In this article , the present state of cotton production in Xinjiang is introduced. The strong points and problems in cotton production are discussed in detail. In addition, cotton research advances are reviewed in a ...In this article , the present state of cotton production in Xinjiang is introduced. The strong points and problems in cotton production are discussed in detail. In addition, cotton research advances are reviewed in a comprehensive manner. In consideration of all this, the authors expound some monographic topics and disciplinary projects regarding Xinjiang cotton research which are to be implemented in the years to come.展开更多
In order to support scientific evaluation and decision-making,this paper characterizes and identifies core researchers and their research topics by modeling the portrait of core researchers in technical fields.In this...In order to support scientific evaluation and decision-making,this paper characterizes and identifies core researchers and their research topics by modeling the portrait of core researchers in technical fields.In this paper,we constructed a portrait model of core researchers,explained the information attributes and their label data in each dimension of the portrait.Selected six identification indicators that can be measured,used the CRITIC method and gray correlation method to determine the weight coefficient and comprehensive score of the index,and designed quantitative identification methods for core researchers using Price's calculation formula and golden section coefficient.Took the field of artificial intelligence as an example for empirical analysis and result verification,selected representative core researchers to track the changes of research topics at the two levels of their teams and individuals,and characterize them based on the portrait model.展开更多
Here we report on a study that combined a scoping review with co-occurrence analysis to assess the current state of publications and research topics in the area of international research collaboration measurement(IRCM...Here we report on a study that combined a scoping review with co-occurrence analysis to assess the current state of publications and research topics in the area of international research collaboration measurement(IRCM).Our study found that IRCM studies have been published in source titles of diverse subject areas and that there are two core research topics that have been commonly discussed across different subject areas in the IRCM domain-scientific productivity measurement and scientific impact measurement.The appearance of papers about IRCM in venues beyond those concerned only with bibliometric measures indicates the broad importance of IRCM for diverse research subjects,and that studies of IRC within particular fields should draw on diverse venues to provide a holistic and interdisciplinary picture of IRCM.展开更多
Purpose: Based on the weak tie theory, this paper proposes a series of connection indicators Acof weak tie subnets and weak tie nodes to detect research topics, recognize their connections, and understand their evolut...Purpose: Based on the weak tie theory, this paper proposes a series of connection indicators Acof weak tie subnets and weak tie nodes to detect research topics, recognize their connections, and understand their evolution.Design/methodology/approach: First, keywords are extracted from article titles and preprocessed. Second, high-frequency keywords are selected to generate weak tie co-occurrence networks. By removing the internal lines of clustered sub-topic networks, we focus on the analysis of weak tie subnets’ composition and functions and the weak tie nodes’ roles.Findings: The research topics’ clusters and themes changed yearly; the subnets clustered with technique-related and methodology-related topics have been the core, important subnets for years; while close subnets are highly independent, research topics are generally concentrated and most topics are application-related; the roles and functions of nodes and weak ties are diversified.Research limitations: The parameter values are somewhat inconsistent; the weak tie subnets and nodes are classified based on empirical observations, and the conclusions are not verified or compared to other methods.Practical implications: The research is valuable for detecting important research topics as well as their roles, interrelations, and evolution trends. Originality/value: To contribute to the strength of weak tie theory, the research translates weak and strong ties concepts to co-occurrence strength, and analyzes weak ties’ functions. Also, the research proposes a quantitative method to classify and measure the topics’ clusters and nodes.展开更多
The major research program,"Catalysis science for carbon-based energy conversion",from the national science foundation of China(NSFC)answers to the main strategic needs of China for the efficien use of carbo...The major research program,"Catalysis science for carbon-based energy conversion",from the national science foundation of China(NSFC)answers to the main strategic needs of China for the efficien use of carbon-based energy and targets to address the key scientifi issues involved in the catalytic interfaces.The research program aims to improve the catalytic activation of C–H and C–O bonds and the C–C coupling process,展开更多
How to select a research topic that is appropriate for a clinician and that can lead to a peer-reviewed publication?In this essay,I will provide 5 tips:keep it interesting,keep it relevant,keep it inclusive,keep it si...How to select a research topic that is appropriate for a clinician and that can lead to a peer-reviewed publication?In this essay,I will provide 5 tips:keep it interesting,keep it relevant,keep it inclusive,keep it simple,and keep it trying.Keep it展开更多
