Search Results (583)

The built environment plays a crucial role in shaping residents’ quality of life and emotional well-being. In the context of growing efforts to promote livable and walkable cities, a key question emerges: how can emerging technologies—particularly virtual reality (VR)—be leveraged to evaluate and enhance urban environments through the lens of pedestrian emotional perception? This study systematically reviewed the literature published between 2015 and 2024 in the China National Knowledge Infrastructure (CNKI) and Web of Science (WOS) databases, ultimately identifying 37 Chinese-language and 113 English-language journal articles. Using bibliometric analysis and CiteSpace, the research mapped publication trends, research hotspots, and disciplinary networks across linguistic contexts. Results reveal that Chinese-language studies often emphasize embodied cognition and electroencephalogram (EEG) monitoring, while English-language studies focus more on VR application in stress recovery and health assessment. Based on this synthesis, this study proposes a “sensory–cognitive–affective” framework and a set of spatial intervention strategies, offering a novel perspective for emotion-driven urban design. The findings highlight a paradigm shift from engineering-oriented planning to human-centered approaches, with VR technologies serving as a critical enabling tool. This review contributes both conceptual and methodological foundations for future research at the intersection of immersive technologies, built environment studies, and urban emotional well-being. Full article

Background: Hepatopancreatobiliary (HPB) surgery is among the most complex domains in oncologic care, where decisions entail significant risk–benefit considerations. Artificial intelligence (AI) has emerged as a promising tool for improving individualized decision-making through enhanced risk stratification, complication prediction, and survival modeling. However, its role in HPB oncologic surgery has not been comprehensively assessed. Methods: This systematic review was conducted in accordance with PRISMA guidelines and registered with PROSPERO ID: CRD420251114173. A comprehensive search across six databases was performed through 30 May 2025. Eligible studies evaluated AI applications in risk–benefit assessment in HPB cancer surgery. Inclusion criteria encompassed peer-reviewed, English-language studies involving human s ubjects. Two independent reviewers conducted study selection, data extraction, and quality appraisal. Results: Thirteen studies published between 2020 and 2024 met the inclusion criteria. Most studies employed retrospective designs with sample sizes ranging from small institutional cohorts to large national databases. AI models were developed for cancer risk prediction (n = 9), postoperative complication modeling (n = 4), and survival prediction (n = 3). Common algorithms included Random Forest, XGBoost, Decision Trees, Artificial Neural Networks, and Transformer-based models. While internal performance metrics were generally favorable, external validation was reported in only five studies, and calibration metrics were often lacking. Integration into clinical workflows was described in just two studies. No study addressed cost-effectiveness or patient perspectives. Overall risk of bias was moderate to high, primarily due to retrospective designs and incomplete reporting. Conclusions: AI demonstrates early promise in augmenting risk–benefit assessment for HPB oncologic surgery, particularly in predictive modeling. However, its clinical utility remains limited by methodological weaknesses and a lack of real-world integration. Future research should focus on prospective, multicenter validation, standardized reporting, clinical implementation, cost-effectiveness analysis, and the incorporation of patient-centered outcomes. Full article

The frequency of technology use is an important factor that can significantly influence employees’ well-being and the perceived quality of their work life in an ever-changing digital workplace. The introduction of new technologies affects the lives of employees. It is therefore important how employees themselves perceive new technologies and the need to digitalize their work tasks. Previous studies have focused more on technology adoption or quality of work life separately. The main aim of the article is to present the results of analyses on how the frequency of technology use is related to employees’ perception of digitalization in their workplace, as well as the impact these factors have on their perceived quality of work life. This study simultaneously examines the impact of perceptions of technological change and frequency of technology use on quality of work life in the context of medium-sized and large industrial enterprises in Slovakia. In this way, it is possible to better understand the connection between digitalization and employee well-being. The research tool was a questionnaire that focused on the perceived quality of work life of employees and questions related to the perception of digitalization and to the frequency of technology use. Hypothesis testing was processed using IBM SPSS version 25 software. Considering the results, it can be stated that a positive perception of technological changes and regular use of technology in the workplace are related to a higher level of quality of work life perceived by employees. The results can be used for multiple strategic and practical applications in organizational development and human-centered approaches to digital transformation. Full article

