General laws of funding for scientific citations:how citations change in funded and unfunded research between basic and applied sciences

Purpose:The goal of this study is to analyze the relationship between funded and unfunded papers and their citations in both basic and applied sciences.Design/methodology/approach:A power law model analyzes the relationship between research funding and citations of papers using 831,337 documents recorded in the Web of Science database.Findings:The original results reveal general characteristics of the diffusion of science in research fields:a)Funded articles receive higher citations compared to unfunded papers in journals;b)Funded articles exhibit a super-linear growth in citations,surpassing the increase seen in unfunded articles.This finding reveals a higher diffusion of scientific knowledge in funded articles.Moreover,c)funded articles in both basic and applied sciences demonstrate a similar expected change in citations,equivalent to about 1.23%,when the number of funded papers increases by 1%in journals.This result suggests,for the first time,that funding effect of scientific research is an invariant driver,irrespective of the nature of the basic or applied sciences.Originality/value:This evidence suggests empirical laws of funding for scientific citations that explain the importance of robust funding mechanisms for achieving impactful research outcomes in science and society.These findings here also highlight that funding for scientific research is a critical driving force in supporting citations and the dissemination of scientific knowledge in recorded documents in both basic and applied sciences.Practical implications:This comprehensive result provides a holistic view of the relationship between funding and citation performance in science to guide policymakers and R&D managers with science policies by directing funding to research in promoting the scientific development and higher diffusion of results for the progress of human society.

Dynamic analysis of axle box bearings on the high-speed train caused by wheel-rail excitation

To explore the impact of wheel-rail excitation on the dynamic performance of axle box bearings,a dynamic model of the high-speed train including axle box bearings is developed.Subsequently,the dynamic response characteristics of the axle box bearing are examined.The investigation focuses on the acceleration characteristics of bearing vibration under excitation of track irregularities and wheel flats.In addition,experiments on both normal and faulty bearings are conducted separately,and the correctness of the model and some conclusions are verified.According to the research,track irregularity is unfavorable for bearing fault detection based on resonance demodulation.Under the same speed conditions,the acceleration peak of bearing is inversely proportional to the length of the wheel flat and directly proportional to its depth.The paper will contribute to a deeper understanding of the dynamic performance of axle box bearings.

Citation distributions and research evaluations:The impossibility of formulating a universal indicator

Purpose:To analyze the diversity of citation distributions to publications in different research topics to investigate the accuracy of size-independent,rank-based indicators.The top percentile-based indicators are the most common indicators of this type,and the evaluations of Japan are the most evident misjudgments.Design/methodology/approach:The distributions of citations to publications from countries and journals in several research topics were analyzed along with the corresponding global publications using histograms with logarithmic binning,double rank plots,and normal probability plots of log-transformed numbers of citations.Findings:Size-independent,top percentile-based indicators are accurate when the global ranks of local publications fit a power law,but deviations in the least cited papers are frequent in countries and occur in all journals with high impact factors.In these cases,a single indicator is misleading.Comparisons of the proportions of uncited papers are the best way to predict these deviations.Research limitations:This study is fundamentally analytical,and its results describe mathematical facts that are self-evident.Practical implications:Respectable institutions,such as the OECD,the European Commission,and the U.S.National Science Board,produce research country rankings and individual evaluations using size-independent percentile indicators that are misleading in many countries.These misleading evaluations should be discontinued because they can cause confusion among research policymakers and lead to incorrect research policies.Originality/value:Studies linking the lower tail of citation distribution,including uncited papers,to percentile research indicators have not been performed previously.The present results demonstrate that studies of this type are necessary to find reliable procedures for research assessments.

Joint Modeling of Citation Networks and User Preferences for Academic Tagging Recommender System

In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniques and tries to combine nodes’textual content for modelling.They still do not,however,directly simulate many interactions in network learning.In order to address these issues,we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations.Specifically,we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles in the citation network.Then,the Commuting Matrix for massive node pair paths is used to improve computational performance.Finally,the two commonalities mentioned above are combined with the interaction paper labels based on the additivity of Poisson distribution.In addition,we also consider solving the model’s parameters by applying variational inference.Experimental results demonstrate that our suggested framework agrees and significantly outperforms the state-of-the-art baseline on two real datasets by efficiently merging the three relational data.Based on the Area Under Curve(AUC)and Mean Average Precision(MAP)analysis,the performance of the suggested task is evaluated,and it is demonstrated to have a greater solving efficiency than current techniques.

