Search Results (102)

Background: Older adults are highly vulnerable to infectious diseases due to immunosenescence, multimorbidity, and atypical presentations. Artificial intelligence (AI) offers promising opportunities to improve diagnosis, prognosis, treatment, and continuity of care in this population. This review summarizes current applications of AI in the management of infections in older adults across diagnostic, prognostic, therapeutic, and preventive domains. Methods: We conducted a narrative review of peer-reviewed studies retrieved from PubMed, Scopus, and Web of Science, focusing on AI-based tools for infection diagnosis, risk prediction, antimicrobial stewardship, prevention of healthcare-associated infections, and post-discharge care in individuals aged ≥65 years. Results: AI models, including machine learning, deep learning, and natural language processing techniques, have demonstrated high performance in detecting infections such as sepsis, pneumonia, and healthcare-associated infections (Area Under the Curve AUC up to 0.98). Prognostic algorithms integrating frailty and functional status enhance the prediction of mortality, complications, and readmission. AI-driven clinical decision support systems contribute to optimized antimicrobial therapy and timely interventions, while remote monitoring and telemedicine applications support safer hospital-to-home transitions and reduced 30-day readmissions. However, the implementation of these technologies is limited by the underrepresentation of frail older adults in training datasets, lack of real-world validation in geriatric settings, and the insufficient explainability of many models. Additional barriers include system interoperability issues and variable digital infrastructure, particularly in long-term care and community settings. Conclusions: AI has strong potential to support predictive and personalized infection management in older adults. Future research should focus on developing geriatric-specific, interpretable models, improving system integration, and fostering interdisciplinary collaboration to ensure safe and equitable implementation. Full article

Industry 5.0 (I5) represents a significant evolution in the trajectory of industrial development, emphasizing a human-centric approach that integrates advanced technologies with the goal of promoting sustainable growth, resilience, and enhanced human well-being. While Industry 4.0 already posed considerable challenges for industrial organizations, particularly in terms of technological integration, workforce adaptation, and strategic realignment, the shift toward Industry 5.0 has introduced additional complexities. The accelerated pace of innovation and the evolving expectations for human–machine collaboration have intensified these challenges. Large manufacturing corporations are already facing difficulties in adapting to this new paradigm; thus, the question arises: how are Small and Medium-sized Enterprises (SMEs), which typically operate with limited resources, infrastructure, and financial capacity, managing this transition? This paper presents a scoping review of 17 research papers, chosen from an initial set of 37 publications sourced from Scopus, Web of Science and ScienceDirect on the implementation of Industry 5.0 in SMEs. A comprehensive synthesis of existing research was conducted to elucidate the current state of the topic, identify the research questions addressed, and outline future directions for this emerging paradigm. Full article

Vertiports, as the foundational ground infrastructure for Urban Air Mobility (UAM), have garnered increasing scholarly attention in recent years. To examine how the existing literature has reviewed and summarized vertiport-related knowledge, this study conducts a bibliometric analysis of publications (2000–2024) from four major databases, including Web of Science and Scopus, using VOSviewer and CiteSpace. By analyzing co-citation and keyword co-occurrence patterns, the results suggest that vertiport research frontiers are shifting toward facility location, network planning, airspace and scheduling management, scalable infrastructure, and integration with ground transport systems. Scholars and institutions in the United States, China, Europe, and South Korea have taken leading roles in advancing this field, though collaboration among research organizations still requires strengthening. Overall, the findings reveal future research pathways and provide support for the planning and integration of vertiport infrastructure in UAM operations. Full article

Category management (CM) is crucial for optimising retailer–supplier partnerships via technological integration and data sharing. However, the role of CM in Saudi Arabia’s unique fast-moving consumer goods sector (FMCG) remains underexplored. This study aimed to answer the following research question: How do cloud-based inventory platforms and real-time data sharing improve forecasting accuracy and inventory turnover for retailer–supplier CM partnerships in Saudi Arabia’s FMCG sector? A systematic review of 87 studies from the Web of Science and Scopus databases was conducted, followed by thematic analysis. The findings indicate that CM improves demand forecasting, inventory optimisation, and collaborative decision-making. Key implementation barriers include cultural resistance to data sharing, high technology costs for small and medium-sized enterprises, and infrastructural limitations. Success relies on phased technology adoption, relational data governance, and trust building that aligns with Saudi cultural norms. The study concludes that CM is essential for leveraging technology and data capabilities, and it offers a contextualised framework to overcome local barriers and support the achievement of Vision 2030 objectives. This study provides practical strategies for sector stakeholders to adopt high-impact, low-cost technology and a basis for future comparative studies in Gulf Cooperation Council markets. Full article

