Purpose: This study's objective was to examine international research trends in behavior management that had been written about in journals that were indexed by Scopus and authored by scientists from all around the world.Patients and methods: We examined publications in the Scopus database using bibliometric and content analysis. We only retrieved English-language articles. The VOSviewer program was used for content analysisResults: We found 808 papers on behavior management during the previous 50 years by following the study strategy. The study concentrated more on authors, nations, institutions, journals, documents, and keywords, as well as the annual scientific production (classification by subject area and document type)Conclusion: The finding prompts a discussion regarding behavior management for next research.

The Land Surface Temperature (LST) is an essential indicator for analyzing the Surface Urban Heat Island (SUHI). A factor contributing to its occurrence is the reflections of the different materials in urban and rural areas, which significantly affect the energy balance near the surface. Therefore, recent studies have increasingly used the Local Climate Zones (LCZ) classification system to discriminate those urban areas. Therefore, our study aims to do a systematic review using the PRISMA method of LCZ classification applied to understand the LST and the SUHI phenomenon. At first, it was found in the scientific literature 10,403 articles which, after passing through filtering stages, resulted in 51 that were further analyzed. Our results showed that these articles were very recent, beginning in 2016. However, presenting an increasing trend. China was the country with more studies. Landsat and TERRA/AQUA sensors appeared in 82% of the studies. The method that appears the most to LCZ definitions is from the World Urban Database. Finally, considering the current climatic changes, this systematic review can help new studies on SUHI identification through LCZ in different world areas using remote sensing data to estimate the LST.

Mercury is classified as one of the world’s most toxic and dangerous pollutants. It tends to bio-accumulate and biomagnify within the trophic chain and is persistent. Various approaches are available to remediate Hg-affected sites, including phytoremediation, which includes the use of plants to clean up contaminated environments. Phytoremediation of mercury contamination is at-tracting increasing attention because of its advantages: it is environmentally friendly, inexpensive, simple, and can improve soil fertility. In this report, VOSviewer, and Bibliometrix software were used to analyze 457 and 697 documents published from 2000 to 2023, retrieved from the data-bases WoS and Scopus, respectively. China, India, the United States, and Spain are the top four most productive countries. The largest topic area was environmental sciences, and the Chinese Academy of Sciences was the organization that contributed the most to the overall number of pub-lications. The keywords with the highest frequency, excluding phytoremediation and mercury in WoS, were heavy metals, accumulation, cadmium, soils, and phytoextraction. In Scopus, the most frequent keywords were bioremediation, heavy metals, soil pollution, bioaccumulation, biodeg-radation, and environmental. From the above analysis, we concluded that future research should focus on 1) finding native plants, 2) increasing remediation ability through assisted phytoremedi-ation, 3) studies of molecular mechanisms in plants with phytoremediation potential, and 4) ge-netic engineering applications. This study provides insight into trending themes and serves as a reference for future research.

This bibliometric study explores the cryptocurrency accounting (CA) literature and the connections between authors, institutions, and countries where cryptocurrency activity involves transactions that must be legally recognized in accounting, assure accuracy and reliability for auditing, and adhere to tax compliance. The design involves data selection from Web of Science Core Collection (WoS) and Scopus, published between 2007 - 2023. The technique helps identify influential publications, collaboration networks, thematic clusters, and trends in research on CA using tools VOSviewer, Biblioshiny, and MS Excel. The originality of the study lies in its dual role as a support for accounting professionals and academics to develop innovative solutions for the challenges posed by crypto technology across core accounting areas: financial and managerial accounting, taxation, and auditing. The findings offer insights into the themes mentioned, and even if the collaboration between the authors is not very developed, the innovation and public recognition of the subject could raise researchers' interest. The limitation of the dataset is that it does not cover all relevant publications in a different period from the one in which the data was retrieved, 9-11 May 2024. This review might need periodic updates because the CA landscape is constantly changing.

