Homogeneous explosion and shock initiation for a three-step chain-branching reaction model

The role of chain-branching cross-over temperatures in shock-induced ignition of reactive materials is studied by numerical simulation, using a three-step chainbranching reaction model. In order to provide insight into shock initiation, the simpler problem of a spatially homogeneous explosion is first considered. It is shown that for ratios of the cross-over temperature to the initial temperature, T-B, sufficiently less than unity, the homogeneous explosion can be quantitatively described by a widely used two-step model, while for T-B sufficiently above unity the homogeneous explosion can be effectively described by the standard one-step model. From the matchings between these homogeneous-explosion solutions, the parameters of the reduced models are identified in terms of those of the three-step model. When T-B is close to unity, all the reactions of the three-step model have a leading role, and hence in this case the model cannot be reduced further. In the case of shock initiation, for T-B (which is now the ratio of the cross-over temperature to the initial shock temperature) sufficiently below unity, the three-step solutions are qualitatively described by those of the matched two-step model, but there are quantitative differences due to the assumption in the reduced model that a purely chain-branching explosion occurs instantaneously. For T-B sufficiently above unity, the matched one-step model is found to effectively describe the way in which the heat release and fluid dynamics couple. For T-B close to unity, the competition between chain branching and chain termination is important from the outset. In these cases the speed at which the forward moving explosion wave that emerges from the piston is sensitive to T-B, and changes from supersonic to subsonic for a value of T-B just below unity

How important is computing technology for library and information science research?

© 2015 Elsevier Inc. Computers in library and information science (LIS) research have been an object of study or a tool for research for at least fifty years, but how central are computers to the discipline now? This research analyses the titles, abstracts, and keywords of forty years of articles in LIS-classified journals for trends related to computing technologies. The proportion of Scopus LIS articles mentioning some aspect of computing in their title, abstract, or keywords increased steadily from 1986 to 2000, then stabilised at about two thirds, indicating a continuing dominance of computers in most LIS research. Within this general trend, many computer-related terms have peaked and then declined in popularity. For example, the proportion of Scopus LIS article titles, abstracts, or keywords that included the terms "computer" or "computing" decreased fairly steadily from about 20% in 1975 to 5% in 2013, and the proportion explicitly mentioning the web peaked at 18% in 2002. Parallel analyses suggest that computing is substantially less important in two related disciplines: education and communication, and so it should be seen as a key aspect of the LIS identity.Published versio

Differences between journals and years in the proportions of students, researchers and faculty registering Mendeley articles

This article contains two investigations into Mendeley reader counts with the same dataset. Mendeley reader counts provide evidence of early scholarly impact for journal articles, but reflect the reading of a relatively young subset of all researchers. To investigate whether this age bias is constant or varies by narrow field and publication year, this article compares the proportions of student, researcher and faculty readers for articles published 1996-2016 in 36 large monodisciplinary journals. In these journals, undergraduates recorded the newest research and faculty the oldest, with large differences between journals. The existence of substantial differences in the composition of readers between related fields points to the need for caution when using Mendeley readers as substitutes for citations for broad fields. The second investigation shows, with the same data, that there are substantial differences between narrow fields in the time taken for Scopus citations to be as numerous as Mendeley readers. Thus, even narrow field differences can impact on the relative value of Mendeley compared to citation counts

Does Microsoft Academic find early citations?

This is an accepted manuscript of an article published by Springer in Scientometrics on 27/10/2017, available online: https://doi.org/10.1007/s11192-017-2558-9 The accepted version of the publication may differ from the final published version.This article investigates whether Microsoft Academic can use its web search component to identify early citations to recently published articles to help solve the problem of delays in research evaluations caused by the need to wait for citation counts to accrue. The results for 44,398 articles in Nature, Science and seven library and information science journals 1996-2017 show that Microsoft Academic and Scopus citation counts are similar for all years, with no early citation advantage for either. In contrast, Mendeley reader counts are substantially higher for more recent articles. Thus, Microsoft Academic appears to be broadly like Scopus for citation count data, and is apparently not more able to take advantage of online preprints to find early citations

Are Mendeley Reader Counts Useful Impact Indicators in all Fields?