Tracking direct and indirect impact on technology and policy of transformative research via ego citation network

Purpose:The disseminating of academic knowledge to nonacademic audiences partly relies on the transition of subsequent citing papers.This study aims to investigate direct and indirect impact on technology and policy originating from transformative research based on ego citation network.Design/methodology/approach:Key Nobel Prize-winning publications(NPs)in fields of gene engineering and astrophysics are regarded as a proxy for transformative research.In this contribution,we introduce a network-structural indicator of citing patents to measure technological impact of a target article and use policy citations as a preliminary tool for policy impact.Findings:The results show that the impact on technology and policy of NPs are higher than that of their subsequent citation generations in gene engineering but not in astrophysics.Research limitations:The selection of Nobel Prizes is not balanced and the database used in this study,Dimensions,suffers from incompleteness and inaccuracy of citation links.Practical implications:Our findings provide useful clues to better understand the characteristics of transformative research in technological and policy impact.Originality/value:This study proposes a new framework to explore the direct and indirect impact on technology and policy originating from transformative research.

Citation and bibliographic coupling between authors in the field of social network analysis

Purpose:We analyzed the structure of a community of authors working in the field of social network analysis(SNA)based on citation indicators:direct citation and bibliographic coupling metrics.We observed patterns at the micro,meso,and macro levels of analysis.Design/methodology/approach:We used bibliometric network analysis,including the“temporal quantities”approach proposed to study temporal networks.Using a two-mode network linking publications with authors and a one-mode network of citations between the works,we constructed and analyzed the networks of citation and bibliographic coupling among authors.We used an iterated saturation data collection approach.Findings:At the macro-level,we observed the global structural features of citations between authors,showing that 80%of authors have not more than 15 citations from other works.At the meso-level,we extracted the groups of authors citing each other and similar to each other according to their citation patterns.We have seen a division of authors in SNA into groups of social scientists and physicists,as well as into other groups of authors from different disciplines.We found some examples of brokerage between different groups that maintained the common identity of the field.At the micro-level,we extracted authors with extremely high values of received citations,who can be considered as the most prominent authors in the field.We examined the temporal properties of the most popular authors.Research limitations:The main challenge in this approach is the resolution of the author’s name(synonyms and homonyms).We faced the author disambiguation,or“multiple personalities”(Harzing,2015)problem.To remain consistent and comparable with our previously published articles,we used the same SNA data collected up to 2018.The analysis and conclusions on the activity,productivity,and visibility of the authors are relative only to the field of SNA.Practical implications:The proposed approach can be utilized for similar objectives and identifying key structures and characteristics in other disciplines.This may potentially inspire the application of network approaches in other research areas,creating more authors collaborating in the field of SNA.Originality/value:We identified and applied an innovative approach and methods to study the structure of scientific communities,which allowed us to get the findings going beyond those obtained with other methods.We used a new approach to temporal network analysis,which is an important addition to the analysis as it provides detailed information on different measures for the authors and pairs of authors over time.

Research funding and citations in papers of Nobel Laureates in Physics, Chemistry and Medicine, 2019-2020

