize health outcomes.

Abstract The importance of experts in the communication of scientific knowledge cannot be ignored, however, the crisis of trust in experts persists and is widening on social media in China. In this study, nine cases related to experts’ communication of scientific knowledge on Chinese social media Weibo during the period of 11 November 2022 to 22 January 2023 were selected based on the principles of high relevance, high discussion, and high visibility, and public comments on key post under the case were clustered and compared through data mining methods to understand what aspects of the public questioned the experts. The study found that the crisis of trust in experts on social media was the result of the combined effect of the experts, the media, and the public. Conflicting knowledge in expert systems, the perceived common-sense character of communicated knowledge, the lack of rigor and data-supported knowledge, the blurring of the boundaries between experts and administration and between experts and capital, and the dominance of instrumental rationality for experts could all affect public trust in experts. The media’s conscious or unconscious artistic processing of knowledge communicated by experts might mislead the public. The irrational emotion and populist tendencies of the public can amplify feelings of distrust towards experts. This study provides a theoretical and factual basis for understanding the mechanisms of the public’s behavior after receiving knowledge communicated by experts and for enhancing the effectiveness of science communication on social media.

Abstract The catering industry plays an essential role in providing life services. Understanding its spatial patterns offers insights into the economic, cultural and spiritual image of a society. Especially in urban settings, the catering industry is often considered a key element for improving the competitiveness of cities. With rapid urbanization and economic growth in China, the catering industry has become the main driving force to stimulate China’s service sectors. In this study, we conducted a comprehensive spatial analysis to explore the distribution patterns by calculating kernel density and applying the geographically weighted regression (GWR) model with 4.49 million restaurants across 336 cities in China in 2020. The restaurants were categorized into four types: Chinese restaurants (CRs), Western restaurants (WRs), fast-food restaurants (FFRs), and dessert and drink restaurants (DDRs). We incorporated a diverse set of socio-economic indicators to explore potential causal influences, including population size and density, GDP, etc. Our study revealed a gradual decrease in restaurant density from southeast to northwest China, with high density observed in the Pearl River Economic Delta, Yangtze River Economic Delta, Chongqing, and Chengdu regions. In terms of the potential influencing factors, we observed that in west and southwest regions, density appeared to be more affected by GDP per unit area, total tourism revenue, disposable income per capita of urban residents, and total retail sales of social consumption. While in northeast areas, restaurant density was more affected by total retail sales of social consumption, GDP per unit area, number of urban population, and the proportion of tertiary industry in GDP. These insights serve as a direct scientific foundation for informing the strategic planning of different types of restaurants at municipal, provincial, and regional levels.

Abstract Buried pipeline systems are vulnerable to joint damage in earthquakes. Previous studies have shown that bellows joints are effective in increasing deformation capacity and reducing the axial force of the main pipeline. However, the effectiveness of bellows joints in enhancing the deformation capacity of the pipelines is affected by the location of the crossing fault and the soil at the site. This paper constructs and validates a finite element model of a buried steel pipeline connected by a bellows joint using ABAQUS to investigate this issue. The effects of fault location, soil properties, and internal pressure on the bellows joint connected pipelines were analyzed using a finite element model. The results indicate that the bellows joints exhibit the best energy dissipation and deformation enhancement when the fault passes directly through the joints. Bellows joints in soft soil are better at dissipating energy, reducing pipe deformation, and mitigating pipe damage compared to those in hard soils. The internal pressure is helpful to increase the mechanical properties of the pipelines. The findings can provide some guidance for pipeline design and mitigation strategies for ensuring the reliability and safety of buried pipeline systems in earthquake-prone areas.

