With the accelerating global trend of aging, the incidence of acute kidney injury (AKI) among elderly patients with comorbidities is increasing steadily. For elderly patients, AKI not only accelerates the progression of comorbidities, thereby increasing the difficulty of clinical diagnosis and treatment, but also significantly reduces patients' survival rates and quality of life. Therefore, it is of great importance to explore more optimized strategies for AKI management. In recent years, smart healthcare has shown broad application prospects in the management of AKI, covering early risk warning, accurate diagnosis and classification, individualized treatment decision-making, and rehabilitation management. This article systematically sorts out and reviews the application of smart healthcare in AKI management in elderly patients with comorbidities, with a focus on summarizing the advantages and shortcomings of existing technologies, aiming to provide insights into future research and clinical practice in the intelligent management of AKI and promote the transformation of AKI management strategies from disease treatment to proactive health maintenance.

ABSTRACT In the volatile, uncertain, complex, and ambiguous (VUCA) era, traditional incremental innovation struggles to overcome the constraints of technological path dependence and low-end lock-in. In contrast, radical innovation, characterised by profound transformation and disruption of existing technologies and products, has emerged as a critical mechanism for addressing technological bottlenecks and achieving leapfrogging strategies. Grounded in organisational learning theory, this study examines the relationship between organisational unlearning and radical innovation, with knowledge creation as a mediating variable and strategic flexibility as a moderating variable. The findings reveal that organisational unlearning significantly enhances radical innovation. Specifically, unlearning facilitates radical innovation through the mediating mechanism of knowledge creation, while strategic flexibility shapes the boundary conditions of this relationship. This study introduces an internal cognitive perspective to elucidate the micro-level mechanisms linking unlearning and innovation, thereby advancing research in organisational learning and innovation management. At the same time, it offers practical implications by highlighting how firms can refine unlearning–learning mechanisms, cultivate unlearning–learning organisations, optimise knowledge-creation environments, and enhance strategic flexibility to navigate an ever-changing business landscape.

To address calls for multiparadigmatic approaches to critical cross-cultural management (CCM) research, this paper engages with ontological, epistemological, and methodological possibilities from transnational migration studies (TMS). Guided by a mobility lens and adding to existing critical approaches within CCM scholarship that have critiqued Western epistemologies and static cultural models for representation, this paper aims to expand critically-oriented paradigms for research related to ‘people on the move’ and migration experiences. As the ontological premise of TMS, the mobility lens focuses on movement, including experiences of inequality, dispossession, and displacement, and its implications for the formation of social groups that defy categorization and reification through references to national borders. By expanding upon three key concepts from TMS, transnational social fields, scalar notions of being and belonging, and historical conjunctures, the paper contributes to ongoing conversations in critical CCM about ethics and representation beyond methodological nationalism , rethinking the unit of analysis through encounters , and extending the ‘field’ in fieldwork . Building on these potential contributions, the paper engages in three epistemic reflections on ‘ethics on the move’ , representation and surveillance , and interdisciplinarity as emergent considerations for future critical qualitative research on people, mobility, culture, and global work in the broader field of management and organization studies (MOS).

The powerful electromagnetic regulation capability of metasurfaces offers promising strategies for infrared camouflage technology. However, it is difficult to realize dynamic thermal emission control using conventional micro/nanostructures and radiative materials, greatly limiting the camouflage performance in some complicated scenarios. In this work, two types of phase-change material (VO2 and Sb2S3) are incorporated into the design of switchable thermal emitter, which can switch between infrared camouflage and radiative cooling mode. As the temperature rise above 68 °C, the phase transition of VO2 first occurs to enable radiative cooling property (ɛ8–14 μm = 0.64) of the emitter, while its infrared camouflage property can be subsequently activated by continuous heating to the phase transition temperature of Sb2S3 at 270 °C. The symmetric metal–insulator–metal structure ensures high tolerance to both angle and polarization, while the low-loss Sb2S3 layer is expected to maintain the structural integrity through multiple reconfigurations. This study offers a versatile approach to realize dynamic spectral modulation, enabling integrated infrared camouflage and radiative cooling functionalities for future research and applications in camouflage technology and passive thermal management.

MicroRNAs as biomarkers and therapeutic targets in pterygia: A systematic review with quantitative synthesis.