(1) Background: The social robot interaction design is critical in determining acceptance and user experience. However, few studies have systematically discussed the current focus and future research directions of social robot interaction design from a bibliometric perspective. Therefore, in order to identify the latest research progress and evolution trajectory of research hotspots in social robot interaction design over the last decade. (2) Methods: based on 2416 papers related to social robot interaction design collected in the Web of Science (WOS) database, a comprehensive review was conducted by using bibliometrics to draw a knowledge map using VOSviewer and CiteSpace in an integrated manner. (3) Conclusions: The current research hotspots of social robot interaction design mainly focus on #1the study of human-robot relationships in social robot, #2Research on the Emotional Design of Social Robot, #3research on social robot for children's psychotherapy, #4research on companion robot for elderly rehabilitation, and #5research on educational social robot. The reference co-citation identifies the classic literature that forms the basis of the current research, which provides theoretical guidance and methods for the current research. Finally, we discuss several future research directions and challenges in this field.

Blockchain is a path-breaking paradigm, and cryptocurrencies are one of the main application areas of Blockchain technology. Bitcoin leads the cryptocurrency markets, both in terms of market capitalization and in scientific interest. In this paper, we performed a comprehensive bibliometric study of the Bitcoin-related literature. Using the Scopus database, we created a sample that comprises 4495 documents written in the 2011–2020 period. Furthermore, we provided insights about dimensions such as the change in the number of publications over the course of years, the main research areas, types of published documents, most important platforms and sources of Bitcoin publications, highly cited studies, productive authors, author’s countries, and finally main funders of Bitcoin-related research. Lastly, our bibliometric study manifests the current state and future path of Bitcoin literature from distinct perspectives.

The objective of this work is to analyze publications on the Balanced Scorecard (BSC), since 1956 (in the last sixty-five years), identifying evolution trends. Based on bibliometric techniques, the study was carried out based on data available in the Web of Science database through a systematic literature review. Web of Science is one of the main databases in the world, indexing the most cited journals in different areas of research and thus providing a set of data, essential for systematic analyses, including areas of study, list of journals, year of publication, citations from articles, among other relevant information. Because the chosen database is very complete, multidisciplinary and access to the use of Vosviewer software, which we used in this study, is acceptable.From the systematic search, 694 articles published until December 2021 were identified. The analysis of these publications indicates a growing trend in the publication of articles on BSC, highlighting partnership publications as well as their dispersion across journals from different areas.Most are qualitative studies (namely case studies) and questionnaires, as the main method of data collection. The main themes studied, we found that there are several articles on the application or integration of the BSC as a management model and that the studies are essentially concentrated on large companies belonging to the private sector, to the detriment of small and medium-sized companies and public and non-profit organizations profitable.

Objective: To explore the hot spots and development trends of community public health research. Methods: The literature related to this topic was searched in CNKI and PubMed databases, and the trend map of the number of articles was drawn according to the obtained data. The included literature were analyzed with Vosviewer software for keyword and author co-occurrence, and CiteSpace 6.3.R1 Basic software was used for mechanism co-occurrence, key emergence and clustering analysis, and timeline distribution map drawing. Results: 189 Chinese literature and 77 English literature were selected. The Chinese literature focused on “community public health service, emergency management, and community governance”, and the research trend was “community public health emergency management and community governance”; English literature focuses on “nursing education, health education, human qualitative research”. Conclusion: Although the Chinese and English literature shows that scholars in this field have different emphases, the primary community health is the key and difficult point to realize the national public health service project, and improving the basic public health service in the primary community is related to the health of all the people, so it is very important.

Somatic cell nuclear transfer (SCNT) is a reproductive biotechnology with great potential in the reproduction of different species of zootechnical interest, including sheep. This study aimed to carry out a bibliometric analysis of scientific papers published on the application of SCNT in sheep reproduction in the period 1997-2023. The search involved the Science Citation Index Expanded and Social Sciences Citation Index databases of the Main Collection of Web of Sciences with different descriptors. A total of 124 scientific papers were analyzed for different bibliometric indicators using VOSviewer software. Since 2001, the number of SCNT-related documents published concerning sheep reproduction increased and has fluctuated in ensuing years. The main authors, research groups, institutions, countries, documents and journals with the highest number of publications related to SCNT in sheep reproduction were identified, as well as the topics that address the research papers according to the terms: somatic cell, embryo, oocyte, gene expression, SCNT, and sheep.

