Search Results (491)

Oil spill simulation models are essential for predicting the oil spill behavior and movement in marine environments. In this study, we comprehensively reviewed a large and diverse body of peer-reviewed literature obtained from Scopus and Web of Science. Our initial analysis phase focused on examining trends in scientific publications, utilizing the complete dataset derived after systematic screening and database integration. In the second phase, we applied elements of a systematic review to identify and evaluate the most influential contributions in the scientific field of oil spill simulations. Our analysis revealed a steady and accelerating growth of research activity over the past five decades, with a particularly notable expansion in the last two. The field has also experienced a marked increase in collaborative practices, including a rise in international co-authorship and multi-authored contributions, reflecting a more global and interdisciplinary research landscape. We cataloged the key modeling frameworks that have shaped the field from established systems such as OSCAR, OIL-MAP/SIMAP, and GNOME to emerging hybrid and Lagrangian approaches. Hydrodynamic models were consistently central, often integrated with biogeochemical, wave, atmospheric, and oil-spill-specific modules. Environmental variables such as wind, ocean currents, and temperature were frequently used to drive model behavior. Geographically, research has concentrated on ecologically and economically sensitive coastal and marine regions. We conclude that future progress will rely on the real-time integration of high-resolution environmental data streams, the development of machine-learning-based surrogate models to accelerate computations, and the incorporation of advanced biodegradation and weathering mechanisms supported by experimental data. These advancements are expected to enhance the accuracy, responsiveness, and operational value of oil spill modeling tools, supporting environmental monitoring and emergency response. Full article

Introduction: Breakfast has emerged as a critical factor in preventing cardiovascular diseases, driven not only by its nutritional content but also by its alignment with circadian rhythms. However, gaps remain in the literature regarding its clinical impact and thematic evolution. Objective: To characterize the global scientific output on the relationship between breakfast quality and cardiovascular health through a systematic bibliometric analysis. Methodology: The PRISMA 2020 protocol was applied to select 1436 original articles indexed in Scopus and Web of Science (1957–2025). Bibliometric tools, including R (v4.4.2) and VOSviewer (v1.6.19) were used to map productivity, impact, collaboration networks, and emerging thematic areas. Results: Scientific output has grown exponentially since 2000. The most influential journals are the American Journal of Clinical Nutrition, Nutrients, and Diabetes Care. The United States, United Kingdom, and Japan lead in publication volume and citations, with increasing participation from Latin American countries. Thematic trends have shifted from traditional clinical markers to innovative approaches such as chrononutrition, digital health, and personalized nutrition. However, methodological gaps persist, including a predominance of observational studies and an underrepresentation of vulnerable populations. Conclusions: Breakfast is a dietary practice with profound implications for cardiometabolic health. This study provides a comprehensive overview of scientific literature, highlighting both advancements and challenges. Strengthening international collaboration networks, standardizing definitions of a healthy breakfast, and promoting evidence-based interventions in school, clinical, and community settings are recommended. Full article

The evolution of Industry 4.0 and the emerging paradigm of Industry 5.0 have introduced disruptive technologies that are reshaping modern manufacturing environments. Among these, Digital Twin (DT) and Industrial Metaverse (IM) technologies are increasingly recognized for their potential to enhance Occupational Health and Safety (OHS). However, a comprehensive understanding of how these technologies integrate to support OHS in manufacturing remains limited. This study systematically explores the transformative role of DT and IM in creating immersive, intelligent, and human-centric safety ecosystems. Following the PRISMA guidelines, a Systematic Literature Review (SLR) of 75 peer-reviewed studies from the SCOPUS and Web of Science databases was conducted. The review identifies key enabling technologies such as Virtual Reality (VR), Augmented Reality (AR), Extended Reality (XR), Internet of Things (IoT), Artificial Intelligence (AI), Cyber-Physical Systems (CPS), and Collaborative Robots (COBOTS), and highlights their applications in real-time monitoring, immersive safety training, and predictive hazard mitigation. A conceptual framework is proposed, illustrating a synergistic digital ecosystem that integrates predictive analytics, real-time monitoring, and immersive training to enhance the OHS. The findings highlight both the transformative benefits and the key adoption challenges of these technologies, including technical complexities, data security, privacy, ethical concerns, and organizational resistance. This study provides a foundational framework for future research and practical implementation in Industry 5.0. Full article