Purpose:The goal of this study is a comparative analysis of the relation between funding(a main driver for scientific research)and citations in papers of Nobel Laureates in physics,chemistry and medicine over 2019-2020 and the same relation in these research fields as a whole.Design/methodology/approach:This study utilizes a power law model to explore the relationship between research funding and citations of related papers.The study here analyzes 3,539 recorded documents by Nobel Laureates in physics,chemistry and medicine and a broader dataset of 183,016 documents related to the fields of physics,medicine,and chemistry recorded in the Web of Science database.Findings:Results reveal that in chemistry and medicine,funded researches published in papers of Nobel Laureates have higher citations than unfunded studies published in articles;vice versa high citations of Nobel Laureates in physics are for unfunded studies published in papers.Instead,when overall data of publications and citations in physics,chemistry and medicine are analyzed,all papers based on funded researches show higher citations than unfunded ones.Originality/value:Results clarify the driving role of research funding for science diffusion that are systematized in general properties:a)articles concerning funded researches receive more citations than(un)funded studies published in papers of physics,chemistry and medicine sciences,generating a high Matthew effect(a higher growth of citations with the increase in the number of papers);b)research funding increases the citations of articles in fields oriented to applied research(e.g.,chemistry and medicine)more than fields oriented towards basic research(e.g.,physics).Practical implications:The results here explain some characteristics of scientific development and diffusion,highlighting the critical role of research funding in fostering citations and the expansion of scientific knowledge.This finding can support decision-making of policymakers and R&D managers to improve the effectiveness in allocating financial resources in science policies to generate a higher positive scientific and societal impact.

Exploring the Relationship Between Patent Forward Citation and Stock Return Rate Using Empirical Data of China Stock Market

A novel indicator called price-citation was proposed.Based on the company integrated patent database of China listed companies of common stocks(A-shares)with the stock price and the stock return rate data,more than two thousand of A-shares from 2017 to 2020 were selected.The effect of the traditional patent forward citation and the price-citation for discriminating the stock return rate was thoroughly analyzed via ANOVA.The A-shares of forward citation counts above the average showed higher stock return rate means than the A-shares having patents but receiving no forward citations.The price-citation,combining both the financial and patent attributes,defined as the multiplication of the current stock price and the currently receiving forward citation count,showed its excellence in discriminating the stock return rate.The A-shares of higher price-citation showed significantly higher stock return rate means while the A-shares of lower price-citation showed significantly lowest stock return rate means.The price-citation effect had not been changed by COVID-19 though COVID-19 affected the social and economic environment to a considerable extent in 2020.

基于Citation Topic的领域期刊主题演化研究——以行为医学为例

基于论文层面的Citation Topic分类体系,通过测度行为医学领域SCI及SSCI期刊引文主题变动情况,展现国际行为医学领域研究重点以及相关支撑学科的演化。

Irregular initial solidification by mold thermal monitoring in the continuous casting of steels:A review

Occasional irregular initial solidification phenomena,including stickers,deep oscillation marks,depressions,and surface cracks of strand shells in continuous casting molds,are important limitations for developing the high-efficiency continuous casting of steels.The application of mold thermal monitoring(MTM) systems,which use thermocouples to detect and respond to temperature variations in molds,has become an effective method to address irregular initial solidification phenomena.Such systems are widely applied in numerous steel companies for sticker breakout prediction.However,monitoring the surface defects of strands remains immature.Hence,indepth research is necessary to utilize the potential advantages and comprehensive monitoring of MTM systems.This paper summarizes what is included in the irregular initial solidification phenomena and systematically reviews the current state of research on these phenomena by the MTM systems.Furthermore,the influences of mold slag behavior on monitoring these phenomena are analyzed.Finally,the remaining problems of the formation mechanisms and investigations of irregular initial solidification phenomena are discussed,and future research directions are proposed.

InCites中Citation Topics功能应用于科技期刊选题策划的实证研究——以热带医学研究领域为例

以热带医学研究领域为例,探索InCites数据库中的Citation Topics功能在选题策划中的应用。选取Web of Science数据库中热带医学领域近5年SCIE收录的论文,利用Citation Topics,对个别发文量多或被引频次高的研究方向、区域、研究人员、机构进行微观主题举例分析。疟疾微观主题下表现最活跃的区域为USA,机构为University of London,研究人员为Drakeley,Chris,出版物为Malaria Journal,United States Department of Health&Human Services为疟疾微观主题提供的基金资助最多;血吸虫病、疟疾、登革热、包虫囊肿和冠状病毒是中国热带医学领域的研究重点,冠状病毒、血吸虫病、隐孢子虫、登革热和疟疾微观主题的论文影响力相对较高;研究人员Zhou,Xiao-Nong的重点研究方向为血吸虫病、疟疾和包虫囊肿,疟疾、登革热、轮状病毒、犬弓首线虫和莱姆病研究主题的论文质量和关注度高;University of London热带医学领域的研究重点为疟疾、血吸虫病和登革热。InCites中Citation Topics功能可以实现对研究主题、人员、机构、国家/地区等模块进行更精细的分析,有助于科技期刊编辑更高效地制定选题方案。

