Search Results (351)

The balance between exploration and exploitation is a fundamental element in the design and performance of bio-inspired optimization algorithms. However, to date, its conceptual evolution and its treatment in the scientific literature have not been systematically characterized from a bibliometric approach. This study performs an exhaustive analysis of the scientific production on the balance between exploration and exploitation using records extracted from the Web of Science (WoS) database. The processing and analysis of the data were carried out through the combined use of Bibliometrix (R package) and VOSviewer, tools that made it possible to quantify productivity, map collaborative networks, and visualize emerging thematic trends. The results show a sustained growth in the volume of publications over the last decade, as well as the consolidation of academic collaboration networks and the emergence of new thematic lines in the field. In particular, metaheuristic algorithms have demonstrated a significant and growing impact, constituting a fundamental pillar in the advancement and methodological diversification of the exploration–exploitation balance. This work provides a quantitative framework and a structured view of the evolution of research, identifies the main actors and trends, and raises opportunities for future lines of research in the field of optimization using metaheuristics, the most prominent instantiation of bio-inspired optimization algorithms. Full article

With the accelerating globalization and rapid development of science and technology, scientific collaboration has become a key driver of knowledge production, yet its patterns vary significantly across disciplines. This study aims to explore the disciplinary differences in scholars’ scientific collaboration patterns and their underlying mechanisms. Data were collected from the China National Knowledge Infrastructure (CNKI) database, covering papers from four disciplines: mathematics, mechanical engineering, philosophy, and sociology. Using social network analysis, we examined core network metrics (degree centrality, neighbor connectivity, clustering coefficient) in collaboration networks, analyzed collaboration patterns across scholars of different academic ages, and compared the academic age distribution of collaborators and network characteristics across career stages. Key findings include the following. (1) Mechanical engineering exhibits the highest and most stable clustering coefficient (mean 0.62) across all academic ages, reflecting tight team collaboration, with degree centrality increasing fastest with academic age (3.2 times higher for senior vs. beginner scholars), driven by its reliance on experimental resources and skill division. (2) Philosophy shows high degree centrality in early career stages (mean 0.38 for beginners) but a sharp decline in clustering coefficient in senior stages (from 0.42 to 0.17), indicating broad early collaboration but loose later ties due to individualized knowledge production. (3) Mathematics scholars prefer collaborating with high-centrality peers (higher neighbor connectivity, mean 0.51), while sociology shows more inclusive collaboration with dispersed partner centrality. Full article

This study analyzes the relationship between ergonomic and psychosocial risk factors and labor productivity using a bibliometric approach through a general analysis and one that includes inclusion criteria such as English language, open access, and primary research publications to identify only those articles that explicitly address the relationship between ergonomic and psychosocial risk factors and labor productivity. It is recognized that both physical and psychosocial conditions of the work environment directly influence workers’ health and organizational performance. For this purpose, a bibliometric review was conducted in academic databases, including Scopus, Web of Science, ScienceDirect, and Taylor & Francis, resulting in the selection of 4794 relevant articles for general analysis. Additionally, 116 relevant articles were selected based on the inclusion criteria. Tools and methodologies, such as Rayyan, Excel, VOSviewer 1.6.20, and PRISMA, were used to classify the studies and identify trends, collaboration networks, and geographical distribution. The results reveal a sustained growth in scientific production, with clusters on occupational safety and health, work environment factors, and the characteristics of the population, approach, and methodologies used in the studies. Likewise, Procedia Manufacturing, International Journal of Occupational Safety and Ergonomics, and Ergonomics stand out as the main sources of publication, while countries such as Sweden, Poland, and the United States lead the scientific production in this field. In addition, the network of co-occurrence of keywords evidences a comprehensive approach that articulates physical or ergonomic and psychosocial risk factors with organizational performance, while the network of authors shows consolidated collaborations and studies focused on analyzing the relationship between physical demands and musculoskeletal disorders from advanced ergonomic approaches. 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