Complex socio-ecological issues involving climate change and fresh water management highlight the importance of trust in interactions amongst humans in highly variable landscapes subject to multiple pressures. This study investigated the role of trust in establishing and maintaining relationships between individuals in research teams that included private landholders in southeast Australia as well as researchers. Using social constructivist grounded theory methodology, interviews with members of a university research institute, a government agency and a farmer group in Australia’s Murray-Darling Basin were visualized using the Trust/Distrust Matrix. Findings emphasized the importance and differing impacts of trust amongst individuals, and within and between organizations. Interviewees highlighted the impacts of time and location on trust and relationships for effective natural resource management (NRM) research projects on private lands. The authors examined the implications for research managers and multidisciplinary groups seeking to influence NRM in highly contested socio-ecological spaces on agricultural lands.

Tree species identification and mapping is crucial for forest management, biodiversity conservation, and ecological research. Bark images can be captured easily from the ground-level and can provide large amount of information about the tree species and its health. Yet, existing datasets for tree bark images are often limited in scope, lacking diversity in species representation and temporal attributes. To address these limitations, we present BarkVisionAI, a comprehensive dataset of 156001 tree bark images for 13 species collected from diverse forest types across India. Each image is labeled with location, species name, device attributes, and timestamp, providing a robust foundation for studying species identification and the variability of bark characteristics. We are providing detailed metadata information about each image, encouraging its use in ecological research, machine learning model training, and environmental monitoring. Benchmarking experiments using standard image classification models demonstrate the dataset's utility and effectiveness, highlighting its potential as a valuable resource for developing reliable, real-world applications in automated tree species identification and environmental change monitoring.

Abstract Background Despite growing attention to wildland firefighter safety, little is known about the full scope of environmental health hazards experienced occupationally. Previous research has documented exposures to carcinogens and combustion byproducts from smoke, dust, ash, engine exhaust, ignition devices, and location-specific chemical and radiological hazards. With growing attention to firefighters’ health outcomes, more research is needed on the environmental health hazards that they experience routinely and non-routinely. Qualitative research is well suited for exploratory investigations of environmental hazards. This study draws on a long-term ethnographic research project with federal wildland firefighters in Oregon to identify the environmental health hazards that wildland firefighters experience. I took detailed fieldnotes during participant observation working as a wildland firefighter with federal engine and handcrews. I also shadowed an incident management team, attended relevant meetings and trainings, and conducted 22 semi-structured interviews. I analyzed all data in NVivo, a computer program for coding qualitative data. Results Wildland firefighters were aware of commonly identified hazards of their work, including smoke exposure, heat, and “human factors” such as fatigue and diet. Firefighters experience additional hazards that are rarely discussed. Routine but generally unacknowledged hazards include non-vegetation smoke, dust, chemicals in gear and equipment, and fuels and exhaust. Incident- and location-specific hazards include food and water quality concerns, hazards in government housing, and military, radiation, industrial, and mining hazards. Addressing these hazards is challenging because of both practical and cultural barriers. Conclusion This exploratory cataloguing of the environmental health hazards faced by wildland firefighters is unlikely to be surprising to firefighters themselves, yet most of these hazards are underrecognized by land management agencies and researchers, and are incompletely mitigated in the work environment. Many of these hazards are (largely) invisible to those not working on the fireline or are only discussed in isolation, rather than as part of a cumulative or holistic understanding of firefighter health and safety. More attention by fire management agencies, fire leadership, and researchers is needed to the full range of hazards experienced by wildland firefighters.

Moderation analysis in business and management research: Common issues, solutions, and guidelines for future research

Asset allocation is a foundational concept in finance that determines how investment capital is distributed across different asset classes to balance risk and return. It plays a critical role in portfolio construction, long-term wealth creation, and financial stability for individual and institutional investors. This theoretical article examines asset allocation from classical and contemporary financial perspectives, drawing on portfolio theory, behavioral finance, and strategic investment frameworks. The study explores the theoretical foundations of asset allocation, including risk–return trade-offs, diversification benefits, and the role of investor objectives and constraints. It further analyzes strategic, tactical, and dynamic asset allocation approaches, highlighting their relevance under varying market conditions. By synthesizing existing literature, the paper conceptualizes asset allocation as a dynamic decision-making process influenced by economic cycles, market efficiency, and investor behavior. The article contributes to finance literature by providing an integrated theoretical understanding of asset allocation and identifying directions for future empirical research and practical application in portfolio management.