Dynamic Constraint-Driven Event-Triggered Control of Strict-Feedback Systems Without Max/Min Values on Irregular Constraints

This work proposes an event-triggered adaptive control approach for a class of uncertain nonlinear systems under irregular constraints.Unlike the constraints considered in most existing papers,here the external irregular constraints are considered and a constraints switching mechanism(CSM)is introduced to circumvent the difficulties arising from irregular output constraints.Based on the CSM,a new class of generalized barrier functions are constructed,which allows the control results to be independent of the maximum and minimum values(MMVs)of constraints and thus extends the existing results.Finally,we proposed a novel dynamic constraint-driven event-triggered strategy(DCDETS),under which the stress on signal transmission is reduced greatly and no constraints are violated by making a dynamic trade-off among system state,external constraints,and inter-execution intervals.It is proved that the system output is driven to close to the reference trajectory and the semi-global stability is guaranteed under the proposed control scheme,regardless of the external irregular output constraints.Simulation also verifies the effectiveness and benefits of the proposed method.

Performance and Complexity Trade-Off between Short-Length Regular and Irregular LDPC

In this paper, both the high-complexity near-ML list decoding and the low-complexity belief propagation decoding are tested for some well-known regular and irregular LDPC codes. The complexity and performance trade-off is shown clearly and demonstrated with the paradigm of hybrid decoding. For regular LDPC code, the SNR-threshold performance and error-floor performance could be improved to the optimal level of ML decoding if the decoding complexity is progressively increased, usually corresponding to the near-ML decoding with progressively increased size of list. For irregular LDPC code, the SNR-threshold performance and error-floor performance could only be improved to a bottle-neck even with unlimited decoding complexity. However, with the technique of CRC-aided hybrid decoding, the ML performance could be greatly improved and approached with reasonable complexity thanks to the improved code-weight distribution from the concatenation of CRC and irregular LDPC code. Finally, CRC-aided 5GNR-LDPC code is evaluated and the capacity-approaching capability is shown.

WIMS/CITATION在IHNI-1堆芯物理计算中的应用

建立了利用WIMS+CITATION计算医院中子照射器Ⅰ型堆堆芯中子学参数的模型,计算了堆芯的功率分布、顶铍反应性价值、控制棒价值、温度系数、堆芯燃耗等中子学参数,计算结果与文献数据一致,表明文章所建立的计算模型可用于医院中子照射器I型堆堆芯的物理计算。

基于局部加权的Citation-kNN算法

Citation-kNN算法对传统的kNN算法进行了改进,使其可以应用于多示例学习问题,但其0-1决策方式具有一定的局限性,没有充分考虑样本的分布情况。为解决该问题,该文提出局部加权的Citation-kNN算法,综合考虑样本的分布情况,提出基于样本距离加权、基于样本离散度加权的方法,并对各种组合情况进行了实验。在标准数据集MUSK和乳腺超声图像数据库上的实验结果表明,该文提出的方法与Citation-kNN相比,性能有明显提高,并具有良好的适应性。

基于改进Citation-KNN算法的性别识别研究

为了简化系统模型训练方法,提高性别识别系统的整体效率,提出了一种基于改进Citation-KNN算法的说话人性别识别方法。该方法将连续语音切分,训练每段语音的高斯混合模型(Gaussian Mixture Model,GMM)作为多示例包,其所有混合元为相应包中示例;采用改进的Hausdorff距离作为包与包之间的距离测度,通过Citation-KNN算法进行性别识别。该方法以多示例包间距离为分类依据,简化了系统训练,且识别率优于一些传统算法。

Science Citation Index Expanded (SCI-E)及其检索技巧

简要介绍了SCI-E网络数据库及特点,并结合实例说明SCI-E数据库的检索技巧及分析功能的应用。

Writer Stance in Citations: An Ethnolinguistic and Paradigmatic Perspective

This study examines how writer stance is projected in citation from a comparative perspective.The dataset consisted of 120 qualitative and quantitative research articles(RAs)that were authored by Anglophone and Chinese applied linguists.ANO?VA tests revealed marked cross-language and cross-paradigmatic differences in stance-based dialogic engagement.

