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Virtual reality’s (VR) applications in education have been a topic of interest to the academia in recent years. Although literature expands significantly worldwide, the focus on education still presents a high number of opportunities to explore. In Latin America, the literature regarding the use of virtual reality is limited and not yet systematized. Therefore, the present study aims to provide an overview of Latin America’s research publications regarding the use of VR in higher education. Using bibliometric measures and coding in Scopus and Web of Science (WoS) databases’ outputs, we analyzed 126 papers, the majority of them from social sciences, followed by engineering, business, and medicine. Content tree analysis resulted in 5 dimensions: ‘Functional aspects of using VR as a learning tool’, ‘Teaching strategies and methodologies using VR’, ‘Behavioral aspects of using VR as a learning tool’, ‘Outputs of VR use as an educational tool’ and ‘Competencies and readiness to use VR as a learning tool’. Most publications (74,6%) focus or present as one of the discussions the functional aspects of VR, such as access, viability, usefulness, virtual environment, the association with artificial intelligence, among others.

 

 

The gene delivery systems (GDS) for lung cancer (LC) has made significant progress over the past 12 years, yet, there is a great challenge in its clinical application due to low delivery efficiency. This study aims to explore research fields related to gene therapy for LC and predict future directions from a bibliometric perspective. The Web of Science Core Collection collects articles and reviews on GDS for LC published from 2010 to 2022. Comprehensive bibliometric and visual analyses were performed using CiteSpace, VOSviewer, R-Bibliometrix, and Microsoft Excel. The analysis showed that the number of publications on GDS for LC has been increasing over the past 12 years, highlighting the growing interest and research efforts in this area. A rigorous examination of keywords and research hotspots revealed that the themes such as “complex,” “transfection,” “RNA interference,” “extracellular vesicle,” “co-deliver,” “resistance,” etc. dominate the field of GDS for LC. These findings indicated that the research in GDS for LC is evolving, with a noticeable shift toward addressing challenges related to delivery efficiency, transfection methods, and overcoming resistance mechanisms in gene therapy. The comprehensive study provides an overview of the literature on GDS for LC and identifies areas that require further exploration and development. By highlighting emerging research hotspots, our bibliometric analysis offers valuable insights to scholars and researchers, aiding in the identification of gaps, and guiding future efforts toward the development of GDS with more efficiency for LC therapy.

 

 

Decision-making processes in the military domain constitute a strategic field of research in cognitive psychology, although there are currently few scientific publications addressing the topic. Professionals in the field and interested parties need access to data on military decision-making processes to understand where and how the scientific community is directing its investigations on the issue. Military decision-making is a strategic field of study because the military is crucial to the security and defense of a country or community. This work aims to be a point of reference for those involved in various capacities in military decision-making, providing key data regarding research trends over the years, the geographical distribution of scientific productivity, methodologies employed, annual statistics, and the prevalence of the most-investigated terms and topics. Therefore, this study serves as a bibliometric analysis of the literature on military decision-making publihed from 1992 to 2023 on the Scopus and Web of Science databases.

 

 

Wildfire prediction plays a vital role in the management and conservation of forest ecosystems. By providing detailed risk assessments, it contributes to the reduction of fire frequency and severity, safeguards forest resources, supports ecological stability, and ensures human safety. This study systematically reviews wildfire prediction literature from 2003 to 2023, emphasizing research trends and collaborative trends. Our findings reveal a significant increase in research activity between 2019 and 2023, primarily driven by the United States Forest Service and the Chinese Academy of Sciences. The majority of this research was published in prominent journals such as the International Journal of Wildland Fire, Forest Ecology and Management, Remote Sensing, and Forests. These publications predominantly originate from Europe, the United States, and China. Since 2020, there has been substantial growth in the application of machine learning techniques in predicting forest fires, particularly in estimating fire occurrence probabilities, simulating fire spread, and projecting post-fire environmental impacts. Advanced algorithms, including deep learning and ensemble learning, have shown superior accuracy, suggesting promising directions for future research. Additionally, the integration of machine learning with cellular automata has markedly improved the simulation of fire behavior, enhancing both efficiency and precision. The profound impact of climate change on wildfire prediction also necessitates the inclusion of extensive climate data in predictive models. Beyond conventional studies focusing on fire behavior and occurrence probabilities, forecasting the environmental and ecological consequences of fires has become integral to forest fire management and vital for formulating more effective wildfire strategies. The study concludes that significant regional disparities in knowledge exist, underscoring the need for improved research capabilities in underrepresented areas. Moreover, there is an urgent requirement to enhance the application of artificial intelligence algorithms, such as machine learning, deep learning, and ensemble learning, and to intensify efforts in identifying and leveraging various wildfire drivers to refine prediction accuracy. The insights generated from this field will profoundly augment our understanding of wildfire prediction, assisting policymakers and practitioners in managing forest resources more sustainably and averting future wildfire calamities.