Abstract The impact of digitalization on the high-quality development of “technology-sparse” but “labor-intensive” cultural, sports, and tourism enterprises may not follow a linear path. Therefore, there is an urgent need to explore the mechanism by which digitalization contributes to the integrated high-quality development of enterprises from the perspective of resources and capabilities. The majority of studies focus on the theoretical realm, while challenges in acquiring crucial data indicators constrain the advancement of empirical inquiries. This study creates a lexicon of digitized features encompassing strategic, technical, and application layers within cultural, sports, and tourism enterprises. The MD&A texts from annual reports were processed using the TF-IDF algorithm, which is based on machine learning, to assess the level of digitization. Additionally, integration development was incorporated into the evaluation system for high-quality development of cultural, sports, and tourism enterprises via social network analysis. In terms of theoretical contributions, enterprise search and reorganization capabilities were included within the scope of core enterprise capabilities. Furthermore, the study elucidated the roles of human capital and enterprise innovation in the interplay between digitalization and high-quality development, drawing upon the resource-based view and core capabilities theory. Finally, we empirically examined panel data from 116 listed cultural, sports, and tourism companies in Chinese A-share markets from 2010 to 2020. The findings reveal the following: (1) There is an inverted U-shaped association between digitalization and high-quality development, initially promoting then hindering progress, with a persistent pattern over time and robustness against instrumental variable regression and endogeneity tests. Additionally, the majority of cultural, sports, and tourism enterprises fall within a moderate range, indicating a positive impact on high-quality development. (2) Human capital and enterprise innovation are mediators of the inverted U-shaped relationship between digitalization and high-quality development. (3) The influence of digitalization on high-quality development significantly varies depending on the enterprise’s geographical location, life cycle, and risk tolerance. The study reveals the digitalization journey within cultural, sports, and tourism enterprises, offering theoretical insights for fostering collaborative high-quality development within the industry amid digitalization.

Abstract The intersection of geopolitics and energy security is a critical area of study that has garnered increasing interest from scholars around the globe. This paper employs bibliometric theory and methodologies to explore the research trajectory concerning the influence of geopolitical dynamics on energy security. Our findings, derived from both quantitative and qualitative analysis of relevant literature, reveal several key insights. Firstly, there is a notable upward trend in publications on this topic, reflecting a widespread recognition of the intricate link between geopolitics and energy security. This growing body of research aligns with the exponential growth law observed in scientific literature, showcasing a novel pattern of geographical distribution centered around energy issues. Secondly, an examination of collaboration networks at the national, institutional, and individual levels identifies China as the leading country in terms of research partnerships, positioning Chinese institutions and scholars at the forefront of this field. Lastly, our analysis delineates the research evolution within this domain through three distinct phases—pre-, mid-, and post-development stages. It highlights the shifting focus of global researchers towards the energy transition process, energy policy formulation, the stability of energy markets, and the environmental impacts of energy production and consumption. This study not only maps the current landscape of research on geopolitics and energy security but also signals the critical areas of interest and collaboration that shape this vital field of inquiry.

Abstract Encouraging subject teachers to transition to integrated STEM education is an important measure to address the shortage of STEM teachers. However, there is limited research available on the process and characteristics of STEM teacher identity transformation. The study used a hybrid method of Grounded Theory and Epistemic Network Analysis to analyze interview texts of 10 STEM teachers from Zhejiang Province, China. Research has shown that subject teachers go through three stages when transitioning to integrated STEM education: imitation, exploration, and innovation. Throughout each stage, the teacher’s identity changes as they gain a better understanding of integrated STEM education, curriculum and project design, practical methods, and teaching reflection. The study has identified three paths for the transformation of STEM teacher identity, which are influenced by factors such as gender, professional background, school type, and location. Additionally, the study proposes strategies that could encourage subject teachers to transition toward STEM education.

Abstract In recent years, museums have become valuable venues for students to develop career awareness outside of school. However, optimizing the educational potential of museums and improving learners’ outcomes presents a significant challenge in museum learning design. This study integrates three main game elements—goals, stories, and role-playing—into museum visits to design a Gamified Learning Activity (GLA). To verify the effectiveness of the GLA, we conducted a quasi-experiment with 66 elementary school students at the Handicraft Museum. Using a mixed-methods approach with convergent parallel design, we collected quantitative data from knowledge tests and qualitative data from DAST (Draw-a-Scientist-Test) and interviews for a comprehensive analysis. The results showed that learners who participated in the GLA paid more attention to the details of the handicrafts, appreciated the craftsmen more, and eliminated stereotypes about the age of craftsmen. This indicates that the GLA not only enhances learners’ acquisition of museum knowledge but also has a profound impact on their non-cognitive aspects, such as career awareness.