Network Visualization Analysis Research Articles

Public Health and Children’s Subjective Well-Being

AbstractIn recent years, the study of children's subjective well-being has garnered escalating global attention, with its research themes becoming increasingly diverse. However, this field still lacks a systematic review and analysis. Drawing upon the Web of Science database, this study retrieved 32,112 relevant articles published between 2003 and 2022, focusing on the theme of children's subjective well-being. After rigorous screening, 23,711 publications were ultimately retained for analysis. Utilizing bibliometric methods, this study conducted network visualization analysis across multiple dimensions, including countries, institutions, journals, authors, and keywords, aiming to comprehensively reveal the current research landscape of children's subjective well-being. Furthermore, theme modeling techniques were employed to delve into the patterns of theme evolution, and cluster analysis was conducted to categorize related themes. Through qualitative analysis, this study uncovered the developmental trajectory and future research directions in the field of children's subjective well-being. The findings indicate that, in the realm of children's subjective well-being research, developed countries such as those in Europe, America, and Australia have contributed over 30% of the research efforts, both in terms of publication volume and impact. Among them, the United States holds a leading position. The research themes have gradually evolved from an initial focus on the children themselves to exploring their surrounding environments and further delving into the psychological impacts and well-being of children amidst public health emergencies. Notably, the outbreak of the COVID-19 pandemic has prompted scholars to delve deeper into children's well-being, shifting the focus of research from mere exploration of mental health to a more nuanced investigation of psychological impacts. Looking ahead, areas such as public health, psychological impacts, and children's dietary health will emerge as crucial directions for future exploration in the field of children's subjective well-being research, offering significant potential for investigation.

Effects of soil microbial ecology on ginsenoside accumulation in Panax ginseng across different cultivation years

The quality of ginseng is greatly influenced by ecological factors, especially soil factors. However, there are few reports on the association between the physicochemical properties of ginseng rhizosphere soil, enzyme activity, microbial bacterial community, and ginsenoside content accumulation in ginseng planted at different ages. In order to investigate the relationship between the soil microbial ecology of ginseng and the content of ginsenosides, this study compared the differences in the rhizosphere soil microecological environment and ginsenoside accumulation between ginseng planted for one, two, and three years, using soil without ginseng cultivation as a control. The results showed that monomer saponins Ro, Re, Rf, Rb1, and total ginsenoside content increased significantly (P < 0.05), while monomer saponins Rb2, Rd, Rh2, and Rg3 content decreased significantly in three-year-old ginseng, (P < 0.05). And soil pH, soil bulk weight and soil enzyme activity in ginseng rhizosphere soils altered the abundance and diversity of rhizosphere soil bacterial community. Redundancy analysis and Pearson correlation analysis revealed that soil pH, soil bulk density, soil urease, and protease were the primary factors influencing the bacterial community in the soil around roots of one, two, three years old ginseng. Co-occurrence network visualization analysis indicated that seven bacterial communities, Planctomycetota, Methylomirabilota, Verrucomicrobiota and Acidobacteriota at the phylum level, Vicinamibacterales_unclassified, Vicinamibacteraceae_unclassified and Candidatus_Udaeobacter at the genus level, had a significant effect on the synthesis of ginsenosides. In summary, soil urease, pH, and soil bulk density in agricultural soils can regulate soil physicochemical properties, soil enzymatic activities, and soil bacterial community abundance. These factors are key drivers of the ginseng soil microbial ecology in ginseng cultivation. These studies will provide a scientific basis for subsequent optimization of soil improvement techniques for cultivated ginseng in farmland by improving the soil microbial ecology.