The purpose of this article is to demonstrate the ability of bibliometric data from the Lens platform to identify relevant bibliometric/scientometric issues based on the construction of a network of key terms co-occurrence and their clustering. The advantages of using the Lens platform for bibliometric analysis are briefly demonstrated. Key terms were selected on the basis of n-grams and noun phrases. VOSviewer, Scimago Graphica, and Sifaka text mining application were used as analytical tools. Analysis of the Lens metadata on bibliometrics/scientometrics showed their predominant use in the political, social, and medical fields of research.

Relevance of the subject. Keyword selection is critical to finding relevant literature and requires justification for querying abstract databases and other sources to ensure accuracy and completeness. The topic of Energy Systems is of great importance due to the introduction of renewable energy sources, modern control methods, and complex energy systems during the energy transition. The aim of this study. The goal of this paper was to identify keywords that would be useful to subject matter experts when collecting literature on a particular topic, based on entries in the IEEE Terms field. Data. Bibliometric data were exported from the IEEE Xplore platform in the following order: for 2019-2023, 2000 records sorted by relevance, for 2024, 1680 records current as of April 11, 2024. Analytical methods applied and software used. VOSviewer, Scimago Graphica implementing the Clauset-Newman-Moore algorithm and agglomerative hierarchical clustering method implemented in Multidendrograms. Results. The main issues of the Energy Systems topic are presented in tabular and graphical formats. The fpgrowth utility offers flexible data preparation options, which makes it worthwhile to conduct a separate study to analyze the score of co-occurrence terms given by its algorithm.

This article conducts a bibliometric analysis focusing on the influence of globalization and technology in the academic context. Previous studies have focused on analyzing the relationship between the number of research citations and international collaboration, but no study has explored it in the scope of consumer behavior and retail. Leveraging the Scopus database, the research analyzes a significant corpus of 2,111 documents from 1971 to 2022. The findings reveal a distinct surge in academic output related to the topic of technology, reflecting a growing interest in understanding the interaction between technological factors and consumer behavior. The study also explores trends in international collaboration in publications as well as its impact on citation counts.

This paper delves into the critical issue of concrete cracks, a common consequence of environmental factors and external forces, and their potential impact on the structural integrity of buildings. Recognizing the urgency of addressing this issue, the concept of self-healing concrete has emerged, aiming to revolutionize the construction industry by autonomously repairing cracks and minimizing the need for labor-intensive and time-consuming manual interventions. The paper employs a bibliographic analysis methodology to comprehensively explore the most significant technologies associated with self-healing concrete, identifying key research countries/regions and prominent research institutions in this field. Through an examination of scholarly articles, the analysis seeks to uncover key themes, technologies, and contributors within the self-healing concrete domain. Insights into the geographical distribution of research efforts and the roles of influential research institutions are provided, shedding light on collaborative networks and knowledge-sharing dynamics that drive innovation in this evolving field.

The purpose of this study is to bring out a scientometric analysis of the advances of digital transformation in the global banking sector. For this, a background search of the term "Digital Transformation Banking " has been brought out from the Web of Science (Wos) Database, covering records published between 2002 and 2023. A set of 312 publications was identified, which mainly includes a set of 264 academic articles, 29 articles published without cataloging a specific volume of a journal, 9 articles under review, 5 editorial material documents, 4 conference articles, and 1 document is a book chapter. Nowadays the scientific production is low but showing growing development presenting 123 publications and 7,754 citations for the year 2022. Among the scientific production, 43 publications from the Republic of China (8.8%) and 35 publications from Ukraine (7.8%) stand out. ,2%). It is also worth mentioning that the most relevant authors on this topic are Ricardo Palomo, professor and dean of San Pablo University, and Robert J Kauffman, professor at Singapore Management University in terms of influence. Main institutions in terms of scientific production, mainly: the Massachusetts Institute of Technology (MIT) of the United States and the Russian Academy of Sciences of Russia.