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

Unmanned Aerial Vehicle Remote Sensing (UAV-RS) has emerged as a transformative technology in high-resolution Earth observation, with widespread applications in precision agriculture, ecological monitoring, and disaster response. However, a systematic understanding of its scientific evolution and structural bottlenecks remains lacking. This study collected 4985 peer-reviewed articles from the Web of Science Core Collection and conducted a comprehensive scientometric analysis using CiteSpace v.6.2.R4, Origin 2022, and Excel. We examined publication trends, country/institutional collaboration networks, keyword co-occurrence clusters, and emerging research fronts. Results reveal an exponential growth in UAV-RS research since 2015, dominated by application-driven studies. Hotspots include vegetation indices, structure from motion modeling, and deep learning integration. However, foundational challenges—such as platform endurance, sensor coordination, and data standardization—remain underexplored. The global collaboration network exhibits a “strong hubs, weak bridges” pattern, limiting transnational knowledge integration. This review highlights the imbalance between surface-level innovation and deep technological maturity and calls for a paradigm shift from fragmented application responses to integrated systems development. Our findings provide strategic insights for researchers, policymakers, and funding agencies to guide the next stage of UAV-RS evolution. Full article

Radon anomalies have long been explored as potential geochemical precursors to seismic activity due to their responsiveness to subsurface stress variations. However, before this study, the scientific progression of this research domain had not been systematically examined through a quantitative lens. This study presents a comprehensive bibliometric analysis of 379 articles published between 1977 and 2025 and indexed in Scopus and Web of Science. Utilizing the Bibliometrix R-package and its Biblioshiny interface, the analysis investigates temporal publication trends, leading countries, institutions, international collaboration networks, and thematic evolution. The results reveal a marked increase in research output since 2010, with China, India, and Italy emerging as the most prolific contributors. Thematic mapping indicates a shift from conventional geochemical monitoring toward the integration of artificial intelligence techniques, such as decision trees and neural networks, for anomaly detection and predictive modeling. Notwithstanding this methodological evolution, core research themes remain centered on radon concentration monitoring and the analysis of environmental parameters. Overall, the findings highlight the coexistence of traditional and emerging approaches, emphasizing the importance of standardized methodologies and interdisciplinary collaboration. This bibliometric synthesis provides strategic insights to inform future research and strengthen the role of radon monitoring in seismic early warning systems. Full article

With the ongoing advancement of industrialization and rapid urbanization, the emission of volatile organic compounds (VOCs) has increased significantly. As key precursors of PM_2.5 and ozone formation, VOCs pose a growing threat to the health of ecosystems. Due to their complex and dynamic transformation processes across air, water, and soil media, the ecological risks associated with VOCs have attracted increasing attention from both the scientific community and policy-makers. This study systematically reviews the core literature on the ecological impacts of VOCs published between 2005 and 2024, based on data from the Web of Science and Google Scholar databases. Utilizing three bibliometric tools (CiteSpace, VOSviewer, and Bibliometrix), we conducted a comprehensive visual analysis, constructing knowledge maps from multiple perspectives, including research trends, international collaboration, keyword evolution, and author–institution co-occurrence networks. The results reveal a rapid growth in the ecological impact of VOCs (EIVOCs), with an average annual increase exceeding 11% since 2013. Key research themes include source apportionment of air pollutants, ecotoxicological effects, biological response mechanisms, and health risk assessment. China, the United States, and Germany have emerged as leading contributors in this field, with China showing a remarkable surge in research activity in recent years. Keyword co-occurrence and burst analyses highlight “air pollution”, “exposure”, “health”, and “source apportionment” as major research hotspots. However, challenges remain in areas such as ecosystem functional responses, the integration of multimedia pollution pathways, and interdisciplinary coordination mechanisms. There is an urgent need to enhance monitoring technology integration, develop robust ecological risk assessment frameworks, and improve predictive modeling capabilities under climate change scenarios. This study provides scientific insights and theoretical support for the development of future environmental protection policies and comprehensive VOCs management strategies. Full article