Reader counts from the social reference sharing site Mendeley are known to be valuable for early research evaluation. They have strong correlations with citation counts for journal articles but appear about a year before them. There are disciplinary differences in the value of Mendeley reader counts but systematic evidence is needed at the level of narrow fields to reveal its extent. In response, this article compares Mendeley reader counts with Scopus citation counts for journal articles from 2012 in 325 narrow Scopus fields. Despite strong positive correlations in most fields, averaging 0.671, the correlations in some fields are as weak as 0.255. Technical reasons explain most weaker correlations, suggesting that the underlying relationship is almost always strong. The exceptions are caused by unusually high educational or professional use or topics of interest within countries that avoid Mendeley. The findings suggest that if care is taken then Mendeley reader counts can be used for early citation impact evidence in almost all fields and for related impact in some of the remainder. As an additional application of the results, cross-checking with Mendeley data can be used to identify indexing anomalies in citation databases

Do citations and readership identify seminal publications?

This work presents a new approach for analysing the ability of existing research metrics to identify research which has strongly influenced future developments. More specifically, we focus on the ability of citation counts and Mendeley reader counts to distinguish between publications regarded as seminal and publications regarded as literature reviews by field experts. The main motivation behind our research is to gain a better understanding of whether and how well the existing research metrics relate to research quality. For this experiment we have created a new dataset which we call TrueImpactDataset and which contains two types of publications, seminal papers and literature reviews. Using the dataset, we conduct a set of experiments to study how citation and reader counts perform in distinguishing these publication types, following the intuition that causing a change in a field signifies research quality. Our research shows that citation counts work better than a random baseline (by a margin of 10%) in distinguishing important seminal research papers from literature reviews while Mendeley reader counts do not work better than the baseline

Early Mendeley readers correlate with later citation counts

This is an accepted manuscript of an article published by Springer in Scientometrics on 26/03/2018, available online: https://doi.org/10.1007/s11192-018-2715-9 The accepted version of the publication may differ from the final published version.Counts of the number of readers registered in the social reference manager Mendeley have been proposed as an early impact indicator for journal articles. Although previous research has shown that Mendeley reader counts for articles tend to have a strong positive correlation with synchronous citation counts after a few years, no previous studies have compared early Mendeley reader counts with later citation counts. In response, this first diachronic analysis compares reader counts within a month of publication with citation counts after 20 months for ten fields. There were moderate or strong correlations in eight out of ten fields, with the two exceptions being the smallest categories (n=18, 36) with wide confidence intervals. The correlations are higher than the correlations between later citations and early citations, showing that Mendeley reader counts are more useful early impact indicators than citation counts

Can Microsoft Academic be used for citation analysis of preprint archives? The case of the Social Science Research Network

This is an accepted manuscript of an article published by Springer in Scientometrics on 07/03/2018, available online: https://doi.org/10.1007/s11192-018-2704-z The accepted version of the publication may differ from the final published version.Preprint archives play an important scholarly communication role within some fields. The impact of archives and individual preprints are difficult to analyse because online repositories are not indexed by the Web of Science or Scopus. In response, this article assesses whether the new Microsoft Academic can be used for citation analysis of preprint archives, focusing on the Social Science Research Network (SSRN). Although Microsoft Academic seems to index SSRN comprehensively, it groups a small fraction of SSRN papers into an easily retrievable set that has variations in character over time, making any field normalisation or citation comparisons untrustworthy. A brief parallel analysis of arXiv suggests that similar results would occur for other online repositories. Systematic analyses of preprint archives are nevertheless possible with Microsoft Academic when complete lists of archive publications are available from other sources because of its promising coverage and citation results

Social media metrics for new research evaluation

This chapter approaches, both from a theoretical and practical perspective, the most important principles and conceptual frameworks that can be considered in the application of social media metrics for scientific evaluation. We propose conceptually valid uses for social media metrics in research evaluation. The chapter discusses frameworks and uses of these metrics as well as principles and recommendations for the consideration and application of current (and potentially new) metrics in research evaluation.Comment: Forthcoming in Glanzel, W., Moed, H.F., Schmoch U., Thelwall, M. (2018). Springer Handbook of Science and Technology Indicators. Springe

Social media metrics for new research evaluation

Merit, Expertise and Measuremen