This study provides a comprehensive analysis of KM research, highlighting emerging trends and critical gaps. It offers practical insights for researchers and policymakers to guide KM strategy development in HEIs. This study conducts a comprehensive bibliometric analysis of knowledge management (KM) research in Scopus-indexed publications from 1998 to 2024, with a particular focus on developments within higher education institutions (HEIs). The research aims to trace the evolution of KM scholarship, identify influential contributors, and uncover emerging thematic trends. A total of 696 articles were analyzed using both quantitative and qualitative bibliometric techniques, including publication and citation analysis, co-authorship networks, and keyword co-occurrence. Performance analysis assessed scholarly output and impact, while science mapping facilitated by VOS-viewer visualized intellectual structures and research clusters. The findings reveal a significant growth in KM research, peaking in 2023 with 72 publications. Northwestern Polytechnical University stood out in citation impact, and the United Kingdom was identified as the most prolific contributor. The journal Computers and Education led in output, and the most cited article addressed KM readiness in HEIs. Notably, artificial intelligence (AI) and digital transformation emerged as promising directions for future research. This study provides valuable insights into the development of KM in the higher education sector and offers strategic implications for researchers, academics, and policymakers aiming to enhance institutional innovation and competitiveness.

Employee engagement has become a central concept in Human Resource Management (HRM) research due to its role in enhancing employee performance and organizational sustainability. This study employed a content analysis approach to review research trends related to employee engagement, particularly those examining work-life balance and leadership perspectives. A total of 50 peer-reviewed studies published between 2014 and 2025 were analyzed based on research design, antecedent variables, organizational context, theoretical frameworks, and methodological approaches. The findings indicate a significant increase in employee engagement research in recent years, with quantitative cross-sectional designs dominating the literature. Work-life balance and servant leadership emerged as the most frequently examined antecedents of employee engagement, while employee performance remained the primary outcome variable. Job Demands–Resources (JD–R) Theory was identified as the dominant theoretical framework. Based on the findings, this study proposes methodological and contextual recommendations for future employee engagement research.

The article is dedicated to the conceptual analysis of customer interaction models in digitally mediated service ecosystems and their relationship with sustainable growth in sales and service indicators. The relevance of the study is determined by the growing mismatch between linear management models and the non-linear dynamics of contemporary customer interactions shaped by digital platforms, algorithms, and omnichannel environments. The novelty of the work lies in treating customer interaction as a systemic configuration of resource integration rather than as a sequence of isolated transactions. The article describes how value emerges through the interaction of human, digital, and organizational resources and how this process affects long-term performance indicators. Special attention is paid to algorithmic mediation, omnichannel coherence, and the conditions under which value co-creation transforms into value co-destruction. The article sets itself the goal of developing a multi-layered conceptual framework linking interaction configurations to sustainable economic outcomes. To achieve this goal, analytical synthesis, comparative analysis, and conceptual modeling are employed. The study draws on contemporary research in service management, consumer behavior, and AI-enabled organizations. The conclusions demonstrate that sustainable growth depends on managing interaction density, employee agency, and technological governance. The article will be useful for researchers, managers, and practitioners working in service design, customer experience management, and digital strategy.

The 2025 3rd International Conference on Innovation Management, Psychology, Education and Sociology (IMPES 2025) was held in Sapporo, Japan during December 27-28, 2025. The main objectives of the conference are to promote research and development activities in innovation management, social psychology, educational technology, cultural studies, social policy, and sociology. Another goal is to promote the exchange of scientific information among researchers, developers, students, and practitioners around the world. IMPES 2025 can be a scientific forum to accommodate fruitful discussion among international researchers in various fields. We would like to thank all speakers, invited guests, and also other parties and donors for their continuous support to the success of this event. Hopefully, this event provides many benefits for us all. Conference Organizing Chair Sapporo, Japan