This study introduces a novel and user-centered surface abrasion test designed to assess the injury potential of pavement surfaces, particularly for vulnerable road users such as micromobility users. Traditional pavement evaluation methods focus on skid resistance and texture but do not account for the surface’s mechanical aggressiveness during a fall. To address this gap, the proposed test simulates fall conditions by dragging a paraffin wax specimen—used as a low-cost and reproducible proxy to approximate the abrasive response that could affect human skin—over pavement at a controlled speed and load, quantifying material loss as an indicator of surface abrasiveness. The method was validated on three pavement types (smooth ceramic, bituminous, and concrete), demonstrating its sensitivity and repeatability. Unlike conventional point-based tests, it enables continuous evaluation along a predefined length, offering more representative results. A full-scale case study on a micromobility-dedicated bike lane confirmed the test’s responsiveness to surface changes over time. Results suggest the method is practical, reproducible, and applicable to a wide range of pavements. Beyond micromobility, it can be extended to other vulnerable users, such as motorcyclists. The test represents a new metric for infrastructure safety audits focused on injury mitigation. Full article

This study reports on a Design-Based Research (DBR) project that implemented Project-Based Learning (PjBL) in an undergraduate psychology course on Human Resource Development (HRD). The purpose was to move beyond lecture-based instruction and explore how open pedagogy can create authentic, student-centered learning experiences that bridge theory and practice. Over two course iterations (n = 31), students co-designed, implemented, and evaluated HRD interventions for their peers, supported by peer and instructor feedback and complemented by a co-created open-book exam. Quantitative pre- and post-tests revealed significant improvements in students’ knowledge of HRD methods, learning theories, and application competencies, as well as enhanced confidence in their professional qualifications. Students valued the openness of the design, its practical orientation, and the error-friendly learning environment, though challenges emerged regarding workload, communication, and intrinsic motivation. Educators reported a transformation of their role from knowledge transmitter to facilitator and co-learner, while also identifying opportunities to use AI for generating authentic case tasks. The findings suggest that PjBL, combined with open pedagogy, fosters self-directed learning, transparency, and collaboration, thereby contributing to cultural change in higher education toward openness, participation, and innovation. Full article

As cities strive for human-centered and fine-tuned development, Agent-Based Modeling (ABM) has emerged as a powerful tool for simulating pedestrian behavior and optimizing walkable neighborhood design. This study presents a comparative bibliometric analysis of ABM applications in block-scale walkability research from 2015 to 2024, drawing on both Chinese- and English-language literature. Using visualization tools such as VOSviewer, the analysis reveals divergences in national trajectories, methodological approaches, and institutional logics. Chinese research demonstrates a policy-driven growth pattern, particularly following the introduction of the “15-Minute Community Life Circle” initiative, with an emphasis on neighborhood renewal, age-friendly design, and transit-oriented planning. In contrast, international studies show a steady output driven by technological innovation, integrating methods such as deep learning, semantic segmentation, and behavioral simulation to address climate resilience, equity, and mobility complexity. The study also classifies ABM applications into five key application domains, highlighting how Chinese and international studies differ in focus, data inputs, and implementation strategies. Despite these differences, both research streams recognize the value of ABM in transport planning, public health, and low-carbon urbanism. Key challenges identified include data scarcity, algorithmic limitations, and ethical concerns. The study concludes with future research directions, including multimodal data fusion, integration with extended reality, and the development of privacy-aware, cross-cultural modeling standards. These findings reinforce ABM’s potential as a smart urban simulation tool for advancing adaptive, human-centered, and sustainable neighborhood planning. Full article

Recent advancements in the Internet of Things (IoT) and artificial intelligence (AI) are unlocking transformative opportunities across society. One of the most critical challenges addressed by these technologies is the ageing population, which presents mounting concerns for healthcare systems and quality of life worldwide. By supporting continuous monitoring, personal care, and data-driven decision-making, IoT and AI are shifting healthcare delivery from a reactive approach to a proactive one. This paper presents a comprehensive overview of IoT-based systems with a particular focus on the Internet of Healthcare Things (IoHT) and their integration with AI, referred to as the Artificial Intelligence of Things (AIoT). We illustrate the operating procedures of IoHT systems in detail. We highlight their applications in disease management, health promotion, and active ageing. Key enabling technologies, including cloud computing, edge computing architectures, machine learning, and smart sensors, are examined in relation to continuous health monitoring, personalized interventions, and predictive decision support. This paper also indicates potential challenges that IoHT systems face, including data privacy, ethical concerns, and technology transition and aversion, and it reviews corresponding defense mechanisms from perception, policy, and technology levels. Future research directions are discussed, including explainable AI, digital twins, metaverse applications, and multimodal sensor fusion. By integrating IoT and AI, these systems offer the potential to support more adaptive and human-centered healthcare delivery, ultimately improving treatment outcomes and supporting healthy ageing. Full article

