Global Scientific Trends in Research Related to Diabetic Sarcopenia from 1993 to 2023: A Bibliometric Analysis

Objectives: In this study, bibliometric approach was used to explore the literature in the field of research related to Diabetic Myasthenia Gravis in order to identify the current research progress in Diabetic Myasthenia Gravis related research and to help the researchers to predict the future hotspots in the field of research and to provide reference for the research. Methods: Literature related to diabetic sarcopenia published from 1993 to 2023 since the inception of the repository was extracted from the Web of Science Core Collection (WoSCC) and bibliometric analyses were performed. We have analysed the published literature of the last approximately almost 30 years, as well as publication and citation analyses from different countries, institutions, journals and authors. For keywords, we performed co-occurrence, clustering, timeline view and citation burst analysis. Results: On the basis of 1564 publications, we found a continuous increase in the number of publications and citations, especially in the last six years. The United States is the most representative country, and Seoul National University (SNU) is the most representative institution. The most popular journal in the field is Diabetes Care;Fukui, Michiaki is the most prolific author, leading many studies related to diabetic sarcopenia. The most frequently cited reference was a revised European consensus on the definition and diagnosis of sarcopenia;the most cited keywords were related to physiological factors of diabetes, sarcopenia and related conditions, such as “insulin resistance”, “skeletal muscle”, “body composition”, “risk” and “prevalence”. Conclusion: With more and more studies on the relationship between diabetic sarcopenia, this study presents the current status and trend of research related to diabetic sarcopenia over the past nearly 30 years through the visualization software CiteSpace. It can help researchers identify potential collaborators and partner institutions, hotspots and research frontiers in the field of diabetic sarcopenia. However, our work is only based on the English language literature in the WoSCC database, and for future studies, we recommend that researchers explore the literature from multiple databases to enhance the scope of their research.

Hotspots and research trends of Piwi-interacting RNAs from 2006 to 2023 based on bibliometric analysis

Background:Piwi-interacting RNAs(piRNAs)are a type of non-coding RNAs,initially identified in germ cells in 2006,known to bind to the Piwi family proteins.Accumulating studies indicate their importance in genome stability,epigenetics regulation,germ cell differentiation,and tumor development.Despite growing interest in piRNA research,there is a lack of comprehensive bibliometric studies on the subject.This study aims to analyze piRNA research trends from 2006 to 2023.Methods:The literature regarding piRNA was sourced from the Web of Science on April 25,2023.VOSviewer,CiteSpace and a bibliometric online website(https://bibliometric.com/app)were employed to perform bibliometric analysis.Network maps were constructed to evaluate the collaborations among countries,institutions,authors,journals,references,keywords,and research hot pots.Results:In this study,2549 literature were published across 464 countries and 6921 institutions,comprising 2010 articles and 539 reviews.The United States led in publication output(n=1011,39.66%),followed by China(635,24.91%).The University of Tokyo had the most publications among all institutions(n=100,3.92%),followed by the Chinese Academy of Sciences(n=86,3.37%).Among 631 published journals,Nucleic Acids Research was the most published journal(n=83,3.26%).Siomi Mikiko C published the most articles(n=58),with Aravin Alexei A as the most co-cited author.Analysis of term co-occurrence unveiled three highly interconnected clusters,including“piRNA biogenesis and function”,“cancer and regulation”,as well as“protein and species”.The research focus has transferred from male reproductive development to tumor progression.Conclusion:This bibliometric analysis offered a thorough overview of the current state of piRNA research,deepening understanding of the progress in this field over the last 17 years and providing a valuable reference for scholars engaged in piRNA studies.

Research trends on artificial intelligence and endoscopy in digestive diseases: A bibliometric analysis from 1990 to 2022