In recent years, the field of European funds for business development has generated significant interest in the academic literature, stimulated by European Union (EU) regulations and the implementation of business financing programs. This context has led to an increase in research on the impact and use of European funds, particularly in terms of support for economic development and infrastructure. This paper presents a bibliometric analysis, using topic modeling, to examine academic publications on the use and absorption of European funds and how they influence the business environment. Using a dataset of 74 publications indexed in the Clarivate Analytics Web of Science Core Collection, covering the period 2005–2024, the present study aims to identify the main authors, institutions, journals, and collaboration networks involved. It also analyzes research trends, dominant themes, and the countries with the largest contributions in this field, using Latent Dirichlet Allocation (LDA) and BERTopic analysis as a complement to the classical bibliometric approach. The thematic analysis reveals a thematic cohesion around entrepreneurship, EU structural funds, regional development, and innovation. In addition, there has been a significant annual increase in publications in this field, and through the use of thematic maps, word clouds, and collaboration networks, this study provides an overview of the evolution of research on the absorption of European funds and its impact on the business environment. These findings contribute both to deepening academic knowledge and to formulating more effective European policies for optimizing fund absorption and supporting the sustainable development of the business environment. Full article

In the context of global climate change and rapid urbanization, the urban heat island (UHI) effect has emerged as a critical issue impacting urban sustainability. This study analyzes 945 publications retrieved from the Web of Science Core Collection (2000–2025) and employs VOSviewer and Scimago Graphica to construct and visualize a knowledge map. The findings indicate that, since 2013, there has been a significant increase in research interest in utilizing green infrastructure (GI) to mitigate UHI, with China, the United States, and Europe leading international collaboration efforts. Keyword analysis reveals that early studies primarily focused on thermodynamic manifestations. Recent research has shifted toward more diverse topics, including artificial neural networks (ANNs), environmental justice, and public participation. By constructing a knowledge framework, this study clarifies how GI mitigates UHI while simultaneously promoting carbon reduction, enhancing health benefits, and supporting resilient governance. This research provides a comprehensive overview of the role of GI in mitigating UHI, offering theoretical insights and practical solutions for achieving integrated governance that combines climate resilience, biodiversity conservation, and social equity. These findings have significant theoretical and practical implications for advancing both UHI mitigation and sustainable development. Full article

The convergence of decentralized artificial intelligence (DAI), blockchain technology, and smart contracts is reshaping the design and governance of intelligent systems. As these technologies rapidly evolve, addressing privacy within their architecture, usage models, and associated risks has become increasingly critical. This systematic literature review examines architectural patterns, governance frameworks, real-world applications, and persistent challenges in DAI systems. It identifies prevailing designs such as federated learning integrated with consensus protocols, smart contract-based incentive mechanisms, and decentralized verification methods. Drawing from a diverse body of recent literature, the review highlights implementations across sectors, including healthcare, finance, IoT, autonomous systems, and intelligent infrastructure, each demonstrating significant contributions to privacy, security, and collaborative innovation. Despite these advancements, DAI systems face ongoing obstacles such as scalability limitations, privacy trade-offs, and difficulties with regulatory compliance. The review emphasizes the need for integrative governance approaches that balance transparency, accountability, incentive alignment, and ethical oversight. These elements are proposed as co-evolving pillars essential to establishing trustworthiness in decentralized AI ecosystems. This work offers a comprehensive review for understanding the current landscape and guiding the development of responsible and effective DAI systems in the Web3 era. Full article

Background: Type 2 diabetes mellitus (T2DM) is a major global public health challenge. Aerobic exercise (AE) can be a key strategy for non-pharmacological intervention in T2DM through multi-targeted modulation of glucose and lipid metabolism, inhibition of chronic inflammation, and reduction of oxidative stress. This study aims to investigate the current status of AE intervention in T2DM research and analyze its future evolution. Methods: Using the R-based bibliometric software package and the Java-based visualization software CiteSpace and VOSviewer, we analyzed the literature and cited references related to AE intervention in T2DM research included in the Web of Science Core Collection (WOSCC) and China National Knowledge Infrastructure (CNKI) from 2014 to 2024. Results: This study included a total of 882 relevant literature sources (488 of which were indexed in WOSCC and 394 in CNKI). From the perspective of research trends, the number of literature sources on AE interventions for T2DM has shown fluctuating changes over time. In terms of research output, the United States, China, and Canada are at the forefront. It is worth noting that, although China has a relatively high number of published papers, there is still a significant gap in terms of the depth of international collaboration and the presentation of results in top-tier journals. Among researchers, Dai Xia (China) and Riddell MC (Canada) are the scholars with the highest number of published articles in this field. Keyword analysis indicates that mechanisms such as oxidative stress, insulin resistance, inflammatory responses, and glucose metabolism disorders remain core research hotspots. Time-series analysis reveals that the research paradigm in this field has evolved from single exercise methods to comprehensive exercise prescription studies, and multi-dimensional intervention studies combining exercise, diet, and pharmacological interventions are emerging as new research frontiers. Conclusions: This study uses bibliometric methods to visualize and analyze the progress of AE in T2DM intervention research from a broader perspective, providing a scientific overview and macro-level predictions for the research landscape in this field. Full article

