Strength Of Link Research Articles

Research trends, hotspots and future directions of tertiary lymphoid structures in cancer: a comprehensive informatics analysis and visualization study.

Many studies have reported the presence of tertiary lymphoid structures (TLSs) in cancer, but the research progress of TLSs in cancer has not been systematically analyzed. Therefore, we analyzed the global scientific knowledge in the field using informatics methods. The results showed that TLSs in cancer have received increasing attention since the 21st century, with an annual publication growth rate of 27.86%. Unsupervised hierarchical clustering based on machine learning further categorized the research features into four clusters, with the cluster related to immunotherapy being considered an emerging cluster. TLSs and immunotherapy were identified as the top two hotspots with the highest occurrence frequency and total link strength. The Walktrap algorithm indicated that "TLSs, carcinoma, prognostic value" and "high endothelial venules, germinal-centers, node-like structures" are important to TLSs but remain underexplored, representing promising research directions. These findings suggest that cancer-related TLSs have brought new insights into antitumor immunity, and targeting TLSs has the potential to transform the landscape of antitumor immunotherapy.

Bibliometric analysis of the top 500 most cited articles in cancer epidemiology

Purpose: The objective of this work is to provide perceptions for future research by creating a comprehensive bibliometric analysis of the literature on "cancer epidemiology". Material and Methods: Article data was collected from the Web of Science Core Collection (WoSCC) and advanced search was performed using the following keywords: “cancer*” and “epidemi*” between 2010-2024. The results were then refined according to the publication type of Science Citation Index Expanded and Emerging Sources Citation Index, which only consist of original English articles in the WOS database. A summary of the data analysis results examined along with open-source R package Bibliometric and VOS viewer (Version 16.20) programs. Results: The 500 most cited documents published in 180 different sources in the time period 2010-2024 showed a negative annual growth rate of 18.97%, indicating a decrease in publication output. An average of 70.1 co-authors per document was observed, and 60.8% of the collaborative efforts in these articles were found to be foreign co-authorship. The most frequently appearing keywords were found to be "epidemiology" with a total link strength of 625, followed by "cancer" with a total link strength of 372. According to the bibiliometric analysis result, the article by Ferlay, J. mm was found to have more than 72,000 citations. Conclusion: This bibliometric analysis has yielded quantitative data on the expansion of the cancer epidemiology discipline, the level of scientific excellence, and the identification of keywords, so facilitating the determination of the most accomplished topics.

Machine learning in obsessive-compulsive disorder medications

Obsessive-compulsive disorder (OCD) is the fourth most common psychiatric disorder with a significant morbidity rate. Despite various treatment modalities and medications, some patients show no definitive response. The aim of this study is to classify the medications of OCD with machine learning (ML) methods and to compare the classification performances of the decision tree (DT), chi-square automatic interaction detection (CHAID) algorithm, and linear model in ML methods. This research is a descriptive analytical study based on co-word and artificial intelligence methods. The DT models were created with a target (total weight link strength). For hyperparameter optimization, the Gini index was used as the weight total link strength. The performance of the DT model was evaluated based on the prediction model. A total of 116 drugs were extracted from 6574 articles based on co-word analysis, and 56 drugs were classified as the DT's root. These drugs were categorized into six groups in the EWKM diagram. The DT was constructed using the weight.total.link index, with 7 items in Label 3 and 42 items in Label 5 serving as DT leaves. The ML analysis provided valuable insights into the efficacy of various medications such as clomipramine, duloxetine, and pindolol, as well as supplements such as folate, in the treatment of OCD. Treating concomitant diseases, namely hypothyroidism and streptococcal infection could improve the efficacy of treatment.

