Search Results (511)

The cement industry accounts for approximately 7–8% of global CO₂ emissions, primarily due to energy-intensive clinker production and limestone calcination. With cement demand continuing to rise, particularly in emerging economies, decarbonization has become an urgent global challenge. The objective of this study is to systematically map and synthesize existing evidence on technological pathways, policy measures, and economic barriers to four core decarbonization strategies: clinker substitution, energy efficiency, alternative fuels, as well as carbon capture, utilization, and storage (CCUS) in the cement sector, with the goal of identifying practical strategies that can align industry practice with long-term climate goals. A scoping review methodology was adopted, drawing on peer-reviewed journal articles, technical reports, and policy documents to ensure a comprehensive perspective. The results demonstrate that each mitigation pathway is technically feasible but faces substantial real-world constraints. Clinker substitution delivers immediate reduction but is limited by SCM availability/quality, durability qualification, and conservative codes; LC₃ is promising where clay logistics allow. Energy-efficiency measures like waste-heat recovery and advanced controls reduce fuel use but face high capital expenditure, downtime, and diminishing returns in modern plants. Alternative fuels can reduce combustion-related emissions but face challenges of supply chains, technical integration challenges, quality, weak waste-management systems, and regulatory acceptance. CCUS, the most considerable long-term potential, addresses process CO₂ and enables deep reductions, but remains commercially unviable due to current economics, high costs, limited policy support, lack of large-scale deployment, and access to transport and storage. Cross-cutting economic challenges, regulatory gaps, skill shortages, and social resistance including NIMBYism further slow adoption, particularly in low-income regions. This study concludes that a single pathway is insufficient. An integrated portfolio supported by modernized standards, targeted policy incentives, expanded access to SCMs and waste fuels, scaled CCUS investment, and international collaboration is essential to bridge the gap between climate ambition and industrial implementation. Key recommendations include modernizing cement standards to support higher clinker replacement, providing incentives for energy-efficient upgrades, scaling CCUS through joint investment and carbon pricing and expanding access to biomass and waste-derived fuels. Full article

In accordance with the PRISMA 2020 guidelines, this systematic review analyzed 73 publications (1997–2025) to summarize advancements in robotic aircraft skin inspection, focusing on the integrated pipeline from data acquisition to defect analysis. The review included studies on Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) for external skin inspection, which present clear technical contributions, while excluding internal inspections and non-technical reports. Literature was retrieved from IEEE conferences, journals, and other academic databases, and key findings were summarized via the categorical analysis of motion planning, perception modules, and defect detection algorithms. Key limitations identified include the fragmentation of core technical modules, unresolved bottlenecks in dynamic environments, challenges in weak-texture and all-weather perception, and a lack of mature integrated systems with practical validation. The study concludes by advocating for future research in multi-robot heterogeneous collaborative systems, intelligent dynamic task scheduling, large model-based airworthiness assessment, and the expansion of inspection scenarios, all aimed at achieving fully autonomous and reliable operations. Full article

The goal of this study is to estimate the amount of lost data in electron microscopy and to analyze the extent to which experimentally acquired images are utilized in peer-reviewed scientific publications. Analysis of the number of images taken on electron microscopes at a core user facility and the number of images subsequently included in peer-reviewed scientific journals revealed low efficiency of data utilization. Up to around 90% of electron microscopy data generated during routine instrument operation can remain unused. Of the more than 150,000 electron microscopy images evaluated in this study, only approximately 3500 (just over 2%) were made available in publications. For the analyzed dataset, the amount of lost data in electron microscopy can be estimated as >90% (in terms of data being recorded but not being published in peer-reviewed literature). On the one hand, these results highlight a shortcoming in the optimal use of microscopy images; on the other hand, they indicate the existence of a large pool of electron microscopy data that can facilitate research in data science and the development of AI-based projects. The considerations important to unlock the potential of lost data are discussed in the present article. Full article