The construction sector significantly contributes to global environmental degradation through intensive resource extraction, high energy consumption, and substantial waste generation. Addressing this unsustainable trajectory requires integrated approaches that simultaneously improve operational efficiency and material circularity. Lean Construction (LC) and Circular Economy (CE) offer complementary frameworks for enhancing process performance and reducing environmental impacts. However, their combined implementation remains underdeveloped and fragmented. This study conducts a systematic literature review (SLR) of 18 peer-reviewed articles published between 2010 and 2025, selected using PRISMA 2020 guidelines and sourced from Scopus and Web of Science databases. A mixed-method approach combines bibliometric mapping and qualitative content analysis to investigate how LC and CE are jointly operationalized in construction contexts. The findings reveal that LC improves cost, time, and workflow reliability, while CE enables reuse, modularity, and lifecycle extension. Integration is further supported by digital tools—such as Building Information Modelling (BIM), Design for Manufacture and Assembly (DfMA), and digital twins—which enhance traceability and flow optimization. Nonetheless, persistent barriers—including supply chain fragmentation, lack of standards, and regulatory gaps—continue to constrain widespread adoption. This review identifies six strategic enablers for LC-CE integration: crossdisciplinary competencies, collaborative governance, interoperable digital systems, standardized indicators, incentive-based regulation, and pilot demonstrator projects. By consolidating fragmented evidence, the study provides a structured research agenda and practical insights to guide the transition toward more circular, efficient, and sustainable construction practices. Full article

This study investigates how differing national research governance models impact academic performance by comparing European Research Council (ERC) grant winners in the social sciences and humanities from France and the Netherlands. Situated within the broader context of centralized versus decentralized research systems, the analysis aims to understand how these structures shape publication trends, thematic diversity, and collaboration patterns. Drawing on Scopus and SciVal data covering 9996 publications by 305 ERC winners between 2019 and 2023, we employed a multi-method approach, including latent Dirichlet allocation for topic modeling, compound annual growth rate analysis, and co-authorship network analysis. The results show that neuroscience, climate change, and psychology are dominant domains, with language and linguistics particularly prevalent in France and law and political science in the Netherlands. French ERC winners are more likely to be affiliated with national or sectoral institutions, whereas in the Netherlands, elite universities dominate. Collaboration emerged as a key success factor, with an average of four co-authors per publication and network analyses revealing central figures who bridge topical clusters. International collaborations were consistently linked with higher visibility, while single-authored publications showed limited impact. These findings suggest that institutional context and collaborative practices significantly shape research performance in both countries. Full article