Intelligent construction technology based information sharing network for prefabricated building supply chain: a social network analysis approach

PurposeIn the context of Industry 4.0, intelligent construction technologies (ICT) represented by information technology and networking will undoubtedly provide new impetus to the development of the prefabricated building supply chain (PBSC), but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies. Therefore, this paper aims to reveal the interactions between stakeholders and clarify the critical risk nodes and interactions in information sharing of PBSC (IS-PBSC), and propose targeted risk mitigation strategies.Design/methodology/approachFirstly, this paper creatively delineates the risks and critical stakeholders of IS-PBSC. Secondly, Data is collected through questionnaires to understand the degree of risks impact. Thirdly, with the help of NetMiner 4 software, social network analysis is conducted and IS-PBSC risk network is established to reveal critical risk nodes and interactions. Finally, further targeted discussion of critical risk nodes, the effectiveness and reasonableness of the risk mitigation strategies are proposed and verified through NetMiner 4 software simulation.FindingsThe results show that the critical risks cover the entire process of information sharing, with the lack of information management norms and other information assurance-related risks accounting for the largest proportion. In addition, the government dominates in risk control, followed by other stakeholders. The implementation of risk mitigation strategies is effective, with the overall network density reduced by 41.15% and network cohesion reduced by 24%.Research limitations/implicationsIn the context of Industry 4.0, ICT represented by information technology and networking will undoubtedly provide new impetus to the development of the PBSC, but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies.Originality/valueBased on the results of risk network visualization analysis, this paper proposes an ICT-based IS-PBSC mechanism that promotes the development of the integration of ICT and PBSC while safeguarding the benefits of various stakeholders.

Diving into a Heritage Metaverse: Learning from End User-driven Experiences and Perspectives to Enhance Virtual Heritage Interpretation

This study aims to explore the potential of the metaverse to determine if it can be an effective medium for realizing an end-user-driven heritage interpretation platform. To this end, we conducted an in-depth user-study using a combination of qualitative experimental methods (cultural probes and a focus group interview) to obtain data on the thought processes, experiences, and responses of end-users within the metaverse called the Peaceful Hill, a heritage metaverse created by the National Museum of Korea and hosted on Zepeto, a metaverse platform. The twelve participants in their 20s were recruited for a five-day experiment. Through an inductive thematic study, four themes related to the end-user experience in the process of virtual heritage interpretation were identified, as follows: structural components as virtual wider settings, interactive components as life-logging experience, mediating components as an actor, and heritage interpretation components. Then, based on the visual network analysis, we further explored the multiple connections and reciprocal influences of the above themes to uncover differences and similarities in user-perceived experiences in the metaverse compared to existing virtual environments. In addition, we offered insights and design considerations for establishing a participatory heritage interpretation experience in the metaverse.

The impact and management of internet-based public opinion dissemination during emergencies: A case study of Baidu News during the first wave of coronavirus disease 2019 (COVID-19).

The coronavirus disease 2019 (COVID-19) public health emergency has had a huge impact worldwide. We analyzed news headlines and keywords from the initial period of COVID-19, and explored the dissemination timeline of news related to the epidemic, and the impact of Internet-based media on the public using lifecycle theory and agenda-setting theory. We aimed to explore the impact of Baidu news headlines on public attention during the first wave of COVID-19, as well as the management mechanism of regulatory departments for social public opinion. We searched Baidu News using the keywords "Novel Coronavirus" and "COVID-19" from 8 January to 21 February 2020, a total of 45 days, and used Python V3.6 to extract news samples during the first wave of the epidemic. We used text analysis software to structurally process captured news topics and content summaries, applied VOSviewer V6.19 and Ucinet V6.0 to examine key aspects of the data. We analyzed the impact of Baidu News headlines on social opinion during the first wave of COVID-19 in the budding, spread, and outbreak stage of the information lifecycle. From clustering visualization and social network analysis perspectives, we explored the characteristics of Baidu News during the initial stage of the COVID-19. The results indicated that agenda-setting coverage through online media helped to mitigate the negative impact of COVID-19. The findings revealed that news reporting generated a high level of public attention toward a specific emergency event. The public requires accurate and objective information on the progress of COVID-19 through Baidu News headlines to inform their planning for the epidemic. Meanwhile, government can enhance the management mechanism of news dissemination, correct false and inaccurate news, and guide public opinion in a positive direction. In addition, timely official announcements on the progress of the COVID-19 outbreak and responses to matters of public concern can help calm tensions and maintain social stability.