Coastal ecosystems sustain biodiversity, food resources, and human livelihoods, yet are increasingly exposed to climate change, pollution, and anthropogenic stressors. These pressures affect not only ecosystem integrity but also human health, highlighting the urgency of adopting the One Health framework. While One Health has gained global prominence, its systematic application in coastal and marine governance remains limited. This study provides the first bibliometric review of One Health research in coastal and marine contexts, analyzing 154 publications from Scopus (2003–2025) using Bibliometrix under PRISMA-S guidelines. Scientific output was minimal until 2015 but accelerated after 2020, peaking at 37 publications in 2024. Less than 20% of studies explicitly integrated all three One Health dimensions. Research has largely centered on environmental monitoring and aquaculture health, with antimicrobial resistance, climate–health linkages, and integrated coastal indicators underexplored. Keyword mapping revealed two distinct yet connected clusters: a biomedical cluster emphasizing antibiotics, resistance, and microbiology, and an environmental cluster focusing on pollution, ecosystems, and zoonotic risks. Outputs are geographically concentrated in high-income countries, particularly the USA, Brazil, and the UK, while contributions from low- and middle-income coastal regions remain scarce. These findings confirm both the rapid growth and the fragmentation of One Health scholarship in coastal contexts. By identifying gaps, trends, and collaboration patterns, this study builds an evidence base for embedding One Health in coastal monitoring, climate adaptation, and governance, advancing multiple United Nations’s Sustainable Development Goals. Full article

Since the 1960s, theories on the relationship between people and their environment have explored how elements of the built environment may directly or indirectly influence human behavior. In this context, neuroarchitecture is emerging as an interdisciplinary field that integrates neuroscience, architecture, environmental psychology, and cognitive science, with the aim of providing empirical evidence on how architectural spaces affect the human brain. This study investigates the potential of neuroarchitecture to inform environmental design by clarifying its current conceptual framework, examining its practical applications, and identifying the context in which it is being implemented. Beginning with an in-depth analysis of the definition of neuroarchitecture, its theoretical foundations, and the range of interpretations within the academic community, the study then offers a critical review of its practical applications across various design fields. By presenting a comprehensive overview of this emerging discipline, the study also summarizes the measurement techniques commonly employed in related research and critically evaluates design criteria based on observed human responses. Ultimately, neuroarchitecture represents a promising avenue for creating environments that deliberately enhance psychological and physiological well-being, paving the way toward truly human-centered design. Nevertheless, neuroarchitecture is still an emerging experimental field, which entails significant limitations. The experiments conducted are still limited to virtual reality and controlled experimental contexts. In addition, small and heterogeneous population samples have been tested, without considering human variability. Full article

Parkinson’s disease (PD), a progressive neurodegenerative disorder affecting over 10 million people worldwide, necessitates continuous symptom monitoring to optimize treatment and enhance quality of life. Effective communication between patients and healthcare providers (HCPs) is vital but often hindered by fragmented data and cognitive impairments. PARKA AI, a novel iOS application, leverages Apple Watch HealthKit data (e.g., tremor detection, mobility metrics, heart rate, and sleep patterns) and integrates it with self-reported logs (e.g., mood, medication adherence) to empower PD self-management and improve patient–HCP interactions. Employing a human-centered design approach, we developed a high-fidelity prototype using a large language model (LLM)— Google Gemini 1.5 Flash—to process and analyze self-reports and objective sensor-derived data from Apple Healthkit to generate patient-friendly summaries and concise HCP reports. PARKA AI provides accessible data visualizations, personalized self-management tools, and streamlined HCP reports to foster engagement and communication. This paper outlines the derived design requirements, prototype features, and illustrative use cases to show how LLMs can be used in digital health tools. Future work will focus on real-world usability testing to validate the application’s efficacy and accessibility. Full article

Traffic safety is undergoing a profound transformation, driven by advances in data science, sensing technologies, and computational modeling. Proactive approaches are enabling the early identification of potential hazards, real-time decision-making, and the development of smarter, safer transportation systems. This Special Issue summarizes recent progress in traffic safety assessment, highlighting the application of emerging tools such as machine learning, explainable artificial intelligence, and computer vision. These innovations are used to predict crash risks, evaluate surrogate safety measures, and automate the analysis of behavioral data, contributing to more inclusive and adaptive safety frameworks, particularly for vulnerable road users such as pedestrians and cyclists. The research also addresses key challenges, including data integration across diverse sources, aligning safety metrics with human perception, and ensuring the scalability of models in complex environments. By advancing both technical methodologies and human-centered evaluation, these developments signal a shift toward more intelligent, transparent, and equitable approaches to traffic safety assessment and policy-making. Full article