Background: As diabetes mellitus continues to escalate into a global health crisis, particularly in China, the limitations of conventional pharmacotherapy underscore the need for complementary interventions. This study systematically reviews two decades of research progress on acupuncture for diabetes management. Methods: A total of 391 publications met the inclusion criteria from the Web of Science Core Collection (2004–2024) using the search terms “acupuncture” AND “diabetes”. These comprised 294 original studies and 97 reviews. CiteSpace 6.3.R1 was used to perform multidimensional analyses, including co-occurrence networks, centrality algorithms, and silhouette metrics across countries/regions, institutions, authors, journals, references, and keywords. Results: The analysis shows a significant increase in publications on acupuncture for diabetes management after 2013. China and the United States lead in research output, yet collaboration between the two countries remains limited. Most researchers currently work within isolated clusters, underscoring the need for greater exchanges and cooperation. Furthermore, this study identified three key research hotspots: insulin resistance, complications, and interdisciplinary research. Conclusions: This bibliometric analysis reveals dynamic growth patterns and paradigm shifts in acupuncture and diabetes research. The findings provide valuable implications for integrating acupuncture into diabetes treatment. Full article

Digital transformation (DT) is rapidly reshaping education at multiple levels, including curriculum, instructional practices, and institutional culture. Within this context, entrepreneurship education has become a key field for preparing individuals to navigate uncertainty and generate social and economic value in a digital society. Entrepreneurial competencies are increasingly conceptualized as a multidimensional construct that encompasses creativity, problem-solving, critical thinking, collaboration, and digital literacy. This study aims to identify core entrepreneurial competencies relevant to the digital era and examine how technology-integrated instructional strategies contribute to their development. A systematic literature review was conducted in accordance with PRISMA 2020 guidelines, analyzing 72 peer-reviewed journal articles published between January 2021 and June 2025. The findings indicate that DT drives structural changes in education beyond tool adoption, with technologies such as artificial intelligence (AI), data analytics, and digital collaboration platforms serving as catalysts for innovative thinking and entrepreneurial behavior. These technologies are not merely supportive tools but are embedded in competency-based learning processes. This review provides a comprehensive competency framework integrating three domains, AI-collaborative pedagogy validation, and implementation strategies, enabling educators, curriculum developers, and policymakers to redesign entrepreneurship education that aligns with the realities of digital learning environments and fosters future-ready entrepreneurial capabilities. This conceptual framework theoretically systematizes the integration of innovative thinking and ethical execution capabilities required in the digital era, contributing to defining the future direction of entrepreneurship education. Full article

Machine learning (ML) is reshaping how environmental chemicals are monitored and how their hazards are evaluated for human health. Here, we mapped this landscape by analyzing 3150 peer-reviewed articles (1985–2025) from the Web of Science Core Collection. Co-citation, co-occurrence, and temporal trend analyses in VOSviewer and R reveal an exponential publication surge from 2015, dominated by environmental science journals, with China and the United States leading in output. Eight thematic clusters emerged, centered on ML model development, water quality prediction, quantitative structure–activity applications, and per-/polyfluoroalkyl substances, with XGBoost and random forests as the most cited algorithms. A distinct risk assessment cluster indicates migration of these tools toward dose–response and regulatory applications, yet keyword frequencies show a 4:1 bias toward environmental endpoints over human health endpoints. Emerging topics include climate change, microplastics, and digital soil mapping, while lignin, arsenic, and phthalates appear as fast-growing but understudied chemicals. Our findings expose gaps in chemical coverage and health integration. We recommend expanding the substance portfolio, systematically coupling ML outputs with human health data, adopting explainable artificial intelligence workflows, and fostering international collaboration to translate ML advances into actionable chemical risk assessments. 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