Bibliometric Analysis: The Evolution of Entrepreneurship among Islamic Boarding School Students from an Islamic Economic Law Perspective

The increasing interest in entrepreneurship among students of Islamic boarding schools within the framework of Islamic economics has garnered significant scholarly attention. This research employs bibliometric analysis by accessing the Scopus database to examine research trends related to entrepreneurship among Islamic boarding school students from 1996 to 2024. The aim is to identify research trends related to entrepreneurship among students. The research results indicate a growing interest in student entrepreneurship in Islamic boarding schools, particularly in 2019 and 2022. The focus is on entrepreneurial orientation, knowledge management, innovation, implementation strategies, and organizational performance. Visualization network analysis is highly relevant to the Islamic Economic Law Perspective and efforts to combine religious values with modern business principles in the context of Islamic boarding schools. This research has broad implications, not only for developing theory and understanding of Islamic entrepreneurship but also for shaping practices and policies that support entrepreneurship development based on Islamic values in Islamic boarding schools and the general public.

Assessing botanical compatibility in gin production: A mathematical model and network analysis approach

This study introduces a novel methodology for evaluating volatile-compound-based compatibility in 160 botanicals essential for gin production. It establishes a comprehensive botanical pairing system through network analysis, mathematical modeling, and indicator development. Key findings include the benefits of strategic botanical inclusions to recipes for compatibility improvement and a numerical compatibility assessment, revealing an average indicator of 1.78 across thirty validated gin recipes, with a significant threshold at 1.36 indicating superior compatibility. Additionally, two distinct indicators were formulated—one focusing on the percentage of shared compounds due to a specific botanical and another on the botanical’s representation in the recipe. A visual network analysis replaces the traditional aroma classification wheel, offering a comprehensive view of aromatic profiles. This research transforms gin formulation, supported by an extensive database and validated methods.

A comparative study of interactive animation and traditional animation

The article conducted a comprehensive study on the development trends of animation. Through the collection of relevant literature on the subject, it examined the research's impact in various countries. The study utilized the CiteSpace analysis tool to conduct a detailed quantitative analysis of the evolution of the animation field in recent years, covering literature and academic publications from 1990 to 2022. In terms of analytical methods, the study employed various approaches, including visual network analysis, collaboration network analysis, keyword analysis, co-contribution network analysis, and co-citation network analysis. These methods were applied to detect visual networks within the animation field. Through these analytical techniques, the study showcased research hotspots, collaboration relationships, keyword trends, and academic contribution networks within the animation field. The findings revealed a steady increase in the number of publications and papers in the animation field in recent years, indicating that animation has become a highly researched topic. To delve deeper into the comparison between interactive animation and traditional animation, the study employed CiteSpace bibliometric technology and selected 4567 English-language and 1346 Chinese-language documents from the ScienceNet and China National Knowledge Infrastructure databases. Through a systematic evaluation, the study conducted a thorough analysis of the current status of interactive animation and traditional animation, highlighting their differences and projecting potential future trends for interactive animation. This comprehensive research provides a holistic perspective on academic studies in the animation field, contributing to a better understanding of the evolution and future directions of the animation industry.

Research Trends in the Study of Acceptability of Digital Mental Health-Related Interventions: A Bibliometric and Network Visualisation Analysis