In the era of data elements, it is extremely necessary and practically important to analyze network characteristics and evolutionary trends in academic research collaboration in the field of data assets research, which can provide valuable insights for promoting deep cooperation of scholars and enhancing their collaborative efficiency. However, existing studies on data assets research rarely delve into key differentiating characteristics and core thematic priorities between Chinese and international samples of collaboration networks. Based on bibliometric methods and social network analysis, a systematic comparative analysis between Chinese collaboration networks and international collaboration networks is conducted via CiteSpace software by using core literature from the China National Knowledge Infrastructure (CNKI) and Web of Science Core Collection, developed by Clarivate Analytics (WoS). Through observation, we find that the number of publications in this field has reached a preliminary scale with distinct differences in research focus and collaborative features between cooperation networks in China (CNCs) and international cooperation networks (ICNs). In recent years, Chinese samples have primarily focused upon research themes related to data value realization, such as data rights confirmation, data assets accounting, and data trusts. The overall connectivity of CNCs seems relatively weak, and a stable core author group has not formed, while collaborations in CNCs are predominantly localized and short-term. In contrast, international samples in recent years have mainly addressed the contextual application of data assets, exhibiting a collaboration network characterized by multi-center, interdisciplinary, and cross-institutional synergy, while core authors in ICNs are closely interconnected and their connectivity and structure are generally stronger than those of CNCs. Full article

When there is an absence of disaster prevention measures, natural hazards can lead to disasters. An essential part of disaster risk management is the geospatial modeling of devastating hazards, where data sharing is of paramount importance in the context of early-warning systems. This research points out the usefulness of Spatial Data Infrastructures (SDIs) for disaster risk reduction through a literature review, focusing on the necessity of data unification and disposal. Initially, the principles of SDIs are presented, given the fact that this framework contributes significantly to the fulfilment of specific targets and priorities of the Sendai Framework for Disaster Risk Reduction 2015–2030. Thereafter, the challenges of SDIs are investigated in order to underline the main drawbacks stakeholders in emergency management have to come up against, namely the semantic misalignment that impedes efficient data retrieval, malfunctions in the interoperability of datasets and web services, the non-availability of the data in spite of their existence, and a lack of quality data, while also highlighting the obstacles of real case studies on national NSDIs. Thus, diachronic observations on disasters will not be made, despite these comprising a meaningful dataset in disaster mitigation. Consequently, the harmonization of national SDIs with international schemes, such as the Group on Earth Observations (GEO) and European Union’s space program Copernicus, and the usefulness of Artificial Intelligence (AI) and Machine Learning (ML) for disaster mitigation through the prediction of natural hazards are demonstrated. In this paper, for the purpose of disaster preparedness, real-world implementation barriers that preclude SDIs to be completed or deter their functionality are presented, culminating in the proposed future research directions and topics for the SDIs that need further investigation. SDIs constitute an ongoing collaborative effort intending to offer valuable operational tools for decision-making under the threat of a devastating event. Despite the operational potential of SDIs, the complexity of data standardization and coordination remains a core challenge. Full article