Bridges play an increasingly indispensable role in endorsing the economic and social development of societies by linking highways and facilitating the mobility of people and goods. Concurrently, they are susceptible to high traffic volumes and an intricate service environment over their lifespans, resulting in undergoing a progressive deterioration process. Hence, efficient measures of maintenance, repair, and rehabilitation planning are critical to boost the performance condition, safety, and structural integrity of bridges while evading less costly interventions. To this end, this research paper furnishes a mixed review method, comprising systematic literature and scientometric reviews, for the meticulous examination and analysis of the existing research work in relation with maintenance fund allocation models of bridges (BriMai_all). With that in mind, Scopus and Web of Science databases are harnessed collectively to retrieve peer-reviewed journal articles on the subject, culminating in 380 indexed journal articles over the study period (1990–2025). In this respect, VOSviewer and Bibliometrix R package are utilized to create a visualization network of the literature database, covering keyword co-occurrence analysis, country co-authorship analysis, institution co-authorship analysis, journal co-citation analysis, journal co-citation, core journal analysis, and temporal trends. Subsequently, a rigorous systematic literature review is rendered to synthesize the adopted tools and prominent trends of the relevant state of the art. Particularly, the conducted multi-dimensional review examines the six dominant methodical paradigms of bridge maintenance management: (1) multi-criteria decision making, (2) life cycle assessment, (3) digital twins, (4) inspection planning, (5) artificial intelligence, and (6) optimization. It can be argued that this research paper could assist asset managers with a practical guide and a protocol to plan maintenance expenditures and implement sustainable practices for bridges under deterioration. Full article

The integration of machine learning (ML) into sustainable construction materials research, particularly focusing on construction and demolition waste (CDW), has accelerated in recent years, driven by the dual need for digital innovation and environmental responsibility. This study presents a comprehensive scientometric analysis of the global research landscape on ML applications for predicting the performance of sustainable construction materials. A total of 542 publications (2007–2025) were retrieved from Scopus and analyzed using VOSviewer (V1.6.20) and Biblioshiny (Bibliometrix R-package, V5.1.1) to map publication trends, leading sources, key authors, keyword co-occurrence, and emerging thematic clusters. The results reveal a sharp rise in publications after 2018, peaking in 2024, in parallel with the growing global emphasis on the circular economy and the UN Sustainable Development Goals. Leading journals such as Construction and Building Materials, the Journal of Building Engineering, and Materials have emerged as key publication venues. Keyword analysis identified core research areas, including compressive strength prediction, recycled aggregates, and ML algorithm development, with recent trends showing increasing use of ensemble and deep learning methods. The findings highlight three thematic pillars—Performance Characterization, Algorithmic Modeling, and Sustainability Practices—underscoring the interdisciplinary nature of the field. This study also highlights regional disparities in research output and collaboration, underscoring the need for more inclusive and diverse global partnerships. Overall, this study provides a comprehensive and insightful view of the rapidly evolving ML-CDW research landscape, offering valuable guidance for researchers, practitioners, and policymakers in advancing data-driven, sustainable solutions for the future of construction. Full article

The construction of urban underground space develops very fast, and tunnel intersection construction has become a common practice, attracting significant attention due to the associated deformation responses and risk control challenges. To systematically review the research landscape and cutting-edge developments in this field, this study conducts a comprehensive analysis based on 744 publications (1994–2025) from the Web of Science Core Collection using bibliometric methods. Firstly, through visual analyses of annual publication trends, journal distributions, and keyword co-occurrences, the study reveals the evolution and research hotspots of the past three decades. Subsequently, three core dimensions are explored in depth: deformation mechanisms and patterns, deformation analysis methods for ground and existing structures, and ground control and reinforcement techniques. The review highlights the following: (1) Research focus has shifted from single construction scenarios to the complex interactions among multiple tunnels, yet the cumulative deformation effects caused by repeated soil disturbances during sequential excavation remain inadequately understood. (2) The bidirectional coupling between existing tunnels and surrounding soil has become a major research focus and challenge. Particularly in the presence of high-stiffness structures, the “free-field” assumption in the commonly used two-stage method is being questioned, necessitating the development of more refined computational theories. (3) Optimization of construction schemes under complex conditions is key to disturbance control, but current research still lacks systematic multi-objective optimization approaches. In addition, this paper analyzes the current research status and future directions to enhance the deformation perception capability and control technologies in tunnel construction influence zones, thereby further improving the safety and intelligence level of tunnel construction. Full article