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac muscle disorder, yet contemporary genomic and mechanistic research still lacks a cohesive model explaining how diverse genetic architectures give rise to heterogeneous phenotypes. This review synthesizes advances across sarcomeric and non-sarcomeric mutations, including intermediate-effect variants, polygenic modifiers, and ancestry-dependent sources of variant misclassification to elucidate how these factors govern disease penetrance and clinical expression. It critically evaluates how genetic diversity intersects with key molecular pathways, including sarcomeric hypercontractility, calcium dysregulation, mitochondrial energy deficiency, and TGF-β and AKT/mTOR signaling, to drive hypertrophic and fibrotic remodeling. Emerging mechanism-based therapies, such as myosin inhibition, allele-specific silencing, CRISPR-based correction, and metabolic modulation, are examined with respect to their capacity to modify upstream molecular drivers rather than downstream hemodynamic consequences. Persistent challenges, including VUS classification, ancestry-biased databases, inequitable access to genetic testing, and unresolved safety concerns for gene-based therapies, are critically assessed as major barriers to precision-medicine integration. By linking genetic architecture, molecular pathogenesis, and targeted interventions, this review advances a contemporary, mechanistically grounded framework that informs both individualized management and future research directions. Future research should prioritize pathway-specific therapeutics, functional and mechanistic validation of emerging variants, deeper physiologic phenotyping to refine disease modeling, and accelerate translation throughout the continuum of HCM pathophysiology.

IT project management faces critical challenges related to inaccurate resource allocation estimation and project risk assessment, which complicates decision-making and threatens project performance. Although machine learning techniques have been widely adopted in this domain, existing studies predominantly rely on single models or simple ensemble strategies, limiting their ability to capture heterogeneous interactions among organizational, technical, and risk-related factors. This study proposes a hybrid machine learning–based decision support framework that integrates feature-level representation learning and probabilistic decision fusion. Gradient Boosting is reconceptualized as a feature selection and nonlinear interaction modeling mechanism, while Artificial Neural Networks generate latent feature embeddings representing complex project characteristics. These representations are fused through a Naive Bayes classifier to produce calibrated probabilistic predictions, supported by a weighted fusion strategy with F1-score–based threshold optimization to improve stability under imbalanced risk conditions. Experimental evaluation is conducted using 5,997 synthetic IT project records from PT Anugerah Nusa Teknologi. Model performance is evaluated using accuracy, precision, recall, F1-score, and ROC-AUC metrics. Compared to standalone Gradient Boosting, Artificial Neural Network, and Naive Bayes models, the proposed hybrid framework consistently demonstrates superior predictive performance, achieving an accuracy of 0.85, an F1-score of 0.8485, and a ROC-AUC of 0.9050. Theoretically, this study contributes to project management research by demonstrating that IT project outcomes are more effectively modeled through multi-perspective learning rather than isolated predictors. Practically, the proposed framework provides actionable decision support to assist project managers in optimizing resource allocation and prioritizing risk mitigation under uncertainty.

This study examines the determinants of intention to use digital banking services within the Technology Acceptance Model (TAM) framework, focusing on perceived usefulness (PU), perceived ease of use (PEOU), and attitude (ATT). As digital banking adoption grows rapidly in Indonesia amid the regional expansion of fintech innovations across Southeast Asia, understanding the behavioral mechanisms behind adoption becomes increasingly significant for both information systems and management research. A quantitative approach was applied using survey data from 210 active digital banking users in Jakarta, analyzed through Structural Equation Modeling (SEM) with SmartPLS 4.0. The results show that ease of use has a significant positive impact on users’ intention to adopt digital banking, emphasizing the importance of intuitive system design and low-effort interaction. Meanwhile, usefulness and attitude were found statistically insignificant in predicting intention, indicating that functional benefits alone may not directly drive user behavior. Rather than drawing conclusions about user priorities, these findings suggest a more complex interplay between cognitive and experiential factors. The study extends TAM by highlighting the contextual influence of user experience and cultural expectations in emerging digital economies beyond Indonesia. Practically, financial institutions are advised to enhance usability through seamless navigation, efficient processes, and reduced cognitive barriers to strengthen engagement and long-term adoption.