The acceptability of digital health interventions is a multifaceted concept that is central to user engagement. It is influenced by cultural and social norms and it is, also, a key consideration for intervention development and evaluation. For this reason, it is important to have a clear overview of how research in digital interventions’ acceptability has evolved, what type of measures or assessments have been most frequently utilised, and what may be the implications for the knowledge area and future research directions. The purpose of this bibliometric and network visualization analysis was to explore the main research patterns in the study of the acceptability of digital mental health interventions and highlight the key characteristics of knowledge production on this topic. The Web of Science was searched for relevant primary studies, with 990 documents selected for inclusion in this bibliometric analysis. Publications’ metrics, text and author keyword analysis, and bibliographical coupling of the documents provided insights into how technological developments, specific research interests, research priorities, and contexts have shaped research in the field. The main differentiation in acceptability approaches emanated from the studies’ research designs, the stage of intervention development and evaluation, and the extent to which there was a focus on user attitudes, experience, and engagement. These differentiations further indicate the importance of having clarity as to what concepts or elements of acceptability a study addresses as well as approaches that have the potential to address the complexities of acceptability.

Bibliometric Analysis on Stem Cell Transplantation Treatment for Premature Ovarian Failure

To carry out bibliometric analysis on stem cell transplantations for premature ovarian insufficiency (POI), and quickly grasp the clinical significance and potential of stem cell transplantation in the treatment of POI, the current study used the Web of Science core collection to retrieve relevant literature using keywords “stem cells” and “primary ovarian dysfunction”. VOSviewer was used for network visualization analysis of key words, authors, institutions, and countries. The results showed that, annual publications increased steadily from 2000 to 2023 with some fluctuations. China, Shanghai Jiao Tong University, and “Human Reproduction” are the countries, organizations, and journals with the highest output. The keyword map reflects that fertility preservation and hormone replacement therapy are currently hot topics in the treatment of POI. Mesenchymal stem cells (MSCs) and in vitro activation may have the highest potential to be applied in the future. Based on the current bibliometric analysis, the study on clinical efficacy, prognosis, and mechanism of POI treatment using MSCs and their exosomes is a research hotspot with great potential in this field.

Application and Feasibility Analysis of Network Models and Data Analysis in Combating Organized Crime

This article discusses and analyzes in detail the development potential and application of big data mining and network visualization analysis in combating organized crime. Firstly, the article emphasizes the importance of combating criminal gangs and organized crime in modern society, comparing them to the foundation of stable national development and the cornerstone of national progress. Then it explores the security challenges faced by modern society and more issues related to organized crime, including the problem of crime caused by the wealth gap caused by urbanization and economic development, as well as the outdated technology for cracking down on existing security crimes. This article provides a detailed introduction to the potential of big data mining and network visualization, as well as the advantages of these technologies in practical applications. It covers the collection, processing, sharing, and application of data. At the same time, network visualization is used to visualize crime data, helping decision-makers better understand the current situation and problems of public security and organized crime. The article also discusses the application of artificial intelligence and mobile internet technology in combating organized crime. And the potential of big data in improving urban governance. Finally, this article looks ahead and emphasizes that big data mining and network visualization analysis will continue to play an important role in optimizing social security, indicating the broad prospects of these technologies in the future transportation field.

Mobile wallet payments- A Systematic literature review with Bibliometric and Network Visualization analysis over two decades

Mobile wallet payments- A Systematic literature review with Bibliometric and Network Visualization analysis over two decades

Network analysis of the relationship between social support and quality of life in patients with epilepsy