BACKGROUND Recently,artificial intelligence(AI)has been widely used in gastrointestinal endoscopy examinations.AIM To comprehensively evaluate the application of AI-assisted endoscopy in detecting different digestive diseases using bibliometric analysis.METHODS Relevant publications from the Web of Science published from 1990 to 2022 were extracted using a combination of the search terms“AI”and“endoscopy”.The following information was recorded from the included publications:Title,author,institution,country,endoscopy type,disease type,performance of AI,publication,citation,journal and H-index.RESULTS A total of 446 studies were included.The number of articles reached its peak in 2021,and the annual citation numbers increased after 2006.China,the United States and Japan were dominant countries in this field,accounting for 28.7%,16.8%,and 15.7%of publications,respectively.The Tada Tomohiro Institute of Gastroenterology and Proctology was the most influential institution.“Cancer”and“polyps”were the hotspots in this field.Colorectal polyps were the most concerning and researched disease,followed by gastric cancer and gastrointestinal bleeding.Conventional endoscopy was the most common type of examination.The accuracy of AI in detecting Barrett’s esophagus,colorectal polyps and gastric cancer from 2018 to 2022 is 87.6%,93.7%and 88.3%,respectively.The detection rates of adenoma and gastrointestinal bleeding from 2018 to 2022 are 31.3%and 96.2%,respectively.CONCLUSION AI could improve the detection rate of digestive tract diseases and a convolutional neural network-based diagnosis program for endoscopic images shows promising results.

Automated writing evaluation(1995-2022):Research trends and implications

Automated writing evaluation is the use of computer programs to evaluate essays written in an educational setting.This study aims to evaluate the state of the art and the trends of automated writing evaluation research.A total of 206 automated writing evaluation-related publications published in 88 journals between 1995 and 2022 were used as the data in our study.Bibliometric methods were employed to identify the publication trends,venues for publication,productive authors,highly cited articles,seminal works,and the most frequently explored topics across the past decades.The findings show that automated writing evaluation has become a fast-growing interdisciplinary area of interest.In addition,this line of research has witnessed a growing interest in topics pertaining to the latest technology,the perception of children,the teachers’feedback,and complex tasks.Implications of our study for future research are also discussed.

Information Extraction Based on Multi-turn Question Answering for Analyzing Korean Research Trends

Analyzing Research and Development(R&D)trends is important because it can influence future decisions regarding R&D direction.In typical trend analysis,topic or technology taxonomies are employed to compute the popularities of the topics or codes over time.Although it is simple and effective,the taxonomies are difficult to manage because new technologies are introduced rapidly.Therefore,recent studies exploit deep learning to extract pre-defined targets such as problems and solutions.Based on the recent advances in question answering(QA)using deep learning,we adopt a multi-turn QA model to extract problems and solutions from Korean R&D reports.With the previous research,we use the reports directly and analyze the difficulties in handling them using QA style on Information Extraction(IE)for sentence-level benchmark dataset.After investigating the characteristics of Korean R&D,we propose a model to deal with multiple and repeated appearances of targets in the reports.Accordingly,we propose a model that includes an algorithm with two novel modules and a prompt.A newly proposed methodology focuses on reformulating a question without a static template or pre-defined knowledge.We show the effectiveness of the proposed model using a Korean R&D report dataset that we constructed and presented an in-depth analysis of the benefits of the multi-turn QA model.

Research trends of machine learning in traditional medicine:a big-data based tenyear bibliometric analysis

Background:With the rapid development of the world’s technology,the connection and integration between traditional medicine and modern machine learning technology are increasingly close.In this study,we aimed to analyze publications on machine learning in traditional medicine by using bibliometric methods and explore global trends in the field.Methods:Relevant research on machine learning in traditional medicine extracted from the Web of Science Core Collection database.Bibliometric analysis and visualization were performed using the Bibliometrix package in R software.Global trends,source journals,authorship,and thematic keywords analysis were performed in this study.Results:From 2012 to 2022,a total of 282 publications on machine learning in traditional medicine were identified and analyzed.The average annual growth rate of the publications was 13.35%.China had the largest contribution in this field(53.9%),followed by the United States(32.6%).IEEE Access had the largest number of published articles,with a total of 15 articles.Calvin Yu-Chian Chen,Xiao-juan Hu and Jue Wang were the main researchers in this field.Shanghai University of Traditional Chinese Medicine and University of California,San Francisco were the main research institutions.Conclusion:This study provides information on research trends in machine learning in traditional medicine to better understand research hotspots and future developments in this field.According to current global trends,the number of publications in this field will gradually increase.China currently dominated the field.Applied research of machine learning techniques may be the next hot topic in this field and deserves further attention.