Background/Objectives: Despite advancements in surgery, esophagectomy remains one of the most challenging and complex gastrointestinal surgical procedures, burdened by significant perioperative morbidity and mortality rates, as well as high financial costs. Recognizing the need for standardized care provided by a multidisciplinary healthcare team, the EUropean PErioperative MEdical Networking (EUPEMEN) initiative developed a dedicated protocol for perioperative care of patients undergoing esophagectomy, aiming to enhance recovery, reduce morbidity, and homogenize care delivery across European healthcare systems. Methods: Developed through a multidisciplinary European collaboration of five partners, the protocol incorporates expert consensus and the latest scientific evidence. It addresses the entire perioperative pathway, from preoperative preparation to hospital discharge and postoperative recovery, emphasizing patient-centered care, risk mitigation, and early functional restoration. Results: The implementation of the EUPEMEN esophagectomy protocol is expected to improve patient outcomes through a day-by-day structured prehabilitation plan, meticulous intraoperative management, and proactive postoperative rehabilitation. The approach promotes reduced postoperative complications, earlier return to oral intake, and shorter hospital stays, while supporting multidisciplinary coordination. Conclusions: The EUPEMEN protocol for esophagectomy provides a comprehensive guideline framework for optimizing perioperative care in esophageal surgery. In addition, it serves as a practical guide for healthcare professionals committed to advancing surgical recovery and standardizing clinical practice across diverse care environments across Europe. Full article

The significant burden of polypharmacy in clinical settings contrasts sharply with the narrow research focus on drug–drug interactions (DDIs), revealing an important gap in understanding the complexity of real-world multi-drug regimens. The present study addresses this gap by conducting a high-resolution, multidimensional bibliometric and network analysis of 19,151 DDI publications indexed in the Web of Science Core Collection (1975–2025). Using advanced tools, including VOSviewer version 1.6.20, Bibliometrix 5.0.0, and AI-enhanced terminology normalization, global research trajectories, knowledge clusters, and collaborative dynamics were systematically mapped. The analysis revealed an exponential growth in publication volume (from 55 in 1990 to 1194 in 2024), with output led by the United States and a marked acceleration in Chinese contributions after 2015. Key pharmacological agents frequently implicated in DDI research included CYP450-dependent drugs such as statins, antiretrovirals, and central nervous system drugs. Thematic clusters evolved from mechanistic toxicity assessments to complex frameworks involving clinical risk management, oncology co-therapies, and pharmacokinetic modeling. The citation impact peaked at 3.93 per year in 2019, reflecting the increasing integration of DDI research into mainstream areas of pharmaceutical science. The findings highlight a shift toward addressing polypharmacy risks in aging populations, supported by novel computational methodologies. This comprehensive assessment offers insights for researchers and academics aiming to navigate the evolving scientific landscape of DDIs and underlines the need for more nuanced system-level approaches to interaction risk assessment. Future studies should aim to incorporate patient-level real-world data, expand bibliometric coverage to underrepresented regions and non-English literature, and integrate pharmacogenomic and time-dependent variables to enhance predictive models of interaction risk. Cross-validation of AI-based approaches against clinical outcomes and prospective cohort data are also needed to bridge the translational gap and support precision dosing in complex therapeutic regimens. Full article

The agricultural products trade network is essentially a complex adaptive system formed by nonlinear interactions between countries. Based on the complex system theory, this study reveals the dynamic self-organization law of the RCEP regional agricultural products trade network by using the panel data of RCEP agricultural products export trade from 2000 to 2023, combining social network analysis (SNA) and the temporal exponential random graph model (TERGM). The results show the following: (1) The RCEP agricultural products trade network presents a “core-edge” hierarchical structure, with China as the core hub to drive regional resource integration and ASEAN countries developing into secondary core nodes to deepen collaborative dependence. (2) The “China-ASEAN-Japan-Korea “riangle trade structure is formed under the RCEP framework, and the network has the characteristics of a “small world”. The leading mode of South–South trade promotes the regional economic order to shift from the traditional vertical division of labor to multiple coordination. (3) The evolution of trade network system is driven by multiple factors: endogenous reciprocity and network expansion are the core structural driving forces; synergistic optimization of supply and demand matching between economic and financial development to promote system upgrading; geographical proximity and cultural convergence effectively reduce transaction costs and enhance system connectivity, but geographical distance is still the key system constraint that restricts the integration of marginal countries. This study provides a systematic and scientific analytical framework for understanding the resilience mechanism and structural evolution of regional agricultural trade networks under global shocks. Full article