BackgroundIdentifying important types of social support for patients with epilepsy is valuable to construct an effective system for support in daily life. However, previous studies have been inconsistent in identifying the most important types of social support for better quality of life (QOL) due to the high correlations between the social support factors. The present study employed network visualization analysis to identify the relationships between QOL and types of social support. MethodsTwo hundred and eighty-three patients with epilepsy (age range: 18 to 75 years) completed questionnaires of the Medical Outcomes Study Social Support Survey (MOS-SSS) and the Quality of Life in Epilepsy Inventory-31-Problems in the epilepsy monitoring unit at Tohoku University. The MOS-SSS was established to measure the four types of social support including emotional/informational support, tangible support, affectionate support, and positive social interaction. Our network visualization analysis represented the entire structure of the interrelationships between the four functions of social support and QOL. In addition, the relative importance of each function of social support were estimated by the centrality indices using three commonly used centrality indices: strength, betweenness, and closeness. ResultsThe visualized network showed that positive social interaction and emotional/informational support were directly associated with QOL, whereas tangible support and affectionate support were not. Positive social interaction had the highest value for all three centrality indices and affectionate support had the second highest. Therefore, positive social interaction had the strongest connection to the other functions of support. DiscussionOur network analysis and centrality indices findings showed that positive social interaction is the most important within the network of four types of social support and QOL. The emotional informational function is also important for directly improving QOL but is less related to the other functions. The affectionate function might be an indicator of whether a patient has a foundational relationship that leads to other functions of support. ConclusionThese results showed the importance of increasing positive social interaction in the social environment of patients with epilepsy. Therefore, practitioners need to encourage patients with epilepsy to increase their positive social interactions such as doing something enjoyable with others or someone to associate for relaxation to ensure high QOL. Connections outside the epilepsy support are important, such as having fun regardless of epilepsy, rather than only providing emotional or tangible support for epilepsy.

키워드 네트워크 분석 방법을 활용한 유아교육에서의 디지털 관련 연구 동향

This study aimed to analyze the trends in research related to digital aspects in early childhood education by collecting relevant research and conducting keyword network analysis to understand the evolving connections among key terms. The goal was to identify any changes or emerging patterns in research on digital technology and young children. The goal was to identify any emerging patterns or changes in the field of research on young children and digital technology. To achieve this, a total of 661 academic papers were collected from scholarly databases (RISS, KCI, KISS) by searching for keywords such as 'young children digital', 'media', 'smart', 'multimedia', and 'edutech'. Keywords were extracted from these papers after refinement. The analysis included frequency distribution, network visualization, and centrality analysis of the extracted keywords. The research findings are as follows: The research findings indicate, firstly, that studies related to digital technology and young children have shown a consistent increase in trends since 2011. Key keywords such as 'utilization,' 'young children,' 'media,' 'perception,' 'early childhood educators,' and 'digital' emerged as prominent in this research. Secondly, an examination of the research trends over different time periods revealed that studies have increasingly focused on the 'utilization' of 'multimedia', 'smart', and 'digital' technologies, driven by shifts in educational paradigms due to digital transformation. Recently, 'digital', 'play', 'competence' have emerged as central keywords. The outcomes of this study provide valuable insights for educators and children navigating the digital society, aiding in various aspects of support and guiding future research directions.

Network Pharmacology Studies on the Molecular Mechanism of Hashimoto's Thyroiditis Treated with Shutiao Qiji Decoction.

In recent years, the number of patients with Hashimoto's thyroiditis has been increasing, and traditional Chinese medicine ingredients and combinations have been applied to treat Hashimoto's thyroiditis to increase efficacy and reduce side effects during the treatment process. Shutiao Qiji Decoction is one of the Chinese traditional medicine prescriptions, which is commonly used to treat cancer, tumor, etc. It is also used for thyroid-related diseases in the clinic. Hashimoto's thyroiditis is an autoimmune disease. In this study, the mechanism of Shutiao Qiji Decoction in treating Hashimoto's thyroiditis was studied through network pharmacology and molecular docking verification. Each Chinese medicine ingredient of Shutiao Qiji Decoction was retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. The related genes of HT were searched from the UniProt and GeneCards databases. Meanwhile, we used Cytoscape to construct the protein-protein interaction (PPI) visual network analysis, and used the search tool to search the database of Interacting Genes (STRING) to build a PPI network. These key proteins were enriched and analyzed by molecular docking validation, Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Hashimoto's thyroiditis disease model was established in SD rats, and SQD was administered by gavage after the successful establishment of the model. After 6 weeks of continuous administration of the drug by gavage, tissue samples were collected and the thyroid and spleen tissues were visualized by HE staining to verify the therapeutic effect. The results showed that there were 287 TCM active ingredients, 1920 HT-related disease targets, and 176 drug and disease targets in SQD. Through PPI analysis, GP analysis, and KEGG analysis of the common targets of drugs and diseases, we found their pathways of action to be mainly cancer action pathway, PI3K-AKT signaling pathway, and T-cell action pathway. The active ingredients of the drugs in SQD, malvidin, stigmasterol, porin-5-en-3bta-ol, and chrysanthemum stigmasterol, were docked with the related target proteins, MAPK, GSK3β, TSHR, and NOTCH molecules. The best binding energies obtained from docking were mairin with TSHR, stigmasterol with TSHR, poriferast-5-en-3beta-ol with MAPK, and chryseriol with GSK3β, with binding energies of -6.84 kcal/mol, -6.53 kcal/mol, -5.03 kcal/mol, and -5.05 kcal/mol, respectively. HE staining sections of rat thyroid and spleen tissues showed that SQD had a therapeutic effect on Hashimoto's thyroiditis and restored its immune function. It is verified by molecular docking results that Shutiao Qiji Decoction has a potential therapeutic effect on Hashimoto's thyroiditis in the MAPK/TSHR/NOTCH signal pathway, and that the main components, mairin, stigmasterol, poriferast-5-en-3beta-ol, and chryseriol play a role in it. SQD has been shown to have a good therapeutic effect on Hashimoto's thyroiditis.