Functions of Uni- and Multi-citations： Implications for Weighted Citation Analysis

Purpose： （1） To test basic assumptions underlying frequency-weighted citation analysis： （a） Uni-citations correspond to citations that are nonessential to the citing papers; （b） The influence of a cited paper on the citing paper increases with the frequency with which it is cited in the citing paper. （2） To explore the degree to which citation location may be used to help identify nonessential citations. Design/methodology/approach： Each of the in-text citations in all research articles published in Issue 1 of the Journal of the Association for Information Science and Technology （JASIST） 2016 was manually classified into one of these five categories： Applied, Contrastive, Supportive, Reviewed, and Perfunctory. The distributions of citations at different in-text frequencies and in different locations in the text by these functions were analyzed. Findings： Filtering out nonessential citations before assigning weight is important for frequency-weighted citation analysis. For this purpose, removing citations by location is more effective than re-citation analysis that simply removes uni-citations. Removing all citation occurrences in the Background and Literature Review sections and uni-citations in the Introduction section appears to provide a good balance between filtration and error rates. Research limitations： This case study suffers from the limitation of scalability and generalizability. We took careful measures to reduce the impact of other limitations of the data collection approach used. Relying on the researcher＇s judgment to attribute citation functions, this approach is unobtrusive but speculative, and can suffer from a low degree of confidence, thus creating reliability concerns. Practical implications： Weighted citation analysis promises to improve citation analysis for research evaluation, knowledge network analysis, knowledge representation, and information retrieval. The present study showed the importance of filtering out nonessential citations before assigning weight in a weighted citation analysis, which may be a significant step forward to realizing these promises. Originality/value： Weighted citation analysis has long been proposed as a theoretical solution to the problem of citation analysis that treats all citations equally, and has attracted increasing research interest in recent years. The present study showed, for the first time, the importance of filtering out nonessential citations in weighted citation analysis, pointing research in this area in a new direction.

Patent Citations Analysis and Its Value in Research Evaluation： A Review and a New Approach to Map Technology-relevant Research

Purpose： First, to review the state-of-the-art in patent citation analysis, particularly characteristics of patent citations to scientific literature （scientific non-patent references, SNPRs）. Second, to present a novel mapping approach to identify technology-relevant research based on the papers cited by and referring to the SNPRs. Design/methodology/approach： In the review part we discuss the context of SNPRs such as the time lags between scientific achievements and inventions. Also patent-to-patent citation is addressed particularly because this type of patent citation analysis is a major element in the assessment of the economic value of patents. We also review the research on the role of universities and researchers in technological development, with important issues such as universities as sources of technological knowledge and inventor-author relations. We conclude the review part of this paper with an overview of recent research on mapping and network analysis of the science and technology interface and of technological progress in interaction with science. In the second part we apply new techniques for the direct visualization of the cited and citing relations of SNPRs, the mapping of the landscape around SNPRs by bibliographic coupling and co-citation analysis, and the mapping of the conceptual environment of SNPRs by keyword co-occurrence analysis. Findings： We discuss several properties of SNPRs. Only a small minority of publications covered by the Web of Science or Scopus are cited by patents, about 3%-4%. However, for publications based on university-industry collaboration the number of SNPRs is considerably higher, around 15%. The proposed mapping methodology based on a ＂second order SNPR approach＂ enables a better assessment of the technological relevance of research. Research limitations： The main limitation is that a more advanced merging of patent and publication data, in particular unification of author and inventor names, in still a necessity. Practical implications： The proposed mapping methodology enables the creation of a database of technology-relevant papers （TRPs）. In a bibliometric assessment the publications of research groups, research programs or institutes can be matched with the TRPs and thus the extent to which the work of groups, programs or institutes are relevant for technological development can be measured. Originality/value： The review part examines a wide range of findings in the research of patent citation analysis. The mapping approach to identify a broad range of technologyrelevant papers is novel and offers new opportunities in research evaluation practices.