With the progress and development of computer technology,applying machine learning methods to cancer research has become an important research field.To analyze the most recent research status and trends,main research ...With the progress and development of computer technology,applying machine learning methods to cancer research has become an important research field.To analyze the most recent research status and trends,main research topics,topic evolutions,research collaborations,and potential directions of this research field,this study conducts a bibliometric analysis on 6206 research articles worldwide collected from PubMed between 2011 and 2021 concerning cancer research using machine learning methods.Python is used as a tool for bibliometric analysis,Gephi is used for social network analysis,and the Latent Dirichlet Allocation model is used for topic modeling.The trend analysis of articles not only reflects the innovative research at the intersection of machine learning and cancer but also demonstrates its vigorous development and increasing impacts.In terms of journals,Nature Communications is the most influential journal and Scientific Reports is the most prolific one.The United States and Harvard University have contributed the most to cancer research using machine learning methods.As for the research topic,“Support Vector Machine,”“classification,”and“deep learning”have been the core focuses of the research field.Findings are helpful for scholars and related practitioners to better understand the development status and trends of cancer research using machine learning methods,as well as to have a deeper understanding of research hotspots.展开更多
In research and policies,the identifcation of trends as well as emerging topics and topics in decline is an important source of information for both academic and innovation management.Since at present policy analysis ...In research and policies,the identifcation of trends as well as emerging topics and topics in decline is an important source of information for both academic and innovation management.Since at present policy analysis mostly employs qualitative research methods,the following article presents and assesses diferent approaches–trend analysis based on questionnaires,quantitative bibliometric surveys,the use of computer-linguistic approaches and machine learning and qualitative investigations.Against this backdrop,this article examines digital applications in cultural heritage and,in particular,built heritage via various investigative frameworks to identify topics of relevance and trendlines,mainly for European Union(EU)-based research and policies.Furthermore,this article exemplifes and assesses the specifc opportunities and limitations of the diferent methodical approaches against the backdrop of data-driven vs.data-guided analytical frameworks.As its major fndings,our study shows that both research and policies related to digital applications for cultural heritage are mainly driven by the availability of new technologies.Since policies focus on meta-topics such as digitisation,openness or automation,the research descriptors are more granular.In general,data-driven approaches are promising for identifying topics and trendlines and even predicting the development of near future trends.Conversely,qualitative approaches are able to answer“why”questions with regard to whether topics are emerging due to disruptive innovations or due to new terminologies or whether topics are becoming obsolete because they are common knowledge,as is the case for the term“internet”.展开更多
Polymer science is a multiple discipline that studies synthesis,structure,function and application of macromolecules.It encompasses subdisciplines of polymer chemistry,physics and engineering.Despite the fact that pol...Polymer science is a multiple discipline that studies synthesis,structure,function and application of macromolecules.It encompasses subdisciplines of polymer chemistry,physics and engineering.Despite the fact that polymeric展开更多
基金The project is supported by the Research Project "95-001-04-04-02".
文摘In this article , the present state of cotton production in Xinjiang is introduced. The strong points and problems in cotton production are discussed in detail. In addition, cotton research advances are reviewed in a comprehensive manner. In consideration of all this, the authors expound some monographic topics and disciplinary projects regarding Xinjiang cotton research which are to be implemented in the years to come.
基金support from the National Social Science Fund of China(16ZDA224)。
文摘In order to support scientific evaluation and decision-making,this paper characterizes and identifies core researchers and their research topics by modeling the portrait of core researchers in technical fields.In this paper,we constructed a portrait model of core researchers,explained the information attributes and their label data in each dimension of the portrait.Selected six identification indicators that can be measured,used the CRITIC method and gray correlation method to determine the weight coefficient and comprehensive score of the index,and designed quantitative identification methods for core researchers using Price's calculation formula and golden section coefficient.Took the field of artificial intelligence as an example for empirical analysis and result verification,selected representative core researchers to track the changes of research topics at the two levels of their teams and individuals,and characterize them based on the portrait model.
文摘Here we report on a study that combined a scoping review with co-occurrence analysis to assess the current state of publications and research topics in the area of international research collaboration measurement(IRCM).Our study found that IRCM studies have been published in source titles of diverse subject areas and that there are two core research topics that have been commonly discussed across different subject areas in the IRCM domain-scientific productivity measurement and scientific impact measurement.The appearance of papers about IRCM in venues beyond those concerned only with bibliometric measures indicates the broad importance of IRCM for diverse research subjects,and that studies of IRC within particular fields should draw on diverse venues to provide a holistic and interdisciplinary picture of IRCM.