Network Nature of Translation Constellations: Translation Department at a Regional Commercial Enterprise

This article presents an exploratory study conducted using functional and sociocognitive approaches in light of the “material turn” in Translation Studies. It provides a review of works that apply actor-network theory (ANT) and the concept of distributed cognition to the study of translation activities. It also explores the possibility of adopting in translation research the data collection, processing and visualization techniques developed to describe activities in hybrid environments combining face-to-face and mediated interaction. The authors discuss a way of including the artifacts in the translation situation model, following the positions of ANT, visual net-work analysis, and M. Zwilling’s concept of a translational constellation. The objective of the paper is to evaluate a complex method-ology aimed at describing translators’ work-place conditions and their network interactions in a realistic way. The study is based on a semi-structured interview (120 min) with a representative of the translation department at a commercial enterprise in Chelyabinsk, Russia. It shows how specific tasks are performed in a distributed cognitive network, what role is played by such artifacts as a server solution, a terminology database, and email; and how the translation commissioners’ intention can be distributed in a network of interconnected entities.

Research Trends and Future Works on Student Creativity in the Context of Sustainability: A Bibliometric Analysis

Education at the university level must provide learning experiences that facilitate achieving 21st-century skills, one of which is creativity. This study aims to reveal research trends and future work related to creativity at the university level. The method used is a preferred reporting item for systematic review and meta-analysis protocols (PRISMA-P) and bibliometric analysis of the scopus database using vosviewer software. The author selected 778 documents that were considered relevant from English-language journal articles through a selection process. The results show that research topics related to creativity in higher education are still emerging and increasing. The results of the bibliometric analysis using the co-occurrence type of analysis show that there are several dominant keywords outside the search query, including human (36), engineering education (35), critical thinking (31), innovation (28), education for sustainable development (26), and project-based learning (21). Through network visualization analysis, information on the relationship between keywords and the strength of their relationship is obtained. The visualization of overlays shows several topics that are still growing and deserve to be researched, such as entrepreneurs, virtual reality, self-efficacy, etc. Through the help of the openrefine software, the author can find several future works related to specific issues. Several new keywords for future research can be determined. This study concludes that bibliometric analysis through vosviewer has successfully demonstrated trends and future work for creativity in higher education

An Update on Semaglutide Research: A Bibliometric Analysis and a Literature Review.