Trends in Domestic Soundscape Research: Knowledge Graph Analysis Based on Cite Space

The development of soundscape has a history of over 20 years to this day. Based on the CNKI database, a contact graph of authors in the field of soundscape is drawn using Cite Space software, and the number of core authors in the field of soundscape is determined to be 30. Based on the number of papers and the evolution of keywords over the years, the development of soundscape research is divided into three stages: exploration stage(1995-2006), pre development stage(2007-2015), and post development stage(2016-present). The research direction is divided into three categories: soundscape perception, soundscape evaluation, and soundscape design. According to various graph analysis, with the continuous development of science and technology, soundscape research fields and methods are gradually diversified, and fields such as soundscape evaluation, soundscape, landscape architecture, soundscape perception and sound stroll have gradually become hot spots in soundscape research.

Trends in research on osteoarthritis of the knee in conventional medicine:a bibliometric analysis based on big data from 1990-2022

Background:Osteoarthritis of the knee(KOA)is a chronic degenerative disease.KOA is a growing concern due to its high incidence and the pain and other burdens it places on patients.Traditional medicine is a health care model with a long history that includes nature-based treatments,psycho-psychological types of treatments,and more.Traditional medicine is also more effective in diagnosing and treating KOA,and it has never stopped researching KOA.There are no bibliometric studies analyzing articles on the traditional medical diagnosis and management of KOA.This study aimed to comprehensively analyze and analyze the general trends in the study of KOA in traditional medicine from a bibliometric perspective.Methods:All articles reporting on KOA and traditional medicine from 1 January 1990 to 01 November 2022 were obtained from the Web of Science Core.Some software such as CiteSpace,VOS Viewer and Scimago Graphica were used to analyse the publications,which included authors,citations,journals,references,countries where studies were published,institutions and research keywords.The final visualisations were produced using this data.Results:A total of 769 articles were searched.Peijian Tong was identified as the most contributing and published author in the field,and medicine was identified as the most reputable journal in the field of traditional medicine and osteoarthritis of the knee.China is a global leader in the field and a centre of collaboration in the field,with a major concentration of traditional medicine in Asia,which is consistent with the evidence that traditional medicine originated in Asia.According to the data,“osteoarthritis”,“knee osteoarthritis”,“pain”,and“knee”and“hip”were identified as hot keywords for research in this area.Conclusions:The results of this bibliometric study provide a snapshot of the current state of clinical research in the treatment of KOA in traditional medicine and are well placed to envisage future hotspots and possible trends,and may help to provide researchers with more than enough information with a view to guiding the cutting edge of research in this field and the infinite possibilities for the future.

An Analysis of the Research Trends in Blended Learning Methods in Teaching College English Reading Courses

Curtis J.Bonk defined blended learning as a combination of face-to-face and computer-assisted online learning instruction since it was gradually formed after the emergence of the Internet[1,2].Breen pointed out that blended learning is a learning method that combines online and offline learning activities and resources[3].The blended learning approach is popular in school and e-learning.Moreover,it is one of the important trends in promoting higher education reform in the coming years.Therefore,it has attracted the attention of international researchers[4].In this paper,42 articles in Scopus(established by international institutions)and 30 articles in CNKI(found by Chinese mainland institutions)on the query of“college English reading blended learning”in the field of education were analyzed.Furthermore,CiteSpace software was used to analyze the research hotspots and trends with the keyword clusters and citations that occurred in the last two decades(1999 to 2022)to foresee future research prospects.

Visual Analysis of Domestic and Foreign Building Brick Skin Research Based on Citespace

With the progress of the times and the leap of science and technology,the application of brick materials and the research on the brick skin in modern architectural design have shown a dual-track development trend of returning to tradition and innovation.Based on the core collection database resources of Web of Science and the CiteSpace visual analysis tool,this paper constructed and analyzed the spatio-temporal map of keyword co-occurrence network,cluster structure,mutation phenomenon,time course and regional distribution map of building brick skin research.The study revealed that in recent years,the research on brick materials has spanned the study of single material properties and extensively involved in the broad world of construction,especially in the integration of green energy-saving technology,the innovation of fine construction technology of brick skin,and the frontier exploration of digital technology in brick masonry,which has shown particularly significant research vitality and development potential.

