Search Results (2,398)

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

The use of Internet of Things (IoT) for sports innovation has transformed the way athletes train, compete, and recover in any sports activity. This study performs a bibliometric analysis to examine research trends, collaborations, and publications in the realm of IoT and Sports. Our analysis included 780 Scopus articles and 150 WoS articles published during 2012–2025, and duplicates were removed. We analyzed and visualized the bibliometric data using R version 3.6.1, VOSviewer version 1.6.20, and the bibliometrix library. The study provides insights from a bibliometric analysis, showcasing the allocation of topics, scientific contributions, patterns of co-authorship, prominent authors and their productivity over time, notable terms, key sources, publications with citations, analysis of citations, source-specific citation analysis, yearly publication patterns, and the distribution of research papers. The results indicate that China and India have the leading scientific production in the development of IoT and Sports research, with prominent authors like Anton Umek, Anton Kos, and Emiliano Schena making significant contributions. Wearable technology and wearable sensors are the most trending topics in IoT and Sports, followed by medical sciences and artificial intelligence paradigms. The analysis also emphasizes the importance of open-access journals like ‘Journal of Physics: Conference Series’ and ‘IEEE Access’ for their contributions to IoT and Sports research. Future research directions focus on enhancing effective, lightweight, and efficient wearable devices while implementing technologies like edge computing and lightweight AI in wearable technologies. Full article

Ongoing interest in the intersection of spirituality and health has prompted a need for integrated research. This report proposes a distinct approach in a model that allows for successful and harmonious cross-fertilization within these latter two areas of interest. Our work is especially pertinent to inquiries around the role of spirituality in mental health, with special attention to chronic pain conditions. The latter have become an open channel for novel avenues to explore the field of spirituality-based interventions within the arena of psychological inquiry. To address this, the authors developed and implemented the Church and Academia Model, a prototype for an innovative collaborative research project, with the aim of exploring the role of devotional practices, and their potential to be used as therapeutic co-adjuvants or tools to enhance the coping skills of patients with chronic pain. Keeping in mind that the church presents a rich landscape for clinical inquiry with broad relevance for clinicians and society at large, we created a unique hybrid research model. This is a new paradigm that focuses on distinct and well-defined studies where the funding, protocol writing, study design, and implementation are shared by experts from both the pastoral and clinical spaces. A team of theologians, researchers, and healthcare providers, including clinical pain psychologists, built a coalition leveraging their respective skill sets. Each expert is housed in their own environs, creating a functional network that has proven academically productive and pastorally effective. Key outputs include the creation and validation of a new psychometric measure, the Pain-related PRAYER Scale (PPRAYERS), an associated bedside prayer tool and a full-scale dissemination strategy through journal publications and specialty society conferences. This collaborative prototype is also an ideal fit for integrated knowledge translation platforms, and it is a promising paradigm for future collaborative projects focused on spirituality and mental health. Full article

Energy harvesting systems (EHSs) are widely used to power wireless sensors. Piezoelectric harvesters have the advantage of producing an electric signal directly related to the exciting force and can thus be used to power condition monitoring sensors in dynamically loaded structures such as bridges. The need for such monitoring is exemplified by the fact that the condition of close to 25% of public roadway bridges in, e.g., Germany is not satisfactory. Stack-based piezoelectric energy harvesting systems (pEHSs) installed near bridge bearings could provide information about the traffic and dynamic loads on the one hand and condition-dependent changes in the bridge characteristics on the other. This paper presents an approach to co-optimizing the design of the mechanical and electrical components using a nonlinear solver. Such an approach has not been described in the open literature to the best of the authors’ knowledge. The mechanical excitation is estimated through a finite element simulation, and the electric circuitry is modeled in Simulink to account for the nonlinear characteristics of rectifying diodes. We use real traffic data to create statistical randomized scenarios for the optimization and statistical variation. A main result of this work is that it reveals the strong dependence of the energy output on the interaction between bridge, harvester, and traffic details. A second result is that the methodology yields design criteria for the harvester such that the energy output is maximized. Through the case study of an actual middle-sized bridge in Germany, we demonstrate the feasibility of harvesting a time-averaged power of several milliwatts throughout the day. Comparing the total amount of harvested energy for 1000 randomized traffic scenarios, we demonstrate the suitability of pEHS to power wireless sensor nodes. In addition, we show the potential sensory usability for traffic observation (vehicle frequency, vehicle weight, axle load, etc.). Full article