With the global concept of sustainable development gaining widespread acceptance, the resource utilization of solid waste has become an important research direction in the field of building materials. Geopolymer concrete (GPC), especially solid waste-based geopolymer concrete (SWGPC) prepared using various industrial solid wastes as precursors, has gradually become a frontier in green building material research due to its low carbon footprint, high strength, and excellent durability. However, the rapid expansion of literature calls for a systematic review to quantify the knowledge structure, evolution, and emerging trends in this field. Based on two thousand and thirty-nine (2039) relevant articles indexed in the Web of Science Core Collection database between 2008 and 2025, this study employs bibliometric methods and visualization tools such as VOSviewer and CiteSpace to systematically construct a knowledge map of this field. The research comprehensively reveals the developmental trajectory, research hotspots, and frontier dynamics of SWGPC from multiple dimensions, including publication trends, geographical and institutional distribution, mainstream journals, keyword clustering, and burst word analysis. The results indicate that the field has entered a rapid development stage since 2016, with research hotspots focusing on the synergistic utilization of multi-source solid waste, optimization of alkali-activation systems, enhancement of concrete durability, and environmental impact assessment. In recent years, the introduction of emerging technologies such as machine learning, 3D printing, and nano-modification has been driving a paradigm shift in research. This systematic analysis not only clarifies research development trends but also provides a theoretical basis and decision-making support for future interdisciplinary integration and engineering practice transformation. Full article

Background: Cognitive and neuropsychological effects of cancer and its treatments have gained increasing attention over the past decade, with growing evidence of persistent deficits across multiple cancer types. While numerous studies have examined these effects, the literature remains fragmented, and no comprehensive bibliometric synthesis has been conducted to map the field’s intellectual structure and emerging trends. Methods: A bibliometric and science mapping analysis was performed using the Scopus database to identify peer-reviewed articles published between 2015 and 2025 on neuropsychological or cognitive outcomes in adult cancer populations. Data from 179 eligible publications were analyzed with VOSviewer and Microsoft Power BI, applying performance metrics and network mapping techniques, including co-authorship, bibliographic coupling, co-citation, and keyword co-occurrence analyses. Results: Publication output increased steadily over the decade, with leading contributions from the Journal of Neuro-Oncology, Psycho-Oncology, and Brain Imaging and Behavior. Co-citation analysis identified three core intellectual pillars: (i) clinical characterization of cancer-related cognitive impairment, (ii) mechanistic and neuroimaging-based investigations, and (iii) neurosurgical and neuropathological research in brain tumors. Keyword mapping revealed emerging themes in sleep and circadian rhythm research, biological contributors to cognitive decline, and scalable rehabilitation strategies such as web-based cognitive training. Collaborative networks, while showing dense local clusters, remained moderately fragmented across disciplines. Conclusions: This review provides the first quantitative, decade-spanning map of cognitive oncology research, highlighting both consolidated knowledge areas and underexplored domains. Future efforts should prioritize methodological standardization, cross-disciplinary collaboration, and integration of cognitive endpoints into survivorship care, with the ultimate aim of improving functional outcomes and quality of life for cancer survivors. Full article