基金funded by the National Social Science Youth Project “Study on the Interdisciplinary Subject Identification and Prediction” (Grant No.:14CTQ033)
文摘Purpose: Based on the weak tie theory, this paper proposes a series of connection indicators Acof weak tie subnets and weak tie nodes to detect research topics, recognize their connections, and understand their evolution.Design/methodology/approach: First, keywords are extracted from article titles and preprocessed. Second, high-frequency keywords are selected to generate weak tie co-occurrence networks. By removing the internal lines of clustered sub-topic networks, we focus on the analysis of weak tie subnets’ composition and functions and the weak tie nodes’ roles.Findings: The research topics’ clusters and themes changed yearly; the subnets clustered with technique-related and methodology-related topics have been the core, important subnets for years; while close subnets are highly independent, research topics are generally concentrated and most topics are application-related; the roles and functions of nodes and weak ties are diversified.Research limitations: The parameter values are somewhat inconsistent; the weak tie subnets and nodes are classified based on empirical observations, and the conclusions are not verified or compared to other methods.Practical implications: The research is valuable for detecting important research topics as well as their roles, interrelations, and evolution trends. Originality/value: To contribute to the strength of weak tie theory, the research translates weak and strong ties concepts to co-occurrence strength, and analyzes weak ties’ functions. Also, the research proposes a quantitative method to classify and measure the topics’ clusters and nodes.
文摘The major research program,"Catalysis science for carbon-based energy conversion",from the national science foundation of China(NSFC)answers to the main strategic needs of China for the efficien use of carbon-based energy and targets to address the key scientifi issues involved in the catalytic interfaces.The research program aims to improve the catalytic activation of C–H and C–O bonds and the C–C coupling process,
文摘How to select a research topic that is appropriate for a clinician and that can lead to a peer-reviewed publication?In this essay,I will provide 5 tips:keep it interesting,keep it relevant,keep it inclusive,keep it simple,and keep it trying.Keep it
基金Natural Science Foundation of Guangdong Province,Grant/Award Number:2021A1515011339。
文摘With the progress and development of computer technology,applying machine learning methods to cancer research has become an important research field.To analyze the most recent research status and trends,main research topics,topic evolutions,research collaborations,and potential directions of this research field,this study conducts a bibliometric analysis on 6206 research articles worldwide collected from PubMed between 2011 and 2021 concerning cancer research using machine learning methods.Python is used as a tool for bibliometric analysis,Gephi is used for social network analysis,and the Latent Dirichlet Allocation model is used for topic modeling.The trend analysis of articles not only reflects the innovative research at the intersection of machine learning and cancer but also demonstrates its vigorous development and increasing impacts.In terms of journals,Nature Communications is the most influential journal and Scientific Reports is the most prolific one.The United States and Harvard University have contributed the most to cancer research using machine learning methods.As for the research topic,“Support Vector Machine,”“classification,”and“deep learning”have been the core focuses of the research field.Findings are helpful for scholars and related practitioners to better understand the development status and trends of cancer research using machine learning methods,as well as to have a deeper understanding of research hotspots.
基金The project has received funding by the Thüringische Aufbaubank(Grant No 220FGI0045).
文摘In research and policies,the identifcation of trends as well as emerging topics and topics in decline is an important source of information for both academic and innovation management.Since at present policy analysis mostly employs qualitative research methods,the following article presents and assesses diferent approaches–trend analysis based on questionnaires,quantitative bibliometric surveys,the use of computer-linguistic approaches and machine learning and qualitative investigations.Against this backdrop,this article examines digital applications in cultural heritage and,in particular,built heritage via various investigative frameworks to identify topics of relevance and trendlines,mainly for European Union(EU)-based research and policies.Furthermore,this article exemplifes and assesses the specifc opportunities and limitations of the diferent methodical approaches against the backdrop of data-driven vs.data-guided analytical frameworks.As its major fndings,our study shows that both research and policies related to digital applications for cultural heritage are mainly driven by the availability of new technologies.Since policies focus on meta-topics such as digitisation,openness or automation,the research descriptors are more granular.In general,data-driven approaches are promising for identifying topics and trendlines and even predicting the development of near future trends.Conversely,qualitative approaches are able to answer“why”questions with regard to whether topics are emerging due to disruptive innovations or due to new terminologies or whether topics are becoming obsolete because they are common knowledge,as is the case for the term“internet”.
文摘Polymer science is a multiple discipline that studies synthesis,structure,function and application of macromolecules.It encompasses subdisciplines of polymer chemistry,physics and engineering.Despite the fact that polymeric
