Are Noachian-age ridged plains (Nplr) actually early Hesperian in age

Whether or not the Nplr units in Memnonia and Argyre truly represent ridged plains volcanism of Noachian age or are simply areas of younger (Early Hesperian age) volcanism which failed to bury older craters and therefore have a greater total crater age than really applies to the ridged plains portion of those terrains is examined. The Nuekum and Hiller technique is used to determine the number of preserved crater retention surfaces in the Memnonia and Argyre regions where Scott and Tanaka show Nplr units to be common. The results for cratered terrain (Npl) in Memnonia is summarized along with those for ridged plains (Nplr) in both Memnonia and Argyre, and they are compared with similar results obtained for Tempe Terra and Lunae Plunum

Do you cite what I mean? Assessing the semantic scope of bibliographic coupling in economics

Bibliographic Coupling is one of the earliest statistical methods used to analyze scientific production and map scientific structure at different granularity levels. While many authors consider it a measure of semantic similarity, the questions as to “when and to what extent bibliographic coupling can be considered a measure of semantic similarity has not still needs to be established theoretically. Based on an analysis of the correlation between coupling strength and semantic distances of all 2015 economics articles included in the Web of Science database, the present paper shows that the semantic scope of these articles is very limited, thus putting into question the use of bibliographic coupling as a semantic similarity measure

Business and Information Technology Alignment Measurement -- a recent Literature Review

Since technology has been involved in the business context, Business and Information Technology Alignment (BITA) has been one of the main concerns of IT and Business executives and directors due to its importance to overall company performance, especially today in the age of digital transformation. Several models and frameworks have been developed for BITA implementation and for measuring their level of success, each one with a different approach to this desired state. The BITA measurement is one of the main decision-making tools in the strategic domain of companies. In general, the classical-internal alignment is the most measured domain and the external environment evolution alignment is the least measured. This literature review aims to characterize and analyze current research on BITA measurement with a comprehensive view of the works published over the last 15 years to identify potential gaps and future areas of research in the field.Comment: 12 pages, Preprint version, BIS 2018 International Workshops, Berlin, Germany, July 18 to 20, 2018, Revised Paper

Infarct tissue heterogeneity by contrast-enhanced MRI is a novel predictor of mortality in patients with coronary artery disease with reduced left ventricular systolic function

Cardiovascular Aspects of Radiolog

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

ResearchGate versus Google Scholar: Which finds more early citations?

ResearchGate has launched its own citation index by extracting citations from documents uploaded to the site and reporting citation counts on article profile pages. Since authors may upload preprints to ResearchGate, it may use these to provide early impact evidence for new papers. This article assesses the whether the number of citations found for recent articles is comparable to other citation indexes using 2675 recently-published library and information science articles. The results show that in March 2017, ResearchGate found less citations than did Google Scholar but more than both Web of Science and Scopus. This held true for the dataset overall and for the six largest journals in it. ResearchGate correlated most strongly with Google Scholar citations, suggesting that ResearchGate is not predominantly tapping a fundamentally different source of data than Google Scholar. Nevertheless, preprint sharing in ResearchGate is substantial enough for authors to take seriously

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

How to measure influence in social networks?

Today, social networks are a valued resource of social data that can be used to understand the interactions among people and communities. People can influence or be influenced by interactions, shared opinions and emotions. How-ever, in the social network analysis, one of the main problems is to find the most influential people. This work aims to report on the results of literature review whose goal was to identify and analyse the metrics, algorithms and models used to measure the user influence on social networks. The search was carried out in three databases: Scopus, IEEEXplore, and ScienceDirect. We restricted pub-lished articles between the years 2014 until 2020, in English, and we used the following keywords: social networks analysis, influence, metrics, measurements, and algorithms. Backward process was applied to complement the search consid-ering inclusion and exclusion criteria. As a result of this process, we obtained 25 articles: 12 in the initial search and 13 in the backward process. The literature review resulted in the collection of 21 influence metrics, 4 influence algorithms, and 8 models of influence analysis. We start by defining influence and presenting its properties and applications. We then proceed by describing, analysing and categorizing all that were found metrics, algorithms, and models to measure in-fluence in social networks. Finally, we present a discussion on these metrics, al-gorithms, and models. This work helps researchers to quickly gain a broad per-spective on metrics, algorithms, and models for influence in social networks and their relative potentialities and limitations.This work has been supported by IViSSEM: POCI-01-0145-FEDER-28284, COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020