Scientific knowledge and international collaboration are critical to achieving the Sustainable Development Goals (SDGs). This study conducts a large-scale bibliometric analysis of 49.4 million publications indexed in the Web of Science (1945–2023) related to the SDGs, with a specific focus on SDG 3 (Good Health and Well-Being). Since 1992, SDG 3 has accounted for 58% of SDG-related scientific output. Using K-means clustering and network analysis, we classified countries/regions by research productivity and mapped core–periphery collaboration structures. Results reveal a sharp concentration: the United States, China, England, and Germany account for 51.65% of publications. In contrast, the group composed of the 195 least productive countries and territories accounts for approximately 5% of the total scientific output on the SDGs, based on the same clustering method. Collaboration patterns mirror this inequality, with 84.97% of partnerships confined to the core group and only 2.81% involving core–periphery cooperation. These asymmetries limit the capacity of developing regions to generate health research aligned with local needs, constraining equitable progress toward SDG 3. Expanding scientific cooperation, fostering North–South and South–South collaborations, and ensuring equitable research funding are essential to promote inclusive knowledge production and support sustainable global health. Full article

This research presents a comprehensive scientometric analysis of Entrepreneurial Orientation (EO), a fundamental concept in strategic management and business performance. Through a bibliometric approach, 4314 articles indexed in the Web of Science from 1975 to 2024 were analyzed using advanced network analysis tools such as VOSviewer to examine the evolution of scientific production, citations, authors, journals, institutions, and the most influential countries in the field. The findings reveal an exponential growth in “EO” research over the past decades, with a high concentration of scientific output in the last eight years. The United States leads in publication volume and citations, followed by other countries with an increasing contribution. Co-authorship patterns and academic collaboration clusters have been identified, consolidating key research lines that link “EO” with innovation, market orientation, and business performance. This study provides a comprehensive perspective on the evolution of “EO” research, offering valuable insights for academics, policymakers, and professionals interested in new theoretical directions and practical applications that foster knowledge development and business competitiveness. Full article

Due to the limitations of its technology and theory, the traditional traffic control system has been unable to adapt to the needs of new technology and traffic development and needs to be reformed and reconstructed. From the national scientific and technological research and development plan to the traffic control system development projects of relevant enterprises, the common problem is that the advanced signal control system plays an insufficient role in practical application. The existing signal control system excessively relies on the use of IT technology but ignores the basic theory of traffic control and the essential consideration of the traffic environment and optimal regulation of road traffic flow, which greatly limits the scientific and practical value of a traffic control system in China. This narrative review analyzes recent developments and emerging trends in urban traffic control technologies through literature synthesis spanning 2009–2025. With the rapid and large-scale development and application of new transportation technologies such as vehicle–infrastructure networking, vehicle–infrastructure collaboration, and automatic driving, the real-time interaction between the traffic controller and the controlled party has new support. Given these technological advances, there is an urgent need to address the limitations of existing traffic signal control systems. Transportation technology development must leverage rich traffic control interaction conditions and comprehensive data to create next-generation systems. These new traffic optimization control systems should demonstrate high refinement, precision, better responsiveness, and enhanced intelligence. This paper can play a key role and influence for China to lead the development of urban road traffic control systems in the future. The promotion and application of the new generation of urban road traffic signal optimization control systems will improve the efficiency of the road network to a greater extent, reduce operating costs, prevent and alleviate road traffic congestion, and reduce energy consumption and emissions. At the same time, it will also provide the entry point and technical support for the development of vehicle–infrastructure networking and coordination and the automatic driving industry. Full article

Extreme weather events pose increasing risks to air transport operations, affecting flight safety, scheduling, and infrastructure resilience. This paper provides a comprehensive bibliometric analysis of scientific literature addressing the impacts of extreme weather on aviation, based on 1000 documents retrieved from the Web of Science Core Collection (2010–2024). Using VOSviewer software, keyword co-occurrence, overlay visualization, co-authorship networks, and citation analyses were conducted. Results revealed a clear thematic shift from environmental impact assessments toward research emphasizing operational resilience, technological adaptation, and mitigation strategies. Collaboration networks highlighted strong international cooperation, particularly among institutions in the United States, Germany, and the United Kingdom, with growing contributions from emerging research regions. Highly cited studies predominantly focused on emissions modeling and operational mitigation measures. Despite notable advances, the field remains fragmented and geographically uneven, underscoring the need for broader interdisciplinary integration and empirical validation of adaptation strategies. This paper offers a systematic overview of the evolving research landscape and identifies critical directions for future efforts to enhance the resilience and sustainability of global air transport systems under increasing climatic volatility. Full article