This study analyzes the most relevant authors, sources, cooccurrence of keywords, thematic map, and trend topics of the most recent and most cited research papers on semaglutide, a glucagon-like peptide-1 receptor agonist (GLP-1 RA). Also, the content of the 25 most cited papers is summarized. A total of 2995 results appeared in an online electronic search performed on 14 August 2023 in the Scopus database using the termsemaglutide. The most recently published 500 articles and most cited 200 documents were selected for bibliometric analysis. Network analysis visualization was conducted with the help of the VOSviewer software (version 1.6.18) (Centre for Science and Technology Studies, Leiden, the Netherlands) and Biblioshiny (it is a shiny application providing a web interface for bibliometrix) (Departmentof Economics and Statistics, University of Naples Federico II, Naples, Italy). After excluding duplicates and editorials, the data analysis found that 495 most recent documents were published in 279 journals by 2461 authors, and 200 most cited papers were published in 103 sources by 1241 authors. There is an increasing trend in the number of research papers from 2014 to 2022, with a peak in 2022. The most relevant authors in the most recent semaglutide research papers are Chen and Zhang. The pertinent authors of the most cited research papers on semaglutideare Lingvayand Khunti. The most common keywords used in the most recent and most cited research papers aresemaglutide, obesity, diabetes mellitus type 2, glucagon-like peptide-1, glucagon-like peptide-1 receptor agonist, antidiabetic agent, liraglutide, and cardiovascular disease (CVD). The most relevant source is "Diabetes, Obesityand Metabolism"for the research papers on semaglutide. Trend topic analysis suggests that most of the research between 2020 and 2022 on semaglutide was done on non-insulin-dependent diabetes mellitus. The most cited papers provide essential insights into using semaglutide in managing type 2 diabetes mellitus (T2DM), obesity, and related conditions, along with their potential benefits, side effects, and possible mechanisms of action. This analysis highlights that the pharmacological effects of semaglutide extend beyond its role as a glycemic regulator.

DeepDense: Enabling node embedding to dense subgraph mining

Dense subgraphs convey important information and insights about a graph structure. Several applications, such as graph visualization, graph summarization, and complex network analysis rely on discovering the dense subgraphs available within the target graph. This enumeration problem has been intensively addressed by several research communities but remains a challenging problem because of its importance and use. This problem generalizes the clique problem and is thus NP-hard and not approximable in polynomial time in general graphs.In this paper, we propose to deal with this problem in a specific application case where the type of the discovered dense subgraphs is important. This is the case of graph summarization for example. However, existing dense subgraph discovery algorithms are either dedicated to specific kind of structures such as cliques and bicliques or are too general and list the dense subgraphs without giving their types. To deal with this issue, we provide a unified approach that lists dense subgraphs and provides their types. Our approach relies on deep learning. More precisely, we enrich exiting structural node embedding with extra information, computed on node neighborhoods, to effectively capture their belonging to dense subgraphs. We evaluate our approach on several datasets to attest its efficiency and its effectiveness on two main applications: graph summarization and graph clustering. Our results show that our method significantly improves the compression rate in graph summarization, achieving up to 30% size reduction for the largest graphs tested and exceeding 80% for sparse graphs. Additionally, even for highly dense graphs, our method consistently achieves a non-zero AMI score, outperforming other approaches on the clustering application.

Circular Economy: A Bibliometric Analysis of Publications in the Web of Science

The circular economy, which is considered an alternative to the linear economy, is one of the concepts explored within the scope of the sustainable development approach. With the worsening of resource usage and environmental challenges in recent years, research on the circular economy has grown dramatically. In its most basic form, the circular economy is based on the reduction of output and waste, as well as the recovery of waste.&#x0D; &#x0D; This study aims to make a bibliometric analysis of the concept of circular economy, which is of great interest in the academic field. A quantitative approach for reviewing literature in any discipline is bibliometric analysis. In this regard, this study reviewed the literature and did a bibliometric analysis of the papers published in Web of Science between 2004 and 2022. The study examined 4182 studies titled 'circular economy' on the Web of Science. VOSviewer software was utilized in the study to conduct a systematic bibliometric analysis as well as a visual network analysis. As a result of the analysis, it has been revealed that the leading country in the circular economy is China, the institution is European Research Universities Association Leru, Journal is Sustainability and the researcher Patrizia Ghisellini.