Understanding Research Trends in Android Malware Research Using Information Modelling Techniques

Android has been dominating the smartphone market for more than a decade and has managed to capture 87.8%of the market share.Such popularity of Android has drawn the attention of cybercriminals and malware developers.The malicious applications can steal sensitive information like contacts,read personal messages,record calls,send messages to premium-rate numbers,cause financial loss,gain access to the gallery and can access the user’s geographic location.Numerous surveys on Android security have primarily focused on types of malware attack,their propagation,and techniques to mitigate them.To the best of our knowledge,Android malware literature has never been explored using information modelling techniques.Further,promulgation of contemporary research trends in Android malware research has never been done from semantic point of view.This paper intends to identify intellectual core from Android malware literature using Latent Semantic Analysis(LSA).An extensive corpus of 843 articles on Android malware and security,published during 2009–2019,were processed using LSA.Subsequently,the truncated singular Value Decomposition(SVD)technique was used for dimensionality reduction.Later,machine learning methods were deployed to effectively segregate prominent topic solutions with minimal bias.Apropos to observed term and document loading matrix values,this five core research areas and twenty research trends were identified.Further,potential future research directions have been detailed to offer a quick reference for information scientists.The study concludes to the fact that Android security is crucial for pervasive Android devices.Static analysis is the most widely investigated core area within Android security research and is expected to remain in trend in near future.Research trends indicate the need for a faster yet effective model to detect Android applications causing obfuscation,financial attacks and stealing user information.

The Status and Trend of Research on Standards for Eoological Textile in China

The products of ecological textile have represented nowadays the new trend of global consumption and production of textile while become an important means for some countries to utilize “green barrier” as a limitation of import of textile products. Following the entrance of China into the WTO,the position of “green barrier ” becomes significantly important in the trade of textile products. As China is a big country of textile production,speeding up the research on standards for products of ecological textile,countering the latest situation appearing in international trade of textile,to take as quickly as possible responsive measures is a very urgent problem in breaking through the foreign technical trade barrier and promoting the development of foreign trade.

Global Research Trends Related to CO_2 Emissions and Their Enlightenment to China

Given the growing awareness of the likely catastrophic impacts of climate change and close association of climate change with global emissions of greenhouse gases (of which carbon dioxide is more prominent) , considerable research efforts have been devoted to the analysis of carbon dioxide (CO2) emissions and its relationship to sustainable development. Now GHG reduction programs have been coming into effect in many developed countries that have more responsibility for historical CO2 emissions, and the studies have become mature. First, the GHG emissions accounting system is more all-inclusive and the methods are more rational with the effort of IPCC from 1995 and all other researchers related. Second, the responsibility allocation is more rational and fair. Along with the clarity of "carbon transfer" and "carbon leakage", the perspective and methodology for allocating regional CO2 emissions responsibility is turning from production base to consumption base. Third, the decomposition method has become more mature and more complex. For example, the decomposition formulas are including KAYA expression and input-output expression and the decomposition techniques are developed from index analysis to simple average divisia and then adaptive-weighting divisia. Fourth, projection models have become more integrated and long-term. The top-down model and bottom-up model are both inter-embedded and synergetic. Trends above give some advice for the research on CO2 in China, such as emissions factors database construction, deeper-going research on emissions responsibility and structure analysis, promotion of modeling technology and technology-environment database.

Current Situations and Future Development Trend of Farmland Pre-warning Researches in China

This paper summarized theory discussion,main research methods,contents,empirical and engineering researches of farmland prewarning in China.It stated that future researches of farmland pre-warning in China will focus on deepening application of farmland security prewarning models,revealing mechanism of changes in different farmland resources,establishing pre-warning models suitable for research areas,accurate evaluation and prediction of farmland security,and exploring establishing and improving farmland security monitoring system and operating mechanism of all levels.

Waste Research Trends in Japan in the Past Ten Years: Review of What We Had Done before the Catastrophic Events of March 2011

This study analyzes waste research of the past decade in order to determine Japanese trends as well as to learn the problems of Japanese research. The results show that waste research has focused mainly on treatment, management, and recycling, and that research on prior processes such as reduction, collection, and transportation has been very limited. It was also found that research placed stress mostly on materials rather than people and the trend was very similar to that of a ministry oriented research fund. It seems that Japanese waste research has been neither balanced nor strategic. We therefore conclude that a government direction on waste studies might be not appropriate. Japan and Japanese researchers must change their ways of thinking in order not to repeat these mistakes.