As a core component of automated logistics systems, delivery robots hold significant application value in the field of unmanned delivery. This research addresses the robot path planning problem, aiming to enhance delivery efficiency and reduce operational costs through systematic improvements to the RIME optimization algorithm. Through in-depth analysis, we identified several major drawbacks in the standard RIME algorithm for path planning: insufficient global exploration capability in the initial stages, a lack of diversity in the hard RIME search mechanism, and oscillatory phenomena in soft RIME step size adjustment. These issues often lead to undesirable phenomena in path planning, such as local optima traps, path redundancy, or unsmooth trajectories. To address these limitations, this study proposes the Multi-Strategy Controlled Rime Algorithm (MSRIME), whose innovation primarily manifests in three aspects: first, it constructs a multi-strategy collaborative optimization framework, utilizing an infinite folding Fuch chaotic map for intelligent population initialization to significantly enhance the diversity of solutions; second, it designs a cooperative mechanism between a controlled elite strategy and an adaptive search strategy that, through a dynamic control factor, autonomously adjusts the strategy activation probability and adaptation rate, expanding the search space while ensuring algorithmic convergence efficiency; and finally, it introduces a cosine annealing strategy to improve the step size adjustment mechanism, reducing parameter sensitivity and effectively preventing path distortions caused by abrupt step size changes. During the algorithm validation phase, comparative tests were conducted between two groups of algorithms, demonstrating their significant advantages in optimization capability, convergence speed, and stability. Further experimental analysis confirmed that the algorithm’s multi-strategy framework effectively suppresses the impact of coordinate and dimensional differences on path quality during iteration, making it more suitable for delivery robot path planning scenarios. Ultimately, path planning experimental results across various Building Coverage Rate (BCR) maps and diverse application scenarios show that MSRIME exhibits superior performance in key indicators such as path length, running time, and smoothness, providing novel technical insights and practical solutions for the interdisciplinary research between intelligent logistics and computer science. Full article

The number of publications in the scientific literature dealing with geomorphological mapping has increased over the last two decades. Although geomorphological maps are utilised in various contexts, such as hazard assessment, archaeology, and tourism, there is a noticeable lack of interaction between geomorphological products and the social sciences. This study aims to provide a qualitative assessment of the literature on geomorphological maps published in the 2000s with the intent of identifying the purpose of mapping and its field of application. Additionally, a comparative analysis was conducted of the articles relating to both geomorphological maps and social issues to identify the tools that facilitate this interdisciplinary collaboration. The results facilitated the identification of the primary fields of interest for map production, showing that only a limited number of articles employed geomorphological maps for social purposes, for instance, enhancing risk awareness and educating the population about natural hazards. Moreover, the analysis reveals that only a limited number of geomorphological maps are intended to be accessible to people without a high degree of education in earth sciences. In particular, this study highlights a lack of attention to non-specialist users who may struggle to understand the information contained in geomorphological maps. This issue limits the dissemination of geomorphological maps, which are, however, vital for territorial planning and practical purposes. The analyses prompted the authors to consider novel applications of research tools to enhance the dissemination of geomorphological maps, even among non-specialist users. Full article

Advanced three-dimensional extended reality (XR) technologies are highly suitable for cultural heritage research and education. XR tools enable the creation of realistic virtual or augmented reality applications for curating and disseminating information about cultural artifacts and sites. Developing XR applications for cultural heritage requires interdisciplinary collaboration involving strong teamwork and soft skills to manage user requirements, system specifications, and design cycles. Given the diverse end-users, achieving high precision, accuracy, and efficiency in information management and user experience is crucial. Human–computer interaction (HCI) design and evaluation methods are essential for ensuring usability and return on investment. This article presents ten case studies of cultural heritage software projects, illustrating the interdisciplinary work between computer science and HCI design. Students from institutions such as the State University of New York (USA), Glasgow School of Art (UK), University of Granada (Spain), University of Málaga (Spain), Duy Tan University (Vietnam), Imperial College London (UK), Research University Institute of Communication & Computer Systems (Greece), Technical University of Košice (Slovakia), and Indiana University (USA) contributed to creating, assessing, and improving the usability of these diverse cultural heritage applications. The results include a structured typology of CH XR application scenarios, detailed insights into design and evaluation practices across ten international use cases, and a development framework that supports interdisciplinary collaboration and stakeholder integration in phygital cultural heritage projects. Full article