Lagerstroemia is a genus of deciduous and evergreen shrubs and trees belonging to the family Lythraceae. Due to the attention paid to environmental and health issues, Lagerstroemia has become increasingly important in ecological environment protection, drug development, genetic resource protection, and application research. In order to gain an in-depth understanding of the current status and cutting-edge trends of Lagerstroemia research in the world, and objectively reflect the scientific capabilities and influence of relevant research countries, institutions, authors, and journals in this field. Using the visual analysis software VOSviewer and CiteSpace, a statistical analysis of the literature on Lagerstroemia in the Web of Science database was performed from 2002 to 2022. The results showed that the number of articles published on Lagerstromia in the world was increasing. Four of the five articles with the highest citation frequency were from the United States, and the number of articles published in Hortscience was the highest. In terms of subject distribution, the most frequently published subjects were plant sciences, pharmacology and pharmacy. These two disciplines focused on the cultivation of Lagerstroemia species and medicinal research on Lagerstroemia extracts. In terms of categories, science accounted for 41% of the top 10 subjects. Technical science accounted for a relatively large proportion. However, the amount of relevant literature in engineering science needs to be improved. India, the United States, and China were the main research forces in this field. In terms of international cooperation, China had close collaborations with many countries such as the United States, Japan, India, Russia, and the United Kingdom. Beijing Forestry University ranked first in terms of total number of publications, and the Chinese Academy of Sciences had the highest total citations and average citations. Meanwhile, most of the authors at the top of the list were Chinese scholars. Cluster analysis showed that the research of keywords such as “oxidative stress”, “protein” and “corosolic acid” were the research hotspots in recent years. Research on the chemical components and pharmacological effects of Lagerstroemia will be the focus of the research on Lagerstroemia.

The current organisation is facing intensifying competition in the global business world with loads of challenges and tries to sustain itself in the market through innovation and cost-cutting. The scientific community has a growing interest in management to make a niche in the global competitive era. They have started focusing on the expediency of green human resource management (GHRM) to steer the way to excel the organizations and their employees for sustainability. Green HRM tries to build an organization that encourages employees to adopt environmentally friendly workplace behaviours and minimize costs. The aim of this study is to identify and analyse the comprehensive research advances made in the field of green human resource management through bibliometric analysis. The Scopus database has been used to conduct the research. A total of 551 documents were inferred from Scopus, considering the department time period, 2004 to 2023. The outcomes of the study shed light on the eminence of green HRM research, identifying prolific authors and co-authorship patterns, commonly used keywords, country-wise and organization-wise analysis, research themes, theoretical foundations and simple statistics. This comprehensive exploration has provided valuable insights into the concept of green HRM, its objectives, and its potential benefits for businesses and society as a whole.

The article is devoted to a bibliometric analysis of scientific publications reflecting trends in scientific publications related to the energy transition of leading universities in Saudi Arabia. The universities were selected based on the presence of joint publications with the Saudi Arabian Oil Company, they are: King Fahd University of Petroleum and Minerals, King Abdullah University of Science and Technology, and King Saud University. The importance of studying the experience of Saudi Arabia for Russia in the context of the energy transition was highlighted. The analysis was based on Scopus platform data related to Subject Areas: Physical Sciences. Scientists from Saudi Arabian universities are increasingly publishing with co-authors from China, India, Egypt, Pakistan, and Malaysia, while maintaining high interaction with co-authors from the United States, South Korea, and the United Kingdom. Authors from the Russian Federation publish poorly with co-authors from Saudi Arabia. The trends in the topics of scientific publications were investigated, and their connection with the renewable energy topic was shown. The VOSviewer software was used to determine the main research areas using the cluster analysis method based on the co-occurrence of key terms. The analysis was done for both Author's keywords and Index keywords of the Scopus system. Graphical representation of the final choice of terms to describe research trends was proposed. TRANSLATE with x English ArabicHebrewPolish BulgarianHindiPortuguese CatalanHmong DawRomanian Chinese SimplifiedHungarianRussian Chinese TraditionalIndonesianSlovak CzechItalianSlovenian DanishJapaneseSpanish DutchKlingonSwedish EnglishKoreanThai EstonianLatvianTurkish FinnishLithuanianUkrainian FrenchMalayUrdu GermanMalteseVietnamese GreekNorwegianWelsh Haitian CreolePersian TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster Portal Back