Urban areas are at the forefront in addressing global challenges such as climate change and biodiversity loss. Among the key responses are nature-based solutions, which are increasingly being integrated into policy frameworks but which require strong community engagement for their effective implementation. This paper presents the findings of surveys conducted within the Place Lab in Katowice, Poland, an initiative developed as part of an international project and used as a participatory tool for co-creating and implementing green infrastructure. The project applies both place-based and people-centred approaches to support European cities in their transition towards regenerative urbanism. Place Lab activities encourage collaboration between local authorities and residents, enhancing awareness and fostering participation in environmental initiatives. The survey data collected during the project allowed for the evaluation of changes in public attitudes and levels of engagement and for the identification of broader societal phenomena that may influence the implementation of nature-based solutions. The findings revealed, for instance, that more women were interested in supporting the project, that residents tended to be sceptical of governmental actions on climate change, and that views were divided on the trade-off between urban infrastructure such as parking and roads and the presence of green areas. Furthermore, questions of responsibility, awareness, and long-term commitment were frequently raised. Building on the survey results and the existing literature, the study proposes a set of indicators to assess the contribution of citizen participation to the adoption of nature-based solutions. While the effectiveness of nature-based solutions in mitigating climate change impacts can be assessed relatively directly, evaluating civic engagement is more complex. Nevertheless, when conducted transparently and interpreted by experts, indicator-based assessment can offer valuable insights. This study introduces a novel perspective by considering not only drivers of engagement but also the obstacles. The proposed indicators provide a foundation for evaluating community readiness and commitment to nature-based approaches and may be adapted for application in other urban settings and in future research on climate resilience strategies. Full article

Heritage Building Information Modeling (HBIM) has emerged as a key tool in advancing heritage conservation and sustainable management. Preceding reviews had typically concentrated on specific technical aspects but did not provide sufficient bibliometric analysis. This study aims to integrate existing HBIM research to identify key research patterns, emerging trends, and forecast future directions. A total of 1516 documents were initially retrieved from the Web of Science Core Collection using targeted search terms. Following a relevance screening, 1175 documents were related to the topic. CiteSpace 6.4.R1, VOSviewer 1.6.20, and Bibliometrix 4.1, three bibliometric tools, were employed to conduct both quantitative and qualitative assessments. The results show three historical phases of HBIM, identify core journals, influential authors, and leading regions, and extract six major keyword clusters: risk assessment, data acquisition, semantic annotation, digital twins, and energy and equipment management. Nine co-citation clusters further outline the foundational literature in the field. The results highlight growing scholarly interest in workflow integration and digital twin applications. Future projections emphasize the transformative potential of artificial intelligence in HBIM, while also recognizing critical implementation barriers, particularly in developing countries and resource-constrained contexts. This study provides a comprehensive and systematic framework for HBIM research, offering valuable insights for scholars, practitioners, and policymakers involved in heritage preservation and digital management. Full article

Amid rising climate concerns, understanding how renewable energy adoption, human capital, fossil fuel efficiency, and globalization collectively shape CO₂ emissions is crucial for unlocking pathways to a cleaner, resilient, and globally connected low-carbon future. Using China as a case study, this research investigates the drivers of CO₂ emissions, focusing on fossil fuel efficiency, renewable energy adoption, and globalization, utilizing quarterly data from 1984Q1 to 2023Q4. To ensure robust and nuanced insights, the study integrates advanced machine learning techniques alongside Quantile-on-Quantile Kernel Regularized Least Squares (QQ-KRLS) and a Modified Quantile Regression as robustness checks, capturing complex distributional dynamics often overlooked in conventional analyses. To the authors’ knowledge, this is the first empirical study examining such relationships for the case of China. The results reveal that globalization, fossil fuel efficiency, renewable energy, human capital, and financial risk all contribute to increasing CO₂ emissions. The study proposes precise policies based on the findings obtained. Full article