The intersection of green finance and artificial intelligence (AI) represents a rapidly emerging and high-impact research domain with the potential to reshape sustainable economic systems. This study presents a comprehensive bibliometric and network analysis aimed at mapping the scientific landscape, identifying research hotspots, and highlighting methodological trends at this nexus. A dataset of 268 peer-reviewed publications (2014–June 2025) was retrieved from the Web of Science Core Collection, filtered by the Business Economics category. Analytical techniques employed include Bibliometrix in R, VOSviewer, and science mapping tools such as thematic mapping, trend topic analysis, co-citation networks, and co-occurrence clustering. Results indicate an annual growth rate of 53.31%, with China leading in both productivity and impact, followed by Vietnam and the United Kingdom. The most prolific affiliations and authors, primarily based in China, underscore a concentrated regional research output. The most relevant journals include Energy Economics and Finance Research Letters. Network visualizations identified 17 clusters, with focused analysis on the top three: (1) Emission, Health, and Environmental Risk, (2) Institutional and Technological Infrastructure, and (3) Green Innovation and Sustainable Urban Development. The methodological landscape is equally diverse, with top techniques including blockchain technology, large language models, convolutional neural networks, sentiment analysis, and structural equation modeling, demonstrating a blend of traditional econometrics and advanced AI. This study not only uncovers intellectual structures and thematic evolution but also identifies underdeveloped areas and proposes future research directions. These include dynamic topic modeling, regional case studies, and ethical frameworks for AI in sustainable finance. The findings provide a strategic foundation for advancing interdisciplinary collaboration and policy innovation in green AI–finance ecosystems. Full article

Urban blue-green infrastructure (UBGI) is a comprehensive solution that balances environmental, social, and economic development objectives and has emerged as a critical approach for fostering urban resilience and sustainable development. This paper conducts a systematic bibliometric analysis of 975 academic articles published between 2000 and 2023 in the Web of Science Core Collection, focusing specifically on the ecosystem services associated with UBGI. Employing CiteSpace visualization technology, this study elucidates the major research trends, thematic clusters, and international collaboration patterns shaping this field. The research delves into the diverse range of ecosystem services provided by blue-green infrastructure and analyzes their contributions to urban well-being. Findings indicate that regulatory services—particularly climate regulation, biodiversity enhancement, and water resource management—have become central research foci within the contexts of urban green infrastructure (UGI), urban blue infrastructure (UBI), and UBGI. Co-citation and keyword analyses reveal that nature-based solutions, hybrid green–gray infrastructure, and the application of urban resilience frameworks are gaining increasing scholarly attention. By summarizing the evolutionary trajectory and priority directions of UBGI research, this study provides significant insights for future interdisciplinary research aimed at enhancing the supply of urban environmental ecosystem services. Full article

This strategic document outlines Bulgaria’s roadmap for modernizing its cartographic sector from 2025 to 2035, addressing the outdated geospatial infrastructure, lack of standardized digital practices, lack of coordinated digital infrastructure, outdated standards, and fragmented data management systems. The strategy was developed in accordance with the national methodology for strategic planning and through preliminary consultations with key stakeholders, including research institutions, business organizations, and public institutions. It aims to build a human-centered, data-driven geospatial framework aligned with global standards such as ISO 19100 and the EU INSPIRE Directive. Core components include: (1) modernization of the national geodetic system, (2) adoption of remote sensing and AI technologies, (3) development of interactive, web-based geospatial platforms, and (4) implementation of quality assurance and certification standards. A SWOT analysis highlights key strengths—such as existing institutional expertise—and critical challenges, including outdated legislation and insufficient coordination. The strategy emphasizes the need for innovation, regulatory reform, inter-institutional collaboration, and sustained investment. It ultimately positions Bulgarian cartography as a strategic contributor to national sustainable development and digital transformation. Full article

This study delivers a rigorous and in-depth bibliometric examination of 693 scholarly publications addressing the intersection of metaverse technologies and banking, retrieved from the Web of Science Core Collection. Through advanced scientometric tools, including VOSviewer and Bibliometrix, the research systematically unpacks the evolving intellectual and thematic contours of this interdisciplinary frontier. The co-occurrence analysis of keywords reveals a landscape shaped by seven core thematic clusters, encompassing immersive user environments, digital infrastructure, experiential design, and ethical considerations. Factorial analysis uncovers a marked bifurcation between experience-driven narratives and technology-centric frameworks, with integrative concepts such as technology, information, and consumption serving as conceptual bridges. Network visualizations of authorship patterns point to the emergence of high-density collaboration clusters, particularly centered around influential contributors such as Dwivedi and Ooi, while regional distribution patterns indicate a tri-continental dominance led by Asia, North America, and Western Europe. Temporal analysis identifies a significant surge in academic interest beginning in 2022, aligning with increased institutional and commercial experimentation in virtual financial platforms. Our findings argue that the incorporation of metaverse paradigms into banking is not merely a technological shift but a systemic transformation in progress—one that blurs the boundaries between speculative innovation and tangible implementation. This work contributes foundational insights for future inquiry into digital finance systems, algorithmic governance, trust architecture, and the wider socio-economic consequences of banking in virtualized environments. Whether a genuine leap toward financial evolution or a sophisticated illusion, the metaverse in banking must now be treated as a systemic phenomenon worthy of serious scrutiny. 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