Amidst global efforts toward sustainable development, this research addresses underexplored academic dimensions by evaluating the transformative potential of intelligent, sustainable architecture. Employing bibliometric techniques and Citespace 6.4.R1, we analyze two decades (2005–2024) of the Web of Science literature to identify patterns and challenges. Findings demonstrate rising scholarly output, dominated by themes like energy-efficient design, Building Information Modeling integration, and circular economy principles in urban contexts. While Europe and North America lead research activity, systemic limitations persist—including duplicated methodologies, fragmented institutional networks, and incompatible smart technologies. This study advocates for three strategic priorities: fostering interdisciplinary innovation to break homogeneity, establishing cross-sector collaboration frameworks, and accelerating industry–academia knowledge transfer. Intelligent, sustainable architecture emerges as a dual solution—technologically enabling carbon-neutral construction practices while redefining human-centric spatial quality. This dual advantage positions the International Sustainability Alliance as critical infrastructure for achieving UN Sustainable Development Goals, reconciling ecological responsibility with evolving societal demands for resilient, adaptive built environments. Full article

Critical data literacy (CDL) has emerged as a crucial component in data science education, transcending traditional disciplinary boundaries. Promoting CDL requires collaborative approaches to enhance learners’ skills in data science, going beyond mere quantitative reasoning to encompass a comprehensive understanding of data workflows and tools. Despite the growing literature on CDL, there is still a need to explore how students use data science practices for supporting the learning of CDL throughout a summer-long data science program. Drawing on situative perspectives of learning, we utilize a descriptive case study to address our research question: How do data science practices taught in a classroom setting differ from those enacted in real-world social justice projects? Key findings reveal that while the course focused on abstract principles and basic technical skills, the Food Justice Project provided students with a more applied understanding of data tools, ethics, and exploration. Through the project, students demonstrated a deeper engagement with CDL, addressing real-world issues through detailed data analysis and ethical considerations. This manuscript adds to the literature within data science education and has the potential to bridge the gap between theoretical knowledge and practical application, preparing students to address real-world data science challenges through their coursework. Full article

Project delays remain a persistent challenge in the construction industry, having significant financial implications and contributing to disputes between project participants. Forensic Delay Analysis (FDA) has emerged as a specialised function that identifies the root causes of such delays, quantifies their duration, and assigns responsibility to the appropriate parties. While FDA is a widely practised process, it has yet to fully exploit the potential of emerging technologies. This study explores the integration of both existing and emerging technologies for enhancing FDA processes. A Design Science Research (DSR) approach is adopted, with data collection methods that involve the use of the literature, archival materials, case studies and survey methods. The research demonstrates how the use of technologies, such as database management systems (DBMSs), building information modelling (BIM), artificial intelligence (AI) and games engines, can improve the analytical efficiency, data management, and presentation of findings through a case study. The study showcases the transformative potential of these interventions in streamlining FDA processes, ultimately leading to more accurate and efficient resolution of construction disputes. The proposed process is exemplified by the development of a prototype: the Forensic Information Modelling Visualiser (FIMViz). The FIMViz is a practical tool that has received positive evaluation by FDA experts. The prototype and the enhanced FDA process model that underpins it demonstrate significant advancement in FDA practices, promoting improved decision-making and collaboration between project participants. Further development is needed, but the results could ultimately streamline the FDA process and minimise the uncertainties in FDA outcomes, thus reducing the incidence of costly disputes to the wider economic benefit of the industry generally. Full article

Construction projects still face persistent barriers to adopting whole life costing (WLC), such as fragmented data, a lack of standardization, and inadequate tools. This study addresses these limitations by proposing a core ontology for WLC, developed using an ontology design science research methodology. The ontology formalizes WLC knowledge based on ISO 15686-5 and incorporates professional insights from surveys and expert focus groups. Implemented in web ontology language (OWL), it models cost categories, temporal aspects, and discounting logic in a machine-interpretable format. The ontology’s interoperability and extensibility are validated through its integration with the building topology ontology (BOT). Results show that the ontology effectively supports cost breakdown, time-based projections, and calculation of discounted values, offering a reusable structure for different project contexts. Practical validation was conducted using SQWRL queries and Python scripts for cost computation. The solution enables structured data integration and can support decision-making throughout the building life cycle. This work lays the foundation for future semantic web applications such as knowledge graphs, bridging the current technological gap and facilitating more informed and collaborative use of WLC in construction. Full article