This Scoping Review (ScR) synthesizes advances in architectural eye-tracking (ET) research published between 2010 and 2024. Drawing on 75 peer-reviewed studies that met clear inclusion criteria, it monitors the field’s rapid expansion, from only 20 experiments before 2018, to more than 45 new investigations in the three years thereafter, situating these developments within the longer historical evolution of ET hardware and analytical paradigms. The review maps 13 recurrent areas of application, focusing on design evaluation, wayfinding and spatial navigation, end-user experience, and architectural education. Across these domains, ET reliably reveals where occupants focus, for how long, and in what sequence, providing objective evidence that complements designer intuition and conventional post-occupancy surveys. Experts and novices might display distinct gaze signatures; for example, architects spend longer fixating on contextual and structural cues, whereas lay users dwell on decorative details, highlighting possible pedagogical opportunities. Despite these benefits, persistent challenges include data loss in dynamic or outdoor settings, calibration drift, single-user hardware constraints, and the need to triangulate gaze metrics with cognitive or affective measures. Future research directions emphasize integrating ET with virtual or augmented reality (VR) (AR) to validate design interactively, improving mobile tracking accuracy, and establishing shared datasets to enable replication and meta-analysis. Overall, the study demonstrates that ET is maturing into an indispensable, evidence-based lens for creating more intuitive, legible, and human-centered architecture. Full article

With the rapid advancement of artificial intelligence, the deployment of social robots has significantly broadened, extending into diverse fields such as education, medical services, and business. Despite this expansive growth, there remains a notable scarcity of empirical research addressing the underlying psychological mechanisms that influence human–robot interactions. To address this critical research gap, the present study proposes and empirically tests a theoretical model designed to elucidate how users’ multi-dimensional perceived values of social robots influence their attitudinal responses and outcomes. Based on questionnaire data from 569 social robot users, the study reveals that users’ perceived utilitarian value, emotional value, and hedonic value all exert significant positive effects on active involvement, thereby fostering their identification and reinforcing attitudinal loyalty. Among these dimensions, emotional value emerged as the strongest predictor, underscoring the pivotal role of emotional orientation in cultivating lasting human–robot relationships. Furthermore, the findings highlight the critical mediating function of active involvement in linking perceived value to users’ psychological sense of belonging, thereby elucidating the mechanism through which perceived value enhances engagement and promotes sustained long-term interaction. These findings extend the conceptual boundaries of human–machine interaction, offer a theoretical foundation for future explorations of user psychological mechanisms, and inform strategic design approaches centered on emotional interaction and user-oriented experiences, providing practical guidance for optimizing social robot design in applications. Full article

Machine learning (ML) is reshaping how environmental chemicals are monitored and how their hazards are evaluated for human health. Here, we mapped this landscape by analyzing 3150 peer-reviewed articles (1985–2025) from the Web of Science Core Collection. Co-citation, co-occurrence, and temporal trend analyses in VOSviewer and R reveal an exponential publication surge from 2015, dominated by environmental science journals, with China and the United States leading in output. Eight thematic clusters emerged, centered on ML model development, water quality prediction, quantitative structure–activity applications, and per-/polyfluoroalkyl substances, with XGBoost and random forests as the most cited algorithms. A distinct risk assessment cluster indicates migration of these tools toward dose–response and regulatory applications, yet keyword frequencies show a 4:1 bias toward environmental endpoints over human health endpoints. Emerging topics include climate change, microplastics, and digital soil mapping, while lignin, arsenic, and phthalates appear as fast-growing but understudied chemicals. Our findings expose gaps in chemical coverage and health integration. We recommend expanding the substance portfolio, systematically coupling ML outputs with human health data, adopting explainable artificial intelligence workflows, and fostering international collaboration to translate ML advances into actionable chemical risk assessments. Full article

Buber’s analysis of Job, offering four responses to the theodical questions that innocent suffering raises, has been highly influential since its publication in 1942, as has been Steven Kepnes’s more recent application of Buber’s analysis to the Nazi Holocaust. Each of Buber’s specific responses has been, at various points in history and today, taken up by sufferers and by those pondering suffering’s theodical implications. Yet each response retains troubling features. This article, building on Buber and Kepnes, offers an alternate reading of the Book of Job, centering on two points: (i) a possible covenantal, rather than retributive, nature of the God-Job relationship and (ii) an understanding of God’s response to Job as covenantal. This is not to suggest that such a response “solves” suffering, but it is comprehensible to Job from his own knowledge and experience of the world—an important aspect of the covenantal relationship—and is in some measure helpful. The article first reviews Kepnes’s reading of Buber, discusses four aspects of it that remain theodically troubling, and then sketches a covenantal reading of Job, drawing on the work of Edward Greenstein, Moshe Greenberg, David Burrell, Bill McKibben, Susannah Ticciati, and other more recent Jobian scholars. This discussion explores the following: (i) covenant in the Wisdom literature, (ii) a universalist reading of covenant entailing human integrity, reasoned dialogue, and the validity of human knowledge within natural, human capacity, (iii) why Job’s request to God is covenantal, and (iv) why God’s response is as well. Full article