GLP-1 and Body Weight: A Scientometric Analysis About How to Select the Best Articles Containing Pharmacological Treatment Methods

Background: Medications initially intended for diabetes treatment are now being used by other patients for weight loss. In the specialized literature, there are numerous meta-analyses investigating this aspect. Areas of Uncertainty: The authors aimed to explore whether the application of scientometric methods for literature review within meta-analyses could provide clear answers to specific research questions. This approach could help develop a rapid system for selecting articles to read during the information process for clinicians or researchers. Data Sources: We obtained research data from Web of Science Core Collection, using the search phrase “GLP-1 AND Body Weight,” reviews from the past 5 years. This approach led to the identification of 31 relevant articles in the field. Results: A total of 31 reviews were identified in the WOS database and investigated using the VOSviewer bibliographic coupling method. Among these, 7 reviews were found to have the highest influence. The authors analyzed these articles and determined that only these 7 reviews directly address the research question. In addition, an analysis of the impact factor of the journals where the articles are published, the influence power of these articles, and the countries of origin of the authors was conducted. A strong correlation was demonstrated between the impact factor and the total link strength for these 7 reviews. The correlation coefficient of 0.116709 between journal impact factor and number of citations suggests a very weak or nonexistent relationship. A strong positive correlation of 0.879736 exists between journal impact factor and total link strength, indicating a significant association. The correlation coefficient of −0.12505 between citations and total link strength shows a very weak or negligible relationship. Conclusions: Scientometric methods such as VOSviewer are useful in the work of both researchers and clinicians, highlighting the fact that articles in a research field can be identified by several criteria: impact factor, number of citations, authors from research teams that addressed this topic. The weak correlation between journal impact factor and number of citations implies that the prestige of the journal does not significantly affect the citation count of articles. Researchers should focus on the quality and relevance of their work rather than solely targeting high-impact journals. However, the strong positive correlation between impact factor and total link strength suggests that articles in prestigious journals are more likely to share content similarities. Researchers should consider this when selecting journals for publication and aim to contribute to impactful and interconnected research areas. This approach allows quick and easy identification of key articles, serving as a fundamental basis for rapid analysis of research in the field, starting from the analysis of authors' competence, degree of trust of the journal, or degree of interest that researchers have for that article.

Research hotspots and trends of mesenchymal stem cell-derived extracellular vesicles for drug delivery: a bibliometric and visualization analysis from 2013 to 2023.

Our study aims to provide a comprehensive overview of mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) in drug delivery research, focusing on the period between 2013 and 2023. Given the increasing global interest in this field, we utilized bibliometric tools to explore publication trends, key contributors, and thematic research clusters. Data was collected from the Web of Science (WoS) database, and an in-depth bibliometric analysis was conducted using VOSviewer. The analysis encompassed bibliographic coupling, co-citation, co-authorship, and co-occurrence trends, offering a structured insight into global research activity. We also employed Citespace to further analyze thematic clusters in this domain. Our analysis revealed a total of 1,045 publications related to MSC-EVs in drug delivery over the past decade, showing a steady increase in research output. China led in publication count, H-index, prolific authors, and research funding, while the United States ranked highest in total citations, average citation counts, and H-index performance. Pharmaceutics emerged as the leading journal by publication volume, with the Journal of Controlled Release having the strongest total link strength. Top institutions driving research included Shanghai Jiao Tong University, Zhejiang University, and Harvard University. VOSviewer analysis identified four major research clusters: tissue engineering, cancer, neurological diseases, and targeted delivery. Citespace analysis refined this further into ten thematic areas, including differentiation, tissue regeneration, and drug resistance. This bibliometric assessment provides a holistic visualization of the research landscape for MSC-EVs in drug delivery, underlining the significant contributions of China and the United States. Our findings underscore the increasing global importance of MSC-EV research and highlight emerging themes that will likely guide future research directions. The insights from this study offer a foundational framework for identifying nascent frontiers in MSC-EV-based drug delivery.