Studies on human mobility have a long history with increasingly strong connections to multi-disciplines across social science, environmental science, information and technology, computer science, engineering, and health science. However, what is lacking in the current research is a summary of studies on human mobility to identify the evolutional pathway and future research directions. To address this gap, we conduct a systematic review of human mobility-related studies published from 1990 to 2020. Drawing on the selected publications retrieved from the Web of Science, we conduct a bibliometric analysis and network visualisation by CiteSpace and VOSviewer on publication years and numbers, authors and their countries and afflictions, citations, topics, abstracts, keyword, and journals. Our findings show that human mobility-related studies have become increasingly interdisciplinary and multi-dimensional, enhanced by the involvement of multi-source big data, the development of technologies, the innovation of modelling approaches, and the novel applications in various areas. We also summarise four future research directions proposed by top cited authors and mobility studies, in terms of data sources, modelling methods, applications, and technologies. We advocate in-depth research on human mobility to address real-world problems and contribute to social good as promising future orientations through integrating multi-source big data and advanced modelling methods facilitated by artificial intelligence, and machine and deep learning.

This paper explores the multifaceted impact of biofilms, bacterial communities enveloped in extracellular polymeric substance (EPS). Biofilms play a dual role, acting as environmental champions and health threats. They interact with heavy metals, either causing pollution or aiding environmental remediation. Beneficial biofilms generate electricity and repair concrete cracks, offering sustainable solutions. Conversely, they contribute to infections, posing health risks. The study emphasizes the need for in-depth research, utilizing bibliographic methods to analyze global biofilm research. By identifying keywords, core countries, and pivotal organizations, the paper informs future investigations, offering insights into biofilm research evolution and practical applications.

Biofilm serves as the residence for bacteria, wherein bacteria attach to surfaces and produce extracellular polymeric substances, including proteins, polysaccharides, and extracellular DNA. In recent years, biofilm reactors have gained increasing significance, playing a crucial role, for instance, in immobilizing heavy metals from waterways. This paper employs a bibliographic study to analyze the most important keywords and organizations in the field of biofilm reactors, identifying recent significant papers. Additionally, the paper discusses the opportunities for the future development of biofilm reactors. Through this study, a better understanding of key factors in biofilm reactor research is achieved, providing valuable guidance for future studies and applications in this field.

This text mining study delves into the multifaceted contributions of the energy sector to the Sus-tainable Development Goals (SDGs). By analyzing a wide range of academic literature, we un-cover key themes, trends, and challenges shaping the intersection of energy and sustainability. The findings reveal that the energy sector plays a pivotal role in achieving SDGs such as affordable and clean energy (SDG 7) and climate action (SDG 13). Critical issues encompass governance, policy frameworks, and technological innovations. This research underscores the need for inter-disciplinary collaboration and holistic approaches in addressing complex energy-related sus-tainability challenges. The insights derived here provide guidance to policymakers, researchers, and stakeholders seeking to harness the energy sector's potential for a more sustainable and eq-uitable future.

This study aims to determine the role of Industry 4.0 sensors in digital transformation. Using a systematic literature review with a bibliometric analysis, we examine a sample of 52 studies from the SCOPUS database to identify research activity on this topic until December 2022. We find that 2022 was the year with the highest number of peer-reviewed documents on the subject, with 18 publications. We also examine current themes and find that sensors can connect multiple systems and devices, thus enabling machine-to-machine communication and facilitating great precision during product designing, development, and production, thus enabling customization and improving quality. However, despite these benefits, the current sensor technologies face multiple challenges that undermine their maximum adoption.