 

 

Brain metastases challenge cancer treatments with poor prognoses, despite ongoing advancements. Immunotherapy effectively alleviates advanced cancer, exhibiting immense potential to revolutionize brain metastasis management. To identify research priorities that optimize immunotherapies for brain metastases, 2164 related publications were analyzed. Scientometric visualization via R software, VOSviewer, and CiteSpace showed the interrelationships among literature, institutions, authors, and topic areas of focus. The publication rate and citations have grown exponentially over the past decade, with the US, China, and Germany as the major contributors. The University of Texas MD Anderson Cancer Center ranked highest in publications, while Memorial Sloan Kettering Cancer Center was most cited. Clusters of keywords revealed six hotspots: ‘Immunology’, ‘Check Point Inhibitors’, ‘Lung Cancer’, ‘Immunotherapy’, ‘Melanoma’, ‘Breast Cancer’, and ‘Microenvironment’. Melanoma, the most studied primary tumor with brain metastases offers promising immunotherapy advancements with generalizability and adaptability to other cancers. Our results outline the holistic overview of immunotherapy research for brain metastases, which pinpoints the forefront in the field, and directs researchers toward critical inquiries for enhanced mechanistic insight and improved clinical outcomes. Moreover, governmental and funding agencies will benefit from assigning financial resources to entities and regions with the greatest potential for combating brain metastases through immunotherapy.

 

 

This study comprehensively analyzes the relationship between migration and financial markets. We examine existing research on this subject using a scientometric and bibliometric approach. By employing VOSviewer and Bibliometrix tools, we introduce a novel methodology that enhances comprehension of this intricate relationship. The findings underscore two significant outcomes. Firstly, the impact of migration on financial markets is evident through the substantial flow of remittances and microfinance. Secondly, this study uncovers challenges hindering the integration of migrants into formal banking systems, thereby affecting financial market dynamics. This research deepens our understanding of migration’s implications on financial markets, offering practical insights that can guide policymakers and financial institutions in their decision-making processes.

 

 

Research on forest carbon storage (FCS) is crucial for the sustainable development of human society given the context of global climate change. Previous FCS studies formed the science base of the FCS field but lacked a macrolevel knowledge summary. This study combined the scientometric mapping tool VOSviewer and multiple statistical models to conduct a comprehensive knowledge graph mining and analysis of global FCS papers (covering 101 countries, 1712 institutions, 5435 authors, and 276 journals) in the Web of Science database as of 2022, focusing on revealing the macro spatiotemporal pattern, multidimensional research status, and topic evolution process of FCS research at the global scale, so as to grasp the status of global FCS research more clearly and comprehensively, thereby facilitating the future decision-making and practice of researchers. The results showed the following: (1) In the past three decades, the number of FCS papers indicated an increasing trend, with a growth rate of 4.66/yr, particularly significant after 2010. These papers were mainly from Europe, the Americas, and Asia, while there was a huge gap between Africa, Oceania, and the above regions. (2) For the research status at the national, institutional, scholar, and journal levels, the USA, with 331 FCS papers and 18,653 total citations, was the most active and influential country in global FCS research; the United States Forest Service topped the influential ranking with 4115 citations; Grant M. Domke and Jerome Chave were the most active and influential FCS researchers globally, respectively. China’s activity (237 papers) and influence (5403 citations) ranked second, and the Chinese Academy of Sciences was the most active research institution in the world. Currently, FCS research is published in a growing number of journals, among which Forest Ecology and Management ranked first in the number of papers (154 papers) and citations (6374 citations). (3) In recent years, the keyword frequency of monitoring methods, driving factors, and reasonable management for FCS has increased rapidly, and many new related keywords have emerged, which means that researchers are not only focusing on the estimation and monitoring of FCS but also increasingly concerned about its driving mechanism and sustainable development.