The Utilisation of ICT Resources for Teaching and Learning Science in Rural Schools: A Bibliometric Analysis

Information and Communication Technology (ICT) offers pedagogical approaches in science that may enhance engagement in STEM disciplines. It has emerged as a catalyst for quality education and job creation, imparting scientific knowledge and potentially enhancing educational standards for rural students, hence generating increased opportunities for employment and entrepreneurship. This study aimed to explore research trends on the use of ICT in teaching and learning science in rural schools, using available big data on studies done in the past 10 years worldwide. A bibliometric analysis was used to analyse 171 journal articles and conference proceedings papers which were published or in press. These documents were obtained through the SCOPUS database. The keywords used were "ICT in teaching science” OR "rural schools". Data were organised into tables, graphs and visualisations obtained from VOSviewer, then analysed descriptively. Findings from the study revealed insufficient publications of documents in this area per year worldwide, citations and co-citations, poor collaborations and low total link strength for all documents published from 2013-2023. Whereas many studies have been conducted on the use of ICT or STEM education or rural education, few studies incorporated the three terms. Those who have embarked on these studies seem to be losing interest in doing more research in this area. Furthermore, there are insufficient collaborations between authors and countries in this research area. This study recommends that the amount of research and collaborations be increased on regarding the utilisation of ICT resources for teaching science in rural schools.

Bibliometric analysis of Lycium barbarum polysaccharide

To delineate the mounting trends in the application of traditional Chinese medicine (TCM) “Lycium barbarum polysaccharide” (LBP) and provide insights for future research, relevant literature was screened from the Web of Science Core Collection (WOSCC) on LBP. Then, the research trends in these fields were analyzed by using VOSviewer, Excel, and online platforms. Totally, 284 publications on the topic of LBP were identified and “Lycium barbarum polysaccharide” with a total link strength of 683 appeared as the most frequent keyword, which had a strong link to “oxidative stress” and “apoptosis”. A total of 20 countries and regions have published articles in this field, with the largest number of publications in China (265). The main partners of China are the USA and Canada. The top 6 institutions with the highest number of publications all belong to China, among which Ningxia Medical University is the institution with the highest number of publications. The mean citation count of the top 8 most productive authors was 8 (range, 6-11). The author with the highest average citation published 2 articles, with a total of 227 citations. The highest-ranking journal was the International Journal of Biological Macromolecules with 19 articles published and the most cited journal was Biomedicine & Pharmacotherapy, with 484 citation counts. Based on the bibliometrics, this paper analyzed the current research focus and development trends regarding the LBP.

Current research trends in child poverty and psychological resilience research: A bibliometric analysis approach

AbstractThe first of the sustainable development goals is to end poverty by 2030. Although many individual, social, and psychological resources have been proposed to reduce poverty, little is known about psychological resilience factors and related variables in reducing it. While the literature on childhood poverty and psychological resilience indicates that there was a relationship between these variables, it also draws attention to the fact that a growing interest in the need to consider psychological factors in reducing child poverty. Contextually, this study is bibliometric research that aims to reveal the current research trends about child poverty and psychological resilience. The researcher reviewed the Web of Science to highlight current trends in child poverty and resilience research and found 1065 relevant documents that met the inclusion criteria. The research used co‐occurrence, citation, and bibliographic coupling techniques from the bibliometric analysis type. Research results showed that poverty, resilience, children, protective factors, youth, parenting, COVID‐19, stress, and mental health were the nine significant clusters where the poverty and resilience keywords were gathered (items = 120, links = 988, total link strength = 1646). The United States had the most publications and was the most collaborative country. The most associated SDG target was good health and well‐being. Research trends underline that the five most studied keywords were resilience, poverty, children, health, and risk. Thematic map results indicated that socioeconomic status, childhood, and adjustment topics were important, well‐developed, and structuring themes, while resilience, poverty, and children topics were essential themes but still needed to be well‐developed. The research findings highlight the importance of resiliency factors that can potentially reduce child poverty. The results also give researchers essential insights into socioeconomic, mental, psychological, and environmental factors that they can use in their intervention practices holistically in reducing child poverty.

Worldwide research trends on bone metastases of lung cancer: a bibliometric analysis.

