Search Results (3,559)

Plant-based diets are increasingly attracting attention as they play a significant role in human health and environmental sustainability and are believed to be key components of sustainable food systems. In the present study, both pros and cons of the adoption of plant-based diets are analyzed using a bibliometric method integrated with a qualitative examination of the scientific literature. For the bibliometric study, Bibliometrix software was utilized, examining 3245 scientific articles, downloaded from the Scopus database, and printed between the years 1957 and 2025. The analyses were conducted using R software, version 4.4.1, with access to the Bibliometrix package, version 4.1. The results indicate a remarkable rise, in the last two decades, in the scholarly focus on the influence of plant-based diets on the individual’s health condition as well as the environment. Keyword co-occurrence studies and international collaborations demonstrate a dominance of research focus in both the United States and Europe, with significant contributions from the Asia–Pacific region. Furthermore, the current work offers qualitative identification of the benefits of plant diets from various perspectives like nutritional, economic, ecological, and cultural. It also explores the main dissuaders from adhering to these diets, including perceived nutritional hazards, cost perceptions, low availability, and social prohibitions. Findings emphasize that, in spite of all the barriers, plant food-based diets have a wide-ranging ability to provide tangible benefits at both the individual and population levels, and documented in the scientific literature are recommendations of expert-led education programs, economic incentives, and judiciously framed public policies to overcome these barriers and to make this transition possible towards sustainable food choices. Findings provide a comprehensive understanding of the current lines of inquiry and stage the subsequent work on how to motivate sustainability among the general population. Full article

Phytochemistry serves as a vital bridge between traditional medicinal knowledge and modern scientific research, with important implications for pharmaceutical and industrial applications. This review offers an updated and integrated perspective on Chelidonium majus (greater celandine), focusing on its isoquinoline alkaloids—the principal bioactive constituents—alongside emerging phytochemicals (e.g., lignanamides, polyphenols). Detailed biosynthetic pathways of isoquinoline alkaloids are described, tracing their formation from the shikimate pathway to multiple structural subclasses. Reported biological activities include anticancer, antioxidant, anti-inflammatory, antimicrobial, antiviral, and immunomodulatory effects. A bibliometric analysis was conducted using VOSviewer software (Scopus dataset, 2015–2025), enabling the identification of major research themes and temporal trends. These research tools supported a structured and data-driven overview of the current scientific landscape. However, additional studies are needed to optimize its therapeutic use while ensuring efficacy and safety. Full article

Digital twin technology is reshaping modern agriculture. Digital twins are the virtual replicas of real-world farming systems, which are continuously updated with real-time data, and are revolutionizing the monitoring, simulation, and optimization of agricultural processes. The literature on agricultural digital twins is multidisciplinary, growing rapidly, and often fragmented across disciplines, which lacks well-curated documentation. A bibliometric analysis includes thematic content analysis and science mapping, which provides research trends, gaps, thematic landscape, and key contributors in this continuously evolving and emerging field. Therefore, in this study, we conducted a bibliometric review that included collecting bibliometric data via keyword search strategies on popular scientific databases. The data was further screened, processed, analyzed, and visualized using bibliometric tools to map research trends, landscapes, collaborations, and themes. Key findings show that publications have grown exponentially since 2018, with an annual growth rate of 27.2%. The major contributing countries were China, the USA, the Netherlands, Germany, and India. We observed a collaboration network with distinct geographic clusters, with strong intra-European ties and more localized efforts in China and the USA. The analysis identified seven major research theme clusters revolving around precision farming, Internet of Things integration, artificial intelligence, cyber–physical systems, controlled-environment agriculture, sustainability, and food system applications. We observed that core technologies, such as sensors, artificial intelligence, and data analytics, have been extensively explored, while identifying gaps in research areas. The emerging interests include climate resilience, renewable-energy integration, and supply-chain optimization. The observed transition from task-specific tools to integrated, system-level approaches underline the growing need for adaptive, data-driven decision support. By outlining research trends and identifying strategic research gaps, this review offers insights into leveraging digital twins to improve productivity, sustainability, and resilience in global agriculture. 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