 

 

In order to visualize the content and development patterns of microplastic biodegradation research, the American Chemical Society (ACS), Elsevier, Springer Link, and American Society for Microbiology (ASM) were searched for the years 2012–2022 using Citespace and VOSvivewer for bibliometrics and visual analysis. The biodegradation processes and mechanisms of microplastics were reviewed on this basis. The results showed a sharp increase in the number of publications between 2012 and 2022, peaking in 2020–2021, with 62 more publications than the previous decade. The University of Chinese Academy of Sciences (UCAS), Northwest A&F University (NWAFU), and Chinese Academy of Agricultural Sciences (CAAS) are the top three research institutions in this field. Researchers are mainly located in China, The United States of America (USA), and India. Furthermore, the research in this field is primarily concerned with the screening of functional microorganisms, the determination of functional enzymes, and the analysis of microplastic biodegradation processes and mechanisms. These studies have revealed that the existing functional microorganisms for microplastic biodegradation are bacteria, predominantly Proteobacteria and Firmicutes; fungi, mainly Ascomycota; and some intestinal microorganisms. The main enzymes secreted in the process are hydrolase, oxidative, and depolymerization enzymes. Microorganisms degrade microplastics through the processes of colonization, biofilm retention, and bioenzymatic degradation. These studies have elucidated the current status of and problems in the microbial degradation of microplastics, and provide a direction for further research on the degradation process and molecular mechanism of functional microorganisms.

 

 

The geoscience knowledge graph (GeoKG) has gained worldwide attention due to its ability in the formal representation of spatiotemporal features and relationships of geoscience knowledge. Currently, a quantitative review of the state and trends in GeoKG is still scarce. Thus, a bibliometric analysis was performed in this study to fill the gap. Specifically, based on 294 research articles published from 2012 to 2023, we conducted analyses in terms of the (1) trends in publications and citations; (2) identification of the major papers, sources, researchers, institutions, and countries; (3) scientific collaboration analysis; and (4) detection of major research topics and tendencies. The results revealed that the interest in GeoKG research has rapidly increased after 2019 and is continually expanding. China is the most productive country in this field. Co-authorship analysis shows that inter-national and inter-institutional collaboration should be reinforced. Keyword analysis indicated that geoscience knowledge representation, information extraction, GeoKG construction, and GeoKG-based multi-source data integration were current hotspots. In addition, several important but currently neglected issues, such as the integration of Large Language Models, are highlighted. The findings of this review provide a systematic overview of the development of GeoKG and provide a valuable reference for future research.

 

 

Background In the study of atrial fibrillation (AF), a prevalent cardiac arrhythmia, the utilization of artificial intelligence (AI) in diagnostic and therapeutic strategies holds the potential to address existing limitations. This research employs bibliometrics to objectively investigate research hotspots, development trends, and existing issues in the application of AI within the AF field, aiming to provide targeted recommendations for relevant researchers. Methods Relevant publications on the application of AI in AF field were retrieved from the Web of Science Core Collection (WoSCC) database from 2013 to 2023. The bibliometric analysis was conducted by the R (4.2.2) “bibliometrix” package and VOSviewer(1.6.19). Results Analysis of 912 publications reveals that the field of AI in AF is currently experiencing rapid development. The United States, China, and the United Kingdom have made outstanding contributions to this field. Acharya UR is a notable contributor and pioneer in the area. The following topics have been elucidated: AI’s application in managing the risk of AF complications is a hot mature topic; AI-electrocardiograph for AF diagnosis and AI-assisted catheter ablation surgery are the emerging and booming topics; smart wearables for real-time AF monitoring and AI for individualized AF medication are niche and well-developed topics. Conclusion This study offers comprehensive analysis of the origin, current status, and future trends of AI applications in AF, aiming to advance the development of the field.