Lung cancer has the highest fatality rate among all malignancies worldwide. Within this disease, bone metastasis (BM) emerges as a particularly deleterious site of metastatic dissemination, marked by a dismal prognosis. The objective of this investigation is to shed light on the current international research efforts and the development trajectory on lung cancer BM through a bibliometric analysis (performance and visualization analysis). Data were obtained from the Web of Science Core Collection repository on lung cancer BM from 1 January 2012 to 1 January 2022. Subsequently, the collected data underwent scrutiny using the VOSviewer software to reveal patterns of co-authorship, co-citation, and keyword analysis, while the CiteSpace software facilitated the generation of keyword cluster maps and performed burst analyses. The study included 327 papers of 2,154 authors, 587 organizations, and 41 countries, and explored the cooperation between them and the relationships between citations. Over the past decade, published papers showed a steady growth trend. China had the highest production with 189 papers, and USA had the highest collaboration with other countries, with 43 total link strength. Lung Cancer exhibited the highest frequency of co-cited journals, with a co-citation time of 412 and an IF/JCR partition of 6.081/Q1 in 2021. The most frequently co-cited article, authored by Tsuya A and published in Lung Cancer in 2007, amassed 70 co-citations. High-frequency keywords were categorized into four clusters: pathogenesis, treatment and clinical manifestations, prognosis, and diagnosis. In recent years, there has been a significant increase in the strong citation burst strength of keywords such as "predictor," "skeletal-related events," "efficacy," "migration," "docetaxel," and "impact." Lung adenocarcinoma is the most common type of tumor. This bibliometric study provides a comprehensive analysis of lung cancer BM in the recent 10 years. The field of early diagnosis, pathogenesis, and new treatments is entering a phase of rapid development and remains valuable for future research.

Analisis Bibliometrik: Penggunaan Media Pembelajaran Macromedia Flash 8 di Sekolah Dasar (2019-2023)

Bibliometric research is very important to provide readers with an understanding of research trends, compare authors or journals, and measure research contributions in scientific literature with the keyword "Macromedia Flash 8" on Scopus from 2019-2023. The methods used in this study are searching documents by keyword, using publish or perish, saving documents in the form of RIS files, and Using VOSviewer to display visualizations of bibliometric analysis. The results obtained from the VOSviewer analysis are that for analyzing scopus results there are 10 journals with details in 2019 and 2022, there are no scopus-indexed journals that match keywords, in 2020 there is an increase in research of scopus-indexed journals that match keywords, but in 2023 there is a decrease. Network Visualization has 347 items, 10 clusters, 10211 links, and 10724 total link strengths. The visualization Overlay shows that bright yellow has been researched while items that are opaque yellow such as class, mathematics, test, and others still lack research. The results of this study can provide space for other researchers to conduct further research.

Discovering Islamic marketing potential in shaping blockchain-­based halal logistic services: a bibliometric analysis

Purpose This paper aims to examine the Islamic marketing literature to uncover potential customer adoption behaviours and enhance the effectiveness of blockchain-based halal logistics services in catering to customer demands. The findings of this paper provide substantial contributions to the realms of both halal logistics services and Islamic marketing literature, delineating future paths for research. By delving into halal logistics practices, integration procedures and service provider performance, this paper assists stakeholders in enhancing halal logistics services to meet the changing demands of customers effectively. Design/methodology/approach This paper uses a systematic review incorporating bibliometric analysis to examine past and contemporary research topics, selecting and appraising contributions while analysing and consolidating data. A methodical approach has been used to identify, assess and incorporate pertinent studies on Islamic characteristics, traceability technology, blockchain integration and halal logistics practices. Findings After screening and analysing 139 selected documents with the VOS viewer, it is evident that among a 1,000 keywords, 15 stand out in terms of frequency and link strength. The research highlights the considerable academic interest in themes such as “blockchain”, “halal logistics” and “supply chain”, underscoring their importance. The findings of this paper help bridge the gap in Islamic marketing by linking technology with religious values. It suggests that the integration of blockchain technology in halal logistics enhances operational efficiency while aligning with both operational and Islamic marketing principles, promoting ethical conduct and transparency as key enablers. Practical implications The theoretical significance of this paper lies in establishing a correlation among three key research domains: technology, symbolised by blockchain; customer-centric operations, incorporating the halal supply chain and logistics within Islamic marketing. The outcomes reflect consumer behaviour and Shariah compliance. This integration has the potential to introduce innovative theoretical frameworks that encompass religious ethics in marketing, logistics and technological advancements. Originality/value This paper comprehensively analyses the intersection between blockchain technology, halal logistics, supply chain management and Islamic marketing. The paper has comprehensively analysed previous studies and outlined the future research path for blockchain technology in halal logistics and its application in Islamic marketing literature.

