Selecting the right journal for your research paper is a pivotal decision in the academic publishing journey. This paper aims to guide researchers through the process of choosing a suitable journal for their work by discussing key criteria and offering practical tips.
This is an evolving document. It is devoted to summarizing patterns and laws of knowledge growth. By examining a variety of parameters in data sources such as Wikipedia and Microsoft Academic Graph, we can get deeper insights of how knowledge evolves.
This document describes the ICFP 2020 virtual conference, including the planning process and the criteria that informed its design, plus feedback from the post-conference survey. It is intended to provide a record of the event and give advice to future organizers of virtual conferences.
The scale of manually validated data is currently limited by the effort that small groups of researchers can invest for the curation of such data. Within this paper, we propose the use of registered reports to scale the curation of manually validated data. The idea is inspired by the mechanical turk and replaces monetary payment with authorship of data set publication.
Credit allocation in the mainstream bibliometrics is fundamentally flawed and the popular indicators have been misleading science for decades. Originally a simple technical mistake has become an integral part of our culture and is very difficult to correct. Although the problem has been raised in scientific articles, it seems mostly unknown to wider audience.
An example of inconsistencies in information provided by popular bibliographic services is described and the reasons for these inconsistencies are discussed.
We consider distributions of scientific journals impact factor. Analysing 9028 scientific journals with the largest impact factors, we found that the distribution of them is year-to-year stable (at least for analysed 2011-2013 years), and it has the character of the exponential Boltzmann distribution with the power law asymptotic (tail).
The comparison of two universities in terms of bibliometric indicators frequently faces the problem of assessing the differences as meaningful or not. This Letter to the Editor proposes some benchmarks which can be used for supporting the interpretation of institutional differences.
Digital archives contribute to Big data. Combining social network analysis, coincidence analysis, data reduction, and visual analytics leads to better characterize topics over time, publishers' main themes and best authors of all times, according to the British newspaper The Guardian and from the 3 million records of the British National Bibliography.
This paper analyzes publication efficiency in terms of Hirsch-index or h-index and total citations, with an analogy to the Carnot efficiency used in thermodynamics. Such publication efficiency, with typical value of 30%, can be utilized to normalize the research output judgment, favoring quality outputs in reduced quantity, which is currently lacking in many discipline.
We show that the greater the scientific wealth of a nation, the more likely that it will tend to concentrate this excellence in a few premier institutions. That is, great wealth implies great inequality of distribution. The scientific wealth is interpreted in terms of citation data harvested by Google Scholar Citations for profiled institutions from all countries in the world.
The Journal Impact Factor (JIF) has been heavily criticized over decades. This opinion piece argues that the JIF should not be demonized. It still can be employed for research evaluation purposes by carefully considering the context and academic environment.
The paper comments on "Quantifying long-term scientific impact". It indicates that there is a mistake of [D. S. Wang , C. Song, A. L. Barabasi, Quantifying long-term scientific impact, Science 342, 127 (2013), arXiv:1306.3293].
Using empirical data I demonstrate that the result of performance evaluations by percentiles can be drastically influenced by the proper choice of the journal in which a manuscript is published.
Periodontal diseases are a class of pathologies wherein oral microbes induce harmful immune responses in a susceptible host. Therefore, an agent that can both reduce microbial burden and lessen pathogenesis of localized inflammation would have beneficial effects in periodontal disease; 2,4,4‐trichloro‐2‐hydroxydiphenyl‐ether [triclosan] is currently used in oral care products owing to broad spectrum antimicrobial and anti‐inflammatory properties.ObjectiveTo determine effects of triclosan on the response of oral epithelial cells to stimulation with the inflammatory microbial product lipopolysaccharide (LPS), a ligand for toll‐like receptor 4 [TLR4].Materials/MethodsPrimary human oral epithelial cells were stimulated with LPS in the presence and/or absence of triclosan after which expression of pro‐inflammatory cytokines, β‐defensins, micro‐RNAs [miRNAs], or TLR‐signaling pathway proteins were evaluated.ResultsHere, we demonstrate that triclosan is a potent inhibitor of oral epithelial cell LPS‐induced pro‐inflammatory responses by inducing miRNA regulation of the TLR‐signaling pathway. Triclosan was not a pan‐suppresser of oral epithelial cell responses as β‐defensin 2 [βD2] and βD3 were upregulated by triclosan following LPS‐stimulation.ConclusionsThese data demonstrate both a novel antimicrobial mechanism by which triclosan improves plaque control and an additional anti‐inflammatory property, which could have beneficial effects in periodontal disease resolution.
The creation of a next generation internet (semantic web) is impossible without attributes, allowing the semantic association of documents and their integration into information context. To achieve these goals, the Universal Metadata Standard (ums) may be an ultimative tool, which could serve as a basis for documentography, and is functionally required for interpretation of documents by the automatic operating systems.
VOSviewer is a computer program for creating, visualizing, and exploring bibliometric maps of science. In this report, the new text mining functionality of VOSviewer is presented. A number of examples are given of applications in which VOSviewer is used for analyzing large amounts of text data.
A procedure for bibliographic author metadata extraction from scholarly texts is presented. The author segments are identified based on capitalization and line break patterns. Two main author layout templates, which can retrieve from a varied set of title pages, are provided. Additionally, several disambiguating rules are described.