Identification of topical research issues using bibliometric data is complicated by the fact that the citation of publications from recent years has not yet been formed. In this paper, it is proposed to use the average citation of the journal over two years rather than the article citation to estimate to estimate the weight of the keyword occurring in the sample under consideration. In order to identify the terms that characterize relevant research topics, it is proposed to represent the term co-occurrence network in coordinates of the average occurrence of the term per year and the average normalized citation of the term to visualize the graph. Furthermore, this methodology proposes the use of preprocessing of keywords using a lemmatization dictionary. 3,696 bibliometric records for 2022–2024 from the ScienceDirect platform on the topic of industry digitalization were used for the analysis. The VOSviewer and Scimago Graphica programs were used sequentially. The former was used to display the overall landscape of the study, while the latter was used to analyze in more detail the individual slices of bibliometric data obtained with VOSviewer. A ‘convex hull’ was used to facilitate the perception of cluster boundaries. After analysing the data and highlighting the terms, it is proposed to provide context by quoting strings from publications and defining of lesser-known terms. The industry digitalization is not only a technical and technological issue but also an economic one, as evidenced by terms such as ‘digital economy’ and ‘Industry 5.0’.

Remittances are essential to economies in mountainous regions that face massive labour migration due to limited income generation and employment opportunities. In 2021, the share of remittances to GDP in the top 10 mountainous economies in the world was over 20%. Nonetheless, most are characterized by relatively lower GDP per capita and high poverty levels. Drawing a comparison with other mountainous areas, Phuthadjthaba, an emerging mountainous and border city of South Africa with Lesotho, faces similar out-migration and inferior socio-economic parameters. A global systematic literature review on the impact of remittances on livelihoods specifically targeting mountainous areas is missing. We, therefore, interrogate the role remittances can play in Phuthadijthaba. To inform our intended research, we seek to draw lessons from evidence on how migration and remittances affect mountainous communities globally. Accordingly, we carry out a systematic literature review (SLR) based on an updated Preferred Reporting Item for Systematic Reviews and Meta-Analysis (PRISMA) 2020 statement supported by Bibliometric (co-word) Analysis (BA) in VOSViewer. We collected data from Scopus and Dimensions websites and drew 165 publications, of which only 88 were included after exclusion and inclusion assessments. PRISMA results show that Mountain Research and Development, King Russell, and Nepal is the most productive and cited journal, the most productive and cited author, and the most researched country, respectively. Bibliometric analysis on keyword co-occurrences reveals women, agriculture, labour migration, land management, forest, and poverty, to be the research hotspots. In light of these findings, we proffer important recommendations to future researchers and policymakers.

This article is devoted to a bibliometric analysis of IEEE Energy Internet and Energy Systems Integration Conference proceedings posted in IEEE Xplore in 2017-2021. The main objective of the study was to identify the actual research issues on the Energy Internet topic. Author Keywords, INSPEC Controlled Terms, and terms compiled from n-grams derived from conference papers title and abstract texts were used to describe the actual issues. The terms were clustered using VOSviewer, and the terms included in each cluster were treated as a description of the actual issues. Brief descriptions of several publications relevant to the issue in question were given for task detail. The actual issue, which in my opinion deserves further, more detailed analysis, is proposed.

The article is devoted to identifying promising research issues on the topic of Digital Industry based on the analysis of bibliometric data from Scopus platform for 2018–2022. The definition of promising issues derived from the titles, additionally abstracts, of highly cited works by authors with high publication activity. Authors' Scopus profiles were used to determine their affiliations, which are important for in-depth analysis of selected promising Digital Industry tasks. Metadata filtering to identify highly cited papers on particular issues was performed by keywords, Subject Areas, affiliations with countries and sponsoring organizations. Additionally, bibliometric metadata were clustered based on the co-occurrence of terms using VOSviewer. Within these clusters, articles of interest were identified for the formulation of promising research issues on the topic of Digital Industry, which will be subjected to in-depth analysis in separate papers.