Structuring and empirical validation of a creative activity chain model for innovation in sustainable infrastructure development

This study constructs and empirically validates a Creative Activity Chain (CCA) structure model tailored for innovation in sustainable infrastructure development. In today’s competitive environment, fostering innovation is crucial for maintaining the relevance and effectiveness of infrastructure projects. The research underscores that a significant portion of a project’s long-term value is established during its initial concept and planning stages, highlighting the critical role of creativity in infrastructure development. The CCA model is developed through theoretical frameworks and empirical data, encompassing three key dimensions: creative subject chain, creative action chain, and creative operation chain. The model’s validity is tested with data from five large infrastructure development firms in China, involving 768 R&D staff as respondents. Rigorous statistical methods, including exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation modeling (SEM), and regression analysis, confirm the model’s robustness. The findings reveal significant positive correlations between the creative activity chain’s dimensions and the successful development of sustainable infrastructure projects. Additionally, the study examines the mediating effect of link strength within the creative activity chain, demonstrating its substantial impact on project outcomes. Implications for management include promoting diverse creative teams, systematic process management, and leveraging varied operational tools to enhance creativity in infrastructure development. This research contributes to the literature by introducing an integrated model for managing creative activities in sustainable infrastructure development, offering practical insights for improving innovation processes.

A bibliometric analysis of smallholder farmers’ climate change adaptation challenges: a SADC region outlook

Purpose This paper aims to explore pathways in which adaptation challenges may occur. Focus is on the barriers to adaptation, challenges to adaptation and maladaptation with reference to smallholder farmers in the Southern African Development Community region. Design/methodology/approach Bibliometric analysis techniques were used to track the literature on smallholder farmers’ adaptation challenges. Web of Science was the main data source. A total of 41 articles were retained for analysis and exported into Visualization of Similarities Viewer Software where the development of research on the subject, co-occurrence of keywords analysis, top publishers, citations and total link strength was done. Findings Results indicate that research on smallholder farmers’ adaptation challenges is not new but has gained more consideration post-2020. The main adaptation challenges emanate from perception barriers and constraints based on determinants of adoption, limitations for resilience building and achieving sustainable adaptation as well as contestations around Climate Smart Agriculture technologies. Practical implications Effective design of adaptation policies should center on prioritizing the needs of the local people. This would reduce the occurrences of smallholder farmers’ adaptation challenges, promote resilience building and contribute toward achieving sustainable adaptation. Originality/value It is equally important to document adaptation challenges. However, adaptation challenges are rarely shared with the same enthusiasm as its successes. This work focuses on the matter with the intention of conscientizing smallholder farmers to reduce the risk of repeating the same adaptation mistakes.

DEEP LEARNING APPROACH FOR ASPECT CATEGORY DETECTION: A BIBLIOMETRIC ANALYSIS

This article presents a quantitative and qualitative assessment of current research trends by conducting a bibliometric analysis of the sentiment analysis literature from 2020 to March 2024 using the Scopus database. Our focus is on the review of scientific documents, the arrangement of subject categories, the research trend in aspect category detection, the top 10 scholars that write the most number articles in aspect category detection and keyword trends. Our research shows that specialists in computer science, engineering, mathematics, medicine, decision science, material science, social sciences, business and management accounting, energy, and health are the most common topic groups in this industry. A study of keywords shows that terms like “BERT” and “deep learning” are frequently used together. This highlights the use of sophisticated models like BERT in this field and suggests a tendency to use innovative architecture to achieve better results. Conversely, although terms such as “sentiment analysis” and “aspect-based sentiment analysis” have modest frequency, their link strengths indicate a significant correlation with the main theme, emphasising the relationship between aspect category detection and sentiment analysis in research projects. we also provide the deep-learning technique used by the author for aspect category detection.