Background/Objectives: The field of tracheal reconstruction has undergone significant developments in the last few decades. Accordingly, this bibliometric review aims to identify the most influential publications within the field and their citation characteristics. Methods: A comprehensive search for “tracheal reconstruction” was conducted with the Clarivate’s Web of Science database. The resulting search results were filtered for relevant publications and evaluated to identify the 50 publications with the highest citation counts. Further analysis of these publications was conducted based on the following parameters: authorship, institutional affiliations, country of origin, citation density, year of publication, article type, and level of evidence. VOSviewer (version 1.6.20) was utilized to create co-occurrence maps of authors and keywords. Results: The top 50 publications were cited a total of 6449 times with an average of 128.98 citations per publication. The top three most cited articles were all by Grillo (primarily focused on tracheal stent repair and post-oncologic reconstruction). The majority of the top cited publications articles featured in The Annals of Thoracic Surgery (n = 10) were basic science in nature (32%) and had a level of evidence of Level IV (62%). The publication with the greatest citation density was by Kang et al. focusing on tracheal tissue engineering (TTE). Conclusions: This bibliometric review provides a thorough overview of the key publications that have influenced the field of tracheal reconstruction. Most predominantly, our analysis highlights a shift in focus from primary tracheal reconstruction techniques to more innovative repair paradigms such as TTE. Full article

Participation in horse-related activities frequently involves relocating horses from the home stable to an activity venue, which might require local, regional, or international travel. In these circumstances, horses are exposed to unfamiliar surroundings and experience changes to their daily routines, which could have negative welfare impacts. An online survey was conducted in 2021 to ask experienced horse sector participants about the horse management practices that they perceived worked well and provided for positive horse welfare when undertaken at venues. Qualitative analysis identified four themes: ‘managing venues’, ‘monitoring fitness to participate’, ‘maintaining a healthy equine digestive system’, and ‘using horse behaviors to inform decision-making’. The findings indicate that activity-related individuals selected practices that assisted horses to adapt to venue surroundings, remain calm, and stay healthy. The co-authors propose that experienced participants recognize that practices include both provisions (inputs) and outcomes (the horse’s subjective experiences), resonating with the Five Freedoms and Five Domains models. For horse activity organizations proposing to implement the Five Domains model, the findings indicate that reviewing practices and implementing updates is timely and achievable. The authors propose that continuously updating practices will contribute to safeguarding horses and maintaining the sector’s social license to operate. 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

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

Porcine endogenous retroviruses (PERVs) are integrated into the genome of all pigs. As they can be released as infectious virus particles capable of infecting human cells in vitro, they pose a potential risk for xenotransplantation involving pig cells or organs. To assess whether pigs produce infectious human-tropic viruses, infection assays with human cells are required. There are three main types of assays. First is the incubation of human target cells with gamma-irradiated pig cells. This method ensures that viral transmission is assessed in the absence of replicating pig cells. However, gamma irradiation may alter gene expression in pig cells, potentially affecting the results. Second is the co-culture in a double-chamber system in which pig and human cells are separated by a porous membrane, preventing direct cell-to-cell contact. While this method allows for the detection of infection by free virus particles, it does not account for infection via cell-to-cell transmission, which is a common mode of retroviral infection. And third is the co-culture of pig cells with human cells expressing a resistance gene. The resistance gene allows selective elimination of pig cells upon the addition of a selection medium. This assay enables both free virus and cell-to-cell transmission as well as complete removal of pig cells, which may not be fully achieved in the first type of assay. The third assay best simulates the conditions of in vivo xenotransplantation. However, in all cases the selection of donor and recipient cells is crucial to the experimental outcome. Results only indicate whether a specific pig cell type releases PERVs and whether a specific human cell type is susceptible to infection. A negative infection result does not necessarily reflect the in vivo situation, in which a transplanted organ consists of multiple pig cell types interacting with a diverse range of human cells within a living organism. Knowledge of these limitations is important for authorities regulating clinical applications for xenotransplantation. Full article