Background: In elderly community services, information technology is reshaping the daily lives of older adults in unprecedented ways. It effectively addresses the issue of frailty in the community by strengthening support networks and dynamic risk management. Despite its vast potential, there remains a need to explore further enabling methods in the realm of elderly community services. Objectives: This study aims to provide a significant theoretical and practical foundation for information technology in this field by systematically analyzing the progress and trends of digital transformation facilitated by information technology. Materials and method: To map the advancements and emerging trends in this evolving field, this study conducts a bibliometric analysis of 461 relevant publications from the Web of Science Core Collection (2004–2024). The research employs bibliometric methods and utilizes tools such as CiteSpace and VOSViewer to analyze collaborations, keywords, and citations, as well as to perform data visualization. Results: The findings indicate that current research hotspots mainly focus on “community care”, “access to care”, “technology”, and “older adults”.Potential development trends include (1) further exploration of information technology in elderly care to provide more precise health management solutions; (2) systematically building community elderly service systems to offer more detailed elderly care services; (3) strengthening interdisciplinary information sharing and research collaboration to drive innovation in community elderly care models; and (4) introducing targeted policy and financial support to improve the specific implementation framework of information technology in elderly community services. Conclusions: This study provides empirical support for the development of relevant theories and practices. Furthermore, the research outcomes offer valuable insights into business opportunities for practitioners and provide important recommendations for formulating elderly service policies. Full article

Multi-agent large language models promise flexible, modular architectures for delivering personalized educational content. Drawing on a pilot randomized controlled trial with middle school students (n = 23), we introduce a two-agent GPT-4 framework in which a Profiler agent infers learner-specific preferences and a Rewrite agent dynamically adapts science passages via an explicit message-passing protocol. We implement structured system and user prompts as inter-agent communication schemas to enable real-time content adaptation. The results of an ordinal logistic regression analysis hinted that students may be more likely to prefer texts aligned with their profile, demonstrating the feasibility of multi-agent system-driven personalization and highlighting the need for additional work to build upon this pilot study. Beyond empirical validation, we present a modular multi-agent architecture detailing agent roles, communication interfaces, and scalability considerations. We discuss design best practices, ethical safeguards, and pathways for extending this framework to collaborative agent networks—such as feedback-analysis agents—in K-12 settings. These results advance both our theoretical and applied understanding of multi-agent LLM systems for personalized learning. Full article

The intersection of microbial food safety and antimicrobial resistance (AMR) represents a mounting global threat with profound implications for public health, food safety, and sustainable development. This review explores the complex pathways through which foodborne pathogens—such as Salmonella spp., Escherichia coli (E. coli), Listeria monocytogenes (L. monocytogenes), and Campylobacter spp.—acquire and disseminate resistance within human, animal, and environmental ecosystems. Emphasizing a One Health framework, we examine the drivers of AMR across sectors, including the misuse of antibiotics in agriculture, aquaculture, and clinical settings, and assess the role of environmental reservoirs in sustaining and amplifying resistance genes. We further discuss the evolution of surveillance systems, regulatory policies, and antimicrobial stewardship programs (ASPs) designed to mitigate resistance across the food chain. Innovations in next-generation sequencing, metagenomics, and targeted therapeutics such as bacteriophage therapy, antimicrobial peptides (AMPs), and CRISPR-based interventions offer promising alternatives to conventional antibiotics. However, the translation of these advances into practice remains uneven, particularly in low- and middle-income countries (LMICs) facing significant barriers to diagnostic access, laboratory capacity, and equitable treatment availability. Our analysis underscores the urgent need for integrated, cross-sectoral action—anchored in science, policy, and education—to curb the global spread of AMR. Strengthening surveillance, investing in research, promoting responsible antimicrobial use, and fostering global collaboration are essential to preserving the efficacy of existing treatments and ensuring the microbiological safety of food systems worldwide. Full article