Dynamics of cardio-muscular networks in exercise and fatigue.

A fundamental question in cardiovascular and muscle physiology is how the heart operates in synchrony with distinct muscles to regulate homeostasis, enable movement and adapt to exercise demands and fatigue. Here we investigate how autonomic regulation of cardiac function synchronizes and integrates as a network with the activity of distinct muscles during exercise. Further, weestablish how the network of cardio-muscular interactions reorganizes with fatigue. Thirty healthy young adults performed two body weight squat tests until exhaustion. Simultaneous recordings were taken of a 3-lead electrocardiogram (EKG) along with electromyography (EMG) signals from the left and right vastus lateralis, and left and right erector spinae. We first obtained instantaneous heart rate (HR) derived from the EKG signal and decomposed the EMG recordings in 10 frequency bands (F1-F10). We next quantified pair-wise coupling (cross-correlation) between the time series for HR and all EMG spectral power frequency bands in each leg and back muscle. We uncovered the first profiles of cardio-muscular network interactions, which depend on the role muscles play during exercise and muscle fibre histochemical characteristics. Additionally, we observed a significant decline in the degree of cardio-muscular coupling with fatigue, characterized by complex transitions from synchronous to asynchronous behaviour across a range of timescales. The network approach we utilized introduces new avenues for the development of novel network-based markers, with the potential to characterize multilevel cardio-muscular interactions to assess global health, levels of fatigue, fitness status or the effectiveness of cardiovascular and muscle injury rehabilitation programmes. KEY POINTS: The heart operates in synchrony with muscles to regulate homeostasis, enable movement, and adapt to exercise demands and fatigue. However, the precise mechanisms regulating cardio-muscular coupling remain unknown. This study introduces a pioneering approach to assess cardio-muscular network interactions by examining the synchronization of cardiac function with muscle activity during exercise and fatigue. We uncover the first profiles of cardio-muscular interactions characterized by specific hierarchical organization of link strength. We observe a significant decline in the degree of cardio-muscular coupling with fatigue, marked by complex transitions from synchronous to asynchronous behaviour. This network approach offers new network-based markers to characterize multilevel cardio-muscular interactions to assess global health, levels of fatigue, fitness status or the effectiveness of cardiovascular and muscle injury rehabilitation programmes.

Digital Technology in Quality Management: Bibliometric Computational Mapping Analysis

This study used the bibliometric method and computational mapping analysis using VOSviewer to examine the development of research on the use of digital technology in quality management. Article data were obtained from Google Scholar using the Publish or Perish Reference Manager application. Data collection was conducted based on the keywords "quality management" and "digital technology”. The search found 779 relevant articles. The study period was the last 20 years (2003–2022) and the articles were indexed by Google Scholar. The results showed that research on digital technology in quality management could be divided into four terms. The first term was "quality management”, with 91 links, 1695 total link strength, and 530 related events. The second term was "total quality management”, with a total of 84 links, a total link strength of 1386, and 309 related events. The third term was "quality management system”, with a total of 61 links, the total link strength of 425, and 121 related events. The fourth term was "digital technology”, with a total of 53 links, the total link strength of 551, and 251 related events. The analysis also showed that the number of publications on digital technology in quality management tended to increase over the past 22 years, although it fluctuated every year. The peak occurred in 2020 with 78 articles. The results of this study could serve as a starting point for further research on this topic.

Mapping the Cost of Illness Publications in Five Decades: A Bibliometric Analysis and Publications Landscape

The study aims to map the "cost-of-illness" publications over five decades, identify research areas and conduct a bibliometric analysis of publications on the cost of illness. Study data was obtained from Web of Science database in April 2024. The basic information such as the number of citations, and yearly distribution of publications was extracted with Microsoft Excel, and the VOSviewer version 1.6.15 software program was used for maps. The publications were published between 1975 and 2024; total 879 publications were published from 2015 to 2024 April. A total of 7601 authors have contributed to advancing the literature on cost of illness. A total of 36369 citations have been cited by authors; 2022 was most cited year with 3032 citations; Boncz I. is the prominent author based on publications and total link strength and Leigh, JP is the most cited author; followed by Sebestyen, A. and Koenig, H.H. The top 10 publications have a total of 5352 citations. There has been significant increase in publications and citations related to the cost of the disease in the last five decades. Understanding the context of these publications is essential for researchers who want to work in this field.