Objectives. The aim of the study is to identify relevant research topics based on pooled bibliometric data of International Journal of Hydrogen Energy publications from 2022-2024, collected from The Lens and ScienceDirect platforms. Data source. Bibliometric records of International Journal of Hydrogen Energy articles published in 2022-2024 from The Lens and ScienceDirect platforms were used. Programs and utilities used. VOSviewer, Scimago Graphica, Inkscape, FP-growth utility. Results. The study showed the feasibility of merging bibliometric records from the open platforms ScienceDirect and The Lens, which complement each other. The 'Fields of Study' data of The Lens can be rationally interpreted as system keywords similar to Scopus Index Keywords. The possibility of using 'Fields of Study' data in a method similar to bibliographic coupling is shown. The practicality of using an Alluvial diagram to show the co-occurrence of the four terms was demonstrated. The study also emphasizes the advisability of joint use of VOSviewer and Scimago Graphica programs for complex visualization of bibliometric analysis results. The study identified two dominant publication topics in International Journal of Hydrogen Energy for 2022-2024, which can be described in terms of: 'Catalysis, Hydrogen, Physical_chemistry, Chemical_engineering, Nanotechnology, Electrochemistry, Organic_chemistry, Materials_science' and 'Electrical_engineering, Hydrogen_production, Renewable_energy, Environmental_science, Hydrogen_economy, Hydrogen, Engineering'.

This paper addresses the lack of analytical tools for visual data analysis in IEEE Xplore, an abstract database of publications on technical problems in electronics and electrical engineering. The openness of the platform and the good fillability of a large number of bibliometric record fields make it attractive for visual data analysis. The topic of machine learning and artificial intelligence applied to power systems, which are critical issues in the energy transition process, is chosen as an example for visual data analysis. The programs and utilities used for data analysis were VOSviewer, Scimago Graphica, FP-Growth algorithm, Inkscape, and MultiDendrograms. The use of IEEE Terms field data to identify publication topics in the exported data is analyzed in the most comprehensive way. This paper can be considered a reference for professionals interested in bibliometric analysis and visualization of IEEE Xplore data.

This study explores the pivotal biofilm life cycle, essential for comprehending intricate processes in biofilm formation and dispersal. With profound implications for medicine, environmental science, and industrial applications, the life cycle involves initial attachment, irreversible attachment, maturation, and dispersion. Employing bibliographic analysis, the paper unravels critical aspects, unveiling key keywords, prominent research countries/regions, and significant research organizations. This comprehensive approach provides insights into the current biofilm research landscape, identifying gaps for future exploration. Biofilm's influence extends to medical conditions, environmental ecosystems, and industrial challenges, accentuating the urgency of understanding its life cycle. The study also delves into global research distribution and influential organizations, guiding collaborative efforts. As a forward-looking initiative, it proposes future research opportunities, aiming to steer advancements and address challenges in biofilm science. Ultimately, this analysis contributes to the ongoing progress of biofilm research, fostering interdisciplinary collaboration and inspiring future initiatives.

Objectives. The aim of this study was to demonstrate the ability to visualize the results of the Scilit platform's bibliometric data analysis on the topic "AI & Machine Learning" to identify publications reflecting specific issues of the topic. Data source. Bibliometric records exported from the Scilit platform on the topic "AI & Machine Learning" for the years 2021–2023 were used. For each year, 6,000 records were downloaded in CSV and RIS format. Programs and utilities used. VOSviewer, Scimago Graphica, Inkscape, FP-growth utility, GSDMM algorithm. Used services: Elicit, QuillBot, Litmaps. Results. It has been shown that bibliometric data from the open access abstract database Scilit can serve as a quality alternative to subscription-only databases. Data exported from the Scilit platform require preprocessing to make them available in a format that can be processed by programs such as VOSviewer and Scimago Graphica. The use of GSDMM and FP-growth algorithms is effective for structuring bibliometric data for further visualization. The Scimago Graphica software provides wide possibilities for building compound diagrams, in particular, for representing the network of keywords in such important coordinates for bibliometric analysis as average year of publication and average normalized citation, as well as for building an alluvial diagram of co-occurrence of more than two keywords. The possibility of using such services as elicit.com, quillbot.com and app.litmaps.com to accelerate the selection of publications on the topic under study is shown.