Purpose This study aims to examine how three contextual factors – reciprocity history with the knowledge seeker, communication media richness and the type of requested knowledge – influence knowledge workers’ responses in terms of knowledge hiding (playing dumb and evasive hiding) and knowledge sharing (partial or full sharing). Design/methodology/approach This study uses a quasi-experimental design, using a serious game with a simulated realistic scenario to collect data. A total of 199 knowledge workers from a German automotive company participated in the game, providing valuable insights into their responses to knowledge requests. Findings The results show that knowledge workers vary their knowledge hiding and sharing behaviours depending on reciprocity history with colleagues, the type of knowledge requested and the communication medium used. These findings suggest that a straightforward classification of knowledge hiding and sharing fails to capture the complex and nuanced ways employees manage knowledge requests in organisational settings. Originality/value This paper broadens the scope of knowledge hiding research by examining both knowledge hiding and knowledge sharing behaviours within a single framework and empirically testing the relationships between key antecedents and these behaviours. In addition, the use of a quasi-experimental design, based on a serious game for data collection, offers a novel methodological approach. This method reduces social desirability bias by capturing more authentic knowledge hiding and sharing behaviours compared to traditional approaches, providing a foundation for future research in knowledge management, particularly in the study of socially undesirable behaviours.

Type of the article: Research ArticleThe relevance of the study is determined by the growing need for theoretically grounded typological approaches to personality analysis in the context of organizational transformation, increasing emotional workload, and the growing complexity of team interaction. This necessitates a rethinking of classical typologies in terms of their explanatory potential for understanding behavior in professional settings. The purpose of the article is to conceptually substantiate the applicability of a typological approach to the analysis of organizational behavior through the development of an authorial model of behavioral vectors. The object of the study comprises personality typologies and their interpretative suitability for analyzing interpersonal interaction within organizations. The theoretical framework is based on concepts from personality psychology, typological analysis, and theories of organizational behavior, which made it possible to conduct a comparative analysis of classical and contemporary typological models and to synthesize them within a behavior-oriented analytical framework. As a result, a conceptual model of eight behavioral vectors is proposed, enabling the systematization of typical patterns of motivation, communication, and interaction in team environments. The model expands theoretical possibilities for analyzing behavioral compatibility and for formulating hypotheses regarding team dynamics, conflict potential, and synergy. The findings have theoretical significance for further research in human resource management and organizational behavior and provide a foundation for future empirical validation of the proposed approach.

Introduction Due to the vastness of various construction practices globally, there is a need for knowledge mapping. Through the utilisation of research on Project Risk Management (PRM) for the Construction Industry, it is possible to carry out an investigation into the processes that pertain to knowledge management. To elaborate on the current research emphasis from three different points of view, namely the influence of political risk, risk assessment, and risk management strategies, the knowledge map analysis method has been elected as the appropriate approach. Knowledge mapping provides a systematic way to visualise research trends, identify gaps, and strengthen the understanding of PRM in international construction projects. Methods This scientific investigation, conducted in the field of risk management research, considers publications related to risk management. The study was conducted as a systematic literature review that adopted bibliometrics approach to explore the data from Dimensions database that have been reviewed using PRISMA 2020 statement. This study intends to present Knowledge Mapping for PRM in the Construction Industry, using data from 2000-2025. The analysis focused on three dominant research dimensions: political risk, risk assessment, and risk management strategies. It uses literature on studies that have been carried out on project risk and provides a comprehensive perspective on the topic. Results The knowledge maps revealed distinct clusters of research activity across the three focal areas. Political risk emerged as a consistent theme in studies addressing international and cross-border construction contexts. Research on risk assessment showed significant methodological diversity, while studies on risk management strategies tended to emphasise both technological tools and organisational processes. Overall, the mapping highlighted increasing scholarly attention to integrated and holistic approaches to PRM. Some under-researched areas, particularly knowledge-transfer processes and cross-national learning mechanisms, were also identified. The findings demonstrate that knowledge mapping is a valuable tool for understanding the evolution and priorities of PRM research in the construction industry. Discussion The study makes use of Knowledge Mapping to offer some suggestions for research areas concerning risk management in international construction projects. These knowledge maps are founded on the investigations that were conducted on project risk management. However, the development of Knowledge Maps offers good contribution to knowledge for best practices in the construction sector. By identifying patterns and gaps, the study provides guidance for future investigations and encourages the development of improved risk management practices in global construction projects. The resulting knowledge maps contribute meaningfully to the field by supporting better decision-making, improving risk-handling capabilities, and informing best practices for the construction sector.