Virtual Laboratory and Artificial Intelligence in Science Education: Bibliometric Analysis Based on Scopus Source

This study examines the development of research related to virtual laboratories and artificial intelligence in education. With the assistance of VOSviewer, this study aims to conduct computational mapping on bibliometric data of articles on the keywords: artificial intelligence, virtual laboratories, and education. The method used in this research is bibliometric analysis using VOSviewer. Article data obtained from Scopus-based data, article titles, and abstracts are used to guide the search process by referring to the keywords "laboratorium virtual" and "artificial intelligence in education". It found 359 allegedly relevant articles. The study period used as study material in this study was for the last 5.5 years, namely from 2018 to June 2023. The results of laboratorium virtual and artificial intelligence research in education can be separated into 3 terms, namely artificial intelligence, laboratorium virtual, and education. The term artificial intelligence has 304 links with a total link strength of 12065, the term Laboratorium virtual has 416 links with a total link strength of 5451 links with an accuracy of 212 terms, and the term education has 399 links with a total link strength of 3142 accuracies of 113. The analysis results indicate a significant increase in research related to virtual laboratories and artificial intelligence in education over the past four years. However, the relationship between virtual laboratories and artificial intelligence in education is still relatively rare. In fact, there is no existing relationship between virtual laboratories and artificial intelligence. Based on this information, the opportunity for developing research on virtual laboratories based on artificial intelligence in the field of education is substantial.

Análisis Bibliométrico sobre la Auditoría Tributaria en Web of Science

The objective was to carry out a bibliometric analysis on the Tax Audit in Web of Science, 2024. 177 documents were analyzed with the following filters: keywords ("audit", "tax audit" and "taxation"), original open access articles, in English, Spanish and Portuguese between 2005-2024. VOSviewer was used to analyze categories of co-citations, co-occurrences and co-authorships. It is revealed that 98.3% of the articles are in English; Accounting Review stands out with about 463 citations and a total link strength of 21,110; the keywords "taxation" (53 mentions and 162 strong links) is the most popular; and England (56 documents) is the country with the highest production. It is concluded that research on Tax Audit tends to have increasing relevance in recent years and the phenomenon is related to tax policy and tax compliance. Finally, it is necessary to promote international collaborations and strengthen research production in less represented countries.

Past, Present, and Future of Liver-Brain Axis in Alzheimer's Disease: ABibliometric Review.

No effective drugs currently exist to cure Alzheimer's disease (AD) due to its complexity and the lack of understanding of the involved molecular signaling and pathways. The relationship between liver health and AD is now widely recognized. Still, molecular links and shared pathways between the liver and brain remain unclear, making the liver-brain axis in AD therapies a new area for exploration. However, bibliometric studies on this topic are lacking. This study aims to review the liver-brain axis in AD and identify future research hotspots and trends through bibliometric analysis. Articles and reviews related to AD and liver and its related diseases were searched in the Web of Science Core Collection (WoSCC) database up to 2024. Data were processed and visually analyzed using VOSviewer, CiteSpace, and Pajek. We collected 1,777 articles on AD and liver and its related diseases from 2,517 institutions across 80 countries. Keyword cluster analysis identified 11 clusters, with 'insulin resistance,' 'amyloid-beta,' 'apolipoprotein-E,' 'oxidative stress,' and 'inflammation' appearing most frequently, and exhibiting strong total link strength. These results indicate that these topics have been the primary focus of research on the liver-brain axis in AD. This study is the first to comprehensively analyze the liver-brain axis in AD using bibliometric methods. The research results identify recent research frontiers and hotspots, aiding scholars in gaining a deeper understanding of the correlation between AD and the liver.