A Review and Prospect of the Research on English Teacher Feedback in China from 2011 to 2021

This study uses the literature research method to search the domestic literature on English teacher feedback from 2011 to 2021,and reviews the research on the three main functions of English teacher feedback,namely language function,cognitive function,and emotional function,so as to explore the current situation of domestic research on teacher feedback.The results show that:First,in terms of research methods,the study of teacher feedback mainly adopts the combination of qualitative and quantitative research methods,and reveals the characteristics of the use of teacher feedback in Chinese English classrooms.Secondly,in terms of research objects,the research on teacher feedback in China is biased towards the research in universities and high school classrooms.Finally,in terms of research perspectives,the study of teacher feedback is mainly conducted from the perspective of classification,characteristics and functions of feedback.This paper also finds existing problems in the current research and prospects for future trends in development for future research.

水肥一体研究的热点问题和可视化分析

水肥一体化近年来在农业施肥领域得到快速发展,是目前提高农作物肥效的重要途径。采用文献计量学方法,对水肥一体相关文献进行分析。利用中国CNKI数据库,选取2010-2023年的文献为研究对象,通过对中国知网核心数据库中216篇与“水肥一体”相关中文文献的文献数量、年代分布、期刊分布、发文机构分布、著者信息、研究内容及热点等进行客观、系统地分析,得出结果:自2010-2023年来,国内共发表水肥一体相关文章216篇,数据库内中国最早关于水肥一体方面的文献发表于2010年,发表的文章数量随着年份的增长呈波动式上升;就发表的论文、作者、发文机构等方面而言,有关“水肥一体”的论文主要发表在农业农林学等相关专业刊物上;水肥一体的发文机构是以中国的北京市、山东省、宁夏回族自治区的高等院校和科研院所等机构为重点,其具有雄厚的农业研究实力和较强的学术影响力;研究水肥一体这一领域的核心作者目前尚未形成稳定的群体且数量较少;从研究内容上看,目前中国的水肥一体技术研究重点集中在产量、物联网、控制系统以及滴灌等领域。结果可以客观地反映2010-2023年国内水肥一体相关课题的研究动态,为该领域的研究人员提供数据参考。

中国儿童福利研究的演进、热点与展望:基于CiteSpace的可视化分析

儿童福利是社会保障体系的重要组成部分,发展儿童福利能为社会可持续发展提供宝贵资源与不竭动力。借助CiteSpace软件,对1992—2023年北大中文核心与CSSCI期刊检索出的556篇儿童福利领域相关文献进行研究进展和热点梳理。研究表明,当前中国儿童福利领域已出现一些具有较高影响力的学者和机构,相关研究数量呈逐年递增的态势。中国儿童福利的研究大致经历了初步探索期、深化发展期和稳步提升期三个发展阶段,该领域的研究热点主要集中于儿童福利的内涵界定、儿童福利的责任分野、儿童福利政策理念、儿童福利立法和儿童托育服务五个主题,研究的视角和内容逐渐趋向多样化、深层次。未来研究者应立足于既有成果,从不同角度继续深化儿童福利研究,以设计出合乎中国国情的儿童福利政策。

基于科学知识图谱的劈裂注浆研究热点与发展态势分析

针对传统建筑科学分析方法对工程领域研究存在的局限性,引入科学知识图谱及大数据计量等人工智能方法,借助可视化软件Citespace,检索Web of Science(WOS)核心合集数据库,得到2007~2022年主题为劈裂注浆的文献709篇,对发文总量、学科归属、期刊分布、核心作者、区域合作、关键词和被引文献等方面做科学知识图谱分析。通过区域合作关系图谱的寻径,理清现阶段国际合作的格局,指出中国未来国际合作的主要任务。依据成果数量和突现时间,评析贡献较大的代表性作者。提取318个研究关键词,以发文频次和中心性为导向,筛选精炼了现阶段研究热点。从10个聚类的特性分组出发,展示了理论研究、应用实践和数值模拟的发展脉络,明确了研究的前沿方向。排列10条聚类发展时间线,精炼了注浆效率和封堵效率两条热门主线,同时提示了较难取得研究成果的线路。通过聚焦关键词的时区分布态势,总结热点演进的两个规律,并预测今后两年新热点与2017年研究成果之间的潜在关联。根据文献共被引关系发生的时间,对比4组年度切片的变化,评价了学科知识基础的发展脉络和未来走向。结果表明:科学知识图谱作为人工智能分析方法,能总结分析劈裂注浆近年来的研究热点,并可以预测劈裂注浆在未来阶段的学术研究发展态势。