Background: The growing environmental crisis, driven by population increases and rapid urban development, has amplified the need for sustainable and ecological design approaches. Biomimicry, drawing inspiration from nature’s forms, processes, and systems, offers promising solutions in this context. Particularly in landscape architecture, biomimicry supports the integration of esthetics with ecological responsibility. Methods: This study presents a bibliometric analysis using the Scopus database to quantitatively assess the relationship between biomimicry and sustainable/ecological design within landscape architecture. A stepwise search strategy was applied, and the Biblioshiny tool within the version 4.2.1 of Bibliometrix package in RStudio 2024.04.1+748 software was used for data analysis and visualization. Results: A total of 1634 documents were identified under the keyword “biomimicry,” among which 210 addressed sustainability and/or ecological design. However, only three studies explicitly connected biomimicry, sustainable/ecological principles, and landscape architecture. Keyword trends, publication years, and country-level contributions were also examined. Conclusions: The findings highlight a substantial gap in the literature on the integration of biomimicry within sustainable landscape architecture. This underscores the need for further interdisciplinary research and practice that incorporates biomimetic principles to promote ecological innovation in landscape design. Full article

This study presents a comprehensive bibliometric analysis of research publications on artificial intelligence (AI) applications in higher education, with a particular focus on student performance-related studies. Drawing on 1431 documents retrieved from the Web of Science (WoS) Core Collections, advanced bibliometric tools, such as VOSViewer (1.6.19) and Biblioshiny, were used to explore research trends, citation networks, co-authorship patterns, and keyword co-occurrences. The results revealed an increase in AI-related educational research during the COVID-19 pandemic, reflecting the rise in the reliance on AI for enhancing learning outcomes in times of educational disruption. The findings also indicated that the research focus is gradually moving towards using AI for educational assessment, emphasizing the importance of accurate and data-driven evaluation of student performance. The co-occurrence of keywords and citation analyses confirmed that machine learning, deep learning, and predictive modeling are among the dominant AI techniques applied to assess and predict student outcomes. Furthermore, the study highlights AI’s potential in identifying learning gaps and enabling personalized interventions, allowing educators to address students’ specific needs more effectively. This new trend suggests a growing recognition of AI’s role in refining educational methodologies and improving performance evaluations at the tertiary level. Full article

This review investigates how process parameters and material choices influence the mechanical performance of parts produced by material extrusion additive manufacturing, with a particular focus on Material Extrusion (ME). Through a systematic bibliometric analysis of literature between 2015 and 2025, the study identifies key factors affecting mechanical strength, anisotropy, and structural reliability, including printing temperature, speed, orientation, layer thickness, and interlayer bonding. Emphasis is placed on emerging techniques such as 4D printing, fiber-reinforced composites, and novel monitoring methods like real-time vibration sensing and thermal imaging, which offer promising pathways to improve part performance and process stability. Three research questions guide the analysis: (1) how printing parameters affect micro- to macrostructure and failure behavior, (2) how optimization strategies enhance part quality, and (3) how material and process selection aligns with functional requirements. The review highlights both advances and persistent limitations in process control, material compatibility, and anisotropic strength. It concludes with a call for further integration of predictive modeling, hybrid material systems, and closed-loop process monitoring to unlock the full potential of additive manufacturing in high-performance engineering applications. Full article

In the context of the rapid digitalization of higher education, proactive artificial intelligence (AI) agents embedded within multi-agent systems (MAS) offer new opportunities for personalized learning, improved quality of education, and alignment with sustainable development goals. This study aims to analyze how such AI solutions are perceived by students at Narxoz University (Kazakhstan) prior to their practical implementation. The research focuses on four key aspects: the level of student trust in AI agents, perceived educational value, concerns related to privacy and autonomy, and individual readiness to use MAS tools. The article also explores how these solutions align with the Sustainable Development Goals—specifically SDG 4 (“Quality Education”) and SDG 8 (“Decent Work and Economic Growth”)—through the development of digital competencies and more equitable access to education. Methodologically, the study combines a bibliometric literature analysis, a theoretical review of pedagogical and technological MAS concepts, and a quantitative survey (n = 150) of students. The results reveal a high level of student interest in AI agents and a general readiness to use them, although this is tempered by moderate trust and significant ethical concerns. The findings suggest that the successful integration of AI into educational environments requires a strategic approach from university leadership, including change management, trust-building, and staff development. Thus, MAS technologies are viewed not only as technical innovations but also as managerial advancements that contribute to the creation of a sustainable, human-centered digital pedagogy. Full article