Artificial intelligence (AI) is one of the most influential and rapidly developing phenomena of our time. New fields of study are being created at universities, and managers are constantly introducing new AI solutions for business management, marketing, and advertising new products. Unfortunately, AI is also used to promote dangerous political parties and ideologies. The research problem that is the focus of this work is expressed in the following question: How does the symbiotic relationship between artificial and natural intelligence manifest across three dimensions of human experience—philosophical understanding, educational practice, and pastoral care—and what hermeneutical, phenomenological, and critical realist insights can illuminate both the promises and perils of this emerging co-evolution? In order to address this issue, an interdisciplinary research team was established. This team comprised a philosopher, an educator, and a pastoral theologian. This study is grounded in a critical–hermeneutic meta-analysis of the existing literature, ecclesial documents, and empirical investigations on AI. The results of scientific research allow for a broader insight into the impact of AI on humans and on personal relationships in Christian communities. The authors are concerned not only with providing an in-depth understanding of the issue but also with taking into account the ecumenical perspective of religious, social, and cultural education of contemporary Christians. Our analysis reveals that cultivating a healthy symbiosis between artificial and natural intelligence requires specific competencies and ethical frameworks. We therefore conclude with practical recommendations for Christian formation that neither uncritically embrace nor fearfully reject AI, but rather foster wise discernment for navigating this unprecedented co-evolutionary moment in human history. Full article

We live in an era where digitalization and omnichannel strategies significantly transform retail landscapes, and accurate spatial analytics from Geographic Information Systems (GIS) can deliver substantial competitive benefits. Nonetheless, despite evident practical advantages for specific targeting strategies and operational efficiency, the degree of GIS integration into academic marketing literature remains ambiguous. Clarifying this uncertainty is beneficial for advancing theoretical understanding and ensuring retail strategies fully leverage robust, data-driven spatial intelligence. To examine the intellectual development of the field, co-occurrence analysis, topic mapping, and citation structure visualization were performed on 4952 peer-reviewed articles using the Bibliometrix R package (version 4.3.3) within R software (version 4.4.1). The results demonstrate that although GIS-based methods have been effectively incorporated into fields like site selection and spatial segmentation, traditional marketing research has not yet entirely adopted them. One of the study’s key findings is the distinction between “author keywords” and “keywords plus,” where researchers concentrate on novel topics like omnichannel retail, artificial intelligence, and logistics. However, “Keywords plus” still refers to more traditional terms such as pricing, customer satisfaction, and consumer behavior. This discrepancy presents a misalignment between current research trends and indexed classification practices. Although the mainstream retail research lacks terminology connected to geomarketing, a theme evolution analysis reveals a growing focus on technology-driven and sustainability-related concepts associated with the Retail 4.0 and 5.0 paradigms. These findings underscore a conceptual and structural deficiency in the literature and indicate the necessity for enhanced integration of GIS and spatial decision support systems (SDSS) in retail marketing. Full article

Amid the accelerated digital transformation and with the growing demand for smart manufacturing, the applications of the Internet of Things (IoT) and total quality management (TQM) have attracted increasing attention. Using R for bibliometric analysis, we explored research trends in IoT and TQM in terms of digital transformation and smart manufacturing. Data were gathered from the Web of Science from 1998 to 2025, with a total of 787 publications from 265 sources involving 2326 authors. A total of 31% of the authors collaborated internationally, indicating global interest in this topic. The publications had 33.65 citations on average, totaling 33,599 citations. Wang L.H. and Tao F. were identified as important authors. Keywords of “Industry 4.0”, “cyber-physical systems”, and “big data” underscore the technological significance of IoT and TQM. Major journals such as the Journal of Manufacturing Systems and IEEE Access had notable academic influence. Co-citation analysis results revealed that IoT and TQM played a significant role in driving digital transformation and enhancing production efficiency, offering references for enterprises in strategic planning for smart manufacturing. Full article