Tandem mass spectrometry (MS/MS) for diagnosing inborn errors of metabolism (IEM) is recognized as an ethical, safe, simple, and reliable screening test. Presented bibliometric analysis aims to describe the network structure of the scientific community in the study area at the level of countries, institutions, authors, papers, keywords, and sources; scientific productivity, directions, and collaboration efforts in a considered period (1991–2023.) Using the PRISMA method, we conducted a systematic search for articles reporting using MS/MS to screen for inherited metabolic disorders and inborn errors of metabolism collected from the Web of Science Core Collection (WOSCC.) A total of 451 articles out of 546, by 2,682 authors, published in 190 journals, with 15,440 citations in 8,181 citing articles, with an average citation of 34.24 per article, and an H-index of 64 were retrieved from the WOSCC. The research status of MS/MS in IEM screening was identified. The most relevant current research directions and future areas of interest were revealed: "selective screening for IEM," "new treatments for IEM," "new disorders considered for MS/MS testing," "ethical issues associated with newborn screening," "new technologies that may be used for newborn screening," "use of a combination of MS/MS and gene sequencing," etc.

Recent years have experienced an increase in construction and demolition waste (C&DW), which is the most significant solid waste stream. C&DW is contributing to exceeding all planetary boundaries and presents a range of other issues. In order to better understand the existing research on C&DW, a global bibliographic analysis was undertaken through seven groups of keyword searches and the results visualised using VOCviewer. The results show that C&DW receives only a modest research attention compared to other areas of waste, and this is despite an exponential increase in C&DW research since 2016. The analyses also show that concrete is the most researched material in terms of C&DW, and that reuse, recycling, and circular economy are so far attracting only proportionally modest research attention. This signals a need for further acceleration of the C&DW research, and specifically for more research on reuse, recycling, and circular economy for materials other than concrete.

This study employs a bibliometric analysis of the emerging trends in the area of Money Laundering for Ter-rorism Financing to provide direction for future research in the area. The authors used VOSviewer and an-alysed 2577 published documents generated from the SCOPUS search using the PRISMA methodology. The findings reveal a growing research interest in this area, with a focus on understanding the complex inter-play between money laundering and terrorism financing. Emerging trends such as the use of cryptocurren-cies, trade-based money laundering, and the role of non-profit organizations in facilitating these activities are highlighted. The research contributes to the broader understanding of money laundering for terrorist financing by providing insights into the evolving research landscape and identifying areas for future re-search.

Medical brain image analysis is a necessary step in the Computers Assisted /Aided Diagnosis (CAD) systems. Advancements in both hardware and software in the past few years have led to improved segmentation and classification of various diseases. In the present work, we review the published literature on systems and algorithms that allow for classification, identification, and detection of White Matter Hyperintensities (WMHs) of brain MRI images specifically in cases of ischemic stroke and demyelinating diseases. For the selection criteria, we used the bibliometric networks. Out of a total of 140 documents we selected 38 articles that deal with the main objectives of this study. Based on the analysis and discussion of the revised documents, there is constant growth in the research and proposal of new models of deep learning to achieve the highest accuracy and reliability of the segmentation of ischemic and demyelinating lesions. Models with indicators (Dice Score, DSC: 0.99) were found, however with little practical application due to the uses of small datasets and lack of reproducibility. Therefore, the main conclusion is to establish multidisciplinary research groups to overcome the gap between CAD developments and their complete utilization in the clinical environment.