Background/Objectives: Despite advances in diagnosis and treatment, colorectal cancer (CRC) remains one of the most prevalent and challenging malignancies worldwide. The dysregulation of microRNAs (miRNAs) has emerged as a critical factor in CRC onset, progression, and therapeutic resistance. This study aims to provide an overview of global research trends on miRNAs in CRC, (i) identifying the most studied miRNAs, (ii) exploring under-investigated areas, and (iii) highlighting emerging themes and potential future directions. Methods: To assess the evolution of the global miRNA–CRC research trends, we conducted a bibliometric analysis of 828 CRC–miRNA-focused articles published between 2008 and 2024, sourced from the Scopus database. Bibliometric mapping was performed using the R/Bibliometrix package and by leveraging a customized Python-based pipeline, which is useful for extracting and validating miRNA identifiers (miRNA IDs) based on the miRBase database. This miRNA ID-related approach enabled us to systematically identify the most frequently studied miRNAs over time while highlighting underexplored miRNA. Results: The analysis revealed a substantial and accelerating publication growth rate, delineating three major phases in CRC–miRNA research. China emerged as the leading contributor in terms of the publication volume. miR-21, miR-34a, and miR-195-5p were among the most frequently studied miRNAs, underscoring their relevance to CRC biology and therapy. Keyword and citation analyses identified key thematic areas, such as cell proliferation, epithelial–mesenchymal transition, and chemoresistance, especially to oxaliplatin and 5-fluorouracil. Emerging research frontiers included ferroptosis, ceRNA networks, and exosome-mediated miRNA transport. An analysis of the collaborations indicated strong intra-national collaborations, with room for expanding international research networks. Conclusions: This study provides an in-depth bibliometric landscape of the CRC-related miRNA research by highlighting influential studies and journals while identifying gaps and underexplored topics. These insights offer valuable guidance for future translational and clinical research on this topic. Full article

Tokamak technology, as the cornerstone of nuclear fusion energy, holds immense potential in achieving efficient plasma confinement and high energy densities. To comprehensively map the rapidly evolving landscape of this field, this study employs bibliometric analysis to systematically examine the research and development trends of tokamak technology from 2014 to 2024. The data are drawn from 7702 academic publications in the Scopus database, representing a global research effort. Additionally, the study incorporates 2299 tokamak-related patents from Google Patents over the same period, analyzing their technological trends to highlight the growing significance of tokamak devices. Using the R language and the Bibliometric package, the analysis explores research hotspots, institutional influences, and keyword evolution. The results reveal a multifaceted global landscape: China leads in publication output, and the United States maintains a leading role in citation impacts and technological innovation, with other notable contributions from Germany, Japan, South Korea, and various European countries. Patent trend analysis further reveals the rapid expansion of tokamak applications, particularly with significant innovations in high-temperature superconducting magnets and plasma control technologies. Nevertheless, the study identifies major challenges in the commercialization process, including plasma stability control, material durability, and the sustainability of long-term operations. To address these, the study proposes concrete future directions, emphasizing international collaboration and interdisciplinary integration. These efforts are crucial in accelerating tokamak commercialization, thereby providing a strategic roadmap for researchers, policymakers, and industry stakeholders to advance the global deployment of clean energy solutions. Full article

Metallic multi-material structures are heterogeneous structures characterized by changing composition, microstructures, and site-specific characteristics, advantageous for numerous applications where multifunctionality is desired. Metallic multi-material structures are known as bimetallic structures (BSs), which are functionally graded materials (FGMs). In recent years, wire-arc additive manufacturing (WAAM) advanced as a promising additive manufacturing process to realize the fabrication of these structures due to its high deposition rate, cost-effectiveness, and material utilization efficiency. This review presents a comprehensive overview of the recent progress, processing strategies, and scientific challenges in WAAM of multi-material structures. The paper begins with an introduction to multi-material structures, followed by a bibliometric analysis of the current research landscape. Conventional and additive manufacturing fabrication approaches are presented. The review highlights key developments in processing strategies and critically evaluates research studies on WAAM of BS and FGMs. Major scientific challenges, including porosity, lack of fusion, residual stresses, cracking, material compatibility, and brittle intermetallic phase formation, are critically analyzed. Additionally, modeling, simulation, and process automation issues are discussed as barriers to industrial-scale implementation. The paper concludes with an outlook on future research directions to address existing challenges and accelerate the adoption of WAAM for complex multi-material components. Full article