Background: Chemical burns represent a persistent global health challenge due to their high prevalence, causing lifelong disabilities and socioeconomic burdens. Although research on chemical burns has expanded over the past century, no comprehensive study has mapped the intellectual structure, global collaboration patterns, and thematic evolution of scientific production on chemical burns to determine how research in the area has evolved and the existence of gaps or imbalances that need to be addressed. Objective: The aim was to analyze the scientific production on chemical burns using bibliometric methods, identifying key contributors, evolving themes, and research gaps. Methods: Eligible documents contained the MeSH descriptor and were listed both in PubMed (1946 to 2024) and in the Web of Science Core Collection. The documents were analyzed with Bibliometrix version 5.0 and VOSviewer version 1.6.20. The metrics included were annual productivity, citation networks, co-authorship patterns, and keyword co-occurrence. Results: The analysis included 3943 articles from 757 journals. The annual average was 25.8 articles, with a growth rate of 0.65% from 1946 to 2024. The USA produced the most articles (n = 1547), followed by China (n = 890). The USA also led in international collaboration, working with 26 countries. Harvard University was the leading institution (n = 325) and Burns the leading journal (n = 306), followed by Cornea (n = 132). The most common subject category of the research was surgery (n = 1185 docs) and ophthalmology (n = 984). Reim M. was the most prolific author (n = 35), while Basu S. had the most citations (n = 1159). The main clinical MeSH descriptors were “Eye burns” (n = 1158), “Esophageal stenosis” (n = 683), and “Caustics” (n = 659). Conclusions: The results show slight growth in scientific production on chemical burns. The USA and China are leading research in this field, and the main reported finding was eye burns. Full article

Smart cities and urban planning have succeeded in gathering the attention of researchers worldwide, especially in the last decade, as a result of a series of technological, social and economic developments that have shaped the need for evolution from the traditional way in which the cities were viewed. Technology has been incorporated in many sectors associated with smart cities, such as communications, transportation, energy, and water, resulting in increasing people’s quality of life and satisfying the needs of a society in continuous change. Furthermore, with the rise in machine learning (ML) and artificial intelligence (AI), as well as Geographic Information Systems (GIS), the applications of big data analytics in the context of smart cities and urban planning have diversified, covering a wide range of applications starting with traffic management, environmental monitoring, public safety, and adjusting power distribution based on consumption patterns. In this context, the present paper brings to the fore the papers written in the 2015–2024 period and indexed in Clarivate Analytics’ Web of Science Core Collection and analyzes them from a bibliometric point of view. As a result, an annual growth rate of 10.72% has been observed, showing an increased interest from the scientific community in this area. Through the use of specific bibliometric analyses, key themes, trends, prominent authors and institutions, preferred journals, and collaboration networks among authors, data are extracted and discussed in depth. Thematic maps and topic discovery through Latent Dirichlet Allocation (LDA) and doubled by a BERTopic analysis, n-gram analysis, factorial analysis, and a review of the most cited papers complete the picture on the research carried on in the last decade in this area. The importance of big data analytics in the area of urban planning and smart cities is underlined, resulting in an increase in their ability to enhance urban living by providing personalized and efficient solutions to everyday life situations. Full article

Scholars are showing a growing interest in smart tourism, a promising trend in destination development. The current research studies have established a strong theoretical foundation on the functions of technology and the impacts of smart tourism on travelers. Nevertheless, little is known about the comprehensive and systemic effects on the growth of smart tourism in a particular destination. This study employs bibliometric analysis to examine the scientific literature of smart tourism research, based on 563 relevant publications retrieved from the leading database Web of Science Core Collection between 2000 and 2024 and analyzed using VOSviewer software 1.6.20 packages. The results show that the total number of relevant publications has gradually increased in recent years. Key journals include Tourism Management, Sustainability-Basel, and Annals of Tourism Research. The results also show that authors from the People’s Republic of China have the most publications and international co-authorships, while the most influential institution is the Hong Kong Polytechnic University. Moreover, research keywords have been identified, including smart tourism, smart cities, Internet of Things and big data. The research findings of this study provide valuable insights to further improve smart tourism research. Full article