Background/Objectives: Despite an increase in the number of women medical graduates, gender disparities persist in academic anaesthesiology. Women in medical science face challenges in publications, research funding, editorial board membership, and peer review, and they remain under-represented, particularly in senior authorship and leadership positions. Methods: This repeated cross-sectional bibliometric analysis examined global trends and cross-country differences in the representation of women as first, co-, and senior authors of peer-reviewed articles published in five high-impact anaesthesiology journals over three decades, with a focus on developments in recent years. Gender was assigned to authors’ first names algorithmically in two steps (Gender API and NamSor). Results: A total of 7571 publications were analysed, comprising 37,738 authors. Women constituted 11,732 (31.09%) authorships in total, and men consistently accounted for a substantial majority among authors (p < 0.001). Despite a significant overall increase in authorship by women—peaking in 2022 at 590 (36.88%) first authors, 2245 (37.85%) co-authors, and 402 (28.05%) senior authors (all p < 0.001)—stagnation was observed in recent years, with no significant changes for first and co-authors after 2016 (p > 0.05). Country-level analysis revealed few significant differences, with Japan consistently reporting the lowest percentages of women authors. Conclusions: This study underscores persistent gender disparities in academic anaesthesiology, despite a moderate increase in authorship by women over three decades. Gender disparity remains a global issue, and the recent stagnation highlights the necessity for more comprehensive efforts and innovative strategies to foster a more inclusive research community in academic anaesthesiology. Full article

Background: The ageing population demands effective health solutions for the elderly. Wearable devices offer real-time monitoring and early alerts, but a comprehensive review of research in this field is lacking. This study uses bibliometric methods to analyse trends and advances in wearable devices for the elderly. Methods: Literature from 2014 to 2024 was retrieved from the Web of Science Core Collection using keywords related to the elderly and wearable devices. A total of 1015 English-language papers were analysed using tools including CiteSpace, VOSviewer, and R-Bibliometrix. Results: The annual growth rate of publications was 7.65%, with research increasing from 4 in 2014 to 1015 in 2024. Major contributors were the United States and China, with key authors including Bijan Najafi and Lynn Rochester. Research shifted from fall detection and activity monitoring to heart rate variability, balance, and AI integration. Key themes included “digital health”, “wearable technology”, and “cardiac health monitoring”. Conclusions: Research on wearable devices for the elderly is growing rapidly. Future studies should focus on multimodal sensor fusion, AI-enhanced analytics and personalised health interventions, and long-term, real-world validation of wearable solutions to improve elderly health management. Full article

This study aims to identify and categorize barriers to the success of Data Science (DS) projects through a systematic literature review combined with quantitative methods of analysis. PRISMA is used to conduct a literature review to identify the barriers in the existing literature. With techniques from bibliometrics and network science, the barriers are hierarchically clustered using the Jaccard distance as a measure of dissimilarity. The review identified 27 barriers to the success of DS projects from 26 studies. These barriers were grouped into six thematic clusters: people, data and technology, management, economic, project, and external barriers. The barrier “insufficient skills” is the most frequently cited in the literature and the most frequently considered critical. From the quantitative analysis, the barriers “insufficient skills”, “poor data quality”, “data privacy and security”, “lack of support from top management”, “insufficient funding”, “insufficient ROI or justification”, “government policies and regulation”, and “inadequate, immature or inconsistent methodology” were identified as the most central in their cluster. Full article

Real-time hybrid testing is an efficient testing technique that combines physical testing with numerical calculations to jointly evaluate the performance of complex structures under different external excitations. This study conducted a quantitative bibliometric analysis of 121 RTHT articles published between 1992 and 2025. The survey revealed that only 8% of all test applications addressed soil–structure interaction systems, merely 3% employed finite element models exceeding 10,000 DOFs, and more than 90% of the interface equations were still based on lumped mass assumptions. An RTHT framework based on the branch modal method was proposed to overcome these limitations. Within this framework, the numerical soil substructure was reduced from thousands of DOFs to approximately one hundred DOFs, with a verified peak acceleration error of below 7%. This approach offers a practical reference for real-time hybrid testing of complex systems. Full article